chore: 添加虚拟环境到仓库

- 添加 backend_service/venv 虚拟环境
- 包含所有Python依赖包
- 注意：虚拟环境约393MB，包含12655个文件

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/__init__.py

@@ -0,0 +1,65 @@
+# Names exposed by 'from sympy.physics.quantum import *'
+
+__all__ = [
+    'AntiCommutator',
+
+    'qapply',
+
+    'Commutator',
+
+    'Dagger',
+
+    'HilbertSpaceError', 'HilbertSpace', 'TensorProductHilbertSpace',
+    'TensorPowerHilbertSpace', 'DirectSumHilbertSpace', 'ComplexSpace', 'L2',
+    'FockSpace',
+
+    'InnerProduct',
+
+    'Operator', 'HermitianOperator', 'UnitaryOperator', 'IdentityOperator',
+    'OuterProduct', 'DifferentialOperator',
+
+    'represent', 'rep_innerproduct', 'rep_expectation', 'integrate_result',
+    'get_basis', 'enumerate_states',
+
+    'KetBase', 'BraBase', 'StateBase', 'State', 'Ket', 'Bra', 'TimeDepState',
+    'TimeDepBra', 'TimeDepKet', 'OrthogonalKet', 'OrthogonalBra',
+    'OrthogonalState', 'Wavefunction',
+
+    'TensorProduct', 'tensor_product_simp',
+
+    'hbar', 'HBar',
+
+    '_postprocess_state_mul', '_postprocess_state_pow'
+]
+
+from .anticommutator import AntiCommutator
+
+from .qapply import qapply
+
+from .commutator import Commutator
+
+from .dagger import Dagger
+
+from .hilbert import (HilbertSpaceError, HilbertSpace,
+        TensorProductHilbertSpace, TensorPowerHilbertSpace,
+        DirectSumHilbertSpace, ComplexSpace, L2, FockSpace)
+
+from .innerproduct import InnerProduct
+
+from .operator import (Operator, HermitianOperator, UnitaryOperator,
+        IdentityOperator, OuterProduct, DifferentialOperator)
+
+from .represent import (represent, rep_innerproduct, rep_expectation,
+        integrate_result, get_basis, enumerate_states)
+
+from .state import (KetBase, BraBase, StateBase, State, Ket, Bra,
+        TimeDepState, TimeDepBra, TimeDepKet, OrthogonalKet,
+        OrthogonalBra, OrthogonalState, Wavefunction)
+
+from .tensorproduct import TensorProduct, tensor_product_simp
+
+from .constants import hbar, HBar
+
+# These are private, but need to be imported so they are registered
+# as postprocessing transformers with Mul and Pow.
+from .transforms import _postprocess_state_mul, _postprocess_state_pow

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/anticommutator.py

@@ -0,0 +1,166 @@
+"""The anti-commutator: ``{A,B} = A*B + B*A``."""
+
+from sympy.core.expr import Expr
+from sympy.core.kind import KindDispatcher
+from sympy.core.mul import Mul
+from sympy.core.numbers import Integer
+from sympy.core.singleton import S
+from sympy.printing.pretty.stringpict import prettyForm
+
+from sympy.physics.quantum.dagger import Dagger
+from sympy.physics.quantum.kind import _OperatorKind, OperatorKind
+
+__all__ = [
+    'AntiCommutator'
+]
+
+#-----------------------------------------------------------------------------
+# Anti-commutator
+#-----------------------------------------------------------------------------
+
+
+class AntiCommutator(Expr):
+    """The standard anticommutator, in an unevaluated state.
+
+    Explanation
+    ===========
+
+    Evaluating an anticommutator is defined [1]_ as: ``{A, B} = A*B + B*A``.
+    This class returns the anticommutator in an unevaluated form.  To evaluate
+    the anticommutator, use the ``.doit()`` method.
+
+    Canonical ordering of an anticommutator is ``{A, B}`` for ``A < B``. The
+    arguments of the anticommutator are put into canonical order using
+    ``__cmp__``. If ``B < A``, then ``{A, B}`` is returned as ``{B, A}``.
+
+    Parameters
+    ==========
+
+    A : Expr
+        The first argument of the anticommutator {A,B}.
+    B : Expr
+        The second argument of the anticommutator {A,B}.
+
+    Examples
+    ========
+
+    >>> from sympy import symbols
+    >>> from sympy.physics.quantum import AntiCommutator
+    >>> from sympy.physics.quantum import Operator, Dagger
+    >>> x, y = symbols('x,y')
+    >>> A = Operator('A')
+    >>> B = Operator('B')
+
+    Create an anticommutator and use ``doit()`` to multiply them out.
+
+    >>> ac = AntiCommutator(A,B); ac
+    {A,B}
+    >>> ac.doit()
+    A*B + B*A
+
+    The commutator orders it arguments in canonical order:
+
+    >>> ac = AntiCommutator(B,A); ac
+    {A,B}
+
+    Commutative constants are factored out:
+
+    >>> AntiCommutator(3*x*A,x*y*B)
+    3*x**2*y*{A,B}
+
+    Adjoint operations applied to the anticommutator are properly applied to
+    the arguments:
+
+    >>> Dagger(AntiCommutator(A,B))
+    {Dagger(A),Dagger(B)}
+
+    References
+    ==========
+
+    .. [1] https://en.wikipedia.org/wiki/Commutator
+    """
+    is_commutative = False
+
+    _kind_dispatcher = KindDispatcher("AntiCommutator_kind_dispatcher", commutative=True)
+
+    @property
+    def kind(self):
+        arg_kinds = (a.kind for a in self.args)
+        return self._kind_dispatcher(*arg_kinds)
+
+    def __new__(cls, A, B):
+        r = cls.eval(A, B)
+        if r is not None:
+            return r
+        obj = Expr.__new__(cls, A, B)
+        return obj
+
+    @classmethod
+    def eval(cls, a, b):
+        if not (a and b):
+            return S.Zero
+        if a == b:
+            return Integer(2)*a**2
+        if a.is_commutative or b.is_commutative:
+            return Integer(2)*a*b
+
+        # [xA,yB]  ->  xy*[A,B]
+        ca, nca = a.args_cnc()
+        cb, ncb = b.args_cnc()
+        c_part = ca + cb
+        if c_part:
+            return Mul(Mul(*c_part), cls(Mul._from_args(nca), Mul._from_args(ncb)))
+
+        # Canonical ordering of arguments
+        #The Commutator [A,B] is on canonical form if A < B.
+        if a.compare(b) == 1:
+            return cls(b, a)
+
+    def doit(self, **hints):
+        """ Evaluate anticommutator """
+        # Keep the import of Operator here to avoid problems with
+        # circular imports.
+        from sympy.physics.quantum.operator import Operator
+        A = self.args[0]
+        B = self.args[1]
+        if isinstance(A, Operator) and isinstance(B, Operator):
+            try:
+                comm = A._eval_anticommutator(B, **hints)
+            except NotImplementedError:
+                try:
+                    comm = B._eval_anticommutator(A, **hints)
+                except NotImplementedError:
+                    comm = None
+            if comm is not None:
+                return comm.doit(**hints)
+        return (A*B + B*A).doit(**hints)
+
+    def _eval_adjoint(self):
+        return AntiCommutator(Dagger(self.args[0]), Dagger(self.args[1]))
+
+    def _sympyrepr(self, printer, *args):
+        return "%s(%s,%s)" % (
+            self.__class__.__name__, printer._print(
+                self.args[0]), printer._print(self.args[1])
+        )
+
+    def _sympystr(self, printer, *args):
+        return "{%s,%s}" % (
+            printer._print(self.args[0]), printer._print(self.args[1]))
+
+    def _pretty(self, printer, *args):
+        pform = printer._print(self.args[0], *args)
+        pform = prettyForm(*pform.right(prettyForm(',')))
+        pform = prettyForm(*pform.right(printer._print(self.args[1], *args)))
+        pform = prettyForm(*pform.parens(left='{', right='}'))
+        return pform
+
+    def _latex(self, printer, *args):
+        return "\\left\\{%s,%s\\right\\}" % tuple([
+            printer._print(arg, *args) for arg in self.args])
+
+
+@AntiCommutator._kind_dispatcher.register(_OperatorKind, _OperatorKind)
+def find_op_kind(e1, e2):
+    """Find the kind of an anticommutator of two OperatorKinds."""
+    return OperatorKind

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/boson.py

@@ -0,0 +1,243 @@
+"""Bosonic quantum operators."""
+
+from sympy.core.numbers import Integer
+from sympy.core.singleton import S
+from sympy.functions.elementary.complexes import conjugate
+from sympy.functions.elementary.exponential import exp
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.physics.quantum import Operator
+from sympy.physics.quantum import HilbertSpace, FockSpace, Ket, Bra
+from sympy.functions.special.tensor_functions import KroneckerDelta
+
+
+__all__ = [
+    'BosonOp',
+    'BosonFockKet',
+    'BosonFockBra',
+    'BosonCoherentKet',
+    'BosonCoherentBra'
+]
+
+
+class BosonOp(Operator):
+    """A bosonic operator that satisfies [a, Dagger(a)] == 1.
+
+    Parameters
+    ==========
+
+    name : str
+        A string that labels the bosonic mode.
+
+    annihilation : bool
+        A bool that indicates if the bosonic operator is an annihilation (True,
+        default value) or creation operator (False)
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum import Dagger, Commutator
+    >>> from sympy.physics.quantum.boson import BosonOp
+    >>> a = BosonOp("a")
+    >>> Commutator(a, Dagger(a)).doit()
+    1
+    """
+
+    @property
+    def name(self):
+        return self.args[0]
+
+    @property
+    def is_annihilation(self):
+        return bool(self.args[1])
+
+    @classmethod
+    def default_args(self):
+        return ("a", True)
+
+    def __new__(cls, *args, **hints):
+        if not len(args) in [1, 2]:
+            raise ValueError('1 or 2 parameters expected, got %s' % args)
+
+        if len(args) == 1:
+            args = (args[0], S.One)
+
+        if len(args) == 2:
+            args = (args[0], Integer(args[1]))
+
+        return Operator.__new__(cls, *args)
+
+    def _eval_commutator_BosonOp(self, other, **hints):
+        if self.name == other.name:
+            # [a^\dagger, a] = -1
+            if not self.is_annihilation and other.is_annihilation:
+                return S.NegativeOne
+
+        elif 'independent' in hints and hints['independent']:
+            # [a, b] = 0
+            return S.Zero
+
+        return None
+
+    def _eval_commutator_FermionOp(self, other, **hints):
+        return S.Zero
+
+    def _eval_anticommutator_BosonOp(self, other, **hints):
+        if 'independent' in hints and hints['independent']:
+            # {a, b} = 2 * a * b, because [a, b] = 0
+            return 2 * self * other
+
+        return None
+
+    def _eval_adjoint(self):
+        return BosonOp(str(self.name), not self.is_annihilation)
+
+    def _print_contents_latex(self, printer, *args):
+        if self.is_annihilation:
+            return r'{%s}' % str(self.name)
+        else:
+            return r'{{%s}^\dagger}' % str(self.name)
+
+    def _print_contents(self, printer, *args):
+        if self.is_annihilation:
+            return r'%s' % str(self.name)
+        else:
+            return r'Dagger(%s)' % str(self.name)
+
+    def _print_contents_pretty(self, printer, *args):
+        from sympy.printing.pretty.stringpict import prettyForm
+        pform = printer._print(self.args[0], *args)
+        if self.is_annihilation:
+            return pform
+        else:
+            return pform**prettyForm('\N{DAGGER}')
+
+
+class BosonFockKet(Ket):
+    """Fock state ket for a bosonic mode.
+
+    Parameters
+    ==========
+
+    n : Number
+        The Fock state number.
+
+    """
+
+    def __new__(cls, n):
+        return Ket.__new__(cls, n)
+
+    @property
+    def n(self):
+        return self.label[0]
+
+    @classmethod
+    def dual_class(self):
+        return BosonFockBra
+
+    @classmethod
+    def _eval_hilbert_space(cls, label):
+        return FockSpace()
+
+    def _eval_innerproduct_BosonFockBra(self, bra, **hints):
+        return KroneckerDelta(self.n, bra.n)
+
+    def _apply_from_right_to_BosonOp(self, op, **options):
+        if op.is_annihilation:
+            return sqrt(self.n) * BosonFockKet(self.n - 1)
+        else:
+            return sqrt(self.n + 1) * BosonFockKet(self.n + 1)
+
+
+class BosonFockBra(Bra):
+    """Fock state bra for a bosonic mode.
+
+    Parameters
+    ==========
+
+    n : Number
+        The Fock state number.
+
+    """
+
+    def __new__(cls, n):
+        return Bra.__new__(cls, n)
+
+    @property
+    def n(self):
+        return self.label[0]
+
+    @classmethod
+    def dual_class(self):
+        return BosonFockKet
+
+    @classmethod
+    def _eval_hilbert_space(cls, label):
+        return FockSpace()
+
+
+class BosonCoherentKet(Ket):
+    """Coherent state ket for a bosonic mode.
+
+    Parameters
+    ==========
+
+    alpha : Number, Symbol
+        The complex amplitude of the coherent state.
+
+    """
+
+    def __new__(cls, alpha):
+        return Ket.__new__(cls, alpha)
+
+    @property
+    def alpha(self):
+        return self.label[0]
+
+    @classmethod
+    def dual_class(self):
+        return BosonCoherentBra
+
+    @classmethod
+    def _eval_hilbert_space(cls, label):
+        return HilbertSpace()
+
+    def _eval_innerproduct_BosonCoherentBra(self, bra, **hints):
+        if self.alpha == bra.alpha:
+            return S.One
+        else:
+            return exp(-(abs(self.alpha)**2 + abs(bra.alpha)**2 - 2 * conjugate(bra.alpha) * self.alpha)/2)
+
+    def _apply_from_right_to_BosonOp(self, op, **options):
+        if op.is_annihilation:
+            return self.alpha * self
+        else:
+            return None
+
+
+class BosonCoherentBra(Bra):
+    """Coherent state bra for a bosonic mode.
+
+    Parameters
+    ==========
+
+    alpha : Number, Symbol
+        The complex amplitude of the coherent state.
+
+    """
+
+    def __new__(cls, alpha):
+        return Bra.__new__(cls, alpha)
+
+    @property
+    def alpha(self):
+        return self.label[0]
+
+    @classmethod
+    def dual_class(self):
+        return BosonCoherentKet
+
+    def _apply_operator_BosonOp(self, op, **options):
+        if not op.is_annihilation:
+            return self.alpha * self
+        else:
+            return None

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/cartesian.py

@@ -0,0 +1,341 @@
+"""Operators and states for 1D cartesian position and momentum.
+
+TODO:
+
+* Add 3D classes to mappings in operatorset.py
+
+"""
+
+from sympy.core.numbers import (I, pi)
+from sympy.core.singleton import S
+from sympy.functions.elementary.exponential import exp
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.functions.special.delta_functions import DiracDelta
+from sympy.sets.sets import Interval
+
+from sympy.physics.quantum.constants import hbar
+from sympy.physics.quantum.hilbert import L2
+from sympy.physics.quantum.operator import DifferentialOperator, HermitianOperator
+from sympy.physics.quantum.state import Ket, Bra, State
+
+__all__ = [
+    'XOp',
+    'YOp',
+    'ZOp',
+    'PxOp',
+    'X',
+    'Y',
+    'Z',
+    'Px',
+    'XKet',
+    'XBra',
+    'PxKet',
+    'PxBra',
+    'PositionState3D',
+    'PositionKet3D',
+    'PositionBra3D'
+]
+
+#-------------------------------------------------------------------------
+# Position operators
+#-------------------------------------------------------------------------
+
+
+class XOp(HermitianOperator):
+    """1D cartesian position operator."""
+
+    @classmethod
+    def default_args(self):
+        return ("X",)
+
+    @classmethod
+    def _eval_hilbert_space(self, args):
+        return L2(Interval(S.NegativeInfinity, S.Infinity))
+
+    def _eval_commutator_PxOp(self, other):
+        return I*hbar
+
+    def _apply_operator_XKet(self, ket, **options):
+        return ket.position*ket
+
+    def _apply_operator_PositionKet3D(self, ket, **options):
+        return ket.position_x*ket
+
+    def _represent_PxKet(self, basis, *, index=1, **options):
+        states = basis._enumerate_state(2, start_index=index)
+        coord1 = states[0].momentum
+        coord2 = states[1].momentum
+        d = DifferentialOperator(coord1)
+        delta = DiracDelta(coord1 - coord2)
+
+        return I*hbar*(d*delta)
+
+
+class YOp(HermitianOperator):
+    """ Y cartesian coordinate operator (for 2D or 3D systems) """
+
+    @classmethod
+    def default_args(self):
+        return ("Y",)
+
+    @classmethod
+    def _eval_hilbert_space(self, args):
+        return L2(Interval(S.NegativeInfinity, S.Infinity))
+
+    def _apply_operator_PositionKet3D(self, ket, **options):
+        return ket.position_y*ket
+
+
+class ZOp(HermitianOperator):
+    """ Z cartesian coordinate operator (for 3D systems) """
+
+    @classmethod
+    def default_args(self):
+        return ("Z",)
+
+    @classmethod
+    def _eval_hilbert_space(self, args):
+        return L2(Interval(S.NegativeInfinity, S.Infinity))
+
+    def _apply_operator_PositionKet3D(self, ket, **options):
+        return ket.position_z*ket
+
+#-------------------------------------------------------------------------
+# Momentum operators
+#-------------------------------------------------------------------------
+
+
+class PxOp(HermitianOperator):
+    """1D cartesian momentum operator."""
+
+    @classmethod
+    def default_args(self):
+        return ("Px",)
+
+    @classmethod
+    def _eval_hilbert_space(self, args):
+        return L2(Interval(S.NegativeInfinity, S.Infinity))
+
+    def _apply_operator_PxKet(self, ket, **options):
+        return ket.momentum*ket
+
+    def _represent_XKet(self, basis, *, index=1, **options):
+        states = basis._enumerate_state(2, start_index=index)
+        coord1 = states[0].position
+        coord2 = states[1].position
+        d = DifferentialOperator(coord1)
+        delta = DiracDelta(coord1 - coord2)
+
+        return -I*hbar*(d*delta)
+
+X = XOp('X')
+Y = YOp('Y')
+Z = ZOp('Z')
+Px = PxOp('Px')
+
+#-------------------------------------------------------------------------
+# Position eigenstates
+#-------------------------------------------------------------------------
+
+
+class XKet(Ket):
+    """1D cartesian position eigenket."""
+
+    @classmethod
+    def _operators_to_state(self, op, **options):
+        return self.__new__(self, *_lowercase_labels(op), **options)
+
+    def _state_to_operators(self, op_class, **options):
+        return op_class.__new__(op_class,
+                                *_uppercase_labels(self), **options)
+
+    @classmethod
+    def default_args(self):
+        return ("x",)
+
+    @classmethod
+    def dual_class(self):
+        return XBra
+
+    @property
+    def position(self):
+        """The position of the state."""
+        return self.label[0]
+
+    def _enumerate_state(self, num_states, **options):
+        return _enumerate_continuous_1D(self, num_states, **options)
+
+    def _eval_innerproduct_XBra(self, bra, **hints):
+        return DiracDelta(self.position - bra.position)
+
+    def _eval_innerproduct_PxBra(self, bra, **hints):
+        return exp(-I*self.position*bra.momentum/hbar)/sqrt(2*pi*hbar)
+
+
+class XBra(Bra):
+    """1D cartesian position eigenbra."""
+
+    @classmethod
+    def default_args(self):
+        return ("x",)
+
+    @classmethod
+    def dual_class(self):
+        return XKet
+
+    @property
+    def position(self):
+        """The position of the state."""
+        return self.label[0]
+
+
+class PositionState3D(State):
+    """ Base class for 3D cartesian position eigenstates """
+
+    @classmethod
+    def _operators_to_state(self, op, **options):
+        return self.__new__(self, *_lowercase_labels(op), **options)
+
+    def _state_to_operators(self, op_class, **options):
+        return op_class.__new__(op_class,
+                                *_uppercase_labels(self), **options)
+
+    @classmethod
+    def default_args(self):
+        return ("x", "y", "z")
+
+    @property
+    def position_x(self):
+        """ The x coordinate of the state """
+        return self.label[0]
+
+    @property
+    def position_y(self):
+        """ The y coordinate of the state """
+        return self.label[1]
+
+    @property
+    def position_z(self):
+        """ The z coordinate of the state """
+        return self.label[2]
+
+
+class PositionKet3D(Ket, PositionState3D):
+    """ 3D cartesian position eigenket """
+
+    def _eval_innerproduct_PositionBra3D(self, bra, **options):
+        x_diff = self.position_x - bra.position_x
+        y_diff = self.position_y - bra.position_y
+        z_diff = self.position_z - bra.position_z
+
+        return DiracDelta(x_diff)*DiracDelta(y_diff)*DiracDelta(z_diff)
+
+    @classmethod
+    def dual_class(self):
+        return PositionBra3D
+
+
+# XXX: The type:ignore here is because mypy gives Definition of
+# "_state_to_operators" in base class "PositionState3D" is incompatible with
+# definition in base class "BraBase"
+class PositionBra3D(Bra, PositionState3D):  # type: ignore
+    """ 3D cartesian position eigenbra """
+
+    @classmethod
+    def dual_class(self):
+        return PositionKet3D
+
+#-------------------------------------------------------------------------
+# Momentum eigenstates
+#-------------------------------------------------------------------------
+
+
+class PxKet(Ket):
+    """1D cartesian momentum eigenket."""
+
+    @classmethod
+    def _operators_to_state(self, op, **options):
+        return self.__new__(self, *_lowercase_labels(op), **options)
+
+    def _state_to_operators(self, op_class, **options):
+        return op_class.__new__(op_class,
+                                *_uppercase_labels(self), **options)
+
+    @classmethod
+    def default_args(self):
+        return ("px",)
+
+    @classmethod
+    def dual_class(self):
+        return PxBra
+
+    @property
+    def momentum(self):
+        """The momentum of the state."""
+        return self.label[0]
+
+    def _enumerate_state(self, *args, **options):
+        return _enumerate_continuous_1D(self, *args, **options)
+
+    def _eval_innerproduct_XBra(self, bra, **hints):
+        return exp(I*self.momentum*bra.position/hbar)/sqrt(2*pi*hbar)
+
+    def _eval_innerproduct_PxBra(self, bra, **hints):
+        return DiracDelta(self.momentum - bra.momentum)
+
+
+class PxBra(Bra):
+    """1D cartesian momentum eigenbra."""
+
+    @classmethod
+    def default_args(self):
+        return ("px",)
+
+    @classmethod
+    def dual_class(self):
+        return PxKet
+
+    @property
+    def momentum(self):
+        """The momentum of the state."""
+        return self.label[0]
+
+#-------------------------------------------------------------------------
+# Global helper functions
+#-------------------------------------------------------------------------
+
+
+def _enumerate_continuous_1D(*args, **options):
+    state = args[0]
+    num_states = args[1]
+    state_class = state.__class__
+    index_list = options.pop('index_list', [])
+
+    if len(index_list) == 0:
+        start_index = options.pop('start_index', 1)
+        index_list = list(range(start_index, start_index + num_states))
+
+    enum_states = [0 for i in range(len(index_list))]
+
+    for i, ind in enumerate(index_list):
+        label = state.args[0]
+        enum_states[i] = state_class(str(label) + "_" + str(ind), **options)
+
+    return enum_states
+
+
+def _lowercase_labels(ops):
+    if not isinstance(ops, set):
+        ops = [ops]
+
+    return [str(arg.label[0]).lower() for arg in ops]
+
+
+def _uppercase_labels(ops):
+    if not isinstance(ops, set):
+        ops = [ops]
+
+    new_args = [str(arg.label[0])[0].upper() +
+                str(arg.label[0])[1:] for arg in ops]
+
+    return new_args

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/cg.py

@@ -0,0 +1,754 @@
+#TODO:
+# -Implement Clebsch-Gordan symmetries
+# -Improve simplification method
+# -Implement new simplifications
+"""Clebsch-Gordon Coefficients."""
+
+from sympy.concrete.summations import Sum
+from sympy.core.add import Add
+from sympy.core.expr import Expr
+from sympy.core.function import expand
+from sympy.core.mul import Mul
+from sympy.core.power import Pow
+from sympy.core.relational import Eq
+from sympy.core.singleton import S
+from sympy.core.symbol import (Wild, symbols)
+from sympy.core.sympify import sympify
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.functions.elementary.piecewise import Piecewise
+from sympy.printing.pretty.stringpict import prettyForm, stringPict
+
+from sympy.functions.special.tensor_functions import KroneckerDelta
+from sympy.physics.wigner import clebsch_gordan, wigner_3j, wigner_6j, wigner_9j
+from sympy.printing.precedence import PRECEDENCE
+
+__all__ = [
+    'CG',
+    'Wigner3j',
+    'Wigner6j',
+    'Wigner9j',
+    'cg_simp'
+]
+
+#-----------------------------------------------------------------------------
+# CG Coefficients
+#-----------------------------------------------------------------------------
+
+
+class Wigner3j(Expr):
+    """Class for the Wigner-3j symbols.
+
+    Explanation
+    ===========
+
+    Wigner 3j-symbols are coefficients determined by the coupling of
+    two angular momenta. When created, they are expressed as symbolic
+    quantities that, for numerical parameters, can be evaluated using the
+    ``.doit()`` method [1]_.
+
+    Parameters
+    ==========
+
+    j1, m1, j2, m2, j3, m3 : Number, Symbol
+        Terms determining the angular momentum of coupled angular momentum
+        systems.
+
+    Examples
+    ========
+
+    Declare a Wigner-3j coefficient and calculate its value
+
+        >>> from sympy.physics.quantum.cg import Wigner3j
+        >>> w3j = Wigner3j(6,0,4,0,2,0)
+        >>> w3j
+        Wigner3j(6, 0, 4, 0, 2, 0)
+        >>> w3j.doit()
+        sqrt(715)/143
+
+    See Also
+    ========
+
+    CG: Clebsch-Gordan coefficients
+
+    References
+    ==========
+
+    .. [1] Varshalovich, D A, Quantum Theory of Angular Momentum. 1988.
+    """
+
+    is_commutative = True
+
+    def __new__(cls, j1, m1, j2, m2, j3, m3):
+        args = map(sympify, (j1, m1, j2, m2, j3, m3))
+        return Expr.__new__(cls, *args)
+
+    @property
+    def j1(self):
+        return self.args[0]
+
+    @property
+    def m1(self):
+        return self.args[1]
+
+    @property
+    def j2(self):
+        return self.args[2]
+
+    @property
+    def m2(self):
+        return self.args[3]
+
+    @property
+    def j3(self):
+        return self.args[4]
+
+    @property
+    def m3(self):
+        return self.args[5]
+
+    @property
+    def is_symbolic(self):
+        return not all(arg.is_number for arg in self.args)
+
+    # This is modified from the _print_Matrix method
+    def _pretty(self, printer, *args):
+        m = ((printer._print(self.j1), printer._print(self.m1)),
+            (printer._print(self.j2), printer._print(self.m2)),
+            (printer._print(self.j3), printer._print(self.m3)))
+        hsep = 2
+        vsep = 1
+        maxw = [-1]*3
+        for j in range(3):
+            maxw[j] = max(m[j][i].width() for i in range(2))
+        D = None
+        for i in range(2):
+            D_row = None
+            for j in range(3):
+                s = m[j][i]
+                wdelta = maxw[j] - s.width()
+                wleft = wdelta //2
+                wright = wdelta - wleft
+
+                s = prettyForm(*s.right(' '*wright))
+                s = prettyForm(*s.left(' '*wleft))
+
+                if D_row is None:
+                    D_row = s
+                    continue
+                D_row = prettyForm(*D_row.right(' '*hsep))
+                D_row = prettyForm(*D_row.right(s))
+            if D is None:
+                D = D_row
+                continue
+            for _ in range(vsep):
+                D = prettyForm(*D.below(' '))
+            D = prettyForm(*D.below(D_row))
+        D = prettyForm(*D.parens())
+        return D
+
+    def _latex(self, printer, *args):
+        label = map(printer._print, (self.j1, self.j2, self.j3,
+                    self.m1, self.m2, self.m3))
+        return r'\left(\begin{array}{ccc} %s & %s & %s \\ %s & %s & %s \end{array}\right)' % \
+            tuple(label)
+
+    def doit(self, **hints):
+        if self.is_symbolic:
+            raise ValueError("Coefficients must be numerical")
+        return wigner_3j(self.j1, self.j2, self.j3, self.m1, self.m2, self.m3)
+
+
+class CG(Wigner3j):
+    r"""Class for Clebsch-Gordan coefficient.
+
+    Explanation
+    ===========
+
+    Clebsch-Gordan coefficients describe the angular momentum coupling between
+    two systems. The coefficients give the expansion of a coupled total angular
+    momentum state and an uncoupled tensor product state. The Clebsch-Gordan
+    coefficients are defined as [1]_:
+
+    .. math ::
+        C^{j_3,m_3}_{j_1,m_1,j_2,m_2} = \left\langle j_1,m_1;j_2,m_2 | j_3,m_3\right\rangle
+
+    Parameters
+    ==========
+
+    j1, m1, j2, m2 : Number, Symbol
+        Angular momenta of states 1 and 2.
+
+    j3, m3: Number, Symbol
+        Total angular momentum of the coupled system.
+
+    Examples
+    ========
+
+    Define a Clebsch-Gordan coefficient and evaluate its value
+
+        >>> from sympy.physics.quantum.cg import CG
+        >>> from sympy import S
+        >>> cg = CG(S(3)/2, S(3)/2, S(1)/2, -S(1)/2, 1, 1)
+        >>> cg
+        CG(3/2, 3/2, 1/2, -1/2, 1, 1)
+        >>> cg.doit()
+        sqrt(3)/2
+        >>> CG(j1=S(1)/2, m1=-S(1)/2, j2=S(1)/2, m2=+S(1)/2, j3=1, m3=0).doit()
+        sqrt(2)/2
+
+
+    Compare [2]_.
+
+    See Also
+    ========
+
+    Wigner3j: Wigner-3j symbols
+
+    References
+    ==========
+
+    .. [1] Varshalovich, D A, Quantum Theory of Angular Momentum. 1988.
+    .. [2] `Clebsch-Gordan Coefficients, Spherical Harmonics, and d Functions
+        <https://pdg.lbl.gov/2020/reviews/rpp2020-rev-clebsch-gordan-coefs.pdf>`_
+        in P.A. Zyla *et al.* (Particle Data Group), Prog. Theor. Exp. Phys.
+        2020, 083C01 (2020).
+    """
+    precedence = PRECEDENCE["Pow"] - 1
+
+    def doit(self, **hints):
+        if self.is_symbolic:
+            raise ValueError("Coefficients must be numerical")
+        return clebsch_gordan(self.j1, self.j2, self.j3, self.m1, self.m2, self.m3)
+
+    def _pretty(self, printer, *args):
+        bot = printer._print_seq(
+            (self.j1, self.m1, self.j2, self.m2), delimiter=',')
+        top = printer._print_seq((self.j3, self.m3), delimiter=',')
+
+        pad = max(top.width(), bot.width())
+        bot = prettyForm(*bot.left(' '))
+        top = prettyForm(*top.left(' '))
+
+        if not pad == bot.width():
+            bot = prettyForm(*bot.right(' '*(pad - bot.width())))
+        if not pad == top.width():
+            top = prettyForm(*top.right(' '*(pad - top.width())))
+        s = stringPict('C' + ' '*pad)
+        s = prettyForm(*s.below(bot))
+        s = prettyForm(*s.above(top))
+        return s
+
+    def _latex(self, printer, *args):
+        label = map(printer._print, (self.j3, self.m3, self.j1,
+                    self.m1, self.j2, self.m2))
+        return r'C^{%s,%s}_{%s,%s,%s,%s}' % tuple(label)
+
+
+class Wigner6j(Expr):
+    """Class for the Wigner-6j symbols
+
+    See Also
+    ========
+
+    Wigner3j: Wigner-3j symbols
+
+    """
+    def __new__(cls, j1, j2, j12, j3, j, j23):
+        args = map(sympify, (j1, j2, j12, j3, j, j23))
+        return Expr.__new__(cls, *args)
+
+    @property
+    def j1(self):
+        return self.args[0]
+
+    @property
+    def j2(self):
+        return self.args[1]
+
+    @property
+    def j12(self):
+        return self.args[2]
+
+    @property
+    def j3(self):
+        return self.args[3]
+
+    @property
+    def j(self):
+        return self.args[4]
+
+    @property
+    def j23(self):
+        return self.args[5]
+
+    @property
+    def is_symbolic(self):
+        return not all(arg.is_number for arg in self.args)
+
+    # This is modified from the _print_Matrix method
+    def _pretty(self, printer, *args):
+        m = ((printer._print(self.j1), printer._print(self.j3)),
+            (printer._print(self.j2), printer._print(self.j)),
+            (printer._print(self.j12), printer._print(self.j23)))
+        hsep = 2
+        vsep = 1
+        maxw = [-1]*3
+        for j in range(3):
+            maxw[j] = max(m[j][i].width() for i in range(2))
+        D = None
+        for i in range(2):
+            D_row = None
+            for j in range(3):
+                s = m[j][i]
+                wdelta = maxw[j] - s.width()
+                wleft = wdelta //2
+                wright = wdelta - wleft
+
+                s = prettyForm(*s.right(' '*wright))
+                s = prettyForm(*s.left(' '*wleft))
+
+                if D_row is None:
+                    D_row = s
+                    continue
+                D_row = prettyForm(*D_row.right(' '*hsep))
+                D_row = prettyForm(*D_row.right(s))
+            if D is None:
+                D = D_row
+                continue
+            for _ in range(vsep):
+                D = prettyForm(*D.below(' '))
+            D = prettyForm(*D.below(D_row))
+        D = prettyForm(*D.parens(left='{', right='}'))
+        return D
+
+    def _latex(self, printer, *args):
+        label = map(printer._print, (self.j1, self.j2, self.j12,
+                    self.j3, self.j, self.j23))
+        return r'\left\{\begin{array}{ccc} %s & %s & %s \\ %s & %s & %s \end{array}\right\}' % \
+            tuple(label)
+
+    def doit(self, **hints):
+        if self.is_symbolic:
+            raise ValueError("Coefficients must be numerical")
+        return wigner_6j(self.j1, self.j2, self.j12, self.j3, self.j, self.j23)
+
+
+class Wigner9j(Expr):
+    """Class for the Wigner-9j symbols
+
+    See Also
+    ========
+
+    Wigner3j: Wigner-3j symbols
+
+    """
+    def __new__(cls, j1, j2, j12, j3, j4, j34, j13, j24, j):
+        args = map(sympify, (j1, j2, j12, j3, j4, j34, j13, j24, j))
+        return Expr.__new__(cls, *args)
+
+    @property
+    def j1(self):
+        return self.args[0]
+
+    @property
+    def j2(self):
+        return self.args[1]
+
+    @property
+    def j12(self):
+        return self.args[2]
+
+    @property
+    def j3(self):
+        return self.args[3]
+
+    @property
+    def j4(self):
+        return self.args[4]
+
+    @property
+    def j34(self):
+        return self.args[5]
+
+    @property
+    def j13(self):
+        return self.args[6]
+
+    @property
+    def j24(self):
+        return self.args[7]
+
+    @property
+    def j(self):
+        return self.args[8]
+
+    @property
+    def is_symbolic(self):
+        return not all(arg.is_number for arg in self.args)
+
+    # This is modified from the _print_Matrix method
+    def _pretty(self, printer, *args):
+        m = (
+            (printer._print(
+                self.j1), printer._print(self.j3), printer._print(self.j13)),
+            (printer._print(
+                self.j2), printer._print(self.j4), printer._print(self.j24)),
+            (printer._print(self.j12), printer._print(self.j34), printer._print(self.j)))
+        hsep = 2
+        vsep = 1
+        maxw = [-1]*3
+        for j in range(3):
+            maxw[j] = max(m[j][i].width() for i in range(3))
+        D = None
+        for i in range(3):
+            D_row = None
+            for j in range(3):
+                s = m[j][i]
+                wdelta = maxw[j] - s.width()
+                wleft = wdelta //2
+                wright = wdelta - wleft
+
+                s = prettyForm(*s.right(' '*wright))
+                s = prettyForm(*s.left(' '*wleft))
+
+                if D_row is None:
+                    D_row = s
+                    continue
+                D_row = prettyForm(*D_row.right(' '*hsep))
+                D_row = prettyForm(*D_row.right(s))
+            if D is None:
+                D = D_row
+                continue
+            for _ in range(vsep):
+                D = prettyForm(*D.below(' '))
+            D = prettyForm(*D.below(D_row))
+        D = prettyForm(*D.parens(left='{', right='}'))
+        return D
+
+    def _latex(self, printer, *args):
+        label = map(printer._print, (self.j1, self.j2, self.j12, self.j3,
+                self.j4, self.j34, self.j13, self.j24, self.j))
+        return r'\left\{\begin{array}{ccc} %s & %s & %s \\ %s & %s & %s \\ %s & %s & %s \end{array}\right\}' % \
+            tuple(label)
+
+    def doit(self, **hints):
+        if self.is_symbolic:
+            raise ValueError("Coefficients must be numerical")
+        return wigner_9j(self.j1, self.j2, self.j12, self.j3, self.j4, self.j34, self.j13, self.j24, self.j)
+
+
+def cg_simp(e):
+    """Simplify and combine CG coefficients.
+
+    Explanation
+    ===========
+
+    This function uses various symmetry and properties of sums and
+    products of Clebsch-Gordan coefficients to simplify statements
+    involving these terms [1]_.
+
+    Examples
+    ========
+
+    Simplify the sum over CG(a,alpha,0,0,a,alpha) for all alpha to
+    2*a+1
+
+        >>> from sympy.physics.quantum.cg import CG, cg_simp
+        >>> a = CG(1,1,0,0,1,1)
+        >>> b = CG(1,0,0,0,1,0)
+        >>> c = CG(1,-1,0,0,1,-1)
+        >>> cg_simp(a+b+c)
+        3
+
+    See Also
+    ========
+
+    CG: Clebsh-Gordan coefficients
+
+    References
+    ==========
+
+    .. [1] Varshalovich, D A, Quantum Theory of Angular Momentum. 1988.
+    """
+    if isinstance(e, Add):
+        return _cg_simp_add(e)
+    elif isinstance(e, Sum):
+        return _cg_simp_sum(e)
+    elif isinstance(e, Mul):
+        return Mul(*[cg_simp(arg) for arg in e.args])
+    elif isinstance(e, Pow):
+        return Pow(cg_simp(e.base), e.exp)
+    else:
+        return e
+
+
+def _cg_simp_add(e):
+    #TODO: Improve simplification method
+    """Takes a sum of terms involving Clebsch-Gordan coefficients and
+    simplifies the terms.
+
+    Explanation
+    ===========
+
+    First, we create two lists, cg_part, which is all the terms involving CG
+    coefficients, and other_part, which is all other terms. The cg_part list
+    is then passed to the simplification methods, which return the new cg_part
+    and any additional terms that are added to other_part
+    """
+    cg_part = []
+    other_part = []
+
+    e = expand(e)
+    for arg in e.args:
+        if arg.has(CG):
+            if isinstance(arg, Sum):
+                other_part.append(_cg_simp_sum(arg))
+            elif isinstance(arg, Mul):
+                terms = 1
+                for term in arg.args:
+                    if isinstance(term, Sum):
+                        terms *= _cg_simp_sum(term)
+                    else:
+                        terms *= term
+                if terms.has(CG):
+                    cg_part.append(terms)
+                else:
+                    other_part.append(terms)
+            else:
+                cg_part.append(arg)
+        else:
+            other_part.append(arg)
+
+    cg_part, other = _check_varsh_871_1(cg_part)
+    other_part.append(other)
+    cg_part, other = _check_varsh_871_2(cg_part)
+    other_part.append(other)
+    cg_part, other = _check_varsh_872_9(cg_part)
+    other_part.append(other)
+    return Add(*cg_part) + Add(*other_part)
+
+
+def _check_varsh_871_1(term_list):
+    # Sum( CG(a,alpha,b,0,a,alpha), (alpha, -a, a)) == KroneckerDelta(b,0)
+    a, alpha, b, lt = map(Wild, ('a', 'alpha', 'b', 'lt'))
+    expr = lt*CG(a, alpha, b, 0, a, alpha)
+    simp = (2*a + 1)*KroneckerDelta(b, 0)
+    sign = lt/abs(lt)
+    build_expr = 2*a + 1
+    index_expr = a + alpha
+    return _check_cg_simp(expr, simp, sign, lt, term_list, (a, alpha, b, lt), (a, b), build_expr, index_expr)
+
+
+def _check_varsh_871_2(term_list):
+    # Sum((-1)**(a-alpha)*CG(a,alpha,a,-alpha,c,0),(alpha,-a,a))
+    a, alpha, c, lt = map(Wild, ('a', 'alpha', 'c', 'lt'))
+    expr = lt*CG(a, alpha, a, -alpha, c, 0)
+    simp = sqrt(2*a + 1)*KroneckerDelta(c, 0)
+    sign = (-1)**(a - alpha)*lt/abs(lt)
+    build_expr = 2*a + 1
+    index_expr = a + alpha
+    return _check_cg_simp(expr, simp, sign, lt, term_list, (a, alpha, c, lt), (a, c), build_expr, index_expr)
+
+
+def _check_varsh_872_9(term_list):
+    # Sum( CG(a,alpha,b,beta,c,gamma)*CG(a,alpha',b,beta',c,gamma), (gamma, -c, c), (c, abs(a-b), a+b))
+    a, alpha, alphap, b, beta, betap, c, gamma, lt = map(Wild, (
+        'a', 'alpha', 'alphap', 'b', 'beta', 'betap', 'c', 'gamma', 'lt'))
+    # Case alpha==alphap, beta==betap
+
+    # For numerical alpha,beta
+    expr = lt*CG(a, alpha, b, beta, c, gamma)**2
+    simp = S.One
+    sign = lt/abs(lt)
+    x = abs(a - b)
+    y = abs(alpha + beta)
+    build_expr = a + b + 1 - Piecewise((x, x > y), (0, Eq(x, y)), (y, y > x))
+    index_expr = a + b - c
+    term_list, other1 = _check_cg_simp(expr, simp, sign, lt, term_list, (a, alpha, b, beta, c, gamma, lt), (a, alpha, b, beta), build_expr, index_expr)
+
+    # For symbolic alpha,beta
+    x = abs(a - b)
+    y = a + b
+    build_expr = (y + 1 - x)*(x + y + 1)
+    index_expr = (c - x)*(x + c) + c + gamma
+    term_list, other2 = _check_cg_simp(expr, simp, sign, lt, term_list, (a, alpha, b, beta, c, gamma, lt), (a, alpha, b, beta), build_expr, index_expr)
+
+    # Case alpha!=alphap or beta!=betap
+    # Note: this only works with leading term of 1, pattern matching is unable to match when there is a Wild leading term
+    # For numerical alpha,alphap,beta,betap
+    expr = CG(a, alpha, b, beta, c, gamma)*CG(a, alphap, b, betap, c, gamma)
+    simp = KroneckerDelta(alpha, alphap)*KroneckerDelta(beta, betap)
+    sign = S.One
+    x = abs(a - b)
+    y = abs(alpha + beta)
+    build_expr = a + b + 1 - Piecewise((x, x > y), (0, Eq(x, y)), (y, y > x))
+    index_expr = a + b - c
+    term_list, other3 = _check_cg_simp(expr, simp, sign, S.One, term_list, (a, alpha, alphap, b, beta, betap, c, gamma), (a, alpha, alphap, b, beta, betap), build_expr, index_expr)
+
+    # For symbolic alpha,alphap,beta,betap
+    x = abs(a - b)
+    y = a + b
+    build_expr = (y + 1 - x)*(x + y + 1)
+    index_expr = (c - x)*(x + c) + c + gamma
+    term_list, other4 = _check_cg_simp(expr, simp, sign, S.One, term_list, (a, alpha, alphap, b, beta, betap, c, gamma), (a, alpha, alphap, b, beta, betap), build_expr, index_expr)
+
+    return term_list, other1 + other2 + other4
+
+
+def _check_cg_simp(expr, simp, sign, lt, term_list, variables, dep_variables, build_index_expr, index_expr):
+    """ Checks for simplifications that can be made, returning a tuple of the
+    simplified list of terms and any terms generated by simplification.
+
+    Parameters
+    ==========
+
+    expr: expression
+        The expression with Wild terms that will be matched to the terms in
+        the sum
+
+    simp: expression
+        The expression with Wild terms that is substituted in place of the CG
+        terms in the case of simplification
+
+    sign: expression
+        The expression with Wild terms denoting the sign that is on expr that
+        must match
+
+    lt: expression
+        The expression with Wild terms that gives the leading term of the
+        matched expr
+
+    term_list: list
+        A list of all of the terms is the sum to be simplified
+
+    variables: list
+        A list of all the variables that appears in expr
+
+    dep_variables: list
+        A list of the variables that must match for all the terms in the sum,
+        i.e. the dependent variables
+
+    build_index_expr: expression
+        Expression with Wild terms giving the number of elements in cg_index
+
+    index_expr: expression
+        Expression with Wild terms giving the index terms have when storing
+        them to cg_index
+
+    """
+    other_part = 0
+    i = 0
+    while i < len(term_list):
+        sub_1 = _check_cg(term_list[i], expr, len(variables))
+        if sub_1 is None:
+            i += 1
+            continue
+        if not build_index_expr.subs(sub_1).is_number:
+            i += 1
+            continue
+        sub_dep = [(x, sub_1[x]) for x in dep_variables]
+        cg_index = [None]*build_index_expr.subs(sub_1)
+        for j in range(i, len(term_list)):
+            sub_2 = _check_cg(term_list[j], expr.subs(sub_dep), len(variables) - len(dep_variables), sign=(sign.subs(sub_1), sign.subs(sub_dep)))
+            if sub_2 is None:
+                continue
+            if not index_expr.subs(sub_dep).subs(sub_2).is_number:
+                continue
+            cg_index[index_expr.subs(sub_dep).subs(sub_2)] = j, expr.subs(lt, 1).subs(sub_dep).subs(sub_2), lt.subs(sub_2), sign.subs(sub_dep).subs(sub_2)
+        if not any(i is None for i in cg_index):
+            min_lt = min(*[ abs(term[2]) for term in cg_index ])
+            indices = [ term[0] for term in cg_index]
+            indices.sort()
+            indices.reverse()
+            [ term_list.pop(j) for j in indices ]
+            for term in cg_index:
+                if abs(term[2]) > min_lt:
+                    term_list.append( (term[2] - min_lt*term[3])*term[1] )
+            other_part += min_lt*(sign*simp).subs(sub_1)
+        else:
+            i += 1
+    return term_list, other_part
+
+
+def _check_cg(cg_term, expr, length, sign=None):
+    """Checks whether a term matches the given expression"""
+    # TODO: Check for symmetries
+    matches = cg_term.match(expr)
+    if matches is None:
+        return
+    if sign is not None:
+        if not isinstance(sign, tuple):
+            raise TypeError('sign must be a tuple')
+        if not sign[0] == (sign[1]).subs(matches):
+            return
+    if len(matches) == length:
+        return matches
+
+
+def _cg_simp_sum(e):
+    e = _check_varsh_sum_871_1(e)
+    e = _check_varsh_sum_871_2(e)
+    e = _check_varsh_sum_872_4(e)
+    return e
+
+
+def _check_varsh_sum_871_1(e):
+    a = Wild('a')
+    alpha = symbols('alpha')
+    b = Wild('b')
+    match = e.match(Sum(CG(a, alpha, b, 0, a, alpha), (alpha, -a, a)))
+    if match is not None and len(match) == 2:
+        return ((2*a + 1)*KroneckerDelta(b, 0)).subs(match)
+    return e
+
+
+def _check_varsh_sum_871_2(e):
+    a = Wild('a')
+    alpha = symbols('alpha')
+    c = Wild('c')
+    match = e.match(
+        Sum((-1)**(a - alpha)*CG(a, alpha, a, -alpha, c, 0), (alpha, -a, a)))
+    if match is not None and len(match) == 2:
+        return (sqrt(2*a + 1)*KroneckerDelta(c, 0)).subs(match)
+    return e
+
+
+def _check_varsh_sum_872_4(e):
+    alpha = symbols('alpha')
+    beta = symbols('beta')
+    a = Wild('a')
+    b = Wild('b')
+    c = Wild('c')
+    cp = Wild('cp')
+    gamma = Wild('gamma')
+    gammap = Wild('gammap')
+    cg1 = CG(a, alpha, b, beta, c, gamma)
+    cg2 = CG(a, alpha, b, beta, cp, gammap)
+    match1 = e.match(Sum(cg1*cg2, (alpha, -a, a), (beta, -b, b)))
+    if match1 is not None and len(match1) == 6:
+        return (KroneckerDelta(c, cp)*KroneckerDelta(gamma, gammap)).subs(match1)
+    match2 = e.match(Sum(cg1**2, (alpha, -a, a), (beta, -b, b)))
+    if match2 is not None and len(match2) == 4:
+        return S.One
+    return e
+
+
+def _cg_list(term):
+    if isinstance(term, CG):
+        return (term,), 1, 1
+    cg = []
+    coeff = 1
+    if not isinstance(term, (Mul, Pow)):
+        raise NotImplementedError('term must be CG, Add, Mul or Pow')
+    if isinstance(term, Pow) and term.exp.is_number:
+        if term.exp.is_number:
+            [ cg.append(term.base) for _ in range(term.exp) ]
+        else:
+            return (term,), 1, 1
+    if isinstance(term, Mul):
+        for arg in term.args:
+            if isinstance(arg, CG):
+                cg.append(arg)
+            else:
+                coeff *= arg
+        return cg, coeff, coeff/abs(coeff)

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/circuitplot.py

@@ -0,0 +1,370 @@
+"""Matplotlib based plotting of quantum circuits.
+
+Todo:
+
+* Optimize printing of large circuits.
+* Get this to work with single gates.
+* Do a better job checking the form of circuits to make sure it is a Mul of
+  Gates.
+* Get multi-target gates plotting.
+* Get initial and final states to plot.
+* Get measurements to plot. Might need to rethink measurement as a gate
+  issue.
+* Get scale and figsize to be handled in a better way.
+* Write some tests/examples!
+"""
+
+from __future__ import annotations
+
+from sympy.core.mul import Mul
+from sympy.external import import_module
+from sympy.physics.quantum.gate import Gate, OneQubitGate, CGate, CGateS
+
+
+__all__ = [
+    'CircuitPlot',
+    'circuit_plot',
+    'labeller',
+    'Mz',
+    'Mx',
+    'CreateOneQubitGate',
+    'CreateCGate',
+]
+
+np = import_module('numpy')
+matplotlib = import_module(
+    'matplotlib', import_kwargs={'fromlist': ['pyplot']},
+    catch=(RuntimeError,))  # This is raised in environments that have no display.
+
+if np and matplotlib:
+    pyplot = matplotlib.pyplot
+    Line2D = matplotlib.lines.Line2D
+    Circle = matplotlib.patches.Circle
+
+#from matplotlib import rc
+#rc('text',usetex=True)
+
+class CircuitPlot:
+    """A class for managing a circuit plot."""
+
+    scale = 1.0
+    fontsize = 20.0
+    linewidth = 1.0
+    control_radius = 0.05
+    not_radius = 0.15
+    swap_delta = 0.05
+    labels: list[str] = []
+    inits: dict[str, str] = {}
+    label_buffer = 0.5
+
+    def __init__(self, c, nqubits, **kwargs):
+        if not np or not matplotlib:
+            raise ImportError('numpy or matplotlib not available.')
+        self.circuit = c
+        self.ngates = len(self.circuit.args)
+        self.nqubits = nqubits
+        self.update(kwargs)
+        self._create_grid()
+        self._create_figure()
+        self._plot_wires()
+        self._plot_gates()
+        self._finish()
+
+    def update(self, kwargs):
+        """Load the kwargs into the instance dict."""
+        self.__dict__.update(kwargs)
+
+    def _create_grid(self):
+        """Create the grid of wires."""
+        scale = self.scale
+        wire_grid = np.arange(0.0, self.nqubits*scale, scale, dtype=float)
+        gate_grid = np.arange(0.0, self.ngates*scale, scale, dtype=float)
+        self._wire_grid = wire_grid
+        self._gate_grid = gate_grid
+
+    def _create_figure(self):
+        """Create the main matplotlib figure."""
+        self._figure = pyplot.figure(
+            figsize=(self.ngates*self.scale, self.nqubits*self.scale),
+            facecolor='w',
+            edgecolor='w'
+        )
+        ax = self._figure.add_subplot(
+            1, 1, 1,
+            frameon=True
+        )
+        ax.set_axis_off()
+        offset = 0.5*self.scale
+        ax.set_xlim(self._gate_grid[0] - offset, self._gate_grid[-1] + offset)
+        ax.set_ylim(self._wire_grid[0] - offset, self._wire_grid[-1] + offset)
+        ax.set_aspect('equal')
+        self._axes = ax
+
+    def _plot_wires(self):
+        """Plot the wires of the circuit diagram."""
+        xstart = self._gate_grid[0]
+        xstop = self._gate_grid[-1]
+        xdata = (xstart - self.scale, xstop + self.scale)
+        for i in range(self.nqubits):
+            ydata = (self._wire_grid[i], self._wire_grid[i])
+            line = Line2D(
+                xdata, ydata,
+                color='k',
+                lw=self.linewidth
+            )
+            self._axes.add_line(line)
+            if self.labels:
+                init_label_buffer = 0
+                if self.inits.get(self.labels[i]): init_label_buffer = 0.25
+                self._axes.text(
+                    xdata[0]-self.label_buffer-init_label_buffer,ydata[0],
+                    render_label(self.labels[i],self.inits),
+                    size=self.fontsize,
+                    color='k',ha='center',va='center')
+        self._plot_measured_wires()
+
+    def _plot_measured_wires(self):
+        ismeasured = self._measurements()
+        xstop = self._gate_grid[-1]
+        dy = 0.04 # amount to shift wires when doubled
+        # Plot doubled wires after they are measured
+        for im in ismeasured:
+            xdata = (self._gate_grid[ismeasured[im]],xstop+self.scale)
+            ydata = (self._wire_grid[im]+dy,self._wire_grid[im]+dy)
+            line = Line2D(
+                xdata, ydata,
+                color='k',
+                lw=self.linewidth
+            )
+            self._axes.add_line(line)
+        # Also double any controlled lines off these wires
+        for i,g in enumerate(self._gates()):
+            if isinstance(g, (CGate, CGateS)):
+                wires = g.controls + g.targets
+                for wire in wires:
+                    if wire in ismeasured and \
+                           self._gate_grid[i] > self._gate_grid[ismeasured[wire]]:
+                        ydata = min(wires), max(wires)
+                        xdata = self._gate_grid[i]-dy, self._gate_grid[i]-dy
+                        line = Line2D(
+                            xdata, ydata,
+                            color='k',
+                            lw=self.linewidth
+                            )
+                        self._axes.add_line(line)
+    def _gates(self):
+        """Create a list of all gates in the circuit plot."""
+        gates = []
+        if isinstance(self.circuit, Mul):
+            for g in reversed(self.circuit.args):
+                if isinstance(g, Gate):
+                    gates.append(g)
+        elif isinstance(self.circuit, Gate):
+            gates.append(self.circuit)
+        return gates
+
+    def _plot_gates(self):
+        """Iterate through the gates and plot each of them."""
+        for i, gate in enumerate(self._gates()):
+            gate.plot_gate(self, i)
+
+    def _measurements(self):
+        """Return a dict ``{i:j}`` where i is the index of the wire that has
+        been measured, and j is the gate where the wire is measured.
+        """
+        ismeasured = {}
+        for i,g in enumerate(self._gates()):
+            if getattr(g,'measurement',False):
+                for target in g.targets:
+                    if target in ismeasured:
+                        if ismeasured[target] > i:
+                            ismeasured[target] = i
+                    else:
+                        ismeasured[target] = i
+        return ismeasured
+
+    def _finish(self):
+        # Disable clipping to make panning work well for large circuits.
+        for o in self._figure.findobj():
+            o.set_clip_on(False)
+
+    def one_qubit_box(self, t, gate_idx, wire_idx):
+        """Draw a box for a single qubit gate."""
+        x = self._gate_grid[gate_idx]
+        y = self._wire_grid[wire_idx]
+        self._axes.text(
+            x, y, t,
+            color='k',
+            ha='center',
+            va='center',
+            bbox={"ec": 'k', "fc": 'w', "fill": True, "lw": self.linewidth},
+            size=self.fontsize
+        )
+
+    def two_qubit_box(self, t, gate_idx, wire_idx):
+        """Draw a box for a two qubit gate. Does not work yet.
+        """
+        # x = self._gate_grid[gate_idx]
+        # y = self._wire_grid[wire_idx]+0.5
+        print(self._gate_grid)
+        print(self._wire_grid)
+        # unused:
+        # obj = self._axes.text(
+        #     x, y, t,
+        #     color='k',
+        #     ha='center',
+        #     va='center',
+        #     bbox=dict(ec='k', fc='w', fill=True, lw=self.linewidth),
+        #     size=self.fontsize
+        # )
+
+    def control_line(self, gate_idx, min_wire, max_wire):
+        """Draw a vertical control line."""
+        xdata = (self._gate_grid[gate_idx], self._gate_grid[gate_idx])
+        ydata = (self._wire_grid[min_wire], self._wire_grid[max_wire])
+        line = Line2D(
+            xdata, ydata,
+            color='k',
+            lw=self.linewidth
+        )
+        self._axes.add_line(line)
+
+    def control_point(self, gate_idx, wire_idx):
+        """Draw a control point."""
+        x = self._gate_grid[gate_idx]
+        y = self._wire_grid[wire_idx]
+        radius = self.control_radius
+        c = Circle(
+            (x, y),
+            radius*self.scale,
+            ec='k',
+            fc='k',
+            fill=True,
+            lw=self.linewidth
+        )
+        self._axes.add_patch(c)
+
+    def not_point(self, gate_idx, wire_idx):
+        """Draw a NOT gates as the circle with plus in the middle."""
+        x = self._gate_grid[gate_idx]
+        y = self._wire_grid[wire_idx]
+        radius = self.not_radius
+        c = Circle(
+            (x, y),
+            radius,
+            ec='k',
+            fc='w',
+            fill=False,
+            lw=self.linewidth
+        )
+        self._axes.add_patch(c)
+        l = Line2D(
+            (x, x), (y - radius, y + radius),
+            color='k',
+            lw=self.linewidth
+        )
+        self._axes.add_line(l)
+
+    def swap_point(self, gate_idx, wire_idx):
+        """Draw a swap point as a cross."""
+        x = self._gate_grid[gate_idx]
+        y = self._wire_grid[wire_idx]
+        d = self.swap_delta
+        l1 = Line2D(
+            (x - d, x + d),
+            (y - d, y + d),
+            color='k',
+            lw=self.linewidth
+        )
+        l2 = Line2D(
+            (x - d, x + d),
+            (y + d, y - d),
+            color='k',
+            lw=self.linewidth
+        )
+        self._axes.add_line(l1)
+        self._axes.add_line(l2)
+
+def circuit_plot(c, nqubits, **kwargs):
+    """Draw the circuit diagram for the circuit with nqubits.
+
+    Parameters
+    ==========
+
+    c : circuit
+        The circuit to plot. Should be a product of Gate instances.
+    nqubits : int
+        The number of qubits to include in the circuit. Must be at least
+        as big as the largest ``min_qubits`` of the gates.
+    """
+    return CircuitPlot(c, nqubits, **kwargs)
+
+def render_label(label, inits={}):
+    """Slightly more flexible way to render labels.
+
+    >>> from sympy.physics.quantum.circuitplot import render_label
+    >>> render_label('q0')
+    '$\\\\left|q0\\\\right\\\\rangle$'
+    >>> render_label('q0', {'q0':'0'})
+    '$\\\\left|q0\\\\right\\\\rangle=\\\\left|0\\\\right\\\\rangle$'
+    """
+    init = inits.get(label)
+    if init:
+        return r'$\left|%s\right\rangle=\left|%s\right\rangle$' % (label, init)
+    return r'$\left|%s\right\rangle$' % label
+
+def labeller(n, symbol='q'):
+    """Autogenerate labels for wires of quantum circuits.
+
+    Parameters
+    ==========
+
+    n : int
+        number of qubits in the circuit.
+    symbol : string
+        A character string to precede all gate labels. E.g. 'q_0', 'q_1', etc.
+
+    >>> from sympy.physics.quantum.circuitplot import labeller
+    >>> labeller(2)
+    ['q_1', 'q_0']
+    >>> labeller(3,'j')
+    ['j_2', 'j_1', 'j_0']
+    """
+    return ['%s_%d' % (symbol,n-i-1) for i in range(n)]
+
+class Mz(OneQubitGate):
+    """Mock-up of a z measurement gate.
+
+    This is in circuitplot rather than gate.py because it's not a real
+    gate, it just draws one.
+    """
+    measurement = True
+    gate_name='Mz'
+    gate_name_latex='M_z'
+
+class Mx(OneQubitGate):
+    """Mock-up of an x measurement gate.
+
+    This is in circuitplot rather than gate.py because it's not a real
+    gate, it just draws one.
+    """
+    measurement = True
+    gate_name='Mx'
+    gate_name_latex='M_x'
+
+class CreateOneQubitGate(type):
+    def __new__(mcl, name, latexname=None):
+        if not latexname:
+            latexname = name
+        return type(name + "Gate", (OneQubitGate,),
+            {'gate_name': name, 'gate_name_latex': latexname})
+
+def CreateCGate(name, latexname=None):
+    """Use a lexical closure to make a controlled gate.
+    """
+    if not latexname:
+        latexname = name
+    onequbitgate = CreateOneQubitGate(name, latexname)
+    def ControlledGate(ctrls,target):
+        return CGate(tuple(ctrls),onequbitgate(target))
+    return ControlledGate

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/circuitutils.py

@@ -0,0 +1,488 @@
+"""Primitive circuit operations on quantum circuits."""
+
+from functools import reduce
+
+from sympy.core.sorting import default_sort_key
+from sympy.core.containers import Tuple
+from sympy.core.mul import Mul
+from sympy.core.symbol import Symbol
+from sympy.core.sympify import sympify
+from sympy.utilities import numbered_symbols
+from sympy.physics.quantum.gate import Gate
+
+__all__ = [
+    'kmp_table',
+    'find_subcircuit',
+    'replace_subcircuit',
+    'convert_to_symbolic_indices',
+    'convert_to_real_indices',
+    'random_reduce',
+    'random_insert'
+]
+
+
+def kmp_table(word):
+    """Build the 'partial match' table of the Knuth-Morris-Pratt algorithm.
+
+    Note: This is applicable to strings or
+    quantum circuits represented as tuples.
+    """
+
+    # Current position in subcircuit
+    pos = 2
+    # Beginning position of candidate substring that
+    # may reappear later in word
+    cnd = 0
+    # The 'partial match' table that helps one determine
+    # the next location to start substring search
+    table = []
+    table.append(-1)
+    table.append(0)
+
+    while pos < len(word):
+        if word[pos - 1] == word[cnd]:
+            cnd = cnd + 1
+            table.append(cnd)
+            pos = pos + 1
+        elif cnd > 0:
+            cnd = table[cnd]
+        else:
+            table.append(0)
+            pos = pos + 1
+
+    return table
+
+
+def find_subcircuit(circuit, subcircuit, start=0, end=0):
+    """Finds the subcircuit in circuit, if it exists.
+
+    Explanation
+    ===========
+
+    If the subcircuit exists, the index of the start of
+    the subcircuit in circuit is returned; otherwise,
+    -1 is returned.  The algorithm that is implemented
+    is the Knuth-Morris-Pratt algorithm.
+
+    Parameters
+    ==========
+
+    circuit : tuple, Gate or Mul
+        A tuple of Gates or Mul representing a quantum circuit
+    subcircuit : tuple, Gate or Mul
+        A tuple of Gates or Mul to find in circuit
+    start : int
+        The location to start looking for subcircuit.
+        If start is the same or past end, -1 is returned.
+    end : int
+        The last place to look for a subcircuit.  If end
+        is less than 1 (one), then the length of circuit
+        is taken to be end.
+
+    Examples
+    ========
+
+    Find the first instance of a subcircuit:
+
+    >>> from sympy.physics.quantum.circuitutils import find_subcircuit
+    >>> from sympy.physics.quantum.gate import X, Y, Z, H
+    >>> circuit = X(0)*Z(0)*Y(0)*H(0)
+    >>> subcircuit = Z(0)*Y(0)
+    >>> find_subcircuit(circuit, subcircuit)
+    1
+
+    Find the first instance starting at a specific position:
+
+    >>> find_subcircuit(circuit, subcircuit, start=1)
+    1
+
+    >>> find_subcircuit(circuit, subcircuit, start=2)
+    -1
+
+    >>> circuit = circuit*subcircuit
+    >>> find_subcircuit(circuit, subcircuit, start=2)
+    4
+
+    Find the subcircuit within some interval:
+
+    >>> find_subcircuit(circuit, subcircuit, start=2, end=2)
+    -1
+    """
+
+    if isinstance(circuit, Mul):
+        circuit = circuit.args
+
+    if isinstance(subcircuit, Mul):
+        subcircuit = subcircuit.args
+
+    if len(subcircuit) == 0 or len(subcircuit) > len(circuit):
+        return -1
+
+    if end < 1:
+        end = len(circuit)
+
+    # Location in circuit
+    pos = start
+    # Location in the subcircuit
+    index = 0
+    # 'Partial match' table
+    table = kmp_table(subcircuit)
+
+    while (pos + index) < end:
+        if subcircuit[index] == circuit[pos + index]:
+            index = index + 1
+        else:
+            pos = pos + index - table[index]
+            index = table[index] if table[index] > -1 else 0
+
+        if index == len(subcircuit):
+            return pos
+
+    return -1
+
+
+def replace_subcircuit(circuit, subcircuit, replace=None, pos=0):
+    """Replaces a subcircuit with another subcircuit in circuit,
+    if it exists.
+
+    Explanation
+    ===========
+
+    If multiple instances of subcircuit exists, the first instance is
+    replaced.  The position to being searching from (if different from
+    0) may be optionally given.  If subcircuit cannot be found, circuit
+    is returned.
+
+    Parameters
+    ==========
+
+    circuit : tuple, Gate or Mul
+        A quantum circuit.
+    subcircuit : tuple, Gate or Mul
+        The circuit to be replaced.
+    replace : tuple, Gate or Mul
+        The replacement circuit.
+    pos : int
+        The location to start search and replace
+        subcircuit, if it exists.  This may be used
+        if it is known beforehand that multiple
+        instances exist, and it is desirable to
+        replace a specific instance.  If a negative number
+        is given, pos will be defaulted to 0.
+
+    Examples
+    ========
+
+    Find and remove the subcircuit:
+
+    >>> from sympy.physics.quantum.circuitutils import replace_subcircuit
+    >>> from sympy.physics.quantum.gate import X, Y, Z, H
+    >>> circuit = X(0)*Z(0)*Y(0)*H(0)*X(0)*H(0)*Y(0)
+    >>> subcircuit = Z(0)*Y(0)
+    >>> replace_subcircuit(circuit, subcircuit)
+    (X(0), H(0), X(0), H(0), Y(0))
+
+    Remove the subcircuit given a starting search point:
+
+    >>> replace_subcircuit(circuit, subcircuit, pos=1)
+    (X(0), H(0), X(0), H(0), Y(0))
+
+    >>> replace_subcircuit(circuit, subcircuit, pos=2)
+    (X(0), Z(0), Y(0), H(0), X(0), H(0), Y(0))
+
+    Replace the subcircuit:
+
+    >>> replacement = H(0)*Z(0)
+    >>> replace_subcircuit(circuit, subcircuit, replace=replacement)
+    (X(0), H(0), Z(0), H(0), X(0), H(0), Y(0))
+    """
+
+    if pos < 0:
+        pos = 0
+
+    if isinstance(circuit, Mul):
+        circuit = circuit.args
+
+    if isinstance(subcircuit, Mul):
+        subcircuit = subcircuit.args
+
+    if isinstance(replace, Mul):
+        replace = replace.args
+    elif replace is None:
+        replace = ()
+
+    # Look for the subcircuit starting at pos
+    loc = find_subcircuit(circuit, subcircuit, start=pos)
+
+    # If subcircuit was found
+    if loc > -1:
+        # Get the gates to the left of subcircuit
+        left = circuit[0:loc]
+        # Get the gates to the right of subcircuit
+        right = circuit[loc + len(subcircuit):len(circuit)]
+        # Recombine the left and right side gates into a circuit
+        circuit = left + replace + right
+
+    return circuit
+
+
+def _sympify_qubit_map(mapping):
+    new_map = {}
+    for key in mapping:
+        new_map[key] = sympify(mapping[key])
+    return new_map
+
+
+def convert_to_symbolic_indices(seq, start=None, gen=None, qubit_map=None):
+    """Returns the circuit with symbolic indices and the
+    dictionary mapping symbolic indices to real indices.
+
+    The mapping is 1 to 1 and onto (bijective).
+
+    Parameters
+    ==========
+
+    seq : tuple, Gate/Integer/tuple or Mul
+        A tuple of Gate, Integer, or tuple objects, or a Mul
+    start : Symbol
+        An optional starting symbolic index
+    gen : object
+        An optional numbered symbol generator
+    qubit_map : dict
+        An existing mapping of symbolic indices to real indices
+
+    All symbolic indices have the format 'i#', where # is
+    some number >= 0.
+    """
+
+    if isinstance(seq, Mul):
+        seq = seq.args
+
+    # A numbered symbol generator
+    index_gen = numbered_symbols(prefix='i', start=-1)
+    cur_ndx = next(index_gen)
+
+    # keys are symbolic indices; values are real indices
+    ndx_map = {}
+
+    def create_inverse_map(symb_to_real_map):
+        rev_items = lambda item: (item[1], item[0])
+        return dict(map(rev_items, symb_to_real_map.items()))
+
+    if start is not None:
+        if not isinstance(start, Symbol):
+            msg = 'Expected Symbol for starting index, got %r.' % start
+            raise TypeError(msg)
+        cur_ndx = start
+
+    if gen is not None:
+        if not isinstance(gen, numbered_symbols().__class__):
+            msg = 'Expected a generator, got %r.' % gen
+            raise TypeError(msg)
+        index_gen = gen
+
+    if qubit_map is not None:
+        if not isinstance(qubit_map, dict):
+            msg = ('Expected dict for existing map, got ' +
+                   '%r.' % qubit_map)
+            raise TypeError(msg)
+        ndx_map = qubit_map
+
+    ndx_map = _sympify_qubit_map(ndx_map)
+    # keys are real indices; keys are symbolic indices
+    inv_map = create_inverse_map(ndx_map)
+
+    sym_seq = ()
+    for item in seq:
+        # Nested items, so recurse
+        if isinstance(item, Gate):
+            result = convert_to_symbolic_indices(item.args,
+                                                 qubit_map=ndx_map,
+                                                 start=cur_ndx,
+                                                 gen=index_gen)
+            sym_item, new_map, cur_ndx, index_gen = result
+            ndx_map.update(new_map)
+            inv_map = create_inverse_map(ndx_map)
+
+        elif isinstance(item, (tuple, Tuple)):
+            result = convert_to_symbolic_indices(item,
+                                                 qubit_map=ndx_map,
+                                                 start=cur_ndx,
+                                                 gen=index_gen)
+            sym_item, new_map, cur_ndx, index_gen = result
+            ndx_map.update(new_map)
+            inv_map = create_inverse_map(ndx_map)
+
+        elif item in inv_map:
+            sym_item = inv_map[item]
+
+        else:
+            cur_ndx = next(gen)
+            ndx_map[cur_ndx] = item
+            inv_map[item] = cur_ndx
+            sym_item = cur_ndx
+
+        if isinstance(item, Gate):
+            sym_item = item.__class__(*sym_item)
+
+        sym_seq = sym_seq + (sym_item,)
+
+    return sym_seq, ndx_map, cur_ndx, index_gen
+
+
+def convert_to_real_indices(seq, qubit_map):
+    """Returns the circuit with real indices.
+
+    Parameters
+    ==========
+
+    seq : tuple, Gate/Integer/tuple or Mul
+        A tuple of Gate, Integer, or tuple objects or a Mul
+    qubit_map : dict
+        A dictionary mapping symbolic indices to real indices.
+
+    Examples
+    ========
+
+    Change the symbolic indices to real integers:
+
+    >>> from sympy import symbols
+    >>> from sympy.physics.quantum.circuitutils import convert_to_real_indices
+    >>> from sympy.physics.quantum.gate import X, Y, H
+    >>> i0, i1 = symbols('i:2')
+    >>> index_map = {i0 : 0, i1 : 1}
+    >>> convert_to_real_indices(X(i0)*Y(i1)*H(i0)*X(i1), index_map)
+    (X(0), Y(1), H(0), X(1))
+    """
+
+    if isinstance(seq, Mul):
+        seq = seq.args
+
+    if not isinstance(qubit_map, dict):
+        msg = 'Expected dict for qubit_map, got %r.' % qubit_map
+        raise TypeError(msg)
+
+    qubit_map = _sympify_qubit_map(qubit_map)
+    real_seq = ()
+    for item in seq:
+        # Nested items, so recurse
+        if isinstance(item, Gate):
+            real_item = convert_to_real_indices(item.args, qubit_map)
+
+        elif isinstance(item, (tuple, Tuple)):
+            real_item = convert_to_real_indices(item, qubit_map)
+
+        else:
+            real_item = qubit_map[item]
+
+        if isinstance(item, Gate):
+            real_item = item.__class__(*real_item)
+
+        real_seq = real_seq + (real_item,)
+
+    return real_seq
+
+
+def random_reduce(circuit, gate_ids, seed=None):
+    """Shorten the length of a quantum circuit.
+
+    Explanation
+    ===========
+
+    random_reduce looks for circuit identities in circuit, randomly chooses
+    one to remove, and returns a shorter yet equivalent circuit.  If no
+    identities are found, the same circuit is returned.
+
+    Parameters
+    ==========
+
+    circuit : Gate tuple of Mul
+        A tuple of Gates representing a quantum circuit
+    gate_ids : list, GateIdentity
+        List of gate identities to find in circuit
+    seed : int or list
+        seed used for _randrange; to override the random selection, provide a
+        list of integers: the elements of gate_ids will be tested in the order
+        given by the list
+
+    """
+    from sympy.core.random import _randrange
+
+    if not gate_ids:
+        return circuit
+
+    if isinstance(circuit, Mul):
+        circuit = circuit.args
+
+    ids = flatten_ids(gate_ids)
+
+    # Create the random integer generator with the seed
+    randrange = _randrange(seed)
+
+    # Look for an identity in the circuit
+    while ids:
+        i = randrange(len(ids))
+        id = ids.pop(i)
+        if find_subcircuit(circuit, id) != -1:
+            break
+    else:
+        # no identity was found
+        return circuit
+
+    # return circuit with the identity removed
+    return replace_subcircuit(circuit, id)
+
+
+def random_insert(circuit, choices, seed=None):
+    """Insert a circuit into another quantum circuit.
+
+    Explanation
+    ===========
+
+    random_insert randomly chooses a location in the circuit to insert
+    a randomly selected circuit from amongst the given choices.
+
+    Parameters
+    ==========
+
+    circuit : Gate tuple or Mul
+        A tuple or Mul of Gates representing a quantum circuit
+    choices : list
+        Set of circuit choices
+    seed : int or list
+        seed used for _randrange; to override the random selections, give
+        a list two integers, [i, j] where i is the circuit location where
+        choice[j] will be inserted.
+
+    Notes
+    =====
+
+    Indices for insertion should be [0, n] if n is the length of the
+    circuit.
+    """
+    from sympy.core.random import _randrange
+
+    if not choices:
+        return circuit
+
+    if isinstance(circuit, Mul):
+        circuit = circuit.args
+
+    # get the location in the circuit and the element to insert from choices
+    randrange = _randrange(seed)
+    loc = randrange(len(circuit) + 1)
+    choice = choices[randrange(len(choices))]
+
+    circuit = list(circuit)
+    circuit[loc: loc] = choice
+    return tuple(circuit)
+
+# Flatten the GateIdentity objects (with gate rules) into one single list
+
+
+def flatten_ids(ids):
+    collapse = lambda acc, an_id: acc + sorted(an_id.equivalent_ids,
+                                        key=default_sort_key)
+    ids = reduce(collapse, ids, [])
+    ids.sort(key=default_sort_key)
+    return ids

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/commutator.py

@@ -0,0 +1,256 @@
+"""The commutator: [A,B] = A*B - B*A."""
+
+from sympy.core.add import Add
+from sympy.core.expr import Expr
+from sympy.core.kind import KindDispatcher
+from sympy.core.mul import Mul
+from sympy.core.power import Pow
+from sympy.core.singleton import S
+from sympy.printing.pretty.stringpict import prettyForm
+
+from sympy.physics.quantum.dagger import Dagger
+from sympy.physics.quantum.kind import _OperatorKind, OperatorKind
+
+
+__all__ = [
+    'Commutator'
+]
+
+#-----------------------------------------------------------------------------
+# Commutator
+#-----------------------------------------------------------------------------
+
+
+class Commutator(Expr):
+    """The standard commutator, in an unevaluated state.
+
+    Explanation
+    ===========
+
+    Evaluating a commutator is defined [1]_ as: ``[A, B] = A*B - B*A``. This
+    class returns the commutator in an unevaluated form. To evaluate the
+    commutator, use the ``.doit()`` method.
+
+    Canonical ordering of a commutator is ``[A, B]`` for ``A < B``. The
+    arguments of the commutator are put into canonical order using ``__cmp__``.
+    If ``B < A``, then ``[B, A]`` is returned as ``-[A, B]``.
+
+    Parameters
+    ==========
+
+    A : Expr
+        The first argument of the commutator [A,B].
+    B : Expr
+        The second argument of the commutator [A,B].
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum import Commutator, Dagger, Operator
+    >>> from sympy.abc import x, y
+    >>> A = Operator('A')
+    >>> B = Operator('B')
+    >>> C = Operator('C')
+
+    Create a commutator and use ``.doit()`` to evaluate it:
+
+    >>> comm = Commutator(A, B)
+    >>> comm
+    [A,B]
+    >>> comm.doit()
+    A*B - B*A
+
+    The commutator orders it arguments in canonical order:
+
+    >>> comm = Commutator(B, A); comm
+    -[A,B]
+
+    Commutative constants are factored out:
+
+    >>> Commutator(3*x*A, x*y*B)
+    3*x**2*y*[A,B]
+
+    Using ``.expand(commutator=True)``, the standard commutator expansion rules
+    can be applied:
+
+    >>> Commutator(A+B, C).expand(commutator=True)
+    [A,C] + [B,C]
+    >>> Commutator(A, B+C).expand(commutator=True)
+    [A,B] + [A,C]
+    >>> Commutator(A*B, C).expand(commutator=True)
+    [A,C]*B + A*[B,C]
+    >>> Commutator(A, B*C).expand(commutator=True)
+    [A,B]*C + B*[A,C]
+
+    Adjoint operations applied to the commutator are properly applied to the
+    arguments:
+
+    >>> Dagger(Commutator(A, B))
+    -[Dagger(A),Dagger(B)]
+
+    References
+    ==========
+
+    .. [1] https://en.wikipedia.org/wiki/Commutator
+    """
+    is_commutative = False
+
+    _kind_dispatcher = KindDispatcher("Commutator_kind_dispatcher", commutative=True)
+
+    @property
+    def kind(self):
+        arg_kinds = (a.kind for a in self.args)
+        return self._kind_dispatcher(*arg_kinds)
+
+    def __new__(cls, A, B):
+        r = cls.eval(A, B)
+        if r is not None:
+            return r
+        obj = Expr.__new__(cls, A, B)
+        return obj
+
+    @classmethod
+    def eval(cls, a, b):
+        if not (a and b):
+            return S.Zero
+        if a == b:
+            return S.Zero
+        if a.is_commutative or b.is_commutative:
+            return S.Zero
+
+        # [xA,yB]  ->  xy*[A,B]
+        ca, nca = a.args_cnc()
+        cb, ncb = b.args_cnc()
+        c_part = ca + cb
+        if c_part:
+            return Mul(Mul(*c_part), cls(Mul._from_args(nca), Mul._from_args(ncb)))
+
+        # Canonical ordering of arguments
+        # The Commutator [A, B] is in canonical form if A < B.
+        if a.compare(b) == 1:
+            return S.NegativeOne*cls(b, a)
+
+    def _expand_pow(self, A, B, sign):
+        exp = A.exp
+        if not exp.is_integer or not exp.is_constant() or abs(exp) <= 1:
+            # nothing to do
+            return self
+        base = A.base
+        if exp.is_negative:
+            base = A.base**-1
+            exp = -exp
+        comm = Commutator(base, B).expand(commutator=True)
+
+        result = base**(exp - 1) * comm
+        for i in range(1, exp):
+            result += base**(exp - 1 - i) * comm * base**i
+        return sign*result.expand()
+
+    def _eval_expand_commutator(self, **hints):
+        A = self.args[0]
+        B = self.args[1]
+
+        if isinstance(A, Add):
+            # [A + B, C]  ->  [A, C] + [B, C]
+            sargs = []
+            for term in A.args:
+                comm = Commutator(term, B)
+                if isinstance(comm, Commutator):
+                    comm = comm._eval_expand_commutator()
+                sargs.append(comm)
+            return Add(*sargs)
+        elif isinstance(B, Add):
+            # [A, B + C]  ->  [A, B] + [A, C]
+            sargs = []
+            for term in B.args:
+                comm = Commutator(A, term)
+                if isinstance(comm, Commutator):
+                    comm = comm._eval_expand_commutator()
+                sargs.append(comm)
+            return Add(*sargs)
+        elif isinstance(A, Mul):
+            # [A*B, C] -> A*[B, C] + [A, C]*B
+            a = A.args[0]
+            b = Mul(*A.args[1:])
+            c = B
+            comm1 = Commutator(b, c)
+            comm2 = Commutator(a, c)
+            if isinstance(comm1, Commutator):
+                comm1 = comm1._eval_expand_commutator()
+            if isinstance(comm2, Commutator):
+                comm2 = comm2._eval_expand_commutator()
+            first = Mul(a, comm1)
+            second = Mul(comm2, b)
+            return Add(first, second)
+        elif isinstance(B, Mul):
+            # [A, B*C] -> [A, B]*C + B*[A, C]
+            a = A
+            b = B.args[0]
+            c = Mul(*B.args[1:])
+            comm1 = Commutator(a, b)
+            comm2 = Commutator(a, c)
+            if isinstance(comm1, Commutator):
+                comm1 = comm1._eval_expand_commutator()
+            if isinstance(comm2, Commutator):
+                comm2 = comm2._eval_expand_commutator()
+            first = Mul(comm1, c)
+            second = Mul(b, comm2)
+            return Add(first, second)
+        elif isinstance(A, Pow):
+            # [A**n, C] -> A**(n - 1)*[A, C] + A**(n - 2)*[A, C]*A + ... + [A, C]*A**(n-1)
+            return self._expand_pow(A, B, 1)
+        elif isinstance(B, Pow):
+            # [A, C**n] -> C**(n - 1)*[C, A] + C**(n - 2)*[C, A]*C + ... + [C, A]*C**(n-1)
+            return self._expand_pow(B, A, -1)
+
+        # No changes, so return self
+        return self
+
+    def doit(self, **hints):
+        """ Evaluate commutator """
+        # Keep the import of Operator here to avoid problems with
+        # circular imports.
+        from sympy.physics.quantum.operator import Operator
+        A = self.args[0]
+        B = self.args[1]
+        if isinstance(A, Operator) and isinstance(B, Operator):
+            try:
+                comm = A._eval_commutator(B, **hints)
+            except NotImplementedError:
+                try:
+                    comm = -1*B._eval_commutator(A, **hints)
+                except NotImplementedError:
+                    comm = None
+            if comm is not None:
+                return comm.doit(**hints)
+        return (A*B - B*A).doit(**hints)
+
+    def _eval_adjoint(self):
+        return Commutator(Dagger(self.args[1]), Dagger(self.args[0]))
+
+    def _sympyrepr(self, printer, *args):
+        return "%s(%s,%s)" % (
+            self.__class__.__name__, printer._print(
+                self.args[0]), printer._print(self.args[1])
+        )
+
+    def _sympystr(self, printer, *args):
+        return "[%s,%s]" % (
+            printer._print(self.args[0]), printer._print(self.args[1]))
+
+    def _pretty(self, printer, *args):
+        pform = printer._print(self.args[0], *args)
+        pform = prettyForm(*pform.right(prettyForm(',')))
+        pform = prettyForm(*pform.right(printer._print(self.args[1], *args)))
+        pform = prettyForm(*pform.parens(left='[', right=']'))
+        return pform
+
+    def _latex(self, printer, *args):
+        return "\\left[%s,%s\\right]" % tuple([
+            printer._print(arg, *args) for arg in self.args])
+
+
+@Commutator._kind_dispatcher.register(_OperatorKind, _OperatorKind)
+def find_op_kind(e1, e2):
+    """Find the kind of an anticommutator of two OperatorKinds."""
+    return OperatorKind

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/constants.py

@@ -0,0 +1,59 @@
+"""Constants (like hbar) related to quantum mechanics."""
+
+from sympy.core.numbers import NumberSymbol
+from sympy.core.singleton import Singleton
+from sympy.printing.pretty.stringpict import prettyForm
+import mpmath.libmp as mlib
+
+#-----------------------------------------------------------------------------
+# Constants
+#-----------------------------------------------------------------------------
+
+__all__ = [
+    'hbar',
+    'HBar',
+]
+
+
+class HBar(NumberSymbol, metaclass=Singleton):
+    """Reduced Plank's constant in numerical and symbolic form [1]_.
+
+    Examples
+    ========
+
+        >>> from sympy.physics.quantum.constants import hbar
+        >>> hbar.evalf()
+        1.05457162000000e-34
+
+    References
+    ==========
+
+    .. [1] https://en.wikipedia.org/wiki/Planck_constant
+    """
+
+    is_real = True
+    is_positive = True
+    is_negative = False
+    is_irrational = True
+
+    __slots__ = ()
+
+    def _as_mpf_val(self, prec):
+        return mlib.from_float(1.05457162e-34, prec)
+
+    def _sympyrepr(self, printer, *args):
+        return 'HBar()'
+
+    def _sympystr(self, printer, *args):
+        return 'hbar'
+
+    def _pretty(self, printer, *args):
+        if printer._use_unicode:
+            return prettyForm('\N{PLANCK CONSTANT OVER TWO PI}')
+        return prettyForm('hbar')
+
+    def _latex(self, printer, *args):
+        return r'\hbar'
+
+# Create an instance for everyone to use.
+hbar = HBar()

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/dagger.py

@@ -0,0 +1,95 @@
+"""Hermitian conjugation."""
+
+from sympy.core import Expr, sympify
+from sympy.functions.elementary.complexes import adjoint
+
+__all__ = [
+    'Dagger'
+]
+
+
+class Dagger(adjoint):
+    """General Hermitian conjugate operation.
+
+    Explanation
+    ===========
+
+    Take the Hermetian conjugate of an argument [1]_. For matrices this
+    operation is equivalent to transpose and complex conjugate [2]_.
+
+    Parameters
+    ==========
+
+    arg : Expr
+        The SymPy expression that we want to take the dagger of.
+    evaluate : bool
+        Whether the resulting expression should be directly evaluated.
+
+    Examples
+    ========
+
+    Daggering various quantum objects:
+
+        >>> from sympy.physics.quantum.dagger import Dagger
+        >>> from sympy.physics.quantum.state import Ket, Bra
+        >>> from sympy.physics.quantum.operator import Operator
+        >>> Dagger(Ket('psi'))
+        <psi|
+        >>> Dagger(Bra('phi'))
+        |phi>
+        >>> Dagger(Operator('A'))
+        Dagger(A)
+
+    Inner and outer products::
+
+        >>> from sympy.physics.quantum import InnerProduct, OuterProduct
+        >>> Dagger(InnerProduct(Bra('a'), Ket('b')))
+        <b|a>
+        >>> Dagger(OuterProduct(Ket('a'), Bra('b')))
+        |b><a|
+
+    Powers, sums and products::
+
+        >>> A = Operator('A')
+        >>> B = Operator('B')
+        >>> Dagger(A*B)
+        Dagger(B)*Dagger(A)
+        >>> Dagger(A+B)
+        Dagger(A) + Dagger(B)
+        >>> Dagger(A**2)
+        Dagger(A)**2
+
+    Dagger also seamlessly handles complex numbers and matrices::
+
+        >>> from sympy import Matrix, I
+        >>> m = Matrix([[1,I],[2,I]])
+        >>> m
+        Matrix([
+        [1, I],
+        [2, I]])
+        >>> Dagger(m)
+        Matrix([
+        [ 1,  2],
+        [-I, -I]])
+
+    References
+    ==========
+
+    .. [1] https://en.wikipedia.org/wiki/Hermitian_adjoint
+    .. [2] https://en.wikipedia.org/wiki/Hermitian_transpose
+    """
+
+    @property
+    def kind(self):
+        """Find the kind of a dagger of something (just the kind of the something)."""
+        return self.args[0].kind
+
+    def __new__(cls, arg, evaluate=True):
+        if hasattr(arg, 'adjoint') and evaluate:
+            return arg.adjoint()
+        elif hasattr(arg, 'conjugate') and hasattr(arg, 'transpose') and evaluate:
+            return arg.conjugate().transpose()
+        return Expr.__new__(cls, sympify(arg))
+
+adjoint.__name__ = "Dagger"
+adjoint._sympyrepr = lambda a, b: "Dagger(%s)" % b._print(a.args[0])

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/density.py

@@ -0,0 +1,315 @@
+from itertools import product
+
+from sympy.core.add import Add
+from sympy.core.containers import Tuple
+from sympy.core.function import expand
+from sympy.core.mul import Mul
+from sympy.core.singleton import S
+from sympy.functions.elementary.exponential import log
+from sympy.matrices.dense import MutableDenseMatrix as Matrix
+from sympy.printing.pretty.stringpict import prettyForm
+from sympy.physics.quantum.dagger import Dagger
+from sympy.physics.quantum.operator import HermitianOperator
+from sympy.physics.quantum.represent import represent
+from sympy.physics.quantum.matrixutils import numpy_ndarray, scipy_sparse_matrix, to_numpy
+from sympy.physics.quantum.trace import Tr
+
+
+class Density(HermitianOperator):
+    """Density operator for representing mixed states.
+
+    TODO: Density operator support for Qubits
+
+    Parameters
+    ==========
+
+    values : tuples/lists
+    Each tuple/list should be of form (state, prob) or [state,prob]
+
+    Examples
+    ========
+
+    Create a density operator with 2 states represented by Kets.
+
+    >>> from sympy.physics.quantum.state import Ket
+    >>> from sympy.physics.quantum.density import Density
+    >>> d = Density([Ket(0), 0.5], [Ket(1),0.5])
+    >>> d
+    Density((|0>, 0.5),(|1>, 0.5))
+
+    """
+    @classmethod
+    def _eval_args(cls, args):
+        # call this to qsympify the args
+        args = super()._eval_args(args)
+
+        for arg in args:
+            # Check if arg is a tuple
+            if not (isinstance(arg, Tuple) and len(arg) == 2):
+                raise ValueError("Each argument should be of form [state,prob]"
+                                 " or ( state, prob )")
+
+        return args
+
+    def states(self):
+        """Return list of all states.
+
+        Examples
+        ========
+
+        >>> from sympy.physics.quantum.state import Ket
+        >>> from sympy.physics.quantum.density import Density
+        >>> d = Density([Ket(0), 0.5], [Ket(1),0.5])
+        >>> d.states()
+        (|0>, |1>)
+
+        """
+        return Tuple(*[arg[0] for arg in self.args])
+
+    def probs(self):
+        """Return list of all probabilities.
+
+        Examples
+        ========
+
+        >>> from sympy.physics.quantum.state import Ket
+        >>> from sympy.physics.quantum.density import Density
+        >>> d = Density([Ket(0), 0.5], [Ket(1),0.5])
+        >>> d.probs()
+        (0.5, 0.5)
+
+        """
+        return Tuple(*[arg[1] for arg in self.args])
+
+    def get_state(self, index):
+        """Return specific state by index.
+
+        Parameters
+        ==========
+
+        index : index of state to be returned
+
+        Examples
+        ========
+
+        >>> from sympy.physics.quantum.state import Ket
+        >>> from sympy.physics.quantum.density import Density
+        >>> d = Density([Ket(0), 0.5], [Ket(1),0.5])
+        >>> d.states()[1]
+        |1>
+
+        """
+        state = self.args[index][0]
+        return state
+
+    def get_prob(self, index):
+        """Return probability of specific state by index.
+
+        Parameters
+        ===========
+
+        index : index of states whose probability is returned.
+
+        Examples
+        ========
+
+        >>> from sympy.physics.quantum.state import Ket
+        >>> from sympy.physics.quantum.density import Density
+        >>> d = Density([Ket(0), 0.5], [Ket(1),0.5])
+        >>> d.probs()[1]
+        0.500000000000000
+
+        """
+        prob = self.args[index][1]
+        return prob
+
+    def apply_op(self, op):
+        """op will operate on each individual state.
+
+        Parameters
+        ==========
+
+        op : Operator
+
+        Examples
+        ========
+
+        >>> from sympy.physics.quantum.state import Ket
+        >>> from sympy.physics.quantum.density import Density
+        >>> from sympy.physics.quantum.operator import Operator
+        >>> A = Operator('A')
+        >>> d = Density([Ket(0), 0.5], [Ket(1),0.5])
+        >>> d.apply_op(A)
+        Density((A*|0>, 0.5),(A*|1>, 0.5))
+
+        """
+        new_args = [(op*state, prob) for (state, prob) in self.args]
+        return Density(*new_args)
+
+    def doit(self, **hints):
+        """Expand the density operator into an outer product format.
+
+        Examples
+        ========
+
+        >>> from sympy.physics.quantum.state import Ket
+        >>> from sympy.physics.quantum.density import Density
+        >>> from sympy.physics.quantum.operator import Operator
+        >>> A = Operator('A')
+        >>> d = Density([Ket(0), 0.5], [Ket(1),0.5])
+        >>> d.doit()
+        0.5*|0><0| + 0.5*|1><1|
+
+        """
+
+        terms = []
+        for (state, prob) in self.args:
+            state = state.expand()  # needed to break up (a+b)*c
+            if (isinstance(state, Add)):
+                for arg in product(state.args, repeat=2):
+                    terms.append(prob*self._generate_outer_prod(arg[0],
+                                                                arg[1]))
+            else:
+                terms.append(prob*self._generate_outer_prod(state, state))
+
+        return Add(*terms)
+
+    def _generate_outer_prod(self, arg1, arg2):
+        c_part1, nc_part1 = arg1.args_cnc()
+        c_part2, nc_part2 = arg2.args_cnc()
+
+        if (len(nc_part1) == 0 or len(nc_part2) == 0):
+            raise ValueError('Atleast one-pair of'
+                             ' Non-commutative instance required'
+                             ' for outer product.')
+
+        # We were able to remove some tensor product simplifications that
+        # used to be here as those transformations are not automatically
+        # applied by transforms.py.
+        op = Mul(*nc_part1)*Dagger(Mul(*nc_part2))
+
+        return Mul(*c_part1)*Mul(*c_part2) * op
+
+    def _represent(self, **options):
+        return represent(self.doit(), **options)
+
+    def _print_operator_name_latex(self, printer, *args):
+        return r'\rho'
+
+    def _print_operator_name_pretty(self, printer, *args):
+        return prettyForm('\N{GREEK SMALL LETTER RHO}')
+
+    def _eval_trace(self, **kwargs):
+        indices = kwargs.get('indices', [])
+        return Tr(self.doit(), indices).doit()
+
+    def entropy(self):
+        """ Compute the entropy of a density matrix.
+
+        Refer to density.entropy() method  for examples.
+        """
+        return entropy(self)
+
+
+def entropy(density):
+    """Compute the entropy of a matrix/density object.
+
+    This computes -Tr(density*ln(density)) using the eigenvalue decomposition
+    of density, which is given as either a Density instance or a matrix
+    (numpy.ndarray, sympy.Matrix or scipy.sparse).
+
+    Parameters
+    ==========
+
+    density : density matrix of type Density, SymPy matrix,
+    scipy.sparse or numpy.ndarray
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum.density import Density, entropy
+    >>> from sympy.physics.quantum.spin import JzKet
+    >>> from sympy import S
+    >>> up = JzKet(S(1)/2,S(1)/2)
+    >>> down = JzKet(S(1)/2,-S(1)/2)
+    >>> d = Density((up,S(1)/2),(down,S(1)/2))
+    >>> entropy(d)
+    log(2)/2
+
+    """
+    if isinstance(density, Density):
+        density = represent(density)  # represent in Matrix
+
+    if isinstance(density, scipy_sparse_matrix):
+        density = to_numpy(density)
+
+    if isinstance(density, Matrix):
+        eigvals = density.eigenvals().keys()
+        return expand(-sum(e*log(e) for e in eigvals))
+    elif isinstance(density, numpy_ndarray):
+        import numpy as np
+        eigvals = np.linalg.eigvals(density)
+        return -np.sum(eigvals*np.log(eigvals))
+    else:
+        raise ValueError(
+            "numpy.ndarray, scipy.sparse or SymPy matrix expected")
+
+
+def fidelity(state1, state2):
+    """ Computes the fidelity [1]_ between two quantum states
+
+    The arguments provided to this function should be a square matrix or a
+    Density object. If it is a square matrix, it is assumed to be diagonalizable.
+
+    Parameters
+    ==========
+
+    state1, state2 : a density matrix or Matrix
+
+
+    Examples
+    ========
+
+    >>> from sympy import S, sqrt
+    >>> from sympy.physics.quantum.dagger import Dagger
+    >>> from sympy.physics.quantum.spin import JzKet
+    >>> from sympy.physics.quantum.density import fidelity
+    >>> from sympy.physics.quantum.represent import represent
+    >>>
+    >>> up = JzKet(S(1)/2,S(1)/2)
+    >>> down = JzKet(S(1)/2,-S(1)/2)
+    >>> amp = 1/sqrt(2)
+    >>> updown = (amp*up) + (amp*down)
+    >>>
+    >>> # represent turns Kets into matrices
+    >>> up_dm = represent(up*Dagger(up))
+    >>> down_dm = represent(down*Dagger(down))
+    >>> updown_dm = represent(updown*Dagger(updown))
+    >>>
+    >>> fidelity(up_dm, up_dm)
+    1
+    >>> fidelity(up_dm, down_dm) #orthogonal states
+    0
+    >>> fidelity(up_dm, updown_dm).evalf().round(3)
+    0.707
+
+    References
+    ==========
+
+    .. [1] https://en.wikipedia.org/wiki/Fidelity_of_quantum_states
+
+    """
+    state1 = represent(state1) if isinstance(state1, Density) else state1
+    state2 = represent(state2) if isinstance(state2, Density) else state2
+
+    if not isinstance(state1, Matrix) or not isinstance(state2, Matrix):
+        raise ValueError("state1 and state2 must be of type Density or Matrix "
+                         "received type=%s for state1 and type=%s for state2" %
+                         (type(state1), type(state2)))
+
+    if state1.shape != state2.shape and state1.is_square:
+        raise ValueError("The dimensions of both args should be equal and the "
+                         "matrix obtained should be a square matrix")
+
+    sqrt_state1 = state1**S.Half
+    return Tr((sqrt_state1*state2*sqrt_state1)**S.Half).doit()

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/fermion.py

@@ -0,0 +1,191 @@
+"""Fermionic quantum operators."""
+
+from sympy.core.numbers import Integer
+from sympy.core.singleton import S
+from sympy.physics.quantum import Operator
+from sympy.physics.quantum import HilbertSpace, Ket, Bra
+from sympy.functions.special.tensor_functions import KroneckerDelta
+
+
+__all__ = [
+    'FermionOp',
+    'FermionFockKet',
+    'FermionFockBra'
+]
+
+
+class FermionOp(Operator):
+    """A fermionic operator that satisfies {c, Dagger(c)} == 1.
+
+    Parameters
+    ==========
+
+    name : str
+        A string that labels the fermionic mode.
+
+    annihilation : bool
+        A bool that indicates if the fermionic operator is an annihilation
+        (True, default value) or creation operator (False)
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum import Dagger, AntiCommutator
+    >>> from sympy.physics.quantum.fermion import FermionOp
+    >>> c = FermionOp("c")
+    >>> AntiCommutator(c, Dagger(c)).doit()
+    1
+    """
+    @property
+    def name(self):
+        return self.args[0]
+
+    @property
+    def is_annihilation(self):
+        return bool(self.args[1])
+
+    @classmethod
+    def default_args(self):
+        return ("c", True)
+
+    def __new__(cls, *args, **hints):
+        if not len(args) in [1, 2]:
+            raise ValueError('1 or 2 parameters expected, got %s' % args)
+
+        if len(args) == 1:
+            args = (args[0], S.One)
+
+        if len(args) == 2:
+            args = (args[0], Integer(args[1]))
+
+        return Operator.__new__(cls, *args)
+
+    def _eval_commutator_FermionOp(self, other, **hints):
+        if 'independent' in hints and hints['independent']:
+            # [c, d] = 0
+            return S.Zero
+
+        return None
+
+    def _eval_anticommutator_FermionOp(self, other, **hints):
+        if self.name == other.name:
+            # {a^\dagger, a} = 1
+            if not self.is_annihilation and other.is_annihilation:
+                return S.One
+
+        elif 'independent' in hints and hints['independent']:
+            # {c, d} = 2 * c * d, because [c, d] = 0 for independent operators
+            return 2 * self * other
+
+        return None
+
+    def _eval_anticommutator_BosonOp(self, other, **hints):
+        # because fermions and bosons commute
+        return 2 * self * other
+
+    def _eval_commutator_BosonOp(self, other, **hints):
+        return S.Zero
+
+    def _eval_adjoint(self):
+        return FermionOp(str(self.name), not self.is_annihilation)
+
+    def _print_contents_latex(self, printer, *args):
+        if self.is_annihilation:
+            return r'{%s}' % str(self.name)
+        else:
+            return r'{{%s}^\dagger}' % str(self.name)
+
+    def _print_contents(self, printer, *args):
+        if self.is_annihilation:
+            return r'%s' % str(self.name)
+        else:
+            return r'Dagger(%s)' % str(self.name)
+
+    def _print_contents_pretty(self, printer, *args):
+        from sympy.printing.pretty.stringpict import prettyForm
+        pform = printer._print(self.args[0], *args)
+        if self.is_annihilation:
+            return pform
+        else:
+            return pform**prettyForm('\N{DAGGER}')
+
+    def _eval_power(self, exp):
+        from sympy.core.singleton import S
+        if exp == 0:
+            return S.One
+        elif exp == 1:
+            return self
+        elif (exp > 1) == True and exp.is_integer == True:
+            return S.Zero
+        elif (exp < 0) == True or exp.is_integer == False:
+            raise ValueError("Fermionic operators can only be raised to a"
+                " positive integer power")
+        return Operator._eval_power(self, exp)
+
+class FermionFockKet(Ket):
+    """Fock state ket for a fermionic mode.
+
+    Parameters
+    ==========
+
+    n : Number
+        The Fock state number.
+
+    """
+
+    def __new__(cls, n):
+        if n not in (0, 1):
+            raise ValueError("n must be 0 or 1")
+        return Ket.__new__(cls, n)
+
+    @property
+    def n(self):
+        return self.label[0]
+
+    @classmethod
+    def dual_class(self):
+        return FermionFockBra
+
+    @classmethod
+    def _eval_hilbert_space(cls, label):
+        return HilbertSpace()
+
+    def _eval_innerproduct_FermionFockBra(self, bra, **hints):
+        return KroneckerDelta(self.n, bra.n)
+
+    def _apply_from_right_to_FermionOp(self, op, **options):
+        if op.is_annihilation:
+            if self.n == 1:
+                return FermionFockKet(0)
+            else:
+                return S.Zero
+        else:
+            if self.n == 0:
+                return FermionFockKet(1)
+            else:
+                return S.Zero
+
+
+class FermionFockBra(Bra):
+    """Fock state bra for a fermionic mode.
+
+    Parameters
+    ==========
+
+    n : Number
+        The Fock state number.
+
+    """
+
+    def __new__(cls, n):
+        if n not in (0, 1):
+            raise ValueError("n must be 0 or 1")
+        return Bra.__new__(cls, n)
+
+    @property
+    def n(self):
+        return self.label[0]
+
+    @classmethod
+    def dual_class(self):
+        return FermionFockKet

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/grover.py

@@ -0,0 +1,345 @@
+"""Grover's algorithm and helper functions.
+
+Todo:
+
+* W gate construction (or perhaps -W gate based on Mermin's book)
+* Generalize the algorithm for an unknown function that returns 1 on multiple
+  qubit states, not just one.
+* Implement _represent_ZGate in OracleGate
+"""
+
+from sympy.core.numbers import pi
+from sympy.core.sympify import sympify
+from sympy.core.basic import Atom
+from sympy.functions.elementary.integers import floor
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.matrices.dense import eye
+from sympy.core.numbers import NegativeOne
+from sympy.physics.quantum.qapply import qapply
+from sympy.physics.quantum.qexpr import QuantumError
+from sympy.physics.quantum.hilbert import ComplexSpace
+from sympy.physics.quantum.operator import UnitaryOperator
+from sympy.physics.quantum.gate import Gate
+from sympy.physics.quantum.qubit import IntQubit
+
+__all__ = [
+    'OracleGate',
+    'WGate',
+    'superposition_basis',
+    'grover_iteration',
+    'apply_grover'
+]
+
+
+def superposition_basis(nqubits):
+    """Creates an equal superposition of the computational basis.
+
+    Parameters
+    ==========
+
+    nqubits : int
+        The number of qubits.
+
+    Returns
+    =======
+
+    state : Qubit
+        An equal superposition of the computational basis with nqubits.
+
+    Examples
+    ========
+
+    Create an equal superposition of 2 qubits::
+
+        >>> from sympy.physics.quantum.grover import superposition_basis
+        >>> superposition_basis(2)
+        |0>/2 + |1>/2 + |2>/2 + |3>/2
+    """
+
+    amp = 1/sqrt(2**nqubits)
+    return sum(amp*IntQubit(n, nqubits=nqubits) for n in range(2**nqubits))
+
+class OracleGateFunction(Atom):
+    """Wrapper for python functions used in `OracleGate`s"""
+
+    def __new__(cls, function):
+        if not callable(function):
+            raise TypeError('Callable expected, got: %r' % function)
+        obj = Atom.__new__(cls)
+        obj.function = function
+        return obj
+
+    def _hashable_content(self):
+        return type(self), self.function
+
+    def __call__(self, *args):
+        return self.function(*args)
+
+
+class OracleGate(Gate):
+    """A black box gate.
+
+    The gate marks the desired qubits of an unknown function by flipping
+    the sign of the qubits.  The unknown function returns true when it
+    finds its desired qubits and false otherwise.
+
+    Parameters
+    ==========
+
+    qubits : int
+        Number of qubits.
+
+    oracle : callable
+        A callable function that returns a boolean on a computational basis.
+
+    Examples
+    ========
+
+    Apply an Oracle gate that flips the sign of ``|2>`` on different qubits::
+
+        >>> from sympy.physics.quantum.qubit import IntQubit
+        >>> from sympy.physics.quantum.qapply import qapply
+        >>> from sympy.physics.quantum.grover import OracleGate
+        >>> f = lambda qubits: qubits == IntQubit(2)
+        >>> v = OracleGate(2, f)
+        >>> qapply(v*IntQubit(2))
+        -|2>
+        >>> qapply(v*IntQubit(3))
+        |3>
+    """
+
+    gate_name = 'V'
+    gate_name_latex = 'V'
+
+    #-------------------------------------------------------------------------
+    # Initialization/creation
+    #-------------------------------------------------------------------------
+
+    @classmethod
+    def _eval_args(cls, args):
+        if len(args) != 2:
+            raise QuantumError(
+                'Insufficient/excessive arguments to Oracle.  Please ' +
+                'supply the number of qubits and an unknown function.'
+            )
+        sub_args = (args[0],)
+        sub_args = UnitaryOperator._eval_args(sub_args)
+        if not sub_args[0].is_Integer:
+            raise TypeError('Integer expected, got: %r' % sub_args[0])
+
+        function = args[1]
+        if not isinstance(function, OracleGateFunction):
+            function = OracleGateFunction(function)
+
+        return (sub_args[0], function)
+
+    @classmethod
+    def _eval_hilbert_space(cls, args):
+        """This returns the smallest possible Hilbert space."""
+        return ComplexSpace(2)**args[0]
+
+    #-------------------------------------------------------------------------
+    # Properties
+    #-------------------------------------------------------------------------
+
+    @property
+    def search_function(self):
+        """The unknown function that helps find the sought after qubits."""
+        return self.label[1]
+
+    @property
+    def targets(self):
+        """A tuple of target qubits."""
+        return sympify(tuple(range(self.args[0])))
+
+    #-------------------------------------------------------------------------
+    # Apply
+    #-------------------------------------------------------------------------
+
+    def _apply_operator_Qubit(self, qubits, **options):
+        """Apply this operator to a Qubit subclass.
+
+        Parameters
+        ==========
+
+        qubits : Qubit
+            The qubit subclass to apply this operator to.
+
+        Returns
+        =======
+
+        state : Expr
+            The resulting quantum state.
+        """
+        if qubits.nqubits != self.nqubits:
+            raise QuantumError(
+                'OracleGate operates on %r qubits, got: %r'
+                % (self.nqubits, qubits.nqubits)
+            )
+        # If function returns 1 on qubits
+            # return the negative of the qubits (flip the sign)
+        if self.search_function(qubits):
+            return -qubits
+        else:
+            return qubits
+
+    #-------------------------------------------------------------------------
+    # Represent
+    #-------------------------------------------------------------------------
+
+    def _represent_ZGate(self, basis, **options):
+        """
+        Represent the OracleGate in the computational basis.
+        """
+        nbasis = 2**self.nqubits  # compute it only once
+        matrixOracle = eye(nbasis)
+        # Flip the sign given the output of the oracle function
+        for i in range(nbasis):
+            if self.search_function(IntQubit(i, nqubits=self.nqubits)):
+                matrixOracle[i, i] = NegativeOne()
+        return matrixOracle
+
+
+class WGate(Gate):
+    """General n qubit W Gate in Grover's algorithm.
+
+    The gate performs the operation ``2|phi><phi| - 1`` on some qubits.
+    ``|phi> = (tensor product of n Hadamards)*(|0> with n qubits)``
+
+    Parameters
+    ==========
+
+    nqubits : int
+        The number of qubits to operate on
+
+    """
+
+    gate_name = 'W'
+    gate_name_latex = 'W'
+
+    @classmethod
+    def _eval_args(cls, args):
+        if len(args) != 1:
+            raise QuantumError(
+                'Insufficient/excessive arguments to W gate.  Please ' +
+                'supply the number of qubits to operate on.'
+            )
+        args = UnitaryOperator._eval_args(args)
+        if not args[0].is_Integer:
+            raise TypeError('Integer expected, got: %r' % args[0])
+        return args
+
+    #-------------------------------------------------------------------------
+    # Properties
+    #-------------------------------------------------------------------------
+
+    @property
+    def targets(self):
+        return sympify(tuple(reversed(range(self.args[0]))))
+
+    #-------------------------------------------------------------------------
+    # Apply
+    #-------------------------------------------------------------------------
+
+    def _apply_operator_Qubit(self, qubits, **options):
+        """
+        qubits: a set of qubits (Qubit)
+        Returns: quantum object (quantum expression - QExpr)
+        """
+        if qubits.nqubits != self.nqubits:
+            raise QuantumError(
+                'WGate operates on %r qubits, got: %r'
+                % (self.nqubits, qubits.nqubits)
+            )
+
+        # See 'Quantum Computer Science' by David Mermin p.92 -> W|a> result
+        # Return (2/(sqrt(2^n)))|phi> - |a> where |a> is the current basis
+        # state and phi is the superposition of basis states (see function
+        # create_computational_basis above)
+        basis_states = superposition_basis(self.nqubits)
+        change_to_basis = (2/sqrt(2**self.nqubits))*basis_states
+        return change_to_basis - qubits
+
+
+def grover_iteration(qstate, oracle):
+    """Applies one application of the Oracle and W Gate, WV.
+
+    Parameters
+    ==========
+
+    qstate : Qubit
+        A superposition of qubits.
+    oracle : OracleGate
+        The black box operator that flips the sign of the desired basis qubits.
+
+    Returns
+    =======
+
+    Qubit : The qubits after applying the Oracle and W gate.
+
+    Examples
+    ========
+
+    Perform one iteration of grover's algorithm to see a phase change::
+
+        >>> from sympy.physics.quantum.qapply import qapply
+        >>> from sympy.physics.quantum.qubit import IntQubit
+        >>> from sympy.physics.quantum.grover import OracleGate
+        >>> from sympy.physics.quantum.grover import superposition_basis
+        >>> from sympy.physics.quantum.grover import grover_iteration
+        >>> numqubits = 2
+        >>> basis_states = superposition_basis(numqubits)
+        >>> f = lambda qubits: qubits == IntQubit(2)
+        >>> v = OracleGate(numqubits, f)
+        >>> qapply(grover_iteration(basis_states, v))
+        |2>
+
+    """
+    wgate = WGate(oracle.nqubits)
+    return wgate*oracle*qstate
+
+
+def apply_grover(oracle, nqubits, iterations=None):
+    """Applies grover's algorithm.
+
+    Parameters
+    ==========
+
+    oracle : callable
+        The unknown callable function that returns true when applied to the
+        desired qubits and false otherwise.
+
+    Returns
+    =======
+
+    state : Expr
+        The resulting state after Grover's algorithm has been iterated.
+
+    Examples
+    ========
+
+    Apply grover's algorithm to an even superposition of 2 qubits::
+
+        >>> from sympy.physics.quantum.qapply import qapply
+        >>> from sympy.physics.quantum.qubit import IntQubit
+        >>> from sympy.physics.quantum.grover import apply_grover
+        >>> f = lambda qubits: qubits == IntQubit(2)
+        >>> qapply(apply_grover(f, 2))
+        |2>
+
+    """
+    if nqubits <= 0:
+        raise QuantumError(
+            'Grover\'s algorithm needs nqubits > 0, received %r qubits'
+            % nqubits
+        )
+    if iterations is None:
+        iterations = floor(sqrt(2**nqubits)*(pi/4))
+
+    v = OracleGate(nqubits, oracle)
+    iterated = superposition_basis(nqubits)
+    for iter in range(iterations):
+        iterated = grover_iteration(iterated, v)
+        iterated = qapply(iterated)
+
+    return iterated

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/hilbert.py

@@ -0,0 +1,653 @@
+"""Hilbert spaces for quantum mechanics.
+
+Authors:
+* Brian Granger
+* Matt Curry
+"""
+
+from functools import reduce
+
+from sympy.core.basic import Basic
+from sympy.core.singleton import S
+from sympy.core.sympify import sympify
+from sympy.sets.sets import Interval
+from sympy.printing.pretty.stringpict import prettyForm
+from sympy.physics.quantum.qexpr import QuantumError
+
+
+__all__ = [
+    'HilbertSpaceError',
+    'HilbertSpace',
+    'TensorProductHilbertSpace',
+    'TensorPowerHilbertSpace',
+    'DirectSumHilbertSpace',
+    'ComplexSpace',
+    'L2',
+    'FockSpace'
+]
+
+#-----------------------------------------------------------------------------
+# Main objects
+#-----------------------------------------------------------------------------
+
+
+class HilbertSpaceError(QuantumError):
+    pass
+
+#-----------------------------------------------------------------------------
+# Main objects
+#-----------------------------------------------------------------------------
+
+
+class HilbertSpace(Basic):
+    """An abstract Hilbert space for quantum mechanics.
+
+    In short, a Hilbert space is an abstract vector space that is complete
+    with inner products defined [1]_.
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum.hilbert import HilbertSpace
+    >>> hs = HilbertSpace()
+    >>> hs
+    H
+
+    References
+    ==========
+
+    .. [1] https://en.wikipedia.org/wiki/Hilbert_space
+    """
+
+    def __new__(cls):
+        obj = Basic.__new__(cls)
+        return obj
+
+    @property
+    def dimension(self):
+        """Return the Hilbert dimension of the space."""
+        raise NotImplementedError('This Hilbert space has no dimension.')
+
+    def __add__(self, other):
+        return DirectSumHilbertSpace(self, other)
+
+    def __radd__(self, other):
+        return DirectSumHilbertSpace(other, self)
+
+    def __mul__(self, other):
+        return TensorProductHilbertSpace(self, other)
+
+    def __rmul__(self, other):
+        return TensorProductHilbertSpace(other, self)
+
+    def __pow__(self, other, mod=None):
+        if mod is not None:
+            raise ValueError('The third argument to __pow__ is not supported \
+            for Hilbert spaces.')
+        return TensorPowerHilbertSpace(self, other)
+
+    def __contains__(self, other):
+        """Is the operator or state in this Hilbert space.
+
+        This is checked by comparing the classes of the Hilbert spaces, not
+        the instances. This is to allow Hilbert Spaces with symbolic
+        dimensions.
+        """
+        if other.hilbert_space.__class__ == self.__class__:
+            return True
+        else:
+            return False
+
+    def _sympystr(self, printer, *args):
+        return 'H'
+
+    def _pretty(self, printer, *args):
+        ustr = '\N{LATIN CAPITAL LETTER H}'
+        return prettyForm(ustr)
+
+    def _latex(self, printer, *args):
+        return r'\mathcal{H}'
+
+
+class ComplexSpace(HilbertSpace):
+    """Finite dimensional Hilbert space of complex vectors.
+
+    The elements of this Hilbert space are n-dimensional complex valued
+    vectors with the usual inner product that takes the complex conjugate
+    of the vector on the right.
+
+    A classic example of this type of Hilbert space is spin-1/2, which is
+    ``ComplexSpace(2)``. Generalizing to spin-s, the space is
+    ``ComplexSpace(2*s+1)``.  Quantum computing with N qubits is done with the
+    direct product space ``ComplexSpace(2)**N``.
+
+    Examples
+    ========
+
+    >>> from sympy import symbols
+    >>> from sympy.physics.quantum.hilbert import ComplexSpace
+    >>> c1 = ComplexSpace(2)
+    >>> c1
+    C(2)
+    >>> c1.dimension
+    2
+
+    >>> n = symbols('n')
+    >>> c2 = ComplexSpace(n)
+    >>> c2
+    C(n)
+    >>> c2.dimension
+    n
+
+    """
+
+    def __new__(cls, dimension):
+        dimension = sympify(dimension)
+        r = cls.eval(dimension)
+        if isinstance(r, Basic):
+            return r
+        obj = Basic.__new__(cls, dimension)
+        return obj
+
+    @classmethod
+    def eval(cls, dimension):
+        if len(dimension.atoms()) == 1:
+            if not (dimension.is_Integer and dimension > 0 or dimension is S.Infinity
+            or dimension.is_Symbol):
+                raise TypeError('The dimension of a ComplexSpace can only'
+                                'be a positive integer, oo, or a Symbol: %r'
+                                % dimension)
+        else:
+            for dim in dimension.atoms():
+                if not (dim.is_Integer or dim is S.Infinity or dim.is_Symbol):
+                    raise TypeError('The dimension of a ComplexSpace can only'
+                                    ' contain integers, oo, or a Symbol: %r'
+                                    % dim)
+
+    @property
+    def dimension(self):
+        return self.args[0]
+
+    def _sympyrepr(self, printer, *args):
+        return "%s(%s)" % (self.__class__.__name__,
+                           printer._print(self.dimension, *args))
+
+    def _sympystr(self, printer, *args):
+        return "C(%s)" % printer._print(self.dimension, *args)
+
+    def _pretty(self, printer, *args):
+        ustr = '\N{LATIN CAPITAL LETTER C}'
+        pform_exp = printer._print(self.dimension, *args)
+        pform_base = prettyForm(ustr)
+        return pform_base**pform_exp
+
+    def _latex(self, printer, *args):
+        return r'\mathcal{C}^{%s}' % printer._print(self.dimension, *args)
+
+
+class L2(HilbertSpace):
+    """The Hilbert space of square integrable functions on an interval.
+
+    An L2 object takes in a single SymPy Interval argument which represents
+    the interval its functions (vectors) are defined on.
+
+    Examples
+    ========
+
+    >>> from sympy import Interval, oo
+    >>> from sympy.physics.quantum.hilbert import L2
+    >>> hs = L2(Interval(0,oo))
+    >>> hs
+    L2(Interval(0, oo))
+    >>> hs.dimension
+    oo
+    >>> hs.interval
+    Interval(0, oo)
+
+    """
+
+    def __new__(cls, interval):
+        if not isinstance(interval, Interval):
+            raise TypeError('L2 interval must be an Interval instance: %r'
+            % interval)
+        obj = Basic.__new__(cls, interval)
+        return obj
+
+    @property
+    def dimension(self):
+        return S.Infinity
+
+    @property
+    def interval(self):
+        return self.args[0]
+
+    def _sympyrepr(self, printer, *args):
+        return "L2(%s)" % printer._print(self.interval, *args)
+
+    def _sympystr(self, printer, *args):
+        return "L2(%s)" % printer._print(self.interval, *args)
+
+    def _pretty(self, printer, *args):
+        pform_exp = prettyForm('2')
+        pform_base = prettyForm('L')
+        return pform_base**pform_exp
+
+    def _latex(self, printer, *args):
+        interval = printer._print(self.interval, *args)
+        return r'{\mathcal{L}^2}\left( %s \right)' % interval
+
+
+class FockSpace(HilbertSpace):
+    """The Hilbert space for second quantization.
+
+    Technically, this Hilbert space is a infinite direct sum of direct
+    products of single particle Hilbert spaces [1]_. This is a mess, so we have
+    a class to represent it directly.
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum.hilbert import FockSpace
+    >>> hs = FockSpace()
+    >>> hs
+    F
+    >>> hs.dimension
+    oo
+
+    References
+    ==========
+
+    .. [1] https://en.wikipedia.org/wiki/Fock_space
+    """
+
+    def __new__(cls):
+        obj = Basic.__new__(cls)
+        return obj
+
+    @property
+    def dimension(self):
+        return S.Infinity
+
+    def _sympyrepr(self, printer, *args):
+        return "FockSpace()"
+
+    def _sympystr(self, printer, *args):
+        return "F"
+
+    def _pretty(self, printer, *args):
+        ustr = '\N{LATIN CAPITAL LETTER F}'
+        return prettyForm(ustr)
+
+    def _latex(self, printer, *args):
+        return r'\mathcal{F}'
+
+
+class TensorProductHilbertSpace(HilbertSpace):
+    """A tensor product of Hilbert spaces [1]_.
+
+    The tensor product between Hilbert spaces is represented by the
+    operator ``*`` Products of the same Hilbert space will be combined into
+    tensor powers.
+
+    A ``TensorProductHilbertSpace`` object takes in an arbitrary number of
+    ``HilbertSpace`` objects as its arguments. In addition, multiplication of
+    ``HilbertSpace`` objects will automatically return this tensor product
+    object.
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum.hilbert import ComplexSpace, FockSpace
+    >>> from sympy import symbols
+
+    >>> c = ComplexSpace(2)
+    >>> f = FockSpace()
+    >>> hs = c*f
+    >>> hs
+    C(2)*F
+    >>> hs.dimension
+    oo
+    >>> hs.spaces
+    (C(2), F)
+
+    >>> c1 = ComplexSpace(2)
+    >>> n = symbols('n')
+    >>> c2 = ComplexSpace(n)
+    >>> hs = c1*c2
+    >>> hs
+    C(2)*C(n)
+    >>> hs.dimension
+    2*n
+
+    References
+    ==========
+
+    .. [1] https://en.wikipedia.org/wiki/Hilbert_space#Tensor_products
+    """
+
+    def __new__(cls, *args):
+        r = cls.eval(args)
+        if isinstance(r, Basic):
+            return r
+        obj = Basic.__new__(cls, *args)
+        return obj
+
+    @classmethod
+    def eval(cls, args):
+        """Evaluates the direct product."""
+        new_args = []
+        recall = False
+        #flatten arguments
+        for arg in args:
+            if isinstance(arg, TensorProductHilbertSpace):
+                new_args.extend(arg.args)
+                recall = True
+            elif isinstance(arg, (HilbertSpace, TensorPowerHilbertSpace)):
+                new_args.append(arg)
+            else:
+                raise TypeError('Hilbert spaces can only be multiplied by \
+                other Hilbert spaces: %r' % arg)
+        #combine like arguments into direct powers
+        comb_args = []
+        prev_arg = None
+        for new_arg in new_args:
+            if prev_arg is not None:
+                if isinstance(new_arg, TensorPowerHilbertSpace) and \
+                    isinstance(prev_arg, TensorPowerHilbertSpace) and \
+                        new_arg.base == prev_arg.base:
+                    prev_arg = new_arg.base**(new_arg.exp + prev_arg.exp)
+                elif isinstance(new_arg, TensorPowerHilbertSpace) and \
+                        new_arg.base == prev_arg:
+                    prev_arg = prev_arg**(new_arg.exp + 1)
+                elif isinstance(prev_arg, TensorPowerHilbertSpace) and \
+                        new_arg == prev_arg.base:
+                    prev_arg = new_arg**(prev_arg.exp + 1)
+                elif new_arg == prev_arg:
+                    prev_arg = new_arg**2
+                else:
+                    comb_args.append(prev_arg)
+                    prev_arg = new_arg
+            elif prev_arg is None:
+                prev_arg = new_arg
+        comb_args.append(prev_arg)
+        if recall:
+            return TensorProductHilbertSpace(*comb_args)
+        elif len(comb_args) == 1:
+            return TensorPowerHilbertSpace(comb_args[0].base, comb_args[0].exp)
+        else:
+            return None
+
+    @property
+    def dimension(self):
+        arg_list = [arg.dimension for arg in self.args]
+        if S.Infinity in arg_list:
+            return S.Infinity
+        else:
+            return reduce(lambda x, y: x*y, arg_list)
+
+    @property
+    def spaces(self):
+        """A tuple of the Hilbert spaces in this tensor product."""
+        return self.args
+
+    def _spaces_printer(self, printer, *args):
+        spaces_strs = []
+        for arg in self.args:
+            s = printer._print(arg, *args)
+            if isinstance(arg, DirectSumHilbertSpace):
+                s = '(%s)' % s
+            spaces_strs.append(s)
+        return spaces_strs
+
+    def _sympyrepr(self, printer, *args):
+        spaces_reprs = self._spaces_printer(printer, *args)
+        return "TensorProductHilbertSpace(%s)" % ','.join(spaces_reprs)
+
+    def _sympystr(self, printer, *args):
+        spaces_strs = self._spaces_printer(printer, *args)
+        return '*'.join(spaces_strs)
+
+    def _pretty(self, printer, *args):
+        length = len(self.args)
+        pform = printer._print('', *args)
+        for i in range(length):
+            next_pform = printer._print(self.args[i], *args)
+            if isinstance(self.args[i], (DirectSumHilbertSpace,
+                          TensorProductHilbertSpace)):
+                next_pform = prettyForm(
+                    *next_pform.parens(left='(', right=')')
+                )
+            pform = prettyForm(*pform.right(next_pform))
+            if i != length - 1:
+                if printer._use_unicode:
+                    pform = prettyForm(*pform.right(' ' + '\N{N-ARY CIRCLED TIMES OPERATOR}' + ' '))
+                else:
+                    pform = prettyForm(*pform.right(' x '))
+        return pform
+
+    def _latex(self, printer, *args):
+        length = len(self.args)
+        s = ''
+        for i in range(length):
+            arg_s = printer._print(self.args[i], *args)
+            if isinstance(self.args[i], (DirectSumHilbertSpace,
+                 TensorProductHilbertSpace)):
+                arg_s = r'\left(%s\right)' % arg_s
+            s = s + arg_s
+            if i != length - 1:
+                s = s + r'\otimes '
+        return s
+
+
+class DirectSumHilbertSpace(HilbertSpace):
+    """A direct sum of Hilbert spaces [1]_.
+
+    This class uses the ``+`` operator to represent direct sums between
+    different Hilbert spaces.
+
+    A ``DirectSumHilbertSpace`` object takes in an arbitrary number of
+    ``HilbertSpace`` objects as its arguments. Also, addition of
+    ``HilbertSpace`` objects will automatically return a direct sum object.
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum.hilbert import ComplexSpace, FockSpace
+
+    >>> c = ComplexSpace(2)
+    >>> f = FockSpace()
+    >>> hs = c+f
+    >>> hs
+    C(2)+F
+    >>> hs.dimension
+    oo
+    >>> list(hs.spaces)
+    [C(2), F]
+
+    References
+    ==========
+
+    .. [1] https://en.wikipedia.org/wiki/Hilbert_space#Direct_sums
+    """
+    def __new__(cls, *args):
+        r = cls.eval(args)
+        if isinstance(r, Basic):
+            return r
+        obj = Basic.__new__(cls, *args)
+        return obj
+
+    @classmethod
+    def eval(cls, args):
+        """Evaluates the direct product."""
+        new_args = []
+        recall = False
+        #flatten arguments
+        for arg in args:
+            if isinstance(arg, DirectSumHilbertSpace):
+                new_args.extend(arg.args)
+                recall = True
+            elif isinstance(arg, HilbertSpace):
+                new_args.append(arg)
+            else:
+                raise TypeError('Hilbert spaces can only be summed with other \
+                Hilbert spaces: %r' % arg)
+        if recall:
+            return DirectSumHilbertSpace(*new_args)
+        else:
+            return None
+
+    @property
+    def dimension(self):
+        arg_list = [arg.dimension for arg in self.args]
+        if S.Infinity in arg_list:
+            return S.Infinity
+        else:
+            return reduce(lambda x, y: x + y, arg_list)
+
+    @property
+    def spaces(self):
+        """A tuple of the Hilbert spaces in this direct sum."""
+        return self.args
+
+    def _sympyrepr(self, printer, *args):
+        spaces_reprs = [printer._print(arg, *args) for arg in self.args]
+        return "DirectSumHilbertSpace(%s)" % ','.join(spaces_reprs)
+
+    def _sympystr(self, printer, *args):
+        spaces_strs = [printer._print(arg, *args) for arg in self.args]
+        return '+'.join(spaces_strs)
+
+    def _pretty(self, printer, *args):
+        length = len(self.args)
+        pform = printer._print('', *args)
+        for i in range(length):
+            next_pform = printer._print(self.args[i], *args)
+            if isinstance(self.args[i], (DirectSumHilbertSpace,
+                          TensorProductHilbertSpace)):
+                next_pform = prettyForm(
+                    *next_pform.parens(left='(', right=')')
+                )
+            pform = prettyForm(*pform.right(next_pform))
+            if i != length - 1:
+                if printer._use_unicode:
+                    pform = prettyForm(*pform.right(' \N{CIRCLED PLUS} '))
+                else:
+                    pform = prettyForm(*pform.right(' + '))
+        return pform
+
+    def _latex(self, printer, *args):
+        length = len(self.args)
+        s = ''
+        for i in range(length):
+            arg_s = printer._print(self.args[i], *args)
+            if isinstance(self.args[i], (DirectSumHilbertSpace,
+                 TensorProductHilbertSpace)):
+                arg_s = r'\left(%s\right)' % arg_s
+            s = s + arg_s
+            if i != length - 1:
+                s = s + r'\oplus '
+        return s
+
+
+class TensorPowerHilbertSpace(HilbertSpace):
+    """An exponentiated Hilbert space [1]_.
+
+    Tensor powers (repeated tensor products) are represented by the
+    operator ``**`` Identical Hilbert spaces that are multiplied together
+    will be automatically combined into a single tensor power object.
+
+    Any Hilbert space, product, or sum may be raised to a tensor power. The
+    ``TensorPowerHilbertSpace`` takes two arguments: the Hilbert space; and the
+    tensor power (number).
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum.hilbert import ComplexSpace, FockSpace
+    >>> from sympy import symbols
+
+    >>> n = symbols('n')
+    >>> c = ComplexSpace(2)
+    >>> hs = c**n
+    >>> hs
+    C(2)**n
+    >>> hs.dimension
+    2**n
+
+    >>> c = ComplexSpace(2)
+    >>> c*c
+    C(2)**2
+    >>> f = FockSpace()
+    >>> c*f*f
+    C(2)*F**2
+
+    References
+    ==========
+
+    .. [1] https://en.wikipedia.org/wiki/Hilbert_space#Tensor_products
+    """
+
+    def __new__(cls, *args):
+        r = cls.eval(args)
+        if isinstance(r, Basic):
+            return r
+        return Basic.__new__(cls, *r)
+
+    @classmethod
+    def eval(cls, args):
+        new_args = args[0], sympify(args[1])
+        exp = new_args[1]
+        #simplify hs**1 -> hs
+        if exp is S.One:
+            return args[0]
+        #simplify hs**0 -> 1
+        if exp is S.Zero:
+            return S.One
+        #check (and allow) for hs**(x+42+y...) case
+        if len(exp.atoms()) == 1:
+            if not (exp.is_Integer and exp >= 0 or exp.is_Symbol):
+                raise ValueError('Hilbert spaces can only be raised to \
+                positive integers or Symbols: %r' % exp)
+        else:
+            for power in exp.atoms():
+                if not (power.is_Integer or power.is_Symbol):
+                    raise ValueError('Tensor powers can only contain integers \
+                    or Symbols: %r' % power)
+        return new_args
+
+    @property
+    def base(self):
+        return self.args[0]
+
+    @property
+    def exp(self):
+        return self.args[1]
+
+    @property
+    def dimension(self):
+        if self.base.dimension is S.Infinity:
+            return S.Infinity
+        else:
+            return self.base.dimension**self.exp
+
+    def _sympyrepr(self, printer, *args):
+        return "TensorPowerHilbertSpace(%s,%s)" % (printer._print(self.base,
+        *args), printer._print(self.exp, *args))
+
+    def _sympystr(self, printer, *args):
+        return "%s**%s" % (printer._print(self.base, *args),
+        printer._print(self.exp, *args))
+
+    def _pretty(self, printer, *args):
+        pform_exp = printer._print(self.exp, *args)
+        if printer._use_unicode:
+            pform_exp = prettyForm(*pform_exp.left(prettyForm('\N{N-ARY CIRCLED TIMES OPERATOR}')))
+        else:
+            pform_exp = prettyForm(*pform_exp.left(prettyForm('x')))
+        pform_base = printer._print(self.base, *args)
+        return pform_base**pform_exp
+
+    def _latex(self, printer, *args):
+        base = printer._print(self.base, *args)
+        exp = printer._print(self.exp, *args)
+        return r'{%s}^{\otimes %s}' % (base, exp)

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/identitysearch.py

@@ -0,0 +1,853 @@
+from collections import deque
+from sympy.core.random import randint
+
+from sympy.external import import_module
+from sympy.core.basic import Basic
+from sympy.core.mul import Mul
+from sympy.core.numbers import Number, equal_valued
+from sympy.core.power import Pow
+from sympy.core.singleton import S
+from sympy.physics.quantum.represent import represent
+from sympy.physics.quantum.dagger import Dagger
+
+__all__ = [
+    # Public interfaces
+    'generate_gate_rules',
+    'generate_equivalent_ids',
+    'GateIdentity',
+    'bfs_identity_search',
+    'random_identity_search',
+
+    # "Private" functions
+    'is_scalar_sparse_matrix',
+    'is_scalar_nonsparse_matrix',
+    'is_degenerate',
+    'is_reducible',
+]
+
+np = import_module('numpy')
+scipy = import_module('scipy', import_kwargs={'fromlist': ['sparse']})
+
+
+def is_scalar_sparse_matrix(circuit, nqubits, identity_only, eps=1e-11):
+    """Checks if a given scipy.sparse matrix is a scalar matrix.
+
+    A scalar matrix is such that B = bI, where B is the scalar
+    matrix, b is some scalar multiple, and I is the identity
+    matrix.  A scalar matrix would have only the element b along
+    it's main diagonal and zeroes elsewhere.
+
+    Parameters
+    ==========
+
+    circuit : Gate tuple
+        Sequence of quantum gates representing a quantum circuit
+    nqubits : int
+        Number of qubits in the circuit
+    identity_only : bool
+        Check for only identity matrices
+    eps : number
+        The tolerance value for zeroing out elements in the matrix.
+        Values in the range [-eps, +eps] will be changed to a zero.
+    """
+
+    if not np or not scipy:
+        pass
+
+    matrix = represent(Mul(*circuit), nqubits=nqubits,
+                       format='scipy.sparse')
+
+    # In some cases, represent returns a 1D scalar value in place
+    # of a multi-dimensional scalar matrix
+    if (isinstance(matrix, int)):
+        return matrix == 1 if identity_only else True
+
+    # If represent returns a matrix, check if the matrix is diagonal
+    # and if every item along the diagonal is the same
+    else:
+        # Due to floating pointing operations, must zero out
+        # elements that are "very" small in the dense matrix
+        # See parameter for default value.
+
+        # Get the ndarray version of the dense matrix
+        dense_matrix = matrix.todense().getA()
+        # Since complex values can't be compared, must split
+        # the matrix into real and imaginary components
+        # Find the real values in between -eps and eps
+        bool_real = np.logical_and(dense_matrix.real > -eps,
+                                   dense_matrix.real < eps)
+        # Find the imaginary values between -eps and eps
+        bool_imag = np.logical_and(dense_matrix.imag > -eps,
+                                   dense_matrix.imag < eps)
+        # Replaces values between -eps and eps with 0
+        corrected_real = np.where(bool_real, 0.0, dense_matrix.real)
+        corrected_imag = np.where(bool_imag, 0.0, dense_matrix.imag)
+        # Convert the matrix with real values into imaginary values
+        corrected_imag = corrected_imag * complex(1j)
+        # Recombine the real and imaginary components
+        corrected_dense = corrected_real + corrected_imag
+
+        # Check if it's diagonal
+        row_indices = corrected_dense.nonzero()[0]
+        col_indices = corrected_dense.nonzero()[1]
+        # Check if the rows indices and columns indices are the same
+        # If they match, then matrix only contains elements along diagonal
+        bool_indices = row_indices == col_indices
+        is_diagonal = bool_indices.all()
+
+        first_element = corrected_dense[0][0]
+        # If the first element is a zero, then can't rescale matrix
+        # and definitely not diagonal
+        if (first_element == 0.0 + 0.0j):
+            return False
+
+        # The dimensions of the dense matrix should still
+        # be 2^nqubits if there are elements all along the
+        # the main diagonal
+        trace_of_corrected = (corrected_dense/first_element).trace()
+        expected_trace = pow(2, nqubits)
+        has_correct_trace = trace_of_corrected == expected_trace
+
+        # If only looking for identity matrices
+        # first element must be a 1
+        real_is_one = abs(first_element.real - 1.0) < eps
+        imag_is_zero = abs(first_element.imag) < eps
+        is_one = real_is_one and imag_is_zero
+        is_identity = is_one if identity_only else True
+        return bool(is_diagonal and has_correct_trace and is_identity)
+
+
+def is_scalar_nonsparse_matrix(circuit, nqubits, identity_only, eps=None):
+    """Checks if a given circuit, in matrix form, is equivalent to
+    a scalar value.
+
+    Parameters
+    ==========
+
+    circuit : Gate tuple
+        Sequence of quantum gates representing a quantum circuit
+    nqubits : int
+        Number of qubits in the circuit
+    identity_only : bool
+        Check for only identity matrices
+    eps : number
+        This argument is ignored. It is just for signature compatibility with
+        is_scalar_sparse_matrix.
+
+    Note: Used in situations when is_scalar_sparse_matrix has bugs
+    """
+
+    matrix = represent(Mul(*circuit), nqubits=nqubits)
+
+    # In some cases, represent returns a 1D scalar value in place
+    # of a multi-dimensional scalar matrix
+    if (isinstance(matrix, Number)):
+        return matrix == 1 if identity_only else True
+
+    # If represent returns a matrix, check if the matrix is diagonal
+    # and if every item along the diagonal is the same
+    else:
+        # Added up the diagonal elements
+        matrix_trace = matrix.trace()
+        # Divide the trace by the first element in the matrix
+        # if matrix is not required to be the identity matrix
+        adjusted_matrix_trace = (matrix_trace/matrix[0]
+                                 if not identity_only
+                                 else matrix_trace)
+
+        is_identity = equal_valued(matrix[0], 1) if identity_only else True
+
+        has_correct_trace = adjusted_matrix_trace == pow(2, nqubits)
+
+        # The matrix is scalar if it's diagonal and the adjusted trace
+        # value is equal to 2^nqubits
+        return bool(
+            matrix.is_diagonal() and has_correct_trace and is_identity)
+
+if np and scipy:
+    is_scalar_matrix = is_scalar_sparse_matrix
+else:
+    is_scalar_matrix = is_scalar_nonsparse_matrix
+
+
+def _get_min_qubits(a_gate):
+    if isinstance(a_gate, Pow):
+        return a_gate.base.min_qubits
+    else:
+        return a_gate.min_qubits
+
+
+def ll_op(left, right):
+    """Perform a LL operation.
+
+    A LL operation multiplies both left and right circuits
+    with the dagger of the left circuit's leftmost gate, and
+    the dagger is multiplied on the left side of both circuits.
+
+    If a LL is possible, it returns the new gate rule as a
+    2-tuple (LHS, RHS), where LHS is the left circuit and
+    and RHS is the right circuit of the new rule.
+    If a LL is not possible, None is returned.
+
+    Parameters
+    ==========
+
+    left : Gate tuple
+        The left circuit of a gate rule expression.
+    right : Gate tuple
+        The right circuit of a gate rule expression.
+
+    Examples
+    ========
+
+    Generate a new gate rule using a LL operation:
+
+    >>> from sympy.physics.quantum.identitysearch import ll_op
+    >>> from sympy.physics.quantum.gate import X, Y, Z
+    >>> x = X(0); y = Y(0); z = Z(0)
+    >>> ll_op((x, y, z), ())
+    ((Y(0), Z(0)), (X(0),))
+
+    >>> ll_op((y, z), (x,))
+    ((Z(0),), (Y(0), X(0)))
+    """
+
+    if (len(left) > 0):
+        ll_gate = left[0]
+        ll_gate_is_unitary = is_scalar_matrix(
+            (Dagger(ll_gate), ll_gate), _get_min_qubits(ll_gate), True)
+
+    if (len(left) > 0 and ll_gate_is_unitary):
+        # Get the new left side w/o the leftmost gate
+        new_left = left[1:len(left)]
+        # Add the leftmost gate to the left position on the right side
+        new_right = (Dagger(ll_gate),) + right
+        # Return the new gate rule
+        return (new_left, new_right)
+
+    return None
+
+
+def lr_op(left, right):
+    """Perform a LR operation.
+
+    A LR operation multiplies both left and right circuits
+    with the dagger of the left circuit's rightmost gate, and
+    the dagger is multiplied on the right side of both circuits.
+
+    If a LR is possible, it returns the new gate rule as a
+    2-tuple (LHS, RHS), where LHS is the left circuit and
+    and RHS is the right circuit of the new rule.
+    If a LR is not possible, None is returned.
+
+    Parameters
+    ==========
+
+    left : Gate tuple
+        The left circuit of a gate rule expression.
+    right : Gate tuple
+        The right circuit of a gate rule expression.
+
+    Examples
+    ========
+
+    Generate a new gate rule using a LR operation:
+
+    >>> from sympy.physics.quantum.identitysearch import lr_op
+    >>> from sympy.physics.quantum.gate import X, Y, Z
+    >>> x = X(0); y = Y(0); z = Z(0)
+    >>> lr_op((x, y, z), ())
+    ((X(0), Y(0)), (Z(0),))
+
+    >>> lr_op((x, y), (z,))
+    ((X(0),), (Z(0), Y(0)))
+    """
+
+    if (len(left) > 0):
+        lr_gate = left[len(left) - 1]
+        lr_gate_is_unitary = is_scalar_matrix(
+            (Dagger(lr_gate), lr_gate), _get_min_qubits(lr_gate), True)
+
+    if (len(left) > 0 and lr_gate_is_unitary):
+        # Get the new left side w/o the rightmost gate
+        new_left = left[0:len(left) - 1]
+        # Add the rightmost gate to the right position on the right side
+        new_right = right + (Dagger(lr_gate),)
+        # Return the new gate rule
+        return (new_left, new_right)
+
+    return None
+
+
+def rl_op(left, right):
+    """Perform a RL operation.
+
+    A RL operation multiplies both left and right circuits
+    with the dagger of the right circuit's leftmost gate, and
+    the dagger is multiplied on the left side of both circuits.
+
+    If a RL is possible, it returns the new gate rule as a
+    2-tuple (LHS, RHS), where LHS is the left circuit and
+    and RHS is the right circuit of the new rule.
+    If a RL is not possible, None is returned.
+
+    Parameters
+    ==========
+
+    left : Gate tuple
+        The left circuit of a gate rule expression.
+    right : Gate tuple
+        The right circuit of a gate rule expression.
+
+    Examples
+    ========
+
+    Generate a new gate rule using a RL operation:
+
+    >>> from sympy.physics.quantum.identitysearch import rl_op
+    >>> from sympy.physics.quantum.gate import X, Y, Z
+    >>> x = X(0); y = Y(0); z = Z(0)
+    >>> rl_op((x,), (y, z))
+    ((Y(0), X(0)), (Z(0),))
+
+    >>> rl_op((x, y), (z,))
+    ((Z(0), X(0), Y(0)), ())
+    """
+
+    if (len(right) > 0):
+        rl_gate = right[0]
+        rl_gate_is_unitary = is_scalar_matrix(
+            (Dagger(rl_gate), rl_gate), _get_min_qubits(rl_gate), True)
+
+    if (len(right) > 0 and rl_gate_is_unitary):
+        # Get the new right side w/o the leftmost gate
+        new_right = right[1:len(right)]
+        # Add the leftmost gate to the left position on the left side
+        new_left = (Dagger(rl_gate),) + left
+        # Return the new gate rule
+        return (new_left, new_right)
+
+    return None
+
+
+def rr_op(left, right):
+    """Perform a RR operation.
+
+    A RR operation multiplies both left and right circuits
+    with the dagger of the right circuit's rightmost gate, and
+    the dagger is multiplied on the right side of both circuits.
+
+    If a RR is possible, it returns the new gate rule as a
+    2-tuple (LHS, RHS), where LHS is the left circuit and
+    and RHS is the right circuit of the new rule.
+    If a RR is not possible, None is returned.
+
+    Parameters
+    ==========
+
+    left : Gate tuple
+        The left circuit of a gate rule expression.
+    right : Gate tuple
+        The right circuit of a gate rule expression.
+
+    Examples
+    ========
+
+    Generate a new gate rule using a RR operation:
+
+    >>> from sympy.physics.quantum.identitysearch import rr_op
+    >>> from sympy.physics.quantum.gate import X, Y, Z
+    >>> x = X(0); y = Y(0); z = Z(0)
+    >>> rr_op((x, y), (z,))
+    ((X(0), Y(0), Z(0)), ())
+
+    >>> rr_op((x,), (y, z))
+    ((X(0), Z(0)), (Y(0),))
+    """
+
+    if (len(right) > 0):
+        rr_gate = right[len(right) - 1]
+        rr_gate_is_unitary = is_scalar_matrix(
+            (Dagger(rr_gate), rr_gate), _get_min_qubits(rr_gate), True)
+
+    if (len(right) > 0 and rr_gate_is_unitary):
+        # Get the new right side w/o the rightmost gate
+        new_right = right[0:len(right) - 1]
+        # Add the rightmost gate to the right position on the right side
+        new_left = left + (Dagger(rr_gate),)
+        # Return the new gate rule
+        return (new_left, new_right)
+
+    return None
+
+
+def generate_gate_rules(gate_seq, return_as_muls=False):
+    """Returns a set of gate rules.  Each gate rules is represented
+    as a 2-tuple of tuples or Muls.  An empty tuple represents an arbitrary
+    scalar value.
+
+    This function uses the four operations (LL, LR, RL, RR)
+    to generate the gate rules.
+
+    A gate rule is an expression such as ABC = D or AB = CD, where
+    A, B, C, and D are gates.  Each value on either side of the
+    equal sign represents a circuit.  The four operations allow
+    one to find a set of equivalent circuits from a gate identity.
+    The letters denoting the operation tell the user what
+    activities to perform on each expression.  The first letter
+    indicates which side of the equal sign to focus on.  The
+    second letter indicates which gate to focus on given the
+    side.  Once this information is determined, the inverse
+    of the gate is multiplied on both circuits to create a new
+    gate rule.
+
+    For example, given the identity, ABCD = 1, a LL operation
+    means look at the left value and multiply both left sides by the
+    inverse of the leftmost gate A.  If A is Hermitian, the inverse
+    of A is still A.  The resulting new rule is BCD = A.
+
+    The following is a summary of the four operations.  Assume
+    that in the examples, all gates are Hermitian.
+
+        LL : left circuit, left multiply
+             ABCD = E -> AABCD = AE -> BCD = AE
+        LR : left circuit, right multiply
+             ABCD = E -> ABCDD = ED -> ABC = ED
+        RL : right circuit, left multiply
+             ABC = ED -> EABC = EED -> EABC = D
+        RR : right circuit, right multiply
+             AB = CD -> ABD = CDD -> ABD = C
+
+    The number of gate rules generated is n*(n+1), where n
+    is the number of gates in the sequence (unproven).
+
+    Parameters
+    ==========
+
+    gate_seq : Gate tuple, Mul, or Number
+        A variable length tuple or Mul of Gates whose product is equal to
+        a scalar matrix
+    return_as_muls : bool
+        True to return a set of Muls; False to return a set of tuples
+
+    Examples
+    ========
+
+    Find the gate rules of the current circuit using tuples:
+
+    >>> from sympy.physics.quantum.identitysearch import generate_gate_rules
+    >>> from sympy.physics.quantum.gate import X, Y, Z
+    >>> x = X(0); y = Y(0); z = Z(0)
+    >>> generate_gate_rules((x, x))
+    {((X(0),), (X(0),)), ((X(0), X(0)), ())}
+
+    >>> generate_gate_rules((x, y, z))
+    {((), (X(0), Z(0), Y(0))), ((), (Y(0), X(0), Z(0))),
+     ((), (Z(0), Y(0), X(0))), ((X(0),), (Z(0), Y(0))),
+     ((Y(0),), (X(0), Z(0))), ((Z(0),), (Y(0), X(0))),
+     ((X(0), Y(0)), (Z(0),)), ((Y(0), Z(0)), (X(0),)),
+     ((Z(0), X(0)), (Y(0),)), ((X(0), Y(0), Z(0)), ()),
+     ((Y(0), Z(0), X(0)), ()), ((Z(0), X(0), Y(0)), ())}
+
+    Find the gate rules of the current circuit using Muls:
+
+    >>> generate_gate_rules(x*x, return_as_muls=True)
+    {(1, 1)}
+
+    >>> generate_gate_rules(x*y*z, return_as_muls=True)
+    {(1, X(0)*Z(0)*Y(0)), (1, Y(0)*X(0)*Z(0)),
+     (1, Z(0)*Y(0)*X(0)), (X(0)*Y(0), Z(0)),
+     (Y(0)*Z(0), X(0)), (Z(0)*X(0), Y(0)),
+     (X(0)*Y(0)*Z(0), 1), (Y(0)*Z(0)*X(0), 1),
+     (Z(0)*X(0)*Y(0), 1), (X(0), Z(0)*Y(0)),
+     (Y(0), X(0)*Z(0)), (Z(0), Y(0)*X(0))}
+    """
+
+    if isinstance(gate_seq, Number):
+        if return_as_muls:
+            return {(S.One, S.One)}
+        else:
+            return {((), ())}
+
+    elif isinstance(gate_seq, Mul):
+        gate_seq = gate_seq.args
+
+    # Each item in queue is a 3-tuple:
+    #     i)   first item is the left side of an equality
+    #    ii)   second item is the right side of an equality
+    #   iii)   third item is the number of operations performed
+    # The argument, gate_seq, will start on the left side, and
+    # the right side will be empty, implying the presence of an
+    # identity.
+    queue = deque()
+    # A set of gate rules
+    rules = set()
+    # Maximum number of operations to perform
+    max_ops = len(gate_seq)
+
+    def process_new_rule(new_rule, ops):
+        if new_rule is not None:
+            new_left, new_right = new_rule
+
+            if new_rule not in rules and (new_right, new_left) not in rules:
+                rules.add(new_rule)
+            # If haven't reached the max limit on operations
+            if ops + 1 < max_ops:
+                queue.append(new_rule + (ops + 1,))
+
+    queue.append((gate_seq, (), 0))
+    rules.add((gate_seq, ()))
+
+    while len(queue) > 0:
+        left, right, ops = queue.popleft()
+
+        # Do a LL
+        new_rule = ll_op(left, right)
+        process_new_rule(new_rule, ops)
+        # Do a LR
+        new_rule = lr_op(left, right)
+        process_new_rule(new_rule, ops)
+        # Do a RL
+        new_rule = rl_op(left, right)
+        process_new_rule(new_rule, ops)
+        # Do a RR
+        new_rule = rr_op(left, right)
+        process_new_rule(new_rule, ops)
+
+    if return_as_muls:
+        # Convert each rule as tuples into a rule as muls
+        mul_rules = set()
+        for rule in rules:
+            left, right = rule
+            mul_rules.add((Mul(*left), Mul(*right)))
+
+        rules = mul_rules
+
+    return rules
+
+
+def generate_equivalent_ids(gate_seq, return_as_muls=False):
+    """Returns a set of equivalent gate identities.
+
+    A gate identity is a quantum circuit such that the product
+    of the gates in the circuit is equal to a scalar value.
+    For example, XYZ = i, where X, Y, Z are the Pauli gates and
+    i is the imaginary value, is considered a gate identity.
+
+    This function uses the four operations (LL, LR, RL, RR)
+    to generate the gate rules and, subsequently, to locate equivalent
+    gate identities.
+
+    Note that all equivalent identities are reachable in n operations
+    from the starting gate identity, where n is the number of gates
+    in the sequence.
+
+    The max number of gate identities is 2n, where n is the number
+    of gates in the sequence (unproven).
+
+    Parameters
+    ==========
+
+    gate_seq : Gate tuple, Mul, or Number
+        A variable length tuple or Mul of Gates whose product is equal to
+        a scalar matrix.
+    return_as_muls: bool
+        True to return as Muls; False to return as tuples
+
+    Examples
+    ========
+
+    Find equivalent gate identities from the current circuit with tuples:
+
+    >>> from sympy.physics.quantum.identitysearch import generate_equivalent_ids
+    >>> from sympy.physics.quantum.gate import X, Y, Z
+    >>> x = X(0); y = Y(0); z = Z(0)
+    >>> generate_equivalent_ids((x, x))
+    {(X(0), X(0))}
+
+    >>> generate_equivalent_ids((x, y, z))
+    {(X(0), Y(0), Z(0)), (X(0), Z(0), Y(0)), (Y(0), X(0), Z(0)),
+     (Y(0), Z(0), X(0)), (Z(0), X(0), Y(0)), (Z(0), Y(0), X(0))}
+
+    Find equivalent gate identities from the current circuit with Muls:
+
+    >>> generate_equivalent_ids(x*x, return_as_muls=True)
+    {1}
+
+    >>> generate_equivalent_ids(x*y*z, return_as_muls=True)
+    {X(0)*Y(0)*Z(0), X(0)*Z(0)*Y(0), Y(0)*X(0)*Z(0),
+     Y(0)*Z(0)*X(0), Z(0)*X(0)*Y(0), Z(0)*Y(0)*X(0)}
+    """
+
+    if isinstance(gate_seq, Number):
+        return {S.One}
+    elif isinstance(gate_seq, Mul):
+        gate_seq = gate_seq.args
+
+    # Filter through the gate rules and keep the rules
+    # with an empty tuple either on the left or right side
+
+    # A set of equivalent gate identities
+    eq_ids = set()
+
+    gate_rules = generate_gate_rules(gate_seq)
+    for rule in gate_rules:
+        l, r = rule
+        if l == ():
+            eq_ids.add(r)
+        elif r == ():
+            eq_ids.add(l)
+
+    if return_as_muls:
+        convert_to_mul = lambda id_seq: Mul(*id_seq)
+        eq_ids = set(map(convert_to_mul, eq_ids))
+
+    return eq_ids
+
+
+class GateIdentity(Basic):
+    """Wrapper class for circuits that reduce to a scalar value.
+
+    A gate identity is a quantum circuit such that the product
+    of the gates in the circuit is equal to a scalar value.
+    For example, XYZ = i, where X, Y, Z are the Pauli gates and
+    i is the imaginary value, is considered a gate identity.
+
+    Parameters
+    ==========
+
+    args : Gate tuple
+        A variable length tuple of Gates that form an identity.
+
+    Examples
+    ========
+
+    Create a GateIdentity and look at its attributes:
+
+    >>> from sympy.physics.quantum.identitysearch import GateIdentity
+    >>> from sympy.physics.quantum.gate import X, Y, Z
+    >>> x = X(0); y = Y(0); z = Z(0)
+    >>> an_identity = GateIdentity(x, y, z)
+    >>> an_identity.circuit
+    X(0)*Y(0)*Z(0)
+
+    >>> an_identity.equivalent_ids
+    {(X(0), Y(0), Z(0)), (X(0), Z(0), Y(0)), (Y(0), X(0), Z(0)),
+     (Y(0), Z(0), X(0)), (Z(0), X(0), Y(0)), (Z(0), Y(0), X(0))}
+    """
+
+    def __new__(cls, *args):
+        # args should be a tuple - a variable length argument list
+        obj = Basic.__new__(cls, *args)
+        obj._circuit = Mul(*args)
+        obj._rules = generate_gate_rules(args)
+        obj._eq_ids = generate_equivalent_ids(args)
+
+        return obj
+
+    @property
+    def circuit(self):
+        return self._circuit
+
+    @property
+    def gate_rules(self):
+        return self._rules
+
+    @property
+    def equivalent_ids(self):
+        return self._eq_ids
+
+    @property
+    def sequence(self):
+        return self.args
+
+    def __str__(self):
+        """Returns the string of gates in a tuple."""
+        return str(self.circuit)
+
+
+def is_degenerate(identity_set, gate_identity):
+    """Checks if a gate identity is a permutation of another identity.
+
+    Parameters
+    ==========
+
+    identity_set : set
+        A Python set with GateIdentity objects.
+    gate_identity : GateIdentity
+        The GateIdentity to check for existence in the set.
+
+    Examples
+    ========
+
+    Check if the identity is a permutation of another identity:
+
+    >>> from sympy.physics.quantum.identitysearch import (
+    ...     GateIdentity, is_degenerate)
+    >>> from sympy.physics.quantum.gate import X, Y, Z
+    >>> x = X(0); y = Y(0); z = Z(0)
+    >>> an_identity = GateIdentity(x, y, z)
+    >>> id_set = {an_identity}
+    >>> another_id = (y, z, x)
+    >>> is_degenerate(id_set, another_id)
+    True
+
+    >>> another_id = (x, x)
+    >>> is_degenerate(id_set, another_id)
+    False
+    """
+
+    # For now, just iteratively go through the set and check if the current
+    # gate_identity is a permutation of an identity in the set
+    for an_id in identity_set:
+        if (gate_identity in an_id.equivalent_ids):
+            return True
+    return False
+
+
+def is_reducible(circuit, nqubits, begin, end):
+    """Determines if a circuit is reducible by checking
+    if its subcircuits are scalar values.
+
+    Parameters
+    ==========
+
+    circuit : Gate tuple
+        A tuple of Gates representing a circuit.  The circuit to check
+        if a gate identity is contained in a subcircuit.
+    nqubits : int
+        The number of qubits the circuit operates on.
+    begin : int
+        The leftmost gate in the circuit to include in a subcircuit.
+    end : int
+        The rightmost gate in the circuit to include in a subcircuit.
+
+    Examples
+    ========
+
+    Check if the circuit can be reduced:
+
+    >>> from sympy.physics.quantum.identitysearch import is_reducible
+    >>> from sympy.physics.quantum.gate import X, Y, Z
+    >>> x = X(0); y = Y(0); z = Z(0)
+    >>> is_reducible((x, y, z), 1, 0, 3)
+    True
+
+    Check if an interval in the circuit can be reduced:
+
+    >>> is_reducible((x, y, z), 1, 1, 3)
+    False
+
+    >>> is_reducible((x, y, y), 1, 1, 3)
+    True
+    """
+
+    current_circuit = ()
+    # Start from the gate at "end" and go down to almost the gate at "begin"
+    for ndx in reversed(range(begin, end)):
+        next_gate = circuit[ndx]
+        current_circuit = (next_gate,) + current_circuit
+
+        # If a circuit as a matrix is equivalent to a scalar value
+        if (is_scalar_matrix(current_circuit, nqubits, False)):
+            return True
+
+    return False
+
+
+def bfs_identity_search(gate_list, nqubits, max_depth=None,
+       identity_only=False):
+    """Constructs a set of gate identities from the list of possible gates.
+
+    Performs a breadth first search over the space of gate identities.
+    This allows the finding of the shortest gate identities first.
+
+    Parameters
+    ==========
+
+    gate_list : list, Gate
+        A list of Gates from which to search for gate identities.
+    nqubits : int
+        The number of qubits the quantum circuit operates on.
+    max_depth : int
+        The longest quantum circuit to construct from gate_list.
+    identity_only : bool
+        True to search for gate identities that reduce to identity;
+        False to search for gate identities that reduce to a scalar.
+
+    Examples
+    ========
+
+    Find a list of gate identities:
+
+    >>> from sympy.physics.quantum.identitysearch import bfs_identity_search
+    >>> from sympy.physics.quantum.gate import X, Y, Z
+    >>> x = X(0); y = Y(0); z = Z(0)
+    >>> bfs_identity_search([x], 1, max_depth=2)
+    {GateIdentity(X(0), X(0))}
+
+    >>> bfs_identity_search([x, y, z], 1)
+    {GateIdentity(X(0), X(0)), GateIdentity(Y(0), Y(0)),
+     GateIdentity(Z(0), Z(0)), GateIdentity(X(0), Y(0), Z(0))}
+
+    Find a list of identities that only equal to 1:
+
+    >>> bfs_identity_search([x, y, z], 1, identity_only=True)
+    {GateIdentity(X(0), X(0)), GateIdentity(Y(0), Y(0)),
+     GateIdentity(Z(0), Z(0))}
+    """
+
+    if max_depth is None or max_depth <= 0:
+        max_depth = len(gate_list)
+
+    id_only = identity_only
+
+    # Start with an empty sequence (implicitly contains an IdentityGate)
+    queue = deque([()])
+
+    # Create an empty set of gate identities
+    ids = set()
+
+    # Begin searching for gate identities in given space.
+    while (len(queue) > 0):
+        current_circuit = queue.popleft()
+
+        for next_gate in gate_list:
+            new_circuit = current_circuit + (next_gate,)
+
+            # Determines if a (strict) subcircuit is a scalar matrix
+            circuit_reducible = is_reducible(new_circuit, nqubits,
+                                             1, len(new_circuit))
+
+            # In many cases when the matrix is a scalar value,
+            # the evaluated matrix will actually be an integer
+            if (is_scalar_matrix(new_circuit, nqubits, id_only) and
+                not is_degenerate(ids, new_circuit) and
+                    not circuit_reducible):
+                ids.add(GateIdentity(*new_circuit))
+
+            elif (len(new_circuit) < max_depth and
+                  not circuit_reducible):
+                queue.append(new_circuit)
+
+    return ids
+
+
+def random_identity_search(gate_list, numgates, nqubits):
+    """Randomly selects numgates from gate_list and checks if it is
+    a gate identity.
+
+    If the circuit is a gate identity, the circuit is returned;
+    Otherwise, None is returned.
+    """
+
+    gate_size = len(gate_list)
+    circuit = ()
+
+    for i in range(numgates):
+        next_gate = gate_list[randint(0, gate_size - 1)]
+        circuit = circuit + (next_gate,)
+
+    is_scalar = is_scalar_matrix(circuit, nqubits, False)
+
+    return circuit if is_scalar else None

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/innerproduct.py

@@ -0,0 +1,138 @@
+"""Symbolic inner product."""
+
+from sympy.core.expr import Expr
+from sympy.core.kind import NumberKind
+from sympy.functions.elementary.complexes import conjugate
+from sympy.printing.pretty.stringpict import prettyForm
+from sympy.physics.quantum.dagger import Dagger
+
+
+__all__ = [
+    'InnerProduct'
+]
+
+
+# InnerProduct is not an QExpr because it is really just a regular commutative
+# number. We have gone back and forth about this, but we gain a lot by having
+# it subclass Expr. The main challenges were getting Dagger to work
+# (we use _eval_conjugate) and represent (we can use atoms and subs). Having
+# it be an Expr, mean that there are no commutative QExpr subclasses,
+# which simplifies the design of everything.
+
+class InnerProduct(Expr):
+    """An unevaluated inner product between a Bra and a Ket [1].
+
+    Parameters
+    ==========
+
+    bra : BraBase or subclass
+        The bra on the left side of the inner product.
+    ket : KetBase or subclass
+        The ket on the right side of the inner product.
+
+    Examples
+    ========
+
+    Create an InnerProduct and check its properties:
+
+        >>> from sympy.physics.quantum import Bra, Ket
+        >>> b = Bra('b')
+        >>> k = Ket('k')
+        >>> ip = b*k
+        >>> ip
+        <b|k>
+        >>> ip.bra
+        <b|
+        >>> ip.ket
+        |k>
+
+    In quantum expressions, inner products will be automatically
+    identified and created::
+
+        >>> b*k
+        <b|k>
+
+    In more complex expressions, where there is ambiguity in whether inner or
+    outer products should be created, inner products have high priority::
+
+        >>> k*b*k*b
+        <b|k>*|k><b|
+
+    Notice how the inner product <b|k> moved to the left of the expression
+    because inner products are commutative complex numbers.
+
+    References
+    ==========
+
+    .. [1] https://en.wikipedia.org/wiki/Inner_product
+    """
+
+    kind = NumberKind
+
+    is_complex = True
+
+    def __new__(cls, bra, ket):
+        # Keep the import of BraBase and KetBase here to avoid problems
+        # with circular imports.
+        from sympy.physics.quantum.state import KetBase, BraBase
+        if not isinstance(ket, KetBase):
+            raise TypeError('KetBase subclass expected, got: %r' % ket)
+        if not isinstance(bra, BraBase):
+            raise TypeError('BraBase subclass expected, got: %r' % ket)
+        obj = Expr.__new__(cls, bra, ket)
+        return obj
+
+    @property
+    def bra(self):
+        return self.args[0]
+
+    @property
+    def ket(self):
+        return self.args[1]
+
+    def _eval_conjugate(self):
+        return InnerProduct(Dagger(self.ket), Dagger(self.bra))
+
+    def _sympyrepr(self, printer, *args):
+        return '%s(%s,%s)' % (self.__class__.__name__,
+            printer._print(self.bra, *args), printer._print(self.ket, *args))
+
+    def _sympystr(self, printer, *args):
+        sbra = printer._print(self.bra)
+        sket = printer._print(self.ket)
+        return '%s|%s' % (sbra[:-1], sket[1:])
+
+    def _pretty(self, printer, *args):
+        # Print state contents
+        bra = self.bra._print_contents_pretty(printer, *args)
+        ket = self.ket._print_contents_pretty(printer, *args)
+        # Print brackets
+        height = max(bra.height(), ket.height())
+        use_unicode = printer._use_unicode
+        lbracket, _ = self.bra._pretty_brackets(height, use_unicode)
+        cbracket, rbracket = self.ket._pretty_brackets(height, use_unicode)
+        # Build innerproduct
+        pform = prettyForm(*bra.left(lbracket))
+        pform = prettyForm(*pform.right(cbracket))
+        pform = prettyForm(*pform.right(ket))
+        pform = prettyForm(*pform.right(rbracket))
+        return pform
+
+    def _latex(self, printer, *args):
+        bra_label = self.bra._print_contents_latex(printer, *args)
+        ket = printer._print(self.ket, *args)
+        return r'\left\langle %s \right. %s' % (bra_label, ket)
+
+    def doit(self, **hints):
+        try:
+            r = self.ket._eval_innerproduct(self.bra, **hints)
+        except NotImplementedError:
+            try:
+                r = conjugate(
+                    self.bra.dual._eval_innerproduct(self.ket.dual, **hints)
+                )
+            except NotImplementedError:
+                r = None
+        if r is not None:
+            return r
+        return self

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/kind.py

@@ -0,0 +1,103 @@
+"""Kinds for Operators, Bras, and Kets.
+
+This module defines kinds for operators, bras, and kets. These are useful
+in various places in ``sympy.physics.quantum`` as you often want to know
+what the kind is of a compound expression. For example, if you multiply
+an operator, bra, or ket by a number, you get back another operator, bra,
+or ket - even though if you did an ``isinstance`` check you would find that
+you have a ``Mul`` instead. The kind system is meant to give you a quick
+way of determining how a compound expression behaves in terms of lower
+level kinds.
+
+The resolution calculation of kinds for compound expressions can be found
+either in container classes or in functions that are registered with
+kind dispatchers.
+"""
+
+from sympy.core.mul import Mul
+from sympy.core.kind import Kind, _NumberKind
+
+
+__all__ = [
+    '_KetKind',
+    'KetKind',
+    '_BraKind',
+    'BraKind',
+    '_OperatorKind',
+    'OperatorKind',
+]
+
+
+class _KetKind(Kind):
+    """A kind for quantum kets."""
+
+    def __new__(cls):
+        obj = super().__new__(cls)
+        return obj
+
+    def __repr__(self):
+        return "KetKind"
+
+# Create an instance as many situations need this.
+KetKind = _KetKind()
+
+
+class _BraKind(Kind):
+    """A kind for quantum bras."""
+
+    def __new__(cls):
+        obj = super().__new__(cls)
+        return obj
+
+    def __repr__(self):
+        return "BraKind"
+
+# Create an instance as many situations need this.
+BraKind = _BraKind()
+
+
+from sympy.core.kind import Kind
+
+class _OperatorKind(Kind):
+    """A kind for quantum operators."""
+
+    def __new__(cls):
+        obj = super().__new__(cls)
+        return obj
+
+    def __repr__(self):
+        return "OperatorKind"
+
+# Create an instance as many situations need this.
+OperatorKind = _OperatorKind()
+
+
+#-----------------------------------------------------------------------------
+# Kind resolution.
+#-----------------------------------------------------------------------------
+
+# Note: We can't currently add kind dispatchers for the following combinations
+#       as the Mul._kind_dispatcher is set to commutative and will also
+#       register the opposite order, which isn't correct for these pairs:
+#
+# 1. (_OperatorKind, _KetKind)
+# 2. (_BraKind, _OperatorKind)
+# 3. (_BraKind, _KetKind)
+
+
+@Mul._kind_dispatcher.register(_NumberKind, _KetKind)
+def _mul_number_ket_kind(lhs, rhs):
+    """Perform the kind calculation of NumberKind*KetKind -> KetKind."""
+    return KetKind
+
+
+@Mul._kind_dispatcher.register(_NumberKind, _BraKind)
+def _mul_number_bra_kind(lhs, rhs):
+    """Perform the kind calculation of NumberKind*BraKind -> BraKind."""
+    return BraKind
+
+
+@Mul._kind_dispatcher.register(_NumberKind, _OperatorKind)
+def _mul_operator_kind(lhs, rhs):
+    """Perform the kind calculation of NumberKind*OperatorKind -> OperatorKind."""
+    return OperatorKind

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/matrixcache.py

@@ -0,0 +1,103 @@
+"""A cache for storing small matrices in multiple formats."""
+
+from sympy.core.numbers import (I, Rational, pi)
+from sympy.core.power import Pow
+from sympy.functions.elementary.exponential import exp
+from sympy.matrices.dense import Matrix
+
+from sympy.physics.quantum.matrixutils import (
+    to_sympy, to_numpy, to_scipy_sparse
+)
+
+
+class MatrixCache:
+    """A cache for small matrices in different formats.
+
+    This class takes small matrices in the standard ``sympy.Matrix`` format,
+    and then converts these to both ``numpy.matrix`` and
+    ``scipy.sparse.csr_matrix`` matrices. These matrices are then stored for
+    future recovery.
+    """
+
+    def __init__(self, dtype='complex'):
+        self._cache = {}
+        self.dtype = dtype
+
+    def cache_matrix(self, name, m):
+        """Cache a matrix by its name.
+
+        Parameters
+        ----------
+        name : str
+            A descriptive name for the matrix, like "identity2".
+        m : list of lists
+            The raw matrix data as a SymPy Matrix.
+        """
+        try:
+            self._sympy_matrix(name, m)
+        except ImportError:
+            pass
+        try:
+            self._numpy_matrix(name, m)
+        except ImportError:
+            pass
+        try:
+            self._scipy_sparse_matrix(name, m)
+        except ImportError:
+            pass
+
+    def get_matrix(self, name, format):
+        """Get a cached matrix by name and format.
+
+        Parameters
+        ----------
+        name : str
+            A descriptive name for the matrix, like "identity2".
+        format : str
+            The format desired ('sympy', 'numpy', 'scipy.sparse')
+        """
+        m = self._cache.get((name, format))
+        if m is not None:
+            return m
+        raise NotImplementedError(
+            'Matrix with name %s and format %s is not available.' %
+            (name, format)
+        )
+
+    def _store_matrix(self, name, format, m):
+        self._cache[(name, format)] = m
+
+    def _sympy_matrix(self, name, m):
+        self._store_matrix(name, 'sympy', to_sympy(m))
+
+    def _numpy_matrix(self, name, m):
+        m = to_numpy(m, dtype=self.dtype)
+        self._store_matrix(name, 'numpy', m)
+
+    def _scipy_sparse_matrix(self, name, m):
+        # TODO: explore different sparse formats. But sparse.kron will use
+        # coo in most cases, so we use that here.
+        m = to_scipy_sparse(m, dtype=self.dtype)
+        self._store_matrix(name, 'scipy.sparse', m)
+
+
+sqrt2_inv = Pow(2, Rational(-1, 2), evaluate=False)
+
+# Save the common matrices that we will need
+matrix_cache = MatrixCache()
+matrix_cache.cache_matrix('eye2', Matrix([[1, 0], [0, 1]]))
+matrix_cache.cache_matrix('op11', Matrix([[0, 0], [0, 1]]))  # |1><1|
+matrix_cache.cache_matrix('op00', Matrix([[1, 0], [0, 0]]))  # |0><0|
+matrix_cache.cache_matrix('op10', Matrix([[0, 0], [1, 0]]))  # |1><0|
+matrix_cache.cache_matrix('op01', Matrix([[0, 1], [0, 0]]))  # |0><1|
+matrix_cache.cache_matrix('X', Matrix([[0, 1], [1, 0]]))
+matrix_cache.cache_matrix('Y', Matrix([[0, -I], [I, 0]]))
+matrix_cache.cache_matrix('Z', Matrix([[1, 0], [0, -1]]))
+matrix_cache.cache_matrix('S', Matrix([[1, 0], [0, I]]))
+matrix_cache.cache_matrix('T', Matrix([[1, 0], [0, exp(I*pi/4)]]))
+matrix_cache.cache_matrix('H', sqrt2_inv*Matrix([[1, 1], [1, -1]]))
+matrix_cache.cache_matrix('Hsqrt2', Matrix([[1, 1], [1, -1]]))
+matrix_cache.cache_matrix(
+    'SWAP', Matrix([[1, 0, 0, 0], [0, 0, 1, 0], [0, 1, 0, 0], [0, 0, 0, 1]]))
+matrix_cache.cache_matrix('ZX', sqrt2_inv*Matrix([[1, 1], [1, -1]]))
+matrix_cache.cache_matrix('ZY', Matrix([[I, 0], [0, -I]]))

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/matrixutils.py

@@ -0,0 +1,272 @@
+"""Utilities to deal with sympy.Matrix, numpy and scipy.sparse."""
+
+from sympy.core.expr import Expr
+from sympy.core.numbers import I
+from sympy.core.singleton import S
+from sympy.matrices.matrixbase import MatrixBase
+from sympy.matrices import eye, zeros
+from sympy.external import import_module
+
+__all__ = [
+    'numpy_ndarray',
+    'scipy_sparse_matrix',
+    'sympy_to_numpy',
+    'sympy_to_scipy_sparse',
+    'numpy_to_sympy',
+    'scipy_sparse_to_sympy',
+    'flatten_scalar',
+    'matrix_dagger',
+    'to_sympy',
+    'to_numpy',
+    'to_scipy_sparse',
+    'matrix_tensor_product',
+    'matrix_zeros'
+]
+
+# Conditionally define the base classes for numpy and scipy.sparse arrays
+# for use in isinstance tests.
+
+np = import_module('numpy')
+if not np:
+    class numpy_ndarray:
+        pass
+else:
+    numpy_ndarray = np.ndarray  # type: ignore
+
+scipy = import_module('scipy', import_kwargs={'fromlist': ['sparse']})
+if not scipy:
+    class scipy_sparse_matrix:
+        pass
+    sparse = None
+else:
+    sparse = scipy.sparse
+    scipy_sparse_matrix = sparse.spmatrix # type: ignore
+
+
+def sympy_to_numpy(m, **options):
+    """Convert a SymPy Matrix/complex number to a numpy matrix or scalar."""
+    if not np:
+        raise ImportError
+    dtype = options.get('dtype', 'complex')
+    if isinstance(m, MatrixBase):
+        return np.array(m.tolist(), dtype=dtype)
+    elif isinstance(m, Expr):
+        if m.is_Number or m.is_NumberSymbol or m == I:
+            return complex(m)
+    raise TypeError('Expected MatrixBase or complex scalar, got: %r' % m)
+
+
+def sympy_to_scipy_sparse(m, **options):
+    """Convert a SymPy Matrix/complex number to a numpy matrix or scalar."""
+    if not np or not sparse:
+        raise ImportError
+    dtype = options.get('dtype', 'complex')
+    if isinstance(m, MatrixBase):
+        return sparse.csr_matrix(np.array(m.tolist(), dtype=dtype))
+    elif isinstance(m, Expr):
+        if m.is_Number or m.is_NumberSymbol or m == I:
+            return complex(m)
+    raise TypeError('Expected MatrixBase or complex scalar, got: %r' % m)
+
+
+def scipy_sparse_to_sympy(m, **options):
+    """Convert a scipy.sparse matrix to a SymPy matrix."""
+    return MatrixBase(m.todense())
+
+
+def numpy_to_sympy(m, **options):
+    """Convert a numpy matrix to a SymPy matrix."""
+    return MatrixBase(m)
+
+
+def to_sympy(m, **options):
+    """Convert a numpy/scipy.sparse matrix to a SymPy matrix."""
+    if isinstance(m, MatrixBase):
+        return m
+    elif isinstance(m, numpy_ndarray):
+        return numpy_to_sympy(m)
+    elif isinstance(m, scipy_sparse_matrix):
+        return scipy_sparse_to_sympy(m)
+    elif isinstance(m, Expr):
+        return m
+    raise TypeError('Expected sympy/numpy/scipy.sparse matrix, got: %r' % m)
+
+
+def to_numpy(m, **options):
+    """Convert a sympy/scipy.sparse matrix to a numpy matrix."""
+    dtype = options.get('dtype', 'complex')
+    if isinstance(m, (MatrixBase, Expr)):
+        return sympy_to_numpy(m, dtype=dtype)
+    elif isinstance(m, numpy_ndarray):
+        return m
+    elif isinstance(m, scipy_sparse_matrix):
+        return m.todense()
+    raise TypeError('Expected sympy/numpy/scipy.sparse matrix, got: %r' % m)
+
+
+def to_scipy_sparse(m, **options):
+    """Convert a sympy/numpy matrix to a scipy.sparse matrix."""
+    dtype = options.get('dtype', 'complex')
+    if isinstance(m, (MatrixBase, Expr)):
+        return sympy_to_scipy_sparse(m, dtype=dtype)
+    elif isinstance(m, numpy_ndarray):
+        if not sparse:
+            raise ImportError
+        return sparse.csr_matrix(m)
+    elif isinstance(m, scipy_sparse_matrix):
+        return m
+    raise TypeError('Expected sympy/numpy/scipy.sparse matrix, got: %r' % m)
+
+
+def flatten_scalar(e):
+    """Flatten a 1x1 matrix to a scalar, return larger matrices unchanged."""
+    if isinstance(e, MatrixBase):
+        if e.shape == (1, 1):
+            e = e[0]
+    if isinstance(e, (numpy_ndarray, scipy_sparse_matrix)):
+        if e.shape == (1, 1):
+            e = complex(e[0, 0])
+    return e
+
+
+def matrix_dagger(e):
+    """Return the dagger of a sympy/numpy/scipy.sparse matrix."""
+    if isinstance(e, MatrixBase):
+        return e.H
+    elif isinstance(e, (numpy_ndarray, scipy_sparse_matrix)):
+        return e.conjugate().transpose()
+    raise TypeError('Expected sympy/numpy/scipy.sparse matrix, got: %r' % e)
+
+
+# TODO: Move this into sympy.matrices.
+def _sympy_tensor_product(*matrices):
+    """Compute the kronecker product of a sequence of SymPy Matrices.
+    """
+    from sympy.matrices.expressions.kronecker import matrix_kronecker_product
+
+    return matrix_kronecker_product(*matrices)
+
+
+def _numpy_tensor_product(*product):
+    """numpy version of tensor product of multiple arguments."""
+    if not np:
+        raise ImportError
+    answer = product[0]
+    for item in product[1:]:
+        answer = np.kron(answer, item)
+    return answer
+
+
+def _scipy_sparse_tensor_product(*product):
+    """scipy.sparse version of tensor product of multiple arguments."""
+    if not sparse:
+        raise ImportError
+    answer = product[0]
+    for item in product[1:]:
+        answer = sparse.kron(answer, item)
+    # The final matrices will just be multiplied, so csr is a good final
+    # sparse format.
+    return sparse.csr_matrix(answer)
+
+
+def matrix_tensor_product(*product):
+    """Compute the matrix tensor product of sympy/numpy/scipy.sparse matrices."""
+    if isinstance(product[0], MatrixBase):
+        return _sympy_tensor_product(*product)
+    elif isinstance(product[0], numpy_ndarray):
+        return _numpy_tensor_product(*product)
+    elif isinstance(product[0], scipy_sparse_matrix):
+        return _scipy_sparse_tensor_product(*product)
+
+
+def _numpy_eye(n):
+    """numpy version of complex eye."""
+    if not np:
+        raise ImportError
+    return np.array(np.eye(n, dtype='complex'))
+
+
+def _scipy_sparse_eye(n):
+    """scipy.sparse version of complex eye."""
+    if not sparse:
+        raise ImportError
+    return sparse.eye(n, n, dtype='complex')
+
+
+def matrix_eye(n, **options):
+    """Get the version of eye and tensor_product for a given format."""
+    format = options.get('format', 'sympy')
+    if format == 'sympy':
+        return eye(n)
+    elif format == 'numpy':
+        return _numpy_eye(n)
+    elif format == 'scipy.sparse':
+        return _scipy_sparse_eye(n)
+    raise NotImplementedError('Invalid format: %r' % format)
+
+
+def _numpy_zeros(m, n, **options):
+    """numpy version of zeros."""
+    dtype = options.get('dtype', 'float64')
+    if not np:
+        raise ImportError
+    return np.zeros((m, n), dtype=dtype)
+
+
+def _scipy_sparse_zeros(m, n, **options):
+    """scipy.sparse version of zeros."""
+    spmatrix = options.get('spmatrix', 'csr')
+    dtype = options.get('dtype', 'float64')
+    if not sparse:
+        raise ImportError
+    if spmatrix == 'lil':
+        return sparse.lil_matrix((m, n), dtype=dtype)
+    elif spmatrix == 'csr':
+        return sparse.csr_matrix((m, n), dtype=dtype)
+
+
+def matrix_zeros(m, n, **options):
+    """"Get a zeros matrix for a given format."""
+    format = options.get('format', 'sympy')
+    if format == 'sympy':
+        return zeros(m, n)
+    elif format == 'numpy':
+        return _numpy_zeros(m, n, **options)
+    elif format == 'scipy.sparse':
+        return _scipy_sparse_zeros(m, n, **options)
+    raise NotImplementedError('Invaild format: %r' % format)
+
+
+def _numpy_matrix_to_zero(e):
+    """Convert a numpy zero matrix to the zero scalar."""
+    if not np:
+        raise ImportError
+    test = np.zeros_like(e)
+    if np.allclose(e, test):
+        return 0.0
+    else:
+        return e
+
+
+def _scipy_sparse_matrix_to_zero(e):
+    """Convert a scipy.sparse zero matrix to the zero scalar."""
+    if not np:
+        raise ImportError
+    edense = e.todense()
+    test = np.zeros_like(edense)
+    if np.allclose(edense, test):
+        return 0.0
+    else:
+        return e
+
+
+def matrix_to_zero(e):
+    """Convert a zero matrix to the scalar zero."""
+    if isinstance(e, MatrixBase):
+        if zeros(*e.shape) == e:
+            e = S.Zero
+    elif isinstance(e, numpy_ndarray):
+        e = _numpy_matrix_to_zero(e)
+    elif isinstance(e, scipy_sparse_matrix):
+        e = _scipy_sparse_matrix_to_zero(e)
+    return e

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/operator.py

@@ -0,0 +1,653 @@
+"""Quantum mechanical operators.
+
+TODO:
+
+* Fix early 0 in apply_operators.
+* Debug and test apply_operators.
+* Get cse working with classes in this file.
+* Doctests and documentation of special methods for InnerProduct, Commutator,
+  AntiCommutator, represent, apply_operators.
+"""
+from typing import Optional
+
+from sympy.core.add import Add
+from sympy.core.expr import Expr
+from sympy.core.function import (Derivative, expand)
+from sympy.core.mul import Mul
+from sympy.core.numbers import oo
+from sympy.core.singleton import S
+from sympy.printing.pretty.stringpict import prettyForm
+from sympy.physics.quantum.dagger import Dagger
+from sympy.physics.quantum.kind import OperatorKind
+from sympy.physics.quantum.qexpr import QExpr, dispatch_method
+from sympy.matrices import eye
+from sympy.utilities.exceptions import sympy_deprecation_warning
+
+
+
+__all__ = [
+    'Operator',
+    'HermitianOperator',
+    'UnitaryOperator',
+    'IdentityOperator',
+    'OuterProduct',
+    'DifferentialOperator'
+]
+
+#-----------------------------------------------------------------------------
+# Operators and outer products
+#-----------------------------------------------------------------------------
+
+
+class Operator(QExpr):
+    """Base class for non-commuting quantum operators.
+
+    An operator maps between quantum states [1]_. In quantum mechanics,
+    observables (including, but not limited to, measured physical values) are
+    represented as Hermitian operators [2]_.
+
+    Parameters
+    ==========
+
+    args : tuple
+        The list of numbers or parameters that uniquely specify the
+        operator. For time-dependent operators, this will include the time.
+
+    Examples
+    ========
+
+    Create an operator and examine its attributes::
+
+        >>> from sympy.physics.quantum import Operator
+        >>> from sympy import I
+        >>> A = Operator('A')
+        >>> A
+        A
+        >>> A.hilbert_space
+        H
+        >>> A.label
+        (A,)
+        >>> A.is_commutative
+        False
+
+    Create another operator and do some arithmetic operations::
+
+        >>> B = Operator('B')
+        >>> C = 2*A*A + I*B
+        >>> C
+        2*A**2 + I*B
+
+    Operators do not commute::
+
+        >>> A.is_commutative
+        False
+        >>> B.is_commutative
+        False
+        >>> A*B == B*A
+        False
+
+    Polymonials of operators respect the commutation properties::
+
+        >>> e = (A+B)**3
+        >>> e.expand()
+        A*B*A + A*B**2 + A**2*B + A**3 + B*A*B + B*A**2 + B**2*A + B**3
+
+    Operator inverses are handle symbolically::
+
+        >>> A.inv()
+        A**(-1)
+        >>> A*A.inv()
+        1
+
+    References
+    ==========
+
+    .. [1] https://en.wikipedia.org/wiki/Operator_%28physics%29
+    .. [2] https://en.wikipedia.org/wiki/Observable
+    """
+    is_hermitian: Optional[bool] = None
+    is_unitary: Optional[bool] = None
+    @classmethod
+    def default_args(self):
+        return ("O",)
+
+    kind = OperatorKind
+
+    #-------------------------------------------------------------------------
+    # Printing
+    #-------------------------------------------------------------------------
+
+    _label_separator = ','
+
+    def _print_operator_name(self, printer, *args):
+        return self.__class__.__name__
+
+    _print_operator_name_latex = _print_operator_name
+
+    def _print_operator_name_pretty(self, printer, *args):
+        return prettyForm(self.__class__.__name__)
+
+    def _print_contents(self, printer, *args):
+        if len(self.label) == 1:
+            return self._print_label(printer, *args)
+        else:
+            return '%s(%s)' % (
+                self._print_operator_name(printer, *args),
+                self._print_label(printer, *args)
+            )
+
+    def _print_contents_pretty(self, printer, *args):
+        if len(self.label) == 1:
+            return self._print_label_pretty(printer, *args)
+        else:
+            pform = self._print_operator_name_pretty(printer, *args)
+            label_pform = self._print_label_pretty(printer, *args)
+            label_pform = prettyForm(
+                *label_pform.parens(left='(', right=')')
+            )
+            pform = prettyForm(*pform.right(label_pform))
+            return pform
+
+    def _print_contents_latex(self, printer, *args):
+        if len(self.label) == 1:
+            return self._print_label_latex(printer, *args)
+        else:
+            return r'%s\left(%s\right)' % (
+                self._print_operator_name_latex(printer, *args),
+                self._print_label_latex(printer, *args)
+            )
+
+    #-------------------------------------------------------------------------
+    # _eval_* methods
+    #-------------------------------------------------------------------------
+
+    def _eval_commutator(self, other, **options):
+        """Evaluate [self, other] if known, return None if not known."""
+        return dispatch_method(self, '_eval_commutator', other, **options)
+
+    def _eval_anticommutator(self, other, **options):
+        """Evaluate [self, other] if known."""
+        return dispatch_method(self, '_eval_anticommutator', other, **options)
+
+    #-------------------------------------------------------------------------
+    # Operator application
+    #-------------------------------------------------------------------------
+
+    def _apply_operator(self, ket, **options):
+        return dispatch_method(self, '_apply_operator', ket, **options)
+
+    def _apply_from_right_to(self, bra, **options):
+        return None
+
+    def matrix_element(self, *args):
+        raise NotImplementedError('matrix_elements is not defined')
+
+    def inverse(self):
+        return self._eval_inverse()
+
+    inv = inverse
+
+    def _eval_inverse(self):
+        return self**(-1)
+
+
+class HermitianOperator(Operator):
+    """A Hermitian operator that satisfies H == Dagger(H).
+
+    Parameters
+    ==========
+
+    args : tuple
+        The list of numbers or parameters that uniquely specify the
+        operator. For time-dependent operators, this will include the time.
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum import Dagger, HermitianOperator
+    >>> H = HermitianOperator('H')
+    >>> Dagger(H)
+    H
+    """
+
+    is_hermitian = True
+
+    def _eval_inverse(self):
+        if isinstance(self, UnitaryOperator):
+            return self
+        else:
+            return Operator._eval_inverse(self)
+
+    def _eval_power(self, exp):
+        if isinstance(self, UnitaryOperator):
+            # so all eigenvalues of self are 1 or -1
+            if exp.is_even:
+                from sympy.core.singleton import S
+                return S.One # is identity, see Issue 24153.
+            elif exp.is_odd:
+                return self
+        # No simplification in all other cases
+        return Operator._eval_power(self, exp)
+
+
+class UnitaryOperator(Operator):
+    """A unitary operator that satisfies U*Dagger(U) == 1.
+
+    Parameters
+    ==========
+
+    args : tuple
+        The list of numbers or parameters that uniquely specify the
+        operator. For time-dependent operators, this will include the time.
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum import Dagger, UnitaryOperator
+    >>> U = UnitaryOperator('U')
+    >>> U*Dagger(U)
+    1
+    """
+    is_unitary = True
+    def _eval_adjoint(self):
+        return self._eval_inverse()
+
+
+class IdentityOperator(Operator):
+    """An identity operator I that satisfies op * I == I * op == op for any
+    operator op.
+
+    .. deprecated:: 1.14.
+        Use the scalar S.One instead as the multiplicative identity for
+        operators and states.
+
+    Parameters
+    ==========
+
+    N : Integer
+        Optional parameter that specifies the dimension of the Hilbert space
+        of operator. This is used when generating a matrix representation.
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum import IdentityOperator
+    >>> IdentityOperator() # doctest: +SKIP
+    I
+    """
+    is_hermitian = True
+    is_unitary = True
+    @property
+    def dimension(self):
+        return self.N
+
+    @classmethod
+    def default_args(self):
+        return (oo,)
+
+    def __init__(self, *args, **hints):
+        sympy_deprecation_warning(
+            """
+            IdentityOperator has been deprecated. In the future, please use
+            S.One as the identity for quantum operators and states.
+            """,
+            deprecated_since_version="1.14",
+            active_deprecations_target='deprecated-operator-identity',
+        )
+        if not len(args) in (0, 1):
+            raise ValueError('0 or 1 parameters expected, got %s' % args)
+
+        self.N = args[0] if (len(args) == 1 and args[0]) else oo
+
+    def _eval_commutator(self, other, **hints):
+        return S.Zero
+
+    def _eval_anticommutator(self, other, **hints):
+        return 2 * other
+
+    def _eval_inverse(self):
+        return self
+
+    def _eval_adjoint(self):
+        return self
+
+    def _apply_operator(self, ket, **options):
+        return ket
+
+    def _apply_from_right_to(self, bra, **options):
+        return bra
+
+    def _eval_power(self, exp):
+        return self
+
+    def _print_contents(self, printer, *args):
+        return 'I'
+
+    def _print_contents_pretty(self, printer, *args):
+        return prettyForm('I')
+
+    def _print_contents_latex(self, printer, *args):
+        return r'{\mathcal{I}}'
+
+    def _represent_default_basis(self, **options):
+        if not self.N or self.N == oo:
+            raise NotImplementedError('Cannot represent infinite dimensional' +
+                                      ' identity operator as a matrix')
+
+        format = options.get('format', 'sympy')
+        if format != 'sympy':
+            raise NotImplementedError('Representation in format ' +
+                                      '%s not implemented.' % format)
+
+        return eye(self.N)
+
+
+class OuterProduct(Operator):
+    """An unevaluated outer product between a ket and bra.
+
+    This constructs an outer product between any subclass of ``KetBase`` and
+    ``BraBase`` as ``|a><b|``. An ``OuterProduct`` inherits from Operator as they act as
+    operators in quantum expressions.  For reference see [1]_.
+
+    Parameters
+    ==========
+
+    ket : KetBase
+        The ket on the left side of the outer product.
+    bar : BraBase
+        The bra on the right side of the outer product.
+
+    Examples
+    ========
+
+    Create a simple outer product by hand and take its dagger::
+
+        >>> from sympy.physics.quantum import Ket, Bra, OuterProduct, Dagger
+
+        >>> k = Ket('k')
+        >>> b = Bra('b')
+        >>> op = OuterProduct(k, b)
+        >>> op
+        |k><b|
+        >>> op.hilbert_space
+        H
+        >>> op.ket
+        |k>
+        >>> op.bra
+        <b|
+        >>> Dagger(op)
+        |b><k|
+
+    In quantum expressions, outer products will be automatically
+    identified and created::
+
+        >>> k*b
+        |k><b|
+
+    However, the creation of inner products always has higher priority than that of
+    outer products:
+
+        >>> b*k*b
+        <b|k>*<b|
+
+    References
+    ==========
+
+    .. [1] https://en.wikipedia.org/wiki/Outer_product
+    """
+    is_commutative = False
+
+    def __new__(cls, *args, **old_assumptions):
+        from sympy.physics.quantum.state import KetBase, BraBase
+
+        if len(args) != 2:
+            raise ValueError('2 parameters expected, got %d' % len(args))
+
+        ket_expr = expand(args[0])
+        bra_expr = expand(args[1])
+
+        if (isinstance(ket_expr, (KetBase, Mul)) and
+                isinstance(bra_expr, (BraBase, Mul))):
+            ket_c, kets = ket_expr.args_cnc()
+            bra_c, bras = bra_expr.args_cnc()
+
+            if len(kets) != 1 or not isinstance(kets[0], KetBase):
+                raise TypeError('KetBase subclass expected'
+                                ', got: %r' % Mul(*kets))
+
+            if len(bras) != 1 or not isinstance(bras[0], BraBase):
+                raise TypeError('BraBase subclass expected'
+                                ', got: %r' % Mul(*bras))
+
+            if not kets[0].dual_class() == bras[0].__class__:
+                raise TypeError(
+                    'ket and bra are not dual classes: %r, %r' %
+                    (kets[0].__class__, bras[0].__class__)
+                    )
+
+            # TODO: make sure the hilbert spaces of the bra and ket are
+            # compatible
+            obj = Expr.__new__(cls, *(kets[0], bras[0]), **old_assumptions)
+            obj.hilbert_space = kets[0].hilbert_space
+            return Mul(*(ket_c + bra_c)) * obj
+
+        op_terms = []
+        if isinstance(ket_expr, Add) and isinstance(bra_expr, Add):
+            for ket_term in ket_expr.args:
+                for bra_term in bra_expr.args:
+                    op_terms.append(OuterProduct(ket_term, bra_term,
+                                                 **old_assumptions))
+        elif isinstance(ket_expr, Add):
+            for ket_term in ket_expr.args:
+                op_terms.append(OuterProduct(ket_term, bra_expr,
+                                             **old_assumptions))
+        elif isinstance(bra_expr, Add):
+            for bra_term in bra_expr.args:
+                op_terms.append(OuterProduct(ket_expr, bra_term,
+                                             **old_assumptions))
+        else:
+            raise TypeError(
+                'Expected ket and bra expression, got: %r, %r' %
+                (ket_expr, bra_expr)
+                )
+
+        return Add(*op_terms)
+
+    @property
+    def ket(self):
+        """Return the ket on the left side of the outer product."""
+        return self.args[0]
+
+    @property
+    def bra(self):
+        """Return the bra on the right side of the outer product."""
+        return self.args[1]
+
+    def _eval_adjoint(self):
+        return OuterProduct(Dagger(self.bra), Dagger(self.ket))
+
+    def _sympystr(self, printer, *args):
+        return printer._print(self.ket) + printer._print(self.bra)
+
+    def _sympyrepr(self, printer, *args):
+        return '%s(%s,%s)' % (self.__class__.__name__,
+            printer._print(self.ket, *args), printer._print(self.bra, *args))
+
+    def _pretty(self, printer, *args):
+        pform = self.ket._pretty(printer, *args)
+        return prettyForm(*pform.right(self.bra._pretty(printer, *args)))
+
+    def _latex(self, printer, *args):
+        k = printer._print(self.ket, *args)
+        b = printer._print(self.bra, *args)
+        return k + b
+
+    def _represent(self, **options):
+        k = self.ket._represent(**options)
+        b = self.bra._represent(**options)
+        return k*b
+
+    def _eval_trace(self, **kwargs):
+        # TODO if operands are tensorproducts this may be will be handled
+        # differently.
+
+        return self.ket._eval_trace(self.bra, **kwargs)
+
+
+class DifferentialOperator(Operator):
+    """An operator for representing the differential operator, i.e. d/dx
+
+    It is initialized by passing two arguments. The first is an arbitrary
+    expression that involves a function, such as ``Derivative(f(x), x)``. The
+    second is the function (e.g. ``f(x)``) which we are to replace with the
+    ``Wavefunction`` that this ``DifferentialOperator`` is applied to.
+
+    Parameters
+    ==========
+
+    expr : Expr
+           The arbitrary expression which the appropriate Wavefunction is to be
+           substituted into
+
+    func : Expr
+           A function (e.g. f(x)) which is to be replaced with the appropriate
+           Wavefunction when this DifferentialOperator is applied
+
+    Examples
+    ========
+
+    You can define a completely arbitrary expression and specify where the
+    Wavefunction is to be substituted
+
+    >>> from sympy import Derivative, Function, Symbol
+    >>> from sympy.physics.quantum.operator import DifferentialOperator
+    >>> from sympy.physics.quantum.state import Wavefunction
+    >>> from sympy.physics.quantum.qapply import qapply
+    >>> f = Function('f')
+    >>> x = Symbol('x')
+    >>> d = DifferentialOperator(1/x*Derivative(f(x), x), f(x))
+    >>> w = Wavefunction(x**2, x)
+    >>> d.function
+    f(x)
+    >>> d.variables
+    (x,)
+    >>> qapply(d*w)
+    Wavefunction(2, x)
+
+    """
+
+    @property
+    def variables(self):
+        """
+        Returns the variables with which the function in the specified
+        arbitrary expression is evaluated
+
+        Examples
+        ========
+
+        >>> from sympy.physics.quantum.operator import DifferentialOperator
+        >>> from sympy import Symbol, Function, Derivative
+        >>> x = Symbol('x')
+        >>> f = Function('f')
+        >>> d = DifferentialOperator(1/x*Derivative(f(x), x), f(x))
+        >>> d.variables
+        (x,)
+        >>> y = Symbol('y')
+        >>> d = DifferentialOperator(Derivative(f(x, y), x) +
+        ...                          Derivative(f(x, y), y), f(x, y))
+        >>> d.variables
+        (x, y)
+        """
+
+        return self.args[-1].args
+
+    @property
+    def function(self):
+        """
+        Returns the function which is to be replaced with the Wavefunction
+
+        Examples
+        ========
+
+        >>> from sympy.physics.quantum.operator import DifferentialOperator
+        >>> from sympy import Function, Symbol, Derivative
+        >>> x = Symbol('x')
+        >>> f = Function('f')
+        >>> d = DifferentialOperator(Derivative(f(x), x), f(x))
+        >>> d.function
+        f(x)
+        >>> y = Symbol('y')
+        >>> d = DifferentialOperator(Derivative(f(x, y), x) +
+        ...                          Derivative(f(x, y), y), f(x, y))
+        >>> d.function
+        f(x, y)
+        """
+
+        return self.args[-1]
+
+    @property
+    def expr(self):
+        """
+        Returns the arbitrary expression which is to have the Wavefunction
+        substituted into it
+
+        Examples
+        ========
+
+        >>> from sympy.physics.quantum.operator import DifferentialOperator
+        >>> from sympy import Function, Symbol, Derivative
+        >>> x = Symbol('x')
+        >>> f = Function('f')
+        >>> d = DifferentialOperator(Derivative(f(x), x), f(x))
+        >>> d.expr
+        Derivative(f(x), x)
+        >>> y = Symbol('y')
+        >>> d = DifferentialOperator(Derivative(f(x, y), x) +
+        ...                          Derivative(f(x, y), y), f(x, y))
+        >>> d.expr
+        Derivative(f(x, y), x) + Derivative(f(x, y), y)
+        """
+
+        return self.args[0]
+
+    @property
+    def free_symbols(self):
+        """
+        Return the free symbols of the expression.
+        """
+
+        return self.expr.free_symbols
+
+    def _apply_operator_Wavefunction(self, func, **options):
+        from sympy.physics.quantum.state import Wavefunction
+        var = self.variables
+        wf_vars = func.args[1:]
+
+        f = self.function
+        new_expr = self.expr.subs(f, func(*var))
+        new_expr = new_expr.doit()
+
+        return Wavefunction(new_expr, *wf_vars)
+
+    def _eval_derivative(self, symbol):
+        new_expr = Derivative(self.expr, symbol)
+        return DifferentialOperator(new_expr, self.args[-1])
+
+    #-------------------------------------------------------------------------
+    # Printing
+    #-------------------------------------------------------------------------
+
+    def _print(self, printer, *args):
+        return '%s(%s)' % (
+            self._print_operator_name(printer, *args),
+            self._print_label(printer, *args)
+        )
+
+    def _print_pretty(self, printer, *args):
+        pform = self._print_operator_name_pretty(printer, *args)
+        label_pform = self._print_label_pretty(printer, *args)
+        label_pform = prettyForm(
+            *label_pform.parens(left='(', right=')')
+        )
+        pform = prettyForm(*pform.right(label_pform))
+        return pform

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/operatorordering.py

@@ -0,0 +1,290 @@
+"""Functions for reordering operator expressions."""
+
+import warnings
+
+from sympy.core.add import Add
+from sympy.core.mul import Mul
+from sympy.core.numbers import Integer
+from sympy.core.power import Pow
+from sympy.physics.quantum import Commutator, AntiCommutator
+from sympy.physics.quantum.boson import BosonOp
+from sympy.physics.quantum.fermion import FermionOp
+
+__all__ = [
+    'normal_order',
+    'normal_ordered_form'
+]
+
+
+def _expand_powers(factors):
+    """
+    Helper function for normal_ordered_form and normal_order: Expand a
+    power expression to a multiplication expression so that that the
+    expression can be handled by the normal ordering functions.
+    """
+
+    new_factors = []
+    for factor in factors.args:
+        if (isinstance(factor, Pow)
+                and isinstance(factor.args[1], Integer)
+                and factor.args[1] > 0):
+            for n in range(factor.args[1]):
+                new_factors.append(factor.args[0])
+        else:
+            new_factors.append(factor)
+
+    return new_factors
+
+def _normal_ordered_form_factor(product, independent=False, recursive_limit=10,
+                                _recursive_depth=0):
+    """
+    Helper function for normal_ordered_form_factor: Write multiplication
+    expression with bosonic or fermionic operators on normally ordered form,
+    using the bosonic and fermionic commutation relations. The resulting
+    operator expression is equivalent to the argument, but will in general be
+    a sum of operator products instead of a simple product.
+    """
+
+    factors = _expand_powers(product)
+
+    new_factors = []
+    n = 0
+    while n < len(factors) - 1:
+        current, next = factors[n], factors[n + 1]
+        if any(not isinstance(f, (FermionOp, BosonOp)) for f in (current, next)):
+            new_factors.append(current)
+            n += 1
+            continue
+
+        key_1 = (current.is_annihilation, str(current.name))
+        key_2 = (next.is_annihilation, str(next.name))
+
+        if key_1 <= key_2:
+            new_factors.append(current)
+            n += 1
+            continue
+
+        n += 2
+        if current.is_annihilation and not next.is_annihilation:
+            if isinstance(current, BosonOp) and isinstance(next, BosonOp):
+                if current.args[0] != next.args[0]:
+                    if independent:
+                        c = 0
+                    else:
+                        c = Commutator(current, next)
+                    new_factors.append(next * current + c)
+                else:
+                    new_factors.append(next * current + 1)
+            elif isinstance(current, FermionOp) and isinstance(next, FermionOp):
+                if current.args[0] != next.args[0]:
+                    if independent:
+                        c = 0
+                    else:
+                        c = AntiCommutator(current, next)
+                    new_factors.append(-next * current + c)
+                else:
+                    new_factors.append(-next * current + 1)
+        elif (current.is_annihilation == next.is_annihilation and
+            isinstance(current, FermionOp) and isinstance(next, FermionOp)):
+            new_factors.append(-next * current)
+        else:
+            new_factors.append(next * current)
+
+    if n == len(factors) - 1:
+        new_factors.append(factors[-1])
+
+    if new_factors == factors:
+        return product
+    else:
+        expr = Mul(*new_factors).expand()
+        return normal_ordered_form(expr,
+                                   recursive_limit=recursive_limit,
+                                   _recursive_depth=_recursive_depth + 1,
+                                   independent=independent)
+
+
+def _normal_ordered_form_terms(expr, independent=False, recursive_limit=10,
+                               _recursive_depth=0):
+    """
+    Helper function for normal_ordered_form: loop through each term in an
+    addition expression and call _normal_ordered_form_factor to perform the
+    factor to an normally ordered expression.
+    """
+
+    new_terms = []
+    for term in expr.args:
+        if isinstance(term, Mul):
+            new_term = _normal_ordered_form_factor(
+                term, recursive_limit=recursive_limit,
+                _recursive_depth=_recursive_depth, independent=independent)
+            new_terms.append(new_term)
+        else:
+            new_terms.append(term)
+
+    return Add(*new_terms)
+
+
+def normal_ordered_form(expr, independent=False, recursive_limit=10,
+                        _recursive_depth=0):
+    """Write an expression with bosonic or fermionic operators on normal
+    ordered form, where each term is normally ordered. Note that this
+    normal ordered form is equivalent to the original expression.
+
+    Parameters
+    ==========
+
+    expr : expression
+        The expression write on normal ordered form.
+    independent : bool (default False)
+        Whether to consider operator with different names as operating in
+        different Hilbert spaces. If False, the (anti-)commutation is left
+        explicit.
+    recursive_limit : int (default 10)
+        The number of allowed recursive applications of the function.
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum import Dagger
+    >>> from sympy.physics.quantum.boson import BosonOp
+    >>> from sympy.physics.quantum.operatorordering import normal_ordered_form
+    >>> a = BosonOp("a")
+    >>> normal_ordered_form(a * Dagger(a))
+    1 + Dagger(a)*a
+    """
+
+    if _recursive_depth > recursive_limit:
+        warnings.warn("Too many recursions, aborting")
+        return expr
+
+    if isinstance(expr, Add):
+        return _normal_ordered_form_terms(expr,
+                                          recursive_limit=recursive_limit,
+                                          _recursive_depth=_recursive_depth,
+                                          independent=independent)
+    elif isinstance(expr, Mul):
+        return _normal_ordered_form_factor(expr,
+                                           recursive_limit=recursive_limit,
+                                           _recursive_depth=_recursive_depth,
+                                           independent=independent)
+    else:
+        return expr
+
+
+def _normal_order_factor(product, recursive_limit=10, _recursive_depth=0):
+    """
+    Helper function for normal_order: Normal order a multiplication expression
+    with bosonic or fermionic operators. In general the resulting operator
+    expression will not be equivalent to original product.
+    """
+
+    factors = _expand_powers(product)
+
+    n = 0
+    new_factors = []
+    while n < len(factors) - 1:
+
+        if (isinstance(factors[n], BosonOp) and
+                factors[n].is_annihilation):
+            # boson
+            if not isinstance(factors[n + 1], BosonOp):
+                new_factors.append(factors[n])
+            else:
+                if factors[n + 1].is_annihilation:
+                    new_factors.append(factors[n])
+                else:
+                    if factors[n].args[0] != factors[n + 1].args[0]:
+                        new_factors.append(factors[n + 1] * factors[n])
+                    else:
+                        new_factors.append(factors[n + 1] * factors[n])
+                    n += 1
+
+        elif (isinstance(factors[n], FermionOp) and
+              factors[n].is_annihilation):
+            # fermion
+            if not isinstance(factors[n + 1], FermionOp):
+                new_factors.append(factors[n])
+            else:
+                if factors[n + 1].is_annihilation:
+                    new_factors.append(factors[n])
+                else:
+                    if factors[n].args[0] != factors[n + 1].args[0]:
+                        new_factors.append(-factors[n + 1] * factors[n])
+                    else:
+                        new_factors.append(-factors[n + 1] * factors[n])
+                    n += 1
+
+        else:
+            new_factors.append(factors[n])
+
+        n += 1
+
+    if n == len(factors) - 1:
+        new_factors.append(factors[-1])
+
+    if new_factors == factors:
+        return product
+    else:
+        expr = Mul(*new_factors).expand()
+        return normal_order(expr,
+                            recursive_limit=recursive_limit,
+                            _recursive_depth=_recursive_depth + 1)
+
+
+def _normal_order_terms(expr, recursive_limit=10, _recursive_depth=0):
+    """
+    Helper function for normal_order: look through each term in an addition
+    expression and call _normal_order_factor to perform the normal ordering
+    on the factors.
+    """
+
+    new_terms = []
+    for term in expr.args:
+        if isinstance(term, Mul):
+            new_term = _normal_order_factor(term,
+                                            recursive_limit=recursive_limit,
+                                            _recursive_depth=_recursive_depth)
+            new_terms.append(new_term)
+        else:
+            new_terms.append(term)
+
+    return Add(*new_terms)
+
+
+def normal_order(expr, recursive_limit=10, _recursive_depth=0):
+    """Normal order an expression with bosonic or fermionic operators. Note
+    that this normal order is not equivalent to the original expression, but
+    the creation and annihilation operators in each term in expr is reordered
+    so that the expression becomes normal ordered.
+
+    Parameters
+    ==========
+
+    expr : expression
+        The expression to normal order.
+
+    recursive_limit : int (default 10)
+        The number of allowed recursive applications of the function.
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum import Dagger
+    >>> from sympy.physics.quantum.boson import BosonOp
+    >>> from sympy.physics.quantum.operatorordering import normal_order
+    >>> a = BosonOp("a")
+    >>> normal_order(a * Dagger(a))
+    Dagger(a)*a
+    """
+    if _recursive_depth > recursive_limit:
+        warnings.warn("Too many recursions, aborting")
+        return expr
+
+    if isinstance(expr, Add):
+        return _normal_order_terms(expr, recursive_limit=recursive_limit,
+                                   _recursive_depth=_recursive_depth)
+    elif isinstance(expr, Mul):
+        return _normal_order_factor(expr, recursive_limit=recursive_limit,
+                                    _recursive_depth=_recursive_depth)
+    else:
+        return expr

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/operatorset.py

@@ -0,0 +1,279 @@
+""" A module for mapping operators to their corresponding eigenstates
+and vice versa
+
+It contains a global dictionary with eigenstate-operator pairings.
+If a new state-operator pair is created, this dictionary should be
+updated as well.
+
+It also contains functions operators_to_state and state_to_operators
+for mapping between the two. These can handle both classes and
+instances of operators and states. See the individual function
+descriptions for details.
+
+TODO List:
+- Update the dictionary with a complete list of state-operator pairs
+"""
+
+from sympy.physics.quantum.cartesian import (XOp, YOp, ZOp, XKet, PxOp, PxKet,
+                                             PositionKet3D)
+from sympy.physics.quantum.operator import Operator
+from sympy.physics.quantum.state import StateBase, BraBase, Ket
+from sympy.physics.quantum.spin import (JxOp, JyOp, JzOp, J2Op, JxKet, JyKet,
+                                        JzKet)
+
+__all__ = [
+    'operators_to_state',
+    'state_to_operators'
+]
+
+#state_mapping stores the mappings between states and their associated
+#operators or tuples of operators. This should be updated when new
+#classes are written! Entries are of the form PxKet : PxOp or
+#something like 3DKet : (ROp, ThetaOp, PhiOp)
+
+#frozenset is used so that the reverse mapping can be made
+#(regular sets are not hashable because they are mutable
+state_mapping = { JxKet: frozenset((J2Op, JxOp)),
+                  JyKet: frozenset((J2Op, JyOp)),
+                  JzKet: frozenset((J2Op, JzOp)),
+                  Ket: Operator,
+                  PositionKet3D: frozenset((XOp, YOp, ZOp)),
+                  PxKet: PxOp,
+                  XKet: XOp }
+
+op_mapping = {v: k for k, v in state_mapping.items()}
+
+
+def operators_to_state(operators, **options):
+    """ Returns the eigenstate of the given operator or set of operators
+
+    A global function for mapping operator classes to their associated
+    states. It takes either an Operator or a set of operators and
+    returns the state associated with these.
+
+    This function can handle both instances of a given operator or
+    just the class itself (i.e. both XOp() and XOp)
+
+    There are multiple use cases to consider:
+
+    1) A class or set of classes is passed: First, we try to
+    instantiate default instances for these operators. If this fails,
+    then the class is simply returned. If we succeed in instantiating
+    default instances, then we try to call state._operators_to_state
+    on the operator instances. If this fails, the class is returned.
+    Otherwise, the instance returned by _operators_to_state is returned.
+
+    2) An instance or set of instances is passed: In this case,
+    state._operators_to_state is called on the instances passed. If
+    this fails, a state class is returned. If the method returns an
+    instance, that instance is returned.
+
+    In both cases, if the operator class or set does not exist in the
+    state_mapping dictionary, None is returned.
+
+    Parameters
+    ==========
+
+    arg: Operator or set
+         The class or instance of the operator or set of operators
+         to be mapped to a state
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum.cartesian import XOp, PxOp
+    >>> from sympy.physics.quantum.operatorset import operators_to_state
+    >>> from sympy.physics.quantum.operator import Operator
+    >>> operators_to_state(XOp)
+    |x>
+    >>> operators_to_state(XOp())
+    |x>
+    >>> operators_to_state(PxOp)
+    |px>
+    >>> operators_to_state(PxOp())
+    |px>
+    >>> operators_to_state(Operator)
+    |psi>
+    >>> operators_to_state(Operator())
+    |psi>
+    """
+
+    if not (isinstance(operators, (Operator, set)) or issubclass(operators, Operator)):
+        raise NotImplementedError("Argument is not an Operator or a set!")
+
+    if isinstance(operators, set):
+        for s in operators:
+            if not (isinstance(s, Operator)
+                   or issubclass(s, Operator)):
+                raise NotImplementedError("Set is not all Operators!")
+
+        ops = frozenset(operators)
+
+        if ops in op_mapping:  # ops is a list of classes in this case
+            #Try to get an object from default instances of the
+            #operators...if this fails, return the class
+            try:
+                op_instances = [op() for op in ops]
+                ret = _get_state(op_mapping[ops], set(op_instances), **options)
+            except NotImplementedError:
+                ret = op_mapping[ops]
+
+            return ret
+        else:
+            tmp = [type(o) for o in ops]
+            classes = frozenset(tmp)
+
+            if classes in op_mapping:
+                ret = _get_state(op_mapping[classes], ops, **options)
+            else:
+                ret = None
+
+            return ret
+    else:
+        if operators in op_mapping:
+            try:
+                op_instance = operators()
+                ret = _get_state(op_mapping[operators], op_instance, **options)
+            except NotImplementedError:
+                ret = op_mapping[operators]
+
+            return ret
+        elif type(operators) in op_mapping:
+            return _get_state(op_mapping[type(operators)], operators, **options)
+        else:
+            return None
+
+
+def state_to_operators(state, **options):
+    """ Returns the operator or set of operators corresponding to the
+    given eigenstate
+
+    A global function for mapping state classes to their associated
+    operators or sets of operators. It takes either a state class
+    or instance.
+
+    This function can handle both instances of a given state or just
+    the class itself (i.e. both XKet() and XKet)
+
+    There are multiple use cases to consider:
+
+    1) A state class is passed: In this case, we first try
+    instantiating a default instance of the class. If this succeeds,
+    then we try to call state._state_to_operators on that instance.
+    If the creation of the default instance or if the calling of
+    _state_to_operators fails, then either an operator class or set of
+    operator classes is returned. Otherwise, the appropriate
+    operator instances are returned.
+
+    2) A state instance is returned: Here, state._state_to_operators
+    is called for the instance. If this fails, then a class or set of
+    operator classes is returned. Otherwise, the instances are returned.
+
+    In either case, if the state's class does not exist in
+    state_mapping, None is returned.
+
+    Parameters
+    ==========
+
+    arg: StateBase class or instance (or subclasses)
+         The class or instance of the state to be mapped to an
+         operator or set of operators
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum.cartesian import XKet, PxKet, XBra, PxBra
+    >>> from sympy.physics.quantum.operatorset import state_to_operators
+    >>> from sympy.physics.quantum.state import Ket, Bra
+    >>> state_to_operators(XKet)
+    X
+    >>> state_to_operators(XKet())
+    X
+    >>> state_to_operators(PxKet)
+    Px
+    >>> state_to_operators(PxKet())
+    Px
+    >>> state_to_operators(PxBra)
+    Px
+    >>> state_to_operators(XBra)
+    X
+    >>> state_to_operators(Ket)
+    O
+    >>> state_to_operators(Bra)
+    O
+    """
+
+    if not (isinstance(state, StateBase) or issubclass(state, StateBase)):
+        raise NotImplementedError("Argument is not a state!")
+
+    if state in state_mapping:  # state is a class
+        state_inst = _make_default(state)
+        try:
+            ret = _get_ops(state_inst,
+                           _make_set(state_mapping[state]), **options)
+        except (NotImplementedError, TypeError):
+            ret = state_mapping[state]
+    elif type(state) in state_mapping:
+        ret = _get_ops(state,
+                       _make_set(state_mapping[type(state)]), **options)
+    elif isinstance(state, BraBase) and state.dual_class() in state_mapping:
+        ret = _get_ops(state,
+                       _make_set(state_mapping[state.dual_class()]))
+    elif issubclass(state, BraBase) and state.dual_class() in state_mapping:
+        state_inst = _make_default(state)
+        try:
+            ret = _get_ops(state_inst,
+                           _make_set(state_mapping[state.dual_class()]))
+        except (NotImplementedError, TypeError):
+            ret = state_mapping[state.dual_class()]
+    else:
+        ret = None
+
+    return _make_set(ret)
+
+
+def _make_default(expr):
+    # XXX: Catching TypeError like this is a bad way of distinguishing between
+    # classes and instances. The logic using this function should be rewritten
+    # somehow.
+    try:
+        ret = expr()
+    except TypeError:
+        ret = expr
+
+    return ret
+
+
+def _get_state(state_class, ops, **options):
+    # Try to get a state instance from the operator INSTANCES.
+    # If this fails, get the class
+    try:
+        ret = state_class._operators_to_state(ops, **options)
+    except NotImplementedError:
+        ret = _make_default(state_class)
+
+    return ret
+
+
+def _get_ops(state_inst, op_classes, **options):
+    # Try to get operator instances from the state INSTANCE.
+    # If this fails, just return the classes
+    try:
+        ret = state_inst._state_to_operators(op_classes, **options)
+    except NotImplementedError:
+        if isinstance(op_classes, (set, tuple, frozenset)):
+            ret = tuple(_make_default(x) for x in op_classes)
+        else:
+            ret = _make_default(op_classes)
+
+    if isinstance(ret, set) and len(ret) == 1:
+        return ret[0]
+
+    return ret
+
+
+def _make_set(ops):
+    if isinstance(ops, (tuple, list, frozenset)):
+        return set(ops)
+    else:
+        return ops

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/pauli.py

@@ -0,0 +1,675 @@
+"""Pauli operators and states"""
+
+from sympy.core.add import Add
+from sympy.core.mul import Mul
+from sympy.core.numbers import I
+from sympy.core.power import Pow
+from sympy.core.singleton import S
+from sympy.functions.elementary.exponential import exp
+from sympy.physics.quantum import Operator, Ket, Bra
+from sympy.physics.quantum import ComplexSpace
+from sympy.matrices import Matrix
+from sympy.functions.special.tensor_functions import KroneckerDelta
+
+__all__ = [
+    'SigmaX', 'SigmaY', 'SigmaZ', 'SigmaMinus', 'SigmaPlus', 'SigmaZKet',
+    'SigmaZBra', 'qsimplify_pauli'
+]
+
+
+class SigmaOpBase(Operator):
+    """Pauli sigma operator, base class"""
+
+    @property
+    def name(self):
+        return self.args[0]
+
+    @property
+    def use_name(self):
+        return bool(self.args[0]) is not False
+
+    @classmethod
+    def default_args(self):
+        return (False,)
+
+    def __new__(cls, *args, **hints):
+        return Operator.__new__(cls, *args, **hints)
+
+    def _eval_commutator_BosonOp(self, other, **hints):
+        return S.Zero
+
+
+class SigmaX(SigmaOpBase):
+    """Pauli sigma x operator
+
+    Parameters
+    ==========
+
+    name : str
+        An optional string that labels the operator. Pauli operators with
+        different names commute.
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum import represent
+    >>> from sympy.physics.quantum.pauli import SigmaX
+    >>> sx = SigmaX()
+    >>> sx
+    SigmaX()
+    >>> represent(sx)
+    Matrix([
+    [0, 1],
+    [1, 0]])
+    """
+
+    def __new__(cls, *args, **hints):
+        return SigmaOpBase.__new__(cls, *args, **hints)
+
+    def _eval_commutator_SigmaY(self, other, **hints):
+        if self.name != other.name:
+            return S.Zero
+        else:
+            return 2 * I * SigmaZ(self.name)
+
+    def _eval_commutator_SigmaZ(self, other, **hints):
+        if self.name != other.name:
+            return S.Zero
+        else:
+            return - 2 * I * SigmaY(self.name)
+
+    def _eval_commutator_BosonOp(self, other, **hints):
+        return S.Zero
+
+    def _eval_anticommutator_SigmaY(self, other, **hints):
+        return S.Zero
+
+    def _eval_anticommutator_SigmaZ(self, other, **hints):
+        return S.Zero
+
+    def _eval_adjoint(self):
+        return self
+
+    def _print_contents_latex(self, printer, *args):
+        if self.use_name:
+            return r'{\sigma_x^{(%s)}}' % str(self.name)
+        else:
+            return r'{\sigma_x}'
+
+    def _print_contents(self, printer, *args):
+        return 'SigmaX()'
+
+    def _eval_power(self, e):
+        if e.is_Integer and e.is_positive:
+            return SigmaX(self.name).__pow__(int(e) % 2)
+
+    def _represent_default_basis(self, **options):
+        format = options.get('format', 'sympy')
+        if format == 'sympy':
+            return Matrix([[0, 1], [1, 0]])
+        else:
+            raise NotImplementedError('Representation in format ' +
+                                      format + ' not implemented.')
+
+
+class SigmaY(SigmaOpBase):
+    """Pauli sigma y operator
+
+    Parameters
+    ==========
+
+    name : str
+        An optional string that labels the operator. Pauli operators with
+        different names commute.
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum import represent
+    >>> from sympy.physics.quantum.pauli import SigmaY
+    >>> sy = SigmaY()
+    >>> sy
+    SigmaY()
+    >>> represent(sy)
+    Matrix([
+    [0, -I],
+    [I,  0]])
+    """
+
+    def __new__(cls, *args, **hints):
+        return SigmaOpBase.__new__(cls, *args)
+
+    def _eval_commutator_SigmaZ(self, other, **hints):
+        if self.name != other.name:
+            return S.Zero
+        else:
+            return 2 * I * SigmaX(self.name)
+
+    def _eval_commutator_SigmaX(self, other, **hints):
+        if self.name != other.name:
+            return S.Zero
+        else:
+            return - 2 * I * SigmaZ(self.name)
+
+    def _eval_anticommutator_SigmaX(self, other, **hints):
+        return S.Zero
+
+    def _eval_anticommutator_SigmaZ(self, other, **hints):
+        return S.Zero
+
+    def _eval_adjoint(self):
+        return self
+
+    def _print_contents_latex(self, printer, *args):
+        if self.use_name:
+            return r'{\sigma_y^{(%s)}}' % str(self.name)
+        else:
+            return r'{\sigma_y}'
+
+    def _print_contents(self, printer, *args):
+        return 'SigmaY()'
+
+    def _eval_power(self, e):
+        if e.is_Integer and e.is_positive:
+            return SigmaY(self.name).__pow__(int(e) % 2)
+
+    def _represent_default_basis(self, **options):
+        format = options.get('format', 'sympy')
+        if format == 'sympy':
+            return Matrix([[0, -I], [I, 0]])
+        else:
+            raise NotImplementedError('Representation in format ' +
+                                      format + ' not implemented.')
+
+
+class SigmaZ(SigmaOpBase):
+    """Pauli sigma z operator
+
+    Parameters
+    ==========
+
+    name : str
+        An optional string that labels the operator. Pauli operators with
+        different names commute.
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum import represent
+    >>> from sympy.physics.quantum.pauli import SigmaZ
+    >>> sz = SigmaZ()
+    >>> sz ** 3
+    SigmaZ()
+    >>> represent(sz)
+    Matrix([
+    [1,  0],
+    [0, -1]])
+    """
+
+    def __new__(cls, *args, **hints):
+        return SigmaOpBase.__new__(cls, *args)
+
+    def _eval_commutator_SigmaX(self, other, **hints):
+        if self.name != other.name:
+            return S.Zero
+        else:
+            return 2 * I * SigmaY(self.name)
+
+    def _eval_commutator_SigmaY(self, other, **hints):
+        if self.name != other.name:
+            return S.Zero
+        else:
+            return - 2 * I * SigmaX(self.name)
+
+    def _eval_anticommutator_SigmaX(self, other, **hints):
+        return S.Zero
+
+    def _eval_anticommutator_SigmaY(self, other, **hints):
+        return S.Zero
+
+    def _eval_adjoint(self):
+        return self
+
+    def _print_contents_latex(self, printer, *args):
+        if self.use_name:
+            return r'{\sigma_z^{(%s)}}' % str(self.name)
+        else:
+            return r'{\sigma_z}'
+
+    def _print_contents(self, printer, *args):
+        return 'SigmaZ()'
+
+    def _eval_power(self, e):
+        if e.is_Integer and e.is_positive:
+            return SigmaZ(self.name).__pow__(int(e) % 2)
+
+    def _represent_default_basis(self, **options):
+        format = options.get('format', 'sympy')
+        if format == 'sympy':
+            return Matrix([[1, 0], [0, -1]])
+        else:
+            raise NotImplementedError('Representation in format ' +
+                                      format + ' not implemented.')
+
+
+class SigmaMinus(SigmaOpBase):
+    """Pauli sigma minus operator
+
+    Parameters
+    ==========
+
+    name : str
+        An optional string that labels the operator. Pauli operators with
+        different names commute.
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum import represent, Dagger
+    >>> from sympy.physics.quantum.pauli import SigmaMinus
+    >>> sm = SigmaMinus()
+    >>> sm
+    SigmaMinus()
+    >>> Dagger(sm)
+    SigmaPlus()
+    >>> represent(sm)
+    Matrix([
+    [0, 0],
+    [1, 0]])
+    """
+
+    def __new__(cls, *args, **hints):
+        return SigmaOpBase.__new__(cls, *args)
+
+    def _eval_commutator_SigmaX(self, other, **hints):
+        if self.name != other.name:
+            return S.Zero
+        else:
+            return -SigmaZ(self.name)
+
+    def _eval_commutator_SigmaY(self, other, **hints):
+        if self.name != other.name:
+            return S.Zero
+        else:
+            return I * SigmaZ(self.name)
+
+    def _eval_commutator_SigmaZ(self, other, **hints):
+        return 2 * self
+
+    def _eval_commutator_SigmaMinus(self, other, **hints):
+        return SigmaZ(self.name)
+
+    def _eval_anticommutator_SigmaZ(self, other, **hints):
+        return S.Zero
+
+    def _eval_anticommutator_SigmaX(self, other, **hints):
+        return S.One
+
+    def _eval_anticommutator_SigmaY(self, other, **hints):
+        return I * S.NegativeOne
+
+    def _eval_anticommutator_SigmaPlus(self, other, **hints):
+        return S.One
+
+    def _eval_adjoint(self):
+        return SigmaPlus(self.name)
+
+    def _eval_power(self, e):
+        if e.is_Integer and e.is_positive:
+            return S.Zero
+
+    def _print_contents_latex(self, printer, *args):
+        if self.use_name:
+            return r'{\sigma_-^{(%s)}}' % str(self.name)
+        else:
+            return r'{\sigma_-}'
+
+    def _print_contents(self, printer, *args):
+        return 'SigmaMinus()'
+
+    def _represent_default_basis(self, **options):
+        format = options.get('format', 'sympy')
+        if format == 'sympy':
+            return Matrix([[0, 0], [1, 0]])
+        else:
+            raise NotImplementedError('Representation in format ' +
+                                      format + ' not implemented.')
+
+
+class SigmaPlus(SigmaOpBase):
+    """Pauli sigma plus operator
+
+    Parameters
+    ==========
+
+    name : str
+        An optional string that labels the operator. Pauli operators with
+        different names commute.
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum import represent, Dagger
+    >>> from sympy.physics.quantum.pauli import SigmaPlus
+    >>> sp = SigmaPlus()
+    >>> sp
+    SigmaPlus()
+    >>> Dagger(sp)
+    SigmaMinus()
+    >>> represent(sp)
+    Matrix([
+    [0, 1],
+    [0, 0]])
+    """
+
+    def __new__(cls, *args, **hints):
+        return SigmaOpBase.__new__(cls, *args)
+
+    def _eval_commutator_SigmaX(self, other, **hints):
+        if self.name != other.name:
+            return S.Zero
+        else:
+            return SigmaZ(self.name)
+
+    def _eval_commutator_SigmaY(self, other, **hints):
+        if self.name != other.name:
+            return S.Zero
+        else:
+            return I * SigmaZ(self.name)
+
+    def _eval_commutator_SigmaZ(self, other, **hints):
+        if self.name != other.name:
+            return S.Zero
+        else:
+            return -2 * self
+
+    def _eval_commutator_SigmaMinus(self, other, **hints):
+        return SigmaZ(self.name)
+
+    def _eval_anticommutator_SigmaZ(self, other, **hints):
+        return S.Zero
+
+    def _eval_anticommutator_SigmaX(self, other, **hints):
+        return S.One
+
+    def _eval_anticommutator_SigmaY(self, other, **hints):
+        return I
+
+    def _eval_anticommutator_SigmaMinus(self, other, **hints):
+        return S.One
+
+    def _eval_adjoint(self):
+        return SigmaMinus(self.name)
+
+    def _eval_mul(self, other):
+        return self * other
+
+    def _eval_power(self, e):
+        if e.is_Integer and e.is_positive:
+            return S.Zero
+
+    def _print_contents_latex(self, printer, *args):
+        if self.use_name:
+            return r'{\sigma_+^{(%s)}}' % str(self.name)
+        else:
+            return r'{\sigma_+}'
+
+    def _print_contents(self, printer, *args):
+        return 'SigmaPlus()'
+
+    def _represent_default_basis(self, **options):
+        format = options.get('format', 'sympy')
+        if format == 'sympy':
+            return Matrix([[0, 1], [0, 0]])
+        else:
+            raise NotImplementedError('Representation in format ' +
+                                      format + ' not implemented.')
+
+
+class SigmaZKet(Ket):
+    """Ket for a two-level system quantum system.
+
+    Parameters
+    ==========
+
+    n : Number
+        The state number (0 or 1).
+
+    """
+
+    def __new__(cls, n):
+        if n not in (0, 1):
+            raise ValueError("n must be 0 or 1")
+        return Ket.__new__(cls, n)
+
+    @property
+    def n(self):
+        return self.label[0]
+
+    @classmethod
+    def dual_class(self):
+        return SigmaZBra
+
+    @classmethod
+    def _eval_hilbert_space(cls, label):
+        return ComplexSpace(2)
+
+    def _eval_innerproduct_SigmaZBra(self, bra, **hints):
+        return KroneckerDelta(self.n, bra.n)
+
+    def _apply_from_right_to_SigmaZ(self, op, **options):
+        if self.n == 0:
+            return self
+        else:
+            return S.NegativeOne * self
+
+    def _apply_from_right_to_SigmaX(self, op, **options):
+        return SigmaZKet(1) if self.n == 0 else SigmaZKet(0)
+
+    def _apply_from_right_to_SigmaY(self, op, **options):
+        return I * SigmaZKet(1) if self.n == 0 else (-I) * SigmaZKet(0)
+
+    def _apply_from_right_to_SigmaMinus(self, op, **options):
+        if self.n == 0:
+            return SigmaZKet(1)
+        else:
+            return S.Zero
+
+    def _apply_from_right_to_SigmaPlus(self, op, **options):
+        if self.n == 0:
+            return S.Zero
+        else:
+            return SigmaZKet(0)
+
+    def _represent_default_basis(self, **options):
+        format = options.get('format', 'sympy')
+        if format == 'sympy':
+            return Matrix([[1], [0]]) if self.n == 0 else Matrix([[0], [1]])
+        else:
+            raise NotImplementedError('Representation in format ' +
+                                      format + ' not implemented.')
+
+
+class SigmaZBra(Bra):
+    """Bra for a two-level quantum system.
+
+    Parameters
+    ==========
+
+    n : Number
+        The state number (0 or 1).
+
+    """
+
+    def __new__(cls, n):
+        if n not in (0, 1):
+            raise ValueError("n must be 0 or 1")
+        return Bra.__new__(cls, n)
+
+    @property
+    def n(self):
+        return self.label[0]
+
+    @classmethod
+    def dual_class(self):
+        return SigmaZKet
+
+
+def _qsimplify_pauli_product(a, b):
+    """
+    Internal helper function for simplifying products of Pauli operators.
+    """
+    if not (isinstance(a, SigmaOpBase) and isinstance(b, SigmaOpBase)):
+        return Mul(a, b)
+
+    if a.name != b.name:
+        # Pauli matrices with different labels commute; sort by name
+        if a.name < b.name:
+            return Mul(a, b)
+        else:
+            return Mul(b, a)
+
+    elif isinstance(a, SigmaX):
+
+        if isinstance(b, SigmaX):
+            return S.One
+
+        if isinstance(b, SigmaY):
+            return I * SigmaZ(a.name)
+
+        if isinstance(b, SigmaZ):
+            return - I * SigmaY(a.name)
+
+        if isinstance(b, SigmaMinus):
+            return (S.Half + SigmaZ(a.name)/2)
+
+        if isinstance(b, SigmaPlus):
+            return (S.Half - SigmaZ(a.name)/2)
+
+    elif isinstance(a, SigmaY):
+
+        if isinstance(b, SigmaX):
+            return - I * SigmaZ(a.name)
+
+        if isinstance(b, SigmaY):
+            return S.One
+
+        if isinstance(b, SigmaZ):
+            return I * SigmaX(a.name)
+
+        if isinstance(b, SigmaMinus):
+            return -I * (S.One + SigmaZ(a.name))/2
+
+        if isinstance(b, SigmaPlus):
+            return I * (S.One - SigmaZ(a.name))/2
+
+    elif isinstance(a, SigmaZ):
+
+        if isinstance(b, SigmaX):
+            return I * SigmaY(a.name)
+
+        if isinstance(b, SigmaY):
+            return - I * SigmaX(a.name)
+
+        if isinstance(b, SigmaZ):
+            return S.One
+
+        if isinstance(b, SigmaMinus):
+            return - SigmaMinus(a.name)
+
+        if isinstance(b, SigmaPlus):
+            return SigmaPlus(a.name)
+
+    elif isinstance(a, SigmaMinus):
+
+        if isinstance(b, SigmaX):
+            return (S.One - SigmaZ(a.name))/2
+
+        if isinstance(b, SigmaY):
+            return - I * (S.One - SigmaZ(a.name))/2
+
+        if isinstance(b, SigmaZ):
+            # (SigmaX(a.name) - I * SigmaY(a.name))/2
+            return SigmaMinus(b.name)
+
+        if isinstance(b, SigmaMinus):
+            return S.Zero
+
+        if isinstance(b, SigmaPlus):
+            return S.Half - SigmaZ(a.name)/2
+
+    elif isinstance(a, SigmaPlus):
+
+        if isinstance(b, SigmaX):
+            return (S.One + SigmaZ(a.name))/2
+
+        if isinstance(b, SigmaY):
+            return I * (S.One + SigmaZ(a.name))/2
+
+        if isinstance(b, SigmaZ):
+            #-(SigmaX(a.name) + I * SigmaY(a.name))/2
+            return -SigmaPlus(a.name)
+
+        if isinstance(b, SigmaMinus):
+            return (S.One + SigmaZ(a.name))/2
+
+        if isinstance(b, SigmaPlus):
+            return S.Zero
+
+    else:
+        return a * b
+
+
+def qsimplify_pauli(e):
+    """
+    Simplify an expression that includes products of pauli operators.
+
+    Parameters
+    ==========
+
+    e : expression
+        An expression that contains products of Pauli operators that is
+        to be simplified.
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum.pauli import SigmaX, SigmaY
+    >>> from sympy.physics.quantum.pauli import qsimplify_pauli
+    >>> sx, sy = SigmaX(), SigmaY()
+    >>> sx * sy
+    SigmaX()*SigmaY()
+    >>> qsimplify_pauli(sx * sy)
+    I*SigmaZ()
+    """
+    if isinstance(e, Operator):
+        return e
+
+    if isinstance(e, (Add, Pow, exp)):
+        t = type(e)
+        return t(*(qsimplify_pauli(arg) for arg in e.args))
+
+    if isinstance(e, Mul):
+
+        c, nc = e.args_cnc()
+
+        nc_s = []
+        while nc:
+            curr = nc.pop(0)
+
+            while (len(nc) and
+                   isinstance(curr, SigmaOpBase) and
+                   isinstance(nc[0], SigmaOpBase) and
+                   curr.name == nc[0].name):
+
+                x = nc.pop(0)
+                y = _qsimplify_pauli_product(curr, x)
+                c1, nc1 = y.args_cnc()
+                curr = Mul(*nc1)
+                c = c + c1
+
+            nc_s.append(curr)
+
+        return Mul(*c) * Mul(*nc_s)
+
+    return e

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/piab.py

@@ -0,0 +1,72 @@
+"""1D quantum particle in a box."""
+
+from sympy.core.numbers import pi
+from sympy.core.singleton import S
+from sympy.core.symbol import Symbol
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.functions.elementary.trigonometric import sin
+from sympy.sets.sets import Interval
+
+from sympy.physics.quantum.operator import HermitianOperator
+from sympy.physics.quantum.state import Ket, Bra
+from sympy.physics.quantum.constants import hbar
+from sympy.functions.special.tensor_functions import KroneckerDelta
+from sympy.physics.quantum.hilbert import L2
+
+m = Symbol('m')
+L = Symbol('L')
+
+
+__all__ = [
+    'PIABHamiltonian',
+    'PIABKet',
+    'PIABBra'
+]
+
+
+class PIABHamiltonian(HermitianOperator):
+    """Particle in a box Hamiltonian operator."""
+
+    @classmethod
+    def _eval_hilbert_space(cls, label):
+        return L2(Interval(S.NegativeInfinity, S.Infinity))
+
+    def _apply_operator_PIABKet(self, ket, **options):
+        n = ket.label[0]
+        return (n**2*pi**2*hbar**2)/(2*m*L**2)*ket
+
+
+class PIABKet(Ket):
+    """Particle in a box eigenket."""
+
+    @classmethod
+    def _eval_hilbert_space(cls, args):
+        return L2(Interval(S.NegativeInfinity, S.Infinity))
+
+    @classmethod
+    def dual_class(self):
+        return PIABBra
+
+    def _represent_default_basis(self, **options):
+        return self._represent_XOp(None, **options)
+
+    def _represent_XOp(self, basis, **options):
+        x = Symbol('x')
+        n = Symbol('n')
+        subs_info = options.get('subs', {})
+        return sqrt(2/L)*sin(n*pi*x/L).subs(subs_info)
+
+    def _eval_innerproduct_PIABBra(self, bra):
+        return KroneckerDelta(bra.label[0], self.label[0])
+
+
+class PIABBra(Bra):
+    """Particle in a box eigenbra."""
+
+    @classmethod
+    def _eval_hilbert_space(cls, label):
+        return L2(Interval(S.NegativeInfinity, S.Infinity))
+
+    @classmethod
+    def dual_class(self):
+        return PIABKet

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/qapply.py

@@ -0,0 +1,263 @@
+"""Logic for applying operators to states.
+
+Todo:
+* Sometimes the final result needs to be expanded, we should do this by hand.
+"""
+
+from sympy.concrete import Sum
+from sympy.core.add import Add
+from sympy.core.kind import NumberKind
+from sympy.core.mul import Mul
+from sympy.core.power import Pow
+from sympy.core.singleton import S
+from sympy.core.sympify import sympify, _sympify
+
+from sympy.physics.quantum.anticommutator import AntiCommutator
+from sympy.physics.quantum.commutator import Commutator
+from sympy.physics.quantum.dagger import Dagger
+from sympy.physics.quantum.innerproduct import InnerProduct
+from sympy.physics.quantum.operator import OuterProduct, Operator
+from sympy.physics.quantum.state import State, KetBase, BraBase, Wavefunction
+from sympy.physics.quantum.tensorproduct import TensorProduct
+
+__all__ = [
+    'qapply'
+]
+
+
+#-----------------------------------------------------------------------------
+# Main code
+#-----------------------------------------------------------------------------
+
+
+def ip_doit_func(e):
+    """Transform the inner products in an expression by calling ``.doit()``."""
+    return e.replace(InnerProduct, lambda *args: InnerProduct(*args).doit())
+
+
+def sum_doit_func(e):
+    """Transform the sums in an expression by calling ``.doit()``."""
+    return e.replace(Sum, lambda *args: Sum(*args).doit())
+
+
+def qapply(e, **options):
+    """Apply operators to states in a quantum expression.
+
+    Parameters
+    ==========
+
+    e : Expr
+        The expression containing operators and states. This expression tree
+        will be walked to find operators acting on states symbolically.
+    options : dict
+        A dict of key/value pairs that determine how the operator actions
+        are carried out.
+
+        The following options are valid:
+
+        * ``dagger``: try to apply Dagger operators to the left
+          (default: False).
+        * ``ip_doit``: call ``.doit()`` in inner products when they are
+          encountered (default: True).
+        * ``sum_doit``: call ``.doit()`` on sums when they are encountered
+          (default: False). This is helpful for collapsing sums over Kronecker
+          delta's that are created when calling ``qapply``.
+
+    Returns
+    =======
+
+    e : Expr
+        The original expression, but with the operators applied to states.
+
+    Examples
+    ========
+
+        >>> from sympy.physics.quantum import qapply, Ket, Bra
+        >>> b = Bra('b')
+        >>> k = Ket('k')
+        >>> A = k * b
+        >>> A
+        |k><b|
+        >>> qapply(A * b.dual / (b * b.dual))
+        |k>
+        >>> qapply(k.dual * A / (k.dual * k))
+        <b|
+    """
+    from sympy.physics.quantum.density import Density
+
+    dagger = options.get('dagger', False)
+    sum_doit = options.get('sum_doit', False)
+    ip_doit = options.get('ip_doit', True)
+
+    e = _sympify(e)
+
+    # Using the kind API here helps us to narrow what types of expressions
+    # we call ``ip_doit_func`` on.
+    if e.kind == NumberKind:
+        return ip_doit_func(e) if ip_doit else e
+
+    # This may be a bit aggressive but ensures that everything gets expanded
+    # to its simplest form before trying to apply operators. This includes
+    # things like (A+B+C)*|a> and A*(|a>+|b>) and all Commutators and
+    # TensorProducts. The only problem with this is that if we can't apply
+    # all the Operators, we have just expanded everything.
+    # TODO: don't expand the scalars in front of each Mul.
+    e = e.expand(commutator=True, tensorproduct=True)
+
+    # If we just have a raw ket, return it.
+    if isinstance(e, KetBase):
+        return e
+
+    # We have an Add(a, b, c, ...) and compute
+    # Add(qapply(a), qapply(b), ...)
+    elif isinstance(e, Add):
+        result = 0
+        for arg in e.args:
+            result += qapply(arg, **options)
+        return result.expand()
+
+    # For a Density operator call qapply on its state
+    elif isinstance(e, Density):
+        new_args = [(qapply(state, **options), prob) for (state,
+                     prob) in e.args]
+        return Density(*new_args)
+
+    # For a raw TensorProduct, call qapply on its args.
+    elif isinstance(e, TensorProduct):
+        return TensorProduct(*[qapply(t, **options) for t in e.args])
+
+    # For a Sum, call qapply on its function.
+    elif isinstance(e, Sum):
+        result = Sum(qapply(e.function, **options), *e.limits)
+        result = sum_doit_func(result) if sum_doit else result
+        return result
+
+    # For a Pow, call qapply on its base.
+    elif isinstance(e, Pow):
+        return qapply(e.base, **options)**e.exp
+
+    # We have a Mul where there might be actual operators to apply to kets.
+    elif isinstance(e, Mul):
+        c_part, nc_part = e.args_cnc()
+        c_mul = Mul(*c_part)
+        nc_mul = Mul(*nc_part)
+        if not nc_part: # If we only have a commuting part, just return it.
+            result = c_mul
+        elif isinstance(nc_mul, Mul):
+            result = c_mul*qapply_Mul(nc_mul, **options)
+        else:
+            result = c_mul*qapply(nc_mul, **options)
+        if result == e and dagger:
+            result = Dagger(qapply_Mul(Dagger(e), **options))
+        result = ip_doit_func(result) if ip_doit else result
+        result = sum_doit_func(result) if sum_doit else result
+        return result
+
+    # In all other cases (State, Operator, Pow, Commutator, InnerProduct,
+    # OuterProduct) we won't ever have operators to apply to kets.
+    else:
+        return e
+
+
+def qapply_Mul(e, **options):
+
+    args = list(e.args)
+    extra = S.One
+    result = None
+
+    # If we only have 0 or 1 args, we have nothing to do and return.
+    if len(args) <= 1 or not isinstance(e, Mul):
+        return e
+    rhs = args.pop()
+    lhs = args.pop()
+
+    # Make sure we have two non-commutative objects before proceeding.
+    if (not isinstance(rhs, Wavefunction) and sympify(rhs).is_commutative) or \
+            (not isinstance(lhs, Wavefunction) and sympify(lhs).is_commutative):
+        return e
+
+    # For a Pow with an integer exponent, apply one of them and reduce the
+    # exponent by one.
+    if isinstance(lhs, Pow) and lhs.exp.is_Integer:
+        args.append(lhs.base**(lhs.exp - 1))
+        lhs = lhs.base
+
+    # Pull OuterProduct apart
+    if isinstance(lhs, OuterProduct):
+        args.append(lhs.ket)
+        lhs = lhs.bra
+
+    if isinstance(rhs, OuterProduct):
+        extra = rhs.bra # Append to the right of the result
+        rhs = rhs.ket
+
+    # Call .doit() on Commutator/AntiCommutator.
+    if isinstance(lhs, (Commutator, AntiCommutator)):
+        comm = lhs.doit()
+        if isinstance(comm, Add):
+            return qapply(
+                e.func(*(args + [comm.args[0], rhs])) +
+                e.func(*(args + [comm.args[1], rhs])),
+                **options
+            )*extra
+        else:
+            return qapply(e.func(*args)*comm*rhs, **options)*extra
+
+    # Apply tensor products of operators to states
+    if isinstance(lhs, TensorProduct) and all(isinstance(arg, (Operator, State, Mul, Pow)) or arg == 1 for arg in lhs.args) and \
+            isinstance(rhs, TensorProduct) and all(isinstance(arg, (Operator, State, Mul, Pow)) or arg == 1 for arg in rhs.args) and \
+            len(lhs.args) == len(rhs.args):
+        result = TensorProduct(*[qapply(lhs.args[n]*rhs.args[n], **options) for n in range(len(lhs.args))]).expand(tensorproduct=True)
+        return qapply_Mul(e.func(*args), **options)*result*extra
+
+    # For Sums, move the Sum to the right.
+    if isinstance(rhs, Sum):
+        if isinstance(lhs, Sum):
+            if set(lhs.variables).intersection(set(rhs.variables)):
+                raise ValueError('Duplicated dummy indices in separate sums in qapply.')
+            limits = lhs.limits + rhs.limits
+            result = Sum(qapply(lhs.function*rhs.function, **options), *limits)
+            return qapply_Mul(e.func(*args)*result, **options)
+        else:
+            result = Sum(qapply(lhs*rhs.function, **options), *rhs.limits)
+            return qapply_Mul(e.func(*args)*result, **options)
+
+    if isinstance(lhs, Sum):
+        result = Sum(qapply(lhs.function*rhs, **options), *lhs.limits)
+        return qapply_Mul(e.func(*args)*result, **options)
+
+    # Now try to actually apply the operator and build an inner product.
+    _apply = getattr(lhs, '_apply_operator', None)
+    if _apply is not None:
+        try:
+            result = _apply(rhs, **options)
+        except NotImplementedError:
+            result = None
+    else:
+        result = None
+
+    if result is None:
+        _apply_right = getattr(rhs, '_apply_from_right_to', None)
+        if _apply_right is not None:
+            try:
+                result = _apply_right(lhs, **options)
+            except NotImplementedError:
+                result = None
+
+    if result is None:
+        if isinstance(lhs, BraBase) and isinstance(rhs, KetBase):
+            result = InnerProduct(lhs, rhs)
+
+    # TODO: I may need to expand before returning the final result.
+    if isinstance(result, (int, complex, float)):
+        return _sympify(result)
+    elif result is None:
+        if len(args) == 0:
+            # We had two args to begin with so args=[].
+            return e
+        else:
+            return qapply_Mul(e.func(*(args + [lhs])), **options)*rhs*extra
+    elif isinstance(result, InnerProduct):
+        return result*qapply_Mul(e.func(*args), **options)*extra
+    else:  # result is a scalar times a Mul, Add or TensorProduct
+        return qapply(e.func(*args)*result, **options)*extra

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/qasm.py

@@ -0,0 +1,224 @@
+"""
+
+qasm.py - Functions to parse a set of qasm commands into a SymPy Circuit.
+
+Examples taken from Chuang's page: https://web.archive.org/web/20220120121541/https://www.media.mit.edu/quanta/qasm2circ/
+
+The code returns a circuit and an associated list of labels.
+
+>>> from sympy.physics.quantum.qasm import Qasm
+>>> q = Qasm('qubit q0', 'qubit q1', 'h q0', 'cnot q0,q1')
+>>> q.get_circuit()
+CNOT(1,0)*H(1)
+
+>>> q = Qasm('qubit q0', 'qubit q1', 'cnot q0,q1', 'cnot q1,q0', 'cnot q0,q1')
+>>> q.get_circuit()
+CNOT(1,0)*CNOT(0,1)*CNOT(1,0)
+"""
+
+__all__ = [
+    'Qasm',
+    ]
+
+from math import prod
+
+from sympy.physics.quantum.gate import H, CNOT, X, Z, CGate, CGateS, SWAP, S, T,CPHASE
+from sympy.physics.quantum.circuitplot import Mz
+
+def read_qasm(lines):
+    return Qasm(*lines.splitlines())
+
+def read_qasm_file(filename):
+    return Qasm(*open(filename).readlines())
+
+def flip_index(i, n):
+    """Reorder qubit indices from largest to smallest.
+
+    >>> from sympy.physics.quantum.qasm import flip_index
+    >>> flip_index(0, 2)
+    1
+    >>> flip_index(1, 2)
+    0
+    """
+    return n-i-1
+
+def trim(line):
+    """Remove everything following comment # characters in line.
+
+    >>> from sympy.physics.quantum.qasm import trim
+    >>> trim('nothing happens here')
+    'nothing happens here'
+    >>> trim('something #happens here')
+    'something '
+    """
+    if '#' not in line:
+        return line
+    return line.split('#')[0]
+
+def get_index(target, labels):
+    """Get qubit labels from the rest of the line,and return indices
+
+    >>> from sympy.physics.quantum.qasm import get_index
+    >>> get_index('q0', ['q0', 'q1'])
+    1
+    >>> get_index('q1', ['q0', 'q1'])
+    0
+    """
+    nq = len(labels)
+    return flip_index(labels.index(target), nq)
+
+def get_indices(targets, labels):
+    return [get_index(t, labels) for t in targets]
+
+def nonblank(args):
+    for line in args:
+        line = trim(line)
+        if line.isspace():
+            continue
+        yield line
+    return
+
+def fullsplit(line):
+    words = line.split()
+    rest = ' '.join(words[1:])
+    return fixcommand(words[0]), [s.strip() for s in rest.split(',')]
+
+def fixcommand(c):
+    """Fix Qasm command names.
+
+    Remove all of forbidden characters from command c, and
+    replace 'def' with 'qdef'.
+    """
+    forbidden_characters = ['-']
+    c = c.lower()
+    for char in forbidden_characters:
+        c = c.replace(char, '')
+    if c == 'def':
+        return 'qdef'
+    return c
+
+def stripquotes(s):
+    """Replace explicit quotes in a string.
+
+    >>> from sympy.physics.quantum.qasm import stripquotes
+    >>> stripquotes("'S'") == 'S'
+    True
+    >>> stripquotes('"S"') == 'S'
+    True
+    >>> stripquotes('S') == 'S'
+    True
+    """
+    s = s.replace('"', '') # Remove second set of quotes?
+    s = s.replace("'", '')
+    return s
+
+class Qasm:
+    """Class to form objects from Qasm lines
+
+    >>> from sympy.physics.quantum.qasm import Qasm
+    >>> q = Qasm('qubit q0', 'qubit q1', 'h q0', 'cnot q0,q1')
+    >>> q.get_circuit()
+    CNOT(1,0)*H(1)
+    >>> q = Qasm('qubit q0', 'qubit q1', 'cnot q0,q1', 'cnot q1,q0', 'cnot q0,q1')
+    >>> q.get_circuit()
+    CNOT(1,0)*CNOT(0,1)*CNOT(1,0)
+    """
+    def __init__(self, *args, **kwargs):
+        self.defs = {}
+        self.circuit = []
+        self.labels = []
+        self.inits = {}
+        self.add(*args)
+        self.kwargs = kwargs
+
+    def add(self, *lines):
+        for line in nonblank(lines):
+            command, rest = fullsplit(line)
+            if self.defs.get(command): #defs come first, since you can override built-in
+                function = self.defs.get(command)
+                indices = self.indices(rest)
+                if len(indices) == 1:
+                    self.circuit.append(function(indices[0]))
+                else:
+                    self.circuit.append(function(indices[:-1], indices[-1]))
+            elif hasattr(self, command):
+                function = getattr(self, command)
+                function(*rest)
+            else:
+                print("Function %s not defined. Skipping" % command)
+
+    def get_circuit(self):
+        return prod(reversed(self.circuit))
+
+    def get_labels(self):
+        return list(reversed(self.labels))
+
+    def plot(self):
+        from sympy.physics.quantum.circuitplot import CircuitPlot
+        circuit, labels = self.get_circuit(), self.get_labels()
+        CircuitPlot(circuit, len(labels), labels=labels, inits=self.inits)
+
+    def qubit(self, arg, init=None):
+        self.labels.append(arg)
+        if init: self.inits[arg] = init
+
+    def indices(self, args):
+        return get_indices(args, self.labels)
+
+    def index(self, arg):
+        return get_index(arg, self.labels)
+
+    def nop(self, *args):
+        pass
+
+    def x(self, arg):
+        self.circuit.append(X(self.index(arg)))
+
+    def z(self, arg):
+        self.circuit.append(Z(self.index(arg)))
+
+    def h(self, arg):
+        self.circuit.append(H(self.index(arg)))
+
+    def s(self, arg):
+        self.circuit.append(S(self.index(arg)))
+
+    def t(self, arg):
+        self.circuit.append(T(self.index(arg)))
+
+    def measure(self, arg):
+        self.circuit.append(Mz(self.index(arg)))
+
+    def cnot(self, a1, a2):
+        self.circuit.append(CNOT(*self.indices([a1, a2])))
+
+    def swap(self, a1, a2):
+        self.circuit.append(SWAP(*self.indices([a1, a2])))
+
+    def cphase(self, a1, a2):
+        self.circuit.append(CPHASE(*self.indices([a1, a2])))
+
+    def toffoli(self, a1, a2, a3):
+        i1, i2, i3 = self.indices([a1, a2, a3])
+        self.circuit.append(CGateS((i1, i2), X(i3)))
+
+    def cx(self, a1, a2):
+        fi, fj = self.indices([a1, a2])
+        self.circuit.append(CGate(fi, X(fj)))
+
+    def cz(self, a1, a2):
+        fi, fj = self.indices([a1, a2])
+        self.circuit.append(CGate(fi, Z(fj)))
+
+    def defbox(self, *args):
+        print("defbox not supported yet. Skipping: ", args)
+
+    def qdef(self, name, ncontrols, symbol):
+        from sympy.physics.quantum.circuitplot import CreateOneQubitGate, CreateCGate
+        ncontrols = int(ncontrols)
+        command = fixcommand(name)
+        symbol = stripquotes(symbol)
+        if ncontrols > 0:
+            self.defs[command] = CreateCGate(symbol)
+        else:
+            self.defs[command] = CreateOneQubitGate(symbol)

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/qexpr.py

@@ -0,0 +1,409 @@
+from sympy.core.expr import Expr
+from sympy.core.symbol import Symbol
+from sympy.core.sympify import sympify
+from sympy.matrices.dense import Matrix
+from sympy.printing.pretty.stringpict import prettyForm
+from sympy.core.containers import Tuple
+from sympy.utilities.iterables import is_sequence
+
+from sympy.physics.quantum.dagger import Dagger
+from sympy.physics.quantum.matrixutils import (
+    numpy_ndarray, scipy_sparse_matrix,
+    to_sympy, to_numpy, to_scipy_sparse
+)
+
+__all__ = [
+    'QuantumError',
+    'QExpr'
+]
+
+
+#-----------------------------------------------------------------------------
+# Error handling
+#-----------------------------------------------------------------------------
+
+class QuantumError(Exception):
+    pass
+
+
+def _qsympify_sequence(seq):
+    """Convert elements of a sequence to standard form.
+
+    This is like sympify, but it performs special logic for arguments passed
+    to QExpr. The following conversions are done:
+
+    * (list, tuple, Tuple) => _qsympify_sequence each element and convert
+      sequence to a Tuple.
+    * basestring => Symbol
+    * Matrix => Matrix
+    * other => sympify
+
+    Strings are passed to Symbol, not sympify to make sure that variables like
+    'pi' are kept as Symbols, not the SymPy built-in number subclasses.
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum.qexpr import _qsympify_sequence
+    >>> _qsympify_sequence((1,2,[3,4,[1,]]))
+    (1, 2, (3, 4, (1,)))
+
+    """
+
+    return tuple(__qsympify_sequence_helper(seq))
+
+
+def __qsympify_sequence_helper(seq):
+    """
+       Helper function for _qsympify_sequence
+       This function does the actual work.
+    """
+    #base case. If not a list, do Sympification
+    if not is_sequence(seq):
+        if isinstance(seq, Matrix):
+            return seq
+        elif isinstance(seq, str):
+            return Symbol(seq)
+        else:
+            return sympify(seq)
+
+    # base condition, when seq is QExpr and also
+    # is iterable.
+    if isinstance(seq, QExpr):
+        return seq
+
+    #if list, recurse on each item in the list
+    result = [__qsympify_sequence_helper(item) for item in seq]
+
+    return Tuple(*result)
+
+
+#-----------------------------------------------------------------------------
+# Basic Quantum Expression from which all objects descend
+#-----------------------------------------------------------------------------
+
+class QExpr(Expr):
+    """A base class for all quantum object like operators and states."""
+
+    # In sympy, slots are for instance attributes that are computed
+    # dynamically by the __new__ method. They are not part of args, but they
+    # derive from args.
+
+    # The Hilbert space a quantum Object belongs to.
+    __slots__ = ('hilbert_space', )
+
+    is_commutative = False
+
+    # The separator used in printing the label.
+    _label_separator = ''
+
+    def __new__(cls, *args, **kwargs):
+        """Construct a new quantum object.
+
+        Parameters
+        ==========
+
+        args : tuple
+            The list of numbers or parameters that uniquely specify the
+            quantum object. For a state, this will be its symbol or its
+            set of quantum numbers.
+
+        Examples
+        ========
+
+        >>> from sympy.physics.quantum.qexpr import QExpr
+        >>> q = QExpr(0)
+        >>> q
+        0
+        >>> q.label
+        (0,)
+        >>> q.hilbert_space
+        H
+        >>> q.args
+        (0,)
+        >>> q.is_commutative
+        False
+        """
+
+        # First compute args and call Expr.__new__ to create the instance
+        args = cls._eval_args(args, **kwargs)
+        if len(args) == 0:
+            args = cls._eval_args(tuple(cls.default_args()), **kwargs)
+        inst = Expr.__new__(cls, *args)
+        # Now set the slots on the instance
+        inst.hilbert_space = cls._eval_hilbert_space(args)
+        return inst
+
+    @classmethod
+    def _new_rawargs(cls, hilbert_space, *args, **old_assumptions):
+        """Create new instance of this class with hilbert_space and args.
+
+        This is used to bypass the more complex logic in the ``__new__``
+        method in cases where you already have the exact ``hilbert_space``
+        and ``args``. This should be used when you are positive these
+        arguments are valid, in their final, proper form and want to optimize
+        the creation of the object.
+        """
+
+        obj = Expr.__new__(cls, *args, **old_assumptions)
+        obj.hilbert_space = hilbert_space
+        return obj
+
+    #-------------------------------------------------------------------------
+    # Properties
+    #-------------------------------------------------------------------------
+
+    @property
+    def label(self):
+        """The label is the unique set of identifiers for the object.
+
+        Usually, this will include all of the information about the state
+        *except* the time (in the case of time-dependent objects).
+
+        This must be a tuple, rather than a Tuple.
+        """
+        if len(self.args) == 0:  # If there is no label specified, return the default
+            return self._eval_args(list(self.default_args()))
+        else:
+            return self.args
+
+    @property
+    def is_symbolic(self):
+        return True
+
+    @classmethod
+    def default_args(self):
+        """If no arguments are specified, then this will return a default set
+        of arguments to be run through the constructor.
+
+        NOTE: Any classes that override this MUST return a tuple of arguments.
+        Should be overridden by subclasses to specify the default arguments for kets and operators
+        """
+        raise NotImplementedError("No default arguments for this class!")
+
+    #-------------------------------------------------------------------------
+    # _eval_* methods
+    #-------------------------------------------------------------------------
+
+    def _eval_adjoint(self):
+        obj = Expr._eval_adjoint(self)
+        if obj is None:
+            obj = Expr.__new__(Dagger, self)
+        if isinstance(obj, QExpr):
+            obj.hilbert_space = self.hilbert_space
+        return obj
+
+    @classmethod
+    def _eval_args(cls, args):
+        """Process the args passed to the __new__ method.
+
+        This simply runs args through _qsympify_sequence.
+        """
+        return _qsympify_sequence(args)
+
+    @classmethod
+    def _eval_hilbert_space(cls, args):
+        """Compute the Hilbert space instance from the args.
+        """
+        from sympy.physics.quantum.hilbert import HilbertSpace
+        return HilbertSpace()
+
+    #-------------------------------------------------------------------------
+    # Printing
+    #-------------------------------------------------------------------------
+
+    # Utilities for printing: these operate on raw SymPy objects
+
+    def _print_sequence(self, seq, sep, printer, *args):
+        result = []
+        for item in seq:
+            result.append(printer._print(item, *args))
+        return sep.join(result)
+
+    def _print_sequence_pretty(self, seq, sep, printer, *args):
+        pform = printer._print(seq[0], *args)
+        for item in seq[1:]:
+            pform = prettyForm(*pform.right(sep))
+            pform = prettyForm(*pform.right(printer._print(item, *args)))
+        return pform
+
+    # Utilities for printing: these operate prettyForm objects
+
+    def _print_subscript_pretty(self, a, b):
+        top = prettyForm(*b.left(' '*a.width()))
+        bot = prettyForm(*a.right(' '*b.width()))
+        return prettyForm(binding=prettyForm.POW, *bot.below(top))
+
+    def _print_superscript_pretty(self, a, b):
+        return a**b
+
+    def _print_parens_pretty(self, pform, left='(', right=')'):
+        return prettyForm(*pform.parens(left=left, right=right))
+
+    # Printing of labels (i.e. args)
+
+    def _print_label(self, printer, *args):
+        """Prints the label of the QExpr
+
+        This method prints self.label, using self._label_separator to separate
+        the elements. This method should not be overridden, instead, override
+        _print_contents to change printing behavior.
+        """
+        return self._print_sequence(
+            self.label, self._label_separator, printer, *args
+        )
+
+    def _print_label_repr(self, printer, *args):
+        return self._print_sequence(
+            self.label, ',', printer, *args
+        )
+
+    def _print_label_pretty(self, printer, *args):
+        return self._print_sequence_pretty(
+            self.label, self._label_separator, printer, *args
+        )
+
+    def _print_label_latex(self, printer, *args):
+        return self._print_sequence(
+            self.label, self._label_separator, printer, *args
+        )
+
+    # Printing of contents (default to label)
+
+    def _print_contents(self, printer, *args):
+        """Printer for contents of QExpr
+
+        Handles the printing of any unique identifying contents of a QExpr to
+        print as its contents, such as any variables or quantum numbers. The
+        default is to print the label, which is almost always the args. This
+        should not include printing of any brackets or parentheses.
+        """
+        return self._print_label(printer, *args)
+
+    def _print_contents_pretty(self, printer, *args):
+        return self._print_label_pretty(printer, *args)
+
+    def _print_contents_latex(self, printer, *args):
+        return self._print_label_latex(printer, *args)
+
+    # Main printing methods
+
+    def _sympystr(self, printer, *args):
+        """Default printing behavior of QExpr objects
+
+        Handles the default printing of a QExpr. To add other things to the
+        printing of the object, such as an operator name to operators or
+        brackets to states, the class should override the _print/_pretty/_latex
+        functions directly and make calls to _print_contents where appropriate.
+        This allows things like InnerProduct to easily control its printing the
+        printing of contents.
+        """
+        return self._print_contents(printer, *args)
+
+    def _sympyrepr(self, printer, *args):
+        classname = self.__class__.__name__
+        label = self._print_label_repr(printer, *args)
+        return '%s(%s)' % (classname, label)
+
+    def _pretty(self, printer, *args):
+        pform = self._print_contents_pretty(printer, *args)
+        return pform
+
+    def _latex(self, printer, *args):
+        return self._print_contents_latex(printer, *args)
+
+    #-------------------------------------------------------------------------
+    # Represent
+    #-------------------------------------------------------------------------
+
+    def _represent_default_basis(self, **options):
+        raise NotImplementedError('This object does not have a default basis')
+
+    def _represent(self, *, basis=None, **options):
+        """Represent this object in a given basis.
+
+        This method dispatches to the actual methods that perform the
+        representation. Subclases of QExpr should define various methods to
+        determine how the object will be represented in various bases. The
+        format of these methods is::
+
+            def _represent_BasisName(self, basis, **options):
+
+        Thus to define how a quantum object is represented in the basis of
+        the operator Position, you would define::
+
+            def _represent_Position(self, basis, **options):
+
+        Usually, basis object will be instances of Operator subclasses, but
+        there is a chance we will relax this in the future to accommodate other
+        types of basis sets that are not associated with an operator.
+
+        If the ``format`` option is given it can be ("sympy", "numpy",
+        "scipy.sparse"). This will ensure that any matrices that result from
+        representing the object are returned in the appropriate matrix format.
+
+        Parameters
+        ==========
+
+        basis : Operator
+            The Operator whose basis functions will be used as the basis for
+            representation.
+        options : dict
+            A dictionary of key/value pairs that give options and hints for
+            the representation, such as the number of basis functions to
+            be used.
+        """
+        if basis is None:
+            result = self._represent_default_basis(**options)
+        else:
+            result = dispatch_method(self, '_represent', basis, **options)
+
+        # If we get a matrix representation, convert it to the right format.
+        format = options.get('format', 'sympy')
+        result = self._format_represent(result, format)
+        return result
+
+    def _format_represent(self, result, format):
+        if format == 'sympy' and not isinstance(result, Matrix):
+            return to_sympy(result)
+        elif format == 'numpy' and not isinstance(result, numpy_ndarray):
+            return to_numpy(result)
+        elif format == 'scipy.sparse' and \
+                not isinstance(result, scipy_sparse_matrix):
+            return to_scipy_sparse(result)
+
+        return result
+
+
+def split_commutative_parts(e):
+    """Split into commutative and non-commutative parts."""
+    c_part, nc_part = e.args_cnc()
+    c_part = list(c_part)
+    return c_part, nc_part
+
+
+def split_qexpr_parts(e):
+    """Split an expression into Expr and noncommutative QExpr parts."""
+    expr_part = []
+    qexpr_part = []
+    for arg in e.args:
+        if not isinstance(arg, QExpr):
+            expr_part.append(arg)
+        else:
+            qexpr_part.append(arg)
+    return expr_part, qexpr_part
+
+
+def dispatch_method(self, basename, arg, **options):
+    """Dispatch a method to the proper handlers."""
+    method_name = '%s_%s' % (basename, arg.__class__.__name__)
+    if hasattr(self, method_name):
+        f = getattr(self, method_name)
+        # This can raise and we will allow it to propagate.
+        result = f(arg, **options)
+        if result is not None:
+            return result
+    raise NotImplementedError(
+        "%s.%s cannot handle: %r" %
+        (self.__class__.__name__, basename, arg)
+    )

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/qft.py

@@ -0,0 +1,215 @@
+"""An implementation of qubits and gates acting on them.
+
+Todo:
+
+* Update docstrings.
+* Update tests.
+* Implement apply using decompose.
+* Implement represent using decompose or something smarter. For this to
+  work we first have to implement represent for SWAP.
+* Decide if we want upper index to be inclusive in the constructor.
+* Fix the printing of Rk gates in plotting.
+"""
+
+from sympy.core.expr import Expr
+from sympy.core.numbers import (I, Integer, pi)
+from sympy.core.symbol import Symbol
+from sympy.functions.elementary.exponential import exp
+from sympy.matrices.dense import Matrix
+from sympy.functions import sqrt
+
+from sympy.physics.quantum.qapply import qapply
+from sympy.physics.quantum.qexpr import QuantumError, QExpr
+from sympy.matrices import eye
+from sympy.physics.quantum.tensorproduct import matrix_tensor_product
+
+from sympy.physics.quantum.gate import (
+    Gate, HadamardGate, SwapGate, OneQubitGate, CGate, PhaseGate, TGate, ZGate
+)
+
+from sympy.functions.elementary.complexes import sign
+
+__all__ = [
+    'QFT',
+    'IQFT',
+    'RkGate',
+    'Rk'
+]
+
+#-----------------------------------------------------------------------------
+# Fourier stuff
+#-----------------------------------------------------------------------------
+
+
+class RkGate(OneQubitGate):
+    """This is the R_k gate of the QTF."""
+    gate_name = 'Rk'
+    gate_name_latex = 'R'
+
+    def __new__(cls, *args):
+        if len(args) != 2:
+            raise QuantumError(
+                'Rk gates only take two arguments, got: %r' % args
+            )
+        # For small k, Rk gates simplify to other gates, using these
+        # substitutions give us familiar results for the QFT for small numbers
+        # of qubits.
+        target = args[0]
+        k = args[1]
+        if k == 1:
+            return ZGate(target)
+        elif k == 2:
+            return PhaseGate(target)
+        elif k == 3:
+            return TGate(target)
+        args = cls._eval_args(args)
+        inst = Expr.__new__(cls, *args)
+        inst.hilbert_space = cls._eval_hilbert_space(args)
+        return inst
+
+    @classmethod
+    def _eval_args(cls, args):
+        # Fall back to this, because Gate._eval_args assumes that args is
+        # all targets and can't contain duplicates.
+        return QExpr._eval_args(args)
+
+    @property
+    def k(self):
+        return self.label[1]
+
+    @property
+    def targets(self):
+        return self.label[:1]
+
+    @property
+    def gate_name_plot(self):
+        return r'$%s_%s$' % (self.gate_name_latex, str(self.k))
+
+    def get_target_matrix(self, format='sympy'):
+        if format == 'sympy':
+            return Matrix([[1, 0], [0, exp(sign(self.k)*Integer(2)*pi*I/(Integer(2)**abs(self.k)))]])
+        raise NotImplementedError(
+            'Invalid format for the R_k gate: %r' % format)
+
+
+Rk = RkGate
+
+
+class Fourier(Gate):
+    """Superclass of Quantum Fourier and Inverse Quantum Fourier Gates."""
+
+    @classmethod
+    def _eval_args(self, args):
+        if len(args) != 2:
+            raise QuantumError(
+                'QFT/IQFT only takes two arguments, got: %r' % args
+            )
+        if args[0] >= args[1]:
+            raise QuantumError("Start must be smaller than finish")
+        return Gate._eval_args(args)
+
+    def _represent_default_basis(self, **options):
+        return self._represent_ZGate(None, **options)
+
+    def _represent_ZGate(self, basis, **options):
+        """
+            Represents the (I)QFT In the Z Basis
+        """
+        nqubits = options.get('nqubits', 0)
+        if nqubits == 0:
+            raise QuantumError(
+                'The number of qubits must be given as nqubits.')
+        if nqubits < self.min_qubits:
+            raise QuantumError(
+                'The number of qubits %r is too small for the gate.' % nqubits
+            )
+        size = self.size
+        omega = self.omega
+
+        #Make a matrix that has the basic Fourier Transform Matrix
+        arrayFT = [[omega**(
+            i*j % size)/sqrt(size) for i in range(size)] for j in range(size)]
+        matrixFT = Matrix(arrayFT)
+
+        #Embed the FT Matrix in a higher space, if necessary
+        if self.label[0] != 0:
+            matrixFT = matrix_tensor_product(eye(2**self.label[0]), matrixFT)
+        if self.min_qubits < nqubits:
+            matrixFT = matrix_tensor_product(
+                matrixFT, eye(2**(nqubits - self.min_qubits)))
+
+        return matrixFT
+
+    @property
+    def targets(self):
+        return range(self.label[0], self.label[1])
+
+    @property
+    def min_qubits(self):
+        return self.label[1]
+
+    @property
+    def size(self):
+        """Size is the size of the QFT matrix"""
+        return 2**(self.label[1] - self.label[0])
+
+    @property
+    def omega(self):
+        return Symbol('omega')
+
+
+class QFT(Fourier):
+    """The forward quantum Fourier transform."""
+
+    gate_name = 'QFT'
+    gate_name_latex = 'QFT'
+
+    def decompose(self):
+        """Decomposes QFT into elementary gates."""
+        start = self.label[0]
+        finish = self.label[1]
+        circuit = 1
+        for level in reversed(range(start, finish)):
+            circuit = HadamardGate(level)*circuit
+            for i in range(level - start):
+                circuit = CGate(level - i - 1, RkGate(level, i + 2))*circuit
+        for i in range((finish - start)//2):
+            circuit = SwapGate(i + start, finish - i - 1)*circuit
+        return circuit
+
+    def _apply_operator_Qubit(self, qubits, **options):
+        return qapply(self.decompose()*qubits)
+
+    def _eval_inverse(self):
+        return IQFT(*self.args)
+
+    @property
+    def omega(self):
+        return exp(2*pi*I/self.size)
+
+
+class IQFT(Fourier):
+    """The inverse quantum Fourier transform."""
+
+    gate_name = 'IQFT'
+    gate_name_latex = '{QFT^{-1}}'
+
+    def decompose(self):
+        """Decomposes IQFT into elementary gates."""
+        start = self.args[0]
+        finish = self.args[1]
+        circuit = 1
+        for i in range((finish - start)//2):
+            circuit = SwapGate(i + start, finish - i - 1)*circuit
+        for level in range(start, finish):
+            for i in reversed(range(level - start)):
+                circuit = CGate(level - i - 1, RkGate(level, -i - 2))*circuit
+            circuit = HadamardGate(level)*circuit
+        return circuit
+
+    def _eval_inverse(self):
+        return QFT(*self.args)
+
+    @property
+    def omega(self):
+        return exp(-2*pi*I/self.size)

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/qubit.py

@@ -0,0 +1,811 @@
+"""Qubits for quantum computing.
+
+Todo:
+* Finish implementing measurement logic. This should include POVM.
+* Update docstrings.
+* Update tests.
+"""
+
+
+import math
+
+from sympy.core.add import Add
+from sympy.core.mul import Mul
+from sympy.core.numbers import Integer
+from sympy.core.power import Pow
+from sympy.core.singleton import S
+from sympy.functions.elementary.complexes import conjugate
+from sympy.functions.elementary.exponential import log
+from sympy.core.basic import _sympify
+from sympy.external.gmpy import SYMPY_INTS
+from sympy.matrices import Matrix, zeros
+from sympy.printing.pretty.stringpict import prettyForm
+
+from sympy.physics.quantum.hilbert import ComplexSpace
+from sympy.physics.quantum.state import Ket, Bra, State
+
+from sympy.physics.quantum.qexpr import QuantumError
+from sympy.physics.quantum.represent import represent
+from sympy.physics.quantum.matrixutils import (
+    numpy_ndarray, scipy_sparse_matrix
+)
+from mpmath.libmp.libintmath import bitcount
+
+__all__ = [
+    'Qubit',
+    'QubitBra',
+    'IntQubit',
+    'IntQubitBra',
+    'qubit_to_matrix',
+    'matrix_to_qubit',
+    'matrix_to_density',
+    'measure_all',
+    'measure_partial',
+    'measure_partial_oneshot',
+    'measure_all_oneshot'
+]
+
+#-----------------------------------------------------------------------------
+# Qubit Classes
+#-----------------------------------------------------------------------------
+
+
+class QubitState(State):
+    """Base class for Qubit and QubitBra."""
+
+    #-------------------------------------------------------------------------
+    # Initialization/creation
+    #-------------------------------------------------------------------------
+
+    @classmethod
+    def _eval_args(cls, args):
+        # If we are passed a QubitState or subclass, we just take its qubit
+        # values directly.
+        if len(args) == 1 and isinstance(args[0], QubitState):
+            return args[0].qubit_values
+
+        # Turn strings into tuple of strings
+        if len(args) == 1 and isinstance(args[0], str):
+            args = tuple( S.Zero if qb == "0" else S.One for qb in args[0])
+        else:
+            args = tuple( S.Zero if qb == "0" else S.One if qb == "1" else qb for qb in args)
+        args = tuple(_sympify(arg) for arg in args)
+
+        # Validate input (must have 0 or 1 input)
+        for element in args:
+            if element not in (S.Zero, S.One):
+                raise ValueError(
+                    "Qubit values must be 0 or 1, got: %r" % element)
+        return args
+
+    @classmethod
+    def _eval_hilbert_space(cls, args):
+        return ComplexSpace(2)**len(args)
+
+    #-------------------------------------------------------------------------
+    # Properties
+    #-------------------------------------------------------------------------
+
+    @property
+    def dimension(self):
+        """The number of Qubits in the state."""
+        return len(self.qubit_values)
+
+    @property
+    def nqubits(self):
+        return self.dimension
+
+    @property
+    def qubit_values(self):
+        """Returns the values of the qubits as a tuple."""
+        return self.label
+
+    #-------------------------------------------------------------------------
+    # Special methods
+    #-------------------------------------------------------------------------
+
+    def __len__(self):
+        return self.dimension
+
+    def __getitem__(self, bit):
+        return self.qubit_values[int(self.dimension - bit - 1)]
+
+    #-------------------------------------------------------------------------
+    # Utility methods
+    #-------------------------------------------------------------------------
+
+    def flip(self, *bits):
+        """Flip the bit(s) given."""
+        newargs = list(self.qubit_values)
+        for i in bits:
+            bit = int(self.dimension - i - 1)
+            if newargs[bit] == 1:
+                newargs[bit] = 0
+            else:
+                newargs[bit] = 1
+        return self.__class__(*tuple(newargs))
+
+
+class Qubit(QubitState, Ket):
+    """A multi-qubit ket in the computational (z) basis.
+
+    We use the normal convention that the least significant qubit is on the
+    right, so ``|00001>`` has a 1 in the least significant qubit.
+
+    Parameters
+    ==========
+
+    values : list, str
+        The qubit values as a list of ints ([0,0,0,1,1,]) or a string ('011').
+
+    Examples
+    ========
+
+    Create a qubit in a couple of different ways and look at their attributes:
+
+        >>> from sympy.physics.quantum.qubit import Qubit
+        >>> Qubit(0,0,0)
+        |000>
+        >>> q = Qubit('0101')
+        >>> q
+        |0101>
+
+        >>> q.nqubits
+        4
+        >>> len(q)
+        4
+        >>> q.dimension
+        4
+        >>> q.qubit_values
+        (0, 1, 0, 1)
+
+    We can flip the value of an individual qubit:
+
+        >>> q.flip(1)
+        |0111>
+
+    We can take the dagger of a Qubit to get a bra:
+
+        >>> from sympy.physics.quantum.dagger import Dagger
+        >>> Dagger(q)
+        <0101|
+        >>> type(Dagger(q))
+        <class 'sympy.physics.quantum.qubit.QubitBra'>
+
+    Inner products work as expected:
+
+        >>> ip = Dagger(q)*q
+        >>> ip
+        <0101|0101>
+        >>> ip.doit()
+        1
+    """
+
+    @classmethod
+    def dual_class(self):
+        return QubitBra
+
+    def _eval_innerproduct_QubitBra(self, bra, **hints):
+        if self.label == bra.label:
+            return S.One
+        else:
+            return S.Zero
+
+    def _represent_default_basis(self, **options):
+        return self._represent_ZGate(None, **options)
+
+    def _represent_ZGate(self, basis, **options):
+        """Represent this qubits in the computational basis (ZGate).
+        """
+        _format = options.get('format', 'sympy')
+        n = 1
+        definite_state = 0
+        for it in reversed(self.qubit_values):
+            definite_state += n*it
+            n = n*2
+        result = [0]*(2**self.dimension)
+        result[int(definite_state)] = 1
+        if _format == 'sympy':
+            return Matrix(result)
+        elif _format == 'numpy':
+            import numpy as np
+            return np.array(result, dtype='complex').transpose()
+        elif _format == 'scipy.sparse':
+            from scipy import sparse
+            return sparse.csr_matrix(result, dtype='complex').transpose()
+
+    def _eval_trace(self, bra, **kwargs):
+        indices = kwargs.get('indices', [])
+
+        #sort index list to begin trace from most-significant
+        #qubit
+        sorted_idx = list(indices)
+        if len(sorted_idx) == 0:
+            sorted_idx = list(range(0, self.nqubits))
+        sorted_idx.sort()
+
+        #trace out for each of index
+        new_mat = self*bra
+        for i in range(len(sorted_idx) - 1, -1, -1):
+            # start from tracing out from leftmost qubit
+            new_mat = self._reduced_density(new_mat, int(sorted_idx[i]))
+
+        if (len(sorted_idx) == self.nqubits):
+            #in case full trace was requested
+            return new_mat[0]
+        else:
+            return matrix_to_density(new_mat)
+
+    def _reduced_density(self, matrix, qubit, **options):
+        """Compute the reduced density matrix by tracing out one qubit.
+           The qubit argument should be of type Python int, since it is used
+           in bit operations
+        """
+        def find_index_that_is_projected(j, k, qubit):
+            bit_mask = 2**qubit - 1
+            return ((j >> qubit) << (1 + qubit)) + (j & bit_mask) + (k << qubit)
+
+        old_matrix = represent(matrix, **options)
+        old_size = old_matrix.cols
+        #we expect the old_size to be even
+        new_size = old_size//2
+        new_matrix = Matrix().zeros(new_size)
+
+        for i in range(new_size):
+            for j in range(new_size):
+                for k in range(2):
+                    col = find_index_that_is_projected(j, k, qubit)
+                    row = find_index_that_is_projected(i, k, qubit)
+                    new_matrix[i, j] += old_matrix[row, col]
+
+        return new_matrix
+
+
+class QubitBra(QubitState, Bra):
+    """A multi-qubit bra in the computational (z) basis.
+
+    We use the normal convention that the least significant qubit is on the
+    right, so ``|00001>`` has a 1 in the least significant qubit.
+
+    Parameters
+    ==========
+
+    values : list, str
+        The qubit values as a list of ints ([0,0,0,1,1,]) or a string ('011').
+
+    See also
+    ========
+
+    Qubit: Examples using qubits
+
+    """
+    @classmethod
+    def dual_class(self):
+        return Qubit
+
+
+class IntQubitState(QubitState):
+    """A base class for qubits that work with binary representations."""
+
+    @classmethod
+    def _eval_args(cls, args, nqubits=None):
+        # The case of a QubitState instance
+        if len(args) == 1 and isinstance(args[0], QubitState):
+            return QubitState._eval_args(args)
+        # otherwise, args should be integer
+        elif not all(isinstance(a, (int, Integer)) for a in args):
+            raise ValueError('values must be integers, got (%s)' % (tuple(type(a) for a in args),))
+        # use nqubits if specified
+        if nqubits is not None:
+            if not isinstance(nqubits, (int, Integer)):
+                raise ValueError('nqubits must be an integer, got (%s)' % type(nqubits))
+            if len(args) != 1:
+                raise ValueError(
+                    'too many positional arguments (%s). should be (number, nqubits=n)' % (args,))
+            return cls._eval_args_with_nqubits(args[0], nqubits)
+        # For a single argument, we construct the binary representation of
+        # that integer with the minimal number of bits.
+        if len(args) == 1 and args[0] > 1:
+            #rvalues is the minimum number of bits needed to express the number
+            rvalues = reversed(range(bitcount(abs(args[0]))))
+            qubit_values = [(args[0] >> i) & 1 for i in rvalues]
+            return QubitState._eval_args(qubit_values)
+        # For two numbers, the second number is the number of bits
+        # on which it is expressed, so IntQubit(0,5) == |00000>.
+        elif len(args) == 2 and args[1] > 1:
+            return cls._eval_args_with_nqubits(args[0], args[1])
+        else:
+            return QubitState._eval_args(args)
+
+    @classmethod
+    def _eval_args_with_nqubits(cls, number, nqubits):
+        need = bitcount(abs(number))
+        if nqubits < need:
+            raise ValueError(
+                'cannot represent %s with %s bits' % (number, nqubits))
+        qubit_values = [(number >> i) & 1 for i in reversed(range(nqubits))]
+        return QubitState._eval_args(qubit_values)
+
+    def as_int(self):
+        """Return the numerical value of the qubit."""
+        number = 0
+        n = 1
+        for i in reversed(self.qubit_values):
+            number += n*i
+            n = n << 1
+        return number
+
+    def _print_label(self, printer, *args):
+        return str(self.as_int())
+
+    def _print_label_pretty(self, printer, *args):
+        label = self._print_label(printer, *args)
+        return prettyForm(label)
+
+    _print_label_repr = _print_label
+    _print_label_latex = _print_label
+
+
+class IntQubit(IntQubitState, Qubit):
+    """A qubit ket that store integers as binary numbers in qubit values.
+
+    The differences between this class and ``Qubit`` are:
+
+    * The form of the constructor.
+    * The qubit values are printed as their corresponding integer, rather
+      than the raw qubit values. The internal storage format of the qubit
+      values in the same as ``Qubit``.
+
+    Parameters
+    ==========
+
+    values : int, tuple
+        If a single argument, the integer we want to represent in the qubit
+        values. This integer will be represented using the fewest possible
+        number of qubits.
+        If a pair of integers and the second value is more than one, the first
+        integer gives the integer to represent in binary form and the second
+        integer gives the number of qubits to use.
+        List of zeros and ones is also accepted to generate qubit by bit pattern.
+
+    nqubits : int
+        The integer that represents the number of qubits.
+        This number should be passed with keyword ``nqubits=N``.
+        You can use this in order to avoid ambiguity of Qubit-style tuple of bits.
+        Please see the example below for more details.
+
+    Examples
+    ========
+
+    Create a qubit for the integer 5:
+
+        >>> from sympy.physics.quantum.qubit import IntQubit
+        >>> from sympy.physics.quantum.qubit import Qubit
+        >>> q = IntQubit(5)
+        >>> q
+        |5>
+
+    We can also create an ``IntQubit`` by passing a ``Qubit`` instance.
+
+        >>> q = IntQubit(Qubit('101'))
+        >>> q
+        |5>
+        >>> q.as_int()
+        5
+        >>> q.nqubits
+        3
+        >>> q.qubit_values
+        (1, 0, 1)
+
+    We can go back to the regular qubit form.
+
+        >>> Qubit(q)
+        |101>
+
+    Please note that ``IntQubit`` also accepts a ``Qubit``-style list of bits.
+    So, the code below yields qubits 3, not a single bit ``1``.
+
+        >>> IntQubit(1, 1)
+        |3>
+
+    To avoid ambiguity, use ``nqubits`` parameter.
+    Use of this keyword is recommended especially when you provide the values by variables.
+
+        >>> IntQubit(1, nqubits=1)
+        |1>
+        >>> a = 1
+        >>> IntQubit(a, nqubits=1)
+        |1>
+    """
+    @classmethod
+    def dual_class(self):
+        return IntQubitBra
+
+    def _eval_innerproduct_IntQubitBra(self, bra, **hints):
+        return Qubit._eval_innerproduct_QubitBra(self, bra)
+
+class IntQubitBra(IntQubitState, QubitBra):
+    """A qubit bra that store integers as binary numbers in qubit values."""
+
+    @classmethod
+    def dual_class(self):
+        return IntQubit
+
+
+#-----------------------------------------------------------------------------
+# Qubit <---> Matrix conversion functions
+#-----------------------------------------------------------------------------
+
+
+def matrix_to_qubit(matrix):
+    """Convert from the matrix repr. to a sum of Qubit objects.
+
+    Parameters
+    ----------
+    matrix : Matrix, numpy.matrix, scipy.sparse
+        The matrix to build the Qubit representation of. This works with
+        SymPy matrices, numpy matrices and scipy.sparse sparse matrices.
+
+    Examples
+    ========
+
+    Represent a state and then go back to its qubit form:
+
+        >>> from sympy.physics.quantum.qubit import matrix_to_qubit, Qubit
+        >>> from sympy.physics.quantum.represent import represent
+        >>> q = Qubit('01')
+        >>> matrix_to_qubit(represent(q))
+        |01>
+    """
+    # Determine the format based on the type of the input matrix
+    format = 'sympy'
+    if isinstance(matrix, numpy_ndarray):
+        format = 'numpy'
+    if isinstance(matrix, scipy_sparse_matrix):
+        format = 'scipy.sparse'
+
+    # Make sure it is of correct dimensions for a Qubit-matrix representation.
+    # This logic should work with sympy, numpy or scipy.sparse matrices.
+    if matrix.shape[0] == 1:
+        mlistlen = matrix.shape[1]
+        nqubits = log(mlistlen, 2)
+        ket = False
+        cls = QubitBra
+    elif matrix.shape[1] == 1:
+        mlistlen = matrix.shape[0]
+        nqubits = log(mlistlen, 2)
+        ket = True
+        cls = Qubit
+    else:
+        raise QuantumError(
+            'Matrix must be a row/column vector, got %r' % matrix
+        )
+    if not isinstance(nqubits, Integer):
+        raise QuantumError('Matrix must be a row/column vector of size '
+                           '2**nqubits, got: %r' % matrix)
+    # Go through each item in matrix, if element is non-zero, make it into a
+    # Qubit item times the element.
+    result = 0
+    for i in range(mlistlen):
+        if ket:
+            element = matrix[i, 0]
+        else:
+            element = matrix[0, i]
+        if format in ('numpy', 'scipy.sparse'):
+            element = complex(element)
+        if element:
+            # Form Qubit array; 0 in bit-locations where i is 0, 1 in
+            # bit-locations where i is 1
+            qubit_array = [int(i & (1 << x) != 0) for x in range(nqubits)]
+            qubit_array.reverse()
+            result = result + element*cls(*qubit_array)
+
+    # If SymPy simplified by pulling out a constant coefficient, undo that.
+    if isinstance(result, (Mul, Add, Pow)):
+        result = result.expand()
+
+    return result
+
+
+def matrix_to_density(mat):
+    """
+    Works by finding the eigenvectors and eigenvalues of the matrix.
+    We know we can decompose rho by doing:
+    sum(EigenVal*|Eigenvect><Eigenvect|)
+    """
+    from sympy.physics.quantum.density import Density
+    eigen = mat.eigenvects()
+    args = [[matrix_to_qubit(Matrix(
+        [vector, ])), x[0]] for x in eigen for vector in x[2] if x[0] != 0]
+    if (len(args) == 0):
+        return S.Zero
+    else:
+        return Density(*args)
+
+
+def qubit_to_matrix(qubit, format='sympy'):
+    """Converts an Add/Mul of Qubit objects into it's matrix representation
+
+    This function is the inverse of ``matrix_to_qubit`` and is a shorthand
+    for ``represent(qubit)``.
+    """
+    return represent(qubit, format=format)
+
+
+#-----------------------------------------------------------------------------
+# Measurement
+#-----------------------------------------------------------------------------
+
+
+def measure_all(qubit, format='sympy', normalize=True):
+    """Perform an ensemble measurement of all qubits.
+
+    Parameters
+    ==========
+
+    qubit : Qubit, Add
+        The qubit to measure. This can be any Qubit or a linear combination
+        of them.
+    format : str
+        The format of the intermediate matrices to use. Possible values are
+        ('sympy','numpy','scipy.sparse'). Currently only 'sympy' is
+        implemented.
+
+    Returns
+    =======
+
+    result : list
+        A list that consists of primitive states and their probabilities.
+
+    Examples
+    ========
+
+        >>> from sympy.physics.quantum.qubit import Qubit, measure_all
+        >>> from sympy.physics.quantum.gate import H
+        >>> from sympy.physics.quantum.qapply import qapply
+
+        >>> c = H(0)*H(1)*Qubit('00')
+        >>> c
+        H(0)*H(1)*|00>
+        >>> q = qapply(c)
+        >>> measure_all(q)
+        [(|00>, 1/4), (|01>, 1/4), (|10>, 1/4), (|11>, 1/4)]
+    """
+    m = qubit_to_matrix(qubit, format)
+
+    if format == 'sympy':
+        results = []
+
+        if normalize:
+            m = m.normalized()
+
+        size = max(m.shape)  # Max of shape to account for bra or ket
+        nqubits = int(math.log(size)/math.log(2))
+        for i in range(size):
+            if m[i]:
+                results.append(
+                    (Qubit(IntQubit(i, nqubits=nqubits)), m[i]*conjugate(m[i]))
+                )
+        return results
+    else:
+        raise NotImplementedError(
+            "This function cannot handle non-SymPy matrix formats yet"
+        )
+
+
+def measure_partial(qubit, bits, format='sympy', normalize=True):
+    """Perform a partial ensemble measure on the specified qubits.
+
+    Parameters
+    ==========
+
+    qubits : Qubit
+        The qubit to measure.  This can be any Qubit or a linear combination
+        of them.
+    bits : tuple
+        The qubits to measure.
+    format : str
+        The format of the intermediate matrices to use. Possible values are
+        ('sympy','numpy','scipy.sparse'). Currently only 'sympy' is
+        implemented.
+
+    Returns
+    =======
+
+    result : list
+        A list that consists of primitive states and their probabilities.
+
+    Examples
+    ========
+
+        >>> from sympy.physics.quantum.qubit import Qubit, measure_partial
+        >>> from sympy.physics.quantum.gate import H
+        >>> from sympy.physics.quantum.qapply import qapply
+
+        >>> c = H(0)*H(1)*Qubit('00')
+        >>> c
+        H(0)*H(1)*|00>
+        >>> q = qapply(c)
+        >>> measure_partial(q, (0,))
+        [(sqrt(2)*|00>/2 + sqrt(2)*|10>/2, 1/2), (sqrt(2)*|01>/2 + sqrt(2)*|11>/2, 1/2)]
+    """
+    m = qubit_to_matrix(qubit, format)
+
+    if isinstance(bits, (SYMPY_INTS, Integer)):
+        bits = (int(bits),)
+
+    if format == 'sympy':
+        if normalize:
+            m = m.normalized()
+
+        possible_outcomes = _get_possible_outcomes(m, bits)
+
+        # Form output from function.
+        output = []
+        for outcome in possible_outcomes:
+            # Calculate probability of finding the specified bits with
+            # given values.
+            prob_of_outcome = 0
+            prob_of_outcome += (outcome.H*outcome)[0]
+
+            # If the output has a chance, append it to output with found
+            # probability.
+            if prob_of_outcome != 0:
+                if normalize:
+                    next_matrix = matrix_to_qubit(outcome.normalized())
+                else:
+                    next_matrix = matrix_to_qubit(outcome)
+
+                output.append((
+                    next_matrix,
+                    prob_of_outcome
+                ))
+
+        return output
+    else:
+        raise NotImplementedError(
+            "This function cannot handle non-SymPy matrix formats yet"
+        )
+
+
+def measure_partial_oneshot(qubit, bits, format='sympy'):
+    """Perform a partial oneshot measurement on the specified qubits.
+
+    A oneshot measurement is equivalent to performing a measurement on a
+    quantum system. This type of measurement does not return the probabilities
+    like an ensemble measurement does, but rather returns *one* of the
+    possible resulting states. The exact state that is returned is determined
+    by picking a state randomly according to the ensemble probabilities.
+
+    Parameters
+    ----------
+    qubits : Qubit
+        The qubit to measure.  This can be any Qubit or a linear combination
+        of them.
+    bits : tuple
+        The qubits to measure.
+    format : str
+        The format of the intermediate matrices to use. Possible values are
+        ('sympy','numpy','scipy.sparse'). Currently only 'sympy' is
+        implemented.
+
+    Returns
+    -------
+    result : Qubit
+        The qubit that the system collapsed to upon measurement.
+    """
+    import random
+    m = qubit_to_matrix(qubit, format)
+
+    if format == 'sympy':
+        m = m.normalized()
+        possible_outcomes = _get_possible_outcomes(m, bits)
+
+        # Form output from function
+        random_number = random.random()
+        total_prob = 0
+        for outcome in possible_outcomes:
+            # Calculate probability of finding the specified bits
+            # with given values
+            total_prob += (outcome.H*outcome)[0]
+            if total_prob >= random_number:
+                return matrix_to_qubit(outcome.normalized())
+    else:
+        raise NotImplementedError(
+            "This function cannot handle non-SymPy matrix formats yet"
+        )
+
+
+def _get_possible_outcomes(m, bits):
+    """Get the possible states that can be produced in a measurement.
+
+    Parameters
+    ----------
+    m : Matrix
+        The matrix representing the state of the system.
+    bits : tuple, list
+        Which bits will be measured.
+
+    Returns
+    -------
+    result : list
+        The list of possible states which can occur given this measurement.
+        These are un-normalized so we can derive the probability of finding
+        this state by taking the inner product with itself
+    """
+
+    # This is filled with loads of dirty binary tricks...You have been warned
+
+    size = max(m.shape)  # Max of shape to account for bra or ket
+    nqubits = int(math.log2(size) + .1)  # Number of qubits possible
+
+    # Make the output states and put in output_matrices, nothing in them now.
+    # Each state will represent a possible outcome of the measurement
+    # Thus, output_matrices[0] is the matrix which we get when all measured
+    # bits return 0. and output_matrices[1] is the matrix for only the 0th
+    # bit being true
+    output_matrices = []
+    for i in range(1 << len(bits)):
+        output_matrices.append(zeros(2**nqubits, 1))
+
+    # Bitmasks will help sort how to determine possible outcomes.
+    # When the bit mask is and-ed with a matrix-index,
+    # it will determine which state that index belongs to
+    bit_masks = []
+    for bit in bits:
+        bit_masks.append(1 << bit)
+
+    # Make possible outcome states
+    for i in range(2**nqubits):
+        trueness = 0  # This tells us to which output_matrix this value belongs
+        # Find trueness
+        for j in range(len(bit_masks)):
+            if i & bit_masks[j]:
+                trueness += j + 1
+        # Put the value in the correct output matrix
+        output_matrices[trueness][i] = m[i]
+    return output_matrices
+
+
+def measure_all_oneshot(qubit, format='sympy'):
+    """Perform a oneshot ensemble measurement on all qubits.
+
+    A oneshot measurement is equivalent to performing a measurement on a
+    quantum system. This type of measurement does not return the probabilities
+    like an ensemble measurement does, but rather returns *one* of the
+    possible resulting states. The exact state that is returned is determined
+    by picking a state randomly according to the ensemble probabilities.
+
+    Parameters
+    ----------
+    qubits : Qubit
+        The qubit to measure.  This can be any Qubit or a linear combination
+        of them.
+    format : str
+        The format of the intermediate matrices to use. Possible values are
+        ('sympy','numpy','scipy.sparse'). Currently only 'sympy' is
+        implemented.
+
+    Returns
+    -------
+    result : Qubit
+        The qubit that the system collapsed to upon measurement.
+    """
+    import random
+    m = qubit_to_matrix(qubit)
+
+    if format == 'sympy':
+        m = m.normalized()
+        random_number = random.random()
+        total = 0
+        result = 0
+        for i in m:
+            total += i*i.conjugate()
+            if total > random_number:
+                break
+            result += 1
+        return Qubit(IntQubit(result, nqubits=int(math.log2(max(m.shape)) + .1)))
+    else:
+        raise NotImplementedError(
+            "This function cannot handle non-SymPy matrix formats yet"
+        )

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/represent.py

@@ -0,0 +1,574 @@
+"""Logic for representing operators in state in various bases.
+
+TODO:
+
+* Get represent working with continuous hilbert spaces.
+* Document default basis functionality.
+"""
+
+from sympy.core.add import Add
+from sympy.core.expr import Expr
+from sympy.core.mul import Mul
+from sympy.core.numbers import I
+from sympy.core.power import Pow
+from sympy.integrals.integrals import integrate
+from sympy.physics.quantum.dagger import Dagger
+from sympy.physics.quantum.commutator import Commutator
+from sympy.physics.quantum.anticommutator import AntiCommutator
+from sympy.physics.quantum.innerproduct import InnerProduct
+from sympy.physics.quantum.qexpr import QExpr
+from sympy.physics.quantum.tensorproduct import TensorProduct
+from sympy.physics.quantum.matrixutils import flatten_scalar
+from sympy.physics.quantum.state import KetBase, BraBase, StateBase
+from sympy.physics.quantum.operator import Operator, OuterProduct
+from sympy.physics.quantum.qapply import qapply
+from sympy.physics.quantum.operatorset import operators_to_state, state_to_operators
+
+
+__all__ = [
+    'represent',
+    'rep_innerproduct',
+    'rep_expectation',
+    'integrate_result',
+    'get_basis',
+    'enumerate_states'
+]
+
+#-----------------------------------------------------------------------------
+# Represent
+#-----------------------------------------------------------------------------
+
+
+def _sympy_to_scalar(e):
+    """Convert from a SymPy scalar to a Python scalar."""
+    if isinstance(e, Expr):
+        if e.is_Integer:
+            return int(e)
+        elif e.is_Float:
+            return float(e)
+        elif e.is_Rational:
+            return float(e)
+        elif e.is_Number or e.is_NumberSymbol or e == I:
+            return complex(e)
+    raise TypeError('Expected number, got: %r' % e)
+
+
+def represent(expr, **options):
+    """Represent the quantum expression in the given basis.
+
+    In quantum mechanics abstract states and operators can be represented in
+    various basis sets. Under this operation the follow transforms happen:
+
+    * Ket -> column vector or function
+    * Bra -> row vector of function
+    * Operator -> matrix or differential operator
+
+    This function is the top-level interface for this action.
+
+    This function walks the SymPy expression tree looking for ``QExpr``
+    instances that have a ``_represent`` method. This method is then called
+    and the object is replaced by the representation returned by this method.
+    By default, the ``_represent`` method will dispatch to other methods
+    that handle the representation logic for a particular basis set. The
+    naming convention for these methods is the following::
+
+        def _represent_FooBasis(self, e, basis, **options)
+
+    This function will have the logic for representing instances of its class
+    in the basis set having a class named ``FooBasis``.
+
+    Parameters
+    ==========
+
+    expr  : Expr
+        The expression to represent.
+    basis : Operator, basis set
+        An object that contains the information about the basis set. If an
+        operator is used, the basis is assumed to be the orthonormal
+        eigenvectors of that operator. In general though, the basis argument
+        can be any object that contains the basis set information.
+    options : dict
+        Key/value pairs of options that are passed to the underlying method
+        that finds the representation. These options can be used to
+        control how the representation is done. For example, this is where
+        the size of the basis set would be set.
+
+    Returns
+    =======
+
+    e : Expr
+        The SymPy expression of the represented quantum expression.
+
+    Examples
+    ========
+
+    Here we subclass ``Operator`` and ``Ket`` to create the z-spin operator
+    and its spin 1/2 up eigenstate. By defining the ``_represent_SzOp``
+    method, the ket can be represented in the z-spin basis.
+
+    >>> from sympy.physics.quantum import Operator, represent, Ket
+    >>> from sympy import Matrix
+
+    >>> class SzUpKet(Ket):
+    ...     def _represent_SzOp(self, basis, **options):
+    ...         return Matrix([1,0])
+    ...
+    >>> class SzOp(Operator):
+    ...     pass
+    ...
+    >>> sz = SzOp('Sz')
+    >>> up = SzUpKet('up')
+    >>> represent(up, basis=sz)
+    Matrix([
+    [1],
+    [0]])
+
+    Here we see an example of representations in a continuous
+    basis. We see that the result of representing various combinations
+    of cartesian position operators and kets give us continuous
+    expressions involving DiracDelta functions.
+
+    >>> from sympy.physics.quantum.cartesian import XOp, XKet, XBra
+    >>> X = XOp()
+    >>> x = XKet()
+    >>> y = XBra('y')
+    >>> represent(X*x)
+    x*DiracDelta(x - x_2)
+    """
+
+    format = options.get('format', 'sympy')
+    if format == 'numpy':
+        import numpy as np
+    if isinstance(expr, QExpr) and not isinstance(expr, OuterProduct):
+        options['replace_none'] = False
+        temp_basis = get_basis(expr, **options)
+        if temp_basis is not None:
+            options['basis'] = temp_basis
+        try:
+            return expr._represent(**options)
+        except NotImplementedError as strerr:
+            #If no _represent_FOO method exists, map to the
+            #appropriate basis state and try
+            #the other methods of representation
+            options['replace_none'] = True
+
+            if isinstance(expr, (KetBase, BraBase)):
+                try:
+                    return rep_innerproduct(expr, **options)
+                except NotImplementedError:
+                    raise NotImplementedError(strerr)
+            elif isinstance(expr, Operator):
+                try:
+                    return rep_expectation(expr, **options)
+                except NotImplementedError:
+                    raise NotImplementedError(strerr)
+            else:
+                raise NotImplementedError(strerr)
+    elif isinstance(expr, Add):
+        result = represent(expr.args[0], **options)
+        for args in expr.args[1:]:
+            # scipy.sparse doesn't support += so we use plain = here.
+            result = result + represent(args, **options)
+        return result
+    elif isinstance(expr, Pow):
+        base, exp = expr.as_base_exp()
+        if format in ('numpy', 'scipy.sparse'):
+            exp = _sympy_to_scalar(exp)
+        base = represent(base, **options)
+        # scipy.sparse doesn't support negative exponents
+        # and warns when inverting a matrix in csr format.
+        if format == 'scipy.sparse' and exp < 0:
+            from scipy.sparse.linalg import inv
+            exp = - exp
+            base = inv(base.tocsc()).tocsr()
+        if format == 'numpy':
+            return np.linalg.matrix_power(base, exp)
+        return base ** exp
+    elif isinstance(expr, TensorProduct):
+        new_args = [represent(arg, **options) for arg in expr.args]
+        return TensorProduct(*new_args)
+    elif isinstance(expr, Dagger):
+        return Dagger(represent(expr.args[0], **options))
+    elif isinstance(expr, Commutator):
+        A = expr.args[0]
+        B = expr.args[1]
+        return represent(Mul(A, B) - Mul(B, A), **options)
+    elif isinstance(expr, AntiCommutator):
+        A = expr.args[0]
+        B = expr.args[1]
+        return represent(Mul(A, B) + Mul(B, A), **options)
+    elif not isinstance(expr, (Mul, OuterProduct, InnerProduct)):
+        # We have removed special handling of inner products that used to be
+        # required (before automatic transforms).
+        # For numpy and scipy.sparse, we can only handle numerical prefactors.
+        if format in ('numpy', 'scipy.sparse'):
+            return _sympy_to_scalar(expr)
+        return expr
+
+    if not isinstance(expr, (Mul, OuterProduct, InnerProduct)):
+        raise TypeError('Mul expected, got: %r' % expr)
+
+    if "index" in options:
+        options["index"] += 1
+    else:
+        options["index"] = 1
+
+    if "unities" not in options:
+        options["unities"] = []
+
+    result = represent(expr.args[-1], **options)
+    last_arg = expr.args[-1]
+
+    for arg in reversed(expr.args[:-1]):
+        if isinstance(last_arg, Operator):
+            options["index"] += 1
+            options["unities"].append(options["index"])
+        elif isinstance(last_arg, BraBase) and isinstance(arg, KetBase):
+            options["index"] += 1
+        elif isinstance(last_arg, KetBase) and isinstance(arg, Operator):
+            options["unities"].append(options["index"])
+        elif isinstance(last_arg, KetBase) and isinstance(arg, BraBase):
+            options["unities"].append(options["index"])
+
+        next_arg = represent(arg, **options)
+        if format == 'numpy' and isinstance(next_arg, np.ndarray):
+            # Must use np.matmult to "matrix multiply" two np.ndarray
+            result = np.matmul(next_arg, result)
+        else:
+            result = next_arg*result
+        last_arg = arg
+
+    # All three matrix formats create 1 by 1 matrices when inner products of
+    # vectors are taken. In these cases, we simply return a scalar.
+    result = flatten_scalar(result)
+
+    result = integrate_result(expr, result, **options)
+
+    return result
+
+
+def rep_innerproduct(expr, **options):
+    """
+    Returns an innerproduct like representation (e.g. ``<x'|x>``) for the
+    given state.
+
+    Attempts to calculate inner product with a bra from the specified
+    basis. Should only be passed an instance of KetBase or BraBase
+
+    Parameters
+    ==========
+
+    expr : KetBase or BraBase
+        The expression to be represented
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum.represent import rep_innerproduct
+    >>> from sympy.physics.quantum.cartesian import XOp, XKet, PxOp, PxKet
+    >>> rep_innerproduct(XKet())
+    DiracDelta(x - x_1)
+    >>> rep_innerproduct(XKet(), basis=PxOp())
+    sqrt(2)*exp(-I*px_1*x/hbar)/(2*sqrt(hbar)*sqrt(pi))
+    >>> rep_innerproduct(PxKet(), basis=XOp())
+    sqrt(2)*exp(I*px*x_1/hbar)/(2*sqrt(hbar)*sqrt(pi))
+
+    """
+
+    if not isinstance(expr, (KetBase, BraBase)):
+        raise TypeError("expr passed is not a Bra or Ket")
+
+    basis = get_basis(expr, **options)
+
+    if not isinstance(basis, StateBase):
+        raise NotImplementedError("Can't form this representation!")
+
+    if "index" not in options:
+        options["index"] = 1
+
+    basis_kets = enumerate_states(basis, options["index"], 2)
+
+    if isinstance(expr, BraBase):
+        bra = expr
+        ket = (basis_kets[1] if basis_kets[0].dual == expr else basis_kets[0])
+    else:
+        bra = (basis_kets[1].dual if basis_kets[0]
+               == expr else basis_kets[0].dual)
+        ket = expr
+
+    prod = InnerProduct(bra, ket)
+    result = prod.doit()
+
+    format = options.get('format', 'sympy')
+    result = expr._format_represent(result, format)
+    return result
+
+
+def rep_expectation(expr, **options):
+    """
+    Returns an ``<x'|A|x>`` type representation for the given operator.
+
+    Parameters
+    ==========
+
+    expr : Operator
+        Operator to be represented in the specified basis
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum.cartesian import XOp, PxOp, PxKet
+    >>> from sympy.physics.quantum.represent import rep_expectation
+    >>> rep_expectation(XOp())
+    x_1*DiracDelta(x_1 - x_2)
+    >>> rep_expectation(XOp(), basis=PxOp())
+    <px_2|*X*|px_1>
+    >>> rep_expectation(XOp(), basis=PxKet())
+    <px_2|*X*|px_1>
+
+    """
+
+    if "index" not in options:
+        options["index"] = 1
+
+    if not isinstance(expr, Operator):
+        raise TypeError("The passed expression is not an operator")
+
+    basis_state = get_basis(expr, **options)
+
+    if basis_state is None or not isinstance(basis_state, StateBase):
+        raise NotImplementedError("Could not get basis kets for this operator")
+
+    basis_kets = enumerate_states(basis_state, options["index"], 2)
+
+    bra = basis_kets[1].dual
+    ket = basis_kets[0]
+
+    result = qapply(bra*expr*ket)
+    return result
+
+
+def integrate_result(orig_expr, result, **options):
+    """
+    Returns the result of integrating over any unities ``(|x><x|)`` in
+    the given expression. Intended for integrating over the result of
+    representations in continuous bases.
+
+    This function integrates over any unities that may have been
+    inserted into the quantum expression and returns the result.
+    It uses the interval of the Hilbert space of the basis state
+    passed to it in order to figure out the limits of integration.
+    The unities option must be
+    specified for this to work.
+
+    Note: This is mostly used internally by represent(). Examples are
+    given merely to show the use cases.
+
+    Parameters
+    ==========
+
+    orig_expr : quantum expression
+        The original expression which was to be represented
+
+    result: Expr
+        The resulting representation that we wish to integrate over
+
+    Examples
+    ========
+
+    >>> from sympy import symbols, DiracDelta
+    >>> from sympy.physics.quantum.represent import integrate_result
+    >>> from sympy.physics.quantum.cartesian import XOp, XKet
+    >>> x_ket = XKet()
+    >>> X_op = XOp()
+    >>> x, x_1, x_2 = symbols('x, x_1, x_2')
+    >>> integrate_result(X_op*x_ket, x*DiracDelta(x-x_1)*DiracDelta(x_1-x_2))
+    x*DiracDelta(x - x_1)*DiracDelta(x_1 - x_2)
+    >>> integrate_result(X_op*x_ket, x*DiracDelta(x-x_1)*DiracDelta(x_1-x_2),
+    ...     unities=[1])
+    x*DiracDelta(x - x_2)
+
+    """
+    if not isinstance(result, Expr):
+        return result
+
+    options['replace_none'] = True
+    if "basis" not in options:
+        arg = orig_expr.args[-1]
+        options["basis"] = get_basis(arg, **options)
+    elif not isinstance(options["basis"], StateBase):
+        options["basis"] = get_basis(orig_expr, **options)
+
+    basis = options.pop("basis", None)
+
+    if basis is None:
+        return result
+
+    unities = options.pop("unities", [])
+
+    if len(unities) == 0:
+        return result
+
+    kets = enumerate_states(basis, unities)
+    coords = [k.label[0] for k in kets]
+
+    for coord in coords:
+        if coord in result.free_symbols:
+            #TODO: Add support for sets of operators
+            basis_op = state_to_operators(basis)
+            start = basis_op.hilbert_space.interval.start
+            end = basis_op.hilbert_space.interval.end
+            result = integrate(result, (coord, start, end))
+
+    return result
+
+
+def get_basis(expr, *, basis=None, replace_none=True, **options):
+    """
+    Returns a basis state instance corresponding to the basis specified in
+    options=s. If no basis is specified, the function tries to form a default
+    basis state of the given expression.
+
+    There are three behaviors:
+
+    1. The basis specified in options is already an instance of StateBase. If
+       this is the case, it is simply returned. If the class is specified but
+       not an instance, a default instance is returned.
+
+    2. The basis specified is an operator or set of operators. If this
+       is the case, the operator_to_state mapping method is used.
+
+    3. No basis is specified. If expr is a state, then a default instance of
+       its class is returned.  If expr is an operator, then it is mapped to the
+       corresponding state.  If it is neither, then we cannot obtain the basis
+       state.
+
+    If the basis cannot be mapped, then it is not changed.
+
+    This will be called from within represent, and represent will
+    only pass QExpr's.
+
+    TODO (?): Support for Muls and other types of expressions?
+
+    Parameters
+    ==========
+
+    expr : Operator or StateBase
+        Expression whose basis is sought
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum.represent import get_basis
+    >>> from sympy.physics.quantum.cartesian import XOp, XKet, PxOp, PxKet
+    >>> x = XKet()
+    >>> X = XOp()
+    >>> get_basis(x)
+    |x>
+    >>> get_basis(X)
+    |x>
+    >>> get_basis(x, basis=PxOp())
+    |px>
+    >>> get_basis(x, basis=PxKet)
+    |px>
+
+    """
+
+    if basis is None and not replace_none:
+        return None
+
+    if basis is None:
+        if isinstance(expr, KetBase):
+            return _make_default(expr.__class__)
+        elif isinstance(expr, BraBase):
+            return _make_default(expr.dual_class())
+        elif isinstance(expr, Operator):
+            state_inst = operators_to_state(expr)
+            return (state_inst if state_inst is not None else None)
+        else:
+            return None
+    elif (isinstance(basis, Operator) or
+          (not isinstance(basis, StateBase) and issubclass(basis, Operator))):
+        state = operators_to_state(basis)
+        if state is None:
+            return None
+        elif isinstance(state, StateBase):
+            return state
+        else:
+            return _make_default(state)
+    elif isinstance(basis, StateBase):
+        return basis
+    elif issubclass(basis, StateBase):
+        return _make_default(basis)
+    else:
+        return None
+
+
+def _make_default(expr):
+    # XXX: Catching TypeError like this is a bad way of distinguishing
+    # instances from classes. The logic using this function should be
+    # rewritten somehow.
+    try:
+        expr = expr()
+    except TypeError:
+        return expr
+
+    return expr
+
+
+def enumerate_states(*args, **options):
+    """
+    Returns instances of the given state with dummy indices appended
+
+    Operates in two different modes:
+
+    1. Two arguments are passed to it. The first is the base state which is to
+       be indexed, and the second argument is a list of indices to append.
+
+    2. Three arguments are passed. The first is again the base state to be
+       indexed. The second is the start index for counting.  The final argument
+       is the number of kets you wish to receive.
+
+    Tries to call state._enumerate_state. If this fails, returns an empty list
+
+    Parameters
+    ==========
+
+    args : list
+        See list of operation modes above for explanation
+
+    Examples
+    ========
+
+    >>> from sympy.physics.quantum.cartesian import XBra, XKet
+    >>> from sympy.physics.quantum.represent import enumerate_states
+    >>> test = XKet('foo')
+    >>> enumerate_states(test, 1, 3)
+    [|foo_1>, |foo_2>, |foo_3>]
+    >>> test2 = XBra('bar')
+    >>> enumerate_states(test2, [4, 5, 10])
+    [<bar_4|, <bar_5|, <bar_10|]
+
+    """
+
+    state = args[0]
+
+    if len(args) not in (2, 3):
+        raise NotImplementedError("Wrong number of arguments!")
+
+    if not isinstance(state, StateBase):
+        raise TypeError("First argument is not a state!")
+
+    if len(args) == 3:
+        num_states = args[2]
+        options['start_index'] = args[1]
+    else:
+        num_states = len(args[1])
+        options['index_list'] = args[1]
+
+    try:
+        ret = state._enumerate_state(num_states, **options)
+    except NotImplementedError:
+        ret = []
+
+    return ret

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/sho1d.py

@@ -0,0 +1,679 @@
+"""Simple Harmonic Oscillator 1-Dimension"""
+
+from sympy.core.numbers import (I, Integer)
+from sympy.core.singleton import S
+from sympy.core.symbol import Symbol
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.physics.quantum.constants import hbar
+from sympy.physics.quantum.operator import Operator
+from sympy.physics.quantum.state import Bra, Ket, State
+from sympy.physics.quantum.qexpr import QExpr
+from sympy.physics.quantum.cartesian import X, Px
+from sympy.functions.special.tensor_functions import KroneckerDelta
+from sympy.physics.quantum.hilbert import ComplexSpace
+from sympy.physics.quantum.matrixutils import matrix_zeros
+
+#------------------------------------------------------------------------------
+
+class SHOOp(Operator):
+    """A base class for the SHO Operators.
+
+    We are limiting the number of arguments to be 1.
+
+    """
+
+    @classmethod
+    def _eval_args(cls, args):
+        args = QExpr._eval_args(args)
+        if len(args) == 1:
+            return args
+        else:
+            raise ValueError("Too many arguments")
+
+    @classmethod
+    def _eval_hilbert_space(cls, label):
+        return ComplexSpace(S.Infinity)
+
+class RaisingOp(SHOOp):
+    """The Raising Operator or a^dagger.
+
+    When a^dagger acts on a state it raises the state up by one. Taking
+    the adjoint of a^dagger returns 'a', the Lowering Operator. a^dagger
+    can be rewritten in terms of position and momentum. We can represent
+    a^dagger as a matrix, which will be its default basis.
+
+    Parameters
+    ==========
+
+    args : tuple
+        The list of numbers or parameters that uniquely specify the
+        operator.
+
+    Examples
+    ========
+
+    Create a Raising Operator and rewrite it in terms of position and
+    momentum, and show that taking its adjoint returns 'a':
+
+        >>> from sympy.physics.quantum.sho1d import RaisingOp
+        >>> from sympy.physics.quantum import Dagger
+
+        >>> ad = RaisingOp('a')
+        >>> ad.rewrite('xp').doit()
+        sqrt(2)*(m*omega*X - I*Px)/(2*sqrt(hbar)*sqrt(m*omega))
+
+        >>> Dagger(ad)
+        a
+
+    Taking the commutator of a^dagger with other Operators:
+
+        >>> from sympy.physics.quantum import Commutator
+        >>> from sympy.physics.quantum.sho1d import RaisingOp, LoweringOp
+        >>> from sympy.physics.quantum.sho1d import NumberOp
+
+        >>> ad = RaisingOp('a')
+        >>> a = LoweringOp('a')
+        >>> N = NumberOp('N')
+        >>> Commutator(ad, a).doit()
+        -1
+        >>> Commutator(ad, N).doit()
+        -RaisingOp(a)
+
+    Apply a^dagger to a state:
+
+        >>> from sympy.physics.quantum import qapply
+        >>> from sympy.physics.quantum.sho1d import RaisingOp, SHOKet
+
+        >>> ad = RaisingOp('a')
+        >>> k = SHOKet('k')
+        >>> qapply(ad*k)
+        sqrt(k + 1)*|k + 1>
+
+    Matrix Representation
+
+        >>> from sympy.physics.quantum.sho1d import RaisingOp
+        >>> from sympy.physics.quantum.represent import represent
+        >>> ad = RaisingOp('a')
+        >>> represent(ad, basis=N, ndim=4, format='sympy')
+        Matrix([
+        [0,       0,       0, 0],
+        [1,       0,       0, 0],
+        [0, sqrt(2),       0, 0],
+        [0,       0, sqrt(3), 0]])
+
+    """
+
+    def _eval_rewrite_as_xp(self, *args, **kwargs):
+        return (S.One/sqrt(Integer(2)*hbar*m*omega))*(
+            S.NegativeOne*I*Px + m*omega*X)
+
+    def _eval_adjoint(self):
+        return LoweringOp(*self.args)
+
+    def _eval_commutator_LoweringOp(self, other):
+        return S.NegativeOne
+
+    def _eval_commutator_NumberOp(self, other):
+        return S.NegativeOne*self
+
+    def _apply_operator_SHOKet(self, ket, **options):
+        temp = ket.n + S.One
+        return sqrt(temp)*SHOKet(temp)
+
+    def _represent_default_basis(self, **options):
+        return self._represent_NumberOp(None, **options)
+
+    def _represent_XOp(self, basis, **options):
+        # This logic is good but the underlying position
+        # representation logic is broken.
+        # temp = self.rewrite('xp').doit()
+        # result = represent(temp, basis=X)
+        # return result
+        raise NotImplementedError('Position representation is not implemented')
+
+    def _represent_NumberOp(self, basis, **options):
+        ndim_info = options.get('ndim', 4)
+        format = options.get('format','sympy')
+        matrix = matrix_zeros(ndim_info, ndim_info, **options)
+        for i in range(ndim_info - 1):
+            value = sqrt(i + 1)
+            if format == 'scipy.sparse':
+                value = float(value)
+            matrix[i + 1, i] = value
+        if format == 'scipy.sparse':
+            matrix = matrix.tocsr()
+        return matrix
+
+    #--------------------------------------------------------------------------
+    # Printing Methods
+    #--------------------------------------------------------------------------
+
+    def _print_contents(self, printer, *args):
+        arg0 = printer._print(self.args[0], *args)
+        return '%s(%s)' % (self.__class__.__name__, arg0)
+
+    def _print_contents_pretty(self, printer, *args):
+        from sympy.printing.pretty.stringpict import prettyForm
+        pform = printer._print(self.args[0], *args)
+        pform = pform**prettyForm('\N{DAGGER}')
+        return pform
+
+    def _print_contents_latex(self, printer, *args):
+        arg = printer._print(self.args[0])
+        return '%s^{\\dagger}' % arg
+
+class LoweringOp(SHOOp):
+    """The Lowering Operator or 'a'.
+
+    When 'a' acts on a state it lowers the state up by one. Taking
+    the adjoint of 'a' returns a^dagger, the Raising Operator. 'a'
+    can be rewritten in terms of position and momentum. We can
+    represent 'a' as a matrix, which will be its default basis.
+
+    Parameters
+    ==========
+
+    args : tuple
+        The list of numbers or parameters that uniquely specify the
+        operator.
+
+    Examples
+    ========
+
+    Create a Lowering Operator and rewrite it in terms of position and
+    momentum, and show that taking its adjoint returns a^dagger:
+
+        >>> from sympy.physics.quantum.sho1d import LoweringOp
+        >>> from sympy.physics.quantum import Dagger
+
+        >>> a = LoweringOp('a')
+        >>> a.rewrite('xp').doit()
+        sqrt(2)*(m*omega*X + I*Px)/(2*sqrt(hbar)*sqrt(m*omega))
+
+        >>> Dagger(a)
+        RaisingOp(a)
+
+    Taking the commutator of 'a' with other Operators:
+
+        >>> from sympy.physics.quantum import Commutator
+        >>> from sympy.physics.quantum.sho1d import LoweringOp, RaisingOp
+        >>> from sympy.physics.quantum.sho1d import NumberOp
+
+        >>> a = LoweringOp('a')
+        >>> ad = RaisingOp('a')
+        >>> N = NumberOp('N')
+        >>> Commutator(a, ad).doit()
+        1
+        >>> Commutator(a, N).doit()
+        a
+
+    Apply 'a' to a state:
+
+        >>> from sympy.physics.quantum import qapply
+        >>> from sympy.physics.quantum.sho1d import LoweringOp, SHOKet
+
+        >>> a = LoweringOp('a')
+        >>> k = SHOKet('k')
+        >>> qapply(a*k)
+        sqrt(k)*|k - 1>
+
+    Taking 'a' of the lowest state will return 0:
+
+        >>> from sympy.physics.quantum import qapply
+        >>> from sympy.physics.quantum.sho1d import LoweringOp, SHOKet
+
+        >>> a = LoweringOp('a')
+        >>> k = SHOKet(0)
+        >>> qapply(a*k)
+        0
+
+    Matrix Representation
+
+        >>> from sympy.physics.quantum.sho1d import LoweringOp
+        >>> from sympy.physics.quantum.represent import represent
+        >>> a = LoweringOp('a')
+        >>> represent(a, basis=N, ndim=4, format='sympy')
+        Matrix([
+        [0, 1,       0,       0],
+        [0, 0, sqrt(2),       0],
+        [0, 0,       0, sqrt(3)],
+        [0, 0,       0,       0]])
+
+    """
+
+    def _eval_rewrite_as_xp(self, *args, **kwargs):
+        return (S.One/sqrt(Integer(2)*hbar*m*omega))*(
+            I*Px + m*omega*X)
+
+    def _eval_adjoint(self):
+        return RaisingOp(*self.args)
+
+    def _eval_commutator_RaisingOp(self, other):
+        return S.One
+
+    def _eval_commutator_NumberOp(self, other):
+        return self
+
+    def _apply_operator_SHOKet(self, ket, **options):
+        temp = ket.n - Integer(1)
+        if ket.n is S.Zero:
+            return S.Zero
+        else:
+            return sqrt(ket.n)*SHOKet(temp)
+
+    def _represent_default_basis(self, **options):
+        return self._represent_NumberOp(None, **options)
+
+    def _represent_XOp(self, basis, **options):
+        # This logic is good but the underlying position
+        # representation logic is broken.
+        # temp = self.rewrite('xp').doit()
+        # result = represent(temp, basis=X)
+        # return result
+        raise NotImplementedError('Position representation is not implemented')
+
+    def _represent_NumberOp(self, basis, **options):
+        ndim_info = options.get('ndim', 4)
+        format = options.get('format', 'sympy')
+        matrix = matrix_zeros(ndim_info, ndim_info, **options)
+        for i in range(ndim_info - 1):
+            value = sqrt(i + 1)
+            if format == 'scipy.sparse':
+                value = float(value)
+            matrix[i,i + 1] = value
+        if format == 'scipy.sparse':
+            matrix = matrix.tocsr()
+        return matrix
+
+
+class NumberOp(SHOOp):
+    """The Number Operator is simply a^dagger*a
+
+    It is often useful to write a^dagger*a as simply the Number Operator
+    because the Number Operator commutes with the Hamiltonian. And can be
+    expressed using the Number Operator. Also the Number Operator can be
+    applied to states. We can represent the Number Operator as a matrix,
+    which will be its default basis.
+
+    Parameters
+    ==========
+
+    args : tuple
+        The list of numbers or parameters that uniquely specify the
+        operator.
+
+    Examples
+    ========
+
+    Create a Number Operator and rewrite it in terms of the ladder
+    operators, position and momentum operators, and Hamiltonian:
+
+        >>> from sympy.physics.quantum.sho1d import NumberOp
+
+        >>> N = NumberOp('N')
+        >>> N.rewrite('a').doit()
+        RaisingOp(a)*a
+        >>> N.rewrite('xp').doit()
+        -1/2 + (m**2*omega**2*X**2 + Px**2)/(2*hbar*m*omega)
+        >>> N.rewrite('H').doit()
+        -1/2 + H/(hbar*omega)
+
+    Take the Commutator of the Number Operator with other Operators:
+
+        >>> from sympy.physics.quantum import Commutator
+        >>> from sympy.physics.quantum.sho1d import NumberOp, Hamiltonian
+        >>> from sympy.physics.quantum.sho1d import RaisingOp, LoweringOp
+
+        >>> N = NumberOp('N')
+        >>> H = Hamiltonian('H')
+        >>> ad = RaisingOp('a')
+        >>> a = LoweringOp('a')
+        >>> Commutator(N,H).doit()
+        0
+        >>> Commutator(N,ad).doit()
+        RaisingOp(a)
+        >>> Commutator(N,a).doit()
+        -a
+
+    Apply the Number Operator to a state:
+
+        >>> from sympy.physics.quantum import qapply
+        >>> from sympy.physics.quantum.sho1d import NumberOp, SHOKet
+
+        >>> N = NumberOp('N')
+        >>> k = SHOKet('k')
+        >>> qapply(N*k)
+        k*|k>
+
+    Matrix Representation
+
+        >>> from sympy.physics.quantum.sho1d import NumberOp
+        >>> from sympy.physics.quantum.represent import represent
+        >>> N = NumberOp('N')
+        >>> represent(N, basis=N, ndim=4, format='sympy')
+        Matrix([
+        [0, 0, 0, 0],
+        [0, 1, 0, 0],
+        [0, 0, 2, 0],
+        [0, 0, 0, 3]])
+
+    """
+
+    def _eval_rewrite_as_a(self, *args, **kwargs):
+        return ad*a
+
+    def _eval_rewrite_as_xp(self, *args, **kwargs):
+        return (S.One/(Integer(2)*m*hbar*omega))*(Px**2 + (
+            m*omega*X)**2) - S.Half
+
+    def _eval_rewrite_as_H(self, *args, **kwargs):
+        return H/(hbar*omega) - S.Half
+
+    def _apply_operator_SHOKet(self, ket, **options):
+        return ket.n*ket
+
+    def _eval_commutator_Hamiltonian(self, other):
+        return S.Zero
+
+    def _eval_commutator_RaisingOp(self, other):
+        return other
+
+    def _eval_commutator_LoweringOp(self, other):
+        return S.NegativeOne*other
+
+    def _represent_default_basis(self, **options):
+        return self._represent_NumberOp(None, **options)
+
+    def _represent_XOp(self, basis, **options):
+        # This logic is good but the underlying position
+        # representation logic is broken.
+        # temp = self.rewrite('xp').doit()
+        # result = represent(temp, basis=X)
+        # return result
+        raise NotImplementedError('Position representation is not implemented')
+
+    def _represent_NumberOp(self, basis, **options):
+        ndim_info = options.get('ndim', 4)
+        format = options.get('format', 'sympy')
+        matrix = matrix_zeros(ndim_info, ndim_info, **options)
+        for i in range(ndim_info):
+            value = i
+            if format == 'scipy.sparse':
+                value = float(value)
+            matrix[i,i] = value
+        if format == 'scipy.sparse':
+            matrix = matrix.tocsr()
+        return matrix
+
+
+class Hamiltonian(SHOOp):
+    """The Hamiltonian Operator.
+
+    The Hamiltonian is used to solve the time-independent Schrodinger
+    equation. The Hamiltonian can be expressed using the ladder operators,
+    as well as by position and momentum. We can represent the Hamiltonian
+    Operator as a matrix, which will be its default basis.
+
+    Parameters
+    ==========
+
+    args : tuple
+        The list of numbers or parameters that uniquely specify the
+        operator.
+
+    Examples
+    ========
+
+    Create a Hamiltonian Operator and rewrite it in terms of the ladder
+    operators, position and momentum, and the Number Operator:
+
+        >>> from sympy.physics.quantum.sho1d import Hamiltonian
+
+        >>> H = Hamiltonian('H')
+        >>> H.rewrite('a').doit()
+        hbar*omega*(1/2 + RaisingOp(a)*a)
+        >>> H.rewrite('xp').doit()
+        (m**2*omega**2*X**2 + Px**2)/(2*m)
+        >>> H.rewrite('N').doit()
+        hbar*omega*(1/2 + N)
+
+    Take the Commutator of the Hamiltonian and the Number Operator:
+
+        >>> from sympy.physics.quantum import Commutator
+        >>> from sympy.physics.quantum.sho1d import Hamiltonian, NumberOp
+
+        >>> H = Hamiltonian('H')
+        >>> N = NumberOp('N')
+        >>> Commutator(H,N).doit()
+        0
+
+    Apply the Hamiltonian Operator to a state:
+
+        >>> from sympy.physics.quantum import qapply
+        >>> from sympy.physics.quantum.sho1d import Hamiltonian, SHOKet
+
+        >>> H = Hamiltonian('H')
+        >>> k = SHOKet('k')
+        >>> qapply(H*k)
+        hbar*k*omega*|k> + hbar*omega*|k>/2
+
+    Matrix Representation
+
+        >>> from sympy.physics.quantum.sho1d import Hamiltonian
+        >>> from sympy.physics.quantum.represent import represent
+
+        >>> H = Hamiltonian('H')
+        >>> represent(H, basis=N, ndim=4, format='sympy')
+        Matrix([
+        [hbar*omega/2,              0,              0,              0],
+        [           0, 3*hbar*omega/2,              0,              0],
+        [           0,              0, 5*hbar*omega/2,              0],
+        [           0,              0,              0, 7*hbar*omega/2]])
+
+    """
+
+    def _eval_rewrite_as_a(self, *args, **kwargs):
+        return hbar*omega*(ad*a + S.Half)
+
+    def _eval_rewrite_as_xp(self, *args, **kwargs):
+        return (S.One/(Integer(2)*m))*(Px**2 + (m*omega*X)**2)
+
+    def _eval_rewrite_as_N(self, *args, **kwargs):
+        return hbar*omega*(N + S.Half)
+
+    def _apply_operator_SHOKet(self, ket, **options):
+        return (hbar*omega*(ket.n + S.Half))*ket
+
+    def _eval_commutator_NumberOp(self, other):
+        return S.Zero
+
+    def _represent_default_basis(self, **options):
+        return self._represent_NumberOp(None, **options)
+
+    def _represent_XOp(self, basis, **options):
+        # This logic is good but the underlying position
+        # representation logic is broken.
+        # temp = self.rewrite('xp').doit()
+        # result = represent(temp, basis=X)
+        # return result
+        raise NotImplementedError('Position representation is not implemented')
+
+    def _represent_NumberOp(self, basis, **options):
+        ndim_info = options.get('ndim', 4)
+        format = options.get('format', 'sympy')
+        matrix = matrix_zeros(ndim_info, ndim_info, **options)
+        for i in range(ndim_info):
+            value = i + S.Half
+            if format == 'scipy.sparse':
+                value = float(value)
+            matrix[i,i] = value
+        if format == 'scipy.sparse':
+            matrix = matrix.tocsr()
+        return hbar*omega*matrix
+
+#------------------------------------------------------------------------------
+
+class SHOState(State):
+    """State class for SHO states"""
+
+    @classmethod
+    def _eval_hilbert_space(cls, label):
+        return ComplexSpace(S.Infinity)
+
+    @property
+    def n(self):
+        return self.args[0]
+
+
+class SHOKet(SHOState, Ket):
+    """1D eigenket.
+
+    Inherits from SHOState and Ket.
+
+    Parameters
+    ==========
+
+    args : tuple
+        The list of numbers or parameters that uniquely specify the ket
+        This is usually its quantum numbers or its symbol.
+
+    Examples
+    ========
+
+    Ket's know about their associated bra:
+
+        >>> from sympy.physics.quantum.sho1d import SHOKet
+
+        >>> k = SHOKet('k')
+        >>> k.dual
+        <k|
+        >>> k.dual_class()
+        <class 'sympy.physics.quantum.sho1d.SHOBra'>
+
+    Take the Inner Product with a bra:
+
+        >>> from sympy.physics.quantum import InnerProduct
+        >>> from sympy.physics.quantum.sho1d import SHOKet, SHOBra
+
+        >>> k = SHOKet('k')
+        >>> b = SHOBra('b')
+        >>> InnerProduct(b,k).doit()
+        KroneckerDelta(b, k)
+
+    Vector representation of a numerical state ket:
+
+        >>> from sympy.physics.quantum.sho1d import SHOKet, NumberOp
+        >>> from sympy.physics.quantum.represent import represent
+
+        >>> k = SHOKet(3)
+        >>> N = NumberOp('N')
+        >>> represent(k, basis=N, ndim=4)
+        Matrix([
+        [0],
+        [0],
+        [0],
+        [1]])
+
+    """
+
+    @classmethod
+    def dual_class(self):
+        return SHOBra
+
+    def _eval_innerproduct_SHOBra(self, bra, **hints):
+        result = KroneckerDelta(self.n, bra.n)
+        return result
+
+    def _represent_default_basis(self, **options):
+        return self._represent_NumberOp(None, **options)
+
+    def _represent_NumberOp(self, basis, **options):
+        ndim_info = options.get('ndim', 4)
+        format = options.get('format', 'sympy')
+        options['spmatrix'] = 'lil'
+        vector = matrix_zeros(ndim_info, 1, **options)
+        if isinstance(self.n, Integer):
+            if self.n >= ndim_info:
+                return ValueError("N-Dimension too small")
+            if format == 'scipy.sparse':
+                vector[int(self.n), 0] = 1.0
+                vector = vector.tocsr()
+            elif format == 'numpy':
+                vector[int(self.n), 0] = 1.0
+            else:
+                vector[self.n, 0] = S.One
+            return vector
+        else:
+            return ValueError("Not Numerical State")
+
+
+class SHOBra(SHOState, Bra):
+    """A time-independent Bra in SHO.
+
+    Inherits from SHOState and Bra.
+
+    Parameters
+    ==========
+
+    args : tuple
+        The list of numbers or parameters that uniquely specify the ket
+        This is usually its quantum numbers or its symbol.
+
+    Examples
+    ========
+
+    Bra's know about their associated ket:
+
+        >>> from sympy.physics.quantum.sho1d import SHOBra
+
+        >>> b = SHOBra('b')
+        >>> b.dual
+        |b>
+        >>> b.dual_class()
+        <class 'sympy.physics.quantum.sho1d.SHOKet'>
+
+    Vector representation of a numerical state bra:
+
+        >>> from sympy.physics.quantum.sho1d import SHOBra, NumberOp
+        >>> from sympy.physics.quantum.represent import represent
+
+        >>> b = SHOBra(3)
+        >>> N = NumberOp('N')
+        >>> represent(b, basis=N, ndim=4)
+        Matrix([[0, 0, 0, 1]])
+
+    """
+
+    @classmethod
+    def dual_class(self):
+        return SHOKet
+
+    def _represent_default_basis(self, **options):
+        return self._represent_NumberOp(None, **options)
+
+    def _represent_NumberOp(self, basis, **options):
+        ndim_info = options.get('ndim', 4)
+        format = options.get('format', 'sympy')
+        options['spmatrix'] = 'lil'
+        vector = matrix_zeros(1, ndim_info, **options)
+        if isinstance(self.n, Integer):
+            if self.n >= ndim_info:
+                return ValueError("N-Dimension too small")
+            if format == 'scipy.sparse':
+                vector[0, int(self.n)] = 1.0
+                vector = vector.tocsr()
+            elif format == 'numpy':
+                vector[0, int(self.n)] = 1.0
+            else:
+                vector[0, self.n] = S.One
+            return vector
+        else:
+            return ValueError("Not Numerical State")
+
+
+ad = RaisingOp('a')
+a = LoweringOp('a')
+H = Hamiltonian('H')
+N = NumberOp('N')
+omega = Symbol('omega')
+m = Symbol('m')

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/shor.py

@@ -0,0 +1,173 @@
+"""Shor's algorithm and helper functions.
+
+Todo:
+
+* Get the CMod gate working again using the new Gate API.
+* Fix everything.
+* Update docstrings and reformat.
+"""
+
+import math
+import random
+
+from sympy.core.mul import Mul
+from sympy.core.singleton import S
+from sympy.functions.elementary.exponential import log
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.core.intfunc import igcd
+from sympy.ntheory import continued_fraction_periodic as continued_fraction
+from sympy.utilities.iterables import variations
+
+from sympy.physics.quantum.gate import Gate
+from sympy.physics.quantum.qubit import Qubit, measure_partial_oneshot
+from sympy.physics.quantum.qapply import qapply
+from sympy.physics.quantum.qft import QFT
+from sympy.physics.quantum.qexpr import QuantumError
+
+
+class OrderFindingException(QuantumError):
+    pass
+
+
+class CMod(Gate):
+    """A controlled mod gate.
+
+    This is black box controlled Mod function for use by shor's algorithm.
+    TODO: implement a decompose property that returns how to do this in terms
+    of elementary gates
+    """
+
+    @classmethod
+    def _eval_args(cls, args):
+        # t = args[0]
+        # a = args[1]
+        # N = args[2]
+        raise NotImplementedError('The CMod gate has not been completed.')
+
+    @property
+    def t(self):
+        """Size of 1/2 input register.  First 1/2 holds output."""
+        return self.label[0]
+
+    @property
+    def a(self):
+        """Base of the controlled mod function."""
+        return self.label[1]
+
+    @property
+    def N(self):
+        """N is the type of modular arithmetic we are doing."""
+        return self.label[2]
+
+    def _apply_operator_Qubit(self, qubits, **options):
+        """
+            This directly calculates the controlled mod of the second half of
+            the register and puts it in the second
+            This will look pretty when we get Tensor Symbolically working
+        """
+        n = 1
+        k = 0
+        # Determine the value stored in high memory.
+        for i in range(self.t):
+            k += n*qubits[self.t + i]
+            n *= 2
+
+        # The value to go in low memory will be out.
+        out = int(self.a**k % self.N)
+
+        # Create array for new qbit-ket which will have high memory unaffected
+        outarray = list(qubits.args[0][:self.t])
+
+        # Place out in low memory
+        for i in reversed(range(self.t)):
+            outarray.append((out >> i) & 1)
+
+        return Qubit(*outarray)
+
+
+def shor(N):
+    """This function implements Shor's factoring algorithm on the Integer N
+
+    The algorithm starts by picking a random number (a) and seeing if it is
+    coprime with N. If it is not, then the gcd of the two numbers is a factor
+    and we are done. Otherwise, it begins the period_finding subroutine which
+    finds the period of a in modulo N arithmetic. This period, if even, can
+    be used to calculate factors by taking a**(r/2)-1 and a**(r/2)+1.
+    These values are returned.
+    """
+    a = random.randrange(N - 2) + 2
+    if igcd(N, a) != 1:
+        return igcd(N, a)
+    r = period_find(a, N)
+    if r % 2 == 1:
+        shor(N)
+    answer = (igcd(a**(r/2) - 1, N), igcd(a**(r/2) + 1, N))
+    return answer
+
+
+def getr(x, y, N):
+    fraction = continued_fraction(x, y)
+    # Now convert into r
+    total = ratioize(fraction, N)
+    return total
+
+
+def ratioize(list, N):
+    if list[0] > N:
+        return S.Zero
+    if len(list) == 1:
+        return list[0]
+    return list[0] + ratioize(list[1:], N)
+
+
+def period_find(a, N):
+    """Finds the period of a in modulo N arithmetic
+
+    This is quantum part of Shor's algorithm. It takes two registers,
+    puts first in superposition of states with Hadamards so: ``|k>|0>``
+    with k being all possible choices. It then does a controlled mod and
+    a QFT to determine the order of a.
+    """
+    epsilon = .5
+    # picks out t's such that maintains accuracy within epsilon
+    t = int(2*math.ceil(log(N, 2)))
+    # make the first half of register be 0's |000...000>
+    start = [0 for x in range(t)]
+    # Put second half into superposition of states so we have |1>x|0> + |2>x|0> + ... |k>x>|0> + ... + |2**n-1>x|0>
+    factor = 1/sqrt(2**t)
+    qubits = 0
+    for arr in variations(range(2), t, repetition=True):
+        qbitArray = list(arr) + start
+        qubits = qubits + Qubit(*qbitArray)
+    circuit = (factor*qubits).expand()
+    # Controlled second half of register so that we have:
+    # |1>x|a**1 %N> + |2>x|a**2 %N> + ... + |k>x|a**k %N >+ ... + |2**n-1=k>x|a**k % n>
+    circuit = CMod(t, a, N)*circuit
+    # will measure first half of register giving one of the a**k%N's
+
+    circuit = qapply(circuit)
+    for i in range(t):
+        circuit = measure_partial_oneshot(circuit, i)
+    # Now apply Inverse Quantum Fourier Transform on the second half of the register
+
+    circuit = qapply(QFT(t, t*2).decompose()*circuit, floatingPoint=True)
+    for i in range(t):
+        circuit = measure_partial_oneshot(circuit, i + t)
+    if isinstance(circuit, Qubit):
+        register = circuit
+    elif isinstance(circuit, Mul):
+        register = circuit.args[-1]
+    else:
+        register = circuit.args[-1].args[-1]
+
+    n = 1
+    answer = 0
+    for i in range(len(register)/2):
+        answer += n*register[i + t]
+        n = n << 1
+    if answer == 0:
+        raise OrderFindingException(
+            "Order finder returned 0. Happens with chance %f" % epsilon)
+    #turn answer into r using continued fractions
+    g = getr(answer, 2**t, N)
+    return g

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/state.py

@@ -0,0 +1,987 @@
+"""Dirac notation for states."""
+
+from sympy.core.cache import cacheit
+from sympy.core.containers import Tuple
+from sympy.core.expr import Expr
+from sympy.core.function import Function
+from sympy.core.numbers import oo, equal_valued
+from sympy.core.singleton import S
+from sympy.functions.elementary.complexes import conjugate
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.integrals.integrals import integrate
+from sympy.printing.pretty.stringpict import stringPict
+from sympy.physics.quantum.qexpr import QExpr, dispatch_method
+from sympy.physics.quantum.kind import KetKind, BraKind
+
+
+__all__ = [
+    'KetBase',
+    'BraBase',
+    'StateBase',
+    'State',
+    'Ket',
+    'Bra',
+    'TimeDepState',
+    'TimeDepBra',
+    'TimeDepKet',
+    'OrthogonalKet',
+    'OrthogonalBra',
+    'OrthogonalState',
+    'Wavefunction'
+]
+
+
+#-----------------------------------------------------------------------------
+# States, bras and kets.
+#-----------------------------------------------------------------------------
+
+# ASCII brackets
+_lbracket = "<"
+_rbracket = ">"
+_straight_bracket = "|"
+
+
+# Unicode brackets
+# MATHEMATICAL ANGLE BRACKETS
+_lbracket_ucode = "\N{MATHEMATICAL LEFT ANGLE BRACKET}"
+_rbracket_ucode = "\N{MATHEMATICAL RIGHT ANGLE BRACKET}"
+# LIGHT VERTICAL BAR
+_straight_bracket_ucode = "\N{LIGHT VERTICAL BAR}"
+
+# Other options for unicode printing of <, > and | for Dirac notation.
+
+# LEFT-POINTING ANGLE BRACKET
+# _lbracket = "\u2329"
+# _rbracket = "\u232A"
+
+# LEFT ANGLE BRACKET
+# _lbracket = "\u3008"
+# _rbracket = "\u3009"
+
+# VERTICAL LINE
+# _straight_bracket = "\u007C"
+
+
+class StateBase(QExpr):
+    """Abstract base class for general abstract states in quantum mechanics.
+
+    All other state classes defined will need to inherit from this class. It
+    carries the basic structure for all other states such as dual, _eval_adjoint
+    and label.
+
+    This is an abstract base class and you should not instantiate it directly,
+    instead use State.
+    """
+
+    @classmethod
+    def _operators_to_state(self, ops, **options):
+        """ Returns the eigenstate instance for the passed operators.
+
+        This method should be overridden in subclasses. It will handle being
+        passed either an Operator instance or set of Operator instances. It
+        should return the corresponding state INSTANCE or simply raise a
+        NotImplementedError. See cartesian.py for an example.
+        """
+
+        raise NotImplementedError("Cannot map operators to states in this class. Method not implemented!")
+
+    def _state_to_operators(self, op_classes, **options):
+        """ Returns the operators which this state instance is an eigenstate
+        of.
+
+        This method should be overridden in subclasses. It will be called on
+        state instances and be passed the operator classes that we wish to make
+        into instances. The state instance will then transform the classes
+        appropriately, or raise a NotImplementedError if it cannot return
+        operator instances. See cartesian.py for examples,
+        """
+
+        raise NotImplementedError(
+            "Cannot map this state to operators. Method not implemented!")
+
+    @property
+    def operators(self):
+        """Return the operator(s) that this state is an eigenstate of"""
+        from .operatorset import state_to_operators  # import internally to avoid circular import errors
+        return state_to_operators(self)
+
+    def _enumerate_state(self, num_states, **options):
+        raise NotImplementedError("Cannot enumerate this state!")
+
+    def _represent_default_basis(self, **options):
+        return self._represent(basis=self.operators)
+
+    def _apply_operator(self, op, **options):
+        return None
+
+    #-------------------------------------------------------------------------
+    # Dagger/dual
+    #-------------------------------------------------------------------------
+
+    @property
+    def dual(self):
+        """Return the dual state of this one."""
+        return self.dual_class()._new_rawargs(self.hilbert_space, *self.args)
+
+    @classmethod
+    def dual_class(self):
+        """Return the class used to construct the dual."""
+        raise NotImplementedError(
+            'dual_class must be implemented in a subclass'
+        )
+
+    def _eval_adjoint(self):
+        """Compute the dagger of this state using the dual."""
+        return self.dual
+
+    #-------------------------------------------------------------------------
+    # Printing
+    #-------------------------------------------------------------------------
+
+    def _pretty_brackets(self, height, use_unicode=True):
+        # Return pretty printed brackets for the state
+        # Ideally, this could be done by pform.parens but it does not support the angled < and >
+
+        # Setup for unicode vs ascii
+        if use_unicode:
+            lbracket, rbracket = getattr(self, 'lbracket_ucode', ""), getattr(self, 'rbracket_ucode', "")
+            slash, bslash, vert = '\N{BOX DRAWINGS LIGHT DIAGONAL UPPER RIGHT TO LOWER LEFT}', \
+                                  '\N{BOX DRAWINGS LIGHT DIAGONAL UPPER LEFT TO LOWER RIGHT}', \
+                                  '\N{BOX DRAWINGS LIGHT VERTICAL}'
+        else:
+            lbracket, rbracket = getattr(self, 'lbracket', ""), getattr(self, 'rbracket', "")
+            slash, bslash, vert = '/', '\\', '|'
+
+        # If height is 1, just return brackets
+        if height == 1:
+            return stringPict(lbracket), stringPict(rbracket)
+        # Make height even
+        height += (height % 2)
+
+        brackets = []
+        for bracket in lbracket, rbracket:
+            # Create left bracket
+            if bracket in {_lbracket, _lbracket_ucode}:
+                bracket_args = [ ' ' * (height//2 - i - 1) +
+                                 slash for i in range(height // 2)]
+                bracket_args.extend(
+                    [' ' * i + bslash for i in range(height // 2)])
+            # Create right bracket
+            elif bracket in {_rbracket, _rbracket_ucode}:
+                bracket_args = [ ' ' * i + bslash for i in range(height // 2)]
+                bracket_args.extend([ ' ' * (
+                    height//2 - i - 1) + slash for i in range(height // 2)])
+            # Create straight bracket
+            elif bracket in {_straight_bracket, _straight_bracket_ucode}:
+                bracket_args = [vert] * height
+            else:
+                raise ValueError(bracket)
+            brackets.append(
+                stringPict('\n'.join(bracket_args), baseline=height//2))
+        return brackets
+
+    def _sympystr(self, printer, *args):
+        contents = self._print_contents(printer, *args)
+        return '%s%s%s' % (getattr(self, 'lbracket', ""), contents, getattr(self, 'rbracket', ""))
+
+    def _pretty(self, printer, *args):
+        from sympy.printing.pretty.stringpict import prettyForm
+        # Get brackets
+        pform = self._print_contents_pretty(printer, *args)
+        lbracket, rbracket = self._pretty_brackets(
+            pform.height(), printer._use_unicode)
+        # Put together state
+        pform = prettyForm(*pform.left(lbracket))
+        pform = prettyForm(*pform.right(rbracket))
+        return pform
+
+    def _latex(self, printer, *args):
+        contents = self._print_contents_latex(printer, *args)
+        # The extra {} brackets are needed to get matplotlib's latex
+        # rendered to render this properly.
+        return '{%s%s%s}' % (getattr(self, 'lbracket_latex', ""), contents, getattr(self, 'rbracket_latex', ""))
+
+
+class KetBase(StateBase):
+    """Base class for Kets.
+
+    This class defines the dual property and the brackets for printing. This is
+    an abstract base class and you should not instantiate it directly, instead
+    use Ket.
+    """
+
+    kind = KetKind
+
+    lbracket = _straight_bracket
+    rbracket = _rbracket
+    lbracket_ucode = _straight_bracket_ucode
+    rbracket_ucode = _rbracket_ucode
+    lbracket_latex = r'\left|'
+    rbracket_latex = r'\right\rangle '
+
+    @classmethod
+    def default_args(self):
+        return ("psi",)
+
+    @classmethod
+    def dual_class(self):
+        return BraBase
+
+    #-------------------------------------------------------------------------
+    # _eval_* methods
+    #-------------------------------------------------------------------------
+
+    def _eval_innerproduct(self, bra, **hints):
+        """Evaluate the inner product between this ket and a bra.
+
+        This is called to compute <bra|ket>, where the ket is ``self``.
+
+        This method will dispatch to sub-methods having the format::
+
+            ``def _eval_innerproduct_BraClass(self, **hints):``
+
+        Subclasses should define these methods (one for each BraClass) to
+        teach the ket how to take inner products with bras.
+        """
+        return dispatch_method(self, '_eval_innerproduct', bra, **hints)
+
+    def _apply_from_right_to(self, op, **options):
+        """Apply an Operator to this Ket as Operator*Ket
+
+        This method will dispatch to methods having the format::
+
+            ``def _apply_from_right_to_OperatorName(op, **options):``
+
+        Subclasses should define these methods (one for each OperatorName) to
+        teach the Ket how to implement OperatorName*Ket
+
+        Parameters
+        ==========
+
+        op : Operator
+            The Operator that is acting on the Ket as op*Ket
+        options : dict
+            A dict of key/value pairs that control how the operator is applied
+            to the Ket.
+        """
+        return dispatch_method(self, '_apply_from_right_to', op, **options)
+
+
+class BraBase(StateBase):
+    """Base class for Bras.
+
+    This class defines the dual property and the brackets for printing. This
+    is an abstract base class and you should not instantiate it directly,
+    instead use Bra.
+    """
+
+    kind = BraKind
+
+    lbracket = _lbracket
+    rbracket = _straight_bracket
+    lbracket_ucode = _lbracket_ucode
+    rbracket_ucode = _straight_bracket_ucode
+    lbracket_latex = r'\left\langle '
+    rbracket_latex = r'\right|'
+
+    @classmethod
+    def _operators_to_state(self, ops, **options):
+        state = self.dual_class()._operators_to_state(ops, **options)
+        return state.dual
+
+    def _state_to_operators(self, op_classes, **options):
+        return self.dual._state_to_operators(op_classes, **options)
+
+    def _enumerate_state(self, num_states, **options):
+        dual_states = self.dual._enumerate_state(num_states, **options)
+        return [x.dual for x in dual_states]
+
+    @classmethod
+    def default_args(self):
+        return self.dual_class().default_args()
+
+    @classmethod
+    def dual_class(self):
+        return KetBase
+
+    def _represent(self, **options):
+        """A default represent that uses the Ket's version."""
+        from sympy.physics.quantum.dagger import Dagger
+        return Dagger(self.dual._represent(**options))
+
+
+class State(StateBase):
+    """General abstract quantum state used as a base class for Ket and Bra."""
+    pass
+
+
+class Ket(State, KetBase):
+    """A general time-independent Ket in quantum mechanics.
+
+    Inherits from State and KetBase. This class should be used as the base
+    class for all physical, time-independent Kets in a system. This class
+    and its subclasses will be the main classes that users will use for
+    expressing Kets in Dirac notation [1]_.
+
+    Parameters
+    ==========
+
+    args : tuple
+        The list of numbers or parameters that uniquely specify the
+        ket. This will usually be its symbol or its quantum numbers. For
+        time-dependent state, this will include the time.
+
+    Examples
+    ========
+
+    Create a simple Ket and looking at its properties::
+
+        >>> from sympy.physics.quantum import Ket
+        >>> from sympy import symbols, I
+        >>> k = Ket('psi')
+        >>> k
+        |psi>
+        >>> k.hilbert_space
+        H
+        >>> k.is_commutative
+        False
+        >>> k.label
+        (psi,)
+
+    Ket's know about their associated bra::
+
+        >>> k.dual
+        <psi|
+        >>> k.dual_class()
+        <class 'sympy.physics.quantum.state.Bra'>
+
+    Take a linear combination of two kets::
+
+        >>> k0 = Ket(0)
+        >>> k1 = Ket(1)
+        >>> 2*I*k0 - 4*k1
+        2*I*|0> - 4*|1>
+
+    Compound labels are passed as tuples::
+
+        >>> n, m = symbols('n,m')
+        >>> k = Ket(n,m)
+        >>> k
+        |nm>
+
+    References
+    ==========
+
+    .. [1] https://en.wikipedia.org/wiki/Bra-ket_notation
+    """
+
+    @classmethod
+    def dual_class(self):
+        return Bra
+
+
+class Bra(State, BraBase):
+    """A general time-independent Bra in quantum mechanics.
+
+    Inherits from State and BraBase. A Bra is the dual of a Ket [1]_. This
+    class and its subclasses will be the main classes that users will use for
+    expressing Bras in Dirac notation.
+
+    Parameters
+    ==========
+
+    args : tuple
+        The list of numbers or parameters that uniquely specify the
+        ket. This will usually be its symbol or its quantum numbers. For
+        time-dependent state, this will include the time.
+
+    Examples
+    ========
+
+    Create a simple Bra and look at its properties::
+
+        >>> from sympy.physics.quantum import Bra
+        >>> from sympy import symbols, I
+        >>> b = Bra('psi')
+        >>> b
+        <psi|
+        >>> b.hilbert_space
+        H
+        >>> b.is_commutative
+        False
+
+    Bra's know about their dual Ket's::
+
+        >>> b.dual
+        |psi>
+        >>> b.dual_class()
+        <class 'sympy.physics.quantum.state.Ket'>
+
+    Like Kets, Bras can have compound labels and be manipulated in a similar
+    manner::
+
+        >>> n, m = symbols('n,m')
+        >>> b = Bra(n,m) - I*Bra(m,n)
+        >>> b
+        -I*<mn| + <nm|
+
+    Symbols in a Bra can be substituted using ``.subs``::
+
+        >>> b.subs(n,m)
+        <mm| - I*<mm|
+
+    References
+    ==========
+
+    .. [1] https://en.wikipedia.org/wiki/Bra-ket_notation
+    """
+
+    @classmethod
+    def dual_class(self):
+        return Ket
+
+#-----------------------------------------------------------------------------
+# Time dependent states, bras and kets.
+#-----------------------------------------------------------------------------
+
+
+class TimeDepState(StateBase):
+    """Base class for a general time-dependent quantum state.
+
+    This class is used as a base class for any time-dependent state. The main
+    difference between this class and the time-independent state is that this
+    class takes a second argument that is the time in addition to the usual
+    label argument.
+
+    Parameters
+    ==========
+
+    args : tuple
+        The list of numbers or parameters that uniquely specify the ket. This
+        will usually be its symbol or its quantum numbers. For time-dependent
+        state, this will include the time as the final argument.
+    """
+
+    #-------------------------------------------------------------------------
+    # Initialization
+    #-------------------------------------------------------------------------
+
+    @classmethod
+    def default_args(self):
+        return ("psi", "t")
+
+    #-------------------------------------------------------------------------
+    # Properties
+    #-------------------------------------------------------------------------
+
+    @property
+    def label(self):
+        """The label of the state."""
+        return self.args[:-1]
+
+    @property
+    def time(self):
+        """The time of the state."""
+        return self.args[-1]
+
+    #-------------------------------------------------------------------------
+    # Printing
+    #-------------------------------------------------------------------------
+
+    def _print_time(self, printer, *args):
+        return printer._print(self.time, *args)
+
+    _print_time_repr = _print_time
+    _print_time_latex = _print_time
+
+    def _print_time_pretty(self, printer, *args):
+        pform = printer._print(self.time, *args)
+        return pform
+
+    def _print_contents(self, printer, *args):
+        label = self._print_label(printer, *args)
+        time = self._print_time(printer, *args)
+        return '%s;%s' % (label, time)
+
+    def _print_label_repr(self, printer, *args):
+        label = self._print_sequence(self.label, ',', printer, *args)
+        time = self._print_time_repr(printer, *args)
+        return '%s,%s' % (label, time)
+
+    def _print_contents_pretty(self, printer, *args):
+        label = self._print_label_pretty(printer, *args)
+        time = self._print_time_pretty(printer, *args)
+        return printer._print_seq((label, time), delimiter=';')
+
+    def _print_contents_latex(self, printer, *args):
+        label = self._print_sequence(
+            self.label, self._label_separator, printer, *args)
+        time = self._print_time_latex(printer, *args)
+        return '%s;%s' % (label, time)
+
+
+class TimeDepKet(TimeDepState, KetBase):
+    """General time-dependent Ket in quantum mechanics.
+
+    This inherits from ``TimeDepState`` and ``KetBase`` and is the main class
+    that should be used for Kets that vary with time. Its dual is a
+    ``TimeDepBra``.
+
+    Parameters
+    ==========
+
+    args : tuple
+        The list of numbers or parameters that uniquely specify the ket. This
+        will usually be its symbol or its quantum numbers. For time-dependent
+        state, this will include the time as the final argument.
+
+    Examples
+    ========
+
+    Create a TimeDepKet and look at its attributes::
+
+        >>> from sympy.physics.quantum import TimeDepKet
+        >>> k = TimeDepKet('psi', 't')
+        >>> k
+        |psi;t>
+        >>> k.time
+        t
+        >>> k.label
+        (psi,)
+        >>> k.hilbert_space
+        H
+
+    TimeDepKets know about their dual bra::
+
+        >>> k.dual
+        <psi;t|
+        >>> k.dual_class()
+        <class 'sympy.physics.quantum.state.TimeDepBra'>
+    """
+
+    @classmethod
+    def dual_class(self):
+        return TimeDepBra
+
+
+class TimeDepBra(TimeDepState, BraBase):
+    """General time-dependent Bra in quantum mechanics.
+
+    This inherits from TimeDepState and BraBase and is the main class that
+    should be used for Bras that vary with time. Its dual is a TimeDepBra.
+
+    Parameters
+    ==========
+
+    args : tuple
+        The list of numbers or parameters that uniquely specify the ket. This
+        will usually be its symbol or its quantum numbers. For time-dependent
+        state, this will include the time as the final argument.
+
+    Examples
+    ========
+
+        >>> from sympy.physics.quantum import TimeDepBra
+        >>> b = TimeDepBra('psi', 't')
+        >>> b
+        <psi;t|
+        >>> b.time
+        t
+        >>> b.label
+        (psi,)
+        >>> b.hilbert_space
+        H
+        >>> b.dual
+        |psi;t>
+    """
+
+    @classmethod
+    def dual_class(self):
+        return TimeDepKet
+
+
+class OrthogonalState(State):
+    """General abstract quantum state used as a base class for Ket and Bra."""
+    pass
+
+class OrthogonalKet(OrthogonalState, KetBase):
+    """Orthogonal Ket in quantum mechanics.
+
+    The inner product of two states with different labels will give zero,
+    states with the same label will give one.
+
+        >>> from sympy.physics.quantum import OrthogonalBra, OrthogonalKet
+        >>> from sympy.abc import m, n
+        >>> (OrthogonalBra(n)*OrthogonalKet(n)).doit()
+        1
+        >>> (OrthogonalBra(n)*OrthogonalKet(n+1)).doit()
+        0
+        >>> (OrthogonalBra(n)*OrthogonalKet(m)).doit()
+        <n|m>
+    """
+
+    @classmethod
+    def dual_class(self):
+        return OrthogonalBra
+
+    def _eval_innerproduct(self, bra, **hints):
+
+        if len(self.args) != len(bra.args):
+            raise ValueError('Cannot multiply a ket that has a different number of labels.')
+
+        for arg, bra_arg in zip(self.args, bra.args):
+            diff = arg - bra_arg
+            diff = diff.expand()
+
+            is_zero = diff.is_zero
+
+            if is_zero is False:
+                return S.Zero # i.e. Integer(0)
+
+            if is_zero is None:
+                return None
+
+        return S.One # i.e. Integer(1)
+
+
+class OrthogonalBra(OrthogonalState, BraBase):
+    """Orthogonal Bra in quantum mechanics.
+    """
+
+    @classmethod
+    def dual_class(self):
+        return OrthogonalKet
+
+
+class Wavefunction(Function):
+    """Class for representations in continuous bases
+
+    This class takes an expression and coordinates in its constructor. It can
+    be used to easily calculate normalizations and probabilities.
+
+    Parameters
+    ==========
+
+    expr : Expr
+           The expression representing the functional form of the w.f.
+
+    coords : Symbol or tuple
+           The coordinates to be integrated over, and their bounds
+
+    Examples
+    ========
+
+    Particle in a box, specifying bounds in the more primitive way of using
+    Piecewise:
+
+        >>> from sympy import Symbol, Piecewise, pi, N
+        >>> from sympy.functions import sqrt, sin
+        >>> from sympy.physics.quantum.state import Wavefunction
+        >>> x = Symbol('x', real=True)
+        >>> n = 1
+        >>> L = 1
+        >>> g = Piecewise((0, x < 0), (0, x > L), (sqrt(2//L)*sin(n*pi*x/L), True))
+        >>> f = Wavefunction(g, x)
+        >>> f.norm
+        1
+        >>> f.is_normalized
+        True
+        >>> p = f.prob()
+        >>> p(0)
+        0
+        >>> p(L)
+        0
+        >>> p(0.5)
+        2
+        >>> p(0.85*L)
+        2*sin(0.85*pi)**2
+        >>> N(p(0.85*L))
+        0.412214747707527
+
+    Additionally, you can specify the bounds of the function and the indices in
+    a more compact way:
+
+        >>> from sympy import symbols, pi, diff
+        >>> from sympy.functions import sqrt, sin
+        >>> from sympy.physics.quantum.state import Wavefunction
+        >>> x, L = symbols('x,L', positive=True)
+        >>> n = symbols('n', integer=True, positive=True)
+        >>> g = sqrt(2/L)*sin(n*pi*x/L)
+        >>> f = Wavefunction(g, (x, 0, L))
+        >>> f.norm
+        1
+        >>> f(L+1)
+        0
+        >>> f(L-1)
+        sqrt(2)*sin(pi*n*(L - 1)/L)/sqrt(L)
+        >>> f(-1)
+        0
+        >>> f(0.85)
+        sqrt(2)*sin(0.85*pi*n/L)/sqrt(L)
+        >>> f(0.85, n=1, L=1)
+        sqrt(2)*sin(0.85*pi)
+        >>> f.is_commutative
+        False
+
+    All arguments are automatically sympified, so you can define the variables
+    as strings rather than symbols:
+
+        >>> expr = x**2
+        >>> f = Wavefunction(expr, 'x')
+        >>> type(f.variables[0])
+        <class 'sympy.core.symbol.Symbol'>
+
+    Derivatives of Wavefunctions will return Wavefunctions:
+
+        >>> diff(f, x)
+        Wavefunction(2*x, x)
+
+    """
+
+    #Any passed tuples for coordinates and their bounds need to be
+    #converted to Tuples before Function's constructor is called, to
+    #avoid errors from calling is_Float in the constructor
+    def __new__(cls, *args, **options):
+        new_args = [None for i in args]
+        ct = 0
+        for arg in args:
+            if isinstance(arg, tuple):
+                new_args[ct] = Tuple(*arg)
+            else:
+                new_args[ct] = arg
+            ct += 1
+
+        return super().__new__(cls, *new_args, **options)
+
+    def __call__(self, *args, **options):
+        var = self.variables
+
+        if len(args) != len(var):
+            raise NotImplementedError(
+                "Incorrect number of arguments to function!")
+
+        ct = 0
+        #If the passed value is outside the specified bounds, return 0
+        for v in var:
+            lower, upper = self.limits[v]
+
+            #Do the comparison to limits only if the passed symbol is actually
+            #a symbol present in the limits;
+            #Had problems with a comparison of x > L
+            if isinstance(args[ct], Expr) and \
+                not (lower in args[ct].free_symbols
+                     or upper in args[ct].free_symbols):
+                continue
+
+            if (args[ct] < lower) == True or (args[ct] > upper) == True:
+                return S.Zero
+
+            ct += 1
+
+        expr = self.expr
+
+        #Allows user to make a call like f(2, 4, m=1, n=1)
+        for symbol in list(expr.free_symbols):
+            if str(symbol) in options.keys():
+                val = options[str(symbol)]
+                expr = expr.subs(symbol, val)
+
+        return expr.subs(zip(var, args))
+
+    def _eval_derivative(self, symbol):
+        expr = self.expr
+        deriv = expr._eval_derivative(symbol)
+
+        return Wavefunction(deriv, *self.args[1:])
+
+    def _eval_conjugate(self):
+        return Wavefunction(conjugate(self.expr), *self.args[1:])
+
+    def _eval_transpose(self):
+        return self
+
+    @property
+    def is_commutative(self):
+        """
+        Override Function's is_commutative so that order is preserved in
+        represented expressions
+        """
+        return False
+
+    @classmethod
+    def eval(self, *args):
+        return None
+
+    @property
+    def variables(self):
+        """
+        Return the coordinates which the wavefunction depends on
+
+        Examples
+        ========
+
+            >>> from sympy.physics.quantum.state import Wavefunction
+            >>> from sympy import symbols
+            >>> x,y = symbols('x,y')
+            >>> f = Wavefunction(x*y, x, y)
+            >>> f.variables
+            (x, y)
+            >>> g = Wavefunction(x*y, x)
+            >>> g.variables
+            (x,)
+
+        """
+        var = [g[0] if isinstance(g, Tuple) else g for g in self._args[1:]]
+        return tuple(var)
+
+    @property
+    def limits(self):
+        """
+        Return the limits of the coordinates which the w.f. depends on If no
+        limits are specified, defaults to ``(-oo, oo)``.
+
+        Examples
+        ========
+
+            >>> from sympy.physics.quantum.state import Wavefunction
+            >>> from sympy import symbols
+            >>> x, y = symbols('x, y')
+            >>> f = Wavefunction(x**2, (x, 0, 1))
+            >>> f.limits
+            {x: (0, 1)}
+            >>> f = Wavefunction(x**2, x)
+            >>> f.limits
+            {x: (-oo, oo)}
+            >>> f = Wavefunction(x**2 + y**2, x, (y, -1, 2))
+            >>> f.limits
+            {x: (-oo, oo), y: (-1, 2)}
+
+        """
+        limits = [(g[1], g[2]) if isinstance(g, Tuple) else (-oo, oo)
+                  for g in self._args[1:]]
+        return dict(zip(self.variables, tuple(limits)))
+
+    @property
+    def expr(self):
+        """
+        Return the expression which is the functional form of the Wavefunction
+
+        Examples
+        ========
+
+            >>> from sympy.physics.quantum.state import Wavefunction
+            >>> from sympy import symbols
+            >>> x, y = symbols('x, y')
+            >>> f = Wavefunction(x**2, x)
+            >>> f.expr
+            x**2
+
+        """
+        return self._args[0]
+
+    @property
+    def is_normalized(self):
+        """
+        Returns true if the Wavefunction is properly normalized
+
+        Examples
+        ========
+
+            >>> from sympy import symbols, pi
+            >>> from sympy.functions import sqrt, sin
+            >>> from sympy.physics.quantum.state import Wavefunction
+            >>> x, L = symbols('x,L', positive=True)
+            >>> n = symbols('n', integer=True, positive=True)
+            >>> g = sqrt(2/L)*sin(n*pi*x/L)
+            >>> f = Wavefunction(g, (x, 0, L))
+            >>> f.is_normalized
+            True
+
+        """
+
+        return equal_valued(self.norm, 1)
+
+    @property  # type: ignore
+    @cacheit
+    def norm(self):
+        """
+        Return the normalization of the specified functional form.
+
+        This function integrates over the coordinates of the Wavefunction, with
+        the bounds specified.
+
+        Examples
+        ========
+
+            >>> from sympy import symbols, pi
+            >>> from sympy.functions import sqrt, sin
+            >>> from sympy.physics.quantum.state import Wavefunction
+            >>> x, L = symbols('x,L', positive=True)
+            >>> n = symbols('n', integer=True, positive=True)
+            >>> g = sqrt(2/L)*sin(n*pi*x/L)
+            >>> f = Wavefunction(g, (x, 0, L))
+            >>> f.norm
+            1
+            >>> g = sin(n*pi*x/L)
+            >>> f = Wavefunction(g, (x, 0, L))
+            >>> f.norm
+            sqrt(2)*sqrt(L)/2
+
+        """
+
+        exp = self.expr*conjugate(self.expr)
+        var = self.variables
+        limits = self.limits
+
+        for v in var:
+            curr_limits = limits[v]
+            exp = integrate(exp, (v, curr_limits[0], curr_limits[1]))
+
+        return sqrt(exp)
+
+    def normalize(self):
+        """
+        Return a normalized version of the Wavefunction
+
+        Examples
+        ========
+
+            >>> from sympy import symbols, pi
+            >>> from sympy.functions import sin
+            >>> from sympy.physics.quantum.state import Wavefunction
+            >>> x = symbols('x', real=True)
+            >>> L = symbols('L', positive=True)
+            >>> n = symbols('n', integer=True, positive=True)
+            >>> g = sin(n*pi*x/L)
+            >>> f = Wavefunction(g, (x, 0, L))
+            >>> f.normalize()
+            Wavefunction(sqrt(2)*sin(pi*n*x/L)/sqrt(L), (x, 0, L))
+
+        """
+        const = self.norm
+
+        if const is oo:
+            raise NotImplementedError("The function is not normalizable!")
+        else:
+            return Wavefunction((const)**(-1)*self.expr, *self.args[1:])
+
+    def prob(self):
+        r"""
+        Return the absolute magnitude of the w.f., `|\psi(x)|^2`
+
+        Examples
+        ========
+
+            >>> from sympy import symbols, pi
+            >>> from sympy.functions import sin
+            >>> from sympy.physics.quantum.state import Wavefunction
+            >>> x, L = symbols('x,L', real=True)
+            >>> n = symbols('n', integer=True)
+            >>> g = sin(n*pi*x/L)
+            >>> f = Wavefunction(g, (x, 0, L))
+            >>> f.prob()
+            Wavefunction(sin(pi*n*x/L)**2, x)
+
+        """
+
+        return Wavefunction(self.expr*conjugate(self.expr), *self.variables)

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tensorproduct.py

@@ -0,0 +1,363 @@
+"""Abstract tensor product."""
+
+from sympy.core.add import Add
+from sympy.core.expr import Expr
+from sympy.core.kind import KindDispatcher
+from sympy.core.mul import Mul
+from sympy.core.power import Pow
+from sympy.core.sympify import sympify
+from sympy.matrices.dense import DenseMatrix as Matrix
+from sympy.matrices.immutable import ImmutableDenseMatrix as ImmutableMatrix
+from sympy.printing.pretty.stringpict import prettyForm
+from sympy.utilities.exceptions import sympy_deprecation_warning
+
+from sympy.physics.quantum.dagger import Dagger
+from sympy.physics.quantum.kind import (
+    KetKind, _KetKind,
+    BraKind, _BraKind,
+    OperatorKind, _OperatorKind
+)
+from sympy.physics.quantum.matrixutils import (
+    numpy_ndarray,
+    scipy_sparse_matrix,
+    matrix_tensor_product
+)
+from sympy.physics.quantum.state import Ket, Bra
+from sympy.physics.quantum.trace import Tr
+
+
+__all__ = [
+    'TensorProduct',
+    'tensor_product_simp'
+]
+
+#-----------------------------------------------------------------------------
+# Tensor product
+#-----------------------------------------------------------------------------
+
+_combined_printing = False
+
+
+def combined_tensor_printing(combined):
+    """Set flag controlling whether tensor products of states should be
+    printed as a combined bra/ket or as an explicit tensor product of different
+    bra/kets. This is a global setting for all TensorProduct class instances.
+
+    Parameters
+    ----------
+    combine : bool
+        When true, tensor product states are combined into one ket/bra, and
+        when false explicit tensor product notation is used between each
+        ket/bra.
+    """
+    global _combined_printing
+    _combined_printing = combined
+
+
+class TensorProduct(Expr):
+    """The tensor product of two or more arguments.
+
+    For matrices, this uses ``matrix_tensor_product`` to compute the Kronecker
+    or tensor product matrix. For other objects a symbolic ``TensorProduct``
+    instance is returned. The tensor product is a non-commutative
+    multiplication that is used primarily with operators and states in quantum
+    mechanics.
+
+    Currently, the tensor product distinguishes between commutative and
+    non-commutative arguments.  Commutative arguments are assumed to be scalars
+    and are pulled out in front of the ``TensorProduct``. Non-commutative
+    arguments remain in the resulting ``TensorProduct``.
+
+    Parameters
+    ==========
+
+    args : tuple
+        A sequence of the objects to take the tensor product of.
+
+    Examples
+    ========
+
+    Start with a simple tensor product of SymPy matrices::
+
+        >>> from sympy import Matrix
+        >>> from sympy.physics.quantum import TensorProduct
+
+        >>> m1 = Matrix([[1,2],[3,4]])
+        >>> m2 = Matrix([[1,0],[0,1]])
+        >>> TensorProduct(m1, m2)
+        Matrix([
+        [1, 0, 2, 0],
+        [0, 1, 0, 2],
+        [3, 0, 4, 0],
+        [0, 3, 0, 4]])
+        >>> TensorProduct(m2, m1)
+        Matrix([
+        [1, 2, 0, 0],
+        [3, 4, 0, 0],
+        [0, 0, 1, 2],
+        [0, 0, 3, 4]])
+
+    We can also construct tensor products of non-commutative symbols:
+
+        >>> from sympy import Symbol
+        >>> A = Symbol('A',commutative=False)
+        >>> B = Symbol('B',commutative=False)
+        >>> tp = TensorProduct(A, B)
+        >>> tp
+        AxB
+
+    We can take the dagger of a tensor product (note the order does NOT reverse
+    like the dagger of a normal product):
+
+        >>> from sympy.physics.quantum import Dagger
+        >>> Dagger(tp)
+        Dagger(A)xDagger(B)
+
+    Expand can be used to distribute a tensor product across addition:
+
+        >>> C = Symbol('C',commutative=False)
+        >>> tp = TensorProduct(A+B,C)
+        >>> tp
+        (A + B)xC
+        >>> tp.expand(tensorproduct=True)
+        AxC + BxC
+    """
+    is_commutative = False
+
+    _kind_dispatcher = KindDispatcher("TensorProduct_kind_dispatcher", commutative=True)
+
+    @property
+    def kind(self):
+        """Calculate the kind of a tensor product by looking at its children."""
+        arg_kinds = (a.kind for a in self.args)
+        return self._kind_dispatcher(*arg_kinds)
+
+    def __new__(cls, *args):
+        if isinstance(args[0], (Matrix, ImmutableMatrix, numpy_ndarray,
+                                                    scipy_sparse_matrix)):
+            return matrix_tensor_product(*args)
+        c_part, new_args = cls.flatten(sympify(args))
+        c_part = Mul(*c_part)
+        if len(new_args) == 0:
+            return c_part
+        elif len(new_args) == 1:
+            return c_part * new_args[0]
+        else:
+            tp = Expr.__new__(cls, *new_args)
+            return c_part * tp
+
+    @classmethod
+    def flatten(cls, args):
+        # TODO: disallow nested TensorProducts.
+        c_part = []
+        nc_parts = []
+        for arg in args:
+            cp, ncp = arg.args_cnc()
+            c_part.extend(list(cp))
+            nc_parts.append(Mul._from_args(ncp))
+        return c_part, nc_parts
+
+    def _eval_adjoint(self):
+        return TensorProduct(*[Dagger(i) for i in self.args])
+
+    def _eval_rewrite(self, rule, args, **hints):
+        return TensorProduct(*args).expand(tensorproduct=True)
+
+    def _sympystr(self, printer, *args):
+        length = len(self.args)
+        s = ''
+        for i in range(length):
+            if isinstance(self.args[i], (Add, Pow, Mul)):
+                s = s + '('
+            s = s + printer._print(self.args[i])
+            if isinstance(self.args[i], (Add, Pow, Mul)):
+                s = s + ')'
+            if i != length - 1:
+                s = s + 'x'
+        return s
+
+    def _pretty(self, printer, *args):
+
+        if (_combined_printing and
+                (all(isinstance(arg, Ket) for arg in self.args) or
+                 all(isinstance(arg, Bra) for arg in self.args))):
+
+            length = len(self.args)
+            pform = printer._print('', *args)
+            for i in range(length):
+                next_pform = printer._print('', *args)
+                length_i = len(self.args[i].args)
+                for j in range(length_i):
+                    part_pform = printer._print(self.args[i].args[j], *args)
+                    next_pform = prettyForm(*next_pform.right(part_pform))
+                    if j != length_i - 1:
+                        next_pform = prettyForm(*next_pform.right(', '))
+
+                if len(self.args[i].args) > 1:
+                    next_pform = prettyForm(
+                        *next_pform.parens(left='{', right='}'))
+                pform = prettyForm(*pform.right(next_pform))
+                if i != length - 1:
+                    pform = prettyForm(*pform.right(',' + ' '))
+
+            pform = prettyForm(*pform.left(self.args[0].lbracket))
+            pform = prettyForm(*pform.right(self.args[0].rbracket))
+            return pform
+
+        length = len(self.args)
+        pform = printer._print('', *args)
+        for i in range(length):
+            next_pform = printer._print(self.args[i], *args)
+            if isinstance(self.args[i], (Add, Mul)):
+                next_pform = prettyForm(
+                    *next_pform.parens(left='(', right=')')
+                )
+            pform = prettyForm(*pform.right(next_pform))
+            if i != length - 1:
+                if printer._use_unicode:
+                    pform = prettyForm(*pform.right('\N{N-ARY CIRCLED TIMES OPERATOR}' + ' '))
+                else:
+                    pform = prettyForm(*pform.right('x' + ' '))
+        return pform
+
+    def _latex(self, printer, *args):
+
+        if (_combined_printing and
+                (all(isinstance(arg, Ket) for arg in self.args) or
+                 all(isinstance(arg, Bra) for arg in self.args))):
+
+            def _label_wrap(label, nlabels):
+                return label if nlabels == 1 else r"\left\{%s\right\}" % label
+
+            s = r", ".join([_label_wrap(arg._print_label_latex(printer, *args),
+                                        len(arg.args)) for arg in self.args])
+
+            return r"{%s%s%s}" % (self.args[0].lbracket_latex, s,
+                                  self.args[0].rbracket_latex)
+
+        length = len(self.args)
+        s = ''
+        for i in range(length):
+            if isinstance(self.args[i], (Add, Mul)):
+                s = s + '\\left('
+            # The extra {} brackets are needed to get matplotlib's latex
+            # rendered to render this properly.
+            s = s + '{' + printer._print(self.args[i], *args) + '}'
+            if isinstance(self.args[i], (Add, Mul)):
+                s = s + '\\right)'
+            if i != length - 1:
+                s = s + '\\otimes '
+        return s
+
+    def doit(self, **hints):
+        return TensorProduct(*[item.doit(**hints) for item in self.args])
+
+    def _eval_expand_tensorproduct(self, **hints):
+        """Distribute TensorProducts across addition."""
+        args = self.args
+        add_args = []
+        for i in range(len(args)):
+            if isinstance(args[i], Add):
+                for aa in args[i].args:
+                    tp = TensorProduct(*args[:i] + (aa,) + args[i + 1:])
+                    c_part, nc_part = tp.args_cnc()
+                    # Check for TensorProduct object: is the one object in nc_part, if any:
+                    # (Note: any other object type to be expanded must be added here)
+                    if len(nc_part) == 1 and isinstance(nc_part[0], TensorProduct):
+                        nc_part = (nc_part[0]._eval_expand_tensorproduct(), )
+                    add_args.append(Mul(*c_part)*Mul(*nc_part))
+                break
+
+        if add_args:
+            return Add(*add_args)
+        else:
+            return self
+
+    def _eval_trace(self, **kwargs):
+        indices = kwargs.get('indices', None)
+        exp = self
+
+        if indices is None or len(indices) == 0:
+            return Mul(*[Tr(arg).doit() for arg in exp.args])
+        else:
+            return Mul(*[Tr(value).doit() if idx in indices else value
+                         for idx, value in enumerate(exp.args)])
+
+
+def tensor_product_simp_Mul(e):
+    """Simplify a Mul with tensor products.
+
+    .. deprecated:: 1.14.
+        The transformations applied by this function are not done automatically
+        when tensor products are combined.
+
+    Originally, the main use of this function is to simplify a ``Mul`` of
+    ``TensorProduct``s to a ``TensorProduct`` of ``Muls``.
+    """
+    sympy_deprecation_warning(
+        """
+        tensor_product_simp_Mul has been deprecated. The transformations
+        performed by this function are now done automatically when
+        tensor products are multiplied.
+        """,
+        deprecated_since_version="1.14",
+        active_deprecations_target='deprecated-tensorproduct-simp'
+    )
+    return e
+
+def tensor_product_simp_Pow(e):
+    """Evaluates ``Pow`` expressions whose base is ``TensorProduct``
+
+    .. deprecated:: 1.14.
+        The transformations applied by this function are not done automatically
+        when tensor products are combined.
+    """
+    sympy_deprecation_warning(
+        """
+        tensor_product_simp_Pow has been deprecated. The transformations
+        performed by this function are now done automatically when
+        tensor products are exponentiated.
+        """,
+        deprecated_since_version="1.14",
+        active_deprecations_target='deprecated-tensorproduct-simp'
+    )
+    return e
+
+
+def tensor_product_simp(e, **hints):
+    """Try to simplify and combine tensor products.
+
+    .. deprecated:: 1.14.
+        The transformations applied by this function are not done automatically
+        when tensor products are combined.
+
+    Originally, this function tried to pull expressions inside of ``TensorProducts``.
+    It only worked for relatively simple cases where the products have
+    only scalars, raw ``TensorProducts``, not ``Add``, ``Pow``, ``Commutators``
+    of ``TensorProducts``.
+    """
+    sympy_deprecation_warning(
+        """
+        tensor_product_simp has been deprecated. The transformations
+        performed by this function are now done automatically when
+        tensor products are combined.
+        """,
+        deprecated_since_version="1.14",
+        active_deprecations_target='deprecated-tensorproduct-simp'
+    )
+    return e
+
+
+@TensorProduct._kind_dispatcher.register(_OperatorKind, _OperatorKind)
+def find_op_kind(e1, e2):
+    return OperatorKind
+
+
+@TensorProduct._kind_dispatcher.register(_KetKind, _KetKind)
+def find_ket_kind(e1, e2):
+    return KetKind
+
+
+@TensorProduct._kind_dispatcher.register(_BraKind, _BraKind)
+def find_bra_kind(e1, e2):
+    return BraKind

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_anticommutator.py

@@ -0,0 +1,56 @@
+from sympy.core.numbers import Integer
+from sympy.core.symbol import symbols
+
+from sympy.physics.quantum.dagger import Dagger
+from sympy.physics.quantum.anticommutator import AntiCommutator as AComm
+from sympy.physics.quantum.operator import Operator
+
+
+a, b, c = symbols('a,b,c')
+A, B, C, D = symbols('A,B,C,D', commutative=False)
+
+
+def test_anticommutator():
+    ac = AComm(A, B)
+    assert isinstance(ac, AComm)
+    assert ac.is_commutative is False
+    assert ac.subs(A, C) == AComm(C, B)
+
+
+def test_commutator_identities():
+    assert AComm(a*A, b*B) == a*b*AComm(A, B)
+    assert AComm(A, A) == 2*A**2
+    assert AComm(A, B) == AComm(B, A)
+    assert AComm(a, b) == 2*a*b
+    assert AComm(A, B).doit() == A*B + B*A
+
+
+def test_anticommutator_dagger():
+    assert Dagger(AComm(A, B)) == AComm(Dagger(A), Dagger(B))
+
+
+class Foo(Operator):
+
+    def _eval_anticommutator_Bar(self, bar):
+        return Integer(0)
+
+
+class Bar(Operator):
+    pass
+
+
+class Tam(Operator):
+
+    def _eval_anticommutator_Foo(self, foo):
+        return Integer(1)
+
+
+def test_eval_commutator():
+    F = Foo('F')
+    B = Bar('B')
+    T = Tam('T')
+    assert AComm(F, B).doit() == 0
+    assert AComm(B, F).doit() == 0
+    assert AComm(F, T).doit() == 1
+    assert AComm(T, F).doit() == 1
+    assert AComm(B, T).doit() == B*T + T*B

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_boson.py

@@ -0,0 +1,50 @@
+from math import prod
+
+from sympy.core.numbers import Rational
+from sympy.functions.elementary.exponential import exp
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.physics.quantum import Dagger, Commutator, qapply
+from sympy.physics.quantum.boson import BosonOp
+from sympy.physics.quantum.boson import (
+    BosonFockKet, BosonFockBra, BosonCoherentKet, BosonCoherentBra)
+
+
+def test_bosonoperator():
+    a = BosonOp('a')
+    b = BosonOp('b')
+
+    assert isinstance(a, BosonOp)
+    assert isinstance(Dagger(a), BosonOp)
+
+    assert a.is_annihilation
+    assert not Dagger(a).is_annihilation
+
+    assert BosonOp("a") == BosonOp("a", True)
+    assert BosonOp("a") != BosonOp("c")
+    assert BosonOp("a", True) != BosonOp("a", False)
+
+    assert Commutator(a, Dagger(a)).doit() == 1
+
+    assert Commutator(a, Dagger(b)).doit() == a * Dagger(b) - Dagger(b) * a
+
+    assert Dagger(exp(a)) == exp(Dagger(a))
+
+
+def test_boson_states():
+    a = BosonOp("a")
+
+    # Fock states
+    n = 3
+    assert (BosonFockBra(0) * BosonFockKet(1)).doit() == 0
+    assert (BosonFockBra(1) * BosonFockKet(1)).doit() == 1
+    assert qapply(BosonFockBra(n) * Dagger(a)**n * BosonFockKet(0)) \
+        == sqrt(prod(range(1, n+1)))
+
+    # Coherent states
+    alpha1, alpha2 = 1.2, 4.3
+    assert (BosonCoherentBra(alpha1) * BosonCoherentKet(alpha1)).doit() == 1
+    assert (BosonCoherentBra(alpha2) * BosonCoherentKet(alpha2)).doit() == 1
+    assert abs((BosonCoherentBra(alpha1) * BosonCoherentKet(alpha2)).doit() -
+               exp((alpha1 - alpha2) ** 2 * Rational(-1, 2))) < 1e-12
+    assert qapply(a * BosonCoherentKet(alpha1)) == \
+        alpha1 * BosonCoherentKet(alpha1)

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_cartesian.py

@@ -0,0 +1,113 @@
+"""Tests for cartesian.py"""
+
+from sympy.core.numbers import (I, pi)
+from sympy.core.singleton import S
+from sympy.core.symbol import symbols
+from sympy.functions.elementary.exponential import exp
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.functions.special.delta_functions import DiracDelta
+from sympy.sets.sets import Interval
+from sympy.testing.pytest import XFAIL
+
+from sympy.physics.quantum import qapply, represent, L2, Dagger
+from sympy.physics.quantum import Commutator, hbar
+from sympy.physics.quantum.cartesian import (
+    XOp, YOp, ZOp, PxOp, X, Y, Z, Px, XKet, XBra, PxKet, PxBra,
+    PositionKet3D, PositionBra3D
+)
+from sympy.physics.quantum.operator import DifferentialOperator
+
+x, y, z, x_1, x_2, x_3, y_1, z_1 = symbols('x,y,z,x_1,x_2,x_3,y_1,z_1')
+px, py, px_1, px_2 = symbols('px py px_1 px_2')
+
+
+def test_x():
+    assert X.hilbert_space == L2(Interval(S.NegativeInfinity, S.Infinity))
+    assert Commutator(X, Px).doit() == I*hbar
+    assert qapply(X*XKet(x)) == x*XKet(x)
+    assert XKet(x).dual_class() == XBra
+    assert XBra(x).dual_class() == XKet
+    assert (Dagger(XKet(y))*XKet(x)).doit() == DiracDelta(x - y)
+    assert (PxBra(px)*XKet(x)).doit() == \
+        exp(-I*x*px/hbar)/sqrt(2*pi*hbar)
+    assert represent(XKet(x)) == DiracDelta(x - x_1)
+    assert represent(XBra(x)) == DiracDelta(-x + x_1)
+    assert XBra(x).position == x
+    assert represent(XOp()*XKet()) == x*DiracDelta(x - x_2)
+    assert represent(XBra("y")*XKet()) == DiracDelta(x - y)
+    assert represent(
+        XKet()*XBra()) == DiracDelta(x - x_2) * DiracDelta(x_1 - x)
+
+    rep_p = represent(XOp(), basis=PxOp)
+    assert rep_p == hbar*I*DiracDelta(px_1 - px_2)*DifferentialOperator(px_1)
+    assert rep_p == represent(XOp(), basis=PxOp())
+    assert rep_p == represent(XOp(), basis=PxKet)
+    assert rep_p == represent(XOp(), basis=PxKet())
+
+    assert represent(XOp()*PxKet(), basis=PxKet) == \
+        hbar*I*DiracDelta(px - px_2)*DifferentialOperator(px)
+
+
+@XFAIL
+def _text_x_broken():
+    # represent has some broken logic that is relying in particular
+    # forms of input, rather than a full and proper handling of
+    # all valid quantum expressions. Marking this test as XFAIL until
+    # we can refactor represent.
+    assert represent(XOp()*XKet()*XBra('y')) == \
+        x*DiracDelta(x - x_3)*DiracDelta(x_1 - y)
+
+
+def test_p():
+    assert Px.hilbert_space == L2(Interval(S.NegativeInfinity, S.Infinity))
+    assert qapply(Px*PxKet(px)) == px*PxKet(px)
+    assert PxKet(px).dual_class() == PxBra
+    assert PxBra(x).dual_class() == PxKet
+    assert (Dagger(PxKet(py))*PxKet(px)).doit() == DiracDelta(px - py)
+    assert (XBra(x)*PxKet(px)).doit() == \
+        exp(I*x*px/hbar)/sqrt(2*pi*hbar)
+    assert represent(PxKet(px)) == DiracDelta(px - px_1)
+
+    rep_x = represent(PxOp(), basis=XOp)
+    assert rep_x == -hbar*I*DiracDelta(x_1 - x_2)*DifferentialOperator(x_1)
+    assert rep_x == represent(PxOp(), basis=XOp())
+    assert rep_x == represent(PxOp(), basis=XKet)
+    assert rep_x == represent(PxOp(), basis=XKet())
+
+    assert represent(PxOp()*XKet(), basis=XKet) == \
+        -hbar*I*DiracDelta(x - x_2)*DifferentialOperator(x)
+    assert represent(XBra("y")*PxOp()*XKet(), basis=XKet) == \
+        -hbar*I*DiracDelta(x - y)*DifferentialOperator(x)
+
+
+def test_3dpos():
+    assert Y.hilbert_space == L2(Interval(S.NegativeInfinity, S.Infinity))
+    assert Z.hilbert_space == L2(Interval(S.NegativeInfinity, S.Infinity))
+
+    test_ket = PositionKet3D(x, y, z)
+    assert qapply(X*test_ket) == x*test_ket
+    assert qapply(Y*test_ket) == y*test_ket
+    assert qapply(Z*test_ket) == z*test_ket
+    assert qapply(X*Y*test_ket) == x*y*test_ket
+    assert qapply(X*Y*Z*test_ket) == x*y*z*test_ket
+    assert qapply(Y*Z*test_ket) == y*z*test_ket
+
+    assert PositionKet3D() == test_ket
+    assert YOp() == Y
+    assert ZOp() == Z
+
+    assert PositionKet3D.dual_class() == PositionBra3D
+    assert PositionBra3D.dual_class() == PositionKet3D
+
+    other_ket = PositionKet3D(x_1, y_1, z_1)
+    assert (Dagger(other_ket)*test_ket).doit() == \
+        DiracDelta(x - x_1)*DiracDelta(y - y_1)*DiracDelta(z - z_1)
+
+    assert test_ket.position_x == x
+    assert test_ket.position_y == y
+    assert test_ket.position_z == z
+    assert other_ket.position_x == x_1
+    assert other_ket.position_y == y_1
+    assert other_ket.position_z == z_1
+
+    # TODO: Add tests for representations

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_cg.py

@@ -0,0 +1,183 @@
+from sympy.concrete.summations import Sum
+from sympy.core.numbers import Rational
+from sympy.core.singleton import S
+from sympy.core.symbol import symbols
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.physics.quantum.cg import Wigner3j, Wigner6j, Wigner9j, CG, cg_simp
+from sympy.functions.special.tensor_functions import KroneckerDelta
+
+
+def test_cg_simp_add():
+    j, m1, m1p, m2, m2p = symbols('j m1 m1p m2 m2p')
+    # Test Varshalovich 8.7.1 Eq 1
+    a = CG(S.Half, S.Half, 0, 0, S.Half, S.Half)
+    b = CG(S.Half, Rational(-1, 2), 0, 0, S.Half, Rational(-1, 2))
+    c = CG(1, 1, 0, 0, 1, 1)
+    d = CG(1, 0, 0, 0, 1, 0)
+    e = CG(1, -1, 0, 0, 1, -1)
+    assert cg_simp(a + b) == 2
+    assert cg_simp(c + d + e) == 3
+    assert cg_simp(a + b + c + d + e) == 5
+    assert cg_simp(a + b + c) == 2 + c
+    assert cg_simp(2*a + b) == 2 + a
+    assert cg_simp(2*c + d + e) == 3 + c
+    assert cg_simp(5*a + 5*b) == 10
+    assert cg_simp(5*c + 5*d + 5*e) == 15
+    assert cg_simp(-a - b) == -2
+    assert cg_simp(-c - d - e) == -3
+    assert cg_simp(-6*a - 6*b) == -12
+    assert cg_simp(-4*c - 4*d - 4*e) == -12
+    a = CG(S.Half, S.Half, j, 0, S.Half, S.Half)
+    b = CG(S.Half, Rational(-1, 2), j, 0, S.Half, Rational(-1, 2))
+    c = CG(1, 1, j, 0, 1, 1)
+    d = CG(1, 0, j, 0, 1, 0)
+    e = CG(1, -1, j, 0, 1, -1)
+    assert cg_simp(a + b) == 2*KroneckerDelta(j, 0)
+    assert cg_simp(c + d + e) == 3*KroneckerDelta(j, 0)
+    assert cg_simp(a + b + c + d + e) == 5*KroneckerDelta(j, 0)
+    assert cg_simp(a + b + c) == 2*KroneckerDelta(j, 0) + c
+    assert cg_simp(2*a + b) == 2*KroneckerDelta(j, 0) + a
+    assert cg_simp(2*c + d + e) == 3*KroneckerDelta(j, 0) + c
+    assert cg_simp(5*a + 5*b) == 10*KroneckerDelta(j, 0)
+    assert cg_simp(5*c + 5*d + 5*e) == 15*KroneckerDelta(j, 0)
+    assert cg_simp(-a - b) == -2*KroneckerDelta(j, 0)
+    assert cg_simp(-c - d - e) == -3*KroneckerDelta(j, 0)
+    assert cg_simp(-6*a - 6*b) == -12*KroneckerDelta(j, 0)
+    assert cg_simp(-4*c - 4*d - 4*e) == -12*KroneckerDelta(j, 0)
+    # Test Varshalovich 8.7.1 Eq 2
+    a = CG(S.Half, S.Half, S.Half, Rational(-1, 2), 0, 0)
+    b = CG(S.Half, Rational(-1, 2), S.Half, S.Half, 0, 0)
+    c = CG(1, 1, 1, -1, 0, 0)
+    d = CG(1, 0, 1, 0, 0, 0)
+    e = CG(1, -1, 1, 1, 0, 0)
+    assert cg_simp(a - b) == sqrt(2)
+    assert cg_simp(c - d + e) == sqrt(3)
+    assert cg_simp(a - b + c - d + e) == sqrt(2) + sqrt(3)
+    assert cg_simp(a - b + c) == sqrt(2) + c
+    assert cg_simp(2*a - b) == sqrt(2) + a
+    assert cg_simp(2*c - d + e) == sqrt(3) + c
+    assert cg_simp(5*a - 5*b) == 5*sqrt(2)
+    assert cg_simp(5*c - 5*d + 5*e) == 5*sqrt(3)
+    assert cg_simp(-a + b) == -sqrt(2)
+    assert cg_simp(-c + d - e) == -sqrt(3)
+    assert cg_simp(-6*a + 6*b) == -6*sqrt(2)
+    assert cg_simp(-4*c + 4*d - 4*e) == -4*sqrt(3)
+    a = CG(S.Half, S.Half, S.Half, Rational(-1, 2), j, 0)
+    b = CG(S.Half, Rational(-1, 2), S.Half, S.Half, j, 0)
+    c = CG(1, 1, 1, -1, j, 0)
+    d = CG(1, 0, 1, 0, j, 0)
+    e = CG(1, -1, 1, 1, j, 0)
+    assert cg_simp(a - b) == sqrt(2)*KroneckerDelta(j, 0)
+    assert cg_simp(c - d + e) == sqrt(3)*KroneckerDelta(j, 0)
+    assert cg_simp(a - b + c - d + e) == sqrt(
+        2)*KroneckerDelta(j, 0) + sqrt(3)*KroneckerDelta(j, 0)
+    assert cg_simp(a - b + c) == sqrt(2)*KroneckerDelta(j, 0) + c
+    assert cg_simp(2*a - b) == sqrt(2)*KroneckerDelta(j, 0) + a
+    assert cg_simp(2*c - d + e) == sqrt(3)*KroneckerDelta(j, 0) + c
+    assert cg_simp(5*a - 5*b) == 5*sqrt(2)*KroneckerDelta(j, 0)
+    assert cg_simp(5*c - 5*d + 5*e) == 5*sqrt(3)*KroneckerDelta(j, 0)
+    assert cg_simp(-a + b) == -sqrt(2)*KroneckerDelta(j, 0)
+    assert cg_simp(-c + d - e) == -sqrt(3)*KroneckerDelta(j, 0)
+    assert cg_simp(-6*a + 6*b) == -6*sqrt(2)*KroneckerDelta(j, 0)
+    assert cg_simp(-4*c + 4*d - 4*e) == -4*sqrt(3)*KroneckerDelta(j, 0)
+    # Test Varshalovich 8.7.2 Eq 9
+    # alpha=alphap,beta=betap case
+    # numerical
+    a = CG(S.Half, S.Half, S.Half, Rational(-1, 2), 1, 0)**2
+    b = CG(S.Half, S.Half, S.Half, Rational(-1, 2), 0, 0)**2
+    c = CG(1, 0, 1, 1, 1, 1)**2
+    d = CG(1, 0, 1, 1, 2, 1)**2
+    assert cg_simp(a + b) == 1
+    assert cg_simp(c + d) == 1
+    assert cg_simp(a + b + c + d) == 2
+    assert cg_simp(4*a + 4*b) == 4
+    assert cg_simp(4*c + 4*d) == 4
+    assert cg_simp(5*a + 3*b) == 3 + 2*a
+    assert cg_simp(5*c + 3*d) == 3 + 2*c
+    assert cg_simp(-a - b) == -1
+    assert cg_simp(-c - d) == -1
+    # symbolic
+    a = CG(S.Half, m1, S.Half, m2, 1, 1)**2
+    b = CG(S.Half, m1, S.Half, m2, 1, 0)**2
+    c = CG(S.Half, m1, S.Half, m2, 1, -1)**2
+    d = CG(S.Half, m1, S.Half, m2, 0, 0)**2
+    assert cg_simp(a + b + c + d) == 1
+    assert cg_simp(4*a + 4*b + 4*c + 4*d) == 4
+    assert cg_simp(3*a + 5*b + 3*c + 4*d) == 3 + 2*b + d
+    assert cg_simp(-a - b - c - d) == -1
+    a = CG(1, m1, 1, m2, 2, 2)**2
+    b = CG(1, m1, 1, m2, 2, 1)**2
+    c = CG(1, m1, 1, m2, 2, 0)**2
+    d = CG(1, m1, 1, m2, 2, -1)**2
+    e = CG(1, m1, 1, m2, 2, -2)**2
+    f = CG(1, m1, 1, m2, 1, 1)**2
+    g = CG(1, m1, 1, m2, 1, 0)**2
+    h = CG(1, m1, 1, m2, 1, -1)**2
+    i = CG(1, m1, 1, m2, 0, 0)**2
+    assert cg_simp(a + b + c + d + e + f + g + h + i) == 1
+    assert cg_simp(4*(a + b + c + d + e + f + g + h + i)) == 4
+    assert cg_simp(a + b + 2*c + d + 4*e + f + g + h + i) == 1 + c + 3*e
+    assert cg_simp(-a - b - c - d - e - f - g - h - i) == -1
+    # alpha!=alphap or beta!=betap case
+    # numerical
+    a = CG(S.Half, S(
+        1)/2, S.Half, Rational(-1, 2), 1, 0)*CG(S.Half, Rational(-1, 2), S.Half, S.Half, 1, 0)
+    b = CG(S.Half, S(
+        1)/2, S.Half, Rational(-1, 2), 0, 0)*CG(S.Half, Rational(-1, 2), S.Half, S.Half, 0, 0)
+    c = CG(1, 1, 1, 0, 2, 1)*CG(1, 0, 1, 1, 2, 1)
+    d = CG(1, 1, 1, 0, 1, 1)*CG(1, 0, 1, 1, 1, 1)
+    assert cg_simp(a + b) == 0
+    assert cg_simp(c + d) == 0
+    # symbolic
+    a = CG(S.Half, m1, S.Half, m2, 1, 1)*CG(S.Half, m1p, S.Half, m2p, 1, 1)
+    b = CG(S.Half, m1, S.Half, m2, 1, 0)*CG(S.Half, m1p, S.Half, m2p, 1, 0)
+    c = CG(S.Half, m1, S.Half, m2, 1, -1)*CG(S.Half, m1p, S.Half, m2p, 1, -1)
+    d = CG(S.Half, m1, S.Half, m2, 0, 0)*CG(S.Half, m1p, S.Half, m2p, 0, 0)
+    assert cg_simp(a + b + c + d) == KroneckerDelta(m1, m1p)*KroneckerDelta(m2, m2p)
+    a = CG(1, m1, 1, m2, 2, 2)*CG(1, m1p, 1, m2p, 2, 2)
+    b = CG(1, m1, 1, m2, 2, 1)*CG(1, m1p, 1, m2p, 2, 1)
+    c = CG(1, m1, 1, m2, 2, 0)*CG(1, m1p, 1, m2p, 2, 0)
+    d = CG(1, m1, 1, m2, 2, -1)*CG(1, m1p, 1, m2p, 2, -1)
+    e = CG(1, m1, 1, m2, 2, -2)*CG(1, m1p, 1, m2p, 2, -2)
+    f = CG(1, m1, 1, m2, 1, 1)*CG(1, m1p, 1, m2p, 1, 1)
+    g = CG(1, m1, 1, m2, 1, 0)*CG(1, m1p, 1, m2p, 1, 0)
+    h = CG(1, m1, 1, m2, 1, -1)*CG(1, m1p, 1, m2p, 1, -1)
+    i = CG(1, m1, 1, m2, 0, 0)*CG(1, m1p, 1, m2p, 0, 0)
+    assert cg_simp(
+        a + b + c + d + e + f + g + h + i) == KroneckerDelta(m1, m1p)*KroneckerDelta(m2, m2p)
+
+
+def test_cg_simp_sum():
+    x, a, b, c, cp, alpha, beta, gamma, gammap = symbols(
+        'x a b c cp alpha beta gamma gammap')
+    # Varshalovich 8.7.1 Eq 1
+    assert cg_simp(x * Sum(CG(a, alpha, b, 0, a, alpha), (alpha, -a, a)
+                   )) == x*(2*a + 1)*KroneckerDelta(b, 0)
+    assert cg_simp(x * Sum(CG(a, alpha, b, 0, a, alpha), (alpha, -a, a)) + CG(1, 0, 1, 0, 1, 0)) == x*(2*a + 1)*KroneckerDelta(b, 0) + CG(1, 0, 1, 0, 1, 0)
+    assert cg_simp(2 * Sum(CG(1, alpha, 0, 0, 1, alpha), (alpha, -1, 1))) == 6
+    # Varshalovich 8.7.1 Eq 2
+    assert cg_simp(x*Sum((-1)**(a - alpha) * CG(a, alpha, a, -alpha, c,
+                   0), (alpha, -a, a))) == x*sqrt(2*a + 1)*KroneckerDelta(c, 0)
+    assert cg_simp(3*Sum((-1)**(2 - alpha) * CG(
+        2, alpha, 2, -alpha, 0, 0), (alpha, -2, 2))) == 3*sqrt(5)
+    # Varshalovich 8.7.2 Eq 4
+    assert cg_simp(Sum(CG(a, alpha, b, beta, c, gamma)*CG(a, alpha, b, beta, cp, gammap), (alpha, -a, a), (beta, -b, b))) == KroneckerDelta(c, cp)*KroneckerDelta(gamma, gammap)
+    assert cg_simp(Sum(CG(a, alpha, b, beta, c, gamma)*CG(a, alpha, b, beta, c, gammap), (alpha, -a, a), (beta, -b, b))) == KroneckerDelta(gamma, gammap)
+    assert cg_simp(Sum(CG(a, alpha, b, beta, c, gamma)*CG(a, alpha, b, beta, cp, gamma), (alpha, -a, a), (beta, -b, b))) == KroneckerDelta(c, cp)
+    assert cg_simp(Sum(CG(
+        a, alpha, b, beta, c, gamma)**2, (alpha, -a, a), (beta, -b, b))) == 1
+    assert cg_simp(Sum(CG(2, alpha, 1, beta, 2, gamma)*CG(2, alpha, 1, beta, 2, gammap), (alpha, -2, 2), (beta, -1, 1))) == KroneckerDelta(gamma, gammap)
+
+
+def test_doit():
+    assert Wigner3j(S.Half, Rational(-1, 2), S.Half, S.Half, 0, 0).doit() == -sqrt(2)/2
+    assert Wigner3j(1/2,1/2,1/2,1/2,1/2,1/2).doit() == 0
+    assert Wigner3j(9/2,9/2,9/2,9/2,9/2,9/2).doit() ==  0
+    assert Wigner6j(1, 2, 3, 2, 1, 2).doit() == sqrt(21)/105
+    assert Wigner6j(3, 1, 2, 2, 2, 1).doit() == sqrt(21) / 105
+    assert Wigner9j(
+        2, 1, 1, Rational(3, 2), S.Half, 1, S.Half, S.Half, 0).doit() == sqrt(2)/12
+    assert CG(S.Half, S.Half, S.Half, Rational(-1, 2), 1, 0).doit() == sqrt(2)/2
+    # J minus M is not integer
+    assert Wigner3j(1, -1, S.Half, S.Half, 1, S.Half).doit() == 0
+    assert CG(4, -1, S.Half, S.Half, 4, Rational(-1, 2)).doit() == 0

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_circuitplot.py

@@ -0,0 +1,69 @@
+from sympy.physics.quantum.circuitplot import labeller, render_label, Mz, CreateOneQubitGate,\
+     CreateCGate
+from sympy.physics.quantum.gate import CNOT, H, SWAP, CGate, S, T
+from sympy.external import import_module
+from sympy.testing.pytest import skip
+
+mpl = import_module('matplotlib')
+
+def test_render_label():
+    assert render_label('q0') == r'$\left|q0\right\rangle$'
+    assert render_label('q0', {'q0': '0'}) == r'$\left|q0\right\rangle=\left|0\right\rangle$'
+
+def test_Mz():
+    assert str(Mz(0)) == 'Mz(0)'
+
+def test_create1():
+    Qgate = CreateOneQubitGate('Q')
+    assert str(Qgate(0)) == 'Q(0)'
+
+def test_createc():
+    Qgate = CreateCGate('Q')
+    assert str(Qgate([1],0)) == 'C((1),Q(0))'
+
+def test_labeller():
+    """Test the labeller utility"""
+    assert labeller(2) == ['q_1', 'q_0']
+    assert labeller(3,'j') == ['j_2', 'j_1', 'j_0']
+
+def test_cnot():
+    """Test a simple cnot circuit. Right now this only makes sure the code doesn't
+    raise an exception, and some simple properties
+    """
+    if not mpl:
+        skip("matplotlib not installed")
+    else:
+        from sympy.physics.quantum.circuitplot import CircuitPlot
+
+    c = CircuitPlot(CNOT(1,0),2,labels=labeller(2))
+    assert c.ngates == 2
+    assert c.nqubits == 2
+    assert c.labels == ['q_1', 'q_0']
+
+    c = CircuitPlot(CNOT(1,0),2)
+    assert c.ngates == 2
+    assert c.nqubits == 2
+    assert c.labels == []
+
+def test_ex1():
+    if not mpl:
+        skip("matplotlib not installed")
+    else:
+        from sympy.physics.quantum.circuitplot import CircuitPlot
+
+    c = CircuitPlot(CNOT(1,0)*H(1),2,labels=labeller(2))
+    assert c.ngates == 2
+    assert c.nqubits == 2
+    assert c.labels == ['q_1', 'q_0']
+
+def test_ex4():
+    if not mpl:
+        skip("matplotlib not installed")
+    else:
+        from sympy.physics.quantum.circuitplot import CircuitPlot
+
+    c = CircuitPlot(SWAP(0,2)*H(0)* CGate((0,),S(1)) *H(1)*CGate((0,),T(2))\
+                    *CGate((1,),S(2))*H(2),3,labels=labeller(3,'j'))
+    assert c.ngates == 7
+    assert c.nqubits == 3
+    assert c.labels == ['j_2', 'j_1', 'j_0']

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_circuitutils.py

@@ -0,0 +1,402 @@
+from sympy.core.mul import Mul
+from sympy.core.numbers import Integer
+from sympy.core.symbol import Symbol
+from sympy.utilities import numbered_symbols
+from sympy.physics.quantum.gate import X, Y, Z, H, CNOT, CGate
+from sympy.physics.quantum.identitysearch import bfs_identity_search
+from sympy.physics.quantum.circuitutils import (kmp_table, find_subcircuit,
+        replace_subcircuit, convert_to_symbolic_indices,
+        convert_to_real_indices, random_reduce, random_insert,
+        flatten_ids)
+from sympy.testing.pytest import slow
+
+
+def create_gate_sequence(qubit=0):
+    gates = (X(qubit), Y(qubit), Z(qubit), H(qubit))
+    return gates
+
+
+def test_kmp_table():
+    word = ('a', 'b', 'c', 'd', 'a', 'b', 'd')
+    expected_table = [-1, 0, 0, 0, 0, 1, 2]
+    assert expected_table == kmp_table(word)
+
+    word = ('P', 'A', 'R', 'T', 'I', 'C', 'I', 'P', 'A', 'T', 'E', ' ',
+            'I', 'N', ' ', 'P', 'A', 'R', 'A', 'C', 'H', 'U', 'T', 'E')
+    expected_table = [-1, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0,
+                      0, 0, 0, 0, 1, 2, 3, 0, 0, 0, 0, 0]
+    assert expected_table == kmp_table(word)
+
+    x = X(0)
+    y = Y(0)
+    z = Z(0)
+    h = H(0)
+    word = (x, y, y, x, z)
+    expected_table = [-1, 0, 0, 0, 1]
+    assert expected_table == kmp_table(word)
+
+    word = (x, x, y, h, z)
+    expected_table = [-1, 0, 1, 0, 0]
+    assert expected_table == kmp_table(word)
+
+
+def test_find_subcircuit():
+    x = X(0)
+    y = Y(0)
+    z = Z(0)
+    h = H(0)
+    x1 = X(1)
+    y1 = Y(1)
+
+    i0 = Symbol('i0')
+    x_i0 = X(i0)
+    y_i0 = Y(i0)
+    z_i0 = Z(i0)
+    h_i0 = H(i0)
+
+    circuit = (x, y, z)
+
+    assert find_subcircuit(circuit, (x,)) == 0
+    assert find_subcircuit(circuit, (x1,)) == -1
+    assert find_subcircuit(circuit, (y,)) == 1
+    assert find_subcircuit(circuit, (h,)) == -1
+    assert find_subcircuit(circuit, Mul(x, h)) == -1
+    assert find_subcircuit(circuit, Mul(x, y, z)) == 0
+    assert find_subcircuit(circuit, Mul(y, z)) == 1
+    assert find_subcircuit(Mul(*circuit), (x, y, z, h)) == -1
+    assert find_subcircuit(Mul(*circuit), (z, y, x)) == -1
+    assert find_subcircuit(circuit, (x,), start=2, end=1) == -1
+
+    circuit = (x, y, x, y, z)
+    assert find_subcircuit(Mul(*circuit), Mul(x, y, z)) == 2
+    assert find_subcircuit(circuit, (x,), start=1) == 2
+    assert find_subcircuit(circuit, (x, y), start=1, end=2) == -1
+    assert find_subcircuit(Mul(*circuit), (x, y), start=1, end=3) == -1
+    assert find_subcircuit(circuit, (x, y), start=1, end=4) == 2
+    assert find_subcircuit(circuit, (x, y), start=2, end=4) == 2
+
+    circuit = (x, y, z, x1, x, y, z, h, x, y, x1,
+               x, y, z, h, y1, h)
+    assert find_subcircuit(circuit, (x, y, z, h, y1)) == 11
+
+    circuit = (x, y, x_i0, y_i0, z_i0, z)
+    assert find_subcircuit(circuit, (x_i0, y_i0, z_i0)) == 2
+
+    circuit = (x_i0, y_i0, z_i0, x_i0, y_i0, h_i0)
+    subcircuit = (x_i0, y_i0, z_i0)
+    result = find_subcircuit(circuit, subcircuit)
+    assert result == 0
+
+
+def test_replace_subcircuit():
+    x = X(0)
+    y = Y(0)
+    z = Z(0)
+    h = H(0)
+    cnot = CNOT(1, 0)
+    cgate_z = CGate((0,), Z(1))
+
+    # Standard cases
+    circuit = (z, y, x, x)
+    remove = (z, y, x)
+    assert replace_subcircuit(circuit, Mul(*remove)) == (x,)
+    assert replace_subcircuit(circuit, remove + (x,)) == ()
+    assert replace_subcircuit(circuit, remove, pos=1) == circuit
+    assert replace_subcircuit(circuit, remove, pos=0) == (x,)
+    assert replace_subcircuit(circuit, (x, x), pos=2) == (z, y)
+    assert replace_subcircuit(circuit, (h,)) == circuit
+
+    circuit = (x, y, x, y, z)
+    remove = (x, y, z)
+    assert replace_subcircuit(Mul(*circuit), Mul(*remove)) == (x, y)
+    remove = (x, y, x, y)
+    assert replace_subcircuit(circuit, remove) == (z,)
+
+    circuit = (x, h, cgate_z, h, cnot)
+    remove = (x, h, cgate_z)
+    assert replace_subcircuit(circuit, Mul(*remove), pos=-1) == (h, cnot)
+    assert replace_subcircuit(circuit, remove, pos=1) == circuit
+    remove = (h, h)
+    assert replace_subcircuit(circuit, remove) == circuit
+    remove = (h, cgate_z, h, cnot)
+    assert replace_subcircuit(circuit, remove) == (x,)
+
+    replace = (h, x)
+    actual = replace_subcircuit(circuit, remove,
+                     replace=replace)
+    assert actual == (x, h, x)
+
+    circuit = (x, y, h, x, y, z)
+    remove = (x, y)
+    replace = (cnot, cgate_z)
+    actual = replace_subcircuit(circuit, remove,
+                     replace=Mul(*replace))
+    assert actual == (cnot, cgate_z, h, x, y, z)
+
+    actual = replace_subcircuit(circuit, remove,
+                     replace=replace, pos=1)
+    assert actual == (x, y, h, cnot, cgate_z, z)
+
+
+def test_convert_to_symbolic_indices():
+    (x, y, z, h) = create_gate_sequence()
+
+    i0 = Symbol('i0')
+    exp_map = {i0: Integer(0)}
+    actual, act_map, sndx, gen = convert_to_symbolic_indices((x,))
+    assert actual == (X(i0),)
+    assert act_map == exp_map
+
+    expected = (X(i0), Y(i0), Z(i0), H(i0))
+    exp_map = {i0: Integer(0)}
+    actual, act_map, sndx, gen = convert_to_symbolic_indices((x, y, z, h))
+    assert actual == expected
+    assert exp_map == act_map
+
+    (x1, y1, z1, h1) = create_gate_sequence(1)
+    i1 = Symbol('i1')
+
+    expected = (X(i0), Y(i0), Z(i0), H(i0))
+    exp_map = {i0: Integer(1)}
+    actual, act_map, sndx, gen = convert_to_symbolic_indices((x1, y1, z1, h1))
+    assert actual == expected
+    assert act_map == exp_map
+
+    expected = (X(i0), Y(i0), Z(i0), H(i0), X(i1), Y(i1), Z(i1), H(i1))
+    exp_map = {i0: Integer(0), i1: Integer(1)}
+    actual, act_map, sndx, gen = convert_to_symbolic_indices((x, y, z, h,
+                                         x1, y1, z1, h1))
+    assert actual == expected
+    assert act_map == exp_map
+
+    exp_map = {i0: Integer(1), i1: Integer(0)}
+    actual, act_map, sndx, gen = convert_to_symbolic_indices(Mul(x1, y1,
+                                         z1, h1, x, y, z, h))
+    assert actual == expected
+    assert act_map == exp_map
+
+    expected = (X(i0), X(i1), Y(i0), Y(i1), Z(i0), Z(i1), H(i0), H(i1))
+    exp_map = {i0: Integer(0), i1: Integer(1)}
+    actual, act_map, sndx, gen = convert_to_symbolic_indices(Mul(x, x1,
+                                         y, y1, z, z1, h, h1))
+    assert actual == expected
+    assert act_map == exp_map
+
+    exp_map = {i0: Integer(1), i1: Integer(0)}
+    actual, act_map, sndx, gen = convert_to_symbolic_indices((x1, x, y1, y,
+                                         z1, z, h1, h))
+    assert actual == expected
+    assert act_map == exp_map
+
+    cnot_10 = CNOT(1, 0)
+    cnot_01 = CNOT(0, 1)
+    cgate_z_10 = CGate(1, Z(0))
+    cgate_z_01 = CGate(0, Z(1))
+
+    expected = (X(i0), X(i1), Y(i0), Y(i1), Z(i0), Z(i1),
+                H(i0), H(i1), CNOT(i1, i0), CNOT(i0, i1),
+                CGate(i1, Z(i0)), CGate(i0, Z(i1)))
+    exp_map = {i0: Integer(0), i1: Integer(1)}
+    args = (x, x1, y, y1, z, z1, h, h1, cnot_10, cnot_01,
+            cgate_z_10, cgate_z_01)
+    actual, act_map, sndx, gen = convert_to_symbolic_indices(args)
+    assert actual == expected
+    assert act_map == exp_map
+
+    args = (x1, x, y1, y, z1, z, h1, h, cnot_10, cnot_01,
+            cgate_z_10, cgate_z_01)
+    expected = (X(i0), X(i1), Y(i0), Y(i1), Z(i0), Z(i1),
+                H(i0), H(i1), CNOT(i0, i1), CNOT(i1, i0),
+                CGate(i0, Z(i1)), CGate(i1, Z(i0)))
+    exp_map = {i0: Integer(1), i1: Integer(0)}
+    actual, act_map, sndx, gen = convert_to_symbolic_indices(args)
+    assert actual == expected
+    assert act_map == exp_map
+
+    args = (cnot_10, h, cgate_z_01, h)
+    expected = (CNOT(i0, i1), H(i1), CGate(i1, Z(i0)), H(i1))
+    exp_map = {i0: Integer(1), i1: Integer(0)}
+    actual, act_map, sndx, gen = convert_to_symbolic_indices(args)
+    assert actual == expected
+    assert act_map == exp_map
+
+    args = (cnot_01, h1, cgate_z_10, h1)
+    exp_map = {i0: Integer(0), i1: Integer(1)}
+    actual, act_map, sndx, gen = convert_to_symbolic_indices(args)
+    assert actual == expected
+    assert act_map == exp_map
+
+    args = (cnot_10, h1, cgate_z_01, h1)
+    expected = (CNOT(i0, i1), H(i0), CGate(i1, Z(i0)), H(i0))
+    exp_map = {i0: Integer(1), i1: Integer(0)}
+    actual, act_map, sndx, gen = convert_to_symbolic_indices(args)
+    assert actual == expected
+    assert act_map == exp_map
+
+    i2 = Symbol('i2')
+    ccgate_z = CGate(0, CGate(1, Z(2)))
+    ccgate_x = CGate(1, CGate(2, X(0)))
+    args = (ccgate_z, ccgate_x)
+
+    expected = (CGate(i0, CGate(i1, Z(i2))), CGate(i1, CGate(i2, X(i0))))
+    exp_map = {i0: Integer(0), i1: Integer(1), i2: Integer(2)}
+    actual, act_map, sndx, gen = convert_to_symbolic_indices(args)
+    assert actual == expected
+    assert act_map == exp_map
+
+    ndx_map = {i0: Integer(0)}
+    index_gen = numbered_symbols(prefix='i', start=1)
+    actual, act_map, sndx, gen = convert_to_symbolic_indices(args,
+                                         qubit_map=ndx_map,
+                                         start=i0,
+                                         gen=index_gen)
+    assert actual == expected
+    assert act_map == exp_map
+
+    i3 = Symbol('i3')
+    cgate_x0_c321 = CGate((3, 2, 1), X(0))
+    exp_map = {i0: Integer(3), i1: Integer(2),
+               i2: Integer(1), i3: Integer(0)}
+    expected = (CGate((i0, i1, i2), X(i3)),)
+    args = (cgate_x0_c321,)
+    actual, act_map, sndx, gen = convert_to_symbolic_indices(args)
+    assert actual == expected
+    assert act_map == exp_map
+
+
+def test_convert_to_real_indices():
+    i0 = Symbol('i0')
+    i1 = Symbol('i1')
+
+    (x, y, z, h) = create_gate_sequence()
+
+    x_i0 = X(i0)
+    y_i0 = Y(i0)
+    z_i0 = Z(i0)
+
+    qubit_map = {i0: 0}
+    args = (z_i0, y_i0, x_i0)
+    expected = (z, y, x)
+    actual = convert_to_real_indices(args, qubit_map)
+    assert actual == expected
+
+    cnot_10 = CNOT(1, 0)
+    cnot_01 = CNOT(0, 1)
+    cgate_z_10 = CGate(1, Z(0))
+    cgate_z_01 = CGate(0, Z(1))
+
+    cnot_i1_i0 = CNOT(i1, i0)
+    cnot_i0_i1 = CNOT(i0, i1)
+    cgate_z_i1_i0 = CGate(i1, Z(i0))
+
+    qubit_map = {i0: 0, i1: 1}
+    args = (cnot_i1_i0,)
+    expected = (cnot_10,)
+    actual = convert_to_real_indices(args, qubit_map)
+    assert actual == expected
+
+    args = (cgate_z_i1_i0,)
+    expected = (cgate_z_10,)
+    actual = convert_to_real_indices(args, qubit_map)
+    assert actual == expected
+
+    args = (cnot_i0_i1,)
+    expected = (cnot_01,)
+    actual = convert_to_real_indices(args, qubit_map)
+    assert actual == expected
+
+    qubit_map = {i0: 1, i1: 0}
+    args = (cgate_z_i1_i0,)
+    expected = (cgate_z_01,)
+    actual = convert_to_real_indices(args, qubit_map)
+    assert actual == expected
+
+    i2 = Symbol('i2')
+    ccgate_z = CGate(i0, CGate(i1, Z(i2)))
+    ccgate_x = CGate(i1, CGate(i2, X(i0)))
+
+    qubit_map = {i0: 0, i1: 1, i2: 2}
+    args = (ccgate_z, ccgate_x)
+    expected = (CGate(0, CGate(1, Z(2))), CGate(1, CGate(2, X(0))))
+    actual = convert_to_real_indices(Mul(*args), qubit_map)
+    assert actual == expected
+
+    qubit_map = {i0: 1, i2: 0, i1: 2}
+    args = (ccgate_x, ccgate_z)
+    expected = (CGate(2, CGate(0, X(1))), CGate(1, CGate(2, Z(0))))
+    actual = convert_to_real_indices(args, qubit_map)
+    assert actual == expected
+
+
+@slow
+def test_random_reduce():
+    x = X(0)
+    y = Y(0)
+    z = Z(0)
+    h = H(0)
+    cnot = CNOT(1, 0)
+    cgate_z = CGate((0,), Z(1))
+
+    gate_list = [x, y, z]
+    ids = list(bfs_identity_search(gate_list, 1, max_depth=4))
+
+    circuit = (x, y, h, z, cnot)
+    assert random_reduce(circuit, []) == circuit
+    assert random_reduce(circuit, ids) == circuit
+
+    seq = [2, 11, 9, 3, 5]
+    circuit = (x, y, z, x, y, h)
+    assert random_reduce(circuit, ids, seed=seq) == (x, y, h)
+
+    circuit = (x, x, y, y, z, z)
+    assert random_reduce(circuit, ids, seed=seq) == (x, x, y, y)
+
+    seq = [14, 13, 0]
+    assert random_reduce(circuit, ids, seed=seq) == (y, y, z, z)
+
+    gate_list = [x, y, z, h, cnot, cgate_z]
+    ids = list(bfs_identity_search(gate_list, 2, max_depth=4))
+
+    seq = [25]
+    circuit = (x, y, z, y, h, y, h, cgate_z, h, cnot)
+    expected = (x, y, z, cgate_z, h, cnot)
+    assert random_reduce(circuit, ids, seed=seq) == expected
+    circuit = Mul(*circuit)
+    assert random_reduce(circuit, ids, seed=seq) == expected
+
+
+@slow
+def test_random_insert():
+    x = X(0)
+    y = Y(0)
+    z = Z(0)
+    h = H(0)
+    cnot = CNOT(1, 0)
+    cgate_z = CGate((0,), Z(1))
+
+    choices = [(x, x)]
+    circuit = (y, y)
+    loc, choice = 0, 0
+    actual = random_insert(circuit, choices, seed=[loc, choice])
+    assert actual == (x, x, y, y)
+
+    circuit = (x, y, z, h)
+    choices = [(h, h), (x, y, z)]
+    expected = (x, x, y, z, y, z, h)
+    loc, choice = 1, 1
+    actual = random_insert(circuit, choices, seed=[loc, choice])
+    assert actual == expected
+
+    gate_list = [x, y, z, h, cnot, cgate_z]
+    ids = list(bfs_identity_search(gate_list, 2, max_depth=4))
+
+    eq_ids = flatten_ids(ids)
+
+    circuit = (x, y, h, cnot, cgate_z)
+    expected = (x, z, x, z, x, y, h, cnot, cgate_z)
+    loc, choice = 1, 30
+    actual = random_insert(circuit, eq_ids, seed=[loc, choice])
+    assert actual == expected
+    circuit = Mul(*circuit)
+    actual = random_insert(circuit, eq_ids, seed=[loc, choice])
+    assert actual == expected

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_commutator.py

@@ -0,0 +1,81 @@
+from sympy.core.numbers import Integer
+from sympy.core.symbol import symbols
+
+from sympy.physics.quantum.dagger import Dagger
+from sympy.physics.quantum.commutator import Commutator as Comm
+from sympy.physics.quantum.operator import Operator
+
+
+a, b, c = symbols('a,b,c')
+n = symbols('n', integer=True)
+A, B, C, D = symbols('A,B,C,D', commutative=False)
+
+
+def test_commutator():
+    c = Comm(A, B)
+    assert c.is_commutative is False
+    assert isinstance(c, Comm)
+    assert c.subs(A, C) == Comm(C, B)
+
+
+def test_commutator_identities():
+    assert Comm(a*A, b*B) == a*b*Comm(A, B)
+    assert Comm(A, A) == 0
+    assert Comm(a, b) == 0
+    assert Comm(A, B) == -Comm(B, A)
+    assert Comm(A, B).doit() == A*B - B*A
+    assert Comm(A, B*C).expand(commutator=True) == Comm(A, B)*C + B*Comm(A, C)
+    assert Comm(A*B, C*D).expand(commutator=True) == \
+        A*C*Comm(B, D) + A*Comm(B, C)*D + C*Comm(A, D)*B + Comm(A, C)*D*B
+    assert Comm(A, B**2).expand(commutator=True) == Comm(A, B)*B + B*Comm(A, B)
+    assert Comm(A**2, C**2).expand(commutator=True) == \
+        Comm(A*B, C*D).expand(commutator=True).replace(B, A).replace(D, C) == \
+        A*C*Comm(A, C) + A*Comm(A, C)*C + C*Comm(A, C)*A + Comm(A, C)*C*A
+    assert Comm(A, C**-2).expand(commutator=True) == \
+        Comm(A, (1/C)*(1/D)).expand(commutator=True).replace(D, C)
+    assert Comm(A + B, C + D).expand(commutator=True) == \
+        Comm(A, C) + Comm(A, D) + Comm(B, C) + Comm(B, D)
+    assert Comm(A, B + C).expand(commutator=True) == Comm(A, B) + Comm(A, C)
+    assert Comm(A**n, B).expand(commutator=True) == Comm(A**n, B)
+
+    e = Comm(A, Comm(B, C)) + Comm(B, Comm(C, A)) + Comm(C, Comm(A, B))
+    assert e.doit().expand() == 0
+
+
+def test_commutator_dagger():
+    comm = Comm(A*B, C)
+    assert Dagger(comm).expand(commutator=True) == \
+        - Comm(Dagger(B), Dagger(C))*Dagger(A) - \
+        Dagger(B)*Comm(Dagger(A), Dagger(C))
+
+
+class Foo(Operator):
+
+    def _eval_commutator_Bar(self, bar):
+        return Integer(0)
+
+
+class Bar(Operator):
+    pass
+
+
+class Tam(Operator):
+
+    def _eval_commutator_Foo(self, foo):
+        return Integer(1)
+
+
+def test_eval_commutator():
+    F = Foo('F')
+    B = Bar('B')
+    T = Tam('T')
+    assert Comm(F, B).doit() == 0
+    assert Comm(B, F).doit() == 0
+    assert Comm(F, T).doit() == -1
+    assert Comm(T, F).doit() == 1
+    assert Comm(B, T).doit() == B*T - T*B
+    assert Comm(F**2, B).expand(commutator=True).doit() == 0
+    assert Comm(F**2, T).expand(commutator=True).doit() == -2*F
+    assert Comm(F, T**2).expand(commutator=True).doit() == -2*T
+    assert Comm(T**2, F).expand(commutator=True).doit() == 2*T
+    assert Comm(T**2, F**3).expand(commutator=True).doit() == 2*F*T*F + 2*F**2*T + 2*T*F**2

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_constants.py

@@ -0,0 +1,13 @@
+from sympy.core.numbers import Float
+
+from sympy.physics.quantum.constants import hbar
+
+
+def test_hbar():
+    assert hbar.is_commutative is True
+    assert hbar.is_real is True
+    assert hbar.is_positive is True
+    assert hbar.is_negative is False
+    assert hbar.is_irrational is True
+
+    assert hbar.evalf() == Float(1.05457162e-34)

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_dagger.py

@@ -0,0 +1,103 @@
+from sympy.core.expr import Expr
+from sympy.core.mul import Mul
+from sympy.core.numbers import (I, Integer)
+from sympy.core.symbol import symbols
+from sympy.functions.elementary.complexes import conjugate
+from sympy.matrices.dense import Matrix
+
+from sympy.physics.quantum.dagger import adjoint, Dagger
+from sympy.external import import_module
+from sympy.testing.pytest import skip, warns_deprecated_sympy
+from sympy.physics.quantum.operator import Operator, IdentityOperator
+
+
+def test_scalars():
+    x = symbols('x', complex=True)
+    assert Dagger(x) == conjugate(x)
+    assert Dagger(I*x) == -I*conjugate(x)
+
+    i = symbols('i', real=True)
+    assert Dagger(i) == i
+
+    p = symbols('p')
+    assert isinstance(Dagger(p), conjugate)
+
+    i = Integer(3)
+    assert Dagger(i) == i
+
+    A = symbols('A', commutative=False)
+    assert Dagger(A).is_commutative is False
+
+
+def test_matrix():
+    x = symbols('x')
+    m = Matrix([[I, x*I], [2, 4]])
+    assert Dagger(m) == m.H
+
+
+def test_dagger_mul():
+    O = Operator('O')
+    assert Dagger(O)*O == Dagger(O)*O
+    with warns_deprecated_sympy():
+        I = IdentityOperator()
+        assert Dagger(O)*O*I == Mul(Dagger(O), O)*I
+    assert Dagger(O)*Dagger(O) == Dagger(O)**2
+    assert Dagger(O)*Dagger(I) == Dagger(O)
+
+
+class Foo(Expr):
+
+    def _eval_adjoint(self):
+        return I
+
+
+def test_eval_adjoint():
+    f = Foo()
+    d = Dagger(f)
+    assert d == I
+
+np = import_module('numpy')
+
+
+def test_numpy_dagger():
+    if not np:
+        skip("numpy not installed.")
+
+    a = np.array([[1.0, 2.0j], [-1.0j, 2.0]])
+    adag = a.copy().transpose().conjugate()
+    assert (Dagger(a) == adag).all()
+
+
+scipy = import_module('scipy', import_kwargs={'fromlist': ['sparse']})
+
+
+def test_scipy_sparse_dagger():
+    if not np:
+        skip("numpy not installed.")
+    if not scipy:
+        skip("scipy not installed.")
+    else:
+        sparse = scipy.sparse
+
+    a = sparse.csr_matrix([[1.0 + 0.0j, 2.0j], [-1.0j, 2.0 + 0.0j]])
+    adag = a.copy().transpose().conjugate()
+    assert np.linalg.norm((Dagger(a) - adag).todense()) == 0.0
+
+
+def test_unknown():
+    """Check treatment of unknown objects.
+    Objects without adjoint or conjugate/transpose methods
+    are sympified and wrapped in dagger.
+    """
+    x = symbols("x", commutative=False)
+    result = Dagger(x)
+    assert result.args == (x,) and isinstance(result, adjoint)
+
+
+def test_unevaluated():
+    """Check that evaluate=False returns unevaluated Dagger.
+    """
+    x = symbols("x", real=True)
+    assert Dagger(x) == x
+    result = Dagger(x, evaluate=False)
+    assert result.args == (x,) and isinstance(result, adjoint)

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_density.py

@@ -0,0 +1,289 @@
+from sympy.core.numbers import Rational
+from sympy.core.singleton import S
+from sympy.core.symbol import symbols
+from sympy.functions.elementary.exponential import log
+from sympy.external import import_module
+from sympy.physics.quantum.density import Density, entropy, fidelity
+from sympy.physics.quantum.state import Ket, TimeDepKet
+from sympy.physics.quantum.qubit import Qubit
+from sympy.physics.quantum.represent import represent
+from sympy.physics.quantum.dagger import Dagger
+from sympy.physics.quantum.cartesian import XKet, PxKet, PxOp, XOp
+from sympy.physics.quantum.spin import JzKet
+from sympy.physics.quantum.operator import OuterProduct
+from sympy.physics.quantum.trace import Tr
+from sympy.functions import sqrt
+from sympy.testing.pytest import raises
+from sympy.physics.quantum.matrixutils import scipy_sparse_matrix
+from sympy.physics.quantum.tensorproduct import TensorProduct
+
+
+def test_eval_args():
+    # check instance created
+    assert isinstance(Density([Ket(0), 0.5], [Ket(1), 0.5]), Density)
+    assert isinstance(Density([Qubit('00'), 1/sqrt(2)],
+                              [Qubit('11'), 1/sqrt(2)]), Density)
+
+    #test if Qubit object type preserved
+    d = Density([Qubit('00'), 1/sqrt(2)], [Qubit('11'), 1/sqrt(2)])
+    for (state, prob) in d.args:
+        assert isinstance(state, Qubit)
+
+    # check for value error, when prob is not provided
+    raises(ValueError, lambda: Density([Ket(0)], [Ket(1)]))
+
+
+def test_doit():
+
+    x, y = symbols('x y')
+    A, B, C, D, E, F = symbols('A B C D E F', commutative=False)
+    d = Density([XKet(), 0.5], [PxKet(), 0.5])
+    assert (0.5*(PxKet()*Dagger(PxKet())) +
+            0.5*(XKet()*Dagger(XKet()))) == d.doit()
+
+    # check for kets with expr in them
+    d_with_sym = Density([XKet(x*y), 0.5], [PxKet(x*y), 0.5])
+    assert (0.5*(PxKet(x*y)*Dagger(PxKet(x*y))) +
+            0.5*(XKet(x*y)*Dagger(XKet(x*y)))) == d_with_sym.doit()
+
+    d = Density([(A + B)*C, 1.0])
+    assert d.doit() == (1.0*A*C*Dagger(C)*Dagger(A) +
+                        1.0*A*C*Dagger(C)*Dagger(B) +
+                        1.0*B*C*Dagger(C)*Dagger(A) +
+                        1.0*B*C*Dagger(C)*Dagger(B))
+
+    #  With TensorProducts as args
+    # Density with simple tensor products as args
+    t = TensorProduct(A, B, C)
+    d = Density([t, 1.0])
+    assert d.doit() == \
+        1.0 * TensorProduct(A*Dagger(A), B*Dagger(B), C*Dagger(C))
+
+    # Density with multiple Tensorproducts as states
+    t2 = TensorProduct(A, B)
+    t3 = TensorProduct(C, D)
+
+    d = Density([t2, 0.5], [t3, 0.5])
+    assert d.doit() == (0.5 * TensorProduct(A*Dagger(A), B*Dagger(B)) +
+                        0.5 * TensorProduct(C*Dagger(C), D*Dagger(D)))
+
+    #Density with mixed states
+    d = Density([t2 + t3, 1.0])
+    assert d.doit() == (1.0 * TensorProduct(A*Dagger(A), B*Dagger(B)) +
+                        1.0 * TensorProduct(A*Dagger(C), B*Dagger(D)) +
+                        1.0 * TensorProduct(C*Dagger(A), D*Dagger(B)) +
+                        1.0 * TensorProduct(C*Dagger(C), D*Dagger(D)))
+
+    #Density operators with spin states
+    tp1 = TensorProduct(JzKet(1, 1), JzKet(1, -1))
+    d = Density([tp1, 1])
+
+    # full trace
+    t = Tr(d)
+    assert t.doit() == 1
+
+    #Partial trace on density operators with spin states
+    t = Tr(d, [0])
+    assert t.doit() == JzKet(1, -1) * Dagger(JzKet(1, -1))
+    t = Tr(d, [1])
+    assert t.doit() == JzKet(1, 1) * Dagger(JzKet(1, 1))
+
+    # with another spin state
+    tp2 = TensorProduct(JzKet(S.Half, S.Half), JzKet(S.Half, Rational(-1, 2)))
+    d = Density([tp2, 1])
+
+    #full trace
+    t = Tr(d)
+    assert t.doit() == 1
+
+    #Partial trace on density operators with spin states
+    t = Tr(d, [0])
+    assert t.doit() == JzKet(S.Half, Rational(-1, 2)) * Dagger(JzKet(S.Half, Rational(-1, 2)))
+    t = Tr(d, [1])
+    assert t.doit() == JzKet(S.Half, S.Half) * Dagger(JzKet(S.Half, S.Half))
+
+
+def test_apply_op():
+    d = Density([Ket(0), 0.5], [Ket(1), 0.5])
+    assert d.apply_op(XOp()) == Density([XOp()*Ket(0), 0.5],
+                                        [XOp()*Ket(1), 0.5])
+
+
+def test_represent():
+    x, y = symbols('x y')
+    d = Density([XKet(), 0.5], [PxKet(), 0.5])
+    assert (represent(0.5*(PxKet()*Dagger(PxKet()))) +
+            represent(0.5*(XKet()*Dagger(XKet())))) == represent(d)
+
+    # check for kets with expr in them
+    d_with_sym = Density([XKet(x*y), 0.5], [PxKet(x*y), 0.5])
+    assert (represent(0.5*(PxKet(x*y)*Dagger(PxKet(x*y)))) +
+            represent(0.5*(XKet(x*y)*Dagger(XKet(x*y))))) == \
+        represent(d_with_sym)
+
+    # check when given explicit basis
+    assert (represent(0.5*(XKet()*Dagger(XKet())), basis=PxOp()) +
+            represent(0.5*(PxKet()*Dagger(PxKet())), basis=PxOp())) == \
+        represent(d, basis=PxOp())
+
+
+def test_states():
+    d = Density([Ket(0), 0.5], [Ket(1), 0.5])
+    states = d.states()
+    assert states[0] == Ket(0) and states[1] == Ket(1)
+
+
+def test_probs():
+    d = Density([Ket(0), .75], [Ket(1), 0.25])
+    probs = d.probs()
+    assert probs[0] == 0.75 and probs[1] == 0.25
+
+    #probs can be symbols
+    x, y = symbols('x y')
+    d = Density([Ket(0), x], [Ket(1), y])
+    probs = d.probs()
+    assert probs[0] == x and probs[1] == y
+
+
+def test_get_state():
+    x, y = symbols('x y')
+    d = Density([Ket(0), x], [Ket(1), y])
+    states = (d.get_state(0), d.get_state(1))
+    assert states[0] == Ket(0) and states[1] == Ket(1)
+
+
+def test_get_prob():
+    x, y = symbols('x y')
+    d = Density([Ket(0), x], [Ket(1), y])
+    probs = (d.get_prob(0), d.get_prob(1))
+    assert probs[0] == x and probs[1] == y
+
+
+def test_entropy():
+    up = JzKet(S.Half, S.Half)
+    down = JzKet(S.Half, Rational(-1, 2))
+    d = Density((up, S.Half), (down, S.Half))
+
+    # test for density object
+    ent = entropy(d)
+    assert entropy(d) == log(2)/2
+    assert d.entropy() == log(2)/2
+
+    np = import_module('numpy', min_module_version='1.4.0')
+    if np:
+        #do this test only if 'numpy' is available on test machine
+        np_mat = represent(d, format='numpy')
+        ent = entropy(np_mat)
+        assert isinstance(np_mat, np.ndarray)
+        assert ent.real == 0.69314718055994529
+        assert ent.imag == 0
+
+    scipy = import_module('scipy', import_kwargs={'fromlist': ['sparse']})
+    if scipy and np:
+        #do this test only if numpy and scipy are available
+        mat = represent(d, format="scipy.sparse")
+        assert isinstance(mat, scipy_sparse_matrix)
+        assert ent.real == 0.69314718055994529
+        assert ent.imag == 0
+
+
+def test_eval_trace():
+    up = JzKet(S.Half, S.Half)
+    down = JzKet(S.Half, Rational(-1, 2))
+    d = Density((up, 0.5), (down, 0.5))
+
+    t = Tr(d)
+    assert t.doit() == 1.0
+
+    #test dummy time dependent states
+    class TestTimeDepKet(TimeDepKet):
+        def _eval_trace(self, bra, **options):
+            return 1
+
+    x, t = symbols('x t')
+    k1 = TestTimeDepKet(0, 0.5)
+    k2 = TestTimeDepKet(0, 1)
+    d = Density([k1, 0.5], [k2, 0.5])
+    assert d.doit() == (0.5 * OuterProduct(k1, k1.dual) +
+                        0.5 * OuterProduct(k2, k2.dual))
+
+    t = Tr(d)
+    assert t.doit() == 1.0
+
+
+def test_fidelity():
+    #test with kets
+    up = JzKet(S.Half, S.Half)
+    down = JzKet(S.Half, Rational(-1, 2))
+    updown = (S.One/sqrt(2))*up + (S.One/sqrt(2))*down
+
+    #check with matrices
+    up_dm = represent(up * Dagger(up))
+    down_dm = represent(down * Dagger(down))
+    updown_dm = represent(updown * Dagger(updown))
+
+    assert abs(fidelity(up_dm, up_dm) - 1) < 1e-3
+    assert fidelity(up_dm, down_dm) < 1e-3
+    assert abs(fidelity(up_dm, updown_dm) - (S.One/sqrt(2))) < 1e-3
+    assert abs(fidelity(updown_dm, down_dm) - (S.One/sqrt(2))) < 1e-3
+
+    #check with density
+    up_dm = Density([up, 1.0])
+    down_dm = Density([down, 1.0])
+    updown_dm = Density([updown, 1.0])
+
+    assert abs(fidelity(up_dm, up_dm) - 1) < 1e-3
+    assert abs(fidelity(up_dm, down_dm)) < 1e-3
+    assert abs(fidelity(up_dm, updown_dm) - (S.One/sqrt(2))) < 1e-3
+    assert abs(fidelity(updown_dm, down_dm) - (S.One/sqrt(2))) < 1e-3
+
+    #check mixed states with density
+    updown2 = sqrt(3)/2*up + S.Half*down
+    d1 = Density([updown, 0.25], [updown2, 0.75])
+    d2 = Density([updown, 0.75], [updown2, 0.25])
+    assert abs(fidelity(d1, d2) - 0.991) < 1e-3
+    assert abs(fidelity(d2, d1) - fidelity(d1, d2)) < 1e-3
+
+    #using qubits/density(pure states)
+    state1 = Qubit('0')
+    state2 = Qubit('1')
+    state3 = S.One/sqrt(2)*state1 + S.One/sqrt(2)*state2
+    state4 = sqrt(Rational(2, 3))*state1 + S.One/sqrt(3)*state2
+
+    state1_dm = Density([state1, 1])
+    state2_dm = Density([state2, 1])
+    state3_dm = Density([state3, 1])
+
+    assert fidelity(state1_dm, state1_dm) == 1
+    assert fidelity(state1_dm, state2_dm) == 0
+    assert abs(fidelity(state1_dm, state3_dm) - 1/sqrt(2)) < 1e-3
+    assert abs(fidelity(state3_dm, state2_dm) - 1/sqrt(2)) < 1e-3
+
+    #using qubits/density(mixed states)
+    d1 = Density([state3, 0.70], [state4, 0.30])
+    d2 = Density([state3, 0.20], [state4, 0.80])
+    assert abs(fidelity(d1, d1) - 1) < 1e-3
+    assert abs(fidelity(d1, d2) - 0.996) < 1e-3
+    assert abs(fidelity(d1, d2) - fidelity(d2, d1)) < 1e-3
+
+    #TODO: test for invalid arguments
+    # non-square matrix
+    mat1 = [[0, 0],
+            [0, 0],
+            [0, 0]]
+
+    mat2 = [[0, 0],
+            [0, 0]]
+    raises(ValueError, lambda: fidelity(mat1, mat2))
+
+    # unequal dimensions
+    mat1 = [[0, 0],
+            [0, 0]]
+    mat2 = [[0, 0, 0],
+            [0, 0, 0],
+            [0, 0, 0]]
+    raises(ValueError, lambda: fidelity(mat1, mat2))
+
+    # unsupported data-type
+    x, y = 1, 2  # random values that is not a matrix
+    raises(ValueError, lambda: fidelity(x, y))

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_fermion.py

@@ -0,0 +1,62 @@
+from pytest import raises
+
+import sympy
+from sympy.physics.quantum import Dagger, AntiCommutator, qapply
+from sympy.physics.quantum.fermion import FermionOp
+from sympy.physics.quantum.fermion import FermionFockKet, FermionFockBra
+from sympy import Symbol
+
+
+def test_fermionoperator():
+    c = FermionOp('c')
+    d = FermionOp('d')
+
+    assert isinstance(c, FermionOp)
+    assert isinstance(Dagger(c), FermionOp)
+
+    assert c.is_annihilation
+    assert not Dagger(c).is_annihilation
+
+    assert FermionOp("c") == FermionOp("c", True)
+    assert FermionOp("c") != FermionOp("d")
+    assert FermionOp("c", True) != FermionOp("c", False)
+
+    assert AntiCommutator(c, Dagger(c)).doit() == 1
+
+    assert AntiCommutator(c, Dagger(d)).doit() == c * Dagger(d) + Dagger(d) * c
+
+
+def test_fermion_states():
+    c = FermionOp("c")
+
+    # Fock states
+    assert (FermionFockBra(0) * FermionFockKet(1)).doit() == 0
+    assert (FermionFockBra(1) * FermionFockKet(1)).doit() == 1
+
+    assert qapply(c * FermionFockKet(1)) == FermionFockKet(0)
+    assert qapply(c * FermionFockKet(0)) == 0
+
+    assert qapply(Dagger(c) * FermionFockKet(0)) == FermionFockKet(1)
+    assert qapply(Dagger(c) * FermionFockKet(1)) == 0
+
+
+def test_power():
+    c = FermionOp("c")
+    assert c**0 == 1
+    assert c**1 == c
+    assert c**2 == 0
+    assert c**3 == 0
+    assert Dagger(c)**1 == Dagger(c)
+    assert Dagger(c)**2 == 0
+
+    assert (c**Symbol('a')).func == sympy.core.power.Pow
+    assert (c**Symbol('a')).args == (c, Symbol('a'))
+
+    with raises(ValueError):
+        c**-1
+
+    with raises(ValueError):
+        c**3.2
+
+    with raises(TypeError):
+        c**1j

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_gate.py

@@ -0,0 +1,360 @@
+from sympy.core.mul import Mul
+from sympy.core.numbers import (I, Integer, Rational, pi)
+from sympy.core.symbol import (Wild, symbols)
+from sympy.functions.elementary.exponential import exp
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.matrices import Matrix, ImmutableMatrix
+
+from sympy.physics.quantum.gate import (XGate, YGate, ZGate, random_circuit,
+        CNOT, IdentityGate, H, X, Y, S, T, Z, SwapGate, gate_simp, gate_sort,
+        CNotGate, TGate, HadamardGate, PhaseGate, UGate, CGate)
+from sympy.physics.quantum.commutator import Commutator
+from sympy.physics.quantum.anticommutator import AntiCommutator
+from sympy.physics.quantum.represent import represent
+from sympy.physics.quantum.qapply import qapply
+from sympy.physics.quantum.qubit import Qubit, IntQubit, qubit_to_matrix, \
+    matrix_to_qubit
+from sympy.physics.quantum.matrixutils import matrix_to_zero
+from sympy.physics.quantum.matrixcache import sqrt2_inv
+from sympy.physics.quantum import Dagger
+
+
+def test_gate():
+    """Test a basic gate."""
+    h = HadamardGate(1)
+    assert h.min_qubits == 2
+    assert h.nqubits == 1
+
+    i0 = Wild('i0')
+    i1 = Wild('i1')
+    h0_w1 = HadamardGate(i0)
+    h0_w2 = HadamardGate(i0)
+    h1_w1 = HadamardGate(i1)
+
+    assert h0_w1 == h0_w2
+    assert h0_w1 != h1_w1
+    assert h1_w1 != h0_w2
+
+    cnot_10_w1 = CNOT(i1, i0)
+    cnot_10_w2 = CNOT(i1, i0)
+    cnot_01_w1 = CNOT(i0, i1)
+
+    assert cnot_10_w1 == cnot_10_w2
+    assert cnot_10_w1 != cnot_01_w1
+    assert cnot_10_w2 != cnot_01_w1
+
+
+def test_UGate():
+    a, b, c, d = symbols('a,b,c,d')
+    uMat = Matrix([[a, b], [c, d]])
+
+    # Test basic case where gate exists in 1-qubit space
+    u1 = UGate((0,), uMat)
+    assert represent(u1, nqubits=1) == uMat
+    assert qapply(u1*Qubit('0')) == a*Qubit('0') + c*Qubit('1')
+    assert qapply(u1*Qubit('1')) == b*Qubit('0') + d*Qubit('1')
+
+    # Test case where gate exists in a larger space
+    u2 = UGate((1,), uMat)
+    u2Rep = represent(u2, nqubits=2)
+    for i in range(4):
+        assert u2Rep*qubit_to_matrix(IntQubit(i, 2)) == \
+            qubit_to_matrix(qapply(u2*IntQubit(i, 2)))
+
+
+def test_cgate():
+    """Test the general CGate."""
+    # Test single control functionality
+    CNOTMatrix = Matrix(
+        [[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 0, 1], [0, 0, 1, 0]])
+    assert represent(CGate(1, XGate(0)), nqubits=2) == CNOTMatrix
+
+    # Test multiple control bit functionality
+    ToffoliGate = CGate((1, 2), XGate(0))
+    assert represent(ToffoliGate, nqubits=3) == \
+        Matrix(
+            [[1, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0],
+    [0, 0, 0, 1, 0, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0,
+        1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 1],
+    [0, 0, 0, 0, 0, 0, 1, 0]])
+
+    ToffoliGate = CGate((3, 0), XGate(1))
+    assert qapply(ToffoliGate*Qubit('1001')) == \
+        matrix_to_qubit(represent(ToffoliGate*Qubit('1001'), nqubits=4))
+    assert qapply(ToffoliGate*Qubit('0000')) == \
+        matrix_to_qubit(represent(ToffoliGate*Qubit('0000'), nqubits=4))
+
+    CYGate = CGate(1, YGate(0))
+    CYGate_matrix = Matrix(
+        ((1, 0, 0, 0), (0, 1, 0, 0), (0, 0, 0, -I), (0, 0, I, 0)))
+    # Test 2 qubit controlled-Y gate decompose method.
+    assert represent(CYGate.decompose(), nqubits=2) == CYGate_matrix
+
+    CZGate = CGate(0, ZGate(1))
+    CZGate_matrix = Matrix(
+        ((1, 0, 0, 0), (0, 1, 0, 0), (0, 0, 1, 0), (0, 0, 0, -1)))
+    assert qapply(CZGate*Qubit('11')) == -Qubit('11')
+    assert matrix_to_qubit(represent(CZGate*Qubit('11'), nqubits=2)) == \
+        -Qubit('11')
+    # Test 2 qubit controlled-Z gate decompose method.
+    assert represent(CZGate.decompose(), nqubits=2) == CZGate_matrix
+
+    CPhaseGate = CGate(0, PhaseGate(1))
+    assert qapply(CPhaseGate*Qubit('11')) == \
+        I*Qubit('11')
+    assert matrix_to_qubit(represent(CPhaseGate*Qubit('11'), nqubits=2)) == \
+        I*Qubit('11')
+
+    # Test that the dagger, inverse, and power of CGate is evaluated properly
+    assert Dagger(CZGate) == CZGate
+    assert pow(CZGate, 1) == Dagger(CZGate)
+    assert Dagger(CZGate) == CZGate.inverse()
+    assert Dagger(CPhaseGate) != CPhaseGate
+    assert Dagger(CPhaseGate) == CPhaseGate.inverse()
+    assert Dagger(CPhaseGate) == pow(CPhaseGate, -1)
+    assert pow(CPhaseGate, -1) == CPhaseGate.inverse()
+
+
+def test_UGate_CGate_combo():
+    a, b, c, d = symbols('a,b,c,d')
+    uMat = Matrix([[a, b], [c, d]])
+    cMat = Matrix([[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, a, b], [0, 0, c, d]])
+
+    # Test basic case where gate exists in 1-qubit space.
+    u1 = UGate((0,), uMat)
+    cu1 = CGate(1, u1)
+    assert represent(cu1, nqubits=2) == cMat
+    assert qapply(cu1*Qubit('10')) == a*Qubit('10') + c*Qubit('11')
+    assert qapply(cu1*Qubit('11')) == b*Qubit('10') + d*Qubit('11')
+    assert qapply(cu1*Qubit('01')) == Qubit('01')
+    assert qapply(cu1*Qubit('00')) == Qubit('00')
+
+    # Test case where gate exists in a larger space.
+    u2 = UGate((1,), uMat)
+    u2Rep = represent(u2, nqubits=2)
+    for i in range(4):
+        assert u2Rep*qubit_to_matrix(IntQubit(i, 2)) == \
+            qubit_to_matrix(qapply(u2*IntQubit(i, 2)))
+
+def test_UGate_OneQubitGate_combo():
+    v, w, f, g = symbols('v w f g')
+    uMat1 = ImmutableMatrix([[v, w], [f, g]])
+    cMat1 = Matrix([[v, w + 1, 0, 0], [f + 1, g, 0, 0], [0, 0, v, w + 1], [0, 0, f + 1, g]])
+    u1 = X(0) + UGate(0, uMat1)
+    assert represent(u1, nqubits=2) == cMat1
+
+    uMat2 = ImmutableMatrix([[1/sqrt(2), 1/sqrt(2)], [I/sqrt(2), -I/sqrt(2)]])
+    cMat2_1 = Matrix([[Rational(1, 2) + I/2, Rational(1, 2) - I/2],
+                      [Rational(1, 2) - I/2, Rational(1, 2) + I/2]])
+    cMat2_2 = Matrix([[1, 0], [0, I]])
+    u2 = UGate(0, uMat2)
+    assert represent(H(0)*u2, nqubits=1) == cMat2_1
+    assert represent(u2*H(0), nqubits=1) == cMat2_2
+
+def test_represent_hadamard():
+    """Test the representation of the hadamard gate."""
+    circuit = HadamardGate(0)*Qubit('00')
+    answer = represent(circuit, nqubits=2)
+    # Check that the answers are same to within an epsilon.
+    assert answer == Matrix([sqrt2_inv, sqrt2_inv, 0, 0])
+
+
+def test_represent_xgate():
+    """Test the representation of the X gate."""
+    circuit = XGate(0)*Qubit('00')
+    answer = represent(circuit, nqubits=2)
+    assert Matrix([0, 1, 0, 0]) == answer
+
+
+def test_represent_ygate():
+    """Test the representation of the Y gate."""
+    circuit = YGate(0)*Qubit('00')
+    answer = represent(circuit, nqubits=2)
+    assert answer[0] == 0 and answer[1] == I and \
+        answer[2] == 0 and answer[3] == 0
+
+
+def test_represent_zgate():
+    """Test the representation of the Z gate."""
+    circuit = ZGate(0)*Qubit('00')
+    answer = represent(circuit, nqubits=2)
+    assert Matrix([1, 0, 0, 0]) == answer
+
+
+def test_represent_phasegate():
+    """Test the representation of the S gate."""
+    circuit = PhaseGate(0)*Qubit('01')
+    answer = represent(circuit, nqubits=2)
+    assert Matrix([0, I, 0, 0]) == answer
+
+
+def test_represent_tgate():
+    """Test the representation of the T gate."""
+    circuit = TGate(0)*Qubit('01')
+    assert Matrix([0, exp(I*pi/4), 0, 0]) == represent(circuit, nqubits=2)
+
+
+def test_compound_gates():
+    """Test a compound gate representation."""
+    circuit = YGate(0)*ZGate(0)*XGate(0)*HadamardGate(0)*Qubit('00')
+    answer = represent(circuit, nqubits=2)
+    assert Matrix([I/sqrt(2), I/sqrt(2), 0, 0]) == answer
+
+
+def test_cnot_gate():
+    """Test the CNOT gate."""
+    circuit = CNotGate(1, 0)
+    assert represent(circuit, nqubits=2) == \
+        Matrix([[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 0, 1], [0, 0, 1, 0]])
+    circuit = circuit*Qubit('111')
+    assert matrix_to_qubit(represent(circuit, nqubits=3)) == \
+        qapply(circuit)
+
+    circuit = CNotGate(1, 0)
+    assert Dagger(circuit) == circuit
+    assert Dagger(Dagger(circuit)) == circuit
+    assert circuit*circuit == 1
+
+
+def test_gate_sort():
+    """Test gate_sort."""
+    for g in (X, Y, Z, H, S, T):
+        assert gate_sort(g(2)*g(1)*g(0)) == g(0)*g(1)*g(2)
+    e = gate_sort(X(1)*H(0)**2*CNOT(0, 1)*X(1)*X(0))
+    assert e == H(0)**2*CNOT(0, 1)*X(0)*X(1)**2
+    assert gate_sort(Z(0)*X(0)) == -X(0)*Z(0)
+    assert gate_sort(Z(0)*X(0)**2) == X(0)**2*Z(0)
+    assert gate_sort(Y(0)*H(0)) == -H(0)*Y(0)
+    assert gate_sort(Y(0)*X(0)) == -X(0)*Y(0)
+    assert gate_sort(Z(0)*Y(0)) == -Y(0)*Z(0)
+    assert gate_sort(T(0)*S(0)) == S(0)*T(0)
+    assert gate_sort(Z(0)*S(0)) == S(0)*Z(0)
+    assert gate_sort(Z(0)*T(0)) == T(0)*Z(0)
+    assert gate_sort(Z(0)*CNOT(0, 1)) == CNOT(0, 1)*Z(0)
+    assert gate_sort(S(0)*CNOT(0, 1)) == CNOT(0, 1)*S(0)
+    assert gate_sort(T(0)*CNOT(0, 1)) == CNOT(0, 1)*T(0)
+    assert gate_sort(X(1)*CNOT(0, 1)) == CNOT(0, 1)*X(1)
+    # This takes a long time and should only be uncommented once in a while.
+    # nqubits = 5
+    # ngates = 10
+    # trials = 10
+    # for i in range(trials):
+    #     c = random_circuit(ngates, nqubits)
+    #     assert represent(c, nqubits=nqubits) == \
+    #            represent(gate_sort(c), nqubits=nqubits)
+
+
+def test_gate_simp():
+    """Test gate_simp."""
+    e = H(0)*X(1)*H(0)**2*CNOT(0, 1)*X(1)**3*X(0)*Z(3)**2*S(4)**3
+    assert gate_simp(e) == H(0)*CNOT(0, 1)*S(4)*X(0)*Z(4)
+    assert gate_simp(X(0)*X(0)) == 1
+    assert gate_simp(Y(0)*Y(0)) == 1
+    assert gate_simp(Z(0)*Z(0)) == 1
+    assert gate_simp(H(0)*H(0)) == 1
+    assert gate_simp(T(0)*T(0)) == S(0)
+    assert gate_simp(S(0)*S(0)) == Z(0)
+    assert gate_simp(Integer(1)) == Integer(1)
+    assert gate_simp(X(0)**2 + Y(0)**2) == Integer(2)
+
+
+def test_swap_gate():
+    """Test the SWAP gate."""
+    swap_gate_matrix = Matrix(
+        ((1, 0, 0, 0), (0, 0, 1, 0), (0, 1, 0, 0), (0, 0, 0, 1)))
+    assert represent(SwapGate(1, 0).decompose(), nqubits=2) == swap_gate_matrix
+    assert qapply(SwapGate(1, 3)*Qubit('0010')) == Qubit('1000')
+    nqubits = 4
+    for i in range(nqubits):
+        for j in range(i):
+            assert represent(SwapGate(i, j), nqubits=nqubits) == \
+                represent(SwapGate(i, j).decompose(), nqubits=nqubits)
+
+
+def test_one_qubit_commutators():
+    """Test single qubit gate commutation relations."""
+    for g1 in (IdentityGate, X, Y, Z, H, T, S):
+        for g2 in (IdentityGate, X, Y, Z, H, T, S):
+            e = Commutator(g1(0), g2(0))
+            a = matrix_to_zero(represent(e, nqubits=1, format='sympy'))
+            b = matrix_to_zero(represent(e.doit(), nqubits=1, format='sympy'))
+            assert a == b
+
+            e = Commutator(g1(0), g2(1))
+            assert e.doit() == 0
+
+
+def test_one_qubit_anticommutators():
+    """Test single qubit gate anticommutation relations."""
+    for g1 in (IdentityGate, X, Y, Z, H):
+        for g2 in (IdentityGate, X, Y, Z, H):
+            e = AntiCommutator(g1(0), g2(0))
+            a = matrix_to_zero(represent(e, nqubits=1, format='sympy'))
+            b = matrix_to_zero(represent(e.doit(), nqubits=1, format='sympy'))
+            assert a == b
+            e = AntiCommutator(g1(0), g2(1))
+            a = matrix_to_zero(represent(e, nqubits=2, format='sympy'))
+            b = matrix_to_zero(represent(e.doit(), nqubits=2, format='sympy'))
+            assert a == b
+
+
+def test_cnot_commutators():
+    """Test commutators of involving CNOT gates."""
+    assert Commutator(CNOT(0, 1), Z(0)).doit() == 0
+    assert Commutator(CNOT(0, 1), T(0)).doit() == 0
+    assert Commutator(CNOT(0, 1), S(0)).doit() == 0
+    assert Commutator(CNOT(0, 1), X(1)).doit() == 0
+    assert Commutator(CNOT(0, 1), CNOT(0, 1)).doit() == 0
+    assert Commutator(CNOT(0, 1), CNOT(0, 2)).doit() == 0
+    assert Commutator(CNOT(0, 2), CNOT(0, 1)).doit() == 0
+    assert Commutator(CNOT(1, 2), CNOT(1, 0)).doit() == 0
+
+
+def test_random_circuit():
+    c = random_circuit(10, 3)
+    assert isinstance(c, Mul)
+    m = represent(c, nqubits=3)
+    assert m.shape == (8, 8)
+    assert isinstance(m, Matrix)
+
+
+def test_hermitian_XGate():
+    x = XGate(1, 2)
+    x_dagger = Dagger(x)
+
+    assert (x == x_dagger)
+
+
+def test_hermitian_YGate():
+    y = YGate(1, 2)
+    y_dagger = Dagger(y)
+
+    assert (y == y_dagger)
+
+
+def test_hermitian_ZGate():
+    z = ZGate(1, 2)
+    z_dagger = Dagger(z)
+
+    assert (z == z_dagger)
+
+
+def test_unitary_XGate():
+    x = XGate(1, 2)
+    x_dagger = Dagger(x)
+
+    assert (x*x_dagger == 1)
+
+
+def test_unitary_YGate():
+    y = YGate(1, 2)
+    y_dagger = Dagger(y)
+
+    assert (y*y_dagger == 1)
+
+
+def test_unitary_ZGate():
+    z = ZGate(1, 2)
+    z_dagger = Dagger(z)
+
+    assert (z*z_dagger == 1)

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_grover.py

@@ -0,0 +1,92 @@
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.matrices.dense import Matrix
+from sympy.physics.quantum.represent import represent
+from sympy.physics.quantum.qapply import qapply
+from sympy.physics.quantum.qubit import IntQubit
+from sympy.physics.quantum.grover import (apply_grover, superposition_basis,
+        OracleGate, grover_iteration, WGate)
+
+
+def return_one_on_two(qubits):
+    return qubits == IntQubit(2, qubits.nqubits)
+
+
+def return_one_on_one(qubits):
+    return qubits == IntQubit(1, nqubits=qubits.nqubits)
+
+
+def test_superposition_basis():
+    nbits = 2
+    first_half_state = IntQubit(0, nqubits=nbits)/2 + IntQubit(1, nqubits=nbits)/2
+    second_half_state = IntQubit(2, nbits)/2 + IntQubit(3, nbits)/2
+    assert first_half_state + second_half_state == superposition_basis(nbits)
+
+    nbits = 3
+    firstq = (1/sqrt(8))*IntQubit(0, nqubits=nbits) + (1/sqrt(8))*IntQubit(1, nqubits=nbits)
+    secondq = (1/sqrt(8))*IntQubit(2, nbits) + (1/sqrt(8))*IntQubit(3, nbits)
+    thirdq = (1/sqrt(8))*IntQubit(4, nbits) + (1/sqrt(8))*IntQubit(5, nbits)
+    fourthq = (1/sqrt(8))*IntQubit(6, nbits) + (1/sqrt(8))*IntQubit(7, nbits)
+    assert firstq + secondq + thirdq + fourthq == superposition_basis(nbits)
+
+
+def test_OracleGate():
+    v = OracleGate(1, lambda qubits: qubits == IntQubit(0))
+    assert qapply(v*IntQubit(0)) == -IntQubit(0)
+    assert qapply(v*IntQubit(1)) == IntQubit(1)
+
+    nbits = 2
+    v = OracleGate(2, return_one_on_two)
+    assert qapply(v*IntQubit(0, nbits)) == IntQubit(0, nqubits=nbits)
+    assert qapply(v*IntQubit(1, nbits)) == IntQubit(1, nqubits=nbits)
+    assert qapply(v*IntQubit(2, nbits)) == -IntQubit(2, nbits)
+    assert qapply(v*IntQubit(3, nbits)) == IntQubit(3, nbits)
+
+    assert represent(OracleGate(1, lambda qubits: qubits == IntQubit(0)), nqubits=1) == \
+           Matrix([[-1, 0], [0, 1]])
+    assert represent(v, nqubits=2) == Matrix([[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, -1, 0], [0, 0, 0, 1]])
+
+
+def test_WGate():
+    nqubits = 2
+    basis_states = superposition_basis(nqubits)
+    assert qapply(WGate(nqubits)*basis_states) == basis_states
+
+    expected = ((2/sqrt(pow(2, nqubits)))*basis_states) - IntQubit(1, nqubits=nqubits)
+    assert qapply(WGate(nqubits)*IntQubit(1, nqubits=nqubits)) == expected
+
+
+def test_grover_iteration_1():
+    numqubits = 2
+    basis_states = superposition_basis(numqubits)
+    v = OracleGate(numqubits, return_one_on_one)
+    expected = IntQubit(1, nqubits=numqubits)
+    assert qapply(grover_iteration(basis_states, v)) == expected
+
+
+def test_grover_iteration_2():
+    numqubits = 4
+    basis_states = superposition_basis(numqubits)
+    v = OracleGate(numqubits, return_one_on_two)
+    # After (pi/4)sqrt(pow(2, n)), IntQubit(2) should have highest prob
+    # In this case, after around pi times (3 or 4)
+    iterated = grover_iteration(basis_states, v)
+    iterated = qapply(iterated)
+    iterated = grover_iteration(iterated, v)
+    iterated = qapply(iterated)
+    iterated = grover_iteration(iterated, v)
+    iterated = qapply(iterated)
+    # In this case, probability was highest after 3 iterations
+    # Probability of Qubit('0010') was 251/256 (3) vs 781/1024 (4)
+    # Ask about measurement
+    expected = (-13*basis_states)/64 + 264*IntQubit(2, numqubits)/256
+    assert qapply(expected) == iterated
+
+
+def test_grover():
+    nqubits = 2
+    assert apply_grover(return_one_on_one, nqubits) == IntQubit(1, nqubits=nqubits)
+
+    nqubits = 4
+    basis_states = superposition_basis(nqubits)
+    expected = (-13*basis_states)/64 + 264*IntQubit(2, nqubits)/256
+    assert apply_grover(return_one_on_two, 4) == qapply(expected)

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_hilbert.py

@@ -0,0 +1,110 @@
+from sympy.physics.quantum.hilbert import (
+    HilbertSpace, ComplexSpace, L2, FockSpace, TensorProductHilbertSpace,
+    DirectSumHilbertSpace, TensorPowerHilbertSpace
+)
+
+from sympy.core.numbers import oo
+from sympy.core.symbol import Symbol
+from sympy.printing.repr import srepr
+from sympy.printing.str import sstr
+from sympy.sets.sets import Interval
+
+
+def test_hilbert_space():
+    hs = HilbertSpace()
+    assert isinstance(hs, HilbertSpace)
+    assert sstr(hs) == 'H'
+    assert srepr(hs) == 'HilbertSpace()'
+
+
+def test_complex_space():
+    c1 = ComplexSpace(2)
+    assert isinstance(c1, ComplexSpace)
+    assert c1.dimension == 2
+    assert sstr(c1) == 'C(2)'
+    assert srepr(c1) == 'ComplexSpace(Integer(2))'
+
+    n = Symbol('n')
+    c2 = ComplexSpace(n)
+    assert isinstance(c2, ComplexSpace)
+    assert c2.dimension == n
+    assert sstr(c2) == 'C(n)'
+    assert srepr(c2) == "ComplexSpace(Symbol('n'))"
+    assert c2.subs(n, 2) == ComplexSpace(2)
+
+
+def test_L2():
+    b1 = L2(Interval(-oo, 1))
+    assert isinstance(b1, L2)
+    assert b1.dimension is oo
+    assert b1.interval == Interval(-oo, 1)
+
+    x = Symbol('x', real=True)
+    y = Symbol('y', real=True)
+    b2 = L2(Interval(x, y))
+    assert b2.dimension is oo
+    assert b2.interval == Interval(x, y)
+    assert b2.subs(x, -1) == L2(Interval(-1, y))
+
+
+def test_fock_space():
+    f1 = FockSpace()
+    f2 = FockSpace()
+    assert isinstance(f1, FockSpace)
+    assert f1.dimension is oo
+    assert f1 == f2
+
+
+def test_tensor_product():
+    n = Symbol('n')
+    hs1 = ComplexSpace(2)
+    hs2 = ComplexSpace(n)
+
+    h = hs1*hs2
+    assert isinstance(h, TensorProductHilbertSpace)
+    assert h.dimension == 2*n
+    assert h.spaces == (hs1, hs2)
+
+    h = hs2*hs2
+    assert isinstance(h, TensorPowerHilbertSpace)
+    assert h.base == hs2
+    assert h.exp == 2
+    assert h.dimension == n**2
+
+    f = FockSpace()
+    h = hs1*hs2*f
+    assert h.dimension is oo
+
+
+def test_tensor_power():
+    n = Symbol('n')
+    hs1 = ComplexSpace(2)
+    hs2 = ComplexSpace(n)
+
+    h = hs1**2
+    assert isinstance(h, TensorPowerHilbertSpace)
+    assert h.base == hs1
+    assert h.exp == 2
+    assert h.dimension == 4
+
+    h = hs2**3
+    assert isinstance(h, TensorPowerHilbertSpace)
+    assert h.base == hs2
+    assert h.exp == 3
+    assert h.dimension == n**3
+
+
+def test_direct_sum():
+    n = Symbol('n')
+    hs1 = ComplexSpace(2)
+    hs2 = ComplexSpace(n)
+
+    h = hs1 + hs2
+    assert isinstance(h, DirectSumHilbertSpace)
+    assert h.dimension == 2 + n
+    assert h.spaces == (hs1, hs2)
+
+    f = FockSpace()
+    h = hs1 + f + hs2
+    assert h.dimension is oo
+    assert h.spaces == (hs1, f, hs2)

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_identitysearch.py

@@ -0,0 +1,492 @@
+from sympy.external import import_module
+from sympy.core.mul import Mul
+from sympy.core.numbers import Integer
+from sympy.physics.quantum.dagger import Dagger
+from sympy.physics.quantum.gate import (X, Y, Z, H, CNOT,
+        IdentityGate, CGate, PhaseGate, TGate)
+from sympy.physics.quantum.identitysearch import (generate_gate_rules,
+        generate_equivalent_ids, GateIdentity, bfs_identity_search,
+        is_scalar_sparse_matrix,
+        is_scalar_nonsparse_matrix, is_degenerate, is_reducible)
+from sympy.testing.pytest import skip
+
+
+def create_gate_sequence(qubit=0):
+    gates = (X(qubit), Y(qubit), Z(qubit), H(qubit))
+    return gates
+
+
+def test_generate_gate_rules_1():
+    # Test with tuples
+    (x, y, z, h) = create_gate_sequence()
+    ph = PhaseGate(0)
+    cgate_t = CGate(0, TGate(1))
+
+    assert generate_gate_rules((x,)) == {((x,), ())}
+
+    gate_rules = {((x, x), ()),
+                      ((x,), (x,))}
+    assert generate_gate_rules((x, x)) == gate_rules
+
+    gate_rules = {((x, y, x), ()),
+                      ((y, x, x), ()),
+                      ((x, x, y), ()),
+                      ((y, x), (x,)),
+                      ((x, y), (x,)),
+                      ((y,), (x, x))}
+    assert generate_gate_rules((x, y, x)) == gate_rules
+
+    gate_rules = {((x, y, z), ()), ((y, z, x), ()), ((z, x, y), ()),
+                      ((), (x, z, y)), ((), (y, x, z)), ((), (z, y, x)),
+                      ((x,), (z, y)), ((y, z), (x,)), ((y,), (x, z)),
+                      ((z, x), (y,)), ((z,), (y, x)), ((x, y), (z,))}
+    actual = generate_gate_rules((x, y, z))
+    assert actual == gate_rules
+
+    gate_rules = {
+        ((), (h, z, y, x)), ((), (x, h, z, y)), ((), (y, x, h, z)),
+         ((), (z, y, x, h)), ((h,), (z, y, x)), ((x,), (h, z, y)),
+         ((y,), (x, h, z)), ((z,), (y, x, h)), ((h, x), (z, y)),
+         ((x, y), (h, z)), ((y, z), (x, h)), ((z, h), (y, x)),
+         ((h, x, y), (z,)), ((x, y, z), (h,)), ((y, z, h), (x,)),
+         ((z, h, x), (y,)), ((h, x, y, z), ()), ((x, y, z, h), ()),
+         ((y, z, h, x), ()), ((z, h, x, y), ())}
+    actual = generate_gate_rules((x, y, z, h))
+    assert actual == gate_rules
+
+    gate_rules = {((), (cgate_t**(-1), ph**(-1), x)),
+                      ((), (ph**(-1), x, cgate_t**(-1))),
+                      ((), (x, cgate_t**(-1), ph**(-1))),
+                      ((cgate_t,), (ph**(-1), x)),
+                      ((ph,), (x, cgate_t**(-1))),
+                      ((x,), (cgate_t**(-1), ph**(-1))),
+                      ((cgate_t, x), (ph**(-1),)),
+                      ((ph, cgate_t), (x,)),
+                      ((x, ph), (cgate_t**(-1),)),
+                      ((cgate_t, x, ph), ()),
+                      ((ph, cgate_t, x), ()),
+                      ((x, ph, cgate_t), ())}
+    actual = generate_gate_rules((x, ph, cgate_t))
+    assert actual == gate_rules
+
+    gate_rules = {(Integer(1), cgate_t**(-1)*ph**(-1)*x),
+                      (Integer(1), ph**(-1)*x*cgate_t**(-1)),
+                      (Integer(1), x*cgate_t**(-1)*ph**(-1)),
+                      (cgate_t, ph**(-1)*x),
+                      (ph, x*cgate_t**(-1)),
+                      (x, cgate_t**(-1)*ph**(-1)),
+                      (cgate_t*x, ph**(-1)),
+                      (ph*cgate_t, x),
+                      (x*ph, cgate_t**(-1)),
+                      (cgate_t*x*ph, Integer(1)),
+                      (ph*cgate_t*x, Integer(1)),
+                      (x*ph*cgate_t, Integer(1))}
+    actual = generate_gate_rules((x, ph, cgate_t), return_as_muls=True)
+    assert actual == gate_rules
+
+
+def test_generate_gate_rules_2():
+    # Test with Muls
+    (x, y, z, h) = create_gate_sequence()
+    ph = PhaseGate(0)
+    cgate_t = CGate(0, TGate(1))
+
+    # Note: 1 (type int) is not the same as 1 (type One)
+    expected = {(x, Integer(1))}
+    assert generate_gate_rules((x,), return_as_muls=True) == expected
+
+    expected = {(Integer(1), Integer(1))}
+    assert generate_gate_rules(x*x, return_as_muls=True) == expected
+
+    expected = {((), ())}
+    assert generate_gate_rules(x*x, return_as_muls=False) == expected
+
+    gate_rules = {(x*y*x, Integer(1)),
+                      (y, Integer(1)),
+                      (y*x, x),
+                      (x*y, x)}
+    assert generate_gate_rules(x*y*x, return_as_muls=True) == gate_rules
+
+    gate_rules = {(x*y*z, Integer(1)),
+                      (y*z*x, Integer(1)),
+                      (z*x*y, Integer(1)),
+                      (Integer(1), x*z*y),
+                      (Integer(1), y*x*z),
+                      (Integer(1), z*y*x),
+                      (x, z*y),
+                      (y*z, x),
+                      (y, x*z),
+                      (z*x, y),
+                      (z, y*x),
+                      (x*y, z)}
+    actual = generate_gate_rules(x*y*z, return_as_muls=True)
+    assert actual == gate_rules
+
+    gate_rules = {(Integer(1), h*z*y*x),
+                      (Integer(1), x*h*z*y),
+                      (Integer(1), y*x*h*z),
+                      (Integer(1), z*y*x*h),
+                      (h, z*y*x), (x, h*z*y),
+                      (y, x*h*z), (z, y*x*h),
+                      (h*x, z*y), (z*h, y*x),
+                      (x*y, h*z), (y*z, x*h),
+                      (h*x*y, z), (x*y*z, h),
+                      (y*z*h, x), (z*h*x, y),
+                      (h*x*y*z, Integer(1)),
+                      (x*y*z*h, Integer(1)),
+                      (y*z*h*x, Integer(1)),
+                      (z*h*x*y, Integer(1))}
+    actual = generate_gate_rules(x*y*z*h, return_as_muls=True)
+    assert actual == gate_rules
+
+    gate_rules = {(Integer(1), cgate_t**(-1)*ph**(-1)*x),
+                      (Integer(1), ph**(-1)*x*cgate_t**(-1)),
+                      (Integer(1), x*cgate_t**(-1)*ph**(-1)),
+                      (cgate_t, ph**(-1)*x),
+                      (ph, x*cgate_t**(-1)),
+                      (x, cgate_t**(-1)*ph**(-1)),
+                      (cgate_t*x, ph**(-1)),
+                      (ph*cgate_t, x),
+                      (x*ph, cgate_t**(-1)),
+                      (cgate_t*x*ph, Integer(1)),
+                      (ph*cgate_t*x, Integer(1)),
+                      (x*ph*cgate_t, Integer(1))}
+    actual = generate_gate_rules(x*ph*cgate_t, return_as_muls=True)
+    assert actual == gate_rules
+
+    gate_rules = {((), (cgate_t**(-1), ph**(-1), x)),
+                      ((), (ph**(-1), x, cgate_t**(-1))),
+                      ((), (x, cgate_t**(-1), ph**(-1))),
+                      ((cgate_t,), (ph**(-1), x)),
+                      ((ph,), (x, cgate_t**(-1))),
+                      ((x,), (cgate_t**(-1), ph**(-1))),
+                      ((cgate_t, x), (ph**(-1),)),
+                      ((ph, cgate_t), (x,)),
+                      ((x, ph), (cgate_t**(-1),)),
+                      ((cgate_t, x, ph), ()),
+                      ((ph, cgate_t, x), ()),
+                      ((x, ph, cgate_t), ())}
+    actual = generate_gate_rules(x*ph*cgate_t)
+    assert actual == gate_rules
+
+
+def test_generate_equivalent_ids_1():
+    # Test with tuples
+    (x, y, z, h) = create_gate_sequence()
+
+    assert generate_equivalent_ids((x,)) == {(x,)}
+    assert generate_equivalent_ids((x, x)) == {(x, x)}
+    assert generate_equivalent_ids((x, y)) == {(x, y), (y, x)}
+
+    gate_seq = (x, y, z)
+    gate_ids = {(x, y, z), (y, z, x), (z, x, y), (z, y, x),
+                    (y, x, z), (x, z, y)}
+    assert generate_equivalent_ids(gate_seq) == gate_ids
+
+    gate_ids = {Mul(x, y, z), Mul(y, z, x), Mul(z, x, y),
+                    Mul(z, y, x), Mul(y, x, z), Mul(x, z, y)}
+    assert generate_equivalent_ids(gate_seq, return_as_muls=True) == gate_ids
+
+    gate_seq = (x, y, z, h)
+    gate_ids = {(x, y, z, h), (y, z, h, x),
+                    (h, x, y, z), (h, z, y, x),
+                    (z, y, x, h), (y, x, h, z),
+                    (z, h, x, y), (x, h, z, y)}
+    assert generate_equivalent_ids(gate_seq) == gate_ids
+
+    gate_seq = (x, y, x, y)
+    gate_ids = {(x, y, x, y), (y, x, y, x)}
+    assert generate_equivalent_ids(gate_seq) == gate_ids
+
+    cgate_y = CGate((1,), y)
+    gate_seq = (y, cgate_y, y, cgate_y)
+    gate_ids = {(y, cgate_y, y, cgate_y), (cgate_y, y, cgate_y, y)}
+    assert generate_equivalent_ids(gate_seq) == gate_ids
+
+    cnot = CNOT(1, 0)
+    cgate_z = CGate((0,), Z(1))
+    gate_seq = (cnot, h, cgate_z, h)
+    gate_ids = {(cnot, h, cgate_z, h), (h, cgate_z, h, cnot),
+                    (h, cnot, h, cgate_z), (cgate_z, h, cnot, h)}
+    assert generate_equivalent_ids(gate_seq) == gate_ids
+
+
+def test_generate_equivalent_ids_2():
+    # Test with Muls
+    (x, y, z, h) = create_gate_sequence()
+
+    assert generate_equivalent_ids((x,), return_as_muls=True) == {x}
+
+    gate_ids = {Integer(1)}
+    assert generate_equivalent_ids(x*x, return_as_muls=True) == gate_ids
+
+    gate_ids = {x*y, y*x}
+    assert generate_equivalent_ids(x*y, return_as_muls=True) == gate_ids
+
+    gate_ids = {(x, y), (y, x)}
+    assert generate_equivalent_ids(x*y) == gate_ids
+
+    circuit = Mul(*(x, y, z))
+    gate_ids = {x*y*z, y*z*x, z*x*y, z*y*x,
+                    y*x*z, x*z*y}
+    assert generate_equivalent_ids(circuit, return_as_muls=True) == gate_ids
+
+    circuit = Mul(*(x, y, z, h))
+    gate_ids = {x*y*z*h, y*z*h*x,
+                    h*x*y*z, h*z*y*x,
+                    z*y*x*h, y*x*h*z,
+                    z*h*x*y, x*h*z*y}
+    assert generate_equivalent_ids(circuit, return_as_muls=True) == gate_ids
+
+    circuit = Mul(*(x, y, x, y))
+    gate_ids = {x*y*x*y, y*x*y*x}
+    assert generate_equivalent_ids(circuit, return_as_muls=True) == gate_ids
+
+    cgate_y = CGate((1,), y)
+    circuit = Mul(*(y, cgate_y, y, cgate_y))
+    gate_ids = {y*cgate_y*y*cgate_y, cgate_y*y*cgate_y*y}
+    assert generate_equivalent_ids(circuit, return_as_muls=True) == gate_ids
+
+    cnot = CNOT(1, 0)
+    cgate_z = CGate((0,), Z(1))
+    circuit = Mul(*(cnot, h, cgate_z, h))
+    gate_ids = {cnot*h*cgate_z*h, h*cgate_z*h*cnot,
+                    h*cnot*h*cgate_z, cgate_z*h*cnot*h}
+    assert generate_equivalent_ids(circuit, return_as_muls=True) == gate_ids
+
+
+def test_is_scalar_nonsparse_matrix():
+    numqubits = 2
+    id_only = False
+
+    id_gate = (IdentityGate(1),)
+    actual = is_scalar_nonsparse_matrix(id_gate, numqubits, id_only)
+    assert actual is True
+
+    x0 = X(0)
+    xx_circuit = (x0, x0)
+    actual = is_scalar_nonsparse_matrix(xx_circuit, numqubits, id_only)
+    assert actual is True
+
+    x1 = X(1)
+    y1 = Y(1)
+    xy_circuit = (x1, y1)
+    actual = is_scalar_nonsparse_matrix(xy_circuit, numqubits, id_only)
+    assert actual is False
+
+    z1 = Z(1)
+    xyz_circuit = (x1, y1, z1)
+    actual = is_scalar_nonsparse_matrix(xyz_circuit, numqubits, id_only)
+    assert actual is True
+
+    cnot = CNOT(1, 0)
+    cnot_circuit = (cnot, cnot)
+    actual = is_scalar_nonsparse_matrix(cnot_circuit, numqubits, id_only)
+    assert actual is True
+
+    h = H(0)
+    hh_circuit = (h, h)
+    actual = is_scalar_nonsparse_matrix(hh_circuit, numqubits, id_only)
+    assert actual is True
+
+    h1 = H(1)
+    xhzh_circuit = (x1, h1, z1, h1)
+    actual = is_scalar_nonsparse_matrix(xhzh_circuit, numqubits, id_only)
+    assert actual is True
+
+    id_only = True
+    actual = is_scalar_nonsparse_matrix(xhzh_circuit, numqubits, id_only)
+    assert actual is True
+    actual = is_scalar_nonsparse_matrix(xyz_circuit, numqubits, id_only)
+    assert actual is False
+    actual = is_scalar_nonsparse_matrix(cnot_circuit, numqubits, id_only)
+    assert actual is True
+    actual = is_scalar_nonsparse_matrix(hh_circuit, numqubits, id_only)
+    assert actual is True
+
+
+def test_is_scalar_sparse_matrix():
+    np = import_module('numpy')
+    if not np:
+        skip("numpy not installed.")
+
+    scipy = import_module('scipy', import_kwargs={'fromlist': ['sparse']})
+    if not scipy:
+        skip("scipy not installed.")
+
+    numqubits = 2
+    id_only = False
+
+    id_gate = (IdentityGate(1),)
+    assert is_scalar_sparse_matrix(id_gate, numqubits, id_only) is True
+
+    x0 = X(0)
+    xx_circuit = (x0, x0)
+    assert is_scalar_sparse_matrix(xx_circuit, numqubits, id_only) is True
+
+    x1 = X(1)
+    y1 = Y(1)
+    xy_circuit = (x1, y1)
+    assert is_scalar_sparse_matrix(xy_circuit, numqubits, id_only) is False
+
+    z1 = Z(1)
+    xyz_circuit = (x1, y1, z1)
+    assert is_scalar_sparse_matrix(xyz_circuit, numqubits, id_only) is True
+
+    cnot = CNOT(1, 0)
+    cnot_circuit = (cnot, cnot)
+    assert is_scalar_sparse_matrix(cnot_circuit, numqubits, id_only) is True
+
+    h = H(0)
+    hh_circuit = (h, h)
+    assert is_scalar_sparse_matrix(hh_circuit, numqubits, id_only) is True
+
+    # NOTE:
+    # The elements of the sparse matrix for the following circuit
+    # is actually 1.0000000000000002+0.0j.
+    h1 = H(1)
+    xhzh_circuit = (x1, h1, z1, h1)
+    assert is_scalar_sparse_matrix(xhzh_circuit, numqubits, id_only) is True
+
+    id_only = True
+    assert is_scalar_sparse_matrix(xhzh_circuit, numqubits, id_only) is True
+    assert is_scalar_sparse_matrix(xyz_circuit, numqubits, id_only) is False
+    assert is_scalar_sparse_matrix(cnot_circuit, numqubits, id_only) is True
+    assert is_scalar_sparse_matrix(hh_circuit, numqubits, id_only) is True
+
+
+def test_is_degenerate():
+    (x, y, z, h) = create_gate_sequence()
+
+    gate_id = GateIdentity(x, y, z)
+    ids = {gate_id}
+
+    another_id = (z, y, x)
+    assert is_degenerate(ids, another_id) is True
+
+
+def test_is_reducible():
+    nqubits = 2
+    (x, y, z, h) = create_gate_sequence()
+
+    circuit = (x, y, y)
+    assert is_reducible(circuit, nqubits, 1, 3) is True
+
+    circuit = (x, y, x)
+    assert is_reducible(circuit, nqubits, 1, 3) is False
+
+    circuit = (x, y, y, x)
+    assert is_reducible(circuit, nqubits, 0, 4) is True
+
+    circuit = (x, y, y, x)
+    assert is_reducible(circuit, nqubits, 1, 3) is True
+
+    circuit = (x, y, z, y, y)
+    assert is_reducible(circuit, nqubits, 1, 5) is True
+
+
+def test_bfs_identity_search():
+    assert bfs_identity_search([], 1) == set()
+
+    (x, y, z, h) = create_gate_sequence()
+
+    gate_list = [x]
+    id_set = {GateIdentity(x, x)}
+    assert bfs_identity_search(gate_list, 1, max_depth=2) == id_set
+
+    # Set should not contain degenerate quantum circuits
+    gate_list = [x, y, z]
+    id_set = {GateIdentity(x, x),
+                  GateIdentity(y, y),
+                  GateIdentity(z, z),
+                  GateIdentity(x, y, z)}
+    assert bfs_identity_search(gate_list, 1) == id_set
+
+    id_set = {GateIdentity(x, x),
+                  GateIdentity(y, y),
+                  GateIdentity(z, z),
+                  GateIdentity(x, y, z),
+                  GateIdentity(x, y, x, y),
+                  GateIdentity(x, z, x, z),
+                  GateIdentity(y, z, y, z)}
+    assert bfs_identity_search(gate_list, 1, max_depth=4) == id_set
+    assert bfs_identity_search(gate_list, 1, max_depth=5) == id_set
+
+    gate_list = [x, y, z, h]
+    id_set = {GateIdentity(x, x),
+                  GateIdentity(y, y),
+                  GateIdentity(z, z),
+                  GateIdentity(h, h),
+                  GateIdentity(x, y, z),
+                  GateIdentity(x, y, x, y),
+                  GateIdentity(x, z, x, z),
+                  GateIdentity(x, h, z, h),
+                  GateIdentity(y, z, y, z),
+                  GateIdentity(y, h, y, h)}
+    assert bfs_identity_search(gate_list, 1) == id_set
+
+    id_set = {GateIdentity(x, x),
+                  GateIdentity(y, y),
+                  GateIdentity(z, z),
+                  GateIdentity(h, h)}
+    assert id_set == bfs_identity_search(gate_list, 1, max_depth=3,
+                                         identity_only=True)
+
+    id_set = {GateIdentity(x, x),
+                  GateIdentity(y, y),
+                  GateIdentity(z, z),
+                  GateIdentity(h, h),
+                  GateIdentity(x, y, z),
+                  GateIdentity(x, y, x, y),
+                  GateIdentity(x, z, x, z),
+                  GateIdentity(x, h, z, h),
+                  GateIdentity(y, z, y, z),
+                  GateIdentity(y, h, y, h),
+                  GateIdentity(x, y, h, x, h),
+                  GateIdentity(x, z, h, y, h),
+                  GateIdentity(y, z, h, z, h)}
+    assert bfs_identity_search(gate_list, 1, max_depth=5) == id_set
+
+    id_set = {GateIdentity(x, x),
+                  GateIdentity(y, y),
+                  GateIdentity(z, z),
+                  GateIdentity(h, h),
+                  GateIdentity(x, h, z, h)}
+    assert id_set == bfs_identity_search(gate_list, 1, max_depth=4,
+                                         identity_only=True)
+
+    cnot = CNOT(1, 0)
+    gate_list = [x, cnot]
+    id_set = {GateIdentity(x, x),
+                  GateIdentity(cnot, cnot),
+                  GateIdentity(x, cnot, x, cnot)}
+    assert bfs_identity_search(gate_list, 2, max_depth=4) == id_set
+
+    cgate_x = CGate((1,), x)
+    gate_list = [x, cgate_x]
+    id_set = {GateIdentity(x, x),
+                  GateIdentity(cgate_x, cgate_x),
+                  GateIdentity(x, cgate_x, x, cgate_x)}
+    assert bfs_identity_search(gate_list, 2, max_depth=4) == id_set
+
+    cgate_z = CGate((0,), Z(1))
+    gate_list = [cnot, cgate_z, h]
+    id_set = {GateIdentity(h, h),
+                  GateIdentity(cgate_z, cgate_z),
+                  GateIdentity(cnot, cnot),
+                  GateIdentity(cnot, h, cgate_z, h)}
+    assert bfs_identity_search(gate_list, 2, max_depth=4) == id_set
+
+    s = PhaseGate(0)
+    t = TGate(0)
+    gate_list = [s, t]
+    id_set = {GateIdentity(s, s, s, s)}
+    assert bfs_identity_search(gate_list, 1, max_depth=4) == id_set
+
+
+def test_bfs_identity_search_xfail():
+    s = PhaseGate(0)
+    t = TGate(0)
+    gate_list = [Dagger(s), t]
+    id_set = {GateIdentity(Dagger(s), t, t)}
+    assert bfs_identity_search(gate_list, 1, max_depth=3) == id_set

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_innerproduct.py

@@ -0,0 +1,71 @@
+from sympy.core.numbers import (I, Integer)
+
+from sympy.physics.quantum.innerproduct import InnerProduct
+from sympy.physics.quantum.dagger import Dagger
+from sympy.physics.quantum.state import Bra, Ket, StateBase
+
+
+def test_innerproduct():
+    k = Ket('k')
+    b = Bra('b')
+    ip = InnerProduct(b, k)
+    assert isinstance(ip, InnerProduct)
+    assert ip.bra == b
+    assert ip.ket == k
+    assert b*k == InnerProduct(b, k)
+    assert k*(b*k)*b == k*InnerProduct(b, k)*b
+    assert InnerProduct(b, k).subs(b, Dagger(k)) == Dagger(k)*k
+
+
+def test_innerproduct_dagger():
+    k = Ket('k')
+    b = Bra('b')
+    ip = b*k
+    assert Dagger(ip) == Dagger(k)*Dagger(b)
+
+
+class FooState(StateBase):
+    pass
+
+
+class FooKet(Ket, FooState):
+
+    @classmethod
+    def dual_class(self):
+        return FooBra
+
+    def _eval_innerproduct_FooBra(self, bra):
+        return Integer(1)
+
+    def _eval_innerproduct_BarBra(self, bra):
+        return I
+
+
+class FooBra(Bra, FooState):
+    @classmethod
+    def dual_class(self):
+        return FooKet
+
+
+class BarState(StateBase):
+    pass
+
+
+class BarKet(Ket, BarState):
+    @classmethod
+    def dual_class(self):
+        return BarBra
+
+
+class BarBra(Bra, BarState):
+    @classmethod
+    def dual_class(self):
+        return BarKet
+
+
+def test_doit():
+    f = FooKet('foo')
+    b = BarBra('bar')
+    assert InnerProduct(b, f).doit() == I
+    assert InnerProduct(Dagger(f), Dagger(b)).doit() == -I
+    assert InnerProduct(Dagger(f), f).doit() == Integer(1)

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_kind.py

@@ -0,0 +1,75 @@
+"""Tests for sympy.physics.quantum.kind."""
+
+from sympy.core.kind import NumberKind, UndefinedKind
+from sympy.core.symbol import symbols
+
+from sympy.physics.quantum.kind import (
+    OperatorKind, KetKind, BraKind
+)
+from sympy.physics.quantum.anticommutator import AntiCommutator
+from sympy.physics.quantum.commutator import Commutator
+from sympy.physics.quantum.dagger import Dagger
+from sympy.physics.quantum.operator import Operator
+from sympy.physics.quantum.state import Ket, Bra
+from sympy.physics.quantum.tensorproduct import TensorProduct
+
+k = Ket('k')
+b = Bra('k')
+A = Operator('A')
+B = Operator('B')
+x, y, z = symbols('x y z', integer=True)
+
+def test_bra_ket():
+    assert k.kind == KetKind
+    assert b.kind == BraKind
+    assert (b*k).kind == NumberKind # inner product
+    assert (x*k).kind == KetKind
+    assert (x*b).kind == BraKind
+
+
+def test_operator_kind():
+    assert A.kind == OperatorKind
+    assert (A*B).kind == OperatorKind
+    assert (x*A).kind == OperatorKind
+    assert (x*A*B).kind == OperatorKind
+    assert (x*k*b).kind == OperatorKind # outer product
+
+
+def test_undefind_kind():
+    # Because of limitations in the kind dispatcher API, we are currently
+    # unable to have OperatorKind*KetKind -> KetKind (and similar for bras).
+    assert (A*k).kind == UndefinedKind
+    assert (b*A).kind == UndefinedKind
+    assert (x*b*A*k).kind == UndefinedKind
+
+
+def test_dagger_kind():
+    assert Dagger(k).kind == BraKind
+    assert Dagger(b).kind == KetKind
+    assert Dagger(A).kind == OperatorKind
+
+
+def test_commutator_kind():
+    assert Commutator(A, B).kind == OperatorKind
+    assert Commutator(A, x*B).kind == OperatorKind
+    assert Commutator(x*A, B).kind == OperatorKind
+    assert Commutator(x*A, x*B).kind == OperatorKind
+
+
+def test_anticommutator_kind():
+    assert AntiCommutator(A, B).kind == OperatorKind
+    assert AntiCommutator(A, x*B).kind == OperatorKind
+    assert AntiCommutator(x*A, B).kind == OperatorKind
+    assert AntiCommutator(x*A, x*B).kind == OperatorKind
+
+
+def test_tensorproduct_kind():
+    assert TensorProduct(k,k).kind == KetKind
+    assert TensorProduct(b,b).kind == BraKind
+    assert TensorProduct(x*k,y*k).kind == KetKind
+    assert TensorProduct(x*b,y*b).kind == BraKind
+    assert TensorProduct(x*b*k, y*b*k).kind == NumberKind
+    assert TensorProduct(x*k*b, y*k*b).kind == OperatorKind
+    assert TensorProduct(A, B).kind == OperatorKind
+    assert TensorProduct(A, x*B).kind == OperatorKind
+    assert TensorProduct(x*A, B).kind == OperatorKind

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_matrixutils.py

@@ -0,0 +1,136 @@
+from sympy.core.random import randint
+
+from sympy.core.numbers import Integer
+from sympy.matrices.dense import (Matrix, ones, zeros)
+
+from sympy.physics.quantum.matrixutils import (
+    to_sympy, to_numpy, to_scipy_sparse, matrix_tensor_product,
+    matrix_to_zero, matrix_zeros, numpy_ndarray, scipy_sparse_matrix
+)
+
+from sympy.external import import_module
+from sympy.testing.pytest import skip
+
+m = Matrix([[1, 2], [3, 4]])
+
+
+def test_sympy_to_sympy():
+    assert to_sympy(m) == m
+
+
+def test_matrix_to_zero():
+    assert matrix_to_zero(m) == m
+    assert matrix_to_zero(Matrix([[0, 0], [0, 0]])) == Integer(0)
+
+np = import_module('numpy')
+
+
+def test_to_numpy():
+    if not np:
+        skip("numpy not installed.")
+
+    result = np.array([[1, 2], [3, 4]], dtype='complex')
+    assert (to_numpy(m) == result).all()
+
+
+def test_matrix_tensor_product():
+    if not np:
+        skip("numpy not installed.")
+
+    l1 = zeros(4)
+    for i in range(16):
+        l1[i] = 2**i
+    l2 = zeros(4)
+    for i in range(16):
+        l2[i] = i
+    l3 = zeros(2)
+    for i in range(4):
+        l3[i] = i
+    vec = Matrix([1, 2, 3])
+
+    #test for Matrix known 4x4 matrices
+    numpyl1 = np.array(l1.tolist())
+    numpyl2 = np.array(l2.tolist())
+    numpy_product = np.kron(numpyl1, numpyl2)
+    args = [l1, l2]
+    sympy_product = matrix_tensor_product(*args)
+    assert numpy_product.tolist() == sympy_product.tolist()
+    numpy_product = np.kron(numpyl2, numpyl1)
+    args = [l2, l1]
+    sympy_product = matrix_tensor_product(*args)
+    assert numpy_product.tolist() == sympy_product.tolist()
+
+    #test for other known matrix of different dimensions
+    numpyl2 = np.array(l3.tolist())
+    numpy_product = np.kron(numpyl1, numpyl2)
+    args = [l1, l3]
+    sympy_product = matrix_tensor_product(*args)
+    assert numpy_product.tolist() == sympy_product.tolist()
+    numpy_product = np.kron(numpyl2, numpyl1)
+    args = [l3, l1]
+    sympy_product = matrix_tensor_product(*args)
+    assert numpy_product.tolist() == sympy_product.tolist()
+
+    #test for non square matrix
+    numpyl2 = np.array(vec.tolist())
+    numpy_product = np.kron(numpyl1, numpyl2)
+    args = [l1, vec]
+    sympy_product = matrix_tensor_product(*args)
+    assert numpy_product.tolist() == sympy_product.tolist()
+    numpy_product = np.kron(numpyl2, numpyl1)
+    args = [vec, l1]
+    sympy_product = matrix_tensor_product(*args)
+    assert numpy_product.tolist() == sympy_product.tolist()
+
+    #test for random matrix with random values that are floats
+    random_matrix1 = np.random.rand(randint(1, 5), randint(1, 5))
+    random_matrix2 = np.random.rand(randint(1, 5), randint(1, 5))
+    numpy_product = np.kron(random_matrix1, random_matrix2)
+    args = [Matrix(random_matrix1.tolist()), Matrix(random_matrix2.tolist())]
+    sympy_product = matrix_tensor_product(*args)
+    assert not (sympy_product - Matrix(numpy_product.tolist())).tolist() > \
+        (ones(sympy_product.rows, sympy_product.cols)*epsilon).tolist()
+
+    #test for three matrix kronecker
+    sympy_product = matrix_tensor_product(l1, vec, l2)
+
+    numpy_product = np.kron(l1, np.kron(vec, l2))
+    assert numpy_product.tolist() == sympy_product.tolist()
+
+
+scipy = import_module('scipy', import_kwargs={'fromlist': ['sparse']})
+
+
+def test_to_scipy_sparse():
+    if not np:
+        skip("numpy not installed.")
+    if not scipy:
+        skip("scipy not installed.")
+    else:
+        sparse = scipy.sparse
+
+    result = sparse.csr_matrix([[1, 2], [3, 4]], dtype='complex')
+    assert np.linalg.norm((to_scipy_sparse(m) - result).todense()) == 0.0
+
+epsilon = .000001
+
+
+def test_matrix_zeros_sympy():
+    sym = matrix_zeros(4, 4, format='sympy')
+    assert isinstance(sym, Matrix)
+
+def test_matrix_zeros_numpy():
+    if not np:
+        skip("numpy not installed.")
+
+    num = matrix_zeros(4, 4, format='numpy')
+    assert isinstance(num, numpy_ndarray)
+
+def test_matrix_zeros_scipy():
+    if not np:
+        skip("numpy not installed.")
+    if not scipy:
+        skip("scipy not installed.")
+
+    sci = matrix_zeros(4, 4, format='scipy.sparse')
+    assert isinstance(sci, scipy_sparse_matrix)

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_operator.py

@@ -0,0 +1,269 @@
+from sympy.core.function import (Derivative, Function, diff)
+from sympy.core.mul import Mul
+from sympy.core.numbers import (Integer, pi)
+from sympy.core.symbol import (Symbol, symbols)
+from sympy.core.sympify import sympify
+from sympy.functions.elementary.trigonometric import sin
+from sympy.physics.quantum.qexpr import QExpr
+from sympy.physics.quantum.dagger import Dagger
+from sympy.physics.quantum.hilbert import HilbertSpace
+from sympy.physics.quantum.operator import (Operator, UnitaryOperator,
+                                            HermitianOperator, OuterProduct,
+                                            DifferentialOperator,
+                                            IdentityOperator)
+from sympy.physics.quantum.state import Ket, Bra, Wavefunction
+from sympy.physics.quantum.qapply import qapply
+from sympy.physics.quantum.represent import represent
+from sympy.physics.quantum.spin import JzKet, JzBra
+from sympy.physics.quantum.trace import Tr
+from sympy.matrices import eye
+
+from sympy.testing.pytest import warns_deprecated_sympy
+
+
+class CustomKet(Ket):
+    @classmethod
+    def default_args(self):
+        return ("t",)
+
+
+class CustomOp(HermitianOperator):
+    @classmethod
+    def default_args(self):
+        return ("T",)
+
+t_ket = CustomKet()
+t_op = CustomOp()
+
+
+def test_operator():
+    A = Operator('A')
+    B = Operator('B')
+    C = Operator('C')
+
+    assert isinstance(A, Operator)
+    assert isinstance(A, QExpr)
+
+    assert A.label == (Symbol('A'),)
+    assert A.is_commutative is False
+    assert A.hilbert_space == HilbertSpace()
+
+    assert A*B != B*A
+
+    assert (A*(B + C)).expand() == A*B + A*C
+    assert ((A + B)**2).expand() == A**2 + A*B + B*A + B**2
+
+    assert t_op.label[0] == Symbol(t_op.default_args()[0])
+
+    assert Operator() == Operator("O")
+    with warns_deprecated_sympy():
+        assert A*IdentityOperator() == A
+
+
+def test_operator_inv():
+    A = Operator('A')
+    assert A*A.inv() == 1
+    assert A.inv()*A == 1
+
+
+def test_hermitian():
+    H = HermitianOperator('H')
+
+    assert isinstance(H, HermitianOperator)
+    assert isinstance(H, Operator)
+
+    assert Dagger(H) == H
+    assert H.inv() != H
+    assert H.is_commutative is False
+    assert Dagger(H).is_commutative is False
+
+
+def test_unitary():
+    U = UnitaryOperator('U')
+
+    assert isinstance(U, UnitaryOperator)
+    assert isinstance(U, Operator)
+
+    assert U.inv() == Dagger(U)
+    assert U*Dagger(U) == 1
+    assert Dagger(U)*U == 1
+    assert U.is_commutative is False
+    assert Dagger(U).is_commutative is False
+
+
+def test_identity():
+    with warns_deprecated_sympy():
+        I = IdentityOperator()
+        O = Operator('O')
+        x = Symbol("x")
+        three = sympify(3)
+
+        assert isinstance(I, IdentityOperator)
+        assert isinstance(I, Operator)
+
+        assert I * O == O
+        assert O * I == O
+        assert I * Dagger(O) == Dagger(O)
+        assert Dagger(O) * I == Dagger(O)
+        assert isinstance(I * I, IdentityOperator)
+        assert three * I == three
+        assert I * x == x
+        assert I.inv() == I
+        assert Dagger(I) == I
+        assert qapply(I * O) == O
+        assert qapply(O * I) == O
+
+        for n in [2, 3, 5]:
+            assert represent(IdentityOperator(n)) == eye(n)
+
+
+def test_outer_product():
+    k = Ket('k')
+    b = Bra('b')
+    op = OuterProduct(k, b)
+
+    assert isinstance(op, OuterProduct)
+    assert isinstance(op, Operator)
+
+    assert op.ket == k
+    assert op.bra == b
+    assert op.label == (k, b)
+    assert op.is_commutative is False
+
+    op = k*b
+
+    assert isinstance(op, OuterProduct)
+    assert isinstance(op, Operator)
+
+    assert op.ket == k
+    assert op.bra == b
+    assert op.label == (k, b)
+    assert op.is_commutative is False
+
+    op = 2*k*b
+
+    assert op == Mul(Integer(2), k, b)
+
+    op = 2*(k*b)
+
+    assert op == Mul(Integer(2), OuterProduct(k, b))
+
+    assert Dagger(k*b) == OuterProduct(Dagger(b), Dagger(k))
+    assert Dagger(k*b).is_commutative is False
+
+    #test the _eval_trace
+    assert Tr(OuterProduct(JzKet(1, 1), JzBra(1, 1))).doit() == 1
+
+    # test scaled kets and bras
+    assert OuterProduct(2 * k, b) == 2 * OuterProduct(k, b)
+    assert OuterProduct(k, 2 * b) == 2 * OuterProduct(k, b)
+
+    # test sums of kets and bras
+    k1, k2 = Ket('k1'), Ket('k2')
+    b1, b2 = Bra('b1'), Bra('b2')
+    assert (OuterProduct(k1 + k2, b1) ==
+            OuterProduct(k1, b1) + OuterProduct(k2, b1))
+    assert (OuterProduct(k1, b1 + b2) ==
+            OuterProduct(k1, b1) + OuterProduct(k1, b2))
+    assert (OuterProduct(1 * k1 + 2 * k2, 3 * b1 + 4 * b2) ==
+            3 * OuterProduct(k1, b1) +
+            4 * OuterProduct(k1, b2) +
+            6 * OuterProduct(k2, b1) +
+            8 * OuterProduct(k2, b2))
+
+
+def test_operator_dagger():
+    A = Operator('A')
+    B = Operator('B')
+    assert Dagger(A*B) == Dagger(B)*Dagger(A)
+    assert Dagger(A + B) == Dagger(A) + Dagger(B)
+    assert Dagger(A**2) == Dagger(A)**2
+
+
+def test_differential_operator():
+    x = Symbol('x')
+    f = Function('f')
+    d = DifferentialOperator(Derivative(f(x), x), f(x))
+    g = Wavefunction(x**2, x)
+    assert qapply(d*g) == Wavefunction(2*x, x)
+    assert d.expr == Derivative(f(x), x)
+    assert d.function == f(x)
+    assert d.variables == (x,)
+    assert diff(d, x) == DifferentialOperator(Derivative(f(x), x, 2), f(x))
+
+    d = DifferentialOperator(Derivative(f(x), x, 2), f(x))
+    g = Wavefunction(x**3, x)
+    assert qapply(d*g) == Wavefunction(6*x, x)
+    assert d.expr == Derivative(f(x), x, 2)
+    assert d.function == f(x)
+    assert d.variables == (x,)
+    assert diff(d, x) == DifferentialOperator(Derivative(f(x), x, 3), f(x))
+
+    d = DifferentialOperator(1/x*Derivative(f(x), x), f(x))
+    assert d.expr == 1/x*Derivative(f(x), x)
+    assert d.function == f(x)
+    assert d.variables == (x,)
+    assert diff(d, x) == \
+        DifferentialOperator(Derivative(1/x*Derivative(f(x), x), x), f(x))
+    assert qapply(d*g) == Wavefunction(3*x, x)
+
+    # 2D cartesian Laplacian
+    y = Symbol('y')
+    d = DifferentialOperator(Derivative(f(x, y), x, 2) +
+                             Derivative(f(x, y), y, 2), f(x, y))
+    w = Wavefunction(x**3*y**2 + y**3*x**2, x, y)
+    assert d.expr == Derivative(f(x, y), x, 2) + Derivative(f(x, y), y, 2)
+    assert d.function == f(x, y)
+    assert d.variables == (x, y)
+    assert diff(d, x) == \
+        DifferentialOperator(Derivative(d.expr, x), f(x, y))
+    assert diff(d, y) == \
+        DifferentialOperator(Derivative(d.expr, y), f(x, y))
+    assert qapply(d*w) == Wavefunction(2*x**3 + 6*x*y**2 + 6*x**2*y + 2*y**3,
+                                       x, y)
+
+    # 2D polar Laplacian (th = theta)
+    r, th = symbols('r th')
+    d = DifferentialOperator(1/r*Derivative(r*Derivative(f(r, th), r), r) +
+                             1/(r**2)*Derivative(f(r, th), th, 2), f(r, th))
+    w = Wavefunction(r**2*sin(th), r, (th, 0, pi))
+    assert d.expr == \
+        1/r*Derivative(r*Derivative(f(r, th), r), r) + \
+        1/(r**2)*Derivative(f(r, th), th, 2)
+    assert d.function == f(r, th)
+    assert d.variables == (r, th)
+    assert diff(d, r) == \
+        DifferentialOperator(Derivative(d.expr, r), f(r, th))
+    assert diff(d, th) == \
+        DifferentialOperator(Derivative(d.expr, th), f(r, th))
+    assert qapply(d*w) == Wavefunction(3*sin(th), r, (th, 0, pi))
+
+
+def test_eval_power():
+    from sympy.core import Pow
+    from sympy.core.expr import unchanged
+    O = Operator('O')
+    U = UnitaryOperator('U')
+    H = HermitianOperator('H')
+    assert O**-1 == O.inv() # same as doc test
+    assert U**-1 == U.inv()
+    assert H**-1 == H.inv()
+    x = symbols("x", commutative = True)
+    assert unchanged(Pow, H, x) # verify Pow(H,x)=="X^n"
+    assert H**x == Pow(H, x)
+    assert Pow(H,x) == Pow(H, x, evaluate=False) # Just check
+    from sympy.physics.quantum.gate import XGate
+    X = XGate(0) # is hermitian and unitary
+    assert unchanged(Pow, X, x) # verify Pow(X,x)=="X^x"
+    assert X**x == Pow(X, x)
+    assert Pow(X, x, evaluate=False) == Pow(X, x) # Just check
+    n = symbols("n", integer=True, even=True)
+    assert X**n == 1
+    n = symbols("n", integer=True, odd=True)
+    assert X**n == X
+    n = symbols("n", integer=True)
+    assert unchanged(Pow, X, n) # verify Pow(X,n)=="X^n"
+    assert X**n == Pow(X, n)
+    assert Pow(X, n, evaluate=False)==Pow(X, n) # Just check
+    assert X**4 == 1
+    assert X**7 == X

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_operatorordering.py

@@ -0,0 +1,50 @@
+from sympy.physics.quantum import Dagger
+from sympy.physics.quantum.boson import BosonOp
+from sympy.physics.quantum.fermion import FermionOp
+from sympy.physics.quantum.operatorordering import (normal_order,
+                                                 normal_ordered_form)
+
+
+def test_normal_order():
+    a = BosonOp('a')
+
+    c = FermionOp('c')
+
+    assert normal_order(a * Dagger(a)) == Dagger(a) * a
+    assert normal_order(Dagger(a) * a) == Dagger(a) * a
+    assert normal_order(a * Dagger(a) ** 2) == Dagger(a) ** 2 * a
+
+    assert normal_order(c * Dagger(c)) == - Dagger(c) * c
+    assert normal_order(Dagger(c) * c) == Dagger(c) * c
+    assert normal_order(c * Dagger(c) ** 2) == Dagger(c) ** 2 * c
+
+
+def test_normal_ordered_form():
+    a = BosonOp('a')
+    b = BosonOp('b')
+
+    c = FermionOp('c')
+    d = FermionOp('d')
+
+    assert normal_ordered_form(Dagger(a) * a) == Dagger(a) * a
+    assert normal_ordered_form(a * Dagger(a)) == 1 + Dagger(a) * a
+    assert normal_ordered_form(a ** 2 * Dagger(a)) == \
+        2 * a + Dagger(a) * a ** 2
+    assert normal_ordered_form(a ** 3 * Dagger(a)) == \
+        3 * a ** 2 + Dagger(a) * a ** 3
+
+    assert normal_ordered_form(Dagger(c) * c) == Dagger(c) * c
+    assert normal_ordered_form(c * Dagger(c)) == 1 - Dagger(c) * c
+    assert normal_ordered_form(c ** 2 * Dagger(c)) == Dagger(c) * c ** 2
+    assert normal_ordered_form(c ** 3 * Dagger(c)) == \
+        c ** 2 - Dagger(c) * c ** 3
+
+    assert normal_ordered_form(a * Dagger(b), True) == Dagger(b) * a
+    assert normal_ordered_form(Dagger(a) * b, True) == Dagger(a) * b
+    assert normal_ordered_form(b * a, True) == a * b
+    assert normal_ordered_form(Dagger(b) * Dagger(a), True) == Dagger(a) * Dagger(b)
+
+    assert normal_ordered_form(c * Dagger(d), True) == -Dagger(d) * c
+    assert normal_ordered_form(Dagger(c) * d, True) == Dagger(c) * d
+    assert normal_ordered_form(d * c, True) == -c * d
+    assert normal_ordered_form(Dagger(d) * Dagger(c), True) == -Dagger(c) * Dagger(d)

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_operatorset.py

@@ -0,0 +1,68 @@
+from sympy.core.singleton import S
+
+from sympy.physics.quantum.operatorset import (
+    operators_to_state, state_to_operators
+)
+
+from sympy.physics.quantum.cartesian import (
+    XOp, XKet, PxOp, PxKet, XBra, PxBra
+)
+
+from sympy.physics.quantum.state import Ket, Bra
+from sympy.physics.quantum.operator import Operator
+from sympy.physics.quantum.spin import (
+    JxKet, JyKet, JzKet, JxBra, JyBra, JzBra,
+    JxOp, JyOp, JzOp, J2Op
+)
+
+from sympy.testing.pytest import raises
+
+
+def test_spin():
+    assert operators_to_state({J2Op, JxOp}) == JxKet
+    assert operators_to_state({J2Op, JyOp}) == JyKet
+    assert operators_to_state({J2Op, JzOp}) == JzKet
+    assert operators_to_state({J2Op(), JxOp()}) == JxKet
+    assert operators_to_state({J2Op(), JyOp()}) == JyKet
+    assert operators_to_state({J2Op(), JzOp()}) == JzKet
+
+    assert state_to_operators(JxKet) == {J2Op, JxOp}
+    assert state_to_operators(JyKet) == {J2Op, JyOp}
+    assert state_to_operators(JzKet) == {J2Op, JzOp}
+    assert state_to_operators(JxBra) == {J2Op, JxOp}
+    assert state_to_operators(JyBra) == {J2Op, JyOp}
+    assert state_to_operators(JzBra) == {J2Op, JzOp}
+
+    assert state_to_operators(JxKet(S.Half, S.Half)) == {J2Op(), JxOp()}
+    assert state_to_operators(JyKet(S.Half, S.Half)) == {J2Op(), JyOp()}
+    assert state_to_operators(JzKet(S.Half, S.Half)) == {J2Op(), JzOp()}
+    assert state_to_operators(JxBra(S.Half, S.Half)) == {J2Op(), JxOp()}
+    assert state_to_operators(JyBra(S.Half, S.Half)) == {J2Op(), JyOp()}
+    assert state_to_operators(JzBra(S.Half, S.Half)) == {J2Op(), JzOp()}
+
+
+def test_op_to_state():
+    assert operators_to_state(XOp) == XKet()
+    assert operators_to_state(PxOp) == PxKet()
+    assert operators_to_state(Operator) == Ket()
+
+    assert state_to_operators(operators_to_state(XOp("Q"))) == XOp("Q")
+    assert state_to_operators(operators_to_state(XOp())) == XOp()
+
+    raises(NotImplementedError, lambda: operators_to_state(XKet))
+
+
+def test_state_to_op():
+    assert state_to_operators(XKet) == XOp()
+    assert state_to_operators(PxKet) == PxOp()
+    assert state_to_operators(XBra) == XOp()
+    assert state_to_operators(PxBra) == PxOp()
+    assert state_to_operators(Ket) == Operator()
+    assert state_to_operators(Bra) == Operator()
+
+    assert operators_to_state(state_to_operators(XKet("test"))) == XKet("test")
+    assert operators_to_state(state_to_operators(XBra("test"))) == XKet("test")
+    assert operators_to_state(state_to_operators(XKet())) == XKet()
+    assert operators_to_state(state_to_operators(XBra())) == XKet()
+
+    raises(NotImplementedError, lambda: state_to_operators(XOp))

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_pauli.py

@@ -0,0 +1,159 @@
+from sympy.core.mul import Mul
+from sympy.core.numbers import I
+from sympy.matrices.dense import Matrix
+from sympy.printing.latex import latex
+from sympy.physics.quantum import (Dagger, Commutator, AntiCommutator, qapply,
+                                   Operator, represent)
+from sympy.physics.quantum.pauli import (SigmaOpBase, SigmaX, SigmaY, SigmaZ,
+                                         SigmaMinus, SigmaPlus,
+                                         qsimplify_pauli)
+from sympy.physics.quantum.pauli import SigmaZKet, SigmaZBra
+from sympy.testing.pytest import raises
+
+
+sx, sy, sz = SigmaX(), SigmaY(), SigmaZ()
+sx1, sy1, sz1 = SigmaX(1), SigmaY(1), SigmaZ(1)
+sx2, sy2, sz2 = SigmaX(2), SigmaY(2), SigmaZ(2)
+
+sm, sp = SigmaMinus(), SigmaPlus()
+sm1, sp1 = SigmaMinus(1), SigmaPlus(1)
+A, B = Operator("A"), Operator("B")
+
+
+def test_pauli_operators_types():
+
+    assert isinstance(sx, SigmaOpBase) and isinstance(sx, SigmaX)
+    assert isinstance(sy, SigmaOpBase) and isinstance(sy, SigmaY)
+    assert isinstance(sz, SigmaOpBase) and isinstance(sz, SigmaZ)
+    assert isinstance(sm, SigmaOpBase) and isinstance(sm, SigmaMinus)
+    assert isinstance(sp, SigmaOpBase) and isinstance(sp, SigmaPlus)
+
+
+def test_pauli_operators_commutator():
+
+    assert Commutator(sx, sy).doit() == 2 * I * sz
+    assert Commutator(sy, sz).doit() == 2 * I * sx
+    assert Commutator(sz, sx).doit() == 2 * I * sy
+
+
+def test_pauli_operators_commutator_with_labels():
+
+    assert Commutator(sx1, sy1).doit() == 2 * I * sz1
+    assert Commutator(sy1, sz1).doit() == 2 * I * sx1
+    assert Commutator(sz1, sx1).doit() == 2 * I * sy1
+
+    assert Commutator(sx2, sy2).doit() == 2 * I * sz2
+    assert Commutator(sy2, sz2).doit() == 2 * I * sx2
+    assert Commutator(sz2, sx2).doit() == 2 * I * sy2
+
+    assert Commutator(sx1, sy2).doit() == 0
+    assert Commutator(sy1, sz2).doit() == 0
+    assert Commutator(sz1, sx2).doit() == 0
+
+
+def test_pauli_operators_anticommutator():
+
+    assert AntiCommutator(sy, sz).doit() == 0
+    assert AntiCommutator(sz, sx).doit() == 0
+    assert AntiCommutator(sx, sm).doit() == 1
+    assert AntiCommutator(sx, sp).doit() == 1
+
+
+def test_pauli_operators_adjoint():
+
+    assert Dagger(sx) == sx
+    assert Dagger(sy) == sy
+    assert Dagger(sz) == sz
+
+
+def test_pauli_operators_adjoint_with_labels():
+
+    assert Dagger(sx1) == sx1
+    assert Dagger(sy1) == sy1
+    assert Dagger(sz1) == sz1
+
+    assert Dagger(sx1) != sx2
+    assert Dagger(sy1) != sy2
+    assert Dagger(sz1) != sz2
+
+
+def test_pauli_operators_multiplication():
+
+    assert qsimplify_pauli(sx * sx) == 1
+    assert qsimplify_pauli(sy * sy) == 1
+    assert qsimplify_pauli(sz * sz) == 1
+
+    assert qsimplify_pauli(sx * sy) == I * sz
+    assert qsimplify_pauli(sy * sz) == I * sx
+    assert qsimplify_pauli(sz * sx) == I * sy
+
+    assert qsimplify_pauli(sy * sx) == - I * sz
+    assert qsimplify_pauli(sz * sy) == - I * sx
+    assert qsimplify_pauli(sx * sz) == - I * sy
+
+
+def test_pauli_operators_multiplication_with_labels():
+
+    assert qsimplify_pauli(sx1 * sx1) == 1
+    assert qsimplify_pauli(sy1 * sy1) == 1
+    assert qsimplify_pauli(sz1 * sz1) == 1
+
+    assert isinstance(sx1 * sx2, Mul)
+    assert isinstance(sy1 * sy2, Mul)
+    assert isinstance(sz1 * sz2, Mul)
+
+    assert qsimplify_pauli(sx1 * sy1 * sx2 * sy2) == - sz1 * sz2
+    assert qsimplify_pauli(sy1 * sz1 * sz2 * sx2) == - sx1 * sy2
+
+
+def test_pauli_states():
+    sx, sz = SigmaX(), SigmaZ()
+
+    up = SigmaZKet(0)
+    down = SigmaZKet(1)
+
+    assert qapply(sx * up) == down
+    assert qapply(sx * down) == up
+    assert qapply(sz * up) == up
+    assert qapply(sz * down) == - down
+
+    up = SigmaZBra(0)
+    down = SigmaZBra(1)
+
+    assert qapply(up * sx, dagger=True) == down
+    assert qapply(down * sx, dagger=True) == up
+    assert qapply(up * sz, dagger=True) == up
+    assert qapply(down * sz, dagger=True) == - down
+
+    assert Dagger(SigmaZKet(0)) == SigmaZBra(0)
+    assert Dagger(SigmaZBra(1)) == SigmaZKet(1)
+    raises(ValueError, lambda: SigmaZBra(2))
+    raises(ValueError, lambda: SigmaZKet(2))
+
+
+def test_use_name():
+    assert sm.use_name is False
+    assert sm1.use_name is True
+    assert sx.use_name is False
+    assert sx1.use_name is True
+
+
+def test_printing():
+    assert latex(sx) == r'{\sigma_x}'
+    assert latex(sx1) == r'{\sigma_x^{(1)}}'
+    assert latex(sy) == r'{\sigma_y}'
+    assert latex(sy1) == r'{\sigma_y^{(1)}}'
+    assert latex(sz) == r'{\sigma_z}'
+    assert latex(sz1) == r'{\sigma_z^{(1)}}'
+    assert latex(sm) == r'{\sigma_-}'
+    assert latex(sm1) == r'{\sigma_-^{(1)}}'
+    assert latex(sp) == r'{\sigma_+}'
+    assert latex(sp1) == r'{\sigma_+^{(1)}}'
+
+
+def test_represent():
+    assert represent(sx) == Matrix([[0, 1], [1, 0]])
+    assert represent(sy) == Matrix([[0, -I], [I, 0]])
+    assert represent(sz) == Matrix([[1, 0], [0, -1]])
+    assert represent(sm) == Matrix([[0, 0], [1, 0]])
+    assert represent(sp) == Matrix([[0, 1], [0, 0]])

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_piab.py

@@ -0,0 +1,29 @@
+"""Tests for piab.py"""
+
+from sympy.core.numbers import pi
+from sympy.core.singleton import S
+from sympy.core.symbol import symbols
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.functions.elementary.trigonometric import sin
+from sympy.sets.sets import Interval
+from sympy.functions.special.tensor_functions import KroneckerDelta
+from sympy.physics.quantum import L2, qapply, hbar, represent
+from sympy.physics.quantum.piab import PIABHamiltonian, PIABKet, PIABBra, m, L
+
+i, j, n, x = symbols('i j n x')
+
+
+def test_H():
+    assert PIABHamiltonian('H').hilbert_space == \
+        L2(Interval(S.NegativeInfinity, S.Infinity))
+    assert qapply(PIABHamiltonian('H')*PIABKet(n)) == \
+        (n**2*pi**2*hbar**2)/(2*m*L**2)*PIABKet(n)
+
+
+def test_states():
+    assert PIABKet(n).dual_class() == PIABBra
+    assert PIABKet(n).hilbert_space == \
+        L2(Interval(S.NegativeInfinity, S.Infinity))
+    assert represent(PIABKet(n)) == sqrt(2/L)*sin(n*pi*x/L)
+    assert (PIABBra(i)*PIABKet(j)).doit() == KroneckerDelta(i, j)
+    assert PIABBra(n).dual_class() == PIABKet

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_printing.py

@@ -0,0 +1,900 @@
+# -*- encoding: utf-8 -*-
+"""
+TODO:
+* Address Issue 2251, printing of spin states
+"""
+from __future__ import annotations
+from typing import Any
+
+from sympy.physics.quantum.anticommutator import AntiCommutator
+from sympy.physics.quantum.cg import CG, Wigner3j, Wigner6j, Wigner9j
+from sympy.physics.quantum.commutator import Commutator
+from sympy.physics.quantum.constants import hbar
+from sympy.physics.quantum.dagger import Dagger
+from sympy.physics.quantum.gate import CGate, CNotGate, IdentityGate, UGate, XGate
+from sympy.physics.quantum.hilbert import ComplexSpace, FockSpace, HilbertSpace, L2
+from sympy.physics.quantum.innerproduct import InnerProduct
+from sympy.physics.quantum.operator import Operator, OuterProduct, DifferentialOperator
+from sympy.physics.quantum.qexpr import QExpr
+from sympy.physics.quantum.qubit import Qubit, IntQubit
+from sympy.physics.quantum.spin import Jz, J2, JzBra, JzBraCoupled, JzKet, JzKetCoupled, Rotation, WignerD
+from sympy.physics.quantum.state import Bra, Ket, TimeDepBra, TimeDepKet
+from sympy.physics.quantum.tensorproduct import TensorProduct
+from sympy.physics.quantum.sho1d import RaisingOp
+
+from sympy.core.function import (Derivative, Function)
+from sympy.core.numbers import oo
+from sympy.core.power import Pow
+from sympy.core.singleton import S
+from sympy.core.symbol import (Symbol, symbols)
+from sympy.matrices.dense import Matrix
+from sympy.sets.sets import Interval
+from sympy.testing.pytest import XFAIL
+
+# Imports used in srepr strings
+from sympy.physics.quantum.spin import JzOp
+
+from sympy.printing import srepr
+from sympy.printing.pretty import pretty as xpretty
+from sympy.printing.latex import latex
+
+MutableDenseMatrix = Matrix
+
+
+ENV: dict[str, Any] = {}
+exec('from sympy import *', ENV)
+exec('from sympy.physics.quantum import *', ENV)
+exec('from sympy.physics.quantum.cg import *', ENV)
+exec('from sympy.physics.quantum.spin import *', ENV)
+exec('from sympy.physics.quantum.hilbert import *', ENV)
+exec('from sympy.physics.quantum.qubit import *', ENV)
+exec('from sympy.physics.quantum.qexpr import *', ENV)
+exec('from sympy.physics.quantum.gate import *', ENV)
+exec('from sympy.physics.quantum.constants import *', ENV)
+
+
+def sT(expr, string):
+    """
+    sT := sreprTest
+    from sympy/printing/tests/test_repr.py
+    """
+    assert srepr(expr) == string
+    assert eval(string, ENV) == expr
+
+
+def pretty(expr):
+    """ASCII pretty-printing"""
+    return xpretty(expr, use_unicode=False, wrap_line=False)
+
+
+def upretty(expr):
+    """Unicode pretty-printing"""
+    return xpretty(expr, use_unicode=True, wrap_line=False)
+
+
+def test_anticommutator():
+    A = Operator('A')
+    B = Operator('B')
+    ac = AntiCommutator(A, B)
+    ac_tall = AntiCommutator(A**2, B)
+    assert str(ac) == '{A,B}'
+    assert pretty(ac) == '{A,B}'
+    assert upretty(ac) == '{A,B}'
+    assert latex(ac) == r'\left\{A,B\right\}'
+    sT(ac, "AntiCommutator(Operator(Symbol('A')),Operator(Symbol('B')))")
+    assert str(ac_tall) == '{A**2,B}'
+    ascii_str = \
+"""\
+/ 2  \\\n\
+<A ,B>\n\
+\\    /\
+"""
+    ucode_str = \
+"""\
+⎧ 2  ⎫\n\
+⎨A ,B⎬\n\
+⎩    ⎭\
+"""
+    assert pretty(ac_tall) == ascii_str
+    assert upretty(ac_tall) == ucode_str
+    assert latex(ac_tall) == r'\left\{A^{2},B\right\}'
+    sT(ac_tall, "AntiCommutator(Pow(Operator(Symbol('A')), Integer(2)),Operator(Symbol('B')))")
+
+
+def test_cg():
+    cg = CG(1, 2, 3, 4, 5, 6)
+    wigner3j = Wigner3j(1, 2, 3, 4, 5, 6)
+    wigner6j = Wigner6j(1, 2, 3, 4, 5, 6)
+    wigner9j = Wigner9j(1, 2, 3, 4, 5, 6, 7, 8, 9)
+    assert str(cg) == 'CG(1, 2, 3, 4, 5, 6)'
+    ascii_str = \
+"""\
+ 5,6    \n\
+C       \n\
+ 1,2,3,4\
+"""
+    ucode_str = \
+"""\
+ 5,6    \n\
+C       \n\
+ 1,2,3,4\
+"""
+    assert pretty(cg) == ascii_str
+    assert upretty(cg) == ucode_str
+    assert latex(cg) == 'C^{5,6}_{1,2,3,4}'
+    assert latex(cg ** 2) == R'\left(C^{5,6}_{1,2,3,4}\right)^{2}'
+    sT(cg, "CG(Integer(1), Integer(2), Integer(3), Integer(4), Integer(5), Integer(6))")
+    assert str(wigner3j) == 'Wigner3j(1, 2, 3, 4, 5, 6)'
+    ascii_str = \
+"""\
+/1  3  5\\\n\
+|       |\n\
+\\2  4  6/\
+"""
+    ucode_str = \
+"""\
+⎛1  3  5⎞\n\
+⎜       ⎟\n\
+⎝2  4  6⎠\
+"""
+    assert pretty(wigner3j) == ascii_str
+    assert upretty(wigner3j) == ucode_str
+    assert latex(wigner3j) == \
+        r'\left(\begin{array}{ccc} 1 & 3 & 5 \\ 2 & 4 & 6 \end{array}\right)'
+    sT(wigner3j, "Wigner3j(Integer(1), Integer(2), Integer(3), Integer(4), Integer(5), Integer(6))")
+    assert str(wigner6j) == 'Wigner6j(1, 2, 3, 4, 5, 6)'
+    ascii_str = \
+"""\
+/1  2  3\\\n\
+<       >\n\
+\\4  5  6/\
+"""
+    ucode_str = \
+"""\
+⎧1  2  3⎫\n\
+⎨       ⎬\n\
+⎩4  5  6⎭\
+"""
+    assert pretty(wigner6j) == ascii_str
+    assert upretty(wigner6j) == ucode_str
+    assert latex(wigner6j) == \
+        r'\left\{\begin{array}{ccc} 1 & 2 & 3 \\ 4 & 5 & 6 \end{array}\right\}'
+    sT(wigner6j, "Wigner6j(Integer(1), Integer(2), Integer(3), Integer(4), Integer(5), Integer(6))")
+    assert str(wigner9j) == 'Wigner9j(1, 2, 3, 4, 5, 6, 7, 8, 9)'
+    ascii_str = \
+"""\
+/1  2  3\\\n\
+|       |\n\
+<4  5  6>\n\
+|       |\n\
+\\7  8  9/\
+"""
+    ucode_str = \
+"""\
+⎧1  2  3⎫\n\
+⎪       ⎪\n\
+⎨4  5  6⎬\n\
+⎪       ⎪\n\
+⎩7  8  9⎭\
+"""
+    assert pretty(wigner9j) == ascii_str
+    assert upretty(wigner9j) == ucode_str
+    assert latex(wigner9j) == \
+        r'\left\{\begin{array}{ccc} 1 & 2 & 3 \\ 4 & 5 & 6 \\ 7 & 8 & 9 \end{array}\right\}'
+    sT(wigner9j, "Wigner9j(Integer(1), Integer(2), Integer(3), Integer(4), Integer(5), Integer(6), Integer(7), Integer(8), Integer(9))")
+
+
+def test_commutator():
+    A = Operator('A')
+    B = Operator('B')
+    c = Commutator(A, B)
+    c_tall = Commutator(A**2, B)
+    assert str(c) == '[A,B]'
+    assert pretty(c) == '[A,B]'
+    assert upretty(c) == '[A,B]'
+    assert latex(c) == r'\left[A,B\right]'
+    sT(c, "Commutator(Operator(Symbol('A')),Operator(Symbol('B')))")
+    assert str(c_tall) == '[A**2,B]'
+    ascii_str = \
+"""\
+[ 2  ]\n\
+[A ,B]\
+"""
+    ucode_str = \
+"""\
+⎡ 2  ⎤\n\
+⎣A ,B⎦\
+"""
+    assert pretty(c_tall) == ascii_str
+    assert upretty(c_tall) == ucode_str
+    assert latex(c_tall) == r'\left[A^{2},B\right]'
+    sT(c_tall, "Commutator(Pow(Operator(Symbol('A')), Integer(2)),Operator(Symbol('B')))")
+
+
+def test_constants():
+    assert str(hbar) == 'hbar'
+    assert pretty(hbar) == 'hbar'
+    assert upretty(hbar) == 'ℏ'
+    assert latex(hbar) == r'\hbar'
+    sT(hbar, "HBar()")
+
+
+def test_dagger():
+    x = symbols('x', commutative=False)
+    expr = Dagger(x)
+    assert str(expr) == 'Dagger(x)'
+    ascii_str = \
+"""\
+ +\n\
+x \
+"""
+    ucode_str = \
+"""\
+ †\n\
+x \
+"""
+    assert pretty(expr) == ascii_str
+    assert upretty(expr) == ucode_str
+    assert latex(expr) == r'x^{\dagger}'
+    sT(expr, "Dagger(Symbol('x', commutative=False))")
+
+
+@XFAIL
+def test_gate_failing():
+    a, b, c, d = symbols('a,b,c,d')
+    uMat = Matrix([[a, b], [c, d]])
+    g = UGate((0,), uMat)
+    assert str(g) == 'U(0)'
+
+
+def test_gate():
+    a, b, c, d = symbols('a,b,c,d')
+    uMat = Matrix([[a, b], [c, d]])
+    q = Qubit(1, 0, 1, 0, 1)
+    g1 = IdentityGate(2)
+    g2 = CGate((3, 0), XGate(1))
+    g3 = CNotGate(1, 0)
+    g4 = UGate((0,), uMat)
+    assert str(g1) == '1(2)'
+    assert pretty(g1) == '1 \n 2'
+    assert upretty(g1) == '1 \n 2'
+    assert latex(g1) == r'1_{2}'
+    sT(g1, "IdentityGate(Integer(2))")
+    assert str(g1*q) == '1(2)*|10101>'
+    ascii_str = \
+"""\
+1 *|10101>\n\
+ 2        \
+"""
+    ucode_str = \
+"""\
+1 ⋅❘10101⟩\n\
+ 2        \
+"""
+    assert pretty(g1*q) == ascii_str
+    assert upretty(g1*q) == ucode_str
+    assert latex(g1*q) == r'1_{2} {\left|10101\right\rangle }'
+    sT(g1*q, "Mul(IdentityGate(Integer(2)), Qubit(Integer(1),Integer(0),Integer(1),Integer(0),Integer(1)))")
+    assert str(g2) == 'C((3,0),X(1))'
+    ascii_str = \
+"""\
+C   /X \\\n\
+ 3,0\\ 1/\
+"""
+    ucode_str = \
+"""\
+C   ⎛X ⎞\n\
+ 3,0⎝ 1⎠\
+"""
+    assert pretty(g2) == ascii_str
+    assert upretty(g2) == ucode_str
+    assert latex(g2) == r'C_{3,0}{\left(X_{1}\right)}'
+    sT(g2, "CGate(Tuple(Integer(3), Integer(0)),XGate(Integer(1)))")
+    assert str(g3) == 'CNOT(1,0)'
+    ascii_str = \
+"""\
+CNOT   \n\
+    1,0\
+"""
+    ucode_str = \
+"""\
+CNOT   \n\
+    1,0\
+"""
+    assert pretty(g3) == ascii_str
+    assert upretty(g3) == ucode_str
+    assert latex(g3) == r'\text{CNOT}_{1,0}'
+    sT(g3, "CNotGate(Integer(1),Integer(0))")
+    ascii_str = \
+"""\
+U \n\
+ 0\
+"""
+    ucode_str = \
+"""\
+U \n\
+ 0\
+"""
+    assert str(g4) == \
+"""\
+U((0,),Matrix([\n\
+[a, b],\n\
+[c, d]]))\
+"""
+    assert pretty(g4) == ascii_str
+    assert upretty(g4) == ucode_str
+    assert latex(g4) == r'U_{0}'
+    sT(g4, "UGate(Tuple(Integer(0)),ImmutableDenseMatrix([[Symbol('a'), Symbol('b')], [Symbol('c'), Symbol('d')]]))")
+
+
+def test_hilbert():
+    h1 = HilbertSpace()
+    h2 = ComplexSpace(2)
+    h3 = FockSpace()
+    h4 = L2(Interval(0, oo))
+    assert str(h1) == 'H'
+    assert pretty(h1) == 'H'
+    assert upretty(h1) == 'H'
+    assert latex(h1) == r'\mathcal{H}'
+    sT(h1, "HilbertSpace()")
+    assert str(h2) == 'C(2)'
+    ascii_str = \
+"""\
+ 2\n\
+C \
+"""
+    ucode_str = \
+"""\
+ 2\n\
+C \
+"""
+    assert pretty(h2) == ascii_str
+    assert upretty(h2) == ucode_str
+    assert latex(h2) == r'\mathcal{C}^{2}'
+    sT(h2, "ComplexSpace(Integer(2))")
+    assert str(h3) == 'F'
+    assert pretty(h3) == 'F'
+    assert upretty(h3) == 'F'
+    assert latex(h3) == r'\mathcal{F}'
+    sT(h3, "FockSpace()")
+    assert str(h4) == 'L2(Interval(0, oo))'
+    ascii_str = \
+"""\
+ 2\n\
+L \
+"""
+    ucode_str = \
+"""\
+ 2\n\
+L \
+"""
+    assert pretty(h4) == ascii_str
+    assert upretty(h4) == ucode_str
+    assert latex(h4) == r'{\mathcal{L}^2}\left( \left[0, \infty\right) \right)'
+    sT(h4, "L2(Interval(Integer(0), oo, false, true))")
+    assert str(h1 + h2) == 'H+C(2)'
+    ascii_str = \
+"""\
+     2\n\
+H + C \
+"""
+    ucode_str = \
+"""\
+     2\n\
+H ⊕ C \
+"""
+    assert pretty(h1 + h2) == ascii_str
+    assert upretty(h1 + h2) == ucode_str
+    assert latex(h1 + h2)
+    sT(h1 + h2, "DirectSumHilbertSpace(HilbertSpace(),ComplexSpace(Integer(2)))")
+    assert str(h1*h2) == "H*C(2)"
+    ascii_str = \
+"""\
+     2\n\
+H x C \
+"""
+    ucode_str = \
+"""\
+     2\n\
+H ⨂ C \
+"""
+    assert pretty(h1*h2) == ascii_str
+    assert upretty(h1*h2) == ucode_str
+    assert latex(h1*h2)
+    sT(h1*h2,
+       "TensorProductHilbertSpace(HilbertSpace(),ComplexSpace(Integer(2)))")
+    assert str(h1**2) == 'H**2'
+    ascii_str = \
+"""\
+ x2\n\
+H  \
+"""
+    ucode_str = \
+"""\
+ ⨂2\n\
+H  \
+"""
+    assert pretty(h1**2) == ascii_str
+    assert upretty(h1**2) == ucode_str
+    assert latex(h1**2) == r'{\mathcal{H}}^{\otimes 2}'
+    sT(h1**2, "TensorPowerHilbertSpace(HilbertSpace(),Integer(2))")
+
+
+def test_innerproduct():
+    x = symbols('x')
+    ip1 = InnerProduct(Bra(), Ket())
+    ip2 = InnerProduct(TimeDepBra(), TimeDepKet())
+    ip3 = InnerProduct(JzBra(1, 1), JzKet(1, 1))
+    ip4 = InnerProduct(JzBraCoupled(1, 1, (1, 1)), JzKetCoupled(1, 1, (1, 1)))
+    ip_tall1 = InnerProduct(Bra(x/2), Ket(x/2))
+    ip_tall2 = InnerProduct(Bra(x), Ket(x/2))
+    ip_tall3 = InnerProduct(Bra(x/2), Ket(x))
+    assert str(ip1) == '<psi|psi>'
+    assert pretty(ip1) == '<psi|psi>'
+    assert upretty(ip1) == '⟨ψ❘ψ⟩'
+    assert latex(
+        ip1) == r'\left\langle \psi \right. {\left|\psi\right\rangle }'
+    sT(ip1, "InnerProduct(Bra(Symbol('psi')),Ket(Symbol('psi')))")
+    assert str(ip2) == '<psi;t|psi;t>'
+    assert pretty(ip2) == '<psi;t|psi;t>'
+    assert upretty(ip2) == '⟨ψ;t❘ψ;t⟩'
+    assert latex(ip2) == \
+        r'\left\langle \psi;t \right. {\left|\psi;t\right\rangle }'
+    sT(ip2, "InnerProduct(TimeDepBra(Symbol('psi'),Symbol('t')),TimeDepKet(Symbol('psi'),Symbol('t')))")
+    assert str(ip3) == "<1,1|1,1>"
+    assert pretty(ip3) == '<1,1|1,1>'
+    assert upretty(ip3) == '⟨1,1❘1,1⟩'
+    assert latex(ip3) == r'\left\langle 1,1 \right. {\left|1,1\right\rangle }'
+    sT(ip3, "InnerProduct(JzBra(Integer(1),Integer(1)),JzKet(Integer(1),Integer(1)))")
+    assert str(ip4) == "<1,1,j1=1,j2=1|1,1,j1=1,j2=1>"
+    assert pretty(ip4) == '<1,1,j1=1,j2=1|1,1,j1=1,j2=1>'
+    assert upretty(ip4) == '⟨1,1,j₁=1,j₂=1❘1,1,j₁=1,j₂=1⟩'
+    assert latex(ip4) == \
+        r'\left\langle 1,1,j_{1}=1,j_{2}=1 \right. {\left|1,1,j_{1}=1,j_{2}=1\right\rangle }'
+    sT(ip4, "InnerProduct(JzBraCoupled(Integer(1),Integer(1),Tuple(Integer(1), Integer(1)),Tuple(Tuple(Integer(1), Integer(2), Integer(1)))),JzKetCoupled(Integer(1),Integer(1),Tuple(Integer(1), Integer(1)),Tuple(Tuple(Integer(1), Integer(2), Integer(1)))))")
+    assert str(ip_tall1) == '<x/2|x/2>'
+    ascii_str = \
+"""\
+ / | \\ \n\
+/ x|x \\\n\
+\\ -|- /\n\
+ \\2|2/ \
+"""
+    ucode_str = \
+"""\
+ ╱ │ ╲ \n\
+╱ x│x ╲\n\
+╲ ─│─ ╱\n\
+ ╲2│2╱ \
+"""
+    assert pretty(ip_tall1) == ascii_str
+    assert upretty(ip_tall1) == ucode_str
+    assert latex(ip_tall1) == \
+        r'\left\langle \frac{x}{2} \right. {\left|\frac{x}{2}\right\rangle }'
+    sT(ip_tall1, "InnerProduct(Bra(Mul(Rational(1, 2), Symbol('x'))),Ket(Mul(Rational(1, 2), Symbol('x'))))")
+    assert str(ip_tall2) == '<x|x/2>'
+    ascii_str = \
+"""\
+ / | \\ \n\
+/  |x \\\n\
+\\ x|- /\n\
+ \\ |2/ \
+"""
+    ucode_str = \
+"""\
+ ╱ │ ╲ \n\
+╱  │x ╲\n\
+╲ x│─ ╱\n\
+ ╲ │2╱ \
+"""
+    assert pretty(ip_tall2) == ascii_str
+    assert upretty(ip_tall2) == ucode_str
+    assert latex(ip_tall2) == \
+        r'\left\langle x \right. {\left|\frac{x}{2}\right\rangle }'
+    sT(ip_tall2,
+       "InnerProduct(Bra(Symbol('x')),Ket(Mul(Rational(1, 2), Symbol('x'))))")
+    assert str(ip_tall3) == '<x/2|x>'
+    ascii_str = \
+"""\
+ / | \\ \n\
+/ x|  \\\n\
+\\ -|x /\n\
+ \\2| / \
+"""
+    ucode_str = \
+"""\
+ ╱ │ ╲ \n\
+╱ x│  ╲\n\
+╲ ─│x ╱\n\
+ ╲2│ ╱ \
+"""
+    assert pretty(ip_tall3) == ascii_str
+    assert upretty(ip_tall3) == ucode_str
+    assert latex(ip_tall3) == \
+        r'\left\langle \frac{x}{2} \right. {\left|x\right\rangle }'
+    sT(ip_tall3,
+       "InnerProduct(Bra(Mul(Rational(1, 2), Symbol('x'))),Ket(Symbol('x')))")
+
+
+def test_operator():
+    a = Operator('A')
+    b = Operator('B', Symbol('t'), S.Half)
+    inv = a.inv()
+    f = Function('f')
+    x = symbols('x')
+    d = DifferentialOperator(Derivative(f(x), x), f(x))
+    op = OuterProduct(Ket(), Bra())
+    assert str(a) == 'A'
+    assert pretty(a) == 'A'
+    assert upretty(a) == 'A'
+    assert latex(a) == 'A'
+    sT(a, "Operator(Symbol('A'))")
+    assert str(inv) == 'A**(-1)'
+    ascii_str = \
+"""\
+ -1\n\
+A  \
+"""
+    ucode_str = \
+"""\
+ -1\n\
+A  \
+"""
+    assert pretty(inv) == ascii_str
+    assert upretty(inv) == ucode_str
+    assert latex(inv) == r'A^{-1}'
+    sT(inv, "Pow(Operator(Symbol('A')), Integer(-1))")
+    assert str(d) == 'DifferentialOperator(Derivative(f(x), x),f(x))'
+    ascii_str = \
+"""\
+                    /d            \\\n\
+DifferentialOperator|--(f(x)),f(x)|\n\
+                    \\dx           /\
+"""
+    ucode_str = \
+"""\
+                    ⎛d            ⎞\n\
+DifferentialOperator⎜──(f(x)),f(x)⎟\n\
+                    ⎝dx           ⎠\
+"""
+    assert pretty(d) == ascii_str
+    assert upretty(d) == ucode_str
+    assert latex(d) == \
+        r'DifferentialOperator\left(\frac{d}{d x} f{\left(x \right)},f{\left(x \right)}\right)'
+    sT(d, "DifferentialOperator(Derivative(Function('f')(Symbol('x')), Tuple(Symbol('x'), Integer(1))),Function('f')(Symbol('x')))")
+    assert str(b) == 'Operator(B,t,1/2)'
+    assert pretty(b) == 'Operator(B,t,1/2)'
+    assert upretty(b) == 'Operator(B,t,1/2)'
+    assert latex(b) == r'Operator\left(B,t,\frac{1}{2}\right)'
+    sT(b, "Operator(Symbol('B'),Symbol('t'),Rational(1, 2))")
+    assert str(op) == '|psi><psi|'
+    assert pretty(op) == '|psi><psi|'
+    assert upretty(op) == '❘ψ⟩⟨ψ❘'
+    assert latex(op) == r'{\left|\psi\right\rangle }{\left\langle \psi\right|}'
+    sT(op, "OuterProduct(Ket(Symbol('psi')),Bra(Symbol('psi')))")
+
+
+def test_qexpr():
+    q = QExpr('q')
+    assert str(q) == 'q'
+    assert pretty(q) == 'q'
+    assert upretty(q) == 'q'
+    assert latex(q) == r'q'
+    sT(q, "QExpr(Symbol('q'))")
+
+
+def test_qubit():
+    q1 = Qubit('0101')
+    q2 = IntQubit(8)
+    assert str(q1) == '|0101>'
+    assert pretty(q1) == '|0101>'
+    assert upretty(q1) == '❘0101⟩'
+    assert latex(q1) == r'{\left|0101\right\rangle }'
+    sT(q1, "Qubit(Integer(0),Integer(1),Integer(0),Integer(1))")
+    assert str(q2) == '|8>'
+    assert pretty(q2) == '|8>'
+    assert upretty(q2) == '❘8⟩'
+    assert latex(q2) == r'{\left|8\right\rangle }'
+    sT(q2, "IntQubit(8)")
+
+
+def test_spin():
+    lz = JzOp('L')
+    ket = JzKet(1, 0)
+    bra = JzBra(1, 0)
+    cket = JzKetCoupled(1, 0, (1, 2))
+    cbra = JzBraCoupled(1, 0, (1, 2))
+    cket_big = JzKetCoupled(1, 0, (1, 2, 3))
+    cbra_big = JzBraCoupled(1, 0, (1, 2, 3))
+    rot = Rotation(1, 2, 3)
+    bigd = WignerD(1, 2, 3, 4, 5, 6)
+    smalld = WignerD(1, 2, 3, 0, 4, 0)
+    assert str(lz) == 'Lz'
+    ascii_str = \
+"""\
+L \n\
+ z\
+"""
+    ucode_str = \
+"""\
+L \n\
+ z\
+"""
+    assert pretty(lz) == ascii_str
+    assert upretty(lz) == ucode_str
+    assert latex(lz) == 'L_z'
+    sT(lz, "JzOp(Symbol('L'))")
+    assert str(J2) == 'J2'
+    ascii_str = \
+"""\
+ 2\n\
+J \
+"""
+    ucode_str = \
+"""\
+ 2\n\
+J \
+"""
+    assert pretty(J2) == ascii_str
+    assert upretty(J2) == ucode_str
+    assert latex(J2) == r'J^2'
+    sT(J2, "J2Op(Symbol('J'))")
+    assert str(Jz) == 'Jz'
+    ascii_str = \
+"""\
+J \n\
+ z\
+"""
+    ucode_str = \
+"""\
+J \n\
+ z\
+"""
+    assert pretty(Jz) == ascii_str
+    assert upretty(Jz) == ucode_str
+    assert latex(Jz) == 'J_z'
+    sT(Jz, "JzOp(Symbol('J'))")
+    assert str(ket) == '|1,0>'
+    assert pretty(ket) == '|1,0>'
+    assert upretty(ket) == '❘1,0⟩'
+    assert latex(ket) == r'{\left|1,0\right\rangle }'
+    sT(ket, "JzKet(Integer(1),Integer(0))")
+    assert str(bra) == '<1,0|'
+    assert pretty(bra) == '<1,0|'
+    assert upretty(bra) == '⟨1,0❘'
+    assert latex(bra) == r'{\left\langle 1,0\right|}'
+    sT(bra, "JzBra(Integer(1),Integer(0))")
+    assert str(cket) == '|1,0,j1=1,j2=2>'
+    assert pretty(cket) == '|1,0,j1=1,j2=2>'
+    assert upretty(cket) == '❘1,0,j₁=1,j₂=2⟩'
+    assert latex(cket) == r'{\left|1,0,j_{1}=1,j_{2}=2\right\rangle }'
+    sT(cket, "JzKetCoupled(Integer(1),Integer(0),Tuple(Integer(1), Integer(2)),Tuple(Tuple(Integer(1), Integer(2), Integer(1))))")
+    assert str(cbra) == '<1,0,j1=1,j2=2|'
+    assert pretty(cbra) == '<1,0,j1=1,j2=2|'
+    assert upretty(cbra) == '⟨1,0,j₁=1,j₂=2❘'
+    assert latex(cbra) == r'{\left\langle 1,0,j_{1}=1,j_{2}=2\right|}'
+    sT(cbra, "JzBraCoupled(Integer(1),Integer(0),Tuple(Integer(1), Integer(2)),Tuple(Tuple(Integer(1), Integer(2), Integer(1))))")
+    assert str(cket_big) == '|1,0,j1=1,j2=2,j3=3,j(1,2)=3>'
+    # TODO: Fix non-unicode pretty printing
+    # i.e. j1,2 -> j(1,2)
+    assert pretty(cket_big) == '|1,0,j1=1,j2=2,j3=3,j1,2=3>'
+    assert upretty(cket_big) == '❘1,0,j₁=1,j₂=2,j₃=3,j₁,₂=3⟩'
+    assert latex(cket_big) == \
+        r'{\left|1,0,j_{1}=1,j_{2}=2,j_{3}=3,j_{1,2}=3\right\rangle }'
+    sT(cket_big, "JzKetCoupled(Integer(1),Integer(0),Tuple(Integer(1), Integer(2), Integer(3)),Tuple(Tuple(Integer(1), Integer(2), Integer(3)), Tuple(Integer(1), Integer(3), Integer(1))))")
+    assert str(cbra_big) == '<1,0,j1=1,j2=2,j3=3,j(1,2)=3|'
+    assert pretty(cbra_big) == '<1,0,j1=1,j2=2,j3=3,j1,2=3|'
+    assert upretty(cbra_big) == '⟨1,0,j₁=1,j₂=2,j₃=3,j₁,₂=3❘'
+    assert latex(cbra_big) == \
+        r'{\left\langle 1,0,j_{1}=1,j_{2}=2,j_{3}=3,j_{1,2}=3\right|}'
+    sT(cbra_big, "JzBraCoupled(Integer(1),Integer(0),Tuple(Integer(1), Integer(2), Integer(3)),Tuple(Tuple(Integer(1), Integer(2), Integer(3)), Tuple(Integer(1), Integer(3), Integer(1))))")
+    assert str(rot) == 'R(1,2,3)'
+    assert pretty(rot) == 'R (1,2,3)'
+    assert upretty(rot) == 'ℛ (1,2,3)'
+    assert latex(rot) == r'\mathcal{R}\left(1,2,3\right)'
+    sT(rot, "Rotation(Integer(1),Integer(2),Integer(3))")
+    assert str(bigd) == 'WignerD(1, 2, 3, 4, 5, 6)'
+    ascii_str = \
+"""\
+ 1         \n\
+D   (4,5,6)\n\
+ 2,3       \
+"""
+    ucode_str = \
+"""\
+ 1         \n\
+D   (4,5,6)\n\
+ 2,3       \
+"""
+    assert pretty(bigd) == ascii_str
+    assert upretty(bigd) == ucode_str
+    assert latex(bigd) == r'D^{1}_{2,3}\left(4,5,6\right)'
+    sT(bigd, "WignerD(Integer(1), Integer(2), Integer(3), Integer(4), Integer(5), Integer(6))")
+    assert str(smalld) == 'WignerD(1, 2, 3, 0, 4, 0)'
+    ascii_str = \
+"""\
+ 1     \n\
+d   (4)\n\
+ 2,3   \
+"""
+    ucode_str = \
+"""\
+ 1     \n\
+d   (4)\n\
+ 2,3   \
+"""
+    assert pretty(smalld) == ascii_str
+    assert upretty(smalld) == ucode_str
+    assert latex(smalld) == r'd^{1}_{2,3}\left(4\right)'
+    sT(smalld, "WignerD(Integer(1), Integer(2), Integer(3), Integer(0), Integer(4), Integer(0))")
+
+
+def test_state():
+    x = symbols('x')
+    bra = Bra()
+    ket = Ket()
+    bra_tall = Bra(x/2)
+    ket_tall = Ket(x/2)
+    tbra = TimeDepBra()
+    tket = TimeDepKet()
+    assert str(bra) == '<psi|'
+    assert pretty(bra) == '<psi|'
+    assert upretty(bra) == '⟨ψ❘'
+    assert latex(bra) == r'{\left\langle \psi\right|}'
+    sT(bra, "Bra(Symbol('psi'))")
+    assert str(ket) == '|psi>'
+    assert pretty(ket) == '|psi>'
+    assert upretty(ket) == '❘ψ⟩'
+    assert latex(ket) == r'{\left|\psi\right\rangle }'
+    sT(ket, "Ket(Symbol('psi'))")
+    assert str(bra_tall) == '<x/2|'
+    ascii_str = \
+"""\
+ / |\n\
+/ x|\n\
+\\ -|\n\
+ \\2|\
+"""
+    ucode_str = \
+"""\
+ ╱ │\n\
+╱ x│\n\
+╲ ─│\n\
+ ╲2│\
+"""
+    assert pretty(bra_tall) == ascii_str
+    assert upretty(bra_tall) == ucode_str
+    assert latex(bra_tall) == r'{\left\langle \frac{x}{2}\right|}'
+    sT(bra_tall, "Bra(Mul(Rational(1, 2), Symbol('x')))")
+    assert str(ket_tall) == '|x/2>'
+    ascii_str = \
+"""\
+| \\ \n\
+|x \\\n\
+|- /\n\
+|2/ \
+"""
+    ucode_str = \
+"""\
+│ ╲ \n\
+│x ╲\n\
+│─ ╱\n\
+│2╱ \
+"""
+    assert pretty(ket_tall) == ascii_str
+    assert upretty(ket_tall) == ucode_str
+    assert latex(ket_tall) == r'{\left|\frac{x}{2}\right\rangle }'
+    sT(ket_tall, "Ket(Mul(Rational(1, 2), Symbol('x')))")
+    assert str(tbra) == '<psi;t|'
+    assert pretty(tbra) == '<psi;t|'
+    assert upretty(tbra) == '⟨ψ;t❘'
+    assert latex(tbra) == r'{\left\langle \psi;t\right|}'
+    sT(tbra, "TimeDepBra(Symbol('psi'),Symbol('t'))")
+    assert str(tket) == '|psi;t>'
+    assert pretty(tket) == '|psi;t>'
+    assert upretty(tket) == '❘ψ;t⟩'
+    assert latex(tket) == r'{\left|\psi;t\right\rangle }'
+    sT(tket, "TimeDepKet(Symbol('psi'),Symbol('t'))")
+
+
+def test_tensorproduct():
+    tp = TensorProduct(JzKet(1, 1), JzKet(1, 0))
+    assert str(tp) == '|1,1>x|1,0>'
+    assert pretty(tp) == '|1,1>x |1,0>'
+    assert upretty(tp) == '❘1,1⟩⨂ ❘1,0⟩'
+    assert latex(tp) == \
+        r'{{\left|1,1\right\rangle }}\otimes {{\left|1,0\right\rangle }}'
+    sT(tp, "TensorProduct(JzKet(Integer(1),Integer(1)), JzKet(Integer(1),Integer(0)))")
+
+
+def test_big_expr():
+    f = Function('f')
+    x = symbols('x')
+    e1 = Dagger(AntiCommutator(Operator('A') + Operator('B'), Pow(DifferentialOperator(Derivative(f(x), x), f(x)), 3))*TensorProduct(Jz**2, Operator('A') + Operator('B')))*(JzBra(1, 0) + JzBra(1, 1))*(JzKet(0, 0) + JzKet(1, -1))
+    e2 = Commutator(Jz**2, Operator('A') + Operator('B'))*AntiCommutator(Dagger(Operator('C')*Operator('D')), Operator('E').inv()**2)*Dagger(Commutator(Jz, J2))
+    e3 = Wigner3j(1, 2, 3, 4, 5, 6)*TensorProduct(Commutator(Operator('A') + Dagger(Operator('B')), Operator('C') + Operator('D')), Jz - J2)*Dagger(OuterProduct(Dagger(JzBra(1, 1)), JzBra(1, 0)))*TensorProduct(JzKetCoupled(1, 1, (1, 1)) + JzKetCoupled(1, 0, (1, 1)), JzKetCoupled(1, -1, (1, 1)))
+    e4 = (ComplexSpace(1)*ComplexSpace(2) + FockSpace()**2)*(L2(Interval(
+        0, oo)) + HilbertSpace())
+    assert str(e1) == '(Jz**2)x(Dagger(A) + Dagger(B))*{Dagger(DifferentialOperator(Derivative(f(x), x),f(x)))**3,Dagger(A) + Dagger(B)}*(<1,0| + <1,1|)*(|0,0> + |1,-1>)'
+    ascii_str = \
+"""\
+                 /                                      3        \\                                 \n\
+                 |/                                   +\\         |                                 \n\
+    2  / +    +\\ <|                    /d            \\ |   +    +>                                 \n\
+/J \\ x \\A  + B /*||DifferentialOperator|--(f(x)),f(x)| | ,A  + B |*(<1,0| + <1,1|)*(|0,0> + |1,-1>)\n\
+\\ z/             \\\\                    \\dx           / /         /                                 \
+"""
+    ucode_str = \
+"""\
+                 ⎧                                      3        ⎫                                 \n\
+                 ⎪⎛                                   †⎞         ⎪                                 \n\
+    2  ⎛ †    †⎞ ⎨⎜                    ⎛d            ⎞ ⎟   †    †⎬                                 \n\
+⎛J ⎞ ⨂ ⎝A  + B ⎠⋅⎪⎜DifferentialOperator⎜──(f(x)),f(x)⎟ ⎟ ,A  + B ⎪⋅(⟨1,0❘ + ⟨1,1❘)⋅(❘0,0⟩ + ❘1,-1⟩)\n\
+⎝ z⎠             ⎩⎝                    ⎝dx           ⎠ ⎠         ⎭                                 \
+"""
+    assert pretty(e1) == ascii_str
+    assert upretty(e1) == ucode_str
+    assert latex(e1) == \
+        r'{J_z^{2}}\otimes \left({A^{\dagger} + B^{\dagger}}\right) \left\{\left(DifferentialOperator\left(\frac{d}{d x} f{\left(x \right)},f{\left(x \right)}\right)^{\dagger}\right)^{3},A^{\dagger} + B^{\dagger}\right\} \left({\left\langle 1,0\right|} + {\left\langle 1,1\right|}\right) \left({\left|0,0\right\rangle } + {\left|1,-1\right\rangle }\right)'
+    sT(e1, "Mul(TensorProduct(Pow(JzOp(Symbol('J')), Integer(2)), Add(Dagger(Operator(Symbol('A'))), Dagger(Operator(Symbol('B'))))), AntiCommutator(Pow(Dagger(DifferentialOperator(Derivative(Function('f')(Symbol('x')), Tuple(Symbol('x'), Integer(1))),Function('f')(Symbol('x')))), Integer(3)),Add(Dagger(Operator(Symbol('A'))), Dagger(Operator(Symbol('B'))))), Add(JzBra(Integer(1),Integer(0)), JzBra(Integer(1),Integer(1))), Add(JzKet(Integer(0),Integer(0)), JzKet(Integer(1),Integer(-1))))")
+    assert str(e2) == '[Jz**2,A + B]*{E**(-2),Dagger(D)*Dagger(C)}*[J2,Jz]'
+    ascii_str = \
+"""\
+[    2      ] / -2  +  +\\ [ 2   ]\n\
+[/J \\ ,A + B]*<E  ,D *C >*[J ,J ]\n\
+[\\ z/       ] \\         / [    z]\
+"""
+    ucode_str = \
+"""\
+⎡    2      ⎤ ⎧ -2  †  †⎫ ⎡ 2   ⎤\n\
+⎢⎛J ⎞ ,A + B⎥⋅⎨E  ,D ⋅C ⎬⋅⎢J ,J ⎥\n\
+⎣⎝ z⎠       ⎦ ⎩         ⎭ ⎣    z⎦\
+"""
+    assert pretty(e2) == ascii_str
+    assert upretty(e2) == ucode_str
+    assert latex(e2) == \
+        r'\left[J_z^{2},A + B\right] \left\{E^{-2},D^{\dagger} C^{\dagger}\right\} \left[J^2,J_z\right]'
+    sT(e2, "Mul(Commutator(Pow(JzOp(Symbol('J')), Integer(2)),Add(Operator(Symbol('A')), Operator(Symbol('B')))), AntiCommutator(Pow(Operator(Symbol('E')), Integer(-2)),Mul(Dagger(Operator(Symbol('D'))), Dagger(Operator(Symbol('C'))))), Commutator(J2Op(Symbol('J')),JzOp(Symbol('J'))))")
+    assert str(e3) == \
+        "Wigner3j(1, 2, 3, 4, 5, 6)*[Dagger(B) + A,C + D]x(-J2 + Jz)*|1,0><1,1|*(|1,0,j1=1,j2=1> + |1,1,j1=1,j2=1>)x|1,-1,j1=1,j2=1>"
+    ascii_str = \
+"""\
+          [ +          ]  /   2     \\                                                                 \n\
+/1  3  5\\*[B  + A,C + D]x |- J  + J |*|1,0><1,1|*(|1,0,j1=1,j2=1> + |1,1,j1=1,j2=1>)x |1,-1,j1=1,j2=1>\n\
+|       |                 \\        z/                                                                 \n\
+\\2  4  6/                                                                                             \
+"""
+    ucode_str = \
+"""\
+          ⎡ †          ⎤  ⎛   2     ⎞                                                                 \n\
+⎛1  3  5⎞⋅⎣B  + A,C + D⎦⨂ ⎜- J  + J ⎟⋅❘1,0⟩⟨1,1❘⋅(❘1,0,j₁=1,j₂=1⟩ + ❘1,1,j₁=1,j₂=1⟩)⨂ ❘1,-1,j₁=1,j₂=1⟩\n\
+⎜       ⎟                 ⎝        z⎠                                                                 \n\
+⎝2  4  6⎠                                                                                             \
+"""
+    assert pretty(e3) == ascii_str
+    assert upretty(e3) == ucode_str
+    assert latex(e3) == \
+        r'\left(\begin{array}{ccc} 1 & 3 & 5 \\ 2 & 4 & 6 \end{array}\right) {\left[B^{\dagger} + A,C + D\right]}\otimes \left({- J^2 + J_z}\right) {\left|1,0\right\rangle }{\left\langle 1,1\right|} \left({{\left|1,0,j_{1}=1,j_{2}=1\right\rangle } + {\left|1,1,j_{1}=1,j_{2}=1\right\rangle }}\right)\otimes {{\left|1,-1,j_{1}=1,j_{2}=1\right\rangle }}'
+    sT(e3, "Mul(Wigner3j(Integer(1), Integer(2), Integer(3), Integer(4), Integer(5), Integer(6)), TensorProduct(Commutator(Add(Dagger(Operator(Symbol('B'))), Operator(Symbol('A'))),Add(Operator(Symbol('C')), Operator(Symbol('D')))), Add(Mul(Integer(-1), J2Op(Symbol('J'))), JzOp(Symbol('J')))), OuterProduct(JzKet(Integer(1),Integer(0)),JzBra(Integer(1),Integer(1))), TensorProduct(Add(JzKetCoupled(Integer(1),Integer(0),Tuple(Integer(1), Integer(1)),Tuple(Tuple(Integer(1), Integer(2), Integer(1)))), JzKetCoupled(Integer(1),Integer(1),Tuple(Integer(1), Integer(1)),Tuple(Tuple(Integer(1), Integer(2), Integer(1))))), JzKetCoupled(Integer(1),Integer(-1),Tuple(Integer(1), Integer(1)),Tuple(Tuple(Integer(1), Integer(2), Integer(1))))))")
+    assert str(e4) == '(C(1)*C(2)+F**2)*(L2(Interval(0, oo))+H)'
+    ascii_str = \
+"""\
+// 1    2\\    x2\\   / 2    \\\n\
+\\\\C  x C / + F  / x \\L  + H/\
+"""
+    ucode_str = \
+"""\
+⎛⎛ 1    2⎞    ⨂2⎞   ⎛ 2    ⎞\n\
+⎝⎝C  ⨂ C ⎠ ⊕ F  ⎠ ⨂ ⎝L  ⊕ H⎠\
+"""
+    assert pretty(e4) == ascii_str
+    assert upretty(e4) == ucode_str
+    assert latex(e4) == \
+        r'\left(\left(\mathcal{C}^{1}\otimes \mathcal{C}^{2}\right)\oplus {\mathcal{F}}^{\otimes 2}\right)\otimes \left({\mathcal{L}^2}\left( \left[0, \infty\right) \right)\oplus \mathcal{H}\right)'
+    sT(e4, "TensorProductHilbertSpace((DirectSumHilbertSpace(TensorProductHilbertSpace(ComplexSpace(Integer(1)),ComplexSpace(Integer(2))),TensorPowerHilbertSpace(FockSpace(),Integer(2)))),(DirectSumHilbertSpace(L2(Interval(Integer(0), oo, false, true)),HilbertSpace())))")
+
+
+def _test_sho1d():
+    ad = RaisingOp('a')
+    assert pretty(ad) == ' \N{DAGGER}\na '
+    assert latex(ad) == 'a^{\\dagger}'

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_qapply.py

@@ -0,0 +1,152 @@
+from sympy.core.mul import Mul
+from sympy.core.numbers import (I, Integer, Rational)
+from sympy.core.singleton import S
+from sympy.core.symbol import symbols
+from sympy.functions.elementary.miscellaneous import sqrt
+
+from sympy.physics.quantum.anticommutator import AntiCommutator
+from sympy.physics.quantum.commutator import Commutator
+from sympy.physics.quantum.constants import hbar
+from sympy.physics.quantum.dagger import Dagger
+from sympy.physics.quantum.gate import H, XGate, IdentityGate
+from sympy.physics.quantum.operator import Operator, IdentityOperator
+from sympy.physics.quantum.qapply import qapply
+from sympy.physics.quantum.spin import Jx, Jy, Jz, Jplus, Jminus, J2, JzKet
+from sympy.physics.quantum.tensorproduct import TensorProduct
+from sympy.physics.quantum.state import Ket
+from sympy.physics.quantum.density import Density
+from sympy.physics.quantum.qubit import Qubit, QubitBra
+from sympy.physics.quantum.boson import BosonOp, BosonFockKet, BosonFockBra
+from sympy.testing.pytest import warns_deprecated_sympy
+
+
+j, jp, m, mp = symbols("j j' m m'")
+
+z = JzKet(1, 0)
+po = JzKet(1, 1)
+mo = JzKet(1, -1)
+
+A = Operator('A')
+
+
+class Foo(Operator):
+    def _apply_operator_JzKet(self, ket, **options):
+        return ket
+
+
+def test_basic():
+    assert qapply(Jz*po) == hbar*po
+    assert qapply(Jx*z) == hbar*po/sqrt(2) + hbar*mo/sqrt(2)
+    assert qapply((Jplus + Jminus)*z/sqrt(2)) == hbar*po + hbar*mo
+    assert qapply(Jz*(po + mo)) == hbar*po - hbar*mo
+    assert qapply(Jz*po + Jz*mo) == hbar*po - hbar*mo
+    assert qapply(Jminus*Jminus*po) == 2*hbar**2*mo
+    assert qapply(Jplus**2*mo) == 2*hbar**2*po
+    assert qapply(Jplus**2*Jminus**2*po) == 4*hbar**4*po
+
+
+def test_extra():
+    extra = z.dual*A*z
+    assert qapply(Jz*po*extra) == hbar*po*extra
+    assert qapply(Jx*z*extra) == (hbar*po/sqrt(2) + hbar*mo/sqrt(2))*extra
+    assert qapply(
+        (Jplus + Jminus)*z/sqrt(2)*extra) == hbar*po*extra + hbar*mo*extra
+    assert qapply(Jz*(po + mo)*extra) == hbar*po*extra - hbar*mo*extra
+    assert qapply(Jz*po*extra + Jz*mo*extra) == hbar*po*extra - hbar*mo*extra
+    assert qapply(Jminus*Jminus*po*extra) == 2*hbar**2*mo*extra
+    assert qapply(Jplus**2*mo*extra) == 2*hbar**2*po*extra
+    assert qapply(Jplus**2*Jminus**2*po*extra) == 4*hbar**4*po*extra
+
+
+def test_innerproduct():
+    assert qapply(po.dual*Jz*po, ip_doit=False) == hbar*(po.dual*po)
+    assert qapply(po.dual*Jz*po) == hbar
+
+
+def test_zero():
+    assert qapply(0) == 0
+    assert qapply(Integer(0)) == 0
+
+
+def test_commutator():
+    assert qapply(Commutator(Jx, Jy)*Jz*po) == I*hbar**3*po
+    assert qapply(Commutator(J2, Jz)*Jz*po) == 0
+    assert qapply(Commutator(Jz, Foo('F'))*po) == 0
+    assert qapply(Commutator(Foo('F'), Jz)*po) == 0
+
+
+def test_anticommutator():
+    assert qapply(AntiCommutator(Jz, Foo('F'))*po) == 2*hbar*po
+    assert qapply(AntiCommutator(Foo('F'), Jz)*po) == 2*hbar*po
+
+
+def test_outerproduct():
+    e = Jz*(mo*po.dual)*Jz*po
+    assert qapply(e) == -hbar**2*mo
+    assert qapply(e, ip_doit=False) == -hbar**2*(po.dual*po)*mo
+    assert qapply(e).doit() == -hbar**2*mo
+
+
+def test_tensorproduct():
+    a = BosonOp("a")
+    b = BosonOp("b")
+    ket1 = TensorProduct(BosonFockKet(1), BosonFockKet(2))
+    ket2 = TensorProduct(BosonFockKet(0), BosonFockKet(0))
+    ket3 = TensorProduct(BosonFockKet(0), BosonFockKet(2))
+    bra1 = TensorProduct(BosonFockBra(0), BosonFockBra(0))
+    bra2 = TensorProduct(BosonFockBra(1), BosonFockBra(2))
+    assert qapply(TensorProduct(a, b ** 2) * ket1) == sqrt(2) * ket2
+    assert qapply(TensorProduct(a, Dagger(b) * b) * ket1) == 2 * ket3
+    assert qapply(bra1 * TensorProduct(a, b * b),
+                  dagger=True) == sqrt(2) * bra2
+    assert qapply(bra2 * ket1).doit() == S.One
+    assert qapply(TensorProduct(a, b * b) * ket1) == sqrt(2) * ket2
+    assert qapply(Dagger(TensorProduct(a, b * b) * ket1),
+                  dagger=True) == sqrt(2) * Dagger(ket2)
+
+
+def test_dagger():
+    lhs = Dagger(Qubit(0))*Dagger(H(0))
+    rhs = Dagger(Qubit(1))/sqrt(2) + Dagger(Qubit(0))/sqrt(2)
+    assert qapply(lhs, dagger=True) == rhs
+
+
+def test_issue_6073():
+    x, y = symbols('x y', commutative=False)
+    A = Ket(x, y)
+    B = Operator('B')
+    assert qapply(A) == A
+    assert qapply(A.dual*B) == A.dual*B
+
+
+def test_density():
+    d = Density([Jz*mo, 0.5], [Jz*po, 0.5])
+    assert qapply(d) == Density([-hbar*mo, 0.5], [hbar*po, 0.5])
+
+
+def test_issue3044():
+    expr1 = TensorProduct(Jz*JzKet(S(2),S.NegativeOne)/sqrt(2), Jz*JzKet(S.Half,S.Half))
+    result = Mul(S.NegativeOne, Rational(1, 4), 2**S.Half, hbar**2)
+    result *= TensorProduct(JzKet(2,-1), JzKet(S.Half,S.Half))
+    assert qapply(expr1) == result
+
+
+# Issue 24158: Tests whether qapply incorrectly evaluates some ket*op as op*ket
+def test_issue24158_ket_times_op():
+    P = BosonFockKet(0) * BosonOp("a") # undefined term
+    # Does lhs._apply_operator_BosonOp(rhs) still evaluate ket*op as op*ket?
+    assert qapply(P) == P   # qapply(P) -> BosonOp("a")*BosonFockKet(0) = 0 before fix
+    P = Qubit(1) * XGate(0) # undefined term
+    # Does rhs._apply_operator_Qubit(lhs) still evaluate ket*op as op*ket?
+    assert qapply(P) == P   # qapply(P) -> Qubit(0) before fix
+    P1 = Mul(QubitBra(0), Mul(QubitBra(0), Qubit(0)), XGate(0)) # legal expr <0| * (<1|*|1>) * X
+    assert qapply(P1) == QubitBra(0) * XGate(0)     # qapply(P1) -> 0 before fix
+    P1 = qapply(P1, dagger = True)  # unsatisfactorily -> <0|*X(0), expect <1| since dagger=True
+    assert qapply(P1, dagger = True) == QubitBra(1) # qapply(P1, dagger=True) -> 0 before fix
+    P2 = QubitBra(0) * (QubitBra(0) * Qubit(0)) * XGate(0) # 'forgot' to set brackets
+    P2 = qapply(P2, dagger = True) # unsatisfactorily -> <0|*X(0), expect <1| since dagger=True
+    assert P2 == QubitBra(1) # qapply(P1) -> 0 before fix
+    # Pull Request 24237: IdentityOperator from the right without dagger=True option
+    with warns_deprecated_sympy():
+        assert qapply(QubitBra(1)*IdentityOperator()) == QubitBra(1)
+        assert qapply(IdentityGate(0)*(Qubit(0) + Qubit(1))) == Qubit(0) + Qubit(1)

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_qasm.py

@@ -0,0 +1,89 @@
+from sympy.physics.quantum.qasm import Qasm, flip_index, trim,\
+     get_index, nonblank, fullsplit, fixcommand, stripquotes, read_qasm
+from sympy.physics.quantum.gate import X, Z, H, S, T
+from sympy.physics.quantum.gate import CNOT, SWAP, CPHASE, CGate, CGateS
+from sympy.physics.quantum.circuitplot import Mz
+
+def test_qasm_readqasm():
+    qasm_lines = """\
+    qubit q_0
+    qubit q_1
+    h q_0
+    cnot q_0,q_1
+    """
+    q = read_qasm(qasm_lines)
+    assert q.get_circuit() == CNOT(1,0)*H(1)
+
+def test_qasm_ex1():
+    q = Qasm('qubit q0', 'qubit q1', 'h q0', 'cnot q0,q1')
+    assert q.get_circuit() == CNOT(1,0)*H(1)
+
+def test_qasm_ex1_methodcalls():
+    q = Qasm()
+    q.qubit('q_0')
+    q.qubit('q_1')
+    q.h('q_0')
+    q.cnot('q_0', 'q_1')
+    assert q.get_circuit() == CNOT(1,0)*H(1)
+
+def test_qasm_swap():
+    q = Qasm('qubit q0', 'qubit q1', 'cnot q0,q1', 'cnot q1,q0', 'cnot q0,q1')
+    assert q.get_circuit() == CNOT(1,0)*CNOT(0,1)*CNOT(1,0)
+
+
+def test_qasm_ex2():
+    q = Qasm('qubit q_0', 'qubit q_1', 'qubit q_2', 'h  q_1',
+             'cnot q_1,q_2', 'cnot q_0,q_1', 'h q_0',
+             'measure q_1', 'measure q_0',
+             'c-x q_1,q_2', 'c-z q_0,q_2')
+    assert q.get_circuit() == CGate(2,Z(0))*CGate(1,X(0))*Mz(2)*Mz(1)*H(2)*CNOT(2,1)*CNOT(1,0)*H(1)
+
+def test_qasm_1q():
+    for symbol, gate in [('x', X), ('z', Z), ('h', H), ('s', S), ('t', T), ('measure', Mz)]:
+        q = Qasm('qubit q_0', '%s q_0' % symbol)
+        assert q.get_circuit() == gate(0)
+
+def test_qasm_2q():
+    for symbol, gate in [('cnot', CNOT), ('swap', SWAP), ('cphase', CPHASE)]:
+        q = Qasm('qubit q_0', 'qubit q_1', '%s q_0,q_1' % symbol)
+        assert q.get_circuit() == gate(1,0)
+
+def test_qasm_3q():
+    q = Qasm('qubit q0', 'qubit q1', 'qubit q2', 'toffoli q2,q1,q0')
+    assert q.get_circuit() == CGateS((0,1),X(2))
+
+def test_qasm_flip_index():
+    assert flip_index(0, 2) == 1
+    assert flip_index(1, 2) == 0
+
+def test_qasm_trim():
+    assert trim('nothing happens here') == 'nothing happens here'
+    assert trim("Something #happens here") == "Something "
+
+def test_qasm_get_index():
+    assert get_index('q0', ['q0', 'q1']) == 1
+    assert get_index('q1', ['q0', 'q1']) == 0
+
+def test_qasm_nonblank():
+    assert list(nonblank('abcd')) == list('abcd')
+    assert list(nonblank('abc ')) == list('abc')
+
+def test_qasm_fullsplit():
+    assert fullsplit('g q0,q1,q2,  q3') == ('g', ['q0', 'q1', 'q2', 'q3'])
+
+def test_qasm_fixcommand():
+    assert fixcommand('foo') == 'foo'
+    assert fixcommand('def') == 'qdef'
+
+def test_qasm_stripquotes():
+    assert stripquotes("'S'") == 'S'
+    assert stripquotes('"S"') == 'S'
+    assert stripquotes('S') == 'S'
+
+def test_qasm_qdef():
+    # weaker test condition (str) since we don't have access to the actual class
+    q = Qasm("def Q,0,Q",'qubit q0','Q q0')
+    assert str(q.get_circuit()) == 'Q(0)'
+
+    q = Qasm("def CQ,1,Q", 'qubit q0', 'qubit q1', 'CQ q0,q1')
+    assert str(q.get_circuit()) == 'C((1),Q(0))'

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_qexpr.py

@@ -0,0 +1,64 @@
+from sympy.core.numbers import Integer
+from sympy.core.symbol import Symbol
+from sympy.concrete import Sum
+from sympy.physics.quantum.qexpr import QExpr, _qsympify_sequence
+from sympy.physics.quantum.hilbert import HilbertSpace
+from sympy.core.containers import Tuple
+
+x = Symbol('x')
+y = Symbol('y')
+n = Symbol('n', integer=True)
+m = Symbol('m', integer=True)
+
+
+def test_qexpr_new():
+    q = QExpr(0)
+    assert q.label == (0,)
+    assert q.hilbert_space == HilbertSpace()
+    assert q.is_commutative is False
+
+    q = QExpr(0, 1)
+    assert q.label == (Integer(0), Integer(1))
+
+    q = QExpr._new_rawargs(HilbertSpace(), Integer(0), Integer(1))
+    assert q.label == (Integer(0), Integer(1))
+    assert q.hilbert_space == HilbertSpace()
+
+
+def test_qexpr_commutative():
+    q1 = QExpr(x)
+    q2 = QExpr(y)
+    assert q1.is_commutative is False
+    assert q2.is_commutative is False
+    assert q1*q2 != q2*q1
+
+    q = QExpr._new_rawargs(Integer(0), Integer(1), HilbertSpace())
+    assert q.is_commutative is False
+
+
+def test_qexpr_free_symbols():
+    q1 = QExpr(x, y)
+    assert q1.free_symbols == {x, y}
+
+
+def test_qexpr_sum():
+    q1 = Sum(QExpr(n), (n,0,2))
+    assert q1.doit() == QExpr(0) + QExpr(1) + QExpr(2)
+
+    q2 = Sum(QExpr(n, m), (n, 0, 2), (m, 0, 2))
+    assert q2.doit() == QExpr(0, 0) + QExpr(0, 1) + QExpr(0, 2) + \
+        QExpr(1, 0) + QExpr(1, 1) + QExpr(1, 2) + \
+        QExpr(2, 0) + QExpr(2, 1) + QExpr(2, 2)
+
+
+def test_qexpr_subs():
+    q1 = QExpr(x, y)
+    assert q1.subs(x, y) == QExpr(y, y)
+    assert q1.subs({x: 1, y: 2}) == QExpr(1, 2)
+
+
+def test_qsympify():
+    assert _qsympify_sequence([[1, 2], [1, 3]]) == (Tuple(1, 2), Tuple(1, 3))
+    assert _qsympify_sequence(([1, 2, [3, 4, [2, ]], 1], 3)) == \
+        (Tuple(1, 2, Tuple(3, 4, Tuple(2,)), 1), 3)
+    assert _qsympify_sequence((1,)) == (1,)

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_qft.py

@@ -0,0 +1,52 @@
+from sympy.core.numbers import (I, pi)
+from sympy.core.symbol import Symbol
+from sympy.functions.elementary.exponential import exp
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.matrices.dense import Matrix
+
+from sympy.physics.quantum.qft import QFT, IQFT, RkGate
+from sympy.physics.quantum.gate import (ZGate, SwapGate, HadamardGate, CGate,
+                                        PhaseGate, TGate)
+from sympy.physics.quantum.qubit import Qubit
+from sympy.physics.quantum.qapply import qapply
+from sympy.physics.quantum.represent import represent
+
+from sympy.functions.elementary.complexes import sign
+
+
+def test_RkGate():
+    x = Symbol('x')
+    assert RkGate(1, x).k == x
+    assert RkGate(1, x).targets == (1,)
+    assert RkGate(1, 1) == ZGate(1)
+    assert RkGate(2, 2) == PhaseGate(2)
+    assert RkGate(3, 3) == TGate(3)
+
+    assert represent(
+        RkGate(0, x), nqubits=1) == Matrix([[1, 0], [0, exp(sign(x)*2*pi*I/(2**abs(x)))]])
+
+
+def test_quantum_fourier():
+    assert QFT(0, 3).decompose() == \
+        SwapGate(0, 2)*HadamardGate(0)*CGate((0,), PhaseGate(1)) * \
+        HadamardGate(1)*CGate((0,), TGate(2))*CGate((1,), PhaseGate(2)) * \
+        HadamardGate(2)
+
+    assert IQFT(0, 3).decompose() == \
+        HadamardGate(2)*CGate((1,), RkGate(2, -2))*CGate((0,), RkGate(2, -3)) * \
+        HadamardGate(1)*CGate((0,), RkGate(1, -2))*HadamardGate(0)*SwapGate(0, 2)
+
+    assert represent(QFT(0, 3), nqubits=3) == \
+        Matrix([[exp(2*pi*I/8)**(i*j % 8)/sqrt(8) for i in range(8)] for j in range(8)])
+
+    assert QFT(0, 4).decompose()  # non-trivial decomposition
+    assert qapply(QFT(0, 3).decompose()*Qubit(0, 0, 0)).expand() == qapply(
+        HadamardGate(0)*HadamardGate(1)*HadamardGate(2)*Qubit(0, 0, 0)
+    ).expand()
+
+
+def test_qft_represent():
+    c = QFT(0, 3)
+    a = represent(c, nqubits=3)
+    b = represent(c.decompose(), nqubits=3)
+    assert a.evalf(n=10) == b.evalf(n=10)

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_qubit.py

@@ -0,0 +1,264 @@
+import random
+
+from sympy.core.numbers import (Integer, Rational)
+from sympy.core.singleton import S
+from sympy.core.symbol import symbols
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.matrices.dense import Matrix
+from sympy.physics.quantum.qubit import (measure_all, measure_all_oneshot, measure_partial,
+                                         matrix_to_qubit, matrix_to_density,
+                                         qubit_to_matrix, IntQubit,
+                                         IntQubitBra, QubitBra)
+from sympy.physics.quantum.gate import (HadamardGate, CNOT, XGate, YGate,
+                                        ZGate, PhaseGate)
+from sympy.physics.quantum.qapply import qapply
+from sympy.physics.quantum.represent import represent
+from sympy.physics.quantum.shor import Qubit
+from sympy.testing.pytest import raises
+from sympy.physics.quantum.density import Density
+from sympy.physics.quantum.trace import Tr
+
+x, y = symbols('x,y')
+
+epsilon = .000001
+
+
+def test_Qubit():
+    array = [0, 0, 1, 1, 0]
+    qb = Qubit('00110')
+    assert qb.flip(0) == Qubit('00111')
+    assert qb.flip(1) == Qubit('00100')
+    assert qb.flip(4) == Qubit('10110')
+    assert qb.qubit_values == (0, 0, 1, 1, 0)
+    assert qb.dimension == 5
+    for i in range(5):
+        assert qb[i] == array[4 - i]
+    assert len(qb) == 5
+    qb = Qubit('110')
+
+
+def test_QubitBra():
+    qb = Qubit(0)
+    qb_bra = QubitBra(0)
+    assert qb.dual_class() == QubitBra
+    assert qb_bra.dual_class() == Qubit
+
+    qb = Qubit(1, 1, 0)
+    qb_bra = QubitBra(1, 1, 0)
+    assert represent(qb, nqubits=3).H == represent(qb_bra, nqubits=3)
+
+    qb = Qubit(0, 1)
+    qb_bra = QubitBra(1,0)
+    assert qb._eval_innerproduct_QubitBra(qb_bra) == Integer(0)
+
+    qb_bra = QubitBra(0, 1)
+    assert qb._eval_innerproduct_QubitBra(qb_bra) == Integer(1)
+
+
+def test_IntQubit():
+    # issue 9136
+    iqb = IntQubit(0, nqubits=1)
+    assert qubit_to_matrix(Qubit('0')) == qubit_to_matrix(iqb)
+
+    qb = Qubit('1010')
+    assert qubit_to_matrix(IntQubit(qb)) == qubit_to_matrix(qb)
+
+    iqb = IntQubit(1, nqubits=1)
+    assert qubit_to_matrix(Qubit('1')) == qubit_to_matrix(iqb)
+    assert qubit_to_matrix(IntQubit(1)) == qubit_to_matrix(iqb)
+
+    iqb = IntQubit(7, nqubits=4)
+    assert qubit_to_matrix(Qubit('0111')) == qubit_to_matrix(iqb)
+    assert qubit_to_matrix(IntQubit(7, 4)) == qubit_to_matrix(iqb)
+
+    iqb = IntQubit(8)
+    assert iqb.as_int() == 8
+    assert iqb.qubit_values == (1, 0, 0, 0)
+
+    iqb = IntQubit(7, 4)
+    assert iqb.qubit_values == (0, 1, 1, 1)
+    assert IntQubit(3) == IntQubit(3, 2)
+
+    #test Dual Classes
+    iqb = IntQubit(3)
+    iqb_bra = IntQubitBra(3)
+    assert iqb.dual_class() == IntQubitBra
+    assert iqb_bra.dual_class() == IntQubit
+
+    iqb = IntQubit(5)
+    iqb_bra = IntQubitBra(5)
+    assert iqb._eval_innerproduct_IntQubitBra(iqb_bra) == Integer(1)
+
+    iqb = IntQubit(4)
+    iqb_bra = IntQubitBra(5)
+    assert iqb._eval_innerproduct_IntQubitBra(iqb_bra) == Integer(0)
+    raises(ValueError, lambda: IntQubit(4, 1))
+
+    raises(ValueError, lambda: IntQubit('5'))
+    raises(ValueError, lambda: IntQubit(5, '5'))
+    raises(ValueError, lambda: IntQubit(5, nqubits='5'))
+    raises(TypeError, lambda: IntQubit(5, bad_arg=True))
+
+def test_superposition_of_states():
+    state = 1/sqrt(2)*Qubit('01') + 1/sqrt(2)*Qubit('10')
+    state_gate = CNOT(0, 1)*HadamardGate(0)*state
+    state_expanded = Qubit('01')/2 + Qubit('00')/2 - Qubit('11')/2 + Qubit('10')/2
+    assert qapply(state_gate).expand() == state_expanded
+    assert matrix_to_qubit(represent(state_gate, nqubits=2)) == state_expanded
+
+
+#test apply methods
+def test_apply_represent_equality():
+    gates = [HadamardGate(int(3*random.random())),
+     XGate(int(3*random.random())), ZGate(int(3*random.random())),
+        YGate(int(3*random.random())), ZGate(int(3*random.random())),
+        PhaseGate(int(3*random.random()))]
+
+    circuit = Qubit(int(random.random()*2), int(random.random()*2),
+    int(random.random()*2), int(random.random()*2), int(random.random()*2),
+        int(random.random()*2))
+    for i in range(int(random.random()*6)):
+        circuit = gates[int(random.random()*6)]*circuit
+
+    mat = represent(circuit, nqubits=6)
+    states = qapply(circuit)
+    state_rep = matrix_to_qubit(mat)
+    states = states.expand()
+    state_rep = state_rep.expand()
+    assert state_rep == states
+
+
+def test_matrix_to_qubits():
+    qb = Qubit(0, 0, 0, 0)
+    mat = Matrix([1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
+    assert matrix_to_qubit(mat) == qb
+    assert qubit_to_matrix(qb) == mat
+
+    state = 2*sqrt(2)*(Qubit(0, 0, 0) + Qubit(0, 0, 1) + Qubit(0, 1, 0) +
+                       Qubit(0, 1, 1) + Qubit(1, 0, 0) + Qubit(1, 0, 1) +
+                       Qubit(1, 1, 0) + Qubit(1, 1, 1))
+    ones = sqrt(2)*2*Matrix([1, 1, 1, 1, 1, 1, 1, 1])
+    assert matrix_to_qubit(ones) == state.expand()
+    assert qubit_to_matrix(state) == ones
+
+
+def test_measure_normalize():
+    a, b = symbols('a b')
+    state = a*Qubit('110') + b*Qubit('111')
+    assert measure_partial(state, (0,), normalize=False) == \
+        [(a*Qubit('110'), a*a.conjugate()), (b*Qubit('111'), b*b.conjugate())]
+    assert measure_all(state, normalize=False) == \
+        [(Qubit('110'), a*a.conjugate()), (Qubit('111'), b*b.conjugate())]
+
+
+def test_measure_partial():
+    #Basic test of collapse of entangled two qubits (Bell States)
+    state = Qubit('01') + Qubit('10')
+    assert measure_partial(state, (0,)) == \
+        [(Qubit('10'), S.Half), (Qubit('01'), S.Half)]
+    assert measure_partial(state, int(0)) == \
+        [(Qubit('10'), S.Half), (Qubit('01'), S.Half)]
+    assert measure_partial(state, (0,)) == \
+        measure_partial(state, (1,))[::-1]
+
+    #Test of more complex collapse and probability calculation
+    state1 = sqrt(2)/sqrt(3)*Qubit('00001') + 1/sqrt(3)*Qubit('11111')
+    assert measure_partial(state1, (0,)) == \
+        [(sqrt(2)/sqrt(3)*Qubit('00001') + 1/sqrt(3)*Qubit('11111'), 1)]
+    assert measure_partial(state1, (1, 2)) == measure_partial(state1, (3, 4))
+    assert measure_partial(state1, (1, 2, 3)) == \
+        [(Qubit('00001'), Rational(2, 3)), (Qubit('11111'), Rational(1, 3))]
+
+    #test of measuring multiple bits at once
+    state2 = Qubit('1111') + Qubit('1101') + Qubit('1011') + Qubit('1000')
+    assert measure_partial(state2, (0, 1, 3)) == \
+        [(Qubit('1000'), Rational(1, 4)), (Qubit('1101'), Rational(1, 4)),
+         (Qubit('1011')/sqrt(2) + Qubit('1111')/sqrt(2), S.Half)]
+    assert measure_partial(state2, (0,)) == \
+        [(Qubit('1000'), Rational(1, 4)),
+         (Qubit('1111')/sqrt(3) + Qubit('1101')/sqrt(3) +
+          Qubit('1011')/sqrt(3), Rational(3, 4))]
+
+
+def test_measure_all():
+    assert measure_all(Qubit('11')) == [(Qubit('11'), 1)]
+    state = Qubit('11') + Qubit('10')
+    assert measure_all(state) == [(Qubit('10'), S.Half),
+           (Qubit('11'), S.Half)]
+    state2 = Qubit('11')/sqrt(5) + 2*Qubit('00')/sqrt(5)
+    assert measure_all(state2) == \
+        [(Qubit('00'), Rational(4, 5)), (Qubit('11'), Rational(1, 5))]
+
+    # from issue #12585
+    assert measure_all(qapply(Qubit('0'))) == [(Qubit('0'), 1)]
+
+
+def test_measure_all_oneshot():
+    random.seed(42)
+    # for issue #27092
+    assert measure_all_oneshot(Qubit('11')) == Qubit('11')
+    assert measure_all_oneshot(Qubit('1')) == Qubit('1')
+    assert measure_all_oneshot(Qubit('0')/sqrt(2) + Qubit('1')/sqrt(2)) == \
+            Qubit('0')
+
+
+def test_eval_trace():
+    q1 = Qubit('10110')
+    q2 = Qubit('01010')
+    d = Density([q1, 0.6], [q2, 0.4])
+
+    t = Tr(d)
+    assert t.doit() == 1.0
+
+    # extreme bits
+    t = Tr(d, 0)
+    assert t.doit() == (0.4*Density([Qubit('0101'), 1]) +
+                        0.6*Density([Qubit('1011'), 1]))
+    t = Tr(d, 4)
+    assert t.doit() == (0.4*Density([Qubit('1010'), 1]) +
+                        0.6*Density([Qubit('0110'), 1]))
+    # index somewhere in between
+    t = Tr(d, 2)
+    assert t.doit() == (0.4*Density([Qubit('0110'), 1]) +
+                        0.6*Density([Qubit('1010'), 1]))
+    #trace all indices
+    t = Tr(d, [0, 1, 2, 3, 4])
+    assert t.doit() == 1.0
+
+    # trace some indices, initialized in
+    # non-canonical order
+    t = Tr(d, [2, 1, 3])
+    assert t.doit() == (0.4*Density([Qubit('00'), 1]) +
+                        0.6*Density([Qubit('10'), 1]))
+
+    # mixed states
+    q = (1/sqrt(2)) * (Qubit('00') + Qubit('11'))
+    d = Density( [q, 1.0] )
+    t = Tr(d, 0)
+    assert t.doit() == (0.5*Density([Qubit('0'), 1]) +
+                        0.5*Density([Qubit('1'), 1]))
+
+
+def test_matrix_to_density():
+    mat = Matrix([[0, 0], [0, 1]])
+    assert matrix_to_density(mat) == Density([Qubit('1'), 1])
+
+    mat = Matrix([[1, 0], [0, 0]])
+    assert matrix_to_density(mat) == Density([Qubit('0'), 1])
+
+    mat = Matrix([[0, 0], [0, 0]])
+    assert matrix_to_density(mat) == 0
+
+    mat = Matrix([[0, 0, 0, 0],
+                  [0, 0, 0, 0],
+                  [0, 0, 1, 0],
+                  [0, 0, 0, 0]])
+
+    assert matrix_to_density(mat) == Density([Qubit('10'), 1])
+
+    mat = Matrix([[1, 0, 0, 0],
+                  [0, 0, 0, 0],
+                  [0, 0, 0, 0],
+                  [0, 0, 0, 0]])
+
+    assert matrix_to_density(mat) == Density([Qubit('00'), 1])

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_represent.py

@@ -0,0 +1,186 @@
+from sympy.core.numbers import (Float, I, Integer)
+from sympy.matrices.dense import Matrix
+from sympy.external import import_module
+from sympy.testing.pytest import skip
+
+from sympy.physics.quantum.dagger import Dagger
+from sympy.physics.quantum.represent import (represent, rep_innerproduct,
+                                             rep_expectation, enumerate_states)
+from sympy.physics.quantum.state import Bra, Ket
+from sympy.physics.quantum.operator import Operator, OuterProduct
+from sympy.physics.quantum.tensorproduct import TensorProduct
+from sympy.physics.quantum.tensorproduct import matrix_tensor_product
+from sympy.physics.quantum.commutator import Commutator
+from sympy.physics.quantum.anticommutator import AntiCommutator
+from sympy.physics.quantum.innerproduct import InnerProduct
+from sympy.physics.quantum.matrixutils import (numpy_ndarray,
+                                               scipy_sparse_matrix, to_numpy,
+                                               to_scipy_sparse, to_sympy)
+from sympy.physics.quantum.cartesian import XKet, XOp, XBra
+from sympy.physics.quantum.qapply import qapply
+from sympy.physics.quantum.operatorset import operators_to_state
+from sympy.testing.pytest import raises
+
+Amat = Matrix([[1, I], [-I, 1]])
+Bmat = Matrix([[1, 2], [3, 4]])
+Avec = Matrix([[1], [I]])
+
+
+class AKet(Ket):
+
+    @classmethod
+    def dual_class(self):
+        return ABra
+
+    def _represent_default_basis(self, **options):
+        return self._represent_AOp(None, **options)
+
+    def _represent_AOp(self, basis, **options):
+        return Avec
+
+
+class ABra(Bra):
+
+    @classmethod
+    def dual_class(self):
+        return AKet
+
+
+class AOp(Operator):
+
+    def _represent_default_basis(self, **options):
+        return self._represent_AOp(None, **options)
+
+    def _represent_AOp(self, basis, **options):
+        return Amat
+
+
+class BOp(Operator):
+
+    def _represent_default_basis(self, **options):
+        return self._represent_AOp(None, **options)
+
+    def _represent_AOp(self, basis, **options):
+        return Bmat
+
+
+k = AKet('a')
+b = ABra('a')
+A = AOp('A')
+B = BOp('B')
+
+_tests = [
+    # Bra
+    (b, Dagger(Avec)),
+    (Dagger(b), Avec),
+    # Ket
+    (k, Avec),
+    (Dagger(k), Dagger(Avec)),
+    # Operator
+    (A, Amat),
+    (Dagger(A), Dagger(Amat)),
+    # OuterProduct
+    (OuterProduct(k, b), Avec*Avec.H),
+    # TensorProduct
+    (TensorProduct(A, B), matrix_tensor_product(Amat, Bmat)),
+    # Pow
+    (A**2, Amat**2),
+    # Add/Mul
+    (A*B + 2*A, Amat*Bmat + 2*Amat),
+    # Commutator
+    (Commutator(A, B), Amat*Bmat - Bmat*Amat),
+    # AntiCommutator
+    (AntiCommutator(A, B), Amat*Bmat + Bmat*Amat),
+    # InnerProduct
+    (InnerProduct(b, k), (Avec.H*Avec)[0])
+]
+
+
+def test_format_sympy():
+    for test in _tests:
+        lhs = represent(test[0], basis=A, format='sympy')
+        rhs = to_sympy(test[1])
+        assert lhs == rhs
+
+
+def test_scalar_sympy():
+    assert represent(Integer(1)) == Integer(1)
+    assert represent(Float(1.0)) == Float(1.0)
+    assert represent(1.0 + I) == 1.0 + I
+
+
+np = import_module('numpy')
+
+
+def test_format_numpy():
+    if not np:
+        skip("numpy not installed.")
+
+    for test in _tests:
+        lhs = represent(test[0], basis=A, format='numpy')
+        rhs = to_numpy(test[1])
+        if isinstance(lhs, numpy_ndarray):
+            assert (lhs == rhs).all()
+        else:
+            assert lhs == rhs
+
+
+def test_scalar_numpy():
+    if not np:
+        skip("numpy not installed.")
+
+    assert represent(Integer(1), format='numpy') == 1
+    assert represent(Float(1.0), format='numpy') == 1.0
+    assert represent(1.0 + I, format='numpy') == 1.0 + 1.0j
+
+
+scipy = import_module('scipy', import_kwargs={'fromlist': ['sparse']})
+
+
+def test_format_scipy_sparse():
+    if not np:
+        skip("numpy not installed.")
+    if not scipy:
+        skip("scipy not installed.")
+
+    for test in _tests:
+        lhs = represent(test[0], basis=A, format='scipy.sparse')
+        rhs = to_scipy_sparse(test[1])
+        if isinstance(lhs, scipy_sparse_matrix):
+            assert np.linalg.norm((lhs - rhs).todense()) == 0.0
+        else:
+            assert lhs == rhs
+
+
+def test_scalar_scipy_sparse():
+    if not np:
+        skip("numpy not installed.")
+    if not scipy:
+        skip("scipy not installed.")
+
+    assert represent(Integer(1), format='scipy.sparse') == 1
+    assert represent(Float(1.0), format='scipy.sparse') == 1.0
+    assert represent(1.0 + I, format='scipy.sparse') == 1.0 + 1.0j
+
+x_ket = XKet('x')
+x_bra = XBra('x')
+x_op = XOp('X')
+
+
+def test_innerprod_represent():
+    assert rep_innerproduct(x_ket) == InnerProduct(XBra("x_1"), x_ket).doit()
+    assert rep_innerproduct(x_bra) == InnerProduct(x_bra, XKet("x_1")).doit()
+    raises(TypeError, lambda: rep_innerproduct(x_op))
+
+
+def test_operator_represent():
+    basis_kets = enumerate_states(operators_to_state(x_op), 1, 2)
+    assert rep_expectation(
+        x_op) == qapply(basis_kets[1].dual*x_op*basis_kets[0])
+
+
+def test_enumerate_states():
+    test = XKet("foo")
+    assert enumerate_states(test, 1, 1) == [XKet("foo_1")]
+    assert enumerate_states(
+        test, [1, 2, 4]) == [XKet("foo_1"), XKet("foo_2"), XKet("foo_4")]

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_sho1d.py

@@ -0,0 +1,176 @@
+"""Tests for sho1d.py"""
+
+from sympy.concrete import Sum
+from sympy.core import oo
+from sympy.core.numbers import (I, Integer)
+from sympy.core.singleton import S
+from sympy.core.symbol import Symbol, symbols
+from sympy.functions.combinatorial.factorials import factorial
+from sympy.functions.elementary.exponential import exp
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.functions.elementary.complexes import Abs
+from sympy.functions.special.tensor_functions import KroneckerDelta
+from sympy.physics.quantum import Dagger
+from sympy.physics.quantum.constants import hbar
+from sympy.physics.quantum import Commutator
+from sympy.physics.quantum.qapply import qapply
+from sympy.physics.quantum.innerproduct import InnerProduct
+from sympy.physics.quantum.cartesian import X, Px
+from sympy.physics.quantum.hilbert import ComplexSpace
+from sympy.physics.quantum.represent import represent
+from sympy.simplify import simplify
+from sympy.external import import_module
+from sympy.tensor import IndexedBase, Idx
+from sympy.testing.pytest import skip, raises
+
+from sympy.physics.quantum.sho1d import (RaisingOp, LoweringOp,
+                                        SHOKet, SHOBra,
+                                        Hamiltonian, NumberOp)
+
+ad = RaisingOp('a')
+a = LoweringOp('a')
+k = SHOKet('k')
+kz = SHOKet(0)
+kf = SHOKet(1)
+k3 = SHOKet(3)
+b = SHOBra('b')
+b3 = SHOBra(3)
+H = Hamiltonian('H')
+N = NumberOp('N')
+omega = Symbol('omega')
+m = Symbol('m')
+ndim = Integer(4)
+p = Symbol('p', integer=True)
+q = Symbol('q', nonnegative=True, integer=True)
+
+
+np = import_module('numpy')
+scipy = import_module('scipy', import_kwargs={'fromlist': ['sparse']})
+
+ad_rep_sympy = represent(ad, basis=N, ndim=4, format='sympy')
+a_rep = represent(a, basis=N, ndim=4, format='sympy')
+N_rep = represent(N, basis=N, ndim=4, format='sympy')
+H_rep = represent(H, basis=N, ndim=4, format='sympy')
+k3_rep = represent(k3, basis=N, ndim=4, format='sympy')
+b3_rep = represent(b3, basis=N, ndim=4, format='sympy')
+
+def test_RaisingOp():
+    assert Dagger(ad) == a
+    assert Commutator(ad, a).doit() == Integer(-1)
+    assert Commutator(ad, N).doit() == Integer(-1)*ad
+    assert qapply(ad*k) == (sqrt(k.n + 1)*SHOKet(k.n + 1)).expand()
+    assert qapply(ad*kz) == (sqrt(kz.n + 1)*SHOKet(kz.n + 1)).expand()
+    assert qapply(ad*kf) == (sqrt(kf.n + 1)*SHOKet(kf.n + 1)).expand()
+    assert ad.rewrite('xp').doit() == \
+        (Integer(1)/sqrt(Integer(2)*hbar*m*omega))*(Integer(-1)*I*Px + m*omega*X)
+    assert ad.hilbert_space == ComplexSpace(S.Infinity)
+    for i in range(ndim - 1):
+        assert ad_rep_sympy[i + 1,i] == sqrt(i + 1)
+
+    if not np:
+        skip("numpy not installed.")
+
+    ad_rep_numpy = represent(ad, basis=N, ndim=4, format='numpy')
+    for i in range(ndim - 1):
+        assert ad_rep_numpy[i + 1,i] == float(sqrt(i + 1))
+
+    if not np:
+        skip("numpy not installed.")
+    if not scipy:
+        skip("scipy not installed.")
+
+    ad_rep_scipy = represent(ad, basis=N, ndim=4, format='scipy.sparse', spmatrix='lil')
+    for i in range(ndim - 1):
+        assert ad_rep_scipy[i + 1,i] == float(sqrt(i + 1))
+
+    assert ad_rep_numpy.dtype == 'float64'
+    assert ad_rep_scipy.dtype == 'float64'
+
+def test_LoweringOp():
+    assert Dagger(a) == ad
+    assert Commutator(a, ad).doit() == Integer(1)
+    assert Commutator(a, N).doit() == a
+    assert qapply(a*k) == (sqrt(k.n)*SHOKet(k.n-Integer(1))).expand()
+    assert qapply(a*kz) == Integer(0)
+    assert qapply(a*kf) == (sqrt(kf.n)*SHOKet(kf.n-Integer(1))).expand()
+    assert a.rewrite('xp').doit() == \
+        (Integer(1)/sqrt(Integer(2)*hbar*m*omega))*(I*Px + m*omega*X)
+    for i in range(ndim - 1):
+        assert a_rep[i,i + 1] == sqrt(i + 1)
+
+def test_NumberOp():
+    assert Commutator(N, ad).doit() == ad
+    assert Commutator(N, a).doit() == Integer(-1)*a
+    assert Commutator(N, H).doit() == Integer(0)
+    assert qapply(N*k) == (k.n*k).expand()
+    assert N.rewrite('a').doit() == ad*a
+    assert N.rewrite('xp').doit() == (Integer(1)/(Integer(2)*m*hbar*omega))*(
+        Px**2 + (m*omega*X)**2) - Integer(1)/Integer(2)
+    assert N.rewrite('H').doit() == H/(hbar*omega) - Integer(1)/Integer(2)
+    for i in range(ndim):
+        assert N_rep[i,i] == i
+    assert N_rep == ad_rep_sympy*a_rep
+
+def test_Hamiltonian():
+    assert Commutator(H, N).doit() == Integer(0)
+    assert qapply(H*k) == ((hbar*omega*(k.n + Integer(1)/Integer(2)))*k).expand()
+    assert H.rewrite('a').doit() == hbar*omega*(ad*a + Integer(1)/Integer(2))
+    assert H.rewrite('xp').doit() == \
+        (Integer(1)/(Integer(2)*m))*(Px**2 + (m*omega*X)**2)
+    assert H.rewrite('N').doit() == hbar*omega*(N + Integer(1)/Integer(2))
+    for i in range(ndim):
+        assert H_rep[i,i] == hbar*omega*(i + Integer(1)/Integer(2))
+
+def test_SHOKet():
+    assert SHOKet('k').dual_class() == SHOBra
+    assert SHOBra('b').dual_class() == SHOKet
+    assert InnerProduct(b,k).doit() == KroneckerDelta(k.n, b.n)
+    assert k.hilbert_space == ComplexSpace(S.Infinity)
+    assert k3_rep[k3.n, 0] == Integer(1)
+    assert b3_rep[0, b3.n] == Integer(1)
+
+def test_sho_sums():
+    e1 = Sum(SHOKet(p)*SHOBra(p), (p, 0, 1))
+    assert e1.doit() == SHOKet(0)*SHOBra(0) + SHOKet(1)*SHOBra(1)
+
+    # Test qapply with Sum on the left
+    assert qapply(
+        Sum(SHOKet(p)*SHOBra(p), (p, 0, oo))*SHOKet(q),
+        sum_doit=True
+    ) == SHOKet(q)
+
+    # Test qapply with Sum on the right
+    a = IndexedBase('a')
+    n = symbols('n', cls=Idx)
+    result = qapply(SHOBra(q)*Sum(a[n]*SHOKet(n), (n,0,oo)), sum_doit=True)
+    assert result == a[q]
+
+    # Test qapply with a product of Sums
+    result = qapply(
+        SHOBra(q)*Sum(SHOKet(p)*SHOBra(p), (p, 0, oo))*Sum(a[n]*SHOKet(n), (n,0,oo)),
+        sum_doit=True
+    )
+    assert result == a[q]
+
+    with raises(ValueError):
+        result = qapply(
+            SHOBra(q)*Sum(SHOKet(p)*SHOBra(p), (p, 0, oo))*Sum(a[p]*SHOKet(p), (p,0,oo)),
+            sum_doit=True
+        )
+
+def test_sho_coherant_state():
+    alpha = Symbol('alpha', is_complex=True)
+    cstate = exp(-Abs(alpha)**2/S(2))*Sum(((alpha**p)/sqrt(factorial(p)))*SHOKet(p), (p,0,oo))
+    # Projection onto the number eigenstate
+    assert qapply(SHOBra(q)*cstate, sum_doit=True) == exp(-Abs(alpha)**2/S(2))*alpha**q/sqrt(factorial(q))
+    # Ensure that the coherent state is an eigenstate of annihilation operator
+    assert simplify(qapply(SHOBra(q)*a*cstate, sum_doit=True)) == simplify(qapply(SHOBra(q)*alpha*cstate, sum_doit=True))
+
+def test_issue_26495():
+    nbar = Symbol('nbar', real=True, nonnegative=True)
+    n = Symbol('n', integer=True)
+    i = Symbol('i', integer=True, nonnegative=True)
+    j = Symbol('j', integer=True, nonnegative=True)
+    rho = Sum((nbar/(1+nbar))**n*SHOKet(n)*SHOBra(n), (n,0,oo))
+    result = qapply(SHOBra(i)*rho*SHOKet(j), sum_doit=True)
+    assert simplify(result) == (nbar/(nbar+1))**i*KroneckerDelta(i,j)

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_shor.py

@@ -0,0 +1,21 @@
+from sympy.testing.pytest import XFAIL
+
+from sympy.physics.quantum.qapply import qapply
+from sympy.physics.quantum.qubit import Qubit
+from sympy.physics.quantum.shor import CMod, getr
+
+
+@XFAIL
+def test_CMod():
+    assert qapply(CMod(4, 2, 2)*Qubit(0, 0, 1, 0, 0, 0, 0, 0)) == \
+        Qubit(0, 0, 1, 0, 0, 0, 0, 0)
+    assert qapply(CMod(5, 5, 7)*Qubit(0, 0, 1, 0, 0, 0, 0, 0, 0, 0)) == \
+        Qubit(0, 0, 1, 0, 0, 0, 0, 0, 1, 0)
+    assert qapply(CMod(3, 2, 3)*Qubit(0, 1, 0, 0, 0, 0)) == \
+        Qubit(0, 1, 0, 0, 0, 1)
+
+
+def test_continued_frac():
+    assert getr(513, 1024, 10) == 2
+    assert getr(169, 1024, 11) == 6
+    assert getr(314, 4096, 16) == 13

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_state.py

@@ -0,0 +1,248 @@
+from sympy.core.add import Add
+from sympy.core.function import diff
+from sympy.core.mul import Mul
+from sympy.core.numbers import (I, Integer, Rational, oo, pi)
+from sympy.core.power import Pow
+from sympy.core.singleton import S
+from sympy.core.symbol import (Symbol, symbols)
+from sympy.core.sympify import sympify
+from sympy.functions.elementary.complexes import conjugate
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.functions.elementary.trigonometric import sin
+from sympy.testing.pytest import raises
+
+from sympy.physics.quantum.dagger import Dagger
+from sympy.physics.quantum.qexpr import QExpr
+from sympy.physics.quantum.state import (
+    Ket, Bra, TimeDepKet, TimeDepBra,
+    KetBase, BraBase, StateBase, Wavefunction,
+    OrthogonalKet, OrthogonalBra
+)
+from sympy.physics.quantum.hilbert import HilbertSpace
+
+x, y, t = symbols('x,y,t')
+
+
+class CustomKet(Ket):
+    @classmethod
+    def default_args(self):
+        return ("test",)
+
+
+class CustomKetMultipleLabels(Ket):
+    @classmethod
+    def default_args(self):
+        return ("r", "theta", "phi")
+
+
+class CustomTimeDepKet(TimeDepKet):
+    @classmethod
+    def default_args(self):
+        return ("test", "t")
+
+
+class CustomTimeDepKetMultipleLabels(TimeDepKet):
+    @classmethod
+    def default_args(self):
+        return ("r", "theta", "phi", "t")
+
+
+def test_ket():
+    k = Ket('0')
+
+    assert isinstance(k, Ket)
+    assert isinstance(k, KetBase)
+    assert isinstance(k, StateBase)
+    assert isinstance(k, QExpr)
+
+    assert k.label == (Symbol('0'),)
+    assert k.hilbert_space == HilbertSpace()
+    assert k.is_commutative is False
+
+    # Make sure this doesn't get converted to the number pi.
+    k = Ket('pi')
+    assert k.label == (Symbol('pi'),)
+
+    k = Ket(x, y)
+    assert k.label == (x, y)
+    assert k.hilbert_space == HilbertSpace()
+    assert k.is_commutative is False
+
+    assert k.dual_class() == Bra
+    assert k.dual == Bra(x, y)
+    assert k.subs(x, y) == Ket(y, y)
+
+    k = CustomKet()
+    assert k == CustomKet("test")
+
+    k = CustomKetMultipleLabels()
+    assert k == CustomKetMultipleLabels("r", "theta", "phi")
+
+    assert Ket() == Ket('psi')
+
+
+def test_bra():
+    b = Bra('0')
+
+    assert isinstance(b, Bra)
+    assert isinstance(b, BraBase)
+    assert isinstance(b, StateBase)
+    assert isinstance(b, QExpr)
+
+    assert b.label == (Symbol('0'),)
+    assert b.hilbert_space == HilbertSpace()
+    assert b.is_commutative is False
+
+    # Make sure this doesn't get converted to the number pi.
+    b = Bra('pi')
+    assert b.label == (Symbol('pi'),)
+
+    b = Bra(x, y)
+    assert b.label == (x, y)
+    assert b.hilbert_space == HilbertSpace()
+    assert b.is_commutative is False
+
+    assert b.dual_class() == Ket
+    assert b.dual == Ket(x, y)
+    assert b.subs(x, y) == Bra(y, y)
+
+    assert Bra() == Bra('psi')
+
+
+def test_ops():
+    k0 = Ket(0)
+    k1 = Ket(1)
+    k = 2*I*k0 - (x/sqrt(2))*k1
+    assert k == Add(Mul(2, I, k0),
+        Mul(Rational(-1, 2), x, Pow(2, S.Half), k1))
+
+
+def test_time_dep_ket():
+    k = TimeDepKet(0, t)
+
+    assert isinstance(k, TimeDepKet)
+    assert isinstance(k, KetBase)
+    assert isinstance(k, StateBase)
+    assert isinstance(k, QExpr)
+
+    assert k.label == (Integer(0),)
+    assert k.args == (Integer(0), t)
+    assert k.time == t
+
+    assert k.dual_class() == TimeDepBra
+    assert k.dual == TimeDepBra(0, t)
+
+    assert k.subs(t, 2) == TimeDepKet(0, 2)
+
+    k = TimeDepKet(x, 0.5)
+    assert k.label == (x,)
+    assert k.args == (x, sympify(0.5))
+
+    k = CustomTimeDepKet()
+    assert k.label == (Symbol("test"),)
+    assert k.time == Symbol("t")
+    assert k == CustomTimeDepKet("test", "t")
+
+    k = CustomTimeDepKetMultipleLabels()
+    assert k.label == (Symbol("r"), Symbol("theta"), Symbol("phi"))
+    assert k.time == Symbol("t")
+    assert k == CustomTimeDepKetMultipleLabels("r", "theta", "phi", "t")
+
+    assert TimeDepKet() == TimeDepKet("psi", "t")
+
+
+def test_time_dep_bra():
+    b = TimeDepBra(0, t)
+
+    assert isinstance(b, TimeDepBra)
+    assert isinstance(b, BraBase)
+    assert isinstance(b, StateBase)
+    assert isinstance(b, QExpr)
+
+    assert b.label == (Integer(0),)
+    assert b.args == (Integer(0), t)
+    assert b.time == t
+
+    assert b.dual_class() == TimeDepKet
+    assert b.dual == TimeDepKet(0, t)
+
+    k = TimeDepBra(x, 0.5)
+    assert k.label == (x,)
+    assert k.args == (x, sympify(0.5))
+
+    assert TimeDepBra() == TimeDepBra("psi", "t")
+
+
+def test_bra_ket_dagger():
+    x = symbols('x', complex=True)
+    k = Ket('k')
+    b = Bra('b')
+    assert Dagger(k) == Bra('k')
+    assert Dagger(b) == Ket('b')
+    assert Dagger(k).is_commutative is False
+
+    k2 = Ket('k2')
+    e = 2*I*k + x*k2
+    assert Dagger(e) == conjugate(x)*Dagger(k2) - 2*I*Dagger(k)
+
+
+def test_wavefunction():
+    x, y = symbols('x y', real=True)
+    L = symbols('L', positive=True)
+    n = symbols('n', integer=True, positive=True)
+
+    f = Wavefunction(x**2, x)
+    p = f.prob()
+    lims = f.limits
+
+    assert f.is_normalized is False
+    assert f.norm is oo
+    assert f(10) == 100
+    assert p(10) == 10000
+    assert lims[x] == (-oo, oo)
+    assert diff(f, x) == Wavefunction(2*x, x)
+    raises(NotImplementedError, lambda: f.normalize())
+    assert conjugate(f) == Wavefunction(conjugate(f.expr), x)
+    assert conjugate(f) == Dagger(f)
+
+    g = Wavefunction(x**2*y + y**2*x, (x, 0, 1), (y, 0, 2))
+    lims_g = g.limits
+
+    assert lims_g[x] == (0, 1)
+    assert lims_g[y] == (0, 2)
+    assert g.is_normalized is False
+    assert g.norm == sqrt(42)/3
+    assert g(2, 4) == 0
+    assert g(1, 1) == 2
+    assert diff(diff(g, x), y) == Wavefunction(2*x + 2*y, (x, 0, 1), (y, 0, 2))
+    assert conjugate(g) == Wavefunction(conjugate(g.expr), *g.args[1:])
+    assert conjugate(g) == Dagger(g)
+
+    h = Wavefunction(sqrt(5)*x**2, (x, 0, 1))
+    assert h.is_normalized is True
+    assert h.normalize() == h
+    assert conjugate(h) == Wavefunction(conjugate(h.expr), (x, 0, 1))
+    assert conjugate(h) == Dagger(h)
+
+    piab = Wavefunction(sin(n*pi*x/L), (x, 0, L))
+    assert piab.norm == sqrt(L/2)
+    assert piab(L + 1) == 0
+    assert piab(0.5) == sin(0.5*n*pi/L)
+    assert piab(0.5, n=1, L=1) == sin(0.5*pi)
+    assert piab.normalize() == \
+        Wavefunction(sqrt(2)/sqrt(L)*sin(n*pi*x/L), (x, 0, L))
+    assert conjugate(piab) == Wavefunction(conjugate(piab.expr), (x, 0, L))
+    assert conjugate(piab) == Dagger(piab)
+
+    k = Wavefunction(x**2, 'x')
+    assert type(k.variables[0]) == Symbol
+
+def test_orthogonal_states():
+    bracket = OrthogonalBra(x) * OrthogonalKet(x)
+    assert bracket.doit() == 1
+
+    bracket = OrthogonalBra(x) * OrthogonalKet(x+1)
+    assert bracket.doit() == 0
+
+    bracket = OrthogonalBra(x) * OrthogonalKet(y)
+    assert bracket.doit() == bracket

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_tensorproduct.py

@@ -0,0 +1,142 @@
+from sympy.core.numbers import I
+from sympy.core.symbol import symbols
+from sympy.core.expr import unchanged
+from sympy.matrices import Matrix, SparseMatrix, ImmutableMatrix
+from sympy.testing.pytest import warns_deprecated_sympy
+
+from sympy.physics.quantum.commutator import Commutator as Comm
+from sympy.physics.quantum.tensorproduct import TensorProduct
+from sympy.physics.quantum.tensorproduct import TensorProduct as TP
+from sympy.physics.quantum.tensorproduct import tensor_product_simp
+from sympy.physics.quantum.dagger import Dagger
+from sympy.physics.quantum.qubit import Qubit, QubitBra
+from sympy.physics.quantum.operator import OuterProduct, Operator
+from sympy.physics.quantum.density import Density
+from sympy.physics.quantum.trace import Tr
+
+A = Operator('A')
+B = Operator('B')
+C = Operator('C')
+D = Operator('D')
+x = symbols('x')
+y = symbols('y', integer=True, positive=True)
+
+mat1 = Matrix([[1, 2*I], [1 + I, 3]])
+mat2 = Matrix([[2*I, 3], [4*I, 2]])
+
+
+def test_sparse_matrices():
+    spm = SparseMatrix.diag(1, 0)
+    assert unchanged(TensorProduct, spm, spm)
+
+
+def test_tensor_product_dagger():
+    assert Dagger(TensorProduct(I*A, B)) == \
+        -I*TensorProduct(Dagger(A), Dagger(B))
+    assert Dagger(TensorProduct(mat1, mat2)) == \
+        TensorProduct(Dagger(mat1), Dagger(mat2))
+
+
+def test_tensor_product_abstract():
+
+    assert TP(x*A, 2*B) == x*2*TP(A, B)
+    assert TP(A, B) != TP(B, A)
+    assert TP(A, B).is_commutative is False
+    assert isinstance(TP(A, B), TP)
+    assert TP(A, B).subs(A, C) == TP(C, B)
+
+
+def test_tensor_product_expand():
+    assert TP(A + B, B + C).expand(tensorproduct=True) == \
+        TP(A, B) + TP(A, C) + TP(B, B) + TP(B, C)
+    #Tests for fix of issue #24142
+    assert TP(A-B, B-A).expand(tensorproduct=True) == \
+        TP(A, B) - TP(A, A) - TP(B, B) + TP(B, A)
+    assert TP(2*A + B, A + B).expand(tensorproduct=True) == \
+        2 * TP(A, A) + 2 * TP(A, B) + TP(B, A) + TP(B, B)
+    assert TP(2 * A * B + A, A + B).expand(tensorproduct=True) == \
+        2 * TP(A*B, A) + 2 * TP(A*B, B) + TP(A, A) + TP(A, B)
+
+
+def test_tensor_product_commutator():
+    assert TP(Comm(A, B), C).doit().expand(tensorproduct=True) == \
+        TP(A*B, C) - TP(B*A, C)
+    assert Comm(TP(A, B), TP(B, C)).doit() == \
+        TP(A, B)*TP(B, C) - TP(B, C)*TP(A, B)
+
+
+def test_tensor_product_simp():
+    with warns_deprecated_sympy():
+        assert tensor_product_simp(TP(A, B)*TP(B, C)) == TP(A*B, B*C)
+        # tests for Pow-expressions
+        assert TP(A, B)**y == TP(A**y, B**y)
+        assert tensor_product_simp(TP(A, B)**y) == TP(A**y, B**y)
+        assert tensor_product_simp(x*TP(A, B)**2) == x*TP(A**2,B**2)
+        assert tensor_product_simp(x*(TP(A, B)**2)*TP(C,D)) == x*TP(A**2*C,B**2*D)
+        assert tensor_product_simp(TP(A,B)-TP(C,D)**y) == TP(A,B)-TP(C**y,D**y)
+
+
+def test_issue_5923():
+    # most of the issue regarding sympification of args has been handled
+    # and is tested internally by the use of args_cnc through the quantum
+    # module, but the following is a test from the issue that used to raise.
+    assert TensorProduct(1, Qubit('1')*Qubit('1').dual) == \
+        TensorProduct(1, OuterProduct(Qubit(1), QubitBra(1)))
+
+
+def test_eval_trace():
+    # This test includes tests with dependencies between TensorProducts
+    #and density operators. Since, the test is more to test the behavior of
+    #TensorProducts it remains here
+
+    # Density with simple tensor products as args
+    t = TensorProduct(A, B)
+    d = Density([t, 1.0])
+    tr = Tr(d)
+    assert tr.doit() == 1.0*Tr(A*Dagger(A))*Tr(B*Dagger(B))
+
+    ## partial trace with simple tensor products as args
+    t = TensorProduct(A, B, C)
+    d = Density([t, 1.0])
+    tr = Tr(d, [1])
+    assert tr.doit() == 1.0*A*Dagger(A)*Tr(B*Dagger(B))*C*Dagger(C)
+
+    tr = Tr(d, [0, 2])
+    assert tr.doit() == 1.0*Tr(A*Dagger(A))*B*Dagger(B)*Tr(C*Dagger(C))
+
+    # Density with multiple Tensorproducts as states
+    t2 = TensorProduct(A, B)
+    t3 = TensorProduct(C, D)
+
+    d = Density([t2, 0.5], [t3, 0.5])
+    t = Tr(d)
+    assert t.doit() == (0.5*Tr(A*Dagger(A))*Tr(B*Dagger(B)) +
+                        0.5*Tr(C*Dagger(C))*Tr(D*Dagger(D)))
+
+    t = Tr(d, [0])
+    assert t.doit() == (0.5*Tr(A*Dagger(A))*B*Dagger(B) +
+                        0.5*Tr(C*Dagger(C))*D*Dagger(D))
+
+    #Density with mixed states
+    d = Density([t2 + t3, 1.0])
+    t = Tr(d)
+    assert t.doit() == ( 1.0*Tr(A*Dagger(A))*Tr(B*Dagger(B)) +
+                        1.0*Tr(A*Dagger(C))*Tr(B*Dagger(D)) +
+                        1.0*Tr(C*Dagger(A))*Tr(D*Dagger(B)) +
+                        1.0*Tr(C*Dagger(C))*Tr(D*Dagger(D)))
+
+    t = Tr(d, [1] )
+    assert t.doit() == ( 1.0*A*Dagger(A)*Tr(B*Dagger(B)) +
+                        1.0*A*Dagger(C)*Tr(B*Dagger(D)) +
+                        1.0*C*Dagger(A)*Tr(D*Dagger(B)) +
+                        1.0*C*Dagger(C)*Tr(D*Dagger(D)))
+
+
+def test_pr24993():
+    from sympy.matrices.expressions.kronecker import matrix_kronecker_product
+    from sympy.physics.quantum.matrixutils    import matrix_tensor_product
+    X = Matrix([[0, 1], [1, 0]])
+    Xi = ImmutableMatrix(X)
+    assert TensorProduct(Xi, Xi) == TensorProduct(X, X)
+    assert TensorProduct(Xi, Xi) == matrix_tensor_product(X, X)
+    assert TensorProduct(Xi, Xi) == matrix_kronecker_product(X, X)

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_trace.py

@@ -0,0 +1,109 @@
+from sympy.core.containers import Tuple
+from sympy.core.symbol import symbols
+from sympy.matrices.dense import Matrix
+from sympy.physics.quantum.trace import Tr
+from sympy.testing.pytest import raises, warns_deprecated_sympy
+
+
+def test_trace_new():
+    a, b, c, d, Y = symbols('a b c d Y')
+    A, B, C, D = symbols('A B C D', commutative=False)
+
+    assert Tr(a + b) == a + b
+    assert Tr(A + B) == Tr(A) + Tr(B)
+
+    #check trace args not implicitly permuted
+    assert Tr(C*D*A*B).args[0].args == (C, D, A, B)
+
+    # check for mul and adds
+    assert Tr((a*b) + ( c*d)) == (a*b) + (c*d)
+    # Tr(scalar*A) = scalar*Tr(A)
+    assert Tr(a*A) == a*Tr(A)
+    assert Tr(a*A*B*b) == a*b*Tr(A*B)
+
+    # since A is symbol and not commutative
+    assert isinstance(Tr(A), Tr)
+
+    #POW
+    assert Tr(pow(a, b)) == a**b
+    assert isinstance(Tr(pow(A, a)), Tr)
+
+    #Matrix
+    M = Matrix([[1, 1], [2, 2]])
+    assert Tr(M) == 3
+
+    ##test indices in different forms
+    #no index
+    t = Tr(A)
+    assert t.args[1] == Tuple()
+
+    #single index
+    t = Tr(A, 0)
+    assert t.args[1] == Tuple(0)
+
+    #index in a list
+    t = Tr(A, [0])
+    assert t.args[1] == Tuple(0)
+
+    t = Tr(A, [0, 1, 2])
+    assert t.args[1] == Tuple(0, 1, 2)
+
+    #index is tuple
+    t = Tr(A, (0))
+    assert t.args[1] == Tuple(0)
+
+    t = Tr(A, (1, 2))
+    assert t.args[1] == Tuple(1, 2)
+
+    #trace indices test
+    t = Tr((A + B), [2])
+    assert t.args[0].args[1] == Tuple(2) and t.args[1].args[1] == Tuple(2)
+
+    t = Tr(a*A, [2, 3])
+    assert t.args[1].args[1] == Tuple(2, 3)
+
+    #class with trace method defined
+    #to simulate numpy objects
+    class Foo:
+        def trace(self):
+            return 1
+    assert Tr(Foo()) == 1
+
+    #argument test
+    # check for value error, when either/both arguments are not provided
+    raises(ValueError, lambda: Tr())
+    raises(ValueError, lambda: Tr(A, 1, 2))
+
+
+def test_trace_doit():
+    a, b, c, d = symbols('a b c d')
+    A, B, C, D = symbols('A B C D', commutative=False)
+
+    #TODO: needed while testing reduced density operations, etc.
+
+
+def test_permute():
+    A, B, C, D, E, F, G = symbols('A B C D E F G', commutative=False)
+    t = Tr(A*B*C*D*E*F*G)
+
+    assert t.permute(0).args[0].args == (A, B, C, D, E, F, G)
+    assert t.permute(2).args[0].args == (F, G, A, B, C, D, E)
+    assert t.permute(4).args[0].args == (D, E, F, G, A, B, C)
+    assert t.permute(6).args[0].args == (B, C, D, E, F, G, A)
+    assert t.permute(8).args[0].args == t.permute(1).args[0].args
+
+    assert t.permute(-1).args[0].args == (B, C, D, E, F, G, A)
+    assert t.permute(-3).args[0].args == (D, E, F, G, A, B, C)
+    assert t.permute(-5).args[0].args == (F, G, A, B, C, D, E)
+    assert t.permute(-8).args[0].args == t.permute(-1).args[0].args
+
+    t = Tr((A + B)*(B*B)*C*D)
+    assert t.permute(2).args[0].args == (C, D, (A + B), (B**2))
+
+    t1 = Tr(A*B)
+    t2 = t1.permute(1)
+    assert id(t1) != id(t2) and t1 == t2
+
+def test_deprecated_core_trace():
+    with warns_deprecated_sympy():
+        from sympy.core.trace import Tr # noqa:F401

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/tests/test_transforms.py

@@ -0,0 +1,75 @@
+"""Tests of transforms of quantum expressions for Mul and Pow."""
+
+from sympy.core.symbol import symbols
+from sympy.testing.pytest import raises
+
+from sympy.physics.quantum.operator import (
+    Operator, OuterProduct
+)
+from sympy.physics.quantum.state import Ket, Bra
+from sympy.physics.quantum.innerproduct import InnerProduct
+from sympy.physics.quantum.tensorproduct import TensorProduct
+
+
+k1 = Ket('k1')
+k2 = Ket('k2')
+k3 = Ket('k3')
+b1 = Bra('b1')
+b2 = Bra('b2')
+b3 = Bra('b3')
+A = Operator('A')
+B = Operator('B')
+C = Operator('C')
+x, y, z = symbols('x y z')
+
+
+def test_bra_ket():
+    assert b1*k1 == InnerProduct(b1, k1)
+    assert k1*b1 == OuterProduct(k1, b1)
+    # Test priority of inner product
+    assert OuterProduct(k1, b1)*k2 == InnerProduct(b1, k2)*k1
+    assert b1*OuterProduct(k1, b2) == InnerProduct(b1, k1)*b2
+
+
+def test_tensor_product():
+    # We are attempting to be rigourous and raise TypeError when a user tries
+    # to combine bras, kets, and operators in a manner that doesn't make sense.
+    # In particular, we are not trying to interpret regular ``*`` multiplication
+    # as a tensor product.
+    with raises(TypeError):
+        k1*k1
+    with raises(TypeError):
+        b1*b1
+    with raises(TypeError):
+        k1*TensorProduct(k2, k3)
+    with raises(TypeError):
+        b1*TensorProduct(b2, b3)
+    with raises(TypeError):
+        TensorProduct(k2, k3)*k1
+    with raises(TypeError):
+        TensorProduct(b2, b3)*b1
+
+    assert TensorProduct(A, B, C)*TensorProduct(k1, k2, k3) == \
+        TensorProduct(A*k1, B*k2, C*k3)
+    assert TensorProduct(b1, b2, b3)*TensorProduct(A, B, C) == \
+        TensorProduct(b1*A, b2*B, b3*C)
+    assert TensorProduct(b1, b2, b3)*TensorProduct(k1, k2, k3) == \
+        InnerProduct(b1, k1)*InnerProduct(b2, k2)*InnerProduct(b3, k3)
+    assert TensorProduct(b1, b2, b3)*TensorProduct(A, B, C)*TensorProduct(k1, k2, k3) == \
+        TensorProduct(b1*A*k1, b2*B*k2, b3*C*k3)
+
+
+def test_outer_product():
+    assert OuterProduct(k1, b1)*OuterProduct(k2, b2) == \
+        InnerProduct(b1, k2)*OuterProduct(k1, b2)
+
+
+def test_compound():
+    e1 = b1*A*B*k1*b2*k2*b3
+    assert e1 == InnerProduct(b2, k2)*b1*A*B*OuterProduct(k1, b3)
+
+    e2 = TensorProduct(k1, k2)*TensorProduct(b1, b2)
+    assert e2 == TensorProduct(
+        OuterProduct(k1, b1),
+        OuterProduct(k2, b2)
+    )

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/trace.py

@@ -0,0 +1,230 @@
+from sympy.core.add import Add
+from sympy.core.containers import Tuple
+from sympy.core.expr import Expr
+from sympy.core.mul import Mul
+from sympy.core.power import Pow
+from sympy.core.sorting import default_sort_key
+from sympy.core.sympify import sympify
+from sympy.matrices import Matrix
+
+
+def _is_scalar(e):
+    """ Helper method used in Tr"""
+
+    # sympify to set proper attributes
+    e = sympify(e)
+    if isinstance(e, Expr):
+        if (e.is_Integer or e.is_Float or
+            e.is_Rational or e.is_Number or
+            (e.is_Symbol and e.is_commutative)
+                ):
+            return True
+
+    return False
+
+
+def _cycle_permute(l):
+    """ Cyclic permutations based on canonical ordering
+
+    Explanation
+    ===========
+
+    This method does the sort based ascii values while
+    a better approach would be to used lexicographic sort.
+
+    TODO: Handle condition such as symbols have subscripts/superscripts
+    in case of lexicographic sort
+
+    """
+
+    if len(l) == 1:
+        return l
+
+    min_item = min(l, key=default_sort_key)
+    indices = [i for i, x in enumerate(l) if x == min_item]
+
+    le = list(l)
+    le.extend(l)  # duplicate and extend string for easy processing
+
+    # adding the first min_item index back for easier looping
+    indices.append(len(l) + indices[0])
+
+    # create sublist of items with first item as min_item and last_item
+    # in each of the sublist is item just before the next occurrence of
+    # minitem in the cycle formed.
+    sublist = [[le[indices[i]:indices[i + 1]]] for i in
+               range(len(indices) - 1)]
+
+    # we do comparison of strings by comparing elements
+    # in each sublist
+    idx = sublist.index(min(sublist))
+    ordered_l = le[indices[idx]:indices[idx] + len(l)]
+
+    return ordered_l
+
+
+def _rearrange_args(l):
+    """ this just moves the last arg to first position
+     to enable expansion of args
+     A,B,A ==> A**2,B
+    """
+    if len(l) == 1:
+        return l
+
+    x = list(l[-1:])
+    x.extend(l[0:-1])
+    return Mul(*x).args
+
+
+class Tr(Expr):
+    """ Generic Trace operation than can trace over:
+
+    a) SymPy matrix
+    b) operators
+    c) outer products
+
+    Parameters
+    ==========
+    o : operator, matrix, expr
+    i : tuple/list indices (optional)
+
+    Examples
+    ========
+
+    # TODO: Need to handle printing
+
+    a) Trace(A+B) = Tr(A) + Tr(B)
+    b) Trace(scalar*Operator) = scalar*Trace(Operator)
+
+    >>> from sympy.physics.quantum.trace import Tr
+    >>> from sympy import symbols, Matrix
+    >>> a, b = symbols('a b', commutative=True)
+    >>> A, B = symbols('A B', commutative=False)
+    >>> Tr(a*A,[2])
+    a*Tr(A)
+    >>> m = Matrix([[1,2],[1,1]])
+    >>> Tr(m)
+    2
+
+    """
+    def __new__(cls, *args):
+        """ Construct a Trace object.
+
+        Parameters
+        ==========
+        args = SymPy expression
+        indices = tuple/list if indices, optional
+
+        """
+
+        # expect no indices,int or a tuple/list/Tuple
+        if (len(args) == 2):
+            if not isinstance(args[1], (list, Tuple, tuple)):
+                indices = Tuple(args[1])
+            else:
+                indices = Tuple(*args[1])
+
+            expr = args[0]
+        elif (len(args) == 1):
+            indices = Tuple()
+            expr = args[0]
+        else:
+            raise ValueError("Arguments to Tr should be of form "
+                             "(expr[, [indices]])")
+
+        if isinstance(expr, Matrix):
+            return expr.trace()
+        elif hasattr(expr, 'trace') and callable(expr.trace):
+            #for any objects that have trace() defined e.g numpy
+            return expr.trace()
+        elif isinstance(expr, Add):
+            return Add(*[Tr(arg, indices) for arg in expr.args])
+        elif isinstance(expr, Mul):
+            c_part, nc_part = expr.args_cnc()
+            if len(nc_part) == 0:
+                return Mul(*c_part)
+            else:
+                obj = Expr.__new__(cls, Mul(*nc_part), indices )
+                #this check is needed to prevent cached instances
+                #being returned even if len(c_part)==0
+                return Mul(*c_part)*obj if len(c_part) > 0 else obj
+        elif isinstance(expr, Pow):
+            if (_is_scalar(expr.args[0]) and
+                    _is_scalar(expr.args[1])):
+                return expr
+            else:
+                return Expr.__new__(cls, expr, indices)
+        else:
+            if (_is_scalar(expr)):
+                return expr
+
+            return Expr.__new__(cls, expr, indices)
+
+    @property
+    def kind(self):
+        expr = self.args[0]
+        expr_kind = expr.kind
+        return expr_kind.element_kind
+
+    def doit(self, **hints):
+        """ Perform the trace operation.
+
+        #TODO: Current version ignores the indices set for partial trace.
+
+        >>> from sympy.physics.quantum.trace import Tr
+        >>> from sympy.physics.quantum.operator import OuterProduct
+        >>> from sympy.physics.quantum.spin import JzKet, JzBra
+        >>> t = Tr(OuterProduct(JzKet(1,1), JzBra(1,1)))
+        >>> t.doit()
+        1
+
+        """
+        if hasattr(self.args[0], '_eval_trace'):
+            return self.args[0]._eval_trace(indices=self.args[1])
+
+        return self
+
+    @property
+    def is_number(self):
+        # TODO : improve this implementation
+        return True
+
+    #TODO: Review if the permute method is needed
+    # and if it needs to return a new instance
+    def permute(self, pos):
+        """ Permute the arguments cyclically.
+
+        Parameters
+        ==========
+
+        pos : integer, if positive, shift-right, else shift-left
+
+        Examples
+        ========
+
+        >>> from sympy.physics.quantum.trace import Tr
+        >>> from sympy import symbols
+        >>> A, B, C, D = symbols('A B C D', commutative=False)
+        >>> t = Tr(A*B*C*D)
+        >>> t.permute(2)
+        Tr(C*D*A*B)
+        >>> t.permute(-2)
+        Tr(C*D*A*B)
+
+        """
+        if pos > 0:
+            pos = pos % len(self.args[0].args)
+        else:
+            pos = -(abs(pos) % len(self.args[0].args))
+
+        args = list(self.args[0].args[-pos:] + self.args[0].args[0:-pos])
+
+        return Tr(Mul(*(args)))
+
+    def _hashable_content(self):
+        if isinstance(self.args[0], Mul):
+            args = _cycle_permute(_rearrange_args(self.args[0].args))
+        else:
+            args = [self.args[0]]
+
+        return tuple(args) + (self.args[1], )

backend_service/venv/lib/python3.13/site-packages/sympy/physics/quantum/transforms.py

@@ -0,0 +1,291 @@
+"""Transforms that are always applied to quantum expressions.
+
+This module uses the kind and _constructor_postprocessor_mapping APIs
+to transform different combinations of Operators, Bras, and Kets into
+Inner/Outer/TensorProducts. These transformations are registered
+with the postprocessing API of core classes like `Mul` and `Pow` and
+are always applied to any expression involving Bras, Kets, and
+Operators. This API replaces the custom `__mul__` and `__pow__`
+methods of the quantum classes, which were found to be inconsistent.
+
+THIS IS EXPERIMENTAL.
+"""
+from sympy.core.basic import Basic
+from sympy.core.expr import Expr
+from sympy.core.mul import Mul
+from sympy.core.singleton import S
+from sympy.multipledispatch.dispatcher import (
+    Dispatcher, ambiguity_register_error_ignore_dup
+)
+from sympy.utilities.misc import debug
+
+from sympy.physics.quantum.innerproduct import InnerProduct
+from sympy.physics.quantum.kind import KetKind, BraKind, OperatorKind
+from sympy.physics.quantum.operator import (
+    OuterProduct, IdentityOperator, Operator
+)
+from sympy.physics.quantum.state import BraBase, KetBase, StateBase
+from sympy.physics.quantum.tensorproduct import TensorProduct
+
+
+#-----------------------------------------------------------------------------
+# Multipledispatch based transformed for Mul and Pow
+#-----------------------------------------------------------------------------
+
+_transform_state_pair = Dispatcher('_transform_state_pair')
+"""Transform a pair of expression in a Mul to their canonical form.
+
+All functions that are registered with this dispatcher need to take
+two inputs and return either tuple of transformed outputs, or None if no
+transform is applied. The output tuple is inserted into the right place
+of the ``Mul`` that is being put into canonical form. It works something like
+the following:
+
+``Mul(a, b, c, d, e, f) -> Mul(*(_transform_state_pair(a, b) + (c, d, e, f))))``
+
+The transforms here are always applied when quantum objects are multiplied.
+
+THIS IS EXPERIMENTAL.
+
+However, users of ``sympy.physics.quantum`` can import this dispatcher and
+register their own transforms to control the canonical form of products
+of quantum expressions.
+"""
+
+@_transform_state_pair.register(Expr, Expr)
+def _transform_expr(a, b):
+    """Default transformer that does nothing for base types."""
+    return None
+
+
+# The identity times anything is the anything.
+_transform_state_pair.add(
+    (IdentityOperator, Expr),
+    lambda x, y: (y,),
+    on_ambiguity=ambiguity_register_error_ignore_dup
+)
+_transform_state_pair.add(
+    (Expr, IdentityOperator),
+    lambda x, y: (x,),
+    on_ambiguity=ambiguity_register_error_ignore_dup
+)
+_transform_state_pair.add(
+    (IdentityOperator, IdentityOperator),
+    lambda x, y: S.One,
+    on_ambiguity=ambiguity_register_error_ignore_dup
+)
+
+@_transform_state_pair.register(BraBase, KetBase)
+def _transform_bra_ket(a, b):
+    """Transform a bra*ket -> InnerProduct(bra, ket)."""
+    return (InnerProduct(a, b),)
+
+@_transform_state_pair.register(KetBase, BraBase)
+def _transform_ket_bra(a, b):
+    """Transform a keT*bra -> OuterProduct(ket, bra)."""
+    return (OuterProduct(a, b),)
+
+@_transform_state_pair.register(KetBase, KetBase)
+def _transform_ket_ket(a, b):
+    """Raise a TypeError if a user tries to multiply two kets.
+
+    Multiplication based on `*` is not a shorthand for tensor products.
+    """
+    raise TypeError(
+        'Multiplication of two kets is not allowed. Use TensorProduct instead.'
+    )
+
+@_transform_state_pair.register(BraBase, BraBase)
+def _transform_bra_bra(a, b):
+    """Raise a TypeError if a user tries to multiply two bras.
+
+    Multiplication based on `*` is not a shorthand for tensor products.
+    """
+    raise TypeError(
+        'Multiplication of two bras is not allowed. Use TensorProduct instead.'
+    )
+
+@_transform_state_pair.register(OuterProduct, KetBase)
+def _transform_op_ket(a, b):
+    return (InnerProduct(a.bra, b), a.ket)
+
+@_transform_state_pair.register(BraBase, OuterProduct)
+def _transform_bra_op(a, b):
+    return (InnerProduct(a, b.ket), b.bra)
+
+@_transform_state_pair.register(TensorProduct, KetBase)
+def _transform_tp_ket(a, b):
+    """Raise a TypeError if a user tries to multiply TensorProduct(*kets)*ket.
+
+    Multiplication based on `*` is not a shorthand for tensor products.
+    """
+    if a.kind == KetKind:
+        raise TypeError(
+            'Multiplication of TensorProduct(*kets)*ket is invalid.'
+        )
+
+@_transform_state_pair.register(KetBase, TensorProduct)
+def _transform_ket_tp(a, b):
+    """Raise a TypeError if a user tries to multiply ket*TensorProduct(*kets).
+
+    Multiplication based on `*` is not a shorthand for tensor products.
+    """
+    if b.kind == KetKind:
+        raise TypeError(
+            'Multiplication of ket*TensorProduct(*kets) is invalid.'
+        )
+
+@_transform_state_pair.register(TensorProduct, BraBase)
+def _transform_tp_bra(a, b):
+    """Raise a TypeError if a user tries to multiply TensorProduct(*bras)*bra.
+
+    Multiplication based on `*` is not a shorthand for tensor products.
+    """
+    if a.kind == BraKind:
+        raise TypeError(
+            'Multiplication of TensorProduct(*bras)*bra is invalid.'
+        )
+
+@_transform_state_pair.register(BraBase, TensorProduct)
+def _transform_bra_tp(a, b):
+    """Raise a TypeError if a user tries to multiply bra*TensorProduct(*bras).
+
+    Multiplication based on `*` is not a shorthand for tensor products.
+    """
+    if b.kind == BraKind:
+        raise TypeError(
+            'Multiplication of bra*TensorProduct(*bras) is invalid.'
+        )
+
+@_transform_state_pair.register(TensorProduct, TensorProduct)
+def _transform_tp_tp(a, b):
+    """Combine a product of tensor products if their number of args matches."""
+    debug('_transform_tp_tp', a, b)
+    if len(a.args) == len(b.args):
+        if a.kind == BraKind and b.kind == KetKind:
+            return tuple([InnerProduct(i, j) for (i, j) in zip(a.args, b.args)])
+        else:
+            return (TensorProduct(*(i*j for (i, j) in zip(a.args, b.args))), )
+
+@_transform_state_pair.register(OuterProduct, OuterProduct)
+def _transform_op_op(a, b):
+    """Extract an inner produt from a product of outer products."""
+    return (InnerProduct(a.bra, b.ket), OuterProduct(a.ket, b.bra))
+
+
+#-----------------------------------------------------------------------------
+# Postprocessing transforms for Mul and Pow
+#-----------------------------------------------------------------------------
+
+
+def _postprocess_state_mul(expr):
+    """Transform a ``Mul`` of quantum expressions into canonical form.
+
+    This function is registered ``_constructor_postprocessor_mapping`` as a
+    transformer for ``Mul``. This means that every time a quantum expression
+    is multiplied, this function will be called to transform it into canonical
+    form as defined by the binary functions registered with
+    ``_transform_state_pair``.
+
+    The algorithm of this function is as follows. It walks the args
+    of the input ``Mul`` from left to right and calls ``_transform_state_pair``
+    on every overlapping pair of args. Each time ``_transform_state_pair``
+    is called it can return a tuple of items or None. If None, the pair isn't
+    transformed. If a tuple, then the last element of the tuple goes back into
+    the args to be transformed again and the others are extended onto the result
+    args list.
+
+    The algorithm can be visualized in the following table:
+
+    step   result                                 args
+    ============================================================================
+    #0     []                                     [a, b, c, d, e, f]
+    #1     []                                     [T(a,b), c, d, e, f]
+    #2     [T(a,b)[:-1]]                          [T(a,b)[-1], c, d, e, f]
+    #3     [T(a,b)[:-1]]                          [T(T(a,b)[-1], c), d, e, f]
+    #4     [T(a,b)[:-1], T(T(a,b)[-1], c)[:-1]]   [T(T(T(a,b)[-1], c)[-1], d), e, f]
+    #5     ...
+
+    One limitation of the current implementation is that we assume that only the
+    last item of the transformed tuple goes back into the args to be transformed
+    again. These seems to handle the cases needed for Mul. However, we may need
+    to extend the algorithm to have the entire tuple go back into the args for
+    further transformation.
+    """
+    args = list(expr.args)
+    result = []
+
+    # Continue as long as we have at least 2 elements
+    while len(args) > 1:
+        # Get first two elements
+        first = args.pop(0)
+        second = args[0]  # Look at second element without popping yet
+
+        transformed = _transform_state_pair(first, second)
+
+        if transformed is None:
+            # If transform returns None, append first element
+            result.append(first)
+        else:
+            # This item was transformed, pop and discard
+            args.pop(0)
+            # The last item goes back to be transformed again
+            args.insert(0, transformed[-1])
+            # All other items go directly into the result
+            result.extend(transformed[:-1])
+
+    # Append any remaining element
+    if args:
+        result.append(args[0])
+
+    return Mul._from_args(result, is_commutative=False)
+
+
+def _postprocess_state_pow(expr):
+    """Handle bras and kets raised to powers.
+
+    Under ``*`` multiplication this is invalid. Users should use a
+    TensorProduct instead.
+    """
+    base, exp = expr.as_base_exp()
+    if base.kind == KetKind or base.kind == BraKind:
+        raise TypeError(
+            'A bra or ket to a power is invalid, use TensorProduct instead.'
+        )
+
+
+def _postprocess_tp_pow(expr):
+    """Handle TensorProduct(*operators)**(positive integer).
+
+    This handles a tensor product of operators, to an integer power.
+    The power here is interpreted as regular multiplication, not
+    tensor product exponentiation. The form of exponentiation performed
+    here leaves the space and dimension of the object the same.
+
+    This operation does not make sense for tensor product's of states.
+    """
+    base, exp = expr.as_base_exp()
+    debug('_postprocess_tp_pow: ', base, exp, expr.args)
+    if isinstance(base, TensorProduct) and exp.is_integer and exp.is_positive and base.kind == OperatorKind:
+        new_args = [a**exp for a in base.args]
+        return TensorProduct(*new_args)
+
+
+#-----------------------------------------------------------------------------
+# Register the transformers with Basic._constructor_postprocessor_mapping
+#-----------------------------------------------------------------------------
+
+
+Basic._constructor_postprocessor_mapping[StateBase] = {
+    "Mul": [_postprocess_state_mul],
+    "Pow": [_postprocess_state_pow]
+}
+
+Basic._constructor_postprocessor_mapping[TensorProduct] = {
+    "Mul": [_postprocess_state_mul],
+    "Pow": [_postprocess_tp_pow]
+}
+
+Basic._constructor_postprocessor_mapping[Operator] = {
+    "Mul": [_postprocess_state_mul]
+}