Source code for pennylane.ops.op_math.adjoint_class

# Copyright 2018-2022 Xanadu Quantum Technologies Inc.

# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at


# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# See the License for the specific language governing permissions and
# limitations under the License.
This submodule defines the symbolic operation that indicates the adjoint of an operator.
import pennylane as qml
from pennylane.math import conj, transpose, moveaxis
from pennylane.operation import Observable, Operation

from .symbolicop import SymbolicOp

# pylint: disable=no-member
class AdjointOperation(Operation):
    """This mixin class is dynamically added to an ``Adjoint`` instance if the provided base class
    is an ``Operation``.

    .. warning::
        This mixin class should never be initialized independent of ``Adjoint``.

    Overriding the dunder method ``__new__`` in ``Adjoint`` allows us to customize the creation of
    an instance and dynamically add in parent classes.

    .. note:: Once the ``Operation`` class does not contain any unique logic any more, this mixin
    class can be removed.

    # This inverse behavior only needs to temporarily patch behavior until in-place inversion is
    # removed.

    def _inverse(self):
        return self.base._inverse  # pylint: disable=protected-access

    def _inverse(self, boolean):
        self.base._inverse = boolean  # pylint: disable=protected-access
        # refresh name as base_name got updated.
        self._name = f"Adjoint({})"

    def inv(self):
        # refresh name as base_name got updated.
        self._name = f"Adjoint({})"
        return self

    def base_name(self):
        return self._name

    def name(self):
        return self._name

    # pylint: disable=missing-function-docstring
    def basis(self):
        return self.base.basis

    def control_wires(self):
        return self.base.control_wires

    def single_qubit_rot_angles(self):
        omega, theta, phi = self.base.single_qubit_rot_angles()
        return [-phi, -theta, -omega]

    def grad_method(self):
        return self.base.grad_method

    # pylint: disable=missing-function-docstring
    def grad_recipe(self):
        return self.base.grad_recipe

    def get_parameter_shift(self, idx):
        return self.base.get_parameter_shift(idx)

    def parameter_frequencies(self):
        return self.base.parameter_frequencies

    def generator(self):
        return -1.0 * self.base.generator()

# pylint: disable=too-many-public-methods
[docs]class Adjoint(SymbolicOp): """ The Adjoint of an operator. Args: base (~.operation.Operator): The operator that is adjointed. .. seealso:: :func:`~.adjoint`, :meth:`~.operation.Operator.adjoint` This is a *developer*-facing class, and the :func:`~.adjoint` transform should be used to construct instances of this class. **Example** >>> op = Adjoint(qml.S(0)) >>> 'Adjoint(S)' >>> qml.matrix(op) array([[1.-0.j, 0.-0.j], [0.-0.j, 0.-1.j]]) >>> qml.generator(Adjoint(qml.RX(1.0, wires=0))) (PauliX(wires=[0]), 0.5) >>> Adjoint(qml.RX(1.234, wires=0)).data [1.234] .. details:: :title: Developer Details This class mixes in parent classes based on the inheritance tree of the provided ``Operator``. For example, when provided an ``Operation``, the instance will inherit from ``Operation`` and the ``AdjointOperation`` mixin. >>> op = Adjoint(qml.RX(1.234, wires=0)) >>> isinstance(op, qml.operation.Operation) True >>> isinstance(op, AdjointOperation) True >>> op.grad_method 'A' If the base class is an ``Observable`` instead, the ``Adjoint`` will be an ``Observable`` as well. >>> op = Adjoint(1.0 * qml.PauliX(0)) >>> isinstance(op, qml.operation.Observable) True >>> isinstance(op, qml.operation.Operation) False >>> Adjoint(qml.PauliX(0)) @ qml.PauliY(1) Adjoint(PauliX)(wires=[0]) @ PauliY(wires=[1]) """ _operation_type = None # type if base inherits from operation and not observable _operation_observable_type = None # type if base inherits from both operation and observable _observable_type = None # type if base inherits from observable and not operation # pylint: disable=unused-argument def __new__(cls, base=None, do_queue=True, id=None): """Mixes in parents based on inheritance structure of base. Though all the types will be named "Adjoint", their *identity* and location in memory will be different based on ``base``'s inheritance. We cache the different types in private class variables so that: >>> Adjoint(op).__class__ is Adjoint(op).__class__ True >>> type(Adjoint(op)) == type(Adjoint(op)) True >>> Adjoint(qml.RX(1.2, wires=0)).__class__ is Adjoint._operation_type True >>> Adjoint(qml.PauliX(0)).__class__ is Adjoint._operation_observable_type True """ if isinstance(base, Operation): if isinstance(base, Observable): if cls._operation_observable_type is None: class_bases = (AdjointOperation, Adjoint, SymbolicOp, Observable, Operation) cls._operation_observable_type = type( "Adjoint", class_bases, dict(cls.__dict__) ) return object.__new__(cls._operation_observable_type) # not an observable if cls._operation_type is None: class_bases = (AdjointOperation, Adjoint, SymbolicOp, Operation) cls._operation_type = type("Adjoint", class_bases, dict(cls.__dict__)) return object.__new__(cls._operation_type) if isinstance(base, Observable): if cls._observable_type is None: class_bases = (Adjoint, SymbolicOp, Observable) cls._observable_type = type("Adjoint", class_bases, dict(cls.__dict__)) return object.__new__(cls._observable_type) return object.__new__(Adjoint) def __init__(self, base=None, do_queue=True, id=None): self._name = f"Adjoint({})" super().__init__(base, do_queue=do_queue, id=id) def __repr__(self): return f"Adjoint({self.base})" # pylint: disable=protected-access def _check_batching(self, params): self.base._check_batching(params) @property def batch_size(self): return self.base.batch_size @property def ndim_params(self): return self.base.ndim_params
[docs] def label(self, decimals=None, base_label=None, cache=None): base_label = self.base.label(decimals, base_label, cache=cache) return f"({base_label})†" if self.base.arithmetic_depth > 0 else f"{base_label}†"
[docs] def matrix(self, wire_order=None): if isinstance(self.base, qml.Hamiltonian): base_matrix = qml.matrix(self.base, wire_order=wire_order) else: base_matrix = self.base.matrix(wire_order=wire_order) return moveaxis(conj(base_matrix), -2, -1)
# pylint: disable=arguments-differ
[docs] def sparse_matrix(self, wire_order=None, format="csr"): base_matrix = self.base.sparse_matrix(wire_order=wire_order) return transpose(conj(base_matrix)).asformat(format=format)
# pylint: disable=arguments-renamed, invalid-overridden-method @property def has_decomposition(self): return self.base.has_adjoint or self.base.has_decomposition
[docs] def decomposition(self): if self.base.has_adjoint: return [self.base.adjoint()] base_decomp = self.base.decomposition() return [Adjoint(op) for op in reversed(base_decomp)]
[docs] def eigvals(self): # Cannot define ``compute_eigvals`` because Hermitian only defines ``eigvals`` return conj(self.base.eigvals())
# pylint: disable=arguments-renamed, invalid-overridden-method @property def has_diagonalizing_gates(self): return self.base.has_diagonalizing_gates
[docs] def diagonalizing_gates(self): return self.base.diagonalizing_gates()
# pylint: disable=arguments-renamed, invalid-overridden-method @property def has_adjoint(self): return True
[docs] def adjoint(self): return self.base.queue()
[docs] def simplify(self): base = self.base.simplify() if self.base.has_adjoint: return base.adjoint().simplify() return Adjoint(base=base.simplify())