Source code for pennylane.ops.op_math.controlled_ops

# 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 contains controlled operators based on the Controlled and ControlledOp class.

import warnings
from typing import Iterable

from pennylane.operation import AnyWires
from pennylane.ops.qubit.matrix_ops import QubitUnitary
from .controlled import ControlledOp

# pylint: disable=too-few-public-methods
[docs]class ControlledQubitUnitary(ControlledOp): r"""ControlledQubitUnitary(U, control_wires, wires, control_values) Apply an arbitrary fixed unitary to ``wires`` with control from the ``control_wires``. In addition to default ``Operation`` instance attributes, the following are available for ``ControlledQubitUnitary``: * ``control_wires``: wires that act as control for the operation * ``control_values``: the state on which to apply the controlled operation (see below) * ``target_wires``: the wires the unitary matrix will be applied to * ``active_wires``: Wires modified by the operator. This is the control wires followed by the target wires. **Details:** * Number of wires: Any (the operation can act on any number of wires) * Number of parameters: 1 * Number of dimensions per parameter: (2,) * Gradient recipe: None Args: base (Union[array[complex], QubitUnitary]): square unitary matrix or a QubitUnitary operation. If passing a matrix, this will be used to construct a QubitUnitary operator that will be used as the base operator. If providing a ``qml.QubitUnitary``, this will be used as the base directly. control_wires (Union[Wires, Sequence[int], or int]): the control wire(s) wires (Union[Wires, Sequence[int], or int]): the wire(s) the unitary acts on (optional if U is provided as a QubitUnitary) control_values (List[int, bool]): a list providing the state of the control qubits to control on (default is the all 1s state) unitary_check (bool): whether to check whether an array U is unitary when creating the operator (default False) do_queue (bool): indicates whether the operator should be recorded when created in a tape context **Example** The following shows how a single-qubit unitary can be applied to wire ``2`` with control on both wires ``0`` and ``1``: >>> U = np.array([[ 0.94877869, 0.31594146], [-0.31594146, 0.94877869]]) >>> qml.ControlledQubitUnitary(U, control_wires=[0, 1], wires=2) Controlled(QubitUnitary(array([[ 0.94877869, 0.31594146], [-0.31594146, 0.94877869]]), wires=[2]), control_wires=[0, 1]) Alternatively, the same operator can be constructed with a QubitUnitary: >>> base = qml.QubitUnitary(U, wires=2) >>> qml.ControlledQubitUnitary(base, control_wires=[0, 1]) Controlled(QubitUnitary(array([[ 0.94877869, 0.31594146], [-0.31594146, 0.94877869]]), wires=[2]), control_wires=[0, 1]) Typically controlled operations apply a desired gate if the control qubits are all in the state :math:`\vert 1\rangle`. However, there are some situations where it is necessary to apply a gate conditioned on all qubits being in the :math:`\vert 0\rangle` state, or a mix of the two. The state on which to control can be changed by passing a string of bits to `control_values`. For example, if we want to apply a single-qubit unitary to wire ``3`` conditioned on three wires where the first is in state ``0``, the second is in state ``1``, and the third in state ``1``, we can write: >>> qml.ControlledQubitUnitary(U, control_wires=[0, 1, 2], wires=3, control_values=[0, 1, 1]) or >>> qml.ControlledQubitUnitary(U, control_wires=[0, 1, 2], wires=3, control_values=[False, True, True]) """ num_wires = AnyWires """int: Number of wires that the operator acts on.""" num_params = 1 """int: Number of trainable parameters that the operator depends on.""" ndim_params = (2,) """tuple[int]: Number of dimensions per trainable parameter that the operator depends on.""" grad_method = None """Gradient computation method.""" # pylint: disable= too-many-arguments def __init__( self, base, control_wires, wires=None, control_values=None, do_queue=True, unitary_check=False, work_wires=None, ): if getattr(base, "wires", False) and wires is not None: warnings.warn( "base operator already has wires; values specified through wires kwarg will be ignored." ) if isinstance(base, Iterable): base = QubitUnitary(base, wires=wires, unitary_check=unitary_check) super().__init__( base, control_wires, control_values=control_values, work_wires=work_wires, do_queue=do_queue, ) self._name = "ControlledQubitUnitary" def _controlled(self, wire): ctrl_wires = self.control_wires + wire values = None if self.control_values is None else self.control_values + [True] new_op = ControlledQubitUnitary( self.base, control_wires=ctrl_wires, control_values=values, work_wires=self.work_wires, ) return new_op