Source code for pennylane.templates.state_preparations.cosine_window

# Copyright 2018-2021 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

#     http://www.apache.org/licenses/LICENSE-2.0

# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
r"""
Contains the CosineWindow template.
"""
import numpy as np

import pennylane as qml
from pennylane import capture, math, register_resources
from pennylane.control_flow import for_loop
from pennylane.decomposition import add_decomps, adjoint_resource_rep, resource_rep
from pennylane.exceptions import WireError
from pennylane.operation import StatePrepBase
from pennylane.wires import Wires



[docs]
class CosineWindow(StatePrepBase):
    r"""CosineWindow(wires)
    Prepares an initial state with a cosine wave function.

    The wave function is defined below where :math:`m` is the number of wires.

    .. math::

        |\psi\rangle = \sqrt{2^{1-m}} \sum_{k=0}^{2^m-1} \cos(\frac{\pi k}{2^m} - \frac{\pi}{2}) |k\rangle,

    .. figure:: ../../_static/templates/state_preparations/cosine_window.png
        :align: center
        :width: 65%
        :target: javascript:void(0);

    .. note::

        The wave function is shifted by :math:`\frac{\pi}{2}` units so that the window is centered.

    For more details see `Phys. Rev. D 106 (2022) <https://journals.aps.org/prd/abstract/10.1103/PhysRevD.106.034503>`_.

    .. seealso:: :class:`~.QuantumPhaseEstimation` and :class:`~.QFT`.

    Args:
        wires (Sequence[int] or int): the wire(s) the operation acts on

    **Example**

    >>> dev = qml.device('default.qubit', wires=2)
    >>> @qml.qnode(dev)
    ... def example_circuit():
    ...     qml.CosineWindow(wires=range(2))
    ...     return qml.probs()
    >>> print(example_circuit())
    [1.87469973e-33 2.50000000e-01 5.00000000e-01 2.50000000e-01]
    """

    resource_keys = {"num_wires"}


[docs]
    @staticmethod
    def compute_decomposition(wires):  # pylint: disable=arguments-differ
        r"""Representation of the operator as a product of other operators (static method).
        It is efficiently decomposed from one QFT over all qubits and one-qubit rotation gates.

        Args:
            wires (Iterable, Wires): the wire(s) the operation acts on

        Returns:
            list[Operator]: decomposition into lower level operations
        """

        decomp_ops = []

        decomp_ops.append(qml.Hadamard(wires=wires[-1]))
        decomp_ops.append(qml.RZ(np.pi, wires=wires[-1]))
        decomp_ops.append(qml.adjoint(qml.QFT)(wires=wires))

        for ind, wire in enumerate(wires):
            decomp_ops.append(qml.PhaseShift(np.pi * 2 ** (-ind - 1), wires=wire))

        return decomp_ops


    @property
    def resource_params(self) -> dict:
        return {
            "num_wires": len(self.wires),
        }


[docs]
    def label(self, decimals=None, base_label=None, cache=None):
        return "CosineWindow"



[docs]
    def state_vector(self, wire_order=None):
        r"""Calculation of the state vector generated by the cosine window.

        Args:
            wire_order (Iterable, Wires): Custom order of wires for the returned state vector.

        Raises:
            WireError: Custom wire_order must contain all wires.

        Returns:
            TensorLike[complex]: output state
        """

        num_op_wires = len(self.wires)
        op_vector_shape = (2,) * num_op_wires
        coeff = np.sqrt(2 ** (1 - num_op_wires))
        vector = np.array(
            [
                coeff * np.cos(-np.pi / 2 + np.pi * x / 2**num_op_wires)
                for x in range(2**num_op_wires)
            ]
        )
        op_vector = math.reshape(vector, op_vector_shape)

        if wire_order is None or Wires(wire_order) == self.wires:
            return op_vector

        wire_order = Wires(wire_order)
        if not wire_order.contains_wires(self.wires):
            raise WireError(f"Custom wire_order must contain all {self.name} wires")

        num_total_wires = len(wire_order)
        indices = tuple(
            [Ellipsis] + [slice(None)] * num_op_wires + [0] * (num_total_wires - num_op_wires)
        )
        ket_shape = [2] * num_total_wires
        ket = np.zeros(ket_shape, dtype=np.complex128)
        ket[indices] = op_vector

        if self.wires != wire_order[:num_op_wires]:
            current_order = self.wires + list(Wires.unique_wires([wire_order, self.wires]))
            desired_order = [current_order.index(w) for w in wire_order]
            ket = ket.transpose(desired_order)

        return math.convert_like(ket, op_vector)




def _cosine_window_resources(num_wires):
    return {
        resource_rep(qml.Hadamard): 1,
        resource_rep(qml.RZ): 1,
        adjoint_resource_rep(qml.QFT, {"num_wires": num_wires}): 1,
        resource_rep(qml.PhaseShift): num_wires,
    }


@register_resources(_cosine_window_resources)
def _cosine_window_decomposition(wires):
    qml.Hadamard(wires=wires[-1])
    qml.RZ(np.pi, wires=wires[-1])
    qml.adjoint(qml.QFT)(wires=wires)

    if capture.enabled():
        wires = qml.math.array(wires, like="jax")

    @for_loop(len(wires))
    def wires_loop(ind):
        wire = wires[ind]
        qml.PhaseShift(np.pi * 2 ** (-ind - 1), wires=wire)

    wires_loop()  # pylint: disable=no-value-for-parameter


add_decomps(CosineWindow, _cosine_window_decomposition)
_modules/pennylane/templates/state_preparations/cosine_window
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Source code for pennylane.templates.state_preparations.cosine_window

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