Source code for pennylane.templates.subroutines.aqft
# Copyright 2018-2023 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.
"""
This submodule contains the template for AQFT.
"""
import warnings
import numpy as np
import pennylane as qml
from pennylane.operation import Operation
[docs]class AQFT(Operation):
r"""AQFT(order, wires)
Apply an approximate quantum Fourier transform (AQFT).
The `AQFT <https://arxiv.org/abs/1803.04933>`_ method helps to reduce the number of ``ControlledPhaseShift`` operations required
for QFT by only using a maximum of ``order`` number of ``ControlledPhaseShift`` gates per qubit.
.. seealso:: :class:`~.QFT`
Args:
order (int): the order of approximation
wires (int or Iterable[Number, str]]): the wire(s) the operation acts on
**Example**
The approximate quantum Fourier transform is applied by specifying the corresponding wires and
the order of approximation:
.. code-block::
wires = 3
dev = qml.device('default.qubit', wires=wires)
@qml.qnode(dev)
def circuit_aqft():
qml.X(0)
qml.Hadamard(1)
qml.AQFT(order=1,wires=range(wires))
return qml.state()
.. code-block:: pycon
>>> circuit_aqft()
[ 0.5 +0.j -0.25-0.25j 0. +0.j -0.25+0.25j 0.5 +0.j -0.25-0.25j 0. +0.j -0.25+0.25j]
.. details::
:title: Usage Details
**Order**
The order of approximation must be a whole number less than :math:`n-1`
where :math:`n` is the number of wires the operation is being applied on.
This creates four cases for different ``order`` values:
* ``order`` :math:`< 0`
This will raise a ``ValueError``
* ``order`` :math:`= 0`
This will warn the user that only a Hadamard transform is being applied.
.. code-block::
@qml.qnode(dev)
def circ():
qml.AQFT(order=0, wires=range(6))
return qml.probs()
The resulting circuit is:
>>> print(qml.draw(circ, expansion_strategy='device')())
UserWarning: order=0, applying Hadamard transform warnings.warn("order=0, applying Hadamard transform")
0: ──H─╭SWAP─────────────┤ ╭Probs
1: ──H─│─────╭SWAP───────┤ ├Probs
2: ──H─│─────│─────╭SWAP─┤ ├Probs
3: ──H─│─────│─────╰SWAP─┤ ├Probs
4: ──H─│─────╰SWAP───────┤ ├Probs
5: ──H─╰SWAP─────────────┤ ╰Probs
* :math:`0 <` ``order`` :math:`< n-1`
This is the intended AQFT use case.
.. code-block::
@qml.qnode(dev)
def circ():
qml.AQFT(order=2, wires=range(4))
return qml.probs()
The resulting circuit is:
>>> print(qml.draw(circ, expansion_strategy='device')())
0: ──H─╭Rϕ(1.57)─╭Rϕ(0.79)────────────────────────────────────────╭SWAP───────┤ ╭Probs
1: ────╰●────────│──────────H─╭Rϕ(1.57)─╭Rϕ(0.79)─────────────────│─────╭SWAP─┤ ├Probs
2: ──────────────╰●───────────╰●────────│──────────H─╭Rϕ(1.57)────│─────╰SWAP─┤ ├Probs
3: ─────────────────────────────────────╰●───────────╰●─────────H─╰SWAP───────┤ ╰Probs
* ``order`` :math:`\geq n-1`
Using the QFT class is recommended in this case. The AQFT operation here is
equivalent to QFT.
"""
def __init__(self, order, wires=None, id=None):
n_wires = len(wires)
if not isinstance(order, int):
warnings.warn(f"The order must be an integer. Using order = {round(order)}")
order = round(order)
if order >= n_wires - 1:
warnings.warn(
f"The order ({order}) is >= to the number of wires - 1 ({n_wires-1}). Using the QFT class is recommended in this case."
)
order = n_wires - 1
if order < 0:
raise ValueError("Order can not be less than 0")
if order == 0:
warnings.warn("order=0, applying Hadamard transform")
self.hyperparameters["order"] = order
super().__init__(wires=wires, id=id)
@property
def num_params(self):
return 0
[docs] @staticmethod
def compute_decomposition(wires, order): # pylint: disable=arguments-differ
r"""Representation of the operator as a product of other operators (static method).
.. math:: O = O_1 O_2 \dots O_n.
.. seealso:: :meth:`~.AQFT.decomposition`.
Args:
wires (Iterable, Wires): wires that the operator acts on
order (int): order of approximation
Returns:
list[Operator]: decomposition of the operator
**Example:**
>>> qml.AQFT.compute_decomposition((0, 1, 2), 3, order=1)
[Hadamard(wires=[0]), ControlledPhaseShift(1.5707963267948966, wires=[1, 0]), Hadamard(wires=[1]), ControlledPhaseShift(1.5707963267948966, wires=[2, 1]), Hadamard(wires=[2]), SWAP(wires=[0, 2])]
"""
n_wires = len(wires)
shifts = [2 * np.pi * 2**-i for i in range(2, n_wires + 1)]
decomp_ops = []
for i, wire in enumerate(wires):
decomp_ops.append(qml.Hadamard(wire))
counter = 0
for shift, control_wire in zip(shifts[: len(shifts) - i], wires[i + 1 :]):
if counter >= order:
break
op = qml.ControlledPhaseShift(shift, wires=[control_wire, wire])
decomp_ops.append(op)
counter = counter + 1
first_half_wires = wires[: n_wires // 2]
last_half_wires = wires[-(n_wires // 2) :]
for wire1, wire2 in zip(first_half_wires, reversed(last_half_wires)):
swap = qml.SWAP(wires=[wire1, wire2])
decomp_ops.append(swap)
return decomp_ops
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