# Copyright (c) 2024, Jiun-Cheng Jiang. All rights reserved.
#
# 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.
import numpy as np
import torch
[docs]
def qml_solver(x: torch.Tensor, theta: torch.Tensor, reps: int, **kwargs):
"""
Single-qubit data reuploading circuit using PennyLane.
Args
----
x : torch.Tensor
shape: (batch_size, in_dim)
theta : torch.Tensor
shape: (reps, 2)
reps : int
qml_device : str
default: "default.qubit"
"""
import pennylane as qml # type: ignore
qml_device: str = kwargs.get("qml_device", "default.qubit")
dev = qml.device(qml_device, wires=1)
@qml.qnode(dev, interface="torch")
def circuit(x: torch.Tensor, theta: torch.Tensor):
"""
Args
----
x : torch.Tensor
shape: (batch_size, in_dim)
theta : torch.Tensor
shape: (reps, 2)
"""
qml.RY(np.pi / 2, wires=0)
for l in range(reps):
qml.RZ(theta[l, 0], wires=0)
qml.RY(theta[l, 1], wires=0)
qml.RZ(x, wires=0)
qml.RZ(theta[reps, 0], wires=0)
qml.RY(theta[reps, 1], wires=0)
return qml.expval(qml.PauliZ(0))
return circuit(x, theta)