#
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# Copyright © 2032-2024 QPerfect. 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.
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import mimiqcircuits.operations.gates.gate as mcg
from numpy import ndarray
import symengine as se
import sympy as sp
import numpy as np
[docs]
class GateCustom(mcg.Gate):
"""One or Two qubit Custom gates.
Examples:
>>> from mimiqcircuits import Circuit, GateCustom
>>> import numpy as np
>>> matrix = np.array([[1, 0, 0, 0],[0, 1, 0, 0],[0, 0, 0, -1j],[0, 0, 1j, 0]])
>>> c = Circuit()
>>> c.push(GateCustom(matrix), 0, 1)
2-qubit circuit with 1 instructions:
└── Custom([1.0 + 0.0*I, 0.0 + 0.0*I, 0.0 + 0.0*I, 0.0 + 0.0*I]...[0.0 + 0.0*I, 0.0 + 0.0*I, 0.0 + 1.0*I, 0.0 + 0.0*I]) @ q[0,1]
<BLANKLINE>
"""
_name = "Custom"
_num_qubits = None
_qregsizes = None
def __init__(self, matrix):
super().__init__()
if isinstance(matrix, ndarray):
mat = se.Matrix(matrix.tolist())
elif isinstance(matrix, se.Matrix):
mat = matrix
else:
raise TypeError(
f"{type(matrix)} not supported in GateCustom, use symengine.Matrix or numpy.ndarray."
)
if mat.rows != mat.cols:
raise ValueError("Matrix is not square")
tolerance = 1e-8
if any(
isinstance(mat[i, j], (se.Symbol, str))
for i in range(mat.rows)
for j in range(mat.cols)
):
pass
else:
if not self.is_unitary(mat, tol=tolerance):
raise ValueError("Matrix is not unitary")
num_qubits = (mat.rows >> 2) + 1
if mat.rows != 2**num_qubits:
raise ValueError("Wrong number of the rows for the matrix")
self.matrix = mat
self._num_qubits = num_qubits
self._qregsizes = [
num_qubits,
]
@property
def _matrix(self):
return self.matrix
@property
def num_qubits(self):
return self._num_qubits
[docs]
def inverse(self):
return GateCustom(self.matrix.inv())
[docs]
@staticmethod
def is_unitary(matrix, tol=1e-8):
conjugate_transpose = matrix.transpose().conjugate()
product = matrix * conjugate_transpose
identity_matrix = se.eye(matrix.rows)
return all(
abs(product[i, j] - identity_matrix[i, j]) < tol
for i in range(matrix.rows)
for j in range(matrix.cols)
)
def __repr__(self):
return self.pretty_print()
def __str__(self):
return f"{self._name}({se.Matrix(self.matrix).tolist()[0]}...{se.Matrix(self.matrix).tolist()[-1]})"
[docs]
def pretty_print(self):
if isinstance(self.matrix, se.Matrix):
U = np.array(self.matrix.tolist(), dtype=object)
else:
U = np.array(self.matrix, dtype=object)
result = f"{self._num_qubits}-qubit GateCustom:\n"
rows, cols = U.shape
for i in range(rows):
if i < rows - 1:
result += "├── "
else:
result += "└── "
result += " ".join(map(str, U[i, :]))
if i < rows - 1:
result += "\n"
return result
[docs]
def evaluate(self, d):
sympy_matrix = sp.Matrix(self.matrix)
matrix = sympy_matrix.applyfunc(
lambda entry: entry.subs(d)
if not isinstance(entry, (float, int))
else entry
)
evaluated_matrix = se.Matrix(matrix.tolist())
return GateCustom(evaluated_matrix)
__all__ = ["Custom"]
