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# Licensed under the Apache License, Version 2.0 (the "License"). You
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from typing import Any, List, Sequence
import numpy as np
from braket.circuits.operator import Operator
[docs]class QuantumOperator(Operator):
"""A quantum operator is the definition of a quantum operation for a quantum device."""
def __init__(self, qubit_count: int, ascii_symbols: Sequence[str]):
"""
Args:
qubit_count (int): Number of qubits this quantum operator interacts with.
ascii_symbols (Sequence[str]): ASCII string symbols for the quantum operator.
These are used when printing a diagram of circuits.
Length must be the same as `qubit_count`, and index ordering is expected
to correlate with target ordering on the instruction.
For instance, if CNOT instruction has the control qubit on the first index and
target qubit on the second index. Then ASCII symbols would have ["C", "X"] to
correlate a symbol with that index.
Raises:
ValueError: `qubit_count` is less than 1, `ascii_symbols` are None, or
`ascii_symbols` length != `qubit_count`
"""
if qubit_count < 1:
raise ValueError(f"qubit_count, {qubit_count}, must be greater than zero")
self._qubit_count = qubit_count
if ascii_symbols is None:
raise ValueError("ascii_symbols must not be None")
if len(ascii_symbols) != qubit_count:
msg = f"ascii_symbols, {ascii_symbols}, length must equal qubit_count, {qubit_count}"
raise ValueError(msg)
self._ascii_symbols = tuple(ascii_symbols)
@property
def qubit_count(self) -> int:
"""int: Returns number of qubits this quantum operator interacts with."""
return self._qubit_count
@property
def ascii_symbols(self) -> List[str]:
"""List[str]: Returns the ascii symbols for the quantum operator."""
return self._ascii_symbols
@property
def name(self) -> str:
"""
Returns the name of the quantum operator
Returns:
The name of the quantum operator as a string
"""
return self.__class__.__name__
[docs] def to_ir(self, *args, **kwargs) -> Any:
"""Returns IR representation of quantum operator
Args:
*args: Positional arguments
**kwargs: Keyword arguments
"""
raise NotImplementedError("to_ir has not been implemented yet.")
[docs] def to_matrix(self, *args, **kwargs) -> Any:
"""Returns a matrix representation of the quantum operator
Returns:
np.ndarray: A matrix representation of the quantum operator
"""
raise NotImplementedError("to_matrix has not been implemented yet.")
[docs] def matrix_equivalence(self, other):
"""
Whether the matrix form of two gates are equivalent
Args:
other (Gate): Gate instance to compare this quantum operator to
Returns:
bool: If matrix forms of this quantum operator and the other quantum operator
are equivalent
"""
if not isinstance(other, QuantumOperator):
return NotImplemented
try:
return np.allclose(self.to_matrix(), other.to_matrix())
except ValueError:
return False
def __repr__(self):
return f"{self.name}('qubit_count': {self.qubit_count})"