/
_typing.py
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/
_typing.py
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# Copyright (C) 2020 Unitary Fund
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
"""Defines input / output types for a quantum computer (simulator):
* SUPPORTED_PROGRAM_TYPES: All supported packages / circuits which Mitiq can
interface with,
* QPROGRAM: All supported packages / circuits which are installed in the
environment Mitiq is run in, and
* QuantumResult: An object returned by a quantum computer (simulator) running
a quantum program from which expectation values to be mitigated can be
computed. Note this includes expectation values themselves.
"""
from dataclasses import dataclass
from typing import cast, Iterable, List, Optional, Tuple, Union
import numpy as np
import numpy.typing as npt
from cirq import Circuit as _Circuit
# Supported quantum programs.
SUPPORTED_PROGRAM_TYPES = {
"cirq": "Circuit",
"pyquil": "Program",
"qiskit": "QuantumCircuit",
"braket": "Circuit",
"pennylane": "QuantumTape",
}
try:
from pyquil import Program as _Program
except ImportError: # pragma: no cover
_Program = _Circuit # type: ignore
try:
from qiskit import QuantumCircuit as _QuantumCircuit
except ImportError: # pragma: no cover
_QuantumCircuit = _Circuit
try:
from braket.circuits import Circuit as _BKCircuit
except ImportError: # pragma: no cover
_BKCircuit = _Circuit
try:
from pennylane.tape import QuantumTape as _QuantumTape
except ImportError: # pragma: no cover
_QuantumTape = _Circuit
# Supported + installed quantum programs.
QPROGRAM = Union[_Circuit, _Program, _QuantumCircuit, _BKCircuit, _QuantumTape]
# Define MeasurementResult, a result obtained by measuring qubits on a quantum
# computer.
Bitstring = List[int]
@dataclass
class MeasurementResult:
"""Bitstrings sampled from a quantum computer."""
result: List[Bitstring]
qubit_indices: Optional[Tuple[int, ...]] = None
def __post_init__(self) -> None:
if not set(b for bits in self.result for b in bits).issubset({0, 1}):
raise ValueError(
"MeasurementResult contains elements which are not (0, 1)."
)
self._bitstrings = np.array(self.result)
if isinstance(self.result, np.ndarray):
self.result = cast(List[Bitstring], self.result.tolist())
if not self.qubit_indices:
self.qubit_indices = tuple(range(self.nqubits))
else:
if len(self.qubit_indices) != self.nqubits:
raise ValueError(
f"MeasurementResult has {self.nqubits} qubit(s) but there "
f"are {len(self.qubit_indices)} `qubit_indices`."
)
self._measurements = dict(zip(self.qubit_indices, self._bitstrings.T))
@property
def shots(self) -> int:
return self._bitstrings.shape[0]
@property
def nqubits(self) -> int:
return (
self._bitstrings.shape[1]
if len(self._bitstrings.shape) >= 2
else 0
)
@property
def asarray(self) -> npt.NDArray[np.int64]:
return self._bitstrings
def __getitem__(self, indices: List[int]) -> npt.NDArray[np.int64]:
return np.array([self._measurements[i] for i in indices]).T
def __iter__(self) -> Iterable[Bitstring]:
yield from self.result
# An `executor` function inputs a quantum program and outputs an object from
# which expectation values can be computed. Explicitly, this object can be one
# of the following types:
QuantumResult = Union[
float, # The expectation value itself.
MeasurementResult, # Sampled bitstrings.
np.ndarray, # Density matrix.
# TODO: Support the following:
# Sequence[np.ndarray], # Wavefunctions sampled via quantum trajectories.
]