# Source code for mitiq.zne.zne

```
# 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/>.
"""High-level zero-noise extrapolation tools."""
from typing import Callable, Optional, Union, List
from functools import wraps
from mitiq import Executor, Observable, QPROGRAM, QuantumResult
from mitiq.zne.inference import Factory, RichardsonFactory
from mitiq.zne.scaling import fold_gates_at_random
[docs]def execute_with_zne(
circuit: QPROGRAM,
executor: Union[Executor, Callable[[QPROGRAM], QuantumResult]],
observable: Optional[Observable] = None,
*,
factory: Optional[Factory] = None,
scale_noise: Callable[[QPROGRAM, float], QPROGRAM] = fold_gates_at_random,
num_to_average: int = 1,
) -> float:
"""Estimates the error-mitigated expectation value associated to the
input circuit, via the application of zero-noise extrapolation (ZNE).
Args:
circuit: The input circuit to execute with ZNE.
executor: A Mitiq executor that executes a circuit and returns the
unmitigated ``QuantumResult`` (e.g. an expectation value).
observable: Observable to compute the expectation value of. If
``None``, the ``executor`` must return an expectation value.
Otherwise, the ``QuantumResult`` returned by ``executor`` is used
to compute the expectation of the observable.
factory: ``Factory`` object that determines the zero-noise
extrapolation method.
scale_noise: The function for scaling the noise of a quantum circuit.
A list of built-in functions can be found in ``mitiq.zne.scaling``.
num_to_average: Number of times expectation values are computed by
the executor after each call to ``scale_noise``, then averaged.
Returns:
The expectation value estimated with ZNE.
"""
if not factory:
factory = RichardsonFactory(scale_factors=[1.0, 2.0, 3.0])
if not isinstance(factory, Factory):
raise TypeError(
f"Argument `factory` must be of type mitiq.factories.Factory "
f"but type(factory) is {type(factory)}."
)
if not callable(scale_noise):
raise TypeError("Argument `scale_noise` must be callable.")
if num_to_average < 1:
raise ValueError("Argument `num_to_average` must be a positive int.")
return factory.run(
circuit, executor, observable, scale_noise, int(num_to_average)
).reduce()
[docs]def mitigate_executor(
executor: Callable[[QPROGRAM], QuantumResult],
observable: Optional[Observable] = None,
*,
factory: Optional[Factory] = None,
scale_noise: Callable[[QPROGRAM, float], QPROGRAM] = fold_gates_at_random,
num_to_average: int = 1,
) -> Callable[[QPROGRAM], float]:
"""Returns a modified version of the input 'executor' which is
error-mitigated with zero-noise extrapolation (ZNE).
Args:
executor: A function that executes a circuit and returns the
unmitigated `QuantumResult` (e.g. an expectation value).
observable: Observable to compute the expectation value of. If None,
the `executor` must return an expectation value. Otherwise,
the `QuantumResult` returned by `executor` is used to compute the
expectation of the observable.
factory: Factory object determining the zero-noise extrapolation
method.
scale_noise: Function for scaling the noise of a quantum circuit.
num_to_average: Number of times expectation values are computed by
the executor after each call to scale_noise, then averaged.
Returns:
The error-mitigated version of the input executor.
"""
executor_obj = Executor(executor)
if not executor_obj.can_batch:
@wraps(executor)
def new_executor(circuit: QPROGRAM) -> float:
return execute_with_zne(
circuit,
executor,
observable,
factory=factory,
scale_noise=scale_noise,
num_to_average=num_to_average,
)
else:
@wraps(executor)
def new_executor(circuits: List[QPROGRAM]) -> List[float]:
return [
execute_with_zne(
circuit,
executor,
observable,
factory=factory,
scale_noise=scale_noise,
num_to_average=num_to_average,
)
for circuit in circuits
]
return new_executor
[docs]def zne_decorator(
observable: Optional[Observable] = None,
*,
factory: Optional[Factory] = None,
scale_noise: Callable[[QPROGRAM, float], QPROGRAM] = fold_gates_at_random,
num_to_average: int = 1,
) -> Callable[
[Callable[[QPROGRAM], QuantumResult]], Callable[[QPROGRAM], float]
]:
"""Decorator which adds an error-mitigation layer based on zero-noise
extrapolation (ZNE) to an executor function, i.e., a function which
executes a quantum circuit with an arbitrary backend and returns a
``QuantumResult`` (e.g. an expectation value).
Args:
observable: Observable to compute the expectation value of. If None,
the `executor` being decorated must return an expectation value.
Otherwise, the `QuantumResult` returned by the `executor` is used
to compute the expectation of the observable.
factory: Factory object determining the zero-noise extrapolation
method.
scale_noise: Function for scaling the noise of a quantum circuit.
num_to_average: Number of times expectation values are computed by
the executor after each call to scale_noise, then averaged.
Returns:
The error-mitigating decorator to be applied to an executor function.
"""
# Raise an error if the decorator is used without parenthesis
if callable(observable):
raise TypeError(
"Decorator must be used with parentheses (i.e., @zne_decorator()) "
"even if no explicit arguments are passed."
)
def decorator(
executor: Callable[[QPROGRAM], QuantumResult]
) -> Callable[[QPROGRAM], float]:
return mitigate_executor(
executor,
observable,
factory=factory,
scale_noise=scale_noise,
num_to_average=num_to_average,
)
return decorator
```