Source code for qiskit_experiments.library.calibration.half_angle_cal
# This code is part of Qiskit.
#
# (C) Copyright IBM 2021.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any modifications or derivative works of this code must retain this
# copyright notice, and modified files need to carry a notice indicating
# that they have been altered from the originals.
"""Half angle calibration."""
from typing import Dict, Optional, Sequence
import numpy as np
from qiskit.circuit import QuantumCircuit
from qiskit.providers.backend import Backend
from qiskit_experiments.framework import ExperimentData
from qiskit_experiments.calibration_management import (
BaseCalibrationExperiment,
Calibrations,
)
from qiskit_experiments.library.characterization import HalfAngle
from qiskit_experiments.calibration_management.update_library import BaseUpdater
from qiskit_experiments.warnings import qubit_deprecate
[docs]class HalfAngleCal(BaseCalibrationExperiment, HalfAngle):
"""Calibration version of the half-angle experiment."""
@qubit_deprecate()
def __init__(
self,
physical_qubits: Sequence[int],
calibrations: Calibrations,
backend: Optional[Backend] = None,
schedule_name: str = "sx",
cal_parameter_name: Optional[str] = "amp",
auto_update: bool = True,
):
"""see class :class:`HalfAngle` for details.
Args:
physical_qubits: Sequence containing the qubit for which to run the
half-angle calibration.
calibrations: The calibrations instance with the schedules.
backend: Optional, the backend to run the experiment on.
schedule_name: The name of the schedule to calibrate which defaults to sx.
cal_parameter_name: The name of the parameter in the schedule to update. This will
default to amp since the complex amplitude contains the phase of the pulse.
auto_update: Whether or not to automatically update the calibrations. By
default this variable is set to True.
"""
super().__init__(
calibrations,
physical_qubits,
backend=backend,
schedule_name=schedule_name,
cal_parameter_name=cal_parameter_name,
auto_update=auto_update,
)
def _metadata(self) -> Dict[str, any]:
"""Add metadata to the experiment data making it more self contained.
The following keys are added to the experiment's metadata:
cal_param_value: The value of the pulse amplitude. This value together with
the fit result will be used to find the new value of the pulse amplitude.
cal_param_name: The name of the parameter in the calibrations.
cal_schedule: The name of the schedule in the calibrations.
cal_group: The calibration group to which the parameter belongs.
"""
metadata = super()._metadata()
metadata["cal_param_value"] = self._cals.get_parameter_value(
self._param_name,
self._physical_qubits,
self._sched_name,
group=self.experiment_options.group,
)
return metadata
def _attach_calibrations(self, circuit: QuantumCircuit):
"""Adds the calibrations to the transpiled circuits."""
for gate in ["y", "sx"]:
schedule = self._cals.get_schedule(gate, self.physical_qubits)
circuit.add_calibration(gate, self.physical_qubits, schedule)
[docs] def update_calibrations(self, experiment_data: ExperimentData):
r"""Update the value of the parameter in the calibrations.
The parameter that is updated is the phase of the sx pulse. This phase is contained
in the complex amplitude of the pulse. The update rule for the half angle calibration is
therefore:
..math::
A \to A \cdot e^{-i{\rm d}\theta_\text{hac}/2}
where :math:`A` is the complex amplitude of the sx pulse which has an angle which might be
different from the angle of the x pulse due to the non-linearity in the mixer's skew. The
angle :math:`{\rm d}\theta_\text{hac}` is the angle deviation measured through the error
amplifying pulse sequence.
Args:
experiment_data: The experiment data from which to extract the measured over/under
rotation used to adjust the amplitude.
"""
result_index = self.experiment_options.result_index
group = experiment_data.metadata["cal_group"]
prev_amp = experiment_data.metadata["cal_param_value"]
d_theta = BaseUpdater.get_value(experiment_data, "d_hac", result_index)
new_amp = prev_amp * np.exp(-1.0j * d_theta / 2)
BaseUpdater.add_parameter_value(
self._cals,
experiment_data,
new_amp,
self._param_name,
self._sched_name,
group,
)