Source code for qiskit_experiments.library.characterization.analysis.t2ramsey_analysis

# 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.
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"""
T2Ramsey Experiment class.
"""
from typing import Union
import qiskit_experiments.curve_analysis as curve
from qiskit_experiments.framework import Options


[docs] class T2RamseyAnalysis(curve.DampedOscillationAnalysis): """T2 Ramsey result analysis class.""" @classmethod def _default_options(cls) -> Options: """Default analysis options.""" options = super()._default_options() options.plotter.set_figure_options( xlabel="Delay", ylabel="P(1)", xval_unit="s", ) options.result_parameters = [ curve.ParameterRepr("freq", "Frequency", "Hz"), curve.ParameterRepr("tau", "T2star", "s"), ] return options def _evaluate_quality(self, fit_data: curve.CurveFitResult) -> Union[str, None]: """Algorithmic criteria for whether the fit is good or bad. A good fit has: - a reduced chi-squared lower than three and greater than zero - relative error of amp is less than 10 percent - relative error of tau is less than 10 percent - relative error of freq is less than 10 percent """ amp = fit_data.ufloat_params["amp"] tau = fit_data.ufloat_params["tau"] freq = fit_data.ufloat_params["freq"] criteria = [ 0 < fit_data.reduced_chisq < 3, curve.utils.is_error_not_significant(amp, fraction=0.1), curve.utils.is_error_not_significant(tau, fraction=0.1), curve.utils.is_error_not_significant(freq, fraction=0.1), ] if all(criteria): return "good" return "bad"