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IBM Quantum Platform

qiskit_noise_learning.analysis.CurveFitObservables

class qiskit_noise_learning.analysis.CurveFitObservables

GitHub

Bases: AnalysisStage

Fit observable data to exponential decays of the form a * f**fragment_depth, and average any remaining observables over randomizations.

This stage will curve fit data for any unbound paths in fit.paths. If fit.paths is None, any path in the data with multiple fragment depths will be curve fit. In both cases, any remaining paths will be averaged.

Each curve-fit row carries the following per-row metadata, which the averaged rows do not have:

  • "spam_fidelity", "spam_fidelity_std": the fitted prefactor aa and its 1-sigma uncertainty.
  • "chi_squared": the raw chi-squared of the fit.
  • "reduced_chi_squared": the raw chi-squared divided by the degrees of freedom, that is the number of fragment depths minus the two fit parameters, or nan if there are none.

__init__

__init__()


Methods

Column 1
Column 2
__init__()
run(fit)Run this stage, returning a new Fit with the output level populated.

Attributes

Column 1
Column 2
input_levelThe data level this stage reads.
output_levelThe data level this stage writes.

input_level

The data level this stage reads.

output_level

The data level this stage writes.

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