StarkP1SpectAnalysis#

class StarkP1SpectAnalysis[source]#

Analysis class for StarkP1Spectroscopy.

Overview

The P1 landscape is hardly predictable because of the random appearance of lossy TLS notches, and hence this analysis doesn’t provide any generic mathematical model to fit the measurement data. A developer may subclass this to conduct own analysis. The StarkP1SpectAnalysis._run_spect_analysis() is a hook method where you can define a custom analysis protocol.

By default, this analysis just visualizes the measured P1 values against Stark tone amplitudes. The tone amplitudes can be converted into the amount of Stark shift when the calibrated coefficients are provided in the analysis option, or the calibration experiment results are available in the result database.

Analysis options

These are the keyword arguments of the run() method.

Options

  • Defined in the class StarkP1SpectAnalysis:

    • plotter (Plotter)

      Default value: Instance of CurvePlotter
      Plotter to visualize P1 landscape.

    • data_processor (DataProcessor)

      Default value: Instance of DataProcessor
      Data processor to compute P1 value.

    • stark_coefficients (Union[Dict, str])

      Default value: None
      Dictionary of Stark shift coefficients to convert tone amplitudes into amount of Stark shift. This dictionary must include all keys defined in StarkP1SpectAnalysis.stark_coefficients_names, which are calibrated with StarkRamseyXYAmpScan. Alternatively, it searches for these coefficients in the result database when “latest” is set. This requires having the experiment service set in the experiment data to analyze.

    • x_key (str)

      Default value: "xval"
      Key of the circuit metadata to represent x value.

  • Defined in the class BaseAnalysis:

    • figure_names (str or List[str])

      Default value: None
      Identifier of figures that appear in the experiment data to sort figures by name.

See also

qiskit_experiments.library.driven_freq_tuning.StarkRamseyXYAmpScan

Initialization

Initialize the analysis object.

Attributes

options#

Return the analysis options for run() method.

plotter#

Curve plotter instance.

Methods

config()#

Return the config dataclass for this analysis

Return type:

AnalysisConfig

copy()#

Return a copy of the analysis

Return type:

BaseAnalysis

classmethod from_config(config)#

Initialize an analysis class from analysis config

Return type:

BaseAnalysis

run(experiment_data, replace_results=False, **options)#

Run analysis and update ExperimentData with analysis result.

Parameters:

  • experiment_data (ExperimentData) – the experiment data to analyze.

  • replace_results (bool) – If True clear any existing analysis results, figures, and artifacts in the experiment data and replace with new results. See note for additional information.

  • options – additional analysis options. See class documentation for supported options.

Returns:

An experiment data object containing analysis results, figures, and artifacts.

Raises:

QiskitError – If experiment_data container is not valid for analysis.

Return type:

ExperimentData

Note

Updating Results

If analysis is run with replace_results=True then any analysis results, figures, and artifacts in the experiment data will be cleared and replaced with the new analysis results. Saving this experiment data will replace any previously saved data in a database service using the same experiment ID.

If analysis is run with replace_results=False and the experiment data being analyzed has already been saved to a database service, or already contains analysis results or figures, a copy with a unique experiment ID will be returned containing only the new analysis results and figures. This data can then be saved as its own experiment to a database service.

set_options(**fields)#

Set the analysis options for run() method.

Parameters:

fields – The fields to update the options