iqm.benchmarks.randomized_benchmarking.randomized_benchmarking_common.plot_rb_decay

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iqm.benchmarks.randomized_benchmarking.randomized_benchmarking_common.plot_rb_decay#

iqm.benchmarks.randomized_benchmarking.randomized_benchmarking_common.plot_rb_decay(identifier: str, qubits_array: list[list[int]], dataset: Dataset, observations: dict[int, dict[str, Any]], violin: bool = True, scatter: bool = True, bars: bool = False, shade_stdev: bool = False, shade_meanerror: bool = False, logscale: bool = True, interleaved_gate: str | None = None, mrb_2q_density: float | dict[str, float] | None = None, mrb_2q_ensemble: dict[str, dict[str, float]] | None = None, is_eplg: bool = False) → tuple[str, Figure]#

Plot the fidelity decay and the fit to the model.

Parameters:

  • identifier (str) – the type of RB experiment

  • qubits_array (list[list[int]]) – Array of sets of qubits for which to plot decays

  • dataset (Dataset) – the dataset from the experiment

  • observations (dict[int, dict[str, Any]]) – the corresponding observations from the experiment

  • bars (bool) – Whether error bars are plotted or not.

  • violin (bool) – Whether violins are plotted or not.

  • scatter (bool) – Whether all individual points are plotted or not.

  • shade_stdev (bool) – Whether standard deviations are shaded or not.

  • shade_meanerror (bool) – Whether to shade standard deviations.

  • logscale (bool) – Whether x-axis uses logscale.

  • interleaved_gate (str | None) – The label or the interleaved gate.

  • mrb_2q_density (float | dict[str, float] | None) – Density of MRB 2Q gates.

  • mrb_2q_ensemble (dict[str, dict[str, float]] | None) – MRB ensemble of 2Q gates.

  • is_eplg (bool) – Whether the experiment is EPLG or not.

Returns:

The plot title and the figure

Return type:

tuple[str, Figure]

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