iqm.benchmarks.compressive_gst.gst_analysis

iqm.benchmarks.compressive_gst.gst_analysis#

Data analysis code for compressive gate set tomography

Functions

bootstrap_errors(dataset, y, K, X, E, rho, ...)

Resamples circuit outcomes a number of times and computes GST estimates for each repetition All results are then returned in order to compute bootstrap-error bars for GST estimates.

dataset_counts_to_mgst_format(dataset, ...)

Turns the dictionary of outcomes obtained from qiskit backend

generate_gate_results(dataset, qubit_layout, ...)

Produces all result tables for arbitrary Kraus rank estimates

generate_non_gate_results(df_o[, ...])

Creates error bars (if bootstrapping was used) and formats results for non-gate errors.

generate_unit_rank_gate_results(dataset, ...)

Produces all result tables for Kraus rank 1 estimates

mgst_analysis(run)

Analysis function for compressive GST

pandas_results_to_observations(dataset, ...)

Converts high level GST results from a pandas Dataframe to a simple observation dictionary

process_bootstrap_samples(y_sampled, attrs, ...)

Process a single bootstrap sample for Gate Set Tomography.

process_layout(args)

Process a single qubit layout for Gate Set Tomography analysis.

process_plots(dataset, qubit_layout, ...)

Process and generate all plots for a single qubit layout.

run_mGST_wrapper(dataset, y)

Wrapper function for mGST algorithm execution which prepares an initialization and sets the alg.