acquire_rb_data

forest.benchmarking.randomized_benchmarking.acquire_rb_data(qc: pyquil.api._quantum_computer.QuantumComputer, experiments: Iterable[forest.benchmarking.observable_estimation.ObservablesExperiment], num_shots: int = 500, active_reset: bool = False, show_progress_bar: bool = False) → List[List[forest.benchmarking.observable_estimation.ExperimentResult]]

Runs each ObservablesExperiment and returns each group of resulting ExperimentResults

Parameters:

• qc – a quantum computer, e.g. QVM or QPU, that runs the experiments
• experiments – a list of Observables experiments
• num_shots – the number of shots to run each group of simultaneous ExperimentSettings
• active_reset – Boolean flag indicating whether experiments should begin with an active reset instruction (this can make the collection of experiments run a lot faster).
• show_progress_bar – displays a progress bar via tqdm if true.

Returns:

a list of ExperimentResults for each ObservablesExperiment