ParallelExperiment

class ParallelExperiment(experiments, backend=None, flatten_results=True, analysis=None, experiment_type=None)[source]

Combine multiple experiments into a parallel experiment.

Parallel experiments combine individual experiments on disjoint subsets of qubits into a single composite experiment on the union of those qubits. The component experiment circuits are combined to run in parallel on the respective qubits.

Analysis of parallel experiments is performed using the CompositeAnalysis class which handles marginalizing the composite experiment circuit data into individual child ExperimentData containers for each component experiment which are then analyzed using the corresponding analysis class for that component experiment.

See CompositeAnalysis documentation for additional information.

Initialize the analysis object.

Parameters:
  • experiments (List[BaseExperiment]) – a list of experiments.

  • backend (Backend | None) – Optional, the backend to run the experiment on.

  • flatten_results (bool) – If True flatten all component experiment results into a single ExperimentData container, including nested composite experiments. If False save each component experiment results as a separate child ExperimentData container. This kwarg is ignored if the analysis kwarg is used.

  • analysis (CompositeAnalysis | None) – Optional, the composite analysis class to use. If not provided this will be initialized automatically from the supplied experiments.

Attributes

analysis

Return the analysis instance for the experiment

backend

Return the backend for the experiment

experiment_options

Return the options for the experiment.

experiment_type

Return experiment type.

num_experiments

Return the number of sub experiments

num_qubits

Return the number of qubits for the experiment.

physical_qubits

Return the device qubits for the experiment.

run_options

Return options values for the experiment run() method.

transpile_options

Return the transpiler options for the run() method.

Methods

circuits()[source]

Return a list of experiment circuits.

Returns:

A list of QuantumCircuit.

Note

These circuits should be on qubits [0, .., N-1] for an N-qubit experiment. The circuits mapped to physical qubits are obtained via the internal _transpiled_circuits() method.

component_experiment(index=None)

Return the component Experiment object.

Parameters:

index (int) – Experiment index, or None if all experiments are to be returned.

Returns:

The component experiment(s).

Return type:

BaseExperiment

config()

Return the config dataclass for this experiment

Return type:

ExperimentConfig

copy()

Return a copy of the experiment

Return type:

BaseExperiment

classmethod from_config(config)

Initialize an experiment from experiment config

Return type:

BaseExperiment

job_info(backend=None)

Get information about job distribution for the experiment on a specific backend.

Parameters:

backend (Backend) – Optional, the backend for which to get job distribution information. If not specified, the experiment must already have a set backend.

Returns:

A dictionary containing information about job distribution.

  • ”Total number of circuits in the experiment”: Total number of circuits in the experiment.

  • ”Maximum number of circuits per job”: Maximum number of circuits in one job based on backend and experiment settings.

  • ”Total number of jobs”: Number of jobs needed to run this experiment on the currently set backend.

Return type:

dict

Raises:

QiskitError – if backend is not specified.

run(backend=None, sampler=None, analysis='default', timeout=None, backend_run=None, **run_options)

Run an experiment and perform analysis.

Parameters:
  • backend (Backend | None) – Optional, the backend to run on. Will override existing backend settings.

  • sampler (BaseSamplerV2 | None) – Optional, the sampler to run the experiment on. If None then a sampler will be invoked from previously set backend

  • analysis (BaseAnalysis | None) – Optional, a custom analysis instance to use for performing analysis. If None analysis will not be run. If "default" the experiments analysis() instance will be used if it contains one.

  • timeout (float | None) – Time to wait for experiment jobs to finish running before cancelling.

  • backend_run (bool | None) – Use backend run (temp option for testing)

  • run_options – backend runtime options used for circuit execution.

Returns:

The experiment data object.

Raises:

QiskitError – If experiment is run with an incompatible existing ExperimentData container.

Return type:

ExperimentData

set_experiment_options(**fields)

Set the experiment options.

Parameters:

fields – The fields to update the options

Raises:

AttributeError – If the field passed in is not a supported options

set_run_options(**fields)

Set options values for the experiment run() method.

Parameters:

fields – The fields to update the options

See also

The Setting options for your experiment guide for code example.

set_transpile_options(**fields)

Set the transpiler options for run() method.

Parameters:

fields – The fields to update the options

Raises:

QiskitError – If initial_layout is one of the fields.

See also

The Setting options for your experiment guide for code example.