CompositeExperiment#

class CompositeExperiment(experiments, physical_qubits, backend=None, experiment_type=None, flatten_results=None, analysis=None)[source]#

Composite Experiment base class

Initialize the composite experiment object.

Parameters:

experiments (List[BaseExperiment]) – a list of experiment objects.
physical_qubits (Sequence[int]) – list of physical qubits for the experiment.
backend (Backend | None) – Optional, the backend to run the experiment on.
experiment_type (str | None) – Optional, composite experiment subclass name.
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.

Raises:

QiskitError – If the provided analysis class is not a CompositeAnalysis instance.

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

abstract 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)[source]#

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()[source]#

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, analysis='default', timeout=None, **run_options)#

Run an experiment and perform analysis.

Parameters:

backend (Backend | None) – Optional, the backend to run the experiment on. This will override any currently set backends for the single execution.
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.
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)[source]#

Set options values for the experiment run() method.

Parameters:: fields – The fields to update the options