MultiStateDiscrimination¶

class MultiStateDiscrimination(physical_qubits, backend=None, n_states=None, schedules=None)[source]¶

An experiment that discriminates between the first \(n\) energy states.

Overview

The experiment creates \(n\) circuits that prepare, respectively, the energy states \(|0\rangle,\cdots,|n-1\rangle\). For, e.g., \(n=4\) the circuits are of the form

Circuit preparing \(|0\rangle\)

           ░ ┌─┐
       q: ─░─┤M├
           ░ └╥┘
    meas: ════╩═

...

Circuit preparing \(|3\rangle\)

          ┌───┐┌─────┐┌─────┐ ░ ┌─┐
       q: ┤ X ├┤ x12 ├┤ x23 ├─░─┤M├
          └───┘└─────┘└─────┘ ░ └╥┘
    meas: ═══════════════════════╩═

References

Qiskit Textbook

Analysis class reference

MultiStateDiscriminationAnalysis

Experiment options

These options can be set by the set_experiment_options() method.

Options

Defined in the class MultiStateDiscrimination:
- n_states (int)
  
  Default value: 2
  
  The number of states to discriminate.
- schedules (dict)
  
  Default value: None
  
  A dictionary of the schedules for the gates in the experiment. Each key is a gate name of the form xii+1 which should implement an x-rotation between level i and i+1.
Defined in the class BaseExperiment:
- max_circuits (Optional[int])
  
  Default value: None
  
  The maximum number of circuits per job when running an experiment on a backend.

Example

from qiskit_experiments.library.characterization import MultiStateDiscrimination

exp=MultiStateDiscrimination((0,), backend=backend)

exp_data=exp.run().block_for_results()
display(exp_data.figure(0))
exp_data.analysis_results(dataframe=True)

../_images/qiskit_experiments.library.characterization.MultiStateDiscrimination_1_0.png

	name	experiment	components	value	quality	backend	run_time
1539b112	discriminator_config	MultiStateDiscrimination	[Q0]	{'params': {'priors': None, 'reg_param': 0.0, ...	None	PulseBackendV2	None
880a1c1c	fidelity	MultiStateDiscrimination	[Q0]	0.989746	None	PulseBackendV2	None

Initialization

Setup an experiment to prepare different energy states on a given qubit.

Parameters:

physical_qubits (Sequence[int]) – A single-element sequence containing the qubit on which to run the experiment.
backend (Backend | None) – Optional, the backend to run the experiment on.
n_states (int | None) – The number of energy levels to prepare.
schedules (Dict[str, ScheduleBlock] | None) – The schedules of the x gates between neighboring energy levels.

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_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]¶

Create the circuits for the multi state discrimination experiment.

Returns:: A list of circuits preparing the different energy states.
Return type:: List[QuantumCircuit]

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