ReadoutAngle#

class ReadoutAngle(physical_qubits, backend=None)[source]#

An experiment to measure the angle between ground and excited state IQ clusters.

Overview

Design and analyze experiments for estimating readout angle of the qubit. The readout angle is the average of two angles: the angle of the IQ cluster center of the ground state, and the angle of the IQ cluster center of the excited state.

Each experiment consists of the following steps:

  1. Circuits generation: two circuits, the first circuit measures the qubit in the ground state, the second circuit sets the qubit in the excited state and measures it. Measurements are in level 1 (kerneled).

  2. Backend execution: actually running the circuits on the device (or a simulator that supports level 1 measurements). The backend returns the cluster centers of the ground and excited states.

  3. Analysis of results: return the average of the angles of the two centers.

Analysis class reference

ReadoutAngleAnalysis

Experiment options

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

Options

  • 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.

Initialization

Initialize the readout angle experiment class

Parameters:

  • physical_qubits (Sequence[int]) – a single-element sequence containing the qubit whose readout angle is to be estimated

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

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]#

Return a list of experiment circuits

Returns:

The experiment circuits

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, 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)#

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.