Note

This is the documentation for the current state of the development branch of Qiskit Experiments. The documentation or APIs here can change prior to being released.

FineSXAmplitudeCal¶

class FineSXAmplitudeCal(physical_qubits, calibrations, schedule_name, backend=None, cal_parameter_name='amp', auto_update=True)[source]¶

A calibration experiment to calibrate the amplitude of the SX schedule.

Analysis class reference

FineAmplitudeAnalysis

Experiment options

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

Options

Defined in the class FineSXAmplitudeCal:
- repetitions (List[int])
  
  Default value: [0, 1, 2, 3, 5, …]
  
  By default the repetitions take on odd numbers for \(\pi/2\) target angles as this ideally prepares states on the equator of the Bloch sphere. Note that the repetitions include two repetitions which plays the same role as including a circuit with an X gate.
- target_angle (float)
  
  Default value: 1.5707963267948966
  
  The target angle per gate.
Defined in the class BaseCalibrationExperiment:
- result_index (int)
  
  Default value: -1
  
  The index of the result from which to update the calibrations.
- group (str)
  
  Default value: "default"
  
  The calibration group to which the parameter belongs. This will default to the value “default”.
Defined in the class FineAmplitude:
- gate (Gate)
  
  Default value: None
  
  This is a gate class such as XGate, so that one can obtain a gate by doing options.gate().
- normalization (bool)
  
  Default value: True
  
  If set to True the DataProcessor will normalized the measured signal to the interval [0, 1]. Defaults to True.
- add_cal_circuits (bool)
  
  Default value: False
  
  If set to True then two circuits to calibrate 0 and 1 points will be added. These circuits are often needed to properly calibrate the amplitude of the ping-pong oscillation that encodes the errors. This helps account for state preparation and measurement errors.
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.

See also

Initialization

See class FineAmplitude for details.

Parameters:

physical_qubits (Sequence[int]) – Sequence containing the qubit(s) for which to run the fine amplitude calibration. This can be a pair of qubits which correspond to control and target qubit.
calibrations (Calibrations) – The calibrations instance with the schedules.
schedule_name (str) – The name of the schedule to calibrate.
backend (Backend | None) – Optional, the backend to run the experiment on.
cal_parameter_name (str | None) – The name of the parameter in the schedule to update.
auto_update (bool) – Whether or not to automatically update the calibrations. By default this variable is set to True.
gate – The gate to repeat in the quantum circuit. If this argument is None (the default), then the gate is built from the schedule name.
measurement_qubits – The qubits in the given physical qubits that need to be measured.

Attributes

analysis: BaseAnalysis¶: Return the analysis instance for the experiment.

Note

Analysis instance set to calibration experiment is implicitly patched to run calibration updater to update the parameters in the calibration table.

backend¶: Return the backend for the experiment

calibrations¶: Return the calibrations.

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()¶

Create the circuits for the fine amplitude calibration experiment.

Returns:: A list of circuits with a variable number of gates.
Raises:: CalibrationError – If the analysis options do not contain the angle_per_gate.
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

enable_restless(rep_delay=None, override_processor_by_restless=True, suppress_t1_error=False)¶

Enables a restless experiment by setting the restless run options and the restless data processor.

Deprecated since version 0.8: The method qiskit_experiments.framework.restless_mixin.RestlessMixin.enable_restless() is deprecated as of qiskit-experiments 0.8. It will be removed no earlier than 3 months after the release date. Support for restless experiments has been deprecated.

Parameters:

rep_delay (float | None) – The repetition delay. This is the delay between a measurement and the subsequent quantum circuit. Since the backends have dynamic repetition rates, the repetition delay can be set to a small value which is required for restless experiments. Typical values are 1 us or less.
override_processor_by_restless (bool) – If False, a data processor that is specified in the analysis options of the experiment is not overridden by the restless data processor. The default is True.
suppress_t1_error (bool) – If True, the default is False, then no error will be raised when rep_delay is larger than the T1 times of the qubits. Instead, a warning will be logged as restless measurements may have a large amount of noise.

Raises:

DataProcessorError – If the attribute rep_delay_range is not defined for the backend.
DataProcessorError – If a data processor has already been set but override_processor_by_restless is True.
DataProcessorError – If the experiment analysis does not have the data_processor option.
DataProcessorError – If the rep_delay is equal to or greater than the T1 time of one of the physical qubits in the experiment and the flag ignore_t1_check is False.

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