FineSXAmplitude#

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

A fine amplitude experiment with all the options set for the \(\pi/2\)-rotation.

Overview

FineSXAmplitude is a subclass of FineAmplitude and is used to set the appropriate values for the default options.

Analysis class reference

FineAmplitudeAnalysis

Experiment options

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

Options

Defined in the class FineSXAmplitude:
- gate (Gate)
  
  Default value: Instance of SXGate
  
  FineSXAmplitude calibrates an SXGate.
- add_cal_circuits (bool)
  
  Default value: False
  
  If set to True then two circuits to calibrate 0 and 1 points will be added. This option is set to False by default for FineSXAmplitude since the amplitude calibration can be achieved with two SX gates and this is included in the repetitions.
- 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.
Defined in the class FineAmplitude:
- normalization (bool)
  
  Default value: True
  
  If set to True the DataProcessor will normalized the measured signal to the interval [0, 1]. Defaults to True.
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

Superclass qiskit_experiments.library.characterization.fine_amplitude.FineAmplitude

Initialization

Initialize the experiment.

Attributes

analysis: BaseAnalysis#: 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()#

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.

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, 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