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.

FineXDrag¶

class FineXDrag(physical_qubits, backend=None)[source]¶

Class to fine characterize the DRAG parameter of an X gate.

Analysis class reference

ErrorAmplificationAnalysis

Experiment options

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

Options

Defined in the class FineXDrag:
- gate (Gate)
  
  Default value: Instance of XGate
  
  FineXDrag calibrates an XGate.
Defined in the class FineDrag:
- repetitions (List[int])
  
  Default value: [0, 1, 2, 3, 4, …]
  
  A list of the number of times that Rp - Rm gate sequence is repeated.
- schedule (ScheduleBlock)
  
  Default value: None
  
  The schedule for the plus rotation.
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 FineXDrag

exp = FineXDrag(physical_qubits=(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.FineXDrag_1_0.png

	name	experiment	components	value	quality	backend	run_time	chisq
a8516d63	@Parameters_ErrorAmplificationAnalysis	FineXDrag	[Q0]	CurveFitResult:\n - fitting method: least_squa...	good	PulseBackendV2	None	None
a86d0e64	d_theta	FineXDrag	[Q0]	-0.55655+/-0.00034	good	PulseBackendV2	None	1.514772

See also

Superclass qiskit_experiments.library.characterization.fine_drag.FineDrag

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 DRAG calibration experiment.

Returns:: A list of circuits with a variable number of gates. Each gate has the same pulse schedule.
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