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.

FineDragCal¶

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

A calibration version of the fine DRAG experiment.

Analysis class reference

ErrorAmplificationAnalysis

Experiment options

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

Options

Defined in the class FineDragCal:
- target_angle (float)
  
  Default value: 3.141592653589793
  
  The target rotation angle of the gate being calibrated. This value is needed for the update rule.
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 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.
- gate (Gate)
  
  Default value: None
  
  This is the gate such as XGate() that will be in the circuits.
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.calibration_management.calibrations import Calibrations
from qiskit_experiments.calibration_management.basis_gate_library             import FixedFrequencyTransmon
from qiskit_experiments.library import FineDragCal

library = FixedFrequencyTransmon(default_values={"duration": 320, "amp": 0.030, "beta": 0.0})
cals = Calibrations.from_backend(backend, libraries=[library])

exp_cal = FineDragCal((0,),
                  calibrations=cals,
                  backend=backend,
                  schedule_name="sx",
                  cal_parameter_name="β",
                  auto_update=True,
                  )

cal_data = exp_cal.run().block_for_results()
display(cal_data.figure(0))
cal_data.analysis_results(dataframe=True)

../_images/qiskit_experiments.library.calibration.FineDragCal_1_0.png

	name	experiment	components	value	quality	backend	run_time	chisq
4ad9d555	@Parameters_ErrorAmplificationAnalysis	FineDragCal	[Q0]	CurveFitResult:\n - fitting method: least_squa...	good	PulseBackendV2	None	None
f5c67116	d_theta	FineDragCal	[Q0]	-0.0174+/-0.0013	good	PulseBackendV2	None	0.961285

See also

Initialization

See class FineDrag for details.

Note that this class implicitly assumes that the target angle of the gate is \(\pi\) as seen from the default experiment options.

Parameters:

physical_qubits (Sequence[int]) – Sequence containing the qubit for which to run the fine drag calibration.
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.

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 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.

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