RoughDrag#

class RoughDrag(physical_qubits, schedule, betas=None, backend=None)[source]#

An experiment that scans the DRAG parameter to find the optimal value.

Overview

A Derivative Removal by Adiabatic Gate (DRAG) pulse is designed to minimize phase errors and leakage resulting from the presence of a neighbouring transition. DRAG is a standard pulse with an additional derivative component. The optimal value of the DRAG parameter, \(\beta\), is chosen to primarily minimize phase errors resulting from the AC Stark shift and potentially leakage errors. The DRAG pulse is

\[f(t) = \Omega(t) + 1j \beta d/dt \Omega(t)\]

Here, \(\Omega\) is the envelop of the in-phase component of the pulse and \(\beta\) is the strength of the quadrature which we refer to as the DRAG parameter and seek to calibrate in this experiment. The DRAG calibration will run several series of circuits. In a given circuit a Rp(β) - Rm(β) block is repeated \(N\) times. Here, Rp is a rotation with a positive angle and Rm is the same rotation with a native angle and is implemented by the gate sequence Rz(π) - Rp(β) - Rz(π) where the Z rotations are virtual. As example the circuit of a single repetition, i.e. \(N=1\), is shown below.

           ┌───────┐┌───────┐┌───────┐┌───────┐ ░ ┌─┐
      q_0: ┤ Rp(β) ├┤ Rz(π) ├┤ Rp(β) ├┤ Rz(π) ├─░─┤M├
           └───────┘└───────┘└───────┘└───────┘ ░ └╥┘
measure: 1/════════════════════════════════════════╩═
                                                   0

The parameter β is scanned to find the value that minimizes the unwanted Z-rotation. Note that the analysis class requires this experiment to run with three repetition numbers.

References

[1] J. M. Gambetta, F. Motzoi, S. T. Merkel, F. K. Wilhelm, Analytic control methods for high fidelity unitary operations in a weakly nonlinear oscillator, Phys. Rev. A 83, 012308 (2011), doi: 10.1103/PhysRevA.83.012308 (open)

[2] F. Motzoi, J. M. Gambetta, P. Rebentrost, F. K. Wilhelm, Simple pulses for elimination of leakage in weakly nonlinear qubits, Phys. Rev. Lett. 103, 110501 (2009), doi: 10.1103/PhysRevLett.103.110501 (open)

[3] Zijun Chen, Julian Kelly, Chris Quintana, R. Barends, B. Campbell, Yu Chen, B. Chiaro, A. Dunsworth, A. Fowler, E. Lucero, E. Jeffrey, A. Megrant, J. Mutus, M. Neeley, C. Neill, P. J. J. O’Malley, P. Roushan, D. Sank, A. Vainsencher, J. Wenner, T. C. White, A. N. Korotkov, John M. Martinis, Measuring and Suppressing Quantum State Leakage in a Superconducting Qubit, Phys. Rev. Lett. 116, 020501 (2016), doi: 10.1103/PhysRevLett.116.020501 (open)

User manual

Calibrating the value of the DRAG coefficient

Analysis class reference

DragCalAnalysis

Experiment options

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

Options

Defined in the class RoughDrag:
- schedule (ScheduleBlock)
  
  Default value: None
  
  The schedule of the rotation.
- reps (List[int])
  
  Default value: [1, 3, 5]
  
  The number of times the Rp - Rm gate sequence is repeated in each series. Note that this list must always have a length of three as otherwise the analysis class will not run.
- betas (Iterable)
  
  Default value: array(-5.0, -4.8, -4.6, -4.4, -4.2, ..., size=51)
  
  the values of the DRAG parameter to scan.
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 a Drag experiment in the given qubit.

Parameters:

physical_qubits (Sequence[int]) – Sequence containing the qubit for which to run the Drag calibration.
schedule (ScheduleBlock) – The schedule to run. This schedule should have one free parameter corresponding to a DRAG parameter.
betas (Iterable[float] | None) – The values of the DRAG parameter to scan. If None is given the default range linspace(-5, 5, 51) is used.
backend (Backend | None) – Optional, the backend to run the experiment on.

Raises:

QiskitError – If the schedule does not have a free parameter.

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()[source]#

Create the circuits for the Drag calibration.

Returns:: The circuits that will run the Drag calibration.
Return type:: circuits
Raises:: QiskitError – If the number of different repetition series is not three.

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