FineZXAmplitude#

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

A fine amplitude experiment for the RZXGate(np.pi / 2).

Overview

FineZXAmplitude is a subclass of FineAmplitude and is used to set the appropriate values for the default options to calibrate a RZXGate(np.pi / 2).

Analysis class reference

FineAmplitudeAnalysis

Experiment options

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

Options

Defined in the class FineZXAmplitude:
- 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 FineZXAmplitude since the amplitude calibration can be achieved with two RZX gates and this is included in the repetitions.
- repetitions (List[int])
  
  Default value: [0, 1, 2, 3, 4, …]
  
  A list of the number of times that the gate is repeated.
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.
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

To run this experiment, the user will have to provide the instruction schedule map in the transpile options that contains the schedule for the experiment.

qubits = (1, 2)
inst_map = InstructionScheduleMap()
inst_map.add("szx", qubits, my_schedule)

fine_amp = FineZXAmplitude(qubits, backend)
fine_amp.set_transpile_options(inst_map=inst_map)

Here, my_schedule is the pulse schedule that will implement the RZXGate(np.pi / 2) rotation.

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)[source]#

Enable restless measurements.

We wrap the method of the RestlessMixin to readout both qubits. This forces the control qubit to be in either the 0 or 1 state before the next circuit starts since restless measurements do not reset qubits.

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.

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