qiskit_ibm_runtime.options_models.NoiseLearnerV3Options
pydantic model NoiseLearnerV3Options
Bases: BaseOptionsModel
Options for NoiseLearnerV3.
Config
- validate_assignment: bool = True
- extra: str = forbid
bit_flip_checks
field
Type: BitFlipChecksOptions
Default value: BitFlipChecksOptions(pre_circuit=PreCircuitBitFlipChecksOptions(enable=False, x_pulse_type='xslow', strategy='node'), post_circuit=PostCircuitBitFlipChecksOptions(enable=False, x_pulse_type='xslow', strategy='node'))
Options to apply bit-flip checks to the results of noise learning circuits.
environment
field
Type: EnvironmentOptions
Default value: EnvironmentOptions(log_level='WARNING', job_tags=[], private=False, max_execution_time=None, image=None)
Options related to the execution environment.
execution
field
Type: ExecutionOptions
Default value: ExecutionOptions(init_qubits=True, rep_delay=None, scheduler_timing=False, stretch_values=False)
Low-level execution options.
experimental
field
Type: dict
Default value: {}
Experimental options.
These options are subject to change without notification, and stability is not guaranteed.
layer_pair_depths
field
Type: list[Annotated[int, Field(ge``=``0)]]
Default value: [0, 1, 2, 4, 16, 32]
The circuit depths (measured in number of pairs) to use in Pauli Lindblad experiments.
Pairs are used as the unit because we exploit the order-2 nature of our entangling gates in the noise learning implementation. For example, a value of 3 corresponds to 6 repetitions of the layer of interest.
This field is ignored by TREX experiments.
num_randomizations
field
Type: Annotated[int, Field(ge``=``1)]
Default value: 32
The number of random circuits to use per learning circuit configuration.
For TREX experiments, a configuration is a measurement basis.
For Pauli Lindblad experiments, a configuration is a measurement basis and depth setting. For example, if your experiment has six depths, then setting this value to 32 will result in a total of 32 * 9 * 6 circuits that need to be executed (where 9 is the number of circuits that need to be implemented to measure all the required observables, see the note in the docstring for NoiseLearnerOptions for mode details), at shots_per_randomization each.
Constraints
- ge = 1
post_selection
field
Type: PostSelectionOptions
Default value: PostSelectionOptions(enable=False, x_pulse_type='xslow', strategy='node')
Options for post selecting the results of noise learning circuits.
shots_per_randomization
field
Type: Annotated[int, Field(ge``=``1)]
Default value: 128
The total number of shots to use per randomized learning circuit.
Constraints
- ge = 1