qiskit_noise_learning.analysis.ZeroPostSelect
class qiskit_noise_learning.analysis.ZeroPostSelect(creg_identifier: Callable[[list[str]], Iterator[str]] | None = None, mode: Literal['node', 'edge'] = 'edge')
Bases: AnalysisStage
Apply a mask to raw data based on whether bit values are all False.
This post-selection stage identifies cregs and masks shots whose bit patterns indicate failure. It can be configured to operate in one of two modes:
-
"node": Shots are discarded if any bit in the identified creg is True. -
"edge": Shots are discarded if there exists a pair of neighbouring qubits in thecoupling map for which both bits are True.
Parameters
- creg_identifier – A callable that, given a list of present creg names, returns an iterator over creg names to post-select on. Defaults to identifying cregs with naming pattern
"*_ps". - mode – Post-selection mode; either
"node"or"edge".
__init__
__init__(creg_identifier: Callable[[list[str]], Iterator[str]] | None = None, mode: Literal['node', 'edge'] = 'edge')
Methods
Column 1 | Column 2 |
|---|---|
__init__([creg_identifier, mode]) | |
run(fit) | Run this stage, returning a new Fit with the output level populated. |
Attributes
Column 1 | Column 2 |
|---|---|
creg_identifier | |
input_level | The data level this stage reads. |
mode | |
output_level | The data level this stage writes. |
input_level
The data level this stage reads.
output_level
The data level this stage writes.