qiskit_noise_learning.protocols.process_vanilla_result
qiskit_noise_learning.protocols.process_vanilla_result(result: QuantumProgramResult, raw_data_stage: AnalysisStage | None = None) → tuple[list[PauliLindbladMap], list[str], Fit]
Analyze the result of a program built by prepare_vanilla_program().
Applies the standard “vanilla” learning program analysis using curve fitting and LegacySolve fit the model.
Example:
noise_maps, gate_names, fit = process_vanilla_result(job.result())
noise_maps[0]Parameters
- result – The result of a program built by
prepare_vanilla_program(). - raw_data_stage – An optional analysis stage to run on the raw data ahead of the standard analysis, typically to post-select on registers that a pass manager added during preparation. It must consume and produce
RawData.
Returns
A (noise_maps, gate_names, fit) tuple, whose first two entries are parallel to the instructions submitted to prepare_vanilla_program(). I.e. for instruction idx, noise_maps[idx] is the learned noise map, and gate_names[idx] is the name assigned to the instruction used in the returned fit. A noise map acts on the qubits of its instruction, its qubit j being the j-th of the instruction in ascending physical-qubit order.
Raises
- TypeError – If raw_data_stage is not an analysis stage.
- ValueError – If raw_data_stage does not consume and produce
RawData, if result holds no program items, if the result’s passthrough data carries no vanilla protocol data or carries it at an incompatible version, if the result violates the solver’s assumptions, or if the fitted model gives no noise for one of the gates the program was built from.