laboneq_applications.analysis.amplitude_fine

This module defines the analysis for an amplitude-fine experiment.

The experiment is defined in laboneq_applications.experiments.

In this analysis, we first interpret the raw data into qubit populations using principle-component analysis or rotation and projection on the measured calibration states. Then we fit a cosine model to the qubit population and extract ... . Finally, we plot the data and the fit.

analysis_workflow(result, qubits, amplification_qop, repetitions, target_angle, phase_offset, parameter_to_update=None, options=None)

The amplitude-fine analysis Workflow.

The workflow consists of the following steps:

• calculate_qubit_population
• fit_data
• extract_qubit_parameters
• plot_raw_complex_data_1d
• plot_population

Parameters:

Name	Type	Description	Default
result	RunExperimentResults	The experiment results returned by the run_experiment task.	required
qubits	Qubits	The qubits on which to run the analysis. May be either a single qubit or a list of qubits. The UIDs of these qubits must exist in the result.	required
amplification_qop	str	str to identify the quantum operation to repeat to produce error amplification.	required
repetitions	QubitSweepPoints	Number of times to repeat the quantum operations used to amplify the rotation errors. If qubits is a single qubit, repetitions must be a list of integers. Otherwise it must be a list of lists of integers.	required
target_angle	float	target angle the specified quantum operation shuould rotate. The target_angle is used as initial guess for fitting.	required
phase_offset	float	initial guess for phase_offset of fit.	required
parameter_to_update	str | None	str that defines the qubit parameter to be updated.	None
options	TuneUpAnalysisWorkflowOptions | None	The options for building the workflow, passed as an instance of [TuneUpAnalysisWorkflowOptions]. See the docstring of this class for more information.	None

Returns:

Name	Type	Description
WorkflowBuilder	None	The builder for the analysis workflow.

Example

options = analysis_workflow.options()
options.close_figures(False)
result = analysis_workflow(
    results=results
    qubits=[q0, q1],
    amplification_qop='x180',
    repetitions=[
        [1,2,3,4],
        [1,2,3,4],
    ],
    options=options,
).run()

extract_qubit_parameters(qubits, fit_results, processed_fit_results, parameter_to_update=None, options=None)

Extract the qubit parameters from the fit results.

Parameters:

Name	Type	Description	Default
qubits	Qubits	The qubits on which to run the analysis. May be either a single qubit or a list of qubits. The UIDs of these qubits must exist in the processed_data_dict and fit_results.	required
fit_results	dict[str, ModelResult]	the fit-results dictionary returned by fit_data	required
processed_fit_results	dict[str, Variable] | None	the processed fit-results dictionary returned by process_fit_data	required
parameter_to_update	str | None	str that defines the parameter to be updated.	None
options	TuneupAnalysisOptions | None	The options for extracting the qubit parameters. See [TuneupAnalysisOptions], [TuneupExperimentOptions] and [BaseExperimentOptions] for accepted options. Overwrites the options from [TuneupAnalysisOptions], [TuneupExperimentOptions] and [BaseExperimentOptions].	None

Returns:

Type	Description
dict[str, dict[str, dict[str, int | float | Variable | None]]]	dict with extracted qubit parameters and the previous values for those qubit
dict[str, dict[str, dict[str, int | float | Variable | None]]]	parameters. The dictionary has the following form:
dict[str, dict[str, dict[str, int | float | Variable | None]]]	```python
dict[str, dict[str, dict[str, int | float | Variable | None]]]	{ "new_parameter_values": { q.uid: { qb_param_name: qb_param_value }, } "old_parameter_values": { q.uid: { qb_param_name: qb_param_value }, }
dict[str, dict[str, dict[str, int | float | Variable | None]]]	}
dict[str, dict[str, dict[str, int | float | Variable | None]]]	```

Raises: ValueError: If fit_results are empty (have length 0).

fit_data(qubits, processed_data_dict, target_angle, phase_offset, options=None)

Perform a fit of a cosine model to the data.

Parameters:

Name	Type	Description	Default
qubits	Qubits	The qubits on which to run the analysis. May be either a single qubit or a list of qubits. The UIDs of these qubits must exist in the processed_data_dict.	required
processed_data_dict	dict[str, dict[str, ArrayLike]]	the processed data dictionary returned by process_raw_data	required
target_angle	float	target angle the specified quantum operation shuould rotate. The target_angle is used as initial guess for fitting.	required
phase_offset	float	initial guess for phase_offset of fit.	required
options	TuneupAnalysisOptions | None	The options for processing the raw data. See [TuneupAnalysisOptions], [TuneupExperimentOptions] and [BaseExperimentOptions] for accepted options. Overwrites the options from [TuneupAnalysisOptions], [TuneupExperimentOptions] and [BaseExperimentOptions].	None

Returns:

Type	Description
dict[str, ModelResult]	dict with qubit UIDs as keys and the fit results for each qubit as keys.

plot_population(qubits, processed_data_dict, amplification_qop, fit_results, processed_fit_results, parameter_to_update, qubit_parameters, options=None)

Create the amplitude-Rabi plots.

Parameters:

Name	Type	Description	Default
qubits	Qubits	The qubits on which to run the analysis. May be either a single qubit or a list of qubits. The UIDs of these qubits must exist in the processed_data_dict, fit_results and qubit_parameters.	required
processed_data_dict	dict[str, dict[str, ArrayLike]]	the processed data dictionary returned by process_raw_data	required
fit_results	dict[str, ModelResult] | None	the fit-results dictionary returned by fit_data	required
amplification_qop	str	str to identify the quantum operation to repeat.	required
processed_fit_results	dict[str, Variable] | None	the processed fit-results dictionary returned by process_fit_data	required
parameter_to_update	str	str that defines the parameter to be updated.	required
qubit_parameters	dict[str, dict[str, dict[str, int | float | Variable | None]]] | None	the qubit-parameters dictionary returned by extract_qubit_parameters	required
options	TuneupAnalysisOptions | None	The options for processing the raw data. See [TuneupAnalysisOptions], [TuneupExperimentOptions] and [BaseExperimentOptions] for accepted options. Overwrites the options from [TuneupAnalysisOptions], [TuneupExperimentOptions] and [BaseExperimentOptions].	None

Returns:

Type	Description
dict[str, Figure]	dict with qubit UIDs as keys and the figures for each qubit as values.

process_fit_results(qubits, fit_results, target_angle, options=None)

Process fit results to extract correction factor.

Parameters:

Name	Type	Description	Default
qubits	Qubits	The qubits on which to run the analysis. May be either a single qubit or a list of qubits. The UIDs of these qubits must exist in the processed_data_dict.	required
fit_results	dict[str, ModelResult] | None	the fit-results dictionary returned by fit_data	required
target_angle	float	target angle the specified quantum operation shuould rotate. The target_angle is used as initial guess for fitting.	required
options	TuneupAnalysisOptions | None	The options for processing the raw data. See [TuneupAnalysisOptions], [TuneupExperimentOptions] and [BaseExperimentOptions] for accepted options. Overwrites the options from [TuneupAnalysisOptions], [TuneupExperimentOptions] and [BaseExperimentOptions].	None

Returns:

Type	Description
dict[str, Variable]	dict with qubit UIDs as keys and the processed fit results for each qubit
dict[str, Variable]	as keys.

xaxis_label(amplification_qop)

Small task to create the x-axis label based on amplification_qop.

Parameters:

Name	Type	Description	Default
amplification_qop	str	str to identify the quantum operation to repeat to produce error amplification.	required

Returns:

Type	Description
str	strings with the x-axis label for the amplitude-fine experiment