laboneq_applications.analysis.lifetime_measurement

This module defines the analysis for an lifetime_measurement experiment.

The experiment is defined in laboneq_applications.experiments.

In this analysis, we first interpret the raw data into qubit population using principle-component analysis or rotation and projection on the measured calibration states. Then we fit an exponential-decay model to the qubit population and extract the qubit energy relaxation time lifetime_measurement from the fit. Finally, we plot the data and the fit.

analysis_workflow(result, qubits, delays, options=None)

The lifetime_measurement 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 of the lifetime_measurement experiment workflow.	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
delays	QubitSweepPoints	The delays that were swept over in the lifetime_measurement experiment for each qubit. If qubits is a single qubit, delays must be an array of numbers. Otherwise, it must be a list of arrays of numbers.	required
options	TuneUpAnalysisWorkflowOptions | None	The options for building the workflow, passed as an instance of [TuneUpAnalysisWorkflowOptions]. In addition to options from [WorkflowOptions], the following custom options are supported: do_fitting, do_plotting, do_raw_data_plotting, do_qubit_population_plotting and the options of the [TuneupAnalysisOptions] class. See the docstring of [TuneUpAnalysisWorkflowOptions] for more details	None

Returns:

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

Example

options = TuneUpAnalysisWorkflowOptions()
result = analysis_workflow(
    results=results
    qubits=[q0, q1],
    delays=[
        np.linspace(0, 10e-6, 11),
        np.linspace(0, 10e-6, 11),
    ],
    options=options,
).run()

extract_qubit_parameters(qubits, fit_results, 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.	required
fit_results	dict[str, ModelResult]	the fit-results dictionary returned by fit_data	required
options	TuneupAnalysisOptions | None	The options for extracting the qubit parameters. See [TuneupAnalysisOptions], [TuneupExperimentOptions] and [BaseExperimentOptions] for accepted options.	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]]]	```
dict[str, dict[str, dict[str, int | float | Variable | None]]]	If the do_fitting option is False, the new_parameter_values are not extracted
dict[str, dict[str, dict[str, int | float | Variable | None]]]	and the function only returns the old_parameter_values.
dict[str, dict[str, dict[str, int | float | Variable | None]]]	If a qubit uid is not found in fit_results, the new_parameter_values entry for
dict[str, dict[str, dict[str, int | float | Variable | None]]]	that qubit is left empty.

fit_data(qubits, processed_data_dict, options=None)

Perform a fit of an exponential-decay model to the qubit state population.

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 processed_data_dict	required
processed_data_dict	dict[str, dict[str, ArrayLike]]	the processed data dictionary returned by process_raw_data	required
options	TuneupAnalysisOptions | None	The options for processing the raw data. See [TuneupAnalysisOptions], [TuneupExperimentOptions] and [BaseExperimentOptions] for accepted options.	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, fit_results, qubit_parameters, options=None)

Create the lifetime_measurement 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 processed_data_dict.	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
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.	None

Returns:

Type	Description
dict[str, Figure]	dict with qubit UIDs as keys and the figures for each qubit as values.
dict[str, Figure]	If a qubit uid is not found in fit_results, the fit and the textbox with the
dict[str, Figure]	extracted qubit parameters are not plotted.