laboneq_applications.contrib.experiments.measurement_qndness

This module defines the qubit measurement QND experiment.

In this experiment, we first prepare the qubit in a superposition state using an x90 pulse, ensuring a random yet equal probability of measuring each qubit state. We then perform an initial measurement pulse, followed by additional measurement pulses. By comparing the results of these measurements, we can determine whether the qubit state is preserved after the initial measurement.

The pulse sequence for the qubit measurement QND experiment is as follows:

qb - [ x90 ] [ measure ] - [ delay (fixed) ] - [ measure ]

If multiple qubits are passed to the run workflow, the above pulses are applied in parallel on all the qubits.

QNDnessExperimentOptions

Base options for the resonator spectroscopy experiment.

Additional attributes

acquisition_type: Acquisition type to use for the experiment. Default: AcquisitionType.DISCRIMINATION. averaging_mode: Averaging mode to use for the experiment. Default: AveragingMode.SINGLE_SHOT.

acquisition_type = option_field(AcquisitionType.DISCRIMINATION, description='Acquisition type to use for the experiment.') class-attribute instance-attribute

averaging_mode = option_field(AveragingMode.SINGLE_SHOT, description='Averaging mode to use for the experiment.') class-attribute instance-attribute

delay_between_measurements = option_field(1e-06, description='Time delay between successive measurement operations.') class-attribute instance-attribute

transition = option_field('ge', description='Transition to perform the experiment on. May be any transition supported by the quantum operations.') class-attribute instance-attribute

use_cal_traces = option_field(True, description='Whether to include calibration traces in the experiment.') class-attribute instance-attribute

create_experiment(qpu, qubits, options=None)

Creates a Measurement QND Experiment.

Parameters:

Name	Type	Description	Default
qpu	QPU	The QPU consisting of the original QPUs and quantum operations.	required
qubits	Qubits	The qubits to run the experiments on. May be either a single qubit or a list of qubits.	required
options	QNDnessExperimentOptions | None	The options for building the experiment. See [QNDnessExperimentOptions] and [BaseExperimentOptions] for accepted options.	None

Returns:

Name	Type	Description
Experiment	Experiment	The generated LabOne Q experiment instance to be compiled
	Experiment	and executed.

Example

options = QNDnessExperimentOptions()
qpu = QPU(
    qubits=[q1, q2],
)
create_experiment(
    qpu=qpu,
    qubits=[q1, q2],
    options=options,
)

experiment_workflow(session, qpu, qubits, temporary_parameters=None, options=None)

The Qubit Measurement QNDness Workflow.

The workflow consists of the following steps:

• create_experiment
• compile_experiment
• run_experiment
• analysis_workflow
• update_qpu

Parameters:

Name	Type	Description	Default
session	Session	The connected session to use for running the experiment.	required
qpu	QPU	The qpu consisting of the original qubits and quantum operations.	required
qubits	Qubits	The qubits to run the experiments on. May be either a single qubit or a list of qubits.	required
temporary_parameters	dict[str, dict | QuantumParameters] | None	The temporary parameters to update the qubits with.	None
options	TuneUpWorkflowOptions | None	The options for building the workflow. In addition to options from [WorkflowOptions], the following custom options are supported: - create_experiment: The options for creating the experiment.	None

Returns:

Type	Description
None	None

Example

options = experiment_workflow.options()
options.count(2**9)
options.delay_between_measurements(1e-6)
qpu = QPU(
    qubits=[TunableTransmonQubit("q0"), TunableTransmonQubit("q1")],
    quantum_operations=TunableTransmonOperations(),
)
qubits = qpu.qubits
temporary_parameters = {}
for q in qubits_to_measure:
    temp_pars = deepcopy(q.parameters)
    temporary_parameters[q.uid] = temp_pars
result = experiment_workflow(
    session=session,
    qpu=qpu,
    qubits=qubits_to_measure,
    temporary_parameters=temporary_parameters,
    options=options,
).run()