laboneq_applications.experiments.ramsey

This module defines the Ramsey experiment.

In this experiment, we sweep the wait time between two x90 pulses on a given qubit transition in order to determine the T2 time of the qubit.

The Ramsey experiment has the following pulse sequence:

qb --- [ prep transition ] --- [ x90_transition ] --- [ delay ] ---
[ x90_transition ] --- [ measure ]

The second x90 pulse has a delay dependent phase that generates an oscillation of the qubit population at the frequency detuning.

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

create_experiment(qpu, qubits, delays, detunings=None, options=None)

Creates a Ramsey Experiment where the phase of the second pulse is swept.

Parameters:

Name	Type	Description	Default
qpu	QPU	The qpu consisting of the original qubits and quantum operations.	required
qubits	QuantumElements	The qubits to run the experiments on. May be either a single qubit or a list of qubits.	required
delays	QubitSweepPoints	The delays (in seconds) of the second x90 pulse to sweep over for each qubit. If qubits is a single qubit, delays must be a list of numbers or an array. Otherwise, it must be a list of lists of numbers or arrays.	required
detunings	float | Sequence[float] | None	The effective detuning in Hz used to calculate the phase increment of the second pulse in the Ramsey sequence. For perfectly resonant excitation pulses, this simulates oscillations of the qubit state vector around the Bloch sphere at the given frequency. This parameter and the fitted frequency of the oscillations can then be used to calculate the true qubit resonance frequency. detunings is a list of float values for each qubit following the order in qubits.	None
options	TuneupExperimentOptions | None	The options for building the experiment. See [TuneupExperimentOptions] and [BaseExperimentOptions] for accepted options. Overwrites the options from [TuneupExperimentOptions] and [BaseExperimentOptions].	None

Returns:

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

Raises:

Type	Description
ValueError	If the lengths of qubits and delays do not match.
ValueError	If delays is not a list of numbers when a single qubit is passed.
ValueError	If delays is not a list of lists of numbers when a list of qubits is passed.
ValueError	If the experiment uses calibration traces and the averaging mode is sequential.

Example

options = TuneupExperimentOptions()
qpu = QPU(
    quantum_elements=[TunableTransmonQubit("q0"), TunableTransmonQubit("q1")],
    quantum_operations=TunableTransmonOperations(),
)
temp_qubits = qpu.copy_quantum_elements()
create_experiment(
    qpu=qpu,
    qubits=temp_qubits,
    delays=[
        np.linspace(0, 20e-6, 51),
        np.linspace(0, 30e-6, 52),
    ],
    detunings = [1e6, 1.346e6],
    options=options,
)

evaluate_experiment(analysis_results, qubits, evaluation_parameters=None)

Evaluates the Ramsey analysis workflow result.

Parameters:

Name	Type	Description	Default
analysis_results	WorkflowResult	The analysis workflow results.	required
qubits	QuantumElements	The qubits to run the experiments on.	required
evaluation_parameters	dict[str, Any] | None	The evaluation parameters.	None

Returns:

Type	Description
dict[str, dict[str, bool]]	The evaluation flags.

experiment_workflow(session, qpu, qubits, *, delays, detunings=None, evaluation_parameters=None, temporary_parameters=None, options=None)

The Ramsey Workflow.

The workflow consists of the following steps:

• create_experiment
• compile_experiment
• run_experiment
• analysis_workflow
• evaluate_experiment
• update_qpu

Changed in version 26.4.0.

The evaluation_parameters argument has been added. This argument replaces the evaluation_parameter, evaluation_parameter_thresholds, and evaluation_fit_r2_thresholds arguments.

Deprecated in version 26.1.0.

The qubits argument of type QuantumElements is deprecated. Please pass qubits of type list[str] | str instead, i.e., the quantum element UIDs instead of the quantum element instances.

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	QuantumElements | list[str] | str	The qubits to run the experiments on, passed by UID. May be either a single qubit or a list of qubits.	required
delays	QubitSweepPoints	The delays (in seconds) of the second x90 pulse to sweep over for each qubit. If qubits is a single qubit, delays must be a list of numbers or an array. Otherwise, it must be a list of lists of numbers or arrays.	required
detunings	float | Sequence[float] | None	The detuning in Hz to generate oscillating qubit occupations. detunings is a list of float values for each qubits following the order in qubits.	None
evaluation_parameters	dict[str, Any] | None	The dictionary of parameters used for the evaluation task. The default evaluation parameters are defined in the evaluate_experiment task.	None
temporary_parameters	dict[str | tuple[str, str, str], dict | QuantumParameters] | None	The temporary parameters with which to update the quantum elements and topology edges. For quantum elements, the dictionary key is the quantum element UID. For topology edges, the dictionary key is the edge tuple (tag, source node UID, target node UID).	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:

Name	Type	Description
result	None	The result of the workflow.

Example

options = experiment_workflow.options()
options.create_experiment.count(10)
options.create_experiment.transition("ge")
setup = DeviceSetup("my_device")
qpu = QPU(
    quantum_elements=[TunableTransmonQubit("q0"), TunableTransmonQubit("q1")],
    quantum_operations=TunableTransmonOperations(),
)
temp_qubits = qpu.copy_quantum_elements()
result = experiment_workflow(
    session=session,
    qpu=qpu,
    qubits=temp_qubits,
    delays=[[0.1, 0.5, 1], [0.1, 0.5, 1]],
    detunings = {'q0':1e6,'q1':1.346e6},
    options=options,
).run()