RabiExperiment

class RabiExperiment(qubit_freq)

Bases: NormalizableMeasurement, Optimizable

Analytic model of the general Rabi formula.

__init__(qubit_freq)

Parameters:

qubit_freq (float) – Resonance of the single qubit.

Methods

__init__(qubit_freq)
calculate_normalized_scalar(times)	Carry out a measurement operation.
get_parameters()	Return a list of parameters accessible in this measurement.
get_value(times)	Return measurement in the range [0, 1].
set_all_optimizable_parameters(all_params)	Set all optimizable parameters in the optimization.
set_optimizable_parameters(params)	Set which parameters associated with the object shall be considered during optimization.

Attributes

all_optimizable_parameters	Get the optimizable parameters.
name	Get the name of the parameter.
optimizable_parameters	Get the optimizable parameters.

property all_optimizable_parameters: list[Quantity]

Get the optimizable parameters.

Returns:

The list of all the optimizable parameters considered in the optimization.

calculate_normalized_scalar(times)

Carry out a measurement operation.

Gives the result of a general Rabi oscillation, depending on drive frequency, amplitude and time.

Note

Returns the measurement value at the last time point.

Returns:

Result of a general Rabi oscillation.

Return type:

Float

get_parameters()

Return a list of parameters accessible in this measurement.

Returns:

List of parameters accessible in this measurement.

Return type:

list[Quantity]

get_value(times)

Return measurement in the range [0, 1].

property name: str | None

Get the name of the parameter.

Returns:

Name of the parameter.

property optimizable_parameters: list[Quantity]

Get the optimizable parameters.

Returns:

The list of optimizable parameters associated with the object.

set_all_optimizable_parameters(all_params)

Set all optimizable parameters in the optimization.

Parameters:

all_params (list[Quantity]) – List of optimizable parameters to be set.

set_optimizable_parameters(params)

Set which parameters associated with the object shall be considered during optimization.

All quantities that are not in the response of get_parameters will be filtered out. This function is called by the optimizer before gradient based optimization to tell the layers which gradients to compute.

Parameters:

params (list[Quantity]) – List of optimizable parameters to be set.