paraqeet.measurement.goat_over_grape.GOATOverGRAPE

class paraqeet.measurement.goat_over_grape.GOATOverGRAPE(measurement, propagation, generators)

Bases: NormalizableMeasurement, Differentiable

Combine GRAPE propagation with analytic gradients of GOAT via chain rule.

Parameters:

• measurement (StateTransferFidelityGRAPE) – A StateTransferFidelityGRAPE measurement.

• propagation (DifferentiablePropagation) – Propagation method used for the optimization. Used to determine the time grid.

• generators (PWCGenerator | list[PWCGenerator]) – A PWCGenerator or a list of PWCGenerators that are used for propagation.

__init__(measurement, propagation, generators)

Parameters:

• measurement (StateTransferFidelityGRAPE)

• propagation (DifferentiablePropagation)

• generators (PWCGenerator | list[PWCGenerator])

Methods

__init__(measurement, propagation, generators)
calculate_normalized_scalar(times)	Passthrough the measurement.
get_value_and_gradient(times)	Compute gradients with GRAPE and use the chain rule to provide the gradients for the optimizer.
measure(times)	Sum of plain weighted measurements.

calculate_normalized_scalar(times)

Passthrough the measurement.

Returns:

Returns the normalized weighted sum.

Return type:

Array

Parameters:

times (Array | float)

get_value_and_gradient(times)

Compute gradients with GRAPE and use the chain rule to provide the gradients for the optimizer.

Returns:

• Array – Function value.

• Array – Gradients.

Parameters:

times (Array)

Return type:

tuple[Array, Array] | tuple[float, Array]

measure(times)

Sum of plain weighted measurements.

Returns:

Returns the plain weighted sum.

Return type:

Array

Parameters:

times (Array)