qutip_qoc.pulse_optim module

This module is the entry point for the optimization of control pulses. It provides the function optimize_pulses which prepares and runs the GOAT, JOPT, GRAPE or CRAB optimization.

qutip_qoc.pulse_optim.optimize_pulses(objectives, control_parameters, tlist, algorithm_kwargs=None, optimizer_kwargs=None, minimizer_kwargs=None, integrator_kwargs=None)

Run GOAT, JOPT, GRAPE or CRAB optimization.

Parameters:

objectiveslist of qutip_qoc.Objective

List of objectives to be optimized. Each objective is weighted by its weight attribute.

control_parametersdict

Dictionary of options for the control pulse optimization. The keys of this dict must be a unique string identifier for each control Hamiltonian / function. For the GOAT and JOPT algorithms, the dict may optionally also contain the key “__time__”. For each control function it must specify:

control_iddict

• guess: ndarray, shape (n,)

  Initial guess. Array of real elements of size (n,), where n is the number of independent variables.

• boundssequence, optional

  Sequence of (min, max) pairs for each element in guess. None is used to specify no bound.

__time__dict, optional

Only supported by GOAT and JOPT. If given the pulse duration is treated as optimization parameter. It must specify both:

• guess: ndarray, shape (n,)

  Initial guess. Array of real elements of size (n,), where n is the number of independent variables.

• boundssequence, optional

  Sequence of (min, max) pairs for each element in guess. None is used to specify no bound.

GRAPE and CRAB bounds are only one pair of (min, max) limiting the amplitude of all tslots equally.

tlist: List.

Time over which system evolves.

algorithm_kwargsdict, optional

Dictionary of options for the optimization algorithm.

• algstr

  Algorithm to use for the optimization. Supported are: “GRAPE”, “CRAB”, “GOAT”, “JOPT”.

• fid_err_targfloat, optional

  Fidelity error target for the optimization.

• max_iterint, optional

  Maximum number of iterations to perform. Referes to local minimizer steps. Global steps default to 0 (no global optimization). Can be overridden by specifying in minimizer_kwargs.

Algorithm specific keywords for GRAPE,CRAB can be found in qutip_qtrl.pulseoptim.optimize_pulse().

optimizer_kwargsdict, optional

Dictionary of options for the global optimizer. Only supported by GOAT and JOPT.

• methodstr, optional

  Algorithm to use for the global optimization. Supported are: “basinhopping”, “dual_annealing”

• max_iterint, optional

  Maximum number of iterations to perform. Default is 0 (no global optimization).

Full list of options can be found in scipy.optimize.basinhopping() and scipy.optimize.dual_annealing().

minimizer_kwargsdict, optional

Dictionary of options for the local minimizer.

• methodstr, optional

  Algorithm to use for the local optimization. Gradient driven methods are supported.

Full list of options and methods can be found in scipy.optimize.minimize().

integrator_kwargsdict, optional

Dictionary of options for the integrator. Only supported by GOAT and JOPT. Options for the solver, see MESolver.options and Integrator for a list of all options.

Returns:

resultqutip_qoc.Result

Optimization result.