qutip_qoc._optimizer module

This module contains the optimization routine to find the control parameters in a local and global search. It also contains the callback class to keep track of the optimization process.

qutip_qoc._optimizer._global_local_optimization(objectives, control_parameters, time_interval, time_options, algorithm_kwargs, optimizer_kwargs, minimizer_kwargs, integrator_kwargs, qtrl_optimizers=None)

Optimize a pulse sequence to implement a given target unitary by optimizing the parameters of the pulse functions. The algorithm is a two-layered approach. The outer layer does a global optimization using basin-hopping or dual annealing. The inner layer does a local optimization using a gradient- based method (no gradient for CRAB). Gradients and error values are calculated in the MultiObjective module.

Parameters:

objectiveslist of qutip_qoc.Objective

List of objectives to be optimized.

control_parametersdict

Dictionary of options for the control pulse optimization. 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_intervalqutip_qoc._TimeInterval

Time interval for the optimization.

time_optionsdict, optional

Only supported by GOAT and JOPT. Dictionary of options for the time interval optimization. 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.

algorithm_kwargsdict, optional

Dictionary of options for the optimization algorithm.

• algstr

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

• fid_err_targfloat, optional

  Fidelity error target for the optimization.

• max_iterint, optional

  Maximum number of global iterations to perform. Can be overridden by specifying in optimizer_kwargs/minimizer_kwargs.

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.

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.