# Closed-loop optimization¶

Toolkit for closed-loop optimizations.

For a quick introduction, see the Find optimal pulses with automated optimization tutorial and the How to automate closed-loop hardware optimization user guide.

The Boulder Opal Toolkits are currently in beta phase of development. Breaking changes may be introduced.

## Functions¶

Methods to perform common tasks. You can access them from the closed_loop namespace of the Qctrl object. For example, to use optimize:

qctrl = Qctrl()
qctrl.closed_loop.optimize(...)


Following is a list of functions in the closed_loop toolkit:

 optimize Run a closed-loop optimization to find a minimum of the given cost function.

## Classes¶

Classes to store common data types for the methods in the toolkit. You can access them from the closed_loop namespace of the Qctrl object. For example, to use Cmaes:

qctrl = Qctrl()
qctrl.closed_loop.Cmaes(...)


Following is a list of classes in the closed_loop toolkit:

 Cmaes The covariance matrix adaptation evolution strategy (CMA-ES) optimizer. CrossEntropy The cross-entropy optimizer. GaussianProcess The Gaussian process optimizer. NeuralNetwork The neural network optimizer. Optimizer Abstract class for optimizers used in closed-loop control. SimulatedAnnealing The simulated annealing optimizer.