# CrossEntropyInitializer¶

class qctrl.dynamic.types.closed_loop_optimization_step.CrossEntropyInitializer(*, elite_fraction, rng_seed=None)

Configuration for the cross-entropy optimizer. Note that this optimizer requires at least $lceil 2 / elite_fraction rceil$` results each step, to have at least 2 surviving elite points, and will throw an error if you don’t provide enough points for the initial step. If you don’t provide enough results for subsequent steps, the optimizer will not advance and will request more test points following the same distribution as in the previous step.

Variables
• elite_fraction (float) – The top fraction of test points that the algorithm uses to generate the next distribution.

• rng_seed (int) – Seed for the random number generator.