bounds (List[qctrl.dynamic.types.closed_loop_optimization_step.BoxConstraint]) – The per-parameter bounds on the test points. The bounds are defined by
imposing a box constraint on each individual parameter. That is, for
each parameter \(x_j\), the optimizer is only allowed to search the
next test point subject to the constraint such that \(x^{\rm
lower}_j \leq x_j \leq x^{\rm upper}_j\). These constraints must be in
the same order as parameters in CostFunctionResult.
initial_mean (List[float], optional) – The initial mean of the multivariate normal distribution. If passed, it
must have the same length as the number of parameters. Defaults to an
array of ones.
initial_step_size (float, optional) – The initial step size \(\sigma\) for the multivariate normal
distribution from which new test points are sampled. Defaults to one.
seed (int, optional) – Seed for the random number generator. If set, must be non-negative. Use
this option to generate deterministic results from the optimizer.
rng_seed (int, optional) – This parameter will be removed, please use seed instead.