  Numerical simulation of complex optical structures enables their optimization
with respect to specific objectives. Often, optimization is done by multiple
successive parameter scans, which are time consuming and computationally
expensive. We employ here Bayesian optimization with Gaussian processes in
order to automatize and speed up the optimization process. As a toy example, we
demonstrate optimization of the shape of a free-form reflective meta surface
such that it diffracts light into a specific diffraction order. For this
example, we compare the performance of six different Bayesian optimization
approaches with various acquisition functions and various kernels of the
Gaussian process.
