Black box evolutionary optimization design of complex optical systems

Freeform optics bring new degrees of freedom to optical systems and require the abilities both to describe any surface (continuous or not) and to optimize their shape together with the geometry of the entire system. This increases the number of variables, and therefore the complexity of the fitness function to be minimized in order to obtain highest optical performance. Most proprietary algorithms from commercial solutions cannot handle more than tens of variables and/or noisy function landscape limiting the implementation of such free-form in optical systems. Here, CMA-ES algorithm is coupled to parallel computation of ray tracing simulations able to cover the high computational demand. The benefits of such state-of-the-art evolutionary optimization algorithms is a one-step convergence by exploring the entire landscape of solutions without the need of any starting optical architecture.