Genetic semi-analytical optimization approach for the inverse design of layered metasurfaces

We demonstrate a method for the inverse design of stacked metasurfaces, applicable
to any objective that can be expressed via scattering matrices, layering the metasurfaces in far-field approximation. By linking a semi analytical stacking algorithm with a modified genetic algorithm we developed an computationally efficient optimization tool. During optimization, the composition and the number of the layers is adjusted simultaneously and dynamically for continuous and discrete parameters. The method enables us to inversely design layered metasurface stacks in a matter of seconds avoiding thousands of rigorous simulations. We demonstrate the optimization performance of the algorithm for the example of a plasmonic broadband circular polarizer.