Reflectarray and GRIN Lens Performance Enhancement via Adjoint Optimization

For electromagnetic design problems with seemingly intractable solutions, an optimization strategy best suited to the nature of the problem can be used to significantly cut the required simulation time. Traditional global optimizations require substantial simulation time for problems with large numbers of design variables, including reflectarray or gradient index (GRIN) lens structures with a large volume of unit cells. To design these complex structures at improved speeds, one can exploit the adjoint optimization (AO) approach to quickly optimize solutions with an unlimited number of parameters using physics-based gradient computation and local optimization algorithms.