Research on intelligent algorithms for amplitude optimization of wavefront shaping.

This paper demonstrates further research on intelligent algorithms of binary amplitude optimization for wavefront shaping by numerical simulations. A better fitness function of the genetic algorithm (GA) has been presented after a comparative analysis of enhancement. With this new discriminant, we have achieved a relative enhancement of 0.225, which is higher than the theoretical value (0.159). In addition, we have also proposed a kind of modified particle swarm optimization algorithm (PSO), which has a higher enhancement than the unmodified PSO and a faster convergence speed than the GA. These studies provide remarkable insights into future exploration of intelligent algorithms for wavefront shaping.