Feng Qi, Zhang Bin, Liu Zhipeng, Lin Chengyou, Ding Yingchun
Appl Opt. 2017 Apr 20;56(12):3240-3244. doi: 10.1364/AO.56.003240.
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.
本文通过数值模拟对波前整形的二元振幅优化智能算法进行了进一步研究。在增强效果的对比分析之后，提出了一种更好的遗传算法（GA）适应度函数。基于这种新的判别方法，我们实现了0.225的相对增强，高于理论值（0.159）。此外，我们还提出了一种改进的粒子群优化算法（PSO），它比未改进的PSO具有更高的增强效果，且收敛速度比GA更快。这些研究为波前整形智能算法的未来探索提供了显著的见解。
