基于粒子群与遗传算法的消色差超透镜自动设计

本文利用智能优化算法，对宽波段消色差超透镜进行设计优化。首先，研究构建于二氧化硅基底上的硅纳米柱这一微单元结构的光学特性，通过数值仿真扫描单元结构的半径构建相位数据库。之后，通过使用粒子群与遗传算法的混合算法(PSO＿GA)在相位数据库中找到最佳相位矩阵，即对应每个位置最佳的单元结构。最后，构建超透镜，通过仿真实验验证其可实现红外波段(1000 nm～1250 nm)的聚焦，且消色差效果优于传统粒子群优化算法所获得的超透镜结构。此超透镜的设计为平面光学器件的自动化设计提供了一种解决方法。

Automatic design of achromatic metalens based on particle swarm and genetic algorithm

In this paper,an intelligent optimization algorithm is used to optimize the design of a wide band achromatic superlens.Firstly,the optical properties of silicon nanocrystals(SI nanocrystals)constructed on silica substrate are studied,and a database is constructed by scanning the radius of the unit structure through numerical simulation.Then,a hybrid algorithm of particle swarm optimization and genetic algorithm(PSO_GA)is used to find the optimal phase matrix in the phase database,that is,the optimal cell structure corresponding to each position.Finally,the superlens is constructed,and verified through simulation experiments that it can realize the focusing in infrared band(1000～1250 nm),and the achromatic effect is better than that of the superlens structure obtained by the traditional particle swarm optimization algorithm.Therefore,the design of this superlens provides a solution for the automatic design of planar optical devices.