东华大学学报（英文版）2025，Vol.42Issue(2)：168-176,9.DOI:10.19884/j.1672-5220.202404001
基于生成对抗网络模型的双波长双聚焦超透镜设计
Design of Dual-Wavelength Bifocal Metalens Based on Generative Adversarial Network Model
摘要
Abstract
Multifocal metalenses are of great concern in optical communications,optical imaging and micro-optics systems,but their design is extremely challenging.In recent years,deep learning methods have provided novel solutions to the design of optical planar devices.Here,an approach is proposed to explore the use of generative adversarial networks(GANs)to realize the design of metalenses with different focusing positions at dual wavelengths.This approach includes a forward network and an inverse network,where the former predicts the optical response of meta-atoms and the latter generates structures that meet specific requirements.Compared to the traditional search method,the inverse network demonstrates higher precision and efficiency in designing a dual-wavelength bifocal metalens.The results will provide insights and methodologies for the design of tunable wavelength metalenses,while also highlighting the potential of deep learning in optical device design.关键词
生成对抗网络/超透镜/前向网络/逆向设计Key words
generative adversarial network(GAN)/metalens/forward network/inverse design分类
物理学引用本文复制引用
刘港成,王军凯,林森,伍滨和,王春瑞,周健,孙浩..基于生成对抗网络模型的双波长双聚焦超透镜设计[J].东华大学学报（英文版）,2025,42(2):168-176,9.基金项目
National Natural Science Foundation of China(No.61975029) （No.61975029）
