Total Transmission from Deep Learning Designs

作     者：Bei Wu Zhan-Lei Hao Jin-Hui Chen Qiao-Liang Bao Yi-Neng Liu Huan-Yang Chen Bei Wu;Zhan-Lei Hao;Jin-Hui Chen;Qiao-Liang Bao;Yi-Neng Liu;Huan-Yang Chen

作者机构：Department of PhysicsXiamen UniversityXiamen 361005 Institute of Electromagnetics and AcousticsXiamen UniversityXiamen 361005 Xiamen Key Laboratory of Multiphysics Electronic InformationXiamen 361005 Fujian Provincial Key Laboratory of Electromagnetic Wave Science and Detection TechnologyXiamen 361005 Fujian Engineering Research Center for EDAXiamen 361005 

出 版 物：《Journal of Electronic Science and Technology》 (电子科技学刊（英文版）)

年 卷 期：2022年第20卷第1期

页      面：9-19页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 070207[理学-光学] 07[理学] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0803[工学-光学工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 0702[理学-物理学] 

基　　金：supported by the National Key Research and Development Program of China under Grant No.2020YFA0710100 the National Natural Science Foundation of China under Grants No.92050102,No.11874311,and No.11504306 the Fundamental Research Funds for the Central Universities under Grant No.20720200074 

主　　题：Artificial neural networks(ANNs) deep learning forward spectral prediction inverse material design total transmission 

摘      要：Total transmission plays an important role in efficiency improvement and wavefront control,and has made great progress in many applications,such as the optical film and signal ***,many traditional physical methods represented by transformation optics have been studied to achieve total ***,these methods have strict limitations on the size of the photonic structure,and the calculation is ***,we exploit deep learning to achieve this *** deep learning,the data-driven prediction and design are carried out by artificial neural networks(ANNs),which provide a convenient architecture for large dataset *** taking the transmission characteristic of the multi-layer stacks as an example,we demonstrate how optical materials can be designed by using *** trained network directly establishes the mapping from optical materials to transmission spectra,and enables the forward spectral prediction and inverse material design of total transmission in the given parameter *** work paves the way for the optical material design with special properties based on deep learning.