基于物理信息神经网络的光波衍射问题求解  

Solving Light Wave Diffraction Problem Based on Physics-Informed Neural Networks

作　　者：陈旭早 袁利军[1] CHEN Xuzao;YUAN Lijun(School of Mathematics and Statistics,Chongqing Technology and Business University,Chongqing 400067,China)

机构地区：[1]重庆工商大学数学与统计学院,重庆400067

出　　处：《吉林大学学报（理学版）》2024年第2期423-430,共8页Journal of Jilin University:Science Edition

基　　金：重庆市自然科学基金(批准号:CSTB2022NSCQ-MSX0610)。

摘　　要：用物理信息神经网络方法数值求解间断系数光波衍射问题.结果表明:用光滑函数近似间断系数可大幅度提高物理信息神经网络求解精度;用物理信息神经网络求解散射场比直接求解总场效果更好.最后通过数值实验验证理论结果的正确性.We used the physics-informed neural networks method to numerically solve the problem of discontinuous coefficient light wave diffraction.The results show that approximating the discontinuous coefficient with a smooth function can significantly improve the accuracy of the physics-informed neural network solution.Using physics-informed neural networks to solve the scattered field is better than directly solving the total field.Finally,the correctness of the theoretical results is verified through numerical experiments.

关 键 词：物理信息神经网络 光波衍射 间断系数 光滑函数 

分 类 号：O436[机械工程—光学工程]