吉林大学学报(理学版) ›› 2024, Vol. 62 ›› Issue (2): 423-0430.

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基于物理信息神经网络的光波衍射问题求解

陈旭早, 袁利军   

  1. 重庆工商大学 数学与统计学院, 重庆 400067
  • 收稿日期:2023-05-16 出版日期:2024-03-26 发布日期:2024-03-26
  • 通讯作者: 袁利军 E-mail:ljyuan@ctbu.edu.cn

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

CHEN Xuzao, YUAN Lijun   

  1. School of Mathematics and Statistics, Chongqing Technology and Business University, Chongqing 400067, China
  • Received:2023-05-16 Online:2024-03-26 Published:2024-03-26

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.

关键词: 物理信息神经网络, 光波衍射, 间断系数, 光滑函数

Abstract: 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.

Key words: physics-informed neural network, light wave diffraction, discontinuous coefficient, smooth function

中图分类号: 

  • O436