基于深度学习的纳米粒子阵列电场预测OA北大核心CSTPCD

The calculation of the electric fields of nanoparticle arrays metasurface require a lot of time and computing power.To achieve the fast calculation of the electric field of nanoparticle arrays,with the help of the deep learning method,this study proposes a mapping deep neural network from low-precision electric field to high-precision electric field.This neural network can predict the electric field with high-precision according to the electric field with low-precision.The mean square error is 5.6×10-3 and the mean norm relative error is 1.5%.The numerical results confirm that the model can fast and accurately predict the electric field on the surface of a nanoparticle array.Compared with the existing research results,the error of this model is lower by an order of magnitude.This work helps to solve the problem of fast design of nanoparticle arrays with surface enhancement of Raman scattering.