Research and Application of Deep Learning in the Design of Metasurface Structures

This paper provides an in-depth discussion on the research and application of deep learning in the design of metasurface structures. Firstly, the basic theoretical foundation of metasurfaces is systematically introduced to lay the foundation for subsequent research. Then, the theoretical framework of deep learning applied to metasurface design is elaborated, focusing on the application of deep neural network (DNN) model in the spectral prediction of metasurface structures. The efficient prediction of the spectral response of the metasurface structure is achieved by constructing the DNN model and training it with the metasurface structure and spectral data. The experimental results show that the model can accurately predict the spectral properties of the metasurface structure, and the prediction results are highly consistent with the experimental data, which verifies the accuracy and reliability of the model. This study provides an efficient and accurate deep learning method for the design and optimisation of metasurface structures, and provides new ideas and directions for the development and application of future metasurface technology.