Neural Network‐Assisted End‐to‐End Design for Full Light Field Control of Meta‐Optics

Meta-optics, with unique light-matter interactions and extensive design space, underpins versatile and compact optical devices through flexible multi-parameter light field control. However, conventional designs struggle with the intricate interdependencies of nano-structural complex responses across wavelengths and polarizations at a system level, hindering high-performance full-light field control. Here, a neural network-assisted end-to-end design framework that facilitates global, gradient-based optimization of multifunctional meta-optics layouts for full light field control is proposed. Its superiority over separated design is showcased by utilizing the limited design space for multi-wavelength-polarization…

• NN
  National Natural Science Foundation of China

  Award: 62275078
• NK
  National Key Research and Development Program of China

  Award: 2023YFB2806504