Multiplexed metasurfaces for diffractive optics via a phase correlation method

The multiplexing capability of metasurfaces has been successfully demonstrated in applications such as holography and diffractive neural networks. However, identifying a suitable structure that simultaneously satisfies the phase requirements across multiple channels remains a significant challenge in many multiplexing design scenarios. In this study, we propose an innovative phase correlation method for metasurface multiplexing design that utilizes a multi-layer perceptron (MLP) to establish phase correlations across multiple channels. This approach reduces the difficulty of multi-channel phase training by converting it into a simpler single-channel optimization task, thereby reducing design complexity and computational cost. Using the proposed method, we design a dual-wavelength multiplexed diffractive neural network (DW-MDNN) and a multi-wavelength metasurface color holography under a linear polarization. The designed multiplexed metasurface achieves up to 90% classification accuracy in image recognition and exhibits good performance in color holography.