Metasurface-enabled on-chip multiplexed diffractive neural networks in the visible

Abstract Replacing electrons with photons is a compelling route toward high-speed, massively parallel, and low-power artificial intelligence computing. Recently, diffractive networks composed of phase surfaces were trained to perform machine learning tasks through linear optical transformations. However, the existing architectures often comprise bulky components and, most critically, they cannot mimic the human brain for multitasking. Here, we demonstrate a multi-skilled diffractive neural network based on a metasurface device, which can perform on-chip multi-channel sensing and multitasking in the visible. The polarization multiplexing scheme of the subwavelength nanostructures is applied to construct a…

• NN
  National Natural Science Foundation of China

  Awards: 52005175, 5211101255
• SK
  State Key Laboratory of Tribology

  Award: SKLTKF20B04