On-chip diffractive optical neural network based on binary metasurfaces
Kang Yang, Jian Lin, Pengjun Wang, Weiwei Chen, Shixun Dai, Lin Li, Jiafeng Ni, Qiang Fu, Jun Li, Tingge Dai, Jianyi Yang · Optics Express · 2025
This paper proposes and investigates an on-chip diffractive optical neural network based on binary metasurfaces. The genetic algorithm and finite-difference time-domain method are used to optimize the binary metasurfaces to achieve relatively compact area size and excellent performance. To prove the effectiveness of our proposal, a single-layer diffractive optical neural network based on binary metasurfaces is designed to execute a classification task on the Iris dataset. The area size of the designed single-layer diffractive optical neural network is only 16.5 µm × 23 µm. In the simulation, a validation accuracy of 90.0% is attained. The designed single-layer diffractive optical neural network was fabricated on a 220-nm silicon-on-insulator platform as a proof of concept. Measurement results show that the validation accuracy of the fabricated single-layer diffractive optical neural network is 78.3%.