AI-assisted on-chip nanophotonic convolver based on silicon metasurface
Liao Kun,
Gan Tianyi,
Hu Xiaoyong,
Gong Qihuang
Affiliations
Liao Kun
State Key Laboratory for Mesoscopic Physics and Department of Physics, Collaborative Innovation Center of Quantum Matter, Beijing Academy of Quantum Information Sciences, Nano-optoelectronics Frontier Center of Ministry of Education, Peking University, Beijing 100871, China
Gan Tianyi
State Key Laboratory for Mesoscopic Physics and Department of Physics, Collaborative Innovation Center of Quantum Matter, Beijing Academy of Quantum Information Sciences, Nano-optoelectronics Frontier Center of Ministry of Education, Peking University, Beijing 100871, China
Hu Xiaoyong
State Key Laboratory for Mesoscopic Physics and Department of Physics, Collaborative Innovation Center of Quantum Matter, Beijing Academy of Quantum Information Sciences, Nano-optoelectronics Frontier Center of Ministry of Education, Peking University, Beijing 100871, China
Gong Qihuang
State Key Laboratory for Mesoscopic Physics and Department of Physics, Collaborative Innovation Center of Quantum Matter, Beijing Academy of Quantum Information Sciences, Nano-optoelectronics Frontier Center of Ministry of Education, Peking University, Beijing 100871, China
Convolution operation is of great significance in on-chip all-optical signal processing, especially in signal analysis and image processing. It is a basic and important mathematical operation in the realization of all-optical computing. Here, we propose and experimentally implement a dispersionless metalens for dual wavelengths, a 4f optical processing system, and then demonstrate the on-chip nanophotonic convolver based on silicon metasurface with the optimization assistance of inverse design. The characteristic size of the dispersionless metalens device is 8 × 9.4 μm, and the focusing efficiency is up to 79% and 85% at wavelengths of 1000 and 1550 nm, respectively. The feature size of the convolver is 24 × 9.4 μm, and the proposed convolver allows spatial convolution operation on any desired function at dual wavelengths simultaneously. This work provides a potential scheme for the further development of on-chip all-optical computing.
