Photonic Chip Based on Ultrafast Laser-Induced Reversible Phase Change for Convolutional Neural Network
Jiawang Xie, Jianfeng Yan, Haoze Han, Yuzhi Zhao, Ma Luo, Jiaqun Li, Heng Guo, Ming Qiao
Abstract
Photonic computing has emerged as a promising technology for the ever-increasing computational demands of machine learning and artificial intelligence. Due to the advantages in computing speed, integrated photonic chips have attracted wide research attention on performing convolutional neural network algorithm. Programmable photonic chips are vital for achieving practical applications of photonic computing. Herein, a programmable photonic chip based on ultrafast laser-induced phase change is fabricated for photonic computing. Through designing the ultrafast laser pulses, the Sb film integrated into photonic waveguides can be reversibly switched between crystalline and amorphous phase, resulting in a large contrast in refractive index and extinction coefficient. As a consequence, the light transmission of waveguides can be switched between write and erase states. To determine the phase change time, the transient laser-induced phase change dynamics of Sb film are revealed at atomic scale, and the time-resolved transient reflectivity is measured. Based on the integrated photonic chip, photonic convolutional neural networks are built to implement machine learning algorithm, and images recognition task is achieved. This work paves a route for fabricating programmable photonic chips by designed ultrafast laser, which will facilitate the application of photonic computing in artificial intelligence.