Optical ReLU using membrane lasers for an all-optical neural network
Naoki Takahashi, Weicheng Fang, Ruihao Xue, Sho Okada, Yoshitaka Ohiso, Tomohiro Amemiya, Nobuhiko Nishiyama · Optics Letters · 2022
In this study, we propose low power consumption, programmable on-chip optical nonlinear units (ONUs) for all-optical neural networks (all-ONNs). The proposed units were constructed using a III-V semiconductor membrane laser, and the nonlinearity of the laser was used as the activation function of a rectified linear unit (ReLU). By measuring the relationship of the output power and input light, we succeeded in obtaining the response as an activation function of the ReLU with low power consumption. With its low-power operation and high compatibility with silicon photonics, we believe that this is a very promising device for realizing the ReLU function in optical circuits.