Hardware-algorithm collaborative computing with photonic spiking neuron chip based on integrated Fabry–Pérot laser with saturable absorber

Xiang, S. et al. (2023) Hardware-algorithm collaborative computing with photonic spiking neuron chip based on integrated Fabry–Pérot laser with saturable absorber. Optica, 10(2), pp. 162-171. (doi: 10.1364/OPTICA.468347)

Abstract

Photonic neuromorphic computing has emerged as a promising approach to building a low-latency and energy-efficient non-von Neuman computing system. A photonic spiking neural network (PSNN) exploits brain-like spatiotemporal processing to realize high-performance neuromorphic computing. However, the nonlinear computation of a PSNN remains a significant challenge. Here, we propose and fabricate a photonic spiking neuron chip based on an integrated Fabry–Perot laser with a saturable absorber (FP-SA). The nonlinear neuron-like dynamics including temporal integration, threshold and spike generation, a refractory period, inhibitory behavior and cascadability are experimentally demonstrated, which offers an indispensable fundamental building block to construct the PSNN hardware. Furthermore, we propose time-multiplexed temporal spike encoding to realize a functional PSNN far beyond the hardware integration scale limit. PSNNs with single/cascaded photonic spiking neurons are experimentally demonstrated to realize hardware-algorithm collaborative computing, showing the capability to perform classification tasks with a supervised learning algorithm, which paves the way for a multilayer PSNN that can handle complex tasks.

• Item Type: Articles
• Additional Information: Funding: National Key Research and Development Program of China (2021YFB2801900, 2021YFB2801902, 2021YFB2801904, 2018YFE0201200); National Natural Science Foundation of China (61974177, 61674119); National Outstanding Youth Science Fund Project of National Natural Science Foundation of China (62022062); Fundamental Research Funds for the Central Universities (JB210114).
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Hou, Dr Lianping
• Authors: Xiang, S., Shi, Y., Guo, X., Zhang, Y., Wang, H., Zheng, D., Song, Z., Han, Y., Gao, S., Zhao, S., Gu, B., Wang, H., Zhu, X., Hou, L., Chen, X., Zheng, W., Ma, X., and Hao, Y.
• College/School: College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
• Journal Name: Optica
• Publisher: The Optical Society
• ISSN: 2334-2536
• ISSN (Online): 2334-2536
• Published Online: 24 January 2023
• Copyright Holders: Copyright © 2023 Optica Publishing Group
• First Published: First published in Optica 2023
• Publisher Policy: Reproduced under the terms of the Optica Open Access Publishing Agreement