Laser & Optoelectronics Progress, Volume. 62, Issue 17, 1739011(2025)
Research Progress of Photonic Spiking Neural Networks (Invited)
The rapid development of the new generation of information technology, such as generative artificial intelligence, large models, and deep learning, has led to explosive growth in global data traffic, which puts forward higher requirements for computing power and energy consumption. Brain-inspired computing is committed to using the brain's structure, function and low-power information processing mechanism for reference to develop new information processing modes, computing models, algorithms and intelligent systems to effectively alleviate the current pressure on computing power and energy consumption. Among them, pulse neural network has many advantages, such as sparse coding, low power consumption, outstanding spatio-temporal information processing ability, and biological rationality. Optical pulse neural network further integrates the advantages of pulse neural network and photonics, such as high speed, large bandwidth, low energy consumption, and strong parallel processing ability, and has become a hot research topic. This paper reviews the work of major research teams at home and abroad in the modeling of photonic pulse neurons, device development and dynamic characteristics research, the model architecture of photonic pulse neural networks, integrated chips and other aspects, and looks forward to the challenges and future development directions.
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Yahui Zhang, Shuiying Xiang, Xingxing Guo, Yanan Han, Changjian Xie, Tao Wang, Yue Hao. Research Progress of Photonic Spiking Neural Networks (Invited)[J]. Laser & Optoelectronics Progress, 2025, 62(17): 1739011
Category: AI for Optics
Received: Apr. 16, 2025
Accepted: Jun. 19, 2025
Published Online: Sep. 12, 2025
The Author Email: Shuiying Xiang (syxiang@xidian.edu.cn)
CSTR:32186.14.LOP251019