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

Xiang, Shuiying; Shi, Yuechun; Guo, Xingxing; ZHANG, YAHUI; Wang, Hongji; ZHENG, DIAN ZHUANG; Song, Ziwei; Han, Yanan; Gao, Shuang; Zhao, Shihao; Gu, Biling; WANG, Hailing; Zhu, Xiaojun; Hou, Lianping; Chen, Xiangfei; Zheng, Wanhua; Ma, Xiaohua; Hao, Yue

doi:10.1364/optica.468347

Cited by 50 publications

(3 citation statements)

References 66 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this paper, we numerically investigate the occurrence and evolution of EEs in the chaotic output of a multimode Fabry-Perot (FP) laser with optical feedback. Benefiting from multiple longitudinal lasing modes, Fabry-Perot lasers have been widely investigated in different fields such as reinforcement learning [20], reservoir computing [21], secure communications [22], and biological neurons [23]. As we know, the appearance of EEs in the chaotic output may degrade the performance of the chaos-based applications mentioned above.…”

Section: Introductionmentioning

confidence: 99%

Characterizing Extreme Events in a Fabry–Perot Laser with Optical Feedback

Ge,

Huang,

et al. 2024

Photonics

View full text Add to dashboard Cite

The study of extreme events (EEs) in photonics has expanded significantly due to straightforward implementation conditions. EEs have not been discussed systematically, to the best of our knowledge, in the chaotic dynamics of a Fabry–Perot laser with optical feedback, so we address this in the current contribution. Herein, we not only find EEs in all modes but also divide the EEs in total output into two categories for further discussion. The two types of EEs have similar statistical features to conventional rogue waves. The occurrence probability of EEs undergoes a saturation effect as the feedback strength increases. Additionally, we analyze the influence of feedback strength, feedback delay, and pump current on the probability of EEs defined by two criteria of EEs and find similar trends. We hope that this work contributes to a deep understanding and serves as inspiration for further research into various multimode semiconductor laser systems.

show abstract

Section: Introductionmentioning

confidence: 99%

Characterizing Extreme Events in a Fabry–Perot Laser with Optical Feedback

Ge,

Huang,

et al. 2024

Photonics

View full text Add to dashboard Cite

show abstract

“…An excitable LIF neuron can be physically realized using a vertical-cavity surface-emitting laser (VCSEL) combined with a saturable absorber (SA) in a cavity structure [14]. A photonic spiking neuron chip, based on an integrated Fabry-Perot laser with a saturable absorber (FP-SA), is capable of performing classification tasks using a supervised learning algorithm [15]. The integration of lasers and saturable absorption materials, such as graphene [14,16] and C 60 [17], enables simulation of the inference process using externally imported weighted spikes.…”

Section: Introductionmentioning

confidence: 99%

Neuromorphic Photonics Based on Phase Change Materials

Wang

et al. 2023

Nanomaterials

View full text Add to dashboard Cite

Neuromorphic photonics devices based on phase change materials (PCMs) and silicon photonics technology have emerged as promising solutions for addressing the limitations of traditional spiking neural networks in terms of scalability, response delay, and energy consumption. In this review, we provide a comprehensive analysis of various PCMs used in neuromorphic devices, comparing their optical properties and discussing their applications. We explore materials such as GST (Ge2Sb2Te5), GeTe-Sb2Te3, GSST (Ge2Sb2Se4Te1), Sb2S3/Sb2Se3, Sc0.2Sb2Te3 (SST), and In2Se3, highlighting their advantages and challenges in terms of erasure power consumption, response rate, material lifetime, and on-chip insertion loss. By investigating the integration of different PCMs with silicon-based optoelectronics, this review aims to identify potential breakthroughs in computational performance and scalability of photonic spiking neural networks. Further research and development are essential to optimize these materials and overcome their limitations, paving the way for more efficient and high-performance photonic neuromorphic devices in artificial intelligence and high-performance computing applications.

show abstract

“…[12] Recently, photonic www.lpr-journal.org neuromorphic systems have achieved significant advancements. Some photonic devices for photonic neuromorphic computing are being investigated, [26][27][28][29][30][31][32][33][34][35] such as semiconductor optical amplifiers, [29] Mach-Zehnder interferometer, [30] mirroring resonators, [31] distributed feedback laser, [32] Fabry-Pérot laser with a saturable absorber, [33] hybrid resonant tunneling diode circuits, [34] and quantum resonant tunneling. [35] Some semiconductor lasers have been demonstrated to function as photonic spiking neurons.…”

Section: Introductionmentioning

confidence: 99%

Hardware Implementation of Ultra‐Fast Obstacle Avoidance Based on a Single Photonic Spiking Neuron

Gao,

Xiang,

Song

et al. 2023

Laser & Photonics Reviews

Self Cite

View full text Add to dashboard Cite

Visual obstacle avoidance is widely applied to unmanned aerial vehicles (UAVs) and mobile robot fields. A simple system architecture, low power consumption, optimized processing, and real‐time performance are extremely needed due to the limited payload of some mini UAVs. To address these issues, an obstacle avoidance system harnessing the rate encoding features of a photonic spiking neuron based on a Fabry–Pérot (FP) laser is proposed, which simulates the monocular vision. Here, time to collision is used to describe the distance of obstacles. The experimental results show that the FP laser excites ultra‐fast spike responses in real time for the following cases, facilitating the generation of control commands by motor neurons to realize accurate decision‐making. Four cases of mobile obstacle avoidance scenarios, including “Constant velocity approach”, “Approach and retreat”, “The motion state involving stays”, and “Approach with different velocities”, and obstacle avoidance problems with multiple stationary obstacles appearing simultaneously are experimentally analyzed. The system exhibits a spike response rate of up to 5 GHz. This work proves the feasibility of applying the ultra‐fast photonic obstacle avoidance system to UAVs and other fields in the future and highlights the potential of photonic neuromorphic processor platforms.

show abstract

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

Cited by 50 publications

References 66 publications

Characterizing Extreme Events in a Fabry–Perot Laser with Optical Feedback

Characterizing Extreme Events in a Fabry–Perot Laser with Optical Feedback

Neuromorphic Photonics Based on Phase Change Materials

Hardware Implementation of Ultra‐Fast Obstacle Avoidance Based on a Single Photonic Spiking Neuron

Contact Info

Product

Resources

About