Spiking dynamics and synchronization properties of optical neurons based on VCSEL-SAs

Han, Yanan; Xiang, Shuiying; Song, Ziwei; Wen, Aijun

doi:10.1007/s11071-021-06699-3

Cited by 6 publications

(1 citation statement)

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“…Propagation of generated spiking events between in-series connected VCSEL-neurons has also been experimentally demonstrated [20], paving the way towards interconnected architectures of multiple VCSELbased photonic spike processing platforms. Furthermore, twosection VCSEL-SAs have been demonstrated as analogous to leaky integrate-and-fire (LIF) class neurons [21] and utilized in coupled arrangements for spike synchronization [22], pattern recognition [23], winner-takes-all algorithms [24], spike sequence learning [25] and motion detection [26].…”

Section: Introductionmentioning

confidence: 99%

Spiking Behaviour in Laterally-Coupled Pairs of VCSELs With Applications in Neuromorphic Photonics

Hejda

Vaughan

Henning

et al. 2023

IEEE J. Select. Topics Quantum Electron.

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We report a theoretical study on laterally-coupled pairs of vertical-cavity surface-emitting lasers (VCSELs) operated under conditions that generate or suppress high-speed optical spiking regimes, and show their potential in exemplar functionalities for use in photonic neuromorphic computing systems. The VCSEL numerical analysis is based on a system of five coupled mode equations, which, for the case of weak coupling, are reduced to a set of three equations that predict the saddle-node stability boundary in terms of device parameters and operating conditions. These results guide numerical simulation to demonstrate multiple neuron-like dynamics, including single-and multiple-spike emission, spiking inhibition, and rebound spiking directly in the optical domain. Importantly, these behaviours are obtained at sub-nanosecond rates, hence multiple orders of magnitude faster than the millisecond timescales of biological neurons. The mechanisms responsible are explained by reference to appropriate phase portraits. The coupled VCSELs model is then used for demonstration of high-speed, all-optical digital-tospiking encoding and for representation of digital image data using rate-coded spike trains.

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