Zhang, W., Hejda, M., Malysheva, E., Al-taai, Q. , Javaloyes, J., Wasige, E. , Figueiredo, J. M. L., Calzadilla, V., Romeira, B. and Hurtado, A. (2023) Tuneable presynaptic weighting in optoelectronic spiking neurons built with laser-coupled resonant tunneling diodes. Journal of Physics D: Applied Physics, 56, 084001. (doi: 10.1088/1361-6463/aca914)
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Abstract
Optoelectronic spiking neurons are regarded as highly promising systems for novel light-powered neuromorphic computing hardware. Here, we investigate an optoelectronic (O/E/O) spiking neuron built with an excitable resonant tunnelling diode (RTD) coupled to a photodetector and a vertical-cavity surface-emitting laser (VCSEL). This work provides the first experimental report on the control of the amplitude (weighting factor) of the fired optical spikes directly in the neuron, introducing a simple way for presynaptic spike amplitude tuning. Notably, a very simple mechanism (the control of VCSEL bias) is used to tune the amplitude of the spikes fired by the optoelectronic neuron, hence enabling an easy and high-speed option for the weighting of optical spiking signals in future interconnected photonic spike-processing nodes. Furthermore, we validate the feasibility of this layout using a simulation of a monolithically-integrated, RTD-powered, nanoscale optoelectronic spiking neuron model, confirming the system's potential for delivering weighted optical spiking signals at very high speeds (GHz firing rates). These results demonstrate the high degree of flexibility of RTD-based artificial optoelectronic spiking neurons and highlight their potential towards compact, high-speed and low-energy photonic spiking neural networks for use in future, light-enabled neuromorphic hardware.
Item Type: | Articles |
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Additional Information: | The authors acknowledge support by the European Commission (Grant 828841-ChipAI-H2020-FETOPEN-2018-2020) and by the UK Research and Innovation (UKRI) Turing AI Acceleration Fellowships Programme (EP/V025198/1). |
Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Wasige, Professor Edward and Al-Taai, Dr Qusay and ZHANG, WEIKANG and Javaloyes, Dr Julien |
Authors: | Zhang, W., Hejda, M., Malysheva, E., Al-taai, Q., Javaloyes, J., Wasige, E., Figueiredo, J. M. L., Calzadilla, V., Romeira, B., and Hurtado, A. |
College/School: | College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering |
Journal Name: | Journal of Physics D: Applied Physics |
Publisher: | IOP Publishing |
ISSN: | 0022-3727 |
ISSN (Online): | 1361-6463 |
Published Online: | 06 December 2022 |
Copyright Holders: | Copyright © 2022 The Authors |
First Published: | First published in Journal of Physics D: Applied Physics 56:084001 |
Publisher Policy: | Reproduced under a Creative Commons License |
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