Journal Physics D: Applied Physics, volume 56, issue 8, pages 84001

Tuneable presynaptic weighting in optoelectronic spiking neurons built with laser-coupled resonant tunneling diodes

Weikang Zhang 1
Matěj Hejda 1
Ekaterina Malysheva 2
Qusay Raghib Ali Al-Taai 3
Julien Javaloyes 4
Edward Wasige 3
Jose Alaor Figueiredo 5
Victor Dolores Calzadilla 2
B. Romeira 6
ANTONIO HURTADO 1
Publication typeJournal Article
Publication date2023-02-07
Q1
Q2
SJR0.681
CiteScore6.8
Impact factor3.1
ISSN00223727, 13616463
Surfaces, Coatings and Films
Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Acoustics and Ultrasonics
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.

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Zhang W. et al. Tuneable presynaptic weighting in optoelectronic spiking neurons built with laser-coupled resonant tunneling diodes // Journal Physics D: Applied Physics. 2023. Vol. 56. No. 8. p. 84001.
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Zhang W., Hejda M., Malysheva E., Raghib Ali Al-Taai Q., Javaloyes J., Wasige E., Figueiredo J. A., Dolores Calzadilla V., Romeira B., HURTADO A. Tuneable presynaptic weighting in optoelectronic spiking neurons built with laser-coupled resonant tunneling diodes // Journal Physics D: Applied Physics. 2023. Vol. 56. No. 8. p. 84001.
RIS |
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RIS Copy
TY - JOUR
DO - 10.1088/1361-6463/aca914
UR - https://doi.org/10.1088/1361-6463/aca914
TI - Tuneable presynaptic weighting in optoelectronic spiking neurons built with laser-coupled resonant tunneling diodes
T2 - Journal Physics D: Applied Physics
AU - Zhang, Weikang
AU - Hejda, Matěj
AU - Malysheva, Ekaterina
AU - Raghib Ali Al-Taai, Qusay
AU - Javaloyes, Julien
AU - Wasige, Edward
AU - Figueiredo, Jose Alaor
AU - Dolores Calzadilla, Victor
AU - Romeira, B.
AU - HURTADO, ANTONIO
PY - 2023
DA - 2023/02/07
PB - IOP Publishing
SP - 84001
IS - 8
VL - 56
SN - 0022-3727
SN - 1361-6463
ER -
BibTex |
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@article{2023_Zhang,
author = {Weikang Zhang and Matěj Hejda and Ekaterina Malysheva and Qusay Raghib Ali Al-Taai and Julien Javaloyes and Edward Wasige and Jose Alaor Figueiredo and Victor Dolores Calzadilla and B. Romeira and ANTONIO HURTADO},
title = {Tuneable presynaptic weighting in optoelectronic spiking neurons built with laser-coupled resonant tunneling diodes},
journal = {Journal Physics D: Applied Physics},
year = {2023},
volume = {56},
publisher = {IOP Publishing},
month = {feb},
url = {https://doi.org/10.1088/1361-6463/aca914},
number = {8},
pages = {84001},
doi = {10.1088/1361-6463/aca914}
}
MLA
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MLA Copy
Zhang, Weikang, et al. “Tuneable presynaptic weighting in optoelectronic spiking neurons built with laser-coupled resonant tunneling diodes.” Journal Physics D: Applied Physics, vol. 56, no. 8, Feb. 2023, p. 84001. https://doi.org/10.1088/1361-6463/aca914.
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