Towards neuromorphic photonic networks of ultrafast spiking laser neurons

Robertson, J. and Wade, E. and Kopp, Y. and Bueno, J. and Hurtado, A. (2020) Towards neuromorphic photonic networks of ultrafast spiking laser neurons. IEEE Journal of Selected Topics in Quantum Electronics, 26 (1). 7700715. ISSN 0792-1233 (https://doi.org/10.1109/JSTQE.2019.2931215)

[thumbnail of Robertson-etal-JSTQE-2019-Towards-neuromorphic-photonic-networks-of-ultrafast]
Preview
Text. Filename: Robertson_etal_JSTQE_2019_Towards_neuromorphic_photonic_networks_of_ultrafast.pdf
Accepted Author Manuscript

Download (1MB)| Preview

Abstract

We report on ultrafast artificial laser neurons and on their potentials for future neuromorphic (brain-like) photonic information processing systems. We introduce our recent and ongoing activities demonstrating controllable excitation of spiking signals in optical neurons based upon Vertical-Cavity Surface Emitting Lasers (VCSEL-Neurons). These spiking regimes are analogous to those exhibited by biological neurons, but at sub-nanosecond speeds (>7 orders of magnitude faster). We also describe diverse approaches, based on optical or electronic excitation techniques, for the activation/inhibition of sub-ns spiking signals in VCSEL-Neurons. We report our work demonstrating the communication of spiking patterns between VCSEL-Neurons towards future implementations of optical neuromorphic networks. Furthermore, new findings show that VCSEL-Neurons can perform multiple neuro-inspired spike processing tasks. We experimentally demonstrate photonic spiking memory modules using single and mutually-coupled VCSEL-Neurons. Additionally, the ultrafast emulation of neuronal circuits in the retina using VCSEL-Neuron systems is demonstrated experimentally for the first time to our knowledge. Our results are obtained with off-the-shelf VCSELs operating at the telecom wavelengths of 1310 and 1550 nm. This makes our approach fully compatible with current optical network and data centre technologies; hence offering great potentials for future ultrafast neuromorphic laser-neuron networks for new paradigms in brain-inspired computing and Artificial Intelligence.

ORCID iDs

Robertson, J., Wade, E., Kopp, Y., Bueno, J. and Hurtado, A. ORCID logoORCID: https://orcid.org/0000-0002-4448-9034;