Subwavelength neuromorphic nanophotonic integrated circuits for spike-based computing : challenges and prospects

Romeira, B. and Nieder, J. B. and Jacob, B. and Adão, R. M. R. and Camarneiro, F. and Alanis, J. Arturo and Hejda, M. and Hurtado, A. and Lourenço, J. and Castro Alves, D. and Figueiredo, J. M. L. and Ortega-Piwonka, I. and Javaloyes, J.; (2021) Subwavelength neuromorphic nanophotonic integrated circuits for spike-based computing : challenges and prospects. In: Proceedings Volume 11804, Emerging Topics in Artificial Intelligence (ETAI) 2021. Emerging Topics in Artificial Intelligence, 11804 . SPIE, USA. ISBN 9781510644472 (https://doi.org/10.1117/12.2591852)

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Abstract

Event-activated biological-inspired subwavelength (sub-λ) optical neural networks are of paramount importance for energy-efficient and high-bandwidth artificial intelligence (AI) systems. Despite the significant advances to build active optical artificial neurons using for example phase-change materials, lasers, photodetectors, and modulators, miniaturized integrated sources and detectors suited for few-photon spike-based operation and of interest for neuromorphic optical computing are still lacking. In this invited paper we outline the main challenges, opportunities, and recent results towards the development of interconnected neuromorphic nanoscale light-emitting diodes (nanoLEDs) as key-enabling artificial spiking neuron circuits in photonic neural networks. This method of spike generation in neuromorphic nanoLEDs paves the way for sub-λ incoherent neural circuits for fast and efficient asynchronous brain-inspired computation.

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