Temporal information processing with an integrated laser neuron

Hsuan Tung Peng, Gerasimos Angelatos, Thomas Ferreira de Lima, Mitchell A. Nahmias, Alexander N. Tait, Siamak Abbaslou, Bhavin J. Shastri, Paul R. Prucnal

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

Spiking neural networks enable efficient information processing in real-time. Excitable lasers can exhibit ultrafast spiking dynamics, and when preceded by a photodetector in an O/E/O link, can process optical spikes at different wavelengths and thus be interconnected in large neural networks. Here, we experimentally demonstrate and numerically simulate the spiking dynamics of a laser neuron fabricated in a photonic integrated circuit. Our spiking laser neuron is shown to perform coincidence detection with nanosecond time resolution, and we observe refractory periods in the order of 0.1 ns. We propose a method to implement XOR classification using our laser neurons, and simulations of the resultant dynamics indicate robust tolerance to timing jitter.

Original languageEnglish (US)
Article number8760358
JournalIEEE Journal of Selected Topics in Quantum Electronics
Volume26
Issue number1
DOIs
StatePublished - Jan 1 2020

All Science Journal Classification (ASJC) codes

  • Atomic and Molecular Physics, and Optics
  • Electrical and Electronic Engineering

Keywords

  • Excitable lasers
  • IndexTerms-Neuromorphicphotonics
  • Photonic neural networks
  • Photonicintegratedcircuits
  • Spiking neural networks

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