Neuromorphic encoding of image pixel data into rate-coded optical spike trains with a photonic VCSEL-neuron

Hejda, Matej and Robertson, Joshua and Bueno, Julian and Alanis, Juan and Hurtado, Antonio (2021) Neuromorphic encoding of image pixel data into rate-coded optical spike trains with a photonic VCSEL-neuron. APL Photonics, 6 (6). 060802. ISSN 2378-0967 (https://doi.org/10.1063/5.0048674)

[thumbnail of Hejda-etal-APL-2021-Neuromorphic-encoding-of-image-pixel-data-into-rate-coded]
Preview
 Text. Filename: Hejda_etal_APL_2021_Neuromorphic_encoding_of_image_pixel_data_into_rate_coded.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo
Download (7MB)| Preview

Abstract

Driven by the increasing significance of artificial intelligence, the field of neuromorphic (brain-inspired) photonics is attracting increasing interest, promising new, high-speed, and energy-efficient computing hardware for key applications in information processing and computer vision. Widely available photonic devices, such as vertical-cavity surface emitting lasers (VCSELs), offer highly desirable properties for photonic implementations of neuromorphic systems, such as high-speed and low energy operation, neuron-like dynamical responses, and ease of integration into chip-scale systems. Here, we experimentally demonstrate encoding of digital image data into continuous, rate-coded, up to GHz-speed optical spike trains with a VCSEL-based photonic spiking neuron. Moreover, our solution makes use of off-the-shelf fiber-optic components with operation at telecom wavelengths, therefore making the system compatible with current optical network and data center technologies. This VCSEL-based spiking encoder paves the way toward optical spike-based data processing and ultrafast neuromorphic vision systems.

ORCID iDs

Hejda, Matej ORCID logoORCID: https://orcid.org/0000-0003-4493-9426, Robertson, Joshua, Bueno, Julian, Alanis, Juan and Hurtado, Antonio ORCID logoORCID: https://orcid.org/0000-0002-4448-9034;
CORE (COnnecting REpositories)