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arXiv · 2110.01617

Ultrafast Neuromorphic Photonic Image Processing with a VCSEL Neuron

Joshua Robertson·Paul Kirkland·Juan Arturo Alanis·Matěj Hejda·Julián Bueno·Gaetano Di Caterina·Antonio Hurtado
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Abstract

The ever-increasing demand for Artificial Intelligence (AI) systems is underlining a significant requirement for new, AI-optimised hardware. Neuromorphic (brain-like) processors are one highly-promising solution, with photonic-enabled realizations receiving increasing attention. Among these, approaches based upon Vertical Cavity Surface Emitting Lasers (VCSELs) are attracting interest given their favourable attributes and mature technology. Here, we demonstrate a hardware-friendly neuromorphic photonic spike processor, using a single VCSEL, for all-optical image edge-feature detection. This exploits the ability of a VCSEL-based photonic neuron to integrate temporally-encoded pixel data at high speed; and fire fast (100ps-long) optical spikes upon detecting desired image features. Furthermore, the photonic system is combined with a software-implemented spiking neural network yielding a full platform for complex image classification tasks. This work therefore highlights the potentials of VCSEL-based platforms for novel, ultrafast, all-optical neuromorphic processors interfacing with current computation and communication systems for use in future light-enabled AI and computer vision functionalities.

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Joshua Robertson, Paul Kirkland, Juan Arturo Alanis, Matěj Hejda, Julián Bueno, Gaetano Di Caterina, Antonio Hurtado. 2021-10-04. Ultrafast Neuromorphic Photonic Image Processing with a VCSEL Neuron. https://arxiv.org/abs/2110.01617

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