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Neuromorphic photonics: towards ultrafast brain-inspired computing systems (Conference Presentation)
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Paper Abstract

Photonic techniques emulating the brain’s powerful computational capabilities are attracting considerable research interest as these offer promise for ultrafast operation speeds. In this talk we will review our approaches for ultrafast photonic neuronal models based upon Semiconductor Lasers, the very same devices used to transmit internet data traffic over fiber-optic telecommunication networks. We will show that a wide range of neuronal computational features, including spike activation, spiking inhibition, bursting, etc., can be optically reproduced with these devices in a controllable and reproducible way at sub-nanosecond time scales (up to 9 orders of magnitude faster than the millisecond timescales of biological neurons). Moreover, all our results are obtained using off-the-shelf, inexpensive Vertical-Cavity Surface Emitting Lasers (VCSELs) emitting at 1310 nm and 1550 nm; hence making our approach fully compatible with current optical communication technologies. Further, we will also introduce our recent work demonstrating the successful communication of sub-nanosecond spiking signals between interconnected artificial VCSEL-based photonic neurons and the potential of these systems for the ultrafast emulation of basic cortical neuronal circuits. These early results offer great prospects for novel neuromorphic (brain-like) photonic networks for brain-inspired ultrafast information processing systems going beyond traditional digital computing platforms.

Paper Details

Date Published: 8 March 2019
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Proc. SPIE 10926, Quantum Sensing and Nano Electronics and Photonics XVI, 1092604 (8 March 2019); doi: 10.1117/12.2503546
Show Author Affiliations
Antonio Hurtado, Univ. of Strathclyde (United Kingdom)
Joshua Robertson, Univ. of Strathclyde (United Kingdom)
Ewan Wade, Univ. of Strathclyde (United Kingdom)


Published in SPIE Proceedings Vol. 10926:
Quantum Sensing and Nano Electronics and Photonics XVI
Manijeh Razeghi, Editor(s)

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