Literature DB >> 29715770

Numerical demonstration of neuromorphic computing with photonic crystal cavities.

Floris Laporte, Andrew Katumba, Joni Dambre, Peter Bienstman.   

Abstract

We propose a new design for a passive photonic reservoir computer on a silicon photonics chip which can be used in the context of optical communication applications, and study it through detailed numerical simulations. The design consists of a photonic crystal cavity with a quarter-stadium shape, which is known to foster interesting mixing dynamics. These mixing properties turn out to be very useful for memory-dependent optical signal processing tasks, such as header recognition. The proposed, ultra-compact photonic crystal cavity exhibits a memory of up to 6 bits, while simultaneously accepting bitrates in a wide region of operation. Moreover, because of the inherent low losses in a high-Q photonic crystal cavity, the proposed design is very power efficient.

Year:  2018        PMID: 29715770     DOI: 10.1364/OE.26.007955

Source DB:  PubMed          Journal:  Opt Express        ISSN: 1094-4087            Impact factor:   3.894


  7 in total

1.  Wave physics as an analog recurrent neural network.

Authors:  Tyler W Hughes; Ian A D Williamson; Momchil Minkov; Shanhui Fan
Journal:  Sci Adv       Date:  2019-12-20       Impact factor: 14.136

2.  Addressing limited weight resolution in a fully optical neuromorphic reservoir computing readout.

Authors:  Chonghuai Ma; Floris Laporte; Joni Dambre; Peter Bienstman
Journal:  Sci Rep       Date:  2021-02-04       Impact factor: 4.379

3.  Simulating self-learning in photorefractive optical reservoir computers.

Authors:  Floris Laporte; Joni Dambre; Peter Bienstman
Journal:  Sci Rep       Date:  2021-01-29       Impact factor: 4.379

4.  Comparing different nonlinearities in readout systems for optical neuromorphic computing networks.

Authors:  Chonghuai Ma; Joris Lambrecht; Floris Laporte; Xin Yin; Joni Dambre; Peter Bienstman
Journal:  Sci Rep       Date:  2021-12-17       Impact factor: 4.379

5.  A Comprehensive Survey on Nanophotonic Neural Networks: Architectures, Training Methods, Optimization, and Activations Functions.

Authors:  Konstantinos Demertzis; Georgios D Papadopoulos; Lazaros Iliadis; Lykourgos Magafas
Journal:  Sensors (Basel)       Date:  2022-01-18       Impact factor: 3.576

Review 6.  Nanosystems, Edge Computing, and the Next Generation Computing Systems.

Authors:  Ali Passian; Neena Imam
Journal:  Sensors (Basel)       Date:  2019-09-19       Impact factor: 3.576

7.  Reservoir computing based on a silicon microring and time multiplexing for binary and analog operations.

Authors:  Massimo Borghi; Stefano Biasi; Lorenzo Pavesi
Journal:  Sci Rep       Date:  2021-08-02       Impact factor: 4.379

  7 in total

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