Photonic information processing at 20GS/s rates based on semiconductor lasers with delayed optical feedback

Julián Bueno, Daniel Brunner, Miguel C. Soriano, Ingo Fischer

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

Abstract

Photonic implementations of novel information processing schemes based on machine learning approaches like reservoir computing (RC) [1] have raised strong interest in the last years due to their speed and performance. A reservoir computer, conceptionally as simple as a semiconductor laser with delayed optical feedback already proved excellent performance at 5 GSamples/s rates thanks to its nonlinear responses in the GHz regime [2]. Reported bandwidths of 80GHz of semiconductor laser with optical injection [3] open the possibility of realizing photonic reservoir computers based on semiconductor lasers at high speeds. The study of the properties of the system and their impact on the RC performance is crucial to better understand the underlying physics, improve designs and tailor systems for specific tasks.
Original languageEnglish
Title of host publication2017 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC)
Place of PublicationPiscataway, NJ
PublisherIEEE
Number of pages1
ISBN (Electronic)9781509067367
DOIs
Publication statusPublished - 30 Oct 2017
EventThe European Conference on Lasers and Electro-Optics, CLEO_Europe 2017 - Munich, Germany
Duration: 25 Jun 201729 Jun 2017

Conference

ConferenceThe European Conference on Lasers and Electro-Optics, CLEO_Europe 2017
CountryGermany
CityMunich
Period25/06/1729/06/17

Keywords

  • laser feedback
  • learning (artificial intelligence)
  • optical computing
  • semiconductor lasers

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