Attojoule modulators for photonic neuromorphic computing

Rubab Amin, Jonathan George, Jacob Khurgin, Tarek El-Ghazawi, Paul R. Prucnal, Volker J. Sorger

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

2 Scopus citations

Abstract

We show how the nonlinear transfer function of electrooptic modulators enables vector matrix multiplications of photonic neural networks. Here the modulators energy-per-bit function and signal-to-noise ratio are critical factors impacting system performance.

Original languageEnglish (US)
Title of host publicationCLEO
Subtitle of host publicationApplications and Technology, CLEO_AT 2018
PublisherOSA - The Optical Society
ISBN (Electronic)9781557528209
DOIs
StatePublished - Jan 1 2018
EventCLEO: Applications and Technology, CLEO_AT 2018 - San Jose, United States
Duration: May 13 2018May 18 2018

Publication series

NameOptics InfoBase Conference Papers
VolumePart F92-CLEO_AT 2018

Other

OtherCLEO: Applications and Technology, CLEO_AT 2018
CountryUnited States
CitySan Jose
Period5/13/185/18/18

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Mechanics of Materials

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  • Cite this

    Amin, R., George, J., Khurgin, J., El-Ghazawi, T., Prucnal, P. R., & Sorger, V. J. (2018). Attojoule modulators for photonic neuromorphic computing. In CLEO: Applications and Technology, CLEO_AT 2018 (Optics InfoBase Conference Papers; Vol. Part F92-CLEO_AT 2018). OSA - The Optical Society. https://doi.org/10.1364/CLEO_AT.2018.ATh1Q.4