Transparent conductive oxides as a material platform for a realization of all-optical photonic neural networks.

Journal: Scientific reports
Published Date:

Abstract

Photonics integrated circuits have an enormous potential to serve as a framework for a new class of information processing machines and can enable ultrafast artificial neural networks. They can overcome the existing speed and power limits of the electronic processing elements and provide additional benefits of photonics such as high-bandwidth, sub-nanosecond latencies and low-energy interconnect credentials leading to a new paradigm called neuromorphic photonics. The main obstacle to realizing such a task is a lack of proper material platform that imposes serious requirements on the architecture of the network. Here we suggest and justify that transparent conductive oxides can be an excellent candidate for such a task as they provide nonlinearity and bistability under both optical and electrical inputs.

Authors

  • Jacek Gosciniak
    Institute of Microelectronics and Optoelectronics, Warsaw University of Technology, Koszykowa 75, 00-662, Warsaw, Poland. jacek.gosciniak@pw.edu.pl.
  • Jacob B Khurgin
    Electrical and Computer Engineering Department, Johns Hopkins University, Baltimore, MD, 21218, USA.

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