Transparent conductive oxides and low-loss nitride-rich silicon waveguides as building blocks for neuromorphic photonics

Abstract

Fully CMOS-compatible photonic memory holding devices hold a potential in the development of ultrafast artificial neural networks. Leveraging the benefits of photonics such as high-bandwidth, low latencies, low-energy interconnect, and high speed, they can overcome the existing limits of electronic processing. To satisfy all these requirements, a photonic platform is proposed that combines low-loss nitride-rich silicon as a guide and low-loss transparent conductive oxides as an active material that can provide high nonlinearity and bistability under both electrical and optical signals.