2023/07/31 by Jacek Gosciniak, Gosciniak, Jacek, Jacob B. Khurgin +1 · 1 citation
Engineering · Computer Science · #Photonic and Optical Devices #Neural Networks and Reservoir Computing #Advanced Memory and Neural Computing
paper · pdf · doi:10.48550/arxiv.2308.00178
Fully CMOS-compatible photonic memory holding devices hold a potential in a 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 the electronic processing. To satisfy all these requirements a new 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.