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

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...

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Veröffentlicht in:	Applied physics letters 2023-11, Vol.123 (22)
Hauptverfasser:	Gosciniak, Jacek, Khurgin, Jacob B.
Format:	Artikel
Sprache:	eng
Schlagworte:	Applied physics Artificial neural networks Holding devices Memory devices Nitrides Optical communication Photonics Silicon Waveguides
Online-Zugang:	Volltext
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