Photonic architectures for in-memory computing using nonreciprocal optical materials

This invited talk will discuss various strategies for photonic in-memory computing using nonvolatile optical materials on an integrated silicon photonics platform. Both experimental demonstrations and methods for modeling large scale photonic neural networks will be presented.

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Publication Details

Published
2024-10-02
DOI
https://doi.org/10.1117/12.3027373
Primary Topic
Neural Networks and Reservoir Computing
Type
article
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article

Photonic architectures for in-memory computing using nonreciprocal optical materials

Nathan Youngblood
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Neural Networks and Reservoir Computing
article

Photonic architectures for in-memory computing using nonreciprocal optical materials

Nathan Youngblood
article en

Abstract

This invited talk will discuss various strategies for photonic in-memory computing using nonvolatile optical materials on an integrated silicon photonics platform. Both experimental demonstrations and methods for modeling large scale photonic neural networks will be presented.

University of Pittsburgh (US)
Openalex Percentile: Top 85%
Neural Networks and Reservoir Computing
DOISourceOpenAlex
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Photonic architectures for in-memory computing using nonreciprocal optical materials — Nathan Youngblood · (2024) | TGRS Research Map | TGRS