Scalable and efficient coherent photonic unit cell for time-multiplexed multiplication and correlation detection

Sadra Rahimi Kari; Dominique Pantin; Nathan Youngblood

doi:10.1117/12.2649510

17 March 2023 Scalable and efficient coherent photonic unit cell for time-multiplexed multiplication and correlation detection

Sadra Rahimi Kari, Dominique Pantin, Nathan Youngblood

Author Affiliations +

Proceedings Volume PC12438, AI and Optical Data Sciences IV; PC1243803 (2023) https://doi.org/10.1117/12.2649510
Event: SPIE OPTO, 2023, San Francisco, California, United States

Abstract

Recent developments in the field of artificial intelligence have become a significant computational burden for current electronic hardware. In order to keep up with the increasing advancements in deep learning research, novel approaches to computation are required to address the slowing progress in computing performance and efficiency of electronic hardware. We will present our experimental results on a general-purpose optical processor that takes advantage of time multiplexing in integrated photonics and can perform not only dot products but also real-time correlation detection on stochastic bitstreams. This approach to optical processing has a significant compute efficiency advantage for long-bit sequences.

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Citation Download Citation

Sadra Rahimi Kari, Dominique Pantin, and Nathan Youngblood "Scalable and efficient coherent photonic unit cell for time-multiplexed multiplication and correlation detection", Proc. SPIE PC12438, AI and Optical Data Sciences IV, PC1243803 (17 March 2023); https://doi.org/10.1117/12.2649510

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