Article
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Photonic Multiplexing Techniques for Optical Neuromorphic Computing
Version 1
: Received: 26 August 2022 / Approved: 29 August 2022 / Online: 29 August 2022 (07:20:07 CEST)
How to cite: Moss, D. Photonic Multiplexing Techniques for Optical Neuromorphic Computing. Preprints 2022, 2022080470. https://doi.org/10.20944/preprints202208.0470.v1 Moss, D. Photonic Multiplexing Techniques for Optical Neuromorphic Computing. Preprints 2022, 2022080470. https://doi.org/10.20944/preprints202208.0470.v1
Abstract
The simultaneous advances in artificial neural networks and photonic integration technologies have spurred extensive research in optical computing and optical neural networks (ONNs). The potential to simultaneously exploit multiple physical dimensions of time, wavelength and space give ONNs the ability to achieve computing operations with high parallelism and large-data throughput. Different photonic multiplexing techniques based on these multiple degrees of freedom have enabled ONNs with large-scale interconnectivity and linear computing functions. Here, we review the recent advances of ONNs based on different approaches to photonic multiplexing, and present our outlook on key technologies needed to further advance these photonic multiplexing/hybrid-multiplexing techniques of ONNs.
Keywords
optical neural network; photonic multiplexing; optical computing operation; integrated optics
Subject
Physical Sciences, Optics and Photonics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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