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Main Authors: Honda, Yoshihiro, Shoji, Yuya, Amemiya, Tomohiro
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2408.13129
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author Honda, Yoshihiro
Shoji, Yuya
Amemiya, Tomohiro
author_facet Honda, Yoshihiro
Shoji, Yuya
Amemiya, Tomohiro
contents In this study, we experimentally demonstrated that the nonlinear optical coefficient of the original Si can be enhanced by incorporating a metamaterial structure into an existing silicon waveguide. The two-photon absorption coefficient enhanced by the metamaterial structure was 424 cm/GW, which is 1.2x10^3 times higher than that of Si. Using this metamaterial waveguide-based nonlinear optical activation function, we achieved a high inference accuracy of 98.36% in the handwritten character recognition task, comparable to that obtained with the ReLU function as the activation function. Therefore, our approach can contribute to the realization of more power-efficient and compact all-optical neural networks.
format Preprint
id arxiv_https___arxiv_org_abs_2408_13129
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Optical activation function using a metamaterial waveguide for an all-optical neural network
Honda, Yoshihiro
Shoji, Yuya
Amemiya, Tomohiro
Optics
Applied Physics
In this study, we experimentally demonstrated that the nonlinear optical coefficient of the original Si can be enhanced by incorporating a metamaterial structure into an existing silicon waveguide. The two-photon absorption coefficient enhanced by the metamaterial structure was 424 cm/GW, which is 1.2x10^3 times higher than that of Si. Using this metamaterial waveguide-based nonlinear optical activation function, we achieved a high inference accuracy of 98.36% in the handwritten character recognition task, comparable to that obtained with the ReLU function as the activation function. Therefore, our approach can contribute to the realization of more power-efficient and compact all-optical neural networks.
title Optical activation function using a metamaterial waveguide for an all-optical neural network
topic Optics
Applied Physics
url https://arxiv.org/abs/2408.13129