非線形散乱媒体を利用した光暗号化、計算、機械学習(Exploiting Nonlinear Scattering Medium for Optical Encryption, Computation, and Machine Learning)

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非線形散乱媒体の光学応答を解読する: スケーラブルな物理演算子への飛躍 Decoding the Optical Response of Nonlinear Scattering Media: A Leap Towards Highly Scalable Physical Operators

2023-08-02 韓国基礎科学研究院(IBS)

◆シンガポール国立大学(NUS)のチームが、散乱媒体を光学的な計算や機械学習に利用する方法を発見しました。従来、散乱媒体の情報は「混乱」しており、簡単な線形行列で表現できませんでしたが、この研究では非線形散乱媒体の光学入出力応答を3次テンソルで定義できることがわかりました。
◆バリウムチタン酸バリウムナノ粒子を使ってこの現象を実証し、非線形光学暗号化や全光論理ゲートを実現することに成功しました。この研究は光学計算や機械学習の新たな展望を開くものであり、特に非線形光学層はモデルの性能向上に重要です。これらの成果はオプティカルコンピューティングと機械学習の分野に革新的な応用をもたらすことが期待されています。

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乱れた非線形媒質の散乱テンソルを測定する Measuring the scattering tensor of a disordered nonlinear medium

Jungho Moon,Ye-Chan Cho,Sungsam Kang,Mooseok Jang & Wonshik Choi
Nature Physics  Published:31 July 2023
DOI:https://doi.org/10.1038/s41567-023-02163-8

extended data figure 1

Abstract

A complex scattering medium offers spatial mixing of the incoming waves via numerous randomly wired channels, making it act as a unique linear optical operator. However, its use as a nonlinear operator has been unexplored due to the difficulty in formulating the nonlinear wave–medium interaction. Here we present a theoretical framework and experimental proof that a third-order scattering tensor completely describes the input–output response of a nonlinear scattering medium made of second-harmonic-generation nanoparticles. The rank of the nonlinear scattering tensor is higher than that of a second-order scattering tensor describing a linear scattering medium, scaling with the number of the spatially orthogonal illumination channels. We implement the inverse of the nonlinear scattering tensor by tensor reshaping and minimization operation, which enables us to retrieve the original incident wave from the speckled nonlinear wave. Using the increased rank of the scattering tensor along with its inverse operation, we demonstrate that the disordered nonlinear medium can be used as a highly scalable nonlinear optical operator for optical encryptions, all-optical multichannel logic AND gates, and optical kernel methods in machine learning.

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