Diffraction casting  

作　　者：Ryosuke Mashiko Makoto Naruse Ryoichi Horisaki 

机构地区：[1]The University of Tokyo,Graduate School of Information Science and Technology,Department of Information Physics and Computing,Tokyo,Japan

出　　处：《Advanced Photonics》2024年第5期81-94,共14页先进光子学(英文)

基　　金：supported by Japan Society for the Promotion of Science(Grant Nos.JP20K05361,JP22H05197,and JP23K26567).

摘　　要：Optical computing is considered a promising solution for the growing demand for parallel computing in various cutting-edge fields that require high integration and high-speed computational capacity.We propose an optical computation architecture called diffraction casting(DC)for flexible and scalable parallel logic operations.In DC,a diffractive neural network is designed for single instruction,multiple data(SIMD)operations.This approach allows for the alteration of logic operations simply by changing the illumination patterns.Furthermore,it eliminates the need for encoding and decoding of the input and output,respectively,by introducing a buffer around the input area,facilitating end-to-end all-optical computing.We numerically demonstrate DC by performing all 16 logic operations on two arbitrary 256-bit parallel binary inputs.Additionally,we showcase several distinctive attributes inherent in DC,such as the benefit of cohesively designing the diffractive elements for SIMD logic operations that assure high scalability and high integration capability.Our study offers a design architecture for optical computers and paves the way for a next-generation optical computing paradigm.

关 键 词：optical computing diffractive neural network SIMD operations parallel computing logic operations machine learning 

分 类 号：O436.1[机械工程—光学工程]