Optical Extreme Learning Machines with Atomic Vapors

Atoms Pub Date : 2024-01-08 DOI:10.3390/atoms12020010
Nuno A Silva, Vicente Rocha, Tiago D. Ferreira
{"title":"Optical Extreme Learning Machines with Atomic Vapors","authors":"Nuno A Silva, Vicente Rocha, Tiago D. Ferreira","doi":"10.3390/atoms12020010","DOIUrl":null,"url":null,"abstract":"Extreme learning machines explore nonlinear random projections to perform computing tasks on high-dimensional output spaces. Since training only occurs at the output layer, the approach has the potential to speed up the training process and the capacity to turn any physical system into a computing platform. Yet, requiring strong nonlinear dynamics, optical solutions operating at fast processing rates and low power can be hard to achieve with conventional nonlinear optical materials. In this context, this manuscript explores the possibility of using atomic gases in near-resonant conditions to implement an optical extreme learning machine leveraging their enhanced nonlinear optical properties. Our results suggest that these systems have the potential not only to work as an optical extreme learning machine but also to perform these computations at the few-photon level, paving opportunities for energy-efficient computing solutions.","PeriodicalId":502621,"journal":{"name":"Atoms","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atoms","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/atoms12020010","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Extreme learning machines explore nonlinear random projections to perform computing tasks on high-dimensional output spaces. Since training only occurs at the output layer, the approach has the potential to speed up the training process and the capacity to turn any physical system into a computing platform. Yet, requiring strong nonlinear dynamics, optical solutions operating at fast processing rates and low power can be hard to achieve with conventional nonlinear optical materials. In this context, this manuscript explores the possibility of using atomic gases in near-resonant conditions to implement an optical extreme learning machine leveraging their enhanced nonlinear optical properties. Our results suggest that these systems have the potential not only to work as an optical extreme learning machine but also to perform these computations at the few-photon level, paving opportunities for energy-efficient computing solutions.
利用原子蒸汽的光学极限学习机
极限学习机探索非线性随机投影,在高维输出空间执行计算任务。由于训练只发生在输出层,因此这种方法有可能加快训练过程,并有能力将任何物理系统转化为计算平台。然而,由于需要强大的非线性动力学,传统的非线性光学材料很难实现快速处理速度和低功耗的光学解决方案。在这种情况下,本手稿探讨了在近共振条件下利用原子气体的增强非线性光学特性实现光学极端学习机的可能性。我们的研究结果表明,这些系统不仅具有作为光学极限学习机的潜力,而且还能在少光子水平上执行这些计算,从而为高能效计算解决方案铺平道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信