用深度学习来解释和设计复杂的纳米光子结构

A. Raman
{"title":"用深度学习来解释和设计复杂的纳米光子结构","authors":"A. Raman","doi":"10.1117/12.2595477","DOIUrl":null,"url":null,"abstract":"A central challenge in the development of nanophotonic structures and metamaterials is identifying the optimal design for a target functionality and understanding the physical mechanisms that enable the optimized device’s capabilities. In this talk, we will describe deep learning-driven strategies to both design complex nanophotonic structures, including across multiple device categories, as well as understand their behavior. We will highlight potential pathways to making deep learning a tool for global inverse design across multiple device categories, while also opening up the 'black box' of the machine learning algorithm to understand why a particular optimized design works well.","PeriodicalId":389503,"journal":{"name":"Metamaterials, Metadevices, and Metasystems 2021","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Deep learning to explain and design complex nanophotonic structures\",\"authors\":\"A. Raman\",\"doi\":\"10.1117/12.2595477\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A central challenge in the development of nanophotonic structures and metamaterials is identifying the optimal design for a target functionality and understanding the physical mechanisms that enable the optimized device’s capabilities. In this talk, we will describe deep learning-driven strategies to both design complex nanophotonic structures, including across multiple device categories, as well as understand their behavior. We will highlight potential pathways to making deep learning a tool for global inverse design across multiple device categories, while also opening up the 'black box' of the machine learning algorithm to understand why a particular optimized design works well.\",\"PeriodicalId\":389503,\"journal\":{\"name\":\"Metamaterials, Metadevices, and Metasystems 2021\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Metamaterials, Metadevices, and Metasystems 2021\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2595477\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Metamaterials, Metadevices, and Metasystems 2021","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2595477","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

纳米光子结构和超材料发展的一个核心挑战是确定目标功能的最佳设计,并了解实现优化设备功能的物理机制。在这次演讲中,我们将描述深度学习驱动的策略,以设计复杂的纳米光子结构,包括跨多个设备类别,以及理解它们的行为。我们将重点介绍使深度学习成为跨多个设备类别的全局逆向设计工具的潜在途径,同时也将打开机器学习算法的“黑匣子”,以了解为什么特定的优化设计效果良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Deep learning to explain and design complex nanophotonic structures
A central challenge in the development of nanophotonic structures and metamaterials is identifying the optimal design for a target functionality and understanding the physical mechanisms that enable the optimized device’s capabilities. In this talk, we will describe deep learning-driven strategies to both design complex nanophotonic structures, including across multiple device categories, as well as understand their behavior. We will highlight potential pathways to making deep learning a tool for global inverse design across multiple device categories, while also opening up the 'black box' of the machine learning algorithm to understand why a particular optimized design works well.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Disrupting the photonics innovation cycle with data- and physics-driven algorithms Revealing the energy spectrum of plasmonic hot-carriers via single molecule transport measurements Engineered epsilon-near-zero metafilm with Ag-SiNx multilayer structure Surface roughness simulation in topologically complex optical metadevices and metasystems Designing hybrid lenses using metaoptics for enhanced optical performance
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1