神经网络逆设计电化学等离激元光开关
Inverse Design of Electrochemical Plasmon Optical Switching Based on Neural Network
DOI: 10.12677/japc.2024.132037, PDF,   
作者: 梁明乾：上海理工大学光子芯片研究院，上海；上海理工大学光电信息与计算机工程学院，上海；张轶楠*：上海理工大学光子芯片研究院，上海
关键词: 逆设计；纳米光子学；神经网络；等离激元；光开关；Inverse Design； Nanophotonics； Neural Network； Plasmon； Optical Switching
摘要: 等离激元产生于光与金属纳米结构的相互作用，其共振特性已成为纳米光子学领域的一个研究重点，基于可调谐等离子体共振的金属纳米结构光开关受到广泛关注。与此同时，如何设计高性能的纳米开关结构也成为一个重要的研究方向，深度学习方法在纳米光子结构的逆设计中展现出强大的应用潜力，可以高效利用巨大的参数空间。本文利用神经网络近似金属纳米结构的光学响应，并通过反向传播来实现纳米结构的逆设计，分析了光栅光开关的性能优势，并对未来研究方向进行了展望。
Abstract: The resonance characteristics of plasmon generated by the interaction between light and metal nanostructures have become a research focus in the field of nanophotonics, and the metal nanostructured optical switches based on tunable plasmon resonance have received extensive attention. At the same time, how to design high-performance nanoswitch structures has become an important research direction, and deep learning methods show strong application potential in the inverse design of nanophoton structures, which can efficiently use huge parameter space. In this paper, neural networks are used to approximate the optical response of metal nanostructures, and inverse design of nanostructures is realized through backpropagation. The performance advantages of grating optical switches are analyzed, and the future research directions are prospected.
文章引用：梁明乾, 张轶楠. 神经网络逆设计电化学等离激元光开关[J]. 物理化学进展, 2024, 13(2): 317-325. https://doi.org/10.12677/japc.2024.132037

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