Prediction of toroidal dipole resonance in dielectric metasurface by deep learning

IF 3.5 2区物理与天体物理 Q2 PHYSICS, APPLIED

Applied Physics Letters Pub Date : 2025-02-21 DOI:10.1063/5.0252353

Yangyang Yu, Shaojun You, Ying Zhang, Lulu Wang, Hong Duan, Haoxuan He, Yiyuan Wang, Shengyun Luo, Jing Xu, Jing Huang, Chaobiao Zhou

引用次数: 0

Abstract

Toroidal dipole (TD) resonance is a promising method for enhancing light–matter interactions, offering significant potential in photonic device design. While numerical simulations are commonly used to study TD resonances, they are computationally expensive and time consuming. In this study, we propose deep learning strategies to predict TD resonances induced by Brillouin zone folding. A fully connected neural network is developed to predict transmission mapping, transmission spectra, multipole scattering, and TD components. Comparison with numerical simulations shows that the neural network predicts TD resonance efficiently and accurately. Experimental validation through fabricated samples further confirms the strong TD response. Our work presents an effective tool for quickly and precisely exploring nanophotonic properties and offers a promising approach for predicting high-quality factor TD resonators.

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来源期刊

Applied Physics Letters 物理-物理：应用

CiteScore

6.40

自引率

10.00%

发文量

1821

审稿时长

1.6 months

期刊介绍： Applied Physics Letters (APL) features concise, up-to-date reports on significant new findings in applied physics. Emphasizing rapid dissemination of key data and new physical insights, APL offers prompt publication of new experimental and theoretical papers reporting applications of physics phenomena to all branches of science, engineering, and modern technology. In addition to regular articles, the journal also publishes invited Fast Track, Perspectives, and in-depth Editorials which report on cutting-edge areas in applied physics. APL Perspectives are forward-looking invited letters which highlight recent developments or discoveries. Emphasis is placed on very recent developments, potentially disruptive technologies, open questions and possible solutions. They also include a mini-roadmap detailing where the community should direct efforts in order for the phenomena to be viable for application and the challenges associated with meeting that performance threshold. Perspectives are characterized by personal viewpoints and opinions of recognized experts in the field. Fast Track articles are invited original research articles that report results that are particularly novel and important or provide a significant advancement in an emerging field. Because of the urgency and scientific importance of the work, the peer review process is accelerated. If, during the review process, it becomes apparent that the paper does not meet the Fast Track criterion, it is returned to a normal track.