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用于预测由连续统中的束缚态引起的法诺共振线形的机器学习方法。

Machine learning method for predicting line-shapes of Fano resonances induced by bound states in the continuum.

作者信息

Gerasimov V S, Kostyukov A S, Ershov A E, Maksimov D N, Kimberg V, Molokeev M S, Polyutov S P

机构信息

International Research Center of Spectroscopy and Quantum Chemistry, Siberian Federal University, Krasnoyarsk, Russia, 660041.

Institute of Computational Modelling SB RAS, Krasnoyarsk, Russia, 660036.

出版信息

Sci Rep. 2025 Aug 25;15(1):31187. doi: 10.1038/s41598-025-16192-1.

Abstract

We consider resonances induced by symmetry protected bound states in the continuum in dielectric gratings with in-plane mirror symmetry. It is shown that the shape of the resonance in transmittance is controlled by two parameters in a generic formula which can be derived in the framework of the coupled mode theory. It is numerically demonstrated that the formula encompasses various line-shapes including asymmetric Fano, Lorentzian, and anti-Lorentzian resonances. It is confirmed that the transmittance zeros are always present even in the absence up-down symmetry. At the same time reflectance zeros are not generally present in the single mode approximation. It is found that the line-shapes of Fano resonances can be predicted to a good accuracy by the random forest machine learning method which outperforms the standard least square methods approximation in error by an order of magnitude in error with the training dataset size [Formula: see text].

摘要

我们考虑具有面内镜像对称性的介质光栅中连续谱中对称性保护束缚态所诱导的共振。结果表明,透过率共振的形状由一个通用公式中的两个参数控制,该公式可在耦合模理论框架下推导得出。数值结果表明,该公式涵盖了各种线形,包括非对称法诺、洛伦兹和反洛伦兹共振。结果证实,即使不存在上下对称性,透过率零点也总是存在。同时,在单模近似中,反射率零点通常不存在。研究发现,随机森林机器学习方法能够以较高的精度预测法诺共振的线形,在训练数据集规模下,其误差比标准最小二乘法近似小一个数量级[公式:见原文]。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6d8/12379286/cf89198b87eb/41598_2025_16192_Fig1_HTML.jpg

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