arXiv：cs.LG· Shuangteng Lei, Li Yu, Tianxin Li, Wei Lu·· 3 小时前
在介电傅里叶空间中学习跨超表面家族的 qBIC 共振
Learning qBIC Resonances across Metasurface Families in Dielectric Fourier Space
AI 导读
研究将七个介电超表面家族的 2015 个样本映射到共享倒格矢网格，用两个冻结低阶傅里叶通道捕捉共振偏移，分支内平均 R² 达 0.871-0.999。五通道 K 空间主干建模宽带光谱，局部复 K 空间专家通过可微 Fano 层参数化 qBIC 共振，在几何阻隔测试集上将共振位置 MAE 从 3.2 nm 降至 0.95 nm，共振深度误差降低 14 倍。同一坐标还支持光谱到结构重建。
正文
Abstract:Bound states in the continuum (BIC) metasurfaces are typically described by geometry-specific parameters, hindering cross-geometry comparison, while ultranarrow qBIC features are easily diluted in full-spectrum learning. Here, 2015 samples from seven dielectric metasurface families are mapped to a shared reciprocal-lattice grid, where two frozen low-order Fourier channels capture resonance shifts with mean within-branch $R^2$ values of 0.871-0.999. Field-level analysis of two representative branches further confirms that these shifts are consistent with the Maxwell-Fourier perturbation picture. A five-channel K-space backbone models the broadband spectrum, while a local complex K-space expert parameterizes the qBIC resonance through a differentiable Fano layer. The expert reduces resonance-position mean absolute error (MAE) from 3.2 to 0.95 nm and the resonance-depth error by 14-fold on a geometry-blocked test set. The same coordinate supports spectrum-to-structure reconstruction.
| Comments: | 45 pages,5 main figures and 1 main table; includes Supplementary Information with 11 supplementary figures and 3 supplementary tables |
| Subjects: | Optics (physics.optics); Machine Learning (cs.LG); Computational Physics (physics.comp-ph) |
| Cite as: | arXiv:2610.11500 [physics.optics] |
| (or arXiv:2610.11500v1 [physics.optics] for this version) | |
| https://doi.org/10.48550/arXiv.2610.11500 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Shuangteng Lei [view email]
[v1]
Thu, 8 Oct 2026 08:40:24 UTC (2,775 KB)
来源：arXiv：cs.LG · arxiv.org