Physics-Embedded autoencoder for solving broadband light field modulation with metasurfaces

IF 4.6 2区物理与天体物理 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Results in Physics Pub Date : 2025-09-22 DOI:10.1016/j.rinp.2025.108434

Siyuan Cheng , Hong Xu , Song Ye , Shuyuan Xiao , Wentao Zhang , Xiaowei Qu , Ming Chen , Wei Huang

引用次数: 0

Abstract

In this paper, we propose a novel AI-based method to arrange metasurface’s structures for light field modulation, which is based on an autoencoder embedded with the physics equation. For the problem of light-field modulation, we employ the Rayleigh–Sommerfeld equation within the autoencoder method. We employ this AI method to design a focus lens with a focusing efficiency of 32.5% to 56% within the 1000 to 1250 nm range, and a far-field imaging metasurface spanning the same wavelength range. Our full-wave simulations confirm the correction of our designs.

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物理-嵌入式自编码器解决宽带光场调制与超表面

本文提出了一种基于人工智能的光场调制超表面结构排列方法，该方法基于嵌入物理方程的自编码器。对于光场调制问题，我们在自编码器方法中采用了瑞利-索默菲尔德方程。利用该方法设计了1000 ~ 1250 nm范围内聚焦效率为32.5% ~ 56%的聚焦透镜，以及跨越相同波长范围的远场成像超表面。我们的全波模拟证实了我们设计的正确性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Results in Physics MATERIALS SCIENCE, MULTIDISCIPLINARYPHYSIC-PHYSICS, MULTIDISCIPLINARY

CiteScore

8.70

自引率

9.40%

发文量

754

审稿时长

50 days

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