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长波红外计算多光谱超表面及光谱重建方法

Long-wave infrared computational multispectral metasurface and spectral reconstruction method.

作者信息

Wang Shang, Lu Lidan, Zhu Lianqing

机构信息

School of Instrument Science and Opto-Electronics Engineering, Beijing Information Science and Technology University, Beijing, 100192, China.

出版信息

Sci Rep. 2025 Jul 1;15(1):22274. doi: 10.1038/s41598-025-06599-1.

Abstract

We demonstrate a computational multispectral metasurface employing a 3×3 photonic crystal array architecture that operates across the longwave infrared spectrum (8-11.5 [Formula: see text] m). The designed structure achieves remarkable optical performance with peak transmittance reaching 75.8% and broadband energy utilization efficiency of 41.37%. Notably, the inter-channel transmittance correlation coefficient of 0.17 indicates superior spectral discrimination compared to conventional grating-based systems. We also considered the angular dependence of the array on the incident light. Additionally, to evaluate the spectral reconstruction performance of the transmission spectra under different photonic crystals, a spectral reconstruction deep learning network was constructed with the mean squared error is 2.86[Formula: see text]. This architecture establishes a hardware-algorithm co-design framework for next-generation infrared multispectral systems, demonstrating the potential for integrated superlattice detectors with sub-100 [Formula: see text] m[Formula: see text] pixel pitch, which represents a critical advancement for portable spectroscopic applications.

摘要

我们展示了一种采用3×3光子晶体阵列结构的计算多光谱超表面,其工作在长波红外光谱(8 - 11.5微米)范围内。所设计的结构实现了卓越的光学性能,峰值透过率达到75.8%,宽带能量利用效率为41.37%。值得注意的是,0.17的通道间透过率相关系数表明,与传统的基于光栅的系统相比,具有卓越的光谱分辨能力。我们还考虑了阵列对入射光的角度依赖性。此外,为了评估不同光子晶体下透射光谱的光谱重建性能,构建了一个光谱重建深度学习网络,其均方误差为2.86。这种架构为下一代红外多光谱系统建立了一个硬件 - 算法协同设计框架,展示了具有亚100微米像素间距的集成超晶格探测器的潜力,这代表了便携式光谱应用的一项关键进展。

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