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基于衍射神经网络的超紧凑多焦点光学器件的反向设计。

Inverse design of ultracompact multi-focal optical devices by diffractive neural networks.

出版信息

Opt Lett. 2022 Jun 1;47(11):2842-2845. doi: 10.1364/OL.460186.

Abstract

We propose an efficient inverse design approach for multifunctional optical elements based on adaptive deep diffractive neural networks (a-DNNs). Specifically, we introduce a-DNNs and design two-layer diffractive devices that can selectively focus incident radiation over two well-separated spectral bands at desired distances. We investigate focusing efficiencies at two wavelengths and achieve targeted spectral line shapes and spatial point-spread functions (PSFs) with optimal focusing efficiency. In particular, we demonstrate control of the spectral bandwidths at separate focal positions beyond the theoretical limit of single-lens devices with the same aperture size. Finally, we demonstrate devices that produce super-oscillatory focal spots at desired wavelengths. The proposed method is compatible with current diffractive optics and doublet metasurface technology for ultracompact multispectral imaging and lensless microscopy applications.

摘要

我们提出了一种基于自适应深度衍射神经网络 (a-DNN) 的多功能光学元件的高效反设计方法。具体来说,我们引入了 a-DNN 并设计了两层衍射器件,这些器件可以在期望的距离处选择性地将入射辐射聚焦在两个分离的光谱带中。我们研究了两个波长的聚焦效率,并实现了具有最佳聚焦效率的目标光谱线形状和空间点扩散函数 (PSF)。特别是,我们证明了在具有相同孔径尺寸的单透镜器件的理论极限之外,在单独的焦点位置控制光谱带宽的能力。最后,我们演示了在期望波长产生超振荡焦点的器件。所提出的方法与当前的衍射光学和双元超表面技术兼容,可用于超紧凑多光谱成像和无透镜显微镜应用。

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