论文标题
通过衍射神经网络的超模型多核光学设备的逆设计
Inverse design of ultracompact multi-focal optical devices by diffractive neural networks
论文作者
论文摘要
我们为基于自适应深度衍射神经网络（A-D $^2 $ nns）的多功能光学元素提出了一种有效的逆设计方法。具体而言，我们介绍了A-D $^2 $ NNS和设计两层衍射设备，这些设备可以在所需距离的两个良好分离的光谱频段上选择性地聚焦入射辐射。我们研究了两个波长的聚焦效率，并具有最佳的聚焦效率，并实现了靶向的光谱线形和空间点传播函数（PSF）。特别是，我们在单独的焦点位置上表明了光谱带宽的控制，超出了具有相同光圈大小的单镜头设备的理论极限。最后，我们演示了在所需波长处产生超振荡焦点斑点的设备。所提出的方法与用于超模型的多光谱成像和无透镜显微镜应用的当前衍射光学和Doublet MetaSurface Technology兼容。
We propose an efficient inverse design approach for multifunctional optical elements based on adaptive deep diffractive neural networks (a-D$^2$NNs). Specifically, we introduce a-D$^2$NNs 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 lineshapes 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.
