基于全光衍射深度神经网络的多维全息超构器件设计

      Design of Multi-dimensional Holographic Meta-devices Based on All-Optical Diffractive Deep Neural Networks

      • 摘要: 为满足全息成像系统对多维电磁自由度联合调控的需求,本研究提出了一种基于全光衍射深度神经网的多维全息超构器件设计方法。该方法结合了全光衍射深度神经网络的多层空间级联机制与角谱传播理论,构建了由宽带纯相位超构表面和线极化超构表面组成的多层空间级联结构,实现了对频率、极化、空间位置及传输方向等多个电磁自由度的协同调控。仿真结果表明,所设计的超构器件在多个频点和极化状态下均可实现高对比度、低串扰的全息成像效果,兼具多功能融合、信息存储量大和可重构性强的特点,为动态全息显示、光学加密与高容量信息存储等领域提供了新的设计思路。

         

        Abstract: To meet the demand for the coordinated manipulation of multi-dimensional electromagnetic degrees of freedom in holographic imaging systems, we propose a design method for multi-dimensional holographic meta-devices based on all-optical diffractive deep neural networks (D2NNs). The method combines the multi-layer spatial cascading mechanism of all-optical D2NNs with the angular spectrum theory, and constructs a multi-layer spatially cascaded structure composed of broadband pure-phase metasurfaces and linearly polarized metasurfaces, enabling the coordinated manipulation of multiple electromagnetic degrees of freedom, including frequency, polarization, spatial position, and transmission direction. Simulation shows that the designed meta-devices can achieve holographic imaging with high contrast and low crosstalk under multiple frequencies and polarization states, and feature multi-function integration, large storage capacity, and strong reconfigurability, providing a new design method for fields such as dynamic holographic display, optical encryption, and high-capacity information storage.

         

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