Wang Hai Peng, Cao Du Ming, Pang Xiao Yu, Zhang Xiao Hong, Wang Shi Yu, Hou Wen Ying, Nie Chen Chen, Li Yun Bo
Opt Express. 2023 Nov 6;31(23):37763-37777. doi: 10.1364/OE.503139.
In recent years, deep learning (DL) has demonstrated significant potential in the inverse design of metasurfaces, and the generation of metasurfaces with customized transmission characteristics of frequency band remains a challenging and underexplored area. In this study, we propose a DL-assisted method for the inverse design of transmissive metasurfaces. The method consists of a generative adversarial network (GAN)-based graph generator, an electromagnetic response predictor, and a genetic algorithm optimizer. By integrating these components, we can obtain customized metasurfaces with desired transmission characteristics of frequency band. We demonstrate the effectiveness of the proposed method through examples of inverse-designed three-layer cascaded transmissive metasurfaces with wideband, dual-band, and stopband responses in the 8∼12 GHz frequency range. Specifically, we realize three different types of dual-band metasurfaces, namely double-wide, front-wide and rear-narrow, and front-narrow and rear-wide configurations. Additionally, we analyze the accuracy and reliability of the inverse design method by employing data from the training dataset, self-defined objectives, and bandwidth-reduced target responses scaled from the wideband type as design inputs. Quantitative evaluation is performed using metrics such as mean absolute error and average precision. The proposed method successfully achieves the desired effect as intended.
近年来，深度学习（DL）在超表面的逆向设计中展现出巨大潜力，而生成具有定制频段传输特性的超表面仍然是一个具有挑战性且未被充分探索的领域。在本研究中，我们提出了一种用于透射型超表面逆向设计的深度学习辅助方法。该方法由基于生成对抗网络（GAN）的图形生成器、电磁响应预测器和遗传算法优化器组成。通过整合这些组件，我们可以获得具有所需频段传输特性的定制超表面。我们通过在8至12 GHz频率范围内逆向设计的三层级联透射型超表面的宽带、双频和阻带响应示例，展示了所提方法的有效性。具体而言，我们实现了三种不同类型的双频超表面，即双宽、前宽后窄以及前窄后宽配置。此外，我们通过使用来自训练数据集的数据、自定义目标以及从宽带类型缩放而来的带宽减小的目标响应作为设计输入，来分析逆向设计方法的准确性和可靠性。使用平均绝对误差和平均精度等指标进行定量评估。所提方法成功实现了预期的理想效果。
