Panda Soumyashree S, Choudhary Sumit, Joshi Siddharth, Sharma Satinder K, Hegde Ravi S
Opt Lett. 2022 May 15;47(10):2586-2589. doi: 10.1364/OL.458746.
While the large design degrees of freedom (DOFs) give metasurfaces a tremendous versatility, they make the inverse design challenging. Metasurface designers mostly rely on simple shapes and ordered placements, which restricts the achievable performance. We report a deep learning based inverse design flow that enables a fuller exploitation of the meta-atom shape. Using a polygonal shape encoding that covers a broad gamut of lithographically realizable resonators, we demonstrate the inverse design of color filters in an amorphous silicon material platform. The inverse-designed transmission-mode color filter metasurfaces are experimentally realized and exhibit enhancement in the color gamut.
虽然大的设计自由度赋予了超表面极大的通用性，但也使得逆向设计具有挑战性。超表面设计者大多依赖简单形状和有序排列，这限制了可实现的性能。我们报告了一种基于深度学习的逆向设计流程，该流程能够更充分地利用超原子形状。通过使用一种多边形形状编码，它涵盖了光刻可实现的谐振器的广泛范围，我们展示了非晶硅材料平台中滤色器的逆向设计。通过实验实现了逆向设计的透射模式滤色器超表面，并在色域方面有了增强。
