Observing sequential aspects of metasurface with deep neural networks

Jaebum Noh; Younghwan Yang; Junsuk Rho

doi:10.1117/12.2676322

6 October 2023 Observing sequential aspects of metasurface with deep neural networks

Jaebum Noh, Younghwan Yang, Junsuk Rho

Proceedings Volume PC12655, Emerging Topics in Artificial Intelligence (ETAI) 2023; PC1265517 (2023) https://doi.org/10.1117/12.2676322
Event: SPIE Nanoscience + Engineering, 2023, San Diego, California, United States

Conference Poster

Abstract

We have developed two deep neural networks (inverse network / forward network) for obtaining metasurface operating at visible bandwidth. Unlike other studies, the neural networks involve not only the geometry of the metasurface but also incorporate refractive index information for metasurface designers. With the inverse network, inverse designs of metasurfaces displaying specific spectra have been conducted. Also, using the forward network, we have demonstrated a dual-mode metasurface with a reflective image / transmissive hologram, and an achromatic metalens. The networks provide vast design choices and fast calculation speed for engineers.

Citation Download Citation

Jaebum Noh, Younghwan Yang, and Junsuk Rho "Observing sequential aspects of metasurface with deep neural networks", Proc. SPIE PC12655, Emerging Topics in Artificial Intelligence (ETAI) 2023, PC1265517 (6 October 2023); https://doi.org/10.1117/12.2676322

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