Optimizing the design of birefringent metasurfaces with deep learning neural networks

Athena Xu; Behrooz Semnani; Anna Maria Houk; Mohammad Soltani; Jacqueline Treacy; Michal Bajcsy

doi:10.1117/12.3000591

13 March 2024 Optimizing the design of birefringent metasurfaces with deep learning neural networks

Athena Xu, Behrooz Semnani, Anna Maria Houk, Mohammad Soltani, Jacqueline Treacy, Michal Bajcsy

Proceedings Volume 12896, Photonic and Phononic Properties of Engineered Nanostructures XIV; 1289606 (2024) https://doi.org/10.1117/12.3000591
Event: SPIE OPTO, 2024, San Francisco, California, United States

Abstract

Metasurface presents itself as a method to create flat optical devices that generate customizable wavefronts at the nanoscale. The traditional metasurface design process involves solving Maxwell’s equations through forward simulations and implementing trial-and-error to achieve the desired spectral response. This approach is computationally expensive and typically requires multiple iterations. In this study, we propose a reverse engineering solution that utilizes a deep learning artificial neural network (DNN). The ideal phase and transmission spectrums are inputted into the neural network, and the predicted dimensions which correspond to these spectrums are outputted by the network. The prediction process is less computationally expensive than forward simulations and is orders of magnitude faster to execute. Our neural network aims to identify the dimensions of elliptical nanopillars that will create the ideal phase response with a near unity transmission in a 20 nm wavelength interval surrounding the center wavelength of the spectral response. We have trained such a reverse DNN to predict the optimal dimensions for a birefringent metasurface composed of elliptical nanopillars.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Athena Xu, Behrooz Semnani, Anna Maria Houk, Mohammad Soltani, Jacqueline Treacy, and Michal Bajcsy "Optimizing the design of birefringent metasurfaces with deep learning neural networks", Proc. SPIE 12896, Photonic and Phononic Properties of Engineered Nanostructures XIV, 1289606 (13 March 2024); https://doi.org/10.1117/12.3000591

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