Volume 564, 1 August 2024, 130622Author links open overlay panel, , , , Highlights•

A polarization-multiplexing metasurface which can modulate the amplitude and phase of incident.

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Proposed a forward design method based on neural network to design the polarization-multiplexing metasurface hologram.

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Proposed an end-to-end optimization framework using neural networks to design the multiplexing metasurface.

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The end-to-end framework enables direct mapping of geometric parameters of the metasurface to holographic images.

Abstract

In this work we present a polarization-multiplexing metasurface hologram designed with neural network, which can modulate the amplitude and phase of incident light with four nanopillars comprised unit structures with high efficiency. Then, to improve image quality by minimizing the difference between the complex amplitude field modulated by the structure and that obtained through the network, we developed an end-to-end framework-assisted multifunctional metasurface design method based on the aforementioned neural network, which can directly map geometric parameters of the metasurface to holographic images. The comparative results indicate that for the end-to-end framework, although the optimized distributions of complex amplitudes are limited by the selected finite number of structures, in the simulation results, higher-quality images can still be obtained compared to the forward design method. Full-wave simulation results show our proposed method can obtain higher quality holographic images compared to the GS algorithm. This work may open new possibilities in holographic displays and multifunctional optical devices.

Section snippetsCRediT authorship contribution statement

Zhuang Miao: Writing – original draft, Software, Methodology, Data curation. Weijie Shi: Writing – review & editing, Validation. Renchao Jin: Writing – review & editing, Software. Jiaqi Li: Writing – review & editing, Conceptualization. Weibing Lu: Writing – review & editing.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This work is supported by the National Science Funds for Distinguished Young Scientists under grant number 61925103, National Natural Science Foundation of China 62231001, 62101115，Fundamental Research funds for the central universities (2242022k60004) The data that support the findings of this study are available from the corresponding author upon reasonable request.

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