A Neuro Metasurface Mode-Router for Fiber Mode Demultiplexing and Communications

Yu Zhao; Huijiao Wang; Zile Li; Tian Huang; Chao Yang; Ying Qiu; Yuhan Gong; Zhou Zhou; Congling Liang; Lei Yu; Jin Tao; Shaohua Yu; Guoxing Zheng

doi:10.1016/j.eng.2024.11.012

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Engineering ›› 2025, Vol. 45 ›› Issue (2) : 88-96. DOI: 10.1016/j.eng.2024.11.012

Research

Article

A Neuro Metasurface Mode-Router for Fiber Mode Demultiplexing and Communications

Yu Zhao^a^,^# ,
Huijiao Wang^a^,^# ,
Zile Li^a^,^b^,^# ,
Tian Huang^a ,
Chao Yang^c ,
Ying Qiu^c ,
Yuhan Gong^c ,
Zhou Zhou^a ,
Congling Liang^a ,
Lei Yu^a^,^* ,
Jin Tao^b^,^c^,^* ,
Shaohua Yu^b ,
Guoxing Zheng^a^,^b^,^d^,^*

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Abstract

Advancements in mode-division multiplexing (MDM) techniques, aimed at surpassing the Shannon limit and augmenting transmission capacity, have garnered significant attention in optical fiber communication, propelling the demand for high-quality multiplexers and demultiplexers. However, the criteria for ideal-mode multiplexers/demultiplexers, such as performance, scalability, compatibility, and ultra-compactness, have only partially been achieved using conventional bulky devices (e.g., waveguides, gratings, and free space optics)—an issue that will substantially restrict the application of MDM techniques. Here, we present a neuro-meta-router (NMR) optimized through deep learning that achieves spatial multi-mode division and supports multi-channel communication, potentially offering scalability, compatibility, and ultra-compactness. An MDM communication system based on an NMR is theoretically designed and experimentally demonstrated to enable simultaneous and independent multi-dataset transmission, showcasing a capacity of up to 100 gigabits per second (Gbps) and a symbol error rate down to the order of 10⁻⁴, all achieved without any compensation technologies or correlation devices. Our work presents a paradigm that merges metasurfaces, fiber communications, and deep learning, with potential applications in intelligent metasurface-aided optical interconnection, as well as all-optical pattern recognition and classification.

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Metasurfaces / Deep learning / Mode-division multiplexing / Fiber communication

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Yu Zhao, Huijiao Wang, Zile Li, Tian Huang, Chao Yang, Ying Qiu, Yuhan Gong, Zhou Zhou, Congling Liang, Lei Yu, Jin Tao, Shaohua Yu, Guoxing Zheng. A Neuro Metasurface Mode-Router for Fiber Mode Demultiplexing and Communications. Engineering, 2025, 45(2): 88‒96 https://doi.org/10.1016/j.eng.2024.11.012

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