Deep learning-enabled ultra-broadband terahertz high-dimensional photodetector

Research context

Capturing multi-dimensional optical information is indispensable in modern optics. However, existing photodetectors can at best detect light fields whose wavelengths or polarizations are predefined at several specific values. Integrating broadband high-dimensional continuous photodetection including intensity, polarization, and wavelength within a single device still poses formidable challenges. Here we present a metasurface-mediated high-dimensional detector that projects polarimetric and spectral responses into the Orbital Angular Momentum (OAM) domain via dispersion-driven OAM multiplication. By decoupling the frequency-controlled transmission phase response and polarization-controlled geometric phase response, spectrum and polarization information are encoded into unique polaritonic vortex patterns, which can be accurately deciphered via machine learning technique. Eventually our neural-network assisted metadevice achieves full characterization of intensity-polarization-frequency 3D continuous parametric space, so that light with arbitrarily mixed polarization states across 0.3-1.1 THz can be accurately detected with total error <5.1%. Our technology also showcases application

Keywords: Terahertz radiation, Photodetector, Broadband, Optoelectronics, Computer science, Materials science, Telecommunications

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15 citations · OpenAlex · observed 2026-09-08

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Cite / 引用

Zong-Kun Zhang, Teng Zhang, Zong-Peng Zhang, Ming-Zhe Chong, Mingqing Xiao, Pu Peng, Peijie Feng, Haonan Sun, Zhipeng Zheng, Xiaofei Zang, Zheyu Fang, Ming-Yao Xia. Deep learning-enabled ultra-broadband terahertz high-dimensional photodetector. Nature Communications (2025). https://doi.org/10.1038/s41467-025-63364-8

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