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Frontiers of Optoelectronics

ISSN 2095-2759

ISSN 2095-2767(Online)

CN 10-1029/TN

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Front. Optoelectron.    2024, Vol. 17 Issue (3) : 22    https://doi.org/10.1007/s12200-024-00126-2
Polarization and wavelength routers based on diffractive neural network
Xiaohong Lin1, Yulan Fu1(), Kuo Zhang2, Xinping Zhang1, Shuai Feng2, Xiaoyong Hu3,4,5()
1. School of Physics and Optoelectronic Engineering, Beijing University of Technology, Beijing 100124, China
2. School of Science, Minzu University of China, Beijing 100081, China
3. State Key Laboratory for Mesoscopic Physics and Department of Physics, Collaborative Innovation Center of Quantum Matter, Beijing Academy of Quantum Information Sciences, Nano-Optoelectronics Frontier Center of Ministry of Education, Peking University, Beijing 100871, China
4. Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan 030006, China
5. Peking University Yangtze Delta Institute of Optoelectronics, Nantong 226010, China
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Abstract

In the field of information processing, all-optical routers are significant for achieving high-speed, high-capacity signal processing and transmission. In this study, we developed three types of structurally simple and flexible routers using the deep diffractive neural network (D2NN), capable of routing incident light based on wavelength and polarization. First, we implemented a polarization router for routing two orthogonally polarized light beams. The second type is the wavelength router that can route light with wavelengths of 1550, 1300, and 1100 nm, demonstrating outstanding performance with insertion loss as low as 0.013 dB and an extinction ratio of up to 18.96 dB, while also maintaining excellent polarization preservation. The final router is the polarization-wavelength composite router, capable of routing six types of input light formed by pairwise combinations of three wavelengths (1550, 1300, and 1100 nm) and two orthogonal linearly polarized lights, thereby enhancing the information processing capability of the device. These devices feature compact structures, maintaining high contrast while exhibiting low loss and passive characteristics, making them suitable for integration into future optical components. This study introduces new avenues and methodologies to enhance performance and broaden the applications of future optical information processing systems.

Keywords Optical diffractive neural network      All-optical routers      Polarization degree of freedom      Wavelength degree of freedom     
Corresponding Author(s): Yulan Fu,Xiaoyong Hu   
About author:

#These authors contributed equally to this work.

Issue Date: 08 August 2024
 Cite this article:   
Xiaohong Lin,Yulan Fu,Kuo Zhang, et al. Polarization and wavelength routers based on diffractive neural network[J]. Front. Optoelectron., 2024, 17(3): 22.
 URL:  
https://academic.hep.com.cn/foe/EN/10.1007/s12200-024-00126-2
https://academic.hep.com.cn/foe/EN/Y2024/V17/I3/22
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