Year
Month
(Peer-Reviewed) Towards integrated mode-division demultiplexing spectrometer by deep learning
Ze-huan Zheng 郑泽寰 ¹ ², Sheng-ke Zhu 朱圣科 ¹ ⁴, Ying Chen 陈颖 ³, Huanyang Chen 陈焕阳 ⁵, Jin-hui Chen 陈锦辉 ¹ ⁴ ⁶
¹ Shenzhen Research Institute, Xiamen University, Shenzhen 518000, China
中国 深圳 厦门大学深圳研究院
² Xiamen Power Supply Bureau of Fujian Electric Power Company Limited, State Grid, Xiamen 361004, China
中国 厦门 福建省电力有限公司 厦门供电局
³ College of Information Science and Engineering, Fujian Provincial Key Laboratory of Light Propagation and Transformation, Huaqiao University, Xiamen 361021, China
福建省光传输与变换重点实验室 华侨大学信息科学与工程学院
⁴ Institute of Electromagnetics and Acoustics, Xiamen University, Xiamen 361005, China
中国 厦门 厦门大学电磁声学研究院
⁵ College of Physical Science and Technology, Xiamen University, Xiamen 361005, China
中国 厦门 厦门大学物理科学与技术学院
⁶ Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen 361005, China
中国 厦门 中国福建能源材料科学与技术创新实验室(嘉庚创新实验室)
Opto-Electronic Science, 2022-11-01
Abstract

Miniaturized spectrometers have been widely researched in recent years, but few studies are conducted with on-chip multimode schemes for mode-division multiplexing (MDM) systems. Here we propose an ultracompact mode-division demultiplexing spectrometer that includes branched waveguide structures and graphene-based photodetectors, which realizes simultaneously spectral dispersing and light fields detecting.

In the bandwidth of 1500–1600 nm, the designed spectrometer achieves the single-mode spectral resolution of 7 nm for each mode of TE1–TE4 by Tikhonov regularization optimization. Empowered by deep learning algorithms, the 15-nm resolution of parallel reconstruction for TE1–TE4 is achieved by a single-shot measurement. Moreover, by stacking the multimode response in TE1–TE4 to the single spectra, the 3-nm spectral resolution is realized.

This design reveals an effective solution for on-chip MDM spectroscopy, and may find applications in multimode sensing, interconnecting and processing.
Towards integrated mode-division demultiplexing spectrometer by deep learning_1
Towards integrated mode-division demultiplexing spectrometer by deep learning_2
Towards integrated mode-division demultiplexing spectrometer by deep learning_3
  • Programmable directional photonic spiking neuron based on a non-Hermitian silicon microresonator
  • Stefano Biasi, Bülent Aslan, Stefano Gretter, Davide Olivieri, Alessandro Foradori, Riccardo Franchi, Lorenzo Pavesi
  • Opto-Electronic Science
  • 2026-08-26
  • Mutual empowerment of artificial intelligence and metasurfaces: intelligent nanophotonics and optical intelligence
  • Yu Zhao, Zile Li, Yongquan Zeng, Shaohua Yu, Guoxing Zheng
  • Opto-Electronic Science
  • 2026-08-26
  • Heterogeneously integrated micro-ring with SnS₂ for dual-functional optical modulation and photodetection
  • Jinyi Du, Lidan Lu, Xu Zhang, Bofei Zhu, Wenbo Bo, Yingjie Xu, Guang Chen, Yanlin He, Guanghui Ren, Xiaoping Lou, Zheng You, Lianqing Zhu
  • Opto-Electronic Advances
  • 2026-08-25
  • Hardware-aware lightweight photonic spiking neural network for pattern classification
  • Shuiying Xiang, Yahui Zhang, Shangxuan Shi, Haowen Zhao, Dianzhuang Zheng, Xingxing Guo, Yanan Han, Ye Tian, Liyue Zhang, Yuechun Shi, Yue Hao
  • Opto-Electronic Advances
  • 2026-08-25
  • PhyspeNet: An empirical physics-aware network for adaptive speckle reconstructive spectrometry
  • Junrui Liang, Min Jiang, Jun Li, Zhongming Huang, Junhong He, Yanting Guo, Yanzhao Ke, Jun Ye, Jiangming Xu, Jinyong Leng, Pu Zhou
  • Opto-Electronic Advances
  • 2026-08-25
  • Video-rate wavefront capture and replay via single-shot reference-free measurement: toward holographic telepresence
  • Minwook Kim, Chansuk Park, Chulmin Oh, KyeoReh Lee, Herve Hugonnet, YongKeun Park
  • Opto-Electronic Advances
  • 2026-08-25
  • Luminescent YAG:Ce³⁺ 3D micro-structures via multi-photon laser lithography
  • Robertas Virkėtis, Greta Merkininkaitė, Artūr Harnik, Ugnė Ūsaitė, Dominykas Dapšys, Arturo Susarrey-Arce, Simas Šakirzanovas, Mangirdas Malinauskas
  • Opto-Electronic Advances
  • 2026-08-25
  • A 36 × 240 Gbps hybrid mode/wavelength division multiplexing transmitter using lithium niobate on insulator
  • Mingyu Zhu, Weihan Wang, Ruitao Ma, Aoyun Gao, Chun Gao, Zexu Wang, Fei Huang, Zhenyuan Bao, Dajian Liu, Jiaxuan Gan, Zejie Yu, Huan Li, Weike Zhao, Daoxin Dai
  • Opto-Electronic Advances
  • 2026-08-25
  • Scalable spatiotemporal interleaving network for high-density integrated photonic convolution
  • Hudi Liu, Jingchi Li, Hua Zhong, Yu He, Yikai Su
  • Opto-Electronic Science
  • 2026-07-24
  • From non-resonant to resonant meta-devices: imaging, color routing, displaying, and beyond
  • Weihan Liu, Yao Liang, Borui Leng, Shufan Chen, Peng-Yi Feng, Din Ping Tsai
  • Opto-Electronic Science
  • 2026-07-24
  • Light-perception-based interactive control of an underwater digital twin hand
  • Jinlong Lu, Chao Zhang, Hengchang Nong, Dongying Wang, Hongyu Zhou, Junjie Weng, Yuehua Deng, Yang Yu, Qiang Bian, Jianfa Zhang, Chaofan Zhang, Zhenrong Zhang, Junbo Yang
  • Opto-Electronic Advances
  • 2026-07-10
  • Digital twin optical computing system
  • Run Sun, Yuemin Li, Tingzhao Fu, Wencan Liu, Sigang Yang, Hongwei Chen
  • Opto-Electronic Advances
  • 2026-07-10



  • Brillouin scattering spectrum for liquid detection and applications in oceanography                                Crosstalk-free achromatic full Stokes imaging polarimetry metasurface enabled by polarization-dependent phase optimization
    About
    |
    Contact
    |
    Copyright © PubCard