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Denoising-autoencoder-facilitated MEMS computational spectrometer with enhanced resolution on a silicon photonic chip

Author

Listed:
  • Jing Zhou

    (Shanghai University
    Shanghai University)

  • Hui Zhang

    (Tongji University
    MOE Key Laboratory of Advanced Micro-Structured Materials
    Tongji University
    Shanghai Frontiers Science Center of Digital Optics)

  • Qifeng Qiao

    (Shanghai Industrial μTechnology Research Institute (SITRI))

  • Heng Chen

    (Shanghai University
    Shanghai University)

  • Qian Huang

    (Shanghai University
    Shanghai University)

  • Hanxing Wang

    (Shanghai University
    Shanghai University)

  • Qinghua Ren

    (Shanghai University
    Shanghai University)

  • Nan Wang

    (Shanghai University
    Shanghai University)

  • Yiming Ma

    (Shanghai University
    Shanghai University)

  • Chengkuo Lee

    (National University of Singapore
    National University of Singapore
    National Centre for Advanced Integrated Photonics (NCAIP))

Abstract

Silicon photonics enables the construction of chip-scale spectrometers, in which those using a single tunable interferometer provide a simple and cost-effective solution. Among various tuning mechanisms, electrostatic MEMS reconfiguration stands out as an ideal candidate, given its high tuning efficiency and ultra-low power consumption. Nonetheless, MEMS devices face significant noise challenges arising from their susceptible minuscule components, adversely impacting spectral resolution. Here, we propose a distinct paradigm of spectrometers through synergizing an easily-fabricated MEMS-reconfigurable low-loss waveguide coupler on a silicon photonic chip and a convolutional autoencoder denoising (CAED) mechanism. The spectrometer offers a 300 nm bandwidth and a reconstruction resolution of 0.3 nm in a noise-free condition. In a noisy environment with a signal-to-noise ratio as low as 30 dB, the reconstruction resolution of the interferograms processed by the CAED exhibits an enhancement from 1.2 to 0.4 nm, approaching the noise-free value. Our technology is envisaged to provide a powerful and cost-effective solution for applications requiring accurate, broadband, and energy-efficient spectral analysis.

Suggested Citation

  • Jing Zhou & Hui Zhang & Qifeng Qiao & Heng Chen & Qian Huang & Hanxing Wang & Qinghua Ren & Nan Wang & Yiming Ma & Chengkuo Lee, 2024. "Denoising-autoencoder-facilitated MEMS computational spectrometer with enhanced resolution on a silicon photonic chip," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-54704-1
    DOI: 10.1038/s41467-024-54704-1
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