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

Jing Zhou, Hui Zhang, Qifeng Qiao, Heng Chen, Qian Huang, Hanxing Wang, Qinghua Ren, Nan Wang, Yiming Ma () and Chengkuo Lee ()
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Jing Zhou: Shanghai University
Hui Zhang: Tongji University
Qifeng Qiao: Shanghai Industrial μTechnology Research Institute (SITRI)
Heng Chen: Shanghai University
Qian Huang: Shanghai University
Hanxing Wang: Shanghai University
Qinghua Ren: Shanghai University
Nan Wang: Shanghai University
Yiming Ma: Shanghai University
Chengkuo Lee: National University of Singapore

Nature Communications, 2024, vol. 15, issue 1, 1-12

Abstract: 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.

Date: 2024
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DOI: 10.1038/s41467-024-54704-1

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