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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