Optoelectronics Letters, Volume. 17, Issue 12, 705(2021)
Deep learning enables temperature-robust spectrometer with high resolution
Traditional multi-mode fiber spectrometers rely on algorithms to reconstruct the transmission matrix of the fiber, facing the challenge that the same wavelength can lead to many totally de-correlated speckle patterns as the transfer matrix changes rapidly with environment fluctuations (typically temperature fluctuation). In this manuscript, we theoretically propose a multi-mode-fiber (MMF) based, artificial intelligence assisted spectrometer which is ultra-robust to temperature fluctuation. It has been demonstrated that the proposed spectrometer can reach a resolution of 0.1 pm and automatically reject the noise introduced by temperature fluctuation. The system is ultra-robust and with ultra-high spectral resolution which is beneficial for real life applications.
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GAN Jiaan, SHEN Mengyan, XIAO Xin, NONG Jinpeng, FENG Fu. Deep learning enables temperature-robust spectrometer with high resolution[J]. Optoelectronics Letters, 2021, 17(12): 705
Received: Aug. 9, 2021
Accepted: Aug. 23, 2021
Published Online: Jan. 10, 2022
The Author Email: Jinpeng NONG (nongjp@cqu.edu.cn)