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Near-infrared speckle wavemeter based on nonlinear frequency conversion

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Abstract

The wavemeter is an important instrument for spectrum analysis, widely used in spectral calibration, remote sensing, atomic physics, and high-precision metrology. However, near-infrared (NIR) wavemeters require infrared-sensitive detectors that are expensive and less sensitive compared to silicon-based visible light detectors. To circumvent these limitations, we propose an NIR speckle wavemeter based on nonlinear frequency conversion. We combine a scattering medium and the deep learning technique to invert the nonlinear mapping of the NIR wavelength and speckles in the visible wave band. With the outstanding performance of deep learning, a high-precision wavelength resolution of 1 pm is achievable in our experiment. We further demonstrate the robustness of our system and show that the recognition of power parameters and multi-spectral lines is also feasible. The proposed method offers a convenient and flexible way to measure NIR light, and it offers the possibility of cost reduction in miniaturized wavemeter systems.

© 2023 Optica Publishing Group

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Supplementary Material (1)

NameDescription
Supplement 1       S1 Measurement of the transport mean free path of the TiO2 powder S2 Prediction ability of unknown input wavelength

Data availability

Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

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