Based on the model- and data-driven strategy, a spectroscopy learning method that can extract the novel and hidden information from the line list databases has been applied to the R branch emission spectra of 3–0 band of the ground electronic state of 12C16O. The labeled line lists such as line intensities and Einstein A coefficients quoted in HITRAN2020 are collected to enhance the dataset. The quantified spectroscopy-learned spectroscopic constants is beneficial for improving the extrapolative accuracy beyond the measurements. Explicit comparisons are made for line positions, line intensities, Einstein A coefficients, which demonstrate that the model- and data-driven spectroscopy learning approach is a promising and an easy-to-implement strategy.
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