Reliable stellar abundances of individual stars with the MUSE integral-field spectrograph

@article{Wang2022ReliableSA,
  title={Reliable stellar abundances of individual stars with the MUSE integral-field spectrograph},
  author={Zixiang Wang and Michael R. Hayden and Sanjib Sharma and Maosheng Xiang and Yuan-Sen Ting and Joss Bland-Hawthorn and Boquan Chen},
  journal={Monthly Notices of the Royal Astronomical Society},
  year={2022}
}
We present a novel approach to deriving stellar labels for stars observed in MUSE fields making use of data-driven machine learning methods. Taking advantage of the comparable spectral properties (resolution, wavelength coverage) of the LAMOST and MUSE instruments, we adopt the Data-Driven Payne (DD-Payne) model used on LAMOST observations and apply it to stars observed in MUSE fields. Remarkably, in spite of instrumental differences, according to the cross-validation of 27 LAMOST-MUSE common… 

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