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Description
In this era of large-scale spectroscopic stellar surveys, measurements of stellar attributes ("labels," i.e., parameters and abundances) must be made precise and consistent across surveys. Here, we demonstrate that this can be achieved by a data-driven approach to spectral modeling. With The Cannon, we transfer information from the APOGEE survey to determine precise T_eff_, logg, [Fe/H], and [{alpha}/M] from the spectra of 450000 LAMOST giants. The Cannon fits a predictive model for LAMOST spectra using 9952 stars observed in common between the two surveys, taking five labels from APOGEE DR12 as ground truth T_eff_, logg, [Fe/H], [{alpha}/M], and K-band extinction A_k_. The model is then used to infer T_eff_, logg, [Fe/H], and [{alpha}/M] for 454180 giants, 20% of the LAMOST DR2 stellar sample. These are the first [{alpha}/M] values for the full set of LAMOST giants, and the largest catalog of [{alpha}/M] for giant stars to date. Furthermore, these labels are by construction on the APOGEE label scale; for spectra with S/N>50, cross-validation of the model yields typical uncertainties of 70K in T_eff_, 0.1 in logg, 0.1 in [Fe/H], and 0.04 in [{alpha}/M], values comparable to the broadly stated, conservative APOGEE DR12 uncertainties. Thus, by using "label transfer" to tie low-resolution (LAMOST R~1800) spectra to the label scale of a much higher-resolution (APOGEE R~22500) survey, we substantially reduce the inconsistencies between labels measured by the individual survey pipelines. This demonstrates that label transfer with The Cannon can successfully bring different surveys onto the same physical scale.
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