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          Institute: MPI für Astronomie     Collection: Publikationen_mpia     Display Documents



ID: 742406.0, MPI für Astronomie / Publikationen_mpia
Measuring 14 elemental abundances with R = 1800 LAMOST spectra
Authors:Ting, Y.-S.; Rix, H.-W.; Conroy, C.; Ho, A. Y. Q.; Lin, J.
Date of Publication (YYYY-MM-DD):2017
Title of Journal:The Astrophysical Journal Letters
Volume:849
Issue / Number:1
Start Page:id. L9 (6 pp)
Audience:Not Specified
Abstract / Description:The LAMOST survey has acquired low-resolution spectra (R = 1800) for 5 million stars across the Milky Way, far more than any current stellar survey at a corresponding or higher spectral resolution. It is often assumed that only very few elemental abundances can be measured from such low-resolution spectra, limiting their utility for Galactic archaeology studies. However, Ting et al. used ab initio models to argue that low-resolution spectra should enable precision measurements of many elemental abundances, at least in theory. Here, we verify this claim in practice by measuring the relative abundances of 14 elements from LAMOST spectra with a precision of ≲ 0.1 dex for objects with {{S}}/{{{N}}}{LAMOST}≳ 30 (per pixel). We employ a spectral modeling method in which a data-driven model is combined with priors that the model gradient spectra should resemble ab initio spectral models. This approach assures that the data-driven abundance determinations draw on physically sensible features in the spectrum in their predictions and do not just exploit astrophysical correlations among abundances. Our analysis is constrained to the number of elemental abundances measured in the APOGEE survey, which is the source of the training labels. Obtaining high quality/resolution spectra for a subset of LAMOST stars to measure more elemental abundances as training labels and then applying this method to the full LAMOST catalog will provide a sample with more than 20 elemental abundances, which is an order of magnitude larger than current high-resolution surveys, substantially increasing the sample size for Galactic archaeology.
Free Keywords:methods: data analysis; stars: abundances
External Publication Status:published
Document Type:Article
Communicated by:N. N.
Affiliations:MPI für Astronomie
Identifiers:ISSN:0004-637X
URL:http://adsabs.harvard.edu/abs/2017ApJ...849L...9T
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