文章基本信息

标题：APOGEE Net: An Expanded Spectral Model of Both Low-mass and High-mass Stars
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作者：Dani Sprague ; Connor Culhane ; Marina Kounkel 等
期刊名称：The Astronomical journal
印刷版ISSN：0004-6256
电子版ISSN：1538-3881
出版年度：2022
卷号：163
期号：4
页码：1-13
DOI：10.3847/1538-3881/ac4de7
语种：English
出版社：American Institute of Physics
摘要：We train a convolutional neural network, APOGEE Net, to predict Teff, , and, for some stars, [Fe/H], based on the APOGEE spectra. This is the first pipeline adapted for these data that is capable of estimating these parameters in a self-consistent manner not only for low-mass stars, (such as main-sequence dwarfs, pre-main-sequence stars, and red giants), but also high-mass stars with Teff in excess of 50,000 K, including hot dwarfs and blue supergiants. The catalog of ∼650,000 stars presented in this paper allows for a detailed investigation of the star-forming history of not just the Milky Way, but also of the Magellanic clouds, as different type of objects tracing different parts of these galaxies can be more cleanly selected through their distinct placement in Teff– parameter space than in previous APOGEE catalogs produced through different pipelines.