The GALAH Survey: A New Sample of Extremely Metal-poor Stars Using a Machine-learning Classification Algorithm

Extremely metal-poor (EMP) stars provide a valuable probe of early chemical enrichment in the Milky Way. Here we leverage a large sample of ∼600,000 high-resolution stellar spectra from the GALAH survey plus a machine-learning algorithm to find 54 candidates with estimated [Fe/H] ≤−3.0, six of which...

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Vydané v:	The Astrophysical journal Ročník 930; číslo 1; s. 47 - 67
Hlavní autori:	Hughes, Arvind C. N., Spitler, Lee R., Zucker, Daniel B., Nordlander, Thomas, Simpson, Jeffrey, Da Costa, Gary S., Ting, Yuan-Sen, Li, Chengyuan, Bland-Hawthorn, Joss, Buder, Sven, Casey, Andrew R., De Silva, Gayandhi M., D’Orazi, Valentina, Freeman, Ken C., Hayden, Michael R., Kos, Janez, Lewis, Geraint F., Lin, Jane, Lind, Karin, Martell, Sarah L., Schlesinger, Katharine J., Sharma, Sanjib, Zwitter, Tomaž
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Philadelphia The American Astronomical Society 01.05.2022 IOP Publishing
Predmet:	Algorithms Astrophysics CEMP stars Classification Distribution functions Galactic archaeology Galaxy stellar content High resolution spectroscopy Machine learning Metallicity Milky Way Polls & surveys Population II stars Population III stars Spectroscopy Stars Stellar abundances Stellar classification Stellar spectra
ISSN:	0004-637X, 1538-4357, 1538-4357
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Popis
Shrnutí:	Extremely metal-poor (EMP) stars provide a valuable probe of early chemical enrichment in the Milky Way. Here we leverage a large sample of ∼600,000 high-resolution stellar spectra from the GALAH survey plus a machine-learning algorithm to find 54 candidates with estimated [Fe/H] ≤−3.0, six of which have [Fe/H] ≤−3.5. Our sample includes ∼20% main-sequence EMP candidates, unusually high for EMP star surveys. We find the magnitude-limited metallicity distribution function of our sample is consistent with previous work that used more complex selection criteria. The method we present has significant potential for application to the next generation of massive stellar spectroscopic surveys, which will expand the available spectroscopic data well into the millions of stars.
Bibliografia:	AAS37160 Stars and Stellar Physics ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ISSN:	0004-637X 1538-4357 1538-4357
DOI:	10.3847/1538-4357/ac5fa7