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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Veröffentlicht in:The Astrophysical journal Jg. 930; H. 1; S. 47 - 67
Hauptverfasser: 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
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Philadelphia The American Astronomical Society 01.05.2022
IOP Publishing
Schlagworte:
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
Online-Zugang:Volltext
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Zusammenfassung: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.
Bibliographie:AAS37160
Stars and Stellar Physics
ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:0004-637X
1538-4357
1538-4357
DOI:10.3847/1538-4357/ac5fa7