SIMBAD references

2022ApJ...930...47H - Astrophys. J., 930, 47-47 (2022/May-1)

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

HUGHES A.C.N., SPITLER L.R., ZUCKER D.B., NORDLANDER T., SIMPSON J., DA COSTA G.S., TING Y.-S., LI C., BLAND-HAWTHORN J., BUDER S., CASEY A.R., DE SILVA G.M., D'ORAZI V., FREEMAN K.C., HAYDEN M.R., KOS J., LEWIS G.F., LIN J., LIND K., MARTELL S.L., SCHLESINGER K.J., SHARMA S., ZWITTER T. (The GALAH Collaboration)

Abstract (from CDS):

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.

Abstract Copyright: © 2022. The Author(s). Published by the American Astronomical Society.

Journal keyword(s): Galactic archaeology - Stellar abundances - Stellar classification - Classification - CEMP stars - Population II stars - Population III stars - Galaxy stellar content - High resolution spectroscopy

Status at CDS : All or part of tables of objects will be ingested in SIMBAD with priority 1.

Simbad objects: 23

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