In:
Monthly Notices of the Royal Astronomical Society, Oxford University Press (OUP)
Abstract:
Very metal-poor stars ($\rm [Fe/H] & lt; -2$) in the Milky Way are fossil records of early chemical evolution and the assembly and structure of the Galaxy. However, they are rare and hard to find. Gaia DR3 has provided over 200 million low-resolution (R ≈ 50) XP spectra, which provides an opportunity to greatly increase the number of candidate metal-poor stars. In this work, we utilise the XGBoost classification algorithm to identify ∼200,000 very metal-poor star candidates. Compared to past work, we increase the candidate metal-poor sample by about an order of magnitude, with comparable or better purity than past studies. Firstly, we develop three classifiers for bright stars (BP & lt; 16). They are Classifier-T (for Turn-off stars), Classifier-GC (for Giant stars with high completeness), and Classifier-GP (for Giant stars with high purity) with expected purity of 52 %/45 %/76 % and completeness of 32 %/93 %/66 % respectively. These three classifiers obtained a total of 11,000/111,000/44,000 bright metal-poor candidates. We apply model-T and model-GP on faint stars (BP & gt; 16) and obtain 38,000/41,000 additional metal-poor candidates with purity 29 %/52 %, respectively. We make our metal-poor star catalogs publicly available, for further exploration of the metal-poor Milky Way.
Type of Medium:
Online Resource
ISSN:
0035-8711
,
1365-2966
DOI:
10.1093/mnras/stad3775
Language:
English
Publisher:
Oxford University Press (OUP)
Publication Date:
2023
detail.hit.zdb_id:
2016084-7
SSG:
16,12
