Abstract / Description of output
Very metal-poor stars ([Fe/H] < -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 about 188,000 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 < 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 47%/47%/74% and completeness of 40%/94%/65% respectively. These three classifiers obtained a total of 11,000/116,000/45,000 bright metal-poor candidates. We apply model-T and model-GP on faint stars (BP > 16) and obtain 13,000/48,500 additional metal-poor candidates with purity 40%/50%, respectively. We make our metal-poor star catalogs publicly available, for further exploration of the metal-poor Milky Way.
Original language | English |
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Pages (from-to) | 10937-10954 |
Number of pages | 18 |
Journal | Monthly Notices of the Royal Astronomical Society |
Volume | 527 |
Issue number | 4 |
Early online date | 12 Dec 2023 |
DOIs | |
Publication status | Published - 1 Feb 2024 |
Keywords / Materials (for Non-textual outputs)
- methods: statistical
- stars: Population II
- techniques: spectroscopic
- techniques: photometric