The CatSouth Quasar Candidate Catalog for the Southern Sky and a Unified All-sky Catalog Based on Gaia DR3

Abstract The Gaia DR3 has provided a large sample of more than 6.6 million quasar candidates with high completeness but low purity. Previous work on the CatNorth quasar candidate catalog has shown that including external multiband data and applying machine learning methods can efficiently purify the original Gaia DR3 quasar candidate catalog and improve the redshift estimates. In this paper, we extend the Gaia DR3 quasar candidate selection to the Southern Hemisphere using data from SkyMapper, CatWISE, and Visible and Infrared Survey Telescope for Astronomy surveys. We train an XGBoost classifier on a unified set of high-confidence stars and spectroscopically confirmed quasars and galaxies. For sources with available Gaia BP/RP spectra, spectroscopic redshifts are derived using a pretrained convolutional neural network (RegNet). We also train an ensemble photometric redshift estimation model based on XGBoost, TabNet, and FT-Transformer, achieving a root mean square error of 0.2256 and a normalized median absolute deviation of 0.0187 on the validation set. By merging CatSouth with the previously published CatNorth catalog, we construct the unified all-sky CatGlobe catalog with nearly 1.9 million sources at G < 21, providing a comprehensive and high-purity quasar candidate sample for future spectroscopic and cosmological investigations.

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Publication Details

Journal
The Astrophysical Journal Supplement Series
Published
2025-08-01
DOI
https://doi.org/10.3847/1538-4365/ade999
Citations
4
Primary Topic
Galaxies: Formation, Evolution, Phenomena
Type
article
Field-Weighted Citation Impact
4.62

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article

The CatSouth Quasar Candidate Catalog for the Southern Sky and a Unified All-sky Catalog Based on Gaia DR3

K. I. Caputi, Christian Wolf, Yuxuan Pang, R. J. Bouwens et al.
4 citations
The Astrophysical Journal Supplement Series
Galaxies: Formation, Evolution, Phenomena
4.62
article

The CatSouth Quasar Candidate Catalog for the Southern Sky and a Unified All-sky Catalog Based on Gaia DR3

K. I. Caputi, Christian Wolf, Yuxuan Pang, R. J. Bouwens, Jin Qin, Yanli Ai, Zhi-Ying Huo, Ravi Joshi, Da-Ming Yang, Yifan Li, Yuming Fu, Yanxia Zhang, Xue-Bing Wu, Huimei Wang, Rui Zhu
article en
4 citations

Abstract

Abstract The Gaia DR3 has provided a large sample of more than 6.6 million quasar candidates with high completeness but low purity. Previous work on the CatNorth quasar candidate catalog has shown that including external multiband data and applying machine learning methods can efficiently purify the original Gaia DR3 quasar candidate catalog and improve the redshift estimates. In this paper, we extend the Gaia DR3 quasar candidate selection to the Southern Hemisphere using data from SkyMapper, CatWISE, and Visible and Infrared Survey Telescope for Astronomy surveys. We train an XGBoost classifier on a unified set of high-confidence stars and spectroscopically confirmed quasars and galaxies. For sources with available Gaia BP/RP spectra, spectroscopic redshifts are derived using a pretrained convolutional neural network (RegNet). We also train an ensemble photometric redshift estimation model based on XGBoost, TabNet, and FT-Transformer, achieving a root mean square error of 0.2256 and a normalized median absolute deviation of 0.0187 on the validation set. By merging CatSouth with the previously published CatNorth catalog, we construct the unified all-sky CatGlobe catalog with nearly 1.9 million sources at G < 21, providing a comprehensive and high-purity quasar candidate sample for future spectroscopic and cosmological investigations.

The Astrophysical Journal Supplement SeriesVol. 279(2)
Australian National University (AU), Leiden University (NL), Indian Institute of Astrophysics (IN), University of Groningen (NL), Chinese Academy of Sciences (CN), Peking University (CN), Kavli Institute for Theoretical Sciences (CN), Shenzhen Technology University (CN), National Astronomical Observatories (CN), Guangdong Institute of New Materials (CN)
Nederlandse Organisatie voor Wetenschappelijk Onderzoek
Openalex Percentile: Top 5%
Galaxies: Formation, Evolution, Phenomena
4.62
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