Unveiling Quasars in Gaia DR3: Multimodal Classification and Redshift Estimation of BP/RP Sources with Deep Learning

The Astrophysical Journal Supplement Series, vol. 283, pp. 38

Abstract

Abstract We present a multimodal deep learning framework that classifies stars, galaxies, and quasars and accurately estimates quasar redshifts using Gaia DR3’s low-resolution BP/RP (XP) spectra, alongside astrometric, photometric, and CatWISE mid-infrared data. Our hierarchical classification model achieves an overall accuracy of 99.90%. Evaluating class-specific performance under a one-versus-rest framework, a precision of 99.61% and a recall of 99.83% are achieved for quasars. Furthermore, our spectral redshift regression model, SpecNet-Z, attains an rms error of 0.0682, a normalized median absolute deviation ( σ NMAD ) of 0.0048, and a catastrophic outlier rate of only 0.42%, demonstrating superior performance in the template-fitting approach in Gaia DR3. Applying this framework to the 219 million sources with public XP spectra, we produce the XP-Quasars catalog, containing 123,342 high-purity quasar candidates. This catalog includes 3763 new candidates not listed in the official GDR3 QSO catalog. Our work provides a robust and scalable method that serves as a valuable resource for current active galactic nuclei and cosmological studies and as a vital precursor for the analysis of the complete XP spectra dataset anticipated in Gaia DR4. The XP-Quasar catalog and associated source code are publicly available via Zenodo ( https://doi.org/10.5281/zenodo.17960118 ) and GitHub ( https://github.com/Shijinghang/xp-quasars ).

Authors 13

1. Jinghang Shi

   Chinese Academy of Sciences · National Astronomical Observatories · University of Chinese Academy of Sciences

   Affiliation as printed

   National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, People’s Republic of China; zyx@bao.ac.cn, lal@bao.ac.cn

   University of Chinese Academy of Sciences, Beijing 100049, People’s Republic of China

2. Yanxia Zhang

   Chinese Academy of Sciences · National Astronomical Observatories

   Affiliation as printed

   National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, People’s Republic of China; zyx@bao.ac.cn, lal@bao.ac.cn

3. Changhua Li

   Chinese Academy of Sciences · National Astronomical Observatories

   Affiliation as printed

   National Astronomical Data Center, Beijing 100101, People’s Republic of China

   National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, People’s Republic of China; zyx@bao.ac.cn, lal@bao.ac.cn

4. J. L. Zhang

   Chinese Academy of Sciences · National Astronomical Observatories

   Affiliation as printed

   National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, People’s Republic of China; zyx@bao.ac.cn, lal@bao.ac.cn

5. Zihan Kang

   Chinese Academy of Sciences · National Astronomical Observatories · University of Chinese Academy of Sciences

   Affiliation as printed

   National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, People’s Republic of China; zyx@bao.ac.cn, lal@bao.ac.cn

   University of Chinese Academy of Sciences, Beijing 100049, People’s Republic of China

6. Shirui Wei

   Chinese Academy of Sciences · National Astronomical Observatories · University of Chinese Academy of Sciences

   Affiliation as printed

   National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, People’s Republic of China; zyx@bao.ac.cn, lal@bao.ac.cn

   University of Chinese Academy of Sciences, Beijing 100049, People’s Republic of China

7. Yuming Fu Aachen Leiden Observatory

   Leiden University · University of Groningen · Leiden Observatory

   Affiliation as printed

   Kapteyn Astronomical Institute, University of Groningen, P.O. Box 800, 9700 AV Groningen, The Netherlands

   Leiden Observatory, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands

8. Xue-Bing Wu

   Chinese Academy of Sciences · Peking University · National Astronomical Observatories

   Affiliation as printed

   Department of Astronomy, School of Physics, Peking University, Beijing 100871, People’s Republic of China

   Kavli Institute for Astronomy and Astrophysics, Peking University, Beijing 100871, People’s Republic of China

   National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, People’s Republic of China; zyx@bao.ac.cn, lal@bao.ac.cn

9. Xiao Kong

   Chinese Academy of Sciences · National Astronomical Observatories

   Affiliation as printed

   National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, People’s Republic of China; zyx@bao.ac.cn, lal@bao.ac.cn

10. Ali Luo

    Chinese Academy of Sciences · National Astronomical Observatories · University of Chinese Academy of Sciences

    Affiliation as printed

    National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, People’s Republic of China; zyx@bao.ac.cn, lal@bao.ac.cn

    University of Chinese Academy of Sciences, Beijing 100049, People’s Republic of China

11. Yongheng Zhao

    Chinese Academy of Sciences · National Astronomical Observatories

    Affiliation as printed

    National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, People’s Republic of China; zyx@bao.ac.cn, lal@bao.ac.cn

12. Dongwei Fan

    Chinese Academy of Sciences · National Astronomical Observatories

    Affiliation as printed

    National Astronomical Data Center, Beijing 100101, People’s Republic of China

    National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, People’s Republic of China; zyx@bao.ac.cn, lal@bao.ac.cn

13. Caizhan Yue

    Tianjin University

    Affiliation as printed

    College of Intelligence and Computing, Tianjin University, Tianjin, 300350, People’s Republic of China