A Machine Learning Quasar Candidate Catalog with Photometric Redshifts from KiDS DR5 and AllWISE
Year: 2026
Type: article
Abstract: We present two complementary machine-readable catalogs for quasar (QSO) candidate selection in the Kilo-Degree Survey (KiDS) DR5. The KiDS-only catalog covers the full survey source sample and provides optical/near-infrared-based classifications together with QSO photometric redshift estimates derived without Wide-field Infrared Survey Explorer (WISE) information. The KiDS–AllWISE catalog is restricted to sources with AllWISE counterparts and provides WISE-assisted classifications and photometric redshifts. Separate stacking ensembles are trained to distinguish galaxies, stars, and QSOs. On a stratified held-out test set, the WISE-assisted classifier achieves an overall accuracy of 98.34%, a macroaveraged area under the receiver operating characteristic curve (ROC AUC) of 99.78%, and a QSO F1-score of 97.09%. Spatially disjoint R.A.-block validation yields QSO F1-scores of 95.87%–96.31%, indicating only modest spatial degradation. Feature-ablation tests show that W1/W2-based mid-infrared information provides the largest gain in QSO recovery, whereas Bayesian photometric redshift (BPZ)-derived quantities have only a minor effect. For QSO photometric redshift estimation, we train a LightGBM–XGBoost ensemble on Sloan Digital Sky Survey (SDSS) DR16 Quasar Catalog (DR16Q) quasars with valid optical and WISE photometry. On 94,057 held-out quasars, the WISE-assisted model achieves σ NMAD = 0.0633 and a catastrophic-outlier fraction of η = 12.0%; excluding WISE features degrades these values to σ NMAD = 0.0948 and η = 26.8%. Both catalogs provide probability-ranked QSO candidates and thresholded p Q samples for different follow-up priorities. As the candidates are not spectroscopically confirmed, statistical applications require independent calibration of the corresponding selection functions.
Authors: Sen Pang, Yanxia Zhang, Jinghang Shi
Language: English
Subfield: Astronomy and Astrophysics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $4,499
Funders: U.S. Department of Energy, Alfred P. Sloan Foundation, Yale University, Carnegie Institution of Washington, Vanderbilt University, Ohio State University, University of Washington, Johns Hopkins University, Carnegie Mellon University, University of Notre Dame, University of Portsmouth, New Mexico State University, York University, University of Oxford, National Natural Science Foundation of China, Ministério da Ciência, Tecnologia e Inovação, Universidad Nacional Autónoma de México, Max-Planck-Institut für Astrophysik, Max-Planck-Institut für Astronomie, Instituto de Astrofísica de Canarias, Office of Science, University of Colorado Boulder, Smithsonian Astrophysical Observatory, Leibniz-Gemeinschaft, Lawrence Berkeley National Laboratory
Awards: G7555188699, G8207393527
OpenAlex ID: W7222913549