KiDS-BEXGO catalog

DOI

Within a Kilo-Degree Survey (KiDS) Strongly lensed QUAsar Detection project (KiDS-SQuaD), we built a catalogue of bright extragalactic objects from the KiDS DR4, with the main objective to select the reliable gravitationally lensed quasar candidates. We used machine learning algorithm, trained on Sloan Digital Sky Survey DR14 data, to classify sources from subsample (r<22mag) of KiDS DR4 on three classes: stars, quasars and galaxies. Resulting KiDS Bright EXtraGalactic Objects catalogue (KiDS-BEXGO) contains ~6M galaxies and ~0.2M quasars. KiDS-BEXGO represents the first comprehensive identification of bright extragalactic objects in the KiDS DR4 data.

Cone search capability for table J/A+A/632/A56/catalog (KiDS-BEXGO catalog)

Identifier
DOI http://doi.org/10.26093/cds/vizier.36320056
Source https://dc.g-vo.org/rr/q/lp/custom/CDS.VizieR/J/A+A/632/A56
Related Identifier https://cdsarc.cds.unistra.fr/viz-bin/cat/J/A+A/632/A56
Related Identifier https://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/A+A/632/A56
Metadata Access http://dc.g-vo.org/rr/q/pmh/pubreg.xml?verb=GetRecord&metadataPrefix=oai_b2find&identifier=ivo://CDS.VizieR/J/A+A/632/A56
Provenance
Creator Khramtsov V.; Sergeyev A.; Spiniello C.; Tortora C.; Napolitano N.R.,Agnello A.; Getman F.; de Jong J.T.A.; Kuijken K.; Radovich M.,Shan H.-Y.; Shulga V.
Publisher CDS
Publication Year 2019
Rights https://cds.unistra.fr/vizier-org/licences_vizier.html
OpenAccess true
Contact CDS support team <cds-question(at)unistra.fr>
Representation
Resource Type Dataset; AstroObjects
Discipline Astrophysical Processes; Astrophysics and Astronomy; Galactic and extragalactic Astronomy; High Energy Astrophysics; Natural Sciences; Observational Astronomy; Physics; Stellar Astronomy