A photometric catalogue of quasars and other point sources in the Sloan Digital Sky Survey

Abstract

We present a catalogue of about six million unresolved photometric detections in the Sloan Digital Sky Survey (SDSS) Seventh Data Release, classifying them into stars, galaxies and quasars. We use a machine learning classifier trained on a subset of spectroscopically confirmed objects from 14th to 22ndmagnitude in the SDSSiband. Our catalogue consists of 2430625 quasars, 3544036 stars and 63586 unresolved galaxies from 14th to 24thmagnitude in the SDSSiband. Our algorithm recovers 99.96 per cent of spectroscopically confirmed quasars and 99.51 per cent of stars toi~ 21.3 in the colour window that we study. The level of contamination due to data artefacts for objects beyondi= 21.3 is highly uncertain and all mention of completeness and contamination in the paper are valid only for objects brighter than this magnitude. However, a comparison of the predicted number of quasars with the theoretical number counts shows reasonable agreement. © 2011 The Authors Monthly Notices of the Royal Astronomical Society © 2011 RAS.