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 22nd magnitude in the SDSS i band. Our catalogue consists of 2 430 625 quasars, 3 544 036 stars and 63 586 unresolved galaxies from 14th to 24th magnitude in the SDSS i band. Our algorithm recovers 99.96 per cent of spectroscopically confirmed quasars and 99.51 per cent of stars to i ∼ 21.3 in the colour window that we study. The level of contamination due to data artefacts for objects beyond i = 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.
- Publication:
-
Monthly Notices of the Royal Astronomical Society
- Pub Date:
- January 2012
- DOI:
- 10.1111/j.1365-2966.2011.19674.x
- arXiv:
- arXiv:1011.2173
- Bibcode:
- 2012MNRAS.419...80A
- Keywords:
-
- methods: statistical;
- techniques: photometric;
- astronomical data bases: miscellaneous;
- catalogues;
- surveys;
- Astrophysics - Instrumentation and Methods for Astrophysics;
- Computer Science - Artificial Intelligence
- E-Print:
- 16 pages, Ref. No. MN-10-2382-MJ.R2, accepted for publication in MNRAS Main Journal, April 2011