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Efficient Photometric Selection of Quasars from the Sloan Digital Sky Survey: 100,000 z<3 Quasars from Data Release One
Journal article

Efficient Photometric Selection of Quasars from the Sloan Digital Sky Survey: 100,000 z<3 Quasars from Data Release One

Gordon T Richards, Robert C Nichol, Alexander G Gray, Robert J Brunner, Robert H Lupton, Daniel E. Vanden Berk, Shang Shan Chong, Michael A Weinstein, Donald P Schneider, Scott F Anderson, …
The Astrophysical journal. Supplement series, v 155(2), pp 257-269
26 Aug 2004
url
https://arxiv.org/pdf/astro-ph/0408505View
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Abstract

Physics - Astrophysics of Galaxies Physics - Cosmology and Nongalactic Astrophysics Physics - Earth and Planetary Astrophysics Physics - High Energy Astrophysical Phenomena Physics - Instrumentation and Methods for Astrophysics Physics - Solar and Stellar Astrophysics
Astrophys.J.Suppl. 155 (2004) 257-269 We present a catalog of 100,563 unresolved, UV-excess (UVX) quasar candidates to g=21 from 2099 deg^2 of the Sloan Digital Sky Survey (SDSS) Data Release One (DR1) imaging data. Existing spectra of 22,737 sources reveals that 22,191 (97.6%) are quasars; accounting for the magnitude dependence of this efficiency, we estimate that 95,502 (95.0%) of the objects in the catalog are quasars. Such a high efficiency is unprecedented in broad-band surveys of quasars. This ``proof-of-concept'' sample is designed to be maximally efficient, but still has 94.7% completeness to unresolved, g<~19.5, UVX quasars from the DR1 quasar catalog. This efficient and complete selection is the result of our application of a probability density type analysis to training sets that describe the 4-D color distribution of stars and spectroscopically confirmed quasars in the SDSS. Specifically, we use a non-parametric Bayesian classification, based on kernel density estimation, to parameterize the color distribution of astronomical sources -- allowing for fast and robust classification. We further supplement the catalog by providing photometric redshifts and matches to FIRST/VLA, ROSAT, and USNO-B sources. Future work needed to extend the this selection algorithm to larger redshifts, fainter magnitudes, and resolved sources is discussed. Finally, we examine some science applications of the catalog, particularly a tentative quasar number counts distribution covering the largest range in magnitude (14.2<g<21.0) ever made within the framework of a single quasar survey.

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