Spectroscopic Target Selection in the Sloan Digital Sky Survey: The Quasar Sample
Gordon T. Richards, Xiaohui Fan, Heidi Jo Newberg, Michael A. Strauss, Daniel E. Vanden Berk, Donald P. Schneider, Brian Yanny, Adam Boucher, Scott Burles, Joshua A. Frieman, James E. Gunn, Patrick B. Hall, Zeljko Ivezic, Stephen Kent, Jon Loveday, Robert H. Lupton, Constance M. Rockosi, David J. Schlegel, Chris Stoughton, Mark SubbaRao, Donald G. York
Abstract
We describe the algorithm for selecting quasar candidates for optical spectroscopy in the Sloan Digital Sky Survey. Quasar candidates are selected via their non-stellar colors in "ugriz" broad-band photometry, and by matching unresolved sources to the FIRST radio catalogs. The automated algorithm is sensitive to quasars at all redshifts lower than z=5.8. Extended sources are also targeted as low-redshift quasar candidates in order to investigate the evolution of Active Galactic Nuclei (AGN) at the faint end of the luminosity function. Nearly 95% of previously known quasars are recovered (based on 1540 quasars in 446 square degrees). The overall completeness, estimated from simulated quasars, is expected to be over 90%, whereas the overall efficiency (quasars:quasar candidates) is better than 65%. The selection algorithm targets ultraviolet excess quasars to i*=19.1 and higher-redshift (z>3) quasars to i*=20.2, yielding approximately 18 candidates per square degree. In addition to selecting ``normal'' quasars, the design of the algorithm makes it sensitive to atypical AGN such as Broad Absorption Line quasars and heavily reddened quasars.
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