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Eight-dimensional mid-infrared/optical Bayesian quasar selection

Richards, Gordon T. and Deo, Rajesh P. and Lacy, Mark and Myers, Adam D. and Nichol, Robert C. and Zakamska, Nadia L. and Brunner, Robert J. and Brandt, W. N. and Gray, Alexander G. and Parejko, John K. and Ptak, Andrew and Schneider, Donald P. and Storrie-Lombardi, Lisa J. and Szalay, Alexander S. (2009) Eight-dimensional mid-infrared/optical Bayesian quasar selection. Astronomical Journal, 137 (4). pp. 3884-3899. ISSN 0004-6256.

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We explore the multidimensional, multiwavelength selection of quasars from mid-infrared (MIR) plus optical data, specifically from Spitzer-Infrared Array Camera (IRAC) and the Sloan Digital Sky Survey (SDSS). Traditionally, quasar selection relies on cuts in two-dimensional color space despite the fact that most modern surveys (optical and IR) are done in more than three bandpasses. In this paper, we apply modern statistical techniques to combined Spitzer MIR and SDSS optical data, allowing up to eight-dimensional (8-D) color selection of quasars. Using a Bayesian selection method, we catalog 5546 quasar candidates to an 8.0 μm depth of 56 μJy over an area of ~24 deg^2. Roughly 70% of these candidates are not identified by applying the same Bayesian algorithm to 4-color SDSS optical data alone. The 8-D optical+MIR selection on this data set recovers 97.7% of known type 1 quasars in this area and greatly improves the effectiveness of identifying 3.5 < z < 5 quasars which are challenging to identify (without considerable contamination) using MIR data alone. We demonstrate that, even using only the two shortest wavelength IRAC bandpasses (3.6 and 4.5 μm), it is possible to use our Bayesian techniques to select quasars with 97% completeness and as little as 10% contamination (as compared to ~60% contamination using color cuts alone). We compute photometric redshifts for our sample; comparison with known objects suggests a photometric redshift accuracy of 93.6% (Δz ± 0.3), remaining roughly constant when the two reddest MIR bands are excluded. Despite the fact that our methods are designed to find type 1 (unobscured) quasars, as many as 1200 of the objects are type 2 (obscured) quasar candidates. Coupling deep optical imaging data, with deep MIR data, could enable selection of quasars in significant numbers past the peak of the quasar luminosity function (QLF) to at least z ~ 4. Such a sample would constrain the shape of the QLF both above and below the break luminosity (L*Q) and enable quasar clustering studies over the largest range of redshift and luminosity to date, yielding significant gains in our understanding of the physics of quasars and their contribution to galaxy evolution.

Item Type:Article
Related URLs:
URLURL TypeDescription
Lacy, Mark0000-0002-3032-1783
Brandt, W. N.0000-0002-0167-2453
Ptak, Andrew0000-0001-5655-1440
Storrie-Lombardi, Lisa J.0000-0002-5987-5210
Additional Information:© 2009 The American Astronomical Society. Received 2008 October 15, accepted for publication 2009 January 17. Published 2009 March 6. G.T.R. acknowledges support from an Alfred P. Sloan Research Fellowship, a Gordon and Betty Moore Fellowship in Data Intensive Sciences, and NASA grants NNX06AE52G and 07-ADP07-0035. We thank Michael Strauss for critical review of the paper, and Ryan Riegel for help with the nonparametric classification algorithm. Funding for the SDSS and SDSS-II has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation, the U.S. Department of Energy, the National Aeronautics and Space Administration, the Japanese Monbukagakusho, the Max Planck Society, and the Higher Education Funding Council for England. The SDSS is managed by the Astrophysical Research Consortium for the Participating Institutions. The Participating Institutions are the American Museum of Natural History, Astrophysical Institute Potsdam, University of Basel, Cambridge University, Case Western Reserve University, University of Chicago, Drexel University, Fermilab, the Institute for Advanced Study, the Japan Participation Group, Johns Hopkins University, the Joint Institute for Nuclear Astrophysics, the Kavli Institute for Particle Astrophysics and Cosmology, the Korean Scientist Group, the Chinese Academy of Sciences (LAMOST), Los Alamos National Laboratory, the Max-Planck- Institute for Astronomy (MPIA), the Max-Planck-Institute for Astrophysics (MPA), New Mexico State University, Ohio State University, University of Pittsburgh, University of Portsmouth, Princeton University, the United States Naval Observatory, and the University of Washington. This work is based (in part) on archival data obtained with the Spitzer Space Telescope, which is operated by the Jet Propulsion Laboratory, California Institute of Technology under a contract with NASA. Support for this work was provided by an award issued by JPL/Caltech (1290740). Part of this work is based on observations obtained with XMM-Newton, an ESA science mission with instruments and contributions directly funded by ESA Member States and the USA (NASA). Some data presented here were obtained at KPNO, a division of the NOAO, which is operated by AURA under cooperative agreement with NSF.
Group:Infrared Processing and Analysis Center (IPAC)
Funding AgencyGrant Number
Alfred P. Sloan FoundationUNSPECIFIED
Gordon and Betty Moore FoundationUNSPECIFIED
Participating InstitutionsUNSPECIFIED
Department of Energy (DOE)UNSPECIFIED
Japanese MonbukagakushoUNSPECIFIED
Max Planck SocietyUNSPECIFIED
Higher Education Funding Council for EnglandUNSPECIFIED
Subject Keywords:catalogs; infrared: galaxies; methods: statistical; quasars: general
Issue or Number:4
Record Number:CaltechAUTHORS:20090420-081943033
Persistent URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:14022
Deposited By: Tony Diaz
Deposited On:21 Apr 2009 19:07
Last Modified:17 Nov 2019 23:43

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