Eight-Dimensional Mid-Infrared/Optical Bayesian Quasar Selection
Gordon T. Richards (1), Rajesh P. Deo (1), Mark Lacy (2), Adam D., Myers (3), Robert C. Nichol (4), Nadia L. Zakamska (5), Robert J. Brunner, (3), W. N. Brandt (6), Alexander G. Gray (7), John K. Parejko (1), Andrew, Ptak (8), Donald P. Schneider (6)

TL;DR
This paper presents a Bayesian multiwavelength approach combining mid-infrared and optical data to efficiently select quasars, significantly improving identification accuracy and redshift estimation over previous methods.
Contribution
The study introduces an 8-dimensional Bayesian quasar selection technique that enhances detection of quasars, including obscured types, using combined MIR and optical data.
Findings
Cataloged 5546 quasar candidates with 97.7% recovery of known quasars.
Achieved 97% completeness and 10% contamination using only two IRAC bands.
Photometric redshift accuracy of 93.6%, stable even with fewer MIR bands.
Abstract
We explore the multidimensional, multiwavelength selection of quasars from mid-IR (MIR) plus optical data, specifically from Spitzer-IRAC and the Sloan Digital Sky Survey (SDSS). We apply modern statistical techniques to combined Spitzer MIR and SDSS optical data, allowing up to 8-D color selection of quasars. Using a Bayesian selection method, we catalog 5546 quasar candidates to an 8.0 um depth of 56 uJy over an area of ~24 sq. deg; ~70% of these candidates are not identified by applying the same Bayesian algorithm to 4-color SDSS optical data alone. Our selection recovers 97.7% of known type 1 quasars in this area and greatly improves the effectiveness of identifying 3.5<z<5 quasars. Even using only the two shortest wavelength IRAC bandpasses, it is possible to use our Bayesian techniques to select quasars with 97% completeness and as little as 10% contamination. This sample has a…
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