Bayesian High-Redshift Quasar Classification from Optical and Mid-IR
  Photometry
  We identify 885,503 type 1 quasar candidates to i<22 using the combination of
optical and mid-IR photometry. Optical photometry is taken from the Sloan
Digital Sky Survey-III: Baryon Oscillation Spectroscopic Survey
(SDSS-III/BOSS), while mid-IR photometry comes from a combination of data from
the Wide-Field Infrared Survey Explorer (WISE) "ALLWISE" data release and
several large-area Spitzer Space Telescope fields. Selection is based on a
Bayesian kernel density algorithm with a training sample of 157,701
spectroscopically-confirmed type-1 quasars with both optical and mid-IR data.
Of the quasar candidates, 733,713 lack spectroscopic confirmation (and 305,623
are objects that we have not previously classified as photometric quasar
candidates). These candidates include 7874 objects targeted as high probability
potential quasars with 3.5<z<5 (of which 6779 are new photometric candidates).
Our algorithm is more complete to z>3.5 than the traditional mid-IR selection
"wedges" and to 2.2<z<3.5 quasars than the SDSS-III/BOSS project. Number counts
and luminosity function analysis suggests that the resulting catalog is
relatively complete to known quasars and is identifying new high-z quasars at
z>3. This catalog paves the way for luminosity-dependent clustering
investigations of large numbers of faint, high-redshift quasars and for further
machine learning quasar selection using Spitzer and WISE data combined with
other large-area optical imaging surveys.
