| A non-parametric Bayesian classification selection algorithm was used to demonstrate that a combination of optical colors and variability features improves quasar classification efficiency and completeness over the use of colors alone, suggesting that this is a good set of features to use in classification algorithms for future time-domain focused sky surveys. These features were used to identify 35,820 type 1 quasar candidates in a 239 square deg field of the Sloan Digital Sky Survey (SDSS) Stripe 82. Color analysis was performed on 5-band single- and multi-epoch SDSS optical photometry and variability parameters were calculated by fitting the structure function of each object in each band with a power law model. Using variability alone, colors alone, and combining variability and colors, quasar completeness of 91%, 93%, and 97% and efficiency of 98%, 98%, and 97%, respectively, was achieved. Particular improvement was seen in the selection of quasars at 2.7 < z < 3.5 where quasars and stars have similar optical colors. Of the 22,867 quasar candidates that are not spectroscopically confirmed, 95.7% are dimmer than coadded i-band magnitude of 19.9, the cut off for spectroscopic follow-up on Stripe 82. Brighter than 19.9, 5.7% more quasar candidates were found without confirming spectra in sky regions otherwise considered complete. In addition to calculating empirical optical photometric redshifts for all candidate quasars, astrometric redshifts were calculated using parameters determined by measuring the differential chromatic refraction (DCR) effect with the purpose of breaking degeneracies in the photometric redshifts. The combined astro-photometric redshifts are more accurate than optical and near-infrared photometric redshifts. Potential observation schedules for the Large Synoptic Survey Telescope (LSST) were analyzed to determine how well quasars of different redshifts can be distinguished using the DCR effect. The resulting quasar sample has sufficient purity (and statistically correctable incompleteness) to produce a luminosity function comparable to those determined by spectroscopic investigations with photometric selection and redshift estimation. The quasar luminosity function of a uniformly-selected spectroscopic quasar sample, grouped according to emission-line properties, suggests that the space density of quasars with different underlying spectral energy distributions (SEDs) has evolved differently with redshift, peaking at different times. |
