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We present an analysis of the mid-infrared (MIR) and optical properties of type 1 (broad-line) quasars detected by the Spitzer Space Telescope. The MIR color-redshift relation is characterized to z $ 3, with predictions to z ¼ 7. We demonstrate how combining MIR and optical colors can yield even more efficient selection of active galactic nuclei (AGNs) than MIR or optical colors alone. Composite spectral energy distributions (SEDs) are constructed for 259 quasars with both Sloan Digital Sky Survey and Spitzer photometry, supplemented by near-IR, GALEX, VLA, and ROSAT data, where available. We discuss how the spectral diversity of quasars influences the determination of bolometric luminosities and accretion rates; assuming the mean SED can lead to errors as large as 50% for individual quasars when inferring a bolometric luminosity from an optical luminosity. Finally, we show that careful consideration of the shape of the mean quasar SED and its redshift dependence leads to a lower estimate of the fraction of reddened /obscured AGNs missed by optical surveys as compared to estimates derived from a single mean MIR to optical flux ratio.

We determine the number counts and z = 0-5 luminosity function for a well-defined, homogeneous sample of quasars from the Sloan Digital Sky Survey (SDSS). We conservatively define the most uniform statistical sample possible, consisting of 15,343 quasars within an effective area of 1622 deg 2 that was derived from a parent sample of 46,420 spectroscopically confirmed broad-line quasars in the 5282 deg 2 of imaging data from SDSS Data Release Three. The sample extends from i = 15 to i = 19.1 at z 3 and to i = 20.2 for z 3. The number counts and luminosity function agree well with the results of the Two-Degree Field QSO Redshift Survey (2QZ) at redshifts and luminosities where the SDSS and 2QZ quasar samples overlap, but the SDSS data probe to much higher redshifts than does the 2QZ sample. The number density of luminous quasars peaks between redshifts 2 and 3, although uncertainties in the selection function in this range do not allow us to determine the peak redshift more precisely. Our best fit model has a flatter bright end slope at high redshift than at low redshift. For z < 2.4 the data are best fit by a redshift-independent slope of β = −3.1 (Φ(L) ∝ L β ). Above z = 2.4 the slope flattens with redshift to β −2.37 at z = 5. This slope change, which is significant at the 5-sigma level, must be accounted for in models of the evolution of accretion onto supermassive black holes.