Clustering Analyses of 300,000 Photometrically Classified Quasars. I. Luminosity and Redshift Evolution in Quasar Bias

Using ~300,000 photometrically classified quasars, by far the largest quasar sample ever used for such analyses, we study the redshift and luminosity evolution of quasar clustering on scales of ~50 h-1 kpc to ~20 h-1 Mpc from redshifts of z̄ ~ 0.75-2.28. We parameterize our clustering amplitudes using realistic dark matter models and find that a ΛCDM power spectrum provides a superb fit to our data with a redshift-averaged quasar bias of b = 2.41 ± 0.08 (P<χ2 = 0.847) for σ8 = 0.9. This represents a better fit than the best-fit power-law model [ω = (0.0493 ± 0.0064) θ-0.928±0.055; P<χ2 = 0.482]. We find bQ increases with redshift. This evolution is significant at >99.6% using our data set alone, increasing to >99.9999% if stellar contamination is not explicitly parameterized. We measure the quasar classification efficiency across our full sample as a = 95.6 ± %, a star-quasar separation comparable to the star-galaxy separation in many photometric studies of galaxy clustering. We derive the mean mass of the dark matter halos hosting quasars as MDMH = (5.2 ± 0.6) × 1012 h-1 M☉. At z̄ ~ 1.9 we find a 1.5 σ deviation from luminosity-independent quasar clustering; this suggests that increasing our sample size by a factor of ~1.8 could begin to constrain any luminosity dependence in quasar bias at z ~ 2. Our results agree with recent studies of quasar environments at z < 0.4, which detected little luminosity dependence to quasar clustering on proper scales ≳50 h-1 kpc. At z < 1.6, our analysis suggests that bQ is constant with luminosity to within ΔbQ ~ 0.6, and that, for g < 21, angular quasar autocorrelation measurements are unlikely to have sufficient statistical power at z ≲ 1.6 to detect any luminosity dependence in quasars' clustering.