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 z̅ 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^{z̅ =1:40}_Q = 2:41±0:08 (P_<x² = 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_<x² = 0:482]. We find b_Q 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 ± ^4:4_1:9 %, 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 M_DMH = (5:2 ± 0:6) x 10¹² h^-1 M_⊙. At  z̅ ∼ 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 b_Q is constant with luminosity to within Δb_Q ∼ 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.