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

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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 kpc/h to ~20 Mpc/h from redshifts of z~0.75 to z~2.28. We parameterize our clustering amplitudes using realistic dark matter models, and find that a LCDM power spectrum provides a superb fit to our data with a redshift-averaged quasar bias of b_Q = 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 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 +/- 4.41.9%, a star-quasar separation comparable with 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)x10¹² M_solar/h. At z~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 kpc/h. At z < 1.6, our analysis suggests that b_Q is constant with luminosity to within ~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.