Title:Nonlinear Stochastic Biasing of Peaks and Halos: Scale-Dependence, Time-Evolution, and Redshift-Space Distortion from Cosmological N-body Simulations

Abstract: We quantify the degree of nonlinearity and stochasticity of the clustering of biased objects, using cosmological N-body simulations. Adopting the peaks and the halos as representative biasing models, we focus on the two-point correlation of the biased objects, dark matter and their cross-correlation. Especially, we take account of the effect of redshift-space distortion and attempt to clarify the scale-dependence and the time-dependence by analyzing the biasing factor and the cross-correlation factor. On small scales, stochasticity and nonlinearity become appreciable and strongly object-dependent, especially in redshift space due to the pair-wise velocity dispersion of the biased objects. Nevertheless, an approximation of deterministic linear biasing $\delta_{\rm obj}\simeq b_{\rm obj} \delta_{\rm mass}$ works reasonably well even in the quasi-linear regime $r > 10 h^{-1}$ Mpc, and linear redshift-space distortion explains the clustering amplitudes in redshift space in this regime.