Quasi-nonlinear evolution of stochastic bias

It is generally believed that the spatial distribution of galaxies does not trace that of the total mass. Understanding the bias effect is therefore n ecessary to determine the cosmological parameters and the primordial densit y fluctuation spectrum from the galaxy survey. The deterministic descriptio n of bias may not be appropriate because of the various stochasticity of ga laxy formation process. In nature, the biasing is epoch dependent, and a re cent deep survey of the galaxy shows large biasing at high redshift. Hence, we investigate quasi-nonlinear evolution of the stochastic bias by using t he tree-level perturbation method. Especially the influence of the initial cross-correlation on the evolution of the skewness and the bi-spectrum is e xamined in detail. We find that the nonlinear bias can be generated dynamic ally. The small value of the initial cross-correlation can bend the delta(g )-delta(m) relation effectively and easily lead to the negative curvature ( b(2) < 0). We also propose a method to predict the bias, cross-correlation, and skewness at high redshift. As an illustration, the possibility of larg e biasing at high redshift is discussed. Provided the present bias paramete r as b = 1.5 and Omega = 1.0, we: predict the large-scale bias to be b = 4. 63 at z = 3 by fitting the bi-spectrum to the Lick catalog data. Our result s will be important for the future deep sky survey.