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Modelling Baryon Acoustic Oscillations with Perturbation Theory and Stochastic Halo Biasing

In this work we investigate the generation of mock halo catalogues based on perturbation theory and nonlinear stochastic biasing with the novel PATCHY-code. In particular, we use Augmented Lagrangian Perturbation Theory (ALPT) to generate a dark matter density field on a mesh starting from Gaussian fluctuations and to compute the peculiar velocity field. ALPT is based on a combination of second order LPT (2LPT) on large scales and the spherical collapse model on smaller scales. We account for the systematic deviation of perturbative approaches from N-body simulations together with halo biasing adopting an exponential bias model. We then account for stochastic biasing by defining three regimes: a low, an intermediate and a high density regime, using a Poisson distribution in the intermediate regime and the negative binomial distribution to model over-dispersion in the high density regime. Since we focus in this study on massive halos, we suppress the generation of halos in the low density regime. The various nonlinear and stochastic biasing parameters, and density thresholds (five) are calibrated with the large BigMultiDark N-body simulation to match the power spectrum of the corresponding halo population. Our mock catalogues show power spectra, both in real- and redshift-space, which are compatible with N-body simulations within about 2% up to k ~ 1 h Mpc^-1 at z = 0.577 for a sample of halos with the typical BOSS CMASS galaxy number density. The corresponding correlation functions are compatible down to a few Mpc. We also find that neglecting over-dispersion in high density regions produces power spectra with deviations of 10% at k ~ 0.4 h Mpc^-1. These results indicate the need to account for an accurate statistical description of the galaxy clustering for precise studies of large-scale surveys.