Nonlinear clustering in models with primordial non-Gaussianity: the halo
  model approach
  We develop the halo model of large-scale structure as an accurate tool for
probing primordial non-Gaussianity. In this study we focus on understanding the
matter clustering at several redshifts. The primordial non-Gaussianity is
modeled as a quadratic correction to the local Gaussian potential, and is
characterized by the parameter f_NL. In our formulation of the halo model we
pay special attention to the effect of halo exclusion, and show that this can
potentially solve the long standing problem of excess power on large scales in
this model. The model depends on the mass function, clustering and density
profiles of halos. We test these ingredients using a large ensemble of
high-resolution Gaussian and non-Gaussian numerical simulations. In particular,
we provide a first exploration of how density profiles change in the presence
of primordial non-Gaussianities. We find that for f_NL positive/negative high
mass halos have an increased/decreased core density, so being more/less
concentrated than in the Gaussian case. We also examine the halo bias and show
that, if the halo model is correct, then there is a small asymmetry in the
scale-dependence of the bias on very large scales, which arises because the
Gaussian bias must be renormalized. We show that the matter power spectrum is
modified by ~2.5% and ~3.5% on scales k~1.0 h/Mpc at z=0 and z=1, respectively.
Our halo model calculation reproduces the absolute amplitude to within 10% and
the ratio of non-Gaussian to Gaussian spectra to within 1%. We also measure the
matter correlation functions and find similarly good agreement between the
model and the data. We anticipate that this modeling will be useful for
constraining f_NL from measurements of the shear correlation function in future
weak lensing surveys such as Euclid.
