The nonlinear probability distribution function in models with local   primordial non-Gaussianity
  We use the spherical evolution approximation to investigate nonlinear evolution from the non-Gaussian initial conditions characteristic of the local f_nl model. We provide an analytic formula for the nonlinearly evolved probability distribution function of the dark matter which shows that the under-dense tail of the nonlinear PDF in the f_nl model should differ significantly from that for Gaussian initial conditions. Measurements of the under-dense tail in numerical simulations may be affected by discreteness effects, and we use a Poisson counting model to describe this effect. Once this has been accounted for, our model is in good quantitative agreement with the simulations. 
Tsz Yan Lam (Penn) and Ravi K. Sheth (Penn)