Choose to smooth: Gaussian streaming with the truncated Zel'dovich
  approximation
  We calculate the dark matter halo correlation function in redshift space
using the Gaussian streaming model (GSM). To determine the scale dependent
functions entering the streaming model we use local Lagrangian bias together
with Convolution Lagrangian perturbation theory (CLPT) which constitutes an
approximation to the Post-Zel'dovich approximation. On the basis of N-body
simulations we demonstrate that a smoothing of the initial conditions with the
Lagrangian radius improves the Zel'dovich approximation and its ability to
predict the displacement field of proto-halos. Based on this observation we
implement a "truncated" CLPT by smoothing the initial power spectrum and
investigate the dependence of the streaming model ingredients on the smoothing
scale. We find that the real space correlation functions of halos and their
mean pairwise velocity are optimised if the coarse graining scale is chosen to
be 1 Mpc/h at z=0, while the pairwise velocity dispersion is optimised if the
smoothing scale is chosen to be the Lagrangian size of the halo. We compare
theoretical results for the halo correlation function in redshift space to
measurements within the Horizon Run 2 N-body simulation halo catalog. We find
that this simple two-filter smoothing procedure in the spirit of the truncated
Zel'dovich approximation significantly improves the GSM+CLPT prediction of the
redshift space halo correlation function over the whole mass range from large
galaxy to galaxy cluster-sized halos.
