Understanding the non-linear clustering of high redshift galaxies
  We incorporate the non-linear clustering of dark matter halos, as modelled by
Jose et al. (2016) into the halo model to better understand the clustering of
Lyman break galaxies (LBGs) in the redshift range $z=3-5$. We find that, with
this change, the predicted LBG clustering increases significantly on
quasi-linear scales ($0.1 \leq r\,/\,h^{-1} \,{\rm Mpc} \leq 10$) compared to
that in the linear halo bias model. This in turn results in an increase in the
clustering of LBGs by an order of magnitude on angular scales $5" \leq \theta
\leq 100"$. Remarkably, the predictions of our new model on the whole remove
the systematic discrepancy between the linear halo bias predictions and the
observations. The correlation length and large scale galaxy bias of LBGs are
found to be significantly higher in the non-linear halo bias model than in the
linear halo bias model. The resulting two-point correlation function retains an
approximate power-law form in contrast with that computed using the linear halo
bias theory. We also find that the non-linear clustering of LBGs increases with
increasing luminosity and redshift. Our work emphasizes the importance of using
non-linear halo bias in order to model the clustering of high-z galaxies to
probe the physics of galaxy formation and extract cosmological parameters
reliably.
