Achieving Convergence in Galaxy Formation Models by Augmenting N-body   Merger Trees
  Accurate modeling of galaxy formation in a hierarchical, cold dark matter universe requires the use of sufficiently high-resolution merger trees to obtain convergence in the predicted properties of galaxies. When semi-analytic galaxy formation models are applied to cosmological N-body simulation merger trees, it is often the case that those trees have insufficient resolution to give converged galaxy properties. We demonstrate a method to augment the resolution of N-body merger trees by grafting in branches of Monte Carlo merger trees with higher resolution, but which are consistent with the pre-existing branches in the N-body tree. We show that this approach leads to converged galaxy properties. 
Andrew J. Benson (1), Chris Cannella (2), Shaun Cole (3) ((1) Carnegie   Observatories, (2) Caltech, (3) University of Durham)
astro-ph.GA