Andrés N. Ruiz, Nelson D. Padilla, Mariano J. Domínguez, Sofía A. Cora
We test and present the application of the full rescaling method by Angulo &
White (2010) to change the cosmology of halo catalogues in numerical
simulations for cosmological parameter search using semi-analytic galaxy
properties. We show that a reduced form of the method can be applied in small
simulations with box side of ~50/h Mpc. We perform statistical tests on the
accuracy of the properties of rescaled individual haloes, and also on the
rescaled population as a whole. We find that individual positions and
velocities are recovered with almost no detectable biases. The dispersion in
the recovered halo mass does not seem to depend on the resolution of the
simulation. Regardless of the halo mass, the individual accretion histories,
spin parameter evolution and fraction of mass in substructures are well
recovered. The mass of rescaled haloes can be underestimated (overestimated)
for negative (positive) variations of either sigma_8 or Omega_m, in a way that
does not depend on the halo mass. Statistics of abundances and correlation
functions of haloes show also small biases of <10 percent when moving away from
the base simulation by up to 2 times the uncertainty in the WMAP7 cosmological
parameters. The merger tree properties related to the final galaxy population
in haloes also show small biases; the time since the last major merger, the
assembly time-scale, and a time-scale related to the stellar ages show
correlated biases which indicate that the spectral shapes of galaxies would
only be affected by global age changes of ~150 Myr. We show some of these
biases for different separations in the cosmological parameters with respect to
the desired cosmology so that these can be used to estimate the expected
accuracy of the resulting halo population. We also present a way to construct
grids of simulations to provide stable accuracy across the Omega_m vs sigma_8
parameter space.
View original:
http://arxiv.org/abs/1103.5074
No comments:
Post a Comment