How accurate is it to update the cosmology of your halo catalogues?

Abstract

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.

14 pages, 2 tables, 10 figures. Accepted for publication in MNRAS

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