Abstract

ABSTRACT The structural and dynamic properties of the dark matter haloes, though an important ingredient in understanding large-scale structure formation, require more conservative particle resolution than those required by halo mass alone in a simulation. This reduces the parameter space of the simulations, more severely for high redshift and large-volume mocks, which are required by the next-generation large-sky surveys. Here, we incorporate redshift and cosmology dependence into an algorithm that assigns accurate halo properties such as concentration, spin, velocity, and spatial distribution to the subresolution haloes in a simulation. By focusing on getting the right correlations with halo mass and local tidal anisotropy α measured at 4 × halo radius, our method will also recover the correlations of these small-scale structural properties with the large-scale environment, i.e. the halo assembly bias at all scales greater than 5 × halo radius. We find that the distribution of halo properties is universal with redshift and cosmology. By applying the algorithm to a large-volume simulation $(600\, h^{-1}\, {\rm Mpc})^3$, we can access the 30–500 particle haloes, thus gaining an order of magnitude in halo mass and two to three orders of magnitude in number density at z = 2–4. This technique reduces the cost of mocks required for the estimation of covariance matrices, weak lensing studies, or any large-scale clustering analysis with less massive haloes.

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