Dynamical analysis of clusters of galaxies from cosmological simulations
arXiv:2105.09126 · doi:10.1051/0004-6361/202140326
Abstract
Studies of cluster mass and velocity anisotropy profiles are useful tests of dark matter models, and of the assembly history of clusters of galaxies. These studies might be affected by unknown systematics caused by projection effects. We aim at testing observational methods for the determination of mass and velocity anisotropy profiles of clusters of galaxies. Particularly, we focus on the MAMPOSSt technique (Mamon et al. 2013). We use results from two semi-analytic models of galaxy formation coupled with high-resolution N-body cosmological simulations, the catalog of De Lucia & Blaizot (2007) and the FIRE catalog based on the new GAlaxy Evolution and Assembly model. We test the reliability of the Jeans equation in recovering the true mass profile when full projected phase-space information is available. We examine the reliability of the MAMPOSSt method in estimating the true mass and velocity anisotropy profiles of the simulated halos when only projected phase-space information is available, as in observations. The spherical Jeans equation provides a reliable tool for the determination of cluster mass profiles, also for subsamples of tracers separated by galaxy color. Results are equally good for prolate and oblate clusters. Using only projected phase-space information, MAMPOSSt provides estimates of the mass profile with a standard deviation of 35-69 %, and a negative bias of 7-17 %, nearly independent of radius, and that we attribute to the presence of interlopers in the projected samples. The bias changes sign, that is, the mass is over-estimated, for prolate clusters with their major axis aligned along the line-of-sight. MAMPOSSt measures the velocity anisotropy profiles accurately in the inner cluster regions, with a slight overestimate in the outer regions, both for the whole sample of observationally-identified cluster members and separately for red and blue galaxies.
14 pages, 17 figures
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