We review how dark matter is distributed in our local neighbourhood from an observational and theoretical perspective. We will start by describing first the dark matter halo of our own galaxy and in the Local Group. Then we proceed to describe the da
rk matter distribution in the more extended area known as the Local Universe. Depending on the nature of dark matter, numerical simulations predict different abundances of substructures in Local Group galaxies, in the number of void regions and in the abundance of low rotational velocity galaxies in the Local Universe. By comparing these predictions with the most recent observations, strong constrains on the physical properties of the dark matter particles can be derived. We devote particular attention to the results from the Constrained Local UniversE Simulations (CLUES) project, a special set of simulations whose initial conditions are constrained by observational data from the Local Universe. The resulting simulations are designed to reproduce the observed structures in the nearby universe. The CLUES provides a numerical laboratory for simulating the Local Group of galaxies and exploring the physics of galaxy formation in an environment designed to follow the observed Local Universe. It has come of age as the numerical analogue of Near-Field Cosmology.
The local universe is the best known part of our universe. Within the CLUES project (http://clues-project.org - Constrained Local UniversE Simulations) we perform numerical simulations of the evolution of the local universe. For these simulations we
construct initial conditions based on observational data of the galaxy distribution in the local universe. Here we review the technique of these constrained simulations. In the second part we summarize our predictions of a possible Warm Dark Matter cosmology for the observed local distribution of galaxies and the local spectrum of mini-voids as well as a study of the satellite dynamics in a simulated Local Group.
We describe the basic ideas of MPI parallelization of the N-body Adaptive Refinement Tree (ART) code. The code uses self-adaptive domain decomposition where boundaries of the domains (parallelepipeds) constantly move -- with many degrees of freedom -
- in the search of the minimum of CPU time. The actual CPU time spent by each MPI task on previous time-step is used to adjust boundaries for the next time-step. For a typical decomposition of 5^3 domains, the number of possible changes in boundaries is 3^{84}. We describe two algorithms of finding minimum of CPU time for configurations with a large number of domains. Each MPI task in our code solves the N-body problem where the large-scale distribution of matter outside of the boundaries of a domain is represented by relatively few temporary large particles created by other domains. At the beginning of a zero-level time-step, domains create and exchange large particles. Then each domain advances all its particles for many small time-steps. At the end of the large step, the domains decide where to place new boundaries and re-distribute particles. The scheme requires little communications between processors and is very efficient for large cosmological simulations.
We present the mass and X-ray temperature functions derived from a sample of more than 15,000 galaxy clusters of the MareNostrum Universe cosmological SPH simulations. In these simulations, we follow structure formation in a cubic volume of 500/h Mpc
on a side assuming cosmological parameters consistent with either the first or third year WMAP data and gaussian initial conditions. We compare our numerical predictions with the most recent observational estimates of the cluster X-ray temperature functions and find that the low normalization cosmological model inferred from the 3 year WMAP data results is barely compatible with the present epoch X-ray cluster abundances. We can only reconcile the simulations with the observational data if we assume a normalization of the Mass-Temperature relation which is a factor of 2.5--3 smaller than our non-radiative simulations predict. This deviation seems to be too large to be accounted by the effects of star formation or cooling in the ICM, not taken into account in these simulations.
