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Register a new userThe Cluster Distribution as a Test for Dark Matter Models. I: Clustering Properties
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We present simulations of the cluster distribution in several dark matter models, using an optimized version of the truncated Zeldovich approximation (TZA). We compare them with N-body cluster simulations and find that the TZA provides a very accurate description of the cluster distribution as long as fluctuations on the cluster mass scale are in the mildly non-linear regime. The simulated dark matter models are: Standard CDM (SCDM), Tilted CDM (TCDM) with n=0.7, Cold+Hot DM (CHDM) with 30% of hot component, low Hubble constant (h=0.3) CDM (LOWH) and a spatially flat low-density CDM model with Omega_0=0.2. We compare the simulations with a redshift sample of Abell/ACO clusters, using the integral of the 2-point correlation function and the probability density function. We find that the best models at reproducing the data are CHDM and LCDM. All the other models are ruled out. The reduced skewness S_3 is fairly constant with S_3=1.9, independent of the DM model and consistent with observational data. The abundances of clusters predicted using the Press--Schechter theory provide strong constraints: only the CHDM, LOWH and LCDM models appear to produce the correct number-density of clusters.
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We estimate the variance and the skewness of the cluster distribution in several dark matter (DM) models. The cluster simulations are based on the Zeldovich approximation, the low computational cost of which allows us to run 50 random realizations of each model. We compare our results with those coming from a similar analysis of a redshift sample of Abell/ACO clusters. Within the list of the considered models, we find that only the model based on Cold+Hot DM (with $Omega_{rm hot}=0.3$) provides a good fit to the data. The standard CDM model and the low-density ($Omega_{circ}=0.2$) CDM models, both with and without a cosmological constant term ($Omega_Lambda =0.8$) are ruled out. The tilted CDM model with primordial spectral index $n=0.7$ and a low Hubble constant ($h=0.3$) CDM model are only marginally consistent with the data.
We have simulated the formation of a galaxy cluster in a $Lambda$CDM universe using twelve different codes modeling only gravity and non-radiative hydrodynamics (art, arepo, hydra and 9 incarnations of GADGET). This range of codes includes particle based, moving and fixed mesh codes as well as both Eulerian and Lagrangian fluid schemes. The various GADGET implementations span traditional and advanced smoothed-particle hydrodynamics (SPH) schemes. The goal of this comparison is to assess the reliability of cosmological hydrodynamical simulations of clusters in the simplest astrophysically relevant case, that in which the gas is assumed to be non-radiative. We compare images of the cluster at $z=0$, global properties such as mass, and radial profiles of various dynamical and thermodynamical quantities. The underlying gravitational framework can be aligned very accurately for all the codes allowing a detailed investigation of the differences that develop due to the various gas physics implementations employed. As expected, the mesh-based codes ART and AREPO form extended entropy cores in the gas with rising central gas temperatures. Those codes employing traditional SPH schemes show falling entropy profiles all the way into the very centre with correspondingly rising density profiles and central temperature
The dependence of Hubble parameter on redshift can be determined directly from the dipole of luminosity distance to Supernovae Ia. We investigate the possibility of using the data on dipole of the luminosity distance obtained from the Supernovae Ia compilations SDSS, Union2.1, JLA and Pantheon to distinguish the dark energy models.
Determining the structure of galaxy clusters is essential for an understanding of large scale structure in the universe, and may hold important clues to the identity and nature of dark matter particles. Moreover, the core dark matter distribution may offer insight into the structure formation process. Unfortunately, cluster cores also tend to be the site of complicated astrophysics. X-ray imaging spectroscopy of relaxed clusters, a standard technique for mapping their dark matter distributions, is often complicated by the presence of their putative ``cooling flow gas, and the dark matter profile one derives for a cluster is sensitive to assumptions made about the distribution of this gas. Here we present a statistical analysis of these assumptions and their effect on our understanding of dark matter in galaxy clusters.
Galaxy cluster mass distributions offer an important test of the cold dark matter picture of structure formation, and may even contain clues about the nature of dark matter. X-ray imaging spectroscopy of relaxed systems can map cluster dark matter distributions, but are usually complicated by the presence of central cool components in the intracluster medium. Here we describe a statistically correct approach to distinguishing amongst simple alternative models of the cool component, and apply it to one cluster. We also present mass profiles and central density slopes for five clusters derived from Chandra data, and illustrate how assumptions about the cool component affect the resulting mass profiles. For four of these objects, we find that the central density profile (r < 200 h_50^-1 kpc) rho(r) = r^a with -2 < a < -1, for either of two models of the central cool component. These results are consistent with standard CDM predictions.
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