No Arabic abstract
We present an analytic parametric model to describe the baryonic and dark matter distributions in clusters of galaxies with spherical symmetry. It is assumed that the dark matter density follows a Navarro, Frenk and White (NFW) profile and that the gas pressure is described by a generalised NFW (GNFW) profile. By further demanding hydrostatic equilibrium and that the gas fraction is small throughout the cluster, one obtains unique functional forms, dependent on basic cluster parameters, for the radial profiles of all the properties of interest in the cluster. We show these profiles are consistent both with numerical simulations and multi-wavelength observations of clusters. We also use our model to analyse six simulated SZ clusters as well as A611 SZ data from the Arcminute Microkelvin Imager (AMI). In each case, we derive the radial profile of the enclosed total mass and the gas pressure and show that the results are in good agreement with our model prediction.
The dominant baryonic component of galaxy clusters is hot gas whose distribution is commonly probed through X-ray emission arising from thermal bremsstrahlung. The density profile thus obtained has been traditionally modeled with a beta-profile, a simple function with only three parameters. However, this model is known to be insufficient for characterizing the range of cluster gas distributions, and attempts to rectify this shortcoming typically introduce additional parameters to increase the fitting flexibility. We use cosmological and physical considerations to obtain a family of profiles for the gas with fewer parameters than the beta-model but which better accounts for observed gas profiles over wide radial intervals.
We present a parameterized model of the intra-cluster medium that is suitable for jointly analysing pointed observations of the Sunyaev-Zeldovich (SZ) effect and X-ray emission in galaxy clusters. The model is based on assumptions of hydrostatic equilibrium, the Navarro, Frenk and White (NFW) model for the dark matter, and a softened power law profile for the gas entropy. We test this entropy-based model against high and low signal-to-noise mock observations of a relaxed and recently-merged cluster from N-body/hydrodynamic simulations, using Bayesian hyper-parameters to optimise the relative statistical weighting of the mock SZ and X-ray data. We find that it accurately reproduces both the global values of the cluster temperature, total mass and gas mass fraction (fgas), as well as the radial dependencies of these quantities outside of the core (r > kpc). For reference we also provide a comparison with results from the single isothermal beta model. We confirm previous results that the single isothermal beta model can result in significant biases in derived cluster properties.
We build a spherical halo model for galaxies using a general scalar-tensor theory of gravity in its Newtonian limit. The scalar field is described by a time-independent Klein-Gordon equation with a source that is coupled to the standard Poisson equation of Newtonian gravity. Our model, by construction, fits both the observed rotation velocities of stars in spirals and a typical luminosity profile. As a result, the form of the new Newtonian potential, the scalar field, and dark matter distribution in a galaxy are determined. Taking into account the constraints for the fundamental parameters of the theory (lambda,alpha), we analyze the influence of the scalar field in the dark matter distribution, resulting in shallow density profiles in galactic centers.
A new simple expression for the circular velocity of spiral galaxies is proposed and tested against HI Nearby Galaxy Survey (THINGS) data set. Its accuracy is compared with the one coming from MOND.
We present a method to estimate the lensing potential from massive galaxy clusters for given observational X-ray data. The concepts developed and applied in this work can easily be combined with other techniques to infer the lensing potential, e.g. weak gravitational lensing or galaxy kinematics, to obtain an overall best fit model for the lensing potential. After elaborating on the physical details and assumptions the method is based on, we explain how the numerical algorithm itself is implemented with a Richardson-Lucy algorithm as a central part. Our reconstruction method is tested on simulated galaxy clusters with a spherically symmetric NFW density profile filled with gas in hydrostatic equilibrium. We describe in detail how these simulated observational data sets are created and how they need to be fed into our algorithm. We test the robustness of the algorithm against small parameter changes and estimate the quality of the reconstructed lensing potentials. As it turns out we achieve a very high degree of accuracy in reconstructing the lensing potential. The statistical errors remain below 2.0% whereas the systematical error does not exceed 1.0%.