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We present results obtained with a new XMM-Newton observation of A2142, a famous textbook example of cluster with multiple cold fronts, which has been studied in detail with Chandra but whose large scale properties are presented here for the first time. We report the discovery of a a new cold front, the most distant one ever detected in a galaxy cluster, at about one Mpc from the center to the SE. Residual images, thermodynamics and metal abundance maps are qualitatively in agreement with predictions from numerical simulations of the sloshing phenomenon. However, the scales involved are much larger, similarly to what recently observed in the Perseus cluster. These results show that sloshing is a cluster-wide phenomenon, not confined in the cores, which extends well beyond the cooling region involving a large fraction of the ICM up to almost half of the virial radius. The absence of a cool core and a newly discovered giant radio halo in A2142, in spite of its relaxed X-ray morphology, suggest that large scale sloshing, or the intermediate merger which caused it, may trigger Mpc-scale radio emission and may lead to the disruption of the cluster cool core
Clumping and turbulence are expected to affect the matter accreted onto the outskirts of galaxy clusters. To determine their impact on the thermodynamic properties of Abell 2142 we perform an analysis of the X-ray temperature data from XMM-Newton via
We present an analysis of a 72 ks Chandra observation of the double cluster Abell 1644 (z=0.047). The X-ray temperatures indicate the masses are M500=2.6+/-0.4 x10^{14} h^{-1} M_sun for the northern subcluster and M500=3.1+/-0.4 x10^{14} h^{-1} M_sun
We report on a spectral study at radio frequencies of the giant radio halo in A2142 (z=0.0909), which we performed to explore its nature and origin. A2142 is not a major merger and the presence of a giant radio halo is somewhat surprising. We perform
In the context of cosmic microwave background (CMB) data analysis, we compare the efficiency at large scale of two angular power spectrum algorithms, implementing, respectively, the quadratic maximum likelihood (QML) estimator and the pseudo spectrum