Permanent URL to this publication: http://dx.doi.org/10.5167/uzh-41879
PDF (Accepted manuscript, Version 2)
PDF (Accepted manuscript, Version 1)
Context. Strong lensing studies can provide detailed mass maps of the inner regions even in dynamically active galaxy clusters.
Aims. We illustrate the important role of a proper modelling of the intracluster medium, i.e., the main baryonic component. We demonstrate that the addition of a new contribution accounting for the gas can increase the statistical significance of the lensing model.
Methods. We propose a parametric method for strong lensing analyses that exploits multiwavelength observations. The mass model accounts for cluster-sized dark matter halos, galaxies (whose stellar mass can be obtained from optical analyses), and the intracluster medium. The gas distribution is fitted to lensing data exploiting prior knowledge from X-ray observations. This gives an unbiased insight into each matter component and allows us to study the dynamical status of a cluster. The method was applied to AC 114, an irregular X-ray cluster.
Results. We find positive evidence of dynamical activity, the dark matter distribution being shifted and rotated with respect to the gas. On the other hand, the dark matter follows the galaxy density in terms of both shape and orientation, illustrating the collisionless nature of dark matter. The inner region (250 kpc) is underluminous in optical bands, whereas the gas fraction (~20 ± 5%) slightly exceeds typical values. Evidence of lensing and X-ray suggests that the cluster develops in the plane of the sky and is not affected by the lensing over-concentration bias. Despite the dynamical activity, the matter distribution seems to agree with predictions of N-body simulations. An universal cusped profile provides a good description of either the overall or the dark matter distribution, whereas theoretical scaling relations seem to be accurately fitted.
|Item Type:||Journal Article, refereed, original work|
|Communities & Collections:||07 Faculty of Science > Institute for Computational Science|
|Deposited On:||03 Mar 2011 15:55|
|Last Modified:||10 Jul 2014 07:58|
|Citations:||Web of Science®. Times Cited: 9|
Scopus®. Citation Count: 4
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