Cluster geometry and inclinations from deprojection uncertainties. Cluster geometry and inclination

Abstract

Context: The determination of cluster masses is a complex problem that would be aided by information about the cluster shape and orientation (with respect to the line-of-sight).
Aims: It is in this context, that we have developed a scheme for identifying the intrinsic morphology and inclination of a cluster, by looking for the signature of the true cluster characteristics in the inter-comparison of the different deprojected emissivity profiles (that all project to the same X-ray brightness distribution) and complimenting this with SZe data when available.
Methods: We deproject the cluster X-ray surface brightness profile under assumptions about geometry and inclination that correspond to four extreme scenarios; the deprojection is performed by the non-parametric algorithm DOPING. The formalism is tested with model clusters and is then applied to a sample of 24 clusters. While the shape determination is possible by implementing the X-ray brightness alone, the estimation of the inclination is usually markedly improved upon by the usage of SZe data that is available for the considered sample.
Results: We spot 8 prolate systems, 1 oblate and 15 of the clusters in our sample as triaxial. In fact, for systems identified as triaxial, we are able to discern how the three semi-axis lengths compare with each other. This, when compounded by the information about the line-of-sight extent, allows us to constrain the intrinsic axial ratios and the inclination quite tightly.