Cluster Geometry & Inclinations from Deprojection Uncertainties
Dalia Chakrabarty (Nottingham), Elisabetta De Filippis (Napoli) Helen, Russell (IOA)

TL;DR
This paper presents a method to determine the intrinsic shape and orientation of galaxy clusters by comparing deprojected X-ray profiles under different geometries and inclinations, enhanced by SZe data, to better estimate cluster masses.
Contribution
It introduces a novel scheme combining multiple deprojection assumptions and SZe data to identify cluster morphology and inclination, improving mass estimation accuracy.
Findings
Identified 8 prolate, 1 oblate, and 15 triaxial clusters.
Successfully constrained the inclination and intrinsic axial ratios of triaxial clusters.
Demonstrated the method's effectiveness with a sample of 24 galaxy clusters.
Abstract
{The determination of cluster masses is a complex problem that would be aided by information about the cluster shape and orientation (along the line-of-sight).} {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 by using SZe data when available.} {We deproject the cluster X-ray surface brightness profile under the assumptions of four different geometry and inclination configurations for the observed system; these 4 configurations correspond to four extreme geometry+inclination scenarios. The deprojection in question is performed by the non-parametric algorithm DOPING. The formalism is tested with model systems…
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