Morphology parameters: substructure identification in X-ray galaxy clusters^⋆

¹ Astrophysics, Cosmology and Gravity Centre (ACGC), Astronomy Department, University of Cape Town, Private Bag X3, 7700 Rondebosch, Republic of South Africa
e-mail: viral.parekh2912@gmail.com
² Raman Research Institute, Sadashivanagar, 560080 Bangalore, India
³ Laboratoire Lagrange, UMR7293, Université de Nice Sophia-Antipolis, CNRS, Observatoire de la Côte d’ Azur, 06300 Nice, France
⁴ Department of Physics and Astrophysics, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium
⁵ European Space Agency (ESTEC), Keplerlaan 1, 2200 AG Noordwijk, The Netherland

Received: 3 May 2014
Accepted: 21 November 2014

Abstract

Context. In recent years multi-wavelength observations have shown the presence of substructures related to merging events in a large proportion of galaxy clusters. Clusters can be roughly grouped into two categories – relaxed and non-relaxed – and a proper characterisation of the dynamical state of these systems is crucial for both astrophysical and cosmological studies.

Aims. In this paper we investigate the use of a number of morphological parameters (Gini, M₂₀, concentration, asymmetry, smoothness, ellipticity, and Gini of the second-order moment, G_M) introduced to automatically classify clusters as relaxed or dynamically disturbed systems.

Methods. We apply our method to a sample of clusters at different redshifts extracted from the Chandra archive and investigate possible correlations between morphological parameters and other X-ray gas properties.

Results. We conclude that a combination of the adopted parameters is a very useful tool for properly characterising the X-ray cluster morphology. According to our results, three parameters – Gini, M₂₀, and concentration – are very promising for identifying cluster mergers. The Gini coefficient is a particularly powerful tool, especially at high redshift, because it is independent of the choice of the position of the cluster centre. We find that high Gini (>0.65), high concentration (>1.55), and low M₂₀ (<–2.0) values are associated with relaxed clusters, while low Gini (<0.4), low concentration (<1.0), and high M₂₀ (>–1.4) characterise dynamically perturbed systems. We also estimate the X-ray cluster morphological parameters in the case of radio loud clusters. Since they are in excellent agreement with previous analyses we confirm that diffuse intracluster radio sources are associated with major mergers.