Abstract

The CHEX-MATE sample was built to provide an overview of the statistical properties of the underlying cluster population and to set the stage for future X-ray missions. In this work, we perform a morphological analysis of the 118 clusters included in the sample with the aim to provide a classification of their dynamical state which will be useful for future studies of the collaboration.

Highlights

  • Clusters of galaxies are the largest virialised systems of the Universe and include between 100 - 1000 galaxies

  • We perform a morphological analysis of the 118 clusters included in the sample with the aim to provide a classification of their dynamical state which will be useful for future studies of the collaboration

  • We present the morphological analysis of the clusters in the CHEX-MATE sample with the aim to provide a classification of their dynamical state, which will be useful for future studies of the collaboration

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Summary

Introduction

Clusters of galaxies are the largest virialised systems of the Universe and include between 100 - 1000 galaxies. By identifying specific features in the X-ray morphology of clusters is possible to derive their dynamical state, which is an important property to consider in both astrophysical and cosmological studies. On the one hand there are the relaxed systems, whose X-ray emission is characterised by a spherical symmetry and are assumed to be in hydrostatic equilibrium allowing a proper mass estimate [e.g., 1, 2], which is an important cosmological quantity. A classification of the dynamical state is crucial when dealing with large samples of clusters, since it allows to recognise the most proper objects to use in specific analysis. We present the morphological analysis of the clusters in the CHEX-MATE sample with the aim to provide a classification of their dynamical state, which will be useful for future studies of the collaboration. We will retrace the steps taken over the last years to test and check the procedure elaborated until now in this field

Dataset and methods
Visual classification
Morphological parameters
The observed sample
The simulated sample
ROC curves
Study of the systematics
Combining the morphological parameters
Findings
Conclusions
Full Text
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