X-ray/optical classification of cluster mergers and the evolution of the cluster merger fraction

TL;DR

This study classifies a complete sample of X-ray luminous galaxy clusters to identify disturbed systems, analyze merger fractions over redshift, and provide insights into cluster evolution and collision dynamics.

Contribution

It introduces a robust morphological classification method for a large cluster sample, expanding previous data, and analyzes the evolution of cluster merger fractions with redshift.

Findings

Identified 10 complex, recently merged systems.

Detected a significant increase in disturbed clusters starting at z ~ 0.4.

Provided a third public release of MACS clusters, adding 24 new clusters.

Abstract

We present the results of a simple but robust morphological classification of a statis- tically complete sample of 108 of the most X-ray luminous clusters at 0.15 < z < 0.7 observed with Chandra. Our aims are to (a) identify the most disturbed massive clusters to be used as gravitational lenses for studies of the distant universe and as probes of particle acceleration mechanisms resulting in non-thermal radio emission, (b) find cluster mergers featuring subcluster trajectories that make them suitable for quantitative analyses of cluster collisions, and (c) constrain the evolution with redshift of the cluster merger fraction. Finally, (d) this paper represents the third public release of clusters from the MACS sample, adding 24 clusters to the 46 published previously. To classify clusters by degree of relaxation, we use the projected offset of the brightest cluster galaxy from the peak (or the global centroid) of the X-ray emission as a measure of the segregation between the intracluster gas and dark matter. Regarding (a), we identify ten complex systems likely to have undergone multiple merger events in the recent past. Regarding (b), we identify eleven systems likely to be post-collision, binary, head-on mergers (BHOMs), as well as another six mergers that are possible BHOMs but probably harder to interpret because of non-negligible impact parameters and merger axes closer to our line of sight. Regarding (c), we find a highly significant increase with redshift in the fraction of morphologically disturbed clusters starting at z \sim 0.4, in spite of a detection bias in our sample against very disturbed systems at high redshift. A larger sample of clusters with high-quality X-ray data in particular at high redshift will be needed to trace the evolutionary history of cluster growth and relaxation closer to the primary epoch of cluster formation z \sim 1.