New observational recipes for measuring dynamical state of galaxy clusters

TL;DR

This paper develops improved observational recipes using multiple indicators from simulations to classify the dynamical state of galaxy clusters, aiding understanding of their assembly and merger history.

Contribution

It introduces new recipes combining multiple indicators, optimized through a rotation matrix method, to better distinguish merger stages in galaxy clusters.

Findings

Using more indicators improves classification accuracy.

Stellar mass gap and center offset are the most dominant indicators.

Recipes show good agreement with literature on cluster dynamical states.

Abstract

During cluster assembly, a cluster's virialization process leaves behind signatures that can provide information on its dynamical state. However, no clear consensus yet exists on the best way to achieve this. Therefore, we attempt to derive improved recipes for classifying the dynamical state of clusters in observations using cosmological simulations. Cluster halo mass and their subhalos' mass are used to $ 10^{14}M_{\odot} h^{-1}$ and $10^{10}M_{\odot} h^{-1}$ to calculate five independent dynamical state indicators. We experiment with recipes by combining two to four indicators for detecting specific merger stages like recent and ancient mergers. These recipes are made by plotting merging clusters and a control sample of relaxed clusters in multiple indicators parameter space, and then applying a rotation matrix method to derive the best way to separate mergers from the control sample. The success of the recipe is quantified using the success rate and the overlap percentage of the merger and control histograms along the newly rotated $x$-axis. This provides us with recipes using different numbers of combined indicators and for different merger stage. Among the recipes, the stellar mass gap and center offset are the first and second most dominant of the indicators, and using more indicators improves the effectiveness of the recipe. When applied to observations, our results show good agreement with literature values of cluster dynamical state.