Dynamical Search for Substructures in Galaxy Clusters, A Hierarchical Clustering Method

TL;DR

This paper introduces a new hierarchical clustering method based on dynamical arguments to identify and analyze substructures within galaxy clusters, demonstrating its stability and applicability to real data.

Contribution

The paper presents a novel dynamical hierarchical clustering method for galaxy substructure detection, validated with simulations and applied to real galaxy clusters.

Findings

The method identifies more stable subgroups during cluster evolution.

It shows good agreement between phase-space and coordinate-based structures.

Applied to real clusters, it reveals substructure in ABCG151 but not in ABCG2670.

Abstract

We propose a new hierarchical method which uses dynamical arguments to find and describe substructures in galaxy clusters. This method (hereafter h--method or h--analysis) uses a hierarchical clustering analysis to determine the relationship between galaxies according to their relative binding energies. We have tested from N-body simulations, the two following features of the proposed method: 1) It extracts subgroups which are much more stable during the cluster evolution than those given by other techniques. 2) There exists a reasonable similarity between the structures found when only the coordinates ($x, y, v_z$) provided by "observations" are considered, and those found by using the six phase--space coordinates We have applied this method to two Abell clusters: ABCG151 and ABCG2670. Our results imply that ABCG151 is separated into two clusters, one of them is again divided into two subclusters. ABCG2670 has no subclustering. Our method allows however to extract the most bound galaxies in its dynamical core.