Galaxy population identification with a phylogenetic approach.

Abstract

We propose a phylogenetic approach as a novel and robust tool capable of detecting galaxy populations (GPs) based on their chemical composition. This method clusters galaxies into the hierarchical structure of a phylogenetic tree that connects galaxies through features we call "nodes". The branches of the tree are interpreted as different GPs and the length between nodes (NodeLength) as the internal chemical variation along a branch. The NodeLength works as a chemical index, thus relating galaxy stellar populations with other structural and local environmental properties of galaxies. We apply the phylogenetic approach using 30 abundance indices from the Sloan Digital Sky Survey to 475 galaxies in the Coma cluster (0,015 < z < 0,033) and 438 galaxies in the field (0,035 < z < 0,054). We find that Coma is a complex system with multiple populations. It has three main GPs that can readily be identified in color-magnitude space, and several minor structures in its red sequence. On the other hand, the field is more homogeneous, presenting one main GP. This phylogenetic analysis of cluster and field galaxies, shows a contrast in terms of how chemically related galaxies are within different environments. We also find that, regardless of their morphology, galaxies can have a similar chemical composition. Therefore, this new approach to study galaxy properties and their evolution makes it possible to perform robust analyses and interpretations without introducing biases by first selecting samples based on a specific characteristic like stellar mass, morphology, sSFR or metallicity, as done with more traditional techniques.