Network Analysis of Cosmic Structures : Network Centrality and Topological Environment

TL;DR

This study applies network analysis techniques to the cosmic web, classifying galaxy environments based on centrality measures and exploring their relation to galaxy properties, demonstrating the potential of network cosmology.

Contribution

Introduces a novel application of network centrality measures to classify cosmic structures and analyze galaxy properties within these topological environments.

Findings

Different galaxy populations show varied properties across topological regions

Preliminary results suggest correlations between environment and galaxy characteristics

Network analysis offers a promising approach for cosmic structure studies

Abstract

We apply simple analyses techniques developed for the study of complex networks to the study of the cosmic web, the large scale galaxy distribution. In this paper, we measure three network centralities (ranks of topological importance), Degree Centrality (DC), Closeness Centrality (CL), and Betweenness Centrality (BC) from a network built from the Cosmological Evolution Survey (COSMOS) catalog. We define 8 galaxy populations according to the centrality measures; Void, Wall, and Cluster by DC, Main Branch and Dangling Leaf by BC, and Kernel, Backbone, and Fracture by CL. We also define three populations by voronoi tessellation density to compare these with the DC selection. We apply the topological selections to galaxies in the (photometric) redshift range $0.91<z<0.94$ from the COSMOS survey, and explore whether the red and blue galaxy populations show differences in color, star-formation rate (SFR) and stellar mass in the different topological regions. Despite the limitations and uncertainties associated with using photometric redshift and indirect measurements of galactic parameters, the preliminary results illustrate the potential of network analysis. The coming future surveys will provide better statistical samples to test and improve this "network cosmology".