Using Networking Algorithms to Assess the Environment of Galaxy Groups

Abstract

Understanding the environment in which a galaxy resides is crucial to our understanding of galaxy evolution. Most galaxies (~70%) live in groups and it is important to develop a quantitative understanding of how galaxies are distributed within groups and how groups are distributed in the larger scale structure. In addition to the traditional friends-of-friends algorithm, I have applied various concepts from networking algorithms to understand the network of galaxy groups in clusters, and to understand the substructure within groups. Doing so provides a new method of gauging the large scale environments of galaxies and groups, and will result in a more concrete way to define a group and to quantify the strength of the community structure that exists.