Dark Matter Halo Finders

This website is developed as part of our Science Research Mentoring Program (SRMP) project at the Center for Astrophysics (CfA), Harvard University.

It serves to provide the scientific background needed for our project in terms of not only the tools we adopt to conduct it, but also the various scientific concepts we learned in the process. We summarize our most major findings through various 2D and 3D images and videos and illustrate their significance by tying them back to cutting edge discoveries in the field of astronomy and extragalactic astrophysics.

In our project, we consider the question of whether the conclusions we draw from large-scale (cosmological) simulations are strongly influenced by our choice of a halo finder. Cosmological simulations contain billions of particles made of dark matter, an elusive component of our Universe whose nature we don't yet understand. Halo finding algorithms or halo finders, for short, are algorithms which attempt to identify groups of dark matter particles as bound self-gravitating structures in cosmological simulations. They are called halos since their shapes are roughly spherical and because the current standard model of the Universe assumes that they envelop galaxies and provide the conditions for their formation (and subsequently our existence).

Perhaps the most widely used halo finder is the so called friends-of-friends algorithm (FoF) because of its relative ease of implementation and computational efficiency. However, there are many drawbacks to using it which we explore in this project. On the other hand, a more sophisticated algorithm could possibly alleviate some of these issues. An example of such a state-of-the-art algorithm is ROCKSTAR, which is a lot more cumbersome to incorporate and requires more computational resources to run. Follow the links below to find out how the two compare against each other and which one yields more physical results!

Click on any of the links below and dive into the details of our study!