A Holistic Approach to Modeling Galaxy Groups and Clusters

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Galaxy groups and clusters are remarkable systems. With masses ranging from an equivalent of 10,000 billion suns to a mind-boggling million billion suns, these systems are the largest, most massive gravitationally bound objects in the Universe. They stand out as rich concentrations of bright galaxies and are among the most luminous X-ray sources in the universe. As a result, they are easy to identify out to vast distances. They are also the youngest of the cosmic structures to have formed and as such, still bear the imprints of the conditions that led to their formation. Because of all these factors, the most massive of these systems have been identified as potentially powerful probes of the geometry and the expansion of the universe. However, the use of clusters as cosmological probes depends critically on how well we understand why groups and clusters in the local universe look the way they do, and what these systems would have looked like at an earlier epoch. My research focuses on these two issues. I am developing realistic predictive models to describe, in detail, how groups and clusters formed and how they have changed over time. The modeling involves using state-of-the-art computer simulations, carried out on powerful supercomputers, to replicate "virtually" the universe's 13.7 billion year history and identify the conditions that led to the systems we observe today. Over the course of time, groups and clusters are influenced by an incredibly complex web of processes all influencing one another, processes such as those that govern the birth, life and death of stars, those that shape the ebb and flow of convergent dark matter flows that give rise to increasingly larger cosmic structures with time, and those that govern the response of supermassive black holes as they capture and draw in gas from their surroundings. Realistic numerical simulations are the only way of unraveling this web and making sense of how the observed properties of galaxy groups and clusters emerged.