Discovery and Modeling of Merging Galaxy Clusters

University Of California-Davis, Davis CA

Investigators

Abstract

A cluster of galaxies is an enormous laboratory hosting a variety of physical processes that play out on a stage millions of light-years across. A particularly dramatic process is when two clusters collide and merge. Because most of the mass of each cluster is dark matter, a cluster merger serves as a "dark matter collider" capable of revealing how dark matter particles interact with each other---something no Earthbound lab can currently do. The team will identify merging cluster candidates using a new technique, then study the candidates in greater detail to identify the simplest systems, and finally model them to create an ensemble of well-modeled dark matter laboratories. The team will also expand research opportunities for undergraduates by continuing participation in Cal-Bridge, which helps undergraduates bridge up to PhD programs with long-term support, and by running graduate admissions boot camps open to all. The team will mine large optical cluster catalogs (currently using redMaPPer while establishing a foundation for using future larger catalogs) for candidates with signs of binarity, then study those candidates with X-ray data (both archival and newly pointed) to identify "dissociative" systems where gas has separated from galaxies. The team will conduct a spectroscopic survey of each dissociative system to further assess binarity; quantify the line-of-sight velocity difference between the subclusters; and assess potentially confusing foreground/background structures. The team will then use gravitational lensing to map the mass in good candidate systems, and model binary systems by extracting analogs from cosmological simulations. The proposed work includes upgrading from using dark-matter-only simulations to using hydro simulations, and modeling and observation of shock positions to better constrain the merger scenario. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.