Numerical Simulations with Self-Interacting Dark Matter

University Of California-Irvine, Irvine CA

Investigators

Abstract

This award funds the research activities of Professor James Bullock at the University of California, Irvine. Professor Bullock's research aims to explore the nature of dark matter using supercomputer simulations. Dark matter stands among the deepest mysteries in science. It makes up some 85% of the clustering matter in the universe, yet its fundamental nature remains unknown. The existence of dark matter provides one of the strongest pieces of evidence that our understanding of nature remains incomplete. The most popular idea at this time is that the dark matter is made of a single particle that interacts only weakly with itself (and with normal matter), but this model faces some difficulties reproducing observations on the scales of galaxies. An intriguing solution is that the dark matter is more complex, with its own set of strong self-interactions, analogous, perhaps, to the particles that make up the visible world. This award will support supercomputer simulations of galaxy formation including both standard dark matter and more complex dark matter to determine whether or not galaxy observations provide evidence that dark matter is self-interacting. As a result, research in this area advances the national interest by promoting the progress of science in one of its most fundamental directions: the discovery and understanding of the universe. Moreover, the simulation codes and analysis software will be made public and Professor Bullock will mentor graduate students, undergraduate students, and high-school students as part of this project, providing these young people with mathematical, computational, and data-mining training that will be a valuable asset for them and their communities well past the funding period. Professor Bullock will also give public lectures on this research. More technically, Professor Bullock will use a suite of simulations to provide the most accurate and robust constraints yet derived on the dark matter self-interaction cross-section and to determine whether or not self-interacting dark matter (SIDM) models provide a better match to data than standard cold dark matter once realistic treatments of baryons are included. The work will include 1) focused, idealized simulations of individual galaxies and merging galaxy clusters; 2) cosmological simulations; and 3) full hydrodynamic simulations of galaxy formation set within the SIDM framework. This work builds upon an existing and well-tested code, and will involve running models with velocity-independent, isotropic, energy-exchange cross-sections as well as models with more complex behavior in velocity-dependence and non-isotropic scattering.