No Mode Left Behind: New Methods for Precision Cosmology

New York University, New York NY

Investigators

Abstract

The large scale structure of the universe includes clusters of galaxies. The size of these clusters and the spacing of galaxies within the clusters depends on the nature of dark matter. This project will use computers and artificial intelligence to model the growth of this large scale structure, using a new method that will produce more detailed models over a wider range of dark matter conditions. These models can be compared with observations of galaxy clusters to improve our understanding of dark matter. These models also will be used to produce videos for public outreach and education. Users will be able to "fly through" the universe to visualize the large scale structure. The project will develop an emulator that can reproduce expected large scale structure properties for a particular parameter set based on full N-body simulations of neighboring parameters sets within parameter space. Thus, the more computationally expensive high-resolution simulations can done over a sparse set of parameters and then the emulator will be able to fill in the rest of parameter space. The higher resolution of the large scale structure models will allow current and future surveys to probe scales at the sub-megaparsec level, instead of the current resolutions of ~10 Mpc. The project will use the data from these simulations to produce "fly-through" 3 dimensional visualizations of large scale structure for use in public outreach and education. 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.