CAREER: Simulations of Galaxy and Cluster Formation: The New Frontiers

University Of Chicago, Chicago IL

Investigators

Abstract

Proposal ID: AST-0239759 Institution: University of Chicago PI: Kravtsov, Andrey Dr. Andrey Kravtsov will use his CAREER award at the University of Chicago to pursue an understanding of how galaxies and galaxy clusters form within the framework of the Big Bang cosmology. Comparisons of data and theoretical predictions show that Cold Dark Matter models work remarkably well at scales larger than one megaparsec, but have serious difficulties in explaining an increasing number of observations at smaller scales. Dr. Kravtsov will model the formation of galaxy clusters and individual galaxies, including important physical processes such as star formation, stellar energy feedback, and heavy element enrichment, at an unprecedented level of sophistication and detail. High-resolution simulations will be used to study the effects of stellar feedback and metal enrichment on the properties of galaxies, the intergalactic medium, and intracluster gas of galaxy clusters as well as possible observational signatures of these effects. The improved feedback models will be used in a larger set of lower-resolution simulations of galaxies and galaxy clusters to evaluate the statistical effects of feedback on the morphology and structural properties of galaxies and thermal properties of the intracluster medium. He will make both the codes and the results of the simulations available to the scientific community. Cosmology, and the field of structure formation in particular, is an exciting subject with broad popular appeal. However, currently there are very few resources concerning the formation of large-scale structure available to educators and the public. Dr. Kravtsov will integrate his research projects into education and outreach by (1) working to deliver results of research in the area of structure formation as both public lectures and high-quality visualizations for educators and the general public; (2) involving undergraduate and graduate students in the proposed research activities; (3) developing new projects and classes introducing students to modern computational techniques and algorithms.