Development of Novel Statistical Tools for the Analysis of Astronomical Data

ended

We propose an interdisciplinary collaboration network involving leading groups in Astrophysics (Astrophysics Group in Crete, Geneva Observatory, University of Cambridge, Smithsonian Astrophysical Observatory, Caltech, and Nortwestern University), and Statistics (Imperial College, University of Cambridge, Simon Fraser University). The goal of this project is to share expertise between the different fields and geographical areas in order to tackle key questions in observational Astrophysics, related to the nature of dark energy and dark matter, the populations of accreting binary stars in galaxies and their evolution, the morphological and activity classification of galaxies, and the identification and characterization of fast evolving, or transient, sources. To address each of these questions we will use state-of-the-art observations and theoretical models, and we will develop novel, principled tools for statistical analysis in the domains of source classification, structure detection, and fitting. The methods developed under this program will have lasting value and applications beyond the field of Astrophysics.