Astrophysics is an ancient science which in the past 50 years has seen an explosion in the volume of available data. This is thanks to the construction of telescopes and the launch of satellites with state of the art instruments that allow the study of extremely faint objects from the Milky Way to in the very early Universe. In parallel Statistics, a major branch of Mathematics - another ancient science - has seen major advances in the past century with the development of novel methods that have revolutionized the analysis of large volumes of data. This project combines the power of modern statistical methods with state of the art astronomical data and simulations, in order to solve outstanding problems in Astrophysics through the development of novel statistical tools. Our efforts focus on problems related to:
(i) The classification of objects detected in large and/or deep surveys of the sky with ground and space-based observatories
(ii) The characterization of the populations of stars and galaxies observed in these surveys
(iii) The characterization of faint and/or blended objects in optical and X-ray observations
(iv) Modelling the cosmological evolution of the supernovae that are used as probes of the expansion of the Universe
(v) Analysis of astronomical data with complex multi-dimensional models
Addressing these problems is key for solving long-standing questions that are in the forefront of modern Astrophysics, including the cosmological evolution of galaxies and their stellar populations, the formation and evolution of binary stellar systems containing black holes or neutron stars, and the expansion of the Universe. The complexity of these problems and the large volume of diverse, multi-observatory data required entail the development of advanced analytic methods.
In order to achieve these goals we have formed a broad international network between 3 European institutions (Foundation for Research and Technology Hellas; Imperial College; Geneva Observatory) and 4 US-based institutes (Smithsonian Astrophysical Observatory; Northwestern University; University of California, Davis; Ohio State University). This network involves leading groups in Astrophysics and Statistics. The statistical methods developed as part of this effort will be used to address long-standing questions, while at the same time training the next generation of researchers in state-of-the-art statistical techniques. Such techniques are now commonly used in a wide variety of applications spanning virtually all areas of science: e.g. biology, discovery of new drugs and treatments, economics, weather forecasting, disaster management, and computer science (internet analytics). Therefore, this program has far reaching implications, either directly (through the development of tools and methods that are readily used in other disciplines) or indirectly by training young researchers to become fluent in modern data management and analysis techniques.
