Benjamin Wandelt
Cosmic Mysteries vs Cosmic Data
The mysteries of the cosmic beginning, gravitational clustering, and cosmic acceleration persist. How can we distill cosmological information from the next generation of data sets? Taking examples from the cosmic microwave background, large scale structure, and supernova cosmology, I will discuss both novel cosmological tests and approaches to inference from cosmological data that solve otherwise intractable problems when extracting information from current and upcoming surveys. The philosophy is to use new computational approaches and physics-inspired artificial intelligence to achieve a number of goals: allow maximum freedom to design realistic forward models; be robust to systematic nuisances; accurately combine multiple probes; move beyond simplistic likelihood assumptions; naturally allow quantitative model comparison; and address tensions in the data.