OKC colloquia
Deciphering the dynamical Universe via large-scale Bayesian data interpretation
by
→
Europe/Stockholm
FA32
FA32
Description
Modern cosmology aims at investigating the dynamics of the Universe at the largest scales and the formation of cosmic structures at smaller scales. Over past decades there has been a natural progression in cosmology: Starting from observations of the homogeneous expansion dynamics with supernovae of type Ia the field has focused on the observation of small perturbations in the linear regime of structure formation as they appear in the cosmic microwave background, and on observations of linearly evolving structures through the distribution of galaxies.
A natural next step is to do cosmology with nonlinearly evolving structures, making up a large fraction of the signal in optical surveys. This forces cosmology to deal with nonlinear perturbations along with their inherently non-Gaussian statistics in observations.
In my talk, I will discuss a new approach to studying the dynamic and non-linear evolution of cosmic structures in observations via large-scale Bayesian methods. Our technology infers 3D initial conditions from which observed structures originate, maps out non-linear density and velocity fields, and provides dynamic structure formation histories including a detailed treatment of uncertainties. Data application provides an unprecedented view of the dynamical evolution of structures surrounding us. This will be exemplified by highly detailed dynamical reconstructions of the Coma cluster and Sloan Great Wall but more generally by the entire large-scale structure in the Nearby Universe.