Speaker
Description
Title: Gravity, computation, and machine learning - Numerical methods for relativity
Abstract: Numerical relativity started with the goal to solve Einstein's equations on the computer, which translates into mathematical and numerical methods for partial differential equations, and simulations on supercomputers. Current efforts have expanded into multi-physics simulations that are by now directly connected to observations, in particular gravitational waves and multimessenger events like kilonovae. Alternative models beyond astrophysics are being explored as well, including e.g. boson stars. We will give a compact review of the numerical issues involved, and we will also mention in passsing recent applications of machine learning to gravitational wave data analysis.
