This project aims to develop a systematic quantitative theory of convergence to stationarity for non-reversible Markov processes with a focus on high-dimensional state spaces and degenerate noise. In particular, we will consider the acceleration of Markov chain Monte Carlo methods, convergence acceleration in the absence of convexity, and the role of non-reversibility for stochastic dynamics at and near criticality.