Event-chain Monte Carlo and the true self-avoiding walk

We study the large-scale dynamics of event-chain Monte Carlo (ECMC) algorithms in one dimension and their relation to the true self-avoiding walk. In particular, we study the influence of stress and different forms of interaction on the equilibration and sampling properties of algorithms that satisfy global balance but not local balance. We conclude that a broad class of interaction potentials, corresponding to different physical systems, display identical large-scale dynamics.