Abstract Novel Monte Carlo methods to generate samples from a target distribution, such as posterior Bayesian analysis, have rapidly expanded in the past decade. Algorithms based on Piecewise Deterministic Markov Processes (PDMPs), non-reversible continuous-time processes, are developing into their own research branch, thanks important properties (e.g., super-efficiency). Nevertheless, practice...