Subgeometric hypocoercivity for piecewise-deterministic Markov process Monte Carlo methods

We extend the hypocoercivity framework for piecewise-deterministic Markov process (PDMP) Monte Carlo established in [Andrieu et. al. (2018)] to heavy-tailed target distributions, which exhibit subgeometric rates of convergence equilibrium. make use weak Poincar\'e inequalities, as developed work [Grothaus and Wang (2019)], ideas we adapt PDMPs interest. On way report largely potential-independent approaches bounding explicitly solutions Poisson equation Langevin diffusion its first second derivatives, required here control various terms arising application result.