Jump-diffusion algorithms are applied to sampling from Bayesian posterior distributions. We consider a class of random sampling algorithms based on continuous-time jump processes. The semigroup theory of random processes lets us show that limiting cases of certain jump processes acting on discretized spaces converge to diffusion processes as the discretization is refined. https://www.jmannino.com/best-catch-Sophie-Allport-Bee-Blackout-Ready-Made-Eyelet-Curtains-Duck-Egg-special-save/