  Analogue to the well-known Langevin Monte Carlo method, in this article we
provide a method to sample from a target distribution \(\pi\) by simulating a
solution of a stochastic differential equation. Hereby, the stochastic
differential equation is driven by a general L\'evy process which - other than
in the case of Langevin Monte Carlo - allows for non-smooth targets. Our method
will be fully explored in the particular setting of target distributions
supported on the half-line \((0,\infty)\) and a compound Poisson driving noise.
Several illustrative examples conclude the article.
