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General approximation method for the distribution of Markov processes conditioned not to be killed

Denis Villemonais (2014)

ESAIM: Probability and Statistics

We consider a strong Markov process with killing and prove an approximation method for the distribution of the process conditioned not to be killed when it is observed. The method is based on a Fleming−Viot type particle system with rebirths, whose particles evolve as independent copies of the original strong Markov process and jump onto each others instead of being killed. Our only assumption is that the number of rebirths of the Fleming−Viot type system doesn’t explode in finite time almost surely...

Gradient flows of the entropy for jump processes

Matthias Erbar (2014)

Annales de l'I.H.P. Probabilités et statistiques

We introduce a new transport distance between probability measures on ℝ d that is built from a Lévy jump kernel. It is defined via a non-local variant of the Benamou–Brenier formula. We study geometric and topological properties of this distance, in particular we prove existence of geodesics. For translation invariant jump kernels we identify the semigroup generated by the associated non-local operator as the gradient flow of the relative entropy w.r.t. the new distance and show that the entropy is...

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