Criteria for exponential convergence to quasi-stationary distributions and applications to multi-dimensional diffusions

Nicolas Champagnat 1, 2 Koléhè Coulibaly-Pasquier 2 Denis Villemonais 1, 2
1 TOSCA - TO Simulate and CAlibrate stochastic models
CRISAM - Inria Sophia Antipolis - Méditerranée , IECL - Institut Élie Cartan de Lorraine : UMR7502
Abstract : We consider general Markov processes with absorption and provide criteria ensuring the exponential convergence in total variation of the distribution of the process conditioned not to be absorbed. The first one is based on two-sided estimates on the transition kernel of the process and the second one on gradient estimates on its semigroup. We apply these criteria to multi-dimensional diffusion processes in bounded domains of $\R^d$ or in compact Riemannian manifolds with boundary, with absorption at the boundary.
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Nicolas Champagnat, Koléhè Coulibaly-Pasquier, Denis Villemonais. Criteria for exponential convergence to quasi-stationary distributions and applications to multi-dimensional diffusions. Séminaire de Probabilités XLIX, 2215, Springer, pp. 165-182, 2018, Lecture Notes in Mathematics, ⟨10.1007/978-3-319-92420-5_5⟩. ⟨hal-01293622v2⟩

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