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Exponential ergodicity for SDEs and McKean-Vlasov processes with Lévy noise

Published 30 Jan 2019 in math.PR | (1901.11125v2)

Abstract: We study stochastic differential equations (SDEs) of McKean-Vlasov type with distribution dependent drifts and driven by pure jump L\'{e}vy processes. We prove a uniform in time propagation of chaos result, providing quantitative bounds on convergence rate of interacting particle systems with L\'{e}vy noise to the corresponding McKean-Vlasov SDE. By applying techniques that combine couplings, appropriately constructed $L1$-Wasserstein distances and Lyapunov functions, we show exponential convergence of solutions of such SDEs to their stationary distributions. Our methods allow us to obtain results that are novel even for a broad class of L\'{e}vy-driven SDEs with distribution independent coefficients.

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