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arxiv: 1803.01892 · v1 · submitted 2018-03-05 · 🧮 math.CA · math.OC· math.PR

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Controllability implies mixing I. Convergence in the total variation metric

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classification 🧮 math.CA math.OCmath.PR
keywords controllabilitymetricconvergencemixingpartpointsolidstationary
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This paper is the first part of a project devoted to studying the interconnection between controllability properties of a dynamical system and the large-time asymptotics of trajectories for the associated stochastic system. It is proved that the approximate controllability to a given point and the solid controllability from the same point imply the uniqueness of a stationary measure and exponential mixing in the total variation metric. This result is then applied to random differential equations on a compact Riemannian manifold. In the second part, we shall replace the solid controllability by a stabilisability condition and prove that it is still sufficient for the uniqueness of a stationary distribution, whereas the convergence to it holds in the weaker dual-Lipschitz metric.

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