2015
DOI: 10.1214/ejp.v20-4054
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Kinetic Brownian motion on Riemannian manifolds

Abstract: International audienceWe consider in this work a one parameter family of hypoelliptic diffusion processes on the unit tangent bundle T 1 M of a Riemannian manifold (M, g), collectively called kinetic Brownian motions, that are random perturbations of the geodesic flow, with a parameter σ quantifying the size of the noise. Projection on M of these processes provides random C 1 paths in M. We show, both qualitively and quantitatively, that the laws of these M-valued paths provide an interpolation between geodesi… Show more

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Cited by 34 publications
(60 citation statements)
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“…Our proof exhibits striking similarities with [3]. Our "internal" 0 space seems to play the same role as the compact sphere in their paper and their proof also uses theory of rough paths to control convergences.…”
Section: Open Questionsmentioning
confidence: 62%
“…Our proof exhibits striking similarities with [3]. Our "internal" 0 space seems to play the same role as the compact sphere in their paper and their proof also uses theory of rough paths to control convergences.…”
Section: Open Questionsmentioning
confidence: 62%
“…The presence of anisotropy drastically complexifies the approach and computations compared to the isotropic framework. Namely, in the isotropic Euclidean setting considered in Section 2.2 of [ABT15] and which is the core of the proof when associated with rough paths techniques, the homogenisation of kinetic Brownian motion was proved using Itô calculus and standard martingale techniques. As it will be clear in Section 2 below, the Doob-Meyer decomposition of the velocity process given by equation (1.1) gets more involved here, its invariant measure is not likely to be easy to describe, and martingale techniques need explicit solutions of the Poisson equation which seems hopeless in this context.…”
Section: Introductionmentioning
confidence: 99%
“…Langevin-Kramers equations model the motion of a noisy, damped, diffusing particle of non-zero mass, m. In the simplest case, the stochastic differential equation (SDE) has the form on the early literature and [4,5,6,7,8,9,10,11,12,13,14] for further mathematical results in this direction.…”
Section: Introductionmentioning
confidence: 99%