Evolution of Gaussian Concentration

Abstract : We study the behavior of the Gaussian concentration bound (GCB) under stochastic time evolution. More precisely, in the context of a diffusion process on R d we prove in various settings that if we start the process from an initial probability measure satisfying GCB, then at later times GCB holds, and estimates for the constant are provided. Under additional conditions, we show that GCB holds for the unique invariant measure. This yields a semigroup interpolation method to prove Gaussian concentration for measures which are not available in explicit form. We also consider diffusions "coming down from infinity" for which we show that, from any starting measure, at positive times, GCB holds.
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Contributor : Jean-René Chazottes <>
Submitted on : Thursday, June 27, 2019 - 5:39:24 PM
Last modification on : Monday, July 8, 2019 - 2:59:19 PM


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  • HAL Id : hal-02167399, version 1


J.-R Chazottes, P. Collet, F Redig. Evolution of Gaussian Concentration. 2019. ⟨hal-02167399⟩



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