Regularization by noise for rough differential equations driven by Gaussian rough paths

Fuente: arXiv
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Auteurs principaux: Catellier, Rémi, Duboscq, Romain
Format: Preprint
Publié: 2022
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author Catellier, Rémi
Duboscq, Romain
author_facet Catellier, Rémi
Duboscq, Romain
contents We consider the rough differential equation with drift driven by a Gaussian geometric rough path. Under natural conditions on the rough path, namely non-determinism, and uniform ellipticity conditions on the diffusion coefficient, we prove path-by-path well-posedness of the equation for poorly regular drifts. In the case of the fractional Brownian motion $B^H$ for $H>\frac14$, we prove that the drift may be taken to be $κ>0$ Hölder continuous and bounded for $κ>\frac32 - \frac1{2H}$. A flow transform of the equation and Malliavin calculus for Gaussian rough paths are used to achieve such a result.
format Preprint
id arxiv_https___arxiv_org_abs_2207_04251
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Regularization by noise for rough differential equations driven by Gaussian rough paths
Catellier, Rémi
Duboscq, Romain
Probability
We consider the rough differential equation with drift driven by a Gaussian geometric rough path. Under natural conditions on the rough path, namely non-determinism, and uniform ellipticity conditions on the diffusion coefficient, we prove path-by-path well-posedness of the equation for poorly regular drifts. In the case of the fractional Brownian motion $B^H$ for $H>\frac14$, we prove that the drift may be taken to be $κ>0$ Hölder continuous and bounded for $κ>\frac32 - \frac1{2H}$. A flow transform of the equation and Malliavin calculus for Gaussian rough paths are used to achieve such a result.
title Regularization by noise for rough differential equations driven by Gaussian rough paths
topic Probability
url https://arxiv.org/abs/2207.04251