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Regularisation by Gaussian rough path lifts of fractional Brownian motions

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arxiv 2412.01645 v2 pith:3XGKNCGW submitted 2024-12-02 math.PR

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keywords roughalphabrownianfractionalgaussiannoisepathadditive
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abstract

The aim of the paper is to show the probabilistically strong well-posedness of rough differential equations with distributional drifts driven by the Gaussian rough path lift of fractional Brownian motion with Hurst parameter $H\in(1/3,1/2)$. We assume that the noise is nondegenerate and the drift lies in the Besov-H\"older space $\mathcal{C}^\alpha$ for some $\alpha>1-1/(2H)$. The latter condition matches the one of the additive noise case, thereby providing a multiplicative analogue of Catellier-Gubinelli in the regime $H\in(1/3,1/2)$.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Construction of the 1d Self-repelling Brownian Polymer

    math.PR 2025-09 conditional novelty 7.0 of 10

    The 1d self-repelling Brownian polymer, with the singular Dirac interaction, is constructed in the annealed random-environment setting as a unique energy solution, and it is shown to be superdiffusive.

  2. On the density of singular SDEs with fractional noise and applications to McKean-Vlasov equations

    math.PR 2025-06 accept novelty 7.0 of 10

    Singular fBm-driven SDEs with distributional drifts have densities with Besov regularity and Gaussian tails, and the associated McKean-Vlasov equations are well-posed down to the subcritical scaling threshold.

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