Search results for " 60L50"

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Geometric rough paths on infinite dimensional spaces

2022

Similar to ordinary differential equations, rough paths and rough differential equations can be formulated in a Banach space setting. For $\alpha\in (1/3,1/2)$, we give criteria for when we can approximate Banach space-valued weakly geometric $\alpha$-rough paths by signatures of curves of bounded variation, given some tuning of the H\"older parameter. We show that these criteria are satisfied for weakly geometric rough paths on Hilbert spaces. As an application, we obtain Wong-Zakai type result for function space valued martingales using the notion of (unbounded) rough drivers.

22E65 53C17 60H10 60L20 60L50Applied MathematicsProbability (math.PR)Metric Geometry (math.MG)VDP::Mathematics: 410:Matematikk og Naturvitenskap: 400::Matematikk: 410::Topologi/geometri: 415 [VDP]:Matematikk: 410 [VDP]:Mathematics: 410 [VDP]Mathematics - Metric GeometryFOS: MathematicsVDP::Matematikk: 410MatematikkAnalysisMathematics - ProbabilityMathematics
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Solution properties of the incompressible Euler system with rough path advection

2021

The present paper aims to establish the local well-posedness of Euler's fluid equations on geometric rough paths. In particular, we consider the Euler equations for the incompressible flow of an ideal fluid whose Lagrangian transport velocity possesses an additional rough-in-time, divergence-free vector field. In recent work, we have demonstrated that this system can be derived from Clebsch and Hamilton-Pontryagin variational principles that possess a perturbative geometric rough path Lie-advection constraint. In this paper, we prove the local well-posedness of the system in $L^2$-Sobolev spaces $H^m$ with integer regularity $m\ge \lfloor d/2\rfloor+2$ and establish a Beale-Kato-Majda (BKM)…

Physics::Fluid DynamicsMathematics - Analysis of PDEsProbability (math.PR)FOS: MathematicsMathematics::Analysis of PDEs60L20 60L50 60H15 76B03 35Q31VDP::Matematikk og Naturvitenskap: 400::Matematikk: 410AnalysisMathematics - ProbabilityAnalysis of PDEs (math.AP)
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