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In this paper we consider the stochastic primitive equation for geophysical flows subject to transport noise and turbulent pressure. Admitting very rough noise terms, the global existence and uniqueness of solutions to this stochastic…

Analysis of PDEs · Mathematics 2022-10-26 Antonio Agresti , Matthias Hieber , Amru Hussein , Martin Saal

In this work we study fractal properties of rough differential equations driven by a fractional Brownian motions with Hurst parameter $H>\frac{1}{4}$. In particular, we show that the Hausdorff dimension of the sample paths of the solution…

Probability · Mathematics 2015-01-29 Shuwen Lou , Cheng Ouyang

We provide an account for the existence and uniqueness of solutions to rough differential equations under the framework of controlled rough paths. The case when the driving path is $\beta$-H\"older continuous, for $\beta>1/3$, is widely…

Classical Analysis and ODEs · Mathematics 2020-09-29 Horatio Boedihardjo , Xi Geng

Uncertainties are abundant in complex systems. Mathematical models for these systems thus contain random effects or noises. The models are often in the form of stochastic differential equations, with some parameters to be determined by…

Numerical Analysis · Mathematics 2015-03-13 Jiarui Yang , Jinqiao Duan

In this work we present a condition for the regularity, in both space and Malliavin sense, of strong solutions to SDEs driven by Brownian motion. We conjecture that this condition is optimal. As a consequence, we are able to improve the…

Probability · Mathematics 2015-09-11 David Banos , Torstein Nilssen

The stochastic partial differential equation analyzed in this work, is motivated by a simplified mesoscopic physical model for phase separation. It describes pattern formation due to adsorption and desorption mechanisms involved in surface…

Probability · Mathematics 2018-02-20 D. C. Antonopoulou , D. Farazakis , G. D. Karali

The theory of rough paths arose from a desire to establish continuity properties of ordinary differential equations involving terms of low regularity. While essentially an analytic theory, its main motivation and applications are in…

Classical Analysis and ODEs · Mathematics 2025-01-28 Ilya Chevyrev

Fractional Gaussian noise models the time series with long-range dependence; when the Hurst index $H>1/2$, it has positive correlation reflecting a persistent autocorrelation structure. This paper studies the numerical method for solving…

Numerical Analysis · Mathematics 2020-07-29 Daxin Nie , Jing Sun , Weihua Deng

We develop the rough path counterpart of It\^o stochastic integration and - differential equations driven by general semimartingales. This significantly enlarges the classes of (It\^o / forward) stochastic differential equations treatable…

Probability · Mathematics 2017-09-18 Peter K. Friz , Huilin Zhang

We consider a nonlinear stochastic partial differential equation (SPDE) in divergence form where the forcing term is a Gaussian noise, that is white in time and colored in space such that the gradient of the solution is H\"older-continuous,…

Analysis of PDEs · Mathematics 2022-02-03 Florian Kunick

We consider anticipative Stratonovich stochastic differential equations driven by some stochastic process lifted to a rough path. Neither adaptedness of initial point and vector fields nor commuting conditions between vector field is…

Probability · Mathematics 2011-11-10 Laure Coutin , Peter Friz , Nicolas Victoir

We explore the limit of stochastic differential equations driven by some random processes satisfying singularly perturbed second order stochastic differential equations. The main tool we employ is the universal limit theorem in rough path…

Probability · Mathematics 2026-04-08 Qingming Zhao , Xueru Liu , Wei Wang

We study a regularization by noise phenomenon for the continuous parabolic Anderson model with a potential shifted along paths of fractional Brownian motion. We demonstrate that provided the Hurst parameter is chosen sufficiently small,…

Probability · Mathematics 2022-05-11 Florian Bechtold

In this paper we study a class of distribution dependent stochastic differential equations driven by fractional Brownian motions with Hurst parameter H\in(1/2,1). We prove the well-posedness of this type equations, and then establish a…

Probability · Mathematics 2021-06-01 Xiliang Fan , Xing Huang , Yongqiang Suo , Chenggui Yuan

A Langevin equation is proposed to describe the transport of overdamped Brownian particles in a periodic rough potential and driven by an unbiased periodic force. The equation can be transformed into the Fokker-Planck equation by using the…

Statistical Mechanics · Physics 2023-04-05 Peng Wang , Yang Zhang , Peng-Juan Zhang , Jie Huo , Xu-Ming Wang

The stochastic Cahn-Hilliard equation driven by a fractional Brownian sheet provides a more accurate model for correlated space-time random perturbations. This study delves into two key aspects: first, it rigorously examines the regularity…

Numerical Analysis · Mathematics 2026-02-16 Nan Deng , Wanrong Cao

In this paper, we study a class of one-dimensional stochastic differential equations driven by fractional Brownian motion with Hurst parameter $H>\ff 1 2$. The drift term of the equation is locally Lipschitz and unbounded in the…

Probability · Mathematics 2019-01-01 Shao-Qin Zhang , Chenggui Yuan

In this paper we study a stochastic differential equation driven by a fractional Brownian motion with a discontinuous coefficient. We also give an approximation to the solution of the equation. This is a first step to define a fractional…

Probability · Mathematics 2016-07-25 Johanna Garzón , Jorge A. León , Soledad Torres

We construct solutions to Burgers type equations perturbed by a multiplicative space-time white noise in one space dimension. Due to the roughness of the driving noise, solutions are not regular enough to be amenable to classical methods.…

Probability · Mathematics 2016-06-02 Martin Hairer , Hendrik Weber

We show in this work how the machinery of C^1-approximate flows introduced in our previous work "Flows driven by rough paths", provides a very efficient tool for proving well-posedness results for path-dependent rough differential equations…

Probability · Mathematics 2013-09-06 Ismael Bailleul
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