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We prove the exponential stability of the zero solution of a stochastic differential equation with a H\"older noise, under the strong dissipativity assumption. As a result, we also prove that there exists a random pullback attractor for a…

Probability · Mathematics 2019-05-14 Luu Hoang Duc , Phan Thanh Hong , Nguyen Dinh Cong

We mainly investigate the log-Harnack inequality for the reflected stochastic partial differential equation driven by multiplicative noises based on the gradient estimate of the associated Markov semigroup. To do it, the penalization method…

Probability · Mathematics 2020-07-22 Bin Xie

We prove the large deviation principle for the law of the solutions to a class of parabolic semilinear stochastic partial differential equations driven by multiplicative noise, in $C\big([0,T]:L^\rho(D)\big)$, where $D\subset {\mathbb R}^d$…

Probability · Mathematics 2020-10-28 Leila Setayeshgar

This paper is concerned with the large deviation principle of the non-local fractional stochastic reaction-diffusion equation with a polynomial drift of arbitrary degree driven by multiplicative noise defined on unbounded domains. We first…

Probability · Mathematics 2023-05-23 Bixiang Wang

In this article, we study the stability of solutions to 3D stochastic primitive equations driven by fractional noise. Since the fractional Brownian motion is essentially different from Brownian motion, lots of stochastic analysis tools are…

Probability · Mathematics 2021-04-21 Lidan Wang , Guoli Zhou

In this paper, under a one-sided Lipschitz condition on the drift coefficient we adopt (via contraction principle) a exponential approximation argument to investigate large deviations for neutral stochastic functional differential…

Probability · Mathematics 2019-03-18 Yongqiang Suo , Chenggui Yuan

A probabilistic method for solving the Monge-Kantorovich mass transport problem on $R^d$ is introduced. A system of empirical measures of independent particles is built in such a way that it obeys a doubly indexed large deviation principle…

Probability · Mathematics 2007-10-09 Christian Léonard

We study the existence and uniqueness, the regularity, and the long-time behavior of strong solutions to stochastic curve shortening flow driven by a transport-type pure jump L\'evy noise. To obtain the existence and uniqueness of strong…

Probability · Mathematics 2026-05-12 Xiaotian Ge , Shijie Shang , Weina Wu , Jianliang Zhai

This paper provides a large deviation principle for Non-Markovian, Brownian motion driven stochastic differential equations with random coefficients. Similar to Gao and Liu \cite{GL}, this extends the corresponding results collected in…

Probability · Mathematics 2014-07-22 Jin Ma , Zhenjie Ren , Nizar Touzi , Jianfeng Zhang

In this work, a stochastic representation based on a physical transport principle is proposed to account for mesoscale eddy effects on the large-scale oceanic circulation. This stochastic framework arises from a decomposition of the…

Geophysics · Physics 2022-07-26 Long Li , Bruno Deremble , Noé Lahaye , Etienne Mémin

The theory of stochastic approximations form the theoretical foundation for studying convergence properties of many popular recursive learning algorithms in statistics, machine learning and statistical physics. Large deviations for…

Probability · Mathematics 2025-02-05 Henrik Hult , Adam Lindhe , Pierre Nyquist , Guo-Jhen Wu

We recently proposed a method for estimation of states and parameters in stochastic differential equations, which included intermediate time points between observations and used the Laplace approximation to integrate out these intermediate…

Probability · Mathematics 2025-04-01 Uffe Høgsbro Thygesen

We prove a large deviation principle for stochastic differential equations driven by semimartingales, with additive controls. Conditions are given in terms of characteristics of driven semimartingales, so that if the noise-control pairs…

Probability · Mathematics 2024-08-13 Qiao Huang , Wei Wei , Jinqiao Duan

In this paper, we are concerned with multi-scale distribution dependent stochastic differential equations driven by fractional Brownian motion (with Hurst index $H>\frac12$ and standard Brownian motion, simultaneously. Our aim is to…

Probability · Mathematics 2023-06-12 Shen Gunagjun , Zhou Huan , Wu Jianglun

We consider a $p$-Laplace evolution problem with multiplicative noise on a bounded domain $D \subset \mathbb{R}^d$ with homogeneous Dirichlet boundary conditions for $1<p< \infty$. The random initial data is merely integrable. Consequently,…

Analysis of PDEs · Mathematics 2021-03-02 Niklas Sapountzoglou , Aleksandra Zimmermann

We study the large deviations principle (LDP) for stationary solutions of a class of stochastic differential equations (SDE) in infinite time intervals by the weak convergence approach, and then establish the LDP for the invariant measures…

Probability · Mathematics 2022-06-07 Peipei Gao , Yong Liu , Yue Sun , Zuohuan Zheng

In this paper, we establish existence and uniqueness of strong solutions for a stochastic differential equation driven by an additive noise given by the sum of two correlated fractional Brownian sheets with different Hurst parameters. Our…

Probability · Mathematics 2026-03-11 Rachid Belfadli , Youssef Ouknine , Ercan Sönmez

We study an evolutionary $p$-Laplace problem whose potential is subject to a translation in time. Provided the trajectory along which the potential is translated admits a sufficiently regular local time, we establish existence of solutions…

Analysis of PDEs · Mathematics 2023-07-24 Florian Bechtold , Jörn Wichmann

We establish a quadratic transportation cost inequality under the uniform norm for solutions to mean reflected stochastic partial differential equations, a new type of equation in which the compensating reflection part depends not on the…

Probability · Mathematics 2026-05-19 Beibei Zhang , Bin Qian

In this paper, we show the existence and uniqueness of a strong solution to stochastic 3D tamed Navier-Stokes equations driven by multiplicative Levy noise with periodic boundary conditions. Then we establish the large deviation principles…

Probability · Mathematics 2020-02-24 Zhao Dong , Rangrang Zhang