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In this work, we focus on the global solvability and uniform large deviations for the solutions of stochastic generalized Burgers-Huxley (SGBH) equation perturbed by a small multiplicative white in time and colored in space noise. The SGBH…

概率论 · 数学 2023-02-14 Ankit Kumar , Vivek Kumar , Manil T. Mohan

The present work is concerned about two-dimensional stochastic convective Brinkman-Forchheimer (2D SCBF) equations perturbed by a white noise (non degenerate) in smooth bounded domains in $\R^{2}$. We establish two important properties of…

概率论 · 数学 2021-01-19 Ankit Kumar , Manil T. Mohan

The present work deals with the global solvability as well as absolute continuity of the law of the solution to stochastic generalized Burgers-Huxley (SGBH) equation driven by multiplicative space-time white noise in a bounded interval of…

概率论 · 数学 2023-07-06 Ankit Kumar , Manil T. Mohan

In this work, we consider the stochastic Burgers-Huxley equation perturbed by multiplicative Gaussian noise, and discuss about the global solvability results and asymptotic behavior of solutions. We show the existence of a global strong…

概率论 · 数学 2020-10-20 Manil T. Mohan

We study the small noise asymptotic for stochastic Burgers equations on $(0,1)$ with Dirichlet boundary condition. We consider the case that the noise is more singular than space-time white noise. We let the noise magnitude $\sqrt{\epsilon}…

概率论 · 数学 2024-12-02 Rui Bai , Chunrong Feng , Huaizhong Zhao

In this work, we investigate the Central Limit Theorem (CLT) and Moderate Deviation Principle (MDP) for the stochastic generalized Burgers-Huxley (SGBH) equation with multiplicative Gaussian noise. The SGBH equation is a…

概率论 · 数学 2024-07-30 Vivek Kumar , Ankit Kumar , Manil T. Mohan

We shall establish a large deviation principle for some occupation measure of the stochastic real Ginzburg-Landau equation driven by $\alpha$-stable noises. As a consequence, we obtain the exact rate of exponential ergodicity of the…

概率论 · 数学 2015-01-28 Ran Wang , Jie Xiong , Lihu Xu

We establish a large deviation principle for the occupation measure of the stochastic real Ginzburg-Landau equation driven by $\alpha$-stable noises. The proof is based on a hyper-exponential recurrence criterion. Our result indicates a…

概率论 · 数学 2015-10-14 Ran Wang , Jie Xiong , Lihu Xu

We prove the existence and uniqueness of invariant measures for the fractional stochastic Burgers equation (FSBE) driven by fractional power of the Laplacian and space-time white noise. We show also that the transition measures of the…

概率论 · 数学 2011-06-13 Zdzisław Brzeźniak , Latifa Debbi , Ben Goldys

We consider the damped nonlinear wave (NLW) equation driven by a spatially regular white noise. Assuming that the noise is non-degenerate in all Fourier modes, we establish a large deviations principle (LDP) for the occupation measures of…

偏微分方程分析 · 数学 2015-05-15 Davit Martirosyan , Vahagn Nersesyan

In this paper, we investigate the stochastic damped Burgers equation with multiplicative space-time white noise defined on the entire real line. We prove the existence and uniqueness of a mild solution of the stochastic damped Burgers…

动力系统 · 数学 2025-01-22 Zhenxin Liu , Zhiyuan Shi

Using the hyper-exponential recurrence criterion, a large deviation principle for the occupation measure is derived for a class of non-linear monotone stochastic partial differential equations. The main results are applied to many concrete…

概率论 · 数学 2016-01-26 Ran Wang , Jie Xiong , Lihu Xu

In this paper, we establish the existence and uniqueness of invariant measures for a class of semilinear stochastic partial differential equations driven by multiplicative noise on a bounded domain. The main results can be applied to SPDEs…

概率论 · 数学 2018-12-12 Zhao Dong , Rangrang Zhang

In this paper we study the Large Deviation Principle (LDP in abbreviation) for a class of Stochastic Partial Differential Equations (SPDEs) in the whole space $\mathbb{R}^d$, with arbitrary dimension $d\geq 1$, under random influence which…

概率论 · 数学 2015-05-20 Tarik El Mellali , Mohamed Mellouk

We consider invariant measures for the stochastic Burgers equation on $\mathbb{R}$, forced by the derivative of a spacetime-homogeneous Gaussian noise that is white in time and smooth in space. An invariant measure is indecomposable, or…

概率论 · 数学 2025-10-01 Alexander Dunlap , Cole Graham , Lenya Ryzhik

We introduce the uniqueness, existence, $L_p$-regularity, and maximal H\"older regularity of the solution to semilinear stochastic partial differential equation driven by a multiplicative space-time white noise: $$ u_t = au_{xx} + bu_{x} +…

概率论 · 数学 2022-05-24 Beom-Seok Han

We study the ergodicity of stochastic reaction-diffusion equation driven by subordinate Brownian motions. After establishing the strong Feller property and irreducibility of the system, we prove the tightness of the solution's law. These…

概率论 · 数学 2017-01-06 Ran Wang , Lihu Xu

In this article, we established a large deviation principle for invariant measures of solutions of stochastic partial differential equations with two reflecting walls driven by space-time white noise.

概率论 · 数学 2012-04-02 Tusheng Zhang

We consider a stochastic Cahn-Hilliard partial differential equation driven by a space-time white noise. We prove the Large Deviations Principle (LDP) for the law of the solutions in the H\"older norm. We use the weak convergence approach…

概率论 · 数学 2017-08-29 Lahcen Boulanba , Mohamed Mellouk

This paper investigates the stochastic Cahn-Hilliard equation (SCHE) driven by additive space-time white noise. We first refine the analytical ergodic theory by proving that the continuum equation admits a unique invariant measure in the…

数值分析 · 数学 2025-12-09 Nan Deng , Yibo Wang , Wanrong Cao
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