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The main goal of the work is to study the stochastic averaging principle for two time-scales stochastic evolution equations driven by L\'evy process. The solution of reduced equation with modified coefficient is derived to approximate the…

Dynamical Systems · Mathematics 2021-11-04 Bin Pei , Yong Xu

A recent paper of Melbourne & Stuart, A note on diffusion limits of chaotic skew product flows, Nonlinearity 24 (2011) 1361-1367, gives a rigorous proof of convergence of a fast-slow deterministic system to a stochastic differential…

Dynamical Systems · Mathematics 2015-06-15 Georg A. Gottwald , Ian Melbourne

In this paper, we establish a small time large deviation principles for scalar stochastic conservation laws driven by multiplicative noise. The doubling of variables method plays a key role.

Probability · Mathematics 2020-04-08 Zhao Dong , Rangrang Zhang

The aim of this paper is to develop tractable large deviation approximations for the empirical measure of a small noise diffusion. The starting point is the Freidlin-Wentzell theory, which shows how to approximate via a large deviation…

Probability · Mathematics 2021-01-11 Paul Dupuis , Guo-Jhen Wu

The limiting behavior of stochastic evolution processes with small noise intensity $\epsilon$ is investigated in distribution-based approach. Let $\mu^{\epsilon}$ be stationary measure for stochastic process $X^{\epsilon}$ with small…

Probability · Mathematics 2016-11-23 Lifeng Chen , Zhao Dong , Jifa Jiang , Jianliang Zhai

We prove the validity of a small noise large deviation principle for the family of invariant measures $\{\mu_\epsilon\}_{\epsilon>0} $ associated to the one dimensional stochastic Allen-Cahn equation with inhomogeneous Dirichlet boundary…

Probability · Mathematics 2026-04-03 Rui Bai , Chunrong Feng , Huaizhong Zhao

This paper introduces a family of stochastic extragradient-type algorithms for a class of nonconvex-nonconcave problems characterized by the weak Minty variational inequality (MVI). Unlike existing results on extragradient methods in the…

Optimization and Control · Mathematics 2023-02-20 Thomas Pethick , Olivier Fercoq , Puya Latafat , Panagiotis Patrinos , Volkan Cevher

We derive a Gronwall type inequality for mild solutions of non-autonomous parabolic rough partial differential equations (RPDEs). This inequality together with an analysis of the Cameron-Martin space associated to the noise, allows us to…

Probability · Mathematics 2025-10-30 Alexandra Blessing , Mazyar Ghani Varzaneh , Tim Seitz

We present a systematic study of moment evolution in multidimensional stochastic difference systems, focusing on characterizing systems whose low-order moments diverge in the neighborhood of a stable fixed point. We consider systems with a…

Mathematical Physics · Physics 2009-11-10 Dennis M. Wilkinson

We establish the large deviation principle for stochastic differential equations with averaging in the case when all coefficients of the fast component depend on the slow one, including diffusion.

Probability · Mathematics 2013-06-11 Alexander Yu. Veretennikov

In this paper, we establish the Freidlin-Wentzell's large deviations for quasilinear parabolic stochastic partial differential equations with multiplicative noise, which are neither monotone nor locally monotone. The proof is based on the…

Probability · Mathematics 2019-12-23 Zhao Dong , Rangrang Zhang , Tusheng Zhang

We establish the moderate deviation principle for the solutions of a class of stochastic partial differential equations with non-Lipschitz continuous coefficients. As an application, we derive the moderate deviation principle for two…

Probability · Mathematics 2016-11-04 Parisa Fatheddin , Jie Xiong

In this paper, we study the asymptotic behavior for multi-scale stochastic differential equations driven by L\'evy processes. The optimal strong convergence order 1/2 is obtained by studying the regularity estimates for the solution of…

Probability · Mathematics 2023-09-26 Yinghui Shi , Xiaobin Sun , Liqiong Wang , Yingchao Xie

The present paper focuses on the stochastic nonlinear Schrodinger equation with polynomial nonlinearity, and a zero-order (no derivatives involved) linear damping. Here, the random forcing term appears as a mix of a nonlinear noise in the…

Probability · Mathematics 2026-03-31 Sandip Roy , Debopriya Mukherjee , Manil Thankamani Mohan

Large deviation estimates for the following linear parabolic equation are studied: \[ \frac{\partial u}{\partial t}=\tr\Big(a(x)D^2u\Big) + b(x)\cdot D u + \int_{\R^N} \Big\{(u(x+y)-u(x)-(D u(x)\cdot y)\ind{|y|<1}(y)\Big\}\d\mu(y), \] where…

Analysis of PDEs · Mathematics 2009-09-09 Cristina Brändle , Emmanuel Chasseigne

In this paper, we present sufficient conditions and criteria to establish the large and moderate deviation principle of multivalued McKean-Vlasov stochastic differential equation by means of the weak convergence method.

Probability · Mathematics 2022-08-31 Fengwu Zhu , Wei Liu

In this paper, we establish the existence of weak solutions for distribution-dependent stochastic differential equations (DDSDEs) driven by a broad class of L\'{e}vy noises, where the drift coefficients satisfy specific integrability…

Probability · Mathematics 2026-04-15 Mingkun Ye

We study the large deviations of a simple noise-perturbed dynamical system having continuous sets of steady states, which mimick those found in some partial differential equations related, for example, to turbulence problems. The system is…

Statistical Mechanics · Physics 2012-06-05 Freddy Bouchet , Hugo Touchette

We investigate the stochastic evolution equations describing the motion of a Non-Newtonian fluids excited by multiplicative noise of L\'evy type. By making use of Galerkin approximation we can prove that the system has a global…

Probability · Mathematics 2014-05-15 Erika Hausenblas , Paul Andre Razafimandimby

We provide a unified treatment of pathwise Large and Moderate deviations principles for a general class of multidimensional stochastic Volterra equations with singular kernels, not necessarily of convolution form. Our methodology is based…

Probability · Mathematics 2022-04-15 Antoine Jacquier , Alexandre Pannier
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