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In this paper we develop a new approach to nonlinear stochastic partial differential equations with Gaussian noise. Our aim is to provide an abstract framework which is applicable to a large class of SPDEs and includes many important cases…

Functional Analysis · Mathematics 2022-05-02 Antonio Agresti , Mark Veraar

Semilinear stochastic evolution equations with multiplicative L\'evy noise and monotone nonlinear drift are considered. Unlike other similar work we do not impose coercivity conditions on coefficients. Existence and uniqueness of the mild…

Probability · Mathematics 2013-12-03 Erfan Salavati , Bijan Z. Zangeneh

We obtain a large deviation principle describing the small time asymptotics of the solution of a stochastic evolution equation with multiplicative noise. Our assumptions are a condition on the linear drift operator that is satisfied by…

Probability · Mathematics 2010-12-06 Terence Jegaraj

The aim of this paper is threefold. Firstly, we prove the existence and the uniqueness of a global strong (in both the probabilistic and the PDE senses) $\mathrm{H}^{1}_2$-valued solution to the 2D stochastic Navier-Stokes equations (SNSEs)…

Probability · Mathematics 2021-10-06 Zdzislaw Brzezniak , Xuhui Peng , Jianliang Zhai

This thesis is devoted to the study of ergodicity and large deviations for the stochastic nonlinear wave (NLW) equation with smooth white noise in 3D. Under some standard growth and dissipativity assumptions on the nonlinearity, we show…

Analysis of PDEs · Mathematics 2015-11-30 Davit Martirosyan

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

In this paper, we establish large deviation principle for the strong solution of a doubly nonlinear PDE driven by small multiplicative Brownian noise. Motononicity arguments and the weak convergence approach have been exploited in the…

Probability · Mathematics 2022-12-27 Ananta K Majee

We present a comprehensive theory of critical spaces for the broad class of quasilinear parabolic evolution equations. The approach is based on maximal $L_p$-regularity in time-weighted function spaces. It is shown that our notion of…

Analysis of PDEs · Mathematics 2017-10-18 Jan Pruess , Gieri Simonett , Mathias Wilke

The one-dimensional SDE with non Lipschitz diffusion coefficient $dX_{t} = b(X_{t})dt + \sigma X_{t}^{\gamma} dB_{t}, \ X_{0}=x, \ \gamma<1$ is widely studied in mathematical finance. Several works have proposed asymptotic analysis of…

Probability · Mathematics 2014-08-26 Giovanni Conforti , Stefano De Marco , Jean-Dominique Deuschel

In this paper, we present a sufficient condition for the large deviation criteria of Budhiraja, Dupuis and Maroulas for functionals of Brownian motions. We then establish a large deviation principle for obstacle problems of quasi-linear…

Probability · Mathematics 2017-12-07 Anis Matoussi , Wissal Sabbagh , Tusheng Zhang

This study focuses on large deviation principles for fully coupled multiscale multivalued stochastic systems, in which the slow component is governed by a multivalued stochastic differential equation and the fast component is described by a…

Probability · Mathematics 2025-12-12 Huijie Qiao

For parabolic stochastic partial differential equations (SPDEs), we show that the numerical methods, including the spatial spectral Galerkin method and further the full discretization via the temporal accelerated exponential Euler method,…

Numerical Analysis · Mathematics 2021-06-22 Chuchu Chen , Ziheng Chen , Jialin Hong , Diancong Jin

This work is concerned with Freidlin-Wentzell type large deviation principle for a family of multi-scale quasilinear and semilinear stochastic partial differential equations. Employing the weak convergence method and Khasminskii's time…

Probability · Mathematics 2021-08-23 Wei Hong , Shihu Li , Wei Liu

This paper investigates the asymptotic behavior of path-dependent multivalued McKean-Vlasov stochastic differential equations perturbed by small noise. Specifically, we first establish a large deviation principle for such equations under…

Probability · Mathematics 2026-05-11 Ying Ma , Huijie Qiao

In this article, we establish the Freidlin-Wentzell type large deviation principle and central limit theorem for stochastic fractional conservation laws with small multiplicative noise in kinetic formulation framework. The weak convergence…

Probability · Mathematics 2023-06-08 Soumya Ranjan Behera , Ananta K. Majee

We prove here the validity of a large deviation principle for the family of invariant measures associated to a two dimensional Navier-Stokes equation on a torus, perturbed by a smooth additive noise.

Probability · Mathematics 2015-09-02 Zdzislaw Brzezniak , Sandra Cerrai

In this work, we investigate the McKean-Vlasov stochastic partial differential equations driven by Poisson random measure. By adapting the variational framework, we prove the well-posedness and large deviation principle for a class of…

Probability · Mathematics 2025-08-05 Yuhang Jiang , Jinming Li , Shihu Li

The climate system is a complex, chaotic system with many degrees of freedom and variability on a vast range of temporal and spatial scales. Attaining a deeper level of understanding of its dynamical processes is a scientific challenge of…

Statistical Mechanics · Physics 2021-06-28 Vera Melinda Galfi , Valerio Lucarini , Francesco Ragone , Jeroen Wouters

The large deviations principles are established for a class of multidimensional degenerate stochastic differential equations with reflecting boundary conditions. The results include two cases where the initial conditions are adapted and…

Probability · Mathematics 2007-05-23 Zongxia Liang

In this paper we develop a method to solve evolution equations on Gelfand triples with time-fractional derivative based on monotonicity techniques. Applications include deterministic and stochastic quasi-linear partial differential…

Analysis of PDEs · Mathematics 2018-05-31 Wei Liu , Michael Röckner , José Luís da Silva