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Since the seminal work of Wiener, the chaos expansion has evolved to a powerful methodology for studying a broad range of stochastic differential equations. Yet its complexity for systems subject to the white noise remains significant. The…

Numerical Analysis · Mathematics 2018-06-28 M. H. Gorji

We devise an explicit method to integrate $\alpha$-stable stochastic differential equations (SDEs) with non-Lipschitz coefficients. To mitigate against numerical instabilities caused by unbounded increments of the L\'evy noise, we use a…

Dynamical Systems · Mathematics 2021-06-04 Georg A. Gottwald , Ian Melbourne

Data-driven methods have recently made great progress in the discovery of partial differential equations (PDEs) from spatial-temporal data. However, several challenges remain to be solved, including sparse noisy data, incomplete candidate…

Computational Physics · Physics 2021-09-28 Hao Xu , Dongxiao Zhang , Junsheng Zeng

We study convergence to the invariant measure for a class of semilinear stochastic evolution equations driven by L\'evy noise, including the case of cylindrical noise. For a certain class of equations we prove the exponential rate of…

Probability · Mathematics 2014-04-15 Anna Chonowska-Michalik , Beniamin Goldys

The aim of these notes is to give an overview of the current results about existence and uniqueness of solutions for the stochastic Euler equation driven by a Brownian noise in a two-dimensional bounded domain.

Probability · Mathematics 2013-08-16 Hakima Bessaih

In this paper, we combine deterministic splitting methods with a polynomial chaos expansion method for solving stochastic parabolic evolution problems. The stochastic differential equation is reduced to a system of deterministic equations…

Numerical Analysis · Mathematics 2021-07-02 Andreas Kofler , Tijana Levajković , Hermann Mena , Alexander Ostermann

In this paper, we first show the well-posedness of the SDEs driven by L\'{e}vy noises under mild conditions. Then, we consider the existence and uniqueness of periodic solutions of the SDEs. To establish the ergodicity and uniqueness of…

Probability · Mathematics 2019-06-20 Xiao-Xia Guo , Wei Sun

We consider one-dimensional stochastic differential equations with a boundary condition, driven by a Poisson process. We study existence and uniqueness of solutions and the absolute continuity of the law of the solution. In the case when…

Probability · Mathematics 2007-05-23 Aureli Alabert , Miguel A. Marmolejo

The evaluation of the path-integral representation for stochastic processes in the weak-noise limit shows that these systems are governed by a set of equations which are those of a classical dynamics. We show that, even when the noise is…

Condensed Matter · Physics 2009-10-22 S. J. B. Einchcomb , A. J. McKane

In this paper we study approximations to 3D Navier-Stokes (NS) equation driven by space-time white noise by paracontrolled distribution proposed in [GIP13]. A solution theory for this equation has been developed recently in [ZZ14] based on…

Probability · Mathematics 2014-09-18 Rongchan Zhu , Xiangchan Zhu

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

In this paper we focus on the stochastic Euler-Poincar\'{e} equations with pseudo-differential/multiplicative noise. We first establish two new cancellation properties on pseudo-differential operators, which play a key role in energy…

Analysis of PDEs · Mathematics 2022-09-16 Hao Tang

In this paper we are concerned with the 2D incompressible Navier-Stokes equations driven by space-time white noise. We establish existence of infinitely many global-in-time probabilistically strong and analytically weak solutions $u$ for…

Probability · Mathematics 2023-04-18 Huaxiang Lü , Xiangchan Zhu

In this paper we consider a general class of second order stochastic partial differential equations on $\mathbb{R}^d$ driven by a Gaussian noise which is white in time and it has a homogeneous spatial covariance. Using the techniques of…

Probability · Mathematics 2014-10-08 Yaozhong Hu , Jingyu Huang , David Nualart , Xiaobin Sun

We prove existence and uniqueness of strong solutions for a class of semilinear stochastic evolution equations driven by general Hilbert space-valued semimartingales, with drift equal to the sum of a linear maximal monotone operator in…

Probability · Mathematics 2019-11-01 Carlo Marinelli , Luca Scarpa

In this paper, we study the weak irreducibility of stochastic delay differential equations(SDDEs) driven by pure jump noise. The main contribution of this paper is to provide a concise proof of weak irreducibility, releasing condition…

Probability · Mathematics 2025-09-03 Hao Yang , Jian Wang

We show that the system of point vortices, perturbed by a certain transport type noise, converges weakly to the vorticity form of 2D Navier--Stokes equations driven by the space-time white noise.

Probability · Mathematics 2020-10-01 Franco Flandoli , Dejun Luo

A parameter estimation problem is considered for a one-dimensional stochastic wave equation driven by additive space-time Gaussian white noise. The estimator is of spectral type and utilizes a finite number of the spatial Fourier…

Probability · Mathematics 2008-10-02 W. Liu , S. V. Lototsky

This is an overview about natural sample spaces for differential equations driven by various noises. Appropriate sample spaces are needed in order to facilitate a random dynamical systems approach for stochastic differential equations. The…

Dynamical Systems · Mathematics 2009-12-02 Jinqiao Duan , Xingye Kan , Bjaorn Schmalfuss

We consider stochastic dynamics of a particle on a plane in presence of two noises and a confining parabolic potential - an analog of the experimentally-relevant Brownian Gyrator (BG) model. In contrast to the standard BG model, we suppose…

Statistical Mechanics · Physics 2025-12-16 Timothée Herbeau , Leonid Pastur , Pascal Viot , Gleb Oshanin
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