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Related papers: Approximations to the Stochastic Burgers Equation

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This study considers the problem of the extreme behavior exhibited by solutions to Burgers equation subject to stochastic forcing. More specifically, we are interested in the maximum growth achieved by the "enstrophy" (the Sobolev $H^1$…

Fluid Dynamics · Physics 2018-01-17 Diogo Poças , Bartosz Protas

We consider the approximation via modulation equations for nonlinear SPDEs on unbounded domains with additive space time white noise. Close to a bifurcation an infinite band of eigenvalues changes stability, and we study the impact of small…

Probability · Mathematics 2019-10-30 Luigi Amedeo Bianchi , Dirk Blömker , Guido Schneider

The paper formulates Bayesian inverse problems for inference in a topological measure space given noisy observations. Conditions for the validity of the Bayes formula and the well-posedness of the posterior measure are studied. The abstract…

Probability · Mathematics 2011-05-11 Viet Ha Hoang

A Freidlin-Wentzell type large deviation principle is established for stochastic partial differential equations with slow and fast time-scales, where the slow component is a one-dimensional stochastic Burgers equation with small noise and…

Probability · Mathematics 2020-03-10 Xiaobin Sun , Ran Wang , Lihu Xu , Xue Yang

I analyse a generalised Burger's equation to develop an accurate finite difference approximation to its dynamics. The analysis is based upon centre manifold theory so we are assured that the finite difference model accurately models the…

chao-dyn · Physics 2007-05-23 A. J. Roberts

We consider parabolic stochastic partial differential equations driven by white noise in time. We prove exponential convergence of the transition probabilities towards a unique invariant measure under suitable conditions. These conditions…

Probability · Mathematics 2007-05-23 Martin Hairer

We consider the one-dimensional Burgers' equation forced by fractional derivative of order $\frac{1}{2}$ applied on space-time white noise. Relying on the approaches of Anderson Hamiltonian from Allez and Chouk (2015, arXiv:1511.02718…

Analysis of PDEs · Mathematics 2025-03-04 Kazuo Yamazaki

We derive the scaling function for the one dimensional noisy Burgers equation in the two-soliton approximation within the weak noise canonical phase space approach. The result is in agreement with an earlier heuristic expression and…

Statistical Mechanics · Physics 2014-10-07 Hans C. Fogedby

The influence of small random perturbations on a deterministic dynamical system with a locally stable equilibrium is considered. The perturbed system is described by the It\^{o} stochastic differential equation. It is assumed that the noise…

Mathematical Physics · Physics 2016-02-18 Oskar Sultanov

We establish upper bounds for the weak and strong error resulting from a perturbation of the noise driving the stochastic Burgers equation, where we assume the noise to be additive and of trace class and the initial value to be sufficiently…

Probability · Mathematics 2026-03-20 Sonja Cox , Matas Urbonas

This paper is devoted to the numerical analysis of a fully discrete finite element approximation for the stochastic Benjamin-Bona-Mahony equation driven by multiplicative noise. We first establish the existence and uniqueness of solutions…

Numerical Analysis · Mathematics 2026-03-10 Hung D. Nguyen , Thoa Thieu , Liet Vo

The Stochastic Burgers equation was introduced in [H. van Beijeren, R. Kutner and H. Spohn, Excess noise for driven diffusive systems, PRL, 1985] as a continuous approximation of the fluctuations of the asymmetric simple exclusion process.…

Probability · Mathematics 2024-12-03 Damiano De Gaspari , Levi Haunschmid-Sibitz

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

We consider the stochastic Cahn-Hilliard equation with additive space-time white noise $\epsilon^{\gamma}\dot{W}$ in dimension $d=2,3$, where $\epsilon>0$ is an interfacial width parameter. We study numerical approximation of the equation…

Numerical Analysis · Mathematics 2025-01-09 Ľubomír Baňas , Jean Daniel Mukam

A relativistic generalization of the inviscid Burgers equation was proposed by LeFloch, Makhlof, and Okutmustur and then investigated on a Schwarzschild background. Here, we extend their analysis to a Friedmann-Lemaitre-Robertson-Walker…

Analysis of PDEs · Mathematics 2015-12-29 Tuba Ceylan , Philippe G. LeFloch , Baver Okutmustur

We study the long time statistics of a two-dimensional Hamiltonian system in the presence of Gaussian white noise. While the original dynamics is known to exhibit finite time explosion, we demonstrate that under the impact of the stochastic…

Probability · Mathematics 2025-08-06 Hung D. Nguyen , Lekun Wang

This paper investigates the pathwise uniform convergence in probability of fully discrete finite-element approximations for the two-dimensional stochastic Navier-Stokes equations with multiplicative noise, subject to no-slip boundary…

Numerical Analysis · Mathematics 2025-02-11 Binjie Li , Xiaoping Xie , Qin Zhou

In this paper, we consider a quasi-linear stochastic heat equation on $[0,1]$, with Dirichlet boundary conditions and controlled by the space-time white noise. We formally replace the random perturbation by a family of noisy inputs…

Probability · Mathematics 2009-07-16 Xavier Bardina , Maria Jolis , Lluis Quer-Sardanyons

In this paper we show that solutions of stochastic partial differential equations driven by Brownian motion can be approximated by stochastic partial differential equations forced by pure jump noise/random kicks. Applications to stochastic…

Probability · Mathematics 2014-01-31 Giulia Di Nunno , Tusheng Zhang

Optimal upper and lower error estimates for strong full-discrete numerical approximations of the stochastic heat equation driven by space-time white noise are obtained. In particular, we establish the optimality of strong convergence rates…

Probability · Mathematics 2021-11-02 Sebastian Becker , Benjamin Gess , Arnulf Jentzen , Peter E. Kloeden