English
Related papers

Related papers: An Invariance Principle for some Reaction-Diffusio…

200 papers

A novel principle is presented which allows for the proof of bounded weak solutions to a class of physically relevant, strongly coupled parabolic systems exhibiting a formal gradient-flow structure. The main feature of these systems is that…

Analysis of PDEs · Mathematics 2015-06-11 Ansgar Jüngel

This is a survey on the intermittent behavior of the parabolic {Anderson} model, which is the Cauchy problem for the heat equation with random potential on the lattice $\Z^d$. We first introduce the model and give heuristic explanations of…

Probability · Mathematics 2007-05-23 Juergen Gaertner , Wolfgang Koenig

A generalized uncertainty principle is obtained from a conformally transformed action containing a scalar field and a unique constraint. The constraint's Lagrange multiplier is found to obey a relativistic diffusion equation transforming…

High Energy Physics - Theory · Physics 2020-04-24 Dor Gabay

We establish a central limit theorem for partial sums of stationary linear random fields with dependent innovations, and an invariance principle for anisotropic fractional Brownian sheets. Our result is a generalization of the invariance…

Probability · Mathematics 2013-02-14 Yizao Wang

We present a general method for studying long time asymptotics of nonlinear parabolic partial differential equations. The method does not rely on a priori estimates such as the maximum principle. It applies to systems of coupled equations,…

chao-dyn · Physics 2008-02-03 J. Bricmont , A. Kupiainen , G. Lin

Measure Differential Equations (MDE) describe the evolution of probability measures driven by probability velocity fields, i.e. probability measures on the tangent bundle. They are, on one side, a measure-theoretic generalization of…

Analysis of PDEs · Mathematics 2020-12-18 Fabio Camilli , Giulia Cavagnari , Raul De Maio , Benedetto Piccoli

This work concerns generalized backward stochastic differential equations, which are coupled with a family of reflecting diffusion processes. First of all, we establish the large deviation principle for forward stochastic differential…

Probability · Mathematics 2024-07-23 Yawen Liu , Huijie Qiao

This work concerns about stochastic Burgers type equations with reflection. First of all, by means of the equicontinuous uniform Laplace principle, we prove the Freidlin-Wentzell uniform large deviation principle for these equations…

Probability · Mathematics 2025-06-19 Huijie Qiao

A parameter estimation problem for a class of semilinear stochastic evolution equations is considered. Conditions for consistency and asymptotic normality are given in terms of growth and continuity properties of the nonlinear part.…

Statistics Theory · Mathematics 2020-02-26 Gregor Pasemann , Wilhelm Stannat

This work explores the use of a forward-backward martingale method together with a decoupling argument and entropic estimates between the conditional and averaged measures to prove a strong averaging principle for stochastic differential…

Probability · Mathematics 2017-09-18 Bob Pepin

We prove the almost sure invariance principle for stationary R^d--valued processes (with dimension-independent very precise error terms), solely under a strong assumption on the characteristic functions of these processes. This assumption…

Dynamical Systems · Mathematics 2011-02-10 Sébastien Gouëzel

The parabolic Anderson model is defined as the partial differential equation \partial u(x,t)/\partial t = \kappa\Delta u(x,t) + \xi(x,t)u(x,t), x\in\Z^d, t\geq 0, where \kappa \in [0,\infty) is the diffusion constant, \Delta is the discrete…

Probability · Mathematics 2016-05-25 Dirk Erhard , Frank den Hollander , Gregory Maillard

We investigate a wide class of two-dimensional hyperbolic systems with singularities, and prove the almost sure invariance principle (ASIP) for the random process generated by sequences of dynamically H\"older observables. The observables…

Dynamical Systems · Mathematics 2018-08-01 Jianyu Chen , Hongkun Zhang , Yun Yang

We devise an abstract, modular scheme to prove continuity of the Lyapunov exponents for a general class of linear cocycles. The main assumption is the availability of appropriate large deviation type (LDT) estimates which are uniform in the…

Dynamical Systems · Mathematics 2015-07-13 Pedro Duarte , Silvius Klein

We introduce a new $\Phi $-derivable approach for the Anderson impurity model in a BCS superconductor. The regime of validity of this conserving theory extends well beyond that of the Hartree-Fock approximation. This is the first…

Superconductivity · Physics 2009-10-30 Ari T. Alastalo , Robert J. Joynt , Martti M. Salomaa

This paper presents theoretical advances in the application of the Stochastic Partial Differential Equation (SPDE) approach in geostatistics. We show a general approach to construct stationary models related to a wide class of linear SPDEs,…

Statistics Theory · Mathematics 2018-07-30 Ricardo Carrizo Vergara , Denis Allard , Nicolas Desassis

Parameter estimation for a parabolic linear stochastic partial differential equation in one space dimension is studied observing the solution field on a discrete grid in a fixed bounded domain. Considering an infill asymptotic regime in…

Statistics Theory · Mathematics 2019-11-26 Florian Hildebrandt , Mathias Trabs

We derive the universality principle for empirical spectral distributions of sample covariance matrices and their Stieltjes transforms. This principle states the following. Suppose quadratic forms of random vectors $y_p$ in $R^p$ satisfy a…

Probability · Mathematics 2014-12-23 Pavel Yaskov

In this paper, we consider a class of slow-fast systems of stochastic partial differential equations where the nonlinearity in the slow equation is not continuous and unbounded. We first provide conditions that ensure the existence of a…

Probability · Mathematics 2023-01-02 Sandra Cerrai , Yichun Zhu

We consider the generalized parabolic Anderson equation (gPAM) in 2 dimensions with periodic boundary. This is an example of a singular semilinear stochastic partial differential equations, solutions of which require renormalization and…

Probability · Mathematics 2016-11-04 K. Chouk , P. K. Friz