Sharp Gaussian regularity on the circle and applications to the fractional stochastic heat equation
27 pages
English

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Sharp Gaussian regularity on the circle and applications to the fractional stochastic heat equation

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27 pages
English
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Sharp Gaussian regularity on the circle, and applications to the fractional stochastic heat equation March 29, 2004 1 Introduction This article has two purposes: to present a sharp regularity theory for Gaussian fields on the unit circle S1, and to apply this theory to formulate a spatial regularity theory for the stochastic heat equation (SHE). In this introduction, we describe the results that we aim at, and the road that we take to achieve them. We have in mind the equation ∂X ∂t (t, x) = ∆xX (t, x) + ∂B ∂t (t, x) : x ? S1; t ? [0, 1]; u (0, x) = 0, (1) where B is a Gaussian field on [0, 1] ? S1 whose behavior in time is that of fractional Brownian motion (fBm) with any parameter H ? (0, 1), and whose behavior in space is homogeneous, and can be completely arbitrary within that restriction. By “regularity theory” for a Gaussian field Y we mean a characterization of almost- sure modulus of continuity for Y that can be written using information about Y 's covari- ance. We seek necessary and sufficient conditions whenever possible, hence the use of the word “characterization”. By “spatial regularity theory” for the stochastic heat equation, we mean a characerization of the almost-sure modulus of continuity for the equation's solu- tion in its space parameter x ? S1, that can be written using

  • necessary

  • dimensional situations

  • single gaussian field

  • gaussian field

  • gaussian random

  • gaussian regularity

  • without loss

  • additive gaussian fractional

  • higer-dimensional spaces

  • nearly necessary


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Nombre de lectures 14
Langue English

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Sharp
Gaussian regularity on the circle, and the fractional stochastic heat equa
applications to tion
1 Introduction
March 29, 2004
This article has two purposes: to present a sharpregularity theoryfor Gaussian elds on the unit circleS1formulate a spatial regularity theory for the, and to apply this theory to stochastic heat equation (SHE). In this introduction, we describe the results that we aim at, and the road that we take to achieve them. We have in mind the equation Xt(t, x) = xX(t, x) +Bt(t, x) :xS1;t[0,1];u(0, x (1)) = 0, whereBis a Gaussian eld on [0,1]×S1whose behavior in time is that of fractional Brownian motion (fBm) with any parameterH(0,1), and whose behavior in space is homogeneous, and can be completely arbitrary within that restriction. By “regularity theory” for a Gaussian eldYwe mean airazitnoteacarchof almost-sure modulus of continuity forYthat can be written using information aboutY’s covari-ance. We seek necessaryandconditions whenever possible, hence the use of thesucient word “characterization”. By “spatial regularity theory” for the stochastic heat equation, we mean a characerization of the almost-sure modulus of continuity for the equation’s solu-tion in its space parameterxS1,that can be written using information about the spatial covariance of the equation’s data (additive Gaussian fractional noise∂B/∂t), or that can be formulated in exact relation to the data’s almost sure modulus of continuity inx. Let us be more specic about the distinction between the various characterizations. LetY(x) := (Ix)HB(1, x dened a homogeneous Gaussian eld on). ThisS1. We can also abusively use the notationYfor the random eldY:= (I)HBon [0,1]×S1, which can be called the “2H-fractional spatial antiderivative” ofB is well understood. It (for the Brownian case, see [19], or more recently [16], [17], [12]) that in our one-dimensional situation,Bdoes not need to be a bonade function inxfor the SHE (1) to have a solution. In fact onlyY[15] it is shown that this is a necessaryneeds to be a bonade function; in and sucient condition even in the fractional Brownian case. Once a condition for existence is given, it is natural to seek conditions for regu-larity. We consider two types of conditions for guaranteeing/characterizing the fact that the solutionXof the SHE (1) admits a given xed functionfas an almost-sure uniform modulus of continuity:
Type I (anintrinsicorpathwisecondition): the fact that the same almost-sure continuity holds forY:= (I)HB; Type II (a conditionon the distribution condition that can be written using the): a covariance function ofY.
1
From the applied physical point of view, the necessary Type I condition may be quite useful. Indeed, the solution of a stochastic PDE can be a model for a turbulent
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