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Gaussian Fluctuations for the stochastic Burgers equation in dimension $d\geq 2$

Giuseppe Cannizzaro, Massimiliano Gubinelli and Fabio Toninelli

First issued 12 April 2023 · PDF

Abstract

The goal of the present paper is to establish a framework which allows to rigorously determine the large-scale Gaussian fluctuations for a class of singular SPDEs at and above criticality, and therefore beyond the range of applicability of pathwise techniques, such as the theory of Regularity Structures. To this purpose, we focus on a $d$-dimensional generalization of the Stochastic Burgers equation (SBE) introduced in [H. van Beijeren, R. Kutner and H. Spohn, Excess noise for driven diffusive systems, PRL, 1985]. In both the critical $d=2$ and super-critical $d\geq 3$ cases, we show that the scaling limit of (the regularised) SBE is given by a stochastic heat equation with non-trivially renormalised coefficient, introducing a set of tools that we expect to be applicable more widely. For $d\ge3$ the scaling adopted is the classical diffusive one, while in $d=2$ it is the weak coupling scaling which corresponds to tuning down the strength of the interaction in a scale-dependent way.

Versions

  1. Version 2 (arXiv v2) current
    16 October 2023
    arXiv comments: 68 pages, 4 figures. A mistake in an earlier version has been corrected
  2. Version 1 (arXiv v1)
    12 April 2023
    arXiv comments: 65 pages

Cite

Giuseppe Cannizzaro, Massimiliano Gubinelli and Fabio Toninelli. Gaussian Fluctuations for the stochastic Burgers equation in dimension $d\geq 2$. Papers of Massimiliano Gubinelli, 2023, version 2. https://mgubi.org/papers/paper/burgers-gaussian-fluctuations/

Licence: arXiv.org perpetual, non-exclusive license to distribute; all other rights reserved to the authors

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Papers of Massimiliano Gubinelli: an OpenSheaf archive (format 0.1, a draft); this page is generated by opensheaf-py from the archive.