Characterizing models in regularity structures: a quasilinear case

Fuente: arXiv
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Main Author: Tempelmayr, Markus
Format: Preprint
Published: 2023
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author Tempelmayr, Markus
author_facet Tempelmayr, Markus
contents We give a novel characterization of the centered model in regularity structures which persists for rough drivers even as a mollification fades away. We present our result for a class of quasilinear equations driven by noise, however we believe that the method is robust and applies to a much broader class of subcritical equations. Furthermore, we prove that a convergent sequence of noise ensembles, satisfying uniformly a spectral gap assumption, implies the corresponding convergence of the associated models. Combined with the characterization, this establishes a universality-type result.
format Preprint
id arxiv_https___arxiv_org_abs_2303_18192
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Characterizing models in regularity structures: a quasilinear case
Tempelmayr, Markus
Probability
Analysis of PDEs
60H17, 60L30, 60H07
We give a novel characterization of the centered model in regularity structures which persists for rough drivers even as a mollification fades away. We present our result for a class of quasilinear equations driven by noise, however we believe that the method is robust and applies to a much broader class of subcritical equations. Furthermore, we prove that a convergent sequence of noise ensembles, satisfying uniformly a spectral gap assumption, implies the corresponding convergence of the associated models. Combined with the characterization, this establishes a universality-type result.
title Characterizing models in regularity structures: a quasilinear case
topic Probability
Analysis of PDEs
60H17, 60L30, 60H07
url https://arxiv.org/abs/2303.18192