Characterizing models in regularity structures: a quasilinear case
Probability
2025-06-10 v2 Analysis of PDEs
Abstract
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.
Cite
@article{arxiv.2303.18192,
title = {Characterizing models in regularity structures: a quasilinear case},
author = {Markus Tempelmayr},
journal= {arXiv preprint arXiv:2303.18192},
year = {2025}
}
Comments
Minor typographical changes