Ergodicity for SPDEs driven by divergence-free transport noise

arXiv (Cornell University) 2026 Preprint Open access

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Authors: Benjamin Gess, Rishabh S. Gvalani, Adrian Martini
DOI: 10.48550/arxiv.2601.22056
Cited by: 0

Abstract

We study the ergodic behaviour of the McKean-Vlasov equations driven by common, divergence-free transport noise. In particular, we show that in dimension $d\geq 2$, if the noise is mixing and sufficiently strong it can enforce the uniqueness of invariant probability measures, even if the deterministic part of equation has multiple steady states.

Fields of Study & Subjects

Stochastic processes and statistical mechanics Stochastic processes and financial applications Mathematical Dynamics and Fractals

Publication details

Journal / source
arXiv (Cornell University)
Publication date
29 January 2026
Document type
Preprint