Strong Uniqueness by Kraichnan Transport Noise for the 2D Boussinesq Equations with Zero Viscosity

Fuente: arXiv
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Main Authors: Jiao, Shuaijie, Luo, Dejun
Format: Preprint
Published: 2025
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author Jiao, Shuaijie
Luo, Dejun
author_facet Jiao, Shuaijie
Luo, Dejun
contents We investigate the inviscid 2D Boussinesq equations driven by rough transport noise of Kraichnan type with regularity index $α\in (0,1/2)$. For all $1<p<\infty$, we establish the existence and uniqueness of probabilistic strong solutions for all $L^p$ initial vorticity and $L^2$ initial temperature, under the parameter constraint $0<α< 1-1/(p\wedge 2)$. The key ingredient is the anomalous regularity due to the noise proven by Coghi and Maurelli \cite{CogMau} who dealt with stochastic 2D Euler equations. Combining techniques from analysis and probability, we demonstrate how the additional regularity from noise compensates the singularity due to the nonlinear parts and coupled terms.
format Preprint
id arxiv_https___arxiv_org_abs_2504_19153
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Strong Uniqueness by Kraichnan Transport Noise for the 2D Boussinesq Equations with Zero Viscosity
Jiao, Shuaijie
Luo, Dejun
Probability
Analysis of PDEs
We investigate the inviscid 2D Boussinesq equations driven by rough transport noise of Kraichnan type with regularity index $α\in (0,1/2)$. For all $1<p<\infty$, we establish the existence and uniqueness of probabilistic strong solutions for all $L^p$ initial vorticity and $L^2$ initial temperature, under the parameter constraint $0<α< 1-1/(p\wedge 2)$. The key ingredient is the anomalous regularity due to the noise proven by Coghi and Maurelli \cite{CogMau} who dealt with stochastic 2D Euler equations. Combining techniques from analysis and probability, we demonstrate how the additional regularity from noise compensates the singularity due to the nonlinear parts and coupled terms.
title Strong Uniqueness by Kraichnan Transport Noise for the 2D Boussinesq Equations with Zero Viscosity
topic Probability
Analysis of PDEs
url https://arxiv.org/abs/2504.19153