English

A proof of Onsager's conjecture for the stochastic 3D Euler equations

Probability 2025-11-13 v3 Analysis of PDEs

Abstract

This paper investigates the stochastic 3D Euler equations on a periodic domain T3\mathbb{T}^3, driven by a GGGG^*-Wiener process BB of trace class: \begin{align*} \mathrm{d} u+\mathrm{div}(u\otimes u)\,\mathrm{d} t+\nabla p\,\mathrm{d}t=\mathrm{d}B, \quad \mathrm{div} u=0. \end{align*} First, for any ϑ<1/3\vartheta<1/3, we construct infinitely many global-in-time probabilistically strong and analytically weak solutions uC([0,),Cϑ(T3,R3))u\in C([0,\infty),C^{\vartheta}(\mathbb{T}^3,\mathbb{R}^3)). These solutions dissipate the energy pathwisely up to a stopping time t\mathfrak{t}, which can be chosen arbitrarily large with high probability, i.e. it holds almost surely \begin{align*} \|u(t\wedge\mathfrak{t})\|_{L^2}^2< \|u(s\wedge\mathfrak{t})\|_{L^2}^2 +2 \int_{s\wedge\mathfrak{t}}^{t\wedge\mathfrak{t}} \big\langle u(r), \mathrm{d} B(r) \big\rangle +\mathrm{Tr}\big(GG^*\big) (t\wedge\mathfrak{t}-s\wedge\mathfrak{t}), \end{align*} for any 0s<t<0\leq s < t<\infty. We also provide a brief proof of energy conservation for ϑ>1/3\vartheta>1/3 based on \cite{CET94}, thereby confirming the Onsager theorem for the stochastic 3D Euler equations. Second, let 0<ϑˉ<βˉ<1/30<\bar{\vartheta}<\bar{\beta}<1/3, we construct infinitely many global-in-time probabilistically strong and analytically weak solutions in C([0,),Cϑˉ(T3,R3))C([0,\infty),C^{\bar{\vartheta}}(\mathbb{T}^3,\mathbb{R}^3)) for arbitrary divergence-free initial data in Cβˉ(T3,R3)C^{\bar{\beta}}(\mathbb{T}^3,\mathbb{R}^3). Our construction relies on the convex integration method developed in the deterministic setting by \cite{Ise18}, adapting it to the stochastic context by introducing a novel energy inequality into the convex integration scheme and combining stochastic analysis arguments with a Wong--Zakai type estimate.

Keywords

Cite

@article{arxiv.2505.06915,
  title  = {A proof of Onsager's conjecture for the stochastic 3D Euler equations},
  author = {Huaxiang Lü and Lin Lü and Rongchan Zhu},
  journal= {arXiv preprint arXiv:2505.06915},
  year   = {2025}
}

Comments

59 pages