Table of Contents
Fetching ...

Almost global existence for the stochastic Navier-Stokes equations with small $H^{1/2}$ data

Mustafa Sencer Aydın, Igor Kukavica, Fanhui Xu

TL;DR

This work studies global existence for the stochastic Navier-Stokes equations with multiplicative noise on $\mathbb{T}^3$ for initial data in $H^{1/2}$, achieving almost global-in-time solutions with high probability when data and noise are small. A key innovation is an infinite decomposition of the initial data into smoother components $u_0=\sum_{k\ge0} v_0^{(k)}$, enabling a cascade of SNSE-type problems with cutoffs and a fixed-point scheme to control the nonlinear advection via $H^{\frac12+\delta}$ regularity. The authors prove global energy bounds and probabilistic stopping-time controls, then pass to the limit to obtain a probabilistically strong solution up to a stopping time $\tau$, with $\mathbb{P}(\tau=\infty)\ge 1-p_0$ under small data/noise, and a local-in-time existence result when the noise is not necessarily small. The approach leverages the stochastic heat equation as a core auxiliary tool to manage regularity and energy, offering a novel pathway around criticality for SNSE with multiplicative noise. These results advance understanding of stochastic fluid models at critical regularity and provide quantitative probabilistic guarantees for global behavior in low-regularity regimes.

Abstract

We address the global existence of solutions to the stochastic Navier-Stokes equations with multiplicative noise and with initial data in $H^{1/2}(\mathbb{T}^{3})$. We prove that the solution exists globally in time with probability arbitrarily close to~$1$ if the initial data and noise are sufficiently small. If the noise is not assumed to be small, then the solution is global on a sufficiently small deterministic time interval with probability arbitrarily close to~$1$.

Almost global existence for the stochastic Navier-Stokes equations with small $H^{1/2}$ data

TL;DR

This work studies global existence for the stochastic Navier-Stokes equations with multiplicative noise on for initial data in , achieving almost global-in-time solutions with high probability when data and noise are small. A key innovation is an infinite decomposition of the initial data into smoother components , enabling a cascade of SNSE-type problems with cutoffs and a fixed-point scheme to control the nonlinear advection via regularity. The authors prove global energy bounds and probabilistic stopping-time controls, then pass to the limit to obtain a probabilistically strong solution up to a stopping time , with under small data/noise, and a local-in-time existence result when the noise is not necessarily small. The approach leverages the stochastic heat equation as a core auxiliary tool to manage regularity and energy, offering a novel pathway around criticality for SNSE with multiplicative noise. These results advance understanding of stochastic fluid models at critical regularity and provide quantitative probabilistic guarantees for global behavior in low-regularity regimes.

Abstract

We address the global existence of solutions to the stochastic Navier-Stokes equations with multiplicative noise and with initial data in . We prove that the solution exists globally in time with probability arbitrarily close to~ if the initial data and noise are sufficiently small. If the noise is not assumed to be small, then the solution is global on a sufficiently small deterministic time interval with probability arbitrarily close to~.
Paper Structure (7 sections, 11 theorems, 127 equations)

This paper contains 7 sections, 11 theorems, 127 equations.

Key Result

Theorem 2.1

Let ${{u}}_0\in L^\infty(\Omega; H^{1/2}(\mathbb T^3))$ be such that $\nabla\cdot u_0=0$ and $\int_{\mathbb T^3} u_0=0$. Suppose that the assumptions EQ04 and EQ05 hold, where $\epsilon_{\sigma}\in(0,1]$ is sufficiently small. For every $p_0\in(0,1]$, there exists $\epsilon_0\in(0,1]$ such that if then there is a stopping time $\tau\in(0,\infty]$ and a unique solution $(u, \tau)$ of EQ01 on $(\Om

Theorems & Definitions (22)

  • Theorem 2.1: Global solution with small noise and initial data
  • Theorem 2.2: Local solution with small initial data
  • Lemma 3.1
  • proof : Proof of Lemma \ref{['L01']}
  • Lemma 4.1: Decomposition of initial data
  • Lemma 4.2
  • proof : Proof of Lemma \ref{['LM01']}
  • Lemma 4.3
  • proof : Proof of Lemma \ref{['LM01']}
  • Lemma 4.4: An $H^{\frac{1}{2}}$-energy control
  • ...and 12 more