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arXiv 2601.22073math.AP
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概率意义下的随机欧拉方程强解

Probabilistically Strong Solutions to Stochastic Euler Equations

Max–Planck–Institute for Mathematics in the Sciences, Leipzig(莱比锡马克斯·普朗克科学计量学研究所);Weierstrass Institute for Applied Analysis and Stochastics (WIAS), Berlin(柏林魏尔斯特拉斯应用分析与随机性研究所)

Benjamin Gess, Robert Lasarzik

AI总结:

本文提出了一种随机背景下能量变分解的方法,解决了随机欧拉方程概率意义下强解的构造问题,并将其推广到由传输噪声驱动的流体。

摘要:

本文建立了随机不可压缩纳维-斯托克斯方程的概率意义下测度值解的存在性,并证明了在粘性消失极限下,这些解收敛于随机不可压缩欧拉方程的概率意义下强解。特别是,这解决了构造满足一般$ L^2 $初始数据能量不等式的随机欧拉方程概率意义下强解的开放问题。我们引入了随机背景下能量变分解的概念,以处理非线性项而不改变概率空间。此外,我们将这些结果推广到由传输噪声驱动的流体。

英文摘要:

In this paper, we establish the existence of probabilistically strong, measure-valued solutions for the stochastic incompressible Navier--Stokes equations with additive and transport noise. Considering the vanishing viscosity limit, we prove the convergence of these solutions to probabilistically strong, dissipative weak solutions to the stochastic incompressible Euler equations with additive and transport noise. Introducing the concept of energy-variational solutions in the stochastic context we are able to treat the nonlinearities without changing the probability space. This resolves the open problem of constructing, in three dimensions, probabilistically, strong solutions of the stochastic Euler equations as vanishing-viscosity limits on the prescribed stochastic basis. In addition, the constructed solutions satisfy the energy inequality and general $L^2$ initial data is treated.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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