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arXiv math/0512056math.APcs.NAmath.NA
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三维随机Navier-Stokes方程的指数混合

Exponential mixing for the 3D stochastic Navier--Stokes equations

Cyril Odasso

AI总结:

研究三维Navier-Stokes方程在时间白噪声驱动下的弱解指数收敛到平衡态,通过耦合方法并引入新思想克服非唯一性问题。

摘要:

我们研究由时间白噪声驱动的三维Navier-Stokes方程(NS3D)。我们证明,如果噪声在空间上足够光滑且非退化,则弱解指数收敛到平衡态。我们使用耦合方法。二维情形所用的论证不适用,因为众所周知,NS3D的唯一性是开放问题。我们引入了新思想。但注意,由于我们处理非退化噪声,出现了许多简化。

英文摘要:

We study the Navier-Stokes equations in dimension 3 (NS3D) driven by a noise which is white in time. We establish that if the noise is at same time sufficiently smooth and non degenerate in space, then the weak solutions converge exponentially fast to equilibrium. We use a coupling method. The arguments used in dimension two do not apply since, as is well known, uniqueness is an open problem for NS3D. New ideas are introduced. Note however that many simplifications appears since we work with non degenerate noises.

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