Uniform Large Deviation Principle for the Solutions of Two-Dimensional Stochastic Navier–Stokes Equations in Vorticity Form

IF 1.6 2区 数学 Q2 MATHEMATICS, APPLIED
Ankit Kumar, Manil T. Mohan
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引用次数: 0

Abstract

The main objective of this paper is to demonstrate the uniform large deviation principle (UDLP) for the solutions of two-dimensional stochastic Navier–Stokes equations (SNSE) in the vorticity form when perturbed by two distinct types of noises. We first consider an infinite-dimensional additive noise that is white in time and colored in space and then consider a finite-dimensional Wiener process with linear growth coefficient. In order to obtain the ULDP for 2D SNSE in the vorticity form, where the noise is white in time and colored in space, we utilize the existence and uniqueness result from B. Ferrario et. al., Stochastic Process. Appl., 129 (2019), 1568–1604, and the uniform contraction principle. For the finite-dimensional multiplicative Wiener noise, we first prove the existence of a unique local mild solution to the vorticity equation using a truncation and fixed point arguments. We then establish the global existence of the truncated system by deriving a uniform energy estimate for the local mild solution. By applying stopping time arguments and a version of Skorokhod’s representation theorem, we conclude the global existence and uniqueness of a solution to our model. We employ the weak convergence approach to establish the ULDP for the law of the solutions in two distinct topologies. We prove ULDP in the \({{\textrm{C}}([0,T];{\textrm{L}}^p({\mathbb {T}}^2))}\) topology, for \(p>2\), taking into account the uniformity of the initial conditions contained in bounded subsets of \({{\textrm{L}}^p({\mathbb {T}}^2)}\). Finally, in \({{\textrm{C}}([0,T]\times {\mathbb {T}}^2)}\) topology, the uniformity of initial conditions lying in bounded subsets of \({{\textrm{C}}({\mathbb {T}}^2)}\) is considered.

二维随机纳维-斯托克斯方程涡度形式解的均匀大偏差原理
本文的主要目的是证明涡度形式的二维随机纳维-斯托克斯方程(SNSE)解在受到两种不同类型噪声扰动时的均匀大偏差原理(UDLP)。我们首先考虑在时间上为白噪声、在空间上为彩色噪声的无穷维加法噪声,然后考虑具有线性增长系数的有限维维纳过程。为了得到涡度形式的二维 SNSE(噪声在时间上是白的,在空间上是彩色的)的 ULDP,我们利用了 B. Ferrario 等人的 Stochastic Process.应用》,129 (2019),1568-1604,以及均匀收缩原理。对于有限维乘法维纳噪声,我们首先利用截断和定点论证证明了涡度方程唯一局部温和解的存在性。然后,我们通过推导局部温和解的均匀能量估计,建立了截断系统的全局存在性。通过应用停止时间论证和斯科洛霍德表示定理的一个版本,我们得出了模型解的全局存在性和唯一性结论。我们采用弱收敛方法,建立了两种不同拓扑结构中解规律的 ULDP。考虑到初始条件包含在 \({{\textrm{L}}^p({\mathbb {T}}^2)}\) 的有界子集中的均匀性,我们在 \({{\textrm{C}}([0,T];{\textrm{L}}^p({\mathbb {T}}^2)}\) 拓扑中证明了 ULDP。最后,在 \({{\textrm{C}}([0,T]\times {\mathbb {T}}^2)}\ 的拓扑中,考虑了初始条件位于 \({{\textrm{C}}({\mathbb {T}}^2)}\ 的有界子集中的均匀性。
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来源期刊
CiteScore
3.30
自引率
5.60%
发文量
103
审稿时长
>12 weeks
期刊介绍: The Applied Mathematics and Optimization Journal covers a broad range of mathematical methods in particular those that bridge with optimization and have some connection with applications. Core topics include calculus of variations, partial differential equations, stochastic control, optimization of deterministic or stochastic systems in discrete or continuous time, homogenization, control theory, mean field games, dynamic games and optimal transport. Algorithmic, data analytic, machine learning and numerical methods which support the modeling and analysis of optimization problems are encouraged. Of great interest are papers which show some novel idea in either the theory or model which include some connection with potential applications in science and engineering.
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