{"title":"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","authors":"Ankit Kumar, Manil T. Mohan","doi":"10.1007/s00245-024-10150-5","DOIUrl":null,"url":null,"abstract":"<div><p>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 <i>B. Ferrario et. al., Stochastic Process. Appl.,</i> <b>129</b> <i> (2019), 1568–1604,</i> and the <i>uniform contraction principle</i>. 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 <span>\\({{\\textrm{C}}([0,T];{\\textrm{L}}^p({\\mathbb {T}}^2))}\\)</span> topology, for <span>\\(p>2\\)</span>, taking into account the uniformity of the initial conditions contained in bounded subsets of <span>\\({{\\textrm{L}}^p({\\mathbb {T}}^2)}\\)</span>. Finally, in <span>\\({{\\textrm{C}}([0,T]\\times {\\mathbb {T}}^2)}\\)</span> topology, the uniformity of initial conditions lying in bounded subsets of <span>\\({{\\textrm{C}}({\\mathbb {T}}^2)}\\)</span> is considered.</p></div>","PeriodicalId":55566,"journal":{"name":"Applied Mathematics and Optimization","volume":"90 1","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Uniform Large Deviation Principle for the Solutions of Two-Dimensional Stochastic Navier–Stokes Equations in Vorticity Form\",\"authors\":\"Ankit Kumar, Manil T. Mohan\",\"doi\":\"10.1007/s00245-024-10150-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>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 <i>B. Ferrario et. al., Stochastic Process. Appl.,</i> <b>129</b> <i> (2019), 1568–1604,</i> and the <i>uniform contraction principle</i>. 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 <span>\\\\({{\\\\textrm{C}}([0,T];{\\\\textrm{L}}^p({\\\\mathbb {T}}^2))}\\\\)</span> topology, for <span>\\\\(p>2\\\\)</span>, taking into account the uniformity of the initial conditions contained in bounded subsets of <span>\\\\({{\\\\textrm{L}}^p({\\\\mathbb {T}}^2)}\\\\)</span>. Finally, in <span>\\\\({{\\\\textrm{C}}([0,T]\\\\times {\\\\mathbb {T}}^2)}\\\\)</span> topology, the uniformity of initial conditions lying in bounded subsets of <span>\\\\({{\\\\textrm{C}}({\\\\mathbb {T}}^2)}\\\\)</span> is considered.</p></div>\",\"PeriodicalId\":55566,\"journal\":{\"name\":\"Applied Mathematics and Optimization\",\"volume\":\"90 1\",\"pages\":\"\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2024-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Mathematics and Optimization\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s00245-024-10150-5\",\"RegionNum\":2,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATHEMATICS, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Mathematics and Optimization","FirstCategoryId":"100","ListUrlMain":"https://link.springer.com/article/10.1007/s00245-024-10150-5","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
Uniform Large Deviation Principle for the Solutions of Two-Dimensional Stochastic Navier–Stokes Equations in Vorticity Form
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.
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.