{"title":"具有乘性噪声和非线性阻尼的随机离散波动方程不变测度的大偏差原理","authors":"Yongkang Zhang, Xiaojun Li","doi":"10.1016/j.bulsci.2025.103670","DOIUrl":null,"url":null,"abstract":"<div><div>In this paper, we study the large deviation principle of invariant measures of a class of discrete wave equations with multiplicative noise and nonlinear damping, defined on a <em>N</em>-dimensional integer set. We first establish the existence of invariant measures for the stochastic system and analyze the limiting behavior of these measures as the noise intensity approaches zero. Next, we prove the Freidlin-Wentzell uniform large deviations and the Dembo-Zeitouni uniform large deviations of the solutions of the stochastic system. Lastly, we derive the large deviations of invariant measures by combining exponential probability estimates and arguments based on weighted spaces.</div></div>","PeriodicalId":55313,"journal":{"name":"Bulletin des Sciences Mathematiques","volume":"204 ","pages":"Article 103670"},"PeriodicalIF":0.9000,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Large deviation principles of invariant measures of stochastic discrete wave equations with multiplicative noise and nonlinear damping\",\"authors\":\"Yongkang Zhang, Xiaojun Li\",\"doi\":\"10.1016/j.bulsci.2025.103670\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In this paper, we study the large deviation principle of invariant measures of a class of discrete wave equations with multiplicative noise and nonlinear damping, defined on a <em>N</em>-dimensional integer set. We first establish the existence of invariant measures for the stochastic system and analyze the limiting behavior of these measures as the noise intensity approaches zero. Next, we prove the Freidlin-Wentzell uniform large deviations and the Dembo-Zeitouni uniform large deviations of the solutions of the stochastic system. Lastly, we derive the large deviations of invariant measures by combining exponential probability estimates and arguments based on weighted spaces.</div></div>\",\"PeriodicalId\":55313,\"journal\":{\"name\":\"Bulletin des Sciences Mathematiques\",\"volume\":\"204 \",\"pages\":\"Article 103670\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2025-05-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Bulletin des Sciences Mathematiques\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S000744972500096X\",\"RegionNum\":3,\"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":"Bulletin des Sciences Mathematiques","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S000744972500096X","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
Large deviation principles of invariant measures of stochastic discrete wave equations with multiplicative noise and nonlinear damping
In this paper, we study the large deviation principle of invariant measures of a class of discrete wave equations with multiplicative noise and nonlinear damping, defined on a N-dimensional integer set. We first establish the existence of invariant measures for the stochastic system and analyze the limiting behavior of these measures as the noise intensity approaches zero. Next, we prove the Freidlin-Wentzell uniform large deviations and the Dembo-Zeitouni uniform large deviations of the solutions of the stochastic system. Lastly, we derive the large deviations of invariant measures by combining exponential probability estimates and arguments based on weighted spaces.