{"title":"随机艾伦-卡恩方程的弱误差分析","authors":"Dominic Breit, Andreas Prohl","doi":"10.1007/s40072-024-00326-z","DOIUrl":null,"url":null,"abstract":"<p>We prove strong rate <i>resp.</i> weak rate <span>\\({{\\mathcal {O}}}(\\tau )\\)</span> for a structure preserving temporal discretization (with <span>\\(\\tau \\)</span> the step size) of the stochastic Allen–Cahn equation with additive <i>resp.</i> multiplicative colored noise in <span>\\(d=1,2,3\\)</span> dimensions. Direct variational arguments exploit the one-sided Lipschitz property of the cubic nonlinearity in the first setting to settle first order strong rate. It is the same property which allows for uniform bounds for the derivatives of the solution of the related Kolmogorov equation, and then leads to weak rate <span>\\({{\\mathcal {O}}}(\\tau )\\)</span> in the presence of multiplicative noise. Hence, we obtain twice the rate of convergence known for the strong error in the presence of multiplicative noise.</p>","PeriodicalId":48569,"journal":{"name":"Stochastics and Partial Differential Equations-Analysis and Computations","volume":null,"pages":null},"PeriodicalIF":1.4000,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Weak error analysis for the stochastic Allen–Cahn equation\",\"authors\":\"Dominic Breit, Andreas Prohl\",\"doi\":\"10.1007/s40072-024-00326-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>We prove strong rate <i>resp.</i> weak rate <span>\\\\({{\\\\mathcal {O}}}(\\\\tau )\\\\)</span> for a structure preserving temporal discretization (with <span>\\\\(\\\\tau \\\\)</span> the step size) of the stochastic Allen–Cahn equation with additive <i>resp.</i> multiplicative colored noise in <span>\\\\(d=1,2,3\\\\)</span> dimensions. Direct variational arguments exploit the one-sided Lipschitz property of the cubic nonlinearity in the first setting to settle first order strong rate. It is the same property which allows for uniform bounds for the derivatives of the solution of the related Kolmogorov equation, and then leads to weak rate <span>\\\\({{\\\\mathcal {O}}}(\\\\tau )\\\\)</span> in the presence of multiplicative noise. Hence, we obtain twice the rate of convergence known for the strong error in the presence of multiplicative noise.</p>\",\"PeriodicalId\":48569,\"journal\":{\"name\":\"Stochastics and Partial Differential Equations-Analysis and Computations\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2024-02-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Stochastics and Partial Differential Equations-Analysis and Computations\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1007/s40072-024-00326-z\",\"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":"Stochastics and Partial Differential Equations-Analysis and Computations","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s40072-024-00326-z","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
Weak error analysis for the stochastic Allen–Cahn equation
We prove strong rate resp. weak rate \({{\mathcal {O}}}(\tau )\) for a structure preserving temporal discretization (with \(\tau \) the step size) of the stochastic Allen–Cahn equation with additive resp. multiplicative colored noise in \(d=1,2,3\) dimensions. Direct variational arguments exploit the one-sided Lipschitz property of the cubic nonlinearity in the first setting to settle first order strong rate. It is the same property which allows for uniform bounds for the derivatives of the solution of the related Kolmogorov equation, and then leads to weak rate \({{\mathcal {O}}}(\tau )\) in the presence of multiplicative noise. Hence, we obtain twice the rate of convergence known for the strong error in the presence of multiplicative noise.
期刊介绍:
Stochastics and Partial Differential Equations: Analysis and Computations publishes the highest quality articles presenting significantly new and important developments in the SPDE theory and applications. SPDE is an active interdisciplinary area at the crossroads of stochastic anaylsis, partial differential equations and scientific computing. Statistical physics, fluid dynamics, financial modeling, nonlinear filtering, super-processes, continuum physics and, recently, uncertainty quantification are important contributors to and major users of the theory and practice of SPDEs. The journal is promoting synergetic activities between the SPDE theory, applications, and related large scale computations. The journal also welcomes high quality articles in fields strongly connected to SPDE such as stochastic differential equations in infinite-dimensional state spaces or probabilistic approaches to solving deterministic PDEs.