{"title":"On the Relationship Between Viscosity and Distribution Solutions for Nonlinear Neumann Type PDEs: The Probabilistic Approach","authors":"Jiagang Ren, Shoutian Wang, Jing Wu","doi":"10.1007/s00245-025-10222-0","DOIUrl":null,"url":null,"abstract":"<div><p>Based on probabilistic methods, we discuss the relationship between viscosity and distribution solutions for semi-linear partial differential equations (PDEs) with Neumann boundary conditions. We also extend the research to a type of nonlinear PDEs, which is completed through the well-posedness and continuity results of solutions to the corresponding forward-backward SDE.</p></div>","PeriodicalId":55566,"journal":{"name":"Applied Mathematics and Optimization","volume":"91 1","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2025-01-18","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/s00245-025-10222-0","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0
Abstract
Based on probabilistic methods, we discuss the relationship between viscosity and distribution solutions for semi-linear partial differential equations (PDEs) with Neumann boundary conditions. We also extend the research to a type of nonlinear PDEs, which is completed through the well-posedness and continuity results of solutions to the corresponding forward-backward SDE.
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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