非线性SPDEs和最大规律性:一个扩展的调查
Antonio Agresti1,2, Mark Veraar3
1Delft Institute of Applied Mathematics, Delft University of Technology, P.O. Box , 5031 2600 GA Delft, The Netherlands.
概括
这项调查探讨了使用最大规律性的随机演化方程的正确性. 它介绍了非线性随机局部微分方程 (SPDEs) 中的急剧膨胀标准和正则化.
科学领域:
- 随机分析
- 部分微分方程
- 数学物理
背景情况:
- 随机演化方程的正确位置对于复杂系统的建模至关重要.
- 最大的规律性技术为分析这些方程提供了强大的工具.
- 现有的理论往往没有明确的扩大和即时规范化标准.
研究的目的:
- 介绍近期在随机演化方程的定位理论上的进展.
- 引入和应用基于关键空间的新框架.
- 改进,统一和扩展以前的非线性随机部分微分方程 (SPDEs) 的结果.
主要方法:
- 在随机演变方程中使用最大规律技术.
- 开发关键空间的抽象概念,与非线性SPDEs的缩放不变空间相吻合.
- 将抽象框架应用于特定的SPDEs,包括Navier-Stokes和反应扩散系统.
主要成果:
- 为非线性SPDEs建立了明确的扩充标准和即时规范化结果.
- 提供对现有理论的统一和精细分析.
- 为纳维埃-斯托克斯方程推导了新的塞林式膨胀标准.
结论:
- 关键空间框架为广泛的SPDEs提供了一个统一的解决方案.
- 这些结果有助于我们更好地理解膨胀现象和规范性质.
- 在抽象的随机演变方程和具体的SPDEs中确定了未解决的问题.
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