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Mean curvature flow in higher co-dimensions

更高维数中的平均曲率流

基本信息

批准号：
274149541
负责人：
Professor Dr. Knut Smoczyk
金额：
--
依托单位：
Institut für Differentialgeometrie
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2015
资助国家：
德国
起止时间：
2014-12-31 至 2019-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/274149541?language=en
关键词：
Mean curvature flow higher co

项目摘要

In this research project we intend to investigate analytic properties of the mean curvature flow (MCF) in higher co-dimension of submanifolds of a Riemannian or Kählerian manifold and its implications on the topology and geometry of submanifolds. Specifically, one of our main objectives is to use MCF to understand the topology and geometry of smooth maps between Riemannian or Kählerian manifolds. This plan can be achieved by evolving the corresponding graphical submanifold in the product space by the mean curvature flow. A prime motivation for the study of the graphical mean curvature flow is a question posed by Gromov of how the Jacobians of a map between given Riemannian manifolds affects the homotopy type of the map. A second motivation is a general question of Yau of how to deform a symplectomorphism into a homolorphic map. We would like to mention that these problems have attracted the attention of many mathematicians during the last decade. Another aim is to understand the singularities of the MCF. In particular, we are interested to study in detail translating solitons of the mean curvature flow. One of the major problems of singular analysis of MCF is the classification of such objects. Our approach to attack this problem is to combine the analysis of elliptic systems of PDEs with techniques arising from minimal submanifold theory.

在本研究项目中，我们打算研究黎曼流形或Kählerian流形的高协维子流形的平均曲率流（MCF）的解析性质及其对子流形拓扑和几何的意义。具体来说，我们的主要目标之一是使用MCF来理解黎曼流形或Kählerian流形之间的光滑映射的拓扑和几何。这个方案可以通过平均曲率流在积空间中演化相应的图形子流形来实现。研究图形平均曲率流的一个主要动机是Gromov提出的一个问题，即给定黎曼流形之间映射的雅可比矩阵如何影响映射的同伦类型。第二个动机是一个关于如何将一个辛同态映射变形成一个同态映射的一般问题。我们想提一下，这些问题在过去十年中引起了许多数学家的注意。另一个目标是理解MCF的奇异性。我们特别有兴趣详细研究平均曲率流的平移孤子。MCF奇异分析的主要问题之一是这些对象的分类。我们解决这个问题的方法是将偏微分方程椭圆系统的分析与最小子流形理论的技术相结合。