This lecture focuses on the mean curvature flow within the framework of geometric measure theory, an object called Brakke flow, and discusses its definitions and recent research results.
A time-parameterized family of surfaces is a mean curvature flow if the velocity of the surface is given by the mean curvature of the surface itself at each point and time. The mean curvature flow may be considered as a gradient flow of surface measure, and its static (or time-independent) object is precisely a minimal surface. In general, the mean curvature flow develops singularities, and it is natural to consider the flow within the framework which allows singularities. The convenient notion for that purpose is a varifold. In this lecture, starting from the definition of Brakke flow, the up-to-date research results will be explained.
Understanding on the notions of mean curvature flow and Brakke flow within the framework of geometric measure theory is the goal.
mean curvature flow, geometric measure theory
✔ Specialist skills | Intercultural skills | Communication skills | Critical thinking skills | Practical and/or problem-solving skills |
Standard lecture course.
Course schedule | Required learning | |
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Class 1 | Definitions of mean curvature flow and Brakke flow | Details will be provided during each class session. |
Class 2 | Some basic notions from geometric measure theory | |
Class 3 | Huisken's monotonicity formula | |
Class 4 | Compactness theorem of Brakke fllow | |
Class 5 | Tangent flow of Brakke flow | |
Class 6 | Overview on existence and regularity theorems of Brakke flow | |
Class 7 | Outline of proof of Kim-Tonegawa's existence theorem |
To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.
Brakke's mean curvature flow: an introduction, Springerbrief, Yoshihiro Tonegawa
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Assignments. Details will be announced during the session.
Familiarity with general measure theory is desirable but not necessary.
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