Special Lecture on Mathematics 3

Numbering Code U-SCI00 17103 LJ55 Year/Term 2021 ・ Intensive, year-round
Number of Credits 1 Course Type
Target Year 1st year students or above Target Student
Language English Day/Period Intensive
Instructor name Nobert Pozar (Part-time Lecturer)
Karel SVADLENKA (Graduate School of Science Associate Professor)
Outline and Purpose of the Course ☆応用数学Ⅱ(Applied MathematicsⅡ)☆
This course will cover the mean curvature flow from the point of view of the level set method and viscosity solutions. In particular, we will study the anisotropic and crystalline mean curvature flows that appear in material science as models of the evolution of crystals, in image processing and other fields. We will take the point of view of the level set method that allows us to find the solution of the flow as a solution of a nonlinear parabolic partial differential equation. Since the most natural notion of generalized solutions are the viscosity solutions, we will spend some time on their introduction and cover some basic properties like the comparison principle and stability.
Course Goals You will become familiar with the mean curvature flow and its anisotropic variants, understand the basic level set method for tracking geometric flows and understand the fundamentals of the theory of viscosity solutions. You will be able to perform basic computations with viscosity solutions of geometric flows.
Schedule and Contents 1. Introduction, examples of curvature flows and applications, description of surface evolution (1回)
2. Level set method, viscosity solutions for the mean curvature flow (1回)
3. Anisotropic mean curvature flow, examples of solutions (2回)
4. Total variation flow and the crystalline mean curvature flow (1回)
Course Requirements Basic knowledge of linear algebra and calculus of functions of multiple variables is expected. Some knowledge of basic partial differential equations is recommended.
Study outside of Class (preparation and review) Review of basic notions in the calculus of functions of multiple variables is recommended: partial derivatives, gradient, chain rule, implicit function theorem.
References, etc. Reference texts will be discussed during the lectures.
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