eBook - PDF
Mean Curvature Flow
Proceedings of the John H. Barrett Memorial Lectures held at the University of Tennessee, Knoxville, May 29–June 1, 2018
- 149 pages
- English
- PDF
- Available on iOS & Android
eBook - PDF
Mean Curvature Flow
Proceedings of the John H. Barrett Memorial Lectures held at the University of Tennessee, Knoxville, May 29–June 1, 2018
About this book
With contributions by leading experts in geometric analysis, this volume is documenting the material presented in the John H. Barrett Memorial Lectures held at the University of Tennessee, Knoxville, on May 29 - June 1, 2018. The central topic of the 2018 lectures was mean curvature flow, and the material in this volume covers all recent developments in this vibrant area that combines partial differential equations with differential geometry.
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Yes, you can access Mean Curvature Flow by Theodora Bourni,Mat Langford in PDF and/or ePUB format, as well as other popular books in Matematica & Geometria differenziale. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Foreword
- Contents
- Introducing Mean Curvature Flow
- Self-similar solutions of mean curvature flow
- Ancient solutions in geometric flows
- An extension to the Morse energy gradient flow
- Regularity of non-compact inverse mean curvature flow
- Area preserving curve shortening flow
- Second Order Renormalization Group Flow
- Analysis of Velà zquez’s solution to the mean curvature flow with a type II singularity
- Some recent applications of mean curvature flow with surgery
- Identifying shrinking solitons by their asymptotic geometries
- Geometric singularities under the Gigli-Mantegazza flow
- Pinched ancient solutions to high codimension mean curvature flow
- On the unknoteddness of self shrinkers in R<sup>3</sup>
- Gluing constructions for self-translating and self-shrinking surfaces under mean curvature flow
- The level set flow of a hypersurface in R4 of low entropy does not disconnect
- Application of Mean Curvature Flow for surface parametrizations