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E-raamat: Extrinsic Geometric Flows

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Extrinsic geometric flows are characterized by a submanifold evolving in an ambient space with velocity determined by its extrinsic curvature. The goal of this book is to give an extensive introduction to a few of the most prominent extrinsic flows, namely, the curve shortening flow, the mean curvature flow, the Gauss curvature flow, the inverse-mean curvature flow, and fully nonlinear flows of mean curvature and inverse-mean curvature type. The authors highlight techniques and behaviors that frequently arise in the study of these (and other) flows. To illustrate the broad applicability of the techniques developed, they also consider general classes of fully nonlinear curvature flows.

The book is written at the level of a graduate student who has had a basic course in differential geometry and has some familiarity with partial differential equations. It is intended also to be useful as a reference for specialists. In general, the authors provide detailed proofs, although for some more specialized results they may only present the main ideas; in such cases, they provide references for complete proofs. A brief survey of additional topics, with extensive references, can be found in the notes and commentary at the end of each chapter.
Preface xiii
A Guide for the Reader xv
The heat equation (Chapter 1) xv
Curve shortening flow (Chapters 2--4) xv
Mean curvature flow (Chapters 5--14) xvi
Gaub curvature flows (Chapters 15--17) xix
Fully nonlinear curvature flows (Chapters 18--20) xx
Acknowledgments xx
Suggested Course Outlines xxiii
Notation and Symbols xxv
Chapter 1 The Heat Equation
1(36)
§ 1.1 Introduction
1(2)
§ 1.2 Gradient flow
3(1)
§ 1.3 Invariance properties
3(5)
§ 1.4 The maximum principle
8(4)
§ 1.5 Well-posedness
12(2)
§ 1.6 Asymptotic behavior
14(3)
§ 1.7 The Bernstein method
17(1)
§ 1.8 The Harnack inequality
17(2)
§ 1.9 Further monotonicity formulae
19(2)
§ 1.10 Sharp gradient estimates
21(8)
§ 1.11 Notes and commentary
29(4)
§ 1.12 Exercises
33(4)
Chapter 2 Introduction To Curve Shortening
37(26)
§ 2.1 Basic geometric theory of planar curves
38(4)
§ 2.2 Curve shortening flow
42(3)
§ 2.3 Graphs of functions
45(3)
§ 2.4 The support function
48(2)
§ 2.5 Short-time existence
50(1)
§ 2.6 Smoothing
51(3)
§ 2.7 Global existence
54(5)
§ 2.8 Notes and commentary
59(1)
§ 2.9 Exercises
59(4)
Chapter 3 The Gage-Hamilton-Grayson Theorem
63(32)
§ 3.1 The avoidance principle
64(2)
§ 3.2 Preserving embeddedness
66(2)
§ 3.3 Huisken's distance comparison estimate
68(6)
§ 3.4 A curvature bound by distance comparison
74(8)
§ 3.5 Grayson's theorem
82(6)
§ 3.6 Singularities of immersed solutions
88(2)
§ 3.7 Notes and commentary
90(2)
§ 3.8 Exercises
92(3)
Chapter 4 Self-Similar And Ancient Solutions
95(30)
§ 4.1 Invariance properties
95(1)
§ 4.2 Self-similar solutions
96(6)
§ 4.3 Monotonicity formulae
102(8)
§ 4.4 Ancient solutions
110(6)
§ 4.5 Classification of convex ancient solutions on S1
116(6)
§ 4.6 Notes and commentary
122(1)
§ 4.7 Exercises
123(2)
Chapter 5 Hypersurfaces In Euclidean Space
125(48)
§ 5.1 Parametrized hypersurfaces
125(18)
§ 5.2 Alternative representations of hypersurfaces
143(9)
§ 5.3 Dynamical properties
152(12)
§ 5.4 Curvature flows
164(5)
§ 5.5 Notes and commentary
169(1)
§ 5.6 Exercises
169(4)
Chapter 6 Introduction To Mean Curvature Flow
173(50)
§ 6.1 The mean curvature flow
173(3)
§ 6.2 Invariance properties and self-similar solutions
176(3)
§ 6.3 Evolution equations
179(5)
§ 6.4 Short-time existence
184(5)
§ 6.5 The maximum principle
189(3)
§ 6.6 The avoidance principle
192(4)
§ 6.7 Preserving embeddedness
196(1)
§ 6.8 Long-time existence
197(9)
§ 6.9 Weak solutions
206(9)
§ 6.10 Notes and commentary
215(4)
§ 6.11 Exercises
219(4)
Chapter 7 Mean Curvature Flow Of Entire Graphs
223(20)
§ 7.1 Introduction
223(1)
§ 7.2 Preliminary calculations
224(3)
§ 7.3 The Dirichlet problem
227(1)
§ 7.4 A priori height and gradient estimates
228(4)
§ 7.5 Local a priori estimates for the curvature
232(6)
§ 7.6 Proof of Theorem 7.1
238(1)
§ 7.7 Convergence to self-similarly expanding solutions
239(1)
§ 7.8 Self-similarly shrinking entire graphs
240(1)
§ 7.9 Notes and commentary
240(1)
§ 7.10 Exercises
241(2)
Chapter 8 Huisken's Theorem
243(38)
§ 8.1 Pinching is preserved
244(2)
§ 8.2 Pinching improves: The roundness estimate
246(10)
§ 8.3 A gradient estimate for the curvature
256(3)
§ 8.4 Huisken's theorem
259(7)
§ 8.5 Regularity of the arrival time
266(1)
§ 8.6 Huisken's theorem via width pinching
267(7)
§ 8.7 Notes and commentary
274(4)
§ 8.8 Exercises
278(3)
Chapter 9 Mean Convex Mean Curvature Flow
281(30)
§ 9.1 Singularity formation
281(3)
§ 9.2 Preserving pinching conditions
284(10)
§ 9.3 Pinching improves: Convexity and cylindrical estimates
294(7)
§ 9.4 A natural class of initial data
301(2)
§ 9.5 A gradient estimate for the curvature
303(5)
§ 9.6 Notes and commentary
308(1)
§ 9.7 Exercises
309(2)
Chapter 10 Monotonicity Formulae
311(34)
§ 10.1 Huisken's monotonicity formula
311(8)
§ 10.2 Hamilton's Harnack estimate
319(19)
§ 10.3 Notes and commentary
338(4)
§ 10.4 Exercises
342(3)
Chapter 11 Singularity Analysis
345(50)
§ 11.1 Local uniform convergence of mean curvature flows
345(9)
§ 11.2 Neck detection
354(9)
§ 11.3 The Brakke--White regularity theorem
363(3)
§ 11.4 Huisken's theorem revisited
366(5)
§ 11.5 The structure of singularities
371(18)
§ 11.6 Notes and commentary
389(5)
§ 11.7 Exercises
394(1)
Chapter 12 Noncollapsing
395(30)
§ 12.1 The inscribed and exscribed curvatures
395(7)
§ 12.2 Differential inequalities for the inscribed and exscribed curvatures
402(10)
§ 12.3 The Gage--Hamilton and Huisken theorems via noncollapsing
412(3)
§ 12.4 The Haslhofer--Kleiner curvature estimate
415(6)
§ 12.5 Notes and commentary
421(1)
§ 12.6 Exercises
422(3)
Chapter 13 Self-Similar Solutions
425(78)
§ 13.1 Shrinkers --- an introduction
425(1)
§ 13.2 The Gaubian area functional
426(5)
§ 13.3 Mean convex shrinkers
431(12)
§ 13.4 Compact embedded self-shrinking surfaces
443(9)
§ 13.5 Translators --- an introduction
452(2)
§ 13.6 The Dirichlet problem for graphical translators
454(1)
§ 13.7 Cylindrical translators
455(1)
§ 13.8 Rotational translators
456(6)
§ 13.9 The convexity estimates of Spruck, Sun, and Xiao
462(6)
§ 13.10 Asymptotics
468(1)
§ 13.11 X.-J. Wang's dichotomy
469(1)
§ 13.12 Rigidity of the bowl soliton
470(7)
§ 13.13 Flying wings
477(13)
§ 13.14 Bowloids
490(2)
§ 13.15 Notes and commentary
492(7)
§ 13.16 Exercises
499(4)
Chapter 14 Ancient Solutions
503(40)
§ 14.1 Rigidity of the shrinking sphere
504(5)
§ 14.2 A convexity estimate
509(2)
§ 14.3 A gradient estimate for the curvature
511(2)
§ 14.4 Asymptotics
513(3)
§ 14.5 X.-J. Wang's dichotomy
516(9)
§ 14.6 Ancient solutions to curve shortening flow revisited
525(6)
§ 14.7 Ancient ovaloids
531(2)
§ 14.8 Ancient pancakes
533(3)
§ 14.9 Notes and commentary
536(4)
§ 14.10 Exercises
540(3)
Chapter 15 Gaub Curvature Flows
543(38)
§ 15.1 Invariance properties and self-similar solutions
545(1)
§ 15.2 Basic evolution equations
546(2)
§ 15.3 Chou's long-time existence theorem
548(10)
§ 15.4 Differential Harnack estimates
558(2)
§ 15.5 Firey's conjecture
560(10)
§ 15.6 Variational structure and entropy formulae
570(8)
§ 15.7 Notes and commentary
578(1)
§ 15.8 Exercises
578(3)
Chapter 16 The Affine Normal Flow
581(26)
§ 16.1 Affine invariance
582(4)
§ 16.2 Affine-renormalized solutions
586(4)
§ 16.3 Convergence and the limit flow
590(1)
§ 16.4 Self-similarly shrinking solutions are ellipsoids
590(3)
§ 16.5 Convergence without affine corrections
593(8)
§ 16.6 Notes and commentary
601(1)
§ 16.7 Exercises
602(5)
Chapter 17 Flows By Superaffine Powers Of The Gaub Curvature
607(32)
§ 17.1 Bounds on diameter, speed, and inradius
607(6)
§ 17.2 Convergence to a shrinking self-similar solution
613(5)
§ 17.3 Shrinking self-similar solutions are round
618(15)
§ 17.4 Notes and commentary
633(2)
§ 17.5 Exercises
635(4)
Chapter 18 Fully Nonlinear Curvature Flows
639(48)
§ 18.1 Introduction
639(2)
§ 18.2 Symmetric functions and their differentiability properties
641(9)
§ 18.3 Examples
650(5)
§ 18.4 Short-time existence
655(3)
§ 18.5 The avoidance principle
658(2)
§ 18.6 Differential Harnack estimates
660(4)
§ 18.7 Entropy estimates
664(6)
§ 18.8 Alexandrov reflection
670(12)
§ 18.9 Notes and commentary
682(1)
§ 18.10 Exercises
683(4)
Chapter 19 Flows Of Mean Curvature Type
687(24)
§ 19.1 Convex hypersurfaces contract to round points
687(11)
§ 19.2 Evolving nonconvex hypersurfaces
698(10)
§ 19.3 Notes and commentary
708(1)
§ 19.4 Exercises
709(2)
Chapter 20 Flows Of Inverse-Mean Curvature Type
711(16)
§ 20.1 Convex hypersurfaces expand to round infinity
711(12)
§ 20.2 Notes and commentary
723(1)
§ 20.3 Exercises
724(3)
Bibliography 727(26)
Index 753
Ben Andrews, The Australian National University, Canberra, Australia.

Bennett Chow, University of California, San Diego, La Jolla, CA.

Christine Guenther, Pacific University, Forrest Grove, OR.

Mat Langford, University of Tennessee, Knoxville, TN.