The Double Bubble Problem in Spherical and Hyperbolic Space
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Intrinsic Volumes and Polar Sets in Spherical Space
1 INTRINSIC VOLUMES AND POLAR SETS IN SPHERICAL SPACE FUCHANG GAO, DANIEL HUG, ROLF SCHNEIDER Abstract. For a convex body of given volume in spherical space, the total invariant measure of hitting great subspheres becomes minimal, equivalently the volume of the polar body becomes maximal, if and only if the body is a spherical cap. This result can be considered as a spherical counterpart of two Euclidean inequalities, the Urysohn inequality connecting mean width and volume, and the Blaschke-Santal´oinequality for the volumes of polar convex bodies. Two proofs are given; the first one can be adapted to hyperbolic space. MSC 2000: 52A40 (primary); 52A55, 52A22 (secondary) Keywords: spherical convexity, Urysohn inequality, Blaschke- Santal´oinequality, intrinsic volume, quermassintegral, polar convex bodies, two-point symmetrization In the classical geometry of convex bodies in Euclidean space, the intrinsic volumes (or quermassintegrals) play a central role. These functionals have counterparts in spherical and hyperbolic geometry, and it is a challenge for a geometer to find analogues in these spaces for the known results about Euclidean intrinsic volumes. In the present paper, we prove one such result, an inequality of isoperimetric type in spherical (or hyperbolic) space, which can be considered as a counterpart to the Urysohn inequality and is, in the spherical case, also related to the Blaschke-Santal´oinequality. Before stating the result (at the beginning of Section 2), we want to recall and collect the basic facts about intrinsic volumes in Euclidean space, describe their noneuclidean counterparts, and state those open problems about the latter which we consider to be of particular interest. -
Universität Regensburg Mathematik
UniversitÄatRegensburg Mathematik Parametric Approximation of Surface Clusters driven by Isotropic and Anisotropic Surface Energies J.W. Barrett, H. Garcke, R. NÄurnberg Preprint Nr. 04/2009 Parametric Approximation of Surface Clusters driven by Isotropic and Anisotropic Surface Energies John W. Barrett† Harald Garcke‡ Robert N¨urnberg† Abstract We present a variational formulation for the evolution of surface clusters in R3 by mean curvature flow, surface diffusion and their anisotropic variants. We intro- duce the triple junction line conditions that are induced by the considered gradient flows, and present weak formulations of these flows. In addition, we consider the case where a subset of the boundaries of these clusters are constrained to lie on an external boundary. These formulations lead to unconditionally stable, fully dis- crete, parametric finite element approximations. The resulting schemes have very good properties with respect to the distribution of mesh points and, if applicable, volume conservation. This is demonstrated by several numerical experiments, in- cluding isotropic double, triple and quadruple bubbles, as well as clusters evolving under anisotropic mean curvature flow and anisotropic surface diffusion, including for regularized crystalline surface energy densities. Key words. surface clusters, mean curvature flow, surface diffusion, soap bubbles, triple junction lines, parametric finite elements, anisotropy, tangential movement AMS subject classifications. 65M60, 65M12, 35K55, 53C44, 74E10, 74E15 1 Introduction Equilibrium soap bubble clusters are stationary solutions of the variational problem in which one seeks a least area way to enclose and separate a number of regions with pre- scribed volumes. The relevant energy in this case is given as the sum of the total surface area. -
17 Measure Concentration for the Sphere
17 Measure Concentration for the Sphere In today’s lecture, we will prove the measure concentration theorem for the sphere. Recall that this was one of the vital steps in the analysis of the Arora-Rao-Vazirani approximation algorithm for sparsest cut. Most of the material in today’s lecture is adapted from Matousek’s book [Mat02, chapter 14] and Keith Ball’s lecture notes on convex geometry [Bal97]. n n−1 Notation: We will use the notation Bn to denote the ball of unit radius in R and S n to denote the sphere of unit radius in R . Let µ denote the normalized measure on the unit sphere (i.e., for any measurable set S ⊆ Sn−1, µ(A) denotes the ratio of the surface area of µ to the entire surface area of the sphere Sn−1). Recall that the n-dimensional volume of a ball n n n of radius r in R is given by the formula Vol(Bn) · r = vn · r where πn/2 vn = n Γ 2 + 1 Z ∞ where Γ(x) = tx−1e−tdt 0 n−1 The surface area of the unit sphere S is nvn. Theorem 17.1 (Measure Concentration for the Sphere Sn−1) Let A ⊆ Sn−1 be a mea- n−1 surable subset of the unit sphere S such that µ(A) = 1/2. Let Aδ denote the δ-neighborhood n−1 n−1 of A in S . i.e., Aδ = {x ∈ S |∃z ∈ A, ||x − z||2 ≤ δ}. Then, −nδ2/2 µ(Aδ) ≥ 1 − 2e . Thus, the above theorem states that if A is any set of measure 0.5, taking a step of even √ O (1/ n) around A covers almost 99% of the entire sphere. -
Spherical Cap Packing Asymptotics and Rank-Extreme Detection Kai Zhang
IEEE TRANSACTIONS ON INFORMATION THEORY 1 Spherical Cap Packing Asymptotics and Rank-Extreme Detection Kai Zhang Abstract—We study the spherical cap packing problem with a observations can be written as probabilistic approach. Such probabilistic considerations result Pn ¯ ¯ in an asymptotic sharp universal uniform bound on the maximal i=1(Xi − X)(Yi − Y ) Cb(X; Y ) = q q inner product between any set of unit vectors and a stochastically Pn (X − X¯)2 Pn (Y − Y¯ )2 independent uniformly distributed unit vector. When the set of i=1 i i=1 i unit vectors are themselves independently uniformly distributed, (I.1) we further develop the extreme value distribution limit of where Xi’s and Yi’s are the n independent and identically the maximal inner product, which characterizes its uncertainty distributed (i.i.d.) observations of X and Y respectively, around the bound. and X¯ and Y¯ are the sample means of X and Y As applications of the above asymptotic results, we derive (1) respectively. The sample correlation coefficient possesses an asymptotic sharp universal uniform bound on the maximal spurious correlation, as well as its uniform convergence in important statistical properties and was carefully studied distribution when the explanatory variables are independently in the classical case when the number of variables is Gaussian distributed; and (2) an asymptotic sharp universal small compared to the number of observations. How- bound on the maximum norm of a low-rank elliptically dis- ever, the situation has dramatically changed in the new tributed vector, as well as related limiting distributions. With high-dimensional paradigm [1, 2] as the large number these results, we develop a fast detection method for a low-rank structure in high-dimensional Gaussian data without using the of variables in the data leads to the failure of many spectrum information. -
Cannonballs and Honeycombs, Volume 47, Number 4
fea-hales.qxp 2/11/00 11:35 AM Page 440 Cannonballs and Honeycombs Thomas C. Hales hen Hilbert intro- market. “We need you down here right duced his famous list of away. We can stack the oranges, but 23 problems, he said we’re having trouble with the arti- a test of the perfec- chokes.” Wtion of a mathe- To me as a discrete geometer Figure 1. An matical problem is whether it there is a serious question be- optimal can be explained to the first hind the flippancy. Why is arrangement person in the street. Even the gulf so large between of equal balls after a full century, intuition and proof? is the face- Hilbert’s problems have Geometry taunts and de- centered never been thoroughly fies us. For example, what cubic tested. Who has ever chatted with about stacking tin cans? Can packing. a telemarketer about the Riemann hy- anyone doubt that parallel rows pothesis or discussed general reciprocity of upright cans give the best arrange- laws with the family physician? ment? Could some disordered heap of cans Last year a journalist from Plymouth, New waste less space? We say certainly not, but the Zealand, decided to put Hilbert’s 18th problem to proof escapes us. What is the shape of the cluster the test and took it to the street. Part of that prob- of three, four, or five soap bubbles of equal vol- lem can be phrased: Is there a better stacking of ume that minimizes total surface area? We blow oranges than the pyramids found at the fruit stand? bubbles and soon discover the answer but cannot In pyramids the oranges fill just over 74% of space prove it. -
Introduction to Nonlinear Geometric Pdes
Introduction to nonlinear geometric PDEs Thomas Marquardt January 16, 2014 ETH Zurich Department of Mathematics Contents I. Introduction and review of useful material 1 1. Introduction 3 1.1. Scope of the lecture . .3 1.2. Accompanying books . .4 1.3. A historic survey . .5 2. Review: Differential geometry 7 2.1. Hypersurfaces in Rn ..............................7 2.2. Isometric immersions . 11 2.3. First variation of area . 12 3. Review: Linear PDEs of second order 15 3.1. Elliptic PDEs in H¨older spaces . 15 3.2. Elliptic PDEs in Sobolev spaces . 18 3.3. Parabolic PDEs in H¨older spaces . 20 II. Nonlinear elliptic PDEs of second order 25 4. General theory for quasilinear problems 27 4.1. Fixed point theorems: From Brouwer to Leray-Schauder . 27 4.2. Reduction to a priori estimates in the C1,β-norm . 29 4.3. Reduction to a priori estimates in the C1-norm . 30 5. The prescribed mean curvature problem 33 5.1. C0-estimate . 33 5.2. Interior gradient estimate . 37 5.3. Boundary gradient estimate . 40 5.4. Existence and uniqueness theorem . 45 6. General theory for fully nonlinear problems 49 6.1. Fully nonlinear Dirichlet problems . 50 6.2. Fully nonlinear oblique derivative problems . 52 7. The capillary surface problem 57 7.1. C0-estimate . 58 7.2. Global gradient estimate . 60 7.3. Existence and uniqueness theorem . 66 III. Geometric evolution equations 67 8. Classical solutions of MCF and IMCF 69 8.1. Short-time existence . 69 8.2. Evolving graphs under mean curvature flow . 74 8.3. -
1875–2012 Dr. Jan E. Wynn
HISTORY OF THE DEPARTMENT OF MATHEMATICS BRIGHAM YOUNG UNIVERSITY 1875–2012 DR. LYNN E. GARNER DR. GURCHARAN S. GILL DR. JAN E. WYNN Copyright © 2013, Department of Mathematics, Brigham Young University All rights reserved 2 Foreword In August 2012, the leadership of the Department of Mathematics of Brigham Young University requested the authors to compose a history of the department. The history that we had all heard was that the department had come into being in 1954, formed from the Physics Department, and with a physicist as the first chairman. This turned out to be partially true, in that the Department of Mathematics had been chaired by physicists until 1958, but it was referred to in the University Catalog as a department as early as 1904 and the first chairman was appointed in 1906. The authors were also part of the history of the department as professors of mathematics: Gurcharan S. Gill 1960–1999 Lynn E. Garner 1963–2007 Jan E. Wynn 1966–2000 Dr. Gill (1956–1958) and Dr. Garner (1960–1962) were also students in the department and hold B. S. degrees in Mathematics from BYU. We decided to address the history of the department by dividing it into three eras of quite different characteristics. The first era (1875–1978): Early development of the department as an entity, focusing on rapid growth during the administration of Kenneth L. Hillam as chairman. The second era (1978–1990): Efforts to bring the department in line with national standards in the mathematics community and to establish research capabilities, during the administration of Peter L. -
14-Geometry.Pdf
14. Geometry Po-Shen Loh CMU Putnam Seminar, Fall 2020 1 Classical results Archimedes' Principle. Let a sphere of radius 1 be inscribed inside a cylinder of radius 1 and height 2. Then for any two planes parallel to the base of the cylinder, the cylindrical strip that they cut out of the cylinder has surface area equal to that of the strip that they cut out of the sphere. 2 Problems 1. Two circles C1 and C2 intersect at A and B. C1 has radius 1. L denotes the arc AB of C2 which lies inside C1. L divides C1 into two parts of equal area. Show L has length greater than 2. p 2. Show that if X is a square of side 1 and X = A [ B, thenp A or B has diameter at least 5=2. Show that we can find A and B both having diameter at most 5=2. The diameter of a set is the maximum (strictly speaking, the supremum) of all distances between pairs of points in the set. 3. Let S be a spherical cap with distance taken along great circles. Show that we cannot find a distance preserving map from S to the plane. 4. Let k be a positive real and let P1;P2;:::;Pn be points in the plane. What is the locus of P such that P 2 PPi = k? State in geometric terms the conditions on k for such points P to exist. 5. Let S be a set of n points in the plane such that the greatest distance between two points of S is 1. -
THE GEOMETRY of BUBBLES and FOAMS University of Illinois Department of Mathematics Urbana, IL, USA 61801-2975 Abstract. We Consi
THE GEOMETRY OF BUBBLES AND FOAMS JOHN M. SULLIVAN University of Illinois Department of Mathematics Urbana, IL, USA 61801-2975 Abstract. We consider mathematical models of bubbles, foams and froths, as collections of surfaces which minimize area under volume constraints. The resulting surfaces have constant mean curvature and an invariant notion of equilibrium forces. The possible singularities are described by Plateau's rules; this means that combinatorially a foam is dual to some triangulation of space. We examine certain restrictions on the combina- torics of triangulations and some useful ways to construct triangulations. Finally, we examine particular structures, like the family of tetrahedrally close-packed structures. These include the one used by Weaire and Phelan in their counterexample to the Kelvin conjecture, and they all seem useful for generating good equal-volume foams. 1. Introduction This survey records, and expands on, the material presented in the author's series of two lectures on \The Mathematics of Soap Films" at the NATO School on Foams (Cargese, May 1997). The first lecture discussed the dif- ferential geometry of constant mean curvature surfaces, while the second covered the combinatorics of foams. Soap films, bubble clusters, and foams and froths can be modeled math- ematically as collections of surfaces which minimize their surface area sub- ject to volume constraints. Each surface in such a solution has constant mean curvature, and is thus called a cmc surface. In Section 2 we examine a more general class of variational problems for surfaces, and then concen- trate on cmc surfaces. Section 3 describes the balancing of forces within a cmc surface. -
1 Appendices 1 A1. Calculation of the Height of a Spherical Cap 2 A2. Surface Area of a Spherical Rectangle 3 A3. Calculation Of
1 Appendices 2 A1. Calculation of the height of a spherical cap 3 A2. Surface area of a spherical rectangle 4 A3. Calculation of fields of vision and lateral surface angles of cropped detectors (cameras) 5 A4. Non-uniformly distributed approach directions: derivation of equations 10 and 11 6 A5. Step-by-step guide to using the density estimation formula 7 1 8 A1. Calculation of the height of a spherical cap 9 The top section of an acoustic – i.e. conical – detection zone is a spherical cap. The surface area 10 of this cap is determined by the radius of the corresponding sphere (here, given by the cone’s slant 11 height s) and the cap’s height h. The following trigonometric calculations yield the formula for h that is 12 used in equation 5 of the main text (cf. Figure S1 for notation): 휙 14 퐴퐶 = 푠 cos and 퐴퐵 = 퐴퐷 = 푠 2 13 As such, 휙 15 ℎ = 퐷퐶 = 퐴퐷 − 퐴퐶 = 푠 (1 − cos ) (푆1.1) 2 16 17 Figure S1. Cross section of an acoustic detection zone, showing the measurements needed to calculate 18 the height h of the spherical cap (shaded region). The detector is located at the vertex A, which is also the center 19 of the sphere of radius s that the spherical cap is a part of. The angle 흓 is the opening angle of the detector. See 20 text for calculations. 21 2 22 A2. Surface area of a spherical rectangle 23 The top section of a camera-trap’s detection zone is a spherical rectangle whose surface area 24 can be calculated by considering the proportion of the surface area of the sphere of radius s that it 25 covers. -
Kepler's Conjecture
KEPLER’S CONJECTURE How Some of the Greatest Minds in History Helped Solve One of the Oldest Math Problems in the World George G. Szpiro John Wiley & Sons, Inc. KEPLER’S CONJECTURE How Some of the Greatest Minds in History Helped Solve One of the Oldest Math Problems in the World George G. Szpiro John Wiley & Sons, Inc. This book is printed on acid-free paper.●∞ Copyright © 2003 by George G. Szpiro. All rights reserved Published by John Wiley & Sons, Inc., Hoboken, New Jersey Published simultaneously in Canada Illustrations on pp. 4, 5, 8, 9, 23, 25, 31, 32, 34, 45, 47, 50, 56, 60, 61, 62, 66, 68, 69, 73, 74, 75, 81, 85, 86, 109, 121, 122, 127, 130, 133, 135, 138, 143, 146, 147, 153, 160, 164, 165, 168, 171, 172, 173, 187, 188, 218, 220, 222, 225, 226, 228, 230, 235, 236, 238, 239, 244, 245, 246, 247, 249, 250, 251, 253, 258, 259, 261, 264, 266, 268, 269, 274, copyright © 2003 by Itay Almog. All rights reserved Photos pp. 12, 37, 54, 77, 100, 115 © Nidersächsische Staats- und Universitätsbib- liothek, Göttingen; p. 52 © Department of Mathematics, University of Oslo; p. 92 © AT&T Labs; p. 224 © Denis Weaire No part of this publication may be reproduced, stored in a retrieval system, or trans- mitted in any form or by any means, electronic, mechanical, photocopying, record- ing, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, 222 Rosewood Drive, Danvers, MA 01923, (978) 750-8400, fax (978) 750-4470, or on the web at www.copyright.com. -
Lie Sphere Geometry in Lattice Cosmology
Classical and Quantum Gravity PAPER • OPEN ACCESS Lie sphere geometry in lattice cosmology To cite this article: Michael Fennen and Domenico Giulini 2020 Class. Quantum Grav. 37 065007 View the article online for updates and enhancements. This content was downloaded from IP address 131.169.5.251 on 26/02/2020 at 00:24 IOP Classical and Quantum Gravity Class. Quantum Grav. Classical and Quantum Gravity Class. Quantum Grav. 37 (2020) 065007 (30pp) https://doi.org/10.1088/1361-6382/ab6a20 37 2020 © 2020 IOP Publishing Ltd Lie sphere geometry in lattice cosmology CQGRDG Michael Fennen1 and Domenico Giulini1,2 1 Center for Applied Space Technology and Microgravity, University of Bremen, 065007 Bremen, Germany 2 Institute for Theoretical Physics, Leibniz University of Hannover, Hannover, Germany M Fennen and D Giulini E-mail: [email protected] Received 23 September 2019, revised 18 December 2019 Lie sphere geometry in lattice cosmology Accepted for publication 10 January 2020 Published 18 February 2020 Printed in the UK Abstract In this paper we propose to use Lie sphere geometry as a new tool to CQG systematically construct time-symmetric initial data for a wide variety of generalised black-hole configurations in lattice cosmology. These configurations are iteratively constructed analytically and may have any 10.1088/1361-6382/ab6a20 degree of geometric irregularity. We show that for negligible amounts of dust these solutions are similar to the swiss-cheese models at the moment Paper of maximal expansion. As Lie sphere geometry has so far not received much attention in cosmology, we will devote a large part of this paper to explain its geometric background in a language familiar to general relativists.