Recent Progress on Polytopes Günter M. Ziegler∗
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LINEAR ALGEBRA METHODS in COMBINATORICS László Babai
LINEAR ALGEBRA METHODS IN COMBINATORICS L´aszl´oBabai and P´eterFrankl Version 2.1∗ March 2020 ||||| ∗ Slight update of Version 2, 1992. ||||||||||||||||||||||| 1 c L´aszl´oBabai and P´eterFrankl. 1988, 1992, 2020. Preface Due perhaps to a recognition of the wide applicability of their elementary concepts and techniques, both combinatorics and linear algebra have gained increased representation in college mathematics curricula in recent decades. The combinatorial nature of the determinant expansion (and the related difficulty in teaching it) may hint at the plausibility of some link between the two areas. A more profound connection, the use of determinants in combinatorial enumeration goes back at least to the work of Kirchhoff in the middle of the 19th century on counting spanning trees in an electrical network. It is much less known, however, that quite apart from the theory of determinants, the elements of the theory of linear spaces has found striking applications to the theory of families of finite sets. With a mere knowledge of the concept of linear independence, unexpected connections can be made between algebra and combinatorics, thus greatly enhancing the impact of each subject on the student's perception of beauty and sense of coherence in mathematics. If these adjectives seem inflated, the reader is kindly invited to open the first chapter of the book, read the first page to the point where the first result is stated (\No more than 32 clubs can be formed in Oddtown"), and try to prove it before reading on. (The effect would, of course, be magnified if the title of this volume did not give away where to look for clues.) What we have said so far may suggest that the best place to present this material is a mathematics enhancement program for motivated high school students. -
Centrally Symmetric Polytopes with Many Faces
Centrally symmetric polytopes with many faces by Seung Jin Lee A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Mathematics) in The University of Michigan 2013 Doctoral Committee: Professor Alexander I. Barvinok, Chair Professor Thomas Lam Professor John R. Stembridge Professor Martin J. Strauss Professor Roman Vershynin TABLE OF CONTENTS CHAPTER I. Introduction and main results ............................ 1 II. Symmetric moment curve and its neighborliness ................ 6 2.1 Raked trigonometric polynomials . 7 2.2 Roots and multiplicities . 9 2.3 Parametric families of trigonometric polynomials . 14 2.4 Critical arcs . 19 2.5 Neighborliness of the symmetric moment curve . 28 2.6 The limit of neighborliness . 31 2.7 Neighborliness for generalized moment curves . 37 III. Centrally symmetric polytopes with many faces . 41 3.1 Introduction . 41 3.1.1 Cs neighborliness . 41 3.1.2 Antipodal points . 42 3.2 Centrally symmetric polytopes with many edges . 44 3.3 Applications to strict antipodality problems . 49 3.4 Cs polytopes with many faces of given dimension . 52 3.5 Constructing k-neighborly cs polytopes . 56 APPENDICES :::::::::::::::::::::::::::::::::::::::::: 62 BIBLIOGRAPHY ::::::::::::::::::::::::::::::::::::::: 64 ii CHAPTER I Introduction and main results A polytope is the convex hull of a set of finitely many points in Rd. A polytope P ⊂ Rd is centrally symmetric (cs, for short) if P = −P .A convex body is a compact convex set with non-empty interior. A face of a polytope (or a convex body) P can be defined as the intersection of P and a closed halfspace H such that the boundary of H contains no interior point of P . -
15 BASIC PROPERTIES of CONVEX POLYTOPES Martin Henk, J¨Urgenrichter-Gebert, and G¨Unterm
15 BASIC PROPERTIES OF CONVEX POLYTOPES Martin Henk, J¨urgenRichter-Gebert, and G¨unterM. Ziegler INTRODUCTION Convex polytopes are fundamental geometric objects that have been investigated since antiquity. The beauty of their theory is nowadays complemented by their im- portance for many other mathematical subjects, ranging from integration theory, algebraic topology, and algebraic geometry to linear and combinatorial optimiza- tion. In this chapter we try to give a short introduction, provide a sketch of \what polytopes look like" and \how they behave," with many explicit examples, and briefly state some main results (where further details are given in subsequent chap- ters of this Handbook). We concentrate on two main topics: • Combinatorial properties: faces (vertices, edges, . , facets) of polytopes and their relations, with special treatments of the classes of low-dimensional poly- topes and of polytopes \with few vertices;" • Geometric properties: volume and surface area, mixed volumes, and quer- massintegrals, including explicit formulas for the cases of the regular simplices, cubes, and cross-polytopes. We refer to Gr¨unbaum [Gr¨u67]for a comprehensive view of polytope theory, and to Ziegler [Zie95] respectively to Gruber [Gru07] and Schneider [Sch14] for detailed treatments of the combinatorial and of the convex geometric aspects of polytope theory. 15.1 COMBINATORIAL STRUCTURE GLOSSARY d V-polytope: The convex hull of a finite set X = fx1; : : : ; xng of points in R , n n X i X P = conv(X) := λix λ1; : : : ; λn ≥ 0; λi = 1 : i=1 i=1 H-polytope: The solution set of a finite system of linear inequalities, d T P = P (A; b) := x 2 R j ai x ≤ bi for 1 ≤ i ≤ m ; with the extra condition that the set of solutions is bounded, that is, such that m×d there is a constant N such that jjxjj ≤ N holds for all x 2 P . -
Notes on Convex Sets, Polytopes, Polyhedra, Combinatorial Topology, Voronoi Diagrams and Delaunay Triangulations
Notes on Convex Sets, Polytopes, Polyhedra, Combinatorial Topology, Voronoi Diagrams and Delaunay Triangulations Jean Gallier and Jocelyn Quaintance Department of Computer and Information Science University of Pennsylvania Philadelphia, PA 19104, USA e-mail: [email protected] April 20, 2017 2 3 Notes on Convex Sets, Polytopes, Polyhedra, Combinatorial Topology, Voronoi Diagrams and Delaunay Triangulations Jean Gallier Abstract: Some basic mathematical tools such as convex sets, polytopes and combinatorial topology, are used quite heavily in applied fields such as geometric modeling, meshing, com- puter vision, medical imaging and robotics. This report may be viewed as a tutorial and a set of notes on convex sets, polytopes, polyhedra, combinatorial topology, Voronoi Diagrams and Delaunay Triangulations. It is intended for a broad audience of mathematically inclined readers. One of my (selfish!) motivations in writing these notes was to understand the concept of shelling and how it is used to prove the famous Euler-Poincar´eformula (Poincar´e,1899) and the more recent Upper Bound Theorem (McMullen, 1970) for polytopes. Another of my motivations was to give a \correct" account of Delaunay triangulations and Voronoi diagrams in terms of (direct and inverse) stereographic projections onto a sphere and prove rigorously that the projective map that sends the (projective) sphere to the (projective) paraboloid works correctly, that is, maps the Delaunay triangulation and Voronoi diagram w.r.t. the lifting onto the sphere to the Delaunay diagram and Voronoi diagrams w.r.t. the traditional lifting onto the paraboloid. Here, the problem is that this map is only well defined (total) in projective space and we are forced to define the notion of convex polyhedron in projective space. -
36 COMPUTATIONAL CONVEXITY Peter Gritzmann and Victor Klee
36 COMPUTATIONAL CONVEXITY Peter Gritzmann and Victor Klee INTRODUCTION The subject of Computational Convexity draws its methods from discrete mathe- matics and convex geometry, and many of its problems from operations research, computer science, data analysis, physics, material science, and other applied ar- eas. In essence, it is the study of the computational and algorithmic aspects of high-dimensional convex sets (especially polytopes), with a view to applying the knowledge gained to convex bodies that arise in other mathematical disciplines or in the mathematical modeling of problems from outside mathematics. The name Computational Convexity is of more recent origin, having first ap- peared in print in 1989. However, results that retrospectively belong to this area go back a long way. In particular, many of the basic ideas of Linear Programming have an essentially geometric character and fit very well into the conception of Compu- tational Convexity. The same is true of the subject of Polyhedral Combinatorics and of the Algorithmic Theory of Polytopes and Convex Bodies. The emphasis in Computational Convexity is on problems whose underlying structure is the convex geometry of normed vector spaces of finite but generally not restricted dimension, rather than of fixed dimension. This leads to closer con- nections with the optimization problems that arise in a wide variety of disciplines. Further, in the study of Computational Convexity, the underlying model of com- putation is mainly the binary (Turing machine) model that is common in studies of computational complexity. This requirement is imposed by prospective appli- cations, particularly in mathematical programming. For the study of algorithmic aspects of convex bodies that are not polytopes, the binary model is often aug- mented by additional devices called \oracles." Some cases of interest involve other models of computation, but the present discussion focuses on aspects of computa- tional convexity for which binary models seem most natural. -
Combinatorial Aspects of Convex Polytopes Margaret M
Combinatorial Aspects of Convex Polytopes Margaret M. Bayer1 Department of Mathematics University of Kansas Carl W. Lee2 Department of Mathematics University of Kentucky August 1, 1991 Chapter for Handbook on Convex Geometry P. Gruber and J. Wills, Editors 1Supported in part by NSF grant DMS-8801078. 2Supported in part by NSF grant DMS-8802933, by NSA grant MDA904-89-H-2038, and by DIMACS (Center for Discrete Mathematics and Theoretical Computer Science), a National Science Foundation Science and Technology Center, NSF-STC88-09648. 1 Definitions and Fundamental Results 3 1.1 Introduction : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 3 1.2 Faces : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 3 1.3 Polarity and Duality : : : : : : : : : : : : : : : : : : : : : : : : : 3 1.4 Overview : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 4 2 Shellings 4 2.1 Introduction : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 4 2.2 Euler's Relation : : : : : : : : : : : : : : : : : : : : : : : : : : : : 4 2.3 Line Shellings : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 5 2.4 Shellable Simplicial Complexes : : : : : : : : : : : : : : : : : : : 5 2.5 The Dehn-Sommerville Equations : : : : : : : : : : : : : : : : : : 6 2.6 Completely Unimodal Numberings and Orientations : : : : : : : 7 2.7 The Upper Bound Theorem : : : : : : : : : : : : : : : : : : : : : 8 2.8 The Lower Bound Theorem : : : : : : : : : : : : : : : : : : : : : 9 2.9 Constructions Using Shellings : : : : : : : : : : : : : -
The Geometry of Colour
The Geometry of Colour Paul Centore The Geometry of Colour Paul Centore Suggested Cataloging Data Centore, Paul The Geometry of Colour/P. Centore 221 p., 21.6 by 14.0 cm ISBN 978-0-9990291-0-7 1. Color 2. Color—Mathematics 3. Colorimetry 4. Convex Geometry I. Centore, Paul, 1968- II. Title QC495.C397 2017 535.6 Coopyright c 2017 by Paul Centore • All rights reserved Printed in the United States of America ISBN 978-0-9990291-0-7 ISBN 9780999029107 9 780999 029107 Introduction Colour is a universal experience, which has been investigated since an- tiquity. Today, colour science rests firmly on both empirical findings and theoretical development. Unlike many technical fields, colour sci- ence considers not only physical factors, but also human perception, and the relationships between the two. A basic part of colour science is colour matching, which identifies when two side-by-side lights, viewed in isolation through an aperture, produce the same colour. The Geometry of Colour formulates colour matching mathematically, emphasizing geometric constructions and understanding. The motiva- tion for writing it was the unifying insight that many apparently dis- parate objects in colour science share a common zonohedral structure. The book aims at both rigor and intuition. Fortunately, many colour science objects can be explicitly constructed in a three-dimensional vector space, and, while linear algebra insures rigorous definitions, a premium is placed on a concrete visual and spatial presentation— ideally, a motivated reader could build literal models, for example with foam board and glue. This book is intended for mathematicians, colour scientists, and, as much as possible, curious non-specialists. -
Rigidity and Polyhedral Combinatorics the American Institute of Mathematics
Rigidity and polyhedral combinatorics The American Institute of Mathematics The following compilation of participant contributions is only intended as a lead-in to the AIM workshop \Rigidity and polyhedral combinatorics." This material is not for public distribution. Corrections and new material are welcomed and can be sent to [email protected] Version: Mon Nov 26 14:43:28 2007 1 2 Table of Contents A. Participant Contributions . 3 1. Alexandrov, Victor 2. Bezdek, Karoly 3. Bobenko, Alexander 4. Dolbilin, Nikolay 5. Fernandez, Silvia 6. Fillastre, Francois 7. Graver, Jack 8. Izmestiev, Ivan 9. Martin, Jeremy 10. Nevo, Eran 11. Panina, Gayane 12. Rote, Gunter 13. Sabitov, Idzhad 14. Schlenker, Jean-Marc 15. Schulze, Bernd 16. Servatius, Brigitte 17. Stachel, Hellmuth 18. Tabachnikov, Sergei 19. Tarasov, Alexey 20. Thurston, Dylan 21. Whiteley, Walter 22. Ye, Yinyu 3 Chapter A: Participant Contributions A.1 Alexandrov, Victor In the moment my research interests are focused at the Strong Bellows Conjecture which reads as follows: every two polyhedra in Euclidean 3-space, such that one of them is obtained from the other by a continuous flex, are scissor congruent, that is, one of them can be cut into \small" simplices which, being moved independently one from another, give a partition of the other polyhedron. A.2 Bezdek, Karoly Recall that the intersection of finitely many closed unit balls of E3 is called a ball- polyhedron (for more details see [blnp]). Also, it is natural to assume that removing any of the balls in question yields the intersection of the remaining balls to become a larger set. -
$ K $-Sets and Rectilinear Crossings in Complete Uniform Hypergraphs
k-Sets and Rectilinear Crossings in Complete Uniform Hypergraphs Rahul Gangopadhyay1 and Saswata Shannigrahi2 1 IIIT Delhi, India [email protected] 2 Saint Petersburg State University, Russia [email protected] Abstract. In this paper, we study the d-dimensional rectilinear drawings d of the complete d-uniform hypergraph K2d. Anshu et al. [Computational Geometry: Theory and Applications, 2017] used Gale transform and Ham- Sandwich theorem to prove that there exist Ω 2d crossing pairs of hy- d peredges in such a drawing of K2d. We improve this lower bound by showing that there exist Ω 2d√d crossing pairs of hyperedges in a d- d dimensional rectilinear drawing of K2d. We also prove the following re- sults. 1. There are Ω 2dd3/2 crossing pairs of hyperedges in a d-dimensional d rectilinear drawing of K2d when its 2d vertices are either not in convex position in Rd or form the vertices of a d-dimensional convex polytope that is t-neighborly but not (t + 1)-neighborly for some constant t 1 ≥ independent of d. 2. There are Ω 2dd5/2 crossing pairs of hyperedges in a d-dimensional d rectilinear drawing of K2d when its 2d vertices form the vertices of a d- dimensional convex polytope that is ( d/2 t )-neighborly for some ⌊ ⌋ − ′ constant t 0 independent of d. ′ ≥ Keywords: Rectilinear Crossing Number · Neighborly Polytope · Gale · · · · arXiv:1806.02574v5 [math.CO] 28 Oct 2019 Transform Affine Gale Diagram Balanced Line j-Facet k-Set 1 Introduction d For a sufficiently large positive integer d, let Kn denote the complete d-uniform d hypergraph with n 2d vertices. -
A Vertex and Hyperplane Descriptions of Polytopes
A Vertex and Hyperplane Descriptions of Polytopes Everything should be made as simple as possible, but not simpler. Albert Einstein In this appendix, we prove that every polytope has a vertex and a hyperplane description. This appendix owes everything to G¨unter Ziegler’s beautiful ex- position in [193]; in fact, these pages contain merely a few cherries picked from [193, Lecture 1]. As in Chapter 3, it is easier to move to the world of cones. To be as concrete as possible, let us call K ⊆ Rd an h-cone if d K = x ∈ R : A x ≤ 0 for some A ∈ Rm×d; in this case K is given as the intersection of m halfspaces determined by the rows of A. We use the notation K = hcone(A). On the other hand, we call K ⊆ Rd a v-cone if K = {B y : y ≥ 0} for some B ∈ Rd×n, that is, K is a pointed cone with the column vectors of B as generators. In this case we use the notation K = vcone(B). Note that, according to our definitions, any h- or v-cone contains the origin in its apex. We will prove that every h-cone is a v-cone and vice versa. More precisely: Theorem A.1. For every A ∈ Rm×d there exists B ∈ Rd×n (for some n) such that hcone(A) = vcone(B). Conversely, for every B ∈ Rd×n there exists A ∈ Rm×d (for some m) such that vcone(B) = hcone(A). We will prove the two halves of Theorem A.1 in Sections A.1 and A.2. -
An Introduction to Convex Polytopes
Graduate Texts in Mathematics Arne Brondsted An Introduction to Convex Polytopes 9, New YorkHefdelbergBerlin Graduate Texts in Mathematics90 Editorial Board F. W. GehringP. R. Halmos (Managing Editor) C. C. Moore Arne Brondsted An Introduction to Convex Polytopes Springer-Verlag New York Heidelberg Berlin Arne Brondsted K, benhavns Universitets Matematiske Institut Universitetsparken 5 2100 Kobenhavn 0 Danmark Editorial Board P. R. Halmos F. W. Gehring C. C. Moore Managing Editor University of Michigan University of California Indiana University Department of at Berkeley Department of Mathematics Department of Mathematics Ann Arbor, MI 48104 Mathematics Bloomington, IN 47405 U.S.A. Berkeley, CA 94720 U.S.A. U.S.A. AMS Subject Classifications (1980): 52-01, 52A25 Library of Congress Cataloging in Publication Data Brondsted, Arne. An introduction to convex polytopes. (Graduate texts in mathematics; 90) Bibliography : p. 1. Convex polytopes.I. Title.II. Series. QA64.0.3.B76 1982 514'.223 82-10585 With 3 Illustrations. © 1983 by Springer-Verlag New York Inc. All rights reserved. No part of this book may be translated or reproduced in any form without written permission from Springer-Verlag, 175 Fifth Avenue, New York, New York 10010, U.S.A. Typeset by Composition House Ltd., Salisbury, England. Printed and bound by R. R. Donnelley & Sons, Harrisonburg, VA. Printed in the United States of America. 987654321 ISBN 0-387-90722-X Springer-Verlag New York Heidelberg Berlin ISBN 3-540-90722-X Springer-Verlag Berlin Heidelberg New York Preface The aim of this book is to introduce the reader to the fascinating world of convex polytopes. The highlights of the book are three main theorems in the combinatorial theory of convex polytopes, known as the Dehn-Sommerville Relations, the Upper Bound Theorem and the Lower Bound Theorem. -
SIX TOPICS on INSCRIBABLE POLYTOPES 3 Circumscribability of 3-Polytopes [19] by Linear Programming (See Also [32], [33], [35])
SIX TOPICS ON INSCRIBABLE POLYTOPES ARNAU PADROL AND GUNTER¨ M. ZIEGLER ABSTRACT. Inscribability of polytopes is a classic subject but also a lively research area nowadays. We illustrate this with a selection of well-known results and recent develop- ments on six particular topics related to inscribable polytopes. Along the way we collect a list of (new and old) open questions. Jakob Steiner ended his 1832 geometry book Systematische Entwicklung der Abhangig-¨ keit geometrischer Gestalten von einander [41] with a list of 85 open problems. Problem 77 reads as follows: 77) Wenn irgend ein convexes Polyeder gegeben ist l¨aßt sich dann immer (oder in welchen F¨allen nur) irgend ein anderes, welches mit ihm in Hin- sicht der Art und der Zusammensetzung der Grenzfl¨achen ¨ubereinstimmt (oder von gleicher Gattung ist), in oder um eine Kugelfl¨ache, oder in oder um irgend eine andere Fl¨ache zweiten Grades beschreiben (d.h. daß seine Ecken alle in dieser Fl¨ache liegen oder seine Grenzfl¨achen alle diese Fl¨ache ber¨uhren)? It asks whether every (3-dimensional) polytope is inscribable; that is, whether for ev- ery 3-polytope there is a combinatorially equivalent polytope with all the vertices on the sphere. And if not, which are the cases of 3-polytopes that do have such a realization? He also asks the same question for circumscribable polytopes, those that have a realization with all the facets tangent to the sphere, as well as for other surfaces of degree 2. There was no progress on this question until 1928, when Ernst Steinitz showed that inscribability and circumscribability are polar concepts and presented the first examples of polytopes that cannot be inscribed/circumscribed.