Simplicial Cells in Arrangements of Hyperplanes
|
|
- Darlene Barrett
- 5 years ago
- Views:
Transcription
1 Simplicial Cells in Arrangements of Hyperplanes Christoph Dätwyler This paper is a report written due to the authors presentation of a paper written by Shannon [1] in The presentation was part of a seminar in combinatorics, organized by Prof. Dr. K. Fukuda at ETH Zürich in Shannon proved in his paper the generalization of two older theorems to higher dimensions. The report covers the rst few pages of Shannons paper, in which a proof of one of these generalized theorems is given. 1 Introduction and Denition In a rst part two theorems going back to Roberts, Eberhard and Levi are stated. The goal of the second part then is to arrive at a proof of a generalization of the theorem of Eberhard and Levi. For a proof of a generalization of the theorem of Roberts, the reader is referred to the paper of Shannon. We start with the denition of some basic terms and concepts we will need. Denition. We destinguish the following two types of arrangements of hyperplanes: A projective d-arrangement H is a nite collection of n = n(h) hyperplanes in real d-dimensional projective space with H =. H partitions P d into k-cells, subsets homeomorphic to an open ball in R k, for 0 k d, forming the associated cell complex C(H). A Euclidean d-arrangement H is required to have the additional property that K for each K H with n(k) = d. Then H partitions R d into k-cells, convex sets, some of which are unbounded. If we simply talk about a d-arrangement, we mean by it a projective one. Otherwise the word Euclidean is explicitely written. But let us just note here that, it actually hardly makes any dierence whether a statement is understood in the projective or Euclidean sense, as there is sort of a duality between them. For a projective d-arrangement H and a hyperplane L P d containing no vertices of C(H) we can regard H as a Euclidean d-arrangement in the ane space A d (L) = P d L. In the case where d = 2, we take the following construction as model for a projective arrangement: Consider S 2 the unit 2-sphere in R 3. Intersecting the 1
2 sphere with planes through the origin yields an arrangement of circles on it. By identify antipodal points, we can represent the arrangement as semicircles on a hemisphere. These semicircles are our hyperplanes. To get an intuitive imagination of A 2 (L) one can think of an arrangement of circles on the 2-sphere. Now one adds one more circle, not passing through any of the intersection points of the circles already on the sphere, and call it L. This circle L devides the sphere into two hemispheres with boundary L and pointsymmetric (with respect to the origin) arrangements of hyperplanes. Due to this symmetry one can pick any of these two. The circle L lies in a plane, say P. Consider the (unique) plane P parallel to P, which intersects the chosen hemisphere, say H, at exactly one point. For every point p on H, one can associate the line l p through the origin and p itself, which intersects the plane P at exactly one point i p. Thus one obtains the corresponding Euclidean arrangement (on P ) by sending every point p of H along l p to its according point i p on P. Note that the points on L are sent to innity. The condition that L does not pass through any vertex is necessary in order to end up with a valid Euclidean arrangement. To see this, let L pass through a vertex of the arrangement on S 2. In the corresponding Euclidean arrangement the vertex is sent to innity and the semicircles passing through the vertex become parallel lines. But by the denition of a Euclidean arrangement, parallel lines are not allowed. Denition. A projective or Euclidean d-arrangement is called simple if the intersection of any d + 1 hyperplanes is empty. A projective or Euclidean d-arrangement H is called near trivial (or a near pencil) if there is a point in P d or R d contained in all hyperplanes of H but one. 2 The Theorems of Roberts, Eberhard and Levi Roberts (1889) stated and tried to prove the following Theorem 1 (Roberts). If His a simple 2-arrangement and H is a line of H, then there are at least n(h) 3 triangles of C(H) which have no edge on H. Grünbaum (1972) conjectured that Theorem 1 is true for all 2-arrangements which are not near trivial. This indeed holds true. It directly follows from Theorem 2, the generalization of Theorem 1, proven in Shannons paper, but not discussed in this report. Theorem 2. Let H be a d-arrangement which is not near trivial and let H be a hyperplane of H. Then there are at least n(h) d 1 simplicial d-cells of C(H), each having no facet in H. Observing that the assumption for an arrangement to be simple is stronger than not to be near trivial and that in the case d = 2 simplicial 2-cells are triangles and facets correspond to edges, we get exactly Theorem 1 as special case of Theorem 2 with d = 2. 2
3 One year after Roberts Eberhard proved the following result for simple planar arrangements and Levi in 1926 proved it for all planar arrangements: Theorem 3. Let H be a 2-arrangement and H a line of H. There are at least three triangles of C(H), each having an edge on H. C(H) contains at least n(h) triangles altogether. Remark. We can construct a simple 2-arrangement of n 4 lines having a cell complex containing exactly n triangles by letting the arrangement consist of n tangent lines to a circle in R 2 (considered as part of P 2 ). 3 A Generalization of the Theorems of Eberhard and Levi Similar to Theorem 1, Theorem 3 can be generalized. Theorem 4. Let H be a d-arrangement and H a hyperplane of H. Then 1. there are at least d + 1 simplicial d-cells of C(H), each having a facet on H 2. C(H) contains at least n(h) simplicial d-cells altogether. The topic of this section is to discuss, how Theorem 4 can be proven. The way we will go about it is as follows: Use Lemma 5 to prove Lemma 7. Use Lemma 8, a restatement of Lemma 7 in a dierent context, and Lemma 9 to prove Theorem 4. Let us start with introducing the notion of an induced arrangement. Denition. Let U = K 1 and V = K 2, K 1, K 2 H, be two non-intersecting ats of H. The induced (projective or Euclidean) arrangement on U with respect to V is dened as the set {U} {U H : H H, U H, V H} and denoted by L(H, U, V ). If V = we write L(H, U) instead of L(H, U, ). Now we can formulate and prove Lemma 1 Lemma 5. Let H be a Euclidean d-arrangement. bounded d-simplex. Then C(H) contains a Proof. Induction on d: d = 1: Since H =, C(H) has k 2 vertices and k 1 1 bounded 1-cells. d 2: Let H be a hyperplane of H and p a vertex of C(H) such that dist(p, H) is positive and minimal. Since L(H, H, {p}) is Euclidean of dim d 1 it has by the induction hypothesis a bounded d 1-simplex p 1 p 2...p d. Since p was chosen to be the point nearest to H, each of the segments pp i will be an edge of C(H). Hence pp 1...p d will be a bounded d-simplex of 3
4 C(H). One has to justify why such a point p of minimal positive distance always exists. This essentially follows from how a Euclidean d-arrangement was dened. Because not all hyperplanes intersect in a single point, there exists a vertex p L 0, L 0 a hyperplane, and a hyperplane L such that p / L. Because the intersection of any d hyperplanes is non-empty, we can write p = d 1 i=0 L i. Then l = d 1 i=1 L i is a line and l L 0 because otherwise p would not be a vertex (note that l L 0 = p). Because p / L it follows that l L / L 0 and because any d hyperplanes have to intersect, the intersection point of l L is non-empty and hence a candidate for the point with positive minimal distance. The following Lemma 6 is just Lemma 5 adapted to the projective setting. Lemma 6. Let H be a d-arrangement and let L P d be a hyperplane containing no vertices of C(H). Then there is a d-simplex D C(H) with L D =. The next step uses Lemma 5 to prove Lemma 7. Denition. If H is a Euclidean d-arrangement, then an unbounded d-cell D C(H) is a d-cone if the closure of D has only one extreme point. D is simplicial if the closure of D is the convex hull of d rays. Lemma 7. If H is a Euclidean d-arrangement, then C(H) contains at least d + 1 simplicial d-cones. Proof. Let C be the convex hull of the vertices C(H) (green in the picture). Lemma 5 implies that C is a d-dimensional convex polytope in R d and therefore has at least d + 1 extreme points (red). Let p be one such extreme point and let L be a hyperplane not of H such that L C = and such that the distance between L and C is minimized only at p. 4
5 Then L(H, L, {p}) is a Euclidean d 1-arrangement and by Lemma 5 contains a bounded d 1-simplex p 1...p d C(L(H, L, {p})) (in the picture this would correspond to p 1 p 2 ). The convex hull of the rays pp 1,..., pp d will be the closure of a d-cone with vertex p (grey) and since C has at least d + 1 extreme points, the claimed statement follows. 8. Again we can formulate Lemma 7 in the projective context. This is Lemma Lemma 8. Let H be an arrangement in P d and H a hyperplane of H. Suppose the convex hull (in A d (H)) of the vertices C(H) not contained in H is d-dimensional. Then there are at least d + 1 d-simplices of C(H), each having a facet contained in H. Suppose H is an arrangement in P d and U and V are ats of H satisfying U V = and the dimension of U + the dimension of V = d 1 U H or V H for each H H then H is the join of the two induced arrangements L(H, U) and L(H, V ) and we write H = L(H, U) L(H, V ). Lemma 9. Let H be an arrangement in P d. If there is a hyperplane H H containing some face of each d-cell of C(H), then there exist ats U and V of H such that H = L(H, U) L(H, V ). Proof. The proof uses the following result due to Zaslavsky: 5
6 Theorem. Let H be an arrangement in P d. Then the number of d-cells which do not contain some face of a hyperplane H of H is independent of the choice of H. This allows us to make the following assumption: (*) Each hyperplane H of H contains some face of every d-cell of C(H). This is actually only possible for near pencils (follows directly from Theorem 2). Now use induction on d and n = n(h) d + 1: d = 1: The above assuption (*) implies n = 2 and the conclusion follows with U and V the two points of the arrangement. d 2, n = d + 1: Take U = K 1, V = K 2, where K 1 and K 1 are any collections with K 1 K 2 = H and U V =. d 2, n d + 2: Consider H = H {H 0 }, H 0 a hyperplane of H. Case 1: H is trivial. Then take U = H 0, V = H. Case 2: Otherwise, since n(h ) < n and H satises assuption (*), there are ats X and Y of H (and hence of H) such that H = L(H, X) L(H, Y ). Case 2.1: X H 0 or Y H 0. Then we are done, as H 0 can be included in one of the arrangements. Case 2.2: Otherwise consider X H 0 L(H, X) and Y H 0 L(H, Y ). Case 2.2.1: E.g. X H 0 is incident with each maximal cell of C(L(H, X)). Then, since dim(x) < d there exist ats U and V of L(H, X) such that L(H, X) = L(H, U ) L(H, V ). If e.g. U X H 0, we let U = U and V = V Y giving H = L(H, U) L(H, V ). Case 2.2.2: There exist maximal cells A and B, not incident with X H 0 in L(H, X) and Y H 0 in L(H, Y ) respectively. Then A B contains two d-cells of C(H) one of which 6
7 cannot be incident with H 0 contrary to assuption (*). This concludes the proof. Now we are ready to prove Theorem 4. Proof of Theorem Induction on d: d = 1: Clear. d 2: Distinguish two cases: Case 1: H is not the join of two induced arrangements. Then the result follows from Lemma 8 and 9 because Lemma 9 asserts that there exists a hyperplane H of H and a d-cell of C(H) such that this d-cell does not have a face on H. Hence Lemma 8 applies since the convex hull of the vertices C(H) not contained in H is d-dimensional. Case 2: H = L(H, U) L(H, V ) where dim(u) = r, dim(v ) = s and r + s = d 1. Let H be a hyperplane of H containing e.g. U. By the induction hypothesis there are at least r + 1 simplicial r-cells in C(L(H, U)) and s + 1 simplicial s-cells in C(L(H, V )) each of the latter having a facet in H V. The join of one such cell from C(L(H, U)) and another from C(L(H, V )) contains two simplicial d-cells of C(H), each with a facet in H. There are at least (r + 1)(s + 1) possible joins of maximal simplicial cells and hence at least 2(r + 1)(s + 1) = 2(rs + r + s + 1) r+s=d 1 = 2(rs + d) 2d d + 1 simplicial d-cells of C(H) each having a facet in H. 2. Since the total number of incidences between hyperplanes and facets of d- simplices is at least n(h)(d+1) (by 1. of Theorem 4), it follows that there 7
8 must be at least n(h) simplicial d-cells altogehter in C(H) as a d-simplex has d + 1 facets and hence n(h)(d+1) d+1 = n(h). References [1] Shannon, R.W., Simplicial Cells in Arrangements of Hyperplanes, Geom. Dedicata, 8(2): ,
Chapter 8. Voronoi Diagrams. 8.1 Post Oce Problem
Chapter 8 Voronoi Diagrams 8.1 Post Oce Problem Suppose there are n post oces p 1,... p n in a city. Someone who is located at a position q within the city would like to know which post oce is closest
More information10. Line Arrangements Lecture on Monday 2 nd November, 2009 by Michael Homann
10. Line Arrangements Lecture on Monday 2 nd November, 2009 by Michael Homann During the course of this lecture we encountered several situations where it was convenient to assume
More informationThe Charney-Davis conjecture for certain subdivisions of spheres
The Charney-Davis conjecture for certain subdivisions of spheres Andrew Frohmader September, 008 Abstract Notions of sesquiconstructible complexes and odd iterated stellar subdivisions are introduced,
More informationLectures 19: The Gauss-Bonnet Theorem I. Table of contents
Math 348 Fall 07 Lectures 9: The Gauss-Bonnet Theorem I Disclaimer. As we have a textbook, this lecture note is for guidance and supplement only. It should not be relied on when preparing for exams. In
More informationPlanar Graphs. 1 Graphs and maps. 1.1 Planarity and duality
Planar Graphs In the first half of this book, we consider mostly planar graphs and their geometric representations, mostly in the plane. We start with a survey of basic results on planar graphs. This chapter
More informationVoronoi diagram and Delaunay triangulation
Voronoi diagram and Delaunay triangulation Ioannis Emiris & Vissarion Fisikopoulos Dept. of Informatics & Telecommunications, University of Athens Computational Geometry, spring 2015 Outline 1 Voronoi
More informationHowever, this is not always true! For example, this fails if both A and B are closed and unbounded (find an example).
98 CHAPTER 3. PROPERTIES OF CONVEX SETS: A GLIMPSE 3.2 Separation Theorems It seems intuitively rather obvious that if A and B are two nonempty disjoint convex sets in A 2, then there is a line, H, separating
More informationPartitions and Packings of Complete Geometric Graphs with Plane Spanning Double Stars and Paths
Partitions and Packings of Complete Geometric Graphs with Plane Spanning Double Stars and Paths Master Thesis Patrick Schnider July 25, 2015 Advisors: Prof. Dr. Emo Welzl, Manuel Wettstein Department of
More informationLecture 2 September 3
EE 381V: Large Scale Optimization Fall 2012 Lecture 2 September 3 Lecturer: Caramanis & Sanghavi Scribe: Hongbo Si, Qiaoyang Ye 2.1 Overview of the last Lecture The focus of the last lecture was to give
More informationMonotone Paths in Geometric Triangulations
Monotone Paths in Geometric Triangulations Adrian Dumitrescu Ritankar Mandal Csaba D. Tóth November 19, 2017 Abstract (I) We prove that the (maximum) number of monotone paths in a geometric triangulation
More informationFACES OF CONVEX SETS
FACES OF CONVEX SETS VERA ROSHCHINA Abstract. We remind the basic definitions of faces of convex sets and their basic properties. For more details see the classic references [1, 2] and [4] for polytopes.
More informationSimplicial Complexes: Second Lecture
Simplicial Complexes: Second Lecture 4 Nov, 2010 1 Overview Today we have two main goals: Prove that every continuous map between triangulable spaces can be approximated by a simplicial map. To do this,
More informationMATH 890 HOMEWORK 2 DAVID MEREDITH
MATH 890 HOMEWORK 2 DAVID MEREDITH (1) Suppose P and Q are polyhedra. Then P Q is a polyhedron. Moreover if P and Q are polytopes then P Q is a polytope. The facets of P Q are either F Q where F is a facet
More informationPebble Sets in Convex Polygons
2 1 Pebble Sets in Convex Polygons Kevin Iga, Randall Maddox June 15, 2005 Abstract Lukács and András posed the problem of showing the existence of a set of n 2 points in the interior of a convex n-gon
More information[8] that this cannot happen on the projective plane (cf. also [2]) and the results of Robertson, Seymour, and Thomas [5] on linkless embeddings of gra
Apex graphs with embeddings of face-width three Bojan Mohar Department of Mathematics University of Ljubljana Jadranska 19, 61111 Ljubljana Slovenia bojan.mohar@uni-lj.si Abstract Aa apex graph is a graph
More informationThe Borsuk-Ulam theorem- A Combinatorial Proof
The Borsuk-Ulam theorem- A Combinatorial Proof Shreejit Bandyopadhyay April 14, 2015 1 Introduction The Borsuk-Ulam theorem is perhaps among the results in algebraic topology having the greatest number
More informationLinear Programming in Small Dimensions
Linear Programming in Small Dimensions Lekcija 7 sergio.cabello@fmf.uni-lj.si FMF Univerza v Ljubljani Edited from slides by Antoine Vigneron Outline linear programming, motivation and definition one dimensional
More informationFrom acute sets to centrally symmetric 2-neighborly polytopes
From acute sets to centrally symmetric -neighborly polytopes Isabella Novik Department of Mathematics University of Washington Seattle, WA 98195-4350, USA novik@math.washington.edu May 1, 018 Abstract
More informationmaximize c, x subject to Ax b,
Lecture 8 Linear programming is about problems of the form maximize c, x subject to Ax b, where A R m n, x R n, c R n, and b R m, and the inequality sign means inequality in each row. The feasible set
More informationGeometry. Every Simplicial Polytope with at Most d + 4 Vertices Is a Quotient of a Neighborly Polytope. U. H. Kortenkamp. 1.
Discrete Comput Geom 18:455 462 (1997) Discrete & Computational Geometry 1997 Springer-Verlag New York Inc. Every Simplicial Polytope with at Most d + 4 Vertices Is a Quotient of a Neighborly Polytope
More informationG 6i try. On the Number of Minimal 1-Steiner Trees* Discrete Comput Geom 12:29-34 (1994)
Discrete Comput Geom 12:29-34 (1994) G 6i try 9 1994 Springer-Verlag New York Inc. On the Number of Minimal 1-Steiner Trees* B. Aronov, 1 M. Bern, 2 and D. Eppstein 3 Computer Science Department, Polytechnic
More informationarxiv: v1 [math.co] 12 Aug 2018
CONVEX UNION REPRESENTABILITY AND CONVEX CODES R. AMZI JEFFS AND ISABELLA NOVIK arxiv:1808.03992v1 [math.co] 12 Aug 2018 Abstract. We introduce and investigate d-convex union representable complexes: the
More information9 Bounds for the Knapsack Problem (March 6)
9 Bounds for the Knapsack Problem (March 6) In this lecture, I ll develop both upper and lower bounds in the linear decision tree model for the following version of the (NP-complete) Knapsack 1 problem:
More informationRay shooting from convex ranges
Discrete Applied Mathematics 108 (2001) 259 267 Ray shooting from convex ranges Evangelos Kranakis a, Danny Krizanc b, Anil Maheshwari a;, Jorg-Rudiger Sack a, Jorge Urrutia c a School of Computer Science,
More informationIn what follows, we will focus on Voronoi diagrams in Euclidean space. Later, we will generalize to other distance spaces.
Voronoi Diagrams 4 A city builds a set of post offices, and now needs to determine which houses will be served by which office. It would be wasteful for a postman to go out of their way to make a delivery
More information4. Simplicial Complexes and Simplicial Homology
MATH41071/MATH61071 Algebraic topology Autumn Semester 2017 2018 4. Simplicial Complexes and Simplicial Homology Geometric simplicial complexes 4.1 Definition. A finite subset { v 0, v 1,..., v r } R n
More informationof a set of n straight lines, have been considered. Among them are k-sets in higher dimensions or k-levels of curves in two dimensions and surfaces in
Point-sets with few k-sets Helmut Alt? Stefan Felsner Ferran Hurtado y Marc Noy y Abstract A k-set of a nite set S of points in the plane is a subset of cardinality k that can be separated from the rest
More informationOn the number of distinct directions of planes determined by n points in R 3
On the number of distinct directions of planes determined by n points in R 3 Rom Pinchasi August 27, 2007 Abstract We show that any set of n points in R 3, that is not contained in a plane, determines
More informationON THE EMPTY CONVEX PARTITION OF A FINITE SET IN THE PLANE**
Chin. Ann. of Math. 23B:(2002),87-9. ON THE EMPTY CONVEX PARTITION OF A FINITE SET IN THE PLANE** XU Changqing* DING Ren* Abstract The authors discuss the partition of a finite set of points in the plane
More informationA PROOF OF THE LOWER BOUND CONJECTURE FOR CONVEX POLYTOPES
PACIFIC JOURNAL OF MATHEMATICS Vol. 46, No. 2, 1973 A PROOF OF THE LOWER BOUND CONJECTURE FOR CONVEX POLYTOPES DAVID BARNETTE A d polytope is defined to be a cz-dimensional set that is the convex hull
More informationIntegral Geometry and the Polynomial Hirsch Conjecture
Integral Geometry and the Polynomial Hirsch Conjecture Jonathan Kelner, MIT Partially based on joint work with Daniel Spielman Introduction n A lot of recent work on Polynomial Hirsch Conjecture has focused
More informationAn Introduction to Computational Geometry: Arrangements and Duality
An Introduction to Computational Geometry: Arrangements and Duality Joseph S. B. Mitchell Stony Brook University Some images from [O Rourke, Computational Geometry in C, 2 nd Edition, Chapter 6] Arrangement
More informationModeling and Analysis of Hybrid Systems
Modeling and Analysis of Hybrid Systems Convex polyhedra Prof. Dr. Erika Ábrahám Informatik 2 - LuFG Theory of Hybrid Systems RWTH Aachen University Szeged, Hungary, 27 September - 06 October 2017 Ábrahám
More informationModeling and Analysis of Hybrid Systems
Modeling and Analysis of Hybrid Systems 6. Convex polyhedra Prof. Dr. Erika Ábrahám Informatik 2 - LuFG Theory of Hybrid Systems RWTH Aachen University Szeged, Hungary, 27 September - 06 October 2017 Ábrahám
More informationarxiv: v1 [cs.cg] 7 Oct 2017
A Proof of the Orbit Conjecture for Flipping Edge-Labelled Triangulations Anna Lubiw 1, Zuzana Masárová 2, and Uli Wagner 2 arxiv:1710.02741v1 [cs.cg] 7 Oct 2017 1 School of Computer Science, University
More informationSimplicial Hyperbolic Surfaces
Simplicial Hyperbolic Surfaces Talk by Ken Bromberg August 21, 2007 1-Lipschitz Surfaces- In this lecture we will discuss geometrically meaningful ways of mapping a surface S into a hyperbolic manifold
More informationShellings, the Euler-Poincaré Formula for Polytopes, Dehn-Sommerville Equations, the Upper Bound Theorem
Chapter 8 Shellings, the Euler-Poincaré Formula for Polytopes, Dehn-Sommerville Equations, the Upper Bound Theorem 8.1 Shellings The notion of shellability is motivated by the desire to give an inductive
More informationRestricted-Orientation Convexity in Higher-Dimensional Spaces
Restricted-Orientation Convexity in Higher-Dimensional Spaces ABSTRACT Eugene Fink Derick Wood University of Waterloo, Waterloo, Ont, Canada N2L3G1 {efink, dwood}@violetwaterlooedu A restricted-oriented
More informationRigid Ball-Polyhedra in Euclidean 3-Space
Discrete Comput Geom (2013) 49:189 199 DOI 10.1007/s00454-012-9480-y Rigid Ball-Polyhedra in Euclidean 3-Space Károly Bezdek Márton Naszódi Received: 15 September 2011 / Revised: 30 September 2012 / Accepted:
More informationRigidity of ball-polyhedra via truncated Voronoi and Delaunay complexes
!000111! NNNiiinnnttthhh IIInnnttteeerrrnnnaaatttiiiooonnnaaalll SSSyyymmmpppooosssiiiuuummm ooonnn VVVooorrrooonnnoooiii DDDiiiaaagggrrraaammmsss iiinnn SSSccciiieeennnccceee aaannnddd EEEnnngggiiinnneeeeeerrriiinnnggg
More informationWeak Dynamic Coloring of Planar Graphs
Weak Dynamic Coloring of Planar Graphs Caroline Accurso 1,5, Vitaliy Chernyshov 2,5, Leaha Hand 3,5, Sogol Jahanbekam 2,4,5, and Paul Wenger 2 Abstract The k-weak-dynamic number of a graph G is the smallest
More informationConvex Geometry arising in Optimization
Convex Geometry arising in Optimization Jesús A. De Loera University of California, Davis Berlin Mathematical School Summer 2015 WHAT IS THIS COURSE ABOUT? Combinatorial Convexity and Optimization PLAN
More informationChapter 11. Line Arrangements
Chapter 11 Line Arrangements During the course of this lecture we encountered several situations where it was convenient to assume that a point set is \in general position". In the plane general position
More informationMath 5593 Linear Programming Lecture Notes
Math 5593 Linear Programming Lecture Notes Unit II: Theory & Foundations (Convex Analysis) University of Colorado Denver, Fall 2013 Topics 1 Convex Sets 1 1.1 Basic Properties (Luenberger-Ye Appendix B.1).........................
More informationThree applications of Euler s formula. Chapter 10
Three applications of Euler s formula Chapter 10 A graph is planar if it can be drawn in the plane R without crossing edges (or, equivalently, on the -dimensional sphere S ). We talk of a plane graph if
More informationWinning Positions in Simplicial Nim
Winning Positions in Simplicial Nim David Horrocks Department of Mathematics and Statistics University of Prince Edward Island Charlottetown, Prince Edward Island, Canada, C1A 4P3 dhorrocks@upei.ca Submitted:
More informationMath 414 Lecture 2 Everyone have a laptop?
Math 44 Lecture 2 Everyone have a laptop? THEOREM. Let v,...,v k be k vectors in an n-dimensional space and A = [v ;...; v k ] v,..., v k independent v,..., v k span the space v,..., v k a basis v,...,
More informationLecture 15: The subspace topology, Closed sets
Lecture 15: The subspace topology, Closed sets 1 The Subspace Topology Definition 1.1. Let (X, T) be a topological space with topology T. subset of X, the collection If Y is a T Y = {Y U U T} is a topology
More informationLecture 12 March 4th
Math 239: Discrete Mathematics for the Life Sciences Spring 2008 Lecture 12 March 4th Lecturer: Lior Pachter Scribe/ Editor: Wenjing Zheng/ Shaowei Lin 12.1 Alignment Polytopes Recall that the alignment
More informationComputational Geometry: Lecture 5
Computational Geometry: Lecture 5 Don Sheehy January 29, 2010 1 Degeneracy In many of the algorithms that we have discussed so far, we have run into problems when that input is somehow troublesome. For
More informationChapter 4 Concepts from Geometry
Chapter 4 Concepts from Geometry An Introduction to Optimization Spring, 2014 Wei-Ta Chu 1 Line Segments The line segment between two points and in R n is the set of points on the straight line joining
More informationPlanarity. 1 Introduction. 2 Topological Results
Planarity 1 Introduction A notion of drawing a graph in the plane has led to some of the most deep results in graph theory. Vaguely speaking by a drawing or embedding of a graph G in the plane we mean
More informationOn the positive semidenite polytope rank
On the positive semidenite polytope rank Davíd Trieb Bachelor Thesis Betreuer: Tim Netzer Institut für Mathematik Universität Innsbruck February 16, 017 On the positive semidefinite polytope rank - Introduction
More information6.2 Classification of Closed Surfaces
Table 6.1: A polygon diagram 6.1.2 Second Proof: Compactifying Teichmuller Space 6.2 Classification of Closed Surfaces We saw that each surface has a triangulation. Compact surfaces have finite triangulations.
More informationNesting points in the sphere. Dan Archdeacon. University of Vermont. Feliu Sagols.
Nesting points in the sphere Dan Archdeacon Dept. of Computer Science University of Vermont Burlington, VT, USA 05405 e-mail: dan.archdeacon@uvm.edu Feliu Sagols Dept. of Computer Science University of
More informationarxiv: v2 [cs.cg] 24 Jul 2011
Ice-Creams and Wedge Graphs Eyal Ackerman Tsachik Gelander Rom Pinchasi Abstract arxiv:116.855v2 [cs.cg] 24 Jul 211 What is the minimum angle α > such that given any set of α-directional antennas (that
More informationTriangulations of Simplicial Polytopes
Beiträge zur Algebra und Geometrie Contributions to Algebra and Geometry Volume 45 (004), No. 1, 37-46. Triangulations of Simplicial Polytopes Peter McMullen University College London Gower Street, London
More informationLet and be a differentiable function. Let Then be the level surface given by
Module 12 : Total differential, Tangent planes and normals Lecture 35 : Tangent plane and normal [Section 35.1] > Objectives In this section you will learn the following : The notion tangent plane to a
More informationEuler s Theorem. Brett Chenoweth. February 26, 2013
Euler s Theorem Brett Chenoweth February 26, 2013 1 Introduction This summer I have spent six weeks of my holidays working on a research project funded by the AMSI. The title of my project was Euler s
More informationExercise set 2 Solutions
Exercise set 2 Solutions Let H and H be the two components of T e and let F E(T ) consist of the edges of T with one endpoint in V (H), the other in V (H ) Since T is connected, F Furthermore, since T
More informationLecture 3. Corner Polyhedron, Intersection Cuts, Maximal Lattice-Free Convex Sets. Tepper School of Business Carnegie Mellon University, Pittsburgh
Lecture 3 Corner Polyhedron, Intersection Cuts, Maximal Lattice-Free Convex Sets Gérard Cornuéjols Tepper School of Business Carnegie Mellon University, Pittsburgh January 2016 Mixed Integer Linear Programming
More informationLecture 3: Convex sets
Lecture 3: Convex sets Rajat Mittal IIT Kanpur We denote the set of real numbers as R. Most of the time we will be working with space R n and its elements will be called vectors. Remember that a subspace
More informationElementary Combinatorial Topology
Elementary Combinatorial Topology Frédéric Meunier Université Paris Est, CERMICS, Ecole des Ponts Paristech, 6-8 avenue Blaise Pascal, 77455 Marne-la-Vallée Cedex E-mail address: frederic.meunier@cermics.enpc.fr
More informationComputational Geometry Lecture Duality of Points and Lines
Computational Geometry Lecture Duality of Points and Lines INSTITUTE FOR THEORETICAL INFORMATICS FACULTY OF INFORMATICS 11.1.2016 Duality Transforms We have seen duality for planar graphs and duality of
More informationCS 372: Computational Geometry Lecture 10 Linear Programming in Fixed Dimension
CS 372: Computational Geometry Lecture 10 Linear Programming in Fixed Dimension Antoine Vigneron King Abdullah University of Science and Technology November 7, 2012 Antoine Vigneron (KAUST) CS 372 Lecture
More informationarxiv: v2 [math.gt] 27 Feb 2014
SIMPLE GAME INDUCED MANIFOLDS PAVEL GALASHIN 1 AND GAIANE PANINA 2 arxiv:1311.6966v2 [math.gt] 27 Feb 2014 Abstract. Starting by a simple game Q as a combinatorial data, we build up a cell complex M(Q),
More informationEXTREME POINTS AND AFFINE EQUIVALENCE
EXTREME POINTS AND AFFINE EQUIVALENCE The purpose of this note is to use the notions of extreme points and affine transformations which are studied in the file affine-convex.pdf to prove that certain standard
More informationL-CONVEX-CONCAVE SETS IN REAL PROJECTIVE SPACE AND L-DUALITY
MOSCOW MATHEMATICAL JOURNAL Volume 3, Number 3, July September 2003, Pages 1013 1037 L-CONVEX-CONCAVE SETS IN REAL PROJECTIVE SPACE AND L-DUALITY A. KHOVANSKII AND D. NOVIKOV Dedicated to Vladimir Igorevich
More information5. THE ISOPERIMETRIC PROBLEM
Math 501 - Differential Geometry Herman Gluck March 1, 2012 5. THE ISOPERIMETRIC PROBLEM Theorem. Let C be a simple closed curve in the plane with length L and bounding a region of area A. Then L 2 4 A,
More informationCS 473: Algorithms. Ruta Mehta. Spring University of Illinois, Urbana-Champaign. Ruta (UIUC) CS473 1 Spring / 29
CS 473: Algorithms Ruta Mehta University of Illinois, Urbana-Champaign Spring 2018 Ruta (UIUC) CS473 1 Spring 2018 1 / 29 CS 473: Algorithms, Spring 2018 Simplex and LP Duality Lecture 19 March 29, 2018
More informationarxiv: v2 [math.co] 23 Jan 2018
CONNECTIVITY OF CUBICAL POLYTOPES HOA THI BUI, GUILLERMO PINEDA-VILLAVICENCIO, AND JULIEN UGON arxiv:1801.06747v2 [math.co] 23 Jan 2018 Abstract. A cubical polytope is a polytope with all its facets being
More informationLecture 5: Duality Theory
Lecture 5: Duality Theory Rajat Mittal IIT Kanpur The objective of this lecture note will be to learn duality theory of linear programming. We are planning to answer following questions. What are hyperplane
More informationVoronoi Diagram. Xiao-Ming Fu
Voronoi Diagram Xiao-Ming Fu Outlines Introduction Post Office Problem Voronoi Diagram Duality: Delaunay triangulation Centroidal Voronoi tessellations (CVT) Definition Applications Algorithms Outlines
More informationCrossing Families. Abstract
Crossing Families Boris Aronov 1, Paul Erdős 2, Wayne Goddard 3, Daniel J. Kleitman 3, Michael Klugerman 3, János Pach 2,4, Leonard J. Schulman 3 Abstract Given a set of points in the plane, a crossing
More informationbe a polytope. has such a representation iff it contains the origin in its interior. For a generic, sort the inequalities so that
( Shelling (Bruggesser-Mani 1971) and Ranking Let be a polytope. has such a representation iff it contains the origin in its interior. For a generic, sort the inequalities so that. a ranking of vertices
More informationLecture 2 - Introduction to Polytopes
Lecture 2 - Introduction to Polytopes Optimization and Approximation - ENS M1 Nicolas Bousquet 1 Reminder of Linear Algebra definitions Let x 1,..., x m be points in R n and λ 1,..., λ m be real numbers.
More informationSmall Survey on Perfect Graphs
Small Survey on Perfect Graphs Michele Alberti ENS Lyon December 8, 2010 Abstract This is a small survey on the exciting world of Perfect Graphs. We will see when a graph is perfect and which are families
More informationChordal graphs and the characteristic polynomial
Discrete Mathematics 262 (2003) 211 219 www.elsevier.com/locate/disc Chordal graphs and the characteristic polynomial Elizabeth W. McMahon ;1, Beth A. Shimkus 2, Jessica A. Wolfson 3 Department of Mathematics,
More informationAn Improved Bound for k-sets in Three Dimensions. November 30, Abstract
An Improved Bound for k-sets in Three Dimensions Micha Sharir Shakhar Smorodinsky y Gabor Tardos z November 30, 1999 Abstract We prove that the maximum number of k-sets in a set S of n points in IR 3 is
More informationCHRISTOS A. ATHANASIADIS
FLAG SUBDIVISIONS AND γ-vectors CHRISTOS A. ATHANASIADIS Abstract. The γ-vector is an important enumerative invariant of a flag simplicial homology sphere. It has been conjectured by Gal that this vector
More informationMa/CS 6b Class 26: Art Galleries and Politicians
Ma/CS 6b Class 26: Art Galleries and Politicians By Adam Sheffer The Art Gallery Problem Problem. We wish to place security cameras at a gallery, such that they cover it completely. Every camera can cover
More informationThe Farey Tessellation
The Farey Tessellation Seminar: Geometric Structures on manifolds Mareike Pfeil supervised by Dr. Gye-Seon Lee 15.12.2015 Introduction In this paper, we are going to introduce the Farey tessellation. Since
More informationK 4 C 5. Figure 4.5: Some well known family of graphs
08 CHAPTER. TOPICS IN CLASSICAL GRAPH THEORY K, K K K, K K, K K, K C C C C 6 6 P P P P P. Graph Operations Figure.: Some well known family of graphs A graph Y = (V,E ) is said to be a subgraph of a graph
More informationTheorem 2.9: nearest addition algorithm
There are severe limits on our ability to compute near-optimal tours It is NP-complete to decide whether a given undirected =(,)has a Hamiltonian cycle An approximation algorithm for the TSP can be used
More informationA GRAPH FROM THE VIEWPOINT OF ALGEBRAIC TOPOLOGY
A GRAPH FROM THE VIEWPOINT OF ALGEBRAIC TOPOLOGY KARL L. STRATOS Abstract. The conventional method of describing a graph as a pair (V, E), where V and E repectively denote the sets of vertices and edges,
More informationProblem Set 3. MATH 776, Fall 2009, Mohr. November 30, 2009
Problem Set 3 MATH 776, Fall 009, Mohr November 30, 009 1 Problem Proposition 1.1. Adding a new edge to a maximal planar graph of order at least 6 always produces both a T K 5 and a T K 3,3 subgraph. Proof.
More informationIn this lecture, we ll look at applications of duality to three problems:
Lecture 7 Duality Applications (Part II) In this lecture, we ll look at applications of duality to three problems: 1. Finding maximum spanning trees (MST). We know that Kruskal s algorithm finds this,
More informationIce-Creams and Wedge Graphs
Ice-Creams and Wedge Graphs Eyal Ackerman Tsachik Gelander Rom Pinchasi Abstract What is the minimum angle α > such that given any set of α-directional antennas (that is, antennas each of which can communicate
More informationBasics of Combinatorial Topology
Chapter 7 Basics of Combinatorial Topology 7.1 Simplicial and Polyhedral Complexes In order to study and manipulate complex shapes it is convenient to discretize these shapes and to view them as the union
More informationLecture 9: Linear Programming
Lecture 9: Linear Programming A common optimization problem involves finding the maximum of a linear function of N variables N Z = a i x i i= 1 (the objective function ) where the x i are all non-negative
More informationNotes in Computational Geometry Voronoi Diagrams
Notes in Computational Geometry Voronoi Diagrams Prof. Sandeep Sen and Prof. Amit Kumar Indian Institute of Technology, Delhi Voronoi Diagrams In this lecture, we study Voronoi Diagrams, also known as
More informationSynthetic Geometry. 1.1 Foundations 1.2 The axioms of projective geometry
Synthetic Geometry 1.1 Foundations 1.2 The axioms of projective geometry Foundations Def: A geometry is a pair G = (Ω, I), where Ω is a set and I a relation on Ω that is symmetric and reflexive, i.e. 1.
More informationMath 443/543 Graph Theory Notes 5: Planar graphs and coloring
Math 443/543 Graph Theory Notes 5: Planar graphs and coloring David Glickenstein October 10, 2014 1 Planar graphs The Three Houses and Three Utilities Problem: Given three houses and three utilities, can
More informationTHE DIMENSION OF POSETS WITH PLANAR COVER GRAPHS
THE DIMENSION OF POSETS WITH PLANAR COVER GRAPHS STEFAN FELSNER, WILLIAM T. TROTTER, AND VEIT WIECHERT Abstract. Kelly showed that there exist planar posets of arbitrarily large dimension, and Streib and
More informationLecture 5: Simplicial Complex
Lecture 5: Simplicial Complex 2-Manifolds, Simplex and Simplicial Complex Scribed by: Lei Wang First part of this lecture finishes 2-Manifolds. Rest part of this lecture talks about simplicial complex.
More informationMath 6510 Homework 3
Notational Note: In any presentation of a group G, I will explicitly set the relation equal to e as opposed to simply writing a presentation like G = a, b, c, d abcd 1. This is a bit untraditional, but
More informationChapter 7. Nearest Point Problems on Simplicial Cones 315 where M is a positive denite symmetric matrix of order n. Let F be a nonsingular matrix such
Chapter 7 NEAREST POINT PROBLEMS ON SIMPLICIAL CONES Let ; = fb. 1 ::: B. n g be a given linearly independent set of column vectors in R n, and let b 2 R n be another given column vector. Let B = (B. 1
More informationCS522: Advanced Algorithms
Lecture 1 CS5: Advanced Algorithms October 4, 004 Lecturer: Kamal Jain Notes: Chris Re 1.1 Plan for the week Figure 1.1: Plan for the week The underlined tools, weak duality theorem and complimentary slackness,
More informationTHREE LECTURES ON BASIC TOPOLOGY. 1. Basic notions.
THREE LECTURES ON BASIC TOPOLOGY PHILIP FOTH 1. Basic notions. Let X be a set. To make a topological space out of X, one must specify a collection T of subsets of X, which are said to be open subsets of
More informationProblem 3.1 (Building up geometry). For an axiomatically built-up geometry, six groups of axioms needed:
Math 3181 Dr. Franz Rothe September 29, 2016 All3181\3181_fall16h3.tex Names: Homework has to be turned in this handout. For extra space, use the back pages, or put blank pages between. The homework can
More information