Intersection Patterns of Curves
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Proofs with Perpendicular Lines
3.4 Proofs with Perpendicular Lines EEssentialssential QQuestionuestion What conjectures can you make about perpendicular lines? Writing Conjectures Work with a partner. Fold a piece of paper D in half twice. Label points on the two creases, as shown. a. Write a conjecture about AB— and CD — . Justify your conjecture. b. Write a conjecture about AO— and OB — . AOB Justify your conjecture. C Exploring a Segment Bisector Work with a partner. Fold and crease a piece A of paper, as shown. Label the ends of the crease as A and B. a. Fold the paper again so that point A coincides with point B. Crease the paper on that fold. b. Unfold the paper and examine the four angles formed by the two creases. What can you conclude about the four angles? B Writing a Conjecture CONSTRUCTING Work with a partner. VIABLE a. Draw AB — , as shown. A ARGUMENTS b. Draw an arc with center A on each To be prof cient in math, side of AB — . Using the same compass you need to make setting, draw an arc with center B conjectures and build a on each side of AB— . Label the C O D logical progression of intersections of the arcs C and D. statements to explore the c. Draw CD — . Label its intersection truth of your conjectures. — with AB as O. Write a conjecture B about the resulting diagram. Justify your conjecture. CCommunicateommunicate YourYour AnswerAnswer 4. What conjectures can you make about perpendicular lines? 5. In Exploration 3, f nd AO and OB when AB = 4 units. -
Some Intersection Theorems for Ordered Sets and Graphs
IOURNAL OF COMBINATORIAL THEORY, Series A 43, 23-37 (1986) Some Intersection Theorems for Ordered Sets and Graphs F. R. K. CHUNG* AND R. L. GRAHAM AT&T Bell Laboratories, Murray Hill, New Jersey 07974 and *Bell Communications Research, Morristown, New Jersey P. FRANKL C.N.R.S., Paris, France AND J. B. SHEARER' Universify of California, Berkeley, California Communicated by the Managing Editors Received May 22, 1984 A classical topic in combinatorics is the study of problems of the following type: What are the maximum families F of subsets of a finite set with the property that the intersection of any two sets in the family satisfies some specified condition? Typical restrictions on the intersections F n F of any F and F’ in F are: (i) FnF’# 0, where all FEF have k elements (Erdos, Ko, and Rado (1961)). (ii) IFn F’I > j (Katona (1964)). In this paper, we consider the following general question: For a given family B of subsets of [n] = { 1, 2,..., n}, what is the largest family F of subsets of [n] satsifying F,F’EF-FnFzB for some BE B. Of particular interest are those B for which the maximum families consist of so- called “kernel systems,” i.e., the family of all supersets of some fixed set in B. For example, we show that the set of all (cyclic) translates of a block of consecutive integers in [n] is such a family. It turns out rather unexpectedly that many of the results we obtain here depend strongly on properties of the well-known entropy function (from information theory). -
Mutant Knots and Intersection Graphs 1 Introduction
Mutant knots and intersection graphs S. V. CHMUTOV S. K. LANDO We prove that if a finite order knot invariant does not distinguish mutant knots, then the corresponding weight system depends on the intersection graph of a chord diagram rather than on the diagram itself. Conversely, if we have a weight system depending only on the intersection graphs of chord diagrams, then the composition of such a weight system with the Kontsevich invariant determines a knot invariant that does not distinguish mutant knots. Thus, an equivalence between finite order invariants not distinguishing mutants and weight systems depending on intersections graphs only is established. We discuss relationship between our results and certain Lie algebra weight systems. 57M15; 57M25 1 Introduction Below, we use standard notions of the theory of finite order, or Vassiliev, invariants of knots in 3-space; their definitions can be found, for example, in [6] or [14], and we recall them briefly in Section 2. All knots are assumed to be oriented. Two knots are said to be mutant if they differ by a rotation of a tangle with four endpoints about either a vertical axis, or a horizontal axis, or an axis perpendicular to the paper. If necessary, the orientation inside the tangle may be replaced by the opposite one. Here is a famous example of mutant knots, the Conway (11n34) knot C of genus 3, and Kinoshita–Terasaka (11n42) knot KT of genus 2 (see [1]). C = KT = Note that the change of the orientation of a knot can be achieved by a mutation in the complement to a trivial tangle. -
Complete Intersection Dimension
PUBLICATIONS MATHÉMATIQUES DE L’I.H.É.S. LUCHEZAR L. AVRAMOV VESSELIN N. GASHAROV IRENA V. PEEVA Complete intersection dimension Publications mathématiques de l’I.H.É.S., tome 86 (1997), p. 67-114 <http://www.numdam.org/item?id=PMIHES_1997__86__67_0> © Publications mathématiques de l’I.H.É.S., 1997, tous droits réservés. L’accès aux archives de la revue « Publications mathématiques de l’I.H.É.S. » (http:// www.ihes.fr/IHES/Publications/Publications.html) implique l’accord avec les conditions géné- rales d’utilisation (http://www.numdam.org/conditions). Toute utilisation commerciale ou im- pression systématique est constitutive d’une infraction pénale. Toute copie ou impression de ce fichier doit contenir la présente mention de copyright. Article numérisé dans le cadre du programme Numérisation de documents anciens mathématiques http://www.numdam.org/ COMPLETE INTERSECTION DIMENSION by LUGHEZAR L. AVRAMOV, VESSELIN N. GASHAROV, and IRENA V. PEEVA (1) Abstract. A new homological invariant is introduced for a finite module over a commutative noetherian ring: its CI-dimension. In the local case, sharp quantitative and structural data are obtained for modules of finite CI- dimension, providing the first class of modules of (possibly) infinite projective dimension with a rich structure theory of free resolutions. CONTENTS Introduction ................................................................................ 67 1. Homological dimensions ................................................................... 70 2. Quantum regular sequences .............................................................. -
And Are Lines on Sphere B That Contain Point Q
11-5 Spherical Geometry Name each of the following on sphere B. 3. a triangle SOLUTION: are examples of triangles on sphere B. 1. two lines containing point Q SOLUTION: and are lines on sphere B that contain point Q. ANSWER: 4. two segments on the same great circle SOLUTION: are segments on the same great circle. ANSWER: and 2. a segment containing point L SOLUTION: is a segment on sphere B that contains point L. ANSWER: SPORTS Determine whether figure X on each of the spheres shown is a line in spherical geometry. 5. Refer to the image on Page 829. SOLUTION: Notice that figure X does not go through the pole of ANSWER: the sphere. Therefore, figure X is not a great circle and so not a line in spherical geometry. ANSWER: no eSolutions Manual - Powered by Cognero Page 1 11-5 Spherical Geometry 6. Refer to the image on Page 829. 8. Perpendicular lines intersect at one point. SOLUTION: SOLUTION: Notice that the figure X passes through the center of Perpendicular great circles intersect at two points. the ball and is a great circle, so it is a line in spherical geometry. ANSWER: yes ANSWER: PERSEVERANC Determine whether the Perpendicular great circles intersect at two points. following postulate or property of plane Euclidean geometry has a corresponding Name two lines containing point M, a segment statement in spherical geometry. If so, write the containing point S, and a triangle in each of the corresponding statement. If not, explain your following spheres. reasoning. 7. The points on any line or line segment can be put into one-to-one correspondence with real numbers. -
Intersection of Convex Objects in Two and Three Dimensions
Intersection of Convex Objects in Two and Three Dimensions B. CHAZELLE Yale University, New Haven, Connecticut AND D. P. DOBKIN Princeton University, Princeton, New Jersey Abstract. One of the basic geometric operations involves determining whether a pair of convex objects intersect. This problem is well understood in a model of computation in which the objects are given as input and their intersection is returned as output. For many applications, however, it may be assumed that the objects already exist within the computer and that the only output desired is a single piece of data giving a common point if the objects intersect or reporting no intersection if they are disjoint. For this problem, none of the previous lower bounds are valid and algorithms are proposed requiring sublinear time for their solution in two and three dimensions. Categories and Subject Descriptors: E.l [Data]: Data Structures; F.2.2 [Analysis of Algorithms]: Nonnumerical Algorithms and Problems General Terms: Algorithms, Theory, Verification Additional Key Words and Phrases: Convex sets, Fibonacci search, Intersection 1. Introduction This paper describes fast algorithms for testing the predicate, Do convex objects P and Q intersect? where an object is taken to be a line or a polygon in two dimensions or a plane or a polyhedron in three dimensions. The related problem Given convex objects P and Q, compute their intersection has been well studied, resulting in linear lower bounds and linear or quasi-linear upper bounds [2, 4, 11, 15-171. Lower bounds for this problem use arguments This research was supported in part by the National Science Foundation under grants MCS 79-03428, MCS 81-14207, MCS 83-03925, and MCS 83-03926, and by the Defense Advanced Project Agency under contract F33615-78-C-1551, monitored by the Air Force Offtce of Scientific Research. -
Representations of Edge Intersection Graphs of Paths in a Tree Martin Charles Golumbic, Marina Lipshteyn, Michal Stern
Representations of Edge Intersection Graphs of Paths in a Tree Martin Charles Golumbic, Marina Lipshteyn, Michal Stern To cite this version: Martin Charles Golumbic, Marina Lipshteyn, Michal Stern. Representations of Edge Intersection Graphs of Paths in a Tree. 2005 European Conference on Combinatorics, Graph Theory and Appli- cations (EuroComb ’05), 2005, Berlin, Germany. pp.87-92. hal-01184396 HAL Id: hal-01184396 https://hal.inria.fr/hal-01184396 Submitted on 14 Aug 2015 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. EuroComb 2005 DMTCS proc. AE, 2005, 87–92 Representations of Edge Intersection Graphs of Paths in a Tree Martin Charles Golumbic1,† Marina Lipshteyn1 and Michal Stern1 1Caesarea Rothschild Institute, University of Haifa, Haifa, Israel Let P be a collection of nontrivial simple paths in a tree T . The edge intersection graph of P, denoted by EP T (P), has vertex set that corresponds to the members of P, and two vertices are joined by an edge if the corresponding members of P share a common edge in T . An undirected graph G is called an edge intersection graph of paths in a tree, if G = EP T (P) for some P and T . -
Complex Intersection Bodies
COMPLEX INTERSECTION BODIES A. KOLDOBSKY, G. PAOURIS, AND M. ZYMONOPOULOU Abstract. We introduce complex intersection bodies and show that their properties and applications are similar to those of their real counterparts. In particular, we generalize Busemann's the- orem to the complex case by proving that complex intersection bodies of symmetric complex convex bodies are also convex. Other results include stability in the complex Busemann-Petty problem for arbitrary measures and the corresponding hyperplane inequal- ity for measures of complex intersection bodies. 1. Introduction The concept of an intersection body was introduced by Lutwak [37], as part of his dual Brunn-Minkowski theory. In particular, these bodies played an important role in the solution of the Busemann-Petty prob- lem. Many results on intersection bodies have appeared in recent years (see [10, 22, 34] and references there), but almost all of them apply to the real case. The goal of this paper is to extend the concept of an intersection body to the complex case. Let K and L be origin symmetric star bodies in Rn: Following [37], we say that K is the intersection body of L if the radius of K in every direction is equal to the volume of the central hyperplane section of L perpendicular to this direction, i.e. for every ξ 2 Sn−1; −1 ? kξkK = jL \ ξ j; (1) ? n where kxkK = minfa ≥ 0 : x 2 aKg, ξ = fx 2 R :(x; ξ) = 0g; and j · j stands for volume. By a theorem of Busemann [8] the intersection body of an origin symmetric convex body is also convex. -
NP-Complete and Cliques
CSC373— Algorithm Design, Analysis, and Complexity — Spring 2018 Tutorial Exercise 10: Cliques and Intersection Graphs for Intervals 1. Clique. Given an undirected graph G = (V,E) a clique (pronounced “cleek” in Canadian, heh?) is a subset of vertices K ⊆ V such that, for every pair of distinct vertices u,v ∈ K, the edge (u,v) is in E. See Clique, Graph Theory, Wikipedia. A second concept that will be useful is the notion of a complement graph Gc. We say Gc is the complement (graph) of G = (V,E) iff Gc = (V,Ec), where Ec = {(u,v) | u,v ∈ V,u 6= v, and (u,v) ∈/ E} (see Complement Graph, Wikipedia). That is, the complement graph Gc is the graph over the same set of vertices, but it contains all (and only) the edges that are not in E. Finally, a clique K ⊂ V of G =(V,E) is said to be a maximal clique iff there is no superset W such that K ⊂ W ⊆ V and W is a clique of G. Consider the decision problem: Clique: Given an undirected graph and an integer k, does there exist a clique K of G with |K|≥ k? Clearly, Clique is in NP. We wish to show that Clique is NP-complete. To do this, it is convenient to first note that the independent set problem IndepSet(G, k) is very closely related to the Clique problem for the complement graph, i.e., Clique(Gc,k). Use this strategy to show: IndepSet ≡p Clique. (1) 2. Consider the interval scheduling problem we started this course with (which is also revisited in Assignment 3, Question 1). -
Points, Lines, and Planes a Point Is a Position in Space. a Point Has No Length Or Width Or Thickness
Points, Lines, and Planes A Point is a position in space. A point has no length or width or thickness. A point in geometry is represented by a dot. To name a point, we usually use a (capital) letter. A A (straight) line has length but no width or thickness. A line is understood to extend indefinitely to both sides. It does not have a beginning or end. A B C D A line consists of infinitely many points. The four points A, B, C, D are all on the same line. Postulate: Two points determine a line. We name a line by using any two points on the line, so the above line can be named as any of the following: ! ! ! ! ! AB BC AC AD CD Any three or more points that are on the same line are called colinear points. In the above, points A; B; C; D are all colinear. A Ray is part of a line that has a beginning point, and extends indefinitely to one direction. A B C D A ray is named by using its beginning point with another point it contains. −! −! −−! −−! In the above, ray AB is the same ray as AC or AD. But ray BD is not the same −−! ray as AD. A (line) segment is a finite part of a line between two points, called its end points. A segment has a finite length. A B C D B C In the above, segment AD is not the same as segment BC Segment Addition Postulate: In a line segment, if points A; B; C are colinear and point B is between point A and point C, then AB + BC = AC You may look at the plus sign, +, as adding the length of the segments as numbers. -
INTERSECTION GEOMETRY Learning Outcomes
INTERSECTION GEOMETRY Learning Outcomes 5-2 At the end of this module, you will be able to: 1. Explain why tight/right angle intersections are best 2. Describe why pedestrians need access to all corners 3. Assess good crosswalk placement: where peds want to cross & where drivers can see them 4. Explain how islands can break up complex intersections Designing for Pedestrian Safety – Intersection Geometry Intersection Crashes Some basic facts: 5-3 1. Most (urban) crashes occur at intersections 2. 40% occur at signalized intersections 3. Most are associated with turning movements 4. Geometry matters: keeping intersections tight, simple & slow speed make them safer for everyone Designing for Pedestrian Safety – Intersection Geometry 5-4 Philadelphia PA Small, tight intersections best for pedestrians… Simple, few conflicts, slow speeds Designing for Pedestrian Safety – Intersection Geometry 5-5 Atlanta GA Large intersections can work for pedestrians with mitigation Designing for Pedestrian Safety – Intersection Geometry Skewed intersections 5-6 Skew increases crossing distance & speed of turning cars Designing for Pedestrian Safety – Intersection Geometry 5-7 Philadelphia PA Cars can turn at high speed Designing for Pedestrian Safety – Intersection Geometry 5-8 Skew increases crosswalk length, decreases visibility Designing for Pedestrian Safety – Intersection Geometry 5-9 Right angle decreases crosswalk length, increases visibility Designing for Pedestrian Safety – Intersection Geometry 5-10 Bend OR Skewed intersection reduces visibility Driver -
On Intersection Graphs of Graphs and Hypergraphs: a Survey
Intersection Graphs of Graphs and Hypergraphs: A Survey Ranjan N. Naika aDepartment of Mathematics, Lincoln University, PA, USA [email protected] Abstract The survey is devoted to the developmental milestones on the characterizations of intersection graphs of graphs and hypergraphs. The theory of intersection graphs of graphs and hypergraphs has been a classical topic in the theory of special graphs. To conclude, at the end, we have listed some open problems posed by various authors whose work has contributed to this survey and also the new trends coming out of intersection graphs of hyeprgraphs. Keywords: Hypergraphs, Intersection graphs, Line graphs, Representative graphs, Derived graphs, Algorithms (ALG),, Forbidden induced subgraphs (FIS), Krausz partitions, Eigen values Mathematics Subject Classification : 06C62, 05C65, 05C75, 05C85, 05C69 1. Introduction We follow the terminology of Berge, C. [3] and [4]. This survey does not address intersection graphs of other types of graphs such as interval graphs etc. An introduction of intersection graphs of interval graphs etc. are available in Pal [40]. A graph or a hypergraph is a pair (V, E), where V is the vertex set and E is the edge set a family of nonempty subsets of V. Two edges of a hypergraph are l -intersecting if they share at least l common vertices. This concept was studied in [6] and [18] by Bermond, Heydemann and Sotteau. A hypergraph H is called a k-uniform hypergraph if its edges have k number of vertices. A hypergraph is linear if any two edges have at most one common vertex. A 2-uniform linear hypergraph is called a graph or a linear graph.