Quadrisecants Give New Lower Bounds for the Ropelength of a Knot
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The Borromean Rings: a Video About the New IMU Logo
The Borromean Rings: A Video about the New IMU Logo Charles Gunn and John M. Sullivan∗ Technische Universitat¨ Berlin Institut fur¨ Mathematik, MA 3–2 Str. des 17. Juni 136 10623 Berlin, Germany Email: {gunn,sullivan}@math.tu-berlin.de Abstract This paper describes our video The Borromean Rings: A new logo for the IMU, which was premiered at the opening ceremony of the last International Congress. The video explains some of the mathematics behind the logo of the In- ternational Mathematical Union, which is based on the tight configuration of the Borromean rings. This configuration has pyritohedral symmetry, so the video includes an exploration of this interesting symmetry group. Figure 1: The IMU logo depicts the tight config- Figure 2: A typical diagram for the Borromean uration of the Borromean rings. Its symmetry is rings uses three round circles, with alternating pyritohedral, as defined in Section 3. crossings. In the upper corners are diagrams for two other three-component Brunnian links. 1 The IMU Logo and the Borromean Rings In 2004, the International Mathematical Union (IMU), which had never had a logo, announced a competition to design one. The winning entry, shown in Figure 1, was designed by one of us (Sullivan) with help from Nancy Wrinkle. It depicts the Borromean rings, not in the usual diagram (Figure 2) but instead in their tight configuration, the shape they have when tied tight in thick rope. This IMU logo was unveiled at the opening ceremony of the International Congress of Mathematicians (ICM 2006) in Madrid. We were invited to produce a short video [10] about some of the mathematics behind the logo; it was shown at the opening and closing ceremonies, and can be viewed at www.isama.org/jms/Videos/imu/. -
Robot Vision: Projective Geometry
Robot Vision: Projective Geometry Ass.Prof. Friedrich Fraundorfer SS 2018 1 Learning goals . Understand homogeneous coordinates . Understand points, line, plane parameters and interpret them geometrically . Understand point, line, plane interactions geometrically . Analytical calculations with lines, points and planes . Understand the difference between Euclidean and projective space . Understand the properties of parallel lines and planes in projective space . Understand the concept of the line and plane at infinity 2 Outline . 1D projective geometry . 2D projective geometry ▫ Homogeneous coordinates ▫ Points, Lines ▫ Duality . 3D projective geometry ▫ Points, Lines, Planes ▫ Duality ▫ Plane at infinity 3 Literature . Multiple View Geometry in Computer Vision. Richard Hartley and Andrew Zisserman. Cambridge University Press, March 2004. Mundy, J.L. and Zisserman, A., Geometric Invariance in Computer Vision, Appendix: Projective Geometry for Machine Vision, MIT Press, Cambridge, MA, 1992 . Available online: www.cs.cmu.edu/~ph/869/papers/zisser-mundy.pdf 4 Motivation – Image formation [Source: Charles Gunn] 5 Motivation – Parallel lines [Source: Flickr] 6 Motivation – Epipolar constraint X world point epipolar plane x x’ x‘TEx=0 C T C’ R 7 Euclidean geometry vs. projective geometry Definitions: . Geometry is the teaching of points, lines, planes and their relationships and properties (angles) . Geometries are defined based on invariances (what is changing if you transform a configuration of points, lines etc.) . Geometric transformations -
COMBINATORICS, Volume
http://dx.doi.org/10.1090/pspum/019 PROCEEDINGS OF SYMPOSIA IN PURE MATHEMATICS Volume XIX COMBINATORICS AMERICAN MATHEMATICAL SOCIETY Providence, Rhode Island 1971 Proceedings of the Symposium in Pure Mathematics of the American Mathematical Society Held at the University of California Los Angeles, California March 21-22, 1968 Prepared by the American Mathematical Society under National Science Foundation Grant GP-8436 Edited by Theodore S. Motzkin AMS 1970 Subject Classifications Primary 05Axx, 05Bxx, 05Cxx, 10-XX, 15-XX, 50-XX Secondary 04A20, 05A05, 05A17, 05A20, 05B05, 05B15, 05B20, 05B25, 05B30, 05C15, 05C99, 06A05, 10A45, 10C05, 14-XX, 20Bxx, 20Fxx, 50A20, 55C05, 55J05, 94A20 International Standard Book Number 0-8218-1419-2 Library of Congress Catalog Number 74-153879 Copyright © 1971 by the American Mathematical Society Printed in the United States of America All rights reserved except those granted to the United States Government May not be produced in any form without permission of the publishers Leo Moser (1921-1970) was active and productive in various aspects of combin• atorics and of its applications to number theory. He was in close contact with those with whom he had common interests: we will remember his sparkling wit, the universality of his anecdotes, and his stimulating presence. This volume, much of whose content he had enjoyed and appreciated, and which contains the re• construction of a contribution by him, is dedicated to his memory. CONTENTS Preface vii Modular Forms on Noncongruence Subgroups BY A. O. L. ATKIN AND H. P. F. SWINNERTON-DYER 1 Selfconjugate Tetrahedra with Respect to the Hermitian Variety xl+xl + *l + ;cg = 0 in PG(3, 22) and a Representation of PG(3, 3) BY R. -
Arxiv:1502.03029V2 [Math.GT] 16 Apr 2015 De.Then Edges
COUNTING GENERIC QUADRISECANTS OF POLYGONAL KNOTS ALDO-HILARIO CRUZ-COTA, TERESITA RAMIREZ-ROSAS Abstract. Let K be a polygonal knot in general position with vertex set V . A generic quadrisecant of K is a line that is disjoint from the set V and intersects K in exactly four distinct points. We give an upper bound for the number of generic quadrisecants of a polygonal knot K in general position. This upper bound is in terms of the number of edges of K. 1. Introduction In this article, we study polygonal knots in three dimensional space that are in general position. Given such a knot K, we define a quadrisecant of K as an unoriented line that intersects K in exactly four distinct points. We require that these points are not vertices of the knot, in which case we say that the quadrisecant is generic. Using geometric and combinatorial arguments, we give an upper bound for the number of generic quadrisecants of a polygonal knot K in general position. This bound is in terms of the number n ≥ 3 of edges of K. More precisely, we prove the following. Main Theorem 1. Let K be a polygonal knot in general position, with exactly n n edges. Then K has at most U = (n − 3)(n − 4)(n − 5) generic quadrisecants. n 12 Applying Main Theorem 1 to polygonal knots with few edges, we obtain the following. (1) If n ≤ 5, then K has no generic quadrisecant. (2) If n = 6, then K has at most three generic quadrisecants. (3) If n = 7, then K has at most 14 generic quadrisecants. -
Performance Evaluation of Genetic Algorithm and Simulated Annealing in Solving Kirkman Schoolgirl Problem
FUOYE Journal of Engineering and Technology (FUOYEJET), Vol. 5, Issue 2, September 2020 ISSN: 2579-0625 (Online), 2579-0617 (Paper) Performance Evaluation of Genetic Algorithm and Simulated Annealing in solving Kirkman Schoolgirl Problem *1Christopher A. Oyeleye, 2Victoria O. Dayo-Ajayi, 3Emmanuel Abiodun and 4Alabi O. Bello 1Department of Information Systems, Ladoke Akintola University of Technology, Ogbomoso, Nigeria 2Department of Computer Science, Ladoke Akintola University of Technology, Ogbomoso, Nigeria 3Department of Computer Science, Kwara State Polytechnic, Ilorin, Nigeria 4Department of Mathematical and Physical Sciences, Afe Babalola University, Ado-Ekiti, Nigeria [email protected]|[email protected]|[email protected]|[email protected] Received: 15-FEB-2020; Reviewed: 12-MAR-2020; Accepted: 28-MAY-2020 http://dx.doi.org/10.46792/fuoyejet.v5i2.477 Abstract- This paper provides performance evaluation of Genetic Algorithm and Simulated Annealing in view of their software complexity and simulation runtime. Kirkman Schoolgirl is about arranging fifteen schoolgirls into five triplets in a week with a distinct constraint of no two schoolgirl must walk together in a week. The developed model was simulated using MATLAB version R2015a. The performance evaluation of both Genetic Algorithm (GA) and Simulated Annealing (SA) was carried out in terms of program size, program volume, program effort and the intelligent content of the program. The results obtained show that the runtime for GA and SA are 11.23sec and 6.20sec respectively. The program size for GA and SA are 2.01kb and 2.21kb, respectively. The lines of code for GA and SA are 324 and 404, respectively. The program volume for GA and SA are 1121.58 and 3127.92, respectively. -
Blocking Set Free Configurations and Their Relations to Digraphs and Hypergraphs
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector DISCRETE MATHEMATICS ELSIZI’IER Discrete Mathematics 1651166 (1997) 359.-370 Blocking set free configurations and their relations to digraphs and hypergraphs Harald Gropp* Mihlingstrasse 19. D-69121 Heidelberg, German> Abstract The current state of knowledge concerning the existence of blocking set free configurations is given together with a short history of this problem which has also been dealt with in terms of digraphs without even dicycles or 3-chromatic hypergraphs. The question is extended to the case of nonsymmetric configurations (u,, b3). It is proved that for each value of I > 3 there are only finitely many values of u for which the existence of a blocking set free configuration is still unknown. 1. Introduction In the language of configurations the existence of blocking sets was investigated in [3, 93 for the first time. Further papers [4, 201 yielded the result that the existence problem for blocking set free configurations v3 has been nearly solved. There are only 8 values of v for which it is unsettled whether there is a blocking set free configuration ~7~:u = 15,16,17,18,20,23,24,26. The existence of blocking set free configurations is equivalent to the existence of certain hypergraphs and digraphs. In these two languages results have been obtained much earlier. In Section 2 the relations between configurations, hypergraphs, and digraphs are exhibited. Furthermore, a nearly forgotten result of Steinitz is described In his dissertation of 1894 Steinitz proved the existence of a l-factor in a regular bipartite graph 20 years earlier then Kiinig. -
1 Introduction
Contents | 1 1 Introduction Is the “cable spaghetti” on the floor really knotted or is it enough to pull on both ends of the wire to completely unfold it? Since its invention, knot theory has always been a place of interdisciplinarity. The first knot tables composed by Tait have been motivated by Lord Kelvin’s theory of atoms. But it was not until a century ago that tools for rigorously distinguishing the trefoil and its mirror image as members of two different knot classes were derived. In the first half of the twentieth century, knot theory seemed to be a place mainly drivenby algebraic and combinatorial arguments, mentioning the contributions of Alexander, Reidemeister, Seifert, Schubert, and many others. Besides the development of higher dimensional knot theory, the search for new knot invariants has been a major endeav- our since about 1960. At the same time, connections to applications in DNA biology and statistical physics have surfaced. DNA biology had made a huge progress and it was well un- derstood that the topology of DNA strands matters: modeling of the interplay between molecules and enzymes such as topoisomerases necessarily involves notions of ‘knot- tedness’. Any configuration involving long strands or flexible ropes with a relatively small diameter leads to a mathematical model in terms of curves. Therefore knots appear almost naturally in this context and require techniques from algebra, (differential) geometry, analysis, combinatorics, and computational mathematics. The discovery of the Jones polynomial in 1984 has led to the great popularity of knot theory not only amongst mathematicians and stimulated many activities in this direction. -
Self-Dual Configurations and Regular Graphs
SELF-DUAL CONFIGURATIONS AND REGULAR GRAPHS H. S. M. COXETER 1. Introduction. A configuration (mci ni) is a set of m points and n lines in a plane, with d of the points on each line and c of the lines through each point; thus cm = dn. Those permutations which pre serve incidences form a group, "the group of the configuration." If m — n, and consequently c = d, the group may include not only sym metries which permute the points among themselves but also reci procities which interchange points and lines in accordance with the principle of duality. The configuration is then "self-dual," and its symbol («<*, n<j) is conveniently abbreviated to na. We shall use the same symbol for the analogous concept of a configuration in three dimensions, consisting of n points lying by d's in n planes, d through each point. With any configuration we can associate a diagram called the Menger graph [13, p. 28],x in which the points are represented by dots or "nodes," two of which are joined by an arc or "branch" when ever the corresponding two points are on a line of the configuration. Unfortunately, however, it often happens that two different con figurations have the same Menger graph. The present address is concerned with another kind of diagram, which represents the con figuration uniquely. In this Levi graph [32, p. 5], we represent the points and lines (or planes) of the configuration by dots of two colors, say "red nodes" and "blue nodes," with the rule that two nodes differently colored are joined whenever the corresponding elements of the configuration are incident. -
Geometry and Dynamics of Configuration Spaces Mickaël Kourganoff
Geometry and dynamics of configuration spaces Mickaël Kourganoff To cite this version: Mickaël Kourganoff. Geometry and dynamics of configuration spaces. Differential Geometry [math.DG]. Ecole normale supérieure de lyon - ENS LYON, 2015. English. NNT : 2015ENSL1049. tel-01250817 HAL Id: tel-01250817 https://tel.archives-ouvertes.fr/tel-01250817 Submitted on 5 Jan 2016 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. These` en vue de l’obtention du grade de Docteur de l’Universit´ede Lyon, d´elivr´epar l’Ecole´ Normale Sup´erieurede Lyon Discipline : Math´ematiques pr´esent´eeet soutenue publiquement le 4 d´ecembre 2015 par Micka¨el Kourganoff G´eom´etrieet dynamique des espaces de configuration Directeur de th`ese: Abdelghani Zeghib Devant la commission d’examen form´eede : Viviane Baladi (Universit´ePierre et Marie Curie, Paris), examinatrice Thierry Barbot (Universit´ed’Avignon), rapporteur G´erard Besson (Universit´ede Grenoble), examinateur Etienne´ Ghys( Ecole´ Normale Sup´erieure de Lyon), examinateur Boris Hasselblatt (Tufts University), rapporteur Mark Pollicott (University of Warwick), rapporteur BrunoS evennec´ ( Ecole´ Normale Sup´erieure de Lyon), examinateur Abdelghani Zeghib( Ecole´ Normale Sup´erieure de Lyon), directeur Unit´ede Math´ematiques Pures et Appliqu´ees– Ecole´ doctorale InfoMaths 2 Remerciements Mes premiers remerciements vont `aGhani, qui m’a fait d´ecouvrir un sujet passionnant, riche et original, et m’a laiss´eune grande libert´e,tout en sachant s’impliquer dans le d´etaild`esque n´ecessaire. -
Introduction to Geometric Knot Theory 2: Ropelength and Tight Knots
Introduction to Geometric Knot Theory 2: Ropelength and Tight Knots Jason Cantarella University of Georgia ICTP Knot Theory Summer School, Trieste, 2009 Review from first lecture: Definition (Federer 1959) The reach of a space curve is the largest so that any point in an -neighborhood of the curve has a unique nearest neighbor on the curve. Idea reach(K ) (also called thickness) is controlled by curvature maxima (kinks) and self-distance minima (struts). Cantarella Geometric Knot Theory Ropelength Definition The ropelength of K is given by Rop(K ) = Len(K )/ reach(K ). Theorem (with Kusner, Sullivan 2002, Gonzalez, De la Llave 2003, Gonzalez, Maddocks, Schuricht, Von der Mosel 2002) Ropelength minimizers (called tight knots) exist in each knot and link type and are C1,1. We can bound Rop in terms of Cr. Cantarella Geometric Knot Theory Ropelength Definition The ropelength of K is given by Rop(K ) = Len(K )/ reach(K ). Theorem (with Kusner, Sullivan 2002, Gonzalez, De la Llave 2003, Gonzalez, Maddocks, Schuricht, Von der Mosel 2002) Ropelength minimizers (called tight knots) exist in each knot and link type and are C1,1. We can bound Rop in terms of Cr. Cantarella Geometric Knot Theory Ropelength Definition The ropelength of K is given by Rop(K ) = Len(K )/ reach(K ). Theorem (with Kusner, Sullivan 2002, Gonzalez, De la Llave 2003, Gonzalez, Maddocks, Schuricht, Von der Mosel 2002) Ropelength minimizers (called tight knots) exist in each knot and link type and are C1,1. We can bound Rop in terms of Cr. Cantarella Geometric Knot Theory Ropelength Definition The ropelength of K is given by Rop(K ) = Len(K )/ reach(K ). -
Total Curvature, Ropelength and Crossing Number of Thick Knots
Total Curvature, Ropelength and Crossing Number of Thick Knots Yuanan Diao and Claus Ernst Abstract. We first study the minimum total curvature of a knot when it is embedded on the cubic lattice. Let K be a knot or link with a lattice embedding of minimum total curvature ¿(K) among all possible lattice embeddingsp of K. We show that there exist positive constants c1 and c2 such that c1 Cr(K) · ¿(K) · c2Cr(K) for any knot type K. Furthermore we show that the powers of Cr(K) in the above inequalities are sharp hence cannot be improved in general. Our results and observations show that lattice embeddings with minimum total curvature are quite different from those with minimum or near minimum lattice embedding length. In addition, we discuss the relationship between minimal total curvature and minimal ropelength for a given knot type. At the end of the paper, we study the total curvatures of smooth thick knots and show that there are some essential differences between the total curvatures of smooth thick knots and lattice knots. 1. Introduction An essential field in the area of geometric knot theory concerns questions about the behavior of thick knots. One such question is about the ropelength of a knot. That is, if we are to tie a given knot with a rope of unit thickness, how long does the rope needs to be? In particular, for a given knot K whose crossing number is Cr(K), can we express the ropelength L(K) of K as a function of Cr(K)? Or alternatively, can we find a lower and upper bound of L(K) in terms of Cr(K)? For a general lower bound, it is shown in [3, 4] that there exists a constant a > 0 such that for any knot type K, L(K) ¸ a ¢ (Cr(K))3=4. -
Intel® MAX® 10 FPGA Configuration User Guide
Intel® MAX® 10 FPGA Configuration User Guide Subscribe UG-M10CONFIG | 2021.07.02 Send Feedback Latest document on the web: PDF | HTML Contents Contents 1. Intel® MAX® 10 FPGA Configuration Overview................................................................ 4 2. Intel MAX 10 FPGA Configuration Schemes and Features...............................................5 2.1. Configuration Schemes..........................................................................................5 2.1.1. JTAG Configuration.................................................................................... 5 2.1.2. Internal Configuration................................................................................ 6 2.2. Configuration Features.........................................................................................13 2.2.1. Remote System Upgrade...........................................................................13 2.2.2. Configuration Design Security....................................................................20 2.2.3. SEU Mitigation and Configuration Error Detection........................................ 24 2.2.4. Configuration Data Compression................................................................ 27 2.3. Configuration Details............................................................................................ 28 2.3.1. Configuration Sequence............................................................................ 28 2.3.2. Intel MAX 10 Configuration Pins................................................................