Edge Bounds and Degeneracy of Triangle-Free Penny Graphs and Squaregraphs
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Knowledge Spaces Applications in Education Knowledge Spaces
Jean-Claude Falmagne · Dietrich Albert Christopher Doble · David Eppstein Xiangen Hu Editors Knowledge Spaces Applications in Education Knowledge Spaces Jean-Claude Falmagne • Dietrich Albert Christopher Doble • David Eppstein • Xiangen Hu Editors Knowledge Spaces Applications in Education Editors Jean-Claude Falmagne Dietrich Albert School of Social Sciences, Department of Psychology Dept. Cognitive Sciences University of Graz University of California, Irvine Graz, Austria Irvine, CA, USA Christopher Doble David Eppstein ALEKS Corporation Donald Bren School of Information Irvine, CA, USA & Computer Sciences University of California, Irvine Irvine, CA, USA Xiangen Hu Department of Psychology University of Memphis Memphis, TN, USA ISBN 978-3-642-35328-4 ISBN 978-3-642-35329-1 (eBook) DOI 10.1007/978-3-642-35329-1 Springer Heidelberg New York Dordrecht London Library of Congress Control Number: 2013942001 © Springer-Verlag Berlin Heidelberg 2013 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher’s location, in its current version, and permission for use must always be obtained from Springer. -
Drawing Graphs and Maps with Curves
Report from Dagstuhl Seminar 13151 Drawing Graphs and Maps with Curves Edited by Stephen Kobourov1, Martin Nöllenburg2, and Monique Teillaud3 1 University of Arizona – Tucson, US, [email protected] 2 KIT – Karlsruhe Institute of Technology, DE, [email protected] 3 INRIA Sophia Antipolis – Méditerranée, FR, [email protected] Abstract This report documents the program and the outcomes of Dagstuhl Seminar 13151 “Drawing Graphs and Maps with Curves”. The seminar brought together 34 researchers from different areas such as graph drawing, information visualization, computational geometry, and cartography. During the seminar we started with seven overview talks on the use of curves in the different communities represented in the seminar. Abstracts of these talks are collected in this report. Six working groups formed around open research problems related to the seminar topic and we report about their findings. Finally, the seminar was accompanied by the art exhibition Bending Reality: Where Arc and Science Meet with 40 exhibits contributed by the seminar participants. Seminar 07.–12. April, 2013 – www.dagstuhl.de/13151 1998 ACM Subject Classification I.3.5 Computational Geometry and Object Modeling, G.2.2 Graph Theory, F.2.2 Nonnumerical Algorithms and Problems Keywords and phrases graph drawing, information visualization, computational cartography, computational geometry Digital Object Identifier 10.4230/DagRep.3.4.34 Edited in cooperation with Benjamin Niedermann 1 Executive Summary Stephen Kobourov Martin Nöllenburg Monique Teillaud License Creative Commons BY 3.0 Unported license © Stephen Kobourov, Martin Nöllenburg, and Monique Teillaud Graphs and networks, maps and schematic map representations are frequently used in many fields of science, humanities and the arts. -
Degenerate Eigenvalue Problem 32.1 Degenerate Perturbation
Physics 342 Lecture 32 Degenerate Eigenvalue Problem Lecture 32 Physics 342 Quantum Mechanics I Wednesday, April 23rd, 2008 We have the matrix form of the first order perturbative result from last time. This carries over pretty directly to the Schr¨odingerequation, with only minimal replacement (the inner product and finite vector space change, but notationally, the results are identical). Because there are a variety of quantum mechanical systems with degenerate spectra (like the Hydrogen 2 eigenstates, each En has n associated eigenstates) and we want to be able to predict the energy shift associated with perturbations in these systems, we can copy our arguments for matrices to cover matrices with more than one eigenvector per eigenvalue. The punch line of that program is that we can use the non-degenerate perturbed energies, provided we start with the \correct" degenerate linear combinations. 32.1 Degenerate Perturbation N×N Going back to our symmetric matrix example, we have A IR , and 2 again, a set of eigenvectors and eigenvalues: A xi = λi xi. This time, suppose that the eigenvalue λi has a set of M associated eigenvectors { that is, suppose a set of eigenvectors yj satisfy: A yj = λi yj j = 1 M (32.1) −! 1 of 9 32.1. DEGENERATE PERTURBATION Lecture 32 (so this represents M separate equations) that are themselves orthonormal1. Clearly, any linear combination of these vectors is also an eigenvector: M M X X A βk yk = λi βk yk: (32.2) k=1 k=1 M PM Define the general combination of yi to be z βk yk, also an f gi=1 ≡ k=1 eigenvector of A with eigenvalue λi. -
DEGENERACY CURVES, GAPS, and DIABOLICAL POINTS in the SPECTRA of NEUMANN PARALLELOGRAMS P Overfelt
DEGENERACY CURVES, GAPS, AND DIABOLICAL POINTS IN THE SPECTRA OF NEUMANN PARALLELOGRAMS P Overfelt To cite this version: P Overfelt. DEGENERACY CURVES, GAPS, AND DIABOLICAL POINTS IN THE SPECTRA OF NEUMANN PARALLELOGRAMS. 2020. hal-03017250 HAL Id: hal-03017250 https://hal.archives-ouvertes.fr/hal-03017250 Preprint submitted on 20 Nov 2020 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. DEGENERACY CURVES, GAPS, AND DIABOLICAL POINTS IN THE SPECTRA OF NEUMANN PARALLELOGRAMS P. L. OVERFELT Abstract. In this paper we consider the problem of solving the Helmholtz equation over the space of all parallelograms subject to Neumann boundary conditions and determining the degeneracies occurring in their spectra upon changing the two parameters, angle and side ratio. This problem is solved numerically using the finite element method (FEM). Specifically for the lowest eleven normalized eigenvalue levels of the family of Neumann parallelograms, the intersection of two (or more) adjacent eigen- value level surfaces occurs in one of three ways: either as an isolated point associated with the special geometries, i.e., the rectangle, the square, or the rhombus, as part of a degeneracy curve which appears to contain an infinite number of points, or as a diabolical point in the Neumann parallelogram spec- trum. -
A Singular One-Dimensional Bound State Problem and Its Degeneracies
A Singular One-Dimensional Bound State Problem and its Degeneracies Fatih Erman1, Manuel Gadella2, Se¸cil Tunalı3, Haydar Uncu4 1 Department of Mathematics, Izmir˙ Institute of Technology, Urla, 35430, Izmir,˙ Turkey 2 Departamento de F´ısica Te´orica, At´omica y Optica´ and IMUVA. Universidad de Valladolid, Campus Miguel Delibes, Paseo Bel´en 7, 47011, Valladolid, Spain 3 Department of Mathematics, Istanbul˙ Bilgi University, Dolapdere Campus 34440 Beyo˘glu, Istanbul,˙ Turkey 4 Department of Physics, Adnan Menderes University, 09100, Aydın, Turkey E-mail: [email protected], [email protected], [email protected], [email protected] October 20, 2017 Abstract We give a brief exposition of the formulation of the bound state problem for the one-dimensional system of N attractive Dirac delta potentials, as an N N matrix eigenvalue problem (ΦA = ωA). The main aim of this paper is to illustrate that the non-degeneracy× theorem in one dimension breaks down for the equidistantly distributed Dirac delta potential, where the matrix Φ becomes a special form of the circulant matrix. We then give elementary proof that the ground state is always non-degenerate and the associated wave function may be chosen to be positive by using the Perron-Frobenius theorem. We also prove that removing a single center from the system of N delta centers shifts all the bound state energy levels upward as a simple consequence of the Cauchy interlacing theorem. Keywords. Point interactions, Dirac delta potentials, bound states. 1 Introduction Dirac delta potentials or point interactions, or sometimes called contact potentials are one of the exactly solvable classes of idealized potentials, and are used as a pedagogical tool to illustrate various physically important phenomena, where the de Broglie wavelength of the particle is much larger than the range of the interaction. -
11.-HYPERBOLA-THEORY.Pdf
12. HYPERBOLA 1. INTRODUCTION A hyperbola is the locus of a point which moves in the plane in such a way that Z the ratio of its distance from a fixed point in the same plane to its distance X’ P from a fixed line is always constant which is always greater than unity. M The fixed point is called the focus, the fixed line is called the directrix. The constant ratio is generally denoted by e and is known as the eccentricity of the Directrix hyperbola. A hyperbola can also be defined as the locus of a point such that S (focus) the absolute value of the difference of the distances from the two fixed points Z’ (foci) is constant. If S is the focus, ZZ′ is the directrix and P is any point on the hyperbola as show in figure. Figure 12.1 SP Then by definition, we have = e (e > 1). PM Note: The general equation of a conic can be taken as ax22+ 2hxy + by + 2gx + 2fy += c 0 This equation represents a hyperbola if it is non-degenerate (i.e. eq. cannot be written into two linear factors) ahg ∆ ≠ 0, h2 > ab. Where ∆=hb f gfc MASTERJEE CONCEPTS 1. The general equation ax22+ 2hxy + by + 2gx + 2fy += c 0 can be written in matrix form as ahgx ah x x y + 2gx + 2fy += c 0 and xy1hb f y = 0 hb y gfc1 Degeneracy condition depends on the determinant of the 3x3 matrix and the type of conic depends on the determinant of the 2x2 matrix. -
Forbidden Configurations in Discrete Geometry
FORBIDDEN CONFIGURATIONS IN DISCRETE GEOMETRY This book surveys the mathematical and computational properties of finite sets of points in the plane, covering recent breakthroughs on important problems in discrete geometry and listing many open prob- lems. It unifies these mathematical and computational views using for- bidden configurations, which are patterns that cannot appear in sets with a given property, and explores the implications of this unified view. Written with minimal prerequisites and featuring plenty of fig- ures, this engaging book will be of interest to undergraduate students and researchers in mathematics and computer science. Most topics are introduced with a related puzzle or brain-teaser. The topics range from abstract issues of collinearity, convexity, and general position to more applied areas including robust statistical estimation and network visualization, with connections to related areas of mathe- matics including number theory, graph theory, and the theory of per- mutation patterns. Pseudocode is included for many algorithms that compute properties of point sets. David Eppstein is Chancellor’s Professor of Computer Science at the University of California, Irvine. He has more than 350 publications on subjects including discrete and computational geometry, graph the- ory, graph algorithms, data structures, robust statistics, social network analysis and visualization, mesh generation, biosequence comparison, exponential algorithms, and recreational mathematics. He has been the moderator for data structures and algorithms -
Graphs in Nature
Graphs in Nature David Eppstein University of California, Irvine Symposium on Geometry Processing, July 2019 Inspiration: Steinitz's theorem Purely combinatorial characterization of geometric objects: Graphs of convex polyhedra are exactly the 3-vertex-connected planar graphs Image: Kluka [2006] Overview Cracked surfaces, bubble foams, and crumpled paper also form natural graph-like structures What properties do these graphs have? How can we recognize and synthesize them? I. Cracks and Needles Motorcycle graphs: Canonical quad mesh partitioning Paper at SGP'08 [Eppstein et al. 2008] Problem: partition irregular quad-mesh into regular submeshes Inspiration: Light cycle game from TRON movies Mesh partitioning method Grow cut paths outwards from each irregular (non-degree-4) vertex Cut paths continue straight across regular (degree-4) vertices They stop when they run into another path Result: approximation to optimal partition (exact optimum is NP-complete) Mesh-free motorcycle graphs Earlier... Motorcycles move from initial points with given velocities When they hit trails of other motorcycles, they crash [Eppstein and Erickson 1999] Application of mesh-free motorcycle graphs Initially: A simplified model of the inward movement of reflex vertices in straight skeletons, a rectilinear variant of medial axes with applications including building roof construction, folding and cutting problems, surface interpolation, geographic analysis, and mesh construction Later: Subroutine for constructing straight skeletons of simple polygons [Cheng and Vigneron 2007; Huber and Held 2012] Image: Huber [2012] Construction of mesh-free motorcycle graphs Main ideas: Define asymmetric distance: Time when one motorcycle would crash into another's trail Repeatedly find closest pair and eliminate crashed motorcycle Image: Dancede [2011] O(n17=11+) [Eppstein and Erickson 1999] Improved to O(n4=3+) [Vigneron and Yan 2014] Additional log speedup using mutual nearest neighbors instead of closest pairs [Mamano et al. -
Sparsification–A Technique for Speeding up Dynamic Graph Algorithms
Sparsification–A Technique for Speeding Up Dynamic Graph Algorithms DAVID EPPSTEIN University of California, Irvine, Irvine, California ZVI GALIL Columbia University, New York, New York GIUSEPPE F. ITALIANO Universita` “Ca’ Foscari” di Venezia, Venice, Italy AND AMNON NISSENZWEIG Tel-Aviv University, Tel-Aviv, Israel Abstract. We provide data structures that maintain a graph as edges are inserted and deleted, and keep track of the following properties with the following times: minimum spanning forests, graph connectivity, graph 2-edge connectivity, and bipartiteness in time O(n1/2) per change; 3-edge connectivity, in time O(n2/3) per change; 4-edge connectivity, in time O(na(n)) per change; k-edge connectivity for constant k, in time O(nlogn) per change; 2-vertex connectivity, and 3-vertex connectivity, in time O(n) per change; and 4-vertex connectivity, in time O(na(n)) per change. A preliminary version of this paper was presented at the 33rd Annual IEEE Symposium on Foundations of Computer Science (Pittsburgh, Pa.), 1992. D. Eppstein was supported in part by National Science Foundation (NSF) Grant CCR 92-58355. Z. Galil was supported in part by NSF Grants CCR 90-14605 and CDA 90-24735. G. F. Italiano was supported in part by the CEE Project No. 20244 (ALCOM-IT) and by a research grant from Universita` “Ca’ Foscari” di Venezia; most of his work was done while at IBM T. J. Watson Research Center. Authors’ present addresses: D. Eppstein, Department of Information and Computer Science, University of California, Irvine, CA 92717, e-mail: [email protected], internet: http://www.ics. -
Triangle-Free Penny Graphs: Degeneracy, Choosability, and Edge Count
Triangle-Free Penny Graphs: Degeneracy, Choosability, and Edge Count David Eppstein 25th International Symposium on Graph Drawing & Network Visualization Boston, Massachusetts, September 2017 Circle packing theorem Contacts of interior-disjoint disks in the plane form a planar graph All planar graphs can be represented this way Unique (up to M¨obius)for triangulated graphs [Koebe 1936; Andreev 1970; Thurston 2002] Balanced circle packing Some planar graphs may require exponentially-different radii a b c d But polynomial radii are e f g h i j k possible for: l m n o I Trees p I Outerpaths I Cactus graphs a I Bounded tree-depth b c d [Alam et al. 2015] j e g h i f m k l p n o Perfect balance Circle packings with all radii equal represent penny graphs [Harborth 1974; Erd}os1987] Penny graphs as proximity graphs Given any finite set of points in the plane Draw an edge between each closest pair of points (Pennies: circles centered at the given points with radius = half the minimum distance) So penny graphs may also be called closest-pair graphs or minimum-distance graphs Penny graphs as optimal graph drawings Penny graphs are exactly graphs that can be drawn I With no crossings I All edges equal length I Angular resolution ≥ π=3 Properties of penny graphs 3-degenerate (convex hull vertices have degree ≤ 3) ) easy proof of 4-color theorem; 4-list-colorable [Hartsfield and Ringel 2003] p Number of edges at most 3n − 12n − 3 Maximized by packing into a hexagon [Harborth 1974; Kupitz 1994] NP-hard to recognize, even for trees [Bowen et al. -
Removing Degeneracy May Require a Large Dimension Increase∗
THEORY OF COMPUTING, Volume 3 (2007), pp. 159–177 http://theoryofcomputing.org Removing Degeneracy May Require a Large Dimension Increase∗ Jirˇ´ı Matousekˇ Petr Skovroˇ nˇ Received: March 12, 2007; published: September 26, 2007. Abstract: Many geometric algorithms are formulated for input objects in general position; sometimes this is for convenience and simplicity, and sometimes it is essential for the al- gorithm to work at all. For arbitrary inputs this requires removing degeneracies, which has usually been solved by relatively complicated and computationally demanding perturbation methods. The result of this paper can be regarded as an indication that the problem of removing degeneracies has no simple “abstract” solution. We consider LP-type problems, a successful axiomatic framework for optimization problems capturing, e. g., linear programming and the smallest enclosing ball of a point set. For infinitely many integers D we construct a D- dimensional LP-type problem such that in order to remove degeneracies from it, we have to increase the dimension to at least (1 + ε)D, where ε > 0 is an absolute constant. The proof consists of showing that certain posets cannot be covered by pairwise disjoint copies of Boolean algebras under some restrictions on their placement. To this end, we prove that certain systems of linear inequalities are unsolvable, which seems to require surprisingly precise calculations. ∗An extended abstract of this paper has appeared in Proceedings of European Conference on Combinatorics, Graph Theory and Applications 2007 (Eurocomb), pp. 107–113. ACM Classification: F.2.2 AMS Classification: 68U05, 06A07, 68R99 Key words and phrases: LP-type problem, degeneracy, general position, geometric computation, par- tially ordered set Authors retain copyright to their work and grant Theory of Computing unlimited rights to publish the work electronically and in hard copy. -
Degeneracy and All That = ∫
DEGENERACY AND ALL THAT The Nature of Thermodynamics, Statistical Mechanics and Classical Mechanics Thermodynamics The study of the equilibrium bulk properties of matter within the context of four laws or ‘facts of experience’ that relate measurable properties, like temperature, pressure, and volume etc. It is important to understand that from the viewpoint of thermodynamics the microscopic nature of matter is irrelevant, that is, thermodynamics would apply equally well if matter formed a continuum. In addition, thermodynamics is a measurement or laboratory based science and is not a branch of metaphysics. Statistical Mechanics Statistical Mechanics is a statistical approach to solving the classical n body problem in order to study the same bulk properties of matter as thermodynamics but doing so at the microscopic level. In this way Statistical Mechanics allows an understanding of the equilibrium properties of matter at a molecular level. Statistical Mechanics makes heavy use of Thermodynamics, Classical Mechanics and Quantum Mechanics for its development and hence the perquisites for this course. Classical Mechanics The Classical Mechanical approach to studying the n body problem involves solving six simultaneous differential equations for each particle in the system. This assumes one knows the initial position q(t) and momentum p(t) of each particle at time to. Since the bulk properties of the system of interest are themselves functions of the q and p, i.e., G=G[p(t),q(t)] we can then do a time average of the form 1 t0 G Gobs G[ p ( t ), q ( t )] dt t0 where is long enough to ensure G is independent of , i.e., fluctuations are negligible.