Quick but Odd Growth of Cacti
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Coloring ($ P 6 $, Diamond, $ K 4 $)-Free Graphs
Coloring (P6, diamond, K4)-free graphs T. Karthick∗ Suchismita Mishra† June 28, 2021 Abstract We show that every (P6, diamond, K4)-free graph is 6-colorable. Moreover, we give an example of a (P6, diamond, K4)-free graph G with χ(G) = 6. This generalizes some known results in the literature. 1 Introduction We consider simple, finite, and undirected graphs. For notation and terminology not defined here we refer to [22]. Let Pn, Cn, Kn denote the induced path, induced cycle and complete graph on n vertices respectively. If G1 and G2 are two vertex disjoint graphs, then their union G1 ∪ G2 is the graph with V (G1 ∪ G2) = V (G1) ∪ V (G2) and E(G1 ∪ G2) = E(G1) ∪ E(G2). Similarly, their join G1 + G2 is the graph with V (G1 + G2) = V (G1) ∪ V (G2) and E(G1 + G2) = E(G1) ∪ E(G2)∪{(x,y) | x ∈ V (G1), y ∈ V (G2)}. For any positive integer k, kG denotes the union of k graphs each isomorphic to G. If F is a family of graphs, a graph G is said to be F-free if it contains no induced subgraph isomorphic to any member of F. A clique (independent set) in a graph G is a set of vertices that are pairwise adjacent (non-adjacent) in G. The clique number of G, denoted by ω(G), is the size of a maximum clique in G. A k-coloring of a graph G = (V, E) is a mapping f : V → {1, 2,...,k} such that f(u) 6= f(v) whenever uv ∈ E. -
Arxiv:2006.06067V2 [Math.CO] 4 Jul 2021
Treewidth versus clique number. I. Graph classes with a forbidden structure∗† Cl´ement Dallard1 Martin Milaniˇc1 Kenny Storgelˇ 2 1 FAMNIT and IAM, University of Primorska, Koper, Slovenia 2 Faculty of Information Studies, Novo mesto, Slovenia [email protected] [email protected] [email protected] Treewidth is an important graph invariant, relevant for both structural and algo- rithmic reasons. A necessary condition for a graph class to have bounded treewidth is the absence of large cliques. We study graph classes closed under taking induced subgraphs in which this condition is also sufficient, which we call (tw,ω)-bounded. Such graph classes are known to have useful algorithmic applications related to variants of the clique and k-coloring problems. We consider six well-known graph containment relations: the minor, topological minor, subgraph, induced minor, in- duced topological minor, and induced subgraph relations. For each of them, we give a complete characterization of the graphs H for which the class of graphs excluding H is (tw,ω)-bounded. Our results yield an infinite family of χ-bounded induced-minor-closed graph classes and imply that the class of 1-perfectly orientable graphs is (tw,ω)-bounded, leading to linear-time algorithms for k-coloring 1-perfectly orientable graphs for every fixed k. This answers a question of Breˇsar, Hartinger, Kos, and Milaniˇc from 2018, and one of Beisegel, Chudnovsky, Gurvich, Milaniˇc, and Servatius from 2019, respectively. We also reveal some further algorithmic implications of (tw,ω)- boundedness related to list k-coloring and clique problems. In addition, we propose a question about the complexity of the Maximum Weight Independent Set prob- lem in (tw,ω)-bounded graph classes and prove that the problem is polynomial-time solvable in every class of graphs excluding a fixed star as an induced minor. -
Vertex Cover Reconfiguration and Beyond
algorithms Article Vertex Cover Reconfiguration and Beyond † Amer E. Mouawad 1,*, Naomi Nishimura 2, Venkatesh Raman 3 and Sebastian Siebertz 4,‡ 1 Department of Informatics, University of Bergen, PB 7803, N-5020 Bergen, Norway 2 School of Computer Science, University of Waterloo, Waterloo, ON N2L 3G1, Canada; [email protected] 3 Institute of Mathematical Sciences, Chennai 600113, India; [email protected] 4 Institute of Informatics, University of Warsaw, 02-097 Warsaw, Poland; [email protected] * Correspondence: [email protected] † This paper is an extended version of our paper published in the 25th International Symposium on Algorithms and Computation (ISAAC 2014). ‡ The work of Sebastian Siebertz is supported by the National Science Centre of Poland via POLONEZ Grant Agreement UMO-2015/19/P/ST6/03998, which has received funding from the European Union’s Horizon 2020 research and innovation programme (Marie Skłodowska-Curie Grant Agreement No. 665778). Received: 11 October 2017; Accepted: 7 Febuary 2018; Published: 9 Febuary 2018 Abstract: In the Vertex Cover Reconfiguration (VCR) problem, given a graph G, positive integers k and ` and two vertex covers S and T of G of size at most k, we determine whether S can be transformed into T by a sequence of at most ` vertex additions or removals such that every operation results in a vertex cover of size at most k. Motivated by results establishing the W[1]-hardness of VCR when parameterized by `, we delineate the complexity of the problem restricted to various graph classes. In particular, we show that VCR remains W[1]-hard on bipartite graphs, is NP-hard, but fixed-parameter tractable on (regular) graphs of bounded degree and more generally on nowhere dense graphs and is solvable in polynomial time on trees and (with some additional restrictions) on cactus graphs. -
Isometric Diamond Subgraphs
Isometric Diamond Subgraphs David Eppstein Computer Science Department, University of California, Irvine [email protected] Abstract. We test in polynomial time whether a graph embeds in a distance- preserving way into the hexagonal tiling, the three-dimensional diamond struc- ture, or analogous higher-dimensional structures. 1 Introduction Subgraphs of square or hexagonal tilings of the plane form nearly ideal graph draw- ings: their angular resolution is bounded, vertices have uniform spacing, all edges have unit length, and the area is at most quadratic in the number of vertices. For induced sub- graphs of these tilings, one can additionally determine the graph from its vertex set: two vertices are adjacent whenever they are mutual nearest neighbors. Unfortunately, these drawings are hard to find: it is NP-complete to test whether a graph is a subgraph of a square tiling [2], a planar nearest-neighbor graph, or a planar unit distance graph [5], and Eades and Whitesides’ logic engine technique can also be used to show the NP- completeness of determining whether a given graph is a subgraph of the hexagonal tiling or an induced subgraph of the square or hexagonal tilings. With stronger constraints on subgraphs of tilings, however, they are easier to con- struct: one can test efficiently whether a graph embeds isometrically onto the square tiling, or onto an integer grid of fixed or variable dimension [7]. In an isometric em- bedding, the unweighted distance between any two vertices in the graph equals the L1 distance of their placements in the grid. An isometric embedding must be an induced subgraph, but not all induced subgraphs are isometric. -
Graphs with Few Trivial Characteristic Ideals
University of Rhode Island DigitalCommons@URI Mathematics Faculty Publications Mathematics 2021 Graphs with few trivial characteristic ideals Carlos A. Alfaro Michael D. Barrus John Sinkovic Ralihe R. Villagrán Follow this and additional works at: https://digitalcommons.uri.edu/math_facpubs The University of Rhode Island Faculty have made this article openly available. Please let us know how Open Access to this research benefits you. This is a pre-publication author manuscript of the final, published article. Terms of Use This article is made available under the terms and conditions applicable towards Open Access Policy Articles, as set forth in our Terms of Use. Graphs with few trivial characteristic ideals Carlos A. Alfaroa, Michael D. Barrusb, John Sinkovicc and Ralihe R. Villagr´and a Banco de M´exico Mexico City, Mexico [email protected] bDepartment of Mathematics University of Rhode Island Kingston, RI 02881, USA [email protected] cDepartment of Mathematics Brigham Young University - Idaho Rexburg, ID 83460, USA [email protected] dDepartamento de Matem´aticas Centro de Investigaci´ony de Estudios Avanzados del IPN Apartado Postal 14-740, 07000 Mexico City, Mexico [email protected] Abstract We give a characterization of the graphs with at most three trivial characteristic ideals. This implies the complete characterization of the regular graphs whose critical groups have at most three invariant factors equal to 1 and the characterization of the graphs whose Smith groups have at most 3 invariant factors equal to 1. We also give an alternative and simpler way to obtain the characterization of the graphs whose Smith groups have at most 3 invariant factors equal to 1, and a list of minimal forbidden graphs for the family of graphs with Smith group having at most 4 invariant factors equal to 1. -
Dynamical Systems Associated with Adjacency Matrices
DISCRETE AND CONTINUOUS doi:10.3934/dcdsb.2018190 DYNAMICAL SYSTEMS SERIES B Volume 23, Number 5, July 2018 pp. 1945{1973 DYNAMICAL SYSTEMS ASSOCIATED WITH ADJACENCY MATRICES Delio Mugnolo Delio Mugnolo, Lehrgebiet Analysis, Fakult¨atMathematik und Informatik FernUniversit¨atin Hagen, D-58084 Hagen, Germany Abstract. We develop the theory of linear evolution equations associated with the adjacency matrix of a graph, focusing in particular on infinite graphs of two kinds: uniformly locally finite graphs as well as locally finite line graphs. We discuss in detail qualitative properties of solutions to these problems by quadratic form methods. We distinguish between backward and forward evo- lution equations: the latter have typical features of diffusive processes, but cannot be well-posed on graphs with unbounded degree. On the contrary, well-posedness of backward equations is a typical feature of line graphs. We suggest how to detect even cycles and/or couples of odd cycles on graphs by studying backward equations for the adjacency matrix on their line graph. 1. Introduction. The aim of this paper is to discuss the properties of the linear dynamical system du (t) = Au(t) (1.1) dt where A is the adjacency matrix of a graph G with vertex set V and edge set E. Of course, in the case of finite graphs A is a bounded linear operator on the finite di- mensional Hilbert space CjVj. Hence the solution is given by the exponential matrix etA, but computing it is in general a hard task, since A carries little structure and can be a sparse or dense matrix, depending on the underlying graph. -
Approximation Algorithms for Problems in Makespan Minimization on Unrelated Parallel Machines
Western University Scholarship@Western Electronic Thesis and Dissertation Repository 4-8-2019 10:30 AM Approximation Algorithms for Problems in Makespan Minimization on Unrelated Parallel Machines Daniel R. Page The University of Western Ontario Supervisor Solis-Oba, Roberto The University of Western Ontario Graduate Program in Computer Science A thesis submitted in partial fulfillment of the equirr ements for the degree in Doctor of Philosophy © Daniel R. Page 2019 Follow this and additional works at: https://ir.lib.uwo.ca/etd Part of the Discrete Mathematics and Combinatorics Commons, and the Theory and Algorithms Commons Recommended Citation Page, Daniel R., "Approximation Algorithms for Problems in Makespan Minimization on Unrelated Parallel Machines" (2019). Electronic Thesis and Dissertation Repository. 6109. https://ir.lib.uwo.ca/etd/6109 This Dissertation/Thesis is brought to you for free and open access by Scholarship@Western. It has been accepted for inclusion in Electronic Thesis and Dissertation Repository by an authorized administrator of Scholarship@Western. For more information, please contact [email protected]. Abstract A fundamental problem in scheduling is makespan minimization on unrelated parallel ma- chines (RjjCmax). Let there be a set J of jobs and a set M of parallel machines, where every + job J j 2 J has processing time or length pi; j 2 Q on machine Mi 2 M. The goal in RjjCmax is to schedule the jobs non-preemptively on the machines so as to minimize the length of the schedule, the makespan. A ρ-approximation algorithm produces in polynomial time a feasible solution such that its objective value is within a multiplicative factor ρ of the optimum, where ρ is called its approximation ratio. -
A Tight Extremal Bound on the Lovász Cactus Number in Planar Graphs
A Tight Extremal Bound on the Lovász Cactus Number in Planar Graphs Parinya Chalermsook Aalto University, Espoo, Finland parinya.chalermsook@aalto.fi Andreas Schmid Max Planck Institute for Informatics, Saarbrücken, Germany [email protected] Sumedha Uniyal Aalto University, Espoo, Finland sumedha.uniyal@aalto.fi Abstract A cactus graph is a graph in which any two cycles are edge-disjoint. We present a constructive proof of the fact that any plane graph G contains a cactus subgraph C where C contains at least 1 a 6 fraction of the triangular faces of G. We also show that this ratio cannot be improved by showing a tight lower bound. Together with an algorithm for linear matroid parity, our bound implies two approximation algorithms for computing “dense planar structures” inside any graph: (i) 1 A 6 approximation algorithm for, given any graph G, finding a planar subgraph with a maximum 1 number of triangular faces; this improves upon the previous 11 -approximation; (ii) An alternate (and 4 arguably more illustrative) proof of the 9 approximation algorithm for finding a planar subgraph with a maximum number of edges. Our bound is obtained by analyzing a natural local search strategy and heavily exploiting the exchange arguments. Therefore, this suggests the power of local search in handling problems of this kind. 2012 ACM Subject Classification Mathematics of computing → Graph theory Keywords and phrases Graph Drawing, Matroid Matching, Maximum Planar Subgraph, Local Search Algorithms Digital Object Identifier 10.4230/LIPIcs.STACS.2019.19 Related Version Full Version: https://arxiv.org/abs/1804.03485. Funding Parinya Chalermsook: Part of this work was done while PC and AS were visiting the Simons Institute for the Theory of Computing. -
Graph-Theoretic Properties of the Class of Phonological Neighbourhood Networks
Graph-theoretic Properties of the Class of Phonological Neighbourhood Networks Rory Turnbull Newcastle University [email protected] Abstract flan clan This paper concerns the structure of phono- plant logical neighbourhood networks, which are a graph-theoretic representation of the phono- plane logical lexicon. These networks represent each word as a node and links are placed be- plan planner tween words which are phonological neigh- bours, usually defined as a string edit distance plaque of one. Phonological neighbourhood networks have been used to study many aspects of the planned mental lexicon and psycholinguistic theories pan of speech production and perception. This pa- plans per offers preliminary graph-theoretic observa- tions about phonological neighbourhood net- Figure 1: Example phonological neighbourhood net- works considered as a class. To aid this ex- work centred around the English word plan. Note that ploration, this paper introduces the concept of some neighbours of a word are neighbours of each the hyperlexicon, the network consisting of all other. Adapted from Turnbull and Peperkamp(2017). possible words for a given symbol set and their neighbourhood relations. The construction of the hyperlexicon is discussed, and basic prop- 0 0 erties are derived. This work is among the first of w), intransitive (if w is a neighbour of w , and w to directly address the nature of phonological is a neighbour of w00, it is not necessarily the case neighbourhood networks from an analytic per- that w is a neighbour of w00), and anti-reflexive (w spective. cannot be a neighbour of itself). Figure1 shows an abbreviated phonological 1 Motivation neighbourhood network for some words of English. -
Gridline Graphs in Three and Higher Dimensions Susanna Lange Grand Valley State University
Grand Valley State University ScholarWorks@GVSU Honors Projects Undergraduate Research and Creative Practice 12-2015 Gridline Graphs in Three and Higher Dimensions Susanna Lange Grand Valley State University Holly Raglow Grand Valley State University Follow this and additional works at: http://scholarworks.gvsu.edu/honorsprojects Part of the Physical Sciences and Mathematics Commons Recommended Citation Lange, Susanna and Raglow, Holly, "Gridline Graphs in Three and Higher Dimensions" (2015). Honors Projects. 535. http://scholarworks.gvsu.edu/honorsprojects/535 This Open Access is brought to you for free and open access by the Undergraduate Research and Creative Practice at ScholarWorks@GVSU. It has been accepted for inclusion in Honors Projects by an authorized administrator of ScholarWorks@GVSU. For more information, please contact [email protected]. Gridline Graphs in Three and Higher Dimensions Susanna Lange, Holly Raglow Advisor: Dr. Feryal Alayont December 16, 2015 Introduction In mathematics, a graph is a collection of vertices and edges represented by an image with vertices as points and edges as lines. While there are many different types of graphs in graph theory, we will focus on gridline graphs (also called graphs of (0; 1) matrices, or rook's graphs). Definition. In two dimensions, a gridline graph is a graph whose vertices can be labeled by points in the plane in such a way that two vertices are adjacent, meaning they share an edge, if and only if they have one coordinate in common. In other words, in a two dimensional gridline graph, two vertices are not connected if they differ in both the x coordinate and the y coordinate. -
Maximum Bounded Rooted-Tree Problem: Algorithms and Polyhedra
Maximum Bounded Rooted-Tree Problem : Algorithms and Polyhedra Jinhua Zhao To cite this version: Jinhua Zhao. Maximum Bounded Rooted-Tree Problem : Algorithms and Polyhedra. Combinatorics [math.CO]. Université Clermont Auvergne, 2017. English. NNT : 2017CLFAC044. tel-01730182 HAL Id: tel-01730182 https://tel.archives-ouvertes.fr/tel-01730182 Submitted on 13 Mar 2018 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. Numéro d’Ordre : D.U. 2816 EDSPIC : 799 Université Clermont Auvergne École Doctorale Sciences Pour l’Ingénieur de Clermont-Ferrand THÈSE Présentée par Jinhua ZHAO pour obtenir le grade de Docteur d’Université Spécialité : Informatique Le Problème de l’Arbre Enraciné Borné Maximum : Algorithmes et Polyèdres Soutenue publiquement le 19 juin 2017 devant le jury M. ou Mme Mohamed DIDI-BIHA Rapporteur et examinateur Sourour ELLOUMI Rapporteuse et examinatrice Ali Ridha MAHJOUB Rapporteur et examinateur Fatiha BENDALI Examinatrice Hervé KERIVIN Directeur de Thèse Philippe MAHEY Directeur de Thèse iii Acknowledgments First and foremost I would like to thank my PhD advisors, Professors Philippe Mahey and Hervé Kerivin. Without Professor Philippe Mahey, I would never have had the chance to come to ISIMA or LIMOS here in France in the first place, and I am really grateful and honored to be accepted as a PhD student of his. -
"Some Contributions to Parameterized Complexity"
Laboratoire d'Informatique, de Robotique et de Micro´electronique de Montpellier Universite´ de Montpellier Speciality: Computer Science Habilitation `aDiriger des Recherches (HDR) Ignasi Sau Valls Some Contributions to Parameterized Complexity Quelques Contributions en Complexit´eParam´etr´ee Version of June 21, 2018 { Defended on June 25, 2018 Committee: Reviewers: Michael R. Fellows - University of Bergen (Norway) Fedor V. Fomin - University of Bergen (Norway) Rolf Niedermeier - Technische Universit¨at Berlin (Germany) Examinators: Jean-Claude Bermond - CNRS, U. de Nice-Sophia Antipolis (France) Marc Noy - Univ. Polit`ecnica de Catalunya (Catalonia) Dimitrios M. Thilikos - CNRS, Universit´ede Montpellier (France) Gilles Trombettoni - Universit´ede Montpellier (France) Contents 0 R´esum´eet projet de recherche7 1 Introduction 13 1.1 Contextualization................................. 13 1.2 Scientific collaborations ............................. 15 1.3 Organization of the manuscript......................... 17 2 Curriculum vitae 19 2.1 Education and positions............................. 19 2.2 Full list of publications.............................. 20 2.3 Supervised students ............................... 32 2.4 Awards, grants, scholarships, and projects................... 33 2.5 Teaching activity................................. 34 2.6 Committees and administrative duties..................... 35 2.7 Research visits .................................. 36 2.8 Research talks................................... 38 2.9 Journal and conference