CMSC 27130 Honors Discrete Mathematics
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Blast Domination for Mycielski's Graph of Graphs
International Journal of Engineering and Advanced Technology (IJEAT) ISSN: 2249 – 8958, Volume-8, Issue-6S3, September 2019 Blast Domination for Mycielski’s Graph of Graphs K. Ameenal Bibi, P.Rajakumari AbstractThe hub of this article is a search on the behavior of is the minimum cardinality of a distance-2 dominating set in the Blast domination and Blast distance-2 domination for 퐺. Mycielski’s graph of some particular graphs and zero divisor graphs. Definition 2.3[7] A non-empty subset 퐷 of 푉 of a connected graph 퐺 is Key Words:Blast domination number, Blast distance-2 called a Blast dominating set, if 퐷 is aconnected dominating domination number, Mycielski’sgraph. set and the induced sub graph < 푉 − 퐷 >is triple connected. The minimum cardinality taken over all such Blast I. INTRODUCTION dominating sets is called the Blast domination number of The concept of triple connected graphs was introduced by 퐺and is denoted by tc . Paulraj Joseph et.al [9]. A graph is said to be triple c (G) connected if any three vertices lie on a path in G. In [6] the Definition2.4 authors introduced triple connected domination number of a graph. A subset D of V of a nontrivial graph G is said to A non-empty subset 퐷 of vertices in a graph 퐺 is a blast betriple connected dominating set, if D is a dominating set distance-2 dominating set if every vertex in 푉 − 퐷 is within and <D> is triple connected. The minimum cardinality taken distance-2 of atleast one vertex in 퐷. -
Determination and Testing the Domination Numbers of Tadpole Graph, Book Graph and Stacked Book Graph Using MATLAB Ayhan A
College of Basic Education Researchers Journal Vol. 10, No. 1 Determination and Testing the Domination Numbers of Tadpole Graph, Book Graph and Stacked Book Graph Using MATLAB Ayhan A. khalil Omar A.Khalil Technical College of Mosul -Foundation of Technical Education Received: 11/4/2010 ; Accepted: 24/6/2010 Abstract: A set is said to be dominating set of G if for every there exists a vertex such that . The minimum cardinality of vertices among dominating set of G is called the domination number of G denoted by . We investigate the domination number of Tadpole graph, Book graph and Stacked Book graph. Also we test our theoretical results in computer by introducing a matlab procedure to find the domination number , dominating set S and draw this graph that illustrates the vertices of domination this graphs. It is proved that: . Keywords: Dominating set, Domination number, Tadpole graph, Book graph, stacked graph. إﯾﺟﺎد واﺧﺗﺑﺎر اﻟﻌدد اﻟﻣﮭﯾﻣن(اﻟﻣﺳﯾطر)Domination number ﻟﻠﺑﯾﺎﻧﺎت ﺗﺎدﺑول (Tadpole graph)، ﺑﯾﺎن ﺑوك (Book graph) وﺑﯾﺎن ﺳﺗﺎﻛﯾت ﺑوك (Stacked Book graph) ﺑﺎﺳﺗﻌﻣﺎل اﻟﻣﺎﺗﻼب أﯾﮭﺎن اﺣﻣد ﺧﻠﯾل ﻋﻣر اﺣﻣد ﺧﻠﯾل اﻟﻛﻠﯾﺔ اﻟﺗﻘﻧﯾﺔ-ﻣوﺻل- ھﯾﺋﺔ اﻟﺗﻌﻠﯾم اﻟﺗﻘﻧﻲ ﻣﻠﺧص اﻟﺑﺣث : ﯾﻘﺎل ﻷﯾﺔ ﻣﺟﻣوﻋﺔ ﺟزﺋﯾﺔ S ﻣن ﻣﺟﻣوﻋﺔ اﻟرؤوس V ﻓﻲ ﺑﯾﺎن G ﺑﺄﻧﻬﺎ ﻣﺟﻣوﻋﺔ ﻣﻬﯾﻣﻧﺔ Dominating set إذا ﻛﺎن ﻟﻛل أرس v ﻓﻲ اﻟﻣﺟﻣوﻋﺔ V-S ﯾوﺟد أرس u ﻓﻲS ﺑﺣﯾث uv ﺿﻣن 491 Ayhan A. & Omar A. ﺣﺎﻓﺎت اﻟﺑﯾﺎن،. وﯾﻌرف اﻟﻌدد اﻟﻣﻬﯾﻣن Domination number ﺑﺄﻧﻪ أﺻﻐر ﻣﺟﻣوﻋﺔ أﺳﺎﺳﯾﺔ ﻣﻬﯾﻣﻧﺔ Domination. ﻓﻲ ﻫذا اﻟﺑﺣث ﺳوف ﻧدرس اﻟﻌدد اﻟﻣﻬﯾﻣن Domination number ﻟﺑﯾﺎن ﺗﺎدﺑول (Tadpole graph) ، ﺑﯾﺎن ﺑوك (Book graph) وﺑﯾﺎن ﺳﺗﺎﻛﯾت ﺑوك ( Stacked Book graph). -
Graphs with Flexible Labelings
Graphs with Flexible Labelings Georg Grasegger∗ Jan Legersk´yy Josef Schichoy For a flexible labeling of a graph, it is possible to construct infinitely many non-equivalent realizations keeping the distances of connected points con- stant. We give a combinatorial characterization of graphs that have flexible labelings, possibly non-generic. The characterization is based on colorings of the edges with restrictions on the cycles. Furthermore, we give necessary criteria and sufficient ones for the existence of such colorings. 1 Introduction Given a graph together with a labeling of its edges by positive real numbers, we are interested in the set of all functions from the set of vertices to the real plane such that the distance between any two connected vertices is equal to the label of the edge connecting them. Apparently, any such \realization" gives rise to infinitely many equivalent ones, by the action of the group of Euclidean congruence transformations. If the set of equivalence classes is finite and non-empty, then we say that the labeled graph is rigid; if this set is infinite, then we say that the labeling is flexible. The main result in this paper is a combinatorial characterization of graphs that have a flexible labeling. The characterization of graphs such that a generically chosen assign- ment of the vertices to the real plane gives a flexible labeling is classical: by a theorem of Geiringer-Pollaczek [8] which was rediscovered by Laman [6], this is true if the graph contains no Laman subgraph with the same set of vertices. Here, a graph G = (VG;EG) is called a Laman graph if and only if jEGj = 2jVGj − 3 and jEH j ≤ 2jVH j − 3 for any ∗Johann Radon Institute for Computational and Applied Mathematics (RICAM), Austrian Academy of Sciences arXiv:1708.05298v2 [math.CO] 19 Nov 2018 yResearch Institute for Symbolic Computation (RISC), Johannes Kepler University Linz This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sk lodowska-Curie grant agreement No 675789. -
Constructing Arbitrarily Large Graphs with a Specified Number Of
Electronic Journal of Graph Theory and Applications 4 (1) (2019), 1–8 Constructing Arbitrarily Large Graphs with a Specified Number of Hamiltonian Cycles Michael Haythorpea aSchool of Computer Science, Engineering and Mathematics, Flinders University, 1284 South Road, Clovelly Park, SA 5042, Australia michael.haythorpe@flinders.edu.au Abstract A constructive method is provided that outputs a directed graph which is named a broken crown graph, containing 5n − 9 vertices and k Hamiltonian cycles for any choice of integers n ≥ k ≥ 4. The construction is not designed to be minimal in any sense, but rather to ensure that the graphs produced remain non-trivial instances of the Hamiltonian cycle problem even when k is chosen to be much smaller than n. Keywords: Hamiltonian cycles, Graph Construction, Broken Crown Mathematics Subject Classification : 05C45 1. Introduction The Hamiltonian cycle problem (HCP) is a famous NP-complete problem in which one must determine whether a given graph contains a simple cycle traversing all vertices of the graph, or not. Such a simple cycle is called a Hamiltonian cycle (HC), and a graph containing at least one arXiv:1902.10351v1 [math.CO] 27 Feb 2019 Hamiltonian cycle is said to be a Hamiltonian graph. Typically, randomly generated graphs (such as Erdos-R˝ enyi´ graphs), if connected, are Hamil- tonian and contain many Hamiltonian cycles. Although HCP is an NP-complete problem, for these graphs it is often fairly easy for a sophisticated heuristic (e.g. see Concorde [1], Keld Helsgaun’s LKH [4] or Snakes-and-ladders Heuristic [2]) to discover one of the multitude of Hamiltonian cy- cles through a clever search. -
Dominating Cycles in Halin Graphs*
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Discrete Mathematics 86 (1990) 215-224 215 North-Holland DOMINATING CYCLES IN HALIN GRAPHS* Mirosiawa SKOWRONSKA Institute of Mathematics, Copernicus University, Chopina 12/18, 87-100 Torun’, Poland Maciej M. SYStO Institute of Computer Science, University of Wroclaw, Przesmyckiego 20, 51-151 Wroclaw, Poland Received 2 December 1988 A cycle in a graph is dominating if every vertex lies at distance at most one from the cycle and a cycle is D-cycle if every edge is incident with a vertex of the cycle. In this paper, first we provide recursive formulae for finding a shortest dominating cycle in a Hahn graph; minor modifications can give formulae for finding a shortest D-cycle. Then, dominating cycles and D-cycles in a Halin graph H are characterized in terms of the cycle graph, the intersection graph of the faces of H. 1. Preliminaries The various domination problems have been extensively studied. Among them is the problem whether a graph has a dominating cycle. All graphs in this paper have no loops and multiple edges. A dominating cycle in a graph G = (V(G), E(G)) is a subgraph C of G which is a cycle and every vertex of V(G) \ V(C) is adjacent to a vertex of C. There are graphs which have no dominating cycles, and moreover, determining whether a graph has a dominating cycle on at most 1 vertices is NP-complete even in the class of planar graphs [7], chordal, bipartite and split graphs [3]. -
Tight Bounds for Online Edge Coloring
Tight Bounds for Online Edge Coloring Ilan Reuven Cohen∗1, Binghui Peng†‡2, and David Wajc§¶k3 1Carnegie Mellon University and University of Pittsburgh 2Tsinghua University 3Carnegie Mellon University Abstract Vizing’s celebrated theorem asserts that any graph of maximum degree ∆ admits an edge coloring using at most ∆ + 1 colors. In contrast, Bar-Noy, Motwani and Naor showed over a quarter century ago that the trivial greedy algorithm, which uses 2∆ 1 colors, is optimal among online algorithms. Their lower bound has a caveat, however: it− only applies to low- degree graphs, with ∆ = O(log n), and they conjectured the existence of online algorithms using ∆(1 + o(1)) colors for ∆= ω(log n). Progress towards resolving this conjecture was only made under stochastic arrivals (Aggarwal et al., FOCS’03 and Bahmani et al., SODA’10). We resolve the above conjecture for adversarial vertex arrivals in bipartite graphs, for which we present a (1+ o(1))∆-edge-coloring algorithm for ∆= ω(log n) known a priori. Surprisingly, if ∆ is not known ahead of time, we show that no e Ω(1) ∆-edge-coloring algorithm exists. e−1 − We then provide an optimal, e + o(1) ∆-edge-coloring algorithm for unknown ∆= ω(log n). e−1 Key to our results, and of possible independent interest, is a novel fractional relaxation for edge coloring, for which we present optimal fractional online algorithms and a near-lossless online rounding scheme, yielding our optimal randomized algorithms. ∗Email address: [email protected]. †Email address: [email protected]. ‡Work done in part while the author was visiting Carnegie Mellon University. -
Hamilton Cycle Heuristics in Hard Graphs (Under the Direction of Pro- Fessor Carla D
ABSTRACT SHIELDS, IAN BEAUMONT Hamilton Cycle Heuristics in Hard Graphs (Under the direction of Pro- fessor Carla D. Savage) In this thesis, we use computer methods to investigate Hamilton cycles and paths in several families of graphs where general results are incomplete, including Kneser graphs, cubic Cayley graphs and the middle two levels graph. We describe a novel heuristic which has proven useful in finding Hamilton cycles in these families and compare its performance to that of other algorithms and heuristics. We describe methods for handling very large graphs on personal computers. We also explore issues in reducing the possible number of generating sets for cubic Cayley graphs generated by three involutions. Hamilton Cycle Heuristics in Hard Graphs by Ian Beaumont Shields A dissertation submitted to the Graduate Faculty of North Carolina State University in partial fulfillment of the requirements for the Degree of Doctor of Philosophy Computer Science Raleigh 2004 APPROVED BY: ii Dedication To my wife Pat, and my children, Catherine, Brendan and Michael, for their understanding during these years of study. To the memory of Hanna Neumann who introduced me to combinatorial group theory. iii Biography Ian Shields was born on March 10, 1949 in Melbourne, Australia. He grew up and attended school near the foot of the Dandenong ranges. After a short time in actuarial work he attended the Australian National University in Canberra, where he graduated in 1973 with first class honours in pure mathematics. Ian worked for IBM and other companies in Australia, Canada and the United States, before resuming part-time study for a Masters Degree in Computer Science at North Carolina State University which he received in May 1995. -
Are Highly Connected 1-Planar Graphs Hamiltonian? Arxiv:1911.02153V1 [Cs.DM] 6 Nov 2019
Are highly connected 1-planar graphs Hamiltonian? Therese Biedl Abstract It is well-known that every planar 4-connected graph has a Hamiltonian cycle. In this paper, we study the question whether every 1-planar 4-connected graph has a Hamiltonian cycle. We show that this is false in general, even for 5-connected graphs, but true if the graph has a 1-planar drawing where every region is a triangle. 1 Introduction Planar graphs are graphs that can be drawn without crossings. They have been one of the central areas of study in graph theory and graph algorithms, and there are numerous results both for how to solve problems more easily on planar graphs and how to draw planar graphs (see e.g. [1, 9, 10])). We are here interested in a theorem by Tutte [17] that states that every planar 4-connected graph has a Hamiltonian cycle (definitions are in the next section). This was an improvement over an earlier result by Whitney that proved the existence of a Hamiltonian cycle in a 4-connected triangulated planar graph. There have been many generalizations and improvements since; in particular we can additionally fix the endpoints and one edge that the Hamiltonian cycle must use [16, 12]. Also, 4-connected planar graphs remain Hamiltonian even after deleting 2 vertices [14]. Hamiltonian cycles in planar graphs can be computed in linear time; this is quite straightforward if the graph is triangulated [2] and a bit more involved for general 4-connected planar graphs [5]. There are many graphs that are near-planar, i.e., that are \close" to planar graphs. -
On the Number of Cycles in a Graph with Restricted Cycle Lengths
On the number of cycles in a graph with restricted cycle lengths D´anielGerbner,∗ Bal´azsKeszegh,y Cory Palmer,z Bal´azsPatk´osx October 12, 2016 Abstract Let L be a set of positive integers. We call a (directed) graph G an L-cycle graph if all cycle lengths in G belong to L. Let c(L; n) be the maximum number of cycles possible in an n-vertex L-cycle graph (we use ~c(L; n) for the number of cycles in directed graphs). In the undirected case we show that for any fixed set L, we have k=` c(L; n) = ΘL(nb c) where k is the largest element of L and 2` is the smallest even element of L (if L contains only odd elements, then c(L; n) = ΘL(n) holds.) We also give a characterization of L-cycle graphs when L is a single element. In the directed case we prove that for any fixed set L we have ~c(L; n) = (1 + n 1 k 1 o(1))( k−1 ) − , where k is the largest element of L. We determine the exact value of ~c(fkg; n−) for every k and characterize all graphs attaining this maximum. 1 Introduction In this paper we examine graphs that contain only cycles of some prescribed lengths (where the length of a cycle or a path is the number of its edges). Let L be a set of positive integers. We call a graph G an L-cycle graph if all cycle lengths in G belong to L. -
Convex Polytopes and Tilings with Few Flag Orbits
Convex Polytopes and Tilings with Few Flag Orbits by Nicholas Matteo B.A. in Mathematics, Miami University M.A. in Mathematics, Miami University A dissertation submitted to The Faculty of the College of Science of Northeastern University in partial fulfillment of the requirements for the degree of Doctor of Philosophy April 14, 2015 Dissertation directed by Egon Schulte Professor of Mathematics Abstract of Dissertation The amount of symmetry possessed by a convex polytope, or a tiling by convex polytopes, is reflected by the number of orbits of its flags under the action of the Euclidean isometries preserving the polytope. The convex polytopes with only one flag orbit have been classified since the work of Schläfli in the 19th century. In this dissertation, convex polytopes with up to three flag orbits are classified. Two-orbit convex polytopes exist only in two or three dimensions, and the only ones whose combinatorial automorphism group is also two-orbit are the cuboctahedron, the icosidodecahedron, the rhombic dodecahedron, and the rhombic triacontahedron. Two-orbit face-to-face tilings by convex polytopes exist on E1, E2, and E3; the only ones which are also combinatorially two-orbit are the trihexagonal plane tiling, the rhombille plane tiling, the tetrahedral-octahedral honeycomb, and the rhombic dodecahedral honeycomb. Moreover, any combinatorially two-orbit convex polytope or tiling is isomorphic to one on the above list. Three-orbit convex polytopes exist in two through eight dimensions. There are infinitely many in three dimensions, including prisms over regular polygons, truncated Platonic solids, and their dual bipyramids and Kleetopes. There are infinitely many in four dimensions, comprising the rectified regular 4-polytopes, the p; p-duoprisms, the bitruncated 4-simplex, the bitruncated 24-cell, and their duals. -
THE CHROMATIC POLYNOMIAL 1. Introduction a Common Problem in the Study of Graph Theory Is Coloring the Vertices of a Graph So Th
THE CHROMATIC POLYNOMIAL CODY FOUTS Abstract. It is shown how to compute the Chromatic Polynomial of a sim- ple graph utilizing bond lattices and the M¨obiusInversion Theorem, which requires the establishment of a refinement ordering on the bond lattice and an exploration of the Incidence Algebra on a partially ordered set. 1. Introduction A common problem in the study of Graph Theory is coloring the vertices of a graph so that any two connected by a common edge are different colors. The vertices of the graph in Figure 1 have been colored in the desired manner. This is called a Proper Coloring of the graph. Frequently, we are concerned with determining the least number of colors with which we can achieve a proper coloring on a graph. Furthermore, we want to count the possible number of different proper colorings on a graph with a given number of colors. We can calculate each of these values by using a special function that is associated with each graph, called the Chromatic Polynomial. For simple graphs, such as the one in Figure 1, the Chromatic Polynomial can be determined by examining the structure of the graph. For other graphs, it is very difficult to compute the function in this manner. However, there is a connection between partially ordered sets and graph theory that helps to simplify the process. Utilizing subgraphs, lattices, and a special theorem called the M¨obiusInversion Theorem, we determine an algorithm for calculating the Chromatic Polynomial for any graph we choose. Figure 1. A simple graph colored so that no two vertices con- nected by an edge are the same color. -
An Introduction to Algebraic Graph Theory
An Introduction to Algebraic Graph Theory Cesar O. Aguilar Department of Mathematics State University of New York at Geneseo Last Update: March 25, 2021 Contents 1 Graphs 1 1.1 What is a graph? ......................... 1 1.1.1 Exercises .......................... 3 1.2 The rudiments of graph theory .................. 4 1.2.1 Exercises .......................... 10 1.3 Permutations ........................... 13 1.3.1 Exercises .......................... 19 1.4 Graph isomorphisms ....................... 21 1.4.1 Exercises .......................... 30 1.5 Special graphs and graph operations .............. 32 1.5.1 Exercises .......................... 37 1.6 Trees ................................ 41 1.6.1 Exercises .......................... 45 2 The Adjacency Matrix 47 2.1 The Adjacency Matrix ...................... 48 2.1.1 Exercises .......................... 53 2.2 The coefficients and roots of a polynomial ........... 55 2.2.1 Exercises .......................... 62 2.3 The characteristic polynomial and spectrum of a graph .... 63 2.3.1 Exercises .......................... 70 2.4 Cospectral graphs ......................... 73 2.4.1 Exercises .......................... 84 3 2.5 Bipartite Graphs ......................... 84 3 Graph Colorings 89 3.1 The basics ............................. 89 3.2 Bounds on the chromatic number ................ 91 3.3 The Chromatic Polynomial .................... 98 3.3.1 Exercises ..........................108 4 Laplacian Matrices 111 4.1 The Laplacian and Signless Laplacian Matrices .........111 4.1.1