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Relaxations of the Weakly Chordal Condition in Graphs Mississippi State University Scholars Junction Theses and Dissertations Theses and Dissertations 8-6-2021 Relaxations of the weakly chordal condition in graphs Benjamin Lee Hathcock [email protected] Follow this and additional works at: https://scholarsjunction.msstate.edu/td Recommended Citation Hathcock, Benjamin Lee, "Relaxations of the weakly chordal condition in graphs" (2021). Theses and Dissertations. 5183. https://scholarsjunction.msstate.edu/td/5183 This Graduate Thesis - Open Access is brought to you for free and open access by the Theses and Dissertations at Scholars Junction. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of Scholars Junction. For more information, please contact [email protected]. Relaxations of the weakly chordal condition in graphs By Benjamin Lee Hathcock Approved by: Vaidyanathan Sivaraman (Major Professor) Robert C. Smith Paul Fabel Mohammad Sephrirar (Graduate Coordinator) Rick Travis (Dean, College of Arts and Sciences) A Thesis Submitted to the Faculty of Mississippi State University In Partial Fulfillment of the Requirements For the Degree of Master of Science in Mathematics in the College of Arts and Sciences Mississippi State, Mississippi August 2021 Name: Benjamin Lee Hathcock Date of Degree: August 6, 2021 Institution: Mississippi State University Major Field: Mathematics Major Professor: Vaidyanathan Sivaraman Title of Study: Relaxations of the weakly chordal condition in graphs Pages in Study: 26 Candidate for Degree of Master of Science Both chordal and weakly chordal graphs have been topics of research in graph theory for many years. Upon reading their definitions it is clear that the weakly chordal class of graphs is a relaxation of the chordal condition for graphs. The question is then asked could we possibly find and study the properties if we, in turn, relaxed the weakly chordal condition for graphs? We start by providing the definitions and basic results needed later on. In the second chap- ter, we discuss perfect graphs, some of their properties and some subclasses that were researched. The third chapter is focused on a new class of graphs, the definition of which relaxes the restrictions for chordal and weakly chordal graphs, and extends certain results from weakly chordal graphs to this class. DEDICATION I would like to dedicate this research to my sister, Hailey Teasler and my brother-in-law John Teasler. ii ACKNOWLEDGEMENTS The author would like to express his most sincere gratitude to the many people without whose time and assistance this thesis wouldn’t have been created. First of all, I’d like to thank to Dr. Russ Woodroofe for working with me in coming up with the topic of my research and guiding me along the way. I’d also like to express my limitless gratitude to Dr. Vaidyanathan Sivaraman for continuing to give me assistance and for being an inspiration to me. Expressed appreciation also goes to the other members of my committee, namely, Dr. Paul Fabel, Dr. Robert Smith, and Dr. Mohammad Sepehrifar. Finally, I’d like to thank all of the Mississippi State support staff who have helped me with the paperwork used in this study. iii TABLE OF CONTENTS DEDICATION . ii ACKNOWLEDGEMENTS . iii LIST OF FIGURES . v CHAPTER I. INTRODUCTION TO GRAPH THEORY . 1 II. PERFECT GRAPHS . 7 III. LANGUID GRAPHS AND MAIN RESULTS . 17 3.1 Defining Languid Graphs . 17 3.2 Perfection of Graphs With No Holes Except Six Cycles . 22 REFERENCES . 25 iv LIST OF FIGURES 1.1 4 simple graphs: a path graph with of 3 edges, a cycle graph with 4 edges, the Petersen graph, and an icosahedron graph. 2 1.2 A Graph (G), A subgraph of G, An induced subgraph of G ............. 4 1.3 A k-coloring of the previous example graphs. 4 1.4 A Graph G, a matching of G, an induced matching of G ............... 6 1.5 A cycle of 5 vertices, its line graph, and its K. Cameron Graph. 7 2.6 An imperfect graph, followed by 2 perfect graphs . 8 3.7 The forbidden graphs of type 3 where the solid lines represent required edges and the dotted lines represent optional edges. ....................... 18 3.8 Example of a graph that has a minimal cutset that does not yield an even pair or 3-pair in G. ...................................... 23 v CHAPTER I INTRODUCTION TO GRAPH THEORY We begin this chapter by introducing foundational definitions, and by stating some of the established Graph Theory results which will be used later. Many interesting problems, both applied and theoretical can be solved using models which consist of only 2 axiomatic concepts. These mathematical models are called graphs and the 2 axiomatic concepts for graphs are that data consists of 1. a set of points 2. lines joining some pairs of those points. More formally, Graph theory is the study of mathematical structures used to model pairwise relations between objects. Definition 1.1. A graph G is an ordered pair (V;E), where V is some set and E is a set of 2-point subsets of V. The elements of the set V are called the vertices of the graph G, and the elements of the set E are called the edges of G. To say a graph has a vertex set V with edge set E we can write G = (V;E). It is common to depict graphs as drawings in the plane. Vertices are represented by points in the plane (i.e. dots, bullets, little circles, etc), and drawing a line (straight or curved) between two vertices if they are connected by an edge. 1 A graph is called finite if V is a finite set, it is called null if V is empty, and it is called simple if G contains no loops (an edge that connects a vertex to itself) or multiple edges between 2 adjacent vertices. We provide an example of some graphs in Figure 1.1. Figure 1.1: 4 simple graphs: a path graph with of 3 edges, a cycle graph with 4 edges, the Petersen graph, and an icosahedron graph. Two vertices of a graph are considered adjacent if they share an edge. Two edges are considered incident if they share a vertex. The two vertices incident to an edge are called its endpoints. The degree of a vertex, deg(v) is the number of edges incident to v. A graph is complete if every vertex in G is adjacent to every other vertex in G. The complement of a graph G, is a graph G that has the same vertex set, but whose vertices in G are adjacent if and only if they are not adjacent in G. Definition 1.2. A walk in G is a sequence (v0;e1;v1;e2;:::;et;vt) of vertices vi and edges ei such that for 1 ≤ i ≤ t, the edge ei has endpoints vi−1 and vi. A walk can be thought of as going from a starting vertex v0 and traversing edges to adjacent vertices and finally stopping at vt . Both edges and vertices can be repeated in a walk. Definition 1.3. A trail in G is a sequence (v0;e1;v1;e2;:::;et;vt) of vertices vi and edges ei such that for 1 ≤ i ≤ t, the edge ei has endpoints vi−1 and vi, and each e1;e2;:::;et is distinct. A trail is walk in which vertices can be repeated but edges cannot. 2 Definition 1.4. A path in G is a sequence (v0;e1;v1;e2;:::;et;vt) of vertices vi and edges ei such that for 1 ≤ i ≤ t, the edge ei has endpoints vi−1 and vi, and each v1;v2;:::;vt is distinct. A path is a walk where vertices cannot be repeated. The length of a walk, trail, or path is the number of edges that each contain. A path of length m is denoted Pm. If P = (v0;e1;v1;e2;:::;et;vt) is a path with m ≥ 3, then the graph C = P [ (et+1;v0) is called a cycle. We denote a cycle consisting of n vertices as Cn. We let a chord of a Cn in a graph G be an edge connecting two non-consecutive vertices (i.e. a shortcut) of that cycle. Definition 1.5. A non-empty graph G is called connected if any two of its vertices can be joined by a path. If G is not connected then it is considered disconnected. Unless otherwise stated, graphs mentioned will be simple, connected, graphs. Definition 1.6. A cutset is a non-empty set of vertices C such that G −C is disconnected. Definition 1.7. A subgraph H, of G is a graph such that the vertex set of H is a subset of the vertex set of G, and the edge set of H is a subset of the edge set of G, denoted V(H) ⊆ V(G);and E(H) ⊆ E(G), respectively. We say that H is an induced subgraph of G, if the vertex set of H is a subset of the vertex set of G and the edge set of H contains exactly the edges in G that join the vertices of H, written T V(H) V(H) ⊆ V(G) and E(H) = E(G) V 2 . The neighborhood of a vertex v in a graph G, denoted NG(v), is the subgraph of G induced by all vertices adjacent to v together with all edges adjacent to those vertices. Figure 1.2 provides an example of the differences between a subgraph and induced subgraph. 3 Figure 1.2: A Graph (G), A subgraph of G, An induced subgraph of G Definition 1.8.
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