Lemma. Let G be a graph and e an edge of G. Then e is a bridge of G if and only if e does not lie in any cycle of G.

Size: px
Start display at page:

Download "Lemma. Let G be a graph and e an edge of G. Then e is a bridge of G if and only if e does not lie in any cycle of G."

Transcription

1 Lemma. Let G be a graph and e an edge of G. Then e is a bridge of G if and only if e does not lie in any cycle of G. Lemma. If e = xy is a bridge of the connected graph G, then G e consists of exactly two components one containing x and the other containing y. Lemma. If v is a cutvertex of the graph G. then δ( v) 2. So, an endvertex of a graph cannot be a cutvertex. Let P denote some property of graphs. Then A graph G is said to be minimal with respect to P if and only if G has P but for every edge e of G, G - e does not have P. If a property is worth studying at all, then it is worth studying those graphs that are minimal with respect to P. Graphs that are minimal with respect to connectedness are called trees. Thus a graph G is a tree if it is connected but for every edge e, G - e is not connected. That means that every edge of G must be a bridge. That in turn means that G cannot contain a cycle. So equivalently, we may define a graph G to be a tree if and only if G is connected and has no cycles. Examples of trees. Notice that there are two 'types' of trees on 4 vertices and three 'types' of trees on 5 vertices. We will make it clear soon just what we really mean by a 'type' of graph. (If we accidentally said there were 4 types of trees on 5 vertices - this is wrong- would we have made a 'type of graph'-ical error?) It is also interesting to notice that there is one tree on V = {a}, one tree on V = {a, b}, 3 distinct trees on V = {a, b, c}, 16 distinct trees on V = {a, b, c, d} and 125 distinct trees on V = {a, b, c, d, e}. How many distinct trees are there on V = {a, b, c, d, e, f}? How many 'types' of trees are there on six vertices?

2 A subgraph H of G that has the same vertex set as G (i.e., V(H) = V(G) ) is called a spanning subgraph of G. Theorem. If G is any connected graph, then G has a spanning subgraph that is a tree. (Such a subgraph is called, naturally enough, a spanning tree for G). Theorem. If G is a tree on n vertices, then G has n - 1 edges. Theorem. If G is a connected graph on n vertices and n - 1 edges, then G is a tree. Theorem. If G is a graph on n vertices having no cycles and n - 1 edges, then G is a tree. Theorem. Every tree on n 2 vertices contains at least two end-vertices. So we have used phrases like, 'G and H are the same type' to 'G and H are essentially the same,' and the time has come to make these ideas more precise. Two graphs G and H are identical if they have exactly the same set of vertices and edges. How the graph is drawn does not matter - the picture is just a representation of the graph. The two graphs below are identical. Example: Notice that the top two graphs in each collection yield a collection of 4 distinct graphs. However the bottom graphs in each group are identical to the one directly above. However, the top graph in each group of three is more than just different from its counterpoint in the other group. The graphs in each column have the same structure, which is quite different from the graphs in the other column. The graphs on the left differ from one-another only in names of vertices (similarly for the other group). We can turn any graph on the left into the other by simply renaming (we say relabeling) the vertices. But there is no way to rename the vertices in any graph on the on the left to produce one of the graphs on the right.

3 We say that two graphs are isomorphic if they differ only in their labels; i.e., we can turn one into the other by renaming the vertices. More precisely, A graph G is isomorphic to a graph H if there exists a bijection (i.e., 1-1 correspondence) φ: V ( G) V ( H) such that for every two vertices x and y of G, xy E( G) φ( x) φ( y) E( H) φ is called an isomorphism and it represents the relabeling that turns G into H. The idea is that if two graphs are isomorphic then they have exactly the same graphtheoretic properties. Two isomorphic graphs differ only in the names of the vertices and nothing else. In other words G and H are isomorphic if you can obtain H from G by renaming the vertices of G properly. The function φ describes how to rename the vertices. Note that the isomorphic relation is an equivalence realation lf the set of all graphs. For a given graph G, we say that the class of all graphs isomorphic to G (i.e., the equivalence class of G) forms an isomorphism class. Examples There are two isomorphism classes of trees of order 4 - we say up to isomorphism there are two trees of order 4. Up to isomorphism there are three trees of order 5. Up to isomorphism there are two graphs of order two. Up to isomorphism there are four graphs (not just trees) of order three. When we ask if two graphs are isomorphic we are essentially asking if we can reassign labels to the vertices so that the resulting graphs are identical. Of course two unlabeled graphs are isomorphic if we can assign labels to each of them so that the resulting graphs are identical. When we draw a graph without labels, we are referring to an isomorphism class of graphs. So, suppose that someone has promised you a great deal of money to determine if two graphs each with 30 vertices are isomorphic. If the graphs are isomorphic, then you can convince me of that by exhibiting a particular isomorphism. It might be quite difficult to determine an isomorphism - but it is likely doable. But at least you can potentially find something to convince me that you did your job. But what if the graphs are not isomorphic? What then? Well, consider this. Are the graphs below isomorphic? No - clearly not. Why not? Well, because of the triangle in the graph on the right.

4 Suppose that G and H are isomorphic graphs and G has a triangle abc. Then the images of a,b, and c under the isomorphism must be a triangle in H So if G has a triangle, then so does any graph isomorphic to it. In general, to show that two graphs are isomorphic we can just exhibit an isomorphism, How would you show that two graphs are not isomorphic? So we can point to the triangle as evidence that the isomorphism does not exist. In general any property of graphs that is preserved by isomorphisms could be used. Such properties are called graph-theoretic properties. Examples Here are some other such properties. If G and H are isomorphic then They have the same number of vertices They have the same number of edges. They have the same number of even-order cycles They have the same number of triangles They have the same degree sequence. If one of them contains 4 mutually adjacent vertices so does the other. If one has exactly two cut vertices, so does the other. If one contains a pair of adjacent vertices of degree 3, then so does the other. So to convince someone that there is no isomorphism you could provide a graph-theoretic property of one graph that is not shared by the other. Clearly, any two complete graphs on n vertices are isomorphic. Clearly any two paths on n vertices are isomorphic. We denote a complete graph on n vertices by K n and a path on n vertices by P n and a cycle on n vertices by C n. Here are a few more examples. If G has a (induced) subgraph isomorphic to F, then H has a (induced) subgraph isomorphic to F. If G has a vertex of degree 4 adjacent to a vertex of degree 7, then H also has a vertex of degree 4 adjacent to a vertex of degree 7. If G is isomorphic to H, then the subgraph of G induced by the vertices of degree 2 is isomorphic to the subgraph of H induced by the vertices of degree 2. If G is isomorphic to H and G and H both have exactly one vertex of degree 7, then subgraphs of G and H obtained by removing that vertex are also isomorphic. These are just a few of the infinite number of possible criteria that we might use to demonstrate that two graphs are not isomorphic. The Theorem below is frequently useful. Theorem. If G and H are isomorphic, then so are their complements.

5 If G and H have a large number of edges, it may be easier to deal with the their complements. Reconstruction Conjecture: Suppose that I take a graph and I delete a vertex one at a time and write down on an index card an unlabeled graph that is isomorphic to the vertex-deleted graph. Now I give you the index cards. Can you figure out, up to isomorphism, what the graph was? i.e., can you reconstruct the graph? The conjecture is that yes, that is always possible for graphs on n 2 vertices, But no one has proven it. And maybe it s not true. But it is known to be true for small and for graphs that are not connected. Questions: (i). Why do we require n 2 here? (ii). Can you prove that all regular graphs are reconstructible? It isn t too hard to figure out some of the properties of the graph from the set of vertexdeleted subgraphs. For example, you can find n, q the number of vertices and edges, and the degree sequence quite easily. You can also tell if the original graph was connected. Can you figure out how? Here is the official version of the Reconstruction Conjecture. Conjecture: Given the n 2 vertex deleted subgraphs G v1, G v2,, G v n (unlabelled), it is possible to reconstruct G. Effectively this asserts that any two non-isomorphic graphs will produce distinct sets of vertex deleted subgraphs. Theorem. Let G be a graph with n vertices and q edges. For each i = 1, 2,, n let q i denote the number of edges in G v i qi i= 1. Then q = n 2. n

HOMEWORK 4 SOLUTIONS. Solution: The Petersen graph contains a cycle of odd length as a subgraph. Hence,

HOMEWORK 4 SOLUTIONS. Solution: The Petersen graph contains a cycle of odd length as a subgraph. Hence, HOMEWORK 4 SOLUTIONS (1) Determine the chromatic number of the Petersen graph. Solution: The Petersen graph contains a cycle of odd length as a subgraph. Hence, 3 χ(c 5 ) χ(p ). As the Petersen graph is

More information

Fundamental Properties of Graphs

Fundamental Properties of Graphs Chapter three In many real-life situations we need to know how robust a graph that represents a certain network is, how edges or vertices can be removed without completely destroying the overall connectivity,

More information

K 4 C 5. Figure 4.5: Some well known family of graphs

K 4 C 5. Figure 4.5: Some well known family of graphs 08 CHAPTER. TOPICS IN CLASSICAL GRAPH THEORY K, K K K, K K, K K, K C C C C 6 6 P P P P P. Graph Operations Figure.: Some well known family of graphs A graph Y = (V,E ) is said to be a subgraph of a graph

More information

2. CONNECTIVITY Connectivity

2. CONNECTIVITY Connectivity 2. CONNECTIVITY 70 2. Connectivity 2.1. Connectivity. Definition 2.1.1. (1) A path in a graph G = (V, E) is a sequence of vertices v 0, v 1, v 2,..., v n such that {v i 1, v i } is an edge of G for i =

More information

K 4,4 e Has No Finite Planar Cover

K 4,4 e Has No Finite Planar Cover K 4,4 e Has No Finite Planar Cover Petr Hliněný Dept. of Applied Mathematics, Charles University, Malostr. nám. 25, 118 00 Praha 1, Czech republic (E-mail: hlineny@kam.ms.mff.cuni.cz) February 9, 2005

More information

HW Graph Theory SOLUTIONS (hbovik) - Q

HW Graph Theory SOLUTIONS (hbovik) - Q 1, Diestel 9.3: An arithmetic progression is an increasing sequence of numbers of the form a, a+d, a+ d, a + 3d.... Van der Waerden s theorem says that no matter how we partition the natural numbers into

More information

WUCT121. Discrete Mathematics. Graphs

WUCT121. Discrete Mathematics. Graphs WUCT121 Discrete Mathematics Graphs WUCT121 Graphs 1 Section 1. Graphs 1.1. Introduction Graphs are used in many fields that require analysis of routes between locations. These areas include communications,

More information

5 Graph Theory Basics

5 Graph Theory Basics November 14, 2017 5 Graph Theory Basics William T. Trotter trotter@math.gatech.edu Basic Definitions Definition A graph G is a pair (V, E) where V is a finite set and E is a set of 2-element subsets of

More information

A graph is finite if its vertex set and edge set are finite. We call a graph with just one vertex trivial and all other graphs nontrivial.

A graph is finite if its vertex set and edge set are finite. We call a graph with just one vertex trivial and all other graphs nontrivial. 2301-670 Graph theory 1.1 What is a graph? 1 st semester 2550 1 1.1. What is a graph? 1.1.2. Definition. A graph G is a triple (V(G), E(G), ψ G ) consisting of V(G) of vertices, a set E(G), disjoint from

More information

WALL, NICOLE TURPIN, M.A. On the Reconstruction Conjecture. (2008) Directed by Dr. Paul Duvall. 56 pp.

WALL, NICOLE TURPIN, M.A. On the Reconstruction Conjecture. (2008) Directed by Dr. Paul Duvall. 56 pp. WALL, NICOLE TURPIN, M.A. On the Reconstruction Conjecture. (2008) Directed by Dr. Paul Duvall. 56 pp. Every graph of order three or more is reconstructible. Frank Harary restated one of the most famous

More information

On Universal Cycles of Labeled Graphs

On Universal Cycles of Labeled Graphs On Universal Cycles of Labeled Graphs Greg Brockman Harvard University Cambridge, MA 02138 United States brockman@hcs.harvard.edu Bill Kay University of South Carolina Columbia, SC 29208 United States

More information

Adjacent: Two distinct vertices u, v are adjacent if there is an edge with ends u, v. In this case we let uv denote such an edge.

Adjacent: Two distinct vertices u, v are adjacent if there is an edge with ends u, v. In this case we let uv denote such an edge. 1 Graph Basics What is a graph? Graph: a graph G consists of a set of vertices, denoted V (G), a set of edges, denoted E(G), and a relation called incidence so that each edge is incident with either one

More information

CONNECTIVITY AND NETWORKS

CONNECTIVITY AND NETWORKS CONNECTIVITY AND NETWORKS We begin with the definition of a few symbols, two of which can cause great confusion, especially when hand-written. Consider a graph G. (G) the degree of the vertex with smallest

More information

MATH20902: Discrete Maths, Solutions to Problem Set 1. These solutions, as well as the corresponding problems, are available at

MATH20902: Discrete Maths, Solutions to Problem Set 1. These solutions, as well as the corresponding problems, are available at MATH20902: Discrete Maths, Solutions to Problem Set 1 These solutions, as well as the corresponding problems, are available at https://bit.ly/mancmathsdiscrete.. (1). The upper panel in the figure below

More information

Suggested problems - solutions

Suggested problems - solutions Suggested problems - solutions Examples and models Material for this section references College Geometry: A Discovery Approach, 2/e, David C. Kay, Addison Wesley, 2001. In particular, see section 2.2,

More information

Definition: A graph G = (V, E) is called a tree if G is connected and acyclic. The following theorem captures many important facts about trees.

Definition: A graph G = (V, E) is called a tree if G is connected and acyclic. The following theorem captures many important facts about trees. Tree 1. Trees and their Properties. Spanning trees 3. Minimum Spanning Trees 4. Applications of Minimum Spanning Trees 5. Minimum Spanning Tree Algorithms 1.1 Properties of Trees: Definition: A graph G

More information

Math 776 Graph Theory Lecture Note 1 Basic concepts

Math 776 Graph Theory Lecture Note 1 Basic concepts Math 776 Graph Theory Lecture Note 1 Basic concepts Lectured by Lincoln Lu Transcribed by Lincoln Lu Graph theory was founded by the great Swiss mathematician Leonhard Euler (1707-178) after he solved

More information

arxiv: v1 [math.co] 5 Nov 2010

arxiv: v1 [math.co] 5 Nov 2010 Segment representation of a subclass of co-planar graphs Mathew C. Francis, Jan Kratochvíl, and Tomáš Vyskočil arxiv:1011.1332v1 [math.co] 5 Nov 2010 Department of Applied Mathematics, Charles University,

More information

Lecture 19 Thursday, March 29. Examples of isomorphic, and non-isomorphic graphs will be given in class.

Lecture 19 Thursday, March 29. Examples of isomorphic, and non-isomorphic graphs will be given in class. CIS 160 - Spring 2018 (instructor Val Tannen) Lecture 19 Thursday, March 29 GRAPH THEORY Graph isomorphism Definition 19.1 Two graphs G 1 = (V 1, E 1 ) and G 2 = (V 2, E 2 ) are isomorphic, write G 1 G

More information

γ(ɛ) (a, b) (a, d) (d, a) (a, b) (c, d) (d, d) (e, e) (e, a) (e, e) (a) Draw a picture of G.

γ(ɛ) (a, b) (a, d) (d, a) (a, b) (c, d) (d, d) (e, e) (e, a) (e, e) (a) Draw a picture of G. MAD 3105 Spring 2006 Solutions for Review for Test 2 1. Define a graph G with V (G) = {a, b, c, d, e}, E(G) = {r, s, t, u, v, w, x, y, z} and γ, the function defining the edges, is given by the table ɛ

More information

The Graphs of Triangulations of Polygons

The Graphs of Triangulations of Polygons The Graphs of Triangulations of Polygons Matthew O Meara Research Experience for Undergraduates Summer 006 Basic Considerations Let Γ(n) be the graph with vertices being the labeled planar triangulation

More information

The following is a summary, hand-waving certain things which actually should be proven.

The following is a summary, hand-waving certain things which actually should be proven. 1 Basics of Planar Graphs The following is a summary, hand-waving certain things which actually should be proven. 1.1 Plane Graphs A plane graph is a graph embedded in the plane such that no pair of lines

More information

6c Lecture 3 & 4: April 8 & 10, 2014

6c Lecture 3 & 4: April 8 & 10, 2014 6c Lecture 3 & 4: April 8 & 10, 2014 3.1 Graphs and trees We begin by recalling some basic definitions from graph theory. Definition 3.1. A (undirected, simple) graph consists of a set of vertices V and

More information

1 Some Solution of Homework

1 Some Solution of Homework Math 3116 Dr. Franz Rothe May 30, 2012 08SUM\3116_2012h1.tex Name: Use the back pages for extra space 1 Some Solution of Homework Proposition 1 (Counting labeled trees). There are n n 2 different labeled

More information

MITOCW watch?v=hverxup4cfg

MITOCW watch?v=hverxup4cfg MITOCW watch?v=hverxup4cfg PROFESSOR: We've briefly looked at graph isomorphism in the context of digraphs. And it comes up in even more fundamental way really for simple graphs where the definition is

More information

Characterizing Graphs (3) Characterizing Graphs (1) Characterizing Graphs (2) Characterizing Graphs (4)

Characterizing Graphs (3) Characterizing Graphs (1) Characterizing Graphs (2) Characterizing Graphs (4) S-72.2420/T-79.5203 Basic Concepts 1 S-72.2420/T-79.5203 Basic Concepts 3 Characterizing Graphs (1) Characterizing Graphs (3) Characterizing a class G by a condition P means proving the equivalence G G

More information

CS195H Homework 5. Due:March 12th, 2015

CS195H Homework 5. Due:March 12th, 2015 CS195H Homework 5 Due:March 12th, 2015 As usual, please work in pairs. Math Stuff For us, a surface is a finite collection of triangles (or other polygons, but let s stick with triangles for now) with

More information

And Now From a New Angle Special Angles and Postulates LEARNING GOALS

And Now From a New Angle Special Angles and Postulates LEARNING GOALS And Now From a New Angle Special Angles and Postulates LEARNING GOALS KEY TERMS. In this lesson, you will: Calculate the complement and supplement of an angle. Classify adjacent angles, linear pairs, and

More information

What is a Graphon? Daniel Glasscock, June 2013

What is a Graphon? Daniel Glasscock, June 2013 What is a Graphon? Daniel Glasscock, June 2013 These notes complement a talk given for the What is...? seminar at the Ohio State University. The block images in this PDF should be sharp; if they appear

More information

The Structure of Bull-Free Perfect Graphs

The Structure of Bull-Free Perfect Graphs The Structure of Bull-Free Perfect Graphs Maria Chudnovsky and Irena Penev Columbia University, New York, NY 10027 USA May 18, 2012 Abstract The bull is a graph consisting of a triangle and two vertex-disjoint

More information

1 Digraphs. Definition 1

1 Digraphs. Definition 1 1 Digraphs Definition 1 Adigraphordirected graphgisatriplecomprisedofavertex set V(G), edge set E(G), and a function assigning each edge an ordered pair of vertices (tail, head); these vertices together

More information

Math 777 Graph Theory, Spring, 2006 Lecture Note 1 Planar graphs Week 1 Weak 2

Math 777 Graph Theory, Spring, 2006 Lecture Note 1 Planar graphs Week 1 Weak 2 Math 777 Graph Theory, Spring, 006 Lecture Note 1 Planar graphs Week 1 Weak 1 Planar graphs Lectured by Lincoln Lu Definition 1 A drawing of a graph G is a function f defined on V (G) E(G) that assigns

More information

Notebook Assignments

Notebook Assignments Notebook Assignments These six assignments are a notebook using techniques from class in the single concrete context of graph theory. This is supplemental to your usual assignments, and is designed for

More information

Math 443/543 Graph Theory Notes 11: Graph minors and Kuratowski s Theorem

Math 443/543 Graph Theory Notes 11: Graph minors and Kuratowski s Theorem Math 443/543 Graph Theory Notes 11: Graph minors and Kuratowski s Theorem David Glickenstein November 26, 2008 1 Graph minors Let s revisit some de nitions. Let G = (V; E) be a graph. De nition 1 Removing

More information

1 Matchings with Tutte s Theorem

1 Matchings with Tutte s Theorem 1 Matchings with Tutte s Theorem Last week we saw a fairly strong necessary criterion for a graph to have a perfect matching. Today we see that this condition is in fact sufficient. Theorem 1 (Tutte, 47).

More information

PACKING DIGRAPHS WITH DIRECTED CLOSED TRAILS

PACKING DIGRAPHS WITH DIRECTED CLOSED TRAILS PACKING DIGRAPHS WITH DIRECTED CLOSED TRAILS PAUL BALISTER Abstract It has been shown [Balister, 2001] that if n is odd and m 1,, m t are integers with m i 3 and t i=1 m i = E(K n) then K n can be decomposed

More information

Definition 1.1. A matching M in a graph G is called maximal if there is no matching M in G so that M M.

Definition 1.1. A matching M in a graph G is called maximal if there is no matching M in G so that M M. 1 Matchings Before, we defined a matching as a set of edges no two of which share an end in common. Suppose that we have a set of jobs and people and we want to match as many jobs to people as we can.

More information

HW Graph Theory Name (andrewid) - X. 1: Draw K 7 on a torus with no edge crossings.

HW Graph Theory Name (andrewid) - X. 1: Draw K 7 on a torus with no edge crossings. 1: Draw K 7 on a torus with no edge crossings. A quick calculation reveals that an embedding of K 7 on the torus is a -cell embedding. At that point, it is hard to go wrong if you start drawing C 3 faces,

More information

On vertex types of graphs

On vertex types of graphs On vertex types of graphs arxiv:1705.09540v1 [math.co] 26 May 2017 Pu Qiao, Xingzhi Zhan Department of Mathematics, East China Normal University, Shanghai 200241, China Abstract The vertices of a graph

More information

Graph Theory Mini-course

Graph Theory Mini-course Graph Theory Mini-course Anthony Varilly PROMYS, Boston University, Boston, MA 02215 Abstract Intuitively speaking, a graph is a collection of dots and lines joining some of these dots. Many problems in

More information

An Investigation of the Planarity Condition of Grötzsch s Theorem

An Investigation of the Planarity Condition of Grötzsch s Theorem Le Chen An Investigation of the Planarity Condition of Grötzsch s Theorem The University of Chicago: VIGRE REU 2007 July 16, 2007 Abstract The idea for this paper originated from Professor László Babai

More information

Discrete Applied Mathematics. A revision and extension of results on 4-regular, 4-connected, claw-free graphs

Discrete Applied Mathematics. A revision and extension of results on 4-regular, 4-connected, claw-free graphs Discrete Applied Mathematics 159 (2011) 1225 1230 Contents lists available at ScienceDirect Discrete Applied Mathematics journal homepage: www.elsevier.com/locate/dam A revision and extension of results

More information

MATH 350 GRAPH THEORY & COMBINATORICS. Contents

MATH 350 GRAPH THEORY & COMBINATORICS. Contents MATH 350 GRAPH THEORY & COMBINATORICS PROF. SERGEY NORIN, FALL 2013 Contents 1. Basic definitions 1 2. Connectivity 2 3. Trees 3 4. Spanning Trees 3 5. Shortest paths 4 6. Eulerian & Hamiltonian cycles

More information

Matching and Factor-Critical Property in 3-Dominating-Critical Graphs

Matching and Factor-Critical Property in 3-Dominating-Critical Graphs Matching and Factor-Critical Property in 3-Dominating-Critical Graphs Tao Wang a,, Qinglin Yu a,b a Center for Combinatorics, LPMC Nankai University, Tianjin, China b Department of Mathematics and Statistics

More information

Math 778S Spectral Graph Theory Handout #2: Basic graph theory

Math 778S Spectral Graph Theory Handout #2: Basic graph theory Math 778S Spectral Graph Theory Handout #: Basic graph theory Graph theory was founded by the great Swiss mathematician Leonhard Euler (1707-178) after he solved the Königsberg Bridge problem: Is it possible

More information

arxiv: v1 [cs.dm] 13 Apr 2012

arxiv: v1 [cs.dm] 13 Apr 2012 A Kuratowski-Type Theorem for Planarity of Partially Embedded Graphs Vít Jelínek, Jan Kratochvíl, Ignaz Rutter arxiv:1204.2915v1 [cs.dm] 13 Apr 2012 Abstract A partially embedded graph (or Peg) is a triple

More information

8 Colouring Planar Graphs

8 Colouring Planar Graphs 8 Colouring Planar Graphs The Four Colour Theorem Lemma 8.1 If G is a simple planar graph, then (i) 12 v V (G)(6 deg(v)) with equality for triangulations. (ii) G has a vertex of degree 5. Proof: For (i),

More information

CS473-Algorithms I. Lecture 13-A. Graphs. Cevdet Aykanat - Bilkent University Computer Engineering Department

CS473-Algorithms I. Lecture 13-A. Graphs. Cevdet Aykanat - Bilkent University Computer Engineering Department CS473-Algorithms I Lecture 3-A Graphs Graphs A directed graph (or digraph) G is a pair (V, E), where V is a finite set, and E is a binary relation on V The set V: Vertex set of G The set E: Edge set of

More information

CHAPTER 2. Graphs. 1. Introduction to Graphs and Graph Isomorphism

CHAPTER 2. Graphs. 1. Introduction to Graphs and Graph Isomorphism CHAPTER 2 Graphs 1. Introduction to Graphs and Graph Isomorphism 1.1. The Graph Menagerie. Definition 1.1.1. A simple graph G = (V, E) consists of a set V of vertices and a set E of edges, represented

More information

Computing Linkless and Flat Embeddings of Graphs in R 3

Computing Linkless and Flat Embeddings of Graphs in R 3 Computing Linkless and Flat Embeddings of Graphs in R 3 Stephan Kreutzer Technical University Berlin based on joint work with Ken-ichi Kawarabayashi, Bojan Mohar and Bruce Reed Graph Theory @ Georgie Tech

More information

Infinite locally random graphs

Infinite locally random graphs Infinite locally random graphs Pierre Charbit and Alex D. Scott Abstract Motivated by copying models of the web graph, Bonato and Janssen [3] introduced the following simple construction: given a graph

More information

Naming Angles. One complete rotation measures 360º. Half a rotation would then measure 180º. A quarter rotation would measure 90º.

Naming Angles. One complete rotation measures 360º. Half a rotation would then measure 180º. A quarter rotation would measure 90º. Naming Angles What s the secret for doing well in geometry? Knowing all the angles. An angle can be seen as a rotation of a line about a fixed point. In other words, if I were mark a point on a paper,

More information

Key Graph Theory Theorems

Key Graph Theory Theorems Key Graph Theory Theorems Rajesh Kumar MATH 239 Intro to Combinatorics August 19, 2008 3.3 Binary Trees 3.3.1 Problem (p.82) Determine the number, t n, of binary trees with n edges. The number of binary

More information

PETAL GRAPHS. Vellore, INDIA

PETAL GRAPHS. Vellore, INDIA International Journal of Pure and Applied Mathematics Volume 75 No. 3 2012, 269-278 ISSN: 1311-8080 (printed version) url: http://www.ijpam.eu PA ijpam.eu PETAL GRAPHS V. Kolappan 1, R. Selva Kumar 2 1,2

More information

HW Graph Theory SOLUTIONS (hbovik)

HW Graph Theory SOLUTIONS (hbovik) Diestel 1.3: Let G be a graph containing a cycle C, and assume that G contains a path P of length at least k between two vertices of C. Show that G contains a cycle of length at least k. If C has length

More information

A Reduction of Conway s Thrackle Conjecture

A Reduction of Conway s Thrackle Conjecture A Reduction of Conway s Thrackle Conjecture Wei Li, Karen Daniels, and Konstantin Rybnikov Department of Computer Science and Department of Mathematical Sciences University of Massachusetts, Lowell 01854

More information

Synthetic Geometry. 1.1 Foundations 1.2 The axioms of projective geometry

Synthetic Geometry. 1.1 Foundations 1.2 The axioms of projective geometry Synthetic Geometry 1.1 Foundations 1.2 The axioms of projective geometry Foundations Def: A geometry is a pair G = (Ω, I), where Ω is a set and I a relation on Ω that is symmetric and reflexive, i.e. 1.

More information

DO NOT RE-DISTRIBUTE THIS SOLUTION FILE

DO NOT RE-DISTRIBUTE THIS SOLUTION FILE Professor Kindred Math 104, Graph Theory Homework 2 Solutions February 7, 2013 Introduction to Graph Theory, West Section 1.2: 26, 38, 42 Section 1.3: 14, 18 Section 2.1: 26, 29, 30 DO NOT RE-DISTRIBUTE

More information

definition. An angle is the union of two rays with a common end point.

definition. An angle is the union of two rays with a common end point. Chapter 3 Angles What s the secret for doing well in geometry? Knowing all the angles. As we did in the last chapter, we will introduce new terms and new notations, the building blocks for our success.

More information

Number Theory and Graph Theory

Number Theory and Graph Theory 1 Number Theory and Graph Theory Chapter 6 Basic concepts and definitions of graph theory By A. Satyanarayana Reddy Department of Mathematics Shiv Nadar University Uttar Pradesh, India E-mail: satya8118@gmail.com

More information

Lecture 4: Walks, Trails, Paths and Connectivity

Lecture 4: Walks, Trails, Paths and Connectivity Lecture 4: Walks, Trails, Paths and Connectivity Rosa Orellana Math 38 April 6, 2015 Graph Decompositions Def: A decomposition of a graph is a list of subgraphs such that each edge appears in exactly one

More information

Chapter 3 Trees. Theorem A graph T is a tree if, and only if, every two distinct vertices of T are joined by a unique path.

Chapter 3 Trees. Theorem A graph T is a tree if, and only if, every two distinct vertices of T are joined by a unique path. Chapter 3 Trees Section 3. Fundamental Properties of Trees Suppose your city is planning to construct a rapid rail system. They want to construct the most economical system possible that will meet the

More information

Definition 1 (Hand-shake model). A hand shake model is an incidence geometry for which every line has exactly two points.

Definition 1 (Hand-shake model). A hand shake model is an incidence geometry for which every line has exactly two points. Math 3181 Dr. Franz Rothe Name: All3181\3181_spr13t1.tex 1 Solution of Test I Definition 1 (Hand-shake model). A hand shake model is an incidence geometry for which every line has exactly two points. Definition

More information

The statement implies that any three intersection points of two distinct planes lie on a line.

The statement implies that any three intersection points of two distinct planes lie on a line. Math 3181 Dr. Franz Rothe February 23, 2015 All3181\3181_spr15ts1.tex 1 Solution of Test Name: Problem 1.1. The second part of Hilbert s Proposition 1 states: Any two different planes have either no point

More information

A Practical 4-coloring Method of Planar Graphs

A Practical 4-coloring Method of Planar Graphs A Practical 4-coloring Method of Planar Graphs Mingshen Wu 1 and Weihu Hong 2 1 Department of Math, Stat, and Computer Science, University of Wisconsin-Stout, Menomonie, WI 54751 2 Department of Mathematics,

More information

Graph Theory. 1 Introduction to Graphs. Martin Stynes Department of Mathematics, UCC January 26, 2011

Graph Theory. 1 Introduction to Graphs. Martin Stynes Department of Mathematics, UCC   January 26, 2011 Graph Theory Martin Stynes Department of Mathematics, UCC email: m.stynes@ucc.ie January 26, 2011 1 Introduction to Graphs 1 A graph G = (V, E) is a non-empty set of nodes or vertices V and a (possibly

More information

INTRODUCTION TO THE HOMOLOGY GROUPS OF COMPLEXES

INTRODUCTION TO THE HOMOLOGY GROUPS OF COMPLEXES INTRODUCTION TO THE HOMOLOGY GROUPS OF COMPLEXES RACHEL CARANDANG Abstract. This paper provides an overview of the homology groups of a 2- dimensional complex. It then demonstrates a proof of the Invariance

More information

Assignment # 4 Selected Solutions

Assignment # 4 Selected Solutions Assignment # 4 Selected Solutions Problem 2.3.3 Let G be a connected graph which is not a tree (did you notice this is redundant?) and let C be a cycle in G. Prove that the complement of any spanning tree

More information

Math 443/543 Graph Theory Notes 5: Planar graphs and coloring

Math 443/543 Graph Theory Notes 5: Planar graphs and coloring Math 443/543 Graph Theory Notes 5: Planar graphs and coloring David Glickenstein October 10, 2014 1 Planar graphs The Three Houses and Three Utilities Problem: Given three houses and three utilities, can

More information

V10 Metabolic networks - Graph connectivity

V10 Metabolic networks - Graph connectivity V10 Metabolic networks - Graph connectivity Graph connectivity is related to analyzing biological networks for - finding cliques - edge betweenness - modular decomposition that have been or will be covered

More information

2010 SMT Power Round

2010 SMT Power Round Definitions 2010 SMT Power Round A graph is a collection of points (vertices) connected by line segments (edges). In this test, all graphs will be simple any two vertices will be connected by at most one

More information

Rigidity, connectivity and graph decompositions

Rigidity, connectivity and graph decompositions First Prev Next Last Rigidity, connectivity and graph decompositions Brigitte Servatius Herman Servatius Worcester Polytechnic Institute Page 1 of 100 First Prev Next Last Page 2 of 100 We say that a framework

More information

The planar cubic Cayley graphs of connectivity 2

The planar cubic Cayley graphs of connectivity 2 The planar cubic Cayley graphs of connectivity 2 Agelos Georgakopoulos Technische Universität Graz Steyrergasse 30, 8010 Graz, Austria March 2, 2011 Abstract We classify the planar cubic Cayley graphs

More information

MC302 GRAPH THEORY SOLUTIONS TO HOMEWORK #1 9/19/13 68 points + 6 extra credit points

MC302 GRAPH THEORY SOLUTIONS TO HOMEWORK #1 9/19/13 68 points + 6 extra credit points MC02 GRAPH THEORY SOLUTIONS TO HOMEWORK #1 9/19/1 68 points + 6 extra credit points 1. [CH] p. 1, #1... a. In each case, for the two graphs you say are isomorphic, justify it by labeling their vertices

More information

Haga's Origamics. Haga's Origamics are a series of activities designed to illustrate the science behind simple paper folding.

Haga's Origamics. Haga's Origamics are a series of activities designed to illustrate the science behind simple paper folding. Haga's Origamics Haga's Origamics are a series of activities designed to illustrate the science behind simple paper folding. Activity I : TUPS (Turned-Up Parts) Take a square piece of paper and label the

More information

CHAPTER 8. Copyright Cengage Learning. All rights reserved.

CHAPTER 8. Copyright Cengage Learning. All rights reserved. CHAPTER 8 RELATIONS Copyright Cengage Learning. All rights reserved. SECTION 8.3 Equivalence Relations Copyright Cengage Learning. All rights reserved. The Relation Induced by a Partition 3 The Relation

More information

Rubber bands. Chapter Rubber band representation

Rubber bands. Chapter Rubber band representation Chapter 1 Rubber bands In the previous chapter, we already used the idea of looking at the graph geometrically, by placing its nodes on the line and replacing the edges by rubber bands. Since, however,

More information

Graph Theory S 1 I 2 I 1 S 2 I 1 I 2

Graph Theory S 1 I 2 I 1 S 2 I 1 I 2 Graph Theory S I I S S I I S Graphs Definition A graph G is a pair consisting of a vertex set V (G), and an edge set E(G) ( ) V (G). x and y are the endpoints of edge e = {x, y}. They are called adjacent

More information

CS 217 Algorithms and Complexity Homework Assignment 2

CS 217 Algorithms and Complexity Homework Assignment 2 CS 217 Algorithms and Complexity Homework Assignment 2 Shanghai Jiaotong University, Fall 2015 Handed out on 2015-10-19 Due on 2015-10-26 You can hand in your solution either as a printed file or hand-written

More information

REU 2006 Discrete Math Lecture 5

REU 2006 Discrete Math Lecture 5 REU 2006 Discrete Math Lecture 5 Instructor: László Babai Scribe: Megan Guichard Editors: Duru Türkoğlu and Megan Guichard June 30, 2006. Last updated July 3, 2006 at 11:30pm. 1 Review Recall the definitions

More information

1. a graph G = (V (G), E(G)) consists of a set V (G) of vertices, and a set E(G) of edges (edges are pairs of elements of V (G))

1. a graph G = (V (G), E(G)) consists of a set V (G) of vertices, and a set E(G) of edges (edges are pairs of elements of V (G)) 10 Graphs 10.1 Graphs and Graph Models 1. a graph G = (V (G), E(G)) consists of a set V (G) of vertices, and a set E(G) of edges (edges are pairs of elements of V (G)) 2. an edge is present, say e = {u,

More information

(Refer Slide Time: 06:01)

(Refer Slide Time: 06:01) Data Structures and Algorithms Dr. Naveen Garg Department of Computer Science and Engineering Indian Institute of Technology, Delhi Lecture 28 Applications of DFS Today we are going to be talking about

More information

Graph Theory: Introduction

Graph Theory: Introduction Graph Theory: Introduction Pallab Dasgupta, Professor, Dept. of Computer Sc. and Engineering, IIT Kharagpur pallab@cse.iitkgp.ernet.in Resources Copies of slides available at: http://www.facweb.iitkgp.ernet.in/~pallab

More information

MAT 3271: Selected Solutions to the Assignment 6

MAT 3271: Selected Solutions to the Assignment 6 Chapter 2: Major Exercises MAT 3271: Selected Solutions to the Assignment 6 1. Since a projective plan is a model of incidence geometry, Incidence Axioms 1-3 and Propositions 2.1-2.5 (which follow logically

More information

Assignment 4 Solutions of graph problems

Assignment 4 Solutions of graph problems Assignment 4 Solutions of graph problems 1. Let us assume that G is not a cycle. Consider the maximal path in the graph. Let the end points of the path be denoted as v 1, v k respectively. If either of

More information

CS6702 GRAPH THEORY AND APPLICATIONS 2 MARKS QUESTIONS AND ANSWERS

CS6702 GRAPH THEORY AND APPLICATIONS 2 MARKS QUESTIONS AND ANSWERS CS6702 GRAPH THEORY AND APPLICATIONS 2 MARKS QUESTIONS AND ANSWERS 1 UNIT I INTRODUCTION CS6702 GRAPH THEORY AND APPLICATIONS 2 MARKS QUESTIONS AND ANSWERS 1. Define Graph. A graph G = (V, E) consists

More information

Introduction to Graphs

Introduction to Graphs Introduction to Graphs Slides by Lap Chi Lau The Chinese University of Hong Kong This Lecture In this part we will study some basic graph theory. Graph is a useful concept to model many problems in computer

More information

DO NOT RE-DISTRIBUTE THIS SOLUTION FILE

DO NOT RE-DISTRIBUTE THIS SOLUTION FILE Professor Kindred Math 104, Graph Theory Homework 3 Solutions February 14, 2013 Introduction to Graph Theory, West Section 2.1: 37, 62 Section 2.2: 6, 7, 15 Section 2.3: 7, 10, 14 DO NOT RE-DISTRIBUTE

More information

3-connected {K 1,3, P 9 }-free graphs are hamiltonian connected

3-connected {K 1,3, P 9 }-free graphs are hamiltonian connected 3-connected {K 1,3, P 9 }-free graphs are hamiltonian connected Qiuju Bian 1, Ronald J. Gould 2, Paul Horn 3, Susan Janiszewski 2, Steven La Fleur 2, Paul Wrayno 4 1 School of Mathematics and Information

More information

Answers to specimen paper questions. Most of the answers below go into rather more detail than is really needed. Please let me know of any mistakes.

Answers to specimen paper questions. Most of the answers below go into rather more detail than is really needed. Please let me know of any mistakes. Answers to specimen paper questions Most of the answers below go into rather more detail than is really needed. Please let me know of any mistakes. Question 1. (a) The degree of a vertex x is the number

More information

Paths. Path is a sequence of edges that begins at a vertex of a graph and travels from vertex to vertex along edges of the graph.

Paths. Path is a sequence of edges that begins at a vertex of a graph and travels from vertex to vertex along edges of the graph. Paths Path is a sequence of edges that begins at a vertex of a graph and travels from vertex to vertex along edges of the graph. Formal Definition of a Path (Undirected) Let n be a nonnegative integer

More information

Introduction to Graph Theory

Introduction to Graph Theory Introduction to Graph Theory Tandy Warnow January 20, 2017 Graphs Tandy Warnow Graphs A graph G = (V, E) is an object that contains a vertex set V and an edge set E. We also write V (G) to denote the vertex

More information

1 Solution of Homework I

1 Solution of Homework I Math 3181 Dr. Franz Rothe Name: All3181\3181_spr13h1.tex 1 Solution of Homework I 10 Problem 1.1. As far as two-dimensional geometry is concerned, Hilbert s Proposition 1 reduces to one simple statement:

More information

Let s use a more formal definition. An angle is the union of two rays with a common end point.

Let s use a more formal definition. An angle is the union of two rays with a common end point. hapter 2 ngles What s the secret for doing well in geometry? Knowing all the angles. s we did in the last chapter, we will introduce new terms and new notations, the building blocks for our success. gain,

More information

Problem Set 2 Solutions

Problem Set 2 Solutions Problem Set 2 Solutions Graph Theory 2016 EPFL Frank de Zeeuw & Claudiu Valculescu 1. Prove that the following statements about a graph G are equivalent. - G is a tree; - G is minimally connected (it is

More information

VIZING S THEOREM AND EDGE-CHROMATIC GRAPH THEORY. Contents

VIZING S THEOREM AND EDGE-CHROMATIC GRAPH THEORY. Contents VIZING S THEOREM AND EDGE-CHROMATIC GRAPH THEORY ROBERT GREEN Abstract. This paper is an expository piece on edge-chromatic graph theory. The central theorem in this subject is that of Vizing. We shall

More information

Graph Theory Day Four

Graph Theory Day Four Graph Theory Day Four February 8, 018 1 Connected Recall from last class, we discussed methods for proving a graph was connected. Our two methods were 1) Based on the definition, given any u, v V(G), there

More information

Module 11. Directed Graphs. Contents

Module 11. Directed Graphs. Contents Module 11 Directed Graphs Contents 11.1 Basic concepts......................... 256 Underlying graph of a digraph................ 257 Out-degrees and in-degrees.................. 258 Isomorphism..........................

More information

V :non-empty vertex ornode set E V V :edge set G (V, E) :directed graph on V, or digraph on V

V :non-empty vertex ornode set E V V :edge set G (V, E) :directed graph on V, or digraph on V -93-11. Graph Theory Example: V :non-empty vertex ornode set E V V :edge set G (V, E) :directed graph on V, or digraph on V b e f V={a, b, c, d, e, f, g} a c d f E={(a,b), (b,c), (c,a),... } Note: (a,

More information

Independence Number and Cut-Vertices

Independence Number and Cut-Vertices Independence Number and Cut-Vertices Ryan Pepper University of Houston Downtown, Houston, Texas 7700 pepperr@uhd.edu Abstract We show that for any connected graph G, α(g) C(G) +1, where α(g) is the independence

More information