Math 222 (A1) Solutions to Assignment 4

Size: px
Start display at page:

Download "Math 222 (A1) Solutions to Assignment 4"

Transcription

1 Math (1) Solutions to ssignment 1. We have captured several people whom we suspect are part of a spy ring. They are identified as,,,,,, and. fter interrogation, admits to having met the other six. admits to having met five, to having met four, to having met three, to having met two, to having met two, and to having met one. None of them would identify whom they knew, and no spy would claim to have met more people than he has actually met. ssume that is telling the truth and there is only one liar. Who is the lying spy, if it is known in addition that the number of acquaintances he gives is 3 less than the true value? Why? irst recall the following from class: In the acquaintanceship graph, with vertices being the spies and with an edge between two vertices if and only if the corresponding spies have met, if all of the spies were telling the truth, there would be an even number of vertices with odd degree, but the degree sequence is deg() = 6, deg() =, deg() =, deg() = 3, deg() =, deg( ) =, deg() = 1. Therefore, not all of the spies are telling the truth. We know that is telling the truth and there is only one liar. ny spy who lies will claim to know less than he actually does, so must be telling the truth, since there are only 6 other spies. lso, is telling the truth, since if not, then has met 6 or more spies, which implies that has met and, thus would also be lying, but there is only one liar. If both and are telling the truth, then one of or is lying, and since deg() = 1, then has met all of,,,, and, and the situation (so far) is as shown in the diagram. If is lying, then deg(), and this leads to a contradiction. Similarly, if is lying, then deg(), and this also leads to a contradiction. Therefore, the liar is either or. This much we did in class. Solution: To solve the problem, we now consider now the two possible cases. ase 1. is lying and is telling the truth. In this case, would have met only, and since is lying, then has met + 3 = other spies, and since he cannot have met, he must have met,,, and. ut, who is telling the truth, has met others, namely,,,, and, and has met all 6 others. Thus,, and have all met, but this would make a liar, which is a contradiction. Thus, this case cannot occur. ase. is telling the truth and is lying. If is lying, he must have met = other spies, and the graph shows that this case is possible. Thus, the lying spy is. 1

2 . substantial collection of jewels is in a chest in one of two underground labyrinths, and they are in a room with an odd number of doors. ach door connects two different rooms. The first labyrinth has two entrance doors and the other has three, and only one of these labyrinths has any rooms with an odd number of doors. ssume that the labyrinth with two entrance doors does not contain any room with an odd number of doors. Prove that it is possible to enter this labyrinth by one entrance door and exit by the other. Solution: We know from the hypotheses that the labyrinth with two entrance doors has only rooms with an even number of doors. Suppose it is not possible to enter through one entrance door and exit by the other. Remove all of the labyrinth except for the part accessible from one of the entrance doors. In other words, look at the component that contains one of the entrance doors. onsider the graph that represents this component, where the area outside the labyrinth is represented by one vertex and the rooms are represented by other vertices. oors are represented by edges between the vertices. The graph is connected (all rooms belong to the same component) and the outside vertex has degree exactly one. y the parity theorem, there must be an even number of vertices with odd degree, which means that at least one other door has odd degree. ut this vertex would then represent a room with an odd number of doors. However, this room is part of the original labyrinth. Thus, we have a contradiction. 3. There are seven code words, denoted by,,,,,, and. ll code words have different frequencies: occurs on the average of 10 times out of 100;, 0 out of 100;, 9 out of 100;, 31 out of 100;, out of 100;, out of 100; and, 19 out of 100. ll our messages are to be sent in dots and dashes, but unlike Morse code, which has pauses between letters, we want the code words to go out without pauses. Trained people can send dots accurately at the rate of two per second, including the silence before the next dot or dash. ashes are slower, however, achieving rates of only one per second. Suppose that we are not allowed to use dot dot as a code word. esign an unambiguous code such that an average message of 100 code words takes no more than 00 seconds. Solution: ach code word is represented by a dash followed by 0 to 6 dots. Those with higher frequencies have fewer dots, so the codes would be assigned as follows: = = = = = = = Since each dash signifies the beginning of a code word, there is no ambiguity. This code will take = 191. seconds to send the 100 code words. Other more efficient solutions are possible. I believe the record for the past years is 186. seconds.

3 . tiger of the fiercest species has escaped from a zoo and is hiding in an abandoned temple. The zoo has keepers who are trained to catch tigers. The tiger may be in any room. The tiger may run from one room to another while they are looking for it, although it won t run into a room that has a keeper in it. The temple has no windows and only one entrance. Of its rooms, all but one connect to one other room or to three others. The last room connects to two other rooms. There are no doors of any kind between rooms. The rooms are dark and the tiger may find many hiding places, even though none of the rooms is very large. There is only one way to walk from any room to any other in the temple. We do not want to lay traps or put barriers between rooms. The temple is small enough that moving from room to room takes almost no time. oing a thorough search of a room takes a keeper 0 minutes. If he finds the tiger he can use his stun gun. Time is of the essence, because the tiger can scatch its way through various parts of the temple wall in under three hours. It is imperative that at no time should the tiger have a free path to the entrance. esign the layout of the temple with the properties above as stated by hief Inspector Singh, so that an escaped tiger inside the temple can be trapped by two keepers in hours and 0 minutes. What is the maximum number of rooms? Solution: In hours and 0 minutes, each keeper can search up to a maximum of rooms, so the number of rooms cannot be greater than 1. onsider the rooms as being the vertices of a graph and the connections between the rooms as being the edges (we are ignoring the entrance door). One vertex has degree exactly, all the others have degree 3 or 1. There must be an even number of vertices with odd degree, so there can be a maximum of 1 vertices with odd degree. Thus there can be no more than 13 rooms in the temple. The diagram below shows that 13 rooms are possible. The two keepers can search the rooms in alphabetical order, and can find the tiger in hours and 0 minutes. I K H J L M. graph has 11 vertices labeled to K, and the following 18 edges with their lengths given: (8), (), (), (6), (), (), (), (), () H(), H(), I(), J(), I(), J(), HK(), IK(), JK() pply Kruskal s algorithm to construct a minimum-length spanning tree. Solution: We apply Kruskal s algorithm as summarized in the following chart. I I H H J J HK JK H I J K

4 The graphical solution below is also acceptable. The edges were selected using the order of the edges as given in the previous table. K 8 J 6 I H 6. pply ijkstra s algorithm to construct a shortest-path spanning tree from the vertex in the graph in the preceding problem. Solution: We apply ijkstra s algorithm as summarized in the following chart: H I J K, 0,,,,,,,,,,, 8,,,,,,,,,, 8,, 9,10,,,,,, 8, 9,10, 9,,,,, 9,10, 9,,,,,10, 9,13,,,,10,13,11,13,,13,11,13,,13,13 I,16,13 I,16 I,16 I H J IK

5 graphical solution is given below, and is also acceptable. Using ijkstra s algorithm, starting at, the shortest-path spanning tree for the graph is shown below: K 8 J 6 I H. graph consists of vertices V 1, V, V 3, V, V, V 6, V. Two vertices V i and V j are joined by an edge if and only if the absolute difference between i and j is neither 3 nor. Is this graph planar? If so, draw it without crossing edges. If not, explain why not. Solution: The graph is nonplanar since it contains a subdivision of K 3,3 (see the diagram below). V 1 V 1 V V V V V 6 V 6 V 3 V 3 V V V V (original graph) (subdivision of K 3,3 ) elete the edges V V 3, V V, V 6 V, and V V 1, from the original graph, and the resulting subgraph has V, V 3, and V 6 in one bipartition set and V 1, V, and V in the other bipartition set, with V subdividing the edge V V.

6 8. labyrinth contains 1 rooms. ach room is connected to at least 6 others by a direct tunnel that does not pass through any other room. ach of nine of the rooms are directly connected to at least others. Show that you can pass from one room to any other room by a sequence of tunnels. Solution: onsider the graph whose vertices are the rooms, where there is an edge joining two vertices if and only if there is at least one tunnel directly connecting the corresponding rooms. Supposing that the graph is not connected, then it has at least two connected components, and each component must contain at least vertices, since each room is connected to at least 6 others. Since 1 = + 8, the graph can only have two connected components, one containing vertices and the other containing 8 vertices. Now, there are nine rooms each connected to at least others. Since the component with eight vertices cannot account for all of these, at least one of these nine rooms must belong to the other component. That is, in the component with rooms, one of the rooms is adjacent to others. ut this is a contradiction, since in a -vertex component, each vertex is adjacent to at most 6 others. Therefore the graph must be connected. Note: With only 8 rooms connected to others (instead of 9) it is possible to have components, namely K + K 8. 6

Solutions to Assignment 5

Solutions to Assignment 5 Solutions to ssignment 5. We have captured several people whom we suspect are part of a spy ring. They are identified as,,,, E, F, and G. fter interrogation, admits to having met the other six. admits

More information

The Six Color Theorem

The Six Color Theorem The Six Color Theorem The Six Color Theorem Theorem. Let G be a planar graph. There exists a proper -coloring of G. Proof. Let G be a the smallest planar graph (by number of vertices) that has no proper

More information

Math 485, Graph Theory: Homework #3

Math 485, Graph Theory: Homework #3 Math 485, Graph Theory: Homework #3 Stephen G Simpson Due Monday, October 26, 2009 The assignment consists of Exercises 2129, 2135, 2137, 2218, 238, 2310, 2313, 2314, 2315 in the West textbook, plus the

More information

Definition For vertices u, v V (G), the distance from u to v, denoted d(u, v), in G is the length of a shortest u, v-path. 1

Definition For vertices u, v V (G), the distance from u to v, denoted d(u, v), in G is the length of a shortest u, v-path. 1 Graph fundamentals Bipartite graph characterization Lemma. If a graph contains an odd closed walk, then it contains an odd cycle. Proof strategy: Consider a shortest closed odd walk W. If W is not a cycle,

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

Ma/CS 6b Class 5: Graph Connectivity

Ma/CS 6b Class 5: Graph Connectivity Ma/CS 6b Class 5: Graph Connectivity By Adam Sheffer Communications Network We are given a set of routers and wish to connect pairs of them to obtain a connected communications network. The network should

More information

Kuratowski Notes , Fall 2005, Prof. Peter Shor Revised Fall 2007

Kuratowski Notes , Fall 2005, Prof. Peter Shor Revised Fall 2007 Kuratowski Notes 8.30, Fall 005, Prof. Peter Shor Revised Fall 007 Unfortunately, the OCW notes on Kuratowski s theorem seem to have several things substantially wrong with the proof, and the notes from

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

Topic 10 Part 2 [474 marks]

Topic 10 Part 2 [474 marks] Topic Part 2 [474 marks] The complete graph H has the following cost adjacency matrix Consider the travelling salesman problem for H a By first finding a minimum spanning tree on the subgraph of H formed

More information

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

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

Math 100 Homework 4 B A C E

Math 100 Homework 4 B A C E Math 100 Homework 4 Part 1 1. nswer the following questions for this graph. (a) Write the vertex set. (b) Write the edge set. (c) Is this graph connected? (d) List the degree of each vertex. (e) oes the

More information

Discrete Wiskunde II. Lecture 6: Planar Graphs

Discrete Wiskunde II. Lecture 6: Planar Graphs , 2009 Lecture 6: Planar Graphs University of Twente m.uetz@utwente.nl wwwhome.math.utwente.nl/~uetzm/dw/ Planar Graphs Given an undirected graph (or multigraph) G = (V, E). A planar embedding of G is

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

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

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

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

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

Problem Set 3. MATH 776, Fall 2009, Mohr. November 30, 2009

Problem Set 3. MATH 776, Fall 2009, Mohr. November 30, 2009 Problem Set 3 MATH 776, Fall 009, Mohr November 30, 009 1 Problem Proposition 1.1. Adding a new edge to a maximal planar graph of order at least 6 always produces both a T K 5 and a T K 3,3 subgraph. Proof.

More information

Math 443/543 Graph Theory Notes 2: Transportation problems

Math 443/543 Graph Theory Notes 2: Transportation problems Math 443/543 Graph Theory Notes 2: Transportation problems David Glickenstein September 15, 2014 1 Readings This is based on Chartrand Chapter 3 and Bondy-Murty 18.1, 18.3 (part on Closure of a Graph).

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

Theorem 3.1 (Berge) A matching M in G is maximum if and only if there is no M- augmenting path.

Theorem 3.1 (Berge) A matching M in G is maximum if and only if there is no M- augmenting path. 3 Matchings Hall s Theorem Matching: A matching in G is a subset M E(G) so that no edge in M is a loop, and no two edges in M are incident with a common vertex. A matching M is maximal if there is no matching

More information

14 More Graphs: Euler Tours and Hamilton Cycles

14 More Graphs: Euler Tours and Hamilton Cycles 14 More Graphs: Euler Tours and Hamilton Cycles 14.1 Degrees The degree of a vertex is the number of edges coming out of it. The following is sometimes called the First Theorem of Graph Theory : Lemma

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

Intermediate Math Circles Wednesday, February 8, 2017 Graph Theory I

Intermediate Math Circles Wednesday, February 8, 2017 Graph Theory I Intermediate Math Circles Wednesday, February 8, 2017 Graph Theory I Many of you are probably familiar with the term graph. To you a graph may mean a line or curve defined by a function y = f(x). It may

More information

Ma/CS 6b Class 4: Matchings in General Graphs

Ma/CS 6b Class 4: Matchings in General Graphs Ma/CS 6b Class 4: Matchings in General Graphs By Adam Sheffer Reminder: Hall's Marriage Theorem Theorem. Let G = V 1 V 2, E be a bipartite graph. There exists a matching of size V 1 in G if and only if

More information

FOUR EDGE-INDEPENDENT SPANNING TREES 1

FOUR EDGE-INDEPENDENT SPANNING TREES 1 FOUR EDGE-INDEPENDENT SPANNING TREES 1 Alexander Hoyer and Robin Thomas School of Mathematics Georgia Institute of Technology Atlanta, Georgia 30332-0160, USA ABSTRACT We prove an ear-decomposition theorem

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

v 1 v 2 r 3 r 4 v 3 v 4 Figure A plane embedding of K 4.

v 1 v 2 r 3 r 4 v 3 v 4 Figure A plane embedding of K 4. Chapter 6 Planarity Section 6.1 Euler s Formula In Chapter 1 we introduced the puzzle of the three houses and the three utilities. The problem was to determine if we could connect each of the three utilities

More information

Planar graphs. Chapter 8

Planar graphs. Chapter 8 Chapter 8 Planar graphs Definition 8.1. A graph is called planar if it can be drawn in the plane so that edges intersect only at vertices to which they are incident. Example 8.2. Different representations

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

SAMPLE. MODULE 5 Undirected graphs

SAMPLE. MODULE 5 Undirected graphs H P T R MOUL Undirected graphs How do we represent a graph by a diagram and by a matrix representation? How do we define each of the following: graph subgraph vertex edge (node) loop isolated vertex bipartite

More information

v V Question: How many edges are there in a graph with 10 vertices each of degree 6?

v V Question: How many edges are there in a graph with 10 vertices each of degree 6? ECS20 Handout Graphs and Trees March 4, 2015 (updated 3/9) Notion of a graph 1. A graph G = (V,E) consists of V, a nonempty set of vertices (or nodes) and E, a set of pairs of elements of V called edges.

More information

Characterizations of graph classes by forbidden configurations

Characterizations of graph classes by forbidden configurations Characterizations of graph classes by forbidden configurations Zdeněk Dvořák September 14, 2015 We consider graph classes that can be described by excluding some fixed configurations. Let us give some

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

MC 302 GRAPH THEORY 10/1/13 Solutions to HW #2 50 points + 6 XC points

MC 302 GRAPH THEORY 10/1/13 Solutions to HW #2 50 points + 6 XC points MC 0 GRAPH THEORY 0// Solutions to HW # 0 points + XC points ) [CH] p.,..7. This problem introduces an important class of graphs called the hypercubes or k-cubes, Q, Q, Q, etc. I suggest that before you

More information

An Introduction to Graph Theory

An Introduction to Graph Theory An Introduction to Graph Theory Evelyne Smith-Roberge University of Waterloo March 22, 2017 What is a graph? Definition A graph G is: a set V (G) of objects called vertices together with: a set E(G), of

More information

The angle measure at for example the vertex A is denoted by m A, or m BAC.

The angle measure at for example the vertex A is denoted by m A, or m BAC. MT 200 ourse notes on Geometry 5 2. Triangles and congruence of triangles 2.1. asic measurements. Three distinct lines, a, b and c, no two of which are parallel, form a triangle. That is, they divide the

More information

Hamiltonian cycles in bipartite quadrangulations on the torus

Hamiltonian cycles in bipartite quadrangulations on the torus Hamiltonian cycles in bipartite quadrangulations on the torus Atsuhiro Nakamoto and Kenta Ozeki Abstract In this paper, we shall prove that every bipartite quadrangulation G on the torus admits a simple

More information

Section 8.2 Graph Terminology. Undirected Graphs. Definition: Two vertices u, v in V are adjacent or neighbors if there is an edge e between u and v.

Section 8.2 Graph Terminology. Undirected Graphs. Definition: Two vertices u, v in V are adjacent or neighbors if there is an edge e between u and v. Section 8.2 Graph Terminology Undirected Graphs Definition: Two vertices u, v in V are adjacent or neighbors if there is an edge e between u and v. The edge e connects u and v. The vertices u and v are

More information

Math236 Discrete Maths with Applications

Math236 Discrete Maths with Applications Math236 Discrete Maths with Applications P. Ittmann UKZN, Pietermaritzburg Semester 1, 2012 Ittmann (UKZN PMB) Math236 2012 1 / 19 Degree Sequences Let G be a graph with vertex set V (G) = {v 1, v 2, v

More information

Chapter 11: Graphs and Trees. March 23, 2008

Chapter 11: Graphs and Trees. March 23, 2008 Chapter 11: Graphs and Trees March 23, 2008 Outline 1 11.1 Graphs: An Introduction 2 11.2 Paths and Circuits 3 11.3 Matrix Representations of Graphs 4 11.5 Trees Graphs: Basic Definitions Informally, a

More information

Order from Chaos. University of Nebraska-Lincoln Discrete Mathematics Seminar

Order from Chaos. University of Nebraska-Lincoln Discrete Mathematics Seminar Order from Chaos University of Nebraska-Lincoln Discrete Mathematics Seminar Austin Mohr Department of Mathematics Nebraska Wesleyan University February 8, 20 The (, )-Puzzle Start by drawing six dots

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

Discrete mathematics

Discrete mathematics Discrete mathematics Petr Kovář petr.kovar@vsb.cz VŠB Technical University of Ostrava DiM 470-2301/02, Winter term 2018/2019 About this file This file is meant to be a guideline for the lecturer. Many

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

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

Brief History. Graph Theory. What is a graph? Types of graphs Directed graph: a graph that has edges with specific directions

Brief History. Graph Theory. What is a graph? Types of graphs Directed graph: a graph that has edges with specific directions Brief History Graph Theory What is a graph? It all began in 1736 when Leonhard Euler gave a proof that not all seven bridges over the Pregolya River could all be walked over once and end up where you started.

More information

CPS 102: Discrete Mathematics. Quiz 3 Date: Wednesday November 30, Instructor: Bruce Maggs NAME: Prob # Score. Total 60

CPS 102: Discrete Mathematics. Quiz 3 Date: Wednesday November 30, Instructor: Bruce Maggs NAME: Prob # Score. Total 60 CPS 102: Discrete Mathematics Instructor: Bruce Maggs Quiz 3 Date: Wednesday November 30, 2011 NAME: Prob # Score Max Score 1 10 2 10 3 10 4 10 5 10 6 10 Total 60 1 Problem 1 [10 points] Find a minimum-cost

More information

Math 575 Exam 3. (t). What is the chromatic number of G?

Math 575 Exam 3. (t). What is the chromatic number of G? Math 575 Exam 3 Name 1 (a) Draw the Grötsch graph See your notes (b) Suppose that G is a graph having 6 vertices and 9 edges and that the chromatic polynomial of G is given below Fill in the missing coefficients

More information

[8] that this cannot happen on the projective plane (cf. also [2]) and the results of Robertson, Seymour, and Thomas [5] on linkless embeddings of gra

[8] that this cannot happen on the projective plane (cf. also [2]) and the results of Robertson, Seymour, and Thomas [5] on linkless embeddings of gra Apex graphs with embeddings of face-width three Bojan Mohar Department of Mathematics University of Ljubljana Jadranska 19, 61111 Ljubljana Slovenia bojan.mohar@uni-lj.si Abstract Aa apex graph is a graph

More information

Ma/CS 6b Class 12: Ramsey Theory

Ma/CS 6b Class 12: Ramsey Theory Ma/CS 6b Class 12: Ramsey Theory By Adam Sheffer The Pigeonhole Principle The pigeonhole principle. If n items are put into m containers, such that n > m, then at least one container contains more than

More information

5 Graphs

5 Graphs 5 Graphs jacques@ucsd.edu Some of the putnam problems are to do with graphs. They do not assume more than a basic familiarity with the definitions and terminology of graph theory. 5.1 Basic definitions

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

Planarity: dual graphs

Planarity: dual graphs : dual graphs Math 104, Graph Theory March 28, 2013 : dual graphs Duality Definition Given a plane graph G, the dual graph G is the plane graph whose vtcs are the faces of G. The correspondence between

More information

The Game of Criss-Cross

The Game of Criss-Cross Chapter 5 The Game of Criss-Cross Euler Characteristic ( ) Overview. The regions on a map and the faces of a cube both illustrate a very natural sort of situation: they are each examples of regions that

More information

5 Matchings in Bipartite Graphs and Their Applications

5 Matchings in Bipartite Graphs and Their Applications 5 Matchings in Bipartite Graphs and Their Applications 5.1 Matchings Definition 5.1 A matching M in a graph G is a set of edges of G, none of which is a loop, such that no two edges in M have a common

More information

Advanced Combinatorial Optimization September 17, Lecture 3. Sketch some results regarding ear-decompositions and factor-critical graphs.

Advanced Combinatorial Optimization September 17, Lecture 3. Sketch some results regarding ear-decompositions and factor-critical graphs. 18.438 Advanced Combinatorial Optimization September 17, 2009 Lecturer: Michel X. Goemans Lecture 3 Scribe: Aleksander Madry ( Based on notes by Robert Kleinberg and Dan Stratila.) In this lecture, we

More information

A generalization of Mader s theorem

A generalization of Mader s theorem A generalization of Mader s theorem Ajit A. Diwan Department of Computer Science and Engineering Indian Institute of Technology, Bombay Mumbai, 4000076, India. email: aad@cse.iitb.ac.in 18 June 2007 Abstract

More information

INTRODUCTION TO GRAPH THEORY. 1. Definitions

INTRODUCTION TO GRAPH THEORY. 1. Definitions INTRODUCTION TO GRAPH THEORY D. JAKOBSON 1. Definitions A graph G consists of vertices {v 1, v 2,..., v n } and edges {e 1, e 2,..., e m } connecting pairs of vertices. An edge e = (uv) is incident with

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

Instructor: Paul Zeitz, University of San Francisco

Instructor: Paul Zeitz, University of San Francisco Berkeley Math Circle Graph Theory and Ramsey Theory Instructor: Paul Zeitz, University of San Francisco (zeitz@usfca.edu) Definitions 1 A graph is a pair (V,E), where V is a finite set and E is a set of

More information

Shuli s Math Problem Solving Column

Shuli s Math Problem Solving Column huli s Math Problem olving Column Volume, Issue March, 009 Edited and uthored by huli ong Colorado prings, Colorado shuli_song@yahoo.com Content. Math Trick: Mental Calculation: aa bc. Math Competition

More information

Ma/CS 6b Class 10: Kuratowski's Theorem

Ma/CS 6b Class 10: Kuratowski's Theorem Ma/CS 6b Class 10: Kuratowski's Theorem By Adam Sheffer Recall: Plane Graphs A plane graph is a drawing of a graph in the plane such that the edges are noncrossing curves. 1 Recall: Planar Graphs The drawing

More information

Ma/CS 6b Class 10: Kuratowski's Theorem

Ma/CS 6b Class 10: Kuratowski's Theorem Ma/CS 6b Class 10: Kuratowski's Theorem By Adam Sheffer Plane Graphs A plane graph is a drawing of a graph in the plane such that the edges are noncrossing curves. 1 Planar Graphs The drawing on the left

More information

Minimum spanning trees

Minimum spanning trees Carlos Moreno cmoreno @ uwaterloo.ca EI-3 https://ece.uwaterloo.ca/~cmoreno/ece5 Standard reminder to set phones to silent/vibrate mode, please! During today's lesson: Introduce the notion of spanning

More information

Sections 5.2, 5.3. & 5.4

Sections 5.2, 5.3. & 5.4 MATH 11008: Graph Theory Terminology Sections 5.2, 5.3. & 5.4 Routing problem: A routing problem is concerned with finding ways to route the delivery of good and/or services to an assortment of destinations.

More information

Graphic TSP in cubic graphs

Graphic TSP in cubic graphs Graphic TSP in cubic graphs arxiv:1608.07568v2 [cs.dm] 30 Aug 2016 Zdeněk Dvořák Daniel Král Bojan Mohar Abstract We prove that every simple 2-connected cubic n-vertex graph contains a spanning closed

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

Chapter 3: Paths and Cycles

Chapter 3: Paths and Cycles Chapter 3: Paths and Cycles 5 Connectivity 1. Definitions: Walk: finite sequence of edges in which any two consecutive edges are adjacent or identical. (Initial vertex, Final vertex, length) Trail: walk

More information

Characterization of Graphs with Eulerian Circuits

Characterization of Graphs with Eulerian Circuits Eulerian Circuits 3. 73 Characterization of Graphs with Eulerian Circuits There is a simple way to determine if a graph has an Eulerian circuit. Theorems 3.. and 3..2: Let G be a pseudograph that is connected

More information

Matching Algorithms. Proof. If a bipartite graph has a perfect matching, then it is easy to see that the right hand side is a necessary condition.

Matching Algorithms. Proof. If a bipartite graph has a perfect matching, then it is easy to see that the right hand side is a necessary condition. 18.433 Combinatorial Optimization Matching Algorithms September 9,14,16 Lecturer: Santosh Vempala Given a graph G = (V, E), a matching M is a set of edges with the property that no two of the edges have

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

The Konigsberg Bridge Problem

The Konigsberg Bridge Problem The Konigsberg Bridge Problem This is a classic mathematical problem. There were seven bridges across the river Pregel at Königsberg. Is it possible to take a walk in which each bridge is crossed exactly

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

MAS 341: GRAPH THEORY 2016 EXAM SOLUTIONS

MAS 341: GRAPH THEORY 2016 EXAM SOLUTIONS MS 41: PH THEOY 2016 EXM SOLUTIONS 1. Question 1 1.1. Explain why any alkane C n H 2n+2 is a tree. How many isomers does C 6 H 14 have? Draw the structure of the carbon atoms in each isomer. marks; marks

More information

Section 3.1: Nonseparable Graphs Cut vertex of a connected graph G: A vertex x G such that G x is not connected. Theorem 3.1, p. 57: Every connected

Section 3.1: Nonseparable Graphs Cut vertex of a connected graph G: A vertex x G such that G x is not connected. Theorem 3.1, p. 57: Every connected Section 3.1: Nonseparable Graphs Cut vertex of a connected graph G: A vertex x G such that G x is not connected. Theorem 3.1, p. 57: Every connected graph G with at least 2 vertices contains at least 2

More information

Ma/CS 6a Class 8: Eulerian Cycles

Ma/CS 6a Class 8: Eulerian Cycles Ma/CS 6a Class 8: Eulerian Cycles By Adam Sheffer The Bridges of Königsberg Can we travel the city while crossing every bridge exactly once? 1 How Graph Theory was Born Leonhard Euler 1736 Eulerian Cycle

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

Ma/CS 6b Class 10: Ramsey Theory

Ma/CS 6b Class 10: Ramsey Theory Ma/CS 6b Class 10: Ramsey Theory By Adam Sheffer The Pigeonhole Principle The pigeonhole principle. If n items are put into m containers, such that n > m, then at least one container contains more than

More information

SANDRA SPIROFF AND CAMERON WICKHAM

SANDRA SPIROFF AND CAMERON WICKHAM A ZERO DIVISOR GRAPH DETERMINED BY EQUIVALENCE CLASSES OF ZERO DIVISORS arxiv:0801.0086v2 [math.ac] 17 Aug 2009 SANDRA SPIROFF AND CAMERON WICKHAM Abstract. We study the zero divisor graph determined by

More information

PAIRED-DOMINATION. S. Fitzpatrick. Dalhousie University, Halifax, Canada, B3H 3J5. and B. Hartnell. Saint Mary s University, Halifax, Canada, B3H 3C3

PAIRED-DOMINATION. S. Fitzpatrick. Dalhousie University, Halifax, Canada, B3H 3J5. and B. Hartnell. Saint Mary s University, Halifax, Canada, B3H 3C3 Discussiones Mathematicae Graph Theory 18 (1998 ) 63 72 PAIRED-DOMINATION S. Fitzpatrick Dalhousie University, Halifax, Canada, B3H 3J5 and B. Hartnell Saint Mary s University, Halifax, Canada, B3H 3C3

More information

Graph Theory Problems Instructor: Natalya St. Clair. 1 The Seven Bridges of Königsberg Problem

Graph Theory Problems Instructor: Natalya St. Clair. 1 The Seven Bridges of Königsberg Problem Graph Theory Problems erkeley Math ircles 2015 Lecture Notes Graph Theory Problems Instructor: Natalya St. lair 1 The Seven ridges of Königsberg Problem Königsberg is an ancient city of Prussia, now Kalingrad,

More information

Weak Dynamic Coloring of Planar Graphs

Weak Dynamic Coloring of Planar Graphs Weak Dynamic Coloring of Planar Graphs Caroline Accurso 1,5, Vitaliy Chernyshov 2,5, Leaha Hand 3,5, Sogol Jahanbekam 2,4,5, and Paul Wenger 2 Abstract The k-weak-dynamic number of a graph G is the smallest

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

3 and 4-Bandwidth Critical Graphs

3 and 4-Bandwidth Critical Graphs and -Bandwidth Critical Graphs nn Kilzer ugust, 00 bstract This paper investigates and -bandwidth critical graphs. It concludes Holly Westerfield s proof that only six types of -bandwidth critical graphs

More information

Lecture 5: More Examples/Applications of Quasirandom Graphs

Lecture 5: More Examples/Applications of Quasirandom Graphs Random and Quasirandom Graphs Instructor: Padraic Bartlett Lecture 5: More Examples/Applications of Quasirandom Graphs Week 4 Mathcamp 2012 In our last class, we saw that the Paley graphs were an example

More information

LECTURE 26 PRIM S ALGORITHM

LECTURE 26 PRIM S ALGORITHM DATA STRUCTURES AND ALGORITHMS LECTURE 26 IMRAN IHSAN ASSISTANT PROFESSOR AIR UNIVERSITY, ISLAMABAD STRATEGY Suppose we take a vertex Given a single vertex v 1, it forms a minimum spanning tree on one

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

Acyclic Colorings of Graph Subdivisions

Acyclic Colorings of Graph Subdivisions Acyclic Colorings of Graph Subdivisions Debajyoti Mondal, Rahnuma Islam Nishat, Sue Whitesides, and Md. Saidur Rahman 3 Department of Computer Science, University of Manitoba Department of Computer Science,

More information

Topics in Combinatorial Optimization February 5, Lecture 2

Topics in Combinatorial Optimization February 5, Lecture 2 8.997 Topics in Combinatorial Optimization February 5, 2004 Lecture 2 Lecturer: Michel X. Goemans Scribe: Robert Kleinberg In this lecture, we will: Present Edmonds algorithm for computing a maximum matching

More information

On the packing chromatic number of some lattices

On the packing chromatic number of some lattices On the packing chromatic number of some lattices Arthur S. Finbow Department of Mathematics and Computing Science Saint Mary s University Halifax, Canada BH C art.finbow@stmarys.ca Douglas F. Rall Department

More information

Recognizing Interval Bigraphs by Forbidden Patterns

Recognizing Interval Bigraphs by Forbidden Patterns Recognizing Interval Bigraphs by Forbidden Patterns Arash Rafiey Simon Fraser University, Vancouver, Canada, and Indiana State University, IN, USA arashr@sfu.ca, arash.rafiey@indstate.edu Abstract Let

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

Modules. 6 Hamilton Graphs (4-8 lectures) Introduction Necessary conditions and sufficient conditions Exercises...

Modules. 6 Hamilton Graphs (4-8 lectures) Introduction Necessary conditions and sufficient conditions Exercises... Modules 6 Hamilton Graphs (4-8 lectures) 135 6.1 Introduction................................ 136 6.2 Necessary conditions and sufficient conditions............. 137 Exercises..................................

More information

We have already seen the transportation problem and the assignment problem. Let us take the transportation problem, first.

We have already seen the transportation problem and the assignment problem. Let us take the transportation problem, first. Advanced Operations Research Prof. G. Srinivasan Department of Management Studies Indian Institute of Technology, Madras Lecture 19 Network Models In this lecture, we will discuss network models. (Refer

More information

arxiv: v3 [cs.dm] 12 Jun 2014

arxiv: v3 [cs.dm] 12 Jun 2014 On Maximum Differential Coloring of Planar Graphs M. A. Bekos 1, M. Kaufmann 1, S. Kobourov, S. Veeramoni 1 Wilhelm-Schickard-Institut für Informatik - Universität Tübingen, Germany Department of Computer

More information

Computer Science 280 Fall 2002 Homework 10 Solutions

Computer Science 280 Fall 2002 Homework 10 Solutions Computer Science 280 Fall 2002 Homework 10 Solutions Part A 1. How many nonisomorphic subgraphs does W 4 have? W 4 is the wheel graph obtained by adding a central vertex and 4 additional "spoke" edges

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

arxiv: v1 [cs.cc] 30 Jun 2017

arxiv: v1 [cs.cc] 30 Jun 2017 Hamiltonicity is Hard in Thin or Polygonal Grid Graphs, but Easy in Thin Polygonal Grid Graphs Erik D. Demaine Mikhail Rudoy arxiv:1706.10046v1 [cs.cc] 30 Jun 2017 Abstract In 2007, Arkin et al. [3] initiated

More information