Graph Theory (MA522)

Euler

This is the homepage of MA522 for the academic year 2009-2010. The page will be regularly updated throughout the first semester. Any suggestions for improving it are welcomed by its author, Rachel Quinlan.

Contents

Lecturer
Course Content
Course Activities - what students do
Learning Outcomes
Assessment and Feedback
Weekly Problems to Think About
Recommended Reading


Lecturer for Graph Theory (MA522)

Dr Rachel Quinlan
Office : Room 105, Ground Floor, Áras de Brún
Phone : (49)3796
email : rachel.quinlan@nuigalway.ie

Course Content

Graphs are mathematical constructions used to describe collections of objects some pairs of which are related to each other. For example a family tree is a collection of people in which some are related to others by parentage. Another example would be an airline's route map in which services are indicated by lines joining different airports. Mathematical graphs can be represented as diagrams involving collections of vertices (dots), some pairs of which are connected by edges (lines). In this course we will consider the first four topics from the following list, and some of the last four according to the preferences of the class.

Prerequisites

No particularly advanced knowledge from any other area of mathematics is needed for the study of graph theory. Some knowledge of linear algebra, particularly matrix algebra, would be helpful. Otherwise what is needed is general mathematical experience. This is an advanced course and students will be expected both to construct and to critically assess mathematical proofs of moderate complexity, and to demonstrate proficiency in the communication of mathematical ideas.

Course Activities - what students do

There will be three components to the course activities.
  1. Study of the course text
    The course text is (some of) the book Graph Theory with Applications, by J.A. Bondy and U.S.R. Murty. This book is freely available online here. Students are expected to engage in independent study of this text or at least in certain prescribed sections of it. Consultation of other books on graph theory is also encouraged.
  2. Seminar Series
    We will have two weekly seminars. Seminars will be held in C219 at 1.00 on Tuesdays and at 4.00 on Wednesdays. The online dictionary dictionary.com defines seminar as follows :
    ``a small group of students, as in a university, engaged in advanced study and original research with a member of the faculty and meeting regularly to exchange information and hold discussions.''
    Each seminar session will focus on a particular section or sections of the lecture notes; these should be studied in advance of the seminar. Topics for seminar discussion will include :
  3. Working on Assigned Tasks
    The course will include at least four sets of assigned tasks. These tasks will include some very specific problems to solve and also some more open-ended topics to investigate. They will also include presentations of specific topics to the class.

Note on Workload
This module accounts for 9 ECTS credits. One ECTS credit is considered to equate to 25 to 30 hours of work by a student. This means that you should expect to spend upwards of 200 hours in total working on this Graph Theory course.


Learning Outcomes

Upon successful completion of this module students will be able to

Assessment and Feedback

Assessment : a combination to be decided of written assignments, presentations, and participation in seminars. Feedback will be provided on all submitted work and opportunities to obtain feedback before final submission will be available.

Weekly Problems to Think About . . .

. . . and discuss in the seminars. Problems that have particular relevance to the general theory are marked with a dagger. Problems that I think are hard are marked with a star.

Suggestions for Supplementary Reading



Note The picture at the top of this page is of a German stamp issued in 1983, honouring Leonhard Euler. For more stamps featuring mathematics and mathematicians, see this site.
NUI, Galway School of Mathematics, Statistics and Applied Mathematics