Adjacency Matrices

Consider a directed graph with n vertices, . The simplest graph representation scheme uses an matrix A of zeroes and ones given by

That is, the element of the matrix, is a one only if is an edge in G. The matrix A is called an adjacency matrix  .

For example, the adjacency matrix for graph in Figure  is

Clearly, the number of ones in the adjacency matrix is equal to the number of edges in the graph.

One advantage of using an adjacency matrix is that it is easy to determine the sets of edges emanating from a given vertex. For example, consider vertex . Each one in the row corresponds to an edge that emanates from vertex . Conversely, each one in the column corresponds to an edge incident on vertex .

We can also use adjacency matrices to represent undirected graphs. That is, we represent an undirected graph with n vertices, using an matrix A of zeroes and ones given by

Since the two sets and are equivalent, matrix A is symmetric about the diagonal. That is, . Furthermore, all of the entries on the diagonal are zero. That is, for .

For example, the adjacency matrix for graph in Figure  is

In this case, there are twice as many ones in the adjacency matrix as there are edges in the undirected graph.

A simple variation allows us to use an adjacency matrix to represent an edge-labeled graph. For example, given numeric edge labels, we can represent a graph (directed or undirected) using an matrix A in which the is the numeric label associated with edge in the case of a directed graph, and edge , in an undirected graph.

For example, the adjacency matrix for the graph in Figure  is

In this case, the array entries corresponding to non-existent edges have all been set to . Here serves as a kind of sentinel . The value to use for the sentinel depends on the application. For example, if the edges represent routes between geographic locations, then a route of length is much like one that does not exist.

Since the adjacency matrix has entries, the amount of spaced needed to represent the edges of a graph is , regardless of the actual number of edges in the graph. If the graph contains relatively few edges, e.g., if , then most of the elements of the adjacency matrix will be zero (or ). A matrix in which most of the elements are zero (or ) is a sparse matrix  .

Copyright © 1998 by Bruno R. Preiss, P.Eng. All rights reserved.