Recently there is huge interest in graph theory and intensive study on computing integer powers of matrices. In this paper, we consider one type of directed graph. Then we obtain a general form of the adjacency matrices of the graph. By using the well-known property which states the i, j entry of A A is adjacency matrix is equal to the number of walks of length m from vertex i to vertex j, we s...

Adjacencies stand at the beginning of a multitude of planning tasks. Especially in hospital planning they are essential for describing relationships between different organizational units – e.g. ‘close’, ‘distant’ or ‘neutral’. Mathematically, these terms map to relative weights between each pair of units in the range [-1, 1] which are put into a (symmetric) adjacency matrix. This matrix subseq...

Characterization of singular graphs can be reduced to the non-trivial solutions of a system of linear homogeneous equations Ax = 0 for the 0-1 adjacency matrix A. A graph G is singular of nullity η(G) ≥ 1, if the dimension of the nullspace ker(A) of its adjacency matrix A is η(G). Necessary and sufficient conditions are determined for a graph to be singular in terms of admissible induced subgra...

We consider weighted graphs, where the edge weights are positive definite matrices. The eigenvalues of a graph are the eigenvalues of its adjacency matrix. We obtain another upper bound which is sharp on the spectral radius of the adjacency matrix and compare with some known upper bounds with the help of some examples of graphs. We also characterize graphs for which the bound is attained.

In this paper we obtain several characterizations of the adjacency matrix of a probe interval graph. In course of this study we describe an easy method of obtaining interval representation of an interval bipartite graph from its adjacency matrix. Finally, we note that if we add a loop at every probe vertex of a probe interval graph, then the Ferrers dimension of the corresponding symmetric bipa...

Graph algorithms that test adjacencies are usually implemented with an adjacency-matrix representation because the adjacency takes constant time matrices, but it linear in degree of vertices lists. In this article, we review adjacency-map representation, which supports tests expected time, and show graph run faster maps than lists by a small factor if they do not one or two orders magnitude per...

There is a connection between the expansion of a graph and the eigengap (or spectral gap) of the normalized adjacency matrix (that is, the gap between the first and second largest eigenvalues). Recall that the largest eigenvalue of the normalized adjacency matrix is 1; denote it by λ1 and denote the second largest eigenvalue by λ2. We will see that a large gap (that is, small λ2) implies good e...

Two different elementary approaches for deriving an explicit formula for the distribution of the range of a simple random walk on Z of length n are presented. Both of them rely on Hermann Weyl’s discrepancy norm, which equals the maximal partial sum of the elements of a sequence. By this the original combinatorial problem on Z can be turned into a known path-enumeration problem on a bounded lat...

A graph is called integral if all the eigenvalues of its adjacency matrix are integers. In this paper, we give a useful sufficient and necessary condition for complete r-partite graphs to be integral, from which we can construct infinite many new classes of such integral graphs. It is proved that the problem of finding such integral graphs is equivalent to the problem of solving some Diophantin...

In this paper we will prove that μ(G) + μ(G) ≤ 1 + √ 3 2 n − 1 where μ(G), μ(G) are the greatest eigenvalues of the adjacency matrices of the graph G and its complement and n denotes the number of vertices of G.