Complex systems of interacting components often can be modeled by a graph that consists of a set of n nodes and a set of m edges. Such a graph can be represented by an adjacency matrix A is an element of Rn & times;n , whose (ij) th entry is one if there is an edge pointing from node i to node j, and is zero otherwise. The matrix A and its low-order powers reveal important properties of the graph and allow the enumeration of short paths and cycles that are important for determining short-range communication in the graph as well as node clustering. Closed-form expressions for path matrices of length up to four are derived, and a novel indicator of the structural propensity of the graph to form clusters is proposed. Numerical examples illustrate our analysis.
A Note on Short-Range Network Communication and Clustering / Al-Hajri, N., Darvishi, M.T., Noschese, S., Reichel, L.. - In: MATHEMATICS. - ISSN 2227-7390. - 14:17(2026). [10.3390/math14173143]
A Note on Short-Range Network Communication and Clustering
Noschese S.;
2026
Abstract
Complex systems of interacting components often can be modeled by a graph that consists of a set of n nodes and a set of m edges. Such a graph can be represented by an adjacency matrix A is an element of Rn & times;n , whose (ij) th entry is one if there is an edge pointing from node i to node j, and is zero otherwise. The matrix A and its low-order powers reveal important properties of the graph and allow the enumeration of short paths and cycles that are important for determining short-range communication in the graph as well as node clustering. Closed-form expressions for path matrices of length up to four are derived, and a novel indicator of the structural propensity of the graph to form clusters is proposed. Numerical examples illustrate our analysis.| File | Dimensione | Formato | |
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