Path Laplacian matrices : introduction and application to the analysis of consensus in networks

Estrada, Ernesto (2012) Path Laplacian matrices : introduction and application to the analysis of consensus in networks. Linear Algebra and its Applications, 436 (9). pp. 3373-3391. ISSN 0024-3795

Full text not available in this repository.Request a copy from the Strathclyde author

Abstract

The concept of k-pathLaplacian matrix of a graph is motivated and introduced. The pathLaplacian matrices are a natural generalization of the combinatorial Laplacian of a graph. They are defined by using path matrices accounting for the existence of shortest paths of length k between two nodes. This new concept is motivated by the problem of determining whether every node of a graph can be visited by means of a process consisting of hopping from one node to another separated at distance k from it. The problem is solved by using the multiplicity of the trivial eigenvalue of the corresponding k-pathLaplacian matrix. We apply these matrices to the analysis of the consensus among agents in a networked system. We show how the consensus in different types of network topologies is accelerated by considering not only nearest neighbors but also the influence of long-range interacting ones. Further applications of pathLaplacian matrices in a variety of other fields, e.g., synchronization, flocking, Markov chains, etc., will open a new avenue in algebraic graph theory.

Creators(s): Estrada, Ernesto ORCID logoORCID: https://orcid.org/0000-0002-3066-7418;
Item type:Article
ID code:40662
Keywords:graph theory, path matrices, laplacian matrix, consensusanalysis, synchronization, Mathematics, Discrete Mathematics and Combinatorics, Algebra and Number Theory, Geometry and Topology, Numerical Analysis
Subjects:Science > Mathematics
Department:Faculty of Science > Mathematics and Statistics
Depositing user: Pure Administrator
Date deposited:02 Aug 2012 10:42
Last modified:05 Mar 2021 03:56
URI:https://strathprints.strath.ac.uk/id/eprint/40662
Export data:
CORE (COnnecting REpositories)