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On the exponential generating function for non-backtracking walks. (English) Zbl 1394.05119
Summary: We derive an explicit formula for the exponential generating function associated with non-backtracking walks around a graph. We study both undirected and directed graphs. Our results allow us to derive computable expressions for non-backtracking versions of network centrality measures based on the matrix exponential. We find that eliminating backtracking walks in this context does not significantly increase the computational expense. We show how the new measures may be interpreted in terms of standard exponential centrality computation on a certain multilayer network. Insights from this block matrix interpretation also allow us to characterize centrality measures arising from general matrix functions. Rigorous analysis on the star graph illustrates the effect of non-backtracking and shows that localization can be eliminated when we restrict to non-backtracking walks. We also investigate the localization issue on synthetic networks.

05C82 Small world graphs, complex networks (graph-theoretic aspects)
05C85 Graph algorithms (graph-theoretic aspects)
05C90 Applications of graph theory
05C50 Graphs and linear algebra (matrices, eigenvalues, etc.)
15A15 Determinants, permanents, traces, other special matrix functions
65F50 Computational methods for sparse matrices
90B10 Deterministic network models in operations research
Full Text: DOI
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