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Autores principales: Arrigo, Francesca, Higham, Desmond J., Noferini, Vanni, Wood, Ryan
Formato: Preprint
Publicado: 2022
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Acceso en línea:https://arxiv.org/abs/2202.02888
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author Arrigo, Francesca
Higham, Desmond J.
Noferini, Vanni
Wood, Ryan
author_facet Arrigo, Francesca
Higham, Desmond J.
Noferini, Vanni
Wood, Ryan
contents We extend the notion of nonbacktracking walks from unweighted graphs to graphs whose edges have a nonnegative weight. Here the weight associated with a walk is taken to be the product over the weights along the individual edges. We give two ways to compute the associated generating function, and corresponding node centrality measures. One method works directly on the original graph and one uses a line graph construction followed by a projection. The first method is more efficient, but the second has the advantage of extending naturally to time-evolving graphs. Computational results are also provided.
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institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Weighted enumeration of nonbacktracking walks on weighted graphs
Arrigo, Francesca
Higham, Desmond J.
Noferini, Vanni
Wood, Ryan
Combinatorics
We extend the notion of nonbacktracking walks from unweighted graphs to graphs whose edges have a nonnegative weight. Here the weight associated with a walk is taken to be the product over the weights along the individual edges. We give two ways to compute the associated generating function, and corresponding node centrality measures. One method works directly on the original graph and one uses a line graph construction followed by a projection. The first method is more efficient, but the second has the advantage of extending naturally to time-evolving graphs. Computational results are also provided.
title Weighted enumeration of nonbacktracking walks on weighted graphs
topic Combinatorics
url https://arxiv.org/abs/2202.02888