Weighted enumeration of nonbacktracking walks on weighted graphs

TL;DR

This paper extends nonbacktracking walks to weighted graphs, providing methods to compute their generating functions and centrality measures, with applications to dynamic graphs and computational validation.

Contribution

Introduces two methods for weighted nonbacktracking walk enumeration, including a line graph approach suitable for evolving graphs, and offers computational results.

Findings

Efficient direct computation method for weighted nonbacktracking walks.

Line graph approach extends to time-evolving graphs.

Validated methods with computational experiments.

Abstract

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.