The Walk-Length Filtration for Persistent Homology on Weighted Directed Graphs

Fuente: arXiv
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Autori principali: Muñoz, David E., Munch, Elizabeth, Khasawneh, Firas A.
Natura: Preprint
Pubblicazione: 2025
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author Muñoz, David E.
Munch, Elizabeth
Khasawneh, Firas A.
author_facet Muñoz, David E.
Munch, Elizabeth
Khasawneh, Firas A.
contents Directed graphs arise in many applications where computing persistent homology helps to encode the shape and structure of the input information. However, there are only a few ways to turn the directed graph information into an undirected simplicial complex filtration required by the standard persistent homology framework. In this paper, we present a new filtration constructed from a directed graph, called the walk-length filtration. This filtration mirrors the behavior of small walks visiting certain collections of vertices in the directed graph. We show that, while the persistence is not stable under the usual $L_\infty$-style network distance, a generalized $L_1$-style distance is, indeed, stable. We further provide an algorithm for its computation, and investigate the behavior of this filtration in examples, including cycle networks and synthetic hippocampal networks with a focus on comparison to the often used Dowker filtration.
format Preprint
id arxiv_https___arxiv_org_abs_2506_22263
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle The Walk-Length Filtration for Persistent Homology on Weighted Directed Graphs
Muñoz, David E.
Munch, Elizabeth
Khasawneh, Firas A.
Computational Geometry
Algebraic Topology
55N31
Directed graphs arise in many applications where computing persistent homology helps to encode the shape and structure of the input information. However, there are only a few ways to turn the directed graph information into an undirected simplicial complex filtration required by the standard persistent homology framework. In this paper, we present a new filtration constructed from a directed graph, called the walk-length filtration. This filtration mirrors the behavior of small walks visiting certain collections of vertices in the directed graph. We show that, while the persistence is not stable under the usual $L_\infty$-style network distance, a generalized $L_1$-style distance is, indeed, stable. We further provide an algorithm for its computation, and investigate the behavior of this filtration in examples, including cycle networks and synthetic hippocampal networks with a focus on comparison to the often used Dowker filtration.
title The Walk-Length Filtration for Persistent Homology on Weighted Directed Graphs
topic Computational Geometry
Algebraic Topology
55N31
url https://arxiv.org/abs/2506.22263