Grounded Persistent Path Homology: A Stable, Topological Descriptor for Weighted Digraphs

Abstract Weighted digraphs are used to model a variety of natural systems and can exhibit interesting structure across a range of scales. In order to understand and compare these systems, we require stable, interpretable, multiscale descriptors. To this end, we propose grounded persistent path homology ( GrPPH )—a new, functorial, topological descriptor that describes the structure of an edge-weighted digraph via a persistence barcode. We show there is a choice of circuit basis for the graph which yields geometrically interpretable representatives for the features in the barcode. Moreover, we show the barcode is stable, in bottleneck distance, to both numerical and structural perturbations.

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Publication Details

Journal
Foundations of Computational Mathematics
Published
2024-08-23
DOI
https://doi.org/10.1007/s10208-024-09679-2
Citations
3
Primary Topic
Topological and Geometric Data Analysis
Type
article
Field-Weighted Citation Impact
1.08

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article

Grounded Persistent Path Homology: A Stable, Topological Descriptor for Weighted Digraphs

Heather A. Harrington, Ulrike Tillmann, Thomas Chaplin
3 citations
Foundations of Computational Mathematics
Topological and Geometric Data Analysis
1.08
article

Grounded Persistent Path Homology: A Stable, Topological Descriptor for Weighted Digraphs

Heather A. Harrington, Ulrike Tillmann, Thomas Chaplin
article en
3 citations

Abstract

Abstract Weighted digraphs are used to model a variety of natural systems and can exhibit interesting structure across a range of scales. In order to understand and compare these systems, we require stable, interpretable, multiscale descriptors. To this end, we propose grounded persistent path homology ( GrPPH )—a new, functorial, topological descriptor that describes the structure of an edge-weighted digraph via a persistence barcode. We show there is a choice of circuit basis for the graph which yields geometrically interpretable representatives for the features in the barcode. Moreover, we show the barcode is stable, in bottleneck distance, to both numerical and structural perturbations.

Foundations of Computational MathematicsVol. 25(5)
Isaac Newton Institute for Mathematical Sciences (GB), University of Cambridge (GB), University of Oxford (GB), Center for Systems Biology Dresden (DE), Max Planck Institute of Molecular Cell Biology and Genetics (DE), Technische Universität Dresden (DE)
Engineering and Physical Sciences Research Council
Openalex Percentile: Top 20%
Topological and Geometric Data Analysis
1.08
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Grounded Persistent Path Homology: A Stable, Topological Descriptor for Weighted Digraphs — Heather A. Harrington, Ulrike Tillmann, et al. · Foundations of Computational Mathematics (2024) | TGRS Research Map | TGRS