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Graph Pseudometrics from a Topological Point of View

dc.contributor.authorGarcia-Pulido, Ana Luciaen
dc.contributor.authorHess, Kathrynen
dc.contributor.authorTan, Janeen
dc.contributor.authorTurner, Katharineen
dc.contributor.authorWang, Beien
dc.contributor.authorYerolemou, Nayaen
dc.date.accessioned2025-03-15T08:32:24Z
dc.date.available2025-03-15T08:32:24Z
dc.date.issued2022en
dc.description.abstractWe explore pseudometrics for directed graphs in order to better understand their topological properties. The directed flag complex associated to a directed graph provides a useful bridge between network science and topology. Indeed, it has often been observed that phenomena exhibited by real-world networks reflect the topology of their flag complexes, as measured, for example, by Betti numbers or simplex counts. As it is often computationally expensive (or even unfeasible) to determine such topological features exactly, it would be extremely valuable to have pseudometrics on the set of directed graphs that can both detect the topological differences and be computed efficiently. To facilitate work in this direction, we introduce methods to measure how well a graph pseudometric captures the topology of a directed graph. We then use these methods to evaluate some well-established pseudometrics, using test data drawn from several families of random graphs.en
dc.description.sponsorshipAcknowledgments This work began at the Women in Computational Topology Workshop in 2019. The authors wish to thank the Mathematical Sciences Institute at ANU, the US National Science Foundation through the award CCF-1841455, the Australian Mathematical Sciences Institute, and the Association of Women in Mathematics for their financial support. ALGP is supported by the EPSRC grant “New Approaches to Data Science: Application Driven Topological Data Analysis” EP/R018472/1. NY is supported by the Alan Turing Institute under the EPSRC grant EP/N510129/1. KT is supported by an ARC DECRA fellowship. BW is supported in part by DOE DE-SC0021015 and NSF DBI-1661375. The authors would also like to thank Erika Roldán for insightful contributions, Gesine Reinert for sharing the source code for TriadEMD and TriadEuclid, the Oxford Mathematical Institute for providing access to computational resources, and the anonymous referees whose comments have helped to clarify this paper.en
dc.description.statustrueen
dc.format.extent30en
dc.identifier.issn2364-5733en
dc.identifier.otherresearchoutputwizard:a383154xPUB34274en
dc.identifier.otherScopus:85130549408en
dc.identifier.urihttps://dspace-test.anu.edu.au/handle/1885/733716694
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85130549408&partnerID=8YFLogxKen
dc.language.isoEnglishen
dc.relation.ispartofseriesAssociation for Women in Mathematics Seriesen
dc.rightsPublisher Copyright: © 2022, The Author(s) and the Association for Women in Mathematics.en
dc.titleGraph Pseudometrics from a Topological Point of Viewen
dc.typeChapteren
local.bibliographicCitation.lastpage128en
local.bibliographicCitation.startpage99en
local.contributor.affiliationGarcia-Pulido, Ana Lucia; University of Liverpoolen
local.contributor.affiliationHess, Kathryn; Swiss Federal Institute of Technology Lausanneen
local.contributor.affiliationTan, Jane; University of Oxforden
local.contributor.affiliationTurner, Katharine; Mathematical Sciences Institute Research, Mathematical Sciences Institute, ANU College of Systems and Society, The Australian National Universityen
local.contributor.affiliationWang, Bei; University of Utahen
local.contributor.affiliationYerolemou, Naya; University of Oxforden
local.identifier.doi10.1007/978-3-030-95519-9_5en
local.identifier.essn2364-5741en
local.identifier.pure87204d9c-0592-4472-8c81-13da08ddd8c8en
local.type.statusPublisheden

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