Redefining Network Topology in Complex Systems: Merging Centrality Metrics, Spectral Theory, and Diffusion Dynamics

Redefining Network Topology in Complex Systems: Merging Centrality Metrics, Spectral Theory, and Diffusion Dynamics | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 29 May 2025 V1 Latest version Share on Redefining Network Topology in Complex Systems: Merging Centrality Metrics, Spectral Theory, and Diffusion Dynamics Author : Arsh Jha 0009-0009-4767-8226 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.174854030.01804422/v1 207 views 110 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract This paper introduces a novel framework that combines traditional centrality measures with eigenvalue spectra and diffusion processes for a more comprehensive analysis of complex networks. While centrality measures such as degree, closeness, and betweenness have been commonly used to assess nodal importance, they provide limited insight into dynamic network behaviors. By incorporating eigenvalue analysis, which evaluates network robustness and connectivity through spectral properties, and diffusion processes that model information flow, this framework offers a deeper understanding of how networks function under dynamic conditions. Applied to synthetic networks, the approach identifies key nodes not only by centrality but also by their role in diffusion dynamics and vulnerability points, offering a multi-dimensional view that traditional methods alone cannot. This integrated analysis enables a more precise identification of critical nodes and potential weaknesses, with implications for improving network resilience in fields ranging from epidemiology to cybersecurity Supplementary Material File (2503.21709v1 (1).pdf) Download 525.49 KB Information & Authors Information Version history V1 Version 1 29 May 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords centrality measures diffusion processes eigenvalue spectra information flow network analysis network robustness synthetic networks Authors Affiliations Arsh Jha 0009-0009-4767-8226 [email protected] North Carolina School of Science and Mathematics, North Carolina View all articles by this author Metrics & Citations Metrics Article Usage 207 views 110 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Arsh Jha. Redefining Network Topology in Complex Systems: Merging Centrality Metrics, Spectral Theory, and Diffusion Dynamics. Authorea . 29 May 2025. DOI: https://doi.org/10.22541/au.174854030.01804422/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . Format Please select one from the list RIS (ProCite, Reference Manager) EndNote BibTex Medlars RefWorks Direct import Tips for downloading citations document.getElementById('citMgrHelpLink').addEventListener('click', function() { popupHelp(this.href); return false; }); $(".js__slcInclude").on("change", function(e){ if ($(this).val() == 'refworks') $('#direct').prop("checked", false); $('#direct').prop("disabled", ($(this).val() == 'refworks')); }); Cited by Angelo Leogrande, Carlo Drago, Alberto Costantiello, Massimo Arnone, From Connectivity to Commerce: A Multi-Technique Investigation of E-Commerce Drivers in Italy’s Regional Landscape, Journal of Theoretical and Applied Electronic Commerce Research, 21 , 5, (137), (2026). https://doi.org/10.3390/jtaer21050137 Crossref Giovanni Colonna, Advancing Liver Cancer Treatment Through Dynamic Genomics and Systems Biology: A Path Toward Personalized Oncology, DNA, 6 , 1, (6), (2026). https://doi.org/10.3390/dna6010006 Crossref Loading... 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