Cui, Kai ; KhudaBukhsh, Wasiur R. ; Koeppl, Heinz (2022)
Motif-based mean-field approximation of interacting particles on clustered networks.
In: Physical Review E, 105 (4)
doi: 10.1103/PhysRevE.105.L042301
Artikel, Bibliographie
Dies ist die neueste Version dieses Eintrags.
Kurzbeschreibung (Abstract)
Interacting particles on graphs are routinely used to study magnetic behavior in physics, disease spread in epidemiology, and opinion dynamics in social sciences. The literature on mean-field approximations of such systems for large graphs typically remains limited to specific dynamics, or assumes cluster-free graphs for which standard approximations based on degrees and pairs are often reasonably accurate. Here, we propose a motif-based mean-field approximation that considers higher-order subgraph structures in large clustered graphs. Numerically, our equations agree with stochastic simulations where existing methods fail.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2022 |
| Autor(en): | Cui, Kai ; KhudaBukhsh, Wasiur R. ; Koeppl, Heinz |
| Art des Eintrags: | Bibliographie |
| Titel: | Motif-based mean-field approximation of interacting particles on clustered networks |
| Sprache: | Englisch |
| Publikationsjahr: | April 2022 |
| Verlag: | American Physical Society |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Physical Review E |
| Jahrgang/Volume einer Zeitschrift: | 105 |
| (Heft-)Nummer: | 4 |
| DOI: | 10.1103/PhysRevE.105.L042301 |
| URL / URN: | https://link.aps.org/doi/10.1103/PhysRevE.105.L042301 |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | Interacting particles on graphs are routinely used to study magnetic behavior in physics, disease spread in epidemiology, and opinion dynamics in social sciences. The literature on mean-field approximations of such systems for large graphs typically remains limited to specific dynamics, or assumes cluster-free graphs for which standard approximations based on degrees and pairs are often reasonably accurate. Here, we propose a motif-based mean-field approximation that considers higher-order subgraph structures in large clustered graphs. Numerically, our equations agree with stochastic simulations where existing methods fail. |
| Freie Schlagworte: | Complex systems, Epidemic, Dynamical mean field theory, Mean field theory, emergenCITY, emergenCITY_KOM |
| ID-Nummer: | Artikel-ID: L042301 |
| Zusätzliche Informationen: | Erstveröffentlichung |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik > Bioinspirierte Kommunikationssysteme 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Self-Organizing Systems Lab LOEWE LOEWE > LOEWE-Zentren LOEWE > LOEWE-Zentren > emergenCITY |
| Hinterlegungsdatum: | 07 Sep 2022 08:49 |
| Letzte Änderung: | 16 Jan 2025 15:22 |
| PPN: | 49897944X |
| Export: | |
| Suche nach Titel in: | TUfind oder in Google |
Verfügbare Versionen dieses Eintrags
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Motif-based mean-field approximation of interacting particles on clustered networks. (deposited 16 Dez 2024 14:04)
- Motif-based mean-field approximation of interacting particles on clustered networks. (deposited 07 Sep 2022 08:49) [Gegenwärtig angezeigt]
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