Report
Motif-based mean-field approximation of interacting particles on clustered networks
| العنوان: | Motif-based mean-field approximation of interacting particles on clustered networks |
|---|---|
| المؤلفون: | Cui, Kai, KhudaBukhsh, Wasiur R., Koeppl, Heinz |
| سنة النشر: | 2022 |
| مصطلحات موضوعية: | Physics - Physics and Society, Condensed Matter - Disordered Systems and Neural Networks, Condensed Matter - Statistical Mechanics |
| الوصف: | Interacting particles on graphs are routinely used to study magnetic behaviour in physics, disease spread in epidemiology, and opinion dynamics in social sciences. The literature on mean-field approximations of such systems for large graphs is limited to 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. Comment: v2: Added references; adjusted length. v3: Full-length references |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2201.04999 |
| رقم الانضمام: | edsarx.2201.04999 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |