تقرير
Chimera states in neural networks and power systems
| العنوان: | Chimera states in neural networks and power systems |
|---|---|
| المؤلفون: | Deng, Shengfeng, Ódor, Géza |
| المصدر: | Chaos 34, (2024) 033135 |
| سنة النشر: | 2023 |
| المجموعة: | Condensed Matter Nonlinear Sciences Physics (Other) |
| مصطلحات موضوعية: | Condensed Matter - Statistical Mechanics, Condensed Matter - Disordered Systems and Neural Networks, Nonlinear Sciences - Chaotic Dynamics, Physics - Computational Physics |
| الوصف: | Partial, frustrated synchronization and chimera-like states are expected to occur in Kuramoto-like models if the spectral dimension of the underlying graph is low: $d_s < 4$. We provide numerical evidence that this really happens in case of the high-voltage power grid of Europe ($d_s < 2$), a large human connectome (KKI113) and in case of the largest, exactly known brain network corresponding to the fruit-fly (FF) connectome ($d_s < 4$), even though their graph dimensions are much higher, i.e.: $d^{EU}_g\simeq 2.6(1)$ and $d^{FF}_g\simeq 5.4(1)$, $d^{\mathrm{KKI113}}_g\simeq 3.4(1)$. We provide local synchronization results of the first- and second-order (Shinomoto) Kuramoto models by numerical solutions on the FF and the European power-grid graphs, respectively, and show the emergence of \red{chimera-like} patterns on the graph community level as well as by the local order parameters. |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.1063/5.0154581 |
| URL الوصول: | http://arxiv.org/abs/2307.02216 |
| رقم الأكسشن: | edsarx.2307.02216 |
| قاعدة البيانات: | arXiv |
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