Collective excitability in highly diluted networks of rotators
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arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
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2022
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| _version_ | 1866915308953927680 |
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| author | Paolini, Gabriele Ciszak, Marzena Marino, Francesco Olmi, Simona Torcini, Alessandro |
| author_facet | Paolini, Gabriele Ciszak, Marzena Marino, Francesco Olmi, Simona Torcini, Alessandro |
| contents | We report on collective excitable events in a highly-diluted random network of non-excitable nodes. Excitability arises thanks to a self-sustained local adaptation mechanism that drives the system on a slow time-scale across a hysteretic phase transition involving states with different degrees of synchronization. These phenomena have been investigated for the Kuramoto model with bimodal distribution of the natural frequencies and for the Kuramoto model with inertia and an unimodal frequency distribution. We consider global and local stimulation protocols and characterize the system response for different level of dilution. We compare the results with those obtained in the fully-coupled case showing that such collective phenomena are remarkably robust against network diluteness. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2206_07112 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Collective excitability in highly diluted networks of rotators Paolini, Gabriele Ciszak, Marzena Marino, Francesco Olmi, Simona Torcini, Alessandro Disordered Systems and Neural Networks Adaptation and Self-Organizing Systems We report on collective excitable events in a highly-diluted random network of non-excitable nodes. Excitability arises thanks to a self-sustained local adaptation mechanism that drives the system on a slow time-scale across a hysteretic phase transition involving states with different degrees of synchronization. These phenomena have been investigated for the Kuramoto model with bimodal distribution of the natural frequencies and for the Kuramoto model with inertia and an unimodal frequency distribution. We consider global and local stimulation protocols and characterize the system response for different level of dilution. We compare the results with those obtained in the fully-coupled case showing that such collective phenomena are remarkably robust against network diluteness. |
| title | Collective excitability in highly diluted networks of rotators |
| topic | Disordered Systems and Neural Networks Adaptation and Self-Organizing Systems |
| url | https://arxiv.org/abs/2206.07112 |