Accelerating consensus of self-driven swarm via adaptive speed
| dc.creator | Zhang, Jue | |
| dc.creator | Zhao, Yang | |
| dc.creator | Tian, Baomei | |
| dc.creator | Peng, Liqian | |
| dc.creator | Zhang, Hai-Tao | |
| dc.creator | Wang, Bing-Hong | |
| dc.creator | Zhou, Tao | |
| dc.date | 2007-11-25 | |
| dc.date | 2008-09-28 | |
| dc.date.accessioned | 2026-07-07T12:34:09Z | |
| dc.date.available | 2026-07-07T12:34:09Z | |
| dc.description | In resent years, Vicsek model has attracted more and more attention and been well developed. However, the in-depth analysis on the convergence time are scarce thus far. In this paper, we study some certain factors that mainly govern the convergence time of Vicsek model. By extensively numerical simulations, we find the convergence time scales in a power law with $r^2\ln N$ in the noise-free case, where $r$ and $N$ are horizon radius and the number of particles. Furthermore, to accelerate the convergence, we propose a new model in which the speed of each particle is variable. The convergence time can be remarkably shortened compared with the standard Vicsek model. | |
| dc.description | 11 pages, 6 figures | |
| dc.identifier | https://arxiv.org/abs/0711.3896 | |
| dc.identifier | http://arxiv.org/abs/0711.3896 | |
| dc.identifier | Physica A 388: 1237-1242 (2009) | |
| dc.identifier | doi:10.1016/j.physa.2008.11.043 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/217326 | |
| dc.subject | Disordered Systems and Neural Networks | |
| dc.subject | Statistical Mechanics | |
| dc.title | Accelerating consensus of self-driven swarm via adaptive speed | |
| dc.type | text |