极端事件和事件大小波动在网络上重置随机路径时的波动.
Xiaohan Sun1, Shaoxiang Zhu2, Anlin Li1
1School of Mathematical Science, Jiangsu University, Zhenjiang 212013, China.
Entropy (Basel, Switzerland)
|December 24, 2025
概括
复杂网络中的随机重置可以减少交通拥堵等极端事件. 这种控制机制抑制了事件的概率,并集中了波动,特别是在脆弱的节点.
科学领域:
- 网络科学 网络科学
- 统计物理 统计物理
- 复杂的系统复杂的系统.
背景情况:
- 随机步行对于模拟复杂网络中的运输至关重要.
- 随机重置优化了搜索时间,但其对极端事件的影响还未得到充分研究.
- 极端事件,如交通拥堵或服务器过载,是关键的网络现象.
研究的目的:
- 研究随机重置对复杂网络中极端事件的概率和规模的影响.
- 了解重置如何影响关键网络现象,如拥堵和故障.
- 探索重置作为缓解极端事件的控制机制的潜力.
主要方法:
- 静止职业概率的分析推导.
- 随机走路的综合数值模拟与随机重置.
- 在网络节点上对极端事件的发生和规模进行系统分析.
主要成果:
- 随机重置显著降低极端事件的概率.
- 重置集中事件大小波动而不是消除它们.
- 观察到一种普遍的抑制效应,随着重置率的增加,极端事件的概率单调地下降.
- 低度节点和远离重置点的节点从抑制中获益最多.
结论:
- 随机重置是缓解复杂网络中极端事件的有效策略.
- 这些发现为利用重置作为控制机制提供了理论依据.
- 重置提供了一个可调节的方法来管理网络系统中的关键现象.
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