大多数选票模型在无规模网络上的关键短期行为
D S M Alencar1, J F S Neto1, T F A Alves1
1Departamento de Física, <a href="https://ror.org/00kwnx126">Universidade Federal do Piauí</a>, 57072-970, Teresina - PI, Brazil.
Physical review. E
|November 20, 2024
概括
我们分析了无规模网络上的多数投票模型的短期动态. 我们的发现揭示了依赖网络结构和参数的关键行为,为复杂系统动态提供了洞察力.
科学领域:
- 统计物理 统计物理
- 网络科学 网络科学
- 复杂的系统复杂的系统.
背景情况:
- 多数投票模型是研究复杂系统中的意见动态和阶段过渡的基本工具.
- 无规模网络表现出独特的拓性质,显著影响新出现的行为.
研究的目的:
- 调查大多数投票模型的关键短时间动态,特别是在无规模网络上.
- 引入和验证一个异质的平均场理论来描述这些动态.
主要方法:
- 为无尺度网络量身定制的异质平均场理论的开发.
- 广泛的蒙特卡洛模拟来分析顺序参数和随时间推移的易感性.
- 对动态和时间相关指数的封闭式表达式的导出.
主要成果:
- 异质平均场理论准确地预测了短时间的行为.
- 短时间缩放显示了对于5/2 < γ < 7/2.2.的非普遍的关键行为.
- 对于γ ≥ 7/2,观察到平均场Ising临界度与对数校正,匹配静止缩放.
结论:
- 这项研究提供了一个全面的了解在无规模网络上的多数投票模型中短时间的关键现象.
- 这些发现突出了网络拓和动态过程之间的相互作用.
- 由此产生的理论框架为模拟各种复杂系统中的集体行为提供了有价值的见解.
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