在Yaldram-Khan催化反应模型的临界行为的拓学诱导的修改
Paulo F Gomes1,2, Henrique A Fernandes1, Roberto da Silva3
1Grupo de Redes Complexas Aplicadas de Jataí, Universidade Federal de Jataí, Jataí, Brazil.
复杂的网络影响了Yaldram-Khan模型.
科学领域:
- 统计物理 统计物理
- 复杂的系统复杂的系统.
- 网络科学 网络科学
背景情况:
- 雅尔德拉姆-汗模型是统计物理学中研究催化过程的基本模型.
- 了解阶段过渡和网络结构的影响对于复杂系统研究至关重要.
研究的目的:
- 研究复杂网络作为触媒表面对Yaldram-Khan模型相位图的影响.
- 通过埃尔多斯-雷尼网络 (ERN) 和随机几何图 (RGG) 引入随机性时分析相变的行为.
主要方法:
- 进行了广泛的稳定状态蒙特卡洛模拟.
- 分离率被固定为r_NO = 1.
- 反应窗口的行为被分析为平均网络程度的函数.
主要成果:
- 埃尔多斯-雷尼网络 (ERN) 保持了所有平均度的相位过渡的性质.
- 随机几何图 (RGG) 在低平均度上显示了两个二次相位过渡.
- 网络拓大大改变了相位图和过渡特征.
结论:
- 复杂的网络结构,特别是ERN和RGG,在Yaldram-Khan模型的阶段过渡中引入了不同的行为.
- 由于RGG的空间限制,与ERN的长距离随机性相比,其相位过渡动态不同.
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