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Comparison of Simulations with a Mean-Field Approach vs. Synthetic Correlated Networks
Symmetry ( IF 2.2 ) Pub Date : 2021-01-16 , DOI: 10.3390/sym13010141 Maria Letizia Bertotti , Giovanni Modanese
Symmetry ( IF 2.2 ) Pub Date : 2021-01-16 , DOI: 10.3390/sym13010141 Maria Letizia Bertotti , Giovanni Modanese
It is well known that dynamical processes on complex networks are influenced by the degree correlations. A common way to take these into account in a mean-field approach is to consider the function (average nearest neighbors degree). We re-examine the standard choices of for scale-free networks and a new family of functions which is independent from the simple ansatz but still displays a remarkable scale invariance. A rewiring procedure is then used to explicitely construct synthetic networks using the full correlation from which is derived. We consistently find that the functions of concrete synthetic networks deviate from ideal assortativity or disassortativity at large k. The consequences of this deviation on a diffusion process (the network Bass diffusion and its peak time) are numerically computed and discussed for some low-dimensional samples. Finally, we check that although the functions of the new family have an asymptotic behavior for large networks different from previous estimates, they satisfy the general criterium for the absence of an epidemic threshold.
中文翻译:
均值场方法与综合相关网络的仿真比较
众所周知,复杂网络上的动力学过程受程度相关性的影响。在均值场方法中考虑这些因素的常见方法是考虑函数 (平均最近邻居度)。我们重新检查的标准选择 适用于无标度网络和独立于简单ansatz的新功能系列 但仍然显示出明显的尺度不变性。然后使用重新布线过程使用完全相关性显式构建合成网络 从中 派生。我们始终发现 在k较大时,混凝土合成网络的功能偏离了理想的可分解性。对于一些低维样本,通过数值计算并讨论了这种偏差对扩散过程(网络低音扩散及其峰值时间)的影响。最后,我们检查了 新家族的功能对于不同于先前估计的大型网络具有渐近行为,它们满足了没有流行阈值的一般标准。
更新日期:2021-01-18
中文翻译:
均值场方法与综合相关网络的仿真比较
众所周知,复杂网络上的动力学过程受程度相关性的影响。在均值场方法中考虑这些因素的常见方法是考虑函数