论文标题
控制随机幂律网络中的平均程度
Controlling the average degree in random power-law networks
论文作者
论文摘要
我们描述了一个程序，该程序允许连续调整具有幂律学位分布$ p（k）$的不相关网络的平均度$ \ langle k \ rangle $。 Inn命令为此，我们将低$ K $区域的$ p（k）$修改，同时将大$ k $尾巴保存到截止日期。然后，我们使用修改后的$ P（k）$来获取通过配置模型构建网络所需的度序列。我们分析了最接近的邻居学位和本地聚类，以验证$ k $依赖性的缺失。最后，引入了进一步的修改，以消除平均程度的样本波动。
We describe a procedure that allows continuously tuning the average degree $\langle k \rangle$ of uncorrelated networks with power-law degree distribution $p(k)$. Inn order to do this, we modify the low-$k$ region of $p(k)$, while preserving the large-$k$ tail up to a cutoff. Then, we use the modified $p(k)$ to obtain the degree sequence required to construct networks through the configuration model. We analyze the resulting nearest-neighbor degree and local clustering to verify the absence of $k$-dependencies. Finally, a further modification is introduced to eliminate the sample fluctuations in the average degree.
