Controlling the average degree in random power-law networks

Autor:	Vieira, Allan, Moura, Judson, Anteneodo, Celia
Rok vydání:	2022
Předmět:	Condensed Matter - Statistical Mechanics Condensed Matter - Disordered Systems and Neural Networks Computer Science - Social and Information Networks
Druh dokumentu:	Working Paper
Popis:	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. Comment: 13 pages, 8 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2203.11784 Zobrazit plný text záznamu View this record from Arxiv