A local-world evolving hypernetwork model

doi:10.1088/1674-1056/23/1/018901

中国物理B ›› 2014, Vol. 23 ›› Issue (1): 18901-018901.doi: 10.1088/1674-1056/23/1/018901

• INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY • 上一篇下一篇

A local-world evolving hypernetwork model

杨光勇, 刘建国

Research Center of Complex Systems Science, University of Shanghai for Science and Technology, Shanghai 200093, China

收稿日期:2013-05-28 修回日期:2013-07-30 出版日期:2013-11-12 发布日期:2013-11-12
基金资助:
Project supported by the National Natural Science Foundation of China (Grant Nos. 71071098, 91024026, and 71171136). Liu Jian-Guo is supported by the Shanghai Rising-Star Program, China (Grant No. 11QA1404500), and the Leading Academic Discipline Project of Shanghai City, China (Grant No. XTKX2012).

A local-world evolving hypernetwork model

Yang Guang-Yong (杨光勇), Liu Jian-Guo (刘建国)

Research Center of Complex Systems Science, University of Shanghai for Science and Technology, Shanghai 200093, China

Received:2013-05-28 Revised:2013-07-30 Online:2013-11-12 Published:2013-11-12
Contact: Liu Jian-Guo E-mail:liujg004@ustc.edu.cn
Supported by:
Project supported by the National Natural Science Foundation of China (Grant Nos. 71071098, 91024026, and 71171136). Liu Jian-Guo is supported by the Shanghai Rising-Star Program, China (Grant No. 11QA1404500), and the Leading Academic Discipline Project of Shanghai City, China (Grant No. XTKX2012).

摘要/Abstract

摘要： Complex hypernetworks are ubiquitous in the real system. It is very important to investigate the evolution mechanisms. In this paper, we present a local-world evolving hypernetwork model by taking into account the hyperedge growth and local-world hyperedge preferential attachment mechanisms. At each time step, a newly added hyperedge encircles a new coming node and a number of nodes from a randomly selected local world. The number of the selected nodes from the local world obeys the uniform distribution and its mean value is m. The analytical and simulation results show that the hyperdegree approximately obeys the power-law form and the exponent of hyperdegree distribution is γ=2+1/m. Furthermore, we numerically investigate the node degree, hyperedge degree, clustering coefficient, as well as the average distance, and find that the hypernetwork model shares the scale-free and small-world properties, which shed some light for deeply understanding the evolution mechanism of the real systems.

关键词: local-world evolving hypernetwork model, power-law form, small-world property

Abstract: Complex hypernetworks are ubiquitous in the real system. It is very important to investigate the evolution mechanisms. In this paper, we present a local-world evolving hypernetwork model by taking into account the hyperedge growth and local-world hyperedge preferential attachment mechanisms. At each time step, a newly added hyperedge encircles a new coming node and a number of nodes from a randomly selected local world. The number of the selected nodes from the local world obeys the uniform distribution and its mean value is m. The analytical and simulation results show that the hyperdegree approximately obeys the power-law form and the exponent of hyperdegree distribution is γ=2+1/m. Furthermore, we numerically investigate the node degree, hyperedge degree, clustering coefficient, as well as the average distance, and find that the hypernetwork model shares the scale-free and small-world properties, which shed some light for deeply understanding the evolution mechanism of the real systems.

Key words: local-world evolving hypernetwork model, power-law form, small-world property

中图分类号: (Networks and genealogical trees)

89.75.Hc

89.65.Ef (Social organizations; anthropology ?) 05.70.Ln (Nonequilibrium and irreversible thermodynamics)

杨光勇, 刘建国. A local-world evolving hypernetwork model[J]. 中国物理B, 2014, 23(1): 18901-018901.

Yang Guang-Yong (杨光勇), Liu Jian-Guo (刘建国). A local-world evolving hypernetwork model[J]. Chin. Phys. B, 2014, 23(1): 18901-018901.

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A local-world evolving hypernetwork model

A local-world evolving hypernetwork model

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