中国物理B ›› 2017, Vol. 26 ›› Issue (2): 28901-028901.doi: 10.1088/1674-1056/26/2/028901

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

Scaling of weighted spectral distribution in weighted small-world networks

Bo Jiao(焦波), Xiao-Qun Wu(吴晓群)   

  1. 1 Luoyang Electronic Equipment Test Center, Luoyang 471003, China;
    2 School of Mathematics and Statistics, Wuhan University, Wuhan 430072, China
  • 收稿日期:2016-09-26 修回日期:2016-11-01 出版日期:2017-02-05 发布日期:2017-02-05
  • 通讯作者: Bo Jiao E-mail:jiaoboleetc@outlook.com
  • 基金资助:
    Project supported by the National Natural Science Foundation of China (Grant Nos. 61402485, 61573262, and 61303061).

Scaling of weighted spectral distribution in weighted small-world networks

Bo Jiao(焦波)1, Xiao-Qun Wu(吴晓群)2   

  1. 1 Luoyang Electronic Equipment Test Center, Luoyang 471003, China;
    2 School of Mathematics and Statistics, Wuhan University, Wuhan 430072, China
  • Received:2016-09-26 Revised:2016-11-01 Online:2017-02-05 Published:2017-02-05
  • Contact: Bo Jiao E-mail:jiaoboleetc@outlook.com
  • Supported by:
    Project supported by the National Natural Science Foundation of China (Grant Nos. 61402485, 61573262, and 61303061).

摘要: Many real-world systems can be modeled by weighted small-world networks with high clustering coefficients. Recent studies for rigorously analyzing the weighted spectral distribution (WSD) have focused on unweighted networks with low clustering coefficients. In this paper, we rigorously analyze the WSD in a deterministic weighted scale-free small-world network model and find that the WSD grows sublinearly with increasing network order (i.e., the number of nodes) and provides a sensitive discrimination for each input of this model. This study demonstrates that the scaling feature of the WSD exists in the weighted network model which has high and order-independent clustering coefficients and reasonable power-law exponents.

关键词: weighted spectral distribution, weighted small-world network, scaling

Abstract: Many real-world systems can be modeled by weighted small-world networks with high clustering coefficients. Recent studies for rigorously analyzing the weighted spectral distribution (WSD) have focused on unweighted networks with low clustering coefficients. In this paper, we rigorously analyze the WSD in a deterministic weighted scale-free small-world network model and find that the WSD grows sublinearly with increasing network order (i.e., the number of nodes) and provides a sensitive discrimination for each input of this model. This study demonstrates that the scaling feature of the WSD exists in the weighted network model which has high and order-independent clustering coefficients and reasonable power-law exponents.

Key words: weighted spectral distribution, weighted small-world network, scaling

中图分类号:  (Structures and organization in complex systems)

  • 89.75.Fb
89.75.Da (Systems obeying scaling laws)