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A novel evolving scale-free model with tunable attractiveness |
Liu Xuan (刘绚)a, Liu Tian-Qi (刘天琪)a, Wang Hao (王昊)b, Li Xing-Yuan (李兴源)a |
a School of Electrical Engineering and Automation, Sichuan University, Chengdu 610000, China; b College of Electronics and Information Engineering, Sichuan University, Chengdu 610000, China |
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Abstract In this paper, a new evolving model with tunable attractiveness is presented. Based on the Barabasi—Albert (BA) model, we introduce the attractiveness of node which can change with node degree. Using the mean-field theory, we obtain the analytical expression of power-law degree distribution with the exponent $\gamma \in (3,\infty)$. The new model is more homogeneous and has a lower clustering coefficient and bigger average path length than the BA model.
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Revised: 18 January 2010
Accepted manuscript online:
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PACS:
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89.75.Hc
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(Networks and genealogical trees)
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02.30.Jr
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(Partial differential equations)
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02.50.Cw
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(Probability theory)
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Fund: Project supported by the National Key Technology Research and Development Program of the Ministry of Science and Technology of China (Grant No. 2008BAA13B01). |
Cite this article:
Liu Xuan (刘绚), Liu Tian-Qi (刘天琪), Wang Hao (王昊), Li Xing-Yuan (李兴源) A novel evolving scale-free model with tunable attractiveness 2010 Chin. Phys. B 19 070204
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