期刊:
Journal of Statistical Mechanics: Theory and Experiment,2017年2017(9):093401- ISSN:1742-5468
通讯作者:
Zhu, Yueying
作者机构:
[Zhu, Yueying; Wang, Qiuping Alexandre] Univ Maine, UMR CNRS 6283, IMMM, F-72085 Le Mans, France.;[Zhu, Yueying; Li, Wei; Cai, Xu] Cent China Normal Univ, Complex Sci Ctr, Wuhan 430079, Hubei, Peoples R China.;[Zhu, Yueying; Li, Wei; Cai, Xu] Cent China Normal Univ, Inst Particle Phys, Wuhan 430079, Hubei, Peoples R China.;[Wang, Qiuping Alexandre] Yncrea, HEI, F-59014 Lille, France.;[Li, Wei] Max Planck Inst Math Sci, Inselst 22, D-04103 Leipzig, Germany.
通讯机构:
[Zhu, Yueying] U;[Zhu, Yueying] C;Univ Maine, UMR CNRS 6283, IMMM, F-72085 Le Mans, France.;Cent China Normal Univ, Complex Sci Ctr, Wuhan 430079, Hubei, Peoples R China.;Cent China Normal Univ, Inst Particle Phys, Wuhan 430079, Hubei, Peoples R China.
关键词:
agent-based models;algorithmic game theory;evolutionary game theory;nonlinear dynamics
作者机构:
[Zou, Yijiang; Zhao, Longfeng; Deng, Weibing; Li, Wei; Su, Zhu; Han, Jihui; Han, JH; Li, W] Cent China Normal Univ, Complex Sci Ctr, Wuhan, Hubei, Peoples R China.;[Zou, Yijiang; Zhao, Longfeng; Deng, Weibing; Li, Wei; Su, Zhu; Han, Jihui; Han, JH; Li, W] Cent China Normal Univ, Inst Particle Phys, Wuhan, Hubei, Peoples R China.;[Han, Jihui] Zhengzhou Univ Light Ind, Sch Comp & Commun Engn, Zhengzhou, Henan, Peoples R China.
通讯机构:
[Han, JH; Li, W; Deng, WB] C;[Han, Jihui] Z;Cent China Normal Univ, Complex Sci Ctr, Wuhan, Hubei, Peoples R China.;Cent China Normal Univ, Inst Particle Phys, Wuhan, Hubei, Peoples R China.;Zhengzhou Univ Light Ind, Sch Comp & Commun Engn, Zhengzhou, Henan, Peoples R China.
关键词:
Community structure;Network analysis;Algorithms;Internet;Color codes;Food web structure;Neural networks;Metabolic networks
摘要:
An adaptive label propagation algorithm (ALPA) is proposed to detect and monitor communities in dynamic networks. Unlike the traditional methods by re-computing the whole community decomposition after each modification of the network, ALPA takes into account the information of historical communities and updates its solution according to the network modifications via a local label propagation process, which generally affects only a small portion of the network. This makes it respond to network changes at low computational cost. The effectiveness of ALPA has been tested on both synthetic and real-world networks, which shows that it can successfully identify and track dynamic communities. Moreover, ALPA could detect communities with high quality and accuracy compared to other methods. Therefore, being low-complexity and parameter-free, ALPA is a scalable and promising solution for some real-world applications of community detection in dynamic networks.
作者机构:
[Zhang, Rui; Jiang, Jian] Wuhan Text Univ, Coll Math & Comp Sci, Wuhan 430200, Peoples R China.;[Guo, Long] China Univ Geosci, Sch Math & Phys, Wuhan 430074, Peoples R China.;[Li, Wei; Cai, Xu] Cent China Normal Univ, Inst Particle Phys, Complex Sci Ctr, Wuhan 430079, Peoples R China.
通讯机构:
[Jiang, Jian] W;Wuhan Text Univ, Coll Math & Comp Sci, Wuhan 430200, Peoples R China.
关键词:
多层航空运输网络;网络聚合过程
摘要:
The air transportation network, one of the common multilayer complex systems, is composed of a collection of individual airlines, and each airline corresponds to a different layer. An important question is then how many airlines are really necessary to represent the optimal structure of a multilayer air transportation system. Here we take the Chinese air transportation network (CATN) as an example to explore the nature of multiplex systems through the procedure of network aggregation. Specifically, we propose a series of structural measures to characterize the CATN from the multilayered to the aggregated network level. We show how these measures evolve during the network aggregation process in which layers are gradually merged together and find that there is an evident structural transition that happened in the aggregated network with nine randomly chosen airlines merged, where the network features and construction cost of this network are almost equivalent to those of the present CATN with twenty-two airlines under this condition. These findings could shed some light on network structure optimization and management of the Chinese air transportation system.
期刊:
International Journal of Modern Physics C,2016年27(10):1650122 ISSN:0129-1831
通讯作者:
Zhu, Yueying
作者机构:
[Wang, Qiuping A.; Zhu, Yueying] Univ Maine, IMMM, UMR CNRS 6283, F-72085 Le Mans, France.;[Zhao, Longfeng; Zhu, Yueying; Li, Wei; Cai, Xu] Cent China Normal Univ, Complex Sci Ctr, Wuhan 430079, Peoples R China.;[Zhao, Longfeng; Zhu, Yueying; Li, Wei; Cai, Xu] Cent China Normal Univ, Inst Particle Phys, Wuhan 430079, Peoples R China.;[Li, Wei] Max Planck Inst Math Sci, Inselst 22, D-04103 Leipzig, Germany.
通讯机构:
[Zhu, Yueying] U;[Zhu, Yueying] C;Univ Maine, IMMM, UMR CNRS 6283, F-72085 Le Mans, France.;Cent China Normal Univ, Complex Sci Ctr, Wuhan 430079, Peoples R China.;Cent China Normal Univ, Inst Particle Phys, Wuhan 430079, Peoples R China.
关键词:
Random walks;metro network;Laplacian spectrum;shortest path length
摘要:
In this paper, we investigate the random walks on metro systems in 28 cities from worldwide via the Laplacian spectrum to realize the trapping process on real systems. The average trapping time is a primary description to response the trapping process. Firstly, we calculate the mean trapping time to each target station and to each entire system, respectively. Moreover, we also compare the average trapping time with the strength (the weighted degree) and average shortest path length for each station, separately. It is noted that the average trapping time has a close inverse relation with the station’s strength but rough positive correlation with the average shortest path length. And we also catch the information that the mean trapping time to each metro system approximately positively correlates with the system’s size. Finally, the trapping process on weighted and unweighted metro systems is compared to each other for better understanding the influence of weights on trapping process on metro networks. Numerical results show that the weights have no significant impact on the trapping performance on metro networks.
作者机构:
School of Science, Jiangnan University, Wuxi, 214122, China;[池丽平; 李炜] College of Physical Science and Technology, Huazhong Normal University, Wuhan, 430079, China;[郭龙] School of Mathematics and Physics, China University of Geosciences (Wuhan), Wuhan, 430074, China;[江健] Research Center of Nonlinear Science and College of Mathematics and Computer Science, Wuhan Textile University, Wuhan, 430200, China;[辜姣] School of Science, Jiangnan University, Wuxi, 214122, China, College of Physical Science and Technology, Huazhong Normal University, Wuhan, 430079, China
通讯机构:
[Guo, L.] S;School of Mathematics and Physics, China University of Geosciences (Wuhan), Wuhan, China
作者机构:
[Deng, Weibing; Li, Wei; Han, Jihui; Han, JH; Li, W] Cent China Normal Univ, Complex Sci Ctr, Wuhan 430079, Peoples R China.;Cent China Normal Univ, Inst Particle Phys, Wuhan 430079, Peoples R China.
通讯机构:
[Han, JH; Li, W; Deng, WB] C;Cent China Normal Univ, Complex Sci Ctr, Wuhan 430079, Peoples R China.
摘要:
Aiming at improving the efficiency and accuracy of community detection in complex networks, we proposed a new algorithm, which is based on the idea that communities could be detected from subnetworks by comparing the internal and external cohesion of each subnetwork. In our method, similar nodes are firstly gathered into meta-communities, which are then decided to be retained or merged through a multilevel label propagation process, until all of them meet our community criterion. Our algorithm requires neither any priori information of communities nor optimization of any objective function. Experimental results on both synthetic and real-world networks show that, our algorithm performs quite well and runs extremely fast, compared with several other popular algorithms. By tuning a resolution parameter, we can also observe communities at different scales, so this could reveal the hierarchical structure of the network. To further explore the effectiveness of our method, we applied it to the E-Coli transcriptional regulatory network, and found that all the identified modules have strong structural and functional coherence.
摘要:
The standard model of particle physics describes the fundamental particles and their interactions via the strong, electromagnetic and weak forces. It provides precise predictions for measurable quantities that can be tested experimentally. The probabilities, or branching fractions, of the strange B meson (B-s(0)) and the B-0 meson decaying into two oppositely charged muons (mu(+) and mu(-)) are especially interesting because of their sensitivity to theories that extend the standard model. The standard model predicts that the B-s(0)->mu(+)mu(-) and B-0 ->mu(+)mu(-) decays are very rare, with about four of the former occurring for every billion B-s(0) mesons produced, and one of the latter occurring for every ten billion B-0 mesons(1). A difference in the observed branching fractions with respect to the predictions of the standard model would provide a direction in which the standard model should be extended. Before the Large Hadron Collider (LHC) at CERN2 started operating, no evidence for either decay mode had been found. Upper limits on the branching fractions were an order of magnitude above the standard model predictions. The CMS (Compact Muon Solenoid) and LHCb(Large Hadron Collider beauty) collaborations have performed a joint analysis of the data from proton-proton collisions that they collected in 2011 at a centre-of-mass energy of seven teraelectronvolts and in 2012 at eight teraelectronvolts. Here we report the first observation of the B-s(0)->mu(+)mu(-) decay, with a statistical significance exceeding six standard deviations, and the best measurement so far of its branching fraction. Furthermore, we obtained evidence for the B-0 ->mu(+)mu(-) decay with a statistical significance of three standard deviations. Both measurements are statistically compatible with standard model predictions and allow stringent constraints to be placed on theories beyond the standard model. The LHC experiments will resume taking data in 2015, recording proton-proton collisions at a centre-of-mass energy of 13 teraelectronvolts, which will approximately double the production rates of B-s(0) and B-0 mesons and lead to further improvements in the precision of these crucial tests of the standard model.