【摘 要】
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How complex a network is crucially impacts its function and performance.In many modern applications,the networks involved have a growth property and sparse
【机 构】
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DepartmentofMathematics,TongjiUniversity,Shanghai,200092
【出 处】
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第十九届全国凝聚态理论与统计物理学术会议
论文部分内容阅读
How complex a network is crucially impacts its function and performance.In many modern applications,the networks involved have a growth property and sparse structures,which pose challenges to physicists and applied mathematicians.Here,we introduce the forest likelihood as a plausible measure to gauge how difficult it is to construct a forest in a non-preferential attachment manner.Based on the notions of admittable labeling and path construction,we propose algorithms for computing the forest likelihood of any given forest.Concrete examples as well as the distributions of forest likelihoods for all forests with some fixed numbers of nodes are presented.Moreover,we illustrate the ideas on real-life networks,including a benzenoid tree,a mathematical family tree,and a peer-to-peer network.
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