稀疏图收敛的一个L^{p}$理论II: LD收敛、商和右收敛

IF 2.1 1区 数学 Q1 STATISTICS & PROBABILITY
C. Borgs, J. Chayes, Henry Cohn, Yufei Zhao
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引用次数: 84

摘要

通过分析收敛的不同概念,我们扩展了在同伴论文中介绍的稀疏图极限的LpLp理论。在适当的节点权值限制下,证明了度量收敛、商收敛、微正则基态能量收敛、微正则自由能收敛和大偏差收敛的等价性。我们的定理将密集图收敛的广泛适用性扩展到所有具有无界平均度的稀疏图,而证明需要基于一致上正则性的新技术。我们的理论应用的例子包括随机块模型,幂律图和w -随机图的稀疏版本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An $L^{p}$ theory of sparse graph convergence II: LD convergence, quotients and right convergence
We extend the LpLp theory of sparse graph limits, which was introduced in a companion paper, by analyzing different notions of convergence. Under suitable restrictions on node weights, we prove the equivalence of metric convergence, quotient convergence, microcanonical ground state energy convergence, microcanonical free energy convergence and large deviation convergence. Our theorems extend the broad applicability of dense graph convergence to all sparse graphs with unbounded average degree, while the proofs require new techniques based on uniform upper regularity. Examples to which our theory applies include stochastic block models, power law graphs and sparse versions of WW-random graphs.
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来源期刊
Annals of Probability
Annals of Probability 数学-统计学与概率论
CiteScore
4.60
自引率
8.70%
发文量
61
审稿时长
6-12 weeks
期刊介绍: The Annals of Probability publishes research papers in modern probability theory, its relations to other areas of mathematics, and its applications in the physical and biological sciences. Emphasis is on importance, interest, and originality – formal novelty and correctness are not sufficient for publication. The Annals will also publish authoritative review papers and surveys of areas in vigorous development.
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