Majority dynamics on sparse random graphs

IF 0.9 3区 数学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Debsoumya Chakraborti, Jeong Han Kim, Joonkyung Lee, T. Tran
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引用次数: 5

Abstract

Majority dynamics on a graph G$$ G $$ is a deterministic process such that every vertex updates its ±1$$ \pm 1 $$ ‐assignment according to the majority assignment on its neighbor simultaneously at each step. Benjamini, Chan, O'Donnell, Tamuz and Tan conjectured that, in the Erdős–Rényi random graph G(n,p)$$ G\left(n,p\right) $$ , the random initial ±1$$ \pm 1 $$ ‐assignment converges to a 99%$$ 99\% $$ ‐agreement with high probability whenever p=ω(1/n)$$ p=\omega \left(1/n\right) $$ . This conjecture was first confirmed for p≥λn−1/2$$ p\ge \lambda {n}^{-1/2} $$ for a large constant λ$$ \lambda $$ by Fountoulakis, Kang and Makai. Although this result has been reproved recently by Tran and Vu and by Berkowitz and Devlin, it was unknown whether the conjecture holds for p0$$ {\lambda}^{\prime }>0 $$ .
稀疏随机图上的多数动态
图G $$ G $$上的多数动态是一个确定性过程,使得每个顶点在每一步同时根据其邻居的多数分配更新其±1 $$ \pm 1 $$‐分配。Benjamini, Chan, O'Donnell, Tamuz和Tan推测,在Erdős-Rényi随机图G(n,p) $$ G\left(n,p\right) $$中,随机初始±1 $$ \pm 1 $$‐分配收敛于99%$$ 99\% $$ ‐agreement with high probability whenever p=ω(1/n)$$ p=\omega \left(1/n\right) $$ . This conjecture was first confirmed for p≥λn−1/2$$ p\ge \lambda {n}^{-1/2} $$ for a large constant λ$$ \lambda $$ by Fountoulakis, Kang and Makai. Although this result has been reproved recently by Tran and Vu and by Berkowitz and Devlin, it was unknown whether the conjecture holds for p0$$ {\lambda}^{\prime }>0 $$ .
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来源期刊
Random Structures & Algorithms
Random Structures & Algorithms 数学-计算机:软件工程
CiteScore
2.50
自引率
10.00%
发文量
56
审稿时长
>12 weeks
期刊介绍: It is the aim of this journal to meet two main objectives: to cover the latest research on discrete random structures, and to present applications of such research to problems in combinatorics and computer science. The goal is to provide a natural home for a significant body of current research, and a useful forum for ideas on future studies in randomness. Results concerning random graphs, hypergraphs, matroids, trees, mappings, permutations, matrices, sets and orders, as well as stochastic graph processes and networks are presented with particular emphasis on the use of probabilistic methods in combinatorics as developed by Paul Erdõs. The journal focuses on probabilistic algorithms, average case analysis of deterministic algorithms, and applications of probabilistic methods to cryptography, data structures, searching and sorting. The journal also devotes space to such areas of probability theory as percolation, random walks and combinatorial aspects of probability.
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