Sharp thresholds in adaptive random graph processes

IF 0.9 3区 数学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING Random Structures & Algorithms Pub Date : 2023-11-07 DOI:10.1002/rsa.21197
Calum MacRury, Erlang Surya
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Abstract

Abstract The ‐process is a single player game in which the player is initially presented the empty graph on vertices. In each step, a subset of edges is independently sampled according to a distribution . The player then selects one edge from , and adds to its current graph. For a fixed monotone increasing graph property , the objective of the player is to force the graph to satisfy in as few steps as possible. The ‐process generalizes both the Achlioptas process and the semi‐random graph process. We prove a sufficient condition for the existence of a sharp threshold for in the ‐process. Using this condition, in the semi‐random process we prove the existence of a sharp threshold when corresponds to being Hamiltonian or to containing a perfect matching. This resolves two of the open questions proposed by Ben‐Eliezer et al. (RSA, 2020).
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自适应随机图处理中的尖锐阈值
这个过程是一个单人游戏,在这个游戏中,玩家最初看到的是一个空的顶点图。在每一步中,根据一个分布对边缘子集进行独立采样。然后玩家从中选择一条边,并将其添加到当前图形中。对于固定的单调递增图形属性,玩家的目标是迫使图形在尽可能少的步骤中得到满足。该过程推广了Achlioptas过程和半随机图过程。在此过程中,我们证明了一个尖锐阈值存在的充分条件。利用这个条件,我们证明了在半随机过程中,当对应于哈密顿量或包含完美匹配时,存在一个尖锐阈值。这解决了Ben - Eliezer等人(RSA, 2020)提出的两个开放性问题。
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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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