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The hitting time of clique factors

Authors: Annika Heckel; Marc Kaufmann; Noëla Müller; Matija Pasch;

The hitting time of clique factors

Abstract

AbstractIn [Trans. Am. Math. Soc. 375 (2022), no. 1, 627–668], Kahn gave the strongest possible, affirmative, answer to Shamir's problem, which had been open since the late 1970s: Let and let be divisible by . Then, in the random ‐uniform hypergraph process on vertices, as soon as the last isolated vertex disappears, a perfect matching emerges. In the present work, we prove the analogue of this result for clique factors in the random graph process: at the time that the last vertex joins a copy of the complete graph , the random graph process contains a ‐factor. Our proof draws on a novel sequence of couplings which embeds the random hypergraph process into the cliques of the random graph process. An analogous result is proved for clique factors in the ‐uniform hypergraph process ().

Countries
Switzerland, Netherlands, Sweden, Switzerland
Keywords

FOS: Computer and information sciences, Discrete Mathematics (cs.DM), Discrete Mathematics, Computer Sciences, perfect matching, Probability (math.PR), Random graphs (graph-theoretic aspects), clique factor, Diskret matematik, Hypergraphs, hitting time, 05C80, 05C70, 05C65, clique factor; hitting time; hypergraphs; perfect matching; random graphs, Datavetenskap (datalogi), hypergraphs, Edge subsets with special properties (factorization, matching, partitioning, covering and packing, etc.), FOS: Mathematics, Mathematics - Combinatorics, Combinatorics (math.CO), Mathematics - Probability, random graphs, Computer Science - Discrete Mathematics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
hybrid