2021
DOI: 10.48550/arxiv.2101.12205
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Cycle decompositions in $3$-uniform hypergraphs

Abstract: We show that 3-graphs on n vertices whose codegree is at least p2{3 `op1qqn can be decomposed into tight cycles and admit Euler tours, subject to the trivial necessary divisibility conditions. We also provide a construction showing that our bounds are best possible up to the op1q term. All together, our results answer in the negative some recent questions of Glock, Joos, Kühn, and Osthus.

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Cited by 5 publications
(12 citation statements)
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“…This in particular includes the case that 𝛿(H) ≥ (1∕2 + o(1))n, settles a question posed by Glock, Kühn, and Osthus for graphs [5], and improves significantly on previous results [4]. This is particularly interesting as very recently, Piga and Sanhueza-Matamala [11] showed that for 3-graphs the decomposition threshold for (long) cycles is in fact 2∕3. It is therefore plausible that for hypergraphs of higher uniformity this threshold is also significantly higher than 1∕2.…”
Section: Discussionsupporting
confidence: 82%
“…This in particular includes the case that 𝛿(H) ≥ (1∕2 + o(1))n, settles a question posed by Glock, Kühn, and Osthus for graphs [5], and improves significantly on previous results [4]. This is particularly interesting as very recently, Piga and Sanhueza-Matamala [11] showed that for 3-graphs the decomposition threshold for (long) cycles is in fact 2∕3. It is therefore plausible that for hypergraphs of higher uniformity this threshold is also significantly higher than 1∕2.…”
Section: Discussionsupporting
confidence: 82%
“…This is analogous to the fact that for fixed j ∈ N, in a random triple system with m = N 2 triples, the number of (j, j − 2)-configurations is of the same order m, but in a random triple system with m = o(N 2 ) triples, the number of (j, j − 2)configurations is negligible compared to m. Actually, this is the key fact underlying Brown, Erdős, and Sós' lower bound for the (j, j − 2)-problem 6. Related ideas using Euler tours also appear in papers of Keevash[35] and Piga and Sanhueza-Matamala[50].…”
mentioning
confidence: 96%
“…The next result compares probabilities of sum of Bernoulli random variables (not necessarily independent) with binomial random variables. This seems a fairly standard result that may be found in [25], for example. Lemma 2.17.…”
Section: Another Useful Inequalitiessupporting
confidence: 63%