Exact threshold and limiting distribution for non-linear Hamilton cycles

Abstract

For positive integers r > ≥ 1, an -cycle in an r-uniform hypergraph is a cycle where each edge consists of r vertices and each pair of consecutive edges intersect in vertices. For ≥ 2, we determine the limiting distribution of the number of Hamilton -cycles in an Erdos--R\'enyi random hypergraph. The behavior is distinguished in two cases: -When ≥ 3, the number of cycles concentrates when the expectation diverges and converges to a Poisson distribution when the expectation is constant. -When = 2, the normalized number of cycles converges to a lognormal distribution when the expectation diverges and converges to a lognormal mixture of Poisson distributions when the expectation is constant. As a result we pin down the exact threshold for the appearance of non-linear Hamilton cycles in random hypergraphs, confirming a conjecture of Narayanan and Schacht.

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