Given integers k, j with 1 ≤ j ≤ k − 1, we consider the length of the longest j-tight path in the binomial random k-uniform hypergraph H k (n, p). We show that this length undergoes a phase transition from logarithmic length to linear and determine the critical threshold, as well as proving upper and lower bounds on the length in the subcritical and supercritical ranges.In particular, for the supercritical case we introduce the Pathfinder algorithm, a depth-first search algorithm which discovers j-tight paths in a k-uniform hypergraph. We prove that, in the supercritical case, with high probability this algorithm will find a long j-tight path.
Given integers k, j with 1 ≤ j ≤ k − 1, we consider the length of the longest j-tight path in the binomial random k-uniform hypergraph H k (n, p). We show that this length undergoes a phase transition from logarithmic length to linear and determine the critical threshold, as well as proving upper and lower bounds on the length in the subcritical and supercritical ranges.In particular, for the supercritical case we introduce the Pathfinder algorithm, a depth-first search algorithm which discovers j-tight paths in a k-uniform hypergraph. We prove that, in the supercritical case, with high probability this algorithm will find a long j-tight path.
Motivated by the bootstrap percolation process for graphs, we define a new, high-order generalisation to k-uniform hypergraphs, in which we infect j-sets of vertices for some integer 1 ≤ j ≤ k − 1. We investigate the smallest possible size of an initially infected set which ultimately percolates and determine the exact size in almost all cases of k and j.
Inspired by the study of loose cycles in hypergraphs, we define the loose core in hypergraphs as a structure which mirrors the close relationship between cycles and 2-cores in graphs. We prove that in the r-uniform binomial random hypergraph H r (n, p), the order of the loose core undergoes a phase transition at a certain critical threshold and determine this order, as well as the number of edges, asymptotically in the subcritical and supercritical regimes.Our main tool is an algorithm called CoreConstruct, which enables us to analyse a peeling process for the loose core. By analysing this algorithm we determine the asymptotic degree distribution of vertices in the loose core and in particular how many vertices and edges the loose core contains. As a corollary we obtain an improved upper bound on the length of the longest loose cycle in H r (n, p).
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