Quasirandomness in hypergraphs

An $n$-vertex graph $G$ of edge density $p$ is considered to be quasirandom if it shares several important properties with the random graph $G(n,p)$. A well-known theorem of Chung, Graham and Wilson states that many such `typical' properties are asymptotically equivalent and, thus, a graph $G$ possessing one such property automatically satisfies the others. In recent years, work in this area has focused on uncovering more quasirandom graph properties and on extending the known results to other discrete structures. In the context of hypergraphs, however, one may consider several different notions of quasirandomness. A complete description of these notions has been provided recently by Towsner, who proved several central equivalences using an analytic framework. We give short and purely combinatorial proofs of the main equivalences in Towsner's result.Comment: 19 page

Small rainbow cliques in randomly perturbed dense graphs

For two graphs G and H, write G rbw −→ H if G has the property that every proper colouring of its edges yields a rainbow copy of H. We study the thresholds for such so-called anti-Ramsey properties in randomly perturbed dense graphs, which are unions of the form G ∪ G(n, p), where G is an n-vertex graph with edge-density at least d > 0, and d is independent of n. In a companion paper, we proved that the threshold for the property G ∪ G(n, p) rbw −→ K` is n −1/m2(Kd`/2e) , whenever ` ≥ 9. For smaller `, the thresholds behave more erratically, and for 4 ≤ ` ≤ 7 they deviate downwards significantly from the aforementioned aesthetic form capturing the thresholds for large cliques. In particular, we show that the thresholds for ` ∈ {4, 5, 7} are n −5/4 , n −1 , and n −7/15, respectively. For ` ∈ {6, 8} we determine the threshold up to a (1 + o(1))-factor in the exponent: they are n −(2/3+o(1)) and n −(2/5+o(1)), respectively. For ` = 3, the threshold is n −2 ; this follows from a more general result about odd cycles in our companion paper

Large rainbow cliques in randomly perturbed dense graphs

For two graphs G and H, write G⟶ rbw H if G has the property that every proper colouring of its edges yields a rainbow copy of H. We study the thresholds for such so-called anti-Ramsey properties in randomly perturbed dense graphs, which are unions of the form G∪ G(n, p), where G is an n-vertex graph with edge-density at least d, and d is a constant that does not depend on n. We determine the threshold for the property G∪ G(n, p) ⟶ rbw Ks for every s. We show that for s≥ 9 the threshold is n-1/m2(K⌈s/2⌉) ; in fact, our 1-statement is a supersaturation result. This turns out to (almost) be the threshold for s= 8 as well, but for every 4 ≤ s≤ 7, the threshold is lower and is different for each 4 ≤ s≤ 7. Moreover, we prove that for every ℓ≥ 2 the threshold for the property G∪ G(n, p) ⟶ rbw C2ℓ-1 is n- 2 ; in particular, the threshold does not depend on the length of the cycle C2ℓ-1. It is worth mentioning that for even cycles, or more generally for any fixed bipartite graph, no random edges are needed at all

Rainbow Cliques in Randomly Perturbed Dense Graphs

For two graphs G and H, write G⟶ rbw H if G has the property that every proper colouring of its edges yields a rainbow copy of H. We study the thresholds for such so-called anti-Ramsey properties in randomly perturbed dense graphs, which are unions of the form G∪ G(n, p), where G is an n-vertex graph with edge-density at least d, and d is a constant that does not depend on n. We determine the threshold for the property G∪ G(n, p) ⟶ rbw Ks for every s. We show that for s≥ 9 the threshold is n-1/m2(K⌈s/2⌉) ; in fact, our 1-statement is a supersaturation result. This turns out to (almost) be the threshold for s= 8 as well, but for every 4 ≤ s≤ 7, the threshold is lower and is different for each 4 ≤ s≤ 7. Moreover, we prove that for every ℓ≥ 2 the threshold for the property G∪ G(n, p) ⟶ rbw C2ℓ-1 is n- 2 ; in particular, the threshold does not depend on the length of the cycle C2ℓ-1. It is worth mentioning that for even cycles, or more generally for any fixed bipartite graph, no random edges are needed at all

Quasirandomness in hypergraphs

A graph G is called quasirandom if it possesses typical properties of the corresponding random graph G(n,p) with the same edge density as G. A well-known theorem of Chung, Graham and Wilson states that, in fact, many such ‘typical’ properties are asymptotically equivalent and, thus, a graph G possessing one property immediately satisfies the others. In recent years, more quasirandom graph properties have been found and extensions to hypergraphs have been explored. For the latter, however, there exist several distinct notions of quasirandomness. A complete description of these notions has been provided recently by Towsner, who proved several central equivalences using an analytic framework. The purpose of this paper is to give short purely combinatorial proofs of most of Towsner's results