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Let f^{(r)}(n;s,k) be the maximum number of edges of an r-uniform hypergraph on n vertices not containing a subgraph with k edges and at most s vertices. In 1973, Brown, Erdős, and Sós conjectured that the limit \begin{equation*} \lim _{n\to \infty } n^{-2} f^{(3)}(n;k+2,k) \end{equation*} exists for all k and confirmed it for k=2. Recently, Glock showed this for k=3. We settle the next open case, k=4, by showing that f^{(3)}(n;6,4)=\left (\frac {7}{36}+o(1)\right)n^2 as n\to \infty. More generally, for all k\in \{3,4\}, r\ge 3 and t\in [2,r-1], we compute the value of the limit \lim _{n\to \infty } n^{-t}f^{(r)}(n;k(r-t)+t,k), which settles a problem of Shangguan and Tamo. [ABSTRACT FROM AUTHOR]

We prove that any quasirandom uniform hypergraph H can be approximately decomposed into any collection of bounded degree hypergraphs with almost as many edges. In fact, our results also apply to multipartite hypergraphs and even to the sparse setting when the density of H quickly tends to 0 in terms of the number of vertices of H. Our results answer and address questions of Kim, Kühn, Osthus and Tyomkyn; and Glock, Kühn and Osthus as well as Keevash. The provided approximate decompositions exhibit strong quasirandom properties which are very useful for forthcoming applications. Our results also imply approximate solutions to natural hypergraph versions of long-standing graph decomposition problems, as well as several decomposition results for (quasi)random simplicial complexes into various more elementary simplicial complexes such as triangulations of spheres and other manifolds. [ABSTRACT FROM AUTHOR]

We show that for all d ∈ {3, . . .,n - 1} the size of the largest component of a random d-regular graph on n vertices around the percolation threshold p = 1/(d-1) is Θ(n2/3), with high probability. This extends known results for fixed d ≥ 3 and for d = n - 1, confirming a prediction of Nachmias and Peres on a question of Benjamini. As a corollary, for the largest component of the percolated random d-regular graph, we also determine the diameter and the mixing time of the lazy random walk. In contrast to previous approaches, our proof is based on a simple application of the switching method. [ABSTRACT FROM AUTHOR]