One of the first results in graph theory was Dirac’s theorem which claims that if the minimum degree in a graph is at least half of the number of vertices, then it contains a Hamiltonian cycle. This result has inspired countless other results all stating that in dense graphs we can find sparse spanning subgraphs. Along these lines, one of the most far-reaching results is the celebrated Bandwidth Theorem, proved around 10 years ago by Böttcher, Schacht, and Taraz. It states, rougly speaking, that every n-vertex graph with minimum degree at least (r−1r+o(1))n contains a copy of all n-vertex graphs H such that χ(H)≤r,Δ(H)=O(1), and the bandwidth of H is o(n). This was conjectured earlier by Bollobás and Komlós. The proof is using the Regularity method based on the Regularity Lemma and the Blow-up Lemma.
Ever since the Bandwith Theorem came out, it has been open whether one could prove a similar statement for sparse random graphs. In this remarkable, deep paper the authors do just that, they establish sparse random analogues of the Bandwidth Theorem. In particular, the authors show that, for every positive integer Δ, if p≫(lognn)1/Δ, then asymptotically almost surely, every subgraph G⊆G(n,p) with δ(G)≥(r−1r+o(1))np contains a copy of every r-colourable spanning (i.e., n-vertex) graph H with maximum degree at most Δ and bandwidth o(n), provided that H contains at least Cp−2 vertices that do not lie on a triangle (of H). (The requirement about vertices not lying on triangles is necessary, as pointed out by Huang, Lee, and Sudakov.) The main tool used in the proof is the recent monumental sparse Blow-up Lemma due to Allen, Böttcher, Hàn, Kohayakawa, and Person.