Spread blow-up lemma with an application to perturbed random graphs
Rajko Nenadov, Huy Tuan Pham
TL;DR
The paper proves a spread version of the blow-up lemma by combining algorithmic embedding techniques with spread perfect matchings, yielding an $O(1/N)$-spread distribution over embeddings of a spanning graph $H$ into systems of $(\varepsilon,\delta)$-super-regular pairs. This spread blow-up lemma enables probabilistic threshold reasoning via the Kahn–Kalai framework and is applied to perturbed random graphs to establish an approximate threshold for the appearance of the $k$-th power of Hamilton cycles in $G\cup G(n,p)$ under a typical minimum-degree regime. The main technical contributions are the construction of a carefully phased embedding algorithm with quasirandom control and a vertex-spread analysis that leverages recent results on spread perfect matchings. The results bridge the regularity method with random perturbations and provide robust tools for embedding problems in dense-plus-random graph models, with potential to tighten threshold results further in the perturbed setting.
Abstract
Combining ideas of Pham, Sah, Sawhney, and Simkin on spread perfect matchings in super-regular bipartite graphs with an algorithmic blow-up lemma, we prove a spread version of the blow-up lemma. Intuitively, this means that there exists a probability measure over copies of a desired spanning graph $H$ in a given system of super-regular pairs which does not heavily pin down any subset of vertices. This allows one to complement the use of the blow-up lemma with the recently resolved Kahn-Kalai conjecture. As an application, we prove an approximate version of a conjecture of Böttcher, Parczyk, Sgueglia, and Skokan on the threshold for appearance of powers of Hamilton cycles in perturbed random graphs.
