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A criterion for Andrásfai--Erdős--Sós type theorems and applications

Published 30 Jan 2024 in math.CO and cs.CC | (2401.17219v4)

Abstract: The classical Andr\'{a}sfai--Erd\H{o}s--S\'{o}s Theorem states that for 2\ell\ge 2, every nn-vertex K+1K_{\ell+1}-free graph with minimum degree greater than 3431n\frac{3\ell-4}{3\ell-1}n must be \ell-partite. We establish a simple criterion for rr-graphs, r2r \geq 2, to exhibit an Andr\'{a}sfai--Erd\H{o}s--S\'{o}s type property, also known as degree-stability. This leads to a classification of most previously studied hypergraph families with this property. An immediate application of this result, combined with a general theorem by Keevash--Lenz--Mubayi, solves the spectral Tur\'{a}n problems for a large class of hypergraphs. For every rr-graph FF with degree-stability, there is a simple algorithm to decide the FF-freeness of an nn-vertex rr-graph with minimum degree greater than (π(F)εF)(nr1)(\pi(F) - \varepsilon_F)\binom{n}{r-1} in time O(n<sup>r)O(n<sup>r), where $\varepsilon_F &gt;0$ is a constant. In particular, for the complete graph K+1K_{\ell+1}, we can take εK+1=(3<sup>2)<sup>1\varepsilon_{K_{\ell+1}} = (3\ell<sup>2-\ell)<sup>{-1}, and this bound is tight up to some multiplicative constant factor unless W[1]=FPT\mathbf{W[1]} = \mathbf{FPT}. Based on a result by Chen--Huang--Kanj--Xia, we further show that for every fixed $C &gt; 0$, this problem cannot be solved in time n<sup>o()n<sup>{o(\ell)} if we replace εK+1\varepsilon_{K_{\ell+1}} with (C)<sup>1(C\ell)<sup>{-1} unless ETH\mathbf{ETH} fails. Furthermore, we apply the degree-stability of K+1K_{\ell+1} to decide the K+1K_{\ell+1}-freeness of graphs whose size is close to the Tur\'{a}n bound in time (+1)n<sup>2(\ell+1)n<sup>2, partially improving a recent result by Fomin--Golovach--Sagunov--Simonov. As an intermediate step, we show that for a specific class of rr-graphs FF, the (surjective) FF-coloring problem can be solved in time O(n<sup>r)O(n<sup>r), provided the input rr-graph has nn vertices and a large minimum degree, refining several previous results.

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