language-icon Old Web
English
Sign In

Continuous Tur\'an numbers

2021 
In this paper, we define a notion of containment and avoidance for subsets of $\mathbb{R}^2$. Then we introduce a new, continuous and super-additive extremal function for subsets $P \subseteq \mathbb{R}^2$ called $px(n, P)$, which is the supremum of $\mu_2(S)$ over all open $P$-free subsets $S \subseteq [0, n]^2$, where $\mu_2(S)$ denotes the Lebesgue measure of $S$ in $\mathbb{R}^2$. We show that $px(n, P)$ fully encompasses the Zarankiewicz problem and more generally the 0-1 matrix extremal function $ex(n, M)$ up to a constant factor. More specifically, we define a natural correspondence between finite subsets $P \subseteq \mathbb{R}^2$ and 0-1 matrices $M_P$, and we prove that $px(n, P) = \Theta(ex(n, M_P))$ for all finite subsets $P \subseteq \mathbb{R}^2$, where the constants in the bounds depend only on the distances between the points in $P$. We also discuss bounded infinite subsets $P$ for which $px(n, P)$ grows faster than $ex(n, M)$ for all fixed 0-1 matrices $M$. In particular, we show that $px(n, P) = \Theta(n^{2})$ for any open subset $P \subseteq \mathbb{R}^2$. We prove an even stronger result, that if $Q_P$ is the set of points with rational coordinates in any open subset $P \subseteq \mathbb{R}^2$, then $px(n, Q_P) = \Theta(n^2)$. Finally, we obtain a strengthening of the K\H{o}vari-S\'{o}s-Tur\'{a}n theorem that applies to infinite subsets of $\mathbb{R}^2$. Specifically, for subsets $P_{s, t, c} \subseteq \mathbb{R}^2$ consisting of $t$ horizontal line segments of length $s$ with left endpoints on the same vertical line with consecutive segments a distance of $c$ apart, we prove that $px(n, P_{s, t,c}) = O(s^{\frac{1}{t}}n^{2-\frac{1}{t}})$, where the constant in the bound depends on $t$ and $c$. When $t = 2$, we show that this bound is sharp up to a constant factor that depends on $c$.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    41
    References
    0
    Citations
    NaN
    KQI
    []