Sharp Hypercontractivity for Global Functions
Nathan Keller, Noam Lifshitz, Omri Marcus
TL;DR
This work proves sharp hypercontractive and level-$d$ inequalities for global functions on general finite product spaces, extending the sharp, classical results beyond the uniform hypercube. The authors introduce restriction-based globalness and Gaussian encodings to reduce to Gaussian space and achieve tight dependence on the noise parameter $ ho$ and the level $d$, addressing a long-standing gap left by prior qualitative results. They then derive quantitative applications, notably sharp bounds on the sizes of smeared intersecting families and a suite of consequences for functions on the symmetric group $S_n$, including hypercontractivity, level-$d$ inequalities, character bounds, and variants of Roth’s theorem and Bogolyubov-type lemmas, with implications for diameter bounds and number-theoretic problems such as Furstenberg–Sárközy. The results unify and extend techniques across analysis of Boolean functions, combinatorics, and group theory, enabling sharper quantitative control in extremal problems under weak symmetry conditions. Overall, the paper provides a robust framework for sharp probabilistic-analytic bounds on global functions in diverse discrete settings, with broad downstream impact in combinatorics and theoretical computer science.
Abstract
For a function $f$ on the hypercube $\{0,1\}^n$ with Fourier expansion $f=\sum_{S\subseteq[n]}\hat f(S)χ_S$, the hypercontractive inequality allows bounding norms of $T_ρf=\sum_Sρ^{|S|} \hat f(S)χ_S$ in terms of norms of $f$. If $f$ is Boolean-valued, the level-$d$ inequality allows bounding the norm of $f^{=d}=\sum_{|S|=d}\hat f(S)χ_S$ in terms of $E[f]$. These inequalities play a central role in analysis of Boolean functions and its applications. While both inequalities hold in a sharp form when the hypercube is endowed with the uniform measure, they do not hold for more general discrete product spaces, and finding a `natural' generalization was a long-standing open problem. In 2024, Keevash et al.~obtained a hypercontractive inequality for general discrete product spaces, that holds for functions which are `global' -- namely, are not significantly affected by a restriction of a small set of coordinates. This hypercontractive inequality is not sharp, which precludes applications to $S_n$ and to other settings where sharpness of the bound is crucial. Also, no sharp level-$d$ inequality for global functions over general discrete product spaces is known. We obtain sharp versions of the hypercontractive inequality and of the level-$d$ inequality for this setting. Our inequalities open the way for diverse applications to extremal set theory, group theory, theoretical computer science, and number theory. We demonstrate this by proving quantitative bounds on the size of intersecting families of sets and vectors under weak symmetry conditions and by describing numerous applications that were obtained using our results -- to the study of functions over $S_n$, including hypercontractivity and level-$d$ inequalities, character bounds, variants of Roth's theorem and of Bogolyubov's lemma and diameter bounds, and an application to the Furstenberg-S{á}rk{ö}zy problem.