Product Space Models of Correlation: Between Noise Stability and Additive Combinatorics
Jan H\k{a}z{\l}a, Thomas Holenstein, Elchanan Mossel

TL;DR
This paper explores the connection between noise stability and additive combinatorics, establishing bounds and characterizing obstructions for correlation inequalities in product spaces with bounded correlation.
Contribution
It generalizes previous results by addressing the correlation question for multiple functions and bounded correlation, combining analytic and combinatorial methods.
Findings
Established correlation bounds for =2 and >2 with bounded correlation () < 1.
Characterized obstructions to lower bounds in multi-function settings.
Integrated techniques from influences, hyper-contraction, and additive combinatorics.
Abstract
There is a common theme to some research questions in additive combinatorics and noise stability. Both study the following basic question: Let be a probability distribution over a space with all marginals equal. Let where be random vectors such that for every coordinate the tuples are i.i.d. according to . A central question that is addressed in both areas is: - Does there exist a function independent of such that for every with : \begin{align*} \mathrm{E} \left[ \prod_{j=1}^\ell f(X^{(j)}) \right] \ge c(\mu) > 0 \, ? \end{align*} Instances of this question include the finite field model version…
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