Given a Boolean function f:{ -1,1}n → {-1,1}, define the Fourier distribution to be the distribution on subsets of [n], where each S ⊆ [n] is sampled with probability f (S)2. The Fourier Entropy-influence (FEI) conjecture of Friedgut and Kalai [28] seeks to relate two fundamental measures associated with the Fourier distribution: does there exist a universal constant C > 0 such that H(f2) ≤ C · Inf (f), where H(f2) is the Shannon entropy of the Fourier distribution of f and Inf(f) is the total influence of f? In this article, we present three new contributions toward the FEI conjecture: (1) Our first contribution shows that H(f2) ≤ 2 · aUC⊕(f), where a UC⊕(f) is the average unambiguous parity-certificate complexity of f. This improves upon several bounds shown by Chakraborty et al. [20]. We further improve this bound for unambiguous DNFs. We also discuss how our work makes Mansour's conjecture for DNFs a natural next step toward resolution of the FEI conjecture. (2) We next consider the weaker Fourier Min-entropy-influence (FMEI) conjecture posed by O'Donnell and others [50, 53], which asks if H∞ (f2) ≤ C · Inf(f), where H ∞ (f2) is the min-entropy of the Fourier distribution. We show H∞(f2) ≤ 2·Cmin⊕(f), where Cmin⊕(f) is the minimum parity-certificate complexity of f. We also show that for all ϵ≥0, we have H∞(f2) ≤ 2 log (||f||1,ϵ/(1-ϵ)), where ||f||1,ϵ is the approximate spectral norm of f. As a corollary, we verify the FMEI conjecture for the class of read-k DNFs (for constant k). (3) Our third contribution is to better understand implications of the FEI conjecture for the structure of polynomials that 1/3-approximate a Boolean function on the Boolean cube. We pose a conjecture: no flat polynomial(whose non-zero Fourier coefficients have the same magnitude) of degree d and sparsity 2ω(d) can 1/3-approximate a Boolean function. This conjecture is known to be true assuming FEI, and we prove the conjecture unconditionally (i.e., without assuming the FEI conjecture) for a class of polynomials. We discuss an intriguing connection between our conjecture and the constant for the Bohnenblust-Hille inequality, which has been extensively studied in functional analysis.

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doi.org/10.1145/3470860
ACM Transactions on Computation Theory
Algorithms and Complexity

Arunachalam, S, Chakraborty, S, Koucký, M, Saurabh, N, & de Wolf, R.M. (2021). Improved bounds on Fourier Entropy and Min-entropy. ACM Transactions on Computation Theory, 13(4), 1–40. doi:10.1145/3470860