Improved bounds on Fourier entropy and Min-entropy

Abstract

Given a Boolean function f:\-1,1\n \-1,1\, the Fourier distribution assigns probability f(S)2 to S⊂eq [n]. The Fourier Entropy-Influence (FEI) conjecture of Friedgut and Kalai asks if 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. 1) We consider the weaker Fourier Min-entropy-Influence (FMEI) conjecture. This asks if H∞(f2)≤ C Inf(f), where H∞(f2) is the min-entropy of the Fourier distribution. We show H∞(f2)≤ 2C(f), where C(f) is the minimum parity certificate complexity of f. We also show that for every ε≥ 0, we have H∞(f2)≤ 2 (\|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). 2) We show that H(f2)≤ 2 aUC(f), where aUC(f) is the average unambiguous parity certificate complexity of f. This improves upon Chakraborty et al. An important consequence of the FEI conjecture is the long-standing Mansour's conjecture. We show that a weaker version of FEI already implies Mansour's conjecture: is H(f2)≤ C \C0(f),C1(f)\?, where C0(f), C1(f) are the 0- and 1-certificate complexities of f, respectively. 3) We study what FEI implies about the structure of polynomials that 1/3-approximate a Boolean function. We pose a conjecture (which is implied by FEI): no "flat" degree-d polynomial of sparsity 2ω(d) can 1/3-approximate a Boolean function. We prove this conjecture unconditionally for a particular class of polynomials.

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