Improved Bounds on Fourier Entropy and Min-entropy

Srinivasan Arunachalam, Sourav Chakraborty, M. Koucký, Nitin Saurabh, R. D. Wolf
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引用次数: 12

Abstract

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 ˆ (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(fˆ2) ≤ C ⋅ Inf (f), where H(fˆ2) 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(fˆ2) ≤ 2 ⋅ aUC⊕(f), where aUC⊕(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 ∞ fˆ2) ≤ C ⋅ Inf(f), where H ∞ fˆ2) is the min-entropy of the Fourier distribution. We show H∞(fˆ2) ≤ 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∞(fˆ2)≤2 log⁡(∥fˆ∥1,ε/(1−ε)), where ∥fˆ∥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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傅里叶熵和最小熵的改进界
给定布尔函数f:{-1,1} ^{n}→{-1,1,定义傅里叶分布为[n]子集上的分布,其中每个S≤[n]以概率f≤(S)2抽样。Friedgut和Kalai[28]的傅里叶熵-影响(FEI)猜想试图将与傅里叶分布相关的两个基本测度联系起来:是否存在一个普适常数C > 0,使得H(f²)≤C·Inf(f),其中H(f²)是f的傅里叶分布的香农熵,而Inf(f)是f的总影响。本文中,我们对FEI猜想提出了三个新的贡献:(1)我们的第一个贡献表明H(f²)≤2⋅aUC⊕(f),其中aUC⊕(f)是f的平均无二义奇偶证明复杂度。这改进了Chakraborty等人[20]给出的几个边界。我们进一步改进了无二义dnf的边界。我们还讨论了我们的工作如何使Mansour的dnf猜想成为解决FEI猜想的自然下一步。(2)我们接下来考虑O'Donnell和其他人[50,53]提出的较弱的傅立叶最小熵影响(FMEI)猜想,该猜想询问H∞f²)≤C⋅Inf(f),其中H∞f²)是傅里叶分布的最小熵。我们显示H∞(fˆ2)≤2⋅Cmin⊕(f),在Cmin⊕(f)的最低parity-certificate复杂性是f。我们还表明,所有ε≥0,我们有H∞(fˆ2)≤2日志⁡(∥fˆ∥1 /ε(1−ε)),在∥fˆ∥1,ε是近似谱范数f。作为推论,我们验证类的FMEI猜想read-k DNFs(常数k)。(3)我们的第三个贡献是为了更好地理解影响范猜想的多项式的结构1/3-approximate布尔函数的布尔立方体。我们提出一个猜想:没有阶数为d且稀疏度为2ω(d)的平坦多项式(其非零傅立叶系数具有相同大小)可以1/3近似布尔函数。假设FEI为真,我们对一类多项式无条件地证明了这个猜想(即不假设FEI猜想)。我们讨论了我们的猜想与bohnenblust - hill不等式常数之间的有趣联系,这在泛函分析中得到了广泛的研究。
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