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A Robust Khintchine Inequality, and Algorithms for Computing Optimal Constants in Fourier Analysis and High-Dimensional Geometry

机译:鲁棒的Khintchine不等式,以及在傅立叶分析和高维几何中计算最佳常数的算法

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This paper makes two contributions towards determining some well-studied optimal constants in Fourier analysis of Boolean functions and high-dimensional geometry. 1. It has been known since 1994 [GL94] that every linear threshold function has squared Fourier mass at least 1/2 on its degree-0 and degree-1 coefficients. Denote the minimum such Fourier mass by W~(≤1)[LTF], where the minimum is taken over all n-variable linear threshold functions and all n ≥ 0. Benjamini, Kalai and Schramm [BKS99] have conjectured that the true value of W~(≤1) [LTF] is 2/π. We make progress on this conjecture by proving that W~(≤1)[LTF] ≥ 1/2+c for some absolute constant c > 0. The key ingredient in our proof is a "robust" version of the well-known Khintchine inequality in functional analysis, which we believe may be of independent interest. 2. We give an algorithm with the following property: given any η > 0, the algorithm runs in time 2~(poly(1/η)) and determines the value of W~(≤1)[LTF] up to an additive error of ±η. We give a similar 2~(poly(1/η))-time algorithm to determine Tomaszewski's constant to within an additive error of ±η, this is the minimum (over all origin-centered hyperplanes H) fraction of points in {-1, 1}~n that lie within Euclidean distance 1 of H. Tomaszewski's constant is conjectured to be 1/2; lower bounds on it have been given by Holzman and Kleitman [HK92] and independently by Ben-Tal, Nemirovski and Roos [BTNR02]. Our algorithms combine tools from anti-concentration of sums of independent random variables, Fourier analysis, and Hermite analysis of linear threshold functions.
机译:本文对确定布尔函数和高维几何的傅立叶分析中一些经过充分研究的最佳常数做出了两个贡献。 1.自1994年以来就已经知道[GL94],每个线性阈值函数的0度和1度系数的傅立叶质量平方至少为1/2。用W〜(≤1)[LTF]表示这种傅立叶质量的最小值,其中最小值适用于所有n变量线性阈值函数且所有n≥0。Benjamini,Kalai和Schramm [BKS99]推测真实值W〜(≤1)的[LTF]为2 /π。通过证明W〜(≤1)[LTF]≥1/2 + c且绝对常数c> 0,我们对此猜想取得了进展。我们证明的关键要素是著名的Khintchine的“健壮”版本功能分析中的不平等,我们认为这可能与独立利益有关。 2.我们给出一种具有以下性质的算法:给定η> 0,该算法在时间2〜(poly(1 /η))内运行,并确定W〜(≤1)[LTF]的值,直至加法运算误差为±η。我们给出了一个类似的2〜(poly(1 /η))时间算法来确定Tomaszewski常数在±η的加性误差内,这是{-1中点的最小分数(在所有以原点为中心的超平面H上) ,1}〜n位于H的欧几里得距离1之内。Tomaszewski常数被猜想为1/2;下限由Holzman和Kleitman [HK92]以及Ben-Tal,Nemirovski和Roos [BTNR02]独立给出。我们的算法结合了来自独立随机变量和的反集中,傅里叶分析和线性阈值函数的Hermite分析等工具。

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