In this paper, we give a cubic Goldreich-Levin algorithm which makes polynomially-many queries to a function $f \colon \mathbb F_p^n \to \mathbb C$ and produces a decomposition of $f$ as a sum of cubic phases and a small error term. This is a natural higher-order generalization of the classical Goldreich-Levin algorithm. The classical (linear) Goldreich-Levin algorithm has wide-ranging applications in learning theory, coding theory and the construction of pseudorandom generators in cryptography, as well as being closely related to Fourier analysis. Higher-order Goldreich-Levin algorithms on the other hand involve central problems in higher-order Fourier analysis, namely the inverse theory of the Gowers $U^k$ norms, which are well-studied in additive combinatorics. The only known result in this direction prior to this work is the quadratic Goldreich-Levin theorem, proved by Tulsiani and Wolf in 2011. The main step of their result involves an algorithmic version of the $U^3$ inverse theorem. More complications appear in the inverse theory of the $U^4$ and higher norms. Our cubic Goldreich-Levin algorithm is based on algorithmizing recent work by Gowers and Mili\'cevi\'c who proved new quantitative bounds for the $U^4$ inverse theorem. Our cubic Goldreich-Levin algorithm is constructed from two main tools: an algorithmic $U^4$ inverse theorem and an arithmetic decomposition result in the style of the Frieze-Kannan graph regularity lemma. As one application of our main theorem we solve the problem of self-correction for cubic Reed-Muller codes beyond the list decoding radius. Additionally we give a purely combinatorial result: an improvement of the quantitative bounds on the $U^4$ inverse theorem.
翻译:在本文中, 我们给出了一个立方的 Goldreich- Levin 算法, 使多立方- 多立方计算对一个函数 $f\ colonom f\ mathbb F_ p ⁇ n\ to\ mathb C$, 并产生一个以立方阶段和小错误术语总和为总和的分解 。 这是古典的 Goldreich- Levin 算法的自然高阶概括化。 古典( 线性) Goldreich- Levin 算法在学习理论、 codi- 理论和在加密中建造假币生成器方面有着广泛的应用, 也与 Fourier 的算法分析密切相关。 高端的Goldreich- Levin 算法在高端分析中涉及中心问题, 即Gowers $Ukn- kak 规则的反向反向理论。 在2011年中, 我们的主要算法变法4, 以新算法4 和新算法的立方 4 4 的自我演化结果为我们的主要变式。