Explicit, almost optimal, epsilon-balanced codes

A. Ta-Shma
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引用次数: 67

Abstract

The question of finding an epsilon-biased set with close to optimal support size, or, equivalently, finding an explicit binary code with distance 1-ϵ/2 and rate close to the Gilbert-Varshamov bound, attracted a lot of attention in recent decades. In this paper we solve the problem almost optimally and show an explicit ϵ-biased set over k bits with support size O(k/ϵ2+o(1)). This improves upon all previous explicit constructions which were in the order of k2/ϵ2, k/ϵ3 or k5/4/ϵ5/2. The result is close to the Gilbert-Varshamov bound which is O(k/ϵ2) and the lower bound which is Ω(k/ϵ2 log1/ϵ). The main technical tool we use is bias amplification with the s-wide replacement product. The sum of two independent samples from an ϵ-biased set is ϵ2 biased. Rozenman and Wigderson showed how to amplify the bias more economically by choosing two samples with an expander. Based on that they suggested a recursive construction that achieves sample size O(k/ϵ4). We show that amplification with a long random walk over the s-wide replacement product reduces the bias almost optimally.
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显式的,几乎最优的,平衡的代码
近几十年来,找到一个接近最优支持大小的ε偏集的问题,或者等价地,找到一个距离为1- ε /2且速率接近吉尔伯特-瓦尔沙莫夫界的显式二进制码的问题,吸引了很多关注。在本文中,我们几乎最优地解决了这个问题,并给出了一个显式的ϵ-biased集合,其支持大小为O(k/ϵ2+ O(1))。这改进了以前所有显式结构,其顺序为k2/ϵ2, k/ϵ3或k5/4/ϵ5/2。结果接近吉尔伯特-瓦尔沙莫夫界,即O(k/ϵ2)和下界Ω(k/ϵ2 log1/ λ)。我们使用的主要技术工具是带有s宽替换产品的偏置放大。来自ϵ-biased集合的两个独立样本的和是ϵ2有偏的。罗森曼和威格森展示了如何用膨胀器选择两个样本,从而更经济地放大偏差。在此基础上,他们提出了一个递归结构,达到样本大小O(k/ϵ4)。我们表明,在s-wide替换产品上进行长时间随机漫步的放大几乎可以最佳地减少偏差。
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