Error reduction for weighted PRGs against read once branching programs

Gil Cohen, Dean Doron, Oren Renard, Ori Sberlo, A. Ta-Shma
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引用次数: 15

Abstract

Weighted pseudorandom generators (WPRGs), introduced by Braverman, Cohen and Garg [5], are a generalization of pseudorandom generators (PRGs) in which arbitrary real weights are considered, rather than a probability mass. Braverman et al. constructed WPRGs against read once branching programs (ROBPs) with near-optimal dependence on the error parameter. Chattopadhyay and Liao [6] somewhat simplified the technically involved BCG construction, also obtaining some improvement in parameters. In this work we devise an error reduction procedure for PRGs against ROBPs. More precisely, our procedure transforms any PRG against length n width w ROBP with error 1/poly(n) having seed length s to a WPRG with seed length s + O(log w/ε · log log 1/ε). By instantiating our procedure with Nisan's PRG [17] we obtain a WPRG with seed length O(log n · log(nw) + log w/ε · log log 1/ε). This improves upon [5] and is incomparable with [6]. Our construction is significantly simpler on the technical side and is conceptually cleaner. Another advantage of our construction is its low space complexity O(log nw) + poly(log log 1/ε) which is logarithmic in n for interesting values of the error parameter ε. Previous constructions (like [5, 6]) specify the seed length but not the space complexity, though it is plausible they can also achieve such (or close) space complexity.
加权prg对一次读分支程序的误差减少
加权伪随机生成器(Weighted pseudo - random generators, WPRGs)是由Braverman、Cohen和Garg[5]引入的,它是对伪随机生成器(pseudo - random generators, prg)的一种推广,其中考虑了任意的实权重,而不是概率质量。Braverman等人针对只读一次分支程序(robp)构建了wprg,该程序对误差参数的依赖接近最优。Chattopadhyay和Liao[6]在一定程度上简化了BCG构造所涉及的技术,在参数上也有一定的改进。在这项工作中,我们设计了一个PRGs对抗robp的错误减少程序。更准确地说,我们的过程将任何长度为n宽度为w的PRG,误差为1/poly(n),种子长度为s,转换为种子长度为s + O(log w/ε·log log 1/ε)的WPRG。通过用Nisan的PRG实例化我们的过程[17],我们得到了种子长度为O(log n·log(nw) + log w/ε·log log 1/ε)的WPRG。这在[5]的基础上有所改进,是[6]无法比拟的。我们的构造在技术方面明显更简单,概念上也更清晰。我们构造的另一个优点是它的低空间复杂度O(log nw) + poly(log log 1/ε),对于误差参数ε的有趣值,它是n的对数。以前的结构(如[5,6])指定了种子长度,但没有指定空间复杂度,尽管它们似乎也可以达到这样(或接近)的空间复杂度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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