首页> 外文期刊>Electronic Colloquium on Computational Complexity >A Note on the Limitations of Two Black-Box Techniques in Quantified Derandomization
【24h】

A Note on the Limitations of Two Black-Box Techniques in Quantified Derandomization

机译:关于黑盒技术在量化非随机化中的局限性的注记

获取原文
           

摘要

The quantified derandomization problem of a circuit class with a function B : N N is the following: Given an input circuit C over n bits, deterministically distinguish between the case that C accepts all but B ( n ) of its inputs and the case that C rejects all but B ( n ) of its inputs. This generalizes the standard derandomization problem, which is the special case where B ( n ) = 2 n 3 .A major goal of this framework is to serve as a stepping-stone on the way to standard derandomization. Specifically, we want to construct reductions of the standard derandomization problem of a class to the quantified derandomization problem (e.g., using strong error-reduction), and to then construct an algorithm that solves the latter. In this note we show that if both the reduction (from standard derandomization to quantified derandomization) and the algorithm (for quantified derandomization) are constructed using two specific natural techniques that only rely on ``black-box'' access to the input circuit C , then a naive combination of the two algorithms does not suffice to yield a standard derandomization of . That is, when using these two techniques, the parameter value B ( n ) to which standard derandomization is reduced is necessarily larger than the value B ( n ) that the quantified derandomization algorithm can handle.
机译:具有函数B的电路类别的量化去随机化问题:NN如下:给定输入电路C超过n位,确定性地区分C接受除输入B(n)以外的所有情况和C拒绝其输入的情况除B(n)以外的所有输入。这概括了标准非随机化问题,这是B(n)= 2 n 3的特例。此框架的主要目标是充当标准非随机化的垫脚石。具体而言,我们想要构造一类标准去随机化问题到量化去随机化问题的简化(例如,使用强错误减少),然后构造一种解决后者的算法。在本说明中,我们表明,如果减少(从标准去随机化到量化去随机化)和算法(用于量化去随机化)都是使用两种仅依靠对输入电路C的``黑匣子''访问的特定自然技术构造而成的,则这两种算法的幼稚组合不足以产生的标准去随机化。即,当使用这两种技术时,标准去随机化被减小到的参数值B(n)必须大于量化去随机化算法可以处理的参数B(n)。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号