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arXiv 2211.01062cs.CC
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通过有理函数求值进行多项式恒等测试

Polynomial Identity Testing via Evaluation of Rational Functions

Ivan Hu, Dieter van Melkebeek, Andrew Morgan

AI总结:

本文提出基于单变量有理函数求值的多项式恒等测试命中集生成器,通过刻画其消失理想获得紧界和确定性成员测试,并给出在去随机化与代数分支程序下界中的新应用。

摘要:

我们引入一种用于多项式恒等测试的命中集生成器,该生成器基于在与变量相关联的横坐标处对低次单变量有理函数进行求值。我们建立了该生成器与Shpilka和Volkovich引入的一个生成器之间在重新缩放意义下的等价性,后者具有类似结构但使用多元多项式。我们启动了对命中集生成器能力的系统性分析研究,通过刻画它们的消失理想,即它们未能命中的多项式集合。我们为我们的生成器提供了两个这样的刻画。首先,我们构造了一小组多项式,它们共同生成消失理想。作为推论,我们得到了消失理想中最小次数、稀疏性和集合多重线性的划分类大小的紧界。其次,受与交错代数联系的启发,我们为消失理想的多线性部分开发了一个结构化的确定性成员测试。我们给出了一个基于交错代数的推导以及所需的背景知识,还给出了一个基于零替换和偏导数的推导,从而避免了对交错代数的需要。作为我们分析方法实用性的证据,我们重新推导了基于Shpilka和Volkovich生成器的已知去随机化结果,并给出了在只读一次遗忘代数分支程序的去随机化/下界中的一个新应用。

英文摘要:

$ \newcommand{\ie}{i.\,e.} $We introduce a hitting set generator for Polynomial Identity Testing based on evaluations of low-degree univariate rational functions at abscissas associated with the variables. We establish an equivalence up to rescaling with a generator introduced by Shpilka and Volkovich, which has a similar structure but uses multivariate polynomials. We initiate a systematic analytic study of the power of hitting set generators by characterizing their vanishing ideals, \ie, the sets of polynomials that they fail to hit. We provide two such characterizations for our generator. First, we develop a small collection of polynomials that jointly produce the vanishing ideal. As corollaries, we obtain tight bounds on the minimum degree, sparseness, and partition class size of set-multilinearity in the vanishing ideal. Second, inspired by a connection to alternating algebra, we develop a structured deterministic membership test for the multilinear part of the vanishing ideal. We present a derivation based on alternating algebra along with the required background, as well as one in terms of zero substitutions and partial derivatives, avoiding the need for alternating algebra. As evidence of the utility of our analytic approach, we rederive known derandomization results based on the generator by Shpilka and Volkovich and present a new application in derandomization / lower bounds for read-once oblivious algebraic branching programs.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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