小素数域上多元多项式的最优检验

Elad Haramaty, Amir Shpilka, M. Sudan
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引用次数: 29

摘要

我们考虑测试一个给定函数的问题 $f : \F_q^n \right arrow \F_q$ 接近于 $n$-变量度 $d$ 有限域上的多项式 $\F_q$ 的 $q$元素。对这个属性的自然的、低查询的测试是选择最小的维度 $t = t_{q,d}\approx d/q$ 使得每一个度数大于 $d$揭示了这方面 {\em 一些} $t$的-维仿射子空间 $\F_q^n$ 为了验证这一点 $f$ 当被限制在 {\em 随机的} $t$五维仿射子空间最多是一个次多项式 $d$ 在这个子空间上。这样的测试只会使 $q^t$ 查询,独立于 $n$. 以前的作品,由阿隆等人。 \cite{AKKLR}考夫曼和罗恩 \cite{KaufmanRon06} 以及Jutla等人。 \cite{JPRZ04},表明这种自然测试拒绝了$\Omega(1)$-远非程度 $d$-至少有概率的多项式 $\Omega(q^{-t})$. (前期工作 \cite{AKKLR} 只考虑的情况 $q=2$,而工作 \cite{JPRZ04}只考虑了素数的情况 $q$. 结果是 \cite{KaufmanRon06} 对所有字段都适用。)从而得到距离度空间等距离的函数的检测概率为常数 $d$ 多项式,测试的结果 $q^{2t}$ 查询。考夫曼和罗恩还指出,当 $q$ 它是素数 $q^t$ 查询是必要的。因此,这些测试与已知的下界至少相差一个二次因子。Bhattacharyya等人。 \cite{BKSSZ10} 对于二元场的情况,给出了该检验的最优分析,并表明自然检验实际上拒绝了以下函数 $\Omega(1)$-远非程度 $d$-带概率的多项式$\Omega(1)$. 在这项工作中,我们将这一结果推广到所有领域,表明自然测试确实拒绝了以下函数 $\Omega(1)$-远非程度 $d$ 带的多项式$\Omega(1)$-概率,其中常数只依赖于 $q$ 字段大小。因此,我们的分析表明,这个测试是最佳的(匹配已知的下界),当 $q$ 是质数。我们工作的主要技术成分是对“超平面”(协维仿射子空间)数量的严密分析 $1$),其中一个程度的限制 $d$多项式的次数小于 $d$. 我们证明了这种超平面的数量最多是 $O(q^{t_{q,d}})$ ——在常数因子范围内是紧密的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal Testing of Multivariate Polynomials over Small Prime Fields
We consider the problem of testing if a given function $f : \F_q^n \right arrow \F_q$ is close to a $n$-variate degree $d$ polynomial over the finite field $\F_q$ of $q$elements. The natural, low-query, test for this property would be to pick the smallest dimension $t = t_{q,d}\approx d/q$ such that every function of degree greater than $d$reveals this aspect on {\em some} $t$-dimensional affine subspace of $\F_q^n$ and to test that $f$ when restricted to a {\em random} $t$-dimensional affine subspace is a polynomial of degree at most $d$ on this subspace. Such a test makes only $q^t$ queries, independent of $n$. Previous works, by Alon et al.~\cite{AKKLR}, and Kaufman and Ron~\cite{KaufmanRon06} and Jutla et al.~\cite{JPRZ04}, showed that this natural test rejected functions that were$\Omega(1)$-far from degree $d$-polynomials with probability at least $\Omega(q^{-t})$. (The initial work~\cite{AKKLR} considered only the case of $q=2$, while the work~\cite{JPRZ04}only considered the case of prime $q$. The results in \cite{KaufmanRon06} hold for all fields.) Thus to get a constant probability of detecting functions that are at constant distance from the space of degree $d$ polynomials, the tests made $q^{2t}$ queries. Kaufman and Ron also noted that when $q$ is prime, then $q^t$ queries are necessary. Thus these tests were off by at least a quadratic factor from known lower bounds. Bhattacharyya et al.~\cite{BKSSZ10} gave an optimal analysis of this test for the case of the binary field and showed that the natural test actually rejects functions that were $\Omega(1)$-far from degree $d$-polynomials with probability$\Omega(1)$. In this work we extend this result for all fields showing that the natural test does indeed reject functions that are $\Omega(1)$-far from degree $d$ polynomials with$\Omega(1)$-probability, where the constants depend only on $q$ the field size. Thus our analysis thus shows that this test is optimal (matches known lower bounds) when $q$ is prime. The main technical ingredient in our work is a tight analysis of the number of ``hyper planes'' (affine subspaces of co-dimension $1$) on which the restriction of a degree $d$polynomial has degree less than $d$. We show that the number of such hyper planes is at most $O(q^{t_{q,d}})$ -- which is tight to within constant factors.
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