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Sums of products of polynomials in few variables : lower bounds and polynomial identity testing

机译:几个变量的多项式乘积的和:下界和多项式恒等性检验

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We study the complexity of representing polynomials as a sum of products of polynomials in few variables. More precisely, we study representations of the form P = T i =1 d j =1 Q i j such that each Q i j is an arbitrary polynomial that depends on at most s variables. We prove the following results. 1. Over fields of characteristic zero, for every constant such that 0 1 , we give an explicit family of polynomials P N , where P N is of degree n in N = n O (1) variables, such that any representation of the above type for P N with s = N requires Td n ( n ) . This strengthens a recent result of Kayal and Saha [KS14a] which showed similar lower bounds for the model of sums of products of linear forms in few variables. It is known that any asymptotic improvement in the exponent of the lower bounds (even for s = n ) would separate VP and VNP[KS14a]. 2. We obtain a deterministic subexponential time blackbox polynomial identity testing (PIT) algorithm for circuits computed by the above model when T and the individual degree of each variable in P are at most log O (1) N and s N for any constant 1 2 . We get quasipolynomial running time when s log O (1) N . The PIT algorithm is obtained by combining our lower bounds with the hardness-randomness tradeoffs developed in [DSY09, KI04]. To the best of our knowledge, this is the first nontrivial PIT algorithm for this model (even for the case s = 2 ), and the first nontrivial PIT algorithm obtained from lower bounds for small depth circuits.
机译:我们研究了在很少的变量中将多项式表示为多项式乘积之和的复杂性。更准确地说,我们研究P = T i = 1 d j = 1 Q i j形式的表示形式,以使每个Q i j是一个最多取决于s个变量的任意多项式。我们证明以下结果。 1.在特征零的字段上,对于每个常数0 1,我们给出一个明确的多项式族PN,其中PN在N = n O(1)变量中的度为n,因此对于s = N的PN需要Td n(n)。这加强了Kayal和Saha [KS14a]的最新结果,该结果显示了在很少变量的情况下线性形式的乘积和模型的相似下界。众所周知,下界指数的任何渐近改善(即使对于s = n)都将VP和VNP [KS14a]分开。 2.当T和P中每个变量的单个度分别为log O(1)N和s N对于任何常数1时,对于上述模型计算的电路,我们获得确定性的亚指数时间黑盒多项式身份测试(PIT)算法。 2。当s log O(1)N时,我们得到准多项式运行时间。 PIT算法是通过将我们的下限与[DSY09,KI04]中开发的硬度-随机性折衷相结合而获得的。据我们所知,这是该模型的第一个非平凡的PIT算法(即使对于s = 2的情况),也是从小深度电路的下限获得的第一个非平凡的PIT算法。

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