稀疏多项式分解相关问题的求解

Pranav Bisht, Ilya Volkovich
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引用次数: 1

摘要

在Bhargava, Saraf和Volkovich [FOCS ' 18;JACM ' 20]给出了常单次多项式的第一因子稀疏性界。特别地,证明了多项式的任何因子最多有s项,且单个次以d为界,其本身最多有s O (d2 log n)项。据推测,“真正的”稀疏性界应该是多项式(即s poly(d))。在本文中,我们通过提出多项式时间算法来支持这一猜想,这些算法将隐含在一个多项式大小的稀疏性界中。特别地,我们给出了有效的(确定性的)算法来测试Σ [2] ΠΣΠ [ind - deg]电路的同一性,以及测试稀疏多项式是否为精确幂。因此,我们的算法依赖于不同的技术。
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On Solving Sparse Polynomial Factorization Related Problems
In a recent result of Bhargava, Saraf and Volkovich [FOCS’18; JACM’20], the first factor sparsity bound for constant individual degree polynomials was shown. In particular, it was shown that any factor of a polynomial with at most s terms and individual degree bounded by d can itself have at most s O ( d 2 log n ) terms. It is conjectured, though, that the “true” sparsity bound should be polynomial (i.e. s poly( d ) ). In this paper we provide supporting evidence for this conjecture by presenting polynomial-time algorithms for several problems that would be implied by a polynomial-size sparsity bound. In particular, we give efficient (deterministic) algorithms for identity testing of Σ [2] ΠΣΠ [ ind - deg d ] circuits and testing if a sparse polynomial is an exact power. Hence, our algorithms rely on different techniques.
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