Enhancing the extended hensel construction by using Gröbner basis

Tateaki Sasaki, D. Inaba
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引用次数: 1

Abstract

Contrary to that the general Hensel construction (GHC: [3]) uses univariate initial Hensel factors, the extended Hensel construction (EHC: [8]) uses multivariate initial Hensel factors determined by the Newton polygon (see below) of the given multivariate polynomial F (x, u) ∈ K[x, u], where (u) = (u1,...,u), with ≥ 2, and K is a number field. The F(x, u) may be such that its leading coefficient may vanish at (u) = (0) = (0,...,0), and even may be F(x, 0) = 0. The EHC was used so far for computing series expansion of multivariate algebraic function determined by F(x, u) = 0, at critical points [8, 5] and for factorization [4, 1] and GCD computation [7] of F(x, u), without shifting the origin of u. It allows us to construct efficient algorithms for sparse multivariate polynomials [1, 7]. The EHC is another and promising approach than Zippel's sparse Hensel lifting [9, 10].
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利用Gröbner为基础加强延伸自身建设
与一般Hensel构造(GHC:[3])使用单变量初始Hensel因子不同,扩展Hensel构造(EHC:[8])使用由给定多元多项式F (x, u)∈K[x, u]的牛顿多边形(见下)决定的多变量初始Hensel因子,其中(u) = (u1,…,u),其中,r≥2,K是一个数域。F(x, u)可以使其前系数在(u) =(0) =(0,…,0)处消失,甚至可以使F(x, 0) = 0。迄今为止,EHC被用于计算由F(x, u) = 0决定的多元代数函数在临界点处的级数展开[8,5],以及F(x, u)在不移动u原点的情况下的因数分解[4,1]和GCD计算[7],它允许我们构建高效的稀疏多元多项式算法[1,7]。EHC是另一种比Zippel的稀疏Hensel提升方法更有前途的方法[9,10]。
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