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Constructing Sylvester-type resultant matrices using the Dixon formulation

机译:使用Dixon公式构造Sylvester型结果矩阵

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A new method for constructing Sylvester-type resultant matrices for multivariate elimination is proposed. Unlike sparse resultant constructions discussed recently in the literature or the Macaulay resultant construction, the proposed method does not explicitly use the support of a polynomial system in the construction. Instead, a multiplier set for each polynomial is obtained from the Dixon resultant formulation using an arbitrary term (or a polynomial) for the construction. As shown in the Proceedings of the ACM Symposium on Theory of Computing (1996), the generalized Dixon resultant formulation implicitly exploits the sparse structure of the polynomial system. As a result, the proposed construction for Sylvester-type resultant matrices is sparse in the sense that the matrix size is determined by the support structure of the polynomial system, instead of the total degree of the polynomial system. The proposed construction is a generalization of a related construction proposed by the authors in which the monomial 1 is used (RCWA' 00, Proceedings of the 7th Rhine Workshop (2000), 167). It is shown that any polynomial (with support inside or outside the support of the polynomial system) can be used instead insofar as that polynomial does not vanish on any of the common zeros of the polynomial system. For generic unmixed polynomial systems (in which every polynomial in the polynomial system has the same support, i.e., the same set of terms), it is shown that the choice of a polynomial does not affect the matrix size insofar as the terms in the polynomial also appear in the polynomial system. The main advantage of the proposed construction is for mixed polynomial systems. Supports of a mixed polynomial system can be translated so as to have a maximal overlap, and a polynomial is selected with support from the overlapped subset of translated supports. Determining an appropriate translation vector for each support and a term from the overlapped support can be formulated as an optimization problem. It is shown that under certain conditions on the supports of polynomials in a mixed polynomial system, a polynomial can be selected leading to a Dixon dialytic matrix of the smallest size, thus implying that the projection operator computed using the proposed construction is either the resultant or has an extraneous factor of minimal degree. The proposed construction is compared theoretically and empirically, on a number of examples, with other methods for generating Sylvester-type resultant matrices.
机译:提出了一种构造用于多变量消除的Sylvester型结果矩阵的新方法。与文献中最近讨论的稀疏结果构造或Macaulay结果构造不同,所提出的方法未在构造中明确使用多项式系统的支持。取而代之的是,使用构造的任意项(或多项式)从Dixon结果公式中获得每个多项式的乘数集。如ACM计算理论研讨会的论文集(1996)中所示,广义Dixon结果公式隐式地利用了多项式系统的稀疏结构。结果,从矩阵大小是由多项式系统的支持结构而不是多项式系统的总度确定的意义上来说,拟议的Sylvester型结果矩阵的构造是稀疏的。提出的结构是作者提出的相关结构的概括,其中使用了多项式1(RCWA'00,《第七莱茵河研讨会的论文集》(2000年),第167页)。结果表明,可以使用任何多项式(在多项式系统的支持范围内或之外的支持范围),只要该多项式不会在多项式系统的任何公零上消失即可。对于一般的非混合多项式系统(其中多项式系统中的每个多项式都有相同的支持,即,相同的项集),表明多项式的选择不影响矩阵大小,只要多项式中的项也出现在多项式系统中。所提出的构造的主要优点是用于混合多项式系统。可以对混合多项式系统的支持进行转换,以使其具有最大的重叠,然后从转换后的支持的重叠子集中选择具有支持的多项式。确定每种支持物的适当翻译向量以及来自重叠支持物的术语可被表述为优化问题。结果表明,在一定条件下,在混合多项式系统中多项式的支持下,可以选择一个多项式,从而生成最小尺寸的Dixon透析矩阵,从而暗示使用所提出的结构计算的投影算子要么是结果,要么是具有最小程度的无关紧要因素。理论上和经验上,在许多示例中,将所提出的构造与其他生成Sylvester型结果矩阵的方法进行了比较。

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