Effective computation of resultants is a central problem in elimination theory and polynomial system solving. Commonly, we compute the resultant as a quotient of determinants of matrices and we say that there exists a determinantal formula when we can express it as a determinant of a matrix whose elements are the coefficients of the input polynomials. We study the resultant in the context of mixed multilinear polynomial systems, that is multilinear systems with polynomials having different supports, on which determinantal formulas were not known. We construct determinantal formulas for two kind of multilinear systems related to the Multiparameter Eigenvalue Problem (MEP): first, when the polynomials agree in all but one block of variables; second, when the polynomials are bilinear with different supports, related to a bipartite graph. We use the Weyman complex to construct Koszul-type determinantal formulas that generalize Sylvester-type formulas. We can use the matrices associated to these formulas to solve square systems without computing the resultant. The combination of the resultant matrices with the eigenvalue and eigenvector criterion for polynomial systems leads to a new approach for solving MEP.
翻译:生成物的有效计算是消除理论和多元系统解决的中心问题。 通常, 我们计算得出的结果是矩阵决定因素的商数, 并且我们说, 当我们可以将它表达为一个矩阵的决定因素时, 我们有一个决定性的公式, 这个矩阵的元素是输入多分子数的系数。 我们从混合多线多线多元系统的角度来研究结果, 这个系统是多线性系统, 具有不同支持的多线性决定式多线性系统, 并不知道这些公式。 我们为与多线性基值问题( MEP) 相关的两种多线性系统构建了确定性公式公式的确定性公式: 首先, 当多线性系统在全部变量中达成一致时; 第二, 当多线性系统具有不同支持的双线性, 与双线性图有关。 我们用Weyman复杂系统来构建 Koszul 型决定性公式, 将Sylvester- 型公式普遍化。 我们可以使用与这些公式相关的矩阵相关的矩阵来解析平方系统, 而不计算结果性模型。 将结果模型和模型的组合结果性标值作为新的模型。