The structure of sparse resultant matrices

Resultants characterize the existence of roots of systems of multivariatc nonlinear polynomial equations, while their matrices reduce the computation of all common zeros to a problemi nlirmaralgebra. Sparse elimination theory ha.s introduced the sparse resultant, which takes into account the sparse structurr of the polynomials. The construction of sparse resultant, or Newton, matrices is a critical step in the computation of the resultant and the solution of the system. We exploit the matrix structure and decrease the time complexity of constructing such matrices to roughly quadratic inthe matrix dimension, whereas the previous methods had cubic complexity. The space complexity is also decreased by one order of magnitude. These results imply similar improvements in the complexity of computing the resultant itself and of solving zero-dimensional systems. We apply some novel techniques for determining the rank of rectangularmatrices byanexact or numerical computation. Finally, we improve theexisting complexity forpolynomid multiplication under our model of sparseness, offering bounds linear in the number of variables and the number of nonzero terms.