Software for Polynomials

SLV: Sturmbased solver on Maple.
Real solving of univariate equations and bivariate systems, operations on real algebraic numbers,
based on our paper at ACM ISSAC 2007.

Sparse resultants by the Incremental Algorithm.
AnsiC library and standalone implementation of the incremental algorithm
for building sparse resultant matrices of Sylvestertype
and for using them in computing all
common roots of a wellconstrained 0dimensional polynomial system.
Optimal Sylvestertype matrices are
constructed for all systems where this is provably possible.
See a tech. report on the code, and the
JSC article.
Maple functions
for connecting Maple to the program, including conversion of
Maple input to the appropriate format: file
"mapl2form" and file
"maplib".
Recent C++ code by Dr Clement Laroche here.

Sparse Resultants by Mixed Subdivisions
Maple overall implementation
(spares9,2004)
of the greedy method (a CannyPedersen variant of the original algorithm) to construct a sparse resultant matrix, including the computation of supports and Newton polytopes;
see our article (J.ACM'00).
There is the option to apply the D'AndreaEmiris perturbation for handling degenerate coefficients (paper).
These are all standalone functions.
The matrix construction is included in the general Maple resultant library (1998):
multires.
Here are the relevant
Maple functions.
Maple functions for format conversion:
mapl2form.
The user gains further / full control with functions in
"mapl2mapl".
Additional Maple routines for polynomials and matrices:
maplib.

Sparse Resultants for Multihomogeneous Systems
"scaledmhomo.mpl" contains Maple routines for testing the existence, computing the dimension, and constructing sparse resultant matrices of Sylvester, Bezout, or hybrid type, either determinantal or not, for systems whose Newton polytopes are scale copies of a single polytope.
Here is the paper with A. Mantzaflaris and
an example worksheet;
based on the paper with A. Dickenstein.

MARS
is a Maple/Matlab/C package for resultant matrices and eigensolving.
Jointly with A. Wallack and D. Manocha.

Mixed Volume, Mixed Subdivisions, Convex Hulls, and more: see software in
Discrete and Computational Geometry.
Ioannis Z. Emiris, 2020
This page is hardly maintained anymore.