14 research outputs found
Toric Border Bases
We extend the theory and the algorithms of Border Bases to systems of Laurent
polynomial equations, defining "toric" roots. Instead of introducing new
variables and new relations to saturate by the variable inverses, we propose a
more efficient approach which works directly with the variables and their
inverse. We show that the commutation relations and the inversion relations
characterize toric border bases. We explicitly describe the first syzygy module
associated to a toric border basis in terms of these relations. Finally, a new
border basis algorithm for Laurent polynomials is described and a proof of its
termination is given for zero-dimensional toric ideals
Stable normal forms for polynomial system solving
This paper describes and analyzes a method for computing border bases of a
zero-dimensional ideal . The criterion used in the computation involves
specific commutation polynomials and leads to an algorithm and an
implementation extending the one provided in [MT'05]. This general border basis
algorithm weakens the monomial ordering requirement for \grob bases
computations. It is up to date the most general setting for representing
quotient algebras, embedding into a single formalism Gr\"obner bases, Macaulay
bases and new representation that do not fit into the previous categories. With
this formalism we show how the syzygies of the border basis are generated by
commutation relations. We also show that our construction of normal form is
stable under small perturbations of the ideal, if the number of solutions
remains constant. This new feature for a symbolic algorithm has a huge impact
on the practical efficiency as it is illustrated by the experiments on
classical benchmark polynomial systems, at the end of the paper
Solving Polynomial Systems via a Stabilized Representation of Quotient Algebras
We consider the problem of finding the isolated common roots of a set of
polynomial functions defining a zero-dimensional ideal I in a ring R of
polynomials over C. We propose a general algebraic framework to find the
solutions and to compute the structure of the quotient ring R/I from the null
space of a Macaulay-type matrix. The affine dense, affine sparse, homogeneous
and multi-homogeneous cases are treated. In the presented framework, the
concept of a border basis is generalized by relaxing the conditions on the set
of basis elements. This allows for algorithms to adapt the choice of basis in
order to enhance the numerical stability. We present such an algorithm and show
numerical results
On the asymptotic and practical complexity of solving bivariate systems over the reals
This paper is concerned with exact real solving of well-constrained,
bivariate polynomial systems. The main problem is to isolate all common real
roots in rational rectangles, and to determine their intersection
multiplicities. We present three algorithms and analyze their asymptotic bit
complexity, obtaining a bound of \sOB(N^{14}) for the purely projection-based
method, and \sOB(N^{12}) for two subresultant-based methods: this notation
ignores polylogarithmic factors, where bounds the degree and the bitsize of
the polynomials. The previous record bound was \sOB(N^{14}).
Our main tool is signed subresultant sequences. We exploit recent advances on
the complexity of univariate root isolation, and extend them to sign evaluation
of bivariate polynomials over two algebraic numbers, and real root counting for
polynomials over an extension field. Our algorithms apply to the problem of
simultaneous inequalities; they also compute the topology of real plane
algebraic curves in \sOB(N^{12}), whereas the previous bound was
\sOB(N^{14}).
All algorithms have been implemented in MAPLE, in conjunction with numeric
filtering. We compare them against FGB/RS, system solvers from SYNAPS, and
MAPLE libraries INSULATE and TOP, which compute curve topology. Our software is
among the most robust, and its runtimes are comparable, or within a small
constant factor, with respect to the C/C++ libraries.
Key words: real solving, polynomial systems, complexity, MAPLE softwareComment: 17 pages, 4 algorithms, 1 table, and 1 figure with 2 sub-figure
Solving polynomial systems via symbolic-numeric reduction to geometric involutive form
AbstractWe briefly survey several existing methods for solving polynomial systems with inexact coefficients, then introduce our new symbolic-numeric method which is based on the geometric (Jet) theory of partial differential equations. The method is stable and robust. Numerical experiments illustrate the performance of the new method
Resultant-based methods for plane curves intersection problems
http://www.springeronline.com/3-540-28966-6We present an algorithm for solving polynomial equations, which uses generalized eigenvalues and eigenvectors of resultant matrices. We give special attention to the case of two bivariate polynomials and the Sylvester or Bezout resultant constructions. We propose a new method to treat multiple roots, detail its numerical aspects and describe experiments on tangential problems, which show the efficiency of the approach. An industrial application of the method is presented at the end of the paper. It consists in recovering cylinders from a large cloud of points and requires intensive resolution of polynomial equations