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56
Numerical Decomposition of the Solution Sets of Polynomial Systems into Irreducible Components
, 2001
"... In engineering and applied mathematics, polynomial systems arise whose solution sets contain components of different dimensions and multiplicities. In this article we present algorithms, based on homotopy continuation, that compute much of the geometric information contained in the primary decomposi ..."
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Cited by 58 (27 self)
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In engineering and applied mathematics, polynomial systems arise whose solution sets contain components of different dimensions and multiplicities. In this article we present algorithms, based on homotopy continuation, that compute much of the geometric information contained in the primary decomposition of the solution set. In particular, ignoring multiplicities, our algorithms lay out the decomposition of the set of solutions into irreducible components, by finding, at each dimension, generic points on each component. As byproducts, the computation also determines the degree of each component and an upper bound on itsmultiplicity. The bound issharp (i.e., equal to one) for reduced components. The algorithms make essential use of generic projection and interpolation, and can, if desired, describe each irreducible component precisely as the common zeroesof a finite number of polynomials.
Numerical Homotopies to compute generic Points on positive dimensional Algebraic Sets
 Journal of Complexity
, 1999
"... Many applications modeled by polynomial systems have positive dimensional solution components (e.g., the path synthesis problems for fourbar mechanisms) that are challenging to compute numerically by homotopy continuation methods. A procedure of A. Sommese and C. Wampler consists in slicing the com ..."
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Cited by 52 (24 self)
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Many applications modeled by polynomial systems have positive dimensional solution components (e.g., the path synthesis problems for fourbar mechanisms) that are challenging to compute numerically by homotopy continuation methods. A procedure of A. Sommese and C. Wampler consists in slicing the components with linear subspaces in general position to obtain generic points of the components as the isolated solutions of an auxiliary system. Since this requires the solution of a number of larger overdetermined systems, the procedure is computationally expensive and also wasteful because many solution paths diverge. In this article an embedding of the original polynomial system is presented, which leads to a sequence of homotopies, with solution paths leading to generic points of all components as the isolated solutions of an auxiliary system. The new procedure significantly reduces the number of paths to solutions that need to be followed. This approach has been implemented and applied to...
Algebraic Solution of systems of polynomial equations using Gröbner bases
 Applied Algebra, Algebraic Algorithms and Error Correcting Codes, Proceedings of AAECC5, volume 356 of LNCS
, 1989
"... One of the most important applications of Buchberger's algorithm for Gröbner basis computation [BUC1,2,4] is the solution of systems of polynomial equations (having finitely many roots)... ..."
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Cited by 49 (4 self)
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One of the most important applications of Buchberger's algorithm for Gröbner basis computation [BUC1,2,4] is the solution of systems of polynomial equations (having finitely many roots)...
PHoM  a Polyhedral Homotopy Continuation Method for Polynomial Systems
 Computing
, 2003
"... PHoM is a software package in C++ for finding all isolated solutions of polynomial systems using a polyhedral homotopy continuation method. Among three modules constituting the package, the first module StartSystem constructs a family of polyhedrallinear homotopy functions, based on the polyhedral ..."
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Cited by 29 (11 self)
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PHoM is a software package in C++ for finding all isolated solutions of polynomial systems using a polyhedral homotopy continuation method. Among three modules constituting the package, the first module StartSystem constructs a family of polyhedrallinear homotopy functions, based on the polyhedral homotopy theory, from input data for a given system of polynomial equations f (x) = 0. The second module CMPSc traces the solution curves of the homotopy equations to compute all isolated solutions of f (x) = 0. The third module Verify checks whether all isolated solutions of f (x) = 0 have been approximated correctly. We describe numerical methods used in each module and the usage of the package. Numerical results to demonstrate the performance of PHoM include some large polynomial systems that have not been solved previously.
"One sugar cube, please" or Selection strategies in the Buchberger algorithm
 Proceedings of the ISSAC'91, ACM Press
, 1991
"... In this paper we describe some experimental findings on selection strategies for Gröbner basis computation with the Buchberger algorithm. In particular, the results suggest that the "sugar flavor" of the "normal selection", implemented first in CoCoA, then in AlPI, and now in SCR ..."
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Cited by 24 (2 self)
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In this paper we describe some experimental findings on selection strategies for Gröbner basis computation with the Buchberger algorithm. In particular, the results suggest that the "sugar flavor" of the "normal selection", implemented first in CoCoA, then in AlPI, and now in SCRATCHPADII, is the best choice for a selection strategy. It has to be combined with the "straightforward" simplification strategy and with a special form of the GebauerMöller criteria to obtain the best results. The idea of the "sugar flavor" is the following: the Buchberger algorithm for homogeneous ideals, with degreecompatible term ordering and normal selection strategy, usually works fine. Homogenizing the basis of the ideal is good for the strategy, but bad for the basis to be computed. The sugar flavor computes, for every polynomial in the course of the algorithm, "the degree that it would have if computed with the homogeneous algorithm", and uses this phantom degree (the sugar) only for the selection strategy. We have tested several examples with different selection strategies, and the sugar flavor has proved to be always the best choice or very near to it. The comparison between the different variants of the sugar flavor has been made, but the results are up to now inconclusive. We include a complete deterministic description of the Buchberger algorithm as it was used in our experiments.
Parallelizing Algorithms for Symbolic Computation using MAPLE
 IN FOURTH ACM SIGPLAN SYMPOSIUM ON PRINCIPLES AND PRACTICE OF PARALLEL PROGRAMMING
, 1993
"... MAPLE (speak: parallel Maple) is a portable system for parallel symbolic computation. The system is built as an interface between the parallel declarative programming language Strand and the sequential computer algebra system Maple, thus providing the elegance of Strand and the power of the exis ..."
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Cited by 20 (1 self)
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MAPLE (speak: parallel Maple) is a portable system for parallel symbolic computation. The system is built as an interface between the parallel declarative programming language Strand and the sequential computer algebra system Maple, thus providing the elegance of Strand and the power of the existing sequential algorithms in Maple. The implementation of different parallel programming paradigms shows that it is fairly easy to parallelize even complex algebraic algorithms using this system. Sample applications (among them algorithms solving multivariate nonlinear equation systems) are implemented on various parallel architectures. For example a straightforward parallelization of the complex and important problem of real root isolation has been parallelized using a generic Strand program of fewer than 20 lines of code and a slight modification of 5 lines in the original sequential Maple source. Even with such a simple modification we gained a speedup of 5 times, that is better than thos...
Monomial Representations for Gröbner Bases Computations
 PROCEEDINGS OF ISSAC 1998, ACM PRESS
, 1998
"... Monomial representations and operations for Gröbner bases computations are investigated from an implementation point of view. The technique of vectorized monomial operations is introduced and it is shown how it expedites computations of Gröbner bases. Furthermore, a rankbased monomial representatio ..."
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Cited by 15 (1 self)
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Monomial representations and operations for Gröbner bases computations are investigated from an implementation point of view. The technique of vectorized monomial operations is introduced and it is shown how it expedites computations of Gröbner bases. Furthermore, a rankbased monomial representation and comparison technique is examined and it is concluded that this technique does not yield an additional speedup over vectorized comparisons. Extensive benchmark tests with the Computer Algebra System Singular are used to evaluate these concepts.
StrategyAccurate Parallel Buchberger Algorithms
, 1996
"... this paper we describe two parallel formulations of Buchberger algorithm, one for y ..."
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Cited by 13 (0 self)
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this paper we describe two parallel formulations of Buchberger algorithm, one for y
The SymbolicData Project: Towards an Electronic Repository of Tools and Data for Benchmarks of Computer Algebra Software
, 2000
"... The SymbolicData project has the following three main goals: 1. to systematically collect existing symbolic computation benchmark data and to produce tools to extend and maintain this collection; 2. to design and implement concepts for trusted benchmarks computations on the collected data; and 3. to ..."
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Cited by 10 (2 self)
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The SymbolicData project has the following three main goals: 1. to systematically collect existing symbolic computation benchmark data and to produce tools to extend and maintain this collection; 2. to design and implement concepts for trusted benchmarks computations on the collected data; and 3. to provide tools for data access/selection/transformation using di erent technologies. SymbolicData has developed from a \grass root initiative" of a small number of people to a stage where it should be presented to, and evaluated and used by a wider community. In this paper we report about the current state of the project, i.e., we describe the main design principles and tools which were developed to realize our goals. 1