13,588 research outputs found
Sparse Gr\"obner Bases: the Unmixed Case
Toric (or sparse) elimination theory is a framework developped during the
last decades to exploit monomial structures in systems of Laurent polynomials.
Roughly speaking, this amounts to computing in a \emph{semigroup algebra},
\emph{i.e.} an algebra generated by a subset of Laurent monomials. In order to
solve symbolically sparse systems, we introduce \emph{sparse Gr\"obner bases},
an analog of classical Gr\"obner bases for semigroup algebras, and we propose
sparse variants of the and FGLM algorithms to compute them. Our prototype
"proof-of-concept" implementation shows large speed-ups (more than 100 for some
examples) compared to optimized (classical) Gr\"obner bases software. Moreover,
in the case where the generating subset of monomials corresponds to the points
with integer coordinates in a normal lattice polytope and under regularity assumptions, we prove complexity bounds which depend
on the combinatorial properties of . These bounds yield new
estimates on the complexity of solving -dim systems where all polynomials
share the same Newton polytope (\emph{unmixed case}). For instance, we
generalize the bound on the maximal degree in a Gr\"obner
basis of a -dim. bilinear system with blocks of variables of sizes
to the multilinear case: . We also propose
a variant of Fr\"oberg's conjecture which allows us to estimate the complexity
of solving overdetermined sparse systems.Comment: 20 pages, Corollary 6.1 has been corrected, ISSAC 2014, Kobe : Japan
(2014
New Structured Matrix Methods for Real and Complex Polynomial Root-finding
We combine the known methods for univariate polynomial root-finding and for
computations in the Frobenius matrix algebra with our novel techniques to
advance numerical solution of a univariate polynomial equation, and in
particular numerical approximation of the real roots of a polynomial. Our
analysis and experiments show efficiency of the resulting algorithms.Comment: 18 page
Matrix-F5 algorithms and tropical Gr\"obner bases computation
Let be a field equipped with a valuation. Tropical varieties over can
be defined with a theory of Gr\"obner bases taking into account the valuation
of . Because of the use of the valuation, this theory is promising for
stable computations over polynomial rings over a -adic fields.We design a
strategy to compute such tropical Gr\"obner bases by adapting the Matrix-F5
algorithm. Two variants of the Matrix-F5 algorithm, depending on how the
Macaulay matrices are built, are available to tropical computation with
respective modifications. The former is more numerically stable while the
latter is faster.Our study is performed both over any exact field with
valuation and some inexact fields like or In the latter case, we track the loss in precision,
and show that the numerical stability can compare very favorably to the case of
classical Gr\"obner bases when the valuation is non-trivial. Numerical examples
are provided
Computing Minimal Polynomials of Matrices
We present and analyse a Monte-Carlo algorithm to compute the minimal
polynomial of an matrix over a finite field that requires
field operations and O(n) random vectors, and is well suited for successful
practical implementation. The algorithm, and its complexity analysis, use
standard algorithms for polynomial and matrix operations. We compare features
of the algorithm with several other algorithms in the literature. In addition
we present a deterministic verification procedure which is similarly efficient
in most cases but has a worst-case complexity of . Finally, we report
the results of practical experiments with an implementation of our algorithms
in comparison with the current algorithms in the {\sf GAP} library
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