BlockKrylov techniques in the context of sparseFGLM algorithms
Abstract
Consider a zerodimensional ideal $I$ in $\mathbb{K}[X_1,\dots,X_n]$. Inspired by Faugère and Mou's Sparse FGLM algorithm, we use Krylov sequences based on multiplication matrices of $I$ in order to compute a description of its zero set by means of univariate polynomials. Steel recently showed how to use Coppersmith's blockWiedemann algorithm in this context; he describes an algorithm that can be easily parallelized, but only computes parts of the output in this manner. Using generating series expressions going back to work of Bostan, Salvy, and Schost, we show how to compute the entire output for a small overhead, without making any assumption on the ideal $I$ other than it having dimension zero. We then propose a refinement of this idea that partially avoids the introduction of a generic linear form. We comment on experimental results obtained by an implementation based on the C++ libraries Eigen, LinBox and NTL.
 Publication:

arXiv eprints
 Pub Date:
 December 2017
 arXiv:
 arXiv:1712.04177
 Bibcode:
 2017arXiv171204177H
 Keywords:

 Computer Science  Symbolic Computation
 EPrint:
 32 pages, 7 algorithms, 2 tables