Section: New Results
Fundamental Algorithms and Structured Systems
Structured polynomial systems: the quasi-homogeneous case
Let
Structured polynomial systems: the determinantal case
In [13] , We study the complexity of solving
the generalized MinRank problem, i.e. computing the set of
points where the evaluation of a polynomial matrix has rank at most
On the Complexity of the Generalized MinRank Problem
In [13] we study the complexity of solving the generalized MinRank
problem, i.e. computing the set of points where the evaluation of
a polynomial matrix has rank at most
On the Complexity of Computing Gröbner Bases for Quasi-homogeneous Systems
Let
In [29] , we design strategies for computing
Gröbner bases for quasi-homogeneous systems by adapting existing
algorithms for homogeneous systems to the quasi-homogeneous case.
Overall, under genericity assumptions, we show that for a generic
zero-dimensional quasi-homogeneous system, the complexity of the
full strategy is polynomial in the weighted Bézout bound
We provide some experimental results based on generic systems as well as systems arising from a cryptography problem. They show that taking advantage of the quasi-homogeneous structure of the systems allow us to solve systems that were out of reach otherwise.
Gröbner bases of ideals invariant under a commutative group : the non-modular case
In [30] , we propose efficient algorithms to compute the Gröbner basis of an
ideal
Signature Rewriting in Gröbner Basis Computation
In [27] we introduce the RB algorithm for Gröbner basis computation, a simpler yet equivalent algorithm to F5GEN. RB contains the original unmodified F5 algorithm as a special case, so it is possible to study and understand F5 by considering the simpler RB. We present simple yet complete proofs of this fact and of F5's termination and correctness. RB is parametrized by a rewrite order and it contains many published algorithms as special cases, including SB. We prove that SB is the best possible instantiation of RB in the following sense. Let X be any instantiation of RB (such as F5). Then the S-pairs reduced by SB are always a subset of the S-pairs reduced by X and the basis computed by SB is always a subset of the basis computed by X.
An analysis of inhomogeneous signature-based Gröbner basis computations
In [8] we give an insight into the behaviour of signature-based Gröbner basis algorithms, like F5, G2V or SB, for inhomogeneous input. On the one hand, it seems that the restriction to sig-safe reductions puts a penalty on the performance. The lost connection between polynomial degree and signature degree can disallow lots of reductions and can lead to an overhead in the computations. On the other hand, the way critical pairs are sorted and corresponding s-polynomials are handled in signature- based algorithms is a very efficient one, strongly connected to sorting w.r.t. the well-known sugar degree of polynomials.
Improving incremental signature-based Gröbner basis algorithms
In [9] we describe a combination of ideas to improve incremental signature-based Gröbner basis algorithms having a big impact on their performance. Besides explaining how to combine already known optimizations to achieve more efficient algorithms, we show how to improve them even more. Although our idea has a positive affect on all kinds of incremental signature-based algorithms, the way this impact is achieved can be quite different. Based on the two best-known algorithms in this area, F5 and G2V, we explain our idea, both from a theoretical and a practical point of view.
A new algorithmic scheme for computing characteristic sets
Ritt-Wu's algorithm of characteristic sets is the most representative for triangularizing sets of multivariate polynomials. Pseudo-division is the main operation used in this algorithm. In [18] we present a new algorithmic scheme for computing generalized characteristic sets by introducing other admissible reductions than pseudo-division. A concrete subalgorithm is designed to triangularize polynomial sets using selected admissible reductions and several effective elimination strategies and to replace the algorithm of basic sets (used in Ritt-Wu's algorithm). The proposed algorithm has been implemented and experimental results show that it performs better than Ritt-Wu's algorithm in terms of computing time and simplicity of output for a number of non-trivial test examples