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 $F_5$ 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 $\mathcal P\subset\mathbb R^n$ and under regularity assumptions, we prove complexity bounds which depend on the combinatorial properties of $\mathcal P$. These bounds yield new estimates on the complexity of solving $0$-dim systems where all polynomials share the same Newton polytope (\emph{unmixed case}). For instance, we generalize the bound $\min(n_1,n_2)+1$ on the maximal degree in a Gr\"obner basis of a $0$-dim. bilinear system with blocks of variables of sizes $(n_1,n_2)$ to the multilinear case: $\sum n_i - \max(n_i)+1$. 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

Gröbner Bases of Ideals Invariant under a Commutative Group: the Non-Modular Case

International audienceWe propose efficient algorithms to compute the Gröbner basis of an ideal $I\subset k[x_1,\dots,x_n]$ globally invariant under the action of a commutative matrix group $G$, in the non-modular case (where $char(k)$ doesn't divide $|G|$). The idea is to simultaneously diagonalize the matrices in $G$, and apply a linear change of variables on $I$ corresponding to the base-change matrix of this diagonalization. We can now suppose that the matrices acting on $I$ are diagonal. This action induces a grading on the ring $R=k[x_1,\dots,x_n]$, compatible with the degree, indexed by a group related to $G$, that we call $G$-degree. The next step is the observation that this grading is maintained during a Gröbner basis computation or even a change of ordering, which allows us to split the Macaulay matrices into $|G|$ submatrices of roughly the same size. In the same way, we are able to split the canonical basis of $R/I$ (the staircase) if $I$ is a zero-dimensional ideal. Therefore, we derive \emph{abelian} versions of the classical algorithms $F_4$, $F_5$ or FGLM. Moreover, this new variant of $F_4/F_5$ allows complete parallelization of the linear algebra steps, which has been successfully implemented. On instances coming from applications (NTRU crypto-system or the Cyclic-n problem), a speed-up of more than 400 can be obtained. For example, a Gröbner basis of the Cyclic-11 problem can be solved in less than 8 hours with this variant of $F_4$. Moreover, using this method, we can identify new classes of polynomial systems that can be solved in polynomial time

Résolution de systèmes polynomiaux structurés de dimension zéro.

Multivariate polynomial systems arise naturally in many scientific fields. These systems coming from applications often carry a specific algebraic structure.A classical method for solving polynomial systems isbased on the computation of a Gr\"obner basis of the ideal associatedto the system.This thesis presents new tools for solving suchstructured systems, where the structure is induced by the action of a particular group or a monomial structure, which include multihomogeneous or quasihomogeneous systems.On the one hand, this thesis proposes new algorithmsusing these algebraic structures to improve the efficiency of solving suchsystems (invariant under the action of a group or having a support in a particular set of monomials). These techniques allow to solve a problem arising in physics for instances out of reach until now.On the other hand, these tools improve the complexity bounds for solving several families of structured polynomial systems (systems globally invariant under the action of an abelian group or with their support in the same polytope). This allows in particular to extend known results on bilinear systems to general mutlihomogeneous systems.Les systèmes polynomiaux à plusieurs variables apparaissent naturellement dans de nombreux domaines scientifiques. Ces systèmes issus d'applications possèdent une structure algébrique spécifique. Une méthode classique pour résoudre des systèmes polynomiaux repose sur le calcul d'une base de Gröbner de l'idéal associé au système. Cette thèse présente de nouveaux outils pour la résolution de tels systèmes structurés, lorsque la structure est induite par l'action d'un groupe ou une structure monomiale particulière, qui englobent les systèmes multi-homogènes ou quasi-homogènes. D'une part, cette thèse propose de nouveaux algorithmes qui exploitent ces structures algébriques pour améliorer l'efficacité de la résolution de systèmes (systèmes invariant sous l'action d'un groupe ou à support dans un ensemble de monômes particuliers). Ces techniques permettent notamment de résoudre un problème issu de la physique pour des instances hors de portée jusqu'à présent. D'autre part, ces outils permettent d'améliorer les bornes de complexité de résolution de plusieurs familles de systèmes polynomiaux structurés (systèmes globalement invariant sous l'action d'un groupe abélien, individuellement invariant sous l'action d'un groupe quelconque, ou ayant leur support dans un même polytope). Ceci permet en particulier d'étendre des résultats connus sur les systèmes bilinéaires aux systèmes mutli-homogènes généraux

Solving zero-dimensional structured polynomial systems

Les systèmes polynomiaux à plusieurs variables apparaissent naturellement dans de nombreux domaines scientifiques. Ces systèmes issus d'applications possèdent une structure algébrique spécifique. Une méthode classique pour résoudre des systèmes polynomiaux repose sur le calcul d'une base de Gröbner de l'idéal associé au système. Cette thèse présente de nouveaux outils pour la résolution de tels systèmes structurés, lorsque la structure est induite par l'action d'un groupe ou une structure monomiale particulière, qui englobent les systèmes multi-homogènes ou quasi-homogènes. D'une part, cette thèse propose de nouveaux algorithmes qui exploitent ces structures algébriques pour améliorer l'efficacité de la résolution de systèmes (systèmes invariant sous l'action d'un groupe ou à support dans un ensemble de monômes particuliers). Ces techniques permettent notamment de résoudre un problème issu de la physique pour des instances hors de portée jusqu'à présent. D'autre part, ces outils permettent d'améliorer les bornes de complexité de résolution de plusieurs familles de systèmes polynomiaux structurés (systèmes globalement invariant sous l'action d'un groupe abélien, individuellement invariant sous l'action d'un groupe quelconque, ou ayant leur support dans un même polytope). Ceci permet en particulier d'étendre des résultats connus sur les systèmes bilinéaires aux systèmes mutli-homogènes généraux.Multivariate polynomial systems arise naturally in many scientific fields. These systems coming from applications often carry a specific algebraic structure.A classical method for solving polynomial systems isbased on the computation of a Gr\"obner basis of the ideal associatedto the system.This thesis presents new tools for solving suchstructured systems, where the structure is induced by the action of a particular group or a monomial structure, which include multihomogeneous or quasihomogeneous systems.On the one hand, this thesis proposes new algorithmsusing these algebraic structures to improve the efficiency of solving suchsystems (invariant under the action of a group or having a support in a particular set of monomials). These techniques allow to solve a problem arising in physics for instances out of reach until now.On the other hand, these tools improve the complexity bounds for solving several families of structured polynomial systems (systems globally invariant under the action of an abelian group or with their support in the same polytope). This allows in particular to extend known results on bilinear systems to general mutlihomogeneous systems

Solving Polynomial Systems Globally Invariant Under an Action of the Symmetric Group and Application to the Equilibria of N vortices in the Plane

We propose an efficient algorithm to solve polynomial systems of which equations are globally invariant under an action of the symmetric group SN acting on the variable xi with σ(xi) = x σ(i) and the number of variables is a multiple of N. For instance, we can assume that swapping two variables (or two pairs of variables) in one equation gives rise to another equation of the system (perhaps changing the sign). The idea is to apply many times divided difference operators to the original system in order to obtain a new system of equations involving only the symmetric functions of a subset of the variables. The next step is to solve the system using Gröbner techniques; this is usually several order faster than computing the Gröbner basis of the original system since the number of solutions of the corresponding ideal, which is always finite has been divided by at least N!

Sparse Gröbner 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 semigroup algebra, i.e. an algebra generated by a subset of Laurent monomials. In order to solve symbolically sparse systems, we introduce sparse Gröbner bases, an analog of classical Gröbner bases for semigroup algebras, and we propose sparse variants of the F 5 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) Gröbner bases software. Moreover, in the case where the generating subset of monomials corresponds to the points with integer coordinates in a normal lattice polytope P ⊂ R n and under regularity assumptions, we prove complexity bounds which depend on the combinatorial properties of P. These bounds yield new estimates on the complexity of solving 0-dim systems where all polynomials share the same Newton polytope (unmixed case). For instance, we generalize the bound min(n 1 , n 2 ) + 1 on the maximal degree in a Gröbner basis of a 0-dim. bilinear system with blocks of variables of sizes (n 1 , n 2 ) to the multilinear case: n i − max(n i ) + 1. We also propose a variant of Fröberg's conjecture which allows us to estimate the complexity of solving overdetermined sparse systems