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##### SALSA - 2011

Project Team Salsa

Overall Objectives
Application Domains
Software
Contracts and Grants with Industry
Partnerships and Cooperations
Bibliography

Project Team Salsa

Overall Objectives
Application Domains
Software
Contracts and Grants with Industry
Partnerships and Cooperations
Bibliography

## Section: Scientific Foundations

### Introduction

For polynomial system solving, the mathematical specification of the result of a computation, in particular when the number of solutions is infinite, is itself a difficult problem [1] , [58] , [57] . Sorting the most frequently asked questions appearing in the applications, one distinguishes several classes of problems which are different either by their mathematical structure or by the significance that one can give to the word "solving".

Some of the following questions have a different meaning in the real case or in the complex case, others are posed only in the real case  :

• zero-dimensional systems (with a finite number of complex solutions - which include the particular case of univariate polynomials); The questions in general are well defined (numerical approximation, number of solutions, etc) and the handled mathematical objects are relatively simple and well-known;

• parametric systems: They are generally zero-dimensional for almost all the parameters' values. The goal is to characterize the solutions of the system (number of real solutions, existence of a parameterization, etc.) with respect to parameters' values.

• positive dimensional systems: For a direct application, the first question is the existence of zeros of a particular type (for example real, real positive, in a finite field). The resolution of such systems can be considered as a black box for the study of more general problems (semi-algebraic sets for example) and information to be extracted is generally the computation of a point per connected component in the real case.

• constructible and semi-algebraic sets: As opposed to what occurs numerically, the addition of constraints or inequalities complicates the problem. Even if semi-algebraic sets represent the basic object of the real geometry, their automatic "and effective study" remains a major challenge. To date, the state of the art is poor since only two classes of methods are existing :

• the Cylindrical Algebraic Decomposition which basically computes a partition of the ambient space in cells where the signs of a given set of polynomials are constant;

• deformations based methods that turn the problem into solving algebraic varieties.

The first solution is limited in terms of performances (maximum 3 or 4 variables) because of a recursive treatment variable by variable, the second also because of the use of a sophisticated arithmetic (formal infinitesimals).

• quantified formulas; deciding efficiently if a first order formula is valid or not is certainly one of the greatest challenges in "effective" real algebraic geometry. However this problem is relatively well encircled since it can always be rewritten as the conjunction of (supposed to be) simpler problems like the computation of a point per connected component of a semi-algebraic set.

As explained in some parts of this document, the iniquity of the studied mathematical objects does not imply the uncut of the related algorithms. The priorities we put on our algorithmic work are generally dictated by the applications. Thus, above items naturally structure the algorithmic part of our research topics.

For each of these goals, our work is to design the most efficient possible algorithms: there is thus a strong correlation between implementations and applications, but a significant part of the work is dedicated to the identification of black-box allowing a modular approach of the problems. For example, the resolution of the zero-dimensional systems is a prerequisite for the algorithms treating of parametric or positive dimensional systems.

An essential class of black-box developed in the project does not appear directly in the absolute objectives counted above : the "algebraic or complex" resolutions. They are mostly reformulations, more algorithmically usable, of the studied systems. One distinguishes two categories of complementary objects :

• ideals representations: From a computational point of view these are the structures which are used in the first steps;

• varieties representations: The algebraic variety, or more generally the constructible or semi-algebraic set is the studied object.

To give a simple example, in ${ℂ}^{2}$ the variety $\left\{\left(0,0\right)\right\}$ can be seen like the zeros set of more or less complicated ideals (for example, ideal($X,Y$), ideal(${X}^{2},Y$), ideal(${X}^{2},X,Y,{Y}^{3}$), etc). The entry which is given to us is a system of equations, i.e.  an ideal. It is essential, in many cases, to understand the structure of this object to be able to correctly treat the degenerated cases. A striking example is certainly the study of the singularities. To take again the preceding example, the variety is not singular, but this cannot be detected by the blind application of the Jacobian criterion (one could wrongfully think that all the points are singular, contradicting, for example, Sard's lemma).

The basic tools that we develop and use to understand in an automatic way the algebraic and geometrical structures are on the one hand Gröbner bases (the most known object used to represent an ideal without loss of information) and on the other hand triangular sets (effective way to represent the varieties).