Section: Application Domains


Applications are fundamental for our research for several reasons.

The first one is that they are the only source of fair tests for the algorithms. In fact, the complexity of the solving process depends very irregularly of the problem itself. Therefore, random tests do not give a right idea of the practical behavior of a program, and the complexity analysis, when possible, does not necessarily provide realistic information.

A second reason is that, as quoted above, we need real world problems to determine which specifications of algorithms are really useful. Conversely, it is frequently by solving specific problems through ad hoc methods that we found new algorithms with general impact.

Finally, obtaining successes with problems which are intractable by the other known approaches is the best proof for the quality of our work.

On the other hand, there is a specific difficulty. The problems which may be solved with our methods may be formulated in many different ways, and their usual formulation is rarely well suited for polynomial system solving or for exact computations. Frequently, it is not even clear that the problem is purely algebraic, because researchers and engineers are used to formulate them in a differential way or to linearize them.

Therefore, our software may not be used as black boxes, and we have to understand the origin of the problem in order to translate it in a form which is well suited for our solvers.

It follows that many of our results, published or in preparation, are classified in scientific domains which are different from ours, like cryptography, error correcting codes, robotics, signal processing, statistics or biophysics.