Option Co-ordinator:
François Alouges
Mail: francois.alouges@polytechnique.edu

Option Director:
Grégoire Allaire
Mail: gregoire.allaire@polytechnique.edu

Applied Mathematics Department Secretary:
Tel: 01 69 33 46 01.
Fax: 01 69 33 46 46.
Mail: departement@cmapx.polytechnique.fr

Scientific computing is the art of the engineer devoted to producing numerical simulations based on a scientific analysis and with computers. Most of problems that can be formalised with mathematical equations lead to problems too complicated to be solved with elementary methods or with methods of formal calculus. The objective of scientific computing is to propose approximate numerical solutions for problems that can be modelised with a mathematical equation. The development of scientific computing is related to the increasing of computer power. It is an applied science in continuous evolution.

The industries that use and develop scientific computing are first the main partners of State technical administrations in charge of the conception and development of complex systems: space and aeronautics, nuclear, automotive industry, petroleum industry, civil engineering.
Reduced to amount development and the certification of complex systems only few years ago, the numerical simulation allows the reduction of important development times on conception cycles and the production of more sophisticated products.

The option "scientific computing" is devoted to students needing training in scientific computing, either for the analysis of an industrial problem, or the initiation to scientific research, whatever can be the future choice in terms of career orientation. For those who wish to enter the Master Program "Mathematical Modeling" in Applied Mathematics of the Ecole Polytechnique (co-organised with Paris 6 University), the training period can be an important first step.

Examples of subjects studied in recent years

Adaptive and multi-scales methods.
Assessment and design of optical fiber systems.
Inverse problem in electromagnetism.
Aeroelastic modelling.

Requirements : Some knowledge of numerical analysis and/or optimization.

Evaluation mechanism : Written report and oral defense

Last Modification : Monday 8 April 2013