Description

The aim of this first-semester course is to review the classical techniques of computational physics, using the Python language. After a brief review of the basics of the language and the tools for data analysis and representation, we'll study Monte-Carlo techniques, classical methods of interpolation, integration and differentiation, solutions of systems of ordinary differential equations and solutions of systems of partial differential equations. These notions will serve as a foundation for the concepts that will be further discussed during the second semester course.  The lectures are accompanied by exercise sessions on machines.

Compétences visées

•    Applying knowledge in physics;

•    Apply methods from mathematics and digital technology;

•    Produce a critical analysis, with hindsight and perspective;

•    Develop and manage an experimental project, including digital aspects;

•    Operate an experimental device, including digital aspects, from use to data analysis;

•    Communicate in writing and orally, including in English.

Syllabus

• Basic Python and Data representation
• Monte-Carlo and Random Processes
• Integration and differentiation
• Ordinary Differential Equations
• Partial Differential Equations

Contacts

Responsable(s) de l'enseignement

• Dominique Aubert

MCC

Les épreuves indiquées respectent et appliquent le règlement de votre formation, disponible dans l'onglet Documents de la description de la formation.

Régime d'évaluation

CT (Contrôle terminal, mêlé de contrôle continu)

Coefficient

1.0

Évaluation initiale / Session principale - Épreuves

Seconde chance / Session de rattrapage - Épreuves