Simulation Tools

This module will cover selected methods of numerical physics with applications relevant to the Fundamental Physics track. After a review of programming with Python 3, numerical algorithms for solving nonlinear equations, ordinary differential equations and systems of linear equations will be studied. A major part of the module will concern numerical linear algebra and its applications in physics and numerical analysis. Finally, an introduction to systems of formal calculus is included.

Deepening of skills in programming and numerical physics. Understanding of how the chosen algorithms work and their limitations; knowing how to implement them in order to solve physics problems numerically; critical appraisal of the results.

Procedural programming (ideally with Python). Knowledge of physics, mathematics and computer science at the L2 level.

Recommended Prerequisites*: Good practice of Python 3 and basic skills in scientific programming, "Physics on a computer" from L2 or equivalent.

CCI

• Scientific programming with Python 3 : Review and refinements
• Search for zeros of functions
• Numerical solution of ordinary differential equations
• Matrix calculation with NumPy
• Methods of numerical linear algebra: Systems of linear equations, matrix decompositions, diagonalization
• Applications: Interpolation, fitting/regression, discretization of differential operators, optimization
• Introduction to symbolic computation

CM : 12 h

TP : 15 h