Simulation tools

This module covers selected methods of numerical physics with applications relevant to the Fundamental Physics pathway. 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, there will be an introduction to formal calculus systems.

Deepening skills in programming and numerical physics. Understand how chosen algorithms work and their limitations; implement them to solve physics problems numerically; critically appraise results.

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

Recommended prerequisites* : Good knowledge 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
• Finding the 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, adjustment/regression, discretization of differential operators, optimization
• Introduction to symbolic calculation

CM : 12 h

Practical work: 15 h