Simulation Tools

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

Further development of programming and computational physics skills. Understanding how selected algorithms work and their limitations; knowing how to implement them to solve physics problems numerically; critical evaluation of results.

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

Recommended prerequisites*: Proficiency in Python 3 and basic skills in scientific programming; the “Computational Physics” course from the second year of undergraduate studies or equivalent.

CCI

• Scientific Programming with Python 3: Review and In-Depth Study
• Finding the Zeros of Functions
• Numerical Solution of Ordinary Differential Equations
• Matrix Calculations with NumPy
• Methods in Numerical Linear Algebra: Systems of Linear Equations, Matrix Decompositions, Diagonalization
• Applications: Interpolation, fitting/regression, discretization of differential operators, optimization
• Introduction to Symbolic Computation

CM: 12:00 p.m.

Practical Training: 3:00 p.m.