Computational Physics: Scientific Programming with Python

From numerical methods to exciting applications: Differential equations, eigenvalue problems, Monte Carlo methods & more

Created by: Dr. Börge Göbel
Scientist in Quantum Physics, Programmer and Instructor

What Will I Learn?

• Getting Started: A beginner-friendly crash course about NumPy, functions, loops, conditionals, lists, arrays & plots
• Numerical methods: Derivatives & integrals, differential equations & eigenvalue problems, interpolation & Monte Carlo methods
• Practice at Physics Problems: Moment of inertia, magnetic field of a wire, radioactive decay, harmonic oscillators, free fall, rolling balls
• Application to Advanced Problems: Chaotic systems, heat equation, 3-body problem, spaceship mission, coupled pendulums, magnetism, graphene & quantum physics

Requirements

• Software: None, I will show you how to install Python which is free.
• Programming: Previous experience is helpful but not required. We start with a 2h crash course.
• School mathematics: Knowing the basics about derivatives & integrals.
• Physics: Helpful but not required.

Target audience

• This course is for everyone: Python beginners & advanced programmers
• Everyone who likes physics and/or programming
• Science students, who want to explore a modern field of physics
• ... or who want to prepare for their computational physics exam 😉