## Admission Requirements

Knowledge of statistical physics is expected, as well as basic programming skills.

## Description

An important aspect of physics research is modeling: complex physical systems are simplified through a sequence of controlled approximations to a model that lends itself for computations, either analytic or by computer. In this course, the origin of a number of widely used models will be discussed. For instance, the liquid-gas transition of Argon can be studied by a Lennard-Jones system of particles. Insight into these models can be obtained through a number of ways, one of which is computer simulations. During this course, simulation methods of various models will be discussed in the lectures as well as in computer lab sessions.

There are three projects:

Project 1: Molecular dynamics simulation of Argon atoms

Project 2: Monte Carlo simulation of the two-dimensional Ising model

Project 3: Choice from a large number of possible projects (march of the penguins, computational astrophysics, lattice Boltzmann model, simulation of piano strings, self-organized criticality, pandemics and more)

Note: The course is also offered in a short version (3 EC). The long version (6 EC) is recommended for students who expect to go into performing computational research projects in the future whereas the short version (first project only) is recommended for all students.

## Course Objectives

After completion of this course, you will be able to:

write efficient and well-documented computer code and validate it,

assess the pros and cons of various computational methods,

investigate particular topics in computational physics and present the findings in scientifc reports and an oral presentation

## Soft Skills

You will be able to:

master a new field of study in computational physics within a given time period

present your findings to fellow students in a convincing and inspiring way

write structured essays on computational projects

## Timetable

See Brightspace.

## Mode of Instruction

One meeting per week, consisting of a mixture of lectures and supervised working on the projects. There will be online learning material as well.

The main emphasis of the course are the computational projects that are mostly performed outside the regular contact hours. In a hands-on approach, concepts are immediately applied to a concrete problem. The basic concepts taught in the lecture will be deepened by the students individually in setting up and running the simulations, and by independent literature study.

## Assessment method

The students (working in pairs) produce two reports (project 1 and 2) including the code and an analysis of the results.

Project 3 is chosen from a large set of possible problems and is presented as a talk.

The final grade is the average of the grades for these three projects.

### Brightspace

Course material & assignments are placed on Brightspace.

## Reading list

See Brightspace.

## Contact information

Lecturer Dr. Matthieu Schaller