Please note that this course description is preliminary. The final course description will be released in the Summer of 2020
Knowledge of statistical physics is expected, as well as basic programming skills.
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, we focus on one particular system as example: a large number of Argon atoms in a container modelled by by a Lennard-Jones system of particles.
To do so, you write a molecular dynamics simulation of Argon atoms and investigate the physical properties of the three different phases (gas, liquid, solid).
During the course you learn step by step how to write this complex code in a mix of lectures and computer lab sessions.
Note: The course is also offered in a long version (6 EC). The long version has two additional projects and is recommended for students who expect to go into performing computational research projects in the future whereas the short version (3 EC) is recommended for all students.
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 a particular topic in computational physics and present the findings in a scientifc report
Generic skills (Soft Skills)
You will be able to:
master a new field of study in computational physics within a given time period
write structured essays on computational projects
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.
The students (working in pairs) produce a report which will be graded.
Course material & assignments are placed on Blackboard.
To have access to Blackboard you need a ULCN-account.Blackboard UL
A script and links to papers will be provided.
Lecturers Prof.dr.Helmut Schiessel