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, 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 the 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; choice from three possible subject: (a) Ising model, (b) variational quantum Monte Carlo of the Helium atom or (c) polymer statistics (Rosenbluth algorithm)
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 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.
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
Generic skills (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
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 two reports (project 1 and 2). 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.
Course material & assignments are placed on Blackboard.
To have access to Blackboard you need a ULCN-account.Blackboard UL
Prof.dr.Helmut Schiessel Dr. Michael Wimmer