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Computational Physics (3 EC)

Vak 2018-2019

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, we focus on one particular system as example: a large number of Argon atoms in a container as studied 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 as well as 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.

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 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

Timetable

Physics Schedule

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 a report which will be graded.

Blackboard

Course material & assignments are placed on Blackboard.
To have access to Blackboard you need a ULCN-account.Blackboard UL

Reading list

see Blackboard

Contact information

Lecturers
Prof.dr.Helmut Schiessel
Dr. Michael Wimmer