FY820: Computational statistical physics
If there are fewer than 12 students enrolled, the course may. be held with another teaching form.
Cancelled spring 2019
computational techniques to investigate statistical mechanical models.
This is important to describe physical problem and to solve practical
problems of engineering relevance.
The course builds on the knowledge
acquired in the courses FY509 ( or FY523 and FY524) and FY802, and provides a foundation for
thesis projects in statistical physics of complex systems.
In relation to the competence profile of the degree it is the explicit focus of the course to:
- Give the competence to model certain physical phenomena.
- Give programming skills.
- Give knowledge and understanding of the phenomenology of complex systems.
Expected learning outcome
The learning objectives of the course is that the student demonstrates the ability to:
- Use and modify other’s computer codes and write own codes.
- Use statistics to test model hypotheses.
- Visualize data.
The following main topics are contained in the course:
- Kinetic Monte Carlo methods.
- Molecular Dynamics.
Exam element a)
Oral exam based on written report
To be announced during the course
Indicative number of lessons
- project work 30. Students work in small groups. The final report describes the result of their work.
- Report writing 6. The students can get feed-back and guidance.