Course-PM

FKA122 / FIM540 Computational physics lp2 HT24 (7.5 hp)

Course is offered by the department of Physics

Contact details

Examiner: Julia Wiktor (julia.wiktor@chalmers.se)

Lecturer: Julia Wiktor (julia.wiktor@chalmers.se)

Lecturer: Matthias Geilhufe (matthias.geilhufe@chalmers.se)

Assistant: Lucas Svensson (lucas.svensson@chalmers.se)

Assistant: Viktor Martvall (vikmar@chalmers.se)

Assistant: Tobias Hainer (tobias.hainer@chalmers.se)

Assistant: Tobias Möslinger (tobias.moeslinger@chalmers.se)

Course purpose

The aim of the course is to refine computational skills by providing direct experience in using a computer to solve problems in physics. Numerical techniques are introduced and applied in a broad spectrum of various physical problems. The course is designed to develop an understanding of modeling physical systems using different numerical techniques.

Course specific prerequisites

Basic programming knowledge and experience, preferably in python and C. Basic undergraduate physics. You could benefit from taking the course TIF035 Statistical physics in parallel.

Schedule

TimeEdit

Course literature

Lecture notes will be made available.

Recommended but not required additional literature.
For numerical methods:
Willliam H. Press et al.,
"Numerical Recipes; The Art of Scientific Computing",
(3rd edition, Cambridge University Press, 2007),
For more experienced students:
J.M.Thijssen,
"Computational Physics",
(2nd edition, Cambridge University Press, 2007).

Course design

The different numerical techniques and the physical problems are presented in a series of lectures. The most important part in the course is the students own activity in applying the methods and solving a set of exercises and homework assignments. Scheduled computer laboratory sessions are provided, with instructors available for consultation. The programming language C is being used in the course.

Learning objectives and syllabus

Learning objectives:

• use C to solve numerical problems.
• explain and numerically apply the basic idea behind the molecular dynamics simulation method.
• explain how random numbers can be used to treat static and dynamic phenomena and numerically apply the methodology.
• explain and numerically apply the Metropolis Monte Carlo method.
• integrate knowledge in modeling physical systems with various numerical techniques.
• write well-structured technical reports where computational results are presented and explained.
• communicate results and conclusions in a clear way.

Link to the syllabus on Studieportalen.

Study plan

Examination form

The examination is based on exercises and homework assignments.