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Graduate courses

Departments' graduate courses for PhD-students.


Syllabus for

Academic year
FKA121 - Computational physics
Syllabus adopted 2015-02-20 by Head of Programme (or corresponding)
Owner: MPAPP
7,5 Credits
Grading: TH - Five, Four, Three, Not passed
Education cycle: Second-cycle
Major subject: Engineering Physics
Department: 16 - PHYSICS

Teaching language: English
Open for exchange students
Block schedule: D

Course module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 Summer course No Sp
0199 Examination 7,5 c Grading: TH   7,5 c   12 Jan 2016 pm H,  Contact examiner,  Contact examiner

In programs

MPAPP APPLIED PHYSICS, MSC PROGR, Year 1 (compulsory elective)


Professor  Göran Wahnström


In order to be eligible for a second cycle course the applicant needs to fulfil the general and specific entry requirements of the programme that owns the course. (If the second cycle course is owned by a first cycle programme, second cycle entry requirements apply.)
Exemption from the eligibility requirement: Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling these requirements.

Course specific prerequisites

Some programming knowledge and experience. Basic undergraduate physics.


The aim of the course is to refine computational skills by providing direct experience in using a computer to solve problems in physics. A large number of different numerical techniques is 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.

Learning outcomes (after completion of the course the student should be able to)

  • use C to solve numerical problems and to visualize computational results.

  • explain and numerically apply the basic idea behind the molecular dynamics simulation method.

  • explain how random numbers can be used to treat kinetic and dynamic phenomena and numerically apply the methodology.

  • explain and numerically apply the basic idea behind 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.
  • Content

  • the programming language C

  • ordinary differential equations, molecular dynamics simulation

  • random numbers, random processes, Brownian dynamics

  • discrete and fast Fourier transforms, power spectrum analysis

  • Monte Carlo integration, Metropolis Monte Carlo, variational Monte Carlo

  • Organisation

    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 and partly MATLAB are being used in the course.


    Lecture notes will be made available. Recommended additional literature. For MATLAB:
    Eva Pärt-Enander and Anders Sjöberg,
    "The MATLAB 5 Handbook"
    (Addison-Wesley, 1999).
    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:
    "Computational Physics",
    (2nd edition, Cambridge University Press, 2007).


    The examination will be based on exercises and homework assignments and a final exam.

    Page manager Published: Thu 04 Feb 2021.