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Institutionernas kurser för doktorander


Kursplan för

TIF035 - Computational materials physics
Kursplanen fastställd 2012-02-22 av programansvarig (eller motsvarande)
Ägare: MPAPP
7,5 Poäng
Betygskala: TH - Fem, Fyra, Tre, Underkänt
Utbildningsnivå: Avancerad nivå
Huvudområde: Teknisk fysik
Institution: 16 - FYSIK

Undervisningsspråk: Engelska
Sökbar för utbytesstudenter
Blockschema: B

Modul   Poängfördelning   Tentamensdatum
Lp1 Lp2 Lp3 Lp4 Sommarkurs Ej Lp
0105 Inlämningsuppgift 7,5 hp Betygskala: TH   7,5 hp    

I program



Docent  Anders Hellman




För kurser inom Chalmers utbildningsprogram gäller samma behörighetskrav som till de(t) program kursen ingår i.

Kursspecifika förkunskaper

Basic undergraduate physics and mathematics, computing and numerical analysis. Computing and numerical methods at the level of FKA121 Computational Physics is recommended. It is an advantage to have some knowledge of quantum mechanics, condensed matter physics and/or statistical physics at the advanced undergraduate level.


The aim of the course is to outline modern computational methods and schemes providing challenges for the future and to develop practical experience in carrying out high performance computing. The course introduces numerical methods and new areas of physics that can be studied with these methods. It gives examples of how physics can be applied in a much broader context than usually discussed in the traditional physics undergraduate curriculum and it teaches structured programming in the context of doing science.

Lärandemål (efter fullgjord kurs ska studenten kunna)

After completion of this course, the student should be able to

  • use the objected-oriented scripting language Python to steer and organize large scale computing tasks and to provide simple visualization.

  • efficiently use MATLAB and/or C/Fortran to solve numerical problems.

  • know some of the major open-source implementations of molecular dynamics (MD) simulations and the density functional theory (DFT) for the electronic structure problem.

  • comprehend and apply the MD simulation technique.

  • synthesize DFT concepts through experience in writing codes for simple systems.

  • comprehend and analyze DFT methods and concepts.

  • integrate knowledge in modeling physical systems with various numerical techniques.

  • write technical reports where computational results are presented and explained.

  • communicate results and conclusions in a clear way.
  • Innehåll

  • introductory Python

  • the molecular dynamics simulation technique for many-particle systems

  • simplified tight-binding methods and model potentials

  • basics of density functional theory for the electronic structure problem

  • plane-wave and localized orbitals basis set methods

  • steering and combining results from various programming codes
  • Organisation

    Basic theory and methods are covered by a series of lectures. The students get training by applying the theory and methods in exercises and homework problems. An important part consists of practical training of carrying out large scale computations using primarily preexisting molecular dynamics and/or electronic structure codes. This training includes also experience of using Python, an object-oriented scripting languages, as a common platform to steer and analyze and combine results from various codes.


    Lecture notes will be made available.
    Course book:
    "Computational Physics",
    (2nd edition, Cambridge University Press, 2007).
    Recommended additional material for numerical methods:
    Willliam H. Press et al.,
    "Numerical Recipes; The Art of Scientific Computing",
    (3rd edition, Cambridge University Press, 2007),


    The examination will be individualized and adjusted to previous background and interests. In general the examination consists of coding assignments (graded), computing-lab assignments (pass or fail), and more individualized projects with a report and a presentation (graded).

    Sidansvarig Publicerad: må 13 jul 2020.