Syllabus for Computational Physics

Beräkningsfysik

Syllabus

  • 5 credits
  • Course code: 1FA573
  • Education cycle: Second cycle
  • Main field(s) of study and in-depth level: Physics A1N, Computational Science A1N

    Explanation of codes

    The code indicates the education cycle and in-depth level of the course in relation to other courses within the same main field of study according to the requirements for general degrees:

    First cycle
    G1N: has only upper-secondary level entry requirements
    G1F: has less than 60 credits in first-cycle course/s as entry requirements
    G1E: contains specially designed degree project for Higher Education Diploma
    G2F: has at least 60 credits in first-cycle course/s as entry requirements
    G2E: has at least 60 credits in first-cycle course/s as entry requirements, contains degree project for Bachelor of Arts/Bachelor of Science
    GXX: in-depth level of the course cannot be classified.

    Second cycle
    A1N: has only first-cycle course/s as entry requirements
    A1F: has second-cycle course/s as entry requirements
    A1E: contains degree project for Master of Arts/Master of Science (60 credits)
    A2E: contains degree project for Master of Arts/Master of Science (120 credits)
    AXX: in-depth level of the course cannot be classified.

  • Grading system: Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
  • Established: 2010-03-18
  • Established by:
  • Revised: 2018-08-30
  • Revised by: The Faculty Board of Science and Technology
  • Applies from: week 30, 2019
  • Entry requirements: 120 credits with Scientific Computing I and II and Quantum Physics or equivalent.
  • Responsible department: Department of Physics and Astronomy

Learning outcomes

On completion of the course, the student should be able to:

  • account for how numerical methods can be developed
  • apply his practical experiences on physical problems
  • account for various scientific problems the different methods can be used to solve
  • account for the role as computer models and simulations play at studies of physical systems within material technology

Content

Overview and advanced study of numerical methods. The course is focused against practical aspects of computational physics and contain set-up and writing of software to solve physical problems particularly within molecular dynamics, statistical physics and material physics. Different aspects of molecular dynamics simulations, for example the precision of pair-potentials and the length of time steps, will be highlighted. Different aspects of stochastic and deterministic simulations by Monte Carlo simulations and Langevin methods will be discussed. Numerical aspects of electronic structure calculations with tight-binding approximation will be covered along with more sophisticated Hartree-Fock and Density Functional theory.

Instruction

Strong emphasis on computer exercises and project work; in addition teaching sessions and seminars.

Assessment

Computer exercises and project work. 
 
If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.

Reading list

Reading list

Applies from: week 30, 2019

  • Koonin, Steven E. Computational physics

    Redwood City, Ca.: Addison-Wesley, cop. 1986

    Find in the library