FYS9460 – Disordered Systems and Percolation

Schedule, syllabus and examination date

Choose semester

Changes in the course due to coronavirus

Autumn 2020 the exams of most courses at the MN Faculty will be conducted as digital home exams or oral exams, using the normal grading scale. The semester page for your course will be updated with any changes in the form of examination.

See general guidelines for examination at the MN Faculty autumn 2020.

Course content

The course provides an introduction to methods and problems in modern statistical physics with emphasis on algorithmic and computational methods. The applications addressed and the computational methods introduced are relevant for material science, complex systems, chemistry, solid-state, molecular-, and bio-physics.

The course aims to build understanding for the macroscopic effects of microscopic interactions using numerical simulations of microscopic models coupled with a concurrent development of a relevant theoretical framework.

The course gives an introduction to the most central numerical methods in molecular dynamics modeling, algorithmic modeling of disordered systems, and to discrete models for fluids, including:

  • Atomic- and molecular dynamics for various ensembles, thermostats, fluctuations, and the coupling to continuum models
  • Random walks, renormalization, scaling, and fractals
  • Percolation: Finite-size scaling, Cluster- and subset geometry, Renormalization
  • Disordered systems: Diffusion, transport, and mechanical properties of disordered systems, Dynamic processes in disordered systems, and Growth processes far from equilibrium
  • Discrete models for fluids: Lattice-gas and lattice-Boltzman models, Dissipative Particle Dynamics, and Smoothed Particle Hydrodynamics

The extent of coverage of the various subjects depends on the choice of projects, and on student interests.

Learning outcome

The student learns a range of central algorithms and methods used in modern statistical physics. The course is project based. Through the projects the student will be exposed to problems from concurrent research. The aim is to be able to reproduce and potentially extend these results. The students learn to develop well-structured codes, to analyze complex systems, and to apply sound scientific principles when studying their own data. Examples and applications will mainly come from material science and the geo-sciences.

Admission to the course

PhD candidates from the University of Oslo should apply for classes and register for examinations through Studentweb.

If a course has limited intake capacity, priority will be given to PhD candidates who follow an individual education plan where this particular course is included. Some national researchers’ schools may have specific rules for ranking applicants for courses with limited intake capacity.

PhD candidates who have been admitted to another higher education institution must apply for a position as a visiting student within a given deadline.

FYS3400 – Condensed Matter Physics

FYS3150 – Computational Physics

Overlapping courses


The course extends over a full semester with 2 hours of lectures and 2 hours of colloquia per week. Compulsory theoretical and numerical assignments are included together with a written project report.


Written project report forms the basis of a final oral exam.

Grading scale

Grades are awarded on a pass/fail scale. Read more about the grading system.

Resit an examination

This course offers both postponed and resit of examination. Read more:

Special examination arrangements, use of sources, explanations and appeals

See more about examinations at UiO

Last updated from FS (Common Student System) Oct. 21, 2020 3:12:28 PM

Facts about this course


If the course is offered, a minimum of four students is required for ordinary lectures to take place. If less than four students participate, an exam will be given, but one should not expect ordinary teaching.

Teaching language
Norwegian (English on request)