FYS9460 – Disordered Systems and Percolation
Schedule, syllabus and examination date
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.
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.
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.
Recommended previous knowledge
- 10 credits overlap with FYS4460 – Uordnede systemer og perkolasjon.
- 5 credits overlap with FYS4465 – Dynamics of Complex Media.
- 5 credits overlap with FYS9465 – Dynamics of Complex Media.
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.
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: