Course content

The course covers simulation methods in many-particle systems applied to, amongst others classical fluids and spin systems. The course provides a theoretical basis as well as practical experience with application of molecular-dynamics and Monte-Carlo simulations.

Learning outcome

Knowledge: - Monte-Carlo and molecular dynamics algorithms. - Approaches for modelling the properties and dynamics of the particles in simulations. - Methods for speeding up simulations. Skills: - Be able to use several tools used in simulation methods in statistical physics. - Be able to write simple programs for molecular dynamics and Monte Carlo simulations. - Be able to decide the applicability of different methods of simulating problems within statistical physics. General Competence: Be able to communicate and present obtained knowledge.

Learning methods and activities

Lectures, seminars, problems, programming assignments. If there are less than 4 registered students, the course coordinator will decide whether the course will take place.

Compulsory assignments

• Exercises

Further on evaluation

Portfolio assessment is the basis for the grade in the course. The portfolio includes exercises counting 70 % and an oral exam counting 30 %. The results for the entire portfolio are graded passed or not passed. Passed requires at least 70% score in total for the portfolio, as well as passing each individual Component. For a re-take of an examination, all assessments during the course must be re-taken.

Recommended previous knowledge

An introductory programming course & statistical physics, thermodynamics, or equivalent.

Course materials

Understanding Molecular Simulation, by Daan Frenkel and Berend Smit. Other material that will be provided.