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Graduate courses

Departments' graduate courses for PhD-students.


Syllabus for

Academic year
FFR120 - Simulation of complex systems
Simulering av komplexa system
Syllabus adopted 2019-02-14 by Head of Programme (or corresponding)
Owner: MPCAS
7,5 Credits
Grading: TH - Five, Four, Three, Fail
Education cycle: Second-cycle
Major subject: Engineering Physics
Department: 16 - PHYSICS

Teaching language: English
Application code: 11112
Open for exchange students: Yes
Block schedule: D+

Module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 Summer course No Sp
0199 Project 7,5 c Grading: TH   7,5 c    

In programs



Giovanni Volpe

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In order to be eligible for a second cycle course the applicant needs to fulfil the general and specific entry requirements of the programme that owns the course. (If the second cycle course is owned by a first cycle programme, second cycle entry requirements apply.)
Exemption from the eligibility requirement: Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling these requirements.

Course specific prerequisites

The students are expected to have a background in natural science corresponding to an undergraduate education in mathematics, computer science, physics, chemistry, or biology. Furthermore, the students are expected to have programming experience in C, C++, Pascal, Matlab, or some other equivalent language.


The course introduces the students to simulation techniques frequently used in complex systems, emphasising agent based modelling and networks. We discuss examples of applications in physics, biology and social science. The aim of the course is to 1) give the students the level of understanding needed to decide on simulation methodology for a specific problem, 2) define and implement a moderate size simulation project, and 3) evaluate the results from their simulations.

Learning outcomes (after completion of the course the student should be able to)

-Describe the fundamental ideas behind the simulation methods discussed in the course, in particular agent based modelling and networks.
-Implement simulation codes in each of the methods.
-Analyse and discuss the results of simulations.
-Plan, manage, execute and report a small-scale simulation project.


Much of modelling in the sciences focuses on simple models, highlighting key mechanisms using small sets of moving parts. However, in complex systems the interesting features are often a direct result of having large sets of particles or agents with different characteristics. This makes new tools a necessity. The course introduces simulation techniques frequently used in complex systems to handle models with many heterogeneous parts. The weight will be on agent-based modelling and networks. For each technique we discuss its background, where its strengths and weaknesses lie, and study examples in physics, biology and social science. We also learn how to validate the outcomes of simulation models in order to reach scientifically sound conclusions.


The course is based on a series of lectures covering the various topics. The students work on simulation projects in groups of two to four students. A tutor supervises each group. Complementary to the lectures there are supervised computer labs where the students solve a variety of small simulation tasks which should be reported as home assignments.


Handouts of shorter texts and articles related to the subjects discussed at the lectures.

Examination including compulsory elements

The examination is based on:

- Homework assignments
- Projects (oral presentation and written report)

Page manager Published: Thu 04 Feb 2021.