Course syllabus for Simulation of complex systems

Course syllabus adopted 2021-02-08 by Head of Programme (or corresponding).

Overview

  • Swedish nameSimulering av komplexa system
  • CodeFFR120
  • Credits7.5 Credits
  • OwnerMPCAS
  • Education cycleSecond-cycle
  • Main field of studyEngineering Physics
  • DepartmentPHYSICS
  • GradingTH - Pass with distinction (5), Pass with credit (4), Pass (3), Fail

Course round 1

  • Teaching language English
  • Application code 11124
  • Block schedule
  • Open for exchange studentsYes

Credit distribution

0199 Project 7.5 c
Grading: TH		 7.5 c

In programmes

Examiner

  • Giovanni Volpe
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Eligibility

General entry requirements for Master's level (second cycle)
Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.

Specific entry requirements

English 6 (or by other approved means with the equivalent proficiency level)
Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.

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.

Aim

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.
- Discuss the ethical implications of the simulations and of the choices made in the simulation models.


Content

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. Finally, we also learn how to evaluate the ethical implications of the simulations and of the choices made in the simulation models.

Organisation

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.

Literature

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

Examination including compulsory elements

The examination is based on:

- 40% homework assignments. Each homework is compulsory.
- 60% group project. This is also compulsory. The evaluation includes a oral presentation (20%) and a written report (40%).

The course examiner may assess individual students in other ways than what is stated above if there are special reasons for doing so, for example if a student has a decision from Chalmers on educational support due to disability.