Simulation of Complex Systems


  • Basic knowledge of mathematics and computer science

Learning targets / competencies:

  • Ability to model, simulate, analyse and verify complex static and dynamic systems
  • Ability to recognise sources of numerical errors
  • Ability to use verification techniques based on interval methods


  • Recap: Positional systems, floating point numbers, sources of numerical errors
  • Interval methods and software: Basic arithmetic, function evaluation, optimization, ODEs
  • Applications: System modeling/simulation/verification/analysis


  • W. Tucker. Validated Numerics: A Short Introduction to Rigorous Computations, Princeton University Press, 2011
  • Further literature will be given during the lectures


1 CH Lecture
1CH Seminar
2 CH Laboratory-based practical classes

Prerequisite for admission to examinations is successful submission of laboratory work

120 minute written examination 
20 minute oral examination or alternative assessment

5 CR