Complexity Science - Einzelansicht

The course gives an overview of the research field of complexity science. First lecture 17 April 2023 at 9 am.

If you are interested in taking the course but cannot attend on Monday 17 April do write to me :: email karoline.wiesner@uni-potsdam.de.

Topics include 

on the theory side: Shannon information theory, equilibrium statistical mechanics, network theory and

on the applications side: physics, climate science, social science.

The lecture times (currently Mondays 8am) will be decided in the first week of term, depending on the schedule of the participants.

Moodle page (key he9djs)

https://moodle2.uni-potsdam.de/course/view.php?id=31361

As introduction I recommend chapters 1 and 2 of the book "What is a complex system?", available as e-book through the University library (you have to be on the University's VPN network).

The direct link:

https://www.degruyter.com/document/doi/10.12987/9780300256130/html

Mathematics: A strong background in mathematics is essential for understanding complex systems. Students should have a good understanding of calculus, linear algebra, probability theory, and statistics.

Programming: Students should have experience in programming, preferably in a language such as Python, or R, which are commonly used in complex systems modeling and analysis.

Physics: A basic understanding of physics, including mechanics, thermodynamics, and statistical mechanics, is helpful in understanding the dynamics of complex systems.