Details zur Lehrveranstaltung
Network Dynamics and Research on Complex Systems | |||||||
Modul: | Phy-Ma-Vert: Physikalische Vertiefung | ||||||
Lecture language | German | ||||||
Summary of Lecture: | Complex Systems are all around us and most of them are dynamic. Many systems show properties of networks, many units, interacting via intricate topologies. Examples include neural networks in the brain, electric power grids, air transportation networks as well as metabolic or gene regulatory networks in the cell. To understand their collective behavior is far from trivial. Here, we learn methods and tools to grasp why physics thinking may contribute substantially to understand collective structural and dynamical phenomena and the mechanisms underlying them, why some systems may be more complex than others and how to approach analyzing, predicting or even controlling multi-dimensional complex systems. | ||||||
data set up-to-date | |||||||
Scope: | lecture: 3 hours/week tutorials: 1 hours/week | ||||||
Time/location: | DI(4) BAR/I86c, MI(5) ug.W. BAR/I86c | ||||||
Tutorials: |
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Audience: | Vertiefung Bachelor (PV) und Master (alle) | ||||||
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Previous knowledge: | basic knowledge about differential equations and probability theory, ideally statistical physics and stochastics | Certificate: | Mini research, brief report, summary talk, or oral exam | ||||
Enrolment: | bis 15.4.2019 | ||||||
Web-reference: | http://networkdynamics.info | ||||||
Please register for the course also at OPAL at your earliest convenience.
First event will take place in the first week of the semester. Once you know what a nonlinear differential equation is, you are welcome to join. |