Predicting Transitions in Compex Systems. International Workshop at Dresden, Germany. 23-27 April 2018
Cristina Masoller is a co-organizer of the workshop and Ullrich Parlitz is going to speech in a special invited coloquium.
During the week of April 23-27 2018, world leading experts from various countries (Gemany, USA, UK, Spain, Australia, Japan, etc etc) will meet at MPIPKS to discuss the most recent advances in the development of novel methodologies for improving our understanding of critical transitions in complex systems, with emphasis on advancing their predictability.
Complex systems (composed by large number of nonlinear units with nonlinear interactions) are ubiquitous in nature and their main characteristic is that they are not “reducible”, i.e., trying to understand and predict the behavior of the system based on the behavior of the individual elements or subsets of elements will most certainty fail.
In these systems, it is often observed that they can undergo sudden, critical and dangerous transitions to different operation regimes. Trying to understand the underlying mechanisms that trigger such transitions and to predict future transitions based on observed data are hot topics in nonlinear science, which have produced very interesting recent developments, thanks to the "big data" tools that allow for recording, storing and managing huge amount of data, crucial for understanding complex systems.
During the meeting in Dresden, experts will address most recent developments in the field, with specific applications to neurodynamics (epilepsy), climate dynamics (tipping points in the climate system), ecology (population extinction), etc. as well as the development of mathematical and computational tools aimed at identifying in the observed data, patterns and early warning signals of critical transitions ahead.
The meeting, which will be attended by more than 70 scientists, is being organized by Klaus Lehnertz (Germany), Jaroslav Hlinka (Czech Republic) and Cristina Masoller (Spain) and is funded by MPIPKS and DFG.