Non-autonomous Dynamics in Complex Systems: Theory and Applications to Critical Transitions

International Seminar and Workshop
09 - 27 October 2023

Workshop Week: 16 - 20 October

This workshop aims to bring together scientists from various disciplines of the natural and physical sciences, particularly from research areas dealing with complex systems and applications to aspects of earth system science, biosciences and network dynamics. The workshop will focus on mathematical approaches, methodologies and applications where non-autonomous, multiple timescale and transient dynamics are important to understand and predict nonlinear behaviour such as critical transitions in complex systems.

We plan a two-week training seminar for PhD students and other early career researchers during the weeks immediately before (9-13 October) and after (24-27 October) the one-week research workshop (16-20 October). The seminar program will include introductory lectures as well as more advanced lectures to address both methodological problems and problems from applications, all related to the topics of the workshop shown on the website. In addition, it is planned to have one or more short courses, some of which may include also hands-on activities on the computer. The attendees will give short talks about their own research projects at the start of the seminar to foster the discussion among themselves but also with the organizers and senior scientists present. Furthermore, we will stimulate collaborations between young researchers and senior scientists by offering joint research mini-projects for attendees, which can also be solved in small groups.

• properties of pullback and snapshot attractors
• random and input-driven dynamical systems
• rate-induced transitions and tipping points
• computational methods for non-autonomous
  systems
• early warning signals for critical transitions
• role of chaotic long-lived transients
• climate dynamics including atmosphere, ocean,
  cryosphere, and biosphere
• applications to neurodynamics, complex networks
  and medicine
• applications in engineering, physical sciences and
  learning systems
• control of critical transitions