The Max Planck Institute for Dynamics and Self-Organization (MPIDS) is engaged in a variety of dynamical and in particular self-organizational phenomena: from vortices in turbulent flows, neural networks in the brain, to granular matter and complex fluids. Although these systems can be assigned to different disciplines, they often follow similar laws and can thus be studied and described using similar methods. Among the more than 250 employees of the institute, there are physicists, chemists, geologists, computer scientists and mathematicians, in close collaboration.
The institute has been founded in 1925 as the Kaiser-Wilhelm Institute for Flow Research and belongs to the oldest and most traditional institutes of the Max Planck Society. The founding director Ludwig Prandtl dominantly influenced the early decades and established the institute as a leading one for experimental and theoretical flow research.
Still today most of its researchers are concerned with flow research, but typically look at it in a larger context of dynamical and in particular self-organizational phenomena. The renaming of the institute to Max Planck Institute for Dynamics and Self-Organization has been a consequence of this reorientation.
What we want
No matter how well we understand how a single droplet of water is formed in the laboratory, we cannot predict how countless droplets form clouds that substantially affect the Earth’s climate. And although we can accurately characterize a single neuron’s impulse, we do not yet understand how billions of them form a single thought. In such systems, animate or inanimate, processes of self-organization are at work: Many interacting parts organize themselves independently, without external control, into a complex whole. At our institute we explore the mechanisms underlying these processes in order to gain a detailed understanding of complex systems. Also the major challenges of the 21st century, from climate change and economic crises to problems in energy supply and transport, are closely linked to these scientific questions. Without a deep understanding of dynamics and self-organization in complex and highly networked systems we cannot face these challenges. With our basic research not only do we want to deepen our understanding of nature, but also want to contribute to a sustainable existence on this planet.