CRC 1114 Postcards
A project created for the CRC 1114 Final Conference by Jana Jerosch, with pictures and explanations provided by CRC members.
Hello, Goodbye, and Thank You from CRC 1114
Participants in the 2026 Final Conference were able to send postcards to friends and collaborators all over the world.
Together through high and low
Attractor of the Charney-deVore (1979) model of atmospheric flow as two-dimensional histograms. Also indicated are two unstable fixed points. The system is characterized by intermittent chaos and exhibits regions of quasistationary behavior studied in CRC 1114's project A08.
Image credit: Henry Schöller
We forecast: No cold-fronts between us
Streamlines of the three-dimensional wind field in a cold-frontal environment. The visualization of the cold-front itself has been omitted for aesthetic reasons. CRC 1114's project C06 investigated the interactions between large-scaled cold-fronts and small-scaled convective cells.
Image credit: Anne Gossing
Oceans can't keep experts on fluid dynamics apart
Passive scalar mixing describes how concentrations mix inside of a moving fluid, like oil spills in the ocean or milk in coffee. The long-term mixing behavior of fluid flows was studied analytically and numerically in project A08.
Image credit: Robin Chemnitz
Goodbye isn't optimal, but we'll make the best of it
"Particles on fluctuating membranes can experience effective interactions that act across multiple length scales, giving rise to rich and complex aggregation behavior. In an initial and ultimately naive attempt, I sought to approximate the membrane mediated forces with a pairwise potential, optimizing force-field parameters to best reproduce the stochastic motion of membrane-bound particles. The optimization converged disastrously, forcing me to directly inspect the objective function landscape over a small patch of parameter space. What emerged was this artwork: a glimpse of the function’s intricately complex structure, and a definitive explanation for why any simple optimization strategy was doomed from the start.“
Image credit: Mohsen Sadeghi
Let's keep in touch, no matter the barriers
Proteins like Ubiquitin can have very high energy barriers which makes it unfeasible to study their folding process with traditional techniques. CRC 1114’s project A04 used machine learning to build models which can navigate across these energy frontiers.
Image credit: Aldo Pasos-Trejo
Working hard to always keep you in our minds
Preventing Amyloid-β aggregation (peptides shown in red and blue) through an inhibitor molecule (green) is a key strategy in Alzheimer's drug research. The ISOKANN algorithm (developed in CRC 1114's projects A05/B05/B03) extracts the slowest collective dynamics with regard to inhibitor binding to the peptides (x-axis) and self-association of the peptides (y-axis). At high y-values of the mountainous free-energy landscape successful inhibiton is shown, low y-values correspond to failed inhibition.
Image credit: Lenard Neander / Marcus Weber