Our paper on poroelastic effects in espresso brewing is out now in Physics of Fluids. ☕ Inside: computer tomography, hydrodynamics and elasticity modelling, and lots of measurements! doi.org/10.1063/5.03...

Grokking, as hysteresis. L2 regularization drives first-order phase transitions in deep linear networks and below the critical strength, the metastable phase coexists with the global one. Trapped a networks reproduce all hallmarks of grokking & noise-driven escape. openreview.net/forum?id=AkQ...

Our work on practical insights into nonlinear dimensionality reduction with Diffusion Maps is now out! Parametrization, pitfalls & component selection 🚀 Great read for the weekend! Preprint on arXiv: arxiv.org/abs/2601.20428

At this Scientific Machine Learning workshop we showed that strong regularization can cause phase transitions in neural networks. By linking these transitions to the geometric curvature of the training landscape, we reveal a new way to understand and optimize how neural networks learn.

A few weeks ago, our group spent a few days at Burg Hohenstein for our annual retreat — great discussions, beautiful surroundings, and a chance to recharge before the new semester! 🧠🏰

Had a very enjoyable (and productive!) time at a group retreat of @complexityup.bsky.social, especially since it was in the middle of the famous Elbsandstein climbing region.

The #Complexity Science Research Group in Potsdam is specialised in two major fields. One of them is the analysis of politcal systems using tools from . 🧪 1/6 🧵Here's a thread on @karowiesner.bsky.social's research and the many papers she has published on this topic!

This semester, we've been offering two courses on complexity science 🧪 While the master's students delve deeper into the methods and philosophy of complex systems, the bachelor's students get an introduction to the field with some useful applications.

With extreme events happening more often due to #climatechange, we need to understand how ecological networks are affected by them 🧪 In this group, Chris Jones examined a model capable of providing such predictions efficiently by analyzing the dependences between species. arxiv.org/abs/2306.15428

Evaluating The Impact Of Species Specialisation On Ecological Network Robustness Using Analytic Methods

Ecological networks describe the interactions between different species, informing us of how they rely on one another for food, pollination and survival. If a species in an ecosystem is under threat of extinction, it can affect other species in the system and possibly result in their secondary extinction as well. Understanding how (primary) extinctions cause secondary extinctions on ecological networks has been considered previously using computational methods. However, these methods do not provide an explanation for the properties which make ecological networks robust, and can be computationally expensive. We develop a new analytic model for predicting secondary extinctions which requires no non-deterministic computational simulation. Our model can predict secondary extinctions when primary extinctions occur at random or due to some targeting based on the number of links per species or risk of extinction, and can be applied to an ecological network of any number of layers. Using our model, we consider how false positives and negatives in network data affect predictions for network robustness. We have also extended the model to predict scenarios in which secondary extinctions occur once species lose a certain percentage of interaction strength, and to model the loss of interactions as opposed to just species extinction. From our model, it is possible to derive new analytic results such as how ecological networks are most robust when secondary species degree variance is minimised. Additionally, we show that both specialisation and generalisation in distribution of interaction strength can be advantageous for network robustness, depending upon the extinction scenario being considered.

arxiv.org

When does #democracy #backslide, what triggers civil #conflict, and how can statistical #physics and #complexity science help us uncover the links between these phenomena? Intense discussions across disciplinary boundaries this last week at @csh.ac.at. Watch this space!

Complexity Science Hub@csh.ac.at · last yr.

Why do some countries democratize while others backslide? A workshop at CSH, organized by @spintheory.bsky.social and @karowiesner.bsky.social, brought together leading experts to explore how statistical physics can help us better understand the link between democratization and civil war.

This May, two of our Master's students defended their master's theses! 🧪 Both worked on completely different types of systems. However, what connects both of them is clear: #complexity.

Why do some countries democratize while others backslide? A workshop at CSH, organized by @spintheory.bsky.social and @karowiesner.bsky.social, brought together leading experts to explore how statistical physics can help us better understand the link between democratization and civil war.

📣 IFISC is offering 4 scholarships for students enrolling in the Master in Physics of Complex Systems at UIB for the 25-26 academic year. One of the grants is sponsored by Fundación Sicómoro. ℹ ifisc.uib-csic.es/master/fello... Learn about the master's degree: ▶ youtu.be/usn8Ea2kBWk?...

Check out and engage with the Young Researchers of the Complex Systems Society! @yrcss.bsky.social is bringing together young scientists with a common scientific interest in complex systems and creates opportunities for them to get together.

Young Researchers of the Complex Systems Society@yrcss.bsky.social · last yr.

Early-Career Scientists: Want to Travel for Complex Systems Research? We’ve Got You! 🌍 Bridge: 🌉 To build new collaborations! SECS: 🎓 To attend complexity science events! New for 2025: ⚡ Special grants for scientists from low-income countries. yrcss.cssociety.org/grants/ Apply by April 4th!

Meet Paula, one of the PhDs in our group! 🧪 Before joining us, she did her Bachelor's in Physics and Master's degree in Physics of Complex Systems and Biophysics at the University of Barcelona. Now, let's talk about her current #research! 1/10🧵 #WomenInSTEM #SciCom #Complexity

1/6🧵 #Complex systems without emergence are like a long office day without coffe. While emergence is a fascinating phenomenon with a central role in nature and society, it's a challenge to intuitively point out what it actually is. Beyond a minimalist and vague definition, that is... 🧪

It's great to see a new student enter our group meetings every now and then, #academicsky! While we're talking about quite specific topics ranging from neural networks to governments and earth climate, our meetings are open for everyone.

Hey, #academicsky! In January, we got together twice with Prof. Jan Härter's Climate Physics group of the Physics Institute in Potsdam. Each member of both groups got to present their current projects to each other.

If you're interested in hearing @karowiesner.bsky.social talk about #complexity, check out the episodes on Simplifying Complexity with her! We highly recommend giving the rest a listen too - there are plenty of systems and phenomena to explore. 🧪

Simplifying Complexity@bhcomplexity.bsky.social · 2y ago

Hear more from Karoline Wiesner on our #SimplifyingComplexity podcast where she talks in detail about the 10 features of complex systems Apple: buff.ly/3VTjG9I Spotify: buff.ly/3WaR9MA 🧪⚛️ #complex #complexity

As a highly interdisciplinary field of research, #Complexity Science didn’t just come out of nothing. It grew out of ideas from cybernetics and later, concepts like cellular automata. Due to it relying on the groundwork of other sciences, it emerged only recently as an independent field.🧪

Hello there! We're the Complexity Science group at the University of Potsdam, consisting of professor @karowiesner.bsky.social , post-docs, PhDs, as well as master's and bachelor's students and student assistants.

What is a complex system? #Complexity can be found anywhere from neural networks and ant colonies, to climatic systems and governments. Here, at the University of Potsdam, the research group led by physicist @karowiesner.bsky.social explores ways to quantify and better understand complexity.