Building Blocks of Matter and Fundamental Interactions (TRA Matter)

Third TRA Matter Network Symposium ''MATTER connects''

October 28, 2024

On October 28, we held our third Networking Symposium“MATTER connects”, which was attended by 50 scientists ranging from PhD students to experienced researchers. The day's agenda included various activities, including two interdisciplinary talks from different disciplines to which participants could ask questions.

In addition, the scientists had the opportunity to exchange ideas and discuss with colleagues from other disciplines during the poster session. These annual networking meeting aim to bring together researchers from different fields and promote exchange across different research areas of TRA Matter.

Workshop on Machine-Learning-Based Sampling in Lattice FieldTheory and Quantum Chemistry

October 25, 2024

The recent Bethe Forum, supported by TRA Matter and the CRC NuMeriQs, successfully brought together researchers from various fields facing similar challenges in their work. Modern scientific research is increasingly interdisciplinary, with many fields now integrating artificial intelligence and machine learning. Despite tackling similar problems, these different sub-communities often struggle to "talk" to each other. This lack of communication presents a significant barrier to collaboration and sharing tools that could accelerate progress in multiple domains. For example, while the incorporation of physical symmetries into machine learning models has been widely studied in quantum chemistry, it’s only recently gaining traction in lattice quantum field theory. To address this challenge, the workshop Machine-Learning-Based Sampling in Lattice Field Theory and Quantum Chemistry (add link to website) was initiated by Dr. Kim A. Nicoli and Prof. Lena Funcke from TRA Matter, along with Tom Froembgen (University of Bonn) and Dr. Shinichi Nakajima (BIFOLD). The event aimed to bring together academic and industry experts facing similar challenges that recently started to be tackled by machine learning methods. A core focus of the workshop was on the Boltzmann distribution, an essential quantity in physical systems and critical for simulations and estimating physical observables. Recent advances in Generative AI have highlighted efficient protocols using machine learning for sampling from the target Boltzmann distribution of a given physical system. Both the lattice field theory and quantum chemistry communities have developed innovative tools for this purpose, and the forum provided an opportunity to explore how these tools might benefit each field. The Bethe Forum was a great success, drawing a diverse audience including Master's and PhD students, postdoctoral researchers, faculty, and industry professionals. Notably, two technical staff members from cusp.ai, a pioneering startup focused on developing CO2-capturing materials through machine learning, participated in the workshop and presented some of their work. The forum featured a rich program with thirteen technical talks, a poster session, three panel discussions, a Bethe colloquium on Normalizing Flows for Lattice QCD by Dr.Gurtej Kanwar, and a TRA colloquium on Symmetries and Equivariance in AI for Science by Prof. Jan Gerken. Alongside the daily business, there was a lot of room for social gatherings, which was highly appreciated by the
participants. The organizing team thanks all the speakers for their insightful and accessible presentations, as well as the participants for fostering a relaxed, engaging environment that encouraged discussion and collaboration. We hope our efforts in bringing these communities togetherwill pave the way for future collaborations. Encouraged by the success of this first edition, the organizing team is already looking forward to planning the next edition for 2026.

Interdisciplinary hands-on workshop “Machine Learning” for young scientists from the fields of matter, modelling and life sciences

March 19 + 20, 2024

Around 60 post-docs and doctoral students from the transdisciplinary research areas “Matter”, “Modelling”, “Life and Health” and the “Bonner Forum Biomedizin” (BFB) took part in this year's interdisciplinary hands-on workshop “Machine Learning”. At the two-day workshop, early career scientists gained insights into machine learning and its theoretical concepts in various ways. Following a basic lecture in three parts by Prof. Dr. Bauckhage, all participants had the opportunity to try out what they had learned in practical application exercises. On the second day, lectures provided insights on the application of “Physics-informed Neural Networks” (PINN) to model gene regulation in stem cells (Dr. Maria Mircea), the use of generative AI models for physical questions (Dr. Kim Nicoli) and the Use of “Active Learning” for behavior analysis in neuroscience (Dr. Jens Tillmann). The event ended with a small networking session in which the participants were able to exchange information about their research and what they had learned during these two days of workshop.

We would like to thank the excellent speakers and dedicated tutors for their contribution to the success of this workshop!

Speakers

Prof. Dr. Connie C. Lu

Institut für Anorganische Chemie

Prof. Dr. Sebastian Neubert

Helmholtz-Institut für Strahlen- und Kernphysik