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Stay informed with our latest news and announcements on this page. For more in-depth content, we also encourage visitors to explore our bimonthly STRUCTURES Newsletter magazine, which features a variety of articles, interviews with members, and background information on our latest research and activities.

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ENUMATH: International Conference Brings Together 600 Numerical Mathematicians in Hei­del­berg

Conference logo
Conference photo
The ENUMATH conference took place September 1 - 5 in Hei­del­berg.
 
The event brought together mathematicians and computational scientists, who shared their latest research, exchanged ideas and identified new avenues for collaboration. (Photos: © R. Scheichl, P. Bastian)

From September 1 to 5, 2025, Hei­del­berg Uni­ver­si­ty welcomed the international numerical mathematics community to the Neuenheimer Feld campus for 2025's Eu­ro­pean Conference on Numerical Mathematics and Advanced Applications (ENUMATH). The event, supported by the STRUC­TURES Cluster of Excellence, brought together more than 750 participants from over 30 countries and six continents, including leading experts as well as early-career researchers. Over the course of five days, mathematicians and computational scientists from all backgrounds shared their latest results, exchanged ideas, and explored new directions for applying numerical mathematics in science and industry.

Alongside invited plenary lectures by leading international experts, the scientific program consisted of over 600 talks in mini-symposia and contributed sessions, as well as a large poster session. Vibrant discussions spanned from advances in discretization schemes and multi-scale modelling to questions on uncertainty quantification, optimisation, and scientific ma­chine learning – reflecting the broad scope and growing role of numerical mathematics in solving complex scientific and industrial challenges.

This year's conference was chaired by STRUC­TURES member Robert Scheichl. The local organization committee included Peter Bastian, Roland Herzog, Vincent Heuveline, Guido Kanschat, Ekaterina Kostina, and Jakob Zech – members of STRUC­TURES, IWR and IMa. The Programme Committee consisted of nine international experts from various countries across Europe. Their efforts, supported by numerous colleagues, institutions, and partners, made the conference a big success.

Since its launch in 1995, ENUMATH has established itself as a central forum for the exchange of ideas in numerical mathematics. The Hei­del­berg meeting continued this tradition by fostering international collaboration and providing a platform for early-career researchers to present their work alongside established experts. Proceedings of the conference will appear with Springer, extending the impact of the lively discussions in Hei­del­berg to the wider mathematical community.

For STRUC­TURES, supporting ENUMATH was a way of underlining the importance of numerical mathematics for our mission to connect disciplines and methods across the natural sciences. It was a great pleasure to welcome the international numerical mathematics community to Hei­del­berg, a vibrant hub for mathematics and computational science in Europe.

Further information:

New Re­search Group: Ma­chine Learning Solutions for Star Formation (StarForML)

Portrait of Victor Ksoll
Dr. Victor Ksoll (Picture © Kerstin Schmid / Foto Sauer) 

We are pleased to announce that our member Victor Ksoll will establish a new re­search group at the Institute of Theo­re­ti­cal Astrophysics (ITA), one of the participating institutes in STRUC­TURES, starting in early 2026. Supported by funding from the Carl Zeiss Foundation, the group – titled “Ma­chine Learning Solutions for Star Formation” (StarForML) – will develop innovative ma­chine learning algorithms for the efficient analysis of astrophysical observational data.

The group’s re­search will focus in particular on star formation, a complex process spanning a vast range of sclaes from molecular clouds to individual protostars. Comparing theo­re­ti­cal predictions to observations requires solving so-called inverse problems, which are computationally intensive. Given the massive data volumes produced by modern telescopes, ma­chine learning has become an indispensable tool for tackling this challenge in an automated fashion. Dr. Ksoll’s goal is to design ma­chine learning methods for such inverse problems in astronomy to enhance our understanding of star formation while increasing the transparency and interpretability of these computational approaches. The group will also employ transfer learning techniques to bridge the gap between simulations and real observational data.

About Victor Ksoll
Victor Ksoll studied physics at the Uni­ver­si­ty of Hei­del­berg, where he also earned his doctorate in astronomy. His re­search included stays at the Institute of Planetology and Astrophysics in Grenoble, France, and the Space Telescope Science Institute in Baltimore, USA. Within STRUC­TURES, he is involved in projects CP 1 (Cosmic Structure Formation) and CP 2 (From Dust to Planets) in addition to various Exploratory Projects. He is also a member of STRUCTURES' Young Researchers Convent (YRC).

Further information:

STRUCTURES-25: New Ma­chine Learning Model Advances Decades-Old Quan­tum Chemistry Puzzle

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The STRUCTURES25 pipeline predicts the target energy as a functional of the electron density for a given molecular constitution and geometry. The gradient of the energy is obtained by automatic differentiation and used to iteratively find the ground state in density optimization (Remme et al. 2025, J. Am. Chem. Soc).

Researchers at Hei­del­berg Uni­ver­si­ty have made a significant advance in computational quan­tum chemistry with the development of STRUCTURES25, a new orbital-free density functional theory (OF-DFT) method powered by ma­chine learning.

In the 1960s, physicists Hohenberg and Kohn made a landmark discovery: the ground-state energy of a molecule or material is completely determined by its electron density — a function describing where electrons are most likely to be found. In principle, this meant that the complex, many-body equations of quan­tum mechanics could be replaced with a simpler task: finding the energy density functional in terms of this density and minimizing it. 

For decades, however, sufficiently good approximations for the universal kinetic energy density functional have remained unknown, requiring the use of Kohn–Sham density functional theory (KS-DFT) instead – where auxiliary wave functions or “orbitals” were reintroduced. While highly successful in practice, the computational cost of KS-DFT can be prohibitive for larger systems, prompting renewed interest in orbital-free density functional theory.

Within our cluster, the Hamprecht and Dreuw Groups, combining their expertise in ma­chine learning and quan­tum chemistry, have been developing a new method to learn it directly. Their current model, STRUCTURES25, achieves chemical accuracy in energy predictions and successfully converges to physically meaningful electron densities for small organic molecules, a long-sought goal that could revolutionize the efficiency of calculations for huge molecular systems. Augmenting the training data with densities obtained from perturbed potentials proved key to these results.

With these advances, the team has brought Hohenberg's and Kohn’s original vision a big step closer to reality — and opened the door to fast, accurate quantum-level modelling of systems far beyond the reach of today’s most widely used methods.

Original Publication:

R. Remme, T. Kaczun, T. Ebert, C. A. Gehrig, D. Geng, G. Gerhartz, M. K. Ickler, M. V. Klockow, P. Lippmann, J. S. Schmidt, S. Wagner, A. Dreuw, and F. A. Hamprecht, Journal of the American Chemical Society, DOI: 10.1021/jacs.5c06219.

Further information:

STRUC­TURES Scientists Build a Matter-Wave Microscope to Reveal Hidden Correlations

Image of atoms and a wave function under a magnifying glass
The new technique allows expanding the wave function of atoms, enabling to image them at length scales previously unresolvable. (Image credit: S. Stapelberg / STRUCTURES)

Understanding complex quan­tum systems remains a central challenge in modern physics. These systems can display correlations, pairing, and exotic states of matter that are key to both fundamental science and future quan­tum technologies. Yet, many of these processes occur on spatial scales too small to be resolved even with advanced imaging techniques. In particular, while current single-atom imaging techniques are powerful, they fail once the relevant structures fall below the resolution limit of the detection method, leaving essential microscopic correlations hidden.

To overcome this fundamental limitation, Sandra Brandstetter and her colleagues from the group of STRUC­TURES member Selim Jochim have developed a novel "matter-wave microscope". Before imaging the atoms, their approach first magnifies their wave function by a factor of about 50. This is achieved by precisely controlling the atoms' time evolution within specially designed optical potentials, essentially performing two “rotations” of the wave function in phase space, without disturbing the correlations that are of interest for their study.

This new technique unlocks the ability to access arbitrary higher-order correlations. Its applications extend to in-depth studies of fermionic pairing and other exotic systems; and help reveal the building blocks of future quan­tum technologies.

Further information:

Breakthrough in X-ray Raman Spectroscopy Uncovers Atomic Structures

Image showing an X-ray signal as a wave form
An incoming X-ray light wave interacts with atoms (purple dots) in a gas to amplify specific spikes (right) in the light wave. (Image credit: Stacy Huang/Argonne National Laboratory.)
 
Image of an X-ray beam propagating through a dense gas, amplifying signals.
As an incoming X-ray light wave propagates through dense gas, it amplifies Raman signals which are analyzed with a grating, providing extremely high-resolution spectra. (Image credit: Stacy Huang/Argonne National Laboratory.)

An international team of researchers involving STRUC­TURES member Thomas Pfeifer has achieved a long-sought milestone in X-ray science.

When intense laser light passes through a gas, it can undergo Raman scattering, a process where photons exchange energy with molecular vibrations and emerge at new frequencies. At high intensities this weak effect becomes self-amplifying, a regime known as stimulated Raman scattering (SRS), first observed in the 1960s. By analyzing the scattered light, researchers can extract detailed information about the molecular structure of the gas. For decades, theorists predicted that a similar effect should occur with X-rays, where the interaction would probe the motion of electrons in atoms rather than molecular vibrations. The effect, known as stimulated X-ray Raman scattering, was demonstrated in earlier studies, but without the resolution needed to spectroscopically resolve electronic excitations.

In a new study published in Nature, researchers from the Argonne National Laboratory (USA) along with the Max Planck Institute for Nuclear Physics (MPIK) in Hei­del­berg and the Eu­ro­pean X-ray Free Electron Laser (Eu­ro­pean XFEL) in Hamburg, have overcome this barrier. In an experiment carried out at the Eu­ro­pean XFEL, they directed intense X-ray pulses through a compact, high-pressure neon gas cell designed at MPIK. As the pulses propagated, they drove the characteristic stimulated Raman amplification, producing distinct X-ray “fingerprints” of the neon atoms' excited states. 

The breakthrough came from analyzing the scattered X-rays with a stochastic approach that turns the inherent noise of XFEL pulses into an advantage. Each pulse has a noisy, spiky spectrum; correlating the spectral spikes of incident and scattered X-rays for over 18,000 individual shots, the team could effectively bypass the limits of the spectrometer itself. This “super-resolution” approach – reminiscent of the optical super-resolution techniques recognized by the 2014 Nobel Prize in Chemistry – proved crucial. It enabled the recovery of narrow Raman features that would normally be blurred by both the finite bandwidth of the source and the resolution of the spectrometer. Thomas Pfeifer, STRUC­TURES member at MPIK and co-author of the study, emphasizes: “The experience of our Hei­del­berg team on high-pressure gas-phase targets for quantum-physics re­search as well as the data-analysis idea of the super-resolution approach were key contributions to the success of this experiment.” 

The findings not only confirm SXRS as a powerful tool for probing matter but also demonstrate dramatic improvements in signal strength and efficiency compared to traditional Raman techniques. Supported by detailed simulations, they also reveal the competition between Raman scattering in neutral atoms and lasing in ionized ones during X-ray propagation. Together, these advances open the door to a new era of X-ray science, where researchers can track the ultrafast movements of electrons that govern the outcome of chemical reactions. This paves the way for deeper insights into materials, catalysis, and biological processes.

Further information:

Schöntal Discussion Workshop 2025 on Inverse Problems

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Participants of the Schöntal Workshop 2025.

For four days in August, sixteen students and two professors gathered at the beautiful Schöntal Abbey to study and discuss about the topic of Inverse Problems. Participants were organized in four groups, each of which carefully prepared subtopics, and presented them during the workshop, leading to in-depth discussions. The Schöntal workshop was thus a lively and enriching experience! 

The annual workshop, funded by STRUC­TURES' Young Researchers Convent (YRC), brings together early-career researchers from different areas of STRUC­TURES to engage in discussion over topics that go be­yond the standard curriculum of a lecture. This year's workshop, marking its ninth edition, was organized by Rebecca Maria Kuntz, Carlos Pastor Marcos, Han­nes Heisler, and Sander Hummerich.

Further information:

YAM Network Meeting 2025 in Hei­del­berg

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YAM Fellows from four German clusters of excellence: HCM Bonn, Mathematics Münster, MATH+ Berlin, STRUC­TURES Hei­del­berg
 
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During the YAM network meeting in Hei­del­berg, the fellows presented and discussed their research, and shared experiences from their re­search stays.
 
Event photo
The event was complemented by a guided city tour through Hei­del­berg's Old Town.

On June 31 and July 01, the STRUC­TURES Cluster of Excellence had the pleasure of welcoming YAM fellows and organizers from various German clusters of excellence to this year's YAM network meeting in Hei­del­berg. During the meeting, which took place at the STRUC­TURES “Oberstübchen”, the YAM fellows presented and discussed their research, shared experiences from their stays in Germany, and engaged in dialogue with peers and coordinators. In addition, the second day featured two talks on career opportunities for mathematicians in Germany by invited guests Dr. Helke Hillebrand (Graduate Academy Hei­del­berg) and Dr. Patrick Wagner (heiSKILLS Competence and Language Centre). The programme was complemented by a campus tour, a guided walk through Hei­del­berg's Old Town, a group dinner and several informal opportunities for networking and exchange.

The two-day meeting fostered lively discussion, providing valuable insights and new connections for both fellows and coordinators of YAM. During the final feedback session, participants shared their impressions and feedback directly with the YAM coordination team, contributing to the continuous development of the programme.

The YAM (Young African Mathematicians) Programme is a collaborative initiative between the five centres of the African Institute for Mathematical Science (AIMS – Cameroon, Senegal, Rwanda, Ghana and South Africa) and four German clusters of excellence (HCM Bonn, Mathematics Münster, MATH+ Berlin, STRUC­TURES Hei­del­berg) that cover mathematical research. Its mission is to encourage young, talented and highly motivated graduates of the AIMS master's programme to conduct a re­search stay at an excellent mathematical institution in Germany. Supervised by a professor (and supported by mentors), the fellows pursue independent re­search and participate in a structured curriculum of courses and lectures.

More than a visiting fellowship, YAM seeks to build a strong and lasting network among young African researchers and the German mathematics community. Regular network meetings, such as the one held in Hei­del­berg, play a key role in fostering exchange and collaboration across institutions and continents.

STRUC­TURES is proud to have been an official partner of the YAM Programme since 2023. Through its contribution to the YAM Programme, STRUC­TURES aims to promote international cooperation, diversity and equal opportunities.  In the first year of its contribution, STRUC­TURES has hosted the YAM fellows Richarlotte Razafindravola and Olivette Tchouangnou Chuagua. In the 2024/25 period, we were happy to welcome Mina Chavelle Tchoua Tchoua, Mickaya Aimé Razana­parany, and Eunisse Nzetchuen Mangaptche. The local YAM coordination team in Hei­del­berg consists of Prof. Hans Knüpfer, Dr. May-Britt Becker and the STRUC­TURES Office team. 

Further information:


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