ERIK MCLEAN / UNSPLASH

Physikalisches Kolloquium

Freitag, 21. November 2025 17:00 Uhr  Can solids flow? Answers from magnetic quantum gases

Prof. Dr. Lauriane Chomaz, Physikalisches Institut, Universität Heidelberg Can solids flow? Answers from magnetic quantum gases Prof. Dr. Lauriane Chomaz, Physikalisches Institut, Universität Heidelberg Ultracold gases of highly magnetic atoms exhibit unique interaction properties that lead to striking collective behaviors [1]. Exotic states of matter have been discovered to form and stabilize themselves in regimes where these gases were originally predicted to be unstable. These states include ultradilute quantum droplets, quantum crystals, and most notably socalled supersolids, which combine the seemingly antithetical properties of a superfluid (where atoms are fully delocalized) and of a solid (where atoms tend to be localized at specific positions) [2]. After discussing the seminal observations of these states, to which I participated, and how they relied on the long-standing progress in the field, I will elaborate on our current understanding and present ongoing research on their topic, especially within my group at Heidelberg University, where we are currently exploring structural transitions between supersolid crystalline organizations. [1] L. Chomaz & al, Dipolar physics: a review of experiments with magnetic quantum gases, Reports on Progress in Physics 86, 026401 (2023) [2] L. Chomaz, Quantum-stabilized states in magnetic dipolar quantum gases, arXiv preprint arxiv:2504.06221 (2025)

Teilchenkolloquium

CP asymmetry in D0?K0SK0S

Dr. Giulia Tuci, Physikalisches Institut, Uni Heidelberg

Astronomisches Kolloquium

Dienstag, 18. November 2025 16:30 Uhr  From Data to Laws: Symbolic Regression and Differentiable Analytic Networks for (Astro)physics

Rodrigo Ibata, Observatoire Astronomique de Strasbourg Over the next few years, Rubin/LSST, Euclid, Roman, SKA, and other instruments will produce petascale, information?rich datasets that trace stars, galaxies, and large-scale structure with unprecedented fidelity. Hidden in these data may be regularities that point to new and unexpected physical relationships. Can we build modelling frameworks that can discover such relationships accurately, efficiently, and in forms we can interpret? I will present two complementary directions we are developing to address this question. The first, PhySO, is a physics-aware symbolic regression engine which proposes compact mathematical equations using deep reinforcement learning with a dimensional-analysis grammar and imposable constraints. The second, NestyNet, assembles networks with analytic derivatives and trains them using second-order methods, yielding fast, high accuracy fits to datasets, solvers for ODEs/PDEs, action-angle transformations, Gaussian-mixture inference, and dynamical modelling, with exact gradients and Hessians throughout. I will demonstrate how symbolic search coupled with accurate derivatives and with PDE constraints can rediscover analytic solutions from textbook physics. This approach is a practical route toward explainable, robust models for the forthcoming data deluge-aimed less at "automating Kepler" than at accelerating analysis while keeping physical insight. To arrange a visit with the speaker during the visit, please contact their host: Morgan Fouesnau

Zentrum für Quantendynamik Kolloquium

Mittwoch, 26. November 2025 16:30 Uhr  tba

Prof. Guido Pupillo, Institut de science et d'ingénierie supramoléculaires, Unversité de Strasbourg