|
Calendar of Physics Talks Vienna
| When physics meets machine learning: new tools for a new era |
| Speaker: | Luigi Favaro (UC Louvain) |
| Abstract: | The interplay between physics and machine learning is opening a new era in how we simulate and analyze collider events. In this talk, I will show how machine learning is affecting the collider simulation chain by replacing expensive components with precise surrogate models that maintain accuracy across the full phase space. Beyond speed, the most powerful gains come from integrating physical knowledge directly into model architectures. Whether through physics-motivated parameterizations or by directly embedding known symmetries into the architecture, we obtain models that are more robust, data-efficient, and physically consistent. Throughout, I will argue that physicists bring irreplaceable expertise to this effort, and that the dialogue between domain knowledge and modern machine learning is what will ultimately maximize the discovery potential of experiments like the LHC. |
| Date: | Tue, 24.03.2026 |
| Time: | 10:00 |
| Duration: | 60 min |
| Location: | PSK (Postsparkasse) meeting room 2 (in the 3rd floor) |
| Contact: | Claudius Krause (MBI Vienna) |
| Dijkgraaf-Witten TQFT with defects |
| Speaker: | Catherine Meusburger (FAU Erlangen) |
| Abstract: | We give a gauge theoretical construction of 3d Dijkgraaf-Witten TQFT with defects. It does not require choices of triangulations, allows an easy computation of examples and can be applied to defects in Kitaev's quantum double model. This is joint work with João Faria Martins, arXiv: 2410.18049 |
| Date: | Tue, 24.03.2026 |
| Time: | 14:00 |
| Duration: | 60 min |
| Location: | Erwin-Schroedinger-HS, Boltzmanngasse 5, 1090 Wien, 5.Stock |
| Contact: | S. Fredenhagen, M. Sperling |
|