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Calendar of Physics Talks Vienna
| Foundation models for HEP |
| Speaker: | Anna Hallin (Uni Hamburg) |
| Abstract: | Foundation models are machine learning models designed to handle a wide range of datasets and tasks. After being pre-trained on a specific task on a specific dataset, these models can be fine-tuned for various downstream applications, including different tasks and datasets. Developing such models for physics data could significantly enhance performance in the field and substantially cut down the necessary training time and data requirements. In this talk, I will give an introduction to foundation models and provide an overview of the foundation models that exist for particle physics today. I will also present our foundation model OmniJet-alpha, and discuss some challenges and outlooks for the future. |
| Date: | Tue, 01.07.2025 |
| Time: | 10:00 |
| Duration: | 60 min |
| Location: | PSK (Postsparkasse) meeting room 8 (5B.1, in the 5th floor) |
| Contact: | Claudius Krause (HEPHY) |
| Lower limit on scalar ultralight dark matter from optical cavities |
| Speaker: | Tejas Deshpande (Northwestern University) |
| Abstract: | Direct detection of dark matter (DM) poses one of the most urgent questions in fundamental physics. Scalar ultralight DM (ULDM) is a promising candidate whose coupling to the standard model (SM) of particle physics is expected to cause variations in the fundamental constants like the fine-structure constant and electron mass and thereby the Bohr radius. The latter causes an oscillation in the size of atoms and chemical bonds and consequently the size of macroscopic solids at the ULDM's Compton frequency. We experimentally demonstrate an optomechanical scheme to detect ULDM involving measurement of the ULDM-driven differential length change between two optical Fabry-Perot sapphire cavities. For Compton frequencies in the 5 kHz to 100 kHz range, we improve upon existing limits on the coupling of ULDM to the SM by up to two orders of magnitude. The new limits are presented for two cases: (i |
| Date: | Tue, 01.07.2025 |
| Time: | 11:00 |
| Duration: | 45 min |
| Location: | Helmut Rauch Hörsaal ATI |
| Contact: | René Sedmik |
| From Spectra to Structure (and back): A neural network for high-throughout materials characterization with X-ray photoelectron spectroscopy |
| Speaker: | Florian Simperl (TU Wien, IAP, FB Atom- und Plasmaphysik) |
| Abstract: | X-ray photoelectron spectroscopy (XPS) is a characterisation technique that is sensitive to surface properties (down to 10 nm). It is used to investigate material properties, including chemical composition, chemical depth distribution or core-shell nanoparticles [1, 2]. In recent years, XPS has become a reliable and advanced experimental technique in various scientific and engineering disciplines. Traditionally, extracting accurate quantitative information from XPS data required trained experts to perform time consuming empirical peak fitting for each individual spectrum. In response to the growing need for reliable, instantaneous spectral analysis, we present an automated, quantitative XPS analysis pipeline that combines the Simulation of Electron Spectra for Surface Analysis (SESSA) software with a transformer-based neural network architecture. For this study, SESSA was used to generat |
| Date: | Tue, 01.07.2025 |
| Time: | 16:00 |
| Location: | TU Wien, Institut für Angewandte Physik, E134 1040 Wien, Wiedner HauptstraÃe 8-10 Yellow Tower âBâ, 5th floor, SEM.R. DB gelb 05 B |
| Contact: | Ao.Univ.Prof. Dr. Wolfgang Werner |
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