Prof. Dr. Jan Kieseler
(Karlsruhe Institute of Technology (KIT))hosted by Seminar Series on Scientific Computing
"From Detector Signals to Physics with Machine Learning"
Large-scale particle detectors at CERN’s Large Hadron Collider (LHC) and its upcoming high-luminosity upgrade (HL-LHC) record millions of collisions per second, producing sparse, irregular, high-dimensional sensor data from conceptually very different sub-detector systems, such as tracking and calorimetry. Future collider concepts push granularity requirements even further: they aim at unprecedented measurement precision and, despite operating at lower particle densities, place new demands on particle detection (reconstruction) algorithms. Meeting the physics goals of these experiments—precision measurements and searches for extremely rare processes—requires algorithms that can reliably extract thousands of overlapping particles under tight performance and computing constraints, and translate robustly to ultimate-precision detectors.
| Time: | Tuesday, 02.12.2025, 15:15 |
|---|---|
| Place: | Hybrid (Room 32-349 and via Zoom) |
| Video: | https://uni-kl-de.zoom-x.de/j/69269239534?pwd=Z9UOzMpkhMjrxVhll3d49sNHFe9Fd1.1 |
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