T 77: Data, AI, Computing, Electronics VIII (Fast ML, Triggers)
Thursday, April 3, 2025, 16:15–18:15, VG 2.102
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16:15 |
T 77.1 |
Optimization of the muon momentum resolution in the ATLAS first-level trigger with machine learning techniques — •Francisco Resende, Davide Cieri, Oliver Kortner, and Sandra Kortner
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16:30 |
T 77.2 |
Convolutional Neural Networks on FPGAs for Processing of ATLAS Liquid Argon Calorimeter Signals — Anna Franke, Manuel Gutsche, Markus Helbig, Rainer Hentges, Arno Straessner, •Johann Christoph Voigt, and Philipp Welle
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16:45 |
T 77.3 |
Using Transformer based Graph Neural Networks to Identify Hadronically Decaying Tau Leptons with the ATLAS trigger — •Athul Dev Sudhakar Ponnu and Stan Lai
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17:00 |
T 77.4 |
Forward Electron Identification at the ATLAS First Level Trigger for the High Luminosity LHC — •Maximilian Linkert, Stefan Tapprogge, and Adrian Alvarez Fernandez
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17:15 |
T 77.5 |
First Level Trigger Algorithm for Electron Identification in ATLAS — •Julia Troppens, Maximilian Linkert, Dennis Layh, and Stefan Tapprogge
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17:30 |
T 77.6 |
Development of machine-learning based topological triggers for the CMS Level-1 trigger — •Karla Kleinbölting, Lukas Ebeling, Johannes Haller, Finn Jonathan Labe, Balduin Letzer, Artur Lobanov, Lara Markus, and Matthias Schröder
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17:45 |
T 77.7 |
Implementation of a two-level AI-enhanced trigger on a single chip with AI cores for live reconstruction — •Patrick Schwäbig for the Lohengrin collaboration
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18:00 |
T 77.8 |
Performance of a Quantized Neural Network on an FPGA for Next Generation Radio Array DAQ Systems — •Adam Rifaie for the IceCube-Gen2 collaboration
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