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Revolutionizing the CMS High-Level Trigger system at the HL-LHC with Next-Generation Triggers2026 CERN Document Server (European Organization for Nuclear Research) article Physics and Astronomy Particle Detector Development and Performance Open access
Elena Vernazza, M. Rovere, M. Musich, Bruno Afonso Fontana Santos Alves, Luca Ferragina, Jan Schulz
0citations -
The scientific potential and technological challenges of the High-Luminosity Large Hadron Collider program2022 Reports on Progress in Physics article Physics and Astronomy Particle Detector Development and Performance Open access
O. Brüning, Heather M. Gray, Katja Klein, M. Lamont, M. Narain, R. Polifka, +1 more
19citations -
Experience with the alpaka performance portability library in the CMS software2025 EPJ Web of Conferences conference-paper Computer Science Parallel Computing and Optimization Techniques Open access
Jaafar Alawieh, Kareen Arutjunjan, Miguel Bacharov Durasov, U. Behrens, Andrea Bocci, James G. Branson, +41 more
1citations -
Beam test performance studies of CMS Phase-2 Outer Tracker module prototypes2024 Journal of Instrumentation article Physics and Astronomy Particle Detector Development and Performance Open access
W. Adam, T. Bergauer, K. Damanakis, M. Dragicevic, Rudolf Konrad Fruhwirth, H. Steininger, +92 more
2citations -
Performance portability for the CMS Reconstruction with Alpaka2023 Journal of Physics Conference Series conference-paper Computer Science Parallel Computing and Optimization Techniques Open access
Andrea Bocci, Angéla Czirkos, Antonio Di Pilato, Felice Pantaleo, Gabrielle Hugo, M. J. Kortelainen, +1 more
4citations -
Design and construction of the CMS Outer Tracker for the HL-LHC Upgrade0citations
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Heterogeneous reconstruction of hadronic particle flow clusters with the Alpaka Portability Library2025 EPJ Web of Conferences conference-paper Computer Science Parallel Computing and Optimization Techniques Open access
Andrea Bocci, Abhishek Das, K. Hatakeyama, Florian Lorkowski, Felice Pantaleo, W. Redjeb, +2 more
0citations -
Search for dark matter with machine learning techniques in leptonic final states and missing transverse energy at the CMS experiment0citations