CERN Accelerating science

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1.
Hybrid Quantum Classical Graph Neural Networks for Particle Track Reconstruction / Tüysüz, Cenk (Middle East Tech. U., Ankara) ; Rieger, Carla (ETH, Zurich (main)) ; Novotny, Kristiane (Lancaster U.) ; Demirköz, Bilge (Middle East Tech. U., Ankara) ; Dobos, Daniel (Lancaster U.) ; Potamianos, Karolos (Oxford U.) ; Vallecorsa, Sofia (CERN) ; Vlimant, Jean-Roch (Caltech) ; Forster, Richard (Lancaster U.)
The Large Hadron Collider (LHC) at the European Organisation for Nuclear Research (CERN) will be upgraded to further increase the instantaneous rate of particle collisions (luminosity) and become the High Luminosity LHC (HL-LHC). This increase in luminosity will significantly increase the number of particles interacting with the detector. [...]
arXiv:2109.12636.- 2021-12-01 - 20 p. - Published in : Quant. Machine Intell. 3 (2021) 29 Fulltext: Tüysüz2021_Article_HybridQuantumClassicalGraphNeu (1) - PDF; document - PDF; 2109.12636 - PDF; Fulltext from publisher: PDF;
2.
Collaboration Spotting : A Visual Analytics Platform to Assist Knowledge Discovery / Le Goff, Jean-Marie (CERN) ; Agocs, Adam (CERN) ; Dardanis, Dimitris (CERN) ; Forster, Richard (CERN) ; Ouvrard, Xavier (CERN) ; Rattinger, André (CERN)
2017 - Published in : ERCIM News (2017) , no. 111, pp. 46-48 Fulltext: PDF; External link: Fulltext

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