CERN Accelerating science

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1.
Performance of Particle Tracking Using a Quantum Graph Neural Network / Tüysüz, Cenk (Middle East Tech. U., Ankara) ; Novotny, Kristiane (Unlisted, CH) ; Rieger, Carla (Zurich, ETH) ; Carminati, Federico (CERN) ; Demirköz, Bilge (Middle East Tech. U., Ankara) ; Dobos, Daniel (Unlisted, CH ; Lancaster U.) ; Fracas, Fabio (CERN ; Padua U.) ; Potamianos, Karolos (Unlisted, CH ; Oxford U.) ; Vallecorsa, Sofia (CERN) ; Vlimant, Jean-Roch (Caltech)
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. [...]
arXiv:2012.01379.
- 6 p.
Fulltext
2.
Quantum Track Reconstruction Algorithms for non-HEP applications / Novotny, Kristiane Sylvia (gluoNNet) ; Tüysüz, Cenk (Middle East Tech. U., Ankara) ; Rieger, Carla (Zurich, ETH) ; Dobos, Daniel (gluoNNet ; Lancaster U.) ; Potamianos, Karolos Jozef (gluoNNet ; Oxford U.) ; Vallecorsa, Sofia (CERN) ; Carminati, Federico (CERN) ; Demirköz, Bilge (Middle East Tech. U., Ankara) ; Vlimant, Jean-Roch (Caltech) ; Fracas, Fabio (Padua U.)
The expected increase in simultaneous collisions creates a challenge for accurate particle track reconstruction in High Luminosity LHC experiments. Similar challenges can be seen in non-HEP trajectory reconstruction use-cases, where tracking and track evaluation algorithms are used. [...]
SISSA, 2021 - 6 p. - Published in : PoS ICHEP2020 (2021) 983 Fulltext: PDF;
In : 40th International Conference on High Energy Physics (ICHEP), Prague, Czech Republic, 28 Jul - 6 Aug 2020, pp.983
3.
A Quantum Graph Neural Network Approach to Particle Track Reconstruction / Tüysüz, Cenk (Middle East Tech. U., Ankara) ; Carminati, Federico (CERN) ; Demirköz, Bilge (Middle East Tech. U., Ankara) ; Dobos, Daniel (Lancaster U.) ; Fracas, Fabio (CERN ; Padua U.) ; Novotny, Kristiane ; Potamianos, Karolos (DESY) ; Vallecorsa, Sofia (CERN) ; Vlimant, Jean-Roch (Caltech)
Unprecedented increase of complexity and scale of data is expected in computation necessary for the tracking detectors of the High Luminosity Large Hadron Collider (HL-LHC) experiments. [...]
arXiv:2007.06868.
- 6 p.
Fulltext
4.
Particle Track Reconstruction with Quantum Algorithms / Tüysüz, Cenk (Middle East Tech. U., Ankara ; Unlisted, TR) ; Carminati, Federico (CERN) ; Demirköz, Bilge (Middle East Tech. U., Ankara) ; Dobos, Daniel (Unlisted, CH ; Lancaster U. (main)) ; Fracas, Fabio (CERN) ; Novotny, Kristiane (Unlisted, CH) ; Potamianos, Karolos (Unlisted, CH ; DESY) ; Vallecorsa, Sofia (CERN) ; Vlimant, Jean-Roch (Caltech)
Accurate determination of particle track reconstruction parameters will be a major challenge for the High Luminosity Large Hadron Collider (HL-LHC) experiments. The expected increase in the number of simultaneous collisions at the HL-LHC and the resulting high detector occupancy will make track reconstruction algorithms extremely demanding in terms of time and computing resources. [...]
arXiv:2003.08126.- 2020 - 7 p. - Published in : EPJ Web Conf. 245 (2020) 09013 Fulltext: 2003.08126 - PDF; fulltext1785920 - PDF; Fulltext from publisher: PDF;
In : 24th International Conference on Computing in High Energy and Nuclear Physics, Adelaide, Australia, 4 - 8 Nov 2019, pp.09013

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