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A Quantum Graph Neural Network Approach to Particle Track Reconstruction
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. While currently used Kalman filter based algorithms are reaching their limits in terms of ambiguities from increas...
Autores principales: | Tüysüz, Cenk, Carminati, Federico, Demirköz, Bilge, Dobos, Daniel, Fracas, Fabio, Novotny, Kristiane, Potamianos, Karolos, Vallecorsa, Sofia, Vlimant, Jean-Roch |
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Lenguaje: | eng |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.5281/zenodo.4088474 http://cds.cern.ch/record/2725679 |
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