Cargando…
Hybrid Quantum Classical Graph Neural Networks for Particle Track Reconstruction
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...
Autores principales: | Tüysüz, Cenk, Rieger, Carla, Novotny, Kristiane, Demirköz, Bilge, Dobos, Daniel, Potamianos, Karolos, Vallecorsa, Sofia, Vlimant, Jean-Roch, Forster, Richard |
---|---|
Lenguaje: | eng |
Publicado: |
2021
|
Materias: | |
Acceso en línea: | https://dx.doi.org/10.1007/s42484-021-00055-9 http://cds.cern.ch/record/2782574 |
Ejemplares similares
-
Performance of Particle Tracking Using a Quantum Graph Neural Network
por: Tüysüz, Cenk, et al.
Publicado: (2020) -
A Quantum Graph Neural Network Approach to Particle Track Reconstruction
por: Tüysüz, Cenk, et al.
Publicado: (2020) -
Embedding of particle tracking data using hybrid quantum-classical neural networks
por: Rieger, Carla, et al.
Publicado: (2021) -
Quantum Track Reconstruction Algorithms for non-HEP applications
por: Novotny, Kristiane Sylvia, et al.
Publicado: (2021) -
Particle Track Reconstruction with Quantum Algorithms
por: Tüysüz, Cenk, et al.
Publicado: (2020)