Quantum Generative Adversarial Networks in a Continuous-Variable Architecture to Simulate High Energy Physics Detectors

Deep Neural Networks (DNNs) come into the limelight in High Energy Physics (HEP) in order to manipulate the increasing amount of data encountered in the next generation of accelerators. Recently, the HEP community has suggested Generative Adversarial Networks (GANs) to replace traditional time-consu...

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Detalles Bibliográficos
Autores principales: Chang, Su Yeon, Vallecorsa, Sofia, Combarro, Elías F., Carminati, Federico
Lenguaje:eng
Publicado: 2021
Materias:
cs.LG
Computing and Computers
quant-ph
General Theoretical Physics
Acceso en línea:http://cds.cern.ch/record/2751529

Internet

http://cds.cern.ch/record/2751529

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