Particle-based fast jet simulation at the LHC with variational autoencoders

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorEuropean Organization for Nuclear Research (CERN)-
Autor(es): dc.contributorNational and Kapodistrian University of Athens-
Autor(es): dc.contributorUniversity of California San Diego-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorCalifornia Institute of Technology-
Autor(es): dc.creatorTouranakou, Mary-
Autor(es): dc.creatorChernyavskaya, Nadezda-
Autor(es): dc.creatorDuarte, Javier-
Autor(es): dc.creatorGunopulos, Dimitrios-
Autor(es): dc.creatorKansal, Raghav-
Autor(es): dc.creatorOrzari, Breno-
Autor(es): dc.creatorPierini, Maurizio-
Autor(es): dc.creatorTomei, Thiago-
Autor(es): dc.creatorVlimant, Jean-Roch-
Data de aceite: dc.date.accessioned2025-08-21T15:55:41Z-
Data de disponibilização: dc.date.available2025-08-21T15:55:41Z-
Data de envio: dc.date.issued2023-03-01-
Data de envio: dc.date.issued2023-03-01-
Data de envio: dc.date.issued2022-09-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1088/2632-2153/ac7c56-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/240570-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/240570-
Descrição: dc.descriptionWe study how to use deep variational autoencoders (VAEs) for a fast simulation of jets of particles at the Large Hadron Collider. We represent jets as a list of constituents, characterized by their momenta. Starting from a simulation of the jet before detector effects, we train a deep VAE to return the corresponding list of constituents after detection. Doing so, we bypass both the time-consuming detector simulation and the collision reconstruction steps of a traditional processing chain, speeding up significantly the events generation workflow. Through model optimization and hyperparameter tuning, we achieve state-of-the-art precision on the jet four-momentum, while providing an accurate description of the constituents momenta, and an inference time comparable to that of a rule-based fast simulation.-
Descrição: dc.descriptionEuropean Organization for Nuclear Research (CERN)-
Descrição: dc.descriptionDepartment of Informatics and Telecommunications National and Kapodistrian University of Athens-
Descrição: dc.descriptionUniversity of California San Diego, La Jolla-
Descrição: dc.descriptionUniversidade Estadual Paulista, SP-
Descrição: dc.descriptionCalifornia Institute of Technology-
Descrição: dc.descriptionUniversidade Estadual Paulista, SP-
Idioma: dc.languageen-
Relação: dc.relationMachine Learning: Science and Technology-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectgenerative models-
Palavras-chave: dc.subjectparticle physics-
Palavras-chave: dc.subjectsparse data simulation-
Título: dc.titleParticle-based fast jet simulation at the LHC with variational autoencoders-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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