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pro vyhledávání: '"Zepeda, Erik A."'
Autor:
Zepeda, Erik, Ortiz, Antonio
Over the last years, Machine Learning (ML) tools have been successfully applied to a wealth of problems in high-energy physics. In this work, we discuss the extraction of the average number of Multiparton Interactions ($\langle N_{\rm mpi} \rangle$)
Externí odkaz:
http://arxiv.org/abs/2110.01748
Autor:
Ortiz, Antonio, Zepeda, Erik
Publikováno v:
J. Phys. G: Nucl. Part. Phys. 48 (2021) 085014
Over the last years, Machine Learning (ML) methods have been successfully applied to a wealth of problems in high-energy physics. For instance, in a previous work we have reported that using ML techniques one can extract the Multiparton Interactions
Externí odkaz:
http://arxiv.org/abs/2101.10274
Autor:
Ortiz, Antonio, Paz, Antonio, Romo, Jose D., Tripathy, Sushanta, Zepeda, Erik A., Bautista, Irais
Publikováno v:
Phys. Rev. D 102, 076014 (2020)
Multi-Parton Interactions (MPI) in pp collisions have attracted the attention of the heavy-ion community since they can help to elucidate the origin of collective-like effects discovered in small collision systems at the LHC. In this work, we report
Externí odkaz:
http://arxiv.org/abs/2004.03800