Deep Neural Network to Describe the Measurement of the Higgs Production in the Full Leptonic Channel via Vector Boson Fusion

Luis Sánchez, Félix Díaz, Jhonny Rojas

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this article, an analysis of the Higgs boson production via vector boson fusion in the SM H→WW→ 2l2ν (l = e, μ) is performed from an optimization technique in the event selection, called DNN analysis. This analysis compares the standard selection process that CERN performs to study the production of a particle from a cut-based analysis, where the study of statistical significance shows that DNN analysis can better separate signal and background events. To perform the DNN analysis, we optimized the neural network configuration to discriminate signal and background events effectively. Moreover, studies of activation functions such as RELU and Sigmoid, stochastic optimization methods such as ADAM, and regularization methods such as Dropout. All this leads to constructing an optimal neural network topology capable of learning events and signal and background discrimination. Finally, we found an important improvement of approximately 47 % and 27 % for ZVBF and ZHiggs, respectively.

Original languageEnglish
Title of host publicationProceedings of the 21st LACCEI International Multi-Conference for Engineering, Education and Technology
Subtitle of host publicationLeadership in Education and Innovation in Engineering in the Framework of Global Transformations: Integration and Alliances for Integral Development, LACCEI 2023
EditorsMaria M. Larrondo Petrie, Jose Texier, Rodolfo Andres Rivas Matta
PublisherLatin American and Caribbean Consortium of Engineering Institutions
ISBN (Electronic)9786289520743
StatePublished - 2023
Event21st LACCEI International Multi-Conference for Engineering, Education and Technology, LACCEI 2023 - Buenos Aires, Argentina
Duration: 19 Jul 202321 Jul 2023

Publication series

NameProceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
Volume2023-July
ISSN (Electronic)2414-6390

Conference

Conference21st LACCEI International Multi-Conference for Engineering, Education and Technology, LACCEI 2023
Country/TerritoryArgentina
CityBuenos Aires
Period19/07/2321/07/23

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