Portraying double Higgs at the Large Hadron Collider

2019/04/30 by Jeong Han Kim, Minho Kim, Kyoungchul Kong +3 · 2 citations
Physics and Astronomy · #Astronomy #Channel (broadcasting) #Classical mechanics #Collider #Computer science #Geography #Higgs boson #High-Energy Particle Collisions Research #Jet (fluid) #Kinematics #Large Hadron Collider #Lepton #Luminosity #Nuclear physics #Particle Detector Development and Performance #Particle physics #Particle physics theoretical and experimental studies #Physics #Production (economics) #SIGNAL (programming language) #Sensitivity (control systems) #Standard Model (mathematical formulation) #hep-ex #hep-ph

paper · pdf · doi:10.1007/jhep09(2019)047

published as JHEP 09 (2019) 047 · 37 pages. Matched to published version. Revisions in section 1, 2. Replaced figures. Added references. Conclusions unchanged

openalex publication_date 2019/09/01 · arxiv created 2019/09/18 · arxiv updated 2019/09/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05

Abstract

A bstract We examine the discovery potential for double Higgs production at the high luminosity LHC in the final state with two b -tagged jets, two leptons and missing transverse momentum. Although this dilepton final state has been considered a difficult channel due to the large backgrounds, we argue that it is possible to obtain sizable signal significance, by adopting a deep learning framework making full use of the relevant kinematics along with the jet images from the Higgs decay. For the relevant number of signal events we obtain a substantial increase in signal sensitivity over existing analyses. We discuss relative improvements at each stage and the correlations among the different input variables for the neutral network. The proposed method can be easily generalized to the semi-leptonic channel of double Higgs production, as well as to other processes with similar final states.

Citations

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