%0 Journal Article
%A Ai, Xiaocong
%A Hsu, Shih-Chieh
%A Li, Kena
%A Lu, Chih-Ting
%T Probing highly collimated photon-jets with deep learning
%J Journal of physics / Conference Series
%V 2438
%N 1
%@ 1742-6588
%C Bristol
%I IOP Publ.
%M PUBDB-2025-02560
%M arXiv:2203.16703
%M DESY-22-034
%P 012114 
%D 2023
%X Many extensions of the standard model (SM) predict the existence of axion-like particles and/or dark Higgs in the sub-GeV scale. Two new sub-GeV particles, a scalar and a pseudoscalar, produced through the Higgs boson exotic decays, are investigated. The decay signatures of these two new particles with highly collimated photons in the final states are discriminated from the ones of SM backgrounds using the Convolutional Neural Networks and Boosted Decision Trees techniques. The sensitivities of searching for such new physics signatures at the Large Hadron Collider are obtained.
%B 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research
%C 29 Nov 2021 - 3 Dec 2021, Daejeon (South Korea)
Y2 29 Nov 2021 - 3 Dec 2021
M2 Daejeon, South Korea
%K decay: exotic (INSPIRE)
%K new physics: signature (INSPIRE)
%K collimator (INSPIRE)
%K axion-like particles (INSPIRE)
%K sensitivity (INSPIRE)
%K photon (INSPIRE)
%K new particle (INSPIRE)
%K CERN LHC Coll (INSPIRE)
%K background (INSPIRE)
%K Higgs particle (INSPIRE)
%K neural network (INSPIRE)
%K pseudoscalar (INSPIRE)
%F PUB:(DE-HGF)8 ; PUB:(DE-HGF)16
%9 Contribution to a conference proceedingsJournal Article
%R 10.1088/1742-6596/2438/1/012114
%U https://bib-pubdb1.desy.de/record/634646