Contribution to a conference proceedings/Journal Article

PUBDB-2025-02560

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Probing highly collimated photon-jets with deep learning

Ai, X. (Corresponding author)DESY* ; Hsu, S.-C. ; Li, K.Extern* ; Lu, C.-T.

2023
IOP Publ. Bristol

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Please use a persistent id in citations: doi:10.1088/1742-6596/2438/1/012114  doi:10.3204/PUBDB-2025-02560

Report No.: DESY-22-034; arXiv:2203.16703

Abstract: 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.

Keyword(s): decay: exotic ; new physics: signature ; collimator ; axion-like particles ; sensitivity ; photon ; new particle ; CERN LHC Coll ; background ; Higgs particle ; neural network ; pseudoscalar

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Contributing Institute(s):

1. Z_ATUP (Z_ATUP)

Research Program(s):

1. 611 - Fundamental Particles and Forces (POF4-611) (POF4-611)

Experiment(s):

1. LHC: ATLAS

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Database coverage:
; ; ; Nationallizenz ; SCOPUS

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Linked articles:

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Preprint Ai, X. (Corresponding author)DESY* ; Hsu, S.-C. ; Li, K.Extern* ; Lu, C.-T.
Probing highly collimated photon-jets with deep learning
[10.3204/PUBDB-2022-01293]     Files  Fulltext by arXiv.org BibTeX | EndNote: XML, Text | RIS

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