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Report number arXiv:1906.09058 ; CERN-LHCb-DP-2019-004
Title Real-time discrimination of photon pairs using machine learning at the LHC
Author(s) Benson, Sean (Nikhef, Amsterdam) ; Casais Vidal, Adrián (Santiago de Compostela U., IGFAE) ; Cid Vidal, Xabier (Santiago de Compostela U., IGFAE) ; Puig Navarro, Albert (Zurich U.)
Collaboration LHCb Collaboration
Imprint 2019-06-21. - 16 p.
Note Submitted to SciPost Physics
In: SciPost Phys. 7 (2019) 062
DOI 10.21468/SciPostPhys.7.5.062 (publication)
Subject category hep-ex ; Particle Physics - Experiment
Abstract ALP-mediated decays and other as-yet unobserved $B$ decays to di-photon final states are a challenge to select in hadron collider environments due to the large backgrounds that come directly from the $pp$ collision. We present the strategy implemented by the LHCb experiment in 2018 to efficiently select such photon pairs. A fast neural network topology, implemented in the LHCb real-time selection framework achieves high efficiency across a mass range of $4-20$ GeV$/c^{2}$. We discuss implications and future prospects for the LHCb experiment.
Copyright/License preprint: (License: CC BY 4.0)

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 Notice créée le 2019-06-25, modifiée le 2020-02-29

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