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Tagging fully hadronic exotic decays of the vectorlike B quark using a graph neural network

Jai Bardhan1,*, Tanumoy Mandal2,†, Subhadip Mitra1,3,‡, Cyrin Neeraj1,§, and Mihir Rawat1,∥

  • *Contact author: jai.bardhan@research.iiit.ac.in
  • †Contact author: tanumoy@iisertvm.ac.in
  • ‡Contact author: subhadip.mitra@iiit.ac.in
  • §Contact author: cyrin.neeraj@research.iiit.ac.in
  • ∥Contact author: mihir.r@research.iiit.ac.in
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Phys. Rev. D 112, 015015 – Published 15 July, 2025

DOI: https://doi.org/10.1103/hk9n-37kx

Abstract

Following up on our earlier study [J. Bardhan et al., Phys. Rev. D 107, 115001 (2023)], we investigate the LHC prospects of pair-produced vectorlike B quarks decaying exotically to a new gauge-singlet (pseudo)scalar field Φ and a b quark. After the electroweak symmetry breaking, the Φ decays predominantly to gg/bb final states, leading to a fully hadronic 2b+4j or 6b signature. Because of the large Standard Model background and the lack of leptonic handles, it is a difficult channel to probe. To overcome the challenge, we employ a hybrid deep learning model containing a graph neural network followed by a deep neural network. We estimate that such a state-of-the-art deep learning analysis pipeline can lead to a performance comparable to that in the semileptonic mode, taking the discovery (exclusion) reach up to about MB=1.8(2.4)  TeV at HL-LHC when B decays fully exotically, i.e., BR(B→bΦ)=100%.

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Phys. Rev. D 112, 015015– Published 15 July, 2025
  • Received 25 May 2025
  • Accepted 27 June 2025
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