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Search for tt¯H/A→tt¯tt¯ production in proton–proton collisions at s=13 TeV with the ATLAS detector

Aad, G. ; Åkesson, T.P.A. LU orcid ; Astrand, K.S.V. LU ; Doglioni, C. LU ; Ekman, P.A. LU orcid ; Hedberg, V. LU ; Herde, H. LU orcid ; Konya, B. LU ; Lytken, E. LU orcid and Poettgen, R. LU orcid , et al. (2025) In European Physical Journal C 85(5).
Abstract
A search is presented for a heavy scalar (H) or pseudo-scalar (A) predicted by the two-Higgs-doublet models, where the H/A is produced in association with a top-quark pair (tt¯H/A), and with the H/A decaying into a tt¯ pair. The full LHC Run 2 proton–proton collision data collected by the ATLAS experiment is used, corresponding to an integrated luminosity of 139fb-1. Events are selected requiring exactly one or two opposite-charge electrons or muons. Data-driven corrections are applied to improve the modelling of the tt¯+jets background in the regime with high jet and b-jet multiplicities. These include a novel multi-dimensional kinematic reweighting based on a neural network trained using data and simulations. An H/A-mass parameterised... (More)
A search is presented for a heavy scalar (H) or pseudo-scalar (A) predicted by the two-Higgs-doublet models, where the H/A is produced in association with a top-quark pair (tt¯H/A), and with the H/A decaying into a tt¯ pair. The full LHC Run 2 proton–proton collision data collected by the ATLAS experiment is used, corresponding to an integrated luminosity of 139fb-1. Events are selected requiring exactly one or two opposite-charge electrons or muons. Data-driven corrections are applied to improve the modelling of the tt¯+jets background in the regime with high jet and b-jet multiplicities. These include a novel multi-dimensional kinematic reweighting based on a neural network trained using data and simulations. An H/A-mass parameterised graph neural network is trained to optimise the signal-to-background discrimination. In combination with the previous search performed by the ATLAS Collaboration in the multilepton final state, the observed upper limits on the tt¯H/A→tt¯tt¯ production cross-section at 95% confidence level range between 14 fb and 5.0 fb for an H/A with mass between 400 GeV and 1000 GeV, respectively. Assuming that both the H and A contribute to the tt¯tt¯ cross-section, tanβ values below 1.7 or 0.7 are excluded for a mass of 400 GeV or 1000 GeV, respectively. The results are also used to constrain a model predicting the pair production of a colour-octet scalar, with the scalar decaying into a tt¯ pair. © The Author(s) 2025. (Less)
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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Germanium compounds, Neural networks, Protons, Tellurium compounds, ATLAS detectors, ATLAS experiment, Data driven, Heavy scalar, Higgs doublet models, Integrated luminosity, Multi dimensional, Opposite charge, Proton proton collisions, Top quarks, Fighter aircraft
in
European Physical Journal C
volume
85
issue
5
article number
573
publisher
Springer Nature
external identifiers
  • scopus:105009301920
ISSN
1434-6044
DOI
10.1140/epjc/s10052-025-14041-z
language
English
LU publication?
yes
id
c479e5ca-2f38-4325-a7d3-8a1ebbe854a8
date added to LUP
2026-03-19 08:29:28
date last changed
2026-09-05 06:08:55
@article{c479e5ca-2f38-4325-a7d3-8a1ebbe854a8,
  abstract     = {{A search is presented for a heavy scalar (H) or pseudo-scalar (A) predicted by the two-Higgs-doublet models, where the H/A is produced in association with a top-quark pair (tt¯H/A), and with the H/A decaying into a tt¯ pair. The full LHC Run 2 proton–proton collision data collected by the ATLAS experiment is used, corresponding to an integrated luminosity of 139fb-1. Events are selected requiring exactly one or two opposite-charge electrons or muons. Data-driven corrections are applied to improve the modelling of the tt¯+jets background in the regime with high jet and b-jet multiplicities. These include a novel multi-dimensional kinematic reweighting based on a neural network trained using data and simulations. An H/A-mass parameterised graph neural network is trained to optimise the signal-to-background discrimination. In combination with the previous search performed by the ATLAS Collaboration in the multilepton final state, the observed upper limits on the tt¯H/A→tt¯tt¯ production cross-section at 95% confidence level range between 14 fb and 5.0 fb for an H/A with mass between 400 GeV and 1000 GeV, respectively. Assuming that both the H and A contribute to the tt¯tt¯ cross-section, tanβ values below 1.7 or 0.7 are excluded for a mass of 400 GeV or 1000 GeV, respectively. The results are also used to constrain a model predicting the pair production of a colour-octet scalar, with the scalar decaying into a tt¯ pair. © The Author(s) 2025.}},
  author       = {{Aad, G. and Åkesson, T.P.A. and Astrand, K.S.V. and Doglioni, C. and Ekman, P.A. and Hedberg, V. and Herde, H. and Konya, B. and Lytken, E. and Poettgen, R. and Simpson, N.D. and Smirnova, O. and Wallin, E.J. and Zwalinski, L.}},
  issn         = {{1434-6044}},
  keywords     = {{Germanium compounds; Neural networks; Protons; Tellurium compounds; ATLAS detectors; ATLAS experiment; Data driven; Heavy scalar; Higgs doublet models; Integrated luminosity; Multi dimensional; Opposite charge; Proton proton collisions; Top quarks; Fighter aircraft}},
  language     = {{eng}},
  number       = {{5}},
  publisher    = {{Springer Nature}},
  series       = {{European Physical Journal C}},
  title        = {{Search for tt¯H/A→tt¯tt¯ production in proton–proton collisions at s=13 TeV with the ATLAS detector}},
  url          = {{http://dx.doi.org/10.1140/epjc/s10052-025-14041-z}},
  doi          = {{10.1140/epjc/s10052-025-14041-z}},
  volume       = {{85}},
  year         = {{2025}},
}