% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Aad:614738,
      author       = {Aad, Georges and others},
      collaboration = {{ATLAS Collaboration}},
      title        = {{S}earch for $t\bar{t}{H}/{A} \rightarrow t\bar{t}t\bar{t}$
                      production in proton-proton collisions at $\sqrt{s}=13$
                      {T}e{V} with the {ATLAS} detector},
      reportid     = {PUBDB-2024-05958, arXiv:2408.17164. CERN-EP-2024-197},
      year         = {2024},
      note         = {51 pages in total, author list starting page 34, 11
                      figures, 3 tables, submitted to EPJC. All figures including
                      auxiliary figures are available at
                      https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/EXOT-2022-13/},
      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 ($t\bar{t}H/A$), and with the $H/A$ decaying
                      into a $t\bar{t}$ pair. Events are selected requiring
                      exactly one or two opposite-charge electrons or muons.
                      Data-driven corrections are applied to improve the modelling
                      of the $t\bar{t}$+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 $t\bar{t}H/A \rightarrow t\bar{t}t\bar{t}$ 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 $t\bar{t}t\bar{t}$ cross-section,
                      $\tan\beta$ 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
                      $t\bar{t}$ pair.},
      keywords     = {top, pair production (INSPIRE) / jet, background (INSPIRE)
                      / p p, scattering (INSPIRE) / GeV (INSPIRE) / ATLAS
                      (INSPIRE) / neural network (INSPIRE) / muon (INSPIRE) /
                      multiplicity (INSPIRE) / higher-dimensional (INSPIRE) /
                      electron (INSPIRE) / kinematics (INSPIRE) / TeV (INSPIRE)},
      cin          = {ATLAS},
      cid          = {I:(DE-H253)ATLAS-20120731},
      pnm          = {611 - Fundamental Particles and Forces (POF4-611) / DFG
                      project G:(GEPRIS)469666862 - Präzisionstests des
                      Standardmodells unter der Verwendung von geboosteten
                      W/Z-Bosonen am Large Hadron Collider (469666862)},
      pid          = {G:(DE-HGF)POF4-611 / G:(GEPRIS)469666862},
      experiment   = {EXP:(DE-H253)LHC-Exp-ATLAS-20150101},
      typ          = {PUB:(DE-HGF)25},
      eprint       = {2408.17164},
      howpublished = {arXiv:2408.17164},
      archivePrefix = {arXiv},
      SLACcitation = {$\%\%CITATION$ = $arXiv:2408.17164;\%\%$},
      doi          = {10.3204/PUBDB-2024-05958},
      url          = {https://bib-pubdb1.desy.de/record/614738},
}