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@ARTICLE{Aad:634595,
      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 $\sqrt{s}=13$
                      $\text {{T}e{V}}$ with the {ATLAS} detector},
      journal      = {The European physical journal / C},
      volume       = {85},
      number       = {5},
      issn         = {1434-6044},
      address      = {Heidelberg},
      publisher    = {Springer},
      reportid     = {PUBDB-2025-02509, arXiv:2408.17164. CERN-EP-2024-197},
      pages        = {573},
      year         = {2025},
      note         = {Eur. Phys. J. C 85 (2025) 573. 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. The full LHC Run 2 proton–proton
                      collision data collected by the ATLAS experiment is used,
                      corresponding to an integrated luminosity of $139~\text
                      {fb}^{-1}.$ Events are selected requiring exactly one or two
                      opposite-charge electrons or muons. Data-driven corrections
                      are applied to improve the modelling of the $t\bar{t}$+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 $\text {GeV}$
                      and 1000 $\text {GeV}$, 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 $\text {GeV}$ or 1000 $\text {GeV}$,
                      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.},
      cin          = {ATLAS},
      ddc          = {530},
      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) / REALDARK
                      - REAL-time discovery strategies for DARK matter and dark
                      sector signals at the ATLAS detector with Run-3 LHC data
                      (101002463) / DITTO - Comprehensive search for new phenomena
                      in the dilepton spectrum at the LHC (101089007)},
      pid          = {G:(DE-HGF)POF4-611 / G:(GEPRIS)469666862 /
                      G:(EU-Grant)101002463 / G:(EU-Grant)101089007},
      experiment   = {EXP:(DE-H253)LHC-Exp-ATLAS-20150101},
      typ          = {PUB:(DE-HGF)16},
      eprint       = {2408.17164},
      howpublished = {arXiv:2408.17164},
      archivePrefix = {arXiv},
      SLACcitation = {$\%\%CITATION$ = $arXiv:2408.17164;\%\%$},
      doi          = {10.1140/epjc/s10052-025-14041-z},
      url          = {https://bib-pubdb1.desy.de/record/634595},
}