Publications [#360772] of Ayana T. Arce

Papers Accepted
  1. Aad, G; Abbott, B; Abbott, DC; Abud, AA; Abeling, K; Abhayasinghe, DK; Abidi, SH; Abramowicz, H; Abreu, H; Abulaiti, Y; Hoffman, ACA; Acharya, BS; Achkar, B; Adam, L; Bourdarios, CA; Adamczyk, L; Adamek, L; Adelman, J; Adiguzel, A; Adorni, S; Adye, T; Affolder, AA; Afik, Y; Agapopoulou, C; Agaras, MN; Agarwala, J; Aggarwal, A; Agheorghiesei, C; Aguilar-Saavedra, JA; Ahmad, A; Ahmadov, F; Ahmed, WS; Ai, X; Aielli, G; Akatsuka, S; Akbiyik, M; Åkesson, TPA; Akimov, AV; Khoury, KA; Alberghi, GL; Albert, J; Verzini, MJA; Alderweireldt, S; Aleksa, M; Aleksandrov, IN; Alexa, C; Alexopoulos, T; Alfonsi, A; Alfonsi, F; Alhroob, M; Ali, B; Ali, S; Aliev, M; Alimonti, G; Allaire, C; Allbrooke, BMM; Allport, PP; Aloisio, A; Alonso, F; Alpigiani, C; Camelia, EA; Estevez, MA; Alviggi, MG; Coutinho, YA; Ambler, A; Ambroz, L; Amelung, C; Amidei, D; Santos, SPAD; Amoroso, S; Amrouche, CS; Anastopoulos, C; Andari, N; Andeen, T; Anders, JK; Andrean, SY; Andreazza, A; Andrei, V; Angelidakis, S; Angerami, A; Anisenkov, AV; Annovi, A; Antel, C; Anthony, MT; Antipov, E; Antonelli, M; Antrim, DJA; Anulli, F; Aoki, M; Pozo, JAA; Aparo, MA; Bella, LA; Aranzabal, N; Ferraz, VA; Arcangeletti, C; Arce, ATH; Arena, E; Arguin, JF; Argyropoulos, S; Arling, JH, Search for R-parity-violating supersymmetry in a final state containing leptons and many jets with the ATLAS experiment using √s=13TeV proton–proton collision data, European Physical Journal C, vol. 81 no. 11 (November, 2021) [doi] .

    Abstract:
    A search for R-parity-violating supersymmetry in final states characterized by high jet multiplicity, at least one isolated light lepton and either zero or at least three b-tagged jets is presented. The search uses 139fb-1 of s=13TeV proton–proton collision data collected by the ATLAS experiment during Run 2 of the Large Hadron Collider. The results are interpreted in the context of R-parity-violating supersymmetry models that feature gluino production, top-squark production, or electroweakino production. The dominant sources of background are estimated using a data-driven model, based on observables at medium jet multiplicity, to predict the b-tagged jet multiplicity distribution at the higher jet multiplicities used in the search. Machine-learning techniques are used to reach sensitivity to electroweakino production, extending the data-driven background estimation to the shape of the machine-learning discriminant. No significant excess over the Standard Model expectation is observed and exclusion limits at the 95% confidence level are extracted, reaching as high as 2.4 TeV in gluino mass, 1.35 TeV in top-squark mass, and 320 (365) GeV in higgsino (wino) mass.

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