Karlsruhe 2024 – wissenschaftliches Programm

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T: Fachverband Teilchenphysik

T 2: Search for new particles 1 (LHC)

T 2.6: Vortrag

Montag, 4. März 2024, 17:15–17:30, Geb. 20.30: 1.067

Search for new phenomena with top-quark pairs using 140 fb⁻¹ of data at √s = 13 TeV with the ATLAS detector — •Simran Gurdasani, Daniele Zanzi, and Christian Weiser — Albert-Ludwigs-Universitaet Freiburg, Germany

This presentation will highlight the latest search for Beyond Standard Model (BSM) phenomena within the tt+E_T^miss 1-lepton (1L) final state within the ATLAS experiment. Utilizing proton-proton collision data from LHC Run-2 at √s = 13 TeV with 140 fb⁻¹ of data, Dark Matter (DM) production via scalar/pseudo-scalar mediators and SUSY stop pair production are explored. The improved approach is heavily inspired by Machine Learning techniques using Neural Nets (NN) to first reconstruct hadronically decaying top quarks and then discern signal events from background. Across various kinematic spaces, signal presence is inferred by template fitting the NN output distributions. Furthermore, the improved 1L results are combined with previously published 0L and 2L results for the tt+E_T^miss final state yielding the best limits on stop pair production and DM production via scalar/pseudo-scalar mediators for the ATLAS Run-2 dataset. Additionally, a first time ever interpretation is performed in the context of a search for effective vector contact interactions between top quarks and all three generations of left-handed neutrinos (ttνν).

Keywords: Dark Matter; Supersymmetry; EFT; Machine Learning; Top Reconstruction