Combination of searches for heavy spin-1 resonances using 139 fb−1 of proton-proton collision data at √s = 13 TeV with the ATLAS detector

A combination of searches for new heavy spin-1 resonances decaying into diferent pairings of W, Z, or Higgs bosons, as well as directly into leptons or quarks, is presented. The data sample used corresponds to 139 fb−1 of proton-proton collisions at √ s = 13 TeV collected during 2015–2018 with the ATLAS detector at the CERN Large Hadron Collider. Analyses selecting quark pairs (qq, bb, tt¯, and tb) or third-generation leptons (τν and τ τ ) are included in this kind of combination for the frst time. A simplifed model predicting a spin-1 heavy vector-boson triplet is used. Cross-section limits are set at the 95% confdence level and are compared with predictions for the benchmark model. These limits are also expressed in terms of constraints on couplings of the heavy vector-boson triplet to quarks, leptons, and the Higgs boson. The complementarity of the various analyses increases the sensitivity to new physics, and the resulting constraints are stronger than those from any individual analysis considered. The data exclude a heavy vector-boson triplet with mass below 5.8 TeV in a weakly coupled scenario, below 4.4 TeV in a strongly coupled scenario, and up to 1.5 TeV in the case of production via vector-boson fusion

Search for new phenomena with top-quark pairs and large missing transverse momentum using 140 fb−1 of pp collision data at \sqrt{s} = 13 TeV with the ATLAS detector

A search is conducted for new phenomena in events with a top quark pair and large missing transverse momentum, where the top quark pair is reconstructed in final states with one isolated electron or muon and multiple jets. The search is performed using the Large Hadron Collider proton-proton collision data sample at a centre-of-mass energy of \sqrt{s} = 13 TeV recorded by the ATLAS detector that corresponds to an integrated luminosity of 140 fb^{−1}. An analysis based on neural network classifiers is optimised to search for directly produced pairs of supersymmetric partners of the top quark (stop), and to search for spin-0 mediators, produced in association with a pair of top quarks, that decay into dark-matter particles. In the stop search, the analysis is designed to target models in which the mass difference between the stop and the neutralino from the stop decay is close to the top quark mass. This new search is combined with previously published searches in final states with different lepton multiplicities. No significant excess above the Standard Model background is observed, and limits at 95% confidence level are set. Models with neutralinos with masses up to 570 GeV are excluded, while for small neutralino masses models are excluded for stop masses up to 1230 GeV. Scalar (pseudoscalar) dark matter mediator masses as large as 350 (370) GeV are excluded when the coupling strengths of the mediator to Standard Model and dark-matter particles are both set to one. At lower mediator masses, models with production cross-sections as small as 0.15 (0.16) times the nominal predictions are excluded. Results of this search are also used to set constraints on effective four-fermion contact interactions between top quarks and neutrinos

Accuracy versus precision in boosted top tagging with the ATLAS detector

Abstract The identification of top quark decays where the top quark has a large momentum transverse to the beam axis, known as top tagging, is a crucial component in many measurements of Standard Model processes and searches for beyond the Standard Model physics at the Large Hadron Collider. Machine learning techniques have improved the performance of top tagging algorithms, but the size of the systematic uncertainties for all proposed algorithms has not been systematically studied. This paper presents the performance of several machine learning based top tagging algorithms on a dataset constructed from simulated proton-proton collision events measured with the ATLAS detector at √ s = 13 TeV. The systematic uncertainties associated with these algorithms are estimated through an approximate procedure that is not meant to be used in a physics analysis, but is appropriate for the level of precision required for this study. The most performant algorithms are found to have the largest uncertainties, motivating the development of methods to reduce these uncertainties without compromising performance. To enable such efforts in the wider scientific community, the datasets used in this paper are made publicly available.</jats:p

Search for light long-lived particles in pp collisions at √s = 13 TeV using displaced vertices in the ATLAS inner detector

A search for long-lived particles (LLPs) using 140 fb−1 of pp collision data with √s = 13 TeV recorded by the ATLAS experiment at the LHC is presented. The search targets LLPs with masses between 5 and 55 GeV that decay hadronically in the ATLAS inner detector. Benchmark models with LLP pair production from exotic decays of the Higgs boson and models featuring long-lived axionlike particles (ALPs) are considered. No significant excess above the expected background is observed. Upper limits are placed on the branching ratio of the Higgs boson to pairs of LLPs, the cross section for ALPs produced in association with a vector boson, and, for the first time, on the branching ratio of the top quark to an ALP and a u/c quark