The luminosity determination for the ATLAS detector at the LHC during Run 2 is presented, with pp collisions at a centre-of-mass energy $$\sqrt{s}=13$$ TeV. The absolute luminosity scale is determined using van der Meer beam separation scans during dedicated running periods in each year, and extrapolated to the physics data-taking regime using complementary measurements from several luminosity-sensitive detectors. The total uncertainties in the integrated luminosity for each individual year of data-taking range from 0.9% to 1.1%, and are partially correlated between years. After standard data-quality selections, the full Run 2 pp data sample corresponds to an integrated luminosity of $$140.1\pm 1.2$$ $$\hbox {fb}^{-1}$$ , i.e. an uncertainty of 0.83%. A dedicated sample of low-pileup data recorded in 2017–2018 for precision Standard Model physics measurements is analysed separately, and has an integrated luminosity of $$338.1\pm 3.1$$ $$\hbox {pb}^{-1}$$ .
The flavour-tagging algorithms developed by the ATLAS Collaboration and used to analyse its dataset of $$\sqrt{s} = 13$$ TeV pp collisions from Run 2 of the Large Hadron Collider are presented. These new tagging algorithms are based on recurrent and deep neural networks, and their performance is evaluated in simulated collision events. These developments yield considerable improvements over previous jet-flavour identification strategies. At the 77% b-jet identification efficiency operating point, light-jet (charm-jet) rejection factors of 170 (5) are achieved in a sample of simulated Standard Model $$t\bar{t}$$ events; similarly, at a c-jet identification efficiency of 30%, a light-jet (b-jet) rejection factor of 70 (9) is obtained.
This paper presents the observation of four-top-quark ( $$t\bar{t}t\bar{t}$$ ) production in proton-proton collisions at the LHC. The analysis is performed using an integrated luminosity of 140 $$\hbox {fb}^{-1}$$ at a centre-of-mass energy of 13 TeV collected using the ATLAS detector. Events containing two leptons with the same electric charge or at least three leptons (electrons or muons) are selected. Event kinematics are used to separate signal from background through a multivariate discriminant, and dedicated control regions are used to constrain the dominant backgrounds. The observed (expected) significance of the measured $$t\bar{t}t\bar{t}$$ signal with respect to the standard model (SM) background-only hypothesis is 6.1 (4.3) standard deviations. The $$t\bar{t}t\bar{t}$$ production cross section is measured to be $$22.5^{+6.6}_{-5.5}$$ fb, consistent with the SM prediction of $$12.0 \pm 2.4$$ fb within 1.8 standard deviations. Data are also used to set limits on the three-top-quark production cross section, being an irreducible background not measured previously, and to constrain the top-Higgs Yukawa coupling and effective field theory operator coefficients that affect $$t\bar{t}t\bar{t}$$ production.
The identification of b-jets, referred to as b-tagging, is an important part of many physics analyses in the ATLAS experiment at the Large Hadron Collider and an accurate calibration of its performance is essential for high-quality physics results. This publication describes the calibration of the light-flavour jet mistagging efficiency in a data sample of proton–proton collision events at $$\sqrt{s}=13$$ TeV corresponding to an integrated luminosity of 139 fb $$^{-1}$$ . The calibration is performed in a sample of Z bosons produced in association with jets. Due to the low mistagging efficiency for light-flavour jets, a method which uses modified versions of the b-tagging algorithms referred to as flip taggers is used in this work. A fit to the jet-flavour-sensitive secondary-vertex mass is performed to extract a scale factor from data, to correct the light-flavour jet mistagging efficiency in Monte Carlo simulations, while simultaneously correcting the b-jet efficiency. With this procedure, uncertainties coming from the modeling of jets from heavy-flavour hadrons are considerably lower than in previous calibrations of the mistagging scale factors, where they were dominant. The scale factors obtained in this calibration are consistent with unity within uncertainties.