The luminosity determination for the ATLAS detector at the LHC during Run 2 is presented, with pp collisions at a centre-of-mass energy $$\sqrt{s}=13$$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 $$140.1\pm 1.2$$140.1 ± 1.2 $$\hbox {fb}^{-1}$$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 $$338.1\pm 3.1$$338.1 ± 3.1 $$\hbox {pb}^{-1}$$pb - 1 .

The flavour-tagging algorithms developed by the ATLAS Collaboration and used to analyse its dataset of $$\sqrt{s} = 13$$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 $$t\bar{t}$$t t ¯ events; similarly, at a c-jet identification efficiency of 30%, a light-jet (b-jet) rejection factor of 70 (9) is obtained.

A search for chargino–neutralino pair production in three-lepton final states with missing transverse momentum is presented. The study is based on a dataset of $$\sqrt{s} = 13$$s = 13 TeV pp collisions recorded with the ATLAS detector at the LHC, corresponding to an integrated luminosity of 139 $$\hbox {fb}^{-1}$$fb - 1 . No significant excess relative to the Standard Model predictions is found in data. The results are interpreted in simplified models of supersymmetry, and statistically combined with results from a previous ATLAS search for compressed spectra in two-lepton final states. Various scenarios for the production and decay of charginos ( $${\tilde{\chi }}^\pm _1$$χ ~ 1 ± ) and neutralinos ( $${\tilde{\chi }}^0_2$$χ ~ 2 0 ) are considered. For pure higgsino $${\tilde{\chi }}^\pm _1{\tilde{\chi }}^0_2$$χ ~ 1 ± χ ~ 2 0 pair-production scenarios, exclusion limits at 95% confidence level are set on $${\tilde{\chi }}^0_2$$χ ~ 2 0 masses up to 210 GeV. Limits are also set for pure wino $${\tilde{\chi }}^\pm _1{\tilde{\chi }}^0_2$$χ ~ 1 ± χ ~ 2 0 pair production, on $${\tilde{\chi }}^0_2$$χ ~ 2 0 masses up to 640 GeV for decays via on-shell W and Z bosons, up to 300 GeV for decays via off-shell W and Z bosons, and up to 190 GeV for decays via W and Standard Model Higgs bosons.

The ATLAS experiment at the Large Hadron Collider has a broad physics programme ranging from precision measurements to direct searches for new particles and new interactions, requiring ever larger and ever more accurate datasets of simulated Monte Carlo events. Detector simulation with Geant4 is accurate but requires significant CPU resources. Over the past decade, ATLAS has developed and utilized tools that replace the most CPU-intensive component of the simulation—the calorimeter shower simulation—with faster simulation methods. Here, AtlFast3, the next generation of high-accuracy fast simulation in ATLAS, is introduced. AtlFast3 combines parameterized approaches with machine-learning techniques and is deployed to meet current and future computing challenges, and simulation needs of the ATLAS experiment. With highly accurate performance and significantly improved modelling of substructure within jets, AtlFast3 can simulate large numbers of events for a wide range of physics processes.

A technique is presented to measure the efficiency with which c-jets are mistagged as b-jets (mistagging efficiency) using $$t\bar{t}$$t t ¯ events, where one of the W bosons decays into an electron or muon and a neutrino and the other decays into a quark–antiquark pair. The measurement utilises the relatively large and known $$W\rightarrow cs$$W → c s branching ratio, which allows a measurement to be made in an inclusive c-jet sample. The data sample used was collected by the ATLAS detector at $$\sqrt{s} = 13$$s = 13 $$\text {TeV}$$TeV and corresponds to an integrated luminosity of 139 fb $$^{-1}$$- 1 . Events are reconstructed using a kinematic likelihood technique which selects the mapping between jets and $$t\bar{t}$$t t ¯ decay products that yields the highest likelihood value. The distribution of the b-tagging discriminant for jets from the hadronic W decays in data is compared with that in simulation to extract the mistagging efficiency as a function of jet transverse momentum. The total uncertainties are in the range 3–17%. The measurements generally agree with those in simulation but there are some differences in the region corresponding to the most stringent b-jet tagging requirement.