This article documents the muon reconstruction and identification efficiency obtained by the ATLAS experiment for 139 $$\hbox {fb}^{-1}$$fb-1 ofppcollision data at $$\sqrt{s}=13$$s=13 TeV collected between 2015 and 2018 during Run 2 of the LHC. The increased instantaneous luminosity delivered by the LHC over this period required a reoptimisation of the criteria for the identification of prompt muons. Improved and newly developed algorithms were deployed to preserve high muon identification efficiency with a low misidentification rate and good momentum resolution. The availability of large samples of $$Z\rightarrow \mu \mu $$Z→μμ and $$J/\psi \rightarrow \mu \mu $$J/ψ→μμ decays, and the minimisation of systematic uncertainties, allows the efficiencies of criteria for muon identification, primary vertex association, and isolation to be measured with an accuracy at the per-mille level in the bulk of the phase space, and up to the percent level in complex kinematic configurations. Excellent performance is achieved over a range of transverse momenta from 3 GeV to several hundred GeV, and across the full muon detector acceptance of $$|\eta |<2.7$$|η|<2.7 .

Jet energy scale and resolution measurements with their associated uncertainties are reported for jets using 36–81 fb $$^{-1}$$-1 of proton–proton collision data with a centre-of-mass energy of $$\sqrt{s}=13$$s=13 $${\text {Te}}{\text {V}}$$TeV collected by the ATLAS detector at the LHC. Jets are reconstructed using two different input types: topo-clusters formed from energy deposits in calorimeter cells, as well as an algorithmic combination of charged-particle tracks with those topo-clusters, referred to as the ATLAS particle-flow reconstruction method. The anti- $$k_t$$kt jet algorithm with radius parameter $$R=0.4$$R=0.4 is the primary jet definition used for both jet types. This result presents new jet energy scale and resolution measurements in the high pile-up conditions of late LHC Run 2 as well as a full calibration of particle-flow jets in ATLAS. Jets are initially calibrated using a sequence of simulation-based corrections. Next, several in situ techniques are employed to correct for differences between data and simulation and to measure the resolution of jets. The systematic uncertainties in the jet energy scale for central jets ( $$|\eta |<1.2$$|η|<1.2 ) vary from 1% for a wide range of high- $$p_{{\text {T}}}$$pT jets ( $$250<p_{{\text {T}}} <2000~{\text {Ge}}{\text {V}}$$250<pT<2000GeV ), to 5% at very low $$p_{{\text {T}}}$$pT ( $$20~{\text {Ge}}{\text {V}}$$20GeV ) and 3.5% at very high $$p_{{\text {T}}}$$pT ( $$>2.5~{\text {Te}}{\text {V}}$$>2.5TeV ). The relative jet energy resolution is measured and ranges from ( $$24 \pm 1.5$$24±1.5 )% at 20 $${\text {Ge}}{\text {V}}$$GeV to ( $$6 \pm 0.5$$6±0.5 )% at 300 $${\text {Ge}}{\text {V}}$$GeV .

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 .

We present new measurements of electron scattering from high-momentum nucleons in nuclei. These data allow an improved determination of the strength of two-nucleon correlations for several nuclei, including light nuclei where clustering effects can, for the first time, be examined. The data also include the kinematic region where three-nucleon correlations are expected to dominate.

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.

New Jefferson Lab data are presented on the nuclear dependence of the inclusive cross section from ${}^2\mathrm{H}$, ${}^3\mathrm{He}$, ${}^4\mathrm{He}$, ${}^9\mathrm{Be}$ and ${}^{12}\mathrm{C}$ for $0.3<x<0.9$, $Q^2\approx 3–6{\mathrm{GeV}}^2$. These data represent the first measurement of the EMC effect for ${}^3\mathrm{He}$ at large $x$ and a significant improvement for ${}^4\mathrm{He}$. The data do not support previous $A$-dependent or density-dependent fits to the EMC effect and suggest that the nuclear dependence of the quark distributions may depend on the local nuclear environment.