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The rejection of forward jets originating from additional proton–proton interactions (pile-up) is crucial for a variety of physics analyses at the LHC, including Standard Model measurements and searches for physics beyond the Standard Model. The identification of such jets is challenging due to the lack of track and vertex information in the pseudorapidity range |η| > 2.5. This paper presents a novel strategy for forward pile-up jet tagging that exploits jet shapes and topological jet correlations in pile-up interactions. Measurements of the per-jet tagging efficiency are presented using a data set of 3.2 fb-1 of proton–proton collisions at a centre-of-mass energy of 13 TeV collected with the ATLAS detector. The fraction of pile-up jets rejected in the range 2.5 < |η| < 4.5 is estimated in simulated events with an average of 22 interactions per bunch-crossing. It increases with jet transverse momentum and, for jets with transverse momentum between 20 and 50 GeV, it ranges between 49% and 67% with an efficiency of 85% for selecting hard-scatter jets. A case study is performed in Higgs boson production via the vector-boson fusion process, showing that these techniques mitigate the background growth due to additional proton–proton interactions, thus enhancing the reach for such signatures.

This paper presents the method and performance of primary vertex reconstruction in proton–proton collision data recorded by the ATLAS experiment during Run 1 of the LHC. The studies presented focus on data taken during 2012 at a centre-of-mass energy of $\\sqrt{s} = 8$ TeV. The performance has been measured as a function of the number of interactions per bunch crossing over a wide range, from one to seventy. The measurement of the position and size of the luminous region and its use as a constraint to improve the primary vertex resolution are discussed. A longitudinal vertex position resolution of about $30 \\mu m$ is achieved for events with high multiplicity of reconstructed tracks. The transverse position resolution is better than $20 \\mu m$ and is dominated by the precision on the size of the luminous region. An analytical model is proposed to describe the primary vertex reconstruction efficiency as a function of the number of interactions per bunch crossing and of the longitudinal size of the luminous region. Agreement between the data and the predictions of this model is better than 3% up to seventy interactions per bunch crossing.

The reconstruction and calibration algorithms used to calculate missing transverse momentum ( $E_{\\text {T}}^{\\text {miss}}$ ) with the ATLAS detector exploit energy deposits in the calorimeter and tracks reconstructed in the inner detector as well as the muon spectrometer. Various strategies are used to suppress effects arising from additional proton–proton interactions, called pileup, concurrent with the hard-scatter processes. Tracking information is used to distinguish contributions from the pileup interactions using their vertex separation along the beam axis. The performance of the $E_{\\text {T}}^{\\text {miss}}$ reconstruction algorithms, especially with respect to the amount of pileup, is evaluated using data collected in proton–proton collisions at a centre-of-mass energy of 8 $\\text {TeV}$ during 2012, and results are shown for a data sample corresponding to an integrated luminosity of $20.3\\, \\mathrm{fb}^{-1}$ . The simulation and modelling of $E_{\\text {T}}^{\\text {miss}}$ in events containing a Z boson decaying to two charged leptons (electrons or muons) or a W boson decaying to a charged lepton and a neutrino are compared to data. The acceptance for different event topologies, with and without high transverse momentum neutrinos, is shown for a range of threshold criteria for $E_{\\text {T}}^{\\text {miss}}$ , and estimates of the systematic uncertainties in the $E_{\\text {T}}^{\\text {miss}}$ measurements are presented.

A search for direct production of top squark pairs in events with jets and large transverse momentum imbalance is presented. The data are based on proton-proton collisions at a center-of-mass energy of 13 TeV, collected with the CMS detector in 2016 at the CERN LHC, and correspond to an integrated luminosity of 35.9 fb$^{−1}$. The search considers a variety of R-parity conserving supersymmetric models, including ones for which the top squark and neutralino masses are nearly degenerate. Specialized jet reconstruction tools are developed to exploit the unique characteristics of the signal topologies. With no significant excess of events observed above the standard model expectations, upper limits are set on the direct top squark pair production cross section in the context of simplified supersymmetric models for various decay hypotheses. Models with larger differences in mass between the top squark and neutralino are probed for masses up to 1040 and 500 GeV, respectively, whereas models with a more compressed mass hierarchy are probed up to 660 and 610 GeV, respectively. The smallest mass difference probed is for masses near to 550 and 540 GeV, respectively.

The reconstruction of the signal from hadrons and jets emerging from the proton–proton collisions at the Large Hadron Collider (LHC) and entering the ATLAS calorimeters is based on a three-dimensional topological clustering of individual calorimeter cell signals. The cluster formation follows cell signal-significance patterns generated by electromagnetic and hadronic showers. In this, the clustering algorithm implicitly performs a topological noise suppression by removing cells with insignificant signals which are not in close proximity to cells with significant signals. The resulting topological cell clusters have shape and location information, which is exploited to apply a local energy calibration and corrections depending on the nature of the cluster. Topological cell clustering is established as a well-performing calorimeter signal definition for jet and missing transverse momentum reconstruction in ATLAS.