Correlated long-range mixed-harmonic fluctuations measured in pp, p+Pb and low-multiplicity Pb+Pb collisions with the ATLAS detector

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In situ calibration of large-radius jet energy and mass in 13 TeV proton–proton collisions with the ATLAS detector

The response of the ATLAS detector to largeradius jets is measured in situ using 36.2 fb−1 of √s = 13 TeV proton–proton collisions provided by the LHC and recorded by the ATLAS experiment during 2015 and 2016. The jet energy scale is measured in events where the jet recoils against a reference object, which can be either a calibrated photon, a reconstructed Z boson, or a system of well-measured small-radius jets. The jet energy resolution and a calibration of forward jets are derived using dijet balance measurements. The jet mass response is measured with two methods: using mass peaks formed by W bosons and top quarks with large transverse momenta and by comparing the jet mass measured using the energy deposited in the calorimeter with that using the momenta of charged-particle tracks. The transversemomentum and mass responses in simulations are found to be about 2–3% higher than in data. This difference is adjusted for with a correction factor. The results of the different methods are combined to yield a calibration over a large range of transverse momenta (pT). The precision of the relative jet energy scale is 1–2% for 200 GeV < pT < 2 TeV, while that of the mass scale is 2–10%. The ratio of the energy resolutions in data and simulation is measured to a precision of 10–15% over the same pT range

Performance of top-quark and W -boson tagging with ATLAS in Run 2 of the LHC

The performance of identification algorithms (“taggers”) for hadronically decaying top quarks and W bosons in pp collisions at √s=13 TeV recorded by the ATLAS experiment at the Large Hadron Collider is presented. A set of techniques based on jet shape observables are studied to determine a set of optimal cut-based taggers for use in physics analyses. The studies are extended to assess the utility of combinations of substructure observables as a multivariate tagger using boosted decision trees or deep neural networks in comparison with taggers based on two-variable combinations. In addition, for highly boosted top-quark tagging, a deep neural network based on jet constituent inputs as well as a re-optimisation of the shower deconstruction technique is presented. The performance of these taggers is studied in data collected during 2015 and 2016 corresponding to 36.1 fb −1 for the tt ¯ and γ+jet and 36.7 fb −1 −1 for the dijet event topologies

Measurements of the charge asymmetry in top-quark pair production in the dilepton final state at s √ =8 TeV with the ATLAS detector

Measurements of the top-antitop quark pair production charge asymmetry in the dilepton channel, characterized by two high-pT leptons (electrons or muons), are presented using data corresponding to an integrated luminosity of 20.3  fb−1 from pp collisions at a center-of-mass energy s√=8  TeV collected with the ATLAS detector at the Large Hadron Collider at CERN. Inclusive and differential measurements as a function of the invariant mass, transverse momentum, and longitudinal boost of the tt¯ system are performed both in the full phase space and in a fiducial phase space closely matching the detector acceptance. Two observables are studied: AℓℓC based on the selected leptons and Att¯C based on the reconstructed tt¯ final state. The inclusive asymmetries are measured in the full phase space to be AℓℓC=0.008±0.006 and Att¯C=0.021±0.016, which are in agreement with the Standard Model predictions of AℓℓC=0.0064±0.0003 and Att¯C=0.0111±0.0004

The performance of the jet trigger for the ATLAS detector during 2011 data taking

The performance of the jet trigger for the ATLAS detector at the LHC during the 2011 data taking period is described. During 2011 the LHC provided proton–proton collisions with a centre-of-mass energy of 7 TeV and heavy ion collisions with a 2.76 TeV per nucleon–nucleon collision energy. The ATLAS trigger is a three level system designed to reduce the rate of events from the 40 MHz nominal maximum bunch crossing rate to the approximate 400 Hz which can be written to offline storage. The ATLAS jet trigger is the primary means for the online selection of events containing jets. Events are accepted by the trigger if they contain one or more jets above some transverse energy threshold. During 2011 data taking the jet trigger was fully efficient for jets with transverse energy above 25 GeV for triggers seeded randomly at Level 1. For triggers which require a jet to be identified at each of the three trigger levels, full efficiency is reached for offline jets with transverse energy above 60 GeV. Jets reconstructed in the final trigger level and corresponding to offline jets with transverse energy greater than 60 GeV, are reconstructed with a resolution in transverse energy with respect to offline jets, of better than 4 % in the central region and better than 2.5 % in the forward direction

Measurement of the photon identification efficiencies with the ATLAS detector using LHC Run 2 data collected in 2015 and 2016

The efficiency of the photon identification criteria in the ATLAS detector is measured using 36.1 fb1 to 36.7 fb1 of pp collision data at s√=13 TeV collected in 2015 and 2016. The efficiencies are measured separately for converted and unconverted isolated photons, in four different pseudorapidity regions, for transverse momenta between 10 GeV and 1.5 TeV. The results from the combination of three data-driven techniques are compared with the predictions from simulation after correcting the variables describing the shape of electromagnetic showers in simulation for the average differences observed relative to data. Data-to-simulation efficiency ratios are determined to account for the small residual efficiency differences. These factors are measured with uncertainties between 0.5% and 5% depending on the photon transverse momentum and pseudorapidity. The impact of the isolation criteria on the photon identification efficiency, and that of additional soft pp interactions, are also discussed. The probability of reconstructing an electron as a photon candidate is measured in data, and compared with the predictions from simulation. The efficiency of the reconstruction of photon conversions is measured using a sample of photon candidates from Z→μμγ events, exploiting the properties of the ratio of the energies deposited in the first and second longitudinal layers of the ATLAS electromagnetic calorimeter

Elliptic flow of identified hadrons in Pb-Pb collisions at 1asNN = 2.76 TeV

The elliptic flow coefficient (v2) of identified particles in Pb-Pb collisions at 1asNN = 2.76 TeV was measured with the ALICE detector at the Large Hadron Collider (LHC). The results were obtained with the Scalar Product method, a two-particle corre- lation technique, using a pseudo-rapidity gap of | 06\u3b7| > 0.9 between the identified hadron under study and the reference particles. The v2 is reported for \u3c0\ub1, K\ub1, K0S, p+p, \u3c6, \u39b+\u39b, \u39e 12+\u39e+ and \u3a9 12+\u3a9+ in several collision centralities. In the low transverse momentum (pT) region, pT 3 GeV/c

Food addiction: Prevalence, psychopathological correlates and associations with quality of life in a large sample

Objective To determine the prevalence of food addiction in a large Brazilian non-clinical sample. Sociodemographic and psychopathological correlates of food addiction as well as associations with quality (QoL) domains were also investigated. Methods This cross-sectional study obtained data from a Brazilian anonymous web-based research platform (N = 7639; 71.3% females). Participants provided sociodemographic data and completed the modified Yale Food Addiction Scale 2.0, PHQ-9, hypomania checklist (HCL-32), Fagerstr\uf6m Test for Nicotine Dependence, AUDIT, modified Skin picking-Stanford questionnaire, Minnesota impulsive disorders interview, Symptom Checklist-90-Revised inventory (SCL-90R), early trauma inventory self report-short form, and the WHO Quality of Life instrument-Abbreviated version (WHOQOL-Bref). Associations were adjusted to potential confounders through multivariable models. Results The prevalence of food addiction was 4.32% (95%CI: 3.89\u20134.80%), and was more common among females. Food addiction was associated with a positive screen for a major depressive episode (OR = 4.41; 95%CI: 3.46\u20135.62), bipolar spectrum disorder (OR = 1.98; 95%CI: 1.43\u20132.75), and skin picking disorder (OR = 2.02; 95%CI: 1.31\u20133.09). Food addiction was also independently associated with exposure to early life psychological and sexual abuse (P = 0.008) as well as with reduced physical, psychological, social, and environment QoL (all P < 0.001). Conclusions Food addiction may be common in low and middle-income countries, though possibly less prevalent than in the US. Food addiction was associated with co-occurring mood disorders and skin picking disorder as well as with early life psychological and sexual abuse. Finally, food addiction was independently associated with broad reductions in QoL. Public health efforts towards the early recognition and management of food addiction are warranted. \ua9 2017 Elsevier Lt