Measurement of the inclusive jet cross-sections in proton-proton collisions at \( \sqrt{s}=8 \) TeV with the ATLAS detector

Journal of High Energy Physics, Sep 2017

Inclusive jet production cross-sections are measured in proton-proton collisions at a centre-of-mass energy of \( \sqrt{s}=8 \) TeV recorded by the ATLAS experiment at the Large Hadron Collider at CERN. The total integrated luminosity of the analysed data set amounts to 20.2 fb−1. Double-differential cross-sections are measured for jets defined by the anti-k t jet clustering algorithm with radius parameters of R = 0.4 and R = 0.6 and are presented as a function of the jet transverse momentum, in the range between 70 GeV and 2.5 TeV and in six bins of the absolute jet rapidity, between 0 and 3.0. The measured cross-sections are compared to predictions of quantum chromodynamics, calculated at next-to-leading order in perturbation theory, and corrected for non-perturbative and electroweak effects. The level of agreement with predictions, using a selection of different parton distribution functions for the proton, is quantified. Tensions between the data and the theory predictions are observed.

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Measurement of the inclusive jet cross-sections in proton-proton collisions at \( \sqrt{s}=8 \) TeV with the ATLAS detector

Received: June 8 TeV with the p ATLAS detector Inclusive jet production cross-sections are measured in proton-proton collisions at a centre-of-mass energy of p s = 8 TeV recorded by the ATLAS experiment at the Large Hadron Collider at CERN. The total integrated luminosity of the analysed data set amounts to 20:2 fb 1 . Double-di erential cross-sections are measured for jets de ned by the anti-kt jet clustering algorithm with radius parameters of R = 0:4 and R = 0:6 and are presented as a function of the jet transverse momentum, in the range between 70 GeV and 2.5 TeV and in six bins of the absolute jet rapidity, between 0 and 3:0. The measured cross-sections are compared to predictions of quantum chromodynamics, calculated at next-to-leading order in perturbation theory, and corrected for non-perturbative and electroweak e ects. The level of agreement with predictions, using a selection of di erent parton distribution functions for the proton, is quanti ed. Tensions between the data and the theory predictions are observed. Hadron-Hadron scattering (experiments); Jet physics 1 Introduction Event and jet selection 6 Jet energy calibration and resolution Jet reconstruction Jet energy calibration Jet energy scale uncertainties Jet energy resolution and uncertainties Jet angular resolution and uncertainties 2 3 5 7 8 9 6.1 6.2 6.3 6.4 6.5 9.1 9.2 9.3 9.4 { 1 { Unfolding of detector e ects Propagation of the statistical and systematic uncertainties Theoretical predictions Next-to-leading-order QCD calculation Electroweak corrections Non-perturbative corrections NLO QCD matched with parton showers and hadronisation 10 Results 10.1 Qualitative comparisons of data to NLO QCD calculations 10.2 Quantitative comparison of data to NLO QCD calculations 10.3 Quantitative comparison of data to NLO QCD calculations with alternative 10.4 Comparisons with NLO QCD calculation including parton showers and fragcorrelation scenarios mentation 11 Conclusion correlation scenarios The ATLAS collaboration A Quantitative comparison of data to NLO QCD calculations with alternate Introduction The Large Hadron Collider (LHC) [ 1 ] at CERN, colliding protons on protons, provides a unique opportunity to explore the production of hadronic jets in the TeV energy range. In Quantum Chromodynamics (QCD), jet production can be interpreted as the fragmentation of quarks and gluons produced in a short-distance scattering process. The inclusive jet production cross-section (p + p ! jet + X) gives valuable information about the strong coupling constant ( s) and the structure of the proton. It is also among the processes directly testing the experimentally accessible space-time distances. Next-to-leading-order (NLO) perturbative QCD calculations [ 2, 3 ] give quantitative rst calculations of some sub-processes [10, 11], the complete NNLO QCD inclusive jet cross-section calculation was published recently [12]. As xed-order QCD calculations only make predictions for the quarks and gluons associated with the short-distance scattering process, corrections for the fragmentation of these partons to particles need to be applied. The measurements can also be compared to Monte Carlo event generator predictions that directly simulate the particles entering the detector. These event generators can be based on calculations with leading-order (LO) or NLO accuracy for the description of the short-distance scattering process as well as additional QCD radiation, hadronisation and multiple parton interactions [13]. Inclusive jet production cross-sections have been measured in proton-antiproton collisions at the Tevatron collider at various centre-of-mass energies. The latest and most precise measurements at p s = 1:96 TeV can be found in refs. [14, 15]. At the LHC, the ALICE, p s = 13 TeV [25]. ATLAS and CMS collaborations have measured inclusive jet cross-sections in proton-proton collisions at centre-of-mass energies of p s = 2:76 TeV [16{18] and p and recently the CMS Collaboration has also measured them at p s = 7 TeV [19{23], s = 8 TeV [24] and This paper presents the measurement of the inclusive jet cross-sections in protonproton collisions at a centre-of-mass energy of p s = 8 TeV using data collected by the ATLAS experiment in 2012 corresponding to an integrated luminosity of 20:2 fb 1 . The cross-sections are measured double-di erentially and presented as a function of the jet transverse momentum, pT, in six equal-width bins of the absolute jet rapidity, jyj. Jets are reconstructed using the anti-kt jet clustering algorithm [26] with radius parameters of R = 0:4 and R = 0:6. The measurement is performed for two jet radius parameters, since the uncertainties in the theoretical predictions are di erent. The kinematic region of 70 GeV pT 2:5 TeV and jyj < 3 is covered. The measurements explore a higher centre-of-mass energy than the previous ATLAS measurements and are also more precise due to the higher integrated luminosity and the better knowledge of the jet energy measurement uncertainties. Fixed-order NLO QCD predictions calculated for a suite of proton parton distribution function (PDF) sets, corrected for non-perturbative (hadronisation and underlying event) and electroweak e ects, are quantitatively compared to the measurement results, unfolded for detector e ects. The { 2 { results are also compared to the predictions of a Monte Carlo event generator based on the NLO QCD calculation for the short-distance scattering process matched with parton showers, followed by hadronisation. The measurement is performed with two di erent jet radius parameters to test the sensitivity to perturbative (higher-order corrections and parton shower) and non-perturbative e ects. The outline of the paper is as follows. A brief description of the ATLAS detector is given in section 2. The inclusive jet production cross-section is de ned in section 4. Section 3 gives an overview of the data set and Monte Carlo simulations used. The details of the experimental measurement are presented in the next sections. Section 5 describes the event and jet selection for the measurement. The jet energy calibration and the uncertainmeasurements to the theory predictions are presented in section 10. 2 ATLAS detector The ATLAS experiment [27] at the LHC is a multipurpose particle detector with a forwardbackward symmetric cylindrical geometry and a near 4 coverage in solid angle.1 It consists of an inner tracking detector surrounded by a thin superconducting solenoid providing a 2 T axial magnetic eld, electromagnetic and hadron calorimeters, and a muon spectrometer. The inner tracking detector covers the pseudorapidity range j j < 2:5 and is made of silicon pixel, silicon microstrip, and transition-radiation tracking detectors. Lead/liquid-argon (LAr) sampling calorimeters provide electromagnetic (EM) energy measurements with high granularity. A hadron (steel/scintillator-tile) calorimeter covers the central pseudorapidity range (j j < 1:7). The endcap and forward regions are instrumented with LAr calorimeters for EM and hadronic energy measurements up to j j = 4:9. The muon spectrometer surrounds the calorimeters and is based on three large air-core toroid superconducting magnets with eight coils each. Its bending power ranges between 2.0 and 6.0 T m for most of the detector. A three-level trigger system is used to select events. The rst-level trigger is implemented in hardware and uses a subset of the detector information to reduce the accepted event rate to at most 75 kHz. This is followed by two software-based trigger levels that together reduce the accepted event rate to 400 Hz on average depending on the data-taking conditions during 2012. plane, angle the jet rapidity. The relevant systems used to select events with jets are the minimum-bias trigger scintillators (MBTS), located in front of the endcap cryostats covering 2:1 < j j < 3:8, as well as calorimeter-based jet triggers covering j j < 3:2 for central jets [28]. 1ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP)in the centre of the detector and the z-axis along the beam pipe. The x-axis points from the IP to the centre of the LHC ring, and the y-axis points upwards. Cylindrical coordinates (r; ) are used in the transverse being the azimuthal angle around the z-axis. The pseudorapidity is de ned in terms of the polar as = ln tan( =2). Angular distance is measured in units of R p( y)2 + ( )2, where y is { 3 { p The measurement uses proton-proton collision data at a centre-of-mass energy of s = 8 TeV collected by the ATLAS detector during the data-taking period of the LHC in 2012. The LHC beams were operated with proton bunches organised in \bunch trains", with bunch-crossing intervals (or bunch spacing) of 50 ns. The absolute luminosity measurement is derived from beam-separation scans performed in November 2012 and corresponds to 20:2 fb 1 with an uncertainty of 1:9%. The uncertainty in the luminosity is determined following the technique described in refs. [29]. The average number of interactions per bunch crossing, h i, was 10 h i events considered in this analysis have good detector status and data quality. 36. All data For the simulation of the detector response to scattered particles in proton-proton collisions, events are generated with the Pythia 8 [30] (v8.160) Monte Carlo event generator. It uses LO QCD matrix elements for 2 ! 2 processes, along with a leading-logarithmic (LL) pT-ordered parton shower [31] including photon radiation, underlying-event simulation with multiple parton interactions [32], and hadronisation with the Lund string model [33]. The MC event generator's parameter values are set according to the AU2 underlying event tune [34] and the CT10 PDF set [ 35 ] is used. The stable particles from the generated events are passed through the ATLAS detector simulation [ 36 ] based on the Geant4 software toolkit [ 37 ] and are reconstructed using the same version of the ATLAS software as used to process the data. E ects from multiple proton-proton interactions in the same and neighbouring bunch crossings (pile-up) are included by overlaying inclusive proton-proton collision events (minimum bias), which consist of single-, double- and non-di ractive collisions generated by the Pythia 8 event generator using the A2 tune [34] based on the MSTW2008 LO PDF set [ 38 ]. The Monte Carlo events are weighted such that the distribution of the generated mean number of proton-proton collisions per bunch crossing matches that of the corresponding data-taking period. The particles from additional interactions are added before the signal digitisation and reconstruction steps of the detector simulation, but are not considered a signal and are therefore not used in the de nition of the cross-section measurement de ned in section 4. For the evaluation of non-perturbative e ects, the Pythia 8 [30] (v8.186) and Herwig++ [ 39 ] (v2.7.1) [ 40 ] event generators are also employed as described in section 9.3. The latter also uses LO matrix elements for the 2 ! 2 short-distance process together with a LL angle-ordered parton shower [ 41 ]. It implements an underlying-event simulation based on an eikonal model [ 42 ] and the hadronisation process based on the cluster model [43]. The Powheg [44{46] method provides MC event generation based on an NLO QCD calculation matched to LL parton showers using the Powheg Box 1.0 package [47]. In this simulation the CT10 PDF set [ 35 ] is used. The simulation of parton showers, the hadronisation and the underlying event is based on Pythia 8 [30] using the AU2 tune [34]. These predictions are refered to as the Powheg predictions in the following. The renormalisation and factorisation scales for the xed-order NLO prediction are set to the transverse momentum of each of the outgoing partons of the 2 ! 2 process, pBTorn. { 4 { In addition to the hard scatter, Powheg also generates the hardest partonic emission in the event using the LO 2 ! 3 matrix element or parton showers. The radiative emissions in the parton showers are limited by the matching scale M provided by Powheg. 4 Inclusive jet cross-section de nition Jets are identi ed with the anti-kt [26] clustering algorithm using the four-momentum recombination scheme, implemented in the FastJet [48] library, using two values of the jet radius parameter, R = 0:4 and R = 0:6. Throughout this paper, the jet cross-section measurements refer to jets built from stable particles de ned by having a proper mean decay length of c > 10 mm. Muons and neutrinos from decaying hadrons are included in this de nition. More information about the particle de nition can be found in ref. [49]. These jets are called \particle-level" jets in the following. The inclusive jet double-di erential cross-section, d2 =dpTdy, is measured as a function of the jet transverse momentum pT in bins of rapidity y. In this context, \inclusive" crosssection means that all reconstructed jets in accepted events contribute to the measurement in the bins corresponding to their pT and y values. The kinematic range of the measurement is 70 GeV pT 2:5 TeV and jyj < 3. 5 Event and jet selection A set of single-jet triggers with various pT thresholds are used to preselect events to be recorded. The highest threshold trigger accepts all events passing the threshold. To keep the trigger rate to an acceptable level, the triggers with lower pT thresholds are only read out for a fraction of all events. A pT-dependent trigger strategy is adopted in order to optimise the statistical power of the measurement. Trigger e ciencies are studied using the trigger decisions in samples selected by lower-threshold jet triggers. The e ciency of the lowest pT jet trigger is determined with an independent trigger based on the MBTS scintillators. For each measurement bin, the trigger is chosen such that the highest e ective luminosity (i.e. the lowest prescale factor) is obtained and the trigger is fully e cient. This procedure is performed separately for each of the jet radius parameters and for each jet rapidity bin. At least one reconstructed vertex with at least two associated well-reconstructed tracks is required. Jet quality criteria are applied to reject jets from beam-gas events, beam-halo events, cosmic-ray muons and calorimeter noise bursts following the procedure described in ref. [50]. In the 2012 data set the central hadron calorimeter had a few modules turned o for certain long time periods or su ered from power-supply trips that made them nonoperational for a few minutes. The energy deposited in these modules is estimated using the energy depositions in the neighbouring modules [50]. This correction overestimates the true deposited energy. Therefore, events where a jet with pT 40 GeV points to such a calorimeter region are rejected both in data and simulation. { 5 { 6.1 Jet energy calibration and resolution Jet reconstruction Jets are de ned with the anti-kt clustering algorithm with the jet radius parameters R = 0:4 and R = 0:6. The input objects for the jet algorithm are three-dimensional topological clusters (topoclusters) [51, 52] built from the energy deposits in calorimeter cells. A local cluster weighting calibration (LCW) based on the topology of the calorimeter energy deposits is then applied to each topocluster to improve the energy resolution for hadrons impinging on the calorimeter [51, 52]. The four-momentum of the LCW-scale jet is de ned as the sum of four-momenta of the locally calibrated clusters in the calorimeter treating HJEP09(217) each cluster as a four-momentum with zero mass. 6.2 Jet energy calibration Jets are calibrated using the procedure described in refs. [50, 51]. The jet energy is corrected for the e ect of multiple proton-proton interactions (pile-up) both in collision data and in simulated events. Further corrections depending on the jet energy and the jet pseudorapidity ( ) are applied to achieve a calibration that matches the energy of jets composed of stable particles in simulated events. Fluctuations in the particle content of jets and in hadronic calorimeter showers are reduced with the help of observables characterising internal jet properties. These corrections are applied sequentially (Global Sequential Calibration). Di erences between data and Monte Carlo simulation are evaluated using insitu techniques exploiting the pT balance of a jet and a well-measured object such as a photon ( +jet balance), a Z boson (Z+jet balance) or a system of jets (multijet balance). These processes are used to calibrate the jet energy in the central detector region, while the pT balance in dijet events is used to achieve an intercalibration of jets in the forward region with respect to central jets (dijet balance). The calibration procedure that establishes the jet energy scale (JES) and the associated systematic uncertainty is given in more detail in the following: Pile-up correction. Jets are corrected for the contributions from additional protonproton interactions within the same (in-time) or nearby (out-of-time) bunch crossings [53]. First, for each event a correction based on the jet area and the median pT density [ 54, 55 ] is calculated. The jet area is a measure of the susceptibility of the jet to pile-up and is determined for each jet. The density, , is a measure of the pile-up activity in the event. Subsequently, an average o set subtraction is performed based on the number of additional interactions and reconstructed vertices (NPV ) in the event. It is derived by comparing reconstructed calorimeter jets, with the jet-area correction applied, to particle jets in simulated inclusive jet events. The correction for contributions from additional proton-proton interactions can also remove part of the soft physics contributions, e.g. the contribution from the underlying event. This contribution is restored on average by the MC-based jet energy scale correction discussed below. The impact of pile-up subtraction on the jet energy resolution is corrected for in the unfolding step (see section 7). { 6 { Jet energy scale. The energy and the direction of jets are corrected for instrumental e ects (non-compensating response of the calorimeter, energy losses in dead material, and out-of-cone e ects) and the jet energy scale is restored on average to that of the particles entering the calorimeter using an inclusive jet Monte Carlo simulation [ 56 ]. These corrections are derived in bins of energy and the pseudorapidity of the jet. Global sequential correction. The topology of the calorimeter energy deposits and of the tracks associated with jets can be exploited to correct for uctuations in the jet's particle content [51, 57]. The measured mean jet energy depends on quantities such as the number of tracks, the radial extent of the jets as measured from the tracks in the jets, the longitudinal and lateral extent of the hadronic shower in the calorimeter and the hits in the muon detector associated with the jet. A correction of the jet energy based on these quantities can therefore improve the jet resolution and reduce the dependence on jet fragementation e ects. The correction is constructed from a MC sample based on one generator such that the jet energy scale correction is unchanged for the inclusive jet sample, but the jet energy resolution is improved and the sensitivity to jet fragmentation e ects such as di erences between quarkor gluon-induced jets is moderated. The dependence of this correction on the MC generator is treated as uncertainty. Correction for di erence between data and Monte Carlo simulation. A residual calibration is applied to correct for remaining di erences between the jet energy response in data and simulation. This correction is derived insitu by comparing the results of +jet, Z+jet, dijet and multijet pT-balance techniques [ 56, 58, 59 ]. The level of agreement between the jet energy response in the Monte Carlo simulation and the one in the data is evaluated by exploiting the pT balance between a photon or a Z boson and a jet. In the pT range above about 800 GeV, which cannot be reached by +jet events, the recoil system of low-pT jets in events with more than two jets is used (multijet balance). This correction is applied to the central detector region. The relative response in all detector regions is equalised using an intercalibration method that uses the pT balance in dijet events where one jet is central and one jet is in the forward region of the detector ( -intercalibration). In the region above pT = 1:7 TeV, where the insitu techniques do not have su cient statistical precision, the uncertainty in the jet energy measurement is derived from single-hadron response measurements [60, 61]. 6.3 Jet energy scale uncertainties The jet calibration corrections are combined following the procedure described in ref. [ 56 ]. The systematic and statistical uncertainties of each of the above mentioned corrections contribute to the total JES uncertainty as independent systematic components. The insitu techniques are based on various processes leading to jets with di erent fragmentation patterns. Di erences in the calorimeter response to jets initiated by quarks { 7 { or gluons in the short-distance processes lead to an additional uncertainty. Limited knowledge of the exact avour composition of the analysed data sample is also considered as an uncertainty. An estimation of avour composition based on the Pythia and the Powheg + Pythia Monte Carlo simulations is used in order to reduce this uncertainty. A systematic uncertainty needs to be assigned to the correction, based on the muon hits behind the jet, that corrects jets with large energy deposition behind the calorimeter (punch-through). In total, 66 independent systematic components uncorrelated among each other and fully correlated across pT and , constitute the full JES uncertainty in the con guration with the most detailed description of correlations [ 56 ]. A simpli cation is performed in this standard con guration: the -intercalibration statistical uncertainty being treated as one uncertainty component fully correlated between the jet rapidity and pT bins for which the -intercalibration was performed. However, at the level of precision achieved in this analysis a detailed description of the statistical uncertainties of the -intercalibration calibration procedure is important. For this reason, in this measurement, the total statistical uncertainty of the -intercalibration in the standard con guration is replaced by 240 (250) uncertainty components for jets with R = 0:4 (R = 0:6), propagated from the various bins of the insitu -intercalibration analysis [58]. The total uncertainty in the JES is below 1% for 100 GeV < pT < 1500 GeV in the central detector region (j j 0:8) rising both towards lower and higher pT and larger j j [ 56 ]. 6.4 Jet energy resolution and uncertainties The fractional uncertainty in the jet pT resolution (JER) is derived using the same insitu techniques as used to determine the JES uncertainty from the width of the ratio of the pT of a jet to the pT of a well-measured particle such as a photon or a Z boson [59]. In addition, the balance between the jet transverse momenta in events with two jets at high pT can be used ( -intercalibration) [58]. This method allows measurement of the JER at high jet rapidities and in a wide range of transverse momenta. The results from individual methods are combined similarly to those for the JES [ 56 ]. This JER evaluation includes a correction for physics e ects such as radiation of extra jets which can also alter the pT ratio width. This correction is obtained from a Monte Carlo simulation. The JER uncertainty has in total 11 systematic uncertainty components. Nine systematic components are obtained by combining the systematic uncertainties associated with the insitu methods. The last two are the uncertainty due to the electronic and pileup noise measured in inclusive proton-proton collisions and the absolute JER di erence between data and MC simulation as determined with the insitu methods. The latter is non-zero only for low-pT jets in forward rapidity regions. In the rest of the phase-space region the JER in MC simulation is better than in data and this uncertainty is eliminated by smearing the jet pT in simulation such that the resulting resolution matches closely the one in data. Each JER systematic component describes an uncertainty that is fully correlated in jet pT and pseudorapidity. The 11 JER components are treated independently from each other. { 8 { HJEP09(217) The jet angular resolution (JAR) is estimated from comparisons of the polar angles of a reconstructed jet and the matched particle-level jet using the Monte Carlo simulation. This estimate is cross-checked by comparing the standard jets using calorimeter energy deposits as inputs to the ones using tracks in the inner detector [50, 51]. A relative uncertainty of 10% is assigned to the JAR to account for possible di erences between data and MC simulation. 7 Unfolding of detector e ects The reconstructed jet spectra in data are unfolded to correct for detector ine ciencies and resolution e ects to obtain the inclusive jet cross-section that refers to the stable particles entering the detector. The detector unfolding is based on Monte Carlo simulation and is performed in three consecutive steps, namely, a correction for the matching impurity at reconstruction level, the unfolding for resolution e ects and a correction for the matching ine ciency at particle level, as explained below. In order to account for migrations from lower pT into the region of interest, this study is performed in a wider pT range than the one for the nal result. The unfolding of the detector resolution in jet pT is based on a modi ed Bayesian technique, the Iterative Dynamically Stabilised (IDS) method [62]. This unfolding method uses a transfer matrix describing the migrations of jets across the pT bins, between the particle level and the reconstruction level. A minimal number of iterations in the IDS unfolding method is chosen such that the residual bias, evaluated through a data-driven closure test (see below), is within a tolerance of 1% in the bins with less than 10% statistical uncertainty. In this measurement this is achieved after one iteration. The transfer matrix used in the unfolding is derived by matching a particle level jet with a reconstructed jet in Monte Carlo simulations, when both are closer to each other than to any other jet and lie within a radius of R = 0:3. The matching purity, P, is de ned as the ratio of the number of matched reconstructed jets to the total number of reconstructed jets. The matching e ciency, E , is de ned as the ratio of the number of matched particle jets to the total number of particle jets. If jets migrate to other rapidity bins, they are considered together with the jets that are completely unmatched. In this way the migrations across rapidity bins are e ectively taken into account by bin-to-bin corrections. The nal result is given by X j Ni part = Nj reco Pj Aij = Ei; and N where i and j are the bin indices of the jets at particle- and reconstructed-levels and N reco are the number of particle-level and reconstructed jets in a given bin. The symbol A denotes the unfolding matrix obtained by the IDS method from the transfer matrix. The element Aij describes the probability for a reconstructed jet in pT bin j to originate from particle-level pT bin i. (7.1) part { 9 { The precision of the unfolding technique is assessed using a data-driven closure test [20, 62]. The particle-level pT spectrum in the MC simulation is reweighted such that the reweighted reconstructed spectrum and the data agree. The reconstructed spectrum in this reweighted MC simulation is then unfolded using the same procedure as for the data. The ratio of the unfolded spectrum to the reweighted particle-level spectrum provides an estimate of the unfolding bias. The residual bias is taken into account as a systematic uncertainty. After one IDS iteration, this uncertainty is of the order of a few per mille in the whole phase-space region, except for the very high pT bins in each of the rapidity bins, where it grows to a few percent (up to 15% in certain cases). The statistical and systematic uncertainties are evaluated by repeating the unfolding HJEP09(217) as explained in section 8. 8 Propagation of the statistical and systematic uncertainties The statistical uncertainties are propagated through the unfolding procedure using an ensemble of pseudo-experiments. For each pseudo-experiment in the ensemble, a weight uctuated according to a Poisson distribution with a mean value equal to one is applied to each event in data and simulation. This procedure takes into account the correlation between jets produced in the same event. The unfolding is performed for each pseudoexperiment. An ensemble of 10000 pseudo-experiments is used to calculate a covariance matrix for the cross-section in each jet rapidity bin. The total statistical uncertainty is obtained from the covariance matrix, where bin-to-bin correlations are also encoded. The separate contributions from the data and from the MC statistics are obtained from the same procedure by uctuating only either the data or the simulated events. Furthermore, an overall covariance matrix is constructed to describe the full statistical covariance among all analysis bins. To propagate the JES uncertainties to the measurement, the jet pT is scaled up and down by one standard deviation of each of the components (see section 6) in the MC simulation. The resulting pT spectra are unfolded for detector e ects using the nominal unfolding matrix. The di erence between the nominal unfolded cross-section and the one with the jet pT scaled up and down is taken as a systematic uncertainty. The uncertainty in the JER is the second largest individual source of systematic uncertainty. The e ect of each of the 11 JER systematic uncertainty components is evaluated by smearing the energy of the reconstructed jets in the MC simulation such that the resolution is degraded by the size of each uncertainty component. A new transfer matrix is constructed using the smeared jets and is used to unfold the data spectra. The di erence of the cross-sections unfolded with the jet-energy-smeared transfer matrix and the nominal transfer matrix is taken as a systematic uncertainty. The JER uncertainty is applied symmetrically as an upward and downward variation. The JAR is propagated to the cross-section in the same way as for the JER. The uncertainty associated with the residual model dependence in the unfolding procedure is described in section 7. The systematic uncertainties propagated through the unfolding are evaluated using a set of pseudo-experiments for each component, as in the evaluation of the statistical uncertainties. The use of pseudo-experiments for the evaluation of the systematic uncertainties allows an evaluation of the statistical uctuations. The statistical uctuations of the systematic uncertainties are reduced using a smoothing procedure. For each component, the pT bins are combined until the propagated uncertainty value in the bin has a Poisson statistical signi cance larger than two standard deviations. A Gaussian kernel smoothing [50] is used to restore the original ne bins. An uncertainty for the jet cleaning procedure described in section 5 is estimated from the relative di erence between the e ciencies obtained from the distributions with and without the jet quality cut in data and simulation. The uncertainty in the luminosity measurement of 1:9% [29] is propagated as being correlated across all measurement bins. An uncertainty in the beam energy of 0:1% [63] is considered when comparing data with the theory prediction at a xed beam energy. The induced uncertainty at the crosssection level is evaluated by comparing the theory predictions at the nominal and shifted beam energies. It amounts for 0:2% at low pT and 1% at high pT in the central region and rises up to 3% at highest pT and high rapidity. This uncertainty is similar for jets with R = 0:4 and R = 0:6. The individual systematic uncertainty sources are treated as uncorrelated with each other for the quantitative comparison of the data and the theory prediction. When shown in gures the individual uncertainties are added in quadrature to obtain the total systematic uncertainty. The shape of the systematic uncertainties follows a log-normal distribution, as in the analysis of inclusive jet production at 7 TeV [19]. The systematic uncertainties in the inclusive jet cross-section measurement are shown in gure 1 for representative rapidity regions for anti-kt jets with R = 0:4 and R = 0:6. In the central (forward) region the total uncertainty is about 5% (10%) at medium pT of 300{600 GeV. The uncertainty increases towards both lower and higher pT reaching to 15% at low pT and 50% at high pT. The JES and JER uncertainties for jets with di erent sizes are rather similar at the jet level. However, at the cross-section level di erences occur due to the di erent slopes of the distributions. The dominant systematic uncertainty source for the measurement of the inclusive jet cross-sections is related to the jet energy measurement. The jet energy scale uncertainty is larger than the jet energy resolution uncertainty. 9 9.1 Theoretical predictions Next-to-leading-order QCD calculation The NLOJet++ [64] (v4.1.3) software program is used to calculate the NLO QCD predictions for the 2 ! 2 processes for the inclusive jet cross-sections. The renormalisation and factorisation scales are set to the pT of the leading jet in the event, i.e. R = F = pjet;max. T For fast and exible calculations with various PDFs as well as di erent renormalisation and factorisation scales, the APPLGRID software [65] is interfaced with NLOJet++. 0y.6 t n i 0e.4 r c e 0iv.2 t a l 0 −0.2 −0.4 0y.6 t n i 0e.4 r c e 0iv.2 t a l 0 −0.2 −0.4 Other Statistics Jet energy scale Jet energy resolution Total systematic uncertainty a a t t n n u u Other Statistics Jet energy scale Jet energy resolution Total systematic uncertainty e e R R n i 0e.4 r c Relative systematic uncertainty for the inclusive jet cross-section as a function of the jet transverse momentum pT;jet. The total systematic uncertainty is shown by the black line. The individual uncertainties are shown in colours: the jet energy scale (red), jet energy resolution (yellow) and the other uncertainties (JAR, jet selection, luminosity and unfolding bias) added in quadrature. The results are shown for the (a,b) rst and (c,d) last jet rapidity bins and for anti-kt jets with (a,c) R = 0:4 and (b,d) R = 0:6. The statistical uncertainty is shown by the vertical error bar on each point. The inclusive jet cross-sections are presented for the CT14 [66], MMHT2014 [67], NNPDF3.0 [68], HERAPDF2.0 [69] PDF sets provided by the LHAPDF6 [70] library. The value for the strong coupling constant s is taken from the corresponding PDF set. Three sources of uncertainty in the NLO QCD calculation are considered: the PDFs, the choice of renormalisation and factorisation scales, and the value of s. The PDF uncertainty is de ned at 68% con dence level (CL) and is evaluated following the prescriptions given for each PDF set, as recommended by the PDF4LHC group for PDF-sensitive analyses [71]. The scale uncertainty is evaluated by varying the renormalisation and factorisation scales by a factor of two with respect to the original choice in the calculation. The envelope of the cross-sections with all possible combinations of the scale variations, except the ones when the two scales are varied in opposite directions, is considered as a systematic uncertainty. An alternative scale choice, R = enters the cross-section calculation, is also considered. This scale choice is proposed in ref. [72]. The di erence with respect to the prediction obtained for the pjet;max scale choice is treated as an additional uncertainty. The uncertainty from s is evaluated by calculating the cross-sections using two PDF sets determined with two di erent values of s and then scaling the cross-section di erence corresponding to an s uncertainty s = 0:0015 as T F = pjTet, the pT of each individual jet that recommended in ref. [71]. The uncertainties in the NLO QCD cross-section predictions obtained with the CT14 PDF set are shown in gure 2 for representative phase-space regions. The renormalisation and factorisation scale uncertainty is the dominant uncertainty in most phase-space regions, rising from around 5 10% at low pT in the central rapidity bin to about 50% in the highest pT bins in the most forward rapidity region. This uncertainty is asymmetric and it is larger for anti-kt jets with R = 0:6 than for jets with R = 0:4. The alternative scale choice, pjTet, leads to a similar inclusive jet cross-section at the highest jet pT, but gives an increasingly higher cross-section when the jet pT decreases. For pT = 70 GeV this di erence is about 10%. The PDF uncertainties vary from 5% to 50% depending on the jet pT and rapidity. The s uncertainty is about 3% and is rather constant in the considered phase-space regions. 9.2 Electroweak corrections The NLO QCD predictions are corrected for electroweak e ects derived using an NLO calculation in the electroweak coupling ( ) and based on a LO QCD calculation [ 73 ]. The CTEQ6L1 PDF set is used [ 74 ]. This calculation includes tree-level e ects on the crosssection of O( S; 2) as well as e ects of loops of weak interactions at O( s2). E ects of photon or W=Z radiation are not included in the corrections. Real W=Z radiation may a ect the cross-section by a few percent at pT 1 TeV [ 75 ]. The correction factors were derived in the phase space considered for the measurement presented here and are provided by the authors of ref. [ 73 ] through a private communication. No uncertainty associated with these corrections is presently estimated. Figure 3 shows the electroweak corrections for jets with R = 0:4 and R = 0:6. The correction reaches more than 10% for the highest pT in the lowest rapidity bin, but decreases rapidly as the rapidity increases. It is less than 3% for jets with jyj > 1. 9.3 Non-perturbative corrections In order to compare the xed-order NLO QCD calculations to the measured inclusive jet cross-sections, corrections for non-perturbative (NP) e ects need to be applied. Each −0.3 y0.4 t n i ce0.2 C 0 Q s= 8 TeV N 0 e v i t CT14 PDF set in the (a,b) central and (c,d) forward region for anti-kt jets with (a,c) R = 0:4 and (b,d) R = 0:6. Shown are the uncertainties due to the renormalisation and factorisation scales, the s, the PDF and the total uncertainty. The default scale choice p T jet;max is used. bin of the NLO QCD cross-section is multiplied by the corresponding correction for nonperturbative e ects. The corrections are derived using LO Monte Carlo event generators complemented by the leading-logarithmic parton shower by evaluating the bin-wise ratio of the cross-section with and without the hadronisation and the underlying event processes. 1kc.06 a 1ew.04 r 1tc.02 E 1 0.5≤ |y| <1.0 1fan.12 1kc.06 a 1ew.04 pT for all jet rapidity bins for anti-kt jets with (a) R = 0:4 and (b) R = 0:6. The MC event generators are run twice, once with the hadronisation and underlying event switched on and again with these two processes switched o . The inclusive jet crosssections are built either from the stable particles or from the last partons in the event record, i.e. the partons after the parton showers nished and before the hadronisation process starts. These partons are the ones that are used in the Lund string model and the cluster fragmentation model to form the nal-state hadrons. The bin-by-bin ratios of the inclusive jet cross-sections are taken as an estimate for the non-perturbative corrections. The nominal correction is obtained from the Pythia 8 event generator [30] with the AU2 tune using the CT10 PDF [ 35 ], i.e. the same con guration as used to correct the data for detector e ects (see section 3). The uncertainty is estimated as the envelope of the corrections obtained from a series of alternative Monte Carlo event generator con gurations as shown in table 1. The correction factors are shown in gure 4 in representative rapidity bins for anti-kt jets with R = 0:4 and R = 0:6 as a function of the jet pT. The nominal correction increases the cross-section by 4% (15%) for pT = 70 GeV for anti-kt jets with R = 0:4 (R = 0:6). The large di erences between the two jet sizes result from the di erent interplay of hadronisation and underlying-event e ects. While for anti-kt jets with R = 0:4 the contribution from the hadronisation tends to cancel with the one from the underlying event, for anti-kt jets with R = 0:6 the e ect from the underlying event becomes dominant. At large pT the non-perturbative correction factor is close to 1. There is only a small dependence of the non-perturbative corrections on the jet rapidity. Generator Pythia 8 Tune CTEQ6L [ 74 ] NNPDF2.3L [79, 80] CT10 [ 35 ] CTEQ6L [ 74 ] NNPDF2.3L [79, 80] MRSTW2008lo [81] CTEQ6L [ 74 ] CTEQ6L [ 74 ] UE-EE-4 [82, 83] CTEQ6L [ 74 ] Herwig++ UE-EE-5 [82, 83] MRSTW2008lo [81] perturbative corrections. The name of the generator and the soft physics model tune as well as the PDF set used when deriving the tune is speci ed. The nominal correction is larger than the correction from other MC con gurations. The corrections based on Pythia 8 with the Monash [76] or the A14 [77] tunes give correction factors that are closer to 1. The corrections based on Herwig++ give corrections that are much lower than the one based on Pythia 8. The correction based on Herwig++ is 10% (1%) for pT = 70 GeV for anti-kt jets with R = 0:4 (R = 0:6). 9.4 NLO QCD matched with parton showers and hadronisation The measured inclusive jet cross-section can be directly compared to predictions based on the Powheg Monte Carlo generator where an NLO QCD calculation for the hard scattering 2 ! 2 process is matched to parton showers, hadronisation and underlying event. A procedure to estimate the e ect of the matching of the hard scattering and the parton shower is not yet well established. Therefore, no uncertainties are shown for the Powheg predictions. The Powheg prediction's uncertainty due to PDF is expected to be similar to that in xed-order NLO calculations, whereas the uncertainty due to s is expected to be larger, and the uncertainty due to the renormalisation and factorisation scales smaller. The simulation using a matched parton shower has a more coherent treatment of the e ect of parton showers and hadronisation than the approach using a xed-order NLO QCD calculation corrected for non-perturbative e ects. However, ambiguities in the matching procedure and the tuning of the parton shower parameters based on processes simulated only at leading order by Pythia 8 may introduce additional theoretical uncertainties. Therefore, quantitative comparisons using theoretical uncertainties based on Powheg are not performed in this paper. HJEP09(217) n i1o.15 t rre 1.1 o 0.8 r1.25 t a1.2 c f n i1o.15 t rre 1.1 o 0N.85 ATLAS Simulation 3 10 p T,jet ATLAS Simulation Pythia8 4C­CTEQ6L Pythia8 MONASH­NNPDF2.3L Pythia8 A14­NNPDF2.3L Pythia8 A14­MSTW2008lo Pythia8 A14­CTEQL1 Herwig++ UE­EE­5­CTEQ6L1 Herwig++ UE­EE­5­MRST** Herwig++ UE­EE­4­CTEQ6L1 Uncertainty Pythia8 4C­CTEQ6L Pythia8 MONASH­NNPDF2.3L Pythia8 A14­NNPDF2.3L Pythia8 A14­MSTW2008lo Pythia8 A14­CTEQL1 Herwig++ UE­EE­5­CTEQ6L1 Herwig++ UE­EE­5­MRST** Herwig++ UE­EE­4­CTEQ6L1 Uncertainty HJEP09(217) ATLAS Simulation 80 10 2 2×10 2 3×10 2 p T,jet [GeV] ATLAS Simulation 80 10 2 2×10 2 3×10 2 p T,jet [GeV] and (c,d) most forward region, for jets de ned by the anti-kt algorithm with (a,c) R = 0:4 and (b,d) R = 0:6. The corrections are derived using Pythia 8 and Herwig++ with several soft physics tunes. The envelope of all MC con guration variations is shown as a band. 10 Results 10.1 Qualitative comparisons of data to NLO QCD calculations The measured double-di erential inclusive jet cross-sections are shown in gure 5 and gure 6 as a function of the jet pT for anti-kt jets with R = 0:4 and R = 0:6 for each jet rapidity bin. The cross-section covers 11 orders of magnitude in the central rapidity region and 9 orders of magnitude in the forward region. Jet transverse momenta above pT = 2 TeV [pb 104 10−1 10−2 10−3 10−4 10−5 10−6 10−7 10−8 are shown for jets identi ed using the anti-kt algorithm with R = 0:4. For better visibility the cross-sections are multiplied by the factors indicated in the legend. The data are compared to the NLO QCD prediction with the MMHT2014 PDF set corrected for non-perturbative and electroweak e ects. The error bars indicate the statistical uncertainty and the systematic uncertainty in the measurement added in quadrature. The statistical uncertainty is shown separately by the inner vertical line. are observed. In the most forward region the jet pT reaches about 500 GeV. Tabulated values of all observed results, with full details of uncertainties and their correlations, are also provided in the Durham HEP database [84]. The measurement is compared to an NLO QCD prediction using the MMHT2014 PDF set [67] based on NLOJet++ corrected for non-perturbative and electroweak e ects. The shaded band shows the total theory uncertainty as explained in section 9.1. This theory prediction describes the gross features in the data. The ratio of NLO QCD calculations to data corrected for non-perturbative and electroweak e ects for various PDF sets is shown in gure 7 and gure 8 for anti-kt jets R = 0:4 and R = 0:6, respectively. At low pT the level of agreement is very sensitive to [pb 104 d / σ 2 10 1 10−1 10−2 10−3 10−4 10−5 10−6 10−7 10−8 are shown for jets identi ed using the anti-kt algorithm with R = 0:6. For better visibility the cross-sections are multiplied by the factors indicated in the legend. The data are compared to the NLO QCD prediction with the MMHT2014 PDF set corrected for non-perturbative and electroweak e ects. The error bars indicate the statistical uncertainty and the systematic uncertainty in the measurement added in quadrature. The statistical uncertainty is shown separately by the inner vertical line. non-perturbative e ects. When using Pythia 8 as the nominal non-perturbative correction, the NLO QCD prediction is typically about 10{20% above the data at low pT, whereas the NLO QCD prediction corrected with Herwig++ follows the data well for anti-kt jets with R = 0:4, while it is 5{10% below the data for anti-kt jets with R = 0:6. The comparison is also in uenced by the nominal choice of renormalisation and factorisation scales in the NLO QCD calculation. 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Hamal117, K. Hamano172, A. Hamilton147a, G.N. Hamity141, P.G. Hamnett45, L. Han36a, S. Han35a, K. Hanagaki69;w, K. Hanawa157, M. Hance139, B. Haney124, P. Hanke60a, J.B. Hansen39, J.D. Hansen39, M.C. Hansen23, P.H. Hansen39, K. Hara164, A.S. Hard176, T. Harenberg178, F. Hariri119, S. Harkusha95, R.D. Harrington49, P.F. Harrison173, N.M. Hartmann102, M. Hasegawa70, Y. Hasegawa142, A. Hasib49, S. Hassani138, S. Haug18, R. Hauser93, L. Hauswald47, L.B. Havener38, M. Havranek130, C.M. Hawkes19, R.J. Hawkings32, D. Hayakawa159, D. Hayden93, C.P. Hays122, J.M. Hays79, H.S. Hayward77, S.J. Haywood133, S.J. Head19, T. Heck86, V. Hedberg84, L. Heelan8, K.K. Heidegger51, S. Heim45, T. Heim16, B. Heinemann45;x, J.J. Heinrich102, L. Heinrich112, C. Heinz55, J. Hejbal129, L. Helary32, A. Held171, S. Hellman148a;148b, C. Helsens32, J. Henderson122, R.C.W. Henderson75, Y. Heng176, S. Henkelmann171, A.M. Henriques Correia32, S. Henrot-Versille119, G.H. Herbert17, H. Herde25, V. Herget177, HJEP09(217) G.G. Hesketh81, N.P. Hessey163a, J.W. Hetherly43, S. Higashino69, E. Higon-Rodriguez170, T. Javurek51, M. Javurkova51, F. Jeanneau138, L. Jeanty16, J. Jejelava54a;aa, A. Jelinskas173, P. Jenni51;ab, C. Jeske173, S. Jezequel5, H. Ji176, J. Jia150, H. Jiang67, Y. Jiang36a, Z. Jiang145, S. Jiggins81, J. Jimenez Pena170, S. Jin35a, A. Jinaru28b, O. Jinnouchi159, H. Jivan147c, P. Johansson141, K.A. Johns7, C.A. Johnson64, W.J. Johnson140, K. Jon-And148a;148b, R.W.L. Jones75, S.D. Jones151, S. Jones7, T.J. Jones77, J. Jongmanns60a, P.M. Jorge128a;128b, J. Jovicevic163a, X. Ju176, A. Juste Rozas13;v, M.K. Kohler175, A. Kaczmarska42, M. Kado119, H. Kagan113, M. Kagan145, S.J. Kahn88, T. Kaji174, E. Kajomovitz48, C.W. Kalderon84, A. Kaluza86, S. Kama43, A. Kamenshchikov132, N. Kanaya157, S. Kaneti30, L. Kanjir78, V.A. Kantserov100, J. Kanzaki69, B. Kaplan112, L.S. Kaplan176, D. Kar147c, K. Karakostas10, N. Karastathis10, M.J. Kareem57, E. Karentzos10, S.N. Karpov68, Z.M. Karpova68, K. Karthik112, V. Kartvelishvili75, A.N. Karyukhin132, K. Kasahara164, L. Kashif176, R.D. Kass113, A. Kastanas149, Y. Kataoka157, C. Kato157, A. Katre52, J. Katzy45, K. Kawade105, K. Kawagoe73, T. Kawamoto157, G. Kawamura57, E.F. Kay77, V.F. Kazanin111;c, R. Keeler172, R. Kehoe43, J.S. Keller45, J.J. Kempster80, H. Keoshkerian161, O. Kepka129, B.P. Kersevan78, S. Kersten178, R.A. Keyes90, M. Khader169, F. Khalil-zada12, A. Khanov116, A.G. Kharlamov111;c, T. Kharlamova111;c, A. Khodinov160, T.J. Khoo52, V. Khovanskiy99; , E. Khramov68, J. Khubua54b;ac, S. Kido70, C.R. Kilby80, H.Y. Kim8, S.H. Kim164, Y.K. Kim33, N. Kimura156, O.M. Kind17, B.T. King77, D. Kirchmeier47, J. Kirk133, A.E. Kiryunin103, T. Kishimoto157, D. Kisielewska41a, K. Kiuchi164, O. Kivernyk5, E. Kladiva146b, T. Klapdor-Kleingrothaus51, M.H. Klein38, M. Klein77, U. Klein77, K. Kleinknecht86, P. Klimek110, A. Klimentov27, R. Klingenberg46, T. Klingl23, T. Klioutchnikova32, E.-E. Kluge60a, P. Kluit109, S. Kluth103, J. Knapik42, E. Kneringer65, E.B.F.G. Knoops88, A. Knue103, A. Kobayashi157, D. Kobayashi159, T. Kobayashi157, M. Kobel47, M. Kocian145, P. Kodys131, T. Ko as31, E. Ko eman109, N.M. Kohler103, T. Koi145, M. Kolb60b, I. Koletsou5, A.A. Komar98; , Y. Komori157, T. Kondo69, N. Kondrashova36c, K. Koneke51, A.C. Konig108, T. Kono69;ad, R. Konoplich112;ae, N. Konstantinidis81, R. Kopeliansky64, S. Koperny41a, A.K. Kopp51, K. Korcyl42, K. Kordas156, A. Korn81, A.A. Korol111;c, I. Korolkov13, E.V. Korolkova141, O. Kortner103, S. Kortner103, T. Kosek131, V.V. Kostyukhin23, A. Kotwal48, A. Koulouris10, A. Kourkoumeli-Charalampidi123a;123b, C. Kourkoumelis9, E. Kourlitis141, V. Kouskoura27, A.B. Kowalewska42, R. Kowalewski172, T.Z. Kowalski41a, C. Kozakai157, W. Kozanecki138, A.S. Kozhin132, V.A. Kramarenko101, G. Kramberger78, D. Krasnopevtsev100, M.W. Krasny83, HJEP09(217) J. Kretzschmar77, K. Kreutzfeldt55, P. Krieger161, K. Krizka33, K. Kroeninger46, H. Kroha103, J. Kroll129, J. Kroll124, J. Kroseberg23, J. Krstic14, U. Kruchonak68, H. Kruger23, N. Krumnack67, M.C. Kruse48, M. Kruskal24, T. Kubota91, H. Kucuk81, S. Kuday4b, J.T. Kuechler178, S. Kuehn32, A. Kugel60c, F. Kuger177, T. Kuhl45, V. Kukhtin68, R. Kukla88, Y. Kulchitsky95, S. Kuleshov34b, Y.P. Kulinich169, M. Kuna134a;134b, T. Kunigo71, A. Kupco129, O. Kuprash155, H. Kurashige70, L.L. Kurchaninov163a, Y.A. Kurochkin95, M.G. Kurth35a, V. Kus129, E.S. Kuwertz172, M. Kuze159, J. Kvita117, T. Kwan172, D. Kyriazopoulos141, A. La Rosa103, J.L. La Rosa Navarro26d, L. La Rotonda40a;40b, C. Lacasta170, F. Lacava134a;134b, J. Lacey45, H. Lacker17, D. Lacour83, E. Ladygin68, R. Lafaye5, B. Laforge83, T. Lagouri179, S. Lai57, S. Lammers64, W. Lampl7, E. Lancon27, U. Landgraf51, M.P.J. Landon79, M.C. Lanfermann52, V.S. Lang60a, J.C. Lange13, A.J. Lankford166, F. Lanni27, K. Lantzsch23, A. Lanza123a, A. Lapertosa53a;53b, S. Laplace83, J.F. Laporte138, T. Lari94a, F. Lasagni Manghi22a;22b, M. Lassnig32, P. Laurelli50, W. Lavrijsen16, A.T. Law139, P. Laycock77, T. Lazovich59, M. Lazzaroni94a;94b, B. Le91, O. Le Dortz83, E. Le Guirriec88, E.P. Le Quilleuc138, M. LeBlanc172, T. LeCompte6, F. Ledroit-Guillon58, C.A. Lee27, G.R. Lee133;af, S.C. Lee153, L. Lee59, B. Lefebvre90, G. Lefebvre83, M. Lefebvre172, F. Legger102, C. Leggett16, A. Lehan77, G. Lehmann Miotto32, X. Lei7, W.A. Leight45, M.A.L. Leite26d, R. Leitner131, D. Lellouch175, B. Lemmer57, K.J.C. Leney81, T. Lenz23, B. Lenzi32, R. Leone7, S. Leone126a;126b, C. Leonidopoulos49, G. Lerner151, C. Leroy97, A.A.J. Lesage138, C.G. Lester30, M. Levchenko125, J. Lev^eque5, D. Levin92, L.J. Levinson175, M. Levy19, D. Lewis79, B. Li36a;s, C. Li36a, H. Li150, L. Li36c, Q. Li35a, S. Li48, X. Li36c, Y. Li143, Z. Liang35a, B. Liberti135a, A. Liblong161, K. Lie169, J. Liebal23, W. Liebig15, A. Limosani152, S.C. Lin153;ag, T.H. Lin86, B.E. Lindquist150, A.E. Lionti52, E. Lipeles124, A. Lipniacka15, M. Lisovyi60b, T.M. Liss169, A. Lister171, A.M. Litke139, B. Liu153;ah, H. Liu92, H. Liu27, J.K.K. Liu122, J. Liu36b, J.B. Liu36a, K. Liu88, L. Liu169, M. Liu36a, Y.L. Liu36a, Y. Liu36a, M. Livan123a;123b, A. Lleres58, J. Llorente Merino35a, S.L. Lloyd79, C.Y. Lo62b, F. Lo Sterzo153, E.M. Lobodzinska45, P. Loch7, F.K. Loebinger87, K.M. Loew25, A. Loginov179; , T. Lohse17, K. Lohwasser45, M. Lokajicek129, B.A. Long24, J.D. Long169, R.E. Long75, L. Longo76a;76b, K.A. Looper113, J.A. Lopez34b, D. Lopez Mateos59, I. Lopez Paz13, A. Lopez Solis83, J. Lorenz102, N. Lorenzo Martinez5, M. Losada21, P.J. Losel102, X. Lou35a, A. Lounis119, J. Love6, P.A. Love75, H. Lu62a, N. Lu92, Y.J. Lu63, H.J. Lubatti140, C. Luci134a;134b, A. Lucotte58, C. Luedtke51, F. Luehring64, W. Lukas65, L. Luminari134a, O. Lundberg148a;148b, B. Lund-Jensen149, P.M. Luzi83, D. Lynn27, R. Lysak129, E. Lytken84, V. Lyubushkin68, H. Ma27, L.L. Ma36b, Y. Ma36b, G. Maccarrone50, A. Macchiolo103, C.M. Macdonald141, B. Macek78, J. Machado Miguens124;128b, D. Mada ari88, R. Madar37, H.J. Maddocks168, W.F. Mader47, A. Madsen45, J. Maeda70, S. Maeland15, T. Maeno27, A.S. Maevskiy101, E. Magradze57, J. Mahlstedt109, C. Maiani119, C. Maidantchik26a, A.A. Maier103, T. Maier102, A. Maio128a;128b;128d, S. Majewski118, Y. Makida69, N. Makovec119, B. Malaescu83, Pa. Malecki42, V.P. Maleev125, F. Malek58, U. Mallik66, D. Malon6, C. Malone30, S. Maltezos10, S. Malyukov32, J. Mamuzic170, G. Mancini50, L. Mandelli94a, I. Mandic78, J. Maneira128a;128b, L. Manhaes de Andrade Filho26b, J. Manjarres Ramos163b, A. Mann102, A. Manousos32, B. Mansoulie138, J.D. Mansour35a, R. Mantifel90, M. Mantoani57, S. Manzoni94a;94b, L. Mapelli32, G. Marceca29, L. March52, L. Marchese122, G. Marchiori83, M. Marcisovsky129, M. Marjanovic37, D.E. Marley92, F. Marroquim26a, S.P. Marsden87, Z. Marshall16, M.U.F Martensson168, S. Marti-Garcia170, C.B. Martin113, T.A. Martin173, V.J. Martin49, B. Martin dit Latour15, M. Martinez13;v, V.I. Martinez Outschoorn169, S. Martin-Haugh133, V.S. Martoiu28b, A.C. Martyniuk81, A. Marzin32, L. Masetti86, T. Mashimo157, R. Mashinistov98, J. Masik87, A.L. Maslennikov111;c, L. Massa135a;135b, HJEP09(217) R.P. Middleton133, S. Miglioranzi53a;53b, L. Mijovic49, G. Mikenberg175, M. Mikestikova129, M. Mikuz78, M. Milesi91, A. Milic27, D.W. Miller33, C. Mills49, A. Milov175, D.A. Milstead148a;148b, A.A. Minaenko132, Y. Minami157, I.A. Minashvili68, A.I. Mincer112, B. Mindur41a, M. Mineev68, Y. Minegishi157, Y. Ming176, L.M. Mir13, K.P. Mistry124, T. Mitani174, J. Mitrevski102, V.A. Mitsou170, A. Miucci18, P.S. Miyagawa141, A. Mizukami69, J.U. Mjornmark84, M. Mlynarikova131, T. Moa148a;148b, K. Mochizuki97, P. Mogg51, S. Mohapatra38, S. Molander148a;148b, R. Moles-Valls23, R. Monden71, M.C. Mondragon93, K. Monig45, J. Monk39, E. Monnier88, A. Montalbano150, J. Montejo Berlingen32, F. Monticelli74, S. Monzani94a;94b, R.W. Moore3, N. Morange119, D. Moreno21, M. Moreno Llacer57, P. Morettini53a, S. Morgenstern32, D. Mori144, T. Mori157, M. Morii59, M. Morinaga157, V. Morisbak121, A.K. Morley152, G. Mornacchi32, J.D. Morris79, L. Morvaj150, P. Moschovakos10, M. Mosidze54b, H.J. Moss141, J. Moss145;aj, K. Motohashi159, R. Mount145, E. Mountricha27, E.J.W. Moyse89, S. Muanza88, R.D. Mudd19, F. Mueller103, J. Mueller127, R.S.P. Mueller102, D. Muenstermann75, P. Mullen56, G.A. Mullier18, F.J. Munoz Sanchez87, W.J. Murray173;133, H. Musheghyan57, M. Muskinja78, A.G. Myagkov132;ak, M. Myska130, B.P. Nachman16, O. Nackenhorst52, K. Nagai122, R. Nagai69;ad, K. Nagano69, Y. Nagasaka61, K. Nagata164, M. Nagel51, E. Nagy88, A.M. Nairz32, Y. Nakahama105, K. Nakamura69, T. Nakamura157, I. Nakano114, R.F. Naranjo Garcia45, R. Narayan11, D.I. Narrias Villar60a, I. Naryshkin125, T. Naumann45, G. Navarro21, R. Nayyar7, H.A. Neal92, P.Yu. Nechaeva98, T.J. Neep138, A. Negri123a;123b, M. Negrini22a, S. Nektarijevic108, C. Nellist119, A. Nelson166, M.E. Nelson122, S. Nemecek129, P. Nemethy112, A.A. Nepomuceno26a, M. Nessi32;al, M.S. Neubauer169, M. Neumann178, P.R. Newman19, T.Y. Ng62c, T. Nguyen Manh97, R.B. Nickerson122, R. Nicolaidou138, J. Nielsen139, V. Nikolaenko132;ak, I. Nikolic-Audit83, K. Nikolopoulos19, J.K. Nilsen121, P. Nilsson27, Y. Ninomiya157, A. Nisati134a, N. Nishu35c, R. Nisius103, T. Nobe157, Y. Noguchi71, M. Nomachi120, I. Nomidis31, M.A. Nomura27, T. Nooney79, M. Nordberg32, N. Norjoharuddeen122, O. Novgorodova47, S. Nowak103, M. Nozaki69, L. Nozka117, K. Ntekas166, E. Nurse81, F. Nuti91, K. O'connor25, D.C. O'Neil144, A.A. O'Rourke45, V. O'Shea56, F.G. Oakham31;d, H. Oberlack103, T. Obermann23, J. Ocariz83, A. Ochi70, I. Ochoa38, J.P. Ochoa-Ricoux34a, S. Oda73, S. Odaka69, H. Ogren64, A. Oh87, S.H. Oh48, C.C. Ohm16, H. Ohman168, H. Oide53a;53b, H. Okawa164, Y. Okumura157, T. Okuyama69, A. Olariu28b, L.F. Oleiro Seabra128a, S.A. Olivares Pino49, D. Oliveira Damazio27, A. Olszewski42, J. Olszowska42, A. Onofre128a;128e, K. Onogi105, P.U.E. Onyisi11;z, M.J. Oreglia33, Y. Oren155, D. Orestano136a;136b, N. Orlando62b, R.S. Orr161, B. Osculati53a;53b; , R. Ospanov87, G. Otero y Garzon29, H. Otono73, M. Ouchrif137d, F. Ould-Saada121, A. Ouraou138, K.P. Oussoren109, Q. Ouyang35a, M. Owen56, R.E. Owen19, V.E. Ozcan20a, N. Ozturk8, K. Pachal144, A. Pacheco Pages13, L. Pacheco Rodriguez138, C. Padilla Aranda13, S. Pagan Griso16, M. Paganini179, F. Paige27, P. Pais89, G. Palacino64, S. Palazzo40a;40b, S. Palestini32, M. Palka41b, D. Pallin37, E.St. Panagiotopoulou10, I. Panagoulias10, HJEP09(217) Th.D. Papadopoulou10, K. Papageorgiou9, A. Paramonov6, D. Paredes Hernandez179, A.J. Parker75, M.A. Parker30, K.A. Parker45, F. Parodi53a;53b, J.A. Parsons38, U. Parzefall51, V.R. Pascuzzi161, J.M. Pasner139, E. Pasqualucci134a, S. Passaggio53a, Fr. Pastore80, S. Pataraia178, J.R. Pater87, T. Pauly32, J. Pearce172, B. Pearson103, S. Pedraza Lopez170, R. Pedro128a;128b, S.V. Peleganchuk111;c, O. Penc129, C. Peng35a, H. Peng36a, J. Penwell64, B.S. Peralva26b, M.M. Perego138, D.V. Perepelitsa27, L. Perini94a;94b, H. Pernegger32, S. Perrella106a;106b, R. Peschke45, V.D. Peshekhonov68; , K. Peters45, R.F.Y. Peters87, B.A. Petersen32, T.C. Petersen39, E. Petit58, A. Petridis1, C. Petridou156, P. Petro 119, E. Petrolo134a, M. Petrov122, F. Petrucci136a;136b, N.E. Pettersson89, A. Peyaud138, R. Pezoa34b, P.W. Phillips133, G. Piacquadio150, E. Pianori173, A. Picazio89, E. Piccaro79, M.A. Pickering122, R. Piegaia29, J.E. Pilcher33, A.D. Pilkington87, A.W.J. Pin87, M. Pinamonti167a;167c;am, J.L. Pinfold3, H. Pirumov45, M. Pitt175, L. Plazak146a, M.-A. Pleier27, V. Pleskot86, E. Plotnikova68, D. Pluth67, P. Podberezko111, R. Poettgen148a;148b, R. Poggi123a;123b, L. Poggioli119, D. Pohl23, G. Polesello123a, A. Poley45, A. Policicchio40a;40b, R. Polifka32, A. Polini22a, C.S. Pollard56, V. Polychronakos27, K. Pommes32, D. Ponomarenko100, L. Pontecorvo134a, B.G. Pope93, G.A. Popeneciu28d, A. Poppleton32, S. Pospisil130, K. Potamianos16, I.N. Potrap68, C.J. Potter30, G. Poulard32, J. Poveda32, M.E. Pozo Astigarraga32, P. Pralavorio88, A. Pranko16, S. Prell67, D. Price87, L.E. Price6, M. Primavera76a, S. Prince90, N. Proklova100, K. Proko ev62c, F. Prokoshin34b, S. Protopopescu27, J. Proudfoot6, M. Przybycien41a, D. Puddu136a;136b, A. Puri169, P. Puzo119, J. Qian92, G. Qin56, Y. Qin87, A. Quadt57, M. Queitsch-Maitland45, D. Quilty56, S. Raddum121, V. Radeka27, V. Radescu122, S.K. Radhakrishnan150, P. Radlo 118, P. Rados91, F. Ragusa94a;94b, G. Rahal182, J.A. Raine87, S. Rajagopalan27, C. Rangel-Smith168, M.G. Ratti94a;94b, D.M. Rauch45, F. Rauscher102, S. Rave86, T. Ravenscroft56, I. Ravinovich175, J.H. Rawling87, M. Raymond32, A.L. Read121, N.P. Readio 77, M. Reale76a;76b, D.M. Rebuzzi123a;123b, A. Redelbach177, G. Redlinger27, R. Reece139, R.G. Reed147c, K. Reeves44, L. Rehnisch17, J. Reichert124, A. Reiss86, C. Rembser32, H. Ren35a, M. Rescigno134a, S. Resconi94a, E.D. Resseguie124, S. Rettie171, E. Reynolds19, O.L. Rezanova111;c, P. Reznicek131, R. Rezvani97, R. Richter103, S. Richter81, E. Richter-Was41b, O. Ricken23, M. Ridel83, P. Rieck103, C.J. Riegel178, J. Rieger57, O. Rifki115, M. Rijssenbeek150, A. Rimoldi123a;123b, M. Rimoldi18, L. Rinaldi22a, B. Ristic52, E. Ritsch32, I. Riu13, F. Rizatdinova116, E. Rizvi79, C. Rizzi13, R.T. Roberts87, S.H. Robertson90;o, A. Robichaud-Veronneau90, D. Robinson30, J.E.M. Robinson45, A. Robson56, E. Rocco86, C. Roda126a;126b, Y. Rodina88;an, S. Rodriguez Bosca170, A. Rodriguez Perez13, D. Rodriguez Rodriguez170, S. Roe32, C.S. Rogan59, O. R hne121, J. Rolo 59, A. Romaniouk100, M. Romano22a;22b, S.M. Romano Saez37, E. Romero Adam170, N. Rompotis77, M. Ronzani51, L. Roos83, S. Rosati134a, K. Rosbach51, P. Rose139, N.-A. Rosien57, V. Rossetti148a;148b, E. Rossi106a;106b, L.P. Rossi53a, J.H.N. Rosten30, R. Rosten140, M. Rotaru28b, I. Roth175, J. Rothberg140, D. Rousseau119, A. Rozanov88, Y. Rozen154, X. Ruan147c, F. Rubbo145, F. Ruhr51, A. Ruiz-Martinez31, Z. Rurikova51, N.A. Rusakovich68, H.L. Russell140, J.P. Rutherfoord7, N. Ruthmann32, Y.F. Ryabov125, M. Rybar169, G. Rybkin119, S. Ryu6, A. Ryzhov132, G.F. Rzehorz57, A.F. Saavedra152, G. Sabato109, S. Sacerdoti29, H.F-W. Sadrozinski139, R. Sadykov68, F. Safai Tehrani134a, P. Saha110, M. Sahinsoy60a, M. Saimpert45, M. Saito157, T. Saito157, H. Sakamoto157, Y. Sakurai174, G. Salamanna136a;136b, J.E. Salazar Loyola34b, D. Salek109, P.H. Sales De Bruin168, D. Salihagic103, A. Salnikov145, J. Salt170, D. Salvatore40a;40b, F. Salvatore151, A. Salvucci62a;62b;62c, A. Salzburger32, D. Sammel51, D. Sampsonidis156, J. Sanchez170, V. Sanchez Martinez170, A. Sanchez Pineda167a;167c, H. Sandaker121, R.L. Sandbach79, HJEP09(217) C. Santoni37, R. Santonico135a;135b, H. Santos128a, I. Santoyo Castillo151, K. Sapp127, A. Sapronov68, J.G. Saraiva128a;128d, B. Sarrazin23, O. Sasaki69, K. Sato164, E. Sauvan5, G. Savage80, P. Savard161;d, N. Savic103, C. Sawyer133, L. Sawyer82;u, J. Saxon33, C. Sbarra22a, A. Sbrizzi22a;22b, T. Scanlon81, D.A. Scannicchio166, M. Scarcella152, V. Scarfone40a;40b, J. Schaarschmidt140, P. Schacht103, B.M. Schachtner102, D. Schaefer32, L. Schaefer124, R. Schaefer45, J. Schae er86, S. Schaepe23, S. Schaetzel60b, U. Schafer86, A.C. Scha er119, D. Schaile102, R.D. Schamberger150, V. Scharf60a, V.A. Schegelsky125, D. Scheirich131, M. Schernau166, C. Schiavi53a;53b, S. Schier139, L.K. Schildgen23, C. Schillo51, M. Schioppa40a;40b, S. Schlenker32, K.R. Schmidt-Sommerfeld103, K. Schmieden32, C. Schmitt86, S. Schmitt45, S. Schmitz86, U. Schnoor51, L. Schoe el138, A. Schoening60b, B.D. Schoenrock93, E. Schopf23, M. Schott86, J.F.P. Schouwenberg108, J. Schovancova181, S. Schramm52, N. Schuh86, A. Schulte86, M.J. Schultens23, H.-C. Schultz-Coulon60a, H. Schulz17, M. Schumacher51, B.A. Schumm139, Ph. Schune138, A. Schwartzman145, T.A. Schwarz92, H. Schweiger87, Ph. Schwemling138, R. Schwienhorst93, J. Schwindling138, T. Schwindt23, A. Sciandra23, G. Sciolla25, F. Scuri126a;126b, F. Scutti91, J. Searcy92, P. Seema23, S.C. Seidel107, A. Seiden139, J.M. Seixas26a, G. Sekhniaidze106a, K. Sekhon92, S.J. Sekula43, N. Semprini-Cesari22a;22b, C. Serfon121, L. Serin119, L. Serkin167a;167b, M. Sessa136a;136b, R. Seuster172, H. Severini115, T. S ligoj78, F. Sforza32, A. Sfyrla52, E. Shabalina57, N.W. Shaikh148a;148b, L.Y. Shan35a, R. Shang169, J.T. Shank24, M. Shapiro16, P.B. Shatalov99, K. Shaw167a;167b, S.M. Shaw87, A. Shcherbakova148a;148b, C.Y. Shehu151, Y. Shen115, P. Sherwood81, L. Shi153;ao, S. Shimizu70, C.O. Shimmin179, M. Shimojima104, I.P.J. Shipsey122, S. Shirabe73, M. Shiyakova68;ap, J. Shlomi175, A. Shmeleva98, D. Shoaleh Saadi97, M.J. Shochet33, S. Shojaii94a, D.R. Shope115, S. Shrestha113, E. Shulga100, M.A. Shupe7, P. Sicho129, A.M. Sickles169, P.E. Sidebo149, E. Sideras Haddad147c, O. Sidiropoulou177, D. Sidorov116, A. Sidoti22a;22b, F. Siegert47, Dj. Sijacki14, J. Silva128a;128d, S.B. Silverstein148a, V. Simak130, Lj. Simic14, S. Simion119, E. Simioni86, B. Simmons81, M. Simon86, P. Sinervo161, N.B. Sinev118, M. Sioli22a;22b, G. Siragusa177, I. Siral92, S.Yu. Sivoklokov101, J. Sjolin148a;148b, M.B. Skinner75, P. Skubic115, M. Slater19, T. Slavicek130, M. Slawinska109, K. Sliwa165, R. Slovak131, V. Smakhtin175, B.H. Smart5, J. Smiesko146a, N. Smirnov100, S.Yu. Smirnov100, Y. Smirnov100, L.N. Smirnova101;aq, O. Smirnova84, J.W. Smith57, M.N.K. Smith38, R.W. Smith38, M. Smizanska75, K. Smolek130, A.A. Snesarev98, I.M. Snyder118, S. Snyder27, R. Sobie172;o, F. Socher47, A. So er155, D.A. Soh153, G. Sokhrannyi78, C.A. Solans Sanchez32, M. Solar130, E.Yu. Soldatov100, U. Soldevila170, A.A. Solodkov132, A. Soloshenko68, O.V. Solovyanov132, V. Solovyev125, P. Sommer51, H. Son165, H.Y. Song36a;ar, A. Sopczak130, D. Sosa60b, C.L. Sotiropoulou126a;126b, R. Soualah167a;167c, A.M. Soukharev111;c, D. South45, B.C. Sowden80, S. Spagnolo76a;76b, M. Spalla126a;126b, M. Spangenberg173, F. Spano80, D. Sperlich17, F. Spettel103, T.M. Spieker60a, R. Spighi22a, G. Spigo32, L.A. Spiller91, M. Spousta131, R.D. St. Denis56; , A. Stabile94a, R. Stamen60a, S. Stamm17, E. Stanecka42, R.W. Stanek6, C. Stanescu136a, M.M. Stanitzki45, S. Stapnes121, E.A. Starchenko132, G.H. Stark33, J. Stark58, S.H Stark39, P. Staroba129, P. Starovoitov60a, S. Starz32, R. Staszewski42, P. Steinberg27, B. Stelzer144, H.J. Stelzer32, O. Stelzer-Chilton163a, H. Stenzel55, G.A. Stewart56, M.C. Stockton118, M. Stoebe90, G. Stoicea28b, P. Stolte57, S. Stonjek103, A.R. Stradling8, A. Straessner47, M.E. Stramaglia18, J. Strandberg149, S. Strandberg148a;148b, A. Strandlie121, M. Strauss115, P. Strizenec146b, R. Strohmer177, D.M. Strom118, R. Stroynowski43, A. Strubig108, S.A. Stucci27, B. Stugu15, N.A. Styles45, D. Su145, J. Su127, S. Suchek60a, Y. Sugaya120, M. Suk130, V.V. Sulin98, S. Sultansoy4c, T. Sumida71, S. Sun59, X. Sun3, K. Suruliz151, C.J.E. Suster152, M.R. Sutton151, S. Suzuki69, M. Svatos129, M. Swiatlowski33, S.P. Swift2, I. Sykora146a, T. Sykora131, D. Ta51, HJEP09(217) R. Takashima72, T. Takeshita142, Y. Takubo69, M. Talby88, A.A. Talyshev111;c, J. Tanaka157, M. Tanaka159, R. Tanaka119, S. Tanaka69, R. Tanioka70, B.B. Tannenwald113, S. Tapia Araya34b, S. Tapprogge86, S. Tarem154, G.F. Tartarelli94a, P. Tas131, M. Tasevsky129, T. Tashiro71, E. Tassi40a;40b, A. Tavares Delgado128a;128b, Y. Tayalati137e, A.C. Taylor107, G.N. Taylor91, P.T.E. Taylor91, W. Taylor163b, P. Teixeira-Dias80, D. Temple144, H. Ten Kate32, P.K. Teng153, J.J. Teoh120, F. Tepel178, S. Terada69, K. Terashi157, J. Terron85, S. Terzo13, M. Testa50, R.J. Teuscher161;o, T. Theveneaux-Pelzer88, J.P. Thomas19, J. Thomas-Wilsker80, P.D. Thompson19, A.S. Thompson56, L.A. Thomsen179, E. Thomson124, M.J. Tibbetts16, R.E. Ticse Torres88, V.O. Tikhomirov98;as, Yu.A. Tikhonov111;c, S. Timoshenko100, P. Tipton179, S. Tisserant88, K. Todome159, S. Todorova-Nova5, J. Tojo73, S. Tokar146a, K. Tokushuku69, E. Tolley59, L. Tomlinson87, M. Tomoto105, L. Tompkins145;at, K. Toms107, B. Tong59, P. Tornambe51, E. Torrence118, H. Torres144, E. Torro Pastor140, J. Toth88;au, F. Touchard88, D.R. Tovey141, C.J. Treado112, T. Trefzger177, F. Tresoldi151, A. Tricoli27, I.M. Trigger163a, S. Trincaz-Duvoid83, M.F. Tripiana13, W. Trischuk161, B. Trocme58, A. Trofymov45, C. Troncon94a, M. Trottier-McDonald16, M. Trovatelli172, L. Truong167a;167c, M. Trzebinski42, A. Trzupek42, K.W. Tsang62a, J.C-L. Tseng122, P.V. Tsiareshka95, G. Tsipolitis10, N. Tsirintanis9, S. Tsiskaridze13, V. Tsiskaridze51, E.G. Tskhadadze54a, K.M. Tsui62a, I.I. Tsukerman99, V. Tsulaia16, S. Tsuno69, D. Tsybychev150, Y. Tu62b, A. Tudorache28b, V. Tudorache28b, T.T. Tulbure28a, A.N. Tuna59, S.A. Tupputi22a;22b, S. Turchikhin68, D. Turgeman175, I. Turk Cakir4b;av, R. Turra94a, P.M. Tuts38, G. Ucchielli22a;22b, I. Ueda69, M. Ughetto148a;148b, F. Ukegawa164, G. Unal32, A. Undrus27, G. Unel166, F.C. Ungaro91, Y. Unno69, C. Unverdorben102, J. Urban146b, P. Urquijo91, P. Urrejola86, G. Usai8, J. Usui69, L. Vacavant88, V. Vacek130, B. Vachon90, C. Valderanis102, E. Valdes Santurio148a;148b, S. Valentinetti22a;22b, A. Valero170, L. Valery13, S. Valkar131, A. Vallier5, J.A. Valls Ferrer170, W. Van Den Wollenberg109, H. van der Graaf109, N. van Eldik154, P. van Gemmeren6, J. Van Nieuwkoop144, I. van Vulpen109, M.C. van Woerden109, M. Vanadia134a;134b, W. Vandelli32, R. Vanguri124, A. Vaniachine160, P. Vankov109, G. Vardanyan180, R. Vari134a, E.W. Varnes7, C. Varni53a;53b, T. Varol43, D. Varouchas119, A. Vartapetian8, K.E. Varvell152, J.G. Vasquez179, G.A. Vasquez34b, F. Vazeille37, T. Vazquez Schroeder90, J. Veatch57, V. Veeraraghavan7, L.M. Veloce161, F. Veloso128a;128c, S. Veneziano134a, A. Ventura76a;76b, M. Venturi172, N. Venturi161, A. Venturini25, V. Vercesi123a, M. Verducci136a;136b, W. Verkerke109, J.C. Vermeulen109, M.C. Vetterli144;d, N. Viaux Maira34b, O. Viazlo84, I. Vichou169; , T. Vickey141, O.E. Vickey Boeriu141, G.H.A. Viehhauser122, S. Viel16, L. Vigani122, M. Villa22a;22b, M. Villaplana Perez94a;94b, E. Vilucchi50, M.G. Vincter31, V.B. Vinogradov68, A. Vishwakarma45, C. Vittori22a;22b, I. Vivarelli151, S. Vlachos10, M. Vlasak130, M. Vogel178, P. Vokac130, G. Volpi126a;126b, H. von der Schmitt103, E. von Toerne23, V. Vorobel131, K. Vorobev100, M. Vos170, R. Voss32, J.H. Vossebeld77, N. Vranjes14, M. Vranjes Milosavljevic14, V. Vrba130, M. Vreeswijk109, R. Vuillermet32, I. Vukotic33, P. Wagner23, W. Wagner178, J. Wagner-Kuhr102, H. Wahlberg74, S. Wahrmund47, J. Wakabayashi105, J. Walder75, R. Walker102, W. Walkowiak143, V. Wallangen148a;148b, C. Wang35b, C. Wang36b;aw, F. Wang176, H. Wang16, H. Wang3, J. Wang45, J. Wang152, Q. Wang115, R. Wang6, S.M. Wang153, T. Wang38, W. Wang153;ax, W. Wang36a, Z. Wang36c, C. Wanotayaroj118, A. Warburton90, C.P. Ward30, D.R. Wardrope81, A. Washbrook49, P.M. Watkins19, A.T. Watson19, M.F. Watson19, G. Watts140, S. Watts87, B.M. Waugh81, A.F. Webb11, S. Webb86, M.S. 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Zwalinski32 Barcelona, Spain CA, U.S.A. 1 Department of Physics, University of Adelaide, Adelaide, Australia 2 Physics Department, SUNY Albany, Albany NY, U.S.A. 3 Department of Physics, University of Alberta, Edmonton AB, Canada 4 (a) Department of Physics, Ankara University, Ankara; (b) Istanbul Aydin University, Istanbul; (c) Division of Physics, TOBB University of Economics and Technology, Ankara, Turkey 5 LAPP, CNRS/IN2P3 and Universite Savoie Mont Blanc, Annecy-le-Vieux, France 6 High Energy Physics Division, Argonne National Laboratory, Argonne IL, U.S.A. 7 Department of Physics, University of Arizona, Tucson AZ, U.S.A. 8 Department of Physics, The University of Texas at Arlington, Arlington TX, U.S.A. 9 Physics Department, National and Kapodistrian University of Athens, Athens, Greece 10 Physics Department, National Technical University of Athens, Zografou, Greece 11 Department of Physics, The University of Texas at Austin, Austin TX, U.S.A. 12 Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan 13 Institut de F sica d'Altes Energies (IFAE), The Barcelona Institute of Science and Technology, 14 Institute of Physics, University of Belgrade, Belgrade, Serbia 15 Department for Physics and Technology, University of Bergen, Bergen, Norway 16 Physics Division, Lawrence Berkeley National Laboratory and University of California, Berkeley 17 Department of Physics, Humboldt University, Berlin, Germany 18 Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics, University of Bern, Bern, Switzerland 19 School of Physics and Astronomy, University of Birmingham, Birmingham, U.K. 20 (a) Department of Physics, Bogazici University, Istanbul; (b) Department of Physics Engineering, Gaziantep University, Gaziantep; (d) Istanbul Bilgi University, Faculty of Engineering and Natural Sciences, Istanbul; (e) Bahcesehir University, Faculty of Engineering and Natural Sciences, Istanbul, Turkey 21 Centro de Investigaciones, Universidad Antonio Narino, Bogota, Colombia HJEP09(217) Bologna, Italy 23 Physikalisches Institut, University of Bonn, Bonn, Germany 24 Department of Physics, Boston University, Boston MA, U.S.A. 25 Department of Physics, Brandeis University, Waltham MA, U.S.A. 26 (a) Universidade Federal do Rio De Janeiro COPPE/EE/IF, Rio de Janeiro; (b) Electrical Circuits Department, Federal University of Juiz de Fora (UFJF), Juiz de Fora; (c) Federal University of Sao Joao del Rei (UFSJ), Sao Joao del Rei; (d) Instituto de Fisica, Universidade de Sao Paulo, Sao Paulo, Brazil 27 Physics Department, Brookhaven National Laboratory, Upton NY, U.S.A. 28 (a) Transilvania University of Brasov, Brasov; (b) Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest; (c) Department of Physics, Alexandru Ioan Cuza University of Iasi, Iasi; (d) National Institute for Research and Development of Isotopic and Molecular Technologies, Physics Department, Cluj Napoca; (e) University Politehnica Bucharest, Bucharest; (f) West University in Timisoara, Timisoara, Romania 29 Departamento de F sica, Universidad de Buenos Aires, Buenos Aires, Argentina 30 Cavendish Laboratory, University of Cambridge, Cambridge, U.K. 31 Department of Physics, Carleton University, Ottawa ON, Canada 32 CERN, Geneva, Switzerland 33 Enrico Fermi Institute, University of Chicago, Chicago IL, U.S.A. 34 (a) Departamento de F sica, Ponti cia Universidad Catolica de Chile, Santiago; (b) Departamento de F sica, Universidad Tecnica Federico Santa Mar a, Valpara so, Chile 35 (a) Institute of High Energy Physics, Chinese Academy of Sciences, Beijing; (b) Department of Physics, Nanjing University, Jiangsu; (c) Physics Department, Tsinghua University, Beijing 100084, China 36 (a) Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Anhui; (b) School of Physics, Shandong University, Shandong; (c) Department of Physics and Astronomy, Key Laboratory for Particle Physics, Astrophysics and Cosmology, Ministry of Education; Shanghai Key Laboratory for Particle Physics and Cosmology, Shanghai Jiao Tong University, Shanghai (also at PKU-CHEP), China 37 Universite Clermont Auvergne, CNRS/IN2P3, LPC, Clermont-Ferrand, France 38 Nevis Laboratory, Columbia University, Irvington NY, U.S.A. 39 Niels Bohr Institute, University of Copenhagen, Kobenhavn, Denmark 40 (a) INFN Gruppo Collegato di Cosenza, Laboratori Nazionali di Frascati; (b) Dipartimento di Fisica, Universita della Calabria, Rende, Italy 41 (a) AGH University of Science and Technology, Faculty of Physics and Applied Computer Science, Krakow; (b) Marian Smoluchowski Institute of Physics, Jagiellonian University, Krakow, Poland 42 Institute of Nuclear Physics Polish Academy of Sciences, Krakow, Poland 43 Physics Department, Southern Methodist University, Dallas TX, U.S.A. 44 Physics Department, University of Texas at Dallas, Richardson TX, U.S.A. 45 DESY, Hamburg and Zeuthen, Germany 46 Lehrstuhl fur Experimentelle Physik IV, Technische Universitat Dortmund, Dortmund, Germany 47 Institut fur Kern- und Teilchenphysik, Technische Universitat Dresden, Dresden, Germany 48 Department of Physics, Duke University, Durham NC, U.S.A. 49 SUPA - School of Physics and Astronomy, University of Edinburgh, Edinburgh, U.K. 50 INFN Laboratori Nazionali di Frascati, Frascati, Italy 51 Fakultat fur Mathematik und Physik, Albert-Ludwigs-Universitat, Freiburg, Germany 52 Departement de Physique Nucleaire et Corpusculaire, Universite de Geneve, Geneva, Switzerland 53 (a) INFN Sezione di Genova; (b) Dipartimento di Fisica, Universita di Genova, Genova, Italy 54 (a) E. Andronikashvili Institute of Physics, Iv. Javakhishvili Tbilisi State University, Tbilisi; (b) High Energy Physics Institute, Tbilisi State University, Tbilisi, Georgia 55 II Physikalisches Institut, Justus-Liebig-Universitat Giessen, Giessen, Germany 57 II Physikalisches Institut, Georg-August-Universitat, Gottingen, Germany 58 Laboratoire de Physique Subatomique et de Cosmologie, Universite Grenoble-Alpes, CNRS/IN2P3, Grenoble, France 59 Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge MA, U.S.A. 60 (a) Kirchho -Institut fur Physik, Ruprecht-Karls-Universitat Heidelberg, Heidelberg; (b) Physikalisches Institut, Ruprecht-Karls-Universitat Heidelberg, Heidelberg; (c) ZITI Institut fur technische Informatik, Ruprecht-Karls-Universitat Heidelberg, Mannheim, Germany 61 Faculty of Applied Information Science, Hiroshima Institute of Technology, Hiroshima, Japan 62 (a) Department of Physics, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong; (b) Department of Physics, The University of Hong Kong, Hong Kong; (c) Department of Physics and Institute for Advanced Study, The Hong Kong University of Science and Technology, Clear Water 63 Department of Physics, National Tsing Hua University, Taiwan, Taiwan 64 Department of Physics, Indiana University, Bloomington IN, U.S.A. 65 Institut fur Astro- und Teilchenphysik, Leopold-Franzens-Universitat, Innsbruck, Austria 66 University of Iowa, Iowa City IA, U.S.A. 67 Department of Physics and Astronomy, Iowa State University, Ames IA, U.S.A. 68 Joint Institute for Nuclear Research, JINR Dubna, Dubna, Russia 69 KEK, High Energy Accelerator Research Organization, Tsukuba, Japan 70 Graduate School of Science, Kobe University, Kobe, Japan 71 Faculty of Science, Kyoto University, Kyoto, Japan 72 Kyoto University of Education, Kyoto, Japan 73 Research Center for Advanced Particle Physics and Department of Physics, Kyushu University, Fukuoka, Japan Lecce, Italy 74 Instituto de F sica La Plata, Universidad Nacional de La Plata and CONICET, La Plata, Argentina 75 Physics Department, Lancaster University, Lancaster, U.K. 76 (a) INFN Sezione di Lecce; (b) Dipartimento di Matematica e Fisica, Universita del Salento, 77 Oliver Lodge Laboratory, University of Liverpool, Liverpool, U.K. 78 Department of Experimental Particle Physics, Jozef Stefan Institute and Department of Physics, University of Ljubljana, Ljubljana, Slovenia 79 School of Physics and Astronomy, Queen Mary University of London, London, U.K. 80 Department of Physics, Royal Holloway University of London, Surrey, U.K. 81 Department of Physics and Astronomy, University College London, London, U.K. 82 Louisiana Tech University, Ruston LA, U.S.A. 83 Laboratoire de Physique Nucleaire et de Hautes Energies, UPMC and Universite Paris-Diderot and CNRS/IN2P3, Paris, France 84 Fysiska institutionen, Lunds universitet, Lund, Sweden 85 Departamento de Fisica Teorica C-15, Universidad Autonoma de Madrid, Madrid, Spain 86 Institut fur Physik, Universitat Mainz, Mainz, Germany 87 School of Physics and Astronomy, University of Manchester, Manchester, U.K. 88 CPPM, Aix-Marseille Universite and CNRS/IN2P3, Marseille, France 89 Department of Physics, University of Massachusetts, Amherst MA, U.S.A. 90 Department of Physics, McGill University, Montreal QC, Canada 91 School of Physics, University of Melbourne, Victoria, Australia 92 Department of Physics, The University of Michigan, Ann Arbor MI, U.S.A. 93 Department of Physics and Astronomy, Michigan State University, East Lansing MI, U.S.A. 94 (a) INFN Sezione di Milano; (b) Dipartimento di Fisica, Universita di Milano, Milano, Italy 95 B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk, Republic of Belarus Moscow, Russia 97 Group of Particle Physics, University of Montreal, Montreal QC, Canada 98 P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow, Russia 99 Institute for Theoretical and Experimental Physics (ITEP), Moscow, Russia 100 National Research Nuclear University MEPhI, Moscow, Russia 101 D.V. Skobeltsyn Institute of Nuclear Physics, M.V. Lomonosov Moscow State University, 102 Fakultat fur Physik, Ludwig-Maximilians-Universitat Munchen, Munchen, Germany 103 Max-Planck-Institut fur Physik (Werner-Heisenberg-Institut), Munchen, Germany 104 Nagasaki Institute of Applied Science, Nagasaki, Japan 105 Graduate School of Science and Kobayashi-Maskawa Institute, Nagoya University, Nagoya, Japan 106 (a) INFN Sezione di Napoli; (b) Dipartimento di Fisica, Universita di Napoli, Napoli, Italy 107 Department of Physics and Astronomy, University of New Mexico, Albuquerque NM, U.S.A. 108 Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen, Netherlands Netherlands 109 Nikhef National Institute for Subatomic Physics and University of Amsterdam, Amsterdam, 110 Department of Physics, Northern Illinois University, DeKalb IL, U.S.A. 111 Budker Institute of Nuclear Physics, SB RAS, Novosibirsk, Russia 112 Department of Physics, New York University, New York NY, U.S.A. 113 Ohio State University, Columbus OH, U.S.A. 114 Faculty of Science, Okayama University, Okayama, Japan 115 Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman OK, 116 Department of Physics, Oklahoma State University, Stillwater OK, U.S.A. 117 Palacky University, RCPTM, Olomouc, Czech Republic 118 Center for High Energy Physics, University of Oregon, Eugene OR, U.S.A. 119 LAL, Univ. Paris-Sud, CNRS/IN2P3, Universite Paris-Saclay, Orsay, France 120 Graduate School of Science, Osaka University, Osaka, Japan 121 Department of Physics, University of Oslo, Oslo, Norway 122 Department of Physics, Oxford University, Oxford, U.K. 123 (a) INFN Sezione di Pavia; (b) Dipartimento di Fisica, Universita di Pavia, Pavia, Italy 124 Department of Physics, University of Pennsylvania, Philadelphia PA, U.S.A. 125 National Research Centre "Kurchatov Institute" B.P.Konstantinov Petersburg Nuclear Physics Institute, St. Petersburg, Russia 126 (a) INFN Sezione di Pisa; (b) Dipartimento di Fisica E. Fermi, Universita di Pisa, Pisa, Italy 127 Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh PA, U.S.A. 128 (a) Laboratorio de Instrumentaca~o e F sica Experimental de Part culas - LIP, Lisboa; (b) Faculdade de Ci^encias, Universidade de Lisboa, Lisboa; (c) Department of Physics, University of Coimbra, Coimbra; (d) Centro de F sica Nuclear da Universidade de Lisboa, Lisboa; (e) Departamento de Fisica, Universidade do Minho, Braga; (f) Departamento de Fisica Teorica y del Cosmos and CAFPE, Universidad de Granada, Granada; (g) Dep Fisica and CEFITEC of Faculdade de Ciencias e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal 129 Institute of Physics, Academy of Sciences of the Czech Republic, Praha, Czech Republic 130 Czech Technical University in Prague, Praha, Czech Republic 131 Charles University, Faculty of Mathematics and Physics, Prague, Czech Republic 132 State Research Center Institute for High Energy Physics (Protvino), NRC KI, Russia 133 Particle Physics Department, Rutherford Appleton Laboratory, Didcot, U.K. 134 (a) INFN Sezione di Roma; (b) Dipartimento di Fisica, Sapienza Universita di Roma, Roma, Italy 135 (a) INFN Sezione di Roma Tor Vergata; (b) Dipartimento di Fisica, Universita di Roma Tor Vergata, Roma, Italy Roma, Italy 137 (a) Faculte des Sciences Ain Chock, Reseau Universitaire de Physique des Hautes Energies Universite Hassan II, Casablanca; (b) Centre National de l'Energie des Sciences Techniques Nucleaires, Rabat; (c) Faculte des Sciences Semlalia, Universite Cadi Ayyad, LPHEA-Marrakech; (d) Faculte des Sciences, Universite Mohamed Premier and LPTPM, Oujda; (e) Faculte des sciences, Universite Mohammed V, Rabat, Morocco 138 DSM/IRFU (Institut de Recherches sur les Lois Fondamentales de l'Univers), CEA Saclay (Commissariat a l'Energie Atomique et aux Energies Alternatives), Gif-sur-Yvette, France 139 Santa Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz CA, 140 Department of Physics, University of Washington, Seattle WA, U.S.A. 141 Department of Physics and Astronomy, University of She eld, She eld, U.K. 142 Department of Physics, Shinshu University, Nagano, Japan 143 Department Physik, Universitat Siegen, Siegen, Germany 144 Department of Physics, Simon Fraser University, Burnaby BC, Canada 145 SLAC National Accelerator Laboratory, Stanford CA, U.S.A. 146 (a) Faculty of Mathematics, Physics & Informatics, Comenius University, Bratislava; (b) Department of Subnuclear Physics, Institute of Experimental Physics of the Slovak Academy of Sciences, Kosice, Slovak Republic 147 (a) Department of Physics, University of Cape Town, Cape Town; (b) Department of Physics, University of Johannesburg, Johannesburg; (c) School of Physics, University of the Witwatersrand, Johannesburg, South Africa 148 (a) Department of Physics, Stockholm University; (b) The Oskar Klein Centre, Stockholm, Sweden 149 Physics Department, Royal Institute of Technology, Stockholm, Sweden 150 Departments of Physics & Astronomy and Chemistry, Stony Brook University, Stony Brook NY, 151 Department of Physics and Astronomy, University of Sussex, Brighton, U.K. 152 School of Physics, University of Sydney, Sydney, Australia 153 Institute of Physics, Academia Sinica, Taipei, Taiwan 154 Department of Physics, Technion: Israel Institute of Technology, Haifa, Israel 155 Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv University, Tel Aviv, 156 Department of Physics, Aristotle University of Thessaloniki, Thessaloniki, Greece 157 International Center for Elementary Particle Physics and Department of Physics, The University of Tokyo, Tokyo, Japan 158 Graduate School of Science and Technology, Tokyo Metropolitan University, Tokyo, Japan 159 Department of Physics, Tokyo Institute of Technology, Tokyo, Japan 160 Tomsk State University, Tomsk, Russia 161 Department of Physics, University of Toronto, Toronto ON, Canada 162 (a) INFN-TIFPA; (b) University of Trento, Trento, Italy 163 (a) TRIUMF, Vancouver BC; (b) Department of Physics and Astronomy, York University, Toronto ON, Canada 164 Faculty of Pure and Applied Sciences, and Center for Integrated Research in Fundamental Science and Engineering, University of Tsukuba, Tsukuba, Japan 165 Department of Physics and Astronomy, Tufts University, Medford MA, U.S.A. 166 Department of Physics and Astronomy, University of California Irvine, Irvine CA, U.S.A. 167 (a) INFN Gruppo Collegato di Udine, Sezione di Trieste, Udine; (b) ICTP, Trieste; (c) Dipartimento di Chimica, Fisica e Ambiente, Universita di Udine, Udine, Italy 168 Department of Physics and Astronomy, University of Uppsala, Uppsala, Sweden 169 Department of Physics, University of Illinois, Urbana IL, U.S.A. 170 Instituto de Fisica Corpuscular (IFIC), Centro Mixto Universidad de Valencia - CSIC, Spain 172 Department of Physics and Astronomy, University of Victoria, Victoria BC, Canada 173 Department of Physics, University of Warwick, Coventry, U.K. 174 Waseda University, Tokyo, Japan 175 Department of Particle Physics, The Weizmann Institute of Science, Rehovot, Israel 176 Department of Physics, University of Wisconsin, Madison WI, U.S.A. 177 Fakultat fur Physik und Astronomie, Julius-Maximilians-Universitat, Wurzburg, Germany 178 Fakultat fur Mathematik und Naturwissenschaften, Fachgruppe Physik, Bergische Universitat Wuppertal, Wuppertal, Germany 179 Department of Physics, Yale University, New Haven CT, U.S.A. 180 Yerevan Physics Institute, Yerevan, Armenia 181 CH-1211 Geneva 23, Switzerland 182 Centre de Calcul de l'Institut National de Physique Nucleaire et de Physique des Particules (IN2P3), Villeurbanne, France a Also at Department of Physics, King's College London, London, U.K. b Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan c Also at Novosibirsk State University, Novosibirsk, Russia d Also at TRIUMF, Vancouver BC, Canada e Also at Department of Physics & Astronomy, University of Louisville, Louisville, KY, U.S.A. f Also at Physics Department, An-Najah National University, Nablus, Palestine g Also at Department of Physics, California State University, Fresno CA, U.S.A. h Also at Department of Physics, University of Fribourg, Fribourg, Switzerland i Also at II Physikalisches Institut, Georg-August-Universitat, Gottingen, Germany j Also at Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona, Spain k Also at Departamento de Fisica e Astronomia, Faculdade de Ciencias, Universidade do Porto, Portugal l Also at Tomsk State University, Tomsk, Russia m Also at The Collaborative Innovation Center of Quantum Matter (CICQM), Beijing, China n Also at Universita di Napoli Parthenope, Napoli, Italy o Also at Institute of Particle Physics (IPP), Canada p Also at Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest, Romania q Also at Department of Physics, St. Petersburg State Polytechnical University, St. Petersburg, HJEP09(217) Russia r Also at Borough of Manhattan Community College, City University of New York, New York City, s Also at Department of Physics, The University of Michigan, Ann Arbor MI, U.S.A. t Also at Centre for High Performance Computing, CSIR Campus, Rosebank, Cape Town, u Also at Louisiana Tech University, Ruston LA, U.S.A. v Also at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona, Spain w Also at Graduate School of Science, Osaka University, Osaka, Japan x Also at Fakultat fur Mathematik und Physik, Albert-Ludwigs-Universitat, Freiburg, Germany y Also at Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen, Netherlands z Also at Department of Physics, The University of Texas at Austin, Austin TX, U.S.A. aa Also at Institute of Theoretical Physics, Ilia State University, Tbilisi, Georgia ab Also at CERN, Geneva, Switzerland ac Also at Georgian Technical University (GTU),Tbilisi, Georgia ad Also at Ochadai Academic Production, Ochanomizu University, Tokyo, Japan ae Also at Manhattan College, New York NY, U.S.A. af Also at Departamento de F sica, Ponti cia Universidad Catolica de Chile, Santiago, Chile ah Also at School of Physics, Shandong University, Shandong, China ai Also at Departamento de Fisica Teorica y del Cosmos and CAFPE, Universidad de Granada, aj Also at Department of Physics, California State University, Sacramento CA, U.S.A. ak Also at Moscow Institute of Physics and Technology State University, Dolgoprudny, Russia al Also at Departement de Physique Nucleaire et Corpusculaire, Universite de Geneve, Geneva, Hungary Deceased Also at International School for Advanced Studies (SISSA), Trieste, Italy an Also at Institut de F sica d'Altes Energies (IFAE), The Barcelona Institute of Science and Technology, Barcelona, Spain ao Also at School of Physics, Sun Yat-sen University, Guangzhou, China aq Also at Faculty of Physics, M.V.Lomonosov Moscow State University, Moscow, Russia ar Also at Institute of Physics, Academia Sinica, Taipei, Taiwan as Also at National Research Nuclear University MEPhI, Moscow, Russia at Also at Department of Physics, Stanford University, Stanford CA, U.S.A. au Also at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest, Also at CPPM, Aix-Marseille Universite and CNRS/IN2P3, Marseille, France ax Also at Department of Physics, Nanjing University, Jiangsu, China ay Also at University of Malaya, Department of Physics, Kuala Lumpur, Malaysia az Also at LAL, Univ. 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M. Aaboud, G. Aad, B. Abbott, J. Abdallah, O. Abdinov, B. Abeloos, S. H. Abidi, O. S. AbouZeid, N. L. Abraham, H. Abramowicz, H. Abreu, R. Abreu, Y. Abulaiti, B. S. Acharya, S. Adachi, L. Adamczyk, J. Adelman, M. Adersberger, T. Adye, A. A. Affolder, T. Agatonovic-Jovin, C. Agheorghiesei, J. A. Aguilar-Saavedra, S. P. Ahlen, F. Ahmadov, G. Aielli, S. Akatsuka, H. Akerstedt, T. P. A. Åkesson, A. V. Akimov, G. L. Alberghi, J. Albert, M. J. Alconada Verzini, M. Aleksa, I. N. Aleksandrov, C. Alexa, G. Alexander, T. Alexopoulos, M. Alhroob, B. Ali, M. Aliev, G. Alimonti, J. Alison, S. P. Alkire, B. M. M. Allbrooke, B. W. Allen, P. P. Allport, A. Aloisio, A. Alonso, F. Alonso, C. Alpigiani, A. A. Alshehri, M. Alstaty, B. Alvarez Gonzalez, D. Álvarez Piqueras, M. G. Alviggi, B. T. Amadio, Y. Amaral Coutinho, C. Amelung, D. Amidei, S. P. Amor Dos Santos, A. Amorim, S. Amoroso, G. Amundsen, C. Anastopoulos, L. S. Ancu, N. Andari, T. Andeen, C. F. Anders, J. K. Anders, K. J. Anderson, A. Andreazza, V. Andrei, S. Angelidakis, I. Angelozzi, A. Angerami, F. Anghinolfi, A. V. Anisenkov, N. Anjos, A. Annovi, C. Antel, M. Antonelli, A. Antonov, D. J. Antrim, F. Anulli, M. Aoki, L. Aperio Bella, G. Arabidze, Y. Arai, J. P. Araque, V. Araujo Ferraz, A. T. H. Arce, R. E. Ardell, F. A. Arduh, J-F. Arguin, S. Argyropoulos, M. Arik, A. J. Armbruster, L. J. Armitage, O. Arnaez, H. Arnold, M. Arratia, O. Arslan, A. Artamonov, G. Artoni, S. Artz, S. Asai, N. Asbah, A. Ashkenazi, L. Asquith, K. Assamagan, R. Astalos, M. Atkinson, N. B. Atlay, K. Augsten, G. Avolio, B. Axen, M. K. Ayoub, G. Azuelos, A. E. Baas, M. J. Baca, H. Bachacou, K. Bachas, M. Backes, M. Backhaus, P. Bagiacchi, P. Bagnaia, H. Bahrasemani, J. T. Baines, M. Bajic, O. K. Baker, E. M. Baldin, P. Balek, T. Balestri, F. Balli, W. K. Balunas, E. Banas, Sw. Banerjee, A. A. E. Bannoura, L. Barak, E. L. Barberio, D. Barberis, M. Barbero, T. Barillari, M-S Barisits, T. Barklow, N. Barlow, S. L. Barnes, B. M. Barnett, R. M. Barnett, Z. Barnovska-Blenessy, A. Baroncelli, G. Barone, A. J. Barr, L. Barranco Navarro, F. Barreiro, J. Barreiro Guimarães da Costa, R. Bartoldus, A. E. Barton, P. Bartos, A. Basalaev, A. Bassalat, R. L. Bates, S. J. Batista, J. R. Batley, M. Battaglia, M. Bauce, F. Bauer, H. S. Bawa, J. B. Beacham, M. D. Beattie, T. Beau, P. H. Beauchemin, P. Bechtle, H. P. Beck, K. Becker, M. Becker, M. Beckingham, C. Becot, A. J. Beddall, A. Beddall, V. A. Bednyakov, M. Bedognetti, C. P. Bee, T. A. Beermann, M. Begalli, M. Begel, J. K. Behr, A. S. Bell, G. Bella, L. Bellagamba, A. Bellerive, M. Bellomo, K. Belotskiy, O. Beltramello, N. L. Belyaev, O. Benary, D. Benchekroun, M. Bender, K. Bendtz, N. Benekos, Y. Benhammou, E. Benhar Noccioli, J. Benitez, D. P. Benjamin, M. Benoit, J. R. Bensinger, S. Bentvelsen, L. Beresford, M. Beretta, D. Berge, E. Bergeaas Kuutmann, N. Berger, J. Beringer, S. Berlendis, N. R. Bernard, G. Bernardi, C. Bernius, F. U. Bernlochner, T. Berry, P. Berta, C. 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Caloba, S. Calvente Lopez. Measurement of the inclusive jet cross-sections in proton-proton collisions at \( \sqrt{s}=8 \) TeV with the ATLAS detector, Journal of High Energy Physics, 2017, 20, DOI: 10.1007/JHEP09(2017)020