Measurements of differential production cross sections for a Z boson in association with jets in pp collisions at \( \sqrt{s}=8 \) TeV

Journal of High Energy Physics, Apr 2017

Cross sections for the production of a Z boson in association with jets in proton-proton collisions at a centre-of-mass energy of \( \sqrt{s}=8 \) TeV are measured using a data sample collected by the CMS experiment at the LHC corresponding to 19.6 fb−1. Differential cross sections are presented as functions of up to three observables that describe the jet kinematics and the jet activity. Correlations between the azimuthal directions and the rapidities of the jets and the Z boson are studied in detail. The predictions of a number of multileg generators with leading or next-to-leading order accuracy are compared with the measurements. The comparison shows the importance of including multi-parton contributions in the matrix elements and the improvement in the predictions when next-to-leading order terms are included.

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Measurements of differential production cross sections for a Z boson in association with jets in pp collisions at \( \sqrt{s}=8 \) TeV

Received: November erential production cross sections M. Gouzevitch 0 1 2 3 4 5 6 7 G. Grenier 0 1 2 3 4 5 6 7 B. Ille 0 1 2 3 4 5 6 7 F. Lagarde 0 1 2 3 4 5 6 7 I.B. Laktineh 0 1 2 3 4 5 6 7 M. Lethuillier 0 1 2 3 4 5 6 7 L. Mirabito 0 1 2 3 4 5 6 7 0 Open Access , Copyright CERN 1 s = 8 TeV are measured using 2 [46] R. Frederix , S. Frixione, V. Hirschi, F. Maltoni, R. Pittau and P. Torrielli, Four-lepton 3 Florida State University , Tallahassee , USA 4 University of Minnesota , Minneapolis , USA 5 Rice University , Houston , USA 6 tute' (MEPhI) , Moscow , Russia 7 University , Budapest , Hungary Cross sections for the production of a Z boson in association with jets in proton-proton collisions at a centre-of-mass energy of p a data sample collected by the CMS experiment at the LHC corresponding to 19.6 fb 1. Di erential cross sections are presented as functions of up to three observables that describe the jet kinematics and the jet activity. Correlations between the azimuthal directions and the rapidities of the jets and the Z boson are studied in detail. The predictions of a number of multileg generators with leading or next-to-leading order accuracy are compared with the measurements. The comparison shows the importance of including multi-parton contributions in the matrix elements and the improvement in the predictions when nextto-leading order terms are included. ArXiv ePrint: 1611.03844 for the bene t of the CMS Collaboration. Hadron-Hadron scattering (experiments); Particle and resonance production 8 TeV boson in association with jets in pp collisions 1 Introduction 2 3 4 The CMS collaboration The CMS detector, simulation, and data samples Event reconstruction and selection Background subtraction and correction for the detector response Systematic uncertainties Theoretical predictions Jet transverse momentum Jet and Z boson rapidity Di erential cross section in jet HT Di erential cross section for the dijet invariant mass Multidimensional di erential cross sections The high centre-of-mass energy of proton-proton (pp) collisions at the CERN LHC produces events with large jet transverse momenta (pT) and high jet multiplicities in association with a Z= boson. For convenience Z= is denoted as Z. The selection of events in which the Z boson decays into two oppositely charged electrons or muons provides a signal sample that is not signi cantly contaminated by background processes. This decay channel can be reconstructed with high e ciency due to the presence of charged leptons in the nal state and is well suited for the validation of calculations within the framework of perturbative quantum chromodynamics (QCD). Furthermore, the production of massive vector bosons with jets is an important background to a number of standard model (SM) processes (single top and tt production, vector boson fusion, WW scattering, Higgs boson production) as well as searches for physics beyond the SM. A good understanding of this background is vital to these searches and measurements. Perturbative QCD calculations of the di erential cross sections involve di erent powers of the strong coupling constant s and di erent kinematic scales and are therefore technically challenging. The issue has been addressed over the last 15 years by merging processes with di erent parton multiplicities before the parton showering, initially at tree level, and more recently with matrix elements calculated at next-to-leading order (NLO) using multileg matrix-element (ME) event generators [1, 2]. In this paper we present measurements of the di erential cross sections for Z boson production in association with jets at p s = 8 TeV, in the electron and muon decay channels, using a data sample corresponding to an integrated luminosity of 19.6 fb 1 measurements are compared with calculations obtained from di erent multileg ME event generators with leading order (LO) MEs (tree level), NLO MEs and a combination of NLO and LO MEs. Measurements of the Z + jets cross section were previously reported by the CDF and D0 Collaborations in proton-antiproton (pp) collisions at a centre-of-mass energy s = 7 TeV were published by the ATLAS [5, 6] and CMS [7, 8] Collaborations. The cross sections are restricted to the phase space where the lepton transverse momenta are greater than 20 GeV, their absolute pseudorapidities are less than 2:4, and the dilepton mass is in the interval 91 20 GeV. The jets are de ned using the infrared and collinear safe anti-kt algorithm applied to all visible particles; the radius parameter is set to 0.5 [9]. The four-momenta of the particles are summed and therefore the jets can be massive. The di erential cross sections include only those jets with transverse momentum is the azimuthal angle. In addition, the absolute jet rapidity is required to be smaller than 2.4. The jets are referred to as 1st, 2nd, 3rd, etc. according to their transverse momenta, starting with the highest-pT jet, and denoted as j1, j2, j3, etc. To further investigate the QCD dynamics towards low Bjorken-x values, multidimensional di erential cross sections are measured for Z + 1 jet production in an extended phase space with jet rapidities up to 4.7. The extension of the rapidity coverage from 2.4 to 4.7 is used to tag events from vector boson fusion (e.g., Higgs production). Typically, the Z + jets events constitute a background for such processes, and a good understanding of their production di erential cross section including jets in the forward region is important. For each jet multiplicity (Njets) a number of measurements are made: the total cross section in the de ned phase space, the di erential cross sections as functions of the jet transverse momentum scalar sum HT, and the di erential cross sections as a function of the individual jet kinematics (transverse momentum pT, and absolute rapidity jyj). For the leading jet a double di erential cross section is measured as a function of its absolute rapidity and transverse momentum. Correlations in the jet kinematics are studied with one-dimensional and multidimensional di erential cross section measurements, via 1) the distributions in the azimuthal angles between the Z boson and the leading jet and between the two leading jets, and 2) the rapidity distributions of the Z boson and the leading jet. These two rapidities are used as variables of a three-dimensional di erential cross section measurement together with the transverse momentum of the jet. The Lorentz boost along the beam axis introduces a large correlation amongst the Z boson and the jet rapidities. The two rapidities are combined to form a variable uncorrelated with the event boost along the beam axis, ydi = 0:5 jy(Z) y(ji)j and a highly boost-dependent variable, these variables. The distribution of ydi is mostly sensitive to the parton scattering, while ysum is expected to be sensitive to the parton distribution functions (PDFs) of the proton. The Drell-Yan process, where the Z boson can decay into a pair of neutrinos, is a background to searches for new phenomena, such as dark matter, supersymmetry, and other theories beyond the SM that predict the presence of invisible particle(s) in the nal state. It is particularly important when the Z boson has a large transverse momentum, leading to a large missing transverse energy. The azimuthal angle between the jets is a good handle to suppress backgrounds coming from QCD multijet events, while the HT variable can be used to select events with large jet activity. For such analyses it is important to have a good model of Z + jets production and therefore a good understanding of these observables. This motivates the measurement of the distributions of the azimuthal angles between the jets and between the Z boson and the jets for di erent thresholds applied to the Z boson transverse momentum, the HT variable, and the jet multiplicity. These angles can be measured with high precision, and thus provide an excellent avenue to test the accuracy of SM predictions [10]. The dijet mass is an essential observable in the selection of Higgs boson events produced by vector boson fusion and it is important to model well both this process and its backgrounds. This observable is measured in Z + jets events for the two leading jets. Section 2 describes the experimental setup and the data samples used for the measurements, while the object reconstruction and the event selection are presented in section 3. Section 4 is dedicated to the subtraction of the background contribution and the correction of the detector response, and section 5 to the estimation of the measurement uncertainties. Finally, the results are presented and compared to di erent theoretical predictions in section 6 and summarised in section 7. The CMS detector, simulation, and data samples The central feature of the CMS apparatus is a superconducting solenoid of 6 m internal diameter, providing a magnetic eld of 3.8 T. Within the solenoid volume are a silicon pixel and strip tracker covering the range j j < 2:5 together with a calorimeter covering the range j j < 3. The latter consists of a lead tungstate crystal electromagnetic calorimeter (ECAL), and a brass and scintillator hadron calorimeter (HCAL). The HCAL is complemented by an outer calorimeter placed outside the solenoid used to measure the tails of hadron calorimeter built using radiation-hard technology. Gas-ionization detectors exploiting three technologies, drift tubes, cathode strip chambers, and resistive-plate chambers, are embedded in the steel ux-return yoke outside the solenoid and constitute the muon system, used to identify and reconstruct muons over the range j j < 2:4. A more detailed description of the CMS detector, together with a de nition of the coordinate system used and the relevant kinematic variables, can be found in ref. [11]. Simulated events are used to both subtract the contribution from background processes and to correct for the detector response. The signal and the background (from WW, WZ, ZZ, tt, and single top quark processes) are modelled with the tree-level matrix element event generator MadGraph v5.1.3.30 [12] interfaced with pythia 6.4.26 [13]. The PDF CTEQ6L1 [14] and the Z2* pythia 6 tune [15, 16] are used. For the ME calculations, s is set to 0:130 at the Z boson mass scale. The ve processes pp ! Z + Njets jets, Njets = 0; : : : ; 4, are included in the ME calculations. The kt MLM [17, 18] scheme with the merging scale set to 20 GeV is used for the matching of the parton showering (PS) with the ME calculations. The same setup is used to estimate the background from + jets. The signal sample is normalised to the inclusive cross section calculated at next-to-next-to-leading order (NNLO) with fewz 2.0 [19] using the CTEQ6M PDF set [14]. Samples of WW, WZ, ZZ events are normalised to the inclusive cross section calculated at NLO using the mcfm 6.6 [20] generator. Finally, an NNLO plus next-tonext-to-leading log (NNLO + NNLL) calculation [21] is used for the normalisation of the tt sample. When comparing the measurements with the predictions from theory, several other event generators are used for the Drell-Yan process. Those, which are not used for the measurement itself, are described in section 6. The detector response is simulated with Geant4 [22]. The events reconstructed by the detector contain several superimposed proton-proton interactions, including one interaction with a high pT track that passes the trigger requirements. The majority of interactions, which do not pass trigger requirements, typically produce low energy (soft) particles because of the larger cross section for these soft events. The e ect of this superposition of interactions is denoted as pileup. The samples of simulated events are generated with a distribution of the number of proton-proton interactions per beam bunch crossing close to the one observed in data. The number of pileup interactions, averaging around 20, varies with the beam conditions. The correct description of pileup is ensured by reweighting the simulated sample to match the measured distribution of pileup interactions. Event reconstruction and selection Events with at least two leptons (electrons or muons) are selected. The trigger accepts events with two isolated electrons (muons) with a pT of at least 8 and 17 GeV. After reconstruction these leptons are restricted to a kinematic and geometric acceptance of pT > 20 GeV and j j < 2:4. We require that the oppositely charged, same- avor leptons form a pair with an invariant mass within a window of 91 20 GeV. The ECAL barrelendcap transition region 1:444 < j j < 1:566 is excluded for the electrons. The acceptance is extended to the full j j < 2:4 region when correcting for the detector response. Information from all detectors is combined using the particle- ow (PF) algorithm [23, 24] to produce an event consisting of reconstructed particle candidates. The PF candidates are then used to build jets and calculate lepton isolation. The quadratic sum of transverse momenta of the tracks associated to the reconstructed vertices is used to select the primary vertex (PV) of interest. Because pileup involves typically soft particles, the PV with the highest sum is chosen. The electrons are reconstructed with the algorithm described in ref. [25]. Identi cation criteria based on the electromagnetic shower shape and the energy sharing between R = ECAL and HCAL are applied. The momentum is estimated by combining the energy measurement in the ECAL with the momentum measurement in the tracker. For each electron candidate, an isolation variable, quantifying the energy ow in the vicinity of its trajectory, is built by summing the transverse momenta of the PF candidates within a cone of size compatible with the primary event vertex. This sum is a ected by neutral particles from pileup events, which cannot be rejected with a vertex criterion. An average energy density R is calculated event by event using the method introduced in ref. [26] and used to estimate and subtract the neutral particle contribution. The electron is considered isolated if the isolation variable value is less than 15% of the transverse momentum of the electron. The electron candidates are required to be consistent with a particle originating from the PV in the event. Muon candidates are matched to tracks measured in the tracker, and they are required to satisfy the identi cation and quality criteria described in ref. [27] that are based on the number of tracker hits and the response of the muon detectors. The background from cosmic ray muons, which appear as two back-to-back muons, is reduced by criteria on the impact parameter and by requiring that the muon pairs have an acollinearity larger than 2.5 mrad. An isolation variable is de ned that is similar to that for electrons, but with a neutral pileup particles. For the muons this contribution is estimated from the sum of the transverse momenta of the charged particles rejected by the vertex requirement, considered as coming from pileup. This sum is multiplied by a factor of 0.5 to take into account the relative fraction of neutral and charged particles. A muon is considered isolated if the isolation variable value is below 20% of its transverse momentum. The e ciencies for the lepton trigger, reconstruction, and identi cation are measured with the \tag-and-probe" method [28]. The simulation is corrected using the ratios of the e ciencies obtained in the data sample to those obtained in the simulated sample. These scale factors for lepton reconstruction and identi cation typically range from 0.95 to 1.05 depending on the lepton transverse momentum and rapidity. The overall e ciency of trigger and event selection is 58% for the electron channel and 88% for the muon channel. The anti-kT algorithm, with a radius parameter of 0.5, is used to cluster PF candidates to form hadronic jets. The jet momentum is determined as the vectorial sum of all particle momenta. Charged hadrons identi ed as coming from a pileup event vertex are rejected from the jet clustering. The remaining contribution from pileup events, which comes from neutral hadrons and from charged hadrons whose PV has not been unambiguously identi ed, is estimated and subtracted event-by-event using a technique based on the jet area method [9, 29]. Jet energy corrections are derived from the simulation, and are con rmed with in situ measurements using the energy balance of dijet and photon+jet events [30]. Jets with a transverse momentum less than 30 GeV or overlapping within The single di erential cross sections are measured for jet rapidity within jyj < 2:4, which is the region with the best jet resolution and pileup rejection. In this measurement, the jet multiplicity refers to the number of jets ful lling the jet criteria, within the jyj < 2:4 ito 1 = 7 = 7 = 0 = 1 = 2 = 3 = 4 = 5 = 6 = 0 = 1 = 2 = 3 = 4 = 5 = 6 level in the jet rapidity region jyj < 2:4. The data points are shown with statistical error bars. Beneath each plot the ratio of the number of events predicted by the simulation to the measured values is displayed, together with the statistical uncertainties in simulation and data added in boundary for the one-dimensional di erential cross sections. For the multidimensional di erential cross sections reported in section 6.8 the region for the jet rapidity is extended Background subtraction and correction for the detector response In gure 1 the event yield in the electron and muon channels is compared to the simulation. The agreement between simulation and data is excellent up to four jets. Since the Z + jets simulation does not include more than four partons in the ME calculations, we expect a less accurate prediction of the signal for jet multiplicities above four. Background contamination is below 1% for a jet multiplicity of one and increases with the jet multiplicity. The background represents 2% of the event yield for a jet multiplicity of 2 and 20% for a jet multiplicity of 5. The background contribution is estimated from the samples of simulated events described in section 2 and subtracted bin-by-bin from the data. The simulations are validated data control sample, as explained in section 5. The background contribution from multijet events where the jets are misidenti ed as leptons is checked with a lepton control sample using two leptons with the same avor and charge and found to be negligible. Unfolding the detector response corrects the signal distribution for the migration of events between closely separated bins and across boundaries of the ducial region. The unfolding procedure also includes a correction for the e ciency of the trigger, and the lepton reconstruction and identi cation. The unfolding procedure is applied separately to each measured di erential cross section. In a rst step, the data distribution is corrected to remove the background contribution and the contribution from signal process events outside of the de ned phase space. Then, the iterative D'Agostini method [31], as implemented in the statistical analysis toolkit RooUnfold [32], is used to correct for bin-to-bin migration and for e ciency. Using the simulation the method generates a response matrix that relates the probability that an event in bin i of the di erential cross section is reconstructed in bin j. These probabilities include the case of bin-i events that do not pass the selection criteria on the reconstructed event or fall outside the distribution boundaries. For the three-dimensional di erential cross section, the method is applied within each (y(j1); y(Z)) bin, where the unfolding is performed with respect to the pT(j1) observable. Similarly, the unfolding of the double di erential cross sections is performed with respect to the most The response matrices are built from reconstructed and generated quantities using the MadGraph 5 + pythia 6 Z + jets simulation sample. The generated values refer to the leptons from the decay of the Z boson and to the jets built from the stable particles using the same algorithm as for the measurements. The momenta of all the photons whose distance to the lepton axis is smaller than 0.1 are added to the lepton momentum to account for the e ects of nal-state radiation, and the lepton is said to be \dressed". Although this process does not recover all the nal-state radiation; it removes most di erences between electrons and muons, and the dilepton mass spectra are identical for the two decay channels after this procedure, as checked with the MadGraph 5 + pythia 6 simulation. The Z boson is reconstructed from the dressed lepton momentum vectors. The phase space for the cross section measurement is restricted to pT > 20 GeV and j j < 2:4 for both dressed charged leptons, a dilepton mass within 91 20 GeV, and the jet kinematics constrained to pT > 30 GeV and jyj < 2:4. For the extended multidimensional cross sections the phase space is extended to jyj < 4:7. The measured cross section values include the Z branching fraction to a single lepton The rejection of jets originating from pileup is more di cult outside the tracker geometric acceptance, since the vertex constraint cannot be used to reject the charged particles coming from pileup. Consequently, despite the jet pileup rejection criterion, a contamination of jets from pileup remains and needs to be subtracted. This region beyond the tracker acceptance, 2:5 < jyj < 4:7, is used only for the Z + 1 jet multidimensional di erential cross section measurements, where only the leading jet is relevant. The fraction of events in which a jet comes from pileup, denoted as fPU, is estimated using a control sample of a Z boson associated with one jet, obtained by requiring one jet with pT above 30 GeV and a veto condition of no other jets with pT > 12 GeV and above 20% of the Z boson transverse momentum. Since a Z boson and a jet coming from two di erent pp collisions are independent, the distribution of (Z; j) is expected to be at, which is con rmed by the simulation. For the Z boson and the jet from a pp ! Z + 1 jet event the distribution is expected to peak at . The constraint on additional jets enforces the pT balance between the Z boson and the jet, reducing the contribution to low values of (Z; j). The simulation shows that this contribution is negligible in the region (Z; j) < 1. Therefore, fPU is estimated from the fraction of events in that region. The value of fPU is 30% in the most forward part (3:2 < jyj < 4:7) and lowest pT measurement bin (30 GeV to 40 GeV). The fraction of pileup events estimated from the pileup control sample is used to correct the signal data sample. The same method is applied to the simulation. The ratio of the value of fPU obtained from the simulation to that measured in data decreases monotonically as a function of pT. In the pT bin 30{50 GeV it ranges up to 1.25 (1.35) for jy(j1)j between 2.5 are identical with or without the pileup subtraction. Since the jy(j)j < 2:4 region contains the bulk of the events and including the jy(j)j > 2:4 region does not improve the precision of the measurement, most of the di erential cross section measurements are limited to jy(j)j < 2:4. The subtraction of pileup contributions is not needed when con ning measurements to this region. Systematic uncertainties The systematic uncertainty in the background-subtracted data distributions is estimated by varying independently each of the contributing factors before the unfolding, and computing the di erence induced by the variation in the unfolded distributions. The observed di erence between the positive and negative uncertainties is small and the two are therefore averaged. The di erent sources of uncertainties are independent and are added in quadrature. The unfolded histogram can be written as a linear combination of the bin contents of the background-subtracted data histogram [31]. This linear combination is used to propagate analytically the statistical uncertainties to the unfolded results and calculate the full covariance matrix for each distribution, separately for each Z boson decay channel. The dominant source of systematic uncertainties is the jet energy correction. The various contributions are listed in table 1. The jet energy correction uncertainty (JEC in the table) is calculated by varying this correction by one standard deviation. This uncertainty is pT- and -dependent and varies from 1.5% up to 5% for j j < 2:5 and from 7% to 30% for j j > 2:5. The uncertainty in the measured cross section is between 5.3% and 28% depending on the jet multiplicity. The jet energy resolution (JER) uncertainty is estimated for data and simulation in ref. [33]. The resulting uncertainty in the measurement is below 1% for all the multiplicities. Other signi cant background contributions come from tt, diboson, and Z ! processes. The related uncertainty (Bkg) is estimated by varying the cross section for each of the background processes (tt, ZZ, WZ, and WW) independently by 10% for tt and 6% for diboson processes. The normalisation variation for the tt events is chosen to cover the maximum observed di erence between the simulation and the data in the jet multiplicity, transverse momentum, and rapidity distributions when selecting events with two leptons of oppositely charged, di erent avours ( e ). The uncertainty in diboson cross sections covers theoretical and PDF contributions. The resulting uncertainty in the measurement increases with the jet multiplicity and reaches 4.3%. Another source of uncertainty is the modelling of the pileup (PU). The number of interactions per bunch crossing in simulated samples is varied by 5%. This covers e ects a function of the exclusive jet multiplicity and details of the systematic uncertainties. The column denoted Tot unc contains the total uncertainty; the column denoted Stat contains the statistical uncertainty; the remaining columns contain the systematic uncertainties. related to the modeling of simulated minimum bias events of 3%, the estimate of the number of interactions per bunch crossing in data based on luminosity measurements of 2.6%, and the experimental uncertainties entering inelastic cross section measurements of 2.9%. The resulting uncertainties range from 0.26% to 5.6% depending on the jet multiplicity. The uncertainty from the pileup subtraction performed in the forward region, jyj > 2:5, is estimated by varying up and down the pileup fraction fPU described in section 4 by half the di erence from the value obtained in the simulation. In the region covered by the tracker and where no correction is applied, it is veri ed that the jet multiplicity does not depend on the number of vertices reconstructed in the event. This indicates that the jets from pileup events have a negligible impact on the measurement. The unfolding procedure has an uncertainty due to its dependence on the simulation used to estimate the response matrix (Unf sys) and to the nite size of the simulation sample (Unf stat). The rst contribution is estimated using an alternative event generator, sherpa 1.4 [34], and taking the di erence between the two results to represent the uncertainty. The distribution obtained with the alternative generator di ers su ciently from the nominal one to cover the di erences with the data. The statistical uncertainty in the response matrix is analytically propagated to the unfolded result [31]. When added in quadrature and depending on the kinematic variable and jet multiplicity, the total unfolding uncertainty varies up to 10%. The uncertainty in the e ciency of the lepton reconstruction, identi cation, and isolation is propagated to the measurement by varying the total data-to-simulation scale factor by one standard deviation. It amounts to 2.5% and 2.6% in the dimuon and dielectron channels, respectively. The uncertainty in the integrated luminosity amounts to 2.6% [35]. Since the background event yield normalisation also depends on the integrated luminosity, the e ect of the above uncertainty on the background yield (Lumi) can be larger and amounts to 3.9% in the bins with low signal purity. The measurements from the electron and muon channels are consistent and are combined using a weighted average. For each bin of the measured di erential cross sections, the results of each of the two measurements are weighted by the inverse of the squared total uncertainty. The covariance matrix of the combination, the diagonal elements of which are used to extract the measurement uncertainties, is computed assuming full correlation between the two channels for all the uncertainty sources except for statistical uncertainties and those associated with lepton reconstruction and identi cation, which are taken to be uncorrelated. The measured di erential cross sections are compared to the results obtained from three di erent calculations as described below. Theoretical predictions The measurements are compared to a tree level calculation and two multileg NLO calculations. The rst prediction is computed with MadGraph 5 [12] interfaced with pythia 6 (denoted as MG5 + PY6 in the gure legends), for parton showering and hadronisation, with the con guration described in section 2. The total cross section is normalised to the NNLO cross section computed with fewz 2.0 [19]. Two multileg NLO predictions including parton showers using the MC@NLO [36] method are used. For these two predictions the total cross section is normalised to the one obtained with the respective event generators. The total cross section values used for the normalisation are summarised in table 2. rst multileg NLO prediction with parton shower is computed with sherpa 2 (2.0.0) [34] and BlackHat [37, 38] for the one-loop corrections. The matrix elements include the ve processes pp ! Z + Njets jets; Njets 4, with an NLO accuracy for Njets calculations and showering description. The merging of PS and ME calculations is done with the MEPS@NLO method [1] and the merging scale is set to 20 GeV. The second multileg NLO prediction is computed with MadGraph5 aMC@NLO [40] (denoted as mg5 amc in the following) interfaced with pythia 8 using the CUETP8M1 tune [16, 41] for parton showering, underlying events, and hadronisation. The matrix elements include the Z boson production processes with 0, 1, and 2 partons at NLO. The FxFx [2] merging scheme is used with a merging scale parameter set to 30 GeV. The NNPDF 3.0 NLO PDF [42] is used for the ME calculations while the NNPDF 2.3 QCD + QED LO [43, 44] is used for the backward evolution of the showering. For the ME calculations, s is set to the current PDG world average [45] rounded to s(mZ) = 0:118. For the showering and underlying events the value of the CUETP8M1 tune, s(mZ) = 0:130, is used. The larger value is expected to compensate for the missing higher order include the contribution from the xed-order calculation and from the NNPDF 3.0 PDF set. The two uncertainties are added in quadrature. The xed-order calculation uncertainties are estimated by varying the renormalisation and the factorisation scales by factors of MadGraph 5 + pythia 6, 4 j LO+PS 2 j NLO, 3; 4 j LO+PS mg5 amc + pythia 8, 2 j NLO Dilepton mass Native cross window [GeV] section [pb] comparison plots. The cross section used for the plots together with the one obtained from the generated sample (\native") and their ratio (k) are provided. The cross section values correspond to the dilepton mass windows used for the respective samples and indicated in the table. the uncertainty. The reweighting method [46] provided by the mg5 amc generator is used to derive the cross sections with the di erent renormalisation and factorisation scales and with the di erent PDF replicas used in the PDF uncertainty determination. For the NLO predictions, weighted samples are used (limited to 1 weights in the case of aMC@NLO), which can lead to larger statistical uctuations than expected for unweighted samples in some bins of the histograms presented in this section. The cross sections for jet multiplicities from 0 to 7, and the comparisons with various predictions are presented in this section. Figure 2 shows the cross section for both inclusive and exclusive jet multiplicities and the numbers are compared with the prediction obtained with mg5 amc + pythia 8 in table 3 for the exclusive case. The agreement with the predictions is very good for jet multiplicities up to the maximum number of nal-state partons included in the ME calculations, namely three for mg5 amc + pythia 8 and four for both MadGraph 5 + pythia 6 and sherpa 2. The level of precision of the measurement does not allow us to probe the improvement expected from the additional NLO terms. The cross section is reduced by a factor of ve for each additional jet. The predictions already agree well at tree level (MadGraph 5 + pythia 6) renorcalculation, which does not include this jet multiplicity in the matrix elements, predicts a di erent cross section from those that do. The predictions that include four jets in the matrix elements are in better agreement with the data, but the di erence between the predictions is limited to roughly one standard deviation of the measurement uncertainty. The large uncertainty is due to the sensitivity of the jet pT threshold acceptance to the MadGraph 5 + pythia 6, while neither of these includes this multiplicity in the ME calculations. The theoretical uncertainty shown in the gure for the mg5 amc + pythia 8 prediction uses the standard method described in the previous subsection. In the case of the exclusive jet multiplicity, the presence of large logarithms in the perturbative calculation can lead to an underestimate of this uncertainty, so the Steward and Tackmann prescription (ST) provides a better estimate [47]. The uncertainties calculated with both 0.00060 (syst) 0.00051 (stat) 0.0622 +00::00006732 0.0096 +00::00001113 0.00157+00::0000002236 The cross section calculated with mg5 amc is given in the third column together with the total uncertainty that covers the theoretical (standard method), PDF, s, and statistical uncertainties. The theoretical uncertainty obtained with the standard and ST methods are compared in the two last columns. The uncertainty on the measurement is separated in systematic and statistical components when the latter is not negligible. prescriptions are provided in table 3. For the calculations considered here, the increase of the ST uncertainty with respect to the standard one is moderate. This is consistent with the observation that the agreement with the measurement and the coverage of the di erence by the theoretical uncertainty in gure 2 is similar for the inclusive and exclusive Jet transverse momentum Knowledge of the kinematics of SM events with large jet multiplicity is essential for the LHC experiments since these events are backgrounds to searches for new physics that predict decay chains of heavy coloured particles, such as squarks, gluinos, or heavy top quark partners. The measured di erential cross sections as a function of jet pT for the 1st, 2nd, 3rd, 4th, and 5th jets are presented in gures 3{5. The cross sections fall rapidly with increasing pT. The cross section for the leading jet is measured for pT values between 30 GeV and 1 TeV and decreases by more than ve orders of magnitude over this range. The cross section for the fth jet is measured for pT values between 30 and 100 GeV and decreases even faster, mainly because of the phase space covered. For the leading jet, the agreement of the MadGraph 5 + pythia 6 prediction with the measurement is very good up to 150 GeV. Discrepancies are observed from 450 GeV. A similar excess in the ratio with the tree-level calculation was observed at well as in the ATLAS measurement [5], which used Alpgen [48] interfaced to herwig [49] for the predictions. The calculations that include NLO terms for this jet multiplicity do not Njse 102 t taaD 1.5 / anti-kT (R = 0.5) jets Nje 102 d taaD 1.5 / anti-kT (R = 0.5) jets CMS SHERPA 2 (? 2j NLO 3,4j LO + PS) MG5_aMC + PY8 (? 2j NLO + PS) CMS SHERPA 2 (? 2j NLO 3,4j LO + PS) MG5_aMC + PY8 (? 2j NLO + PS) = 0 = 1 = 2 = 3 = 4 = 5 = 6 = 7 ? 0 ? 1 ? 2 ? 3 ? 4 ? 5 ? 6 ? 7 exclusive and (right) inclusive jet multiplicity distributions compared to the predictions calculated with MadGraph 5 + pythia 6, sherpa 2, and mg5 amc + pythia 8. The lower panels show the ratios of the theoretical predictions to the measurements. Error bars around the experimental points show the statistical uncertainty, while the cross-hatched bands indicate the statistical and systematic uncertainties added in quadrature. The boxes around the mg5 amc + pythia 8 to measurement ratio represent the uncertainty on the prediction, including statistical, theoretical (from scale variations), and PDF uncertainties. The dark green area represents the statistical and theoretical uncertainties only, while the light green area represents the statistical uncertainty alone. show this discrepancy. The prediction from sherpa 2 shows some disagreement with data in the low transverse momentum region. The second jet shows similar behaviour. Both MadGraph 5 + pythia 6 and mg5 amc + pythia 8 are in good agreement with the measurement for the third jet pT spectrum. The shape predicted by the calculations from sherpa 2 di ers from the measurement since the predicted spectrum is harder. For the 4th jet, the three predictions agree well with the measurements. Calculations from sherpa 2 and mg5 amc + pythia 8 predict di erent spectra. Based on the experimental uncertainties it is di cult to arbitrate between the two, although we expect the one that includes four partons in the matrix elements to be more accurate. The agreement of sherpa 2 and MadGraph 5 + pythia 6 calculations with the measured 5th jet pT spectrum is similar. In summary, including many jet multiplicities in the matrix elements provides a good description of the di erent jet transverse momentum spectra. Including NLO terms improves the agreement with the measured spectra. Nevertheless, some di erences are observed between the predictions calculated with sherpa 2 and mg5 amc + pythia 8. The two calculations di er in many ways, other than the xed order: di erent PDF choices, j)p1T10-1 ( d /d? 10-2 GM 0.5 taaD 1.5 / anti-kT (R = 0.5) jets CMS SHERPA 2 (? 2j NLO 3,4j LO + PS) MG5_aMC + PY8 (? 2j NLO + PS) CMS SHERPA 2 (? 2j NLO 3,4j LO + PS) MG5_aMC + PY8 (? 2j NLO + PS) p /d? 10-2 GM 0.5 taaD 1.5 / anti-kT (R = 0.5) jets 100 200 300 400 500 600 700 800 900 1000 the (left) 1st and (right) 2nd jet pT compared to the predictions calculated with MadGraph 5 + pythia 6, sherpa 2, and mg5 amc + pythia 8. The lower panels show the ratios of the theoretical predictions to the measurements. Error bars around the experimental points show the statistical uncertainty, while the cross-hatched bands indicate the statistical and systematic uncertainties added in quadrature. The boxes around the mg5 amc + pythia 8 to measurement ratio represent the uncertainty on the prediction, including statistical, theoretical (from scale variations), and PDF uncertainties. The dark green area represents the statistical and theoretical uncertainties only, while the light green area represents the statistical uncertainty alone. di erent jet merging schemes, and di erent showering models. In ref. [8] it was shown that the jet pT spectra have little dependence on the PDF choice, therefore the di erence between the two generator is likely to be due to the di erent parton showerings or jet Jet and Z boson rapidity The di erential cross sections as a function of the absolute rapidity of the rst, second, third, fourth, and fth jets are presented in gures 6, 7, and 8, including all events with at least one, two, three, four, and ve jets. The di erential cross sections in jyj have similar shapes for all jets while they vary by about a factor 2 in the range from 0 to 2.4. The predictions obtained with sherpa 2 provide the best overall description regarding the shape of data distributions. The predictions of both MadGraph 5 + pythia 6 and mg5 amc + pythia 8 have a more central distribution than is measured for jets 1 to 4, although this behaviour is less pronounced for the latter. The di erence could be attributed to the di erent showering methods and the di erent PDF choices for the three predictions. Given the experimental uncertainties, the shape of the spectrum of the 5th jet rapidity is equally well described by the three calculations. p [ j) 3 10-1 ( p /d 10-2 ? d 10-3 taaD 1.5 / anti-kT (R = 0.5) jets p /d? 10-2 taaD 1.5 / anti-kT (R = 0.5) jets CMS SHERPA 2 (? 2j NLO 3,4j LO + PS) MG5_aMC + PY8 (? 2j NLO + PS) CMS SHERPA 2 (? 2j NLO 3,4j LO + PS) MG5_aMC + PY8 (? 2j NLO + PS) Stat. ? theo. the (left) 3rd and (right) 4th jet pT compared to the predictions calculated with MadGraph 5 + pythia 6, sherpa 2, and mg5 amc + pythia 8. The lower panels show the ratios of the theoretical predictions to the measurements. Error bars around the experimental points show the statistical uncertainty, while the cross-hatched bands indicate the statistical and systematic uncertainties added in quadrature. The boxes around the mg5 amc + pythia 8 to measurement ratio represent the uncertainty on the prediction, including statistical, theoretical (from scale variations), and PDF uncertainties. The dark green area represents the statistical and theoretical uncertainties only, while the light green area represents the statistical uncertainty alone. The Z boson rapidity distribution is presented in gure 9 with no requirement on the Z boson transverse momentum. To minimize the uncertainties the measurement is done for the normalized distributions. The relative contributions of matrix elements and parton shower depend on the Z transverse momentum. The measurement is also performed with a lower limit of 150 and 300 GeV on the Z boson transverse momentum. Each distribution is normalised to unity. The three calculations are in very good agreement with the measured values. The agreement of the prediction calculated with sherpa 2 degrades when applying a threshold on the Z boson pT, though it is still consistent with data within the statistical The correlations in rapidity between the di erent objects (Z boson and jets) are shown in gures 10 to 14. The normalised cross section is presented as a function of the rapidity MadGraph 5 + pythia 6. Such an e ect was previously observed at p A large discrepancy is observed between the measured cross section and that predicted by s = 7 TeV [50] and is con rmed here with an increased statistical precision and with an extended range in ydi (Z; j1). The discrepancy is signi cantly reduced when a threshold is applied to CMS SHERPA 2 (? 2j NLO 3,4j LO + PS) MG5_aMC + PY8 (? 2j NLO + PS) /beG 10-1 taaD 1.5 / 10-4 anti-kT (R = 0.5) jets the 5th jet pT compared to the predictions calculated with MadGraph 5 + pythia 6, sherpa 2, and mg5 amc + pythia 8. The lower panels show the ratios of the theoretical predictions to the measurements. Error bars around the experimental points show the statistical uncertainty, while the cross-hatched bands indicate the statistical and systematic uncertainties added in quadrature. The boxes around the mg5 amc + pythia 8 to measurement ratio represent the uncertainty on the prediction, including statistical, theoretical (from scale variations), and PDF uncertainties. The dark green area represents the statistical and theoretical uncertainties only, while the light green area represents the statistical uncertainty alone. the transverse momentum of the Z boson as shown in the same gure. This observation supports the attribution of the discrepancy to the matching procedure between the ME and PS, as discussed in [50]. By contrast, a quite good agreement is found, independently of any threshold on the Z boson transverse momentum, for the NLO predictions of sherpa 2 and mg5 amc + pythia 8. This improvement is expected to come from additional diagrams at NLO with a gluon propagator in the t-channel that populate the forward rapidity regions. The presence of additional jets in the event should reduce the dependence on the ME/PS matching for the rst jet since this jet will have a larger pT on average. Figure 11 shows the normalised cross section for Z production with at least two jets as a function of the rapidity di erence between the Z boson and the leading jet, ydi (Z; j1), between the Z boson and the second-leading jet, ydi (Z; j2), and between the Z boson and the system formed by the two leading jets, ydi (Z; dijet). The discrepancies between the measured cross sections and the MadGraph 5 + pythia 6 predictions are present in all three cases, but they are less pronounced than in the one-jet case ( gure 11a compared to gure 10a). The NLO predictions from sherpa 2 and mg5 amc + pythia 8 reproduce the measured dependencies much better than MadGraph 5 + pythia 6 does. | j)( 1 50 taaD 1.5 / 10 panjetti->kT30(RG=eV0,.5|y)jejet|ts< 2.4 | j)( 2 10 taaD 1.5 / 2 panjetti->kT30(RG=eV0,.5|y)jejet|ts< 2.4 SHERPA 2 (? 2j NLO 3,4j LO + PS) MG5_aMC + PY8 (? 2j NLO + PS) SHERPA 2 (? 2j NLO 3,4j LO + PS) MG5_aMC + PY8 (? 2j NLO + PS) 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 the (left) 1st and (right) 2nd jet jyj compared to the predictions calculated with MadGraph 5 + pythia 6, sherpa 2, and mg5 amc + pythia 8. The lower panels show the ratios of the theoretical predictions to the measurements. Error bars around the experimental points show the statistical uncertainty, while the cross-hatched bands indicate the statistical and systematic uncertainties added in quadrature. The boxes around the mg5 amc + pythia 8 to measurement ratio represent the uncertainty on the prediction, including statistical, theoretical (from scale variations), and PDF uncertainties. The dark green area represents the statistical and theoretical uncertainties only, while the light green area represents the statistical uncertainty alone. The rapidity correlation of the two leading jets, independently of the Z boson rapidity, is displayed in gure 12, showing the rapidity sum and rapidity di erence between the two jets. There is a good agreement between the measured cross section and the three predictions for the rapidity sum dependence. The rapidity di erence presents a discrepancy with MadGraph 5 + pythia 6 at large values, while the NLO predictions of sherpa 2 and mg5 amc + pythia 8 are in good agreement with the data. The rapidity sum for the system of the Z boson and the leading jet is studied with di erent thresholds applied to the transverse momentum of the Z boson. Figure 13 shows the normalised cross section as a function of the rapidity sum of the Z boson and the leading 300 GeV. The observed discrepancy between the measured cross section and that predicted by MadGraph 5 + pythia 6 is similar to the e ect that has been found at 7 TeV [50], and is con rmed here with increased statistical precision. The discrepancy almost vanishes when the transverse momentum of the Z boson is required to be larger than 150 GeV. The NLO predictions of sherpa 2 and mg5 amc + pythia 8 are in good agreement with taaD 1.5 / anti-kT (R = 0.5) jets CMS SHERPA 2 (? 2j NLO 3,4j LO + PS) MG5_aMC + PY8 (? 2j NLO + PS) CMS SHERPA 2 (? 2j NLO 3,4j LO + PS) MG5_aMC + PY8 (? 2j NLO + PS) /yd 0.3 | taaD 1.5 / anti-kT (R = 0.5) jets 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 the (left) 3rd and (right) 4th jet jyj compared to the predictions calculated with MadGraph 5 + pythia 6, sherpa 2, and mg5 amc + pythia 8. The lower panels show the ratios of the theoretical predictions to the measurements. Error bars around the experimental points show the statistical uncertainty, while the cross-hatched bands indicate the statistical and systematic uncertainties added in quadrature. The boxes around the mg5 amc + pythia 8 to measurement ratio represent the uncertainty on the prediction, including statistical, theoretical (from scale variations), and PDF uncertainties. The dark green area represents the statistical and theoretical uncertainties only, while the light green area represents the statistical uncertainty alone. the measured cross section independently of the Z boson transverse momentum. This improvement with respect to MadGraph 5 + pythia 6 can be attributed to either the di erent PDF choice, or to the NLO terms. For dijet events, gure 14 shows cross sections as a function of rapidity sums, for the Z boson and the leading jet, for the Z boson and the second-leading jet, and for the Z boson and the dijet system of the two leading jets. Comparison between the measured cross sections and the MadGraph 5 + pythia 6 predictions exhibit a small disagreement for a rapidity sum above 1 for each jet, and the discrepancies increase when the dijet system is considered. Comparison with NLO predictions from sherpa 2 and from mg5 amc + pythia 8 shows a very good agreement. The rapidity correlation study con rms the observations made at p s = 7 TeV, and shows that the behaviour with respect to the tree-level prediction is similar for the correlation with the second jet and enhanced when considering the dijet system consisting of the two leading jets. The study demonstrates that the two NLO predictions improve the agreement with the measurements, especially for the rapidity di erence observables. CMS SHERPA 2 (? 2j NLO 3,4j LO + PS) MG5_aMC + PY8 (? 2j NLO + PS) taaD 1.5 / anti-kT (R = 0.5) jets 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 the 5th jet jyj compared to the predictions calculated with MadGraph 5 + pythia 6, sherpa 2, and mg5 amc + pythia 8. The lower panels show the ratios of the theoretical predictions to the measurements. Error bars around the experimental points show the statistical uncertainty, while the cross-hatched bands indicate the statistical and systematic uncertainties added in quadrature. The boxes around the mg5 amc + pythia 8 to measurement ratio represent the uncertainty on the prediction, including statistical, theoretical (from scale variations), and PDF uncertainties. The dark green area represents the statistical and theoretical uncertainties only, while the light green area represents the statistical uncertainty alone. Di erential cross section in jet HT The hadronic activity of an event can be probed with the scalar sum of the transverse momenta of the jets, HT. Measuring hadronic activity is important in searches for signatures with high jet activity or, by contrast, when wishing to veto such activity, for instance in the central region when looking for vector boson fusion induced processes. In this section we present measurements of the spectra for this variable in Z + jets events. The di erential cross sections are shown in gures 15{17 for the di erent inclusive jet multiplicities. 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De Bruyn, K. Deroover, N. Heracleous, S. Lowette, S. Moortgat, L. Moreels, A. Olbrechts, Q. Python, S. Tavernier, W. Van Doninck, P. Van Mulders, I. Van Parijs Universite Libre de Bruxelles, Bruxelles, Belgium H. Brun, C. Caillol, B. Clerbaux, G. De Lentdecker, H. Delannoy, G. Fasanella, L. Favart, R. Goldouzian, A. Grebenyuk, G. Karapostoli, T. Lenzi, A. Leonard, J. Luetic, T. Maerschalk, A. Marinov, A. Randle-conde, T. Seva, C. Vander Velde, P. Vanlaer, R. Yonamine, F. Zenoni, F. Zhang2 Ghent University, Ghent, Belgium A. Cimmino, T. Cornelis, D. Dobur, A. Fagot, G. Garcia, M. Gul, D. Poyraz, S. Salva, R. Schofbeck, A. Sharma, M. Tytgat, W. Van Driessche, E. Yazgan, N. Zaganidis Universite Catholique de Louvain, Louvain-la-Neuve, Belgium H. Bakhshiansohi, C. Belu 3, O. Bondu, S. Brochet, G. Bruno, A. Caudron, S. De Visscher, C. Delaere, M. Delcourt, B. Francois, A. Giammanco, A. Jafari, P. Jez, M. Komm, V. Lemaitre, A. Magitteri, A. Mertens, M. Musich, C. Nuttens, K. Piotrzkowski, L. Quertenmont, M. Selvaggi, M. Vidal Marono, S. Wertz Universite de Mons, Mons, Belgium Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil W.L. Alda Junior, F.L. Alves, G.A. Alves, L. Brito, C. Hensel, A. Moraes, M.E. Pol, P. Rebello Teles Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil G.G. Da Silveira5, D. De Jesus Damiao, C. De Oliveira Martins, S. Fonseca De Souza, L.M. Huertas Guativa, H. Malbouisson, D. Matos Figueiredo, C. Mora Herrera, L. Mundim, H. Nogima, W.L. Prado Da Silva, A. Santoro, A. Sznajder, E.J. Tonelli Manganote4, A. Vilela Pereira J.C. Ruiz Vargas Universidade Estadual Paulista a, Universidade Federal do ABC b, S~ao Paulo, S. Ahujaa, C.A. Bernardesb, S. Dograa, T.R. Fernandez Perez Tomeia, E.M. Gregoresb, P.G. Mercadanteb, C.S. Moona, S.F. Novaesa, Sandra S. Padulaa, D. Romero Abadb, Institute for Nuclear Research and Nuclear Energy, So a, Bulgaria A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, M. Rodozov, S. Stoykova, G. Sultanov, M. VuUniversity of So a, So a, Bulgaria A. Dimitrov, I. Glushkov, L. Litov, B. Pavlov, P. Petkov Beihang University, Beijing, China H. Zhang, J. Zhao Institute of High Energy Physics, Beijing, China M. Ahmad, J.G. Bian, G.M. Chen, H.S. Chen, M. Chen, Y. Chen7, T. Cheng, C.H. Jiang, D. Leggat, Z. Liu, F. Romeo, S.M. Shaheen, A. Spiezia, J. Tao, C. Wang, Z. Wang, State Key Laboratory of Nuclear Physics and Technology, Peking University, Y. Ban, G. Chen, Q. Li, S. Liu, Y. Mao, S.J. Qian, D. Wang, Z. Xu Universidad de Los Andes, Bogota, Colombia C. Avila, A. Cabrera, L.F. Chaparro Sierra, C. Florez, J.P. Gomez, C.F. Gonzalez Hernandez, J.D. Ruiz Alvarez, J.C. Sanabria University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Split, Croatia N. Godinovic, D. Lelas, I. Puljak, P.M. Ribeiro Cipriano, T. Sculac University of Split, Faculty of Science, Split, Croatia Z. Antunovic, M. Kovac Institute Rudjer Boskovic, Zagreb, Croatia V. Brigljevic, D. Ferencek, K. Kadija, S. Micanovic, L. Sudic, T. Susa University of Cyprus, Nicosia, Cyprus A. Attikis, G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos, P.A. Razis, Charles University, Prague, Czech Republic M. Finger8, M. Finger Jr.8 Universidad San Francisco de Quito, Quito, Ecuador E. Carrera Jarrin Academy of Scienti c Research and Technology of the Arab Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt A. Ellithi Kamel9, M.A. Mahmoud10;11, A. Radi11;12 National Institute of Chemical Physics and Biophysics, Tallinn, Estonia B. Calpas, M. Kadastik, M. Murumaa, L. Perrini, M. Raidal, A. Tiko, C. Veelken Department of Physics, University of Helsinki, Helsinki, Finland P. Eerola, J. Pekkanen, M. Voutilainen Helsinki Institute of Physics, Helsinki, Finland J. Harkonen, V. Karimaki, R. Kinnunen, T. Lampen, K. Lassila-Perini, S. Lehti, T. Linden, P. Luukka, J. Tuominiemi, E. Tuovinen, L. Wendland Lappeenranta University of Technology, Lappeenranta, Finland J. Talvitie, T. Tuuva IRFU, CEA, Universite Paris-Saclay, Gif-sur-Yvette, France M. Besancon, F. Couderc, M. Dejardin, D. Denegri, B. Fabbro, J.L. Faure, C. Favaro, F. Ferri, S. Ganjour, S. Ghosh, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry, I. Kucher, E. Locci, M. Machet, J. Malcles, J. Rander, A. Rosowsky, M. Titov, A. Zghiche Laboratoire Leprince-Ringuet, Ecole Polytechnique, IN2P3-CNRS, Palaiseau, Institut Pluridisciplinaire Hubert Curien, Universite de Strasbourg, Universite de Haute Alsace Mulhouse, CNRS/IN2P3, Strasbourg, France J.-L. Agram13, J. Andrea, A. Aubin, D. Bloch, J.-M. Brom, M. Buttignol, E.C. Chabert, N. Chanon, C. Collard, E. Conte13, X. Coubez, J.-C. Fontaine13, D. Gele, U. Goerlach, A.-C. Le Bihan, K. Skovpen, P. Van Hove Centre de Calcul de l'Institut National de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3, Villeurbanne, France Universite de Lyon, Universite Claude Bernard Lyon 1, CNRS-IN2P3, Institut de Physique Nucleaire de Lyon, Villeurbanne, France S. Beauceron, C. Bernet, G. Boudoul, E. Bouvier, C.A. Carrillo Montoya, R. Chierici, D. Contardo, B. Courbon, P. Depasse, H. El Mamouni, J. Fan, J. Fay, S. Gascon, A.L. Pequegnot, S. Perries, A. Popov14, D. Sabes, V. Sordini, M. Vander Donckt, P. Verdier, A. Khvedelidze8 Z. Tsamalaidze8 Georgian Technical University, Tbilisi, Georgia Tbilisi State University, Tbilisi, Georgia RWTH Aachen University, I. Physikalisches Institut, Aachen, Germany C. Autermann, S. Beranek, L. Feld, A. Heister, M.K. Kiesel, K. Klein, M. Lipinski, A. Ostapchuk, M. Preuten, F. Raupach, S. Schael, C. Schomakers, J.F. Schulte, J. Schulz, T. Verlage, H. Weber RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany A. Albert, M. Brodski, E. Dietz-Laursonn, D. Duchardt, M. Endres, M. Erdmann, S. Erdweg, T. Esch, R. Fischer, A. Guth, M. Hamer, T. Hebbeker, C. Heidemann, K. Hoepfner, S. Knutzen, M. Merschmeyer, A. Meyer, P. Millet, S. Mukherjee, M. Olschewski, K. Padeken, T. Pook, M. Radziej, H. Reithler, M. Rieger, F. Scheuch, L. Sonnenschein, D. Teyssier, S. Thuer RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany V. Cherepanov, G. Flugge, W. Haj Ahmad, F. Hoehle, B. Kargoll, T. Kress, A. Kunsken, J. Lingemann, T. Muller, A. Nehrkorn, A. Nowack, I.M. Nugent, C. Pistone, O. Pooth, A. Stahl15 Deutsches Elektronen-Synchrotron, Hamburg, Germany M. Aldaya Martin, C. Asawatangtrakuldee, K. Beernaert, O. Behnke, U. Behrens, A.A. Bin Anuar, K. Borras16, A. Campbell, P. Connor, C. Contreras-Campana, F. Costanza, C. Diez Pardos, G. Dolinska, G. Eckerlin, D. Eckstein, T. Eichhorn, E. Eren, E. Gallo17, J. Garay Garcia, A. Geiser, A. Gizhko, J.M. Grados Luyando, P. Gunnellini, A. Harb, J. Hauk, M. Hempel18, H. Jung, A. Kalogeropoulos, O. Karacheban18, M. Kasemann, J. Keaveney, C. Kleinwort, I. Korol, D. Krucker, W. Lange, A. Lelek, J. Leonard, K. Lipka, A. Lobanov, W. Lohmann18, R. Mankel, I.-A. Melzer-Pellmann, A.B. Meyer, G. Mittag, J. Mnich, A. Mussgiller, E. Ntomari, D. Pitzl, R. Placakyte, A. Raspereza, B. Roland, M.O . Sahin, P. Saxena, T. Schoerner-Sadenius, C. Seitz, S. Spannagel, N. Stefaniuk, G.P. Van Onsem, R. Walsh, C. Wissing University of Hamburg, Hamburg, Germany V. Blobel, M. Centis Vignali, A.R. Draeger, T. Dreyer, E. Garutti, D. Gonzalez, J. Haller, M. Ho mann, A. Junkes, R. Klanner, R. Kogler, N. Kovalchuk, T. Lapsien, T. Lenz, I. Marchesini, D. Marconi, M. Meyer, M. Niedziela, D. Nowatschin, F. Pantaleo15, T. Pei er, A. Perieanu, J. Poehlsen, C. Sander, C. Scharf, P. Schleper, A. Schmidt, S. Schumann, J. Schwandt, H. Stadie, G. Steinbruck, F.M. Stober, M. Stover, H. Tholen, D. Troendle, E. Usai, L. Vanelderen, A. Vanhoefer, B. Vormwald Institut fur Experimentelle Kernphysik, Karlsruhe, Germany C. Barth, C. Baus, J. Berger, E. Butz, T. Chwalek, F. Colombo, W. De Boer, A. Dierlamm, S. Fink, R. Friese, M. Gi els, A. Gilbert, P. Goldenzweig, D. Haitz, F. Hartmann15, S.M. Heindl, U. Husemann, I. Katkov14, P. Lobelle Pardo, B. Maier, H. Mildner, M.U. Mozer, Th. Muller, M. Plagge, G. Quast, K. Rabbertz, S. Rocker, F. Roscher, M. Weber, T. Weiler, S. Williamson, C. Wohrmann, R. Wolf Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece I. Topsis-Giotis G. Anagnostou, G. Daskalakis, T. Geralis, V.A. Giakoumopoulou, A. Kyriakis, D. Loukas, National and Kapodistrian University of Athens, Athens, Greece S. Kesisoglou, A. Panagiotou, N. Saoulidou, E. Tziaferi University of Ioannina, Ioannina, Greece I. Evangelou, G. Flouris, C. Foudas, P. Kokkas, N. Loukas, N. Manthos, I. Papadopoulos, MTA-ELTE Lendulet CMS Particle and Nuclear Physics Group, Eotvos Lorand University, Budapest, Hungary Wigner Research Centre for Physics, Budapest, Hungary G. Bencze, C. Hajdu, P. Hidas, D. Horvath19, F. Sikler, V. Veszpremi, G. Vesztergombi20, Institute of Nuclear Research ATOMKI, Debrecen, Hungary N. Beni, S. Czellar, J. Karancsi21, A. Makovec, J. Molnar, Z. Szillasi Institute of Physics, University of Debrecen M. Bartok20, P. Raics, Z.L. Trocsanyi, B. Ujvari National Institute of Science Education and Research, Bhubaneswar, India S. Bahinipati, S. Choudhury22, P. Mal, K. Mandal, A. Nayak23, D.K. Sahoo, N. Sahoo, Panjab University, Chandigarh, India S. Bansal, S.B. Beri, V. Bhatnagar, R. Chawla, U.Bhawandeep, A.K. Kalsi, A. Kaur, M. Kaur, R. Kumar, P. Kumari, A. Mehta, M. Mittal, J.B. Singh, G. Walia University of Delhi, Delhi, India Ashok Kumar, A. Bhardwaj, B.C. Choudhary, R.B. Garg, S. Keshri, S. Malhotra, M. Naimuddin, N. Nishu, K. Ranjan, R. Sharma, V. Sharma Saha Institute of Nuclear Physics, Kolkata, India R. Bhattacharya, S. Bhattacharya, K. Chatterjee, S. Dey, S. Dutt, S. Dutta, S. Ghosh, N. Majumdar, A. Modak, K. Mondal, S. Mukhopadhyay, S. Nandan, A. Purohit, A. Roy, D. Roy, S. Roy Chowdhury, S. Sarkar, M. Sharan, S. Thakur Indian Institute of Technology Madras, Madras, India Bhabha Atomic Research Centre, Mumbai, India R. Chudasama, D. Dutta, V. Jha, V. Kumar, A.K. Mohanty15, P.K. Netrakanti, L.M. Pant, P. Shukla, A. Topkar B. Sutar Tata Institute of Fundamental Research-A, Mumbai, India T. Aziz, S. Dugad, G. Kole, B. Mahakud, S. Mitra, G.B. Mohanty, B. Parida, N. Sur, Tata Institute of Fundamental Research-B, Mumbai, India S. Banerjee, S. Bhowmik24, R.K. Dewanjee, S. Ganguly, M. Guchait, Sa. Jain, S. Kumar, M. Maity24, G. Majumder, K. Mazumdar, T. Sarkar24, N. Wickramage25 Indian Institute of Science Education and Research (IISER), Pune, India S. Chauhan, S. Dube, V. Hegde, A. Kapoor, K. Kothekar, A. Rane, S. Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran H. Behnamian, S. Chenarani26, E. Eskandari Tadavani, S.M. Etesami26, A. Fahim27, M. Khakzad, M. Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi28, F. Rezaei Hosseinabadi, B. Safarzadeh29, M. Zeinali University College Dublin, Dublin, Ireland M. Felcini, M. Grunewald INFN Sezione di Bari a, Universita di Bari b, Politecnico di Bari c, Bari, Italy M. Abbresciaa;b, C. Calabriaa;b, C. Caputoa;b, A. Colaleoa, D. Creanzaa;c, L. Cristellaa;b, N. De Filippisa;c, M. De Palmaa;b, L. Fiorea, G. Iasellia;c, G. Maggia;c, M. Maggia, G. Minielloa;b, S. Mya;b, S. Nuzzoa;b, A. Pompilia;b, G. Pugliesea;c, R. Radognaa;b, A. Ranieria, G. Selvaggia;b, L. Silvestrisa;15, R. Vendittia;b, P. Verwilligena INFN Sezione di Bologna a, Universita di Bologna b, Bologna, Italy G. Abbiendia, C. Battilana, D. Bonacorsia;b, S. Braibant-Giacomellia;b, L. Brigliadoria;b, R. Campaninia;b, P. Capiluppia;b, A. Castroa;b, F.R. Cavalloa, S.S. Chhibraa;b, G. Codispotia;b, M. Cu ania;b, G.M. Dallavallea, F. Fabbria, A. Fanfania;b, D. Fasanellaa;b, P. Giacomellia, C. Grandia, L. Guiduccia;b, S. Marcellinia, G. Masettia, A. Montanaria, F.L. Navarriaa;b, A. Perrottaa, A.M. Rossia;b, T. Rovellia;b, G.P. Sirolia;b, N. Tosia;b;15 INFN Sezione di Catania a, Universita di Catania b, Catania, Italy S. Albergoa;b, M. Chiorbolia;b, S. Costaa;b, A. Di Mattiaa, F. Giordanoa;b, R. Potenzaa;b, A. Tricomia;b, C. Tuvea;b INFN Sezione di Firenze a, Universita di Firenze b, Firenze, Italy G. Barbaglia, V. Ciullia;b, C. Civininia, R. D'Alessandroa;b, E. Focardia;b, V. Goria;b, P. Lenzia;b, M. Meschinia, S. Paolettia, G. Sguazzonia, L. Viliania;b;15 INFN Laboratori Nazionali di Frascati, Frascati, Italy L. Benussi, S. Bianco, F. Fabbri, D. Piccolo, F. Primavera15 INFN Sezione di Genova a, Universita di Genova b, Genova, Italy V. Calvellia;b, F. Ferroa, M. Lo Veterea;b, M.R. Mongea;b, E. Robuttia, S. Tosia;b INFN Sezione di Milano-Bicocca a, Universita di Milano-Bicocca b, Milano, INFN Sezione di Napoli a, Universita di Napoli 'Federico II' b, Napoli, Italy, Universita della Basilicata c, Potenza, Italy, Universita G. Marconi d, Roma, S. Buontempoa, N. Cavalloa;c, G. De Nardo, S. Di Guidaa;d;15, M. Espositoa;b, F. Fabozzia;c, A.O.M. Iorioa;b, G. Lanzaa, L. Listaa, S. Meolaa;d;15, P. Paoluccia;15, C. Sciaccaa;b, F. Thyssen Trento c, Trento, Italy INFN Sezione di Padova a, Universita di Padova b, Padova, Italy, Universita di P. Azzia;15, N. Bacchettaa, L. Benatoa;b, D. Biselloa;b, A. Bolettia;b, R. Carlina;b, A. Carvalho Antunes De Oliveiraa;b, P. Checchiaa, M. Dall'Ossoa;b, P. De Castro Manzanoa, T. Dorigoa, U. Dossellia, F. Gasparinia;b, U. Gasparinia;b, A. Gozzelinoa, S. Lacapraraa, M. Margonia;b, A.T. Meneguzzoa;b, J. Pazzinia;b;15, N. Pozzobona;b, P. Ronchesea;b, F. Simonettoa;b, E. Torassaa, M. Zanetti, P. Zottoa;b, A. Zucchettaa;b, G. Zumerlea;b INFN Sezione di Pavia a, Universita di Pavia b, Pavia, Italy A. Braghieria, A. Magnania;b, P. Montagnaa;b, S.P. Rattia;b, V. Rea, C. Riccardia;b, P. Salvinia, I. Vaia;b, P. Vituloa;b INFN Sezione di Perugia a, Universita di Perugia b, Perugia, Italy L. Alunni Solestizia;b, G.M. Bileia, D. Ciangottinia;b, L. Fanoa;b, P. Laricciaa;b, R. Leonardia;b, G. Mantovania;b, M. Menichellia, A. Sahaa, A. Santocchiaa;b INFN Sezione di Pisa a, Universita di Pisa b, Scuola Normale Superiore di Pisa c, Pisa, Italy K. Androsova;30, P. Azzurria;15, G. Bagliesia, J. Bernardinia, T. Boccalia, R. Castaldia, M.A. Cioccia;30, R. Dell'Orsoa, S. Donatoa;c, G. Fedi, A. Giassia, M.T. Grippoa;30, F. Ligabuea;c, T. Lomtadzea, L. Martinia;b, A. Messineoa;b, F. Pallaa, A. Rizzia;b, A. SavoyNavarroa;31, P. Spagnoloa, R. Tenchinia, G. Tonellia;b, A. Venturia, P.G. Verdinia A. Zanettia INFN Sezione di Roma a, Universita di Roma b, Roma, Italy S. Gellia;b, E. Longoa;b, F. Margarolia;b, P. Meridiania, G. 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Son, Chonbuk National University, Jeonju, Korea Chonnam National University, Institute for Universe and Elementary Particles, Kwangju, Korea Hanyang University, Seoul, Korea J.A. Brochero Cifuentes, T.J. Kim Korea University, Seoul, Korea S. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, Y. Jo, Y. Kim, B. Lee, K. Lee, K.S. Lee, S. Lee, J. Lim, S.K. Park, Y. Roh Seoul National University, Seoul, Korea J. Almond, J. Kim, H. Lee, S.B. Oh, B.C. Radburn-Smith, S.h. Seo, U.K. Yang, H.D. Yoo, University of Seoul, Seoul, Korea M. Choi, H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park, G. Ryu, M.S. Ryu Sungkyunkwan University, Suwon, Korea Y. Choi, J. Goh, C. Hwang, J. Lee, I. Yu Vilnius University, Vilnius, Lithuania V. Dudenas, A. Juodagalvis, J. Vaitkus { 58 { National Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico H. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-De La Cruz34, A. Hernandez-Almada, R. Lopez-Fernandez, R. Magan~a Villalba, J. Mejia Guisao, A. Sanchez-Hernandez Universidad Iberoamericana, Mexico City, Mexico S. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia Benemerita Universidad Autonoma de Puebla, Puebla, Mexico S. Carpinteyro, I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad Autonoma de San Luis Potos , San Luis Potos , Mexico A. Morelos Pineda University of Auckland, Auckland, New Zealand University of Canterbury, Christchurch, New Zealand National Centre for Physics, Quaid-I-Azam University, Islamabad, Pakistan A. Ahmad, M. Ahmad, Q. Hassan, H.R. Hoorani, W.A. Khan, A. Saddique, M.A. Shah, M. Shoaib, M. Waqas National Centre for Nuclear Research, Swierk, Poland H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Gorski, M. Kazana, K. Nawrocki, K. Romanowska-Rybinska, M. Szleper, P. Zalewski Institute of Experimental Physics, Faculty of Physics, University of Warsaw, K. Bunkowski, A. Byszuk35, K. Doroba, A. Kalinowski, M. Konecki, J. Krolikowski, M. Misiura, M. Olszewski, M. Walczak Laboratorio de Instrumentac~ao e F sica Experimental de Part culas, Lisboa, Joint Institute for Nuclear Research, Dubna, Russia S. Afanasiev, I. Golutvin, V. Karjavin, V. Korenkov, A. Lanev, A. Malakhov, V. Matveev36;37, V.V. Mitsyn, V. Palichik, V. Perelygin, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, E. Tikhonenko, N. Voytishin, B.S. Yuldashev38, A. Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia L. Chtchipounov, V. Golovtsov, Y. Ivanov, V. Kim39, E. Kuznetsova40, V. Murzin, V. Oreshkin, V. Sulimov, A. Vorobyev Institute for Nuclear Research, Moscow, Russia Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov, N. Krasnikov, A. Pashenkov, D. Tlisov, A. Toropin Institute for Theoretical and Experimental Physics, Moscow, Russia V. Epshteyn, V. Gavrilov, N. Lychkovskaya, V. Popov, I. Pozdnyakov, G. Safronov, A. Spiridonov, M. Toms, E. Vlasov, A. Zhokin Moscow Institute of Physics and Technology A. Bylinkin37 National Research Nuclear University 'Moscow Engineering Physics Institute' (MEPhI), Moscow, Russia M. Chadeeva41, E. Popova, E. Tarkovskii P.N. Lebedev Physical Institute, Moscow, Russia V. Andreev, M. Azarkin37, I. Dremin37, M. Kirakosyan, A. Leonidov37, S.V. Rusakov, Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, A. Baskakov, A. Belyaev, E. Boos, M. Dubinin42, L. Dudko, A. Ershov, A. Gribushin, V. Klyukhin, O. Kodolova, I. Lokhtin, I. Miagkov, S. Obraztsov, S. Petrushanko, V. Savrin, Novosibirsk State University (NSU), Novosibirsk, Russia V. Blinov43, Y.Skovpen43 State Research Center of Russian Federation, Institute for High Energy Physics, Protvino, Russia I. Azhgirey, I. Bayshev, S. Bitioukov, D. Elumakhov, V. Kachanov, A. Kalinin, D. Konstantinov, V. Krychkine, V. Petrov, R. Ryutin, A. Sobol, S. Troshin, N. Tyurin, A. Uzunian, University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia P. Adzic44, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic, V. Rekovic nologicas (CIEMAT), J. Alcaraz Maestre, M. Barrio Luna, E. Calvo, M. Cerrada, M. Chamizo Llatas, N. Colino, B. De La Cruz, A. Delgado Peris, A. Escalante Del Valle, C. Fernandez Bedoya, J.P. Fernandez Ramos, J. Flix, M.C. Fouz, P. Garcia-Abia, O. Gonzalez Lopez, S. Goy Lopez, J.M. Hernandez, M.I. Josa, E. Navarro De Martino, A. Perez-Calero Yzquierdo, J. Puerta Pelayo, A. Quintario Olmeda, I. Redondo, L. Romero, M.S. Soares Universidad Autonoma de Madrid, Madrid, Spain J.F. de Troconiz, M. Missiroli, D. Moran Universidad de Oviedo, Oviedo, Spain J. Cuevas, J. Fernandez Menendez, I. Gonzalez Caballero, J.R. Gonzalez Fernandez, E. Palencia Cortezon, S. Sanchez Cruz, I. Suarez Andres, J.M. Vizan Garcia Instituto de F sica de Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, Spain I.J. Cabrillo, A. Calderon, J.R. Castin~eiras De Saa, E. Curras, M. Fernandez, J. GarciaFerrero, G. Gomez, A. Lopez Virto, J. Marco, C. Martinez Rivero, F. Matorras, J. Piedra Gomez, T. Rodrigo, A. Ruiz-Jimeno, L. Scodellaro, N. Trevisani, I. Vila, R. Vilar CERN, European Organization for Nuclear Research, Geneva, Switzerland D. Abbaneo, E. Au ray, G. Auzinger, M. Bachtis, P. Baillon, A.H. Ball, D. Barney, P. Bloch, A. Bocci, A. Bonato, C. Botta, T. Camporesi, R. Castello, M. Cepeda, G. Cerminara, M. D'Alfonso, D. d'Enterria, A. Dabrowski, V. Daponte, A. David, M. De Gruttola, A. De Roeck, E. Di Marco45, M. Dobson, B. Dorney, T. du Pree, D. Duggan, M. Dunser, N. Dupont, A. Elliott-Peisert, S. Fartoukh, G. Franzoni, J. Fulcher, W. Funk, D. Gigi, K. Gill, M. Girone, F. Glege, D. Gulhan, S. Gundacker, M. Gutho , J. Hammer, P. Harris, J. Hegeman, V. Innocente, P. Janot, J. Kieseler, H. Kirschenmann, V. Knunz, A. Kornmayer15, M.J. Kortelainen, K. Kousouris, M. Krammer1, C. Lange, P. Lecoq, C. Lourenco, M.T. Lucchini, L. Malgeri, M. Mannelli, A. Martelli, F. Meijers, J.A. Merlin, S. Mersi, E. Meschi, F. Moortgat, S. Morovic, M. Mulders, H. Neugebauer, S. Orfanelli, L. Orsini, L. Pape, E. Perez, M. Peruzzi, A. Petrilli, G. Petrucciani, A. Pfei er, M. Pierini, A. Racz, T. Reis, G. Rolandi46, M. Rovere, M. Ruan, H. Sakulin, J.B. Sauvan, C. Schafer, C. Schwick, M. Seidel, A. Sharma, P. Silva, P. Sphicas47, J. Steggemann, M. Stoye, Y. Takahashi, M. Tosi, D. Treille, A. Triossi, A. Tsirou, V. Veckalns48, G.I. Veres20, N. Wardle, A. Zagozdzinska35, W.D. Zeuner Paul Scherrer Institut, Villigen, Switzerland W. Bertl, K. Deiters, W. Erdmann, R. Horisberger, Q. Ingram, H.C. Kaestli, D. Kotlinski, U. Langenegger, T. Rohe Institute for Particle Physics, ETH Zurich, Zurich, Switzerland F. Bachmair, L. Bani, L. Bianchini, B. Casal, G. Dissertori, M. Dittmar, M. Donega, C. Grab, C. Heidegger, D. Hits, J. Hoss, G. Kasieczka, P. Lecomtey, W. Lustermann, B. Mangano, M. Marionneau, P. Martinez Ruiz del Arbol, M. Masciovecchio, M.T. Meinhard, D. Meister, F. Micheli, P. Musella, F. Nessi-Tedaldi, F. Pandol , J. Pata, F. Pauss, G. Perrin, L. Perrozzi, M. Quittnat, M. Rossini, M. Schonenberger, A. Starodumov49, V.R. Tavolaro, K. Theo latos, R. Wallny Universitat Zurich, Zurich, Switzerland T.K. Aarrestad, C. Amsler50, L. Caminada, M.F. Canelli, A. De Cosa, C. Galloni, A. Hinzmann, T. Hreus, B. Kilminster, J. Ngadiuba, D. Pinna, G. Rauco, P. Robmann, National Central University, Chung-Li, Taiwan V. Candelise, T.H. Doan, Sh. Jain, R. Khurana, M. Konyushikhin, C.M. Kuo, W. Lin, Y.J. Lu, A. Pozdnyakov, S.S. Yu National Taiwan University (NTU), Taipei, Taiwan Arun Kumar, P. Chang, Y.H. Chang, Y.W. Chang, Y. Chao, K.F. Chen, P.H. Chen, A. Psallidas, J.f. Tsai, Y.M. Tzeng Chulalongkorn University, Faculty of Science, Department of Physics, Bangkok, B. Asavapibhop, K. Kovitanggoon, N. Srimanobhas, N. Suwonjandee Cukurova University - Physics Department, Science and Art Faculty A. Adiguzel, S. Cerci51, S. Damarseckin, Z.S. Demiroglu, C. Dozen, I. Dumanoglu, S. Girgis, G. Gokbulut, Y. Guler, I. Hos, E.E. Kangal52, O. Kara, U. Kiminsu, M. Oglakci, G. Onengut53, K. Ozdemir54, D. Sunar Cerci51, B. Tali51, H. Topakli55, S. Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East Technical University, Physics Department, Ankara, Turkey B. Bilin, S. Bilmis, B. Isildak56, G. Karapinar57, M. Yalvac, M. Zeyrek Bogazici University, Istanbul, Turkey E. Gulmez, M. Kaya58, O. Kaya59, E.A. Yetkin60, T. Yetkin61 Istanbul Technical University, Istanbul, Turkey A. Cakir, K. Cankocak, S. Sen62 Institute for Scintillation Materials of National Academy of Science of Ukraine, Kharkov, Ukraine Kharkov, Ukraine L. Levchuk, P. Sorokin National Scienti c Center, Kharkov Institute of Physics and Technology, University of Bristol, Bristol, United Kingdom R. Aggleton, F. Ball, L. Beck, J.J. Brooke, D. Burns, E. Clement, D. Cussans, H. Flacher, J. Goldstein, M. Grimes, G.P. Heath, H.F. Heath, J. Jacob, L. Kreczko, C. Lucas, D.M. Newbold63, S. Paramesvaran, A. Poll, T. Sakuma, S. Seif El Nasr-storey, D. Smith, Rutherford Appleton Laboratory, Didcot, United Kingdom K.W. Bell, A. Belyaev64, C. Brew, R.M. Brown, L. Calligaris, D. Cieri, D.J.A. Cockerill, J.A. Coughlan, K. Harder, S. Harper, E. Olaiya, D. Petyt, C.H. Shepherd-Themistocleous, A. Thea, I.R. Tomalin, T. Williams { 62 { M. Baber, R. Bainbridge, O. Buchmuller, A. Bundock, D. Burton, S. Casasso, M. Citron, D. Colling, L. Corpe, P. Dauncey, G. Davies, A. De Wit, M. Della Negra, R. Di Maria, P. Dunne, A. Elwood, D. Futyan, Y. Haddad, G. Hall, G. Iles, T. James, R. Lane, C. Laner, R. Lucas63, L. Lyons, A.-M. Magnan, S. Malik, L. Mastrolorenzo, J. Nash, C. Seez, S. Summers, A. Tapper, K. Uchida, M. Vazquez Acosta65, T. Virdee15, J. Wright, Brunel University, Uxbridge, United Kingdom J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, D. Leslie, I.D. Reid, P. Symonds, L. Teodorescu, M. Turner Baylor University, Waco, USA A. Borzou, K. Call, J. Dittmann, K. Hatakeyama, H. Liu, N. Pastika The University of Alabama, Tuscaloosa, USA O. Charaf, S.I. Cooper, C. Henderson, P. Rumerio, C. West Boston University, Boston, USA D. Arcaro, A. Avetisyan, T. Bose, D. Gastler, D. Rankin, C. Richardson, J. Rohlf, L. Sulak, Brown University, Providence, USA G. Benelli, E. Berry, D. Cutts, A. Garabedian, J. Hakala, U. Heintz, J.M. Hogan, O. Jesus, E. Laird, G. Landsberg, Z. Mao, M. Narain, S. Piperov, S. Sagir, E. Spencer, R. Syarif University of California, Davis, Davis, USA R. Breedon, G. Breto, D. Burns, M. Calderon De La Barca Sanchez, S. Chauhan, M. Chertok, J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk, M. Gardner, W. Ko, R. Lander, C. Mclean, M. Mulhearn, D. Pellett, J. Pilot, S. Shalhout, J. Smith, M. Squires, D. Stolp, M. Tripathi, S. Wilbur, R. Yohay University of California, Los Angeles, USA R. Cousins, P. Everaerts, A. Florent, J. Hauser, M. Ignatenko, D. Saltzberg, E. Takasugi, V. Valuev, M. Weber University of California, Riverside, Riverside, USA K. Burt, R. Clare, J. Ellison, J.W. Gary, S.M.A. Ghiasi Shirazi, G. Hanson, J. Heilman, P. Jandir, E. Kennedy, F. Lacroix, O.R. Long, M. Olmedo Negrete, M.I. Paneva, A. Shrinivas, W. Si, H. Wei, S. Wimpenny, B. R. Yates University of California, San Diego, La Jolla, USA J.G. Branson, G.B. Cerati, S. Cittolin, M. Derdzinski, R. Gerosa, A. Holzner, D. Klein, V. Krutelyov, J. Letts, I. Macneill, D. Olivito, S. Padhi, M. Pieri, M. Sani, V. Sharma, S. Simon, M. Tadel, A. Vartak, S. Wasserbaech66, C. Welke, J. Wood, F. Wurthwein, A. Yagil, G. Zevi Della Porta University of California, Santa Barbara - Department of Physics, Santa BarR. Bhandari, J. Bradmiller-Feld, C. Campagnari, A. Dishaw, V. Dutta, K. Flowers, M. Franco Sevilla, P. Ge ert, C. George, F. Golf, L. Gouskos, J. Gran, R. Heller, J. Incandela, N. Mccoll, S.D. Mullin, A. Ovcharova, J. Richman, D. Stuart, I. Suarez, California Institute of Technology, Pasadena, USA D. Anderson, A. Apresyan, J. Bendavid, A. Bornheim, J. Bunn, Y. Chen, J. Duarte, J.M. Lawhorn, A. Mott, H.B. Newman, C. Pena, M. Spiropulu, J.R. Vlimant, S. Xie, Carnegie Mellon University, Pittsburgh, USA M.B. Andrews, V. Azzolini, T. Ferguson, M. Paulini, J. Russ, M. Sun, H. Vogel, I. Vorobiev University of Colorado Boulder, Boulder, USA J.P. Cumalat, W.T. Ford, F. Jensen, A. Johnson, M. Krohn, T. Mulholland, K. Stenson, Cornell University, Ithaca, USA J. Thom, J. Tucker, P. Wittich, M. Zientek Fair eld University, Fair eld, USA J. Alexander, J. Chaves, J. Chu, S. Dittmer, K. Mcdermott, N. Mirman, G. Nicolas Kaufman, J.R. Patterson, A. Rinkevicius, A. Ryd, L. Skinnari, L. So , S.M. Tan, Z. Tao, Fermi National Accelerator Laboratory, Batavia, USA S. Abdullin, M. Albrow, G. Apollinari, S. Banerjee, L.A.T. Bauerdick, A. Beretvas, J. Berryhill, P.C. Bhat, G. Bolla, K. Burkett, J.N. Butler, H.W.K. Cheung, F. 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Rank, L. Shchutska, D. Sperka, L. Thomas, J. Wang, S. Wang, J. Yelton Florida International University, Miami, USA S. Linn, P. Markowitz, G. Martinez, J.L. Rodriguez A. Ackert, J.R. Adams, T. Adams, A. Askew, S. Bein, B. Diamond, S. Hagopian, V. Hagopian, K.F. Johnson, A. Khatiwada, H. Prosper, A. Santra, M. Weinberg Florida Institute of Technology, Melbourne, USA M.M. Baarmand, V. Bhopatkar, S. Colafranceschi68, M. Hohlmann, D. Noonan, T. Roy, University of Illinois at Chicago (UIC), Chicago, USA M.R. Adams, L. Apanasevich, D. Berry, R.R. Betts, I. Bucinskaite, R. Cavanaugh, O. Evdokimov, L. Gauthier, C.E. Gerber, D.J. Hofman, P. Kurt, C. O'Brien, I.D. Sandoval Gonzalez, P. Turner, N. Varelas, H. Wang, Z. Wu, M. Zakaria, J. Zhang The University of Iowa, Iowa City, USA B. Bilki69, W. Clarida, K. Dilsiz, S. Durgut, R.P. Gandrajula, M. Haytmyradov, V. Khristenko, J.-P. Merlo, H. Mermerkaya70, A. Mestvirishvili, A. Moeller, J. Nachtman, H. Ogul, Y. Onel, F. Ozok71, A. Penzo, C. Snyder, E. Tiras, J. Wetzel, K. Yi Johns Hopkins University, Baltimore, USA I. Anderson, B. Blumenfeld, A. Cocoros, N. Eminizer, D. Fehling, L. Feng, A.V. Gritsan, P. Maksimovic, C. Martin, M. Osherson, J. Roskes, U. Sarica, M. Swartz, M. Xiao, Y. Xin, The University of Kansas, Lawrence, USA A. Al-bataineh, P. Baringer, A. Bean, S. Boren, J. Bowen, C. Bruner, J. Castle, L. Forthomme, R.P. Kenny III, A. Kropivnitskaya, D. Majumder, W. Mcbrayer, M. Murray, S. Sanders, R. Stringer, J.D. Tapia Takaki, Q. Wang Kansas State University, Manhattan, USA A. Ivanov, K. Kaadze, S. Khalil, Y. Maravin, A. Mohammadi, L.K. Saini, N. Skhirtladze, Lawrence Livermore National Laboratory, Livermore, USA F. Rebassoo, D. Wright University of Maryland, College Park, USA C. Anelli, A. Baden, O. Baron, A. Belloni, B. Calvert, S.C. Eno, C. Ferraioli, J.A. Gomez, N.J. Hadley, S. Jabeen, R.G. Kellogg, T. Kolberg, J. Kunkle, Y. Lu, A.C. Mignerey, F. Ricci-Tam, Y.H. Shin, A. Skuja, M.B. Tonjes, S.C. Tonwar Massachusetts Institute of Technology, Cambridge, USA D. Abercrombie, B. Allen, A. Apyan, R. Barbieri, A. Baty, R. Bi, K. Bierwagen, S. Brandt, W. Busza, I.A. Cali, Z. Demiragli, L. Di Matteo, G. Gomez Ceballos, M. Goncharov, D. Hsu, Y. Iiyama, G.M. Innocenti, M. Klute, D. Kovalskyi, K. Krajczar, Y.S. Lai, Y.-J. Lee, A. Levin, P.D. Luckey, A.C. Marini, C. Mcginn, C. Mironov, S. Narayanan, X. Niu, C. Paus, C. Roland, G. Roland, J. Salfeld-Nebgen, G.S.F. Stephans, K. Sumorok, K. Tatar, M. Varma, D. Velicanu, J. Veverka, J. Wang, T.W. Wang, B. Wyslouch, M. Yang, A.C. Benvenuti, R.M. Chatterjee, A. Evans, A. Finkel, A. Gude, P. Hansen, S. Kalafut, S.C. Kao, Y. Kubota, Z. Lesko, J. Mans, S. Nourbakhsh, N. Ruckstuhl, R. Rusack, N. Tambe, J. Turkewitz University of Mississippi, Oxford, USA J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, USA E. Avdeeva, R. Bartek, K. Bloom, D.R. Claes, A. Dominguez, C. Fangmeier, R. Gonzalez Suarez, R. Kamalieddin, I. Kravchenko, A. Malta Rodrigues, F. Meier, J. Monroy, J.E. Siado, G.R. Snow, B. Stieger State University of New York at Bu alo, Bu alo, USA M. Alyari, J. Dolen, J. George, A. Godshalk, C. Harrington, I. Iashvili, J. Kaisen, A. Kharchilava, A. Kumar, A. Parker, S. Rappoccio, B. Roozbahani Northeastern University, Boston, USA G. Alverson, E. Barberis, D. Baumgartel, A. Hortiangtham, A. Massironi, D.M. Morse, D. Nash, T. Orimoto, R. Teixeira De Lima, D. Trocino, R.-J. Wang, D. Wood Northwestern University, Evanston, USA S. Bhattacharya, K.A. Hahn, A. Kubik, A. Kumar, J.F. Low, N. Mucia, N. Odell, B. Pollack, M.H. Schmitt, K. Sung, M. Trovato, M. Velasco University of Notre Dame, Notre Dame, USA N. Dev, M. Hildreth, K. Hurtado Anampa, C. Jessop, D.J. Karmgard, N. Kellams, K. Lannon, N. Marinelli, F. Meng, C. Mueller, Y. Musienko36, M. Planer, A. Reinsvold, R. Ruchti, G. Smith, S. Taroni, M. Wayne, M. Wolf, A. Woodard The Ohio State University, Columbus, USA J. Alimena, L. Antonelli, J. Brinson, B. Bylsma, L.S. Durkin, S. Flowers, B. Francis, A. Hart, C. Hill, R. Hughes, W. Ji, B. Liu, W. Luo, D. Puigh, B.L. Winer, H.W. Wulsin Princeton University, Princeton, USA S. Cooperstein, O. Driga, P. Elmer, J. Hardenbrook, P. Hebda, D. Lange, J. Luo, D. Marlow, T. Medvedeva, K. Mei, M. Mooney, J. Olsen, C. Palmer, P. Piroue, D. Stickland, C. Tully, A. Zuranski University of Puerto Rico, Mayaguez, USA Purdue University, West Lafayette, USA A. Barker, V.E. Barnes, S. Folgueras, L. Gutay, M.K. Jha, M. Jones, A.W. Jung, K. Jung, D.H. Miller, N. Neumeister, X. Shi, J. Sun, A. Svyatkovskiy, F. Wang, W. Xie, L. Xu Purdue University Calumet, Hammond, USA N. Parashar, J. Stupak A. Adair, B. Akgun, Z. Chen, K.M. Ecklund, F.J.M. Geurts, M. Guilbaud, W. Li, B. Michlin, M. Northup, B.P. Padley, R. Redjimi, J. Roberts, J. Rorie, Z. Tu, J. Zabel University of Rochester, Rochester, USA B. Betchart, A. Bodek, P. de Barbaro, R. Demina, Y.t. Duh, T. Ferbel, M. Galanti, A. Garcia-Bellido, J. Han, O. Hindrichs, A. Khukhunaishvili, K.H. Lo, P. Tan, M. Verzetti Rutgers, The State University of New Jersey, Piscataway, USA A. Agapitos, J.P. Chou, E. Contreras-Campana, Y. Gershtein, T.A. Gomez Espinosa, E. Halkiadakis, M. Heindl, D. Hidas, E. Hughes, S. Kaplan, R. Kunnawalkam Elayavalli, S. Kyriacou, A. Lath, K. Nash, H. Saka, S. Salur, S. Schnetzer, D. She eld, S. Somalwar, R. Stone, S. Thomas, P. Thomassen, M. Walker University of Tennessee, Knoxville, USA M. Foerster, J. Heideman, G. Riley, K. Rose, S. Spanier, K. Thapa Texas A&M University, College Station, USA O. Bouhali72, A. Celik, M. Dalchenko, M. De Mattia, A. Delgado, S. Dildick, R. Eusebi, J. Gilmore, T. Huang, E. Juska, T. Kamon73, R. Mueller, Y. Pakhotin, R. Patel, A. Perlo , L. Pernie, D. Rathjens, A. Rose, A. Safonov, A. Tatarinov, K.A. Ulmer Texas Tech University, Lubbock, USA N. Akchurin, C. Cowden, J. Damgov, F. De Guio, C. Dragoiu, P.R. Dudero, J. Faulkner, E. Gurpinar, S. Kunori, K. Lamichhane, S.W. Lee, T. Libeiro, T. Peltola, S. Undleeb, I. Volobouev, Z. Wang Vanderbilt University, Nashville, USA P. Sheldon, S. Tuo, J. Velkovska, Q. Xu University of Virginia, Charlottesville, USA A.G. Delannoy, S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, M.W. Arenton, P. Barria, B. Cox, J. Goodell, R. Hirosky, A. Ledovskoy, H. Li, C. Neu, T. Sinthuprasith, X. Sun, Y. Wang, E. Wolfe, F. Xia Wayne State University, Detroit, USA C. Clarke, R. Harr, P.E. Karchin, P. Lamichhane, J. Sturdy University of Wisconsin - Madison, Madison, WI, USA D.A. Belknap, S. Dasu, L. Dodd, S. Duric, B. Gomber, M. Grothe, M. Herndon, A. Herve, P. Klabbers, A. Lanaro, A. Levine, K. Long, R. Loveless, I. Ojalvo, T. Perry, G.A. Pierro, G. Polese, T. Ruggles, A. Savin, N. Smith, W.H. Smith, D. Taylor, N. Woods 1: Also at Vienna University of Technology, Vienna, Austria 2: Also at State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, Haute Alsace Mulhouse, CNRS/IN2P3, Strasbourg, France 4: Also at Universidade Estadual de Campinas, Campinas, Brazil 5: Also at Universidade Federal de Pelotas, Pelotas, Brazil 6: Also at Universite Libre de Bruxelles, Bruxelles, Belgium 7: Also at Deutsches Elektronen-Synchrotron, Hamburg, Germany 8: Also at Joint Institute for Nuclear Research, Dubna, Russia 9: Now at Cairo University, Cairo, Egypt 10: Also at Fayoum University, El-Fayoum, Egypt 11: Now at British University in Egypt, Cairo, Egypt 12: Now at Ain Shams University, Cairo, Egypt 13: Also at Universite de Haute Alsace, Mulhouse, France 14: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, 15: Also at CERN, European Organization for Nuclear Research, Geneva, Switzerland 16: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany 17: Also at University of Hamburg, Hamburg, Germany 18: Also at Brandenburg University of Technology, Cottbus, Germany 19: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary 20: Also at MTA-ELTE Lendulet CMS Particle and Nuclear Physics Group, Eotvos Lorand 21: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary 22: Also at Indian Institute of Science Education and Research, Bhopal, India 23: Also at Institute of Physics, Bhubaneswar, India 24: Also at University of Visva-Bharati, Santiniketan, India 25: Also at University of Ruhuna, Matara, Sri Lanka 26: Also at Isfahan University of Technology, Isfahan, Iran 27: Also at University of Tehran, Department of Engineering Science, Tehran, Iran 28: Also at Yazd University, Yazd, Iran 29: Also at Plasma Physics Research Center, Science and Research Branch, Islamic Azad University, Tehran, Iran 30: Also at Universita degli Studi di Siena, Siena, Italy 31: Also at Purdue University, West Lafayette, USA 32: Also at International Islamic University of Malaysia, Kuala Lumpur, Malaysia 33: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia 34: Also at Consejo Nacional de Ciencia y Tecnolog a, Mexico city, Mexico 35: Also at Warsaw University of Technology, Institute of Electronic Systems, Warsaw, Poland 36: Also at Institute for Nuclear Research, Moscow, Russia at National Research Nuclear University 'Moscow Engineering Physics Insti38: Also at Institute of Nuclear Physics of the Uzbekistan Academy of Sciences, Tashkent, 39: Also at St. Petersburg State Polytechnical University, St. Petersburg, Russia 40: Also at University of Florida, Gainesville, USA 41: Also at P.N. Lebedev Physical Institute, Moscow, Russia 42: Also at California Institute of Technology, Pasadena, USA 43: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia 44: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia 46: Also at Scuola Normale e Sezione dell'INFN, Pisa, Italy 47: Also at National and Kapodistrian University of Athens, Athens, Greece 48: Also at Riga Technical University, Riga, Latvia 49: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia 50: Also at Albert Einstein Center for Fundamental Physics, Bern, Switzerland 51: Also at Adiyaman University, Adiyaman, Turkey 52: Also at Mersin University, Mersin, Turkey 53: Also at Cag University, Mersin, Turkey 54: Also at Piri Reis University, Istanbul, Turkey 55: Also at Gaziosmanpasa University, Tokat, Turkey 56: Also at Ozyegin University, Istanbul, Turkey 57: Also at Izmir Institute of Technology, Izmir, Turkey 58: Also at Marmara University, Istanbul, Turkey 59: Also at Kafkas University, Kars, Turkey 60: Also at Istanbul Bilgi University, Istanbul, Turkey 61: Also at Yildiz Technical University, Istanbul, Turkey 62: Also at Hacettepe University, Ankara, Turkey 63: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom 64: Also at School of Physics and Astronomy, University of Southampton, Southampton, United 65: Also at Instituto de Astrof sica de Canarias, La Laguna, Spain 66: Also at Utah Valley University, Orem, USA 67: Also at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, 68: Also at Facolta Ingegneria, Universita di Roma, Roma, Italy 69: Also at Argonne National Laboratory, Argonne, USA 70: Also at Erzincan University, Erzincan, Turkey 71: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey 72: Also at Texas A&M University at Qatar, Doha, Qatar 73: Also at Kyungpook National University, Daegu, Korea [9] M. 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Measurements of differential production cross sections for a Z boson in association with jets in pp collisions at \( \sqrt{s}=8 \) TeV, Journal of High Energy Physics, 2017, DOI: 10.1007/JHEP04(2017)022