Search for massive resonances decaying into WW, WZ or ZZ bosons in proton-proton collisions at \( \sqrt{s}=13 \) TeV

Journal of High Energy Physics, Mar 2017

A search is presented for new massive resonances decaying to WW, WZ or ZZ bosons in \( \ell \nu q\overline{q} \) and \( q\overline{q}q\overline{q} \) final states. Results are based on data corresponding to an integrated luminosity of 2.3-2.7 fb−1 recorded in proton-proton collisions at \( \sqrt{s}=13 \) TeV with the CMS detector at the LHC. Decays of spin-1 and spin-2 resonances into two vector bosons are sought in the mass range 0.6-4.0 TeV. No significant excess over the standard model background is observed. Combining the results of the \( \ell \nu q\overline{q} \) and \( q\overline{q}q\overline{q} \) final states, cross section and mass exclusion limits are set for models that predict heavy spin-1 and spin-2 resonances. This is the first search for a narrow-width spin-2 resonance at \( \sqrt{s}=13 \) TeV.

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Search for massive resonances decaying into WW, WZ or ZZ bosons in proton-proton collisions at \( \sqrt{s}=13 \) TeV

Received: December massive resonances decaying into W W, The CMS collaboration 0 1 2 3 4 5 6 0 Open Access , Copyright CERN 1 [37] GEANT4 collaboration, S. Agostinelli et al., GEANT4: A Simulation toolkit , Nucl 2 State University of New York at Bu alo , Bu alo , U.S.A 3 tute' (MEPhI) , Moscow , Russia 4 University , Budapest , Hungary 5 15: Also at Tbilisi State University , Tbilisi , Georgia 6 59: Also at Marmara University , Istanbul , Turkey A search is presented for new massive resonances decaying to WW, WZ or integrated luminosity of 2.3{2.7 fb 1 recorded in proton-proton collisions at p ZZ bosons in ` qq and qqqq nal states. Results are based on data corresponding to an and resonance production, proton-proton scattering Beyond Standard Model; Hadron-Hadron scattering (experiments); Particle - Search for s = 13 TeV with the CMS detector at the LHC. Decays of spin-1 and spin-2 resonances into two vector bosons are sought in the mass range 0.6{4.0 TeV. No signi cant excess over the standard model background is observed. Combining the results of the ` qq and qqqq nal states, cross resonances. This is the rst search for a narrow-width spin-2 resonance at p section and mass exclusion limits are set for models that predict heavy spin-1 and spin-2 s = 13 TeV. 1 Introduction 2 The CMS detector 3 Simulated samples 4 Reconstruction and selection of events Trigger and preliminary o ine selection 4.2 Jet reconstruction 4.6 Final event selection and categorization 5 Modeling of background and signal Multijet background 5.2 Top quark production The W+jets background 5.4 Signal modelling 6 Systematic uncertainties 4.1 4.3 4.4 Final reconstruction and selection of leptons and missing transverse momentum The identi cation of W/Z ! qq using jet substructure The reconstruction and identi cation of W ! ` 6.1 Systematic uncertainties in the background estimation 6.2 Systematic uncertainties in the signal prediction 7 Statistical interpretation Limits on narrow-width resonance models Model-independent limits 8 Summary sults A Instructions and additional material for generic interpretation of the reThe CMS collaboration Several theories beyond the standard model (SM) predict the existence of heavy particles that preferentially decay to pairs of vector bosons V, where V represents a W or Z. These models usually aim to clarify open questions in the SM such as the apparently large difference between the electroweak and the gravitational scales. Notable examples of such models include the bulk scenario [1{3] of the Randall-Sundrum warped extra-dimensions (RS1) [4, 5] and a heavy vector-triplet (HVT) model [6]. The bulk graviton model is described by two free parameters: the mass of the rst Kaluza-Klein (KK) excitation of a spin-2 boson (the KK bulk graviton Gbulk) and the ratio k~ known curvature scale of the extra dimension and M Pl MP l= 8 is the reduced Planck mass. The HVT generalises a large number of models that predict spin-1 charged (W0) and neutral (Z0) resonances. Such models can be described in terms of just a few parameters: two coe cients cF and cH, scaling the couplings to fermions, and to the Higgs and longitudinally polarized SM vector bosons respectively, and the strength gV of the new vector boson interaction. Two benchmark models are considered in the HVT scenario. In the from extensions of the SM gauge group, such as the sequential standard model (SSM) [7], that have comparable branching fractions to fermions and gauge bosons. In HVT Model their fermionic couplings are suppressed. This scenario is most representative of composite k=M Pl, where k is the unmodels of Higgs bosons. Searches for diboson resonances have been previously performed in many di erent nal states, placing lower limits on the masses of these resonances above the TeV scale [8{19]. Searches performed with proton-proton collisions at p s = 8 TeV indicated deviations from background expectations at resonance masses of about 2 TeV. The largest excesses of events were observed in the searches in the dijet WW, WZ or ZZ [12, 16] channels, as well as in the semi-leptonic WH ! ` bb nal state [13], and have local signi cances of 3.4 2.2 , respectively. The most stringent lower mass limit for a W0 (Z0) is set at 2.3 (2.0) TeV by a combination of searches in semi-leptonic and all-hadronic nal states performed with proton-proton collisions at p mass limit of 2.6 TeV for a HVT. This paper presents a search for resonances with masses above 0.6 TeV decaying into a pair of vector bosons. The analysis is based on data collected in proton-proton collisions nal state, respectively. The ` +jet search also includes the W ! or e, and qqqq ! ` . The gain in sensitivity from leptons is limited by the small branching The key challenge of the analyses is the reconstruction of the highly energetic decay products. Since the resonances under study have masses of order 1 TeV, their decay products, i.e. the bosons, have on average transverse momenta (pT) of several hundred GeV or more. As a consequence, the particles emerging from the boson decays are very collimated. In particular, the jet-decay products of the bosons cannot be resolved using the standard algorithms, but are instead reconstructed as a single jet object. Dedicated techniques, called jet \V tagging" techniques, are applied to exploit the substructure of such objects, to help resolve jet decays of massive bosons [20, 21]. The V tagging also helps suppress SM backgrounds, which mainly originate from the production of multijet, W+jets, and nonresonant VV events. The nal states considered are either ` qq or qqqq, where the hadronic decay products of the V decay are reconstructed in a single jet. They result in events with either a charged lepton, a neutrino, and a single reconstructed jet (` +jet channel), or two reconstructed jets (dijet channel). As in the analyses of previous data [11, 12], the aim is to reconstruct all decay products of the new resonance to be able to search for a localized enhancement in the diboson invariant mass spectrum. While the analyses in general aim at large resonance masses, we conduct two exclusive searches in the ` +jet nal state, separately optimized for the mass ranges 0.6{1.0 TeV (\low-mass") and > 1 TeV (\high-mass"). This paper is organized as follows. Section 2 brie y describes the CMS detector. Section 3 gives an overview of the simulations used in this analysis. Section 4 provides a detailed description of the reconstruction and event selection. Section 5 describes the background estimation and the signal modelling procedures. Systematic uncertainties are discussed in section 6. The results of the search for a spin-2 bulk graviton and for spin-1 resonances as predicted by HVT models are presented in section 7, and section 8 provides a brief summary. The CMS detector The central feature of the CMS apparatus is a superconducting solenoid of 6 m internal diameter, providing a magnetic eld of 3.8 T. Contained within the solenoid volume are a silicon pixel and strip tracker, a lead tungstate crystal electromagnetic calorimeter (ECAL), and a brass and scintillator hadron calorimeter (HCAL), each composed of a barrel and two endcap sections. Extensive forward calorimetry complements the coverage provided by the barrel and endcap detectors. The forward hadron (HF) calorimeter uses steel as an absorber and quartz bers as the sensitive material. The two halves of the HF are located 11.2 m from the interaction region, one on each end, and together they provide coverage in the pseudorapidity range 3:0 < j j < 5:2. Muons are measured in gas-ionization detectors embedded in the steel ux-return yoke outside the solenoid. A particle- ow (PF) event algorithm [22, 23] reconstructs and identi es each individual particle with an optimized combination of information from the various elements of the CMS detector. The energy of photons is obtained from the ECAL measurement, corrected for suppression of small readout signals. The energy of electrons is determined from a combination of the electron momentum at the primary interaction vertex as determined by the tracker, the energy of the corresponding ECAL cluster, and the energy sum of all bremsstrahlung photons spatially compatible with originating from the electron track. The momentum of muons is obtained from the curvature of the corresponding track. The energy of charged hadrons is determined from a combination of their momentum measured in the tracker and the matching of energies deposited in ECAL and HCAL, also corrected for suppression of small signals and for the response function of the calorimeters to hadronic showers. Finally, the energy of neutral hadrons is obtained from the corresponding corrected ECAL and HCAL energy. A more detailed description of the CMS detector, together with a de nition of the coordinate system and the kinematic variables, can be found in ref. [24]. Simulated samples The bulk graviton model and HVT models are used as benchmark signal processes. In these models, the vector gauge bosons are produced with a longitudinal polarization in more than 99% of the cases. For each resonance hypothesis, we consider masses in the range 0.6 to 4.0 TeV. Simulated signal events are generated at leading order (LO) accuracy with MadGraph5 amc@nlo v2.2.2 [25] with a width of 0.1% of the resonance mass. The Monte Carlo (MC) generated samples of SM backgrounds are used to optimize the analyses. The W+jets SM process is simulated with MadGraph5 amc@nlo, while tt and single top quark events are generated with both powheg v2 [26{31] and MadGraph5 amc@nlo. Diboson (WW, WZ, and ZZ) processes are generated with pythia v8.205 [32, 33]. Parton showering and hadronization are implemented through pythia using the CUETP8M1 tune [34, 35]. The NNPDF 3.0 [36] parton distribution functions (PDFs) are used for all simulated samples, except for diboson ones (WW, WZ and ZZ) for which NNPDF 2.3LO is used. All events are processed through a Geant4-based [37] simulation of the CMS detector. The simulated background is normalized using inclusive cross sections calculated at next-to-leading order (NLO), or next-to-NLO order in quantum chromodynamics (QCD) where available, using mcfm v6.6 [38{41] and fewz v3.1 [42]. Additional simulated minimum-bias interactions are added to the generated events to match the additional particle production observed in the large number of overlapping proton-proton interactions within the same or nearby bunch crossings (pileup). The simulated events are corrected for di erences between data and simulation in the e ciencies of the lepton trigger [43], lepton identi cation and isolation [43], and selection of jets originating from hadronization of b quarks (b jets) [44]. Reconstruction and selection of events Trigger and preliminary o ine selection In the ` +jet channel, events are collected with a trigger requiring either one muon or one electron. For the low-mass ` +jet analysis, both triggers have a pT requirement of 27 GeV. The muons and electrons selected online also satisfy both isolation requirements and identi cation criteria. The selection e ciency of these triggers for leptons satisfying the o ine requirements described in section 4.3, varies in the range 90{95% for the single-muon trigger, depending on the of the muon, and it is >94% for the single-electron trigger. In the high-mass ` +jet analysis, muons selected online must have pT > 45 GeV and j j < 2:1, while the minimum pT threshold for electrons is 105 GeV. There are no requirements on the isolation and loose identi cation criteria are used, since these introduce ine ciencies at high resonance masses. The selection e ciencies with respect to the o ine requirements of the single-muon trigger vary between 90% and 95%. The e ciency is above 98% for the single-electron trigger. In the dijet channel, events are selected online using a variety of di erent hadronic triggers based on the scalar pT sum of all jets in the event (HT) or the presence of at least one jet with loose substructure requirements; the details of jet substructure are described in section 4.4. Events must satisfy at least one of the following four requirements. The rst requirement is simply HT > 800 GeV. The second requirement is HT > 650 GeV and a di erence in between the two leading jets in the event satisfying the condition The accepted jets are further required to have a dijet invariant mass > 900 GeV. The third criterion is that at least one jet with pT > 360 GeV and a trimmed mass (as de ned in section 4.4) mjet > 30 GeV is present in the event. Fourthly, events with HT > 700 GeV and at least one jet with mjet > 50 GeV are also selected for analysis. The pp data collected by CMS with the detector in its fully operational state correspond to 2.3 fb 1 of integrated luminosity [45]. Additional data equivalent of 0.37 fb 1 of integrated luminosity were collected with the HF running in suboptimal conditions; those data are used only for the dijet channel, since jets reconstructed online and used for the calculation of HT are in the range of j j < 3:0. The trigger e ciency is found to be una ected by the condition of the HF. O ine, all events are required to have at least one primary interaction vertex reconstructed within a 24 cm window along the beam axis, with a transverse distance from the mean pp interaction point of less than 2 cm [46]. In the presence of more than one vertex passing these requirements, the primary interaction vertex is chosen to be the one with the highest total p2T, summed over all the associated tracks. Jet reconstruction R = p Jets are clustered from the four-momenta of the particles reconstructed using the CMS PF algorithm, from the FastJet software package [47]. In the jet clustering procedure charged PF candidates not associated with the primary interaction vertex are excluded. Jets used for identifying the W and Z boson decays to qq are clustered using the anti-kT combined secondary vertex b tagging algorithm [44, 49]. The chosen algorithm working point provides a misidenti cation rate of 1% and e ciency of 70%. A correction based on the area of the jet projected on the front face of the calorimeter is used to take into account the extra energy clustered in jets due to neutral particles coming from pileup. Jet energy corrections are obtained from simulation and from dijet and photon+jet events in data, as discussed in ref. [50]. Additional quality criteria are applied to the jets to remove spurious jet-like features originating from isolated noise patterns in the calorimeters or the tracker. The e ciency of these requirements for signal events is above 99%. In the ` +jet channel, the AK8 and AK4 jets are required to be separated from any well-identi ed muon )2 > 0:8 and >0.3, respectively. All AK4 and AK8 jets must have pT > 30 GeV and >200 GeV, respectively, and j j < 2:4 to be considered in the subsequent steps of the analysis. Final reconstruction and selection of leptons and missing transverse moMuons are reconstructed through a t to hits in both the inner tracking system and the muon spectrometer [51]. Muons must satisfy identi cation requirements on the impact parameters of the track, the number of hits reconstructed in both the silicon tracker and the muon detectors, and the uncertainty in the pT. These quality criteria ensure a precise measurement of the four-momentum and rejection of misreconstructed muons. An isolation requirement is applied to suppress background from multijet events where jet constituents are identi ed as muons. A cone of radius R = 0:3 is constructed around the muon direction, and the isolation parameter is de ned as the scalar sum of the pT of all the additional reconstructed tracks within the cone, divided by the muon pT. The e ciency of this muon selection has been measured through a \tag-and-probe" method using Z bosons [43], and it has a negligible dependence on the pileup. In the high-mass ` +jet analysis, events must have exactly one isolated muon with pT > 53 GeV and j j < 2:1. A looser pT requirement of 40 GeV is used for the low resonance mass range. Electron candidates are required to have a match between energy deposited in the ECAL and momentum determined from the reconstructed track [52]. To suppress multijet background, electron candidates must pass stringent identi cation and isolation criteria [53]. Those criteria include requirements on the geometrical matching between ECAL depositions and position of reconstructed tracks, the ratio of the energies deposited in the HCAL and ECAL, the distribution of the ECAL depositions, the impact parameters of the track, and the number of reconstructed hits in the silicon tracker. In the high-mass ` +jet analysis, we require exactly one electron with pT > 120 GeV and j j < 2:5. A looser pT requirement of 45 GeV is used for the low resonance mass range. Reconstructed electrons must also be located outside of the transition region between the ECAL barrel and endcaps (1:44 < j j < 1:57), because the reconstruction of an electron object in this region is not optimal. The missing transverse momentum pmiss is de ned as the magnitude of the vector sum of the transverse momenta of the reconstructed PF objects. The value of pTmiss is modi ed to account for corrections to the energy scale of all the reconstructed AK4 jets in the event. More details on the pTmiss performance in CMS can be found in refs. [54, 55]. Requirements of pTmiss > 40 and > 80 GeV are applied, respectively, in the muon and electron channels in the ` +jet analysis. The threshold is higher in the electron channel to further suppress the larger background from multijet processes. Since the pmiss calculation requires the detector to provide complete geometric coverage, events in data without fully operational HF calorimeter are not considered for the ` +jet channel. The identi cation of W/Z ! qq using jet substructure The AK8 jets are used to reconstruct the W jet and Z jet candidates from their decays to highly boosted quark jets. To discriminate against multijet backgrounds, we exploit both the reconstructed jet mass, which is required to be close to the W or Z boson mass, and the two-prong jet substructure produced by the particle cascades of two high-pT quarks that merge into one jet [21]. Jets that are identi ed as arising from the merged decay products of a V boson are hereafter referred to as \V jets". As a rst step in exploring potential substructure, the jet constituents are subjected to a jet grooming algorithm that improves the resolution in the jet mass and reduces the e ect of pileup [56]. The goal of the algorithm is to recluster the jet constituents, while applying additional requirements that eliminate soft, large-angle QCD radiation that increases the jet mass relative to the initial V boson mass. Di erent jet grooming algorithms have been explored at CMS, and their performance on jets in multijet processes has been studied in detail [56]. In this analysis, we use the jet pruning [57, 58] algorithm for the main analysis and the jet trimming algorithm [59] at the trigger level as well as for cross checks. Jet pruning reclusters each AK8 jet starting from all its original constituents, through the implementation of the Cambridge-Aachen (CA) algorithm [60, 61] to discard \soft" recombinations in each step of the iterative CA procedure. The pruned jet mass, mjet, is computed from the sum of the four-momenta of the constituents that are not removed by the pruning; it is then scaled by the same factor as that used to correct the original jet pT. The jet is considered as a V jet candidate if mjet falls in the range 65 < mjet < 105 GeV, which we de ne as the signal jet mass window. In the low-mass analysis, only W jet candidates are considered, thus the mass window applied is 65 < mjet < 95 GeV. Additional discrimination against jets from gluon and single-quark hadronization is obtained from the quantity called N-subjettiness [62]. The constituents of the jet before the pruning procedure are reclustered using the kT algorithm [60, 63], until N joint objects (subjets) remain in the iterative combination procedure of the algorithm. The N -subjettiness, N , is then de ned as N = where the index k runs over the PF constituents of the jet, and the distances calculated relative to the axis of the n-th subjet. The normalization factor d0 is calculated as d0 = P k pT;kR0, setting R0 to the distance parameter used in the clustering of the original jet. The variable N quanti es the compatibility of the jet clustering with the hypothesis that exactly N subjets are present, with small values of N indicating greater to be a powerful discriminant between jets originating from hadronic V decays and from gluon and single-quark hadronization. Jets from W or Z decays in signal events are characterized by lower values of 21 relative to SM backgrounds. We reject V jet candidates with 21 > 0:75. The remaining events are further categorized according to their value of 21 to enhance the sensitivity of the analysis, as summarized in table 1. Since data/simulation discrepancies in the jet substructure variables mjet and 21 can bias the signal e ciency estimated from simulated samples, the modelling of signal efciency is cross-checked in a signal-free sample with jets having characteristics that are similar to those expected for a genuine signal. A sample of high-pT W bosons that decay to quarks, and are reconstructed as single AK8 jets, is studied in tt and single top quark events. Scale factors for the 21 selection e ciency are extracted following ref. [21]. In this 0:45 < 21 < 0:75 E ciency scale factor as extracted from top quark enriched data and from simulation. and from simulation. These results are used to apply corrections in the V tagging procedure. method, the pruned jet mass distributions of events that pass and fail the 21 selection are tted simultaneously to separate the W boson signal from the combinatorial components in the top quark enriched sample in both data and simulation. The scale factors are listed in table 1 and are used to correct the total signal e ciency and the VV background normalization predicted by the simulation. The uncertainties in the scale factors quoted for the 21 selection include two systematic uncertainties. One comes from the modelling of the nearby jets and pT spectrum in tt MC events, obtained by comparing LO and NLO tt simulation. The other is due to the choice of the models used to t signal and background. The quadratic sum of these systematic uncertainties is found to be smaller than half of the statistical uncertainty in the scale factor. An additional uncertainty is calculated to account for the extrapolation of the scale factor from tt events with an average jet 200 GeV to higher momenta. This is estimated from the di erence between pythia selection, this uncertainty is increased by the ratio of the uncertainties in the scale fac21 < 0:45. The mean hmjeti and resolution value of the Gaussian component of the tted W jet mass are also extracted to obtain corrections that are applied to the simulated pruned jet mass. The values are listed in table 2, where the quoted uncertainties are statistical. The mass peak position is slightly shifted relative to the W boson mass because of the extra energy deposited in the jet cone from pileup, underlying event, and initial-state radiation not completely removed in the jet pruning procedure. For events with top quarks, additional energy contributions arise also from the possible presence of a b jet close to the W jet candidate. Because the kinematic properties of W jets and Z jets are very similar, the same corrections are also used when the V jet is assumed to arise from a Z boson. In the ` +jet channel, identi ed muons and electrons are associated with W longitudinal momentum of the neutrino (pz) is obtained by solving a quadratic equation that sets the ` invariant mass to the known W boson mass [65]. In the case of two real solutions, we choose the one with smaller pz; in the case of two complex solutions, we use their real part. The four-momentum of the neutrino is used to reconstruct the four-momentum of the W ! ` candidate. Final event selection and categorization After reconstructing the two vector bosons, we apply the nal criteria in the search. For all channels, any V boson candidate is required to have pT > 200 GeV. In addition, there are speci c selection criteria chosen for the ` +jet and dijet analyses. For the ` +jet channel, we reject events with more than one well-identi ed muon or electron. We also require that the two V bosons from the decay of a massive resonance are approximately back-to-back: R between the lepton and the V jet is greater than 1.6; the between the vector p~ miss and the W jet, as well as between the W ! ` and V jet candidates, are both greater T than 2 radians. To further reduce the level of the tt background in the ` +jet channel, events are rejected if they contain one or more b-tagged AK4 jets. This veto preserves about 90% of the signal events. For the dijet analysis, we require the two AK8 jets to have jj j < 1:3, while the dijet system invariant mass mjj must be above 1 TeV. To enhance the analysis sensitivity, events are categorized according to the characteristics of the V jet. For the dijet and high-mass ` +jet channels, the V jet is deemed a W or Z boson candidate if its pruned mass falls in the range 65{85 or 85{105 GeV. This leads to three categories for the dijet channel (WW, WZ, and ZZ), and two categories for the ` +jet channel (WW and WZ). For the low-mass ` +jet channel, only W jets are considered in the signal region 65 < mjet < 95 GeV. In addition, in the low- and high-mass ` +jet channels, V jets are selected to have 21 0.6, respectively. A tighter selection is required for the low-mass analysis as more background is expected in that mass range. In the dijet channel, we select \high-purity" (HP) and \low-purity" (LP) V jets by requiring 21 0:45 and 0:45 < 21 < 0:75, respectively. Events are always required to have one HP V jet, and are divided into HP or LP events, depending on whether the other V jet is of high or low purity. Although the HP category dominates the total sensitivity of the analysis, the LP category is retained since for heavy resonances it can improve the signal e ciency with only moderate background contamination. The is therefore based on two and four classes of events for the low- and high-mass ` +jet channels, respectively, depending on their lepton avor (muon or electron), and V jet mass category (W or Z). For the dijet analysis, categorization in V jet purity and mass category (WW, WZ, and ZZ) yields a total of 6 orthogonal classes of events. The two boson candidates are combined into a diboson candidate, with presence of signal then inferred from the observation of localized excesses in the mVV distribution. AK4 jet selections Number of electrons Number of muons Number of b-tagged AK4 jets pmiss (electron channel) pmiss (muon channel) V ! qq (AK8 jet) Back-to-back topology pmiss selections pT > 120 (45) GeV j j < 2:5 (except 1:44 < j j < 1:57) pT > 53 (40) GeV pT > 30 GeV pmiss > 80 GeV pmiss > 40 GeV pT > 200 GeV pT > 200 GeV R(`; Vqq) > 1:6 (Vqq; W` ) > 2 Pruned jet mass 2- to 1-subjettiness ratio mjet categories (only for high-mass analysis) 65 < mjet < 105 (95) GeV 21 < 0:60 (0:45) 65 < mjet < 85 GeV 85 < mjet < 105 GeV nal selections and categories for the ` +jet channel. The values indicated in parentheses correspond to the low-mass analysis. When several diboson resonance candidates are present in the same event, only the one with the highest pT V jet (` +jet analyses) or the two highest mass V jets (dijet analysis) A summary of the nal event selections and categories is presented in table 3 for the ` +jet analyses and in table 4 for the dijet analysis. V ! qq (2 AK8 jets) Pruned jet mass Dijet invariant mass 2- to 1-subjettiness ratio mjet categories 21 categories pT > 200 GeV mjj > 1 TeV 65 < mjet1; mjet2 < 105 GeV 65 < mjet1 < 85 GeV, 65 < mjet2 < 85 GeV 65 < mjet1 < 85 GeV, 85 < mjet2 < 105 GeV 85 < mjet1 < 105 GeV, 85 < mjet2 < 105 GeV 21, jet1 < 0:45, 21, jet2 < 0:45 21, jet1 < 0:45, 0:45 < 21, jet2 < 0:75 Modeling of background and signal The mVV distribution observed in data is dominated by SM background processes where single quark or gluon jets are falsely identi ed as V jets. Depending on the nal state, the dominant processes are multijets (dijet channel) and inclusive W boson production (` +jet channel). Subdominant backgrounds include tt, single top quark, and nonresonant diboson Multijet background In the ` +jet channel, the multijet background is predicted to be negligible from MC simulation, whereas it represents the major contribution in the dijet analysis. For the latter, we assume that the SM background can be described by a smooth, parametrizable, monotonically decreasing distribution. The search is performed by separately tting the background function to each search region and simultaneously adding resonant Breit-Wigner (BW) forms across all search regions to represent the signal. The background probability function is de ned by empirical functional forms of 3 and 2 parameters, respectively: mjj= (mjj=ps)P2 (mjj=ps)P2 ; where mjj is the dijet invariant mass (equivalent to the diboson candidate mass mVV for s is the pp collision energy in the centre of mass, P0 is a normalization parameter, and P1 and P2 parametrize the shape of the mVV distribution. Starting from 21 < 0:6 (high-mass) 21 < 0:45 (low-mass) tracted from the comparison between data and simulation in the top quark enriched control sample. the two-parameter functional form, a Fisher F-test is used to check at 10% con dence level (CL) if additional parameters are needed to model the background distribution. For the WW categories and the WZ HP category, the two-parameter form is found to describe the data spectrum su ciently well, while for all other channels the three-parameter functional form is preferable. Alternative parametrizations and functions with up to ve parameters are also studied as a cross-check. The binning chosen for the t re ects the detector resolution. The t range is chosen to start where the trigger e ciency reaches its plateau, as this minimizes bias from trigger ine ciency, and to extend to the bin after the highest mjj mass point. The results are gure 1. The solid curve represents the maximum likelihood t to the data, xing the number of expected signal events to zero, while the bottom panels show the corresponding pull distributions, quantifying the agreement between the background-only t and the data. The expected contributions from bulk graviton and W0 resonances with a mass of 2 TeV, scaled to their corresponding cross sections, are given by the dashed curves. Top quark production The backgrounds from tt and single top quark production in the ` +jet channel are estimated from data-based correction factors in the normalization of the simulation. A top quark enriched control sample is selected by applying all the analysis requirements in ` +jet events except that the b jet veto is inverted by requiring, instead, at least one b-tagged AK4 jet in the event. From the comparison between data and simulation, normalization correction factors for tt and single top quark background processes are evaluated in the pruned jet mass regions 65 < mjet < 105 GeV and 65 < mjet < 95 GeV, for the electron and muon channels, and for the low- and high-mass selections, separately. The scale factors, summarized in table 5, include both the W boson signal and the combinatorial components mainly due to events where the extra b jet from the top quark decay is in the proximity of the W, and are used to correct the normalization of the tt and single top quark simulated background predictions in the signal regions. The mjet distribution in the top quark enriched sample is shown in the right plot of gure 2, while the left plot shows the 21 distribution. The mjet distribution shows a clear peak for events with a W boson decaying to hadrons, including the combinatorial background. The W+jets background The W+jets background in the ` +jet channel is estimated through the This method assumes that the correlation between mjet and mVV for the dominant W+jets /t(s 102 it t-aaFDσtdaa-202 /t(s 102 it t-aaFDσtdaa-202 /t(s 102 it t-aaFDσtdaa-202 G(2 TeV)→WW, k~=0.5 Dijet invariant mass (TeV) W'(2 TeV)→WZ, HVTB(gV=3) /t(s 102 it t-aaFDσtdaa-202 /t(s 102 it t-aaFDσtdaa-202 /t(s 102 it t-aaFDσtdaa-202 G(2 TeV)→WW, k~=0.5 Dijet invariant mass (TeV) W'(2 TeV)→WZ, HVTB(gV=3) Dijet invariant mass (TeV) G(2 TeV)→ZZ, k~=0.5 CMS Dijet invariant mass (TeV) G(2 TeV)→ZZ, k~=0.5 Dijet invariant mass (TeV) Dijet invariant mass (TeV) the left) and the low-purity (on the right) categories are shown for the WW (top row), WZ (central row), and ZZ (bottom row) mjet regions. The solid curve represents a background-only data distribution, where the lled red area corresponds to the 1 standard deviation statistical uncertainties of the t. The data are represented by the black points. For the ZZ high-purity category (bottom left), we also show the background-only t using the two-parameter functional form (blue solid line), for comparison. Signal benchmarks for a mass of 2 TeV are also shown with black dashed lines. In the lower panel of each plot, the bin-by-bin t residuals, (Ndata N t)= data, are shown. 2.3 fb-1 (13 TeV) 2.3 fb-1 (13 TeV) 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Pruned jet mass (GeV) quark enriched control sample in the muon channel. The tt background is rescaled such that the total number of background events matches the number of events in data. In the lower panel of each plot, the ratio between data and simulation is shown together with the statistical uncertainty in the simulation normalized by its central value. background can be adequately modelled by simulation. A signal-depleted control region (sideband) is de ned by requiring the mass of the V jet to lie below or above the nominal selection; the mVV distribution observed in this region is then extrapolated to the nominal region through a transfer function estimated from simulation. Other minor sources of background, such as tt, single top quark, and SM diboson production, are estimated from simulation after applying correction factors based on control regions in data, as described in sections 4.4 and 5.2. The sideband region is de ned around the jet mass window described in section 4. The lower and upper sidebands correspond to the mjet ranges 40{65 and 135{ 150 GeV, respectively. The Higgs boson mass region, de ned by the range 105{135 GeV, corresponds to the signal region of searches for diboson in nal states with highly Lorentzboosted Higgs bosons [66], and is therefore not used to estimate the background. The overall normalization of the W+jets background in the signal region is determined from a t to the mjet distribution in the lower and upper sidebands of the data. The analytical form of the tting function is chosen from simulation studies, as are the contributions from minor backgrounds. Figure 3 shows the result of this t for the low- and high-mass ` +jet channels. The form of the mVV distribution for the W+jets background in the signal region (SR) is determined from the lower mjet sideband (SB), through the transfer function obtained from the W+jets simulation, and de ned as: MC(mVV) = FMWC+;SjeRts(mVV) FMWC+;SjeBts(mVV) it t-aaFD σtdaa-202 it t-aaFD σtdaa-202 CMS 2.3 fb-1 (13 TeV) ← signal region → ← Higgs → 2.3 fb-1 (13 TeV) Pruned jet mass (GeV) Pruned jet mass (GeV) (right) analyses in the muon channel. All selections are applied except the requirement on mjet signal window. Data are shown as black points. The signal regions and mjet categories of the analyses are indicated by the vertical dotted lines. The shaded mjet region 105{135 GeV is not used in these analyses. In the lower panel of each plot, the bin-by-bin t residuals, (Ndata N t)= data, are shown together with the uncertainty band of the t normalized by the statistical uncertainty of data points, data. where F (mVV) is the probability density function used to describe the mVV spectrum in di erent regions. The upper mjet sideband is not considered in this t since the expected mVV distribution is di erent here, displaying a threshold e ect not present in the lower sideband and signal regions. The adopted parameterization for the mVV spectrum in both the simulation. Tests are performed with alternative functional forms, and the prediction for the backgrounds is found to agree with the one of the default function within the The mVV distribution observed in the lower sideband region is corrected for the presence of minor backgrounds to have an estimate of the W+jets contribution in the control region of the data, FDWA+TjAet;SsB(mVV). The W+jets background distribution in the signal region is then obtained by rescaling FDWA+TjAet;SsB(mVV) by MC(mVV). The minor backgrounds are then added to the W+jets background to obtain the total SM prediction in the sig Figure 4 shows the nal spectrum in mVV for events in all categories for the low- and high-mass analyses. The observed data and the predicted background agree. The highest electron categories, respectively. G(2 TeV), k=0.5 (×100) W'(2 TeV), HVTB(gV=3) it-F ta2 it t-aF tada 20 G(0.75 TeV), k=0.5 (×20) 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 mass analysis obtained from the combined muon and electron channels in the WW-enriched (left) and WZ-enriched (right) signal regions. (Lower plot) Final mVV distributions for data and expected backgrounds in the signal region of the low-mass analysis obtained from the combined muon and electron channels. In each plot the solid curve represents the background estimation provided by ratio method. The hatched band includes both statistical and systematic uncertainties. The data are shown as black points. Signal benchmarks for a mass of 2 TeV (0.75 TeV) are also shown with black dashed lines for the upper (lower) plots. In the lower panel of each plot are the bin-by-bin t residuals, (Ndata N t)/ data, shown together with the uncertainty band of the t normalized by the statistical uncertainty of data, data. Signal modelling Figure 5 shows the simulated mjj and m` +jet distributions for di erent resonance masses from 0.8 to 4.0 TeV. The experimental resolution for the dijet channel is around 4%, while it ranges from 6% at 1 TeV to 4% at 4 TeV in the ` +jet channel. We adopt an analytical W' → WZ (MADGRAPH) W' → WZ (MADGRAPH) Z' → WW (MADGRAPH) Dijet invariant mass (TeV) description of the signal, choosing a double-sided Crystal Ball (CB) function [67] (i.e. a Gaussian core with power law tails on both sides) to describe the simulated resonance distributions. A linear interpolation between a set of reference distributions (corresponding to masses of 0.6, 0.7, 0.8, 1.0, 1.2, 1.4, 1.6, 1.8, 2.0, 2.5, 3.0, 3.5, and 4.0 TeV) is used to estimate the expected distributions for intermediate values of resonance mass. Table 6 summarizes the overall event-selection e ciency for our chosen analysis channels and signal models. All channels are used in the statistical analysis of each signal. Systematic uncertainties Systematic uncertainties in the background estimation For the dijet analysis, the background estimation is obtained from a t to the data. As such, the only relevant uncertainty is the statistical one as represented by the covariance matrix of the t to the dijet function. Di erent parameterizations of the tting function have been studied, and the di erences observed are well within the bounds of the aforementioned uncertainty and are assumed to pose no additional contribution. For the ` +jet analyses, uncertainties in both the distribution and normalization of the background prediction can be important. The uncertainty in the distribution is dominated by the statistical uncertainties in the simultaneous ts to the data of the sideband region, and the simulation in signal and sideband regions. An e ect of almost equal magnitude is due to the uncertainties in the modelling of the transfer function (mVV) between the sideband and the signal region. The uncertainty in the normalization of the background has three sources: the W+jets component, dominated by the statistical uncertainty of the events in the pruned jet mass sideband, varying from 5 to 9%; the tt/single top quark component, dominated by the scale factor obtained from the top quark enriched control ` +jet channel e ciencies are in percent, and include the branching fractions of the two vector bosons to the nal state of the analysis channel, e ects from detector acceptance, as well as reconstruction and selection e ciencies. Values are not indicated for categories and masses where the analysis channel has no sensitivity. region, amounting to about 5{7% and 8% in the muon and electron channels, respectively; and the diboson component, dominated by the V tagging uncertainty, which varies in the range of 3{25%. Systematic uncertainties in the signal prediction The dominant uncertainty in the signal selection e ciency arises from uncertainties in datato-simulation scale factors for the V tagging e ciency derived from a top quark enriched control sample, as described in section 4.4. The normalization uncertainties are summarized in tables 7 and 8 for the dijet and ` +jet channels, respectively. Uncertainties in the reconstruction of jets a ect both the signal e ciency and the distribution in the reconstructed resonance mass. The four-momenta of the reconstructed jets are rescaled or smeared according to the uncertainties in the respective jet energy scale or resolution. The selection e ciencies are recalculated on these modi ed events, with the resulting changes taken as systematic uncertainties that depend on the resonance mass. The induced changes on the reconstructed resonances are propagated as uncertainties in the peak position and width of the Gaussian core. In addition, the induced relative migration among V jet mass categories is evaluated, and found not to a ect the overall signal e ciency. The correlations in these uncertainties between the di erent categories are taken into account. The uncertainty in the lepton energy scale is correlated with the obtained signal e ciency. Changes in lepton energy are propagated to the reconstructed pmiss, and through the entire analysis. The relative change in the number of selected signal events is taken as a systematic uncertainty in the signal normalization. For both lepton avors, the uncertainties are smaller than 1%, and are uncorrelated for di erent lepton avors, but correlated for di erent pruned jet mass and 21 categories. In addition, the induced change in peak position and its width are added as systematic uncertainties in the distribution of the signal. Again, for both lepton avors, the uncertainties are below 1%. The systematic uncertainties in the lepton trigger, identi cation, and isolation e ciencies are obtained using a tag-and-probe method in Z ! `` events [43], and are used only for the ` +jet channel. An uncertainty of 1{3% is assigned to the trigger e ciency for both avors, depending on the lepton pT and . For lepton identi cation and isolation e ciency, the systematic uncertainty is estimated to be 1{2% for the muon and 3% for electron avors. The 2.7% uncertainty in the integrated luminosity [45] applies to the normalization of signal events. Uncertainties in the signal yield due to the choice of PDFs and the values chosen for the factorization ( f ) and renormalization ( r) scales are also taken into account. The PDF uncertainties are evaluated using the NNPDF 3.0 [36] PDFs. The uncertainty related to the choice of f and r scales is evaluated following the proposal in refs. [68, 69] by varying the default choice of scales in the following 6 combinations of factors: ( f , r) section from the choice of PDFs and of factorization and renormalization scales ranges from 4 to 77%, and from 1 to 22%, respectively, depending on the resonance mass, particle type and its production mechanism. These uncertainties are fully correlated among the ` +jet and dijet channels. Tables 7 and 8 summarize the systematic uncertainties in the dijet and ` +jet channels, Statistical interpretation The mVV distribution observed in data and the SM background prediction are compared to check for the presence of a new resonance decaying to vector bosons. No bins with an excess with signi cance larger than three standard deviations are observed. We set upper limits on the production cross section of such resonances by combining the event categories of the dijet and ` +jet analyses. We follow the asymptotic approximation [70] of the CLS criterion described in refs. [71, 72]. 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Van Parijs Universite Libre de Bruxelles, Bruxelles, Belgium H. Brun, 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, D. Vannerom, Q. Wang, R. Yonamine, F. Zenoni, F. Zhang2 Ghent University, Ghent, Belgium A. Cimmino, T. Cornelis, D. Dobur, A. Fagot, M. Gul, I. Khvastunov, D. Poyraz, S. Salva, R. Schofbeck, 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, M. Komm, G. Krintiras, 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 Vargasa Universidade Estadual Paulista a, Universidade Federal do ABC b, S~ao Paulo, S. Ahujaa, C.A. Bernardesa, 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 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, M. Ruan, S.M. Shaheen, A. Spiezia, J. Tao, C. Wang, Z. Wang, H. Zhang, J. Zhao State Key Laboratory of Nuclear Physics and Technology, Peking University, Y. Ban, G. Chen, H. Huang, 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, B. Mesic, T. Susa University of Cyprus, Nicosia, Cyprus A. Attikis, G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos, P.A. Razis, H. Rykaczewski, D. Tsiakkouri 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 M. Kadastik, 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, T. Jarvinen, 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 (IPHC), Universite de Strasbourg, 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, 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, C.A. Carrillo Montoya, R. Chierici, D. Contardo, B. Courbon, P. Depasse, H. El Mamouni, J. Fan, J. Fay, S. Gascon, M. Gouzevitch, S. Perries, A. Popov14, D. Sabes, V. Sordini, M. Vander Donckt, P. Verdier, S. Viret Georgian Technical University, Tbilisi, Georgia T. Toriashvili15 Tbilisi State University, Tbilisi, Georgia RWTH Aachen University, I. Physikalisches Institut, Aachen, Germany C. Autermann, S. Beranek, L. Feld, M.K. Kiesel, K. Klein, M. Lipinski, M. Preuten, C. Schomakers, J. Schulz, T. Verlage 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, B. Kargoll, T. Kress, A. Kunsken, J. Lingemann, T. Muller, A. Nehrkorn, A. Nowack, C. Pistone, O. Pooth, A. Stahl16 Deutsches Elektronen-Synchrotron, Hamburg, Germany M. Aldaya Martin, T. Arndt, C. Asawatangtrakuldee, K. Beernaert, O. Behnke, U. Behrens, A.A. Bin Anuar, K. Borras17, A. Campbell, P. Connor, C. ContrerasCampana, F. Costanza, C. Diez Pardos, G. Dolinska, G. Eckerlin, D. Eckstein, T. Eichhorn, E. Eren, E. Gallo18, J. Garay Garcia, A. Geiser, A. Gizhko, J.M. Grados Luyando, A. Grohsjean, P. Gunnellini, A. Harb, J. Hauk, M. Hempel19, H. Jung, A. Kalogeropoulos, O. Karacheban19, M. Kasemann, J. Keaveney, C. Kleinwort, I. Korol, D. Krucker, W. Lange, A. Lelek, J. Leonard, K. Lipka, A. Lobanov, W. Lohmann19, 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. Pantaleo16, 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 M. Akbiyik, C. Barth, S. Baur, C. Baus, J. Berger, E. Butz, R. Caspart, T. Chwalek, F. Colombo, W. De Boer, A. Dierlamm, S. Fink, B. Freund, R. Friese, M. Gi els, A. Gilbert, Paraskevi, Greece I. Topsis-Giotis S. Kudella, H. Mildner, M.U. Mozer, Th. Muller, M. Plagge, G. Quast, K. Rabbertz, S. Rocker, F. Roscher, D. Schafer, M. Schroder, I. Shvetsov, G. Sieber, H.J. Simonis, R. Ulrich, S. Wayand, M. Weber, T. Weiler, S. Williamson, C. Wohrmann, R. Wolf Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia 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, E. Paradas 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, D. Horvath20, F. Sikler, V. Veszpremi, G. Vesztergombi21, A.J. Zsig Institute of Nuclear Research ATOMKI, Debrecen, Hungary N. Beni, S. Czellar, J. Karancsi22, A. Makovec, J. Molnar, Z. Szillasi Institute of Physics, University of Debrecen M. Bartok21, P. Raics, Z.L. Trocsanyi, B. Ujvari National Institute of Science Education and Research, Bhubaneswar, India S. Bahinipati, S. Choudhury23, P. Mal, K. Mandal, A. Nayak24, 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. Mohanty16, P.K. Netrakanti, L.M. Pant, P. Shukla, A. Topkar 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. Bhowmik25, R.K. Dewanjee, S. Ganguly, M. Guchait, Sa. Jain, S. Kumar, M. Maity25, G. Majumder, K. Mazumdar, T. Sarkar25, N. Wickramage26 Indian Institute of Science Education and Research (IISER), Pune, India S. Chauhan, S. Dube, V. Hegde, A. Kapoor, K. Kothekar, S. Pandey, A. Rane, S. Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran S. Chenarani27, E. Eskandari Tadavani, S.M. Etesami27, M. Khakzad, M. Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi28, F. Rezaei Hosseinabadi, B. Safarzadeh29, 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, A. Sharmaa, L. Silvestrisa;16, 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;16 INFN Sezione di Catania a, Universita di Catania b, Catania, Italy S. Albergoa;b, S. Costaa;b, A. Di Mattiaa, F. Giordanoa;b, R. Potenzaa;b, A. Tricomia;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, P. Lenzia;b, M. Meschinia, S. Paolettia, L. Russoa;30, G. Sguazzonia, D. Stroma, L. Viliania;b;16 INFN Laboratori Nazionali di Frascati, Frascati, Italy L. Benussi, S. Bianco, F. Fabbri, D. Piccolo, F. Primavera16 INFN Sezione di Genova a, Universita di Genova b, Genova, Italy V. Calvellia;b, F. Ferroa, M.R. Mongea;b, E. Robuttia, S. Tosia;b INFN Sezione di Milano-Bicocca a, Universita di Milano-Bicocca b, Milano, L. Brianzaa;b;16, F. Brivioa;b, V. Cirioloa;b, M.E. Dinardoa;b, S. Fiorendia;b;16, S. Gennaia, A. Ghezzia;b, P. Govonia;b, M. Malbertia;b, S. Malvezzia, R.A. Manzonia;b, D. Menascea, L. Moronia, M. Paganonia;b, D. Pedrinia, S. Pigazzinia;b, S. Ragazzia;b, T. Tabarelli de 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;16, M. Espositoa;b, F. Fabozzia;c, F. Fiengaa;b, A.O.M. Iorioa;b, G. Lanzaa, L. Listaa, S. Meolaa;d;16, P. Paoluccia;16, C. Sciaccaa;b, F. Thyssena INFN Sezione di Padova a, Universita di Padova b, Padova, Italy, Universita di Trento c, Trento, Italy P. Azzia;16, N. Bacchettaa, L. Benatoa;b, D. Biselloa;b, A. Bolettia;b, R. Carlina;b, P. Checchiaa, M. Dall'Ossoa;b, P. De Castro Manzanoa, T. Dorigoa, U. Dossellia, F. Gasparinia;b, U. Gasparinia;b, A. Gozzelinoa, M. Margonia;b, A.T. Meneguzzoa;b, M. Michelottoa, J. Pazzinia;b, M. Pegoraroa, N. Pozzobona;b, P. Ronchesea;b, E. Torassaa, M. Zanettia;b, P. Zottoa;b, G. Zumerlea;b INFN Sezione di Pavia a, Universita di Pavia b, Pavia, Italy A. Braghieria, F. Fallavollitaa;b, 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;16, 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 INFN Sezione di Roma a, Universita di Roma b, Roma, Italy L. Baronea;b, F. Cavallaria, M. Cipriania;b, D. Del Rea;b;16, M. Diemoza, S. Gellia;b, E. Longoa;b, F. Margarolia;b, Marzocchia;b, G. Organtinia;b, R. Paramattia, F. Preiatoa;b, S. Rahatloua;b, C. Rovellia, F. Santanastasioa;b INFN Sezione di Torino a, Universita di Torino b, Torino, Italy, Universita del Piemonte Orientale c, Novara, Italy N. Amapanea;b, R. Arcidiaconoa;c;16, S. Argiroa;b, M. Arneodoa;c, N. Bartosika, R. Bellana;b, C. Biinoa, N. Cartigliaa, F. Cennaa;b, M. Costaa;b, R. Covarellia;b, A. Deganoa;b, N. Demariaa, L. Fincoa;b, B. Kiania;b, C. Mariottia, S. Masellia, Kwangju, Korea E. Migliorea;b, V. Monacoa;b, E. Monteila;b, M. Montenoa, M.M. Obertinoa;b, L. Pachera;b, N. Pastronea, M. Pelliccionia, G.L. Pinna Angionia;b, F. Raveraa;b, A. Romeroa;b, M. Ruspaa;c, R. Sacchia;b, K. Shchelinaa;b, V. Solaa, A. Solanoa;b, A. Staianoa, P. Traczyka;b INFN Sezione di Trieste a, Universita di Trieste b, Trieste, Italy S. Belfortea, M. Casarsaa, F. Cossuttia, G. Della Riccaa;b, A. Zanettia Kyungpook National University, Daegu, Korea D.H. Kim, G.N. Kim, M.S. Kim, S. Lee, S.W. Lee, Y.D. Oh, S. Sekmen, D.C. Son, Chonbuk National University, Jeonju, Korea Chonnam National University, Institute for Universe and Elementary Particles, Hanyang University, Seoul, Korea J.A. Brochero Cifuentes, T.J. Kim Korea University, Seoul, Korea J. Lim, S.K. Park, Y. Roh Seoul National University, Seoul, Korea 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 National Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Malaysia I. Ahmed, Z.A. Ibrahim, J.R. Komaragiri, M.A.B. Md Ali32, F. Mohamad Idris33, W.A.T. Wan Abdullah, M.N. Yusli, Z. Zolkapli 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 P. Bunin, M. Gavrilenko, I. Golutvin, I. Gorbunov, A. Kamenev, V. Karjavin, A. Lanev, A. Malakhov, V. Matveev36;37, V. Palichik, V. Perelygin, M. Savina, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, N. Voytishin, A. Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia L. Chtchipounov, V. Golovtsov, Y. Ivanov, V. Kim38, E. Kuznetsova39, 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, Moscow, Russia A. Bylinkin37 National Research Nuclear University 'Moscow Engineering Physics Institute' (MEPhI), Moscow, Russia R. Chistov40, S. Polikarpov, E. Tarkovskii P.N. Lebedev Physical Institute, Moscow, Russia V. Andreev, M. Azarkin37, I. Dremin37, M. Kirakosyan, A. Leonidov37, A. Terkulov Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, A. Baskakov, A. Belyaev, E. Boos, M. Dubinin41, 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. Blinov42, Y.Skovpen42, D. Shtol42 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. Adzic43, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic, V. Rekovic nologicas (CIEMAT), Madrid, Spain 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, E. Curras, M. Fernandez, J. Garcia-Ferrero, G. Gomez, A. Lopez Virto, J. Marco, C. Martinez Rivero, F. Matorras, J. Piedra Gomez, T. Rodrigo, A. RuizJimeno, L. Scodellaro, N. Trevisani, I. Vila, R. Vilar Cortabitarte 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, C. Botta, T. Camporesi, R. Castello, M. Cepeda, G. Cerminara, Y. Chen, D. d'Enterria, A. Dabrowski, V. Daponte, A. David, M. De Gruttola, A. De Roeck, E. Di Marco44, M. Dobson, B. Dorney, T. du Pree, D. Duggan, M. Dunser, N. Dupont, A. Elliott-Peisert, P. Everaerts, S. Fartoukh, G. Franzoni, J. Fulcher, W. Funk, D. Gigi, K. Gill, M. Girone, F. Glege, D. Gulhan, S. Gundacker, M. Gutho , P. Harris, J. Hegeman, V. Innocente, P. Janot, J. Kieseler, H. Kirschenmann, V. Knunz, A. Kornmayer16, 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, P. Milenovic45, F. Moortgat, S. Morovic, M. Mulders, H. Neugebauer, 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, 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, D. Salerno, Y. Yang, A. Zucchetta 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. Chao, K.F. Chen, P.H. Chen, F. Fiori, W.-S. Hou, Y. Hsiung, Y.F. Liu, R.-S. Lu, M. Min~ano Moya, E. Paganis, A. Psallidas, J.f. Tsai Chulalongkorn University, Faculty of Science, Department of Physics, Bangkok, B. Asavapibhop, G. Singh, N. Srimanobhas, N. Suwonjandee { 47 { Cukurova University - Physics Department, Science and Art Faculty A. Adiguzel, S. Damarseckin, Z.S. Demiroglu, C. Dozen, E. Eskut, S. Girgis, G. Gokbulut, Y. Guler, I. Hos51, E.E. Kangal52, O. Kara, A. Kayis Topaksu, U. Kiminsu, M. Oglakci, G. Onengut53, K. Ozdemir54, S. Ozturk55, A. Polatoz, B. Tali56, S. Turkcapar, I.S. Zor bakir, C. Zorbilmez Middle East Technical University, Physics Department, Ankara, Turkey B. Bilin, S. Bilmis, B. Isildak57, G. Karapinar58, M. Yalvac, M. Zeyrek Bogazici University, Istanbul, Turkey E. Gulmez, M. Kaya59, O. Kaya60, E.A. Yetkin61, T. Yetkin62 Istanbul Technical University, Istanbul, Turkey A. Cakir, K. Cankocak, S. Sen63 Institute for Scintillation Materials of National Academy of Science of Ukraine, Kharkov, Ukraine B. Grynyov 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. Newbold64, S. Paramesvaran, A. Poll, T. Sakuma, S. Seif El Nasr-storey, D. Smith, Rutherford Appleton Laboratory, Didcot, United Kingdom K.W. Bell, A. Belyaev65, 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 Imperial College, London, United Kingdom 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. 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Wu University of Florida, Gainesville, U.S.A. D. Acosta, P. Avery, P. Bortignon, D. Bourilkov, A. Brinkerho , A. Carnes, M. Carver, D. Curry, S. Das, R.D. Field, I.K. Furic, J. Konigsberg, A. Korytov, J.F. Low, P. Ma, K. Matchev, H. Mei, G. Mitselmakher, D. Rank, L. Shchutska, D. Sperka, L. Thomas, J. Wang, S. Wang, J. Yelton Florida International University, Miami, U.S.A. S. Linn, P. Markowitz, G. Martinez, J.L. Rodriguez Florida State University, Tallahassee, U.S.A. A. Ackert, T. Adams, A. Askew, S. Bein, S. Hagopian, V. Hagopian, K.F. Johnson, H. Prosper, A. Santra, R. Yohay Florida Institute of Technology, Melbourne, U.S.A. M.M. Baarmand, V. Bhopatkar, S. Colafranceschi, M. Hohlmann, D. Noonan, T. Roy, University of Illinois at Chicago (UIC), Chicago, U.S.A. M.R. Adams, L. Apanasevich, D. Berry, R.R. Betts, I. Bucinskaite, R. Cavanaugh, O. Evdokimov, L. Gauthier, C.E. Gerber, D.J. Hofman, K. Jung, I.D. Sandoval Gonzalez, N. Varelas, H. Wang, Z. Wu, M. Zakaria, J. Zhang B. Bilki68, W. Clarida, K. Dilsiz, S. Durgut, R.P. Gandrajula, M. Haytmyradov, V. Khristenko, J.-P. Merlo, H. Mermerkaya69, A. Mestvirishvili, A. Moeller, J. Nachtman, H. Ogul, Y. Onel, F. Ozok70, A. Penzo, C. Snyder, E. Tiras, J. Wetzel, K. Yi Johns Hopkins University, Baltimore, U.S.A. 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, U.S.A. A. Al-bataineh, P. Baringer, A. Bean, S. Boren, J. Bowen, J. Castle, L. Forthomme, R.P. Kenny III, S. Khalil, A. Kropivnitskaya, D. Majumder, W. Mcbrayer, M. Murray, S. Sanders, R. Stringer, J.D. Tapia Takaki, Q. Wang Kansas State University, Manhattan, U.S.A. A. Ivanov, K. Kaadze, Y. Maravin, A. Mohammadi, L.K. Saini, N. Skhirtladze, S. Toda Lawrence Livermore National Laboratory, Livermore, U.S.A. F. Rebassoo, D. Wright University of Maryland, College Park, U.S.A. C. Anelli, A. 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Rusack, N. Tambe, J. Turkewitz University of Mississippi, Oxford, U.S.A. J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, U.S.A. E. Avdeeva, R. Bartek71, K. Bloom, D.R. Claes, A. Dominguez71, C. Fangmeier, R. Gon zalez Suarez, R. Kamalieddin, I. Kravchenko, A. Malta Rodrigues, F. Meier, J. Monroy, J.E. Siado, G.R. Snow, B. Stieger M. Alyari, J. Dolen, A. Godshalk, C. Harrington, I. Iashvili, J. Kaisen, A. Kharchilava, A. Parker, S. Rappoccio, B. Roozbahani Northeastern University, Boston, U.S.A. G. Alverson, E. Barberis, 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, U.S.A. S. Bhattacharya, O. Charaf, K.A. Hahn, A. Kumar, N. Mucia, N. Odell, B. Pollack, M.H. Schmitt, K. Sung, M. Trovato, M. Velasco University of Notre Dame, Notre Dame, U.S.A. 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, U.S.A. J. Alimena, L. Antonelli, 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, U.S.A. S. Cooperstein, O. Driga, P. Elmer, J. Hardenbrook, P. Hebda, D. Lange, J. Luo, D. Marlow, T. Medvedeva, K. Mei, J. Olsen, C. Palmer, P. Piroue, D. Stickland, A. Svyatkovskiy, University of Puerto Rico, Mayaguez, U.S.A. Purdue University, West Lafayette, U.S.A. A. Barker, V.E. Barnes, S. Folgueras, L. Gutay, M.K. Jha, M. Jones, A.W. Jung, A. Khatiwada, D.H. Miller, N. Neumeister, J.F. Schulte, X. Shi, J. Sun, F. Wang, W. Xie Purdue University Calumet, Hammond, U.S.A. N. Parashar, J. Stupak Rice University, Houston, U.S.A. A. Adair, B. Akgun, Z. Chen, K.M. Ecklund, F.J.M. Geurts, M. Guilbaud, W. Li, B. Michlin, M. Northup, B.P. 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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, U.S.A. S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, P. Sheldon, S. Tuo, J. Velkovska, Q. Xu University of Virginia, Charlottesville, U.S.A. T. Sinthuprasith, X. Sun, Y. Wang, E. Wolfe, F. Xia Wayne State University, Detroit, U.S.A. C. Clarke, R. Harr, P.E. Karchin, J. Sturdy M.W. Arenton, P. Barria, B. Cox, J. Goodell, R. Hirosky, A. Ledovskoy, H. Li, C. Neu, University of Wisconsin - Madison, Madison, WI, U.S.A. D.A. Belknap, J. Buchanan, C. Caillol, 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, 1: Also at Vienna University of Technology, Vienna, Austria 2: Also at State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, 3: Also at Institut Pluridisciplinaire Hubert Curien (IPHC), Universite de Strasbourg, 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, 16: Also at CERN, European Organization for Nuclear Research, Geneva, Switzerland 17: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany 18: Also at University of Hamburg, Hamburg, Germany 19: Also at Brandenburg University of Technology, Cottbus, Germany 20: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary 21: Also at MTA-ELTE Lendulet CMS Particle and Nuclear Physics Group, Eotvos Lorand 22: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary 23: Also at Indian Institute of Science Education and Research, Bhopal, India 24: Also at Institute of Physics, Bhubaneswar, India 25: Also at University of Visva-Bharati, Santiniketan, India 26: Also at University of Ruhuna, Matara, Sri Lanka 27: Also at Isfahan University of Technology, Isfahan, Iran 28: Also at Yazd University, Yazd, Iran University, Tehran, Iran 30: Also at Universita degli Studi di Siena, Siena, Italy 31: Also at Purdue University, West Lafayette, U.S.A. 29: Also at Plasma Physics Research Center, Science and Research Branch, Islamic Azad 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 St. Petersburg State Polytechnical University, St. Petersburg, Russia 39: Also at University of Florida, Gainesville, U.S.A. 40: Also at P.N. Lebedev Physical Institute, Moscow, Russia 41: Also at California Institute of Technology, Pasadena, U.S.A. 42: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia 43: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia 44: Also at INFN Sezione di Roma; Universita di Roma, Roma, Italy 45: Also at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, 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 Istanbul Aydin University, Istanbul, 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 Adiyaman University, Adiyaman, Turkey 57: Also at Ozyegin University, Istanbul, Turkey 58: Also at Izmir Institute of Technology, Izmir, Turkey 60: Also at Kafkas University, Kars, Turkey 61: Also at Istanbul Bilgi University, Istanbul, Turkey 62: Also at Yildiz Technical University, Istanbul, Turkey 63: Also at Hacettepe University, Ankara, Turkey 64: Also at Rutherford Appleton Laboratory, Didcot, U.K. 65: Also at School of Physics and Astronomy, University of Southampton, Southampton, U.K. 66: Also at Instituto de Astrof sica de Canarias, La Laguna, Spain 67: Also at Utah Valley University, Orem, U.S.A. 68: Also at Argonne National Laboratory, Argonne, U.S.A. 69: Also at Erzincan University, Erzincan, Turkey 70: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey 71: Now at The Catholic University of America, Washington, U.S.A. 72: Also at Texas A&M University at Qatar, Doha, Qatar 73: Also at Kyungpook National University, Daegu, Korea [20] CMS collaboration, V Tagging Observables and Correlations, CMS-PAS-JME-14-002 (2014). 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Search for massive resonances decaying into WW, WZ or ZZ bosons in proton-proton collisions at \( \sqrt{s}=13 \) TeV, Journal of High Energy Physics, 2017, DOI: 10.1007/JHEP03(2017)162