Search for a heavy resonance decaying into a Z boson and a vector boson in the \( \nu \overline{\nu}\mathrm{q}\overline{\mathrm{q}} \) final state

Journal of High Energy Physics, Jul 2018

Abstract A search is presented for a heavy resonance decaying into either a pair of Z bosons or a Z boson and a W boson (ZZ or WZ), with a Z boson decaying into a pair of neutrinos and the other boson decaying hadronically into two collimated quarks that are reconstructed as a highly energetic large-cone jet. The search is performed using the data collected with the CMS detector at the CERN LHC during 2016 in proton-proton collisions at a center-of-mass energy of 13 TeV, corresponding to a total integrated luminosity of 35.9 fb−1. No excess is observed in data with regard to background expectations. Results are interpreted in scenarios of physics beyond the standard model. Limits at 95% confidence level on production cross sections are set at 0.9 fb (63 fb) for spin-1 W′ bosons, included in the heavy vector triplet model, with mass 4.0 TeV (1.0 TeV), and at 0.5 fb (40 fb) for spin-2 bulk gravitons with mass 4.0 TeV (1.0 TeV). Lower limits are set on the masses of W′ bosons in the context of two versions of the heavy vector triplet model of 3.1TeV and 3.4 TeV, respectively. Open image in new window

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Search for a heavy resonance decaying into a Z boson and a vector boson in the \( \nu \overline{\nu}\mathrm{q}\overline{\mathrm{q}} \) final state

Received: March Search for a heavy resonance decaying into a A search is presented for a heavy resonance decaying into either a pair of Z bosons or a Z boson and a W boson (ZZ or WZ), with a Z boson decaying into a pair of neutrinos and the other boson decaying hadronically into two collimated quarks that are reconstructed as a highly energetic large-cone jet. The search is performed using the data collected with the CMS detector at the CERN LHC during 2016 in proton-proton collisions at a center-of-mass energy of 13 TeV, corresponding to a total integrated luminosity of 35.9 fb 1 . No excess is observed in data with regard to background expectations. Results are interpreted in scenarios of physics beyond the standard model. Limits at 95% con dence level on production cross sections are set at 0.9 fb (63 fb) for spin-1 W0 bosons, included in the heavy vector triplet model, with mass 4.0 TeV (1.0 TeV), and at 0.5 fb (40 fb) for spin-2 bulk gravitons with mass 4.0 TeV (1.0 TeV). Lower limits are set on the masses of W0 bosons in the context of two versions of the heavy vector triplet model of 3.1 TeV and 3.4 TeV, respectively. Beyond Standard Model; Hadron-Hadron scattering (experiments) - boson HJEP07(218)5 and a vector boson in the qq nal state The CMS collaboration 1 Introduction 2 The CMS detector 3 Data and simulated samples 4 Event reconstruction 5 Event selection 6 Background estimation 7 Systematic uncertainties 8 Results 9 Summary The CMS collaboration the proposed spin-2 particle and ek = k=M Pl, where k is the curvature parameter of the ve-dimensional space-time metric, and M Pl = MPl= 8 is the reduced Planck mass. p { 1 { Other theories extend the SM by adding elds to the SM Lagrangian, resulting in a larger symmetry. New vector bosons arise from the breaking of this symmetry. The heavy vector triplet (HVT) model [6] provides a framework for many BSM models, in particular those where heavy spin-1 partners of the vector bosons (W0 and Z0 bosons) [7, 8] are expected to be weakly coupled to SM particles (referred to as the \HVT model A" scenario), and the composite Higgs model [9, 10], where exotic vector bosons are strongly coupled to ordinary particles (the \HVT model B" scenario). Both scenarios are described by three Lagrangian parameters: the couplings of spin-1 particles to SM fermions (cF) and to SM bosons (cH), and the strength of the interaction (gV). In the HVT model A scenario, gV = 1, cF = 1:316, and cH = 0:556; in HVT model B, gV = 3, cF = 1:024, and cH = 0:976 [6]. Previous searches performed at the CERN LHC looking for evidence for these models have set limits on the production cross section of the new heavy bosons (46.1 fb at a mass of 1.4 TeV and 0.7 fb at a mass of 4.1 TeV), and mass lower limits of 3.3 TeV (3.6 TeV) for HVT model A (model B) [11{15]. In this article, we present the results of a search for heavy resonances decaying into a pair of vector bosons, where one vector boson is a Z boson decaying into neutrinos, while the other boson V (either a W or Z boson) decays hadronically. The vector bosons are mostly produced in a back-to-back topology with large Lorentz boosts because of the large mass of the new particle (on the order of 1 TeV); this implies that the two quarks originating from the vector boson decay are close enough to be reconstructed within one single large-cone jet, an approach that, in this kinematic region, is more e cient than building the vector boson candidate as two distinct standard jets. Since neutrinos do not leave any visible signature in the detector, they are reconstructed as a large amount of missing transverse momentum (p~Tmiss) recoiling against the hadronic component. The sensitivity of the search is enhanced by the relatively high branching fraction of the Z boson into neutrinos (20%) and of the other vector boson into a pair of quarks ( 70%). Jet substructure techniques [16] are exploited to improve the discrimination between signal events and SM background processes. The contributions of the SM backgrounds, composed mainly of Z+jets and W+jets events, are estimated using a method that interpolates the data from control regions into the signal region with a t constrained by the simulation. 2 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. 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. Forward calorimeters extend the pseudorapidity ( ) coverage provided by the barrel and endcap detectors. Muons are detected in gas-ionization chambers embedded in the steel ux-return yoke outside the solenoid. Events of interest are selected using a two-tiered trigger system [17]. The rst level, composed of custom hardware processors, uses information from the calorimeters and muon detectors. The second level, known as { 2 { the high-level trigger (HLT), consists of a farm of processors running a version of the full event reconstruction software optimized for fast processing. 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. [18]. 3 Data and simulated samples The analysis is performed on data collected in 2016 with the CMS detector during protonproton collisions at the LHC at a center-of-mass energy of 13 TeV, corresponding to a total integrated luminosity of 35.9 fb 1. Two signal models are simulated: the rst considers a spin-1 HVT W0 boson decaying into a W and a Z boson for both A and B scenarios, and the second considers a spin-2 bulk graviton G decaying into two Z bosons. Both processes are generated at leading order (LO) with the MadGraph5 amc@nlo v2.2.2 [19] matrix element Monte Carlo (MC) generator for a range of di erent mass hypotheses for the resonances from 0.6 to 4.5 TeV. Signals are generated assuming the resonances have negligible width (0.1% of their masses) compared to the experimental resolution (4{8% depending on their masses); this assumption is the so-called \narrow-width approximation". The actual width of the spin-2 resonances may be larger depending on the value of the curvature parameter ek in the model [ 1, 2 ], but this e ect is only signi cant for values of ek larger than 1, which are not considered in this analysis. For the background, events with a vector boson produced with additional partons are generated at next-to-leading order (NLO) in the FxFx merging scheme [20]. Electroweak corrections at NLO [21] are applied to these samples as a function of the transverse momentum pT of the vector bosons. Top quarkantiquark (tt) and single top quark events are simulated at NLO in the ve- avor scheme with powheg v2 [22{26]. Inclusive diboson production (WW, WZ, ZZ) is considered as well, and generated with pythia 8.212 [27] at LO. The hadronization and fragmentation steps of all simulated samples are handled by pythia with the CUETP8M1 [28] tune. The NNPDF3.1 [29] parton distribution functions are used in the simulations. The e ect of additional proton-proton interactions within the same or nearby bunch crossings (pileup) is accounted for by adding simulated minimum bias events to the hard interaction. The frequency distributions of the pileup events are reweighted to match those observed in data. The simulation of the CMS detector is performed with Geant4 [ 30 ]. 4 Event reconstruction The particle- ow (PF) event algorithm [31] 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 directly from the ECAL measurement, corrected for zero-suppression e ects. 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 { 3 { bremsstrahlung photons spatially compatible with originating from the electron track. The energy 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 ECAL and HCAL energy deposits, corrected for zero-suppression e ects 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 energies. Jets are reconstructed from PF inputs, using FastJet 3.1 [ 32 ] to cluster jets with the anti-kT algorithm [33], with two distance parameters: 0.4 (\AK4" jets) and 0.8 (\AK8" jets). The jet momentum is determined as the four-vector sum of all particle momenta in the jet, and is found from simulation to be within 2 to 10% of the momentum of the quark that initiated the jet, over the whole pT spectrum and detector acceptance. The raw jet energies are further corrected to establish a relative uniform response of the calorimeter in and a calibrated absolute response in pT [34]. Charged particles not associated to the primary vertex are removed from the jet [35]. An additional o set correction is applied to the jet energies to subtract the contribution from pileup [35]. The jet energy scale (JES) is calculated using a detailed MC simulation of the detector, and further adjusted using the pT balance in dijet, multijet, photon+jet and leptonically decaying Z+jet events in data [36]. A smearing procedure has been applied to jets in the simulated samples in order to account for small di erences between the jet momentum resolutions observed in simulation and in data. The jet energy resolution (JER) is 15% at 10 GeV, 8% at 100 GeV, and 4% at 1 TeV [36]. A minimum threshold on the energy recorded in the HCAL is applied to remove spurious jet-like features originating from isolated noise patterns in certain regions. Jets are required to have more than one PF constituent, and they are required to have less than 80% of their total energy originating from neutral hadrons, less than 99% from electrons, and more than 20% from charged hadrons. The jet mass reconstruction is optimized for this analysis using a combination of a jet grooming technique [37, 38] and pileup mitigation [39]. In the jet grooming algorithm, the constituents of the AK8 jets are reclustered using the Cambridge-Aachen algorithm [40, The \modi ed mass drop tagger" algorithm [37], also known as the \soft drop" algorithm, with angular exponent = 0, soft cuto threshold zcut < 0:1, and characteristic radius R0 = 0:8 [38], is applied to remove soft, wide-angle radiation from the jet. The pileup mitigation is performed by the \pileup per particle identi cation" algorithm [39], a method that assigns a weight to each charged or neutral particle, which is determined by the probability for the particle to have originated from the primary vertex of the hard interaction. Finally, the jet mass is corrected with pT-dependent factors [42] to account for the small di erence observed in the reconstructed vector boson mass between data and simulated events in a tt control sample, in which one W boson, originating from the top or antitop quark, decays into leptons and the other W boson decays hadronically. The missing transverse momentum vector is de ned as the negative sum of the pT of all PF candidates in the event: p~miss = T ip~Ti; its magnitude is referred to as pmiss. T This raw quantity is corrected by propagating the e ect of the jet energy corrections. Uncertainties in the p~miss determination arise from mismeasurements caused by detector T { 4 { alignment, unclustered energy deposits, and contributions coming from pileup [43]. Events with spurious missing momentum related to detector noise and badly reconstructed events are rejected [43]. 5 Event selection Events are required to satisfy criteria at the HLT trigger level on either pTmiss or the missing hadronic activity, HTmiss, which is de ned as the magnitude of the transverse component of the negative sum of the three-momenta of all the objects identi ed as jets at trigger level. To avoid ine ciencies due to the prescaling of the triggers during high-luminosity LHC operation, several triggers are used, variously requiring HTmiss or pTmiss > 90, 110, 120 GeV, or pTmiss > 170 GeV, in order to have at least one nonprescaled trigger at any given time. The pTmiss trigger e ciency has been measured with data events satisfying one or more single-muon triggers. A W leptonic decay topology is selected (W ! the presence of pTmiss in the event, due to the neutrino. One muon identi ed by o ine algorithms is required: this not only guarantees that the sample does not overlap with the search ), since it ensures region of the analysis (where events with muons are rejected), but also reduces the contamination from particles or jets misidenti ed as leptons at the trigger level. The additional T condition of having at least one AK8 jet is applied, in order to select events with a topology similar to that of the considered search. The combination of pTmiss triggers reaches a plateau in e ciency of 96% around pmiss > 200 GeV, which is chosen as the minimum pmiss threshold for the event selection. An independent e ciency measurement has been performed using a data set satisfying single-electron triggers, and the discrepancy with the result T based on the muon data set is taken as a systematic uncertainty, which amounts to 1%. The AK8 jets are required to satisfy pT > 200 GeV and j j < 2:4. The largest-pT AK8 jet in the event is assumed to be the hadronically decaying boson (V) candidate. The jet mass (mj) is used to de ne the search region. Since the analysis searches for a diboson resonance where one vector boson decays hadronically, the mass of the jet candidate is expected to lie within a window around the nominal masses of the W and Z bosons, chosen to be between 65 and 105 GeV. Two control regions are de ned that are expected to be depleted in signal: the \low sideband", which lies in the mj range 30{65 GeV, and the \high sideband", with mj above 135 GeV. These sidebands play a crucial role in the background estimation. The region 105{135 GeV is excluded from the sideband selections in order to not overlap with other diboson searches aiming at a nal state containing a hadronically decaying Higgs boson. This exclusion allows the results to be combined with those of other searches in a straightforward manner. The region under 30 GeV is discarded, since jets are not reconstructed su ciently well in this region. Jet substructure is exploited to further improve the ability to identify signal events. The 21 N -subjettiness ratio [16] distinguishes jets with two separable substructure components from jets with only one substructure component. In the former case, the 21 distribution is peaked towards a small fraction of unity; in the latter case, it has a broader shape, centered around larger values closer to 1. Two exclusive search categories are dened: a low-purity category (0:35 < 21 < 0:75) and a high-purity category ( 21 < 0:35). { 5 { In principle, the high-purity category is the most sensitive to the signals explored; nevertheless, the low-purity category allows us to retain a signi cant part of the signal e ciency, especially for very heavy resonances (3{4 TeV). As a consequence, the signal sensitivity improves by up to 40% when the categories are combined. Multiplicative scale factors [42] are used to correct observed discrepancies between data and simulation, and are measured to be 0:99 0:11 for events falling into the high-purity category and 1:03 0:23 for those in the low-purity category. They have been measured with MC simulation and top quark-enriched data samples, and are applied to simulated backgrounds. The reconstructed p~T of the invisibly decaying Z boson is set equal to p~miss. Thus, inT stead of the invariant mass, the resulting reconstructed VZ candidate mass is the transverse HJEP07(218)5 mass mTVZ: q mTVZ = 2ETjpTmiss 1 cos (p~Tj; p~miss) ; T (5.1) where E Tj = Ej sin and (p~Tj; p~miss) is the azimuthal angle between the p~miss and the T T leading AK8 jet transverse momentum vector. The AK4 jets are used for background suppression; they are required to satisfy pT > 30 GeV and j j < 2:4. If the event contains an AK4 jet passing a loose b tagging criterion using the combined secondary vertex (CSVv2) [44, 45] algorithm, and it does not overlap with the AK8 jet identi ed as the V candidate, the event is discarded, since this suggests that the event is more likely to have originated from a top quark decay. Scale factors are applied to correct for the di erent b tagging e ciency in data and simulated samples [44, 45]. A set of selection criteria has been applied to improve the background rejection. By requiring a minimum azimuthal angular separation of 0.5 between p~miss and the p~T of the T AK4 jets outside the cone of the leading AK8 jet, the contribution of background events originating from soft multijet radiation is reduced from 30% to 2% or 3%, depending on the purity category. The single top quark and tt contributions are approximately halved by applying the loose b tag veto described above. Background contributions are further suppressed by requiring a back-to-back topology in the transverse plane between the V and Z candidates, speci cally, Final states with photons, electrons, muons, and hadronically decaying tau leptons are rejected in this analysis. The identi cation of these objects is performed using the variables described in ref. [31]. An event is discarded if it contains at least one photon with pT > 15 GeV and j j < 2:5, at least one electron with pT > 10 GeV and j j < 2:5, at least one muon with pT > 10 GeV and j j < 2:4, or at least one hadronically decaying tau lepton with pT > 18 GeV and j j < 2:4. The main discriminating variables used to perform the background prediction, mj and 21, are compared in data and MC simulation in gure 1. Two signal hypotheses, a spin-1 W0 boson and a spin-2 bulk graviton, are displayed as well. They are characterized by jet mass spectra peaking at the W mass and at the Z mass, respectively, and by a 21 distribution re ecting the two-prong structure of the jet produced in the vector boson hadronic decay, signi cantly di erent from the background. The discrepancy visible between the data and the background prediction is due to the imperfect modeling of the jet substruc{ 6 { CMS Sidebands and signal region ×103 Data Z(νν) + jets W(lν) + jets tt Single t VV Bkg stat. Data Z(νν) + jets W(lν) + jets tt VV Single t Bkg stat. mG = 1 TeV (10 pb) mW' = 3 TeV (10 pb) n i /sb 35 t 2/5×105 background estimation approach, described in section 6, is applied. 6 Background estimation This analysis searches for a localized excess in data in the transverse mass spectrum of the VZ system. Hence, accurate background modeling is crucial to the analysis. The main irreducible background is from events in which a Z boson is produced along with additional jets (\Z+jets") and decays into neutrinos. The second dominant contribution comes from events in which a W boson is produced along with additional jets (\W+jets") and decays leptonically, with the charged lepton falling outside the detector acceptance or not correctly identi ed. Since the production mechanisms of these two processes are the same, these two categories of events are grouped together as \V+jets" events. Smaller background contributions come from events in which at least one top quark (either a tt pair or a single top quark, indicated as \Top" background) or a pair of vector bosons (WW, WZ, or ZZ, which we call \VV" background) is produced; these are referred to as \secondary backgrounds". The background estimation technique [46], which is now known as the \ method", takes advantage of the data sidebands to predict the normalization and mTVZ shape of the { 7 { V+jets background distributions, which are poorly populated by simulations in phase space regions with large transverse momentum. The normalization and shape of the secondary backgrounds are determined from MC simulation. This data-driven approach allows us to improve the agreement between data and predictions, especially in the higher tails of the momentum distributions. The background prediction is performed in two steps for each of the two purity categories. First, the mass spectrum of the AK8 jet is the variable chosen to predict the background event yield in the signal region. Then, once the normalization is determined, the transverse mass distribution of the diboson candidates is used to predict the background shapes in the signal region. To perform the normalization prediction, the mj distribution of each background is tted in simulated samples with an empirical probability density function (pdf), converted into an extended likelihood in order to allow the event yield to vary in the t. The main background is modeled by using two alternative functional forms, and the di erence between the two yield predictions is considered as a systematic uncertainty and propagated to the nal results. The mj spectrum of the V+jets background is smoothly falling in the low-purity category; hence, it is modeled as a power law (main function) or as a Gaussian peak added to a falling exponential (alternative function), in order to check that a di erent description of the slope of the spectrum near the signal region does not signi cantly a ect the nal result. In the high-purity category, the mj spectrum has a peaking component, so it is described by a broad Gaussian peak, centered at approximately 150 GeV, added to a falling exponential (main function), or by an exponential function convolved with an error function to describe the turn-on e ect at low mass (alternative function). The top quark and diboson backgrounds are modeled as Gaussian peaks, centered on the top quark and W or Z masses, respectively, added to a smoothly falling exponential background. Once the extended likelihoods for the main and secondary backgrounds are added together, an extended maximum likelihood t is performed in the data sidebands. The parameters related to the V+jets background and its normalization are allowed to vary according to data, whereas those describing the secondary backgrounds are xed to the theoretical predictions. The expected number of background events in the signal region is then evaluated by integrating the nal extended likelihood that describes the total background. The results of the background estimation are presented in gure 2 as smooth functions, and are compared to data. The t to the data is performed in the sideband regions described in section 5. Data are compared to the method background predictions in the signal region (SR), while the Higgs region is excluded from the analysis. It can be seen that the data agree with the background estimates. The nal step consists in predicting the functional shape of the mT spectrum of the total background. First, the distribution of mTVZ is described separately for each background using MC simulation, both in the signal region and sidebands. The general background shape expected for all SM processes is an exponentially falling function with two parameters, of the form e x=(a+bx). { 8 { g ta2 LSB SR Higgs HSB Data function is de ned as the ratio between the V+jets background pdf in the signal region (fSVR+jets) and that in the sidebands (fSVB+jets), predicted from simulation: (mTVZ) = fSVR+jets(mTVZ) fSVB+jets(mTVZ) : ratio can be interpreted as a transfer function from the sidebands to the signal region, accounting for the small kinematical di erences in the two regions of the V+jets background. The typical correction resulting from using the ratio is on the order of 1{5 per mil. A simultaneous t to MC simulation and data sidebands is performed in order to extract the function and the main background parameters respectively, while the secondary background shapes are taken from predictions from MC simulation, as described in the following equation: fSdRata(mTVZ) = hfSdBata(mTVZ) fSTBop(mTVZ) fSVBV(mTVZ)i (mTVZ) + fSTRop(mTVZ) + fSVRV(mTVZ): The background estimation obtained with the method, i.e., the predicted spectrum of mTVZ in the background-only hypothesis, is compared with data in signi cant excess is observed with regard to the SM expectations. gure 3, and no The robustness of the method is tested by splitting the low sideband into two subregions, one considered as a narrower lower sideband (30{50 GeV) and the other (50{ 65 GeV) taken as a validation region. The predictions obtained by applying the method in the narrow lower sideband and the high sideband are then compared to data distributions in the validation region, and are found to agree. Data g ta2 35.9 fb-1 (13 TeV) Data )a4 g ta2 method in the low-purity (left) and high-purity (right) categories, represented as colored areas bounded by smooth functions. As a reference, the expected distribution of a W0 with a mass of 3 TeV decaying into a W boson and a Z boson is displayed. Data are shown as black markers. 7 Systematic uncertainties The background normalization is predicted from a set of simultaneous ts to the simulated and data samples, so the uncertainty in the normalization is estimated by propagating all the uncertainties a ecting the main and the secondary background ts. The statistical uncertainty in the t, determined by the number of data events in the sidebands, contributes to the uncertainty in the main background event yield by 5% and 15% for the low- and highpurity categories, respectively. A second source of uncertainty is the absolute di erence in the V+jets event yield prediction between the main function and the alternative function used to t the mj spectrum of the V+jets background in the simulated samples. It amounts to 5% and 4% for the low- and high-purity categories, respectively. The uncertainties related to the number of expected events from the secondary backgrounds amount to 68% and 48% for the low- and high-purity categories, respectively, for the top quark background yield, and to 11% and 19%, respectively, for the diboson background yield. Given that the secondary backgrounds are a small fraction of the total, the overall impact of the uncertainties in their event yields is negligible. The uncertainties in the parameters describing the shape of the mTVZ distribution of the main background are obtained by propagating the uncertainties related to each parameter of the simultaneous t to simulation and data sidebands. These parameters are then decorrelated by diagonalizing their covariance matrix with a linear transformation. The normalizations of the secondary backgrounds and of the signal are a ected by a 1% uncertainty in the trigger e ciency, calculated as described in section 5. The impact of the uncertainties in the pT of the reconstructed bosons is evaluated by simultaneously varying their pT within their uncertainties, since p~miss is in uenced by the T pT corrections applied to all the hadronic objects present in the event. The uncertainties related to JES and JER are evaluated by varying their numerical values within their uncertainties. They have a negligible impact (less than 1%) on both the normalization of the signal and secondary backgrounds, and on their shape; namely, on the parameters describing the exponential behavior of the spectra. The uncertainty in p~miss arising from unclustered energy deposits is also negligibly small. Uncertainties related to the mj corrections are considered, and they a ect the signal and background yields by 1%. Uncertainties related to T the jet mass smearing a ect the signal yield by 5.1%, the top quark backgrounds by 3.1%, and the diboson backgrounds by 2.0%. Jet mass smearing uncertainties a ect the parameters describing the top quark and diboson background shapes by 4% and 1%, respectively. The uncertainty related to the 21 scale factors, as described in section 5, has the largest single impact on the nal results. An additional source of uncertainty comes from the jet pT dependence of the 21 scale factors. The 21 distributions are modeled at higher pT regimes (above 200 GeV), where the event yield is very small in data, by using an alternative showering scheme (herwig++ [47]) and compared to pythia. The discrepancy between the predictions is parameterized as a function of the jet pT. In this analysis, the uncertainties due to the 21 scale factor extrapolations at high pT amount to 9{20%, depending on the purity category. The uncertainty in the b tagging e ciency a ecting the veto applied to AK4 jets impacts the signal normalization by 1%, the diboson background normalization by less than 1%, and the top quark background normalization by 2%. A minor source of uncertainty comes from the uncertainty in the total inelastic protonproton cross section at 13 TeV, which a ects the pileup distribution, and thus the normalization of the simulated samples. It amounts to less than 1% for diboson, top quark, and signal samples. 2.5% [48]. A 3% uncertainty is assigned to the e ciency of vetoing hadronically decaying tau leptons. The uncertainty in the measurement of the integrated luminosity amounts to The renormalization and factorization scales used in the simulation are varied by a factor of 2 and a factor of 0.5, both separately and independently. Per-event weights are extracted and propagated to the invariant mass distributions. These scale variations a ect the shape of the top quark background by a total of 1%, and its normalization by 7% (renormalization scale) and 3% (factorization scale); they both a ect the diboson background normalization by 1%. The uncertainty related to the choice of the parton distribution functions used in simulation is estimated by following the prescriptions in ref. [49], using the NNPDF3.1 [29] set. The parameters describing the parton distribution functions are varied together within their uncertainties, and the resulting variations are used as a set of per-event weights, applied to the invariant mass distributions. These uncertainties affect the normalization of the top quark and diboson backgrounds by 0.3% each; the e ect on the top quark and diboson background shapes is negligibly small. Uncertainties of 15% [50, 51] and 10% [52{54] are assigned to the normalization of the diboson and top quark backgrounds, respectively, from the knowledge of the production cross section. An unbinned pro le likelihood t is performed on the nal spectra of the transverse mass of the diboson candidates. The signals are modeled with a Crystal Ball function [55], i.e., a function with a Gaussian core and a power-law behavior in the low tail. Systematic uncertainties are treated as nuisance parameters constrained with a log-normal distribution and pro led during the minimization. The background-only hypothesis is tested in the data, where the low- and high-purity categories have been combined. The asymptotic modi ed frequentist approach [56{58], or CLs criterion, is used to quote 95% con dence level (CL) limits. The observed and expected limits on the product of the cross section and branching fraction ( B(W0 ! WhadZinv)) for a spin-1 W0 decaying into W and Z bosons that in turn decay in the hadronic and invisible channels, respectively, as a function of the mass of the resonance, are shown in gure 4 (left). The hypothesis of a heavy spin-1 resonance, predicted by the HVT model A scenario, is rejected at 95% CL for masses smaller than 3.1 TeV, while the W0 described in the HVT model B context is excluded up to 3.4 TeV. At these mass values, the product of cross section and branching fraction are expected to be 1.4 fb and 1.1 fb, respectively. The observed and expected limits on the product of the cross section and branching fraction ( B(G ! ZhadZinv)) for a spin-2 bulk graviton decaying into a pair of Z bosons, where one Z boson decays hadronically and the other invisibly, are shown in gure 4 (right), as a function of the mass of the resonance. The theoretical predictions for the curvature parameter hypothesis ek = 0:5 are shown for comparison. The results of this search complement those published by the ATLAS collaboration [59], which were obtained from an investigation of the same nal state, using di erent jet substructure and background estimation techniques. The limits obtained here are the best single limits obtained in this nal state. 9 Summary A search has been made for heavy diboson resonances (WZ, ZZ) decaying into a pair of vector bosons, one of which is a Z boson decaying into and the other is a W or Z boson that decays into qq. The data were collected by the CMS detector from proton-proton collisions produced at the LHC at a center-of-mass energy of 13 TeV. In this analysis, the hadronically decaying W or Z boson is reconstructed as a large-cone jet. The invisible decay of the Z boson manifests itself as a large amount of missing transverse momentum recoiling against the jet. The transverse components of the VZ system momentum are used to de ne the transverse mass variable, where a search for a localized excess is performed. The expected background is described with a hybrid data/simulation approach that takes advantage of data sidebands to predict the background normalization and shape in the signal region. To improve the discovery potential, two purity categories are de ned, based on a jet substructure observable. An unbinned maximum likelihood t is performed. No excess is observed in data compared to standard model predictions. Upper limits are CMS W' → WZ → qqνν CMS G → ZZ → qqνν 95% CL limits Observed Expected ± 1 std. deviation ± 2 std. deviations Spin-1 signal W' (HVT model B) Spin-1 signal W' (HVT model A) 3500 4000 mW' (GeV) G ( B ) G ( σ10 1 10−11000 Observed Expected ± 1 std. deviation ± 2 std. deviations Spin-2 signal G (Bulk), k = 0.5 ~ 1500 2000 2500 3000 1500 2000 2500 3000 3500 4000 mG (GeV) a spin-2 bulk graviton signal hypothesis (right), as a function of the W0 and G mass, respectively. The low- and high-purity categories have been combined. The inner and outer shaded bands indicate the 68% and 95% uncertainty intervals associated with the expected limits. Theoretical predictions are shown for: (left) the two HVT models considered, model A (blue dotted-and-dashed line) and model B (red solid line), and (right) a graviton model with a curvature parameter of ek = 0:5 (violet solid line). established at 95% con dence level on the product of the production cross section and branching fraction for a spin-1 heavy vector triplet (HVT) W0 boson and spin-2 bulk graviton, which are in the range 0.9{63 fb and 0.5{40 fb, respectively, depending on the resonance mass. The existence of a W0 boson is excluded at 95% con dence level up to a mass of 3.1 TeV in the HVT model A and up to 3.4 TeV in the HVT model B. Acknowledgments We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative sta s at CERN and at other CMS institutes for their contributions to the success of the CMS e ort. In addition, we gratefully acknowledge the computing centers and personnel of the Worldwide LHC Computing Grid for delivering so e ectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies: BMWFW and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES and CSF (Croatia); RPF (Cyprus); SENESCYT (Ecuador); MoER, ERC IUT, and ERDF (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); NKFIA (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MBIE (New Zealand); PAEC (Pakistan); MSHE and NSC (Poland); FCT (Portugal); JINR (Dubna); MON, RosAtom, RAS, RFBR and RAEP (Russia); MESTD (Serbia); SEIDI, CPAN, PCTI and FEDER (Spain); Swiss Funding Agencies (Switzerland); MST (Taipei); ThEPCenter, IPST, STAR, and NSTDA (Thailand); TUBITAK and TAEK (Turkey); NASU and SFFR (Ukraine); STFC (United Kingdom); DOE and NSF (U.S.A.). Individuals have received support from the Marie-Curie program and the European Research Council and Horizon 2020 Grant, contract No. 675440 (European Union); the Leventis Foundation; the A. P. Sloan Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science Policy O ce; the Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the F.R.S.-FNRS and FWO (Belgium) under HJEP07(218)5 the \Excellence of Science - EOS" - be.h project n. 30820817; the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Lendulet (\Momentum") Program and the Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences, the New National Excellence Program UNKP, the NKFIA research grants 123842, 123959, 124845, 124850 and 125105 (Hungary); the Council of Science and Industrial Research, India; the HOMING PLUS program of the Foundation for Polish Science, co nanced from European Union, Regional Development Fund, the Mobility Plus program of the Ministry of Science and Higher Education, the National Science Center (Poland), contracts Harmonia 2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543, 2014/15/B/ST2/03998, and 2015/19/B/ST2/02861, Sonata-bis 2012/07/E/ST2/01406; the National Priorities Research Program by Qatar National Research Fund; the Programa Estatal de Fomento de la Investigacion Cient ca y Tecnica de Excelencia Mar a de Maeztu, grant MDM-2015-0509 and the Programa Severo Ochoa del Principado de Asturias; the Thalis and Aristeia programs co nanced by EU-ESF and the Greek NSRF; the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University and the Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand); the Welch Foundation, contract C-1845; and the Weston Havens Foundation (U.S.A.). 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Stahl15 Deutsches Elektronen-Synchrotron, Hamburg, Germany M. Aldaya Martin, T. Arndt, C. Asawatangtrakuldee, K. Beernaert, O. Behnke, U. Behrens, A. Bermudez Mart nez, A.A. Bin Anuar, K. Borras16, V. Botta, A. Campbell, P. Connor, C. Contreras-Campana, F. Costanza, C. Diez Pardos, G. Eckerlin, D. Eckstein, T. Eichhorn, E. Eren, E. Gallo17, J. Garay Garcia, A. Geiser, J.M. Grados Luyando, A. Grohsjean, P. Gunnellini, M. Gutho , A. Harb, J. Hauk, M. Hempel18, H. Jung, M. Kasemann, J. Keaveney, C. Kleinwort, I. Korol, D. Krucker, W. Lange, A. Lelek, T. Lenz, J. Leonard, K. Lipka, W. Lohmann18, R. Mankel, I.-A. Melzer-Pellmann, A.B. Meyer, M. Missiroli, G. Mittag, J. Mnich, A. Mussgiller, E. Ntomari, D. Pitzl, A. Raspereza, M. Savitskyi, P. Saxena, R. Shevchenko, N. Stefaniuk, G.P. Van Onsem, R. Walsh, Y. Wen, K. Wichmann, C. Wissing, O. Zenaiev University of Hamburg, Hamburg, Germany R. Aggleton, S. Bein, V. Blobel, M. Centis Vignali, T. Dreyer, E. Garutti, D. Gonzalez, J. Haller, A. Hinzmann, M. Ho mann, A. Karavdina, R. Klanner, R. Kogler, N. Kovalchuk, S. Kurz, T. Lapsien, D. Marconi, M. Meyer, M. Niedziela, D. Nowatschin, F. Pantaleo15, T. Pei er, A. Perieanu, C. Scharf, P. Schleper, A. Schmidt, S. Schumann, J. Schwandt, J. Sonneveld, H. Stadie, G. Steinbruck, F.M. Stober, M. Stover, H. Tholen, D. Troendle, E. Usai, A. Vanhoefer, B. Vormwald Institut fur Experimentelle Teilchenphysik, Karlsruhe, Germany M. Akbiyik, C. Barth, M. Baselga, S. Baur, E. Butz, R. Caspart, T. Chwalek, F. Colombo, W. De Boer, A. Dierlamm, N. Faltermann, B. Freund, R. Friese, M. Gi els, M.A. Harrendorf, F. Hartmann15, S.M. Heindl, U. Husemann, F. Kassel15, S. Kudella, H. Mildner, M.U. Mozer, Th. Muller, M. Plagge, G. Quast, K. Rabbertz, M. Schroder, I. Shvetsov, G. Sieber, H.J. Simonis, R. Ulrich, S. Wayand, M. Weber, T. Weiler, S. Williamson, C. Wohrmann, R. Wolf Paraskevi, Greece Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia G. Anagnostou, G. Daskalakis, T. Geralis, A. Kyriakis, D. Loukas, I. Topsis-Giotis National and Kapodistrian University of Athens, Athens, Greece G. Karathanasis, S. Kesisoglou, A. Panagiotou, N. Saoulidou National Technical University of Athens, Athens, Greece K. Kousouris University of Ioannina, Ioannina, Greece I. Evangelou, C. Foudas, P. Gianneios, P. Katsoulis, P. Kokkas, S. Mallios, N. Manthos, I. Papadopoulos, E. Paradas, J. Strologas, F.A. Triantis, D. Tsitsonis MTA-ELTE Lendulet CMS Particle and Nuclear Physics Group, Eotvos Lorand University, Budapest, Hungary M. Csanad, N. Filipovic, G. Pasztor, O. Suranyi, G.I. Veres19 Wigner Research Centre for Physics, Budapest, Hungary G. Bencze, C. Hajdu, D. Horvath20, A. Hunyadi, F. Sikler, V. Veszpremi, G. Vesztergombi19 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, Debrecen, Hungary M. Bartok19, P. Raics, Z.L. Trocsanyi, B. Ujvari Indian Institute of Science (IISc), Bangalore, India S. Choudhury, J.R. Komaragiri National Institute of Science Education and Research, Bhubaneswar, India S. Bahinipati22, P. Mal, K. Mandal, A. Nayak23, D.K. Sahoo22, N. Sahoo, S.K. Swain Panjab University, Chandigarh, India S. Bansal, S.B. Beri, V. Bhatnagar, R. Chawla, N. Dhingra, A. Kaur, M. Kaur, S. Kaur, R. Kumar, P. Kumari, A. Mehta, J.B. Singh, G. Walia University of Delhi, Delhi, India Ashok Kumar, Aashaq Shah, A. Bhardwaj, S. Chauhan, B.C. Choudhary, R.B. Garg, S. Keshri, A. Kumar, S. Malhotra, M. Naimuddin, K. Ranjan, R. Sharma Saha Institute of Nuclear Physics, HBNI, Kolkata, India R. Bhardwaj, R. Bhattacharya, S. Bhattacharya, U. Bhawandeep, S. Dey, S. Dutt, S. Dutta, S. Ghosh, N. Majumdar, A. Modak, K. Mondal, S. Mukhopadhyay, S. Nandan, A. Purohit, A. Roy, S. Roy Chowdhury, S. Sarkar, M. Sharan, S. Thakur Indian Institute of Technology Madras, Madras, India P.K. Behera Bhabha Atomic Research Centre, Mumbai, India R. Chudasama, D. Dutta, V. Jha, V. Kumar, A.K. Mohanty15, P.K. Netrakanti, L.M. Pant, HJEP07(218)5 P. Shukla, A. Topkar Tata Institute of Fundamental Research-A, Mumbai, India T. Aziz, S. Dugad, B. Mahakud, S. Mitra, G.B. Mohanty, N. Sur, B. Sutar Tata Institute of Fundamental Research-B, Mumbai, India S. Banerjee, S. Bhattacharya, S. Chatterjee, P. Das, 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, S. Pandey, A. Rane, S. Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran S. Chenarani26, E. Eskandari Tadavani, S.M. Etesami26, M. Khakzad, M. Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi27, F. Rezaei Hosseinabadi, B. Safarzadeh28, 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, A. Colaleoa, D. Creanzaa;c, L. Cristellaa;b, N. De Filippisa;c, M. De Palmaa;b, F. Erricoa;b, L. Fiorea, G. Iasellia;c, S. Lezkia;b, G. Maggia;c, M. Maggia, G. Minielloa;b, S. Mya;b, S. Nuzzoa;b, A. Pompilia;b, G. Pugliesea;c, R. Radognaa, A. Ranieria, G. Selvaggia;b, A. Sharmaa, L. Silvestrisa;15, R. Vendittia, P. Verwilligena INFN Sezione di Bologna a, Universita di Bologna b, Bologna, Italy G. Abbiendia, C. Battilanaa;b, D. Bonacorsia;b, L. Borgonovia;b, S. Braibant-Giacomellia;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 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, C. Tuvea;b INFN Sezione di Firenze a, Universita di Firenze b, Firenze, Italy G. Barbaglia, K. Chatterjeea;b, V. Ciullia;b, C. Civininia, R. D'Alessandroa;b, E. Focardia;b, P. Lenzia;b, M. Meschinia, S. Paolettia, L. Russoa;29, G. Sguazzonia, D. Stroma, L. Viliania 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, F. Raveraa;b, E. Robuttia, S. Tosia;b INFN Sezione di Milano-Bicocca a, Universita di Milano-Bicocca b, Milano, Italy A. Benagliaa, A. Beschib, L. Brianzaa;b, F. Brivioa;b, V. Cirioloa;b;15, M.E. Dinardoa;b, S. Fiorendia;b, S. Gennaia, A. Ghezzia;b, P. Govonia;b, M. Malbertia;b, S. Malvezzia, R.A. Manzonia;b, D. Menascea, L. Moronia, M. Paganonia;b, K. Pauwelsa;b, D. Pedrinia, S. Pigazzinia;b;30, S. Ragazzia;b, T. Tabarelli de Fatisa;b INFN Sezione di Napoli a, Universita di Napoli 'Federico II' b, Napoli, Italy, Universita della Basilicata c, Potenza, Italy, Universita G. Marconi d, Roma, Italy F. Thyssena S. Buontempoa, N. Cavalloa;c, S. Di Guidaa;d;15, F. Fabozzia;c, F. Fiengaa;b, A.O.M. Iorioa;b, W.A. Khana, L. Listaa, S. Meolaa;d;15, P. Paoluccia;15, C. Sciaccaa;b, INFN Sezione di Padova a, Universita di Padova b, Padova, Italy, Universita di Trento c, Trento, Italy P. Azzia, 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, P. Lujan, M. Margonia;b, A.T. Meneguzzoa;b, N. Pozzobona;b, P. Ronchesea;b, R. Rossina;b, F. Simonettoa;b, E. Torassaa, M. Zanettia;b, P. Zottoa;b INFN Sezione di Pavia a, Universita di Pavia b, Pavia, Italy A. Braghieria, A. Magnania, P. Montagnaa;b, S.P. Rattia;b, V. Rea, M. Ressegottia;b, 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, M. Biasinia;b, G.M. Bileia, C. Cecchia;b, D. Ciangottinia;b, L. Fanoa;b, P. Laricciaa;b, R. Leonardia;b, E. Manonia, G. Mantovania;b, V. Mariania;b, M. Menichellia, A. Rossia;b, A. Santocchiaa;b, D. Spigaa INFN Sezione di Pisa a, Universita di Pisa b, Scuola Normale Superiore di Pisa c, Pisa, Italy K. Androsova, P. Azzurria;15, G. Bagliesia, T. Boccalia, L. Borrello, R. Castaldia, M.A. Cioccia;b, R. Dell'Orsoa, G. Fedia, L. Gianninia;c, A. Giassia, M.T. Grippoa;29, F. Ligabuea;c, T. Lomtadzea, E. Mancaa;c, G. Mandorlia;c, A. Messineoa;b, F. Pallaa, A. Rizzia;b, A. Savoy-Navarroa;31, P. Spagnoloa, R. Tenchinia, G. Tonellia;b, A. Venturia, P.G. Verdinia INFN Sezione di Roma a, Sapienza Universita di Roma b, Rome, Italy L. Baronea;b, F. Cavallaria, M. Cipriania;b, N. Dacia, Del Rea;b, E. Di Marcoa;b, M. Diemoza, S. Gellia;b, E. Longoa;b, F. Margarolia;b, B. Marzocchia;b, P. Meridiania, G. Organtinia;b, R. Paramattia;b, 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, 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, B. Kiania;b, C. Mariottia, S. Masellia, 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, 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 D.H. Kim, G.N. Kim, M.S. Kim, J. Lee, S. Lee, S.W. Lee, C.S. Moon, Y.D. Oh, S. Sekmen, D.C. Son, Y.C. Yang Kwangju, Korea H. Kim, D.H. Moon, G. Oh Chonnam National University, Institute for Universe and Elementary Particles, Hanyang University, Seoul, Korea J.A. Brochero Cifuentes, J. Goh, T.J. Kim Korea University, Seoul, Korea J. Lim, S.K. Park, Y. Roh Seoul National University, Seoul, Korea S.h. Seo, U.K. Yang, H.D. Yoo, G.B. Yu University of Seoul, Seoul, Korea H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park Sungkyunkwan University, Suwon, Korea Y. Choi, C. Hwang, J. Lee, I. Yu Vilnius University, Vilnius, Lithuania V. Dudenas, A. Juodagalvis, J. Vaitkus S. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, Y. Jo, Y. Kim, K. Lee, K.S. Lee, S. Lee, J. Almond, J. Kim, J.S. Kim, H. Lee, K. Lee, K. Nam, S.B. Oh, B.C. Radburn-Smith, National Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Malaysia M.N. Yusli, Z. Zolkapli I. Ahmed, Z.A. Ibrahim, M.A.B. Md Ali32, F. Mohamad Idris33, W.A.T. Wan Abdullah, Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico Reyes-Almanza, R, Ramirez-Sanchez, G., Duran-Osuna, M. C., H. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-De La Cruz34, Rabadan-Trejo, R. I., R. Lopez-Fernandez, 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 J. Eysermans, I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad Autonoma de San Luis Potos , San Luis Potos , Mexico A. Morelos Pineda D. Krofcheck University of Auckland, Auckland, New Zealand University of Canterbury, Christchurch, New Zealand S. Bheesette, P.H. Butler HJEP07(218)5 M. Waqas M. Szleper, P. Zalewski Warsaw, Poland National Centre for Physics, Quaid-I-Azam University, Islamabad, Pakistan A. Ahmad, M. Ahmad, Q. Hassan, H.R. Hoorani, A. Saddique, M.A. Shah, M. Shoaib, National Centre for Nuclear Research, Swierk, Poland H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Gorski, M. Kazana, K. Nawrocki, 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, A. Pyskir, M. Walczak Laboratorio de Instrumentac~ao e F sica Experimental de Part culas, Lisboa, Portugal P. Bargassa, C. Beir~ao Da Cruz E Silva, A. Di Francesco, P. Faccioli, B. Galinhas, M. Gallinaro, J. Hollar, N. Leonardo, L. Lloret Iglesias, M.V. Nemallapudi, J. Seixas, G. Strong, O. Toldaiev, D. Vadruccio, J. Varela Joint Institute for Nuclear Research, Dubna, Russia S. Afanasiev, V. Alexakhin, P. Bunin, M. Gavrilenko, A. Golunov, I. Golutvin, N. Gorbounov, I. Gorbunov, V. Karjavin, A. Lanev, A. Malakhov, V. Matveev36;37, P. Moisenz, V. Palichik, V. Perelygin, M. Savina, S. Shmatov, V. Smirnov, A. Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia Y. Ivanov, V. Kim38, E. Kuznetsova39, P. Levchenko, V. Murzin, V. Oreshkin, I. Smirnov, D. Sosnov, V. Sulimov, L. Uvarov, S. Vavilov, 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, A. Stepennov, V. Stolin, M. Toms, E. Vlasov, A. Zhokin HJEP07(218)5 Moscow Institute of Physics and Technology, Moscow, Russia T. Aushev, A. Bylinkin37 National Research Nuclear University 'Moscow Engineering Physics Institute' (MEPhI), Moscow, Russia R. Chistov40, M. Danilov40, P. Parygin, D. Philippov, S. Polikarpov, E. Tarkovskii P.N. Lebedev Physical Institute, Moscow, Russia V. Andreev, M. Azarkin37, I. Dremin37, M. Kirakosyan37, S.V. Rusakov, A. Terkulov Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia A. Snigirev A. Baskakov, A. Belyaev, E. Boos, V. Bunichev, M. Dubinin41, L. Dudko, A. Ershov, V. Klyukhin, O. Kodolova, I. Lokhtin, I. Miagkov, S. Obraztsov, M. Per lov, V. Savrin, Novosibirsk State University (NSU), Novosibirsk, Russia V. Blinov42, D. Shtol42, Y. Skovpen42 State Research Center of Russian Federation, Institute for High Energy Physics of NRC &quot;Kurchatov Institute&quot;, Protvino, Russia I. Azhgirey, I. Bayshev, S. Bitioukov, D. Elumakhov, A. Godizov, V. Kachanov, A. Kalinin, D. Konstantinov, P. Mandrik, V. Petrov, R. Ryutin, A. Sobol, S. Troshin, N. Tyurin, A. Uzunian, A. Volkov University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia P. Adzic43, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic Centro de Investigaciones Energeticas Medioambientales y Tecnologicas (CIEMAT), Madrid, Spain J. Alcaraz Maestre, I. Bachiller, M. Barrio Luna, M. Cerrada, N. Colino, B. De La Cruz, A. Delgado Peris, C. Fernandez Bedoya, J.P. Fernandez Ramos, J. Flix, M.C. Fouz, O. Gonzalez Lopez, S. Goy Lopez, J.M. Hernandez, M.I. Josa, D. Moran, A. Perez-Calero Yzquierdo, J. Puerta Pelayo, I. Redondo, L. Romero, M.S. Soares, A. Triossi, A. Alvarez Fernandez Universidad Autonoma de Madrid, Madrid, Spain C. Albajar, J.F. de Troconiz Universidad de Oviedo, Oviedo, Spain J. Cuevas, C. Erice, J. Fernandez Menendez, I. Gonzalez Caballero, J.R. Gonzalez Fernandez, E. Palencia Cortezon, S. Sanchez Cruz, P. Vischia, J.M. Vizan Garcia Instituto de F sica de Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, Spain I.J. Cabrillo, A. Calderon, B. Chazin Quero, E. Curras, J. Duarte Campderros, M. Fernandez, J. Garcia-Ferrero, G. Gomez, A. Lopez Virto, J. Marco, C. Martinez Rivero, P. Martinez Ruiz del Arbol, F. Matorras, J. Piedra Gomez, T. Rodrigo, A. Ruiz-Jimeno, L. Scodellaro, N. Trevisani, I. Vila, R. Vilar Cortabitarte CERN, European Organization for Nuclear Research, Geneva, Switzerland D. Abbaneo, B. Akgun, E. Au ray, P. Baillon, A.H. Ball, D. Barney, J. Bendavid, M. Bianco, A. Bocci, C. Botta, T. Camporesi, R. Castello, M. Cepeda, G. Cerminara, E. Chapon, Y. Chen, D. d'Enterria, A. Dabrowski, V. Daponte, A. David, M. De Gruttola, A. De Roeck, N. Deelen, M. Dobson, T. du Pree, M. Dunser, N. Dupont, A. Elliott-Peisert, P. Everaerts, F. Fallavollita, G. Franzoni, J. Fulcher, W. Funk, D. Gigi, A. Gilbert, K. Gill, F. Glege, D. Gulhan, P. Harris, J. Hegeman, V. Innocente, A. Jafari, P. Janot, O. Karacheban18, J. Kieseler, V. Knunz, A. Kornmayer, M.J. Kortelainen, 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. Milenovic44, F. Moortgat, M. Mulders, H. Neugebauer, J. Ngadiuba, S. Orfanelli, L. Orsini, L. Pape, E. Perez, M. Peruzzi, A. Petrilli, G. Petrucciani, A. Pfei er, M. Pierini, D. Rabady, A. Racz, T. Reis, G. Rolandi45, M. Rovere, H. Sakulin, C. Schafer, C. Schwick, M. Seidel, M. Selvaggi, A. Sharma, P. Silva, P. Sphicas46, A. Stakia, J. Steggemann, M. Stoye, M. Tosi, D. Treille, A. Tsirou, V. Veckalns47, M. Verweij, W.D. Zeuner Paul Scherrer Institut, Villigen, Switzerland W. Bertly, L. Caminada48, K. Deiters, W. Erdmann, R. Horisberger, Q. Ingram, H.C. Kaestli, D. Kotlinski, U. Langenegger, T. Rohe, S.A. Wiederkehr ETH Zurich - Institute for Particle Physics and Astrophysics (IPA), Zurich, Switzerland M. Backhaus, L. Bani, P. Berger, L. Bianchini, B. Casal, G. Dissertori, M. Dittmar, M. Donega, C. Dorfer, C. Grab, C. Heidegger, D. Hits, J. Hoss, G. Kasieczka, T. Klijnsma, W. Lustermann, B. Mangano, M. Marionneau, 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. Reichmann, D.A. Sanz Becerra, M. Schonenberger, L. Shchutska, V.R. Tavolaro, K. Theo latos, M.L. Vesterbacka Olsson, R. Wallny, D.H. Zhu Universitat Zurich, Zurich, Switzerland T.K. Aarrestad, C. Amsler49, M.F. Canelli, A. De Cosa, R. Del Burgo, S. Donato, C. Galloni, T. Hreus, B. Kilminster, D. Pinna, G. Rauco, P. Robmann, D. Salerno, K. Schweiger, C. Seitz, Y. Takahashi, A. Zucchetta National Central University, Chung-Li, Taiwan V. Candelise, Y.H. Chang, K.y. Cheng, T.H. Doan, Sh. Jain, R. Khurana, C.M. Kuo, W. Lin, A. Pozdnyakov, S.S. Yu National Taiwan University (NTU), Taipei, Taiwan Arun Kumar, P. Chang, Y. Chao, K.F. Chen, P.H. Chen, F. Fiori, W.-S. Hou, Y. Hsiung, Y.F. Liu, R.-S. Lu, E. Paganis, A. Psallidas, A. Steen, J.f. Tsai Chulalongkorn University, Faculty of Science, Department of Physics, Bangkok, B. Asavapibhop, K. Kovitanggoon, G. Singh, N. Srimanobhas Cukurova University, Physics Department, Science and Art Faculty, Adana, M.N. Bakirci50, A. Bat, F. Boran, S. Cerci51, S. Damarseckin, Z.S. Demiroglu, C. Dozen, E. Eskut, S. Girgis, G. Gokbulut, Y. Guler, I. Hos52, E.E. Kangal53, O. Kara, U. Kiminsu, M. Oglakci, G. Onengut54, K. Ozdemir55, S. Ozturk50, A. Polatoz, U.G. Tok, S. Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East Technical University, Physics Department, Ankara, Turkey G. Karapinar56, K. Ocalan57, M. Yalvac, M. Zeyrek Bogazici University, Istanbul, Turkey E. Gulmez, M. Kaya58, O. Kaya59, S. Tekten, E.A. Yetkin60 Istanbul Technical University, Istanbul, Turkey M.N. Agaras, S. Atay, A. Cakir, K. Cankocak, Y. Komurcu Institute for Scintillation Materials of National Academy of Science of Ukraine, Kharkov, Ukraine B. Grynyov Kharkov, Ukraine L. Levchuk National Scienti c Center, Kharkov Institute of Physics and Technology, University of Bristol, Bristol, United Kingdom F. Ball, L. Beck, J.J. Brooke, D. Burns, E. Clement, D. Cussans, O. Davignon, H. Flacher, J. Goldstein, G.P. Heath, H.F. Heath, L. Kreczko, D.M. Newbold61, S. Paramesvaran, T. Sakuma, S. Seif El Nasr-storey, D. Smith, V.J. Smith Rutherford Appleton Laboratory, Didcot, United Kingdom K.W. Bell, A. Belyaev62, C. Brew, R.M. Brown, L. Calligaris, D. Cieri, D.J.A. Cockerill, J.A. Coughlan, K. Harder, S. Harper, J. Linacre, E. Olaiya, D. Petyt, C.H. ShepherdThemistocleous, A. Thea, I.R. Tomalin, T. Williams, W.J. Womersley Imperial College, London, United Kingdom G. Auzinger, R. Bainbridge, P. Bloch, J. Borg, S. Breeze, O. Buchmuller, A. Bundock, S. Casasso, M. Citron, D. Colling, L. Corpe, P. Dauncey, G. Davies, A. De Wit, M. Della Negra, R. Di Maria, A. Elwood, Y. Haddad, G. Hall, G. Iles, T. James, R. Lane, C. Laner, L. Lyons, A.-M. Magnan, S. Malik, L. Mastrolorenzo, T. Matsushita, J. Nash, A. Nikitenko6, V. Palladino, M. Pesaresi, D.M. Raymond, A. Richards, A. Rose, E. Scott, C. Seez, A. Shtipliyski, S. Summers, A. Tapper, K. Uchida, M. Vazquez Acosta63, T. Virdee15, N. Wardle, D. Winterbottom, J. Wright, S.C. Zenz Brunel University, Uxbridge, United Kingdom J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, I.D. Reid, L. Teodorescu, S. Zahid Baylor University, Waco, U.S.A. A. Borzou, K. Call, J. Dittmann, K. Hatakeyama, H. Liu, N. Pastika, C. Smith Catholic University of America, Washington DC, U.S.A. R. Bartek, A. Dominguez The University of Alabama, Tuscaloosa, U.S.A. A. Buccilli, S.I. Cooper, C. Henderson, P. Rumerio, C. West Boston University, Boston, U.S.A. D. Arcaro, A. Avetisyan, T. Bose, D. Gastler, D. Rankin, C. Richardson, J. Rohlf, L. Sulak, D. Zou Brown University, Providence, U.S.A. G. Benelli, D. Cutts, M. Hadley, J. Hakala, U. Heintz, J.M. Hogan, K.H.M. Kwok, E. Laird, G. Landsberg, J. Lee, Z. Mao, M. Narain, J. Pazzini, S. Piperov, S. Sagir, R. Syarif, D. Yu University of California, Davis, Davis, U.S.A. R. Band, C. Brainerd, R. Breedon, D. Burns, M. Calderon De La Barca Sanchez, M. Chertok, J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk, W. Ko, R. Lander, C. Mclean, M. Mulhearn, D. Pellett, J. Pilot, S. Shalhout, M. Shi, J. Smith, D. Stolp, K. Tos, M. Tripathi, Z. Wang University of California, Los Angeles, U.S.A. M. Bachtis, C. Bravo, R. Cousins, A. Dasgupta, A. Florent, J. Hauser, M. Ignatenko, N. Mccoll, S. Regnard, D. Saltzberg, C. Schnaible, V. Valuev University of California, Riverside, Riverside, U.S.A. E. Bouvier, K. Burt, R. Clare, J. Ellison, J.W. Gary, S.M.A. Ghiasi Shirazi, G. Hanson, J. Heilman, G. Karapostoli, E. Kennedy, F. Lacroix, O.R. Long, M. Olmedo Negrete, M.I. Paneva, W. Si, L. Wang, H. Wei, S. Wimpenny, B. R. Yates University of California, San Diego, La Jolla, U.S.A. J.G. Branson, S. Cittolin, M. Derdzinski, R. Gerosa, D. Gilbert, B. Hashemi, A. Holzner, D. Klein, G. Kole, V. Krutelyov, J. Letts, M. Masciovecchio, D. Olivito, S. Padhi, M. Pieri, M. Sani, V. Sharma, S. Simon, M. Tadel, A. Vartak, S. Wasserbaech64, J. Wood, F. Wurthwein, A. Yagil, G. Zevi Della Porta bara, U.S.A. I. Suarez, J. Yoo N. Amin, R. Bhandari, J. Bradmiller-Feld, C. Campagnari, A. Dishaw, V. Dutta, M. Franco Sevilla, L. Gouskos, R. Heller, J. Incandela, A. Ovcharova, H. Qu, J. Richman, D. Stuart, California Institute of Technology, Pasadena, U.S.A. D. Anderson, A. Bornheim, J. Bunn, J.M. Lawhorn, H.B. Newman, T. Q. Nguyen, C. Pena, M. Spiropulu, J.R. Vlimant, R. Wilkinson, S. Xie, Z. Zhang, R.Y. Zhu Carnegie Mellon University, Pittsburgh, U.S.A. M.B. Andrews, T. Ferguson, T. Mudholkar, M. Paulini, J. Russ, M. Sun, H. Vogel, I. Vorobiev, M. Weinberg University of Colorado Boulder, Boulder, U.S.A. J.P. Cumalat, W.T. Ford, F. Jensen, A. Johnson, M. Krohn, S. Leontsinis, T. Mulholland, K. Stenson, K.A. Ulmer, S.R. Wagner Cornell University, Ithaca, U.S.A. J. Alexander, J. Chaves, J. Chu, S. Dittmer, K. Mcdermott, N. Mirman, J.R. Patterson, D. Quach, A. Rinkevicius, A. Ryd, L. Skinnari, L. So , S.M. Tan, Z. Tao, J. Thom, J. Tucker, P. Wittich, M. Zientek Fermi National Accelerator Laboratory, Batavia, U.S.A. S. Abdullin, M. Albrow, M. Alyari, G. Apollinari, A. Apresyan, A. Apyan, S. Banerjee, L.A.T. Bauerdick, A. Beretvas, J. Berryhill, P.C. Bhat, G. Bollay, K. Burkett, J.N. Butler, A. Canepa, G.B. Cerati, H.W.K. Cheung, F. Chlebana, M. Cremonesi, J. Duarte, V.D. Elvira, J. Freeman, Z. Gecse, E. Gottschalk, L. Gray, D. Green, S. Grunendahl, O. Gutsche, J. Hanlon, R.M. Harris, S. Hasegawa, J. Hirschauer, Z. Hu, B. Jayatilaka, S. Jindariani, M. Johnson, U. Joshi, B. Klima, B. Kreis, S. Lammel, D. Lincoln, R. Lipton, M. Liu, T. Liu, R. Lopes De Sa, J. Lykken, K. Maeshima, N. Magini, J.M. Marra no, D. Mason, P. McBride, P. Merkel, S. Mrenna, S. Nahn, V. O'Dell, K. Pedro, O. Prokofyev, G. Rakness, L. Ristori, B. Schneider, E. Sexton-Kennedy, A. Soha, W.J. Spalding, L. Spiegel, S. Stoynev, J. Strait, N. Strobbe, L. Taylor, S. Tkaczyk, N.V. Tran, L. Uplegger, E.W. Vaandering, C. Vernieri, M. Verzocchi, R. Vidal, M. Wang, H.A. Weber, A. Whitbeck, W. Wu University of Florida, Gainesville, U.S.A. D. Acosta, P. Avery, P. Bortignon, D. Bourilkov, A. Brinkerho , A. Carnes, M. Carver, D. Curry, R.D. Field, I.K. Furic, S.V. Gleyzer, B.M. Joshi, J. Konigsberg, A. Korytov, K. Kotov, P. Ma, K. Matchev, H. Mei, G. Mitselmakher, K. Shi, D. Sperka, N. Terentyev, L. Thomas, J. Wang, S. Wang, J. Yelton Florida International University, Miami, U.S.A. Y.R. Joshi, S. Linn, P. Markowitz, J.L. Rodriguez Florida State University, Tallahassee, U.S.A. A. Ackert, T. Adams, A. Askew, S. Hagopian, V. Hagopian, K.F. Johnson, T. Kolberg, G. Martinez, T. Perry, H. Prosper, A. Saha, A. Santra, V. Sharma, R. Yohay Florida Institute of Technology, Melbourne, U.S.A. M.M. Baarmand, V. Bhopatkar, S. Colafranceschi, M. Hohlmann, D. Noonan, T. Roy, F. Yumiceva University of Illinois at Chicago (UIC), Chicago, U.S.A. M.R. Adams, L. Apanasevich, D. Berry, R.R. Betts, R. Cavanaugh, X. Chen, O. Evdokimov, C.E. Gerber, D.A. Hangal, D.J. Hofman, K. Jung, J. Kamin, I.D. Sandoval Gonzalez, M.B. Tonjes, H. Trauger, N. Varelas, H. Wang, Z. Wu, J. Zhang The University of Iowa, Iowa City, U.S.A. B. Bilki65, W. Clarida, K. Dilsiz66, S. Durgut, R.P. Gandrajula, M. Haytmyradov, V. Khristenko, J.-P. Merlo, H. Mermerkaya67, A. Mestvirishvili, A. Moeller, J. Nachtman, H. Ogul68, Y. Onel, F. Ozok69, A. Penzo, C. Snyder, E. Tiras, J. Wetzel, K. Yi Johns Hopkins University, Baltimore, U.S.A. B. Blumenfeld, A. Cocoros, N. Eminizer, D. Fehling, L. Feng, A.V. Gritsan, P. Maksimovic, J. Roskes, U. Sarica, M. Swartz, M. Xiao, C. You The University of Kansas, Lawrence, U.S.A. A. Al-bataineh, P. Baringer, A. Bean, S. Boren, J. Bowen, J. Castle, S. Khalil, A. Kropivnitskaya, D. Majumder, W. Mcbrayer, M. Murray, C. Rogan, C. Royon, S. Sanders, E. Schmitz, 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 Lawrence Livermore National Laboratory, Livermore, U.S.A. F. Rebassoo, D. Wright University of Maryland, College Park, U.S.A. A. Baden, O. Baron, A. Belloni, S.C. Eno, Y. Feng, C. Ferraioli, N.J. Hadley, S. Jabeen, G.Y. Jeng, R.G. Kellogg, J. Kunkle, A.C. Mignerey, F. Ricci-Tam, Y.H. Shin, A. Skuja, S.C. Tonwar Massachusetts Institute of Technology, Cambridge, U.S.A. D. Abercrombie, B. Allen, V. Azzolini, R. Barbieri, A. Baty, G. Bauer, R. Bi, S. Brandt, W. Busza, I.A. Cali, M. D'Alfonso, Z. Demiragli, G. Gomez Ceballos, M. Goncharov, D. Hsu, M. Hu, Y. Iiyama, G.M. Innocenti, M. Klute, D. Kovalskyi, Y.-J. Lee, A. Levin, P.D. Luckey, B. Maier, 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, D. Velicanu, J. Wang, T.W. Wang, B. Wyslouch University of Minnesota, Minneapolis, U.S.A. A.C. Benvenuti, R.M. Chatterjee, A. Evans, P. Hansen, J. Hiltbrand, S. Kalafut, Y. Kubota, Z. Lesko, J. Mans, S. Nourbakhsh, N. Ruckstuhl, R. Rusack, J. Turkewitz, M.A. Wadud University of Mississippi, Oxford, U.S.A. J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, U.S.A. E. Avdeeva, K. Bloom, D.R. Claes, C. Fangmeier, F. Golf, R. Gonzalez Suarez, R. Kamalieddin, I. Kravchenko, J. Monroy, J.E. Siado, G.R. Snow, B. Stieger State University of New York at Bu alo, Bu alo, U.S.A. J. Dolen, A. Godshalk, C. Harrington, I. Iashvili, D. Nguyen, A. Parker, S. Rappoccio, B. Roozbahani Northeastern University, Boston, U.S.A. G. Alverson, E. Barberis, C. Freer, A. Hortiangtham, A. Massironi, D.M. Morse, T. Orimoto, R. Teixeira De Lima, T. Wamorkar, B. Wang, A. Wisecarver, D. Wood Northwestern University, Evanston, U.S.A. S. Bhattacharya, O. Charaf, K.A. Hahn, N. Mucia, N. Odell, M.H. Schmitt, K. Sung, M. Trovato, M. Velasco University of Notre Dame, Notre Dame, U.S.A. R. Bucci, N. Dev, M. Hildreth, K. Hurtado Anampa, C. Jessop, D.J. Karmgard, N. Kellams, K. Lannon, W. Li, N. Loukas, N. Marinelli, F. Meng, C. Mueller, Y. Musienko36, M. Planer, A. Reinsvold, R. Ruchti, P. Siddireddy, G. Smith, S. Taroni, M. Wayne, A. Wightman, 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, W. Ji, T.Y. Ling, B. Liu, W. Luo, B.L. Winer, H.W. Wulsin Princeton University, Princeton, U.S.A. S. Cooperstein, O. Driga, P. Elmer, J. Hardenbrook, P. Hebda, S. Higginbotham, A. Kalogeropoulos, D. Lange, J. Luo, D. Marlow, K. Mei, I. Ojalvo, J. Olsen, C. Palmer, P. Piroue, D. Stickland, C. Tully University of Puerto Rico, Mayaguez, U.S.A. S. Malik, S. Norberg Purdue University, West Lafayette, U.S.A. A. Barker, V.E. Barnes, S. Das, S. Folgueras, L. Gutay, M. Jones, A.W. Jung, A. Khatiwada, D.H. Miller, N. Neumeister, C.C. Peng, H. Qiu, J.F. Schulte, J. Sun, F. Wang, R. Xiao, W. Xie Purdue University Northwest, Hammond, U.S.A. T. Cheng, N. Parashar, J. Stupak Rice University, Houston, U.S.A. Z. Chen, K.M. Ecklund, S. Freed, F.J.M. Geurts, M. Guilbaud, M. Kilpatrick, W. Li, B. Michlin, B.P. Padley, J. Roberts, J. Rorie, W. Shi, Z. Tu, J. Zabel, A. Zhang University of Rochester, Rochester, U.S.A. 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 The Rockefeller University, New York, U.S.A. R. Ciesielski, K. Goulianos, C. Mesropian Rutgers, The State University of New Jersey, Piscataway, U.S.A. A. Agapitos, J.P. Chou, Y. Gershtein, T.A. Gomez Espinosa, E. Halkiadakis, M. Heindl, E. Hughes, S. Kaplan, R. Kunnawalkam Elayavalli, S. Kyriacou, A. Lath, R. Montalvo, K. Nash, M. Osherson, H. Saka, S. Salur, S. Schnetzer, D. She eld, S. Somalwar, R. Stone, S. Thomas, P. Thomassen, M. Walker University of Tennessee, Knoxville, U.S.A. A.G. Delannoy, J. Heideman, G. Riley, K. Rose, S. Spanier, K. Thapa Texas A&M University, College Station, U.S.A. O. Bouhali70, A. Castaneda Hernandez70, A. Celik, M. Dalchenko, M. De Mattia, A. Delgado, S. Dildick, R. Eusebi, J. Gilmore, T. Huang, T. Kamon71, R. Mueller, Y. Pakhotin, R. Patel, A. Perlo , L. Pernie, D. Rathjens, A. Safonov, A. Tatarinov Texas Tech University, Lubbock, U.S.A. N. Akchurin, J. Damgov, F. De Guio, P.R. Dudero, J. Faulkner, E. Gurpinar, S. Kunori, K. Lamichhane, S.W. Lee, T. Libeiro, T. Mengke, S. Muthumuni, T. Peltola, S. Undleeb, I. Volobouev, Z. Wang Vanderbilt University, Nashville, U.S.A. P. Sheldon, S. Tuo, J. Velkovska, Q. Xu University of Virginia, Charlottesville, U.S.A. S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, K. Padeken, M.W. Arenton, P. Barria, B. Cox, R. Hirosky, M. Joyce, A. Ledovskoy, H. Li, C. Neu, T. Sinthuprasith, Y. Wang, E. Wolfe, F. Xia Wayne State University, Detroit, U.S.A. R. Harr, P.E. Karchin, N. Poudyal, J. Sturdy, P. Thapa, S. Zaleski University of Wisconsin - Madison, Madison, WI, U.S.A. M. Brodski, J. Buchanan, C. Caillol, D. Carlsmith, S. Dasu, L. Dodd, S. Duric, B. Gomber, M. Grothe, M. Herndon, A. Herve, U. Hussain, P. Klabbers, A. Lanaro, A. Levine, K. Long, R. Loveless, V. Rekovic, T. Ruggles, A. Savin, N. Smith, W.H. Smith, D. Taylor, N. Woods y: Deceased 1: Also at Vienna University of Technology, Vienna, Austria 3: Also at Universidade Estadual de Campinas, Campinas, Brazil 4: Also at Federal University of Rio Grande do Sul, Porto Alegre, Brazil 5: Also at Universite Libre de Bruxelles, Bruxelles, Belgium 6: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia 7: Also at Joint Institute for Nuclear Research, Dubna, Russia 8: Also at Zewail City of Science and Technology, Zewail, Egypt 9: Also at Fayoum University, El-Fayoum, Egypt 10: Now at British University in Egypt, Cairo, Egypt 11: Now at Helwan University, Cairo, Egypt 12: Also at Department of Physics, King Abdulaziz University, Jeddah, Saudi Arabia 13: Also at Universite de Haute Alsace, Mulhouse, France 14: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia 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 MTA-ELTE Lendulet CMS Particle and Nuclear Physics Group, Eotvos Lorand University, Budapest, Hungary 20: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary 21: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary 22: Also at Indian Institute of Technology Bhubaneswar, Bhubaneswar, 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 Yazd University, Yazd, Iran 28: Also at Plasma Physics Research Center, Science and Research Branch, Islamic Azad University, Tehran, Iran 29: Also at Universita degli Studi di Siena, Siena, Italy 30: Also at INFN Sezione di Milano-Bicocca; Universita di Milano-Bicocca, Milano, Italy 31: Also at Purdue University, West Lafayette, U.S.A. 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 37: Now at National Research Nuclear University 'Moscow 38: 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 University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia 46: Also at National and Kapodistrian University of Athens, Athens, Greece 47: Also at Riga Technical University, Riga, Latvia 48: Also at Universitat Zurich, Zurich, Switzerland 49: Also at Stefan Meyer Institute for Subatomic Physics (SMI), Vienna, Austria 50: Also at Gaziosmanpasa University, Tokat, Turkey 51: Also at Adiyaman University, Adiyaman, Turkey 52: Also at Istanbul Aydin University, Istanbul, Turkey 53: Also at Mersin University, Mersin, Turkey 54: Also at Cag University, Mersin, Turkey 55: Also at Piri Reis University, Istanbul, Turkey 56: Also at Izmir Institute of Technology, Izmir, Turkey 57: Also at Necmettin Erbakan University, Konya, 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 Rutherford Appleton Laboratory, Didcot, United Kingdom 62: Also at School of Physics and Astronomy, University of Southampton, Southampton, United Kingdom 63: Also at Instituto de Astrof sica de Canarias, La Laguna, Spain 64: Also at Utah Valley University, Orem, U.S.A. 65: Also at Beykent University, Istanbul, Turkey 66: Also at Bingol University, Bingol, Turkey 67: Also at Erzincan University, Erzincan, Turkey 68: Also at Sinop University, Sinop, Turkey 69: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey 70: Also at Texas A&M University at Qatar, Doha, Qatar 71: Also at Kyungpook National University, Daegu, Korea [1] K. 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The CMS collaboration, A. M. Sirunyan, A. Tumasyan, W. Adam, F. Ambrogi, E. Asilar, T. Bergauer, J. Brandstetter, E. Brondolin, M. Dragicevic, J. Erö, A. Escalante Del Valle, M. Flechl, M. Friedl, R. Frühwirth, V. M. Ghete, J. Grossmann, J. Hrubec, M. Jeitler, A. König, N. Krammer, I. Krätschmer, D. Liko, T. Madlener, I. Mikulec, E. Pree, N. Rad, H. Rohringer, J. Schieck, R. Schöfbeck, M. Spanring, D. Spitzbart, A. Taurok, W. Waltenberger, J. Wittmann, C.-E. Wulz, M. Zarucki, V. Chekhovsky, V. Mossolov, J. Suarez Gonzalez, E. A. De Wolf, D. Di Croce, X. Janssen, J. Lauwers, M. Van De Klundert, H. Van Haevermaet, P. Van Mechelen, N. Van Remortel, S. Abu Zeid, F. Blekman, J. D’Hondt, I. De Bruyn, J. De Clercq, K. Deroover, G. Flouris, D. Lontkovskyi, S. Lowette, I. Marchesini, S. Moortgat, L. Moreels, Q. Python, K. Skovpen, S. Tavernier, W. Van Doninck, P. Van Mulders, I. Van Parijs, D. Beghin, B. Bilin, H. Brun, B. Clerbaux, G. De Lentdecker, H. Delannoy, B. Dorney, G. Fasanella, L. Favart, R. Goldouzian, A. Grebenyuk, A. K. Kalsi, T. Lenzi, J. Luetic, T. Maerschalk, A. Marinov, T. Seva, E. Starling, C. Vander Velde, P. Vanlaer, D. Vannerom, R. Yonamine, F. Zenoni, T. Cornelis, D. Dobur, A. Fagot, M. Gul, I. Khvastunov, D. Poyraz, C. Roskas, S. Salva, D. Trocino, M. Tytgat, W. Verbeke, N. Zaganidis, H. Bakhshiansohi, O. Bondu, S. Brochet, G. Bruno, C. Caputo, A. Caudron, P. David, S. De Visscher, C. Delaere, M. Delcourt, B. Francois, A. Giammanco, M. Komm, G. Krintiras, V. Lemaitre, A. Magitteri, A. Mertens, M. Musich, K. Piotrzkowski, L. Quertenmont, A. Saggio, M. Vidal Marono, S. Wertz, J. Zobec, W. L. Aldá Júnior, F. L. Alves, G. A. Alves, L. Brito, G. Correia Silva, C. Hensel, A. Moraes, M. E. Pol, P. Rebello Teles, E. Belchior Batista Das Chagas, W. Carvalho, J. Chinellato, E. Coelho, E. M. Da Costa, G. G. Da Silveira, D. De Jesus Damiao, S. Fonseca De Souza, L. M. Huertas Guativa, H. Malbouisson, M. Melo De Almeida, C. Mora Herrera, L. Mundim, H. Nogima, L. 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