Search for new phenomena in final states with two opposite-charge, same-flavor leptons, jets, and missing transverse momentum in pp collisions at $$ \sqrt{s}=13 $$ TeV

Journal of High Energy Physics, Mar 2018

The CMS collaboration, A. M. Sirunyan, A. Tumasyan, W. Adam, F. Ambrogi, E. Asilar, T. Bergauer, J. Brandstetter, E. Brondolin, M. Dragicevic, et al.

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Search for new phenomena in final states with two opposite-charge, same-flavor leptons, jets, and missing transverse momentum in pp collisions at $$ \sqrt{s}=13 $$ TeV

JHE Search for new phenomena in nal states with two opposite-charge, same- avor leptons, jets, and missing transverse momentum in pp collisions at s Model, Lepton production Search results are presented for physics beyond the standard model in nal states with two opposite-charge, same- avor leptons, jets, and missing transverse momentum. The data sample corresponds to an integrated luminosity of 35.9 fb 1 of protonproton collisions at p s = 13 TeV collected with the CMS detector at the LHC in 2016. The analysis uses the invariant mass of the lepton pair, searching for a kinematic edge or a resonant-like excess compatible with the Z boson mass. The search for a kinematic edge targets production of particles sensitive to the strong force, while the resonance search targets both strongly and electroweakly produced new physics. The observed yields are consistent with the expectations from the standard model, and the results are interpreted in the context of simpli ed models of supersymmetry. In a gauge mediated supersymmetry breaking (GMSB) model of gluino pair production with decay chains including Z bosons, gluino masses up to 1500{1770 GeV are excluded at the 95% con dence level depending on the lightest neutralino mass. In a model of electroweak chargino-neutralino production, chargino masses as high as 610 GeV are excluded when the lightest neutralino is massless. In GMSB models of electroweak neutralino-neutralino production, neutralino masses up to 500{650 GeV are excluded depending on the decay mode assumed. Finally, in a model with bottom squark pair production and decay chains resulting in a kinematic edge in the dilepton invariant mass distribution, bottom squark masses up to 980{1200 GeV are excluded depending on the mass of the next-to-lightest neutralino. Hadron-Hadron scattering (experiments); Supersymmetry; Beyond Standard - 13 TeV HJEP03(218)76 p The CMS collaboration 1 Introduction 2 Signal models 3 The CMS detector 4 Data sets, triggers, and object selection 5 Signal regions 6 Standard model background predictions Flavor-symmetric backgrounds Drell-Yan+jets backgrounds Backgrounds with Z bosons plus genuine pTmiss Results of the search in the on-Z signal regions Results of the edge search 9.1 Systematic uncertainty in the signal yield 9.2 Interpretations using simpli ed models 6.1 6.2 6.3 8.1 8.2 7 Kinematic t 8 Results 9 Interpretation 10 Summary The CMS collaboration 1 Introduction A Correlation and covariance matrices for the background predictions Supersymmetry (SUSY) [1{8] is a well-studied extension of the standard model (SM) and assumes a new fundamental symmetry that assigns a fermion (boson) to each SM boson (fermion). Supersymmetry resolves the hierarchy problem by stabilizing the Higgs boson (H) mass via additional quantum loop corrections from the top quark superpartner (top squark), which compensate for the large correction due to the top quark. If R-parity [9] is conserved, the lightest SUSY particle (LSP) predicted by the theory is stable and potentially massive, providing a candidate for the observed dark matter. Many SUSY models also lead to the uni cation of the electroweak (EW) and strong forces at high energies [10, 11]. { 1 { of p charge, same- avor (OCSF) leptons (electrons or muons), jets, and missing transverse momentum. Interpretations of the search results are given in terms of simpli ed supersymmetric model spectra. The data set of proton-proton collisions used for this search was collected in 2016 with the CMS detector at the CERN LHC at a center-of-mass energy s = 13 TeV and corresponds to an integrated luminosity of 35.9 fb 1 . Final states including an OCSF dilepton pair can occur in SUSY models via the decay of the superpartner of the SM neutral gauge bosons, the neutralino, when a heavier neutralino decays to a lighter neutralino LSP, or when the lightest neutralino is the next-to-lightest SUSY particle decaying to a gravitino LSP. Depending on the model parameters, the neutralino system (m``) [12], denoted as the \edge signature". This search targets both the on-Z and edge signatures. For the on-Z signature, search regions are optimized separately depending on whether we target strong or EW SUSY production. In the case of strong production, the neutralino is part of a decay chain starting from a gluino or squark, while in the EW case, it is directly produced. The search for a kinematic edge is only performed under the assumption of strong SUSY production. Searches for SUSY in these nal states were performed previously by the CMS [13{18] and ATLAS [19{21] Collaborations. The CMS Collaboration reported the presence of an excess with an edge shape located at m`` = 78:7 1:4 GeV and with a local signi cance p s = 8 TeV [13]. The ATLAS Collaboration did not con rm this excess in its p of 2.4 standard deviations (s.d.) in the data set collected at a center-of-mass-energy of s = 8 TeV dataset, but reported a resonant-like excess of events compatible with the Z boson mass and with a local signi cance of 3.0 s.d. [19]. Neither of these excesses were con rmed in the data sets collected at a center-of-mass-energy of p s = 13 TeV during 2015 by the CMS Collaboration [14] and during 2015 and the rst half of 2016 by the ATLAS Collaboration [21]. 2 Signal models The results of this search are interpreted in the context of various simpli ed models of SUSY [22{26], as described below. In all models, the W, Z, and Higgs bosons are assumed to decay according to their SM branching fractions. This search is designed to be sensitive to both strong and EW SUSY production leading to the on-Z signature. Most of the simpli ed models used for interpretation of the on-Z results represent gauge-mediated supersymmetry breaking (GMSB) models [27{29]. The rst of these GMSB models assumes strong production of a pair of gluinos (g) that each in turn decays into a massless gravitino (Ge ) and an on-shell Z boson. The decay chain corresponding to this gluino GMSB model is shown in gure 1 (upper left). The three other models used for the on-Z signature assume EW production. The upper right diagram in gure 1 corresponds to chargino-neutralino ( e1 - e02) production, with e1 decaying to a W boson and the LSP, e01, while the next-to-lightest neutralino, e02, decays to a Z boson and e10. The production cross sections for this model are computed in a limit of mass-degenerate wino e1 and e20, and light bino e10, with all the other sparticles assumed to be heavy and decoupled. Gauge mediated supersymmetry breaking is not assumed for this WZ model, and the e01 is allowed to be massive. ( e01- e10 The remaining two models considered assume the production of neutralino-neutralino ) pairs in GMSB. For bino- or wino-like neutralinos, the neutralino pair producyielding pair production of tion cross section is very small, and thus we consider a speci c GMSB model with massgravitino as the LSP [27{29]. In the production of any two of these, degenerate higgsinos e1 , e02, and e10 as the next-to-lightest SUSY particles and a massless mediately to e10 and low-momentum particles that do not impact the analysis, e ectively e1 or e02 decays ime01 e01. Intermediate production of either e1 or e02 is therefore not explicitly shown in the lower two diagrams of gure 1 representing these models. In the rst model (lower left of gure 1), the only allowed decay of the lightest neutralino is to a Z boson and a massless gravitino. In the other model (lower two diagrams of gure 1), the lightest neutralino is allowed to decay to a gravitino and either a Z boson or an SM-like Higgs boson, with a 50% branching fraction to each decay channel. The cross sections for e1 , and 0 higgsino pair production are computed in a limit of mass-degenerate higgsino states e2 e10, with all the other sparticles assumed to be heavy and decoupled. Following the convention of real mixing matrices and signed neutralino masses [30], we set the sign of the mass of (anti-symmetric) combinations of higgsino states by setting the product of the elements e01 ( e02) to +1 ( 1). The lightest two neutralino states are de ned as symmetric Ni3 and Ni4 of the neutralino mixing matrix N to +0:5 ( 0:5) for i = 1 (2). The elements U12 and V12 of the chargino mixing matrices U and V are set to 1. The signal model for the edge search, referred to as the slepton edge model, assumes the production of a pair of bottom squarks (be), the superpartner of the bottom quark, where each decays to e20 and a bottom quark. Two decay modes of the e20 are considered, each with a 50% branching fraction; they are both illustrated in gure 2. In the rst mode, the e20 decays to a Z boson and e10, which is stable. The Z boson can be on- or o -shell, depending on the mass di erence between the neutralinos. The second decay mode features sequential two-body decays with an intermediate slepton `e (ee,e): e20 ! `e` ! `` e01 masses of the sleptons are assumed to be degenerate and equal to the average of the minimum possible edge position at 50 GeV. e01 masses. The masses of the be and e02 are free parameters, while the mass of e01 is xed at 100 GeV. This scheme allows the position of the signal edge to vary in the invariant mass distribution depending on the mass di erence between the e20 and e10. The mass of the e01 is chosen in such a way that the e20 mass is always greater by at least 50 GeV, setting the . The e02 and { 3 { q Z Z q q Z G e G e Z G e G e p p p p W± H Z χ0 e1 0 χ e1 G e G e HJEP03(218)76 neutralino or neutralino-neutralino pairs. All the diagrams containing a gravitino (Ge ) represent gauge-mediated SUSY breaking (GMSB) models. p p eb1 eb1 χ0 e2 χ0 e2 ℓ e Z(∗) < 2 in azimuth and j j < 2:5, where the pseudorapidity is de ned as log[tan( =2)], with being the polar angle of the trajectory of the particle with respect to the counterclockwise beam direction. A crys{ 4 { tal electromagnetic calorimeter (ECAL) and a brass and scintillator hadron calorimeter (HCAL) surround the tracking volume. The calorimeters provide energy and direction measurements of electrons and hadronic jets. Muons are detected in gas-ionization detectors embedded in the steel ux-return yoke outside the solenoid. The detector is nearly hermetic, allowing for momentum balance measurements in the plane transverse to the beam direction. A two-tier trigger system selects events of interest for physics analysis. 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. [31]. 4 Data sets, triggers, and object selection This analysis uses data samples of e e and events for the signal region (SR) selections and e (ee, events for control regions (CRs). Events are collected with a set of dilepton , or e ) triggers that require the magnitude of the transverse momentum pT > 17 or 23 GeV for the highest pT lepton, depending on the data taking period, except for the dimuon trigger where the requirement is always pT > 17 GeV. These triggers impose loose isolation criteria on the leptons. For the next-to-highest pT electron (muon), pT > 12 (8) GeV is required, and electrons (muons) must satisfy j j < 2:5 (2:4). In order to retain high signal e ciency, in particular for highly boosted dilepton systems, dilepton triggers without an isolation requirement are also used. These require pT > 33 GeV for both leptons in the dielectron case and pT > 30 GeV for both leptons in the electron-muon case. In the dimuon case, they require either pT > 27 (8) or pT > 30 (11) GeV for the highest (next-to-highest) pT muon depending on the data taking period. The trigger e ciencies are measured in data using events selected by a suite of jet triggers and are found to be 90{96%. The particle- ow (PF) event algorithm [32] reconstructs and identi es particle candidates in the event, referred to as PF objects. To select collision events we require at least one reconstructed vertex. The reconstructed vertex with the largest value of summed physicsobject p2T is taken to be the primary pp interaction vertex. The physics objects used for the primary vertex selection are the objects returned by a jet nding algorithm [33, 34] applied to all charged tracks associated with the vertex, plus the corresponding associated missing transverse momentum. The missing transverse momentum vector p~miss is de ned as the projection onto the plane perpendicular to the beam axis of the negative vector sum of the momenta of all reconstructed PF objects in an event. Its magnitude is referred to as pTmiss. T Electrons, reconstructed by associating tracks with ECAL clusters, are identi ed using a multivariate approach based on information on the cluster shape in the ECAL, track reconstruction quality, and the matching between the track and the ECAL cluster [35]. Electrons from reconstructed photon conversions are rejected. Muons are reconstructed from tracks found in the muon system associated with tracks found in the tracker. They are identi ed based on the quality of the track t and the number of associated hits in the tracking detectors. For both lepton avors, the impact parameter with respect to the primary vertex is required to be within 0.5 mm in the transverse plane and less than 1 mm along the beam direction. The lepton isolation variable is de ned as the scalar pT sum of all PF objects in a cone around the lepton (excluding those identi ed as electrons or { 5 { HJEP03(218)76 p( and muons). To mitigate the impact of additional pp interactions in the same or nearby bunch crossings (pileup), only charged PF objects compatible with the primary vertex are included in the sum, and the average expected pileup contribution is subtracted from the neutral component of the isolation. The isolation sum is required to be smaller than 10 (20)% of the lepton pT for electrons (muons). The cone size varies with lepton pT and is chosen to be )2 + ( )2 = R = 0:2 for pT < 50 GeV, R = 10 GeV=pT for 50 < pT < 200 GeV, R = 0:05 for pT > 200 GeV. This shrinking cone size with increasing pT preserves high e ciency for leptons from Lorentz-boosted boson decays [36]. To identify events with three or more charged leptons, additional leptons beyond the rst two are selected with the looser requirement for the isolation sum to be less than 40% of the lepton pT. Photons are required to pass identi cation criteria based on the cluster shape in the ECAL and the fraction of energy deposited in the HCAL [37]. Photons must satisfy pT > 25 GeV, and be within j j < 2:4, excluding the \transition region" of 1:4 < j j < 1:6 between the ECAL barrel and endcap. Photons are required to be isolated from other PF objects within a cone of R = 0:3. To ensure the photon is well measured, it is required that (p~Tmiss; p~T) > 0:4. To distinguish photons from electrons, the photon is rejected if it can be connected to a pattern of hits in the pixel detector that indicate the presence of a charged particle track. Isolated, charged-particle tracks identi ed by the PF algorithm are selected with looser requirements on a similar set of criteria to the leptons de ned above and are used as a veto on the presence of additional charged leptons. When selecting charged PF objects, a track-based relative isolation is used. The relative track isolation is calculated using all charged PF objects within a cone R = 0:3 and longitudinal impact parameter j zj < 0:1 cm relative to the primary vertex. Particle- ow objects identi ed as electrons or muons (charged hadrons) are required to have pT > 5 (10) GeV and an isolation value less than 20 (10)% of the object pT. Jets are clustered from PF objects, excluding charged hadrons not associated with the primary vertex, using the anti-kT clustering algorithm [33] with a distance parameter of 0.4, implemented in the FastJet package [34, 38]. Jets are required to satisfy j j < 2:4 and pT > 35 GeV, where the pT is corrected for nonuniform detector response and multiple collision (pileup) e ects [39, 40]. A jet is removed from the event if it lies within R < 0:4 of any of the selected leptons or the highest pT photon. The scalar sum of all jet pT is referred to as HT. Corrections to the jet energy are propagated to pTmiss using the procedure developed in ref. [39]. Identi cation of jets originating from b quarks is performed with the combined secondary vertex (CSVv2) algorithm [41], using the medium working point, for which the typical e ciency for b quarks is around 60{75% and the mistagging rate for light- avor jets is around 1.5%. Jets with a lower threshold of pT > 25 GeV are considered, and selected jets are denoted as b-tagged jets. Events are selected by requiring two OCSF leptons (e e or ) with pT > 25 (20) GeV for the highest (next-to-highest) pT lepton and j j < 2:4 for both leptons. The distance between the leptons must satisfy R > 0:1 to avoid reconstruction e ciency differences between electrons and muons in events with collinear leptons. To ensure symmetry in acceptance between electrons and muons, all leptons in the transition region between the { 6 { barrel and endcap of the ECAL, 1:4 < j j < 1:6, are rejected. A control sample of lepton pairs with opposite charge and di erent avor (OCDF), e , is de ned using the same lepton selection criteria. All the parameters above have been chosen in order to maximize the lepton selection e ciency while keeping the e ciencies similar for electrons and muons. Photon events are used to predict one of the main backgrounds of this analysis, and a data control sample is selected as described below in section 6.2. To be consistent with the photon pT threshold applied in this control sample, we require the pT of the dilepton system to be greater than 25 GeV. While the main SM backgrounds are estimated using data control samples, simulated events are used to estimate systematic uncertainties and some SM background components as described below. Next-to-leading order (NLO) and next-to-NLO cross sections [42{47] are used to normalize the simulated background samples, while NLO plus next-to-leadinglogarithmic (NLL) calculations [48{50] are used for the signal samples. Simulated samples of Drell-Yan (DY) processes and photons produced in association with jets are generated with the MadGraph5 amc@nlo2.3.3 event generator [42] to leading order (LO) precision, with up to four additional partons in the matrix element calculations, using the MLM matching scheme [51]. Simulated ttV (V = W; Z) and VVV events are produced with the same generator to NLO precision. Other SM processes, such as VV, tt, and single top quark production, are simulated using powheg 2.0 [52]. The matrix element calculations performed with these generators are interfaced with pythia 8.212 [53] for the simulation of parton showering and hadronization. The NNPDF3.0 parton distribution functions (PDF) [54] are used for all samples. The detector response is simulated with a Geant4 model [55] of the CMS detector. The simulation of new-physics signals is performed using the MadGraph5 amc@nlo program at LO precision, with up to two additional partons in the matrix element calculation. Events are then interfaced with pythia 8.212 for fragmentation and hadronization, and further processed using the CMS fast simulation package [56]. Multiple pp interactions are superimposed on the hard collision, and the simulated samples are reweighted such that the number of collisions per bunch crossing accurately re ects the distribution observed in data. Corrections are applied to the simulated samples to account for di erences between simulation and data in the trigger and reconstruction e ciencies. 5 Signal regions The selections for all SRs, described below, are summarized in table 1. The on-Z search regions are designed to achieve low backgrounds from SM processes, while maintaining sensitivity to a variety of new-physics models, not only the processes described in section 2. The dilepton invariant mass is required to be in the range 86 < T T m`` < 96 GeV, which is compatible with the Z boson mass. The events must contain at least two jets and satisfy pmiss > 100 GeV. The two highest pT jets in the event are T required to have a separation in from p~miss of at least 0.4 to reduce backgrounds where the pmiss in the event comes from jet mismeasurements. Events containing additional electrons (muons) with pT > 10 GeV, j j < 2:5(2:4), and passing the looser isolation criteria from section 4, are rejected, as are events containing an isolated, charged PF candidate passing { 7 { the selections described in that section. Multiple on-Z SRs are de ned using these selection criteria as a baseline: the rst set for the strong production search and two additional regions for EW production searches. For the on-Z strong-production SRs, we make selections requiring a large level of hadronic activity in the event, which we expect in the decays of strongly coupled new particles. We de ne three SR categories: \SRA" (2{3 jets), \SRB" (4{5 jets), and \SRC" ( 6 jets). These categories are further divided as having either zero or at least one btagged jet. The kinematic variable MT2 [57, 58] is used to reduce the background from tt events. This variable was rst introduced to measure the mass of pair-produced particles, each decaying to the same nal state, consisting of a visible and an invisible particle. It is de ned using p~miss and two visible objects (leptons, jets, or combinations thereof) as: MT2 = min p~miss(1)+p~Tmiss(2)=p~Tmiss T h max M T(1); M T(2) i ; (5.1) T masses M T(i) = p 2pvTispmiss(i)[1 T where p~miss(i) (i = 1, 2) are trial vectors obtained by decomposing p~miss. The transverse T cos( )], where is the angle between the transverse T momentum of the visible object and p~miss(i), are obtained by pairing either of these trial vectors with one of the two visible objects. The minimization is performed over all trial momenta satisfying the p~Tmiss constraint. When building MT2 from the two selected leptons and p~miss, denoted MT2(``), its distribution exhibits a sharp decline around the mass of the W T boson for tt events and is therefore well suited to suppress this background. A requirement of MT2(``) > 80 GeV (100 GeV for events with at least one b-tagged jet) is imposed in order to suppress tt backgrounds. Requirements are then placed on HT depending on the number of jets and on the presence or absence of a b-tagged jet in the event, indicated by the labels \b tag" and \b veto," respectively. Finally, each SR is divided into multiple bins in pTmiss, depending on the number of selected jets. The precise requirements are summarized in table 1. The rst EW on-Z search region is denoted the \VZ" region and is designed to be sensitive to signatures where a hadronically decaying W or Z boson is produced in conjunction with the leptonically decaying Z boson. In order to reduce the tt background, events with a b-tagged jet are removed, and we require MT2(``) > 80 GeV. The two jets in the event that are closest in are then required to have a dijet invariant mass mjj < 110 GeV to be consistent with the hadronic decay of a W or Z boson. The SR is then divided into four T bins in pmiss: 100{150, 150{250, 250{350, and > 350 GeV. The second EW-production search region is denoted the \HZ" region and is designed to be sensitive to signatures where a Higgs boson is produced in conjunction with the leptonically decaying Z boson. We target Higgs bosons decaying to bb, due to its dominant branching ratio, and we therefore require events to have exactly two b-tagged jets with an invariant mass, mbb, less than 150 GeV. In order to reduce the tt background, a MT2 variable is calculated using two combinations of one lepton and one b-tagged jet as the visible objects. Each lepton is paired with a b-tagged jet, and all combinations of MT2 are calculated. The smallest value of MT2 is used, denoted MT2(`b`b). The distribution of MT2(`b`b) has an endpoint at the top quark mass for tt events, and we require MT2(`b`b) > 200 GeV. The SR is then divided into three bins in pmiss: 100{150, 150{250, T { 8 { A likelihood discriminant is used to distinguish between events originating from dilepand > 250 GeV. Although the selections for the EW VZ and HZ regions are mutually exclusive, they are not necessarily exclusive with respect to the strong-production SR selections. For interpretations of the analysis results, either the strong-production or the EW regions are considered depending on the signal model. The baseline SR in the edge search requires m`` > 20 GeV, at least two jets, pTmiss > 150 GeV, MT2(``) > 80 GeV, and the two jets with the highest pT to have a separation in from p~miss of at least 0.4. A t is performed in this baseline region to search for a kinematic edge in the m`` spectrum. A counting experiment is also performed in seven bins of m``, excluding the range used for the on-Z search. These are summarized in table 1. tonically decaying top quark pairs and other sources. The observables used for the likelihood discriminator are pmiss, the pT of the dilepton system, j ( )j between the leptons, T lepton and b-tagged jet systems, and should have an endpoint at 2pM (t)2 and an observable called m`b. The latter is the sum of the invariant masses of the two M (W)2 for events resulting from top quark pairs. To calculate m`b, all pairings of a lepton with a jet are considered, and the pairing with the minimum invariant mass is selected. This process is repeated for the remaining lepton and jets, and the sum of the invariant masses of the two lepton-jet pairs is de ned as m`b. If b-tagged jets are present, they are given priority in the calculation of both lepton-jet systems; i.e., if one or more b-tagged jets are present, m`b between the leptons and the b-tagged jet(s) is minimized rst, and then the remaining (b-tagged) jets are considered for the minimization of the sum m`b of the second lepton. To calculate the likelihood discriminant, the probability density functions of the four observables are determined by ts in the di erent- avor (DF) control sample using the same kinematic requirements as the same- avor (SF) SR except removing the MT2(``) selection. The respective t functions are a sum of two exponential functions for pmiss, a second-order polynomial for j ( )j, and a Crystal Ball (CB) function [59] for T both the dilepton pT and m`b distributions. A likelihood function is constructed, and its negative logarithm is taken as the discriminator value. Two categories of events are de ned: \tt-like," with a discriminator value less than 21 and an e ciency of 95% for tt events, and \not-tt-like," which is composed of the remainder of the events. In addition, two aggregate SRs are de ned for the edge search, integrating the mass bins below and above the Z boson mass for the not-tt-like category. 6 Standard model background predictions The backgrounds from SM processes are divided into three categories. Those that produce DF pairs (e ) as often as SF pairs ( , e e ) are referred to as avor-symmetric (FS) backgrounds. Among them, the dominant contribution arises from top quark pair production; subleading contributions are also present from W+W , Z= (! quark production, and leptons from hadron decays. Data samples of DF events are used ), tW single-top to predict the SF background. The remaining background categories contain avor-correlated sources of lepton production that only contribute events with OCSF leptons. The dominant contributions at { 9 { Region SRA b veto 2{3 SRB b veto 4{5 SRC b veto SRA b tag SRB b tag SRC b tag Region VZ HZ Region Edge t tt-like not-tt-like aggregate 6 2{3 4{5 6 2 2 2 2 2 2 =0 =0 =0 1 1 1 =0 =2 >150 >150 >150 >150 >500 >500 | >200 >200 | >80 >80 >80 >80 Electroweak-production on-Z (86 < m`` < 96 GeV) signal regions Njets Nb-jets Dijet mass [GeV] MT2 [GeV] measurement of the jet energies. Data samples of photon events are used to predict this DY+jets background. The nal category comes from events with prompt neutrinos in addition to an OCSF pair from a Z= boson. This includes WZ and ZZ production and processes with lower cross section such as ttZ among others. These backgrounds are referred to as \Z+ " and can be important in the high-pTmiss signal bins. 6.1 Flavor-symmetric backgrounds The method of estimating the FS backgrounds relies on the fact that, for such processes, SF and DF events are produced at the same rate. This allows for prediction of the background yields in the SF sample from those in the DF sample by application of an appropriate correction factor, which is estimated from CRs in data. This factor corrects for di erent avor-dependent reconstruction and identi cation e ciencies and for avor-dependent trigger e ciencies, which can be di erent for electrons and muons. For cases where the DF contribution is of su cient statistical power to make an accurate prediction in the SF channel, a background estimate in the SF channel can therefore be obtained by applying a multiplicative correction factor, RSF/DF, to the DF channel yield. The correction is determined in two independent ways, both based purely on control samples in the data. The two results are then combined using the weighted average according to their uncertainties to obtain the nal factor. The rst approach uses a direct measurement of this correction factor in a data CR independent of the baseline SR, and the second method involves a factorized approach of measuring the e ects of reconstruction, identi cation, and trigger e ciencies separately and then combining them assuming the overall e ciency equal to the product of the individual components. The direct measurement is performed in a CR requiring exactly two jets and 100 < pmiss < 150 GeV, excluding the dilepton invariant mass range 70 < m`` < 110 GeV to T reduce contributions from DY+jets backgrounds. Here, RSF/DF is computed using the observed yield of SF and DF events, RSF/DF = NSF=NDF. Data and simulation agree within 2% in this region. In simulation we nd that RSF/DF di ers by 1% when computed in the SR instead of the CR. We check the dependence of RSF/DF on the main kinematic variables used for the analysis in both data and simulation. Since the statistical power in data is limited, a systematic uncertainty of 4% is assigned based on the variations observed in simulation. The measured value of RSF/DF is 1:107 0:046. For the factorized approach, the ratio of muon to electron reconstruction and identi cation e ciencies, r =e, is measured in a DY+jets-enriched CR requiring at least two jets, pmiss < 50 GeV, and 60 < m`` < 120 GeV. This results in a large sample of e e and T of lepton e ciencies in an event, the e ciency ratio is measured as r =e = p events with similar kinematic distributions to those of the SR. Assuming the factorization =Ne+e . N + This ratio depends on the lepton pT due to trigger and reconstruction e ciency di erences, especially at low lepton pT. A parameterization as a function of the pT of the less energetic lepton is used, and the functional form below is found to empirically describe the data: r =e = C + pT : RT = q T T e e = eT Here C and are constants that are determined from a t to data and checked using simulation. These t parameters are determined to be C = 1:140 0:005 and = 5:20 0:16 GeV. In addition to the t uncertainty, a 10% systematic uncertainty is assigned to account for remaining variations observed when studying the dependence of r =e on the pT of the more energetic lepton, pTmiss, and the jet multiplicity. The trigger e ciencies for the three avor combinations are used to de ne the factor , which takes into account the di erence between SF and DF channels. The e ciencies are estimated from a control sample of events collected with a set of nonoverlapping triggers and range between 90{96%, yielding a nal value of RT = 1:052 0:043. The nal correction is RSF/DF = (1=2)(r =e + r =1e)RT. The correction relies on the assumption that the number of produced DF events is twice the number of produced events in each SF sample. Thus, the number of observed DF events needs to be multiplied by 0:5r =eRT and 0:5r =1eRT to predict the number of dimuon and dielectron from FS processes, respectively. Summing r =e with its inverse leads to a large reduction in the associated uncertainty. Since r =e depends on the lepton kinematic variables, this correction is performed on an event-by-event basis. A separate correction is determined for each SR and combined with the correction from the direct measurement using the weighted average. In the method described above, the statistical uncertainty in the predicted number of events is driven by the statistical uncertainty in the number of data events in the DF HJEP03(218)76 CR. Since RSF/DF is approximately one, the CR yield will be comparable to that of the FS background in the corresponding SR. In the on-Z SRs, the FS background is signi cantly reduced by the requirement that m`` lies within 5 GeV of the Z boson mass. The expected FS background yields in the SRs are often of the order of a few events or less. We therefore modify the prediction method to obtain greater statistical power by relaxing the requirement on m`` for DF events, thereby increasing the number of events in the DF CR. An additional multiplicative factor, , is calculated and multiplied together with RSF/DF in order to translate this into a prediction for the SF SR. The factor is de ned as the number of DF events with jmZ m``j < 5 GeV divided by the number of DF events with m`` > 20 GeV. It is determined from an DF control sample in simulation and validated in the DF data CRs. A value of = 0:065 is measured from simulation. A systematic uncertainty of 30% is assigned by computing in simulation for both the various on-Z SRs and bins of pTmiss. The largest observed di erence from the nominal value is taken as the systematic uncertainty. The value of derived in data agrees with the result derived from simulation within the assigned uncertainty, and the statistical uncertainty in the derivation of is negligible in comparison with the systematic uncertainty. Drell-Yan+jets backgrounds T T T The pmiss from the DY+jets background is estimated from a sample of photon events in data using the pTmiss \templates" method [13{16]. The main premise of this method is that pmiss in DY+jets events originates from the limited detector resolution when measuring the objects making up the hadronic system that recoils against the Z boson. The shape of the pmiss distribution can be estimated from a control sample of +jets events where the jet system recoils against a photon instead of a Z boson. In addition to capturing the T same resolution e ects present in DY+jets events, the +jets sample contains more events because of the branching fraction of Z ! `+` , and it does not have any contamination from signal events in the models considered. For SRs requiring at least one b-tagged jet, some of the observed pmiss can originate from neutrinos in semileptonic b-quark decays. To account for this e ect, the pmiss templates are extracted from a control sample of +jets T events with the same b-tagging requirements as in each SR. The +jets events in data are selected with a suite of single-photon triggers with pT thresholds varying from 22 to 165 GeV. The triggers with thresholds below 165 GeV are prescaled such that only a fraction of accepted events are recorded, and the events are weighted by the trigger prescales to match the integrated luminosity collected with the signal dilepton triggers. In order to account for kinematic di erences between the hadronic systems in the +jets and the DY+jets samples, the +jets sample is reweighted such that the photon pT distribution matches the Z pT distribution in the DY+jets sample. A separate photon CR is de ned for each of the on-Z SRs in table 1, where the same kinematic requirements are applied to the +jets samples as in each SR. The reweighting in boson T pT is performed for each SR. Contributions to the photon sample from other SM processes with genuine pTmiss from prompt neutrinos are subtracted as described below. The resulting pmiss distribution in each SR is then normalized to the observed dilepton data yield in the HJEP03(218)76 with genuine pmiss, e.g. W T tion is applied to the emulated dilepton system in order to match the original momentum of the photon. The analysis requirements on pT and for leptons are applied to the simulated decay products. The variable MT2(``) is constructed using these leptons, showing good agreement with the distribution of MT2(``) in genuine DY+jets events, and a selection is applied to this variable matching each SR requirement. After selecting events with a high-pT photon and large pTmiss, events from EW processes range 50 < pmiss < 100 GeV, where DY+jets is the dominant background, after subtracting other background components. The variable MT2 used in the SR requires two visible objects as input and thus cannot be calculated in the same way in the photon sample. Instead, we emulate this requirement in +jets by simulating the decay of the photon to two leptons. The decay is performed assuming the mother particle has the mass of a Z boson and the momentum of the photon reconstructed from data. We rst consider a system of reference in which the mother particle is at rest. The decay to the leptons is performed in this system accounting for the angular dependence of spin correlations in the matrix element. Then a Lorentz transformawhere the W boson decays to ` , can be present in the tail of the pmiss distribution. To reduce the contamination from these EW processes, events in the photon sample are removed if they contain a lepton ful lling the veto selections for the on-Z regions described in section 5. We then subtract the residual EW contamination using simulation. The relative size of the subtraction grows with increasing pmiss to be as large as around 50% of the prediction or 1 predicted event in the highest pmiss bins. To validate the modeling of the subtracted EW processes, we de ne a data CR by selecting events with exactly one muon and one photon, requiring pmiss > 50 GeV and the transverse mass MT of the muon and pmiss to be greater than 30 GeV. The muon must T satisfy pT > 25 GeV, and the events are selected using a trigger that requires at least one T isolated muon with pT > 24 GeV. This region consists of about 50% W events with the remainder coming primarily from tt events. Agreement is observed between data and the T T prediction from simulation. Based on the level of agreement between data and simulation in the kinematic distributions of photon pT and pmiss, we assign a systematic uncertainty T of 30% in the subtraction of these EW processes. The systematic uncertainty in the prediction takes into account the statistical uncertainty in the +jets sample in each bin of pTmiss, which is the dominant uncertainty in the highest pmiss bins. The statistical uncertainty in the normalization region of 50 < pmiss < T 100 GeV is included and ranges from 7{30%. A closure test of the method is performed in simulation, using +jets to predict the yield of DY+jets in each analysis bin. An uncertainty is assigned from the results of this test as the larger of the di erence between the +jets prediction and the DY+jets yield for each pmiss region or the simulation statistical uncertainty. The values vary between 10 and 80% depending on the pmiss region, with the T larger values coming from regions with low statistics in simulation. The template method is also used to provide a prediction for the background from DY+jets in the edge SRs, where this background is signi cantly smaller due to the m`` requirements. We de ne the ratio rout/in in a DY+jets-dominated sample as the number of SF events in a given bin of m`` divided by the SF yield within 86 < m`` < 96 GeV. The ratio is measured in a DY+jets-dominated CR requiring at least two jets, pTmiss < 50 GeV, and MT2(``) > 80 GeV. Di erent- avor yields in both the numerator and denominator are subtracted from the respective SF yields in order to correct for small FS contributions in the region where rout/in is measured. The value of rout/in ranges from 0.001 to 0.16 for the di erent bins in m``. The DY+jets background contribution to each m`` bin is computed by multiplying the on-Z prediction by rout/in. The dependence of rout/in on pmiss and the T jet multiplicity are studied in the data CR. Based on the statistical precision of this check, and the observed variations as a function of these variables, we assign an uncertainty of 50 (100)% to rout/in in the m`` bins below (above) 150 GeV. Backgrounds with Z bosons plus genuine pmiss T T The pTmiss template method only predicts instrumental pTmiss from jet mismeasurement and thus does not include the genuine pmiss from prompt neutrinos expected in processes like W(` )Z(``), Z(``)Z( ), or lower cross section processes such as ttZ. These processes can be a substantial fraction of the background at high pTmiss and are estimated using simulation. The prediction from simulation is validated by comparing to data in CRs requiring three or four leptons. A region enriched in WZ events is selected by requiring exactly three leptons, at least two jets, no b-tagged jets, pTmiss > 60 GeV, and an OCSF lepton pair with 86 < m`` < 96 GeV. Another three-lepton CR is de ned targeting ttZ by requiring at least two jets, at least two b-tagged jets, pTmiss > 30 GeV, and an OCSF lepton pair as in the WZ region. A four-lepton CR targeting ZZ is constructed by requiring four leptons with two OCSF pairs satisfying m`` > 20 GeV, to remove low-mass resonances, and at least two jets. After subtracting the other processes using simulation in each region, simulation-todata scale factors of 0:98 and ttZ backgrounds respectively. We use the scale factor values to correct the prediction from simulation for each process. Based on the statistical uncertainty in these CRs, and T the agreement between data and simulation in distributions of kinematic variables such as pmiss and the number of jets, we assign systematic uncertainties of 30% for the WZ and ttZ background predictions and 50% for the ZZ prediction. As all other e ects are subdominant, we do not assign further uncertainties to these backgrounds. 7 Kinematic t A simultaneous extended unbinned maximum likelihood t is performed in the m`` distributions of e+e , + , and e events to search for a kinematic edge. The t is performed after the kinematic selection labeled \Edge t" in table 1. The likelihood model contains three components: an FS background component, a DY+jets background component, and a signal component. The Z+ background is contained within the DY+jets component in this method, as both have the same m`` shape. The FS background component is described using a CB function PCB(m``): PCB(m``) = <exp 8 h (m`2` 2CBCB)2 i :A(B + m`` CB CB ) n if m`` CB < CB if m`` CB CB > (7.1) where A = n j j n exp j j 2 2 and B = j j: n j j The FS background model has ve free parameters: the overall normalization, the mean CB and width CB of the Gaussian part, the transition point between the Gaussian part and the power law tail, and the power law parameter n. The DY+jets background component is modeled with the sum of an exponential function, which describes the low-mass rise, and a Breit-Wigner function with a mean and width set to the nominal Z boson values [60], which accounts for the Z boson lineshape. To account for the experimental resolution, the Breit-Wigner function is convolved with a double-sided CB function HJEP03(218)76 where DSCB and DSCB are the mean and width, respectively, of the CB function, and 1 and 2 are the transition points. The full model for the on-Z DY+jets background line shape is thus PDY; on-Z (m``) = m0)dm0; Z DSCB DSCB ) n2 if m`` DSCB > DSCB 2 PDSCB(m``) = <exp h (m`2` 2DSCB > 8>A1(B1 > >:A2(B2 + m`` m`` DSCB ) n1 DDSSCCBB)2 i if m`` DSCB < DSCB if 1 < m`` DSCB DSCB < 2 1 where PBW is the Breit-Wigner function. The complete DY+jets background model has nine free parameters. The signal component is described by a triangular shape, convolved with a Gaussian distribution to account for the experimental resolution: PS(m``) / p 2 1 Z m`e`dge `` 0 y exp (m`` y)2 2 `2` dy: The signal model has two free parameters: the tted signal yield and the position of the edge, m`e`dge. As the rst step, a t is performed separately for e+e and + events in a DY+jetsT enriched CR requiring at least two jets and pmiss < 50 GeV, to determine the shape of backgrounds containing a Z boson. The parameters of the DY+jets background shape are then xed and only the normalizations of these backgrounds are free parameters in the subsequent t. The nal t is performed simultaneously to the dilepton invariant mass distributions in the e+e , + , and e samples. The model for the FS background is the same for the SF and DF events. The RSF/DF factor is treated as a nuisance parameter, parameterized by a Gaussian distribution with a mean value and standard deviation given by the value of RSF/DF and its uncertainties (see section 6.1). The nal t has ten free parameters: a normalization for each of the three t components, four parameters for the shape of the FS background, RSF/DF, the relative fraction of dielectron and dimuon events in the FS prediction, and the position of the signal edge. (7.2) (7.3) (7.4) (7.5) Results The observed number of events in the SRs are compared with the background estimates for the on-Z strong- and EW-production and the edge searches. The covariance and correlation matrices of the background predictions in the di erent SRs are also provided in appendix A to facilitate reinterpretation of these results. For the edge search, the t is performed to search for a kinematic edge in the m`` spectrum. Results of the search in the on-Z signal regions observed with respect to SM expectations. The results for the SRs of the on-Z strong-production search are presented in table 2. The corresponding pmiss distributions are shown in gure 3. No signi cant deviations are The results for the EW SRs in the on-Z search are shown in table 3. The corresponding pmiss distributions are shown in gure 4. The observed data are also consistent with the Results of the edge search The edge search features seven distinct m`` regions, each of which is divided into two bins using the likelihood discriminant, resulting in fourteen SRs. In addition, two aggregate regions integrating the SRs below and above the Z boson mass have been considered in the not-tt-like case. Table 4 summarizes the SM predictions and the observations in these SRs. A graphical representation of these results is shown in gure 5, including the relative contributions of the di erent backgrounds. At high mass and in the not-tt-like regions, the uncertainty in the background prediction is driven by the statistical uncertainty in the number of events in the DF control sample. There is good agreement between prediction and observation for all SRs. The largest deviation is observed in the not-tt-like region for masses between 96 and 150 GeV, with an excess corresponding to a local signi cance of 2.0 standard deviations. The dilepton mass distributions and the results of the kinematic t are shown in gure 6. Table 5 presents a summary of the t results. A signal yield of 61 28 events is obtained when evaluating the signal hypothesis in the baseline SR, with a tted edge position of 144:2+32::32 GeV. This is in agreement with the upwards uctuations in the mass region between 96 and 150 GeV in the counting experiment and corresponds to a local signi cance of 2.3 standard deviations. To estimate the global p-value [61] of the result, the test statistic 2 ln Q, where Q denotes the ratio of the tted likelihood value for the signal-plus-background hypothesis to the background-only hypothesis, is evaluated on data and compared to the respective quantity on a large sample of background-only pseudo-experiments where the edge position can have any value. The resulting p-value is interpreted as the one-sided tail probability of a Gaussian distribution and corresponds to an excess in the observed number of events compared to the SM background prediction with a global signi cance of 1.5 standard deviations. SRA, b veto DY+jets SRA, b tag SRB, b veto SRB, b tag SRC, b veto SRC, b tag Total background each pmiss bin de ned in table 1. The uncertainties shown include both statistical and systematic T components. 5 7 4 0:2+00::21 0:2+00::21 FS Z+ Data Total background CMS SRB, b veto e e SRB, b tag 100 150 200 250 100 150 200 250 T pmiss [GeV3]50 300 s tven 103 SRA, b veto E E ts 103 CMS n e v 10−150 n taaD iitrcdeo 21 P 1 3 1 3 10 10−150 n taaD iitrcdeo 21 CMS s t veE 102 SRC, b veto n 100 150 200 250 100 150 200 250 Data FS Z+ν FS Z+ν FS DY+jets Z+ν T pmiss [GeV3]50 300 35.9 fb-1(13 TeV) T pmiss [GeV3]50 300 Data FS FS DY+jets Z+ν T pmiss [GeV3]50 300 35.9 fb-1(13 TeV) T pmiss [GeV3]50 300 102 10 1 2 10−150 s t n vE 102 10 1 2 1 3 10 10−150 n taaD iitrcdeo 21 10−150 E SRC, b tag 100 150 200 250 100 150 200 250 P on-Z strong-production SRs with no b-tagged jets (left) and at least 1 b-tagged jet (right). The rows show SRA (upper), SRB (middle), and SRC (lower). The lower panel of each plot shows the ratio of observed data to the predicted value in each bin. The hashed band in the upper panels shows the total uncertainty in the background prediction, including statistical and systematic components. The pmiss template prediction for each SR is normalized to the rst bin of each distribution, and T therefore the prediction agrees with the data by construction. EW VZ Region EW HZ Region n n s t the on-Z VZ (left) and HZ (right) electroweak-production SRs. The lower panel of each gure shows the ratio of observed data to the predicted value in each bin. The hashed band in the upper panels shows the total uncertainty in the background prediction, including statistical and systematic sources. The pmiss template prediction for each SR is normalized to the rst bin of each T distribution, and therefore the prediction agrees with the data by construction. Data FS s t e v E 102 10 1 10−150 2 FS Z+ Data Total background de ned in table 1. 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Randle-conde, T. Seva, C. Vander Velde, P. Vanlaer, D. Vannerom, R. Yonamine, F. Zenoni, F. Zhang2 Ghent University, Ghent, Belgium A. Cimmino, T. Cornelis, D. Dobur, A. Fagot, M. Gul, I. Khvastunov, D. Poyraz, C. Roskas, S. Salva, M. Tytgat, W. Verbeke, N. Zaganidis Universite Catholique de Louvain, Louvain-la-Neuve, Belgium H. Bakhshiansohi, O. Bondu, S. Brochet, G. Bruno, C. Caputo, 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, K. Piotrzkowski, L. Quertenmont, M. Vidal Marono, S. Wertz Universite de Mons, Mons, Belgium N. Beliy Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil W.L. Alda Junior, F.L. Alves, G.A. Alves, L. Brito, M. Correa Martins Junior, C. Hensel, A. Moraes, M.E. Pol, P. Rebello Teles Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil E. Belchior Batista Das Chagas, W. Carvalho, J. Chinellato3, A. Custodio, E.M. Da Costa, G.G. Da Silveira4, 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, A. Santoro, A. Sznajder, E.J. Tonelli Manganote3, F. Torres Da Silva De Araujo, A. Vilela Pereira Brazil S. Ahujaa, Sciences Universidade Estadual Paulista a, Universidade Federal do ABC b, S~ao Paulo, C.A. Bernardesa, T.R. Fernandez Perez Tomeia, E.M. Gregoresb, P.G. Mercadanteb, S.F. Novaesa, Sandra S. Padulaa, D. Romero Abadb, J.C. Ruiz Vargasa Institute for Nuclear Research and Nuclear Energy of Bulgaria Academy of A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, M. Misheva, M. Rodozov, M. Shopova, S. Stoykova, G. Sultanov University of So a, So a, Bulgaria A. Dimitrov, I. Glushkov, L. Litov, B. Pavlov, P. Petkov Beihang University, Beijing, China W. Fang5, X. Gao5 Institute of High Energy Physics, Beijing, China M. Ahmad, J.G. Bian, G.M. Chen, H.S. Chen, M. Chen, Y. Chen, C.H. Jiang, D. Leggat, H. Liao, Z. Liu, F. Romeo, S.M. Shaheen, A. Spiezia, J. Tao, C. Wang, Z. Wang, E. Yazgan, H. Zhang, J. Zhao Beijing, China State Key Laboratory of Nuclear Physics and Technology, Peking University, Y. Ban, G. Chen, Q. Li, S. Liu, Y. Mao, S.J. Qian, D. Wang, Z. Xu Universidad de Los Andes, Bogota, Colombia C. Avila, A. Cabrera, L.F. Chaparro Sierra, C. Florez, C.F. Gonzalez Hernandez, J.D. Ruiz Alvarez University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Split, Croatia B. Courbon, 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, A. Starodumov6, T. Susa University of Cyprus, Nicosia, Cyprus M.W. Ather, A. Attikis, G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos, P.A. Razis, H. Rykaczewski Charles University, Prague, Czech Republic M. Finger7, M. Finger Jr.7 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 Kamel8, S. Khalil9, A. Mohamed9 National Institute of Chemical Physics and Biophysics, Tallinn, Estonia R.K. Dewanjee, 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, E. Tuominen, J. Tuominiemi, E. Tuovinen 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, J.L. Faure, F. Ferri, S. Ganjour, S. Ghosh, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry, I. Kucher, E. Locci, M. Machet, J. Malcles, G. Negro, J. Rander, A. Rosowsky, M.O . Sahin, M. Titov Laboratoire Leprince-Ringuet, Ecole polytechnique, CNRS/IN2P3, Universite Paris-Saclay, Palaiseau, France A. Abdulsalam, I. Antropov, S. Ba oni, F. Beaudette, P. Busson, L. Cadamuro, C. Charlot, R. Granier de Cassagnac, M. Jo, S. Lisniak, A. Lobanov, J. Martin Blanco, M. Nguyen, C. Ochando, G. Ortona, P. Paganini, P. Pigard, S. Regnard, R. Salerno, J.B. Sauvan, Y. Sirois, A.G. Stahl Leiton, T. Strebler, Y. Yilmaz, A. Zabi, A. Zghiche Universite de Strasbourg, CNRS, IPHC UMR 7178, F-67000 Strasbourg, France S. Gadrat J.-L. Agram10, J. Andrea, D. Bloch, J.-M. Brom, M. Buttignol, E.C. Chabert, N. Chanon, C. Collard, E. Conte10, X. Coubez, J.-C. Fontaine10, D. Gele, U. Goerlach, M. Jansova, A.-C. Le Bihan, N. Tonon, 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, R. Chierici, D. Contardo, P. Depasse, H. El Mamouni, J. Fay, L. Finco, S. Gascon, M. Gouzevitch, G. Grenier, B. Ille, F. Lagarde, I.B. Laktineh, M. Lethuillier, L. Mirabito, A.L. Pequegnot, S. Perries, A. Popov11, V. Sordini, M. Vander Donckt, S. Viret T. Toriashvili12 L. Rurua Georgian Technical University, Tbilisi, Georgia 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, 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, D. Teyssier, S. Thuer RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany G. Flugge, B. Kargoll, T. Kress, A. Kunsken, J. Lingemann, T. Muller, A. Nehrkorn, A. Nowack, C. Pistone, O. Pooth, A. Stahl13 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. Borras14, V. Botta, A. Campbell, P. Connor, C. Contreras-Campana, F. Costanza, C. Diez Pardos, G. Eckerlin, D. Eckstein, T. Eichhorn, E. Eren, E. Gallo15, J. Garay Garcia, A. Geiser, A. Gizhko, J.M. Grados Luyando, A. Grohsjean, P. Gunnellini, M. Gutho , A. Harb, J. Hauk, M. Hempel16, H. Jung, A. Kalogeropoulos, M. Kasemann, J. Keaveney, C. Kleinwort, I. Korol, D. Krucker, W. Lange, A. Lelek, T. Lenz, J. Leonard, K. Lipka, W. Lohmann16, R. Mankel, I.-A. Melzer-Pellmann, A.B. Meyer, G. Mittag, J. Mnich, A. Mussgiller, E. Ntomari, D. Pitzl, A. Raspereza, B. Roland, M. Savitskyi, P. Saxena, R. Shevchenko, S. Spannagel, N. Stefaniuk, G.P. Van Onsem, R. Walsh, Y. Wen, K. Wichmann, C. Wissing, O. Zenaiev University of Hamburg, Hamburg, Germany 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, I. Marchesini, D. Marconi, M. Meyer, M. Niedziela, D. Nowatschin, F. Pantaleo13, 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, L. Vanelderen, A. Vanhoefer, B. Vormwald Institut fur Experimentelle Kernphysik, Karlsruhe, Germany M. Akbiyik, C. Barth, S. Baur, E. Butz, R. Caspart, T. Chwalek, F. Colombo, W. De Boer, A. Dierlamm, B. Freund, R. Friese, M. Gi els, A. Gilbert, D. Haitz, F. Hartmann13, S.M. Heindl, U. Husemann, F. Kassel13, 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 Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece I. Topsis-Giotis G. Anagnostou, G. Daskalakis, T. Geralis, V.A. Giakoumopoulou, A. Kyriakis, D. Loukas, National and Kapodistrian University of Athens, Athens, Greece 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. Kokkas, S. Mallios, N. Manthos, I. Papadopoulos, E. Paradas, J. Strologas, F.A. Triantis MTA-ELTE Lendulet CMS Particle and Nuclear Physics Group, Eotvos Lorand University, Budapest, Hungary M. Csanad, N. Filipovic, G. Pasztor, G.I. Veres17 Wigner Research Centre for Physics, Budapest, Hungary G. Bencze, C. Hajdu, D. Horvath18, A. Hunyadi, F. Sikler, V. Veszpremi, A.J. Zsigmond Institute of Nuclear Research ATOMKI, Debrecen, Hungary N. Beni, S. Czellar, J. Karancsi19, A. Makovec, J. Molnar, Z. Szillasi Institute of Physics, University of Debrecen, Debrecen, Hungary M. Bartok17, 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. Bahinipati20, S. Bhowmik, P. Mal, K. Mandal, A. Nayak21, D.K. Sahoo20, N. Sahoo, S.K. Swain Panjab University, Chandigarh, India S. Bansal, S.B. Beri, V. Bhatnagar, R. Chawla, N. Dhingra, A.K. Kalsi, A. Kaur, M. 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, D. Roy, S. Roy Chowdhury, S. Sarkar, M. Sharan, S. Thakur HJEP03(218)76 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. Mohanty13, P.K. Netrakanti, L.M. Pant, 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. Maity22, G. Majumder, K. Mazumdar, T. Sarkar22, N. Wickramage23 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. Chenarani24, E. Eskandari Tadavani, S.M. Etesami24, M. Khakzad, M. Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi25, F. Rezaei Hosseinabadi, B. Safarzadeh26, 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;b, A. Ranieria, G. Selvaggia;b, A. Sharmaa, L. Silvestrisa;13, R. Vendittia, P. Verwilligena INFN Sezione di Bologna a, Universita di Bologna b, Bologna, Italy G. Abbiendia, C. Battilanaa;b, D. Bonacorsia;b, S. Braibant-Giacomellia;b, R. Campaninia;b, P. Capiluppia;b, A. Castroa;b, F.R. Cavalloa, S.S. Chhibraa, 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 L. Viliania;b;13 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;27, G. Sguazzonia, D. Stroma, INFN Laboratori Nazionali di Frascati, Frascati, Italy L. Benussi, S. Bianco, F. Fabbri, D. Piccolo, F. Primavera13 INFN Sezione di Genova a, Universita di Genova b, Genova, Italy V. Calvellia;b, F. Ferroa, E. Robuttia, S. Tosia;b INFN Sezione di Milano-Bicocca a, Universita di Milano-Bicocca b, Milano, Italy A. Benagliaa, L. Brianzaa;b, F. Brivioa;b, V. Cirioloa;b, 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;28, 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;13, F. Fabozzia;c, F. Fiengaa;b, A.O.M. Iorioa;b, W.A. Khana, L. Listaa, S. Meolaa;d;13, P. Paoluccia;13, C. Sciaccaa;b, INFN Sezione di Padova a, Universita di Padova b, Padova, Italy, Universita di Trento c, Trento, Italy P. Azzia;13, 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, 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, G. Zumerlea;b INFN Sezione di Pavia a, Universita di Pavia b, Pavia, Italy A. Braghieria, A. Magnania;b, P. Montagnaa;b, S.P. Rattia;b, V. Rea, M. Ressegotti, 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;13, G. Bagliesia, J. Bernardinia, T. Boccalia, L. Borrello, R. Castaldia, M.A. Cioccia;b, R. Dell'Orsoa, G. Fedia, L. Gianninia;c, A. Giassia, M.T. Grippoa;27, F. Ligabuea;c, T. Lomtadzea, E. Mancaa;c, G. Mandorlia;c, L. Martinia;b, A. Messineoa;b, F. Pallaa, A. Rizzia;b, A. Savoy-Navarroa;29, 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, D. Del Rea;b;13, 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, 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, J. Lee, S. Lee, S.W. Lee, C.S. Moon, Y.D. Oh, S. Sekmen, D.C. Son, Y.C. Yang Chonbuk National University, Jeonju, Korea A. Lee Chonnam National University, Institute for Universe and Elementary Particles, Kwangju, Korea H. Kim, D.H. Moon, G. Oh 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 M. Choi, 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 Ali30, F. Mohamad Idris31, W.A.T. Wan Abdullah, HJEP03(218)76 Reyes-Almanza, R, Ramirez-Sanchez, G., Duran-Osuna, M. C., H. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-De La Cruz32, 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 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, 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, M. Szleper, P. Zalewski Warsaw, Poland Institute of Experimental Physics, Faculty of Physics, University of Warsaw, K. Bunkowski, A. Byszuk33, 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, P. Bunin, M. Gavrilenko, I. Golutvin, I. Gorbunov, A. Kamenev, V. Karjavin, A. Lanev, A. Malakhov, V. Matveev34;35, V. Palichik, V. Perelygin, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, N. Voytishin, A. Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia Y. Ivanov, V. Kim36, E. Kuznetsova37, P. Levchenko, V. Murzin, V. Oreshkin, I. Smirnov, 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, M. Toms, E. Vlasov, A. Zhokin Moscow Institute of Physics and Technology, Moscow, Russia T. Aushev, A. Bylinkin35 National Research Nuclear University 'Moscow Engineering Physics Institute' (MEPhI), Moscow, Russia R. Chistov38, M. Danilov38, P. Parygin, D. Philippov, S. Polikarpov, E. Tarkovskii, E. Zhemchugov P.N. Lebedev Physical Institute, Moscow, Russia V. Andreev, M. Azarkin35, I. Dremin35, M. Kirakosyan35, A. Terkulov Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia A. Snigirev A. Baskakov, A. Belyaev, E. Boos, M. Dubinin39, 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. Blinov40, Y.Skovpen40, D. Shtol40 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, A. Volkov University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia P. Adzic41, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic, V. Rekovic Centro de Investigaciones Energeticas Medioambientales y Tecnologicas (CIEMAT), Madrid, Spain J. Alcaraz Maestre, M. Barrio Luna, M. Cerrada, 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, A. Perez-Calero Yzquierdo, J. Puerta Pelayo, A. Quintario Olmeda, I. Redondo, L. Romero, M.S. Soares, A. Alvarez Fernandez Universidad Autonoma de Madrid, Madrid, Spain C. Albajar, J.F. de Troconiz, M. Missiroli, D. Moran J. Cuevas, C. Erice, J. Fernandez Menendez, I. Gonzalez Caballero, J.R. Gonzalez Fernandez, E. Palencia Cortezon, S. Sanchez Cruz, I. Suarez Andres, P. Vischia, J.M. Vizan Garcia Santander, Spain Instituto de F sica de Cantabria (IFCA), CSIC-Universidad de Cantabria, 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, E. Au ray, P. Baillon, A.H. Ball, D. Barney, M. Bianco, P. Bloch, 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, M. Dobson, B. Dorney, T. du Pree, M. Dunser, N. Dupont, A. Elliott-Peisert, P. Everaerts, F. Fallavollita, G. Franzoni, J. Fulcher, W. Funk, D. Gigi, K. Gill, F. Glege, D. Gulhan, P. Harris, J. Hegeman, V. Innocente, P. Janot, O. Karacheban16, J. Kieseler, H. Kirschenmann, V. Knunz, A. Kornmayer13, 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. Milenovic42, F. Moortgat, M. Mulders, H. Neugebauer, S. Orfanelli, L. Orsini, L. Pape, E. Perez, M. Peruzzi, A. Petrilli, G. Petrucciani, A. Pfei er, M. Pierini, A. Racz, T. Reis, G. Rolandi43, M. Rovere, H. Sakulin, C. Schafer, C. Schwick, M. Seidel, M. Selvaggi, A. Sharma, P. Silva, P. Sphicas44, A. Stakia, J. Steggemann, M. Stoye, M. Tosi, D. Treille, A. Triossi, A. Tsirou, V. Veckalns45, M. Verweij, W.D. Zeuner Paul Scherrer Institut, Villigen, Switzerland W. Bertly, L. Caminada46, K. Deiters, W. Erdmann, R. Horisberger, Q. Ingram, H.C. Kaestli, D. Kotlinski, U. Langenegger, T. Rohe, S.A. Wiederkehr Institute for Particle Physics and Astrophysics (IPA), Zurich, Switzerland F. Bachmair, L. Bani, P. Berger, L. Bianchini, B. Casal, G. Dissertori, M. Dittmar, M. Donega, 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, 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. Amsler47, M.F. Canelli, A. De Cosa, R. Del Burgo, S. Donato, C. Galloni, T. Hreus, B. Kilminster, J. Ngadiuba, D. Pinna, G. Rauco, P. Robmann, D. Salerno, C. Seitz, Y. Takahashi, A. Zucchetta National Central University, Chung-Li, Taiwan V. Candelise, 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, Thailand Turkey B. Asavapibhop, K. Kovitanggoon, G. Singh, N. Srimanobhas Cukurova University, Physics Department, Science and Art Faculty, Adana, F. Boran, S. Cerci48, S. Damarseckin, Z.S. Demiroglu, C. Dozen, I. Dumanoglu, S. Girgis, G. Gokbulut, Y. Guler, I. Hos49, E.E. Kangal50, O. Kara, A. Kayis Topaksu, U. Kiminsu, M. Oglakci, G. Onengut51, K. Ozdemir52, D. Sunar Cerci48, B. Tali48, S. Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East Technical University, Physics Department, Ankara, Turkey B. Bilin, G. Karapinar53, K. Ocalan54, M. Yalvac, M. Zeyrek Bogazici University, Istanbul, Turkey E. Gulmez, M. Kaya55, O. Kaya56, S. Tekten, E.A. Yetkin57 Istanbul Technical University, Istanbul, Turkey M.N. Agaras, S. Atay, A. Cakir, K. Cankocak 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, O. Davignon, H. Flacher, J. Goldstein, M. Grimes, G.P. Heath, H.F. Heath, J. Jacob, L. Kreczko, C. Lucas, D.M. Newbold58, S. Paramesvaran, A. Poll, T. Sakuma, S. Seif El Nasr-storey, D. Smith, V.J. Smith Rutherford Appleton Laboratory, Didcot, United Kingdom K.W. Bell, A. Belyaev59, 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 G. Auzinger, R. Bainbridge, 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 Acosta60, T. Virdee13, 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, P. Symonds, L. Teodorescu, M. Turner 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 D. Yu Brown University, Providence, U.S.A. G. Benelli, D. Cutts, A. Garabedian, J. Hakala, U. Heintz, J.M. Hogan, K.H.M. Kwok, E. Laird, G. Landsberg, Z. Mao, M. Narain, J. Pazzini, S. Piperov, S. Sagir, R. Syarif, University of California, Davis, Davis, U.S.A. R. Band, C. Brainerd, D. Burns, M. Calderon De La Barca Sanchez, M. Chertok, J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk, M. Gardner, W. Ko, R. Lander, C. Mclean, M. Mulhearn, D. Pellett, J. Pilot, S. Shalhout, M. Shi, J. Smith, M. Squires, 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, 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, P. Jandir, E. Kennedy, F. Lacroix, O.R. Long, M. Olmedo Negrete, M.I. Paneva, A. Shrinivas, 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, B. Hashemi, A. Holzner, D. Klein, G. Kole, V. Krutelyov, J. Letts, I. Macneill, M. Masciovecchio, D. Olivito, S. Padhi, M. Pieri, M. Sani, V. Sharma, S. Simon, M. Tadel, A. Vartak, S. Wasserbaech61, J. Wood, F. Wurthwein, A. Yagil, G. Zevi Della Porta University of California, Santa Barbara - Department of Physics, Santa Barbara, U.S.A. N. Amin, R. Bhandari, J. Bradmiller-Feld, C. Campagnari, A. Dishaw, V. Dutta, M. Franco Sevilla, C. George, F. Golf, L. Gouskos, J. Gran, R. Heller, J. Incandela, S.D. Mullin, A. Ovcharova, H. Qu, J. Richman, D. Stuart, I. Suarez, J. Yoo California Institute of Technology, Pasadena, U.S.A. D. Anderson, J. Bendavid, A. Bornheim, J.M. Lawhorn, H.B. Newman, T. Nguyen, C. Pena, M. Spiropulu, J.R. Vlimant, 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, S.R. Wagner Cornell University, Ithaca, U.S.A. J. Alexander, J. Chaves, J. Chu, S. Dittmer, K. Mcdermott, N. Mirman, J.R. Patterson, 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, 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, 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, S. Maruyama, 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 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, J. Konigsberg, A. Korytov, K. Kotov, P. Ma, K. Matchev, H. Mei, G. Mitselmakher, D. Rank, 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. Bilki62, W. Clarida, K. Dilsiz63, S. Durgut, R.P. Gandrajula, M. Haytmyradov, V. Khristenko, J.-P. Merlo, H. Mermerkaya64, A. Mestvirishvili, A. Moeller, J. Nachtman, H. Ogul65, Y. Onel, F. Ozok66, 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. Royon, S. Sanders, E. Schmitz, 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. Baden, O. Baron, A. Belloni, B. Calvert, S.C. Eno, 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, R. Bi, S. Brandt, W. Busza, I.A. Cali, M. D'Alfonso, Z. Demiragli, G. Gomez Ceballos, M. Goncharov, D. Hsu, Y. Iiyama, G.M. Innocenti, M. Klute, D. Kovalskyi, Y.S. Lai, 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. 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, S. Kalafut, Y. Kubota, Z. Lesko, J. Mans, S. Nourbakhsh, N. Ruckstuhl, R. Rusack, J. Turkewitz University of Mississippi, Oxford, U.S.A. J.G. Acosta, S. Oliveros E. Avdeeva, K. Bloom, D.R. Claes, C. Fangmeier, 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. M. Alyari, J. Dolen, A. Godshalk, C. Harrington, I. Iashvili, D. Nguyen, A. Parker, S. Rappoccio, B. Roozbahani Northeastern University, Boston, U.S.A. moto, R. Teixeira De Lima, D. Trocino, D. Wood Northwestern University, Evanston, U.S.A. G. Alverson, E. Barberis, A. Hortiangtham, A. Massironi, D.M. Morse, D. Nash, T. OriS. Bhattacharya, O. Charaf, K.A. Hahn, 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. Loukas, N. Marinelli, F. Meng, C. Mueller, Y. Musienko34, 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, 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, S. Higginbotham, 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.K. Jha, M. Jones, A.W. Jung, A. Khatiwada, D.H. Miller, N. Neumeister, C.C. Peng, J.F. Schulte, J. Sun, F. Wang, W. Xie Purdue University Northwest, Hammond, U.S.A. T. Cheng, 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. Padley, J. Roberts, J. Rorie, Z. Tu, J. Zabel 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, M. Foerster, J. Heideman, G. Riley, K. Rose, S. Spanier, K. Thapa Texas A&M University, College Station, U.S.A. O. Bouhali67, A. Castaneda Hernandez67, A. Celik, M. Dalchenko, M. De Mattia, A. Delgado, S. Dildick, R. Eusebi, J. Gilmore, T. Huang, T. Kamon68, R. Mueller, Y. Pakhotin, R. Patel, A. Perlo , L. Pernie, D. Rathjens, A. Safonov, A. Tatarinov, K.A. Ulmer 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. 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. M.W. Arenton, P. Barria, B. Cox, R. Hirosky, 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, J. Sturdy, S. Zaleski University of Wisconsin - Madison, Madison, WI, U.S.A. M. Brodski, J. Buchanan, C. Caillol, 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, 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, N. Woods y: Deceased China 3: Also at Universidade Estadual de Campinas, Campinas, Brazil 4: Also at Universidade Federal de Pelotas, Pelotas, 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: Now at Cairo University, Cairo, Egypt 9: Also at Zewail City of Science and Technology, Zewail, Egypt 10: Also at Universite de Haute Alsace, Mulhouse, France Moscow, Russia 12: Also at Tbilisi State University, Tbilisi, Georgia 13: Also at CERN, European Organization for Nuclear Research, Geneva, Switzerland 14: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany 15: Also at University of Hamburg, Hamburg, Germany 16: Also at Brandenburg University of Technology, Cottbus, Germany 17: Also at MTA-ELTE Lendulet CMS Particle and Nuclear Physics Group, Eotvos Lorand University, Budapest, Hungary 18: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary 19: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary 20: Also at Indian Institute of Technology Bhubaneswar, Bhubaneswar, India 21: Also at Institute of Physics, Bhubaneswar, India 22: Also at University of Visva-Bharati, Santiniketan, India 23: Also at University of Ruhuna, Matara, Sri Lanka 24: Also at Isfahan University of Technology, Isfahan, Iran 25: Also at Yazd University, Yazd, Iran 26: Also at Plasma Physics Research Center, Science and Research Branch, Islamic Azad University, Tehran, Iran 27: Also at Universita degli Studi di Siena, Siena, Italy 28: Also at INFN Sezione di Milano-Bicocca; Universita di Milano-Bicocca, Milano, Italy 29: Also at Purdue University, West Lafayette, U.S.A. 30: Also at International Islamic University of Malaysia, Kuala Lumpur, Malaysia 31: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia 32: Also at Consejo Nacional de Ciencia y Tecnolog a, Mexico city, Mexico 33: Also at Warsaw University of Technology, Institute of Electronic Systems, Warsaw, Poland 34: Also at Institute for Nuclear Research, Moscow, Russia 35: Now at National Research Nuclear University 'Moscow 36: Also at St. Petersburg State Polytechnical University, St. Petersburg, Russia 37: Also at University of Florida, Gainesville, U.S.A. 38: Also at P.N. Lebedev Physical Institute, Moscow, Russia 39: Also at California Institute of Technology, Pasadena, U.S.A. 40: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia 41: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia 42: Also at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia 43: Also at Scuola Normale e Sezione dell'INFN, Pisa, Italy 44: Also at National and Kapodistrian University of Athens, Athens, Greece 45: Also at Riga Technical University, Riga, Latvia 46: Also at Universitat Zurich, Zurich, Switzerland 47: Also at Stefan Meyer Institute for Subatomic Physics (SMI), Vienna, Austria 48: Also at Adiyaman University, Adiyaman, Turkey 49: Also at Istanbul Aydin University, Istanbul, Turkey 50: Also at Mersin University, Mersin, Turkey 51: Also at Cag University, Mersin, Turkey 52: Also at Piri Reis University, Istanbul, Turkey 53: Also at Izmir Institute of Technology, Izmir, Turkey 55: Also at Marmara University, Istanbul, Turkey 56: Also at Kafkas University, Kars, Turkey 57: Also at Istanbul Bilgi University, Istanbul, Turkey 58: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom 59: Also at School of Physics and Astronomy, University of Southampton, Southampton, United Kingdom 60: Also at Instituto de Astrof sica de Canarias, La Laguna, Spain 61: Also at Utah Valley University, Orem, U.S.A. 62: Also at Beykent University, Istanbul, Turkey 63: Also at Bingol University, Bingol, Turkey 64: Also at Erzincan University, Erzincan, Turkey 65: Also at Sinop University, Sinop, Turkey 66: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey 67: Also at Texas A&M University at Qatar, Doha, Qatar 68: Also at Kyungpook National University, Daegu, Korea with Higgs , Z and W bosons in pp collisions at 8 TeV, Phys . 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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, 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, D. Rabady, N. Rad, H. Rohringer, J. Schieck, R. Schöfbeck, M. Spanring, D. Spitzbart, 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, S. Moortgat, L. Moreels, Q. Python, K. Skovpen, S. Tavernier, W. Van Doninck, P. Van Mulders, I. Van Parijs, H. Brun, B. Clerbaux, G. De Lentdecker, H. Delannoy, G. Fasanella, L. Favart, R. Goldouzian, A. Grebenyuk, G. Karapostoli, T. Lenzi, J. 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