Search for the associated production of a Higgs boson with a single top quark in proton-proton collisions at \( \sqrt{s}=8 \) TeV

Journal of High Energy Physics, Jun 2016

This paper presents the search for the production of a Higgs boson in association with a single top quark (tHq), using data collected in proton-proton collisions at a center-of-mass energy of 8 TeV corresponding to an integrated luminosity of 19.7 fb−1. The search exploits a variety of Higgs boson decay modes resulting in final states with photons, bottom quarks, and multiple charged leptons, including tau leptons, and employs a variety of multivariate techniques to maximize sensitivity to the signal. The analysis is optimized for the opposite sign of the Yukawa coupling to that in the standard model, corresponding to a large enhancement of the signal cross section. In the absence of an excess of candidate signal events over the background predictions, 95% confidence level observed (expected) upper limits on anomalous tHq production are set, ranging between 600 (450) fb and 1000 (700) fb depending on the assumed diphoton branching fraction of the Higgs boson. This is the first time that results on anomalous tHq production have been reported.

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Search for the associated production of a Higgs boson with a single top quark in proton-proton collisions at \( \sqrt{s}=8 \) TeV

Revised: May p s = 8 TeV with a single top quark in proton-proton collisions at This paper presents the search for the production of a Higgs boson in association with a single top quark (tHq), using data collected in proton-proton collisions at a center-of-mass energy of 8 TeV corresponding to an integrated luminosity of 19.7 fb 1. The search exploits a variety of Higgs boson decay modes resulting in bottom quarks, and multiple charged leptons, including tau leptons, and employs a variety of multivariate techniques to maximize sensitivity to the signal. The analysis is optimized for the opposite sign of the Yukawa coupling to that in the standard model, corresponding to a large enhancement of the signal cross section. In the absence of an excess of candidate signal events over the background predictions, 95% con dence level observed (expected) upper limits on anomalous tHq production are set, ranging between 600 (450) fb and 1000 (700) fb depending on the assumed diphoton branching fraction of the Higgs boson. This is the rst time that results on anomalous tHq production have been reported. Hadron-Hadron scattering (experiments); Higgs physics; Top physics - The CMS collaboration 1 Introduction 2 The CMS detector, event reconstruction, and simulation H ! 3.2.1 3.2.2 3.2.3 3.3.1 3.3.2 3.4.1 3.4.2 3.4.3 3 Description of the analyses 3.1 3.2 channel 3.3 H ! WW channel 3.4 H ! + channel Event selection Event reconstruction under tHq and tt hypotheses Event classi cation and signal extraction Background modeling Event selection and signal extraction Event selection Background modeling Signal extraction 4 Systematic uncertainties 5 Results 6 Summary The CMS collaboration 1 Introduction A Selected distributions of inputs to the multivariate discriminants The discovery of a Higgs boson by the ATLAS and CMS experiments in 2012 [1{3] opened a new eld for exploration in particle physics. The Higgs boson was discovered through its direct coupling to other known heavy bosons (W, Z) and its indirect coupling to photons, which in the standard model (SM) occurs via a loop involving W bosons or top quarks. Strong evidence for the Higgs boson coupling to fermions has also been established [4, 5]. Moreover, there is evidence of the Higgs boson coupling to bottom quarks from the Tevatron [6] and from CMS [7], and to tau leptons from ATLAS [5] and CMS [8]. It is now critical to test whether the observed Higgs boson is the SM Higgs boson by studying its coupling to other elementary particles. { 1 { b q’ t q b W H W H q’ t typically radiated from the heavier particles of the diagram, i.e. the W boson (left) or the top quark (right). HJEP06(21)7 The coupling of the new boson to the top quark is of special interest. Because of its very large mass [9] the top quark is widely believed to play a special role in the mechanism of electroweak symmetry breaking. Physics beyond the SM could modify the top quark Yukawa coupling without violating current experimental constraints. The most straightforward way to study this coupling is through the measurement of top quark-antiquark pair production in association with a Higgs boson (ttH), as was recently done by ATLAS and CMS [10{13]. Interactions of the Higgs boson with the top quark can also be probed by studying the associated production of a single top quark and a Higgs boson, which proceeds mainly through t-channel diagrams (tHq) [14] in which the Higgs boson is emitted either from an internally exchanged W boson or from a top quark, as shown in gure 1. The associated single top quark and Higgs boson production can also be accompanied by a W in the nal state (tHW). As the couplings of the Higgs boson to the W boson and the top quark have opposite signs in the SM, these two diagrams interfere destructively. The cross section for single top quark plus Higgs boson production via the tHq process in pp collisions at a center-of-mass energy of 8 TeV has been calculated to be about 18 fb at next-to-leading-order (NLO) [15]. Anomalous coupling of the Higgs boson to SM particles would modify the expected rate of tHq events [16]. A number of models have been proposed that would modify the interference between the diagrams involving ttH and WWH couplings. For example, a negative coupling of the Higgs boson to the top quark (Ct = 1) would give rise to about a 15-fold increase in the tHq cross section. Recent work suggests the investigation of anomalous tHq production in events with a pair of photons [17, 18], b quarks [15], or multiple leptons in the nal state [18]. The same interference probes the CP-violating phase of the top quark Yukawa coupling [19{21]. Also, a large rate of single top quark plus Higgs boson events could signal the direct production of heavy new particles as predicted in composite and little Higgs models [22], or new physics showing up as Higgs boson mediated avor changing neutral currents [23]. The apparent exclusion of the Ct = 1 case based on the value of the branching fraction for H ! only holds under the assumption that no new particles contribute to the loop in the main diagram for that decay [24]. This paper reports the rst search for tHq production, focusing on the scenario where the coupling of the Higgs boson to the top quark has a sign opposite to that predicted { 2 { by the SM, using data collected by the CMS experiment at the CERN LHC. Four Higgs boson decay modes are explored. Section 2 describes the CMS detector, the reconstruction algorithms, and the simulated samples. Section 3 outlines the selection, background modeling, and signal extraction techniques for analyses based on H decay channels with photons, hadrons, and multiple leptons. Section 4 describes the systematic uncertainties a ecting the search results. Finally, the procedure for combining the results of the searches is presented in section 5. The results are summarized in section 6. 2 The CMS detector, event reconstruction, and simulation HJEP06(21)7 The central feature of the CMS apparatus is a superconducting solenoid of 6 m internal diameter, providing an axial magnetic eld of 3.8 T. Within the magnet volume, there are a silicon pixel and strip tracker, a lead tungstate crystal electromagnetic calorimeter (ECAL), and a brass and scintillator hadron calorimeter (HCAL), each composed of a barrel and two endcap sections. The tracking detectors provide coverage for charged particles within pseudorapidity j j < 2:5. The ECAL and HCAL calorimeters provide coverage up to j j < 3:0. The ECAL is divided into two distinct regions: the barrel region, which covers j j < 1:48, and the endcap region, which covers 1:48 < j j < 3:00. A quartz- ber forward calorimeter extends the coverage further up to j j < 5:0. Muons are measured in gas-ionization detectors embedded in the steel ux-return yoke outside the solenoid. A 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. [25]. The particle- ow (PF) event reconstruction algorithm [26, 27] consists of reconstructing and identifying each single particle with an optimized combination of all subdetector information. The energy of charged hadrons is determined from a combination of their momentum measured in the tracker and the matching ECAL and HCAL energy deposits. Photon PF candidates are reconstructed from the energy deposits in the ECAL, grouping the individual clusters into a supercluster. The superclustering algorithms achieve an almost complete reconstruction of the energy of photons (and electrons) that convert into electron-positron pairs (emit bremsstrahlung) in the material in front of the ECAL. The photon candidates are identi ed within the ECAL ducial region j j < 2:5, excluding the barrel-endcap transition region 1:44 < j j < 1:57, where photon reconstruction is suboptimal. Isolation requirements are applied to photon candidates by looking at neighboring particle candidates. In the barrel section of the ECAL, an energy resolution of about 1% is achieved for unconverted or late-converting photons in the tens of GeV energy range. The remaining barrel photons have a resolution of about 1.3% up to a pseudorapidity of j j = 1, rising to about 2.5% at j j = 1:4. In the endcaps, the resolution of unconverted or late-converting photons is about 2.5%, while the remaining endcap photons have a resolution between 3 and 4%. Additional details on photon reconstruction and identi cation can be found in refs. [28, 29]. Electrons with pT greater than 7 GeV are reconstructed within the geometrical acceptance of the tracker, j j < 2:5. The electron momentum is determined from the combination of ECAL and tracker measurements. Electron identi cation relies on a multivariate (MVA) { 3 { technique, which combines observables sensitive to the amount of bremsstrahlung along the electron trajectory, the spatial and momentum matching between the electron trajectory and associated clusters, and shower shape observables [29, 30]. In order to increase the lepton e ciency, the H ! leptons analysis uses a looser selection for the MVA discriminant than do the other analysis channels. Muons with pT > 5 GeV are reconstructed within j j < 2:4 [31]. The reconstruction combines information from both the silicon tracker and the muon spectrometer. The PF muons are selected from the reconstructed muon track candidates by applying minimal requirements on the track components in the muon and tracker systems and taking into account matching with energy deposits in the calorimeters [32]. Particles reconstructed with the PF algorithm are clustered into jets using the anti-kT algorithm with a distance parameter of 0.5 [33, 34]. Jet energy corrections are applied to account for the non-linear response of the calorimeters to the particle energies and other detector e ects. These include corrections due to additional interactions within a beam crossing (pileup), where the average energy density from the extra interactions is evaluated on an event-by-event basis and the corresponding energy is subtracted from each jet [35]. The jet energy resolution is also modi ed in simulation with a smearing technique to match what is measured in data [36]. In all the nal states that are studied, jets with j j < 5:0 and transverse momentum down to 20 GeV are considered, though the nal selection depends on the speci c analysis. The hadronic decay of a lepton ( h) produces a narrow jet of charged and neutral hadrons, which are mostly pions. Each neutral pion subsequently decays into a pair of photons. The identi cation of h jets begins with the formation of PF jets by clustering charged hadron and photon objects via the anti-kT algorithm. Additional details on reconstruction and identi cation can be found in ref. [37]. For this analysis, decays involving one or three charged hadrons are used. The missing transverse momentum vector p~miss is de ned as the negative projection T on the plane perpendicular to the beams of the vectorial sum of the momenta of all reconstructed PF candidates in an event. Its magnitude is referred to as ETmiss. Jets are identi ed as originating from b quark production (b tagged) using an algorithm based on the combined properties of secondary vertices and track-based lifetime information, known as the combined secondary vertex (CSV) tagging algorithm [38, 39]. Di erent working points are chosen for the various analyses: a loose working point providing an e ciency for b quark jets of about 85% and a light- avor jet misidenti cation (mistag) rate of 10%, a medium working point with 70% b-quark jet e ciency and 1% light- avor jet mistag rate, and a tight working point with 50% b-quark jet e ciency and 0.1% lightavor jet mistag rate. Only jets with j j < 2:4 (within the CMS tracker acceptance) are identi ed with this technique. A number of Monte Carlo (MC) event generators are used to simulate the signal and backgrounds. Signal events are produced with MadGraph (v5.1.3.30) [40], with a non-SM Yukawa coupling of Ct = 1, and then passed through pythia (v6.426) [41] to add an underlying event and to perform parton showering and hadronization. The masses for the top quark and Higgs boson are set to 173 and 125 GeV, respectively. The CTEQ6L1 [42] { 4 { parton distribution function (PDF) set is used. The sample is produced either using the ve- avor scheme or the four- avor scheme. Processes such as tt plus additional particles (heavy- avor jets, light- avor jets, gluons, or bosons), W/Z plus jets, and di- and tri-boson production are all generated with MadGraph. Single top quark plus jets and inclusive Higgs boson production are generated with powheg (v1.0, r1380) [43, 44]. Both multijet (QCD) and ttH production are simulated with pythia. The detector response is simulated using a detailed description of the CMS detector based on the Geant4 package [45]. All processes have been normalized to the most recent theoretical cross section computations. The simulated samples are reweighted to represent the pileup distribution as measured in the data. To match the performance of reconstructed objects between data and simulation, the latter is corrected with a set of data/MC scale factors. Leptons are corrected for the di erence in trigger e ciency, as well as in lepton identi cation and isolation e ciency. Corrections accounting for residual di erences between data and simulation are applied to the ECAL energy before combining the energy with the momentum determined from the tracker for electrons. Similar corrections are applied to the muon momentum. 3 Description of the analyses The t-channel single top quark plus Higgs boson process has, at tree level, three particles in the nal state: a top quark, a Higgs boson, and an additional quark jet, which tends to be emitted in the forward region. A spectator b quark is produced through splitting of a gluon in the incoming proton, resulting in an additional bottom- avor jet (b jet) that can enter the detector acceptance. Other Higgs boson production mechanisms, such as ttH, are considered as background. All of the analyses make use of the leptonic decay of the top quark, which yields a high-momentum lepton and an identi able b jet. Requiring these objects in the event improves the signal-to-background ratio for each analysis. The analyses are distinguished by the Higgs boson decay channel, as described in the following subsections. 3.1 H ! channel The diphoton branching fraction of the Higgs boson in the standard model is very small (0.23%) but the diphoton nal state allows very good background rejection thanks to the excellent diphoton invariant mass resolution provided by the CMS detector. A negative top quark Yukawa coupling would not only enhance the yield of tHq events, but also more than double the rate of Higgs bosons decaying to diphotons. Thus the diphoton nal state of the Higgs boson decay in tHq events is expected to be highly sensitive to the top quark Yukawa coupling. The data for the diphoton analysis are collected using diphoton triggers with two di erent photon identi cation schemes. One requires calorimetric identi cation based on the electromagnetic shower shape and isolation of the photon candidate. The other requires only that the photon has a high value of the R9 shower shape variable, which is de ned as the ratio of the energy contained in a 3 3 array of ECAL crystals centered on the most energetic deposit in the supercluster to the energy of the whole supercluster. The { 5 { ET thresholds at trigger level are 26 (18) GeV and 36 (22) GeV on the leading (subleading) photon depending on the running period. To maintain a high signal e ciency, trigger paths based on both photon identi cation schemes are combined in the o ine data selection. The event selection requires the presence of two photons, with the transverse momentum of the leading photon (pT1) greater than 50 m =120, where m is the reconstructed invariant mass of the diphoton system, and that of the subleading photon greater than 25 GeV . The stringent requirement on pT1 is found to have very high e ciency (>98%) for the signal and reduces the contributions of nonresonant backgrounds. The presence of exactly one isolated electron or muon with pT > 10 GeV and at least one b quark jet with pT > 20 GeV are required to identify the leptonic decay of the top quark. If more than one jet is b tagged, the one with the largest transverse momentum is chosen as the b jet candidate from the top quark decay. Finally, the highest pT jet in the event that is not b tagged must have pT > 20 GeV and j j > 1. After applying these requirements, a multivariate method is used to further reduce the ttH contribution. A Bayes classi er, L, is constructed as the ratio of signal over signal plus background likelihoods for a chosen set of discriminating observables: L(x) = LS(x) LS(x) + LB(x) Li(x) = Y pij(xj); j (3.1) (3.2) For each event the signal (LS) and background (LB) likelihoods are calculated as the product of the respective signal and background probability density functions (p), evaluated at the observed values (xj): where i stands for each signal or background process and j for each variable considered. The classi er is built from the following variables: the jet multiplicity in the event; the transverse mass of the top quark using the lepton, the candidate b jet and the missing transverse momenta; the pseudorapidity of the light quark candidate; the rapidity gap between the lepton and the forward jet; and the charge of the lepton candidate. The last observable is chosen as the pp initial state is more likely to produce a top quark rather than a top antiquark. All these variables are observed to discriminate well between simulated ttH and tHq events [46]. The linear correlation coe cients for the input variables are all less than 10% for both signal and background processes. The classi er value is required to be greater than 0.25, to suppress the ttH contribution to the signal sample. This requirement retains about 90% of the signal events. The invariant mass of the diphoton system is the primary search variable for a signallike excess, as the signal would appear as a narrow diphoton resonance centered at the known Higgs boson mass mH = 125 GeV. The backgrounds can be classi ed according to their resonant or nonresonant behavior in the diphoton system; a di erent approach has been adopted to estimate the rate from each category. Resonant backgrounds give rise to a Higgs boson decaying to two photons in the nal state. These backgrounds are dominated by the ttH process and also include Higgs { 6 { Data ttH VH Data but for the likelihood discriminant cut (left), and for events passing the full selection (right). The data (black markers) are compared to the MC simulation (stacked histograms). No events are observed after the requirement on the likelihood discriminant. Process events with diphoton mass in the 122{128 GeV range. The additional contributions to the ttH and VH processes arising from the enhanced Higgs to diphoton branching fraction due to the Ct = 1 assumption are marked with a dagger (y). production in association with a vector boson (VH); they appear as an additional contribution under the expected signal peak, and are evaluated using MC simulation. Nonresonant backgrounds are evaluated from the m sidebands. The main nonresonant background processes include diphoton production in association with jets ( +jets), single-photon production in association with jets ( +jets), and diphoton events produced in association with top quarks (tt , t ). The signal region is de ned as the 3 GeV range around the nominal Higgs boson mass. While the contribution of resonant backgrounds is taken from the simulation, nonresonant backgrounds are evaluated by counting the events in the m sidebands 100 GeV < m < (mH 3 GeV) and (mH + 3 GeV) < m < 180 GeV, which have negligible signal contamination. The event yields in the signal region are shown in table 1. The selection has an expected e ciency of 17% for tHq events in the diphoton decay channel. Figure 2 shows the m spectrum for events passing the event selection before and after the likelihood requirement. { 7 { No events pass the selection. In order to model the nonresonant background shape using data, a control region with relaxed b tagging requirements is de ned. The functional form chosen for the m distribution of background events is an exponential, and the uncertainty in the knowledge of the background shape is assessed by de ning an orthogonal control region in which the isolation requirements on one of the two photons are inverted. This uncertainty amounts to 33%. The number of events observed and the systematic uncertainties are later used to set a limit on the rate of tHq production. The search for tHq in the H ! bb decay nal state bene ts from the large Higgs to bottom-antibottom quarks branching fraction, but su ers from signi cant backgrounds from tt events. 3.2.1 Event selection The analysis is performed with data collected with two triggers: one requiring an electron candidate with pT > 27 GeV and j j < 2:4, the other requiring a muon candidate with pT > 24 GeV and j j < 2:1. In each case the lepton must be isolated. The e ect of the triggers is emulated in all simulated data sets. An event in the electron (muon) channel is required to contain exactly one electron (muon) candidate with pT > 30 (26) GeV and pass a set of identi cation criteria labeled as \tight". In order to reject Drell-Yan (DY) and other processes with multiple prompt leptons, events are rejected if additional leptons exist that pass a looser criterion. The signal nal state in this channel is expected to contain at least ve quarks: two b quarks from the Higgs boson decay, one b quark each from the top quark decay and from the strong interaction, and a forward light quark from the t-channel process. Each event is thus required to contain at least four jets with pT > 30 GeV and the threshold for counting additional jets beyond the fourth is chosen to be 20 GeV . Jets with j j > 2:4 are considered only if they have pT > 40 GeV. A tight working point of the CSV b tagging algorithm is chosen to suppress the large background from top quark pair production, which contains a smaller number of genuine b quarks than the signal process. This working point has typical tagging e ciencies of 55% for b jets and 0.1% for light- avor jets. To reject multijet events, a missing transverse energy selection is applied with thresholds optimized per channel: ETmiss > 45 GeV in the electron channel and ETmiss > 35 GeV in the muon channel. As the b quark produced in the strong interaction of the tHq process is often forward and falls outside the acceptance of the detector, two analysis samples are de ned: one of events containing at least four jets with three of them b-tagged and one of events containing at least ve jets with four of them b-tagged. Additionally, a two-tag control sample dominated by tt plus jets events is used for validation of event reconstruction and signal extraction techniques described in the following section. After this event selection is applied, the sample is dominated by the tt plus jets background as well as other background contributions [47]. The three-tag sample has an expected signal-to-background ratio of 0.7%. The four-tag sample has an improved ratio of approximately 2% but su ers from a limited number of events. The background kinematic { 8 { distributions and normalizations are taken from simulation and are adjusted in the nal t, taking into account all systematic uncertainties, which are described in more detail in section 4. A cross-check approach that uses control data samples to model the dominant tt plus jets background in the signal regions by employing b-tagging and mistagging e ciencies in the two-tag control sample gives consistent results. Event reconstruction under tHq and tt hypotheses The selected samples are dominated by tt plus jets production, as shown in section 3.2.3. An arti cial neural network (NN) is employed to separate the signal process from background, based on the features of tHq and tt plus jets events. Prior to this, a correspondence between reconstructed jets and the nal-state objects must be built in order to de ne the input variables to the NN. For this purpose, each event is reconstructed under two hypotheses: (1) that it is a tHq signal event, or (2) that it is a tt plus jets background event. Simulated events are used to assess the correctness of the assignment of jets to quarks. For the jet assignment under the tHq hypothesis in a simulated tHq event, all possible ways to assign four reconstructed jets to the four nal state quarks from tHq ! 3bq` are considered, where a correct event interpretation is present in the case where four jets can be R = p ( )2 + ( )2 = 0:3. matched to the appropriate quarks within a cone of radius If the distance between at least one quark and its assigned jet is larger than this threshold, the event interpretation is agged as wrong. The total number of possible interpretations is reduced by additional requirements: because of b tagging considerations, b quarks can only be associated with central jets (j j < 2:4), while only a jet failing the b tagging requirement can be assigned to the light recoil quark. A NN is trained on tHq events to distinguish between correct and wrong interpretations with variables employing kinematic characteristics of the signal, like the pT of the softest jet from the Higgs boson decay, the j j of the recoil jet, and the R between the reconstructed top quark and the Higgs boson. Other variables include information such as b tagging or the reconstructed jet charge. The interpretation chosen for use in the analysis is the one that gives the largest NN response from all possible tHq jet assignments. Similarly, another NN is used for the interpretation of events under the assumption that they originate from semileptonic tt decays. The NN is trained with tt ! 2b2q` simulated events, using both correct and wrong quark jet assignments in analogy with the tHq jet assignment described above. The number of possible jet-quark combinations is restricted by requiring that only b-tagged jets can be assigned to the two b quarks. The set of variables used under a tt event interpretation is similar to the one of the tHq event interpretation. It makes use of kinematic relations between objects, such as the R between the b and W boson from the hadronically decaying top quark, or the di erence between the reconstructed top quark mass and W boson mass in the hadronic top quark decay. It also employs b tagging information and relations between the jet and lepton charges. The jet assignment yielding the largest NN response is chosen as the event interpretation under the tt hypothesis. Additional details regarding the event interpretation can be found in ref. [47]. { 9 { The tHq and tt plus jets reconstruction algorithms described above are carried out on every event passing the selection criteria. This allows the construction of two sets of observables, where one set describes the event under the tHq hypothesis and the other the event under the tt hypothesis. These two sets, together with the lepton charge, form the list of input variables for the nal NN, which classi es events as signal- or background-like: j j of the recoil jet; number of b-tagged jets among the two jets from the Higgs boson decay; pT of the Higgs boson; pT of the recoil jet; R between the two light- avor jets from the hadronic top quark decay; reconstructed mass of the hadronically decaying top quark; number of b-tagged jets among the two light- avor jets from the hadronic decay of the top quark; and lepton charge [47]. Figure 3 shows the distributions of the nal event classi er in the three-tag and fourtag samples, separated by lepton avor. The distributions of the NN outputs are used to extract the signal and to derive the upper limit on the cross section for tHq production. The normalizations of the distributions are taken from the result of a maximum likelihood t where each background and the signal process are allowed to oat within the assigned systematic and statistical uncertainties. The resulting distributions show a good agreement with data and residual di erences are well covered by the total uncertainties. 3.3 H ! WW channel The Higgs boson decay to two W bosons (with one boson o -shell) has the second-largest branching fraction in the standard model. The associated tHq, H ! WW and t ! Wb nal state allows several combinations of leptonically and/or hadronically decaying W bosons. Two channels are exploited here, in which either all three W bosons decay leptonically, or the pair of W bosons with equal charge, resulting in a signature of either three leptons (electrons or muons), or two same-sign leptons with two light quark jets. The tHW process can also result in this set of leptons. In the tHq process both the tri- and dilepton signatures are accompanied by a b quark and a light- avor forward jet. In addition, a signi cant ETmiss can be expected because of the undetected neutrinos from the leptonic W decays. While the leptonic branching fraction of the W is relatively small, the presence of multiple leptons and identi ed b jets in the nal state reduces the number of background events. The tHq search in this nal state has some acceptance for events where leptons, stemming either from the decay of one or more W bosons, or from Higgs boson decays, give rise to electrons or muons in the decay chain. Events with hadronically decaying leptons are considered separately in section 3.4. The trigger used to select the analysis sample requires the presence of two high-pT electrons or muons. The pT thresholds are 17 and 8 GeV for the leading and subleading leptons, respectively. The trigger e ciency for signal events with two high-pT leptons is higher than 98%, and almost 100% for those with three leptons. Various SM processes contribute as background in the signal region: diboson (WZ, WW, ZZ, W W qq) and triboson (WWW, WWZ, WZZ) production, associated production of tt with a boson (ttW , ttZ, ttH, tt , and tt ), tt with two W bosons (ttWW), CMS b-tagged jets are shown in the upper (lower) row. The left (right) column shows events containing a high-pT electron (muon). All backgrounds are normalized to the output of a maximum likelihood t of the corresponding distributions. \EW" indicates electroweak backgrounds: single top quark, W/Z boson plus jets, and di- and tri-boson production. The line shows the expected contribution from the tHq process with Ct = 1 multiplied by the factor indicated in the legend. In the box below each distribution, the ratio of the observed and predicted event yields is shown. The shaded band represents the post- t systematic and statistical uncertainties. single top quark associated production with a Z boson (tZq), and production of same-sign W bosons via double parton scattering (WW). 3.3.1 Background modeling While diboson backgrounds are produced with a relatively large cross section, their contribution is strongly reduced by imposing a veto on lepton pairs compatible with a Z boson decay in the trilepton channel (Z boson veto) or by vetoing additional leptons in the event in the same-sign dilepton channel. Furthermore, the requirement of a b-tagged or forward jet suppresses contributions from diboson processes. The rate of DY events is strongly reduced by the Z boson veto (trilepton channel) and the third lepton veto (same-sign dilepton channel). Triboson production has a very small cross section and is further reduced by rejecting events with extra leptons. In addition, both diboson and triboson production do not generally include forward jets or jets from b quark decays. Associated production of tt and vector bosons (ttW , ttZ) or Higgs boson (ttH), although having fairly small cross sections, have high lepton and jet multiplicities as well as two nal-state b quarks and can contribute signi cantly. Because of its very large cross section, tt production is expected to be the major source of background for both channels, when additional leptons are produced in the decay of B hadrons or when light jets are misidenti ed as leptons. An additional background in the case of same-sign dileptons arises when the charge of a lepton in events with an opposite-sign lepton pair is misidenti ed. This happens not so much because of track misreconstruction, but rather because of strongly asymmetric conversions of hard bremsstrahlung photons emitted from the initial lepton, and is therefore much more likely to occur for electrons than for muons. In the case where the original electron loses most of its energy to the radiated photon, and the conversion daughter with opposite charge carries most of the momentum, the resulting track can have opposite curvature to the original lepton. Furthermore, the same-sign channel has a contribution from the associated production of two same-sign W bosons and two light quark jets, W W qq. Backgrounds involving nonprompt leptons and charge misidenti cation are estimated using data-driven methods. All the remaining processes are estimated from MC simulation, corrected for data/MC scale factors and pileup distribution, using NLO cross sections where available. The \tight-to-loose" method is used for estimating the tt background. It is based on de ning two lepton selection levels: the tight criteria, corresponding to the full lepton identi cation used in the signal selection; and a looser selection designed to accept more background leptons. The probability of a nonprompt lepton to pass the tight cut after passing the loose cut (the tight-to-loose rate, f ) is then extracted from data control samples. Nonprompt leptons include real leptons from heavy avor hadron decays, jets from light quarks misreconstructed as leptons, as well as photon conversions. Finally, the signal selection is extended with the loose lepton selection, and the additional event yield is weighted to arrive at an estimate for the expected contribution from nonprompt leptons. Events with one tight and one loose lepton obtain a weight of f =(1 f ), whereas events with two loose leptons are weighted by f1 f2= (1 f1)(1 f2) . The method assumes f to be consistent between signal and control samples, and that there are only two categories of leptons with consistent e ciencies of passing the tight selection: prompt leptons from W and Z boson decays, and nonprompt leptons. The tight-to-loose rate is de ned as the ratio between Ntight and Nloose, where Nloose is the number of candidate leptons that pass the loose selection, based on relaxed isolation and impact parameter requirements, and Ntight is the number of loose leptons that also ful ll the tight requirements de ned in the analysis. The rate f is measured in a data sample enriched in background leptons, and parametrized as a function of the pT, , and lepton avor. For the lepton selections used, the electron tight-to-loose rate varies in the range 1{13%, whereas the muon rate varies between 5{23%. Similarly, the contribution of events with a misidenti ed lepton charge to the samesign channel is estimated using the charge misidenti cation probability and the yield of opposite-sign pairs in the signal selection. The electron charge misidenti cation probability is extracted from an independent data sample based on Z boson decays, and cross checked with expectations from MC simulation. It is binned in pT and , and ranges from about 0.03% in the barrel to between 0.08% and 0.28% in the endcap. The muon charge misidenti cation probability in the relevant pT range is negligible. Event selection and signal extraction A relatively loose selection is applied to maintain a large signal e ciency while suppressing the main backgrounds. For the dilepton analysis, the presence of two same-sign leptons with pT > 20 GeV and invariant mass m`` > 20 GeV is required. No additional leptons can be present in the event. At least one central jet with pT > 25 GeV is required to be tagged with the CSV algorithm using a loose working point. The event must also contain at least one forward jet (j j > 1:0) and an additional central jet (j j < 1:0), both with pT > 25 GeV. For the trilepton analysis, the thresholds for the three lepton transverse momenta are pT > 20, 10, and 10 GeV . To suppress contamination from DY events, the reconstructed dilepton invariant mass closest to the Z boson mass (mZ) must respect the constraint jm`` of multiple neutrinos, hence a cut on ETmiss > 30 GeV is applied. Only events with one jet mZj > 15 GeV. The presence of large missing transverse energy suggests the presence with pT > 25 GeV and j j < 2:4 tagged with the medium working point of the CSV algorithm are selected, and at least one forward jet with pT > 25 GeV and j j > 1:5 must be present. The production cross section times branching fraction for the signal (assuming Ct = 1) is just a few fb, resulting in a fairly small signal-to-background fraction even for a tight selection. Therefore a multivariate analysis method is used to build a Bayes classi er as in eqs. (3.1) and (3.2) to further reduce backgrounds. A search for an optimal set of variables is performed, to nd those that best separate the signal and the backgrounds. The discriminating variables can be put into three broad categories: forward activity, jet and b jet multiplicity, and lepton kinematic properties and charge. The variables to enter the classi er are chosen to be minimally correlated while providing good discrimination power. For the same-sign lepton nal state, the following set of variables has been chosen: the scalar sum of the pT of all the jets; the jet multiplicity; the medium b-tagged jet multiplicity; the j j value of the leading jet with j j > 1:0; the value between the most forward jet and second-most forward jet or lepton; the charge of the leptons; the azimuthal angle di erence between the two leptons ( ``); and the pT of the trailing lepton. In the case of the trilepton nal state the selected variables are: the multiplicity of untagged central jets (with j j < 1:5); the number of forward jets with j j > 2:4; the total sum of the charges of the three leptons; the minimum value of R between the leptons in the event; and the value between the b-tagged jet and the most forward jet. To derive an upper limit on the signal production cross section for Ct = 1, a maximum likelihood t of the classi er output is then performed in all three channels. Table 2 shows the observed data yields and the post- t expected number of signal and background events, { 13 { e HJEP06(21)7 tH( )W (Ct = tH(WW)W (Ct = tH( )q (Ct = tH(WW)q (Ct = Total signal (Ct = 1) 1) 1) 1) 1) W W qq WZ, WW, ZZ Rare SM bkg. tt tt ttZ ttH ttW Charge misid Nonprompt Total background 112:1 Data 117 0:13 0:47 0:90 3:73 5:22 6:03 8:83 2:57 1:04 2:02 2:87 14:85 3:24 6:96 63:7 0:14 0:48 0:91 3:84 3:98 0:85 3:25 1:23 0:42 0:60 0:50 3:32 0:47 1:76 12:5 13:5 0:10 0:28 0:59 2:55 3:53 4:60 5:47 1:40 0:50 0:09 2:23 10:18 2:26 33:3 60:1 | 66 shown separately, as well as expected events where the Higgs boson decays to W bosons, or to tau leptons. Uncertainties include systematic and statistical sources. \Rare SM" comprises VVV, tbZ, ZZ, ttWW, and WW processes for the dilepton channels, and WVV for the trilepton channel. where the trilepton channel, ```, consists of eee, ee , e, and nal states. The post- t classi er output for all the channels is shown in gure 4. 3.4 H ! + channel The previous section presented a strategy for identifying tHq events that captured events with leptonically decaying tau leptons. An orthogonal strategy is devised to analyze signal events with a reconstructed tau lepton, through its decay to hadrons ( h). The analysis described here is based on two nal states with three reconstructed leptons, e h and h . These nal states are chosen to select signal events where the two leptons from the Higgs boson decay give rise to an e h or h nal state and the top quark decay produces the third lepton. The major SM background processes that can lead to the same lepton nal state include WZ, ZZ, ttH, and tt + W=Z production. The contributions from reducible backgrounds include tt, single top, W+jets, Z+jets, and multijet production. These contributions are estimated using events from control samples in the data. 19.7 fb-1(8 TeV) Data ven 20 15 10 5 0 tsne 50 v 40 30 20 10 e±μ± channel μ±μ± channel 3-lepton channel E E (right). In the box below each distribution, the ratio of the observed and predicted event yields is shown. The gray band represents the post- t systematic and statistical uncertainties. 3.4.1 Event selection Candidate events are collected using either e or triggers, depending on the nal state. In the nal event selection, the leading (subleading) electron or muon is required to have p `T > 20 (10) GeV. Electrons (muons) are required to have j j < 2:5 (2:4) and to pass basic identi cation requirements. To suppress secondary leptons from b- avored hadron decays, an isolation classi er is computed with boosted decision trees using variables based on impact parameters with respect to the reconstructed primary interaction vertex (de ned as the vertex with highest P p 2T of its associated tracks), variables related to the isolation of the lepton, and variables related to the reconstructed jet closest to each lepton [10]. In addition, either the electron and muon in the e h nal state or the two muons in the h nal state are required to have equal charges. This same-sign requirement suppresses contributions from backgrounds with prompt opposite-sign dileptons and additional jets that can be misidenti ed as hadronic tau leptons, such as Z= + fake jet and ! + tt=Z ! + fake jet. The selected leptons (e, , and h) are required to be at least 0.5 apart in R. To reduce contributions from ZZ and tt Z backgrounds, events with additional isolated electrons and muons are rejected. The h candidate, reconstructed as described in section 2, is required to have pT > 20 GeV, j j < 2:3, and to pass identi cation and isolation criteria to reject misidenti ed h candidates from jets, electrons, or muons [8]. The charge of the h candidate is required to be opposite to that of other leptons, e or . To suppress background events without b quark jets, the presence of at least one jet with pT > 20 GeV and j j < 2:4 identi ed as coming from a b quark with the medium working point of the CSV algorithm is required. This requirement particularly reduces the contamination from Z ! +jets backgrounds. 3.4.2 Background modeling The signal processes as well as irreducible background processes with the same lepton nal state are modeled using simulated events. These irreducible backgrounds include WZ, ZZ, ttH, and tt+W=Z production. The simulation is corrected for di erences between data and simulation, including the distribution of pileup interactions, the e ciencies for the leptons to pass trigger, identi cation, and isolation criteria, and the identi cation e ciency for b quark jets. The contributions from reducible background processes are estimated using a similar tight-to-loose method as discussed in section 3.3.1. The contributions from events where either the charge of an electron or muon is misreconstructed or the h candidate is misidenti ed are negligible. Therefore, three control samples are de ned where one or both leptons fail the tight identi cation and isolation criteria, but pass all other selections: (i) one of the leptons fails the tight criteria; (ii) the other lepton fails the tight criteria; and (iii) both leptons fail the tight criteria. The tight-to-loose rates (f ) for jets misidenti ed as electrons or muons are measured in control regions enriched in W+jets and tt events. The selection criteria for these control regions di er from the signal selection by requiring the transverse mass of the leading isolated `-ETmiss system to be greater than 35 GeV and by requiring that there be no selected h leptons, making the selection orthogonal to the signal sample. The rate f is parameterized based on the lepton pT and the number of jets with pT > 20 GeV in the event, using the k-nearest neighbor algorithm [48]. The small contributions from genuine isolated leptons from WZ, ZZ, and tt + Z=W events in the control region are estimated using simulated samples and subtracted. For two leptons `1 and `2 with rates f1 and f2, the spectra of the reducible background contributions in the signal region are estimated by weighting events in the regions where only `1 or `2 fail the tight selection criteria by f1 or f2, respectively, and events in the region where both leptons fail the tight selection criteria by f1 f2. This procedure is conceptually identical to the one described in section 3.3.1. The reducible background estimation is validated in a control region where the h candidates fail the tight isolation criteria. 3.4.3 Signal extraction To extract the signal contribution, a multivariate method is used that combines the discrimination power of several variables. The signal extraction is performed with a linear discriminant, also known as Fisher discriminant, as implemented in the TMVA package [48]. Because of the small number of simulated and estimated background events in the signal region, the Fisher discriminant is trained using events from a control region with the isolation criteria inverted. This provides a su cient number of training events and avoids overtraining from the events in the signal region, thereby improving the nal expected sensitivity of the analysis. The Fisher discriminant is trained using ten input variables making use of (i) the forward jet present in tHq production, (ii) the expectation of only one b quark jet as opposed to background processes including a tt pair, and (iii) other kinematic di erences between the tHq and the background processes. The training variables are: j j of the jet with the largest j j value and pT > 20 GeV, j j of the jet with the largest j j value and pT > 30 GeV, \centrality" (the ratio of the pT sum of all selected objects and the energy sum), number of b jets, pT of the leading b jet, Data 10 x tHq (Ct=-1) ttW/Z Reducible ttH Diboson Stat. unc. n n E E n i /tsb 8 6 5 4 3 2 1 0 −1 Data 10 x tHq (Ct=-1) ttW/Z Reducible ttH Diboson Stat. unc. eμτh μμτh −0.5 0 h channel (right). The dashed line gives the expected contribution Process tainties include all systematic uncertainties added in quadrature, including uncertainties due to the limited numbers of simulated events or events in control data samples. number of jets with pT > 30 GeV, e h invariant mass ( h mass with the leading muon in the mass ( h channel), h mass ( h mass with the subleading muon in the h channel), e mass in the h channel), and ETmiss. The training is performed assuming the tHq process as a signal and the rest of the processes as background. The tHW process is not considered as a part of the signal in the training because of its background-like shape, but considered as a part of signal for the signal extraction. The signal extraction is performed using a combined maximum likelihood t of the Fisher discriminant distributions in the two channels. Figure 5 shows the nal distributions of the discriminant in the e h and h categories. The expected and observed yields in all categories are given in table 3. Systematic uncertainties Various sources of systematic uncertainty in uence the upper limit on the tHq production cross section. In general, the systematic uncertainties can introduce rate uncertainties on a speci c process as well as shape uncertainties on the distribution from which the upper limit on the process is nally derived. These uncertainties are handled by means of nuisance parameters, which are allowed to oat during the limit setting procedure. The uncertainty in the trigger e ciencies translates into an uncertainty in the nal rates of up to 5%. The uncertainty from the jet energy scale [36] is evaluated by varying the energy scale for all jets in the signal and background simulation simultaneously within their uncertainty as a function of jet pT and , and re-evaluating the yields and discriminant shapes of all processes. The limitations on the knowledge of the jet energy scale lead to an uncertainty that in some channels can be as large as 8%. Jet energy resolution uncertainties have a smaller e ect, up to 3% in the event yields. The corrections for the b tagging e ciencies for light- avored, c, and b quark jets have associated uncertainties [38], which are parameterized as a function of the pT, , and avor of the jets. Their e ect on the analysis is evaluated by shifting the correction factor of each jet up and down within their measured uncertainty. For photon identi cation, the uncertainty in the data/MC e ciency scale factor from the ducial region determines the overall uncertainty, as measured using a tag-and-probe technique applied to Z ! ee events (3.0% in the ECAL barrel, 4.0% in ECAL endcap) [49]. For the uncertainties related to the photon energy scale and resolution, the photon energy is shifted and smeared, respectively, within the known uncertainty for photons [50]. The cross sections used to estimate signal and background rates, where applicable, are of at least NLO accuracy and have associated uncertainties arising primarily from the PDFs and the choice of the factorization and renormalization scales. The e ect from the PDF uncertainties has been evaluated on signal and backgrounds following the PDF4LHC prescription [51, 52], and ranges from 1 to 8% depending on the quark or gluon nature of the colliding partons. The e ect of changing renormalization and factorization scales is evaluated for both signal and backgrounds by changing them simultaneously up and down by factors of two, producing e ects on rates extending up to 13% for ttH production. For the H ! and H ! WW analyses, where the signal is modeled using the ve- avor scheme, the overall event selection e ciency is re-evaluated using a sample simulated with the four- avor scheme. The corresponding change in signal selection e ciency is taken as a systematic uncertainty, and is 5.5% in the diphoton and up to 16% in the multilepton channels. The large tt background in the H ! bb nal state requires a special treatment of the tt + jets background component, which is split into four di erent categories, depending on the avor of the additional nal state partons: tt+bb, tt+b, tt+1=2c, and tt+light avors. Each of the tt + heavy avor components receives a conservative 50% rate uncertainty in addition to what is assigned to the tt background rate uncertainties. Dedicated MadGraph+pythia samples with varied renormalization and factorization scales and with varied matching thresholds are used to introduce additional nuisance parameters, which can alter the rate and the shape of the tt backgrounds. Reweighting the top quark pT distribution for tt events needs to be accounted for by a separate rate and shape systematic uncertainty [53]. The systematic uncertainty arising from scale variations in the sample generation is also taken into account for the signal process. For the statistical uncertainties, bin-by-bin uncertainties in the NN output shape are taken into account. Uncertainties in the e ciencies for lepton identi cation, isolation and impact parameter requirements are estimated by comparing variations in the di erence in performance between data and MC simulation using a high-purity sample of Z boson decays with a tag-and-probe method. These uncertainties vary between 1 and 5%, depending on the lepton avor and selection. The overall uncertainty is about 5% per lepton for the same-sign dilepton nal state, while it is 1.6% in the case of the trilepton nal state. For trigger e ciencies, no scale factors are used on simulation to correct for possible di erences between data and MC, assuming a trigger e ciency of 100% for the double-lepton triggers. The uncertainty in the yields derived from simulation due to the trigger e ciency is about 1%. The uncertainty in the misidenti cation probabilities for nonprompt leptons is estimated from simulation for the same-sign dilepton nal state. The misidenti cation rate is estimated following the same approach and parameterization used in the multijetdominated control sample, but using instead MC samples with a similar composition. This simulation-based misidenti cation rate is then applied to MC samples with the expected background composition in the signal sample, and the amount of disagreement between the number of nonprompt leptons predicted by the parameterized misidenti cation rate and those actually observed in this collection of MC samples is used to estimate the systematic uncertainty. In the case of the same-sign dilepton nal state, the uncertainty is assessed separately for di erent pT, , and b-tagged jet multiplicity bins for each avor. The overall uncertainty amounts to about 40%, which is applied using linear and quadratic deformations of the pT- and -dependent misidenti cation rate. For the trilepton nal state, a similar method is used to estimate a total rate uncertainty of 30%. Additional sources of uncertainty for this nal state are considered. The rst contribution comes from the change in the tight-to-loose rate as a result of applying a requirement on the ETmiss in the multijet control region used to estimate this rate, changing the diboson background contribution. The overall e ect on the nal prediction is about 10%. The second contribution is studied by changing the measured tight-to-loose rate up and down within its statistical uncertainty and propagated to the nal weight estimation. The total e ect on the expected number of events is about 14%. In the H ! analysis, an uncertainty of 50% is assigned to the yield of reducible backgrounds, uncorrelated between channels and categories. 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Suarez Gonzalez Universiteit Antwerpen, Antwerpen, Belgium S. Alderweireldt, T. Cornelis, E.A. De Wolf, X. Janssen, A. Knutsson, J. Lauwers, S. Luyckx, M. Van De Klundert, H. Van Haevermaet, P. Van Mechelen, N. Van Remortel, A. Van Spilbeeck Vrije Universiteit Brussel, Brussel, Belgium S. Abu Zeid, F. Blekman, J. D'Hondt, N. Daci, I. De Bruyn, K. Deroover, N. Heracleous, J. Keaveney, S. Lowette, L. Moreels, A. Olbrechts, Q. Python, D. Strom, S. Tavernier, W. Van Doninck, P. Van Mulders, G.P. Van Onsem, I. Van Parijs Universite Libre de Bruxelles, Bruxelles, Belgium P. Barria, H. Brun, C. Caillol, B. Clerbaux, G. De Lentdecker, G. Fasanella, L. Favart, A. Grebenyuk, G. Karapostoli, T. Lenzi, A. Leonard, T. Maerschalk, A. Marinov, L. Pernie, A. Randle-conde, T. Reis, T. Seva, C. Vander Velde, P. Vanlaer, R. Yonamine, F. Zenoni, F. Zhang3 Ghent University, Ghent, Belgium K. Beernaert, L. Benucci, A. Cimmino, S. Crucy, D. Dobur, A. Fagot, G. Garcia, M. Gul, J. Mccartin, A.A. Ocampo Rios, D. Poyraz, D. Ryckbosch, S. Salva, M. Sigamani, N. Strobbe, M. Tytgat, W. Van Driessche, E. Yazgan, N. Zaganidis Universite Catholique de Louvain, Louvain-la-Neuve, Belgium S. Basegmez, C. Belu 4, O. Bondu, S. Brochet, G. Bruno, A. Caudron, L. Ceard, G.G. Da Silveira, C. Delaere, D. Favart, L. Forthomme, A. Giammanco5, J. Hollar, A. Jafari, P. Jez, M. Komm, V. Lemaitre, A. Mertens, M. Musich, C. Nuttens, L. Perrini, A. Pin, K. Piotrzkowski, A. Popov6, L. Quertenmont, M. Selvaggi, M. Vidal Marono Universite de Mons, Mons, Belgium N. Beliy, G.H. Hammad 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, M. Hamer, C. Hensel, C. Mora Herrera, 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. Chinellato7, A. Custodio, E.M. Da Costa, D. De Jesus Damiao, C. De Oliveira Martins, S. Fonseca De Souza, L.M. Huertas Guativa, H. Malbouisson, D. Matos Figueiredo, L. Mundim, H. Nogima, W.L. Prado Da Silva, A. Santoro, A. Sznajder, E.J. Tonelli Manganote7, A. Vilela Pereira Universidade Estadual Paulista a, Universidade Federal do ABC b, S~ao Paulo, Brazil tova S. Ahujaa, C.A. Bernardesb, A. De Souza Santosb, S. Dograa, T.R. Fernandez Perez Tomeia, E.M. Gregoresb, P.G. Mercadanteb, C.S. Moona;8, S.F. Novaesa, Sandra S. Padulaa, D. Romero Abad, J.C. Ruiz Vargas Institute for Nuclear Research and Nuclear Energy, So a, Bulgaria A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, M. Rodozov, S. Stoykova, G. Sultanov, M. VuUniversity of So a, So a, Bulgaria A. Dimitrov, I. Glushkov, L. Litov, B. Pavlov, P. Petkov Institute of High Energy Physics, Beijing, China M. Ahmad, J.G. Bian, G.M. Chen, H.S. Chen, M. Chen, T. Cheng, R. Du, C.H. Jiang, R. Plestina9, F. Romeo, S.M. Shaheen, J. Tao, C. Wang, Z. Wang, H. Zhang State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, China J.C. Sanabria C. Asawatangtrakuldee, Y. Ban, Q. Li, S. Liu, Y. Mao, S.J. Qian, D. Wang, Z. Xu Universidad de Los Andes, Bogota, Colombia C. Avila, A. Cabrera, L.F. Chaparro Sierra, C. Florez, J.P. Gomez, B. Gomez Moreno, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Split, Croatia N. Godinovic, D. Lelas, I. Puljak, P.M. Ribeiro Cipriano University of Split, Faculty of Science, Split, Croatia Z. Antunovic, M. Kovac Institute Rudjer Boskovic, Zagreb, Croatia V. Brigljevic, K. Kadija, J. Luetic, S. Micanovic, L. Sudic University of Cyprus, Nicosia, Cyprus H. Rykaczewski Charles University, Prague, Czech Republic M. Bodlak, M. Finger10, M. Finger Jr.10 A. Attikis, G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos, P.A. Razis, Academy of Scienti c Research and Technology of the Arab Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt Y. Assran11, M. El Sawy12;13, S. Elgammal13, A. Ellithi Kamel14;14, M.A. Mahmoud15;15 National Institute of Chemical Physics and Biophysics, Tallinn, Estonia B. Calpas, M. Kadastik, M. Murumaa, M. Raidal, A. Tiko, C. Veelken Department of Physics, University of Helsinki, Helsinki, Finland P. Eerola, J. Pekkanen, M. Voutilainen Helsinki Institute of Physics, Helsinki, Finland J. Harkonen, V. Karimaki, R. Kinnunen, T. Lampen, K. Lassila-Perini, S. Lehti, T. Linden, P. Luukka, T. Maenpaa, T. Peltola, E. Tuominen, J. Tuominiemi, E. Tuovinen, L. Wendland J. Talvitie, T. Tuuva Lappeenranta University of Technology, Lappeenranta, Finland DSM/IRFU, CEA/Saclay, Gif-sur-Yvette, France M. Besancon, F. Couderc, M. Dejardin, D. Denegri, B. Fabbro, J.L. Faure, C. Favaro, F. Ferri, S. Ganjour, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry, E. Locci, M. Machet, J. Malcles, J. Rander, A. Rosowsky, M. Titov, A. Zghiche Laboratoire Leprince-Ringuet, Ecole Polytechnique, IN2P3-CNRS, Palaiseau, France I. Antropov, S. Ba oni, F. Beaudette, P. Busson, L. Cadamuro, E. Chapon, C. Charlot, T. Dahms, O. Davignon, N. Filipovic, A. Florent, R. Granier de Cassagnac, S. Lisniak, L. Mastrolorenzo, P. Mine, I.N. Naranjo, M. Nguyen, C. Ochando, G. Ortona, P. Paganini, P. Pigard, S. Regnard, R. Salerno, J.B. Sauvan, Y. Sirois, T. Strebler, Y. Yilmaz, A. Zabi Institut Pluridisciplinaire Hubert Curien, Universite de Strasbourg, Universite de Haute Alsace Mulhouse, CNRS/IN2P3, Strasbourg, France J.-L. Agram16, J. Andrea, A. Aubin, D. Bloch, J.-M. Brom, M. Buttignol, E.C. Chabert, N. Chanon, C. Collard, E. Conte16, X. Coubez, J.-C. Fontaine16, D. Gele, U. Goerlach, C. Goetzmann, A.-C. Le Bihan, J.A. Merlin2, K. Skovpen, P. Van Hove Centre de Calcul de l'Institut National de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3, Villeurbanne, France S. Gadrat Universite de Lyon, Universite Claude Bernard Lyon 1, CNRS-IN2P3, Institut de Physique Nucleaire de Lyon, Villeurbanne, France S. Beauceron, C. Bernet, G. Boudoul, E. Bouvier, C.A. Carrillo Montoya, R. Chierici, D. Contardo, B. Courbon, P. Depasse, H. El Mamouni, J. Fan, J. Fay, S. Gascon, M. Gouzevitch, B. Ille, F. Lagarde, I.B. Laktineh, M. Lethuillier, L. Mirabito, A.L. Pequegnot, S. Perries, J.D. Ruiz Alvarez, D. Sabes, L. Sgandurra, V. Sordini, M. Vander Donckt, P. Verdier, S. Viret Georgian Technical University, Tbilisi, Georgia T. Toriashvili17 Z. Tsamalaidze10 Tbilisi State University, Tbilisi, Georgia RWTH Aachen University, I. Physikalisches Institut, Aachen, Germany C. Autermann, S. Beranek, M. Edelho , L. Feld, A. Heister, M.K. Kiesel, K. Klein, M. Lipinski, A. Ostapchuk, M. Preuten, F. Raupach, S. Schael, J.F. Schulte, T. Verlage, H. Weber, B. Wittmer, V. Zhukov6 RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany M. Ata, M. Brodski, E. Dietz-Laursonn, D. Duchardt, M. Endres, M. Erdmann, S. Erdweg, T. Esch, R. Fischer, A. Guth, T. Hebbeker, C. Heidemann, K. Hoepfner, D. Klingebiel, S. Knutzen, P. Kreuzer, M. Merschmeyer, A. Meyer, P. Millet, M. Olschewski, K. Padeken, P. Papacz, T. Pook, M. Radziej, H. Reithler, M. Rieger, F. Scheuch, L. Sonnenschein, D. Teyssier, S. Thuer RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany V. Cherepanov, Y. Erdogan, G. Flugge, H. Geenen, M. Geisler, F. Hoehle, B. Kargoll, T. Kress, Y. Kuessel, A. Kunsken, J. Lingemann2, A. Nehrkorn, A. Nowack, I.M. Nugent, C. Pistone, O. Pooth, A. Stahl Deutsches Elektronen-Synchrotron, Hamburg, Germany M. Aldaya Martin, I. Asin, N. Bartosik, O. Behnke, U. Behrens, A.J. Bell, K. Borras18, A. Burgmeier, A. Cakir, A. Campbell, S. Choudhury, F. Costanza, C. Diez Pardos, G. Dolinska, S. Dooling, T. Dorland, G. Eckerlin, D. Eckstein, T. Eichhorn, G. Flucke, E. Gallo19, J. Garay Garcia, A. Geiser, A. Gizhko, P. Gunnellini, J. Hauk, M. Hempel20, H. Jung, A. Kalogeropoulos, O. Karacheban20, M. Kasemann, P. Katsas, J. Kieseler, C. Kleinwort, I. Korol, W. Lange, J. Leonard, K. Lipka, A. Lobanov, W. Lohmann20, R. Mankel, I. Mar n20, I.-A. Melzer-Pellmann, A.B. Meyer, G. Mittag, J. Mnich, A. Mussgiller, S. Naumann-Emme, A. Nayak, E. Ntomari, H. Perrey, D. Pitzl, R. Placakyte, A. Raspereza, B. Roland, M.O . Sahin, P. Saxena, T. Schoerner-Sadenius, M. Schroder, C. Seitz, S. Spannagel, K.D. Trippkewitz, R. Walsh, C. Wissing University of Hamburg, Hamburg, Germany V. Blobel, M. Centis Vignali, A.R. Draeger, J. Er e, E. Garutti, K. Goebel, D. Gonzalez, M. Gorner, J. Haller, M. Ho mann, R.S. Hoing, A. Junkes, R. Klanner, R. Kogler, T. Lapsien, T. Lenz, I. Marchesini, D. Marconi, M. Meyer, D. Nowatschin, J. Ott, F. Pantaleo2, T. Pei er, A. Perieanu, N. Pietsch, J. Poehlsen, D. Rathjens, C. Sander, H. Schettler, P. Schleper, E. Schlieckau, A. Schmidt, J. Schwandt, M. Seidel, V. Sola, H. Stadie, G. Steinbruck, H. Tholen, D. Troendle, E. Usai, L. Vanelderen, A. Vanhoefer, B. Vormwald Institut fur Experimentelle Kernphysik, Karlsruhe, Germany M. Akbiyik, C. Barth, C. Baus, J. Berger, C. Boser, E. Butz, T. Chwalek, F. Colombo, W. De Boer, A. Descroix, A. Dierlamm, N. Faltermann, S. Fink, F. Frensch, M. Gi els, Paraskevi, Greece A. Psallidas, I. Topsis-Giotis University of Athens, Athens, Greece A. Gilbert, F. Hartmann2, S.M. Heindl, U. Husemann, I. Katkov6, A. Kornmayer2, P. Lobelle Pardo, B. Maier, H. Mildner, M.U. Mozer, T. Muller, Th. Muller, M. Plagge, G. Quast, K. Rabbertz, S. Rocker, F. Roscher, H.J. Simonis, F.M. Stober, R. Ulrich, J. Wagner-Kuhr, S. Wayand, M. Weber, T. Weiler, C. Wohrmann, R. Wolf Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia G. Anagnostou, G. Daskalakis, T. Geralis, V.A. Giakoumopoulou, A. Kyriakis, D. Loukas, A. Agapitos, S. Kesisoglou, A. Panagiotou, N. Saoulidou, E. Tziaferi University of Ioannina, Ioannina, Greece I. Evangelou, G. Flouris, C. Foudas, P. Kokkas, N. Loukas, N. Manthos, I. Papadopoulos, E. Paradas, J. Strologas Wigner Research Centre for Physics, Budapest, Hungary G. Bencze, C. Hajdu, A. Hazi, P. Hidas, D. Horvath21, F. Sikler, V. Veszpremi, G. Vesztergombi22, A.J. Zsigmond Institute of Nuclear Research ATOMKI, Debrecen, Hungary N. Beni, S. Czellar, J. Karancsi23, J. Molnar, Z. Szillasi University of Debrecen, Debrecen, Hungary M. Bartok24, A. Makovec, P. Raics, Z.L. Trocsanyi, B. Ujvari National Institute of Science Education and Research, Bhubaneswar, India P. Mal, K. Mandal, D.K. Sahoo, N. Sahoo, S.K. Swain Panjab University, Chandigarh, India S. Bansal, S.B. Beri, V. Bhatnagar, R. Chawla, R. Gupta, U.Bhawandeep, A.K. Kalsi, A. Kaur, M. Kaur, R. Kumar, A. Mehta, M. Mittal, J.B. Singh, G. Walia University of Delhi, Delhi, India Ashok Kumar, A. Bhardwaj, B.C. Choudhary, R.B. Garg, A. Kumar, S. Malhotra, M. Naimuddin, N. Nishu, K. Ranjan, R. Sharma, V. Sharma Saha Institute of Nuclear Physics, Kolkata, India S. Bhattacharya, K. Chatterjee, S. Dey, S. Dutta, Sa. Jain, N. Majumdar, A. Modak, K. Mondal, S. Mukherjee, S. Mukhopadhyay, A. Roy, D. Roy, S. Roy Chowdhury, S. Sarkar, M. Sharan P. Shukla, A. Topkar Bhabha Atomic Research Centre, Mumbai, India A. Abdulsalam, R. Chudasama, D. Dutta, V. Jha, V. Kumar, A.K. Mohanty2, L.M. Pant, Tata Institute of Fundamental Research, Mumbai, India T. Aziz, S. Banerjee, S. Bhowmik25, R.M. Chatterjee, R.K. Dewanjee, S. Dugad, S. Ganguly, S. Ghosh, M. Guchait, A. Gurtu26, G. Kole, S. Kumar, B. Mahakud, M. Maity25, B. Sutar, N. Wickramage27 Indian Institute of Science Education and Research (IISER), Pune, India S. Chauhan, S. Dube, S. Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran H. Bakhshiansohi, H. Behnamian, S.M. Etesami28, A. Fahim29, R. Goldouzian, M. Khakzad, M. Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi, F. Rezaei Hosseinabadi, B. Safarzadeh30, M. Zeinali University College Dublin, Dublin, Ireland M. Felcini, M. Grunewald INFN Sezione di Bari a, Universita di Bari b, Politecnico di Bari c, Bari, Italy M. Abbresciaa;b, C. Calabriaa;b, C. Caputoa;b, A. Colaleoa, D. Creanzaa;c, L. Cristellaa;b, N. De Filippisa;c, M. De Palmaa;b, L. Fiorea, G. Iasellia;c, G. Maggia;c, M. Maggia, G. Minielloa;b, S. Mya;c, S. Nuzzoa;b, A. Pompilia;b, G. Pugliesea;c, R. Radognaa;b, A. Ranieria, G. Selvaggia;b, L. Silvestrisa;2, R. Vendittia;b, P. Verwilligena INFN Sezione di Bologna a, Universita di Bologna b, Bologna, Italy G. Abbiendia, C. Battilana2, A.C. Benvenutia, D. Bonacorsia;b, S. Braibant-Giacomellia;b, L. Brigliadoria;b, R. Campaninia;b, P. Capiluppia;b, A. Castroa;b, F.R. Cavalloa, S.S. Chhibraa;b, G. Codispotia;b, M. Cu ania;b, G.M. Dallavallea, F. Fabbria, A. Fanfania;b, D. Fasanellaa;b, P. Giacomellia, C. Grandia, L. Guiduccia;b, S. Marcellinia, G. Masettia, A. 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Malvezzia, R.A. Manzonia;b, B. Marzocchia;b;2, D. Menascea, L. Moronia, M. Paganonia;b, D. Pedrinia, S. Ragazzia;b, N. Redaellia, 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, S. Buontempoa, N. Cavalloa;c, S. Di Guidaa;d;2, M. Espositoa;b, F. Fabozzia;c, A.O.M. Iorioa;b, G. Lanzaa, L. Listaa, S. Meolaa;d;2, M. Merolaa, P. Paoluccia;2, C. Sciaccaa;b, F. Thyssen Trento c, Trento, Italy INFN Sezione di Padova a, Universita di Padova b, Padova, Italy, Universita di P. Azzia;2, N. Bacchettaa, L. Benatoa;b, D. Biselloa;b, A. Bolettia;b, A. Brancaa;b, R. Carlina;b, P. Checchiaa, M. Dall'Ossoa;b;2, T. Dorigoa, U. Dossellia, F. Gasparinia;b, U. Gasparinia;b, A. Gozzelinoa, K. Kanishcheva;c, S. Lacapraraa, M. Margonia;b, A.T. Meneguzzoa;b, J. Pazzinia;b, N. Pozzobona;b, P. Ronchesea;b, F. Simonettoa;b, E. Torassaa, M. Tosia;b, S. Venturaa, M. Zanetti, P. 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Zanettia Kangwon National University, Chunchon, Korea A. Kropivnitskaya, S.K. Nam Kyungpook National University, Daegu, Korea D.H. Kim, G.N. Kim, M.S. Kim, D.J. Kong, S. Lee, Y.D. Oh, A. Sakharov, D.C. Son Chonbuk National University, Jeonju, Korea J.A. Brochero Cifuentes, H. Kim, T.J. Kim Chonnam National University, Institute for Universe and Elementary Particles, S. Choi, Y. Go, D. Gyun, B. Hong, M. Jo, H. Kim, Y. Kim, B. Lee, K. Lee, K.S. Lee, Kwangju, Korea S. Song Korea University, Seoul, Korea S. Lee, S.K. Park, Y. Roh Seoul National University, Seoul, Korea H.D. Yoo University of Seoul, Seoul, Korea Sungkyunkwan University, Suwon, Korea Y. Choi, J. Goh, D. Kim, E. Kwon, J. Lee, I. Yu Vilnius University, Vilnius, Lithuania A. Juodagalvis, J. Vaitkus M. Choi, H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park, G. Ryu, M.S. Ryu National Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Malaysia I. Ahmed, A.A. Bin Anuar, Z.A. Ibrahim, J.R. Komaragiri, M.A.B. Md Ali33, F. Mohamad Idris34, W.A.T. Wan Abdullah, M.N. Yusli Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico E. Casimiro Linares, H. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-De La Cruz35, A. Hernandez-Almada, R. Lopez-Fernandez, A. Sanchez-Hernandez Universidad Iberoamericana, Mexico City, Mexico S. Carrillo Moreno, F. Vazquez Valencia Benemerita Universidad Autonoma de Puebla, Puebla, Mexico I. Pedraza, H.A. Salazar Ibarguen Universidad Autonoma de San Luis Potos , San Luis Potos , Mexico A. Morelos Pineda University of Auckland, Auckland, New Zealand D. Krofcheck P.H. Butler University of Canterbury, Christchurch, New Zealand National Centre for Physics, Quaid-I-Azam University, Islamabad, Pakistan A. Ahmad, M. Ahmad, Q. Hassan, H.R. Hoorani, W.A. Khan, T. Khurshid, M. Shoaib National Centre for Nuclear Research, Swierk, Poland H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Gorski, M. Kazana, K. Nawrocki, K. Romanowska-Rybinska, M. Szleper, P. Zalewski Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Warsaw, Poland G. Brona, K. Bunkowski, A. Byszuk36, K. Doroba, A. Kalinowski, M. Konecki, J. Krolikowski, M. Misiura, M. Olszewski, M. Walczak Laboratorio de Instrumentac~ao e F sica Experimental de Part culas, Lisboa, Portugal P. Bargassa, C. Beir~ao Da Cruz E Silva, A. Di Francesco, P. Faccioli, P.G. Ferreira Parracho, M. Gallinaro, N. Leonardo, L. Lloret Iglesias, F. Nguyen, J. Rodrigues Antunes, J. Seixas, O. Toldaiev, D. Vadruccio, J. Varela, P. Vischia Joint Institute for Nuclear Research, Dubna, Russia S. Afanasiev, P. Bunin, M. Gavrilenko, I. Golutvin, I. Gorbunov, A. Kamenev, V. Karjavin, V. Konoplyanikov, A. Lanev, A. Malakhov, V. Matveev37, P. Moisenz, V. Palichik, V. Perelygin, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, A. Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia V. Golovtsov, Y. Ivanov, V. Kim38, E. Kuznetsova, 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, E. Vlasov, A. Zhokin National Research Nuclear University 'Moscow Engineering Physics InstiA. Bylinkin P.N. Lebedev Physical Institute, Moscow, Russia V. Andreev, M. Azarkin39, I. Dremin39, M. Kirakosyan, A. Leonidov39, G. Mesyats, S.V. Rusakov Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia A. Baskakov, A. Belyaev, E. Boos, V. Bunichev, M. Dubinin40, L. Dudko, V. Klyukhin, O. Kodolova, N. Korneeva, I. Lokhtin, I. Myagkov, S. Obraztsov, M. Per lov, S. Petrushanko, V. Savrin Physics, Protvino, Russia State Research Center of Russian Federation, Institute for High Energy I. Azhgirey, I. Bayshev, S. Bitioukov, V. Kachanov, A. Kalinin, D. Konstantinov, V. Krychkine, V. Petrov, R. Ryutin, A. Sobol, L. Tourtchanovitch, S. Troshin, N. Tyurin, Sciences, Belgrade, Serbia P. Adzic41, J. Milosevic, V. Rekovic University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Centro de Investigaciones Energeticas Medioambientales y Tecnologicas (CIEMAT), Madrid, Spain J. Alcaraz Maestre, E. Calvo, M. Cerrada, M. Chamizo Llatas, N. Colino, B. De La Cruz, A. Delgado Peris, D. Dom nguez Vazquez, A. Escalante Del Valle, C. Fernandez Bedoya, J.P. Fernandez Ramos, J. Flix, M.C. Fouz, P. Garcia-Abia, O. Gonzalez Lopez, S. Goy Lopez, J.M. Hernandez, M.I. Josa, E. Navarro De Martino, A. Perez-Calero Yzquierdo, J. Puerta Pelayo, A. Quintario Olmeda, I. Redondo, L. Romero, J. Santaolalla, M.S. Soares Universidad Autonoma de Madrid, Madrid, Spain C. Albajar, J.F. de Troconiz, M. Missiroli, D. Moran Universidad de Oviedo, Oviedo, Spain J. Cuevas, J. Fernandez Menendez, S. Folgueras, I. Gonzalez Caballero, E. Palencia Cortezon, J.M. Vizan Garcia Santander, Spain Instituto de F sica de Cantabria (IFCA), CSIC-Universidad de Cantabria, I.J. Cabrillo, A. Calderon, J.R. Castin~eiras De Saa, P. De Castro Manzano, J. Duarte Campderros, M. Fernandez, J. Garcia-Ferrero, G. Gomez, A. Lopez Virto, J. Marco, R. Marco, C. Martinez Rivero, F. Matorras, F.J. Munoz Sanchez, J. Piedra Gomez, T. Rodrigo, A.Y. Rodr guez-Marrero, 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, G. Auzinger, M. Bachtis, P. Baillon, A.H. Ball, D. Barney, A. Benaglia, J. Bendavid, L. Benhabib, J.F. Benitez, G.M. Berruti, P. Bloch, A. Bocci, A. Bonato, C. Botta, H. Breuker, T. Camporesi, R. Castello, G. Cerminara, M. D'Alfonso, D. d'Enterria, A. Dabrowski, V. Daponte, A. David, M. De Gruttola, F. De Guio, A. De Roeck, S. De Visscher, E. Di Marco, M. Dobson, M. Dordevic, B. Dorney, T. du Pree, M. Dunser, N. Dupont, A. Elliott-Peisert, G. Franzoni, W. Funk, D. Gigi, K. Gill, D. Giordano, M. Girone, F. Glege, R. Guida, S. Gundacker, M. Gutho , J. Hammer, P. Harris, J. Hegeman, V. Innocente, P. Janot, H. Kirschenmann, M.J. Kortelainen, K. Kousouris, K. Krajczar, P. Lecoq, C. Lourenco, M.T. Lucchini, N. Magini, L. Malgeri, M. Mannelli, A. Martelli, L. Masetti, F. Meijers, S. Mersi, E. Meschi, F. Moortgat, S. Morovic, M. Mulders, M.V. Nemallapudi, H. Neugebauer, S. Orfanelli42, L. Orsini, L. Pape, E. Perez, M. Peruzzi, A. Petrilli, G. Petrucciani, A. Pfei er, D. Piparo, A. Racz, G. Rolandi43, M. Rovere, M. Ruan, H. Sakulin, C. Schafer, C. Schwick, A. Sharma, P. Silva, M. Simon, P. Sphicas44, J. Steggemann, B. Stieger, M. Stoye, Y. Takahashi, D. Treille, A. Triossi, A. Tsirou, G.I. Veres22, N. Wardle, H.K. Wohri, A. Zagozdzinska36, W.D. Zeuner Paul Scherrer Institut, Villigen, Switzerland W. Bertl, K. Deiters, W. Erdmann, R. Horisberger, Q. Ingram, H.C. Kaestli, D. Kotlinski, U. Langenegger, D. Renker, T. Rohe Institute for Particle Physics, ETH Zurich, Zurich, Switzerland F. Bachmair, L. Bani, L. Bianchini, B. Casal, G. Dissertori, M. Dittmar, M. Donega, P. Eller, C. Grab, C. Heidegger, D. Hits, J. Hoss, G. Kasieczka, W. Lustermann, B. Mangano, M. Marionneau, P. Martinez Ruiz del Arbol, M. Masciovecchio, D. Meister, F. Micheli, P. Musella, F. Nessi-Tedaldi, F. Pandol , J. Pata, F. Pauss, L. Perrozzi, M. Quittnat, M. Rossini, A. Starodumov45, M. Takahashi, V.R. Tavolaro, K. Theo latos, R. Wallny Universitat Zurich, Zurich, Switzerland T.K. Aarrestad, C. Amsler46, L. Caminada, M.F. Canelli, V. Chiochia, A. De Cosa, C. Galloni, A. Hinzmann, T. Hreus, B. Kilminster, C. Lange, J. Ngadiuba, D. Pinna, P. Robmann, F.J. Ronga, D. Salerno, Y. Yang National Central University, Chung-Li, Taiwan M. Cardaci, K.H. Chen, T.H. Doan, Sh. Jain, R. Khurana, M. Konyushikhin, C.M. Kuo, W. Lin, Y.J. Lu, S.S. Yu National Taiwan University (NTU), Taipei, Taiwan Arun Kumar, R. Bartek, P. Chang, Y.H. Chang, Y.W. Chang, Y. Chao, K.F. Chen, P.H. Chen, C. Dietz, F. Fiori, U. Grundler, W.-S. Hou, Y. Hsiung, Y.F. Liu, R.-S. Lu, M. Min~ano Moya, E. Petrakou, J.f. Tsai, Y.M. Tzeng Chulalongkorn University, Faculty of Science, Department of Physics, Bangkok, Thailand B. Asavapibhop, K. Kovitanggoon, G. Singh, N. Srimanobhas, N. Suwonjandee Cukurova University, Adana, Turkey A. Adiguzel, S. Cerci47, Z.S. Demiroglu, C. Dozen, I. Dumanoglu, S. Girgis, G. Gokbulut, Y. Guler, E. Gurpinar, I. Hos, E.E. Kangal48, A. Kayis Topaksu, G. Onengut49, K. Ozdemir50, S. Ozturk51, B. Tali47, H. Topakli51, M. Vergili, C. Zorbilmez Middle East Technical University, Physics Department, Ankara, Turkey I.V. Akin, B. Bilin, S. Bilmis, B. Isildak52, G. Karapinar53, M. Yalvac, M. Zeyrek Bogazici University, Istanbul, Turkey E. Gulmez, M. Kaya54, O. Kaya55, E.A. Yetkin56, T. Yetkin57 Istanbul Technical University, Istanbul, Turkey K. Cankocak, S. Sen58, F.I. Vardarl 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, E. Clement, D. Cussans, H. Flacher, J. Goldstein, M. Grimes, G.P. Heath, H.F. Heath, J. Jacob, L. Kreczko, C. Lucas, Z. Meng, D.M. Newbold59, S. Paramesvaran, A. Poll, T. Sakuma, S. Seif El Nasr-storey, S. Senkin, D. Smith, V.J. Smith Rutherford Appleton Laboratory, Didcot, United Kingdom K.W. Bell, A. Belyaev60, 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, W.J. Womersley, S.D. Worm Imperial College, London, United Kingdom M. Baber, R. Bainbridge, O. Buchmuller, A. Bundock, D. Burton, S. Casasso, M. Citron, D. Colling, L. Corpe, N. Cripps, P. Dauncey, G. Davies, A. De Wit, M. Della Negra, P. Dunne, A. Elwood, W. Ferguson, J. Fulcher, D. Futyan, G. Hall, G. Iles, M. Kenzie, R. Lane, R. Lucas59, L. Lyons, A.-M. Magnan, S. Malik, J. Nash, A. Nikitenko45, J. Pela, M. Pesaresi, K. Petridis, D.M. Raymond, A. Richards, A. Rose, C. Seez, A. Tapper, K. Uchida, M. Vazquez Acosta61, T. Virdee, S.C. Zenz Brunel University, Uxbridge, United Kingdom J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, D. Leggat, D. Leslie, I.D. Reid, P. Symonds, L. Teodorescu, M. Turner Baylor University, Waco, U.S.A. A. Borzou, K. Call, J. Dittmann, K. Hatakeyama, A. Kasmi, H. Liu, N. Pastika The University of Alabama, Tuscaloosa, U.S.A. O. Charaf, S.I. Cooper, C. Henderson, P. Rumerio Boston University, Boston, U.S.A. A. Avetisyan, T. Bose, C. Fantasia, D. Gastler, P. Lawson, D. Rankin, C. Richardson, J. Rohlf, J. St. John, L. Sulak, D. Zou Brown University, Providence, U.S.A. J. Alimena, E. Berry, S. Bhattacharya, D. Cutts, N. Dhingra, A. Ferapontov, A. Garabedian, J. Hakala, U. Heintz, E. Laird, G. Landsberg, Z. Mao, M. Narain, S. Piperov, S. Sagir, T. Sinthuprasith, R. Syarif University of California, Davis, Davis, U.S.A. R. Breedon, G. Breto, M. Calderon De La Barca Sanchez, S. Chauhan, M. Chertok, J. Conway, R. Conway, P.T. Cox, R. Erbacher, M. Gardner, W. Ko, R. Lander, M. Mulhearn, D. Pellett, J. Pilot, F. Ricci-Tam, S. Shalhout, J. Smith, M. Squires, D. Stolp, M. Tripathi, S. Wilbur, R. Yohay University of California, Los Angeles, U.S.A. R. Cousins, P. Everaerts, C. Farrell, J. Hauser, M. Ignatenko, D. Saltzberg, E. Takasugi, V. Valuev, M. Weber University of California, Riverside, Riverside, U.S.A. K. Burt, R. Clare, J. Ellison, J.W. Gary, G. Hanson, J. Heilman, M. Ivova PANEVA, P. Jandir, E. Kennedy, F. Lacroix, O.R. Long, A. Luthra, M. Malberti, M. Olmedo Negrete, A. Shrinivas, H. Wei, S. Wimpenny, B. R. Yates University of California, San Diego, La Jolla, U.S.A. J.G. Branson, G.B. Cerati, S. Cittolin, R.T. D'Agnolo, M. Derdzinski, A. Holzner, R. Kelley, D. Klein, J. Letts, I. Macneill, D. Olivito, S. Padhi, M. Pieri, M. Sani, V. Sharma, S. Simon, M. Tadel, A. Vartak, S. Wasserbaech62, C. Welke, F. Wurthwein, A. Yagil, G. Zevi Della Porta University of California, Santa Barbara, Santa Barbara, U.S.A. D. Barge, J. Bradmiller-Feld, C. Campagnari, A. Dishaw, V. Dutta, K. Flowers, M. Franco Sevilla, P. Ge ert, C. George, F. Golf, L. Gouskos, J. Gran, J. Incandela, C. Justus, N. Mccoll, S.D. Mullin, J. Richman, D. Stuart, I. Suarez, W. To, C. West, J. Yoo California Institute of Technology, Pasadena, U.S.A. D. Anderson, A. Apresyan, A. Bornheim, J. Bunn, Y. Chen, J. Duarte, A. Mott, H.B. Newman, C. Pena, M. Pierini, M. Spiropulu, J.R. Vlimant, S. Xie, R.Y. Zhu Carnegie Mellon University, Pittsburgh, U.S.A. M.B. Andrews, V. Azzolini, A. Calamba, B. Carlson, T. Ferguson, M. Paulini, J. Russ, M. Sun, H. Vogel, I. Vorobiev University of Colorado Boulder, Boulder, U.S.A. J.P. Cumalat, W.T. Ford, A. Gaz, F. Jensen, A. Johnson, M. Krohn, T. Mulholland, U. Nauenberg, K. Stenson, S.R. Wagner Cornell University, Ithaca, U.S.A. J. Alexander, A. Chatterjee, J. Chaves, J. Chu, S. Dittmer, N. Eggert, N. Mirman, G. Nicolas Kaufman, J.R. Patterson, A. Rinkevicius, A. Ryd, L. Skinnari, L. So , W. Sun, S.M. Tan, W.D. Teo, J. Thom, J. Thompson, J. Tucker, Y. Weng, P. Wittich Fermi National Accelerator Laboratory, Batavia, U.S.A. S. Abdullin, M. Albrow, J. Anderson, G. Apollinari, S. Banerjee, L.A.T. Bauerdick, A. Beretvas, J. Berryhill, P.C. Bhat, G. Bolla, K. Burkett, J.N. Butler, H.W.K. Cheung, F. Chlebana, S. Cihangir, V.D. Elvira, I. Fisk, J. Freeman, E. Gottschalk, L. Gray, D. Green, S. Grunendahl, O. Gutsche, J. Hanlon, D. Hare, R.M. Harris, S. Hasegawa, J. Hirschauer, Z. Hu, S. Jindariani, M. Johnson, U. Joshi, A.W. Jung, B. Klima, B. Kreis, S. Kwany, S. Lammel, J. Linacre, D. Lincoln, R. Lipton, T. Liu, R. Lopes De Sa, J. Lykken, K. Maeshima, J.M. Marra no, V.I. Martinez Outschoorn, S. Maruyama, D. Mason, P. McBride, P. Merkel, K. Mishra, S. Mrenna, S. Nahn, C. Newman-Holmes, V. O'Dell, K. Pedro, O. Prokofyev, G. Rakness, E. Sexton-Kennedy, A. Soha, W.J. Spalding, L. Spiegel, L. Taylor, S. Tkaczyk, N.V. Tran, L. Uplegger, E.W. Vaandering, C. Vernieri, M. Verzocchi, R. Vidal, H.A. Weber, A. Whitbeck, F. Yang University of Florida, Gainesville, U.S.A. D. Acosta, P. Avery, P. Bortignon, D. Bourilkov, A. Carnes, M. Carver, D. Curry, S. Das, G.P. Di Giovanni, R.D. Field, I.K. Furic, S.V. Gleyzer, J. Hugon, J. Konigsberg, A. Korytov, J.F. Low, P. Ma, K. Matchev, H. Mei, P. Milenovic63, G. Mitselmakher, D. Rank, R. Rossin, L. Shchutska, M. Snowball, D. Sperka, N. Terentyev, L. Thomas, J. Wang, S. Wang, J. Yelton Florida International University, Miami, U.S.A. S. Hewamanage, S. Linn, P. Markowitz, G. Martinez, J.L. Rodriguez Florida State University, Tallahassee, U.S.A. A. Ackert, J.R. Adams, T. Adams, A. Askew, J. Bochenek, B. Diamond, J. Haas, S. Hagopian, V. Hagopian, K.F. Johnson, A. Khatiwada, H. Prosper, M. Weinberg Florida Institute of Technology, Melbourne, U.S.A. M.M. Baarmand, V. Bhopatkar, S. Colafranceschi64, M. Hohlmann, H. Kalakhety, 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, I. Bucinskaite, R. Cavanaugh, O. Evdokimov, L. Gauthier, C.E. Gerber, D.J. Hofman, P. Kurt, C. O'Brien, I.D. Sandoval Gonzalez, C. Silkworth, P. Turner, N. Varelas, Z. Wu, M. Zakaria The University of Iowa, Iowa City, U.S.A. B. Bilki65, W. Clarida, K. Dilsiz, S. Durgut, R.P. Gandrajula, M. Haytmyradov, V. Khristenko, J.-P. Merlo, H. Mermerkaya66, A. Mestvirishvili, A. Moeller, J. Nachtman, H. Ogul, Y. Onel, F. Ozok56, A. Penzo, C. Snyder, E. Tiras, J. Wetzel, K. Yi Johns Hopkins University, Baltimore, U.S.A. I. Anderson, B.A. Barnett, B. Blumenfeld, N. Eminizer, D. Fehling, L. Feng, A.V. Gritsan, P. Maksimovic, C. Martin, M. Osherson, J. Roskes, A. Sady, U. Sarica, M. Swartz, M. Xiao, Y. Xin, C. You P. Baringer, A. Bean, G. Benelli, C. Bruner, R.P. Kenny III, D. Majumder, M. Malek, M. Murray, S. Sanders, R. Stringer, Q. Wang Kansas State University, Manhattan, U.S.A. A. Ivanov, K. Kaadze, S. Khalil, M. Makouski, Y. Maravin, A. Mohammadi, L.K. Saini, N. Skhirtladze, S. Toda Lawrence Livermore National Laboratory, Livermore, U.S.A. D. Lange, 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, J.A. Gomez, N.J. Hadley, S. Jabeen, R.G. Kellogg, T. Kolberg, J. Kunkle, Y. Lu, A.C. Mignerey, Y.H. Shin, A. Skuja, M.B. Tonjes, S.C. Tonwar Massachusetts Institute of Technology, Cambridge, U.S.A. A. Apyan, R. Barbieri, A. Baty, K. Bierwagen, S. Brandt, W. Busza, I.A. Cali, Z. Demiragli, L. Di Matteo, G. Gomez Ceballos, M. Goncharov, D. Gulhan, Y. Iiyama, G.M. Innocenti, M. Klute, D. Kovalskyi, Y.S. Lai, Y.-J. Lee, A. Levin, P.D. Luckey, A.C. Marini, C. Mcginn, C. Mironov, S. Narayanan, X. Niu, C. Paus, D. Ralph, C. Roland, G. Roland, J. SalfeldNebgen, G.S.F. Stephans, K. Sumorok, M. Varma, D. Velicanu, J. Veverka, J. Wang, T.W. Wang, B. Wyslouch, M. Yang, V. Zhukova University of Minnesota, Minneapolis, U.S.A. B. Dahmes, A. Evans, A. Finkel, A. Gude, P. Hansen, S. Kalafut, S.C. Kao, K. Klapoetke, Y. Kubota, Z. Lesko, J. Mans, S. Nourbakhsh, N. Ruckstuhl, R. Rusack, N. Tambe, J. Turkewitz University of Mississippi, Oxford, U.S.A. J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, U.S.A. E. Avdeeva, K. Bloom, S. Bose, D.R. Claes, A. Dominguez, C. Fangmeier, R. Gonzalez Suarez, R. Kamalieddin, J. Keller, D. Knowlton, I. Kravchenko, J. Lazo-Flores, F. Meier, J. Monroy, F. Ratnikov, J.E. Siado, G.R. Snow State University of New York at Bu alo, Bu alo, U.S.A. M. Alyari, J. Dolen, J. George, A. Godshalk, C. Harrington, I. Iashvili, J. Kaisen, A. Kharchilava, A. Kumar, S. Rappoccio, B. Roozbahani Northeastern University, Boston, U.S.A. G. Alverson, E. Barberis, D. Baumgartel, M. Chasco, A. Hortiangtham, A. Massironi, D.M. Morse, D. Nash, T. Orimoto, R. Teixeira De Lima, D. Trocino, R.-J. Wang, D. Wood, J. Zhang Northwestern University, Evanston, U.S.A. K.A. Hahn, A. Kubik, N. Mucia, N. Odell, B. Pollack, A. Pozdnyakov, M. Schmitt, S. Stoynev, K. Sung, M. Trovato, M. Velasco University of Notre Dame, Notre Dame, U.S.A. A. Brinkerho , N. Dev, M. Hildreth, C. Jessop, D.J. Karmgard, N. Kellams, K. Lannon, S. Lynch, N. Marinelli, F. Meng, C. Mueller, Y. Musienko37, T. Pearson, M. Planer, A. Reinsvold, R. Ruchti, G. Smith, S. Taroni, N. Valls, M. Wayne, M. Wolf, A. Woodard The Ohio State University, Columbus, U.S.A. L. Antonelli, J. Brinson, B. Bylsma, L.S. Durkin, S. Flowers, A. Hart, C. Hill, R. Hughes, W. Ji, K. Kotov, T.Y. Ling, B. Liu, W. Luo, D. Puigh, M. Rodenburg, B.L. Winer, H.W. Wulsin Princeton University, Princeton, U.S.A. O. Driga, P. Elmer, J. Hardenbrook, P. Hebda, S.A. Koay, P. Lujan, D. Marlow, T. Medvedeva, M. Mooney, J. Olsen, C. Palmer, P. Piroue, X. Quan, H. Saka, D. Stickland, C. Tully, J.S. Werner, A. Zuranski University of Puerto Rico, Mayaguez, U.S.A. S. Malik Purdue University, West Lafayette, U.S.A. V.E. Barnes, D. Benedetti, D. Bortoletto, L. Gutay, M.K. Jha, M. Jones, K. Jung, D.H. Miller, N. Neumeister, B.C. Radburn-Smith, X. Shi, I. Shipsey, D. Silvers, J. Sun, A. Svyatkovskiy, F. Wang, W. Xie, L. Xu Purdue University Calumet, Hammond, U.S.A. N. Parashar, J. Stupak Rice University, Houston, U.S.A. A. Adair, B. Akgun, Z. Chen, K.M. Ecklund, F.J.M. Geurts, M. Guilbaud, W. Li, B. Michlin, M. Northup, B.P. Padley, R. Redjimi, J. Roberts, J. Rorie, Z. Tu, J. Zabel University of Rochester, Rochester, U.S.A. B. Betchart, A. Bodek, P. de Barbaro, R. Demina, Y. Eshaq, T. Ferbel, M. Galanti, A. Garcia-Bellido, J. Han, A. Harel, O. Hindrichs, A. Khukhunaishvili, G. Petrillo, P. Tan, M. Verzetti Rutgers, The State University of New Jersey, Piscataway, U.S.A. S. Arora, A. Barker, J.P. Chou, C. Contreras-Campana, E. Contreras-Campana, D. Duggan, D. Ferencek, Y. Gershtein, R. Gray, E. Halkiadakis, D. Hidas, E. Hughes, S. Kaplan, R. Kunnawalkam Elayavalli, A. Lath, K. Nash, S. Panwalkar, M. Park, S. Salur, S. Schnetzer, D. She eld, S. Somalwar, R. Stone, S. Thomas, P. Thomassen, M. Walker University of Tennessee, Knoxville, U.S.A. M. Foerster, G. Riley, K. Rose, S. Spanier, A. York Texas A&M University, College Station, U.S.A. O. Bouhali67, A. Castaneda Hernandez67, M. Dalchenko, M. De Mattia, A. Delgado, S. Dildick, R. Eusebi, J. Gilmore, T. Kamon68, V. Krutelyov, R. Mueller, I. Osipenkov, Y. Pakhotin, R. Patel, A. Perlo , A. Rose, A. Safonov, A. Tatarinov, K.A. Ulmer2 Texas Tech University, Lubbock, U.S.A. N. Akchurin, C. Cowden, J. Damgov, C. Dragoiu, P.R. Dudero, J. Faulkner, S. Kunori, K. Lamichhane, S.W. Lee, T. Libeiro, S. Undleeb, I. Volobouev Vanderbilt University, Nashville, U.S.A. E. Appelt, A.G. Delannoy, S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, Y. Mao, A. Melo, H. Ni, P. Sheldon, B. Snook, S. Tuo, J. Velkovska, Q. Xu University of Virginia, Charlottesville, U.S.A. M.W. Arenton, B. Cox, B. Francis, J. Goodell, R. Hirosky, A. Ledovskoy, H. Li, C. Lin, C. Neu, X. Sun, Y. Wang, E. Wolfe, J. Wood, F. Xia Wayne State University, Detroit, U.S.A. J. Sturdy University of Wisconsin, Madison, U.S.A. C. Clarke, R. Harr, P.E. Karchin, C. Kottachchi Kankanamge Don, P. Lamichhane, D.A. Belknap, D. Carlsmith, M. Cepeda, S. Dasu, L. Dodd, S. Duric, E. Friis, B. Gomber, M. Grothe, R. Hall-Wilton, M. Herndon, A. Herve, P. Klabbers, A. Lanaro, A. Levine, K. Long, R. Loveless, A. Mohapatra, I. Ojalvo, T. Perry, G.A. Pierro, G. Polese, T. Ruggles, T. Sarangi, A. Savin, A. Sharma, N. Smith, W.H. Smith, D. Taylor, N. Woods y: Deceased China 1: Also at Vienna University of Technology, Vienna, Austria 2: Also at CERN, European Organization for Nuclear Research, Geneva, Switzerland 3: Also at State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, 4: Also at Institut Pluridisciplinaire Hubert Curien, Universite de Strasbourg, Universite de Haute Alsace Mulhouse, CNRS/IN2P3, Strasbourg, France 5: Also at National Institute of Chemical Physics and Biophysics, Tallinn, Estonia 6: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia 7: Also at Universidade Estadual de Campinas, Campinas, Brazil 8: Also at Centre National de la Recherche Scienti que (CNRS) - IN2P3, Paris, France 9: Also at Laboratoire Leprince-Ringuet, Ecole Polytechnique, IN2P3-CNRS, Palaiseau, France 10: Also at Joint Institute for Nuclear Research, Dubna, Russia 11: Now at Suez University, Suez, Egypt 12: Also at Beni-Suef University, Bani Sweif, Egypt 13: Now at British University in Egypt, Cairo, Egypt 14: Also at Cairo University, Cairo, Egypt 15: Also at Fayoum University, El-Fayoum, Egypt 16: Also at Universite de Haute Alsace, Mulhouse, France 17: Also at Tbilisi State University, Tbilisi, Georgia 18: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany 19: Also at University of Hamburg, Hamburg, Germany 20: Also at Brandenburg University of Technology, Cottbus, Germany 21: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary 23: Also at University of Debrecen, Debrecen, Hungary 24: Also at Wigner Research Centre for Physics, Budapest, Hungary 25: Also at University of Visva-Bharati, Santiniketan, India 26: Now at King Abdulaziz University, Jeddah, Saudi Arabia 27: Also at University of Ruhuna, Matara, Sri Lanka 28: Also at Isfahan University of Technology, Isfahan, Iran 29: Also at University of Tehran, Department of Engineering Science, Tehran, Iran 30: Also at Plasma Physics Research Center, Science and Research Branch, Islamic Azad University, Tehran, Iran 31: Also at Universita degli Studi di Siena, Siena, Italy 32: Also at Purdue University, West Lafayette, U.S.A. 33: Also at International Islamic University of Malaysia, Kuala Lumpur, Malaysia 34: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia 35: Also at Consejo Nacional de Ciencia y Tecnolog a, Mexico city, Mexico 36: Also at Warsaw University of Technology, Institute of Electronic Systems, Warsaw, Poland 37: Also at Institute for Nuclear Research, Moscow, Russia 38: Also at St. Petersburg State Polytechnical University, St. Petersburg, Russia 39: Also at National Research Nuclear University 'Moscow 40: Also at California Institute of Technology, Pasadena, U.S.A. 41: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia 42: Also at National Technical University of Athens, Athens, Greece 43: Also at Scuola Normale e Sezione dell'INFN, Pisa, Italy 44: Also at University of Athens, Athens, Greece 45: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia 46: Also at Albert Einstein Center for Fundamental Physics, Bern, Switzerland 47: Also at Adiyaman University, Adiyaman, Turkey 48: Also at Mersin University, Mersin, Turkey 49: Also at Cag University, Mersin, Turkey 50: Also at Piri Reis University, Istanbul, Turkey 51: Also at Gaziosmanpasa University, Tokat, Turkey 52: Also at Ozyegin University, Istanbul, Turkey 53: Also at Izmir Institute of Technology, Izmir, Turkey 54: Also at Marmara University, Istanbul, Turkey 55: Also at Kafkas University, Kars, Turkey Kingdom Belgrade, Serbia 56: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey 57: Also at Yildiz Technical University, Istanbul, Turkey 58: Also at Hacettepe University, Ankara, Turkey 59: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom 60: Also at School of Physics and Astronomy, University of Southampton, Southampton, United 61: Also at Instituto de Astrof sica de Canarias, La Laguna, Spain 62: Also at Utah Valley University, Orem, U.S.A. 63: Also at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, 64: Also at Facolta Ingegneria, Universita di Roma, Roma, Italy 65: Also at Argonne National Laboratory, Argonne, U.S.A. 67: Also at Texas A&M University at Qatar, Doha, Qatar 68: Also at Kyungpook National University, Daegu, Korea W or a Z boson and decaying to bottom quarks , Phys. 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V. Khachatryan, A. M. Sirunyan, A. Tumasyan, W. Adam. Search for the associated production of a Higgs boson with a single top quark in proton-proton collisions at \( \sqrt{s}=8 \) TeV, Journal of High Energy Physics, 2016, 177, DOI: 10.1007/JHEP06(2016)177