Search for top quark decays via Higgs-boson-mediated flavor-changing neutral currents in pp collisions at \( \sqrt{s}=8 \) TeV

Journal of High Energy Physics, Feb 2017

A search is performed for Higgs-boson-mediated flavor-changing neutral currents in the decays of top quarks. The search is based on proton-proton collision data corresponding to an integrated luminosity of 19.7 fb−1 at a center-of-mass energy of 8 TeV collected with the CMS detector at the LHC. Events in which a top quark pair is produced with one top quark decaying into a charm or up quark and a Higgs boson (H), and the other top quark decaying into a bottom quark and a W boson are selected. The Higgs boson in these events is assumed to subsequently decay into either dibosons or difermions. No significant excess is observed above the expected standard model background, and an upper limit at the 95% confidence level is set on the branching fraction ℬ(t → Hc) of 0.40% and ℬ(t → Hu) of 0.55%, where the expected upper limits are 0.43% and 0.40%, respectively. These results correspond to upper limits on the square of the flavor-changing Higgs boson Yukawa couplings |λ tc H |2 < 6.9 × 10− 3 and |λ tu H |2 < 9.8 × 10− 3.

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Search for top quark decays via Higgs-boson-mediated flavor-changing neutral currents in pp collisions at \( \sqrt{s}=8 \) TeV

Received: October Search for top quark decays via Higgs-boson-mediated avor-changing neutral currents in pp collisions at M. Gouzevitch 0 1 2 3 4 5 G. Grenier 0 1 2 3 4 5 B. Ille 0 1 2 3 4 5 F. Lagarde 0 1 2 3 4 5 I.B. Laktineh 0 1 2 3 4 5 M. Lethuillier 0 1 2 3 4 5 L. Mirabito 0 1 2 3 4 5 0 Cukurova University , Adana , Turkey 1 State University of New York at Bu alo , Bu alo , U.S.A 2 tute' (MEPhI) , Moscow , Russia 3 University , Budapest , Hungary 4 8: Also at Joint Institute for Nuclear Research , Dubna , Russia 5 52: Also at Cag University , Mersin , Turkey A search is performed for Higgs-boson-mediated avor-changing neutral currents in the decays of top quarks. The search is based on proton-proton collision data corresponding to an integrated luminosity of 19.7 fb 1 at a center-of-mass energy of 8 TeV collected with the CMS detector at the LHC. Events in which a top quark pair is produced with one top quark decaying into a charm or up quark and a Higgs boson (H), and the other top quark decaying into a bottom quark and a W boson are selected. The Higgs boson in these events is assumed to subsequently decay into either dibosons or difermions. No signi cant excess is observed above the expected standard model background, and an upper limit at the 95% con dence level is set on the branching fraction B (t ! Hc) of 0.40% and B (t ! Hu) of 0.55%, where the expected upper limits are 0.43% and 0.40%, respectively. These results correspond to upper limits on the square of the avor-changing Higgs boson Yukawa couplings j tHcj2 < 6:9 10 3 and j tHuj2 < 9:8 10 3. p; Flavour Changing Neutral Currents; Hadron-Hadron scattering (experi- 1 Introduction 2 3 4 The CMS detector and trigger Event selection and reconstruction Simulated samples Signal selection and background estimation Multilepton channels b jet + lepton channel Systematic uncertainties The CMS collaboration With the discovery of the Higgs boson (H) [1{3] it is possible to probe new physics by measuring its coupling to other particles. Of particular interest is the neutral current (FCNC) decay of the top quark to the Higgs boson. The investigation of this process at the CERN LHC is motivated by the large tt production cross section and the variety of possible decay modes of the Higgs boson. The next-to-next-to-leading-order tt production cross section at a center-of-mass energy of 8 TeV and with a top quark mass (mt) of 173.5 GeV [4] is 252 pb [5]. The standard model (SM) predicts that the top quark decays with a branching fraction of nearly 100% into a bottom quark and a Wboson (t ! Wb). In the SM, FCNC decays are absent at leading-order and occur only via loop-level processes that are additionally suppressed by the Glashow-Iliopoulos-Maiani mechanism [6, 7]. Because the leading-order decay rate of t ! Wb is also quite large, the SM branching fraction B (t ! Hq), where q is an up or charm quark, is predicted to be of O(10 15) [6{ 8], far below the experimental sensitivity at the LHC. However, some extensions of the SM predict an enhanced t ! Hq decay rate. Thus, observation of a large branching fraction would be clear evidence for new physics. The largest enhancement in B(t ! Hq) is predicted in models that incorporate a two-Higgs doublet, where the branching fraction Photons Jets b jets diphoton + lepton diphoton + hadron b jet + lepton Previous searches for FCNC in top quark decays mediated by a Higgs boson have been performed at the LHC by ATLAS [9, 10] and CMS [11]. The CMS search considered both multilepton and diphoton nal states and the observed upper limit of B(t ! Hc) at the 95% con dence level (CL) was determined to be 0.56%. The recent ATLAS result included nal states where the Higgs boson decays to b quark pairs, and measured the observed upper limits of B(t ! Hc) and B(t ! Hu) at the 95% CL to be 0.46% and 0.45%, respectively. The analysis presented here uses a data sample recorded with the CMS detector and corresponding to an integrated luminosity of 19.7 fb 1 of pp collisions at p s = 8 TeV. The data were recorded in 2012 with instantaneous luminosities of 5{8 average of 21 interactions per bunch crossing. The inelastic collisions that occur in addition to the hard-scattering process in the same beam crossing produce mainly low-pT particles that form the so-called \pileup" background. In this paper, the FCNC decays t ! Hc and t ! Hu are searched for through the processes tt ! Hc + Wb or Hu + Wb. Three independent analyses are perfomed and their results are then combined. The multilepton analysis considers events with two same-sign (SS) leptons or three charged leptons (electrons or muons). This channel is sensitive to the Higgs boson decaying into WW, ZZ, or which have branching fractions of 21.5%, 2.6%, and 6.3%, respectively [12]. The diphoton analysis considers events with two photons, a bottom quark, and a W boson that decays either hadronically or leptonically. The two photons in this channel are used to reconstruct the Higgs boson which decays to diphotons from the hadronization of bottom quarks (b jets), and a leptonically decaying W boson are considered. The b jet + lepton channel takes advantage of the large Higgs boson branching is shown in table 1. The CMS detector and trigger are described in section 2, and the event selection and reconstruction in section 3. Section 4 then discusses the Monte Carlo (MC) simulation samples. The signal selection and background estimations for each of the three analyses are given in section 5, and the systematic uncertainties in section 6. Finally, the individual and combined results from the analyses are presented in section 7. The CMS detector and trigger 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. [14]. The central feature of the CMS apparatus is a superconducting solenoid, 13 m in length and 6 m in diameter, which provides an axial magnetic eld of 3.8 T. Within the eld volume there are several particle detection systems. Charged particle trajectories are measured by silicon pixel and strip trackers, covering 0 2 in azimuth and j j < 2:5 in pseudorapidity. A lead tungstate crystal electromagnetic calorimeter (ECAL) surrounds the tracking volume. A brass and scintillator hadron calorimeter (HCAL) surrounds the ECAL and also covers the region j j < 3. The forward hadron calorimeter (HF) uses steel as the absorber and bers as the sensitive material. The HF extends the calorimeter coverage to the range 3:0 < j j < 5:2. A lead and silicon-strip preshower detector is located in front of the ECAL endcaps. Muons are identi ed and measured in gas-ionization detectors embedded in the steel ux-return yoke outside the solenoid. The detector is nearly hermetic, allowing momentum balance measurements in the plane transverse to the beam direction. Depending on the nal state under consideration, events are selected at the trigger level by either requiring at least two leptons, (ee, or e ), at least two photons, or a single lepton (e or ) to be within the detector acceptance and to pass loose identi cation and kinematic requirements. The dilepton triggers used in the multilepton selection require one lepton with pT > 17 GeV and one lepton with pT > 8 GeV. At the trigger level and during the o ine selection, electrons are required to be within j j < 2:5, and muons are required to be within j j < 2:4. All leptons must be isolated, as described in section 3, and have pT > 20 GeV for the highest-pT lepton, and pT > 10 GeV for all subsequent leptons in the event. For events satisfying the full multilepton selection, the dimuon, dielectron, and electron-muon trigger e ciencies are measured to be 98%, 91%, and 94%, respectively, for the SS dilepton selection, and 100% for the trilepton selection. The diphoton trigger requires the presence of one photon with pT > 36 GeV and a second photon with pT > 22 GeV. Loose isolation and shower shape requirements are applied to both photons [15]. The average diphoton trigger e ciency is measured to be 99.4% after applying the full event selection for photons within j j < 2:5, excluding the barrel-endcap transition region 1:44 < j j < 1:57. The b jet + lepton selection uses the single-lepton triggers. The single-muon trigger requires at least one isolated muon with pT > 24 GeV and j j < 2:1 to be reconstructed online. The single-electron trigger requires at least one isolated electron with pT > 27 GeV and j j < 2:5. The o ine selection further requires that electrons have pT > 30 GeV and muons have pT > 26 GeV. This results in an average trigger e ciency of 84% for the singleelectron triggers and 92% for the single-muon trigger after the b jet + lepton selection. Event selection and reconstruction Events are required to have a primary vertex with a reconstructed longitudinal position within 24 cm of the geometric center of the detector and a transverse position within 2 cm from the nominal interaction point. To distinguish the hard-scattering vertex from vertices arising from pileup interactions, the reconstructed vertex with the highest scalar sum of the p2T of its associated tracks is chosen as the primary vertex. To ensure that leptons originate from the same primary vertex, a loose requirement is applied to their longitudinal and transverse impact parameters with respect to the primary vertex. The particle- ow event algorithm [16, 17] is used to reconstruct and identify individual particles using an optimized combination of information from the elements of the detector. Prompt electrons and muons arising from W and Z decays are typically more isolated than nonprompt leptons arising from the decay of hadrons within jets. In order to distinguish between prompt and nonprompt lepton candidates, a relative isolation parameter is de ned for each lepton candidate. This is calculated by summing the pT of all charged and neutral particles reconstructed using the particle- ow algorithm within a cone of angular radius )2 = 0:4 around the lepton candidate momentum, where are the pseudorapidity and azimuthal angle (in radians) di erences, respectively, between the directions of the lepton and the other particle [18, 19]. This cone excludes the lepton candidate and the charged particles associated with the pileup vertices. The resulting quantity is corrected for additional underlying-event activity owing to neutral particles [3], and then divided by the lepton candidate's pT. The relative isolation parameter is required to be less than 0.15 for electrons and 0.12 for muons. The electron selection criteria are optimized using a multivariate approach that combined information from both the tracks and ECAL clusters, and have a combined identi cation and isolation e ciency of approximately 60% at low pT (10 GeV) and 90% at high pT (50 GeV) for electrons from W or Z boson decays [20]. The training of the multivariate electron reconstruction is performed using simulated events, while the performance is validated using data. Muon candidates are reconstructed with a global trajectory t using hits in the tracker and the muon system. The e ciency for muons to pass both the identi cation and isolation criteria is measured from data to be larger than 95% [3, 21]. For events in which there is an overlap between a muon and an electron, i.e., an electron R < 0:1 of a muon, precedence is given to the muon by vetoing the electron. In the multilepton selection, events in which there are more than three isolated leptons (electron or muon) with pT > 10 GeV are rejected to reduce diboson contamination. The invariant mass of dilepton pairs in the SS channel is required to be greater than 30 GeV in order to reject low-mass resonances and reduce poorly modeled backgrounds (e.g., QCD). In the b jet + lepton selection, events in which there are additional isolated electrons with pT > 20 GeV and j j < 2:5 or isolated muons with pT > 10 GeV and j j < 2:4 are rejected. The photon energy is reconstructed from the sum of signals in the ECAL crystals [15]. The ECAL signals are calibrated [22], and a multivariate regression, developed for a previ analysis [23], is used to estimate the energy of the photon. Clusters are formed from the neighboring ECAL crystals seeded around local maxima of energy deposits, and the collection of clusters that contain the energy of a photon or an electron is called a supercluster. Identi cation criteria are applied to distinguish photons from jets and electrons. The observables used in the photon identi cation criteria are the isolation variables, the ratio of the energy in the HCAL towers behind the supercluster to the electromagnetic energy in the supercluster, the transverse width in of the electromagnetic shower, and the number of charged tracks matched to the supercluster. The photon e ciency identi cation is measured using Z ! e+e events in data by reconstructing the electron showers as photons [24], taking into account the shower shape and whether the electron probe is located in the barrel or endcap. The two highest pT photons must exceed 33 and 25 GeV, Jets are reconstructed from the candidates produced by the particle- ow algorithm. An anti-kT clustering algorithm [25] with a distance parameter of 0.5 is used for jet reconstruction. Jets with a signi cant fraction of energy coming from pileup interactions or not associated with the primary vertex are rejected. Remaining pileup energy in jets is subtracted using a technique that relies on information about the jet area [26{28]. Reconstructed jets are calibrated to take into account di erences in detector response [29]. The jets in the multilepton and b jet + lepton selections are required to have pT > 30 GeV, j j < 2:5, and to be separated from leptons such that R(lepton, jet) > 0:3. The selection of jets in the diphoton events di ers by requiring the jet ET > 20 GeV and the jets be separated from both photons such that R(photon, jet) > 0:3. To characterize the amount of hadronic activity in an event, the scalar sum of the transverse energy of jets passing all of these requirements (HT) is calculated. The missing transverse energy (ETmiss) is calculated as the magnitude of the vector sum of the transverse momenta of all reconstructed particle- ow candidates in the event. Jets originating from the hadronization of b quarks are identi ed by the combined secondary vertex (CSV) b tagging algorithm [30]. The selection criteria that are used have an identi cation e ciency of 66%, and a misidenti cation rate of 18% for charm quarks and 1% for light-quark and gluon jets. The diphoton and b jet + lepton selections require b-tagged jets. Although the identi cation of b jets is not used to select signal events in the multilepton selection, it is used for the purpose of de ning control samples to check the normalization of simulated background processes. No additional tagging is used to discriminate between jets originating from c quarks. The inclusion of b jets in the diphoton and b jet + lepton selections results in a di erence in the sensitivity to the t ! Hu and t ! Hc decay modes. This is caused by the larger likelihood of b tagging a jet originating from a charm quark than from an up quark. The multilepton analyses do not include b tagging to enhance the signal sensitivity so the two FCNC top quark decay modes are indistinguishable. Simulated samples The determination of the expected signal and background yields relies on simulated events, as well as an estimation based on control samples in data, as discussed in later sections. Samples of Drell-Yan, tt, W+jets, W + bb, diboson, tt + Z, tt + W, and triboson events are generated using the MadGraph event generator (v5.1.5.11) [31]. The samples of ZZ to four charged leptons and single top quark events are generated using powheg (v1.0 r1380) [32{ 34]. In all cases, hadronization and showering are done through pythia (v6.426) [35], and decays are simulated using tauola (v2.75) [36]. Three additional production processes are considered for the nonresonant diphoton backgrounds, where the dominant one coming + jets is simulated with sherpa (v1.4.2) [37]. Top quark pairs with one additional photon are simulated with MadGraph, while those with two additional photons are simulated using the whizard (v2.1.1) [38] generator interfaced with pythia. The Z2 tune [39] of pythia is used to model the underlying event. Events that arise from the SM Higgs boson production are treated as a background. The gluon-fusion (ggH) and vector-boson-fusion (VBF) Higgs boson production processes are generated with powheg at next-to-leading order (NLO) in QCD, interfaced with pythia. The associated W/ZH production and ttH processes are simulated with pythia at leading order. The cross sections and branching fractions of the SM Higgs boson processes are set to the values recommended by the LHC Higgs cross section working group [12]. using pythia for the case of the Higgs boson decaying to WW, ZZ, MadGraph for H ! bb. The use of di erent generators is an artifact of the various modes being analyzed separately. The Higgs boson is assumed to have a mass of 125 GeV. The set of parton distribution functions (PDF) used is CTEQ6L [40] in all cases, except for H ! bb, where CT10 [41] is used. The CMS detector response is simulated using a Geant4-based (v9.4) [42] model, and the events are reconstructed and analyzed using the same software used to process collision data. The e ect of pileup is included in the simulation process by superimposing simulated events on the process of interest. The simulated signal events are weighted to account for the di erences between data and simulation of the trigger, reconstruction, and isolation e ciencies, and the distributions of the reconstructed vertices coming from pileup. Additional corrections are applied to account for the energy scale and lepton pT resolution. The observed jet energy resolution and scale [29], top quark pT distribution [43], and b tagging e ciency and discriminator distribution [44] in data are used to correct the simulated events. Corrections accounting for the di erences in lepton selection e ciencies are derived using the tag-and-probe technique [45]. Signal selection and background estimation The sensitivity of the search is enhanced by combining the twelve exclusive channels, shown in table 1, de ned according to the expected decay modes of the Higgs and W bosons. Multilepton channels The multilepton analysis is conducted with the goal of enhancing the signal sensitivity in the trilepton channel: tt ! Hq + Wb ! ` ` q + ` b, and the SS dilepton channel: tt ! Hq + Wb ! ` qqq + ` b, where ` represents either a muon or electron. The main target of optimization is nal states resulting from H ! WW decays. In the case of the trilepton channel, rejection of events containing dileptons originating from resonant Z boson production is necessary to remove backgrounds from WZ production, asymmetric internal conversions (AIC, the process in which nal-state radiation in a Drell-Yan event converts to dileptons where one of the leptons carries most of the photon momentum) [46] or nal-state radiation where the photon is misidenti ed as an electron. A Trilepton invariant mass versus opposite-sign dilepton invariant mass in the trilepton channel after the event selection described in section 3 for simulated signal, estimated background, and data, from left to right. comparison of the two-dimensional distribution of the trilepton mass versus the oppositesign dilepton mass is shown in gure 1 for the estimated signal and background processes, and data. Events satisfying any of the following criteria are vetoed to reduce the contribution from resonant Z production: (1) the invariant mass of an opposite-sign, same- avor (OSSF) lepton pair is within 15 GeV of the Z boson mass [4]; (2) the invariant mass of an OSSF lepton pair is greater than 30 GeV and the trilepton invariant mass is within 10 GeV of the Z boson mass. For the SS dielectron channel, electron pairs with an invariant mass within 15 GeV of the Z boson mass are rejected to reduce the background arising from misidenti cation of the electron charge. No invariant mass requirement is applied to nal states since there is a negligible contamination from resonant Z The jet multiplicity after rejecting events containing a Z boson is shown in gure 2. To improve the sensitivity of the search, we require at least two jets in the nal state. Figure 3 shows the ETmiss and HT distributions for trilepton and SS dilepton events after applying the Z veto and jet requirement. A candidate event in the trilepton channel has no additional requirements on ETmiss or HT. The SS events are required to pass an ETmiss-dependent HT requirement (shown in table 2) and have ETmiss greater than 30 GeV. The ETmiss and HT requirements are obtained by maximizing the estimated signal signi cance, de ned as the number of signal events over the square root of the number of background events. The main sources of background can be divided into two categories according to the origin of the identi ed leptons and the ETmiss. These include (1) irreducible background processes: events with leptons originating from the decay of SM bosons and having large ETmiss arising from neutrinos; (2) reducible background processes: events with misidentied leptons produced either by nonprompt leptons from hadron decays (e.g., semileptonic decays of B mesons), by misidenti ed hadrons, or by mismeasurement of the lepton charge. Given that at least two isolated leptons and two jets are required in the nal state, the main sources of irreducible backgrounds are tt associated with vector boson production, t→ Hc (B = 3%) t→ Hc (B = 3%) leptons (right) after rejecting events with Z bosons. The data are represented by the points with used for the sake of improved visualization. The dominant backgrounds are represented with lled histograms and the background (BG) uncertainty is shown as shaded bands. channel. An event is selected if it satis es one of the three listed sets. WZ ! 3` , ZZ ! 4`, Z ! 4`, and, to a lesser extent, triboson and W The contribution from all of these processes except Z ! 4` production are estimated from simulated samples. The WZ cross section used in the simulation is cross-checked against a control sample from data that is enriched in WZ events by requiring that there be three leptons, with two of them forming a dilepton pair whose invariant mass is consistent with a Z boson. No correction to the WZ normalization is needed. This sample is also used to assess the systematic uncertainty in the simulation of the background. For the presentation of the results, several of the backgrounds are grouped into a single category referred to as the rare backgrounds. The rare background contribution is estimated mainly from simulation (see the following paragraph), and the processes include ZZ ! 4`, tt+Z, tt+W, triboson, W W , and tt+H. The WZ ! 3` background contribution is presented separately. The residual contribution in the trilepton channel from asymmetric internal conversions (AIC) arising from Drell-Yan events is estimated using a data-driven technique [46] that events in data to model Z ! `+` + e= events. This is because the process that gives rise to the two nal states is the same ( nal-state radiation in Drell-Yan events), and the third lepton that is detected in the AIC event carries most of the photon momentum. The `+` + events are scaled based on photon pT-dependent weights coming t→ Hc (B = 3%) t→ Hc (B = 3%) 1 / 16 s t→ Hc (B = 3%) t→ Hc (B = 3%) 20 40 60 80 100 120 140 20 40 60 80 100 120 140 100 200 300 400 500 100 200 300 400 500 (right) channels in data (points with bars) and predicted by the SM background simulations ( lled histograms) after rejecting events containing Z bosons, requiring at least two jets, and the event selection described in section 3. The overall background uncertainty is shown in shaded black. The expected signal assuming a B(t ! Hc) of 3% is shown by the un lled histogram. from a control sample de ned as having a three-body invariant mass within 15 GeV of the Z boson mass. The average conversion probabilities for photons in dimuon and dielectron events are (0:57 0:07)% and (0:7 There are two major types of reducible backgrounds coming from bb, Drell-Yan, W+jets, and tt processes. One source comes from events with either nonprompt leptons produced during the hadronization process of the outgoing quarks (e.g., semileptonic decays of B mesons) or hadrons misidenti ed as prompt leptons. The other source originates from the charge misidenti cation of a lepton in the more frequent production of opposite-sign dileptons. This background mostly contaminates the SS dielectron nal states. Data-driven methods are used to estimate these two types of reducible backgrounds. Mismeasuring the charge of a lepton can be a signi cant source of background in SS dilepton nal states when there are one or more electrons. Even though the probability for mismeasuring the charge of an electron is relatively low ( 0:1%), the production rate of opposite-sign dileptons is very high in comparison to processes that result in genuine SS dileptons. The probability of mismeasuring the charge of a muon is negligible (<10 6) and is therefore not considered here. In order to estimate the probability of misidentifying the charge of an electron from data, a control sample is selected consisting of events containing a dielectron pair with an invariant mass within 15 GeV of the Z boson mass. The rate of charge misidenti cation is then determined from the ratio of the number of SS events to opposite-sign events as a function of pT and . The measured charge misidenti cation for electrons with j j < 1:48 is less than 0.2% for pT < 100 GeV, while for j j > 1:48 it is 0.1% at 10 GeV and increases with pT to 2.5% at 125 GeV. These measurements are in agreement with those obtained from simulated Drell-Yan events. Two control samples are used to estimate the misidenti cation rate of prompt leptons [47{49]: one region is enriched in bb events; the other is enriched in Z + jet production. Both samples are used to estimate the probability of misidentifying nonprompt electrons and muons as a function of pT and . The measured misidenti cation rate for electrons ranges from 2% to 8% and for muons ranges from 1% to 6%. Simulated events are used to correct for the contamination arising from prompt leptons in the nonprompt misidenti cation rate measurement (e.g., WZ production in the Z+jet control region). The rates are then applied to events where one or more of the lepton candidates fail the tight lepton identi cation requirements. The di erences between the nonprompt misidenti cation rates in the two measurement regions and the signal region are then used to estimate the systematic uncertainty of this background. To further assess the systematic uncertainty, the misidenti cation rates are also measured in simulated events that reproduce the background composition of events in the signal region and compared to the rates measured The predicted numbers of background and signal events for the trilepton and SS dileptons are given in table 3. The backgrounds are separated into nonprompt lepton, charge misidenti cation, WZ ! 3` , and the rare backgrounds. The predicted number of sigtable 3, is consistent with the predicted number of background events. Diphoton channel The diphoton analysis is performed using both leptonic and hadronic W boson decays: diphoton system m q + qqb. The mass of the is the primary variable used to search for the Higgs boson decay. The contribution of the nonresonant backgrounds is estimated by tting the m from data in the mass range 100 < m < 180 GeV, whereas the contribution of resonant backgrounds is taken from the simulation. The two highest-pT photons must have pT > m =3 and pT > m The use of pT thresholds scaled by m prevents a distortion of the low end of the m spectrum that would result from a xed threshold [50]. In the rare case of multiple diphoton candidates in an event, the one with the highest pT sum is selected. Charge misidenti cation both statistical and systematic uncertainties added in quadrature. The total number of observed events is given in the last row. The hadronic analysis uses events with at least four jets and exactly one b jet. The b jet and the three jets with the highest pT are used to reconstruct the invariant mass of the two top quarks, mj and mbjj. There are three possible (mj ; mbjj) pairs per event. The combination of jets with the minimum value of jmj =mbjj 1j + jmbjj=mj selected. The allowed ranges for mj , mbjj, and the W boson mass mW associated with mbjj are obtained by maximizing the signal signi cance S= B in the simulation, where S is the number of signal events and B is number of the background events. The background events are assumed to come from +jets and are taken from simulation. The highest signal signi cance is found to be 16% obtained for 142 The leptonic analysis uses events with at least three jets, exactly one b jet, and at least one lepton. The reconstructed top mass mb ` is found from the b jet, the lepton, and ETmiss. The longitudinal momentum of the neutrino is estimated by using the W boson mass as a constraint, which leads to a quadratic equation. If the equation has a complex solution, the real part of the solution is used. If the equation has two real solutions, the one with the smaller value of jmj =mb` 1j + jmb` =mj 1j is chosen. The mass windows for mbjj, mj , and mW are the same as in the hadronic channel. The signal region is de ned using the experimental width of the Higgs boson, 1.4 GeV, around the nominal mass peak position. As in the analysis of the inclusive SM Higgs boson decaying into diphotons [50], the signal shape of the diphoton invariant mass distribution is described by the sum of three Gaussian functions. Although the contribution from the SM Higgs boson background, dominated by the ttH process, is relatively small in comparison to the contribution of the nonresonant diphoton background, the resonant diphoton background cannot be ignored because it has a very similar m Signal + total background fit Signal + total background fit en 8 100 110 120 130 140 150 160 170 180 100 110 120 130 140 150 160 170 180 distribution and the t result of the hadronic (left) and leptonic (right) channels. The dashed line represents the component of the nonresonant diphoton background, while the solid line represents the total background plus signal. The shaded bands represent one and two standard deviation uncertainties of the t. To determine the shape of the nonresonant diphoton background, a function consisting of a test model and the resonant diphoton background is tted to the data under the background-only hypothesis. The model of the resonant diphoton background is the same as the signal function. The background function is used to generate 1000 pseudo-experiment samples that are tted with the background plus signal probability density function. A pull is then de ned as (N t Ngen)= N t , where N t is the tted number of signal events in the pseudo-experiments, Ngen is the number of generated signal events, and is veri ed by injecting signal in the pseudo-experiments. Several models are tried, and the chosen function for nonresonant diphoton background is the one whose bias (o set of the pull distribution) is less than 0.15 and with the minimum number of degrees of freedom for the entire set of tested models. A third-order Bernstein polynomial is selected as the functional form of the background for both the hadronic and leptonic channels. After determining the function to describe the nonresonant diphoton background, a function given by the sum of probability density functions of the resonant and nonresonant diphoton backgrounds and signal is tted to the data. The normalization of the resonant diphoton background is allowed to vary within its uncertainties, while the normalization of the nonresonant component is unconstrained. Table 4 gives a summary of the observed and expected event yields for the two diphoton channels and gure 4 shows the t result overlaid with the data. b jet + lepton channel The basic event selection requirements for the b jet + lepton channel are a single-lepton trigger, one isolated lepton, a minimum ETmiss of 30 GeV, and at least four jets, with at least three of them tagged as b jets. The background is dominated by tt ! bbW+W Nonresonant background Resonant background diphoton selection in the hadronic and leptonic channels in the 100 < m < 180 GeV mass range. 19.7 fb-1 (8 TeV) t→Hc (B=3%) 19.7 fb-1 (8 TeV) t→Hc (B=3%) lepton and neutrino. lepton events has been applied: the ETmiss distribution (left) and the reconstructed transverse mass production. Figure 5 shows the distributions of ETmiss and the W boson transverse mass (MT) for data and simulation after the basic event selection criteria are applied. The transverse mass is de ned as MT = `T is the pT of the lepton, ETmiss is used in place of the pT of the neu(`; )) is the azimuthal angular di erence between the directions of the For both top quark decays t ! Hq ! bbj and t ! Wb ! b` , a full reconstruction of the top quark invariant mass mHq or mWb is possible. However, combinatorial background arises since there is no unambiguous way to match multiple light-quark and b quark jets with the nal-state quarks. Therefore, all possible combinations are examined and a multivariate analysis (MVA) technique [51] is used to select the best candidate for each event. Several variables based on event kinematics and event topology are examined. Considering their signal-to-background separation power, the following variables are used to form a boosted decision tree (BDT) classi er [51]: the invariant masses mHq and mHb of the reconstructed top quarks, the energy of the u or c jet from the t ! qH in the rest frame of its parent top quark, the azimuthal angle between the reconstructed top quarks directions, the azimuthal angle between the reconstructed W boson and the associated b jet the azimuthal angle between the Higgs boson and the associated jet directions, the azimuthal angle between the directions of the b jets resulting from the Higgs The BDT classi er is trained with the correct and wrong combinations of simulated FCNC events determined from the generator-level parton matching. Because only event kinematics and topological variables are used, the Hu and Hc channels share the same BDT classi er. The jet-parton assignment in each event is determined by choosing the combination with the largest BDT classi er score, resulting in the correct assignment in 54% of events, as determined from simulation. The signal is determined using a template t of the output of an arti cial neural network (ANN) [51]. The ANN takes its inputs from the invariant mass of the reconstructed Higgs boson candidate and the CSV discriminator variables of the three b jets from the hadronic top quark and Higgs boson daughters. The training of the ANN is done separately for the t ! Hu and t ! Hc channels. A control sample dominated by tt is selected to validate the simulation used in the training. The sample is constructed by requiring one lepton and four jets, of which exactly two are b jets. Figure 6 show the results of the t performed with the 6840 observed events. The observed number of events and the expected yields of the signal and the main backgrounds estimated from simulation are shown in table 5. The estimated background and signal based on the t of the ANN discriminator output is shown in table 6. The number of signal and background events from the t result for the Hc channel are 74 950 (syst), respectively. The corresponding yields for the Hu channel 59 (syst) and 6640 800 (syst), respectively. Systematic uncertainties In the t to the data, systematic uncertainties are treated as nuisance parameters. Each of them is assigned a log-normal or Gaussian pdf, which is included into the likelihood in a frequentist manner by interpreting it as signal arising from pseudo-measurement distributions. Nuisance parameters can a ect either the signal yield, the shape of kinematic variable distributions, or both. If a speci c source of uncertainty is not included for a given channel, it indicates that the uncertainty is either not applicable to that channel or is found to have negligible impact on the result. B(t → Hu) = 3% B(t → Hc) = 3% Neural network discriminator Neural network discriminator background (lines) where the ANN was trained to discriminate the backgrounds from either t ! Hc (left) or t ! Hu (right) decays. The solid line shows the result of the t of the signal and background templates to data. The dotted line gives the predicted signal distribution from simulation for Predicted number of events Uncertainties combine both statistical and systematic components in quadrature. tting the ANN output trained on t ! Hc and t ! Hu nal states. Uncertainties are statistical and systematic values, respectively. The observed number of events is shown in the last row. The sources of uncertainties common to all analysis channels are: the uncertainty in the total integrated luminosity (2.6%) [52]; the e ects of the event pileup modeling for the signal samples (0.2{3%), which is particularly important for the b jet + lepton channel; the uncertainty in the Higgs boson branching fractions (5%) [13]; the uncertainty in the tt cross section (7.5%) [53]; the uncertainty in the jet energy scale (1{15%) [29] and resolution (0.4{8%), where the larger uncertainty is for the b jet + lepton selection; the uncertainty in the PDF used in the event generators (< 9%) [54]; the assumed top quark pT distribution (1{4%) [43]; the ETmiss resolution (0.2{4%) [29]; the uncertainty in the trigger e ciency (<2%); and the corrections applied to the simulation to account for the di erences in lepton identi cation and isolation e ciencies in data and simulation (0.01{6%), where the larger uncertainty is for the selection of events with a three-electron The uncertainties speci c to the signal description and background estimation for the multilepton analysis come from the 11{13% uncertainty in the ttW and ttZ theoretical cross sections [55]; the 15% uncertainty in the WZ normalization (determined from a control region); the uncertainty in the lepton misidenti cation rate (40% for electrons, 30% for muons); and the 20% uncertainty in the electron charge mismeasurement probability. The uncertainties speci c to the signal description and background estimation for the diphoton channels are the corrections applied to the simulation to account for di erences of the photon identi cation e ciency in data and simulation (0.1{5%); and the uncertainty in the jet and b jet identi cation e ciency (2{3.5%) [30]. The resonant background from the SM Higgs boson production has an uncertainty of 8.1% from the PDF uncertainty and 9.3% from the QCD scale [56]. The uncertainties speci c to the signal description and background estimation for the b jet + lepton channel are dominated by the b jet identi cation. The uncertainty in the b tagging correction has two components: one is from the sample purity (4%) [30] and the other from the sample statistical uncertainty (24%). The uncertainty in the tt+jets cross section, determined using a leading-order event generator, is 1%. The uncertainty in the modeling of the heavy- avor daughters of the W decay in the tt simulated sample is estimated to be 3%. Additional uncertainties arise from the event generator parameters such as the renormalization and factorization scales (5%) [41], the parton-jet matching threshold (1{9%), and the top quark mass (4%). The uncertainties owing to the integrated luminosity, jet energy scale and resolution, pileup, reconstruction of physics objects, signal PDFs, and top quark related uncertainties are assumed to be fully correlated, while all others are treated as uncorrelated. The systematic uncertainties are summarized in table 7. The expected number of events from the SM background processes and the expected numtables 3, 4, and 6 for the multilepton, diphoton, and b jet + lepton selections, respectively. nal results are based on the combination of 12 channels: three SS dilepton, four trilepton, one diphoton + hadrons, two diphoton + lepton, and two b jet + lepton. The Higgs boson branching fraction Jet energy resolution Top quark pT correction Trigger e ciency Identi cation and isolation Lepton misidenti cation Charge misidenti cation Photon identi cation e ciency Corrections per photon - energy resolution - material mismodeling Jet identi cation e ciency b jet identi cation e ciency Higgs boson background - cross section scale factors b jet CSV distribution - statistical precision tt + heavy avor jets Modeling W decay daughters - matching parton-jet threshold - top quark mass are quoted to indicate values that vary across the di erent analyses. is not considered. combination requires the simultaneous t of the data selected by all the individual analyses, accounting for all statistical and systematic uncertainties, and their correlations. As Hq) is expected to be small, the possibility of both top quarks decaying via FCNC No excess beyond the expected SM background is observed and upper limits at the 95% CL on the branching fractions of t ! Hc and t ! Hu are determined using the modi ed frequentist approach (asymptotic CLs method [57{59]). The observed 95% CL upper limits on the branching fractions B(t ! Hc) and B(t ! Hu) are 0.40% and 0.55%, respectively, obtained from the combined multilepton, diphoton, and b jet + lepton channels. A summary of the observed and expected limits is presented in table 8. The diphoton channels are signi cantly more sensitive than the other channels, largely because of the lower uncertainty in the background model. The multilepton and b jet + lepton channels provide a 15% (37%) improvement on the observed (expected) upper limit when combined with the diphoton channel. A previous search for FCNC mediated by Higgs boson interactions via the t ! Hc decay at the LHC made use of trilepton and diphoton nal states [11]. The inclusion of new channels (SS dilepton, diphoton, and b jet + lepton nal states) in addition to re nements in the trilepton and diphoton channels results in an improvement of 30% (34%) in the observed (expected) upper limit on B(t ! Hc). The partial width of the t ! Hq process is related to the square of the Yukawa coupling tq by the formula [60, 61]: t!Hq = coupling is ignored is adopted here: this introduces a factor of two when comparing to the ATLAS result.) Assuming the t ! Wb partial width to be dominant, the upper limit on the t ! Hq branching fractions can be translated into an upper limit on the square of the couplings using the relations: B(t ! Hc) = t!Hc= Total = (0:58 B(t ! Hu) = t!Hu= Total = (0:56 where the CKM matrix element jVtbj is assumed to be equal to unity in the NLO order calculation [62] of t!Wb = 1:372 GeV, and uncertanties arise from uncertainties mc = 1:29 GeV, and mu = 2:3 MeV are used. Based on the analysis results, the observed (expected) 95% CL upper limits on the squares of the top-Higgs Yukawa couplings are: A search for avor-changing neutral currents in the decay of a top quark to a charm or up quark and a Higgs boson based on p s = 8 TeV proton-proton collisions has been presented. Samples of multilepton, diphoton, and b jet + lepton events were selected Multilepton combined b jet + lepton Multilepton combined b jet + lepton jet + lepton; and the combination of all channels. For the expected upper limit, the limit plus and minus a standard deviation are also shown. from data recorded with the CMS detector, corresponding to an integrated luminosity of to decay into WW, ZZ, , and bb. No excess of events above the SM background is observed, and branching fractions of B(t ! Hc) larger than 0.40% and B(t ! Hu) larger than 0.55% are excluded at the 95% con dence level. These observed upper limits on B(t ! 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Kunsken, J. Lingemann, A. Nehrkorn, A. Nowack, I.M. Nugent, C. Pistone, O. Pooth, A. Stahl15 Deutsches Elektronen-Synchrotron, Hamburg, Germany M. Aldaya Martin, I. Asin, K. Beernaert, O. Behnke, U. Behrens, A.A. Bin Anuar, K. Borras18, A. Campbell, P. Connor, C. Contreras-Campana, F. Costanza, C. Diez Pardos, G. Dolinska, G. Eckerlin, D. Eckstein, E. Gallo19, J. Garay Garcia, A. Geiser, A. Gizhko, J.M. Grados Luyando, P. Gunnellini, A. Harb, J. Hauk, M. Hempel20, H. Jung, A. Kalogeropoulos, O. Karacheban20, M. Kasemann, J. Keaveney, J. Kieseler, C. Kleinwort, I. Korol, W. Lange, A. Lelek, J. Leonard, K. Lipka, A. Lobanov, W. Lohmann20, R. Mankel, I.-A. Melzer-Pellmann, A.B. Meyer, G. Mittag, J. Mnich, A. Mussgiller, E. Ntomari, D. Pitzl, R. Placakyte, A. Raspereza, B. Roland, M.O . Sahin, P. Saxena, T. Schoerner Sadenius, C. Seitz, S. Spannagel, N. Stefaniuk, K.D. Trippkewitz, G.P. Van Onsem, R. Walsh, C. Wissing University of Hamburg, Hamburg, Germany V. Blobel, M. Centis Vignali, A.R. Draeger, T. Dreyer, E. Garutti, K. Goebel, D. Gonzalez, J. Haller, M. Ho mann, R.S. Hoing, A. Junkes, R. Klanner, R. Kogler, N. Kovalchuk, T. Lapsien, T. Lenz, I. Marchesini, D. Marconi, M. Meyer, M. Niedziela, D. Nowatschin, J. Ott, F. Pantaleo15, T. Pei er, A. Perieanu, J. Poehlsen, C. Sander, C. Scharf, P. Schleper, E. Schlieckau, A. Schmidt, S. Schumann, J. Schwandt, H. Stadie, G. Steinbruck, F.M. Stober, M. Stover, H. Tholen, D. Troendle, E. Usai, L. Vanelderen, A. Vanhoefer, B. Vormwald Institut fur Experimentelle Kernphysik, Karlsruhe, Germany C. Barth, C. Baus, J. Berger, E. Butz, T. Chwalek, F. Colombo, W. De Boer, A. Dierlamm, S. Fink, R. Friese, M. Gi els, A. Gilbert, D. Haitz, F. Hartmann15, S.M. Heindl, U. Husemann, I. Katkov16, A. Kornmayer15, P. Lobelle Pardo, B. Maier, H. Mildner, M.U. Mozer, T. Muller, Th. Muller, M. Plagge, G. Quast, K. Rabbertz, S. Rocker, M. Weber, T. Weiler, S. Williamson, C. Wohrmann, R. Wolf Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece I. Topsis-Giotis G. Anagnostou, G. Daskalakis, T. Geralis, V.A. Giakoumopoulou, A. Kyriakis, D. Loukas, National and Kapodistrian University of Athens, Athens, Greece 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, MTA-ELTE Lendulet CMS Particle and Nuclear Physics Group, Eotvos Lorand University, Budapest, Hungary Wigner Research Centre for Physics, Budapest, Hungary G. Bencze, C. Hajdu, P. Hidas, D. Horvath21, F. Sikler, V. Veszpremi, G. Vesztergombi22, Institute of Nuclear Research ATOMKI, Debrecen, Hungary N. Beni, S. Czellar, J. Karancsi23, J. Molnar, Z. Szillasi University of Debrecen, Debrecen, Hungary M. Bartok22, A. Makovec, P. Raics, Z.L. Trocsanyi, B. Ujvari National Institute of Science Education and Research, Bhubaneswar, India S. Bahinipati, S. Choudhury24, P. Mal, K. Mandal, A. Nayak25, D.K. Sahoo, N. Sahoo, 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, S. Keshri, A. Kumar, S. Malhotra, M. Naimuddin, N. Nishu, K. Ranjan, R. Sharma, V. Sharma Saha Institute of Nuclear Physics, Kolkata, India R. Bhattacharya, S. Bhattacharya, K. Chatterjee, S. Dey, S. Dutt, S. Dutta, S. Ghosh, N. Majumdar, A. Modak, K. Mondal, S. Mukhopadhyay, S. Nandan, A. Purohit, A. Roy, D. Roy, S. Roy Chowdhury, S. Sarkar, M. Sharan, S. Thakur Indian Institute of Technology Madras, Madras, India Bhabha Atomic Research Centre, Mumbai, India R. Chudasama, D. Dutta, V. Jha, V. Kumar, A.K. Mohanty15, P.K. Netrakanti, L.M. Pant, P. Shukla, A. Topkar Tata Institute of Fundamental Research-A, Mumbai, India T. Aziz, S. Dugad, G. Kole, B. Mahakud, S. Mitra, G.B. Mohanty, N. Sur, B. Sutar Tata Institute of Fundamental Research-B, Mumbai, India S. Banerjee, M. Guchait, Sa. Jain, G. Majumder, K. Mazumdar, N. Wickramage26 Indian Institute of Science Education and Research (IISER), Pune, India S. Chauhan, S. Dube, A. Kapoor, K. Kothekar, A. Rane, S. Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran H. Bakhshiansohi, H. Behnamian, S. Chenarani27, E. Eskandari Tadavani, S.M. Etesami27, A. Fahim28, M. Khakzad, M. Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi, F. Rezaei Hosseinabadi, B. Safarzadeh29, M. Zeinali University College Dublin, Dublin, Ireland M. Felcini, M. Grunewald INFN Sezione di Bari a, Universita di Bari b, Politecnico di Bari c, Bari, Italy M. Abbresciaa;b, C. Calabriaa;b, C. Caputoa;b, A. Colaleoa, D. Creanzaa;c, L. Cristellaa;b, N. De Filippisa;c, M. De Palmaa;b, L. Fiorea, G. Iasellia;c, G. Maggia;c, M. Maggia, G. Minielloa;b, S. Mya;b, S. Nuzzoa;b, A. 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Paolettia, G. Sguazzonia, L. Viliania;b;15 INFN Laboratori Nazionali di Frascati, Frascati, Italy L. Benussi, S. Bianco, F. Fabbri, D. Piccolo, F. Primavera15 INFN Sezione di Genova a, Universita di Genova b, Genova, Italy V. Calvellia;b, F. Ferroa, M. Lo Veterea;b, M.R. Mongea;b, E. Robuttia, S. Tosia;b INFN Sezione di Milano-Bicocca a, Universita di Milano-Bicocca b, Milano, Manzonia;b;15, Marzocchia;b, L. Moronia, M. Paganonia;b, D. Pedrinia, S. Pigazzini, S. Ragazzia;b, T. Tabarelli de Fatisa;b INFN Sezione di Napoli a, Universita di Napoli 'Federico II' b, Napoli, Italy, Universita della Basilicata c, Potenza, Italy, Universita G. Marconi d, Roma, S. Buontempoa, N. Cavalloa;c, G. De Nardo, S. Di Guidaa;d;15, M. Espositoa;b, F. Fabozzia;c, A.O.M. Iorioa;b, G. Lanzaa, L. Listaa, S. Meolaa;d;15, M. Merolaa, P. Paoluccia;15, C. Sciaccaa;b, F. Thyssen INFN Sezione di Padova a, Universita di Padova b, Padova, Italy, Universita di Trento c, Trento, Italy P. Azzia;15, N. Bacchettaa, L. Benatoa;b, D. Biselloa;b, A. Bolettia;b, R. Carlina;b, A. Carvalho Antunes De Oliveiraa;b, P. Checchiaa, M. Dall'Ossoa;b, P. De Castro Manzanoa, T. Dorigoa, U. Dossellia, F. Gasparinia;b, U. Gasparinia;b, A. Gozzelinoa, S. Lacapraraa, M. Margonia;b, A.T. Meneguzzoa;b, J. Pazzinia;b;15, N. Pozzobona;b, P. Ronchesea;b, F. Simonettoa;b, E. Torassaa, M. Zanetti, P. Zottoa;b, A. Zucchettaa;b, G. Zumerlea;b INFN Sezione di Pavia a, Universita di Pavia b, Pavia, Italy A. Braghieria, A. Magnania;b, P. Montagnaa;b, S.P. Rattia;b, V. Rea, C. Riccardia;b, P. Salvinia, I. Vaia;b, P. Vituloa;b INFN Sezione di Perugia a, Universita di Perugia b, Perugia, Italy L. Alunni Solestizia;b, G.M. Bileia, D. Ciangottinia;b, L. Fanoa;b, P. Laricciaa;b, R. Leonardia;b, G. Mantovania;b, M. Menichellia, A. Sahaa, A. Santocchiaa;b INFN Sezione di Pisa a, Universita di Pisa b, Scuola Normale Superiore di Pisa c, Pisa, Italy K. Androsova;30, P. Azzurria;15, G. Bagliesia, J. Bernardinia, T. Boccalia, R. Castaldia, M.A. Cioccia;30, R. Dell'Orsoa, S. Donatoa;c, G. Fedi, A. Giassia, M.T. Grippoa;30, F. Ligabuea;c, T. Lomtadzea, L. Martinia;b, A. Messineoa;b, F. Pallaa, A. Rizzia;b, A. SavoyNavarroa;31, P. Spagnoloa, R. Tenchinia, G. Tonellia;b, A. Venturia, P.G. Verdinia INFN Sezione di Roma a, Universita di Roma b, Roma, Italy L. Baronea;b, F. Cavallaria, M. Cipriania;b, G. D'imperioa;b;15, D. Del Rea;b;15, M. Diemoza, S. Gellia;b, C. Jordaa, E. Longoa;b, F. Margarolia;b, P. Meridiania, G. Organtinia;b, R. Paramattia, F. Preiatoa;b, S. Rahatloua;b, C. Rovellia, F. Santanastasioa;b INFN Sezione di Torino a, Universita di Torino b, Torino, Italy, Universita del Piemonte Orientale c, Novara, Italy N. Amapanea;b, R. Arcidiaconoa;c;15, S. Argiroa;b, M. Arneodoa;c, N. Bartosika, R. Bellana;b, C. Biinoa, N. Cartigliaa, M. Costaa;b, R. Covarellia;b, A. Deganoa;b, N. Demariaa, L. Fincoa;b, B. Kiania;b, C. Mariottia, S. Masellia, E. Migliorea;b, V. Monacoa;b, E. Monteila;b, M.M. Obertinoa;b, L. Pachera;b, N. Pastronea, M. Pelliccionia, G.L. Pinna Angionia;b, F. Raveraa;b, A. Romeroa;b, M. Ruspaa;c, R. Sacchia;b, K. Shchelinaa;b, V. Solaa, A. Solanoa;b, A. Staianoa, P. Traczyka;b INFN Sezione di Trieste a, Universita di Trieste b, Trieste, Italy S. Belfortea, V. Candelisea;b, M. Casarsaa, F. Cossuttia, G. Della Riccaa;b, C. La Licataa;b, A. Schizzia;b, A. Zanettia Kyungpook National University, Daegu, Korea D.H. Kim, G.N. Kim, M.S. Kim, S. Lee, S.W. Lee, Y.D. Oh, S. Sekmen, D.C. Son, H. Kim, A. Lee Chonbuk National University, Jeonju, Korea Hanyang University, Seoul, Korea J.A. Brochero Cifuentes, T.J. Kim Korea University, Seoul, Korea S. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, Y. Jo, Y. Kim, B. Lee, K. Lee, K.S. Lee, S. Lee, J. Lim, S.K. Park, Y. Roh Seoul National University, Seoul, Korea J. Almond, J. Kim, S.B. Oh, S.h. Seo, U.K. Yang, H.D. Yoo, G.B. Yu University of Seoul, Seoul, Korea M. Choi, H. Kim, H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park, G. Ryu, M.S. Ryu Sungkyunkwan University, Suwon, Korea Y. Choi, J. Goh, D. Kim, E. Kwon, J. Lee, I. Yu Vilnius University, Vilnius, Lithuania V. Dudenas, A. Juodagalvis, J. Vaitkus National Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Malaysia I. Ahmed, Z.A. Ibrahim, J.R. Komaragiri, M.A.B. Md Ali32, F. Mohamad Idris33, W.A.T. Wan Abdullah, M.N. Yusli, Z. Zolkapli Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico H. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-De La Cruz34, A. Hernandez-Almada, R. Lopez-Fernandez, J. Mejia Guisao, A. Sanchez-Hernandez Universidad Iberoamericana, Mexico City, Mexico S. Carrillo Moreno, F. Vazquez Valencia Benemerita Universidad Autonoma de Puebla, Puebla, Mexico S. Carpinteyro, I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad Autonoma de San Luis Potos , San Luis Potos , Mexico A. Morelos Pineda University of Auckland, Auckland, New Zealand University of Canterbury, Christchurch, New Zealand National Centre for Physics, Quaid-I-Azam University, Islamabad, Pakistan A. Ahmad, M. Ahmad, Q. Hassan, H.R. Hoorani, W.A. Khan, M.A. Shah, M. Shoaib, National Centre for Nuclear Research, Swierk, Poland H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Gorski, M. Kazana, K. Nawrocki, K. Romanowska-Rybinska, M. Szleper, P. Zalewski Institute of Experimental Physics, Faculty of Physics, University of Warsaw, K. Bunkowski, A. Byszuk35, K. Doroba, A. Kalinowski, M. Konecki, J. Krolikowski, M. Misiura, M. Olszewski, M. Walczak Laboratorio de Instrumentac~ao e F sica Experimental de Part culas, Lisboa, Joint Institute for Nuclear Research, Dubna, Russia P. Bunin, A. Golunov, I. Golutvin, N. Gorbounov, V. Karjavin, V. Korenkov, A. Lanev, A. Malakhov, V. Matveev36;37, V.V. Mitsyn, P. Moisenz, V. Palichik, V. Perelygin, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, E. Tikhonenko, A. Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia L. Chtchipounov, V. Golovtsov, Y. Ivanov, V. Kim38, E. Kuznetsova39, V. Murzin, V. Oreshkin, V. Sulimov, A. Vorobyev Institute for Nuclear Research, Moscow, Russia Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov, N. Krasnikov, A. Pashenkov, D. Tlisov, A. Toropin Institute for Theoretical and Experimental Physics, Moscow, Russia V. Epshteyn, V. Gavrilov, N. Lychkovskaya, V. Popov, I. Pozdnyakov, G. Safronov, A. Spiridonov, M. Toms, E. Vlasov, A. Zhokin { 33 { National Research Nuclear University 'Moscow Engineering Physics Institute' (MEPhI), Moscow, Russia R. Chistov40, V. Rusinov, E. Tarkovskii P.N. Lebedev Physical Institute, Moscow, Russia V. Andreev, M. Azarkin37, I. Dremin37, M. Kirakosyan, A. Leonidov37, S.V. Rusakov, Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, A. Baskakov, A. Belyaev, E. Boos, V. Bunichev, M. Dubinin41, L. Dudko, A. Ershov, V. Klyukhin, O. Kodolova, N. Korneeva, I. Lokhtin, I. Miagkov, S. Obraztsov, M. Per lov, State Research Center of Russian Federation, Institute for High Energy Physics, Protvino, Russia I. Azhgirey, I. Bayshev, S. Bitioukov, D. Elumakhov, V. Kachanov, A. Kalinin, D. Konstantinov, V. Krychkine, V. Petrov, R. Ryutin, A. Sobol, S. Troshin, N. Tyurin, A. Uzunian, University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia P. Adzic42, P. Cirkovic, D. Devetak, J. Milosevic, V. Rekovic nologicas (CIEMAT), Madrid, Spain J. Alcaraz Maestre, E. Calvo, M. Cerrada, M. Chamizo Llatas, N. Colino, B. De La Cruz, A. Delgado Peris, A. Escalante Del Valle, C. Fernandez Bedoya, J.P. Fernandez Ramos, J. Flix, M.C. Fouz, P. Garcia-Abia, O. Gonzalez Lopez, S. Goy Lopez, J.M. Hernandez, M.I. Josa, E. Navarro De Martino, A. Perez-Calero Yzquierdo, J. Puerta Pelayo, A. Quintario Olmeda, I. Redondo, L. Romero, M.S. Soares Universidad Autonoma de Madrid, Madrid, Spain J.F. de Troconiz, M. Missiroli, D. Moran Universidad de Oviedo, Oviedo, Spain J. Cuevas, J. Fernandez Menendez, I. Gonzalez Caballero, J.R. Gonzalez Fernandez, E. Palencia Cortezon, S. Sanchez Cruz, J.M. Vizan Garcia Instituto de F sica de Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, Spain I.J. Cabrillo, A. Calderon, J.R. Castin~eiras De Saa, E. Curras, M. Fernandez, J. GarciaFerrero, G. Gomez, A. Lopez Virto, J. Marco, C. Martinez Rivero, F. Matorras, J. Piedra Gomez, T. Rodrigo, A. Ruiz-Jimeno, L. Scodellaro, N. Trevisani, I. Vila, R. Vilar CERN, European Organization for Nuclear Research, Geneva, Switzerland Paul Scherrer Institut, Villigen, Switzerland W. Bertl, K. Deiters, W. Erdmann, R. Horisberger, Q. Ingram, H.C. Kaestli, D. Kotlinski, U. Langenegger, T. Rohe Institute for Particle Physics, ETH Zurich, Zurich, Switzerland F. Bachmair, L. Bani, L. Bianchini, B. Casal, G. Dissertori, M. Dittmar, M. Donega, P. Eller, C. Grab, C. Heidegger, D. Hits, J. Hoss, G. Kasieczka, P. Lecomtey, W. Lustermann, B. Mangano, M. Marionneau, P. Martinez Ruiz del Arbol, M. Masciovecchio, M.T. Meinhard, D. Meister, F. Micheli, P. Musella, F. Nessi-Tedaldi, F. Pandol , J. Pata, F. Pauss, G. Perrin, L. Perrozzi, M. Quittnat, M. Rossini, M. Schonenberger, A. Starodumov48, M. Takahashi, V.R. Tavolaro, K. Theo latos, R. Wallny Universitat Zurich, Zurich, Switzerland T.K. Aarrestad, C. Amsler49, L. Caminada, M.F. Canelli, V. Chiochia, A. De Cosa, C. Galloni, A. Hinzmann, T. Hreus, B. Kilminster, C. Lange, J. Ngadiuba, D. Pinna, G. Rauco, P. Robmann, D. Salerno, Y. Yang National Central University, Chung-Li, Taiwan T.H. Doan, Sh. Jain, R. Khurana, M. Konyushikhin, C.M. Kuo, W. Lin, Y.J. Lu, A. Pozdnyakov, S.S. Yu National Taiwan University (NTU), Taipei, Taiwan Arun Kumar, P. Chang, Y.H. Chang, Y.W. Chang, Y. Chao, K.F. Chen, P.H. Chen, C. Dietz, F. Fiori, W.-S. Hou, Y. Hsiung, Y.F. Liu, R.-S. Lu, M. Min~ano Moya, E. Paganis, A. Psallidas, J.f. Tsai, Y.M. Tzeng Chulalongkorn University, Faculty of Science, Department of Physics, Bangkok, B. Asavapibhop, G. Singh, N. Srimanobhas, N. Suwonjandee A. Adiguzel, S. Cerci50, S. Damarseckin, Z.S. Demiroglu, C. Dozen, I. Dumanoglu, S. Girgis, G. Gokbulut, Y. Guler, E. Gurpinar, I. Hos, E.E. Kangal51, G. Onengut52, K. Ozdemir53, D. Sunar Cerci50, B. Tali50, H. Topakli54, S. Turkcapar, C. Zorbilmez Middle East Technical University, Physics Department, Ankara, Turkey B. Bilin, S. Bilmis, B. Isildak55, G. Karapinar56, M. Yalvac, M. Zeyrek Bogazici University, Istanbul, Turkey E. Gulmez, M. Kaya57, O. Kaya58, E.A. Yetkin59, T. Yetkin60 Istanbul Technical University, Istanbul, Turkey A. Cakir, K. Cankocak, S. Sen61 Institute for Scintillation Materials of National Academy of Science of Ukraine, Kharkov, Ukraine B. Grynyov Kharkov, Ukraine L. Levchuk, P. Sorokin National Scienti c Center, Kharkov Institute of Physics and Technology, University of Bristol, Bristol, United Kingdom R. Aggleton, F. Ball, L. Beck, J.J. Brooke, D. Burns, E. Clement, D. Cussans, H. Flacher, J. Goldstein, M. Grimes, G.P. Heath, H.F. Heath, J. Jacob, L. Kreczko, C. Lucas, D.M. Newbold62, S. Paramesvaran, A. Poll, T. Sakuma, S. Seif El Nasr-storey, D. Smith, Rutherford Appleton Laboratory, Didcot, United Kingdom K.W. Bell, A. Belyaev63, C. Brew, R.M. Brown, L. Calligaris, D. Cieri, D.J.A. Cockerill, J.A. Coughlan, K. Harder, S. Harper, E. Olaiya, D. Petyt, C.H. Shepherd-Themistocleous, A. Thea, I.R. Tomalin, T. Williams Imperial College, London, United Kingdom M. Baber, R. Bainbridge, O. Buchmuller, A. Bundock, D. Burton, S. Casasso, M. Citron, D. Colling, L. Corpe, P. Dauncey, G. Davies, A. De Wit, M. Della Negra, P. Dunne, A. Elwood, D. Futyan, Y. Haddad, G. Hall, G. Iles, R. Lane, C. Laner, R. Lucas62, L. Lyons, A.-M. Magnan, S. Malik, L. Mastrolorenzo, J. Nash, A. Nikitenko48, J. Pela, B. Penning, M. Pesaresi, D.M. Raymond, A. Richards, A. Rose, C. Seez, A. Tapper, K. Uchida, M. Vazquez Acosta64, T. Virdee15, S.C. Zenz Brunel University, Uxbridge, United Kingdom J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, D. Leslie, I.D. Reid, P. Symonds, L. Teodorescu, M. Turner Baylor University, Waco, U.S.A. A. Borzou, K. Call, J. Dittmann, K. Hatakeyama, H. Liu, N. Pastika O. Charaf, S.I. Cooper, C. Henderson, P. Rumerio Boston University, Boston, U.S.A. D. Arcaro, A. Avetisyan, T. Bose, D. Gastler, D. Rankin, C. Richardson, J. Rohlf, L. Sulak, Brown University, Providence, U.S.A. G. Benelli, E. Berry, D. Cutts, A. Ferapontov, A. Garabedian, J. Hakala, U. Heintz, O. Jesus, E. Laird, G. Landsberg, Z. Mao, M. Narain, S. Piperov, S. Sagir, E. Spencer, University of California, Davis, Davis, U.S.A. R. Breedon, G. Breto, D. Burns, M. Calderon De La Barca Sanchez, S. Chauhan, M. Chertok, J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk, M. 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Whitbeck University of Florida, Gainesville, U.S.A. D. Acosta, P. Avery, P. Bortignon, D. Bourilkov, A. Brinkerho , A. Carnes, M. Carver, D. Curry, S. Das, R.D. Field, I.K. Furic, J. Konigsberg, A. Korytov, P. Ma, K. Matchev, H. Mei, P. Milenovic66, G. Mitselmakher, D. Rank, L. Shchutska, D. Sperka, L. Thomas, J. Wang, S. Wang, J. Yelton Florida International University, Miami, U.S.A. S. Linn, P. Markowitz, G. Martinez, J.L. Rodriguez Florida State University, Tallahassee, U.S.A. A. Ackert, J.R. Adams, T. Adams, A. Askew, S. Bein, B. Diamond, S. Hagopian, V. Hagopian, K.F. Johnson, A. Khatiwada, H. Prosper, A. Santra, M. Weinberg Florida Institute of Technology, Melbourne, U.S.A. M.M. Baarmand, V. Bhopatkar, S. Colafranceschi67, M. Hohlmann, D. Noonan, T. Roy, University of Illinois at Chicago (UIC), Chicago, U.S.A. M.R. Adams, L. Apanasevich, D. Berry, R.R. Betts, I. Bucinskaite, R. Cavanaugh, O. Evdokimov, L. Gauthier, C.E. Gerber, D.J. Hofman, P. Kurt, C. O'Brien, I.D. Sandoval Gonzalez, P. Turner, N. Varelas, Z. Wu, M. Zakaria, J. Zhang B. Bilki68, W. Clarida, K. Dilsiz, S. Durgut, R.P. Gandrajula, M. Haytmyradov, V. Khristenko, J.-P. Merlo, H. Mermerkaya69, A. Mestvirishvili, A. Moeller, J. Nachtman, H. Ogul, Y. Onel, F. Ozok70, A. Penzo, C. Snyder, E. Tiras, J. Wetzel, K. Yi Johns Hopkins University, Baltimore, U.S.A. I. Anderson, B. Blumenfeld, A. Cocoros, N. Eminizer, D. Fehling, L. Feng, A.V. Gritsan, P. Maksimovic, M. Osherson, J. Roskes, U. Sarica, M. Swartz, M. Xiao, Y. Xin, C. You The University of Kansas, Lawrence, U.S.A. A. Al-bataineh, P. Baringer, A. Bean, J. Bowen, C. Bruner, J. Castle, R.P. Kenny III, A. Kropivnitskaya, D. Majumder, W. Mcbrayer, M. Murray, S. Sanders, R. Stringer, J.D. Tapia Takaki, Q. Wang Kansas State University, Manhattan, 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, R. Bi, K. Bierwagen, S. Brandt, W. Busza, I.A. Cali, Z. Demiragli, L. Di Matteo, G. Gomez Ceballos, M. Goncharov, D. Gulhan, D. Hsu, Y. Iiyama, G.M. Innocenti, M. Klute, D. Kovalskyi, K. Krajczar, Y.S. Lai, Y.-J. Lee, A. Levin, P.D. Luckey, A.C. Marini, C. Mcginn, C. Mironov, S. Narayanan, X. Niu, C. Paus, C. Roland, G. Roland, J. Salfeld-Nebgen, G.S.F. Stephans, K. Sumorok, K. Tatar, M. Varma, D. Velicanu, J. Veverka, J. Wang, T.W. Wang, B. Wyslouch, M. Yang, University of Minnesota, Minneapolis, U.S.A. A.C. Benvenuti, R.M. Chatterjee, A. Evans, A. Finkel, A. Gude, P. Hansen, S. Kalafut, S.C. Kao, Y. Kubota, Z. Lesko, J. Mans, S. Nourbakhsh, N. Ruckstuhl, R. Rusack, N. Tambe, J. Turkewitz University of Mississippi, Oxford, U.S.A. J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, U.S.A. E. Avdeeva, R. Bartek, K. Bloom, S. Bose, D.R. Claes, A. Dominguez, C. Fangmeier, R. Gonzalez Suarez, R. Kamalieddin, D. Knowlton, I. Kravchenko, F. Meier, J. Monroy, J.E. Siado, G.R. Snow, B. Stieger M. Alyari, J. Dolen, J. George, A. Godshalk, C. Harrington, I. Iashvili, J. Kaisen, A. Kharchilava, A. Kumar, A. Parker, S. Rappoccio, B. Roozbahani Northeastern University, Boston, 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 Northwestern University, Evanston, U.S.A. S. Bhattacharya, K.A. Hahn, A. Kubik, J.F. Low, N. Mucia, N. Odell, B. Pollack, M.H. Schmitt, K. Sung, M. Trovato, M. Velasco University of Notre Dame, Notre Dame, U.S.A. N. Dev, M. Hildreth, K. Hurtado Anampa, C. Jessop, D.J. Karmgard, N. Kellams, K. Lannon, N. Marinelli, F. Meng, C. Mueller, Y. Musienko36, M. Planer, A. Reinsvold, R. Ruchti, G. Smith, S. Taroni, N. Valls, M. Wayne, M. Wolf, A. Woodard The Ohio State University, Columbus, U.S.A. J. Alimena, L. Antonelli, J. Brinson, B. Bylsma, L.S. Durkin, S. Flowers, B. Francis, A. Hart, C. Hill, R. Hughes, W. Ji, B. Liu, W. Luo, D. Puigh, B.L. Winer, H.W. Wulsin Princeton University, Princeton, U.S.A. S. Cooperstein, O. Driga, P. Elmer, J. Hardenbrook, P. Hebda, J. Luo, D. Marlow, T. Medvedeva, M. Mooney, J. Olsen, C. Palmer, P. Piroue, D. Stickland, C. Tully, University of Puerto Rico, Mayaguez, U.S.A. Purdue University, West Lafayette, U.S.A. A. Barker, V.E. Barnes, D. Benedetti, S. Folgueras, L. Gutay, M.K. Jha, M. Jones, A.W. Jung, K. Jung, D.H. Miller, N. Neumeister, B.C. Radburn-Smith, X. Shi, 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.t. Duh, T. Ferbel, M. Galanti, A. Garcia-Bellido, J. Han, O. Hindrichs, A. Khukhunaishvili, K.H. Lo, P. Tan, M. Verzetti Rutgers, The State University of New Jersey, Piscataway, U.S.A. J.P. Chou, E. Contreras-Campana, Y. Gershtein, T.A. Gomez Espinosa, E. Halkiadakis, M. Heindl, D. Hidas, E. Hughes, S. Kaplan, R. Kunnawalkam Elayavalli, S. Kyriacou, S. Thomas, P. Thomassen, M. Walker University of Tennessee, Knoxville, U.S.A. M. Foerster, J. Heideman, G. Riley, K. Rose, S. Spanier, K. Thapa Texas A&M University, College Station, U.S.A. O. Bouhali71, A. Castaneda Hernandez71, A. Celik, M. Dalchenko, M. De Mattia, A. Delgado, S. Dildick, R. Eusebi, J. Gilmore, T. Huang, E. Juska, T. Kamon72, V. Krutelyov, R. Mueller, Y. Pakhotin, R. Patel, A. Perlo , L. Pernie, D. Rathjens, A. Rose, A. Safonov, A. Tatarinov, K.A. Ulmer Texas Tech University, Lubbock, 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, Z. Wang Vanderbilt University, Nashville, U.S.A. A.G. Delannoy, S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, P. Sheldon, S. Tuo, J. Velkovska, Q. Xu University of Virginia, Charlottesville, U.S.A. T. Sinthuprasith, X. Sun, Y. Wang, E. Wolfe, F. Xia Wayne State University, Detroit, U.S.A. C. Clarke, R. Harr, P.E. Karchin, P. Lamichhane, J. Sturdy M.W. Arenton, P. Barria, B. Cox, J. Goodell, R. Hirosky, A. Ledovskoy, H. Li, C. Neu, University of Wisconsin - Madison, Madison, WI, U.S.A. D.A. Belknap, S. Dasu, L. Dodd, S. Duric, B. Gomber, M. Grothe, M. Herndon, A. Herve, P. Klabbers, A. Lanaro, A. Levine, K. Long, R. Loveless, I. Ojalvo, T. Perry, G.A. Pierro, G. Polese, T. Ruggles, A. Savin, A. Sharma, N. Smith, W.H. Smith, D. Taylor, P. Verwilligen, N. Woods Tata Institute of Fundamental Research, Mumbai, ZZ S. Bhowmik73, R.K. Dewanjee, S. Ganguly, S. Kumar, M. Maity73, B. Parida, T. Sarkar73 1: Also at Vienna University of Technology, Vienna, Austria 2: Also at State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, 3: Also at Institut Pluridisciplinaire Hubert Curien, Universite de Strasbourg, Universite de Haute Alsace Mulhouse, CNRS/IN2P3, Strasbourg, France 4: Also at Universidade Estadual de Campinas, Campinas, Brazil 5: Also at Centre National de la Recherche Scienti que (CNRS) - IN2P3, Paris, France 6: Also at Universite Libre de Bruxelles, Bruxelles, Belgium 7: Also at Deutsches Elektronen-Synchrotron, Hamburg, Germany 9: Also at Helwan University, Cairo, Egypt 10: Now at Zewail City of Science and Technology, Zewail, Egypt 11: Also at Ain Shams University, Cairo, Egypt 12: Also at Fayoum University, El-Fayoum, Egypt 13: Now at British University in Egypt, Cairo, Egypt 14: Also at Universite de Haute Alsace, Mulhouse, France 15: Also at CERN, European Organization for Nuclear Research, Geneva, Switzerland 16: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, 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 22: Also at MTA-ELTE Lendulet CMS Particle and Nuclear Physics Group, Eotvos Lorand 23: Also at University of Debrecen, Debrecen, Hungary 24: Also at Indian Institute of Science Education and Research, Bhopal, India 25: Also at Institute of Physics, Bhubaneswar, India 26: Also at University of Ruhuna, Matara, Sri Lanka 27: Also at Isfahan University of Technology, Isfahan, Iran 28: Also at University of Tehran, Department of Engineering Science, Tehran, Iran 29: Also at Plasma Physics Research Center, Science and Research Branch, Islamic Azad University, Tehran, Iran 30: Also at Universita degli Studi di Siena, Siena, Italy 31: Also at Purdue University, West Lafayette, U.S.A. 32: Also at International Islamic University of Malaysia, Kuala Lumpur, Malaysia 33: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia 34: Also at Consejo Nacional de Ciencia y Tecnolog a, Mexico city, Mexico 35: Also at Warsaw University of Technology, Institute of Electronic Systems, Warsaw, Poland 36: Also at Institute for Nuclear Research, Moscow, Russia at National Research Nuclear University 'Moscow Engineering Physics Insti38: Also at St. Petersburg State Polytechnical University, St. Petersburg, Russia 39: Also at University of Florida, Gainesville, U.S.A. 40: Also at P.N. Lebedev Physical Institute, Moscow, Russia 41: Also at California Institute of Technology, Pasadena, U.S.A. 42: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia 43: Also at INFN Sezione di Roma; Universita di Roma, Roma, Italy 44: Also at National Technical University of Athens, Athens, Greece 45: Also at Scuola Normale e Sezione dell'INFN, Pisa, Italy 46: Also at National and Kapodistrian University of Athens, Athens, Greece 47: Also at Riga Technical University, Riga, Latvia 48: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia 49: Also at Albert Einstein Center for Fundamental Physics, Bern, Switzerland 50: Also at Adiyaman University, Adiyaman, Turkey 51: Also at Mersin University, Mersin, Turkey 53: Also at Piri Reis University, Istanbul, Turkey 54: Also at Gaziosmanpasa University, Tokat, Turkey 55: Also at Ozyegin University, Istanbul, Turkey 56: Also at Izmir Institute of Technology, Izmir, Turkey 57: Also at Marmara University, Istanbul, Turkey 58: Also at Kafkas University, Kars, Turkey 59: Also at Istanbul Bilgi University, Istanbul, Turkey 60: Also at Yildiz Technical University, Istanbul, Turkey 61: Also at Hacettepe University, Ankara, Turkey 62: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom 63: Also at School of Physics and Astronomy, University of Southampton, Southampton, United 64: Also at Instituto de Astrof sica de Canarias, La Laguna, Spain 65: Also at Utah Valley University, Orem, U.S.A. 66: Also at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, 67: Also at Facolta Ingegneria, Universita di Roma, Roma, Italy 68: Also at Argonne National Laboratory, Argonne, U.S.A. 69: Also at Erzincan University, Erzincan, Turkey 70: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey 71: Also at Texas A&M University at Qatar, Doha, Qatar 72: Also at Kyungpook National University, Daegu, Korea 73: Also at University of Visva-Bharati, Santiniketan, India [12] LHC Higgs Cross Section Working Group collaboration , J.R. 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Search for top quark decays via Higgs-boson-mediated flavor-changing neutral currents in pp collisions at \( \sqrt{s}=8 \) TeV, Journal of High Energy Physics, 2017, DOI: 10.1007/JHEP02(2017)079