Measurement of the transverse momentum spectrum of the Higgs boson produced in pp collisions at \( \sqrt{s}=8 \) TeV using H → WW decays

Journal of High Energy Physics, Mar 2017

The cross section for Higgs boson production in pp collisions is studied using the H → W+W− decay mode, followed by leptonic decays of the W bosons to an oppositely charged electron-muon pair in the final state. The measurements are performed using data collected by the CMS experiment at the LHC at a centre-of-mass energy of 8 TeV, corresponding to an integrated luminosity of 19.4 fb−1. The Higgs boson transverse momentum (p T) is reconstructed using the lepton pair p T and missing p T. The differential cross section times branching fraction is measured as a function of the Higgs boson p T in a fiducial phase space defined to match the experimental acceptance in terms of the lepton kinematics and event topology. The production cross section times branching fraction in the fiducial phase space is measured to be 39 ± 8 (stat) ± 9 (syst) fb. The measurements are found to agree, within experimental uncertainties, with theoretical calculations based on the standard model.

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Measurement of the transverse momentum spectrum of the Higgs boson produced in pp collisions at \( \sqrt{s}=8 \) TeV using H → WW decays

Received: June decays The CMS collaboration 0 1 2 3 4 5 0 [56] S. Alioli , P. Nason, C. Oleari and E. Re, NLO Higgs boson production via gluon fusion 1 Chulalongkorn University, Faculty of Science, Department of Physics , Bangkok 2 State University of New York at Bu alo , Bu alo , U.S.A 3 (MEPhI) , Moscow , Russia 4 15: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University 5 59: Also at Istanbul Bilgi University , Istanbul , Turkey The cross section for Higgs boson production in pp collisions is studied using Hadron-Hadron scattering (experiments); Higgs physics - decay mode, followed by leptonic decays of the W bosons to an oppositely charged electron-muon pair in the nal state. The measurements are performed using data collected by the CMS experiment at the LHC at a centre-of-mass energy of 8 TeV, corresponding to an integrated luminosity of 19.4 fb 1. The Higgs boson transverse momentum (pT) is reconstructed using the lepton pair pT and missing pT. The di erential cross section times branching fraction is measured as a function of the Higgs boson pT in a ducial phase space de ned to match the experimental acceptance in terms of the lepton kinematics and event topology. The production cross section times branching fraction in ducial phase space is measured to be 39 9 (syst) fb. The measurements are found to agree, within experimental uncertainties, with theoretical calculations based on the standard model. 1 Introduction The CMS experiment Data and simulated samples Analysis strategy Background estimation Systematic uncertainties Signal extraction The CMS collaboration Unfolding and treatment of systematic uncertainties The discovery of a new boson at the CERN LHC reported by the ATLAS and CMS collaborations [1{3] has been followed by a comprehensive set of measurements aimed at establishing the properties of the new boson. Results reported by ATLAS and CMS [4{22], so far, are consistent with the standard model (SM) expectations for the Higgs boson (H). Measurements of the production cross section of the Higgs boson times branching fraction in a restricted part of the phase space ( ducial phase space) and its kinematic properties represent an important test for possible deviations from the SM predictions. In particular, it has been shown that the Higgs boson transverse momentum (pTH) spectrum can be signi cantly a ected by the presence of interactions not predicted by the SM [23{27]. In addition, these measurements allow accurate tests of the theoretical calculations in the SM Higgs sector, which o er up to next-to-next-to-leading-order (NNLO) accuracy in perturbative Quantum ChromoDynamics (pQCD), up to next-to-next-to-leading-logarithmic (NNLL) accuracy in the resummation of soft-gluon e ects at small pT, and up to next-toleading-order (NLO) accuracy in perturbative electroweak corrections [28{30]. Measurements of the ducial cross sections and of several di erential distributions, for the H ! ZZ ! 4` (` = e; ) and H ! decay channels, and recently by ATLAS [36] decay channel. In this paper we report a measurement of the ducial cross section times branching fraction ( production in H ! W+W decays, based on p B) and pT spectrum for Higgs boson s = 8 TeV LHC data. The analysis is performed looking at di erent avour leptons in the nal state in order to suppress the sizeable contribution of backgrounds containing a same- avour lepton pair originating from Z boson decay. Although the H ! W+W the pTH measurement compared to the H ! ! 2`2 channel has lower resolution in and H ! ZZ ! 4` channels because of neutrinos in the nal state, the channel has a signi cantly larger B, exceeding those for by a factor of 10 and H ! ZZ ! 4` by a factor of 85 for a Higgs boson mass of 125 GeV [37], and is characterized by good signal sensitivity. Such sensitivity allowed the observation of a Higgs boson at the level of 4.3 (5.8 expected) standard deviations for a mass hypothesis of 125.6 GeV using the full LHC data set at 7 and 8 TeV [7]. The measurement is performed in a ducial phase space de ned by kinematic requirements on the leptons that closely match the experimental event selection. The e ect of the limited detector resolution, as well as the selection e ciency with respect to the phase space are corrected to particle level with an unfolding procedure [38]. This procedure is based on the knowledge of the detector response matrix, derived from the simulation of the CMS response to signal events, and consists of an inversion of the response matrix with a regularization prescription to tame unphysical statistical uctuations in the unfolded result. The analysis presented here is based on the previously published H ! W+W measurements by CMS [7]. A notable di erence from those measurements is that this analysis is inclusive in the number of jets, which allows the uncertainties related to the theoretical modelling of additional jets produced in association with the Higgs boson to be reduced. There are two important backgrounds: for pTH values below approximately 50 GeV the dominant background is WW production, while above 50 GeV the production of top-anti-top (tt) quarks dominates. This paper is organized as follows: in section 2 a brief description of the CMS detector is given. The data sets and Monte Carlo (MC) simulated samples are described in section 3. The strategy adopted in the analysis is described in section 4, including the de nition of the ducial phase space. The event selection and a description of all relevant backgrounds are given in section 5, followed by an overview of the systematic uncertainties important for the analysis in section 6. The technique used for the extraction of the Higgs boson signal contribution is described in section 7, together with the signal and background yields and the reconstructed pTH spectrum. The unfolding procedure used to extrapolate the reconstructed spectrum to the ducial phase space is described in section 8, including a detailed description of the treatment of systematic uncertainties in the unfolding. Finally, section 9 presents the result of the measurement of the ducial their comparison with the theoretical predictions. B and pTH spectrum, and The CMS experiment The central feature of the CMS apparatus is a superconducting solenoid of 6 m internal diameter providing a magnetic eld of 3.8 T. Within the solenoid volume are a silicon pixel and strip tracker, which cover a pseudorapidity ( ) region of j j < 2:5, a lead tungstate crystal electromagnetic calorimeter (ECAL), and a brass and scintillator hadron calorimeter (HCAL), each composed of a barrel and two endcap sections, covering j j < 3. Forward calorimetry extends the coverage provided by the barrel and endcap detectors from < 5:2. Muons are measured in gas-ionization detectors embedded in the steel uxreturn yoke outside the solenoid. A more detailed description of the CMS detector, together with a de nition of the coordinate system used and the relevant kinematic variables, can be found in ref. [39]. The particle- ow event algorithm reconstructs and identi es each individual particle with an optimized combination of information from the various elements of the CMS detector [40{44]. The energy of photons is obtained from the ECAL measurement, corrected for instrumental e ects. The energy of electrons is determined from a combination of the electron momentum at the primary interaction vertex as determined by the tracker, the energy of the corresponding ECAL cluster, and the energy sum of all bremsstrahlung photons spatially compatible with originating from the electron track [45]. The momentum of muons is obtained from the curvature of the corresponding track. The energy of charged hadrons is determined from a combination of their momentum measured in the tracker and the matching ECAL and HCAL energy deposits, corrected for zero-suppression e ects and for the response function of the calorimeters to hadronic showers. Finally, the energy of neutral hadrons is obtained from the corresponding corrected ECAL and HCAL energy. Jets are reconstructed from the individual particles using the anti-kt clustering algorithm with a distance parameter of 0.5, as implemented in the fastjet package [46, 47]. The missing transverse momentum vector p~miss is de ned as the projection of the negative vector sum of the momenta of all reconstructed particles in an event on the plane perpendicular to the beams. Its magnitude is referred to as the missing transverse energy ETmiss. Details on the experimental techniques for the reconstruction, identi cation, and isolation of electrons, muons and jets, as well as on the e ciencies of these techniques can be found in refs. [44, 45, 48{52]. Details on the procedure used to calibrate the leptons and jets in this analysis can be found in ref. [7]. Data and simulated samples This analysis makes use of the same data and MC simulated samples as those used in study [7]. Data were recorded by the CMS experiment during 2012 and correspond to an integrated luminosity of 19.4 fb 1 at a centre-of-mass energy of 8 TeV. The events are triggered by requiring the presence of either one or a combination of electron and muon with high pT and tight identi cation and isolation criteria. Singlelepton triggers are characterized by pT thresholds varying from 17 to 27 GeV for electrons and from 17 to 24 GeV for muons. Dilepton e triggers are required to have one electron or one muon with pT > 17 GeV and the other muon or electron with pT > 8 GeV. The average combined trigger e ciency for signal events that pass the full event selection is measured to be about 96% in the e nal state for a Higgs boson mass of 125 GeV. The signal and background processes relevant for this analysis are simulated using several MC programs. Simulations of the Higgs boson production through the gluon fusion (ggH) and vector boson fusion (VBF) mechanisms are performed using the rst version of the powheg generator (powheg V1) [53{57] with NLO accuracy in pQCD, while Pythia 6.426 [58] is used to simulate associated Higgs boson production with vector bosons (VH). The ttH production mechanism contributes less than 1% to the Higgs boson production process and has not been included among the signal processes. The main background processes, nonresonant qq ! W+W using the MadGraph 5.1.3 [59] and powheg V1 [60] event generators respectively. The and tt+jets, are simulated process is simulated using the GG2WW 3.1 generator [61] and the cross section is scaled to the approximate NLO prediction [62, 63]. The tW process is simulated WZ, W , W , tri-bosons (VVV), and W+jets are generated using MadGraph. All signal and background generators are interfaced to Pythia 6 to simulate the e ects of the parton shower, multiple parton interactions, and hadronization. The default parton distribution function (PDF) sets used are CTEQ6L [64] for LO generators and CT10 [65] for NLO generators. The H ! reweighted so that the pTH spectrum and inclusive production cross section closely match the SM calculations that have NNLO+NNLL pQCD accuracy in the description of the process simulation is Higgs boson inclusive production, in accordance with the LHC Higgs Cross section Working Group recommendations [37]. The reweighting of the pTH spectrum is achieved by tuning the powheg generator, as described in detail in ref. [66]. Cross sections computed with NLO pQCD accuracy [37] are used for the background processes. The samples are processed using a simulation of the CMS detector response, as modeled by Geant4 [67]. Minimum bias events are superimposed on the simulated events to emulate the additional pp interactions per bunch crossing (pileup). The events are reweighted to correct for observed di erences between data and simulation in the number of pileup events, trigger e ciency, and lepton reconstruction and identi cation e ciencies [7]. For the comparison of the measured unfolded spectrum with the theoretical predictions, two additional MC generators are used for simulating the SM Higgs boson production in the ggH process: HRes 2.3 [29, 30] and the second version of the powheg generator (powheg V2) [68]. HRes is a partonic level MC generator that computes the SM Higgs boson cross section at NNLO accuracy in pQCD and performs the NNLL resummation of soft-gluon e ects at small pT. The central predictions of HRes are obtained including the exact top and bottom quark mass contribution to the gluon fusion loop, renormalization and factorization scale central values at a Higgs boson mass of 125 GeV. The cross section normalization is scaled, to take into account electroweak corrections, by a factor of 1.05 and the e ects of threshold resummation by a factor of 1.06 [69, 70]. The upper and lower bounds of the uncertainties are obtained by scaling up and down both the renormalization and the factorization scales by a factor of two. The powheg V2 generator is a matrix element based generator that provides a NLO description of the ggH process in association with zero jets, taking into account the nite mass of the bottom and top quarks. The powheg prediction is tuned using the powheg damping factor hdump of 104.17 GeV, in order to match the pTH spectrum predicted by HRes in the full phase space. This factor reduces the emission of additional jets in the high pT regime, and enhances the contribution from the Sudakov form factor in the limit of low pT. The powheg generator is interfaced to the JHUGen generator version 5.2.5 [71{73] for the decay of the Higgs boson to a W boson pair and interfaced with pythia 8 [74] for the simulation of parton shower and hadronization e ects. Analysis strategy The analysis presented here is based on that used in the previously published H measurements by CMS [7], modi ed to be inclusive in the number of jets. This modi cation signi cantly reduces the uncertainties related to the modelling of the number of jets produced in association with the Higgs boson because the number of jets is strongly correlated with pH. Events are selected requiring the presence of two isolated leptons with opposite charge, an electron and a muon, with pT > 20(10) GeV for the leading (subleading) lepton, and with j j < 2:5 for electrons and j j < 2:4 for muons. No additional electron or muon with pT > 10 GeV is allowed. The two leptons are required to originate from a single primary vertex. Among the vertices identi ed in the event, the vertex with the largest P p2 , where the sum runs over all tracks associated with that vertex, is chosen as the primary vertex. The invariant mass of the two leptons, m``, is required to be greater than 12 GeV. A projected ETmiss variable is de ned as the component of p~Tmiss transverse to the nearest lepton if the lepton is situated within the azimuthal angular window of =2 from the p~miss direction, or the ETmiss itself otherwise [7]. Since the ETmiss resolution is degraded T by pileup, the minimum of two projected ETmiss variables is used: one constructed from all identi ed particles (full projected ETmiss), and another constructed from the charged particles only (track projected ETmiss). Events must have both ETmiss and the minimum projected ETmiss above 20 GeV. In order to suppress Z= events, the vector pT sum of the two leptons, p`T`, is required to be greater than 30 GeV and a minimum transverse mass of the lepton plus ETmiss vector of 60 GeV is required. The transverse mass is de ned as mT = (``; p~Tmiss)], where (``; p~Tmiss) is the azimuthal angle between the dilepton momentum and p~miss. Events surviving the requirements on leptons are dominantly those where a top quarkantiquark pair is produced and both W bosons, which are part of the top quark decay chain, decay leptonically (dileptonic tt). These events are identi ed using a b-jet tagging method based on two algorithms: one is the track counting high-e ciency (TCHE) [75], an algorithm based on the impact parameter of the tracks inside the jet, i.e. the distance to the primary vertex at the point of closest approach in the transverse plane; and another is Jet B Probability (JBP), an algorithm that assigns a per track probability of originating from the primary vertex [76]. In addition, soft-muon tagging algorithms are used, which remove events with a nonisolated soft muon, that is likely coming from a b quark decay. No jet with pT > 30 GeV may pass a threshold on the JBP b tagging discriminant corresponding to a b tagging e ciency of 76% and a mistagging e ciency around 10%. No jet with pT between 15 and 30 GeV may pass a TCHE b tagging discriminant threshold chosen to have a high top quark background rejection e ciency [7]. In addition, for events Leading lepton pT Subleading lepton pT Pseudorapidity of electrons and muons Invariant mass of the two charged leptons Charged lepton pair pT Invariant mass of the leptonic system in the transverse plane pT > 20 GeV pT > 10 GeV m`` > 12 GeV are de ned at the Born-level. with no reconstructed jets above 30 GeV, a soft-muon veto is applied. Soft muon candidates are de ned without isolation requirements and have pT > 3 GeV. The e ciency for a b jet with pT between 15 and 30 GeV to be identi ed both by the TCHE and soft-muon algorithms is 32%. Fiducial phase space requirements are chosen in order to minimize the dependence of the measurements on the underlying model of the Higgs boson properties and its production mechanism. The exact requirements are determined by considering the two following correlated quantities: the reconstruction e ciency for signal events originating from within the ducial phase space ( ducial signal e ciency d), and the ratio of the number of reconstructed signal events that are from outside the ducial phase space (\out-of- ducial" signal events) to the number from within the ducial phase space. The requirement of having a small fraction of out-of- ducial signal events, while at the same time preserving a high value of the ducial signal e ciency d, leads to ducial requirements at the generator level on the low-resolution variables, ETmiss and mT, that are looser with respect to those applied in the reconstructed event selection. ducial phase space used for the cross section measurements is de ned at the particle level by the requirements given in table 1. The leptons are de ned as Born-level leptons, i.e. before the emission of nal-state radiation (FSR), and are required not to originate from leptonic decays. The e ect of including FSR is evaluated to be of the order of 5% in each pTH bin. For the VH signal process the two leptons are required to ! 2`2 decays in order to avoid including leptons coming originate from the H ! W+W from the associated W or Z boson. momenta in the transverse plane and p~miss: Experimentally, the Higgs boson pT is reconstructed as the vector sum of the lepton Compared to other di erential analyses of the Higgs boson B, such as those in the H ! ZZ ! 4` and H ! decay channels, this analysis has to cope with limited resolution due to the ETmiss entering the pTH measurement. The e ect of the limited ETmiss resolution has two main implications for the analysis strategy. The rst one is that the choice of the binning in the pTH spectrum needs to take into account the detector resolution. The binning in pTH is built in such a way as to ensure that at least 60% of the signal events generated in a given pTH bin are also reconstructed in that bin. This procedure yields the following bin boundaries: [0, 15], [15, 45], [45, 85], [85, 125], [125, 165], and [165, 1] GeV. The second implication is that migrations of events across bins are signi cant. The signal yield is extracted in each pTH bin with a template t to a two dimensional distribution of m`` and mT. These two observables are chosen for the template t because they are weakly correlated with pH. The level of correlation is checked using simulation. Background estimation The signal extraction procedure requires the determination of the normalization and (m``; mT) shape for each background source. After the event selection is applied, one of the dominant contributions to the background processes arises from the top quark production, including the dileptonic tt and tW processes. The top quark background is divided into two categories with di erent jet multiplicity: the rst category requires events without jets with pT above 30 GeV and the second one requires at least one jet with pT > 30 GeV. For the estimation of the top quark background in the rst category, the same estimate from control samples in data as in ref. [7] is used. The contribution of the background in the second category is estimated independently in each pTH bin, by normalizing it in a control region de ned by requiring at least one jet with a JBP b tagging discriminator value above a given threshold, chosen to have a pure control region enriched in b jets. In addition, the quality of the Monte Carlo description of (m``; mT) kinematics is veri ed for this background by looking at the shapes of these variables in the b jets enriched control region and is found to be satisfactory. The nonresonant qq ! is determined independently in each pTH bin. The distribution, together with the signal yield. Approximately 5% of the W+W shape of the (m``; mT) distribution for this background is taken from the simulation, and its normalization in each pTH bin is obtained from the template t of the (m``; mT) originates from a gluon-gluon initial state via a quark box diagram. This background is treated separately and both normalization and shape are taken from simulation. Backgrounds containing one or two misidenti ed leptons are estimated from events selected with relaxed lepton quality criteria, using the techniques described in ref. [7]. The Z= background process is estimated using Z= selected in data, in which the muons are replaced with simulated decays, thus providing a more accurate description of the experimental conditions than the full simulation [7]. The tauola package [77] is used in the simulation of decays to account for -polarization e ects. Contributions from W production processes are estimated partly from simulated samples. The W cross section is measured from data and the discriminant variables used in the signal extraction for the W process are obtained from data as explained in ref. [7]. The shape of the discriminant variables for the W process and the W section are taken from simulation. Control/template sample events at high m`` and mT 2 jets with at least one passing b tagging criteria events with loosely identi ed leptons events with an identi ed WW Top W+jets W are used to estimate either the normalization or the shape of the discriminant variable. A brief description of the control/template samples is given. A summary of the processes used to estimate backgrounds is reported in table 2. The normalization and shape of the backgrounds are estimated using data control samples whenever possible. The remaining minor background contributions are estimated using simulation. The yield of each background process after the analysis requirements is given in section 7. Systematic uncertainties Systematic uncertainties in this analysis arise from three sources: background predictions, experimental measurements, and theoretical uncertainties. The estimates of most of the systematic uncertainties use the same methods as the published H ! W+W ! 2`2 analysis [7]. One notable di erence is in the uncertainties related to the prediction of the contributions from tt and tW processes. The shapes of these backgrounds are corrected for di erent b tagging e ciency in data and MC simulation, and the normalization is taken from data in a top quark enriched control region independently in each pTH bin, as explained in section 5. The uncertainties related to this procedure arise from the sample size in the control regions for each pTH bin, and are embedded in the scale factors used to extrapolate the top quark background normalization from the control region to the signal region. They vary from 20% to 50% depending on the pTH bin. This analysis takes into account the theoretical uncertainties that a ect the normalization and shape of all backgrounds and the signal distribution shape. These uncertainties arise from missing higher-order corrections in pQCD and PDF uncertainties, and are predicted using MC simulations. The e ect due to the variations in the choice of PDFs and the value of the QCD coupling constant is considered following the PDF4LHC [78, 79] prescription, using CT10, NNPDF2.1 [80] and MSTW2008 [81] PDF sets. The uncertainties in the signal yield associated with the uncertainty in the (m``; mT) shapes due to the missing higher-order corrections are evaluated independently by varying up and down the factorization and renormalization scales by a factor of two, and then using the Stewart-Tackman formulae [82]. Due to the presence of the b-veto, the uncertainty on Uncertainties in backgrounds contributions E ect of the experimental uncertainties on the signal and background yields Integrated luminosity Trigger e ciency Lepton reconstruction and identi cation Lepton energy scale ETmiss modelling Jet energy scale b mistag modelling b jet veto scale factor WW background shape E ect of the theoretical uncertainties on signal yield uncertainties in the normalization of background contributions. The experimental and theoretical uncertainties refer to the e ect on signal yields. A range is speci ed if the uncertainty varies across jet multiplicity must be evaluated. However, this uncertainty is diluted since the b-veto e ciency is weakly dependent on the number of jets in the event. Since the shapes of the WW background templates used in the t are taken from MC simulation, a corresponding shape uncertainty must be accounted for. This uncertainty is estimated in each bin of pTH from the comparisons of the two estimates obtained using the sample produced with MadGraph 5.1.3, and another sample produced using mc@nlo 4.0 [83]. These uncertainties include shape di erences originating from the renormalization and factorization scale choice. The scale dependence is estimated with mc@nlo. A summary of the main sources of systematic uncertainty and the corresponding estimate is reported in table 3. rately in section 8. The systematic uncertainties related to the unfolding procedure are described sepaTotal background 2124 shown in each pTH bin for the signal after applying the analysis selection requirements. The total uncertainty on the number of events is reported. For signal processes, the yield related to the ggH are shown, separated with respect to the contribution of the other production mechanisms Top process takes into account both tt and tW. Signal extraction The signal, including ggH, VBF, and VH production mechanisms, is extracted in each bin of pTH by performing a binned maximum likelihood t simultaneously in all pTH bins to a two-dimensional template for signals and backgrounds in the m``{mT plane. Six di erent signal strength parameters are extracted from the t, one for each pTH bin. The relative contributions of the di erent Higgs production mechanisms in the signal template are taken to be the same as in the SM. The systematic uncertainty sources are considered as nuisance parameters in the t. Because of detector resolution e ects, some of the reconstructed H ! W+W events might originate from outside the ducial phase space. These out-of- ducial signal events cannot be precisely handled by the unfolding procedure and must be subtracted from the measured spectrum. The pTH distribution of the out-of- ducial signal events is taken from simulation, and each bin is multiplied by the corresponding measured signal strength before performing the subtraction. A comparison of data and background prediction is shown in gure 1, where the m`` distribution is shown for each of the six pTH bins. Distributions correspond to the mT window of [60, 110] GeV, in order to emphasize the Higgs boson signal [7]. The corresponding mT distributions are shown in gure 2 for events in an m`` window of [12, 75] GeV. The signal prediction and background estimates after the analysis selection are reported in table 4. Background normalizations correspond to the values obtained from the t. The spectrum shown in gure 3 is obtained after having performed the t and after the subtraction of the out-of- ducial signal events, but before undergoing the unfolding procedure. The theoretical distribution after the detector simulation and event reconstruction is also shown for comparison. pH ≥ 165 GeV a 0 correspond to the values obtained from the t. Signal normalization is xed to the SM expectation. The distributions are shown in an mT window of [60,110] GeV in order to emphasize the Higgs boson (H) signal. The signal contribution is shown both stacked on top of the background and superimposed on it. Ratios of the expected and observed event yields in individual bins are shown in the panels below the plots. The uncertainty band shown in the ratio plot corresponds to the envelope of systematic uncertainties after performing the t to the data. a 0 a 0 D a 0 D a 0 D a 0 D a 0 D a 0 D pH ≥ 165 GeV correspond to the values obtained from the t. Signal normalization is xed to the SM expectation. The distributions are shown in an m`` window of [12,75] GeV in order to emphasize the Higgs boson (H) signal. The signal contribution is shown both stacked on top of the background and superimposed on it. Ratios of the expected and observed event yields in individual bins are shown in the panels below the plots. The uncertainty band shown in the ratio plot corresponds to the envelope of systematic uncertainties after performing the t to the data. ggH (POWHEGV1) + XH 20 40 60 80 100 120 140 160 180 200 before applying the unfolding procedure. Data values after the background subtraction are shown together with the statistical and the systematic uncertainties, determined propagating the sources of uncertainty through the t procedure. The line and dashed area represent the SM theoretical estimates in which the acceptance of the dominant ggH contribution is modelled by powheg V1. cross lled area separately. Unfolding and treatment of systematic uncertainties To facilitate comparisons with theoretical predictions or other experimental results, the signal extracted performing the t has to be corrected for detector resolution and e ciency e ects and for the e ciency of the selection de ned in the analysis. An unfolding procedure is used relying on the RooUnfold package [84], which provides the tools to run various unfolding algorithms. For every variable of interest, simulated samples are used to compare the distribution of that variable before and after the simulated events are processed through CMS detector simulation and events reconstruction. The detector response matrix M is built according to the following equation: where T MC and RMC are two n-dimensional vectors representing the distribution before and after event processing through CMS simulation and reconstruction, respectively. The dimension n of the two vectors corresponds to the number of bins in the distributions, equal to six in this analysis. The response matrix M includes all the e ects related to the detector and analysis selection that a ect the RMC distribution. To avoid the large [0,15] [15,45] [45,85] [85,125][125,165] [165,∞] [0,15] [15,45] [45,85] [85,125][125,165] [165,∞] processes. The matrices are normalized either by row (left) or by column (right) in order to show the purity or stability respectively in diagonal bins. variance and strong negative correlation between the neighbouring bins [38], the unfolding procedure in this analysis relies on the singular value decomposition [85] method based on the Tikhonov regularization function. The regularization parameter is chosen to obtain results that are robust against numerical instabilities and statistical uctuations, following the prescription described in ref. [85]. It has been veri ed using a large number of simulated pseudo-experiments that the coverage of the unfolded uncertainties obtained with this procedure is as expected. The response matrix is built as a two-dimensional histogram, with the generator-level pTH on the y axis and the same variable after the reconstruction on the x axis, using the same binning for both distributions. The resulting detector response matrix, including all signal sources and normalized by row, is shown in gure 4(left). The diagonal bins correspond to the purity P , de ned as the ratio of the number of events generated and reconstructed in a given bin, to the number of events generated in that bin. The same matrix, normalized by column, is shown in gure 4(right). In this case the diagonal bins correspond to the stability S, de ned as the ratio of the number of events generated and reconstructed in a given bin, and the number of events reconstructed in that bin. The P and S parameters provide an estimate of the pTH resolution and migration e ects. The main source of bin migrations e ects in the response matrix is the limited resolution in the measurement of ETmiss. Several closure tests are performed in order to validate the unfolding procedure. To estimate the uncertainty in the unfolding procedure due to the particular model adopted for building the response matrix, two independent gluon fusion samples are used, corresponding to two di erent generators: powheg V1 and JHUGen generators, both interfaced to Pythia 6.4. The JHUGen generator sample is used to build the response matrix while the powheg V1 sample is used for the measured and the MC distributions at generator level. The result of this test shows good agreement between the unfolded and the distribution from MC simulation. An important aspect of this analysis is the treatment of the systematic uncertainties and the error propagation through the unfolding procedure. The sources of uncertainty are divided into three categories, depending on whether the uncertainty a ects only the signal yield (type A), both the signal yield and the response matrix (type B), or only the response matrix (type C). These three classes propagate di erently through the unfolding procedure. Type A uncertainties are extracted directly from the t in the form of a covariance matrix, which is passed to the unfolding tool as the covariance matrix of the measured distribution. The nuisance parameters belonging to this category are the background shape and normalization uncertainties. To extract the e ect of type A uncertainties a dedicated t is performed, xing to constant all the nuisance parameters in the model, but type A nuisance parameters. The nuisance parameters falling in the type B class are: the b veto scale factor. It a ects the signal and background templates by varying the number of events with jets that enter the selection. It also a ects the response matrix because the reconstructed spectrum is harder or softer depending on the number of jets, which in turn depends on the veto. the lepton e ciency scale factor. It a ects the signal and background template shape and normalization. It a ects the response matrix by varying the reconstructed the ETmiss scale and resolution, which have an e ect similar to the above; lepton scale and resolution. The e ect is similar to the above; jet energy scale. It a ects the signal and background template shape and normalization. It also a ects the response matrix because, by varying the fraction of events with jets, the b veto can reject more or fewer events, thus making the reconstructed spectrum harder or softer. The e ect of each type B uncertainty is evaluated separately, since each one changes the response matrix in a di erent way. In order to evaluate their e ect on the signal strengths parameters, two additional ts are performed, each time xing the nuisance parameter value 1 standard deviation with respect to its nominal value. The results of the ts are then compared to the results of the full t obtained by oating all the nuisance parameters, thus determining the relative uncertainty on the signal strengths due to each nuisance parameter. Using these uncertainties, the measured spectra for each type B source are built. The e ects are propagated through the unfolding by building the corresponding variations of the response matrix and unfolding the measured spectra with the appropriate matrix. Type C uncertainties are related to the underlying assumption on the Higgs boson production mechanism used to extract the ducial cross sections. These are evaluated using an alternative shape for the true distribution at generator level. Since the reconstructed spectrum observed in data is consistent with a spectrum that falls to zero in the last three bins of the distribution, a true spectrum in accordance with this assumption is used +0:370= 0:307 +0:210= 0:157 +0:084= 0:078 +0:038= 0:038 +0:020= 0:019 +0:027= 0:027 uncertainty uncertainty +0:211= 0:038 +0:146= 0:041 +0:047= 0:034 +0:018= 0:017 +0:007= 0:007 +0:008= 0:007 separate components of the various sources of uncertainty. to generate a large number of pseudo-experiments. The pseudo-experiments undergo the tting and unfolding procedures described in the previous sections and are used to estimate the bias of the unfolding method with respect to the true spectrum. The observed bias is used as an estimate of the type C uncertainty. As an additional check, the model dependence uncertainty is evaluated using alternative response matrices that are obtained by varying the relative fraction of the VBF and ggH components within the experimental uncertainty, as given by the CMS combined measurement [17]. The bias observed using this approach is found to lie within the uncertainty obtained with the method described before. Type A and B uncertainties are nally combined together after the unfolding summing in quadrature positive and negative contributions separately for each bin. Type C uncertainties, also referred to as \model dependence", are instead quoted separately. The e ect of each source of the uncertainty is quoted for each bin of pTH in table 5. The unfolded pTH spectrum is shown in gure 5. Statistical, systematic, and theoretical uncertainties are shown as separate error bands in the plot. The unfolded spectrum is compared with the SM-based theoretical predictions where the ggH contribution is modelled using the HRes and powheg V2 programs. The comparison shows good agreement between data and theoretical predictions within the uncertainties. The measured values for the di erential cross section in each bin of pTH are reported together with the total uncertainty in table 5. Figure 6 shows the correlation matrix for the six bins of the di erential spectrum. The correlation cor(i,j) of bins i and j is de ned as: where cov(i; j) is the covariance of bins i and j, and (si, sj ) are the standard deviations of bins i and j, respectively. cor(i; j) = 19.4 fb­1 (8 TeV) ggH (POWHEGV2+JHUGen) + XH XH = VBF + VH 20 40 60 80 100 120 140 160 180 200 procedure. Data points are shown, together with statistical and systematic uncertainties. The vertical bars on the data points correspond to the sum in quadrature of the statistical and systematic uncertainties. The model dependence uncertainty is also shown. The pink (and back-slashed lling) and green (and slashed lling) lines and areas represent the SM theoretical estimates in which the acceptance of the dominant ggH contribution is modelled by HRes and powheg V2, respectively. cross lled area separately. The bottom panel shows the ratio of data and powheg V2 theoretical estimate to the HRes theoretical prediction. To measure the inclusive cross section in the ducial phase space, the di erential measured spectrum is integrated over pH. In order to compute the contributions of the bin uncertainties of the di erential spectrum to the inclusive uncertainty, error propagation is performed taking into account the covariance matrix of the six signal strengths. For the extrapolation of this result to the ducial phase space, the unfolding procedure is not needed, and the inclusive measurement has only to be corrected for the ducial phase space selection e ciency . Dividing the measured number of events by the integrated luminosity and correcting for the overall selection e ciency, which is estimated in simulation d = 36:2%, the inclusive ducial d, is computed to be: d = 39 in agreement within the uncertainties with the theoretical estimate of 48 8 fb, computed integrating the spectrum obtained with the powheg V2 program for the ggH process and including the XH contribution. 19.4 fb­1 (8 TeV) [0,15] [15,45] [45,85] [85,125] [125,165] [165,∞] Figure 6. Correlation matrix among the pTH bins of the di erential spectrum. Summary The cross section for Higgs boson production in pp collisions has been studied using the decay mode, followed by leptonic decays of the W bosons to an oppositely charged electron-muon pair in the nal state. Measurements have been performed using data from pp collisions at a centre-of-mass energy of 8 TeV collected by the CMS experiment at the LHC and corresponding to an integrated luminosity of 19.4 fb 1 . The di erential cross section has been measured as a function of the Higgs boson transverse momentum ducial phase space, de ned to match the experimental kinematic acceptance, and summarized in table 1. An unfolding procedure has been used to extrapolate the measured results to the ducial phase space and to correct for the detector e ects. The measurements have been compared to SM theoretical estimations provided by the HRes and powheg V2 generators, showing good agreement within the experimental uncertainties. The inclusive B in the ducial phase space has been measured to be 39 8 (stat) 9 (syst) fb, consistent with the SM expectation. Acknowledgments We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative sta s at CERN and at other CMS institutes for their contributions to the success of the CMS e ort. In addition, we gratefully acknowledge the computing centres and personnel of the Worldwide LHC Computing Grid for delivering so e ectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies: BMWFW and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES and CSF (Croatia); RPF (Cyprus); SENESCYT (Ecuador); MoER, ERC IUT and ERDF (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NIH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MBIE (New Zealand); PAEC (Pakistan); MSHE and NSC (Poland); FCT (Portugal); JINR (Dubna); MON, RosAtom, RAS and RFBR (Russia); MESTD (Serbia); SEIDI and CPAN (Spain); Swiss Funding Agencies (Switzerland); MST (Taipei); ThEPCenter, IPST, STAR and NSTDA (Thailand); TUBITAK and TAEK (Turkey); NASU and SFFR (Ukraine); STFC (United Kingdom); DOE and NSF (U.S.A.). Individuals have received support from the Marie-Curie programme and the European Research Council and EPLANET (European Union); the Leventis Foundation; the A. P. Sloan Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science Policy O ce; the Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Council of Science and Industrial Research, India; the HOMING PLUS programme of the Foundation for Polish Science, co nanced from European Union, Regional Development Fund; the Mobility Plus programme of the Ministry of Science and Higher Education (Poland); the OPUS programme, contract Sonata-bis DEC-2012/07/E/ST2/01406 of the National Science Center (Poland); the Thalis and Aristeia programmes co nanced by EU-ESF and the Greek NSRF; the National Priorities Research Program by Qatar National Research Fund; the Programa Clar n-COFUND del Principado de Asturias; the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University (Thailand); the Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand); and the Welch Foundation, contract C-1845. 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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. Hartmann14, S.M. Heindl, 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 Wigner Research Centre for Physics, Budapest, Hungary G. Bencze, C. Hajdu, P. Hidas, D. Horvath20, F. Sikler, V. Veszpremi, G. Vesztergombi21, Institute of Nuclear Research ATOMKI, Debrecen, Hungary N. Beni, S. Czellar, J. Karancsi22, A. Makovec, J. Molnar, Z. Szillasi University of Debrecen, Debrecen, Hungary M. Bartok21, P. Raics, Z.L. Trocsanyi, B. Ujvari National Institute of Science Education and Research, Bhubaneswar, India S. Bahinipati, S. Choudhury23, P. Mal, K. Mandal, A. Nayak24, D.K. Sahoo, N. Sahoo, Panjab University, Chandigarh, India S. Bansal, S.B. Beri, V. Bhatnagar, R. Chawla, U.Bhawandeep, A.K. Kalsi, A. Kaur, M. Kaur, R. Kumar, 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. Mohanty14, P.K. Netrakanti, L.M. Pant, P. Shukla, A. Topkar Tata Institute of Fundamental Research, Mumbai, India S. Bhowmik25, R.K. Dewanjee, S. Ganguly, S. Kumar, M. Maity25, B. Parida, T. Sarkar25 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. 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. Pompilia;b, G. Pugliesea;c, R. Radognaa;b, A. Ranieria, G. Selvaggia;b, L. Silvestrisa;14, R. Vendittia;b, P. Verwilligena INFN Sezione di Bologna a, Universita di Bologna b, Bologna, Italy G. Abbiendia, C. Battilana, D. Bonacorsia;b, S. Braibant-Giacomellia;b, L. Brigliadoria;b, R. Campaninia;b, P. Capiluppia;b, A. Castroa;b, F.R. Cavalloa, S.S. Chhibraa;b, G. Codispotia;b, M. Cu ania;b, G.M. Dallavallea, F. Fabbria, A. Fanfania;b, D. Fasanellaa;b, P. Giacomellia, C. Grandia, L. Guiduccia;b, S. Marcellinia, G. Masettia, A. Montanaria, F.L. Navarriaa;b, A. Perrottaa, A.M. Rossia;b, T. Rovellia;b, G.P. Sirolia;b, N. Tosia;b;14 INFN Sezione di Catania a, Universita di Catania b, Catania, Italy S. Albergoa;b, M. Chiorbolia;b, S. Costaa;b, A. Di Mattiaa, F. Giordanoa;b, R. Potenzaa;b, A. Tricomia;b, C. Tuvea;b INFN Sezione di Firenze a, Universita di Firenze b, Firenze, Italy G. Barbaglia, V. Ciullia;b, C. Civininia, R. D'Alessandroa;b, E. Focardia;b, V. Goria;b, P. Lenzia;b, M. Meschinia, S. Paolettia, L. Redapi, L. Russoa;30, G. Sguazzonia, L. Viliania;b;14 INFN Laboratori Nazionali di Frascati, Frascati, Italy L. Benussi, S. Bianco, F. Fabbri, D. Piccolo, F. Primavera14 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;14, 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;14, M. Espositoa;b, F. Fabozzia;c, A.O.M. Iorioa;b, G. Lanzaa, L. Listaa, S. Meolaa;d;14, P. Paoluccia;14, C. Sciaccaa;b, F. Thyssen Trento c, Trento, Italy INFN Sezione di Padova a, Universita di Padova b, Padova, Italy, Universita di P. Azzia;14, 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;14, 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;14, 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 A. Zanettia INFN Sezione di Roma a, Universita di Roma b, Roma, Italy 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;14, S. Argiroa;b, M. Arneodoa;c, N. Bartosika, R. Bellana;b, C. Biinoa, N. Cartigliaa, F. Cennaa;b, M. Costaa;b, R. Covarellia;b, A. Deganoa;b, N. Demariaa, L. Fincoa;b, B. Kiania;b, C. Mariottia, S. Masellia, 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, M. Casarsaa, F. Cossuttia, G. Della Riccaa;b, C. La Licataa;b, A. Schizzia;b, Kyungpook National University, Daegu, Korea D.H. Kim, G.N. Kim, M.S. Kim, S. Lee, S.W. Lee, Y.D. Oh, S. Sekmen, D.C. Son, Chonbuk National University, Jeonju, Korea 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, C. Hwang, D. Kim, 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, C. Oropeza Barrera, F. Vazquez Valencia Benemerita Universidad Autonoma de Puebla, Puebla, Mexico S. Carpinteyro, I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad Autonoma de San Luis Potos , San Luis Potos , Mexico A. Morelos Pineda University of Auckland, Auckland, New Zealand D. Krofcheck 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, S. Qazi, M.A. Shah, 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 javin, A. Lanev, A. Malakhov, V. Matveev36;37, P. Moisenz, V. Palichik, V. Perelygin, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, N. Voytishin, A. Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia L. Chtchipounov, V. Golovtsov, Y. Ivanov, V. Kim38, E. Kuznetsova39, V. Murzin, V. Oreshkin, V. Sulimov, A. Vorobyev Institute for Nuclear Research, Moscow, Russia Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov, N. Krasnikov, A. Pashenkov, D. Tlisov, A. Toropin Institute for Theoretical and Experimental Physics, Moscow, Russia V. Epshteyn, V. Gavrilov, N. Lychkovskaya, V. Popov, I. Pozdnyakov, G. Safronov, A. Spiridonov, M. Toms, E. Vlasov, A. Zhokin 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, Moscow, Russia S. Petrushanko, V. Savrin Physics, Protvino, Russia Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, A. Baskakov, A. Belyaev, E. Boos, V. Bunichev, M. Dubinin41, L. Dudko, A. Ershov, A. Gribushin, V. Klyukhin, O. Kodolova, I. Lokhtin, I. Miagkov, S. Obraztsov, State Research Center of Russian Federation, Institute for High Energy 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 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, A. Escalante Del Valle, C. Fernandez Bedoya, J.P. Fernandez Ramos, J. Flix, M.C. Fouz, P. Garcia-Abia, O. Gonzalez Lopez, S. Goy Lopez, J.M. Hernandez, M.I. Josa, E. Navarro De Martino, A. Perez-Calero Yzquierdo, J. Puerta Pelayo, A. Quintario Olmeda, I. Redondo, L. Romero, M.S. Soares Universidad Autonoma de Madrid, Madrid, Spain J.F. de Troconiz, M. Missiroli, D. Moran Universidad de Oviedo, Oviedo, Spain J. Cuevas, J. Fernandez Menendez, I. Gonzalez Caballero, J.R. Gonzalez Fernandez, E. Palencia Cortezon, S. Sanchez Cruz, I. Suarez Andres, J.M. Vizan Garcia Instituto de F sica de Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, Spain I.J. Cabrillo, A. Calderon, J.R. Castin~eiras De Saa, E. Curras, M. Fernandez, J. Garcia-Ferrero, G. Gomez, A. Lopez Virto, J. Marco, C. Martinez Rivero, F. Matorras, R. Vilar Cortabitarte CERN, European Organization for Nuclear Research, Geneva, Switzerland D. Abbaneo, E. Au ray, G. Auzinger, M. Bachtis, P. Baillon, A.H. Ball, D. Barney, P. Bloch, A. Bocci, A. Bonato, C. Botta, T. Camporesi, R. Castello, M. Cepeda, G. Cerminara, M. D'Alfonso, D. d'Enterria, A. Dabrowski, V. Daponte, A. David, M. De Gruttola, F. De Guio, A. De Roeck, E. Di Marco43, M. Dobson, M. Dordevic, B. Dorney, T. du Pree, D. Duggan, M. Dunser, N. Dupont, A. Elliott-Peisert, S. Fartoukh, G. Franzoni, J. Fulcher, W. Funk, D. Gigi, K. Gill, M. Girone, F. Glege, D. Gulhan, S. Gundacker, M. Gutho , J. Hammer, P. Harris, J. Hegeman, V. Innocente, P. Janot, H. Kirschenmann, V. Knunz, A. Kornmayer14, M.J. Kortelainen, K. Kousouris, M. Krammer1, P. Lecoq, C. Lourenco, M.T. Lucchini, L. Malgeri, M. Mannelli, A. Martelli, F. Meijers, S. Mersi, E. Meschi, F. Moortgat, S. Morovic, M. Mulders, H. Neugebauer, S. Orfanelli44, L. Orsini, L. Pape, 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 V. Candelise, T.H. Doan, Sh. Jain, R. Khurana, M. Konyushikhin, C.M. Kuo, W. Lin, Y.J. Lu, A. Pozdnyakov, S.S. Yu National Taiwan University (NTU), Taipei, Taiwan Arun Kumar, P. Chang, Y.H. Chang, Y.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 B. Asavapibhop, G. Singh, N. Srimanobhas, N. Suwonjandee Cukurova University, Adana, Turkey A. Adiguzel, M.N. Bakirci50, S. Damarseckin, Z.S. Demiroglu, C. Dozen, E. Eskut, S. Turkcapar, I.S. Zorbakir, 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 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. Virdee14, 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 A. Borzou, K. Call, J. Dittmann, K. Hatakeyama, 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. 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. Garabedian, J. Hakala, U. Heintz, J.M. Hogan, O. Jesus, E. Laird, G. Landsberg, Z. Mao, M. Narain, S. Piperov, S. Sagir, E. Spencer, R. Syarif 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. Gardner, W. Ko, R. Lander, C. Mclean, 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, A. Florent, 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, P. Jandir, E. Kennedy, F. Lacroix, O.R. Long, M. Malberti, M. Olmedo Negrete, M.I. Paneva, 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, M. Derdzinski, R. Gerosa, A. Holzner, D. Klein, J. Letts, I. Macneill, D. Olivito, S. Padhi, M. Pieri, M. Sani, V. Sharma, S. Simon, M. Tadel, A. Vartak, S. Wasserbaech65, C. Welke, J. Wood, F. Wurthwein, A. Yagil, G. Zevi Della University of California, Santa Barbara, Santa Barbara, U.S.A. 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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. 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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, A. Malta Rodrigues, 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. 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, N. Woods 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 Universite Libre de Bruxelles, Bruxelles, Belgium 6: Also at Deutsches Elektronen-Synchrotron, Hamburg, Germany 7: Also at Joint Institute for Nuclear Research, Dubna, Russia 8: Also at Suez University, Suez, Egypt 9: Now at British University in Egypt, Cairo, Egypt 10: Also at Ain Shams University, Cairo, Egypt 11: Also at Cairo University, Cairo, Egypt 12: Now at Helwan University, Cairo, Egypt 13: Also at Universite de Haute Alsace, Mulhouse, France 14: Also at CERN, European Organization for Nuclear Research, Geneva, Switzerland 16: Also at Tbilisi State University, Tbilisi, Georgia 17: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany 18: Also at University of Hamburg, Hamburg, Germany 19: Also at Brandenburg University of Technology, Cottbus, Germany 20: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary 21: Also at MTA-ELTE Lendulet CMS Particle and Nuclear Physics Group, Eotvos Lorand University, Budapest, Hungary 22: Also at University of Debrecen, Debrecen, Hungary 23: Also at Indian Institute of Science Education and Research, Bhopal, India 24: Also at Institute of Physics, Bhubaneswar, India 25: Also at University of Visva-Bharati, Santiniketan, India 26: Also at University of Ruhuna, Matara, Sri Lanka 27: Also at Isfahan University of Technology, Isfahan, Iran 28: Also at 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 37: Now at National Research Nuclear University 'Moscow Engineering Physics Institute' 38: Also at St. Petersburg State Polytechnical University, St. Petersburg, Russia 39: Also at University of Florida, Gainesville, U.S.A. 40: Also at P.N. Lebedev Physical Institute, Moscow, Russia 41: Also at California Institute of Technology, Pasadena, U.S.A. 42: Also at 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 Gaziosmanpasa University, Tokat, Turkey 51: Also at Mersin University, Mersin, Turkey 52: Also at Cag University, Mersin, Turkey 53: Also at Piri Reis University, Istanbul, Turkey 54: Also at Adiyaman University, Adiyaman, 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 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 [37] LHC Higgs Cross section Working Group collaboration , J.R. 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Measurement of the transverse momentum spectrum of the Higgs boson produced in pp collisions at \( \sqrt{s}=8 \) TeV using H → WW decays, Journal of High Energy Physics, 2017, DOI: 10.1007/JHEP03(2017)032