Measurement and QCD analysis of double-differential inclusive jet cross sections in pp collisions at \( \sqrt{s}=8 \) TeV and cross section ratios to 2.76 and 7 TeV

Journal of High Energy Physics, Mar 2017

A measurement of the double-differential inclusive jet cross section as a function of the jet transverse momentum p T and the absolute jet rapidity |y| is presented. Data from LHC proton-proton collisions at \( \sqrt{s}=8 \) TeV, corresponding to an integrated luminosity of 19.7 fb−1, have been collected with the CMS detector. Jets are reconstructed using the anti-k T clustering algorithm with a size parameter of 0.7 in a phase space region covering jet p T from 74 GeV up to 2.5 TeV and jet absolute rapidity up to |y| = 3.0. The low-p T jet range between 21 and 74 GeV is also studied up to |y| = 4.7, using a dedicated data sample corresponding to an integrated luminosity of 5.6 pb−1. The measured jet cross section is corrected for detector effects and compared with the predictions from perturbative QCD at next-to-leading order (NLO) using various sets of parton distribution functions (PDF). Cross section ratios to the corresponding measurements performed at 2.76 and 7 TeV are presented. From the measured double-differential jet cross section, the value of the strong coupling constant evaluated at the Z mass is α S(M Z) = 0.1164 − 0.0043 + 0.0060 , where the errors include the PDF, scale, nonperturbative effects and experimental uncertainties, using the CT10 NLO PDFs. Improved constraints on PDFs based on the inclusive jet cross section measurement are presented.

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Measurement and QCD analysis of double-differential inclusive jet cross sections in pp collisions at \( \sqrt{s}=8 \) TeV and cross section ratios to 2.76 and 7 TeV

Received: September Measurement and QCD analysis of double-di erential inclusive jet cross sections in pp collisions at Open Access 0 1 2 3 4 5 6 7 Copyright CERN 0 1 2 3 4 5 6 7 0 s = 8 TeV , corresponding to an integrated 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 Rutgers, The State University of New Jersey , Piscataway , U.S.A 4 tute' (MEPhI) , Moscow , Russia 5 University , Budapest , Hungary 6 12: Also at Cairo University , Cairo , Egypt 7 56: Also at Ozyegin University , Istanbul , Turkey A measurement of the double-di erential inclusive jet cross section as a funcData from LHC proton-proton collisions at p tion of the jet transverse momentum pT and the absolute jet rapidity jyj is presented. luminosity of 19.7 fb 1, have been collected with the CMS detector. Jets are reconstructed using the anti-kT clustering algorithm with a size parameter of 0.7 in a phase space region covering jet pT from 74 GeV up to 2.5 TeV and jet absolute rapidity up to jyj = 3:0. The low-pT jet range between 21 and 74 GeV is also studied up to jyj = 4:7, using a dedicated data sample corresponding to an integrated luminosity of 5.6 pb 1 jet cross section is corrected for detector e ects and compared with the predictions from perturbative QCD at next-to-leading order (NLO) using various sets of parton distribution functions (PDF). Cross section ratios to the corresponding measurements performed at 2.76 and 7 TeV are presented. From the measured double-di erential jet cross section, the value of the strong coupling constant evaluated at the Z mass is S(MZ) = 0:1164+00::00006403, where the errors include the PDF, scale, nonperturbative e ects and experimental uncertainties, using the CT10 NLO PDFs. Improved constraints on PDFs based on the inclusive jet cross section measurement are presented. Hadron-Hadron scattering (experiments); Jet physics; QCD; Jets; proton- - and cross section ratios to 2.76 and 1 Introduction 2 The CMS detector 3 Jet reconstruction and event selection Measurement of the jet di erential cross section 5 Theoretical predictions 6 Comparison of theory and data 7 Ratios of cross sections measured at di erent p 8 Determination of S 9 The QCD analysis of the inclusive jet measurements 10 Summary The CMS collaboration Introduction Measurement of the cross sections for inclusive jet production in proton-proton collisions is an ultimate test of quantum chromodynamics (QCD). The process p + p ! jet + X probes the parton-parton interaction as described in perturbative QCD (pQCD), and is sensitive to the value of the strong coupling constant, S. Furthermore, it provides important constraints on the description of the proton structure, expressed by the parton distribution functions (PDFs). centre-of-mass energy p In this analysis, the double-di erential inclusive jet cross section is measured at the lute jet rapidity jyj. Similar measurements have been carried out at the CERN LHC by the ATLAS and CMS Collaborations at 2.76 [1, 2] and 7 TeV [3{6], and by experiments at other hadron colliders [7{11]. The measured inclusive jet cross section at p s = 7 TeV is well described by pQCD calculations at next-to-leading order (NLO) at small jyj, but not at large jyj. The larger the investigations to yet unexplored kinematic regions. In addition, the ratios of di erential cross sections at di erent centre-of-mass energies can be determined. In ref. [12] an increased sensitivity of such ratios to PDFs was suggested. The data were collected with the CMS detector at the LHC during 2012 and correspond to an integrated luminosity of 19.7 fb 1. The average number of multiple collisions within the same bunch crossing (known as pileup) is 21. A low-pileup data sample corresponding to an integrated luminosity of 5.6 pb 1 is collected with an average of four interactions per bunch crossing; this is used for a low-pT jet cross section measurement. The measured cross sections are corrected for detector e ects and compared to the QCD prediction at NLO. The high-pT part of the di erential cross section, where the sensitivity to the value of S is maximal, is measured more accurately than before. Also, the kinematic region of small pT and large y is probed. The measured cross section is used to extract the value of the strong coupling constant at the Z boson mass scale, of S in a wider kinematic range than is accessible at p S(MZ), and to study the scale dependence s = 7 TeV. Further, the impact of the present measurements on PDFs is illustrated in a QCD analysis using the present measurements and the cross sections of deep-inelastic scattering (DIS) at HERA [13]. The CMS detector The central feature of the CMS apparatus is a superconducting solenoid of 6 m internal diameter, providing a magnetic eld of 3.8 T. Within the solenoid volume are a silicon pixel and strip tracker, a lead tungstate crystal electromagnetic calorimeter (ECAL), and a brass and scintillator hadron calorimeter (HCAL), each composed of a barrel and two endcap sections. Forward calorimeters extend the pseudorapidity ( ) coverage [14] provided by the barrel and endcap detectors. Muons are measured in gas-ionization detectors embedded in the steel ux-return yoke outside the solenoid. The silicon tracker measures charged particles within the pseudorapidity range j j < 2:5. It consists of 1440 silicon pixel and 15 148 silicon strip detector modules. For nonisolated particles of 1 < pT < 10 GeV and j j < 1:4, the track resolutions are typically 1.5% in pT and 25{90 (45{150) m in the transverse (longitudinal) impact parameter [15]. The ECAL consists of 75 848 lead tungstate crystals, which provide coverage in j j < 1:479 in a barrel region (EB) and 1:479 < j j < 3:0 in two endcap regions (EE). A preshower detector consisting of two planes of silicon sensors interleaved with a total of 3X0 of lead is located in front of the EE. In the region j j < 1:74, the HCAL cells have widths of 0.087 in 0.087 radians in azimuth ( ). In the { plane, and for j j < 1:48, the HCAL cells map on 5 arrays of ECAL crystals to form calorimeter towers projecting radially outwards from close to the nominal interaction point. For j j > 1:74, the coverage of the towers increases progressively to a maximum of 0.174 in . The hadronic forward (HF) calorimeters consist of iron absorbers with embedded radiation-hard quartz bres, located at 11.2 m from the interaction point on both sides of the experiment covering the region of 2:9 < j j < 5:2. Half of the HF bres run over the full depth of the absorber, while the other half start at a depth of 22 cm from the front of the detector to allow for a separation Trigger pT O ine analysis pT range (GeV) E ective integrated luminosity (pb 1) 133{220 220{300 measurement. The luminosity is known with a 2.6% uncertainty. between electromagnetic and hadronic showers. The { tower segmentation of the HF calorimeters is 0:175 0:175, except for above 4.7, where the segmentation is 0:175 The rst level of the CMS trigger system, composed of custom hardware processors, uses information from the calorimeters and muon detectors to select events in a xed time interval of less than 4 s. The high-level trigger (HLT) processor farm further decreases the event rate from 100 kHz to around 400 Hz, before data storage. 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. [14]. Jet reconstruction and event selection The high-pT jet measurement is based on data sets collected with six single-jet triggers in the HLT system that require at least one jet in the event with jet pT > 40, 80, 140, 200, 260, and 320 GeV, respectively. All triggers were prescaled during the 2012 data-taking period except the highest threshold trigger. The e ciency of each trigger is estimated using triggers with lower pT thresholds, and each is found to exceed 99% above the nominal pT threshold. The pT thresholds of each trigger and the corresponding e ective integrated luminosity are listed in table 1. The jet pT range, reconstructed in the o ine analysis, where the trigger with the lowest pT threshold becomes fully e cient is also shown. This analysis includes jets with 74 < pT < 2500 GeV. Events for the low-pT jet analysis are collected with a trigger that requires at least two charged tracks reconstructed in the pixel detector in coincidence with the nominal bunch crossing time. This selection is highly e cient for nding jets ('100%) and also rejects noncollision background. The pT range considered in the low-pT jet analysis is 21{74 GeV. The particle- ow (PF) event algorithm reconstructs and identi es each individual particle with an optimized combination of information from the various elements of the CMS detector [16, 17]. Selected events are required to have at least one reconstructed interaction vertex, and the primary interaction vertex (PV) is de ned as the reconstructed vertex with the largest sum of p2T of its constituent tracks. The PV is required to be reconstructed from at least ve tracks and to lie within 24 cm in the longitudinal direction from the nominal interaction point [15], and to be consistent with the measured transverse position of the beam. The energy of photons is obtained directly from the ECAL measurement and is corrected for zero-suppression e ects. The energy of electrons is determined from a combination of the electron momentum at the PV 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. The transverse 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 energies. In the forward region, the energies are measured in the HF detector. For each event, hadronic jets are clustered from the reconstructed particles with the infrared and collinear safe anti-kT algorithm [18], as implemented in the FastJet package [19], with a size parameter R of 0.7. Jet momentum is determined as the vector sum of the momenta of all particles in the jet, and is found from simulation to be within 5% to 10% of the true momentum over the whole pT spectrum and detector acceptance, before corrections are applied. In order to suppress the contamination from pileup, only reconstructed charged particles associated to the PV are used in jet clustering. Jet energy scale (JES) corrections are derived from simulation, by using events generated with pythia6 and processed through the CMS detector simulation that is based on the geant 4 [20] package, and from in situ measurements by exploiting the energy balance in dijet, photon+jet, and Z+jet events [21, 22]. The pythia6 version 4.22 [23] is used, with the Z2 tune. The Z2 tune is derived from the Z1 tune [24] but uses the CTEQ6L [25] parton distribtion set whereas the Z1 tune uses the CTEQ5L set. The Z2 tune is the result of retuning the pythia6 parameters PARP(82) and PARP(90) by means of the automated PROFESSOR for residual nonuniformities and nonlinearities in the detector response. An o set correction is required to account for the extra energy clustered into jets due to pileup. The JES correction, applied as a multiplicative factor to the jet four momentum vector, depends on the values of jet and pT. For a jet with a pT of 100 GeV the typical correction is about 10%, and decreases with increasing pT. The jet energy resolution (JER) is approximately 15% at 10 GeV, 8% at 100 GeV, and 4% at 1 TeV. The missing transverse momentum vector, p~miss, is de ned as the projection on the plane perpendicular to the beams of the negative vector sum of the momenta of all reconstructed particles in an event. Its magnitude is referred to as ETmiss. A requirement is made that the ratio of ETmiss and the sum of the transverse energy of the PF particles is smaller than 0.3, which removes background events and leaves a negligible residual contamination. Additional selection criteria are applied to each event to remove spurious jet-like signatures originating from isolated noise patterns in certain HCAL regions. To suppress the noise patterns, tight identi cation criteria are applied: each jet should contain at least two PF particles, one of which is a charged hadron, and the jet energy fraction carried by neutral hadrons and photons should be less than 90%. These criteria have an e ciency greater than 99% for genuine jets. Events are selected that contain at least one jet with a pT higher than the pT threshold of the lowest-threshold trigger that recorded the event. The double-di erential inclusive jet cross section is de ned as where Njets is the number of jets in a kinematic interval (bin) of transverse momentum and rapidity, contributing to the bin; jyj, respectively; Lint;e is the e ective integrated luminosity is the product of the trigger and jet selection e ciencies, and is greater than 99%. The widths of the pT bins increase with pT and are proportional to the pT resolution. The phase space in absolute rapidity jyj is subdivided into six bins starting from y = 0 up to jyj = 3:0 with jyj = 0:5. In the low-pT jet measurement an additional rapidity bin 3:2 < jyj < 4:7 is included. The statistical uncertainty for each bin is computed according to the number of events contributing to at least one entry per event [6], corrected for possible multiple entries per event. This correction is small, since at least 90% of the observed jets in each jyj bin originate from di erent events. In order to compare the measured cross section with theoretical predictions at particle level, the steeply falling jet pT spectra must be corrected for experimental pT resolution. An unfolding procedure, based on the iterative D'Agostini method [27], implemented in the RooUnfold package [28], is used to correct the measured spectra for detector e ects. The response matrix is created by the convolution of theoretically predicted spectra, discussed in section 5, with the JER e ects. These e ects are evaluated as a function of pT with the CMS detector simulation, after correcting for the residual di erences from data [21]. The unfolding procedure induces statistical correlations among the bins. The sizes of these correlations typically vary between 10% and 20%. The dominant contribution to the experimental systematic uncertainty in the measured cross section is from the JES corrections, determined as in ref. [21, 22]. For the high-pT jet data set, this uncertainty is decomposed into 24 independent sources, corresponding to the di erent components of the corrections: pileup e ects, relative calibration of JES versus , absolute JES including pT dependence, and di erences in quark- and gluon-initiated jets. The set of components, used here, is discussed in detail in ref. [22], and represents an evolution of the decomposition presented in ref. [29]. The low-pileup data set uses a reduced number of components, since the pileup-related corrections are negligible, and there is no JES time dependence. Moreover, the central values of the corrections, for the components common between the two data sets, are not the same; the low-pT jet analysis uses corrections computed only on the initial part of the 2012 data sample. The impact of the uncertainty induced by each correction component on the measured cross section is evaluated separately. The JES-induced uncertainty in the cross section depends on pT and y. For the high-pT data, this ranges from 2% to 4% in the sub-TeV region at central rapidity to about 20% in the highest pT bins for rapidities 1:0 < jyj < 2:0. Due to the di erent set of corrections used, the low-pT jet cross section has a larger JES uncertainty than the contiguous bins of the high-pT part, and this e ect becomes more pronounced as the jet rapidity increases. S(MZ) range HERAPDF1.5 [40] avours Nf , the assumed masses Mt and MZ of the top quark and Z boson, the default values of the strong coupling constant S(MZ), and the ranges in S(MZ) available for ts. For CT10 the updated versions of 2012 are used. To account for the residual e ects of small ine ciencies of less than 1% in the trigger performances and jet identi cation, an uncertainty of 1%, uncorrelated across all jet pT and y bins, is assigned to each bin. The unfolding procedure is a ected by the uncertainties in the JER parameterization, which are derived from the simulation. The JER parameters are varied by one standard deviation up and down, and the corresponding response matrices are used to unfold the measured spectra. The JER-induced uncertainty amounts to 1{5% in the high-pT jet region, but can exceed 30% in the low-pT jet region. The uncertainties in the integrated luminosity, which propagate directly to the cross section, are 2:6% [30] and 4:4% [31] for normal and low-pileup data samples, respectively. Other sources of uncertainty, such as the jet angular resolution and the model dependence of the unfolding, arise from the theoretical pT spectrum used to calculate the response matrix and have less than 1% e ect on the cross section. The total experimental systematic uncertainty in the measured cross section is obtained as a quadratic sum of contributions due to uncertainties in JES, JER, and integrated luminosity. Theoretical predictions Theoretical predictions for the jet cross section are known at NLO accuracy in pQCD [32, 33], and the NLO electroweak corrections have been computed in ref. [34]. The pQCD NLO calculations are performed by using the NLOJet++ (version 4.1.3) program [32, 33] as implemented in the fastNLO (version 2.1) package [35]. The renormalization ( R) and factorization ( F) scales are both set to the leading jet pT. The calculations are performed by using six PDF sets determined at NLO: CT10 [36], MSTW2008 [37], NNPDF2.1 [38], NNPDF3.0 [39], HERAPDF1.5 [40], and ABM11 [41]. Each PDF set is available for a range of S(MZ) values. The number of active (massless) avours chosen in NLOJet++ is ve in all of the PDF sets except NNPDF2.1, where it is set to six. All the PDF sets use a variable avour number scheme, except ABM11, which uses a xed scheme. The basic characteristics of each PDF set are summarized in table 2. anti-kt (R = 0.7) anti-kt (R = 0.7) NP correction uncertainty NP correction uncertainty absolute rapidity bins as a function of jet pT. The correction is obtained by averaging LO- and NLO-based predictions, and the envelope of these predictions is used as the uncertainty band. The parton-level calculation at NLO has to be supplemented with corrections due to nonperturbative (NP) e ects, i.e. hadronization and multiparton interactions (MPI). The nonperturbative e ects are estimated using both leading order (LO) and NLO event generators. In the former case, the correction is evaluated by averaging those provided by pythia6 [23] (version 4.26), using tune Z2 , and herwig++ (version 2.4.2) [42], using tune UE [43]. The size of these corrections ranges from 20% at low pT to 1% at the highest pT of 2.5 TeV. The NLO nonperturbative correction is derived using powheg [44{47], interfaced with pythia6 for parton shower, MPI, and hadronization. The nonperturbative correction factors are derived in this case by averaging the results for two di erent tunes of pythia6, Z2 and P11 [48]. Hadronization models have been tuned by using LO calculations for the hard scattering, and applying these tunes to NLO-based calculations is not expected to provide optimal results. On the other hand, the application of nonperturbative corrections based on LO calculations to NLO predictions implicitly assumes that the behaviour of nonperturbative e ects is independent of the hard scattering description. To take into account both facts, the nal number used for the nonperturbative correction, CNP, is an arithmetic average of the LO- and NLO-based estimates. Half the width of the envelope of these predictions is used as the uncertainty due to the nonperturbative correction. Figure 1 shows the nonperturbative correction factors derived by combining both LO- and NLObased calculations. The uncertainty in the NLO pQCD calculation arising from missing higher-order corrections is estimated by varying the renormalization and factorization scales in the following (2; 1), where is the default choice equal to the jet pT, and considering the largest variation in the prediction as the uncertainty. The uncertainty related to the choice of scale ranges from 5% to 10% for jyj < 1:5 and increases to 40% for the outer jyj bins and for high pT. The PDF uncertainties are estimated following the prescription from each PDF group by using the provided eigenvectors (or replicas in case of NNPDF). The corresponding uncertainty in the predicted cross section varies from 5% to 30% in the entire pT range for anti-kt (R = 0.7) CMS Simulation anti-kt (R = 0.7) as a function of jet pT. large as 50% at high pT and even increase up to 100% for the CT10 and HERAPDF1.5 sets. The nonperturbative correction induces an additional uncertainty, which is estimated in the central rapidity bin to range between 1:4% at pT 100 GeV to 0:06% at Overall, the PDF uncertainty is dominant. Electroweak e ects, which arise from the virtual exchange of the massive W and Z gauge bosons, induce corrections with magnitudes given by the Sudakov logarithmic factor W ln2(Q2=M W2), where W is the weak coupling constant, MW is the mass of the W boson, and Q is the energy scale of the interaction. For high-pT jets, the values of the logarithm, and therefore the correction, become large. The derivation of the electroweak correction factor, applied to the NLO pQCD spectrum corrected for nonperturbative e ects, is provided in ref. [34]. Figure 2 shows the electroweak correction for the two extreme rapidity regions as a function of jet pT. In the most central rapidity bin for the high-pT region, the correction factor is as large as 14%. Electroweak corrections are not applied to the low-pT results, where they are negligible. Comparison of theory and data The measured double-di erential cross sections for inclusive jet production are shown in gure 3 as a function of pT in the various jyj ranges after unfolding the detector e ects. This measurement is compared with the theoretical prediction discussed in section 5 using the CT10 PDF set. The ratios of the data to the theoretical predictions in the various jyj ranges are shown for the CT10 PDF set in gure 4. Good agreement is observed for the entire kinematic range with some exceptions in the low-pT region. Figure 5 presents the ratios of the measurements and a number of theoretical predictions based on alternative PDF sets to the CT10 based prediction. A 2 value is computed based on the measurements, their covariance matrices, and the theoretical predictions, as described in detail in section 8. The values for 2 for the comparison between data and theory based on di erent PDF sets for the high-pT region are summarized in table 3. In most cases the theoretical predictions agree with the measurements. The exception is the ABM11 PDF set, where signi cant discrepancies are visible. Signi cant di erences = 5.6 pb-1 CT10 NLO ? NP CT10 NLO ? NP ? EWK 0.5 < |y| < 1.0 ( ? 105 ) 1.0 < |y| < 1.5 ( ? 104 ) 1.5 < |y| < 2.0 ( ? 103 ) 2.0 < |y| < 2.5 ( ? 102 ) 2.5 < |y| < 3.0 ( ? 101 ) 3.2 < |y| < 4.7 ( ? 100 ) Jet p [GeV] the low-pT analysis, lled points for the high-pT one) and NLO predictions based on the CT10 PDF set corrected for the nonperturbative factor for the low-pT data (solid line) and the nonperturbative and electroweak correction factors for the high-pT data (dashed line). The comparison is carried on di erent PDF sets in each jyj range, where cross sections are measured for a number of pT bins Nbins. between the theoretical predictions obtained by using di erent PDF sets are observed in the high-pT range. The predictions based on CT10 PDF show the best agreement with data, quanti ed by the lowest 2 for most rapidity ranges, while predictions using MSTW, ABM11, and HERAPDF1.5 exhibit di erences compared to data and to the prediction based on CT10, exceeding 100% in the highest pT range. In the transition between the low- and high-pT jet regions, some discontinuity can be observed in the measured values, although they are generally compatible within the total experimental uncertainties. The highest pT bins of the low-pT jet range su er from a reduced sample size, and therefore have a statistical uncertainty signi cantly larger than the rst bin of the high-pT jet region. The JES corrections for the low- and high-pT regions Data/Theory(CT10 NLO ? NP) Data/Theory(CT10 NLO ? NP ? EWK) Total exp. sys. unc. Jet p (GeV) 8 TeV Jet p (GeV) 8 TeV CMS = 5.6 pb-1 = 5.6 pb-1 Data/Theory(CT10 NLO ? NP) Data/Theory(CT10 NLO ? NP ? EWK) Total exp. sys. unc. = 5.6 pb-1 = 5.6 pb-1 Data/Theory(CT10 NLO ? NP) Data/Theory(CT10 NLO ? NP ? EWK) Total exp. sys. unc. Data/Theory(CT10 NLO ? NP) Data/Theory(CT10 NLO ? NP ? EWK) Total exp. sys. unc. Data/Theory(CT10 NLO ? NP) Data/Theory(CT10 NLO ? NP ? EWK) Total exp. sys. unc. Jet p (GeV) 8 TeV Data/Theory(CT10 NLO ? NP) Data/Theory(CT10 NLO ? NP ? EWK) Total exp. sys. unc. CMS Jet p (GeV) 8 TeV = 5.6 pb-1 = 5.6 pb-1 Jet p (GeV) Jet p (GeV) CMS anti-kt (R = 0.7) Data/Theory(CT10 NLO ? NP) Total exp. sys. unc. Jet p (GeV) total theoretical (band enclosed by dashed lines) and the total experimental systematic uncertainties (band enclosed by full lines) are shown as well. The error bars correspond to the statistical uncertainty in the data. Data/(CT10 NLO ? NP) Data/(CT10 NLO ? NP ? EWK) Total exp. sys. unc. Data/(CT10 NLO ? NP) Data/(CT10 NLO ? NP ? EWK) Total exp. sys. unc. Jet p (GeV) 8 TeV Data/(CT10 NLO ? NP) Data/(CT10 NLO ? NP ? EWK) Total exp. sys. unc. Jet p (GeV) 8 TeV Jet p (GeV) 8 TeV Data/(CT10 NLO ? NP) Data/(CT10 NLO ? NP ? EWK) Total exp. sys. unc. Data/(CT10 NLO ? NP) Data/(CT10 NLO ? NP ? EWK) Total exp. sys. unc. CMS Data/(CT10 NLO ? NP) Total exp. sys. unc. Jet p (GeV) Jet p (GeV) CMS anti-kt (R = 0.7) Data/(CT10 NLO ? NP) Data/(CT10 NLO ? NP ? EWK) Total exp. sys. unc. = 5.6 pb-1 = 5.6 pb-1 Jet p (GeV) 8 TeV = 5.6 pb-1 = 5.6 pb-1 = 5.6 pb-1 = 5.6 pb-1 200 300 400 Jet p (GeV) set. For comparison, predictions employing ve other PDF sets are shown in addition to the total experimental systematic uncertainties (band enclosed by full lines). The error bars correspond to the statistical uncertainty in the data. are di erent, in particular in the pT-dependent components, and this also contributes to the uctuations in the matching region. The corresponding uncertainties are treated as uncorrelated between the low- and high-pT regions. The overall estimated systematic uncertainties account for these residual e ects. The transition region between the lowand high-pT jet measurements has limited sensitivity to S and no impact in constraining PDFs, since it probes the x-range where the PDFs are well constrained by more precise Ratios of cross sections measured at di erent p Ratios of cross sections measured at di erent energies may show a better sensitivity to PDFs than cross sections at a single energy, provided that the contributions to the theoretical and experimental uncertainties from sources other than the PDFs themselves are reduced. A calculation of the ratio of cross sections measured at 7 and 8 TeV presented in ref. [12], for instance, suggests a larger sensitivity to PDFs in the jet pT range between 1 and 2 TeV. Therefore, it is interesting to study such cross section ratios. Di erential cross sections for the inclusive jet production have been measured by the CMS Collaboration at p di erential cross section presented in this paper at 8 TeV to the corresponding measurements at di erent energies. For pT > 74 GeV, the choice of jet pT and rapidity bins is identical for the various measurements, thus allowing an easy computation of the ratio. Only the high-pT jet data set at 8 TeV is used, since no counterpart of the low-pT jet analysis is available for the other centre-of-mass energies. As a result of partial cancellation of the systematic uncertainties, the relative precision of the ratios is improved compared with the cross section. Experimental correlations between the measurements at di erent centre-of-mass energies are taken into account in the computation of the total experimental uncertainty. As a consequence of the unfolding procedure, the results of the cross section measurements at each energy are statistically correlated between di erent bins, while the measurements at di erent energies are not statistically correlated with each other. The statistical uncertainties in the ratio measurement are calculated by using linear error propagation, taking into account the bin-to-bin correlations in the unfolded data. Correlations between the components of the jet energy corrections at di erent energies are included, as well as correlations in JER. Uncertainties related to the determination of luminosity are assumed to be uncorrelated. The theoretical uncertainties are approached in a similar manner: the uncertainties in nonperturbative corrections, PDFs, and those arising due to scale variations are assumed to be fully correlated. The ratios of the cross sections measured at p s = 7 and 8 TeV are shown in gures 6{7 for the various rapidity bins and they are compared with theoretical predictions obtained using di erent PDF sets. A general agreement between data and theoretical predictions is observed. Some discrepancies are visible at high pT, in particular in the 1:0 < jyj < 1:5 range. In the cross section ratio the central values of the predictions are not strongly in uenced by the choice of the PDFs. However, the uncertainty is mostly dominated by PDF eTV 0.8 8 Data/(NP ? EWK) Data/(NP ? EWK) eTV 0.8 8 Data/(NP ? EWK) Data/(NP ? EWK) s = 7 and 8 TeV, shown as a function of jet pT for the absolute rapidity jyj < 0:5 (left) and 0:5 < jyj < 1:0 (right). The data (closed symbols) are shown with total uncertainties (vertical error bars). The NLO pQCD prediction using the CT10 PDF is shown with its total uncertainty (shaded band) and the contribution of the PDF uncertainty (hatched band). Predictions obtained using alternative PDF sets are shown by lines of di erent styles without uncertainties. The data to theory ratios (bottom panels) are shown by using the same notations for the respective rapidities. The last bin for the jyj < 0:5 region is wider than the others in order to reduce the statistical uncertainty. uncertainties, which are represented here for CT10. The experimental uncertainty in the ratio is considerably larger than the theoretical uncertainty. Consequently, no signi cant constraints on PDFs can be expected from the inclusive jet cross section ratio of 7 to 8 TeV. The ratios of the cross sections measured at 2.76 TeV to those measured at 8 TeV are determined in a similar way. Results are presented in gures 8{10, and compared to theoretical predictions that use di erent PDF sets. In general, the predictions describe the data well. The central value of the theoretical prediction and its uncertainty are completely dominated by the choice of and the uncertainty in the PDFs, demonstrating the strong sensitivity of the 2.76 to 8 TeV cross section ratio to the description of the proton structure. Determination of Measurements of jet production at hadron colliders can be used to determine the strong coupling constant S, as has been previously from the CMS 7 TeV inclusive jet measurement [29], and from Tevatron measurements [49{51]. The procedure to extract ref. [29] is adopted here. Only the high-pT jet data are used, since the sensitivity of the S predictions increases with jet pT. The determination of S is performed by minimizing 2 between the data and the theory prediction. The NLO theory prediction, corrected for nonperturbative and electroweak e ects, is used. At NLO, the dependence of 300 400 500 600 300 400 500 600 eT 0.8 8 ( Data/(NP ? EWK) Data/(NP ? EWK) 1 CMS CMS Data/(NP ? EWK) Data/(NP ? EWK) Data/(NP ? EWK) Data/(NP ? EWK) s = 7 and 8 TeV shown as a function of jet pT for the absolute rapidity 1:0 < jyj < 1:5 (top left), 1:5 < jyj < 2:0 (top right) and 2:0 < jyj < 2:5 (bottom). S is given by: ( R)X^ (0)( F; pT)[1 + S( R)K1( R; F; pT)]; S is the strong coupling, X^ (0)( F; pT) represents the LO contribution to the cross section and K1( R; F; pT) is an NLO correction term. A comparison with the measured spectrum gives an estimate of the input value of from theory, has the best agreement with data. S for which the cross section, predicted 3.5 CMS CT10 Theo. prediction CT10 PDF uncertainty 300 400 500 CT10 Theo. prediction CT10 PDF uncertainty 0.5 ? |y| < 1.0 3.5 CMS 0.5 ? |y| < 1.0 CT10 Theo. prediction CT10 PDF uncertainty 300 400 500 CT10 Theo. prediction CT10 PDF uncertainty 300 400 500 300 400 500 s = 2:76 and 8 TeV are shown as a function of jet pT for the absolute rapidity range jyj < 0:5 (left) and 0:5 < jyj < 1:0 (right). The data (closed symbols) are shown with their statistical (inner error bar) and total (outer error bar) uncertainties. For comparison, the NLO pQCD prediction by using the CT10 PDF is shown with its total uncertainty (light shaded band), while the contribution of the PDF uncertainty is presented by the hatched band. Predictions that use alternative PDF sets are shown by lines of di erent styles without uncertainties. The data to theory ratios (bottom panels) are shown using the same notations for the respective absolute rapidity ranges. The extraction of S is performed by a least squares minimization of the function ( S(MZ)) = T ( S(MZ)) T ( S(MZ)) ; where D is the array of measured values of the double-di erential inclusive jet cross section for the di erent bins in pT and jyj, T ( S(MZ)) is the corresponding set of theoretical cross sections for a given value of S(MZ), and C is the covariance matrix including all the experimental and theoretical uncertainties involved in the measurement. The total eo 2 h 1.0 ? |y| < 1.5 1.0 ? |y| < 1.5 1.5 ? |y| < 2.0 eo 2 h 1.5 ? |y| < 2.0 Figure 9. The ratios of the inclusive jet production cross sections at p s = 2.76 and 8 TeV shown as a function of jet pT for the absolute rapidity ranges 1:0 < jyj < 1:5 and 1:5 < jyj < 2:0. covariance matrix C is built from the individual components as follows: C = Cstat + Cunfolding + CJES + Cuncor + Clumi + CPDF + CNP; Cstat is the statistical covariance matrix, taking into account the correlation between di erent pT bins of the same rapidity range due to unfolding. Di erent rapidity ranges are considered as uncorrelated among themselves; Cunfolding includes the uncertainty induced by the JER parameterization in the unfolding procedure; CJES includes the uncertainty due to JES uncertainties, obtained as the sum of 24 independent matrices, one for each source of uncertainty; Cuncor includes all uncorrelated systematic uncertainties such as trigger and jet identi cation ine ciencies, and time dependence of the jet pT resolution; eo 2 h 2.0 ? |y| < 2.5 2.0 ? |y| < 2.5 eo 2 h 2.5 ? |y| < 3.0 2.5 ? |y| < 3.0 as a function of jet pT for the absolute rapidity ranges 2:0 < jyj < 2:5 and 2:5 < jyj < 3:0. Clumi includes the 2.6% luminosity uncertainty; CPDF is related to uncertainties in the PDF used in the theoretical prediction; CNP includes the uncertainty due to nonperturbative corrections in the theoretical The unfolding, JES, lumi, PDF, and NP systematic uncertainties are considered as 100% correlated among all pT and jyj bins. The extraction of S uses the CT10 NLO PDF set in the theoretical calculation, since it provides the best agreement with measured cross sections, as shown in section 6. This PDF set provides variants corresponding to 16 di erent S(MZ) values in the range 0.112{ 0.127 in steps of 0.001. The sensitivity of the theory prediction to the S choice in the PDF is illustrated in gure 11. The 2 in eq. (8.2) is computed, combining all pT and jyj intervals, for each of the variants corresponding to a di erent S value, as shown in gure 12. The variation of 2 CMS Data/(NLO ? NP ? EWK) Data/(NLO ? NP ? EWK) Data/(NLO ? NP ? EWK) 2 CMS Data/(NLO ? NP ? EWK) Data/(NLO ? NP ? EWK) Data/(NLO ? NP ? EWK) anti-kt (R = 0.7) anti-kt (R = 0.7) 19.7 fb-1 (8TeV) anti-kt (R = 0.7) 19.7 fb-1 (8TeV) anti-kt (R = 0.7) 19.7 fb-1 (8TeV) anti-kt (R = 0.7) 19.7 fb-1 (8TeV) anti-kt (R = 0.7) S(MZ) value of 0.118. Dashed lines represent the ratios of the predictions obtained with the CT10 PDF set evaluated with di erent S(MZ) values, to the central one. The error bars correspond to the total uncertainty of the data. S is tted with a fourth-order polynomial, and the minimum ( 2min) corresponds to S(MZ) value. Uncertainties are determined using the 2 = 1 criterion. The individual contribution from each uncertainty source listed in eq. (8.3) is estimated as the quadratic di erence between the main result and the result of an alternative t, in which that particular source is left out of the covariance matrix de nition. S(MZ) by using the CT10 NLO PDF set and data from all rapidity bins. The uncertainty is obtained from the S(MZ) values for which increased by one with respect to the minimum value, indicated by the box. The curve corresponds to a fourth-degree polynomial t through the available The uncertainties due to the choice of the renormalization and factorization scales are evaluated by variations of the default F values, set to jet pT, in the following six minimization with respect to S(MZ) is repeated in each case, and the maximal upwards and downwards deviations of S(MZ) from the central result are taken as the corresponding In table 4, the tted values of S are presented for each rapidity bin, separately, and for the whole range. The contribution to the uncertainty due to each individual source is also given, together with the best source of uncertainty in the determination of 2min value for each separate t. The largest S is due to the choice of renormalization and factorization scales, pointing to the need for including higher order corrections in the theoretical calculations. 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Hempel19, H. Jung, A. Kalogeropoulos, O. Karacheban19, M. Kasemann, J. Keaveney, J. Kieseler, C. Kleinwort, I. Korol, O. Kuprash, W. Lange, A. Lelek, J. Leonard, K. Lipka, A. Lobanov, W. Lohmann19, 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, 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, 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. Horvath20, F. Sikler, V. Veszpremi, G. Vesztergombi21, A.J. Zsigmond Institute of Nuclear Research ATOMKI, Debrecen, Hungary N. Beni, S. Czellar, J. Karancsi22, J. Molnar, Z. Szillasi University of Debrecen, Debrecen, Hungary M. Bartok21, A. Makovec, 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, 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, S. Bhowmik25, R.K. Dewanjee, S. Ganguly, M. Guchait, Sa. Jain, S. Kumar, M. Maity25, G. Majumder, K. Mazumdar, B. Parida, T. Sarkar25, 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. Pompilia;b, G. Pugliesea;c, R. Radognaa;b, A. Ranieria, G. Selvaggia;b, L. Silvestrisa;15, 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;15 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, 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, Malvezzia, Manzonia;b;15, Marzocchia;b, Menascea, 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, M. Biasottoa;30, A. Bolettia;b, A. Carvalho Antunes De Oliveiraa;b, M. Dall'Ossoa;b, P. De Castro Manzanoa, T. Dorigoa, U. Dossellia, S. Fantinela, F. Fanzagoa, F. Gasparinia;b, U. Gasparinia;b, M. Gulminia;30, S. Lacapraraa, M. Margonia;b, A.T. Meneguzzoa;b, J. Pazzinia;b;15, N. Pozzobona;b, P. Ronchesea;b, E. Torassaa, S. Venturaa, 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;31, P. Azzurria;15, G. Bagliesia, J. Bernardinia, T. Boccalia, R. Castaldia, M.A. Cioccia;31, R. Dell'Orsoa, S. Donatoa;c, G. Fedi, A. Giassia, M.T. Grippoa;31, F. Ligabuea;c, T. Lomtadzea, L. Martinia;b, A. Messineoa;b, F. Pallaa, A. Rizzia;b, A. SavoyNavarroa;32, P. Spagnoloa, R. Tenchinia, G. Tonellia;b, A. Venturia, P.G. Verdinia A. Zanettia H. Kim, A. Lee 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;15, 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, I. Ahmed, Z.A. Ibrahim, J.R. Komaragiri, M.A.B. Md Ali33, F. Mohamad Idris34, 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 Cruz35, 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 P.H. Butler University of Canterbury, Christchurch, New Zealand National Centre for Physics, Quaid-I-Azam University, Islamabad, Pakistan A. Ahmad, M. Ahmad, Q. Hassan, H.R. Hoorani, W.A. Khan, 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, Warsaw, Poland K. Bunkowski, A. Byszuk36, K. Doroba, A. Kalinowski, M. Konecki, J. Krolikowski, M. Misiura, M. Olszewski, M. Walczak Laboratorio de Instrumentac~ao e F sica Experimental de Part culas, Lisboa, Joint Institute for Nuclear Research, Dubna, Russia Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia L. Chtchipounov, V. Golovtsov, Y. Ivanov, V. Kim39, E. Kuznetsova40, 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. Chistov41, V. Rusinov, E. Tarkovskii P.N. Lebedev Physical Institute, Moscow, Russia V. Andreev, M. Azarkin38, I. Dremin38, M. Kirakosyan, A. Leonidov38, S.V. Rusakov, Moscow, Russia Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, A. Baskakov, A. Belyaev, E. Boos, M. Dubinin42, L. Dudko, A. Ershov, A. Gribushin, V. Klyukhin, O. Kodolova, I. Lokhtin, I. Miagkov, S. Obraztsov, S. Petrushanko, V. Savrin, 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. Adzic43, P. Cirkovic, D. Devetak, J. Milosevic, V. Rekovic Medioambientales 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 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. Starodumov49, M. Takahashi, V.R. Tavolaro, K. Theo latos, R. Wallny Universitat Zurich, Zurich, Switzerland T.K. Aarrestad, C. Amsler50, 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, S. Cerci51, S. Damarseckin, Z.S. Demiroglu, C. Dozen, I. Dumanoglu, S. GirS. Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East Technical University, Physics Department, Ankara, Turkey B. Bilin, S. Bilmis, B. Isildak56, G. Karapinar57, M. Yalvac, M. Zeyrek Bogazici University, Istanbul, Turkey E. Gulmez, M. Kaya58, O. Kaya59, E.A. Yetkin60, T. Yetkin61 Istanbul Technical University, Istanbul, Turkey A. Cakir, K. Cankocak, S. Sen62 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. Newbold63, S. Paramesvaran, A. Poll, T. Sakuma, S. Seif El Nasr-storey, D. Smith, Rutherford Appleton Laboratory, Didcot, United Kingdom K.W. Bell, A. Belyaev64, 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. Lucas63, L. Lyons, A.-M. Magnan, S. Malik, L. Mastrolorenzo, J. Nash, A. Nikitenko49, J. Pela, B. Penning, M. Pesaresi, D.M. Raymond, A. Richards, A. Rose, C. Seez, A. Tapper, K. Uchida, M. Vazquez Acosta65, 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 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, 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. 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Uplegger, E.W. Vaandering, C. Vernieri, M. Verzocchi, R. Vidal, M. Wang, H.A. Weber, A. Whitbeck University of Florida, Gainesville, U.S.A. D. Acosta, P. Avery, P. Bortignon, D. Bourilkov, A. Brinkerho , A. Carnes, M. Carver, D. Curry, S. Das, R.D. Field, I.K. Furic, J. Konigsberg, A. Korytov, P. Ma, K. Matchev, H. Mei, P. Milenovic67, 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. Colafranceschi68, 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. Bilki69, W. Clarida, K. Dilsiz, S. Durgut, R.P. Gandrajula, M. Haytmyradov, V. Khristenko, J.-P. Merlo, H. Mermerkaya70, A. Mestvirishvili, A. Moeller, J. Nachtman, H. Ogul, Y. Onel, F. Ozok71, 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. 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, 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. Musienko37, 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 The Rockefeller University, New York, U.S.A. C. Mesropian 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, A. Lath, K. Nash, H. Saka, S. Salur, S. Schnetzer, D. She eld, S. Somalwar, R. Stone, S. Thomas, P. Thomassen, M. Walker University of Tennessee, Knoxville, U.S.A. M. Foerster, J. Heideman, G. Riley, K. Rose, S. Spanier, K. Thapa Texas A&M University, College Station, U.S.A. O. Bouhali72, A. Celik, M. Dalchenko, M. De Mattia, A. Delgado, S. Dildick, R. Eusebi, J. Gilmore, T. Huang, E. Juska, T. Kamon73, 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 y: Deceased 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 8: Also at Joint Institute for Nuclear Research, Dubna, Russia 9: Also at Suez University, Suez, Egypt 10: Now at British University in Egypt, Cairo, Egypt 11: Also at Ain Shams University, Cairo, Egypt 13: Now at Helwan University, 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, Moscow, Russia 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 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 Laboratori Nazionali di Legnaro dell'INFN, Legnaro, Italy 31: Also at Universita degli Studi di Siena, Siena, Italy 32: Also at Purdue University, West Lafayette, U.S.A. 33: Also at International Islamic University of Malaysia, Kuala Lumpur, Malaysia 34: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia 35: Also at Consejo Nacional de Ciencia y Tecnolog a, Mexico city, Mexico 36: Also at Warsaw University of Technology, Institute of Electronic Systems, Warsaw, Poland 37: Also at Institute for Nuclear Research, Moscow, Russia at National Research Nuclear University 'Moscow Engineering Physics Insti39: Also at St. Petersburg State Polytechnical University, St. Petersburg, Russia 40: Also at University of Florida, Gainesville, U.S.A. 41: Also at P.N. Lebedev Physical Institute, Moscow, Russia 42: Also at California Institute of Technology, Pasadena, U.S.A. 43: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia 44: Also at INFN Sezione di Roma; Universita di Roma, Roma, Italy 45: Also at National Technical University of Athens, Athens, Greece 46: Also at Scuola Normale e Sezione dell'INFN, Pisa, Italy 47: Also at National and Kapodistrian University of Athens, Athens, Greece 48: Also at Riga Technical University, Riga, Latvia 49: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia 50: Also at Albert Einstein Center for Fundamental Physics, Bern, Switzerland 51: Also at Adiyaman University, Adiyaman, Turkey 52: Also at Mersin University, Mersin, Turkey 53: Also at Cag University, Mersin, Turkey 54: Also at Piri Reis University, Istanbul, Turkey 55: Also at Gaziosmanpasa University, Tokat, Turkey 57: Also at Izmir Institute of Technology, Izmir, Turkey 58: Also at Marmara University, Istanbul, Turkey 59: Also at Kafkas University, Kars, Turkey 60: Also at Istanbul Bilgi University, Istanbul, Turkey 61: Also at Yildiz Technical University, Istanbul, Turkey 62: Also at Hacettepe University, Ankara, Turkey 63: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom 64: Also at School of Physics and Astronomy, University of Southampton, Southampton, United Belgrade, Serbia 65: Also at Instituto de Astrof sica de Canarias, La Laguna, Spain 66: Also at Utah Valley University, Orem, U.S.A. 67: Also at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, 68: Also at Facolta Ingegneria, Universita di Roma, Roma, Italy 69: Also at Argonne National Laboratory, Argonne, U.S.A. 70: Also at Erzincan University, Erzincan, Turkey 71: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey 72: Also at Texas A&M University at Qatar, Doha, Qatar 73: Also at Kyungpook National University, Daegu, Korea [19] M. 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