Measurement of B anti-B Angular Correlations based on Secondary Vertex Reconstruction at sqrt(s)=7 TeV

EUROPEAN ORGANIZATION FOR NUCLEAR RESEARCH (CERN) CERN-PH-EP/2010-093 2011/02/22 CMS-BPH-10-010 Measurement of BB Angular Correlations based on Secondary Vertex Reconstruction at √s=7 TeV The CMS Collaboration∗ Abstract A measurement of the angular correlations between beauty and anti-beauty hadrons (BB) produced in pp collisions at a centre-of-mass energy of 7 TeV at the CERN LHC is presented, probing for the first time the region of small angular separation. The B hadrons are identified by the presence of displaced secondary vertices from their decays. The B hadron angular separation is reconstructed from the decay vertices and the primary-interaction vertex. The differential BB production cross section, measured from a data sample collected by CMS and corresponding to an integrated luminosity of 3.1 pb−1, shows that a sizable fraction of the BB pairs are produced with small opening angles. These studies provide a test of QCD and further insight into the dynamics of bb production. Submitted to the Journal of High Energy Physics ∗See Appendix A for the list of collaboration members arXiv:1102.3194v2 [hep-ex] 21 Feb 2011 22 The CMS Detector 1 Introduction Beauty quarks are abundantly produced through strong interactions in pp collisions at the CERN Large Hadron Collider (LHC). The hadroproduction of bb pairs is measured to have a large cross section (of the order of 100 µb) at a centre-of-mass energy of 7 TeV [1–3]. Detailed b quark production studies provide substantial information about the dynamics of the underlying hard scattering subprocesses within perturbative Quantum Chromodynamics (pQCD). In lowest order pQCD, i.e. in 2 →2 parton interaction subprocesses, momentum conservation requires the b and b quarks to be emitted in a back-to-back topology. However, higher order 2→2+n(n≥1) subprocesses with additional partons (notably gluons) emitted, give rise to different topologies of the final state b quarks. Consequently, measurements of bb angular and momentum correlations provide information about the underlying production subprocesses and allow for a sensitive test of pQCD leading-order (LO) and next-to-leading order (NLO) cross sections and their evolution with event energy scales. Studies of b quark production at the LHC may provide insight into the hadronisation properties of heavy quarks at these new energy scales, as well as better knowledge of the heavy quark content of the proton. In addition, identification of b quarks and precision measurements of their properties are crucial ingredients for new physics searches in which bb hadroproduction is expected to be one of the main backgrounds. In this paper, angular correlations between pairs of beauty hadrons, hereafter referred to as “B hadrons”, are studied with the Compact Muon Solenoid (CMS) detector, probing for the first time the region of very small angular separation at √s=7 TeV. Measurements of BB-pair production are presented differentially as a function of the opening angle for different event scales, characterised by the leading jet transverse momentum. The extrapolation back to the angular separation of the b quarks, which requires modeling of heavy quark fragmentation and hadronisation, is not considered in this analysis. The results are given for the visible kinematic range defined by the phase space at the hadron level. Measurements of the full range of BB angular separation demand good angular resolution and require the ability to resolve small opening angles when the two B hadrons are inside a single reconstructed jet. The kinematic properties of B hadrons can be reconstructed using jets, leptons from semileptonic decays of B hadrons or secondary vertices (SV) originating from the decay of long-lived B hadrons. In this analysis, a method based on an iterative inclusive secondary vertex finder that exploits the excellent tracking capabilities of the CMS detector is introduced. One advantage of this method is the unique capability to detect BB pairs even at small opening angles, in which case the decay products of the B hadrons tend to be merged into a single jet and the standard B jet tagging techniques [4] are not applicable. Previously, studies of azimuthal bb correlations using vertexing have been done at lower energy in pp collisions [5, 6]. In Section 2, a brief overview of the subdetectors relevant for this analysis is given. Section 3 describes the Monte Carlo (MC) simulations and the programs used for QCD predictions. The event selection, the analysis details, and the determination of efficiencies and systematic uncertainties are described in Section 4. In Section 5 we present the results and compare the data with theoretical predictions. 2 The CMS Detector A detailed description of the CMS detector can be found in Ref. [7]. The central feature of the CMS apparatus is a superconducting solenoid of 6 m internal diameter, with a 3.8 T axial magnetic field. The subdetectors used in the present analysis are tracking detectors and 3 calorimeters, located within the field volume. The tracker consists of a silicon pixel and silicon strip tracker covering the pseudorapidity range |η|<2.5. The pixel tracker consists of three barrel layers and two endcap disks at each barrel end. The strip tracker has 10 barrel layers and 12 endcap disks. The barrel and endcap calorimeters (|η|<3) consist of a lead-tungstate crystal electromagnetic calorimeter (ECAL) and a brass/scintillator hadron calorimeter (HCAL). The ECAL and HCAL cells are grouped into towers, projecting radially outward from the interaction region, for triggering purposes and to facilitate jet reconstruction. The CMS experiment uses a right-handed coordinate system, with the origin at the nominal proton-proton collision point, the x-axis pointing towards the centre of the LHC ring, the y-axis pointing upwards (perpendicular to the LHC plane), and the z-axis pointing along the anticlockwise beam direction. The polar angle θis measured from the positive z-axis and the azimuthal angle φis measured from the positive x-axis in the xy plane. The radius rdenotes the distance from the z-axis and the pseudorapidity is defined by η=−ln(tan(θ/2)). 3 Monte Carlo Simulation and QCD Predictions Different simulation programs at the LO and the NLO level have been utilized to describe the b production process within perturbative QCD. Within the LO picture, three parton level production subprocesses can be defined [8, 9], conventionally denoted by flavour creation (FCR), flavour excitation (FEX) and gluon splitting (GSP), and are implemented in Monte Carlo event generators like PYTHIA [10] and HERWIG [11]. These subprocesses are related to different final state topologies. Notably, in FCR processes the bb pairs are expected to be emitted in a backto-back topology, which corresponds to a large angular separation between the b and b quarks, whereas in GSP the pair emission follows a more collinear topology, i.e. a small angular separation between the b and b quarks. At higher orders in QCD, the FCR, FEX and GSP separation of production subprocesses becomes meaningless and only the combination of the 2 →2 and 2→2+n(n≥1) subprocesses is relevant. Calculations of such processes are implemented in MC@NLO [12–14] or FONLL [15]. The MADGRAPH/MADEVENT [16, 17] generator provides the possibility to simulate 2 →2, 3 subprocesses at tree-level, providing a hybrid solution between 2 →2 at LO and the NLO simulations. We use also the CASCADE [18] generator, which is based on off-shell LO matrix elements using high-energy factorization [19] convolved with unintegrated parton distributions. The basic Monte Carlo event generator applied in this analysis is the LO PYTHIA program (version 6.422 [10]), which is used to determine selection efficiencies and to optimise the vertexing algorithm for B hadron reconstruction. The event samples are generated applying the standard PYTHIA settings [10] with tune D6T [20] for the underlying event and with the CTEQ6L1 [21] proton parton distribution functions (PDF). All events generated by the PYTHIA program are processed with a detailed simulation of the CMS detector response based on the GEANT4 package [22]. For comparison with theoretical predictions, events with two and three partons in the final state are generated by means of the MADGRAPH/MADEVENT4 program, where the showering is performed with PYTHIA, and the jet matching scheme used is “kT-MLM” [23]. The CTEQ6L1 [21] parton distribution functions are used, and the mass of the b quark is set to mb=4.75 GeV. For the events produced with the CASCADE generator, the CCFM set A [24] of parton distributions is used. The calculations include the processes g∗g∗→b¯ band g∗q→gq →b¯ bX. The matrix element of g∗g∗→b¯ balready includes a large fraction of the process g∗g→gg → b¯ bX [19, 25], therefore g∗g→gg →b¯ bX is not added to avoid double counting. 44 Event Selection and Data Analysis A further set of QCD events is produced by means of the MC@NLO generator (version 3.4 [14] with standard scale settings and b-quark mass mb=4.75 GeV), which matches NLO QCD matrix element calculations with parton shower simulations as implemented in HERWIG (version 6.510) [11]. The proton PDF set used is CTEQ6M [21]. For the NLO generated events, no full CMS detector simulation is done. Subsequent to the parton showering and hadronisation process, the generated stable particles in the events are clustered into jets with the anti-kTjet algorithm [26]. 4 Event Selection and Data Analysis The data sample used in this analysis was collected by the CMS experiment during 2010 at a centre-of-mass energy of √s=7 TeV and corresponds to an integrated luminosity of 3.1 ± 0.3 pb−1. Only data from runs when the CMS detector components relevant for this analysis were fully functional and when stable beam conditions were present are used. Events from non-collision processes are rejected by requiring a primary (“collision”) vertex (PV) [27, 28] with at least four well reconstructed tracks. Background from beam-wall and beam halo events, and events faking high energy deposits in the HCAL, are filtered out based on pulse shape, hit multiplicity and timing criteria. 4.1 Analysis Overview The analysis relies on the single-jet trigger in both the hardware-level (L1) and the software high-level (HLT) components of the CMS trigger system [7]. We require at least one HLT jet with uncorrected transverse calorimetric energy EU Tabove a trigger threshold of 15, 30 or 50 GeV. Figure 1 shows the leading jet transverse momentum (pT) spectra with particle flow jets [29] and the corresponding trigger efficiency dependence on pT. The efficiencies, also shown in Figure 1, are determined using events selected with a lower EU T(prescaled) trigger. The event sample is then divided into three energy scale bins corresponding to the pTranges where the different jet triggers are over 99% efficient. These correspond to samples where the transverse momenta of the leading jet, using corrected jet energies [30], exceed 56, 84 and 120 GeV, respectively. The effective integrated luminosity, taking into account the trigger prescale factors, corresponds to 0.031, 0.313 and 3.069 pb−1, respectively, for the three samples, including some overlap. The visible kinematic range for the measurements is defined at the B hadron level by the requirements |η(B)|<2.0 and pT(B)>15 GeV for both of the B hadrons. The leading jet used to define the minimum energy scale is required to be within |η(jet)|<3.0. In this analysis, the HLT triggered events are required to have at least one reconstructed jet with a minimum corrected pT, a reconstructed PV, and in addition at least two reconstructed secondary vertices (SV). For the offline jet reconstruction, particle flow objects [29] are clustered with the anti-kTjet algorithm [26, 31] with a distance parameter RkT=0.5. For further BB angular analysis, these generic secondary vertices are required to originate from B hadron decays, as described in the following paragraphs. The flight direction of the original B hadron is approximated by the vector −→ SV, joining the PV (position of B hadron production) and the SV (position of the B hadron decay). The length |−→ SV|is the three-dimensional flight distance (D3D) and its significance is given by S3D= D3D/σ(D3D), where σ(D3D)is the uncertainty of D3D. In an event with two SVs, which are considered to originate from a bb pair, the angular correla- 4.2 Vertex Reconstruction and BCandidate Identification 5 (GeV) T leading jet p 50 100 150 200 250 300 350 400 450 500 number of events 1 10 2 10 3 10 4 10 5 10 6 10 7 10 8 10 > 15 GeV U T E > 30 GeV U T E > 50 GeV U T E -1 = 7 TeV, L = 3.1 pbsCMS (GeV) T leading jet p 50 100 150 200 250 300 350 400 450 500 number of events 1 10 2 10 3 10 4 10 5 10 6 10 7 10 8 10 (GeV) T leading jet p 0 20 40 60 80 100 120 140 efficiency 0 0.2 0.4 0.6 0.8 1 (GeV) T leading jet p 0 20 40 60 80 100 120 140 efficiency 0 0.2 0.4 0.6 0.8 1 > 15 GeV U T E > 30 GeV U T E > 50 GeV U T E -1 = 7 TeV, L = 3.1 pbsCMS (GeV) T leading jet p 0 20 40 60 80 100 120 140 efficiency 0 0.2 0.4 0.6 0.8 1 Figure 1: The measured transverse momentum distributions of the leading jet in the event (left) and measured efficiency to trigger an event on the high-level trigger as a function of jet pT(right), for three different trigger thresholds. tion variables between the B and B hadrons are calculated using their flight directions. Typical variables used for the characterization of the angular correlations between the two hadrons are the difference in azimuthal angles (∆φ) and the difference in polar angles, usually expressed in terms of pseudorapidity (∆η), or the combined separation variable ∆R=p∆η2+∆φ2. The kinematic regions with ∆R<0.8 and with ∆R>2.4 are used for comparisons or normalisations of the simulation. The cross sections integrated over these two regions will be denoted by σ∆R<0.8 and by σ∆R>2.4, and the ratio by ρ∆R=σ∆R<0.8/σ∆R>2.4. This is inspired by the theoretical predictions, since at low ∆Rvalues the gluon splitting process is expected to contribute significantly, whereas at high ∆Rvalues flavour creation prevails. 4.2 Vertex Reconstruction and BCandidate Identification The primary vertex is reconstructed from tracks of low impact parameter with respect to the nominal interaction region. In cases of multiple interactions in the same bunch crossing (pileup events), the primary interaction vertex is chosen to be the one with the largest squared transverse momentum sum ST=∑p2 Ti, where the sum runs over all tracks associated with the vertex. Residual effects from pile-up events are found to be negligible. Next, the events are required to have at least two reconstructed secondary vertices. An inclusive secondary vertex finding (IVF) technique, completely independent of jet reconstruction, is applied for this purpose. This technique reconstructs secondary vertices by clustering tracks around the so-called seeding tracks characterized by high three-dimensional impact parameter significance Sd=d/σ(d), where dand σ(d)are the impact parameter and its uncertainty at the PV, respectively. The tracks are clustered to a seed track based on their compatibility given their separation distance in three dimensions, the separation distance significance (distance normalised to its uncertainty), and the angular separation. The clustered tracks are then fitted to a common vertex with an outlier-resistant fitter [32, 33]. The vertices sharing more than 70% of the tracks compatible within the uncertainties are merged. As a final step, all tracks are assigned to either the primary or the secondary vertices on the basis of the significance of the track to vertex distance. In this analysis, a SV is required to be made up of at least three tracks, to have a maximal two- 64 Event Selection and Data Analysis dimensional flight distance Dxy =|−→ SVxy|<2.5 cm, a minimal two-dimensional flight distance significance S2D=Dxy/σ(Dxy)>3, and to possess a vertex mass mSV <6.5 GeV. Here, σ(Dxy) is the uncertainty on Dxy. The four-momentum of the vertex pSV = (ESV,~ pSV)is calculated as the sum pSV =∑piover all tracks fitted to that vertex, with pi= (Ei,~ pi), using the pion mass hypothesis for every track to obtain its energy Ei. The vertex mass mSV is calculated as m2 SV =E2 SV −~ p2 SV. The four-momentum of the reconstructed B hadron candidate is then identified with the SV four–momentum, and thus the variables pT(B),η(B)for the B hadron candidates are readily calculated from pSV. Events with at least two secondary vertices may originate from any of the following processes: a) true ’signal’ BB events; b) true BB events where at least one B hadron is not correctly reconstructed (SV from other sources); c) QCD events with light quark and gluon jets, which enter through misidentification of vertices not originating from B decay; d) direct cc production with long lived D hadrons; e) sequential B→D→Xdecay chains, where B hadrons decay to long lived D hadrons, and both B and D vertices are reconstructed. The BB signal events contain a fraction from top quark pair production of less than 1% [34, 35]. Often, both the B and D decay vertices are reconstructed by the IVF. Such topologies need to be distinguished from events with two quasi-collinear B hadrons. To achieve this, an iterative merging procedure is applied to vertices with ∆R<0.4. The procedure is optimised to yield a single B candidate associated with a decay chain B→D→X, while successfully retaining two B candidates also in events where two real B hadrons are emitted nearly collinearly. The vertices are merged into a single B candidate if the invariant mass of the sum over all tracks is below 5.5 GeV and cos β>0.99, where βis the angle between the line connecting the two vertices and the sum of the momenta of the tracks associated to the vertex at largest distance from the PV. All B candidates are retained if they have a minimal 3D flight distance significance S3D>5, a pseudorapidity |η(SV)|<2, a transverse momentum pT(SV)>8 GeV, and a vertex mass mSV >1.4 GeV. The quality of the B candidate reconstruction technique is illustrated in Fig. 2 for events with a leading jet having pT>84 GeV (all selection cuts apart from those on the shown quantities are applied). The simulation describes the data very well in terms of vertex mass and 3D decay length significance distribution. Only those events which have exactly two B hadron candidates and which have a vertex mass sum m1+m2>4.5 GeV are retained. A total of 160, 380 and 1038 events pass all these requirements for the three leading jet pTbins, respectively from the lowest to the highest. The overall contributions from events with three or more B candidates is found to be negligible (less than 1%). 4.3 Efficiency and Resolution This analysis uses selection efficiency corrections as a function of the leading jet pTand the ∆Rbetween the two SVs. The corrections are determined from the simulated PYTHIA event samples. They extrapolate from the measured vertex momenta to the visible phase space of true B hadrons, defined by |η(B)|<2.0, and pT(B)>15 GeV. The momentum measured by the vertex candidate represents of the order of 50% of the true B hadron momentum. The overall event reconstruction efficiencies (including both B hadron decays) are found to be 7.4%, 9.3% and 10.7%, on average, for the three jet pTbins, respectively from the lowest to the highest. The validity of the ∆R-dependence of the efficiencies obtained from simulation is checked using a data driven method based on event mixing, as illustrated below. It is found that the ∆R- 4.4 Systematic Uncertainties 7 vertex mass (GeV) 0 1 2 3 4 5 6 7 8 number of B candidates -1 10 1 10 2 10 3 10 4 10 Data B D Light -1 = 7 TeV, L = 3.1 pbsCMS vertex mass (GeV) 0 1 2 3 4 5 6 7 8 number of B candidates -1 10 1 10 2 10 3 10 4 10 3D flight distance significance 0 50 100 150 200 250 number of B candidates -1 10 1 10 2 10 3 10 Data B D Light -1 = 7 TeV, L = 3.1 pbsCMS 10 20 0 200 400 600 800 3D flight distance significance 0 50 100 150 200 250 number of B candidates -1 10 1 10 2 10 3 10 Figure 2: Properties of the reconstructed B candidates: vertex mass distribution (left) and flight distance significance distribution (right). The inset in the right plot shows a zoom of the flight distance significance distribution with narrower bins and linear scale. The data are shown by the solid points. The decomposition into the different sources, beauty, charm and light quarks, is shown for the PYTHIA Monte Carlo simulation. The simulated distributions are normalised to the total number of data events. All selection cuts apart from those on the shown quantities are applied. dependence is well described by the simulation, justifying this approach. The differences are used to estimate the systematic uncertainties. The resolution achieved in the ∆Rreconstruction is estimated from simulation. The comparison of the ∆Rvalues reconstructed between the two vertices ∆RVV with the values calculated between the original true B hadrons ∆RBB, determines the resolution. This is illustrated in Fig. 3, which shows the two-dimensional distribution ∆RVV versus ∆RBB and its projection onto the diagonal (∆RVV −∆RBB). A fit to this projection directly yields an average resolution better than 0.02 in ∆Rfor the core region, a value much smaller than the ∆Rbin width of 0.4. In order to calculate differential cross sections, a ∆R-dependent purity correction is applied. The contributions to purity due to migration are illustrated in Fig. 3a. The total number of event entries off the diagonal is found to be about 3%. The largest impurity occurs close to ∆RVV ≈3 as can be seen in the 2D plot. These events are due to misreconstructed collinear events where only one B hadron is reconstructed, while a fake vertex is found in the recoiling light quark jet. The largest effect on a single bin is below 10% and this is taken into account in the purity correction. The uncertainty arising from this correction is included in the systematic uncertainties. The average BB purity is found to be 84%, with a variation within about ±10% over the full ∆Rrange in the visible region for the three leading jet pTbins. 4.4 Systematic Uncertainties Uncertainties relevant to the shape of the differential distributions are crucial for this paper. The consistency in shape between the data and the simulation is assessed and the systematic uncertainties are estimated by data driven methods. The systematic uncertainties related to the absolute normalisation are much larger than the shape dependent ones. They sum up to a total of 47%, but do not affect the shape analysis (see below). The dominant contribution originates from the B hadron reconstruction efficiency (±20%, estimated in [4]), which amounts to a total 84 Event Selection and Data Analysis BB R∆ 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 VV R∆ 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 1 10 2 10 637 23 5 1 11 388 8 7 183 2 7 109 1 5 107 2 5 2 135 1 4 2 252 6 5 6 1 1 1 7 471 3 4 1 1 5 2 206 4 4 1 60 4 20 = 7 TeV, SimulationsCMS BB R∆ 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 VV R∆ 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 BB R∆ - VV R∆ -0.2 -0.15 -0.1 -0.05 0 0.05 0.1 0.15 0.2 number of events 0 50 100 150 200 250 300 350 400 = 7 TeV, SimulationsCMS BB R∆ - VV R∆ -0.2 -0.15 -0.1 -0.05 0 0.05 0.1 0.15 0.2 number of events 0 50 100 150 200 250 300 350 400 Figure 3: Resolution of the ∆Rreconstruction, obtained using simulation for the leading jet pT>84 GeV sample. Left: ∆Rvalues reconstructed between the two secondary vertices ∆RVV versus the values between the original B hadrons ∆RBB, in the visible B hadron phase space (see text). Right: projection onto the diagonal (∆RVV −∆RBB). The numbers in the boxes represent the number of events reconstructed in that particular bin. of 44% for reconstructing two B hadrons. In the following the shape dependent systematic uncertainties for the ∆Rdistributions are discussed. The values are quoted in terms of the relative change of the integrated cross section ratio ρ∆R=σ∆R<0.8/σ∆R>2.4. Very similar systematic uncertainties arise for the ∆φdistributions and, hence, they are not quoted separately. •Algorithmic effects. The shape of the ∆Rdependence of the efficiency α(∆R)is checked by means of an event mixing method. This event mixing technique mimics an event with two genuine SVs by merging two independent events, where each has at least one reconstructed SV. The positions of the two PVs are required to be within 20 µm in three-dimensional space. This mixed event is then analysed and the fraction of cases where both original SVs are again properly reconstructed is used to determine the ∆Rdependence of the efficiency to find two genuine SVs in an event which had the SVs already reconstructed. The shape of this efficiency α(∆R)is determined for the data and for the simulated samples independently in bins of ∆R. The vertex reconstruction efficiency as a function of ∆Rfor data and for simulation, and their ratio are shown in Fig. 4. Since in this analysis the shape is the most relevant property, the values in Fig. 4b have been rescaled to the mean value. This ratio exhibits good consistency in shape between simulation and data over the full ∆Rrange, including the region of small ∆R. The differences are found to be within 2% and are taken as systematic uncertainties. •Bhadron momenta. The mean reconstruction efficiency for an observed ∆Rvalue strongly depends on the kinematic properties of the B hadron pair. 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Walzel, E. Widl, C.-E. Wulz National Centre for Particle and High Energy Physics, Minsk, Belarus V. Mossolov, N. Shumeiko, J. Suarez Gonzalez Universiteit Antwerpen, Antwerpen, Belgium L. Benucci, K. Cerny, E.A. De Wolf, X. Janssen, T. Maes, L. Mucibello, S. Ochesanu, B. Roland, R. Rougny, M. Selvaggi, H. Van Haevermaet, P. Van Mechelen, N. Van Remortel Vrije Universiteit Brussel, Brussel, Belgium S. Beauceron, F. Blekman, S. Blyweert, J. D’Hondt, O. Devroede, R. Gonzalez Suarez, A. Kalogeropoulos, J. Maes, M. Maes, S. Tavernier, W. Van Doninck, P. Van Mulders, G.P. Van Onsem, I. Villella Universit´e Libre de Bruxelles, Bruxelles, Belgium O. Charaf, B. Clerbaux, G. De Lentdecker, V. Dero, A.P.R. Gay, G.H. Hammad, T. Hreus, P.E. Marage, L. Thomas, C. Vander Velde, P. Vanlaer, J. Wickens Ghent University, Ghent, Belgium V. Adler, S. Costantini, M. Grunewald, B. Klein, A. Marinov, J. Mccartin, D. Ryckbosch, F. Thyssen, M. Tytgat, L. Vanelderen, P. Verwilligen, S. Walsh, N. Zaganidis Universit´e Catholique de Louvain, Louvain-la-Neuve, Belgium S. Basegmez, G. Bruno, J. Caudron, L. Ceard, J. De Favereau De Jeneret, C. Delaere, P. Demin, D. Favart, A. Giammanco, G. Gr´ egoire, J. Hollar, V. Lemaitre, J. Liao, O. Militaru, S. Ovyn, D. Pagano, A. Pin, K. Piotrzkowski, N. Schul Universit´e de Mons, Mons, Belgium N. Beliy, T. Caebergs, E. Daubie Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil G.A. Alves, D. De Jesus Damiao, M.E. Pol, M.H.G. Souza Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil W. Carvalho, E.M. Da Costa, C. De Oliveira Martins, S. Fonseca De Souza, L. Mundim, H. Nogima, V. Oguri, W.L. Prado Da Silva, A. Santoro, S.M. Silva Do Amaral, A. Sznajder, F. Torres Da Silva De Araujo Instituto de Fisica Teorica, Universidade Estadual Paulista, Sao Paulo, Brazil F.A. Dias, M.A.F. Dias, T.R. Fernandez Perez Tomei, E. M. Gregores2, F. Marinho, S.F. Novaes, Sandra S. Padula Institute for Nuclear Research and Nuclear Energy, Sofia, Bulgaria N. Darmenov1, L. Dimitrov, V. Genchev1, P. Iaydjiev1, S. Piperov, M. Rodozov, S. Stoykova, G. Sultanov, V. Tcholakov, R. Trayanov, I. Vankov 20 A The CMS Collaboration University of Sofia, Sofia, Bulgaria M. Dyulendarova, R. Hadjiiska, V. Kozhuharov, L. Litov, E. Marinova, M. Mateev, B. Pavlov, P. Petkov Institute of High Energy Physics, Beijing, China J.G. Bian, G.M. Chen, H.S. Chen, C.H. Jiang, D. Liang, S. Liang, J. Wang, J. Wang, X. Wang, Z. Wang, M. Xu, M. Yang, J. Zang, Z. Zhang State Key Lab. of Nucl. Phys. and Tech., Peking University, Beijing, China Y. Ban, S. Guo, Y. Guo, W. Li, Y. Mao, S.J. Qian, H. Teng, L. Zhang, B. Zhu, W. Zou Universidad de Los Andes, Bogota, Colombia A. Cabrera, B. Gomez Moreno, A.A. Ocampo Rios, A.F. Osorio Oliveros, J.C. Sanabria Technical University of Split, Split, Croatia N. Godinovic, D. Lelas, K. Lelas, R. Plestina3, D. Polic, I. Puljak University of Split, Split, Croatia Z. Antunovic, M. Dzelalija Institute Rudjer Boskovic, Zagreb, Croatia V. Brigljevic, S. Duric, K. Kadija, S. Morovic University of Cyprus, Nicosia, Cyprus A. Attikis, M. Galanti, J. Mousa, C. Nicolaou, F. Ptochos, P.A. Razis, H. Rykaczewski Charles University, Prague, Czech Republic M. Finger, M. Finger Jr. Academy of Scientific Research and Technology of the Arab Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt Y. Assran4, M.A. Mahmoud5 National Institute of Chemical Physics and Biophysics, Tallinn, Estonia A. Hektor, M. Kadastik, K. Kannike, M. M¨ untel, M. Raidal, L. Rebane Department of Physics, University of Helsinki, Helsinki, Finland V. Azzolini, P. Eerola Helsinki Institute of Physics, Helsinki, Finland S. Czellar, J. H¨ ark¨ onen, A. Heikkinen, V. Karim¨ aki, R. Kinnunen, J. Klem, M.J. Kortelainen, T. Lamp´ en, K. Lassila-Perini, S. Lehti, T. Lind´ en, P. Luukka, T. M¨ aenp¨ a¨ a, E. Tuominen, J. Tuominiemi, E. Tuovinen, D. Ungaro, L. Wendland Lappeenranta University of Technology, Lappeenranta, Finland K. Banzuzi, A. Korpela, T. Tuuva Laboratoire d’Annecy-le-Vieux de Physique des Particules, IN2P3-CNRS, Annecy-le-Vieux, France D. Sillou DSM/IRFU, CEA/Saclay, Gif-sur-Yvette, France M. Besancon, S. Choudhury, M. Dejardin, D. Denegri, B. Fabbro, J.L. Faure, F. Ferri, S. Ganjour, F.X. Gentit, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry, E. Locci, J. Malcles, M. Marionneau, L. Millischer, J. Rander, A. Rosowsky, I. Shreyber, M. Titov, P. Verrecchia 21 Laboratoire Leprince-Ringuet, Ecole Polytechnique, IN2P3-CNRS, Palaiseau, France S. Baffioni, F. Beaudette, L. Bianchini, M. Bluj6, C. Broutin, P. Busson, C. Charlot, T. Dahms, L. Dobrzynski, R. Granier de Cassagnac, M. Haguenauer, P. Min´ e, C. Mironov, C. Ochando, P. Paganini, D. Sabes, R. Salerno, Y. Sirois, C. Thiebaux, B. Wyslouch7, A. Zabi Institut Pluridisciplinaire Hubert Curien, Universit´e de Strasbourg, Universit´e de Haute Alsace Mulhouse, CNRS/IN2P3, Strasbourg, France J.-L. Agram8, J. Andrea, A. Besson, D. Bloch, D. Bodin, J.-M. Brom, M. Cardaci, E.C. Chabert, C. Collard, E. Conte8, F. Drouhin8, C. Ferro, J.-C. Fontaine8, D. Gel´ e, U. Goerlach, S. Greder, P. Juillot, M. Karim8, A.-C. Le Bihan, Y. Mikami, P. Van Hove Centre de Calcul de l’Institut National de Physique Nucleaire et de Physique des Particules (IN2P3), Villeurbanne, France F. Fassi, D. Mercier Universit´e de Lyon, Universit´e Claude Bernard Lyon 1, CNRS-IN2P3, Institut de Physique Nucl´eaire de Lyon, Villeurbanne, France C. Baty, N. Beaupere, M. Bedjidian, O. Bondu, G. Boudoul, D. Boumediene, H. Brun, N. Chanon, R. Chierici, D. Contardo, P. Depasse, H. El Mamouni, A. Falkiewicz, J. Fay, S. Gascon, B. Ille, T. Kurca, T. Le Grand, M. Lethuillier, L. Mirabito, S. Perries, V. Sordini, S. Tosi, Y. Tschudi, P. Verdier, H. Xiao E. Andronikashvili Institute of Physics, Academy of Science, Tbilisi, Georgia L. Megrelidze, V. Roinishvili Institute of High Energy Physics and Informatization, Tbilisi State University, Tbilisi, Georgia D. Lomidze RWTH Aachen University, I. Physikalisches Institut, Aachen, Germany G. Anagnostou, M. Edelhoff, L. Feld, N. Heracleous, O. Hindrichs, R. Jussen, K. Klein, J. Merz, N. Mohr, A. Ostapchuk, A. Perieanu, F. Raupach, J. Sammet, S. Schael, D. Sprenger, H. Weber, M. Weber, B. Wittmer RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany M. Ata, W. Bender, M. Erdmann, J. Frangenheim, T. Hebbeker, A. Hinzmann, K. Hoepfner, C. Hof, T. Klimkovich, D. Klingebiel, P. Kreuzer, D. Lanske†, C. Magass, G. Masetti, M. Merschmeyer, A. Meyer, P. Papacz, H. Pieta, H. Reithler, S.A. Schmitz, L. Sonnenschein, J. Steggemann, D. Teyssier RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany M. Bontenackels, M. Davids, M. Duda, G. Fl¨ ugge, H. Geenen, M. Giffels, W. Haj Ahmad, D. Heydhausen, T. Kress, Y. Kuessel, A. Linn, A. Nowack, L. Perchalla, O. Pooth, J. Rennefeld, P. Sauerland, A. Stahl, M. Thomas, D. Tornier, M.H. Zoeller Deutsches Elektronen-Synchrotron, Hamburg, Germany M. Aldaya Martin, W. Behrenhoff, U. Behrens, M. Bergholz9, K. Borras, A. Cakir, A. Campbell, E. Castro, D. Dammann, G. Eckerlin, D. Eckstein, A. Flossdorf, G. Flucke, A. Geiser, I. Glushkov, J. Hauk, H. Jung, M. Kasemann, I. Katkov, P. Katsas, C. Kleinwort, H. Kluge, A. Knutsson, D. Kr¨ ucker, E. Kuznetsova, W. Lange, W. Lohmann9, R. Mankel, M. Marienfeld, I.-A. MelzerPellmann, A.B. Meyer, J. Mnich, A. Mussgiller, J. Olzem, A. Parenti, A. Raspereza, A. Raval, R. Schmidt9, T. Schoerner-Sadenius, N. Sen, M. Stein, J. Tomaszewska, D. Volyanskyy, R. Walsh, C. Wissing 22 A The CMS Collaboration University of Hamburg, Hamburg, Germany C. Autermann, S. Bobrovskyi, J. Draeger, H. Enderle, U. Gebbert, K. Kaschube, G. Kaussen, R. Klanner, J. Lange, B. Mura, S. Naumann-Emme, F. Nowak, N. Pietsch, C. Sander, H. Schettler, P. Schleper, M. Schr¨ oder, T. Schum, J. Schwandt, A.K. Srivastava, H. Stadie, G. Steinbr¨ uck, J. Thomsen, R. Wolf Institut f¨ur Experimentelle Kernphysik, Karlsruhe, Germany C. Barth, J. Bauer, V. Buege, T. Chwalek, W. De Boer, A. Dierlamm, G. Dirkes, M. Feindt, J. Gruschke, C. Hackstein, F. Hartmann, S.M. Heindl, M. Heinrich, H. Held, K.H. Hoffmann, S. Honc, T. Kuhr, D. Martschei, S. Mueller, Th. M¨ uller, M. Niegel, O. Oberst, A. Oehler, J. Ott, T. Peiffer, D. Piparo, G. Quast, K. Rabbertz, F. Ratnikov, M. Renz, C. Saout, A. Scheurer, P. Schieferdecker, F.-P. Schilling, G. Schott, H.J. Simonis, F.M. Stober, D. Troendle, J. WagnerKuhr, M. Zeise, V. Zhukov10, E.B. Ziebarth Institute of Nuclear Physics ”Demokritos”, Aghia Paraskevi, Greece G. Daskalakis, T. Geralis, S. Kesisoglou, A. Kyriakis, D. Loukas, I. Manolakos, A. Markou, C. Markou, C. Mavrommatis, E. Ntomari, E. Petrakou University of Athens, Athens, Greece L. Gouskos, T.J. Mertzimekis, A. Panagiotou University of Io´annina, Io´annina, Greece I. Evangelou, C. Foudas, P. Kokkas, N. Manthos, I. Papadopoulos, V. Patras, F.A. Triantis KFKI Research Institute for Particle and Nuclear Physics, Budapest, Hungary A. Aranyi, G. Bencze, L. Boldizsar, G. Debreczeni, C. Hajdu1, D. Horvath11, A. Kapusi, K. Krajczar12, A. Laszlo, F. Sikler, G. Vesztergombi12 Institute of Nuclear Research ATOMKI, Debrecen, Hungary N. Beni, J. Molnar, J. Palinkas, Z. Szillasi, V. Veszpremi University of Debrecen, Debrecen, Hungary P. Raics, Z.L. Trocsanyi, B. Ujvari Panjab University, Chandigarh, India S. Bansal, S.B. Beri, V. Bhatnagar, N. Dhingra, R. Gupta, M. Jindal, M. Kaur, J.M. Kohli, M.Z. Mehta, N. Nishu, L.K. Saini, A. Sharma, A.P. Singh, J.B. Singh, S.P. Singh University of Delhi, Delhi, India S. Ahuja, S. Bhattacharya, B.C. Choudhary, P. Gupta, S. Jain, S. Jain, A. Kumar, R.K. Shivpuri Bhabha Atomic Research Centre, Mumbai, India R.K. Choudhury, D. Dutta, S. Kailas, S.K. Kataria, A.K. Mohanty1, L.M. Pant, P. Shukla Tata Institute of Fundamental Research - EHEP, Mumbai, India T. Aziz, M. Guchait13, A. Gurtu, M. Maity14, D. Majumder, G. Majumder, K. Mazumdar, G.B. Mohanty, A. Saha, K. Sudhakar, N. Wickramage Tata Institute of Fundamental Research - HECR, Mumbai, India S. Banerjee, S. Dugad, N.K. Mondal Institute for Research and Fundamental Sciences (IPM), Tehran, Iran H. Arfaei, H. Bakhshiansohi, S.M. Etesami, A. Fahim, M. Hashemi, A. Jafari, M. Khakzad, A. Mohammadi, M. Mohammadi Najafabadi, S. Paktinat Mehdiabadi, B. Safarzadeh, M. Zeinali 23 INFN Sezione di Bari a, Universit`a di Bari b, Politecnico di Bari c, Bari, Italy M. Abbresciaa,b, L. Barbonea,b, C. Calabriaa,b, A. Colaleoa, D. Creanzaa,c, N. De Filippisa,c, M. De Palmaa,b, A. Dimitrova, L. Fiorea, G. Iasellia,c, L. Lusitoa,b,1, G. Maggia,c, M. Maggia, N. Mannaa,b, B. Marangellia,b, S. Mya,c, S. Nuzzoa,b, N. Pacificoa,b, G.A. Pierroa, A. Pompilia,b, G. Pugliesea,c, F. Romanoa,c, G. Rosellia,b, G. Selvaggia,b, L. Silvestrisa, R. Trentaduea, S. Tupputia,b, G. Zitoa INFN Sezione di Bologna a, Universit`a di Bologna b, Bologna, Italy G. Abbiendia, A.C. Benvenutia, D. Bonacorsia, S. Braibant-Giacomellia,b, L. Brigliadoria, P. Capiluppia,b, A. Castroa,b, F.R. Cavalloa, M. Cuffiania,b, G.M. Dallavallea, F. Fabbria, A. Fanfania,b, D. Fasanellaa, P. Giacomellia, M. Giuntaa, C. Grandia, S. Marcellinia, M. Meneghellia,b, A. Montanaria, F.L. Navarriaa,b, F. Odoricia, A. Perrottaa, F. Primaveraa, A.M. Rossia,b, T. Rovellia,b, G. Sirolia,b, R. Travaglinia,b INFN Sezione di Catania a, Universit`a di Catania b, Catania, Italy S. Albergoa,b, G. Cappelloa,b, M. Chiorbolia,b,1, S. Costaa,b, A. Tricomia,b, C. Tuvea INFN Sezione di Firenze a, Universit`a di Firenze b, Firenze, Italy G. Barbaglia, V. Ciullia,b, C. Civininia, R. D’Alessandroa,b, E. Focardia,b, S. Frosalia,b, E. Galloa, S. Gonzia,b, P. Lenzia,b, M. Meschinia, S. Paolettia, G. Sguazzonia, A. Tropianoa,1 INFN Laboratori Nazionali di Frascati, Frascati, Italy L. Benussi, S. Bianco, S. Colafranceschi15, F. Fabbri, D. Piccolo INFN Sezione di Genova, Genova, Italy P. Fabbricatore, R. Musenich INFN Sezione di Milano-Biccoca a, Universit`a di Milano-Bicocca b, Milano, Italy A. Benagliaa,b, F. De Guioa,b,1, L. Di Matteoa,b, A. Ghezzia,b,1, M. Malbertia,b, S. Malvezzia, A. Martellia,b, A. Massironia,b, D. Menascea, L. Moronia, M. Paganonia,b, D. Pedrinia, S. Ragazzia,b, N. Redaellia, S. Salaa, T. Tabarelli de Fatisa,b, V. Tancinia,b INFN Sezione di Napoli a, Universit`a di Napoli ”Federico II” b, Napoli, Italy S. Buontempoa, C.A. Carrillo Montoyaa, A. Cimminoa,b, A. De Cosaa,b, M. De Gruttolaa,b, F. Fabozzia,16, A.O.M. Iorioa, L. Listaa, M. Merolaa,b, P. Nolia,b, P. Paoluccia INFN Sezione di Padova a, Universit`a di Padova b, Universit`a di Trento (Trento) c, Padova, Italy P. Azzia, N. Bacchettaa, P. Bellana,b, A. Brancaa, R. Carlina,b, P. Checchiaa, M. De Mattiaa,b, T. Dorigoa, U. Dossellia, F. Gasparinia,b, U. Gasparinia,b, P. Giubilatoa,b, A. Greselea,c, A. Kaminskiya,b, S. Lacapraraa,17, I. Lazzizzeraa,c, M. Margonia,b, M. Mazzucatoa, A.T. Meneguzzoa,b, M. Nespoloa,1, M. Passaseoa, L. Perrozzia,1, N. Pozzobona,b, P. Ronchesea,b, F. Simonettoa,b, E. Torassaa, M. Tosia,b, A. Triossia, S. Vaninia,b, G. Zumerlea,b INFN Sezione di Pavia a, Universit`a di Pavia b, Pavia, Italy U. Berzanoa, C. Riccardia,b, P. Torrea,b, P. Vituloa,b INFN Sezione di Perugia a, Universit`a di Perugia b, Perugia, Italy M. Biasinia,b, G.M. Bileia, B. Caponeria,b, L. Fan` oa,b, P. Laricciaa,b, A. Lucaronia,b,1, G. Mantovania,b, M. Menichellia, A. Nappia,b, A. Santocchiaa,b, L. Servolia, S. Taronia,b, M. Valdataa,b, R. Volpea,b,1 INFN Sezione di Pisa a, Universit`a di Pisa b, Scuola Normale Superiore di Pisa c, Pisa, Italy P. Azzurria,c, G. Bagliesia, J. Bernardinia,b, T. Boccalia,1, G. Broccoloa,c, R. Castaldia, R.T. D’Agnoloa,c, R. Dell’Orsoa, F. Fioria,b, L. Fo` aa,c, A. Giassia, A. Kraana, F. Ligabuea,c, 24 A The CMS Collaboration T. Lomtadzea, L. Martinia,18, A. Messineoa,b, F. Pallaa, F. Palmonaria, S. Sarkara,c, G. Segneria, A.T. Serbana, P. Spagnoloa, R. Tenchinia, G. Tonellia,b,1, A. Venturia,1, P.G. Verdinia INFN Sezione di Roma a, Universit`a di Roma ”La Sapienza” b, Roma, Italy L. Baronea,b, F. Cavallaria, D. Del Rea,b, E. Di Marcoa,b, M. Diemoza, D. Francia,b, M. Grassia, E. Longoa,b, S. Nourbakhsha, G. Organtinia,b, A. Palmaa,b, F. Pandolfia,b,1, R. Paramattia, S. Rahatloua,b INFN Sezione di Torino a, Universit`a di Torino b, Universit`a del Piemonte Orientale (Novara) c, Torino, Italy N. Amapanea,b, R. Arcidiaconoa,c, S. Argiroa,b, M. Arneodoa,c, C. Biinoa, C. Bottaa,b,1, N. Cartigliaa, R. Castelloa,b, M. Costaa,b, N. Demariaa, A. Grazianoa,b,1, C. Mariottia, M. Maronea,b, S. Masellia, E. Migliorea,b, G. Milaa,b, V. Monacoa,b, M. Musicha,b, M.M. Obertinoa,c, N. Pastronea, M. Pelliccionia,b,1, A. Romeroa,b, M. Ruspaa,c, R. Sacchia,b, V. Solaa,b, A. Solanoa,b, A. Staianoa, D. Trocinoa,b, A. Vilela Pereiraa,b,1 INFN Sezione di Trieste a, Universit`a di Trieste b, Trieste, Italy S. Belfortea, F. Cossuttia, G. Della Riccaa,b, B. Gobboa, D. Montaninoa,b, A. Penzoa Kangwon National University, Chunchon, Korea S.G. Heo Kyungpook National University, Daegu, Korea S. Chang, J. Chung, D.H. Kim, G.N. Kim, J.E. Kim, D.J. Kong, H. Park, D. Son, D.C. Son Chonnam National University, Institute for Universe and Elementary Particles, Kwangju, Korea Zero Kim, J.Y. Kim, S. Song Korea University, Seoul, Korea S. Choi, B. Hong, M. Jo, H. Kim, J.H. Kim, T.J. Kim, K.S. Lee, D.H. Moon, S.K. Park, H.B. Rhee, E. Seo, S. Shin, K.S. Sim University of Seoul, Seoul, Korea M. Choi, S. Kang, H. Kim, C. Park, I.C. Park, S. Park, G. Ryu Sungkyunkwan University, Suwon, Korea Y. Choi, Y.K. Choi, J. Goh, J. Lee, S. Lee, H. Seo, I. Yu Vilnius University, Vilnius, Lithuania M.J. Bilinskas, I. Grigelionis, M. Janulis, D. Martisiute, P. Petrov, T. Sabonis Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico H. Castilla-Valdez, E. De La Cruz-Burelo, R. Lopez-Fernandez, A. S´ anchez-Hern´ andez, L.M. Villasenor-Cendejas Universidad Iberoamericana, Mexico City, Mexico S. Carrillo Moreno, F. Vazquez Valencia Benemerita Universidad Autonoma de Puebla, Puebla, Mexico H.A. Salazar Ibarguen Universidad Aut´onoma de San Luis Potos´ı, San Luis Potos´ı, Mexico E. Casimiro Linares, A. Morelos Pineda, M.A. Reyes-Santos University of Auckland, Auckland, New Zealand P. Allfrey, D. Krofcheck 31 Rice University, Houston, USA C. Boulahouache, V. Cuplov, K.M. Ecklund, F.J.M. Geurts, J.H. Liu, B.P. Padley, R. Redjimi, J. Roberts, J. Zabel University of Rochester, Rochester, USA B. Betchart, A. Bodek, Y.S. Chung, R. Covarelli, P. de Barbaro, R. Demina, Y. Eshaq, H. Flacher, A. Garcia-Bellido, P. Goldenzweig, Y. Gotra, J. Han, A. Harel, D.C. Miner, D. Orbaker, G. Petrillo, D. Vishnevskiy, M. Zielinski The Rockefeller University, New York, USA A. Bhatti, R. Ciesielski, L. Demortier, K. Goulianos, G. Lungu, C. Mesropian, M. Yan Rutgers, the State University of New Jersey, Piscataway, USA O. Atramentov, A. Barker, D. Duggan, Y. Gershtein, R. Gray, E. Halkiadakis, D. Hidas, D. Hits, A. Lath, S. Panwalkar, R. Patel, A. Richards, K. Rose, S. Schnetzer, S. Somalwar, R. Stone, S. Thomas University of Tennessee, Knoxville, USA G. Cerizza, M. Hollingsworth, S. Spanier, Z.C. Yang, A. York Texas A&M University, College Station, USA J. Asaadi, R. Eusebi, J. Gilmore, A. Gurrola, T. Kamon, V. Khotilovich, R. Montalvo, C.N. Nguyen, I. Osipenkov, J. Pivarski, A. Safonov, S. Sengupta, A. Tatarinov, D. Toback, M. Weinberger Texas Tech University, Lubbock, USA N. Akchurin, J. Damgov, C. Jeong, K. Kovitanggoon, S.W. Lee, Y. Roh, A. Sill, I. Volobouev, R. Wigmans, E. Yazgan Vanderbilt University, Nashville, USA E. Appelt, E. Brownson, D. Engh, C. Florez, W. Gabella, W. Johns, P. Kurt, C. Maguire, A. Melo, P. Sheldon, S. Tuo, J. Velkovska University of Virginia, Charlottesville, USA M.W. Arenton, M. Balazs, S. Boutle, M. Buehler, S. Conetti, B. Cox, B. Francis, R. Hirosky, A. Ledovskoy, C. Lin, C. Neu, R. Yohay Wayne State University, Detroit, USA S. Gollapinni, R. Harr, P.E. Karchin, P. Lamichhane, M. Mattson, C. Milst` ene, A. Sakharov University of Wisconsin, Madison, USA M. Anderson, M. Bachtis, J.N. Bellinger, D. Carlsmith, S. Dasu, J. Efron, L. Gray, K.S. Grogg, M. Grothe, R. Hall-Wilton1, M. Herndon, P. Klabbers, J. Klukas, A. Lanaro, C. Lazaridis, J. Leonard, R. Loveless, A. Mohapatra, D. Reeder, I. Ross, A. Savin, W.H. Smith, J. Swanson, M. Weinberg †: Deceased 1: Also at CERN, European Organization for Nuclear Research, Geneva, Switzerland 2: Also at Universidade Federal do ABC, Santo Andre, Brazil 3: Also at Laboratoire Leprince-Ringuet, Ecole Polytechnique, IN2P3-CNRS, Palaiseau, France 4: Also at Suez Canal University, Suez, Egypt 5: Also at Fayoum University, El-Fayoum, Egypt 6: Also at Soltan Institute for Nuclear Studies, Warsaw, Poland 7: Also at Massachusetts Institute of Technology, Cambridge, USA 8: Also at Universit´ e de Haute-Alsace, Mulhouse, France 32 A The CMS Collaboration 9: Also at Brandenburg University of Technology, Cottbus, Germany 10: Also at Moscow State University, Moscow, Russia 11: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary 12: Also at E¨ otv¨ os Lor´ and University, Budapest, Hungary 13: Also at Tata Institute of Fundamental Research - HECR, Mumbai, India 14: Also at University of Visva-Bharati, Santiniketan, India 15: Also at Facolt` a Ingegneria Universit` a di Roma ”La Sapienza”, Roma, Italy 16: Also at Universit` a della Basilicata, Potenza, Italy 17: Also at Laboratori Nazionali di Legnaro dell’ INFN, Legnaro, Italy 18: Also at Universit` a degli studi di Siena, Siena, Italy 19: Also at California Institute of Technology, Pasadena, USA 20: Also at Faculty of Physics of University of Belgrade, Belgrade, Serbia 21: Also at University of California, Los Angeles, Los Angeles, USA 22: Also at University of Florida, Gainesville, USA 23: Also at Universit´ e de Gen` eve, Geneva, Switzerland 24: Also at Scuola Normale e Sezione dell’ INFN, Pisa, Italy 25: Also at INFN Sezione di Roma; Universit` a di Roma ”La Sapienza”, Roma, Italy 26: Also at University of Athens, Athens, Greece 27: Also at The University of Kansas, Lawrence, USA 28: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia 29: Also at Paul Scherrer Institut, Villigen, Switzerland 30: Also at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia 31: Also at Gaziosmanpasa University, Tokat, Turkey 32: Also at Adiyaman University, Adiyaman, Turkey 33: Also at Mersin University, Mersin, Turkey 34: Also at Izmir Institute of Technology, Izmir, Turkey 35: Also at Kafkas University, Kars, Turkey 36: Also at Suleyman Demirel University, Isparta, Turkey 37: Also at Ege University, Izmir, Turkey 38: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom 39: Also at INFN Sezione di Perugia; Universit` a di Perugia, Perugia, Italy 40: Also at Institute for Nuclear Research, Moscow, Russia 41: Also at Horia Hulubei National Institute of Physics and Nuclear Engineering (IFIN-HH), Bucharest, Romania 42: Also at Istanbul Technical University, Istanbul, Turkey