Charged particle multiplicities in pp interactions at root{s}=0.9, 2.36, and 7 TeV

EUROPEAN ORGANIZATION FOR NUCLEAR RESEARCH (CERN) CERN-PH-EP/1020-048 2010/11/29 CMS-QCD-10-004 Charged particle multiplicities in pp interactions at √s=0.9, 2.36, and 7 TeV The CMS Collaboration∗ Abstract Measurements of primary charged hadron multiplicity distributions are presented for non-single-diffractive events in proton-proton collisions at centre-of-mass energies of √s=0.9, 2.36, and 7 TeV, in five pseudorapidity ranges from |η|<0.5 to |η|<2.4. The data were collected with the minimum-bias trigger of the CMS experiment during the LHC commissioning runs in 2009 and the 7 TeV run in 2010. The multiplicity distribution at √s=0.9 TeV is in agreement with previous measurements. At higher energies the increase of the mean multiplicity with √sis underestimated by most event generators. The average transverse momentum as a function of the multiplicity is also presented. The measurement of higher-order moments of the multiplicity distribution confirms the violation of Koba-Nielsen-Olesen scaling that has been observed at lower energies. Submitted to the Journal of High Energy Physics (JHEP) ∗See Appendix A for the list of collaboration members arXiv:1011.5531v1 [hep-ex] 24 Nov 2010 1 1 Introduction The charged hadron multiplicity, or number of primary charged hadrons, n, is a basic global observable characterising final states in high-energy-collision processes. The multiplicity distribution, Pn, is the probability to produce ncharged hadrons in an event, either in full phase space or in restricted phase space domains. In this paper we report measurements of Pnin nonsingle-diffractive [1] proton-proton collisions, at centre-of-mass energies √s=0.9, 2.36, and 7 TeV at the Large Hadron Collider (LHC) [2]. The measurements are based on events recorded by the Compact Muon Solenoid (CMS) [3] experiment, using a minimum-bias trigger. Energy-momentum and charge conservation significantly influence the multiplicity distribution for the full phase space. The distribution in restricted phase space, which is less affected by such constraints, is expected to be a more sensitive probe of the underlying dynamics and can be used to better constrain phenomenological models. Comprehensive reviews on the subject can be found in [1, 4, 5]. The measurements described in this paper are performed for intervals of increasing extent in pseudorapidity from |η|<0.5 up to |η|<2.4, where ηis defined as −ln[tan(θ/2)], and θis the polar angle of the particle with respect to the counterclockwise beam direction. In these measurements primary charged hadrons are defined as all charged hadrons produced in the interaction, including the products of strong and electromagnetic decays, but excluding products of weak decays and hadrons originating from secondary interactions. Independent emission of single particles yields a Poissonian Pn. Deviations from this shape, therefore, reveal correlations. These correlations are predominantly short range in rapidity, attributed to cluster decays, and reflect local conservation of quantum numbers in the hadronisation process. In hadron-hadron interactions, additional large long-range rapidity correlations are observed, whose magnitude increases with √s[6]. In contrast, in e+e−annihilations such long-range correlations are much weaker and practically absent in twoand three-jet event samples [7]. The mean of the multiplicity distribution, hni, is equal to the integral of the inclusive singleparticle density in the considered phase-space domain. Higher-order moments of Pnmeasure event-to-event multiplicity fluctuations. They are related to the two-particle and higher-order inclusive density correlations and provide more detailed dynamical information than that contained in single-particle inclusive spectra [8–12]. The average transverse momentum of the charged particles, hpTi, exhibits a positive correlation with the event multiplicity in hadronhadron collisions ([13–19] and references therein). Traditionally, the sdependence of Pnand its moments has been much discussed [1, 4, 5] in relation to Koba-Nielsen-Olesen (KNO) scaling [20, 21]. In this framework, one studies the KNO function Ψ(z) = hniPn, where z=n/hni. If KNO scaling holds, Ψ(z)and the normalised moments Cq=hnqi/hniqare independent of s. Throughout this paper, we compare the data with existing measurements at similar or lower centre-of-mass energies and with predictions of the multiplicity distribution and its mean value from analytical and event generator Monte Carlo (MC) models. The models are based on the assumption that hadrons are produced via the fragmentation of colour strings. This comparison should allow for a better tuning of the existing MC models to accurately simulate minimumbias events and underlying-event effects. The next section gives a short description of the CMS detector. Section 3 describes the MC models used in the analysis, while Section 4 presents the data samples. The track reconstruction and acceptance are explained in Section 5. Section 6 describes the corrections applied to the data. Section 7 lists all relevant systematic uncertainties. The results are discussed in Section 8. 23 Models 2 The CMS detector A complete description of the CMS detector can be found in [3]. The CMS experiment uses a right-handed coordinate system, with the origin at the nominal interaction point (IP), the x axis pointing to the centre of the LHC ring, the yaxis pointing up, and the zaxis along the counterclockwise beam direction. The central feature of the CMS detector is a superconducting solenoid of 6 m internal diameter, providing an axial magnetic field with nominal strength of 3.8 T. Immersed in the magnetic field are the pixel tracker, the silicon-strip tracker (SST), the lead tungstate electromagnetic calorimeter, the brass/scintillator hadron calorimeter and the muon detection system. In addition to the barrel and endcap calorimeters, the steel/quartz-fibre forward calorimeter (HF) covers the region 2.9 <|η|<5.2. Two of the CMS subdetectors acting as LHC beam monitors, the Beam Scintillation Counters (BSC) and the Beam Pick-up Timing for the eXperiments (BPTX) devices, were used to trigger the detector readout. The BSCs are located along the beam line on each side of the IP at a distance of 10.86 m and are sensitive in the range 3.23 <|η|<4.65. The two BPTX devices, which are located inside the beam pipe at distances of 175 m from the IP, are designed to provide precise information on the bunch structure and timing of the incoming beams, with a time resolution better than 0.2 ns. The tracking detector consists of 1440 silicon-pixel and 15148 silicon-strip detector modules. The barrel part consists of 3 (10) layers of pixel (SST) modules around the IP at distances ranging from 4.4 cm to 1.1 m. Five out of the 10 strip layers are double sided and provide additional zcoordinate measurements. The two endcaps consist of 2 (12) disks of pixel (SST) modules that extend the pseudorapidity acceptance to |η|<2.5. The tracker provides an impact parameter resolution of about 100 µm and a pTresolution of about 0.7% for 1 GeV/ccharged particles at normal incidence [22, 23]. 3 Models The PYTHIA 6 [24] generator and its fragmentation model tuned to CDF data [25, 26], hereafter called PYTHIA D6T, is used as a baseline model to simulate inelastic pp collisions. However, at 7 TeV a dedicated PYTHIA tune [27] describing better the high multiplicities is used for correcting the data. Alternative tunings that differ mainly in the modelling of multiple parton interactions have also been considered [26, 28, 29]. PHOJET [30, 31] is used as an alternative event generator that differs mainly in the underlying dynamical model for particle production. While PYTHIA contains at least one hard scatter per event, particle production in PHOJET, which is based on the dual-parton model [32], is predominantly soft and contains in general multiplestring configurations derived from the dual-parton model with multi-Pomeron exchanges [32]. Each Pomeron exchange gives rise to two strings stretched between either valence or sea partons. At low energies the dominant process is single-Pomeron exchange, which leads to two strings stretched between valence quarks and diquarks. With increasing energy, additional Pomeron exchanges occur, forming strings stretched between sea partons. Because the sea partons carry on average only a small fraction of the momentum of the incident hadrons, these strings are concentrated in the central rapidity region. These extra strings [33, 34] are needed to explain the KNO scaling violations observed at high energies [35, 36], the increase of the central particle density with increasing energy [35–37], the hpTiversus ndependence [38, 39], and long-range rapidity correlations [40]. The distribution of the number of exchanged Pomerons can be obtained from perturbative Reggeon calculus and unitarity, by means of fits to the mea- 3 sured total, elastic, and diffractive cross sections as described in [41–43]. Other alternatives based on the Colour Glass Condensate (CGC) picture with saturated gluons [44] also make predictions for the multiplicity dependence of hpTiand for the long-range rapidity correlations. We also compare our measurements with a new fragmentation model implemented in PYTHIA 8 [45]. In addition to having pT-ordered parton showers, rather than an ordering by virtuality, it differs from its predecessor in the modelling of multiple-parton interactions and the treatment of beam remnants and diffraction. The detailed MC simulation of the CMS detector response is based on GEANT4 [46]. Simulated events were processed and reconstructed in the same manner as collision data. 4 Data sample Near the end of 2009, the CMS experiment collected two datasets of proton-proton collisions at centre-of-mass energies of 0.9 and 2.36 TeV. In March 2010 a new running period at √s=7 TeV started, of which data collected in the first days have been analysed for this paper. The corresponding inelastic proton-proton interaction rates were about 11, 3, and 50 Hz, respectively, for these datasets. At these rates, the fraction of bunch crossings in which two or more minimumbias collisions occurred is negligible [47, 48]. Diffraction is commonly characterised by one (single-diffraction) or two (double-diffraction) colourless exchanges resulting in the observation of a large rapidity interval devoid of any hadron activity (rapidity gap). All results presented in this paper refer to inelastic non-singlediffractive (NSD) interactions and are based on an event selection that retains a large fraction of the non-diffractive (ND) and double-diffractive (DD) events, while disfavouring singlediffractive (SD) events. The trigger and offline event selection are nearly identical to those used in [47, 48]; about three times more events were used in this analysis at √s=0.9 and 7 TeV. The trigger required a signal in any of the BSC scintillator counters, in coincidence with either of the two BPTX devices indicating the presence of at least one proton bunch crossing the IP. Beam halo backgrounds are reduced by using the timing information from the BSC counters at opposite ends of the CMS detector. Additional beam-induced backgrounds are removed by requiring the cluster sizes in the pixel detector to be consistent with a single primary vertex, as described in [47]. NSD events are selected by requiring at least one HF calorimeter tower with more than 3 GeV of total energy in each of the positive-zand negative-zHF calorimeters. Finally, a reconstructed primary vertex is required with the zcoordinate within ±15 cm of the centre of the beam collision region. For the final analysis, totals of about 132, 12, and 442 thousand events were retained at √s= 0.9, 2.36, and 7 TeV, respectively. Event yields at various stages of the selection are shown in Table 1. 5 Track reconstruction and acceptance definition The barrel and endcap pixel and SST detectors are used in the reconstruction of tracks within an acceptance of |η|<2.5. Due to a large drop in reconstruction efficiency near the limits of this range, we restrict the computation of the multiplicity spectra to the region |η|<2.4. In proton-proton collisions at the LHC, the events selected by minimum-bias triggers involve predominantly soft interactions and contain mostly particles with small transverse momenta. 45 Track reconstruction and acceptance definition Table 1: Event yields in each data sample after sequential trigger and event selection. Selection √s(TeV) 0.9 2.36 7 beam background rejection + L1 trigger 254666 18739 610549 all preceding + forward calorimeters 146658 12019 500077 all preceding + primary vertex 132294 11674 441924 These are reconstructed by extending the standard tracking algorithms of the CMS experiment, which are based on a combinatorial track finder [22] that performs multiple iterations. Hits that can be assigned unambiguously to tracks in one iteration are removed from the collection of tracker hits to create a smaller collection that can be used in the subsequent iteration. This iterative procedure was further optimised for primary track reconstruction with pT≥100 MeV/c in minimum-bias events [47]. The reconstruction efficiency, estimated by means of the detector simulation, exceeds 90% for tracks with pT>500 MeV/cand drops below 70% for tracks with pT<100 MeV/c. Contamination from mis-reconstructed tracks is below 5% for pT<500 MeV/c. After three iterations of the combinatorial track finder, the position of the primary vertex is recomputed and then used as an additional constraint in a refit of all previously reconstructed tracks, thus improving the overall resolution in ηand pT. An agglomerative clustering algorithm followed by a Gaussian mixture model [49] were applied in order to optimise the vertex-finding efficiency. The contamination due to decays of long-lived particles (denoted as V0decays) is dominated by charged pions and protons originating from K0 Sand Λdecays. The K0 Sproduction rate is roughly 5% of that for all charged particles [50], and the resulting charged secondaries amount to 7% of all π±. The Λproduction is measured to be 43% of K0 S[51, 52] in this kinematic domain, yielding another 3% of charged secondaries consisting of protons and pions. In order to reduce the contamination of these V0decay products and secondaries produced in interactions of charged particles with the material of the detector, we require all reconstructed tracks to be associated with the primary vertex. This is done by selecting tracks with a small impact parameter with respect to the primary vertex position both in the transverse plane and along the zaxis [47]. Only 1.5% of K0 Sand Λdecay products pass these selections, resulting in a final contamination of 0.2%. The K±/π±ratio is known to be fairly constant over a wide range of centre-of-mass energies and is between 8 and 12% [50]. The K±have a lower reconstruction efficiency at low pTthan pions and mismodeling of the K±/π±ratio could result in a change in the multiplicity distribution. However a doubling of the K±/π±ratio yields a negligible shift of 0.25% in the multiplicity average. This is expected because the hpTiof K±is substantially higher than π±, and K±therefore contribute very little in the pTrange where the reconstruction efficiencies differ. Finally, only tracks with a relative uncertainty on their measured transverse momentum smaller than 10% are selected; this requirement rejects mainly low-quality and badly reconstructed tracks. 5 Table 2: The percentage of single-diffractive events (SD/inelastic) at each centre-of-mass energy as predicted by PYTHIA D6Tand PHOJET. Generator √s(TeV) 0.9 2.36 7 PYTHIA D6T22.5 21.0 19.2 PHOJET 18.9 16.2 13.8 6 Corrections Due to the requirement of significant activity in both ends of the HF, the event selection acceptance for SD events is small: 5% at 0.9 TeV and 7% at 7 TeV. This contribution is therefore subtracted based on simulated PYTHIA events. The PYTHIA and PHOJET predictions of the initial fractions of SD events differ substantially, as seen from Table 2. The difference of the two predictions is taken as the systematic uncertainty related to the SD subtraction. It is customary to normalise the charged hadron multiplicity distribution Pn=σn/σ, where σndenotes the cross section for a fixed multiplicity n, to either the total inelastic cross section or the NSD cross section. For the results presented in this paper the normalisation factor σ corresponds to the latter. The minimum-bias trigger and NSD selection unavoidably introduce a bias in the measured charged hadron multiplicity. Furthermore, a fraction of the events are removed by the requirement of a good quality primary vertex. These effects result in an accepted multiplicity given by Tn=en·Pn, (1) where enis the trigger and event reconstruction efficiency for multiplicity n. This efficiency is close to 100% for multiplicities larger than n=20 and drops gradually to 40% for n=1. Due to inefficiencies in track reconstruction and acceptance, the creation of secondary particles by the interaction of primaries with the beam pipe and the detector material, and the presence of decay products of long-lived hadrons, one will in general not measure the true multiplicity nbut a statistically related quantity m. The statistical distribution Omof this observed multiplicity is related to the true accepted multiplicity distribution by the linear relation Om=∑ n Rm,n·Tn. (2) The problem of inverting the response matrix Rm,n, here taken from MC, is well known and extensive literature on the topic exists [53, 54]. When dealing with limited event samples, an algebraic inversion of Rm,nturns out to be impossible and leads to unstable results. We therefore use a Bayesian unfolding method, as described in [55]. The unfolding procedure introduces large statistical correlations between adjacent bins of the multiplicity spectrum. The full covariance matrix of the unfolded multiplicity spectrum was calculated using a resampling technique [54]. The average transverse momentum hpTias a function of nwas measured as well. For each bin in raw multiplicity, a Monte Carlo based correction factor hpgen Ti/hprec Tiwas applied to convert the measured hpTito the corresponding value for primary charged hadrons. Subsequently, the response matrix Rm,n, weighted by the corrected data, was applied to correct the multiplicities. The correctness of the unfolding procedure was verified using MC events generated with our 67 Systematic uncertainties baseline PYTHIA D6Ttune where we compared the multiplicity distribution of generated primary hadrons with that of reconstructed tracks after unfolding. At all energies considered, an excellent agreement with the generated hadrons is achieved, proving the stability of the procedure. The track reconstruction efficiency of the minimum-bias tracking drops drastically for pT< 100 MeV/c, while the mis-reconstructed track rate increases. Rather than correcting for these effects using MC simulations, we reconstruct the pTspectrum in data themselves and calculate the fraction of charged hadrons with pT<100 MeV/cby extrapolating the measured spectrum in data, using a parametrisation based on an exponential of a third-degree polynomial in pT. The fraction of charged hadrons added by this correction ranges between 5% and 7% depending on the centre-of-mass energy and the pseudorapidity interval under study. The functional form used to extrapolate to the lowest transverse momenta introduces an uncertainty of 1% on this fraction and is taken into account in the systematic uncertainties. The effect of all the correction procedures on the measured raw multiplicity distribution is illustrated in Fig. 1 for a centre-of-mass energy of 7 TeV. n 0 20 40 60 80 100 120 140 160 Events / bin width 0 5000 10000 15000 20000 Before Corrections After Corrections | < 2.4η| CMS NSD 7 TeV Figure 1: A comparison of the uncorrected and fully corrected multiplicity distribution at √s=7 TeV for |η|<2.4 . The uncertainties before corrections are statistical only, while after corrections the statistical and systematic uncertainties are added in quadrature. 7 Systematic uncertainties Four main sources of systematic uncertainty contribute to the total uncertainty on the multiplicity distribution Pnand hpTiversus n: the uncertainty on the trigger and event selection efficiency, the uncertainty on the tracking efficiency and acceptance, the model dependence of the response matrix, and the model dependent SD subtraction. All four are discussed below. The effects of misalignment of the tracking detector, dead sensors, and the uncertainty on the vertex position are much smaller and are contained within the overall tracking systematic uncertainty. For hpTiversus n, the effect of the event selection and SD subtraction was observed to be negligible. 7 Table 3: Summary of systematic uncertainties on the track reconstruction. Source tracking uncertainty (%) Tracking efficiency 2.0 Acceptance 1.0 Pixel hit efficiency 0.3 Pixel cluster splitting 0.2 Correction for secondaries 1.0 Misalignment 0.1 Beam halo 0.1 Multiple track counting 0.1 Mis-reconstructed tracks 0.5 Total 2.5 Trigger and event selection efficiency. The corrections for the trigger and event selection efficiency are based entirely on MC simulation. The largest impact on the overall efficiency is that of the HF coincidence requirement. A cross-check of the multiplicity dependent efficiency with zero-bias events, which are by definition not biased at all (random trigger on collisions), shows good agreement within statistical errors between data and MC. A relative shift of the efficiency correction factors by +5% −7% for low multiplicities, decreasing to ±1% for n∼20, covers the trigger efficiency measured in zero-bias data. This leads to a maximum 5% systematic uncertainty. Tracking efficiency and acceptance. A correct description of the tracking efficiency in the MC simulation of the detector is essential for obtaining a correct response matrix. At low transverse momenta, the efficiency drops due to a loss of hits on the tracks that are stopped within the tracking volume. As in [47], we assign a 2% uncertainty on this efficiency. The remaining contamination is mostly due to secondary tracks originating from interactions with the material of the LHC beam pipe around the interaction point. This is estimated in [47] to be no more than 1%, and is confirmed based on [56]. These uncertainties, together with smaller contributions from misalignment of the tracking detector, beam-halo background, multiple counting of tracks, and mis-reconstructed tracks are added in quadrature to produce a total tracking uncertainty of 2.5%. All correction factors related to track reconstruction are summarised in Table 3. As was discussed in Section 5, the contamination from V0decays after associating tracks with the primary vertex is small (0.2%) and already included in the systematic uncertainty for secondary tracks. The difference in reconstruction efficiency for charged kaons and pions also has a negligible impact on the measured multiplicity distribution. Finally, the extrapolation uncertainty from pT=100 MeV/cto zero is 1% (Section 6). For hpTiversus n, this was taken into account by changing the mean transverse momentum by the average pTof tracks lost during the event reconstruction folded with the tracking efficiency uncertainty. The overall effect of this systematic uncertainty is less than 10% for small multiplicities, but can reach up to 30% for the high multiplicities, where it is the main source of systematic uncertainty. Model dependence. The baseline MC model that is used to unfold the multiplicity distribution underestimates the single-particle densities at zero rapidity by 10% relatively to |η| ∼ 1.5 at √s=0.9 and 2.36 TeV, but correctly describes the 7 TeV data shapes. This discrepancy affects the response matrix used in the unfolding procedure. The effect on the multiplicity distribution is estimated to be at most 3% by means of an alternative MC tune. The robustness of the unfolding procedure was verified by unfolding pseudo-data generated with PHOJET using a response matrix constructed with PYTHIA. The induced variation on Pnis below 3% and is 14 9 Conclusions none is able to describe simultaneously the multiplicity distributions and the pTspectrum at √s=7 TeV. In general, models predict too few low-momentum particles, indicating that by increasing the amount of multiple-parton interactions one effectively introduces too many hard scatters in the event. The change of slope in Pnin the widest central pseudorapidity intervals observed at √s= 7 TeV, combined with the strong linear increase of the Cqmoments, indicates a clear violation of KNO scaling with respect to lower energies. This observation merits further studies. Acknowledgements We wish to congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC machine. We thank the technical and administrative staff at CERN and other CMS institutes. This work was supported by the Austrian Federal Ministry of Science and Research; the Belgium Fonds de la Recherche Scientifique, and Fonds voor Wetenschappelijk Onderzoek; the Brazilian Funding Agencies (CNPq, CAPES, FAPERJ, and FAPESP); the Bulgarian Ministry of Education and Science; CERN; the Chinese Academy of Sciences, Ministry of Science and Technology, and National Natural Science Foundation of China; the Colombian Funding Agency (COLCIENCIAS); the Croatian Ministry of Science, Education and Sport; the Research Promotion Foundation, Cyprus; the Estonian Academy of Sciences and NICPB; the Academy of Finland, Finnish Ministry of Education, and Helsinki Institute of Physics; the Institut National de Physique Nucl´ eaire et de Physique des Particules / CNRS, and Commissariat ` a l’´ Energie Atomique, France; the Bundesministerium f¨ ur Bildung und Forschung, Deutsche Forschungsgemeinschaft, and Helmholtz-Gemeinschaft Deutscher Forschungszentren, Germany; the General Secretariat for Research and Technology, Greece; the National Scientific Research Foundation, and National Office for Research and Technology, Hungary; the Department of Atomic Energy, and Department of Science and Technology, India; the Institute for Studies in Theoretical Physics and Mathematics, Iran; the Science Foundation, Ireland; the Istituto Nazionale di Fisica Nucleare, Italy; the Korean Ministry of Education, Science and Technology and the World Class University program of NRF, Korea; the Lithuanian Academy of Sciences; the Mexican Funding Agencies (CINVESTAV, CONACYT, SEP, and UASLP-FAI); the Pakistan Atomic Energy Commission; the State Commission for Scientific Research, Poland; the Fundac¸˜ ao para a Ciˆ encia e a Tecnologia, Portugal; JINR (Armenia, Belarus, Georgia, Ukraine, Uzbekistan); the Ministry of Science and Technologies of the Russian Federation, and Russian Ministry of Atomic Energy; the Ministry of Science and Technological Development of Serbia; the Ministerio de Ciencia e Innovaci´ on, and Programa Consolider-Ingenio 2010, Spain; the Swiss Funding Agencies (ETH Board, ETH Zurich, PSI, SNF, UniZH, Canton Zurich, and SER); the National Science Council, Taipei; the Scientific and Technical Research Council of Turkey, and Turkish Atomic Energy Authority; the Science and Technology Facilities Council, UK; the US Department of Energy, and the US National Science Foundation. 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Wickens Ghent University, Ghent, Belgium S. Costantini, M. Grunewald, B. Klein, A. Marinov, 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, 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, L. Quertenmont, 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 22 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. Yang, J. Zang, Z. Zhang State Key Lab. of Nucl. Phys. and Tech., Peking University, Beijing, China Y. Ban, S. Guo, W. Li, Y. Mao, S.J. Qian, H. Teng, B. Zhu 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, R. Fereos, M. Galanti, J. Mousa, C. Nicolaou, F. Ptochos, P.A. Razis, H. Rykaczewski 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. 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Andronikashvili Institute of Physics, Academy of Science, Tbilisi, Georgia V. Roinishvili 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. Kreuzer1, 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. 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Thomsen, R. Wolf Institut f¨ur Experimentelle Kernphysik, Karlsruhe, Germany 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, 30 A The CMS Collaboration University of California, Los Angeles, Los Angeles, USA V. Andreev, K. Arisaka, D. Cline, R. Cousins, A. Deisher, J. Duris, S. Erhan1, C. Farrell, J. Hauser, M. Ignatenko, C. Jarvis, C. Plager, G. Rakness, P. Schlein†, J. Tucker, V. Valuev University of California, Riverside, Riverside, USA J. Babb, R. Clare, J. Ellison, J.W. Gary, F. Giordano, G. Hanson, G.Y. Jeng, S.C. Kao, F. Liu, H. Liu, A. Luthra, H. Nguyen, G. Pasztor38, A. Satpathy, B.C. Shen†, R. Stringer, J. Sturdy, S. Sumowidagdo, R. Wilken, S. Wimpenny University of California, San Diego, La Jolla, USA W. Andrews, J.G. Branson, E. Dusinberre, D. Evans, F. Golf, A. Holzner, R. Kelley, M. Lebourgeois, J. Letts, B. Mangano, J. Muelmenstaedt, S. Padhi, C. Palmer, G. Petrucciani, H. Pi, M. Pieri, R. Ranieri, M. Sani, V. Sharma1, S. Simon, Y. Tu, A. Vartak, F. W¨ urthwein, A. Yagil University of California, Santa Barbara, Santa Barbara, USA D. Barge, R. Bellan, C. Campagnari, M. D’Alfonso, T. Danielson, P. Geffert, J. Incandela, C. Justus, P. Kalavase, S.A. Koay, D. Kovalskyi, V. Krutelyov, S. Lowette, N. Mccoll, V. Pavlunin, F. Rebassoo, J. Ribnik, J. Richman, R. Rossin, D. Stuart, W. To, J.R. Vlimant California Institute of Technology, Pasadena, USA A. Bornheim, J. Bunn, Y. Chen, M. Gataullin, D. Kcira, V. Litvine, Y. Ma, A. Mott, H.B. Newman, C. Rogan, V. Timciuc, P. Traczyk, J. Veverka, R. Wilkinson, Y. Yang, R.Y. Zhu Carnegie Mellon University, Pittsburgh, USA B. Akgun, R. Carroll, T. Ferguson, Y. Iiyama, D.W. Jang, S.Y. Jun, Y.F. Liu, M. Paulini, J. Russ, N. Terentyev, H. Vogel, I. Vorobiev University of Colorado at Boulder, Boulder, USA J.P. Cumalat, M.E. Dinardo, B.R. Drell, C.J. Edelmaier, W.T. Ford, B. Heyburn, E. Luiggi Lopez, U. Nauenberg, J.G. Smith, K. Stenson, K.A. Ulmer, S.R. Wagner, S.L. Zang Cornell University, Ithaca, USA L. Agostino, J. Alexander, A. Chatterjee, S. Das, N. Eggert, L.J. Fields, L.K. Gibbons, B. Heltsley, W. Hopkins, A. Khukhunaishvili, B. Kreis, V. Kuznetsov, G. Nicolas Kaufman, J.R. Patterson, D. Puigh, D. Riley, A. Ryd, X. Shi, W. Sun, W.D. Teo, J. Thom, J. Thompson, J. Vaughan, Y. Weng, L. Winstrom, P. Wittich Fairfield University, Fairfield, USA A. Biselli, G. Cirino, D. Winn Fermi National Accelerator Laboratory, Batavia, USA S. Abdullin, M. Albrow, J. Anderson, G. Apollinari, M. Atac, J.A. Bakken, S. Banerjee, L.A.T. Bauerdick, A. Beretvas, J. Berryhill, P.C. Bhat, I. Bloch, F. Borcherding, K. Burkett, J.N. Butler, V. Chetluru, H.W.K. Cheung, F. Chlebana, S. Cihangir, M. Demarteau, D.P. Eartly, V.D. Elvira, I. Fisk, J. Freeman, Y. Gao, E. Gottschalk, D. Green, K. Gunthoti, O. Gutsche, A. Hahn, J. Hanlon, R.M. Harris, J. Hirschauer, B. Hooberman, E. James, H. Jensen, M. Johnson, U. Joshi, R. Khatiwada, B. Kilminster, B. Klima, K. Kousouris, S. Kunori, S. Kwan, P. Limon, R. Lipton, J. Lykken, K. Maeshima, J.M. Marraffino, D. Mason, P. McBride, T. McCauley, T. Miao, K. Mishra, S. Mrenna, Y. Musienko39, C. Newman-Holmes, V. O’Dell, S. Popescu40, R. Pordes, O. Prokofyev, N. Saoulidou, E. Sexton-Kennedy, S. Sharma, A. Soha, W.J. Spalding, L. Spiegel, P. Tan, L. Taylor, S. Tkaczyk, L. Uplegger, E.W. Vaandering, R. Vidal, J. Whitmore, W. Wu, F. Yang, F. Yumiceva, J.C. Yun 31 University of Florida, Gainesville, USA D. Acosta, P. Avery, D. Bourilkov, M. Chen, G.P. Di Giovanni, D. Dobur, A. Drozdetskiy, R.D. Field, M. Fisher, Y. Fu, I.K. Furic, J. Gartner, S. Goldberg, B. Kim, S. Klimenko, J. Konigsberg, A. Korytov, A. Kropivnitskaya, T. Kypreos, K. Matchev, G. Mitselmakher, L. Muniz, Y. Pakhotin, C. Prescott, R. Remington, M. Schmitt, B. Scurlock, P. Sellers, N. Skhirtladze, D. Wang, J. Yelton, M. Zakaria Florida International University, Miami, USA C. Ceron, V. Gaultney, L. Kramer, L.M. Lebolo, S. Linn, P. Markowitz, G. Martinez, J.L. Rodriguez Florida State University, Tallahassee, USA T. Adams, A. Askew, D. Bandurin, J. Bochenek, J. Chen, B. Diamond, S.V. Gleyzer, J. Haas, S. Hagopian, V. Hagopian, M. Jenkins, K.F. Johnson, H. Prosper, S. Sekmen, V. Veeraraghavan Florida Institute of Technology, Melbourne, USA M.M. Baarmand, B. Dorney, S. Guragain, M. Hohlmann, H. Kalakhety, R. Ralich, I. Vodopiyanov University of Illinois at Chicago (UIC), Chicago, USA M.R. Adams, I.M. Anghel, L. Apanasevich, Y. Bai, V.E. Bazterra, R.R. Betts, J. Callner, R. Cavanaugh, C. Dragoiu, E.J. Garcia-Solis, C.E. Gerber, D.J. Hofman, S. Khalatyan, F. Lacroix, C. O’Brien, C. Silvestre, A. Smoron, D. Strom, N. Varelas The University of Iowa, Iowa City, USA U. Akgun, E.A. Albayrak, B. Bilki, K. Cankocak41, W. Clarida, F. Duru, C.K. Lae, E. McCliment, J.-P. Merlo, H. Mermerkaya, A. Mestvirishvili, A. Moeller, J. Nachtman, C.R. Newsom, E. Norbeck, J. Olson, Y. Onel, F. Ozok, S. Sen, J. Wetzel, T. Yetkin, K. Yi Johns Hopkins University, Baltimore, USA B.A. Barnett, B. Blumenfeld, A. Bonato, C. Eskew, D. Fehling, G. Giurgiu, A.V. Gritsan, Z.J. Guo, G. Hu, P. Maksimovic, S. Rappoccio, M. Swartz, N.V. Tran, A. Whitbeck The University of Kansas, Lawrence, USA P. Baringer, A. Bean, G. Benelli, O. Grachov, M. Murray, D. Noonan, V. Radicci, S. Sanders, J.S. Wood, V. Zhukova Kansas State University, Manhattan, USA T. Bolton, I. Chakaberia, A. Ivanov, M. Makouski, Y. Maravin, S. Shrestha, I. Svintradze, Z. Wan Lawrence Livermore National Laboratory, Livermore, USA J. Gronberg, D. Lange, D. Wright University of Maryland, College Park, USA A. Baden, M. Boutemeur, S.C. Eno, D. Ferencek, J.A. Gomez, N.J. Hadley, R.G. Kellogg, M. Kirn, Y. Lu, A.C. Mignerey, K. Rossato, P. Rumerio, F. Santanastasio, A. Skuja, J. Temple, M.B. Tonjes, S.C. Tonwar, E. Twedt Massachusetts Institute of Technology, Cambridge, USA B. Alver, G. Bauer, J. Bendavid, W. Busza, E. Butz, I.A. Cali, M. Chan, V. Dutta, P. Everaerts, G. Gomez Ceballos, M. Goncharov, K.A. Hahn, P. Harris, Y. Kim, M. Klute, Y.-J. Lee, W. Li, C. Loizides, P.D. Luckey, T. Ma, S. Nahn, C. Paus, C. Roland, G. Roland, M. Rudolph, G.S.F. Stephans, K. Sumorok, K. Sung, E.A. Wenger, S. Xie, M. Yang, Y. Yilmaz, A.S. Yoon, M. Zanetti 32 A The CMS Collaboration University of Minnesota, Minneapolis, USA P. Cole, S.I. Cooper, P. Cushman, B. Dahmes, A. De Benedetti, P.R. Dudero, G. Franzoni, J. Haupt, K. Klapoetke, Y. Kubota, J. Mans, V. Rekovic, R. Rusack, M. Sasseville, A. Singovsky University of Mississippi, University, USA L.M. Cremaldi, R. Godang, R. Kroeger, L. Perera, R. Rahmat, D.A. Sanders, D. Summers University of Nebraska-Lincoln, Lincoln, USA K. Bloom, S. Bose, J. Butt, D.R. Claes, A. Dominguez, M. Eads, J. Keller, T. Kelly, I. Kravchenko, J. Lazo-Flores, C. Lundstedt, H. Malbouisson, S. Malik, G.R. Snow State University of New York at Buffalo, Buffalo, USA U. Baur, A. Godshalk, I. Iashvili, A. Kharchilava, A. Kumar, K. Smith Northeastern University, Boston, USA G. Alverson, E. Barberis, D. Baumgartel, O. Boeriu, M. Chasco, K. Kaadze, S. Reucroft, J. Swain, D. Wood, J. Zhang Northwestern University, Evanston, USA A. Anastassov, A. Kubik, N. Odell, R.A. Ofierzynski, B. Pollack, A. Pozdnyakov, M. Schmitt, S. Stoynev, M. Velasco, S. Won University of Notre Dame, Notre Dame, USA L. Antonelli, D. Berry, M. Hildreth, C. Jessop, D.J. Karmgard, J. Kolb, T. Kolberg, K. Lannon, W. Luo, S. Lynch, N. Marinelli, D.M. Morse, T. Pearson, R. Ruchti, J. Slaunwhite, N. Valls, J. Warchol, M. Wayne, J. Ziegler The Ohio State University, Columbus, USA B. Bylsma, L.S. Durkin, J. Gu, C. Hill, P. Killewald, K. Kotov, T.Y. Ling, M. Rodenburg, G. Williams Princeton University, Princeton, USA N. Adam, E. Berry, P. Elmer, D. Gerbaudo, V. Halyo, P. Hebda, A. Hunt, J. Jones, E. Laird, D. Lopes Pegna, D. Marlow, T. Medvedeva, M. Mooney, J. Olsen, P. Pirou´ e, X. Quan, H. Saka, D. Stickland, C. Tully, J.S. Werner, A. Zuranski University of Puerto Rico, Mayaguez, USA J.G. Acosta, X.T. Huang, A. Lopez, H. Mendez, S. Oliveros, J.E. Ramirez Vargas, A. Zatserklyaniy Purdue University, West Lafayette, USA E. Alagoz, V.E. Barnes, G. Bolla, L. Borrello, D. Bortoletto, A. Everett, A.F. Garfinkel, Z. Gecse, L. Gutay, M. Jones, O. Koybasi, A.T. Laasanen, N. Leonardo, C. Liu, V. Maroussov, P. Merkel, D.H. Miller, N. Neumeister, K. Potamianos, I. Shipsey, D. Silvers, A. Svyatkovskiy, H.D. Yoo, J. Zablocki, Y. Zheng Purdue University Calumet, Hammond, USA P. Jindal, N. Parashar Rice University, Houston, USA C. Boulahouache, V. Cuplov, K.M. Ecklund, F.J.M. Geurts, J.H. Liu, J. Morales, B.P. Padley, R. Redjimi, J. Roberts, J. Zabel University of Rochester, Rochester, USA B. Betchart, A. Bodek, Y.S. Chung, P. de Barbaro, R. Demina, Y. Eshaq, H. Flacher, A. Garcia- 33 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, 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, J. Pivarski, A. Safonov, S. Sengupta, A. Tatarinov, D. Toback, M. Weinberger Texas Tech University, Lubbock, USA N. Akchurin, C. Bardak, J. Damgov, C. Jeong, K. Kovitanggoon, S.W. Lee, P. Mane, 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, 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, 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, D. Lomidze, R. Loveless, A. Mohapatra, W. Parker, 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 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 34 A The CMS Collaboration 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 California Institute of Technology, Pasadena, USA 19: Also at Faculty of Physics of University of Belgrade, Belgrade, Serbia 20: Also at University of California, Los Angeles, Los Angeles, USA 21: Also at University of Florida, Gainesville, USA 22: Also at Universit´ e de Gen` eve, Geneva, Switzerland 23: Also at Scuola Normale e Sezione dell’ INFN, Pisa, Italy 24: Also at INFN Sezione di Roma; Universit` a di Roma ”La Sapienza”, Roma, Italy 25: Also at University of Athens, Athens, Greece 26: Also at The University of Kansas, Lawrence, USA 27: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia 28: Also at Paul Scherrer Institut, Villigen, Switzerland 29: Also at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia 30: Also at Adiyaman University, Adiyaman, Turkey 31: Also at Mersin University, Mersin, Turkey 32: Also at Izmir Institute of Technology, Izmir, Turkey 33: Also at Kafkas University, Kars, Turkey 34: Also at Suleyman Demirel University, Isparta, Turkey 35: Also at Ege University, Izmir, Turkey 36: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom 37: Also at INFN Sezione di Perugia; Universit` a di Perugia, Perugia, Italy 38: Also at KFKI Research Institute for Particle and Nuclear Physics, Budapest, Hungary 39: Also at Institute for Nuclear Research, Moscow, Russia 40: Also at Horia Hulubei National Institute of Physics and Nuclear Engineering (IFIN-HH), Bucharest, Romania 41: Also at Istanbul Technical University, Istanbul, Turkey