Measurements of the \(\mathrm{t}\overline{\mathrm{t}}\) production cross section in lepton+jets final states in pp collisions at 8 \(\,\text {TeV}\) and ratio of 8 to 7 \(\,\text {TeV}\) cross sections

The European Physical Journal C, Jan 2017

A measurement of the top quark pair production (\(\mathrm{t}\overline{\mathrm{t}} \)) cross section in proton–proton collisions at the centre-of-mass energy of 8\(\,\text {TeV}\) is presented using data collected with the CMS detector at the LHC, corresponding to an integrated luminosity of 19.6\(\,\text {fb}^{-\text {1}}\). This analysis is performed in the \(\mathrm{t}\overline{\mathrm{t}} \) decay channels with one isolated, high transverse momentum electron or muon and at least four jets, at least one of which is required to be identified as originating from hadronization of a b quark. The calibration of the jet energy scale and the efficiency of b jet identification are determined from data. The measured \(\mathrm{t}\overline{\mathrm{t}} \) cross section is \(228.5 \pm 3.8\,\text {(stat)} \pm 13.7\,\text {(syst)} \pm 6.0\,\text {(lumi)} \text { pb} \). This measurement is compared with an analysis of 7\(\,\text {TeV}\) data, corresponding to an integrated luminosity of 5.0\(\,\text {fb}^{-\text {1}}\), to determine the ratio of 8\(\,\text {TeV}\) to 7\(\,\text {TeV}\) cross sections, which is found to be \(1.43 \pm 0.04\,\text {(stat)} \pm 0.07\,\text {(syst)} \pm 0.05\,\text {(lumi)} \). The measurements are in agreement with QCD predictions up to next-to-next-to-leading order.

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Measurements of the \(\mathrm{t}\overline{\mathrm{t}}\) production cross section in lepton+jets final states in pp collisions at 8 \(\,\text {TeV}\) and ratio of 8 to 7 \(\,\text {TeV}\) cross sections

Eur. Phys. J. C Measurements of the tt production cross section in lepton+jets final states in pp collisions at 8 TeV and ratio of 8 to 7 TeV cross sections CMS Collaboration 0 1 2 3 4 5 6 7 8 9 10 11 13 14 15 16 17 18 22 23 24 25 26 27 28 29 31 32 33 36 37 38 40 41 42 43 44 46 0 CERN , 1211 Geneva 23 , Switzerland 1 University of Sofia , Sofia, Bulgaria A. Dimitrov, I. Glushkov, L. Litov, B. Pavlov, P. Petkov 2 Ghent University , Ghent , Belgium K. Beernaert , L. Benucci, A. Cimmino, S. Costantini, S. Crucy, D. Dobur, A. Fagot, G. Garcia, M. Gul, J. Mccartin, A. A. Ocampo Rios, D. Poyraz, D. Ryckbosch, S. Salva, M. Sigamani, N. Strobbe, M. Tytgat, W. Van Driessche, E. Yazgan, N. Zaganidis 3 Institute Rudjer Boskovic , Zagreb , Croatia V. Brigljevic, K. Kadija, J. Luetic, S. Micanovic, L. Sudic 4 Faculty of Science, University of Split , Split , Croatia Z. Antunovic, M. Kovac 5 State Key Laboratory of Nuclear Physics and Technology, Peking University , Beijing , China C. Asawatangtrakuldee, Y. Ban, Q. Li, S. Liu, Y. Mao, S. J. Qian, D. Wang, Z. Xu 6 Lappeenranta University of Technology , Lappeenranta , Finland J. Talvitie, T. Tuuva 7 Helsinki Institute of Physics , Helsinki, Finland J. Härkönen, V. Karimäki, R. Kinnunen, T. Lampén, K. Lassila-Perini, S. Lehti, T. Lindén, P. Luukka, T. Mäenpää, T. Peltola, E. Tuominen, J. Tuominiemi, E. Tuovinen, L. Wendland 8 Department of Physics, University of Helsinki , Helsinki , Finland P. Eerola, J. Pekkanen, M. Voutilainen 9 Charles University , Prague , Czech Republic M. Bodlak, M. Finger 10 University of Cyprus , Nicosia, Cyprus A. Attikis, G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos, P. A. Razis, H. Rykaczewski 11 III. Physikalisches Institut A, RWTH Aachen University , Aachen, Germany M. Ata, M. Brodski, E. Dietz-Laursonn, D. Duchardt, M. Endres, M. Erdmann, S. Erdweg, T. Esch, R. Fischer, A. Güth, T. Hebbeker, C. Heidemann, K. Hoepfner, D. Klingebiel, S. Knutzen, P. Kreuzer, M. Merschmeyer, A. Meyer, P. Millet, M. Olschewski, K. Padeken, P. Papacz, T. Pook, M. Radziej, H. Reithler, M. Rieger, F. Scheuch, L. Sonnenschein, D. Teyssier, S. Thüer 12 , A. Nehrkorn , A. Nowack, I. M. Nugent, C. Pistone, O. Pooth, A. Stahl 13 I. Physikalisches Institut, RWTH Aachen University , Aachen, Germany C. Autermann, S. Beranek, M. Edelhoff, L. Feld, A. Heister, M. K. Kiesel, K. Klein, M. Lipinski, A. Ostapchuk, M. Preuten, F. Raupach, S. Schael, J. F. Schulte, T. Verlage, H. Weber, B. Wittmer, V. Zhukov 14 Université de Lyon , Université Claude Bernard Lyon 1, CNRS-IN2P3 , Institut de Physique Nucléaire de Lyon , Villeurbanne , France S. Beauceron, C. Bernet, G. Boudoul, E. Bouvier, C. A. Carrillo Montoya, R. Chierici, D. Contardo, B. Courbon, P. Depasse, H. El Mamouni, J. Fan, J. Fay, S. Gascon, M. Gouzevitch, B. Ille, F. Lagarde, I. B. Laktineh, M. Lethuillier, L. Mirabito, A. L. Pequegnot, S. Perries, J. D. Ruiz Alvarez, D. Sabes, L. Sgandurra, V. Sordini, M. Vander Donckt, P. Verdier, S. Viret 15 III. Physikalisches Institut B, RWTH Aachen University , Aachen, Germany V. Cherepanov, Y. Erdogan, G. Flügge, H. Geenen, M. Geisler, F. Hoehle, B. Kargoll, T. Kress, Y. Kuessel, A. Künsken, J. Lingemann 16 Institute of Nuclear Research ATOMKI , Debrecen , Hungary N. Beni, S. Czellar, J. Karancsi 17 Wigner Research Centre for Physics , Budapest, Hungary G. Bencze, C. Hajdu, A. Hazi, P. Hidas, D. Horvath 18 University of Ioánnina , Ioánnina , Greece I. Evangelou, G. Flouris, C. Foudas, P. Kokkas, N. Loukas, N. Manthos, I. Papadopoulos, E. Paradas, J. Strologas 19 , F. Sikler, V. Veszpremi, G. Vesztergombi 20 , J. Molnar, Z. Szillasi 21 , A. Makovec , P. Raics, Z. L. Trocsanyi, B. Ujvari 22 Saha Institute of Nuclear Physics , Kolkata , India S. Bhattacharya, K. Chatterjee, S. Dey, S. Dutta, Sa. Jain, N. Majumdar, A. Modak, K. Mondal, S. Mukherjee, S. Mukhopadhyay, A. Roy, D. Roy, S. Roy Chowdhury, S. Sarkar, M. Sharan 23 University of Delhi , Delhi , India Ashok Kumar , A. Bhardwaj, B. C. Choudhary, R. B. Garg, A. Kumar, S. Malhotra, M. Naimuddin, N. Nishu, K. Ranjan, R. Sharma, V. Sharma 24 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 25 University of Debrecen , Debrecen , Hungary M. Bartók 26 Kangwon National University , Chunchon , Korea A. Kropivnitskaya, S. K. Nam 27 National Centre for Physics, Quaid-I-Azam University , Islamabad, Pakistan A. Ahmad, M. Ahmad, Q. Hassan, H. R. Hoorani, W. A. Khan, T. Khurshid, M. Shoaib 28 Sungkyunkwan University , Suwon, Korea Y. Choi, J. Goh, D. Kim, E. Kwon, J. Lee, I. Yu 29 Seoul National University , Seoul , Korea H. D. Yoo 30 , K. Doroba , A. Kalinowski, M. Konecki, J. Krolikowski, M. Misiura, M. Olszewski, M. Walczak 31 Faculty of Physics, Institute of Experimental Physics University of Warsaw , Warsaw , Poland G. Brona, K. Bunkowski, A. Byszuk 32 Faculty of Physics and Vinca Institute of Nuclear Sciences, University of Belgrade , Belgrade , Serbia P. Adzic 33 Petersburg Nuclear Physics Institute , Gatchina (St. Petersburg), Russia V. Golovtsov, Y. Ivanov, V. Kim 34 , J. Milosevic, V. Rekovic 35 , E. Kuznetsova , P. Levchenko, V. Murzin, V. Oreshkin, I. Smirnov, V. Sulimov, L. Uvarov, S. Vavilov, A. Vorobyev 36 Istanbul Technical University , Istanbul , Turkey A. Cakir, K. Cankocak, S. Sen 37 Bogazici University , Istanbul , Turkey E. Gülmez, M. Kaya 38 Physics Department, Middle East Technical University , Ankara , Turkey I. V. Akin, B. Bilin, S. Bilmis, B. Isildak 39 , M. Yalvac , M. Zeyrek 40 California Institute of Technology , Pasadena, USA D. Anderson, A. Apresyan, A. Bornheim, J. Bunn, Y. Chen, J. Duarte, A. Mott, H. B. Newman, C. Pena, M. Pierini, M. Spiropulu, J. R. Vlimant, S. Xie, R. Y. Zhu 41 Boston University , Boston, USA D. Arcaro, A. Avetisyan, T. Bose, C. Fantasia, D. Gastler, P. Lawson, D. Rankin, C. Richardson, J. Rohlf, J. St. John, L. Sulak, D. Zou 42 Northwestern University , Evanston , USA K. A. Hahn, A. Kubik, N. Mucia, N. Odell , B. Pollack, A. Pozdnyakov, M. Schmitt, S. Stoynev, K. Sung, M. Trovato, M. Velasco 43 Wayne State University , Detroit, USA C. Clarke, R. Harr, P. E. Karchin, C. Kottachchi Kankanamge Don, P. Lamichhane, J. Sturdy 44 Texas Tech University , Lubbock , USA 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 45 , V. Krutelyov, R. Mueller, I. Osipenkov, Y. Pakhotin, R. Patel, A. Perloff, A. Rose, A. Safonov, A. Tatarinov, K. A. Ulmer 46 Texas A&M University, College Station , USA O. Bouhali 47 , M. Dalchenko, M. De Mattia, A. Delgado , S. Dildick, R. Eusebi, J. Gilmore, T. Kamon A measurement of the top quark pair production (tt) cross section in proton-proton collisions at the centre-of-mass energy of 8 TeV is presented using data collected with the CMS detector at the LHC, corresponding to an integrated luminosity of 19.6 fb−1. This analysis is performed in the tt decay channels with one isolated, high transverse momentum electron or muon and at least four jets, at least one of which is required to be identified as originating from hadronization of a b quark. The calibration of the jet energy scale and the efficiency of b jet identification are determined from data. The measured tt cross section is 228.5 ± 3.8 (stat) ± 13.7 (syst) ± 6.0 (lumi) pb. This measurement is compared with an analysis of 7 TeV data, corresponding to an integrated luminosity of 5.0 fb−1, to determine the ratio of 8 TeV to 7 TeV cross sections, which is found to be 1.43 ± 0.04 (stat) ± 0.07 (syst) ± 0.05 (lumi). The measurements are in agreement with QCD predictions up to next-to-next-to-leading order. 1 Introduction Top quarks are abundantly produced at the CERN LHC. The predicted top quark pair production cross section (σtt) in proton–proton (pp) collisions, at a centre-of-mass energy of 8 TeV, is 253 pb, with theoretical uncertainties at the level of 5–6%. A precise measurement of σtt is an important test of perturbative quantum chromodynamics (QCD) at high energies. Furthermore, precision tt cross section measurements can be used to constrain the top quark mass mt and QCD parameters, such as the strong coupling constant αS [1], or the parton distribution functions (PDF) of the proton [2]. The tt production cross section was measured at the LHC at √s = 7 and 8 TeV [3–18,18–25]. In this paper, a measurement of the tt production cross section in the final state with one high transverse momentum lepton (muon or electron) and jets is presented using the 2012 data set at √s = 8 TeV, collected by the CMS experiment at the LHC and corresponding to an integrated luminosity of 19.6 fb−1. To measure the cross section ratio, where several systematic uncertainties cancel, the 2011 data set at √s = 7 TeV, corresponding to an integrated luminosity of 5.0 fb−1, has been concurrently analyzed with a similar strategy to the one developed for the cross section measurement at 8 TeV. The new measurement agrees very well with the previously published CMS result [8]. The larger statistical uncertainty of the present measurement with respect to the previous one is due to the simultaneous determination of the b tagging efficiency, as discussed in Sect. 6. Similarly to the 8 TeV analysis, an additional signal modelling uncertainty has been considered in the 7 TeV analysis, as reported in Sect. 6. In the standard model, top quarks are predominantly produced in pairs via the strong interaction and decay almost exclusively into a W boson and a b quark. The event signature is determined by the subsequent decays of the two W bosons. This analysis uses lepton+jets decays into muons or electrons, where one of the W bosons decays into two quarks and the other to a lepton and a neutrino. Decays of the W boson into a tau lepton and a neutrino can enter the selection if the tau lepton decays leptonically. The top quark decaying into a b quark and a leptonically decaying W boson is defined in the following as the “leptonic top quark”, while the other top quark is referred to as “hadronic top quark”. For the tt signal two jets result from the hadronization of the b and b quarks (b jets), thus b tagging algorithms are employed for the identification of b jets in order to improve the purity of the tt candidate sample. The technique for extracting the tt cross section consists of a binned log-likelihood fit of signal and background to the distribution of a discriminant variable in data showing a good separation between signal and background: the invariant mass of the b jet related to the leptonic top quark and the lepton (M b). The mass of the three-jet combination with the highest transverse momentum in the event (M3) is used as a discriminant in an alternative analysis. The M b variable is related to the leptonic top quark mass, while M3 is a measure for the hadronic top quark mass. Both quantities provide a good separation between signal and background processes. The analysis employs calibration techniques to reduce the experimental uncertainties related to b tagging efficiencies and jet energy scale (JES). The tt topology is reconstructed using a jet sorting algorithm in which the b jet most likely originating from the leptonic top quark is identified. The b tagging efficiency is then determined from a b-enriched sample, in the peak region of the M b distribution, correcting for the contamination from non-b jets, following the method described in Refs. [26,27]. The rate of jets that are wrongly tagged as originating from a b quark is also measured using data as described in [28]. Independently, the JES is determined using the jets associated with the hadronically decaying W boson by correcting the reconstructed mass of the W boson in the simulation to that determined from the data. The results of the cross section measurements are given both for the visible region, i.e. for the phase space corresponding to the event selection, and for the full phase space. The visible region is defined by requiring the presence in the simulation of exactly one lepton, one neutrino, and at least four jets passing the selection criteria, as presented in Sect. 5. This paper is structured as follows: after a description of the CMS detector (see Sect. 2), the data and the simulated samples are discussed in Sect. 3, while Sect. 4 is dedicated to the event selection. The analysis technique and the impact of the systematic uncertainties are addressed in Sect. 5 and in Sect. 6. The results of the cross section measurements are discussed in Sect. 7. Section 8 describes the alternative analysis based on M3, followed by a summary in Sect. 9. 2 The CMS detector The central feature of the CMS apparatus is a superconducting solenoid, of 6 m internal diameter, providing an axial magnetic field of 3.8 T. Within the solenoidal field volume are a silicon pixel and strip tracker which measure charged particle trajectories in the pseudorapidity range |η| < 2.5. Also within the field volume, the silicon detectors are surrounded by a lead tungstate crystal electromagnetic calorimeter (|η| < 3.0) and a brass and scintillator hadron calorimeter (|η| < 5.0) that provide high-resolution energy and direction measurements of electrons and hadronic jets. Muons are measured in gas-ionization detectors embedded in the steel magnetic flux-return yoke outside the solenoid. The muon detection systems provide muon detection in the range |η| < 2.4. A two-level trigger system selects the pp collision events for use in physics analysis. A more detailed description of the CMS detector, together with a definition of the coordinate system used and the relevant kinematic variables, can be found elsewhere [29]. 3 Data and simulation The cross section measurement is performed using the 8 TeV pp collisions recorded by the CMS experiment in 2012, corresponding to an integrated luminosity of 19.6 ± 0.5 fb−1 [30], and the 2011 data set at √s = 7 TeV, corresponding to an integrated luminosity of 5.0 ± 0.2 fb−1 [31]. The tt events are simulated using the Monte Carlo (MC) event generators MadGraph (version 5.1.1.0) [32,33] and powheg (v1.0 r1380) [34,35]. In MadGraph the top quark pairs are generated at leading order with up to three additional high- pT jets. The powheg generator implements matrix elements to next-to-leading order (NLO) in perturbative QCD, with up to one additional jet. The mass of the top quark is set to 172.5 GeV. The CT10 [36] PDF set is used by powheg and the CTEQ6M [37–39] by MadGraph. The pythia (v.6.426) [40] and herwig (v.6.520) [41] generators are used to model the parton showering. The pythia shower matching is done using the MLM prescription [42,43]. The top quark pair production cross section values are predicted to be 177.3+−46..06 (scale) ± 9.0 (PDF+αS) pb at 7 TeV and 252.9+6.4 (scale) ± 11.7 (PDF+αS) pb at 8 TeV, −8.6 as calculated with the Top++ 2.0 program to next-to-nextto-leading order (NNLO) in perturbative QCD, including soft-gluon resummation to next-to-next-to-leading logarithmic (NNLL) order (Ref. [44] and references therein), and assuming mt = 172.5 GeV. The first uncertainty comes from the independent variation of the factorization and renormalization scales, while the second one is associated to variations in the PDF and αS following the PDF4LHC prescription with the MSTW2008 68% confidence level NNLO, CT10 NNLO, and NNPDF2.3 5f FFN PDF sets (Refs. [37,38] and references therein, and Refs. [36,39]). The top quark transverse momentum is reweighted in samples simulated with MadGraph and powheg, when interfaced to pythia, in order to better describe the pT distribution observed in the data. Based on studies of differential distributions [45,46] in the top quark transverse momentum, an event weight w = √w1 w2 is applied, where the weights wi of the two top quarks are given as a function of the generated top quark pT values: wi = exp(0.199−0.00166 pTi/GeV) at 7 TeV, and wi = exp(0.156 − 0.00137 pTi/GeV) at 8 TeV. This reweighting is only applied to the phase space corresponding to the experimental selections in the muon and electron channels. The agreement between data and samples generated with powheg interfaced with herwig is found to be satisfactory, and no reweighting is applied in this case. The W/Z+jets events, i.e. the associated production of W/Z vector bosons with jets, with leptonic decays of the W/Z bosons, constitute the largest background. These are also simulated using MadGraph with matrix elements corresponding to at least one jet and up to four jets. The W/Z+jets events are generated inclusively with respect to the jet flavour. Drell–Yan production of charged leptons is generated for dilepton invariant masses above 50 GeV, as those events constitute the relevant background in the phase space of this analysis. The contribution from Drell–Yan events with dilepton invariant masses below 50 GeV is negligible, as verified with a sample with a mass range of 10–50 GeV. Single top quark production is simulated with powheg. The background processes are normalized to NLO and NNLO cross section calculations [47–51], with the exception of the QCD multijet background, for which the normalization is obtained from data in the M3 analysis (see Sect. 8). In the M b analysis the multijet background is reduced to a negligible fraction (see Sect. 4) and thus not considered further. Pileup signals, i.e. extra activity due to additional pp interactions in the same bunch crossing, are incorporated by simulating additional interactions with a multiplicity matching the one inferred from data. The CMS detector response is modeled using Geant4 [52]. The simulated events are processed by the same reconstruction software as the collision data. 4 Reconstruction and event selection This analysis focuses on the selection of tt lepton+jets decays in the muon and electron channels, with similar selection requirements applied for the two channels. Muons, electrons, photons, and neutral and charged hadrons are reconstructed and identified by the CMS particle-flow (PF) algorithm [53,54]. The energy of muons is obtained from the corresponding track momentum using the combined information of the silicon tracker and the muon system [55]. The energy of electrons is determined from a combination of the track momentum in the tracker, the corresponding cluster energy in the electromagnetic calorimeter, and the energy sum of all bremsstrahlung photons associated to the track [56]. The vertex with the largest pT2 sum of the tracks associated to it is chosen as primary vertex. Candidate tt events are first accepted by dedicated triggers requiring at least one muon or electron. Lepton isolation requirements are applied to improve the purity of the selected sample. At the trigger level the relative muon isolation, the sum of transverse momenta of other particles in a cone of size √ R = ( φ)2 + ( η)2 = 0.4 around the direction of the candidate muon divided by the muon transverse momentum, is required to be less than 0.2. Similarly, for electrons, the corresponding requirement is less than 0.3 in a cone of size 0.3. Events with a muon in the final state are triggered on the presence of a muon candidate with pT > 24 GeV and |η| < 2.1. Events with an electron candidate with |η| < 2.5 are accepted by triggers requiring an electron with pT > 27 GeV. Tighter pT requirements are applied in the offline selections. Muons are required to have a good quality [55] track with pT > 25 GeV and |η| < 2.1. Electrons are identified using a combination of the shower shape information and track-electromagnetic cluster matching [56], and are required to have pT > 32 GeV and |η| < 2.5, with the exclusion of the transition region between the barrel and endcap electromagnetic calorimeter, 1.44 < |η| < 1.57. Electrons identified to come from photon conversions [56] are vetoed. Correction factors for trigger and lepton identification efficiencies have been determined with a tag-and-probe method [57] from data/simulation comparison as a function of the lepton pT and η, and are applied to the simulation. Signal events are required to have at least one pp interaction vertex, successfully reconstructed from at least four tracks, within limits on the longitudinal and radial coordinates [58], and exactly one muon, or electron, with an origin consistent with the reconstructed vertex within limits on the impact parameters. Since the lepton from the W boson decay is expected to be isolated from other activity in the event, isolation requirements are applied. A relative isolation is defined as Irel = (Icharged + Iphoton + Ineutral)/ pT, where pT is the transverse momentum of the lepton and Icharged, Iphoton, and Ineutral are the sums of the transverse energies of the charged particles, the photons, and the neutral particles not identified as photons, in a cone R < 0.4 (0.3) for muons (electrons) around the lepton direction, excluding the lepton itself. The relative isolation Irel is required to be less than 0.12 for muons and 0.10 for electrons. Events with more than one lepton candidate with relaxed requirements are vetoed in order to reject Z boson or tt decays into dileptons. The missing energy in the transverse plane (ETmiss) is defined as the magnitude of the projection on the plane perpendicular to the beams of the vector sum of the momenta of all PF candidates. It is required to be larger than 30 GeV in the muon channel and larger than 40 GeV in the electron channel, because of the larger multijet background. Jets are clustered from the charged and neutral particles reconstructed with the PF algorithm, using the anti-kT jet algorithm [59] with a radius parameter of 0.5. Particles identified as isolated muons or electrons are not used in the jet clustering. Jet energies are corrected for nonlinearities due to different responses in the calorimeters and for the differences between measured and simulated responses [60]. Furthermore, to account for extra activity within a jet cone due to pileup, jet energies are corrected [53,54] for charged hadrons that belong to a vertex other than the primary vertex, and for the amount of pileup expected in the jet area from neutral jet constituents. At least four jets are required with pT > 40 GeV and |η| < 2.5. An additional global calibration factor of the jet V2500 e G 5 /s 2000 t n e vE1500 V3000 e G /52500 s t n ve2000 E 1500 tions are already corrected for the b tagging efficiency scale factor. The hashed area shows the uncertainty in the luminosity measurement and the b tagging systematic uncertainty. The last bin includes the overflow. The ratio between data and simulation is shown in the lower panels for bins with non-zero entries.eps energy scale is obtained by fitting the W boson mass distribution in the data and in the simulation. The scale factor is determined as the ratio of the W boson mass reconstructed from non-b-tagged jet pairs in data and in the simulation. This scale correction is applied in the simulation to all jets before the selection requirements are implemented. It largely reduces the systematic uncertainty related to the jet energy scale, discussed in Sect. 6. To reduce contamination from background processes, at least one of the jets has to be identified as a b jet. The b tagging algorithm used is the “combined secondary vertex” (CSV) algorithm at the medium working point [26, 27], corresponding to a misidentification probability of about 1% for lightparton jets (mistag rate) and an efficiency for b jets in the range 60–70% depending on the jet pT and pseudorapidity. Figure 1 shows kinematic distributions after applying the b tagging requirement. Good agreement between data and simulation is observed. The M b analysis uses control samples in data for the estimation of the b tagging efficiency, as described in Refs. [26– 28]. Among the four leading jets, three are assigned to the hadronically decaying top quark through a χ 2 sorting algorithm using top quark and W boson mass constraints. The remaining fourth jet is the b jet candidate assigned to the eV2500 G 0 1 /s2000 t n e v E1500 Fig. 2 Distributions of the lepton-jet mass in the muon+jets (left) and electron+jets (right) channels, rescaled to the fit results 5 Visible and total cross section measurements The number of tt events is determined with a binned maximum-likelihood fit of distributions (templates), describing signal and background processes, to the data sample passing the final selection, by fitting M b, the invariant mass distribution of the b jet and the lepton. The tt visible (σ vis) and total (σtt) production cross sectt tions are extracted from the number of tt events observed in the data using the equations where Ntt is the number of tt events (including both signal events from the lepton+jets channel considered and events from other decay channels) extracted from the fit, L is the integrated luminosity, A is the tt acceptance, and εtt is the tt selection efficiency within the acceptance requirements outlined in the next section. Results are presented for both the visible and total cross section, in order to separate experimental uncertainties from theoretical assumptions as much as possible. One template is used for tt events (both for the tt signal events and the other tt events passing the selection criteria) and one template for all background processes (W/Z+jets and single top quark production). The fit is performed in the range 0–500 GeV. Figure 2 shows the results for the fit to the data distributions in the muon and electron channels. 5.1 Acceptance The tt acceptance A corresponding to the visible phase space depends on the theoretical model and it is determined at the generator level by requiring the presence of exactly one lepton, one neutrino, and at least four jets, passing pT and |η| selection criteria similar to the ones delineated in Sect. 4. For simplicity a single acceptance definition, corresponding to the tightest selection criteria, is used for both channels at each centre-of-mass energy: exactly one muon, or electron, with pT > 32 GeV and |η| < 2.1, one neutrino with pT > 40 GeV, and at least four jets with pT > 40 GeV and |η| < 2.5. The acceptance values include contributions from other tt decay channels, in particular from the dilepton channel, at the level of about 9%. The acceptance values are provided in Table 1 for the two generators used in this analysis, MadGraph and powheg. The acceptance values are in agreement at the 1–2% level at 8 TeV and at better than 5% at 7 TeV. This different level of agreement is due to the fact that the common acceptance definition described above corresponds the tightest pT criteria, i.e. to the pT requirements of the electron channel at √s = 8 TeV. The reweighted acceptance is determined as the number of reweighted tt events in the visible phase space, Table 1 Average acceptance values for the muon and electron channels obtained with MadGraph and powheg at √s = 7 and 8 TeV, without and with top quark pT-reweighting applied. The statistical uncertainty is 0.0004, i.e. below 3%. The theoretical uncertainties are at the level of 2%, as discussed in the text i.e. the sum of the weights, divided by the total number of (non-reweighted) tt events. The statistical uncertainty in the acceptance calculations is below 3%. The theoretical systematic uncertainties evaluated by varying the PDFs (Sect. 6) or the matching thresholds are in the range 0.1–0.2%. Variation of the factorization and renormalization scale induces a variation of up to 2% in the acceptance. These variations are already included in the systematic uncertainties quoted in Sect. 6. In the following, top quark pT-reweighting [45,46] is always applied to the visible phase space as it provides a better agreement between data and simulation. On the other hand, given that the event weights were only determined in the phase space corresponding to the experimental selection, they have not been used for the extrapolation to the total cross section. Therefore, the non-reweighted acceptance is used to determine the total cross section. However, rescaling by the ratio of the values provided in Table 1 would allow a determination of the total cross section with the reweighted acceptance. The visible cross section does not depend on the acceptance A. 5.2 Selection efficiency The selection efficiency within the acceptance, εtt, is reported in Table 2. It is determined from the pT-reweighted MadGraph simulated sample as the number of events passing the selection criteria outlined in Sect. 4, over the number of events passing the acceptance requirements defined above. The selection efficiency includes the effects of trigger requirements, lepton and jet identification criteria, and b tagging efficiency, which is directly determined from data. A signal selection efficiency within acceptance of 32% in the muon channel and 21% in the electron channel is determined. Similar values (37 and 22%, respectively) are obtained at √s = 7 TeV. For the muon channel the common acceptance requirements used for both channels are tighter than the selection requirements, thus the muon channel efficiency is significantly larger than the electron channel efficiency. The tt selection efficiency, Aεtt, is the number of selected tt events out of all produced tt pairs, in all decay channels. 6 Systematic uncertainties Systematic uncertainties are determined by varying each source within its estimated uncertainty and by propagating the variation to the cross section measurements. Template shapes and signal efficiencies are varied together according to the systematic uncertainty considered. The uncertainty is given by the shift in the fitted cross section and is crosschecked by repeating its estimation with pseudo-experiments using simulation. The systematically varied template shapes are fit to pseudo-data generated using the nominal template shapes and normalizations. The validation with pseudoexperiments shows that the fit performs as expected. All systematic uncertainties, except the ones related to b tagging and to the estimation of the multijet background, are common to both the M b and the M3 measurements. The effect of uncertainties in the JES is evaluated by varying the JES within the pT- and η-dependent uncertainties given in Ref. [60]. The final JES of the simulation is matched to that in data by applying an additional global correction factor α to all jet momenta before selection. The α calibration values are individually determined for nominal conditions and for each of the variations related to JES and JER. In addition to the selection described in Sect. 4, two btagged jets are required in order to increase the signal purity. The mass of the hadronically decaying W boson is reconstructed as the dijet invariant mass from all combinations of non b-tagged jets. The dijet invariant mass distributions are fitted in data and in simulation with a function describing the W boson signal peak and the dijet combinatorial background. The α values are determined as the ratios of the fitted W boson masses in data and in simulation. In the M b analysis α = 1.011 ± 0.004 is obtained with the nominal samples both in the muon and electron channels, with variations of the order of ±1.5% for the samples with down and up variaTable 3 Components (in %) of the JES uncertainty at 8 TeV in the muon and electron channels. The correlation coefficients used in their combination are also shown tions of the JES. The same values are determined by the M3 analysis. This additional calibration reduces the size of the JES systematic uncertainty by approximately 60%. The JES uncertainty, reported in Table 3, consists of several sources, all propagated individually. Details of the individual contributions are explained in [61]. The impact of the jet energy resolution (JER) is estimated by applying η-dependent variations with an average of ±10%. The JES and JER variations are propagated to the E miss. In addition, the contribution to E miss arising T T from energy depositions not contained in jets is varied by ±10% [60]. The uncertainty related to the pileup modelling is determined by propagating a ±5% variation [62] to the central value of the inelastic cross section. Variations in the composition of the main background processes, W+jets and Z+jets, are conservatively evaluated by varying independently their cross sections by ±30% [63–65]. Additional uncertainties on the heavy flavour component in W/Z+jets production are not explicitly taken into account and are assumed to be covered by the 30% uncertainty. The variation of the normalization of the single top quark background by 30% gives a negligible contribution. The trigger efficiency and lepton identification correction factors are determined with a tag-and-probe method [57] in dilepton events and are varied within their pT- and η-dependent uncertainties. Uncertainties from the b tagging efficiency and mistag rate are evaluated in the M3 analysis by varying the correction factors within their uncertainties [26, 27] quoted in Sect. 8. In the M b analysis, on the other hand, the b tagging efficiency for b jets is measured from data, using the technique described in Refs. [26–28], on the same selected event sample as that for the cross section determination, but before b tagging. The M b variable is used not only as a cross section estimator, but also as a b tagging discriminator. The statistical and systematic uncertainties in the b tagging and mistag efficiencies are propagated to the statistical and systematic uncertainties in the cross section measurements. For this reason the statistical uncertainty obtained by the M b analysis is larger than the one of the M3 analysis. A systematic uncertainty is assigned to the choice, based on simulation, of the b-enriched (for M b values below 140 GeV) and of the b-depleted (for M b in the range 140–240 GeV) regions, by shifting the windows by ±30 GeV. Since the b tagging efficiency and mistag rate are derived from data and since they are re-determined when evaluating the effect of the various systematic uncertainties, no additional uncertainties are included. The method is shown [26–28] to be stable for different b tagging algorithms and working points. Theoretical uncertainties are taken from detailed studies performed on simulated samples. They include the common factorization and renormalization scales, which are varied by a factor of 1/4 and 4 from the default value equal to the Q2 for the tt or W/Z+jet events. The effect of the jet-parton matching threshold on tt and W+jets events is studied by varying the threshold used for matching the matrix element level to the particles created in the parton showering by a factor of 0.5 or 2. Uncertainties from the choice of PDF are evaluated by using the Hessian method [66] with the parameters of the CTEQ6.6 PDF set [67]. Other PDF sets (including their uncertainties) yield very similar results. The PDFs and their uncertainties are determined from a fit to collision data yielding the Hessian matrix. Each of the 22 eigenvectors obtained by diagonalizing the matrix is varied within its uncertainties. The differences with respect to the nominal prediction are determined independently for each eigenvector and are added in quadrature. The systematic uncertainty due to the top quark pT-reweighting procedure described in Sect. 3 is evaluated as the difference with respect to the measurement obtained with the non-reweighted sample. Only the variation due to the template shape is considered, as the correction is meant to modify the shape only. A “signal modelling” uncertainty is attributed to the choice of the generators. It comprises changes in matrix element and parton shower implementation. The effect of the matrix element generator is evaluated by using powheg (instead of MadGraph) interfaced to pythia, while the parton shower modelling is evaluated with powheg and herwig instead of powheg and pythia. Regarding the two corresponding uncertainties, the former is always positive and the latter is always negative. For 7 TeV the same values determined for 8 TeV are used. As discussed in Sect. 7, the “signal modelling” uncertainty is symmetrized by taking the larger of the two contributions (±4.4%). An uncertainty of 2.6% [30] (2.2% [31]) is assigned to the determination of the 2012 (2011) integrated luminosity. The resulting effects from all sources are added in quadrature. Tables 4 and 5 provide an overview of the contributions Table 4 Overview of the systematic uncertainties in the measurement of the tt cross sections at 8 TeV, both for the total and the visible cross sections. For the “signal modelling” uncertainty the larger between the matrix element (ME) and parton shower (PS) uncertainties is taken, as explained in Sect. 6. The correlations assumed for the combination of the muon and electron channels are also given Table 5 Overview of the systematic uncertainties in the measurement of the tt cross sections at 7 TeV, both for the total and the visible cross sections. For the “signal modelling” uncertainty the larger between the matrix element (ME) and parton shower (PS) uncertainties is taken, as explained in Sect. 6. The correlations assumed for the combination of the muon and electron channels are also shown. to the systematic uncertainty on the combined cross section measurements in the M b measurements at 7 and 8 TeV. 7 Results and combination The results in the muon and electron channels, shown in Tables 6 and 7, are in good agreement. The combination of the channel results is performed using the best linear unbiased estimator (BLUE) method [68–70]. Asymmetric systematic uncertainties are symmetrized for the use with BLUE by taking half of the full range, except for the “signal modelling” uncertainty, where the maximum, 4.4%, is taken for σtt. Full correlation is assumed for all systematic uncertainties between the two channels, except for lepton identification and trigger uncertainties, which are assumed to be uncorrelated. Owing to the additional jet energy calibration from data, a correlation coefficient of 0.9 is obtained for the overall JES uncertainty. This correlation is determined from the correlation coefficients in Table 3 and it is compatible with the value inferred by comparing the combined result with and Table 6 Visible cross section measurements at √s = 7 and 8 TeV with the reference analysis M b and the alternative analysis M3 (described in Sect. 8). Results obtained for mt = 172.5 GeV with MadGraph and with powheg are shown. The uncertainties are in the order: statistical, systematic, and due to the luminosity determination Table 7 Total cross section measurements at √s = 7 and 8 TeV with the reference analysis M b and the alternative analysis M3 (described in Sect. 8). Results obtained for mt = 172.5 GeV with MadGraph and with powheg are shown. The uncertainties are in the order: statistical, systematic, and due to the luminosity determination. without the additional calibration. Varying the JES correlation coefficient between 0 and 1 has only a minor effect on the combined results. For example, the total cross section at 8 TeV varies by less than 0.5%, and the cross section ratio varies only by approximately 0.1%. A combination based on the relative statistical precision of the two channels would also yield compatible results. Variations of the correlations of other experimental systematic uncertainties have negligible effect on the combined results. The integrated luminosity and the pileup uncertainties are assumed to be fully correlated between channels at the same centre-of-mass energy, and uncorrelated between 7 and 8 TeV for the cross section ratio. 7.1 Results at √s = 8 TeV The visible cross section obtained from the fit to the M b distribution, using MadGraph signal templates for mt = 172.5 GeV, is = 3.80 ± 0.06 (stat) ± 0.18 (syst) ± 0.10 (lumi) pb. The statistical uncertainty includes the contribution from the simultaneous determination of the b tagging efficiency (see Sect. 6). There is excellent agreement with the measurement of the visible cross section using powheg for the efficiency within the kinematic acceptance selected by this analysis. Using the acceptance values of Table 1, the visible cross section measurements in the electron and muon channels are first extrapolated to the full phase space and then combined to obtain the following total cross section measurement σttth. (8 TeV) = 252.9−+86..64(scale) ± 11.7(PDF+αS ) pb (see Sect. 3), for mt = 172.5 GeV. Table 8 Slope values for the muon and electron channels obtained with linear fits to the cross section values at √s = 8 TeV as a function of the top quark mass. The MadGraph generator is used. The change in sign is due to the acceptance A The BLUE combination yields the following relative weights of the muon and electron channels, and their correlations, respectively. At 8 TeV they are: 1.07 (1.09), −0.07 (−0.09), with correlation coefficient 0.88 (0.91) for the total (visible) cross section, while at 7 TeV they are: 0.50 (0.51), 0.50 (0.49), with correlation coefficient 0.71 (0.65). The negative weights of the electron channel in the combination of the total and visible cross section at 8 TeV depend on the choice of the JES correlation coefficient (0.9) used in the combination. Smaller JES correlation coefficients (0.5 for the total cross section and 0.2 for the visible cross section) would yield positive BLUE weights. The negative weights causes the combined central value, 228.5 pb, to lie outside the interval of the two individual measurements, as summarized in Tables 6 and 7. Alternatively, using powheg instead of MadGraph, the combined total cross section at 8 TeV shifts by +8.6 pb. The difference, at the level of less than 4%, is mainly ascribed to the different acceptance for the two generators. All results are summarized in Tables 6 and 7 for mt = 172.5 GeV. For powheg the same relative systematic uncertainties as determined for MadGraph are used. 7.2 Dependence on the top quark mass at √s = 8 TeV Using simulation, the dependence of the measured total cross section on the top quark mass is determined to be linear in the mt range from 161.5 to 184.5 GeV. The top quark mass value used for the central results is 172.5 GeV. The slope values reported in Table 8 can be used to linearly adjust the results in the two channels to other mass values. For mt = 173.3 GeV [71] the adjusted results of the two channels yield a combined cross section value = 227.4 ± 3.8 (stat) ± 13.7 (syst) ± 6.0 (lumi) pb. 7.3 Results at √s = 7 TeV and cross section ratio = 161.7 ± 6.0 (stat) ± 12.0 (syst) ± 3.6 (lumi) pb. The measurements are in good agreement with the theoretical expectation σttth. (7 TeV) = 177.3+−46..06 (scale) ± 9.0 (PDF+αS) pb at 7 TeV, for a top quark mass of 172.5 GeV. From the measurements of the total cross section at the two centre-of-mass energies, a cross section ratio R8/7 is determined. In the ratio the experimental uncertainties, which are correlated between the two analyses (at √s = 7 or 8 TeV, in each channel) cancel out, leading to an improved precision in comparison to the individual measurements at 7 or 8 TeV. The ratio is first determined in the individual muon (1.45 ± 0.09) and electron (1.41±0.09) channels and then combined. The measured ratio is R8/7 = 1.43 ± 0.04 (stat) ± 0.07 (syst) ± 0.05 (lumi). In the combination of the ratios in the two channels the theoretical uncertainties, and the jet-related uncertainties are assumed to be 100% correlated, except the JES uncertainty, which is taken as 90% correlated. The other experimental uncertainties are assumed to be uncorrelated. The expected values of the cross section ratio, for instance Rt8h/.7 = 1.429 ± 0.001 (scale) ± 0.004 (PDF) ± 0.001 (αs) ± 0.001 (mt) [2], for the MSTW08 PDF set and for mt = 173.3 GeV, are in good agreement with the measurement. 8 Alternative approach at √s = 8 TeV using M3 In the M3 analysis similar requirements for the selection of tt lepton+jets decays are used, with slightly different pTthreshold values. Only the differences with respect to the main selection are summarized in the following. At least four jets are required within |η| < 2.5 and with pT > 50, 40, 30, and 30 GeV in the muon channel, and pT > 50, 45, 35, and 30 GeV in the electron channel. Slightly tighter pT selection criteria are applied in the electron channel because of the larger multijet background. Muons are required to have transverse momentum larger than 26 GeV. In the muon channel no explicit requirement is applied on the missing energy in the transverse plane, while E miss has T to be larger than 20 GeV in the electron channel. The M3 analysis uses a correction factor of (0.95 ± 0.02) [26,27] to the simulated events to reproduce the different b tagging efficiency in data and simulation, and a correction factor of (1.11±0.01±0.12) [26,27] to take into account the different probability that a light-quark or gluon jet is identified as a b jet. These correction factors are determined following Refs. [26,27]. No correction factors are applied in the M b analysis, where these efficiencies are determined from data. Different strategies to take into account the multijet background are developed for the M b and M3 analyses. In the forFig. 3 Distributions of the M3 mass in the 8 TeV data, for the muon+jets (left) and electron+jets (right) channels, rescaled to the template likelihood fit results. The last filled bin includes the overflow mer, this background is reduced to a negligible level thanks to tighter selection requirements on E miss and on the trans T verse momenta of the third and fourth jets. In the M3 analysis, looser selection cuts are chosen and the multijet background is considered further in the analysis. Since MC simulation can not adequately reproduce the shape and normalization of multijet events, this background is thus estimated from data. Selected multijet events mostly consist of semileptonic heavy-flavour decays and, in the electron channel, events in which pions in jets are misidentified as electrons. Such events feature lepton candidates not coming from W boson decays and thus not truly isolated. The shape of the accepted multijet background is extracted from a sideband data sample where leptons have large relative isolation, greater than 0.17 in the muon channel and 0.2 in the electron channel. The data sample is selected such that it is rich in multijet background and poor in tt signal and in other processes such as W+jets. The remaining tt, W+jets and Z+jets contamination is estimated and subtracted using simulation. Other backgrounds, for example single top quark production, are neglected because of their smaller contributions. The nominal multijet shape is taken as the distribution measured in the sideband after subtracting the components described above. The template fit is performed with the M3 distribution in the range 0–1400 GeV. One single template is used for tt events (both for the tt signal events and the other tt events passing the selection requirements) and individual templates are used for each background process. The tt, single top quark, W+jets, and Z+jets templates, used in the likelihood maximization, are taken from simulation, while the multijet template is estimated from data as described above. Because of the similarity between the single top quark and the tt templates, the single top quark contribution is constrained by a Gaussian distribution of 30% width to its expected value. The choice of the constraint has a negligible effect on the final result. The normalization of the signal and background processes, including the multijet background, is determined by the fit itself. The muon and electron channels are combined with the BLUE method to obtain the quoted combined result. The measured cross section with the M3 template fit is = 227.1 ± 2.5 (stat) ± 19.1 (syst) ± 6.0 (lumi) pb. The M3 distributions in the muon and electron channels are shown in Fig. 3. Good agreement is observed between data and the templates. The results are compatible with those of the M b analysis and are summarized in Tables 6 and 7. The main contributions to the systematic uncertainties of the combined result are, in decreasing order: signal modelling (4.4%), factorization and renormalization scales (2.9%), multijet background subtraction (2.2%), JES (2.1%), PDF (1.6%), and b tagging efficiency and mistag rate (1.5%). The uncertainty related to the multijet background subtraction is estimated by evaluating two effects. The subtracted tt, W+jets, and Z+jets contaminations are varied by 50%. In addition, we assign an uncertainty to the assumption that the M3 shape does not vary in different regions of relative lepton isolation, by repeating the analysis in six different intervals of the relative lepton isolation. 9 Summary A measurement of the tt production cross section at √s = 8 TeV is presented, using the data collected with the CMS detector and corresponding to an integrated luminosity of 19.6 fb−1. The analysis is performed in the tt lepton+jets decay channel with one muon or electron and at least four jets in the final state with at least one b-tagged jet. The tt cross section is extracted using a binned maximum-likelihood fit of templates from simulated events to the data sample. The results from the two lepton+jets channels are combined using the BLUE method. Techniques based on control samples in data are used to determine the b tagging efficiency and to calibrate the jet energy scale. These techniques allow for a better determination of the corresponding systematic uncertainties, particularly for the JES, which is a dominant source of experimental uncertainty. In the kinematic range defined in the simulation with exactly one muon, or electron, with pT > 32 GeV and |η| < 2.1, one neutrino with pT > 40 GeV, and at least four jets with pT > 40 GeV and |η| < 2.5, the measured visible tt cross section at √s = 8 TeV is 3.80 ± 0.06 (stat) ± 0.18 (syst) ± 0.10 (lumi) pb. Using the MadGraph generator for the extrapolation to the full phase space, the total tt cross section at 8 TeV is 228.5 ± 3.8 (stat) ± 13.7 (syst) ± 6.0 (lumi) pb. The result of an alternative analysis, which makes use of the observable M3, is in good agreement with this value. Furthermore, the analysis performed using data at √s = 7 TeV, yields a total cross section measurement of 161.7 ± 6.0 (stat) ± 12.0 (syst) ± 3.6 (lumi) pb. The measured cross section ratio, where a number of experimental uncertainties cancel out, is 1.43 ± 0.04 (stat) ± 0.07 (syst) ± 0.05 (lumi). All measurements are in agreement with the NNLO theoretical predictions. Acknowledgements We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at CERN and at other CMS institutes for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centres and personnel of the Worldwide LHC Computing Grid for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies: the Austrian Federal Ministry of Science, Research and Economy and the Austrian Science Fund; the Belgian 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, and the Croatian Science Foundation; the Research Promotion Foundation, Cyprus; the Ministry of Education and Research, Estonian Research Council via IUT23-4 and IUT236 and European Regional Development Fund, Estonia; the Academy of Finland, Finnish Ministry of Education and Culture, and Helsinki Institute of Physics; the Institut National de Physique Nucléaire et de Physique des Particules / CNRS, and Commissariat à l’Énergie Atomique et aux Énergies Alternatives / CEA, France; the Bundesministerium für 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 Innovation Office, Hungary; the Department of Atomic Energy and the 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 Ministry of Science, ICT and Future Planning, and National Research Foundation (NRF), Republic of Korea; the Lithuanian Academy of Sciences; the Ministry of Education, and University of Malaya (Malaysia); the Mexican Funding Agencies (CINVESTAV, CONACYT, SEP, and UASLP-FAI); the Ministry of Business, Innovation and Employment, New Zealand; the Pakistan Atomic Energy Commission; the Ministry of Science and Higher Education and the National Science Centre, Poland; the Fundação para a Ciência e a Tecnologia, Portugal; JINR, Dubna; the Ministry of Education and Science of the Russian Federation, the Federal Agency of Atomic Energy of the Russian Federation, Russian Academy of Sciences, and the Russian Foundation for Basic Research; the Ministry of Education, Science and Technological Development of Serbia; the Secretaría de Estado de Investigación, Desarrollo e Innovación and Programa Consolider-Ingenio 2010, Spain; the Swiss Funding Agencies (ETH Board, ETH Zurich, PSI, SNF, UniZH, Canton Zurich, and SER); the Ministry of Science and Technology, Taipei; the Thailand Center of Excellence in Physics, the Institute for the Promotion of Teaching Science and Technology of Thailand, Special Task Force for Activating Research and the National Science and Technology Development Agency of Thailand; the Scientific and Technical Research Council of Turkey, and Turkish Atomic Energy Authority; the National Academy of Sciences of Ukraine, and State Fund for Fundamental Researches, Ukraine; the Science and Technology Facilities Council, UK; the US Department of Energy, and the US National Science Foundation. Individuals have received support from the Marie-Curie programme and the European Research Council and EPLANET (European Union); the Leventis Foundation; the A. P. Sloan Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science Policy Office; the Fonds pour la Formation à la Recherche dans l’Industrie et dans l’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Council of Science and Industrial Research, India; the HOMING PLUS programme of the Foundation for Polish Science, cofinanced from European Union, Regional Development Fund; the Compagnia di San Paolo (Torino); the Consorzio per la Fisica (Trieste); MIUR project 20108T4XTM (Italy); the Thalis and Aristeia programmes cofinanced by EU-ESF and the Greek NSRF; the National Priorities Research Program by Qatar National Research Fund; the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University (Thailand); and the Welch Foundation. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecomm ons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Funded by SCOAP3. Yerevan Physics Institute, Yerevan, Armenia V. Khachatryan, A. M. Sirunyan, A. Tumasyan National Centre for Particle and High Energy Physics, Minsk, Belarus V. Mossolov, N. Shumeiko, J. Suarez Gonzalez Universiteit Antwerpen, Antwerpen, Belgium S. Alderweireldt, T. Cornelis, E. A. De Wolf, X. Janssen, A. Knutsson, J. Lauwers, S. Luyckx, M. Van De Klundert, H. Van Haevermaet, P. Van Mechelen, N. Van Remortel, A. Van Spilbeeck Vrije Universiteit Brussel, Brussel, Belgium S. Abu Zeid, F. Blekman, J. D’Hondt, N. Daci, I. De Bruyn, K. Deroover, N. Heracleous, J. 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Aldá Júnior, F. L. Alves, G. A. Alves, L. Brito, M. Correa Martins Junior, M. Hamer, C. Hensel, C. Mora Herrera, A. Moraes, M. E. Pol, P. Rebello Teles Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil E. Belchior Batista Das Chagas, W. Carvalho, J. Chinellato7, A. Custódio, E. M. Da Costa, D. De Jesus Damiao, C. De Oliveira Martins, S. Fonseca De Souza, L. M. Huertas Guativa, H. Malbouisson, D. Matos Figueiredo, L. Mundim, H. Nogima, W. L. Prado Da Silva, A. Santoro, A. Sznajder, E. J. Tonelli Manganote7, A. Vilela Pereira Universidade Estadual Paulistaa , Universidade Federal do ABCb, São Paulo, Brazil S. Ahujaa , C. A. Bernardesb, A. De Souza Santosb, S. Dograa , T. R. Fernandez Perez Tomeia , E. M. Gregoresb, P. G. Mercadanteb, C. S. Moona ,8, S. F. Novaesa , Sandra S. Padulaa , D. Romero Abad, J. C. Ruiz Vargas Institute for Nuclear Research and Nuclear Energy, Sofia, Bulgaria A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, M. Rodozov, S. Stoykova, G. Sultanov, M. Vutova Universidad de Los Andes, Bogota, Colombia C. Avila, A. Cabrera, L. F. Chaparro Sierra, C. Florez, J. P. Gomez, B. Gomez Moreno, J. C. Sanabria Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, Split, Croatia N. Godinovic, D. Lelas, I. Puljak, P. M. Ribeiro Cipriano Academy of Scientific Research and Technology of the Arab Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt A. A. Abdelalim11,12, A. Awad13,14, M. El Sawy14,15, A. Mahrous11, A. Radi13,14 National Institute of Chemical Physics and Biophysics, Tallinn, Estonia B. Calpas, M. Kadastik, M. Murumaa, M. Raidal, A. Tiko, C. Veelken Laboratoire Leprince-Ringuet, Ecole Polytechnique, IN2P3-CNRS, Palaiseau, France I. Antropov, S. Baffioni, F. Beaudette, P. Busson, L. Cadamuro, E. Chapon, C. Charlot, T. Dahms, O. Davignon, N. Filipovic, A. Florent, R. Granier de Cassagnac, S. Lisniak, L. Mastrolorenzo, P. Miné, I. N. Naranjo, M. Nguyen, C. Ochando, G. Ortona, P. Paganini, P. Pigard, S. Regnard, R. Salerno, J. B. Sauvan, Y. Sirois, T. Strebler, Y. Yilmaz, A. Zabi Institut Pluridisciplinaire Hubert Curien, Université de Strasbourg, Université de Haute Alsace Mulhouse, CNRS/IN2P3, Strasbourg, France J.-L. Agram16, J. Andrea, A. Aubin, D. Bloch, J.-M. Brom, M. Buttignol, E. C. Chabert, N. Chanon, C. Collard, E. Conte16, X. Coubez, J.-C. Fontaine16, D. Gelé, U. Goerlach, C. Goetzmann, A.-C. Le Bihan, J. A. Merlin2, K. Skovpen, P. Van Hove Centre de Calcul de l’Institut National de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3, Villeurbanne, France S. Gadrat Tbilisi State University, Tbilisi, Georgia Z. Tsamalaidze10 Deutsches Elektronen-Synchrotron, Hamburg, Germany M. Aldaya Martin, I. Asin, N. Bartosik, O. Behnke, U. Behrens, A. J. Bell, K. Borras18, A. Burgmeier, A. Campbell, S. Choudhury19, F. Costanza, C. Diez Pardos, G. Dolinska, S. Dooling, T. Dorland, G. Eckerlin, D. Eckstein, T. Eichhorn, G. Flucke, E. Gallo20, J. Garay Garcia, A. Geiser, A. Gizhko, P. Gunnellini, J. Hauk, M. Hempel21, H. Jung, A. Kalogeropoulos, O. Karacheban21, M. Kasemann, P. Katsas, J. Kieseler, C. Kleinwort, I. Korol, W. Lange, J. Leonard, K. Lipka, A. Lobanov, W. Lohmann21, R. Mankel, I. Marfin21, I.-A. Melzer-Pellmann, A. B. Meyer, G. Mittag, J. Mnich, A. Mussgiller, S. Naumann-Emme, A. Nayak, E. Ntomari, H. Perrey, D. Pitzl, R. Placakyte, A. Raspereza, B. Roland, M. Ö. Sahin, P. Saxena, T. Schoerner-Sadenius, M. Schröder, C. Seitz, S. Spannagel, K. D. Trippkewitz, R. Walsh, C. Wissing University of Hamburg, Hamburg, Germany V. Blobel, M. Centis Vignali, A. R. Draeger, J. Erfle, E. Garutti, K. Goebel, D. Gonzalez, M. Görner, J. Haller, M. Hoffmann, R. S. Höing, A. Junkes, R. Klanner, R. Kogler, N. Kovalchuk, T. Lapsien, T. Lenz, I. Marchesini, D. Marconi, M. Meyer, D. Nowatschin, J. Ott, F. Pantaleo2, T. Peiffer, A. Perieanu, N. Pietsch, J. Poehlsen, D. Rathjens, C. Sander, C. Scharf, H. Schettler, P. Schleper, E. Schlieckau, A. Schmidt, J. Schwandt, V. Sola, H. Stadie, G. Steinbrück, H. Tholen, D. Troendle, E. Usai, L. Vanelderen, A. Vanhoefer, B. Vormwald Institut für Experimentelle Kernphysik, Karlsruhe, Germany M. Akbiyik, C. Barth, C. Baus, J. Berger, C. Böser, E. Butz, T. Chwalek, F. Colombo, W. De Boer, A. Descroix, A. Dierlamm, S. Fink, F. Frensch, R. Friese, M. Giffels, A. Gilbert, D. Haitz, F. Hartmann2, S. M. Heindl, U. Husemann, I. Katkov6, A. Kornmayer2, P. Lobelle Pardo, B. Maier, H. Mildner, M. U. Mozer, T. Müller, Th. Müller, M. Plagge, G. Quast, K. Rabbertz, S. Röcker, F. Roscher, G. Sieber, H. J. Simonis, F. M. Stober, R. Ulrich, J. Wagner-Kuhr, S. Wayand, M. Weber, T. Weiler, C. Wöhrmann, R. Wolf Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece G. Anagnostou, G. Daskalakis, T. Geralis, V. A. Giakoumopoulou, A. Kyriakis, D. Loukas, A. Psallidas, I. Topsis-Giotis National and Kapodistrian University of Athens, Athens, Greece A. Agapitos, S. Kesisoglou, A. Panagiotou, N. Saoulidou, E. Tziaferi National Institute of Science Education and Research, Bhubaneswar, India P. Mal, K. Mandal, D. K. Sahoo, N. Sahoo, S. K. Swain Indian Institute of Science Education and Research (IISER), Pune, India S. Chauhan, S. Dube, K. Kothekar, S. Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran H. Bakhshiansohi, H. Behnamian, S. M. Etesami29, A. Fahim30, R. Goldouzian, M. Khakzad, M. Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi, F. Rezaei Hosseinabadi, B. Safarzadeh31, M. Zeinali University College Dublin, Dublin, Ireland M. Felcini, M. Grunewald INFN Sezione di Baria , Università di Barib, Politecnico di Baric, 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 ,c, S. Nuzzoa ,b, A. Pompilia ,b, G. Pugliesea ,c, R. Radognaa ,b, A. Ranieria , G. Selvaggia ,b, L. Silvestrisa ,2, R. Vendittia ,b, P. Verwilligena INFN Sezione di Cataniaa , Università di Cataniab, Catania, Italy G. Cappelloa , M. Chiorbolia ,b, S. Costaa ,b, A. Di Mattiaa , F. Giordanoa ,b, R. Potenzaa ,b, A. Tricomia ,b, C. Tuvea ,b INFN Laboratori Nazionali di Frascati, Frascati, Italy L. Benussi, S. Bianco, F. Fabbri, D. Piccolo, F. Primavera INFN Sezione di Genovaa , Università di Genovab, Genoa, Italy V. Calvellia ,b, F. Ferroa , M. Lo Veterea ,b, M. R. Mongea ,b, E. Robuttia , S. Tosia ,b INFN Sezione di Milano-Bicoccaa , Università di Milano-Bicoccab, Milan, Italy L. Brianza, M. E. Dinardoa , S. Fiorendia ,b, S. Gennaia , R. Gerosaa ,b, A. Ghezzia ,b, P. Govonia ,b, S. Malvezzia , R. A. Manzonia ,b, B. Marzocchia ,b,2, D. Menascea , L. Moronia , M. Paganonia ,b, D. Pedrinia , S. Ragazzia ,b, N. Redaellia , T. Tabarelli de Fatisa ,b INFN Sezione di Napolia , Università di Napoli Federico II’b, Naples, Italy, Università della Basilicatac, Potenza, Italy, Università G. Marconid , Rome, Italy S. Buontempoa , N. Cavalloa ,c, S. Di Guidaa ,d ,2, M. Espositoa ,b, F. Fabozzia ,c, A. O. M. Iorioa ,b, G. Lanzaa , L. Listaa , S. Meolaa ,d ,2, M. Merolaa , P. Paoluccia ,2, C. Sciaccaa ,b, F. Thyssen INFN Sezione di Padovaa , Università di Padovab, Padova, Italy, Università di Trentoc, Trento, Italy P. Azzia ,b, N. Bacchettaa , L. Benatoa ,b, D. Biselloa ,b, A. Bolettia ,b, A. Brancaa ,b, R. Carlina ,b, P. Checchiaa , M. Dall’Ossoa ,b,2, T. Dorigoa , U. Dossellia , F. Gasparinia ,b, U. Gasparinia ,b, A. Gozzelinoa , K. Kanishcheva ,c, S. Lacapraraa , M. Margonia ,b, A. T. Meneguzzoa ,b, J. Pazzinia ,b, N. Pozzobona ,b, P. Ronchesea ,b, F. Simonettoa ,b, E. Torassaa , M. Tosia ,b, S. Venturaa , M. Zanetti, P. Zottoa ,b, A. Zucchettaa ,b,2, G. Zumerlea ,b INFN Sezione di Paviaa , Università di Paviab, Pavia, Italy A. Braghieria , A. Magnania , P. Montagnaa ,b, S. P. Rattia ,b, V. Rea , C. Riccardia ,b, P. Salvinia , I. Vaia , P. Vituloa ,b INFN Sezione di Perugiaa , Università di Perugiab, Perugia, Italy L. Alunni Solestizia ,b, M. Biasinia ,b, G. M. Bileia , D. Ciangottinia ,b,2, L. Fanòa ,b, P. Laricciaa ,b, G. Mantovania ,b, M. Menichellia , A. Sahaa , A. Santocchiaa ,b INFN Sezione di Pisaa , Università di Pisab, Scuola Normale Superiore di Pisa c, Pisa, Italy K. Androsova ,32, P. Azzurria , G. Bagliesia , J. Bernardinia , T. Boccalia , R. Castaldia , M. A. Cioccia ,32, R. Dell’Orsoa , S. Donatoa ,c,2, G. Fedi, L. Foàa ,c,†, A. Giassia , M. T. Grippoa ,32, F. Ligabuea ,c, T. Lomtadzea , L. Martinia ,b, A. Messineoa ,b, F. Pallaa , A. Rizzia ,b, A. Savoy-Navarroa ,33, A. T. Serbana , P. Spagnoloa , R. Tenchinia , G. Tonellia ,b, A. Venturia , P. G. Verdinia INFN Sezione di Romaa , Università di Romab, Rome, Italy L. Baronea ,b, F. Cavallaria , G. D’imperioa ,b,2, D. Del Rea ,b, M. Diemoza , S. Gellia ,b, C. Jordaa , E. Longoa ,b, F. Margarolia ,b, P. Meridiania , G. Organtinia ,b, R. Paramattia , F. Preiatoa ,b, S. Rahatloua ,b, C. Rovellia , F. Santanastasioa ,b, P. Traczyka ,b,2 Chonbuk National University, Jeonju, Korea J. A. Brochero Cifuentes, H. Kim, T. J. Kim Chonnam National University, Institute for Universe and Elementary Particles, Kwangju, Korea S. Song Vilnius University, Vilnius, Lithuania V. Dudenas, A. Juodagalvis, J. Vaitkus National Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Malaysia I. Ahmed, Z. A. Ibrahim, J. R. Komaragiri, M. A. B. Md Ali34, F. Mohamad Idris35, W. A. T. Wan Abdullah, M. N. Yusli Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico E. Casimiro Linares, H. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-De La Cruz36, A. Hernandez-Almada, R. Lopez-Fernandez, A. Sanchez-Hernandez Universidad Iberoamericana, Mexico City, Mexico S. Carrillo Moreno, F. Vazquez Valencia Benemerita Universidad Autonoma de Puebla, Puebla, Mexico I. Pedraza, H. A. Salazar Ibarguen Universidad Autónoma de San Luis Potosí, San Luis Potosí, Mexico A. Morelos Pineda Laboratório de Instrumentação e Física Experimental de Partículas, Lisboa, Portugal P. Bargassa, C. Beirão Da Cruz E. Silva, A. Di Francesco, P. Faccioli, P. G. Ferreira Parracho, M. Gallinaro, N. Leonardo, L. Lloret Iglesias, F. Nguyen, J. Rodrigues Antunes, J. Seixas, O. Toldaiev, D. Vadruccio, J. Varela, P. Vischia 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, E. Vlasov, A. Zhokin National Research Nuclear University ‘Moscow Engineering Physics Institute’ (MEPhI), Moscow, Russia A. Bylinkin P.N. Lebedev Physical Institute, Moscow, Russia V. Andreev, M. Azarkin39, I. Dremin39, M. Kirakosyan, A. Leonidov39, G. Mesyats, S. V. Rusakov State Research Center of Russian Federation, Institute for High Energy Physics, Protvino, Russia I. Azhgirey, I. Bayshev, S. Bitioukov, V. Kachanov, A. Kalinin, D. Konstantinov, V. Krychkine, V. Petrov, R. Ryutin, A. Sobol, L. Tourtchanovitch, S. Troshin, N. Tyurin, A. Uzunian, A. Volkov Centro de Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain J. Alcaraz Maestre, E. Calvo, M. Cerrada, M. Chamizo Llatas, N. Colino, B. De La Cruz, A. Delgado Peris, D. Domínguez Vázquez, A. Escalante Del Valle, C. Fernandez Bedoya, J. P. Fernández 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. Pérez-Calero Yzquierdo, J. Puerta Pelayo, A. Quintario Olmeda, I. Redondo, L. Romero, J. Santaolalla, M. S. Soares Universidad Autónoma de Madrid, Madrid, Spain C. Albajar, J. F. de Trocóniz, M. Missiroli, D. Moran Universidad de Oviedo, Oviedo, Spain J. Cuevas, J. Fernandez Menendez, S. Folgueras, I. Gonzalez Caballero, E. Palencia Cortezon, J. M. Vizan Garcia Instituto de Física de Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, Spain I. J. Cabrillo, A. Calderon, J. R. Castiñeiras De Saa, P. De Castro Manzano, J. Duarte Campderros, M. Fernandez, J. Garcia-Ferrero, G. Gomez, A. Lopez Virto, J. Marco, R. Marco, C. Martinez Rivero, F. Matorras, F. J. Munoz Sanchez, J. Piedra Gomez, T. Rodrigo, A. Y. Rodríguez-Marrero, A. Ruiz-Jimeno, L. Scodellaro, N. Trevisani, I. Vila, R. Vilar Cortabitarte M. Rovere, M. Ruan, H. Sakulin, C. Schäfer, C. Schwick, M. Seidel, A. Sharma, P. Silva, M. Simon, P. Sphicas45, J. Steggemann, B. Stieger, M. Stoye, Y. Takahashi, D. Treille, A. Triossi, A. Tsirou, G. I. Veres23, N. Wardle, H. K. Wöhri, A. Zagozdzinska37, W. D. Zeuner Paul Scherrer Institut, Villigen, Switzerland W. Bertl, K. Deiters, W. Erdmann, R. Horisberger, Q. Ingram, H. C. Kaestli, D. Kotlinski, U. Langenegger, D. Renker, T. Rohe Institute for Scintillation Materials of National Academy of Science of Ukraine, Kharkov, Ukraine B. Grynyov National Scientific Center, Kharkov Institute of Physics and Technology, Kharkov, Ukraine L. Levchuk, P. Sorokin The University of Alabama, Tuscaloosa, USA O. Charaf, S. I. Cooper, C. Henderson, P. Rumerio Brown University, Providence, USA J. Alimena, E. Berry, S. Bhattacharya, D. Cutts, N. Dhingra, A. Ferapontov, A. Garabedian, J. Hakala, U. Heintz, E. Laird, G. Landsberg, Z. Mao, M. Narain, S. Piperov, S. Sagir, R. Syarif University of California, Davis, Davis, USA R. Breedon, G. Breto, M. Calderon De La Barca Sanchez, S. Chauhan, M. Chertok, J. Conway, R. Conway, P. T. Cox, R. Erbacher, M. Gardner, W. Ko, R. Lander, 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, USA R. Cousins, P. Everaerts, C. Farrell, J. Hauser, M. Ignatenko, D. Saltzberg, E. Takasugi, V. Valuev, M. Weber University of California, Riverside, Riverside, USA K. Burt, R. Clare, J. Ellison, J. W. Gary, G. Hanson, J. Heilman, M. Ivova Paneva, P. Jandir, E. Kennedy, F. Lacroix, O. R. Long, A. Luthra, M. Malberti, M. Olmedo Negrete, A. Shrinivas, H. Wei, S. Wimpenny, B. R. Yates University of California, San Diego, La Jolla, USA J. G. Branson, G. B. Cerati, S. Cittolin, R. T. D’Agnolo, M. Derdzinski, A. Holzner, R. Kelley, D. Klein, J. Letts, I. Macneill, D. Olivito, S. Padhi, M. Pieri, M. Sani, V. Sharma, S. Simon, M. Tadel, A. Vartak, S. Wasserbaech63, C. Welke, F. Würthwein, A. Yagil, G. Zevi Della Porta University of California, Santa Barbara, Santa Barbara, USA J. Bradmiller-Feld, C. Campagnari, A. Dishaw, V. Dutta, K. Flowers, M. Franco Sevilla, P. Geffert, C. George, F. Golf, L. Gouskos, J. Gran, J. Incandela, N. Mccoll, S. D. Mullin, J. Richman, D. Stuart, I. Suarez, C. West, J. Yoo Carnegie Mellon University, Pittsburgh, USA M. B. Andrews, V. Azzolini, A. Calamba, B. Carlson, T. Ferguson, M. Paulini, J. Russ, M. Sun, H. Vogel, I. Vorobiev Fermi National Accelerator Laboratory, Batavia, USA S. Abdullin, M. Albrow, J. Anderson, G. Apollinari, S. Banerjee, L. A. T. Bauerdick, A. Beretvas, J. Berryhill, P. C. Bhat, G. Bolla, K. Burkett, J. N. Butler, H. W. K. Cheung, F. Chlebana, S. Cihangir, V. D. Elvira, I. Fisk, J. Freeman, E. Gottschalk, L. Gray, D. Green, S. Grünendahl, O. Gutsche, J. Hanlon, D. Hare, R. M. Harris, S. Hasegawa, J. Hirschauer, Z. Hu, B. Jayatilaka, S. Jindariani, M. Johnson, U. Joshi, A. W. Jung, B. Klima, B. Kreis, S. Kwan†, S. Lammel, J. Linacre, D. Lincoln, R. Lipton, T. Liu, R. Lopes De Sá, J. Lykken, K. Maeshima, J. M. Marraffino, V. I. Martinez Outschoorn, S. Maruyama, D. Mason, P. McBride, P. Merkel, K. Mishra, S. Mrenna, S. Nahn, C. Newman-Holmes, V. O’Dell, K. Pedro, O. Prokofyev, G. Rakness, E. Sexton-Kennedy, A. Soha, W. J. Spalding, L. Spiegel, L. Taylor, S. Tkaczyk, N. V. Tran, L. Uplegger, E. W. Vaandering, C. Vernieri, M. Verzocchi, R. Vidal, H. A. Weber, A. Whitbeck, F. Yang University of Florida, Gainesville, USA D. Acosta, P. Avery, P. Bortignon, D. Bourilkov, A. Carnes, M. Carver, D. Curry, S. Das, G. P. Di Giovanni, R. D. Field, I. K. Furic, S. V. Gleyzer, J. Hugon, J. Konigsberg, A. Korytov, J. F. Low, P. Ma, K. Matchev, H. Mei, P. Milenovic64, G. Mitselmakher, D. Rank, R. Rossin, L. Shchutska, M. Snowball, D. Sperka, N. Terentyev, L. Thomas, J. Wang, S. Wang, J. Yelton Florida International University, Miami, USA S. Hewamanage, S. Linn, P. Markowitz, G. Martinez, J. L. Rodriguez Florida State University, Tallahassee, USA A. Ackert, J. R. Adams, T. Adams, A. Askew, J. Bochenek, B. Diamond, J. Haas, S. Hagopian, V. Hagopian, K. F. Johnson, A. Khatiwada, H. Prosper, M. Weinberg Florida Institute of Technology, Melbourne, USA M. M. Baarmand, V. Bhopatkar, S. Colafranceschi65, M. Hohlmann, H. Kalakhety, D. Noonan, T. Roy, F. Yumiceva University of Illinois at Chicago (UIC), Chicago, USA 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, C. Silkworth, P. Turner, N. Varelas, Z. Wu, M. Zakaria Johns Hopkins University, Baltimore, USA I. Anderson, B. A. Barnett, B. Blumenfeld, N. Eminizer, D. Fehling, L. Feng, A. V. Gritsan, P. Maksimovic, C. Martin, M. Osherson, J. Roskes, A. Sady, U. Sarica, M. Swartz, M. Xiao, Y. Xin, C. You Kansas State University, Manhattan, USA A. Ivanov, K. Kaadze, S. Khalil, M. Makouski, Y. Maravin, A. Mohammadi, L. K. Saini, N. Skhirtladze, S. Toda Lawrence Livermore National Laboratory, Livermore, USA D. Lange, F. Rebassoo, D. Wright University of Maryland, College Park, USA 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 University of Mississippi, Oxford, USA J. G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, USA E. Avdeeva, K. Bloom, S. Bose, D. R. Claes, A. Dominguez, C. Fangmeier, R. Gonzalez Suarez, R. Kamalieddin, J. Keller, D. Knowlton, I. Kravchenko, F. Meier, J. Monroy, F. Ratnikov, J. E. Siado, G. R. Snow State University of New York at Buffalo, Buffalo, USA M. Alyari, J. Dolen, J. George, A. Godshalk, C. Harrington, I. Iashvili, J. Kaisen, A. Kharchilava, A. Kumar, S. Rappoccio, B. Roozbahani Northeastern University, Boston, USA 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, J. Zhang University of Notre Dame, Notre Dame, USA A. Brinkerhoff, N. Dev, M. Hildreth, C. Jessop, D. J. Karmgard, N. Kellams, K. Lannon, S. Lynch, N. Marinelli, F. Meng, C. Mueller, Y. Musienko38, T. Pearson, M. Planer, A. Reinsvold, R. Ruchti, G. Smith, S. Taroni, N. Valls, M. Wayne, M. Wolf, A. Woodard The Ohio State University, Columbus, USA L. Antonelli, J. Brinson, B. Bylsma, L. S. Durkin, S. Flowers, A. Hart, C. Hill, R. Hughes, W. Ji, K. Kotov, T. Y. Ling, B. Liu, W. Luo, D. Puigh, M. Rodenburg, B. L. Winer, H. W. Wulsin Princeton University, Princeton, USA O. Driga, P. Elmer, J. Hardenbrook, P. Hebda, S. A. Koay, P. Lujan, D. Marlow, T. Medvedeva, M. Mooney, J. Olsen, C. Palmer, P. Piroué, H. Saka, D. Stickland, C. Tully, A. Zuranski Purdue University, West Lafayette, USA V. E. Barnes, D. Benedetti, D. Bortoletto, L. Gutay, M. K. Jha, M. Jones, K. Jung, D. H. Miller, N. Neumeister, B. C. Radburn-Smith, X. Shi, I. Shipsey, D. Silvers, J. Sun, A. Svyatkovskiy, F. Wang, W. Xie, L. Xu Purdue University Calumet, Hammond, USA N. Parashar, J. Stupak University of Rochester, Rochester, USA B. Betchart, A. Bodek, P. de Barbaro, R. Demina, Y. Eshaq, T. Ferbel, M. Galanti, A. Garcia-Bellido, J. Han, A. Harel, O. Hindrichs, A. Khukhunaishvili, G. Petrillo, P. Tan, M. Verzetti Rutgers, The State University of New Jersey, Piscataway, USA S. Arora, A. Barker, J. P. Chou, C. Contreras-Campana, E. Contreras-Campana, D. Duggan, D. Ferencek, Y. Gershtein, R. Gray, E. Halkiadakis, D. Hidas, E. Hughes, S. Kaplan, R. Kunnawalkam Elayavalli, A. Lath, K. Nash, S. Panwalkar, M. Park, S. Salur, S. Schnetzer, D. Sheffield, S. Somalwar, R. Stone, S. Thomas, P. Thomassen, M. Walker University of Tennessee, Knoxville, USA M. Foerster, G. Riley, K. Rose, S. Spanier, A. York University of Virginia, Charlottesville, USA M. W. Arenton, B. Cox, B. Francis, J. Goodell, R. Hirosky, A. Ledovskoy, H. Li, C. Lin, C. Neu, T. Sinthuprasith, X. Sun, Y. Wang, E. Wolfe, J. Wood, F. 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Ostapchuk, M. Preuten. Measurements of the \(\mathrm{t}\overline{\mathrm{t}}\) production cross section in lepton+jets final states in pp collisions at 8 \(\,\text {TeV}\) and ratio of 8 to 7 \(\,\text {TeV}\) cross sections, The European Physical Journal C, 2017, 15, DOI: 10.1140/epjc/s10052-016-4504-z