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

Eur. Phys. J. C (2017) 77:15 DOI 10.1140/epjc/s10052-016-4504-z Regular Article - Experimental Physics 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∗ CERN, 1211 Geneva 23, Switzerland Received: 29 February 2016 / Accepted: 14 November 2016 / Published online: 7 January 2017 © CERN for the benefit of the CMS collaboration 2017. This article is published with open access at Springerlink.com Abstract 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 19.6fb−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 8TeV, 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 mtand 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) e-mail: [email protected] and jets is presented using the 2012 data set at √s=8TeV, collectedbytheCMSexperimentattheLHCandcorresponding to an integrated luminosity of 19.6fb−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 5.0fb−1, has been concurrently analyzed with a similar strategy to the one developed for the cross section measurement at 8TeV. 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 7TeV 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 123 15 Page 2 of 27 Eur. Phys. J. C (2017) 77 :15 the highest transverse momentum in the event (M3)isusedas a discriminant in an alternative analysis. The Mbvariable is related to the leptonic top quark mass, while M3is 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bdistribution, 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. 4is dedicated to the event selection. The analysis technique and the impact of the systematic uncertainties are addressed in Sect. 5and in Sect. 6. The results of the cross section measurements are discussed in Sect. 7. Section 8describes 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 surroundedbyaleadtungstatecrystalelectromagneticcalorimeter (|η|<3.0) and a brass and scintillator hadron calorimeter (|η|<5.0) that provide high-resolution energy and direction measurementsofelectronsandhadronicjets.Muonsaremeasured 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 8TeV pp collisions recorded by the CMS experiment in 2012, corresponding to an integrated luminosity of 19.6±0.5fb−1 [30], and the 2011 data set at √s=7 TeV, corresponding to an integrated luminosity of 5.0±0.2fb −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 pairsaregeneratedatleadingorderwithuptothreeadditional high-pTjets. 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]PDFsetisusedby powheg and the CTEQ6M [37–39]byMadGraph.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+4.6 −6.0(scale) ±9.0(PDF+αS)pb at 7 TeV and 252.9+6.4 −8.6(scale) ±11.7(PDF+αS)pb at 8TeV, 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 renormalizationscales,whilethesecondoneisassociatedtovariations in the PDF and αSfollowing 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]). Thetopquarktransversemomentum is reweightedinsamples simulated with MadGraph and powheg, when interfacedtopythia,inordertobetterdescribethe pTdistribution observed in the data. Based on studies of differential distributions [45,46] in the top quark transverse momentum, an event weight w=√w1w2is applied, where the weights wi of the two top quarks are given as a function of the generated top quark pTvalues: wi=exp(0.199−0.00166 pi T/GeV)at 7TeV, and wi=exp(0.156 −0.00137 pi T/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 123 Eur. Phys. J. C (2017) 77 :15 Page 3 of 27 15 W/Z bosons, constitute the largest background. These are alsosimulatedusingMadGraph withmatrixelementscorresponding to at least one jet and up to four jets. The W/Z+jets eventsaregeneratedinclusivelywithrespecttothejetflavour. Drell–Yan production of charged leptons is generated for dilepton invariant masses above 50 GeV, as those events constitutetherelevantbackground in the phase space of this analysis. The contribution from Drell–Yan events with dilepton invariant masses below 50GeV is negligible, as verified with a sample with a mass range of 10–50GeV. 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 M3analysis (see Sect. 8). In the Mbanalysis 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 correspondingtrackmomentumusingthecombinedinformation 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 p2 Tsum 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, isrequiredtobelessthan0.2.Similarly,forelectrons,thecorresponding 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. Eventswithanelectroncandidatewith|η|<2.5areaccepted by triggers requiring an electron with pT>27 GeV. Tighter pTrequirements 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-electromagneticclustermatching[56],andarerequired tohave pT>32 GeVand|η|<2.5,withtheexclusionofthe 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 havebeendetermined withatag-and-probemethod[57]from data/simulationcomparisonasafunctionofthelepton pTand 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, isolationrequirementsareapplied.Arelativeisolationisdefined as Irel =(Icharged +Iphoton +Ineutral)/pT, where pTis 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 relativeisolation Irel is required to be less than 0.12formuons 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 (Emiss T)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 30GeV in the muon channel and larger than 40GeV 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-kTjet 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 123 15 Page 4 of 27 Eur. Phys. J. C (2017) 77 :15 0 200 400 600 800 1000 1200 CMS 1400 Data signaltt trehtot Single t W/Z+jets (GeV) jet1 T p 0 50 100 150 200 250 300 350 400 450 500 Data / MC Events / 5 GeV 0.6 0.8 1 1.2 (8 TeV) -1 19.6 fb 0 500 1000 1500 2000 CMS 2500 Data tlangist trehtot Single t W/Z+jets (GeV) jet2 T p 0 50 100 150 200 250 300 350 400 450 500 Data / MC Events / 5 GeV 0.6 0.8 1 1.2 (8 TeV) -1 19.6 fb 0 500 1000 1500 2000 CMS 2500 3000 Data tlang i st treh t ot Single t W/Z+jets 0 50 100 150 200 250 300 350 400 450 500 Data / MC Events / 5 GeV 0.6 0.8 1 1.2 1 (8 TeV) -1 19.6 fb μ T p (GeV) 0 200 400 600 800 1000 1200 CMS 1400 Data tlang i st treh t ot Single t W/Z+jets 0 50 100 150 200 250 300 Data / MC Events / 3 GeV 0.6 0.8 1 1.2 (8 TeV) -1 19.6 fb (GeV) jmiss T E Fig. 1 Transverse momentum distributions of the firstand secondleading jet (top), the muon and Emiss Tdistribution (bottom) for all relevant processes in the muon+jets channel with the requirement of at least one b-tagged jet. The simulation is normalized to the standard model cross section values and pT-reweighting is applied to the tt contribution. The multijet background is negligible and not shown. The distributions 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 leastoneofthe jetshastobeidentifiedasabjet.Thebtagging 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 pTand pseudorapidity. Figure 1shows kinematic distributions after applying the b tagging requirement. Good agreement between data and simulation is observed. The Mbanalysis 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 χ2sorting algorithm using top quark and W boson mass constraints. The remaining fourth jet is the b jet candidate assigned to the 123 Eur. Phys. J. C (2017) 77 :15 Page 5 of 27 15 (GeV) bμ M 0 50 100 150 200 250 300 350 400 450 500 Events / 10 GeV 0 500 CMS 1000 1500 2000 2500 Data tt Background /ndf = 0.92 2 χFit (8TeV) -1 19.6 fb (GeV) eb M 0 50 100 150 200 250 300 350 400 450 500 Events / 10 GeV 0 200 400 CMS 600 800 1000 1200 1400 1600 1800 Data tt Background /ndf = 0.73 2 χFit (8 TeV) -1 19.6 fb Fig. 2 Distributions of the lepton-jet mass in the muon+jets (left) and electron+jets (right) channels, rescaled to the fit results leptonically decaying top quark. The b tagging algorithm is only applied to this b jet candidate. Owing to differences in the triggers and in the centre-ofmass energies, in the 7 TeV analysis slightly different selection criteria are applied on the lepton pTand Emiss T.The muon transverse momentum is required to be larger than 26GeV, while the electron pThas to be larger than 30GeV. No explicit Emiss Trequirement is needed in the muon channel. Events with Emiss T>30 GeV are selected in the electron channel. 5 Visible and total cross section measurements The number of tt events is determined with a binned maximum-likelihood fit of distributions (templates), describingsignaland background processes, tothedatasample passing the final selection, by fitting Mb, the invariant mass distribution of the b jet and the lepton. The tt visible (σvis tt) and total (σtt) production cross sections are extracted from the number of tt events observed in the data using the equations σvis tt=Ntt Lεtt ,σ tt =σvis tt A,(1) 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, Lis the integrated luminosity, Ais 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 2shows the results for the fit to the data distributions in the muon and electron channels. 5.1 Acceptance The tt acceptance Acorresponding 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 pTand |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 1for the two generators used in this analysis, MadGraph and powheg. The acceptance values are in agreement at the 1–2% level at 8TeV 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 pTcriteria, i.e. to the pTrequirements of the electron channel at √s=8TeV. The reweighted acceptance is determined as the number of reweighted tt events in the visible phase space, 123 15 Page 6 of 27 Eur. Phys. J. C (2017) 77 :15 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 A(√s=7TeV) A(√s=8TeV) No rew. With rew. No rew. With rew. MadGraph 0.0158 0.0156 0.0166 0.0162 powheg 0.0151 0.0149 0.0163 0.0161 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 1would 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 Theselectionefficiencywithintheacceptance,εtt,isreported 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 muonchannel and21% inthe electron channel is determined. Similar values (37 and 22%, respectively) are obtained at √s=7TeV. 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 crosscheckedbyrepeating 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band the M3measurements. The effect of uncertainties in the JES is evaluated by varying the JES within the pTand 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 αto 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,twobtagged 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 αvalues are determined as the ratios of the fitted W boson masses in data and in simulation. In the Mbanalysis 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 2 Signal selection efficiencies, at √s=8TeV, determined from simulation using MadGraph.The non-reweighted acceptance from Table 1is used. The relative statistical uncertainty on εtt is below 3% Channel εtt (√s=7TeV) (%) Aεtt (√s=7 TeV) (%) εtt (√s=8 TeV) (%) Aεtt (√s=8 TeV) (%) μ+jets 37 0.58 32 0.53 e+jets 22 0.36 21 0.35 123 Eur. Phys. J. C (2017) 77 :15 Page 7 of 27 15 Table 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 Source μ+jets e+jets Correlation Absolute scale ±0.33 ±0.40 0.0 Global jet scale factor α±0.59 ±0.39 0.0 Relative FSR ±0.46 ±0.41 1.0 Relative pT±0.67 ±0.57 1.0 Flavour JES ±1.84 ±1.79 1.0 Flavour JES fragmentation ±0.50 ±0.46 1.0 Flavour JES semileptonic BR ±0.11 ±0.16 1.0 High-pTextra ±0.18 ±0.23 1.0 Single pion ±0.21 ±0.27 1.0 Pileup ±0.35 ±0.31 1.0 Time ±0.17 ±0.24 1.0 Total JES ±2.23 ±2.13 0.9 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 Emiss T. In addition, the contribution to Emiss Tarising 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]tothe 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 pTand η-dependent uncertainties. Uncertaintiesfromthebtaggingefficiencyandmistagrate areevaluatedinthe M3analysisbyvaryingthecorrectionfactorswithin their uncertainties[26,27] quotedin Sect. 8.Inthe Mbanalysis, 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bvariable 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banalysis is larger than the one of the M3analysis. A systematic uncertainty is assigned to the choice, based on simulation, of the b-enriched (for Mbvalues below 140 GeV) and of the b-depleted (for Mbin 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 Q2for the ttorW/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. 3is 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 4and 5provide an overview of the contributions 123 15 Page 8 of 27 Eur. Phys. J. C (2017) 77 :15 Table 4 Overview of the systematic uncertainties in the measurement of the ttcross 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 Systematic uncertainty 8 TeV μ+jets (%) e+jets (%) corr. comb.(%) Jet energy scale ±2.2±2.10.9±2.2 Jet energy resolution ±0.8±0.91.0±0.8 Emiss Tunclustered energy ±0.1±0.31.0±0.1 Pileup ±0.5±0.41.0±0.5 Lepton ID / Trigger eff. corrections ±0.4±0.50.0±0.5 b tagging method ±0.3±0.71.0±0.3 Background composition ±0.2±0.31.0±0.2 Factorization/renormalization scales ±1.7±2.61.0±1.7 ME-PS matching threshold ±1.3±2.31.0±1.2 Top quark pT-reweighting ±1.1±1.21.0±1.1 Signal modelling for σtt (σvis tt)±4.4(±2.2)±4.4(±2.4)1.0 ±4.4(±2.3) PDF uncertainties ±2.1±1.91.0±2.1 Sum for σtt (σvis tt )±6.0(±4.6)±6.5(±5.4)±6.0(±4.7) Integrated luminosity ±2.6±2.61.0±2.6 Total for σtt (σvis tt)±6.5(±5.3)±7.0(±6.0)±6.5(±5.3) Table 5 Overview of the systematic uncertainties in the measurement of the ttcross 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. Systematic uncertainty 7 TeV μ+jets (%) e+jets (%) corr. comb.(%) Jet energy scale ±4.8±5.20.9±4.4 Jet energy resolution ±1.4±1.11.0±1.1 Emiss Tunclustered energy <0.05 ±0.31.0±0.2 Pileup ±0.4±0.61.0±0.5 Lepton ID/trigger eff. corrections ±1.4±1.70.0±0.8 b tagging method ±0.5±0.61.0±0.6 Background composition ±0.5±0.41.0±0.5 Factorization/renormalization scales ±3.7±0.41.0±2.1 ME-PS matching threshold ±2.0±1.71.0±1.8 Top quark pT-reweighting ±1.1±1.21.0±1.1 Signal modelling for σtt (σvis tt)±4.4(±2.2)±4.4(±2.4)1.0 ±4.4(±2.3) PDF uncertainties ±2.3±1.91.0±2.2 Sum for σtt (σvis tt)±8.4(±7.5)±7.7(±6.8)±7.4(±6.4) Integrated luminosity ±2.2±2.21.0±2.2 Total for σtt (σvis tt)±8.7(±7.8)±8.0(±7.1)±7.7(±6.7) to the systematic uncertainty on the combined cross section measurements in the Mbmeasurements at 7 and 8 TeV. 7 Results and combination The results in the muon and electron channels, shown in Tables 6and 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 uncertaintiesbetweenthetwochannels,exceptforleptonidentification 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 3and it is compatible with the value inferred by comparing the combined result with and 123 Eur. Phys. J. C (2017) 77 :15 Page 9 of 27 15 Table 6 Visible cross section measurements at √s=7and 8 TeV with the reference analysis Mband the alternative analysis M3(described in Sect. 8). Results obtained for mt=172.5GeVwith MadGraph and with powheg are shown. The uncertainties are in the order: statistical, systematic, and due to the luminosity determination Analysis Generator Channel σvis ttat √s=8TeV MbMadGraph μ+jets 3.80 ±0.06 ±0.18 ±0.10 pb e+jets 3.90 ±0.07 ±0.21 ±0.10 pb Combined 3.80 ±0.06 ±0.18 ±0.10 pb Mbpowheg Combined 3.83 ±0.06 ±0.18 ±0.10 pb M3MadGraph μ+jets 3.79 ±0.05 ±0.24 ±0.10 pb e+jets 3.75 ±0.04 ±0.26 ±0.10 pb Combined 3.78 ±0.04 ±0.25 ±0.10 pb M3powheg Combined 3.88 ±0.05 ±0.27 ±0.10 pb Analysis Generator Channel σvis ttat √s=7TeV MbMadGraph μ+jets 2.48 ±0.09 ±0.19 ±0.06 pb e+jets 2.62 ±0.10 ±0.18 ±0.06 pb Combined 2.55 ±0.09 ±0.18 ±0.06 pb Table 7 Total cross section measurements at √s=7and 8 TeV with the reference analysis Mband the alternative analysis M3(described in Sect. 8). Results obtained for mt=172.5GeVwith MadGraph and with powheg are shown. The uncertainties are in the order: statistical, systematic, and due to the luminosity determination. Analysis Generator Channel σtt at √s=8TeV MbMadGraph μ+jets 228.9±3.4±13.7±6.0pb e+jets 234.6±3.9±15.2±6.2pb Combined 228.5±3.8±13.7±6.0pb Mbpowheg Combined 237.1±3.9±14.2±6.2pb M3MadGraph μ+jets 228.7±2.6±19.0±6.0pb e+jets 225.8±2.4±19.1±5.9pb Combined 227.1±2.5±19.1±6.0pb M3powheg Combined 238.4±2.8±20.0±6.2pb Analysis Generator Channel σtt at √s=7TeV MbMadGraph μ+jets 157.7±5.5±13.2±3.4pb e+jets 165.8±6.5±12.8±3.6pb Combined 161.7±6.0±12.0±3.6pb 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 8TeV 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 8TeV for the cross section ratio. 7.1 Results at √s=8TeV The visible cross section obtained from the fit to the Mb distribution, using MadGraph signal templates for mt= 172.5GeV,is σvis tt(combined) =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 σtt(combined) =228.5±3.8(stat) ±13.7 (syst) ±6.0(lumi)pb. Themeasurementsareingoodagreementwiththetheoretical prediction σth. tt(8TeV)=252.9+6.4 −8.6(scale) ±11.7(PDF+αS)pb (see Sect. 3), for mt=172.5GeV. 123 15 Page 16 of 27 Eur. Phys. J. C (2017) 77 :15 Institute of High Energy Physics, Beijing, China M. Ahmad, J. G. Bian, G. M. Chen, H. S. Chen, M. Chen, T. Cheng, R. Du, C. H. Jiang, R. Plestina9,F.Romeo, S. M. Shaheen, A. Spiezia, J. Tao, C. Wang, Z. Wang, H. Zhang 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 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 Faculty of Science, University of Split, Split, Croatia Z. Antunovic, M. Kovac Institute Rudjer Boskovic, Zagreb, Croatia V. Brigljevic, K. Kadija, J. Luetic, S. Micanovic, L. Sudic University of Cyprus, Nicosia, Cyprus A. Attikis, G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos, P. A. Razis, H. Rykaczewski Charles University, Prague, Czech Republic M. Bodlak, M. Finger10, M. Finger Jr.10 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.Awad 13,14,M.ElSawy 14,15, 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 Department of Physics, University of Helsinki, Helsinki, Finland P. Eerola, J. Pekkanen, M. Voutilainen 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 Lappeenranta University of Technology, Lappeenranta, Finland J. Talvitie, T. Tuuva DSM/IRFU, CEA/Saclay, Gif-sur-Yvette, France M. Besancon, F. Couderc, M. Dejardin, D. Denegri, B. Fabbro, J. L. Faure, C. Favaro, F. Ferri, S. Ganjour, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry, E. Locci, M. Machet, J. Malcles, J. Rander, A. Rosowsky, M. Titov, A. Zghiche 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 123 Eur. Phys. J. C (2017) 77 :15 Page 17 of 27 15 Centre de Calcul de l’Institut National de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3, Villeurbanne, France S. Gadrat 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 Georgian Technical University, Tbilisi, Georgia T. Toriashvili17 Tbilisi State University, Tbilisi, Georgia Z. Tsamalaidze10 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. Zhukov6 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 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. Lingemann2, A. Nehrkorn, A. Nowack, I. M. Nugent, C. Pistone, O. Pooth, A. Stahl 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 123 15 Page 18 of 27 Eur. Phys. J. C (2017) 77 :15 National and Kapodistrian University of Athens, Athens, Greece A. Agapitos, S. Kesisoglou, A. Panagiotou, N. Saoulidou, E. Tziaferi University of Ioánnina, Ioánnina, Greece I. Evangelou, G. Flouris, C. Foudas, P. Kokkas, N. Loukas, N. Manthos, I. Papadopoulos, E. Paradas, J. Strologas Wigner Research Centre for Physics, Budapest, Hungary G. Bencze, C. Hajdu, A. Hazi, P. Hidas, D. Horvath22, F. Sikler, V. Veszpremi, G. Vesztergombi23, A. J. Zsigmond Institute of Nuclear Research ATOMKI, Debrecen, Hungary N. Beni, S. Czellar, J. Karancsi24, J. Molnar, Z. Szillasi University of Debrecen, Debrecen, Hungary M. Bartók25, A. Makovec, P. Raics, Z. L. Trocsanyi, B. Ujvari National Institute of Science Education and Research, Bhubaneswar, India P. Mal, K. Mandal, D. K. Sahoo, N. Sahoo, S. K. Swain Panjab University, Chandigarh, India S. Bansal, S. B. Beri, V. Bhatnagar, R. Chawla, R. Gupta, U. Bhawandeep, A. K. Kalsi, A. Kaur, M. Kaur, R. Kumar, A. Mehta, M. Mittal, J. B. Singh, G. Walia University of Delhi, Delhi, India Ashok Kumar, A. Bhardwaj, B. C. Choudhary, R. B. Garg, A. Kumar, S. Malhotra, M. Naimuddin, N. Nishu, K. Ranjan, R. Sharma, V. Sharma 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 Bhabha Atomic Research Centre, Mumbai, India A. Abdulsalam, R. Chudasama, D. Dutta, V. Jha, V. Kumar, A. K. Mohanty2, L. M. Pant, P. Shukla, A. Topkar Tata Institute of Fundamental Research, Mumbai, India T. Aziz, S. Banerjee, S. Bhowmik26, R. M. Chatterjee, R. K. Dewanjee, S. Dugad, S. Ganguly, S. Ghosh, M. Guchait, A. Gurtu27, G. Kole, S. Kumar, B. Mahakud, M. Maity26, G. Majumder, K. Mazumdar, S. Mitra, G. B. Mohanty, B. Parida, T. Sarkar26, N. Sur, B. Sutar, N. Wickramage28 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.Cristella a,b, N. De Filippisa,c, M. De Palmaa,b,L.Fiore a, G. Iasellia,c, G. Maggia,c, M. Maggia, G. Minielloa,b,S.My a,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 Bolognaa, Università di Bolognab, Bologna, Italy G. Abbiendia, C. Battilana2, A. C. Benvenutia, D. Bonacorsia,b, S. Braibant-Giacomellia,b, L. Brigliadoria,b, R. Campaninia,b, P. Capiluppia,b,A.Castro a,b, F. R. Cavalloa,S.S.Chhibra a,b, G. Codispotia,b, M. Cuffiania,b, G. M. Dallavallea, F. Fabbria, A. Fanfania,b, D. Fasanellaa,b, P. Giacomellia, C. Grandia, L. Guiduccia,b, S. Marcellinia, G. Masettia, A. Montanaria,F.L.Navarria a,b, A. Perrottaa,A.M.Rossi a,b, T. Rovellia,b,G.P.Siroli a,b,N.Tosi a,b, R. Travaglinia,b 123 Eur. Phys. J. C (2017) 77 :15 Page 19 of 27 15 INFN Sezione di Cataniaa, Università di Cataniab, Catania, Italy G. Cappelloa, M. Chiorbolia,b,S.Costa a,b, A. Di Mattiaa, F. Giordanoa,b, R. Potenzaa,b, A. Tricomia,b,C.Tuve a,b INFN Sezione di Firenzea, Università di Firenzeb, Florence, Italy G. Barbaglia, V. Ciullia,b, C. Civininia, R. D’Alessandroa,b, E. Focardia,b, S. Gonzia,b,V.Gori a,b, P. Lenzia,b, M. Meschinia, S. Paolettia, G. Sguazzonia, A. Tropianoa,b, L. Viliania,b,2 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.Ferro a, M. Lo Veterea,b, M. R. Mongea,b, E. Robuttia,S.Tosi a,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.Govoni a,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.DiGuida a,d,2, M. Espositoa,b, F. Fabozzia,c,A.O.M.Iorio a,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.Dorigo a, 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.Tosi a,b, S. Venturaa,M.Zanetti,P.Zotto a,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.Ratti a,b,V.Re a, C. Riccardia,b, P. Salvinia,I.Vai a, P. Vituloa,b INFN Sezione di Perugiaa, Università di Perugiab, Perugia, Italy L. Alunni Solestizia,b,M.Biasini a,b,G.M.Bilei a, 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’Orso a, S. Donatoa,c,2, G. Fedi, L. Foàa,c,†, A. Giassia,M.T.Grippo a,32,F.Ligabue a,c, T. Lomtadzea, L. Martinia,b, A. Messineoa,b,F.Palla a, A. Rizzia,b, A. Savoy-Navarroa,33, A. T. Serbana, P. Spagnoloa, R. Tenchinia,G.Tonelli a,b, A. Venturia, P. G. Verdinia INFN Sezione di Romaa, Università di Romab, Rome, Italy L. Baronea,b,F.Cavallari a, G. D’imperioa,b,2,D.DelRe a,b,M.Diemoz a, S. Gellia,b,C.Jorda a, E. Longoa,b, F. Margarolia,b, P. Meridiania, G. Organtinia,b, R. Paramattia, F. Preiatoa,b,S.Rahatlou a,b,C.Rovelli a, F. Santanastasioa,b, P. Traczyka,b,2 INFN Sezione di Torinoa, Università di Torinob, Turin, Italy, Università del Piemonte Orientale c, Novara, Italy N. Amapanea,b, R. Arcidiaconoa,c,2,S.Argiro a,b, M. Arneodoa,c, R. Bellana,b, C. Biinoa, N. Cartigliaa,M.Costa a,b, R. Covarellia,b, A. Deganoa,b, N. Demariaa,L.Finco a,b,2, B. Kiania,b, C. Mariottia, S. Masellia, E. Migliorea,b, V. Monacoa,b, E. Monteila,b,M.M.Obertino a,b, L. Pachera,b, N. Pastronea, M. Pelliccionia, G. L. Pinna Angionia,b, F. Raveraa,b, A. Romeroa,b, M. Ruspaa,c, R. Sacchia,b, A. Solanoa,b,A.Staiano a, U. Tamponia INFN Sezione di Triestea, Università di Triesteb, Trieste, Italy S. Belfortea, V. Candelisea,b,2, M. Casarsaa,F.Cossutti a, G. Della Riccaa,b, B. Gobboa,C.LaLicata a,b, M. Maronea,b, A. Schizzia,b, A. Zanettia Kangwon National University, Chunchon, Korea A. Kropivnitskaya, S. K. Nam 123 15 Page 20 of 27 Eur. Phys. J. C (2017) 77 :15 Kyungpook National University, Daegu, Korea D. H. Kim, G. N. Kim, M. S. Kim, D. J. Kong, S. Lee, Y. D. Oh, A. Sakharov, D. C. Son 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 Korea University, Seoul, Korea S. Choi, Y. Go, D. Gyun, B. Hong, M. Jo, H. Kim, Y. Kim, B. Lee, K. Lee, K. S. Lee, S. Lee, S. K. Park, Y. Roh Seoul National University, Seoul, Korea H. D. Yoo University of Seoul, Seoul, Korea M.Choi,H.Kim,J.H.Kim,J.S.H.Lee,I.C.Park,G.Ryu,M.S.Ryu Sungkyunkwan University, Suwon, Korea Y.Choi,J.Goh,D.Kim,E.Kwon,J.Lee,I.Yu Vilnius University, Vilnius, Lithuania V. Dudenas, A. Juodagalvis, J. Vaitkus National Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Malaysia I. Ahmed, Z. A. Ibrahim, J. R. Komaragiri, M. A. B. Md 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 University of Auckland, Auckland, New Zealand D. Krofcheck University of Canterbury, Christchurch, New Zealand P. H. Butler 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 National Centre for Nuclear Research, Swierk, Poland H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Górski, M. Kazana, K. Nawrocki, K. Romanowska-Rybinska, M. Szleper, P. Zalewski Faculty of Physics, Institute of Experimental Physics University of Warsaw, Warsaw, Poland G. Brona, K. Bunkowski, A. Byszuk37, K. Doroba, A. Kalinowski, M. Konecki, J. Krolikowski, M. Misiura, M. Olszewski, M. Walczak 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 Joint Institute for Nuclear Research, Dubna, Russia S. Afanasiev, P. Bunin, M. Gavrilenko, I. Golutvin, I. Gorbunov, A. Kamenev, V. Karjavin, V. Konoplyanikov, A. Lanev, 123 Eur. Phys. J. C (2017) 77 :15 Page 21 of 27 15 A. Malakhov, V. Matveev38,39, P. Moisenz, V. Palichik, V. Perelygin, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, A. Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia V. Golovtsov , Y. Ivanov , V. Kim 40, E. Kuznetsova, P. Levchenko, V. Murzin, V. Oreshkin, I. Smirnov, V. Sulimov, L. Uvarov, S. Vavilov, A. Vorobyev Institute for Nuclear Research, Moscow, Russia Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov, N. Krasnikov, A. Pashenkov, D. Tlisov, A. Toropin Institute for Theoretical and Experimental Physics, Moscow, Russia V. Epshteyn, V. Gavrilov, N. Lychkovskaya, V. Popov, I. Pozdnyakov, G. Safronov, A. Spiridonov, 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.Dremin 39, M. Kirakosyan, A. Leonidov39, G. Mesyats, S. V. Rusakov Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia A. Baskakov, A. Belyaev, E. Boos, V. Bunichev, M. Dubinin41, L. Dudko, A. Ershov, A. Gribushin, V. Klyukhin, N. Korneeva, I. Lokhtin, I. Myagkov, S. Obraztsov, M. Perfilov, V. Savrin 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 Faculty of Physics and Vinca Institute of Nuclear Sciences, University of Belgrade, Belgrade, Serbia P. Adzic42,J.Milosevic,V.Rekovic 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 CERN, European Organization for Nuclear Research, Geneva, Switzerland D. Abbaneo, E. Auffray, G. Auzinger, M. Bachtis, P. Baillon, A. H. Ball, D. Barney, A. Benaglia, J. Bendavid, L. Benhabib, J. F. Benitez, G. M. Berruti, P. Bloch, A. Bocci, A. Bonato, C. Botta, H. Breuker, T. Camporesi, R. Castello, G. Cerminara, M. D’Alfonso, D. d’Enterria, A. Dabrowski, V. Daponte, A. David, M. De Gruttola, F. De Guio, A. De Roeck, S. De Visscher, E. Di Marco, M. Dobson, M. Dordevic, B. Dorney, T. du Pree, M. Dünser, N. Dupont, A. Elliott-Peisert, G. Franzoni, W. Funk, D. Gigi, K. Gill, D. Giordano, M. Girone, F. Glege, R. Guida, S. Gundacker, M. Guthoff, J. Hammer, P. Harris, J. Hegeman, V. Innocente, P. Janot, H. Kirschenmann, M. J. Kortelainen, K. Kousouris, K. Krajczar, P. Lecoq, C. Lourenço, M. T. Lucchini, N. Magini, L. Malgeri, M. Mannelli, A. Martelli, L. Masetti, F. Meijers, S. Mersi, E. Meschi, F. Moortgat, S. Morovic, M. Mulders, M. V. Nemallapudi, H. Neugebauer, S. Orfanelli43, L. Orsini, L. Pape, E. Perez, M. Peruzzi, A. Petrilli, G. Petrucciani, A. Pfeiffer, D. Piparo, A. Racz, G. Rolandi44, 123 15 Page 22 of 27 Eur. Phys. J. C (2017) 77 :15 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 Particle Physics, ETH Zurich, Zurich, Switzerland F. Bachmair, L. Bäni, L. Bianchini, B. Casal, G. Dissertori, M. Dittmar, M. Donegà, P. Eller, C. Grab, C. Heidegger, D. Hits, J. Hoss, G. Kasieczka, W. Lustermann, B. Mangano, M. Marionneau, P. Martinez Ruiz del Arbol, M. Masciovecchio, D. Meister, F. Micheli, P. Musella, F. Nessi-Tedaldi, F. Pandolfi, J. Pata, F. Pauss, L. Perrozzi, M. Quittnat, M. Rossini, A. Starodumov46, M. Takahashi, V. R. Tavolaro, K. Theofilatos, R. Wallny Universität Zürich, Zurich, Switzerland T. K. Aarrestad, C. Amsler47, L. Caminada, M. F. Canelli, V. Chiochia, A. De Cosa, C. Galloni, A. Hinzmann, T. Hreus, B. Kilminster, C. Lange, J. Ngadiuba, D. Pinna, P. Robmann, F. J. Ronga, D. Salerno, Y. Yang National Central University, Chung-Li, Taiwan M. Cardaci, K. H. Chen, T. H. Doan, Sh. Jain, R. Khurana, M. Konyushikhin, C. M. Kuo, W. Lin, Y. J. Lu, S. S. Yu National Taiwan University (NTU), Taipei, Taiwan Arun Kumar, R. Bartek, P. Chang, Y. H. Chang, Y. W. Chang, Y. Chao, K. F. Chen, P. H. Chen, C. Dietz, F. Fiori, U. Grundler, W.-S. Hou, Y. Hsiung, Y. F. Liu, R.-S. Lu, M. Miñano Moya, E. Petrakou, J. f. Tsai, Y. M. Tzeng Department of Physics, Faculty of Science, Chulalongkorn University, Bangkok, Thailand B. Asavapibhop, K. Kovitanggoon, G. Singh, N. Srimanobhas, N. Suwonjandee Cukurova University, Adana, Turkey A. Adiguzel, S. Cerci48, Z. S. Demiroglu, C. Dozen, I. Dumanoglu, S. Girgis, G. Gokbulut, Y. Guler, E. Gurpinar, I. Hos, E. E. Kangal49, A. Kayis Topaksu, G. Onengut50, K. Ozdemir51, S. Ozturk52,B.Tali 48, H. Topakli52, M. Vergili, C. Zorbilmez Physics Department, Middle East Technical University, Ankara, Turkey I. V. Akin, B. Bilin, S. Bilmis, B. Isildak53, G. Karapinar54, M. Yalvac, M. Zeyrek Bogazici University, Istanbul, Turkey E. Gülmez, M. Kaya55, O. Kaya56,E.A.Yetkin 57,T.Yetkin 58 Istanbul Technical University, Istanbul, Turkey A. Cakir, K. Cankocak, S. Sen59, F. I. Vardarlı 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 University of Bristol, Bristol, UK R. Aggleton, F. Ball, L. Beck, J. J. Brooke, E. Clement, D. Cussans, H. Flacher, J. Goldstein, M. Grimes, G. P. Heath, H. F. Heath, J. Jacob, L. Kreczko, C. Lucas, Z. Meng, D. M. Newbold60, S. Paramesvaran, A. Poll, T. Sakuma, S. Seif El Nasr-storey, S. Senkin, D. Smith, V. J. Smith Rutherford Appleton Laboratory, Didcot, UK K. W. Bell, A. Belyaev61, C. Brew, R. M. Brown, L. Calligaris, D. Cieri, D. J. A. Cockerill, J. A. Coughlan, K. Harder, S. Harper, E. Olaiya, D. Petyt, C. H. Shepherd-Themistocleous, A. Thea, I. R. Tomalin, T. Williams, W. J. Womersley, S. D. Worm 123 Eur. Phys. J. C (2017) 77 :15 Page 23 of 27 15 Imperial College, London, UK M. Baber, R. Bainbridge, O. Buchmuller, A. Bundock, D. Burton, S. Casasso, M. Citron, D. Colling, L. Corpe, N. Cripps, P. Dauncey, G. Davies, A. De Wit, M. Della Negra, P. Dunne, A. Elwood, W. Ferguson, J. Fulcher, D. Futyan, G. Hall, G. Iles, M. Kenzie, R. Lane, R. Lucas60, L. Lyons, A.-M. Magnan, S. Malik, J. Nash, A. Nikitenko46, J. Pela, M. Pesaresi, K. Petridis, D. M. Raymond, A. Richards, A. Rose, C. Seez, A. Tapper, K. Uchida, M. Vazquez Acosta62, T. Virdee, S. C. Zenz Brunel University, Uxbridge, UK J. E. Cole, P. R. Hobson, A. Khan, P. Kyberd, D. Leggat, D. Leslie, I. D. Reid, P. Symonds, L. Teodorescu, M. Turner Baylor University, Waco, USA A. Borzou, K. Call, J. Dittmann, K. Hatakeyama, H. Liu, N. Pastika The University of Alabama, Tuscaloosa, USA O. Charaf, S. I. Cooper, C. Henderson, P. Rumerio 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 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 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 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 University of Colorado Boulder, Boulder, USA J. P. Cumalat, W. T. Ford, A. Gaz, F. Jensen, A. Johnson, M. Krohn, T. Mulholland, U. Nauenberg, K. Stenson, S. R. Wagner Cornell University, Ithaca, USA J. Alexander, A. Chatterjee, J. Chaves, J. Chu, S. Dittmer, N. Eggert, N. Mirman, G. Nicolas Kaufman, J. R. Patterson, A. Rinkevicius, A. Ryd, L. Skinnari, L. Soffi, W. Sun, S. M. Tan, W. D. Teo, J. Thom, J. Thompson, J. Tucker, Y. Weng, P. Wittich 123 15 Page 24 of 27 Eur. Phys. J. C (2017) 77 :15 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 The University of Iowa, Iowa City, USA B. Bilki66, W. Clarida, K. Dilsiz, S. Durgut, R. P. Gandrajula, M. Haytmyradov, V. Khristenko, J.-P. Merlo, H. Mermerkaya67, A. Mestvirishvili, A. Moeller, J. Nachtman, H. Ogul, Y. Onel, F. Ozok57, A. Penzo, C. Snyder, E. Tiras, J. Wetzel, K. Yi 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 The University of Kansas, Lawrence, USA P. Baringer, A. Bean, G. Benelli, C. Bruner, R. P. Kenny III, D. Majumder, M. Malek, M. Murray, S. Sanders, R. Stringer, Q. Wang 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 123 Eur. Phys. J. C (2017) 77 :15 Page 25 of 27 15 Massachusetts Institute of Technology, Cambridge, USA A. Apyan, R. Barbieri, A. Baty, K. Bierwagen, S. Brandt, W. Busza, I. A. Cali, Z. Demiragli, L. Di Matteo, G. Gomez Ceballos, M. Goncharov, D. Gulhan, Y. Iiyama, G. M. Innocenti, M. Klute, D. Kovalskyi, Y. S. Lai, Y.-J. Lee, A. Levin, P. D. Luckey, A. C. Marini, C. Mcginn, C. Mironov, S. Narayanan, X. Niu, C. Paus, D. Ralph, C. Roland, G. Roland, J. Salfeld-Nebgen, G. S. F. Stephans, K. Sumorok, M. Varma, D. Velicanu, J. Veverka, J. Wang, T. W. Wang, B. Wyslouch, M. Yang, V. Zhukova University of Minnesota, Minneapolis, USA B. Dahmes, A. Evans, A. Finkel, A. Gude, P. Hansen, S. Kalafut, S. C. Kao, K. Klapoetke, Y. Kubota, Z. Lesko, J. Mans, S. Nourbakhsh, N. Ruckstuhl, R. Rusack, N. Tambe, J. Turkewitz 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 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 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 University of Puerto Rico, Mayaguez, USA S. Malik 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 Rice University, Houston, USA A. Adair, B. Akgun, Z. Chen, K. M. Ecklund, F. J. M. Geurts, M. Guilbaud, W. Li, B. Michlin, M. Northup, B. P. Padley, R. Redjimi, J. Roberts, J. Rorie, Z. Tu, J. Zabel University of Rochester, Rochester, 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 123