Measurements of the $$\mathrm {p}\mathrm {p}\rightarrow \mathrm{Z}\mathrm{Z}$$ production cross section and the $$\mathrm{Z}\rightarrow 4\ell $$Z→4ℓ branching fraction, and constraints on anomalous triple gauge couplings at $$\sqrt{s} = 13\,\text {TeV} $$s=13TeV

Eur. Phys. J. C Measurements of the pp → ZZ production cross section and the Z → 4 branching fraction, and constraints on anomalous triple √ gauge couplings at s = 13 TeV CMS Collaboration 0 1 2 3 6 7 0 CERN , 1211 Geneva 23 , Switzerland 1 Universiteit Antwerpen, Antwerpen, Belgium E. A. De Wolf , D. Di Croce, X. Janssen, J. Lauwers, M. Van De Klundert, H. Van Haevermaet, P. Van Mechelen, N. Van Remortel 2 University of Split, Faculty of Science , Split , Croatia Z. Antunovic, M. Kovac 3 Wigner Research Centre for Physics , Budapest, Hungary G. Bencze, C. Hajdu, D. Horvath 4 , Á. Hunyadi , F. Sikler, V. Veszpremi, G. Vesztergombi 5 , A. J. Zsigmond 6 Joint Institute for Nuclear Research , Dubna, Russia S. Afanasiev, P. Bunin, M. Gavrilenko, I. Golutvin, I. Gorbunov, A. Kamenev, V. Karjavin, A. Lanev, A. Malakhov, V. Matveev 7 Institute of Experimental Physics, Faculty of Physics, University of Warsaw , Warsaw , Poland K. Bunkowski, A. Byszuk 8 , K. Doroba , A. Kalinowski, M. Konecki, J. Krolikowski, M. Misiura, M. Olszewski, A. Pyskir, M. Walczak Four-lepton production in proton-proton collisions, pp → (Z/γ ∗)(Z/γ ∗) → 4 , where = e or μ, is studied at a center-of-mass energy of 13 TeV with the CMS detector at the LHC. The data sample corresponds to an integrated luminosity of 35.9 fb−1. The ZZ production cross section, σ (pp → ZZ) = 17.2 ± 0.5 (stat) ± 0.7 (syst) ± 0.4 (theo) ± 0.4 (lumi) pb, measured using events with two opposite-sign, same-flavor lepton pairs produced in the mass region 60 < m + − < 120 GeV, is consistent with standard model predictions. Differential cross sections are measured and are well described by the theoretical predictions. The Z boson branching fraction to four leptons is measured to be mass in the range 80 < m4 < 100 GeV and a dilepton mass m > 4 GeV for all opposite-sign, same-flavor lepton pairs. The results agree with standard model predictions. The invariant mass distribution of the four-lepton system is used to set limits on anomalous ZZZ and ZZγ couplings at 95% confidence level: − 0.0012 < f4Z < 0.0010, − 0.0010 < f5Z < 0.0013, − 0.0012 < f4γ < 0.0013, − 0.0012 < f5γ < 0.0013. - 1 Introduction Measurements of diboson production at the CERN LHC allow precision tests of the standard model (SM). In the SM, ZZ production proceeds mainly through quark-antiquark t and u-channel scattering diagrams. In calculations at higher orders in quantum chromodynamics (QCD), gluon-gluon fusion also contributes via box diagrams with quark loops. There are no tree-level contributions to ZZ production from triple gauge boson vertices in the SM. Anomalous triple gauge couplings (aTGC) could be induced by new physics models such as supersymmetry [ 1 ]. Nonzero aTGCs may be parametrized using an effective Lagrangian as in Ref. [ 2 ]. In this formalism, two ZZZ and two ZZγ couplings are allowed by electromagnetic gauge invariance and Lorentz invariance for on-shell Z bosons. These are described by two CP-violating ( f4V) and two CP-conserving ( f5V) parameters, where V = Z or γ . Previous measurements of the ZZ production cross section by the CMS Collaboration were performed for pairs of on-shell Z bosons, produced in the dilepton mass range 60– 120 GeV [ 3–6 ]. These measurements were made with data sets corresponding to integrated luminosities of 5.1 fb−1 at √s = 7 TeV and 19.6 fb−1 at √s = 8 TeV in the ZZ → 2 2 and ZZ → 2 2ν decay channels, where = e or μ and = e, μ, or τ , and with an integrated luminosity of 2.6 fb−1 at √s = 13 TeV in the ZZ → 2 2 decay channel, where = e or μ. All of them agree with SM predictions. The ATLAS Collaboration produced similar results at √s = 7, 8, and 13 TeV [ 7–10 ], which also agree with the SM. These measurements are important for testing predictions that were recently made available at next-to-nextto-leading order (NNLO) in QCD [ 11 ]. Comparing these predictions with data at a range of center-of-mass energies provides information about the electroweak gauge sector of the SM. Because the uncertainty of the CMS measurement at √s = 13 TeV [ 6 ] was dominated by the statistical uncertainty of the observed data, repeating and extending the measurement with a larger sample of proton-proton collision data at √s = 13 TeV improves the precision of the results. The most stringent previous limits on ZZZ and ZZγ aTGCs from CMS were set using the 7 and 8 TeV data samples: − 0.0022 < f4Z < 0.0026, − 0.0023 < f5Z < 0.0023, − 0.0029 < f4γ < 0.0026, and − 0.0026 < f5γ < 0.0027 at 95% confidence level (CL) [ 4,5 ]. Similar limits were obtained by the ATLAS Collaboration [12], who also recently produced limits using 13 TeV data [ 10 ]. Extending the dilepton mass range to lower values allows measurements of (Z/γ ∗) (Z/γ ∗) production, where Z indicates an on-shell Z boson or an off-shell Z∗ boson. The resulting sample includes Higgs boson events in the H → ZZ∗ → 2 2 channel, and rare decays of a single Z boson to four leptons. The Z → + −γ ∗ → 2 2 decay was studied in detail at LEP [ 13 ] and was observed in pp collisions by CMS [ 6,14 ] and ATLAS [15]. Although the branching fraction for this decay is orders of magnitude smaller than that for the Z → + − decay, the precisely known mass of the Z boson makes the four-lepton mode useful for calibrating mass measurements of the nearby Higgs boson resonance. This paper reports a study of four-lepton production (pp → 2 2 , where 2 and 2 indicate opposite-sign pairs of electrons or muons) at √s = 13 TeV with a data set corresponding to an integrated luminosity of 35.9 ± 0.9 fb−1 recorded in 2016. Cross sections are measured for nonresonant production of pairs of Z bosons, pp → ZZ, where both Z bosons are produced on-shell, defined as the mass range 60– 120 GeV, and resonant pp → Z → 4 production. Detailed discussion of resonant Higgs boson production decaying to ZZ∗, is beyond the scope of this paper and may be found in Ref. [ 16 ]. 2 The CMS detector A detailed description of the CMS detector, together with a definition of the coordinate system used and the relevant kinematic variables, can be found in Ref. [ 17 ]. The central feature of the CMS apparatus is a superconducting solenoid of 6 m internal diameter, providing a magnetic field of 3.8 T. Within the solenoid volume are a silicon pixel and strip tracker, a lead tungstate crystal electromagnetic calorimeter (ECAL), and a brass and scintillator hadron calorimeter, which provide coverage in pseudorapidity |η| < 1.479 in a cylindrical barrel and 1.479 < |η| < 3.0 in two endcap regions. Forward calorimeters extend the coverage provided by the barrel and endcap detectors to |η| < 5.0. Muons are measured in gas-ionization detectors embedded in the steel flux-return yoke outside the solenoid in the range |η| < 2.4, with detection planes made using three technologies: drift tubes, cathode strip chambers, and resistive plate chambers. Electron momenta are estimated by combining energy measurements in the ECAL with momentum measurements in the tracker. The momentum resolution for electrons with transverse momentum pT ≈ 45 GeV from Z → e+e− decays ranges from 1.7% for nonshowering electrons in the barrel region to 4.5% for showering electrons in the endcaps [ 18 ]. Matching muons to tracks identified in the silicon tracker results in a pT resolution for muons with 20 < pT < 100 GeV of 1.3–2.0% in the barrel and better than 6% in the endcaps. The pT resolution in the barrel is better than 10% for muons with pT up to 1 TeV [ 19 ]. 3 Signal and background simulation Signal events are generated with powheg 2.0 [ 20–24 ] at nextto-leading order (NLO) in QCD for quark-antiquark processes and leading order (LO) for quark-gluon processes. This includes ZZ, Zγ ∗, Z, and γ ∗γ ∗ production with a constraint of m > 4 GeV applied to all pairs of oppositely charged leptons at the generator level to avoid infrared divergences. The gg → ZZ process is simulated at LO with mcfm v7.0 [ 25 ]. These samples are scaled to correspond to cross sections calculated at NNLO in QCD for qq → ZZ [ 11 ] (a scaling K factor of 1.1) and at NLO in QCD for gg → ZZ [ 26 ] (K factor of 1.7). The gg → ZZ process is calculated to O αs3 , where αs is the strong coupling constant, while the other contributing processes are calculated to O αs2 ; this higher-order correction is included because the effect is known to be large [ 26 ]. Electroweak ZZ production in association with two jets is generated with Phantom v1.2.8 [ 27 ]. A sample of Higgs boson events is produced in the gluongluon fusion process at NLO with powheg. The Higgs boson decay is modeled with jhugen 3.1.8 [ 28–30 ]. Its cross section is scaled to the NNLO prediction with a K factor of 1.7 [ 26 ]. Samples for background processes containing four prompt leptons in the final state, ttZ and WWZ production, are produced with MadGraph5_amc@nlo v2.3.3 [ 31 ]. The qq → WZ process is generated with powheg. Samples with aTGC contributions included are generated at LO with sherpa v2.1.1 [ 32 ]. Distributions from the sherpa samples are normalized such that the total yield of the SM sample is the same as that of the powheg sample. The pythia v8.175 [ 23,33,34 ] package is used for parton showering, hadronization, and the underlying event simulation, with parameters set by the CUETP8M1 tune [ 35 ], for all samples except the samples generated with sherpa, which performs these functions itself. The NNPDF 3.0 [ 36 ] set is used as the default set of parton distribution functions (PDFs). For all simulated event samples, the PDFs are calculated to the same order in QCD as the process in the sample. The detector response is simulated using a detailed description of the CMS detector implemented with the Geant4 package [ 37 ]. The event reconstruction is performed with the same algorithms used for data. The simulated samples include additional interactions per bunch crossing, referred to as pileup. The simulated events are weighted so that the pileup distribution matches the data, with an average of about 27 interactions per bunch crossing. 4 Event reconstruction All long-lived particles—electrons, muons, photons, and charged and neutral hadrons—in each collision event are identified and reconstructed with the CMS particle-flow (PF) algorithm [ 38 ] from a combination of the signals from all subdetectors. Reconstructed electrons [ 18 ] and muons [ 19 ] are considered candidates for inclusion in four-lepton final states if they have pTe > 7 GeV and |ηe| < 2.5 or pTμ > 5 GeV and |ημ| < 2.4. Lepton candidates are also required to originate from the event vertex, defined as the reconstructed proton-proton interaction vertex with the largest value of summed physics object pT2. The physics objects used in the event vertex definition are the objects returned by a jet finding algorithm [ 39,40 ] applied to all charged tracks associated with the vertex, plus the corresponding associated missing transverse momentum [41]. The distance of closest approach between each lepton track and the event vertex is required to be less than 0.5 cm in the plane transverse to the beam axis, and less than 1 cm in the direction along the beam axis. Furthermore, the significance of the three-dimensional impact parameter relative to the event vertex, SIP3D, is required to satisfy SIP3D ≡ |IP/σIP| < 10 for each lepton, where IP is the distance of closest approach of each lepton track to the event vertex and σIP is its associated uncertainty. Lepton candidates are required to be isolated from other particles in the event. The relative isolation is defined as Riso = pT + max 0, pT + pT − pTPU charged hadrons neutral hadrons photons pT, (1) where the sums run over the charged and neutral hadrons and photons identified by the PF algorithm, in a cone defined by √ R ≡ ( η)2 + ( φ)2 < 0.3 around the lepton trajectory. Here φ is the azimuthal angle in radians. To minimize the contribution of charged particles from pileup to the isolation calculation, charged hadrons are included only if they originate from the event vertex. The contribution of neutral particles from pileup is pTPU. For electrons, pPU is evaluT ated with the “jet area” method described in Ref. [ 42 ]; for muons, it is taken to be half the sum of the pT of all charged particles in the cone originating from pileup vertices. The factor one-half accounts for the expected ratio of charged to neutral particle energy in hadronic interactions. A lepton is considered isolated if Riso < 0.35. The lepton reconstruction, identification, and isolation efficiencies are measured with a “tag-and-probe” technique [ 43 ] applied to a sample of Z → + − data events. The measurements are performed in several bins of pT and |η |. The electron reconstruction and selection efficiency in the ECAL barrel (endcaps) varies from about 85% (77%) at pTe ≈ 10 GeV to about 95% (89%) for pTe ≥ 20 GeV, while in the barrel-endcap transition region this efficiency is about 85% averaged over all electrons with pTe > 7 GeV. The muons are reconstructed and identified with efficiencies above ∼ 98% within |ημ| < 2.4. 5 Event selection The primary triggers for this analysis require the presence of a pair of loosely isolated leptons of the same or different flavors [ 44 ]. The highest pT lepton must have pT > 17 GeV, and the subleading lepton must have pTe > 12 GeV if it is an electron or pTμ > 8 GeV if it is a muon. The tracks of the triggering leptons are required to originate within 2 mm of each other in the plane transverse to the beam axis. Triggers requiring a triplet of lower- pT leptons with no isolation criterion, or a single high- pT electron or muon, are also used. An event is used if it passes any trigger regardless of the decay channel. The total trigger efficiency for events within the acceptance of this analysis is greater than 98%. The four-lepton candidate selections are based on those used in Ref. [ 45 ]. A signal event must contain at least two Z/γ ∗ candidates, each formed from an oppositely charged pair of isolated electron candidates or muon candidates. Among the four leptons, the highest pT lepton must have pT > 20 GeV, and the second-highest pT lepton must have pTe > 12 GeV if it is an electron or pTμ > 10 GeV if it is a muon. All leptons are required to be separated from each other by R ( 1, 2) > 0.02, and electrons are required to be separated from muons by R (e, μ) > 0.05. Within each event, all permutations of leptons giving a valid pair of Z/γ ∗ candidates are considered separately. Within each 4 candidate, the dilepton candidate with an invariant mass closest to 91.2 GeV, taken as the nominal Z boson mass [ 46 ], is denoted Z1 and is required to have a mass greater than 40 GeV. The other dilepton candidate is denoted Z2. Both mZ1 and mZ2 are required to be less than 120 GeV. All pairs of oppositely charged leptons in the 4 candidate are required to have m > 4 GeV regardless of their flavor. If multiple 4 candidates within an event pass all selections, the one with mZ1 closest to the nominal Z boson mass is chosen. In the rare case of further ambiguity, which may arise in less than 0.5% of events when five or more passing lepton candidates are found, the Z2 candidate that maximizes the scalar pT sum of the four leptons is chosen. Additional requirements are applied to select events for measurements of specific processes. The pp → ZZ cross section is measured using events where both mZ1 and mZ2 are greater than 60 GeV. The Z → 4 branching fraction is measured using events with 80 < m4 < 100 GeV, a range chosen to retain most of the decays in the resonance while removing most other processes with four-lepton final states. Decays of the Z bosons to τ leptons with subsequent decays to electrons and muons are heavily suppressed by requirements on lepton pT, and the contribution of such events is less than 0.5% of the total ZZ yield. If these events pass the selection requirements of the analysis, they are considered signal, while they are not considered at generator level in the cross section unfolding procedure. Thus, the correction for possible τ decays is included in the efficiency calculation. 6 Background estimate The major background contributions arise from Z boson and WZ diboson production in association with jets and from tt production. In all these cases, particles from jet fragmentation satisfy both lepton identification and isolation criteria, and are thus misidentified as signal leptons. The probability for such objects to be selected is measured from a sample of Z + candidate events, where Z denotes a pair of oppositely charged, same-flavor leptons that pass all analysis requirements and satisfy |m + − − mZ| < 10 GeV, where mZ is the nominal Z boson mass. Each event in this sample must have exactly one additional object candidate that passes relaxed identification requirements with no isolation requirements applied. The misidentification probability for each lepton flavor, measured in bins of lepton candidate pT and η, is defined as the ratio of the number of candidates that pass the final isolation and identification requirements to the total number in the sample. The number of Z + candidate events is corrected for the contamination from WZ production and ZZ production in which one lepton is not reconstructed. These events have a third genuine, isolated lepton that must be excluded from the misidentification probability calculation. The WZ contamination is suppressed by requiring the missing transverse momentum pmiss to be below T 25 GeV. The pmiss is defined as the magnitude of the missing T transverse momentum vector p miss, the projection onto the T plane transverse to the beams of the negative vector sum of the momenta of all reconstructed PF candidates in the event, corrected for the jet energy scale. Additionally, the transverse mass calculated with p miss and the pT of candidate, mT ≡ √( pT + pTmiss)2 − ( pTT+ pTmiss)2, is required to be less than 30 GeV. The residual contribution of WZ and ZZ events, which may be up to a few percent of the events with candidate passing all selection criteria, is estimated from simulation and subtracted. To account for all sources of background events, two control samples are used to estimate the number of background events in the signal regions. Both are defined to contain events with a dilepton candidate satisfying all requirements (Z1) and two additional lepton candidates + −. In one control sample, enriched in WZ events, one candidate is required to satisfy the full identification and isolation criteria and the other must fail the full criteria and instead satisfy only the relaxed ones; in the other, enriched in Z+jets events, both candi6–10 2–4 1–2 0.6–1.3 1–2 1 1 2.5 dates must satisfy the relaxed criteria, but fail the full criteria. The additional leptons must have opposite charge and the same flavor (e±e∓, μ±μ∓). From this set of events, the expected number of background events in the signal region, denoted “Z + X” in the figures, is obtained by scaling the number of observed Z1 + + − events by the misidentification probability for each lepton failing the selection. It is found to be approximately 4% of the total expected yield. The procedure is described in more detail in Ref. [ 45 ]. In addition to these nonprompt backgrounds, ttZ and WWZ processes contribute a smaller number of events with four prompt leptons, which is estimated from simulated samples to be around 1% of the expected ZZ → 4 yield. In the Z → 4 selection, the contribution from these backgrounds is negligible. The total background contributions to the Z → 4 and ZZ → 4 signal regions are summarized in Sect. 8. 7 Systematic uncertainties The major sources of systematic uncertainty and their effect on the measured cross sections are summarized in Table 1. In both data and simulated event samples, trigger efficiencies are evaluated with a tag-and-probe technique. The ratio of data to simulation is applied to simulated events, and the size of the resulting change in expected yield is taken as the uncertainty in the determination of the trigger efficiency. This uncertainty is around 2% of the final estimated yield. For Z → 4e events, the uncertainty increases to 4%. The lepton identification, isolation, and track reconstruction efficiencies in simulation are corrected with scaling factors derived with a tag-and-probe method and applied as a function of lepton pT and η. To estimate the uncertainties associated with the tag-and-probe technique, the total yield is recomputed with the scaling factors varied up and down by the tag-and-probe fit uncertainties. The uncertainties associated with lepton efficiency in the ZZ → 4 (Z → 4 ) signal regions are found to be 6(10)% in the 4e, 3(6)% in the 2e2μ, and 2(7)% in the 4μ final states. These uncertainties are higher for Z → 4 events because the leptons generally have lower pT, and the samples used in the tag-and-probe method have fewer events and more contamination from nonprompt leptons in this low- pT region. Uncertainties due to the effect of factorization (μF) and renormalization (μR) scale choices on the ZZ → 4 acceptance are evaluated with powheg and mcfm by varying the scales up and down by a factor of two with respect to the default values μF = μR = mZZ. All combinations are considered except those in which μF and μR differ by a factor of four. Parametric uncertainties (PDF + αs ) are evaluated according to the pdf4lhc prescription [ 47 ] in the acceptance calculation, and with NNPDF3.0 in the cross section calculations. An additional theoretical uncertainty arises from scaling the powheg qq → ZZ simulated sample from its NLO cross section to the NNLO prediction, and the mcfm gg → ZZ samples from their LO cross sections to the NLO predictions. The change in the acceptance corresponding to this scaling procedure is found to be 1.1%. All these theoretical uncertainties are added in quadrature. The largest uncertainty in the estimated background yield arises from differences in sample composition between the Z + candidate control sample used to calculate the lepton misidentification probability and the Z + + − control sample. A further uncertainty arises from the limited number of events in the Z + candidate sample. A systematic uncertainty of 40% is applied to the lepton misidentification probability to cover both effects. The size of this uncertainty varies by channel, but is less than 1% of the total expected yield. The uncertainty in the integrated luminosity of the data sample is 2.5% [ 48 ]. 8 Cross section measurements The distributions of the four-lepton mass and the masses of the Z1 and Z2 candidates are shown in Fig. 1. The expected distributions describe the data well within uncertainties. The SM predictions include nonresonant ZZ predictions, production of the SM Higgs boson with mass 125 GeV [ 49 ], and resonant Z → 4 production. The backgrounds estimated from data and simulation are also shown. The reconstructed invariant mass of the Z1 candidates, and a scatter plot showing the correlation between mZ2 and mZ1 in data events, are shown in Fig. 2. In the scatter plot, clusters of events corresponding to ZZ → 4 , Zγ ∗ → 4 , and Z → 4 production can be seen. 165 The four-lepton invariant mass distribution below 100 GeV is shown in Fig. 3 (upper). Figure 3 (lower) shows mZ2 plotted against mZ1 for events with m4 between 80 and 100 GeV, and the observed and expected event yields in this mass region are given in Table 2. The yield of events in the 4e final state is significantly lower than in the 4μ final state because minimum pT thresholds are higher for electrons than for muons, and inefficiencies in the detection of low- pT leptons affect electrons more strongly than they affect muons. The reconstructed four-lepton invariant mass is shown in Fig. 4 (upper) for events with two on-shell Z bosons. Figure 4 (lower) shows the invariant mass distribution for all Z boson candidates in these events. The corresponding observed and expected yields are given in Table 3. The observed yields are used to evaluate the pp → Z → 4 and pp → ZZ → 4 production cross sections from a combined fit to the number of observed events in all the final states. The likelihood is a combination of individual channel likelihoods for the signal and background hypotheses with the statistical and systematic uncertainties in the form of scaling nuisance parameters. The fiducial cross section is measured by scaling the cross section in the simulation by the ratio of the measured and predicted event yields given by the fit. The definitions for the fiducial phase spaces for the Z → 4 and ZZ → 4 cross section measurements are given in Table 4. In the ZZ → 4 case, the Z bosons used in the fiducial definition are built by pairing final-state leptons using the same algorithm as is used to build Z boson candidates from reconstructed leptons. The generator-level leptons used for the fiducial cross section calculation are “dressed” by adding the momenta of generator-level photons within R ( , γ ) < 0.1 to their momenta. The measured cross sections are σfid(pp → Z → 4 ) = 31.2−+11..45 (stat)+−21..91 (syst) ± 0.8 (lumi) fb, σfid(pp → ZZ → 4 ) = 40.9 ± 1.3 (stat) ± 1.4 (syst) ± 1.0 (lumi) fb. The pp → Z → 4 fiducial cross section can be compared to 27.9+1.0 −1.5 ± 0.6 fb calculated at NLO in QCD with powheg using the same settings as used for the simulated sample described in Sect. 3, with dynamic scales μF = μR = m4 . The uncertainties correspond to scale and PDF variations, respectively. The ZZ fiducial cross section can be compared to 34.4+0.7 −0.6 ± 0.5 fb calculated with powheg and mcfm using the same settings as the simulated samples, or to 36.0+0.9 −0.8 computed with matrix at NNLO. The powheg and matrix calculations used dynamic scales μF = μR = m4 , while the contribution from mcfm was computed with dynamic scales μF = μR = 0.5m4 . The pp → Z → 4 fiducial cross section is scaled to σ (pp → Z)B(Z → 4 ) using the acceptance correction factor A = 0.125 ± 0.002, estimated with powheg. This factor (2) 165 Fig. 4 Distributions of (upper) the four-lepton invariant mass mZZ and (lower) dilepton candidate mass for four-lepton events selected with both Z bosons on-shell. Points represent the data, while filled histograms represent the SM prediction and background estimate. Vertical bars on the data points show their statistical uncertainty. Shaded grey regions around the predicted yield represent combined statistical, systematic, theoretical, and integrated luminosity uncertainties. In the mZZ distribution, bin contents are normalized to the bin widths, using a unit bin size of 50 GeV; horizontal bars on the data points show the range of the corresponding bin corrects the fiducial Z → 4 cross section to the phase space with only the 80–100 GeV mass window and m + − > 4 GeV requirements, and also includes a correction, 0.96 ± 0.01, for the contribution of nonresonant four-lepton production to the signal region. The uncertainty takes into account the interference between doubly- and singly-resonant diagrams. The measured cross section is σ (pp → Z)B(Z → 4 ) = 249 ± 11(st at )+−1165(s yst ) ± 4(t heo) ± 6(lumi ) f b (3) The branching fraction for the Z → 4 decay, B(Z → 4 ), is measured by comparing the cross section given by Eq. (3) with the Z → + − cross section, and is computed as B(Z → 4 ) = σ (pp → Z → 4 ) C8600––110200 σ (pp → Z → + −)/B(Z → + −) where σ (pp → Z → + −) = 1870−+4500 pb is the Z → + − cross section times branching fraction calculated at NNLO with fewz v2.0 [ 50 ] in the mass range 60–120 GeV. Its uncertainty includes PDF uncertainties and uncertainties in αs , the charm and bottom quark masses, and the effect of neglected higher-order corrections to the calcula60–120 tion. The factor C80–100 = 0.926 ± 0.001 corrects for the difference in Z boson mass windows and is estimated using powheg. Its uncertainty includes scale and PDF variations. The nominal Z to dilepton branching fraction B(Z → + −) is 0.03366 [ 46 ]. The measured value is B(Z → 4 ) = 4.83+−00..2232(st at )+−00..3229(s yst ) ± 0.08(t heo) ±0.12(lumi ) × 10−6 where the theoretical uncertainty includes the uncertainties in σ (pp → Z)B(Z → + −), C8600––110200, and A. This can be compared with 4.6 × 10−6, computed with MadGraph5_amc@nlo, and is consistent with the CMS and ATLAS measurements at √s = 7, 8, and 13 TeV [ 6, 14, 15 ]. , (4) (5) The total ZZ production cross section for both dilep tons produced in the mass range 60–120 GeV and m + − > 4 GeV is found to be σ (pp → ZZ) = 17.5+−00..65 (stat) ± 0.6 (syst) ± 0.4 (theo) ± 0.4 (lumi) pb. The measured total cross section can be compared to the theoretical value of 14.5+0.5 −0.4 ± 0.2 pb calculated with a combination of powheg and mcfm with the same settings as described for σfid(pp → ZZ → 4 ). It can also be compared to 16.2−+00..46 pb, calculated at NNLO in QCD via matrix v1.0.0_beta4 [ 11, 51 ], or 15.0+0.7 −0.6 ± 0.2 pb, calculated with mcfm at NLO in QCD with additional contributions from LO gg → ZZ diagrams. Both values are calculated with the NNPDF3.0 PDF sets, at NNLO and NLO, respectively, and fixed scales set to μF = μR = mZ. This measurement agrees with the previously published cross section measured by CMS at 13 TeV [ 6 ] based on a 2.6 fb−1 data sample collected in 2015: σ (pp → ZZ) = 14.6−+11..89 (stat)+−00..35 (syst) ± 0.2 (theo) ± 0.4 (lumi) pb. (6) (7) 165 pythia v8 was used for parton showering, hadronization, and underlying event simulation in the powheg, MadGraph5_amc@nlo, and mcfm samples. The lower part of each plot represents the ratio of the measured cross section to the theoretical distributions. The shaded grey areas around the points represent the sum in quadrature of the statistical and systematic uncertainties, while the crosses represent the statistical uncertainties only The two measurements can be combined to yield the “2015 + 2016 cross section” σ (pp → ZZ) = 17.2 ± 0.5 (stat) ± 0.7 (syst) ± 0.4 (theo) ± 0.4 (lumi) pb. (8) The combination was performed once considering the experimental uncertainties to be fully correlated between the 2015 and 2016 data sets, and once considering them to be fully uncorrelated. The results were averaged, and the difference was added linearly to the systematic uncertainty in the combined cross section. The total ZZ cross section is shown in Fig. 5 as a function of the proton-proton center-of-mass energy. Results from CMS [ 3, 4 ] and ATLAS [ 7, 8, 10 ] are compared to predictions from matrix and mcfm with the NNPDF3.0 PDF sets and fixed scales μF = μR = mZ. The matrix prediction uses PDFs calculated at NNLO, while the mcfm prediction uses NLO PDFs. The uncertainties are statistical (inner bars) and statistical and systematic added in quadrature (outer bars). The band around the matrix predictions reflects scale uncertainties, while the band around the mcfm predictions reflects both scale and PDF uncertainties. The measurement of the differential cross sections provides detailed information about ZZ kinematics. The observed yields are unfolded using the iterative technique described in Ref. [ 52 ]. Unfolding is performed with the RooUnfold package [ 53 ] and regularized by stopping after four iterations. Statistical uncertainties in the data distributions are propagated through the unfolding process to give the statistical uncertainties on the normalized differential cross sections. The three decay channels, 4e, 4μ, and 2e2μ, are combined after unfolding because no differences are expected in their kinematic distributions. The generator-level leptons used for the unfolding are dressed as in the fiducial cross section calculation. Fig. 7 Normalized ZZ differential cross sections as a function of the pT of (upper) all Z bosons and (lower) the leading lepton in ZZ events. Other details are as described in the caption of Fig. 6 The differential distributions normalized to the fiducial cross sections are presented in Figs. 6, 7, 8 for the combination of the 4e, 4μ, and 2e2μ decay channels. The fiducial cross section definition includes pT and |η | selections on each lepton, and the 60–120 GeV mass requirement, as described in Table 4 and Sect. 4. Figure 6 shows the normalized differential cross sections as functions of the mass and pT of the ZZ system, Fig. 7 shows them as functions of the pT of all Z bosons and the pT of the leading lepton in each event, and Fig. 8 shows the angular correlations between the two Z bosons. The data are corrected for background contributions and compared with the theoretical predictions from powheg and mcfm, MadGraph5_amc@nlo and mcfm, and matrix. The bottom part of each plot shows the ratio of the measured to the predicted values. The bin sizes are chosen according to the resolution of the relevant variables, while also keeping the statistical uncertainties at a similar level in all bins. The data are well reproduced by the simulation except in the low pT regions, where data tend to have a steeper slope than the prediction. Figure 9 shows the normalized differential four-lepton cross section as a function of m4 , subject only to the common requirements of Table 4. This includes contributions from the Z and Higgs boson resonances and continuum ZZ production. 9 Limits on anomalous triple gauge couplings The presence of aTGCs would increase the yield of events at high four-lepton masses. Figure 10 presents the distribution of the four-lepton reconstructed mass of events with both Z bosons in the mass range 60–120 GeV for the combined 4e, 4μ, and 2e2μ channels. This distribution is used to set the limits on possible contributions from aTGCs. Two simulated samples with nonzero aTGCs are shown as examples, along with the SM distribution simulated by both sherpa and powheg. Fig. 9 The normalized differential four-lepton cross section as a function of the four-lepton mass, subject only to the common requirements of Table 4. SM gg → H → ZZ∗ production is included, simulated with powheg. Other details are as described in the caption of Fig. 6 The invariant mass distributions are interpolated from the sherpa simulations for different values of the anomalous couplings in the range between 0 and 0.015. For each distribution, only one or two couplings are varied while all others are set to zero. The measured signal is obtained from a comparison of the data to a grid of aTGC models in the γ γ ( f4Z, f4 ) and ( f5Z, f5 ) parameter planes. Expected signal values are interpolated between the 2D grid points using a second-degree polynomial, since the cross section for the signal depends quadratically on the coupling parameters. A binned profile likelihood method, Wald Gaussian approximation, and Wilk’s theorem are used to derive one-dimensional limits at a 95% confidence level (CL) on each of the four aTGC parameters, and two-dimensional limits at a 95% CL on the pairs ( f4Z, f4γ ) and ( f5Z, f5γ ) [ 46,54,55 ]. When the limits are calculated for each parameter or pair, all other parameters are set to their SM values. The systematic uncertainties described in Sect. 7 are treated as nuisance parameters with log-normal distributions. No form factor is used when deriving the limits so that the results do not depend on any assumed energy scale characterizing new physics. The constraints on anomalous couplings are displayed in Fig. 11. The curves indicate 68 and 95% confidence levels, and the solid dot shows the coordinates where the likelihood reaches its maximum. Coupling values outside the contours are excluded at and f5Z,γ anomalous coupling parameters are: the corresponding confidence levels. The limits are dominated by statistical uncertainties. The observed one-dimensional 95% CL limits for the f4Z,γ − 0.0012 < f4Z < 0.0010, − 0.0012 < f4γ < 0.0013, − 0.0010 < f5Z < 0.0013, − 0.0012 < f5γ < 0.0013. These are the most stringent limits to date on anomalous ZZZ and ZZγ trilinear gauge boson couplings, improving on the previous strictest results from CMS [ 5 ] by factors of two or more and constraining the coupling parameters more than the corresponding ATLAS results [ 10 ]. One way to impose unitarity on the aTGC models is to restrict the range of four-lepton invariant mass used in the limit calculation. The limits will then depend on the “cutoff” value used. The computation of the one-dimensional limits is repeated for different maximum allowed values of m4 , and the results are presented in Fig. 12 as a function of this cutoff. Fig. 11 Two-dimensional observed 95% CL limits (solid contour) and expected 68 and 95% CL limits (dashed contour) on the ZZZ and ZZγ aTGCs. The upper(lower) plot shows the exclusion contour in the f4Z(5), f4γ(5) parameter planes. The values of couplings outside of contours are excluded at the corresponding confidence level. The solid dot is the point at which the likelihood is at its maximum. The solid lines at the center show the observed one-dimensional 95% CL limits for f4γ,5 (horizontal) and f4Z,5 (vertical). No form factor is used 10 Summary A series of measurements of four-lepton final states in protonproton collisions at √s = 13 TeV have been performed with the CMS detector at the CERN LHC. The measured pp → ZZ cross section is σ (pp → ZZ) = 17.2 ± 0.5 (stat)± 0.7 (syst) ± 0.4 (theo) ± 0.4 (lumi) pb for Z boson masses in the range 60 < mZ < 120 GeV. The measured branching fraction for Z boson decays to four leptons is B(Z → 4 ) = 4.83+−00..2232(st at )+−00..3229(s yst ) ± 0.08(t heo) ± 0.12(lumi ) × 10−6 for four-lepton mass in the range 80 < m4 < 100 GeV and dilepton mass m > 4 GeV for all oppositely charged same-flavor lepton pairs. Normalized differential cross sections were also measured. All results agree well with the SM predictions. Improved limits on anomalous ZZZ and ZZγ triple gauge couplings were established, the most stringent to date. 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 centers 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: BMWFW and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES and CSF (Croatia); RPF (Cyprus); SENESCYT (Ecuador); MoER, ERC IUT, and ERDF (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NIH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MBIE (New Zealand); PAEC (Pakistan); MSHE and NSC (Poland); FCT (Portugal); JINR (Dubna); MON, RosAtom, RAS, RFBR and RAEP (Russia); MESTD (Serbia); SEIDI, CPAN, PCTI and FEDER (Spain); Swiss Funding Agencies (Switzerland); MST (Taipei); ThEPCenter, IPST, STAR, and NSTDA (Thailand); TUBITAK and TAEK (Turkey); NASU and SFFR (Ukraine); STFC (United Kingdom); DOE and NSF (USA). Individuals have received support from the Marie-Curie program and the European Research Council and Horizon 2020 Grant, contract No. 675440 (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 (FRIABelgium); 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 program of the Foundation for Polish Science, cofinanced from European Union, Regional Development Fund, the Mobility Plus program of the Ministry of Science and Higher Education, the National Science Center (Poland), contracts Harmonia 2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543, 2014/15/B/ST2/03998, and 2015/19/B/ST2/02861, Sonata-bis 2012/07/ E/ST2/01406; the National Priorities Research Program by Qatar National Research Fund; the Programa Severo Ochoa del Principado de Asturias; the Thalis and Aristeia programs cofinanced by EU-ESF and the Greek NSRF; the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University and the Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand); the Welch Foundation, contract C-1845; and the Weston Havens Foundation (USA). 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. CMS Collaboration Yerevan Physics Institute, Yerevan, Armenia A. M. Sirunyan, A. Tumasyan Institut für Hochenergiephysik, Vienna, Austria W. Adam, F Ambrogi, E. Asilar, T. Bergauer, J. Brandstetter, E. Brondolin, M. Dragicevic, J. Erö, M. Flechl, M. Friedl, R. Frühwirth1, V. M. Ghete, J. Grossmann, J. Hrubec, M. Jeitler1, A. König, N. Krammer, I. Krätschmer, D. Liko, T. Madlener, I. Mikulec, E. Pree, D. Rabady, N. Rad, H. Rohringer, J. Schieck1, R. Schöfbeck, M. Spanring, D. Spitzbart, W. Waltenberger, J. Wittmann, C.-E. Wulz1, M. 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Nicolaou, F. Ptochos, P. A. Razis, H. Rykaczewski Charles University, Prague, Czech Republic M. Finger7, M. Finger Jr.7 Universidad San Francisco de Quito, Quito, Ecuador E. Carrera Jarrin Academy of Scientific Research and Technology of the Arab Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt Y. Assran8,9, M. A. Mahmoud9,10, A. Mahrous11 National Institute of Chemical Physics and Biophysics, Tallinn, Estonia R. K. Dewanjee, M. Kadastik, L. Perrini, M. Raidal, A. Tiko, C. Veelken Department of Physics, University of Helsinki, Helsinki, Finland P. Eerola, J. Pekkanen, M. Voutilainen Lappeenranta University of Technology, Lappeenranta, Finland J. Talvitie, T. Tuuva Laboratoire Leprince-Ringuet, Ecole Polytechnique, CNRS/IN2P3, Université Paris-Saclay, Palaiseau, France A. Abdulsalam, I. Antropov, S. Baffioni, F. Beaudette, P. Busson, L. Cadamuro, C. Charlot, R. Granier de Cassagnac, M. Jo, S. Lisniak, A. Lobanov, J. Martin Blanco, M. Nguyen, C. Ochando, G. 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Saoulidou National Technical University of Athens, Athens, Greece K. Kousouris MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös Loránd University, Budapest, Hungary M. Csanad, N. Filipovic, G. Pasztor, G. I. Veres18 Institute of Nuclear Research ATOMKI, Debrecen, Hungary N. Beni, S. Czellar, J. Karancsi20, A. Makovec, J. Molnar, Z. Szillasi Institute of Physics, University of Debrecen, Debrecen, Hungary M. Bartók18, P. Raics, Z. L. Trocsanyi, B. Ujvari Indian Institute of Science (IISc), Bangalore, India S. Choudhury, J. R. Komaragiri University of Delhi, Delhi, India Ashok Kumar, Aashaq Shah, A. Bhardwaj, S. Chauhan, B. C. Choudhary, R. B. Garg, S. Keshri, A. Kumar, S. Malhotra, M. Naimuddin, K. Ranjan, R. Sharma Indian Institute of Technology Madras, Madras, India P. K. Behera Bhabha Atomic Research Centre, Mumbai, India R. Chudasama, D. Dutta, V. Jha, V. Kumar, A. K. Mohanty14, P. K. Netrakanti, L. M. Pant, P. Shukla, A. Topkar Tata Institute of Fundamental Research-A, Mumbai, India T. Aziz, S. Dugad, B. Mahakud, S. Mitra, G. B. Mohanty, N. Sur, B. Sutar Indian Institute of Science Education and Research (IISER), Pune, India S. Chauhan, S. Dube, V. Hegde, A. Kapoor, K. Kothekar, S. Pandey, A. Rane, S. Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran S. Chenarani25, E. Eskandari Tadavani, S. M. Etesami25, M. Khakzad, M. Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi26, F. Rezaei Hosseinabadi, B. Safarzadeh27, 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, A. Colaleoa , D. Creanzaa ,c, L. Cristellaa ,b, N. De Filippisa ,c, M. De Palmaa ,b, F. Erricoa ,b, L. Fiorea , G. Iasellia ,c, S. Lezkia ,b, G. Maggia ,c, M. Maggia , G. Minielloa ,b, S. Mya ,b, S. Nuzzoa ,b, A. Pompilia ,b, G. Pugliesea ,c, R. Radognaa ,b, A. Ranieria , G. 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Paoluccia ,14, C. Sciaccaa ,b, F. Thyssena INFN Sezione di Padovaa , Università di Padovab, Padova, Italy, Università di Trentoc, Trento, Italy P. Azzia ,14, N. Bacchettaa , L. Benatoa ,b, D. Biselloa ,b, A. Bolettia ,b, R. Carlina ,b, A. Carvalho Antunes De Oliveiraa ,b, P. Checchiaa , M. Dall’Ossoa ,b, P. De Castro Manzanoa , T. Dorigoa , U. Dossellia , U. Gasparinia ,b, A. Gozzelinoa , S. Lacapraraa , P. Lujan, M. Margonia ,b, A. T. Meneguzzoa ,b, N. Pozzobona ,b, P. Ronchesea ,b, R. Rossina ,b, F. Simonettoa ,b, E. Torassaa , S. Venturaa , M. Zanettia ,b, P. Zottoa ,b INFN Sezione di Paviaa , Università di Paviab, Pavia, Italy A. Braghieria , A. Magnania ,b, P. Montagnaa ,b, S. P. Rattia ,b, V. Rea , M. Ressegotti, C. Riccardia ,b, P. Salvinia , I. Vaia ,b, P. Vituloa ,b INFN Sezione di Perugiaa , Università di Perugiab, Perugia, Italy L. Alunni Solestizia ,b, M. Biasinia ,b, G. M. Bileia , C. Cecchia ,b, D. Ciangottinia ,b, L. Fanòa ,b, P. Laricciaa ,b, R. Leonardia ,b, E. Manonia , G. Mantovania ,b, V. Mariania ,b, M. Menichellia , A. Rossia ,b, A. Santocchiaa ,b, D. Spigaa INFN Sezione di Pisaa , Università di Pisab, Scuola Normale Superiore di Pisac, Pisa, Italy K. Androsova , P. Azzurria ,14, G. Bagliesia , J. Bernardinia , T. Boccalia , L. Borrello, R. Castaldia , M. A. Cioccia ,b, R. Dell’Orsoa , G. Fedia , L. Gianninia ,c, A. Giassia , M. T. Grippoa ,28, F. Ligabuea ,c, T. Lomtadzea , E. Mancaa ,c, G. Mandorlia ,c, L. Martinia ,b, A. Messineoa ,b, F. Pallaa , A. Rizzia ,b, A. Savoy-Navarroa ,30, P. Spagnoloa , R. Tenchinia , G. Tonellia ,b, A. Venturia , P. G. Verdinia INFN Sezione di Romaa , Università di Romab, Roma, Italy L. Baronea ,b, F. Cavallaria , M. Cipriania ,b, N. Dacia , D. Del Rea ,b,14, E. Di Marcoa ,b, M. Diemoza , S. Gellia ,b, E. Longoa ,b, F. Margarolia ,b, B. Marzocchia ,b, P. Meridiania , G. Organtinia ,b, R. Paramattia ,b, F. Preiatoa ,b, S. Rahatloua ,b, C. Rovellia , F. Santanastasioa ,b INFN Sezione di Torinoa , Università di Torinob, Turin, Italy, Università del Piemonte Orientalec, Novara, Italy N. Amapanea ,b, R. Arcidiaconoa ,c, S. Argiroa ,b, M. Arneodoa ,c, N. Bartosika , R. Bellana ,b, C. Biinoa , N. Cartigliaa , F. Cennaa ,b, M. Costaa ,b, R. Covarellia ,b, A. Deganoa ,b, N. Demariaa , B. Kiania ,b, C. Mariottia , S. Masellia , E. Migliorea ,b, V. Monacoa ,b, E. Monteila ,b, M. Montenoa , M. M. Obertinoa ,b, L. Pachera ,b, N. Pastronea , M. Pelliccionia , G. L. Pinna Angionia ,b, F. Raveraa ,b, A. Romeroa ,b, M. Ruspaa ,c, R. Sacchia ,b, K. Shchelinaa ,b, V. Solaa , A. Solanoa ,b, A. Staianoa , P. Traczyka ,b INFN Sezione di Triestea , Università di Triesteb, Trieste, Italy S. Belfortea , M. Casarsaa , F. Cossuttia , G. Della Riccaa ,b, A. Zanettia Kyungpook National University, Daegu, Korea D. H. Kim, G. N. Kim, M. S. Kim, J. Lee, S. Lee, S. W. Lee, C. S. Moon, Y. D. Oh, S. Sekmen, D. C. Son, Y. C. Yang Chonbuk National University, Jeonju, Korea A. Lee Chonnam National University, Institute for Universe and Elementary Particles, Kwangju, Korea H. Kim, D. H. Moon, G. Oh Hanyang University, Seoul, Korea J. A. Brochero Cifuentes, J. Goh, T. J. Kim University of Seoul, Seoul, Korea M. Choi, H. Kim, J. H. Kim, J. S. H. Lee, I. C. Park Sungkyunkwan University, Suwon, Korea Y. Choi, C. Hwang, 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, M. A. B. Md Ali31, F. Mohamad Idris32, W. A. T. Wan Abdullah, M. N. Yusli, Z. Zolkapli Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico R. Reyes-Almanza, G. Ramirez-Sanchez, M. C. Duran-Osuna, H. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-De La Cruz33, R. I. Rabadan-Trejo, R. Lopez-Fernandez, J. Mejia Guisao, A. Sanchez-Hernandez Universidad Iberoamericana, Mexico City, Mexico S. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia Benemerita Universidad Autonoma de Puebla, Puebla, Mexico I. Pedraza, H. A. Salazar Ibarguen, C. Uribe Estrada Universidad Autónoma de San Luis Potosí, San Luis Potosi, 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, A. Saddique, M. A. Shah, M. Shoaib, M. Waqas National Centre for Nuclear Research, Swierk, Poland H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Górski, M. Kazana, K. Nawrocki, M. Szleper, P. Zalewski Laboratório de Instrumentação e Física Experimental de Partículas, Lisboa, Portugal P. Bargassa, C. Beirão Da Cruz E. Silva, A. Di Francesco, P. Faccioli, B. Galinhas, M. Gallinaro, J. Hollar, N. Leonardo, L. Lloret Iglesias, M. V. Nemallapudi, J. Seixas, G. Strong, O. Toldaiev, D. Vadruccio, J. Varela Institute for Theoretical and Experimental Physics, Moscow, Russia V. Epshteyn, V. Gavrilov, N. Lychkovskaya, V. Popov, I. Pozdnyakov, G. Safronov, A. Spiridonov, A. Stepennov, M. Toms, E. Vlasov, A. Zhokin Moscow Institute of Physics and Technology, Moscow, Russia T. Aushev, A. Bylinkin36 National Research Nuclear University ‘Moscow Engineering Physics Institute’ (MEPhI), Moscow, Russia M. Chadeeva39, P. Parygin, D. Philippov, S. Polikarpov, E. Popova, V. Rusinov P.N. Lebedev Physical Institute, Moscow, Russia V. Andreev, M. Azarkin36, I. Dremin36, M. Kirakosyan37, A. Terkulov Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia A. Baskakov, A. Belyaev, E. Boos, M. Dubinin40, L. Dudko, A. Ershov, A. Gribushin, V. Klyukhin, O. Kodolova, I. Lokhtin, I. Miagkov, S. Obraztsov, S. Petrushanko, V. Savrin, A. Snigirev Novosibirsk State University (NSU), Novosibirsk, Russia V. Blinov41, Y. Skovpen41, D. Shtol41 State Research Center of Russian Federation, Institute for High Energy Physics, Protvino, Russia I. Azhgirey, I. Bayshev, S. Bitioukov, D. Elumakhov, V. Kachanov, A. Kalinin, D. Konstantinov, V. Krychkine, V. Petrov, R. Ryutin, A. Sobol, S. Troshin, N. Tyurin, A. Uzunian, A. Volkov University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia P. Adzic42, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic, V. Rekovic Universidad Autónoma de Madrid, Madrid, Spain C. Albajar, J. F. de Trocóniz, M. Missiroli, D. Moran Instituto de Física de Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, Spain I. J. Cabrillo, A. Calderon, B. Chazin Quero, E. Curras, J. Duarte Campderros, M. Fernandez, J. Garcia-Ferrero, G. Gomez, A. Lopez Virto, J. Marco, C. Martinez Rivero, P. Martinez Ruiz del Arbol, F. Matorras, J. Piedra Gomez, T. Rodrigo, A. Ruiz-Jimeno, L. Scodellaro, N. Trevisani, I. Vila, R. Vilar Cortabitarte ETH Zurich - Institute for Particle Physics and Astrophysics (IPA), Zurich, Switzerland F. Bachmair, L. Bäni, P. Berger, L. Bianchini, B. Casal, G. Dissertori, M. Dittmar, M. Donegà, C. Grab, C. Heidegger, D. Hits, J. Hoss, G. Kasieczka, T. Klijnsma, W. Lustermann, B. Mangano, M. Marionneau, M. T. Meinhard, D. Meister, F. Micheli, P. Musella, F. Nessi-Tedaldi, F. Pandolfi, J. Pata, F. Pauss, G. Perrin, L. Perrozzi, M. Quittnat, M. Reichmann, M. Schönenberger, L. Shchutska, V. R. Tavolaro, K. Theofilatos, M. L. Vesterbacka Olsson, R. Wallny, D. H. Zhu National Central University, Chung-Li, Taiwan V. Candelise, T. H. Doan, Sh. Jain, R. Khurana, C. M. Kuo, W. Lin, A. Pozdnyakov, S. S. Yu Chulalongkorn University, Faculty of Science, Department of Physics, Bangkok, Thailand B. Asavapibhop, K. Kovitanggoon, G. Singh, N. Srimanobhas Çukurova University, Physics Department, Science and Art Faculty, Adana, Turkey F. Boran, S. Cerci49, S. Damarseckin, Z. S. Demiroglu, C. Dozen, I. Dumanoglu, S. Girgis, G. Gokbulut, Y. Guler, I. Hos50, E. E. Kangal51, O. Kara, A. Kayis Topaksu, U. Kiminsu, M. Oglakci, G. Onengut52, K. Ozdemir53, D. Sunar Cerci49, B. Tali49, S. Turkcapar, I. S. Zorbakir, C. Zorbilmez Middle East Technical University, Physics Department, Ankara, Turkey B. Bilin, G. Karapinar54, K. Ocalan55, M. Yalvac, M. Zeyrek Bogazici University, Istanbul, Turkey E. Gülmez, M. Kaya56, O. Kaya57, S. Tekten, E. A. Yetkin58 Istanbul Technical University, Istanbul, Turkey M. N. Agaras, S. Atay, A. Cakir, K. Cankocak 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, D. Burns, E. Clement, D. Cussans, O. Davignon, H. Flacher, J. Goldstein, M. Grimes, G. P. Heath, H. F. Heath, J. Jacob, L. Kreczko, C. Lucas, D. M. Newbold59, S. Paramesvaran, A. Poll, T. Sakuma, S. Seif El Nasr-storey, D. Smith, V. J. Smith Rutherford Appleton Laboratory, Didcot, UK K. W. Bell, A. Belyaev60, 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 Brunel University, Uxbridge, UK J. E. Cole, P. R. Hobson, A. Khan, P. Kyberd, 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, C. Smith Catholic University of America, Washington, DC, USA R. Bartek, A. Dominguez The University of Alabama, Tuscaloosa, USA A. Buccilli, S. I. Cooper, C. Henderson, P. Rumerio, C. West Boston University, Boston, USA D. Arcaro, A. Avetisyan, T. Bose, D. Gastler, D. Rankin, C. Richardson, J. Rohlf, L. Sulak, D. Zou University of California, Davis, Davis, USA R. Band, C. Brainerd, D. Burns, M. Calderon De La Barca Sanchez, M. Chertok, J. Conway, R. Conway, P. T. Cox, R. Erbacher, C. Flores, G. Funk, M. Gardner, W. Ko, R. Lander, C. Mclean, M. Mulhearn, D. Pellett, J. Pilot, S. Shalhout, M. Shi, J. Smith, M. Squires, D. Stolp, K. Tos, M. Tripathi, Z. Wang University of California, Riverside, Riverside, USA E. Bouvier, K. Burt, R. Clare, J. Ellison, J. W. Gary, S. M. A. Ghiasi Shirazi, G. Hanson, J. Heilman, P. Jandir, E. Kennedy, F. Lacroix, O. R. Long, M. Olmedo Negrete, M. I. Paneva, A. Shrinivas, W. Si, L. Wang, H. Wei, S. Wimpenny, B. R. Yates University of California, Santa Barbara-Department of Physics, Santa Barbara, USA N. Amin, R. Bhandari, J. Bradmiller-Feld, C. Campagnari, A. Dishaw, V. Dutta, M. Franco Sevilla, C. George, F. Golf, L. Gouskos, J. Gran, R. Heller, J. Incandela, S. D. Mullin, A. Ovcharova, H. Qu, J. Richman, D. Stuart, I. Suarez, J. Yoo Carnegie Mellon University, Pittsburgh, USA M. B. Andrews, T. Ferguson, T. Mudholkar, M. Paulini, J. Russ, M. Sun, H. Vogel, I. Vorobiev, M. Weinberg University of Colorado Boulder, Boulder, USA J. P. Cumalat, W. T. Ford, F. Jensen, A. Johnson, M. Krohn, S. Leontsinis, T. Mulholland, K. Stenson, S. R. Wagner Cornell University, Ithaca, USA J. Alexander, J. Chaves, J. Chu, S. Dittmer, K. Mcdermott, N. Mirman, J. R. Patterson, A. Rinkevicius, A. Ryd, L. Skinnari, L. Soffi, S. M. Tan, Z. Tao, J. Thom, J. Tucker, P. Wittich, M. Zientek Florida International University, Miami, USA Y. R. Joshi, S. Linn, P. Markowitz, J. L. Rodriguez Florida Institute of Technology, Melbourne, USA M. M. Baarmand, V. Bhopatkar, S. Colafranceschi, M. Hohlmann, D. Noonan, T. Roy, F. Yumiceva University of Illinois at Chicago (UIC), Chicago, USA M. R. Adams, L. Apanasevich, D. Berry, R. R. Betts, R. Cavanaugh, X. Chen, O. Evdokimov, C. E. Gerber, D. A. Hangal, D. J. Hofman, K. Jung, J. Kamin, I. D. Sandoval Gonzalez, M. B. Tonjes, H. Trauger, N. Varelas, H. Wang, Z. Wu, J. Zhang Kansas State University, Manhattan, USA A. Ivanov, K. Kaadze, Y. Maravin, A. Mohammadi, L. K. Saini, N. Skhirtladze, S. Toda Lawrence Livermore National Laboratory, Livermore, USA 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, N. J. Hadley, S. Jabeen, G. Y. Jeng, R. G. Kellogg, J. Kunkle, A. C. Mignerey, F. Ricci-Tam, Y. H. Shin, A. Skuja, S. C. Tonwar Massachusetts Institute of Technology, Cambridge, USA D. Abercrombie, B. Allen, V. Azzolini, R. Barbieri, A. Baty, R. Bi, S. Brandt, W. Busza, I. A. Cali, M. D’Alfonso, Z. Demiragli, G. Gomez Ceballos, M. Goncharov, D. Hsu, Y. Iiyama, G. M. Innocenti, M. Klute, D. Kovalskyi, Y. S. Lai, Y.-J. Lee, A. Levin, P. D. Luckey, B. Maier, A. C. Marini, C. Mcginn, C. Mironov, S. Narayanan, X. Niu, C. Paus, C. Roland, G. Roland, J. Salfeld-Nebgen, G. S. F. Stephans, K. Tatar, D. Velicanu, J. Wang, T. W. Wang, B. Wyslouch University of Mississippi, Oxford, USA J. G. Acosta, S. Oliveros State University of New York at Buffalo, Buffalo, USA M. Alyari, J. Dolen, A. Godshalk, C. Harrington, I. Iashvili, D. Nguyen, A. Parker, S. Rappoccio, B. Roozbahani Northwestern University, Evanston, USA S. Bhattacharya, O. Charaf, K. A. Hahn, N. Mucia, N. Odell, B. Pollack, M. H. Schmitt, K. Sung, M. Trovato, M. Velasco The Ohio State University, Columbus, USA J. Alimena, L. Antonelli, B. Bylsma, L. S. Durkin, S. Flowers, B. Francis, A. Hart, C. Hill, W. Ji, B. Liu, W. Luo, D. Puigh, B. L. Winer, H. W. Wulsin University of Puerto Rico, Mayaguez, USA S. Malik, S. Norberg Purdue University Northwest, Hammond, USA T. Cheng, N. Parashar, J. Stupak University of Rochester, Rochester, USA A. Bodek, P. de Barbaro, R. Demina, Y. t. Duh, T. Ferbel, M. Galanti, A. Garcia-Bellido, J. Han, O. Hindrichs, A. Khukhunaishvili, K. H. Lo, P. Tan, M. Verzetti The Rockefeller University, New York, USA R. Ciesielski, K. Goulianos, C. Mesropian Rutgers, The State University of New Jersey, Piscataway, USA A. Agapitos, J. P. Chou, Y. Gershtein, T. A. Gómez Espinosa, E. Halkiadakis, M. Heindl, E. Hughes, S. Kaplan, R. Kunnawalkam Elayavalli, S. Kyriacou, A. Lath, R. Montalvo, K. Nash, M. Osherson, H. Saka, S. Salur, S. Schnetzer, D. Sheffield, S. Somalwar, R. Stone, S. Thomas, P. Thomassen, M. Walker University of Tennessee, Knoxville, USA A. G. Delannoy, M. Foerster, J. Heideman, G. Riley, K. Rose, S. Spanier, K. Thapa Texas Tech University, Lubbock, USA N. Akchurin, J. Damgov, F. De Guio, P. R. Dudero, J. Faulkner, E. Gurpinar, S. Kunori, K. Lamichhane, S. W. Lee, T. Libeiro, T. Peltola, S. Undleeb, I. Volobouev, Z. Wang Vanderbilt University, Nashville, USA S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, P. Sheldon, S. Tuo, J. Velkovska, Q. Xu Wayne State University, Detroit, USA R. Harr, P. E. Karchin, J. Sturdy, S. Zaleski † Deceased 1: Also at Vienna University of Technology, Vienna, Austria 2: Also at State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, China 3: Also at Universidade Estadual de Campinas, Campinas, Brazil 4: Also at Universidade Federal de Pelotas, Pelotas, Brazil 5: Also at Université Libre de Bruxelles, Bruxelles, Belgium 6: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia 7: Also at Joint Institute for Nuclear Research, Dubna, Russia 8: Also at Suez University, Suez, Egypt 9: Now at British University in Egypt, Cairo, Egypt 10: Also at Fayoum University, El-Fayoum, Egypt 11: Now at Helwan University, Cairo, Egypt 12: Also at Université de Haute Alsace, Mulhouse, France 13: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia 14: Also at CERN, European Organization for Nuclear Research, Geneva, Switzerland 15: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany Page 28 of 29 16: Also at University of Hamburg, Hamburg, Germany 17: Also at Brandenburg University of Technology, Cottbus, Germany 18: Also at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös Loránd University, Budapest, Hungary 19: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary 20: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary 21: Also at Indian Institute of Technology Bhubaneswar, Bhubaneswar, India 22: Also at Institute of Physics, Bhubaneswar, India 23: Also at University of Visva-Bharati, Santiniketan, India 24: Also at University of Ruhuna, Matara, Sri Lanka 25: Also at Isfahan University of Technology, Isfahan, Iran 26: Also at Yazd University, Yazd, Iran 27: Also at Plasma Physics Research Center, Science and Research Branch, Islamic Azad University, Tehran, Iran 28: Also at Università degli Studi di Siena, Siena, Italy 29: Also at INFN Sezione di Milano-Bicocca; Università di Milano-Bicocca, Milano, Italy 30: Also at Purdue University, West Lafayette, USA 31: Also at International Islamic University of Malaysia, Kuala Lumpur, Malaysia 32: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia 33: Also at Consejo Nacional de Ciencia y Tecnología, Mexico city, Mexico 34: Also at Warsaw University of Technology, Institute of Electronic Systems, Warsaw, Poland 35: Also at Institute for Nuclear Research, Moscow, Russia 36: Now at National Research Nuclear University ’Moscow Engineering Physics Institute’ (MEPhI), Moscow, Russia 37: Also at St. Petersburg State Polytechnical University, St. Petersburg, Russia 38: Also at University of Florida, Gainesville, USA 39: Also at P.N. Lebedev Physical Institute, Moscow, Russia 40: Also at California Institute of Technology, Pasadena, USA 41: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia 42: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia 43: Also at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia 44: Also at Scuola Normale e Sezione dell’INFN, Pisa, Italy 45: Also at National and Kapodistrian University of Athens, Athens, Greece 46: Also at Riga Technical University, Riga, Latvia 47: Also at Universität Zürich, Zurich, Switzerland 48: Also at Stefan Meyer Institute for Subatomic Physics, (SMI), Vienna, Austria 49: Also at Adiyaman University, Adiyaman, Turkey 50: Also at Istanbul Aydin University, Istanbul, Turkey 51: Also at Mersin University, Mersin, Turkey 52: Also at Cag University, Mersin, Turkey 53: Also at Piri Reis University, Istanbul, Turkey 54: Also at Izmir Institute of Technology, Izmir, Turkey 55: Also at Necmettin Erbakan University, Konya, Turkey 56: Also at Marmara University, Istanbul, Turkey 57: Also at Kafkas University, Kars, Turkey 58: Also at Istanbul Bilgi University, Istanbul, Turkey 59: Also at Rutherford Appleton Laboratory, Didcot, UK 60: Also at School of Physics and Astronomy, University of Southampton, Southampton, UK 61: Also at Instituto de Astrofísica de Canarias, La Laguna, Spain 62: Also at Utah Valley University, Orem, USA 63: Also at USABeykent University, Istanbul, Turkey 64: Also at Bingol University, Bingol, Turkey 65: Also at Erzincan University, Erzincan, Turkey 66: Also at Sinop University, Sinop, Turkey 67: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey 68: Also at Texas A&M University at Qatar, Doha, Qatar 69: Also at Kyungpook National University, Taegu, Korea 1. 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