Search for physics beyond the standard model in events with two leptons of same sign, missing transverse momentum, and jets in proton–proton collisions at \(\sqrt{s} = 13\,\text {TeV} \)

The European Physical Journal C, Sep 2017

A data sample of events from proton–proton collisions with two isolated same-sign leptons, missing transverse momentum, and jets is studied in a search for signatures of new physics phenomena by the CMS Collaboration at the LHC. The data correspond to an integrated luminosity of 35.9\(\,\text {fb}^{-\text {1}}\), and a center-of-mass energy of 13\(\,\text {TeV}\). The properties of the events are consistent with expectations from standard model processes, and no excess yield is observed. Exclusion limits at 95% confidence level are set on cross sections for the pair production of gluinos, squarks, and same-sign top quarks, as well as top-quark associated production of a heavy scalar or pseudoscalar boson decaying to top quarks, and on the standard model production of events with four top quarks. The observed lower mass limits are as high as 1500\(\,\text {GeV}\) for gluinos, 830\(\,\text {GeV}\) for bottom squarks. The excluded mass range for heavy (pseudo)scalar bosons is 350–360 (350–410)\(\,\text {GeV}\). Additionally, model-independent limits in several topological regions are provided, allowing for further interpretations of the results.

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Search for physics beyond the standard model in events with two leptons of same sign, missing transverse momentum, and jets in proton–proton collisions at \(\sqrt{s} = 13\,\text {TeV} \)

Eur. Phys. J. C Search for physics beyond the standard model in events with two leptons of same sign, missing transverse momentum, and jets in √ proton-proton collisions at s = 13 TeV CMS Collaboration 0 1 0 CERN , 1211 Geneva 23 , Switzerland 1 University of Ioánnina , Ioánnina , Greece I. Evangelou, C. Foudas, P. Kokkas, N. Manthos, I. Papadopoulos, E. Paradas, J. Strologas, F. A. Triantis A data sample of events from proton-proton collisions with two isolated same-sign leptons, missing transverse momentum, and jets is studied in a search for signatures of new physics phenomena by the CMS Collaboration at the LHC. The data correspond to an integrated luminosity of 35.9 fb−1, and a center-of-mass energy of 13 TeV. The properties of the events are consistent with expectations from standard model processes, and no excess yield is observed. Exclusion limits at 95% confidence level are set on cross sections for the pair production of gluinos, squarks, and same-sign top quarks, as well as top-quark associated production of a heavy scalar or pseudoscalar boson decaying to top quarks, and on the standard model production of events with four top quarks. The observed lower mass limits are as high as 1500 GeV for gluinos, 830 GeV for bottom squarks. The excluded mass range for heavy (pseudo)scalar bosons is 350-360 (350-410) GeV. Additionally, model-independent limits in several topological regions are provided, allowing for further interpretations of the results. - 1 Introduction Final states with two leptons of same charge, denoted as same-sign (SS) dileptons, are produced rarely by standard model (SM) processes in proton–proton (pp) collisions. Because the SM rates of SS dileptons are low, studies of these final states provide excellent opportunities to search for manifestations of physics beyond the standard model (BSM). Over the last decades, a large number of new physics mechanisms have been proposed to extend the SM and address its shortcomings. Many of these can give rise to potentially large contributions to the SS dilepton signature, e.g., the production of supersymmetric (SUSY) particles [ 1,2 ], SS top quarks [ 3,4 ], scalar gluons (sgluons) [ 5,6 ], heavy scalar bosons of extended Higgs sectors [ 7,8 ], Majorana neutrinos [ 9 ], and vector-like quarks [ 10 ]. In the SUSY framework [ 11–20 ], the SS final state can appear in R-parity conserving models through gluino or squark pair production when the decay of each of the pairproduced particles yields one or more W bosons. For example, a pair of gluinos (which are Majorana particles) can give rise to SS charginos and up to four top quarks, yielding signatures with up to four W bosons, as well as jets, b quark jets, and large missing transverse momentum (ETmiss). Similar signatures can also result from the pair production of bottom squarks, subsequently decaying to charginos and top quarks. While R-parity conserving SUSY models often lead to signatures with large E miss, it is also interesting to study final T states without significant E miss beyond what is produced by T the neutrinos from leptonic W boson decays. For example, some SM and BSM scenarios can lead to the production of SS or multiple top quark pairs, such as the associated production of a heavy (pseudo)scalar, which subsequently decays to a pair of top quarks. This scenario is realized in Type II two Higgs doublet models (2HDM) where associated production with a single top quark or a tt pair can in some cases provide a promising window to probe these heavy (pseudo)scalar bosons [ 21–23 ]. This paper extends the search for new physics presented in Ref. [ 24 ]. We consider final states with two leptons (electrons and muons) of same charge, two or more hadronic jets, and moderate E miss. Compared to searches with zero or one T lepton, this final state provides enhanced sensitivity to lowmomentum leptons and SUSY models with compressed mass spectra. The results are based on an integrated luminosity corresponding to 35.9 fb−1 of √s = 13 TeV proton–proton collisions collected with the CMS detector at the CERN LHC. Previous LHC searches in the SS dilepton channel have been performed by the ATLAS [ 25–27 ] and CMS [ 24,28–32 ] Collaborations. With respect to Ref. [24], the event categorizaP2 P1 W+ W± 0 χ1 0 χ1 W± P1 P2 P1 P2 (c) g g b1 b1 (f) tion is extended to take advantage of the increased integrated luminosity, the estimate of rare SM backgrounds is improved, and the (pseudo)scalar boson interpretation is added. The results of the search are interpreted in a number of specific BSM models discussed in Sect. 2. In addition, modelindependent results are also provided in several kinematic regions to allow for further interpretations. These results are given as a function of hadronic activity and of E miss, as well T as in a set of inclusive regions with different topologies. The full analysis results are also summarized in a smaller set of exclusive regions to be used in combination with the background correlation matrix to facilitate their reinterpretation. 2 Background and signal simulation Monte Carlo (MC) simulations are used to estimate SM background contributions and to estimate the acceptance of the event selection for BSM models. The MadGraph5_amc@nlo 2.2.2 [ 33–35 ] and powheg v2 [ 36, 37 ] next-to-leading order (NLO) generators are used to simulate almost all SM background processes based on the NNPDF3.0 NLO [38] parton distribution functions (PDFs). New physics signal samples, as well as the same-sign W±W± process, are generated with MadGraph5_amc@nlo at leading order (LO) precision, with up to two additional partons in the matrix element calculations, using the NNPDF3.0 LO [ 38 ] PDFs. Parton showering and hadronization, as well as the double-parton scattering production of W±W±, are described using the pythia 8.205 generator [ 39 ] with the CUETP8M1 tune [ 40,41 ]. The Geant4 package [42] is used to model the CMS detector response for background samples, while the CMS fast simulation package [ 43 ] is used for signal samples. To improve on the MadGraph modeling of the multiplicity of additional jets from initial-state radiation (ISR), MadGraph tt MC events are reweighted based on the number of ISR jets (N JISR), so as to make the light-flavor jet multiplicity in dilepton tt events agree with the one observed in data. The same reweighting procedure is applied to SUSY MC events. The reweighting factors vary between 0.92 and 0.51 for N ISR between 1 and 6. We take one half of the deviation J from unity as the systematic uncertainty in these reweighting factors. The new physics signal models probed by this search are shown in Figs. 1 and 2. In each of the simplified SUSY models [ 44,45 ] of Fig. 1, only two or three new particles have masses sufficiently low to be produced on-shell, and the branching fraction for the decays shown are assumed to be 100%. Gluino pair production models giving rise to signatures with up to four b quarks and up to four W bosons are shown in Fig. 1a–e. In these models, the gluino decays to the lightest squark (g → qq), which in turn decays to same-flavor (q → qχ10) or different-flavor (q → q χ1±) quarks. The chargino decays to a W boson and a neutralino (χ1± → W±χ10), where the χ10 escapes detection and is taken to be the lightest SUSY particle (LSP). The first two scenarios considered in Fig. 1a, b include an off-shell thirdgeneration squark (t or b) leading to the three-body decay of g g (a) H(A) t t ¯ t ¯ t b q¯ the gluino, g → ttχ10 (T1tttt) and g → tbχ1+ (T5ttbbWW), resulting in events with four W bosons and four b quarks. In the T5ttbbWW model, the mass splitting between chargino aonfdthneeWutrabloinsoonissasreet ptoromduχc1±ed−ofmf-χs10he=ll a5nGdecVa n, sgoivteharitsetwtoo low transverse momentum ( pT) leptons. The next two models shown (Fig. 1c, d) include an on-shell top squark with different mass splitting between the t and the χ10, and consequently different decay modes: in the T5tttt model the mass splitting is equal to the top quark mass (mt − mχ10 = mt), favoring the t → tχ10 decay, while in the T5ttcc model the mass splitting is only 20 GeV, favoring the flavor changing neutral current t → cχ10 decay. In Fig. 1e, the decay proceeds through a virtual light-flavor squark, leading to a three-body decay to g → qq χ1±, resulting in a signature with two W bosons and four light-flavor jets. The two W bosons can have the same charge, giving rise to SS dileptons. This model, T5qqqqWW, is studied as a function of the gluino and χ10 mass, with two different assumptions for the chargino mass: mχ1± = 0.5(mg+mχ0 ), producing mostly on-shell W bosons, aFnindamllyχ,1±Fi=g. m1fχs10h+ow21s0aGmeVod, eplroofdubcoitntogmofsfq-suhaerlkl pWrobdouscotinosn. followed by the b → tχ1± decay, resulting in two b quarks and four W bosons. This model, T6ttWW, is studied as a function of the b and χ1± masses, keeping the χ10 mass at 50 GeV, resulting in two of the W bosons being produced off-shell when the χ1± and χ10 masses are close. The production cross sections for SUSY models are calculated at NLO plus next-to-leading logarithmic (NLL) accuracy [ 46– 51 ]. The processes shown in Fig. 2, ttH, tHq, and tWH, represent the top quark associated production of a scalar (H) or a pseudoscalar (A). The subsequent decay of the (pseudo)scalar to a pair of top quarks then gives rise to final states including a total of three or four top quarks. For the purpose of interpretation, we use LO cross sections for the production of a heavy Higgs boson in the context of the Type II 2HDM of Ref. [ 23 ]. The mass of the new particle is varied in the range [350, 550] GeV, where the lower mass boundary is chosen in such a way as to allow the decay of the (pseudo)scalar into on-shell top quarks. W H(A) t t ¯ t q¯ b g H(A) W t ¯ t t 3 The CMS detector and event reconstruction The central feature of the CMS detector 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 (HCAL), each composed of a barrel and two endcap sections. Forward calorimeters extend the pseudorapidity (η) coverage provided by the barrel and endcap detectors. Muons are measured in gas-ionization detectors embedded in the steel flux-return yoke outside the solenoid. 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 in Ref. [ 52 ]. Events of interest are selected using a two-tiered trigger system [ 53 ]. The first level (L1), composed of custom hardware processors, uses information from the calorimeters and muon detectors to select events at a rate of around 100 kHz within a time interval of less than 4 μs. The second level, known as the high-level trigger (HLT), consists of a farm of processors running a version of the full event reconstruction software optimized for fast processing, and reduces the event rate to less than 1 kHz before data storage. Events are processed using the particle-flow (PF) algorithm [ 54,55 ], which reconstructs and identifies each individual particle with an optimized combination of information from the various elements of the CMS detector. The energy of photons is directly obtained from the ECAL measurement. The energy of electrons is determined from a combination of the electron momentum at the primary interaction vertex as determined by the tracker, the energy of the corresponding ECAL cluster, and the energy sum of all bremsstrahlung photons spatially compatible with the electron track [56]. The energy of muons is obtained from the curvature of the corresponding track, combining information from the silicon tracker and the muon system [ 57 ]. The energy of charged hadrons is determined from a combination of their momentum measured in the tracker and the matching ECAL and HCAL energy deposits, corrected for the response function of the calorimeters to hadronic showers. Finally, the energy of neutral hadrons is obtained from the corresponding corrected ECAL and HCAL energy. Hadronic jets are clustered from neutral PF candidates and charged PF candidates associated with the primary vertex, using the anti-kT algorithm [ 58,59 ] with a distance parameter R = √( η)2 + ( φ)2 of 0.4. Jet momentum is determined as the vectorial sum of all PF candidate momenta in the jet. An offset correction is applied to jet energies to take into account the contribution from additional proton–proton interactions (pileup) within the same or nearby bunch crossings. Jet energy corrections are derived from simulation, and are improved with in situ measurements of the energy balance in dijet and photon+jet events [ 60,61 ]. Additional selection criteria are applied to each event to remove spurious jet-like features originating from isolated noise patterns in certain HCAL regions. Jets originating from b quarks are identified (b tagged) using the medium working point of the combined secondary vertex algorithm CSVv2 [ 62 ]. The missing transverse momentum vector pmiss is defined as the projection on T the plane perpendicular to the beams of the negative vector sum of the momenta of all reconstructed PF candidates in an event [ 63 ]. Its magnitude is referred to as E miss. The sum of T the transverse momenta of all jets in an event is referred to as HT. 4 Event selection and search strategy The event selection and the definition of the signal regions (SRs) follow closely the analysis strategy established in Ref. [ 24 ]. With respect to the previous search, the general strategy has remained unchanged. We target, in a generic way, new physics signatures that result in SS dileptons, hadronic activity, and E miss, by subdividing the event sam T ple into several SRs sensitive to a variety of new physics models. The number of SRs was increased to take advantage of the larger integrated luminosity. Table 1 summarizes the basic kinematic requirements for jets and leptons (further details, including the lepton identification and isolation requirements, can be found in Ref. [ 24 ]). Events are selected using triggers based on two sets of HLT algorithms, one simply requiring two leptons, and one pT ( GeV) >15 >10 >40 >25 |η| additionally requiring HT > 300 GeV. The HT requirement allows for the lepton isolation requirement to be removed and for the lepton pT thresholds to be set to 8 GeV for both leptons, while in the pure dilepton trigger the leading and subleading leptons are required to have pT > 23 (17) GeV and pT > 12 (8) GeV, respectively, for electrons (muons). Based on these trigger requirements, leptons are classified as high ( pT > 25 GeV) and low (10 < pT < 25 GeV) momentum, and three analysis regions are defined: high-high (HH), high-low (HL), and low-low (LL). The baseline selection used in this analysis requires at least one SS lepton pair with an invariant mass above 8 GeV, at least two jets, and E miss > 50 GeV. To reduce Drell–Yan T backgrounds, events are rejected if an additional loose lepton forms an opposite-sign same-flavor pair with one of the two SS leptons, with an invariant mass less than 12 GeV or between 76 and 106 GeV. Events passing the baseline selection are then divided into SRs to separate the different background processes and to maximize the sensitivity to signatures with different jet multiplicity (Njets), flavor (Nb), visible and invisible energy (HT and E miss), and lepton momentum T spectra (the HH/HL/LL categories mentioned previously). The mmin variable is defined as the smallest of the transverse T masses constructed between pmiss and each of the leptons. T This variable features a cutoff near the W boson mass for processes with only one prompt lepton, so it is used to create SRs where the nonprompt lepton background is negligible. To further improve sensitivity, several regions are split according to the charge of the leptons (++ or −−), taking advantage of the charge asymmetry of SM backgrounds, such as ttW or WZ, with a single W boson produced in pp collisions. Only signal regions dominated by such backgrounds and with a sufficient predicted yield are split by charge. In the HH and HL categories, events in the tail regions HT > 1125 GeV or E miss > 300 GeV are inclusive in Njets, Nb, and mmin in T T order to ensure a reasonable yield of events in these SRs. The exclusive SRs resulting from this classification are defined in Tables 2, 3 and 4. The lepton reconstruction and identification efficiency is in the range of 45–70% (70–90%) for electrons (muons) with pT > 25 GeV, increasing as a function of pT and converging to the maximum value for pT > 60 GeV. In the lowmomentum regime, 15 < pT < 25 GeV for electrons and 10 < pT < 25 GeV for muons, the efficiencies are 40% for electrons and 55% for muons. The lepton trigger efficiency for electrons is in the range of 90–98%, converging to the maximum value for pT > 30 GeV, and around 92% for muons. The chosen b tagging working point results in approximately a 70% efficiency for tagging a b quark jet and a <1% mistagging rate for light-flavor jets in tt events [ 62 ]. The efficiencies of the HT and E miss requirements are mostly T determined by the jet energy and E miss resolutions, which are T discussed in Refs. [ 60,61,64 ]. 200−300 50−200 200−300 50−200 200−300 50−200 200−300 50−200 200−300 50−200 200−300 50−300 300−500 >500 ≥5 2–4 ≥5 2–4 ≥5 2–4 ≥5 2–4 ≥5 2–4 ≥5 2–4 ≥5 2–4 ≥5 2–4 ≥5 2–4 ≥5 2–4 ≥5 2–4 ≥5 ≥2 ≥2 ≥2 SR3 SR11 SR13 (++)/ SR14 (−−) SR23 SR25 (++)/ SR26 (−−) SR35 (++)/ SR36 (−−) SR40 – – between SR3 and SR11 are included in SR3, with the exception of the regions to the right of SR42-45, which are included in those regions Standard model background contributions arise from three sources: processes with prompt SS dileptons, mostly relevant in regions with high E miss or HT; events with a nonprompt T lepton, dominating the overall final state; and opposite-sign dilepton events with a charge-misidentified lepton, the smallest contribution. In this paper we use the shorthand “nonprompt leptons” to refer to electrons or muons from the decays of heavy- or light-flavor hadrons, hadrons misidentified as leptons, or electrons from conversions of photons in jets. Nb 0 1 2 200−300 Table 3 Signal region definitions for the HL selection. Regions split by charge are indicated with (++) and (−−). All unlabeled region are included in the SR above them, for example the unlabeled regions between SR3 and SR8 are included in SR3, with the exception of the regions to the right of SR34-37, which are included in those regions Several categories of SM processes that result in the production of electroweak bosons can give rise to an SS dilepton final state. These include production of multiple bosons in the same event (prompt photons, W, Z, and Higgs bosons), as well as single-boson production in association with top quarks. Among these SM processes, the dominant ones are WZ, ttW, and ttZ production, followed by the W±W± process. The remaining SM processes are grouped into two categories, “Rare” (including ZZ, WWZ, WZZ, ZZZ, tWZ, tZq, as well as tttt and double parton scattering) and “X+γ” (including Wγ, Zγ, ttγ, and tγ). The expected yields from these SM backgrounds are estimated from simulation, accounting for both the theoretical and experimental uncertainties discussed in Sect. 6. For the WZ and ttZ backgrounds, a three-lepton (3L) control region in data is used to scale the simulation, based on a template fit to the distribution of the number of b jets. The 3L control region requires at least two jets, E miss > 30 GeV, T and three leptons, two of which must form an opposite-sign same-flavor pair with an invariant mass within 15 GeV of the Z boson mass. In the fit to data, the normalization and shapes of all the components are allowed to vary according to experimental and theoretical uncertainties. The scale factors obtained from the fit in the phase space of the 3L control region are 1.26 ± 0.09 for the WZ process, and 1.14 ± 0.30 for the ttZ process. The nonprompt lepton background, which is largest for regions with low mmin and low HT, is estimated by the “tight T to-loose” method, which was employed in several previous versions of the analysis [ 28–32 ], and significantly improved in the latest version [ 24 ] to account for the kinematics and flavor of the parent parton of the nonprompt lepton. The tightto-loose method uses two control regions, the measurement region and the application region. The measurement region consists of a sample of single-lepton events enriched in nonprompt leptons by requirements on E miss and transverse mass T that suppress the W → ν contribution. This sample is used to extract the probability for a nonprompt lepton that satisfies the loose selection to also satisfy the tight selection. This probability ( TL) is calculated as a function of lepton pcorr T (defined below) and η, separately for electrons and muons, and separately for lepton triggers with and without an isolation requirement. The application region is a SS dilepton region where both of the leptons satisfy the loose selection but at least one of them fails the tight selection. This region is subsequently divided into a set of subregions with the exact same kinematic requirements as those in the SRs. Events in the subregions are weighted by a factor TL/(1 − TL) for each lepton in the event failing the tight requirement. The nonprompt background in each SR is then estimated as the sum of the event weights in the corresponding subregion. The pcorr parametrization, where pcorr is defined as the lep T T ton pT plus the energy in the isolation cone exceeding the isolation threshold value, is chosen because of its correlation with the parent parton pT, improving the stability of the TL values with respect to the sample kinematics. To improve the stability of the TL values with respect to the flavor of the parent parton, the loose electron selection is adopted. This selection increases the number of nonprompt electrons from the fragmentation and decay of light-flavor partons, resulting in TL values similar to those from heavy-flavor parent partons. The prediction from the tight-to-loose method is crosschecked using an alternative method based on the same principle, similar to that described in Ref. [ 65 ]. In this cross-check, which aims to remove kinematic differences between measurement and application regions, the measurement region is obtained from SS dilepton events where one of the leptons fails the impact parameter requirement. With respect to the nominal method, the loose lepton definition is adapted to reduce the effect of the correlation between isolation and impact parameter. The predictions of the two methods are found to be consistent within systematic uncertainties. Charge misidentification of electrons is a small background that can arise from severe bremsstrahlung in the tracker material. Simulation-based studies with tight leptons indicate that the muon charge misidentification probability is negligible, while for electrons it ranges between 10−5 and 10−3. The charge misidentification background is estimated from data using an opposite-sign control region for each SS SR, scaling the control region yield by the charge misidentification probability measured in simulation. A low-ETmiss control region, with e+e− pairs in the Z boson mass window, is used to cross-check the MC prediction for the misidentification probability, both inclusively and – where the number of events in data allows it – as a function of electron pT and η. 6 Systematic uncertainties Several sources of systematic uncertainty affect the predicted yields for signal and background processes, as summarized in Table 5. Experimental uncertainties are based on measurements in data of the trigger efficiency, the lepton identification efficiency, the b tagging efficiency [ 62 ], the jet energy scale, and the integrated luminosity [ 66 ], as well as on the inelastic cross section value affecting the pileup rate. Theoretical uncertainties related to unknown higher-order effects are estimated by varying simultaneously the factorization and renormalization scales by a factor of two, while uncertainties in the PDFs are obtained using replicas of the NNPDF3.0 set [ 38 ]. Experimental and theoretical uncertainties affect both the overall yield (normalization) and the relative population (shape) across SRs, and they are taken into account for all signal samples as well as for the samples used to estimate the main prompt SS dilepton backgrounds: WZ, ttW, ttZ, W±W±. For the WZ and ttZ backgrounds, the control region fit results are used for the normalization, so these uncertainties are only taken into account for the shape of the backgrounds. For the smallest background samples, Rare and X+γ, a 50% uncertainty is assigned in place of the scale and PDF variations. Table 5 Summary of the sources of uncertainty and their effect on the yields of different processes in the SRs. The first eight uncertainties are related to experimental and theoretical factors for processes estimated using simulation, while the last four uncertainties are assigned to processes whose yield is estimated from data. The first seven uncertainties also apply to signal samples. Reported values are representative for the most relevant signal regions Source Integrated luminosity Lepton selection Trigger efficiency Pileup Jet energy scale b tagging Simulated sample size Scale and PDF variations WZ (normalization) ttZ (normalization) Nonprompt leptons Charge misidentification Typical uncertainty (%) 2.5 4–10 2–7 0–6 1–15 1–15 1–10 10–20 12 30 30–60 20 CMS (b) CMS (d) 1eV000 Baseline selection: 2 SS lep., Njets≥2, ETmiss>50 GeV 0 (c) G 2 / ise800 tr n E /.traedaP 2341 D 0 s itre104 n E 103 102 10 1 10−1 35.9 fb-1 (13 TeV) Data Nonprompt lep. WZ ttZ/H ttW X+γ Rare SM WW Charge misid. 30 35 40 Signal Region 1 2 3 4 5 6 7 8 Signal Region The normalization and the shapes of the nonprompt lepton and charge misidentification backgrounds are estimated from control regions in data. In addition to the statistical uncertainties from the control region yields, dedicated systematic uncertainties are associated with the methods used in this estimate. For the nonprompt lepton background, a 30% uncertainty (increased to 60% for electrons with pT > 50 GeV) accounts for the performance of the method in simulation and for the differences in the two alternative methods described in Sect. 5. In addition, the uncertainty in the prompt lepton yield in the measurement region, relevant when estimating TL for high- pT leptons, results in a 1–30% effect on the estimate. For the charge misidentification background, a 20% uncertainty is assigned to account for possible mismodeling of the charge misidentification rate in simulation. 7 Results and interpretation A comparison between observed yields and the SM background prediction is shown in Fig. 3 for the kinematic variables used to define the analysis SRs: HT, E miss, mTmin, Njets, T and Nb. The distributions are shown after the baseline selection defined in Sect. 4. The full results of the search in each Table 6 Number of expected background and observed events in different SRs in this analysis Eur. Phys. J. C (2017) 77:578 SR1 SR2 SR3 SR4 SR5 SR6 SR7 SR8 SR9 SR10 SR11 SR12 SR13 SR14 SR15 SR16 SR17 SR18 SR19 SR20 SR21 SR22 SR23 SR24 SR25 SR26 SR27 SR28 SR29 SR30 SR31 SR32 SR33 SR34 SR35 SR36 SR37 SR38 SR39 SR40 SR41 SR42 SR43 SR44 SR45 SR46 SR47 SR48 SR49 SR50 SR51 SR are shown in Fig. 4 and Table 6. The SM predictions are generally consistent with the data. The largest deviations are seen in HL SR 36 and 38, with a local significance, taking these regions individually or combining them with other regions adjacent in phase space, that does not exceed 2 standard deviations. These results are used to probe the signal models discussed in Sect. 2: simplified SUSY models, (pseudo)scalar boson production, four top quark production, and SS top quark production. We also interpret the results as modelindependent limits as a function of HT and E miss. With the T exception of the new (pseudo)scalar boson limits, the results can be compared to the previous version of the analysis [ 24 ], ues for a given point in the SUSY particle mass plane. The solid, black curves represent the observed exclusion limits assuming the NLO+NLL cross sections [ 46–51 ] (thick line), or their variations of ±1 standard deviation (thin lines). The dashed, red curves show the expected limits with the corresponding ±1 and ±2 standard deviation experimental uncertainties. Excluded regions are to the left and below the limit curves showing significant improvements due to the increase in the integrated luminosity and the optimization of SR definitions. To obtain exclusion limits at the 95% confidence level (CL), the results from all SRs – including signal and background uncertainties and their correlations – are combined using an asymptotic formulation of the modified frequentist CLs criterion [ 67–70 ]. When testing a model, all new particles not included in the specific model are considered too heavy to take part in the interaction. To convert cross section limits into mass limits, the signal cross sections specified in Sect. 2 are used. The observed SUSY cross section limits as a function of the gluino and LSP masses, as well as the observed and expected mass limits for each simplified model, are shown in Fig. 5 for gluino pair production models with each gluino decaying through a chain containing off- or on-shell thirdgeneration squarks. These models, which result in signatures with two or more b quarks and two or more W bosons in the final state, are introduced in Sect. 2 as T1tttt, T5ttbbWW, T5tttt, and T5ttcc. Figure 6 shows the limits for a model of gluino production followed by a decay through off-shell first- or second-generation squarks and a chargino. Two different assumptions are made on the chargino mass, taken to be between that of the gluino and the LSP. These T5qqqqWW models result in no b quarks and either on-shell or off-shell W bosons. Bottom squark pair production followed by a decay through a chargino, T6ttWW, resulting in two b quarks and four W bosons, is shown in Fig. 7. For all of the models probed, the observed limit agrees well with the expected one, extending the reach of the previous analysis by 200–300 GeV and reaching 1.5, 1.1, and 0.83 TeV for gluino, LSP, and bottom squark masses, respectively. The observed and expected cross section limits on the production of a heavy scalar or a pseudoscalar boson in association with one or two top quarks, followed by its decay to top quarks, are shown in Fig. 8. The limits are compared with the total cross section of the processes described in Sect. 2. The observed limit, which agrees well with the expected one, excludes scalar (pseudoscalar) masses up to 360 (410) GeV. The SM four top quark production, pp → tttt, is normally included among the rare SM backgrounds. When treating this process as signal, its observed (expected) cross section limit is determined to be 42 (27+−183) fb at 95% CL, to be compared to the SM expectation of 9.2−+22..49 fb [ 33 ]. This is a significant improvement with respect to the observed (expected) limits obtained in the previous version of this analysis, 119 (102−+3557) fb [ 24 ], as well as the combination of those results with results from single-lepton and opposite-sign dilepton final states, 69 (71+−3284) fb [ 71 ]. The results of the search are also used to set a limit on the production cross section for SS top quark pairs, σ (pp → tt) + σ (pp → tt). The observed (expected) limit, based on the kinematics of a SM tt sample and determined using the number of b jets distribution in the baseline region, is 1.2 (0.76+−00..32) pb at 95% CL, significantly improved with Model-independent σAε exclusion limit Fig. 8 Limits at 95% CL on the production cross section for heavy scalar (a) and pseudoscalar (b) boson in association to one or two top quarks, followed by its decay to top quarks, as a function of the (pseudo)scalar mass. The red line corresponds to the theoretical cross section in the (pseudo)scalar model respect to the 1.7 (1.5+−00..74) pb observed (expected) limit of the previous analysis [ 24 ]. 7.1 Model-independent limits and additional results The yields and background predictions can be used to test additional BSM physics scenarios. To facilitate such reinterpretations, we provide limits on the number of SS dilepton pairs as a function of the E miss and HT thresholds in the T 0 >1125 >1200 >1300 >1400 >1500 >1600 >1700 >1800 >1900 >2000 H (GeV) T Fig. 9 Limits on the product of cross section, detector acceptance, and selection efficiency, σA , for the production of an SS dilepton pair as a function of the E miss (a) and of HT (b) thresholds T kinematic tails, as well as results from a smaller number of inclusive and exclusive signal regions. The E miss and HT limits are based on combining HH T tail SRs, specifically SR42–45 for high E miss and SR46– T 51 for high HT, and employing the CLs criterion without the asymptotic formulation as a function of the minimum threshold of each kinematic variable. These limits are presented in Fig. 9 in terms of σA , the product of cross section, detector acceptance, and selection efficiency. Where no events are observed, the observed and expected limits reach 0.1 fb, to signal acceptance is assumed in calculating these limits. A dash (–) means that the selection is not applied be compared with a limit of 1.3 fb obtained in the previous analysis [ 24 ]. Results are also provided in Table 7 for a small number of inclusive signal regions, designed based on different topologies and a small number of expected background events. The background expectation, the event count, and the expected BSM yield in any one of these regions can be used to constrain BSM hypotheses in a simple way. In addition, we define a small number of exclusive signal regions based on integrating over the standard signal regions. Their definitions, as well as the expected and observed yields, are specified in Table 8, while the correlation matrix for the background predictions in these regions is given in Fig. 10. This information can be used to construct a simplified likelihood for models of new physics, as described in Ref. [ 72 ]. 8 Summary A sample of same-sign dilepton events produced in proton– proton collisions at 13 TeV, corresponding to an integrated ExSR15 ExSR14 ExSR13 ExSR12 ExSR11 ExSR10 ExSR9 ExSR8 ExSR7 ExSR6 ExSR5 ExSR4 ExSR3 ExSR2 ExSR1 CMS 35.9 fb-1 (13 TeV) 0.285 luminosity of 35.9 fb−1, has been studied to search for manifestations of physics beyond the standard model. The data are found to be consistent with the standard model expectations, and no excess event yield is observed. The results are interpreted as limits at 95% confidence level on cross sections for the production of new particles in simplified supersymmetric models. Using calculations for these cross sections as functions of particle masses, the limits are turned into lower mass limits that are as high as 1500 GeV for gluinos and 830 GeV for bottom squarks, depending on the details of the model. Limits are also provided on the production of heavy scalar (excluding the mass range 350–360 GeV) and pseudoscalar (350–410 GeV) bosons decaying to top quarks in the context of two Higgs doublet models, as well as on same-sign top quark pair production, and the standard model production of four top quarks. Finally, to facilitate further interpretations of the search, model-independent limits are provided as a function of HT and E miss, together with the background T prediction and data yields in a smaller set of signal regions. 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 (UK); DOE and NSF (USA). Individuals have received support from the Marie-Curie program and the European Research Council and EPLANET (European Union); the Leventis Foundation; the A. P. Sloan Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science Policy Office; the Fonds pour la Formation à la Recherche dans l’Industrie et dans l’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Council of Science and Industrial Research, India; the HOMING PLUS 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), con1 0.9 tracts 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 Clarín-COFUND del Principado de Asturias; the Thalis and Aristeia programs cofinanced by EUESF 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); and the Welch Foundation, contract C-1845. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecomm ons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Funded by SCOAP3. Yerevan Physics Institute, Yerevan, Armenia A. M. Sirunyan, A. Tumasyan Institut für Hochenergiephysik, Wien, 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, J. Strauss, W. Waltenberger, J. Wittmann, C. -E. Wulz1, M. 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Finger Jr.6 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. Assran7,8, S. Elgammal8, A. Mahrous9 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 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, O. Davignon, R. Granier de Cassagnac, M. Jo, S. Lisniak, A. Lobanov, J. Martin Blanco, M. Nguyen, C. Ochando, G. Ortona, P. Paganini, P. Pigard, S. Regnard, R. Salerno, J. B. Sauvan, Y. Sirois, A. G. Stahl Leiton, T. Strebler, Y. Yilmaz, A. 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Ujvari Indian Institute of Science (IISc), Bangalore, India S. Choudhury, J. R. Komaragiri National Institute of Science Education and Research, Bhubaneswar, India S. Bahinipati19, S. Bhowmik, P. Mal, K. Mandal, A. Nayak20, D. K. Sahoo19, N. Sahoo, S. K. Swain 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. Mohanty12, 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, B. Parida, 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. Chenarani23, E. Eskandari Tadavani, S. M. Etesami23, M. Khakzad, M. Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi24, F. Rezaei Hosseinabadi, B. Safarzadeh25, M. Zeinali University College Dublin, Dublin, Ireland M. Felcini, M. Grunewald INFN Sezione di Bari a , Università di Bari b, Politecnico di Bari c, Bari, Italy M. Abbresciaa ,b, C. Calabriaa ,b, C. Caputoa ,b, A. Colaleoa , D. Creanzaa ,c, L. Cristellaa ,b, N. De Filippisa ,c, M. De Palmaa ,b, F. Erricoa ,b, L. Fiorea , G. Iasellia ,c, 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. Selvaggia ,b, A. Sharmaa , L. Silvestrisa ,12, R. Vendittia , P. Verwilligena INFN Sezione di Bologna a , Università di Bologna b, Bologna, Italy G. Abbiendia , C. Battilana, D. Bonacorsia ,b, S. Braibant-Giacomellia ,b, L. Brigliadoria ,b, R. Campaninia ,b, P. Capiluppia ,b, A. Castroa ,b, F. R. Cavalloa , S. S. Chhibraa ,b, G. Codispotia ,b, M. Cuffiania ,b, G. M. Dallavallea , F. Fabbria , A. Fanfania ,b, D. Fasanellaa ,b, P. Giacomellia , L. Guiduccia ,b, S. Marcellinia , G. 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Kim Korea University, Seoul, Korea S. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, Y. Jo, Y. Kim, K. Lee, K. S. Lee, S. Lee, J. Lim, S. K. Park, Y. Roh University of Seoul, Seoul, Korea M. Choi, H. Kim, J. H. Kim, J. S. H. Lee, I. C. Park, G. Ryu 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 Ali29, F. Mohamad Idris30, W. A. T. Wan Abdullah, M. N. Yusli, Z. Zolkapli 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 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, A. Saddique, M. A. Shah, M. Shoaib, M. Waqas Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Warsaw, Poland K. Bunkowski, A. Byszuk32, K. Doroba, A. Kalinowski, M. Konecki, J. Krolikowski, M. Misiura, M. Olszewski, A. Pyskir, M. Walczak Laboratório de Instrumentação e Física Experimental de Partículas, Lisbon, Portugal P. Bargassa, C. Beirão Da Cruz Silva, B. Calpas, A. Di Francesco, P. Faccioli, M. Gallinaro, J. Hollar, N. Leonardo, L. Lloret Iglesias, M. V. Nemallapudi, J. Seixas, O. Toldaiev, D. Vadruccio, J. Varela 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. Matveev33,34, V. Palichik, V. Perelygin, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, N. Voytishin, A. Zarubin Moscow Institute of Physics and Technology, Moscow, Russia T. Aushev, A. Bylinkin34 National Research Nuclear University ’Moscow Engineering Physics Institute’ (MEPhI), Moscow, Russia R. Chistov37, M. Danilov37, P. Parygin, D. Philippov, S. Polikarpov, E. Tarkovskii P.N. Lebedev Physical Institute, Moscow, Russia V. Andreev, M. Azarkin34, I. Dremin34, M. Kirakosyan34, A. Terkulov Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia A. Baskakov, A. Belyaev, E. Boos, M. Dubinin38, 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. Blinov39, Y. Skovpen39, D. Shtol39 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. Adzic40, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic, V. Rekovic Universidad Autónoma de Madrid, Madrid, Spain 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, 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 CERN, European Organization for Nuclear Research, Geneva, Switzerland D. Abbaneo, E. Auffray, P. Baillon, A. H. Ball, D. Barney, M. Bianco, P. Bloch, A. Bocci, C. Botta, T. Camporesi, R. Castello, M. Cepeda, G. Cerminara, E. Chapon, Y. Chen, D. d’Enterria, A. Dabrowski, V. 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Zeuner National Central University, Chung-Li, Taiwan V. Candelise, T. H. Doan, Sh. Jain, R. Khurana, M. Konyushikhin, C. M. Kuo, W. Lin, A. Pozdnyakov, S. S. Yu National Taiwan University (NTU), Taipei, Taiwan Arun Kumar, P. Chang, Y. Chao, K. F. Chen, P. H. Chen, F. Fiori, W.-S. Hou, Y. Hsiung, Y. F. Liu, R.-S. Lu, M. Miñano Moya, E. Paganis, A. Psallidas, J. F. Tsai Chulalongkorn University, Faculty of Science, Department of Physics, Bangkok, Thailand B. Asavapibhop, K. Kovitanggoon, G. Singh, N. Srimanobhas Cukurova University, Physics Department, Science and Art Faculty, Adana, Turkey A. Adiguzel48, 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, U. Kiminsu, M. Oglakci, G. Onengut52, K. Ozdemir53, D. Sunar Cerci49, B. Tali49, H. Topakli54, S. Turkcapar, I. S. Zorbakir, C. Zorbilmez Middle East Technical University, Physics Department, Ankara, Turkey B. Bilin, G. Karapinar55, K. Ocalan56, M. Yalvac, M. Zeyrek Bogazici University, Istanbul, Turkey E. Gülmez, M. Kaya57, O. Kaya58, S. Tekten, E. A. Yetkin59 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 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 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 Catholic University of America, Washington, 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, 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, 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 Florida International University, Miami, USA Y. R. Joshi, S. Linn, P. Markowitz, G. Martinez, 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 Johns Hopkins University, Baltimore, USA B. Blumenfeld, A. Cocoros, N. Eminizer, D. Fehling, L. Feng, A. V. Gritsan, P. Maksimovic, J. Roskes, U. Sarica, M. Swartz, M. Xiao, C. You The University of Kansas, Lawrence, USA A. Al-bataineh, P. Baringer, A. Bean, S. Boren, J. Bowen, J. Castle, S. Khalil, A. Kropivnitskaya, D. Majumder, W. Mcbrayer, M. Murray, C. Royon, S. Sanders, E. Schmitz, R. Stringer, J. D. Tapia Takaki, Q. Wang 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 University of Puerto Rico, Mayaguez, USA S. Malik, S. Norberg Purdue University Northwest, Hammond, USA T. Cheng, 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, J. Roberts, J. Rorie, Z. Tu, J. Zabel 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 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 Wayne State University, Detroit, USA C. Clarke, 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 Joint Institute for Nuclear Research, Dubna, Russia 7: Also at Suez University, Suez, Egypt 8: Now at British University in Egypt, Cairo, Egypt 9: Now at Helwan University, Cairo, Egypt 10: Also at Université de Haute Alsace, Mulhouse, France 11: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia 12: Also at CERN, European Organization for Nuclear Research, Geneva, Switzerland 13: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany 14: Also at University of Hamburg, Hamburg, Germany 15: Also at Brandenburg University of Technology, Cottbus, Germany 16: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary 17: Also at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös Loránd University, Budapest, Hungary 18: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary 19: Also at Indian Institute of Technology Bhubaneswar, Bhubaneswar, India 20: Also at Institute of Physics, Bhubaneswar, India 21: Also at University of Visva-Bharati, Santiniketan, India 22: Also at University of Ruhuna, Matara, Sri Lanka 23: Also at Isfahan University of Technology, Isfahan, Iran 24: Also at Yazd University, Yazd, Iran 25: Also at Plasma Physics Research Center, Science and Research Branch, Islamic Azad University, Tehran, Iran 26: Also at Università degli Studi di Siena, Siena, Italy 27: Also at INFN Sezione di Milano-Bicocca; Università di Milano-Bicocca, Milan, Italy 28: Also at Purdue University, West Lafayette, USA 29: Also at International Islamic University of Malaysia, Kuala Lumpur, Malaysia 30: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia 31: Also at Consejo Nacional de Ciencia y Tecnología, Mexico City, Mexico 32: Also at Warsaw University of Technology, Institute of Electronic Systems, Warsaw, Poland 33: Also at Institute for Nuclear Research, Moscow, Russia 34: Now at National Research Nuclear University ’Moscow Engineering Physics Institute’ (MEPhI), Moscow, Russia 35: Also at St. Petersburg State Polytechnical University, St. Petersburg, Russia 36: Also at University of Florida, Gainesville, USA 37: Also at P.N. Lebedev Physical Institute, Moscow, Russia 38: Also at California Institute of Technology, Pasadena, USA 39: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia 40: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia 41: Also at INFN Sezione di Roma; Sapienza Università di Roma, Rome, Italy 42: Also at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia 43: Also at Scuola Normale e Sezione dell’INFN, Pisa, Italy 44: Also at National and Kapodistrian University of Athens, Athens, Greece 45: Also at Riga Technical University, Riga, Latvia 46: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia 47: Also at Albert Einstein Center for Fundamental Physics, Bern, Switzerland 48: Also at Istanbul University, Faculty of Science, Istanbul, Turkey 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 Gaziosmanpasa University, Tokat, Turkey 55: Also at Izmir Institute of Technology, Izmir, Turkey 56: Also at Necmettin Erbakan University, Konya, Turkey 57: Also at Marmara University, Istanbul, Turkey 58: Also at Kafkas University, Kars, Turkey 59: Also at Istanbul Bilgi University, Istanbul, Turkey 60: Also at Rutherford Appleton Laboratory, Didcot, UK 61: Also at School of Physics and Astronomy, University of Southampton, Southampton, UK 62: Also at Instituto de Astrofísica de Canarias, La Laguna, Spain 63: Also at Utah Valley University, Orem, USA 64: Also at BEYKENT UNIVERSITY, Istanbul, Turkey 65: Also at Bingol University, Bingol, Turkey 66: Also at Erzincan University, Erzincan, Turkey 67: Also at Sinop University, Sinop, Turkey 68: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey 69: Also at Texas A&M University at Qatar, Doha, Qatar 70: Also at Kyungpook National University, Taegu, Korea 1. 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