Search for electroweak production of charginos in final states with two τ leptons in pp collisions at \( \sqrt{s}=8 \) TeV

Journal of High Energy Physics, Apr 2017

Results are presented from a search for the electroweak production of supersymmetric particles in pp collisions in final states with two τ leptons. The data sample corresponds to an integrated luminosity between 18.1 fb−1 and 19.6 fb−1 depending on the final state of τ lepton decays, at \( \sqrt{s}=8 \) TeV, collected by the CMS experiment at the LHC. The observed event yields in the signal regions are consistent with the expected standard model backgrounds. The results are interpreted using simplified models describing the pair production and decays of charginos or τ sleptons. For models describing the pair production of the lightest chargino, exclusion regions are obtained in the plane of chargino mass vs. neutralino mass under the following assumptions: the chargino decays into third-generation sleptons, which are taken to be the lightest sleptons, and the sleptons masses lie midway between those of the chargino and the neutralino. Chargino masses below 420 GeV are excluded at a 95% confidence level in the limit of a massless neutralino, and for neutralino masses up to 100 GeV, chargino masses up to 325 GeV are excluded at 95% confidence level. Constraints are also placed on the cross section for pair production of τ sleptons as a function of mass, assuming a massless neutralino.

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Search for electroweak production of charginos in final states with two τ leptons in pp collisions at \( \sqrt{s}=8 \) TeV

Received: October Search for electroweak production of charginos in nal p s nal state of 0 1 2 0 leptons. The data sample 1 [25] A. Barr , C. Lester and P. Stephens, m(T2): The Truth behind the glamour, J. Phys. G 29 2 University , Budapest , Hungary Results are presented from a search for the electroweak production of supersymmetric particles in pp collisions in nal states with two corresponds to an integrated luminosity between 18.1 fb 1 and 19.6 fb 1 depending on the into third-generation sleptons, which are taken to be the lightest sleptons, and the sleptons masses lie midway between those of the chargino and the neutralino. Chargino masses below 420 GeV are excluded at a 95% con dence level in the limit of a massless neutralino, and for neutralino masses up to 100 GeV, chargino masses up to 325 GeV are excluded at 95% con dence level. Constraints are also placed on the cross section for pair production sleptons as a function of mass, assuming a massless neutralino. Hadron-Hadron scattering (experiments); Supersymmetry - s = 8 TeV, collected by the CMS experiment at the LHC. The observed event yields in the signal regions are consistent with the expected standard model backgrounds. The results are interpreted using simpli ed models describing the pair production and decays of charginos or sleptons. For models describing the pair production of the lightest chargino, exclusion regions are obtained in the plane of chargino mass vs. neutralino mass under the following assumptions: the chargino decays 1 Introduction 2 The CMS detector and event reconstruction 3 The Monte Carlo samples 4 De nition of MT2 5 Event selection for the h h channel 6 Event selection for the ` h channel 7 Backgrounds 7.1 7.2 7.3 The QCD multijet background estimation in the h h channel W+jets background estimation in the h h channel The Drell-Yan background estimation Misidenti ed h in the ` h channels 8 Systematic uncertainties 9 Results and interpretation 10 Summary A Additional information for new model testing The CMS collaboration Supersymmetry (SUSY) [1{5] is one of the most promising extensions of the standard model (SM) of elementary particles. Certain classes of SUSY models can lead to the uni cation of gauge couplings at high energy, provide a solution to the gauge hierarchy problem without ne tuning by stabilizing the mass of the Higgs boson against large radiative corrections, and provide a stable dark matter candidate in models with conservation of R-parity. A key prediction of SUSY is the existence of new particles with the same gauge quantum numbers as SM particles but di ering by a half-unit in spin (sparticles). Extensive searches at the LHC have excluded the existence of strongly produced (colored) sparticles in a broad range of scenarios, with lower limits on sparticle masses ranging up to 1.8 TeV for gluino pair production [6{13]. While the limits do depend on the details lepton pairs from chargino (left) or slepton (right) pair of the assumed SUSY particle mass spectrum, constraints on the colorless sparticles are generally much less stringent. This motivates the electroweak SUSY search described in Searches for charginos ( e ), neutralinos ( e0), and sleptons (`e) by the ATLAS and CMS Collaborations are described in refs. [14{20]. In various SUSY models, the lightest SUSY partners of the SM leptons are those of the third generation, resulting in enhanced branching fractions for nal states with leptons [21]. The previous searches for charginos, neutralinos, and sleptons by the CMS Collaboration either did not include the possibility that the scalar lepton and its neutral partner (e and that the initial charginos and neutralinos are produced in vector-boson fusion processes [18]. production is improved and updated in ref. [20]. An ATLAS search for SUSY in the di- channel is reported in ref. [19], excluding chargino masses up to 345 GeV for a massless neutralino ( e01). The ATLAS results on direct e In this paper, a search for the electroweak production of the lightest charginos ( e1 ) and leptons (e) is repo1rted using events with two opposite-sign requirement on the magnitude of the missing transverse momentum vector, assuming the leptons and a modest masses of the third-generation sleptons are between those of the char1gino and the lightest ) are the lightest sleptons [16], or neutralino. Two leptons can be generated in the decay chain of gure 1. The results of the search are interpreted in the context of SUSY simpli ed model spectra (SMS) [22, 23] for both production mechanisms. The results are based on a data set of proton-proton (pp) collisions at p s = 8 TeV collected with the CMS detector at the LHC during 2012, corresponding to integrated luminosities of 18.1 and 19.6 fb 1 in di erent channels. This search makes use of the stransverse mass variable (MT2) [24, 25], which is the extension of transverse mass (MT) to the case where two massive particles with equal mass are created in pairs and decay to two invisible and two visible particles. In the case of this search, the visible particles leptons. The distribution of MT2 re ects the scale of the produced particles and has a longer tail for heavy sparticles compared to lighter SM particles. Hence, SUSY can manifest itself as an excess of events in the high-side tail of the MT2 distribution. Final states are considered where two leptons are each reconstructed via hadronic decays ( h h), or where only one (` h, where ` is an electron or muon). lepton decays hadronically and the other decays leptonically The paper is organized as follows. The CMS detector, the event reconstruction, and the data sets are described in sections 2 and 3. The MT2 variable is introduced in section 4. The selection criteria for the h h and ` h channels are described in section 5 and 6, respectively. A detailed study of the SM backgrounds is presented in section 7, while section 8 is devoted to the description of the systematic uncertainties. The results of the search with its statistical interpretation are presented in section 9. Section 10 presents the summaries. The e ciencies for the important selection criteria are summarized in appendix A and can be used to interpret these results within other phenomenological models. The CMS detector and event reconstruction The central feature of the CMS apparatus is a superconducting solenoid of 6 m internal diameter that provides a magnetic eld of 3.8 T. Within the solenoid volume are a silicon pixel and strip tracker, a lead tungstate crystal electromagnetic calorimeter, and a brass and scintillator hadron calorimeter, each composed of a barrel and two endcap sections. Muons are measured in gas-ionization detectors embedded in the steel ux-return yoke outside the solenoid. Extensive forward calorimetry complements the coverage provided by the barrel and endcap detectors. A more detailed description of the CMS detector, together with a de nition of the coordinate system used and the relevant kinematic variables, can be found To be recorded for further study, events from pp interactions must satisfy criteria imposed by a two-level trigger system. The rst level of the CMS trigger system, composed of custom hardware processors, uses information from the calorimeters and muon detectors to select the most interesting events in a xed time interval of less than 4 s. The high-level trigger processor farm further decreases the event rate from around 100 kHz to less than 1 kHz before data storage [27]. The particle- ow (PF) algorithm [28, 29] reconstructs and identi es each individual particle with an optimized combination of information from the various elements of the CMS detector. Jets are reconstructed from the PF candidates with the anti-kt clustering algorithm [30] using a distance parameter of 0.5. We apply corrections dependent on transverse momentum (pT) and pseudorapidity ( ) to account for residual e ects of nonuniform detector response [31]. A correction to account for multiple pp collisions within the same or nearby bunch crossings (pileup interactions) is estimated on an event-by-event basis using the jet area method described in ref. [32], and is applied to the reconstructed jet pT. The combined secondary vertex algorithm [33] is used to identify (\b tag") jets originating from b quarks. This algorithm is based on the reconstruction of secondary vertices, together with track-based lifetime information. In this analysis a working point is chosen such that, for jets with a pT value greater than 60 GeV the e ciency for tagging a jet containing a b quark is 70% with a light-parton jet misidenti cation rate of 1.5%, and c quark jet misidenti cation rate of 20%. Scale factors are applied to the simulated events to reproduce the tagging e ciencies measured in data, separately for jets originating from b or c quarks, and from light- avor partons. Jets with pT > 40 GeV and j j < 5:0 and b-tagged jets with pT > 20 GeV and j j < 2:4 are considered in this analysis. The PF candidates are used to reconstruct the missing transverse momentum vector p~miss, de ned as the negative of the vector sum of the transverse momenta of all PF candidates. For each event, pTmiss is de ned as the magnitude of p~Tmiss. Hadronically decaying leptons are reconstructed using the hadron-plus-strips algorithm [34]. The constituents of the reconstructed jets are used to identify individual lepton decay modes with one charged hadron and up to two neutral pions, or three charged hadrons. Additional discriminators are used to separate h from electrons and muons. leptons are expected to be isolated in the detector. To discriminate them from quantum chromodynamics (QCD) jets, an isolation variable [35] is de ned by the scalar sum of the transverse momenta of the charged hadrons and photons falling within a cone lepton momentum direction after correcting for the e ect of pileup. The \loose", \medium", and \tight" working points are de ned by requiring the value of the isolation variable not to exceed 2.0, 1.0, and 0.8 GeV, respectively. A similar measure of isolation is computed for charged leptons (e or ), where the isolation variable is divided by the pT of the lepton. This quantity is used to suppress the contribution from leptons produced in hadron decays in jets. The Monte Carlo samples The SUSY signal processes and SM samples, which are used to evaluate potential background contributions, are simulated using CTEQ6L1 [36] parton distribution functions. To model the parton shower and fragmentation, all generators are interfaced with pythia 6.426 [37]. The SM processes of Z+jets, W+jets, tt, and dibosons are generated using the MadGraph 5.1 [38] generator. Single top quark and Higgs boson events are generated with powheg 1.0 [39{42]. In the following, the events from Higgs boson production via gluon fusion, vector-boson fusion, or in association with a W or Z boson or a tt pair are referred to as \hX." Later on, the events containing at least one top quark or one Z boson are referred to as \tX" and \ZX," respectively. The masses of the top quark and Higgs boson are set to be 172.5 GeV [43] and 125 GeV [44], respectively. Since the nal state arising from the pair production of W bosons decaying into leptons is very similar to our signal, in the following gures its contribution is shown as an independent sample labeled as \WW." In one of the signal samples, pairs of charginos are produced with pythia 6.426 and decayed exclusively to the nal states that contain two neutrinos, and two neutralinos, as shown in gure 1 (left). The daughter sparticle in the two-body decay of the 50% branching fraction. The masses of the are set to be equal to the mean value gure 1 (left), so for m(e) = m(e ), the two decay chains (via the e01 masses and consequently are produced on mass shell. If the lepton from the ( e1 ) decay will have a low (high) momentum, resulting in a lower (higher) overall event selection e ciency, producing a weaker (stronger) limit on the chargino mass. In the case where the ( ) mass is close to the situations are opposite. Of the scenarios in which the slepton and the the same mass, the scenario with the highest e ciency overall corresponds to the one in . In this scenario, no decay modes are considered other than those which these masses are half-way between the masses of the sample, pairs of staus are also produced with pythia 6.426, that decay always to two leptons and two neutralinos, gure 1 (right). To improve the modeling of the decays, the tauola 1.1.1a [45] package is used for both signal and background events. In the data set considered in this paper, there are on average 21 pp interactions in each bunch crossing. Such additional interactions are generated with pythia and superimposed on simulated events in a manner consistent with the instantaneous luminosity pro le of the data set. The detector response in the Monte Carlo (MC) background event samples is modeled by a detailed simulation of the CMS detector based on Geant4 [46]. For the simulation of signal events, many samples of events, corresponding to a grid of e1 and e01 mass values, must be generated. To reduce computational requirements, signal events are processed by the CMS fast simulation [47] instead of Geant4. It is veri ed that the CMS fast simulation is in reasonable agreement with the detailed simulation for our signal which has hadronic decays of tau leptons in the nal state. The simulated events are reconstructed with similar algorithms used for collision data. The yields for the simulated SM background samples are normalized to the cross sections available in the literature. These cross sections correspond to next-to-next-toleading-order (NNLO) accuracy for Z+jets [48] and W+jets [49] events. For the tt simulated samples, the cross section used is calculated to full NNLO accuracy including the resummation of next-to-next-to-leading-logarithmic (NNLL) terms [50]. The event yields from diboson production are normalized to the next-to-leading-order (NLO) cross section taken from ref. [51]. The Resummino [52{54] program is used to calculate the signal cross sections at NLO+NLL level where NLL refers to next-to-leading-logarithmic precision. De nition of MT2 The MT2 variable [24, 25] is used in this analysis to discriminate between the SUSY signal and the SM backgrounds as proposed in ref. [55]. This variable has been used extensively by both CMS and ATLAS in searches for supersymmetry [10, 19]. The variable was introduced to measure the mass of primary pair-produced particles that eventually decay to undetected particles (e.g. neutralinos). Assuming the two primary SUSY particles undergo the same decay chain with visible and undetectable particles in the nal state, the system can be described by the visible mass (mvis(i)), transverse energy (ETvis(i)), and transverse between the two decay chains. The quantity p~miss is interpreted as the sum of the transverse momenta of the neutralinos, p~e10(i). In decay chains with neutrinos, p~Tmiss also includes T contributions from the p~T of the neutrinos. The transverse mass of each branch can be de ned as For a given me01 , the MT2 variable is de ned as MT2(me01 ) = =p~Tmiss For the correct value of me01 , the kinematic endpoint of the MT2 distribution is at the mass of the primary particle [56, 57], and it shifts accordingly when the assumed me01 is lower or higher than the correct value. In this analysis, the visible part of the decay chain consists of either the two h ( h h channel) or a combination of a muon or an electron with a h candidate (` h channel), so mvis(i) is the mass of a lepton and can be set to zero. We The background processes with a back-to-back topology of h h or ` h are expected values of pTmiss and the pT of the from Drell-Yan (DY) or dijet events where two jets are misidenti ed as h h or ` h. The resulting MT2 value is close to zero with our choices of me01 and mvis(i), regardless of the candidates. This is not the case for signal events, where the leptons are not in a back-to-back topology because of the presence of two undetected Event selection for the h h channel In this channel data of pp collisions, corresponding to an integrated luminosity of 18.1 fb 1, are used. The events are rst selected with a trigger [58] that requires the presence of two isolated h candidates with pT > 35 GeV and j j < 2.1, passing loose identi cation requirements. O ine, the two h candidates must pass the medium isolation discriminator, pT > 45 GeV and j j < 2.1, and have opposite sign (OS). In events with more than one h h pair, only the pair with the most isolated h objects is considered. Events with extra isolated electrons or muons of pT > 10 GeV and j j < 2.4 are rejected to suppress backgrounds from diboson decays. Inspired from the MC studies, the contribution from the Z ! h h background is reduced by rejecting events where the visible di- h invariant mass is between 55 and 85 GeV (Z boson veto). Furthermore, contributions from low-mass DY and QCD multijet production are reduced by requiring the invariant mass to be greater than 15 GeV . To further reduce Z ! multijet events, pTmiss > 30 GeV and MT2 > 40 GeV are also required. The minimum angle jets, must be greater than 1.0 radians. This requirement reduces backgrounds from QCD multijet events and W+jets events. After applying the preselection described above, additional requirements are introduced to de ne two search regions. The rst search region (SR1) targets models with a large mass di erence ( m) between charginos and neutralinos. In this case, the MT2 signal distribution can have a long tail beyond the distribution of SM backgrounds. The second search region (SR2) is dedicated to models with small values of m. In this case, the sum of the two transverse mass values, MTi = MT( h1; p~Tmiss) + MT( h2; p~Tmiss), provides additional discrimination between signal and SM background processes. The two signal regions (SR) are de ned as: SR1: MT2 > 90 GeV; SR2: MT2 < 90 GeV, MTi > 250 GeV, and events with b-tagged jets are vetoed. The veto on events containing b-tagged jets in SR2 reduces the number of tt events, which are expected in the low-MT2 region. Table 1 summarizes the selection requirements for the di erent signal regions. Event selection for the ` h channel Events in the ` h nal states (e h and h) are collected with triggers that require a loosely isolated h with pT > 20 GeV and j j < 2:3, as well as an isolated electron or muon with j j < 2:1 [58{60]. The minimum pT requirement for the electron (muon) was increased during the data taking from 20 to 22 GeV (17 to 18 GeV) due to the increase in instantaneous luminosity. An integrated luminosity of 19.6 fb 1 is used to study these In the o ine analysis, the electron, muon, and h objects are required to have pT > 25, 20, and 25 GeV, respectively, and the corresponding identi cation and isolation requirements are tightened. The j j requirements are the same as those in the online selections. In events with more than one opposite-sign ` h pair, only the pair that maximizes the scalar pT sum of h and electron or muon is considered. Events with additional loosely isolated leptons with pT > 10 GeV are rejected to suppress backgrounds from Z boson decays. Just as for the h h channel, preselection requirements to suppress QCD multijet, tt, , and low-mass resonance events are applied. These requirements are ` h invariant mass between 15 and 45 GeV or > 75 GeV (Z boson veto), pTmiss > 30 GeV, MT2 > 40 GeV, > 1:0 radians. The events with b-tagged jets are also rejected to reduce the tt background. The nal signal region requirements are MT2 > 90 GeV and MTh > 200 GeV . The latter requirement provides discrimination against the W+jets background. Unlike in the h h channel, events with MT2 < 90 GeV are not used because of the higher level of The summary of the selection requirements is shown in table 1. Figure 2 shows the MT2 distribution after the preselection requirements are imposed. The data are in good agreement with the SM expectations, evaluated from MC simulation, within the statistical uncertainties. A SUSY signal corresponding to high is used to show the expected signal distribution. = 380 GeV; me01 = 1 GeV) The backgrounds are studied in two categories: those with \misidenti ed" h, i.e., events where a quark or gluon jet has been misidenti ed as a h, and those with genuine h candidates. The QCD multijet and W+jets events are the dominant sources in the rst category, while a mixture of tt, Z+jets, diboson, and Higgs boson events dominate the second category. Background estimates are performed using control samples in data whenever possible. Those backgrounds that are taken from simulation are either validated in dedicated control regions or corrected using data-to-simulation scale factors. The estimates of the main backgrounds are discussed below, while the remaining contributions are small and are taken from simulation. /M 1 taa 0 Invariant mass of ` h or h h > 15 GeV Extra lepton veto Z boson mass veto pmiss > 30 GeV MT2 > 40 GeV b-tagged jet veto MTh > 200 GeV MT2 > 90 GeV b-tagged jet veto MT2 < 90 GeV MTi > 250 GeV /M 1 taa 0 to SM expectation in (left) e h and (right) h channels. The signal distribution is shown for thee1st=ati3s8ti0cGaleuVn;cmeret01ai=nt1ieGseaVre. sThohwenla.st bins include all over ows to higher values of MT2. Only m The QCD multijet background estimation in the h h channel Events from QCD multijet production can appear in the signal regions if two hadronic jets are misidenti ed as a h h pair. The isolation variable is a powerful discriminant between misidenti ed and genuine h candidates. To estimate the QCD multijet contribution, an ABCD method is used, where three h h control regions (CRs) are de ned using the loose h isolation requirement, together with lower thresholds on MT2 or MTi variables for the corresponding signal region. The former is changed from MT2 > 90 to >40 GeV, whereas the latter is reduced from MTi > 250 to >100 GeV . In addition, the requirement on Control Region 1 Control Region 2 Control Region 3 the QCD multijet background. is removed to increase the number of events in the CRs. To reduce contamination from genuine h h events in CRs with at least one loose h candidate, same-sign (SS) h h pairs are selected. Residual contributions from genuine h h and W+jets events (non-QCD events) are subtracted based on MC expectations. The CR and signal region are illustrated in gure 3. In the samples dominated by QCD multijet events (CR1 and CR2), the isolation of misidenti ed h candidates is found to be uncorrelated with the search variables MT2 MTi . The QCD multijet background in the signal regions is therefore estimated by scaling the number of QCD multijet events with high MT2 or high MTi and loosely isolated SS h h (CR3) by a transfer factor, which is the y-intercept of a horizontal line tted to the ratio of the numbers of events in CR1 and CR2 in di erent bins of the low values of the search variables. The nal estimate of the background is corrected for the e ciency of the requirement for QCD multijet events. This e ciency is measured in CR1 and CR2, in which the contribution of QCD multijet events is more than 80%. It is checked that the e ciency versus the search variable is same in both CR1 and CR2 and to gain in statistics, two CRs are combined before measuring the e ciency. The e ciency is a falling distribution as a function of the search variable (MT2 or MTi ) and the value of the last bin (65 < MT2 < 90 GeV or 200 < value of the e ciency in the signal regions. MTi < 250 GeV) is used conservatively as the The number of data events in CR3 after subtracting the non-QCD events is 4.81 3.55) for the SR1 (SR2) selection. For SR1 (SR2), the transfer factors e ciencies are measured to be 0.91 0.08), respectively. The reported uncertainties are the quadratic sum of the statistical and 0.11) and 0.03 +00::0043 (0.15 systematic uncertainties. The systematic uncertainty in the background estimates includes the uncertainty in the validity of the assumption that isolation and MT2 or MTi are not correlated, the QCD multijet background estimate 0:06 (stat)+00::1183 (syst) uncertainties are the statistical and systematic uncertainties of the method, and the last uncertainty is the extra systematic uncertainty due to the correlation assumptions. e ciency is extrapolated correctly to the signal regions, and the uncertainties in the residual non-QCD SM backgrounds which are subtracted based on MC expectations for di erent components of the background estimation. The latter includes both the statistical uncertainty of the simulated events and also a 22% systematic uncertainty that will be discussed in section 8, assigned uniformly to all simulated events. Table 2 summarizes the estimation of the QCD multijet background contribution in the two signal regions after extrapolation from the control regions and correcting for the e ciency. To evaluate the uncertainties in the transfer factor and e ciency due to the correlation assumptions, di erent t models are examined: (i) a horizontal line or a line with a constant slope is tted in the distributions of the transfer factor or for 40 < MT2 < 90 GeV in the SR1 case (100 < MTi < 250 GeV in the SR2 case); or (ii) the value of the last bin adjacent to the signal region is used. The weighted average of the estimates is compared with the reported values in table 2 to extract the \ t" uncertainty. W+jets background estimation in the h h channel In the h h channel, the number of remaining events for W+jets from MC is zero, but it has a large statistical uncertainty due to the lack of the statistics in the simulated sample. To have a better estimation, the contribution of the W+jets background in the h h channel is taken from simulated events, using the formula: NSR = FSNBFS: Here NSR is the estimation of W+jets events in the signal region, NBFS is the number of W+jets events before applying the nal selection criterion (MT2 > 90 GeV for SR1 and MTi > 250 GeV for SR2), but after applying all other selection criteria, including MT2 > 40 GeV for SR1 and 40 < MT2 < 90 GeV for SR2. The e ciency of the nal selection ( FS) for SR2. The value of NBFS is 31:9 6:2) for SR1 (SR2), where the uncertainties arise from the limited number of simulated events. The FS is evaluated in a simulated W+jets sample with a pair of opposite-sign h candidates, where the h candidates are selected with the same identi cation requirements as in the signal region, but with looser kinematic selection criteria to improve statistical precision. Additional signal selection requirements on or the lepton veto are applied one by one such that two orthogonal subsamples (passing and failing) are obtained. The FS quantity is calculated in all subsamples. The values are consistent with those obtained from the sample de ned with relaxed requirements within the statistical uncertainties. The W+jets background estimate \syst" comes from the maximum variation of the estimation found from varying the h energy scale within its uncertainty. The \shape" uncertainty takes into account the di erence between the shape of the search variable distribution in data and simulation. measured FS values from the looser-selection samples are 0.028 0.010 and 0.098 for SR1 and SR2, respectively. The uncertainty in the h energy scale is also taken into account in the uncertainty in FS. The W+jets simulated sample is validated in data using a same-sign h control sample, where both the normalization and FS are checked. The ratio of data to MC expectation is found to be 1:05 0:09) for SR1 (SR2), which is compatible with unity within the uncertainties. For FS, to take into account the di erence between the data and MC values, the MC prediction in each of the two signal regions is corrected by the ratio of FS(data) to FS(MC), which is 0:73 0:38) for SR1 (SR2), and its uncertainty is also taken to be the \shape" systematic uncertainty. Table 3 summarizes the estimated results for di erent signal regions for the h h channel. The Drell-Yan background estimation The DY background yield is obtained from the MC simulation. The simulated sample includes production of di erent lepton pairs (ee, ). The contribution from probabilities for ` ! ! `` events is found to be very small, because the misidenti cation h are su ciently low. The dominant background events are Z ! ! h h decays. The misidenti cation probability for h ! ` is also low, so the probability to have DY background contribution from Z ! the ` h channels is negligible. The simulation is validated in a h control region obtained by removing the requirement and by inverting the Z boson veto and also by requiring MT2 < 20 GeV, 40 < MTh < 100 GeV . The distributions of the invariant mass of the system for data and simulated events are in good agreement. The pT of the Z boson system, which is correlated with MT2, is also well reproduced in simulation. Table 4 summarizes the DY background contribution in the di erent signal regions. For ` h channels, only the contributions from the genuine lepton+ h are reported. A separate method is developed in section 7.4 to estimate the misidenti ed lepton contamination in these channels. The systematic uncertainties of the DY background are discussed in detail in section 8. Misidenti ed h in the ` h channels The contribution from misidenti ed h in the ` h channels is estimated using a method which takes into account the probability that a loosely isolated misidenti ed or genuine h passes the tight isolation requirements. If the signal selection is done using the h DY background estimate uncertainties are due to the limited number of MC events. candidates that pass the loose isolation, the number of loose h candidates (Nl) is: Nl = Ng + Nm Nt = rgNg + rmNm where Ng is the number of genuine h candidates and Nm is the number of misidenti ed h candidates. If the selection is tightened, the number of tight h candidates (Nt) is where rg (rm) is the genuine (misidenti ed h) rate, i.e., the probability that a loosely selected genuine (misidenti ed) h candidate passes the tight selection. One can obtain the following expression by eliminating Ng: rmNm = rm(Nt rgNl)=(rm Here, the product rmNm is the contamination of misidenti ed h candidates in the signal region. This is determined by measuring rm and rg along with the number of loose h candidates (Nl) and the number of tight h candidates (Nt). The misidenti cation rate (rm) is measured as the ratio of tightly selected h candidates to loosely selected h candidates in a sample dominated by misidenti ed h candidates. requirement, i.e., pmiss < 30 GeV . The misidenti cation rate is measured to be 0:54 The genuine h candidate rate (rg) is estimated in simulated DY events; it is found to be rg = 0:766 0:003 and almost independent of MT2. A relative systematic uncertainty of 5% is assigned to the central value of rg to cover its variations for di erent values of MT2. The method is validated in the simulated W+jets sample using the misidenti cation rate which is evaluated with the same method as used for data. This misidenti cation of ` h background events in this sample within the uncertainties. These include statistical uncertainties due to the number of events in the sidebands (loosely selected h candidates), as well as systematic uncertainties. The uncertainties in the misidenti cation rate and the genuine h candidate rate are negligible compared to the statistical uncertainties associated to the control regions. The estimates of the misidenti ed h contamination in the two ` h channels are summarized in table 5. The relative statistical and systematic uncertainties are reported separately. Since the same misidenti ed and genuine h candidate rates are used to estimate Channel Total misid (events) Stat (%) rm syst (%) rg syst (%) Total uncert (%) total systematic uncertainty is the quadratic sum of the individual components. All uncertainties are relative. The rm (rg) is shorthand for misidenti ed (genuine) h candidate rate. the backgrounds for both the e h and h channels, the total systematic uncertainties are considered fully correlated between the two channels. The numbers of misidenti ed events (3.30 for the e h channel and 8.15 for the h channel) are consistent within the statistical uncertainties in our control samples. Systematic uncertainties Systematic uncertainties can a ect the shape or normalization of the backgrounds estimated from simulation (tt, Z+jets, diboson, and Higgs boson events), as well as the signal acceptance. Systematic uncertainties of other background contributions are described in sections 7.1, 7.2 and 7.4. The uncertainties are listed below, and summarized in table 6. The energy scales for electron, muon, and h objects a ect the shape of the kinematic distributions. The systematic uncertainties in the muon and electron energy scales are negligible. The visible energy of h object in the MC simulation is scaled up and down by 3%, and all h-related variables are recalculated. The resulting variations nal yields are taken as the systematic uncertainties. They are evaluated to be 10{15% for backgrounds and 2{15% in di erent parts of the signal phase space. The uncertainty in the h identi cation e ciency is 6%. The uncertainty in the trigger e ciency of the h part of the e h and h ( h h) triggers amounts to 3.0% (4.5%) per h candidate. A \tag-and-probe" technique [61] on Z ! used to estimate these uncertainties [35]. The uncertainty in electron and muon trigger, identi cation, and isolation e ciencies The uncertainty due to the scale factor for the b-tagging e ciency and misidenti cation rate is evaluated by varying the factors within their uncertainties. The yields of signal and background events are changed by 8% and 4%, respectively [33]. To evaluate the uncertainty due to pileup, the measured inelastic pp cross section is varied by 5% [62], resulting in a change in the number of simulated pileup interactions. The relevant e ciencies for signal and background events are changed by 4%. The uncertainty in the signal acceptance due to parton distribution function (PDF) uncertainties is taken to be 2% from a similar analysis [16] which follows the PDF4LHC recommendations [63]. The uncertainty in the integrated luminosity is 2.6% [64]. This a ects only the normalization of the signal MC samples. Because for the backgrounds either control samples in data are used or the normalization is measured from data. The uncertainty in the signal acceptance associated with initial-state radiation (ISR) is evaluated by comparing the e ciencies of jet-related requirements in the MadGraph+pythia program. Using the SM WW process, which is expected to be similar to chargino pair production in terms of parton content and process, a 3% uncertainty in the e ciency of b-tagged jets veto and a 6% uncertainty in the requirement are assigned. The uncertainties related to pmiss can arise from di erent sources, e.g. the energy scales of lepton, h, and jet objects, and unclustered energy. The unclustered energy is the energy of the reconstructed objects which do not belong to any jet or lepton with pT > 10 GeV . The e ect of lepton and h energy scales is discussed above. The contribution from the uncertainty in the jet energy scale (2{10% depending on pT) and unclustered energy (10%) is found to be negligible. A conservative value of 5% uncertainty is assigned to both signal and background processes based on MC simulation studies [16, 18]. The performance of the fast detector simulation has some di erences compared to the full detector simulation, especially in track reconstruction [18] that can a ect the h isolation. A 5% systematic uncertainty per h candidate is assigned by comparing the h isolation and identi cation e ciency in the fast and full simulations. The statistical uncertainties due to limited numbers of simulated events also contributes to the overall uncertainties. This uncertainty amounts to 3{15% for the di erent parts of the signal phase space and 13{70% for the backgrounds in di erent For less important backgrounds like tt, dibosons, and Higgs boson production, the number of simulated events remaining after event selection is very small. A 50% uncertainty is considered for these backgrounds to account for the possible theoretical uncertainty in the cross section calculation as well as the shape mismodeling. The systematic uncertainties that can alter the shapes are added in quadrature and treated as correlated when two signal regions of the h h channel are combined. Other systematic uncertainties of these two channels and all of the systematic uncertainties of the ` h channels are treated as uncorrelated. Results and interpretation The observed data and predicted background yields for the four signal regions are summarized in table 7. There is no evidence for an excess of events with respect to the predicted SM values in any of the signal regions. In SR2, two events are observed while 7.07 events Systematic uncertainty source Background (%) h energy scale (*) h identi cation e ciency h trigger e ciency Lepton trigger and ident. e . b-tagged jets veto Integrated luminosity Fast/full h ident. e . Total shape-a ecting sys. Total non-shape-a ecting sys. Low-rate backgrounds DY and rare backgrounds normalization and their shapes. The sources that a ect the shape are indicated by (*) next to their names. These sources are considered correlated between two signal regions of the h h analysis in the nal statistical combination. are expected. The dominant background source is W+jets events. As a cross-check, data and the prediction in the sideband (200 < MTi < 250 GeV) are studied: 13 events are observed with an expectation of 17:1 5:0 (stat+syst) events. This result indicates that the di erence between the observed and predicted event yields in SR2 can be attributed to a downward uctuation in the data. Figure 4 compares the data and the SM expectation in four search regions. The top row shows the MT2 distributions in the ` h channels. In these plots, the QCD multijet, W+jets, and misidenti ed lepton contribution from other channels are based on the estimate described in section 7.4 and labeled as W+jets. The bottom row shows the MT2 and MTi distributions in the two di erent signal regions of the h h channel. The QCD multijet contribution in these plots is obtained using control samples in data, as described in section 7.1. The W+jets contribution in the last bin of the bottom plots is described in section 7.2, while the contribution to other bins is based on simulated events. The uncertainty band in these four plots includes both the statistical and systematic uncertainties. There is no excess of events over the SM expectation. These results are interpreted in the context of a simpli ed model of chargino pair production and decay, which is described in section 3 and corresponds to the left diagram in gure 1. the search. The uncertainties are reported in two parts, the statistical and systematic uncertainties, respectively. The W+jets and QCD multijet main backgrounds are derived from data as described in section 7; the abbreviation \VV" refers to diboson events. The yields for three signal points representing the low, medium, and high m are also shown. SUSY(X, Y) stands for a SUSY signal = X GeV and me01 = Y GeV. A modi ed frequentist approach, known as the LHC-style CLs criterion [65{67], is used to set limits on cross sections at a 95% con dence level (CL). The results on the excluded regions are shown in gure 5. Combining all four signal regions, the observed limits rule limits are within one standard deviation of the expected limits. out e1 masses up to 420 GeV for a massless e01. This can be compared to the ATLAS limit of 345 GeV for a massless e10 [19]. It should be noted that the ATLAS results are based on the h h channel alone. Figure 6 shows the results in the h h channel, where the e1 masses are excluded up to 400 GeV for a massless e10. In the whole region, the observed The results are also interpreted to set limits on ee the right diagram in gure 1. In this simpli ed model, two production, which corresponds to particles are directly produced from the pp collision and decay promptly to two leptons and two neutralinos. The e ect of the two ` h channels are found to be negligible and therefore are not considered. To calculate the production cross section, e is de ned as the left-handed Since the cross section for direct production of sleptons is lower, no point is excluded and a gauge eigenstates [54]. 95% CL upper limit is set on the cross section as a function of the mass. Figure 7 displays the ratio of the obtained upper limit on the cross section and the cross section expected from SUSY (signal strength) versus the mass of the e 1 GeV . The observed limit is within one standard deviation of the expected limit. The best limit, which corresponds to the lowest signal strength, is obtained for m The observed (expected) upper limit on the cross section at this mass is 43 (56) fb which is almost two times larger than the theoretical NLO prediction. A search for SUSY in the nal state has been performed where the pair is produced in a cascade decay from the electroweak production of a chargino pair. The data analyzed were from pp collisions at p CMS a background estimate from data is available, it is used instead of simulation, as described in the text. The signal distribution for a high m scenario with m compared with the yields of ` h channels while a scenario witeh1 lower = 380 GeV and me01 = 1 GeV is = 240 GeV and are included in the last bins. The shown uncertainties include the quadratic sum of the statistical and systematic uncertainties. to integrated luminosities between 18.1 and 19.6 fb 1. To maximize the sensitivity, the selection criteria are optimized for h h (small m), and ` h channels using the variables MT2, MTh , and . The observed number of events is consistent with the SM expectations. In the context of simpli ed models, assuming that the third generation sleptons are the lightest sleptons and that their masses lie midway between that of the chargino and the neutralino, charginos lighter than 420 GeV for a massless neutralino are excluded at a 95% con dence level. For neutralino masses up to 100 GeV, chargino masses up to 325 GeV are excluded at a 95% con dence level. Upper limits on 100 150 200 250 300 350 400 450 500 m?? (GeV) production with the total data set of 2012. The triangle in the bottom-left corner corresponds to e masses below 96 GeV, which has been excluded by the LEP experiments [68]. The expected limits and the contours corresponding to 1 standard deviation from experimental uncertainties are shown as red lines. The observed limits are shown with a black solid line, while the deviation based on the signal cross section uncertainties are shown with narrower black lines. production cross section are also provided, and the best limit obtained is for the massless neutralino scenario, which is two times larger than the theoretical NLO cross We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative sta s at CERN and at other CMS institutes for their contributions to the success of the CMS e ort. In addition, we gratefully acknowledge the computing centres and personnel of the Worldwide LHC Computing Grid for delivering so e ectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies: the Austrian Federal Ministry of Science, Research and Economy and the Austrian Science Fund; the Belgian Fonds de la Recherche Scienti que, and Fonds voor Wetenschappelijk Onderzoek; the Brazilian Funding Agencies (CNPq, CAPES, FAPERJ, and FAPESP); the Bulgarian 100 150 200 250 300 350 400 450 500 m?? (GeV) channel. The conventions are the same as gure 5. Ministry of Education and Science; CERN; the Chinese Academy of Sciences, Ministry of Science and Technology, and National Natural Science Foundation of China; the Colombian Funding Agency (COLCIENCIAS); the Croatian Ministry of Science, Education and Sport, and the Croatian Science Foundation; the Research Promotion Foundation, Cyprus; the Secretariat for Higher Education, Science, Technology and Innovation, Ecuador; the Ministry of Education and Research, Estonian Research Council via IUT23-4 and IUT236 and European Regional Development Fund, Estonia; the Academy of Finland, Finnish Ministry of Education and Culture, and Helsinki Institute of Physics; the Institut National de Physique Nucleaire et de Physique des Particules / CNRS, and Commissariat a l'Energie Atomique et aux Energies Alternatives / CEA, France; the Bundesministerium fur Bildung und Forschung, Deutsche Forschungsgemeinschaft, and Helmholtz-Gemeinschaft Deutscher Forschungszentren, Germany; the General Secretariat for Research and Technology, Greece; the National Scienti c Research Foundation, and National Innovation O ce, Hungary; the Department of Atomic Energy and the Department of Science and Technology, India; the Institute for Studies in Theoretical Physics and Mathematics, Iran; the Science Foundation, Ireland; the Istituto Nazionale di Fisica Nucleare, Italy; the Ministry of Science, ICT and Future Planning, and National Research Foundation (NRF), Republic of Korea; the Lithuanian Academy of Sciences; the Ministry of Education, and University of Malaya (Malaysia); the Mexican Funding Agencies (BUAP, CINVESTAV, CONACYT, LNS, SEP, New Physics Searches, J. 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Carrera Jarrin Academy of Scienti c Research and Technology of the Arab Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt A. Ellithi Kamel9, M.A. Mahmoud10;11, A. Radi11;12 National Institute of Chemical Physics and Biophysics, Tallinn, Estonia B. Calpas, M. Kadastik, M. Murumaa, L. Perrini, M. Raidal, A. Tiko, C. Veelken Department of Physics, University of Helsinki, Helsinki, Finland P. Eerola, J. Pekkanen, M. Voutilainen Helsinki Institute of Physics, Helsinki, Finland J. Harkonen, V. Karimaki, R. Kinnunen, T. Lampen, K. Lassila-Perini, S. Lehti, T. Linden, P. Luukka, J. Tuominiemi, E. Tuovinen, L. Wendland Lappeenranta University of Technology, Lappeenranta, Finland J. Talvitie, T. Tuuva IRFU, CEA, Universite Paris-Saclay, Gif-sur-Yvette, France M. Besancon, F. Couderc, M. Dejardin, D. Denegri, B. Fabbro, J.L. Faure, C. Favaro, F. Ferri, S. Ganjour, S. Ghosh, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry, I. Kucher, E. Locci, M. Machet, J. 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Toriashvili15 Georgian Technical University, Tbilisi, Georgia Tbilisi State University, Tbilisi, Georgia Z. Tsamalaidze8 RWTH Aachen University, I. Physikalisches Institut, Aachen, Germany C. Autermann, S. Beranek, L. Feld, A. Heister, M.K. Kiesel, K. Klein, M. Lipinski, A. Ostapchuk, M. Preuten, F. Raupach, S. Schael, C. Schomakers, J.F. Schulte, J. Schulz, T. Verlage, H. Weber, V. Zhukov14 RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany M. Brodski, E. Dietz-Laursonn, D. Duchardt, M. Endres, M. Erdmann, S. Erdweg, T. Esch, R. Fischer, A. Guth, M. Hamer, T. Hebbeker, C. Heidemann, K. Hoepfner, S. Knutzen, M. Merschmeyer, A. Meyer, P. Millet, S. Mukherjee, M. Olschewski, K. Padeken, T. Pook, M. Radziej, H. Reithler, M. Rieger, F. Scheuch, L. Sonnenschein, D. Teyssier, S. Thuer RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany V. Cherepanov, G. Flugge, W. Haj Ahmad, F. Hoehle, B. Kargoll, T. Kress, A. Kunsken, J. Lingemann, T. Muller, A. 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Dreyer, E. Garutti, D. Gonzalez, J. Haller, M. Ho mann, A. Junkes, R. Klanner, R. Kogler, N. Kovalchuk, T. Lapsien, T. Lenz, I. Marchesini, D. Marconi, M. Meyer, M. Niedziela, D. Nowatschin, F. Pantaleo16, T. Pei er, A. Perieanu, J. Poehlsen, C. Sander, C. Scharf, P. Schleper, A. Schmidt, S. Schumann, J. Schwandt, H. Stadie, G. Steinbruck, F.M. Stober, M. Stover, H. Tholen, D. Troendle, E. Usai, L. Vanelderen, A. Vanhoefer, B. Vormwald Institut fur Experimentelle Kernphysik, Karlsruhe, Germany C. Barth, C. Baus, J. Berger, E. Butz, T. Chwalek, F. Colombo, W. De Boer, A. Dierlamm, S. Fink, R. Friese, M. Gi els, A. Gilbert, P. Goldenzweig, D. Haitz, F. Hartmann16, S.M. Heindl, U. Husemann, I. Katkov14, P. Lobelle Pardo, B. Maier, H. Mildner, M.U. Mozer, Th. Muller, M. Plagge, G. Quast, K. Rabbertz, S. Rocker, F. Roscher, M. Weber, T. Weiler, S. Williamson, C. Wohrmann, R. Wolf Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece I. Topsis-Giotis G. Anagnostou, G. Daskalakis, T. Geralis, V.A. Giakoumopoulou, A. Kyriakis, D. Loukas, National and Kapodistrian University of Athens, Athens, Greece S. Kesisoglou, A. Panagiotou, N. Saoulidou, E. Tziaferi University of Ioannina, Ioannina, Greece I. Evangelou, G. Flouris, C. Foudas, P. Kokkas, N. Loukas, N. Manthos, I. Papadopoulos, MTA-ELTE Lendulet CMS Particle and Nuclear Physics Group, Eotvos Lorand University, Budapest, Hungary Wigner Research Centre for Physics, Budapest, Hungary G. Bencze, C. Hajdu, P. Hidas, D. Horvath20, F. Sikler, V. Veszpremi, G. Vesztergombi21, Institute of Nuclear Research ATOMKI, Debrecen, Hungary N. Beni, S. Czellar, J. Karancsi22, A. Makovec, J. Molnar, Z. Szillasi University of Debrecen, Debrecen, Hungary M. Bartok21, P. Raics, Z.L. Trocsanyi, B. Ujvari National Institute of Science Education and Research, Bhubaneswar, India S. Bahinipati, S. Choudhury23, P. Mal, K. Mandal, A. Nayak24, D.K. Sahoo, N. Sahoo, Panjab University, Chandigarh, India S. Bansal, S.B. Beri, V. Bhatnagar, R. Chawla, U.Bhawandeep, A.K. Kalsi, A. Kaur, M. Kaur, R. Kumar, A. Mehta, M. Mittal, J.B. Singh, G. Walia University of Delhi, Delhi, India Ashok Kumar, A. Bhardwaj, B.C. Choudhary, R.B. Garg, S. Keshri, S. Malhotra, M. Naimuddin, N. Nishu, K. Ranjan, R. Sharma, V. Sharma Saha Institute of Nuclear Physics, Kolkata, India R. Bhattacharya, S. Bhattacharya, K. Chatterjee, S. Dey, S. Dutt, S. Dutta, S. Ghosh, N. Majumdar, A. Modak, K. Mondal, S. Mukhopadhyay, S. Nandan, A. Purohit, A. Roy, D. Roy, S. Roy Chowdhury, S. Sarkar, M. Sharan, S. Thakur Indian Institute of Technology Madras, Madras, India Bhabha Atomic Research Centre, Mumbai, India R. Chudasama, D. Dutta, V. Jha, V. Kumar, A.K. Mohanty16, P.K. Netrakanti, L.M. Pant, P. Shukla, A. Topkar B. Sutar Tata Institute of Fundamental Research-A, Mumbai, India T. Aziz, S. Dugad, G. Kole, B. Mahakud, S. Mitra, G.B. Mohanty, B. Parida, N. Sur, Tata Institute of Fundamental Research-B, Mumbai, India S. Banerjee, S. Bhowmik25, R.K. Dewanjee, S. Ganguly, M. Guchait, Sa. Jain, S. Kumar, M. Maity25, G. Majumder, K. Mazumdar, T. Sarkar25, N. Wickramage26 Indian Institute of Science Education and Research (IISER), Pune, India S. Chauhan, S. Dube, V. Hegde, A. Kapoor, K. Kothekar, A. Rane, S. Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran H. Behnamian, S. Chenarani27, E. Eskandari Tadavani, S.M. Etesami27, A. Fahim28, M. Khakzad, M. Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi29, F. Rezaei Hosseinabadi, B. Safarzadeh30, M. Zeinali University College Dublin, Dublin, Ireland M. Felcini, M. Grunewald INFN Sezione di Bari a, Universita 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, 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. 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Viliania;b;16 INFN Laboratori Nazionali di Frascati, Frascati, Italy L. Benussi, S. Bianco, F. Fabbri, D. Piccolo, F. Primavera16 INFN Sezione di Genova a, Universita di Genova b, Genova, Italy V. Calvellia;b, F. Ferroa, M. Lo Veterea;b, M.R. Mongea;b, E. Robuttia, S. Tosia;b INFN Sezione di Milano-Bicocca a, Universita di Milano-Bicocca b, Milano, INFN Sezione di Napoli a, Universita di Napoli 'Federico II' b, Napoli, Italy, Universita della Basilicata c, Potenza, Italy, Universita G. Marconi d, Roma, S. Buontempoa, N. Cavalloa;c, G. De Nardo, S. Di Guidaa;d;16, M. Espositoa;b, F. Fabozzia;c, A.O.M. Iorioa;b, G. Lanzaa, L. Listaa, S. Meolaa;d;16, P. Paoluccia;16, C. Sciaccaa;b, F. Thyssen Trento c, Trento, Italy INFN Sezione di Padova a, Universita di Padova b, Padova, Italy, Universita di P. Azzia;16, 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, F. Gasparinia;b, U. Gasparinia;b, A. Gozzelinoa, S. Lacapraraa, M. Margonia;b, A.T. Meneguzzoa;b, J. Pazzinia;b;16, N. Pozzobona;b, P. Ronchesea;b, F. Simonettoa;b, E. Torassaa, M. Zanetti, P. Zottoa;b, A. Zucchettaa;b, G. Zumerlea;b INFN Sezione di Pavia a, Universita di Pavia b, Pavia, Italy A. Braghieria, A. Magnania;b, P. Montagnaa;b, S.P. Rattia;b, V. Rea, C. Riccardia;b, P. Salvinia, I. Vaia;b, P. Vituloa;b INFN Sezione di Perugia a, Universita di Perugia b, Perugia, Italy L. Alunni Solestizia;b, G.M. Bileia, D. Ciangottinia;b, L. Fanoa;b, P. Laricciaa;b, R. Leonardia;b, G. Mantovania;b, M. Menichellia, A. Sahaa, A. Santocchiaa;b INFN Sezione di Pisa a, Universita di Pisa b, Scuola Normale Superiore di Pisa c, Pisa, Italy K. Androsova;31, P. Azzurria;16, G. Bagliesia, J. Bernardinia, T. Boccalia, R. Castaldia, M.A. Cioccia;31, R. Dell'Orsoa, S. Donatoa;c, G. Fedi, A. Giassia, M.T. Grippoa;31, F. Ligabuea;c, T. Lomtadzea, L. Martinia;b, A. Messineoa;b, F. Pallaa, A. Rizzia;b, A. SavoyNavarroa;32, P. Spagnoloa, R. Tenchinia, G. Tonellia;b, A. Venturia, P.G. Verdinia A. Zanettia INFN Sezione di Roma a, Universita di Roma b, Roma, Italy S. Gellia;b, E. Longoa;b, F. Margarolia;b, P. Meridiania, G. Organtinia;b, R. Paramattia, F. Preiatoa;b, S. Rahatloua;b, C. Rovellia, F. Santanastasioa;b INFN Sezione di Torino a, Universita di Torino b, Torino, Italy, Universita del Piemonte Orientale c, Novara, Italy N. Amapanea;b, R. Arcidiaconoa;c;16, 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, L. Fincoa;b, B. Kiania;b, C. Mariottia, S. Masellia, E. Migliorea;b, V. Monacoa;b, E. Monteila;b, 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 Trieste a, Universita di Trieste b, Trieste, Italy S. Belfortea, M. Casarsaa, F. Cossuttia, G. Della Riccaa;b, C. La Licataa;b, A. Schizzia;b, Kyungpook National University, Daegu, Korea D.H. Kim, G.N. Kim, M.S. Kim, S. Lee, S.W. Lee, Y.D. Oh, S. Sekmen, D.C. Son, Chonbuk National University, Jeonju, Korea Chonnam National University, Institute for Universe and Elementary Particles, Hanyang University, Seoul, Korea J.A. Brochero Cifuentes, T.J. Kim Korea University, Seoul, Korea S. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, Y. Jo, Y. Kim, B. Lee, K. Lee, K.S. Lee, S. Lee, J. Lim, S.K. Park, Y. Roh Seoul National University, Seoul, Korea J. Almond, J. Kim, H. Lee, S.B. Oh, B.C. Radburn-Smith, S.h. Seo, U.K. Yang, H.D. Yoo, University of Seoul, Seoul, Korea M. Choi, H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park, G. Ryu, M.S. Ryu Sungkyunkwan University, Suwon, Korea Y. Choi, J. Goh, C. Hwang, J. Lee, I. Yu Vilnius University, Vilnius, Lithuania V. Dudenas, A. Juodagalvis, J. Vaitkus { 37 { National Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico H. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-De La Cruz35, A. Hernandez-Almada, R. Lopez-Fernandez, R. Magan~a Villalba, 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 S. Carpinteyro, I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad Autonoma de San Luis Potos , San Luis Potos , Mexico A. Morelos Pineda University of Auckland, Auckland, New Zealand D. Krofcheck University of Canterbury, Christchurch, New Zealand National Centre for Physics, Quaid-I-Azam University, Islamabad, Pakistan A. Ahmad, M. Ahmad, Q. Hassan, H.R. Hoorani, W.A. Khan, M.A. Shah, M. Shoaib, National Centre for Nuclear Research, Swierk, Poland H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Gorski, M. Kazana, K. Nawrocki, K. Romanowska-Rybinska, M. Szleper, P. Zalewski Institute of Experimental Physics, Faculty of Physics, University of Warsaw, K. Bunkowski, A. Byszuk36, K. Doroba, A. Kalinowski, M. Konecki, J. Krolikowski, M. Misiura, M. Olszewski, M. Walczak Laboratorio de Instrumentac~ao e F sica Experimental de Part culas, Lisboa, Joint Institute for Nuclear Research, Dubna, Russia I. Belotelov, P. Bunin, M. Gavrilenko, I. Golutvin, I. Gorbunov, V. Karjavin, A. Lanev, A. Malakhov, V. Matveev37;38, P. Moisenz, V. Palichik, V. Perelygin, M. Savina, S. Shma tov, S. Shulha, N. Skatchkov, V. Smirnov, N. Voytishin, A. Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia L. Chtchipounov, V. Golovtsov, Y. Ivanov, V. Kim39, E. Kuznetsova40, V. Murzin, V. Oreshkin, V. Sulimov, A. Vorobyev Institute for Nuclear Research, Moscow, Russia Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov, N. Krasnikov, A. Pashenkov, D. Tlisov, A. Toropin Institute for Theoretical and Experimental Physics, Moscow, Russia V. Epshteyn, V. Gavrilov, N. Lychkovskaya, V. Popov, I. Pozdnyakov, G. Safronov, A. Spiridonov, M. Toms, E. Vlasov, A. Zhokin Moscow Institute of Physics and Technology A. Bylinkin38 National Research Nuclear University 'Moscow Engineering Physics InstiR. Chistov41, M. Danilov41, V. Rusinov P.N. Lebedev Physical Institute, Moscow, Russia V. Andreev, M. Azarkin38, I. Dremin38, M. Kirakosyan, A. Leonidov38, S.V. Rusakov, Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, A. Baskakov, A. Belyaev, E. Boos, M. Dubinin42, L. Dudko, A. Ershov, A. Gribushin, V. Klyukhin, O. Kodolova, I. Lokhtin, I. Miagkov, S. Obraztsov, S. Petrushanko, V. Savrin, Novosibirsk State University (NSU), Novosibirsk, Russia V. Blinov43, Y.Skovpen43 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, University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia P. Adzic44, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic, V. Rekovic nologicas (CIEMAT), J. Alcaraz Maestre, M. Barrio Luna, E. Calvo, M. Cerrada, M. Chamizo Llatas, N. Colino, B. De La Cruz, A. Delgado Peris, A. Escalante Del Valle, C. Fernandez Bedoya, J.P. Fernandez Ramos, J. Flix, M.C. Fouz, P. Garcia-Abia, O. Gonzalez Lopez, S. Goy Lopez, J.M. Hernandez, M.I. Josa, E. Navarro De Martino, A. Perez-Calero Yzquierdo, J. Puerta Pelayo, A. Quintario Olmeda, I. Redondo, L. Romero, M.S. Soares Universidad Autonoma de Madrid, Madrid, Spain J.F. de Troconiz, M. Missiroli, D. Moran Universidad de Oviedo, Oviedo, Spain J. Cuevas, J. Fernandez Menendez, I. Gonzalez Caballero, J.R. Gonzalez Fernandez, E. Palencia Cortezon, S. Sanchez Cruz, I. Suarez Andres, J.M. Vizan Garcia Instituto de F sica de Cantabria (IFCA), CSIC-Universidad de Cantabria, I.J. Cabrillo, A. Calderon, J.R. Castin~eiras De Saa, E. Curras, M. Fernandez, J. GarciaFerrero, G. Gomez, A. Lopez Virto, J. Marco, C. Martinez Rivero, F. Matorras, J. Piedra Gomez, T. Rodrigo, A. Ruiz-Jimeno, L. Scodellaro, N. Trevisani, I. Vila, R. Vilar CERN, European Organization for Nuclear Research, Geneva, Switzerland D. Abbaneo, E. Au ray, G. Auzinger, M. Bachtis, P. Baillon, A.H. Ball, D. Barney, P. Bloch, A. Bocci, A. Bonato, C. Botta, T. Camporesi, R. Castello, M. Cepeda, G. Cerminara, M. D'Alfonso, D. d'Enterria, A. Dabrowski, V. Daponte, A. David, M. De Gruttola, A. De Roeck, E. Di Marco45, M. Dobson, B. Dorney, T. du Pree, D. Duggan, M. Dunser, N. Dupont, A. Elliott-Peisert, S. Fartoukh, G. Franzoni, J. Fulcher, W. Funk, D. Gigi, K. Gill, M. Girone, F. Glege, D. Gulhan, S. Gundacker, M. Gutho , J. Hammer, P. Harris, J. Hegeman, V. Innocente, P. Janot, J. Kieseler, H. Kirschenmann, V. Knunz, A. Kornmayer16, M.J. Kortelainen, K. Kousouris, M. Krammer1, C. Lange, P. Lecoq, C. Lourenco, M.T. Lucchini, L. Malgeri, M. Mannelli, A. Martelli, F. Meijers, J.A. Merlin, S. Mersi, E. Meschi, F. Moortgat, S. Morovic, M. Mulders, H. Neugebauer, S. Orfanelli, L. Orsini, L. Pape, E. Perez, M. Peruzzi, A. Petrilli, G. Petrucciani, A. Pfei er, M. Pierini, A. Racz, T. Reis, G. Rolandi46, M. Rovere, M. Ruan, H. Sakulin, J.B. Sauvan, C. Schafer, C. Schwick, M. Seidel, A. Sharma, P. Silva, P. Sphicas47, J. Steggemann, M. Stoye, Y. Takahashi, M. Tosi, D. Treille, A. Triossi, A. Tsirou, V. Veckalns48, G.I. Veres21, N. Wardle, A. Zagozdzinska36, W.D. Zeuner Paul Scherrer Institut, Villigen, Switzerland W. Bertl, K. Deiters, W. Erdmann, R. Horisberger, Q. Ingram, H.C. Kaestli, D. Kotlinski, U. Langenegger, T. Rohe Institute for Particle Physics, ETH Zurich, Zurich, Switzerland F. Bachmair, L. Bani, L. Bianchini, B. Casal, G. Dissertori, M. Dittmar, M. Donega, P. Eller, C. Grab, C. Heidegger, D. Hits, J. Hoss, G. Kasieczka, P. Lecomtey, W. Lustermann, B. Mangano, M. Marionneau, P. Martinez Ruiz del Arbol, M. Masciovecchio, M.T. Meinhard, D. Meister, F. Micheli, P. Musella, F. Nessi-Tedaldi, F. Pandol , J. Pata, F. Pauss, G. Perrin, L. Perrozzi, M. Quittnat, M. Rossini, M. Schonenberger, A. Starodumov49, V.R. Tavolaro, K. Theo latos, R. Wallny Universitat Zurich, Zurich, Switzerland T.K. Aarrestad, C. Amsler50, L. Caminada, M.F. Canelli, A. De Cosa, C. Galloni, A. Hinzmann, T. Hreus, B. Kilminster, J. Ngadiuba, D. Pinna, G. Rauco, P. Robmann, National Central University, Chung-Li, Taiwan V. Candelise, T.H. Doan, Sh. Jain, R. Khurana, M. Konyushikhin, C.M. Kuo, W. Lin, Y.J. Lu, A. Pozdnyakov, S.S. Yu National Taiwan University (NTU), Taipei, Taiwan Arun Kumar, P. Chang, Y.H. Chang, Y.W. Chang, Y. Chao, K.F. Chen, P.H. Chen, A. Psallidas, J.f. Tsai, Y.M. Tzeng Chulalongkorn University, Faculty of Science, Department of Physics, Bangkok, B. Asavapibhop, G. Singh, N. Srimanobhas, N. Suwonjandee Cukurova University, Adana, Turkey M.N. Bakirci51, S. Cerci52, S. Damarseckin, Z.S. Demiroglu, C. Dozen, I. Dumanoglu, S. Girgis, G. Gokbulut, Y. Guler, E. Gurpinar, I. Hos, E.E. Kangal53, O. Kara, A. Kayis Topaksu, U. Kiminsu, M. Oglakci, G. Onengut54, K. Ozdemir55, B. Tali52, S. Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East Technical University, Physics Department, Ankara, Turkey B. Bilin, S. Bilmis, B. Isildak56, G. Karapinar57, M. Yalvac, M. Zeyrek Bogazici University, Istanbul, Turkey E. Gulmez, M. Kaya58, O. Kaya59, E.A. Yetkin60, T. Yetkin61 Istanbul Technical University, Istanbul, Turkey A. Cakir, K. Cankocak, S. Sen62 Institute for Scintillation Materials of National Academy of Science of Ukraine, Kharkov, Ukraine Kharkov, Ukraine L. Levchuk, P. Sorokin National Scienti c Center, Kharkov Institute of Physics and Technology, University of Bristol, Bristol, United Kingdom R. Aggleton, F. Ball, L. Beck, J.J. Brooke, D. Burns, E. Clement, D. Cussans, H. Flacher, J. Goldstein, M. Grimes, G.P. Heath, H.F. Heath, J. Jacob, L. Kreczko, C. Lucas, D.M. Newbold63, S. Paramesvaran, A. Poll, T. Sakuma, S. Seif El Nasr-storey, D. Smith, Rutherford Appleton Laboratory, Didcot, United Kingdom D. Barducci, K.W. Bell, A. Belyaev64, C. Brew, R.M. Brown, L. Calligaris, D. Cieri, Themistocleous, A. Thea, I.R. Tomalin, T. Williams Imperial College, London, United Kingdom M. Baber, R. Bainbridge, O. Buchmuller, A. Bundock, D. Burton, S. Casasso, M. Citron, D. Colling, L. Corpe, P. Dauncey, G. Davies, A. De Wit, M. Della Negra, R. Di Maria, P. Dunne, A. Elwood, D. Futyan, Y. Haddad, G. Hall, G. Iles, T. James, R. Lane, C. Laner, R. Lucas63, L. Lyons, A.-M. Magnan, S. Malik, L. Mastrolorenzo, J. Nash, C. Seez, S. Summers, A. Tapper, K. Uchida, M. Vazquez Acosta65, T. Virdee16, J. Wright, Brunel University, Uxbridge, United Kingdom J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, D. Leslie, I.D. Reid, P. Symonds, L. Teodorescu, M. Turner Baylor University, Waco, U.S.A. A. Borzou, K. Call, J. Dittmann, K. Hatakeyama, H. Liu, N. Pastika The University of Alabama, Tuscaloosa, U.S.A. O. Charaf, S.I. Cooper, C. Henderson, P. Rumerio, C. West Boston University, Boston, U.S.A. D. Arcaro, A. Avetisyan, T. Bose, D. Gastler, D. Rankin, C. Richardson, J. Rohlf, L. Sulak, Brown University, Providence, U.S.A. G. Benelli, E. Berry, D. Cutts, A. Garabedian, J. Hakala, U. Heintz, J.M. Hogan, O. Jesus, E. Laird, G. Landsberg, Z. Mao, M. Narain, S. Piperov, S. Sagir, E. Spencer, R. Syarif University of California, Davis, Davis, U.S.A. R. Breedon, G. Breto, D. Burns, M. Calderon De La Barca Sanchez, S. Chauhan, 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, F. Ricci-Tam, S. Shalhout, J. Smith, M. Squires, D. Stolp, M. Tripathi, S. Wilbur, R. Yohay University of California, Los Angeles, U.S.A. R. Cousins, P. Everaerts, A. 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Kamalieddin, I. Kravchenko, A. Malta Rodrigues, F. Meier, J. Monroy, J.E. Siado, G.R. Snow, B. Stieger State University of New York at Bu alo, Bu alo, U.S.A. M. Alyari, J. Dolen, J. George, A. Godshalk, C. Harrington, I. Iashvili, J. Kaisen, A. Kharchilava, A. Kumar, A. Parker, S. Rappoccio, B. Roozbahani Northeastern University, Boston, U.S.A. G. Alverson, E. Barberis, D. Baumgartel, A. Hortiangtham, A. Massironi, D.M. Morse, D. Nash, T. Orimoto, R. Teixeira De Lima, D. Trocino, R.-J. Wang, D. Wood Northwestern University, Evanston, U.S.A. S. Bhattacharya, K.A. Hahn, A. Kubik, A. Kumar, J.F. Low, N. Mucia, N. Odell, B. Pollack, M.H. Schmitt, K. Sung, M. Trovato, M. Velasco University of Notre Dame, Notre Dame, U.S.A. N. Dev, M. Hildreth, K. Hurtado Anampa, C. Jessop, D.J. Karmgard, N. Kellams, K. Lannon, N. Marinelli, F. Meng, C. Mueller, Y. Musienko37, M. Planer, A. Reinsvold, R. Ruchti, G. Smith, S. Taroni, M. Wayne, M. Wolf, A. Woodard The Ohio State University, Columbus, U.S.A. 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Ferbel, M. Galanti, A. Garcia-Bellido, J. Han, O. Hindrichs, A. Khukhunaishvili, K.H. Lo, P. Tan, M. Verzetti Rutgers, The State University of New Jersey, Piscataway, U.S.A. A. Agapitos, J.P. Chou, E. Contreras-Campana, Y. Gershtein, T.A. Gomez Espinosa, E. Halkiadakis, M. Heindl, D. Hidas, E. Hughes, S. Kaplan, R. Kunnawalkam Elayavalli, S. Kyriacou, A. Lath, K. Nash, H. Saka, S. Salur, S. Schnetzer, D. She eld, S. Somalwar, R. Stone, S. Thomas, P. Thomassen, M. Walker University of Tennessee, Knoxville, U.S.A. M. Foerster, J. Heideman, G. Riley, K. Rose, S. Spanier, K. Thapa Texas A&M University, College Station, U.S.A. O. Bouhali72, A. Celik, M. Dalchenko, M. De Mattia, A. Delgado, S. Dildick, R. Eusebi, J. Gilmore, T. Huang, E. Juska, T. Kamon73, R. Mueller, Y. Pakhotin, R. Patel, A. Perlo , L. Pernie, D. Rathjens, A. Rose, A. Safonov, A. Tatarinov, K.A. Ulmer Texas Tech University, Lubbock, U.S.A. N. Akchurin, C. Cowden, J. Damgov, F. De Guio, C. Dragoiu, P.R. Dudero, J. Faulkner, S. Kunori, K. Lamichhane, S.W. Lee, T. Libeiro, T. Peltola, S. Undleeb, I. Volobouev, Vanderbilt University, Nashville, U.S.A. P. Sheldon, S. Tuo, J. Velkovska, Q. Xu University of Virginia, Charlottesville, U.S.A. A.G. Delannoy, S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, M.W. Arenton, P. Barria, B. Cox, J. Goodell, R. Hirosky, A. Ledovskoy, H. Li, C. Neu, T. Sinthuprasith, X. Sun, Y. Wang, E. Wolfe, F. Xia Wayne State University, Detroit, U.S.A. C. Clarke, R. Harr, P.E. Karchin, P. Lamichhane, J. Sturdy University of Wisconsin - Madison, Madison, WI, U.S.A. D.A. Belknap, S. Dasu, L. Dodd, S. Duric, B. Gomber, M. Grothe, M. Herndon, A. Herve, P. Klabbers, A. Lanaro, A. Levine, K. Long, R. Loveless, I. Ojalvo, T. Perry, G. Polese, T. Ruggles, A. Savin, N. Smith, W.H. Smith, D. Taylor, N. Woods 1: Also at Vienna University of Technology, Vienna, Austria 2: Also at State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, Haute Alsace Mulhouse, CNRS/IN2P3, Strasbourg, France 4: Also at Universidade Estadual de Campinas, Campinas, Brazil 5: Also at Universidade Federal de Pelotas, Pelotas, Brazil 6: Also at Universite Libre de Bruxelles, Bruxelles, Belgium 7: Also at Deutsches Elektronen-Synchrotron, Hamburg, Germany 8: Also at Joint Institute for Nuclear Research, Dubna, Russia 9: Also at Cairo University, Cairo, Egypt 10: Also at Fayoum University, El-Fayoum, Egypt 11: Now at British University in Egypt, Cairo, Egypt 12: Now at Ain Shams University, Cairo, Egypt 13: Also at Universite de Haute Alsace, Mulhouse, France 14: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, 15: Also at Tbilisi State University, Tbilisi, Georgia 16: Also at CERN, European Organization for Nuclear Research, Geneva, Switzerland 17: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany 18: Also at University of Hamburg, Hamburg, Germany 19: Also at Brandenburg University of Technology, Cottbus, Germany 20: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary 21: Also at MTA-ELTE Lendulet CMS Particle and Nuclear Physics Group, Eotvos Lorand 22: Also at University of Debrecen, Debrecen, Hungary 23: Also at Indian Institute of Science Education and Research, Bhopal, India 24: Also at Institute of Physics, Bhubaneswar, India 25: Also at University of Visva-Bharati, Santiniketan, India 26: Also at University of Ruhuna, Matara, Sri Lanka 27: Also at Isfahan University of Technology, Isfahan, Iran 28: Also at University of Tehran, Department of Engineering Science, Tehran, Iran 29: Also at Yazd University, Yazd, Iran 30: Also at Plasma Physics Research Center, Science and Research Branch, Islamic Azad University, Tehran, Iran 31: Also at Universita degli Studi di Siena, Siena, Italy 32: Also at Purdue University, West Lafayette, U.S.A. 33: Also at International Islamic University of Malaysia, Kuala Lumpur, Malaysia 34: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia 35: Also at Consejo Nacional de Ciencia y Tecnolog a, Mexico city, Mexico 36: Also at Warsaw University of Technology, Institute of Electronic Systems, Warsaw, Poland 37: Also at Institute for Nuclear Research, Moscow, Russia at National Research Nuclear University 'Moscow Engineering Physics Institute' (MEPhI), Moscow, Russia 39: Also at St. Petersburg State Polytechnical University, St. Petersburg, Russia 40: Also at University of Florida, Gainesville, U.S.A. 41: Also at P.N. Lebedev Physical Institute, Moscow, Russia 42: Also at California Institute of Technology, Pasadena, U.S.A. 43: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia 44: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia 45: Also at INFN Sezione di Roma; Universita di Roma, Roma, Italy 47: Also at National and Kapodistrian University of Athens, Athens, Greece 48: Also at Riga Technical University, Riga, Latvia 49: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia 50: Also at Albert Einstein Center for Fundamental Physics, Bern, Switzerland 51: Also at Gaziosmanpasa University, Tokat, Turkey 52: Also at Adiyaman University, Adiyaman, Turkey 53: Also at Mersin University, Mersin, Turkey 54: Also at Cag University, Mersin, Turkey 55: Also at Piri Reis University, Istanbul, Turkey 56: Also at Ozyegin University, Istanbul, Turkey 57: Also at Izmir Institute of Technology, Izmir, Turkey 58: Also at Marmara University, Istanbul, Turkey 59: Also at Kafkas University, Kars, Turkey 60: Also at Istanbul Bilgi University, Istanbul, Turkey 61: Also at Yildiz Technical University, Istanbul, Turkey 62: Also at Hacettepe University, Ankara, Turkey 63: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom 64: Also at School of Physics and Astronomy, University of Southampton, Southampton, United 65: Also at Instituto de Astrof sica de Canarias, La Laguna, Spain 66: Also at Utah Valley University, Orem, U.S.A. 67: Also at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, 68: Also at Facolta Ingegneria, Universita di Roma, Roma, Italy 69: Also at Argonne National Laboratory, Argonne, U.S.A. 70: Also at Erzincan University, Erzincan, Turkey 71: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey 72: Also at Texas A&M University at Qatar, Doha, Qatar 73: Also at Kyungpook National University, Daegu, Korea [27] CMS collaboration, The CMS trigger system, 2017 JINST 12 P01020 [arXiv:1609 .02366] [28] CMS collaboration, Particle-Flow Event Reconstruction in CMS and Performance for Jets , [29] CMS collaboration, Commissioning of the Particle- ow Event Reconstruction with the rst [30] M. 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Search for electroweak production of charginos in final states with two τ leptons in pp collisions at \( \sqrt{s}=8 \) TeV, Journal of High Energy Physics, 2017, DOI: 10.1007/JHEP04(2017)018