Search for direct production of supersymmetric partners of the top quark in the all-jets final state in proton-proton collisions at \( \sqrt{s}=13 \) TeV

Journal of High Energy Physics, Oct 2017

A search for direct production of top squark pairs in events with jets and large transverse momentum imbalance is presented. The data are based on proton-proton collisions at a center-of-mass energy of 13 TeV, collected with the CMS detector in 2016 at the CERN LHC, and correspond to an integrated luminosity of 35.9 fb−1. The search considers a variety of R-parity conserving supersymmetric models, including ones for which the top squark and neutralino masses are nearly degenerate. Specialized jet reconstruction tools are developed to exploit the unique characteristics of the signal topologies. With no significant excess of events observed above the standard model expectations, upper limits are set on the direct top squark pair production cross section in the context of simplified supersymmetric models for various decay hypotheses. Models with larger differences in mass between the top squark and neutralino are probed for masses up to 1040 and 500 GeV, respectively, whereas models with a more compressed mass hierarchy are probed up to 660 and 610 GeV, respectively. The smallest mass difference probed is for masses near to 550 and 540 GeV, respectively.

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Search for direct production of supersymmetric partners of the top quark in the all-jets final state in proton-proton collisions at \( \sqrt{s}=13 \) TeV

Received: July 13 TeV A search for direct production of top squark pairs in events with jets and large transverse momentum imbalance is presented. The data are based on proton-proton collisions at a center-of-mass energy of 13 TeV, collected with the CMS detector in 2016 at the CERN LHC, and correspond to an integrated luminosity of 35.9 fb 1 considers a variety of R-parity conserving supersymmetric models, including ones for which the top squark and neutralino masses are nearly degenerate. Specialized jet reconstruction tools are developed to exploit the unique characteristics of the signal topologies. With no signi cant excess of events observed above the standard model expectations, upper limits are set on the direct top squark pair production cross section in the context of simpli ed supersymmetric models for various decay hypotheses. Models with larger di erences in mass between the top squark and neutralino are probed for masses up to 1040 and 500 GeV, respectively, whereas models with a more compressed mass hierarchy are probed up to 660 and 610 GeV, respectively. The smallest mass di erence probed is for masses near to 550 and 540 GeV, respectively. Hadron-Hadron scattering (experiments); Supersymmetry - HJEP10(27)5 The CMS collaboration 1 Introduction 2 The CMS detector 3 Simulated events 4 Event reconstruction 4.1 4.2 4.3 6.1 6.2 6.3 6.4 6.5 Identi cation of high-pT top quarks and W bosons Identi cation of intermediate-pT top quarks Identi cation of initial-state radiation 4.4 Identi cation of low-pT b quarks 5 Search strategy 5.1 Strategy for high Validation of the background methods in data 7 Systematic uncertainties 8 Results and interpretation 9 Summary The CMS collaboration 1 Introduction Although the standard model (SM) of particle physics provides a remarkably accurate description of phenomena associated with the known elementary particles and their interactions, it leaves signi cant problems unresolved. It cannot, for instance, explain how the Higgs boson [1{6] can evade divergent quantum corrections, without very signi cant ne tuning [7, 8] of SM parameters, to allow it to have its mass at the weak scale [9{14]. Moreover, an abundance of cosmological observations, including the existence of dark matter, cannot be explained within the context of the SM alone [15{17]. { 1 { ( e0), respectively. For a given fermion f, there are two superpartners corresponding to the fermion's left- and right-handed states. The superpartners mix to form two mass eigenstates, ef1 and ef2, with ef1 being the lighter of the two. The quantum corrections to the value of the Higgs boson mass (mH) from sparticles could cancel the otherwise problematic SM contributions. In this way, SUSY can protect the value of mH [18{21], provided that the mass di erences between the SM particles and their superpartners are not too large. This is particularly important for superpartners of third generation SM particles, because they have the largest couplings to the Higgs boson, and therefore produce the largest corrections. Furthermore, a combination of precision measurements and null search results indicate that the superpartners of the light quarks may have very large masses [22]. In view of these considerations, the superpartners of the top and bottom quarks, the et and eb squarks, respectively, are expected to be among the lightest sparticles, potentially light enough to be produced at the CERN LHC [23]. An important point to note is that SUSY models with R-parity conservation [24, 25] require sparticles to be produced in pairs, with the lightest SUSY particle (LSP) therefore stable on cosmological time scales. This means that if the lightest neutralino, denoted e10, is the LSP, then it is also a very promising dark matter candidate [26] that would remain at the end of all R-parity conserving sparticle cascade decays. The two motivating principles above place the search for pair production e ) and neutralinos of top squarks (etet) among the highest priorities of the LHC program. CMS Collaborations in proton-proton (pp) collisions at center-of-mass energies p The most recent searches for direct etet production were carried out by the ATLAS and s of 7, 8, and 13 TeV at the LHC [27{47]. The searches have provided no evidence for sparticle production in models with et masses up to 900 GeV and e10 masses up to This paper presents a search for direct etet production in R-parity conserving SUSY using data collected in pp collisions at p s = 13 TeV by the CMS experiment at the LHC in 2016, and corresponding to an integrated luminosity of 35.9 fb 1 . The search is based on methods presented in ref. [44], and represents an extension of that search to larger sparticle masses by means of a signi cantly larger dataset and the development of more sensitive search tools. This search focuses on all-hadronic nal states, de ned as those events whose visible content is made up solely of hadronic jets, as would be expected for signal processes in which all W bosons decay to quarks. These nal states have the largest accessible branching fraction. In many SUSY models, the favored et decay modes depend strongly on the mass hierarchy of the sparticles. In particular, di erent ranges of mass di erence m between the et and e10 correspond to very di erent Only the lightest et mass eigenstate, et1, is assumed to be involved in the models considered in this paper, although the results are expected to be equivalent for the heavier eigenstate. nal-state signatures. { 2 { b f f W+ χ0 e1 χ0 e1 W− f′ f′ χ0 e1 χ0 e1 p p p p et1 et1 (c) et1 et1 (f) χ+ e1 b t c c W+∗ χ0 e1 χ0 e1 χ0 e1 0 χ e1 The et1 decay modes of the simpli ed models [48{50] that are used as the basis for our searches are displayed in gure 1. The search regions (SR) are optimized for di erent models and ranges of m. In models with m larger than the W boson mass mW (\high m models"), the simplest decays that we consider are et1 ! t( ) e01, denoted \T2tt", and et1 ! b e1 ! bW \T2bW", under the assumption that the e1 mass lies halfway between the et1 and ee10,01dmenasosteesd. The choice of moderate e1 mass in the latter model permits high momentum objects in the nal state. The e1 represents the lightest chargino, and e01 is the stable LSP, which escapes detection to produce a large transverse momentum imbalance in the event. Another model, denoted \T2tb", is considered under the assumption of equal branching fractions of the two aforementioned decay modes. This model, however, assumes a compressed mass spectrum W bosons from chargino decays are produced far o -shell. m models"), the et1 can decay through the T2tt decay mode with o -shell t and W, through the same decay chain as in the T2bW model, via o -shell W bosons, or decay through a avor changing neutral current process (et1 ! c e01, where c is the charm quark). These will be referred to as the \T2ttC", \T2bWC", and \T2cc" models, respectively, where C denotes the hypothesis of a compressed mass spectrum in the rst two cases. Observations in such low m models are experimentally challenging since the visible decay products are typically very soft (low-momentum), and therefore often evade identi cation. Nevertheless, such models are particularly interesting because their dark matter relic density is predicted to be consistent with the cosmological observations [51]. Specialized jet reconstruction tools and event selection criteria are therefore developed to enhance sensitivity to these signals. { 3 { This paper is organized as follows. A brief description of the CMS detector is presented in section 2, while section 3 discusses the simulation of background and signal processes. Event reconstruction is presented in section 4, followed by a description of the search strategy in section 5. Methods employed to estimate the SM backgrounds and their corresponding systematic uncertainties are detailed in sections 6 and 7, respectively. The discussion of the systematic uncertainties assigned to the signal processes is also presented in section 7. The results of the search and their interpretation in the context of a variety of models of et1 production and decay are presented in detail in section 8, followed by a summary in section 9. 2 The CMS detector The central feature of the CMS apparatus is a superconducting solenoid of 6 m internal diameter, providing a magnetic eld of 3.8 T. Within the solenoid volume are an all-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 ( ) coverage provided by the barrel and endcap detectors. Muons are measured in gas-ionization detectors embedded in the steel ux-return yoke outside the solenoid. 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 around 1 kHz, before data storage. 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 in ref. [52]. 3 Simulated events Monte Carlo (MC) simulated events are used to study the important SM backgrounds, as well as to formulate the overall search for SUSY processes. Background processes composed uniquely of jets produced via the strong interaction of quantum chromodynamics (QCD) are referred to as \QCD multijet" processes. Simulated events originating from tt, W+jets, Z+jets, +jets, and QCD multijet processes are generated using MadGraph5 amc@nlo 2.3.3 [53] at leading order (LO) using the LO NNPDF3.0 [54] parton distribution functions (PDF). The WZ, ZZ, ttZ, and ttW processes are generated using MadGraph5 aMC@NLO at next-to-leading order (NLO), the single top quark process in the tW channel using powheg [55{58] and the WW process is generated at NLO with powheg v2.0 [59], all using the NLO NNPDF3.0 PDF. In all of the aforementioned cases, parton showering and hadronization are simulated in pythia 8.212 [60]. The potential for double counting of partons generated using pythia with those using MadGraph5 amc@nlo is minimized using the MLM [61] and the FXFX [62] matching schemes, in the LO and NLO samples, respectively. To evaluate systematic uncertainties associated with these aspects of event simulation, two additional tt samples are generated { 4 { HJEP10(27)5 using powheg v2.0 [63], where one is interfaced with pythia and the other with herwig++ v2.7.1 [64]. Additional QCD multijet samples are also generated, but interfaced with herwig++ for the modeling of parton showering and hadronization. Signal processes are generated at LO using MadGraph5 amc@nlo based on the LO NNPDF3.0 PDF with pythia used for parton showering and hadronization. Signal production cross sections are calculated using NLO with next-to-leading logarithm (NLL) soft-gluon resummations (NLO+NLL) [65]. The most precise cross section calculations are used to normalize the SM simulated samples, corresponding to next-to-next-to-leading order (NNLO) accuracy [66{ 69] in most cases. Finally, the transverse momentum (p~T, with magnitude pT) spectrum of top quarks in tt events is reweighted (referred to as \top quark pT reweighting") to account for e ects due to missing higher-order corrections in MC simulation, according to the results presented in ref. [70]. A full Geant4-based model [71] is used to simulate the response of the CMS detector to SM background samples. The CMS fast simulation package [72] is used for signal samples after verifying that it provides results that are consistent with those obtained from the full Geant4-based simulation. Event reconstruction is treated in the same manner for MC simulation as for data. A nominal distribution of multiple pp collisions in the same or neighboring bunch crossings (referred to as \pileup") is used to overlay the simulated events. The events are then reweighted to match the pileup pro le observed in the collected data. 4 Event reconstruction Events are reconstructed using the CMS particle- ow (PF) algorithm [73], which combines information from all detector subsystems to reconstruct the properties of the nal-state particles produced in the pp collisions. At least one reconstructed vertex is required; for multiple collision vertices from pileup interactions, the reconstructed vertex with the largest value of summed physics-object p2T is taken to be the primary pp interaction vertex (PV). The physics objects used in this context are the objects returned by a jet nding algorithm [74, 75] applied to all charged tracks associated with the vertex under consideration, plus the corresponding associated missing transverse momentum (the precise de nition is given later in the text). Events a ected by instrumental noise or reconstruction failures are identi ed through dedicated lters and rejected. Reconstructed particles are identi ed as charged hadrons, neutral hadrons, electrons, muons, or photons, to constitute a list of PF candidates. Our primary jet collection is produced by clustering the PF candidates originating from the PV using the anti-kT algorithm [74] with a distance parameter of 0.4. The jet energy is corrected for the contribution from pileup based on the jet area method [76, 77]. Additional corrections to the jet energy scale are applied to compensate for nonuniform detector response [78]. Jets are required to have pT 20 GeV and be contained within the tracker volume of j j 2:4. Jets originating from the hadronization of bottom (b) quarks are identi ed, or \tagged", through the combined secondary vertex (CSVv2) b tagging algorithm [79, 80]. The working point used provides an e ciency for the b tagging of jets originating from { 5 { b quarks that varies from 60 to 75% depending on pT, whereas the misidenti cation rate for light quarks or gluons is 1%, and 15% for charm quarks. A novel soft b tagging algorithm was developed for this analysis and used to identify b quarks with p bT < 20 GeV (i.e. below the jet pT threshold). The algorithm is described in section 4.4. Although the T2cc model involves charm quark jets in the nal state, no dedicated c tagger was used in this analysis. propagated to p~miss. T T To estimate the pT imbalance in the event, the missing transverse momentum, p~Tmiss, is de ned as the negative of the vectorial sum of the p~T of all PF candidates in the event. Its magnitude is denoted pmiss. The jet energy scale corrections applied to the jets are Electrons are reconstructed by combining information from the inner tracker with energy depositions in the ECAL [81]. Muons are reconstructed by combining tracks in the inner tracker and in the muon system [82]. Tracks associated with electrons or muons are required to originate from the PV, and a set of quality criteria is imposed to assure e cient identi cation [81, 82]. To suppress misidenti cation of charged hadrons as leptons, we require electrons and muons to be isolated from jet activity within a pT-dependent cone size de ned by a radius Rrel in the - plane, where is the azimuthal angle in radians. The relative isolation, Irel, is de ned as the scalar sum of the pT of the PF candidates within the cone divided by the lepton pT. Charged PF candidates not originating from the PV, as well as PF candidates identi ed as electrons or muons, are not considered in the sum. The cone size Rrel depends on the lepton pT: Rrel = < > 8>0:2; >>:0:05; pT < 50 GeV; pT 200 GeV: 10 GeV=pT; 50 pT < 200 GeV; (4.1) The decreasing cone radius at larger pT provides high e ciency for the collimated decay products of highly Lorentz-boosted heavy objects [83]. The isolation sum Irel is corrected for contributions of neutral particles originated from pileup interactions using an area-based estimate [77] of pileup energy deposition in the cone. Photons are reconstructed from energy depositions in the ECAL using identi cation algorithms that utilize a collection of variables related to the spatial distribution of shower energy in the supercluster (a group of 5x5 ECAL crystals), the photon isolation, and the fraction of the energy deposited in the HCAL behind the supercluster relative to the energy observed in the supercluster [84]. Tau lepton decays to hadrons, h ! (hadrons) , are reconstructed starting from isolated charged-hadron candidates with pT 10 GeV and j j 2:4. If there are photons with pT 0:5 GeV within a cone of R 0:2 around the charged hadron, the leading pT photon momentum is vectorially added to that of the charged hadron candidate. In addition, we impose a requirement on the transverse mass of the h; for an object with transverse momentum p~T, the transverse mass mT is de ned as: mT(p~T; p~miss) = T 2pTpTmiss(1 q cos ) ; (4.2) { 6 { HJEP10(27)5 where is the di erence in azimuthal angle between p~T and p~miss. T We require the transverse mass of the h to be less than 100 GeV, consistent with the expectation from a h emitted in a W boson decay in a high-multiplicity jet environment. A multivariate boosted decision tree (BDT) classi er [85] is trained to distinguish h decay products from other charged hadrons. Input variables include isolation sums within cones of several radii, R-distances from the h candidate to the nearest charged particle and to the axis of the jet in which it is contained, and the b tagging discriminant value of that jet. Many of the et1 decay modes involve unique nal-state signatures. In view of this, reconstruction tools have been developed to exploit these signatures while signi cantly suppressing the SM background. Signal models with large m have decay chains involving on-shell top quarks and W bosons. Identi cation of jets associated with the decays of top quarks and W bosons to quarks is an important component of the analysis, used to suppress most of the backgrounds in searches that target such signals. Because they exhibit a wide range of Lorentz boosts, we take di erent approaches in their reconstruction depending on whether they have large or small pT; these are described in sections 4.1 and 4.2, respectively. In contrast, the decay products in models with small m are very soft and often fail to be reconstructed through the standard algorithms. We have therefore developed more e ective algorithms for these cases that are described in sections 4.3 and 4.4. 4.1 pT Identi cation of high-pT top quarks and W bosons The decay products of highly boosted top quarks with pT 400 GeV, or W bosons with 200 GeV, are usually contained within a cone of radius R = 0:8 [86]. A collection of \large-R jets", which is distinct from, and possibly overlaps with, the collection of primary jets, is used to reconstruct these boosted objects by means of the anti-kT clustering algorithm with a distance parameter of 0.8. Additional information on jet substructure is obtained by reclustering the constituents of these jets through the Cambridge-Aachen algorithm [87]. The \modi ed mass drop tagger" algorithm [88], also known as the \soft drop" (SD) algorithm, with angular exponent = 0, soft cuto threshold zcut 0:1, and characteristic radius R0 = 0:8 [89], is applied to remove soft, wide-angle radiation from the jet. The performance of the SD algorithm does not depend on the algorithm used initially to reconstruct the large-R jets. Top quark and W boson candidates are selected from the collection of large-R jets after applying a loose preselection based on variables reconstructed using the SD algorithm. In our con guration, the SD algorithm identi es two hard subjets of the large-R jet by reversing the Cambridge-Aachen clustering history. The two hard substructures should correspond to the W boson and b quark jet, in the case of top quark candidates, or to two quark jets of a W boson decay, in the case of a W boson candidate. The top quark (W boson) candidates are required to have soft-drop mass mSD 20 GeV. These mSD requirements incur minimal e ciency losses, and ensure that candidates can only be tagged uniquely. Two separate multivariate BDT are trained to identify candidates for the quark decays of highly boosted top quarks and W bosons. The identi ed objects are subsequently referred to as \merged" top quarks and W bosons, respectively. The input variables to the { 7 { CMS ien0.7 Simulation c c Merged top quarks E E CMS ien0.7 Simulation 0.5 0.4 Merged W bosons Generated ptTop [GeV] two BDT rely on mSD, N-subjettiness ratios ( 3= 2 and 2= 1) [90], observables related to quark-gluon discrimination [91], the b tagging discriminant value, the relative di erence in pT between each of the two subjets within the large-R jet, and the mass of each subjet. The N-subjettiness variable, N , is a measure of the degree to which the jet originates from N subjets. The BDT are trained in MC simulated samples using the Toolkit for Multivariate Data Analysis (TMVA) [92] to discriminate between \background" and \signal" largeR jets. The merged top quark BDT is trained using, for \signal", candidates that are matched to generated quark decays of top quarks in simulated SUSY events. For the merged W boson BDT this procedure is repeated in simulated tt events. For the \background" we consider the remaining candidates that could not be matched. The e ciencies to identify matched top quarks and W bosons are shown in gure 2. The merged W boson tagging e ciency is determined using W bosons originating from generated top quark decays; thus, the moderate drop at large pT can be largely attributed to the merging of the top quark decay products, which reduces the e ectiveness of the jet substructure variables. The misidenti cation rate for jets initiated by either gluons or light quarks depends on the pT of the large-R jet and ranges from 1 to 4% and from 2 to 10% for merged top quarks and W bosons, respectively. The misidenti cation rates for these top quark and W boson taggers are measured in data using a sample of multijet events that is dominated by the QCD multijet process, selected with an HT trigger, where HT is de ned as the scalar sum of the pT of the primary jets in the event. We require the events to contain at least one large-R jet and HT 1 TeV. The misidenti cation rate is measured as a function of the jet pT and , and then compared to the expected rates in simulation. Data-to-simulation ratios are found to deviate from unity by no more than 20%, and are used to correct results obtained with simulated event samples. { 8 { The top quark and W boson tagging e ciencies are measured in data using a sample of lepton+jets events dominated by the semileptonic tt process and selected using a singlemuon trigger. The muon is required to have pT 50 GeV and j j 2:1. To suppress other backgrounds, at least one b-tagged jet is required in the same hemisphere as the muon, and the large-R jet is required to be in the opposite hemisphere. Contributions from processes with no quark decays of top quarks or W bosons are corrected through misidenti cation correction factors applied before obtaining the tagging e ciencies. These observed e ciencies are compared to those estimated in simulation, and simulation-to-data correction factors, typically ranging from 0.9 to 1.1, are extracted and applied to simulated events to account for any dependence on pT. Simulated signal events generated in the CMS fast simulation package are corrected in a similar way for the di erences in tagging performance relative to the full Geant4-based simulations. 4.2 Identi cation of intermediate-pT top quarks The decay products of moderately boosted top quarks are often resolved as three separate jets in the primary jet collection. To avoid overlap with merged top quarks and W bosons, we only consider a \cleaned" subset of jets that are separated by a distance R > 0:8 from all of the candidate merged objects. Three-jet \resolved" top quark candidates are formed by starting with a jet from the cleaned jet collection that is designated to be the b constituent jet. The two jets with highest b tagging discriminant values are the only eligible jets for this step. Two additional constituent jets are designated W constituent jets after being identi ed from all two-jet combinations in the cleaned collection, excluding the already designated b jet. The algorithm is repeated with the remaining b jet. To reduce the combinatorial background before making any stringent selections, we require the two W constituent jets to have invariant mass within 40 GeV of mW = 80 GeV and the combined three-jet system to have invariant mass within 80 GeV of the top quark mass mt = 175 GeV. The three-jet systems that pass these requirements are considered for possible tagging as resolved top quarks. Resolved top quark tagging is carried out using a BDT trained on simulated tt events. It exploits properties of each three-jet candidate, including masses, angular separations, and other kinematic properties of the constituents. Additional input variables are quarkgluon discrimination metrics [93], b tagging discriminant values, and charm quark versus light quark jet discrimination [94] for each of the three jets. The performance of the resolved top quark tagger is shown in gure 3. The drop in e ciency at very high pT stems from the fact that top quark decay products are kinematically more likely to be merged into single large-R jets. Correspondingly, the e ciency of the merged top quark tagger starts to become signi cant in this region, as seen in gure 2 (left). The performance of the resolved top quark tagger is evaluated using the same methodology as that described in section 4.1. Simulation-to-data correction factors ranging from 1.00 to 1.15 are extracted and applied to simulated events to account for di erences with data as a function of pT. Simulated signal events generated in the CMS fast simulation package are corrected in a similar way for di erences in tagging performance relative to the full Geant4-based simulations. { 9 { cn0.9 SCimMuSlation e i Resolved top quarks Resolved top quarks ifc0.8 fE0.7 0.04 0.02 0 100 HJEP10(27)5 200 300 400 500 600 Generated ptTop [GeV] 200 300 400 500 600 Candidate pT [GeV] the pT of the generated top quark. Right: misidenti cation rate in MC simulation as a function of the pT of resolved top quarks, in a sample dominated by the QCD multijet process. 4.3 Identi cation of initial-state radiation m < mW, the LSP is much heavier than the other decay products, and the event has relatively low pmiss. However, in cases where the et1et1 pair recoils against T high-pT initial-state radiation (ISR), the massive LSP can be either moderately or highly boosted, and there can be relatively large values of pTmiss. To take advantage of this possibility, we try to identify an ISR jet candidate in the event. To this end, we use the set of large-R jets described in section 4.1. The use of such jets improves ISR jet identi cation by capturing ISR gluon jets that may have undergone splitting to two or more jets that are distributed over a relatively large solid angle. For events having such jets, the large-R jet with the largest value of pT 200 GeV that fails the \loose" working point of the b tagging algorithm (characterized by a tagging e ciency of 80%, and a misidenti cation rate of 10% for light quarks and gluons, and 40% for charm quarks) is tagged as an ISR jet candidate. This ISR jet is then used in SR that are orthogonal to those that require top quark or W boson candidates. 4.4 Identi cation of low-pT b quarks As previously noted, signal models with small m produce a large fraction of b quarks below the jet pT threshold that subsequently fail to be included in the primary jet collection. Identifying these soft quarks can potentially improve our ability to separate signal events from SM background. To this end, we identify soft b hadrons, not associated to jets, by means of a secondary vertex (SV) reconstructed by the inclusive vertex nding algorithm [95]. Additional requirements for SV observables are used to suppress background from light- avor hadrons and jets. These include the distance in the transverse plane between the SV and PV; the signi cance of this distance; its pointing angle, de ned through the scalar product between the distance vector and the p~SV direction as cos((PV; SV!); p~SV), where p~SV is the total momentum of the tracks associated with the SV; and the number of tracks associated with the SV. The transverse momenta of the tracks associated with an SV are required to sum to pT < 20 GeV, and be separated from any jets (including b-tagged jets) by R > 0:4. This de nition leads to 20% e ciency to identify a b hadron in the pT range from 10 to 20 GeV, for a misidenti cation rate less than one percent. The soft b tagging e ciency in data is measured in a sample dominated by tt events having an e pair, pTmiss 50 GeV, a b-tagged jet, and no additional jets. The presence of an additional soft (pT < 20 GeV), nonisolated is used to estimate the fraction of soft b quarks in data. The soft b tagging performance in simulation agrees with the performance in data within 16%. Simulated signal events produced in the CMS fast simulation package are corrected for di erences in soft b tagging relative to Geant4-based simulations. 5 Search strategy T T Irel With the nal-state signatures of the signals in mind, we select events collected with a pmiss trigger and require pmiss T pmiss generated through the leptonic decay of a W boson are signi cantly suppressed by 250 GeV o ine. The SM backgrounds with intrinsic rejecting events containing isolated electrons or muons with pT 0:1, or Irel 0:2, respectively. The contribution from events in which a W boson decays to a lepton is suppressed by rejecting events containing isolated h candidates. In our \search sample", de ned by the above requirements, the dominant sources of T SM background with intrinsic pmiss are tt, W+jets, and Z+jets, single top quark, and ttZ processes. The contribution from tt and W+jets processes arises from events in which W bosons decay leptonically to produce pTmiss associated with an energetic neutrino, but the charged lepton either falls outside of the kinematic acceptance, or, even more likely, may be misidenti ed as a jet after failing to be identi ed as a lepton. This background is collectively referred to as \lost lepton" background. Contributions arising from ttW and single top T quark processes also enter this category at lower levels. The contributions from Z+jets and ttZ events arise when the Z boson decays to neutrinos, thereby producing signi cant pmiss. Contributions from the QCD multijet process enter the search sample in cases where severe mismeasurements of jet momenta (i.e., jets passing through dead regions, cracks, or transition regions of the detector) produce signi cant arti cial pTmiss, or when neutrinos arise from leptonic decays of heavy- avor hadrons produced during jet fragmentation. We de ne a total of 104 non-overlapping SR with two sets of disjoint baseline selection criteria that are designed speci cally for application in the high and low m signals. Based on the nal-state signatures of models with m > mW, we de ne a high m baseline selection that requires at least ve jets in our primary jet collection (Nj 5), of which at least one is b-tagged (Nb 1). Severely mismeasured high-pT jets in multijet events can lead to large values of pTmiss but generally have p~miss aligned with one of the higher-pT jets T in the event. We therefore add the requirement of separation in azimuthal angle between p~miss and each of the four jets with largest pT, T 1234 0:5, which greatly reduces the contribution from this background. Events passing the high m baseline selection are then divided into multiple non-overlapping SR, optimized for the kinematic properties of moderate to high m signal topologies. In lepton+jets tt events, where most of the pTmiss is due to the leptonic decay of a single W boson, the transverse mass distribution of the neutrino and b quark from the same top quark decay has an endpoint at the mass of the top quark. To take advantage of this fact, we separate events based on the value of the smallest b quark transverse mass in the event, mbT (see (2)). In case there are more than two b-tagged jets, only the two jets with the highest b tagging discriminant value are considered. The two resulting sets of events are the tt-depleted high-mbT category (with mbT 175 GeV), and the tt-enhanced low-mbT category (with mbT < 175 GeV). To target signals with moderate values of m that populate the low-mbT category, we require the presence of at least one resolved top quark and Nj 7. The latter condition assures that a signal event would contain at least one radiated jet, providing a boost to the T system and thereby increasing the pmiss for better discrimination from backgrounds. The high-mbT category is subdivided into two categories: events that do not contain any top quark or W boson candidates with the requirement Nj 7, and events that do contain top quark or W boson candidates, as expected for models with larger values of m and highly boosted top quarks or W bosons. In the latter case, we retain the baseline requirement of Nj 5 and de ne separate SR according to the numbers of candidate merged top quarks (Nt), merged W bosons (NW), and resolved top quarks (Nres). All these regions are further subdivided into SR according to the number of b-tagged jets, Nb = 1 or 2, and di erent ranges of pTmiss. 5.2 Strategy for low m baseline selection is most appropriate for models with m < mW. To this end, we select events that have at least two jets, no top quark or W boson candidates, and small mbT (<175 GeV) when there are b-tagged jets present. In addition, we require an ISR 2, where the last requirement suppresses the QCD multijet process. As discussed in section 4.3, the requirement of an ISR jet provides sensitivity to low m signal topologies, in which intrinsic pTmiss is generated by the decay of et1et1 pairs recoiling against ISR. To further suppress the QCD multijet process, (j1; p~ miss)j T 0:5, j (j2;3; p~ miss)j T we require j 10 p pT jets. In addition, a measure of signi cance in pmiss, de ned as pmiss=pHT T T SE=T GeV, is required to ensure that pTmiss can only arise from undetectable particles or very 0:15, where j1; j2; j3 are the three leadingrare, extreme mismeasurements. Events satisfying the above requirements are further subdivided into SR de ned by Nb, the number of identi ed secondary vertices NSV, pITSR, and pmiss. Events with Nb = 0, T a category used for very soft decay products, are further subdivided by ranges of Nj, 2 to 5 or 6, NSV, and pmiss, after requiring very high pISR to assure a substantial boost to nal T T state jets which, in turn, enhances the e ectiveness of soft b tagging by producing more HJEP10(27)5 Nj mbT 175 GeV T pmiss [GeV] signi cantly displaced b hadron decays. The SR with Nb = NSV = 0 provide sensitivity to the T2cc model. They may also provide sensitivity to similar nal states involving lighter quarks but we have not studied these cases. Events with Nb 1 are subdivided according to the scalar sum of the pT of the leading and subleading (if one is present) b-tagged jets, pbT, to take advantage of the softer b jet pT spectrum expected from the low relative to the SM background. 6 Background estimation The contribution of each SM background process to the search sample is estimated through measurements of dedicated control data events that are translated to predictions for event counts in the corresponding SR with the aid of simulation. The strategy makes use of methods described in ref. [44]. 2{5 2{5 6 6 2 2 2 7 2 2 7 Nb pITSR [GeV] pbT [GeV] 0 1 2 0 0 0 0 0 0 1 1 1 0 300{500 300{500 300{500 300{500 300{500 500 500 500 300 500 500 300 | 20{40 40{70 20{40 40{70 20{40 40{80 80{140 140 40{80 80{140 140 pmiss [GeV] T mbT < 175 GeV (when applicable), j with pITSR 300 GeV, j j 2:4, j 2, pmiss T (j1; p~miss)j T (jISR; p~miss)j T 250 GeV, no leptons, Nt = NW = Nres = 0, 0:5; j 2, and SE=T (j2;3; p~miss) T j p 10 GeV. 0:15, and an ISR jet 6.1 Estimation of the lost-lepton background The lost-lepton (LL) background is estimated from a single-lepton control sample that is based on a sample of events collected with the same pTmiss trigger as the search sample. We create a relatively pure single lepton sample (\1`") by inverting the electron or muon veto requirements described in section 5. More than 90% of the events in these samples contain a single lepton, while the remainder contain two or more leptons. Studies of simulated events indicate that event kinematic variables for di erent lepton avors are su ciently similar to provide a collective estimate of LL backgrounds from a single control sample. Potential contamination by signal is suppressed by requiring mT(p~T(`); p~miss) < 100 GeV, consistent T with the expectation for a W boson decay. In events with more than one identi ed lepton, the one used in this calculation is selected randomly. The selection criteria applied to the single-lepton control sample are the same as those used in the search sample, with the exception of top quark and W boson multiplicity, as discussed below. The LL estimation in each SR is based upon the event count in corresponding singlelepton control regions (CR). The count is translated to a prediction in the SR by means of a transfer factor obtained from simulation, as follows: NpLrLed = T FLL Ndata(1`); (6.1) HJEP10(27)5 where Ndata(1`) corresponds to the event count observed in the relevant single-lepton CR in data, and the transfer factor, T FLL, translates Ndata(1`) to a background prediction in the SR, NpLrLed, and is de ned as: T FLL = NMC(0`) NMC(1`) ; (6.2) where NMC(0`) and NMC(1`) are the LL yields found for simulated events in the search and single-lepton samples, respectively, that include contributions from tt and W+jets events, as well as smaller contributions from single top quark and ttW processes. To improve the statistical uncertainty of this background estimation, CR relevant to m SR are combined for all top quark and W boson multiplicities in both data and simulation. The top quark and W boson tagger results for the simulated events are corrected by the simulation-to-data correction factors discussed in section 4. Simulation is used to extrapolate these results to each SR with its particular top quark and W boson multiplicity. The selection e ciency for each of the other search variables is estimated directly from data in the single-lepton sample. An important source of background in the search arises from events in which a Z boson, produced in association with jets, decays to neutrinos that carry away large pmiss. Two methods are traditionally used [39, 41] to estimate this background. The rst method uses an event sample dominated by Z(``)+jets events, in which the Z bosons have kinematic properties very similar to those in the search sample, after correcting for the di erence in acceptance between charged lepton pairs and pairs of neutrinos. One drawback in this is that these events are statistically limited, especially in the stringently de ned SR often used in SUSY searches. To overcome this limitation, the second method utilizes +jets events, in which the +jets process has similar LO Feynman diagrams to the Z+jets process, but is more copious than the Z(``)+jets by about a factor of ve. To use this sample requires taking into account the di erences in quark-boson couplings and the fact that the Z boson is very massive. Fortunately, these di erences are substantially reduced for the high-pT T bosons in this search. Considering the pros and cons of the two methods led us to use a hybrid method to estimate the Z( ) background that makes use of both procedures. We use the Z(``)+jets sample to get the normalization of the Z( )+jets background. This is done in di erent ranges of Nb and NSV to account for dependence on heavy- avor production. Meanwhile, the +jets events are used to correct the pmiss distributions of simulated events. The T Z(``) sample is collected with dielectron and dimuon triggers that require the leading electron (muon) to have pT 25 (20) GeV, and the subleading electron (muon) to have 15 (10) GeV. The leptons must have j j 2:4 to be within the acceptance of the tracker. The +jets events are collected with a single-photon trigger and an o ine selection of pT 200 GeV and j j 2:5 for the leading photon. To suppress potential contributions from signals and to avoid overlap with the search sample we consider only the events with pmiss < 200 GeV. The transverse momentum of the boson, as determined from the lepton pair or the photon, is added vectorially to p~miss to emulate the kinematic properties of the Z( )+jets process. The modi ed pTmiss, denoted by pTmiss;``and pTmiss; for the Z(``)+jets and +jets processes, respectively, is used to calculate the relevant kinematic variables. The prediction for the Z( ) background in any particular SR is given by: N pred Z! = NZsi!m RZ S ; (6.3) where NZsi!m is the expected number of Z( ) events in simulation, RZ is the avordependent Z+jets normalization factor measured using the Z(``) events, and S is the correction factor for the pTmiss distribution as extracted from the +jets events in data. The factor RZ is calculated by comparing the observed and expected Z(``) yields after T applying the baseline selection criteria, with the exception of the requirements on the azimuthal angles between jets and pmiss. The latter are omitted to retain more events and hence reduce the statistical uncertainty in the RZ estimation, after rst con rming that this omission does not bias the result. To increase the purity of the Z(``) sample, we require the dilepton invariant mass to lie within the Z boson mass window of 80 M`` < 100 GeV. To probe similar phase space as in the search sample, the pT of the dilepton system is required to be above 200 GeV. The normalization of the nonnegligible tt contamination is estimated from the sidebands of the Z boson mass window of 50 M`` < 80 and M`` Small contributions from tZ, ttZ, WZ, and ZZ production, estimated from simulation, are included in the Z(``) sample when measuring RZ; whereas contributions from tW, ttW, and WW are included in the simulated sample used to obtain the normalization factor for the tt contamination. To account for e ects related to heavy- avor production, RZ is calculated separately for the Nb and NSV requirements used in di erent SR. The RZ values are consistent with unity. The uncertainty in RZ, ranging from 1 to 29%, comes mainly from the event counts in data and simulation after implementing the selections, and is treated as a systematic uncertainty in the prediction of the Z( ) background. The correction factor S is calculated in each of the search categories via a comparison T of the pmiss; distributions of +jets events in simulation and data. The event count from simulation is rst normalized to the number of events in data after applying the appropriate m baseline selections. The S factor is estimated separately for each SR, to account for any potential mismodeling of the search variables in simulation. As for the LL background estimation, good agreement between simulation and data for the performance of the top quark and W boson taggers provides a way for us to combine CR for all multiplicities of top quarks and W bosons to calculate S , thereby improving the statistical uncertainty of the result. We then use simulation to extrapolate these results to each SR with its particular top quark and W boson multiplicity, after correcting events using the simulation-to-data correction factors discussed in section 4. An underlying assumption of the hybrid estimation is that any di erences between data and simulation in the pmiss distributions for Z( T ratios of data to simulation for the pTmiss;``and pTmiss; distributions of Z(``)+jets and in the pTmiss; distributions for photon events. We checked this assumption by comparing the +jets samples, respectively. Residual di erences in data and simulation can arise in the process of ) events should be compatible with those object reconstruction or as a result of the absence of higher-order corrections in simulation. Observed di erences are included in the systematic uncertainties of the Z( ) prediction. Estimation of the QCD multijet background The background originating from the QCD multijet process generally constitutes less than 10% of the total SM background in the SR. It is estimated using a control region in data, consisting of events collected with the same trigger as that used in the search. A sample dominated by the QCD multijet process is then obtained by requiring the azimuthal angle between any one of the three leading jets and pmiss, T 123, to be smaller than 0.1. We again translate the observation in the control sample to a prediction in the search sample by means of transfer factors obtained from simulation. Each transfer factor is dened by the ratio between the number of simulated QCD multijet events satisfying the SR selection on the azimuthal angles of the four leading jets and pmiss, to the number of simulated QCD multijet events satisfying 123 0:1. Contributions from other SM processes to the QCD multijet control sample are subtracted after normalizing the simulation to data in dedicated control samples. The estimation is made in each SR. To improve the statistical uncertainty of the prediction, we combine the CR over Nt, NW, and Nres, in data and in simulation. In similarity with the estimations of the LL and Z( ) backgrounds, we extrapolate in top quark and W boson multiplicity using simulation that is corrected for di erences in the top quark and W boson tagging performance with respect to data. In the low m SR categories, we also combine regions of pTmiss in the QCD multijet control sample when yields are limited for the CR de ned by Nb 1, and we assign an uncertainty for the combination based on the data-to-simulation ratios observed in CR with Nb = 0. T The dominant source of events originating from QCD multijet processes that populate T the SR is from the severe mismeasurement of the pT of one or more jets in the event, which translates to large values of arti cial pmiss. The level of mismeasurement can be parameterized via the response variable rjet, de ned as the ratio of the reconstructed pT of the most mismeasured jet in the event to its generated pT, computed without including the loss of visible momentum due to neutrinos. The most mismeasured jet is selected based on the jet with greatest absolute di erence between the reconstructed and generated pT. In data, we construct the observable rjpesteudo, de ned as the ratio of the pT of a given jet to the magnitude of the vector sum of p~T and the total p~miss of the event, which o ers a T measure of the true jet response. The jet closest in Mismeasurement correction factors are extracted by comparing the rjpesteudo distributions in data and simulation. The correction factors are parameterized as functions of rjet and avor of the most mismeasured jet. The corrections range from 4 to 82%, and are applied T to p~miss is chosen for this calculation. to the simulation on an event-by-event basis. Due to the large production cross section of the QCD multijet process, samples of simulated QCD multijet events entering the stringently de ned SR have limited statistics. To increase it, we use a method that lets each event from the original sample appear multiple times. To this end, we use event \smearing", whereby a \new" event is created by randomly assigning rjet values to the leading two jets, ranked by their generated jet pT, and then recalculating all search variables based on the \smeared" jets. The rjet values are sampled from inclusive rjet distributions binned in both generated jet pT and jet avor in a region centered on the original rjet value. Each original event is smeared 100 times, and the statistical uncertainty in evaluated quantities is estimated through a bootstrapping procedure [96] that utilizes 50 pseudo-experiments. We assign a systematic uncertainty of 50% based on the measured di erence in the distribution of the azimuthal angles between the leading jets and pmiss before and after smearing. This accounts for any potential bias introduced in this method. Estimation of \rare" SM backgrounds Contributions from diboson (WW, WZ, and ZZ) processes are relatively small compared to the other backgrounds discussed above, and mainly a ect the SR in the low m analysis. We therefore estimate this background directly from simulation, with an uncertainty in the production cross section of 50% [97{99]. The ttZ contribution is also generally very small due to the rarity of this process. However, in SR requiring more than one top quark or W boson, this process can constitute a signi cant fraction of the total background due to the strong suppression of all other SM backgrounds. The ttZ simulation is validated using a three-lepton control sample, obtained using single-lepton triggers, requiring the presence of exactly three leptons (electrons or muons) that satisfy pT 40 GeV for the 20 GeV for the second and third lepton, and no additional lepton with leading lepton, pT pT 10 GeV. We further require at least ve jets, of which at least two are b-tagged. The same- avor, opposite-sign lepton pair with the highest dilepton pT is assumed to originate from Z boson decay. We require the presence of such a pair with the invariant mass near the Z boson mass (80{100 GeV) and pT greater than 100 GeV to probe boson kinematic properties similar to those in the search sample. The region outside the Z boson mass window is used to constrain the tt background. We nd that yields in simulated ttZ agree with those observed in data. An uncertainty of 24% is assigned to the normalization of the ttZ background in the SR, based on the statistical uncertainty of the simulation-todata correction factor obtained from this comparison. To assess any potential bias related to the extrapolation from the Z boson pT (pT(Z)) range of the control sample to that of the search sample, we evaluate the ttZ simulation-to-data correction factors with di erent requirements on the reconstructed pT(Z), and nd the pT-binned correction factors to be consistent with the inclusive correction factor evaluated for pT 100 GeV. Theoretical uncertainties related to the choice of PDF and renormalization ( R) and factorization ( F) scales are found to be up to 28% in simulated events. 6.5 Validation of the background methods in data categories of mbT The background estimation strategy is validated in a data control sample that is nonoverlapping to the samples used in the search and in the background estimation described above. The validation sample uses the same selection as the search sample, but focuses on low-pTmiss regions that are not utilized in the search. The requirement in high m event 175 GeV is also inverted when selecting events with at least two top quarks or W bosons to increase the statistical power of the validation exercise. Potential signal contamination in the validation regions is negligible. Figure 4 shows the predicted Observed QCD multijet Lost lepton m (right) selections. Ratios of the observed to SM predicted event counts derived from control regions are shown in the lower panel of each plot. The shaded blue band represents the statistical uncertainty combined with the systematic uncertainty resulting from the top quark and W boson tagging correction factors on the background prediction. backgrounds and the observed data in the validation regions. The selections de ning each bin are summarized in table 3. 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Cornelis, D. Dobur, A. Fagot, M. Gul, I. Khvastunov, D. Poyraz, C. Roskas, S. Salva, M. Tytgat, W. Verbeke, N. Zaganidis Universite Catholique de Louvain, Louvain-la-Neuve, Belgium H. Bakhshiansohi, O. Bondu, S. Brochet, G. Bruno, A. Caudron, S. De Visscher, C. Delaere, M. Delcourt, B. Francois, A. Giammanco, A. Jafari, M. Komm, G. Krintiras, V. Lemaitre, A. Magitteri, A. Mertens, M. Musich, K. Piotrzkowski, L. Quertenmont, M. Vidal Marono, S. Wertz N. Beliy Universite de Mons, Mons, Belgium Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil W.L. Alda Junior, F.L. Alves, G.A. Alves, L. Brito, M. Correa Martins Junior, C. Hensel, A. Moraes, M.E. Pol, P. Rebello Teles Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil E. Belchior Batista Das Chagas, W. Carvalho, J. Chinellato3, A. Custodio, E.M. Da Costa, G.G. Da Silveira4, D. De Jesus Damiao, S. Fonseca De Souza, L.M. Huertas Guativa, H. Malbouisson, M. Melo De Almeida, C. Mora Herrera, L. Mundim, H. Nogima, A. Santoro, A. Sznajder, E.J. Tonelli Manganote3, F. Torres Da Silva De Araujo, A. Vilela Pereira Brazil S. Ahujaa, Sciences Universidade Estadual Paulista a, Universidade Federal do ABC b, S~ao Paulo, C.A. Bernardesa, T.R. Fernandez Perez Tomeia, E.M. Gregoresb, P.G. Mercadanteb, S.F. Novaesa, Sandra S. Padulaa, D. Romero Abadb, J.C. Ruiz Vargasa Institute for Nuclear Research and Nuclear Energy of Bulgaria Academy of A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, M. Misheva, M. Rodozov, M. Shopova, S. Stoykova, G. Sultanov University of So a, So a, Bulgaria A. Dimitrov, I. Glushkov, L. Litov, B. Pavlov, P. Petkov Beihang University, Beijing, China W. Fang5, X. Gao5 Institute of High Energy Physics, Beijing, China M. Ahmad, J.G. Bian, G.M. Chen, H.S. Chen, M. Chen, Y. Chen, C.H. Jiang, D. Leggat, H. Liao, Z. Liu, F. Romeo, S.M. Shaheen, A. Spiezia, J. Tao, C. Wang, Z. Wang, E. Yazgan, H. Zhang, J. Zhao Beijing, China State Key Laboratory of Nuclear Physics and Technology, Peking University, Y. Ban, G. Chen, Q. Li, S. Liu, Y. Mao, S.J. Qian, D. Wang, Z. Xu Universidad de Los Andes, Bogota, Colombia C. Avila, A. Cabrera, L.F. Chaparro Sierra, C. Florez, C.F. Gonzalez Hernandez, J.D. Ruiz Alvarez University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Split, Croatia B. Courbon, N. Godinovic, D. Lelas, I. Puljak, P.M. Ribeiro Cipriano, T. Sculac University of Split, Faculty of Science, Split, Croatia Z. Antunovic, M. Kovac Institute Rudjer Boskovic, Zagreb, Croatia V. Brigljevic, D. Ferencek, K. Kadija, B. Mesic, A. Starodumov6, T. Susa University of Cyprus, Nicosia, Cyprus M.W. Ather, A. Attikis, G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos, P.A. Razis, H. Rykaczewski Charles University, Prague, Czech Republic M. Finger7, M. Finger Jr.7 Universidad San Francisco de Quito, Quito, Ecuador E. Carrera Jarrin Academy of Scienti c Research and Technology of the Arab Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt E. El-khateeb8, S. Elgammal9, A. Mohamed10 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 Helsinki Institute of Physics, Helsinki, Finland J. Harkonen, T. Jarvinen, V. Karimaki, R. Kinnunen, T. Lampen, K. Lassila-Perini, S. Lehti, T. Linden, P. Luukka, E. Tuominen, J. Tuominiemi, E. Tuovinen 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, J.L. Faure, F. Ferri, S. Ganjour, S. Ghosh, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry, I. Kucher, E. Locci, M. Machet, J. Malcles, G. Negro, J. Rander, A. Rosowsky, M.O . Sahin, M. Titov Laboratoire Leprince-Ringuet, Ecole polytechnique, CNRS/IN2P3, Universite Paris-Saclay, Palaiseau, France A. Abdulsalam, I. Antropov, S. Ba oni, F. Beaudette, P. Busson, L. Cadamuro, C. Charlot, R. Granier de Cassagnac, M. Jo, S. Lisniak, A. Lobanov, J. Martin Blanco, M. Nguyen, C. Ochando, G. Ortona, P. Paganini, P. Pigard, S. Regnard, R. Salerno, J.B. Sauvan, Y. Sirois, A.G. Stahl Leiton, T. Strebler, Y. Yilmaz, A. Zabi Universite de Strasbourg, CNRS, IPHC UMR 7178, F-67000 Strasbourg, France S. Gadrat J.-L. Agram11, J. Andrea, D. Bloch, J.-M. Brom, M. Buttignol, E.C. Chabert, N. Chanon, C. Collard, E. Conte11, X. Coubez, J.-C. Fontaine11, D. Gele, U. Goerlach, M. Jansova, A.-C. Le Bihan, N. Tonon, P. Van Hove Centre de Calcul de l'Institut National de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3, Villeurbanne, France Universite de Lyon, Universite Claude Bernard Lyon 1, CNRS-IN2P3, Institut de Physique Nucleaire de Lyon, Villeurbanne, France S. Beauceron, C. Bernet, G. Boudoul, R. Chierici, D. Contardo, P. Depasse, H. El Mamouni, J. Fay, L. Finco, S. Gascon, M. Gouzevitch, G. Grenier, B. Ille, F. Lagarde, I.B. Laktineh, M. Lethuillier, L. Mirabito, A.L. Pequegnot, S. Perries, A. Popov12, V. Sordini, M. Vander Donckt, S. Viret A. Khvedelidze7 Z. Tsamalaidze7 Georgian Technical University, Tbilisi, Georgia Tbilisi State University, Tbilisi, Georgia RWTH Aachen University, I. Physikalisches Institut, Aachen, Germany C. Autermann, S. Beranek, L. Feld, M.K. Kiesel, K. Klein, M. Lipinski, M. Preuten, C. Schomakers, J. Schulz, T. Verlage RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany A. Albert, 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, D. Teyssier, S. Thuer RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany G. Flugge, B. Kargoll, T. Kress, A. Kunsken, J. Lingemann, T. Muller, A. Nehrkorn, A. Nowack, C. Pistone, O. Pooth, A. Stahl13 Deutsches Elektronen-Synchrotron, Hamburg, Germany M. Aldaya Martin, T. Arndt, C. Asawatangtrakuldee, K. Beernaert, O. Behnke, U. Behrens, A. Bermudez Mart nez, A.A. Bin Anuar, K. Borras14, V. Botta, A. Campbell, P. Connor, C. Contreras-Campana, F. Costanza, C. Diez Pardos, G. Eckerlin, D. Eckstein, T. Eichhorn, E. Eren, E. Gallo15, J. Garay Garcia, A. Geiser, A. Gizhko, J.M. Grados Luyando, A. Grohsjean, P. Gunnellini, A. Harb, J. Hauk, M. Hempel16, H. Jung, A. Kalogeropoulos, M. Kasemann, J. Keaveney, C. Kleinwort, I. Korol, D. Krucker, W. Lange, A. Lelek, T. Lenz, J. Leonard, K. Lipka, W. Lohmann16, R. Mankel, I.A. Melzer-Pellmann, A.B. Meyer, G. Mittag, J. Mnich, A. Mussgiller, E. Ntomari, D. Pitzl, R. Placakyte, A. Raspereza, B. Roland, M. Savitskyi, P. Saxena, R. Shevchenko, S. Spannagel, N. Stefaniuk, G.P. Van Onsem, R. Walsh, Y. Wen, K. Wichmann, C. Wissing, O. Zenaiev University of Hamburg, Hamburg, Germany S. Bein, V. Blobel, M. Centis Vignali, A.R. Draeger, T. Dreyer, E. Garutti, D. Gonzalez, J. Haller, A. Hinzmann, M. Ho mann, A. Karavdina, R. Klanner, R. Kogler, N. Kovalchuk, S. Kurz, T. Lapsien, I. Marchesini, D. Marconi, M. Meyer, M. Niedziela, D. Nowatschin, F. Pantaleo13, T. Pei er, A. Perieanu, C. Scharf, P. Schleper, A. Schmidt, S. Schumann, J. Schwandt, J. Sonneveld, 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 M. Akbiyik, C. Barth, S. Baur, E. Butz, R. Caspart, T. Chwalek, F. Colombo, W. De Boer, A. Dierlamm, B. Freund, R. Friese, M. Gi els, A. Gilbert, D. Haitz, F. Hartmann13, Paraskevi, Greece I. Topsis-Giotis S.M. Heindl, U. Husemann, F. Kassel13, S. Kudella, H. Mildner, M.U. Mozer, Th. Muller, M. Plagge, G. Quast, K. Rabbertz, M. Schroder, I. Shvetsov, G. Sieber, H.J. Simonis, R. Ulrich, S. Wayand, M. Weber, T. Weiler, S. Williamson, C. Wohrmann, R. Wolf Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia 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 University of Ioannina, Ioannina, Greece I. Evangelou, C. Foudas, P. Kokkas, S. Mallios, N. Manthos, I. Papadopoulos, E. Paradas, J. Strologas, F.A. Triantis MTA-ELTE Lendulet CMS Particle and Nuclear Physics Group, Eotvos Lorand University, Budapest, Hungary M. Csanad, N. Filipovic, G. Pasztor G. Bencze, C. Hajdu, G. Vesztergombi18, A.J. Zsigmond Wigner Research Centre for Physics, Budapest, Hungary D. Horvath17, A. Hunyadi, F. Sikler, V. Veszpremi, Institute of Nuclear Research ATOMKI, Debrecen, Hungary N. Beni, S. Czellar, J. Karancsi19, A. Makovec, J. Molnar, Z. Szillasi Institute of Physics, University of Debrecen, Debrecen, Hungary M. Bartok18, P. Raics, Z.L. Trocsanyi, B. Ujvari Indian Institute of Science (IISc), Bangalore, India S. Choudhury, J.R. Komaragiri National Institute of Science Education and Research, Bhubaneswar, India S. Bahinipati20, S. Bhowmik, P. Mal, K. Mandal, A. Nayak21, D.K. Sahoo20, N. Sahoo, S.K. Swain Panjab University, Chandigarh, India S. Bansal, S.B. Beri, V. Bhatnagar, U. Bhawandeep, R. Chawla, N. Dhingra, A.K. Kalsi, A. Kaur, M. Kaur, R. Kumar, P. Kumari, A. Mehta, J.B. Singh, G. Walia University of Delhi, Delhi, India Ashok Kumar, Aashaq Shah, A. Bhardwaj, S. Chauhan, B.C. Choudhary, R.B. Garg, S. Keshri, A. Kumar, S. Malhotra, M. Naimuddin, K. Ranjan, R. Sharma, V. Sharma Saha Institute of Nuclear Physics, HBNI, Kolkata, India R. Bhardwaj, R. Bhattacharya, S. Bhattacharya, 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 P.K. Behera Bhabha Atomic Research Centre, Mumbai, India R. Chudasama, D. Dutta, V. Jha, V. Kumar, A.K. Mohanty13, 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 Tata Institute of Fundamental Research-B, Mumbai, India S. Banerjee, S. Bhattacharya, S. Chatterjee, P. Das, M. Guchait, Sa. Jain, S. Kumar, M. Maity22, G. Majumder, K. Mazumdar, T. Sarkar22, N. Wickramage23 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. Chenarani24, E. Eskandari Tadavani, S.M. Etesami24, M. Khakzad, M. Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi25, F. Rezaei Hosseinabadi, B. Safarzadeh26, 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, F. Erricoa;b, L. Fiorea, G. Iasellia;c, S. Lezkia;b, G. Maggia;c, M. Maggia, G. Minielloa;b, S. Mya;b, S. Nuzzoa;b, A. Pompilia;b, G. Pugliesea;c, R. Radognaa;b, A. Ranieria, G. Selvaggia;b, A. Sharmaa, L. Silvestrisa;13, R. Vendittia, P. Verwilligena INFN Sezione di Bologna a, Universita di Bologna b, Bologna, Italy G. Abbiendia, C. Battilanaa;b, D. Bonacorsia;b, S. Braibant-Giacomellia;b, R. Campaninia;b, P. Capiluppia;b, A. 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Dall'Ossoa;b, P. De Castro Manzanoa, T. Dorigoa, U. Dossellia, F. Gasparinia;b, A. Gozzelinoa, S. Lacapraraa, M. Margonia;b, G. Marona;29, A.T. Meneguzzoa;b, M. Michelottoa, F. Montecassianoa, N. Pozzobona;b, P. Ronchesea;b, R. Rossina;b, E. Torassaa, M. Zanettia;b, P. Zottoa;b INFN Sezione di Pavia a, Universita di Pavia b, Pavia, Italy A. Braghieria, F. Fallavollitaa;b, A. Magnania;b, P. Montagnaa;b, S.P. Rattia;b, V. Rea, M. Ressegotti, C. Riccardia;b, P. Salvinia, I. Vaia;b, P. Vituloa;b INFN Sezione di Perugia a, Universita di Perugia b, Perugia, Italy L. Alunni Solestizia;b, M. Biasinia;b, G.M. Bileia, C. Cecchia;b, D. Ciangottinia;b, L. Fanoa;b, P. Laricciaa;b, R. Leonardia;b, E. Manonia, G. Mantovania;b, V. Mariania;b, M. Menichellia, A. Rossia;b, A. Santocchiaa;b, D. Spigaa INFN Sezione di Pisa a, Universita di Pisa b, Scuola Normale Superiore di Pisa c, Pisa, Italy K. Androsova, P. Azzurria;13, G. Bagliesia, J. Bernardinia, T. Boccalia, L. Borrello, R. 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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, A. Zanettia Kyungpook National University, Daegu, Korea D.H. Kim, G.N. Kim, M.S. Kim, J. Lee, S. Lee, S.W. Lee, C.S. Moon, Y.D. Oh, S. Sekmen, D.C. Son, Y.C. Yang Chonbuk National University, Jeonju, Korea A. Lee Chonnam National University, Institute for Universe and Elementary Particles, Kwangju, Korea H. Kim, D.H. Moon, G. Oh Hanyang University, Seoul, Korea J.A. Brochero Cifuentes, J. Goh, T.J. Kim Korea University, Seoul, Korea J. Lim, S.K. Park, Y. Roh Seoul National 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. Almond, J. Kim, J.S. Kim, H. Lee, K. Lee, K. Nam, S.B. Oh, B.C. Radburn-Smith, S.h. Seo, U.K. Yang, H.D. Yoo, G.B. Yu 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 HJEP10(27)5 National Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Malaysia M.N. Yusli, Z. Zolkapli I. Ahmed, Z.A. Ibrahim, M.A.B. Md Ali31, F. Mohamad Idris32, W.A.T. Wan Abdullah, Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico H. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-De La Cruz33, R. Lopez-Fernandez, J. Mejia Guisao, A. Sanchez-Hernandez Universidad Iberoamericana, Mexico City, Mexico S. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia Benemerita Universidad Autonoma de Puebla, Puebla, Mexico I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad Autonoma de San Luis Potos , San Luis Potos , Mexico A. Morelos Pineda University of Auckland, Auckland, New Zealand HJEP10(27)5 D. Krofcheck P.H. Butler M. Waqas 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, A. Saddique, 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, Warsaw, Poland K. Bunkowski, A. Byszuk34, K. Doroba, A. Kalinowski, M. Konecki, J. Krolikowski, M. Misiura, M. Olszewski, A. Pyskir, M. Walczak Laboratorio de Instrumentac~ao e F sica Experimental de Part culas, Lisboa, Portugal P. Bargassa, C. Beir~ao Da Cruz E 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. Matveev35;36, V. Palichik, V. Perelygin, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, N. Voytishin, A. Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia Y. Ivanov, V. Kim37, E. Kuznetsova38, P. Levchenko, V. Murzin, V. Oreshkin, I. Smirnov, V. Sulimov, L. Uvarov, S. Vavilov, A. Vorobyev Institute for Nuclear Research, Moscow, Russia Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov, N. Krasnikov, A. Pashenkov, D. Tlisov, A. Toropin Institute for Theoretical and Experimental Physics, Moscow, Russia V. Epshteyn, V. Gavrilov, N. Lychkovskaya, V. Popov, I. Pozdnyakov, G. Safronov, A. Spiridonov, A. Stepennov, M. Toms, E. Vlasov, A. Zhokin HJEP10(27)5 Moscow Institute of Physics and Technology, Moscow, Russia T. Aushev, A. Bylinkin36 National Research Nuclear University 'Moscow Engineering Physics Institute' (MEPhI), Moscow, Russia M. Chadeeva39, P. Parygin, D. Philippov, S. Polikarpov, E. Popova, V. Rusinov P.N. Lebedev Physical Institute, Moscow, Russia V. Andreev, M. Azarkin36, I. Dremin36, M. Kirakosyan36, A. Terkulov Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia A. Snigirev A. Baskakov, A. Belyaev, E. Boos, V. Bunichev, M. Dubinin40, L. Dudko, A. Ershov, V. Klyukhin, O. Kodolova, I. Lokhtin, I. Miagkov, S. Obraztsov, S. Petrushanko, V. Savrin, Novosibirsk State University (NSU), Novosibirsk, Russia V. Blinov41, Y.Skovpen41, D. Shtol41 State Research Center of Russian Federation, Institute for High Energy Physics, Protvino, Russia I. Azhgirey, I. Bayshev, S. Bitioukov, D. Elumakhov, V. Kachanov, A. Kalinin, D. Konstantinov, V. Krychkine, V. Petrov, R. Ryutin, A. Sobol, S. Troshin, N. Tyurin, A. Uzunian, A. Volkov University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia P. Adzic42, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic, V. Rekovic Centro de Investigaciones Energeticas Medioambientales y Tecnologicas (CIEMAT), Madrid, Spain J. Alcaraz Maestre, M. Barrio Luna, M. Cerrada, 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, A. Perez-Calero Yzquierdo, J. Puerta Pelayo, A. Quintario Olmeda, I. Redondo, L. Romero, M.S. Soares, A. Alvarez Fernandez Universidad Autonoma de Madrid, Madrid, Spain J.F. de Troconiz, M. Missiroli, D. Moran Universidad de Oviedo, Oviedo, Spain J. Cuevas, C. Erice, J. Fernandez Menendez, I. Gonzalez Caballero, J.R. Gonzalez Fernandez, E. Palencia Cortezon, S. Sanchez Cruz, I. Suarez Andres, P. Vischia, J.M. Vizan Garcia Santander, Spain Instituto de F sica de Cantabria (IFCA), CSIC-Universidad de Cantabria, 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. Au ray, 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. Daponte, A. David, M. De Gruttola, A. De Roeck, E. Di Marco43, M. Dobson, B. Dorney, T. du Pree, M. Dunser, N. Dupont, A. Elliott-Peisert, P. Everaerts, G. Franzoni, J. Fulcher, W. Funk, D. Gigi, K. Gill, F. Glege, D. Gulhan, S. Gundacker, M. Gutho , P. Harris, J. Hegeman, V. Innocente, P. Janot, O. Karacheban16, J. Kieseler, H. Kirschenmann, V. Knunz, A. Kornmayer13, M.J. Kortelainen, C. Lange, P. Lecoq, C. Lourenco, M.T. Lucchini, L. Malgeri, M. Mannelli, A. Martelli, F. Meijers, J.A. Merlin, S. Mersi, E. Meschi, P. Milenovic44, F. Moortgat, 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. Rolandi45, M. Rovere, H. Sakulin, C. Schafer, C. Schwick, M. Seidel, M. Selvaggi, A. Sharma, P. Silva, P. Sphicas46, J. Steggemann, M. Stoye, M. Tosi, D. Treille, A. Triossi, A. Tsirou, V. Veckalns47, G.I. Veres18, M. Verweij, N. Wardle, W.D. Zeuner Paul Scherrer Institut, Villigen, Switzerland W. Bertly, L. Caminada48, K. Deiters, W. Erdmann, R. Horisberger, Q. Ingram, H.C. Kaestli, D. Kotlinski, U. Langenegger, T. Rohe, S.A. Wiederkehr Institute for Particle Physics, ETH Zurich, Zurich, Switzerland F. Bachmair, L. Bani, P. Berger, L. Bianchini, B. Casal, G. Dissertori, M. Dittmar, M. Donega, C. Grab, C. Heidegger, D. Hits, J. Hoss, G. Kasieczka, T. Klijnsma, W. Lustermann, B. Mangano, M. Marionneau, M.T. Meinhard, D. Meister, F. Micheli, P. Musella, F. Nessi-Tedaldi, F. Pandol , J. Pata, F. Pauss, G. Perrin, L. Perrozzi, M. Quittnat, M. Schonenberger, L. Shchutska, V.R. Tavolaro, K. Theo latos, M.L. Vesterbacka Olsson, R. Wallny, A. Zagozdzinska34, D.H. Zhu Universitat Zurich, Zurich, Switzerland T.K. Aarrestad, C. Amsler49, M.F. Canelli, A. De Cosa, S. Donato, C. Galloni, T. Hreus, B. Kilminster, J. Ngadiuba, D. Pinna, G. Rauco, P. Robmann, D. Salerno, C. Seitz, A. Zucchetta National Central University, Chung-Li, Taiwan V. Candelise, T.H. Doan, Sh. Jain, R. Khurana, C.M. Kuo, W. Lin, A. Pozdnyakov, S.S. Yu 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. Min~ano Moya, E. Paganis, A. Psallidas, J.f. Tsai Chulalongkorn University, Faculty of Science, Department of Physics, Bangkok, Thailand Turkey B. Asavapibhop, K. Kovitanggoon, G. Singh, N. Srimanobhas Cukurova University, Physics Department, Science and Art Faculty, Adana, A. Adiguzel50, M.N. Bakirci51, F. Boran, S. Cerci52, S. Damarseckin, Z.S. Demiroglu, C. Dozen, I. Dumanoglu, S. Girgis, G. Gokbulut, Y. Guler, I. Hos53, E.E. Kangal54, O. Kara, A. Kayis Topaksu, U. Kiminsu, M. Oglakci, G. Onengut55, K. Ozdemir56, B. Tali52, S. Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East Technical University, Physics Department, Ankara, Turkey B. Bilin, G. Karapinar57, K. Ocalan58, M. Yalvac, M. Zeyrek Bogazici University, Istanbul, Turkey E. Gulmez, M. Kaya59, O. Kaya60, S. Tekten, E.A. Yetkin61 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 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, O. Davignon, H. Flacher, J. Goldstein, M. Grimes, G.P. Heath, H.F. Heath, J. Jacob, L. Kreczko, C. Lucas, D.M. Newbold62, S. Paramesvaran, A. Poll, T. Sakuma, S. Seif El Nasr-storey, D. Smith, V.J. Smith Rutherford Appleton Laboratory, Didcot, United Kingdom K.W. Bell, A. Belyaev63, 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 S.C. Zenz M. Turner D. Zou D. Yu Imperial College, London, United Kingdom R. Bainbridge, S. Breeze, O. Buchmuller, A. Bundock, S. Casasso, M. Citron, D. Colling, L. Corpe, P. Dauncey, G. Davies, A. De Wit, M. Della Negra, R. Di Maria, A. Elwood, Y. Haddad, G. Hall, G. Iles, T. James, R. Lane, C. Laner, L. Lyons, A.-M. Magnan, S. Malik, L. Mastrolorenzo, T. Matsushita, J. Nash, A. Nikitenko6, V. Palladino, M. Pesaresi, D.M. Raymond, A. Richards, A. Rose, E. Scott, C. Seez, A. Shtipliyski, S. Summers, A. Tapper, K. Uchida, M. Vazquez Acosta64, T. Virdee13, D. Winterbottom, J. Wright, Brunel University, Uxbridge, United Kingdom J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, I.D. Reid, P. Symonds, L. Teodorescu, Baylor University, Waco, U.S.A. A. Borzou, K. Call, J. Dittmann, K. Hatakeyama, H. Liu, N. Pastika, C. Smith Catholic University of America, Washington DC, U.S.A. R. Bartek, A. Dominguez The University of Alabama, Tuscaloosa, U.S.A. A. Buccilli, 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, D. Cutts, A. Garabedian, J. Hakala, U. Heintz, J.M. Hogan, K.H.M. Kwok, E. Laird, G. Landsberg, Z. Mao, M. Narain, J. Pazzini, S. Piperov, S. Sagir, R. Syarif, University of California, Davis, Davis, U.S.A. R. Band, C. Brainerd, D. Burns, M. Calderon De La Barca Sanchez, M. Chertok, J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk, M. Gardner, W. Ko, R. Lander, C. Mclean, M. Mulhearn, D. Pellett, J. Pilot, S. Shalhout, M. Shi, J. Smith, M. Squires, D. Stolp, K. Tos, M. Tripathi, Z. Wang University of California, Los Angeles, U.S.A. M. Bachtis, C. Bravo, R. Cousins, A. Dasgupta, A. Florent, J. Hauser, M. Ignatenko, N. Mccoll, D. Saltzberg, C. Schnaible, V. Valuev University of California, Riverside, Riverside, U.S.A. E. Bouvier, K. Burt, R. Clare, J. Ellison, J.W. Gary, S.M.A. Ghiasi Shirazi, G. Hanson, J. Heilman, P. Jandir, E. Kennedy, F. Lacroix, O.R. Long, M. Olmedo Negrete, M.I. Paneva, A. Shrinivas, W. Si, L. Wang, H. Wei, S. Wimpenny, B. R. Yates University of California, San Diego, La Jolla, U.S.A. J.G. Branson, S. Cittolin, M. Derdzinski, B. Hashemi, A. Holzner, D. Klein, G. Kole, V. Krutelyov, J. Letts, I. Macneill, M. Masciovecchio, D. Olivito, S. Padhi, M. Pieri, M. Sani, V. Sharma, S. Simon, M. Tadel, A. Vartak, S. Wasserbaech65, J. Wood, F. Wurthwein, A. Yagil, G. Zevi Della Porta University of California, Santa Barbara - Department of Physics, Santa Barbara, U.S.A. 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 California Institute of Technology, Pasadena, U.S.A. D. Anderson, J. Bendavid, A. Bornheim, J.M. Lawhorn, H.B. Newman, T. Nguyen, C. Pena, M. Spiropulu, J.R. Vlimant, S. Xie, Z. Zhang, R.Y. Zhu Carnegie Mellon University, Pittsburgh, U.S.A. M.B. Andrews, T. Ferguson, T. Mudholkar, M. Paulini, J. Russ, M. Sun, H. Vogel, I. Vorobiev, M. Weinberg University of Colorado Boulder, Boulder, U.S.A. J.P. Cumalat, W.T. Ford, F. Jensen, A. Johnson, M. Krohn, S. Leontsinis, T. Mulholland, K. Stenson, S.R. Wagner Cornell University, Ithaca, U.S.A. J. Alexander, J. Chaves, J. Chu, S. Dittmer, K. Mcdermott, N. Mirman, J.R. Patterson, A. Rinkevicius, A. Ryd, L. Skinnari, L. So , S.M. Tan, Z. Tao, J. Thom, J. Tucker, P. Wittich, M. Zientek Fermi National Accelerator Laboratory, Batavia, U.S.A. S. Abdullin, M. Albrow, G. Apollinari, A. Apresyan, A. Apyan, S. Banerjee, L.A.T. Bauerdick, A. Beretvas, J. Berryhill, P.C. Bhat, G. Bolla, K. Burkett, J.N. Butler, A. Canepa, G.B. Cerati, H.W.K. Cheung, F. Chlebana, M. Cremonesi, J. Duarte, V.D. Elvira, J. Freeman, Z. Gecse, E. Gottschalk, L. Gray, D. Green, S. Grunendahl, O. Gutsche, R.M. Harris, S. Hasegawa, J. Hirschauer, Z. Hu, B. Jayatilaka, S. Jindariani, M. Johnson, U. Joshi, B. Klima, B. Kreis, S. Lammel, D. Lincoln, R. Lipton, M. Liu, T. Liu, R. Lopes De Sa, J. Lykken, K. Maeshima, N. Magini, J.M. Marra no, S. Maruyama, D. Mason, P. McBride, P. Merkel, S. Mrenna, S. Nahn, V. O'Dell, K. Pedro, O. Prokofyev, G. Rakness, L. Ristori, B. Schneider, E. Sexton-Kennedy, A. Soha, W.J. Spalding, L. Spiegel, S. Stoynev, J. Strait, N. Strobbe, L. Taylor, S. Tkaczyk, N.V. Tran, L. Uplegger, E.W. Vaandering, C. Vernieri, M. Verzocchi, R. Vidal, M. Wang, H.A. Weber, A. Whitbeck University of Florida, Gainesville, U.S.A. D. Acosta, P. Avery, P. Bortignon, D. Bourilkov, A. Brinkerho , A. Carnes, M. Carver, D. Curry, S. Das, R.D. Field, I.K. Furic, J. Konigsberg, A. Korytov, K. Kotov, P. Ma, K. Matchev, H. Mei, G. Mitselmakher, D. Rank, D. Sperka, N. Terentyev, L. Thomas, J. Wang, S. Wang, J. Yelton Florida International University, Miami, U.S.A. Y.R. Joshi, S. Linn, P. Markowitz, J.L. Rodriguez Florida State University, Tallahassee, U.S.A. A. Ackert, T. Adams, A. Askew, S. Hagopian, V. Hagopian, K.F. Johnson, T. Kolberg, G. Martinez, T. Perry, H. Prosper, A. Saha, A. Santra, R. Yohay Florida Institute of Technology, Melbourne, U.S.A. M.M. Baarmand, V. Bhopatkar, S. Colafranceschi, M. Hohlmann, D. Noonan, T. Roy, F. Yumiceva University of Illinois at Chicago (UIC), Chicago, U.S.A. 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 The University of Iowa, Iowa City, U.S.A. B. Bilki66, W. Clarida, K. Dilsiz67, S. Durgut, R.P. Gandrajula, M. Haytmyradov, V. Khristenko, J.-P. Merlo, H. Mermerkaya68, A. Mestvirishvili, A. Moeller, J. Nachtman, H. Ogul69, Y. Onel, F. Ozok70, A. Penzo, C. Snyder, E. Tiras, J. Wetzel, K. Yi Johns Hopkins University, Baltimore, U.S.A. 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, U.S.A. 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, U.S.A. A. Ivanov, K. Kaadze, Y. Maravin, A. Mohammadi, L.K. Saini, N. Skhirtladze, S. Toda Lawrence Livermore National Laboratory, Livermore, U.S.A. F. Rebassoo, D. Wright University of Maryland, College Park, U.S.A. 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, U.S.A. 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 Minnesota, Minneapolis, U.S.A. A.C. Benvenuti, R.M. Chatterjee, A. Evans, P. Hansen, S. Kalafut, Y. Kubota, Z. Lesko, J. Mans, S. Nourbakhsh, N. Ruckstuhl, R. Rusack, J. Turkewitz University of Mississippi, Oxford, U.S.A. J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, U.S.A. E. Avdeeva, K. Bloom, D.R. Claes, C. Fangmeier, R. Gonzalez Suarez, R. Kamalieddin, I. Kravchenko, 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, A. Godshalk, C. Harrington, I. Iashvili, D. Nguyen, A. Parker, S. Rappoccio, B. Roozbahani Northeastern University, Boston, U.S.A. moto, R. Teixeira De Lima, D. Trocino, D. Wood Northwestern University, Evanston, U.S.A. G. Alverson, E. Barberis, A. Hortiangtham, A. Massironi, D.M. Morse, D. Nash, T. OriS. Bhattacharya, O. Charaf, K.A. Hahn, 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. Loukas, N. Marinelli, F. Meng, C. Mueller, Y. Musienko35, M. Planer, A. Reinsvold, R. Ruchti, G. Smith, S. Taroni, M. Wayne, M. Wolf, A. Woodard The Ohio State University, Columbus, U.S.A. J. Alimena, L. Antonelli, B. Bylsma, L.S. Durkin, S. Flowers, B. Francis, A. Hart, C. Hill, W. Ji, B. Liu, W. Luo, D. Puigh, B.L. Winer, H.W. Wulsin Princeton University, Princeton, U.S.A. A. Benaglia, S. Cooperstein, O. Driga, P. Elmer, J. Hardenbrook, P. Hebda, S. Higginbotham, D. Lange, J. Luo, D. Marlow, K. Mei, I. Ojalvo, J. Olsen, C. Palmer, P. Piroue, D. Stickland, C. Tully University of Puerto Rico, Mayaguez, U.S.A. S. Malik, S. Norberg Purdue University, West Lafayette, U.S.A. W. Xie Purdue University Northwest, Hammond, U.S.A. T. Cheng, N. Parashar, J. Stupak Rice University, Houston, U.S.A. A. Barker, V.E. Barnes, S. Folgueras, L. Gutay, M.K. Jha, M. Jones, A.W. Jung, A. Khatiwada, D.H. Miller, N. Neumeister, C.C. Peng, J.F. Schulte, J. Sun, F. Wang, A. Adair, B. Akgun, Z. Chen, K.M. Ecklund, F.J.M. Geurts, M. Guilbaud, M. Kilpatrick, W. Li, B. Michlin, B.P. Padley, J. Roberts, J. Rorie, Z. Tu, J. Zabel 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, U.S.A. R. Ciesielski, K. Goulianos, C. Mesropian Rutgers, The State University of New Jersey, Piscataway, U.S.A. A. Agapitos, J.P. Chou, Y. Gershtein, T.A. Gomez 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. She eld, S. Somalwar, R. Stone, S. Thomas, P. Thomassen, M. Walker University of Tennessee, Knoxville, U.S.A. A.G. Delannoy, M. Foerster, J. Heideman, G. Riley, K. Rose, S. Spanier, K. Thapa Texas A&M University, College Station, U.S.A. O. Bouhali71, A. Castaneda Hernandez71, A. Celik, M. Dalchenko, M. De Mattia, A. Delgado, S. Dildick, R. Eusebi, J. Gilmore, T. Huang, T. Kamon72, R. Mueller, Y. Pakhotin, R. Patel, A. Perlo , L. Pernie, D. Rathjens, A. Safonov, A. Tatarinov, K.A. Ulmer Texas Tech University, Lubbock, U.S.A. N. Akchurin, J. Damgov, F. De Guio, P.R. Dudero, J. Faulkner, E. Gurpinar, S. Kunori, K. Lamichhane, S.W. Lee, T. Libeiro, T. Peltola, S. Undleeb, I. Volobouev, Z. Wang Vanderbilt University, Nashville, U.S.A. S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, P. Sheldon, S. Tuo, J. Velkovska, Q. Xu University of Virginia, Charlottesville, U.S.A. M.W. Arenton, P. Barria, B. Cox, 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. R. Harr, P.E. Karchin, J. Sturdy, S. Zaleski University of Wisconsin - Madison, Madison, WI, U.S.A. M. Brodski, J. Buchanan, C. Caillol, S. Dasu, L. Dodd, S. Duric, B. Gomber, M. Grothe, M. Herndon, A. Herve, U. Hussain, P. Klabbers, A. Lanaro, A. Levine, K. Long, R. Loveless, G.A. Pierro, G. Polese, T. Ruggles, A. Savin, N. Smith, W.H. Smith, D. Taylor, N. Woods y: Deceased China 1: Also at Vienna University of Technology, Vienna, Austria 2: Also at State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, 3: Also at Universidade Estadual de Campinas, Campinas, Brazil 4: Also at Universidade Federal de Pelotas, Pelotas, Brazil 6: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia 7: Also at Joint Institute for Nuclear Research, Dubna, Russia 8: Now at Ain Shams University, Cairo, Egypt 9: Now at British University in Egypt, Cairo, Egypt 10: Also at Zewail City of Science and Technology, Zewail, Egypt 11: Also at Universite de Haute Alsace, Mulhouse, France 12: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia 13: Also at CERN, European Organization for Nuclear Research, Geneva, Switzerland 14: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany 15: Also at University of Hamburg, Hamburg, Germany 16: Also at Brandenburg University of Technology, Cottbus, Germany 17: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary 18: Also at MTA-ELTE Lendulet CMS Particle and Nuclear Physics Group, Eotvos Lorand University, Budapest, Hungary 19: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary 20: Also at Indian Institute of Technology Bhubaneswar, Bhubaneswar, India 21: Also at Institute of Physics, Bhubaneswar, India 22: Also at University of Visva-Bharati, Santiniketan, India 23: Also at University of Ruhuna, Matara, Sri Lanka 24: Also at Isfahan University of Technology, Isfahan, Iran 25: Also at Yazd University, Yazd, Iran 26: Also at Plasma Physics Research Center, Science and Research Branch, Islamic Azad University, Tehran, Iran 27: Also at Universita degli Studi di Siena, Siena, Italy 28: Also at INFN Sezione di Milano-Bicocca; Universita di Milano-Bicocca, Milano, Italy 29: Also at Laboratori Nazionali di Legnaro dell'INFN, Legnaro, Italy 30: Also at Purdue University, West Lafayette, U.S.A. 31: Also at International Islamic University of Malaysia, Kuala Lumpur, Malaysia 32: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia 33: Also at Consejo Nacional de Ciencia y Tecnolog a, Mexico city, Mexico 34: Also at Warsaw University of Technology, Institute of Electronic Systems, Warsaw, Poland 35: Also at Institute for Nuclear Research, Moscow, Russia 36: Now at National Research Nuclear University 'Moscow 37: Also at St. Petersburg State Polytechnical University, St. Petersburg, Russia 38: Also at University of Florida, Gainesville, U.S.A. 39: Also at P.N. Lebedev Physical Institute, Moscow, Russia 40: Also at California Institute of Technology, Pasadena, U.S.A. 41: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia 42: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia 43: Also at INFN Sezione di Roma; Sapienza Universita di Roma, Rome, Italy 44: Also at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia 45: Also at Scuola Normale e Sezione dell'INFN, Pisa, Italy 46: Also at National and Kapodistrian University of Athens, Athens, Greece 47: Also at Riga Technical University, Riga, Latvia 49: Also at Stefan Meyer Institute for Subatomic Physics (SMI), Vienna, Austria 50: Also at Istanbul University, Faculty of Science, Istanbul, Turkey 51: Also at Gaziosmanpasa University, Tokat, Turkey 52: Also at Adiyaman University, Adiyaman, Turkey 53: Also at Istanbul Aydin University, Istanbul, Turkey 54: Also at Mersin University, Mersin, Turkey 55: Also at Cag University, Mersin, Turkey 56: Also at Piri Reis University, Istanbul, Turkey 57: Also at Izmir Institute of Technology, Izmir, Turkey 58: Also at Necmettin Erbakan University, Konya, Turkey 59: Also at Marmara University, Istanbul, Turkey 60: Also at Kafkas University, Kars, Turkey 61: Also at Istanbul Bilgi University, Istanbul, Turkey 62: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom 63: Also at School of Physics and Astronomy, University of Southampton, Southampton, United Kingdom 64: Also at Instituto de Astrof sica de Canarias, La Laguna, Spain 65: Also at Utah Valley University, Orem, U.S.A. 66: Also at Beykent University, Istanbul, Turkey 67: Also at Bingol University, Bingol, Turkey 68: Also at Erzincan University, Erzincan, Turkey 69: Also at Sinop University, Sinop, Turkey 70: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey 71: Also at Texas A&M University at Qatar, Doha, Qatar 72: Also at Kyungpook National University, Daegu, Korea


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Kargoll, T. Kress, A. Künsken. Search for direct production of supersymmetric partners of the top quark in the all-jets final state in proton-proton collisions at \( \sqrt{s}=13 \) TeV, Journal of High Energy Physics, 2017, 5, DOI: 10.1007/JHEP10(2017)005