Search for dark matter and unparticles in events with a Z boson and missing transverse momentum in proton-proton collisions at \( \sqrt{s}=13 \) TeV

Journal of High Energy Physics, Mar 2017

A search for dark matter and unparticle production at the LHC has been performed using events containing two charged leptons (electrons or muons), consistent with the decay of a Z boson, and large missing transverse momentum. This study is based on data collected with the CMS detector in 2015, corresponding to an integrated luminosity of 2.3 fb−1 of proton-proton collisions at the LHC, at a center-of-mass energy of 13 TeV. No excess over the standard model expectation is observed. Compared to previous searches in this topology, which exclusively relied on effective field theories, the results are interpreted in terms of a simplified model of dark matter production for both vector and axial vector couplings between a mediator and dark matter particles. The first study of this class of models using CMS data at \( \sqrt{s}=13 \) TeV is presented. Additionally, effective field theories of dark matter and unparticle production are used to interpret the data.

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Search for dark matter and unparticles in events with a Z boson and missing transverse momentum in proton-proton collisions at \( \sqrt{s}=13 \) TeV

Received: January proton-proton collisions at s G. Grenier 0 1 2 3 B. Ille 0 1 2 3 F. Lagarde 0 1 2 3 I.B. Laktineh 0 1 2 3 M. Lethuillier 0 1 2 3 L. Mirabito 0 1 2 3 A.L. Pequegnot 0 1 2 3 0 State University of New York at Bu alo , Bu alo , U.S.A 1 tute' (MEPhI) , Moscow , Russia 2 University , Budapest , Hungary 3 59: Also at Marmara University , Istanbul , Turkey A search for dark matter and unparticle production at the LHC has been performed using events containing two charged leptons (electrons or muons), consistent with the decay of a Z boson, and large missing transverse momentum. This study is based on data collected with the CMS detector in 2015, corresponding to an integrated luminosity of 2.3 fb 1 of proton-proton collisions at the LHC, at a center-of-mass energy of 13 TeV. No excess over the standard model expectation is observed. Compared to previous searches in this topology, which exclusively relied on e ective eld theories, the results are interpreted in terms of a simpli ed model of dark matter production for both vector and axial vector couplings between a mediator and dark matter particles. The rst study of this class of Beyond Standard Model; Hadron-Hadron scattering (experiments) - Search for dark boson and missing transverse momentum in models using CMS data at p of dark matter and unparticle production are used to interpret the data. 1 Introduction 2 3 4 The CMS detector Event reconstruction Event selection Background estimation ciencies and systematic uncertainties The DM interpretation Unparticle interpretation Model-independent limits The CMS collaboration Introduction According to the well-established CDM model of cosmology, known matter only comprises about 5% of the total energy content of the universe, with 27% contributed by dark matter (DM) and the rest being dark energy [1]. Although strong astrophysical evidence indicates the existence of DM, there is no evidence yet for nongravitational interactions between DM and standard model (SM) particles. DM searches exploit a number of methods including direct detection [2] and indirect detection [3]. If there are DM particles that can be observed in direct detection experiments, they could have substantial couplings to nucleons, and therefore could be produced at the CERN LHC. A theoretically promising possibility is that DM may take the form of weakly interacting massive particles. Searches for production of such particles at colliders typically consider the case of DM recoiling against a standard model particle (\tag") to obtain a de ned signature [4]. Such searches have been performed using various standard model signatures as tags [5{20]. In models where DM production is mediated by an interaction involving SM quarks, the monojet signature is typically the most sensitive. If DM particles are instead produced via radiation emitted by a standard The study presented here considers the case of a Z boson recoiling against a pair of . The Z boson subsequently decays into two charged leptons (`+` , where due to the undetected DM particles. A simpli ed tree-level ultraviolet-complete model [4] that contains a massive spin-1 mediator exchanged in the s-channel is considered here. In this model, the spin-1 mediator A could have either vector or axial-vector couplings to the SM and DM particles. The DM particle is assumed to be a Dirac fermion. The interaction Lagrangian of the s-channel vector mediated DM model can be written as: Lvector = where the mediator is labeled as A, and its coupling to DM particles is labeled as g . The coupling between the mediator and SM quarks is labeled as gq, and is assumed to be universal to all quarks. The Lagrangian for an axial-vector mediator is obtained by making 5 in all terms. As a benchmark model for DM production via a scalar coupling, an e ective eld theory (EFT) with dimension-7 operators is also considered [4]. It contains SU (2)L U (1)Y gauge invariant couplings between a DM pair and two SM gauge bosons in a four-particle contact interaction. The corresponding interaction Lagrangian is: Ldim. 7 = in which B and F i are the U(1)Y and SU(2)L eld tensors, and denotes the cuto scale. The coupling parameter c1 controls the relative importance of the U(1)Y and SU(2)L elds for DM production. Any multiplicative factor for the U (1)Y and SU (2)L couplings is absorbed into . Note that the choice of modi es the signal cross section, but not the expected kinematic properties of events. The model is nonrenormalizable and should be considered as a benchmark of the sensitivity to this class of interaction. It should be used with caution when making comparisons with other sources of DM constraints, such as direct detection experiments. Figure 1 shows the Feynman diagrams for production of DM pairs ( ) in association with a Z boson in these two types of models. The signature for DM production considered in this paper is the production of a pair of leptons (e+e ) consistent with a Z boson decay, together with a large missing transverse momentum. This same signature is sensitive to other models of physics beyond the SM (BSM), e.g. \unparticles"(U). The unparticle physics concept [21{24] is particularly interesting because it is based on scale invariance, which is anticipated in many BSM physics scenarios [25{27]. The e ects of the scale invariant sector (unparticles) appear as a noninteger number of invisible massless particles. In this scenario, the SM is extended by introducing a scale invariant Banks-Zaks (BZ) eld, which has a nontrivial infrared xed point [28]. This eld can interact with SM particles by exchanging heavy particles with a high mass scale MU. Below this mass scale, the coupling is nonrenormalizable and the interaction is suppressed by powers of MU. The ℓ− ℓ− ℓ− ) in association with a Z boson. Left: the simpli ed model containing a spin-1 mediator A. The constant gq (g ) is the coupling strength between A and quarks (DM). Right: an EFT benchmark with a DM pair coupling to gauge bosons via dimension-7 operators. with a Z boson. The hatched circle indicates the interaction modeled with an EFT operator. EFT Lagrangian can be expressed as: LU = CU OSMOU = in which CU is a normalization factor, dU represents the possible noninteger scaling dimension of the unparticle operator OU, OSM is an operator composed of SM dimension dSM, k = dSM + dBZ 4 > 0 is the scaling dimension, U is the energy scale of the interaction, and dBZ denotes the scaling dimension of the BZ operator at energy U. The parameter = CU U dBZ =MUk is a measure of the coupling between SM particles and unparticles. The scaling dimension dU 1 is constrained by the unitarity condition. Additional details regarding this unparticle model are available in ref. [17]. In this paper, real emission of scalar unparticles is considered. The unparticles are assumed to couple to the standard model quarks in an e ective three-particle interaction. level diagram for the production of unparticles associated with a Z boson. The analysis is based on a data set recorded with the CMS detector in 2015 in pp collisions at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity . A previous CMS search in the same nal state [17], based on data collected at a center-of-mass energy of 8 TeV, found no evidence of new physics and set limits on DM and unparticle production using an EFT description. A CMS analysis of channels [19] has previously set limits on the simpli ed model parameters considered here. Dark matter particle masses of up to 500 GeV (400 GeV) and mediator masses of up to A search performed by the ATLAS Collaboration using p s = 13 TeV data corresponding to an integrated luminosity of 3.2 fb 1 in events with a hadronically decaying V boson and ETmiss has recently reported exclusion of the dimension-7 EFT scenario up to (460 GeV) for DM particle masses of 1 GeV (1 TeV) [20]. 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 a silicon pixel and strip tracker, a lead tungstate crystal electromagnetic calorimeter (ECAL), and a brass and scintillator hadron calorimeter (HCAL), each composed of a barrel and two endcap sections. Forward calorimeters extend the pseudorapidity ( ) [30] 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. 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. [30]. Variables of particular relevance to the present analysis are the missing transverse momentum vector p~miss and the magnitude of this quantity, ETmiss. The quantity p~miss is T T de ned as the projection on the plane perpendicular to the beams of the negative vector sum of the momenta of all reconstructed particles in an event. Samples of simulated DM particle events for both the simpli ed model and EFT interpretations are generated using MadGraph5 amc@nlo 2.2.2 [31] at leading order (LO) and matched to pythia 8.205 [32] using tune CUETP8M1 for parton showering and hadronization [33, 34]. The factorization and renormalization scales are set to the geometric 2T + m2 for all nal-state particles [4, 31], where pT and m are the transverse momentum and mass of each particle. For the simpli ed model of DM production, couplings are chosen according to the recommendations in ref. [35]. The coupling g is set to unity. For gq, values of 1:0 and 0:25 are considered. The width of the mediator is assumed to be determined exclusively by the contributions from the couplings to quarks and the DM particle . Under this assumption, based on the ETmiss distribution at the generator level to the fully simulated samples with mediator width on the ETmiss distribution [35]. The exact dependence of the width on the model parameters is reported in [35]. /eG10−2 s imE1T0−3 10−50 50 100 150 200 250 300 350 400 450 500 10−50 100 200 300 400 500 600 700 800 9001000 c1 = 1 Mmed = 10 GeV Mmed = 200 GeV Mmed = 500 GeV MMmmeedd == 15000000 GGeeVV /eG10−2 s imE1T0−3 /eG10−2 s imE1T0−3 dU = 1.06 dU = 1.50 dU = 1.90 dU = 2.20 10−50 50 100 150 200 250 300 350 400 450 500 mediator (upper left), EFT DM model (upper right), and unparticle scenarios (lower panel). The y-axis corresponds to the integrated cross section per bin divided by the total cross section and bin width. The DM curves are shown for di erent values of the vector mediator mass Mmed in the upper left panel and for di erent values of the DM mass m in the upper right panel. The unparticle curves have the scalar unparticle coupling between unparticle and SM elds set to 1. They are shown for several values of the scaling dimension dU ranging from 1.06 to 2.20, spanning the region of sensitivity of this analysis. The SM background ZZ ! ` `+ histogram. The rightmost bins include over ow. is shown as a red solid Samples for the EFT DM benchmark are generated with = 3 TeV and c1 = 1. Signal predictions for other values of are obtained by rescaling the signal cross section accordingly, while other values of c1 are evaluated using the same reweighting method as for the simpli ed model case. The events for the unparticle model are generated at LO with pythia 8 [29, 36] assuming a cuto hadronization. We evaluate other values of U by rescaling the cross sections as needed. U acts solely as a scaling factor for the cross section and does not in uence the kinematic distributions of unparticle production [29]. The powheg 2.0 [37{41] event generator is used to produce samples of events for the tt, tW, qq ! ZZ, and WZ background processes, which are simulated at next-to-leading order (NLO). The gg ! ZZ process is simulated using mcfm 7.0.1 [42] at NLO. The Drell-Yan (DY, Z= ! `+` ) process is generated using the MadGraph5 amc@nlo event generator at LO and normalized to the next-to-next-to-leading order (NNLO) cross section as calculated using fewz 3.1 [43, 44]. Triboson events (WZZ, WWZ and ZZZ) are simulated using MadGraph5 amc@nlo at NLO. Samples of quantum chromodynamics (QCD) production of multijet events are generated using pythia 8 at LO. For all SM simulation samples, parton showering and hadronization are performed with pythia 8 with tune CUETP8M1. The parton distribution function (PDF) set NNPDF3.0 [45] is used for Monte Carlo (MC) samples, and the detector response is simulated using a detailed description of the SM background ZZ ! ` ` Event reconstruction CMS detector, based on the Geant4 package [46, 47]. Minimum bias events are superimposed on the simulated events to emulate the e ect of additional pp interactions in the same or nearby bunch crossings (pileup). All MC samples are corrected to reproduce the pileup distribution as measured in the data. The average number of pileup interactions per proton bunch crossing is about 12 for the 2015 data sample. The upper left panel of gure 3 shows the distribution of ETmiss at the generator level for DM particles with a mass of 50 GeV in the simpli ed model. The events generated with larger mediator mass Mmed tend to have a broader ETmiss distribution and reach further into the high-ETmiss regime. The analogous distributions in the EFT benchmark model with DM masses m In the unparticle scenario, the events generated with larger scaling dimension dU tend to preferentially populate the high-ETmiss regime, as shown in the lower panel of gure 3. The is shown in all plots for comparison, as a red solid histogram. Events are collected by requiring dilepton triggers (ee or ) with a threshold of pT > 17 GeV for the leading lepton. The threshold for the subleading lepton is pT > 12 (8) GeV for electrons (muons). Single-lepton triggers with thresholds of pT > 23 (20) GeV for electrons (muons) are also included to recover residual trigger ine ciencies. Prior to the selection of leptons, the primary vertex [48] with the largest value of P p2T for the associated tracks is selected as the event vertex. Simulation studies show that this requirement correctly selects the event vertex in more than 99% of both signal and background events. The lepton candidate tracks are required to be compatible with the event vertex. A particle- ow (PF) event algorithm [49, 50] reconstructs and identi es each individual particle with an optimized combination of information from the various elements of the CMS detector. Photon energies are directly obtained from the ECAL measurement, corrected for zero-suppression e ects [30]. Electron energies are determined from a combination of the electron momentum at the event vertex as determined by the tracker, the energy of the corresponding ECAL cluster, and the energy sum of all bremsstrahlung photons spatially compatible with originating from the electron track. Muon momenta are obtained from the curvature of the corresponding track. Charged hadron energies are determined from a combination of their momentum measured in the tracker and the matching ECAL and HCAL energy deposits, corrected for zero-suppression e ects and for the response function of the calorimeters to hadronic showers [50]. Finally, neutral hadron energies are obtained from the corresponding corrected ECAL and HCAL energies. Electron candidates are reconstructed using an algorithm that combines information from the ECAL and the tracker [51]. To reduce the electron misidenti cation rate, the candidates have to satisfy additional identi cation criteria that are based on the shape of the electromagnetic shower in the ECAL. In addition, the electron track is required to originate from the event vertex and to match the shower cluster in the ECAL. Electron candidates with an ECAL cluster in the transition region between ECAL barrel and endcap (1:44 < j j < 1:57) are rejected because the reconstruction of an electron candidate in this region is not optimal. Candidates that are identi ed as coming from photon conversions [51] in the detector material are explicitly removed. Muon candidate reconstruction is based on two algorithms: in the rst, tracks in the silicon tracker are matched with at least one muon segment in any detector plane of the muon system, and in the second algorithm, a combined t is performed to hits in both the silicon tracker and the muon system [52]. The muon candidates in this analysis are required to be reconstructed with at least one of the two algorithms and to be further identi ed as muons by the PF algorithm. To reduce the muon misidenti cation rate, additional identi cation criteria are applied based on the number of spatial points measured in the tracker and in the muon system, the t quality of the muon track, and its consistency with the event vertex location. Leptons produced in the decay of Z bosons are expected to be isolated from hadronic activity in the event. Therefore, an isolation requirement is applied based on the sum of the momenta of the PF candidates found in a cone of radius R = 0:4 around each lepton. The isolation sum is required to be smaller than 15% (20%) of the pT of the electron (muon). For each electron, the mean energy deposit in the isolation cone of the electron, coming from other pp collisions in the same bunch crossing, is estimated following the method described in ref. [51], and subtracted from the isolation sum. For muon candidates, only charged tracks associated with the event vertex are included. The sum of the pT for charged particles not associated with the event vertex in the cone of interest is rescaled by a factor of 0:5, corresponding to the average neutral to charged energy density ratio in jets, and subtracted from the isolation sum. For the purpose of rejecting events containing leptons, hadronically decaying tons ( h) are identi ed using the \hadron-plus-strips" algorithm. The algorithm identi es a jet as a h candidate if a subset of the particles assigned to the jet is consistent with the decay products of a h [53]. In addition, h candidates are required to be isolated from other activity in the event. Jets are reconstructed from PF candidates by using the anti-kT clustering algorithm [54] with a distance parameter of 0.4, as implemented in the FastJet package [55, 56]. Jets are identi ed over the full calorimeter acceptance, j j < 5. The jet momentum is de ned as the vector sum of all particle momenta assigned to the jet, and is found in simulation to be within 5 to 10% of the true hadron-level momentum over the whole pT range and detector acceptance. An overall energy subtraction is applied to correct for the extra energy clustered in jets due to pileup, following the procedure described in ref. [57]. Additional corrections to the jet energy scale and resolution are derived from simulation, and are complemented by measurements of the energy balance in dijet and +jets events [57]. Event selection A preselection with a large yield is used to validate the background model and is followed by a nal selection that is designed to give maximal sensitivity to the signal, as quanti ed by the expected limits achieved. Preselected events are required to have exactly two wellidenti ed, isolated leptons with the same avor and opposite charge (e+e with pT > 20 GeV. The invariant mass of the lepton pair is required to be within of the nominal mass of the Z boson [58]. Only electrons (muons) within the range of j j < 2:5 (2:4) are considered. To reduce the background from the WZ process where the W boson decays leptonically, events are removed if an additional electron or muon is reconstructed with pT > 10 GeV. The event is also removed from the nal selection if a h candidate is reconstructed with pT > 20 GeV. As a loose preselection requirement, the dilepton transverse momentum (p`T`) is required to be larger than 50 GeV to reject the bulk of DY background events. Since only a small amount of hadronic activity is expected in the nal state of both DM and unparticle events, any event having two or more jets with pT > 30 GeV is rejected. Processes involving top quarks are further suppressed with the use of techniques based on soft-muon and secondary-vertex b jet tagging, aimed at identifying the b quarks produced in top quark decays. Soft muons are identi ed using a specialised low-pT set of identi cation criteria focused on the muon candidate track quality. The rejection of events with soft muons having pT > 3 GeV reduces the background from semileptonic decays of B mesons. The b jet tagging technique employed is based on the \combined secondary vertex" algorithm [59, 60]. The algorithm is calibrated to provide, on average, 80% e ciency for tagging jets originating from b quarks, and 10% probability of light- avor jet misidenti cation. Events are rejected if at least one b-tagged jet is reconstructed with pT > 20 GeV within the tracker acceptance (j j < 2:5). nal selection, further kinematic requirements are set in order to achieve the best possible signal extraction. A minimal ETmiss of 80 GeV is required. The angle between the Z boson and the missing transverse momentum in the transverse plane required to be larger than 2:7 radians. The momentum balance of the event de ned by processes such as DY and top quark production. The event selection criteria used for the electron and muon channels are the same. They are summarized in table 1. Figure 4 shows the distributions of ETmiss after preselection in the ee and Background estimation The ZZ and WZ backgrounds are modeled using MC simulation, and normalized to their respective NLO cross sections. Other backgrounds, including tt, tW, WW, Z ! top quark, and DY production are estimated from data for the nal selection. 10−1 10−2 10−3 10−4 10−5 2.3 fb-1 (13 TeV) DM simpl. mod., vector, gq = gDM = 1 Unparticle, dU=1.5 DM simpl. mod., vector, gq = gDM = 1 2.3 fb-1 (13 TeV) Unparticle, dU=1.5 10−1 10−2 10−3 10−4 10−5 3rd-lepton veto Top quark veto p`T`j=p`T` Veto on b jets and soft muons (right) channels. Representative expected signal distributions are shown for the simpli ed model of DM production with vector couplings, the EFT scenario of DM production, and unparticles. The SM expectation is based on simulation only. The total statistical uncertainty in the overall background prediction is shown as a hatched region. Over ow events are included in the rightmost bins. The upper error bars on data points are shown for bins with zero entries (Garwood procedure) in the region up to the last non-zero entry. In the lower panels, the ratio between data and predicted background is shown. The simulation of the ZZ process includes the qq- and gg-induced production modes. In order to correct the ZZ di erential cross section from NLO to NNLO in QCD, dependent K-factors are applied [61]. We apply NLO electroweak (EW) K-factors as a function of the pT of the trailing boson, following the calculations in refs. [62{64]. Electroweak corrections to WZ production are also available, but considered small [64] and The background processes involving ee or pairs not directly resulting from the decay of a Z boson are referred to as nonresonant backgrounds. These backgrounds arise mainly from leptonic W boson decays in tt, tW, and WW events. There are also small contributions from the s- and t-channel single top quark events, W+jets events, and Z ! events in which lepton decays result in electrons or muons and ETmiss. We estimate these nonresonant backgrounds using a data control sample, consisting of events with oppositecharge di erent- avor dilepton pairs (e decay rates for Z ! e+e and Z ! ) that otherwise pass the full selection. As the are almost equal, by equating the ratio of observed dilepton counts to the square of the ratio of e ciencies, the nonresonant backgrounds in channels can be estimated from the e channel: Nbekstg;ee = Nedata, corr kee; kee = = Nedata, corr k ; k comes from the dilepton decay ratios for ee, , and e in these nonresonant backgrounds, and Nedeata and N data are the numbers of selected ee and events from data with masses in the Z boson mass window. The ratio ference between the electron and muon selection e ciencies. The term Nedata, corr is the number of e events observed in data corrected by subtracting the estimated ZZ, WZ, and DY background contributions. The kinematic distributions of the estimated nonresonant backgrounds are obtained from simulation with the overall normalization determined by the method described above. The validity of this procedure for predicting nonresonant backgrounds is checked with simulated events containing tt, tW, WW, W+jets, and processes. We assign a systematic uncertainty of 26% for this background estimation in both the electron and muon channels for ETmiss > 80 GeV, based on closure tests that compare the predictions obtained from the control sample with those from the The DY process is dominant in the region of low ETmiss. This process does not produce undetectable particles, and therefore the measured ETmiss arises from limited detector acceptance and mismeasurement of particle momenta. The estimation of this background uses simulated DY events, which are normalized to data with scale factors obtained by measuring the number of DY events in a background-dominated control region, after subtracting other processes. These scale factors are of order 1.0{1.2. The control region is de ned by applying the full selection with the ETmiss requirement inverted. The reliability of this approach in the high-ETmiss regime has been studied by considering variables sensitive to ETmiss mismeasurement, such as the angular separation between the ETmiss direction and any jet. A normalization uncertainty of 100%, which accommodates any di erences observed in these control regions, is assigned for the DY background estimate. The assigned uncertainty has little impact on the overall signal sensitivity because of the small overall contribution from the DY background prediction. Contributions from QCD production of multijet events is estimated using simulation and found to be negligible after nal selection. The e ciencies for selecting, reconstructing, and identifying isolated leptons are determined from simulation, and corrected with scale factors determined from applying a \tag-andprobe" technique [65] to Z ! `+` events in data. The trigger e ciencies for the electron and muon channels are found to be above 90%, varying as a function of pT and the lepton. The identi cation e ciency, when applying the selection criteria described in section 4, is found to be about 80{86% for electrons and 95% for muons, depending on the pT and of the corresponding lepton. The corresponding data-to-MC scale factors are typically in the range 0.96{1.00 for the electron and 0.96{0.98 for the muon channel, depending on the pT and j j of the lepton candidate. The lepton momentum scale uncertainty is computed by varying the momentum of the leptons by its uncertainties. The lepton momentum uncertainty is 1% for the muons, while the uncertainty for the electrons is 2% in the barrel and 5% in the endcaps. For both channels, the overall uncertainty in the e ciency of selecting and reconstructing leptons in an event is about 3%. In the treatment of systematic uncertainties, both normalization e ects, which only a ect the overall size of individual contributions, as well as shape uncertainties, which also a ect their distribution, are taken into account. The systematic uncertainties are summarized in table 2. Where applicable, the symbol V is used to refer to both Z and W bosons. The impact of each source of uncertainty on the observed strength of a potential signal is also reported. The signal strength is de ned as the ratio of the observed or excluded signal cross-section to the signal cross-section predicted by theory. To calculate the impact, a maximum likelihood t of the combined background and signal model to the expected distribution for unity signal strength is performed. The t is repeated with each individual nuisance parameter varied by its uncertainty. The impact of the uncertainty is then de ned as the relative change induced in the expected best t signal strength by the variation of the respective parameter. In the table, the reference signal is the simpli ed model DM scenario with a vector mediator of mass 200 GeV, a DM particle mass of 50 GeV, and coupling gq = 1:0. The normalization uncertainties in the background estimates from data have been described in section 6. The PDF and S uncertainties (referred to as PDF+ S in the following) for signal and background processes are estimated from the standard deviation (s.d.) of weights according to the replicas provided in the NNPDF3.0 parton distribution While the in uence on the estimated signal acceptance arising from theoryrelated uncertainties is included in the limit calculation, the corresponding e ect on the normalization of the signal process is not. For the simpli ed model of DM production, the e ect of the signal normalization uncertainty is treated separately from the experimental uncertainty and is shown as a dashed band around the observed limit. Since the EFT benchmark and unparticle scenarios are extremely simpli ed, theory-related cross-section uncertainties are not considered to be realistic for these models and are thus neglected. The e ciencies for signal, ZZ, and WZ processes are estimated using simulation, and the uncertainties in the corresponding yields are derived by varying the renormalization and factorization scales, S, and choice of PDFs. The factorization and renormalization scale Source of uncertainty Integrated luminosity Lepton trigger & identi cation e ciency Lepton momentum scale, resolution Jet energy scale, resolution b jet tagging e ciency Factorization, renormalization scales (signal) Factorization, renormalization scales (VV) Factorization, renormalization scales (VVV) EW correction for qq ! ZZ EW uncertainty for WZ tt, tW, WW normalization MC sample size (signal) MC sample size (ZZ, WZ) MC sample size (DY) MC sample size (tt, tW, WW) uncertainty (%) uncertainty (%) ation of the relative yields of the particular background components. The signal uncertainties represent the relative variations in the signal acceptance, and the ranges quoted cover both signals of DM and unparticles with di erent DM masses or scaling dimensions. For shape uncertainties, the numbers correspond to the overall e ect of the shape variation on the yield or acceptance. The symbol \|" indicates that the systematic uncertainty is not applicable. The impact of each group of systematic uncertainties is calculated by performing a maximum likelihood the signal strength with each parameter separately varied by its uncertainty. The number given in the impact column is the relative change of the expected best t signal strength that is introduced by the variation for the simpli ed model signal scenario with a vector mediator of mass 200 GeV, DM of mass 50 GeV, and coupling gq = 1:0. uncertainties are assessed by varying the original scales by factors of 0.5 or 2.0, and amount to 2{3% for ZZ and WZ processes. The e ect of variations in S and choice of PDFs is 2% for the ZZ and WZ backgrounds. A 3% normalization uncertainty is assigned to the WZ background to account for higher-order EW corrections [64]. The uncertainty assigned to the integrated luminosity measurement is 2.7% [67]. Experimental sources of shape uncertainty are the lepton momentum scale, the jet energy scale and resolution, the b tagging e ciency, and the pileup modeling. The effect of each uncertainty is estimated by varying the respective variable of interest by its uncertainties, and propagating the variations to the distribution of ETmiss after the nal selection. In the case of the lepton momentum scale, the uncertainty is computed by varying the momentum of the leptons by their uncertainties. The uncertainty due to the lepton momentum scale is evaluated to be less than 1% (1{7%) for signal (background). The uncertainties in the calibration of the jet energy scale and resolution directly a ect the assignments of jets to jet categories, the ETmiss computation, and all the selections related to jets. The e ect of the jet energy scale uncertainty is estimated by varying the energy scale by 1 s.d. A similar strategy is used to evaluate the systematic uncertainty related to the jet energy resolution. The e ect of the shifts is propagated to ETmiss. The uncertainties in the nal yields are found to be less than 1% for signal and less than 4% In order to reproduce b tagging e ciencies observed in data, an event-by-event reweighting using data-to-simulation scale factors is applied to simulated events. The uncertainty associated with this procedure is obtained by varying the event-by-event weight 1 s.d. The total uncertainty in the nal yields due to b tagging is less than 1% for both signal and background. All simulated events are reweighted to reproduce the pileup conditions observed in data. To compute the uncertainty related to pileup modeling, we shift the mean of the distribution in simulation by 5% [68]. The variation of the nal yields induced by this procedure is 0.5{1% for signal and 1{2% for background. For the processes estimated from simulation, the sizes of the MC samples limit the precision of the modeling, and the resulting statistical uncertainty is incorporated into the shape uncertainty. A similar treatment is applied to the backgrounds estimated from control samples in data, based on the statistical uncertainties in the corresponding control samples. For both the electron and the muon channels, a shape-based analysis is employed. The expected numbers of background and signal events scaled by a signal strength modi er are combined in a binned likelihood for each bin of the ETmiss distribution. The numbers of observed and expected events are shown in table 3, which also includes the expectation for a selected parameter point for each type of signal. Figure 5 shows the ETmiss distributions after the nal selection. The observed distributions agree with the SM background predictions and no excess of events is observed. Upper limits on the contribution of events from new physics are computed by using the modi ed frequentist approach CLs [69{71]. The DM interpretation The results are interpreted in the context of a simpli ed model of DM production. Figure 6 shows 95% con dence level (CL) expected and observed limits on the signal strength production of DM particles via an on-shell mediator (2m to mediator masses of 400 GeV for gq = 1:0 and up to < Mmed) can be excluded up 300 GeV for gq = 0:25. Dark matter particle masses are probed up to 100{150 GeV for vector and up to 50{100 GeV for Simpli ed DM model, vector mediator = 50 GeV, Mmed = 200 GeV Simpli ed DM model, axial-vector mediator EFT DM model = 50 GeV, Mmed = 200 GeV = 1 GeV, Unparticle model dU = 1:05, U = 15 TeV tt/tW/WW/Z ! VVV, ZZ ! 2`2q; 4` The DM signal yields from the simpli ed model are given for mass m = 50 GeV and a mediator benchmark with DM pair coupling to gauge bosons, the signal yields are given for m = 1 GeV, for scaling dimension dU = 1:05, and cuto systematic uncertainties are shown, in that order. = 15 TeV. The corresponding statistical and The simpli ed model allows a calculation of the DM relic abundance in the universe for each parameter point [72, 73]. Parameter combinations consistent with measurements of the DM relic abundance in the universe are indicated in gure 6. For these parameter combinations, no BSM phenomena other than the simpli ed model are needed to account for the relic abundance in the universe. For other parameter values, additional phenomena, such as an extended dark sector, are necessary. The exclusion limits in the Mmed-m plane are translated into limits on the DM-nucleon scattering cross section using the prescription of ref. [35]. The limits are set at 90% CL, and spin-dependent (axial-vector) cases are shown in gure 7, which compares them to the results from direct detection experiments. The comparison of collider and direct detection experiments highlights the complementarity of the two approaches. Especially in the case of lower DM masses and axial-vector couplings, a collider-based search can exclude parameter space not covered by direct detection experiments. In all cases, the DM-mediator coupling g is set to one. Figure 8 shows 95% CL expected limits on the cuto scale of the EFT benchmark model with DM pair coupling to gauge bosons. The limits are derived as a function of DM simpl. mod., vector, gq = gDM = 1 Unparticle, dU=1.5 DM simpl. mod., vector, gq = gDM = 1 Unparticle, dU=1.5 Figure 5. Distributions of ETmiss for the nal selection in the e+e (left) and + nels. Expected signal distributions are shown for the simpli ed model of DM production with vector couplings, the EFT DM production benchmark, and unparticle model. The total uncer sys.) in the overall background is shown as a hatched region. Over ow events are included in the rightmost bins. In the lower panels, the ratio between data and predicted background is shown. the DM particle mass. At low masses, cuto scales up to 480 GeV can be excluded. With increasing DM particle mass, sensitivity decreases with < 250 GeV excluded for and signal strength obs= th as a function of coupling c1 and DM mass m are shown in gure 9. At c1 the interaction is dominated by the ZZ -vertex. With increasing c1, the Z begins to contribute, yielding an improvement in the sensitivity. Unparticle interpretation In the unparticle scenario, 95% CL lower limits are set on the e ective cuto scale = 1 is assumed. The limits on U are shown in gure 10 as a function of the scaling dimension dU. The result is compared with the limits obtained from previous CMS searches in the monojet [15] and mono-Z [17] channels, as well as with a reinterpretation of LEP searches [83]. Comparable sensitivity to the previous CMS mono-Z search is achieved owing to the increase in collision energy, which o sets the larger size of the previous dataset. Model-independent limits As an alternative to the interpretation of the results in speci c models, a simple counting experiment is performed to obtain model-independent expected and observed 95% CL upper limits on the visible cross section vis BSM = A for BSM physics processes, where A is the acceptance and is the identi cation e ciency for a hypothetical signal. The limits as a function of ETmiss thresholds are shown in gure 11. Table 4 shows the total SM background predictions for the numbers of events passing the selection requirements, for di erent ETmiss thresholds, compared with the observed numbers of events. The 95% CL expected and observed upper limits for the contribution of events from BSM sources are also shown. Since Expected 100 200 300 400 500 600 700 800 9001000 10−1 100 200 300 400 500 600 700 800 9001000 10−1 Expected Observed Expected Expected 100 200 300 400 500 600 700 800 9001000 10−1 100 200 300 400 500 600 700 800 9001000 10−1 obs= theo in both vector (left) (upper) and 1 (lower). In all cases, the DM-mediator coupling g is set to one. The expected exclusion curves for unity signal strength are shown as a reference, with black dashed lines indicating 1 s.d. interval due to experimental uncertainties. The red dashed lines show the in uence of theory-related signal normalization uncertainties on the observed limits, which are estimated to be 15%. The solid line labeled \ c h2 = 0:12" identi es the parameter region where no additional new physics beyond the simpli ed model is necessary to reproduce the observed DM relic abundance in the universe [1, 35, 72{74]. the e ciency of reconstructing potential signal events depends on the characteristics of the signal, the model-independent limits are not corrected for the e ciency. For the models considered in this analysis, typical e ciencies are in the range 50{70% (simpli ed DM model), 60{70% (EFT DM model), and 55{60% (unparticle model). The e ciencies are calculated as the ratio of the number of simulated events passing the nal selection to the number of simulated events passing the selection criteria at the generator level (acceptance). Summary A search for physics beyond the standard model has been performed in events with a Z boson and missing transverse momentum, using a data set corresponding to an integrated luminosity of 2.3 fb 1 of pp collisions at a center-of-mass energy of 13 TeV. The observed { 16 { [c10−37 n10−38 e10−40 s10−42 n10−44 c10−46 10−48 10−50 DM10−49 Spin-independent D10−42 Spin-dependent independent (left) and spin-dependent (right) cases, assuming a mediator-quark coupling constant gq = 0:25 and mediator-DM coupling constant g = 1. The line shading indicates the excluded region. Limits from the LUX [75], CDMSLite [76], PandaX-II [77], and CRESST-II [78] experiments are shown for the spin-independent case. Limits from the Super-Kamiokande [79], PICO-2L [80], PICO-60 [81], and IceCube [82] experiments are shown for the spin-dependent case. 2.3 fb-1 (13 TeV) no10−40 Expected ± 1 s.d. Expected ± 2 s.d. c1 = 1 200 400 600 800 1000 1200 of the EFT benchmark of DM production as a function of DM particle mass m . data are consistent with the expected standard model processes. The results are analyzed to obtain limits in three di erent scenarios of physics beyond the standard model. In a simpli ed model of DM production via a vector or axial vector mediator, 95% con dence level limits are obtained on the masses of the DM particles and the mediator. Limits on the DM-nucleon scattering cross section are set at 90% con dence level in spin-dependent and spin-independent coupling scenarios. In an e ective eld theory approach, limits are set on the DM coupling parameters to U(1) and SU(2) gauge elds and on the scale of new (left) and signal strength obs= th (right) as a function of coupling c1 and DM mass m . The expected exclusion curves for unit signal strength are shown as a reference. The gray shaded area bounded by gray dashed lines indicates 1 s.d. interval due to experimental uncertainties. 450 i t 2.3 fb-1 (13 TeV) Observed Expected Expected ± 1 s.d. Expected ± 2 s.d. CMS monojet (8 TeV) CMS mono-Z (8 TeV) 1.2 1.4 1.6 1.8 2 2.2 2.4 2.6 2.8 Scaling dimension d U for a xed coupling of LEP searches [83] are shown for comparison. physics. For an unparticle model, 95% con dence level limits are obtained on the e ective cuto scale as a function of the scaling dimension. In addition, model-independent limits on the contribution to the visible Z + ETmiss cross section from non-standard-model sources are presented as a function of the minimum requirement on ETmiss. These results are the rst limits on unparticle production are the rst of their kind to be presented at p in this signal topology to be interpreted in terms of a simpli ed model. Furthermore, the s = 13 TeV. We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative sta s at CERN and = 14 2.3 fb-1 (13 TeV) 60 80 100 120 140 160 180 200 220 Emiss threshold [GeV] for BSM production of events, as a function of ETmiss threshold. The values plotted correspond to those given in table 4. ETmiss threshold [GeV] Total SM background Observed upper limit Expected upper limit +2 s.d. Expected upper limit +1 s.d. Expected upper limit Expected upper limit Expected upper limit quirements, for di erent ETmiss thresholds, compared with the observed numbers of events. The listed uncertainties include both statistical and systematic components. The 95% CL observed and expected upper limits for the contribution of events from BSM sources are also shown. In addition, 2 s.d. excursions from expected limits are given. at other CMS institutes for their contributions to the success of the CMS e ort. 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Vanlaer, D. Vannerom, R. Yonamine, F. Zenoni, F. Zhang2 Ghent University, Ghent, Belgium A. Cimmino, T. Cornelis, D. Dobur, A. Fagot, M. Gul, I. Khvastunov, D. Poyraz, S. Salva, R. Schofbeck, M. Tytgat, W. Van Driessche, E. Yazgan, N. Zaganidis Universite Catholique de Louvain, Louvain-la-Neuve, Belgium H. Bakhshiansohi, C. Belu 3, 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, C. Nuttens, K. Piotrzkowski, L. Quertenmont, M. Selvaggi, M. Vidal Marono, S. Wertz 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, C. Hensel, A. Moraes, M.E. Pol, P. Rebello Teles Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil G.G. Da Silveira5, D. De Jesus Damiao, C. De Oliveira Martins, S. Fonseca De Souza, L.M. Huertas Guativa, H. 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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, J.P. Gomez, C.F. Gonzalez Hernandez, J.D. Ruiz Alvarez, J.C. Sanabria University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Split, Croatia 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, S. Micanovic, L. Sudic, T. Susa University of Cyprus, Nicosia, Cyprus A. Attikis, G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos, P.A. Razis, H. Rykaczewski, D. Tsiakkouri Charles University, Prague, Czech Republic M. Finger8, M. Finger Jr.8 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 A.A. Abdelalim9;10, A. Mohamed10, A. Mohamed11 National Institute of Chemical Physics and Biophysics, Tallinn, Estonia 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, J. Tuominiemi, E. Tuovinen, L. Wendland Lappeenranta University of Technology, Lappeenranta, Finland J. Talvitie, T. Tuuva IRFU, CEA, Universite Paris-Saclay, Gif-sur-Yvette, France M. Besancon, F. Couderc, M. Dejardin, D. Denegri, B. Fabbro, J.L. Faure, C. Favaro, F. Ferri, S. Ganjour, S. Ghosh, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry, I. Kucher, E. Locci, M. Machet, J. Malcles, J. 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Tsamalaidze8 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, M. Brodski, E. Dietz-Laursonn, D. Duchardt, M. Endres, M. Erdmann, S. Erdweg, T. Esch, R. Fischer, A. Guth, M. Hamer, T. Hebbeker, C. Heidemann, K. Hoepfner, S. Knutzen, M. Merschmeyer, A. Meyer, P. Millet, S. Mukherjee, M. Olschewski, K. Padeken, T. Pook, M. Radziej, H. Reithler, M. Rieger, F. Scheuch, L. Sonnenschein, D. Teyssier, S. Thuer RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany V. Cherepanov, G. Flugge, B. Kargoll, T. Kress, A. Kunsken, J. Lingemann, T. Muller, A. Nehrkorn, A. Nowack, C. Pistone, O. Pooth, A. Stahl15 Deutsches Elektronen-Synchrotron, Hamburg, Germany M. Aldaya Martin, T. Arndt, C. Asawatangtrakuldee, K. 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Marconi, M. Meyer, M. Niedziela, D. Nowatschin, F. Pantaleo15, T. Pei er, A. Perieanu, J. Poehlsen, C. Sander, C. Scharf, P. Schleper, A. Schmidt, S. Schumann, J. Schwandt, H. Stadie, G. Steinbruck, F.M. Stober, M. Stover, H. Tholen, D. Troendle, E. Usai, L. Vanelderen, A. Vanhoefer, B. Vormwald Institut fur Experimentelle Kernphysik, Karlsruhe, Germany M. Akbiyik, C. Barth, S. Baur, C. Baus, J. Berger, E. Butz, R. Caspart, T. Chwalek, F. Colombo, W. De Boer, A. Dierlamm, S. Fink, B. Freund, R. Friese, M. Gi els, A. Gilbert, Paraskevi, Greece I. Topsis-Giotis S. Kudella, H. Mildner, M.U. Mozer, Th. Muller, M. Plagge, G. Quast, K. Rabbertz, S. Rocker, F. Roscher, 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, E. Tziaferi University of Ioannina, Ioannina, Greece I. Evangelou, G. Flouris, C. Foudas, P. Kokkas, N. Loukas, N. Manthos, I. Papadopoulos, E. Paradas MTA-ELTE Lendulet CMS Particle and Nuclear Physics Group, Eotvos Lorand University, Budapest, Hungary Wigner Research Centre for Physics, Budapest, Hungary G. Bencze, C. Hajdu, D. Horvath19, F. Sikler, V. Veszpremi, G. Vesztergombi20, A.J. ZsigInstitute of Nuclear Research ATOMKI, Debrecen, Hungary N. Beni, S. Czellar, J. Karancsi21, A. Makovec, J. Molnar, Z. Szillasi Institute of Physics, University of Debrecen M. Bartok20, P. Raics, Z.L. Trocsanyi, B. Ujvari National Institute of Science Education and Research, Bhubaneswar, India S. Bahinipati, S. Choudhury22, P. Mal, K. Mandal, A. Nayak23, D.K. Sahoo, N. Sahoo, Panjab University, Chandigarh, India S. Bansal, S.B. Beri, V. Bhatnagar, R. Chawla, U.Bhawandeep, A.K. Kalsi, A. Kaur, M. Kaur, R. Kumar, P. Kumari, A. Mehta, M. Mittal, J.B. Singh, G. Walia University of Delhi, Delhi, India Ashok Kumar, A. Bhardwaj, B.C. Choudhary, R.B. Garg, S. Keshri, S. Malhotra, M. Naimuddin, N. Nishu, K. Ranjan, R. Sharma, V. Sharma Saha Institute of Nuclear Physics, Kolkata, India R. Bhattacharya, S. Bhattacharya, K. Chatterjee, S. Dey, S. Dutt, S. Dutta, S. Ghosh, N. Majumdar, A. Modak, K. Mondal, S. Mukhopadhyay, S. Nandan, A. Purohit, A. Roy, D. Roy, S. Roy Chowdhury, S. Sarkar, M. Sharan, S. Thakur Indian Institute of Technology Madras, Madras, India Bhabha Atomic Research Centre, Mumbai, India R. Chudasama, D. Dutta, V. Jha, V. Kumar, A.K. Mohanty15, P.K. Netrakanti, L.M. Pant, P. Shukla, A. Topkar Tata Institute of Fundamental Research-A, Mumbai, India T. Aziz, S. Dugad, G. Kole, B. Mahakud, S. Mitra, G.B. Mohanty, B. Parida, N. Sur, Tata Institute of Fundamental Research-B, Mumbai, India S. Banerjee, S. Bhowmik24, R.K. Dewanjee, S. Ganguly, M. Guchait, Sa. Jain, S. Kumar, M. Maity24, G. Majumder, K. Mazumdar, T. Sarkar24, N. Wickramage25 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. Chenarani26, E. Eskandari Tadavani, S.M. Etesami26, M. Khakzad, M. Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi27, F. Rezaei Hosseinabadi, B. Safarzadeh28, University College Dublin, Dublin, Ireland M. Felcini, M. Grunewald INFN Sezione di Bari a, Universita di Bari b, Politecnico di Bari c, Bari, Italy M. Abbresciaa;b, C. Calabriaa;b, C. Caputoa;b, A. Colaleoa, D. Creanzaa;c, L. Cristellaa;b, N. De Filippisa;c, M. De Palmaa;b, L. Fiorea, G. Iasellia;c, G. Maggia;c, M. Maggia, G. Minielloa;b, S. Mya;b, S. Nuzzoa;b, A. Pompilia;b, G. Pugliesea;c, R. Radognaa;b, A. Ranieria, G. Selvaggia;b, A. Sharmaa, L. Silvestrisa;15, R. Vendittia;b, P. 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Benatoa;b, D. Biselloa;b, A. Bolettia;b, R. Carlina;b, P. Checchiaa, M. Dall'Ossoa;b, P. De Castro Manzanoa, T. Dorigoa, U. Gasparinia;b, A. Gozzelinoa, Gulminia;29, S. Lacapraraa, M. Margonia;b, Marona;29, A.T. Meneguzzoa;b, J. Pazzinia;b, N. Pozzobona;b, P. Ronchesea;b, F. Simonettoa;b, E. Torassaa, S. Venturaa, M. Zanettia;b, P. Zottoa;b, G. Zumerlea;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, C. Riccardia;b, P. Salvinia, I. Vaia;b, P. Vituloa;b INFN Sezione di Perugia a, Universita di Perugia b, Perugia, Italy L. Alunni Solestizia;b, G.M. Bileia, D. Ciangottinia;b, L. Fanoa;b, P. Laricciaa;b, R. Leonardia;b, G. Mantovania;b, M. Menichellia, A. Sahaa, A. Santocchiaa;b INFN Sezione di Pisa a, Universita di Pisa b, Scuola Normale Superiore di Pisa c, Pisa, Italy K. Androsova;30, P. Azzurria;15, G. Bagliesia, J. Bernardinia, T. Boccalia, R. Castaldia, M.A. Cioccia;30, R. Dell'Orsoa, S. Donatoa;c, G. Fedi, A. Giassia, M.T. Grippoa;30, F. Ligabuea;c, T. Lomtadzea, L. Martinia;b, A. Messineoa;b, F. Pallaa, A. Rizzia;b, A. SavoyNavarroa;31, P. Spagnoloa, R. Tenchinia, G. Tonellia;b, A. Venturia, P.G. Verdinia INFN Sezione di Roma a, Universita di Roma b, Roma, Italy L. Baronea;b, F. Cavallaria, M. Cipriania;b, D. Del Rea;b;15, M. Diemoza, S. Gellia;b, E. Longoa;b, F. Margarolia;b, Marzocchia;b, Meridiania, G. Organtinia;b, R. Paramattia, F. Preiatoa;b, S. Rahatloua;b, C. Rovellia, F. Santanastasioa;b INFN Sezione di Torino a, Universita di Torino b, Torino, Italy, Universita del Piemonte Orientale c, Novara, Italy N. Amapanea;b, R. Arcidiaconoa;c;15, S. Argiroa;b, M. Arneodoa;c, N. Bartosika, R. Bellana;b, C. Biinoa, N. Cartigliaa, F. Cennaa;b, M. Costaa;b, R. Covarellia;b, A. Deganoa;b, N. Demariaa, L. Fincoa;b, B. Kiania;b, C. Mariottia, S. Masellia, Kwangju, Korea E. Migliorea;b, V. Monacoa;b, E. Monteila;b, M. Montenoa, M.M. Obertinoa;b, L. Pachera;b, N. Pastronea, M. Pelliccionia, G.L. Pinna Angionia;b, F. Raveraa;b, A. Romeroa;b, M. Ruspaa;c, R. Sacchia;b, K. Shchelinaa;b, V. Solaa, A. Solanoa;b, A. Staianoa, P. Traczyka;b INFN Sezione di 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, S. Lee, S.W. Lee, Y.D. Oh, S. Sekmen, D.C. Son, Chonbuk National University, Jeonju, Korea Chonnam National University, Institute for Universe and Elementary Particles, Hanyang University, Seoul, Korea J.A. Brochero Cifuentes, T.J. Kim Korea University, Seoul, Korea J. Lim, S.K. Park, Y. Roh Seoul National University, Seoul, Korea University of Seoul, Seoul, Korea M. Choi, H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park, G. Ryu, M.S. Ryu Sungkyunkwan University, Suwon, Korea Y. Choi, J. Goh, C. Hwang, J. Lee, I. Yu Vilnius University, Vilnius, Lithuania V. Dudenas, A. Juodagalvis, J. Vaitkus National Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Malaysia I. Ahmed, Z.A. Ibrahim, J.R. Komaragiri, M.A.B. Md Ali32, F. Mohamad Idris33, W.A.T. Wan Abdullah, M.N. Yusli, Z. Zolkapli Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico H. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-De La Cruz34, A. Hernandez-Almada, R. Lopez-Fernandez, R. Magan~a Villalba, J. Mejia Guisao, A. Sanchez-Hernandez Universidad Iberoamericana, Mexico City, Mexico S. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia Benemerita Universidad Autonoma de Puebla, Puebla, Mexico S. Carpinteyro, I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad Autonoma de San Luis Potos , San Luis Potos , Mexico A. Morelos Pineda University of Auckland, Auckland, New Zealand University of Canterbury, Christchurch, New Zealand National Centre for Physics, Quaid-I-Azam University, Islamabad, Pakistan A. Ahmad, M. Ahmad, Q. Hassan, H.R. Hoorani, W.A. Khan, A. Saddique, M.A. Shah, M. Shoaib, M. Waqas National Centre for Nuclear Research, Swierk, Poland H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Gorski, M. Kazana, K. Nawrocki, K. Romanowska-Rybinska, M. Szleper, P. Zalewski Institute of Experimental Physics, Faculty of Physics, University of Warsaw, K. Bunkowski, A. Byszuk35, K. Doroba, A. Kalinowski, M. Konecki, J. Krolikowski, M. Misiura, M. Olszewski, M. Walczak Laboratorio de Instrumentac~ao e F sica Experimental de Part culas, Lisboa, Joint Institute for Nuclear Research, Dubna, Russia N. Skatchkov, V. Smirnov, N. Voytishin, A. Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia L. Chtchipounov, V. Golovtsov, Y. Ivanov, V. Kim38, E. Kuznetsova39, V. Murzin, V. Oreshkin, V. Sulimov, A. Vorobyev Institute for Nuclear Research, Moscow, Russia Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov, N. Krasnikov, A. Pashenkov, D. Tlisov, A. Toropin Institute for Theoretical and Experimental Physics, Moscow, Russia V. Epshteyn, V. Gavrilov, N. Lychkovskaya, V. Popov, I. Pozdnyakov, G. Safronov, A. Spiridonov, M. Toms, E. Vlasov, A. Zhokin Moscow Institute of Physics and Technology, Moscow, Russia A. Bylinkin37 National Research Nuclear University 'Moscow Engineering Physics Institute' (MEPhI), Moscow, Russia M. Chadeeva40, O. Markin, V. Rusinov P.N. Lebedev Physical Institute, Moscow, Russia V. Andreev, M. Azarkin37, I. Dremin37, M. Kirakosyan, A. Leonidov37, A. Terkulov Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia A. Baskakov, A. Belyaev, E. Boos, M. Dubinin41, L. Dudko, A. Ershov, A. Gribushin, V. Klyukhin, O. Kodolova, I. Lokhtin, I. Miagkov, S. Obraztsov, S. Petrushanko, V. Savrin, Novosibirsk State University (NSU), Novosibirsk, Russia V. Blinov42, Y.Skovpen42, D. Shtol42 State Research Center of Russian Federation, Institute for High Energy Physics, Protvino, Russia I. Azhgirey, I. Bayshev, S. Bitioukov, D. Elumakhov, V. Kachanov, A. Kalinin, D. Konstantinov, V. Krychkine, V. Petrov, R. Ryutin, A. Sobol, S. Troshin, N. Tyurin, A. Uzunian, University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia P. Adzic43, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic, V. Rekovic nologicas (CIEMAT), Madrid, Spain J. Alcaraz Maestre, M. Barrio Luna, E. Calvo, M. Cerrada, M. Chamizo Llatas, N. Colino, B. De La Cruz, A. Delgado Peris, A. Escalante Del Valle, C. Fernandez Bedoya, J.P. Fernandez Ramos, J. Flix, M.C. Fouz, P. Garcia-Abia, O. Gonzalez Lopez, S. Goy Lopez, J.M. Hernandez, M.I. Josa, E. Navarro De Martino, A. Perez-Calero Yzquierdo, J. Puerta Pelayo, A. Quintario Olmeda, I. Redondo, L. Romero, M.S. Soares Universidad Autonoma de Madrid, Madrid, Spain J.F. de Troconiz, M. Missiroli, D. Moran Universidad de Oviedo, Oviedo, Spain J. Cuevas, J. Fernandez Menendez, I. Gonzalez Caballero, J.R. Gonzalez Fernandez, E. Palencia Cortezon, S. Sanchez Cruz, I. Suarez Andres, J.M. Vizan Garcia Instituto de F sica de Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, Spain I.J. Cabrillo, A. Calderon, J.R. Castin~eiras De Saa, E. Curras, M. Fernandez, J. GarciaFerrero, G. Gomez, A. Lopez Virto, J. Marco, C. Martinez Rivero, F. Matorras, J. Piedra Gomez, T. Rodrigo, A. Ruiz-Jimeno, L. Scodellaro, N. Trevisani, I. Vila, R. Vilar CERN, European Organization for Nuclear Research, Geneva, Switzerland Paul Scherrer Institut, Villigen, Switzerland W. Bertl, K. Deiters, W. Erdmann, R. Horisberger, Q. Ingram, H.C. Kaestli, D. Kotlinski, U. Langenegger, T. Rohe Institute for Particle Physics, ETH Zurich, Zurich, Switzerland F. Bachmair, L. Bani, L. Bianchini, B. Casal, G. Dissertori, M. Dittmar, M. Donega, C. Grab, C. Heidegger, D. Hits, J. Hoss, G. Kasieczka, P. Lecomtey, W. Lustermann, B. Mangano, M. Marionneau, P. Martinez Ruiz del Arbol, M. Masciovecchio, M.T. Meinhard, D. Meister, F. Micheli, P. Musella, F. Nessi-Tedaldi, F. Pandol , J. Pata, F. Pauss, G. Perrin, L. Perrozzi, M. Quittnat, M. Rossini, M. Schonenberger, A. Starodumov49, V.R. Tavolaro, K. Theo latos, R. Wallny Universitat Zurich, Zurich, Switzerland T.K. Aarrestad, C. Amsler50, L. Caminada, M.F. Canelli, A. De Cosa, C. Galloni, A. Hinzmann, T. Hreus, B. Kilminster, J. Ngadiuba, D. Pinna, G. Rauco, P. Robmann, D. Salerno, Y. Yang, A. Zucchetta National Central University, Chung-Li, Taiwan V. Candelise, T.H. Doan, Sh. Jain, R. Khurana, M. Konyushikhin, C.M. Kuo, W. Lin, Y.J. Lu, A. Pozdnyakov, S.S. Yu National Taiwan University (NTU), Taipei, Taiwan Arun Kumar, P. Chang, Y.H. Chang, Y. 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, B. Asavapibhop, G. Singh, N. Srimanobhas, N. Suwonjandee Cukurova University - Physics Department, Science and Art Faculty A. Adiguzel, M.N. Bakirci51, S. Cerci52, S. Damarseckin, Z.S. Demiroglu, C. Dozen, 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, S. Bilmis, B. Isildak57, G. Karapinar58, M. Yalvac, M. Zeyrek Bogazici University, Istanbul, Turkey E. Gulmez, M. Kaya59, O. Kaya60, E.A. Yetkin61, T. Yetkin62 Istanbul Technical University, Istanbul, Turkey A. Cakir, K. Cankocak, S. Sen63 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, H. Flacher, J. Goldstein, M. Grimes, G.P. Heath, H.F. Heath, J. Jacob, L. Kreczko, C. Lucas, D.M. Newbold64, S. Paramesvaran, A. Poll, T. Sakuma, S. Seif El Nasr-storey, D. Smith, Rutherford Appleton Laboratory, Didcot, United Kingdom K.W. Bell, A. Belyaev65, 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 Imperial College, London, United Kingdom M. Baber, R. Bainbridge, O. Buchmuller, A. Bundock, D. Burton, S. Casasso, M. Citron, D. Colling, L. Corpe, P. Dauncey, G. Davies, A. De Wit, M. Della Negra, R. Di Maria, P. Dunne, A. Elwood, D. Futyan, Y. Haddad, G. Hall, G. Iles, T. James, R. Lane, C. Laner, R. Lucas64, L. Lyons, A.-M. Magnan, S. Malik, L. Mastrolorenzo, J. Nash, A. Nikitenko49, J. Pela, B. Penning, M. Pesaresi, D.M. Raymond, A. Richards, A. Rose, C. Seez, S. Summers, A. Tapper, K. Uchida, M. Vazquez Acosta66, T. Virdee15, J. Wright, Brunel University, Uxbridge, United Kingdom J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, D. Leslie, I.D. Reid, P. Symonds, L. Teodorescu, M. Turner Baylor University, Waco, U.S.A. A. Borzou, K. Call, J. Dittmann, K. Hatakeyama, H. Liu, N. Pastika S.I. Cooper, C. Henderson, P. Rumerio, C. West Boston University, Boston, U.S.A. Brown University, Providence, U.S.A. G. Benelli, D. Cutts, A. Garabedian, J. Hakala, U. Heintz, J.M. Hogan, O. Jesus, K.H.M. Kwok, E. Laird, G. Landsberg, Z. Mao, M. Narain, S. Piperov, S. Sagir, E. Spencer, University of California, Davis, Davis, U.S.A. R. Breedon, D. Burns, M. Calderon De La Barca Sanchez, S. Chauhan, M. Chertok, J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk, M. Gardner, W. Ko, R. Lander, C. Mclean, M. Mulhearn, D. Pellett, J. Pilot, S. Shalhout, J. Smith, M. Squires, D. Stolp, M. Tripathi University of California, Los Angeles, U.S.A. C. Bravo, R. Cousins, A. Dasgupta, A. Florent, J. Hauser, M. Ignatenko, N. Mccoll, D. Saltzberg, C. Schnaible, V. Valuev, M. Weber 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, H. Wei, S. Wimpenny, B. R. Yates University of California, San Diego, La Jolla, U.S.A. J.G. Branson, G.B. Cerati, S. Cittolin, M. Derdzinski, R. Gerosa, A. Holzner, D. Klein, V. Krutelyov, J. Letts, I. Macneill, D. Olivito, S. Padhi, M. Pieri, M. Sani, V. Sharma, S. Simon, M. Tadel, A. Vartak, S. Wasserbaech67, C. Welke, J. Wood, F. Wurthwein, A. Yagil, G. Zevi Della Porta University of California, Santa Barbara - Department of Physics, Santa BarN. 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. 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Taylor, 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 Institut Pluridisciplinaire Hubert Curien (IPHC), Universite de Strasbourg, CNRS/IN2P3, Strasbourg, France 4: Also at Universidade Estadual de Campinas, Campinas, Brazil 5: Also at Universidade Federal de Pelotas, Pelotas, Brazil 6: Also at Universite Libre de Bruxelles, Bruxelles, Belgium 7: Also at Deutsches Elektronen-Synchrotron, Hamburg, Germany 8: Also at Joint Institute for Nuclear Research, Dubna, Russia 9: Also at Helwan University, Cairo, Egypt 10: Now at Zewail City of Science and Technology, Zewail, Egypt 11: Also at Ain Shams University, Cairo, Egypt 12: Also at Universite de Haute Alsace, Mulhouse, France 13: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, 14: Also at Tbilisi State University, Tbilisi, Georgia 17: Also at University of Hamburg, Hamburg, Germany 18: Also at Brandenburg University of Technology, Cottbus, Germany 19: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary 20: Also at MTA-ELTE Lendulet CMS Particle and Nuclear Physics Group, Eotvos Lorand 21: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary 22: Also at Indian Institute of Science Education and Research, Bhopal, India 23: Also at Institute of Physics, Bhubaneswar, India 24: Also at University of Visva-Bharati, Santiniketan, India 25: Also at University of Ruhuna, Matara, Sri Lanka 26: Also at Isfahan University of Technology, Isfahan, Iran 27: Also at Yazd University, Yazd, Iran 28: Also at Plasma Physics Research Center, Science and Research Branch, Islamic Azad University, Tehran, Iran 29: Also at Laboratori Nazionali di Legnaro dell'INFN, Legnaro, Italy 30: Also at Universita degli Studi di Siena, Siena, Italy 31: Also at Purdue University, West Lafayette, U.S.A. 32: Also at International Islamic University of Malaysia, Kuala Lumpur, Malaysia 33: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia 34: Also at Consejo Nacional de Ciencia y Tecnolog a, Mexico city, Mexico 35: Also at Warsaw University of Technology, Institute of Electronic Systems, Warsaw, Poland 36: Also at Institute for Nuclear Research, Moscow, Russia at National Research Nuclear University 'Moscow Engineering Physics Insti38: Also at St. Petersburg State Polytechnical University, St. Petersburg, Russia 39: Also at University of Florida, Gainesville, U.S.A. 40: Also at P.N. Lebedev Physical Institute, Moscow, Russia 41: Also at California Institute of Technology, Pasadena, U.S.A. 42: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia 43: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia 44: Also at INFN Sezione di Roma; Universita di Roma, Roma, Italy 45: Also at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, 46: Also at Scuola Normale e Sezione dell'INFN, Pisa, Italy 47: Also at National and Kapodistrian University of Athens, Athens, Greece 48: Also at Riga Technical University, Riga, Latvia 49: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia 50: Also at Albert Einstein Center for Fundamental Physics, Bern, Switzerland 51: Also at Gaziosmanpasa University, Tokat, Turkey 52: Also at Adiyaman University, Adiyaman, Turkey 53: Also at 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 Ozyegin University, Istanbul, Turkey 58: Also at Izmir Institute of Technology, Izmir, Turkey 60: Also at Kafkas University, Kars, Turkey 61: Also at Istanbul Bilgi University, Istanbul, Turkey 62: Also at Yildiz Technical University, Istanbul, Turkey 63: Also at Hacettepe University, Ankara, Turkey 64: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom 65: Also at School of Physics and Astronomy, University of Southampton, Southampton, United 67: Also at Utah Valley University, Orem, U.S.A. 68: Also at Argonne National Laboratory, Argonne, U.S.A. 69: Also at Erzincan University, Erzincan, Turkey 70: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey 71: Now at The Catholic University of America, Washington, U.S.A. 72: Also at Texas A&M University at Qatar, Doha, Qatar 73: Also at Kyungpook National University, Daegu, Korea [43] R. 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