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UNIVERSIDADE ESTADUAL DE CAMPINAS SISTEMA DE BIBLIOTECAS DA UNICAMP REPOSITÓRIO DA PRODUÇÃO CIENTIFICA E INTELECTUAL DA UNICAMP

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DOI: 10.1007/JHEP07(2017)001

DIRETORIA DE TRATAMENTO DA INFORMAÇÃO

Cidade Universitária Zeferino Vaz Barão Geraldo CEP 13083-970 – Campinas SP Fone: (19) 3521-6493 http://www.repositorio.unicamp.br JHEP07(2017)001 . 1 − Springer July 3, 2017 : June 10, 2017 June 21, 2017 April 11, 2017 : : = 13 TeV us- : s √ Revised Published Received Accepted TeV Published for SISSA by = 13 https://doi.org/10.1007/JHEP07(2017)001 s √ t production is found in the data, and upper limits on the ¯ . resonances in highly boosted 3 t ¯ t 1704.03366 Beyond Standard Model, Hadron-Hadron scattering (experiments) A search for the production of heavy resonances decaying into top quark- , Copyright CERN, cms-publication-committee-chair@cern.ch = 8 TeV. s √ E-mail: Article funded by SCOAP Open Access for the benefit of the CMS Collaboration. ArXiv ePrint: with masses above 2 TeV areat significantly improved compared to those of previous analyses Keywords: hadronic channels usinging data the collected CMS in detectorThe proton-proton at selection the collisions is LHC, optimized at for correspondingboosts. massive to resonances, No an where evidence the integrated for top resonant luminosityproduction t quarks of cross have 2.6 large fb section Lorentz of heavy resonances are set. The exclusion limits for resonances Abstract: antiquark pairs is presented. The analysis is performed in the lepton+jets and fully The CMS collaboration proton-proton collisions at Search for lepton+jets and fully hadronic final states in JHEP07(2017)001 ] 15 10 – 8 t resonance ], electroweak 12 8 ] and axigluons [ 7 – 4 ], colorons [ 3 – 1 9 = 13 TeV . In all of these examples, resonant 6 s – 1 – √ ] in various extensions of the Randall-Sundrum (RS) 14 12 10 8 10 6 3 28 13 ], and Kaluza-Klein (KK) excitations of gluons [ ). t 3 t 11 5 M 1 ) in extended gauge theories [ ], and gravitons [ 0 13 19 ]. These models predict the existence of TeV-scale resonances with produc- 16 , 15 6.2 Fully hadronic6.3 channel Systematic uncertainties 6.4 Fitting procedure 5.1 Lepton+jets channel 5.2 Fully hadronic5.3 channel Tagging variables in lepton+jets and fully hadronic channels 6.1 Lepton+jets channel t production would be observable in the reconstructed invariant mass spectrum of the top gauge bosons [ model [ tion cross sections oft a few picobarns at quark-antiquark pair ( with enhanced couplings to third-generationated quarks, massive especially new the particle top containedin quark. experiments in at these The the theories associ- CERN couldZ-like LHC. be bosons Examples observed of (Z as suchin a resonances t are: models with massive color-singlet extendedextended strong Higgs interaction sectors sectors, [ heavier Higgs siblings in models with 1 Introduction Numerous extensions of the standard model (SM) predict the existence of new interactions 8 Summary The CMS collaboration 7 Results 6 Background model and normalization 3 Event reconstruction 4 Simulated events 5 Event selection and categorization Contents 1 Introduction 2 The CMS detector JHEP07(2017)001 t and have t and non- = 13 TeV at , s ]. We use data √ 27 t decay modes. The . Four benchmark models , 1 − b) 4 q 3 b)(q t with relative decay widths of 1%, 2 q 1 (q b) (or charge conjugate) ` ν → ]. Similarly, searches at the LHC have set − ` spectrum for resonances with masses greater b) – 2 – 18 t , − t b)( 2 17 M q 1 b)(W (q + events are generated in the framework of the sequential → 0 (W of 1.2% [ b) − → t t /M b)(W t pairs using the analysis methods described in ref. [ boson decaying exclusively to t + resonances with masses below 900 GeV that decay into t = 7 and 8 TeV. The most stringent limits are from the CMS 8 TeV t production or from W boson production in association with jets. 0 0 s (W √ → ]. Although the 1% and 30% widths are unphysical for various masses in t t ] at 28 ], which combines searches in the fully hadronic, lepton+jets, and dilepton+jets 26 – 27 19 A search is performed using the In this paper, we present a search for the production of heavy spin-1 or spin-2 reso- Searches performed at the Tevatron have set upper limits on the production cross bosons with masses of up to 2.4 and 2.9 TeV, respectively, and an RS KK gluon with 0 of events from SMIn t the fully hadronictop channel, multijet production. the resultingevents from We samples quantum refer are chromodynamic to dominated (QCD)that the interactions by result as latter SM in well as jet t as NTMJ, production. from and other The processes this term category “QCD comprises multijet” is used to describe the class of where both W bosonsidentifying jets decay hadronically. originating fromthe The the samples sensitivity hadronization into of of categoriesflavor the (electron b that search or quarks is depend muon), improved (b on(“t-tagged” the by number jets), jets), the of and and number jets the of separating found consistent within number leptons with a of a (0 given hadronic b jet). or top jets In 1), quark the or lepton+jets decay the b channel, lepton the subjets resulting (where samples consist subjets mainly are smaller jets where one W bosonand decays the hadronically, associated and neutrino. the The other fully decays hadronic to channel a is muon or an electron, than 500 GeV, where theThe top analysis quarks is from performed thelepton+jets using resonance channel the decay is have lepton+jets large and Lorentz fully boosts. hadronic t that model, assuminglimits SM-like as couplings a to function quarks,ferent of resonance this width, widths. approach allowing The the enableswell-motivated RS results model us KK to with gluon to a be model present predicted reinterpreted is physical provided in width. as models an with example dif- of a specific, the LHC, corresponding toare an considered: integrated luminosity a of10%, Z 2.6 and fb 30%, and aof KK approximately gluon 17%). resonance inSM The the (SSM) RS Z model [ (having a relative decay width channels. This work excludes narrowZ (1.2% relative width) andmass wide of (10% up relative to width) 2.8 TeV, at the 95% CL. nances decaying into t recorded in 2015 with the CMS detector in proton-proton (pp) collisions at section of narrow Z a relative decay widthsub-picobarn Γ limits onrange the [ production crossanalysis section [ of resonances in the 1–3 TeV mass JHEP07(2017)001 8 ). In the φ describe the ], which takes 4 74, the HCAL . 31 1 , and < 30 | 3 contains the results η | 7 5 ECAL crystals arrays to × ) of associated charged particles. T p ) and 0.087 radians in azimuth ( η ] is a superconducting solenoid of 6 m internal 29 – 3 – describes the event selections applied in each channel 5 outlines the methods developed to estimate the various 6 48, the HCAL cells map on to 5 describes the CMS detector, while sections . 1 2 < | η | . Within each tower, the energy deposits in ECAL and HCAL cells are 74, the coverage of the towers increases progressively to a maximum of φ . 1 > | and ∆ η | η ]. The leading primary vertex of the event is defined as the primary vertex ]. 32 29 plane, and for Primary vertices are reconstructed using a deterministic annealing filtering algo- In this paper, section φ – rithm [ with the largest squaredCharged sum of particles transverse associated momentawithin ( with the other same primary bunch crossing vertices (“pileup”) due are removed to from additional further interactions consideration. Event reconstruction is based on theinto CMS particle-flow account (PF) information algorithm from [ allsystem, subdetectors, energy including deposits measurements from indetectors. the the tracking Given ECAL this and information,muons, all HCAL, photons, particles and charged in tracks hadrons, the reconstructed or event are in neutral reconstructed hadrons. the as muon electrons, definition of the coordinate systemin used ref. and the [ relevant kinematic variables, can be found 3 Event reconstruction and directions of hadronic jets.measurement Electron in momenta the are ECAL estimatedforward calorimetry with by complements combining the the the coverage provided momentum energy byMuons measurement the barrel are in and endcap the measured detectors. tracker. inoutside the gas-ionization Extensive solenoid. detectors embedded A in more the detailed steel description flux-return of the yoke CMS detector, together with a cells have widths ofη 0.087 in pseudorapidity ( form calorimeter towers projecting radiallypoint. outwards from For close to the0.174 nominal in interaction ∆ summed to define the calorimeter tower energies, subsequently used to provide the energies The central feature of the CMSdiameter, apparatus providing [ a magneticpixel field and strip of tracker, 3.8 a T.a lead brass tungstate Within and crystal the scintillator electromagnetic hadron solenoid calorimeter calorimeter volume (ECAL), (HCAL). and are In a the silicon region background components using fittingof procedures. the analysis Finally, insummarizes section the the work. form of cross section limits on new2 physics models, and The section CMS detector QCD processes. techniques used for object reconstructionthe and analysis, the respectively. properties of Section simulatedof events utilized the in analysis, and section interactions considered in the generation of samples of simulated events arising solely from JHEP07(2017)001 t ]. ]. 45 40 , 1, and . 39 ] in the 0 ]. 35 65% (in t < 33 ≈ ] using infor- 100 GeV. The cut z 34 ee decays ranges ] is used. In this < T 41 → 4. Tracks associated ], also known as the algorithm [ . < p resolution of 1.3–2.0% 2 44 T T up to 1 TeV [ k 5 by combining tracking < p . T | 2 p η | < ]. The jet energy resolution | 38 η [ | 45 GeV from Z T ≈ p T p ] are applied to the energy of the jets to and = 0, soft cutoff threshold 37 β η – 4 – 500 GeV are taken as hadronic top quark candidates. ]. This algorithm is also able to identify two subjets ] using two different choices of the distance parameter: > 46 T 36 ]. Specifically, the CSVv2 algorithm, as described above, p 8 [ 39 . = 0 0 R ]. ]. ]. The “modified mass drop tagger” algorithm [ 40 34 43 , 1% [ 42 ≈ 3.0 software package [ 4 and 0.8. In the following, we refer to the first set of jets as AK4 or small-radius . The large-radius jets with Jets are clustered using PF candidates as inputs to the anti- Electron candidates are reconstructed in the range Muons are reconstructed using the information collected in the muon detectors and resolution in the barrel is better than 10% for muons with = 0 T characteristic radius within the AK8subjet jet. b tagging The techniquesidentifies subjet [ b-tagged corresponding subjets. to Thesubjets, algorithm the has but b a the comparable quark uncertainties performance are can when larger applied be because to identified of using the limited number of highly boosted algorithm [ “soft drop” (SD) algorithm,and wide-angle recursively radiation declusters jet components a until aconsistent jet hard with splitting boosted into criterion heavy-object two is decays. met, subjets, tomass This obtain discarding algorithm resolution jets has by soft been approximately shown 40% toThe improve relative jet algorithm to is standard reconstruction used techniques with [ angular exponent simulated events) and atagged) mistag of rate (the fraction of light-flavor jetsTo that identify true are top incorrectly quarkalgorithm, decays, the the “CMS constituents top of tagger v2” the algorithm AK8 [ jets are reclustered using the Cambridge-Aachen both jet energyvaries and from 15% mass, at as 10degrades GeV to by a a 8% function few at percent 100 of quarks GeV for are to the identified 4% large-radius using at jets. the 1The The Combined TeV for Secondary small-radius working the Vertex jets point v2 small-radius associated used (CSVv2) jets, with algorithm for and b [ jet b tagging in this analysis has an efficiency of R jets, and the second setradius of jets, jets corrections as based AK8remove on the or energy the large-radius contributions from jets. jet neutral area For hadronscorrections both from [ are pileup the interactions. used small- to Subsequent and account large- for the combined response function of the calorimeters in transverse momentum resolution for electrons with from 1.7% for nonshowering electronsin in the the endcaps barrel [ region to 4.5% for electronsFastJet showering p information with energy depositsmation in on the the ECAL. spatial Candidatesbetween distribution are the identified of [ track the and shower,HCAL, the electromagnetic and track cluster, quality, the the and level fraction the of of spatial activity total match in cluster the energy surrounding in tracker the and calorimeter regions. The the inner tracking detectors,with and muon are candidates must measured be in consistentvertex, with the and muons range originating are from required theinformation to leading to primary tracks satisfy measured identification inin requirements. the the silicon Matching barrel tracker results and muon in better chamber a than 6% in the endcaps for muons with 20 JHEP07(2017)001 ]. Its Mad- 0 TeV, masses . 38 0 program. 69, which . shows the 0 1 < 94%, with the are calculated ], and the MLM 32 N ≈ τ pythia τ 51 , -weighted minimum ]. Figure T 50 ]. All events are inter- p 12 ] is employed to identify 49 48 , 8.205 [ 1%) [ 47 < [ 2 v5.2.2.2 [ /τ t pair in all generated events. The 3 pythia τ -channel processes of single top quark t = 32 τ mc@nlo - and a s . 5 – 5 – miss T p ]. The 57 – 53 of all PF candidates reconstructed in the event [ MadGraph t production via QCD interactions and electroweak produc- T . Corrections to the jet energy scale and jet energy resolution p resonances is performed with the leading-order (v2) [ miss T p 0 210 GeV and the N-subjettiness variable satisfies is above 500 GeV. Jets selected by the jet mass and N-subjettiness in the plane transverse to the beam direction is reconstructed as the < distributions for resonance masses of 2 TeV and 4 TeV, for the various T ] Monte Carlo (MC) program using SM values for the left- and right- for the description of fragmentation and hadronization. boson is required to decay into a t p T t t 0 powheg 49 SD p M ] is used to match the parton shower to the matrix element calculation with < M pythia 52 couplings to top quarks. The simulation is performed for a range of Z ]. This working point selects top quark jets with an efficiency of approximately 0 v5.2.2.2 [ 41 seen in the distributions. t t Background events from t The simulation of KK excitations of a gluon is performed with the The missing M tion of single top(NLO) quarks generator in the tWproduction channel are are simulated with simulatedfaced with with the next-to-leading order assuming the branching fraction ofbranching fraction the to KK bottom gluon (light) intogenerator-level quark top pairs quark being pairs 5% is signal ( hypotheses considered.production is For dominated the byof highest-mass off-shell contributions, samples giving considered, the long the tail resonance toward low values parton showering and hadronization isalgorithm modeled [ with a merging scale of 35 GeV. The KK gluon excitations are simulated with resonance masses between 0.5 and 4 Graph handed Z between 0.5 and 4.030%. TeV, and Higher-order QCD for multijet thetree processes level. three for up relative The to width Z three hypotheses extra of partons are 1%, simulated 10%, at and are propagated to the measurement of 4 Simulated events The simulation of Z subjet b tag ifthe they working contain point at described above. least one soft-dropped subjetnegative identified vector as sum b-tagged of using magnitude is the denoted by point used in thissatisfies analysis 110 is definedcorresponds by to requiring a misidentification that rateof the (for 3% soft-dropped light-flavor quark [ mass and of gluon40% jets) the when in the jet simulation jet criteria are referred to as “t-tagged”. Additionally, t-tagged jets are considered to have a using all PF candidatesdistance from in one the of AK8procedure. N jet. These hypothesized observables are subjet Eachwith used corresponds an axes, to N-prong quantify to defined decay the a by topology. consistencythe the three-pronged of The substructure the one-pass variable of particles minimization a of hadronically a decaying jet top quark. The specific working objects used to measure its efficiency. The N-subjettiness observables JHEP07(2017)001 . > for T , the p [GeV] t . Up to t (13 TeV) pythia pythia t, W/Z+jets, MadGraph pythia Generated M 5, and at least two . 2 5, and at least two jets < . | 2 η , are used to validate the | < | Z' 4 TeV, 1% width Z' 4 TeV, 10% width Z' 4 TeV, 30% width RS gluon 4 TeV η | pythia CMS Simulation 0 2000 4000 0 0.1

50 GeV and 1. The trigger selection employed in the 0.4 0.3 0.2 45 GeV,

. 0.35 0.25 0.15 0.05 Fraction of events of Fraction 2 > > < T T | for the production of new particles with masses of p p η t ] has been used. All simulated samples include | – 6 – t M 65 ]. In the parton shower simulated with , ]. [GeV] t 63 t 64 62 (13 TeV) 45 GeV and Z' 2 TeV, 1% width Z' 2 TeV, 1% width Z' 2 TeV, 10% Z' 2 TeV, 30% width RS gluon 2 TeV > T Generated M p 1 or one electron with . 2 < | η | ]. Diboson processes (VV = WW, WZ, and ZZ) are simulated with 200 (50) GeV for the leading (subleading) AK4 jet reconstructed at trigger level. CMS Simulation 61 . Distributions of generator-level > – 0 2000 4000 T 0 58 p 0.1

0.4 0.3 0.2 In the lepton+jets analysis, we select events oﬄine containing one muon with Simulated QCD multijet events, generated with All events are generated at the center of mass energy of 13 TeV and use the NNPDF 3.0 The associated production of W or Z boson and jets is simulated using

0.45 0.35 0.25 0.15 0.05 Fraction of events of Fraction electron channel requires anwith electron with These trigger choices ensure an efficiency of about 99%50 GeV for and high-mass signal events. 5 Event selection and5.1 categorization Lepton+jets channel Events in the muonpresence channel of are a collected muon with with a single-muon trigger, which requires the parton distribution functions (PDF) [ underlying event tune CUETP8M1 [ the effects of additionalbunch inelastic crossings. proton-proton interactions within the same or adjacent both the matrix element and partonto showering calculations. the NLO The event cross rates sections are normalized from ref. [ background-estimation procedure inwhere the the fully NTMJ background hadronic is channel, estimated from but sideband not regions in in data. the search, The MLM matching scheme is appliedfour to additional match partons the in showers the generated matrixand with element single-top-quark calculations are samples included. arerefs. The [ t normalized to the theoretical predictions described in Figure 1 2 TeV (left) and 4 TeV (right), for the four signal hypotheses considered in this analysis. JHEP07(2017)001 4 . 0. lep . 0 3 ). If (5.1) M > ) and ν < ( system ) are the z | `, j ν p η ( `, j | ( had + R 50 (70) GeV. ` R 50 GeV and M σ > T > p ) is the component and 2 from the t-tagged . 1 `, j t system, are required ( lep 15 GeV and , miss T M rel T 2 p σ p R > > T had p . The values of ∆ M j had ). The longitudinal component of − ν M to the leptonic branch of the event, ( σ z discriminator is used to quantify the p had miss T 2 M p χ + 2 – 7 – t system in the lepton+jets channel is performed t decay. The discriminator is defined as (electron or muon), and lep ` ). In events without t-tagged jets, only small-radius M ν lep ( of the neutrino, z − M p T σ is the small-radius jet with minimal angular separation p lep j M = 2 from the lepton are the invariant masses of the reconstructed semileptonically and 4. In the muon (electron) channel, the leading AK4 jet is required χ 2 . ) 2 φ had < | M η | 20 GeV, where + (∆ 150 GeV. In the electron channel, where jets are often misidentified as elec- 150 (250) GeV, and the subleading AK4 jet must have 30 GeV. Given the highly-boosted topology of the final-state objects, no 2 t hypotheses per event, a two-term 120 GeV. After these requirements, the contributions from NTMJ production ) > > and is interpreted as the > > η ) > ) T T ` T lep p p (∆ p miss T `, j ) are calculated considering small-radius jets with M √ p ( miss T + p = In events containing a t-tagged jet, the large-radius jet is assigned to the hadronically The kinematic reconstruction of the t Events in the muon channel are required to have T rel `, j ( p miss T R rel T t system. We first assign the charged lepton and p where hadronically decaying top quark,resolutions of respectively. the leptonic The and quantities hadronic top quark reconstruction, respectively, and decaying top quark. Only small-radius jetsjet with are a used separation in of ∆ theof reconstruction multiple of t the leptoniccompatibility top of quark each decay. hypothesis Because with of a the t presence the neutrino momentum is inferredto by match constraining the the invariant W masstwo boson of real the mass. solutions are Thisavailable, found, the procedure hypotheses real leads part are is to builtjets taken for a as are both quadratic used to cases. equation reconstruct in If both no the real leptonic and solutions hadronic are top decays. a negligible impact on the signal efficiency of theby lepton+jets assigning analysis. the products int the final state to eitherwhere the leptonic or hadronic branch of the only in both lepton channelssecond are lepton found to to ensureclear be there distinction is negligible. between no lepton+jets We overlapwith and also between two dilepton+jets the reject t-tagged analyses. event jets events to samples that Finally, ensure and we contain orthogonality to veto to a maintain the events a fully hadronic analysis. This veto has background from NTMJ productionsignal hypotheses. while maintaining high efficiency for the( high-mass trons, we find that the most effective approach for rejecting NTMJ events is to require or ∆ of the leptonp momentum orthogonal toThe the values axis used are of optimizedreplaces jet for the this more analysis. conventional lepton This isolation two-dimensional requirement, selection as effectively it significantly reduces the to have Additional reconstructed jets, utilizedto in the have reconstruction ofisolation the t requirements are appliedstages. However, to events the are required leptons to at pass a the two-dimensional trigger selection of level ∆ or in the analysis AK4 jets with JHEP07(2017)001 , lep , are M SD M t background and 32 τ 0. . 1 is given by the mass of 4, and both are required . > 2 | had y < 1 b tag); and events with zero M ∆ | , | 30 for all lepton+jets categories. y | , however this region is excluded < 32 τ 0 and 2 min . 1 χ < | y ∆ t pair reconstructed with the smallest value of | – 8 – 1. . 2 500 GeV, rapidity > | > jets. Events can contain 0, 1, or 2 jets with a b-tagged φ 0 b tag). T , T ∆ p p | reduces the contribution of events from non-t 2 min χ are derived using a sample of simulated events in which all four ) to be larger than 800 GeV. The trigger selection has an efficiency T H had M σ for the lepton+jets channel (upper row) and the fully hadronic channel ) is chosen. In events with a t-tagged jet, 2 ) between the two AK8 jets and the number of jets with at least one b- 2 min y , and χ are the means of the corresponding mass distributions. The values of , and therefore on the resonance mass in a given signal hypothesis. Moreover, had T p had 1000 GeV. The event reconstruction is performed using only AK8 jets. The two M , M > Events are further categorized into six regions based on two criteria: the rapidity Finally, to further enhance sensitivity, events are categorized according to the number Events in the signal region are required to have (labeled lep T 2 M t events and subdominant background processes. The fully hadronic channel also shows t good agreement between thenot simulated affect distribution the and analysis, data. asground. The it relies small Some on discrepancies discrepancy data do is toby visible estimate the at the selection NTMJ high used contribution values for to of t the tagging. back- The distributions of theshown two in variables figure used in(lower the row). t tagging Each algorithm, tity of being the plotted, figures whileagreement maintaining is between all data obtained and other simulation after analysis-level inevents removing selections. the are lepton+jets the divided We decay into selection observe channel, where contributions good on simulated from the generator-level top quan- quarks and other jets from difference (∆ tagged subjet for the twosubjet, highest and they are separated into bins5.3 of Tagging variables in lepton+jets and fully hadronic channels H leading jets are requiredto to be have t tagged.of A the back-to-back two topology leading is jets selected to by satisfy requiring the azimuthal separation 5.2 Fully hadronic channel The fully hadronic channelselection requires criteria. that The at data least werethe two AK4 collected jets jet online energies satisfy with ( kinematic aof trigger and requiring above t the 95%, tagging scalar as sum of measured in simulation, for events that satisfy the offline requirement of t-tagged andwith b-tagged zero jets t-tagged jets as andt-tagged follows: at and least b-tagged one events jets b-tagged with (0 jet t one (0 t tag t-tagged tag jet (1 t tag); events compared to the conventional jetthe mass, jet the softthis dropped provides mass greater is discrimination much between less background dependent and on signal. This upper threshold on processes and maximizes the expected sensitivity of the analysis to new resonances. σ partons of the finalused in state the top hypothesis. quarkχ In decay each event, products the are t the matched large-radius jet to calculated a using reconstructed the soft jet drop algorithm. This choice is made because, and JHEP07(2017)001 , for AK8 (13 TeV) (13 TeV) -1 -1 SD < 0.69 32 τ M 2.6 fb 2.6 fb 500 GeV (upper > < 0.69 32 T τ p | < 2.4, subjet b-tag, | < 2.4, Jet soft-drop mass [GeV] Jet soft-drop mass [GeV] η η 210 GeV, and the distribution =1 pb) =1 pb) σ σ > 400 GeV, | > 500 GeV, | T T < SD t Z' 3 TeV ( Z' 3 TeV ( Data t QCD Data Matched to top quark Unmatched to top quark CMS AK8 jets with p CMS AK8 jets with p < M fully hadronic lepton+jets 0 50 100 150 200 250 300 0 50 100 150 200 250 300 , and the soft dropped mass, 1 1

50 50

69. The lepton+jets channel plots compare

1.5 0.5 1.5 0.5 400 GeV and subjet b tag (lower row). The 32

150 100 150 100

Events/10 GeV Events/10 Events/10 GeV Events/10 τ Data/bkg Data/bkg 0 > < T p – 9 – 32 32 32 τ τ τ Jet Jet (13 TeV) (13 TeV) -1 -1 < 210 GeV SD 2.6 fb 2.6 fb t and QCD multijet simulation. Contributions from a benchmark | < 2.4, | < 2.4, 110 GeV < M | < 2.4, 110 GeV η η < 210 GeV SD =1 pb) =1 pb) σ σ > 400 GeV, | > 500 GeV, | (left) is shown after the selection 110 T T 32 τ t Z' 3 TeV ( Z' 3 TeV ( Data t QCD Data Matched to top quark Unmatched to top quark CMS AK8 jets with p subjet b-tag, 110 < M CMS AK8 jets with p signal model are shown with the black dashed lines. In obtaining the ﬁnal results, NTMJ . Distributions of the N-subjettiness ratio, 0 fully hadronic lepton+jets (right) is shown after the selection 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 1 1

50 50

1.5 0.5 1.5 0.5

200 150 100 150 100

Events/bin Events/bin Data/bkg Data/bkg SD M In this section, we describeestimation the for sources both of the thesources SM lepton+jets background of and and systematic methods fully oftreatment hadronic uncertainty of background channels. considered the backgrounds in We and thento uncertainties this determine introduce in analysis. the the the maximum total likelihood yield Finally, fit of that we SM is processes describe used and the in the statistical analysis of data. production is estimated fromthe data, error and bars simulated include QCD only multijet statistical events contributions. are not used. In6 all plots, Background model and normalization distribution of of data to background simulation, wherethe the generator latter level is to dividedchannel top into plots quarks contributions compare from and data jets othernarrow to matched jets Z at t in top pair or W+jets events. The fully hadronic Figure 2 jets in data androw). simulation, after For the the signal fully selection. hadronic For lepton+jets, final with state, with JHEP07(2017)001 dis- t 2 TeV t 0 b tag) < 30. For M , 0 b tag)), t t , > M t events and 2 min χ 20 24 . . 0 0 t and W+jets produc- 1 b tag); (0 t tag 74 85 , . . ee channel is not used because 1 b tag) and (1 t tag) categories. t events is taken from simulation. , 15. → . 0 002 0 002 0 . . 0 0 79 +jets selection and adding the Z boson . t is removed by subtracting the distribu- µ 051 051 . . = 0 t-dominated region is defined by ` t and W+jets, and the dimuon invariant mass is – 10 – distribution for t 111 GeV. The Z t 010 0 012 0 t . . < 0 0 . As the SFs for the muon and electron channels are . M 1 µµ miss T p 038 043 . . < M ]. Distributions defined in samples dominated by various back- 66 . The two main background processes are t 5 +jets 0 Channel Eff. in data Eff. in MC SF e+jets 0 µ 30. The region dominated by W+jets events is defined by < t events in simulation. The t mistag rate is measured separately for the muon and . The mistag rates in data and simulation, and their ratio (data/simulation SF), for AK8 30. The remaining contamination from t 2 min > χ The final background estimates in this search are determined by fitting the background- The distributions obtained from simulation are corrected to account for known dis- 2 min The fully hadronicNTMJ channel production. has The two shape of primaryThe the normalization sources of of this distribution SMallowed is to vary background: initially within set both rate to t andshape the shape theoretical and uncertainties cross during normalization the section, are statistical but both analysis. is fitted The and extracted for each of the six event categories. giving a total ofdefined 12 by control removing regions themass (CRs). lepton window requirement One veto 71 additional fromof CR, the the dominated stringent by requirement Z+jets, on is 6.2 Fully hadronic channel tribution is used in regionsused dominated in by t a region dominatedand by Z+jets. The t each of these two latterand regions, number six of exclusive b-tagged categories are and defined t-tagged based on lepton jets flavor ((1 t tag); (0 t tag consistent, the weighted average is used: SF only hypothesis to data [ grounds are used simultaneouslyferent in uncertainties a in binned the maximum likelihood background model fit to using constrain the the data. dif- The reconstructed for AK8 jets fromχ a sample dominatedtion by of W+jets, t selectedelectron by channels, requiring in events data to andsimulation simulation. have SFs, The are resulting shown values, in together with table the data-to- Single top quark, Z+jets,background. and diboson production contribute only a smallcrepancies fraction in of the the observeda number of scale data factor and (SF) simulated between events. data In and particular, simulation we for derive the t tagging mistag (t mistag) rate tion. The latter accountscategory, for whereas a the former sizeable fully portion dominates of the the (0 background t in tag the (0 t tag 6.1 Lepton+jets channel Several SM processes contributedescribed to in section the sample obtained from the lepton+jets selection Table 1 jets in the lepton+jets analysis. JHEP07(2017)001 (13 TeV) -1 3000 t contribution 2.6 fb 2000 Jet momentum [GeV] 0). The contamination from . 1000 1 ). The anti-tag requirement > 3 0 ( . 0 b tag 1 b tag 2 b tag 1 t events in simulation, normalized to y| > 1.0 ∆ CMS 500 | < | 1 y 2 1 − −

) and is measured separately for events ∆

10 10 | t mistag rate mistag t T p t as the dominant background component. 69. This “anti-tag and probe” method yields a categories (ﬁgure . – 11 – | 0 y > ∆ | 32 t contribution is subtracted from the NTMJ estimate. τ . (13 TeV) -1 3000 3 2.6 fb t simulation from those measured in the anti-tag and probe 2000 Jet momentum [GeV] 210 GeV and t contribution to the total background predominantly aﬀects the signal < 1000 SD 0 b tag 1 b tag 2 b tag < M y| < 1.0 ∆ 500 CMS | t events survive this selection. This contamination is removed by subtracting the . The mistag rate for the t tagging algorithm in the fully hadronic channel, measured 1 2 1 ]. The method involves selecting a sample of data events with low SM t − −

10 10 25 This singly-tagged control region without any requirements on the second jet has an Once the t mistag rate has been determined from the NTMJ control sample, it is used For the NTMJ estimate, we use a data-driven technique similar to that described in t mistag rate mistag t t production is removed by subtracting the distribution of t momentum of the jet oppositesubjet the b tagged tags, jet, as their shown rapidity in difference, figure and theoverlap number with of the signal region,the and effects is of used double-counting, to the estimate t the NTMJ background. To remove to estimate the normalization andTo shape do of this, NTMJ we use eventsjet. passing a the “single-tagged” To avoid final region bias, event that we selection. require contains randomly events that select with it one at pass of least thetagged, the one t two we t-tagged tagging leading include selection top this described quark event above. jet and candidates If weight and the it randomly by chosen the jet appropriate is t t mistag rate based on the falling into each of theis six designed b to tag selectgenuine and t a sample indistributions data measured dominated in by t selection NTMJ in events. data. A small number of by inverting the tdetermining tagging the N-subjettiness t requirement tagging onsatisfy rate 110 one for selected the jet secondper-jet (anti-tag), jet t and (probe). mistag rate Thetied parameterized anti-tag as to jet a the is function radiation required of within to jet the momentum jet (which than is is more the closely The variation of the t regions with two subjet b tags, which have t ref. [ with data for theand six triangular event points categoriesrespectively. indicate The by the left an (right) t anti-tag plott mistag contains and events rate with probe for procedure.SM events expectation. in The the round, 0, square, 1, and 2 b tag categories, Figure 3 JHEP07(2017)001 ] ]. 73 33 [ η t events t, W+jets and t contamina- T p t system by using t 210 GeV. This method is validated < SD ]. The uncertainty in the total integrated 71 < M t system. These uncertainties are taken into t events that would enter the NTMJ background – 12 – ]. The systematic uncertainty associated with the t and W+jets production in the SM is estimated by 72 ]. The corresponding systematic uncertainty is determined scales used for the parton shower generation and evolution. 63 2 lists the sources of uncertainty and the channels they affect. 6 mb). Q . 2 3 ] and assigned a 20% uncertainty. The effect due to missing higher- 70 0 . – = 13 TeV is 2.7% [ s 67 , = 72 √ 60 inel σ t events, to find the contribution of t 5% ( t, 6% for W+jets, and 20% for Z+jets production. Small contributions to the event The systematic uncertainties related to the muon identification and trigger efficiencies The effect of the uncertainties in the theoretical SM cross sections for t As a final step in determining the shape of the NTMJ background estimate, we correct are treated as uncorrelated,The and both uncertainties are are applied obtainedone as standard by functions deviation. varying of Additional the each systematicto muon corresponding uncertainties of the data-to-simulation 1% identification and SF and 0.5% by are trigger attributed efficiency SF measurements, respectively. Similarly, the Simulated samples for bothfrom background the and NNPDF signal 3.0according processes set to the are [ procedure generatedluminosity described using at in PDFs ref. [ yield of simulated pileupby events is evaluated by varying the inelastic pp cross section [ order corrections in the simulationvarying of the t renormalization andindependently factorization by scales a factor used of inof 2. the initial- Additionally, and simulation we final-state account up radiation for andsimulated on uncertainties in the down with the reconstruction different simulation of the t and Z+jets production are obtainedfor from t the background fityields described arise above, from and single arefrom top 8% theory quark [ and diboson production. Their normalization is taken In particular, we quantifyof the the invariant effect mass ofaccount of in each the the of reconstructed maximum these t in likelihood uncertainties the fit statistical on to interpretation the determineis of measurement the given the total below, data. and yield The table of complete SM list processes, of and systematic uncertainties 6.3 Systematic uncertainties Several sources of systematicrelated uncertainties to are an considered experimental uncertainty in introducedtheoretical this in uncertainty search. the affecting reconstruction Each the of of the simulation event these of or is certain to a background or signal processes. for the fact that thejets second in jet, the having signal no region.procedure t is tagging To mimic applied, used, the has indistribution kinematics different of kinematics which of jet than the we masses signal randomly fromused region, set simulated to a QCD the select “mass-modified” multijet the mass events, signalusing of using region simulated the this selection, QCD same 110 second multijet window events. jet as according to a lated t estimate when the method is appliedtion to of data. about This 1–2% contribution amounts of6–10% to the in a NTMJ t the background other estimate regions), in and the is 0 subtracted b-tag from event the regions NTMJ (about backgroundestimate. This is done by evaluating the t mistag weighting procedure described above on the simu- JHEP07(2017)001 . t t M and treated as uncorrelated. The T p distribution. Simulated QCD multijet events t t dependence, are allowed to vary within uncer- . All other systematic uncertainties are included – 13 – M η 6.2 . The data-to-simulation correction for the efficiency and η distribution. An additional systematic uncertainty is T p t t and M T . Both systematic variations are also propagated to the mea- p η ) control region. µ and T p and the jet mass. A SF is applied to account for differing efficiencies and miss T ]. An uncertainty of 2% is assigned to the efficiency of the electron trigger p 34 [ η The systematic uncertainty associated with the “mass-modified” procedure, which is The uncertainties in the data-to-simulation corrections for jet energy scale and jet and T estimation method, having both tainties, with their final valuesusing estimated the by procedure the outlined fit. in Theas section NTMJ nuisance background parameters is in constrained theand fit, shape and uncertainties, are allowed as to described vary within above, their using corresponding log-normal rate prior distributions. The To improve the flexibilityuncertainties of in several the parameters background through aquark model, maximum pair likelihood we invariant fit mass estimate to distribution,estimates the data as using using central follows. the simulated values top The events and normalizations areSF for left for the the unconstrained t background in tagging thethe efficiency fit. subjet is also The b unconstrained data-to-simulation tagging and efficiency extracted as from the well fit. as The the SF yield for of events from the NTMJ background predicts the doubleassigned t-tagged to the NTMJobserved in background the estimate closure based test, in on the small6.4 shape disagreements of (up the kinematic to Fitting threshold procedure 10%) at low values of used to correct the kinematic biasthe in difference the background between estimation, the isaffects computed uncorrected the by and shape taking and half “mass-modified” normalization of backgroundare the estimates. used in This a closure test to verify that the background estimation procedure accurately the fully hadronic channeldescribed (dominated above, by with gluons a momentum-dependent fromuncertainties uncertainty QCD ranging are from interactions) estimated 5 is to byanti-tag measured 100%. varying and as These the probe anti-tag sample.t criterion mistag Systematic for rate uncertainties are the treated due construction as to of uncorrelated. the the t tagging efficiency and tainties, as a function ofof jet the t taggingis selection for done AK8 by jets leavinglepton+jets is this channel measured parameter (dominated in unconstrained by situ in quarksregion in the from dominated the W+jets) fit. by statistical is W+jets The analysis. measured production t directly with This in mistag an a efficiency uncertainty control of in 19%. the The t mistag rate in functions of the jet surement of misidentification rates of the bties tagging in selection the between SFs datadata-to-simulation are and correction measured simulation. for as Uncertain- the functions subjetas of an b the independent tagging uncertainty jet algorithm and efficiency is is evaluated also by included varying the correction within its uncer- p selection, and isefficiency determined in from a dilepton a (e complementary measurement ofenergy the resolution e+jets are evaluated trigger by varying these corrections within their uncertainties, as uncertainty in the electron identification efficiency is applied as a function of the electron JHEP07(2017)001 → (pp σ

⊕ ⊕

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⊕ ⊕ ⊕ ⊕ ⊕ ⊕

Lepton+jets Fully hadronic t pair. In order to maximize the ) ) ) ) ) ) ) ) ) , η , η , η , η , η , η , η p η T T T T T T T σ σ σ σ σ σ σ ( ( p p p p p p p 1 1 1 1 1 1 1 8% 6% 2% σ σ ( ( ( ( ( ( ( 20% 20% 20% 19% 2.7% 1 1 σ σ σ σ σ σ σ 1 1 1 1 1 1 1 ] is used to extract the upper limits at 95% – 14 – distributions. The systematic uncertainties listed 74 t , t 66 M . A template-based shape analysis is performed using the . Uncertainties that are correlated between channels are labeled t t

M ] for these Uncertainty Channel 66 denotes the uncertainty in the given prior value in the likelihood fit. σ t), for heavy resonances decaying to a t t are introduced as individual nuisance parameters in the limit calculation. For the → . In this table, . Sources of uncertainty and the channels they affect. Uncorrelated uncertainties applied to 2 ⊕ t cross section t matrix element scale t parton shower scale X Source Prior uncertainty t W+jets cross section Z+jets cross section Single-top cross section Diboson cross section Integrated luminosity Pileup modeling Muon identification Muon trigger Electron identification Electron trigger Jet energy scale Jet energy resolution Jet b tagging efficiency Jet b mistag rate Subjet b tagging efficiency Jet t tagging efficiency unconstrained Lepton+jets channel t mistag rate Fully hadronic channel t mistag rate PDFs t t W+jets matrix element scale NTMJ background kinematics NTMJ background closure test ( A Bayesian statistical method [ B ) in table signal cross section parameter, wedata-to-simulation use correction a for uniform t prior tagging distribution.the efficiency other The is uncertainty nuisance left in parameters unconstrained, the correspondinga whereas to each log of a normal systematic prior uncertainty is distribution. modeled with The uncertainty due to the finite size of the simulated confidence level (CL) on the productX of the cross section and branchingexpected fraction, i.e. sensitivity of the search,in twelve exclusive the categories statistical are analysis, employedthe simultaneously as limit-setting procedure described is above.Theta software For package each [ category, the observable used in best fit values obtaineddistributions from of this background maximum and likelihood signal evaluation processes. are used to correct the Table 2 a given channel are labeled withwith a a JHEP07(2017)001 . 6.4 78 8 58 32 541 85 65 377 229 10 in the distributions t t M ) for data and the expected SM back- 129 1090 18 74 4 84 124 248 856 8055 30 780 54 4675 826 1965 10 684 111 635 5 +jets signal region e+jets signal region µ (figure 4 – 15 – for the six categories in the signal region of the 4 16 1260 2 97 15 1016 29 9164 4 547 28 7602 1 103 1 44 2 682 1 333 and 3 distribution to ensure that the statistical uncertainty associated t t M t pair is shown in figure t 119 t 218 ]. The impact of the statistical uncertainty in the simulated samples is limited Data 142 1217 1005 Total background 138 Other 4 W+jets (HF) 2 W+jets (LF) 13 t Process 1 t tag 0 t tags, 1 b tag 0 t tags, 0 b tags Data 252 9230 7966 Total background 258 Other 9 W+jets (HF) 4 W+jets (LF) 27 t Process 1 t tag 0 t tags, 1 b tag 0 t tags, 0 b tags 75 . Numbers of events in the signal region for the lepton+jets analysis. The expected yields for cally and hadronically decaying topin quarks the in analysis. each ofthe the The lepton+jets individual channel, small categories some differences considered discrepancies are are observed covered at by large the systematic uncertainties. For lepton+jets and fully hadronicthe channels, reconstructed respectively. t Thegrounds invariant mass in distribution the of lepton+jetsfit. (fully Good hadronic) agreement signal-region between categoriesmated data systematic after and uncertainties. the background The background prediction modelingis is of observed verified the within data using in the kinematic background-enriched esti- samples distributions for leptons, jets, and the reconstructed leptoni- 7 Results The number of eventsground observed fit in data are and given expected in from tables SM processes after the back- in categories where theto W+jets missing higher-order background corrections dominates. in the These simulated discrepancies events, are and have related little impact on the with the expected background is less than 30% in each bin. samples is introduced inmethod [ the statistical analysisby rebinning according each to the “Barlow-Beeston lite” Table 3 SM backgrounds are obtained fromThe the uncertainties maximum reported likelihood in fit the tothe total the simulation expected and data all described background the include inindicates posterior section the contributions systematic statistical from uncertainties. uncertainties W For in bosons the W+jets produced background, in LF association (HF) with light-flavor (heavy-flavor) jets. JHEP07(2017)001 [GeV] [GeV] [GeV] t t t 1 b tag), and t t t , (13 TeV) (13 TeV) (13 TeV) M M M -1 -1 -1 2.6 fb 2.6 fb 2.6 fb t t t Data Other t Z’ 2.0 TeV, 1% width Data Other t Z’ 2.0 TeV, 1% width Data Other t Z’ 2.0 TeV, 1% width CMS CMS CMS e+jets, 0 t tag, 1 b tag e+jets, 0 t tag, 0 b tag e+jets, 1 t tag 0 1000 2000 3000 0 1000 2000 3000 0 1000 2000 3000 1 1 1 33 22 33 22 22 11 11 11

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Data / Bkg / Data Bkg / Data Data / Bkg / Data Events / 100 GeV GeV 100 100 / / Events Events GeV GeV 100 100 / / Events Events Events / 100 GeV GeV 100 100 / / Events Events – 16 – 30) after the maximum likelihood ﬁt. Distributions < [GeV] [GeV] [GeV] t t t t t t 2 (13 TeV) (13 TeV) (13 TeV) M M M -1 -1 -1 χ 2.6 fb 2.6 fb 2.6 fb for data and expected background, for events passing the signal t t t Data Other t Z’ 2.0 TeV, 1% width Data Other t Z’ 2.0 TeV, 1% width Data Other t Z’ 2.0 TeV, 1% width t t M CMS CMS CMS +jets, 0 t tag, 1 b tag +jets, 0 t tag, 0 b tag +jets, 1 t tag µ µ µ 0 1000 2000 3000 0 1000 2000 3000 0 1000 2000 3000 1 1 1 44 33 22 44 33 22 22 11 11 11 1010 1010 1010 1.5 0.5 1.5 0.5 1.5 0.5

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. Distributions in

Data / Bkg / Data Data / Bkg / Data Data / Bkg / Data Events / 100 GeV GeV 100 100 / / Events Events Events / 100 GeV GeV 100 100 / / Events Events Events / 100 GeV 100 / Events Events / 100 GeV 100 / Events 0 b tag). The signal templates are normalized to a cross section of 1 pb. The uncertainties , with the statistical (light gray) and total (dark gray) uncertainties shown separately. selection of theare lepton+jets analysis shown ( forsplit the into muon three (left) exclusive(0 and t categories tag electron (from (right) uppermostassociated channel. to with the lowest): For backgroundcertainties. each (1 expectation t lepton include The tag), flavor, the lower (0 t panel statistical events tag and in are all each post-fit figure systematic shows un- the ratio of data to predicted SM background, Figure 4 JHEP07(2017)001 [GeV] [GeV] [GeV] t t t t t t (13 TeV) (13 TeV) (13 TeV) M M M -1 -1 -1 2.6 fb 2.6 fb 2.6 fb t t t Data NTMJ t Z’ 2.0 TeV, 1% width Data NTMJ t Z’ 2.0 TeV, 1% width Data NTMJ t Z’ 2.0 TeV, 1% width 1000 2000 3000 1000 2000 3000 4000 1000 2000 3000 4000 CMS CMS CMS y| > 1.0; 1 b tag y| > 1.0; 2 b tag y| > 1.0; 0 b tag ∆ ∆ ∆ | | | 1 1 1 22 33 22 11 11 11

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Data / Bkg / Data Data / Bkg / Data Data / Bkg / Data Events / 100 GeV GeV 100 100 / / Events Events Events / 100 GeV GeV 100 100 / / Events Events Events / 100 GeV GeV 100 100 / / Events Events selection of the fullyfor hadronic the analysis regions with after themost maximum to likelihood lowest). fit. Theassociated signal Distributions with templates are the are shown normalized backgroundcertainties. to expectation a include The cross the lower sectionwith panel statistical of the and in 1 statistical pb. all each (light post-fit figure The gray) uncertainties systematic shows and total un- the (dark ratio gray) of uncertainties data shown separately. to predicted SM background, Figure 5 JHEP07(2017)001 t mass may be 5 t resonances. samples, up to and boson decaying 0 0 4 t. Dedicated cross ]. 8 9 2 0 7 3 ...... 77 3 1 4 7 1 7 7 15 4 43 0 19 8 28 . . . . 4 7 10 60 12 79 7 5 0 signal region production are taken from NLO order 0 signal region . . 0 1 ) of 1%, 10%, or 30%, and a KK gluon 1 > < /M | 2 215 5 278 | 0 248 3 62 . . y 1 121 . . y . 6 7 11 369 8 4 7 ∆ ∆ | | – 18 – . The combination of the lepton+jets and fully 9 – 5 . By varying the nuisance parameters within their prior 5 , and up to 3.3 TeV for the RS KK gluon hypotheses, at the 0 and t 34 t 66 4 Process 0 b tags 1 b tag 2 b tags SM t NTMJ 787 Total background 821 Data 830 264 46 ProcessSM t NTMJTotal backgroundData 882 0 b tags 1 817 b tag 2 b tags 925 387 94 ]. The leading order (LO) predictions for the KK gluon cross sections are t with a relative decay width (Γ 76 , and tabulated in tables 6 . Number of events in the signal region for the fully hadronic analysis. The expected yields Limits are extracted on the cross sections for the various signal hypotheses using the We proceed to set exclusion limits on different benchmark models for t limit of 0.5 TeV, masses3.9 TeV for are the excluded 10% up95% width to CL. Z 4 These TeV limits fordominates are the the close 30% mass to distribution width theresonant by Z point enhancing contribution, the where modifying off-shell the the contribution parton behavior and luminosity of reducing at the the low signal t model from resonant-like to distribution functions, pseudo-experiments areCL performed (1 to and 2 estimateresults, standard the including deviations) 68% observed expected andin limits limits 95% figure on in the thehadronic median resonant channels results. production significantly improves cross the The exclusionall sections, combined limits models, relative are to except previous shown for results those for using a width of 1%. Starting from the lower mass exclusion resonance in the RS model.calculations The [ cross sections for Z multiplied by a factor of 1.3 to account for higher-orderdistributions corrections in [ figures tag categories in the lepton+jetschannel, which channel, have and the the highest 2 signal-to-background b ratios. tag categories inFour the extensions fully to hadronic theexclusively SM to are t considered in the statistical analysis: a Z results, as these categorieschecks are have less confirmed sensitive than thatattributed those the to dominated localized by statistical discrepancies t fluctuations. visible The in sensitivity figures of this analysis is driven by the 1 t Table 4 for SM backgrounds areThe obtained uncertainties from reported the for maximumon the the likelihood total simulation fit expected and to all background data the include described posterior the in systematic statistical uncertainties. the uncertainties text. JHEP07(2017)001 . t of t M boson /M 0 [TeV] [TeV] 1.3) Z' KK g × M (13 TeV) M (13 TeV) -1 -1 = 13 TeV at s 2.6 fb 2.6 fb √ boson with Γ 1 s.d. exp. 2 s.d. exp. 1 s.d. exp. 2 s.d. exp. 0 Observed Expected Z' 10% width (NLO) Observed Expected ± ± ± ± RS gluon (LO CMS CMS 0.5 1 1.5 2 2.5 3 3.5 4 0.5 1 1.5 2 2.5 3 3.5 4 1 1 1 1 2 3 4 4 5 4 3 2 5 4 3 2 2 3 − − − − − − − − 10 10

of 10%, (lower left) a Z

10 10 10 10 10 10 10 10 KK

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presents the Z

−

10 10 10 10 10 10 10 10

Z' 10 10 shows the exclusion limits obtained for the two channels and for their combination.

) [pb] ) t t (Z' t t (Z' ) [pb] ) 10 10 10 10 10 10 → × σ → × σ Β Β 7 /M 5 8 Summary A model-independent search for theing production into of t heavy spin-1 orof spin-2 resonances 2.6 fb decay- the LHC. The analysis is designed to have high sensitivity at resonance masses above nonresonant-like. Because offuture this, searches, a in diﬀerentTable order analysis to strategy be shouldFigure sensitive be to considered such in non-resonant production at large of the resonance mass.with Γ Limits are30% set and (lower using right) four aprediction extensions KK as excitation to a of function the a of SM: gluon the (upper in resonance the mass left) RS is a model. shown Z as The a corresponding dot-dashed theoretical curve. Figure 6 section and branching fractions for the full combination of the analysis results, shown as function JHEP07(2017)001 Z' Z' / M / M resonance Z' Z' (13 TeV) (13 TeV) 2, 3, 4 TeV. 0 Γ -1 Γ -1 , σ 2 s.d. exp. 2.6 fb 2.6 fb ± Expected = 1 1 1 +2 0 − − Z 10 10 M σ 2 s.d. exp. Expected ± 1 s.d. exp. ± Observed Z' 2 TeV (NLO) = 30%) RS KK Gluon /M Median +1 (Γ 1 s.d. exp. 0 ± Observed Z' 4 TeV (NLO) σ 2 2 1 CMS CMS − − − 10 10 1 1 1 1 2 2 − − − −

10 10

Z' Z'

) [pb] ) t t (Z' [pb] ) t t (Z' Β Β × σ → × σ → σ 2 − Z' Z' = 10%) Z – 20 – Excluded mass ranges [TeV] / M / M /M Z' Z' (13 TeV) (13 TeV) Γ -1 Γ -1 (Γ 0 2 s.d. exp. 2.6 fb 2.6 fb ± Expected 1 1 − − 10 10 2 s.d. exp. = 1%) Z ± Expected 1 s.d. exp. Observed Z' 1 TeV (NLO) ± /M (Γ 0 Z 1 s.d. exp. 4.0 0.022 0.016 0.022 0.032 0.049 0.075 3.5 0.025 0.019 0.026 0.036 0.055 0.081 3.0 0.046 0.024 0.033 0.047 0.071 0.099 2.5 0.046 0.031 0.044 0.061 0.090 0.13 2.0 0.10 0.057 0.080 0.12 0.17 0.24 1.5 0.24 0.15 0.20 0.29 0.43 0.62 1.0 1.8 0.75 1.0 1.5 2.2 3.0 0.5 78 32 50 88 150 230 Observed Z' 3 TeV (NLO) ± 1.25 1.1 0.26 0.38 0.53 0.78 1.2 0.75 7.1 2.9 4.3 6.1 8.8 13 2 2 CMS CMS − − Mass [TeV] Observed limits [pb] Expected limits [pb] 10 10 1 1 1 1 2 − − − 10 . Expected and observed limits presented as a function of width, for

10 10

10 . Expected and observed cross section limits at 95% CL, for the 1% width Z

. Comparison of mass exclusion results (in TeV) for the individual channels and for their

Z' Z'

) [pb] ) t t (Z' ) [pb] ) t t (Z' Β Β → × σ → × σ Result Exp. Obs. Exp. Obs. Exp. Obs. Exp. Obs. Lepton+jets 0.6 — 2.1 0.6 — 2.3 0.5 — 3.5 0.5 — 3.4 0.5 — 4.0 0.5 — 4.0 0.5 — 2.9 0.5 — 2.9 Fully hadronic 1.2 — 1.8 1.4 — 1.8 1.0 — 3.2 1.0 — 3.5 1.0 — 3.7 1.0 — 4.0 1.0 — 2.6 1.0 — 2.4 Combined 0.6 — 2.4 0.6 — 2.5 0.5 — 3.7 0.5 — 3.9 0.5 — 4.0 0.5 — 4.0 0.5 — 3.1 0.5 — 3.3 Table 6 hypothesis. Table 5 combination. Figure 7 The corresponding theoretical predictioneach as case. a function of width is shown as a dot-dashed curve in JHEP07(2017)001 t with resonance resonance 0 0 σ σ σ +2 +2 +2 σ σ σ t is found. Limits at Median +1 Median +1 Median +1 σ σ σ 1 1 1 − − − σ σ σ 2 2 2 − − − – 21 – 1.0 3.6 1.2 1.6 2.4 3.7 5.3 2.0 0.22 0.13 0.19 0.28 0.41 0.61 3.0 0.12 0.080 0.11 0.15 0.22 0.32 4.0 0.10 0.075 0.10 0.15 0.23 0.34 0.5 41 26 40 69 130 190 0.5 29 25 43 77 130 200 1.0 4.4 1.3 1.7 2.5 3.8 5.3 1.0 3.5 1.0 1.5 2.1 3.0 4.2 1.5 0.73 0.33 0.44 0.67 1.0 1.4 1.5 0.39 0.21 0.31 0.44 0.65 0.93 2.0 0.21 0.13 0.18 0.27 0.40 0.54 2.0 0.15 0.089 0.12 0.18 0.25 0.38 2.5 0.13 0.082 0.12 0.17 0.25 0.37 2.5 0.068 0.048 0.066 0.097 0.15 0.20 3.0 0.11 0.071 0.094 0.13 0.19 0.29 3.0 0.067 0.039 0.053 0.074 0.11 0.16 3.5 0.093 0.065 0.088 0.13 0.20 0.29 3.5 0.051 0.034 0.047 0.069 0.10 0.16 4.0 0.096 0.073 0.099 0.14 0.22 0.32 4.0 0.050 0.035 0.048 0.072 0.11 0.17 0.75 14 5.0 7.3 12 19 29 0.75 9.1 3.9 5.6 8.1 12 18 1.25 2.2 0.53 0.76 1.1 1.7 2.4 1.25 1.3 0.41 0.55 0.79 1.2 1.6 Mass [TeV] Observed limits [pb] Expected limits [pb] Mass [TeV] Observed limits [pb] Expected limits [pb] Mass [TeV] Observed limits [pb] Expected limits [pb] . Expected and observed cross section limits at 95% CL, for the 30% width Z . Expected and observed cross section limits at 95% CL, for the 10% width Z . Expected and observed cross section limits at 95% CL, for the RS KK gluon hypothesis. boosts of the topdata-to-simulation quarks. scale factor The formain analysis backgrounds. the method No t evidence provides tagging for95% an massive efficiency CL resonances in-situ are that and measurement set decay the to on ofrelative t the decay normalization the widths production of that cross are section the either of narrow or new wide spin-1 compared particles with decaying the to detector t resolution. Table 9 1 TeV, where final-state decay products become collimated because of the large Lorentz Table 8 hypothesis. Table 7 hypothesis. JHEP07(2017)001 ´ Energie ) for resonance 1 − of 1%, 10%, and 30% are /M with 10% relative width and 0 0 TeV, respectively. Kaluza-Klein . bosons as a function of the relative 3 TeV in the Randall-Sundrum model 0 . 5–4 . 5–3 . 9, and 0 . – 22 – 8 TeV, respectively. The present analysis extends . 5–3 . 5, 0 . bosons with relative widths Γ 9 and 2 0 . 6–2 . ] (corresponding to an integrated luminosity of 19.7 fb ´ Energies Alternatives / CEA, France; the Bundesministerium fürBildung 27 This analysis yields approximately the same sensitivity as the previous search based In addition, limits are set on the production of particles in benchmark models beyond Department of Atomic Energy andInstitute the for Department Studies of in Sciencetion, Theoretical and Ireland; Physics Technology, the India; Istituto and the Nazionaleand Mathematics, di Future Iran; Fisica Planning, Nucleare, the and Italy; ScienceLithuanian the National Founda- Ministry Academy Research of Foundation of Science, (NRF), Sciences; ICT Republic the of Korea; Ministry the of Education, and University of Malaya Ministry of Education and Culture,de and Physique Helsinki Nucléaireet de Institute Physique of des Physics; ParticulesAtomique / the et CNRS, Institut aux and National Commissariat àl’ und Forschung, Deutsche Forschungsgemeinschaft, and Helmholtz-Gemeinschaft Deutscher Forschungszentren, Germany; the General Secretariat for Researchthe and National Technology, Greece; Scientific Research Foundation, and National Innovation Office, Hungary; the bian Funding Agency (COLCIENCIAS); theSport, Croatian and Ministry the of Croatian Science Science,the Foundation; Education the Secretariat and Research Promotion for Foundation, Higher Cyprus; Ministry Education, of Education Science, and Technology Research,6 and Estonian and Innovation, Research European Ecuador; Council Regional the via Development IUT23-4 Fund, and Estonia; IUT23- the Academy of Finland, Finnish Federal Ministry of Science,Belgian Research Fonds and de Economy la Recherche andthe Scientifique, the Brazilian and Austrian Funding Fonds Agencies voor Science (CNPq,Ministry Wetenschappelijk Fund; Onderzoek; CAPES, of the Education FAPERJ, and and FAPESP); Science;Science the CERN; and Bulgarian the Technology, and Chinese Academy National of Natural Sciences, Science Ministry Foundation of of China; the Colom- other CMS institutes for theirwe contributions gratefully to acknowledge the success theComputing of computing Grid the for centers CMS delivering effort. and soanalyses. In personnel effectively Finally, addition, the we of acknowledge computing the the infrastructureof enduring Worldwide the essential support LHC LHC to for and the our the construction CMS and detector operation provided by the following funding agencies: the Austrian Acknowledgments We congratulate our colleagues in theformance CERN of accelerator departments the for LHC the and excellent per- thank the technical and administrative staffs at CERN and at on 8 TeV data [ masses in the range 1.0–2.0 TeV.icantly At more higher sensitive. resonance masses, Previous thethe lower present Kaluza-Klein mass analysis gluon is limits signif- were onthe 2 the lower Z mass limits to 3.9 and 3.3 TeV, respectively, for these models. the standard model. Topcolor Z excluded for mass rangesexcitations of of 0 a gluon withare masses in also the excluded. range 0 width This of search the presents resonance limits in on the range Z from 1–30%, for the first time in CMS. JHEP07(2017)001 (1996) 113 B 387 Phys. Lett. , 0 Z – 23 – ), which permits any use, distribution and reproduction in ]. SPIRE IN CC-BY 4.0 ][ This article is distributed under the terms of the Creative Commons Prominent decay modes of a leptophobic hep-ph/9607207 [ Individuals have received support from the Marie-Curie programme and the Euro- J.L. Rosner, [1] References University and the ChulalongkornProject Academic (Thailand); into and Its the 2nd Welch Foundation, Century contract Project C-1845. Open Advancement Access. Attribution License ( any medium, provided the original author(s) and source are credited. monia 2014/14/M/ST2/00428, Opus 2013/11/B/ST2/04202,2014/15/B/ST2/03998, 2014/13/B/ST2/02543 Sonata-bis and 2012/07/E/ST2/01406;grammes the cofinanced Thalis by and EU-ESFProgram Aristeia and by Qatar pro- the National Research Greek Fund;de the NSRF; Programa Asturias; the Clar´ın-COFUNDdel Principado the National Rachadapisek Priorities Sompot Research Fund for Postdoctoral Fellowship, Chulalongkorn Technologie (IWT-Belgium); thethe Ministry Czech of Republic; Education,ING the Youth PLUS and Council programme Sports of ofUnion, (MEYS) Science the Regional of and Foundation for Industrial DevelopmentScience Polish Research, Fund, Science, and India; the cofinanced Higher Mobility the from HOM- Plus Education, European programme the of National the Science Ministry Center of (Poland), contracts Har- pean Research Council andA. EPLANET P. (European Sloan Union); Foundation;Science the the Leventis Policy Alexander Foundation; Office; the vondans the Humboldt l’Agriculture Foundation; Fonds (FRIA-Belgium); the pour the Belgian la Agentschap Federal Formation voor àla Innovatie door Recherche Wetenschap dans en l’Industrie et Task Force for Activating Research andAgency the of National Thailand; Science and the Technology ScientificAtomic Development and Energy Technical Authority; Research Council the of Nationalfor Turkey, Fundamental Academy and Researches, of Ukraine; Turkish the Sciences Sciencethe of and US Ukraine, Technology Facilities Department and Council, of U.K.; State Energy, Fund and the US National Science Foundation. Sciences, and the Russianence Foundation for and Basic Technological Development Research; of theDesarrollo Serbia; Ministry e the of Innovaciónand Programa Secretar´ıade Education, Estado Consolider-Ingenio Sci- deAgencies 2010, Investigación, Spain; (ETH the Board, SwissMinistry ETH Funding of Zurich, Science PSI, and Technology,the SNF, Taipei; the Institute UniZH, Thailand for Canton Center the of Zurich, Promotion Excellence and of in Teaching SER); Physics, Science the and Technology of Thailand, Special and UASLP-FAI); the Ministrythe of Pakistan Business, Atomic Innovation Energy andand Commission; Employment, the the New Ministry National Zealand; of SciencePortugal; Science JINR, Centre, Dubna; and Poland; the Higher Ministry thethe Education of a Funda¸cãopara Federal Education Ciênciae and Agency a Science of of Tecnologia, the Atomic Russian Energy Federation, of the Russian Federation, Russian Academy of (Malaysia); the Mexican Funding Agencies (BUAP, CINVESTAV, CONACYT, LNS, SEP, JHEP07(2017)001 ]. , , ]. ] Phys. , , D 76 (1994) , Phys. 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Onsem, Savitskyi, Mnich, R. P. Walsh,University Saxena, Y. A. of Wen, R. K. Hamburg, Shevchenko, Wichmann, Mussgiller, Hamburg, C. Wissing Germany V. E. Blobel, Ntomari, M. Centis Vignali, A.R. Draeger, T. Dreyer, E. Garutti, D. Gonzalez, J. Haller, Campana, F.E. Costanza, Eren, C. E.A. Grohsjean, Diez Gallo P. Gunnellini, Pardos, A.O. Harb, J. G. Karacheban Hauk, M. Eckerlin, Hempel W. Lange, D. A. Eckstein, Lelek, T. T. Lenz, Eichhorn, J. Leonard, K. Lipka, W. Lohmann A. Nowack, C. Pistone, O. Pooth, A.Deutsches Stahl Elektronen-Synchrotron, Hamburg, Germany M. AldayaU. Martin, Behrens, A.A. Bin T. Anuar, K. Borras Arndt, C. Asawatangtrakuldee, K. Beernaert, O. Behnke, S. Knutzen, M.K. Padeken, Merschmeyer, T. Pook, A.D. M. Teyssier, S. Meyer, Radziej, Thüer H. P. Reithler, M. Millet,RWTH Aachen Rieger, University, S. F. III. Scheuch, Physikalisches Mukherjee, L.G. Institut Sonnenschein, B, Flügge,B. M. Kargoll, Olschewski, Aachen, T. Germany Kress, A. J. Künsken, Lingemann, T. 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Institute S. Sharan, Purohit, of Ghosh, S. A. Technology Thakur Roy, Madras,P.K. Behera Madras, India University of Delhi, Delhi,Ashok India Kumar, A. Bhardwaj, S.hotra, Chauhan, M. B.C. Naimuddin, Choudhary, K. R.B. Ranjan, Garg, A.Saha S. Shah, Institute Keshri, R. S. of Sharma, Mal- Nuclear V. Sharma Physics, Kolkata, India S. Bahinipati S.K. Swain Panjab University, Chandigarh, India S. Bansal, S.B. Beri,A. V. Kaur, Bhatnagar, M. R. Kaur, R. Chawla, Kumar, N. P. Dhingra, Kumari, U.Bhawandeep, A. A.K. Mehta, Kalsi, M. Mittal, J.B. Singh, G. Walia Institute of Physics, University ofM. Bartók Debrecen Indian Institute of ScienceS. (IISc) Choudhury, J.R. Komaragiri National Institute of Science Education and Research, Bhubaneswar, India G. Bencze, C. Hajdu, D.mond Horvath Institute of Nuclear ResearchN. ATOMKI, Debrecen, Beni, S. Hungary Czellar, J. Karancsi MTA-ELTE Particle LendületCMS and Nuclear Physics Group, EötvösLoránd University, Budapest, Hungary M. Csanad, N. Filipovic, G. Pasztor Wigner Research Centre for Physics, Budapest, Hungary National and Kapodistrian UniversityS. of Kesisoglou, Athens, A. Athens, Panagiotou, Greece N. Saoulidou University of Ioánnina,Ioánnina,Greece I. Evangelou, G. Flouris, C.J. Foudas, Strologas, P. Kokkas, F.A. N. Triantis Manthos, I. Papadopoulos, E. Paradas, C. Wöhrmann,R. Wolf Institute of Nuclear andParaskevi, Particle Greece Physics (INPP),G. Anagnostou, NCSR G. Demokritos, Daskalakis, T. Aghia I. Geralis, Topsis-Giotis V.A. Giakoumopoulou, A. Kyriakis, D. Loukas, G. Sieber, H.J. Simonis, R. Ulrich, S. Wayand, M. Weber, T. Weiler, S. Williamson, JHEP07(2017)001 , , , , , , , , , , , a a 22 26 a,b a,b a,b a,b a,b a,b a,b a , P. Lenzi , M. Maggi , Bari, Italy c , A.M. Rossi , A. Tricomi , L. Cristella a,b , P. Giacomelli a,c a , R. Radogna , L. Brigliadori a,b a,c a,b , S.S. Chhibra , P. Verwilligen a,c 13 a a a,b a,b, , G. Maggi a,b , E. Focardi , P.K. Netrakanti, L.M. Pant, , A. Perrotta , Bologna, Italy a,c , Catania, Italy 13 b a,b , D. Creanza , R. Potenza 13 b , Firenze, Italy , Genova, Italy a a,b , D. Fasanella , M. Khakzad, M. Mohammadi b b , R. Venditti a,b 24 , G. Pugliese , L. Viliani a,b 13 a , S. Tosi a,b a, , F.R. Cavallo a , Politecnico di Bari a,b b , F. Rezaei Hosseinabadi, B. Safarzadeh , G. Iaselli a 25 , A. Colaleo , G. Majumder, K. Mazumdar, T. Sarkar , S. Braibant-Giacomelli 22 , A. Fanfani a,b , F.L. Navarria a , F. Giordano a,b – 33 – a a , R. D’Alessandro , E. Robutti , G. Sguazzoni , L. Silvestris , A. Pompili a a 13 27 a,b a,b , A. Castro a, , L. Fiore a,b, a,b a,b , F. Fabbri , C. Caputo , Universitàdi Bologna , Universitàdi Catania a , Universitàdi Firenze , Universitàdi Genova a a a a , G. Masetti a,b a , Universitàdi Bari , N. Tosi , A. Sharma , L. Russo , C. Civinini , A. Di Mattia a , S. Nuzzo a a,b a,b a,b , M.R. Monge a,b a,b a , P. Capiluppi , M. De Palma , C. Calabria 23 , E. Eskandari Tadavani, S.M. Etesami a,b a,c , S. 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Science Dewanjee, Education and S. Research (IISER), Ganguly, Pune, India R. Chudasama, D. Dutta, V. Jha,P. V. Shukla, Kumar, A. A.K. Topkar Mohanty Tata Institute of Fundamental Research-A,T. Mumbai, Aziz, India S. Dugad, B. Mahakud,Tata S. Institute Mitra, of G.B. Fundamental Mohanty, B. Research-B, Parida, Mumbai, N. India Sur, B. Sutar Bhabha Atomic Research Centre, Mumbai, India JHEP07(2017)001 , , , , , , , , , , , , , , a a a a a 27 a,b a,b a,b a,b a,b a,b a,b a,b a, , P. De , Roma, a , V. Re a,b d , A. Savoy- , Milano, a,b b a,b , S. Gennai , F. Fienga , L. Borrello, , D. Menasce a 13 , A. Boletti , S. Lacaprara , C. Sciacca , R. Rossin , S. Ragazzi a,c a , N. Bartosik , Napoli, Italy, , P. Lariccia a,b 13 a,b b , A. Santocchia , R. Covarelli a,b, a,b a,b a a,c a, , M.T. Grippo a,b a a,b , A. Rizzi , P.G. Verdini a a,b , S.P. Ratti a , M. Dall’Osso b a a,b , F. Fabozzi , T. Boccali , A. Saha a,b a a , D. Bisello a,b , A. Gozzelino , Perugia, Italy , S. Fiorendi , L. Fanò 28 b , F. Palla , A. Giassi , S. Pigazzini , Padova, Italy, Universitàdi , R.A. Manzoni , P. Paolucci , M. Costa a,b a, a a,b , P. Zotto , Torino, Italy, Universitàdel a,b b a , P. Ronchese a b a,b , M. Arneodo 13 a,b , Pavia, Italy a,b , Scuola Normale Superiore di , A. Venturi a,b b b a,b a,d, a,b , P. Vitulo , P. Checchia , M. Diemoz, S. Gelli, E. Longo, F. Mar- , P. Montagna a,b a,b 13 , M. Esposito , G. Fedi a,b , M. Menichelli a , J. Bernardini 13 a a,b , S. Malvezzi , U. Gasparini , M. Biasotto , A. Messineo – 34 – , M. Zanetti a,d, , F. Cenna a , I. Vai a a , Universitàdi Milano-Bicocca a,b , S. Meola a , G. Tonelli a,b , S. Argiro a a,b a a , D. Ciangottini 13 , N. Pozzobon a a,b a,c, , Potenza, Italy, UniversitàG. Marconi , A. Magnani c , V. Mariani , Universitàdi Perugia , G. Bagliesi , Universitàdi Napoli ’Federico II’ , R. Dell’Orso , Universitàdi Padova a a,b , Universitàdi Torino , S. Fantinel , K. Pauwels, D. Pedrini a , V. Ciriolo, M.E. Dinardo a,b , P. Salvini , S. Di Guida a , Sapienza Universitàdi Roma , L. Lista 13 , S. Ventura a a , Universitàdi Pavia , Universitàdi Pisa , L. Martini a a a,b a , L. Benato a a a, a a,b a,b a,b , M. Malberti a a,c , R. Tenchini , N. Cartiglia a a , Novara, Italy a,b c , G.M. Bilei a,b a,b , T. Dorigo a , R. Arcidiacono , G. Lanza , F. Brivio , E. Torassa , A.T. Meneguzzo , N. Cavallo , P. Azzurri , G. Mantovani a 13 , F. Fallavollita a,b a,b a , T. Lomtadze a,b , M.A. Ciocci , C. Biino a,b a , P. Govoni , A. Carvalho Antunes De Oliveira a a,b , M. Paganoni , P. Spagnolo , N. Bacchetta a a,b, a,c a a,b a,b 29 a,b , Trento, Italy 13 c a, a, , Pisa, Italy c C. Rovelli, F. Santanastasio INFN Sezione di Torino Piemonte Orientale N. Amapane R. Bellan F. Ligabue Navarro INFN Sezione di Roma L. Barone, F. Cavallari, M.garoli, Cipriani, B. D. Marzocchi, Del Re P. Meridiani, G. Organtini, R. Paramatti, F. Preiato, S. Rahatlou, INFN Sezione diPisa Pisa K. Androsov R. Castaldi M. Ressegotti, C. Riccardi INFN Sezione di Perugia L. AlunniR. Solestizi Leonardi D. Spiga Castro Manzano M. Margoni F. Simonetto INFN Sezione di Pavia A. Braghieri F. Thyssen INFN Sezione di Padova Trento P. Azzi R. Carlin INFN Sezione di Napoli Universitàdella Basilicata Italy S. Buontempo A.O.M. Iorio Italy L. Brianza A. Ghezzi L. Moroni T. Tabarelli de Fatis INFN Sezione di Milano-Bicocca JHEP07(2017)001 , , , a a,b a,c a,b , N. Pastrone , M. Ruspa , E. Migliore a,b a a,b a , R. Lopez-Fernandez, 32 , P. Traczyk , W.A.T. Wan Abdullah, a 31 , L. Pacher a,b , S. Maselli a , A. Zanetti , A. Romero , Trieste, Italy b a,b a,b , A. Staiano a,b , C. Mariotti , F. Mohamad Idris , M.M. Obertino – 35 – , F. Ravera a 30 a,b a,b , G. Della Ricca , A. Solano a a , Universitàdi Trieste , B. Kiani a , V. Sola a , M. Monteno a,b , F. Cossutti a,b a , G.L. Pinna Angioni a , N. Demaria , E. Monteil , K. Shchelina , M. Casarsa a,b a,b a a,b Centro de Investigacion y de EstudiosH. Avanzados del Castilla-Valdez, IPN, E. Mexico De City, LaJ. Mexico Mejia Cruz-Burelo, Guisao, I. A. Heredia-De Sanchez-Hernandez La Cruz Universidad Iberoamericana, Mexico City, Mexico S. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia National CentreMalaysia for Particle Physics,I. Ahmed, Z.A. Universiti Ibrahim,M.N. Malaya, M.A.B. Yusli, Md Z. Kuala Ali Zolkapli Lumpur, Sungkyunkwan University, Suwon, Korea Y. Choi, C. Hwang, J. Lee,Vilnius I. University, Yu Vilnius, Lithuania V. Dudenas, A. Juodagalvis, J. Vaitkus Seoul National University, Seoul, Korea J. Almond, J. Kim, H.G.B. Lee, Yu S.B. Oh, B.C. Radburn-Smith, S.h. Seo,University U.K. of Yang, Seoul, H.D. Yoo, Seoul,M. Korea Choi, H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park, G. Ryu J.A. Brochero Cifuentes, J. Goh, T.J.Korea Kim University, Seoul, Korea S. Cho, S. Choi, Y.J. Go, Lim, D. S.K. Gyun, Park, S. Y. Ha, B. Roh Hong, Y. Jo, Y. Kim, K. Lee, K.S. Lee, S. Lee, A. Lee Chonnam National University, Institute for UniverseKwangju, and Korea Elementary Particles, H. Kim, D.H. Moon Hanyang University, Seoul, Korea Kyungpook National University, Daegu, Korea D.H. Kim, G.N. Kim, M.S.Y.C. Kim, Yang J. Lee, S. Lee, S.W.Chonbuk Lee, National Y.D. University, Oh, Jeonju, S. Korea Sekmen, D.C. Son, V. Monaco M. Pelliccioni R. Sacchi INFN Sezione di Trieste S. Belforte A. Degano JHEP07(2017)001 – 36 – , V. Palichik, V. Perelygin, S. Shmatov, S. Shulha, 35 , P. Levchenko, V. Murzin, V. Oreshkin, I. Smirnov, , 37 34 , K. Doroba, A. Kalinowski, M. Konecki, J. Krolikowski, 33 35 , E. Kuznetsova 36 Institute for Theoretical andV. Experimental Physics, Epshteyn, Moscow, V. Russia A. Gavrilov, Spiridonov, M. N. Toms, E. Lychkovskaya, Vlasov, V.Moscow A. Institute Zhokin Popov, of I. PhysicsT. and Pozdnyakov, Aushev, Technology, Moscow, G. A. Russia Bylinkin Safronov, V. Sulimov, L. Uvarov, S. Vavilov, A.Institute Vorobyev for Nuclear Research,Yu. Moscow, Russia Andreev, A.N. Krasnikov, Dermenev, A. Pashenkov, S. D. Tlisov, Gninenko, A. Toropin N. Golubev, A. Karneyeu, M. Kirsanov, S. Afanasiev, P. Bunin, M. Gavrilenko,A. I. Lanev, Golutvin, A. I. Gorbunov, Malakhov, A. V. Kamenev, Matveev N. V. Skatchkov, Karjavin, V. Smirnov, N. Voytishin, A.Petersburg Zarubin Nuclear Physics Institute,Y. Gatchina Ivanov, (St. V. Petersburg), Kim Russia Portugal P. Bargassa, C.M. Beirão Gallinaro, Da J. CruzO. Hollar, Toldaiev, E D. N. Vadruccio, Silva, Leonardo, J. Varela L. B.Joint Lloret Institute Calpas, Iglesias, for A. Nuclear M.V. Research, Di Nemallapudi, Dubna, J. Russia Francesco, Seixas, P. Faccioli, Institute of Experimental Physics,Warsaw, Poland Faculty of Physics,K. University Bunkowski, of Warsaw, A.M. Byszuk Misiura, M. Olszewski, A. Pyskir,Laboratóriode M. F´ısicaExperimental Instrumenta¸cãoe Walczak de Lisboa, Part´ıculas, M. Shoaib, M. Waqas National Centre for NuclearH. Research, Bialkowska, Swierk, M. Poland Bluj,K. B. 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Castaneda Hernandez 67 Moscow, Russia China Also at Universidad de Antioquia,Also Medellin, at Colombia Joint Institute forNow at Nuclear Ain Research, Dubna, Shams Russia University,Now Cairo, at Egypt British University in Egypt, Cairo, Egypt Also at Vienna University ofAlso at Technology, Vienna, State Austria Key Laboratory of Nuclear Physics and Technology,Also Peking University, at Beijing, Universidade Estadual deAlso Campinas, at Campinas, Universidade Federal Brazil deAlso Pelotas, at Pelotas, UniversitéLibre de Brazil Bruxelles, Bruxelles, Belgium Also at Skobeltsyn Institute ofAlso Nuclear at CERN, Physics, EuropeanAlso Organization Lomonosov at for RWTH Nuclear Moscow Aachen Research, University,Also Geneva, State III. Switzerland at Physikalisches University, University Institut of A, Hamburg,Also Aachen, Hamburg, Germany at Germany Brandenburg University of Technology, Cottbus, Germany Now at Cairo University, Cairo,Also Egypt at Universitéde Haute Alsace, Mulhouse, France 6: 7: 8: 9: 1: 2: 3: 4: 5: 12: 13: 14: 15: 16: 10: 11: D.A. Belknap, J. Buchanan, C. Caillol,M. S. Dasu, Herndon, L. Dodd, A. S.R. Loveless, Duric, G.A. Hervé, B. Pierro, U. Gomber, G. M. Polese, Hussain, Grothe, N. T. Ruggles, Woods A. P. Savin, N. Klabbers, Smith, W.H. Smith, A. D. Taylor, Lanaro, A. Levine, K. Long, sith, X. Sun, Y. Wang, E.Wayne Wolfe, State F. Xia University, Detroit, U.S.A. C. Clarke, R. Harr, P.E. Karchin, J.University of Sturdy, S. Wisconsin Zaleski - Madison, Madison, WI, U.S.A. Vanderbilt University, Nashville, U.S.A. S. Greene, A. Gurrola,S. Tuo, R. J. Janjam, Velkovska, Q. W. Xu Johns,University C. of Virginia, Maguire, Charlottesville, A.M.W. U.S.A. Melo, Arenton, H. P. Barria, Ni, B. P. Cox, Sheldon, R. Hirosky, A. Ledovskoy, H. Li, C. Neu, T. Sinthupra- Texas Tech University, Lubbock, U.S.A. N. Akchurin, J. Damgov, F.S. De Kunori, Guio, C. K. Dragoiu, Lamichhane,Z. P.R. Dudero, Wang S.W. J. Lee, Faulkner, E. T. Gurpinar, Libeiro, T. Peltola, S. Undleeb, I. Volobouev, M. Foerster, J. Heideman, G. Riley, K.Texas A&M Rose, S. University, College Spanier, Station, K.O. U.S.A. Thapa Bouhali gado, S. Dildick, R. Eusebi,R. J. Patel, Gilmore, A. T. Perloff, L. Huang, Perniè,D. T. Rathjens, Kamon A. Safonov, A. Tatarinov, K.A. Ulmer University of Tennessee, Knoxville, U.S.A. JHEP07(2017)001 – 45 – Belgrade, Serbia tute’ (MEPhI), Moscow, Russia University, Tehran, Iran University, Budapest, Hungary Also at Necmettin Erbakan University,Also Konya, at Turkey Marmara University, Istanbul,Also Turkey at Kafkas University, Kars,Also Turkey at Istanbul Bilgi University,Also Istanbul, at Turkey Rutherford Appleton Laboratory, Didcot, United Kingdom Also at Mersin University, Mersin,Also Turkey at Cag University, Mersin,Also Turkey at Piri ReisAlso University, Istanbul, at Turkey Gaziosmanpasa University, Tokat,Also Turkey at Adiyaman University, Adiyaman,Also Turkey at Izmir Institute of Technology, Izmir, Turkey Also at Scuola NormaleAlso e at Sezione National dell’INFN, and Pisa,Also Kapodistrian Italy at University Riga of Technical Athens, University, Athens,Also Riga, Greece at Latvia Institute forAlso Theoretical at and Albert Experimental Physics, Einstein Moscow,Also Center Russia at for Istanbul Fundamental Physics, Aydin Bern, University, Istanbul, Switzerland Turkey Also at California InstituteAlso of at Technology, Pasadena, Budker U.S.A. Institute ofAlso Nuclear at Physics, Faculty of Novosibirsk, Physics, Russia Also University at of INFN Belgrade, Sezione Belgrade,Also di Serbia Roma; at Sapienza University Universitàdi of Roma, Belgrade, Roma, Italy Faculty of Physics and Vinca Institute of Nuclear Sciences, Also at Institute forNow Nuclear Research, Moscow, at Russia National ResearchAlso at Nuclear St. Petersburg StateAlso University Polytechnical at University, University St. ’Moscow of Petersburg, Florida,Also Russia Gainesville, at Engineering U.S.A. P.N. Lebedev Physics Physical Institute, Moscow, Insti- Russia Also at Laboratori NazionaliAlso di at Legnaro Purdue dell’INFN, University, Legnaro, WestAlso Italy Lafayette, at U.S.A. International Islamic UniversityAlso of at Malaysia, Malaysian Kuala Nuclear Lumpur, Agency,Also MOSTI, Malaysia at Kajang, Consejo Malaysia NacionalAlso de at Ciencia Warsaw y University Tecnolog´ıa,Mexico city, of Mexico Technology, Institute of Electronic Systems, Warsaw, Poland Also at University of Ruhuna,Also Matara, at Sri Isfahan Lanka University ofAlso Technology, at Isfahan, Yazd Iran University, Yazd,Also Iran at Plasma Physics ResearchAlso Center, at Universitàdegli Studi Science di and Siena, Siena, Research Italy Branch, Islamic Azad Also at MTA-ELTE LendületCMS Particle andAlso Nuclear at Physics Institute of Group,Also Physics, EötvösLoránd University at of Indian Debrecen, Institute Debrecen,Also of Hungary at Technology Bhubaneswar, Institute Bhubaneswar, of India Also Physics, Bhubaneswar, at India University of Visva-Bharati, Santiniketan, India Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary 56: 57: 58: 59: 60: 50: 51: 52: 53: 54: 55: 44: 45: 46: 47: 48: 49: 39: 40: 41: 42: 43: 34: 35: 36: 37: 38: 28: 29: 30: 31: 32: 33: 23: 24: 25: 26: 27: 18: 19: 20: 21: 22: 17: JHEP07(2017)001 – 46 – Kingdom Also at Texas A&M UniversityAlso at at Qatar, Kyungpook Doha, National Qatar University, Daegu, Korea Also at Instituto deAlso Astrof´ısicade Canarias, at La Utah Laguna, Valley Spain University,Also Orem, at U.S.A. BEYKENT UNIVERSITY,Also Istanbul, Turkey at Erzincan University, Erzincan,Also Turkey at Mimar Sinan University, Istanbul, Istanbul, Turkey Also at School of Physics and Astronomy, University of Southampton, Southampton, United 67: 68: 62: 63: 64: 65: 66: 61: