Search for pair production of third-generation scalar leptoquarks decaying into a top quark and a τ-lepton in pp collisions at \sqrt{s}=13 TeV with the ATLAS detector
EEUROPEAN ORGANISATION FOR NUCLEAR RESEARCH (CERN)
Submitted to: JHEP CERN-EP-2020-24128th January 2021
Search for pair production of third-generationscalar leptoquarks decaying into a top quark and a 𝝉 -lepton in 𝒑 𝒑 collisions at √ 𝒔 =
13 TeV with the
ATLAS detector
The ATLAS Collaboration
A search for pair production of third-generation scalar leptoquarks decaying into a top quarkand a 𝜏 -lepton is presented. The search is based on a dataset of 𝑝 𝑝 collisions at √ 𝑠 =
13 TeVrecorded with the ATLAS detector during Run 2 of the Large Hadron Collider, correspondingto an integrated luminosity of 139 fb − . Events are selected if they have one light lepton(electron or muon) and at least one hadronically decaying 𝜏 -lepton, or at least two lightleptons. In addition, two or more jets, at least one of which must be identified as containing 𝑏 -hadrons, are required. Six final states, defined by the multiplicity and flavour of leptoncandidates, are considered in the analysis. Each of them is split into multiple event categoriesto simultaneously search for the signal and constrain several leading backgrounds. Thesignal-rich event categories require at least one hadronically decaying 𝜏 -lepton candidate andexploit the presence of energetic final-state objects, which is characteristic of signal events. Nosignificant excess above the Standard Model expectation is observed in any of the consideredevent categories, and 95% CL upper limits are set on the production cross section as a functionof the leptoquark mass, for different assumptions about the branching fractions into 𝑡𝜏 and 𝑏𝜈 .Scalar leptoquarks decaying exclusively into 𝑡𝜏 are excluded up to masses of 1 .
43 TeV while,for a branching fraction of 50% into 𝑡𝜏 , the lower mass limit is 1 .
22 TeV. © a r X i v : . [ h e p - e x ] J a n ontents The similarities between the quark and lepton sectors of the Standard Model (SM), which exhibit asimilar structure, raise the possibility of an existing underlying symmetry connecting the two sectors.Consequently, many extensions of the Standard Model of particle physics contain leptoquarks (LQ) [1–7],hypothetical particles that carry non-zero baryon and lepton quantum numbers and are charged underall SM gauge groups. In particular, they are triplets with respect to the strong interaction, and havefractional electric charge. A LQ state can have either spin 0 (scalar LQ) or spin 1 (vector LQ), and onlythe former is considered in this paper. Because of their quantum numbers, LQs couple simultaneouslyto both quarks and leptons, enabling direct transitions between the two. Scalar LQs are assumed tocouple to the quark–lepton pair via a Yukawa interaction, with coupling constants that can vary acrossfermion generations, including the possibility of mixing between different quark and lepton generations.Consequently, scalar LQs can mediate processes that violate lepton flavour universality, and have beenproposed as an explanation for measurements of 𝐵 -meson decays that exhibit tantalising deviations fromSM predictions [8–14]. The assumption that LQs can only interact with leptons and quarks of the samegeneration follows the minimal Buchmüller–Rückl–Wyler (BRW) model [15], which is adopted in thispaper. The quark–lepton–LQ coupling is determined by two parameters: a model parameter 𝛽 and thecoupling parameter 𝜆 . Consequently, the coupling to the charged lepton is given by √ 𝛽𝜆 , while the couplingto the neutrino is given by √︁ − 𝛽𝜆 .In 𝑝 𝑝 collisions, LQs are mainly produced in pairs (LQLQ) via gluon–gluon fusion and quark–antiquarkannihilation, mediated by the strong interaction. There are also lepton-mediated 𝑡 - and 𝑢 -channel productionprocesses that depend on the unknown strength of the Yukawa interaction. However, their contribution canusually be neglected for values of 𝜆 (cid:46)
1, and particularly in the case of third-generation LQs (LQ ), asthey would require third-generation quarks in the initial state. The LQ pair-production cross section can2herefore, to a very good approximation, be taken to depend only on the assumed value of the LQ mass( 𝑚 LQ ) for a given LQ spin and centre-of-mass energy. Furthermore, it is assumed that the value of 𝜆 issuch that LQs have narrow decay widths of about 0.2% of 𝑚 LQ , so that on-shell production dominates.Single LQ production in association with a lepton is also possible, but the cross section depends on thestrength of the Yukawa interaction and it is not considered in this paper.The most recent searches from the ATLAS and CMS experiments for pair production of LQs coupling tothird-generation quarks and leptons were performed using 36.1 fb − of 𝑝 𝑝 collisions at √ 𝑠 =
13 TeV atthe Large Hadron Collider (LHC). The ATLAS results, many of which are reinterpretations of previouslypublished searches for supersymmetric particles, are summarised in Ref. [16]. The different ATLASsearches are not combined statistically and the results are presented as a function of the LQ massand the branching ratio into charged leptons ( B ) for two different classes of LQ signals: up-type LQs(LQ u3 → 𝑏𝜏 / 𝑡𝜈 ) and down-type LQs (LQ d3 → 𝑡𝜏 / 𝑏𝜈 ), which have different electric charges. Both types ofLQs are excluded for masses below 800 GeV independently of B . For the limiting cases of B = B = u3 (LQ d3 ). Searchesfor LQs with off-diagonal couplings to third-generation quarks and first- or second-generation leptonshave also been performed [17, 18]. The CMS experiment has performed searches for leptoquarks [19–23],obtaining similar mass exclusions.This paper presents a dedicated search for the pair production of LQ d3 in the 𝑡𝜏𝑡𝜏 decay mode. Thissearch uses the full Run 2 dataset of 𝑝 𝑝 collisions at √ 𝑠 =
13 TeV recorded with the ATLAS detector andcorresponding to an integrated luminosity of 139 fb − . Events are selected if they have at least one lightlepton (electron or muon, denoted by ℓ ) and at least one hadronically decaying 𝜏 -lepton, or at least two lightleptons. In addition, two or more jets, at least one of which must be identified as containing 𝑏 -hadrons, arerequired. Six final states, defined by the multiplicity and flavour of lepton candidates, are considered in theanalysis. Each of them is split into multiple event categories. The most sensitive event categories requireat least one hadronically decaying 𝜏 -lepton candidate and exploit the presence of energetic final-stateobjects, which is characteristic of signal events. In those event categories the final discriminating variableused is the scalar sum of the transverse momenta of all selected leptons, the selected jets and the missingtransverse momentum; this variable peaks at much higher values for the signal than for the background.The main background contributions arise from top-quark–antitop-quark ( 𝑡 ¯ 𝑡 ) production with a jet or photonmisidentified as a light lepton or with a jet misidentified as a hadronically decaying 𝜏 -lepton, and fromSM processes yielding multiple leptons in the final state, such as 𝑡 ¯ 𝑡 production in association with avector boson or a Higgs boson, and diboson production. The rest of the event categories are designedto be enriched in the most relevant backgrounds. A maximum-likelihood fit is performed across eventcategories to search for the signal and constrain several leading backgrounds simultaneously. Given the lowbackground yields and good signal-to-background separation provided by the final discriminating variableused in the signal-rich event categories, the search sensitivity is determined by the limited number of dataevents rather than by the systematic uncertainties of the background estimation. The search is performed inthe LQ mass range between 500 GeV and 1600 GeV as a function of B .3 ATLAS detector
The ATLAS detector [24] at the LHC covers almost the entire solid angle around the collision point, andconsists of an inner tracking detector surrounded by a thin superconducting solenoid producing a 2 T axialmagnetic field, electromagnetic and hadronic calorimeters, and a muon spectrometer (MS) incorporatingthree large toroidal magnet assemblies. The inner detector contains a high-granularity silicon pixel detector,including the insertable B-layer [25, 26], and a silicon microstrip tracker, together providing a precisereconstruction of tracks of charged particles in the pseudorapidity range | 𝜂 | < .
5. The inner detector alsoincludes a transition radiation tracker that provides tracking and electron identification information for | 𝜂 | < .
0. The calorimeter system covers the pseudorapidity range | 𝜂 | < .
9. Within the region | 𝜂 | < . | 𝜂 | < . | 𝜂 | < .
7, and two copper/LAr hadronicendcap calorimeters. The solid angle coverage is completed with forward copper/LAr and tungsten/LArcalorimeter modules optimised for electromagnetic and hadronic measurements, respectively. The muonspectrometer measures the trajectories of muons with | 𝜂 | < . | 𝜂 | < .
4. A two-level trigger system [27], consisting of a hardware-based first-level triggerfollowed by a software-based high-level trigger (HLT), is used to reduce the event rate to a maximum ofaround 1 kHz for offline storage.
A dataset of 𝑝 𝑝 collisions at √ 𝑠 =
13 TeV collected by the ATLAS experiment during 2015–2018 andcorresponding to an integrated luminosity of 139 fb − is used. The uncertainty in the integrated luminosityis 1.7% [28], obtained using the LUCID-2 detector [29] for the primary luminosity measurements. Thenumber of additional 𝑝 𝑝 interactions per bunch crossing (pile-up) in this dataset ranges from about 8 to70, with an average of 34. Only events recorded under stable beam conditions and for which all detectorsubsystems were known to be in a good operating condition are used. The trigger requirements arediscussed in Section 5.Monte Carlo (MC) simulation samples were produced for the different signal and background processesusing the configurations shown in Table 1, with the samples used to estimate the systematic uncertainties inparentheses. All simulated samples, except those produced with the Sherpa 2.2.1 [30] event generator,utilised EvtGen 1.2.0 [31] to model the decays of heavy-flavour hadrons. Pile-up was modelled using eventsfrom minimum-bias interactions generated with Pythia 8.186 [32] with the A3 set of tuned parameters [33](referred to as the ‘tune’), and overlaid onto the simulated hard-scatter events according to the luminosityprofile of the recorded data. The generated events were processed through a simulation [34] of the ATLAS ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP) in the centre of the detector.The 𝑥 -axis points from the IP to the centre of the LHC ring, the 𝑦 -axis points upward, and the 𝑧 -axis coincides with the axis ofthe beam pipe. Polar coordinates ( 𝑟 , 𝜙 ) are used in the transverse plane, 𝜙 being the azimuthal angle around the beam pipe.The pseudorapidity is defined in terms of the polar angle 𝜃 as 𝜂 = − ln tan ( 𝜃 / ) . Angular distance is measured in units of Δ 𝑅 ≡ √︁ ( Δ 𝜂 ) + ( Δ 𝜙 ) . 𝑝 𝑝 collisions. Corrections were applied to the simulated events so that the particle candidates’selection efficiencies, energy scales and energy resolutions match those determined from data controlsamples. The simulated samples are normalised to their cross sections, and computed to the highest orderavailable in perturbation theory.Samples used to model the LQ d3 signal were generated at next-to-leading order (NLO) in QCD withMadGraph5_aMC@NLO 2.6.0 [36], using the LQ model of Ref. [37] that adds parton showers to previousfixed-order NLO QCD calculations [38, 39], and the NNPDF 3.0 NLO [40] parton distribution function(PDF) set. The parton shower (PS) and hadronisation were modelled using Pythia 8.230 [32] with theA14 tune [41]. MadSpin [42] was used for the decay of the scalar LQ d3 . The coupling parameter 𝜆 was setto 0.3, resulting in the LQ d3 width of about 0 .
2% of its mass [43, 44]. The charge of LQ d3 is set to 1 / 𝑒 ,implying that it decays into either a 𝑡𝜏 or 𝑏𝜈 pair. Most signal samples were produced for a model parameterof 𝛽 = .
5, which corresponds to identical amplitudes for the LQ d3 → 𝑡𝜏 and LQ d3 → 𝑏𝜈 processes and,therefore, similar branching ratios for the two decay modes. The signal samples had a mixture of final statesso that desired branching ratios B were obtained by reweighting the samples based on generator information.These samples were produced for LQ d3 mass values between 500 GeV and 800 GeV, in steps of 100 GeV,and between 800 GeV and 1 . 𝛽 = d3 mass values between 800 GeV and 1 . 𝛼 S , and the PDFs. The crosssections do not include lepton 𝑡 -channel contributions, which are neglected in Ref. [37] and may lead tocorrections at the percent level [49]. Uncertainties affecting the modelling of the signal acceptance wereestimated from the envelope of independent pairs of renormalisation and factorisation scale variations by afactor of 0.5 and 2, by propagating the PDF+ 𝛼 S uncertainties following the PDF4LHC15 prescription [50],and by considering two alternative samples generated with settings that increase or decrease the amount ofQCD radiation [51].Samples used to model the 𝑡 ¯ 𝑡 and single-top-quark background were generated with the NLO generatorPowheg-Box v2 [52–57] using the NNPDF3.0 NLO PDF set. In the 𝑡 ¯ 𝑡 sample, the Powheg-Box modelparameter ℎ damp , which controls matrix element (ME) to PS matching and effectively regulates the high- 𝑝 T radiation, was set to 1.5 times the top-quark mass. Overlaps between the 𝑡 ¯ 𝑡 and 𝑡𝑊 final states wereavoided by using the diagram removal scheme [58]. The parton shower, hadronisation, and underlyingevent were modelled by Pythia 8.210 with the NNPDF2.3 LO [59] PDF set in combination with the A14tune. Uncertainties affecting the modelling of the acceptance and event kinematics of 𝑡 ¯ 𝑡 events due tothe choice of PS and hadronisation model, the NLO ME-to-PS matching, and the effects of initial- andfinal-state QCD radiation [60] are estimated by comparing the nominal predictions with those obtainedusing the alternative simulated samples (see Table 1). The 𝑡 ¯ 𝑡 and single-top-quark simulated samples arenormalised to the cross sections calculated at NNLO in QCD including the resummation of NNLL softgluon terms [61–64].Samples for 𝑡 ¯ 𝑡𝑊 and 𝑡 ¯ 𝑡𝐻 production were generated using the NLO generators Sherpa 2.2.1 and Powheg-Box v2 [65], respectively, with the NNPDF3.0 NLO PDF set. In the case of the 𝑡 ¯ 𝑡𝑊 sample, the ME wascalculated for up to one additional parton at NLO and up to two partons at LO using Comix [66] andOpenLoops [67] and merged with the Sherpa parton shower [68] using the MePs@Nlo prescription [69].5he generated 𝑡 ¯ 𝑡𝐻 events were interfaced to Pythia 8.2 and the A14 tune, and with Higgs decay branchingratios calculated using Hdecay [70, 71]. The cross section used to normalise the 𝑡 ¯ 𝑡𝑊 ( 𝑡 ¯ 𝑡𝐻 ) sampleis 601 (507) fb, which is computed at NLO in QCD with NLO electroweak corrections [36, 70, 72–78]. Uncertainties in the 𝑡 ¯ 𝑡𝑊 ( 𝑡 ¯ 𝑡𝐻 ) cross section include ±
12% ( + . − . ), estimated by varying the QCDfactorisation and renormalisation scales, and ±
4% ( ± . 𝛼 S variations, estimated using thePDF4LHC15 prescription. Uncertainties affecting the modelling of the acceptance and event kinematicsdue to the choice of parton shower and hadronisation model are estimated by comparing the nominalpredictions with those obtained using the alternative simulated samples (see Table 1). In the case of the 𝑡 ¯ 𝑡𝑊 sample, an additional uncertainty on the modelling of the acceptance and event kinematics is consideredfrom renormalisation and factorisation scale variations by a factor of 0.5 and 2, relative to the nominalscales.The samples for 𝑡 ¯ 𝑡 ( 𝑍 / 𝛾 ∗ ) and diboson ( 𝑉𝑉 ) production follow Ref. [51, 85]. For 𝑡 ¯ 𝑡 ( 𝑍 / 𝛾 ∗ ) , the inclusive 𝑡 ¯ 𝑡𝑙 + 𝑙 − ME is computed, including off-shell 𝑍 and 𝛾 ∗ contributions with 𝑚 ( ℓ + ℓ − ) > 𝑡 ¯ 𝑡 sample, including rare 𝑡 → 𝑊 𝑏𝛾 ∗ (→ ℓ + ℓ − ) radiative decays and requiring 𝑚 ( ℓ + ℓ − ) > 𝑡 ¯ 𝑡 → 𝑊 + 𝑏𝑊 − ¯ 𝑏ℓ + ℓ − sample, was added to the 𝑡 ¯ 𝑡 ( 𝑍 / 𝛾 ∗ ) sample and together these form the 𝑡 ¯ 𝑡 ( 𝑍 / 𝛾 ∗ ) (high mass) sample. The contribution from internal photon conversions ( 𝛾 ∗ → ℓ + ℓ − ) with 𝑚 ( ℓ + ℓ − ) < 𝑡 ¯ 𝑡 sample and is referred toas 𝑡 ¯ 𝑡𝛾 ∗ (low mass). Care was taken to avoid both double-counting of contributions and uncovered regionsof phase space when combining the different simulated samples. The cross section for 𝑡 ¯ 𝑡 ( 𝑍 / 𝛾 ∗ → ℓ + ℓ − ) production is 167 fb, computed at NLO in QCD and electroweak couplings [36, 78]. The uncertaintiesfrom QCD scale and PDF+ 𝛼 S variations are ±
12% and ±
4% respectively. The LO cross section from the 𝑡 ¯ 𝑡 → 𝑊 + 𝑏𝑊 − ¯ 𝑏ℓ + ℓ − sample is scaled by a factor of 1.54, based on comparisons between the NNLO+NLLand LO cross sections for 𝑡 ¯ 𝑡 production [86–90], and assigned a 50% normalisation uncertainty, to coverpossible residual effects in the predicted yield due to the simplified normalisation procedure used and/or thefact that the event kinematics were modelled using a LO simulation. Uncertainties affecting the modellingof the acceptance and event kinematics for the 𝑡 ¯ 𝑡 ( 𝑍 / 𝛾 ∗ ) sample include the same QCD scale and tunevariations as considered for the 𝑡 ¯ 𝑡𝐻 sample, PDF variations using the PDF4LHC15 prescription, and acomparison with an alternative LO multileg sample (see Table 1). Diboson backgrounds are normalisedusing the cross sections computed by Sherpa 2.2.2. To cover possible mismodellings in the associatedheavy-flavour production predicted by the parton shower, a 50% normalisation uncertainty is assigned andtreated as correlated between the 𝑊 𝑍 + ≥ 𝑐 and 𝑊 𝑍 + ≥ 𝑏 subprocesses. The remaining rare backgroundcontributions listed in Table 1 are normalised using their NLO theoretical cross sections, except for the 𝑡 ¯ 𝑡𝑡 process, for which a LO cross section is used. To account for the fact that many of these processes arepredicted using a LO simulation, and to cover possible mismodellings in the extreme kinematic regimeprobed by this search, a 50% normalisation uncertainty is assigned to all of them. Interaction vertices from the 𝑝 𝑝 collisions are reconstructed from at least two tracks with transversemomentum ( 𝑝 T ) larger than 500 MeV that are consistent with originating from the beam collision region inthe 𝑥 – 𝑦 plane. If more than one primary vertex candidate is found, the candidate for which the associatedtracks form the largest sum of squared 𝑝 T [91] is selected as the hard-scatter primary vertex.Electron candidates are reconstructed from energy clusters in the electromagnetic calorimeter that areassociated with inner-detector tracks [92]. They are required to satisfy 𝑝 T >
10 GeV and | 𝜂 cluster | < . able 1: The configurations used for event generation of signal and background processes. The samples used toestimate the systematic uncertainties are indicated in parentheses. 𝑉 refers to production of an electroweak boson ( 𝑊 or 𝑍 / 𝛾 ∗ ). The matrix element order refers to the order in the strong coupling constant of the perturbative calculation.If only one parton distribution function is shown, the same one is used for both the ME and parton shower generators;if two are shown, the first is used for the ME calculation and the second for the parton shower. Tune refers to theunderlying-event tune of the parton shower generator. MG5_aMC refers to MadGraph5_aMC@NLO 2.2, 2.3, or2.6; Pythia 6 refers to version 6.427 [79]; Pythia 8 refers to version 8.2; Herwig++ refers to version 2.7 [80];Herwig 7 refers to version 7.0.4 [81]; MePs@Nlo refers to the method used in Sherpa to match the matrix elementto the parton shower. All samples include leading-logarithm photon emission, either modelled by the parton showergenerator or by Photos [82]. The mass of the top quark ( 𝑚 𝑡 ) and SM Higgs boson were set to 172 . d3 LQ d3 MG5_aMC NLO Pythia 8 NNPDF3.0 NLO A14 𝑡 ¯ 𝑡 Powheg-Box NLO Pythia 8 NNPDF3.0 NLO/ A14NNPDF2.3 LO(Powheg-Box) (NLO) (Herwig 7) (NNPDF3.0 NLO/ (H7-UE-MMHT)MMHT2014 LO )(MG5_aMC) (NLO) (Pythia 8) (NNPDF3.0 NLO/ (A14)NNPDF2.3 LO)(Powheg-Box (NLO) (Pythia 8) (NNPDF3.0 NLO/ (A14Var3CUp [41]) ℎ damp = 𝑚 𝑡 ) NNPDF2.3 LO ) 𝑡 ¯ 𝑡𝑊 Sherpa 2.2.1 MePs@Nlo Sherpa NNPDF3.0 NNLO Sherpa default(MG5_aMC) (NLO) (Pythia 8) (NNPDF3.0 NLO/ (A14)NNPDF2.3 LO) 𝑡 ¯ 𝑡 ( 𝑍 / 𝛾 ∗ → ℓ + ℓ − ) MG5_aMC NLO Pythia 8 NNPDF3.0 NLO/ A14NNPDF2.3 LO(Sherpa 2.2.0) (LO multileg) (Sherpa) (NNPDF3.0 NLO) (Sherpa default) 𝑡 ¯ 𝑡 → 𝑊 + 𝑏𝑊 − ¯ 𝑏ℓ + ℓ − MG5_aMC LO Pythia 8 NNPDF3.0 LO A14 𝑡 ¯ 𝑡𝐻 Powheg-Box NLO Pythia 8 NNPDF3.0 NLO / A14NNPDF2.3 LO(Powheg-Box) (NLO) (Herwig 7) (NNPDF3.0 NLO/ (H7-UE-MMHT)MMHT2014 LO [83])Single top Powheg-Box NLO Pythia 8 NNPDF3.0 NLO/ A14( 𝑡 -, 𝑊𝑡 -, 𝑠 -channel) NNPDF2.3 LO 𝑡 ( 𝑍 / 𝛾 ∗ ) MG5_aMC LO Pythia 6 CTEQ6L1 Perugia2012 [84] 𝑡𝑊 ( 𝑍 / 𝛾 ∗ ) MG5_aMC NLO Pythia 8 NNPDF2.3 LO A14 𝑡 ¯ 𝑡𝑡 , 𝑡 ¯ 𝑡𝑡 ¯ 𝑡 MG5_aMC LO Pythia 8 NNPDF2.3 LO A14 𝑡 ¯ 𝑡𝑊 + 𝑊 − MG5_aMC LO Pythia 8 NNPDF2.3 LO A14 𝑉𝑉 , 𝑞𝑞𝑉𝑉 , 𝑉𝑉𝑉
Sherpa 2.2.2 MePs@Nlo Sherpa NNPDF3.0 NNLO Sherpa default
𝑉 𝐻
Pythia 8 LO Pythia 8 NNPDF2.3 LO A14 𝑊 +jets Sherpa 2.2.1 MePs@Nlo Sherpa NNPDF3.0 NLO Sherpa default 𝑍 +jets Sherpa 2.2.1 MePs@Nlo Sherpa NNPDF3.0 NLO Sherpa default excluding the transition region between the endcap and barrel calorimeters (1 . < | 𝜂 cluster | < . 𝑝 T >
10 GeVand | 𝜂 | < .
5. Loose and medium muon identification working points are used [95]. Medium muoncandidates with 𝑝 T >
800 GeV are in addition required to have hits in at least three MS stations (referred toas the ‘high- 𝑝 T working point’), in order to maximise the momentum resolution for the muon track andthus suppress backgrounds with high- 𝑝 T muons arising from momentum mismeasurements.Electron (muon) candidates are matched to the primary vertex by requiring that the significance of theirtransverse impact parameter, 𝑑 , satisfies | 𝑑 / 𝜎 ( 𝑑 )| < ( ) , where 𝜎 ( 𝑑 ) is the measured uncertainty in 𝑑 , and by requiring that their longitudinal impact parameter, 𝑧 , satisfies | 𝑧 sin 𝜃 | < . 𝜃 is the track’s polar angle. To further suppress leptons from heavy-flavour hadron decays, misidentifiedjets, or photon conversions (collectively referred to as ‘non-prompt leptons’), lepton candidates are alsorequired to be isolated in the tracker and in the calorimeter. A track-based lepton isolation criterion isdefined by calculating the quantity 𝐼 𝑅 = (cid:205) 𝑝 trkT , where the scalar sum includes all tracks (excluding thelepton candidate itself) within the cone defined by Δ 𝑅 < 𝑅 cut around the direction of the lepton. The valueof 𝑅 cut is the smaller of 𝑟 min and 10 GeV / 𝑝 ℓ T , where 𝑟 min is set to 0.2 (0.3) for electron (muon) candidatesand where 𝑝 ℓ T is the lepton 𝑝 T . All lepton candidates must satisfy 𝐼 𝑅 / 𝑝 ℓ T < .
15. Additionally, electrons(muons) are required to satisfy a calorimeter-based isolation criterion: the sum of the transverse energywithin a cone of size Δ 𝑅 = . 𝑝 ℓ T . Muons are required to beseparated by Δ 𝑅 > . Δ 𝑅 = . 𝑝 T is considered. An electron lying within Δ 𝑅 = . 𝑏 -tagging discriminant (see description below) referred to as the non-promptlepton BDT [96]. The efficiency at the chosen working point for muons (electrons) that satisfy thecalorimeter- and track-based isolation criteria is about 80% (65%) for 𝑝 T ∼
20 GeV and reaches a plateauof 95% (90%) at 𝑝 T ∼
45 GeV. The corresponding rejection factor against leptons from the decay of 𝑏 -hadrons is about 3.5 (10), after resolving ambiguities between overlapping reconstructed objects. VeryTight muon candidates are Tight muons that pass the non-prompt lepton BDT requirement (referred to The rejection factor is defined as the reciprocal of the efficiency. able 2: Summary of requirements applied to define Loose (L), Tight (T), and Very Tight (T*) light leptons. Thequality cuts for tight muon identification depend on the transverse momentum of the muon candidates. 𝑒 𝜇 L T T* L T T*Identification loose tight tight loose medium mediumor high- 𝑝 T or high- 𝑝 T Isolation Yes YesNon-prompt-lepton veto No No Yes No No YesElectron charge-misassignment veto No No Yes —Electron material-conversion veto No No Yes —Electron internal-conversion veto No No Yes — | 𝑑 |/ 𝜎 𝑑 < < | 𝑧 sin 𝜃 | [mm] < . < . as the ‘non-prompt-lepton veto’). To further suppress material conversions, additional requirements onthe associated track 𝑝 T and on the ratio of the electron’s calorimeter energy to its track’s momentumare applied to tight electrons. Tight electrons with incorrect charge assignment are rejected using aBDT discriminant based on calorimeter and tracking quantities [92]. An efficiency of 88% for isolatedelectrons with correct charge assignment is obtained, with a rejection factor of ∼ 𝑟 >
20 mm that includes the track associated with the electron. The invariant mass of the associated track and the closest (in Δ 𝜂 ) opposite-charge track reconstructed in thesilicon detector, calculated at the conversion vertex, is required to be <
100 MeV. Internal conversioncandidates, which correspond to the internal photon conversions (see Section 3), are required to fail therequirements for material conversions, and the di-track invariant mass, this time calculated at the primaryvertex, is also required to be <
100 MeV. Therefore, Very Tight electron candidates are Tight electronsthat satisfy the non-prompt-lepton veto, the charge-misassignment veto, the internal-conversion veto, andthe material-conversion veto requirements, and have | 𝜂 | <
2. The last requirement rejects a small fractionof electrons with a large charge misassignment rate because of the limited number of hits used in the trackreconstruction.Hadronically decaying 𝜏 -lepton candidates ( 𝜏 had ) are reconstructed from energy clusters in the calorimetersand associated inner-detector tracks [97, 98]. They are required to have either one or three associatedtracks (referred to as ‘one-prong’ and ‘three-prong’ 𝜏 had candidates, respectively), with a total charge of ± 𝑒 . The candidates are required to satisfy 𝑝 T >
25 GeV and | 𝜂 | < .
5, excluding the EM calorimeter’stransition region, and to originate from the primary vertex. A recurrent neural network discriminant usingcalorimeter- and tracking-based variables is used to identify real 𝜏 had candidates and reject jet backgrounds(referred to as ‘fake 𝜏 had candidates’) [99]. Loose and medium identification working points are used,and the selected 𝜏 had candidates are referred to as ‘Loose’ and ‘Medium’, respectively. The loose workingpoint has a target efficiency of 85% (75%) for one-prong (three-prong) 𝜏 had candidates, with an expectedrejection factor against light-jets of 21 (90). The corresponding efficiencies and rejections for the mediumworking point are 75% (60%) and 35 (240) for one-prong (three-prong) 𝜏 had candidates, respectively.Electrons that are reconstructed as one-prong 𝜏 had candidates are removed using a BDT with an efficiency(rejection factor) of 95% (30–100) for real (fake) 𝜏 had candidates depending on the 𝑝 T . Additionally, 𝜏 had The beampipe and insertable B-layer inner radii are 23.5 mm and 33 mm, respectively. Δ 𝑅 > . 𝜏 had reconstruction and identification efficiencies and the 𝜏 had energy scale in the simulation are calibratedto those measured in a data control sample of 𝑍 → 𝜏 + 𝜏 − events [100], and the associated uncertaintiesare considered in the analysis. The uncertainty in the 𝜏 had identification efficiency is split into eightuncorrelated components, corresponding to different 𝜏 had 𝑝 T ranges and separately for one-prong andthree-prong candidates. It is approximately 2.5% (3.0%) for one-prong (three-prong) 𝜏 had candidates with 𝑝 T <
300 GeV, and 3.5% (6.5%) for 𝑝 T ≥
300 GeV. The uncertainty in the 𝜏 had energy scale is about 1.2%(3.0%) for one-prong (three-prong) 𝜏 had candidates [100], and is split into eight independent components.An additional correction and associated uncertainties are estimated for the probability of misidentificationof electrons as 𝜏 had candidates using a data control sample of 𝑍 → 𝑒 + 𝑒 − events.The inputs for jet reconstruction are built by combining measurements from both the tracker and thecalorimeter using the particle flow (PFlow) algorithm [101, 102]. Jet candidates are reconstructed fromsuch PFlow objects using the anti- 𝑘 𝑡 algorithm with a radius parameter 𝑅 = . 𝑍 +jets, 𝛾 +jets and multijet events [102]. Jets are required to satisfy 𝑝 T >
25 GeVand | 𝜂 | < .
5. A jet-vertex tagger (JVT) is used to remove jets associated with pile-up vertices and having 𝑝 T <
60 GeV and | 𝜂 | < . Δ 𝑅 = . 𝜏 had candidate arerejected. Uncertainties associated with jets arise from the JES and JER, and the efficiency to pass the JVTrequirement. The largest contribution results from the JES, whose uncertainty dependence on jet 𝑝 T and 𝜂 ,jet flavour, and pile-up treatment is split into 27 uncorrelated components that are treated independently inthe analysis [102]. The total JES uncertainty varies from 1% to 4% depending on the jet 𝑝 T . A total ofseven uncorrelated uncertainty components affecting the JER are also considered.Jets containing 𝑏 -hadrons are identified ( 𝑏 -tagged) via an algorithm [107, 108] that uses multivariatetechniques to combine information about the impact parameters of displaced tracks and the topologicalproperties of secondary and tertiary decay vertices reconstructed within the jet. For each jet, a valuefor the multivariate 𝑏 -tagging discriminant is calculated. A jet is considered 𝑏 -tagged if this value isabove the threshold corresponding to an average 77% efficiency to tag a 𝑏 -quark jet, with a light-jet rejection factor of about 140, a charm-jet ( 𝑐 -jet) rejection factor of about 4, and a 𝜏 had -jet rejection factorof about 17, as determined for jets with 𝑝 T >
20 GeV and | 𝜂 | < . 𝑡 ¯ 𝑡 events. Correctionfactors derived from dedicated calibration samples enriched in 𝑏 -jets, 𝑐 -jets, or light jets, are appliedto the simulated samples [107, 109, 110]. In the case of 𝜏 had -jets, for which no dedicated calibrationsample exists, the correction factors derived for 𝑐 -jets are used. Uncertainties in these corrections includea total of nine independent sources affecting 𝑏 -jets and five independent sources affecting 𝑐 -jets. Sixsources of uncertainty affecting light jets are also considered. An additional uncertainty is included for theextrapolation of these corrections to jets with 𝑝 T beyond the kinematic reach of the data calibration samplesused ( 𝑝 T >
300 GeV for 𝑏 - and 𝑐 -jets, and 𝑝 T >
750 GeV for light jets); it is taken to be correlated amongthe three jet flavours. Finally, an uncertainty related to the application of 𝑐 -jet scale factors to 𝜏 had -jets isconsidered. The approximate relative size of the 𝑏 -tagging efficiency uncertainty is 2% for 𝑏 -jets, 10% for 𝑐 -jets and 𝜏 had -jets, and 30% for light jets.The missing transverse momentum (cid:174) 𝑝 missT (with magnitude 𝐸 missT ) is defined as the negative vector sum ofthe 𝑝 T of all selected and calibrated objects in the event, including a term to account for momentum fromsoft particles in the event that are not associated with any of the selected objects [111]. This soft term is ‘Light jet’ refers to a jet originating from the hadronisation of a light quark ( 𝑢 , 𝑑 , 𝑠 ) or a gluon. (cid:174) 𝑝 missT . Additional uncertainties originating from the modelling ofthe underlying event, in particular its impact on the 𝑝 T scale and resolution of unclustered energy, arenegligible. The search discussed in this paper targets LQ d3 pair production in the 𝑡𝜏𝑡𝜏 final state, thus being particularlysensitive to high values of B . In this decay mode, there is a high probability that the final state contains atleast one light lepton from a semileptonic top-quark decay or a leptonic 𝜏 -lepton decay, which is used totrigger the event and to help suppress multijet backgrounds. The presence of additional 𝜏 had candidatesand/or additional light leptons is exploited to further reduce SM backgrounds and improve the searchsensitivity. The final state of interest also contains two energetic 𝑏 -jets, and may contain additional light jetsfrom initial- or final-state radiation and/or from a hadronically decaying 𝑊 boson in one of the top-quarkdecays. The multiple sources of leptons in the event motivate the definition of different analysis channelsdepending on the multiplicity of light leptons, the multiplicity of 𝜏 had candidates, and the electric chargesof light leptons (see Section 5.1). The analysis channels are subdivided into different event categories (seeSection 5.2) so that a maximum-likelihood fit is performed across event categories to search for the signaland constrain several leading backgrounds simultaneously. The requirement of multiple leptons in theevent implies the presence of multiple neutrinos, which makes the kinematic reconstruction of the topquarks and consequently of the LQ invariant mass difficult. Nevertheless, the decay of a pair of massiveLQs results in energetic final-state objects, which is exploited in the most sensitive analysis channels, bothin optimising the event selection in the different categories considered and in defining a powerful eventvariable used in the statistical analysis to discriminate the signal from the background. Further details ofthe search strategy are provided in the following sections. The events used in the analysis are selected with high efficiency using single-lepton and dilepton triggers [27],which use electron and muon signatures. Single-lepton triggers with low 𝑝 T threshold and lepton isolationrequirements are combined in a logical OR with higher-threshold triggers without isolation requirements togive maximum efficiency. Single-electron triggers with a 𝑝 T threshold of 24 (26) GeV in the 2015 (2016,2017 and 2018) data-taking period(s) and isolation requirements are used along with triggers with a 60 GeVthreshold and no isolation requirement, and with a 120 (140) GeV threshold with looser identificationcriteria. For single-muon triggers, the lowest 𝑝 T threshold is 20 (26) GeV in 2015 (2016–2018), while thehigher 𝑝 T threshold is 50 GeV for all periods. The dielectron triggers require two electrons that satisfyloose identification criteria with different 𝑝 T thresholds: 12 GeV in 2015, 17 GeV in 2016, and 24 GeVin 2017–2018 . Dimuon triggers utilise asymmetric 𝑝 T thresholds for leading (subleading) muons: 18(8) GeV in 2015 and 22 (8) GeV in 2016–2018. An electron+muon trigger requires events to have anelectron candidate satisfying loose identification with a 17 GeV threshold and a muon candidate with a14 GeV threshold for all periods.Events selected by the trigger are required to satisfy basic preselection requirements. They must haveat least one primary vertex candidate. Events are required to contain either one light lepton and at least11ne 𝜏 had candidate, or at least two light leptons. At this stage, the light leptons and 𝜏 had candidatessatisfy the Loose selection criteria (see Section 4) and have 𝑝 T >
10 GeV and 𝑝 T >
25 GeV, respectively.Furthermore, the leading light lepton in the event is required to have 𝑝 T >
25 GeV. Events with one lightlepton must have been selected by a single-lepton trigger, whereas events with at least two light leptonsare required to be selected by a logical OR of the single-lepton and dilepton triggers. The selected lightleptons are required to match, with Δ 𝑅 < .
15, the corresponding leptons reconstructed by the triggerand to have a 𝑝 T exceeding the trigger 𝑝 T threshold by 1 GeV or 2 GeV (depending on the lepton trigger,lepton multiplicity criteria, and data-taking conditions) besides the 25 GeV requirement for the leadinglight leptons. In addition, two or more jets, at least one of which is 𝑏 -tagged, are required. The triggerrequirement has an efficiency of about 85% (98%) for signal events with one light lepton (at least two lightleptons) satisfying the preselection requirements.Six final states, termed ‘channels’, are analysed, defined by the multiplicity and flavour of Loose leptoncandidates with the 𝑝 T requirements indicated above: • ℓ + ≥ 𝜏 : one light lepton and at least one 𝜏 had candidate; • ℓ OS+ ≥ 𝜏 : two opposite-charge (denoted by OS, standing for opposite-sign) light leptons and atleast one 𝜏 had candidate; • ℓ SS/3 ℓ + ≥ 𝜏 : two same-charge (denoted by SS, standing for same-sign) light leptons or three lightleptons, and at least one 𝜏 had candidate; • ℓ OS+0 𝜏 : two OS light leptons and no 𝜏 had candidates; • ℓ SS+0 𝜏 : two SS light leptons and no 𝜏 had candidates; • ℓ +0 𝜏 : three light leptons and no 𝜏 had candidates.The selection criteria are orthogonal to those of the other channels so that each event only contributes to asingle analysis channel. Finally, in all analysis channels the minimum 𝑝 T requirement on light leptons israised to 25 GeV. The analysis channels with no 𝜏 had candidates are used for the determination of particularbackgrounds, while those with at least one 𝜏 had candidate are in addition used to search for the signal. The channels are subdivided into different event categories optimised either to search for the signal (referredto as ‘signal regions’, or SR), to obtain improved background estimates (referred to as ‘control regions’, orCR), or to validate the estimated backgrounds (referred to as ‘validation regions’, or VR). In the optimisationof the SRs, different features of the LQ signal are exploited, such as the multiplicity of 𝜏 had candidates, thecharge configuration of reconstructed leptons and, especially, the difference in kinematics of final-stateobjects between signal and background. In particular, the effective mass ( 𝑚 eff ), defined as the scalar sum ofthe transverse momenta of all selected leptons, the selected jets and the missing transverse momentum, is apowerful discriminating variable between signal and background. Additional kinematic variables exploitedin the optimisation of the SRs include the 𝑝 T of 𝜏 had candidates, and different invariant mass variablesbased on dilepton pair combinations (e.g. the invariant mass of the two leading 𝜏 had candidates, 𝑚 𝜏𝜏 ). TheCRs are defined by inverting particular selections in order to provide background-rich samples that do notoverlap with the SRs. The VRs are defined to be kinematically closer to the SRs, and they do not overlapwith the other CRs and SRs. A total of 7 SRs, 18 CRs, and 6 VRs are considered, with their definitionsgiven below. For a LQ d3 signal with B =
1, the acceptance times efficiency within the seven SRs is found12o be about 10%, varying only slightly with the LQ d3 mass, with higher mass values resulting in higheracceptance times efficiency to pass the kinematic requirements.In the 1 ℓ + ≥ 𝜏 channel, events are required to have one Tight light lepton and, either one Medium 𝜏 had candidate and no additional Loose 𝜏 had candidates, or at least two Loose 𝜏 had candidates. A total of nineevent categories are defined, which are summarised in Table 3. They consist of two subcategories based onthe multiplicity of 𝜏 had candidates (1 or ≥ 𝜏 had candidate (OS or SS). The splitting between OSand SS events improves the sensitivity, since their background compositions and signal-to-backgroundratios are very different. For each of these subcategories, a CR, a VR, and a SR, are defined. All SRs requireone or two high- 𝑝 T 𝜏 had candidates, as appropriate, a requirement that provides significant backgroundsuppression, as illustrated in Figure 1(a). Further requirements are placed on additional kinematic variables,such as the invariant mass of the light lepton and the 𝜏 had candidate ( 𝑚 ℓ 𝜏 ) (see Figure 1(b)), used in the1 ℓ +1 𝜏 OS and 1 ℓ +1 𝜏 SS SRs, or 𝑚 𝜏𝜏 (see Figure 2(a)), used in the 1 ℓ + ≥ 𝜏 SR.In the 2 ℓ OS+ ≥ 𝜏 channel, events are required to have two OS light leptons satisfying the Tight selectioncriteria, and at least one Loose or Medium 𝜏 had candidate. A total of six event categories are defined,which are summarised in Table 4. Separate SRs and VRs are defined for events with one Medium 𝜏 had candidate (and no additional Loose 𝜏 had candidates) and at least two Loose 𝜏 had candidates. Backgroundswith resonant ℓ + ℓ − pairs from quarkonia or 𝑍 -boson decays are suppressed by requiring that the dileptoninvariant mass ( 𝑚 ℓℓ ) satisfies 𝑚 ℓℓ >
12 GeV and | 𝑚 ℓℓ − 𝑚 𝑍 | >
10 GeV, respectively, where 𝑚 𝑍 representsthe mass of the 𝑍 boson. The latter requirement is referred to as the ‘ 𝑍 -veto’. The event selections arefurther optimised based on the 𝑝 T of the leading 𝜏 had candidate ( 𝑝 𝜏 T , ) and the minimum invariant mass ofa light lepton and a 𝜏 had candidate ( 𝑚 min ℓ 𝜏 ) (see Figure 2(b)). In addition, two dedicated CRs are defined forevents with one Loose or Medium 𝜏 had candidate in order to estimate correction factors to apply to the jetmisidentification (also referred to as ‘fake’) rate in the simulation for both sets of 𝜏 had identification criteria.These CRs are enriched in 𝑍 +jets and dileptonic 𝑡 ¯ 𝑡 events, respectively, and do not take part of the finallikelihood fit. Further details of the fake- 𝜏 had background estimation can be found in Section 6.2.1.In the 2 ℓ SS/3 ℓ + ≥ 𝜏 channel, events are required to have either two light leptons with the same charge(2 ℓ SS) or three light leptons (3 ℓ ) with their charges adding up to ±
1. In addition, at least one Loose 𝜏 had candidate is required. Since two SS light leptons can originate from backgrounds with non-prompt leptons,photon conversions, and electron charge misassignment (QMisID), the two SS light leptons in the eventare required to satisfy the Very Tight selection criteria. In the case of 3 ℓ events, the light lepton that hasopposite charge to the SS lepton pair is required to satisfy the Tight selection criteria. In addition, it isrequired that any 𝑒 ± 𝑒 ± , 𝑒 + 𝑒 − or 𝜇 + 𝜇 − pair in the event satisfies 𝑚 ℓℓ >
12 GeV and | 𝑚 ℓℓ − 𝑚 𝑍 | >
10 GeV.Similarly, 3 ℓ events are required to satisfy | 𝑚 ℓ − 𝑚 𝑍 | >
10 GeV to eliminate potential backgrounds with 𝑍 → ℓ𝛾 ∗ → ℓ where one lepton has very low momentum and is not reconstructed. Selected events fallinto one of three event categories, two SRs and one VR, simply defined using 𝑝 𝜏 T , (see Table 5). Eventswith 𝑝 𝜏 T , >
225 GeV are assigned to the main signal region, SR-H (with the symbol “H” representing“High”), which is optimal for high LQ masses, while events with 125 ≤ 𝑝 𝜏 T , <
225 GeV fall into SR-L(with the symbol “L” standing for “Low”) and extend the sensitivity to lower LQ masses. The VR containsthe events with 25 ≤ 𝑝 𝜏 T , <
125 GeV.Finally, the 2 ℓ OS+0 𝜏 , 2 ℓ SS+0 𝜏 , and 3 ℓ +0 𝜏 channels require there be no 𝜏 had candidates and are primarilyused to improve the background modelling, as discussed in Section 6. Events in the 2 ℓ OS+0 𝜏 channel areselected by requiring an OS 𝑒𝜇 pair with both light leptons satisfying the Tight selection criteria and noadditional Loose light leptons, at least two jets, at least one 𝑏 -tagged jet, and no Loose 𝜏 had candidates. This13 able 3: Summary of event categories in the 1 ℓ + ≥ 𝜏 channel. All events are required to satisfy the preselectionrequirements. “T” denotes the Tight light-lepton selection criteria (see Table 2). The 𝑝 T of the leading and subleading 𝜏 had candidates are denoted by 𝑝 𝜏 T , and 𝑝 𝜏 T , , respectively. The transverse mass of the system formed by the selectedlight lepton and the missing transverse momentum is denoted by 𝑚 T ( ℓ, 𝐸 missT ) .1 ℓ +1 𝜏 OS 1 ℓ +1 𝜏 SS 1 ℓ + ≥ 𝜏 CR VR SR CR VR SR CR VR SR 𝑒 / 𝜇 selection T T T 𝑁 𝜏 had ≥ 𝑁 jets ≥ ≥ ≥ 𝜏 had ID Medium Medium Loose ℓ𝜏 had charge OS SS — 𝑝 𝜏 T , [GeV] ≥
50 50–150 ≥ ≥
50 50–150 ≥ ≥
50 50–100 ≥ 𝑝 𝜏 T , [GeV] — — ≥
25 25–50 ≥ 𝑁 𝑏 -jets ≥ ≥ ≥ ≥ ≥ ≥ 𝑚 ℓ𝜏 [GeV] — ≥
200 — — ≥
200 — 𝑚 T ( ℓ, 𝐸 missT ) [GeV] — — — ≥
100 — 𝑚 𝜏𝜏 [GeV] — — — ≥ 𝐸 missT [GeV] — ≥
80 — — ≥
50 — 𝑚 eff [GeV] < ≥ < ≥ < ≥ ℓ OS+ ≥ 𝜏 channel. All events are required to satisfy the preselectionrequirements. “T” denotes the Tight light-lepton selection criteria (see Table 2).2 ℓ OS+1 𝜏 ℓ OS+ ≥ 𝜏 CR 𝑍 CR 𝑡 ¯ 𝑡 VR SR VR SR 𝑒 / 𝜇 selection T T 𝑒 / 𝜇 combinations 𝑒𝑒 / 𝜇𝜇 𝑒𝜇 𝑒𝑒 / 𝜇𝜇 𝑒𝑒 / 𝜇𝜇 / 𝑒𝜇 𝑒𝑒 / 𝜇𝜇 / 𝑒𝜇𝑍 veto Inverted Yes Yes Yes Yes 𝑚 ℓℓ [GeV] > > 𝑁 𝜏 had ≥ 𝜏 had ID Loose/Medium Medium Loose 𝑝 𝜏 T , [GeV] ≥ ≥
25 25–150 ≥ ≥ ≥ 𝑚 min ℓ𝜏 [GeV] — — < ≥
100 — ≥ 𝑚 𝜏𝜏 [GeV] — <100 ≥ 𝑚 eff [GeV] — < selection provides a 𝑡 ¯ 𝑡 -rich control sample (denoted 𝑡 ¯ 𝑡 𝜏 CR) that does not take part of the final likelihoodfit, but that is used to derive corrections to improve the 𝑡 ¯ 𝑡 background modelling (see Section 6.1.1). Eventsin the 2 ℓ SS+0 𝜏 channel are selected by requiring two SS light leptons satisfying the Very Tight selectioncriteria, except for some event categories where the internal conversion (IntC) or material conversion (MatCor Mat Conv) vetoes are inverted. A total of eight event categories, all of which are CRs, are defined so asto be enriched in different backgrounds: 𝑡 ¯ 𝑡 with non-prompt electrons or muons, 𝑡 ¯ 𝑡𝑊 , internal conversions,and material conversions, (denoted by 2 ℓ tt(e) or 2 ℓ tt( 𝜇 ), 2 ℓ ttW, 2 ℓ IntC, and 2 ℓ MatC, respectively), whichare summarised in Table 6. The last two CRs select events with two SS light leptons containing at least oneelectron that satisfies the corresponding inverted conversion veto requirement. The 2 ℓ tt(e) and 2 ℓ tt( 𝜇 ) CRsselect events with a SS 𝑒𝑒 / 𝜇𝑒 pair and a SS 𝜇𝜇 / 𝑒𝜇 pair, respectively, where the first (second) lepton denotesthe leading (subleading) lepton in 𝑝 T . The definition of these CRs exploits the fact that in SS dilepton14 able 5: Summary of event categories in the 2 ℓ SS/3 ℓ + ≥ 𝜏 channel. All events are required to satisfy the preselectionrequirements. “T” and “T*” denote the Tight and Very Tight light-lepton selection criteria (see Table 2).2 ℓ SS/3 ℓ + ≥ 𝜏 VR SR-L SR-H 𝑒 / 𝜇 selection T* (2 ℓ SS)T*/T (3 ℓ ) 𝑍 veto Yes 𝑚 ℓℓ [GeV] > 𝑁 𝜏 had ≥ 𝜏 had ID Loose 𝑝 𝜏 T , [GeV] 25–125 125–225 ≥
200 400 600 800 1000 [GeV] τ T p − − − − −
10 110 F r a c t i on o f e v en t s / G e V = 13 TeV s ℓ +1 τ ATLAS
Simulation
Total BackgroundLQ (0.9 TeV)LQ (1.1 TeV)LQ (1.3 TeV) (a)
200 400 600 800 1000 m ℓ τ [GeV] F r a c t i on o f e v en t s / G e V = 13 TeV s ℓ +1 τ ATLAS
Simulation
Total BackgroundLQ (0.9 TeV)LQ (1.1 TeV)LQ (1.3 TeV) (b)
Figure 1: Comparison of the distribution of (a) the 𝑝 T of the 𝜏 had candidate ( 𝑝 𝜏 T ), and (b) the invariant mass of thelight lepton and the 𝜏 had candidate ( 𝑚 ℓ𝜏 ), between the total background (shaded histogram) and the LQ signal fordifferent mass values. The selection used corresponds to events in the 1 ℓ +1 𝜏 event category (a) after the preselectionrequirements, and (b) after applying the additional requirement of 𝑝 𝜏 T >
150 GeV. The last bin in each distributioncontains the overflow. events from 𝑡 ¯ 𝑡 production the subleading lepton in 𝑝 T is typically a non-prompt lepton. In addition, theevents are restricted to have two or three jets in order to suppress the contribution from 𝑡 ¯ 𝑡𝑊 production. Inthe case of the 2 ℓ ttW CR, no restriction is imposed on the light-lepton flavours, and the events are requiredto have at least four jets. The 2 ℓ tt(e), 2 ℓ tt( 𝜇 ), and 2 ℓ ttW CRs are further split according to the charge of thelight leptons ( ++ or −− ) in order to improve the discrimination between charge asymmetric and chargesymmetric backgrounds (dominated by 𝑡 ¯ 𝑡𝑊 and 𝑡 ¯ 𝑡 , respectively). Events in the 3 ℓ +0 𝜏 channel are selectedby requiring three light leptons satisfying the Tight or Very Tight selection criteria, with their chargesadding up to ±
1. A total of four CRs are defined, which are summarised in Table 7. Two CRs selectevents compatible with having a 𝑍 -boson candidate, but differing in their jet multiplicity requirements, inorder to provide samples enriched in diboson (denoted by 3 ℓ VV) and 𝑡 ¯ 𝑡 𝑍 backgrounds (denoted by 3 ℓ ttZ),respectively. Similarly to the 2 ℓ SS+0 𝜏 channel, two additional CRs are defined so as to be enriched in15
500 1000 1500 2000 m ττ [GeV] F r a c t i on o f e v en t s / G e V = 13 TeV s ℓ + ≥ τ ATLAS
Simulation
Total BackgroundLQ (0.9 TeV)LQ (1.1 TeV)LQ (1.3 TeV) (a) m min ℓ τ [GeV] F r a c t i on o f e v en t s / G e V = 13 TeV s ℓ OS +1 τ ATLAS
Simulation
Total BackgroundLQ (0.9 TeV)LQ (1.1 TeV)LQ (1.3 TeV) (b)
Figure 2: Comparison of the distribution of (a) the invariant mass of the two leading 𝜏 had candidates ( 𝑚 𝜏𝜏 ), and (b)the minimum invariant mass of a light lepton and a 𝜏 had candidate ( 𝑚 min ℓ𝜏 ), between the total background (shadedhistogram) and the LQ signal for different mass values. The selection used in (a) corresponds to events in the 1 ℓ + ≥ 𝜏 category after the requirements of 𝑝 𝜏 T , >
100 GeV and 𝑝 𝜏 T , >
50 GeV, whereas the selection used in (b) correspondsto events in the 2 ℓ OS+1 𝜏 category after the requirement of 𝑝 𝜏 T >
150 GeV. The last bin in each distribution containsthe overflow.Table 6: Summary of event categories in the 2 ℓ SS+0 𝜏 channel. All events are required to satisfy the preselectionrequirements. “T*” denotes the Very Tight light-lepton selection criteria (see Table 2). Events that belong to thett(e), tt( 𝜇 ), and ttW categories are further split into two CRs for ++ and −− charge events. IntC and MatC stand forinternal and material conversions, respectively. The first (second) light lepton quoted in a pair denotes the leading(subleading) lepton in 𝑝 T . Backgrounds with resonant 𝑒 + 𝑒 − pairs from quarkonia or 𝑍 -boson decays due to electroncharge misassignment are suppressed by requirements on the dielectron invariant mass ( 𝑚 𝑒𝑒 ).2 ℓ SS+0 𝜏 ℓ tt(e) ± ℓ tt( 𝜇 ) ± ℓ ttW ± ℓ IntC 2 ℓ MatC 𝑒 / 𝜇 selection T* 𝑒 / 𝜇 combination 𝑒𝑒 / 𝜇𝑒 𝜇𝜇 / 𝑒𝜇 𝑒𝑒 / 𝜇𝜇 / 𝑒𝜇 / 𝜇𝑒 𝑒𝑒 / 𝑒𝜇 / 𝜇𝑒 𝑒𝑒 / 𝑒𝜇 / 𝜇𝑒 Electron internal conversion veto Yes Yes Yes Inverted YesElectron material conversion veto Yes Yes Yes Yes Inverted 𝑁 jets ≥ ≥ ≥ 𝑍 veto Yes 𝑚 𝑒𝑒 [GeV] ≥ internal- and material-conversion backgrounds, respectively, by inverting the corresponding conversionveto requirement on one of the electrons belonging to the SS lepton pair.The 𝑚 eff distribution is used as the final discriminating variable in all SRs. It peaks at approximately 2 𝑚 LQ for signal events, and at lower values for the backgrounds, as illustrated in Figure 3. The overall rate andcomposition of the background varies across the different SRs, as illustrated in Figure 4. The dominantbackground in the 1 ℓ +1 𝜏 OS SR is 𝑡 ¯ 𝑡 production with both the light lepton and 𝜏 had candidate originating16 able 7: Summary of four CR categories in the 3 ℓ +0 𝜏 channel. All events are required to satisfy the preselectionrequirements. “T” and “T*” denote the Tight and Very Tight light-lepton selection criteria (see Table 2). IntC andMatC stand for internal and material conversions, respectively. Same-charge (opposite-charge) lepton pairs are alsoreferred to as same-sign (opposite-sign) with abbreviation SS (OS). The OS lepton (relative to the SS pair) is denoted ℓ , but is not necessarily the one with highest 𝑝 T ; the remaining SS leptons are denoted ℓ (closest in Δ 𝑅 to ℓ ) and ℓ (the remaining one). 3 ℓ +0 𝜏 ℓ VV 3 ℓ ttZ 3 ℓ IntC 3 ℓ MatC 𝑒 / 𝜇 selection T T T( ℓ ), T*( ℓ and ℓ ) T( ℓ ), T*( ℓ and ℓ )Electron internal conversion veto Yes Yes Inverted( ℓ or ℓ ) Yes( ℓ and ℓ )Electron material conversion veto Yes Yes Yes( ℓ and ℓ ) Inverted( ℓ or ℓ ) 𝑁 jets ≥ ≥ ≥ 𝑍 veto Inverted Inverted Yes Yes 𝑚 ℓℓ [GeV] ≥ [GeV] eff m F r a c t i on o f e v en t s / G e V = 13 TeV s ℓ + ≥ τ ATLAS
Simulation
Total BackgroundLQ (0.9 TeV)LQ (1.1 TeV)LQ (1.3 TeV) (a) [GeV] eff m F r a c t i on o f e v en t s / G e V = 13 TeV s ℓ SS /3 ℓ + ≥ τ ATLAS
Simulation
Total BackgroundLQ (0.9 TeV)LQ (1.1 TeV)LQ (1.3 TeV) (b)
Figure 3: Comparison of the 𝑚 eff distribution in (a) the 1 ℓ + ≥ 𝜏 SR, and (b) the 2 ℓ SS/3 ℓ + ≥ 𝜏 SR-H, between thetotal background (shaded histogram) and the LQ signal for different mass values. The last bin in each distributioncontains the overflow. from the 𝑊 boson decays. In contrast, the main background in the 1 ℓ +1 𝜏 SS SR is also 𝑡 ¯ 𝑡 production, butwith one jet misidentified as a 𝜏 had candidate (fake 𝜏 had ), one non-prompt light lepton, or an electron withmisassigned charge, followed by 𝑡 ¯ 𝑡𝑊 and 𝑉𝑉 production. In the 1 ℓ + ≥ 𝜏 , 2 ℓ OS+1 𝜏 , and 2 ℓ OS+ ≥ 𝜏 SRs,about half of the background is also 𝑡 ¯ 𝑡 with one fake 𝜏 had candidate, while the remaining contributions arisefrom 𝑡 ¯ 𝑡𝑊 , 𝑡 ¯ 𝑡 𝑍 / 𝛾 ∗ , and 𝑡 ¯ 𝑡𝐻 production, with varying fractions across the SRs. Finally, the 2 ℓ SS/3 ℓ + ≥ 𝜏 SRs are dominated by backgrounds with real leptons, with comparable contributions from 𝑡 ¯ 𝑡𝑊 , 𝑡 ¯ 𝑡 𝑍 / 𝛾 ∗ , 𝑡 ¯ 𝑡𝐻 , and 𝑉𝑉 production. Despite their limited purity, the CRs defined above are useful for checking andcorrecting the background prediction (see Section 6) and constraining the related systematic uncertaintiesthrough the likelihood fit to data that also includes the SRs. The VRs are meant to provide an independentvalidation of the background prediction, and thus are not included in the fit.17 TLAS = 13 TeVsSignal regions Wtt Htt *) (high) γ (Z/tt * (low) γ tttt Single top QMisID OtherNon prompt e µ Non prompt Mat Conv had τ Fake Diboson ℓ +1 τOS ℓ +1 τSS ℓ + ≥ τ ℓ OS +1 τ ℓ OS + ≥ τ ℓ SS /3 ℓ + ≥ τ − L ℓ SS /3 ℓ + ≥ τ − H Figure 4: The fractional contributions of the various backgrounds to the total predicted background in each of theseven signal region categories (see Section 5). The background estimation methods are described in Section 6.The background contributions after the likelihood fit to data under the background-only hypothesis are shown (seeSection 7).
Backgrounds are categorised into irreducible and reducible backgrounds. Irreducible backgrounds(Section 6.1) have only prompt selected leptons, i.e. produced in 𝑊 / 𝑍 boson decays, in leptonic 𝜏 -leptondecays, or internal conversions. Reducible backgrounds (Section 6.2) have prompt leptons with misassignedcharge, at least one non-prompt light lepton, or fake 𝜏 had candidates. All backgrounds are estimated usingthe simulated samples described in Section 3, which also discusses the systematic uncertainties in themodelling of these processes, so this is not repeated below. In some cases, the simulation is improvedusing additional corrections derived in data control samples. In particular, the event kinematics of thesimulated 𝑡 ¯ 𝑡 background, or the 𝜏 had fake rate predicted by the simulation, require dedicated correctionsto better describe the data. In addition, the yields of some simulated backgrounds, in particular 𝑡 ¯ 𝑡𝑊 andnon-prompt-lepton backgrounds, are adjusted via normalisation factors that are determined by performinga likelihood fit to data across all event categories as discussed in Section 7. Background contributions with prompt leptons originate from a wide range of physics processes with theirrelative importance varying by channel. In the 1 ℓ +1 𝜏 OS category the main irreducible background is 𝑡 ¯ 𝑡 production, followed by 𝑡𝑊 production, whereas in the rest of analysis channels the main irreduciblebackgrounds originate from 𝑡 ¯ 𝑡𝑊 and 𝑡 ¯ 𝑡 ( 𝑍 / 𝛾 ∗ ) production, followed by 𝑉𝑉 (in particular 𝑊 𝑍 ) production.Smaller contributions originate from the following rare processes: 𝑡 𝑍 , 𝑊𝑡 𝑍 , 𝑡 ¯ 𝑡𝑊𝑊 , 𝑉𝑉𝑉 , 𝑡 ¯ 𝑡𝑡 , and 𝑡 ¯ 𝑡𝑡 ¯ 𝑡 production. 18 .1.1 𝒕 ¯ 𝒕 background Detailed measurements of differential cross sections have shown that the 𝑡 ¯ 𝑡 simulation does not model thetop-quark 𝑝 T spectrum with sufficient accuracy, overestimating it in the high- 𝑝 T tail [112, 113]. In addition,the simulation underestimates the production of 𝑡 ¯ 𝑡 events with high jet multiplicity [113]. This leads todiscrepancies between data and simulation in the distributions of several kinematic quantities of interestin this search, in particular the 𝑚 eff variable. In order to improve the description, dedicated correctionsas a function of jet multiplicity and 𝑚 eff (referred to as ‘kinematic reweighting’) are derived in the 𝑡 ¯ 𝑡 𝜏 CR. The corrections are derived by comparing the data, after subtracting small background contributionsestimated from the simulation, with the predicted sum of 𝑡 ¯ 𝑡 and 𝑡𝑊 processes. The correction factors as afunction of jet multiplicity vary from 1.05 for exactly two jets, to 1.1 for at least six jets. After correctingthe jet multiplicity spectrum, a further correction as a function of 𝑚 eff is derived for each jet multiplicity,and parameterised as a first-degree polynomial. For example, for exactly four jets, the resulting correctionfactor varies from ∼ 𝑚 eff =
200 GeV to ∼ 𝑚 eff = 𝑡 ¯ 𝑡 and 𝑡𝑊 simulated events, and prior to the derivation of any furthercorrections to improve the modelling of fake 𝜏 had candidates or non-prompt leptons (see Sections 6.2.1and 6.2.2). The comparison between data and the background prediction after the kinematic reweightingshows good agreement, as illustrated in Figure 5(b) for the 𝑚 eff distribution in the 1 ℓ +1 𝜏 OS VR, which isdominated by 𝑡 ¯ 𝑡 background with a real 𝜏 had candidate. The modelling of several other kinematic quantifiessuch as the lepton 𝑝 T , 𝐸 missT , and the scalar sum of jet 𝑝 T , is also improved. Although this kinematicreweighting is derived using 𝑡 ¯ 𝑡 dileptonic events, it is also applied to 𝑡 ¯ 𝑡 semileptonic events selected in the1 ℓ +1 𝜏 channel. A systematic uncertainty from the slight difference between the slope of the nominal 𝑚 eff correction factor and that derived in the 1 ℓ +1 𝜏 OS CR is also considered, with negligible impact on thefinal result. 𝒕 ¯ 𝒕𝑾 background The 𝑡 ¯ 𝑡𝑊 background represents a non-negligible background in several event categories. Despite the useof state-of-the-art simulations, accurate modelling of additional QCD radiation in 𝑡 ¯ 𝑡𝑊 production remainschallenging. Event categories sensitive to the 𝑡 ¯ 𝑡𝑊 background were defined in the analysis in order tostudy and constrain this background. These event categories are split by the sign of the sum of leptoncharges (referred to as ‘total charge’) to better discriminate the 𝑡 ¯ 𝑡𝑊 process, which has a large chargeasymmetry, from other SM backgrounds that are charge symmetric. To illustrate this point, the distributionof the scalar sum of the lepton 𝑝 T (denoted by 𝐻 T, lep ) in the 2 ℓ SS+0 𝜏 channel, obtained by subtracting thedistributions for events with positive total charge and with negative total charge, is shown in Figure 6(a). Inthis subtraction, only the charge asymmetric processes remain visible, allowing a better assessment of themodelling of the 𝑡 ¯ 𝑡𝑊 process by the simulation. Disagreement between the data and the prefit predictionfrom the simulation is observed, corresponding to an overall normalisation factor that is assigned to the 𝑡 ¯ 𝑡𝑊 background, and which is determined during the likelihood fit. The measured normalisation factoris ˆ 𝜆 𝑡 ¯ 𝑡𝑊 = . ± .
15, which is compatible with that determined in the SM 𝑡 ¯ 𝑡𝑡 ¯ 𝑡 analysis [114], and witha previous measurement of the 𝑡 ¯ 𝑡𝑊 production cross section [115]. Agreement is improved after theapplication of the background corrections resulting from the likelihood fit, in particular the above 𝑡 ¯ 𝑡𝑊 normalisation factor, as shown in Figure 6(b) for the 𝑚 eff distribution. The sum of 𝑡 ¯ 𝑡 and 𝑡𝑊 backgrounds is considered since they interfere at NLO. − −
10 110 E v en t s / G e V Data ttSingle top Wtt*) γ (Z/tt HttW/Z+jets DibosonOther Uncertainty (1.1 TeV) d3 LQ (1.3 TeV) d3 LQ ATLAS = 13 TeV, 139 fb s j +4 OS µ e CR Pre Fit500 1000 1500 2000 2500 3000 [GeV] eff m ttt D a t a non t (a)
500 1000 1500 2000 2500 3000 [GeV] eff m D a t a / B k g − −
10 110 E v en t s / G e V ATLAS = 13 TeV, 139 fbs VR ℓ +1 τOS Pre Fit
Data had τ Fake tt Single topWtt *) (high) γ (Z/ttHtt DibosonNon prompt e µ Non prompt QMisID OtherUncertaintyPre Kinem. Rew. (b)
Figure 5: (a) Comparison between data and the background prediction for the 𝑚 eff distribution in events selectedby requiring an opposite-charge (OS) 𝑒𝜇 pair, exactly four jets, and at least one 𝑏 -tagged jet. The backgroundcontributions shown are before the likelihood fit to data (“Pre-Fit”). The lower panel displays the ratio of the data,after subtracting the small background contributions estimated from the simulation, to the predicted sum of 𝑡 ¯ 𝑡 and 𝑡𝑊 processes, along with the corresponding fit using a first-degree polynomial (black solid line). The associatedgreen lines represent the estimated uncertainty in the reweighting function. (b) Comparison of the 𝑚 eff distributionbetween data and the pre-fit background prediction after the kinematic reweighting in the 1 ℓ +1 𝜏 OS VR. The totalbackground prediction before the kinematic reweighting (“Pre-Kinem. Rew.”) is shown as a dashed blue histogram.The ratio of the data to the total pre-fit background prediction (“Bkg”) is shown in the lower panel. The size of thecombined statistical and systematic uncertainty in the background prediction is indicated by the blue hatched band.The ratios of the data to the total pre-fit predictions before and after kinematic reweighting are shown in the lowerpanel. The last bin in each figure contains the overflow.
The total yields in the 3 ℓ VV and 3 ℓ ttZ CRs are used in the likelihood fit to improve the prediction of thebackground contribution from the 𝑉𝑉 and 𝑡 ¯ 𝑡 ( 𝑍 / 𝛾 ∗ ) processes, respectively. A comparison of the 𝑚 eff distribution between the data and the total prediction in these two CRs exhibits adequate modelling by thesimulation even before the likelihood fit to data, as shown in Figure 7. The rate of the background frominternal conversions with 𝑚 ( 𝑒 + 𝑒 − ) < ℓ IntC and 3 ℓ IntC).The total yield in each category is used in the likelihood fit to determine the following normalisation factor:ˆ 𝜆 IntC 𝑒 = . ± .
32, where the uncertainty is dominated by the statistical uncertainty. The normalisation ofthe internal-conversion background is validated by comparing data and scaled simulation in a dedicatedcontrol sample enhanced in 𝑍 → 𝜇 + 𝜇 − 𝛾 ∗ (→ 𝑒 + 𝑒 − ) candidate events, defined by requiring two OS Tightmuons and one electron satisfying the Very Tight requirements, except for the internal conversion veto.The level of agreement found between observed and predicted yields is within 25%, which is assigned as asystematic uncertainty associated with the extrapolation of the estimate from the 2 ℓ IntC and 3 ℓ IntC CRs tothe other event categories. 20
T,lep H D a t a / B k g −
10 110 / G e V N + N ATLAS = 13 TeV, 139 fbs ℓ SS +0 τ Post Fit
Data WttDiboson Non prompt e µ Non prompt QMisIDMat Conv OtherUncertainty Pre Fit (a) eff m D a t a / B k g −
10 110 E v en t s / G e V ATLAS = 13 TeV, 139 fbs CR ℓ ttW Post Fit
Data Wtt*) (high) γ (Z/tt * (low) γ ttHtt DibosonNon prompt e µ Non prompt QMisID Mat ConvOther UncertaintyPre Fit (b)
Figure 6: (a) Comparison between data and the background prediction for the distribution of the scalar sum of thelepton 𝑝 T ( 𝐻 T, lep ) in the 2 ℓ SS+0 𝜏 channel, obtained by subtracting the corresponding distributions for events withpositive and negative total charge. In (b) the comparison is performed for the 𝑚 eff distribution in the 2 ℓ ttW CRwithout splitting according to total charge. The background contributions after the likelihood fit to data (“Post-Fit”)under the background-only hypothesis are shown as filled histograms. The total background prediction before thelikelihood fit to data (“Pre-Fit”) is shown as a dashed blue histogram in the upper panel. The ratio of the data tothe background (“Bkg”) prediction is shown in the lower panel, separately for post-fit background (black points)and pre-fit background (dashed blue line). The size of the combined statistical and systematic uncertainty in thebackground prediction is indicated by the blue hatched band. The last bin in each figure contains the overflow. 𝝉 had candidates In most event categories requiring at least one 𝜏 had , the dominant background originates from 𝑡 ¯ 𝑡 productionwith at least one fake 𝜏 had candidate. Consequently, the estimation of fake- 𝜏 had background relies heavilyon the simulation accurately modelling the 𝑡 ¯ 𝑡 event kinematics and the 𝜏 had misidentification rate fromjets. As discussed in Section 6.1.1, a kinematic reweighting is applied to 𝑡 ¯ 𝑡 simulated events in orderto improve the description of the event kinematics. In order to evaluate such a correction factor, whichdepends on the jet multiplicity of the events, fake 𝜏 had candidates in 𝑡 ¯ 𝑡 simulated events are consideredas additional jets. After the kinematic reweighting is applied, a suitable correction to the fake- 𝜏 had ratein the simulation is measured. A CR is defined by requiring an OS 𝑒𝜇 pair, at least two jets, at least one 𝑏 -tagged jet, at least one Loose or Medium 𝜏 had candidate, and 𝑚 eff < 𝑡 ¯ 𝑡 in Table 4).The upper bound on 𝑚 eff ensures that any potential LQ d3 signal contamination would be negligible. ThisCR is enriched in dileptonic 𝑡 ¯ 𝑡 events, such that the selected 𝜏 had candidates primarily originate from jets,and are used to determine a normalisation factor to correct for possible mismodelling of the fake- 𝜏 had rate in the simulation per 𝜏 had candidate. According to the simulation, the flavour composition of the jetsgiving a fake 𝜏 had candidate in this CR is similar to that in the SRs considered. This normalisation factor ismeasured as a function of 𝑝 𝜏 had T , and for one-prong and three-prong 𝜏 had candidates separately. In the case21
500 1000 1500 2000 2500 3000 3500 4000 [GeV] eff m D a t a / B k g −
10 110 E v en t s / G e V ATLAS = 13 TeV, 139 fbs CR ℓ VV Post Fit
Data *) (high) γ (Z/ttDiboson Non prompt e µ Non prompt QMisIDMat Conv OtherUncertainty Pre Fit (a) eff m D a t a / B k g −
10 110 E v en t s / G e V ATLAS = 13 TeV, 139 fbs CR ℓ ttZ Post Fit
Data *) (high) γ (Z/ttDiboson Non prompt e µ Non prompt QMisIDMat Conv OtherUncertainty Pre Fit (b)
Figure 7: Comparison between data and the background prediction for the 𝑚 eff distribution in (a) the 3 ℓ VV CR and(b) the 3 ℓ ttZ CR. The background contributions after the likelihood fit to data (“Post-Fit”) under the background-onlyhypothesis are shown as filled histograms. The total background prediction before the likelihood fit to data (“Pre-Fit”)is shown as a dashed blue histogram in the upper panel. The ratio of the data to the background (“Bkg”) prediction isshown in the lower panel, separately for post-fit background (black points) and pre-fit background (dashed blue line).The size of the combined statistical and systematic uncertainty in the background prediction is indicated by the bluehatched band. The last bin in each figure contains the overflow. of one-prong (three-prong) 𝜏 had candidates satisfying the Loose requirement, the normalisation factorsrange from 1 . ± .
06 (1 . ± .
31) for 𝑝 𝜏 had T in the range of 25–45 GeV (25–50 GeV), to 0 . ± . . ± .
30) for 𝑝 𝜏 had T ≥
100 GeV (
75 GeV ) . The quoted uncertainty includes the statistical uncertainty inthe CR, the uncertainty in the contribution from real 𝜏 had candidates that is subtracted in the CR, and thedifference between this normalisation factor and one measured in a separate CR enhanced in 𝑍 +jets events(denoted by CR 𝑍 in Table 4), which has a different jet-flavour composition of fake 𝜏 had candidates thanCR 𝑡 ¯ 𝑡 . No statistically significant differences are found between the normalisation factors for Loose andMedium 𝜏 had candidates; therefore, the above normalisation factors are applied to all channels requiringat least one 𝜏 had candidate. All simulated background events with at least one fake 𝜏 had candidate arescaled by the product of the corresponding per-candidate normalisation factors calculated according to themultiplicity of fake 𝜏 had and non-prompt light leptons (see Section 6.2.2) before the likelihood fit to data.After applying the kinematic reweighting and the 𝑝 T -dependent fake- 𝜏 had normalisation factors discussedabove, the simulation is found to provide good modelling of relevant kinematic distributions for thefake- 𝜏 had background before the likelihood fit to data, as shown in Figures 8(a) and 8(b). The uncertaintiesassociated with the normalisation factors are accounted for as nuisance parameters in the likelihood fit (seeSection 7). To account for the approximation of treating fake 𝜏 had candidates as jets in the 𝑡 ¯ 𝑡 kinematicreweighting, in the statistical analysis, the uncertainties associated with the PS and hadronisation model,the ME-to-PS matching, and the modelling of QCD radiation, are treated as uncorrelated between 𝑡 ¯ 𝑡 eventswith at least one fake 𝜏 had candidate and the rest of the 𝑡 ¯ 𝑡 events. This includes 𝑡 ¯ 𝑡 as well as other subleading processes such as single top, 𝑉 +jets, etc. τ T p D a t a / B k g −
10 110 E v en t s / G e V ATLAS = 13 TeV, 139 fbs CR ℓ +1 τSS Pre Fit
Data had τ Fake tt Single topWtt *) (high) γ (Z/ttHtt DibosonNon prompt e µ Non prompt QMisID OtherUncertainty Corr. had τ Pre Fake (a) D a t a / B k g −
10 110 E v en t s ATLAS = 13 TeV, 139 fbs VR ℓ OS +1 τ Pre Fit
Data had τ Fake tt Single topWtt *) (high) γ (Z/ttHtt DibosonNon prompt e µ Non prompt QMisID Mat ConvOther Uncertainty (b)
Figure 8: Comparison between data and the background prediction for (a) the 𝜏 had 𝑝 T ( 𝑝 𝜏 T ) distribution in the 1 ℓ +1 𝜏 SSCR, and (b) the jet multiplicity distribution in the 2 ℓ OS+1 𝜏 VR. The background contributions before the likelihoodfit to data (“Pre-Fit”) are shown as filled histograms. The ratio of the data to the background (“Bkg”) predictionis shown in the lower panel. In (a), the total background prediction before the correction with the per-candidatenormalisation factors (“Pre-Fake 𝜏 had Corr.”) is shown as a dashed blue histogram (line) in the upper (lower) panel.The size of the combined statistical and systematic uncertainty in the background prediction is indicated by the bluehatched band. The last bin in each figure contains the overflow.
Non-prompt leptons originate from material conversions, heavy-flavour hadron decays, or the improperreconstruction of other particles, with an admixture strongly depending on the lepton quality requirementsand varying across event categories. These backgrounds are in general very small in all SRs and thus areestimated from simulation, with the normalisation determined by the likelihood fit. The main contributionto the non-prompt-lepton background is from 𝑡 ¯ 𝑡 production, followed by much smaller contributions from 𝑉 +jets and single-top-quark processes. The non-prompt light leptons in the simulated samples are labelledaccording to whether they originate from heavy-flavour (HF) or light-flavour (LF) hadron decays, or from amaterial conversion candidate. The HF category includes leptons from both bottom and charm decays.QMisID backgrounds arise mainly from 𝑡 ¯ 𝑡 production, with one electron having a hard bremsstrahlungemission followed by an asymmetric conversion ( 𝑒 ± → 𝑒 ± 𝛾 ∗ → 𝑒 ± 𝑒 + 𝑒 − ) or a mismeasured track curvature.The muon charge misassignment rate is negligible in the 𝑝 T range relevant to this analysis.Several of the event categories introduced in Section 5 were designed to be enriched in specific processesand are used to derive normalisation factors to improve their modelling by the simulation. The 2 ℓ MatC and3 ℓ MatC CRs are enriched in MatC and QMisID backgrounds and only the total event yield is used. Thereare four CRs enriched in contributions from HF non-prompt leptons in 𝑡 ¯ 𝑡 events, i.e. 2 ℓ tt(e)+, 2 ℓ tt(e)-,2 ℓ tt( 𝜇 )+, and 2 ℓ tt( 𝜇 )-. In these CRs, the 𝐻 T, lep distribution is used to provide separation from the 𝑡 ¯ 𝑡𝑊 background and thus optimise the sensitivity to the HF non-prompt electron and muon contributions. Thesimultaneous fit to these regions, split by total charge, provides additional separation due to the chargeasymmetry of the 𝑡 ¯ 𝑡𝑊 process. Normalisation factors for three non-prompt-lepton background contributions23 T,lep H D a t a / B k g E v en t s / G e V ATLAS = 13 TeV, 139 fbs CR ℓ tt ( e ) − Post Fit
Data Wtt*) (high) γ (Z/tt * (low) γ ttHtt DibosonNon prompt e µ Non prompt QMisID Mat ConvOther UncertaintyPre Fit (a)
50 100 150 200 250 300 350 [GeV]
T,lep H D a t a / B k g E v en t s / G e V ATLAS = 13 TeV, 139 fbs CR ℓ tt ( μ ) − Post Fit
Data Wtt*) (high) γ (Z/tt * (low) γ ttHtt DibosonNon prompt e µ Non prompt QMisID Mat ConvOther UncertaintyPre Fit (b)
Figure 9: Comparison between data and the background prediction for the distribution of the scalar sum of the lepton 𝑝 T ( 𝐻 T, lep ) in (a) the 2 ℓ tt(e)- CR and (b) the 2 ℓ tt( 𝜇 )- CR. The background contributions after the likelihood fit to data(“Post-Fit”) under the background-only hypothesis are shown as filled histograms. The total background predictionbefore the likelihood fit to data (“Pre-Fit”) is shown as a dashed blue histogram in the upper panel. The ratio of thedata to the background (“Bkg”) prediction is shown in the lower panel, separately for post-fit background (blackpoints) and pre-fit background (dashed blue line). The size of the combined statistical and systematic uncertainty inthe background prediction is indicated by the blue hatched band. The last bin in each figure contains the overflow. are estimated from the likelihood fit. The normalisation factor for HF non-prompt leptons is estimatedseparately for electrons and muons, 𝜆 had 𝑒 and 𝜆 had 𝜇 respectively. An additional normalisation factor isdetermined for the sum of MatC and QMisID backgrounds, 𝜆 MatC 𝑒 . The measured normalisation factors are:ˆ 𝜆 had 𝑒 = . ± .
30, ˆ 𝜆 had 𝜇 = . ± .
12, and ˆ 𝜆 MatC 𝑒 = . ± .
24, where the uncertainties are dominated bythe statistical uncertainty. The systematic uncertainties considered are discussed in the following, althoughthey have a negligible impact on the final result. The background estimation procedure for non-prompt lightleptons relies on the simulation to predict the kinematic distributions of the 𝑡 ¯ 𝑡 process, and thus is affectedby related modelling uncertainties (see Section 3). Additional uncertainties are estimated by relaxing leptoncriteria to enrich the samples in the different types of non-prompt leptons, and comparing the data withthe simulation. A 25% uncertainty is estimated for material conversions, based on a comparison betweendata and simulation in a dedicated control sample enhanced in 𝑍 → 𝜇 + 𝜇 − 𝛾 (→ 𝑒 + 𝑒 − ) candidate events,defined by requiring two OS Tight muons and one Tight electron that fails the material conversion vetorequirement. This uncertainty is applied to all categories except for 2 ℓ MatC and 3 ℓ MatC as thus acts as anextrapolation uncertainty. Figures 9(a) and 9(b) display the 𝐻 T, lep distribution in the 2 ℓ tt(e)- and 2 ℓ tt( 𝜇 )-CRs after the likelihood fit to data. As shown in the figures, the spectra for the HF non-prompt electronand muon contributions are softer than those for the 𝑡 ¯ 𝑡𝑊 and 𝑉𝑉 backgrounds. For this comparison, theCRs with negative total charge are selected, as this requirement suppresses the 𝑡 ¯ 𝑡𝑊 and 𝑉𝑉 contributions,due to their charge asymmetry, thus increasing the fraction of non-prompt-lepton background.24 able 8: Summary of the event categories per channel, discriminating variables per event category, and number ofbins used in the statistical analysis. 1 ℓ + ≥ 𝜏 ℓ OS+ ≥ 𝜏 ℓ SS/3 ℓ + ≥ 𝜏 ℓ SS+0 𝜏 ℓ +0 𝜏 Number of event categories 6 2 2 8 4 𝑚 eff spectrum 3 SRs 2 SRs 2 SRs — — 𝐻 T , lep spectrum — — — 6 CRs 2 CRsEvent yield 3 CRs — — 2 CRs 2 CRsTotal number of bins 16 9 6 20 10 A maximum-likelihood fit is performed on all bins in the 22 event categories considered, consisting of15 CRs and 7 SRs (see Table 8), to simultaneously determine the background and LQ d3 signal yields thatare most consistent with the data. The 𝑚 eff spectrum is used in the SRs to maximise the sensitivity tothe LQ d3 signal, while the CRs are used to either determine or constrain different backgrounds. In theeight CRs from the 2 ℓ SS+0 𝜏 and 3 ℓ +0 𝜏 channels that require very tight selection criteria for light leptonsincluding the internal and material conversion vetoes, the 𝐻 T, lep spectrum is used to discriminate between,and separately normalise, the 𝑡 ¯ 𝑡 (with non-prompt electrons and muons) and 𝑡 ¯ 𝑡𝑊 backgrounds, as well as toconstrain the 𝑡 ¯ 𝑡 ( 𝑍 / 𝛾 ∗ ) , and 𝑉𝑉 background predictions. In the remaining seven CRs, the total event yield(i.e. a single bin) is used: three CRs are used to constrain the 𝑡 ¯ 𝑡 background prediction with either real orfake 𝜏 had candidates, and four CRs are used to normalise the backgrounds with an internal conversion, andwith a material conversion or QMisID.The likelihood function L ( 𝜇, (cid:174) 𝜆, (cid:174) 𝜃 ) is constructed as a product of Poisson probability terms over all binsconsidered in the search, and depends on the signal-strength parameter, 𝜇 , defined as a multiplicativefactor applied to the predicted yield for the LQ d3 signal (depending on the assumed LQ d3 mass and theLQ d3 → 𝑡𝜏 branching fraction), (cid:174) 𝜆 , the normalisation factors for several backgrounds (see Section 6), and (cid:174) 𝜃 , a set of nuisance parameters (NP) encoding systematic uncertainties in the signal and backgroundexpectations [116]. Systematic uncertainties can impact the estimated signal and background rates, themigration of events between categories, and the shape of the fitted distributions; they are summarised inTable 9. Both 𝜇 and (cid:174) 𝜆 are treated as free parameters in the likelihood fit. The NPs (cid:174) 𝜃 allow variations ofthe expectations for signal and background according to the systematic uncertainties, subject to Gaussianconstraints in the likelihood fit. Their fitted values represent the deviations from the nominal expectationsthat globally provide the best fit to the data. Statistical uncertainties in each bin due to the limited sizeof the simulated samples are taken into account by dedicated parameters using the Beeston–Barlowtechnique [117].The test statistic 𝑞 𝜇 is defined as the profile likelihood ratio: 𝑞 𝜇 = − (L ( 𝜇, ˆ (cid:174) 𝜆 𝜇 , ˆ (cid:174) 𝜃 𝜇 )/L ( ˆ 𝜇, ˆ (cid:174) 𝜆 ˆ 𝜇 , ˆ (cid:174) 𝜃 ˆ 𝜇 )) ,where ˆ 𝜇 , ˆ (cid:174) 𝜆 ˆ 𝜇 , and ˆ (cid:174) 𝜃 ˆ 𝜇 are the values of the parameters that maximise the likelihood function, and ˆ (cid:174) 𝜆 𝜇 andˆ (cid:174) 𝜃 𝜇 are the values of the parameters that maximise the likelihood function for a given value of 𝜇 . Thetest statistic 𝑞 𝜇 is evaluated with the RooFit package [118]. A related statistic is used to determine theprobability that the observed data are compatible with the background-only hypothesis (i.e. the discoverytest) by setting 𝜇 = 𝑞 ). The 𝑝 -value (referred to as 𝑝 ) representing theprobability of the data being compatible with the background-only hypothesis is estimated by integratingthe distribution of 𝑞 from background-only pseudo-experiments, approximated using the asymptotic25 able 9: Sources of systematic uncertainty considered in the analysis. “N” means that the uncertainty is taken asnormalisation-only for all processes and channels affected. Some of the systematic uncertainties are split into severalcomponents, as indicated by the number in the rightmost column. Systematic uncertainty ComponentsLuminosity 1Pile-up reweighting 1
Physics objects
Electron 6Muon 16 𝜏 -leptons 21Jet energy scale and resolution 34Jet vertex fraction 1Jet flavour tagging 22 𝐸 missT Data-driven reducible background estimates 𝑡 ¯ 𝑡 kinematic reweighting 2Fake- 𝜏 had estimates 14Material conversions modelling 1Internal conversions modelling 1Total (Data-driven reducible background) 18 Systematic uncertainty Components Signal modelling
Cross section (N) 1QCD scale ( 𝜇 f , 𝜇 r ) 1PDFs+ 𝛼 S 𝒕 ¯ 𝒕 modelling Cross section (N) 1Parton shower and hadronisation model 2Generator 2QCD radiation 2QED radiative top-quark decay (N) 1 𝒕 ¯ 𝒕𝑾 modelling QCD scale 1Generator 1 𝒕 ¯ 𝒕 ( 𝒁 / 𝜸 ∗ ) (high mass) modelling Cross section (N) 1Generator 1 𝒕 ¯ 𝒕𝑯 modelling Cross section (N) 1Parton shower and hadronisation model 1
𝑾 𝒁 modelling
Cross section (N) 1Heavy-flavour composition (N) 1
Other background modelling
Cross section (N) 10Total (Signal and background modelling) 30Total (Overall) 153 formulae given in Ref. [119], above the observed value of 𝑞 . Some model dependence exists in theestimation of the 𝑝 , as a given signal scenario needs to be assumed in the calculation of the denominatorof 𝑞 , even if the overall signal normalisation is allowed to float and is fitted to data. The observed 𝑝 ischecked for each explored signal scenario. Upper limits on the signal production cross section for eachof the signal scenarios considered are derived by using 𝑞 𝜇 in the CL s method [120, 121]. For a givensignal scenario, values of the production cross section (parameterised by 𝜇 ) yielding CL s < .
05, whereCL s is computed using the asymptotic approximation [119], are excluded at ≥
95% confidence level (CL).The upper limits derived with the asymptotic approximation agree very well with those estimated viabackground-only pseudo-experiments.A comparison of the distributions of observed and expected yields in the 15 CRs and the 7 SRs afterthe combined likelihood fit under the background-only hypothesis is shown in Figures 10(a) and 10(b),respectively. The corresponding post-fit yields for the SRs can be found in Table 10. In general, goodagreement between the data and predicted background yields is found across all event categories. As shownin Figure 11, good agreement is also obtained between the data and post-fit background prediction in theVRs, which were not used in the fit, giving confidence in the overall procedure.The comparison between data and the background prediction for the 𝑚 eff distributions used in the different26 ℓ + τ O S ℓ + τ SS ℓ + ≥ τ ℓ tt W + ℓ tt W − ℓ tt ( e ) + ℓ tt ( e ) − ℓ tt ( μ ) + ℓ tt ( μ ) − ℓ I n t C ℓ M a t C ℓ VV ℓ tt Z ℓ I n t C ℓ M a t C D a t a / B k g −
10 110 E v en t s ATLAS = 13 TeV, 139 fbsControl regionsPost Fit Data had τ Fake ttSingle top Wtt *) (high) γ (Z/tt* (low) γ tt Htt DibosonNon prompt e µ Non prompt QMisIDMat Conv Other UncertaintyPre Fit (a) ℓ + τ O S ℓ + τ SS ℓ + ≥ τ ℓ O S + τ ℓ O S + ≥ τ ℓ SS / ℓ + ≥ τ − L ℓ SS / ℓ + ≥ τ − H D a t a / B k g −
10 110 E v en t s ATLAS = 13 TeV, 139 fbsSignal regionsPost Fit Data had τ Fake ttSingle top Wtt *) (high) γ (Z/tt* (low) γ tt Htt DibosonNon prompt e µ Non prompt QMisIDMat Conv Other UncertaintyPre Fit (b)
Figure 10: Comparison between data and the background prediction for the event yields in (a) the 15 control regioncategories and (b) the 7 signal region categories. The background contributions after the likelihood fit to data(“Post-Fit”) under the background-only hypothesis are shown as filled histograms. The total background predictionbefore the likelihood fit to data (“Pre-Fit”) is shown as a dashed blue histogram in the upper panel. The ratio of thedata to the background (“Bkg”) prediction is shown in the lower panel, separately for post-fit background (blackpoints) and pre-fit background (dashed blue line). The size of the combined statistical and systematic uncertainty inthe background prediction is indicated by the blue hatched band. The blue triangles indicate points that are outsidethe vertical range of the figure.
SRs is shown in Figures 12 and 13. The binning used for the 𝑚 eff distributions in the different SRsrepresents a compromise between preserving enough discrimination in the fit between the background andthe signal for the different values of LQ mass considered, and keeping the statistical uncertainty of thebackground prediction per bin well below 30%. No significant excess is observed in any of the SRs. The27 able 10: Summary of observed and predicted yields in the seven signal region categories. The background predictionis shown after the combined likelihood fit to data under the background-only hypothesis across all control region andsignal region categories. The expected signal yields that are obtained by using their theoretical cross sections arealso shown with their pre-fit uncertainties, assuming B =
1. Dashes refer to components that are negligible or notapplicable. 1 ℓ +1 𝜏 OS 1 ℓ +1 𝜏 SS 1 ℓ + ≥ 𝜏 Data 339 19 6Total background 340 ±
20 17 . ± . . ± . 𝜏 had . ± . . ± . . ± . 𝑡 ¯ 𝑡 ±
21 2 . ± . . ± . . ± .
56 — 𝑡 ¯ 𝑡𝑊 . ± . . ± .
59 0 . ± . 𝑡 ¯ 𝑡𝑍 / 𝛾 ∗ (high mass) 2 . ± .
65 1 . ± .
30 0 . ± . 𝑡 ¯ 𝑡𝛾 ∗ (low mass) — 0 . ± .
01 — 𝑡 ¯ 𝑡𝐻 . ± .
44 0 . ± .
21 1 . ± . . ± .
66 1 . ± .
27 0 . ± . . ± .
68 3 . ± .
90 0 . ± . . ± .
91 1 . ± .
38 0 . ± . d3 (0 . . ± . . ± . . ± . d3 (1 . . ± . . ± .
74 11 . ± . d3 (1 . . ± .
75 1 . ± .
25 2 . ± . ℓ OS+1 𝜏 ℓ OS+ ≥ 𝜏 ℓ SS/3 ℓ + ≥ 𝜏 -L 2 ℓ SS/3 ℓ + ≥ 𝜏 -HData 13 1 7 3Total background 14 . ± . . ± .
58 5 . ± .
68 0 . ± . 𝜏 had . ± . . ± .
54 0 . ± .
07 0 . ± . 𝑡 ¯ 𝑡𝑊 . ± .
51 — 1 . ± .
39 0 . ± . 𝑡 ¯ 𝑡𝑍 / 𝛾 ∗ (high mass) 0 . ± .
26 0 . ± .
06 1 . ± .
20 0 . ± . 𝑡 ¯ 𝑡𝛾 ∗ (low mass) 0 . ± .
01 — 0 . ± .
02 — 𝑡 ¯ 𝑡𝐻 . ± .
19 0 . ± .
14 1 . ± .
27 0 . ± . . ± .
08 — 0 . ± .
10 0 . ± . 𝑒 . ± .
13 — — —Non-prompt 𝜇 . ± .
28 — 0 . ± .
06 —QMisID 0 . ± .
13 — 0 . ± .
05 —Mat Conv 0 . ± .
15 — 0 . ± .
02 —Other 0 . ± .
22 0 . ± .
03 0 . ± .
28 0 . ± . d3 (0 . . ± . . ± . . ± .
90 13 . ± . d3 (1 . . ± . . ± .
26 1 . ± .
17 3 . ± . d3 (1 . . ± .
31 0 . ± .
08 0 . ± .
05 1 . ± . observed 𝑝 is found to be consistent with the background-only hypothesis for all values of 𝑚 LQ d3 and B considered. The observed and expected 𝑝 as a function of 𝑚 LQ d3 are shown in Figure 14, assuming valuesof B = B = .
5. This illustrates the significant expected sensitivity of the search, which for B = 𝑚 LQ d3 < .
21 TeV and 3 standard deviations for 𝑚 LQ d3 < .
36 TeV.In absence of any significant excess above the SM background prediction, 95% CL upper limits are set onthe cross section for the LQ d3 pair production as a function of the assumed 𝑚 LQ d3 and B . Figure 15(a) shows28 ℓ + τ O S ℓ + τ SS ℓ + ≥ τ ℓ O S + τ ℓ O S + ≥ τ ℓ SS / ℓ + ≥ τ D a t a / B k g −
10 110 E v en t s ATLAS = 13 TeV, 139 fbsValidation regionsPost Fit Data had τ Fake ttSingle top Wtt *) (high) γ (Z/tt* (low) γ tt Htt DibosonNon prompt e µ Non prompt QMisIDMat Conv Other UncertaintyPre Fit
Figure 11: Comparison between data and the background prediction for the event yields in the six validation regioncategories. The background contributions after the likelihood fit to data (“Post-Fit”) under the background-onlyhypothesis are shown as filled histograms. The ratio of the data to the background (“Bkg”) prediction is shown in thelower panel. The total background prediction before the likelihood fit to data (“Pre-Fit”) is shown as a dashed bluehistogram (line) in the upper (lower) panel. The size of the combined statistical and systematic uncertainty in thebackground prediction is indicated by the blue hatched band. the 95% CL upper limits on the LQ d3 pair production cross section as a function of 𝑚 LQ d3 resulting from thecombination of all analysis channels, assuming B =
1. The sensitivity is dominated by the 1 ℓ + ≥ 𝜏 channel,although the 2 ℓ OS+ ≥ 𝜏 and 2 ℓ SS/3 ℓ + ≥ 𝜏 channels bring a significant improvement to the combined limit.The result is completely limited by the statistical uncertainty of the data, with the impact of systematicuncertainties being only to raise the expected cross-section upper limit by 2.3% at 𝑚 LQ d3 = 𝑚 LQ d3 =
500 GeV and 𝑚 LQ d3 = . 𝜏 had identification and energy scale calibration, followed by 𝑡 ¯ 𝑡 modelling. A comparison of the cross-section limits with the theoretical prediction is used to derive95% CL limits on B as a function of 𝑚 LQ d3 , as shown in Figure 15(b). Assuming that B =
1, the observedand expected 95% CL lower limits on 𝑚 LQ d3 are 1 .
43 TeV and 1 .
41 TeV, respectively. The correspondinglimits for B = . .
22 TeV and 1 .
19 TeV, respectively. The above limits assume that the only possibledecay modes are LQ → 𝑡𝜏 / 𝑏𝜈 . In the case of a non-negligible contribution from the LQ → 𝑞𝜏 ( 𝑞 = 𝑢, 𝑐 )decay mode, more stringent limits could be derived for intermediate values of B , since LQLQ → 𝑡𝜏𝑞𝜏 final states would be probed by the 1 ℓ + ≥ 𝜏 SR, which dominates the sensitivity of this search.29
000 1500 2000 2500 3000 3500 4000 [GeV] eff m D a t a / B k g − −
10 110 E v en t s / G e V ATLAS = 13 TeV, 139 fbs ℓ +1 τOS Post Fit
Data (1.1 TeV) d3 LQtt Single top had τ Fake Wtt*) (high) γ (Z/tt HttDiboson Non prompt e µ Non prompt QMisIDOther UncertaintyPre Fit (a) eff m D a t a / B k g − −
10 110 E v en t s / G e V ATLAS = 13 TeV, 139 fbs ℓ +1 τSS Post Fit
Data (1.1 TeV) d3 LQtt Single top had τ Fake Wtt*) (high) γ (Z/tt HttDiboson Non prompt e µ Non prompt QMisIDOther UncertaintyPre Fit (b) eff m D a t a / B k g − −
10 110 E v en t s / G e V ATLAS = 13 TeV, 139 fbs ℓ + ≥ τ Post Fit
Data (1.1 TeV) d3 LQ had τ Fake Wtt*) (high) γ (Z/tt HttDiboson Non prompt e µ Non prompt QMisIDOther UncertaintyPre Fit (c)
Figure 12: Comparison between data and prediction for the 𝑚 eff distribution used in different signal region categoriesof the 1 ℓ + ≥ 𝜏 channel: (a) 1 ℓ +1 𝜏 OS, (b) 1 ℓ +1 𝜏 SS, and (c) 1 ℓ + ≥ 𝜏 . The background contributions after thelikelihood fit to data (“Post-Fit”) under the background-only hypothesis are shown as filled histograms. For illustrativepurposes, the expected signal for 𝑚 LQ d3 = . B =
500 1000 1500 2000 2500 3000 3500 4000 [GeV] eff m D a t a / B k g − −
10 110 E v en t s / G e V ATLAS = 13 TeV, 139 fbs ℓ OS +1 τ Post Fit
Data (1.1 TeV) d3 LQ had τ Fake Wtt*) (high) γ (Z/tt HttDiboson Non prompt e µ Non prompt QMisIDMat Conv OtherUncertainty Pre Fit (a) eff m D a t a / B k g − −
10 110 E v en t s / G e V ATLAS = 13 TeV, 139 fbs ℓ OS + ≥ τ Post Fit
Data (1.1 TeV) d3 LQ had τ Fake *) (high) γ (Z/ttHtt OtherUncertainty Pre Fit (b) eff m D a t a / B k g − −
10 110 E v en t s / G e V ATLAS = 13 TeV, 139 fbs ℓ SS /3 ℓ + ≥ τ − L Post Fit
Data (1.1 TeV) d3 LQWtt *) (high) γ (Z/tt* (low) γ tt HttDiboson had τ Fake µ Non prompt QMisIDMat Conv OtherUncertainty Pre Fit (c)
500 1000 1500 2000 2500 3000 3500 4000 [GeV] eff m D a t a / B k g − −
10 110 E v en t s / G e V ATLAS = 13 TeV, 139 fbs ℓ SS /3 ℓ + ≥ τ − H Post Fit
Data (1.1 TeV) d3 LQWtt *) (high) γ (Z/ttHtt had τ Fake Diboson OtherUncertainty Pre Fit (d)
Figure 13: Comparison between data and prediction for the 𝑚 eff distribution used in different signal regioncategories of the 2 ℓ OS+ ≥ 𝜏 and 2 ℓ SS/3 ℓ + ≥ 𝜏 channels: (a) 2 ℓ OS+1 𝜏 , (b) 2 ℓ OS+ ≥ 𝜏 , (c) 2 ℓ SS/3 ℓ + ≥ 𝜏 -L, and (d)2 ℓ SS/3 ℓ + ≥ 𝜏 -H. The background contributions after the likelihood fit to data (“Post-Fit”) under the background-onlyhypothesis are shown as filled histograms. For illustrative purposes, the expected signal for 𝑚 LQ d3 = . B =
00 800 1000 1200 1400 1600 [GeV] d3 LQ m − − − − − − −
10 110 Lo c a l p ATLAS =13 TeV, 139 fbs =1.0) Β Obs ( =1.0) Β Exp ( =0.5) Β Obs ( =0.5) Β Exp ( σ σ σ σ Figure 14: The observed (solid) local 𝑝 as a function of LQ d3 mass ( 𝑚 LQ d3 ) assuming B = . B = 𝑝 under the hypothesis of a LQ d3 signal at that mass. The horizontaldashed lines indicate the 𝑝 -values corresponding to significances of 2 to 5 standard deviations.
600 800 1000 1200 1400 1600 [GeV] d3 LQ m − − − −
10 1 ) [ pb ] d 3 L Q d 3 L Q → ( pp σ ATLAS = 13 TeV, 139 fbs τ t τ t → d3 LQ d3 LQ95% CL
Obs. limitExp. limit σ ± Exp. +NNLL) approx
Theory (NNLO
Individual limits ≥ Combination (a)
600 800 1000 1200 1400 1600 [GeV] d3 LQ m ) τ t → d 3 ( L Q Β ATLAS = 13 TeV, 139 fbs ) τ t → d3 (LQ Β )=1 ν b → d3 (LQ Β
95% CL
Obs. limitExp. limit σ ± Exp. limit σ ± Theory (b)
Figure 15: (a) Observed (solid line) and expected (dashed line) 95% CL upper limits on the LQ d3 pair productioncross section as a function of 𝑚 LQ d3 resulting from the combination of all analysis channels, assuming B =
1. Thesurrounding shaded band corresponds to the ± ± 𝜎 ) uncertainty around the combined expectedlimit, as estimated using the asymptotic approximation (see text). This approximation is found to overestimate the+1 𝜎 ( − 𝜎 ) uncertainty of the combined expected limit by about 5%–15% (15%–30%), depending on 𝑚 LQ d3 . The redline and band show the theoretical prediction and its ± 𝜎 uncertainty. The individual expected limits for the 1 ℓ + ≥ 𝜏 channel and the combination of the 2 ℓ OS+ ≥ 𝜏 and 2 ℓ SS/3 ℓ + ≥ 𝜏 channels are shown as the magenta and blue dashedlines, respectively. (b) Observed (solid line) and expected (dashed line) 95% CL upper limits on B as a function of 𝑚 LQ d3 resulting from the combination of all analysis channels. The surrounding shaded band corresponds to the ± 𝜎 uncertainty around the combined expected limit. The same statement regarding the asymptotic approximation givenfor (a) applies. The dotted red line around the observed limit indicates how the observed limit changes when varyingthe theoretical prediction for the LQ d3 pair production cross section by its ± 𝜎 uncertainty. Conclusion
A search for pair production of third-generation scalar leptoquarks with a significant branching fractioninto a top quark and a 𝜏 -lepton has been presented. The search is based on the full Run 2 dataset recordedwith the ATLAS detector at Large Hadron Collider, which corresponds to 139 fb − of 𝑝 𝑝 collisionsat √ 𝑠 =
13 TeV. Events are selected if they have one light lepton (electron or muon) and at least onehadronically decaying 𝜏 -lepton, or at least two light leptons, and additional jets. Six final states, definedby the multiplicity and flavour of lepton candidates, are considered in the analysis. Each of them is splitinto multiple event categories used to search for the signal and improve the modelling of several leadingbackgrounds. The signal-rich event categories require at least one hadronically decaying 𝜏 -lepton candidateand employ the total effective mass distribution to discriminate between the signal and the background.The search reaches an expected significance of 5 standard deviations for a scalar leptoquark decayingexclusively into 𝑡𝜏 and with mass below about 1 . 𝜏 -leptons, and the sophisticated eventselection and categorisation employed, which ensures a high signal acceptance and low background yields.No significant excess above the Standard Model expectation is observed in any of the considered eventcategories, and 95% CL upper limits are set on the production cross section as a function of the leptoquarkmass, for different assumptions about the branching fractions into 𝑡𝜏 and 𝑏𝜈 . Scalar leptoquarks decayingexclusively into 𝑡𝜏 are excluded up to masses of 1 .
43 TeV while, for a branching fraction of 50% into 𝑡𝜏 ,the lower mass limit is 1 .
22 TeV. The corresponding expected mass exclusions are 1 .
41 TeV and 1 .
19 TeV,respectively.
Acknowledgements
We thank CERN for the very successful operation of the LHC, as well as the support staff from ourinstitutions without whom ATLAS could not be operated efficiently.We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF,Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada;CERN; ANID, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPOCR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS and CEA-DRF/IRFU,France; SRNSFG, Georgia; BMBF, HGF and MPG, Germany; GSRT, Greece; RGC and Hong Kong SAR,China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO,Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; MNE/IFA, Romania; JINR; MESof Russia and NRC KI, Russian Federation; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia;DST/NRF, South Africa; MICINN, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF andCantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom; DOEand NSF, United States of America. In addition, individual groups and members have received supportfrom BCKDF, CANARIE, Compute Canada, CRC and IVADO, Canada; Beijing Municipal Science &Technology Commission, China; COST, ERC, ERDF, Horizon 2020 and Marie Sk ℓ odowska-Curie Actions,European Union; Investissements d’Avenir Labex, Investissements d’Avenir Idex and ANR, France; DFGand AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF andthe Greek NSRF, Greece; BSF-NSF and GIF, Israel; La Caixa Banking Foundation, CERCA Programme33eneralitat de Catalunya and PROMETEO and GenT Programmes Generalitat Valenciana, Spain; GöranGustafssons Stiftelse, Sweden; The Royal Society and Leverhulme Trust, United Kingdom.The crucial computing support from all WLCG partners is acknowledged gratefully, in particular fromCERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3(France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC(Taiwan), RAL (UK) and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resourceproviders. Major contributors of computing resources are listed in Ref. [122].34 eferences [1] J. C. Pati and A. Salam, Lepton number as the fourth “color” , Phys. Rev. D (1974) 275.[2] H. Georgi and S. Glashow, Unity of All Elementary-Particle Forces ,Phys. Rev. Lett. (1974) 438.[3] S. K. Dimopoulos and L. Susskind, Mass without scalars , Nucl. Phys. B (1979) 237.[4] S. Dimopoulos,
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Blumenschein , G.J. Bobbink , V.S. Bobrovnikov , S.S. Bocchetta , D. Bogavac ,A.G. Bogdanchikov , C. Bohm , V. Boisvert , P. Bokan , T. Bold , A.E. Bolz ,M. Bomben , M. Bona , J.S. Bonilla , M. Boonekamp , C.D. Booth , A.G. Borbély ,H.M. Borecka-Bielska , L.S. Borgna , A. Borisov , G. Borissov , D. Bortoletto , D. Boscherini ,M. Bosman , J.D. Bossio Sola , K. Bouaouda , J. Boudreau , E.V. Bouhova-Thacker ,D. Boumediene , A. Boveia , J. Boyd , D. Boye , I.R. Boyko , A.J. Bozson , J. Bracinik ,N. Brahimi , G. Brandt , O. Brandt , F. Braren , B. Brau , J.E. Brau ,W.D. Breaden Madden , K. Brendlinger , R. Brener , L. Brenner , R. Brenner , S. Bressler ,B. Brickwedde , D.L. Briglin , D. Britton , D. Britzger , I. Brock , R. Brock , G. Brooijmans ,W.K. Brooks , E. Brost , P.A. Bruckman de Renstrom , B. Brüers , D. Bruncko , A. Bruni ,G. Bruni , M. Bruschi , N. Bruscino , L. Bryngemark , T. Buanes , Q. Buat ,P. Buchholz , A.G. Buckley , I.A. Budagov , M.K. Bugge , O. Bulekov , B.A. Bullard ,T.J. Burch , S. Burdin , C.D. Burgard , A.M. Burger , B. Burghgrave , J.T.P. Burr , C.D. Burton ,J.C. Burzynski , V. Büscher , E. Buschmann , P.J. Bussey , J.M. Butler , C.M. Buttar ,J.M. Butterworth , P. Butti , W. Buttinger , C.J. Buxo Vazquez , A. Buzatu ,A.R. Buzykaev , G. Cabras , S. Cabrera Urbán , D. Caforio , H. Cai , V.M.M. Cairo ,O. Cakir , N. Calace , P. Calafiura , G. Calderini , P. Calfayan , G. Callea , L.P. Caloba ,A. Caltabiano , S. Calvente Lopez , D. Calvet , S. Calvet , T.P. Calvet , M. Calvetti ,R. Camacho Toro , S. Camarda , D. Camarero Munoz , P. Camarri , M.T. Camerlingo ,D. Cameron , C. Camincher , S. Campana , M. Campanelli , A. Camplani , V. Canale ,A. Canesse , M. Cano Bret , J. Cantero , T. Cao , Y. Cao , M.D.M. Capeans Garrido ,M. Capua , R. Cardarelli , F. Cardillo , G. Carducci , I. Carli , T. Carli , G. Carlino ,B.T. Carlson , E.M. Carlson , L. Carminati , R.M.D. Carney , S. Caron , E. Carquin ,S. Carrá , G. Carratta , J.W.S. Carter , T.M. Carter , M.P. Casado , A.F. Casha ,E.G. Castiglia , F.L. Castillo , L. Castillo Garcia , V. Castillo Gimenez , N.F. Castro ,A. Catinaccio , J.R. Catmore , A. Cattai , V. Cavaliere , V. Cavasinni , E. Celebi , F. Celli ,K. Cerny , A.S. Cerqueira , A. Cerri , L. Cerrito , F. Cerutti , A. Cervelli , S.A. Cetin ,Z. Chadi , D. Chakraborty , J. Chan , W.S. Chan , W.Y. Chan , J.D. Chapman ,B. Chargeishvili , D.G. Charlton , T.P. Charman , M. Chatterjee , C.C. Chau , S. Che ,S. Chekanov , S.V. Chekulaev , G.A. Chelkov , B. Chen , C. Chen , C.H. Chen , H. Chen ,H. Chen , J. Chen , J. Chen , J. Chen , S. Chen , S.J. Chen , X. Chen , Y. Chen ,Y-H. Chen , H.C. Cheng , H.J. Cheng , A. Cheplakov , E. Cheremushkina ,R. Cherkaoui El Moursli , E. Cheu , K. Cheung , T.J.A. Chevalérias , L. Chevalier , V. Chiarella ,G. Chiarelli , G. Chiodini , A.S. Chisholm , A. Chitan , I. Chiu , Y.H. Chiu , M.V. Chizhov ,K. Choi , A.R. Chomont , Y. Chou , Y.S. Chow , L.D. Christopher , M.C. Chu ,X. Chu , J. Chudoba , J.J. Chwastowski , L. Chytka , D. Cieri , K.M. Ciesla , V. Cindro ,I.A. Cioară , A. Ciocio , F. Cirotto , Z.H. Citron , M. Citterio , D.A. Ciubotaru ,B.M. Ciungu , A. Clark , P.J. Clark , S.E. Clawson , C. Clement , Y. Coadou ,M. Cobal , A. Coccaro , J. Cochran , R. Coelho Lopes De Sa , H. Cohen , A.E.C. Coimbra ,B. Cole , A.P. Colijn , J. Collot , P. Conde Muiño , S.H. Connell , I.A. Connelly ,S. Constantinescu , F. Conventi , A.M. Cooper-Sarkar , F. Cormier , K.J.R. Cormier ,L.D. Corpe , M. Corradi , E.E. Corrigan , F. Corriveau , M.J. Costa , F. Costanza ,D. Costanzo , G. Cowan , J.W. Cowley , J. Crane , K. Cranmer , R.A. Creager ,S. Crépé-Renaudin , F. Crescioli , M. Cristinziani , V. Croft , G. Crosetti , A. Cueto ,T. Cuhadar Donszelmann , H. Cui , A.R. Cukierman , W.R. Cunningham , S. Czekierda ,44. Czodrowski , M.M. Czurylo , M.J. Da Cunha Sargedas De Sousa , J.V. Da Fonseca Pinto ,C. Da Via , W. Dabrowski , F. Dachs , T. Dado , S. Dahbi , T. Dai , C. Dallapiccola ,M. Dam , G. D’amen , V. D’Amico , J. Damp , J.R. Dandoy , M.F. Daneri , M. Danninger ,V. Dao , G. Darbo , O. Dartsi , A. Dattagupta , T. Daubney , S. D’Auria , C. David ,T. Davidek , D.R. Davis , I. Dawson , K. De , R. De Asmundis , M. De Beurs ,S. De Castro , N. De Groot , P. de Jong , H. De la Torre , A. De Maria , D. De Pedis ,A. De Salvo , U. De Sanctis , M. De Santis , A. De Santo , J.B. De Vivie De Regie ,D.V. Dedovich , A.M. Deiana , J. Del Peso , Y. Delabat Diaz , D. Delgove , F. Deliot ,C.M. Delitzsch , M. Della Pietra , D. Della Volpe , A. Dell’Acqua , L. Dell’Asta ,M. Delmastro , C. Delporte , P.A. Delsart , S. Demers , M. Demichev , G. Demontigny ,S.P. Denisov , L. D’Eramo , D. Derendarz , J.E. Derkaoui , F. Derue , P. Dervan , K. Desch ,K. Dette , C. Deutsch , M.R. Devesa , P.O. Deviveiros , F.A. Di Bello , A. Di Ciaccio ,L. Di Ciaccio , W.K. Di Clemente , C. Di Donato , A. Di Girolamo , G. Di Gregorio ,A. Di Luca , B. Di Micco , R. Di Nardo , K.F. Di Petrillo , R. Di Sipio , C. Diaconu ,F.A. Dias , T. Dias Do Vale , M.A. Diaz , F.G. Diaz Capriles , J. Dickinson , M. Didenko ,E.B. Diehl , J. Dietrich , S. Díez Cornell , C. Diez Pardos , A. Dimitrievska , W. Ding ,J. Dingfelder , S.J. Dittmeier , F. Dittus , F. Djama , T. Djobava , J.I. Djuvsland ,M.A.B. Do Vale , M. Dobre , D. Dodsworth , C. Doglioni , J. Dolejsi , Z. Dolezal ,M. Donadelli , B. Dong , J. Donini , A. D’onofrio , M. D’Onofrio , J. Dopke , A. Doria ,M.T. Dova , A.T. Doyle , E. Drechsler , E. Dreyer , T. Dreyer , A.S. Drobac , D. Du ,T.A. du Pree , Y. Duan , F. Dubinin , M. Dubovsky , A. Dubreuil , E. Duchovni ,G. Duckeck , O.A. Ducu , D. Duda , A. Dudarev , A.C. Dudder , E.M. Duffield ,M. D’uffizi , L. Duflot , M. Dührssen , C. Dülsen , M. Dumancic , A.E. Dumitriu ,M. Dunford , S. Dungs , A. Duperrin , H. Duran Yildiz , M. Düren , A. Durglishvili ,D. Duschinger , B. Dutta , D. Duvnjak , G.I. Dyckes , M. Dyndal , S. Dysch , B.S. Dziedzic ,M.G. Eggleston , T. Eifert , G. Eigen , K. Einsweiler , T. Ekelof , H. El Jarrari , V. Ellajosyula ,M. Ellert , F. Ellinghaus , A.A. Elliot , N. Ellis , J. Elmsheuser , M. Elsing , D. Emeliyanov ,A. Emerman , Y. Enari , M.B. Epland , J. Erdmann , A. Ereditato , P.A. Erland , M. Errenst ,M. Escalier , C. Escobar , O. Estrada Pastor , E. Etzion , G. Evans , H. Evans , M.O. Evans ,A. Ezhilov , F. Fabbri , L. Fabbri , V. Fabiani , G. Facini , R.M. Fakhrutdinov ,S. Falciano , P.J. Falke , S. Falke , J. Faltova , Y. Fang , Y. Fang , G. Fanourakis ,M. Fanti , M. Faraj , A. Farbin , A. Farilla , E.M. Farina , T. Farooque ,S.M. Farrington , P. Farthouat , F. Fassi , P. Fassnacht , D. Fassouliotis , M. Faucci Giannelli ,W.J. Fawcett , L. Fayard , O.L. Fedin , W. Fedorko , A. Fehr , M. Feickert , L. Feligioni ,A. Fell , C. Feng , M. Feng , M.J. Fenton , A.B. Fenyuk , S.W. Ferguson , J. Ferrando ,A. Ferrari , P. Ferrari , R. Ferrari , D.E. Ferreira de Lima , A. Ferrer , D. Ferrere ,C. Ferretti , F. Fiedler , A. Filipčič , F. Filthaut , K.D. Finelli , M.C.N. Fiolhais ,L. Fiorini , F. Fischer , J. Fischer , W.C. Fisher , T. Fitschen , I. Fleck , P. Fleischmann ,T. Flick , B.M. Flierl , L. Flores , L.R. Flores Castillo , F.M. Follega , N. Fomin ,J.H. Foo , G.T. Forcolin , B.C. Forland , A. Formica , F.A. Förster , A.C. Forti , E. Fortin ,M.G. Foti , D. Fournier , H. Fox , P. Francavilla , S. Francescato , M. Franchini ,S. Franchino , D. Francis , L. Franco , L. Franconi , M. Franklin , G. Frattari , A.N. Fray ,P.M. Freeman , B. Freund , W.S. Freund , E.M. Freundlich , D.C. Frizzell , D. Froidevaux ,J.A. Frost , M. Fujimoto , C. Fukunaga , E. Fullana Torregrosa , T. Fusayasu , J. Fuster ,A. Gabrielli , A. Gabrielli , S. Gadatsch , P. Gadow , G. Gagliardi , L.G. Gagnon ,G.E. Gallardo , E.J. Gallas , B.J. Gallop , R. Gamboa Goni , K.K. Gan , S. Ganguly ,J. Gao , Y. Gao , Y.S. Gao , F.M. Garay Walls , C. García , J.E. García Navarro ,45.A. García Pascual , C. Garcia-Argos , M. Garcia-Sciveres , R.W. Gardner , N. Garelli ,S. Gargiulo , C.A. Garner , V. Garonne , S.J. Gasiorowski , P. Gaspar , A. Gaudiello ,G. Gaudio , P. Gauzzi , I.L. Gavrilenko , A. Gavrilyuk , C. Gay , G. Gaycken ,E.N. Gazis , A.A. Geanta , C.M. Gee , C.N.P. Gee , J. Geisen , M. Geisen , C. Gemme ,M.H. Genest , C. Geng , S. Gentile , S. George , T. Geralis , L.O. Gerlach ,P. Gessinger-Befurt , G. Gessner , M. Ghasemi Bostanabad , M. Ghneimat , A. Ghosh ,A. Ghosh , B. Giacobbe , S. Giagu , N. Giangiacomi , P. Giannetti , A. Giannini ,G. Giannini , S.M. Gibson , M. Gignac , D.T. Gil , B.J. Gilbert , D. Gillberg , G. Gilles ,N.E.K. Gillwald , D.M. Gingrich , M.P. Giordani , P.F. Giraud , G. Giugliarelli ,D. Giugni , F. Giuli , S. Gkaitatzis , I. Gkialas , E.L. Gkougkousis , P. Gkountoumis ,L.K. Gladilin , C. Glasman , J. Glatzer , P.C.F. Glaysher , A. Glazov , G.R. Gledhill ,I. Gnesi , M. Goblirsch-Kolb , D. Godin , S. Goldfarb , T. Golling , D. Golubkov ,A. Gomes , R. Goncalves Gama , R. Gonçalo , G. Gonella , L. Gonella ,A. Gongadze , F. Gonnella , J.L. Gonski , S. González de la Hoz , S. Gonzalez Fernandez ,R. Gonzalez Lopez , C. Gonzalez Renteria , R. Gonzalez Suarez , S. Gonzalez-Sevilla ,G.R. Gonzalvo Rodriguez , L. Goossens , N.A. Gorasia , P.A. Gorbounov , H.A. Gordon ,B. Gorini , E. Gorini , A. Gorišek , A.T. Goshaw , M.I. Gostkin , C.A. Gottardo ,M. Gouighri , A.G. Goussiou , N. Govender , C. Goy , I. Grabowska-Bold , E.C. Graham ,J. Gramling , E. Gramstad , S. Grancagnolo , M. Grandi , V. Gratchev , P.M. Gravila ,F.G. Gravili , C. Gray , H.M. Gray , C. Grefe , K. Gregersen , I.M. Gregor , P. Grenier ,K. Grevtsov , C. Grieco , N.A. Grieser , A.A. Grillo , K. Grimm , S. Grinstein , J.-F. Grivaz ,S. Groh , E. Gross , J. Grosse-Knetter , Z.J. Grout , C. Grud , A. Grummer , J.C. Grundy ,L. Guan , W. Guan , C. Gubbels , J. Guenther , A. Guerguichon , J.G.R. Guerrero Rojas ,F. Guescini , D. Guest , R. Gugel , A. Guida , T. Guillemin , S. Guindon , J. Guo , W. Guo ,Y. Guo , Z. Guo , R. Gupta , S. Gurbuz , G. Gustavino , M. Guth , P. Gutierrez ,C. Gutschow , C. Guyot , C. Gwenlan , C.B. Gwilliam , E.S. Haaland , A. Haas , C. Haber ,H.K. Hadavand , A. Hadef , M. Haleem , J. Haley , J.J. Hall , G. Halladjian , G.D. Hallewell ,K. Hamano , H. Hamdaoui , M. Hamer , G.N. Hamity , K. Han , L. Han , L. Han , S. Han ,Y.F. Han , K. Hanagaki , M. Hance , D.M. Handl , M.D. Hank , R. Hankache , E. Hansen ,J.B. Hansen , J.D. Hansen , M.C. Hansen , P.H. Hansen , E.C. Hanson , K. Hara ,T. Harenberg , S. Harkusha , P.F. Harrison , N.M. Hartman , N.M. Hartmann , Y. Hasegawa ,A. Hasib , S. Hassani , S. Haug , R. Hauser , M. Havranek , C.M. Hawkes , R.J. Hawkings ,S. Hayashida , D. Hayden , C. Hayes , R.L. Hayes , C.P. Hays , J.M. Hays , H.S. Hayward ,S.J. Haywood , F. He , Y. He , M.P. Heath , V. Hedberg , A.L. Heggelund , N.D. Hehir ,C. Heidegger , K.K. Heidegger , W.D. Heidorn , J. Heilman , S. Heim , T. Heim ,B. Heinemann , J.G. Heinlein , J.J. Heinrich , L. Heinrich , J. Hejbal , L. Helary , A. Held ,S. Hellesund , C.M. Helling , S. Hellman , C. Helsens , R.C.W. Henderson , L. Henkelmann ,A.M. Henriques Correia , H. Herde , Y. Hernández Jiménez , H. Herr , M.G. Herrmann ,T. Herrmann , G. Herten , R. Hertenberger , L. Hervas , G.G. Hesketh , N.P. Hessey , H. Hibi ,S. Higashino , E. Higón-Rodriguez , K. Hildebrand , J.C. Hill , K.K. Hill , K.H. Hiller ,S.J. Hillier , M. Hils , I. Hinchliffe , F. Hinterkeuser , M. Hirose , S. Hirose , D. Hirschbuehl ,B. Hiti , O. Hladik , J. Hobbs , R. Hobincu , N. Hod , M.C. Hodgkinson , A. Hoecker ,D. Hohn , D. Hohov , T. Holm , T.R. Holmes , M. Holzbock , L.B.A.H. Hommels , T.M. Hong ,J.C. Honig , A. Hönle , B.H. Hooberman , W.H. Hopkins , Y. Horii , P. Horn , L.A. Horyn ,S. Hou , A. Hoummada , J. Howarth , J. Hoya , M. Hrabovsky , J. Hrivnac , A. Hrynevich ,T. Hryn’ova , P.J. Hsu , S.-C. Hsu , Q. Hu , S. Hu , Y.F. Hu , D.P. Huang , X. Huang ,Y. Huang , Y. Huang , Z. Hubacek , F. Hubaut , M. Huebner , F. Huegging , T.B. Huffman ,46. Huhtinen , R. Hulsken , R.F.H. Hunter , N. Huseynov , J. Huston , J. Huth , R. Hyneman ,S. Hyrych , G. Iacobucci , G. Iakovidis , I. Ibragimov , L. Iconomidou-Fayard , P. Iengo ,R. Ignazzi , R. Iguchi , T. Iizawa , Y. Ikegami , M. Ikeno , N. Ilic , F. Iltzsche , H. Imam ,G. Introzzi , M. Iodice , K. Iordanidou , V. Ippolito , M.F. Isacson , M. Ishino ,W. Islam , C. Issever , S. Istin , J.M. Iturbe Ponce , R. Iuppa , A. Ivina , J.M. Izen ,V. Izzo , P. Jacka , P. Jackson , R.M. Jacobs , B.P. Jaeger , V. Jain , G. Jäkel , K.B. Jakobi ,K. Jakobs , T. Jakoubek , J. Jamieson , K.W. Janas , R. Jansky , M. Janus , P.A. Janus ,G. Jarlskog , A.E. Jaspan , N. Javadov , T. Javůrek , M. Javurkova , F. Jeanneau , L. Jeanty ,J. Jejelava , P. Jenni , N. Jeong , S. Jézéquel , J. Jia , Z. Jia , H. Jiang , Y. Jiang , Z. Jiang ,S. Jiggins , F.A. Jimenez Morales , J. Jimenez Pena , S. Jin , A. Jinaru , O. Jinnouchi ,H. Jivan , P. Johansson , K.A. Johns , C.A. Johnson , E. Jones , R.W.L. Jones , S.D. Jones ,T.J. Jones , J. Jovicevic , X. Ju , J.J. Junggeburth , A. Juste Rozas , A. Kaczmarska ,M. Kado , H. Kagan , M. Kagan , A. Kahn , C. Kahra , T. Kaji , E. Kajomovitz ,C.W. Kalderon , A. Kaluza , A. Kamenshchikov , M. Kaneda , N.J. Kang , S. Kang ,Y. Kano , J. Kanzaki , L.S. Kaplan , D. Kar , K. Karava , M.J. Kareem , I. Karkanias ,S.N. Karpov , Z.M. Karpova , V. Kartvelishvili , A.N. Karyukhin , E. Kasimi , A. Kastanas ,C. Kato , J. Katzy , K. Kawade , K. Kawagoe , T. Kawaguchi , T. Kawamoto , G. Kawamura ,E.F. Kay , F.I. Kaya , S. Kazakos , V.F. Kazanin , J.M. Keaveney , R. Keeler ,J.S. Keller , E. Kellermann , D. Kelsey , J.J. Kempster , J. Kendrick , K.E. Kennedy , O. Kepka ,S. Kersten , B.P. Kerševan , S. Ketabchi Haghighat , F. Khalil-Zada , M. Khandoga ,A. Khanov , A.G. Kharlamov , T. Kharlamova , E.E. Khoda , T.J. Khoo ,G. Khoriauli , E. Khramov , J. Khubua , S. Kido , M. Kiehn , E. Kim , Y.K. Kim ,N. Kimura , A. Kirchhoff , D. Kirchmeier , J. Kirk , A.E. Kiryunin , T. Kishimoto ,D.P. Kisliuk , V. Kitali , C. Kitsaki , O. Kivernyk , T. Klapdor-Kleingrothaus , M. Klassen ,C. Klein , M.H. Klein , M. Klein , U. Klein , K. Kleinknecht , P. Klimek , A. Klimentov ,F. Klimpel , T. Klingl , T. Klioutchnikova , F.F. Klitzner , P. Kluit , S. Kluth , E. Kneringer ,E.B.F.G. Knoops , A. Knue , D. Kobayashi , M. Kobel , M. Kocian , T. Kodama , P. Kodys ,D.M. Koeck , P.T. Koenig , T. Koffas , N.M. Köhler , M. Kolb , I. Koletsou , T. Komarek ,T. Kondo , K. Köneke , A.X.Y. Kong , A.C. König , T. Kono , V. Konstantinides ,N. Konstantinidis , B. Konya , R. Kopeliansky , S. Koperny , K. Korcyl , K. Kordas ,G. Koren , A. Korn , I. Korolkov , E.V. Korolkova , N. Korotkova , O. Kortner , S. Kortner ,V.V. Kostyukhin , A. Kotsokechagia , A. Kotwal , A. Koulouris ,A. Kourkoumeli-Charalampidi , C. Kourkoumelis , E. Kourlitis , V. Kouskoura , R. Kowalewski ,W. Kozanecki , A.S. Kozhin , V.A. Kramarenko , G. Kramberger , D. Krasnopevtsev ,M.W. Krasny , A. Krasznahorkay , D. Krauss , J.A. Kremer , J. Kretzschmar , K. Kreul ,P. Krieger , F. Krieter , S. Krishnamurthy , A. Krishnan , M. Krivos , K. Krizka ,K. Kroeninger , H. Kroha , J. Kroll , J. Kroll , K.S. Krowpman , U. Kruchonak , H. Krüger ,N. Krumnack , M.C. Kruse , J.A. Krzysiak , A. Kubota , O. Kuchinskaia , S. Kuday ,D. Kuechler , J.T. Kuechler , S. Kuehn , T. Kuhl , V. Kukhtin , Y. Kulchitsky , S. Kuleshov ,Y.P. Kulinich , M. Kuna , A. Kupco , T. Kupfer , O. Kuprash , H. Kurashige ,L.L. Kurchaninov , Y.A. Kurochkin , A. Kurova , M.G. Kurth , E.S. Kuwertz , M. Kuze ,A.K. Kvam , J. Kvita , T. Kwan , C. Lacasta , F. Lacava , D.P.J. Lack , H. Lacker ,D. Lacour , E. Ladygin , R. Lafaye , B. Laforge , T. Lagouri , S. Lai , I.K. Lakomiec ,J.E. Lambert , S. Lammers , W. Lampl , C. Lampoudis , E. Lançon , U. Landgraf ,M.P.J. Landon , V.S. Lang , J.C. Lange , R.J. Langenberg , A.J. Lankford , F. Lanni ,K. Lantzsch , A. Lanza , A. Lapertosa , J.F. Laporte , T. Lari , F. Lasagni Manghi ,M. Lassnig , V. Latonova , T.S. Lau , A. Laudrain , A. Laurier , M. Lavorgna ,47.D. Lawlor , M. Lazzaroni , B. Le , E. Le Guirriec , A. Lebedev , M. LeBlanc ,T. LeCompte , F. Ledroit-Guillon , A.C.A. Lee , C.A. Lee , G.R. Lee , L. Lee , S.C. Lee ,S. Lee , B. Lefebvre , H.P. Lefebvre , M. Lefebvre , C. Leggett , K. Lehmann , N. Lehmann ,G. Lehmann Miotto , W.A. Leight , A. Leisos , M.A.L. Leite , C.E. Leitgeb , R. Leitner ,K.J.C. Leney , T. Lenz , S. Leone , C. Leonidopoulos , A. Leopold , C. Leroy , R. Les ,C.G. Lester , M. Levchenko , J. Levêque , D. Levin , L.J. Levinson , D.J. Lewis , B. Li ,B. Li , C-Q. Li , F. Li , H. Li , H. Li , J. Li , K. Li , L. Li , M. Li , Q.Y. Li ,S. Li , X. Li , Y. Li , Z. Li , Z. Li , Z. Li , Z. Li , Z. Liang , M. Liberatore ,B. Liberti , K. Lie , S. Lim , C.Y. Lin , K. Lin , R.A. Linck , R.E. Lindley , J.H. Lindon ,A. Linss , A.L. Lionti , E. Lipeles , A. Lipniacka , T.M. Liss , A. Lister , J.D. Little , B. Liu ,B.X. Liu , H.B. Liu , J.B. Liu , J.K.K. Liu , K. Liu , M. Liu , M.Y. Liu , P. Liu ,X. Liu , Y. Liu , Y. Liu , Y.L. Liu , Y.W. Liu , M. Livan , A. Lleres ,J. Llorente Merino , S.L. Lloyd , C.Y. Lo , E.M. Lobodzinska , P. Loch , S. Loffredo ,T. Lohse , K. Lohwasser , M. Lokajicek , J.D. Long , R.E. Long , I. Longarini , L. Longo ,I. Lopez Paz , A. Lopez Solis , J. Lorenz , N. Lorenzo Martinez , A.M. Lory , A. Lösle ,X. Lou , X. Lou , A. Lounis , J. Love , P.A. Love , J.J. Lozano Bahilo , M. Lu , Y.J. Lu ,H.J. Lubatti , C. Luci , F.L. Lucio Alves , A. Lucotte , F. Luehring , I. Luise ,L. Luminari , B. Lund-Jensen , N.A. Luongo , M.S. Lutz , D. Lynn , H. Lyons , R. Lysak ,E. Lytken , F. Lyu , V. Lyubushkin , T. Lyubushkina , H. Ma , L.L. Ma , Y. Ma ,D.M. Mac Donell , G. Maccarrone , C.M. Macdonald , J.C. MacDonald , J. Machado Miguens ,R. Madar , W.F. Mader , M. Madugoda Ralalage Don , N. Madysa , J. Maeda , T. Maeno ,M. Maerker , V. Magerl , N. Magini , J. Magro , D.J. Mahon , C. Maidantchik ,A. Maio , K. Maj , O. Majersky , S. Majewski , Y. Makida , N. Makovec ,B. Malaescu , Pa. Malecki , V.P. Maleev , F. Malek , D. Malito , U. Mallik , C. Malone ,S. Maltezos , S. Malyukov , J. Mamuzic , G. Mancini , J.P. Mandalia , I. Mandić ,L. Manhaes de Andrade Filho , I.M. Maniatis , J. Manjarres Ramos , K.H. Mankinen , A. Mann ,A. Manousos , B. Mansoulie , I. Manthos , S. Manzoni , A. Marantis , G. Marceca ,L. Marchese , G. Marchiori , M. Marcisovsky , L. Marcoccia , C. Marcon , M. Marjanovic ,Z. Marshall , M.U.F. Martensson , S. Marti-Garcia , C.B. Martin , T.A. Martin , V.J. Martin ,B. Martin dit Latour , L. Martinelli , M. Martinez , P. Martinez Agullo ,V.I. Martinez Outschoorn , S. Martin-Haugh , V.S. Martoiu , A.C. Martyniuk , A. Marzin ,S.R. Maschek , L. Masetti , T. Mashimo , R. Mashinistov , J. Masik , A.L. Maslennikov ,L. Massa , P. Massarotti , P. Mastrandrea , A. Mastroberardino , T. Masubuchi ,D. Matakias , A. Matic , N. Matsuzawa , P. Mättig , J. Maurer , B. Maček ,D.A. Maximov , R. Mazini , I. Maznas , S.M. Mazza , J.P. Mc Gowan , S.P. Mc Kee ,T.G. McCarthy , W.P. McCormack , E.F. McDonald , A.E. McDougall , J.A. Mcfayden ,G. Mchedlidze , M.A. McKay , K.D. McLean , S.J. McMahon , P.C. McNamara ,C.J. McNicol , R.A. McPherson , J.E. Mdhluli , Z.A. Meadows , S. Meehan , T. Megy ,S. Mehlhase , A. Mehta , B. Meirose , D. Melini , B.R. Mellado Garcia , J.D. Mellenthin ,M. Melo , F. Meloni , A. Melzer , E.D. Mendes Gouveia , A.M. Mendes Jacques Da Costa ,H.Y. Meng , L. Meng , X.T. Meng , S. Menke , E. Meoni , S. Mergelmeyer ,S.A.M. Merkt , C. Merlassino , P. Mermod , L. Merola , C. Meroni , G. Merz ,O. Meshkov , J.K.R. Meshreki , J. Metcalfe , A.S. Mete , C. Meyer , J-P. Meyer ,M. Michetti , R.P. Middleton , L. Mijović , G. Mikenberg , M. Mikestikova , M. Mikuž ,H. Mildner , A. Milic , C.D. Milke , D.W. Miller , L.S. Miller , A. Milov , D.A. Milstead ,A.A. Minaenko , I.A. Minashvili , L. Mince , A.I. Mincer , B. Mindur , M. Mineev ,Y. Minegishi , Y. Mino , L.M. Mir , M. Mironova , T. Mitani , J. Mitrevski , V.A. Mitsou ,48. Mittal , O. Miu , A. Miucci , P.S. Miyagawa , A. Mizukami , J.U. Mjörnmark ,T. Mkrtchyan , M. Mlynarikova , T. Moa , S. Mobius , K. Mochizuki , P. Moder ,P. Mogg , S. Mohapatra , R. Moles-Valls , K. Mönig , E. Monnier , A. Montalbano ,J. Montejo Berlingen , M. Montella , F. Monticelli , S. Monzani , N. Morange ,A.L. Moreira De Carvalho , D. Moreno , M. Moreno Llácer , C. Moreno Martinez ,P. Morettini , M. Morgenstern , S. Morgenstern , D. Mori , M. Morii , M. Morinaga ,V. Morisbak , A.K. Morley , G. Mornacchi , A.P. Morris , L. Morvaj , P. Moschovakos ,B. Moser , M. Mosidze , T. Moskalets , P. Moskvitina , J. Moss , E.J.W. Moyse ,S. Muanza , J. Mueller , R.S.P. Mueller , D. Muenstermann , G.A. Mullier , D.P. Mungo ,J.L. Munoz Martinez , F.J. Munoz Sanchez , P. Murin , W.J. Murray , A. Murrone ,J.M. Muse , M. Muškinja , C. Mwewa , A.G. Myagkov , A.A. Myers , G. Myers , J. Myers ,M. Myska , B.P. Nachman , O. Nackenhorst , A.Nag Nag , K. Nagai , K. Nagano , Y. Nagasaka ,J.L. Nagle , E. Nagy , A.M. Nairz , Y. Nakahama , K. Nakamura , T. Nakamura , H. Nanjo ,F. Napolitano , R.F. Naranjo Garcia , R. Narayan , I. Naryshkin , M. Naseri , T. Naumann ,G. Navarro , P.Y. Nechaeva , F. Nechansky , T.J. Neep , A. Negri , M. Negrini , C. Nellist ,C. Nelson , M.E. Nelson , S. Nemecek , M. Nessi , M.S. Neubauer , F. Neuhaus ,M. Neumann , R. Newhouse , P.R. Newman , C.W. Ng , Y.S. Ng , Y.W.Y. Ng , B. Ngair ,H.D.N. Nguyen , T. Nguyen Manh , E. Nibigira , R.B. Nickerson , R. Nicolaidou ,D.S. Nielsen , J. Nielsen , M. Niemeyer , N. Nikiforou , V. Nikolaenko , I. Nikolic-Audit ,K. Nikolopoulos , P. Nilsson , H.R. Nindhito , A. Nisati , N. Nishu , R. Nisius , I. Nitsche ,T. Nitta , T. Nobe , D.L. Noel , Y. Noguchi , I. Nomidis , M.A. Nomura , M. Nordberg ,J. Novak , T. Novak , O. Novgorodova , R. Novotny , L. Nozka , K. Ntekas , E. Nurse ,F.G. Oakham , J. Ocariz , A. Ochi , I. Ochoa , J.P. Ochoa-Ricoux , K. O’Connor , S. Oda ,S. Odaka , S. Oerdek , A. Ogrodnik , A. Oh , C.C. Ohm , H. Oide , R. Oishi , M.L. Ojeda ,H. Okawa , Y. Okazaki , M.W. O’Keefe , Y. Okumura , A. Olariu , L.F. Oleiro Seabra ,S.A. Olivares Pino , D. Oliveira Damazio , J.L. Oliver , M.J.R. Olsson , A. Olszewski ,J. Olszowska , Ö.O. Öncel , D.C. O’Neil , A.P. O’neill , A. Onofre , P.U.E. Onyisi ,H. Oppen , R.G. Oreamuno Madriz , M.J. Oreglia , G.E. Orellana , D. Orestano ,N. Orlando , R.S. Orr , V. O’Shea , R. Ospanov , G. Otero y Garzon , H. Otono , P.S. Ott ,G.J. Ottino , M. Ouchrif , J. Ouellette , F. Ould-Saada , A. Ouraou , Q. Ouyang , M. Owen ,R.E. Owen , V.E. Ozcan , N. Ozturk , J. Pacalt , H.A. Pacey , K. Pachal , A. Pacheco Pages ,C. Padilla Aranda , S. Pagan Griso , G. Palacino , S. Palazzo , S. Palestini , M. Palka , P. Palni ,C.E. Pandini , J.G. Panduro Vazquez , P. Pani , G. Panizzo , L. Paolozzi , C. Papadatos ,K. Papageorgiou , S. Parajuli , A. Paramonov , C. Paraskevopoulos , D. Paredes Hernandez ,S.R. Paredes Saenz , B. Parida , T.H. Park , A.J. Parker , M.A. Parker , F. Parodi ,E.W. Parrish , J.A. Parsons , U. Parzefall , L. Pascual Dominguez , V.R. Pascuzzi ,J.M.P. Pasner , F. Pasquali , E. Pasqualucci , S. Passaggio , F. Pastore , P. Pasuwan ,S. Pataraia , J.R. Pater , A. Pathak , J. Patton , T. Pauly , J. Pearkes , M. Pedersen ,L. Pedraza Diaz , R. Pedro , T. Peiffer , S.V. Peleganchuk , O. Penc , C. Peng ,H. Peng , B.S. Peralva , M.M. Perego , A.P. Pereira Peixoto , L. Pereira Sanchez ,D.V. Perepelitsa , E. Perez Codina , L. Perini , H. Pernegger , S. Perrella , A. Perrevoort ,K. Peters , R.F.Y. Peters , B.A. Petersen , T.C. Petersen , E. Petit , V. Petousis , C. Petridou ,F. Petrucci , M. Pettee , N.E. Pettersson , K. Petukhova , A. Peyaud , R. Pezoa ,L. Pezzotti , T. Pham , P.W. Phillips , M.W. Phipps , G. Piacquadio , E. Pianori ,A. Picazio , R.H. Pickles , R. Piegaia , D. Pietreanu , J.E. Pilcher , A.D. Pilkington ,M. Pinamonti , J.L. Pinfold , C. Pitman Donaldson , M. Pitt , L. Pizzimento , A. Pizzini ,M.-A. Pleier , V. Plesanovs , V. Pleskot , E. Plotnikova , P. Podberezko , R. Poettgen ,49. Poggi , L. Poggioli , I. Pogrebnyak , D. Pohl , I. Pokharel , G. Polesello , A. Poley ,A. Policicchio , R. Polifka , A. Polini , C.S. Pollard , V. Polychronakos , D. Ponomarenko ,L. Pontecorvo , S. Popa , G.A. Popeneciu , L. Portales , D.M. Portillo Quintero , S. Pospisil ,K. Potamianos , I.N. Potrap , C.J. Potter , H. Potti , T. Poulsen , J. Poveda , T.D. Powell ,G. Pownall , M.E. Pozo Astigarraga , A. Prades Ibanez , P. Pralavorio , M.M. Prapa , S. Prell ,D. Price , M. Primavera , M.L. Proffitt , N. Proklova , K. Prokofiev , F. Prokoshin ,S. Protopopescu , J. Proudfoot , M. Przybycien , D. Pudzha , A. Puri , P. Puzo ,D. Pyatiizbyantseva , J. Qian , Y. Qin , A. Quadt , M. Queitsch-Maitland , G. Rabanal Bolanos ,M. Racko , F. Ragusa , G. Rahal , J.A. Raine , S. Rajagopalan , A. Ramirez Morales ,K. Ran , D.F. Rassloff , D.M. Rauch , F. Rauscher , S. Rave , B. Ravina , I. Ravinovich ,J.H. Rawling , M. Raymond , A.L. Read , N.P. Readioff , M. Reale , D.M. Rebuzzi ,G. Redlinger , K. Reeves , D. Reikher , A. Reiss , A. Rej , C. Rembser , A. Renardi ,M. Renda , M.B. Rendel , A.G. Rennie , S. Resconi , E.D. Resseguie , S. Rettie , B. Reynolds ,E. Reynolds , O.L. Rezanova , P. Reznicek , E. Ricci , R. Richter , S. Richter ,E. Richter-Was , M. Ridel , P. Rieck , O. Rifki , M. Rijssenbeek , A. Rimoldi ,M. Rimoldi , L. Rinaldi , T.T. Rinn , G. Ripellino , I. Riu , P. Rivadeneira ,J.C. Rivera Vergara , F. Rizatdinova , E. Rizvi , C. Rizzi , S.H. Robertson , M. Robin ,D. Robinson , C.M. Robles Gajardo , M. Robles Manzano , A. Robson , A. Rocchi ,C. Roda , S. Rodriguez Bosca , A. Rodriguez Rodriguez , A.M. Rodríguez Vera , S. Roe ,J. Roggel , O. Røhne , R. Röhrig , R.A. Rojas , B. Roland , C.P.A. Roland , J. Roloff ,A. Romaniouk , M. Romano , N. Rompotis , M. Ronzani , L. Roos , S. Rosati , G. Rosin ,B.J. Rosser , E. Rossi , E. Rossi , E. Rossi , L.P. Rossi , L. Rossini , R. Rosten ,M. Rotaru , B. Rottler , D. Rousseau , G. Rovelli , A. Roy , D. Roy , A. Rozanov ,Y. Rozen , X. Ruan , T.A. Ruggeri , F. Rühr , A. Ruiz-Martinez , A. Rummler , Z. Rurikova ,N.A. Rusakovich , H.L. Russell , L. Rustige , J.P. Rutherfoord , E.M. Rüttinger , M. Rybar ,G. Rybkin , E.B. Rye , A. Ryzhov , J.A. Sabater Iglesias , P. Sabatini , L. Sabetta ,S. Sacerdoti , H.F-W. Sadrozinski , R. Sadykov , F. Safai Tehrani , B. Safarzadeh Samani ,M. Safdari , P. Saha , S. Saha , M. Sahinsoy , A. Sahu , M. Saimpert , M. Saito , T. Saito ,H. Sakamoto , D. Salamani , G. Salamanna , A. Salnikov , J. Salt , A. Salvador Salas ,D. Salvatore , F. Salvatore , A. Salvucci , A. Salzburger , J. Samarati , D. Sammel ,D. Sampsonidis , D. Sampsonidou , J. Sánchez , A. Sanchez Pineda , H. Sandaker ,C.O. Sander , I.G. Sanderswood , M. Sandhoff , C. Sandoval , D.P.C. Sankey , M. Sannino ,Y. Sano , A. Sansoni , C. Santoni , H. Santos , S.N. Santpur , A. Santra , K.A. Saoucha ,A. Sapronov , J.G. Saraiva , O. Sasaki , K. Sato , F. Sauerburger , E. Sauvan , P. Savard ,R. Sawada , C. Sawyer , L. Sawyer , I. Sayago Galvan , C. Sbarra , A. Sbrizzi ,T. Scanlon , J. Schaarschmidt , P. Schacht , D. Schaefer , L. Schaefer , U. Schäfer ,A.C. Schaffer , D. Schaile , R.D. Schamberger , E. Schanet , C. Scharf , N. Scharmberg ,V.A. Schegelsky , D. Scheirich , F. Schenck , M. Schernau , C. Schiavi , L.K. Schildgen ,Z.M. Schillaci , E.J. Schioppa , M. Schioppa , K.E. Schleicher , S. Schlenker ,K.R. Schmidt-Sommerfeld , K. Schmieden , C. Schmitt , S. Schmitt , L. Schoeffel ,A. Schoening , P.G. Scholer , E. Schopf , M. Schott , J.F.P. Schouwenberg , J. Schovancova ,S. Schramm , F. Schroeder , A. Schulte , H-C. Schultz-Coulon , M. Schumacher ,B.A. Schumm , Ph. Schune , A. Schwartzman , T.A. Schwarz , Ph. Schwemling ,R. Schwienhorst , A. Sciandra , G. Sciolla , F. Scuri , F. Scutti , L.M. Scyboz ,C.D. Sebastiani , K. Sedlaczek , P. Seema , S.C. Seidel , A. Seiden , B.D. Seidlitz , T. Seiss ,C. Seitz , J.M. Seixas , G. Sekhniaidze , S.J. Sekula , N. Semprini-Cesari , S. Sen ,C. Serfon , L. Serin , L. Serkin , M. Sessa , H. Severini , S. Sevova , F. Sforza ,50. Sfyrla , E. Shabalina , J.D. Shahinian , N.W. Shaikh , D. Shaked Renous , L.Y. Shan ,M. Shapiro , A. Sharma , A.S. Sharma , P.B. Shatalov , K. Shaw , S.M. Shaw , M. Shehade ,Y. Shen , A.D. Sherman , P. Sherwood , L. Shi , C.O. Shimmin , Y. Shimogama ,M. Shimojima , J.D. Shinner , I.P.J. Shipsey , S. Shirabe , M. Shiyakova , J. Shlomi ,A. Shmeleva , M.J. Shochet , J. Shojaii , D.R. Shope , S. Shrestha , E.M. Shrif , M.J. Shroff ,E. Shulga , P. Sicho , A.M. Sickles , E. Sideras Haddad , O. Sidiropoulou , A. Sidoti ,F. Siegert , Dj. Sijacki , M.Jr. Silva , M.V. Silva Oliveira , S.B. Silverstein , S. Simion ,R. Simoniello , C.J. Simpson-allsop , S. Simsek , P. Sinervo , V. Sinetckii , S. Singh ,S. Sinha , M. Sioli , I. Siral , S.Yu. Sivoklokov , J. Sjölin , A. Skaf , E. Skorda ,P. Skubic , M. Slawinska , K. Sliwa , V. Smakhtin , B.H. Smart , J. Smiesko , N. Smirnov ,S.Yu. Smirnov , Y. Smirnov , L.N. Smirnova , O. Smirnova , E.A. Smith , H.A. Smith ,M. Smizanska , K. Smolek , A. Smykiewicz , A.A. Snesarev , H.L. Snoek , I.M. Snyder ,S. Snyder , R. Sobie , A. Soffer , A. Søgaard , F. Sohns , C.A. Solans Sanchez ,E.Yu. Soldatov , U. Soldevila , A.A. Solodkov , A. Soloshenko , O.V. Solovyanov ,V. Solovyev , P. Sommer , H. Son , A. Sonay , W. Song , W.Y. Song , A. Sopczak ,A.L. Sopio , F. Sopkova , S. Sottocornola , R. Soualah , A.M. Soukharev , D. South ,S. Spagnolo , M. Spalla , M. Spangenberg , F. Spanò , D. Sperlich , T.M. Spieker ,G. Spigo , M. Spina , D.P. Spiteri , M. Spousta , A. Stabile , B.L. Stamas , R. Stamen ,M. Stamenkovic , A. Stampekis , E. Stanecka , B. Stanislaus , M.M. Stanitzki , M. Stankaityte ,B. Stapf , E.A. Starchenko , G.H. Stark , J. Stark , P. Staroba , P. Starovoitov , S. Stärz ,R. Staszewski , G. Stavropoulos , M. Stegler , P. Steinberg , A.L. Steinhebel , B. Stelzer ,H.J. Stelzer , O. Stelzer-Chilton , H. Stenzel , T.J. Stevenson , G.A. Stewart , M.C. Stockton ,G. Stoicea , M. Stolarski , S. Stonjek , A. Straessner , J. Strandberg , S. Strandberg ,M. Strauss , T. Strebler , P. Strizenec , R. Ströhmer , D.M. Strom , R. Stroynowski ,A. Strubig , S.A. Stucci , B. Stugu , J. Stupak , N.A. Styles , D. Su , W. Su ,X. Su , N.B. Suarez , V.V. Sulin , M.J. Sullivan , D.M.S. Sultan , S. Sultansoy , T. Sumida ,S. Sun , X. Sun , C.J.E. Suster , M.R. Sutton , S. Suzuki , M. Svatos , M. Swiatlowski ,S.P. Swift , T. Swirski , A. Sydorenko , I. Sykora , M. Sykora , T. Sykora , D. Ta ,K. Tackmann , J. Taenzer , A. Taffard , R. Tafirout , E. Tagiev , R.H.M. Taibah ,R. Takashima , K. Takeda , T. Takeshita , E.P. Takeva , Y. Takubo , M. Talby ,A.A. Talyshev , K.C. Tam , N.M. Tamir , J. Tanaka , R. Tanaka , S. Tapia Araya ,S. Tapprogge , A. Tarek Abouelfadl Mohamed , S. Tarem , K. Tariq , G. Tarna ,G.F. Tartarelli , P. Tas , M. Tasevsky , E. Tassi , G. Tateno , A. Tavares Delgado ,Y. Tayalati , A.J. Taylor , G.N. Taylor , W. Taylor , H. Teagle , A.S. Tee ,R. Teixeira De Lima , P. Teixeira-Dias , H. Ten Kate , J.J. Teoh , K. Terashi , J. Terron ,S. Terzo , M. Testa , R.J. Teuscher , N. Themistokleous , T. Theveneaux-Pelzer , D.W. Thomas ,J.P. Thomas , E.A. Thompson , P.D. Thompson , E. Thomson , E.J. Thorpe , V.O. Tikhomirov ,Yu.A. Tikhonov , S. Timoshenko , P. Tipton , S. Tisserant , K. Todome ,S. Todorova-Nova , S. Todt , J. Tojo , S. Tokár , K. Tokushuku , E. Tolley , R. Tombs ,K.G. Tomiwa , M. Tomoto , L. Tompkins , P. Tornambe , E. Torrence , H. Torres ,E. Torró Pastor , M. Toscani , C. Tosciri , J. Toth , D.R. Tovey , A. Traeet , C.J. Treado ,T. Trefzger , F. Tresoldi , A. Tricoli , I.M. Trigger , S. Trincaz-Duvoid , D.A. Trischuk ,W. Trischuk , B. Trocmé , A. Trofymov , C. Troncon , F. Trovato , L. Truong , M. Trzebinski ,A. Trzupek , F. Tsai , P.V. Tsiareshka , A. Tsirigotis , V. Tsiskaridze , E.G. Tskhadadze ,M. Tsopoulou , I.I. Tsukerman , V. Tsulaia , S. Tsuno , D. Tsybychev , Y. Tu , A. Tudorache ,V. Tudorache , A.N. Tuna , S. Turchikhin , D. Turgeman , I. Turk Cakir , R.J. Turner ,R. Turra , P.M. Tuts , S. Tzamarias , E. Tzovara , K. Uchida , F. Ukegawa , G. Unal ,51. Unal , A. Undrus , G. Unel , F.C. Ungaro , Y. Unno , K. Uno , J. Urban , P. Urquijo ,G. Usai , Z. Uysal , V. Vacek , B. Vachon , K.O.H. Vadla , T. Vafeiadis , A. Vaidya ,C. Valderanis , E. Valdes Santurio , M. Valente , S. Valentinetti , A. Valero , L. Valéry ,R.A. Vallance , A. Vallier , J.A. Valls Ferrer , T.R. Van Daalen , P. Van Gemmeren , S. Van Stroud ,I. Van Vulpen , M. Vanadia , W. Vandelli , M. Vandenbroucke , E.R. Vandewall ,D. Vannicola , R. Vari , E.W. Varnes , C. Varni , T. Varol , D. Varouchas , K.E. Varvell ,M.E. Vasile , G.A. Vasquez , F. Vazeille , D. Vazquez Furelos , T. Vazquez Schroeder , J. Veatch ,V. Vecchio , M.J. Veen , L.M. Veloce , F. Veloso , S. Veneziano , A. Ventura ,A. Verbytskyi , V. Vercesi , M. Verducci , C.M. Vergel Infante , C. Vergis , W. Verkerke ,A.T. Vermeulen , J.C. Vermeulen , C. Vernieri , P.J. Verschuuren , M.C. Vetterli ,N. Viaux Maira , T. Vickey , O.E. Vickey Boeriu , G.H.A. Viehhauser , L. Vigani ,M. Villa , M. Villaplana Perez , E.M. Villhauer , E. Vilucchi , M.G. Vincter , G.S. Virdee ,A. Vishwakarma , C. Vittori , I. Vivarelli , M. Vogel , P. Vokac , J. Von Ahnen ,S.E. von Buddenbrock , E. Von Toerne , V. Vorobel , K. Vorobev , M. Vos , J.H. Vossebeld ,M. Vozak , N. Vranjes , M. Vranjes Milosavljevic , V. Vrba , M. Vreeswijk , N.K. Vu ,R. Vuillermet , I. Vukotic , S. Wada , P. Wagner , W. Wagner , J. Wagner-Kuhr , S. Wahdan ,H. Wahlberg , R. Wakasa , V.M. Walbrecht , J. Walder , R. Walker , S.D. Walker ,W. Walkowiak , V. Wallangen , A.M. Wang , A.Z. Wang , C. Wang , C. Wang , H. Wang ,H. Wang , J. Wang , P. Wang , Q. Wang , R.-J. Wang , R. Wang , R. Wang , S.M. Wang ,W.T. Wang , W. Wang , W.X. Wang , Y. Wang , Z. Wang , C. Wanotayaroj , A. Warburton ,C.P. Ward , R.J. Ward , N. Warrack , A.T. Watson , M.F. Watson , G. Watts , B.M. Waugh ,A.F. Webb , C. Weber , M.S. Weber , S.A. Weber , S.M. Weber , Y. Wei , A.R. Weidberg ,J. Weingarten , M. Weirich , C. Weiser , P.S. Wells , T. Wenaus , B. Wendland , T. Wengler ,S. Wenig , N. Wermes , M. Wessels , T.D. Weston , K. Whalen , A.M. Wharton , A.S. White ,A. White , M.J. White , D. Whiteson , B.W. Whitmore , W. Wiedenmann , C. Wiel , M. Wielers ,N. Wieseotte , C. Wiglesworth , L.A.M. Wiik-Fuchs , H.G. Wilkens , L.J. Wilkins ,D.M. Williams , H.H. Williams , S. Williams , S. Willocq , P.J. Windischhofer ,I. Wingerter-Seez , E. Winkels , F. Winklmeier , B.T. Winter , M. Wittgen , M. Wobisch ,A. Wolf , R. Wölker , J. Wollrath , M.W. Wolter , H. Wolters , V.W.S. Wong ,A.F. Wongel , N.L. Woods , S.D. Worm , B.K. Wosiek , K.W. Woźniak , K. Wraight , S.L. Wu ,X. Wu , Y. Wu , J. Wuerzinger , T.R. Wyatt , B.M. Wynne , S. Xella , J. Xiang , X. Xiao ,X. Xie , I. Xiotidis , D. Xu , H. Xu , H. Xu , L. Xu , R. Xu , T. Xu , W. Xu , Y. Xu ,Z. Xu , Z. Xu , B. Yabsley , S. Yacoob , D.P. Yallup , N. Yamaguchi , Y. Yamaguchi ,A. Yamamoto , M. Yamatani , T. Yamazaki , Y. Yamazaki , J. Yan , Z. Yan , H.J. Yang ,H.T. Yang , S. Yang , T. Yang , X. Yang , X. Yang , Y. Yang , Z. Yang , W-M. Yao ,Y.C. Yap , H. Ye , J. Ye , S. Ye , I. Yeletskikh , M.R. Yexley , E. Yigitbasi , P. Yin , K. Yorita ,K. Yoshihara , C.J.S. Young , C. Young , J. Yu , R. Yuan , X. Yue , M. Zaazoua ,B. Zabinski , G. Zacharis , E. Zaffaroni , J. Zahreddine , A.M. Zaitsev , T. Zakareishvili ,N. Zakharchuk , S. Zambito , D. Zanzi , S.V. Zeißner , C. Zeitnitz , G. Zemaityte , J.C. Zeng ,O. Zenin , T. Ženiš , D. Zerwas , M. Zgubič , B. Zhang , D.F. Zhang , G. Zhang , J. Zhang ,K. Zhang , L. Zhang , L. Zhang , M. Zhang , R. Zhang , S. Zhang , X. Zhang , X. Zhang ,Y. Zhang , Z. Zhang , Z. Zhang , P. Zhao , Y. Zhao , Z. Zhao , A. Zhemchugov ,Z. Zheng , D. Zhong , B. Zhou , C. Zhou , H. Zhou , M. Zhou , N. Zhou , Y. Zhou ,C.G. Zhu , C. Zhu , H.L. Zhu , H. Zhu , J. Zhu , Y. Zhu , X. Zhuang , K. Zhukov ,V. Zhulanov , D. Zieminska , N.I. Zimine , S. Zimmermann , Z. Zinonos , M. Ziolkowski ,L. Živković , G. Zobernig , A. Zoccoli , K. Zoch , T.G. Zorbas , R. Zou , L. Zwalinski .52 Department of Physics, University of Adelaide, Adelaide; Australia. Physics Department, SUNY Albany, Albany NY; United States of America. Department of Physics, University of Alberta, Edmonton AB; Canada. ( 𝑎 ) Department of Physics, Ankara University, Ankara; ( 𝑏 ) Istanbul Aydin University, Application andResearch Center for Advanced Studies, Istanbul; ( 𝑐 ) Division of Physics, TOBB University of Economicsand Technology, Ankara; Turkey. LAPP, Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS/IN2P3, Annecy; France. High Energy Physics Division, Argonne National Laboratory, Argonne IL; United States of America. Department of Physics, University of Arizona, Tucson AZ; United States of America. Department of Physics, University of Texas at Arlington, Arlington TX; United States of America. Physics Department, National and Kapodistrian University of Athens, Athens; Greece. Physics Department, National Technical University of Athens, Zografou; Greece. Department of Physics, University of Texas at Austin, Austin TX; United States of America. ( 𝑎 ) Bahcesehir University, Faculty of Engineering and Natural Sciences, Istanbul; ( 𝑏 ) Istanbul BilgiUniversity, Faculty of Engineering and Natural Sciences, Istanbul; ( 𝑐 ) Department of Physics, BogaziciUniversity, Istanbul; ( 𝑑 ) Department of Physics Engineering, Gaziantep University, Gaziantep; Turkey. Institute of Physics, Azerbaijan Academy of Sciences, Baku; Azerbaijan. Institut de Física d’Altes Energies (IFAE), Barcelona Institute of Science and Technology, Barcelona;Spain. ( 𝑎 ) Institute of High Energy Physics, Chinese Academy of Sciences, Beijing; ( 𝑏 ) Physics Department,Tsinghua University, Beijing; ( 𝑐 ) Department of Physics, Nanjing University, Nanjing; ( 𝑑 ) University ofChinese Academy of Science (UCAS), Beijing; China. Institute of Physics, University of Belgrade, Belgrade; Serbia. Department for Physics and Technology, University of Bergen, Bergen; Norway. Physics Division, Lawrence Berkeley National Laboratory and University of California, Berkeley CA;United States of America. Institut für Physik, Humboldt Universität zu Berlin, Berlin; Germany. Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics, University ofBern, Bern; Switzerland. School of Physics and Astronomy, University of Birmingham, Birmingham; United Kingdom. ( 𝑎 ) Facultad de Ciencias y Centro de Investigaciónes, Universidad Antonio Nariño,Bogotá; ( 𝑏 ) Departamento de Física, Universidad Nacional de Colombia, Bogotá, Colombia; Colombia. ( 𝑎 ) INFN Bologna and Universita’ di Bologna, Dipartimento di Fisica; ( 𝑏 ) INFN Sezione di Bologna; Italy. Physikalisches Institut, Universität Bonn, Bonn; Germany. Department of Physics, Boston University, Boston MA; United States of America. Department of Physics, Brandeis University, Waltham MA; United States of America. ( 𝑎 ) Transilvania University of Brasov, Brasov; ( 𝑏 ) Horia Hulubei National Institute of Physics and NuclearEngineering, Bucharest; ( 𝑐 ) Department of Physics, Alexandru Ioan Cuza University of Iasi,Iasi; ( 𝑑 ) National Institute for Research and Development of Isotopic and Molecular Technologies, PhysicsDepartment, Cluj-Napoca; ( 𝑒 ) University Politehnica Bucharest, Bucharest; ( 𝑓 ) West University in Timisoara,Timisoara; Romania. ( 𝑎 ) Faculty of Mathematics, Physics and Informatics, Comenius University, Bratislava; ( 𝑏 ) Department ofSubnuclear Physics, Institute of Experimental Physics of the Slovak Academy of Sciences, Kosice; SlovakRepublic. Physics Department, Brookhaven National Laboratory, Upton NY; United States of America. Departamento de Física, Universidad de Buenos Aires, Buenos Aires; Argentina. California State University, CA; United States of America.53 Cavendish Laboratory, University of Cambridge, Cambridge; United Kingdom. ( 𝑎 ) Department of Physics, University of Cape Town, Cape Town; ( 𝑏 ) iThemba Labs, WesternCape; ( 𝑐 ) Department of Mechanical Engineering Science, University of Johannesburg,Johannesburg; ( 𝑑 ) University of South Africa, Department of Physics, Pretoria; ( 𝑒 ) School of Physics,University of the Witwatersrand, Johannesburg; South Africa. Department of Physics, Carleton University, Ottawa ON; Canada. ( 𝑎 ) Faculté des Sciences Ain Chock, Réseau Universitaire de Physique des Hautes Energies - UniversitéHassan II, Casablanca; ( 𝑏 ) Faculté des Sciences, Université Ibn-Tofail, Kénitra; ( 𝑐 ) Faculté des SciencesSemlalia, Université Cadi Ayyad, LPHEA-Marrakech; ( 𝑑 ) Moroccan Foundation for Advanced ScienceInnovation and Research (MAScIR), Rabat; ( 𝑒 ) LPMR, Faculté des Sciences, Université Mohamed Premier,Oujda; ( 𝑓 ) Faculté des sciences, Université Mohammed V, Rabat; Morocco. CERN, Geneva; Switzerland. Enrico Fermi Institute, University of Chicago, Chicago IL; United States of America. LPC, Université Clermont Auvergne, CNRS/IN2P3, Clermont-Ferrand; France. Nevis Laboratory, Columbia University, Irvington NY; United States of America. Niels Bohr Institute, University of Copenhagen, Copenhagen; Denmark. ( 𝑎 ) Dipartimento di Fisica, Università della Calabria, Rende; ( 𝑏 ) INFN Gruppo Collegato di Cosenza,Laboratori Nazionali di Frascati; Italy. Physics Department, Southern Methodist University, Dallas TX; United States of America. Physics Department, University of Texas at Dallas, Richardson TX; United States of America. National Centre for Scientific Research "Demokritos", Agia Paraskevi; Greece. ( 𝑎 ) Department of Physics, Stockholm University; ( 𝑏 ) Oskar Klein Centre, Stockholm; Sweden. Deutsches Elektronen-Synchrotron DESY, Hamburg and Zeuthen; Germany. Lehrstuhl für Experimentelle Physik IV, Technische Universität Dortmund, Dortmund; Germany. Institut für Kern- und Teilchenphysik, Technische Universität Dresden, Dresden; Germany. Department of Physics, Duke University, Durham NC; United States of America. SUPA - School of Physics and Astronomy, University of Edinburgh, Edinburgh; United Kingdom. INFN e Laboratori Nazionali di Frascati, Frascati; Italy. Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg; Germany. II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen; Germany. Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève; Switzerland. ( 𝑎 ) Dipartimento di Fisica, Università di Genova, Genova; ( 𝑏 ) INFN Sezione di Genova; Italy. II. Physikalisches Institut, Justus-Liebig-Universität Giessen, Giessen; Germany. SUPA - School of Physics and Astronomy, University of Glasgow, Glasgow; United Kingdom. LPSC, Université Grenoble Alpes, CNRS/IN2P3, Grenoble INP, Grenoble; France. Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge MA; United States ofAmerica. ( 𝑎 ) Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics,University of Science and Technology of China, Hefei; ( 𝑏 ) Institute of Frontier and Interdisciplinary Scienceand Key Laboratory of Particle Physics and Particle Irradiation (MOE), Shandong University,Qingdao; ( 𝑐 ) School of Physics and Astronomy, Shanghai Jiao Tong University, Key Laboratory for ParticleAstrophysics and Cosmology (MOE), SKLPPC, Shanghai; ( 𝑑 ) Tsung-Dao Lee Institute, Shanghai; China. ( 𝑎 ) Kirchhoff-Institut für Physik, Ruprecht-Karls-Universität Heidelberg, Heidelberg; ( 𝑏 ) PhysikalischesInstitut, Ruprecht-Karls-Universität Heidelberg, Heidelberg; Germany. Faculty of Applied Information Science, Hiroshima Institute of Technology, Hiroshima; Japan. ( 𝑎 ) Department of Physics, Chinese University of Hong Kong, Shatin, N.T., Hong Kong; ( 𝑏 ) Departmentof Physics, University of Hong Kong, Hong Kong; ( 𝑐 ) Department of Physics and Institute for Advanced54tudy, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong; China. Department of Physics, National Tsing Hua University, Hsinchu; Taiwan. IJCLab, Université Paris-Saclay, CNRS/IN2P3, 91405, Orsay; France. Department of Physics, Indiana University, Bloomington IN; United States of America. ( 𝑎 ) INFN Gruppo Collegato di Udine, Sezione di Trieste, Udine; ( 𝑏 ) ICTP, Trieste; ( 𝑐 ) DipartimentoPolitecnico di Ingegneria e Architettura, Università di Udine, Udine; Italy. ( 𝑎 ) INFN Sezione di Lecce; ( 𝑏 ) Dipartimento di Matematica e Fisica, Università del Salento, Lecce; Italy. ( 𝑎 ) INFN Sezione di Milano; ( 𝑏 ) Dipartimento di Fisica, Università di Milano, Milano; Italy. ( 𝑎 ) INFN Sezione di Napoli; ( 𝑏 ) Dipartimento di Fisica, Università di Napoli, Napoli; Italy. ( 𝑎 ) INFN Sezione di Pavia; ( 𝑏 ) Dipartimento di Fisica, Università di Pavia, Pavia; Italy. ( 𝑎 ) INFN Sezione di Pisa; ( 𝑏 ) Dipartimento di Fisica E. Fermi, Università di Pisa, Pisa; Italy. ( 𝑎 ) INFN Sezione di Roma; ( 𝑏 ) Dipartimento di Fisica, Sapienza Università di Roma, Roma; Italy. ( 𝑎 ) INFN Sezione di Roma Tor Vergata; ( 𝑏 ) Dipartimento di Fisica, Università di Roma Tor Vergata,Roma; Italy. ( 𝑎 ) INFN Sezione di Roma Tre; ( 𝑏 ) Dipartimento di Matematica e Fisica, Università Roma Tre, Roma;Italy. ( 𝑎 ) INFN-TIFPA; ( 𝑏 ) Università degli Studi di Trento, Trento; Italy. Institut für Astro- und Teilchenphysik, Leopold-Franzens-Universität, Innsbruck; Austria. University of Iowa, Iowa City IA; United States of America. Department of Physics and Astronomy, Iowa State University, Ames IA; United States of America. Joint Institute for Nuclear Research, Dubna; Russia. ( 𝑎 ) Departamento de Engenharia Elétrica, Universidade Federal de Juiz de Fora (UFJF), Juiz deFora; ( 𝑏 ) Universidade Federal do Rio De Janeiro COPPE/EE/IF, Rio de Janeiro; ( 𝑐 ) Instituto de Física,Universidade de São Paulo, São Paulo; Brazil. KEK, High Energy Accelerator Research Organization, Tsukuba; Japan. Graduate School of Science, Kobe University, Kobe; Japan. ( 𝑎 ) AGH University of Science and Technology, Faculty of Physics and Applied Computer Science,Krakow; ( 𝑏 ) Marian Smoluchowski Institute of Physics, Jagiellonian University, Krakow; Poland. Institute of Nuclear Physics Polish Academy of Sciences, Krakow; Poland. Faculty of Science, Kyoto University, Kyoto; Japan. Kyoto University of Education, Kyoto; Japan. Research Center for Advanced Particle Physics and Department of Physics, Kyushu University, Fukuoka ;Japan. Instituto de Física La Plata, Universidad Nacional de La Plata and CONICET, La Plata; Argentina. Physics Department, Lancaster University, Lancaster; United Kingdom. Oliver Lodge Laboratory, University of Liverpool, Liverpool; United Kingdom. Department of Experimental Particle Physics, Jožef Stefan Institute and Department of Physics,University of Ljubljana, Ljubljana; Slovenia. School of Physics and Astronomy, Queen Mary University of London, London; United Kingdom. Department of Physics, Royal Holloway University of London, Egham; United Kingdom. Department of Physics and Astronomy, University College London, London; United Kingdom. Louisiana Tech University, Ruston LA; United States of America. Fysiska institutionen, Lunds universitet, Lund; Sweden. Centre de Calcul de l’Institut National de Physique Nucléaire et de Physique des Particules (IN2P3),Villeurbanne; France. Departamento de Física Teorica C-15 and CIAFF, Universidad Autónoma de Madrid, Madrid; Spain.
Institut für Physik, Universität Mainz, Mainz; Germany.55 School of Physics and Astronomy, University of Manchester, Manchester; United Kingdom.
CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille; France.
Department of Physics, University of Massachusetts, Amherst MA; United States of America.
Department of Physics, McGill University, Montreal QC; Canada.
School of Physics, University of Melbourne, Victoria; Australia.
Department of Physics, University of Michigan, Ann Arbor MI; United States of America.
Department of Physics and Astronomy, Michigan State University, East Lansing MI; United States ofAmerica.
B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk; Belarus.
Research Institute for Nuclear Problems of Byelorussian State University, Minsk; Belarus.
Group of Particle Physics, University of Montreal, Montreal QC; Canada.
P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow; Russia.
National Research Nuclear University MEPhI, Moscow; Russia.
D.V. Skobeltsyn Institute of Nuclear Physics, M.V. Lomonosov Moscow State University, Moscow;Russia.
Fakultät für Physik, Ludwig-Maximilians-Universität München, München; Germany.
Max-Planck-Institut für Physik (Werner-Heisenberg-Institut), München; Germany.
Nagasaki Institute of Applied Science, Nagasaki; Japan.
Graduate School of Science and Kobayashi-Maskawa Institute, Nagoya University, Nagoya; Japan.
Department of Physics and Astronomy, University of New Mexico, Albuquerque NM; United States ofAmerica.
Institute for Mathematics, Astrophysics and Particle Physics, Radboud University/Nikhef, Nijmegen;Netherlands.
Nikhef National Institute for Subatomic Physics and University of Amsterdam, Amsterdam;Netherlands.
Department of Physics, Northern Illinois University, DeKalb IL; United States of America. ( 𝑎 ) Budker Institute of Nuclear Physics and NSU, SB RAS, Novosibirsk; ( 𝑏 ) Novosibirsk State UniversityNovosibirsk; Russia.
Institute for High Energy Physics of the National Research Centre Kurchatov Institute, Protvino; Russia.
Institute for Theoretical and Experimental Physics named by A.I. Alikhanov of National ResearchCentre "Kurchatov Institute", Moscow; Russia.
Department of Physics, New York University, New York NY; United States of America.
Ochanomizu University, Otsuka, Bunkyo-ku, Tokyo; Japan.
Ohio State University, Columbus OH; United States of America.
Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman OK; UnitedStates of America.
Department of Physics, Oklahoma State University, Stillwater OK; United States of America.
Palacký University, RCPTM, Joint Laboratory of Optics, Olomouc; Czech Republic.
Institute for Fundamental Science, University of Oregon, Eugene, OR; United States of America.
Graduate School of Science, Osaka University, Osaka; Japan.
Department of Physics, University of Oslo, Oslo; Norway.
Department of Physics, Oxford University, Oxford; United Kingdom.
LPNHE, Sorbonne Université, Université de Paris, CNRS/IN2P3, Paris; France.
Department of Physics, University of Pennsylvania, Philadelphia PA; United States of America.
Konstantinov Nuclear Physics Institute of National Research Centre "Kurchatov Institute", PNPI, St.Petersburg; Russia.
Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh PA; United States of56merica. ( 𝑎 ) Laboratório de Instrumentação e Física Experimental de Partículas - LIP, Lisboa; ( 𝑏 ) Departamento deFísica, Faculdade de Ciências, Universidade de Lisboa, Lisboa; ( 𝑐 ) Departamento de Física, Universidadede Coimbra, Coimbra; ( 𝑑 ) Centro de Física Nuclear da Universidade de Lisboa, Lisboa; ( 𝑒 ) Departamento deFísica, Universidade do Minho, Braga; ( 𝑓 ) Departamento de Física Teórica y del Cosmos, Universidad deGranada, Granada (Spain); ( 𝑔 ) Dep Física and CEFITEC of Faculdade de Ciências e Tecnologia,Universidade Nova de Lisboa, Caparica; ( ℎ ) Instituto Superior Técnico, Universidade de Lisboa, Lisboa;Portugal.
Institute of Physics of the Czech Academy of Sciences, Prague; Czech Republic.
Czech Technical University in Prague, Prague; Czech Republic.
Charles University, Faculty of Mathematics and Physics, Prague; Czech Republic.
Particle Physics Department, Rutherford Appleton Laboratory, Didcot; United Kingdom.
IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette; France.
Santa Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz CA; UnitedStates of America. ( 𝑎 ) Departamento de Física, Pontificia Universidad Católica de Chile, Santiago; ( 𝑏 ) Universidad AndresBello, Department of Physics, Santiago; ( 𝑐 ) Instituto de Alta Investigación, Universidad deTarapacá; ( 𝑑 ) Departamento de Física, Universidad Técnica Federico Santa María, Valparaíso; Chile.
Universidade Federal de São João del Rei (UFSJ), São João del Rei; Brazil.
Department of Physics, University of Washington, Seattle WA; United States of America.
Department of Physics and Astronomy, University of Sheffield, Sheffield; United Kingdom.
Department of Physics, Shinshu University, Nagano; Japan.
Department Physik, Universität Siegen, Siegen; Germany.
Department of Physics, Simon Fraser University, Burnaby BC; Canada.
SLAC National Accelerator Laboratory, Stanford CA; United States of America.
Physics Department, Royal Institute of Technology, Stockholm; Sweden.
Departments of Physics and Astronomy, Stony Brook University, Stony Brook NY; United States ofAmerica.
Department of Physics and Astronomy, University of Sussex, Brighton; United Kingdom.
School of Physics, University of Sydney, Sydney; Australia.
Institute of Physics, Academia Sinica, Taipei; Taiwan. ( 𝑎 ) E. Andronikashvili Institute of Physics, Iv. Javakhishvili Tbilisi State University, Tbilisi; ( 𝑏 ) HighEnergy Physics Institute, Tbilisi State University, Tbilisi; Georgia.
Department of Physics, Technion, Israel Institute of Technology, Haifa; Israel.
Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv University, Tel Aviv; Israel.
Department of Physics, Aristotle University of Thessaloniki, Thessaloniki; Greece.
International Center for Elementary Particle Physics and Department of Physics, University of Tokyo,Tokyo; Japan.
Graduate School of Science and Technology, Tokyo Metropolitan University, Tokyo; Japan.
Department of Physics, Tokyo Institute of Technology, Tokyo; Japan.
Tomsk State University, Tomsk; Russia.
Department of Physics, University of Toronto, Toronto ON; Canada. ( 𝑎 ) TRIUMF, Vancouver BC; ( 𝑏 ) Department of Physics and Astronomy, York University, Toronto ON;Canada.
Division of Physics and Tomonaga Center for the History of the Universe, Faculty of Pure and AppliedSciences, University of Tsukuba, Tsukuba; Japan.
Department of Physics and Astronomy, Tufts University, Medford MA; United States of America.57 Department of Physics and Astronomy, University of California Irvine, Irvine CA; United States ofAmerica.
Department of Physics and Astronomy, University of Uppsala, Uppsala; Sweden.
Department of Physics, University of Illinois, Urbana IL; United States of America.
Instituto de Física Corpuscular (IFIC), Centro Mixto Universidad de Valencia - CSIC, Valencia; Spain.
Department of Physics, University of British Columbia, Vancouver BC; Canada.
Department of Physics and Astronomy, University of Victoria, Victoria BC; Canada.
Fakultät für Physik und Astronomie, Julius-Maximilians-Universität Würzburg, Würzburg; Germany.
Department of Physics, University of Warwick, Coventry; United Kingdom.
Waseda University, Tokyo; Japan.
Department of Particle Physics and Astrophysics, Weizmann Institute of Science, Rehovot; Israel.
Department of Physics, University of Wisconsin, Madison WI; United States of America.
Fakultät für Mathematik und Naturwissenschaften, Fachgruppe Physik, Bergische UniversitätWuppertal, Wuppertal; Germany.
Department of Physics, Yale University, New Haven CT; United States of America. 𝑎 Also at Borough of Manhattan Community College, City University of New York, New York NY; UnitedStates of America. 𝑏 Also at Centro Studi e Ricerche Enrico Fermi; Italy. 𝑐 Also at CERN, Geneva; Switzerland. 𝑑 Also at CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille; France. 𝑒 Also at Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève;Switzerland. 𝑓 Also at Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona; Spain. 𝑔 Also at Department of Financial and Management Engineering, University of the Aegean, Chios; Greece. ℎ Also at Department of Physics and Astronomy, Michigan State University, East Lansing MI; UnitedStates of America. 𝑖 Also at Department of Physics and Astronomy, University of Louisville, Louisville, KY; United States ofAmerica. 𝑗 Also at Department of Physics, Ben Gurion University of the Negev, Beer Sheva; Israel. 𝑘 Also at Department of Physics, California State University, East Bay; United States of America. 𝑙 Also at Department of Physics, California State University, Fresno; United States of America. 𝑚 Also at Department of Physics, California State University, Sacramento; United States of America. 𝑛 Also at Department of Physics, King’s College London, London; United Kingdom. 𝑜 Also at Department of Physics, St. Petersburg State Polytechnical University, St. Petersburg; Russia. 𝑝 Also at Department of Physics, University of Fribourg, Fribourg; Switzerland. 𝑞 Also at Dipartimento di Matematica, Informatica e Fisica, Università di Udine, Udine; Italy. 𝑟 Also at Faculty of Physics, M.V. Lomonosov Moscow State University, Moscow; Russia. 𝑠 Also at Giresun University, Faculty of Engineering, Giresun; Turkey. 𝑡 Also at Graduate School of Science, Osaka University, Osaka; Japan. 𝑢 Also at Hellenic Open University, Patras; Greece. 𝑣 Also at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona; Spain. 𝑤 Also at Institut für Experimentalphysik, Universität Hamburg, Hamburg; Germany. 𝑥 Also at Institute for Nuclear Research and Nuclear Energy (INRNE) of the Bulgarian Academy ofSciences, Sofia; Bulgaria. 𝑦 Also at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest;Hungary. 𝑧 Also at Institute of Particle Physics (IPP); Canada.58 𝑎 Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku; Azerbaijan. 𝑎𝑏 Also at Instituto de Fisica Teorica, IFT-UAM/CSIC, Madrid; Spain. 𝑎𝑐 Also at Istanbul University, Dept. of Physics, Istanbul; Turkey. 𝑎𝑑 Also at Joint Institute for Nuclear Research, Dubna; Russia. 𝑎𝑒 Also at Moscow Institute of Physics and Technology State University, Dolgoprudny; Russia. 𝑎 𝑓
Also at National Research Nuclear University MEPhI, Moscow; Russia. 𝑎𝑔 Also at Physics Department, An-Najah National University, Nablus; Palestine. 𝑎ℎ Also at Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg; Germany. 𝑎𝑖 Also at The City College of New York, New York NY; United States of America. 𝑎 𝑗
Also at TRIUMF, Vancouver BC; Canada. 𝑎𝑘 Also at Universita di Napoli Parthenope, Napoli; Italy. 𝑎𝑙 Also at University of Chinese Academy of Sciences (UCAS), Beijing; China. ∗∗