Search for pair production of third-generation scalar leptoquarks decaying into a top quark and a tau-lepton in pp collisions at root s=13 TeV with the ATLAS detector

JHEP06(2021)179 Published for SISSA by Springer Received:January 28, 2021 Revised:June 8, 2021 Accepted:June 8, 2021 Published:June 30, 2021 Search for pair production of third-generation scalar leptoquarks decaying into a top quark and a τ-lepton in pp collisions at √s= 13 TeV with the ATLAS detector The ATLAS collaboration E-mail: [email protected] Abstract: A search for pair production of third-generation scalar leptoquarks decaying into a top quark and a τ -lepton is presented. The search is based on a dataset of pp collisions at √s = 13 TeV recorded with the ATLAS detector during Run 2 of the Large Hadron Collider, corresponding to an integrated luminosity of 139fb −1 . Events are selected if they have one light lepton (electron or muon) and at least one hadronically decaying τ -lepton, or at least two light leptons. 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 lepton candidates, are considered in the analysis. Each of them is split into multiple event categories to simultaneously search for the signal and constrain several leading backgrounds. The signal-rich event categories require at least one hadronically decaying τ -lepton candidate and exploit the presence of energetic final-state objects, which is characteristic of signal events. No significant excess above the Standard Model expectation is observed in any of the considered event categories, and 95% CL upper limits are set on the production cross section as a function of 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. Keywords: Beyond Standard Model, Exotics, Hadron-Hadron scattering (experiments) ArXiv ePrint: 2101.11582 Open Access, Copyright CERN, for the benefit of the ATLAS Collaboration. Article funded by SCOAP3. https://doi.org/10.1007/JHEP06(2021)179 JHEP06(2021)179 Contents 1 Introduction 1 2 ATLAS detector 3 3 Data and simulated event samples 4 4 Event reconstruction 7 5 Search strategy 11 5.1 Event selection 12 5.2 Event categorisation 13 6 Background estimation 20 6.1 Irreducible backgrounds 20 6.1.1 t¯ tbackground 20 6.1.2 t¯ tW background 22 6.1.3 Other irreducible backgrounds 22 6.2 Reducible backgrounds 22 6.2.1 Fake τhad candidates 22 6.2.2 Non-prompt light leptons and charge misassignment 25 7 Analysis model and results 26 8 Conclusion 36 The ATLAS collaboration 45 1 Introduction The similarities between the quark and lepton sectors of the Standard Model (SM), which exhibit a similar 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 under all SM gauge groups. In particular, they are triplets with respect to the strong interaction, and have fractional electric charge. A LQ state can have either spin 0 (scalar LQ) or spin 1 (vector LQ), and only the former is considered in this paper. Because of their quantum numbers, LQs couple simultaneously to both quarks and leptons, enabling direct transitions between the two. Scalar LQs are assumed to couple to the quark-lepton pair via a Yukawa interaction, – 1 – JHEP06(2021)179 with coupling constants that can vary across fermion 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 been proposed as an explanation for measurements of B -meson decays that exhibit tantalising deviations from SM predictions [ 8 – 14 ]. The assumption that LQs can only interact with leptons and quarks of the same generation follows the minimal Buchmüller-Rückl-Wyler (BRW) model [ 15 ], which is adopted in this paper. The quark-lepton-LQ coupling is determined by two parameters: a model parameter β and the coupling parameter λ . Consequently, the coupling to the charged lepton is given by √βλ , while the coupling to the neutrino is given by √1−βλ. In pp collisions, LQs are mainly produced in pairs ( LQLQ ) via gluon-gluon fusion and quark-antiquark annihilation, mediated by the strong interaction. There are also leptonmediated t - and u -channel production processes that depend on the unknown strength of the Yukawa interaction. However, their contribution can usually be neglected for values of λ. 1, and particularly in the case of third-generation LQs ( LQ3 ), as they would require third-generation quarks in the initial state. The LQ pair-production cross section can therefore, to a very good approximation, be taken to depend only on the assumed value of the LQ mass ( mLQ ) for a given LQ spin and centre-of-mass energy. Furthermore, it is assumed that the value of λ is such that LQs have narrow decay widths of about 0.2% of mLQ , so that on-shell production dominates. Single LQ production in association with a lepton is also possible, but the cross section depends on the strength 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 to third-generation quarks and leptons were performed using 36.1 fb −1 of pp collisions at √s = 13 TeV at the Large Hadron Collider (LHC). The ATLAS results, many of which are reinterpretations of previously published searches for supersymmetric particles, are summarised in ref. [ 16 ]. The different ATLAS searches are not combined statistically and the results are presented as a function of the LQ mass and the branching ratio into charged leptons ( B ) for two different classes of LQ signals: up-type LQs ( LQu 3→bτ/tν ) and down-type LQs ( LQd 3→tτ/bν ), which have different electric charges. Both types of LQs are excluded for masses below 800 GeV independently of B . For the limiting cases of B = 1 and B = 0, masses below 1000 GeV and 1030 GeV (970 GeV and 920 GeV ) are excluded for LQu 3 ( LQd 3 ). Searches for LQs with off-diagonal couplings to third-generation quarks and firstor second-generation leptons have 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 LQd 3 in the tτtτ decay mode. This search uses the full Run 2 dataset of pp collisions at √s = 13 TeV recorded with the ATLAS detector and corresponding to an integrated luminosity of 139fb −1 . Events are selected if they have at least one light lepton (electron or muon, denoted by ` ) and at least one hadronically decaying τ -lepton, or at least two light leptons. 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 lepton candidates, are considered in the analysis. Each of them is split into multiple event categories. The most sensitive event – 2 – JHEP06(2021)179 categories require at least one hadronically decaying τ -lepton candidate and exploit the presence of energetic final-state objects, which is characteristic of signal events. In those event categories the final discriminating variable used is the scalar sum of the transverse momenta of all selected leptons, the selected jets and the missing transverse 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 photon misidentified as a light lepton or with a jet misidentified as a hadronically decaying τ -lepton, and from SM processes yielding multiple leptons in the final state, such as t¯ t production in association with a vector boson or a Higgs boson, and diboson production. The rest of the event categories are designed to be enriched in the most relevant backgrounds. A maximum-likelihood fit is performed across event categories to search for the signal and constrain several leading backgrounds simultaneously. Given the low background yields and good signal-to-background separation provided by the final discriminating variable used in the signal-rich event categories, the search sensitivity is determined by the limited number of data events rather than by the systematic uncertainties of the background estimation. This search is performed in the LQ mass range between 500 GeV and 1600 GeV as a function of B . By considering LQ masses down to 500 GeV , the coverage of this search partly overlaps with that of ref. [ 16 ], for which masses below 800 GeV were excluded independently of B . At the same time, this search significantly extends the reach to higher LQ masses. 2 ATLAS detector The ATLAS detector [ 24 ] at the LHC covers almost the entire solid angle around the collision point, 1 and consists of an inner tracking detector surrounded by a thin superconducting solenoid producing a 2 T axial magnetic field, electromagnetic and hadronic calorimeters, and a muon spectrometer (MS) incorporating three 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 precise reconstruction of tracks of charged particles in the pseudorapidity range |η|< 2 . 5. The inner detector also includes a transition radiation tracker that provides tracking and electron identification information for |η|< 2 . 0. The calorimeter system covers the pseudorapidity range |η|< 4 . 9. Within the region |η|< 3 . 2, electromagnetic (EM) calorimetry is provided by barrel and endcap high-granularity lead/liquid-argon (LAr) electromagnetic calorimeters, with an additional thin LAr presampler covering |η|< 1 . 8to correct for energy loss in material upstream of the calorimeters. Hadronic calorimetry is provided by a steel/scintillator-tile calorimeter, segmented into three barrel structures within |η|< 1 . 7, and two copper/LAr hadronic endcap calorimeters. The solid angle coverage is completed with forward copper/LAr and tungsten/LAr calorimeter modules optimised for electromagnetic and 1 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 of the 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/ 2). Angular distance is measured in units of ∆ R≡p(∆η)2+ (∆φ)2 . – 3 – JHEP06(2021)179 hadronic measurements, respectively. The muon spectrometer measures the trajectories of muons with |η|< 2 . 7using multiple layers of high-precision tracking chambers located in a toroidal field of approximately 0.5 T and 1 T in the central and endcap regions of ATLAS, respectively. The muon spectrometer is also instrumented with separate trigger chambers covering |η|< 2 . 4. A two-level trigger system [ 27 ], consisting of a hardware-based first-level trigger followed by a software-based high-level trigger (HLT), is used to reduce the event rate to a maximum of around 1 kHz for offline storage. 3 Data and simulated event samples A dataset of pp collisions at √s = 13 TeV collected by the ATLAS experiment during 2015– 2018 and corresponding to an integrated luminosity of 139 fb−1 is used. The uncertainty in the integrated luminosity is 1.7% [ 28 ], obtained using the LUCID-2 detector [ 29 ] for the primary luminosity measurements. The number of additional pp interactions per bunch crossing (pile-up) in this dataset ranges from about 8 to 70, with an average of 34. Only events recorded under stable beam conditions and for which all detector subsystems were known to be in a good operating condition are used. The trigger requirements are discussed in section 5. Monte Carlo (MC) simulation samples were produced for the different signal and background processes using the configurations shown in table 1, with the samples used to estimate the systematic uncertainties in parentheses. 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 events from 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 luminosity profile of the recorded data. The generated events were processed through a simulation [ 34 ] of the ATLAS detector geometry and response using Geant4 [ 35 ], and through the same reconstruction software as the dataset of pp 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 control samples. The simulated samples are normalised to their cross sections, and computed to the highest order available in perturbation theory. Samples used to model the LQd 3 signal were generated at next-to-leading order (NLO) in QCD with MadGraph5_aMC@NLO 2.6.0 [ 36 ], using the LQ model of ref. [ 37 ] that adds parton showers to previous fixed-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 the A14 tune [ 41 ]. MadSpin [ 42 ] was used for the decay of the scalar LQd 3 . The coupling parameter λ was set to 0.3, resulting in the LQd 3 width of about 0 . 2% of its mass [ 15 , 43 ]. The charge of LQd 3 is set to 1 / 3 e , implying that it decays into either a tτ or bν pair. Most signal samples were produced for a model parameter of β = 0 . 5, which corresponds to identical amplitudes for the LQd 3→tτ and LQd 3→bν processes and, therefore, similar branching ratios for the two decay modes. The signal samples had a mixture of final states so that desired branching ratios B were obtained – 4 – JHEP06(2021)179 by reweighting the samples based on generator information. These samples were produced for LQd 3 mass values between 500 GeV and 800 GeV , in steps of 100 GeV , and between 800 GeV and 1 . 6 TeV , in steps of 50 GeV . Additional samples for β = 1 were generated for the same LQd 3 mass values between 800 GeV and 1 . 5 TeV , to gain statistical precision in high-sensitivity signal regions. The leptoquark signal production cross sections were taken from calculations [ 44 – 47 ] of direct top-squark pair production, as both are massive, coloured, scalar particles with the same production modes. The calculations were at approximate next-to-next-to-leading order (NNLO) in QCD with resummation of next-to-next-to-leading logarithmic (NNLL) soft gluon terms, with uncertainties determined by variations of the factorisation and renormalisation scales, the strong coupling constant αS , and the PDFs. The cross sections do not include lepton t -channel contributions, which are neglected in ref. [ 37 ] and may lead to corrections at the percent level [ 48 ]. Uncertainties affecting the modelling of the signal acceptance were estimated from the envelope of independent pairs of renormalisation and factorisation scale variations by a factor of 0.5 and 2, by propagating the PDF+ αS uncertainties following the PDF4LHC15 prescription [ 49 ], and by considering two alternative samples generated with settings that increase or decrease the amount of QCD radiation [50]. Samples used to model the t¯ t and single-top-quark background were generated with the NLO generator Powheg-Box v2 [ 51 – 56 ] using the NNPDF3.0 NLO PDF set. In the t¯ t sample, the Powheg-Box model parameter hdamp , which controls matrix element (ME) to PS matching and effectively regulates the highpT radiation, was set to 1.5 times the top-quark mass. Overlaps between the t¯ t and tW final states were avoided by using the diagram removal scheme [ 57 ]. The parton shower, hadronisation, and underlying event were modelled by Pythia 8.210 with the NNPDF2.3 LO [ 58 ] PDF set in combination with the A14 tune. Uncertainties affecting the modelling of the acceptance and event kinematics of t¯ t events due to the choice of PS and hadronisation model, the NLO ME-to-PS matching, and the effects of initialand final-state QCD radiation [ 59 ] are estimated by comparing the nominal predictions with those obtained using the alternative simulated samples (see table 1). The t¯ t and single-top-quark simulated samples are normalised to the cross sections calculated at NNLO in QCD including the resummation of NNLL soft gluon terms [ 60 – 63 ]. Samples for t¯ tW and t¯ tH production were generated using the NLO generators Sherpa 2.2.1 and Powheg-Box v2 [ 64 ], respectively, with the NNPDF3.0 NLO PDF set. In the case of the t¯ tW sample, the ME was calculated for up to one additional parton at NLO and up to two partons at LO using Comix [ 65 ] and OpenLoops [ 66 ] and merged with the Sherpa parton shower [ 67 ] using the MePs@Nlo prescription [ 68 ]. The generated t¯ tH events were interfaced to Pythia 8.2 and the A14 tune, and with Higgs decay branching ratios calculated using Hdecay [ 69 , 70 ]. The cross section used to normalise the t¯ tW ( t¯ tH ) sample is 601 (507)fb, which is computed at NLO in QCD with NLO electroweak corrections [ 36 , 69 , 71 – 77 ]. Uncertainties in the t¯ tW ( t¯ tH ) cross section include ± 12% ( +5.8% −9.2% ), estimated by varying the QCD factorisation and renormalisation scales, and ± 4% ( ± 3 . 6%) from PDF+ αS variations, estimated using the PDF4LHC15 prescription. Uncertainties affecting the modelling of the acceptance and event kinematics due to the choice of parton shower and hadronisation model are estimated by comparing the nominal – 5 – JHEP06(2021)179 Process Generator ME order Parton shower PDF Tune LQd 3LQd 3MG5_aMC NLO Pythia 8 NNPDF3.0 NLO A14 t¯ tPowheg-Box NLO Pythia 8 NNPDF3.0 NLO/ A14 NNPDF2.3 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]) hdamp = 3mt) 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∗→`+`−)MG5_aMC NLO Pythia 8 NNPDF3.0 NLO/ A14 NNPDF2.3 LO (Sherpa 2.2.0) (LO multileg) (Sherpa) (NNPDF3.0 NLO) (Sherpa default) t¯ t→W+bW−¯ b`+`−MG5_aMC LO Pythia 8 NNPDF3.0 LO A14 t¯ tH Powheg-Box NLO Pythia 8 NNPDF3.0 NLO / A14 NNPDF2.3 LO (Powheg-Box) (NLO) (Herwig 7) (NNPDF3.0 NLO/ (H7-UE-MMHT) MMHT2014 LO [82]) 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 [83] tW(Z/γ∗)MG5_aMC NLO Pythia 8 NNPDF2.3 LO A14 t¯ tt,t¯ tt¯ tMG5_aMC LO Pythia 8 NNPDF2.3 LO A14 t¯ tW+W−MG5_aMC LO Pythia 8 NNPDF2.3 LO A14 V V ,qqV V ,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 Table 1. The configurations used for event generation of signal and background processes. The samples used to estimate 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 the underlyingevent tune of the parton shower generator. MG5_aMC refers to MadGraph5_aMC@NLO 2.2, 2.3, or 2.6; Pythia 6 refers to version 6.427 [ 78 ]; Pythia 8 refers to version 8.2; Herwig++ refers to version 2.7 [ 79 ]; Herwig 7 refers to version 7.0.4 [ 80 ]; MePs@Nlo refers to the method used in Sherpa to match the matrix element to the parton shower. All samples include leading-logarithm photon emission, either modelled by the parton shower generator or by Photos [ 81 ]. The mass of the top quark (mt) and SM Higgs boson were set to 172.5GeV and 125 GeV, respectively. predictions 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 considered from renormalisation and factorisation scale variations by a factor of 0.5 and 2, relative to the nominal scales. The samples for t¯ t ( Z/γ∗ )and diboson ( V V ) production follow refs. [ 50 , 84 ]. For t¯ t ( Z/γ∗ ), the inclusive t¯ tl+l− ME is computed, including off-shell Z and γ∗ contributions – 6 – JHEP06(2021)179 with m ( `+`− ) > 1 GeV . A dedicated t¯ t sample, including rare t→Wbγ∗ ( →`+`− )radiative decays and requiring m ( `+`− ) > 1 GeV , referred to as the t¯ t→W+bW−¯ b`+`− 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∗→`+`− ) with m ( `+`− ) < 1 GeV is modelled by QED multiphoton radiation in the inclusive t¯ t sample and is referred to as t¯ tγ∗ (low mass). Care was taken to avoid both double-counting of contributions and uncovered regions of phase space when combining the different simulated samples. The cross section for t¯ t ( Z/γ∗→`+`− )production is 167 fb, computed at NLO in QCD and electroweak couplings [ 36 , 77 ]. The uncertainties from QCD scale and PDF+ αS variations are ± 12% and ± 4% respectively. The LO cross section from the t¯ t→W+bW−¯ b`+`− sample is scaled by a factor of 1.54, based on comparisons between the NNLO+NLL and LO cross sections for t¯ t production [ 85 – 89 ], and assigned a 50% normalisation uncertainty, to cover possible residual effects in the predicted yield due to the simplified normalisation procedure used and/or the fact that the event kinematics were modelled using a LO simulation. Uncertainties affecting the modelling of the acceptance and event kinematics for the t¯ t ( Z/γ∗ )sample include the same QCD scale and tune variations as considered for the t¯ tH sample, PDF variations using the PDF4LHC15 prescription, and a comparison with an alternative LO multileg sample (see table 1). Diboson backgrounds are normalised using the cross sections computed by Sherpa 2.2.2. To cover possible mismodellings in the associated heavy-flavour production predicted by the parton shower, a 50% normalisation uncertainty is assigned and treated as correlated between the WZ + ≥ 1 c and WZ + ≥ 1 b subprocesses. The remaining rare background contributions listed in table 1are 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 are predicted using a LO simulation, and to cover possible mismodellings in the extreme kinematic regime probed by this search, a 50% normalisation uncertainty is assigned to all of them. 4 Event reconstruction Interaction vertices from the pp collisions are reconstructed from at least two tracks with transverse momentum ( pT ) larger than 500 MeV that are consistent with originating from the beam collision region in the x – y plane. If more than one primary vertex candidate is found, the candidate for which the associated tracks form the largest sum of squared pT [ 90 ] is selected as the hard-scatter primary vertex. Electron candidates are reconstructed from energy clusters in the electromagnetic calorimeter that are associated with inner-detector tracks [ 91 ]. They are required to satisfy pT> 10 GeV and |ηcluster|< 2 . 47, excluding the transition region between the endcap and barrel calorimeters (1 . 37 <|ηcluster|< 1 . 52). Loose and tight electron identification working points are used [ 92 ], based on a likelihood discriminant employing calorimeter, tracking and combined variables that provide separation between electrons and jets. The associated track of an electron candidate is required to have at least two hits in the pixel detector and seven hits total in the pixel and silicon-strip detectors combined. For the tight identification working point, one of these pixel hits must be in the innermost layer (or the – 7 – JHEP06(2021)179 next-to-innermost layer if the module traversed in the innermost layer is non-operational), and there must be no association with a vertex from a reconstructed photon conversion [ 93 ] in the detector material (termed a ‘material conversion’ in this paper). Muon candidates are reconstructed by matching tracks connecting track segments in different layers of the muon spectrometer to tracks found in the inner detector. The resulting muon candidates are re-fitted using the complete track information from both detector systems [ 94 ]. They are required to satisfy pT> 10 GeV and |η|< 2 . 5. Loose and medium muon identification working points are used [ 94 ]. Medium muon candidates with pT> 800 GeV are in addition required to have hits in at least three MS stations (referred to as the ‘highpT working point’), in order to maximise the momentum resolution for the muon track and thus suppress backgrounds with highpT muons arising from momentum mismeasurements. Electron (muon) candidates are matched to the primary vertex by requiring that the significance of their transverse impact parameter, d0 , satisfies |d0/σ ( d0 ) |< 5 (3), where σ ( d0 )is the measured uncertainty in d0 , and by requiring that their longitudinal impact parameter, z0 , satisfies |z0sin θ|< 0 . 5mm, where θ is the track’s polar angle. To further suppress leptons from heavy-flavour hadron decays, misidentified jets, or photon conversions (collectively referred to as ‘non-prompt leptons’), lepton candidates are also required to be isolated in the tracker and in the calorimeter. A track-based lepton isolation criterion is defined by calculating the quantity IR = Pptrk T , where the scalar sum includes all tracks (excluding the lepton candidate itself) within the cone defined by ∆ R < Rcut around the direction of the lepton. The value of Rcut is the smaller of rmin and 10 GeV/p` T , where rmin is set to 0.2 (0.3) for electron (muon) candidates and where p` T is the lepton pT . All lepton candidates must satisfy IR/p` T< 0 . 15. Additionally, electrons (muons) are required to satisfy a calorimeter-based isolation criterion: the sum of the transverse energy within a cone of size ∆ R = 0 . 2around the lepton, after subtracting the contributions from pile-up and the energy deposit of the lepton itself, is required to be less than 20% (30%) of p` T . Muons are required to be separated by ∆ R > 0 . 2from any selected jets (defined below). If two electrons are closer than ∆ R = 0 . 1, only the one with the higher pT is considered. An electron lying within ∆R= 0.1of a selected muon is rejected. Light leptons of different qualities are used in the analysis, as summarised in table 2. ‘Loose’ light leptons simply satisfy the corresponding identification criteria, as well as the isolation and impact parameter requirements discussed above. They are used in the event preselection, and to define non-overlapping analysis channels (see section 5.1). ‘Tight’ and/or ‘Very Tight’ light leptons are then required, depending on the analysis channel, to improve the rejection of particular reducible backgrounds (see section 5.2). They are discussed further in the following. Uncertainties in light-lepton reconstruction, identification, isolation, and trigger efficiencies are taken into account, but have a negligible impact in the analysis. Despite the fact that leptons in decays of hadrons that contain bottomand charmquarks are highly suppressed by the selection criteria described above, several analysis channels considered in this search (see section 5) require additional suppression of backgrounds containing non-prompt leptons, and other processes where the electron charge is incorrectly assigned. Non-prompt leptons are further rejected using a boosted decision – 8 – JHEP06(2021)179 2`OS+1τ2`OS+≥2τ CRZCRt¯ tVR SR VR SR e/µ selection T T e/µ combinations ee/µµ eµ ee/µµ ee/µµ/eµ ee/µµ/eµ Zveto Inverted Yes Yes Yes Yes m`` [GeV] >12 >12 Nτhad 1≥2 τhad ID Loose/Medium Medium Loose pτ T,1[GeV] ≥25 ≥25 25–150 ≥150 ≥25 ≥75 mmin `τ [GeV] — — <100 ≥100 —≥50 mττ [GeV] — <100 ≥100 meff [GeV] — <1000 — — — — Table 4. Summary of event categories in the 2 ` OS+ ≥ 1 τ channel. All events are required to satisfy the preselection requirements. “T” denotes the Tight light-lepton selection criteria (see table 2). 200 400 600 800 1000 [GeV] τ T p 5− 10 4− 10 3− 10 2− 10 1− 10 1 10 Fraction of events / 25 GeV = 13 TeVs 1ℓ+1τ ATLAS Simulation Total Background LQ (0.9 TeV) LQ (1.1 TeV) LQ (1.3 TeV) (a) 200 400 600 800 1000 mℓτ[GeV] 0 0.1 0.2 0.3 0.4 0.5 Fraction of events / 100 GeV = 13 TeVs 1ℓ+1τ ATLAS Simulation Total Background LQ (0.9 TeV) LQ (1.1 TeV) LQ (1.3 TeV) (b) Figure 1. Comparison of the distribution of (a) the pT of the τhad candidate ( pτ T ), and (b) the invariant mass of the light lepton and the τhad candidate ( m`τ ), between the total background (shaded histogram) and the LQ signal for different mass values. The selection used corresponds to events in the 1 ` +1 τ event category (a) after the preselection requirements, and (b) after applying the additional requirement of pτ T> 150 GeV . The last bin in each distribution contains the overflow. figure 2b). In addition, two dedicated CRs are defined for events with one Loose or Medium τhad candidate in order to estimate correction factors to apply to the jet misidentification (also referred to as ‘fake’) rate in the simulation for both sets of τhad identification criteria. These CRs are enriched in Z +jets and dileptonic t¯ t events, respectively, and do not take part of the final likelihood fit. Further details of the fakeτhad background estimation can be found in section 6.2.1. In the 2 ` SS/3 ` + ≥ 1 τ channel, events are required to have either two light leptons with the same charge (2 ` SS) or three light leptons (3 ` ) with their charges adding up to ± 1. In – 15 – JHEP06(2021)179 0 500 1000 1500 2000 mττ [GeV] 0 0.1 0.2 0.3 0.4 0.5 Fraction of events / 100 GeV = 13 TeVs 1ℓ+≥2τ ATLAS Simulation Total Background LQ (0.9 TeV) LQ (1.1 TeV) LQ (1.3 TeV) (a) 0 200 400 600 800 1000 mmin ℓτ[GeV] 0 0.1 0.2 0.3 0.4 0.5 Fraction of events / 100 GeV = 13 TeVs 2ℓOS+1τ ATLAS Simulation Total Background LQ (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 τhad candidates ( mττ ), and (b) the minimum invariant mass of a light lepton and a τhad candidate ( mmin `τ ), between the total background (shaded histogram) and the LQ signal for different mass values. The selection used in (a) corresponds to events in the 1 ` + ≥ 2 τ category after the requirements of pτ T,1> 100 GeV and pτ T,2> 50 GeV , whereas the selection used in (b) corresponds to events in the 2 ` OS+1 τ category after the requirement of pτ T>150 GeV. The last bin in each distribution contains the overflow. addition, at least one Loose τhad 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 event are required to satisfy the Very Tight selection criteria. In the case of 3 ` events, the light lepton that has opposite charge to the SS lepton pair is required to satisfy the Tight selection criteria. In addition, it is required that any e±e± , e+e− or µ+µ− pair in the event satisfies m`` > 12 GeV and |m`` −mZ|> 10 GeV . Similarly, 3 ` events are required to satisfy |m3`−mZ|> 10 GeV to eliminate potential backgrounds with Z→ 2 `γ∗→ 4 ` where one lepton has very low momentum and is not reconstructed. Selected events fall into one of three event categories, two SRs and one VR, simply defined using pτ T,1 (see table 5). Events with pτ T,1> 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 ≤pτ T,1< 225 GeV fall into SR-L (with the symbol “L” standing for “Low”) and extend the sensitivity to lower LQ masses. The VR contains the events with 25 ≤pτ T,1<125 GeV. Finally, the 2 ` OS+0 τ ,2 ` SS+0 τ , and 3 ` +0 τ channels require there be no τhad candidates and are primarily used to improve the background modelling, as discussed in section 6. Events in the 2 ` OS+0 τ channel are selected by requiring an OS eµ pair with both light leptons satisfying the Tight selection criteria and no additional Loose light leptons, at least two jets, at least one b -tagged jet, and no Loose τhad candidates. This selection provides a t¯ t -rich control sample (denoted t¯ t 0 τ CR) that does not take part of the final likelihood fit, but that is used to derive corrections to improve the t¯ t background modelling (see section 6.1.1). Events in the 2 ` SS+0 τ channel are selected by requiring two SS light – 16 – JHEP06(2021)179 2`SS/3`+≥1τ VR SR-L SR-H e/µ selection T* (2`SS) T*/T (3`) Zveto Yes m`` [GeV] >12 Nτhad ≥1 τhad ID Loose pτ T,1[GeV] 25–125 125–225 ≥225 Table 5. Summary of event categories in the 2 ` SS/3 ` + ≥ 1 τ channel. All events are required to satisfy the preselection requirements. “T” and “T*” denote the Tight and Very Tight light-lepton selection criteria (see table 2). leptons satisfying the Very Tight selection criteria, except for some event categories where the internal conversion (IntC) or material conversion (MatC or Mat Conv) vetoes are inverted. A total of eight event categories, all of which are CRs, are defined so as to be enriched in different backgrounds: t¯ t with non-prompt electrons or muons, t¯ tW , internal conversions, and material conversions, (denoted by 2 ` tt(e) or 2 ` tt( µ ), 2 ` ttW, 2 ` IntC, and 2 ` MatC, respectively), which are summarised in table 6. The last two CRs select events with two SS light leptons containing at least one electron that satisfies the corresponding inverted conversion veto requirement. The 2 ` tt(e) and 2 ` tt( µ ) CRs select events with a SS ee / µe pair and a SS µµ / eµ pair, respectively, where the first (second) lepton denotes the leading (subleading) lepton in pT . The definition of these CRs exploits the fact that in SS dilepton events from t¯ t production the subleading lepton in pT is typically a non-prompt lepton. In addition, the events are restricted to have two or three jets in order to suppress the contribution from t¯ tW production. In the case of the 2 ` ttW CR, no restriction is imposed on the light-lepton flavours, and the events are required to have at least four jets. The 2 ` tt(e), 2 ` tt( µ ), and 2 ` ttW CRs are further split according to the charge of the light leptons (++ or −− ) in order to improve the discrimination between charge asymmetric and charge symmetric backgrounds (dominated by t¯ tW and t¯ t , respectively). Events in the 3 ` +0 τ channel are selected by requiring three light leptons satisfying the Tight or Very Tight selection criteria, with their charges adding up to ± 1. A total of four CRs are defined, which are summarised in table 7. Two CRs select events compatible with having a Z -boson candidate, but differing in their jet multiplicity requirements, in order to provide samples enriched in diboson (denoted by 3 ` VV) and t¯ tZ backgrounds (denoted by 3 ` ttZ), respectively. Similarly to the 2 ` SS+0 τ channel, two additional CRs are defined so as to be enriched in internaland material-conversion backgrounds, respectively, by inverting the corresponding conversion veto requirement on one of the electrons belonging to the SS lepton pair. The meff distribution is used as the final discriminating variable in all SRs. It peaks at approximately 2 mLQ for signal events, and at lower values for the backgrounds, as illustrated in figure 3. The overall rate and composition of the background varies across the – 17 – JHEP06(2021)179 2`SS+0τ 2`tt(e)±2`tt(µ)±2`ttW±2`IntC 2`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 Yes Electron material conversion veto Yes Yes Yes Yes Inverted Njets 2–3 2–3 ≥4≥2≥2 Zveto Yes mee [GeV] ≥12 Table 6. Summary of event categories in the 2 ` SS+0 τ channel. All events are required to satisfy the preselection requirements. “T*” denotes the Very Tight light-lepton selection criteria (see table 2). Events that belong to the tt(e), tt( µ ), and ttW categories are further split into two CRs for ++ and −− charge events. IntC and MatC stand for internal and material conversions, respectively. The first (second) light lepton quoted in a pair denotes the leading (subleading) lepton in pT . Backgrounds with resonant e+e−pairs from quarkonia or Z-boson decays due to electron charge misassignment are suppressed by requirements on the dielectron invariant mass (mee). 3`+0τ 3`VV 3`ttZ 3`IntC 3`MatC e/µ selection T T T(`0), T*(`1and `2) T(`0), T*(`1and `2) Electron internal conversion veto Yes Yes Inverted(`1or `2) Yes(`1and `2) Electron material conversion veto Yes Yes Yes(`1and `2) Inverted(`1or `2) Njets 2–3 ≥4≥2≥2 Zveto Inverted Inverted Yes Yes m`` [GeV] ≥12 Table 7. Summary of four CR categories in the 3 ` +0 τ channel. All events are required to satisfy the preselection requirements. “T” and “T*” denote the Tight and Very Tight light-lepton selection criteria (see table 2). IntC and MatC stand for internal and material conversions, respectively. Same-charge (opposite-charge) lepton pairs are also referred to as same-sign (opposite-sign) with abbreviation SS (OS). The OS lepton (relative to the SS pair) is denoted `0 , but is not necessarily the one with highest pT ; the remaining SS leptons are denoted `1 (closest in ∆ R to `0 ) and `2 (the remaining one). different SRs, as illustrated in figure 4. The dominant background in the 1 ` +1 τ OS SR is t¯ t production with both the light lepton and τhad candidate originating from the W boson decays. In contrast, the main background in the 1 ` +1 τ SS SR is also t¯ t production, but with one jet misidentified as a τhad candidate (fake τhad ), one non-prompt light lepton, or an electron with misassigned charge, followed by t¯ tW and V V production. In the 1 ` + ≥ 2 τ , 2 ` OS+1 τ , and 2 ` OS+ ≥ 2 τ SRs, about half of the background is also t¯ t with one fake τhad candidate, while the remaining contributions arise from t¯ tW , t¯ tZ/γ∗ , and t¯ tH production, with varying fractions across the SRs. Finally, the 2 ` SS/3 ` + ≥ 1 τ SRs are dominated by backgrounds with real leptons, with comparable contributions from t¯ tW , t¯ tZ/γ∗ , t¯ tH , and V V production. Despite their limited purity, the CRs defined above are useful for checking – 18 – JHEP06(2021)179 1000 2000 3000 4000 [GeV] eff m 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Fraction of events / 300 GeV = 13 TeVs 1ℓ+≥2τ ATLAS Simulation Total Background LQ (0.9 TeV) LQ (1.1 TeV) LQ (1.3 TeV) (a) 1000 2000 3000 4000 [GeV] eff m 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Fraction of events / 400 GeV = 13 TeVs 2ℓSS/3ℓ+≥1τ ATLAS Simulation Total Background LQ (0.9 TeV) LQ (1.1 TeV) LQ (1.3 TeV) (b) Figure 3. Comparison of the meff distribution in (a) the 1 ` + ≥ 2 τ SR, and (b) the 2 ` SS/3 ` + ≥ 1 τ SR-H, between the total background (shaded histogram) and the LQ signal for different mass values. The last bin in each distribution contains the overflow. ATLAS = 13 TeVs Signal regions Wt t Htt *) (high)γ(Z/tt * (low)γtt tt Single top QMisID Other Non-prompt e µNon-prompt Mat Conv had τFake Diboson 1ℓ+1τOS 1ℓ+1τSS 1ℓ+≥2τ 2ℓOS+1τ 2ℓOS+≥2τ 2ℓSS/3ℓ+≥1τ−L 2ℓSS/3ℓ+≥1τ−H Figure 4. The fractional contributions of the various backgrounds to the total predicted background in each of the seven 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 (see section 7). and correcting the background prediction (see section 6) and constraining the related systematic uncertainties through the likelihood fit to data that also includes the SRs. The VRs are meant to provide an independent validation of the background prediction, and thus are not included in the fit. – 19 – JHEP06(2021)179 6 Background estimation 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-lepton decays, or internal conversions. Reducible backgrounds (section 6.2) have prompt leptons with misassigned charge, at least one non-prompt light lepton, or fake τhad candidates. All backgrounds are estimated using the simulated samples described in section 3, which also discusses the systematic uncertainties in the modelling of these processes, so this is not repeated below. In some cases, the simulation is improved using additional corrections derived in data control samples. In particular, the event kinematics of the simulated t¯ t background, or the τhad fake rate predicted by the simulation, require dedicated corrections to better describe the data. In addition, the yields of some simulated backgrounds, in particular t¯ tW and non-prompt-lepton backgrounds, are adjusted via normalisation factors that are determined by performing a likelihood fit to data across all event categories as discussed in section 7. 6.1 Irreducible backgrounds Background contributions with prompt leptons originate from a wide range of physics processes with their relative importance varying by channel. In the 1 ` +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 irreducible backgrounds originate from t¯ tW and t¯ t ( Z/γ∗ ) production, followed by V V (in particular WZ ) production. Smaller contributions originate from the following rare processes: tZ,WtZ,t¯ tWW,VVV,t¯ tt, and t¯ tt¯ tproduction. 6.1.1 t ¯ tbackground Detailed measurements of differential cross sections have shown that the t¯ t simulation does not model the top-quark pT spectrum with sufficient accuracy, overestimating it in the highpT tail [ 113 , 114 ]. In addition, the simulation underestimates the production of t¯ t events with high jet multiplicity [ 114 ]. This leads to discrepancies between data and simulation in the distributions of several kinematic quantities of interest in this search, in particular the meff variable. In order to improve the description, dedicated corrections as a function of jet multiplicity and meff (referred to as ‘kinematic reweighting’) are derived in the t¯ t 0 τ CR. The corrections are derived by comparing the data, after subtracting small background contributions estimated from the simulation, with the predicted sum of t¯ t and tW processes. 5 The correction factors as a function of jet multiplicity vary from 1.05 for exactly two jets, to 1.1 for at least six jets. After correcting the jet multiplicity spectrum, a further correction as a function of meff is derived for each jet multiplicity, and parameterised as a first-degree polynomial. For example, for exactly four jets, the resulting correction factor varies from ∼ 1.1 for meff = 200 GeV to ∼ 0.4 for meff = 3 TeV , as shown in figure 5a. This kinematic reweighting is applied to all (nominal and alternative) t¯ t and tW simulated events, and prior to the derivation of any further corrections to improve the modelling of fake τhad candidates or non-prompt leptons (see sections 6.2.1 and 6.2.2). The comparison 5The sum of t¯ tand tW backgrounds is considered since they interfere at NLO. – 20 – JHEP06(2021)179 2− 10 1− 10 1 10 2 10 3 10 4 10 5 10 6 10 7 10 8 10 Events / 100 GeV Data tt Single top Wtt *)γ(Z/tt Htt W/Z+jets Diboson Other Uncertainty (1.1 TeV) d 3 LQ (1.3 TeV) d 3 LQ ATLAS -1 = 13 TeV, 139 fbs j+4OSµ eCR Pre-Fit 500 1000 1500 2000 2500 3000 [GeV] eff m 0.5 1 1.5 tt t Data - non-t (a) 500 1000 1500 2000 2500 3000 [GeV] eff m 0 0.5 1 1.5 Data / Bkg 2− 10 1− 10 1 10 2 10 3 10 4 10 5 10 Events / 100 GeV ATLAS -1 = 13 TeV, 139 fbs VR 1ℓ+1τOS Pre-Fit Data had τFake tt Single top Wtt *) (high)γ(Z/tt Htt Diboson Non-prompt e µNon-prompt QMisID Other Uncertainty Pre-Kinem. Rew. (b) Figure 5. (a) Comparison between data and the background prediction for the meff distribution in events selected by requiring an opposite-charge (OS) eµ pair, exactly four jets, and at least one b -tagged jet. The background contributions shown are before the likelihood fit to data (“PreFit”). 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 associated green lines represent the estimated uncertainty in the reweighting function. (b) Comparison of the meff distribution between data and the pre-fit background prediction after the kinematic reweighting in the 1 ` +1 τ OS VR. The total background 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 the combined 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 lower panel. The last bin in each figure contains the overflow. between the data and the background prediction after the kinematic reweighting, and before the likelihood fit (denoted “pre-fit”), is illustrated in figure 5b for the meff distribution in the 1 ` +1 τ OS VR, which is dominated by t¯ t background with a real τhad candidate. Good agreement is observed within the estimated pre-fit uncertainties. The agreement in normalisation is further improved after the likelihood fit (denoted “post-fit”), as shown in figure 11. The modelling of several other kinematic quantifies such as the lepton pT , Emiss T , and the scalar sum of jet pT , is also improved by the kinematic reweighting. Although this kinematic reweighting is derived using t¯ t dileptonic events, it is also applied to t¯ t semileptonic events selected in the 1 ` +1 τ channel. A systematic uncertainty from the slight difference between the slope of the nominal meff correction factor and that derived in the 1`+1τOS CR is also considered, with negligible impact on the final result. – 21 – JHEP06(2021)179 6.1.2 t ¯ tW background The t¯ tW background represents a non-negligible background in several event categories. Despite the use of state-of-the-art simulations, accurate modelling of additional QCD radiation in t¯ tW production remains challenging. Event categories sensitive to the t¯ tW background were defined in the analysis in order to study and constrain this background. These event categories are split by the sign of the sum of lepton charges (referred to as ‘total charge’) to better discriminate the t¯ tW process, which has a large charge asymmetry, from other SM backgrounds that are charge symmetric. To illustrate this point, the distribution of the scalar sum of the lepton pT (denoted by HT, lep ) in the 2 ` SS+0 τ channel, obtained by subtracting the distributions for events with positive total charge and with negative total charge, is shown in figure 6a. In this subtraction, only the charge asymmetric processes remain visible, allowing a better assessment of the modelling of the t¯ tW process by the simulation. Disagreement between the data and the prefit prediction from 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 factor is ˆ λt¯ tW = 1 . 78 ± 0 . 15, which is compatible with that determined in the SM t¯ tt¯ t analysis [ 115 ], and with a previous measurement of the t¯ tW production cross section [ 116 ]. Agreement is improved after the application of the background corrections resulting from the likelihood fit, in particular the above t¯ tW normalisation factor, as shown in figure 6b for the meff distribution. 6.1.3 Other irreducible backgrounds The total yields in the 3 ` VV and 3 ` ttZ CRs are used in the likelihood fit to improve the prediction of the background contribution from the V V and t¯ t ( Z/γ∗ )processes, respectively. A comparison of the meff distribution between the data and the total prediction in these two CRs exhibits adequate modelling by the simulation even before the likelihood fit to data, as shown in figure 7. The rate of the background from internal conversions with m ( e+e− ) < 1 GeV is estimated using the two dedicated CRs (2 ` IntC and 3 ` IntC). The total yield in each category is used in the likelihood fit to determine the following normalisation factor: ˆ λIntC e = 1 . 77 ± 0 . 32, where the uncertainty is dominated by the statistical uncertainty. The normalisation of the internal-conversion background is validated by comparing data and scaled 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 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 a systematic uncertainty associated with the extrapolation of the estimate from the 2`IntC and 3`IntC CRs to the other event categories. 6.2 Reducible backgrounds 6.2.1 Fake τhad candidates In most event categories requiring at least one τhad , the dominant background originates from t¯ t production with at least one fake τhad candidate. Consequently, the estimation – 22 – JHEP06(2021)179 50 100 150 200 250 300 350 400 450 500 [GeV] T,lep H 0 0.5 1 1.5 Data / Bkg 1− 10 1 10 2 10 3 10 4 10 / 50 GeV - -N + N ATLAS -1 = 13 TeV, 139 fbs 2ℓSS+0τ Post-Fit Data Wtt Diboson Non-prompt e µNon-prompt QMisID Mat Conv Other Uncertainty Pre-Fit (a) 0 500 1000 1500 2000 2500 3000 3500 4000 [GeV] eff m 0 0.5 1 1.5 Data / Bkg 1− 10 1 10 2 10 3 10 4 10 Events / 500 GeV ATLAS -1 = 13 TeV, 139 fbs CR 2ℓttW Post-Fit Data Wtt *) (high)γ(Z/tt * (low)γtt Htt Diboson Non-prompt e µNon-prompt QMisID Mat Conv Other Uncertainty Pre-Fit (b) Figure 6. (a) Comparison between data and the background prediction for the distribution of the scalar sum of the lepton pT ( HT, lep ) in the 2 ` SS+0 τ channel, obtained by subtracting the corresponding distributions for events with positive and negative total charge. In (b) the comparison is performed for the meff distribution in the 2 ` ttW CR without 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 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 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 the background prediction is indicated by the blue hatched band. The last bin in each figure contains the overflow. of fakeτhad background relies heavily on the simulation accurately modelling the t¯ t event kinematics and the τhad misidentification rate from jets. As discussed in section 6.1.1, a kinematic reweighting is applied to t¯ t simulated events in order to improve the description of the event kinematics. In order to evaluate such a correction factor, which depends on the jet multiplicity of the events, fake τhad candidates in t¯ t simulated events are considered as additional jets. After the kinematic reweighting is applied, a suitable correction to the fakeτhad rate in 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 τhad candidate, and meff < 1 TeV (denoted by CR t¯ t in table 4). The upper bound on meff ensures that any potential LQd 3 signal contamination would be negligible. This CR is enriched in dileptonic t¯ t events, such that the selected τhad candidates primarily originate from jets, and are used to determine a normalisation factor to correct for possible mismodelling of the fakeτhad rate in the simulation per τhad candidate. According to the simulation, the flavour composition of the jets giving a fake τhad candidate in this CR is similar to that in the SRs considered. This normalisation factor is measured as a function of pτhad T , and for one-prong and three-prong τhad candidates separately. In the case of one-prong – 23 – JHEP06(2021)179 0 500 1000 1500 2000 2500 3000 3500 4000 [GeV] eff m 0.5 0.75 1 1.25 Data / Bkg 1− 10 1 10 2 10 3 10 4 10 Events / 500 GeV ATLAS -1 = 13 TeV, 139 fbs CR 3ℓVV Post-Fit Data *) (high)γ(Z/tt Diboson Non-prompt e µNon-prompt QMisID Mat Conv Other Uncertainty Pre-Fit (a) 0 500 1000 1500 2000 2500 3000 3500 4000 [GeV] eff m 0.5 0.75 1 1.25 Data / Bkg 1− 10 1 10 2 10 3 10 4 10 Events / 500 GeV ATLAS -1 = 13 TeV, 139 fbs CR 3ℓttZ Post-Fit Data *) (high)γ(Z/tt Diboson Non-prompt e µNon-prompt QMisID Mat Conv Other Uncertainty Pre-Fit (b) Figure 7. Comparison between data and the background prediction for the meff distribution in (a) the 3 ` VV CR and (b) the 3 ` ttZ 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 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 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 the background prediction is indicated by the blue hatched band. The last bin in each figure contains the overflow. (three-prong) τhad candidates satisfying the Loose requirement, the normalisation factors range from 1 . 07 ± 0 . 06 (1 . 10 ± 0 . 31) for pτhad T in the range of 25–45 GeV (25–50 GeV ), to 0 . 57 ± 0 . 19 (0 . 80 ± 0 . 30) for pτhad T≥ 100 GeV (75 GeV ). The quoted uncertainty includes the statistical uncertainty in the CR, the uncertainty in the contribution from real τhad candidates that is subtracted in the CR, and the difference 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 τhad candidates than CR t¯ t . No statistically significant differences are found between the normalisation factors for Loose and Medium τhad candidates; therefore, the above normalisation factors are applied to all channels requiring at least one τhad candidate. All simulated background events with at least one fake τhad candidate 6 are scaled by the product of the corresponding per-candidate normalisation factors calculated according to the multiplicity of fake τhad and non-prompt light leptons (see section 6.2.2) before the likelihood fit to data. After applying the kinematic reweighting and the pT-dependent fake-τhad normalisation factors discussed above, the simulation is found to provide good modelling of relevant kinematic distributions for the fakeτhad background before the likelihood fit to data, as shown in figures 8a and 8b. The uncertainties associated with the normalisation factors are accounted for as nuisance parameters in the likelihood fit (see section 7). To account for the approximation of treating 6This includes t¯ tas well as other subleading processes such as single top, V+jets, etc. – 24 – JHEP06(2021)179 1ℓ+1τOS 1ℓ+1τSS 1ℓ+≥2τ 2ℓttW+ 2ℓttW− 2ℓtt(e)+ 2ℓtt(e)− 2ℓtt(μ)+ 2ℓtt(μ)− 2ℓIntC 2ℓMatC 3ℓVV 3ℓttZ3ℓIntC 3ℓMatC 0 0.5 1 1.5 Data / Bkg 1− 10 1 10 2 10 3 10 4 10 5 10 6 10 Events ATLAS -1 = 13 TeV, 139 fbs Control regions Post-Fit Data had τFake tt Single top Wtt *) (high)γ(Z/tt * (low)γtt Htt Diboson Non-prompt e µNon-prompt QMisID Mat Conv Other Uncertainty Pre-Fit (a) 1ℓ+1τOS 1ℓ+1τSS 1ℓ+≥2τ 2ℓOS+1τ 2ℓ OS+≥2τ 2ℓ SS/3ℓ +≥1τ−L 2ℓ SS/3ℓ +≥1τ−H 0 0.5 1 1.5 Data / Bkg 1− 10 1 10 2 10 3 10 4 10 Events ATLAS -1 = 13 TeV, 139 fbs Signal regions Post-Fit Data had τFake tt Single top Wtt *) (high)γ(Z/tt * (low)γtt Htt Diboson Non-prompt e µNon-prompt QMisID Mat Conv Other Uncertainty Pre-Fit (b) Figure 10. Comparison between data and the background prediction for the event yields in (a) the 15 control region categories 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 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 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 the background prediction is indicated by the blue hatched band. The blue triangles indicate points that are outside the vertical range of the figure. assume that the only possible decay 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`+≥2τSR, which dominates the sensitivity of this search. – 31 – JHEP06(2021)179 1ℓ+1τOS 1ℓ+1τSS 1ℓ+≥2τ 2ℓ OS+1τ 2ℓ OS+≥2τ 2ℓSS/3ℓ+≥1τ 0.5 0.75 1 1.25 Data / Bkg 1− 10 1 10 2 10 3 10 4 10 5 10 6 10 Events ATLAS -1 = 13 TeV, 139 fbs Validation regions Post-Fit Data had τFake tt Single top Wtt *) (high)γ(Z/tt * (low)γtt Htt Diboson Non-prompt e µNon-prompt QMisID Mat Conv Other Uncertainty Pre-Fit Figure 11. Comparison between data and the background prediction for the event yields in the six validation region categories. The background contributions after the likelihood fit to data (“Post-Fit”) under the background-only hypothesis are shown as filled histograms. The ratio of the data to the background (“Bkg”) prediction is shown in the lower panel. The total background prediction before the likelihood fit to data (“Pre-Fit”) 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 blue hatched band. – 32 – JHEP06(2021)179 1000 1500 2000 2500 3000 3500 4000 [GeV] eff m 0 0.5 1 1.5 Data / Bkg 2− 10 1− 10 1 10 2 10 3 10 Events / 100 GeV ATLAS -1 = 13 TeV, 139 fbs 1ℓ+1τOS Post-Fit Data (1.1 TeV) d 3 LQ tt Single top had τFake Wtt *) (high)γ(Z/tt Htt Diboson Non-prompt e µNon-prompt QMisID Other Uncertainty Pre-Fit (a) 1000 1500 2000 2500 3000 3500 4000 [GeV] eff m 0 0.5 1 1.5 Data / Bkg 2− 10 1− 10 1 10 2 10 Events / 100 GeV ATLAS -1 = 13 TeV, 139 fbs 1ℓ+1τSS Post-Fit Data (1.1 TeV) d 3 LQ tt Single top had τFake Wtt *) (high)γ(Z/tt Htt Diboson Non-prompt e µNon-prompt QMisID Other Uncertainty Pre-Fit (b) 1000 1500 2000 2500 3000 3500 4000 [GeV] eff m 0 0.5 1 1.5 Data / Bkg 2− 10 1− 10 1 10 2 10 Events / 100 GeV ATLAS -1 = 13 TeV, 139 fbs 1ℓ+≥2τ Post-Fit Data (1.1 TeV) d 3 LQ had τFake Wtt *) (high)γ(Z/tt Htt Diboson Non-prompt e µNon-prompt QMisID Other Uncertainty Pre-Fit (c) Figure 12. Comparison between data and prediction for the meff distribution used in different signal region categories of the 1 ` + ≥ 1 τ channel: (a) 1 ` +1 τ OS, (b) 1 ` +1 τ SS, and (c) 1 ` + ≥ 2 τ . The background contributions after the likelihood fit to data (“Post-Fit”) under the backgroundonly hypothesis are shown as filled histograms. For illustrative purposes, the expected signal for mLQd 3 = 1 . 1 TeV and B = 1 is shown as a unfilled red histogram added to the post-fit background. 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 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 the background prediction is indicated by the blue hatched band. The blue triangles indicate points that are outside the vertical range of the figure. The last bin in each figure contains the overflow. – 33 – JHEP06(2021)179 0 500 1000 1500 2000 2500 3000 3500 4000 [GeV] eff m 0 0.5 1 1.5 Data / Bkg 2− 10 1− 10 1 10 2 10 Events / 100 GeV ATLAS -1 = 13 TeV, 139 fbs 2ℓOS+1τ Post-Fit Data (1.1 TeV) d 3 LQ had τFake Wtt *) (high)γ(Z/tt Htt Diboson Non-prompt e µNon-prompt QMisID Mat Conv Other Uncertainty Pre-Fit (a) 0 500 1000 1500 2000 2500 3000 3500 4000 [GeV] eff m 0 0.5 1 1.5 Data / Bkg 2− 10 1− 10 1 10 Events / 500 GeV ATLAS -1 = 13 TeV, 139 fbs 2ℓOS+≥2τ Post-Fit Data (1.1 TeV) d 3 LQ had τFake *) (high)γ(Z/tt Htt Other Uncertainty Pre-Fit (b) 0 500 1000 1500 2000 2500 3000 3500 4000 [GeV] eff m 0 0.5 1 1.5 Data / Bkg 2− 10 1− 10 1 10 2 10 Events / 500 GeV ATLAS -1 = 13 TeV, 139 fbs 2ℓSS/3ℓ+≥1τ−L Post-Fit Data (1.1 TeV) d 3 LQ Wtt *) (high)γ(Z/tt * (low)γtt Htt Diboson had τFake µNon-prompt QMisID Mat Conv Other Uncertainty Pre-Fit (c) 500 1000 1500 2000 2500 3000 3500 4000 [GeV] eff m 0 0.5 1 1.5 Data / Bkg 2− 10 1− 10 1 10 Events / 500 GeV ATLAS -1 = 13 TeV, 139 fbs 2ℓSS/3ℓ+≥1τ−H Post-Fit Data (1.1 TeV) d 3 LQ Wtt *) (high)γ(Z/tt Htt had τFake Diboson Other Uncertainty Pre-Fit (d) Figure 13. Comparison between data and prediction for the meff distribution used in different signal region categories of the 2 ` OS+ ≥ 1 τ and 2 ` SS/3 ` + ≥ 1 τ channels: (a) 2 ` OS+1 τ , (b) 2 ` OS+ ≥ 2 τ , (c) 2 ` SS/3 ` + ≥ 1 τ -L, and (d) 2 ` SS/3 ` + ≥ 1 τ -H. The background contributions after the likelihood fit to data (“Post-Fit”) under the background-only hypothesis are shown as filled histograms. For illustrative purposes, the expected signal for mLQd 3 = 1 . 1 TeV and B = 1 is shown as unfilled red histogram added to the post-fit background. 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 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 the background prediction is indicated by the blue hatched band. The blue triangles indicate points that are outside the vertical range of the figure. The last bin in each figure contains the overflow. – 34 – JHEP06(2021)179 600 800 1000 1200 1400 1600 [GeV] d 3 LQ m 7− 10 6− 10 5− 10 4− 10 3− 10 2− 10 1− 10 1 10 0 Local p ATLAS -1 =13 TeV, 139 fbs =1.0) Β Obs ( =1.0) Β Exp ( =0.5) Β Obs ( =0.5) Β Exp ( σ2 σ3 σ4 σ5 Figure 14. The observed (solid) local p0 as a function of LQd 3 mass ( mLQd 3 ) assuming B = 0 . 5 (blue) and B = 1 (red). The dashed curve shows the expected local p0 under the hypothesis of a LQd 3 signal at that mass. The horizontal dashed lines indicate the p -values corresponding to significances of 2 to 5 standard deviations. 600 800 1000 1200 1400 1600 [GeV] d 3 LQ m 4− 10 3− 10 2− 10 1− 10 1 ) [pb] d 3 LQ d 3 LQ→(ppσ ATLAS -1 = 13 TeV, 139 fbs τtτ t→ d 3 LQ d 3 LQ 95% CL Obs. limit Exp. limit σ1±Exp. +NNLL) approx Theory (NNLO Individual limits 1 lepton 2 leptons≥ Combination (a) 600 800 1000 1200 1400 1600 [GeV] d 3 LQ m 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 )τ t→ d 3 (LQ Β ATLAS -1 = 13 TeV, 139 fbs )τt→ d 3 (LQ Β )=1-νb→ d 3 (LQ Β 95% CL Obs. limit Exp. limit σ1±Exp. limit σ1±Theory (b) Figure 15. (a) Observed (solid line) and expected (dashed line) 95% CL upper limits on the LQd 3 pair production cross section as a function of mLQd 3 resulting from the combination of all analysis channels, assuming B= 1. The surrounding shaded band corresponds to the ±1 standard deviation ( ± 1 σ ) uncertainty around the combined expected limit, as estimated using the asymptotic approximation (see text). This approximation is found to overestimate the +1 σ ( − 1 σ ) uncertainty of the combined expected limit by about 5%–15% (15%–30%), depending on mLQd 3 . The red line and band show the theoretical prediction and its ±1σuncertainty. The individual expected limits for the 1 ` + ≥ 1 τ channel and the combination of the 2 ` OS+ ≥ 1 τ and 2 ` SS/3 ` + ≥ 1 τ channels are shown as the magenta and blue dashed lines, respectively. (b) Observed (solid line) and expected (dashed line) 95% CL upper limits on B as a function of mLQd 3 resulting from the combination of all analysis channels. The surrounding shaded band corresponds to the ± 1 σ uncertainty around the combined expected limit. The same statement regarding the asymptotic approximation given for (a) applies. The dotted red line around the observed limit indicates how the observed limit changes when varying the theoretical prediction for the LQd 3 pair production cross section by its ±1σuncertainty. – 35 – JHEP06(2021)179 8 Conclusion A search for pair production of third-generation scalar leptoquarks with a significant branching fraction into a top quark and a τ -lepton has been presented. The search is based on the full Run 2 dataset recorded with the ATLAS detector at Large Hadron Collider, which corresponds to 139fb −1 of pp collisions at √s = 13 TeV . Events are selected if they have one light lepton (electron or muon) and at least one hadronically decaying τ -lepton, or at least two light leptons, and additional jets. Six final states, defined by the multiplicity and flavour of lepton candidates, are considered in the analysis. Each of them is split into multiple event categories used to search for the signal and improve the modelling of several leading backgrounds. The signal-rich event categories require at least one hadronically decaying τ -lepton candidate and 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 decaying exclusively into tτ and with mass below about 1 . 2 TeV , which represents a significant improvement compared to previous searches. This results from a combination of the higher integrated luminosity used, a significantly improved identification of hadronically decaying τ -leptons, and the sophisticated event selection 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 event categories, and 95% CL upper limits are set on the production cross section as a function of 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 . The corresponding expected mass exclusions are 1 . 41 TeV and 1.19 TeV, respectively. Acknowledgments We thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions 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, MPO CR 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; MES of 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 and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received – 36 – JHEP06(2021)179 support from BCKDF, CANARIE, Compute Canada, CRC and IVADO, Canada; Beijing Municipal Science & Technology Commission, China; COST, ERC, ERDF, Horizon 2020 and Marie Sk ` odowska-Curie Actions, European Union; Investissements d’Avenir Labex, Investissements d’Avenir Idex and ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and GIF, Israel; La Caixa Banking Foundation, CERCA Programme Generalitat de Catalunya and PROMETEO and GenT Programmes Generalitat Valenciana, Spain; Göran Gustafssons Stiftelse, Sweden; The Royal Society and Leverhulme Trust, United Kingdom. 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Ducu36,27b, D. Duda115, A. Dudarev36, A.C. Dudder100, E.M. Duffield18, M. D’uffizi101, L. Duflot65, M. Dührssen36, C. Dülsen182, M. Dumancic180, A.E. Dumitriu27b, M. Dunford61a, S. Dungs 47 , A. Duperrin 102 , H. Duran Yildiz 4a , M. Düren 56 , A. Durglishvili 159b , D. Duschinger 48 , B. Dutta46, D. Duvnjak1, G.I. Dyckes136, M. Dyndal36, S. Dysch101, B.S. Dziedzic85, M.G. Eggleston49, T. Eifert8, G. Eigen17, K. Einsweiler18, T. Ekelof172, H. El Jarrari35f, V. Ellajosyula172, M. Ellert172, F. Ellinghaus182, A.A. Elliot93, N. Ellis36, J. Elmsheuser29, M. Elsing36, D. Emeliyanov143, A. Emerman39, Y. Enari163, M.B. Epland49, J. Erdmann47, A. Ereditato20, P.A. Erland85, M. Errenst182, M. Escalier65, C. Escobar174, O. Estrada Pastor174, E. Etzion161, G. Evans139a, H. Evans66, M.O. Evans156, A. Ezhilov137, F. Fabbri57, L. Fabbri23b,23a, V. Fabiani119, G. Facini178, R.M. Fakhrutdinov123, S. Falciano73a, P.J. Falke24, S. Falke 36 , J. Faltova 142 , Y. Fang 15a , Y. Fang 15a , G. Fanourakis 44 , M. Fanti 69a,69b , M. Faraj 67a,67c , A. Farbin8, A. Farilla75a, E.M. Farina71a,71b, T. Farooque107, S.M. Farrington50, P. Farthouat36, F. Fassi35f, P. Fassnacht36, D. Fassouliotis9, M. Faucci Giannelli50, W.J. Fawcett32, L. Fayard65, O.L. Fedin137,o, W. Fedorko175, A. Fehr20, M. Feickert173, L. Feligioni102, A. Fell149, C. Feng60b, M. Feng49, M.J. Fenton171, A.B. Fenyuk123, S.W. Ferguson43, J. Ferrando46, A. Ferrari172, P. Ferrari120, R. Ferrari71a, D.E. Ferreira de Lima61b, A. Ferrer174, D. Ferrere54, C. Ferretti106, F. Fiedler 100 , A. Filipčič 92 , F. Filthaut 119 , K.D. Finelli 25 , M.C.N. Fiolhais 139a,139c,a , L. Fiorini 174 , F. Fischer114, J. Fischer100, W.C. Fisher107, T. Fitschen21, I. Fleck151, P. Fleischmann106, T. Flick182, B.M. Flierl114, L. Flores136, L.R. Flores Castillo63a, F.M. Follega76a,76b, N. Fomin17, J.H. Foo167, G.T. Forcolin76a,76b, B.C. Forland66, A. Formica144, F.A. Förster14, A.C. Forti101, E. Fortin102, M.G. Foti134, D. Fournier65, H. Fox90, P. Francavilla72a,72b, S. Francescato73a,73b, M. Franchini23b,23a, S. Franchino61a, D. Francis36, L. Franco5, L. Franconi20, M. Franklin59, G. Frattari 73a,73b , A.N. Fray 93 , P.M. Freeman 21 , B. Freund 110 , W.S. Freund 81b , E.M. Freundlich 47 , – 47 – JHEP06(2021)179 D.C. Frizzell128, D. Froidevaux36, J.A. Frost134, M. Fujimoto126, C. Fukunaga164, E. Fullana Torregrosa174, T. Fusayasu116, J. Fuster174, A. Gabrielli23b,23a, A. Gabrielli36, S. Gadatsch 54 , P. Gadow 115 , G. Gagliardi 55b,55a , L.G. Gagnon 110 , G.E. Gallardo 134 , E.J. Gallas 134 , B.J. Gallop143, R. Gamboa Goni93, K.K. Gan127, S. Ganguly180, J. Gao60a, Y. Gao50, Y.S. Gao 31,l , F.M. Garay Walls 146a , C. García 174 , J.E. García Navarro 174 , J.A. García Pascual 15a , C. Garcia-Argos52, M. Garcia-Sciveres18, R.W. Gardner37, N. Garelli153, S. Gargiulo52, C.A. Garner167, V. Garonne133, S.J. Gasiorowski148, P. Gaspar81b, A. Gaudiello55b,55a, G. Gaudio71a, P. Gauzzi73a,73b, I.L. Gavrilenko111, A. Gavrilyuk124, C. Gay175, G. Gaycken46, E.N. Gazis10, A.A. Geanta27b, C.M. Gee145, C.N.P. Gee143, J. Geisen97, M. Geisen100, C. Gemme55b, M.H. Genest58, C. Geng106, S. Gentile73a,73b, S. George94, T. Geralis44, L.O. Gerlach 53 , P. Gessinger-Befurt 100 , G. Gessner 47 , M. Ghasemi Bostanabad 176 , M. Ghneimat 151 , A. Ghosh65, A. Ghosh78, B. Giacobbe23b, S. Giagu73a,73b, N. Giangiacomi167, P. Giannetti72a, A. Giannini70a,70b, G. Giannini14, S.M. Gibson94, M. Gignac145, D.T. Gil84b, B.J. Gilbert39, D. Gillberg34, G. Gilles182, N.E.K. Gillwald46, D.M. Gingrich3,aj, M.P. Giordani67a,67c, P.F. Giraud 144 , G. Giugliarelli 67a,67c , D. Giugni 69a , F. Giuli 74a,74b , S. Gkaitatzis 162 , I. Gkialas 9,g , E.L. Gkougkousis14, P. Gkountoumis10, L.K. Gladilin113, C. Glasman99, J. Glatzer14, P.C.F. Glaysher 46 , A. Glazov 46 , G.R. Gledhill 131 , I. Gnesi 41b,b , M. Goblirsch-Kolb 26 , D. Godin 110 , S. Goldfarb105, T. Golling54, D. Golubkov123, A. Gomes139a,139b, R. Goncalves Gama53, R. Gonçalo139a,139c, G. Gonella131, L. Gonella21, A. Gongadze80, F. Gonnella21, J.L. Gonski39, S. González de la Hoz 174 , S. Gonzalez Fernandez 14 , R. Gonzalez Lopez 91 , C. Gonzalez Renteria 18 , R. Gonzalez Suarez172, S. Gonzalez-Sevilla54, G.R. Gonzalvo Rodriguez174, L. Goossens36, N.A. Gorasia21, P.A. Gorbounov124, H.A. Gordon29, B. Gorini36, E. Gorini68a,68b, A. Gorišek92, A.T. Goshaw49, M.I. Gostkin80, C.A. Gottardo119, M. Gouighri35b, A.G. Goussiou148, N. Govender 33c , C. Goy 5 , I. Grabowska-Bold 84a , E.C. Graham 91 , J. Gramling 171 , E. Gramstad 133 , S. Grancagnolo19, M. Grandi156, V. Gratchev137, P.M. Gravila27f, F.G. Gravili68a,68b, C. Gray57, H.M. Gray 18 , C. Grefe 24 , K. Gregersen 97 , I.M. Gregor 46 , P. Grenier 153 , K. Grevtsov 46 , C. Grieco 14 , N.A. Grieser128, A.A. Grillo145, K. Grimm31,k, S. Grinstein14,v, J.-F. Grivaz65, S. Groh100, E. Gross180, J. Grosse-Knetter53, Z.J. Grout95, C. Grud106, A. Grummer118, J.C. Grundy134, L. Guan106, W. Guan181, C. Gubbels175, J. Guenther77, A. Guerguichon65, J.G.R. Guerrero Rojas174, F. Guescini115, D. Guest77, R. Gugel100, A. Guida46, T. Guillemin5, S. Guindon36, J. Guo60c, W. Guo106, Y. Guo60a, Z. Guo102, R. Gupta46, S. Gurbuz12c, G. Gustavino128, M. Guth52, P. Gutierrez128, C. Gutschow95, C. Guyot144, C. Gwenlan134, C.B. Gwilliam91, E.S. Haaland133, A. Haas125, C. Haber18, H.K. Hadavand8, A. Hadef100, M. Haleem177, J. Haley129, J.J. Hall149, G. Halladjian107, G.D. Hallewell102, K. Hamano176, H. Hamdaoui35f, M. Hamer24, G.N. Hamity50, K. Han60a, L. Han15c, L. Han60a, S. Han18, Y.F. Han167, K. Hanagaki82,t, M. Hance145, D.M. Handl114, M.D. Hank37, R. Hankache135, E. Hansen97, J.B. Hansen40, J.D. Hansen40, M.C. Hansen24, P.H. Hansen40, E.C. Hanson101, K. Hara169, T. Harenberg182, S. Harkusha108, P.F. Harrison178, N.M. Hartman153, N.M. Hartmann114, Y. Hasegawa150, A. Hasib50, S. Hassani144, S. Haug20, R. Hauser107, M. Havranek141, C.M. Hawkes21, R.J. Hawkings36, S. Hayashida117, D. Hayden107, C. Hayes106, R.L. Hayes175, C.P. Hays134, J.M. Hays93, H.S. Hayward91, S.J. Haywood143, F. He60a, Y. He165, M.P. Heath 50 , V. Hedberg 97 , A.L. Heggelund 133 , N.D. Hehir 93 , C. Heidegger 52 , K.K. Heidegger 52 , W.D. Heidorn79, J. Heilman34, S. Heim46, T. Heim18, B. Heinemann46,ah, J.G. Heinlein136, J.J. Heinrich131, L. Heinrich36, J. Hejbal140, L. Helary46, A. Held125, S. Hellesund133, C.M. Helling145, S. Hellman45a,45b, C. Helsens36, R.C.W. Henderson90, L. Henkelmann32, A.M. Henriques Correia36, H. Herde26, Y. Hernández Jiménez33f, M.G. Herrmann114, T. Herrmann48, G. Herten52, R. Hertenberger114, L. Hervas36, G.G. Hesketh95, N.P. Hessey168a, H. Hibi83, S. Higashino82, E. Higón-Rodriguez174, K. Hildebrand37, J.C. Hill32, K.K. Hill29, – 48 – JHEP06(2021)179 K.H. Hiller 46 , S.J. Hillier 21 , M. Hils 48 , I. Hinchliffe 18 , F. Hinterkeuser 24 , M. Hirose 132 , S. Hirose 169 , D. Hirschbuehl182, B. Hiti92, O. Hladik140, J. Hobbs155, R. Hobincu27e, N. Hod180, M.C. Hodgkinson149, A. Hoecker36, D. Hohn52, D. Hohov65, T. Holm24, T.R. Holmes37, M. Holzbock115, L.B.A.H. Hommels32, T.M. Hong138, J.C. Honig52, A. Hönle115, B.H. Hooberman173, W.H. Hopkins6, Y. Horii117, P. Horn48, L.A. Horyn37, S. Hou158, A. Hoummada35a, J. Howarth57, J. Hoya89, M. Hrabovsky130, J. Hrivnac65, A. Hrynevich109, T. Hryn’ova5, P.J. Hsu64, S.-C. Hsu148, Q. Hu39, S. Hu60c, Y.F. Hu15a,15d,al, D.P. Huang95, X. Huang15c, Y. Huang60a, Y. Huang15a, Z. Hubacek141, F. Hubaut102, M. Huebner24, F. Huegging24, T.B. Huffman134, M. Huhtinen36, R. Hulsken58, R.F.H. Hunter34, N. Huseynov80,aa, J. Huston107, J. Huth59, R. Hyneman153, S. Hyrych28a, G. Iacobucci54, G. Iakovidis29, I. Ibragimov151, L. Iconomidou-Fayard65, P. Iengo36, R. Ignazzi40, R. Iguchi163, T. Iizawa 54 , Y. Ikegami 82 , M. Ikeno 82 , N. Ilic 119,167,z , F. Iltzsche 48 , H. Imam 35a , G. Introzzi 71a,71b , M. Iodice75a, K. Iordanidou168a, V. Ippolito73a,73b, M.F. Isacson172, M. Ishino163, W. Islam129, C. Issever19,46, S. Istin160, J.M. Iturbe Ponce63a, R. Iuppa76a,76b, A. Ivina180, J.M. Izen43, V. Izzo70a, P. Jacka140, P. Jackson1, R.M. Jacobs46, B.P. Jaeger152, V. Jain2, G. Jäkel182, K.B. Jakobi100, K. Jakobs52, T. Jakoubek180, J. Jamieson57, K.W. Janas84a, R. Jansky54, M. Janus53, P.A. Janus84a, G. Jarlskog97, A.E. Jaspan91, N. Javadov80,aa, M. Javurkova103, F. Jeanneau144, L. Jeanty131, J. Jejelava159a, P. Jenni52,c, N. Jeong46, S. Jézéquel5, J. Jia155, Z. Jia15c, H. Jiang79, Y. Jiang60a, Z. Jiang153, S. Jiggins52, F.A. Jimenez Morales38, J. Jimenez Pena115, S. Jin15c, A. Jinaru27b, O. Jinnouchi165, P. Johansson149, K.A. Johns7, E. Jones178, R.W.L. Jones90, S.D. Jones156, T.J. Jones91, J. Jovicevic36, X. Ju18, J.J. Junggeburth115, A. Juste Rozas14,v, A. Kaczmarska85, M. Kado73a,73b, H. Kagan127, M. Kagan153, A. Kahn39, C. Kahra100, T. Kaji179, E. Kajomovitz160, C.W. Kalderon29, A. Kaluza 100 , M. Kaneda 163 , N.J. Kang 145 , S. Kang 79 , Y. Kano 117 , J. Kanzaki 82 , L.S. Kaplan 181 , D. Kar33f, K. Karava134, M.J. Kareem168b, I. Karkanias162, S.N. Karpov80, Z.M. Karpova80, V. Kartvelishvili 90 , A.N. Karyukhin 123 , E. Kasimi 162 , A. Kastanas 45a,45b , C. Kato 60d , J. Katzy 46 , K. Kawade150, K. Kawagoe88, T. Kawamoto144, G. Kawamura53, E.F. Kay176, F.I. Kaya170, S. Kazakos14, V.F. Kazanin122b,122a, J.M. Keaveney33a, R. Keeler176, J.S. Keller34, E. Kellermann97, D. Kelsey156, J.J. Kempster21, K.E. Kennedy39, O. Kepka140, S. Kersten182, B.P. Kerševan92, S. Ketabchi Haghighat167, F. Khalil-Zada13, M. Khandoga144, A. Khanov129, A.G. Kharlamov122b,122a, T. Kharlamova122b,122a, E.E. Khoda175, T.J. Khoo77, G. Khoriauli177, E. Khramov80, J. Khubua159b, S. Kido83, M. Kiehn36, E. Kim165, Y.K. Kim37, N. Kimura95, A. Kirchhoff53, D. Kirchmeier48, J. Kirk143, A.E. Kiryunin115, T. Kishimoto163, D.P. Kisliuk167, V. Kitali46, C. Kitsaki10, O. Kivernyk24, T. Klapdor-Kleingrothaus52, M. Klassen61a, C. Klein34, M.H. Klein106, M. Klein91, U. Klein91, K. Kleinknecht100, P. Klimek36, A. Klimentov29, F. Klimpel36, T. Klingl24, T. Klioutchnikova36, F.F. Klitzner114, P. Kluit120, S. Kluth115, E. Kneringer77, E.B.F.G. Knoops102, A. Knue52, D. Kobayashi88, M. Kobel48, M. Kocian153, P. Kodys 142 , D.M. Koeck 156 , P.T. Koenig 24 , T. Koffas 34 , N.M. Köhler 36 , M. Kolb 144 , I. Koletsou 5 , T. Komarek130, T. Kondo82, K. Köneke52, A.X.Y. Kong1, A.C. König119, T. Kono126, V. Konstantinides95, N. Konstantinidis95, B. Konya97, R. Kopeliansky66, S. Koperny84a, K. Korcyl85, K. Kordas162, G. Koren161, A. Korn95, I. Korolkov14, E.V. Korolkova149, N. Korotkova113, O. Kortner115, S. Kortner115, V.V. Kostyukhin149,166, A. Kotsokechagia65, A. Kotwal 49 , A. Koulouris 10 , A. Kourkoumeli-Charalampidi 71a,71b , C. Kourkoumelis 9 , E. Kourlitis 6 , V. Kouskoura29, R. Kowalewski176, W. Kozanecki101, A.S. Kozhin123, V.A. Kramarenko113, G. Kramberger92, D. Krasnopevtsev60a, M.W. Krasny135, A. Krasznahorkay36, D. Krauss115, J.A. Kremer100, J. Kretzschmar91, K. Kreul19, P. Krieger167, F. Krieter114, S. Krishnamurthy103, A. Krishnan 61b , M. Krivos 142 , K. Krizka 18 , K. Kroeninger 47 , H. Kroha 115 , J. Kroll 140 , J. Kroll 136 , K.S. Krowpman 107 , U. Kruchonak 80 , H. Krüger 24 , N. Krumnack 79 , M.C. Kruse 49 , J.A. Krzysiak 85 , – 49 – JHEP06(2021)179 A. Kubota165, O. Kuchinskaia166, S. Kuday4b, D. Kuechler46, J.T. Kuechler46, S. Kuehn36, T. Kuhl46, V. Kukhtin80, Y. Kulchitsky108,ad, S. Kuleshov146b, Y.P. Kulinich173, A. Kupco140, T. Kupfer47, O. Kuprash52, H. Kurashige83, L.L. Kurchaninov168a, Y.A. Kurochkin108, A. Kurova112, M.G. Kurth15a,15d, M. Kuze165, A.K. Kvam148, J. Kvita130, T. Kwan104, C. Lacasta174, F. Lacava73a,73b, D.P.J. Lack101, H. Lacker19, D. Lacour135, E. Ladygin80, R. Lafaye5, B. Laforge135, T. Lagouri146c, S. Lai53, I.K. Lakomiec84a, J.E. Lambert128, S. Lammers66, W. Lampl7, C. Lampoudis162, E. Lançon29, U. Landgraf52, M.P.J. Landon93, V.S. Lang52, J.C. Lange53, R.J. Langenberg103, A.J. Lankford171, F. Lanni29, K. Lantzsch24, A. Lanza71a, A. Lapertosa55b,55a, J.F. Laporte144, T. Lari69a, F. Lasagni Manghi23b,23a, M. Lassnig36, V. Latonova140, T.S. Lau63a, A. Laudrain100, A. Laurier34, M. Lavorgna70a,70b, S.D. Lawlor94, M. Lazzaroni69a,69b, B. Le101, E. Le Guirriec102, A. Lebedev79, M. LeBlanc7, T. LeCompte 6 , F. Ledroit-Guillon 58 , A.C.A. Lee 95 , C.A. Lee 29 , G.R. Lee 17 , L. Lee 59 , S.C. Lee 158 , S. Lee79, B. Lefebvre168a, H.P. Lefebvre94, M. Lefebvre176, C. Leggett18, K. Lehmann152, N. Lehmann20, G. Lehmann Miotto36, W.A. Leight46, A. Leisos162,u, M.A.L. Leite81c, C.E. Leitgeb114, R. Leitner142, K.J.C. Leney42, T. Lenz24, S. Leone72a, C. Leonidopoulos50, A. Leopold135, C. Leroy110, R. Les107, C.G. Lester32, M. Levchenko137, J. Levêque5, D. Levin106, L.J. Levinson180, D.J. Lewis21, B. Li15b, B. Li106, C-Q. Li60c,60d, F. Li60c, H. Li60a, H. Li60b, J. Li60c, K. Li148, L. Li60c, M. Li15a,15d, Q.Y. Li60a, S. Li60d,60c, X. Li46, Y. Li46, Z. Li60b, Z. Li134, Z. Li104, Z. Li91, Z. Liang15a, M. Liberatore46, B. Liberti74a, K. Lie63c, S. Lim29, C.Y. Lin32, K. Lin107, R.A. Linck66, R.E. Lindley7, J.H. Lindon21, A. Linss46, A.L. Lionti54, E. Lipeles136, A. Lipniacka17, T.M. Liss173,ai, A. Lister175, J.D. Little8, B. Liu79, B.X. Liu152, H.B. Liu 29 , J.B. Liu 60a , J.K.K. Liu 37 , K. Liu 60d,60c , M. Liu 60a , M.Y. Liu 60a , P. Liu 15a , X. Liu 60a , Y. Liu46, Y. Liu15a,15d, Y.L. Liu106, Y.W. Liu60a, M. Livan71a,71b, A. Lleres58, J. Llorente Merino 152 , S.L. Lloyd 93 , C.Y. Lo 63b , E.M. Lobodzinska 46 , P. Loch 7 , S. Loffredo 74a,74b , T. Lohse19, K. Lohwasser149, M. Lokajicek140, J.D. Long173, R.E. Long90, I. Longarini73a,73b, L. Longo 36 , I. Lopez Paz 101 , A. Lopez Solis 149 , J. Lorenz 114 , N. Lorenzo Martinez 5 , A.M. Lory 114 , A. Lösle52, X. Lou45a,45b, X. Lou15a, A. Lounis65, J. Love6, P.A. Love90, J.J. Lozano Bahilo174, M. Lu60a, Y.J. Lu64, H.J. Lubatti148, C. Luci73a,73b, F.L. Lucio Alves15c, A. Lucotte58, F. Luehring66, I. Luise155, L. Luminari73a, B. Lund-Jensen154, N.A. Luongo131, M.S. Lutz161, D. Lynn 29 , H. Lyons 91 , R. Lysak 140 , E. Lytken 97 , F. Lyu 15a , V. Lyubushkin 80 , T. Lyubushkina 80 , H. Ma29, L.L. Ma60b, Y. Ma95, D.M. Mac Donell176, G. Maccarrone51, C.M. Macdonald149, J.C. MacDonald149, J. Machado Miguens136, R. Madar38, W.F. Mader48, M. Madugoda Ralalage Don129, N. Madysa48, J. Maeda83, T. Maeno29, M. Maerker48, V. Magerl52, N. Magini79, J. Magro67a,67c,q, D.J. Mahon39, C. Maidantchik81b, A. Maio139a,139b,139d, K. Maj84a, O. Majersky28a, S. Majewski131, Y. Makida82, N. Makovec65, B. Malaescu135, Pa. Malecki85, V.P. Maleev137, F. Malek58, D. Malito41b,41a, U. Mallik78, C. Malone32, S. Maltezos10, S. Malyukov80, J. Mamuzic174, G. Mancini51, J.P. Mandalia93, I. Mandić92, L. Manhaes de Andrade Filho81a, I.M. Maniatis162, J. Manjarres Ramos48, A. Mann114, B. Mansoulie144, I. Manthos162, S. Manzoni120, A. Marantis162,u, G. Marceca30, L. Marchese134, G. Marchiori135, M. Marcisovsky140, L. Marcoccia74a,74b, C. Marcon97, M. Marjanovic128, Z. Marshall18, M.U.F. Martensson172, S. Marti-Garcia174, C.B. Martin127, T.A. Martin178, V.J. Martin50, B. Martin dit Latour17, L. Martinelli75a,75b, M. Martinez14,v, P. Martinez Agullo174, V.I. Martinez Outschoorn103, S. Martin-Haugh143, V.S. Martoiu27b, A.C. Martyniuk95, A. Marzin36, S.R. Maschek115, L. Masetti100, T. Mashimo163, R. Mashinistov111, J. Masik101, A.L. Maslennikov122b,122a, L. Massa23b,23a, P. Massarotti70a,70b, P. Mastrandrea72a,72b, A. Mastroberardino41b,41a, T. Masubuchi163, D. Matakias29, N. Matsuzawa163, P. Mättig24, J. Maurer27b, B. Maček92, D.A. Maximov122b,122a, R. Mazini158, I. Maznas162, S.M. Mazza145, J.P. Mc Gowan104, S.P. Mc Kee106, W.P. McCormack18, – 50 – JHEP06(2021)179 E.F. McDonald105, A.E. McDougall120, J.A. Mcfayden18, G. Mchedlidze159b, M.A. McKay42, K.D. McLean176, S.J. McMahon143, P.C. McNamara105, C.J. McNicol178, R.A. McPherson176,z, Z.A. Meadows103, T. Megy38, S. Mehlhase114, A. Mehta91, B. Meirose43, D. Melini160, B.R. Mellado Garcia33f, J.D. Mellenthin53, M. Melo28a, F. Meloni46, A. Melzer24, E.D. Mendes Gouveia139a,139e, A.M. Mendes Jacques Da Costa21, H.Y. Meng167, L. Meng36, X.T. Meng 106 , S. Menke 115 , E. Meoni 41b,41a , S. Mergelmeyer 19 , S.A.M. Merkt 138 , C. Merlassino 134 , P. Mermod54,*, L. Merola70a,70b, C. Meroni69a, G. Merz106, O. Meshkov113,111, J.K.R. Meshreki151, J. Metcalfe6, A.S. Mete6, C. Meyer66, J-P. Meyer144, M. Michetti19, R.P. Middleton 143 , L. Mijović 50 , G. Mikenberg 180 , M. Mikestikova 140 , M. Mikuž 92 , H. Mildner 149 , A. Milic167, C.D. Milke42, D.W. Miller37, L.S. Miller34, A. Milov180, D.A. Milstead45a,45b, A.A. Minaenko123, I.A. Minashvili159b, L. Mince57, A.I. Mincer125, B. Mindur84a, M. Mineev80, Y. Mino86, L.M. Mir14, M. Mironova134, T. Mitani179, J. Mitrevski114, V.A. Mitsou174, M. Mittal60c, O. Miu167, A. Miucci20, P.S. Miyagawa93, A. Mizukami82, J.U. Mjörnmark97, T. Mkrtchyan61a, M. Mlynarikova121, T. Moa45a,45b, S. Mobius53, K. Mochizuki110, P. Moder46, P. Mogg114, S. Mohapatra39, R. Moles-Valls24, K. Mönig46, E. Monnier102, A. Montalbano152, J. Montejo Berlingen36, M. Montella95, F. Monticelli89, S. Monzani69a, N. Morange65, A.L. Moreira De Carvalho139a, D. Moreno22a, M. Moreno Llácer174, C. Moreno Martinez14, P. Morettini55b, M. Morgenstern160, S. Morgenstern48, D. Mori152, M. Morii59, M. Morinaga179, V. Morisbak133, A.K. Morley36, G. Mornacchi36, A.P. Morris95, L. Morvaj36, P. Moschovakos36, B. Moser120, M. Mosidze159b, T. Moskalets144, P. Moskvitina119, J. Moss31,m, E.J.W. Moyse103, S. Muanza102, J. Mueller138, R.S.P. Mueller114, D. Muenstermann90, G.A. Mullier97, D.P. Mungo69a,69b, J.L. Munoz Martinez14, F.J. Munoz Sanchez101, P. Murin28b, W.J. Murray178,143, A. Murrone69a,69b, J.M. Muse128, M. Muškinja18, C. Mwewa33a, A.G. Myagkov123,ae, A.A. Myers138, G. Myers66, J. Myers131, M. Myska141, B.P. Nachman18, O. Nackenhorst47, A.Nag Nag48, K. Nagai134, K. Nagano82, Y. Nagasaka62, J.L. Nagle29, E. Nagy102, A.M. Nairz36, Y. Nakahama117, K. Nakamura82, T. Nakamura163, H. Nanjo132, F. Napolitano61a, R.F. Naranjo Garcia46, R. Narayan42, I. Naryshkin137, M. Naseri34, T. Naumann46, G. Navarro22a, P.Y. Nechaeva111, F. Nechansky46, T.J. Neep21, A. Negri71a,71b, M. Negrini23b, C. Nellist119, C. Nelson104, M.E. Nelson45a,45b, S. Nemecek140, M. Nessi36,e, M.S. Neubauer 173 , F. Neuhaus 100 , M. Neumann 182 , R. Newhouse 175 , P.R. Newman 21 , C.W. Ng 138 , Y.S. Ng19, Y.W.Y. Ng171, B. Ngair35f, H.D.N. Nguyen102, T. Nguyen Manh110, E. Nibigira38, R.B. Nickerson 134 , R. Nicolaidou 144 , D.S. Nielsen 40 , J. Nielsen 145 , M. Niemeyer 53 , N. Nikiforou 11 , V. Nikolaenko123,ae, I. Nikolic-Audit135, K. Nikolopoulos21, P. Nilsson29, H.R. Nindhito54, A. Nisati73a, N. Nishu60c, R. Nisius115, I. Nitsche47, T. Nitta179, T. Nobe163, D.L. Noel32, Y. Noguchi86, I. Nomidis135, M.A. Nomura29, M. Nordberg36, J. Novak92, T. Novak92, O. Novgorodova48, R. Novotny118, L. Nozka130, K. Ntekas171, E. Nurse95, F.G. Oakham34,aj, J. Ocariz135, A. Ochi83, I. Ochoa139a, J.P. Ochoa-Ricoux146a, K. O’Connor26, S. Oda88, S. Odaka82, S. Oerdek53, A. Ogrodnik84a, A. Oh101, C.C. Ohm154, H. Oide165, R. Oishi163, M.L. Ojeda167, H. Okawa169, Y. Okazaki86, M.W. O’Keefe91, Y. Okumura163, A. Olariu27b, L.F. Oleiro Seabra139a, S.A. Olivares Pino146a, D. Oliveira Damazio29, J.L. Oliver1, M.J.R. Olsson171, A. Olszewski85, J. Olszowska85, Ö.O. Öncel24, D.C. O’Neil152, A.P. O’neill134, A. Onofre139a,139e, P.U.E. Onyisi11, H. Oppen133, R.G. Oreamuno Madriz121, M.J. Oreglia37, G.E. Orellana89, D. Orestano75a,75b, N. Orlando14, R.S. Orr167, V. O’Shea57, R. Ospanov60a, G. Otero y Garzon30, H. Otono88, P.S. Ott61a, G.J. Ottino18, M. Ouchrif35e, J. Ouellette29, F. Ould-Saada133, A. Ouraou144,*, Q. Ouyang15a, M. Owen57, R.E. Owen143, V.E. Ozcan12c, N. Ozturk8, J. Pacalt130, H.A. Pacey32, K. Pachal49, A. Pacheco Pages14, C. Padilla Aranda14, S. Pagan Griso18, G. Palacino66, S. Palazzo50, S. Palestini36, M. Palka84b, P. Palni84a, C.E. Pandini54, J.G. Panduro Vazquez94, P. Pani46, G. Panizzo67a,67c, L. Paolozzi54, – 51 – JHEP06(2021)179 C. Papadatos110, K. Papageorgiou9,g, S. Parajuli42, A. Paramonov6, C. Paraskevopoulos10, D. Paredes Hernandez63b, S.R. Paredes Saenz134, B. Parida180, T.H. Park167, A.J. Parker31, M.A. Parker32, F. Parodi55b,55a, E.W. Parrish121, J.A. Parsons39, U. Parzefall52, L. Pascual Dominguez135, V.R. Pascuzzi18, J.M.P. Pasner145, F. Pasquali120, E. Pasqualucci73a, S. Passaggio55b, F. Pastore94, P. Pasuwan45a,45b, S. Pataraia100, J.R. Pater101, A. Pathak181,i, J. Patton91, T. Pauly36, J. Pearkes153, M. Pedersen133, L. Pedraza Diaz119, R. Pedro139a, T. Peiffer53, S.V. Peleganchuk122b,122a, O. Penc140, C. Peng63b, H. Peng60a, B.S. Peralva81a, M.M. Perego65, A.P. Pereira Peixoto139a, L. Pereira Sanchez45a,45b, D.V. Perepelitsa29, E. Perez Codina 168a , L. Perini 69a,69b , H. Pernegger 36 , S. Perrella 36 , A. Perrevoort 120 , K. Peters 46 , R.F.Y. Peters101, B.A. Petersen36, T.C. Petersen40, E. Petit102, V. Petousis141, C. Petridou162, F. Petrucci 75a,75b , M. Pettee 183 , N.E. Pettersson 103 , K. Petukhova 142 , A. Peyaud 144 , R. Pezoa 146d , L. Pezzotti 71a,71b , T. Pham 105 , P.W. Phillips 143 , M.W. Phipps 173 , G. Piacquadio 155 , E. Pianori 18 , A. Picazio103, R.H. Pickles101, R. Piegaia30, D. Pietreanu27b, J.E. Pilcher37, A.D. Pilkington101, M. Pinamonti67a,67c, J.L. Pinfold3, C. Pitman Donaldson95, M. Pitt161, L. Pizzimento74a,74b, A. Pizzini120, M.-A. Pleier29, V. Plesanovs52, V. Pleskot142, E. Plotnikova80, P. Podberezko122b,122a, R. Poettgen97, R. Poggi54, L. Poggioli135, I. Pogrebnyak107, D. Pohl24, I. Pokharel53, G. Polesello71a, A. Poley152,168a, A. Policicchio73a,73b, R. Polifka142, A. Polini23b, C.S. Pollard46, V. Polychronakos29, D. Ponomarenko112, L. Pontecorvo36, S. Popa27a, G.A. Popeneciu27d, L. Portales5, D.M. Portillo Quintero58, S. Pospisil141, K. Potamianos46, I.N. Potrap80, C.J. Potter32, H. Potti11, T. Poulsen97, J. Poveda174, T.D. Powell149, M.E. Pozo Astigarraga36, A. Prades Ibanez174, P. Pralavorio102, M.M. Prapa44, S. Prell79, D. Price101, M. Primavera68a, M.L. Proffitt148, N. Proklova112, K. Prokofiev63c, F. Prokoshin80, S. Protopopescu29, J. Proudfoot6, M. Przybycien84a, D. Pudzha137, A. Puri173, P. Puzo65, D. Pyatiizbyantseva112, J. Qian106, Y. Qin101, A. Quadt53, M. Queitsch-Maitland36, G. Rabanal Bolanos 59 , M. Racko 28a , F. Ragusa 69a,69b , G. Rahal 98 , J.A. Raine 54 , S. Rajagopalan 29 , A. Ramirez Morales 93 , K. Ran 15a,15d , D.F. Rassloff 61a , D.M. Rauch 46 , F. Rauscher 114 , S. Rave 100 , B. Ravina57, I. Ravinovich180, J.H. Rawling101, M. Raymond36, A.L. Read133, N.P. Readioff149, M. Reale68a,68b, D.M. Rebuzzi71a,71b, G. Redlinger29, K. Reeves43, D. Reikher161, A. Reiss100, A. Rej151, C. Rembser36, A. Renardi46, M. Renda27b, M.B. Rendel115, A.G. Rennie57, S. Resconi69a, E.D. Resseguie18, S. Rettie95, B. Reynolds127, E. Reynolds21, O.L. Rezanova122b,122a, P. Reznicek142, E. Ricci76a,76b, R. Richter115, S. Richter46, E. Richter-Was84b, M. Ridel135, P. Rieck115, O. Rifki46, M. Rijssenbeek155, A. Rimoldi71a,71b, M. Rimoldi46, L. Rinaldi23b, T.T. Rinn173, G. Ripellino154, I. Riu14, P. Rivadeneira46, J.C. Rivera Vergara 176 , F. Rizatdinova 129 , E. Rizvi 93 , C. Rizzi 36 , S.H. Robertson 104,z , M. Robin 46 , D. Robinson32, C.M. Robles Gajardo146d, M. Robles Manzano100, A. Robson57, A. Rocchi74a,74b, C. Roda72a,72b, S. Rodriguez Bosca174, A. Rodriguez Rodriguez52, A.M. Rodríguez Vera168b, S. Roe 36 , J. Roggel 182 , O. Røhne 133 , R. Röhrig 115 , R.A. Rojas 146d , B. Roland 52 , C.P.A. Roland 66 , J. Roloff29, A. Romaniouk112, M. Romano23b,23a, N. Rompotis91, M. Ronzani125, L. Roos135, S. Rosati73a, G. Rosin103, B.J. Rosser136, E. Rossi46, E. Rossi75a,75b, E. Rossi70a,70b, L.P. Rossi55b, L. Rossini46, R. Rosten14, M. Rotaru27b, B. Rottler52, D. Rousseau65, G. Rovelli71a,71b, A. Roy11, D. Roy33f, A. Rozanov102, Y. Rozen160, X. Ruan33f, T.A. Ruggeri1, F. Rühr 52 , A. Ruiz-Martinez 174 , A. Rummler 36 , Z. Rurikova 52 , N.A. Rusakovich 80 , H.L. Russell 104 , L. Rustige38,47, J.P. Rutherfoord7, M. Rybar142, G. Rybkin65, E.B. Rye133, A. Ryzhov123, J.A. Sabater Iglesias46, P. Sabatini174, L. Sabetta73a,73b, S. Sacerdoti65, H.F-W. Sadrozinski145, R. Sadykov 80 , F. Safai Tehrani 73a , B. Safarzadeh Samani 156 , M. Safdari 153 , P. Saha 121 , S. Saha 104 , M. Sahinsoy115, A. Sahu182, M. Saimpert36, M. Saito163, T. Saito163, H. Sakamoto163, D. Salamani54, G. Salamanna75a,75b, A. Salnikov153, J. Salt174, A. Salvador Salas14, D. Salvatore41b,41a, F. Salvatore156, A. Salvucci63a, A. Salzburger36, J. Samarati36, D. Sammel52, – 52 – JHEP06(2021)179 D. Sampsonidis162, D. Sampsonidou60d,60c, J. Sánchez174, A. Sanchez Pineda67a,36,67c, H. Sandaker133, C.O. Sander46, I.G. Sanderswood90, M. Sandhoff182, C. Sandoval22b, D.P.C. Sankey143, M. Sannino55b,55a, Y. Sano117, A. Sansoni51, C. Santoni38, H. Santos139a,139b, S.N. Santpur 18 , A. Santra 174 , K.A. Saoucha 149 , A. Sapronov 80 , J.G. Saraiva 139a,139d , O. Sasaki 82 , K. Sato169, F. Sauerburger52, E. Sauvan5, P. Savard167,aj, R. Sawada163, C. Sawyer143, L. Sawyer96, I. Sayago Galvan174, C. Sbarra23b, A. Sbrizzi67a,67c, T. Scanlon95, J. Schaarschmidt148, P. Schacht115, D. Schaefer37, L. Schaefer136, U. Schäfer100, A.C. Schaffer65, D. Schaile114, R.D. Schamberger155, E. Schanet114, C. Scharf19, N. Scharmberg101, V.A. Schegelsky137, D. Scheirich142, F. Schenck19, M. Schernau171, C. Schiavi55b,55a, L.K. Schildgen24, Z.M. Schillaci26, E.J. Schioppa68a,68b, M. Schioppa41b,41a, K.E. Schleicher52, S. Schlenker36, K.R. Schmidt-Sommerfeld115, K. Schmieden100, C. Schmitt100, S. Schmitt46, L. Schoeffel144, A. Schoening61b, P.G. Scholer52, E. Schopf134, M. Schott100, J.F.P. Schouwenberg119, J. Schovancova36, S. Schramm54, F. Schroeder182, A. Schulte100, H-C. Schultz-Coulon61a, M. Schumacher52, B.A. Schumm145, Ph. Schune144, A. Schwartzman153, T.A. Schwarz 106 , Ph. Schwemling 144 , R. Schwienhorst 107 , A. Sciandra 145 , G. Sciolla 26 , F. Scuri 72a , F. Scutti105, L.M. Scyboz115, C.D. Sebastiani91, K. Sedlaczek47, P. Seema19, S.C. Seidel118, A. Seiden145, B.D. Seidlitz29, T. Seiss37, C. Seitz46, J.M. Seixas81b, G. Sekhniaidze70a, S.J. Sekula42, N. Semprini-Cesari23b,23a, S. Sen49, C. Serfon29, L. Serin65, L. Serkin67a,67b, M. Sessa60a, H. Severini128, S. Sevova153, F. Sforza55b,55a, A. Sfyrla54, E. Shabalina53, J.D. Shahinian136, N.W. Shaikh45a,45b, D. Shaked Renous180, L.Y. Shan15a, M. Shapiro18, A. Sharma36, A.S. Sharma1, P.B. Shatalov124, K. Shaw156, S.M. Shaw101, M. Shehade180, Y. Shen128, A.D. Sherman25, P. Sherwood95, L. Shi95, C.O. Shimmin183, Y. Shimogama179, M. Shimojima 116 , J.D. Shinner 94 , I.P.J. Shipsey 134 , S. Shirabe 165 , M. Shiyakova 80,x , J. Shlomi 180 , A. Shmeleva111, M.J. Shochet37, J. Shojaii105, D.R. Shope154, S. Shrestha127, E.M. Shrif33f, M.J. Shroff176, E. Shulga180, P. Sicho140, A.M. Sickles173, E. Sideras Haddad33f, A. Sidoti23b,23a, F. Siegert48, Dj. Sijacki16, M.Jr. Silva181, M.V. Silva Oliveira36, S.B. Silverstein45a, S. Simion65, R. Simoniello100, C.J. Simpson-allsop21, S. Simsek12b, P. Sinervo167, V. Sinetckii113, S. Singh152, S. Sinha 33f , M. Sioli 23b,23a , I. Siral 131 , S.Yu. Sivoklokov 113 , J. Sjölin 45a,45b , A. Skaf 53 , E. Skorda 97 , P. Skubic128, M. Slawinska85, K. Sliwa170, V. Smakhtin180, B.H. Smart143, J. Smiesko28b, N. Smirnov 112 , S.Yu. Smirnov 112 , Y. Smirnov 112 , L.N. Smirnova 113,r , O. Smirnova 97 , E.A. Smith 37 , H.A. Smith 134 , M. Smizanska 90 , K. Smolek 141 , A. Smykiewicz 85 , A.A. Snesarev 111 , H.L. Snoek 120 , I.M. Snyder131, S. Snyder29, R. Sobie176,z, A. Soffer161, A. Søgaard50, F. Sohns53, C.A. Solans Sanchez36, E.Yu. Soldatov112, U. Soldevila174, A.A. Solodkov123, A. Soloshenko80, O.V. Solovyanov123, V. Solovyev137, P. Sommer149, H. Son170, A. Sonay14, W. Song143, W.Y. Song168b, A. Sopczak141, A.L. Sopio95, F. Sopkova28b, S. Sottocornola71a,71b, R. Soualah67a,67c, A.M. Soukharev122b,122a, D. South46, S. Spagnolo68a,68b, M. Spalla115, M. Spangenberg178, F. Spanò94, D. Sperlich52, T.M. Spieker61a, G. Spigo36, M. Spina156, M. Spousta142, A. Stabile69a,69b, B.L. Stamas121, R. Stamen61a, M. Stamenkovic120, A. Stampekis 21 , E. Stanecka 85 , B. Stanislaus 134 , M.M. Stanitzki 46 , M. Stankaityte 134 , B. Stapf 120 , E.A. Starchenko123, G.H. Stark145, J. Stark58, P. Staroba140, P. Starovoitov61a, S. Stärz104, R. Staszewski85, G. Stavropoulos44, M. Stegler46, P. Steinberg29, A.L. Steinhebel131, B. Stelzer152,168a, H.J. Stelzer138, O. Stelzer-Chilton168a, H. Stenzel56, T.J. Stevenson156, G.A. Stewart36, M.C. Stockton36, G. Stoicea27b, M. Stolarski139a, S. Stonjek115, A. Straessner48, J. Strandberg154, S. Strandberg45a,45b, M. Strauss128, T. Strebler102, P. Strizenec28b, R. Ströhmer177, D.M. Strom131, R. Stroynowski42, A. Strubig45a,45b, S.A. Stucci29, B. Stugu17, J. Stupak128, N.A. Styles46, D. Su153, W. Su60d,148,60c, X. Su60a, N.B. Suarez138, V.V. Sulin111, M.J. Sullivan91, D.M.S. Sultan54, S. Sultansoy4c, T. Sumida86, S. Sun106, X. Sun101, C.J.E. Suster157, M.R. Sutton156, S. Suzuki82, M. Svatos140, M. Swiatlowski168a, S.P. Swift2, – 53 – JHEP06(2021)179 T. Swirski177, A. Sydorenko100, I. Sykora28a, M. Sykora142, T. Sykora142, D. Ta100, K. Tackmann46,w, J. Taenzer161, A. Taffard171, R. Tafirout168a, E. Tagiev123, R.H.M. Taibah135, R. Takashima87, K. Takeda83, T. Takeshita150, E.P. Takeva50, Y. Takubo82, M. Talby102, A.A. Talyshev122b,122a, K.C. Tam63b, N.M. Tamir161, J. Tanaka163, R. Tanaka65, S. Tapia Araya173, S. Tapprogge100, A. Tarek Abouelfadl Mohamed107, S. Tarem160, K. Tariq60b, G. Tarna27b,d, G.F. Tartarelli69a, P. Tas142, M. Tasevsky140, E. Tassi41b,41a, G. Tateno163, A. Tavares Delgado 139a , Y. Tayalati 35f , A.J. Taylor 50 , G.N. Taylor 105 , W. Taylor 168b , H. Teagle 91 , A.S. Tee 90 , R. Teixeira De Lima 153 , P. Teixeira-Dias 94 , H. Ten Kate 36 , J.J. Teoh 120 , K. Terashi 163 , J. Terron99, S. Terzo14, M. Testa51, R.J. Teuscher167,z, N. Themistokleous50, T. Theveneaux-Pelzer19, D.W. Thomas94, J.P. Thomas21, E.A. Thompson46, P.D. Thompson21, E. Thomson 136 , E.J. Thorpe 93 , V.O. Tikhomirov 111,af , Yu.A. Tikhonov 122b,122a , S. Timoshenko 112 , P. Tipton183, S. Tisserant102, K. Todome23b,23a, S. Todorova-Nova142, S. Todt48, J. Tojo88, S. Tokár28a, K. Tokushuku82, E. Tolley127, R. Tombs32, K.G. Tomiwa33f, M. Tomoto82,117, L. Tompkins153, P. Tornambe103, E. Torrence131, H. Torres48, E. Torró Pastor174, M. Toscani30, C. Tosciri134, J. Toth102,y, D.R. Tovey149, A. Traeet17, C.J. Treado125, T. Trefzger177, F. Tresoldi156, A. Tricoli29, I.M. Trigger168a, S. Trincaz-Duvoid135, D.A. Trischuk175, W. Trischuk167, B. Trocmé58, A. Trofymov65, C. Troncon69a, F. Trovato156, L. Truong33c, M. Trzebinski85, A. Trzupek85, F. Tsai46, P.V. Tsiareshka108,ad, A. Tsirigotis162,u, V. Tsiskaridze155, E.G. Tskhadadze159a, M. Tsopoulou162, I.I. Tsukerman124, V. Tsulaia18, S. Tsuno82, D. Tsybychev155, Y. Tu63b, A. Tudorache27b, V. Tudorache27b, A.N. Tuna36, S. Turchikhin80, D. Turgeman180, I. Turk Cakir4b,s, R.J. Turner21, R. Turra69a, P.M. Tuts39, S. Tzamarias 162 , E. Tzovara 100 , K. Uchida 163 , F. Ukegawa 169 , G. Unal 36 , M. Unal 11 , A. Undrus 29 , G. Unel171, F.C. Ungaro105, Y. Unno82, J. Urban28b, P. Urquijo105, G. Usai8, Z. Uysal12d, V. Vacek141, B. Vachon104, K.O.H. Vadla133, T. Vafeiadis36, A. Vaidya95, C. Valderanis114, E. Valdes Santurio45a,45b, M. Valente168a, S. Valentinetti23b,23a, A. Valero174, L. Valéry46, R.A. Vallance21, A. Vallier36, J.A. Valls Ferrer174, T.R. Van Daalen14, P. Van Gemmeren6, S. Van Stroud95, I. Van Vulpen120, M. Vanadia74a,74b, W. Vandelli36, M. Vandenbroucke144, E.R. Vandewall129, D. Vannicola73a,73b, R. Vari73a, E.W. Varnes7, C. Varni55b,55a, T. Varol158, D. Varouchas65, K.E. Varvell157, M.E. Vasile27b, G.A. Vasquez176, F. Vazeille38, D. Vazquez Furelos14, T. Vazquez Schroeder36, J. Veatch53, V. Vecchio101, M.J. Veen120, L.M. Veloce167, F. Veloso139a,139c, S. Veneziano73a, A. Ventura68a,68b, A. Verbytskyi115, V. Vercesi71a, M. Verducci72a,72b, C.M. Vergel Infante79, C. Vergis24, W. Verkerke120, A.T. Vermeulen120, J.C. Vermeulen120, C. Vernieri153, P.J. Verschuuren94, M.C. Vetterli152,aj, N. Viaux Maira146d, T. Vickey149, O.E. Vickey Boeriu149, G.H.A. Viehhauser134, L. Vigani61b, M. Villa23b,23a, M. Villaplana Perez174, E.M. Villhauer50, E. Vilucchi51, M.G. Vincter34, G.S. Virdee21, A. Vishwakarma50, C. Vittori23b,23a, I. Vivarelli156, M. Vogel182, P. Vokac141, J. Von Ahnen46, S.E. von Buddenbrock33f, E. Von Toerne24, V. Vorobel142, K. Vorobev112, M. Vos 174 , J.H. Vossebeld 91 , M. Vozak 101 , N. Vranjes 16 , M. Vranjes Milosavljevic 16 , V. Vrba 141,* , M. Vreeswijk120, N.K. Vu102, R. Vuillermet36, I. Vukotic37, S. Wada169, P. Wagner24, W. Wagner182, J. Wagner-Kuhr114, S. Wahdan182, H. Wahlberg89, R. Wakasa169, V.M. Walbrecht115, J. Walder143, R. Walker114, S.D. Walker94, W. Walkowiak151, V. Wallangen45a,45b, A.M. Wang59, A.Z. Wang181, C. Wang60a, C. Wang60c, H. Wang18, H. Wang3, J. Wang63a, P. Wang42, Q. Wang128, R.-J. Wang100, R. Wang60a, R. Wang6, S.M. Wang158, W.T. Wang60a, W. Wang15c, W.X. Wang60a, Y. Wang60a, Z. Wang106, C. Wanotayaroj46, A. Warburton104, C.P. Ward32, R.J. Ward21, N. Warrack57, A.T. Watson21, M.F. Watson21, G. Watts148, B.M. Waugh95, A.F. Webb11, C. Weber29, M.S. Weber20, S.M. Weber61a, Y. Wei134, A.R. Weidberg134, J. Weingarten47, M. Weirich100, C. Weiser52, P.S. Wells 36 , T. Wenaus 29 , B. Wendland 47 , T. Wengler 36 , S. Wenig 36 , N. Wermes 24 , M. Wessels 61a , – 54 – JHEP06(2021)179 T.D. Weston20, K. Whalen131, A.M. Wharton90, A.S. White106, A. White8, M.J. White1, D. Whiteson171, B.W. Whitmore90, W. Wiedenmann181, C. Wiel48, M. Wielers143, N. Wieseotte100, C. Wiglesworth40, L.A.M. Wiik-Fuchs52, H.G. Wilkens36, L.J. Wilkins94, D.M. Williams39, H.H. Williams136, S. Williams32, S. Willocq103, P.J. Windischhofer134, I. Wingerter-Seez 5 , E. Winkels 156 , F. Winklmeier 131 , B.T. Winter 52 , M. Wittgen 153 , M. Wobisch 96 , R. Wölker 134 , J. Wollrath 52 , M.W. Wolter 85 , H. Wolters 139a,139c , V.W.S. Wong 175 , A.F. Wongel 46 , N.L. Woods145, S.D. Worm46, B.K. Wosiek85, K.W. Woźniak85, K. Wraight57, S.L. Wu181, X. Wu54, Y. Wu60a, J. Wuerzinger134, T.R. Wyatt101, B.M. Wynne50, S. Xella40, J. Xiang63c, X. Xiao106, X. Xie60a, I. Xiotidis156, D. Xu15a, H. Xu60a, H. Xu60a, L. Xu29, R. Xu136, T. Xu144, W. Xu106, Y. Xu15b, Z. Xu60b, Z. Xu153, B. Yabsley157, S. Yacoob33a, D.P. Yallup95, N. Yamaguchi88, Y. Yamaguchi165, A. Yamamoto82, M. Yamatani163, T. Yamazaki163, Y. Yamazaki83, J. Yan60c, Z. Yan25, H.J. Yang60c,60d, H.T. Yang18, S. Yang60a, T. Yang63c, X. Yang60a, X. Yang60b,58, Y. Yang163, Z. Yang106,60a, W-M. Yao18, Y.C. Yap46, H. Ye15c, J. Ye42, S. Ye29, I. Yeletskikh80, M.R. Yexley90, E. Yigitbasi25, P. Yin39, K. Yorita179, K. Yoshihara79, C.J.S. Young36, C. Young153, J. Yu79, R. Yuan60b,h, X. Yue61a, M. Zaazoua35f, B. Zabinski85, G. Zacharis10, E. Zaffaroni54, J. Zahreddine135, A.M. Zaitsev123,ae, T. Zakareishvili159b, N. Zakharchuk34, S. Zambito36, D. Zanzi36, S.V. Zeißner47, C. Zeitnitz182, G. Zemaityte134, J.C. Zeng173, O. Zenin123, T. Ženiš28a, D. Zerwas65, M. Zgubič134, B. Zhang15c, D.F. Zhang15b, G. Zhang15b, J. Zhang6, K. Zhang15a, L. Zhang15c, L. Zhang60a, M. Zhang173, R. Zhang181, S. Zhang106, X. Zhang60c, X. Zhang60b, Y. Zhang15a,15d, Z. Zhang63a, Z. Zhang65, P. Zhao49, Y. Zhao145, Z. Zhao60a, A. Zhemchugov80, Z. Zheng106, D. Zhong173, B. Zhou106, C. Zhou181, H. Zhou7, M. Zhou155, N. Zhou60c, Y. Zhou7, C.G. Zhu60b, C. Zhu15a,15d, H.L. Zhu60a, H. Zhu15a, J. Zhu106, Y. Zhu60a, X. Zhuang15a, K. Zhukov111, V. Zhulanov122b,122a, D. Zieminska 66 , N.I. Zimine 80 , S. Zimmermann 52,* , Z. Zinonos 115 , M. Ziolkowski 151 , L. Živković 16 , G. Zobernig181, A. Zoccoli23b,23a, K. Zoch53, T.G. Zorbas149, R. Zou37, L. Zwalinski36 1Department of Physics, University of Adelaide, Adelaide; Australia 2Physics Department, SUNY Albany, Albany NY; United States of America 3Department of Physics, University of Alberta, Edmonton AB; Canada 4 (a)Department of Physics, Ankara University, Ankara;(b)Istanbul Aydin University, Application and Research Center for Advanced Studies, Istanbul;(c)Division of Physics, TOBB University of Economics and Technology, Ankara; Turkey 5LAPP, Univ. Savoie Mont Blanc, CNRS/IN2P3, Annecy; France 6 High Energy Physics Division, Argonne National Laboratory, Argonne IL; United States of America 7Department of Physics, University of Arizona, Tucson AZ; United States of America 8Department of Physics, University of Texas at Arlington, Arlington TX; United States of America 9Physics Department, National and Kapodistrian University of Athens, Athens; Greece 10 Physics Department, National Technical University of Athens, Zografou; Greece 11 Department of Physics, University of Texas at Austin, Austin TX; United States of America 12 (a)Bahcesehir University, Faculty of Engineering and Natural Sciences, Istanbul;(b)Istanbul Bilgi University, Faculty of Engineering and Natural Sciences, Istanbul; (c) Department of Physics, Bogazici University, Istanbul; (d) Department of Physics Engineering, Gaziantep University, Gaziantep; Turkey 13 Institute of Physics, Azerbaijan Academy of Sciences, Baku; Azerbaijan 14 Institut de Física d’Altes Energies (IFAE), Barcelona Institute of Science and Technology, Barcelona; Spain 15 (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 of Chinese Academy of Science (UCAS), Beijing; China 16 Institute of Physics, University of Belgrade, Belgrade; Serbia 17 Department for Physics and Technology, University of Bergen, Bergen; Norway – 55 – JHEP06(2021)179 18 Physics Division, Lawrence Berkeley National Laboratory and University of California, Berkeley CA; United States of America 19 Institut für Physik, Humboldt Universität zu Berlin, Berlin; Germany 20 Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics, University of Bern, Bern; Switzerland 21 School of Physics and Astronomy, University of Birmingham, Birmingham; United Kingdom 22 (a)Facultad de Ciencias y Centro de Investigaciónes, Universidad Antonio Nariño, Bogotá; (b) Departamento de Física, Universidad Nacional de Colombia, Bogotá, Colombia; Colombia 23 (a)INFN Bologna and Universita’ di Bologna, Dipartimento di Fisica;(b)INFN Sezione di Bologna; Italy 24 Physikalisches Institut, Universität Bonn, Bonn; Germany 25 Department of Physics, Boston University, Boston MA; United States of America 26 Department of Physics, Brandeis University, Waltham MA; United States of America 27 (a)Transilvania University of Brasov, Brasov;(b)Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest;(c)Department of Physics, Alexandru Ioan Cuza University of Iasi, Iasi;(d)National Institute for Research and Development of Isotopic and Molecular Technologies, Physics Department, Cluj-Napoca; (e) University Politehnica Bucharest, Bucharest; (f) West University in Timisoara, Timisoara; Romania 28 (a) Faculty of Mathematics, Physics and Informatics, Comenius University, Bratislava; (b) Department of Subnuclear Physics, Institute of Experimental Physics of the Slovak Academy of Sciences, Kosice; Slovak Republic 29 Physics Department, Brookhaven National Laboratory, Upton NY; United States of America 30 Departamento de Física, Universidad de Buenos Aires, Buenos Aires; Argentina 31 California State University, CA; United States of America 32 Cavendish Laboratory, University of Cambridge, Cambridge; United Kingdom 33 (a)Department of Physics, University of Cape Town, Cape Town;(b)iThemba Labs, Western Cape;(c)Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg; (d) National Institute of Physics, University of the Philippines Diliman; (e) University of South Africa, Department of Physics, Pretoria; (f) School of Physics, University of the Witwatersrand, Johannesburg; South Africa 34 Department of Physics, Carleton University, Ottawa ON; Canada 35 (a)Faculté des Sciences Ain Chock, Réseau Universitaire de Physique des Hautes Energies - Université Hassan II, Casablanca; (b) Faculté des Sciences, Université Ibn-Tofail, Kénitra; (c) Faculté des Sciences Semlalia, Université Cadi Ayyad, LPHEA-Marrakech; (d) Moroccan Foundation for Advanced Science Innovation and Research (MAScIR), Rabat;(e)LPMR, Faculté des Sciences, Université Mohamed Premier, Oujda;(f)Faculté des sciences, Université Mohammed V, Rabat; Morocco 36 CERN, Geneva; Switzerland 37 Enrico Fermi Institute, University of Chicago, Chicago IL; United States of America 38 LPC, Université Clermont Auvergne, CNRS/IN2P3, Clermont-Ferrand; France 39 Nevis Laboratory, Columbia University, Irvington NY; United States of America 40 Niels Bohr Institute, University of Copenhagen, Copenhagen; Denmark 41 (a)Dipartimento di Fisica, Università della Calabria, Rende;(b)INFN Gruppo Collegato di Cosenza, Laboratori Nazionali di Frascati; Italy 42 Physics Department, Southern Methodist University, Dallas TX; United States of America 43 Physics Department, University of Texas at Dallas, Richardson TX; United States of America 44 National Centre for Scientific Research “Demokritos”, Agia Paraskevi; Greece 45 (a)Department of Physics, Stockholm University;(b)Oskar Klein Centre, Stockholm; Sweden 46 Deutsches Elektronen-Synchrotron DESY, Hamburg and Zeuthen; Germany 47 Lehrstuhl für Experimentelle Physik IV, Technische Universität Dortmund, Dortmund; Germany 48 Institut für Kernund Teilchenphysik, Technische Universität Dresden, Dresden; Germany 49 Department of Physics, Duke University, Durham NC; United States of America 50 SUPA - School of Physics and Astronomy, University of Edinburgh, Edinburgh; United Kingdom – 56 –