Published for SISSA by Springer Received: December 28, 2018 Revised: April 1, 2019 Accepted: April 22, 2019 Published: May 7, 2019 Search for large missing transverse momentum in JHEP05(2019)041 association with one top-quark in proton–proton √ collisions at s = 13 TeV with the ATLAS detector The ATLAS collaboration E-mail: atlas.publications@cern.ch Abstract: This paper describes a search for events with one top-quark and large missing transverse momentum in the final state. Data collected during 2015 and 2016 by the ATLAS experiment from 13 TeV proton–proton collisions at the LHC corresponding to an integrated luminosity of 36.1 fb−1 are used. Two channels are considered, depending on the leptonic or the hadronic decays of the W boson from the top quark. The obtained results are interpreted in the context of simplified models for dark-matter production and for the single production of a vector-like T quark. In the absence of significant deviations from the Standard Model background expectation, 95% confidence-level upper limits on the corresponding production cross-sections are obtained and these limits are translated into constraints on the parameter space of the models considered. Keywords: Beyond Standard Model, Dark matter, FCNC Interaction, Hadron-Hadron scattering (experiments), vector-like quarks ArXiv ePrint: 1812.09743 Open Access, Copyright CERN, https://doi.org/10.1007/JHEP05(2019)041 for the benefit of the ATLAS Collaboration. Article funded by SCOAP3 . Contents 1 Introduction 1 2 Signal phenomenology 3 2.1 DM candidates associated with top-quarks 3 2.2 Single production of vector-like T quarks 4 3 ATLAS detector 5 JHEP05(2019)041 4 Data and simulation samples 5 5 Event reconstruction and object selection 7 6 Event selection and background estimation 9 6.1 Signal region definition 10 6.2 Background estimation 11 7 Systematic uncertainties 13 8 Results 15 9 Conclusions 22 A Event yields in the signal and control regions after the fit to data 23 The ATLAS collaboration 33 1 Introduction In spite of its successes in describing the phenomenology of the fundamental particles and the corresponding interactions, the Standard Model (SM) can be considered as a low-energy approximation of a more fundamental theory with new degrees of freedom and symmetries that would become manifest at a higher energy. One argument supporting the idea that new particles beyond the SM might exist arises from astrophysical measurements, such as the rotational speed of stars in galaxies and gravitational lensing [1–3]. These observations point to the existence of non-light-emitting matter, a dominant fraction of which is of non-baryonic form, usually referred to as dark matter (DM). Even if there are no viable candidates in the SM for particles which could explain DM, proton–proton collisions at the Large Hadron Collider (LHC) may possibly produce new particles that couple both to SM particles and to these DM candidates. While such candidates are not expected to interact significantly with detectors, the SM particles –1– produced in association with the unobserved DM particles could allow these processes to be detected. Search strategies depend on the type of particle or system that is recoiling against the unseen particle. Both ATLAS and CMS have carried out searches for invisible particles produced in association with jets [4–7], photons [8, 9], W or Z bosons [5, 10, 11] and Higgs bosons [12–15], significantly constraining the allowed parameter space for different classes of models predicting DM candidates. This paper describes a search for the production of invisible particles in association with a single top-quark in proton–proton collisions produced at the LHC with a centre-of- √ mass energy of s = 13 TeV and detected using the ATLAS detector. Such a final state, commonly referred to as “mono-top”, is characterised by a top-quark and significant missing JHEP05(2019)041 transverse momentum, which is due to the undetected particles. Background contributions from SM processes [16] are expected to be small. In addition, this search is sensitive to specific DM models, since the presence of top-quarks in the final state constrains the flavour structure of the considered couplings [17, 18]. Similar searches were previously conducted √ by the CDF Collaboration using 7.7 fb−1 of Tevatron pp̄ collisions at s = 1.96 TeV [19] and √ √ by the ATLAS and CMS collaborations using s = 8 TeV [20, 21] and s = 13 TeV [22] LHC data. Searches for new phenomena in events with same-charge leptons and b-tagged jets [23] provide information complementary to the results from mono-top searches and exclude new vector resonances with masses up to 3 TeV, assuming a dark-sector coupling of 1.0 and a coupling to SM particles above 0.3. A final state with a top-quark and missing transverse momentum can also originate from the single production of new vector-like quarks if these decay into a top-quark and a Z boson that decays invisibly into two neutrinos. Vector-like quarks are colour-triplet spin-1/2 fermions in which, in contrast to the SM quarks, the left- and right-handed components have the same properties under transformations of the electroweak symme- try group SU(2)L × U(1)Y . Such new particles are predicted in SM extensions, such as Little Higgs [24, 25] and Composite Higgs [26, 27] models, and are expected to mix with SM quarks [28]. In order to preserve gauge invariance, only a limited set of possible rep- resentations exist [29, 30] and their electric charge can be +2/3e (T quark), −1/3e (B quark), +5/3e (X quark) or −4/3e (Y quark), with e being the elementary charge. In this paper, only the single production of vector-like T quarks (VLT) via an electroweak interaction is considered. Although couplings of T quarks to first- and second-generation SM quarks are not excluded [31, 32], it is common to assume that they couple exclusively to third-generation SM quarks [33]. Such couplings can be described in terms of sin θL [34], where θL is the mixing angle of the T quark with the top-quark, or in terms of a gener- alised coupling κT [35, 36]. The T quarks can decay either via the charged current, i.e. T → W b, or via flavour-changing neutral currents [37], i.e. T → Zt and T → Ht. The T → Zt → ν ν̄W b decay is considered in the present search. The ATLAS and CMS collaborations have sought pair production of T quarks decaying into third-generation quarks in pp collisions at a centre-of-mass energy of 8 TeV [38–41], targeting all three possible decay modes. Searches at 13 TeV have aimed at final states with leptons, targeting the T → Zt decay [42, 43], the T → W b decay [44, 45], as well as general single-lepton and fully hadronic final states with boosted bosons [46, 47] and multiple b- –2– tagged jets [46, 48, 49]. The most stringent mass limit for an isospin singlet T is 1.3 TeV [50]. For such large T masses, the cross-section for single T production may be larger than the pair-production cross-section because of the larger available phase space. Nonetheless, the comparison of single- and pair-production cross-sections depends on the assumed coupling to the SM quarks. Single production of T quarks was sought at 8 TeV [40, 51, 52] by the ATLAS Collaboration. At 13 TeV, the ATLAS and CMS collaborations have sought the decays T → W b [53, 54], T → Ht [55, 56] and T → Zt [43, 57, 58]. In this paper, two channels for the mono-top signature are considered, targeting the case in which the W boson originating from the top-quark decays into an electron or muon and a neutrino (leptonic channel) and the case in which it decays into a pair of quarks JHEP05(2019)041 (hadronic channel). These analyses define different signal regions, maximising the signal discovery sensitivity, and control regions, enriched with the dominant background pro- cesses. The statistical interpretation of the results is based on a simultaneous fit to the signal and control regions to determine a possible signal contribution and constrain the main backgrounds with data, taking into account experimental and theoretical system- atic uncertainties. The paper is organised as follows. The signal models are introduced in section 2. After a brief introduction to the ATLAS detector, given in section 3, the data samples and sam- ples of simulated signal and background events are described in section 4. The algorithms for the reconstruction and identification of final-state particles are summarised in section 5. Section 6 describes the criteria for the selection of candidate signal events. This section also describes the estimation of the background contribution with the help of dedicated control regions in data. The experimental and theoretical systematic uncertainties (section 7) are taken into account in the statistical interpretation of data, with the results presented in section 8. Concluding remarks are given in section 9. 2 Signal phenomenology This paper presents a search for two different signals: DM candidates produced in as- sociation with top-quarks and single production of vector-like T quarks decaying into a top-quark and a Z boson. 2.1 DM candidates associated with top-quarks In this search the resonant and non-resonant production of DM particles associated with a top-quark are considered. The non-resonant case, represented in figure 1(a) and figure 1(b), corresponds to a flavour-changing neutral-current interaction, producing a top-quark and a new vector particle V , which in turn decays invisibly into a pair of DM particles. Such a process can be parameterised through a general Lagrangian [16, 59]: Lint = aVµ ūγ µ PR t + gχ Vµ χ̄γ µ χ + h.c. , where a massive vector boson V is coupled to a DM particle (represented by a Dirac fermion χ) with a strength controlled by the parameter gχ . The term PR is the right- handed chirality projector. The parameter a stands for the coupling constant between the –3– χ χ u V χ̄ u q, νℓ V χ̄ q, νℓ t u + W W+ q̄ ′, ℓ+ t q̄ ′, ℓ+ t g g b b (a) (b) JHEP05(2019)041 q′ q χ d ν̄ W Z q, νℓ T ν φ t W + b b t q̄ ′, ℓ+ q, νℓ W+ q̄ ′, ℓ+ s g b b̄ (c) (d) Figure 1. Representative leading-order diagrams corresponding to the signals sought in this paper: non-resonant (a) t-channel and (b) s-channel production of a top-quark in association with a vector boson V which decays into two DM particles; (c) resonant production of a coloured scalar φ that decays into a DM particle and a top-quark; and (d) single production of a vector-like T quark decaying into Zt (→ ν ν̄bW ). massive vector boson V and the t- and u-quarks, and γ µ are the Dirac matrices. Another possibility is the resonant case, corresponding to the production of a coloured charge-2/3 scalar (φ) decaying into a top-quark and a spin-1/2 DM particle (χ) [60]. This process, represented in figure 1(c), is described by the following Lagrangian [16, 59]: Lint = λφd¯c PR s + yφχ̄PR t + h.c. , where the parameters λ and y represent the couplings of the charged scalar to the d- and s-quarks and to the top-quark and the DM particle χ, respectively. 2.2 Single production of vector-like T quarks The single production of T quarks can occur via a charged W T b or a neutral ZT t vertex. However, ZT t production is suppressed because of the required top quark in the initial state. For this reason, ZT t production is not considered in this analysis and single VLT production refers to T production via the W T b vertex throughout this paper. The T quarks can decay into bW , tH and tZ, with the corresponding branching ratios (B) depending on the specific model considered [33, 36]. The specific case of single production of vector-like T quarks decaying into tZ, followed by the Z boson decaying into neutrinos, results in a mono-top signature. As can be seen in –4– figure 1(d), one important difference between DM production and vector-like T -quark pro- duction is the presence of additional quarks in the single production of T quarks, which will lead to at least one jet being detected at a small angle relative to the beam line. Similarly to the DM case, the topology of the VLT signal has a distinctive signature, characterised by the presence of a top-quark and missing transverse momentum, arising from the Z → ν ν̄ decay (and from the t → bW → `ν decay in the single-lepton channel case). 3 ATLAS detector JHEP05(2019)041 The ATLAS experiment [61] at the LHC is a multipurpose particle detector with nearly 4π coverage around the collision point.1 It consists of an inner tracking detector surrounded by a thin superconducting solenoid providing a 2 T axial magnetic field, electromagnetic and hadron calorimeters, and a muon spectrometer. The inner tracking detector covers the pseudorapidity range |η| < 2.5. It consists of a silicon pixel detector, including the in- sertable B-layer [62, 63] installed after Run 1 of the LHC, a silicon microstrip detector, and a transition-radiation tracking detector. Lead/liquid-argon (LAr) sampling calorimeters provide electromagnetic (EM) energy measurements with high granularity for |η| < 3.2. A steel/scintillator-tile hadron calorimeter covers the central pseudorapidity range (|η| < 1.7). The endcap and forward regions are instrumented with LAr calorimeters for both the EM and hadronic energy measurements up to |η| = 4.9. The outer part of the detector in- cludes a muon spectrometer with high-precision tracking chambers providing coverage up to |η| = 2.7, fast detectors for triggering over |η| < 2.4, and three large air-core toroidal superconducting magnets with eight coils each. A two-level trigger system [64], using cus- tom hardware followed by a software-based trigger level, is used to select events of interest at an average rate of 1 kHz. 4 Data and simulation samples This analysis is performed using pp collision data recorded at a centre-of-mass energy of √ s = 13 TeV with the ATLAS detector during 2015 and 2016 in the periods when the LHC was operating with 25 ns bunch spacing and with an average number of collisions per bunch crossing hµi of around 23. Only periods in which all detector components necessary for this analysis were functional are considered, resulting in a data sample with a total integrated luminosity of 36.1 fb−1 . In the single-lepton channel, events are required to pass at least one of the single-muon or single-electron triggers [64]. The triggers require a pT of at least 20 GeV (26 GeV) for muons and 24 GeV (26 GeV) for electrons for the 2015 (2016) data sets, and also have requirements on lepton reconstruction and isolation. These are complemented by triggers 1 ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP) in the centre of the detector and the z-axis along the beam pipe. The x-axis points from the IP to the centre of the LHC ring, and the y-axis points upwards. Cylindrical coordinates (r, φ) are used in the transverse plane, φ being the azimuthal angle around the z-axis. The pseudorapidity is pdefined in terms of the polar angle θ as η = − ln tan(θ/2). Angular distance is measured in units of ∆R ≡ (∆η)2 + (∆φ)2 . –5– with higher pT thresholds and relaxed isolation and identification requirements to ensure maximum efficiency at higher lepton pT . In the hadronic channel, events are considered if they are accepted by triggers that select events with high missing transverse momentum, with online thresholds of 70 GeV in 2015 and 90 GeV to 110 GeV in 2016. For all signal and background processes of interest, Monte Carlo (MC) events were simulated. Signal events for both the resonant and non-resonant DM scenarios were gener- ated according to a simplified model [65] described in section 1, implemented in Mad- Graph5 aMC@NLOv2.3.2 [66] through FeynRules 2.0 [67, 68]. Such generation was done at leading order (LO) using the NNPDF3.0LO [69] parton distribution function (PDF) JHEP05(2019)041 set. Parton showering, hadronisation and underlying-event modelling were handled using the Pythia 8.212 [70] event generator with the A14 [71] set of tuned parameters, using the NNPDF2.3LO PDF set [72]. Signal samples for the resonant model were generated assuming a DM mass of mχ = 10 GeV and a range of the new scalar masses, mφ , between 1 TeV and 5 TeV, representing two different kinematic regimes. The kinematic distribu- tions predicted by the model have only a small dependence on the coupling parameters and therefore all samples were generated using a coupling constant of λ = 0.2 and a mixing parameter of y = 0.4. The remaining kinematic dependence on the different couplings and masses was accounted for by means of a reweighting procedure (see section 8 for details). Similarly, the signal samples for the non-resonant model were generated for values of mV between 500 GeV and 3 TeV, corresponding to the expected sensitivity of the analysis, and a benchmark DM mass mχ = 1 GeV. The values of the couplings were set to a = 0.5 and gχ = 1.0. The kinematic effect of changing the coupling values was taken into account by using the previously mentioned reweighting procedure. The samples were normalised to the theoretical LO cross-sections, computed with MadGraph5 aMC@NLO. The single production of T quarks was generated using the Feynrules 2.0 implementa- tion of a general model [35] interfaced to MadGraph5 aMC@NLOv2.3.2. The NNPDF2.3 LO PDF set and Pythia 8.212 with the A14 set of tuned parameters were used. Since the current analysis targets a final state with large missing transverse momentum, only the T → Zt decay, with Z decaying invisibly, was considered, as represented in figure 1(d). Samples were generated for T masses in the range from 700 to 2000 GeV with a benchmark coupling of κT = 0.5 in the W T b production vertex. Additional samples were gener- ated with alternative values of κT = 0.1 and 1.0 in order to study the effect of a varying T -quark width on kinematic distributions. The samples were normalised to the next- to-leading-order (NLO) cross-section by correcting the LO cross-sections calculated with MadGraph5 aMC@NLO for the difference between the NLO and LO cross-sections re- ported for the neutral single-T production process via a ZT t coupling [36]. For large values of the coupling the narrow-width approximation used in the cross-section calculation does not apply, so the cross-sections were corrected to include width effects, using a reweighting procedure similar to that previously mentioned, in order to account for the corresponding kinematic effects. For the background samples, several matrix element (ME) event generators were com- bined with parton shower and hadronisation programs. Powheg-Box v2 [73–79] interfaced –6– to Pythia 8.210 using the A14 set of tuned parameters was used to simulate tt̄ production at NLO. Single top production was generated at NLO with Powheg-Box v1 for the t-, W t- and s-channels and at LO with MadGraph5 aMC@NLO for the tZq process, in- terfaced to Pythia 6.428 [80]. The CTEQ6L1 PDF set [81] and the Perugia 2012 set of tuned parameters [82] were used in the parton shower, hadronisation, and underlying-event simulation. The CT10f4 (CT10) PDF set [83] was used in the matrix element calculations for the t-channel (W t- and s- channels). To model the W + jets and Z + jets background the Sherpa v2.2.1 [84] generator was used. Matrix elements were calculated for up to two partons at NLO and up to four partons at LO using the Comix [85] and Open- Loops [86] ME generators, and merged with the Sherpa parton shower [87] according to JHEP05(2019)041 the ME+PS@NLO prescription [88]. The NNPDF3.0 next-to-NLO (NNLO) PDF set [89] was used in conjunction with a Sherpa parton shower tuning from the authors. Diboson processes were simulated with Powheg-Box v2 interfaced to Pythia 8.186. The CT10nlo PDF set was used for the hard process while the CTEQ6L1 PDF set was used for the parton shower. For the simulation of tt̄ events with additional bosons tt̄ + X (X = W , Z, Higgs), MadGraph5 aMC@NLO v2.3.2 interfaced to Pythia 8.186 was used at NLO in QCD. Non-perturbative effects were modelled with the AZNLO set of tuned parameters [90]. The considered cross-sections for the dominant backgrounds, tt̄ and W /Z + jets, were evaluated at NNLO in quantum chromodynamics (QCD) [91, 92]. The calculation for tt̄ also includes next-to-next-to-leading logarithmic soft gluon terms. The EvtGen v1.2.0 program [93] was used to simulate properties of the bottom and charmed hadron decays except for samples generated with Sherpa. All simulated samples except the DM non-resonant signal in the leptonic channel and tt̄ + X processes were pro- cessed with the full simulation of the ATLAS detector [94] using Geant4 [95]. Additional samples used in the estimation of systematic uncertainties were instead produced using Atlfast2 [96], in which a parameterised detector simulation was used for the calorimeter responses. This simulation was also used for the generation of the DM non-resonant signal in the leptonic channel and tt̄ + X processes. All samples were simulated with a varying number of minimum-bias interactions generated with Pythia 8.186 using the A2 set of tuned parameters [97], overlaid on the hard-scattering event to account for the multiple pp interactions in the same or nearby bunch crossings (pile-up). Simulated events were corrected using per-event weights to describe the distribution of the average number of interactions per proton bunch-crossing as observed in data. 5 Event reconstruction and object selection Events are required to have at least one vertex candidate with at least two tracks with pT > 400 MeV. The primary vertex is taken to be the vertex candidate with the largest sum of squared transverse momenta of all associated tracks. Electron candidates are reconstructed from an isolated electromagnetic calorimeter energy deposit matched to a track in the inner detector passing tight likelihood-based re- quirements [98]. They are required to have a transverse energy ET > 30 GeV and pseudora- pidity |η| < 2.47, with the transition region between the barrel and endcap electromagnetic –7– calorimeters, 1.37 < |η| < 1.52, excluded. Electron candidates must have a track satisfying requirements of |d0 |/σd0 < 5 for the transverse impact parameter significance relative to the beamline and |∆z0 sin θ| < 0.5 mm for the longitudinal impact parameter calculated relative to the primary vertex. Furthermore, electrons must satisfy isolation requirements based on inner detector tracks and topological clusters in the calorimeter [99], with an isolation efficiency of 90% (99%) for electrons from Z → ee decays with pT = 25(60) GeV. Correc- tion factors are applied to simulated electrons to take into account the small differences in reconstruction, identification, and isolation efficiencies between data and MC simulation. Muon candidates are reconstructed by combining tracks reconstructed in the inner JHEP05(2019)041 detector with matching tracks reconstructed in the muon spectrometer, and are required to satisfy pT > 30 GeV and |η| < 2.5 [100]. Muon candidates must satisfy requirements of |d0 |/σd0 < 3 and |∆z0 sin θ| < 0.5 mm for the transverse impact parameter significance and the longitudinal impact parameter, respectively. An isolation requirement based on inner detector tracks and topological clusters in the calorimeters is imposed, which achieves an isolation efficiency of 90% (99%) for muons from Z → µµ decays with pT = 25(60) GeV. Similarly to electrons, correction factors are applied to muons to account for the small differences between data and simulation [100]. Jets are reconstructed from topological clusters of energy deposited in the calorime- ter [99] using the anti-kt algorithm [101] with a radius parameter of 0.4 (1.0) for small-R (large-R) jets, as implemented in the FastJet package [102]. Small-R jets are calibrated using an energy- and η-dependent simulation-based calibra- tion scheme with corrections derived from data [103]. Jets are accepted within the fiducial region |η| < 2.5 and pT > 30 GeV (pT > 25 GeV) for the leptonic (hadronic) analysis. In the hadronic channel this threshold has been relaxed to increase forward-jet acceptance. Forward jets in the region 2.5 < |η| < 4.5 are also considered in the vector-like T -quark search analysis. Quality criteria are imposed to reject events that contain any jets arising from non-collision sources or detector noise [104]. To reduce the contribution from jets associated with pile-up, jets with pT < 60 GeV and |η| < 2.4 must satisfy a criterion that matches them to the hard-scatter vertex using information from tracks reconstructed in the inner tracking detector [105]. To prevent double q counting of electron energy deposits as small-R jets, the closest jet with distance ∆Ry,φ ≡ (∆y)2 + (∆φ)2 < 0.2 from a reconstructed electron is removed. If the nearest surviving jet is within ∆Ry,φ = 0.4 of the electron, the electron is discarded to ensure it is sufficiently separated from nearby jet activity. Jets with fewer than three tracks and distance ∆Ry,φ < 0.2 from a muon are removed to reduce the number of jet fakes from muons depositing energy in the calorimeters. Muons with a distance ∆Ry,φ < 0.4 from any of the surviving jets are removed to avoid contamination due to non-prompt muons from heavy-flavour hadron decays. Large-R jets are trimmed [106] to mitigate the impact of initial-state radiation, underlying-event activity and pile-up. The jet energy and pseudorapidity are further cal- ibrated to account for residual detector effects using energy- and η-dependent calibration factors derived from simulation, with uncertainties derived from data [107]. Trimmed large- –8– R jets are considered if they fulfil pT > 250 GeV and |η| < 2.0. To identify large-R jets that are more likely to have originated from hadronically decaying top-quarks than from the fragmentation of other quarks and gluons, jet substructure information is exploited. In the trimming procedure, sub-jets, with radius Rsub = 0.2, are clustered starting from the large-R jet constituents using a kt algorithm. A sub-jet is retained only if it contains at least 5% of the total large-R jet transverse momentum, thereby removing the soft constituents from the large-R jet. A top-tagging algorithm [108] is applied, corre- sponding to a loose working point with an approximately constant top-tagging efficiency of 80% above pT of 400 GeV. The algorithm depends on the calibrated jet mass, measured from clusters in the calorimeter, and the N -subjetiness ratio τ32 [109]. The N -subjetiness JHEP05(2019)041 τN [109] expresses how well a jet can be described as containing N or fewer sub-jets. The ratio τ32 = τ3 /τ2 allows discrimination between jets containing a three-prong structure and jets containing a two-prong structure. In addition to calorimeter-based jets, jets reconstructed from inner detector tracks using the anti-kt algorithm with a radius parameter of 0.2 are also used in the hadronic channel, following a similar strategy as in [110]. They are referred to as track-based jets and are required to satisfy pT > 10 GeV and |η| < 2.5. Small-R calorimeter-based and track-based jets with |η| < 2.5 are b-tagged as likely to contain b-hadrons using multivariate techniques which exploit the long lifetime of b-hadrons and large invariant mass of their decay products relative to c- and light hadrons [111, 112]. The working point used provides an average tagging efficiency of 70% for b-jets and a rejection factor of 12.2 (7.1) against calorimeter-based (track-based) jets initiated by c- quarks and 381 (120) against calorimeter-based (track-based) jets initiated by light-flavour quarks, in simulated tt̄ events. Correction factors are derived and applied to correct for the small differences in b-quark selection efficiency between data and MC simulation [111, 113, 114]. The missing transverse momentum is calculated as the negative vector sum of the transverse momenta of particles in the event, and its magnitude is denoted ET miss . In addi- tion to the identified jets, electrons, muons, hadronically decaying τ -leptons and photons, a track-based soft term is included in the ETmiss calculation by considering tracks associated with the hard-scattering vertex in the event which are not also associated with an identified jet, electron, muon, hadronically decaying τ -lepton, or photon [115, 116]. 6 Event selection and background estimation The experimental signature of mono-top events expected in the DM (resonant and non- resonant) and vector-like T -quark models considered is the presence of a top-quark and significant missing transverse momentum, as seen in section 2. For the case of single VLT production, at least one additional forward jet is also expected. The leptonic channel is only considered in order to target the non-resonant DM model. In this model, the u-quark-initiated production of top-quarks is favoured over anti-top- quark production, due to the PDF structure of the proton. Therefore, positively charged leptons are favoured in the final state. Events that pass preselection are required to contain –9– exactly one positively charged lepton and one b-tagged jet with pT > 30 GeV. In order to reduce the number of multijet background events, which are characterised by low ET miss and low W boson transverse mass2 mW T , it is also required that ET miss > 50 GeV and W miss mT + ET > 60 GeV. In the hadronic channel, because of the large expected Lorentz boost of the top-quarks produced in the signal events, the top-quark decay products can be collimated into a large-R jet. This signature is used in both the non-resonant and resonant DM models and the VLT models. Preselected events are then required to contain zero leptons, one large-R jet with pT > 250 GeV and |η| < 2.0. In order to suppress the multijet background contribution, miss > 200 GeV is also required. JHEP05(2019)041 ET 6.1 Signal region definition The signal region selection is optimised for the different considered benchmarks with sim- ulated data, using variables tested and found to be well-modelled. In the optimisation the sensitivity is estimated by performing a fit to the shape of the most discriminating observ- able including systematic uncertainties (see section 8 for details). These observables are ETmiss in the leptonic channel and the transverse mass of the top-tagged large-R jet (J) and the ET miss system, m (E miss , J)3 , in the hadronic channel. For the tested mass hypothesis, T T the resulting best-performing selections lead to three signal regions: 1L-DM-SR for the non-resonant DM search in the leptonic channel and 0L-DM-SR and 0L-VLT-SR targeting the search in the hadronic channel for DM and VLT quarks, respectively. In the leptonic channel, the mono-top signal is enhanced in regions of phase space characterised by high mW T values. In addition, the lepton and b-tagged jet are closer to each other when originating from the decay of a top-quark than in the case of W + jets and multijet background events. Hence, in addition to the preselection described previously, the region 1L-DM-SR is defined by requiring mW T > 260 GeV and |∆φ(`, b)| < 1.2. In the hadronic channel, events in 0L-DM-SR and 0L-VLT-SR are required to contain exactly one top-tagged large-R jet with pT > 250 GeV and one b-tagged track-based jet, in addition to the preselection criteria. The distance between the top-tagged large-R jet and the ET miss in the transverse plane, ∆Φ(E miss , J), is required to fulfil ∆Φ(E miss , J) ≥ π/2 T T since for signal events they are more likely to be produced back-to-back. In order to suppress background events due to fake ET miss mostly coming from jet mis-reconstruction in multijet production, the asymmetry between ET miss and the p of the top-tagged large- T miss miss R jet defined as Ω = (ET − pT (J))/(ET + pT (J)) is required to be Ω > −0.3. The multijet background is additionally suppressed by requiring the minimum distance between 2 miss p The transverse mass of the lepton and ET system is defined as mW T = miss miss 2pT (`)ET (1 − cos ∆φ(pT (`), ET )), where pT (`) denotes the modulus of the lepton transverse miss momentum, and ∆φ(pT (`), ET ) the azimuthal angle between the missing transverse momentum and the lepton directions. 3 miss miss q The transverse mass of the large-R jet and ET is defined as mT (ET , J) = miss miss m(J)2 + 2ET · ET(J) − pT (J) cos(Φ(J) − Φ(ET )) , where mT (J) is the reconstructed invariant mass of the calibrated calorimeter-cluster constituents of a large-R jet and ET (J) is the projection of its energy in the transverse plane. – 10 – miss and any small-R jet in the transverse plane to be ∆Φ the ET min > 1.0. The signal region 0L-VLT-SR is defined by requiring in addition at least one forward jet with pT > 25 GeV. The signal region requirements are summarised in table 1. 6.2 Background estimation Dedicated control regions enriched in the dominant backgrounds are included in the fit to constrain these backgrounds with data. Multijet production background is estimated from data, while the rest of background processes are taken from simulation. The dominant background in the signal regions is due to tt̄ production in both channels, representing 78% of the total background in the leptonic and 55% (64%) in the DM (VLT) JHEP05(2019)041 hadronic channels. This is followed by contributions from W + jets (13%) and single top production (6.8%) in the leptonic channel and from W + jets and Z + jets production, at the level of 12% (13%) for W + jets and 14% (15%) for Z + jets in the DM (VLT) signal regions, in the hadronic channel. A minor background in the signal region with a non-negligible contribution in the control regions is multijet production. The rest of the backgrounds considered in the analysis are diboson production as well as tt̄ production in association with a Z, W or Higgs boson. The estimation of the multijet background is in particularly important in the control regions used to estimate the main backgrounds. In the leptonic channel the multijet back- ground originates from either misidentification of a jet as a lepton candidate (fake lepton) or from the presence of a non-prompt lepton (e.g., from a semileptonic b- or c-hadron decay) that passes the isolation requirement. The shape and the normalisation of the rel- evant distributions in multijet events and related systematic uncertainties are estimated using a matrix method in the electron channel and the anti-muon method in the muon channel [117]. The matrix method exploits differences in efficiencies to pass loose or tight quality requirements [98] between prompt leptons, obtained from W and Z decays, and non-prompt or fake lepton candidates, from the misidentification of photons or jets. These efficiencies are measured in dedicated control regions. The prompt lepton efficiencies are measured as a function of the pT of the leading jet and the angular distance between the lepton and its nearest jet, while the non-prompt or fake efficiencies are parameterised in terms of the pT of the leading jet, the angle in the transverse plane between the lepton and the ET miss and the b-tagged jet multiplicity. Multijet background events containing non- prompt muons are modelled with the anti-muon method using a sample of events enriched in non-isolated muons [117]. Most of these events originate from b- or c-hadron decays in jets. These events pass the kinematic requirements of the selections described in section 5. Only some of the muon identification criteria are modified, ensuring there is no overlap with the signal selection. The normalisation is determined using a binned maximum-likelihood fit to the number of events observed in data in a control region dominated by multijet events. This region is defined with the preselection criteria, but removing the requirement on ET miss and requiring mW < 60 GeV. T In the hadronic channel the estimation of the multijet background is performed using a set of control regions (B,C and D) dominated by multijet background and defined to be orthogonal to the considered signal region (0L-DM-SR or 0L-VLT-SR). The shape of the – 11 – Selections (leptonic channel) 1L-DM-SR 1L-TCR 1L-WCR Number of leptons =1 =1 =1 pT (`) [GeV] > 30 > 30 > 30 Lepton charge >0 >0 >0 Number of jets =1 =2 =1 Number of b-tagged jets =1 =2 =1 pT (b-tagged jet) [GeV] > 30 > 30 > 30 miss [GeV] ET > 50 > 50 > 50 mW T + ET miss [GeV] > 60 > 60 > 60 W mT [GeV] > 260 60 < mW < 100 60 < mW T < 100 JHEP05(2019)041 T |∆φ(`, b)| < 1.2 — — Selections (hadronic channel) 0L-DM-SR 0L-VLT-SR 0L-TCR 0L-VCR Number of forward jets =0 ≥1 — — Number of leptons =0 =0 =0 miss [GeV] ET > 200 > 200 > 200 Number of large-R jets ≥1 ≥1 ≥1 Number of top-tagged jets ≥1 ≥1 ≥1 miss , J) π π π ∆Φ(ET > 2 > 2 > 2 Number of track-jets ≥1 ≥1 ≥1 Number of b-tagged track-jets =1 ≥2 =0 Veto jet (masked tile-calo) — applied — E miss −p (J) Ω = ETmiss +pT (J) > −0.3 > −0.3 > –0.3 T T ∆Φmin (ET miss , calo jets) > 1.0 0.2 < ∆Φmin < 1.0 > 1.0 Table 1. Overview of the event selections used to define the signal and control regions. multijet background is estimated from the control region B, which differs from the signal region by requiring zero top-tagged large-R jets. This shape is normalised by a factor which is calculated as the ratio of the numbers of multijet events in regions C and D. Region C (region D) differs from the signal region (B region) by requiring ∆Φ(ET miss , J) < π/2. In regions B and D, with zero top-tagged large-R jets, J is a large-R jet chosen ran- domly from the selected large-R jets. The multijet contribution in these control regions is determined from the difference between data and the residual contribution of other back- ground processes evaluated from simulation assuming the theoretical predictions for the corresponding cross-sections. The control regions are defined to be orthogonal to each other and to the signal region. They are required to fulfil the preselection criteria. In the leptonic channel, control regions enriched in tt̄ and W + jets processes are used (referred to as 1L-TCR and 1L-WCR, re- spectively). In the hadronic channel, a control region enriched in tt̄ production (referred to as 0L-TCR) and a region enriched in both the W + jets and Z + jets processes (referred to as 0L-VCR) are defined. The control regions in the leptonic channel, 1L-TCR and 1L-WCR, are defined by modifying the requirement on mWT to a window around the W mass, 60 GeV < mT < W – 12 – 100 GeV, and removing the requirement on |∆φ(`, b)|. For the 1L-TCR, events are also required to contain a second b-tagged jet. The tt̄ control region in the hadronic channel, 0L-TCR, is defined by requiring two b-tagged track-based jets and the minimum distance between the ET miss and any small-R jet in the transverse plane to satisfy ∆Φ min < 1 (in order to reduce the signal contribution) and ∆Φmin > 0.2 in order to suppress the multijet background). Events with calorimeter-based jets located close to disabled modules of the hadronic calorimeter are vetoed. In the 0L-VCR control region a veto on b-tagged track- based jets is applied. Table 1 details the control region selection in comparison with the signal region require- ments. A comparison of the observed and expected distributions for ET miss and m (E miss , J) JHEP05(2019)041 T T in the control regions is shown in figure 2 for the leptonic and hadronic channel, respec- tively. The expectations in the leptonic (hadronic) channel are obtained from a fit of the background-only hypothesis to data in the 1L (0L) control regions, where the nor- malisations of the tt̄ and W + jets (tt̄ and W /Z + jets) processes are treated as nuisance parameters in the fit (see section 8 for details of the fit). 7 Systematic uncertainties The normalisation and shapes of the signal and background estimates are affected by sys- tematic uncertainties from experimental sources and theoretical predictions. Each source of uncertainty is included as a nuisance parameter in the likelihood fit that determines the pos- sible signal contribution. The analysis is limited by statistical uncertainties, thus the inclu- sion of systematic uncertainties leads to only a small degradation of the expected sensitivity. The sources of experimental uncertainty include the uncertainty in the lepton trigger, identification and isolation efficiencies, the lepton energy and momentum scale and resolu- tion [98–100], the ET miss trigger and track-based soft-term scale and resolution [115, 116], the jet pile-up rejection requirement, energy scale and resolution [118], resolutions for rele- vant large-R jet properties (mass, transverse momentum and the N -subjetiness ratio τ32 ), the b-tagging efficiency [111, 112], the pile-up reweighting, and the luminosity. The uncertainty in the combined 2015+2016 integrated luminosity is 2.1%, derived following a methodology similar to that detailed in ref. [119], using a calibration of the luminosity scale through x–y beam-separation scans and using the LUCID-2 detector for the baseline luminosity measurements [120]. This systematic uncertainty is applied to all backgrounds and signals that are estimated using MC events, which are normalised to the measured integrated luminosity. Theoretical cross-section uncertainties are applied to the normalisation of the simu- lated processes. Additional shape uncertainties stemming from theoretical estimations are calculated by comparing samples simulated with different assumptions and are estimated for the dominant backgrounds. Uncertainties in the modelling of the tt̄ and t-channel single top background come from the choice of NLO-matching method, the parton shower and hadronisation modelling, and the amount of additional gluon radiation. The NLO-matching uncertainty is estimated by comparing events produced with Powheg-Box and MadGraph5 aMC@NLO [66], both – 13 – Events / bin Events / bin ATLAS Data ATLAS Data s = 13 TeV , 36.1 fb-1 tt 106 s = 13 TeV , 36.1 fb-1 tt 105 1L-TCR Single top 1L-WCR Single top W+jets W+jets Other 105 Other 4 10 Total Unc. Total Unc. 104 103 103 102 102 JHEP05(2019)041 1.3 1.3 Data/Pred. Data/Pred. 1.15 1.15 1 1 0.85 0.85 0.7 0.7 60 80 100 120 140 160 180 200 60 80 100 120 140 160 180 200 Emiss T [GeV] Emiss T [GeV] (a) (b) 106 Events / bin Events / bin 105 ATLAS Data ATLAS Data s = 13 TeV , 36.1 fb-1 tt s = 13 TeV , 36.1 fb-1 tt 0L-TCR Single top 0L-VCR Single top 104 W+jets 105 W+jets Z+jets Multi-jet Z+jets 103 Other Other Total Unc. 104 Total Unc. 102 103 10 102 1.31 1.3 Data/Pred. Data/Pred. 1.15 1.15 1 1 0.85 0.85 0.7 0.7 500 1000 1500 2000 2500 3000 500 1000 1500 2000 2500 3000 miss miss mT(E ,J) [GeV] mT(E ,J) [GeV] T T (c) (d) miss Figure 2. Comparison of data and SM prediction for the ET distribution in (a) the tt̄ and miss (b) W + jets control regions; and for the transverse mass of the top-tagged large-R jet and ET miss system, mT (ET , J), distribution in the (c) tt̄ and (d) W /Z +jet control regions used for the dark-matter search ((a) and (b)) and vector-like T -quark search ((c) and (d)). Other backgrounds in the 1L regions include multi-jet, Z+jets and diboson contributions, while in the 0L regions it is composed of diboson, tt̄ +X and multi-jet contributions. The expectations in the leptonic (hadronic) channel are obtained from a fit of the background-only hypothesis to data in the 1L (0L) control regions, where the normalisations of the tt̄ and W + jets (tt̄ and W /Z + jets) processes are treated as nuisance parameters in the fit. The error bands include statistical and systematic uncertainties. The last bin contains the overflow events. – 14 – interfaced with Herwig++ [121]. The parton shower, hadronisation, and underlying-event model uncertainty is estimated by comparing two parton shower models, Pythia and Herwig++, while keeping the same hard-scatter matrix element generator. Variations of the amount of additional gluon radiation are estimated by comparing simulated samples with enhanced or reduced radiation and different values of tunable parameters related to additional radiation [122]. The choice of scheme to account for the interference between the W t and tt̄ processes constitutes another source of systematic uncertainty that is estimated by comparing samples using either the diagram removal scheme or the diagram subtraction scheme [123]. JHEP05(2019)041 Modelling uncertainties affecting the shape of the W /Z + jets background are esti- mated in the hadronic channel, where these processes constitute an important background. An uncertainty in the modelling of W /Z + jets is estimated by comparing the nominal simulation with a MadGraph5 aMC@NLO simulation in which matrix elements were calculated at LO for up to four partons. In addition, the effects of independently varying the scales for the renormalisation, factorisation, and resummation by factors of 0.5 and 2 are used. Since the W /Z + jets background is constrained by a control region with a veto on b-tagged jets, an additional uncertainty related to the b-flavour content in the W /Z + jets background is taken into account by varying the number of events containing b-hadrons by 50% [124, 125]. Uncertainties in the modelling of the signal samples have been evaluated for signal points close to the expected exclusion mass limits and found to be negligible. The effects of parton distribution function (PDF) uncertainties on the acceptance of the tt̄ and W /Z + jets backgrounds are estimated following the PDF4LHC prescription [126]. The systematic uncertainty of 50% associated with the data-driven modelling of the multijet events is estimated in the leptonic channel, based on comparisons of the rates obtained using alternative methods, as described in previous analyses [117]. In the case of the hadronic channel, this systematic is derived from a closure test of the data-driven method in a multijet-dominated validation region using simulated dijet samples. A breakdown of the effects of the various sources of systematic uncertainty on the background prediction is presented in table 2 and table 3 for the two searches. The relative effects on the background yields in the signal region after the simultaneous fit to data in the signal and control regions are shown. The dominant background modelling uncertainties are due to the modelling of single top W t production for the leptonic channel and the modelling of the b-flavour content in the W /Z + jets backgrounds. 8 Results In order to test for the presence of a signal, a simultaneous fit to data in the signal and control regions is performed. The fit is based on a profile-likelihood technique, where sys- tematic uncertainties are allowed to vary as Gaussian-distributed nuisance parameters (NP) and subsequently acquire their best-fit values. Additionally, the dominant backgrounds are constrained by treating their normalisation as NP in the fit. The calculation of confidence – 15 – 1L-DM-SR 0L-DM-SR non-tt̄ tt̄ tt̄ Single top W +jets Z+jets Multijet Other b-tagging 4.8 4.6 4.1 2.9 9.2 7.7 — 8.0 ETmiss 12 1.1 2.2 2.1 2.2 2.2 3.0 2.0 Large-R jets — — 9.0 9.5 13 13 — 12 Small-R jets 9.9 7.0 1.3 2.9 1.0 0.5 — 1.0 Lepton 1.2 0.8 < 0.1 < 0.1 < 0.1 < 0.1 — < 0.1 Luminosity 2.0 2.1 2.1 2.1 2.3 2.2 — 2.1 Pile-up 5.3 1.4 0.3 0.3 0.8 1.2 — 1.4 Background modelling 15 14 8.9 5.3 27 27 110 1.0 Total systematic 18 12 6.8 13 32 31 89 16 JHEP05(2019)041 Table 2. Relative effect (in %) of various sources of systematic uncertainty on the predicted background yields in the signal regions used for the dark-matter search, obtained after the fit to data. Individual sources of uncertainties are correlated, and their sum in quadrature is not necessarily equal to the total background uncertainty. 0L-VLT-SR tt̄ Single top W +jets Z+jets Other b-tagging 3.9 3.2 11 7.7 8.4 ETmiss 1.4 1.9 0.8 0.5 0.3 Large-R jets 11 12 15 13 13 Small-R jets 7.3 7.8 7.6 8.3 11 Lepton < 0.1 < 0.1 < 0.1 < 0.1 < 0.1 Luminosity 2.2 2.3 2.4 2.1 2.2 Pile-up 1.3 2.9 4.7 4.1 5.1 Background modelling 14 6.1 28 26 2.7 Total systematic 7.9 15.5 21 19 19.5 Table 3. Relative effect (in %) of various sources of systematic uncertainty on the predicted background yields in the signal region used for the vector-like T -quark search, obtained after the fit to data. Individual sources of uncertainties are correlated, and their sum in quadrature is not necessarily equal to the total background uncertainty. intervals and hypothesis testing is performed using a frequentist method as implemented in RooStats [127] using the asymptotic approximation [128]. The ET miss distribution is used in the 1L signal region and the number of events is used instead in the control regions, while for the case of the 0L regions the distribution of the transverse mass of the top-tagged large-R jet and ET miss system, m (E miss , J), is used T T in signal and control regions. For each of the three fits the binning of the distributions is optimised separately to obtain the highest expected sensitivity. For the testing of the non-resonant DM signal, both the 1L and 0L regions are used simultaneously in the fit (two signal regions and four control regions). For the resonant DM and VLT tests the fits are performed in the corresponding 0L regions, one signal region and two control regions for each fit. Uncertainties due to the limited size of the simulated samples are taken into account in each bin of the fitted distributions. Nuisance parameters accounting for systematic uncertainties are not considered in the fit if they have an impact on either normalisation or shape which is below 1%. The systematic uncertainties are symmetrised – 16 – 1L-DM-SR 1L-TCR 1L-WCR 0L-DM-SR 0L-VLT-SR 0L-TCR 0L-VCR tt̄ 390 ± 140 12 300 ± 3100 8400 ± 1700 10 200 ± 2900 3700 ± 1200 7000 ± 1700 6100 ± 1800 Single top 66 ± 21 2930 ± 760 12 200 ± 1700 1020 ± 260 356 ± 97 274 ± 71 890 ± 250 W +jets 34.2 ± 8.4 1890 ± 640 92 000 ± 24 000 2240 ± 900 770 ± 310 147 ± 87 28 000 ± 12 000 Z+jets 0.40 ± 0.86 112 ± 49 3410 ± 990 2700 ± 1100 850 ± 360 139 ± 83 27 000 ± 11 000 Other 14 ± 15 640 ± 880 7000 ± 10 000 530 ± 190 89 ± 28 1060 ± 640 2730 ± 760 Total Background 500 ± 140 17 900 ± 3400 123 000 ± 26 000 16 600 ± 4500 5800 ± 1700 8600 ± 2000 66 000 ± 22 000 Data 511 17 662 127 286 15 781 5454 8493 62 304 R DM mφ = 1 TeV — — — 11 300 ± 1300 — 56 ± 13 8100 ± 1600 R DM mφ = 2 TeV — — — 469 ± 83 — 4.3 ± 1.1 349 ± 86 NR DM mφ = 1 TeV 165 ± 23 1.02 ± 0.47 20.2 ± 2.8 2090 ± 280 — 29.0 ± 5.9 1600 ± 320 NR DM mφ = 2 TeV 6.5 ± 2.7 0.027 ± 0.013 0.496 ± 0.097 95 ± 13 — 1.08 ± 0.21 75 ± 15 JHEP05(2019)041 VLT mVLT = 0.9 TeV — — — — 112 ± 20 21.0 ± 5.3 76 ± 17 Table 4. Numbers of events observed in the signal and control regions, together with the esti- mated SM backgrounds before the fit to data. The uncertainties include statistical and systematic uncertainties. The expected numbers of events for benchmark signals normalised to the theoretical prediction are also shown. The benchmark signals correspond to: the non-resonant (NR) DM model with mV = 1 TeV and 2 TeV, mχ = 1 GeV, a = 0.5 and gχ = 1; the resonant (R) DM model with mφ = 1 TeV and 2 TeV, mχ = 10 GeV, λ = 0.2 and y = 0.4; and a VLT with a mass of 0.9 TeV. and also smoothed if the bin-to-bin statistical variation is significant. Most uncertainties are found to be neither significantly constrained nor pulled from their initial values. Small variations are observed in the tt̄ modelling and multijet background uncertainties due to the mis-modelling observed in the shape of the transverse momentum distribution of top- quarks [129, 130]. Small variations are also observed in the large-R jet and Z/W + jets modelling uncertainties. The results of the fit show that the data are compatible with the background-only hypothesis. The numbers of events observed in the signal and control regions are presented in table 4, together with the backgrounds estimated prior to the simultaneous fit. The dis- miss or m (E miss , J)) in the signal regions for tribution of the observable used in the fit (ET T T data and the fitted SM expectation under the background-only hypothesis are shown in figure 3. In these plots, the expected contribution from a benchmark signal is also shown for comparison. No significant excess above the SM expectation is found in any of the signal regions. Since there is no evidence of a signal, expected and observed upper limits on the signal cross-section as a function of the V mass for the non-resonant model, the mass of the scalar particle φ for the resonant model and the VLT mass are derived at 95% confidence level (CL) and are shown in figure 4. Comparing the cross-section limits with the theoretical expectation, lower limits on the invisible particle and VLT masses can be derived. The LO values of the cross-section for non-resonant (resonant) DM production are evaluated using MadGraph5 aMC@NLO, as detailed in section 4, assuming mχ = 1 GeV, a = 0.5 and gχ = 1 (mχ = 10 GeV, λ = 0.2 and y = 0.4). For the VLT interpretation, the single-T production cross-section is taken from the NLO calculations for cW = 1, with the coupling cW defined in ref. [36]. The narrow-width approximation is used [36]. For the current analysis, it was checked using dedicated Monte Carlo samples that the chirality of – 17 – Events / bin Events / bin 104 ATLAS Data ATLAS Data NR DM mV = 1 TeV s = 13 TeV , 36.1 fb-1 5 s = 13 TeV , 36.1 fb-1 NR DM mV = 2 TeV NR DM mV = 1 TeV 10 1L-DM-SR 0L-DM-SR tt Post-Fit NR DM mV = 2 TeV Post-Fit Single top 103 W+jets non-tt 104 Z+jets tt Multi-jet Other Total Unc. 103 Total Unc. 102 102 10 10 JHEP05(2019)041 1.31 1.31 Data/Pred. Data/Pred. 1.15 1.15 1 1 0.85 0.85 0.7 0.7 100 200 300 400 500 600 700 800 900 1000 500 1000 1500 2000 2500 3000 Emiss T [GeV] mT(Emiss,J) [GeV] T (a) (b) 106 Events / bin Events / bin ATLAS Data 105 ATLAS Data R DM mφ = 1 TeV s = 13 TeV , 36.1 fb-1 R DM mφ = 2 TeV s = 13 TeV , 36.1 fb-1 VLT mVLT = 0.9 TeV 105 0L-DM-SR tt 0L-VLT-SR tt Single top 104 Single top Post-Fit W+jets Post-Fit 4 W+jets 10 Z+jets Z+jets Multi-jet Other 103 Other 103 Total Unc. Total Unc. 102 102 10 10 1.31 1.31 Data/Pred. Data/Pred. 1.15 1.15 1 1 0.85 0.85 0.7 0.7 500 1000 1500 2000 2500 3000 500 1000 1500 2000 2500 3000 miss mT(E ,J) [GeV] mT(Emiss,J) [GeV] T T (a) (b) miss Figure 3. Comparison of data and fitted expectations for the ET and the transverse mass of the miss miss top-tagged large-R jet and ET system, mT (ET , J), distributions in the signal regions. Other backgrounds in the 1L regions include multi-jet, Z+jets and diboson contributions, while in the 0L regions it is composed of diboson and tt̄ +X contributions. The background-only hypothesis is used in the fit: (a) and (b) including the 1L and 0L DM signal regions as well as the 1L and 0L control regions; (c) 0L DM signal and control regions; (d) 0L VLT signal and control regions. The error bands include statistical and systematic uncertainties. The expected shape of a benchmark signal normalised to the theoretical prediction is added on top of the SM prediction. The benchmark signals correspond to: the non-resonant (NR) DM model with mV = 1 TeV and 2 TeV, mχ = 1 GeV, a = 0.5 and gχ = 1; the resonant (R) DM model with mφ = 1 TeV and 2 TeV, mχ = 10 GeV, λ = 0.2 and y = 0.4; and a VLT with a mass of 0.9 TeV. – 18 – the coupling has negligible impact on the considered observables. The cross-section is also corrected for width effects calculated with MadGraph5 aMC@NLO, assuming that the ratio of NLO to LO cross-sections remains approximately the same for a non-vanishing T - quark width. The computed cross-section is then multiplied by the value of B(T → Zt) in the singlet model, which is ≈ 25% in the range of VLT masses investigated in this analysis. The considered benchmark coupling of κT = 0.5 corresponds to cW = 0.45. The observed (expected) mass limits at 95% CL are 2.0 (1.9) TeV and 3.4 (3.3) TeV for the non-resonant and resonant dark-matter models, respectively. For the VLT case, there is no observed or expected mass exclusion for the considered reference benchmark coupling. JHEP05(2019)041 Two-dimensional exclusion regions in the planes formed by the mediator masses, the DM particle mass, and couplings between the DM, the new heavy particle and the SM fermions are obtained by reweighting the events using the transverse momentum from the vector sum of the momenta of the DM candidates. This procedure is validated with dedicated samples and allows reproduction of the correct event kinematics for the masses and couplings required for the multidimensional scans. The observed (expected) 95% CL upper limit contours for the signal strength σ/σtheory are shown in figures 5(a)–5(c) for the non-resonant model, in which σ is the observed (expected) limit on the model cross- section at a given point of the parameter space and σtheory is the predicted cross-section in the model at the same point. The corresponding results for the resonant model are shown in figures 5(d) and 5(e). Since a reweighting procedure was used to obtain the required signal points, the results shown in figure 5 include a systematic uncertainty in the signal normalisation associated with this procedure. This uncertainty was estimated from dedicated MC samples to be 10% and 25% for the non-resonant and resonant case, respectively, by comparing reweighted samples with those generated with the corresponding signal masses and couplings. The limited sensitivity of the current analysis to single VLT production for low T masses (cf. figure 4(c)) implies that there is also less sensitivity to the corresponding cou- pling. This can be seen in figure 6(a), which shows the expected and observed 95% CL upper limits on cW , taken as the sum in quadrature of the left- and right-handed cou- plings cL,W and cR,W , as a function of the VLT mass. Nonetheless, the sensitivity remains approximately constant for masses up to 1.4 TeV. A singlet T , which corresponds to B(T → Zt) ≈ 25% over the mass range studied in this analysis, was assumed. The ob- tained limits on cW can also be translated into expected and observed 95% CL upper limits for the mixing angle of a singlet T with the SM top-quark, as shown in figure 6(b). For these results, a signal reweighting procedure was adopted in order to take into account the width effects induced by the variation of the cW coupling. The systematic uncertainty in the signal normalisation was estimated to be 3% from dedicated MC samples and was considered when deriving the limits shown in figure 6. In the range m(T ) > 1.1 TeV, the obtained exclusion limit on the cW coupling improves on the previous results [43]. – 19 – 102 σ(pp → tV) [pb] σ(pp → tχ) [pb] ATLAS Theory ATLAS Theory −1 95% CL Exp. -1 95% CL Exp. 102 s = 13 TeV, 36.1 fb s = 13 TeV, 36.1 fb 95% CL Obs. 10 95% CL Obs. Non-resonant DM 95% CL Exp. ±1σ Resonant DM signal 95% CL Exp. ±1σ mχ = 1 GeV, a = 0.5, gχ = 1 95% CL Exp. ±2σ mχ = 10 GeV, λ = 0.2, y = 0.4 95% CL Exp. ±2σ 10 1 JHEP05(2019)041 1 10−1 10−1 10−2 10−2 10−3 10−3 10−4 1000 1200 1400 1600 1800 2000 2200 2400 2600 1000 1500 2000 2500 3000 3500 4000 4500 5000 mV [GeV] mφ [GeV] (a) (b) 102 σ(pp → Tbq) × B(T → tZ) [pb] ATLAS NLO, κ T = 0.5 -1 B(T→Zt) ≈ 0.25 s = 13 TeV, 36.1 fb (singlet model) 10 Single-T Production 95% CL Exp. 95% CL Obs. 95% CL Exp. ±1σ 95% CL Exp. ±2σ 1 10−1 10−2 10−3 600 800 1000 1200 1400 1600 1800 2000 mT [GeV] (c) Figure 4. 95% CL upper limits on the signal cross-section as a function of (a) the V mass in the non-resonant (NR) model, (b) the mass of the scalar particle φ in the resonant (R) model and (c) the VLT mass. LO values for the production cross-section were computed for the non-resonant (resonant) DM production modes assuming mχ = 1 GeV, a = 0.5 and gχ = 1 (mχ = 10 GeV, λ = 0.2 and y = 0.4). – 20 – 0.5 102 102 Observed σ95% CL/ σtheory Observed σ95% CL/ σtheory gχ a ATLAS 0.9 ATLAS 0.45 s = 13 TeV, 36.1 fb-1 s = 13 TeV, 36.1 fb-1 0.8 0.4 Non-resonant DM signal Non-resonant DM signal 10 0.7 10 g χ = 1.0, m χ = 1.0 GeV a = 0.5, mχ = 1.0 GeV 0.35 0.6 0.3 1 0.5 1 0.25 Observed 95% CL 0.4 Observed 95% CL 0.2 Median expected 95% CL Median expected 95% CL 0.3 0.15 Exp. + 1σ 10−1 Exp. + 1σ 10−1 Exp. - 1σ Exp. - 1σ 0.2 Exp. + 2 σ Exp. + 2 σ 0.1 Exp. - 2 σ Exp. - 2 σ 0.1 0.05 10−2 10−2 1000 1500 2000 2500 3000 1000 1500 2000 2500 3000 JHEP05(2019)041 mV [GeV] mV [GeV] (a) (b) 1000 102 mχ [GeV] Observed σ95% CL/ σtheory ATLAS 900 s = 13 TeV, 36.1 fb-1 800 Non-resonant DM signal 10 g χ = 1.0, a = 0.5 700 600 1 500 Observed 95% CL 400 Median expected 95% CL 300 Exp. + 1σ 10−1 Exp. - 1σ Exp. + 2 σ 200 Exp. - 2σ 100 10−2 1000 1500 2000 mV [GeV] (c) 1 102 1 102 Observed σ95% CL/ σtheory Observed σ95% CL/ σtheory λ y ATLAS ATLAS 0.9 0.9 s = 13 TeV, 36.1 fb-1 s = 13 TeV, 36.1 fb-1 0.8 Resonant DM signal 0.8 Resonant DM signal 10 10 y = 0.4, mχ = 1.0 GeV λ = 0.2, mχ = 1.0 GeV 0.7 0.7 0.6 0.6 Observed 95% CL 1 Observed 95% CL 1 0.5 Median expected 95% CL 0.5 Median expected 95% CL Exp. + 1σ Exp. + 1σ 0.4 Exp. - 1σ 0.4 Exp. - 1σ Exp. + 2 σ Exp. + 2 σ 0.3 Exp. - 2 σ 10−1 0.3 Exp. - 2 σ 10−1 0.2 0.2 −2 0.1 10 0.1 10−2 1000 2000 3000 4000 1000 2000 3000 4000 mφ [GeV] mφ [GeV] (d) (e) Figure 5. The 95% CL upper limit contours on the signal strength σ/σtheory are shown for the non-resonant (NR) and resonant (R) DM production models. Non-resonant model: (a) V mass vs a; (b) V mass vs gχ and (c) V mass vs mass of the DM candidate χ. Resonant model: (d) mass of the scalar φ vs λ; (e) mass of the scalar φ vs y. The solid (dashed) lines correspond to the observed (median expected and corresponding ±1σ and ±2σ bands) limits for σ/σtheory = 1. The predicted cross-sections were computed with MadGraph5 aMC@NLO. – 21 – cW = c2L,W + c2R,W 2 95% CL Exp. ± 2σ ATLAS 1.8 s = 13 TeV, 36.1 fb-1 95% CL Exp. ± 1σ 95% CL Exp. Limit 1.6 Observed Limit B(T → Zt) ≈ 0.25 (singlet model) 1.4 1.2 1 0.8 0.6 0.4 JHEP05(2019)041 0.2 700 800 900 1000 1100 1200 1300 1400 1500 mT [GeV] (a) 1 |sin θL| 0.9 0.8 0.7 0.6 0.5 0.4 0.3 95% CL Exp. ± 2σ 0.2 95% CL Exp. ± 1σ ATLAS 95% CL Exp. Limit 0.1 s = 13 TeV, 36.1 fb -1 Observed Limit 0 800 1000 1200 1400 1600 1800 mT [GeV] (b) Figure 6. Expected and observed 95% CL limits from the combination q of the single-production channels on (a) the coupling of the T quark to SM particles, cW = c2L,W + c2R,W assuming a singlet T , corresponding to a B of ≈ 25%; and (b) the absolute value of sin θL , with θL being the mixing angle of a singlet T with the SM top-quark. 9 Conclusions This analysis seeks anomalous production of events with large ET miss and a single top- √ quark in LHC pp data at s = 13 TeV collected by the ATLAS detector in 2015 and 2016, corresponding to an integrated luminosity of 36.1 fb−1 . No deviations with respect to SM predictions are observed and 95% CL upper limits on the production cross-section of three BSM processes are obtained: resonant and non-resonant production of dark matter (DM) in association with single top-quarks, and single production of vector-like T quarks decaying into tZ(→ ν ν̄). These limits are also interpreted in terms of the excluded regions in the parameter space of the considered BSM scenarios. For DM production in the non-resonant scenario, – 22 – masses of a new vector particle coupling to the DM candidate up to 2 TeV are excluded at 95% CL for mχ = 1 GeV, gχ = 1.0 and a = 0.5, while in the resonant case, masses of a new scalar particle coupling to DM up to 3.4 TeV are excluded at 95% CL for mχ = 10 GeV, y = 0.4 and λ = 0.2. For the production of T singlets, couplings of these new quarks to top-quarks and W bosons, cW , above 0.7 are excluded for mT = 1.4 TeV and below. A Event yields in the signal and control regions after the fit to data The numbers of events observed in the signal and control regions are presented in tables 5, 6 and 7, together with the backgrounds estimated in the simultaneous fit to data in the JHEP05(2019)041 corresponding regions under the background-only hypothesis. In table 5, 1L and 0L DM signal regions as well as the 1L and 0L control regions are included in the fit. table 6 includes 0L DM signal and control regions, while VLT signal and control regions are considered for table 7. Leptonic channel 1L-DM-SR 1L-TCR 1L-WCR tt̄ 385 ± 41 12 100 ± 2000 8470 ± 800 Non-tt̄ 117 ± 17 5540 ± 960 119 000 ± 26 000 Total 502 ± 62 17 700 ± 3100 127 000 ± 26 000 Data 511 17 662 127 286 Hadronic channel 0L-DM-SR 0L-TCR 0L-VCR tt̄ 9900 ± 870 7160 ± 620 5900 ± 250 Single top 990 ± 110 273 ± 36 879 ± 98 W +jets 2050 ± 520 119 ± 65 23 100 ± 4900 Z+jets 2460 ± 460 135 ± 61 29 900 ± 4600 Multijet 87 ± 90 760 ± 350 0±0 Other 328 ± 41 50.1 ± 5.6 2670 ± 310 Total 15 800 ± 1200 8490 ± 760 62 400 ± 1500 Data 15 781 8493 62 304 Table 5. Numbers of events observed in the signal and control regions used for the non-resonant dark-matter search, together with the estimated SM backgrounds in the fit to data, under the background-only hypothesis. The uncertainties include statistical and systematic uncertainties. The uncertainties in the individual backgrounds are correlated, and do not necessarily add in quadrature to the total background uncertainty. – 23 – 0L-DM-SR 0L-TCR 0L-VCR tt̄ 9690 ± 620 7110 ± 460 5710 ± 580 Single top 990 ± 110 282 ± 40 870 ± 110 W +jets 2070 ± 540 121 ± 67 23 000 ± 5000 Z+jets 2610 ± 530 149 ± 61 30 100 ± 4700 Other 330 ± 44 51.4 ± 6.1 2670 ± 310 Multijet 92 ± 88 800 ± 360 0±0 Total 15 800 ± 370 8510 ± 280 62 300 ± 1400 Data 15 781 8493 62 304 JHEP05(2019)041 Table 6. Numbers of events observed in the signal and control regions used for the resonant dark-matter search, together with the estimated SM backgrounds in the fit to data, under the background-only hypothesis. The uncertainties include statistical and systematic uncertainties. The uncertainties in the individual backgrounds are correlated, and do not necessarily add in quadrature to the total background uncertainty. 0L-VLT-SR 0L-TCR 0L-VCR tt̄ 3560 ± 280 7160 ± 370 5310 ± 740 Single top 323 ± 45 278 ± 37 820 ± 120 W +jets 660 ± 200 126 ± 72 21 900 ± 5900 Z+jets 830 ± 180 160 ± 64 31 800 ± 4800 Other 82 ± 14 800 ± 320 2590 ± 340 Total 5460 ± 160 8530 ± 270 62 300 ± 1400 Data 5454 8493 62 304 Table 7. Numbers of events observed in the signal and control regions used for the vector-like T - quark search, together with the estimated SM backgrounds in the fit to data, under the background- only hypothesis. The uncertainties include statistical and systematic uncertainties. The uncertain- ties in the individual backgrounds are correlated, and do not necessarily add in quadrature to the total background uncertainty. 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, Aus- tralia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, 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; MES of Russia and NRC KI, Russian Federation; JINR; – 24 – MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DST/NRF, South Africa; MINECO, 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 support from BCKDF, CANARIE, CRC and Compute Canada, Canada; COST, ERC, ERDF, Horizon 2020, and Marie Sklodowska-Curie Actions, European Union; Investissements d’ Avenir Labex and Idex, ANR, France; DFG and AvH Foundation, Ger- many; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and GIF, Israel; CERCA Programme Generalitat de Catalunya, Spain; The Royal Society and Leverhulme Trust, United Kingdom. JHEP05(2019)041 The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (U.K.) and BNL (U.S.A.), the Tier-2 facilities worldwide and large non-WLCG resource providers. Ma- jor contributors of computing resources are listed in ref. [131]. 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Ippolito70a,70b , M.F. Isacson169 , N. Ishijima130 , M. Ishino160 , M. Ishitsuka162 , W. Islam126 , C. Issever132 , S. Istin157 , F. Ito166 , J.M. Iturbe Ponce61a , R. Iuppa73a,73b , A. Ivina177 , H. Iwasaki79 , J.M. Izen42 , V. Izzo67a , P. Jacka138 , P. Jackson1 , R.M. Jacobs24 , V. Jain2 , G. Jäkel179 , K.B. Jakobi97 , K. Jakobs50 , S. Jakobsen74 , T. Jakoubek138 , D.O. Jamin126 , R. Jansky52 , J. Janssen24 , M. Janus51 , P.A. Janus81a , G. Jarlskog94 , N. Javadov77,af , T. Javůrek35 , M. Javurkova50 , F. Jeanneau142 , L. Jeanty18 , J. Jejelava156a,ag , A. Jelinskas175 , P. Jenni50,d , J. Jeong44 , N. Jeong44 , S. Jézéquel5 , H. Ji178 , J. Jia152 , H. Jiang76 , Y. Jiang58a , Z. Jiang150,r , S. Jiggins50 , F.A. Jimenez Morales37 , J. Jimenez Pena171 , S. Jin15c , A. Jinaru27b , O. Jinnouchi162 , H. Jivan32c , P. Johansson146 , K.A. Johns7 , C.A. Johnson63 , W.J. Johnson145 , K. Jon-And43a,43b , R.W.L. Jones87 , S.D. Jones153 , S. Jones7 , T.J. Jones88 , J. Jongmanns59a , P.M. 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Khramov77 , J. Khubua156b , S. Kido80 , M. Kiehn52 , C.R. Kilby91 , Y.K. Kim36 , N. Kimura64a,64c , O.M. Kind19 , B.T. King88 , D. Kirchmeier46 , J. Kirk141 , A.E. Kiryunin113 , T. Kishimoto160 , D. Kisielewska81a , V. Kitali44 , O. Kivernyk5 , E. Kladiva28b,∗ , T. Klapdor-Kleingrothaus50 , M.H. Klein103 , M. Klein88 , U. Klein88 , K. Kleinknecht97 , P. Klimek119 , A. Klimentov29 , T. Klingl24 , T. Klioutchnikova35 , F.F. Klitzner112 , P. Kluit118 , S. Kluth113 , E. Kneringer74 , E.B.F.G. Knoops99 , A. Knue50 , A. Kobayashi160 , D. Kobayashi85 , T. Kobayashi160 , M. Kobel46 , M. Kocian150 , P. Kodys140 , P.T. Koenig24 , T. Koffas33 , E. Koffeman118 , N.M. Köhler113 , T. Koi150 , M. Kolb59b , I. Koletsou5 , T. Kondo79 , N. Kondrashova58c , K. Köneke50 , A.C. König117 , T. Kono79 , R. Konoplich122,am , V. Konstantinides92 , N. Konstantinidis92 , B. Konya94 , R. Kopeliansky63 , S. Koperny81a , – 37 – K. Korcyl82 , K. Kordas159 , G. Koren158 , A. Korn92 , I. Korolkov14 , E.V. Korolkova146 , N. Korotkova111 , O. Kortner113 , S. Kortner113 , T. Kosek140 , V.V. Kostyukhin24 , A. Kotwal47 , A. Koulouris10 , A. Kourkoumeli-Charalampidi68a,68b , C. Kourkoumelis9 , E. Kourlitis146 , V. Kouskoura29 , A.B. Kowalewska82 , R. Kowalewski173 , T.Z. Kowalski81a , C. Kozakai160 , W. Kozanecki142 , A.S. Kozhin121 , V.A. Kramarenko111 , G. Kramberger89 , D. Krasnopevtsev58a , M.W. Krasny133 , A. Krasznahorkay35 , D. Krauss113 , J.A. Kremer81a , J. Kretzschmar88 , P. Krieger164 , K. Krizka18 , K. Kroeninger45 , H. Kroha113 , J. Kroll138 , J. Kroll134 , J. Krstic16 , U. Kruchonak77 , H. Krüger24 , N. Krumnack76 , M.C. Kruse47 , T. Kubota102 , S. Kuday4b , J.T. Kuechler179 , S. Kuehn35 , A. Kugel59a , F. Kuger174 , T. Kuhl44 , V. Kukhtin77 , R. Kukla99 , Y. Kulchitsky105 , S. Kuleshov144b , Y.P. Kulinich170 , M. Kuna56 , T. Kunigo83 , A. Kupco138 , T. Kupfer45 , O. Kuprash158 , H. Kurashige80 , L.L. Kurchaninov165a , Y.A. Kurochkin105 , JHEP05(2019)041 A. Kurova110 , M.G. Kurth15d , E.S. Kuwertz35 , M. Kuze162 , J. Kvita127 , T. Kwan101 , A. La Rosa113 , J.L. La Rosa Navarro78d , L. La Rotonda40b,40a , F. La Ruffa40b,40a , C. Lacasta171 , F. Lacava70a,70b , J. Lacey44 , D.P.J. Lack98 , H. Lacker19 , D. Lacour133 , E. Ladygin77 , R. Lafaye5 , B. Laforge133 , T. Lagouri32c , S. Lai51 , S. Lammers63 , W. Lampl7 , E. Lançon29 , U. Landgraf50 , M.P.J. Landon90 , M.C. Lanfermann52 , V.S. Lang44 , J.C. Lange51 , R.J. Langenberg35 , A.J. Lankford168 , F. Lanni29 , K. Lantzsch24 , A. Lanza68a , A. Lapertosa53b,53a , S. Laplace133 , J.F. Laporte142 , T. Lari66a , F. Lasagni Manghi23b,23a , M. Lassnig35 , T.S. Lau61a , A. Laudrain129 , M. Lavorgna67a,67b , M. Lazzaroni66a,66b , B. Le102 , O. Le Dortz133 , E. Le Guirriec99 , E.P. Le Quilleuc142 , M. LeBlanc7 , T. LeCompte6 , F. Ledroit-Guillon56 , C.A. Lee29 , G.R. Lee144a , L. Lee57 , S.C. Lee155 , B. Lefebvre101 , M. Lefebvre173 , F. Legger112 , C. Leggett18 , K. Lehmann149 , N. Lehmann179 , G. 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Llorente Merino15a , S.L. Lloyd90 , C.Y. Lo61b , F. Lo Sterzo41 , E.M. Lobodzinska44 , P. Loch7 , T. Lohse19 , K. Lohwasser146 , M. Lokajicek138 , J.D. Long170 , R.E. Long87 , L. Longo65a,65b , K.A. Looper123 , J.A. Lopez144b , I. Lopez Paz98 , A. Lopez Solis146 , J. Lorenz112 , N. Lorenzo Martinez5 , M. Losada22 , P.J. Lösel112 , A. Lösle50 , X. Lou44 , X. Lou15a , A. Lounis129 , J. Love6 , P.A. Love87 , J.J. Lozano Bahilo171 , H. Lu61a , M. Lu58a , Y.J. Lu62 , H.J. Lubatti145 , C. Luci70a,70b , A. Lucotte56 , C. Luedtke50 , F. Luehring63 , I. Luise133 , L. Luminari70a , B. Lund-Jensen151 , M.S. Lutz100 , P.M. Luzi133 , D. Lynn29 , R. Lysak138 , E. Lytken94 , F. Lyu15a , V. Lyubushkin77 , T. Lyubushkina77 , H. Ma29 , L.L. Ma58b , Y. Ma58b , G. Maccarrone49 , A. Macchiolo113 , C.M. Macdonald146 , J. Machado Miguens134,137b , D. Madaffari171 , R. Madar37 , W.F. Mader46 , A. Madsen44 , N. Madysa46 , J. Maeda80 , K. Maekawa160 , S. Maeland17 , T. Maeno29 , M. Maerker46 , A.S. Maevskiy111 , V. Magerl50 , D.J. Mahon38 , C. Maidantchik78b , T. Maier112 , A. Maio137a,137b,137d , O. Majersky28a , S. Majewski128 , Y. Makida79 , N. Makovec129 , B. Malaescu133 , Pa. Malecki82 , V.P. Maleev135 , F. Malek56 , U. Mallik75 , D. Malon6 , C. Malone31 , S. Maltezos10 , S. Malyukov35 , J. Mamuzic171 , G. Mancini49 , I. Mandić89 , J. Maneira137a , L. Manhaes de Andrade Filho78a , J. Manjarres Ramos46 , K.H. Mankinen94 , A. Mann112 , A. Manousos74 , B. Mansoulie142 , J.D. Mansour15a , M. Mantoani51 , S. Manzoni66a,66b , A. Marantis159 , G. Marceca30 , L. March52 , L. Marchese132 , G. Marchiori133 , M. Marcisovsky138 , – 38 – C. Marcon94 , C.A. Marin Tobon35 , M. Marjanovic37 , D.E. Marley103 , F. Marroquim78b , Z. Marshall18 , M.U.F Martensson169 , S. Marti-Garcia171 , C.B. Martin123 , T.A. Martin175 , V.J. Martin48 , B. Martin dit Latour17 , M. Martinez14,z , V.I. Martinez Outschoorn100 , S. Martin-Haugh141 , V.S. Martoiu27b , A.C. Martyniuk92 , A. Marzin35 , L. Masetti97 , T. Mashimo160 , R. Mashinistov108 , J. Masik98 , A.L. Maslennikov120b,120a , L.H. Mason102 , L. Massa71a,71b , P. Massarotti67a,67b , P. Mastrandrea5 , A. Mastroberardino40b,40a , T. Masubuchi160 , P. Mättig179 , J. Maurer27b , B. Maček89 , S.J. Maxfield88 , D.A. Maximov120b,120a , R. Mazini155 , I. Maznas159 , S.M. Mazza143 , G. Mc Goldrick164 , S.P. Mc Kee103 , A. McCarn103 , T.G. McCarthy113 , L.I. McClymont92 , W.P. McCormack18 , E.F. McDonald102 , J.A. Mcfayden35 , G. Mchedlidze51 , M.A. McKay41 , K.D. McLean173 , S.J. McMahon141 , P.C. McNamara102 , C.J. McNicol175 , R.A. McPherson173,ad , J.E. Mdhluli32c , Z.A. Meadows100 , S. Meehan145 , JHEP05(2019)041 T.M. Megy50 , S. Mehlhase112 , A. Mehta88 , T. Meideck56 , B. Meirose42 , D. Melini171,h , B.R. Mellado Garcia32c , J.D. Mellenthin51 , M. Melo28a , F. Meloni44 , A. Melzer24 , S.B. Menary98 , E.D. Mendes Gouveia137a , L. Meng88 , X.T. Meng103 , A. Mengarelli23b,23a , S. Menke113 , E. Meoni40b,40a , S. Mergelmeyer19 , S.A.M. Merkt136 , C. Merlassino20 , P. Mermod52 , L. Merola67a,67b , C. Meroni66a , F.S. Merritt36 , A. Messina70a,70b , J. Metcalfe6 , A.S. Mete168 , C. Meyer134 , J. Meyer157 , J-P. Meyer142 , H. Meyer Zu Theenhausen59a , F. Miano153 , R.P. Middleton141 , L. Mijović48 , G. Mikenberg177 , M. Mikestikova138 , M. Mikuž89 , M. Milesi102 , A. Milic164 , D.A. Millar90 , D.W. Miller36 , A. Milov177 , D.A. Milstead43a,43b , A.A. Minaenko121 , M. Miñano Moya171 , I.A. Minashvili156b , A.I. Mincer122 , B. Mindur81a , M. Mineev77 , Y. Minegishi160 , Y. Ming178 , L.M. Mir14 , A. Mirto65a,65b , K.P. Mistry134 , T. Mitani176 , J. Mitrevski112 , V.A. Mitsou171 , M. Mittal58c , A. Miucci20 , P.S. Miyagawa146 , A. Mizukami79 , J.U. Mjörnmark94 , T. Mkrtchyan181 , M. Mlynarikova140 , T. Moa43a,43b , K. Mochizuki107 , P. Mogg50 , S. Mohapatra38 , S. Molander43a,43b , R. Moles-Valls24 , M.C. Mondragon104 , K. Mönig44 , J. Monk39 , E. Monnier99 , A. Montalbano149 , J. Montejo Berlingen35 , F. Monticelli86 , S. Monzani66a , N. Morange129 , D. Moreno22 , M. Moreno Llácer35 , P. Morettini53b , M. Morgenstern118 , S. Morgenstern46 , D. Mori149 , M. Morii57 , M. Morinaga176 , V. Morisbak131 , A.K. Morley35 , G. Mornacchi35 , A.P. Morris92 , J.D. Morris90 , L. Morvaj152 , P. Moschovakos10 , M. Mosidze156b , H.J. Moss146 , J. Moss150,o , K. Motohashi162 , R. Mount150 , E. Mountricha35 , E.J.W. Moyse100 , S. Muanza99 , F. Mueller113 , J. Mueller136 , R.S.P. Mueller112 , D. Muenstermann87 , G.A. Mullier94 , F.J. Munoz Sanchez98 , P. Murin28b , W.J. Murray175,141 , A. Murrone66a,66b , M. Muškinja89 , C. Mwewa32a , A.G. Myagkov121,an , J. Myers128 , M. Myska139 , B.P. Nachman18 , O. Nackenhorst45 , K. Nagai132 , K. Nagano79 , Y. Nagasaka60 , M. Nagel50 , E. Nagy99 , A.M. Nairz35 , Y. Nakahama115 , K. Nakamura79 , T. Nakamura160 , I. Nakano124 , H. Nanjo130 , F. Napolitano59a , R.F. Naranjo Garcia44 , R. Narayan11 , D.I. Narrias Villar59a , I. Naryshkin135 , T. Naumann44 , G. Navarro22 , R. Nayyar7 , H.A. Neal103,∗ , P.Y. Nechaeva108 , T.J. Neep142 , A. Negri68a,68b , M. Negrini23b , S. Nektarijevic117 , C. Nellist51 , M.E. Nelson132 , S. Nemecek138 , P. Nemethy122 , M. Nessi35,f , M.S. Neubauer170 , M. Neumann179 , P.R. Newman21 , T.Y. Ng61c , Y.S. Ng19 , H.D.N. Nguyen99 , T. Nguyen Manh107 , E. Nibigira37 , R.B. Nickerson132 , R. Nicolaidou142 , D.S. Nielsen39 , J. Nielsen143 , N. Nikiforou11 , V. Nikolaenko121,an , I. Nikolic-Audit133 , K. Nikolopoulos21 , P. Nilsson29 , Y. Ninomiya79 , A. Nisati70a , N. Nishu58c , R. Nisius113 , I. Nitsche45 , T. Nitta176 , T. Nobe160 , Y. Noguchi83 , M. Nomachi130 , I. Nomidis133 , M.A. Nomura29 , T. Nooney90 , M. Nordberg35 , N. Norjoharuddeen132 , T. Novak89 , O. Novgorodova46 , R. Novotny139 , L. Nozka127 , K. Ntekas168 , E. Nurse92 , F. Nuti102 , F.G. Oakham33,av , H. Oberlack113 , J. Ocariz133 , A. Ochi80 , I. Ochoa38 , J.P. Ochoa-Ricoux144a , K. O’Connor26 , S. Oda85 , S. Odaka79 , S. Oerdek51 , A. Oh98 , S.H. Oh47 , C.C. Ohm151 , H. Oide53b,53a , M.L. Ojeda164 , H. Okawa166 , Y. Okazaki83 , Y. Okumura160 , T. Okuyama79 , A. Olariu27b , L.F. Oleiro Seabra137a , S.A. Olivares Pino144a , D. Oliveira Damazio29 , J.L. Oliver1 , – 39 – M.J.R. Olsson36 , A. Olszewski82 , J. Olszowska82 , D.C. O’Neil149 , A. Onofre137a,137e , K. Onogi115 , P.U.E. Onyisi11 , H. Oppen131 , M.J. Oreglia36 , G.E. Orellana86 , Y. Oren158 , D. Orestano72a,72b , N. Orlando61b , A.A. O’Rourke44 , R.S. Orr164 , B. Osculati53b,53a,∗ , V. O’Shea55 , R. Ospanov58a , G. Otero y Garzon30 , H. Otono85 , M. Ouchrif34d , F. Ould-Saada131 , A. Ouraou142 , Q. Ouyang15a , M. Owen55 , R.E. Owen21 , V.E. Ozcan12c , N. Ozturk8 , J. Pacalt127 , H.A. Pacey31 , K. Pachal149 , A. Pacheco Pages14 , L. Pacheco Rodriguez142 , C. Padilla Aranda14 , S. Pagan Griso18 , M. Paganini180 , G. Palacino63 , S. Palazzo48 , S. Palestini35 , M. Palka81b , D. Pallin37 , I. Panagoulias10 , C.E. Pandini35 , J.G. Panduro Vazquez91 , P. Pani35 , G. Panizzo64a,64c , L. Paolozzi52 , T.D. Papadopoulou10 , K. Papageorgiou9,k , A. Paramonov6 , D. Paredes Hernandez61b , S.R. Paredes Saenz132 , B. Parida163 , T.H. Park33 , A.J. Parker87 , K.A. Parker44 , M.A. Parker31 , F. Parodi53b,53a , J.A. Parsons38 , U. Parzefall50 , V.R. Pascuzzi164 , JHEP05(2019)041 J.M.P. Pasner143 , E. Pasqualucci70a , S. Passaggio53b , F. Pastore91 , P. Pasuwan43a,43b , S. Pataraia97 , J.R. Pater98 , A. Pathak178,l , T. Pauly35 , B. Pearson113 , M. Pedersen131 , L. Pedraza Diaz117 , R. Pedro137a,137b , S.V. Peleganchuk120b,120a , O. Penc138 , C. Peng15d , H. Peng58a , B.S. Peralva78a , M.M. Perego129 , A.P. Pereira Peixoto137a , D.V. Perepelitsa29 , F. Peri19 , L. Perini66a,66b , H. Pernegger35 , S. Perrella67a,67b , V.D. Peshekhonov77,∗ , K. Peters44 , R.F.Y. Peters98 , B.A. Petersen35 , T.C. Petersen39 , E. Petit56 , A. Petridis1 , C. Petridou159 , P. Petroff129 , M. Petrov132 , F. Petrucci72a,72b , M. Pettee180 , N.E. Pettersson100 , A. Peyaud142 , R. Pezoa144b , T. Pham102 , F.H. Phillips104 , P.W. Phillips141 , M.W. Phipps170 , G. Piacquadio152 , E. Pianori18 , A. Picazio100 , M.A. Pickering132 , R.H. Pickles98 , R. Piegaia30 , J.E. Pilcher36 , A.D. Pilkington98 , M. Pinamonti71a,71b , J.L. Pinfold3 , M. Pitt177 , L. Pizzimento71a,71b , M.-A. Pleier29 , V. Pleskot140 , E. Plotnikova77 , D. Pluth76 , P. Podberezko120b,120a , R. Poettgen94 , R. Poggi52 , L. Poggioli129 , I. Pogrebnyak104 , D. Pohl24 , I. Pokharel51 , G. Polesello68a , A. Poley18 , A. Policicchio70a,70b , R. Polifka35 , A. Polini23b , C.S. Pollard44 , V. Polychronakos29 , D. Ponomarenko110 , L. Pontecorvo35 , G.A. Popeneciu27d , D.M. Portillo Quintero133 , S. Pospisil139 , K. Potamianos44 , I.N. Potrap77 , C.J. Potter31 , H. Potti11 , T. Poulsen94 , J. Poveda35 , T.D. Powell146 , M.E. Pozo Astigarraga35 , P. Pralavorio99 , S. Prell76 , D. Price98 , M. Primavera65a , S. Prince101 , N. Proklova110 , K. Prokofiev61c , F. Prokoshin144b , S. Protopopescu29 , J. Proudfoot6 , M. Przybycien81a , A. Puri170 , P. Puzo129 , J. Qian103 , Y. Qin98 , A. Quadt51 , M. Queitsch-Maitland44 , A. Qureshi1 , P. Rados102 , F. Ragusa66a,66b , G. Rahal95 , J.A. Raine52 , S. Rajagopalan29 , A. Ramirez Morales90 , T. Rashid129 , S. Raspopov5 , M.G. Ratti66a,66b , D.M. Rauch44 , F. Rauscher112 , S. Rave97 , B. Ravina146 , I. Ravinovich177 , J.H. Rawling98 , M. Raymond35 , A.L. Read131 , N.P. Readioff56 , M. Reale65a,65b , D.M. Rebuzzi68a,68b , A. Redelbach174 , G. Redlinger29 , R. Reece143 , R.G. Reed32c , K. Reeves42 , L. Rehnisch19 , J. Reichert134 , D. Reikher158 , A. Reiss97 , C. Rembser35 , H. Ren15d , M. Rescigno70a , S. Resconi66a , E.D. Resseguie134 , S. Rettie172 , E. Reynolds21 , O.L. Rezanova120b,120a , P. Reznicek140 , E. Ricci73a,73b , R. Richter113 , S. Richter44 , E. Richter-Was81b , O. Ricken24 , M. Ridel133 , P. Rieck113 , C.J. Riegel179 , O. Rifki44 , M. Rijssenbeek152 , A. Rimoldi68a,68b , M. Rimoldi20 , L. Rinaldi23b , G. Ripellino151 , B. Ristić87 , E. Ritsch35 , I. Riu14 , J.C. Rivera Vergara144a , F. Rizatdinova126 , E. Rizvi90 , C. Rizzi14 , R.T. Roberts98 , S.H. Robertson101,ad , D. Robinson31 , J.E.M. Robinson44 , A. Robson55 , E. Rocco97 , C. Roda69a,69b , Y. Rodina99 , S. Rodriguez Bosca171 , A. Rodriguez Perez14 , D. Rodriguez Rodriguez171 , A.M. Rodrı́guez Vera165b , S. Roe35 , C.S. Rogan57 , O. Røhne131 , R. Röhrig113 , C.P.A. Roland63 , J. Roloff57 , A. Romaniouk110 , M. Romano23b,23a , N. Rompotis88 , M. Ronzani122 , L. Roos133 , S. Rosati70a , K. Rosbach50 , N-A. Rosien51 , B.J. Rosser134 , E. Rossi44 , E. Rossi72a,72b , E. Rossi67a,67b , L.P. Rossi53b , L. Rossini66a,66b , J.H.N. Rosten31 , R. Rosten14 , M. Rotaru27b , J. Rothberg145 , D. Rousseau129 , D. Roy32c , A. Rozanov99 , Y. Rozen157 , X. Ruan32c , F. Rubbo150 , F. Rühr50 , A. Ruiz-Martinez171 , Z. Rurikova50 , N.A. Rusakovich77 , – 40 – H.L. Russell101 , J.P. Rutherfoord7 , E.M. Rüttinger44,m , Y.F. Ryabov135 , M. Rybar170 , G. Rybkin129 , S. Ryu6 , A. Ryzhov121 , G.F. Rzehorz51 , P. Sabatini51 , G. Sabato118 , S. Sacerdoti129 , H.F-W. Sadrozinski143 , R. Sadykov77 , F. Safai Tehrani70a , P. Saha119 , M. Sahinsoy59a , A. Sahu179 , M. Saimpert44 , M. Saito160 , T. Saito160 , H. Sakamoto160 , A. Sakharov122,am , D. Salamani52 , G. Salamanna72a,72b , J.E. Salazar Loyola144b , P.H. Sales De Bruin169 , D. Salihagic113,∗ , A. Salnikov150 , J. Salt171 , D. Salvatore40b,40a , F. Salvatore153 , A. Salvucci61a,61b,61c , A. Salzburger35 , J. Samarati35 , D. Sammel50 , D. Sampsonidis159 , D. Sampsonidou159 , J. Sánchez171 , A. Sanchez Pineda64a,64c , H. Sandaker131 , C.O. Sander44 , M. Sandhoff179 , C. Sandoval22 , D.P.C. Sankey141 , M. Sannino53b,53a , Y. Sano115 , A. Sansoni49 , C. Santoni37 , H. Santos137a , I. Santoyo Castillo153 , A. Santra171 , A. Sapronov77 , J.G. Saraiva137a,137d , O. Sasaki79 , K. Sato166 , E. Sauvan5 , P. Savard164,av , N. Savic113 , JHEP05(2019)041 R. Sawada160 , C. Sawyer141 , L. Sawyer93,ak , C. Sbarra23b , A. Sbrizzi23a , T. Scanlon92 , J. Schaarschmidt145 , P. Schacht113 , B.M. Schachtner112 , D. Schaefer36 , L. Schaefer134 , J. Schaeffer97 , S. Schaepe35 , U. Schäfer97 , A.C. Schaffer129 , D. Schaile112 , R.D. Schamberger152 , N. Scharmberg98 , V.A. Schegelsky135 , D. Scheirich140 , F. Schenck19 , M. Schernau168 , C. Schiavi53b,53a , S. Schier143 , L.K. Schildgen24 , Z.M. Schillaci26 , E.J. Schioppa35 , M. Schioppa40b,40a , K.E. Schleicher50 , S. Schlenker35 , K.R. Schmidt-Sommerfeld113 , K. Schmieden35 , C. Schmitt97 , S. Schmitt44 , S. Schmitz97 , J.C. Schmoeckel44 , U. Schnoor50 , L. Schoeffel142 , A. Schoening59b , E. Schopf132 , M. Schott97 , J.F.P. Schouwenberg117 , J. Schovancova35 , S. Schramm52 , A. Schulte97 , H-C. Schultz-Coulon59a , M. Schumacher50 , B.A. Schumm143 , Ph. Schune142 , A. Schwartzman150 , T.A. Schwarz103 , Ph. Schwemling142 , R. Schwienhorst104 , A. Sciandra24 , G. Sciolla26 , M. Scornajenghi40b,40a , F. Scuri69a , F. Scutti102 , L.M. Scyboz113 , C.D. Sebastiani70a,70b , P. Seema19 , S.C. Seidel116 , A. Seiden143 , T. Seiss36 , J.M. Seixas78b , G. Sekhniaidze67a , K. Sekhon103 , S.J. Sekula41 , N. Semprini-Cesari23b,23a , S. Sen47 , S. Senkin37 , C. Serfon131 , L. Serin129 , L. Serkin64a,64b , M. Sessa58a , H. Severini125 , F. Sforza167 , A. Sfyrla52 , E. Shabalina51 , J.D. Shahinian143 , N.W. Shaikh43a,43b , L.Y. Shan15a , R. Shang170 , J.T. Shank25 , M. Shapiro18 , A.S. Sharma1 , A. Sharma132 , P.B. Shatalov109 , K. Shaw153 , S.M. Shaw98 , A. Shcherbakova135 , Y. Shen125 , N. Sherafati33 , A.D. Sherman25 , P. Sherwood92 , L. Shi155,ar , S. Shimizu79 , C.O. Shimmin180 , Y. Shimogama176 , M. Shimojima114 , I.P.J. Shipsey132 , S. Shirabe85 , M. Shiyakova77 , J. Shlomi177 , A. Shmeleva108 , D. Shoaleh Saadi107 , M.J. Shochet36 , S. Shojaii102 , D.R. Shope125 , S. Shrestha123 , E. Shulga110 , P. Sicho138 , A.M. Sickles170 , P.E. Sidebo151 , E. Sideras Haddad32c , O. Sidiropoulou35 , A. Sidoti23b,23a , F. Siegert46 , Dj. Sijacki16 , J. Silva137a , M. Silva Jr.178 , M.V. Silva Oliveira78a , S.B. Silverstein43a , S. Simion129 , E. Simioni97 , M. Simon97 , R. Simoniello97 , P. Sinervo164 , N.B. Sinev128 , M. Sioli23b,23a , G. Siragusa174 , I. Siral103 , S.Yu. Sivoklokov111 , J. Sjölin43a,43b , P. Skubic125 , M. Slater21 , T. Slavicek139 , M. Slawinska82 , K. Sliwa167 , R. Slovak140 , V. Smakhtin177 , B.H. Smart5 , J. Smiesko28a , N. Smirnov110 , S.Yu. Smirnov110 , Y. Smirnov110 , L.N. Smirnova111 , O. Smirnova94 , J.W. Smith51 , M. Smizanska87 , K. Smolek139 , A. Smykiewicz82 , A.A. Snesarev108 , I.M. Snyder128 , S. Snyder29 , R. Sobie173,ad , A.M. Soffa168 , A. Soffer158 , A. Søgaard48 , D.A. Soh155 , G. Sokhrannyi89 , C.A. Solans Sanchez35 , M. Solar139 , E.Yu. Soldatov110 , U. Soldevila171 , A.A. Solodkov121 , A. Soloshenko77 , O.V. Solovyanov121 , V. Solovyev135 , P. Sommer146 , H. Son167 , W. Song141 , W.Y. Song165b , A. Sopczak139 , F. Sopkova28b , C.L. Sotiropoulou69a,69b , S. Sottocornola68a,68b , R. Soualah64a,64c,j , A.M. Soukharev120b,120a , D. South44 , B.C. Sowden91 , S. Spagnolo65a,65b , M. Spalla113 , M. Spangenberg175 , F. Spanò91 , D. Sperlich19 , T.M. Spieker59a , R. Spighi23b , G. Spigo35 , L.A. Spiller102 , D.P. Spiteri55 , M. Spousta140 , A. Stabile66a,66b , R. Stamen59a , S. Stamm19 , E. Stanecka82 , R.W. Stanek6 , C. Stanescu72a , B. Stanislaus132 , M.M. Stanitzki44 , B. Stapf118 , S. Stapnes131 , E.A. Starchenko121 , G.H. Stark36 , J. Stark56 , S.H Stark39 , P. Staroba138 , – 41 – P. Starovoitov59a , S. Stärz35 , R. Staszewski82 , M. Stegler44 , P. Steinberg29 , B. Stelzer149 , H.J. Stelzer35 , O. Stelzer-Chilton165a , H. Stenzel54 , T.J. Stevenson153 , G.A. Stewart35 , M.C. Stockton35 , G. Stoicea27b , P. Stolte51 , S. Stonjek113 , A. Straessner46 , J. Strandberg151 , S. Strandberg43a,43b , M. Strauss125 , P. Strizenec28b , R. Ströhmer174 , D.M. Strom128 , R. Stroynowski41 , A. Strubig48 , S.A. Stucci29 , B. Stugu17 , J. Stupak125 , N.A. Styles44 , D. Su150 , J. Su136 , S. Suchek59a , Y. Sugaya130 , M. Suk139 , V.V. Sulin108 , M.J. Sullivan88 , D.M.S. Sultan52 , S. Sultansoy4c , T. Sumida83 , S. Sun103 , X. Sun3 , K. Suruliz153 , C.J.E. Suster154 , M.R. Sutton153 , S. Suzuki79 , M. Svatos138 , M. Swiatlowski36 , S.P. Swift2 , A. Sydorenko97 , I. Sykora28a , T. Sykora140 , D. Ta97 , K. Tackmann44,aa , J. Taenzer158 , A. Taffard168 , R. Tafirout165a , E. Tahirovic90 , N. Taiblum158 , H. Takai29 , R. Takashima84 , E.H. Takasugi113 , K. Takeda80 , T. Takeshita147 , Y. Takubo79 , M. Talby99 , A.A. Talyshev120b,120a , J. Tanaka160 , M. Tanaka162 , JHEP05(2019)041 R. Tanaka129 , B.B. Tannenwald123 , S. Tapia Araya144b , S. Tapprogge97 , A. Tarek Abouelfadl Mohamed133 , S. Tarem157 , G. Tarna27b,e , G.F. Tartarelli66a , P. Tas140 , M. Tasevsky138 , T. Tashiro83 , E. Tassi40b,40a , A. Tavares Delgado137a,137b , Y. Tayalati34e , A.C. Taylor116 , A.J. Taylor48 , G.N. Taylor102 , P.T.E. Taylor102 , W. Taylor165b , A.S. Tee87 , P. Teixeira-Dias91 , H. Ten Kate35 , J.J. Teoh118 , S. Terada79 , K. Terashi160 , J. Terron96 , S. Terzo14 , M. Testa49 , R.J. Teuscher164,ad , S.J. Thais180 , T. Theveneaux-Pelzer44 , F. Thiele39 , D.W. Thomas91 , J.P. Thomas21 , A.S. Thompson55 , P.D. Thompson21 , L.A. Thomsen180 , E. Thomson134 , Y. Tian38 , R.E. Ticse Torres51 , V.O. Tikhomirov108,ao , Yu.A. Tikhonov120b,120a , S. Timoshenko110 , P. Tipton180 , S. Tisserant99 , K. Todome162 , S. Todorova-Nova5 , S. Todt46 , J. Tojo85 , S. Tokár28a , K. Tokushuku79 , E. Tolley123 , K.G. Tomiwa32c , M. Tomoto115 , L. Tompkins150,r , K. Toms116 , B. Tong57 , P. Tornambe50 , E. Torrence128 , H. Torres46 , E. Torró Pastor145 , C. Tosciri132 , J. Toth99,ac , F. Touchard99 , D.R. Tovey146 , C.J. Treado122 , T. Trefzger174 , F. Tresoldi153 , A. Tricoli29 , I.M. Trigger165a , S. Trincaz-Duvoid133 , M.F. Tripiana14 , W. Trischuk164 , B. Trocmé56 , A. Trofymov129 , C. 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Volpi14 , S.E. von Buddenbrock32c , E. Von Toerne24 , V. Vorobel140 , K. Vorobev110 , M. Vos171 , J.H. Vossebeld88 , N. Vranjes16 , M. Vranjes Milosavljevic16 , V. Vrba139 , M. Vreeswijk118 , T. Šfiligoj89 , R. Vuillermet35 , I. Vukotic36 , T. Ženiš28a , L. Živković16 , P. Wagner24 , W. Wagner179 , – 42 – J. Wagner-Kuhr112 , H. Wahlberg86 , S. Wahrmund46 , K. Wakamiya80 , V.M. Walbrecht113 , J. Walder87 , R. Walker112 , S.D. Walker91 , W. Walkowiak148 , V. Wallangen43a,43b , A.M. Wang57 , C. Wang58b,e , F. Wang178 , H. Wang18 , H. Wang3 , J. Wang154 , J. Wang59b , P. Wang41 , Q. Wang125 , R.-J. Wang133 , R. Wang58a , R. Wang6 , S.M. Wang155 , W.T. Wang58a , W. Wang15c,ae , W.X. Wang58a,ae , Y. Wang58a,al , Z. Wang58c , C. Wanotayaroj44 , A. Warburton101 , C.P. Ward31 , D.R. Wardrope92 , A. Washbrook48 , P.M. Watkins21 , A.T. Watson21 , M.F. Watson21 , G. Watts145 , S. Watts98 , B.M. Waugh92 , A.F. Webb11 , S. Webb97 , C. Weber180 , M.S. Weber20 , S.A. Weber33 , S.M. Weber59a , A.R. 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Zwalinski35 1 Department of Physics, University of Adelaide, Adelaide; Australia 2 Physics Department, SUNY Albany, Albany NY; United States of America 3 Department of Physics, University of Alberta, Edmonton AB; Canada 4 Department of Physics(a) , Ankara University, Ankara; Istanbul Aydin University(b) , Istanbul; Division of Physics(c) , TOBB University of Economics and Technology, Ankara; Turkey 5 LAPP, Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS/IN2P3, Annecy; France 6 High Energy Physics Division, Argonne National Laboratory, Argonne IL; United States of America 7 Department of Physics, University of Arizona, Tucson AZ; United States of America 8 Department of Physics, University of Texas at Arlington, Arlington TX; United States of America 9 Physics 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 – 43 – 12 Bahcesehir University(a) , Faculty of Engineering and Natural Sciences, Istanbul; Istanbul Bilgi University(b) , Faculty of Engineering and Natural Sciences, Istanbul; Department of Physics (c) , Bogazici University, Istanbul; Department of Physics Engineering(d) , Gaziantep University, Gaziantep; Turkey 13 Institute of Physics, Azerbaijan Academy of Sciences, Baku; Azerbaijan 14 Institut de Fı́sica d’Altes Energies (IFAE), Barcelona Institute of Science and Technology, Barcelona; Spain 15 Institute of High Energy Physics(a) , Chinese Academy of Sciences, Beijing; Physics Department(b) , Tsinghua University, Beijing; Department of Physics(c) , Nanjing University, Nanjing; University of Chinese Academy of Science (UCAS)(d) , Beijing; China 16 Institute of Physics, University of Belgrade, Belgrade; Serbia 17 Department for Physics and Technology, University of Bergen, Bergen; Norway JHEP05(2019)041 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 Centro de Investigaciónes, Universidad Antonio Nariño, Bogota; Colombia 23 Dipartimento di Fisica e Astronomia(a) , Università di Bologna, Bologna; INFN Sezione di Bologna(b) ; 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 Transilvania University of Brasov(a) , Brasov; Horia Hulubei National Institute of Physics and Nuclear Engineering(b) , Bucharest; Department of Physics(c) , Alexandru Ioan Cuza University of Iasi, Iasi; National Institute for Research and Development of Isotopic and Molecular Technologies(d) , Physics Department, Cluj-Napoca; University Politehnica Bucharest (e) , Bucharest; West University in Timisoara(f ) , Timisoara; Romania 28 Faculty of Mathematics(a) , Physics and Informatics, Comenius University, Bratislava; Department of Subnuclear Physics(b) , 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 Fı́sica, Universidad de Buenos Aires, Buenos Aires; Argentina 31 Cavendish Laboratory, University of Cambridge, Cambridge; United Kingdom 32 Department of Physics(a) , University of Cape Town, Cape Town; Department of Mechanical Engineering Science(b) , University of Johannesburg, Johannesburg; School of Physics(c) , University of the Witwatersrand, Johannesburg; South Africa 33 Department of Physics, Carleton University, Ottawa ON; Canada 34 Faculté des Sciences Ain Chock(a) , Réseau Universitaire de Physique des Hautes Energies — Université Hassan II, Casablanca; Centre National de l’Energie des Sciences Techniques Nucleaires (CNESTEN)(b) , Rabat; Faculté des Sciences Semlalia(c) , Université Cadi Ayyad, LPHEA-Marrakech; Faculté des Sciences(d) , Université Mohamed Premier and LPTPM, Oujda; Faculté des sciences(e) , Université Mohammed V, Rabat; Morocco 35 CERN, Geneva; Switzerland 36 Enrico Fermi Institute, University of Chicago, Chicago IL; United States of America 37 LPC, Université Clermont Auvergne, CNRS/IN2P3, Clermont-Ferrand; France 38 Nevis Laboratory, Columbia University, Irvington NY; United States of America 39 Niels Bohr Institute, University of Copenhagen, Copenhagen; Denmark 40 Dipartimento di Fisica(a) , Università della Calabria, Rende; INFN Gruppo Collegato di Cosenza (b) , Laboratori Nazionali di Frascati; Italy 41 Physics Department, Southern Methodist University, Dallas TX; United States of America – 44 – 42 Physics Department, University of Texas at Dallas, Richardson TX; United States of America 43 Department of Physics(a) , Stockholm University; Oskar Klein Centre(b) , Stockholm; Sweden 44 Deutsches Elektronen-Synchrotron DESY, Hamburg and Zeuthen; Germany 45 Lehrstuhl für Experimentelle Physik IV, Technische Universität Dortmund, Dortmund; Germany 46 Institut für Kern- und Teilchenphysik, Technische Universität Dresden, Dresden; Germany 47 Department of Physics, Duke University, Durham NC; United States of America 48 SUPA — School of Physics and Astronomy, University of Edinburgh, Edinburgh; United Kingdom 49 INFN e Laboratori Nazionali di Frascati, Frascati; Italy 50 Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg; Germany 51 II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen; Germany 52 Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève; Switzerland 53 Dipartimento di Fisica(a) , Università di Genova, Genova; INFN Sezione di Genova(b) ; Italy JHEP05(2019)041 54 II. Physikalisches Institut, Justus-Liebig-Universität Giessen, Giessen; Germany 55 SUPA — School of Physics and Astronomy, University of Glasgow, Glasgow; United Kingdom 56 LPSC, Université Grenoble Alpes, CNRS/IN2P3, Grenoble INP, Grenoble; France 57 Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge MA; United States of America 58 Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics (a) , University of Science and Technology of China, Hefei; Institute of Frontier and Interdisciplinary Science and Key Laboratory of Particle Physics and Particle Irradiation (MOE) (b) , Shandong University, Qingdao; School of Physics and Astronomy(c) , Shanghai Jiao Tong University, KLPPAC-MoE, SKLPPC, Shanghai; Tsung-Dao Lee Institute(d) , Shanghai; China 59 Kirchhoff-Institut für Physik(a) , Ruprecht-Karls-Universität Heidelberg, Heidelberg; Physikalisches Institut(b) , Ruprecht-Karls-Universität Heidelberg, Heidelberg; Germany 60 Faculty of Applied Information Science, Hiroshima Institute of Technology, Hiroshima; Japan 61 Department of Physics(a) , Chinese University of Hong Kong, Shatin, N.T., Hong Kong; Department of Physics(b) , University of Hong Kong, Hong Kong; Department of Physics and Institute for Advanced Study(c) , Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong; China 62 Department of Physics, National Tsing Hua University, Hsinchu; Taiwan 63 Department of Physics, Indiana University, Bloomington IN; United States of America 64 INFN Gruppo Collegato di Udine(a) , Sezione di Trieste, Udine; ICTP(b) , Trieste; Dipartimento Politecnico di Ingegneria e Architettura(c) , Università di Udine, Udine; Italy 65 INFN Sezione di Lecce(a) ; Dipartimento di Matematica e Fisica(b) , Università del Salento, Lecce; Italy 66 INFN Sezione di Milano(a) ; Dipartimento di Fisica(b) , Università di Milano, Milano; Italy 67 INFN Sezione di Napoli(a) ; Dipartimento di Fisica(b) , Università di Napoli, Napoli; Italy 68 INFN Sezione di Pavia(a) ; Dipartimento di Fisica(b) , Università di Pavia, Pavia; Italy 69 INFN Sezione di Pisa(a) ; Dipartimento di Fisica E. Fermi(b) , Università di Pisa, Pisa; Italy 70 INFN Sezione di Roma(a) ; Dipartimento di Fisica(b) , Sapienza Università di Roma, Roma; Italy 71 INFN Sezione di Roma Tor Vergata(a) ; Dipartimento di Fisica(b) , Università di Roma Tor Vergata, Roma; Italy 72 INFN Sezione di Roma Tre(a) ; Dipartimento di Matematica e Fisica(b) , Università Roma Tre, Roma; Italy 73 INFN-TIFPA(a) ; Università degli Studi di Trento(b) , Trento; Italy 74 Institut für Astro- und Teilchenphysik, Leopold-Franzens-Universität, Innsbruck; Austria 75 University of Iowa, Iowa City IA; United States of America 76 Department of Physics and Astronomy, Iowa State University, Ames IA; United States of America 77 Joint Institute for Nuclear Research, Dubna; Russia 78 Departamento de Engenharia Elétrica(a) , Universidade Federal de Juiz de Fora (UFJF), Juiz de Fora; Universidade Federal do Rio De Janeiro COPPE/EE/IF(b) , Rio de Janeiro; Universidade Federal de São João del Rei (UFSJ)(c) , São João del Rei; Instituto de Fı́sica(d) , Universidade de São Paulo, São Paulo; Brazil – 45 – 79 KEK, High Energy Accelerator Research Organization, Tsukuba; Japan 80 Graduate School of Science, Kobe University, Kobe; Japan 81 AGH University of Science and Technology(a) , Faculty of Physics and Applied Computer Science, Krakow; Marian Smoluchowski Institute of Physics(b) , Jagiellonian University, Krakow; Poland 82 Institute of Nuclear Physics Polish Academy of Sciences, Krakow; Poland 83 Faculty of Science, Kyoto University, Kyoto; Japan 84 Kyoto University of Education, Kyoto; Japan 85 Research Center for Advanced Particle Physics and Department of Physics, Kyushu University, Fukuoka; Japan 86 Instituto de Fı́sica La Plata, Universidad Nacional de La Plata and CONICET, La Plata; Argentina 87 Physics Department, Lancaster University, Lancaster; United Kingdom 88 Oliver Lodge Laboratory, University of Liverpool, Liverpool; United Kingdom JHEP05(2019)041 89 Department of Experimental Particle Physics, Jožef Stefan Institute and Department of Physics, University of Ljubljana, Ljubljana; Slovenia 90 School of Physics and Astronomy, Queen Mary University of London, London; United Kingdom 91 Department of Physics, Royal Holloway University of London, Egham; United Kingdom 92 Department of Physics and Astronomy, University College London, London; United Kingdom 93 Louisiana Tech University, Ruston LA; United States of America 94 Fysiska institutionen, Lunds universitet, Lund; Sweden 95 Centre de Calcul de l’Institut National de Physique Nucléaire et de Physique des Particules (IN2P3), Villeurbanne; France 96 Departamento de Fı́sica Teorica C-15 and CIAFF, Universidad Autónoma de Madrid, Madrid; Spain 97 Institut für Physik, Universität Mainz, Mainz; Germany 98 School of Physics and Astronomy, University of Manchester, Manchester; United Kingdom 99 CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille; France 100 Department of Physics, University of Massachusetts, Amherst MA; United States of America 101 Department of Physics, McGill University, Montreal QC; Canada 102 School of Physics, University of Melbourne, Victoria; Australia 103 Department of Physics, University of Michigan, Ann Arbor MI; United States of America 104 Department of Physics and Astronomy, Michigan State University, East Lansing MI; United States of America 105 B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk; Belarus 106 Research Institute for Nuclear Problems of Byelorussian State University, Minsk; Belarus 107 Group of Particle Physics, University of Montreal, Montreal QC; Canada 108 P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow; Russia 109 Institute for Theoretical and Experimental Physics of the National Research Centre Kurchatov Institute, Moscow; Russia 110 National Research Nuclear University MEPhI, Moscow; Russia 111 D.V. Skobeltsyn Institute of Nuclear Physics, M.V. Lomonosov Moscow State University, Moscow; Russia 112 Fakultät für Physik, Ludwig-Maximilians-Universität München, München; Germany 113 Max-Planck-Institut für Physik (Werner-Heisenberg-Institut), München; Germany 114 Nagasaki Institute of Applied Science, Nagasaki; Japan 115 Graduate School of Science and Kobayashi-Maskawa Institute, Nagoya University, Nagoya; Japan 116 Department of Physics and Astronomy, University of New Mexico, Albuquerque NM; United States of America 117 Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen; Netherlands 118 Nikhef National Institute for Subatomic Physics and University of Amsterdam, Amsterdam; Netherlands 119 Department of Physics, Northern Illinois University, DeKalb IL; United States of America – 46 – 120 Budker Institute of Nuclear Physics and NSU(a) , SB RAS, Novosibirsk; Novosibirsk State University Novosibirsk(b) ; Russia 121 Institute for High Energy Physics of the National Research Centre Kurchatov Institute, Protvino; Russia 122 Department of Physics, New York University, New York NY; United States of America 123 Ohio State University, Columbus OH; United States of America 124 Faculty of Science, Okayama University, Okayama; Japan 125 Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman OK; United States of America 126 Department of Physics, Oklahoma State University, Stillwater OK; United States of America 127 Palacký University, RCPTM, Joint Laboratory of Optics, Olomouc; Czech Republic 128 Center for High Energy Physics, University of Oregon, Eugene OR; United States of America JHEP05(2019)041 129 LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay; France 130 Graduate School of Science, Osaka University, Osaka; Japan 131 Department of Physics, University of Oslo, Oslo; Norway 132 Department of Physics, Oxford University, Oxford; United Kingdom 133 LPNHE, Sorbonne Université, Paris Diderot Sorbonne Paris Cité, CNRS/IN2P3, Paris; France 134 Department of Physics, University of Pennsylvania, Philadelphia PA; United States of America 135 Konstantinov Nuclear Physics Institute of National Research Centre “Kurchatov Institute”, PNPI, St. Petersburg; Russia 136 Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh PA; United States of America 137 Laboratório de Instrumentação e Fı́sica Experimental de Partı́culas — LIP (a) ; Departamento de Fı́sica(b) , Faculdade de Ciências, Universidade de Lisboa, Lisboa; Departamento de Fı́sica (c) , Universidade de Coimbra, Coimbra; Centro de Fı́sica Nuclear da Universidade de Lisboa (d) , Lisboa; Departamento de Fı́sica(e) , Universidade do Minho, Braga; Departamento de Fı́sica Teorica y del Cosmos(f ) , Universidad de Granada, Granada (Spain); Dep Fı́sica and CEFITEC of Faculdade de Ciências e Tecnologia(g) , Universidade Nova de Lisboa, Caparica; Portugal 138 Institute of Physics of the Czech Academy of Sciences, Prague; Czech Republic 139 Czech Technical University in Prague, Prague; Czech Republic 140 Charles University, Faculty of Mathematics and Physics, Prague; Czech Republic 141 Particle Physics Department, Rutherford Appleton Laboratory, Didcot; United Kingdom 142 IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette; France 143 Santa Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz CA; United States of America 144 Departamento de Fı́sica(a) , Pontificia Universidad Católica de Chile, Santiago; Departamento de Fı́sica(b) , Universidad Técnica Federico Santa Marı́a, Valparaı́so; Chile 145 Department of Physics, University of Washington, Seattle WA; United States of America 146 Department of Physics and Astronomy, University of Sheffield, Sheffield; United Kingdom 147 Department of Physics, Shinshu University, Nagano; Japan 148 Department Physik, Universität Siegen, Siegen; Germany 149 Department of Physics, Simon Fraser University, Burnaby BC; Canada 150 SLAC National Accelerator Laboratory, Stanford CA; United States of America 151 Physics Department, Royal Institute of Technology, Stockholm; Sweden 152 Departments of Physics and Astronomy, Stony Brook University, Stony Brook NY; United States of America 153 Department of Physics and Astronomy, University of Sussex, Brighton; United Kingdom 154 School of Physics, University of Sydney, Sydney; Australia 155 Institute of Physics, Academia Sinica, Taipei; Taiwan 156 E. Andronikashvili Institute of Physics(a) , Iv. Javakhishvili Tbilisi State University, Tbilisi; High Energy Physics Institute(b) , Tbilisi State University, Tbilisi; Georgia 157 Department of Physics, Technion, Israel Institute of Technology, Haifa; Israel – 47 – 158 Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv University, Tel Aviv; Israel 159 Department of Physics, Aristotle University of Thessaloniki, Thessaloniki; Greece 160 International Center for Elementary Particle Physics and Department of Physics, University of Tokyo, Tokyo; Japan 161 Graduate School of Science and Technology, Tokyo Metropolitan University, Tokyo; Japan 162 Department of Physics, Tokyo Institute of Technology, Tokyo; Japan 163 Tomsk State University, Tomsk; Russia 164 Department of Physics, University of Toronto, Toronto ON; Canada 165 TRIUMF(a) , Vancouver BC; Department of Physics and Astronomy(b) , York University, Toronto ON; Canada 166 Division of Physics and Tomonaga Center for the History of the Universe, Faculty of Pure and JHEP05(2019)041 Applied Sciences, University of Tsukuba, Tsukuba; Japan 167 Department of Physics and Astronomy, Tufts University, Medford MA; United States of America 168 Department of Physics and Astronomy, University of California Irvine, Irvine CA; United States of America 169 Department of Physics and Astronomy, University of Uppsala, Uppsala; Sweden 170 Department of Physics, University of Illinois, Urbana IL; United States of America 171 Instituto de Fı́sica Corpuscular (IFIC), Centro Mixto Universidad de Valencia — CSIC, Valencia; Spain 172 Department of Physics, University of British Columbia, Vancouver BC; Canada 173 Department of Physics and Astronomy, University of Victoria, Victoria BC; Canada 174 Fakultät für Physik und Astronomie, Julius-Maximilians-Universität Würzburg, Würzburg; Germany 175 Department of Physics, University of Warwick, Coventry; United Kingdom 176 Waseda University, Tokyo; Japan 177 Department of Particle Physics, Weizmann Institute of Science, Rehovot; Israel 178 Department of Physics, University of Wisconsin, Madison WI; United States of America 179 Fakultät für Mathematik und Naturwissenschaften, Fachgruppe Physik, Bergische Universität Wuppertal, Wuppertal; Germany 180 Department of Physics, Yale University, New Haven CT; United States of America 181 Yerevan Physics Institute, Yerevan; Armenia a Also at Borough of Manhattan Community College, City University of New York, NY; United States of America b Also at California State University, East Bay; United States of America c Also at Centre for High Performance Computing, CSIR Campus, Rosebank, Cape Town; South Africa d Also at CERN, Geneva; Switzerland e Also at CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille; France f Also at Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève; Switzerland g Also at Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona; Spain h Also at Departamento de Fı́sica Teorica y del Cosmos, Universidad de Granada, Granada (Spain); Spain i Also at Departamento de Fı́sica, Instituto Superior Técnico, Universidade de Lisboa, Lisboa; Portugal j Also at Department of Applied Physics and Astronomy, University of Sharjah, Sharjah; United Arab Emirates k Also at Department of Financial and Management Engineering, University of the Aegean, Chios; Greece l Also at Department of Physics and Astronomy, University of Louisville, Louisville, KY; United States of America – 48 – m Also at Department of Physics and Astronomy, University of Sheffield, Sheffield; United Kingdom n Also at Department of Physics, California State University, Fresno CA; United States of America o Also at Department of Physics, California State University, Sacramento CA; United States of America p Also at Department of Physics, King’s College London, London; United Kingdom q Also at Department of Physics, St. Petersburg State Polytechnical University, St. Petersburg; Russia r Also at Department of Physics, Stanford University; United States of America s Also at Department of Physics, University of Fribourg, Fribourg; Switzerland t Also at Department of Physics, University of Michigan, Ann Arbor MI; United States of America u Also at Giresun University, Faculty of Engineering, Giresun; Turkey v Also at Graduate School of Science, Osaka University, Osaka; Japan JHEP05(2019)041 w Also at Hellenic Open University, Patras; Greece x Also at Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest; Romania y Also at II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen; Germany z Also at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona; Spain aa Also at Institut für Experimentalphysik, Universität Hamburg, Hamburg; Germany ab Also at Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen; Netherlands ac Also at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest; Hungary ad Also at Institute of Particle Physics (IPP); Canada ae Also at Institute of Physics, Academia Sinica, Taipei; Taiwan af Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku; Azerbaijan ag Also at Institute of Theoretical Physics, Ilia State University, Tbilisi; Georgia ah Also at Instituto de Fı́sica Teórica de la Universidad Autónoma de Madrid; Spain ai Also at Istanbul University, Dept. of Physics, Istanbul; Turkey aj Also at LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay; France ak Also at Louisiana Tech University, Ruston LA; United States of America al Also at LPNHE, Sorbonne Université, Paris Diderot Sorbonne Paris Cité, CNRS/IN2P3, Paris; France am Also at Manhattan College, New York NY; United States of America an Also at Moscow Institute of Physics and Technology State University, Dolgoprudny; Russia ao Also at National Research Nuclear University MEPhI, Moscow; Russia ap Also at Physics Dept, University of South Africa, Pretoria; South Africa aq Also at Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg; Germany ar Also at School of Physics, Sun Yat-sen University, Guangzhou; China as Also at The City College of New York, New York NY; United States of America at Also at The Collaborative Innovation Center of Quantum Matter (CICQM), Beijing; China au Also at Tomsk State University, Tomsk, and Moscow Institute of Physics and Technology State University, Dolgoprudny; Russia av Also at TRIUMF, Vancouver BC; Canada aw Also at Universita di Napoli Parthenope, Napoli; Italy ∗ Deceased – 49 –