Published for SISSA by Springer Received: December 20, 2018 Revised: April 15, 2019 Accepted: May 6, 2019 Published: May 27, 2019 Search for single production of vector-like quarks √ decaying into W b in pp collisions at s = 13 TeV JHEP05(2019)164 with the ATLAS detector The ATLAS collaboration E-mail: atlas.publications@cern.ch Abstract: A search for singly produced vector-like quarks Q, where Q can be either a T quark with charge +2/3 or a Y quark with charge −4/3, is performed in proton– proton collision data at a centre-of-mass energy of 13 TeV corresponding to an integrated luminosity of 36.1 fb−1 , recorded with the ATLAS detector at the LHC in 2015 and 2016. The analysis targets Q → W b decays where the W boson decays leptonically. No significant deviation from the expected Standard Model background is observed. Upper limits are set on the QW b coupling strength and the mixing between the Standard Model sector and a singlet T quark or a Y quark from a (B, Y ) doublet or a (T, B, Y ) triplet, taking into account the interference effects with the Standard Model background. The upper limits set on the mixing angle are as small as | sin θL | = 0.18 for a singlet T quark of mass 800 GeV, | sin θR | = 0.17 for a Y quark of mass 800 GeV in a (B, Y ) doublet model and | sin θL | = 0.16 for a Y quark of mass 800 GeV in a (T, B, Y ) triplet model. Within a (B, Y ) doublet model, the limits set on the mixing parameter | sin θR | are comparable with the exclusion limits from electroweak precision observables in the mass range between about 900 GeV and 1250 GeV. Keywords: Exotics, Hadron-Hadron scattering (experiments) ArXiv ePrint: 1812.07343 Open Access, Copyright CERN, https://doi.org/10.1007/JHEP05(2019)164 for the benefit of the ATLAS Collaboration. Article funded by SCOAP3 . Contents 1 Introduction 1 2 ATLAS detector 5 3 Physics object reconstruction 5 4 Background and signal modelling 8 JHEP05(2019)164 4.1 Background modelling 8 4.2 Signal modelling 10 5 Event selection and background estimation 14 5.1 Signal and control regions definition 14 5.2 Estimation of non-prompt and fake lepton backgrounds 15 5.3 Signal candidate mass reconstruction 15 6 Systematic uncertainties 17 6.1 Experimental uncertainties 17 6.2 Theoretical modelling uncertainties 20 7 Results 21 7.1 Statistical interpretation 21 7.2 Fit results 22 7.3 Limits on the VLQ production 23 8 Conclusion 29 The ATLAS collaboration 39 1 Introduction Vector-like quarks (VLQs) are hypothetical spin-1/2 coloured particles with left-handed and right-handed components that transform in the same way under the Standard Model (SM) gauge group. Therefore, their masses are not generated by a Yukawa coupling to the Higgs boson [1]. While the discovery of the Higgs boson (H) at the Large Hadron Collider (LHC) [2, 3] excludes a perturbative, fourth generation of chiral quarks [4], since their contribution to loop-mediated Higgs boson couplings would significantly alter the production cross-section and the decay rates of the Higgs boson, the effects on Higgs boson production and decay rates from loop diagrams including VLQs are much smaller than the uncertainty in the current measurements [1]. In many models, VLQs mix mainly –1– q′ q W W ∼ cW b L/R or sin θL/R ∼ cW b L/R or sin θL/R Y /T b b g b JHEP05(2019)164 Figure 1. Leading-order Feynman diagram for single Y /T production in W b fusion and subsequent decay into W b. The production amplitude scales with sin θL,R [1] or cW b L,R [13, 14] as described in the text. with the SM quarks of the third generation due to the large masses of the bottom and top quarks [5, 6]. Vector-like quarks appear in several extensions of the SM that address the hierarchy problem, such as extra dimensions [7], composite Higgs [8, 9] and Little Higgs [10] models, where they are added to the SM in multiplets. They can also appear in supersymmetric models [11] and are able to stabilise the electroweak vacuum [12]. This analysis concentrates on searches for single production of heavy vector-like quarks Q produced in proton–proton (pp) collisions via W b fusion, pp → Qqb + X, with a subse- quent decay Q → W b. Here Q can be either a T quark with charge +2/3 or a Y quark with charge −4/3 or their antiquarks. An example of a leading-order Feynman diagram is presented in figure 1. Vector-like T quarks can belong to any weak-isospin multiplet, while Y quarks cannot exist as singlets. The interpretation used in this analysis focuses on Y quarks from a (B, Y ) doublet or a (T, B, Y ) triplet, and on singlet T quarks, since T quarks in a (T, B, Y ) triplet do not couple to W b [1]. For singlet T quarks, the branching ratios (Bs) are model- and mass-dependent, but in the high-mass limit, which is considered in this analysis, they converge towards 2:1:1 (W b:Zt:Ht) [1]. Due to its charge, the Y quark can decay only into W b and therefore B(Y → W b) = 100%. As a consequence, Y quarks can be singly produced in pp collisions only via W b fusion, while T quarks can be produced not only by W b fusion but also by Zt and Ht fusion. Single production of vector-like quarks is enabled by their coupling to SM quarks. As a result, searches for singly produced VLQs in pp collisions can be used to probe these couplings as a function of the VLQ mass, whereas searches for pair-produced VLQs allow limits to be set on VLQ masses; these mass limits are rather insensitive to the couplings, because the signals are produced through strong couplings. At high VLQ masses, single VLQ production can become the dominant production mechanism at the LHC, depending on the strength of the Qqb coupling. Results are presented here for two different models that use different formulations of the Lagrangian that describes these new particles and their interactions. In the model discussed in ref. [1] (renormalisable theory), a mixing term between the SM and vector-like quarks is introduced in a renormalisable extension of the –2– SM, while refs. [13, 14] (non-renormalisable theory) use a phenomenological Lagrangian that is parameterised with coupling terms, but is non-renormalisable. The main difference between these approaches is that the Lagrangian in refs. [13, 14] has additional terms that allow larger production cross-sections, while the Lagrangian in ref. [1] gives a complete description of the dependence of the B on the multiplet dimension, with left- and right- handed mixing angles θL and θR as model parameters. Within a given multiplet, θL and θR are functionally related. Therefore, a given value of either the left- or right-handed mixing angle fully determines all Bs for any given heavy-quark mass. For the interpretation in terms of coupling parameters cW L b and cW b as introduced in refs. [13, 14], assumptions R must be made about the Q → W b, Q → Zt and Q → Ht Bs in case of Q = T . The JHEP05(2019)164 relative contribution of the left- and right-handed components of the mixing and coupling also depends on the dimension of the VLQ multiplet. For T singlets, only the left-handed component (sin θL or cW b L ) contributes. For a (B, Y ) doublet model, results are interpreted in terms of the dominant right-handed (sin θR ) component; for a (T, B, Y ) triplet model, results are interpreted in terms of the dominant left-handed (sin θL ) component [1]. The formulation of ref. [1] also allows within a certain multiplet model a comparison of the mixing angles with constraints from electroweak precision observables, such as the ratio Rb of the partial width for Z → bb̄ to the total hadronic Z-boson width and the oblique parameters S and T [15]. A comparison of the respective Lagrangians of the renormalisable models described in ref. [1] and the non-renormalisable models described in refs. [13, 14] √ yields a simple relation between sin θL,R and cW b Wb L,R : cL,R = 2 sin θL,R for the T singlet W b model and (B, Y ) doublet model and cL = 2 sin θL for the (T, B, Y ) triplet model. This relationship is only true within the regime of validity of the renormalisable formulation, and if one considers only the interactions between Q, W and b. The ATLAS and CMS Collaborations have published searches for single and pair pro- duction of vector-like T quarks in all three decay channels [16–34] and set 95% confidence level (CL) lower limits on T - and Y -quark masses. Assuming a B of 100% for the corre- sponding decay channel, the best observed T -quark mass limits are mT > 1430 GeV for T → Ht [23], 1340 GeV for T → Zt [33] and 1350 GeV for T → W b [20], independent of the size of the cW b coupling strengths. In ref. [34], seven individual analyses searching for B B̄ or T T̄ pair production were combined improving model-independent cross-section limits significantly over individual analyses. T quarks with a mass lower than 1310 GeV are excluded for any combination of decays into SM particles by this analysis. The observed lower limit on the pair-produced Y -quark mass is 1350 GeV [26]. These searches also report limits as a function of the assumed Bs. The best observed limits are mT > 1310 GeV and mT > 1280 GeV for a weak-isospin doublet [23] and singlet [27] respectively. Searches for single production of T quarks with decays into Zt [31] and single T /Y -quark production with decays into W b [22] were carried out by the ATLAS Collaboration using the Run-1 √ pp dataset at a centre-of-mass energy s = 8 TeV. In the T → Zt decay channel, assum- ing a mixing parameter sin θL as low as 0.7, T quarks with massesqbetween 450 GeV and 650 GeV are excluded [31], while for a QW b coupling strength of (cW b 2 Wb 2 L ) + (cR ) = 1, the observed lower limit on the T -quark mass assuming B(T → W b) = 0.5 is 950 GeV [22]. –3– The CMS Collaboration studied single T - and Y -quark production using the Run-2 dataset √ at s = 13 TeV collected in 2015 [25, 28–30, 32] and set upper limits on the single-T -quark production cross-section times B(T → Ht) that vary between 0.31 pb and 0.93 pb for T - quark masses in the range 1000–1800 GeV [32], as well as on the single-T -quark production cross-section times B(T → Zt) that vary between 0.98 pb and 0.15 pb (0.6 pb and 0.13 pb) for T -quark masses in the range 700–1700 GeV in the right-handed (left-handed) T b (T t) production channel [25]. For a mass of 1000 GeV, a T -quark production cross-section times branching fraction above 0.8 pb (0.7 pb) is excluded for the T → Ht decay channel assum- ing left-handed (right-handed) coupling of the T quark to SM particles [28]. For Y quarks with a coupling of 0.5 and B(Y → W b) = 1, the observed (expected) lower mass limit is JHEP05(2019)164 1.40 (1.0) TeV [29]. This paper describes a search for Q → W b (Q = T or Y ) production, with the prompt W boson decaying leptonically, giving a lepton + jets signature characterised by the pres- ence of exactly one electron or muon,1 three or more jets and missing transverse momentum from the escaping neutrino. It is assumed that T quarks are produced in W b fusion only. For single production of a T quark, Zt fusion could in principle contribute as well, but can be neglected for this T -singlet search. For equal values of the T Zt and T W b couplings, the cross-section for Zt fusion is about one order of magnitude smaller than for W b fusion [14]. √ For the T -singlet case, the T Zt coupling is about a factor of 2 smaller than the T W b coupling and as a result B(T → Zt) is about a factor of two smaller than B(T → W b). Since the single-VLQ production cross-section scales with coupling squared, the Zt fusion cross-section is lowered by another factor of two compared to the W b fusion cross-section. In addition, the selection efficiency for tZ → T → W b events in the search presented here is about a factor of two smaller than for bW → T → W b, because in tZ → T → W b the accompanying top quark from the gluon splitting leads to additional jets in the final state. The analysis is optimised to search for massive VLQs with a high-momentum b-jet in the final state. The b-jet and the charged lepton originating from the Q decay are approximately back-to-back in the transverse plane since both originate from the decay of a heavy object. The outgoing light quark in the process depicted in figure 1 often produces a jet in the forward region of the detector. The second b-jet from the gluon splitting may be observed in either the forward or central region. Since this b-jet is typically of low energy, it often falls outside the detector acceptance. The main background processes with a single-lepton signature arise from top-quark pair (tt̄) production, single-top-quark production and W -boson production in association with jets (W +jets), with smaller contributions from Z-boson production in association with jets (Z+jets) and from diboson (W W , W Z, ZZ) production. Multijet events also contribute to the selected sample via the misidentification of a jet or a photon as an electron or the presence of a non-prompt electron or muon. To estimate the backgrounds from tt̄ and W +jets events in a consistent and robust fashion, two control regions (CRs) are defined. They are chosen to be orthogonal to the signal region (SR) in order to provide independent data samples enriched in particular background sources. The reconstructed mass of the heavy-quark candidate is used as the discriminating variable in a binned likelihood fit to 1 Electrons and muons from decays of τ -leptons from W → τ ν are taken into account in the selection. –4– test for the presence of a signal, taking into account the interference with SM background processes. A background-only fit to the SR and CRs is also performed to determine whether the observed event yield in the SR is compatible with the corresponding SM background expectation. The results of the binned profile likelihood fits are used to estimate the cW b L,R coupling limits for Y/T quarks. In the case of the right-handed Y quark in a (Y, B) doublet model, where the interference effect with the SM is much smaller than for the other models under consideration, a limit on the production cross-section is also quoted. 2 ATLAS detector JHEP05(2019)164 The ATLAS detector [35] at the LHC is a multipurpose particle detector with a forward- backward symmetric cylindrical geometry that covers nearly the entire solid angle around the collision point.2 It consists of an inner tracking detector (ID) surrounded by a thin superconducting solenoid magnet producing an axial 2 T magnetic field, fine-granularity electromagnetic (EM) and hadronic calorimeters, and a muon spectrometer (MS) incorpo- rating three large air-core toroid magnet assemblies. The ID consists of a high-granularity silicon pixel detector, including an insertable B-layer [36, 37] added in 2014, and a sil- icon microstrip tracker, together providing charged-particle tracking information in the pseudorapidity region |η| < 2.5. It is surrounded by a transition radiation tracker, which enhances electron identification information in the region |η| < 2.0. The EM calorimeter is a lead/liquid-argon sampling detector, divided into a barrel region (|η| < 1.475) and two endcap regions (1.375 < |η| < 3.2), which provides energy measurements of electromagnetic showers. Hadron calorimetry is also based on the sampling technique, with either scintil- lator tiles or liquid argon as the active medium and with steel, copper, or tungsten as the absorber material. The calorimeters cover the region |η| < 4.9. The MS measures the de- flection of muons within |η| < 2.7 using three layers of high-precision tracking chambers lo- cated in a toroidal field of approximately 0.5 T and 1 T in the central and endcap regions re- spectively. The MS is also instrumented with separate trigger chambers covering |η| < 2.4. A two-level trigger system [38], using custom hardware followed by a software-based level, is used to reduce the trigger rate to a maximum of around 1 kHz for offline data storage. 3 Physics object reconstruction The data used in this search correspond to an integrated luminosity of 36.1 fb−1 of pp colli- √ sions at a centre-of-mass energy of s = 13 TeV recorded in 2015 and 2016 with the ATLAS detector. Only data-taking periods with stable beam collisions and all relevant ATLAS de- tector components functioning normally are considered. In this dataset, the average number of simultaneous pp interactions per bunch crossing, or ‘pile-up’, is approximately 24. 2 ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP) in the centre of the detector. The positive x-axis is defined by the direction from the IP to the centre of the LHC ring, with the positive y-axis pointing upwards, while the beam direction defines the z-axis. Cylindrical coordinates (r, φ) are used in the transverse plane, φ being the azimuthal angle around the z-axis. The pseudorapidity η is defined in terms of the polar angle θ by η = − ln tan(θ/2). The transverse momentum (pT ) is defined relative to the beam axis and is calculated as pT = p sin(θ). –5– The final states considered in this search require the presence of one charged lepton (electron or muon) candidate and multiple hadronic jets. Single-electron and single-muon triggers with low transverse-momentum (pT ) thresholds and lepton isolation requirements (in 2016 only) are combined in a logical OR with higher-threshold triggers without any iso- lation requirements to give maximum efficiency. For electrons, triggers with a pT threshold of 24 (26) GeV in 2015 (2016) and isolation requirements (in 2016 only) are used along with triggers with a 60 GeV threshold and no isolation requirement, and with a 120 (140) GeV threshold with looser identification criteria. For muons, triggers with pT thresholds of 20 (26) GeV and isolation requirements in 2015 (2016) are combined with a trigger that has a pT threshold of 50 GeV and no isolation requirements in both years. In addition, JHEP05(2019)164 events must have at least one reconstructed vertex with two or more tracks with pT above 0.4 GeV that is consistent with the beam-collision region in the x–y plane. If multiple ver- tices are reconstructed, the vertex with the largest sum of the squared pT of its associated tracks is taken as the primary vertex. For the final states considered in this analysis, the vertex reconstruction and selection efficiency is close to 100%. Electron candidates [39–41] are reconstructed from isolated energy deposits (clus- ters) in the EM calorimeter, each matched to a reconstructed ID track, within the fidu- cial region of |ηcluster | < 2.47, where ηcluster is the pseudorapidity of the centroid of the calorimeter energy deposit associated with the electron candidate. A veto is placed on elec- trons in the transition region between the barrel and endcap electromagnetic calorimeters, 1.37 < |ηcluster | < 1.52. Electrons must satisfy the tight likelihood identification criterion, based on shower-shape and track-cluster matching variables, and must have a transverse energy ET = Ecluster / cosh(ηtrack ) > 25 GeV, where Ecluster is the electromagnetic cluster energy and ηtrack the track pseudorapidity. Muons are reconstructed [42] by combining a track reconstructed in the ID with one in the MS, using the complete track information from both detectors and accounting for the effects of energy loss and multiple scattering in the material of the detector structure. The muon candidates must satisfy the medium selection criteria [42] and are required to be in the central region of |η| < 2.5. To reduce the contri- bution of leptons from hadronic decays (non-prompt leptons), electrons and muons must satisfy isolation criteria that include both track and calorimeter information, and are tuned to give an overall efficiency of 98%, independent of the pT of the lepton. Electron and muon candidates are required to be isolated from additional tracks within a cone around their p directions with a radius of ∆R ≡ (∆η)2 + (∆φ)2 with ∆R = min(0.2, 10 GeV/pT ) [40] for electrons and ∆R = min(0.3, 10 GeV/pT ) for muons [42]. The lepton calorimeter-based isolation variable is defined as the sum of the calorimeter transverse energy deposits in a cone of size ∆R = 0.2, after subtracting the contribution from the energy deposit of the lepton itself and correcting for pile-up effects, divided by the lepton pT . The significance of the transverse impact parameter d0 , calculated relative to the measured beam-line position, is required to satisfy |d0 /σ(d0 )| < 5 for electrons and |d0 /σ(d0 )| < 3 for muons, where σ(d0 ) is the uncertainty in d0 . Finally, the lepton tracks are matched to the primary vertex of the event by requiring the longitudinal impact parameter z0 to satisfy |z0 sin θtrack | < 0.5 mm, where θtrack is the polar angle of the track.3 3 The longitudinal impact parameter z0 is the difference between the longitudinal position of the track along the beam line at the point where the transverse impact parameter (d0 ) is measured and the longitu- dinal position of the primary vertex. –6– The leptons satisfying the criteria described above are used in the selection of events in the signal and control regions. The estimation of background from non-prompt and fake leptons with the Matrix Method [43], described in section 5.2, uses ‘loose’ leptons in addi- tion to the above ‘tight’ leptons, where the tight sample is a subset of the loose sample. The ‘loose’ selection requires that the muon (electron) satisfies the medium (likelihood medium) requirements, but does not need to satisfy isolation criteria as defined in refs. [40, 42]. Jets are reconstructed from three-dimensional topological calorimeter energy clus- ters [44] using the anti-kt algorithm [45, 46] with a radius parameter of 0.4 [47]. Each topological cluster is calibrated to the electromagnetic energy scale prior to jet reconstruc- tion. The reconstructed jets from the clusters are then calibrated to the particle level JHEP05(2019)164 by the application of corrections derived from simulation and from dedicated calibration √ samples of pp collision data at s = 13 TeV [48, 49]. Data quality criteria are imposed to identify jets arising from non-collision sources or detector noise, and any event containing at least one such jet is removed [50]. Finally, jets considered in this analysis are required to have pT > 25 GeV. The pseudorapidity acceptance for jets differs between different selections: central jets are required to have |η| < 2.5, while forward jets are defined to have 2.5 < |η| < 4.5. Furthermore, jets with a pT < 60 GeV and |η| < 2.4 are required to satisfy criteria implemented in the jet vertex tagger algorithm [51] designed to select jets that originate from the hard scattering and reduce the effect of in-time pile-up. The identification of jets from b-quark decays (b-tagging) is beneficial in this analysis. To identify (tag) jets containing b-hadrons (henceforth referred to as b-jets), a multivariate discriminant is used that combines information about the impact parameters of inner- detector tracks associated with the jet, the presence of displaced secondary vertices, and the reconstructed flight paths of b- and c-hadrons inside the jet [52–55]. Jets are considered to be b-tagged if the value of the multivariate discriminant is larger than a certain threshold. The criterion in use is only calculated for central jets (|η| < 2.5) with pT > 25 GeV and has an efficiency of approximately 85% for b-jets in simulated tt̄ events. The rejection factor against jets originating from light quarks and gluons (henceforth referred to as light- flavour jets) is about 34, and that against jets originating from charm quarks (c-jets) is about 3 [54], determined in simulated tt̄ events. Correction factors are defined to correct the tagging rates in the simulation to match the efficiencies measured in the data control samples [54, 56]. To avoid counting a single detector response as two objects, an overlap removal proce- dure is used. Jets overlapping with identified electron candidates within a cone of ∆R = 0.2 are removed, as the jet and the electron are very likely to be the same physics object. If the nearest jet surviving this requirement is within ∆R = 0.4 of an electron, the electron is discarded, to ensure it is sufficiently separated from nearby jet activity. Muons are removed if they are separated from the nearest jet by ∆R < 0.4, to reduce the background from muons from heavy-flavour hadron decays inside jets. However, if this jet has fewer than three associated tracks, the muon is kept and the jet is removed instead; this avoids an inefficiency for high-energy muons undergoing significant energy loss in the calorimeter. The missing transverse momentum E ~ miss (with magnitude E miss ) is a measure of the T T momentum of the escaping neutrinos. It is defined as the negative vector sum of the trans- –7– verse momenta of all selected and calibrated objects (electrons, muons, photons, hadroni- cally decaying τ -leptons and jets) in the event, including a term to account for energy from soft particles which are not associated with any of the selected objects [57]. This soft term is calculated from inner-detector tracks matched to the selected primary vertex to make it resilient to contamination from pile-up interactions [57]. 4 Background and signal modelling Monte Carlo (MC) simulation samples are used to model the expected signal and SM background distributions. The MC samples were processed either through the full ATLAS JHEP05(2019)164 detector simulation [58] based on Geant4 [59] or through a faster simulation making use of parameterised showers in the calorimeters [60]. Effects of both in-time and out- of-time pile-up, from additional pp collisions in the same and nearby bunch crossings, were modelled by overlaying minimum-bias interactions generated with Pythia 8.186 [61] according to the luminosity profile of the recorded data. The distribution of the number of additional pp interactions in the MC samples was reweighted to match the pile-up conditions observed in data. All simulated samples used EvtGen [62] to model the decays of heavy-flavour hadrons, except for processes modelled using the Sherpa generator [63]. All simulated events were processed using the same reconstruction algorithms and analysis selection requirements as for the data, but small corrections, obtained from comparisons of simulated events with data in dedicated control regions, were applied to trigger and object reconstruction efficiencies, as well as detector resolutions, to better model the observed response. The main parameters of the MC samples used in this search are summarised in table 1. Samples for all SM background processes were generated with the full Geant4 model of the ATLAS detector. 4.1 Background modelling Top-quark pair events were generated with the next-to-leading-order (NLO) generator Powheg-Box 2.0 [64–66] using the CT10 parton distribution function (PDF) set [67], interfaced to Pythia 6.428 [68] with the CTEQ6L PDF set [69] and the Perugia 2012 (P2012) set of tuned parameters for the underlying event (UE) [70]. The hard-process factorisation scale µf and renormalisation scale µr were set to the default Powheg-Box values µ = (m2t + p2T,top )1/2 , where mt is the top-quark mass, mt = 172.5 GeV, and pT,top is the top-quark transverse momentum evaluated for the underlying Born configuration. The hdamp parameter, which controls the transverse momentum of the first additional gluon emission beyond the Born configuration, is set equal to the mass of the top quark. The main effect of this choice is to regulate the high-pT emission against which the tt̄ system recoils. The sample was generated assuming that the top quark decays exclusively through t → W b. Alternative tt̄ samples were produced to model uncertainties in this process. The effects of initial- and final-state radiation (ISR/FSR) were explored using two alternative Powheg-Box 2.0 + Pythia 6.428 samples: one with hdamp set to 2mt , the renormalisation and factorisation scales set to half the nominal value and using the P2012 high-variation UE tuned parameters, giving more radiation, and another with P2012 low-variation UE –8– tuned parameters, hdamp = mt and the renormalisation and factorisation scales set to twice the nominal value, giving less radiation [71]. The values of µr , µf and hdamp were varied together, because these two variations were found to cover the full set of uncertain- ties obtained by changing the scales and the hdamp parameter independently. To provide a comparison with a different parton-shower model, an additional tt̄ sample was gener- ated using the same Powheg-Box settings as the nominal Powheg-Box 2.0 + Pythia 6.428 sample, but with parton showering, hadronisation, and the UE simulated with Her- wig++ 2.7.1 [72] with the UEEE5 tuned parameters [73] and the corresponding CTEQ6L1 PDF set. Additional tt̄ simulation samples were generated using Madgraph5 aMC@NLO 2.2.1 [74] interfaced to Herwig++ 2.7.1 to determine the systematic uncertainties related JHEP05(2019)164 to the use of different models for the hard-scattering generation, while maintaining the same parton shower model. The tt̄ prediction was normalised to the theoretical cross-section for the inclusive tt̄ process of 832+46 −51 pb obtained with Top++ [75], calculated at next-to-next-to-leading order (NNLO) in QCD and including resummation of next-to-next-to-leading logarithmic (NNLL) soft gluon terms [76–80]. Theoretical uncertainties result from variations of the factorisation and renormalisation scales, as well as from uncertainties in the PDF and strong coupling constant αS . The latter two represent the largest contribution to the overall theoretical uncertainty in the cross-section and are calculated using the PDF4LHC prescription [81]. Single-top-quark background processes corresponding to the W t and s-channel produc- tion mechanisms were generated with Powheg-Box 1.0 at NLO [82] using the CT10 PDF set. Overlaps between the tt̄ and W t final states were removed using the “diagram removal” scheme (DR) [83, 84]. The “diagram subtraction” scheme (DS) [84] was considered as an al- ternative method, and the full difference between the two methods assigned as a shape and normalisation uncertainty [85]. Events from t-channel single-top-quark production were generated using the Powheg-Box 1.0 [82] NLO generator, which uses the four-flavour scheme. The fixed four-flavour PDF set CT10f4 was used for the matrix-element calcula- tions. All single-top-quark samples were normalised to the approximate NNLO theoretical cross-sections [86–88]. Pythia 6.428 with the P2012 set of tuned parameters was used to model the parton shower, hadronisation and underlying event. Additional single-top-quark samples were generated using the same Powheg-Box settings as the nominal sample, while parton showering, hadronisation, and the UE were simulated with Herwig++ 2.7.1. The ISR/FSR effects were explored using alternative Powheg-Box 2.0 + Pythia 6.428 sam- ples with a set of P2012 high- and low-variation UE tuned parameters. Another set of single-top-quark samples was generated using Madgraph5 aMC@NLO 2.2.1 interfaced to Herwig++ 2.7.1 to determine the systematic uncertainties associated with the choice of NLO generator. Samples of W/Z+jets events were generated with the Sherpa 2.2.0 generator. The matrix-element calculation was performed with up to two partons at NLO and up to four partons at leading order (LO) using Comix [89] and OpenLoops [90]. The matrix-element calculation was merged with the Sherpa parton shower [91] using the ME+PS@NLO pre- scription [92]. The PDF set used for the matrix-element calculation was CT10 with a ded- –9– Process Generator Tuned PDF set Inclusive cross-section + parton showering/hadronisation parameters order in pQCD Y qb Madgraph5 aMC@NLO 2.2.3 A14 NNPDF2.3 NLO + Pythia 8.210 tt̄ Powheg-Box 2.0 P2012 CT10 NNLO+NNLL + Pythia 6.428 Single top Powheg-Box 1.0 P2012 CT10 NNLO+NNLL + Pythia 6.428 Dibosons Sherpa 2.1.1 Default CT10 NLO W W , W Z, ZZ JHEP05(2019)164 W/Z + jets Sherpa 2.2.0 Default CT10 NNLO tt̄V Madgraph5 aMC@NLO 2.2.3 A14 NNPDF2.3 NLO + Pythia 8.210 tt̄H Madgraph5 aMC@NLO 2.2.3 CTEQ6L1 CT10 NLO + Herwig++ 2.7.1 Table 1. Generators used to model the signals and different background processes. The parameter tune for the underlying event, PDF set, and the highest-order perturbative QCD (pQCD) accuracy used for the normalisation of each sample is given. All processes, except for Y qb signals, were generated at NLO in QCD. The LO cross-sections calculated for the Y qb signal processes in the simulation were normalised to the NLO theoretical cross-section taken from ref. [14]. icated parton shower tuning developed by the Sherpa authors. The W +jets and Z+jets samples were normalised to the NNLO theoretical cross-sections for inclusive W and Z pro- duction calculated with FEWZ [93]. Samples generated with Madgraph5 aMC@NLO 2.2.1+ Pythia 8.186 were compared with the nominal W +jets samples to determine the systematic uncertainties associated with the choice of generator. Diboson events (W W/W Z/ZZ+jets) with one of the bosons decaying hadronically and the other leptonically were generated with the NLO generator Sherpa 2.1.1 and include processes containing up to four electroweak vertices. The matrix element included up to one (ZZ) or zero (W W , W Z) additional partons at NLO and up to three partons at LO using the same procedure as for W/Z+jets. All diboson samples were normalised to their NLO theoretical cross-sections provided by Sherpa. Processes producing smaller backgrounds are also considered, and include tt̄V (V = W, Z) and tt̄H. The tt̄V processes were simulated with Madgraph5 aMC@NLO generator using the NNPDF2.3 PDF set, interfaced to Pythia8 [94] with the A14 UE tune. The tt̄H process was modelled using Madgraph5 aMC@NLO interfaced to Herwig++ 2.7.1. 4.2 Signal modelling Simulated events for signal processes were generated at LO in the four-flavour scheme with the Madgraph5 aMC@NLO 2.2.3 generator using the NNPDF2.3 PDF set, interfaced to Pythia8 for parton showering and hadronisation. Samples of Y qb signals were produced for masses ranging from 800 GeV to 2000 GeV in steps of 100 GeV with equal left-handed – 10 – and right-handed coupling strengths of κT = 0.5 [95]. The coupling parameter κT in the model described in ref. [95] used for the signal production is q related to the coupling √ parameters cL,R in ref. [14] via κT f (m) = cL,R / 2, where f (m) ≈ 1/(1 + O(m−4 W b W b Q )) with √ mQ the VLQ mass in GeV, and therefore κT ≈ cW b L,R / 2 to a very good approximation. These samples were processed either through the full detector simulation or through the faster simulation. The normalisation of signal events produced with the faster simulation was scaled up by 7.2% to correct for efficiency differences. Since the kinematic distributions of the decay products for the T quark and Y quark in the W b decay channel are the same, only Y signal samples were generated and they were JHEP05(2019)164 used to derive the results also for the T qb signals. Other possible decay modes of the T quark (T → Zt, T → Ht) have negligible acceptance in this search. The kinematics of the final-state particles are very similar for left-handed and right-handed couplings, and hence the acceptances for the two chiralities are found to be equal. The LO cross-sections calcu- lated for the signal processes in the simulation were normalised to the next-to-leading-order benchmark calculation from ref. [14], which is performed in the narrow-width approxima- tion (NWA). The single-VLQ production cross-sections and the decay widths of the VLQ resonances are mass- and coupling-dependent. The VLQ width increases with increasing mass and coupling values such that, for sufficiently large masses and couplings, the NWA is no longer valid. The ratio of the single-VLQ production cross-section without the NWA to that with the NWA, calculated at LO using Madgraph5 aMC@NLO 2.2.3, was used to correct the NLO cross-section from ref. [14] as function of VLQ mass and coupling. Sizeable interference effects between the amplitude for VLQ signal production and the SM are possible. In the analysis, two scenarios are considered: 1. T -quark production in a T singlet model, in which the T quark has only a left-handed coupling [1]. The SM process that interferes in this case is t-channel single-top-quark production where the top quark is far off-shell as illustrated in figure 2a. 2. Y -quark production in a (T, B, Y ) triplet or (B, Y ) doublet model, in which the Y quark has only a left-handed coupling or right-handed coupling. The SM process that interferes with Y -quark production is electroweak W − bq production4 as shown in figure 2b. Two cases are considered: a) the Y quark has only a left-handed coupling, which is realised e.g. in a (T, B, Y ) triplet model, in which the right-handed coupling is heavily suppressed [1]. Since in the (T, B, Y ) triplet model the T quark does not couple to W b, T -quark production does not contribute to the final state under consideration; b) the Y quark has only a right-handed coupling, which is realised e.g. in a (B, Y ) doublet model, in which the left-handed coupling is heavily suppressed. The interference effect for the Y quark with a right-handed coupling is much smaller than that for the Y quark with a left-handed coupling. These SM contributions (i.e. σSM ) were not modelled in the ATLAS MC simulations. In order to determine the signal yield and acceptance for different signal couplings, the samples of simulated signal events produced with the nominal coupling strength of 4 The charge-conjugated state W + b̄q interferes with the Ȳ quark. – 11 – JHEP05(2019)164 (a) (b) Figure 2. Leading-order Feynman diagrams for the SM processes that interfere with T -quark or Y - quark production, respectively, as described in the text: (a) t-channel single-top-quark production where the top quark is far off-shell and (b) electroweak W − bq production. κT = 0.5 are corrected on an event-by-event basis using reweighting factors. These factors are obtained by comparing the target VLQ mass distribution in generated signal samples, at particle level, with the nominal one. The reweighting takes three effects into account: 1) the effect of interference calculated at LO, 2) the change in cross-section when going from LO to NLO, 3) the effect from the variation of the coupling strength. The method is validated with fully reconstructed signal samples with varied coupling strengths. The matrix-element squared for the process pp → W bq is given by ∗ |M |2 = |MSM |2 + |MVLQ |2 + 2Re(MSM MVLQ ). As a result, the total cross-section for pp → W bq at LO can be written as σtot LO = σ LO + SM LO LO LO LO σVLQ + σI with the LO SM cross-section σSM , the LO VLQ cross-section σVLQ and the interference-term cross-section σILO . Since the K-factor quantifying the ratio between NLO and LO cross-sections is significantly larger than one for VLQ production, the interference effect has to be modelled at NLO. This modelling uses the K-factors for SM production, KSM , and for VLQ production, KVLQ , writing the total cross-section for pp → W bq at NLO as NLO LO LO + KSM · KVLQ σILO . p σtot = KSM σSM + KVLQ σVLQ (4.1) The KVLQ values as a function of the VLQ mass are taken from ref. [14]. There is no dedicated NLO calculation available for the KSM factor for t-channel single-top-quark pro- duction with t-quarks far off-shell. This KSM factor is set to unity since the K-factor for t-channel single-top-quark production for on-shell t-quarks is very close to one [96]. Since there is no dedicated NLO calculation in the literature for electroweak SM W − bq pro- duction interfering with the Y production amplitude, KSM is set to unity in this case as well. No systematic uncertainties are assigned to any of the KVLQ or KSM factors, because it is assumed that they correspond to the particular model assumptions. To obtain the reweighting factors r, events were generated at LO using Madgraph5 aMC@NLO 2.2.3 – 12 – 1 Fraction of (events + 0.1) / 5 GeV ATLAS Simulation s = 13 TeV cWb L ≈ 0.71 cWb ≈ 0.14 10−1 Y mass = 900 GeV L cWb L ≈ 0.14 + interference 10−2 10−3 JHEP05(2019)164 10−4 600 800 1000 1200 1400 Y quark generated mass [GeV] Figure 3. The generated mass distributions at particle√level for a Y quark with a mass of 900 GeV, for a coupling strength of c0 = κT ≈ 0.5 and cW b Wb L ≈ 1/ 2 (cR = 0 , solid line) and of c0 = cL = Wb 0.14 (dotted line) as defined in ref. [95]. The distribution for a right-handed only and left-handed only Y quark (solid line) is the same. The dashed line shows the generated vector-like quark mass distribution at particle level of a left-handed Y signal with a mass of 900 GeV, coupling strength of cW b L = 0.14 and interference effects with the SM included. The interference effects lead to negative entries in some bins of the distribution. For better visualisation of the tail distribution including the interference effect, the bin contents of all distributions were shifted by +0.1 before normalisation. and r calculated as p KVLQ fVLQ (mW b ; c) + KSM · KVLQ fI (mW b ; c) r(mW b ; c, c0 ) = , (4.2) fVLQ (mW b ; c0 ) where c0 is the nominal coupling used in the simulation, c is the coupling value of interest, and the functions fVLQ (mW b ; c) and fI (mW b ; c) describe the W b invariant mass distri- butions at particle level scaled to the LO cross-sections σSMLO and σ LO respectively. The I reweighting assumes that the phase change as a function of mW b for the VLQ and SM amplitudes at NLO is the same as at LO. Figure 3 shows the generated mass distribution at particle level for a Y quark with a mass of 900 GeV, produced with a coupling strength of 0.5 and scaled to the LO cross- section. It is compared with the generated mass distributions reweighted to a coupling strength of 0.14 with and without the interference term, which is also scaled to the LO cross-section. For the case without interference, it was explicitly checked that events gen- erated with one coupling and reweighted to another target coupling result not only in the same VLQ mass distribution, but also in the same distributions of other kinematical variables when generated directly with this target coupling. – 13 – 5 Event selection and background estimation This search focuses on final states with a leptonically decaying W boson and a b-quark, originating from the decay of a singly produced Q quark. Events are required to have exactly one isolated identified lepton (electron or muon) with pT > 28 GeV that must be matched to the lepton selected by the trigger, large missing transverse momentum ETmiss > 120 GeV from the escaping neutrino, and at least one central jet with p > 25 GeV T satisfying the quality and kinematic criteria discussed in section 3. The requirement on the missing transverse momentum reduces the fraction of selected events originating from non- prompt or misidentified leptons as well as diboson events. In the following, unless stated JHEP05(2019)164 otherwise, only events satisfying this selection, referred to as “preselection”, are considered. If there are any forward jets in the event, their transverse momentum is required to be larger than 40 GeV. 5.1 Signal and control regions definition Events must have at least one b-tagged jet. The highest-pT jet in the event must be b-tagged and have pT > 350 GeV. To further exploit the low multiplicity of high-pT jets in the signal process, an additional requirement is applied: events containing any jet with pT > 75 GeV and |η| < 2.5 and satisfying ∆R(jet, leading jet) < 1.2 or ∆R(jet, leading jet) > 2.7 are rejected (hard central jet veto). This requirement reduces background from production of tt̄ events, which are characterised by a higher multiplicity of high-pT central jets than in signal events. A requirement on the azimuthal separation between the lepton and the b-tagged leading jet, |∆φ (lepton, leading jet)| > 2.5, as well as on the minimum distance ∆R between the lepton and any central jet, ∆R(lepton, jet) > 2.0, increases the signal-to- background ratio because, in signal signatures, leptons from the leptonic W -boson decays should be isolated and recoil against the b-quark jet in the event. Furthermore, similar to t-channel single-top production, the single production of VLQs gives rise to a forward jet (2.5 < |η| < 4.5). Only events with at least one forward jet with pT > 40 GeV are considered. For aqY signal with a mass between 800 GeV and 2000 GeV and a cou- √ pling strength of (cW b 2 Wb 2 L ) + (cR ) ≈ 1/ 2, the signal-to-background ratio (S/B) and √ the signal-to-background significance ratio (S/ B) in the SR are in the range 1.0–0.003 and 22.1–0.3 respectively. The acceptance times efficiency including the leptonic W decay branching fractions5 for these Y signals ranges from 0.7% to 1.8% in the SR. The normalisation of W +jets and tt̄ processes is partially constrained by fitting the predicted yields to data in CRs enriched in W +jets and tt̄ events. Two CRs are defined for this purpose, and also provide samples depleted in expected signal events. The selection requirements for the W +jets CR are the same as for the SR, except that each event is required to have exactly one b-tagged jet and the requirement on the azimuthal separa- tion between the lepton and the b-tagged jet is reversed, |∆φ (lepton, leading jet) | ≤ 2.5. In addition, the b-tagged jet has a slightly lower transverse momentum requirement of pT > 250 GeV and no hard central or forward jet veto is applied. The W +jets CR defini- 5 Events with leptonic τ decays are included. – 14 – tion results in a composition of W +light-jets and W +heavy-flavour-jets final states similar to that in the SR. The selection requirements for the tt̄ CR are the same as for the SR, except that the leading jet pT must be greater than 200 GeV and there must be at least one high-pT jet with pT > 75 GeV and |η| < 2.5 fulfilling either ∆R (jet, leading jet) < 1.2 or ∆R (jet, leading jet) > 2.7. Table 2 summarises the main selection criteria in the SR and theqorthogonal CRs. For Y /T signals with masses of ≥ 800 GeV and a coupling strength √ of (cW b 2 Wb 2 L ) + (cR ) ≈ 1/ 2, the contamination in the tt̄ control region is at most 1% and in the W +jets CR at most 0.6%. A mismodelling of the W +jets background is observed at high jet pT . To correct JHEP05(2019)164 for this mismodelling, the leading jet pT distributions in data and MC-simulated W +jets events are compared after applying the preselection criteria and requiring that the leading jet is a b-tagged jet. The ratio of the distributions is taken as a scaling factor, which is applied to the simulated W +jets events in all kinematic distributions. The correction factors are between approximately 0.9 and 1.1 with statistical uncertainties of 4–10% for a jet pT below 500 GeV, and 0.4–0.8 with a statistical uncertainty of about 11% for higher pT values. These reweighting factors are treated as a systematic uncertainty in the final fit. 6 5.2 Estimation of non-prompt and fake lepton backgrounds Multijet production results in hadrons, photons and non-prompt leptons that may satisfy the lepton selection criteria and give rise to so called “non-prompt and fake” lepton back- grounds. The multijet background normalisation and shape in the mVLQ distributions are estimated with a data-driven method, referred to as the Matrix Method [43]. This method uses the efficiencies of leptons selected using loose requirements (loose leptons) to pass the default tight lepton selection requirements. The efficiencies are obtained in dedicated control regions enriched in real leptons or in non-prompt and fake leptons, and applied to events selected with either the loose or tight lepton definition to obtain the fraction of mul- tijet events. The fake-enriched control regions are defined using the preselection criteria, except that events with electrons are required to have a reconstructed transverse W mass7 mW T < 20 GeV and to have ET miss + mW < 60 GeV, and for events with muons it is required T that the leading muon have |d0 /σ(d0 )| > 5. The real lepton efficiencies are measured using the tag-and-probe method from Z → ee and Z → µµ control regions. Further details can be found in refs. [22, 43]. 5.3 Signal candidate mass reconstruction In the SR, the invariant mass of the reconstructed VLQ candidate mVLQ is used to discrim- inate the signal from the background processes. It is calculated from the leading b-tagged jet and the decay products of the leptonically decaying W -boson candidate. The W -boson 6 The residual difference of about 10% between the data and the SM simulation in the tail of the invariant mass distribution of the reconstructed VLQ candidate after applying the W +jets leading-jet pT correction is included in this systematic uncertainty. 7 The transverse W mass mW T is computed from the missing transverse p momentum p ~Tmiss and the ` W ` miss charged lepton transverse momentum p ~T , and is defined as mT = 2pT ET (1 − cos ∆φ(~ p`T , p ~Tmiss )), ` miss ` miss where ∆φ(~ pT , p ~T ) is the azimuthal angle between p ~T and p~T . – 15 – Region SR tt̄ CR W +jets CR Requirement Preselection Leptons 1 miss ET > 120 GeV Central jets (pT > 25 GeV) ≥1 Selection b-tagged jets ≥1 ≥1 1 JHEP05(2019)164 Leading jet pT > 350 GeV > 200 GeV > 250 GeV Leading jet is b-tagged Yes Yes Yes |∆φ(lepton, leading jet)| > 2.5 > 2.5 ≤ 2.5 Jets (pT > 75 GeV) with ∆R (jet, leading jet) < 1.2 or 0 ≥1 – ∆R (jet, leading jet) > 2.7 ∆R (lepton, jets) > 2.0 — > 2.0 Forward jets (pT > 40 GeV) ≥1 ≥1 – Table 2. Summary of common preselection requirements and selection requirements for the SR compared to those for the tt̄ and W +jets CRs. All other selection requirements are the same for all three regions. candidate is reconstructed by summing the four-momenta of the charged lepton and the neutrino. To obtain the z-component of the neutrino momentum (pz,ν ), the invariant mass of the lepton-neutrino system is set to the W -boson mass and the resulting quadratic equa- ~ miss vector is varied by the minimum amount tion is solved. If no real solution exists, the E T required to produce exactly one real solution. If two real solutions are found, the one with the smaller |pz,ν | is used. The W -boson candidate and the leading b-tagged jet are then used to reconstruct the Q candidate. The mass qresolutions for Y signals with masses between W b W b √ 2 2 800 GeV and 1600 GeV for a coupling of (cL ) + (cR ) ≈ 1/ 2 are 150–550 GeV. Figure 4 shows the VLQ candidate invariant mass distribution in the SR for three simulated left-handed Y signal masses, 900 GeV, 1200 GeV and 1600 GeV, with couplings of cW b L ≈ 0.29, ≈ 0.33 and ≈ 0.91 respectively, without (left figure) and with (right figure) interference included, together with the total SM background. The distribution provides good discrimination between signal and background events in the SR. Depending on the coupling and signal mass it is possible that negative entries occur in some bins of the signal-plus-interference mVLQ distribution due to the interference effect. – 16 – Events / 150 GeV Events / 150 GeV 400 ATLAS Simulation 400 ATLAS Simulation s=13 TeV, 36.1 fb-1 Standard Model s=13 TeV, 36.1 fb-1 Standard Model Y LH 900 GeV, Y LH 900 GeV, 300 300 cWb L = 0.29, x 5 cWb L = 0.29, x 5 Y LH 1200 GeV, Y LH 1200 GeV, 200 cWb L = 0.33, x 5 200 cWb L = 0.33, x 5 Y LH 1600 GeV, Y LH 1600 GeV, cWb L = 0.91, x 5 cWb L = 0.91, x 5 100 100 0 0 JHEP05(2019)164 −100 −100 0 500 1000 1500 2000 2500 0 500 1000 1500 2000 2500 mVLQ [GeV] mVLQ [GeV] (a) (b) Figure 4. Distribution of VLQ candidate mass, mVLQ , in the SR for three different signal masses (a) without and (b) with interference effects, for a left-handed Y signal with a mass of 900 GeV (dashed line), 1200 GeV (dotted) and 1600 GeV (dash-dotted line) and a coupling of cW L b ≈ 0.29, ≈ 0.33 and ≈ 0.91 respectively, together with the total SM background (solid line). The error bars represent the statistical uncertainties. The signal event yield is scaled by a factor of five. Depending on the coupling and signal mass it is possible that negative entries occur in some bins of the signal-plus-interference mVLQ distribution due to the interference effect. The distributions for a right-handed and left-handed Y signal without considering any interference effects are the same. 6 Systematic uncertainties Several sources of systematic uncertainty in this analysis can affect the normalisation of the signal and background and/or their corresponding mVLQ distributions, which are used for the statistical study. They are included as nuisance parameters in the statistical analysis. Sources of uncertainty include the modelling of the detector response, object reconstruction algorithms, uncertainty in the theoretical modelling of the signals and backgrounds, as well as the uncertainty arising from the limited size of the simulated event samples. The following section describes each of the systematic uncertainties considered in the search. Table 3 presents a summary of all systematic uncertainties considered in the anal- ysis. Leading sources of systematic uncertainty in the expected SM background are uncer- tainties that arise from the jet energy scale, flavour-tagging efficiencies (b, c and light) as well as the background modelling, where tt̄ generator uncertainties and single-top-quark DS/DR uncertainties are significantly constrained by the fit (see section 7.1). 6.1 Experimental uncertainties The uncertainty in the combined 2015+2016 integrated luminosity is 2.1%. It is derived, following a methodology similar to that detailed in ref. [97], and using the LUCID-2 detector for the baseline luminosity measurements [98], from calibration of the luminosity scale using x-y beam-separation scans. Experimental sources of systematic uncertainty arise from the reconstruction and mea- miss [57]. Uncertainties associated with leptons surement of jets [49], leptons [40, 42] and ET – 17 – Systematic uncertainty Type SM background [%] Luminosity N 2.1 Pile-up SN 0.3 Reconstructed objects: Electron efficiency, energy scale, resolution SN 0.9 Muon efficiency, momentum scale, resolution SN 0.7 Jet vertex tagger SN 0.1 Jet energy scale SN 6.4 JHEP05(2019)164 Jet energy resolution SN 2.7 Missing transverse momentum SN 0.3 b-tagging efficiency for b-jets SN 0.8 b-tagging efficiency for c-jets SN 1.8 b-tagging efficiency for light-flavour jets SN 8.4 Background model: tt̄ modelling: ISR/FSR SN 0.2 tt̄ modelling: generator SN 3.8 tt̄ modelling: parton shower/hadronisation SN 4.5 tt̄ modelling: interfering background shape S 0.3 Single-top cross-section N 0.4 Single-top modelling: ISR/FSR SN 0.04 Single-top modelling: generator SN 0.3 Single-top modelling: DS/DR SN 3.1 Single-top modelling: parton shower/hadronisation SN 1.6 W +jets modelling: generator SN 0.8 W +jets modelling: reweighting S 4.6 W +jets heavy flavour S 0.04 Diboson + Z+jets normalisation N 0.2 Multijet normalisation N 3.8 Multijet reweighting S 2.1 tt̄ background scaling factor F 26 W +jets background scaling factor F 19 Table 3. Systematic uncertainties considered in this analysis. An uncertainty that affects normal- isation only (cross-section only) for all processes and channels is denoted by “N”, whereas “SN” means that the uncertainty affects both shape and normalisation and “F” means a floating nor- malisation uncertainty. Some of the systematic uncertainties are split into several components for a more accurate treatment. The relative systematic uncertainties in the inclusive expected SM background yields determined from the VLQ candidate invariant mass distribution after the fit to the background-only hypothesis are given in the last column in percentage. The tt̄ and W +jets background scaling-factor uncertainties (last two rows in the table) are the relative systematic uncertainties in the predicted tt̄ and W +jets background respectively. – 18 – arise from the trigger, reconstruction, identification, and isolation efficiencies, as well as the lepton momentum scale and resolution, and are studied using Z → `+ `− and J/ψ → `+ `− decays in data. Uncertainties associated with jets primarily arise from the jet energy scale, jet energy resolution, and the efficiency of the jet vertex tagger requirement. The largest contribution is from the jet energy scale, where the dependence of the uncertainty on jet pT and η, jet flavour, and pile-up is split into 21 uncorrelated components that are treated independently in the analysis [49]. The systematic uncertainty in the ET miss reconstruction is dominated by the uncertainties in the energy calibration and resolution of reconstructed jets and leptons, which are propagated to ET miss and thus are included in the uncertainties in the corresponding objects. In addition, uncertainties in the pT scale and resolution of JHEP05(2019)164 reconstructed tracks that are associated with the hard-scatter vertex but not matched to any reconstructed objects are included. The efficiency of the flavour-tagging algorithm to correctly tag b-jets, or to mis-tag c-jets or light-flavour jets, is measured for each jet flavour. The efficiencies are measured in control samples of simulated events, and in data samples of tt̄ events, D∗ mesons, and jets with impact parameters and secondary vertices consistent with a negative lifetime. Correction factors are defined to correct the tagging rates in the simulation to match the efficiencies measured in the data control samples [54, 56]. The uncertainties associated with these measurements are factorised into statistically independent sources and include a total of six independent sources affecting b-jets and four independent sources affecting c-jets. Each of these uncertainties has a different dependence on jet pT . Seventeen sources of uncertainty affecting light-flavour jets are considered, and depend on jet pT and η. These correction factors are only determined up to a jet pT of 300 GeV for b- and c-jets, and pT of 750 GeV for light-flavour jets. Therefore, an additional uncertainty is included to extrap- olate these corrections to jets with pT beyond the kinematic reach of the data calibration samples used; it is taken to be correlated among the three jet flavours. This uncertainty is evaluated in the simulation by comparing the tagging efficiencies while varying, e.g., the fraction of tracks with shared hits in the silicon detectors or the fraction of fake tracks resulting from random combinations of hits, both of which typically increase at high jet pT due to growing track multiplicity and density of hits within the jet. Finally, an uncertainty related to the application of c-jet scale factors to τ -jets is considered, but has a negligible impact in this analysis [56]. The flavour-tagging systematic uncertainties are the leading sources of experimental uncertainties (added in quadrature, about 8.7% in the expected background yield in the SR). Other large detector-specific uncertainties arise from jet energy scale uncertainties (about a 6.4% effect on the expected background yield) and jet energy resolution uncertain- ties (2.7% in the expected background yield). The total systematic uncertainty associated with ET miss reconstruction is about 0.3% in the SR. The combined effect of all these uncer- tainties results in an overall normalisation uncertainty in the SM background of approxi- mately 6.3% taking into account correlations between the different systematic uncertainties. For the data-driven multijet background, which has a very small contribution in the SR and CRs, a 100% normalisation uncertainty is used, to fully cover discrepancies between the observed data and the SM expectation in multijet-background-enriched regions. The – 19 – large statistical uncertainties associated with the multijet background prediction, which are uncorrelated bin-to-bin in the final discriminating variable, do not cover shape differences in the multijet background electron pT distribution. This mismodelling is corrected by determining reweighting factors in a multijet-background-enriched region which are used as additional shape uncertainties in the final discriminant. These reweighting factors are obtained for electrons with |η| < 1.2 and |η| > 1.2 separately in a region requiring the same selection requirements as the preselection, but loosening the minimum ET miss requirement to 20 GeV and requiring the leading jet is a b-jet. JHEP05(2019)164 6.2 Theoretical modelling uncertainties A number of systematic uncertainties affecting the modelling of tt̄ and single-top-quark processes as described in section 4.1 are considered: uncertainties associated with the modelling of the ISR and FSR, uncertainties associated with the choice of NLO generator, modelling uncertainties in single-top-quark production (for t-channel) based on comparison of the nominal sample with an alternative MC sample described in section 4.1, differences between single-top-quark W t samples produced using the diagram subtraction scheme and W t samples produced using the diagram removal scheme, as well as an uncertainty due to the choice of parton shower and hadronisation model. The tt̄ background normalisation is a free parameter in the fit, while the normalisation of the single-top background has an uncertainty of 6.8% [87]. Uncertainties affecting the modelling of the Z+jets background and diboson back- ground processes include a 5% effect from their respective normalisations to the theoretical NNLO cross-sections [93, 99, 100]. Since both these backgrounds are very small, this un- certainty is applied to the sum of the predicted Z+jets and diboson background processes. The W +jets background normalisation is a free parameter in the fit. The W +light-jets and W +heavy-flavour-jets predictions have similar mVLQ distributions in the SR and CRs. Since the predicted ratios of W +light-jets to W +heavy-flavour-jets events in the SR and CRs are similar, but not identical, a systematic uncertainty is derived by comparing the shape of the complete W +jets sample with the W +heavy-flavour-jets portion alone. In addition, alternative W +jets samples were generated using Madgraph+Pythia8 and compared after applying the preselection criteria plus requiring that the leading jet is a b-tagged jet. To account for the mismodelling of the leading-jet pT spectrum in W +jets events, reweighting factors are obtained at preselection for W +jet events. The mVLQ distributions with and without these W +jets jet-pT correction factors applied to W +jet events are compared in the SR and CRs and used to quantify the systematic uncertainty in the mVLQ shape of W +jets events in the fit. All normalisation uncertainties in the different background processes are treated as uncorrelated. For background estimates based on simulations, the largest sources of the- oretical modelling uncertainties are due to the choice of parton shower and hadronisation model (2–4%), the choice of generator (about 1–3% in the expected background yield) and varying the parameters controlling the initial- and final-state radiation (about 0.1% – 20 – in the expected background yield), where the theoretical modelling uncertainties from tt̄ contribute the most. The systematic uncertainties in the modelling of the high-mass Y /T signal sample which correspond to the choice of PDF set are evaluated following the PDF4LHC15 pre- scription [81]. No further systematic uncertainties in the signal modelling and no uncertain- ties in the NLO signal production cross-section are considered. In addition, a systematic uncertainty of about 2.5% is applied to cover small differences in the reconstructed VLQ mass between signal samples passed through the full simulation of the detector and signal samples produced with the faster simulation (see section 4). JHEP05(2019)164 The ATLAS MC production used in this analysis does not contain simulated events from the SM contributions that lead to interference with the VLQ signal. Therefore, these SM contributions can not be explicitly considered in the background modelling of the fit. A recent MC production at reconstruction level using the four-flavour scheme for one mass point for a left-handed Y quark shows that the mVLQ distribution of the interfering SM contribution is similar but not identical to that of the other background contributions (W +jets, tt̄, single top). To account for the presence of interfering SM contributions in the fit, an additional shape uncertainty is applied to the tt̄ mVLQ template, which leads to an uncertainty of 0.2% in the tt̄ yield. 7 Results 7.1 Statistical interpretation A binned maximum-likelihood fit to the data is performed to test for the presence of a signal. A separate fit is performed for each signal hypothesis with given mass and cou- plings. The inputs to the fit are the distributions of reconstructed VLQ candidate mass mVLQ in the SR and the two CRs. The binned likelihood function L(µ, θ) is constructed as a product of Poisson probability terms over all mVLQ bins considered in the search. It depends on the signal-strength parameter µ, a multiplicative factor to the theoretical signal production cross-section, and θ, a set of nuisance parameters that encode the effect of systematic uncertainties in the signal and background expectations and are implemented in the likelihood function as Gaussian constraints, as well as on the two scale factors for the free-floating tt̄ and W +jets SM background normalisations. Uncertainties in each bin of the mVLQ distributions due to the finite numbers of events in the simulation samples are included using dedicated fit parameters and are propagated to µ. The nuisance parameters θ allow variations of the expectations for signal and background according to the corre- sponding systematic uncertainties, and their fitted values θ̂ correspond to the deviations from the nominal expectations which globally provide the best fit to the data. This pro- cedure reduces the impact of systematic uncertainties on the search sensitivity by taking advantage of the well-populated background-dominated CRs included in the likelihood fit. It also allows the CRs to improve the description of the data. The test statistic qµ is defined as the profile log-likelihood ratio: ˆ qµ = −2 ln(L(µ, θ̂µ )/L(µ̂, θ̂)), where µ̂ and θ̂ are the values of the parameters that – 21 – Source SR tt̄ CR W +jets CR tt̄ 58 ± 21 2715 ± 295 100 ± 29 Single top 29 ± 15 271 ± 118 34 ± 18 W +jets 373 ± 45 1052 ± 143 1077 ± 84 Multijet e 22 ± 20 35 ± 40 0 ± 4 Multijet µ 7 ± 7 92 ± 71 26 ± 20 Z+jets, diboson 20 ± 5 102 ± 20 50 ± 8 tt̄ V 0.3 ± 0.1 21 ± 3 1.6 ± 0.3 JHEP05(2019)164 tt̄ H 0 ± 0 7 ± 1 0.2 ± 0.1 Total 500 ± 30 4300 ± 210 1290 ± 70 Data 497 4227 1274 Table 4. Event yields in the SR and the tt̄ and W +jets CRs after the fit to the background-only hypothesis. The uncertainties include statistical and systematic uncertainties. Due to correlations among the SM backgrounds and the corresponding nuisance parameters, the uncertainties in the individual background components can be larger than the uncertainty in the sum of the background, which is strongly constrained by the data. ˆ maximise the likelihood function (with the constraint 0 ≤ µ̂ ≤ µ), and θ̂µ are the values of the nuisance parameters that maximise the likelihood function for a given value of µ. In the absence of any significant deviation from the background expectation, qµ is used in the CLs method [101, 102] to set an upper limit on the signal production cross-section times branching ratio at the 95% CL. For a given signal scenario, values of the production cross-section (parameterised by µ) yielding CLs < 0.05, where CLs is computed using the asymptotic approximation [103], are excluded at 95% CL. 7.2 Fit results The background-only fit results for the yields in the SR and the two CRs are shown in figure 5. Figure 6 presents the mVLQ distributions after the background-only fit in the SR and the two CRs with the SR binning as used in the background-only fit. The overall tt̄ (W +jets) normalisation is adjusted by a factor of 0.95 ± 0.26 (1.18 ± 0.19), where 0.26 (0.19) is the total uncertainty in the normalisation. An example distribution for a right-handed Y signal and a coupling of cW b R ≈ 0.5 is overlaid, which illustrates what such a signal would look like. Good agreement between the data and the SM backgrounds is found, in particular in the SR for the mVLQ distribution, where no peak above the expected SM background is observed. The numbers of data events in the SR and CRs, and the event yields after fitting the background-only hypothesis to data, together with their systematic uncertainties, are listed in table 4. – 22 – 105 Events ATLAS Data tt s = 13 TeV, 36.1 fb-1 Single top W+jets Q → Wb, Q = T or Y Multijets Other SM bkg. 104 Uncertainty Post-Fit 103 102 JHEP05(2019)164 10 1.151 Data / Pred. 1.075 1 0.925 0.85 SR t t CR Wje ts C R Figure 5. Observed background yields in the SR and in the two CRs after the fit to the data in the control regions and the signal region under the background-only hypothesis. The lower panel shows the ratio of data to the fitted background yields. The error bars, being smaller than the size of the data points and hence not visible in the top part of the plot, represent the statistical uncertainty in the data. The band represents the total (statistical and systematic) uncertainty after the maximum-likelihood fit. 7.3 Limits on the VLQ production When allowing for the signal presence, no significant deviation from the expected SM background is found. In all models considered in this search (T singlet model, right-handed Y in a (B, Y ) doublet model, left-handed Y in a (T, B, Y ) triplet model), interference effects with SM contributions affect the mVLQ distribution (see section 4.2). The effects of the interfering SM contributions (σSM , see eq. (4.1)) in the fit are treated as a systematic uncertainty in the background modelling (see section 6). Therefore, only the interference effect itself (σI ) is explicitly taken into account in the signal template. For the left-handed Y and the T -singlet case, the size and mVLQ distribution of the interfering SM contributions are estimated in three ways: 1. Using the shape of the reweighted template (σVLQ + σI ). 2. Using simulated events in the four- and five-flavour schemes at particle level, with the SR requirements applied. 3. Using the fully-reconstructed MC simulated events mentioned in section 6. – 23 – 600 Events / 100 GeV Events / 100 GeV 140 ATLAS Data ATLAS Data s = 13 TeV, 36.1 fb-1 Y1200 GeV (cWb)2 + (cWb)2 = 0.5 s = 13 TeV, 36.1 fb-1 Y1200 GeV X 30 (cWb)2 + (cWb)2 = 0.5 Q → Wb, Q = T or Y L R 500 Q → Wb, Q = T or Y L R 120 tt tt SR Single top W+jets CR Single top Post-Fit W+jets Post-Fit W+jets 100 400 Multijets Multijets Other SM bkg. Other SM bkg. 80 Uncertainty 300 Uncertainty 60 200 40 JHEP05(2019)164 100 20 1.50 1.50 Data / Pred. Data / Pred. 1.25 1.25 1 1 0.75 0.75 0.5 0.5 600 800 1000 1200 1400 1600 1800 2000 2200 2400 600 800 1000 1200 1400 1600 1800 2000 2200 2400 mVLQ [GeV] mVLQ [GeV] (a) (b) 1600 Events / 100 GeV ATLAS Data 1400 s = 13 TeV, 36.1 fb-1 Y1200 GeV X 10 (cWb)2 + (cWb)2 = 0.5 L R Q → Wb, Q = T or Y tt 1200 tt CR Single top Post-Fit W+jets 1000 Multijets Other SM bkg. 800 Uncertainty 600 400 200 1.250 Data / Pred. 1.125 1 0.875 0.75 500 1000 1500 2000 2500 mVLQ [GeV] (c) Figure 6. Distribution of the VLQ candidate mass, mVLQ , in (a) the SR, (b) the W +jets CR, and (c) the tt̄ CR, after the fit to the background-only hypothesis. The first and last bin include the underflow and overflow respectively. The lower panels show the ratios of data to the fitted back- ground yields. The error bars represent the statistical uncertainty in the data. The band represents the total systematic uncertainty q after the maximum-likelihood fit. An example distribution for a Y signal with a coupling of (cW b 2 Wb 2 L ) + (cR ) ≈ 0.5 without considering any interference effects is overlaid; for better visibility, it is multiplied by a factor of 30 in the W +jets CR and by a factor of 10 in the tt̄ CR. While the total uncertainty decreases when performing the fit, the total uncertainty in the bins around 1450-1600 GeV and 1850-2200 GeV in (b) does not decrease due to significant statistical MC uncertainties in these two bins. – 24 – In the four-flavour scheme, the yield and the mVLQ distribution both agree within statistical uncertainties for the left-handed Y in a (T, B, Y ) triplet model and the T singlet model. For the left-handed Y , the yields in the four- and five-flavour schemes differ by a factor of about two, while the mVLQ distributions in both schemes are very similar. A background-only fit in the SR and CRs shows that the interfering SM contribution, the shape of which is taken from the fully reconstructed MC simulation mentioned above, is in agreement with the size used to simulate the interference templates (σI ) and can affect the total postfit background yield by about 4 %. This effect can be accounted for by adding the shape of the interfering SM background as an additional systematic uncertainty in the tt̄ template (see section 6). Studies show that the expected and observed JHEP05(2019)164 limits change by significantly less than one standard deviation with the addition of this systematic uncertainty. For the right-handed Y in a (B, Y ) doublet model, the interfering SM background contributions are much smaller than other background contributions in the SR and the CRs and are therefore negligible. Nonetheless, the non-simulated SM contributions mentionned above, which would lead to interference with a left-handed Y in a (T, B, Y ) triplet model or a T singlet quark, are non-negligible and are therefore taken into account in the fit by the same additional systematic uncertainty in the tt̄ template. Since the interfering SM contributions are not explicitly taken into account in the fit, upper limits on the total cross-section for pp → W bq, σtot = σVLQ + σI + σSM , times branching ratio can not be determined, but limits on the coupling value of the vector-like T or Y quark to W b in a given model based on σVLQ + σI are set. To set a coupling-value limit, the following iterative procedure is performed: for a fixed Q mass hypothesis and for a given coupling value cW b , a mVLQ signal-plus-interference template hVLQ+I (mVLQ ; cW b ) containing the VLQ (σVLQ ) and the interference contribution (σI ) (but not the interfering SM contribution (σSM )) is constructed by reweighting the default VLQ-only signal template hVLQ (mVLQ ; cW b Wb def ) for a default coupling value (cdef = c0 ) using the ratio r (see eq. (4.2)) defined in section 4.2. The maximum-likelihood fit to signal plus background is performed with the signal template hVLQ+I (mVLQ ; cW b ), and an upper limit on σVLQ +σI is determined. The T -quark branching ratio is set to B(T → W b) = 0.5,8 whereas B(Y → W b) = 1 is used for the Y quark. The theoretical cross-section σVLQ is taken from ref. [14], where the NLO W b fusion cross-section is calculated in the NWA. With rising Q mass and coupling value cW b , the Q width becomes sizeable and the NWA calculation is no longer a good approximation. Therefore, the following correction factor applies to the theoretical cross-section prediction: σLO,noNWA = CNWA , σLO,NWA where σLO,noNWA is the LO cross-section without the NWA and σLO,NWA the LO cross- section with the NWA, both calculated with the Madgraph5 aMC@NLO 2.2.3 [74] gen- erator. It is assumed that CNWA is the same to a good approximation for the calculation of the NLO cross-section. These correction factors reduce the predicted σVLQ value. The 8 For the T singlet model, B(T → W b) = 0.5 is a very good approximation in the mass and coupling ranges relevant to this search. – 25 – reduction becomes stronger with increasing mass and coupling value and is about 40% at a Q mass of 1500 GeV and a coupling value of 0.9. From the upper limit on σVLQ + σI , a 0 0 corresponding coupling value cW b is calculated, a new signal template hVLQ+I (mVLQ ; cW b ) is constructed using the reweighting technique described above, and the fit repeated until 0 convergence is observed in the coupling value cW b . It is explicitly checked that the result of the iterative procedure does not depend on the choice of starting value for cW b , by repeating the full iterative process with a lower or higher starting value than the one at convergence. If the coupling converges to a value smaller than the signal-production value of 0.5, the iterative procedure is repeated with a coupling much lower than the value at convergence. A systematic uncertainty of about 2.5% for the coupling reweighting and a JHEP05(2019)164 shape uncertainty for the interference contribution are assigned to this procedure. Depending on the binning of the mVLQ distribution, it is possible that negative entries occur in some bins of the signal-plus-interference template due to the interference effect when large couplings are considered, and this poses a problem in the limit-setting pro- cedure. To avoid this problem, the last bins in the reconstructed mVLQ distribution are merged until no negative bin entries exist. As a result, a different binning in the mVLQ distribution is chosen for each VLQ mass hypothesis for the T -singlet case and for the left-handed Y case, which guarantees (independent of cW b ) that all bins in the signal- plus-interference template have positive values. The rebinning reduces the sensitivity for high-mass T and left-handed Y signals. As an example, figure 7 shows the fitted VLQ can- didate mass distributions for left-handed Y signals with masses of 900 GeV and 1500 GeV and for left-handed T signals with masses of 800 GeV and 1200 GeV. For the T singlet model, the total integral of the signal-plus-interference template at reconstruction level can become negative for VLQ mass hypotheses above 1200 GeV. As a result, no coupling-value limits are set for the T singlet model with masses above 1200 GeV. Tables 5, 6, and 7 sum- marise the observed and expected 95% CLs upper limits on the coupling value and limits on the mixing angle as a function of Q-quark mass, for the T singlet model (assuming B(T → W b) ≈ 0.5), the right-handed Y in a (B, Y ) doublet model, and the left-handed Y in a (T, B, Y ) triplet model respectively. The parameterisation of ref. [1] in terms of right- or left-handed mixing angles is chosen for the coupling limits; these can be easily trans- lated to the parameterisation of ref. [14] for the models under consideration. In a T singlet model, the upper exclusion limit on | sin θL | (cW b L ) is 0.18 (0.25) for a T quark of mass of 800 GeV, rising to 0.35 (0.49) for a T quark with a mass of 1200 GeV. For a (B, Y ) doublet, the upper exclusion limit on | sin θR | (cW b R ) is 0.17 (0.24) for a signal with a mass of 800 GeV and 0.55 (0.77) for Y quarks with a mass of 1800 GeV. The observed (expected) lower mass limit for Y quarks is about 1.64 TeV (1.80 TeV) for a right-handed coupling value √ of cW b R = 1/ 2. For Y signals in a (T, B, Y ) triplet, the upper exclusion limits on | sin θL | (cW b L ) vary between 0.16 (0.31) and 0.39 (0.78) for masses between 800 GeV and 1600 GeV. In figure 8, these direct mixing-angle bounds are compared with those from electroweak precision observables taken from ref. [1], assuming that there are no multiplets other than the one considered. For the (B, Y ) doublet model, the bounds presented here are com- petitive with the indirect constraints for VLQ masses between 800 GeV and 1250 GeV. – 26 – 80 90 Events / 50 GeV Events / 50 GeV ATLAS Data ATLAS Data 70 s = 13 TeV, 36.1 fb-1 Wb Y900 GeV(cL = 0.27) 80 s = 13 TeV, 36.1 fb-1 Wb Y1500 GeV (cL = 0.64) Y → Wb tt Y → Wb tt SR 70 SR 60 Single top Single top Post-Fit W+jets Post-Fit W+jets 60 50 Multijets Multijets Other SM bkg. Other SM bkg. 50 40 Uncertainty Uncertainty 40 30 30 20 JHEP05(2019)164 20 10 10 1.50 1.50 Data / Pred. Data / Pred. 1.25 1.25 1 1 0.75 0.75 0.5 0.5 600 800 1000 1200 1400 1600 1800 2000 2200 2400 600 800 1000 1200 1400 1600 1800 2000 2200 2400 mVLQ [GeV] mVLQ [GeV] (a) (b) 160 120 Events / 100 GeV Events / 100 GeV ATLAS Data ATLAS Data 140 s = 13 TeV, 36.1 fb-1 Wb T800 GeV (cL = 0.25) s = 13 TeV, 36.1 fb-1 Wb T1200 GeV (cL = 0.49) T → Wb tt 100 T → Wb tt 120 SR Single top SR Single top Post-Fit W+jets Post-Fit W+jets 80 100 Multijets Multijets Other SM bkg. Other SM bkg. 80 Uncertainty 60 Uncertainty 60 40 40 20 20 1.50 1.50 Data / Pred. Data / Pred. 1.25 1.25 1 1 0.75 0.75 0.5 0.5 600 800 1000 1200 1400 1600 1800 2000 2200 2400 600 800 1000 1200 1400 1600 1800 2000 2200 2400 mVLQ [GeV] mVLQ [GeV] (c) (d) Figure 7. Distributions of the VLQ candidate mass, mVLQ , after the fit to the background-only hypotheses for four different binnings chosen for four different signal masses. The first and last bin include the underflow and overflow respectively. The VLQ candidate mass distributions for (a) a left-handed Y signal with mass 900 GeV and coupling cW L b = 0.27, (b) a left-handed Y signal with Wb mass 1500 GeV and coupling cL = 0.64, (c) a left-handed T signal with mass of 800 GeV and coupling cWL b = 0.25 and (d) a left-handed T signal with mass 1200 GeV and coupling cW L b = 0.49 are also shown; all signal distributions include interference. The lower panels show the ratio of data to the fitted background yields. The error bars represent the statistical uncertainty in the data. The band represents the total systematic uncertainty after the maximum-likelihood fit. – 27 – T mass [GeV] Observed limit on Expected limit on Observed limit on Expected limit on +1σ/+2σ +1σ/+2σ | sin θL | | sin θL | −1σ/−2σ cW L b cW b L −1σ/−2σ 0.04/0.08 0.06/0.11 800 0.18 0.19 0.03/0.06 0.25 0.27 0.05/0.08 0.05/0.09 0.07/0.13 900 0.24 0.20 0.05/0.07 0.34 0.29 0.07/0.10 0.06/0.08 0.08/0.12 1000 0.20 0.21 0.07/0.09 0.29 0.30 0.10/0.12 0.09/0.11 0.12/0.15 JHEP05(2019)164 1100 0.25 0.27 0.13/0.15 0.36 0.38 0.18/0.21 0.13/0.14 0.18/0.20 1200 0.35 0.35 0.22/0.23 0.49 0.49 0.31/0.33 Table 5. Observed and expected 95% CL upper limits on | sin θL | and cWL b for a left-handed T quark in a T singlet model with masses of 800 GeV to 1200 GeV assuming B(T → W b) = 0.5. The ±1σ and ±2σ uncertainties in the expected limits are also given. Y mass [GeV] Observed limit on Expected limit on Observed limit on Expected limit on +1σ/+2σ +1σ/+2σ | sin θR | | sin θR | −1σ/−2σ cW R b cW b R −1σ/−2σ 0.04/0.08 0.05/0.12 800 0.17 0.20 0.03/0.05 0.24 0.28 0.04/0.07 0.04/0.08 0.05/0.11 900 0.18 0.19 0.03/0.05 0.26 0.27 0.04/0.07 0.03/0.07 0.04/0.10 1000 0.17 0.17 0.03/0.05 0.25 0.25 0.04/0.07 0.03/0.07 0.05/0.10 1100 0.17 0.18 0.03/0.05 0.24 0.25 0.04/0.07 0.04/0.08 0.05/0.11 1200 0.17 0.20 0.03/0.05 0.25 0.28 0.04/0.08 0.04/0.09 0.06/0.12 1300 0.19 0.22 0.03/0.06 0.27 0.31 0.05/0.08 0.05/0.10 0.06/0.14 1400 0.24 0.25 0.04/0.07 0.35 0.36 0.05/0.10 0.05/0.11 0.07/0.15 1500 0.31 0.28 0.04/0.07 0.44 0.39 0.06/0.11 0.08/0.19 0.11/0.27 1600 0.45 0.37 0.06/0.10 0.64 0.53 0.08/0.14 0.10/0.25 0.15/0.36 1700 0.59 0.46 0.08/0.13 0.83 0.65 0.11/0.18 0.09/0.22 0.13/0.32 1800 0.55 0.43 0.07/0.12 0.77 0.61 0.10/0.17 Table 6. Observed and expected 95% CL upper limits on | sin θR | and cW R b for a right-handed Y quark in a (B, Y ) doublet model with masses of 800 GeV to 1800 GeV. The ±1σ and ±2σ uncertainties in the expected limits are also given. – 28 – Y mass [GeV] Observed limit on Expected limit on Observed limit on Expected limit on +1σ/+2σ +1σ/+2σ | sin θL | | sin θL | −1σ/−2σ cW L b cW b L −1σ/−2σ 0.04/0.09 0.08/0.19 800 0.16 0.20 0.03/0.05 0.31 0.40 0.06/0.11 0.03/0.07 0.06/0.13 900 0.14 0.15 0.02/0.04 0.28 0.30 0.05/0.08 0.03/0.06 0.05/0.12 1000 0.16 0.15 0.02/0.04 0.32 0.29 0.04/0.08 0.03/0.08 0.07/0.15 1100 0.23 0.22 0.03/0.06 0.47 0.43 0.07/0.12 0.03/0.07 0.06/0.13 1200 0.20 0.16 0.40 0.33 JHEP05(2019)164 0.02/0.04 0.05/0.09 0.04/0.08 0.08/0.16 1300 0.25 0.21 0.03/0.06 0.49 0.43 0.07/0.12 0.05/0.10 0.09/0.20 1400 0.18 0.25 0.04/0.07 0.36 0.51 0.08/0.14 0.08/0.18 0.16/0.37 1500 0.32 0.35 0.06/0.10 0.64 0.70 0.12/0.20 0.11/0.28 0.21/0.56 1600 0.39 0.40 0.07/0.12 0.78 0.80 0.14/0.24 Table 7. Observed and expected 95% CL upper limits on | sin θL | and cW L b for a left-handed Y quark in a (T, B, Y ) triplet model with masses of 800 GeV to 1600 GeV. The ±1σ and ±2σ uncertainties in the expected limits are also given. Since the interference effect for the case of the right-handed Y quark is very small, and therefore the signal+interference template is very similar to the one of a pure resonance, a limit on σVLQ +σI times branching ratio is presented for this case in figure 9, corresponding to the | sin θR | and cW b R limits for a (B, Y ) doublet model presented in figure (c). 8 Conclusion A search for the production of a single vector-like quark Q, where Q can be either a T or Y quark, with the subsequent decay into W b has been carried out with the ATLAS experiment at the CERN LHC. The data used in this search correspond to an integrated √ luminosity of 36.1 fb−1 of pp collisions with a centre-of-mass energy s = 13 TeV recorded in 2015 and 2016. The selected events have exactly one isolated electron or muon, a high-pT b-tagged jet, missing transverse momentum and at least one forward jet. The Q candidate is fully reconstructed and its mass is used as a discriminating variable in a maximum-likelihood fit. The observed data distributions are compatible with the expected Standard Model background and no significant excess is observed. The search result is interpreted for Q = T in a T singlet model and Q = Y in either a (B, Y ) doublet model or in a (T, B, Y ) triplet model, taking into account the interference effect with the Standard Model background. Limits at 95% CL are set on the cross-section times branching ratio as a function of the VLQ mass in the case of the (B, Y ) doublet model, where interference has the smallest effect. The search results are translated into limits on the QW b mixing angle or coupling. In the T -singlet case, the 95% CL limit on | sin θL | (cW b L ) varies between 0.18 and 0.35 (0.25 and 0.49) for masses from 800 GeV to 1200 GeV. In the (B, Y ) doublet model, exclusion limits on | sin θR | (cW b R ) vary between 0.17 and 0.55 (0.24 and 0.77) for – 29 – 1 1 2 |sinθL| |sinθL| 1.4 |cL | |cL | Wb Wb ATLAS 95% CL Exclusion Limits ATLAS 95% CL Exclusion Limits 0.9 s=13 TeV, 36.1 fb -1 0.9 s=13 TeV, 36.1 fb -1 1.8 T Singlet 1.2 (T B Y) Triplet 0.8 Observed T LH (With interference) 0.8 Observed Y LH (With interference) 1.6 0.7 Expected 1 0.7 Expected 1.4 Expected ± 1 σ Expected ± 1 σ 0.6 Expected ± 2 σ 0.6 Expected ± 2 σ 1.2 0.8 Indirect EW constraint (S,T) on |sinθL| Indirect EW constraint (R ) on |sinθL| 0.5 0.5 b 1 0.6 0.4 0.4 0.8 0.3 0.4 0.3 0.6 0.2 0.2 0.4 0.2 0.1 0.1 0.2 0 0 0 0 0.8 0.85 0.9 0.95 1 1.05 1.1 1.15 1.2 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 mT [TeV] mY [TeV] JHEP05(2019)164 (a) (b) 1 |sinθR| 1.4 |cR | Wb ATLAS 95% CL Exclusion Limits 0.9 s=13 TeV, 36.1 fb -1 (B,Y) Doublet 1.2 0.8 Observed Y RH (With interference) Expected 0.7 Expected ± 1 σ 1 Expected ± 2 σ 0.6 Indirect EW constraint (S,T) on |sinθR | 0.8 Indirect EW constraint Rb on |sinθR | 0.5 0.6 0.4 0.3 0.4 0.2 0.2 0.1 0 0 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 mY [TeV] (c) Figure 8. Observed (solid line) and expected (short-dashed line) 95% CL limits on (a) the mixing angle | sin θL | and the coupling value cW L b for a singlet T -quark model assuming B(T → W b) ≈ 0.5, (b) | sin θL | and cL for a (T, B, Y ) triplet model, and (c) | sin θR | and cW Wb b R for a (B, Y ) doublet model assuming a branching ratio B(Y → W b) = 1, as a function of the VLQ mass. The surrounding bands correspond to ±1 and ±2 standard deviations around the expected limit. The excluded region is given by the area above the solid line. Constraints from electroweak precision observables, which are only valid for the mixing angles, from either the S and T parameters (dashed-dotted line) or from the Rb values (long-dashed line), are also shown. These constraints are taken from ref. [1], where they are presented as a function of mB (in the (B, Y ) doublet case), respectively, mT (in the (T, B, Y ) triplet case) and translated to mY using the value of the corresponding mixing angle constraint. masses between 800 GeV and 1800 GeV and the | sin θR | bounds presented here are below the indirect electroweak constraints for masses between about 900 GeV and 1250 GeV where exclusion limits on | sin θR | are around 0.18–0.19. In the case of the (T, Y, B) triplet, the limits on | sin θL | (cW b L ) vary between 0.16 and 0.39 (0.31 and 0.78) for masses from 800 GeV to 1600 GeV. For all signal scenarios explored, this analysis is found to significantly improve upon the reach of previous searches. 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. – 30 – σ [pb] 102 ATLAS Observed -1 Expected s = 13 TeV, 36.1 fb 10 95% CLs Exclusion Limits on σ Expected ± 1 σ Expected ± 2 σ 1 10−1 Theory (NLO), BR(Y → Wb)=1 10−2 σth, c2R = 1 no NWA σth, c2 = 1/2 no NWA JHEP05(2019)164 R σth, c2 = 0.322 no NWA 10−3 R σth, c2 = 1 NWA R (B,Y) doublet σth, c2 = 1/2 NWA R 2 σth, c2R = 0.32 NWA Y RH (With interference) 10−4 0.8 1 1.2 1.4 1.6 1.8 mY [TeV] Figure 9. Observed (solid line) and expected (short-dashed line) 95% CL limits on cross-section times branching ratio for the case of the right-handed Y quark for a (B, Y ) doublet model as a function of VLQ mass. For the theoretical prediction, the branching ratio B(Y → W b) is set to one. The theoretical NLO cross-sections for different coupling values are shown for the calculation using the narrow-width approximation (dashed-dotted lines) and using no narrow-width approximation (solid lines) as described in the text. 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; 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. 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 – 31 – (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. [104]. Open Access. 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Kortner113 , S. Kortner113 , T. Kosek139 , V.V. Kostyukhin24 , A. Kotwal47 , – 43 – 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. Kozhin140 , V.A. Kramarenko111 , G. Kramberger89 , D. Krasnopevtsev58a , M.W. Krasny132 , A. Krasznahorkay35 , D. Krauss113 , J.A. Kremer81a , J. Kretzschmar88 , P. Krieger164 , K. Krizka18 , K. Kroeninger45 , H. Kroha113 , J. Kroll137 , J. Kroll133 , 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. Kupco137 , T. Kupfer45 , O. Kuprash158 , H. Kurashige80 , L.L. Kurchaninov165a , Y.A. Kurochkin105 , M.G. Kurth15d , E.S. Kuwertz35 , M. Kuze162 , J. Kvita126 , T. Kwan101 , A. La Rosa113 , J.L. La Rosa Navarro78d , L. La Rotonda40b,40a , F. La Ruffa40b,40a , C. Lacasta171 , JHEP05(2019)164 F. Lacava70a,70b , J. Lacey44 , D.P.J. Lack98 , H. Lacker19 , D. Lacour132 , E. Ladygin77 , R. Lafaye5 , B. Laforge132 , T. Lagouri32c , S. Lai51 , S. Lammers63 , W. Lampl7 , E. Lançon29 , U. Landgraf50 , M.P.J. Landon90 , M.C. Lanfermann52 , V.S. Lang44 , J.C. Lange14 , R.J. Langenberg35 , A.J. Lankford168 , F. Lanni29 , K. Lantzsch24 , A. Lanza68a , A. Lapertosa53b,53a , S. Laplace132 , J.F. Laporte142 , T. Lari66a , F. Lasagni Manghi23b,23a , M. Lassnig35 , T.S. Lau61a , A. Laudrain128 , M. Lavorgna67a,67b , A.T. Law143 , M. Lazzaroni66a,66b , B. Le102 , O. Le Dortz132 , 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. Lehmann Miotto35 , W.A. Leight44 , A. 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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 , N.C. Mc Fadden116 , G. Mc Goldrick164 , S.P. Mc Kee103 , A. McCarn103 , T.G. McCarthy113 , L.I. McClymont92 , 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,ac , J.E. Mdhluli32c , Z.A. Meadows100 , S. Meehan145 , T.M. Megy50 , S. Mehlhase112 , A. Mehta88 , T. Meideck56 , B. Meirose42 , D. Melini171,g , B.R. Mellado Garcia32c , J.D. Mellenthin51 , M. Melo28a , F. Meloni44 , A. Melzer24 , S.B. Menary98 , JHEP05(2019)164 E.D. Mendes Gouveia136a , L. Meng88 , X.T. Meng103 , A. Mengarelli23b,23a , S. Menke113 , E. Meoni40b,40a , S. Mergelmeyer19 , C. Merlassino20 , P. Mermod52 , L. Merola67a,67b , C. Meroni66a , F.S. Merritt36 , A. Messina70a,70b , J. Metcalfe6 , A.S. Mete168 , C. Meyer133 , J. Meyer157 , J-P. Meyer142 , H. Meyer Zu Theenhausen59a , F. Miano153 , R.P. Middleton141 , L. Mijović48 , G. Mikenberg177 , M. Mikestikova137 , M. Mikuž89 , M. Milesi102 , A. Milic164 , D.A. Millar90 , D.W. Miller36 , A. Milov177 , D.A. Milstead43a,43b , A.A. Minaenko140 , M. Miñano Moya171 , I.A. Minashvili156b , A.I. Mincer121 , B. Mindur81a , M. Mineev77 , Y. Minegishi160 , Y. Ming178 , L.M. Mir14 , A. Mirto65a,65b , K.P. Mistry133 , T. Mitani176 , J. Mitrevski112 , V.A. Mitsou171 , A. Miucci20 , P.S. Miyagawa146 , A. Mizukami79 , J.U. Mjörnmark94 , T. Mkrtchyan181 , M. Mlynarikova139 , 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. Morange128 , D. Moreno22 , M. Moreno Llácer35 , P. Morettini53b , M. Morgenstern118 , S. 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Su135 , S. Suchek59a , Y. Sugaya129 , M. Suk138 , 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. Svatos137 , M. Swiatlowski36 , S.P. Swift2 , A. Sydorenko97 , I. Sykora28a , T. Sykora139 , D. Ta97 , K. Tackmann44,z , 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 , R. Tanaka128 , B.B. Tannenwald122 , S. Tapia Araya144b , S. Tapprogge97 , A. Tarek Abouelfadl Mohamed132 , S. Tarem157 , G. Tarna27b,d , G.F. Tartarelli66a , JHEP05(2019)164 P. Tas139 , M. Tasevsky137 , T. Tashiro83 , E. Tassi40b,40a , A. Tavares Delgado136a,136b , Y. Tayalati34e , A.C. Taylor116 , A.J. Taylor48 , G.N. Taylor102 , P.T.E. Taylor102 , W. Taylor165b , A.S. Tee87 , P. Teixeira-Dias91 , H. 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Vaniachine163 , P. Vankov118 , R. Vari70a , E.W. Varnes7 , C. Varni53b,53a , T. Varol41 , D. Varouchas128 , K.E. Varvell154 , G.A. Vasquez144b , J.G. Vasquez180 , F. Vazeille37 , D. Vazquez Furelos14 , T. Vazquez Schroeder101 , J. Veatch51 , V. Vecchio72a,72b , L.M. Veloce164 , F. Veloso136a,136c , S. Veneziano70a , A. Ventura65a,65b , M. Venturi173 , N. Venturi35 , V. Vercesi68a , M. Verducci72a,72b , C.M. Vergel Infante76 , C. Vergis24 , W. Verkerke118 , A.T. Vermeulen118 , J.C. Vermeulen118 , M.C. Vetterli149,ar , N. Viaux Maira144b , M. Vicente Barreto Pinto52 , I. Vichou170,∗ , T. Vickey146 , O.E. Vickey Boeriu146 , G.H.A. Viehhauser131 , S. Viel18 , L. Vigani131 , M. Villa23b,23a , M. Villaplana Perez66a,66b , E. Vilucchi49 , M.G. Vincter33 , V.B. Vinogradov77 , A. Vishwakarma44 , C. Vittori23b,23a , I. Vivarelli153 , S. Vlachos10 , M. Vogel179 , P. Vokac138 , G. Volpi14 , S.E. von Buddenbrock32c , E. Von Toerne24 , V. Vorobel139 , K. Vorobev110 , M. Vos171 , J.H. Vossebeld88 , N. Vranjes16 , M. Vranjes Milosavljevic16 , V. Vrba138 , M. Vreeswijk118 , T. Šfiligoj89 , R. Vuillermet35 , I. Vukotic36 , T. Ženiš28a , L. Živković16 , P. Wagner24 , W. Wagner179 , J. Wagner-Kuhr112 , H. Wahlberg86 , S. Wahrmund46 , K. Wakamiya80 , V.M. Walbrecht113 , J. Walder87 , R. Walker112 , – 48 – S.D. Walker91 , W. Walkowiak148 , V. Wallangen43a,43b , A.M. Wang57 , C. Wang58b,d , F. Wang178 , H. Wang18 , H. Wang3 , J. Wang154 , J. Wang59b , P. Wang41 , Q. Wang124 , R.-J. Wang132 , R. Wang58a , R. Wang6 , S.M. Wang155 , W.T. Wang58a , W. Wang15c,ad , W.X. Wang58a,ad , Y. Wang58a , 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. Weidberg131 , B. Weinert63 , J. Weingarten45 , M. Weirich97 , C. Weiser50 , P.S. Wells35 , T. Wenaus29 , T. Wengler35 , S. Wenig35 , N. Wermes24 , M.D. Werner76 , P. Werner35 , M. Wessels59a , T.D. Weston20 , K. Whalen127 , N.L. Whallon145 , A.M. Wharton87 , A.S. White103 , A. White8 , M.J. White1 , R. White144b , D. Whiteson168 , B.W. Whitmore87 , F.J. Wickens141 , W. Wiedenmann178 , M. Wielers141 , C. Wiglesworth39 , L.A.M. Wiik-Fuchs50 , F. Wilk98 , JHEP05(2019)164 H.G. Wilkens35 , L.J. Wilkins91 , H.H. Williams133 , S. Williams31 , C. Willis104 , S. Willocq100 , J.A. Wilson21 , I. Wingerter-Seez5 , E. Winkels153 , F. Winklmeier127 , O.J. Winston153 , B.T. Winter24 , M. Wittgen150 , M. Wobisch93 , A. Wolf97 , T.M.H. Wolf118 , R. Wolff99 , M.W. Wolter82 , H. Wolters136a,136c , V.W.S. Wong172 , N.L. Woods143 , S.D. Worm21 , B.K. Wosiek82 , K.W. Woźniak82 , K. Wraight55 , M. Wu36 , S.L. Wu178 , X. Wu52 , Y. Wu58a , T.R. Wyatt98 , B.M. Wynne48 , S. Xella39 , Z. Xi103 , L. Xia175 , D. Xu15a , H. Xu58a , L. Xu29 , T. Xu142 , W. Xu103 , B. Yabsley154 , S. Yacoob32a , K. Yajima129 , D.P. Yallup92 , D. Yamaguchi162 , Y. Yamaguchi162 , A. Yamamoto79 , T. Yamanaka160 , F. Yamane80 , M. Yamatani160 , T. Yamazaki160 , Y. Yamazaki80 , Z. Yan25 , H.J. Yang58c,58d , H.T. Yang18 , S. Yang75 , Y. Yang160 , Z. Yang17 , W-M. Yao18 , Y.C. Yap44 , Y. Yasu79 , E. Yatsenko58c,58d , J. Ye41 , S. Ye29 , I. Yeletskikh77 , E. Yigitbasi25 , E. Yildirim97 , K. Yorita176 , K. Yoshihara133 , C.J.S. Young35 , C. Young150 , J. Yu8 , J. Yu76 , X. Yue59a , S.P.Y. Yuen24 , B. Zabinski82 , G. Zacharis10 , E. Zaffaroni52 , R. Zaidan14 , A.M. Zaitsev140,ak , T. Zakareishvili156b , N. Zakharchuk33 , J. Zalieckas17 , S. Zambito57 , D. Zanzi35 , D.R. Zaripovas55 , S.V. Zeißner45 , C. Zeitnitz179 , G. Zemaityte131 , J.C. Zeng170 , Q. Zeng150 , O. Zenin140 , D. Zerwas128 , M. Zgubič131 , D.F. Zhang58b , D. Zhang103 , F. Zhang178 , G. Zhang58a , H. Zhang15c , J. Zhang6 , L. Zhang15c , L. Zhang58a , M. Zhang170 , P. Zhang15c , R. Zhang58a , R. Zhang24 , X. Zhang58b , Y. Zhang15d , Z. Zhang128 , P. Zhao47 , X. Zhao41 , Y. Zhao58b,128,ah , Z. Zhao58a , A. Zhemchugov77 , Z. Zheng103 , D. Zhong170 , B. Zhou103 , C. Zhou178 , L. Zhou41 , M.S. Zhou15d , M. Zhou152 , N. Zhou58c , Y. Zhou7 , C.G. Zhu58b , H.L. Zhu58a , H. Zhu15a , J. Zhu103 , Y. Zhu58a , X. Zhuang15a , K. Zhukov108 , V. Zhulanov120b,120a , A. Zibell174 , D. Zieminska63 , N.I. Zimine77 , S. Zimmermann50 , Z. Zinonos113 , M. Zinser97 , M. Ziolkowski148 , G. Zobernig178 , A. Zoccoli23b,23a , K. Zoch51 , T.G. Zorbas146 , R. Zou36 , M. Zur Nedden19 and L. 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 (a) Department of Physics, Ankara University, Ankara;(b) Istanbul Aydin University, Istanbul;(c) Division of Physics, 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 12 (a) Bahcesehir University, Faculty of Engineering and Natural Sciences, Istanbul; (b) Istanbul Bilgi University, Faculty of Engineering and Natural Sciences, Istanbul;(c) Department of Physics, – 49 – Bogazici University, Istanbul;(d) Department of Physics Engineering, Gaziantep University, Gaziantep; Turkey 13 Institute of Physics, Azerbaijan Academy of Sciences, Baku; Azerbaijan 14 Institut de Fı́sica d’Altes Energies (IFAE), Barcelona Institute of Science and Technology, Barcelona; Spain 15 (a) Institute of High Energy Physics, Chinese Academy of Sciences, Beijing;(b) Physics Department, Tsinghua University, Beijing;(c) Department of Physics, Nanjing University, Nanjing;(d) University of Chinese Academy of Science (UCAS), Beijing; China 16 Institute of Physics, University of Belgrade, Belgrade; Serbia 17 Department for Physics and Technology, University of Bergen, Bergen; Norway 18 Physics Division, Lawrence Berkeley National Laboratory and University of California, Berkeley CA; United States of America JHEP05(2019)164 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 (a) Dipartimento di Fisica e Astronomia, Università di Bologna, Bologna; (b) INFN Sezione di Bologna; Italy 24 Physikalisches Institut, Universität Bonn, Bonn; Germany 25 Department of Physics, Boston University, Boston MA; United States of America 26 Department of Physics, Brandeis University, Waltham MA; United States of America 27 (a) Transilvania University of Brasov, Brasov;(b) Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest;(c) Department of Physics, Alexandru Ioan Cuza University of Iasi, Iasi;(d) National Institute for Research and Development of Isotopic and Molecular Technologies, Physics Department, Cluj-Napoca;(e) University Politehnica Bucharest, Bucharest;(f ) West University in Timisoara, Timisoara; Romania 28 (a) Faculty of Mathematics, Physics and Informatics, Comenius University, Bratislava;(b) Department of Subnuclear Physics, Institute of Experimental Physics of the Slovak Academy of Sciences, Kosice; Slovak Republic 29 Physics Department, Brookhaven National Laboratory, Upton NY; United States of America 30 Departamento de Fı́sica, Universidad de Buenos Aires, Buenos Aires; Argentina 31 Cavendish Laboratory, University of Cambridge, Cambridge; United Kingdom 32 (a) Department of Physics, University of Cape Town, Cape Town;(b) Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg;(c) School of Physics, University of the Witwatersrand, Johannesburg; South Africa 33 Department of Physics, Carleton University, Ottawa ON; Canada 34 (a) Faculté des Sciences Ain Chock, Réseau Universitaire de Physique des Hautes Energies — Université Hassan II, Casablanca;(b) Centre National de l’Energie des Sciences Techniques Nucleaires (CNESTEN), Rabat;(c) Faculté des Sciences Semlalia, Université Cadi Ayyad, LPHEA-Marrakech;(d) Faculté des Sciences, Université Mohamed Premier and LPTPM, Oujda;(e) Faculté des sciences, 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 (a) Dipartimento di Fisica, Università della Calabria, Rende;(b) INFN Gruppo Collegato di Cosenza, Laboratori Nazionali di Frascati; Italy 41 Physics Department, Southern Methodist University, Dallas TX; United States of America 42 Physics Department, University of Texas at Dallas, Richardson TX; United States of America 43 (a) Department of Physics, Stockholm University;(b) Oskar Klein Centre, Stockholm; Sweden – 50 – 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 (a) Dipartimento di Fisica, Università di Genova, Genova;(b) INFN Sezione di Genova; Italy 54 II. Physikalisches Institut, Justus-Liebig-Universität Giessen, Giessen; Germany 55 SUPA — School of Physics and Astronomy, University of Glasgow, Glasgow; United Kingdom JHEP05(2019)164 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 (a) Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei;(b) Institute of Frontier and Interdisciplinary Science and Key Laboratory of Particle Physics and Particle Irradiation (MOE), Shandong University, Qingdao;(c) School of Physics and Astronomy, Shanghai Jiao Tong University, KLPPAC-MoE, SKLPPC, Shanghai;(d) Tsung-Dao Lee Institute, Shanghai; China 59 (a) Kirchhoff-Institut für Physik, Ruprecht-Karls-Universität Heidelberg, Heidelberg; (b) Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg; Germany 60 Faculty of Applied Information Science, Hiroshima Institute of Technology, Hiroshima; Japan 61 (a) Department of Physics, Chinese University of Hong Kong, Shatin, N.T., Hong Kong;(b) Department of Physics, University of Hong Kong, Hong Kong;(c) Department of Physics and Institute for Advanced Study, 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 (a) INFN Gruppo Collegato di Udine, Sezione di Trieste, Udine;(b) ICTP, Trieste;(c) Dipartimento di Chimica, Fisica e Ambiente, Università di Udine, Udine; Italy 65 (a) INFN Sezione di Lecce;(b) Dipartimento di Matematica e Fisica, Università del Salento, Lecce; Italy 66 (a) INFN Sezione di Milano;(b) Dipartimento di Fisica, Università di Milano, Milano; Italy 67 (a) INFN Sezione di Napoli;(b) Dipartimento di Fisica, Università di Napoli, Napoli; Italy 68 (a) INFN Sezione di Pavia;(b) Dipartimento di Fisica, Università di Pavia, Pavia; Italy 69 (a) INFN Sezione di Pisa;(b) Dipartimento di Fisica E. Fermi, Università di Pisa, Pisa; Italy 70 (a) INFN Sezione di Roma;(b) Dipartimento di Fisica, Sapienza Università di Roma, Roma; Italy 71 (a) INFN Sezione di Roma Tor Vergata;(b) Dipartimento di Fisica, Università di Roma Tor Vergata, Roma; Italy 72 (a) INFN Sezione di Roma Tre;(b) Dipartimento di Matematica e Fisica, Università Roma Tre, Roma; Italy 73 (a) INFN-TIFPA;(b) Università degli Studi di Trento, 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 (a) Departamento de Engenharia Elétrica, Universidade Federal de Juiz de Fora (UFJF), Juiz de Fora;(b) Universidade Federal do Rio De Janeiro COPPE/EE/IF, Rio de Janeiro; (c) Universidade Federal de São João del Rei (UFSJ), São João del Rei;(d) Instituto de Fı́sica, Universidade de São Paulo, São Paulo; Brazil 79 KEK, High Energy Accelerator Research Organization, Tsukuba; Japan – 51 – 80 Graduate School of Science, Kobe University, Kobe; Japan 81 (a) AGH University of Science and Technology, Faculty of Physics and Applied Computer Science, Krakow;(b) Marian Smoluchowski Institute of Physics, Jagiellonian University, Krakow; Poland 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 89 Department of Experimental Particle Physics, Jožef Stefan Institute and Department of Physics, JHEP05(2019)164 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 (ITEP), 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 120 (a) Budker Institute of Nuclear Physics, SB RAS, Novosibirsk;(b) Novosibirsk State University Novosibirsk; Russia – 52 – 121 Department of Physics, New York University, New York NY; United States of America 122 Ohio State University, Columbus OH; United States of America 123 Faculty of Science, Okayama University, Okayama; Japan 124 Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman OK; United States of America 125 Department of Physics, Oklahoma State University, Stillwater OK; United States of America 126 Palacký University, RCPTM, Joint Laboratory of Optics, Olomouc; Czech Republic 127 Center for High Energy Physics, University of Oregon, Eugene OR; United States of America 128 LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay; France 129 Graduate School of Science, Osaka University, Osaka; Japan 130 Department of Physics, University of Oslo, Oslo; Norway 131 Department of Physics, Oxford University, Oxford; United Kingdom JHEP05(2019)164 132 LPNHE, Sorbonne Université, Paris Diderot Sorbonne Paris Cité, CNRS/IN2P3, Paris; France 133 Department of Physics, University of Pennsylvania, Philadelphia PA; United States of America 134 Konstantinov Nuclear Physics Institute of National Research Centre “Kurchatov Institute”, PNPI, St. Petersburg; Russia 135 Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh PA; United States of America 136 (a) Laboratório de Instrumentação e Fı́sica Experimental de Partı́culas — LIP; (b) Departamento de Fı́sica, Faculdade de Ciências, Universidade de Lisboa, Lisboa; (c) Departamento de Fı́sica, Universidade de Coimbra, Coimbra;(d) Centro de Fı́sica Nuclear da Universidade de Lisboa, Lisboa;(e) Departamento de Fı́sica, Universidade do Minho, Braga;(f ) Departamento de Fı́sica Teorica y del Cosmos, Universidad de Granada, Granada (Spain); (g) Dep Fı́sica and CEFITEC of Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica; Portugal 137 Institute of Physics, Academy of Sciences of the Czech Republic, Prague; Czech Republic 138 Czech Technical University in Prague, Prague; Czech Republic 139 Charles University, Faculty of Mathematics and Physics, Prague; Czech Republic 140 State Research Center Institute for High Energy Physics, NRC KI, Protvino; Russia 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 (a) Departamento de Fı́sica, Pontificia Universidad Católica de Chile, Santiago; (b) Departamento de Fı́sica, 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 (a) E. Andronikashvili Institute of Physics, Iv. Javakhishvili Tbilisi State University, Tbilisi; (b) High Energy Physics Institute, Tbilisi State University, Tbilisi; Georgia 157 Department of Physics, Technion, Israel Institute of Technology, Haifa; Israel 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 – 53 – 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 (a) TRIUMF, Vancouver BC;(b) Department of Physics and Astronomy, York University, Toronto ON; Canada 166 Division of Physics and Tomonaga Center for the History of the Universe, Faculty of Pure and 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 JHEP05(2019)164 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 Centre for High Performance Computing, CSIR Campus, Rosebank, Cape Town; South Africa c Also at CERN, Geneva; Switzerland d Also at CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille; France e Also at Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève; Switzerland f Also at Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona; Spain g Also at Departamento de Fı́sica Teorica y del Cosmos, Universidad de Granada, Granada (Spain); Spain h Also at Department of Applied Physics and Astronomy, University of Sharjah, Sharjah; United Arab Emirates i Also at Department of Financial and Management Engineering, University of the Aegean, Chios; Greece j Also at Department of Physics and Astronomy, University of Louisville, Louisville, KY; United States of America k Also at Department of Physics and Astronomy, University of Sheffield, Sheffield; United Kingdom l Also at Department of Physics, California State University, Fresno CA; United States of America m Also at Department of Physics, California State University, Sacramento CA; United States of America n Also at Department of Physics, King’s College London, London; United Kingdom – 54 – o Also at Department of Physics, St. Petersburg State Polytechnical University, St. Petersburg; Russia p Also at Department of Physics, Stanford University; United States of America q Also at Department of Physics, University of Fribourg, Fribourg; Switzerland r Also at Department of Physics, University of Michigan, Ann Arbor MI; United States of America s Also at Dipartimento di Fisica E. Fermi, Università di Pisa, Pisa; Italy t Also at Giresun University, Faculty of Engineering, Giresun; Turkey u Also at Graduate School of Science, Osaka University, Osaka; Japan v Also at Hellenic Open University, Patras; Greece w Also at Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest; Romania x Also at II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen; Germany y Also at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona; Spain JHEP05(2019)164 z Also at Institut für Experimentalphysik, Universität Hamburg, Hamburg; Germany aa Also at Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen; Netherlands ab Also at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest; Hungary ac Also at Institute of Particle Physics (IPP); Canada ad Also at Institute of Physics, Academia Sinica, Taipei; Taiwan ae Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku; Azerbaijan af Also at Institute of Theoretical Physics, Ilia State University, Tbilisi; Georgia ag Also at Istanbul University, Dept. of Physics, Istanbul; Turkey ah Also at LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay; France ai Also at Louisiana Tech University, Ruston LA; United States of America aj Also at Manhattan College, New York NY; United States of America ak Also at Moscow Institute of Physics and Technology State University, Dolgoprudny; Russia al Also at National Research Nuclear University MEPhI, Moscow; Russia am Also at Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg; Germany an Also at School of Physics, Sun Yat-sen University, Guangzhou; China ao Also at The City College of New York, New York NY; United States of America ap Also at The Collaborative Innovation Center of Quantum Matter (CICQM), Beijing; China aq Also at Tomsk State University, Tomsk, and Moscow Institute of Physics and Technology State University, Dolgoprudny; Russia ar Also at TRIUMF, Vancouver BC; Canada as Also at Universita di Napoli Parthenope, Napoli; Italy ∗ Deceased – 55 –