Published for SISSA by Springer Received: August 9, 2019 Revised: October 17, 2019 Accepted: November 17, 2019 Published: December 9, 2019 Search for bottom-squark pair production with the ATLAS detector in final states containing Higgs JHEP12(2019)060 bosons, b-jets and missing transverse momentum The ATLAS collaboration E-mail: atlas.publications@cern.ch Abstract: The result of a search for the pair production of the lightest supersymmetric √ partner of the bottom quark (b̃1 ) using 139 fb−1 of proton-proton data collected at s = 13 TeV by the ATLAS detector is reported. In the supersymmetric scenarios considered both of the bottom-squarks decay into a b-quark and the second-lightest neutralino, b̃1 → b + χ̃02 . Each χ̃02 is assumed to subsequently decay with 100% branching ratio into a Higgs boson (h) like the one in the Standard Model and the lightest neutralino: χ̃02 → h + χ̃01 . The χ̃01 is assumed to be the lightest supersymmetric particle (LSP) and is stable. Two signal mass configurations are targeted: the first has a constant LSP mass of 60 GeV; and the second has a constant mass difference between the χ̃02 and χ̃01 of 130 GeV. The final states considered contain no charged leptons, three or more b-jets, and large missing transverse momentum. No significant excess of events over the Standard Model background expectation is observed in any of the signal regions considered. Limits at the 95% confidence level are placed in the supersymmetric models considered, and bottom-squarks with mass up to 1.5 TeV are excluded. Keywords: Hadron-Hadron scattering (experiments), Supersymmetry ArXiv ePrint: 1908.03122 Open Access, Copyright CERN, https://doi.org/10.1007/JHEP12(2019)060 for the benefit of the ATLAS Collaboration. Article funded by SCOAP3 . Contents 1 Introduction 1 2 ATLAS detector 3 3 Data and simulated event samples 4 4 Event reconstruction 5 JHEP12(2019)060 5 Analysis strategy 7 5.1 The SRA selections 9 5.2 The SRB selections 10 5.3 The SRC selections 11 6 Background estimation 12 6.1 A-type CR and VR definitions 14 6.2 B-type CR and VR definitions 14 6.3 C-type CR and VR definitions 15 6.4 Summary of CR and VR results 16 7 Systematic uncertainties 19 8 Results and interpretation 20 9 Conclusion 26 The ATLAS collaboration 33 1 Introduction Supersymmetry (SUSY) [1–6] provides an extension to the Standard Model (SM) that solves the hierarchy problem [7–10] by introducing partners of the known bosons and fermions. In R-parity-conserving models [11], SUSY particles are produced in pairs and the lightest supersymmetric particle (LSP) is stable and provides a candidate for dark matter [12, 13]. The superpartners of the SM bosons (the wino, bino and higgsinos) mix to form the neutralinos (χ̃01,2,3,4 ) and charginos (χ̃± 1,2 ) physical states. For a large selection 0 of models, the LSP is the lightest neutralino (χ̃1 ). Naturalness considerations suggest that the supersymmetric partners of the third-generation quarks are light [14, 15]. If this is assumed, the lightest bottom-squark (b̃1 ) and lightest top-squark (t̃1 ) mass eigenstates1 1 The scalar partners of the left-handed and right-handed chiral components of the bottom quark ( b̃L,R ) or top quark (t̃L,R ) mix to form mass eigenstates for which b̃1 and t̃1 are defined as the lighter of the two states. –1– b p h b̃ χ̃01 χ̃02 χ̃02 χ̃01 b̃ p h JHEP12(2019)060 b Figure 1. Graphical representation of the SUSY signal targeted by this analysis. Bottom squarks are produced in pairs and subsequently decay into bχ̃02 with B = 100%. The two χ̃02 particles decay into hχ̃01 also with B = 100%. could be significantly lighter than the other squarks and the gluinos. As a consequence, b̃1 and t̃1 could be pair-produced with relatively large cross-sections at the Large Hadron Collider (LHC). Depending on the mass hierarchy considered, it is possible that the b̃1 and t̃1 could decay into final states with Higgs bosons, h, like the one in the SM, and this allows the Higgs boson to be used as a probe for new physics. This article presents a search for the pair production of bottom squarks decaying into the LSP via a complex decay chain containing the second-lightest neutralino ( χ̃02 ) and the Higgs boson: b̃1 → b + χ̃02 and subsequently χ̃02 → h + χ̃01 . Such a decay hierarchy is predicted in minimal supersymmetric extensions to the SM (MSSM) [16, 17], with h assumed to be the lightest of the neutral bosons introduced in the MSSM. The bottom squark decaying through a next-to-lightest neutralino is one of the possible modes within the MSSM. Dedicated searches for direct decays into the lightest neutralino ( b̃1 → bχ̃01 ) or a chargino (b̃1 → tχ̃± 1 ) have been reported by the ATLAS and CMS collaborations (see for example [18, 19] and [20–22]). When the LSP is bino-like and the χ̃02 is a wino-higgsino mixture, the branching ratio (B) of χ̃02 → h + χ̃01 is enhanced relative to the other possible χ̃02 decays. The Higgs boson mass is taken to be 125 GeV, and the decay into a pair of bottom quarks is assumed to be the same as in the SM (B = 58% [23, 24]), although it could be enhanced or reduced in the MSSM. This search is interpreted within simplified model scenarios [25, 26] and figure 1 illus- trates the targeted model. In the first set of models, already considered by the ATLAS Collaboration using 8 TeV data [27], the mass of the χ̃01 is fixed at 60 GeV. The bottom- squark and χ̃02 masses vary in the ranges 250–1600 GeV and 200–1500 GeV, respectively. The assumption about the χ̃01 mass is motivated by dark-matter relic density measurements and might be favoured in Higgs-pole annihilation scenarios [28] where mχ̃01 ' mh /2. The previous search performed by ATLAS using 8 TeV data excluded bottom-squark masses up to 750 GeV in this scenario [27]. –2– The second set of SUSY models assumes a fixed mass difference between the χ̃02 and χ̃01 , sufficient to produce an on-shell Higgs boson. The mass difference, ∆m(χ̃02 , χ̃01 ), is set to 130 GeV, whilst bottom-squark and χ̃01 masses vary in the ranges 400–1500 GeV and 1–800 GeV, respectively. A similar scenario is considered by the CMS Collaboration in ref. [29], where the h → γγ decay mode is exploited to exclude bottom-squark masses up to 530 GeV; no prior ATLAS searches have targeted these models. The final states are characterised by a unique signature, which contains many jets, of which up to six can be identified as originating from the fragmentation of b-quarks (referred to as b-jets), missing transverse momentum (pmiss T , the magnitude thereof referred to as miss JHEP12(2019)060 ET ), and no charged leptons (referred to as leptons). New selections and dedicated procedures aiming to maximise the efficiency of reconstructing the Higgs boson candidates decaying into a b-quark pair are employed in this article. Section 2 presents a brief overview of the ATLAS detector, with section 3 describing the data and simulated samples used in the analysis. The event reconstruction methods are explained in section 4. An overview of the analysis strategy is presented in section 5, with the background estimation strategy discussed in section 6. The systematic uncertainties considered in the analysis are described in section 7. Section 8 presents the results and interpretation thereof, with the conclusions presented in section 9. 2 ATLAS detector The ATLAS detector [30] is a multipurpose particle physics detector with a forward- backward symmetric cylindrical geometry and nearly 4π coverage in solid angle.2 The inner tracking detector consists of pixel and silicon microstrip detectors covering the pseu- dorapidity region |η| < 2.5, surrounded by a transition radiation tracker which enhances electron identification in the region |η| < 2.0. Between Run 1 and Run 2, a new inner pixel layer, the insertable B-layer [31, 32], was added at a mean sensor radius of 3.3 cm. The inner detector is surrounded by a thin superconducting solenoid providing an axial 2 T magnetic field and by a fine-granularity lead/liquid-argon (LAr) electromagnetic calorime- ter covering |η| < 3.2. A steel/scintillator-tile calorimeter provides hadronic coverage in the central pseudorapidity range (|η| < 1.7). The endcap and forward regions (1.5 < |η| < 4.9) of the hadronic calorimeter are made of LAr active layers with either copper or tungsten as the absorber material. An extensive muon spectrometer with an air-core toroidal magnet system surrounds the calorimeters. Three layers of high-precision tracking chambers pro- vide coverage in the range |η| < 2.7, while dedicated fast chambers allow triggering in the 2 ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point in the centre of the detector. The positive x-axis is defined by the direction from the interaction point 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 component of momentum in the transverse plane is denoted by pT . The pseudorapidity η is defined in terms of the polar angle θ by η = − ln tan(θ/2). Rapidity is defined as y = 0.5 ln[(E +pz )/(E −pz )] where E denotes the energy, and pz is the component ofpthe momentum along the beam direction. The separation of two objects in η–φ space is given by ∆R = (∆η)2 + (∆φ)2 . –3– region |η| < 2.4. The ATLAS trigger system consists of a hardware-based level-1 trigger followed by a software-based high-level trigger [33]. 3 Data and simulated event samples The data analysed in this study correspond to a total of 139 fb−1 of proton-proton (pp) collision data collected by the ATLAS detector with a centre-of-mass energy of 13 TeV and a 25 ns proton bunch crossing interval in the period between 2015 and 2018. All detector subsystems were required to be operational during data taking. The average number of interactions per bunch crossing (pile-up) increased from hµi = 20 (2015–2016 dataset) to JHEP12(2019)060 hµi = 37 (2018 dataset), with a highest hµi = 38 (2017 dataset). The uncertainty in the combined 2015–2018 integrated luminosity is 1.7 % [34], obtained using the LUCID-2 detector [35] for the primary luminosity measurements. Events are required to pass an ET miss trigger [36] which is fully efficient for events with miss reconstructed ET > 250 GeV. Additional single-lepton triggers requiring electrons or muons are used to estimate the SM backgrounds, with an offline selection of pT (`) > 27 GeV used to ensure the trigger is fully efficient (` = e, µ). Dedicated Monte Carlo (MC) simulated samples are used to model SM processes and estimate the expected signal yields. All samples were produced using the ATLAS simulation infrastructure [37] and GEANT4 [38], or a faster simulation based on a parameterisation of the calorimeter response and GEANT4 for the other detector systems [37]. The SUSY signal samples were generated with MadGraph5 aMC@NLO v2.6.2 [39] at leading order (LO) and interfaced to PYTHIA v8.230 [40] for the modelling of the parton showering (PS), hadronisation and the underlying event with the A14 [41] set of tuned parameters (tune). The matrix element (ME) calculation was performed at tree level and includes the emission of up to two additional partons. The ME-PS matching was done using the CKKW-L [42] prescription, with a matching scale set to one quarter of the bottom-squark mass. The NNPDF2.3 LO [43] parton distribution function (PDF) set was used. Signal cross-sections were calculated to approximate next-to-next-to-leading order in the strong coupling constant, adding the resummation of soft gluon emission at next-to-next-to-leading-logarithm (approximate NNLO+NNLL) [44–47] accuracy. The nominal cross-section and its uncertainty were derived using the PDF4LHC15 mc PDF set, following the recommendations of ref. [48]. For b̃1 masses between 400 GeV and 1.5 TeV, the cross-sections range from 2.1 pb to 0.26 fb, with uncertainties from 6% to 17%. The SM backgrounds considered in this analysis are: tt̄ pair production; single-top- quark production; Z + jets; W + jets; tt̄ production with an electroweak (ttV ) or Higgs (ttH) boson; and diboson production. The samples were simulated using different MC generator programs depending on the process. Pair production of top quarks, tt̄, was generated using POWHEG-BOX v2 [49–52] interfaced with PYTHIA v8.230 and the A14 tune with the NNPDF2.3 LO PDF set for the ME calculations. The hdamp parameter in POWHEG-BOX, which controls the pT of the first additional emission beyond the Born level and thus regulates the pT of the recoil emission against the tt̄ system, was set to 1.5 times the top-quark mass (mt = 172.5 GeV) as a result of studies documented in ref. [53]. –4– The generation of single top quarks in the W t-channel, s-channel and t-channel production modes was performed by POWHEG-BOX v2 [50–52, 54] similarly to the tt̄ samples. For all processes involving top quarks, top-quark spin correlations were preserved. All events with at least one leptonically decaying W boson were retained; fully hadronic tt̄ and single- top events do not contain sufficient ET miss to contribute significantly to the background. The production of tt̄ pairs in association with electroweak vector bosons (W, Z) or Higgs bosons was modelled by samples generated at NLO using MadGraph5 aMC@NLO v2.2.3 and showered with PYTHIA v8.212. Events containing W or Z bosons with associated jets, including jets from the fragmentation of heavy-flavour quarks, were simulated using the SHERPA v2.2.1 [55] generator. Matrix elements were calculated for up to two additional JHEP12(2019)060 partons at NLO and four partons at LO using the Comix [56] and OpenLoops [57] ME generators and were merged with the SHERPA PS [58] using the ME+PS@NLO prescrip- tion [59]. The NNPDF3.0 NNLO [43] PDF set was used in conjunction with a dedicated PS tune developed by the SHERPA authors. Diboson processes were also simulated using the SHERPA generator using the NNPDF3.0 NNLO PDF set. They were calculated for up to one (ZZ) or zero (W W, W Z) additional partons at NLO and up to three additional partons at LO. Other potential sources of backgrounds, such as the production of three or four top quarks or three gauge bosons, are found to be negligible. Finally, contributions from multijet background are estimated from data using a jet smearing procedure described in ref. [60] and are found to be negligible in all regions. All background processes are normalised to the best available theoretical calculation for their respective cross-sections. The NLO tt̄ inclusive production cross-section is corrected to the theory prediction at NNLO in QCD including the resummation of NNLL soft-gluon terms calculated using Top++2.0 [61–67]. Samples of single-top events are normalised to the NLO cross-sections reported in refs. [68–70]. For all samples, except those generated using SHERPA, the EvtGen v1.2.0 [71] pro- gram was used to simulate the properties of the bottom- and charm-hadron decays. All simulated events include a modelling of contributions from pile-up by overlaying minimum- bias pp interactions from the same (in-time pile-up) and nearby (out-of-time pile-up) bunch crossings simulated in PYTHIA v8.186 and EvtGen v1.2.0 with the A3 [72] tune and the NNPDF2.3 LO set [43]. 4 Event reconstruction This search is based upon a selection of events with many b-jets, large missing transverse momentum and no charged leptons (electrons and muons) in the final state. All events are required to have a reconstructed primary vertex which is consistent with the beamspot enve- lope and consists of at least two associated tracks in the inner detector with pT > 500 MeV. If more than one vertex passing the above requirements is found, the one with the largest sum of the squares of transverse momenta of associated tracks [73] is chosen. Jet candidates are reconstructed from three-dimensional clusters of energy in the calorimeter [74] with the anti-kt jet algorithm [75, 76] using a radius parameter of 0.4. The application of a jet energy scale (JES) correction derived from data and simulation [77] –5– is used to calibrate the reconstructed jets. A set of quality criteria is applied to iden- tify jets which arise from non-collision sources or detector noise [78] and any event which contains a jet failing to satisfy these criteria is removed. Additional jets that arise from pile-up interactions are rejected by applying additional track-based selections to jets with pT < 120 GeV and |η| < 2.4 [79], and the jet momentum is corrected by subtracting the expected average energy contribution from pile-up using the jet area method [80]. Jets are classified as either ‘baseline’ or ‘signal’; baseline jets are required to have pT > 20 GeV and |η| < 4.8 whilst signal jets are selected after resolving overlaps with electrons and muons, as described below, and must pass tighter requirements of pT > 30 GeV and |η| < 2.8. Signal jets are identified as b-jets if they are within |η| < 2.5 and are tagged by a mul- JHEP12(2019)060 tivariate algorithm which uses a selection of inputs including information about the impact parameters of inner-detector tracks, the presence of displaced secondary vertices and the reconstructed flight paths of b- and c-hadrons inside the jet [81]. The b-tagging algorithm used has an efficiency of 77%, determined in a sample of simulated tt̄ events. It was chosen as part of the optimisation procedure and the corresponding misidentification rate is 20% for c-jets and 0.9% for light-flavour jets. To compensate for differences between data and MC simulation in the b-tagging efficiencies and mis-tag rates, correction factors are derived from data and applied to the samples of simulated events; details are found in ref. [81]. Electron candidates are reconstructed from energy clusters in the electromagnetic calorimeter matched to a track in the inner detector and are required to satisfy a set of ‘loose’ quality criteria [82]. They are also required to lie within the fiducial volume |η| < 2.47 and have pT > 4.5 GeV. Muon candidates are reconstructed by matching tracks in the inner detector with tracks in the muon spectrometer. Muon candidates which have a transverse (longitudinal) impact parameter relative to the primary vertex larger than 0.2 mm (1 mm) are rejected to suppress muons from cosmic rays. Muon candidates are also required to satisfy ‘medium’ quality criteria [83] and have |η| < 2.5 and pT > 4 GeV. Electron (muon) candidates are matched to the primary vertex by requiring the transverse impact parameter (d0 ) to satisfy |d0 |/σ(d0 ) < 5 (3), and the longitudinal impact parameter (z0 ) to satisfy |z0 sin θ| < 0.5 mm. Lepton candidates remaining after resolving overlaps with baseline jets are called ‘baseline’ leptons. In the control regions where tighter lepton identification is required, ‘signal’ leptons are chosen from the baseline set with pT > 20 GeV and are required to be isolated from other activity in the detector using a criterion designed to accept at least 95% of leptons from Z boson decays; details are found in ref. [84]. In the dilepton control region where the single-lepton triggers are used, the leading lepton is required to have pT > 27 GeV; which ensures full efficiency of the single-lepton trig- gers. Signal electrons are further required to satisfy ‘tight’ quality criteria [82]. The MC events are corrected to account for differences in the lepton trigger, reconstruction and identification efficiencies between data and MC simulation. Possible reconstruction ambiguities between baseline electrons, muons and jets are resolved by firstly removing electron candidates which share an inner detector track with a muon candidate. Jet candidates are then removed if they are within ∆R = p (∆y)2 + (∆φ)2 = 0.2 of an electron candidate; next, electron candidates are discarded if they are within ∆R = 0.4 of a jet. Muons are discarded if they lie within ∆R = 0.4 of –6– any remaining jet, except for the case where the number of tracks associated with the jet is less than three, where the muon is kept and the jet is discarded. Identified τ leptons decaying hadronically are not considered but the following τ -veto procedure is applied to reject events which contain τ -like objects. Candidates (τcand ) are identified as jets which have |η| < 2.5 and less than five inner detector tracks of pT > 500 MeV. If an event contains a tau candidate with a small azimuthal distance to the pmiss T (∆φ(ET miss , τ cand ) < π/3), then the event is vetoed. The missing transverse momentum pmiss T is defined as the negative vector sum of the pT of all selected and calibrated physics objects (electrons, muons, photons [82] and jets) JHEP12(2019)060 in the event, with an extra term added to account for soft energy in the event which is not associated with any of the selected objects [85]. This soft term is calculated from inner- detector tracks with pT above 500 MeV matched to the PV, thus ensuring it is robust against pile-up contamination [86, 87]. 5 Analysis strategy Three sets of non-orthogonal signal regions (SRs) are defined to target different mass hi- erarchies of the SUSY particles involved. These definitions exploit various discriminating observables and algorithms developed to explicitly reconstruct Higgs boson candidates in the decay chain. Events with charged leptons are vetoed in all SRs. Events with one or two charged leptons are used to define control regions (CRs) to aid in the estimation of the main SM backgrounds. Additionally, events with zero charged leptons are utilised to define validation regions (VRs) to ensure the background estimation method, described in section 6, is robust. The optimisation procedure for the event selection aims to maximise the yield of bottom-squark pair production events while reducing SM background contri- butions. It is performed for the two simplified model scenarios introduced in section 1. Since the h → bb decay mode is considered, the final state contains a large jet multiplicity, with many of these jets originating from b-quarks, and large ET miss from the neutralinos. The event selection criteria are defined on the basis of kinematic requirements for the objects described in the previous section and the event variables described below. For these definitions, signal jets are used and are ordered according to decreasing pT . • Njets : the number of signal jets. • Nb-jets : the number of b-jets. • min ∆φ(jet1−4 , pmiss T ): the minimum azimuthal distance between the four highest-pT miss jets and the pT . This is a powerful discriminating variable against multijet back- ground events containing a large amount of ETmiss due to mismeasured jets. Typically, multijet background events exhibit low values of this variable and studies using data- driven multijet estimates indicate that a selection of min ∆φ(jet1−4 , pmiss T ) > 0.4 is sufficient to reduce the multijet background to a negligible level. –7– • ∆φ(j1 , pmiss miss T ): the azimuthal distance between the highest-pT jet and the pT . This variable is used to select events where the pmiss T is expected to be recoiling against the leading jet. • meff : the effective mass [88] of an event is defined as the scalar sum of the pT of all signal jets and the ETmiss , i.e.: X jet miss meff = (pT )i + ET . i≤Njets JHEP12(2019)060 miss -significance” [89] is defined as follows: • S: referred to as the “object-based ET s |pmiss T | 2 S= . σL2 (1 − ρ2LT ) The total momentum resolution of all jets and leptons, at a given pT and |η|, is determined from parameterised Monte Carlo simulation which well reproduces the resolution measured in data. σL is the total momentum resolution after being rotated into the longitudinal (parallel to the pmiss T ) plane. The quantity ρLT is a correlation factor between the longitudinal and transverse momentum resolution (again with respect to the pmiss T ) of each jet or lepton. The significance S is used to discriminate events where the ET miss arises from invisible particles in the final state from events where the ET miss arises from poorly measured particles (and jets). Additionally, it is useful in discriminating between signal events with large ET miss and Z + jets events with medium-to-low ET miss . Additional selections on the pT of the leading jet and of the leading b-jet are also applied as detailed in the following subsections. In all signal regions, events containing baseline leptons with pT > 10 GeV are vetoed, as well as events containing τ -lepton candidates that align with the pmiss T within ∆φ = π/3 . Only events with ET miss > 250 GeV are retained to ensure full efficiency of the trigger. The event kinematics targeted by the three SRs are depicted in figure 2. The first signal region is SRA, designed to target the ‘bulk’ region of both signal models, with moderate- to high-mass splitting between the b̃1 and χ̃02 . In these scenarios all of the b-jets, from both the bottom-squark and Higgs boson decays, are at a relatively high pT and can be resolved in the detector. The b-jets from the Higgs boson can be isolated by removing the ones most likely from the bottom-squark decays and checking the angular separation between the remaining b-jets. The second region, SRB, is designed to target the phase space of the ∆m(χ̃02 , χ̃01 ) = 130 GeV scenario with a small mass splitting between the b̃1 and χ̃02 , referred to as the “compressed” region. An initial-state radiation (ISR)-like selection is used where the small mass splitting between the bottom squark and neutralino leads to relatively soft b-jets from the bottom squark decay, which are difficult to reconstruct. In this scenario it is possible to reconstruct both Higgs bosons using angular separation methods. Finally, SRC is designed –8–               miss   miss ET ET miss ET JHEP12(2019)060 (a) SRA. (b) SRB. (c) SRC. Figure 2. The different event kinematics, in the transverse plane, targeted by the three SRs: (a) kinematics in the bulk region, with high-pT b-jets arising from the bottom-squark decay; (b) kinematics in the compressed region of the ∆m(χ̃02 , χ̃01 ) = 130 GeV scenario with soft b-jets from the bottom squark; (c) kinematics in the compressed region of the m(χ̃01 ) = 60 GeV scenario which also contains soft b-jets from the bottom squark. to target the “compressed” region of the m(χ̃01 ) = 60 GeV signal scenario, where the mass splitting between the b̃1 and χ̃02 is small. The b-jets from the bottom squark decay are very soft and as such a lower b-jet multiplicity is used in this region, when compared to the A- and B-type selections. Additionally, the visible system (b-jets from the bottom squark decay and Higgs boson decay) is produced back-to-back with the reconstructed pmiss T . 5.1 The SRA selections To exploit the kinematic properties of the signal over a large range of b̃1 , χ̃02 and χ̃01 masses, incremental thresholds are imposed on the main discriminating variable, meff , resulting in three mutually exclusive regions, 1.0 < meff < 1.5 TeV, 1.5 < meff < 2.0 TeV and meff > 2.0 TeV. These are labelled as SRA-L, -M and -H, respectively, to maximise coverage across the b̃1 mass range. The selection criteria for the three SRAs are summarised in table 1. At least four b-tagged jets are required. To discriminate against multijet background, events where the pmiss T is aligned with a jet in the transverse plane are rejected by requiring min ∆φ(jet1−4 , pmiss T ) > 0.4. As a large ETmiss is expected from the neutralinos which escape the detector, a selection of ET miss > 350 GeV is used. Additionally, the leading b-jet (b ) 1 is expected to have a large pT , hence a selection of pT (b1 ) > 200 GeV is employed. At least one of the two Higgs boson candidates in the event is identified using a reconstruction algorithm referred to as max-min, which is a two-step procedure to remove the high-pT b-jets from the bottom squark decay and then use the remaining b-jets to reconstruct a Higgs boson in the decay chain. The procedure is implemented as follows: first, pairs of b-jets are formed by iterating through all of the b-jets in the event, and the pair with the largest separation in ∆R is designated as arising from the bottom-squark decay and removed from the subsequent step; second, the pair with the smallest ∆R is identified as a –9– Variable SRA SRA-L SRA-M SRA-H Nleptons (baseline) =0 =0 Njets ≥6 ≥6 Nb-jets ≥4 ≥4 miss [GeV] ET > 350 > 350 min ∆φ(jet1−4 , pmiss T ) [rad] > 0.4 > 0.4 τ veto Yes Yes pT (b1 ) [GeV] > 200 > 200 JHEP12(2019)060 ∆Rmax (b, b) > 2.5 > 2.5 ∆Rmax-min (b, b) < 2.5 < 2.5 m(hcand ) [GeV] > 80 > 80 meff [TeV] > 1.0 ∈ [1.0, 1.5] ∈ [1.5, 2.0] > 2.0 Table 1. Definitions for the SRA, alongside the three varying meff intervals used. The letter appended to the SRA label corresponds to the low (-L), medium (-M) or high (-H) meff selection. This selection is sensitive to the bulk regions of both signal scenarios. The jets and b-jets are ordered by pT . possible Higgs boson candidate and its invariant mass calculated. The following ∆R and mass quantities are defined: • ∆Rmax (b, b): the distance in η–φ between the two b-jets with the maximal angular separation which are most likely to originate from the initial decay of the b̃1 ; • ∆Rmax-min (b, b): the distance in η–φ between the two b-jets with the minimum angu- lar separation which are most likely to originate from the same Higgs boson decay, selected out of the remaining b-jets; • m(hcand ): the invariant mass of the b-jet pair identified as a Higgs candidate by the max-min algorithm. A lower bound on m(hcand ) is used; in the majority of events the distribution peaks around the Higgs boson mass, but in scenarios where the incorrect combination of b-jets is chosen the signal can extend to higher masses. When applied to signal, the max-min algorithm correctly selects a h → bb pairing in 20%–40% of cases for a single Higgs boson decay, depending upon the model. For a signal model corresponding to m(b̃1 , χ̃02 , χ̃01 ) = (1100, 330, 200) GeV, about 3% of the simulated signal events are retained by the SRA selections. 5.2 The SRB selections The SRB region targets small mass-splitting between the b̃1 and χ̃02 (of order 5–20 GeV), in the case of the ∆m(χ̃02 , χ̃01 ) = 130 GeV scenarios. The presence of an ISR jet boosting the bottom squarks, and consequently their decay products, is exploited. To efficiently – 10 – Variable SRB Nleptons (baseline) =0 Njets ≥5 Nb-jets ≥4 miss [GeV] ET > 350 min ∆φ(jet1−4 , pmiss T ) [rad] > 0.4 τ veto Yes m(hcand1 , hcand2 )avg [GeV] ∈ [75, 175] JHEP12(2019)060 Leading jet not b-tagged Yes pT (j1 ) [GeV] > 350 miss )| [rad] |∆φ(j1 , ET > 2.8 meff [TeV] >1 Table 2. Definitions for SRB, targeting the compressed region of the ∆m(χ̃02 , χ̃01 ) = 130 GeV scenario. The jets and b-jets are ordered by pT . suppress SM background contributions, events are selected where the highest-pT jet is not b-tagged and has pT > 350 GeV; this jet is presumed to arise from ISR in the scenario under consideration. Additional selections of ET miss > 350 GeV and ∆φ(j , E miss ) > 2.8 1 T are applied. An meff selection of > 1 TeV is also applied. The soft pT spectrum predicted for b-jets from b̃1 decays can cause the b-jets to be difficult to reconstruct, hence a different algorithm, aiming to reconstruct both Higgs boson candidates, is employed. Differently from the scenarios targeted by SRA, pairs of b-jets with the largest ∆R are found to be more likely to arise from the decay of the same Higgs boson candidate. Two pairs at a time are identified following an iterative procedure, such that at first the pair of b-jets leading to the highest ∆R, ∆Rbb1 , is defined, followed by the second highest ∆R, ∆Rbb2 , built considering only the remaining b-jets. The average mass of the two candidates m(hcand1 , hcand2 )avg is calculated and a requirement is placed on the average mass, cor- responding to a window around the Higgs boson mass: [75, 175] GeV. For a signal model corresponding to m(b̃1 , χ̃02 , χ̃01 ) = (700, 680, 550) GeV, about 0.1% of the simulated signal events are retained by the SRB selections. The efficiency of correctly selecting the b-jets using this algorithm is in the range 15%–30%. The SRB requirements are listed in table 2. 5.3 The SRC selections When considering the scenario with a constant χ̃01 mass of 60 GeV, the ∆R-based Higgs boson reconstruction algorithms are ineffective in the compressed region of phase space with a small mass splitting between the b̃1 and χ̃02 . In the inclusive SRC, the main discriminating quantity is S; a selection of S > 22 is employed. Events are also required to have at least three b-jets. Four non-overlapping regions (SRC22, SRC24, SRC26 and SRC28) are defined as subsets of the inclusive SRC region, with incremental thresholds placed on S as detailed – 11 – Variable SRC SRC22 SRC24 SRC26 SRC28 Nleptons (baseline) =0 =0 Njets ≥4 ≥4 Nb-jets ≥3 ≥3 miss [GeV] ET > 250 > 250 min ∆φ(jet1−4 , pmiss T ) [rad] > 0.4 > 0.4 S > 22 ∈ [22, 24] ∈ [24, 26] ∈ [26, 28] > 28 JHEP12(2019)060 Table 3. Definitions for SRC, alongside the four varying S intervals used. The letter appended to the SRC label corresponds to the lower bound on the S interval. SRC targets small mass splittings between the b̃1 and χ̃02 , in the m(χ̃01 ) = 60 GeV signal scenario. The jets and b-jets are ordered by pT . in table 3, to ensure full coverage of the target models as a function of bottom-squark and neutralino mass. For a signal model corresponding to m(b̃1 , χ̃02 , χ̃01 ) = (1200, 1150, 60) GeV, about 11% of the simulated signal events are retained by the SRC selections. The S variable is effective in rejecting the SM background arising from associated production of a Z boson decaying into neutrinos and b-jets. 6 Background estimation There are two main SM backgrounds which are expected to contribute to the yields for the SRs introduced in the previous section. For SRAs and SRB, the main background is top-quark production which, according to MC estimates, contributes between 70% and 85% of the total background, depending upon the region considered, and is dominated by top-quark pairs produced in association with two b-quarks arising from gluon splitting. In the SRCs, the main backgrounds arise from Z + jets (up to 50% of the total) and from top-quark-related processes (up to 20% of the total). The main SM backgrounds in each SR are determined separately with a profile likeli- hood fit to the event yields in the associated CRs [90]. This is commonly referred to as a background-only fit which constrains and adjusts the normalisation of the background pro- cesses. The background-only fit uses the observed event yield and the expected number of MC events in the associated CRs, which are described by Poisson statistics, as a constraint to adjust the normalisation of the background processes assuming that no signal is present. The normalisation factor is referred to as the µ factor. The CRs are designed to be enriched in specific background contributions relevant to the analysis, whilst minimising the potential signal contamination, and they are orthogonal to the SRs. When performing the fit for SRA, a multi-bin approach is used, with a single CR divided into three bins of meff . Such an approach allows the calculation and use of a single normalisation parameter (applied to the main tt̄ background across all bins of meff ), and additionally enables the fit to take into account the modelling of the meff variable. – 12 – 𝑁(𝑏) 𝑆 SRC28 = 2 b-tags 28 SRC26 = Δ𝜙 jets, 𝐸 26 ∊[0.2, 0.4] ≥4 SRA, SRB CRA𝟏ℓ, CRB𝟏ℓ SRC24 24 CRC𝟏ℓ SRC22 22 CRC2ℓ VRC𝟎ℓ-Z 20 3 VRA0ℓ, VRB0ℓ VRC𝟎ℓ-T 17 15 0 1 ≤ 15 𝑁(ℓ) 0 1 2 𝑁 ℓ (a) (b) JHEP12(2019)060 Figure 3. Schematic diagrams of the fit strategies for (a) the A-, B- and (b) C-type regions. Generally the CRs require a different lepton multiplicity than the SRs. The validation regions are defined with a lower b-jet multiplicity requirement, except in the case of the VRC0`-T region, which instead inverts the SR min ∆φ(jet1−4 , pmiss T ) selection. The systematic uncertainties, described in section 7, are included in the fit as nuisance parameters. They are constrained by Gaussian distributions with widths corresponding to the sizes of the uncertainties and are treated as correlated, when appropriate, between the various regions. The product of the various probability density functions and the Gaussian distributions forms the likelihood function, which the fit maximises by adjusting the background normalisation and the nuisance parameters. This approach reduces the influence of systematic uncertainties on the backgrounds with dedicated CRs, as these are absorbed by the normalisation parameter. Finally, the reliability of the MC extrapolation of the SM background estimates outside of the CRs is evaluated in dedicated VRs, orthogonal to CRs and SRs. The fit strategies for the A- and B-type regions are very similar and are represented schematically in figure 3a. They rely on CRs with a single-lepton requirement, as the tt̄ background in the SR is dominated by semileptonic tt̄ decays where the lepton is not identified. The main background in both regions is tt̄ pair production in association with heavy-flavour jets. The fit strategy for the C-type regions is presented in figure 3b. The strategy is different because the main background in these regions is Z+jets, closely followed by the top-quark backgrounds. In order to define CRs enhanced in tt̄ and Z+jets, additional variables are used: q • mT : the event transverse mass mT is defined as mT = miss (1 − cos(∆φ)), 2pT (`)ET where ∆φ is the difference in azimuthal angle between the lepton and the pmiss T . This is used in the one-lepton CRs to reject multi-jet events which can be misidentified as containing a prompt lepton. • m`` : the invariant mass of the two leptons in the event. Since the two-lepton CR is used to constrain the Z+jets background, the m`` variable is required to be within the Z-mass window: [86, 106] GeV (used exclusively in the two-lepton CR). – 13 – miss : the ‘lepton corrected’ E miss . For the two-lepton CR the transverse momentum • ẼT T vectors of the leptons are subtracted from the ET miss calculation in order to mimic the neutrinos from Z → νν decays (used exclusively in the two-lepton CR). When designing the CRs and VRs, the potential signal contamination is checked in each region to ensure that the contribution from the signal process being targeted is small in the regions. The signal contamination in the CRs and VRs is found to be negligible, at the level of < 1% of the total SM expectation, depending upon the signal mass hierarchy of the models considered in this search. JHEP12(2019)060 6.1 A-type CR and VR definitions A single, tt̄-dominated CR (CRA1`) is defined for the A-type regions and is split into the same three identical meff selections as the SRAs. The CR is defined similarly to the SR selection (as documented in table 1); however, exactly one signal lepton (either e or µ) with pT > 20 GeV is required in the final state. Furthermore, the selections used to isolate the Higgs boson in the SRAs, namely the ∆Rmax (b, b), ∆Rmax-min (b, b) and m(hcand ) selections, are not applied in order to increase the number of events in the CR. The leading b-jet pT selection is lowered to > 100 GeV to further increase the number of events in the region, and a selection on the transverse mass of mT > 20 GeV is applied to suppress misidentified leptons. Such selections result in pure tt̄ CRs, with tt̄ contributing more than 80% of the total SM contribution in each of the CRs. The fraction of top-quark pairs produced in association with b-quarks is equivalent between CRs and SRs, and accounts for about 70% of the total tt̄ background. Figure 4a presents the distribution of m(hcand ) in CRA1`, and shows that this variable is well modelled. A zero-lepton validation region (VRA0`) is also defined, and split according to the same meff thresholds as the SRAs and CRAs. This VR is used to validate the modelling of the tt̄ background when extrapolating from the one-lepton CRs to zero-lepton regions. The selections are based upon the SR selections but the VRs are orthogonal due to the b-jet multiplicity selection, which requires exactly three b-jets. Additionally, the ∆Rmax (b, b), ∆Rmax-min (b, b) and m(hcand ) selections are not applied in this region. A selection of S < 22 is applied to ensure this region is orthogonal to the SRC regions. 6.2 B-type CR and VR definitions For the B-type tt̄ CR (CRB1`), a similar method of using a one-lepton region enriched in tt̄ is implemented. The SR selections (as documented in table 2) are applied, and additionally exactly one signal lepton with pT > 20 GeV is required. The m(hcand1 , hcand2 )avg selection miss )| selection is dropped to increase the number of events in the region, and the |∆φ(j1 , ET is loosened to > 2.2. Similarly to the A-type CR, a selection of mT > 20 GeV is applied to suppress misidentified leptons. These selections result in a pure CR with 80% of the total expected SM background consisting of tt̄. Figure 4b presents the m(hcand1 , hcand2 )avg distribution in this region; it is shown to be well modelled. The associated VR (VRB0`) is defined in a similar manner to the A-type VR, with selections similar to those of the SRB region, but an exclusive b-jet multiplicity selection – 14 – Events / 50 GeV 20 Events / 50 GeV 80 ATLAS tt Other 18 ATLAS tt Other s = 13 TeV, 139 fb-1 s = 13 TeV, 139 fb-1 70 Single-top SM Total 16 Single-top Z+jets CRA1L, post-fit CRB1L, post-fit 60 Data 14 SM Total Data 12 50 10 40 8 30 6 20 4 10 2 2 2 Data/SM Data/SM 1 1 0 0 0 50 100 150 200 250 300 350 400 0 50 100 150 200 250 300 350 400 JHEP12(2019)060 m (hcand) [GeV] m (hcand1,hcand2)avg [GeV] (a) (b) 104 Events / 100 GeV 80 ATLAS Events / 1 Z+jets Other ATLAS tt Other 70 s = 13 TeV, 139 fb-1 103 s = 13 TeV, 139 fb-1 CRC2L, post-fit tt SM Total CRC1L, post-fit Single-top Z+jets 60 Data SM Total Data 102 50 40 10 30 1 20 10 10−1 2 2 Data/SM Data/SM 1 1 0 0 250 300 350 400 450 500 550 600 650 700 750 18 20 22 24 26 28 30 ~ miss Object Based Emiss Significance ET [GeV] T (c) (d) miss Figure 4. Distributions of (a) m(hcand ) in CRA1`, (b) m(hcand1 , hcand2 )avg in CRB1`, (c) ẼT in CRC2`, and (d) S in CRC1` after the background-only fit; ratios of data to SM predictions are reported in the bottom panels. All uncertainties as defined in section 7 are included in the uncertainty bands of the top and bottom panels in each plot. The backgrounds which contribute only a small amount (diboson, W +jets and tt̄ +W/Z/h) are grouped and labelled as ‘Other’. Overflow events which do not fall into the axis range are placed into the rightmost bin. of exactly three b-jets. Additionally, the selections used to reconstruct the Higgs bosons in the event are dropped to enhance the number of events in the region. A selection of S < 22 is also applied to ensure this region is orthogonal to the C-type SRs. 6.3 C-type CR and VR definitions Two CRs are defined for the C-type SRs, one to constrain the Z+jets background (CRC2`) and one to constrain the backgrounds associated with top quarks, tt̄ and single top (CRC1`). A single normalisation parameter is used to constrain both the tt̄ and single-top backgrounds, while the Z+jets background is constrained with an additional normalisation parameter. These CRs are based upon the SR shown in table 3, but are orthogonal due to the different lepton multiplicities required. – 15 – The CRC2` requires two same-flavour (SF) opposite-sign (OS) leptons, with invariant mass in the Z-mass window. The leading two leptons are required to have pT > 27 GeV and pT > 20 GeV respectively. To imitate the ET miss selection in the SR, a selection of miss ẼT > 250 GeV is utilised. For this region the selections on S are dropped to enhance the number of events in the region. Figure 4c shows the ẼT miss distribution in this region. The CRC1` region used to constrain the top-quark-related backgrounds requires one signal lepton with pT > 20 GeV. A selection of S > 17 is applied. Similarly to the A- and B-type CRs, a selection of mT > 20 GeV is applied to remove the multi-jet contribution with fake or non-prompt leptons. Figure 4d presents the S distribution in this region. Two zero-lepton VRs are defined to validate the extrapolation from CR to SR based on JHEP12(2019)060 the SR selections. A VR with zero leptons and two b-jets (VRC0`-Z) with S ∈ [20, 22] and ETmiss ∈ [250, 600] GeV ensures a region orthogonal to the SR, but with a large contribution from the Z+jets process. A second VR is used to validate the modelling of the tt̄ and single-top backgrounds (VRC0`-T); a selection of zero leptons, S ∈ [15, 22] and an inverted selection on the min ∆φ(jet1−4 , pmiss T ) ∈ [0.2, 0.4] is applied to ensure orthogonality. 6.4 Summary of CR and VR results A full overview of the control and validation regions used in the analysis can be found in table 4. The control region pre-fit yields and fitted normalisation factors µbkg for the A-, B- and C-type regions are presented in figure 5a. All µ values are consistent with unity, within 2σ of the normalisation uncertainty, suggesting the modelling of the key SM background processes is already good before performing the fit. Figure 5b presents the observed yields, post-fit background estimates and significance [91] for the A-, B- and C-type validation regions. The background-only fit estimates are in good agreement with the data in these regions, and the post-fit expectation is within 1σ of the central value for all regions. – 16 – Events 104 tt Other ATLAS -1 Single-top s = 13 TeV, 139 fb Z+jets 103 CRs, pre-fit SM Total Data 102 10 1 JHEP12(2019)060 1.2 bkg 1 µ 0.8 CRA1l-L CRA1l-M CRA1l-H CRB1l CRC1l CRC2l (a) 105 Events tt Z+jets ATLAS 104 s = 13 TeV, 139 fb -1 Other Single-top VRs, post-fit SM Total Data 103 102 10 1 Significance 2 0 −2 VRA0l-L VRA0l-M VRA0l-H VRB0l VRC0l-T VRC0l-Z (b) Figure 5. (a) Control region event pre-fit event yields compared with SM MC predictions (top) and post-fit µ scale factors (bottom) for the A-, B- and C-type regions. The uncertainty in the µ factors and the total expected yield include statistical and systematic uncertainties as introduced in section 7. For the A-type regions, since the fit is performed in the meff intervals, the normalisation is applied to all bins equally. (b) Results of the background-only fit extrapolated to VRs for the A-, B- and C-type regions. The normalisation of the backgrounds is obtained from the fit to the CRs. The upper panel shows the observed number of events and the predicted background yields. Statistical and systematic uncertainties as introduced in section 7 are included in the uncertainty band. The lower panel shows the significance in each VR. The significance calculation is performed as described in ref. [91]. The minor backgrounds (diboson, W +jets and tt̄ +W/Z/h) are grouped and labelled as ‘Other’. – 17 – Control Regions Validation Regions Variable Units CRA1` CRB1` CRC1` CRC2` VRA0` VRB0` VRC0`-T VRC0`-Z miss Trigger ET 3 3 3 — 3 3 3 3 Lepton Trigger — — — 3 — — — — miss ET [GeV] > 250 > 300 > 250 < 70 > 350 > 350 > 250 ∈ [250, 600] miss )] min[∆φ(jet1−4 , ET [rad] — — — > 0.2 > 0.4 > 0.4 ∈ [0.2, 0.4] > 1.2 Nleptons (baseline) =1 =1 =1 =2 =0 =0 =0 =0 Nleptons (signal) =1 =1 =1 = 2(SFOS) — — — — pT (`1 ) [GeV] > 20 > 20 > 20 > 27 — — — — pT (`2 ) [GeV] — — — > 20 — — — — mT [GeV] > 20 > 20 > 20 — — — — — m`` [GeV] — — — ∈ [86, 106] — — — — – 18 – τ veto — 3 — — 3 3 — — Njets ≥6 ≥4 ≥4 ≥4 ≥6 ≥4 ≥4 ≥4 Nb-jets ≥4 ≥4 ≥3 ≥3 =3 =3 ≥3 =2 pT (b1 ) [GeV] > 100 — — — > 100 — — — pT (j1 ) [GeV] — > 350 — — — > 350 — — Leading jet not b-tagged — 3 — — — 3 — — miss )| |∆φ(j1 , ET [rad] — > 2.2 — — — > 2.8 — — miss ẼT [GeV] — — — > 250 — — — — S — — > 17 — < 22 < 22 ∈ [15, 22] ∈ [20, 22] meff [TeV] > 1.0 > 1.0 — — > 1.0 > 1.0 — — Table 4. Summary of all control and validation region definitions used in the analysis. JHEP12(2019)060 7 Systematic uncertainties Several sources of experimental and theoretical systematic uncertainty on the signal and background estimates are considered in this analysis. Their impact is reduced by fitting the event yields and normalising the dominant backgrounds in the CRs defined with kinematic selections resembling those of the corresponding SRs (see section 6). Uncertainties due to the numbers of events in the CRs are also introduced in the fit for each region. The magnitude of the contributions arising from detector, theoretical modelling and statistical uncertainties are summarized in table 5. Dominant detector-related systematic uncertainties arise from the b-tagging efficiency JHEP12(2019)060 and mis-tagging rates, and from the jet energy scale and resolution. In SRA and SRB, the contributions of these uncertainties are almost equivalent. In SRC, the b-tagging un- certainty is dominant. The systematic uncertainty on the b-tagging efficiency ranges from 4.5% for b-jets with pT ∈ [35, 40] GeV up to 7.5% for b-jets with high pT (> 100 GeV). The b-tagging uncertainty is estimated by varying the η-, pT - and flavour-dependent scale factors applied to each jet in the simulation within a range that reflects the systematic uncertainty in the measured tagging efficiency and mis-tag rates in data [81]. The uncertainties in the jet energy scale and resolution are based on their respective measurements in data [77, 92]. The uncertainties associated with lepton reconstruction and energy measurements have a negligible impact on the final results; however, the lepton, photon and jet-related uncer- tainties are propagated to the calculation of the ET miss , and additional uncertainties due to the energy scale and resolution of the soft term are included in the ET miss . The systematic uncertainties related to the modelling of the energy of jets and leptons in the simulation are propagated to S. No additional uncertainty on the energy resolution is applied, as the resolutions are taken to be the maximum of the parameterised data and simulation resolutions when performing the calculation for both data and MC simulation. Uncertainties in the modelling of the SM background processes from MC simulation and their theoretical cross-section uncertainties are also taken into account. The dominant uncertainties in SRA and SRB arise from theoretical and modelling uncertainties of the tt̄ background. They are computed as the difference between the predictions from nomi- nal samples and those from additional samples differing in hard-scattering generator and parameter settings, or by using internal weights assigned to the events depending on the choice of renormalisation and factorisation scales, initial- and final-state radiation param- eters, and PDF sets. The impact of the PS and hadronisation model is evaluated by com- paring the nominal generator with a POWHEG sample interfaced to HERWIG 7 [93, 94], using the H7UE set of tuned parameters [94]. To assess the uncertainty due to the choice of hard-scattering generator and matching scheme, an alternative generator setup using aMC@NLO+PYTHIA8 is employed. It uses the shower starting scale, µq = HT /2, where HT is defined here as the scalar sum of the pT of all outgoing partons. The dominant uncertainties in SRC arise from the MC modelling of the Z+jets process, followed by the tt̄ and single-top modelling. The Z+jets (as well as W+jets) modelling uncer- tainties are estimated by considering different merging (CKKW-L) and resummation scales using alternative samples, PDF variations from the NNPDF3.0 NNLO replicas [55], and – 19 – Region SRA SRB SRC Total background expectation 17.1 3.3 37.9 Total background uncertainty 2.8 (16%) 0.9 (27%) 6.2 (16%) Systematic, experimental 1.4 (8%) 0.3 (10%) 3.0 (8%) Systematic, theoretical 2.3 (13%) 0.6 (18%) 3.2 (8%) Statistical, MC samples 0.7 (4%) 0.4 (12%) 2.0 (5%) Table 5. Expected background event yields and dominant systematic uncertainties on background estimates in the A-type (inclusive), B-type and C-type (inclusive) regions. Individual uncertainties JHEP12(2019)060 can be correlated, and do not necessarily add up quadratically to the total background uncertainty. The percentages show the size of the uncertainty relative to the total expected background. variations of factorisation and renormalisation scales in the ME. The latter have been evalu- ated using 7 point-variations, changing the renormalisation and factorisation scales up and down by factors 0.5 and 2, such that when one scale is up the other is down, and vice-versa. For the SUSY signal processes, both the experimental and theoretical uncertainties in the expected signal yield are considered. Experimental uncertainties are found to be 6–36% across the mass plane with fixed LSP mass for A-type SRs, and 4–40% for C-type SRs. For models where ∆m(χ̃02 , χ̃01 ) = 130 GeV is assumed, scenarios where SRB is relevant have uncertainties of 11–37%. In all SRs, the dominant uncertainty on the signal yields is found to be from the b-tagging efficiency. Theoretical uncertainties in the approximate NNLO+NNLL cross-section are calcu- lated for each SUSY signal scenario, and are dominated by the uncertainties in the renor- malisation and factorisation scales, followed by the uncertainty in the PDFs. These are 7–17% for bottom-squark masses in the range between 400 GeV and 1500 GeV. Additional uncertainties in the acceptance and efficiency due to the modelling of ISR and CKKW scale variations in SUSY signal MC samples are also taken into account, and contribute up to ∼10%. 8 Results and interpretation The event yields for all SRs are reported in table 6. The SM background expectations resulting from background-only fits are also reported showing statistical plus systematic uncertainties. The largest background contribution in A-type and B-type SRs arises from tt̄ production, whilst the contribution from Z → ν ν̄ production in association with b- quarks is largest in the C-type SRs, with sub-dominant contributions from the tt̄ and single-top processes. Other background sources are tt̄ +W/Z, tt̄ +h, diboson and W +jets production. The results are also summarised in figure 6, where the significances for each of the SRs are also presented. No significant deviations are observed between expected and observed yields in all signal regions considered. – 20 – 103 Events Z+jets tt ATLAS -1 Single-top s = 13 TeV, 139 fb Other 102 SRs, post-fit SM Total Data 10 1 JHEP12(2019)060 Significance 2 0 −2 SRA-L SRA-M SRA-H SRB SRC22 SRC24 SRC26 SRC28 Figure 6. Results of the background-only fit extrapolated to all SRs. The normalisation of the backgrounds is obtained from the fit to the CRs. The upper panel shows the observed number of events and the predicted background yields. The backgrounds which contribute only a small amount (diboson, W +jets and tt̄ +W/Z/h) are grouped and labelled as “Other”. All uncertainties defined in section 7 are included in the uncertainty band. The lower panel shows the significance in each SR. The significance calculation is performed as described in ref. [91]. Figure 7 shows comparisons between the observed data and the post-fit SM predictions for some relevant kinematic distributions for the inclusive SRA, SRB and SRC selections before selection requirements are applied on the quantity shown. The expected distribu- tions for scenarios with different bottom squark, χ̃02 and χ̃01 masses (depending on the SR considered) are shown for illustrative purposes. The CLs technique [95] is used to place 95% Confidence Level (CL) upper limits on event yields from physics beyond the SM (BSM) for each signal region. The profile- likelihood-ratio test statistic is used to exclude the signal-plus-background hypothesis for specific signal models. When normalised to the integrated luminosity of the data sample, results can be interpreted as corresponding upper limits on the visible cross-section, σvis , defined as the product of the BSM production cross-section, the acceptance and the selec- tion efficiency of a BSM signal. When calculating the model-independent upper limits of the A- and C-type regions, only the inclusive SR selection is used. Table 7 summarises the 95 ) and expected (S 95 ) 95% CL upper limits on the number of BSM events observed (Sobs exp and on σvis for all SRs. The p0 -values, which represent the probability of the SM back- ground to fluctuate to the observed number of events or higher, are also provided and are capped at p0 = 0.5; the associated significance is provided in parentheses. Model-dependent exclusion limits are obtained assuming the two types of SUSY parti- cle mass hierarchies described in section 1. The lightest bottom squark decays exclusively via b̃1 → bχ̃02 with subsequent decay χ̃02 → hχ̃01 . The expected limits from the SRs are – 21 – SRA SRA-L SRA-M SRA-H SRB Observed events 17 12 3 2 3 Fitted SM bkg events 17.1 ± 2.8 8.4 ± 1.7 5.7 ± 0.8 3.0 ± 1.5 3.3 ± 0.9 tt̄ 10.1 ± 2.5 4.7 ± 1.5 3.7 ± 0.6 1.7 ± 1.4 2.3 ± 0.8 Z+jets 2.6 ± 0.4 1.3 ± 0.2 0.9 ± 0.2 0.4 ± 0.1 0.3 ± 0.1 Single-top 1.4 ± 0.3 0.4 ± 0.1 0.3 ± 0.1 0.6 ± 0.2 0.5 ± 0.1 tt̄ +W /Z 1.2 ± 0.3 0.7 ± 0.1 0.3 ± 0.1 0.1 ± 0.0 0.07 ± 0.02 tt̄ +h 1.1 ± 0.2 0.7 ± 0.1 0.3 ± 0.1 0.1 ± 0.0 0.13 ± 0.02 W +jets 0.4 ± 0.1 0.2 ± 0.1 0.1 ± 0.0 – 0.02 ± 0.01 JHEP12(2019)060 Diboson 0.4 ± 0.1 0.3 ± 0.1 – – – m(b̃1 , χ̃02 , χ̃01 ) = (1100, 330, 200) GeV 13.7 ± 0.3 0.7 ± 0.1 6.3 ± 0.2 6.6 ± 0.2 0.3 ± 0.1 m(b̃1 , χ̃02 , χ̃01 ) = (700, 680, 550) GeV 1.3 ± 0.6 0.2 ± 0.1 0.5 ± 0.4 0.6 ± 0.4 7.4 ± 1.2 m(b̃1 , χ̃02 , χ̃01 ) = (1200, 1150, 60) GeV 8.7 ± 0.2 1.4 ± 0.1 3.4 ± 0.1 3.8 ± 0.1 0.6 ± 0.1 SRC SRC22 SRC24 SRC26 SRC28 Observed events 47 28 12 4 3 Fitted SM bkg events 37.9 ± 6.2 21.2 ± 4.1 10.6 ± 2.3 3.7 ± 0.9 2.4 ± 0.6 tt̄ 5.4 ± 2.6 3.9 ± 2.3 1.1 ± 0.6 0.3 ± 0.3 0.1 ± 0.1 Z+jets 17.6 ± 4.7 8.8 ± 2.5 6.0 ± 1.8 1.7 ± 0.7 1.1 ± 0.4 Single-top 5.0 ± 1.5 2.7 ± 1.0 1.2 ± 0.3 0.7 ± 0.2 0.4 ± 0.1 tt̄ +W /Z 4.3 ± 0.6 2.5 ± 0.4 1.1 ± 0.2 0.5 ± 0.1 0.2 ± 0.1 tt̄ +h 0.2 ± 0.0 0.2 ± 0.0 — 0.1 ± 0.0 0.0 ± 0.0 W +jets 3.5 ± 0.8 2.2 ± 0.5 0.6 ± 0.2 0.2 ± 0.1 0.4 ± 0.1 Diboson 1.8 ± 0.3 0.9 ± 0.2 0.6 ± 0.1 0.2 ± 0.0 0.1 ± 0.1 m(b̃1 , χ̃02 , χ̃01 ) = (1100, 330, 200) GeV 0.4 ± 0.1 0.3 ± 0.1 0.1 ± 0.0 0.03 ± 0.02 0.03 ± 0.01 m(b̃1 , χ̃02 , χ̃01 ) = (700, 680, 550) GeV 1.2 ± 0.5 0.5 ± 0.2 0.7 ± 0.4 — — m(b̃1 , χ̃02 , χ̃01 ) = (1200, 1150, 60) GeV 26.7 ± 0.3 6.3 ± 0.2 6.4 ± 0.2 5.8 ± 0.2 8.3 ± 0.2 Table 6. Background-only fit results for the A- and B-type regions (top table) and C-type re- gions (bottom table) performed using 139 fb−1 of data. The quoted uncertainties on the fitted SM background include both the statistical and systematic uncertainties. Signal channel σvis [fb] 95 Sobs 95 Sexp CLB p0 (Z) SRA 0.06 9.0 10.1+4.7 −3.1 0.38 0.50 (0.00) SRB 0.04 4.9 5.1+2.8 −1.7 0.45 0.50 (0.00) SRC 0.19 26.0 20.8+7.0 −5.5 0.80 0.17 (0.97) Table 7. From left to right, observed 95% CL upper limits on the visible cross sections σvis , the 95 95 observed (Sobs ) and expected (Sexp ) 95% CL upper limits on the number of signal events with ± 1 σ excursions of the expectation, the CL of the background-only hypothesis, CL B , the discovery p-value (p0 ), truncated at 0.5, and the associated significance (in parentheses). – 22 – 12 12 Events / 200 GeV Events / 40 GeV ATLAS tt Other ATLAS tt Other 10 s = 13 TeV, 139 fb-1 Z+jets Single-top 10 s = 13 TeV, 139 fb-1 Z+jets Single-top SRA, post-fit SM Total Data SRA, post-fit SM Total Data 8 8 ~ ∼0 ∼0 ~ ∼0 ∼0 m(b1,χ ,χ ) = 1100, 330, 200 GeV m(b1,χ ,χ ) = 1100, 330, 200 GeV 2 1 2 1 6 6 4 4 2 2 1000 1500 2000 2500 3000 0 50 100 150 200 250 300 350 400 450 JHEP12(2019)060 meff [GeV] m(h cand) [GeV] (a) (b) Events / 100 GeV Events / 25 GeV 6 ATLAS tt Z+jets 6 ATLAS tt Other s = 13 TeV, 139 fb-1 Other Single-top s = 13 TeV, 139 fb-1 Z+jets Single-top 5 5 SRB, post-fit SM Total Data SRB, post-fit SM Total Data 4 ~ ∼0 ∼0 m(b1,χ 2 ,χ ) = 700, 680, 550 GeV 1 4 ~ ∼0 ∼0 m(b1,χ ,χ ) = 700, 680, 550 GeV 2 1 3 3 2 2 1 1 100 200 300 400 500 600 700 800 900 50 100 150 200 250 300 350 400 450 p (j ) [GeV] m(h cand1,h cand2)avg [GeV] T 1 (c) (d) 104 Events / 100 GeV Events / 1 ATLAS ATLAS Z+jets tt 25 Z+jets Other s = 13 TeV, 139 fb-1 Other Single-top s = 13 TeV, 139 fb-1 103 SRC, post-fit tt Single-top SM Total Data ~ 0 ∼0 20 SRC, post-fit SM Total Data 102 m(b1,∼ χ ,χ ) = 1200, 1150, 60 GeV 2 1 ~ ∼0 ∼0 m(b1,χ ,χ ) = 1200, 1150, 60 GeV 2 1 10 15 1 10 10−1 5 2 Data/SM 1 0 18 20 22 24 26 28 30 32 34 36 200 400 600 800 1000 1200 1400 miss Object Based Emiss Significance T ET [GeV] (e) (f ) Figure 7. Post-fit distributions of (a) the meff and (b) the m(hcand ) in the inclusive SRA region; (c) the leading jet pT and (d) the m(hcand1 , hcand2 )avg for the Higgs candidates in the SRB region; miss (e) ET and (f) S for SRC regions. All SR selections are applied except for the selection on the variable shown, where the selection on the variable under consideration is denoted by an arrow, except in the case of (e), where the full SRC selection is applied. All uncertainties as defined in section 7 are included in the uncertainty band. The minor backgrounds (diboson, W +jets and tt̄ +W/Z/h) are grouped and labelled as “Other”. For illustration, contributions expected for scenarios with different bottom-squark, χ̃02 and χ̃01 masses depending on the SR considered are superimposed. Overflow events which do not fall into the axis range are placed into the right-most bin. – 23 – compared for each set of scenarios and the observed limits are obtained by choosing the SR with the best expected sensitivity for each SUSY model. The fit procedure takes into account correlations in the yield predictions between control and signal regions due to common background normalisation parameters and systematic uncertainties. The experi- mental systematic uncertainties in the signal are taken into account for the calculation and are assumed to be fully correlated with those in the SM background. Figures 8a and 8b show the observed (solid line) and expected (dashed line) exclusion contours at 95% CL in the b̃1 –χ̃02 mass planes for the two types of SUSY scenarios con- sidered. For the scenarios where the mass of the neutralino is assumed to be 60 GeV, the sensitivity to models with the largest mass difference between the b̃1 and the χ̃02 is achieved JHEP12(2019)060 with the combination of the A-type SRs. Sensitivity to scenarios with small mass differences is obtained with the dedicated C-type SRs. For scenarios with ∆m(χ̃02 , χ̃01 ) = 130 GeV, the sensitivity of the A-type SRs is complemented by the B-type SR in the case of small mass difference between the b̃1 and the χ̃02 . Bottom-squark masses up to 1.5 TeV are excluded for models with fixed mχ̃01 = 60 GeV and χ̃02 masses ∈ [0.5, 1.1] TeV. In case of ∆m(χ̃02 , χ̃01 ) = 130 GeV, bottom-squark masses up to 1.3 TeV are excluded for χ̃02 masses up to 750 GeV. The losses in sensitivity for models where χ̃02 masses are below 190 GeV are due to the stringent requirements on ET miss . The results constitute a large improvement upon previous Run-1 searches and signifi- cantly strengthen the constraints on bottom squark masses; they are also complementary to other searches where bottom squarks are assumed to decay directly to a bottom-quark and a neutralino or to a top-quark and a chargino [96]. – 24 – ~ ~ ~ ∼0 → b h χ ∼0 ; m(χ ∼0) = 60 GeV b1 b1 production ; b1 → b χ 2 1 1 ∼ ) [GeV] 1600 ATLAS s=13 TeV, 139 fb-1, 95% CL 1400 0 2 m(χ Expected Limit (± 1 σexp ) SUSY Observed Limit (± 1 σtheory) 1200 ATLAS 8 TeV, 20.3 fb -1 (observed) 1000 ~b )1 ( m 0 > JHEP12(2019)060 ∼χ )2 ( 800 m n de rbid Fo lly 600 at ica n em Ki 400 200 200 400 600 800 1000 1200 1400 1600 ~ m(b1) [GeV] (a) ~ ~ ~ ∼0 → b h χ ∼0 ; ∆ m (χ ∼0, χ ∼0) = 130 GeV b1 b1 production ; b1 → b χ 2 1 2 1 ∼ ) [GeV] 1400 ATLAS s=13 TeV, 139 fb-1, 95% CL 0 2 1200 m(χ Expected Limit (± 1 σexp) SUSY Observed Limit (± 1 σtheory ) 1000 ~b ) m( 1 ∼0 ) > 800 m (χ 2 en dd rbi y Fo 600 all tic ma Kine 400 200 400 600 800 1000 1200 1400 ~ m(b1) [GeV] (b) Figure 8. Exclusion contour at the 95% CL in the m(b̃1 , χ̃02 ) phase space for (a) the m(χ̃01 ) = 60 GeV signal scenario, ATLAS Run 1 limit taken from ref. [27] and (b) the ∆m(χ̃02 , χ̃01 ) = 130 GeV signal scenario, using the SR with the best-expected sensitivity. The theory uncertainty band contains the systematic uncertainties on the signal model under consideration and the uncertainty in the signal cross section. – 25 – 9 Conclusion The result of a search for pair production of bottom squarks is reported. The analysis √ uses 139 fb−1 of pp collisions at s = 13 TeV collected by the ATLAS experiment at the LHC between 2015 and 2018. R-parity-conserving SUSY scenarios where bottom squarks decay into a b-quark and the second-lightest neutralino, b̃1 → b + χ̃02 , with χ̃02 subsequently decaying into a Higgs boson like the one in the SM and the lightest neutralino, are consid- ered. The search investigates final states containing large missing transverse momentum and three or more b-jets. No significant excess of events above the expected Standard Model background is found and exclusion limits at the 95% confidence level are placed on JHEP12(2019)060 the visible cross-section and on the mass of the bottom squark for various assumptions about the mass hierarchy of the b̃1 , χ̃02 and χ̃01 . Bottom-squark masses up to 1.5 (1.3) TeV are excluded for χ̃02 masses up to 1100 (750) GeV in models with fixed m(χ̃01 ) = 60 GeV (∆m(χ̃02 , χ̃01 ) = 130 GeV). As the first search for such scenarios carried out by ATLAS in Run 2, these results are a significant improvement upon the previous Run-1 result, considerably tightening the constraints on bottom-squark production. Acknowledgments We thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Aus- tralia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; MNE/IFA, Romania; MES of Russia and NRC KI, Russian Federation; JINR; 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 – 26 – (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. [97]. Open Access. 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Handl114 , B. Haney137 , R. Hankache136 , E. Hansen96 , J.B. Hansen40 , J.D. Hansen40 , M.C. Hansen24 , P.H. Hansen40 , E.C. Hanson100 , K. Hara169 , A.S. Hard181 , T. Harenberg182 , S. Harkusha107 , P.F. Harrison178 , N.M. Hartmann114 , Y. Hasegawa150 , A. Hasib50 , S. Hassani145 , S. Haug20 , R. Hauser106 , L.B. Havener39 , M. Havranek142 , C.M. Hawkes21 , R.J. Hawkings36 , D. Hayden106 , C. Hayes155 , R.L. Hayes175 , C.P. Hays135 , J.M. Hays92 , H.S. Hayward90 , S.J. Haywood144 , F. He60a , M.P. Heath50 , V. Hedberg96 , L. Heelan8 , S. Heer24 , K.K. Heidegger52 , W.D. Heidorn78 , J. Heilman34 , S. Heim46 , T. Heim18 , B. Heinemann46,av , J.J. Heinrich131 , L. Heinrich36 , C. Heinz56 , J. Hejbal141 , L. Helary61b , A. Held175 , S. Hellesund134 , C.M. Helling146 , S. Hellman45a,45b , C. Helsens36 , – 36 – R.C.W. Henderson89 , Y. Heng181 , S. Henkelmann175 , A.M. Henriques Correia36 , G.H. Herbert19 , H. Herde26 , V. Herget177 , Y. Hernández Jiménez33c , H. Herr99 , M.G. Herrmann114 , T. Herrmann48 , G. Herten52 , R. Hertenberger114 , L. Hervas36 , T.C. Herwig137 , G.G. Hesketh94 , N.P. Hessey168a , A. Higashida163 , S. Higashino81 , E. Higón-Rodriguez174 , K. Hildebrand37 , E. Hill176 , J.C. Hill32 , K.K. Hill29 , K.H. Hiller46 , S.J. Hillier21 , M. Hils48 , I. Hinchliffe18 , F. Hinterkeuser24 , M. Hirose133 , S. Hirose52 , D. Hirschbuehl182 , B. Hiti91 , O. Hladik141 , D.R. Hlaluku33c , X. Hoad50 , J. Hobbs155 , N. Hod180 , M.C. Hodgkinson149 , A. Hoecker36 , F. Hoenig114 , D. Hohn52 , D. Hohov132 , T.R. Holmes37 , M. Holzbock114 , L.B.A.H Hommels32 , S. Honda169 , T. Honda81 , T.M. Hong139 , A. Hönle115 , B.H. Hooberman173 , W.H. Hopkins6 , Y. Horii117 , P. Horn48 , L.A. Horyn37 , A. Hostiuc148 , S. Hou158 , A. Hoummada35a , J. Howarth100 , J. Hoya88 , M. Hrabovsky130 , J. Hrdinka76 , I. Hristova19 , J. Hrivnac132 , A. Hrynevich108 , JHEP12(2019)060 T. Hryn’ova5 , P.J. Hsu64 , S.-C. Hsu148 , Q. Hu29 , S. Hu60c , Y. Huang15a , Z. Hubacek142 , F. Hubaut101 , M. Huebner24 , F. Huegging24 , T.B. Huffman135 , M. Huhtinen36 , R.F.H. Hunter34 , P. Huo155 , A.M. Hupe34 , N. Huseynov79,ai , J. Huston106 , J. Huth59 , R. Hyneman105 , S. Hyrych28a , G. Iacobucci54 , G. Iakovidis29 , I. Ibragimov151 , L. Iconomidou-Fayard132 , Z. Idrissi35e , P. Iengo36 , R. Ignazzi40 , O. Igonkina120,ac,∗ , R. Iguchi163 , T. Iizawa54 , Y. Ikegami81 , M. Ikeno81 , D. Iliadis162 , N. Ilic119,167,ag , F. Iltzsche48 , G. Introzzi70a,70b , M. Iodice74a , K. Iordanidou168a , V. Ippolito72a,72b , M.F. Isacson172 , M. Ishino163 , M. Ishitsuka165 , W. Islam129 , C. Issever135 , S. Istin160 , F. Ito169 , J.M. Iturbe Ponce63a , R. Iuppa75a,75b , A. Ivina180 , H. Iwasaki81 , J.M. Izen43 , V. Izzo69a , P. Jacka141 , P. Jackson1 , R.M. Jacobs24 , B.P. Jaeger152 , V. Jain2 , G. Jäkel182 , K.B. Jakobi99 , K. Jakobs52 , S. Jakobsen76 , T. Jakoubek141 , J. Jamieson57 , K.W. Janas83a , R. Jansky54 , J. Janssen24 , M. Janus53 , P.A. Janus83a , G. Jarlskog96 , N. Javadov79,ai , T. Javůrek36 , M. Javurkova52 , F. Jeanneau145 , L. Jeanty131 , J. Jejelava159a,aj , A. Jelinskas178 , P. Jenni52,b , J. Jeong46 , N. Jeong46 , S. Jézéquel5 , H. Ji181 , J. Jia155 , H. Jiang78 , Y. Jiang60a , Z. Jiang153,r , S. Jiggins52 , F.A. Jimenez Morales38 , J. Jimenez Pena115 , S. Jin15c , A. Jinaru27b , O. Jinnouchi165 , H. Jivan33c , P. Johansson149 , K.A. Johns7 , C.A. Johnson65 , K. Jon-And45a,45b , R.W.L. Jones89 , S.D. Jones156 , S. Jones7 , T.J. Jones90 , J. Jongmanns61a , P.M. Jorge140a , J. Jovicevic36 , X. Ju18 , J.J. Junggeburth115 , A. Juste Rozas14,aa , A. Kaczmarska84 , M. Kado72a,72b , H. Kagan126 , M. Kagan153 , C. Kahra99 , T. Kaji179 , E. Kajomovitz160 , C.W. Kalderon96 , A. Kaluza99 , A. Kamenshchikov123 , L. Kanjir91 , Y. Kano163 , V.A. Kantserov112 , J. Kanzaki81 , L.S. Kaplan181 , D. Kar33c , M.J. Kareem168b , S.N. Karpov79 , Z.M. Karpova79 , V. Kartvelishvili89 , A.N. Karyukhin123 , L. Kashif181 , R.D. Kass126 , A. Kastanas45a,45b , Y. Kataoka163 , C. Kato60d,60c , J. Katzy46 , K. Kawade82 , K. Kawagoe87 , T. Kawaguchi117 , T. Kawamoto163 , G. Kawamura53 , E.F. Kay176 , V.F. Kazanin122b,122a , R. Keeler176 , R. Kehoe42 , J.S. Keller34 , E. Kellermann96 , D. Kelsey156 , J.J. Kempster21 , J. Kendrick21 , O. Kepka141 , S. Kersten182 , B.P. Kerševan91 , S. Ketabchi Haghighat167 , M. Khader173 , F. Khalil-Zada13 , M. Khandoga145 , A. Khanov129 , A.G. Kharlamov122b,122a , T. Kharlamova122b,122a , E.E. Khoda175 , A. Khodinov166 , T.J. Khoo54 , E. Khramov79 , J. Khubua159b , S. Kido82 , M. Kiehn54 , C.R. Kilby93 , Y.K. Kim37 , N. Kimura94 , O.M. Kind19 , B.T. King90,∗ , D. Kirchmeier48 , J. Kirk144 , A.E. Kiryunin115 , T. Kishimoto163 , D.P. Kisliuk167 , V. Kitali46 , O. Kivernyk5 , E. Kladiva28b,∗ , T. Klapdor-Kleingrothaus52 , M. Klassen61a , M.H. Klein105 , M. Klein90 , U. Klein90 , K. Kleinknecht99 , P. Klimek121 , A. Klimentov29 , T. Klingl24 , T. Klioutchnikova36 , F.F. Klitzner114 , P. Kluit120 , S. Kluth115 , E. Kneringer76 , E.B.F.G. Knoops101 , A. Knue52 , D. Kobayashi87 , T. Kobayashi163 , M. Kobel48 , M. Kocian153 , P. Kodys143 , P.T. Koenig24 , T. Koffas34 , N.M. Köhler36 , T. Koi153 , M. Kolb61b , I. Koletsou5 , T. Komarek130 , T. Kondo81 , N. Kondrashova60c , K. Köneke52 , A.C. König119 , T. Kono125 , R. Konoplich124,aq , V. Konstantinides94 , N. Konstantinidis94 , B. Konya96 , R. Kopeliansky65 , S. Koperny83a , K. Korcyl84 , K. Kordas162 , G. Koren161 , A. Korn94 , I. Korolkov14 , E.V. Korolkova149 , N. Korotkova113 , O. Kortner115 , S. Kortner115 , T. Kosek143 , – 37 – V.V. Kostyukhin24 , A. Kotwal49 , A. Koulouris10 , A. Kourkoumeli-Charalampidi70a,70b , C. Kourkoumelis9 , E. Kourlitis149 , V. Kouskoura29 , A.B. Kowalewska84 , R. Kowalewski176 , C. Kozakai163 , W. Kozanecki145 , A.S. Kozhin123 , V.A. Kramarenko113 , G. Kramberger91 , D. Krasnopevtsev60a , M.W. Krasny136 , A. Krasznahorkay36 , D. Krauss115 , J.A. Kremer83a , J. Kretzschmar90 , P. Krieger167 , F. Krieter114 , A. Krishnan61b , K. Krizka18 , K. Kroeninger47 , H. Kroha115 , J. Kroll141 , J. Kroll137 , J. Krstic16 , U. Kruchonak79 , H. Krüger24 , N. Krumnack78 , M.C. Kruse49 , J.A. Krzysiak84 , T. Kubota104 , O. Kuchinskaia166 , S. Kuday4b , J.T. Kuechler46 , S. Kuehn36 , A. Kugel61a , T. Kuhl46 , V. Kukhtin79 , R. Kukla101 , Y. Kulchitsky107,am , S. Kuleshov147c , Y.P. Kulinich173 , M. Kuna58 , T. Kunigo85 , A. Kupco141 , T. Kupfer47 , O. Kuprash52 , H. Kurashige82 , L.L. Kurchaninov168a , Y.A. Kurochkin107 , A. Kurova112 , M.G. Kurth15a,15d , E.S. Kuwertz36 , M. Kuze165 , A.K. Kvam148 , J. Kvita130 , T. Kwan103 , JHEP12(2019)060 A. La Rosa115 , L. La Rotonda41b,41a , F. La Ruffa41b,41a , C. Lacasta174 , F. Lacava72a,72b , D.P.J. Lack100 , H. Lacker19 , D. Lacour136 , E. Ladygin79 , R. Lafaye5 , B. Laforge136 , T. Lagouri33c , S. Lai53 , S. Lammers65 , W. Lampl7 , C. Lampoudis162 , E. Lançon29 , U. Landgraf52 , M.P.J. Landon92 , M.C. Lanfermann54 , V.S. Lang46 , J.C. Lange53 , R.J. Langenberg36 , A.J. Lankford171 , F. Lanni29 , K. Lantzsch24 , A. Lanza70a , A. Lapertosa55b,55a , S. Laplace136 , J.F. Laporte145 , T. Lari68a , F. Lasagni Manghi23b,23a , M. Lassnig36 , T.S. Lau63a , A. Laudrain132 , A. Laurier34 , M. Lavorgna69a,69b , M. Lazzaroni68a,68b , B. Le104 , E. Le Guirriec101 , M. LeBlanc7 , T. LeCompte6 , F. Ledroit-Guillon58 , C.A. Lee29 , G.R. Lee17 , L. Lee59 , S.C. Lee158 , S.J. Lee34 , B. Lefebvre168a , M. Lefebvre176 , F. Legger114 , C. Leggett18 , K. Lehmann152 , N. Lehmann182 , G. Lehmann Miotto36 , W.A. Leight46 , A. Leisos162,z , M.A.L. Leite80d , C.E. Leitgeb114 , R. Leitner143 , D. Lellouch180,∗ , K.J.C. Leney42 , T. Lenz24 , B. Lenzi36 , R. Leone7 , S. Leone71a , C. Leonidopoulos50 , A. Leopold136 , G. Lerner156 , C. Leroy109 , R. Les167 , C.G. Lester32 , M. Levchenko138 , J. Levêque5 , D. Levin105 , L.J. Levinson180 , D.J. Lewis21 , B. Li15b , B. Li105 , C-Q. Li60a , F. Li60c , H. Li60a , H. Li60b , J. Li60c , K. Li153 , L. Li60c , M. 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Salnikov153 , J. Salt174 , D. Salvatore41b,41a , F. Salvatore156 , A. Salvucci63a,63b,63c , A. Salzburger36 , J. Samarati36 , D. Sammel52 , D. Sampsonidis162 , D. Sampsonidou162 , J. Sánchez174 , A. Sanchez Pineda66a,66c , H. Sandaker134 , C.O. Sander46 , I.G. Sanderswood89 , M. Sandhoff182 , C. Sandoval22 , D.P.C. Sankey144 , M. Sannino55b,55a , Y. Sano117 , A. Sansoni51 , C. Santoni38 , H. Santos140a,140b , S.N. Santpur18 , A. Santra174 , A. Sapronov79 , J.G. Saraiva140a,140d , O. Sasaki81 , K. Sato169 , E. Sauvan5 , P. Savard167,ba , N. Savic115 , R. Sawada163 , C. Sawyer144 , L. Sawyer95,ao , JHEP12(2019)060 C. Sbarra23b , A. Sbrizzi23a , T. Scanlon94 , J. Schaarschmidt148 , P. Schacht115 , B.M. Schachtner114 , D. Schaefer37 , L. Schaefer137 , J. Schaeffer99 , S. Schaepe36 , U. Schäfer99 , A.C. Schaffer132 , D. Schaile114 , R.D. Schamberger155 , N. Scharmberg100 , V.A. Schegelsky138 , D. Scheirich143 , F. Schenck19 , M. Schernau171 , C. Schiavi55b,55a , S. Schier146 , L.K. 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Skubic128 , M. Slawinska84 , K. Sliwa170 , R. Slovak143 , V. Smakhtin180 , B.H. Smart144 , J. Smiesko28a , N. Smirnov112 , S.Yu. Smirnov112 , Y. Smirnov112 , L.N. Smirnova113,w , O. Smirnova96 , J.W. Smith53 , M. Smizanska89 , K. Smolek142 , A. Smykiewicz84 , A.A. Snesarev110 , H.L. Snoek120 , I.M. Snyder131 , S. Snyder29 , R. Sobie176,ag , A.M. Soffa171 , A. Soffer161 , A. Søgaard50 , F. Sohns53 , C.A. Solans Sanchez36 , E.Yu. Soldatov112 , U. Soldevila174 , A.A. Solodkov123 , A. Soloshenko79 , O.V. Solovyanov123 , V. Solovyev138 , P. Sommer149 , H. Son170 , W. Song144 , W.Y. Song168b , A. Sopczak142 , F. Sopkova28b , C.L. Sotiropoulou71a,71b , S. Sottocornola70a,70b , R. Soualah66a,66c,g , A.M. Soukharev122b,122a , D. South46 , S. Spagnolo67a,67b , M. Spalla115 , M. Spangenberg178 , F. Spanò93 , D. Sperlich52 , T.M. Spieker61a , R. Spighi23b , G. Spigo36 , M. Spina156 , D.P. Spiteri57 , M. Spousta143 , A. Stabile68a,68b , B.L. Stamas121 , R. Stamen61a , M. Stamenkovic120 , E. Stanecka84 , R.W. Stanek6 , B. Stanislaus135 , M.M. Stanitzki46 , M. Stankaityte135 , B. Stapf120 , E.A. Starchenko123 , G.H. Stark146 , J. Stark58 , S.H. Stark40 , P. Staroba141 , P. Starovoitov61a , – 41 – S. Stärz103 , R. Staszewski84 , G. Stavropoulos44 , M. Stegler46 , P. Steinberg29 , A.L. Steinhebel131 , B. Stelzer152 , H.J. Stelzer139 , O. Stelzer-Chilton168a , H. Stenzel56 , T.J. Stevenson156 , G.A. Stewart36 , M.C. Stockton36 , G. Stoicea27b , M. Stolarski140a , P. Stolte53 , S. Stonjek115 , A. Straessner48 , J. Strandberg154 , S. Strandberg45a,45b , M. Strauss128 , P. Strizenec28b , R. Ströhmer177 , D.M. Strom131 , R. Stroynowski42 , A. Strubig50 , S.A. Stucci29 , B. Stugu17 , J. Stupak128 , N.A. Styles46 , D. Su153 , S. Suchek61a , V.V. Sulin110 , M.J. Sullivan90 , D.M.S. Sultan54 , S. Sultansoy4c , T. Sumida85 , S. Sun105 , X. Sun3 , K. Suruliz156 , C.J.E. Suster157 , M.R. Sutton156 , S. Suzuki81 , M. Svatos141 , M. Swiatlowski37 , S.P. Swift2 , T. Swirski177 , A. Sydorenko99 , I. Sykora28a , M. Sykora143 , T. Sykora143 , D. Ta99 , K. Tackmann46,ab , J. Taenzer161 , A. Taffard171 , R. Tafirout168a , H. Takai29 , R. Takashima86 , K. Takeda82 , T. Takeshita150 , E.P. Takeva50 , Y. Takubo81 , M. Talby101 , A.A. Talyshev122b,122a , N.M. Tamir161 , JHEP12(2019)060 J. Tanaka163 , M. Tanaka165 , R. Tanaka132 , S. Tapia Araya173 , S. Tapprogge99 , A. Tarek Abouelfadl Mohamed136 , S. Tarem160 , G. Tarna27b,c , G.F. Tartarelli68a , P. Tas143 , M. Tasevsky141 , T. Tashiro85 , E. Tassi41b,41a , A. Tavares Delgado140a,140b , Y. Tayalati35e , A.J. Taylor50 , G.N. Taylor104 , W. Taylor168b , H. Teagle90 , A.S. Tee89 , R. Teixeira De Lima153 , P. Teixeira-Dias93 , H. Ten Kate36 , J.J. Teoh120 , S. Terada81 , K. Terashi163 , J. Terron98 , S. Terzo14 , M. Testa51 , R.J. Teuscher167,ag , S.J. Thais183 , T. Theveneaux-Pelzer46 , F. Thiele40 , D.W. Thomas93 , J.O. Thomas42 , J.P. Thomas21 , A.S. Thompson57 , P.D. Thompson21 , L.A. Thomsen183 , E. Thomson137 , E.J. Thorpe92 , Y. Tian39 , R.E. Ticse Torres53 , V.O. Tikhomirov110,as , Yu.A. Tikhonov122b,122a , S. Timoshenko112 , P. Tipton183 , S. Tisserant101 , K. Todome23b,23a , S. Todorova-Nova5 , S. Todt48 , J. Tojo87 , S. Tokár28a , K. Tokushuku81 , E. Tolley126 , K.G. Tomiwa33c , M. Tomoto117 , L. Tompkins153,r , B. Tong59 , P. Tornambe102 , E. Torrence131 , H. Torres48 , E. Torró Pastor148 , C. Tosciri135 , J. Toth101,ae , D.R. Tovey149 , A. Traeet17 , C.J. Treado124 , T. Trefzger177 , F. Tresoldi156 , A. Tricoli29 , I.M. Trigger168a , S. Trincaz-Duvoid136 , W. Trischuk167 , B. Trocmé58 , A. Trofymov145 , C. Troncon68a , M. Trovatelli176 , F. Trovato156 , L. Truong33b , M. Trzebinski84 , A. Trzupek84 , F. Tsai46 , J.C-L. Tseng135 , P.V. Tsiareshka107,am , A. Tsirigotis162 , N. Tsirintanis9 , V. Tsiskaridze155 , E.G. Tskhadadze159a , M. Tsopoulou162 , I.I. Tsukerman111 , V. Tsulaia18 , S. Tsuno81 , D. Tsybychev155 , Y. Tu63b , A. Tudorache27b , V. Tudorache27b , T.T. Tulbure27a , A.N. Tuna59 , S. Turchikhin79 , D. Turgeman180 , I. Turk Cakir4b,x , R.J. Turner21 , R.T. Turra68a , P.M. Tuts39 , S. Tzamarias162 , E. Tzovara99 , G. Ucchielli47 , K. Uchida163 , I. Ueda81 , M. Ughetto45a,45b , F. Ukegawa169 , G. Unal36 , A. Undrus29 , G. Unel171 , F.C. Ungaro104 , Y. Unno81 , K. Uno163 , J. Urban28b , P. Urquijo104 , G. Usai8 , J. Usui81 , Z. Uysal12d , L. Vacavant101 , V. Vacek142 , B. Vachon103 , K.O.H. Vadla134 , A. Vaidya94 , C. Valderanis114 , E. Valdes Santurio45a,45b , M. Valente54 , S. Valentinetti23b,23a , A. Valero174 , L. Valéry46 , R.A. Vallance21 , A. Vallier36 , J.A. Valls Ferrer174 , T.R. Van Daalen14 , P. Van Gemmeren6 , I. Van Vulpen120 , M. Vanadia73a,73b , W. Vandelli36 , A. Vaniachine166 , D. Vannicola72a,72b , R. Vari72a , E.W. Varnes7 , C. Varni55b,55a , T. Varol42 , D. Varouchas132 , K.E. Varvell157 , M.E. Vasile27b , G.A. Vasquez176 , J.G. Vasquez183 , F. Vazeille38 , D. Vazquez Furelos14 , T. Vazquez Schroeder36 , J. Veatch53 , V. Vecchio74a,74b , M.J. Veen120 , L.M. Veloce167 , F. Veloso140a,140c , S. Veneziano72a , A. Ventura67a,67b , N. Venturi36 , A. Verbytskyi115 , V. Vercesi70a , M. Verducci71a,71b , C.M. Vergel Infante78 , C. Vergis24 , W. Verkerke120 , A.T. Vermeulen120 , J.C. Vermeulen120 , M.C. Vetterli152,ba , N. Viaux Maira147c , M. Vicente Barreto Pinto54 , T. Vickey149 , O.E. Vickey Boeriu149 , G.H.A. Viehhauser135 , L. Vigani61b , M. Villa23b,23a , M. Villaplana Perez68a,68b , E. Vilucchi51 , M.G. Vincter34 , V.B. Vinogradov79 , A. Vishwakarma46 , C. Vittori23b,23a , I. Vivarelli156 , M. Vogel182 , P. Vokac142 , S.E. von Buddenbrock33c , E. Von Toerne24 , V. Vorobel143 , K. Vorobev112 , M. Vos174 , J.H. Vossebeld90 , M. Vozak100 , N. Vranjes16 , M. Vranjes Milosavljevic16 , V. Vrba142 , M. Vreeswijk120 , R. Vuillermet36 , I. Vukotic37 , P. Wagner24 , W. Wagner182 , J. Wagner-Kuhr114 , – 42 – S. Wahdan182 , H. Wahlberg88 , K. Wakamiya82 , V.M. Walbrecht115 , J. Walder89 , R. Walker114 , S.D. Walker93 , W. Walkowiak151 , V. Wallangen45a,45b , A.M. Wang59 , C. Wang60c , C. Wang60b , F. Wang181 , H. Wang18 , H. Wang3 , J. Wang157 , J. Wang61b , P. Wang42 , Q. Wang128 , R.-J. Wang99 , R. Wang60a , R. Wang6 , S.M. Wang158 , W.T. Wang60a , W. Wang15c,ah , W.X. Wang60a,ah , Y. Wang60a,ap , Z. Wang60c , C. Wanotayaroj46 , A. Warburton103 , C.P. Ward32 , D.R. Wardrope94 , N. Warrack57 , A. Washbrook50 , A.T. Watson21 , M.F. Watson21 , G. Watts148 , B.M. Waugh94 , A.F. Webb11 , S. Webb99 , C. Weber183 , M.S. Weber20 , S.A. Weber34 , S.M. Weber61a , A.R. Weidberg135 , J. Weingarten47 , M. Weirich99 , C. Weiser52 , P.S. Wells36 , T. Wenaus29 , T. Wengler36 , S. Wenig36 , N. Wermes24 , M.D. Werner78 , M. Wessels61a , T.D. Weston20 , K. Whalen131 , N.L. Whallon148 , A.M. Wharton89 , A.S. White105 , A. White8 , M.J. White1 , D. Whiteson171 , B.W. Whitmore89 , W. Wiedenmann181 , M. Wielers144 , JHEP12(2019)060 N. Wieseotte99 , C. Wiglesworth40 , L.A.M. Wiik-Fuchs52 , F. Wilk100 , H.G. Wilkens36 , L.J. Wilkins93 , H.H. Williams137 , S. Williams32 , C. Willis106 , S. Willocq102 , J.A. Wilson21 , I. Wingerter-Seez5 , E. Winkels156 , F. Winklmeier131 , O.J. Winston156 , B.T. Winter52 , M. Wittgen153 , M. Wobisch95 , A. Wolf99 , T.M.H. Wolf120 , R. Wolff101 , R.W. Wölker135 , J. Wollrath52 , M.W. Wolter84 , H. Wolters140a,140c , V.W.S. Wong175 , N.L. Woods146 , S.D. Worm21 , B.K. Wosiek84 , K.W. Woźniak84 , K. Wraight57 , S.L. Wu181 , X. Wu54 , Y. Wu60a , T.R. Wyatt100 , B.M. Wynne50 , S. Xella40 , Z. Xi105 , L. Xia178 , D. Xu15a , H. Xu60a,c , L. Xu29 , T. Xu145 , W. Xu105 , Z. Xu60b , Z. Xu153 , B. Yabsley157 , S. Yacoob33a , K. Yajima133 , D.P. Yallup94 , D. Yamaguchi165 , Y. Yamaguchi165 , A. Yamamoto81 , F. Yamane82 , M. Yamatani163 , T. Yamazaki163 , Y. Yamazaki82 , Z. Yan25 , H.J. Yang60c,60d , H.T. Yang18 , S. Yang77 , X. Yang60b,58 , Y. Yang163 , W-M. Yao18 , Y.C. Yap46 , Y. Yasu81 , E. Yatsenko60c,60d , J. Ye42 , S. Ye29 , I. Yeletskikh79 , M.R. Yexley89 , E. Yigitbasi25 , K. Yorita179 , K. Yoshihara137 , C.J.S. Young36 , C. Young153 , J. Yu78 , R. Yuan60b,i , X. Yue61a , S.P.Y. Yuen24 , B. Zabinski84 , G. Zacharis10 , E. Zaffaroni54 , J. Zahreddine136 , A.M. Zaitsev123,ar , T. Zakareishvili159b , N. Zakharchuk34 , S. Zambito59 , D. Zanzi36 , D.R. Zaripovas57 , S.V. Zeißner47 , C. Zeitnitz182 , G. Zemaityte135 , J.C. Zeng173 , O. Zenin123 , T. Ženiš28a , D. Zerwas132 , M. Zgubič135 , D.F. Zhang15b , F. Zhang181 , G. Zhang15b , H. Zhang15c , J. Zhang6 , L. Zhang15c , L. Zhang60a , M. Zhang173 , R. Zhang24 , X. Zhang60b , Y. Zhang15a,15d , Z. Zhang63a , Z. Zhang132 , P. Zhao49 , Y. Zhao60b , Z. Zhao60a , A. Zhemchugov79 , Z. Zheng105 , D. Zhong173 , B. Zhou105 , C. Zhou181 , M.S. Zhou15a,15d , M. Zhou155 , N. Zhou60c , Y. Zhou7 , C.G. Zhu60b , H.L. Zhu60a , H. Zhu15a , J. Zhu105 , Y. Zhu60a , X. Zhuang15a , K. Zhukov110 , V. Zhulanov122b,122a , D. Zieminska65 , N.I. Zimine79 , S. Zimmermann52 , Z. Zinonos115 , M. Ziolkowski151 , L. Živković16 , G. Zobernig181 , A. Zoccoli23b,23a , K. Zoch53 , T.G. Zorbas149 , R. Zou37 and L. Zwalinski36 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, – 43 – 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 JHEP12(2019)060 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 Facultad de Ciencias y Centro de Investigaciónes, Universidad Antonio Nariño, Bogota; Colombia 23 (a) INFN Bologna and Universita’ di Bologna, Dipartimento di Fisica;(b) INFN Sezione di Bologna; Italy 24 Physikalisches Institut, Universität Bonn, Bonn; Germany 25 Department of Physics, Boston University, Boston MA; United States of America 26 Department of Physics, Brandeis University, Waltham MA; United States of America 27 (a) Transilvania University of Brasov, Brasov;(b) Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest;(c) Department of Physics, Alexandru Ioan Cuza University of Iasi, Iasi;(d) National Institute for Research and Development of Isotopic and Molecular Technologies, Physics Department, Cluj-Napoca;(e) University Politehnica Bucharest, Bucharest;(f ) West University in Timisoara, Timisoara; Romania 28 (a) Faculty of Mathematics, Physics and Informatics, Comenius University, Bratislava;(b) Department of Subnuclear Physics, Institute of Experimental Physics of the Slovak Academy of Sciences, Kosice; Slovak Republic 29 Physics Department, Brookhaven National Laboratory, Upton NY; United States of America 30 Departamento de Fı́sica, Universidad de Buenos Aires, Buenos Aires; Argentina 31 California State University, CA; United States of America 32 Cavendish Laboratory, University of Cambridge, Cambridge; United Kingdom 33 (a) Department of Physics, University of Cape Town, Cape Town;(b) Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg;(c) School of Physics, University of the Witwatersrand, Johannesburg; South Africa 34 Department of Physics, Carleton University, Ottawa ON; Canada 35 (a) Faculté des Sciences Ain Chock, Réseau Universitaire de Physique des Hautes Energies — Université Hassan II, Casablanca;(b) Faculté des Sciences, Université Ibn-Tofail, Kénitra;(c) Faculté des Sciences Semlalia, Université Cadi Ayyad, LPHEA-Marrakech;(d) Faculté des Sciences, Université Mohamed Premier and LPTPM, Oujda;(e) Faculté des sciences, Université Mohammed V, Rabat; Morocco 36 CERN, Geneva; Switzerland 37 Enrico Fermi Institute, University of Chicago, Chicago IL; United States of America 38 LPC, Université Clermont Auvergne, CNRS/IN2P3, Clermont-Ferrand; France 39 Nevis Laboratory, Columbia University, Irvington NY; United States of America 40 Niels Bohr Institute, University of Copenhagen, Copenhagen; Denmark 41 (a) Dipartimento di Fisica, Università della Calabria, Rende;(b) INFN Gruppo Collegato di Cosenza, Laboratori Nazionali di Frascati; Italy 42 Physics Department, Southern Methodist University, Dallas TX; United States of America 43 Physics Department, University of Texas at Dallas, Richardson TX; United States of America – 44 – 44 National Centre for Scientific Research “Demokritos”, Agia Paraskevi; Greece 45 (a) Department of Physics, Stockholm University;(b) Oskar Klein Centre, Stockholm; Sweden 46 Deutsches Elektronen-Synchrotron DESY, Hamburg and Zeuthen; Germany 47 Lehrstuhl für Experimentelle Physik IV, Technische Universität Dortmund, Dortmund; Germany 48 Institut für Kern- und Teilchenphysik, Technische Universität Dresden, Dresden; Germany 49 Department of Physics, Duke University, Durham NC; United States of America 50 SUPA — School of Physics and Astronomy, University of Edinburgh, Edinburgh; United Kingdom 51 INFN e Laboratori Nazionali di Frascati, Frascati; Italy 52 Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg; Germany 53 II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen; Germany 54 Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève; Switzerland 55 (a) Dipartimento di Fisica, Università di Genova, Genova;(b) INFN Sezione di Genova; Italy JHEP12(2019)060 56 II. Physikalisches Institut, Justus-Liebig-Universität Giessen, Giessen; Germany 57 SUPA — School of Physics and Astronomy, University of Glasgow, Glasgow; United Kingdom 58 LPSC, Université Grenoble Alpes, CNRS/IN2P3, Grenoble INP, Grenoble; France 59 Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge MA; United States of America 60 (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 61 (a) Kirchhoff-Institut für Physik, Ruprecht-Karls-Universität Heidelberg, Heidelberg; (b) Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg; Germany 62 Faculty of Applied Information Science, Hiroshima Institute of Technology, Hiroshima; Japan 63 (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 64 Department of Physics, National Tsing Hua University, Hsinchu; Taiwan 65 Department of Physics, Indiana University, Bloomington IN; United States of America 66 (a) INFN Gruppo Collegato di Udine, Sezione di Trieste, Udine;(b) ICTP, Trieste;(c) Dipartimento Politecnico di Ingegneria e Architettura, Università di Udine, Udine; Italy 67 (a) INFN Sezione di Lecce;(b) Dipartimento di Matematica e Fisica, Università del Salento, Lecce; Italy 68 (a) INFN Sezione di Milano;(b) Dipartimento di Fisica, Università di Milano, Milano; Italy 69 (a) INFN Sezione di Napoli;(b) Dipartimento di Fisica, Università di Napoli, Napoli; Italy 70 (a) INFN Sezione di Pavia;(b) Dipartimento di Fisica, Università di Pavia, Pavia; Italy 71 (a) INFN Sezione di Pisa;(b) Dipartimento di Fisica E. Fermi, Università di Pisa, Pisa; Italy 72 (a) INFN Sezione di Roma;(b) Dipartimento di Fisica, Sapienza Università di Roma, Roma; Italy 73 (a) INFN Sezione di Roma Tor Vergata;(b) Dipartimento di Fisica, Università di Roma Tor Vergata, Roma; Italy 74 (a) INFN Sezione di Roma Tre;(b) Dipartimento di Matematica e Fisica, Università Roma Tre, Roma; Italy 75 (a) INFN-TIFPA;(b) Università degli Studi di Trento, Trento; Italy 76 Institut für Astro- und Teilchenphysik, Leopold-Franzens-Universität, Innsbruck; Austria 77 University of Iowa, Iowa City IA; United States of America 78 Department of Physics and Astronomy, Iowa State University, Ames IA; United States of America 79 Joint Institute for Nuclear Research, Dubna; Russia 80 (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 – 45 – Paulo, São Paulo; Brazil 81 KEK, High Energy Accelerator Research Organization, Tsukuba; Japan 82 Graduate School of Science, Kobe University, Kobe; Japan 83 (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 84 Institute of Nuclear Physics Polish Academy of Sciences, Krakow; Poland 85 Faculty of Science, Kyoto University, Kyoto; Japan 86 Kyoto University of Education, Kyoto; Japan 87 Research Center for Advanced Particle Physics and Department of Physics, Kyushu University, Fukuoka; Japan 88 Instituto de Fı́sica La Plata, Universidad Nacional de La Plata and CONICET, La Plata; Argentina 89 Physics Department, Lancaster University, Lancaster; United Kingdom JHEP12(2019)060 90 Oliver Lodge Laboratory, University of Liverpool, Liverpool; United Kingdom 91 Department of Experimental Particle Physics, Jožef Stefan Institute and Department of Physics, University of Ljubljana, Ljubljana; Slovenia 92 School of Physics and Astronomy, Queen Mary University of London, London; United Kingdom 93 Department of Physics, Royal Holloway University of London, Egham; United Kingdom 94 Department of Physics and Astronomy, University College London, London; United Kingdom 95 Louisiana Tech University, Ruston LA; United States of America 96 Fysiska institutionen, Lunds universitet, Lund; Sweden 97 Centre de Calcul de l’Institut National de Physique Nucléaire et de Physique des Particules (IN2P3), Villeurbanne; France 98 Departamento de Fı́sica Teorica C-15 and CIAFF, Universidad Autónoma de Madrid, Madrid; Spain 99 Institut für Physik, Universität Mainz, Mainz; Germany 100 School of Physics and Astronomy, University of Manchester, Manchester; United Kingdom 101 CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille; France 102 Department of Physics, University of Massachusetts, Amherst MA; United States of America 103 Department of Physics, McGill University, Montreal QC; Canada 104 School of Physics, University of Melbourne, Victoria; Australia 105 Department of Physics, University of Michigan, Ann Arbor MI; United States of America 106 Department of Physics and Astronomy, Michigan State University, East Lansing MI; United States of America 107 B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk; Belarus 108 Research Institute for Nuclear Problems of Byelorussian State University, Minsk; Belarus 109 Group of Particle Physics, University of Montreal, Montreal QC; Canada 110 P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow; Russia 111 Institute for Theoretical and Experimental Physics of the National Research Centre Kurchatov Institute, Moscow; Russia 112 National Research Nuclear University MEPhI, Moscow; Russia 113 D.V. Skobeltsyn Institute of Nuclear Physics, M.V. Lomonosov Moscow State University, Moscow; Russia 114 Fakultät für Physik, Ludwig-Maximilians-Universität München, München; Germany 115 Max-Planck-Institut für Physik (Werner-Heisenberg-Institut), München; Germany 116 Nagasaki Institute of Applied Science, Nagasaki; Japan 117 Graduate School of Science and Kobayashi-Maskawa Institute, Nagoya University, Nagoya; Japan 118 Department of Physics and Astronomy, University of New Mexico, Albuquerque NM; United States of America 119 Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen; Netherlands 120 Nikhef National Institute for Subatomic Physics and University of Amsterdam, Amsterdam; Netherlands – 46 – 121 Department of Physics, Northern Illinois University, DeKalb IL; United States of America 122 (a) Budker Institute of Nuclear Physics and NSU, SB RAS, Novosibirsk;(b) Novosibirsk State University Novosibirsk; Russia 123 Institute for High Energy Physics of the National Research Centre Kurchatov Institute, Protvino; Russia 124 Department of Physics, New York University, New York NY; United States of America 125 Ochanomizu University, Otsuka, Bunkyo-ku, Tokyo; Japan 126 Ohio State University, Columbus OH; United States of America 127 Faculty of Science, Okayama University, Okayama; Japan 128 Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman OK; United States of America 129 Department of Physics, Oklahoma State University, Stillwater OK; United States of America JHEP12(2019)060 130 Palacký University, RCPTM, Joint Laboratory of Optics, Olomouc; Czech Republic 131 Center for High Energy Physics, University of Oregon, Eugene OR; United States of America 132 LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay; France 133 Graduate School of Science, Osaka University, Osaka; Japan 134 Department of Physics, University of Oslo, Oslo; Norway 135 Department of Physics, Oxford University, Oxford; United Kingdom 136 LPNHE, Sorbonne Université, Université de Paris, CNRS/IN2P3, Paris; France 137 Department of Physics, University of Pennsylvania, Philadelphia PA; United States of America 138 Konstantinov Nuclear Physics Institute of National Research Centre “Kurchatov Institute”, PNPI, St. Petersburg; Russia 139 Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh PA; United States of America 140 (a) Laboratório de Instrumentação e Fı́sica Experimental de Partı́culas — LIP, Lisboa;(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 ) Universidad de Granada, Granada (Spain);(g) Dep Fı́sica and CEFITEC of Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica; (h) Instituto Superior Técnico, Universidade de Lisboa, Lisboa; Portugal 141 Institute of Physics of the Czech Academy of Sciences, Prague; Czech Republic 142 Czech Technical University in Prague, Prague; Czech Republic 143 Charles University, Faculty of Mathematics and Physics, Prague; Czech Republic 144 Particle Physics Department, Rutherford Appleton Laboratory, Didcot; United Kingdom 145 IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette; France 146 Santa Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz CA; United States of America 147 (a) Departamento de Fı́sica, Pontificia Universidad Católica de Chile, Santiago; (b) Universidad Andres Bello, Department of Physics, Santiago;(c) Departamento de Fı́sica, Universidad Técnica Federico Santa Marı́a, Valparaı́so; Chile 148 Department of Physics, University of Washington, Seattle WA; United States of America 149 Department of Physics and Astronomy, University of Sheffield, Sheffield; United Kingdom 150 Department of Physics, Shinshu University, Nagano; Japan 151 Department Physik, Universität Siegen, Siegen; Germany 152 Department of Physics, Simon Fraser University, Burnaby BC; Canada 153 SLAC National Accelerator Laboratory, Stanford CA; United States of America 154 Physics Department, Royal Institute of Technology, Stockholm; Sweden 155 Departments of Physics and Astronomy, Stony Brook University, Stony Brook NY; United States of America 156 Department of Physics and Astronomy, University of Sussex, Brighton; United Kingdom 157 School of Physics, University of Sydney, Sydney; Australia – 47 – 158 Institute of Physics, Academia Sinica, Taipei; Taiwan 159 (a) E. Andronikashvili Institute of Physics, Iv. Javakhishvili Tbilisi State University, Tbilisi; (b) High Energy Physics Institute, Tbilisi State University, Tbilisi; Georgia 160 Department of Physics, Technion, Israel Institute of Technology, Haifa; Israel 161 Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv University, Tel Aviv; Israel 162 Department of Physics, Aristotle University of Thessaloniki, Thessaloniki; Greece 163 International Center for Elementary Particle Physics and Department of Physics, University of Tokyo, Tokyo; Japan 164 Graduate School of Science and Technology, Tokyo Metropolitan University, Tokyo; Japan 165 Department of Physics, Tokyo Institute of Technology, Tokyo; Japan 166 Tomsk State University, Tomsk; Russia JHEP12(2019)060 167 Department of Physics, University of Toronto, Toronto ON; Canada 168 (a) TRIUMF, Vancouver BC;(b) Department of Physics and Astronomy, York University, Toronto ON; Canada 169 Division of Physics and Tomonaga Center for the History of the Universe, Faculty of Pure and Applied Sciences, University of Tsukuba, Tsukuba; Japan 170 Department of Physics and Astronomy, Tufts University, Medford MA; United States of America 171 Department of Physics and Astronomy, University of California Irvine, Irvine CA; United States of America 172 Department of Physics and Astronomy, University of Uppsala, Uppsala; Sweden 173 Department of Physics, University of Illinois, Urbana IL; United States of America 174 Instituto de Fı́sica Corpuscular (IFIC), Centro Mixto Universidad de Valencia — CSIC, Valencia; Spain 175 Department of Physics, University of British Columbia, Vancouver BC; Canada 176 Department of Physics and Astronomy, University of Victoria, Victoria BC; Canada 177 Fakultät für Physik und Astronomie, Julius-Maximilians-Universität Würzburg, Würzburg; Germany 178 Department of Physics, University of Warwick, Coventry; United Kingdom 179 Waseda University, Tokyo; Japan 180 Department of Particle Physics, Weizmann Institute of Science, Rehovot; Israel 181 Department of Physics, University of Wisconsin, Madison WI; United States of America 182 Fakultät für Mathematik und Naturwissenschaften, Fachgruppe Physik, Bergische Universität Wuppertal, Wuppertal; Germany 183 Department of Physics, Yale University, New Haven CT; United States of America 184 Yerevan Physics Institute, Yerevan; Armenia a Also at Borough of Manhattan Community College, City University of New York, New York NY; United States of America b Also at CERN, Geneva; Switzerland c Also at CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille; France d Also at Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève; Switzerland e Also at Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona; Spain f Also at Departamento de Fı́sica, Instituto Superior Técnico, Universidade de Lisboa, Lisboa; Portugal g Also at Department of Applied Physics and Astronomy, University of Sharjah, Sharjah; United Arab Emirates h Also at Department of Financial and Management Engineering, University of the Aegean, Chios; Greece i Also at Department of Physics and Astronomy, Michigan State University, East Lansing MI; United States of America – 48 – 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, Ben Gurion University of the Negev, Beer Sheva; Israel m Also at Department of Physics, California State University, East Bay; United States of America n Also at Department of Physics, California State University, Fresno; United States of America o Also at Department of Physics, California State University, Sacramento; United States of America p Also at Department of Physics, King’s College London, London; United Kingdom q Also at Department of Physics, St. Petersburg State Polytechnical University, St. Petersburg; Russia r Also at Department of Physics, Stanford University, Stanford CA; United States of America s Also at Department of Physics, University of Adelaide, Adelaide; Australia JHEP12(2019)060 t Also at Department of Physics, University of Fribourg, Fribourg; Switzerland u Also at Department of Physics, University of Michigan, Ann Arbor MI; United States of America v Also at Dipartimento di Matematica, Informatica e Fisica, Università di Udine, Udine; Italy w Also at Faculty of Physics, M.V. Lomonosov Moscow State University, Moscow; Russia x Also at Giresun University, Faculty of Engineering, Giresun; Turkey y Also at Graduate School of Science, Osaka University, Osaka; Japan z Also at Hellenic Open University, Patras; Greece aa Also at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona; Spain ab Also at Institut für Experimentalphysik, Universität Hamburg, Hamburg; Germany ac Also at Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen; Netherlands ad Also at Institute for Nuclear Research and Nuclear Energy (INRNE) of the Bulgarian Academy of Sciences, Sofia; Bulgaria ae Also at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest; Hungary af Also at Institute of High Energy Physics, Chinese Academy of Sciences, Beijing; China ag Also at Institute of Particle Physics (IPP), Vancouver; Canada ah Also at Institute of Physics, Academia Sinica, Taipei; Taiwan ai Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku; Azerbaijan aj Also at Institute of Theoretical Physics, Ilia State University, Tbilisi; Georgia ak Also at Instituto de Fisica Teorica, IFT-UAM/CSIC, Madrid; Spain al Also at Istanbul University, Dept. of Physics, Istanbul; Turkey am Also at Joint Institute for Nuclear Research, Dubna; Russia an Also at LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay; France ao Also at Louisiana Tech University, Ruston LA; United States of America ap Also at LPNHE, Sorbonne Université, Université de Paris, CNRS/IN2P3, Paris; France aq Also at Manhattan College, New York NY; United States of America ar Also at Moscow Institute of Physics and Technology State University, Dolgoprudny; Russia as Also at National Research Nuclear University MEPhI, Moscow; Russia at Also at Physics Department, An-Najah National University, Nablus; Palestine au Also at Physics Dept, University of South Africa, Pretoria; South Africa av Also at Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg; Germany aw Also at School of Physics, Sun Yat-sen University, Guangzhou; China ax Also at The City College of New York, New York NY; United States of America ay Also at The Collaborative Innovation Center of Quantum Matter (CICQM), Beijing; China az Also at Tomsk State University, Tomsk, and Moscow Institute of Physics and Technology State University, Dolgoprudny; Russia ba Also at TRIUMF, Vancouver BC; Canada bb Also at Universita di Napoli Parthenope, Napoli; Italy ∗ Deceased – 49 –