Search for squarks and gluinos in final states with one isolated lepton, jets, and missing transverse momentum at \sqrt{s}=13 TeV with the ATLAS detector
EEUROPEAN ORGANISATION FOR NUCLEAR RESEARCH (CERN)
Submitted to: EPJ C CERN-EP-2020-2286th January 2021
Search for squarks and gluinos in final states withone isolated lepton, jets, and missing transverse momentum at √ 𝒔 =
13 TeV with the ATLAS detector
The ATLAS Collaboration
The results of a search for gluino and squark pair production with the pairs decaying via thelightest charginos into a final state consisting of two 𝑊 bosons, the lightest neutralinos ( ˜ 𝜒 ),and quarks, are presented. The signal is characterised by the presence of a single chargedlepton ( 𝑒 ± or 𝜇 ± ) from a 𝑊 boson decay, jets, and missing transverse momentum. The analysisis performed using 139 fb − of proton–proton collision data taken at a centre-of-mass energy √ 𝑠 =
13 TeV delivered by the Large Hadron Collider and recorded by the ATLAS experiment.No statistically significant excess of events above the Standard Model expectation is found.Limits are set on the direct production of squarks and gluinos in simplified models. Masses ofgluino (squark) up to 2.2 TeV (1.4 TeV) are excluded at 95% confidence level for a light ˜ 𝜒 . © a r X i v : . [ h e p - e x ] J a n Introduction
The Standard Model (SM) has proven to be a very successful theory. The discovery of the Higgs bosonboson [1–4] by the ATLAS and CMS collaborations confirmed the predicted electroweak symmetrybreaking, but also highlighted the hierarchy problem [5–8]. Supersymmetry (SUSY) [9–14] is a theoreticalframework which assumes supersymmetric particles differing from their SM partners by a half unit of spin.By introducing a new fermionic (bosonic) supersymmetric partner for each boson (fermion) in the SM,SUSY provides a possible solution to the hierarchy problem. In SUSY models conserving R -parity [15],SUSY particles are produced in pairs. The lightest supersymmetric particle (LSP) has to be stable and ispossibly weakly interacting, constituting a viable dark-matter candidate [16, 17].The partner particles of the SM fermions (quarks and leptons) are the scalar squarks ( ˜ 𝑞 ) and sleptons ( ˜ ℓ ).In the boson sector, the supersymmetric partners of the gluons are the fermionic gluinos ( ˜ 𝑔 ). The fermionicsupersymmetric partners of the Higgs scalars (higgsinos) and of the electroweak gauge bosons (winos andbino) mix to form charged mass eigenstates (charginos) and neutral mass eigenstates (neutralinos). In theminimal supersymmetric extension of the Standard Model (MSSM) [18, 19], two scalar Higgs doubletsalong with their higgsino partners are necessary, resulting in two charginos ( ˜ 𝜒 ± , ) and four neutralinos( ˜ 𝜒 , , , ).Squarks and gluinos, in R -parity-conserving scenarios, can be produced in pairs through the stronginteraction. If strongly interacting gluinos or squarks are present at the TeV scale, they should be producedcopiously in the 13 TeV 𝑝 𝑝 collisions at the Large Hadron Collider (LHC). With the recorded integratedluminosity and the predicted cross-sections for squark and gluino production, the searches are expected tobe sensitive to sparticle masses of a few TeV.This paper targets two simplified SUSY models [20, 21] describing the gluino and squark productionprocesses and their decays. These models, introduced in Ref. [22], serve as benchmarks. In the models,referred to as the gluino and squark one-step models, gluinos or squarks are produced in pairs: gluinossubsequently decay via a virtual squark into a ˜ 𝜒 ± and two light quarks, while squarks decay into a ˜ 𝜒 ± and one light quark ( 𝑞 ∈ { 𝑢, 𝑑, 𝑠, 𝑐 } ). The ˜ 𝜒 ± then decay into a 𝑊 boson and a ˜ 𝜒 . The correspondingdiagrams are shown in Figure 1. It is further assumed that ˜ 𝜒 ± is wino-like and the ˜ 𝜒 is bino-like. Inboth models, the branching fractions for SUSY particles are assumed to be 100% for the aforementionedprocesses squark/gluino decay into ˜ 𝜒 ± and quarks, and ˜ 𝜒 ± → ˜ 𝜒 𝑊 . The SM particles are assumed todecay following their known branching fractions. All other sparticles, which do not explicitly appear in thedecay chains, are set to be kinematically inaccessible and decoupled.In this search, two different types of mass spectra are considered. In the first one, the ˜ 𝜒 ± mass is set to beexactly midway between the masses of the gluino (squark) and the ˜ 𝜒 , so that the relative mass splitting 𝑥 = ( 𝑚 ( ˜ 𝜒 ± ) − 𝑚 ( ˜ 𝜒 ))/( 𝑚 ( ˜ 𝑔 / ˜ 𝑞 ) − 𝑚 ( ˜ 𝜒 )) is equal to 1/2. In the second mass spectrum, the ˜ 𝜒 mass is setto be 60 GeV while the gluino (squark) mass and the relative mass splitting are free parameters.The experimental signature of interest consists of a single charged lepton (electron or muon) producedby the leptonic decay of one of the 𝑊 bosons, at least two jets, and large missing transverse momentum( 𝐸 missT , defined in Section 4) from the undetected neutrino and the two neutralinos. The sparticle massesdetermine the energy available in their decays, so the number of jets and their kinematic properties dependon the mass spectrum chosen. To provide sensitivity to a broad range of mass spectra in the gluino andsquark one-step models, four signal regions with differing jet multiplicity requirements from ≥ ≥ g ˜ g ˜ χ ± ˜ χ ± pp q ¯ q (cid:48) ˜ χ W ± ¯ q (cid:48) q ˜ χ W ± ˜ q ˜ q ˜ χ ± ˜ χ ± pp q (cid:48) ˜ χ W ± q (cid:48) ˜ χ W ± Figure 1: Diagrams for (a) gluino and (b) squark pair production with subsequent decays into quarks and a ˜ 𝜒 ± . The˜ 𝜒 ± decays into a ˜ 𝜒 and a W boson. This analysis targets final states in which one W decays leptonically and theother hadronically. originating from 𝑏 quarks ( 𝑏 -tag and 𝑏 -veto signal regions, respectively) to be sensitive to a wider class ofdecay processes, e.g. gluino decays producing top quarks.The results presented in this paper are based on the ATLAS data collected in proton–proton collisionsat the LHC during 2015–2018 at a centre-of-mass energy of 13 TeV, corresponding to an integratedluminosity of 139 fb − . This analysis supersedes the previous ATLAS search with an integrated luminosityof 36.1 fb − [23]. Similar searches for gluinos and squarks with decays via intermediate supersymmetricparticles were performed by the CMS Collaboration [24, 25]. The ATLAS detector [26–28] is a multipurpose particle detector with nearly 4 𝜋 coverage in solid angle. It consists of an inner tracking detector surrounded by a thin superconducting solenoid providing a2 T axial magnetic field, electromagnetic and hadron calorimeters, and a muon spectrometer. Theinner tracking detector covers the pseudorapidity range | 𝜂 | < .
5. It consists of silicon pixel, siliconmicrostrip, and transition radiation tracking detectors. Lead/liquid-argon (LAr) sampling calorimetersprovide electromagnetic (EM) energy measurements with high granularity. A steel/scintillator-tile hadroncalorimeter covers the central pseudorapidity range ( | 𝜂 | < . | 𝜂 | = .
9. The muonspectrometer surrounds the calorimeters and is based on three large air-core toroidal superconductingmagnets with eight coils each. The field integral of the toroids ranges between 2.0 and 6.0 Tm acrossmost of the detector. The muon spectrometer includes a system of precision tracking chambers and fastdetectors for triggering. A two-level trigger system [29] is used to select events. The first-level trigger isimplemented in hardware and uses a subset of the detector information to keep the accepted rate below ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point in the centre of the detector. Thepositive 𝑥 -axis is defined by the direction from the interaction point to the centre of the LHC ring, with the positive 𝑦 -axispointing upwards, while the beam direction defines the 𝑧 -axis. Cylindrical coordinates ( 𝑟, 𝜙 ) are used in the transverse plane, 𝜙 being the azimuthal angle around the 𝑧 -axis. The pseudorapidity 𝜂 is defined in terms of the polar angle 𝜃 by 𝜂 = − ln tan ( 𝜃 / ) .Rapidity is defined as 𝑦 = 0 . [( 𝐸 + 𝑝 𝑧 )/( 𝐸 − 𝑝 𝑧 )] where 𝐸 denotes the energy and 𝑝 𝑧 is the component of the momentumalong the beam direction. The angular distance Δ 𝑅 is defined as √︁ ( Δ 𝑦 ) + ( Δ 𝜙 ) .
300 kHz. This is followed by a software-based trigger that reduces the accepted event rate to 1 kHz onaverage.
The search is performed using 139 fb − of LHC 𝑝 𝑝 collision data collected between 2015 and 2018 bythe ATLAS detector, with a centre-of-mass energy of 13 TeV and a 25 ns proton bunch crossing interval.The average number of interactions per bunch crossing (pile-up) evolved over the data-taking period from (cid:104) 𝜇 (cid:105) =
13 in 2015, to (cid:104) 𝜇 (cid:105) =
25 in 2016, (cid:104) 𝜇 (cid:105) =
38 in 2017, and (cid:104) 𝜇 (cid:105) =
36 in 2018. The uncertainty in thecombined 2015–2018 integrated luminosity is 1.7% [30], obtained using the LUCID-2 detector [31] for theprimary luminosity measurements.The SM background modelling, signal selection efficiencies, and signal event yield are evaluated usingMonte Carlo (MC) simulated event samples. All the samples are produced by a fast simulation [32]procedure that combines a parameterisation of the calorimeter response with a Geant4 [33] simulation ofthe other detector systems implemented in the ATLAS simulation infrastructure [34].To model the pile-up observed in data, inelastic 𝑝 𝑝 events were generated with Pythia 8.186 [35] usingthe NNPDF2.3LO set of parton distribution functions (PDF) [36] and a set of tuned parameters calledthe A3 tune [37]. These events were overlaid on all simulated hard-scatter events to model the additionalproton–proton interactions in the same and nearby bunch crossings. The pile-up overlay was reweighted tomatch the observed distribution in data. The simulated events are reconstructed with the same algorithmsas used for data.Signal gluino (squark) pair production samples were produced with MadGraph5_aMC@NLO v2.6.2 [38]at next-to-leading order for the hard-scattering matrix element and Pythia 8.212 (Pythia 8.230) forunderlying event, parton shower and hadronization. Signal cross-sections are calculated to approximatenext-to-next-to-leading order in the strong coupling constant, adding the resummation of soft gluon emissionat next-to-next-to-leading-logarithm accuracy (approximate NNLO+NNLL) [39–46]. The nominal cross-section and its uncertainty are derived using the PDF4LHC15_mc PDF set, following the recommendationsof Ref. [47]. A typical cross-section for gluino production with 𝑚 ˜ 𝑔 = 𝑚 ˜ 𝜒 =
200 GeVis 1 . ± .
20 fb, while for squarks with 𝑚 ˜ 𝑞 = 𝑚 ˜ 𝜒 =
200 GeV a typical cross-section is6 . ± . 𝑢 L , ˜ 𝑑 L , ˜ 𝑠 L , and ˜ 𝑐 L ) areassumed to be mass-degenerate. A ‘single squark flavour’ limit is also given assuming that only one suchleft-handed first and second generation quarks is kinematically accessible.All relevant SM backgrounds are considered: 𝑡 ¯ 𝑡 pair production; single-top production ( 𝑠 -channel, 𝑡 -channel,and associated 𝑊𝑡 production); 𝑊 / 𝑍 +jets production; 𝑡 ¯ 𝑡 production with an electroweak boson ( 𝑡 ¯ 𝑡 + 𝑉 ); anddiboson ( 𝑊𝑊 , 𝑊 𝑍 , 𝑍 𝑍 ) production. Different MC event generators were used to produce the backgroundsamples, depending on their production process. The MC-produced events are then normalised to datausing the corresponding theoretical cross-sections. The event generators, the routines for parton showeringand hadronisation, and the parameter tunes and parton distribution functions for all background processesproduced are summarised in Table 1.The 𝑊 +jets events were generated using Sherpa: the generation process includes up to two partons at NLOand four partons at LO using Comix [48] and OpenLoops [49, 50]. The matrix element was merged withthe Sherpa parton shower [51] according to the ME+PS@NLO prescription [52–55] using the set of tuned4 able 1: Overview of MC generators used for different simulated event samples for background. Process Generator Parton shower and Tune PDF Cross-sectionhadronisation 𝑡 ¯ 𝑡 Powheg-Box v2 [58–61] Pythia 8.230 [62] A14 [63] NNPDF2.3LO [36] NNLO+NNLL [64]Single top Powheg-Box v2 [65–67] Pythia 8.230 A14 NNPDF2.3LO NLO+NNLL [68] 𝑊 / 𝑍 +jets Sherpa 2.2.1 [69] Sherpa 2.2.1 Sherpa default NNPDF3.0NNLO NNLO [70]Diboson Sherpa 2.2.1 & 2.2.2 Sherpa 2.2.1 & 2.2.2 Sherpa default NNPDF3.0NNLO NLO 𝑡 ¯ 𝑡 + 𝑉 MG5_aMC@NLO v2.3.3 Pythia 8.210 A14 NNPDF2.3LO NLO [71] parameters developed by the Sherpa authors. To simulate the properties of the bottom- and charm-hadrondecays, the EvtGen v1.2.0 [56] program was used for all samples showered with Pythia.Systematic uncertainties, for both signal and background samples, derived from the MC generatorconfiguration are evaluated using samples produced without detector simulation. The uncertainties accountfor variations of the renormalisation and factorisation scales, the CKKW-L [57] matching scale, as well asdifferent PDF sets and fragmentation/hadronisation models. Details of the MC modelling uncertainties arediscussed in Section 7.
Each event is required to have at least one reconstructed interaction vertex with a minimum of two associatedtracks, each having 𝑝 T >
500 MeV. In events with multiple vertices, the one with the highest sum ofsquared transverse momenta of associated tracks is chosen as the primary vertex (PV) [72]. Baselinequality criteria are applied to reject events with non-collision backgrounds or detector noise [73].Two levels of object definition for leptons and jets are used: ‘baseline’ and ‘signal’. Loose qualityrequirements define baseline objects, which are used in the calculation of missing transverse momentumand in the overlap removal procedure described below. Signal objects, obtained by applying more selectiveidentification criteria to objects passing the baseline requirements, are used as input for the actual searchregion definitions. Isolation criteria applied to a set of track-based and calorimeter-based variables, areused to discriminate between signal leptons and semileptonic heavy-flavour decays, photon conversions aswell as jets misidentified as leptons.Energy deposits in the electromagnetic (EM) calorimeter that are matched to charged-particle tracks inthe inner detector (ID) [74] provide electron candidates. The 𝑝 T of electron is calculated based on theenergy deposited in the EM calorimeter. Baseline electrons must have 𝑝 T > | 𝜂 | < .
47 andmust satisfy the
Loose working point provided by a likelihood-based algorithm, described in Ref. [74]. Thelongitudinal impact parameter 𝑧 relative to the PV is required to satisfy | 𝑧 sin 𝜃 | < . Tight likelihood operating point and the requirement | 𝑑 / 𝜎 ( 𝑑 )| < Loose and
HighPtCaloOnly isolation working points, described in Ref. [74], are applied to signalelectrons having 𝑝 T <
200 GeV and 𝑝 T >
200 GeV, respectively. The longitudinal impact parameter 𝑧 corresponds to the 𝑧 -coordinate distance between the point along the track at which thetransverse impact parameter is defined and the primary vertex. The transverse impact parameter 𝑑 is defined as the distance ofclosest approach in the transverse plane between a track and the beam-line. The uncertainty in 𝑑 is denoted 𝜎 ( 𝑑 ) . 𝑝 T <
200 GeV are refined using the
Loose isolation working point, while those withlarger 𝑝 T are required to pass the HighPtCaloOnly isolation working point, as described in Ref. [74].Muon candidates are reconstructed from matching tracks in the ID and muon spectrometer, refined througha global fit using the hits from both subdetectors [75]. Baseline muons are required to satisfy 𝑝 T > | 𝜂 | < .
7. They are identified using the
Medium identification criteria [75]. As with the electrons,baseline muons are required to satisfy | 𝑧 sin 𝜃 | < . | 𝜂 | < . | 𝑑 / 𝜎 ( 𝑑 )| <
3, andthe
FixedCutLoose isolation working point requirements.Jet candidates are reconstructed from three-dimensional topological energy clusters in the calorimetersusing the anti- 𝑘 𝑡 algorithm [76] with a radius parameter 𝑅 = . | 𝜂 | < . 𝑝 T >
20 GeV. To suppress pile-up interactions, those jets having | 𝜂 | < . 𝑝 T <
120 GeV arerequired to pass the
Medium working point of the jet vertex tagger (JVT), a multivariate algorithm thatidentifies jets originating from the PV using track information [78, 79]. Signal jets must also have | 𝜂 | < . 𝑝 T >
30 GeV.Jets with 𝑝 T >
20 GeV in the region | 𝜂 | < . 𝑏 -hadrons can be ‘ 𝑏 -tagged’ with high efficiencyby the MV2c10 [80], which is a boosted decision tree with improved light-flavour jet and 𝑐 -jet rejection. The 𝑏 -tagging working point provides an efficiency of 77% for jets containing 𝑏 -hadrons in simulated 𝑡 ¯ 𝑡 events,with rejection factors of 110 and 4.9 for light-flavour jets and jets containing 𝑐 -hadrons, respectively [81].Signal 𝑏 -jets should also have 𝑝 T >
30 GeV.An overlap removal procedure is applied to the baseline objects defined above to resolve reconstructionambiguities between electrons, muons and jets. First, any electron sharing the same ID track with a muonis rejected. If two electrons share the same ID track, the one with lower 𝑝 T is discarded. Next, jets arerejected if they lie within Δ 𝑅 = . 𝑝 T -dependent size Δ 𝑅 = min ( . , . +
10 GeV / 𝑝 T ) around a jet. Subsequently, jets are rejected if theyare within Δ 𝑅 = . 𝒑 missT , with magnitude, 𝐸 missT , is calculated as the negative vectorial sumof the transverse momenta of all reconstructed baseline objects (electrons, muons, jets and photons [83])and a soft term. The soft term includes all selected tracks associated with the PV but not matched to anyreconstructed baseline object. To suppress contributions from pile-up and improve the 𝐸 missT resolution,tracks not associated with the PV are excluded from the 𝐸 missT calculation [84, 85].The efficiency differences in the trigger, lepton identification and reconstruction between data andsimulated events are closely evaluated in independent measurements, and are accounted for by applying thecorresponding corrections to the simulation in this analysis. To retain acceptance for soft leptons, events satisfying the 𝐸 missT trigger selection were recorded [86] andused in the search. The trigger efficiency is higher than 98% for offline 𝐸 missT values above 250 GeV.To target the signal-like events, selected events are required to have exactly one signal lepton, either anelectron or a muon. Events with additional baseline leptons are rejected to suppress dilepton 𝑡 ¯ 𝑡 , single-top6 𝑊𝑡 -channel), 𝑍 +jets and diboson backgrounds. The following observables are used to further reducebackground contributions and increase the sensitivity for signal: • The transverse mass, 𝑚 T , is defined from the lepton transverse momentum 𝒑 ℓ T and 𝒑 missT as 𝑚 T = √︃ 𝑝 ℓ T 𝐸 missT (cid:0) − cos [ Δ 𝜙 ( 𝒑 ℓ T , 𝒑 missT )] (cid:1) , where Δ 𝜙 ( 𝒑 ℓ T , 𝒑 missT ) is the azimuthal angle between 𝒑 ℓ T and 𝒑 missT . It has an upper endpoint at the 𝑊 boson mass for 𝑊 +jets events and for semileptonic 𝑡 ¯ 𝑡 events. The 𝑚 T distribution for signal eventsextends significantly beyond that endpoint. • The effective mass, 𝑚 eff , is the scalar sum of the 𝑝 T of the signal lepton and all signal jets and 𝐸 missT : 𝑚 eff = 𝑝 ℓ T + 𝑁 jet ∑︁ 𝑗 = 𝑝 T , 𝑗 + 𝐸 missT . The effective mass provides good discrimination against background events, especially for the signalscenarios with energetic jets. It can also help to distinguish between different signal channels. Forexample gluino production shows higher jet multiplicity than squark production. High-mass gluinosand squarks are expected to produce harder jets than low-mass ones. Thus, the optimal 𝑚 eff valuedepends on the different signal scenarios. To achieve a wide-range sensitivity to various SUSYmodels with a limited number of signal regions, multiple intervals in 𝑚 eff are used in the finalmodel-dependent signal regions. • The aplanarity is a variable designed to provide more global information about the full momentumtensor of the event. It is constructed from the lepton and the jets, and is defined as ( / ) × 𝜆 , where 𝜆 is the smallest eigenvalue of the sphericity tensor [87]. Typical measured aplanarity values lie inthe range 0–0.3, with values near zero indicating highly planar background-like events. Stronglyproduced SUSY signals tend to have high aplanarity values, since they are more spherical thanbackground events due to the multiple objects emitted in the gluino/squark decay chains.Four mutually exclusive signal regions (SRs) are designed to enhance the signal sensitivity. The selectioncriteria for the four SRs are summarised in Table 2. Each SR is optimised for specific SUSY scenarios,as discussed below. They are labelled by the minimum required number of jets and, where relevant, thecharacteristics of the targeted supersymmetric mass spectrum: ,
4J high-x ,
4J low-x , and . Whensetting model-dependent exclusion limits (‘excl’), each SR is divided in 𝑚 eff intervals and in 𝑏 -veto/ 𝑏 -tagcategories, and a simultaneous fit is performed across all bins of the four SRs. This choice enhancesthe sensitivity to a range of new-physics scenarios with or without 𝑏 -quarks in the final states, and withdifferent mass splittings. For model-independent limits and null-hypothesis tests (‘disc’ for discovery),the event yield in each SR is used to search for an excess over the SM background using an optimisedminimum 𝑚 eff value. The discovery SRs require the 𝑏 -veto and are separately optimised for gluino andsquark cases. The systematic uncertainties, fits, and results discussed in the following sections are basedon the exclusion SRs, while the model-independent results are based on the discovery SRs.The SR targets compressed scenarios where differences between 𝑚 ˜ 𝑔 / ˜ 𝑞 , 𝑚 ˜ 𝜒 ± , and 𝑚 ˜ 𝜒 are small and thedecay products tend to have low 𝑝 T . Thus, events are required to have one low- 𝑝 T lepton and at least twojets. The lower 𝑝 ℓ T bound is 7 ( ) GeV for the electron (muon), and the upper 𝑝 ℓ T bound increases withthe jet multiplicity up to 25 GeV. The upper 𝑝 ℓ T requirement ensures the orthogonality between the
7R and other signal regions. The jet multiplicity dependence maintains the balance between backgroundrejection and signal acceptance: the leptons are more energetic for signals with increasing mass splittings.Stringent requirements are placed on 𝐸 missT and on 𝐸 missT / 𝑚 eff to enhance the signal sensitivity by selectingsignal events with boosted final-state neutralinos recoiling against energetic initial-state radiation (ISR) jets.Compared to other SRs, a less stringent lower bound on 𝑚 eff is preferred.The
4J high-x
SR provides sensitivity to the models with a fixed 𝑚 ˜ 𝜒 of 60 GeV and a high 𝑥 value, i.e.when 𝑚 ˜ 𝜒 ± and 𝑚 ˜ 𝑔 / ˜ 𝑞 are relatively close. Events with four or five jets are selected for this scenario. Themass-splitting between 𝑚 ˜ 𝜒 ± and 𝑚 ˜ 𝜒 is large enough to produce a boosted 𝑊 boson that decays into ahigh- 𝑝 T lepton and a neutrino. Large 𝑚 T is thus the most distinguishing characteristic of this SR. Relativelysoft jets are expected to be emitted from the gluino or squark decays. The SM background is furthersuppressed by tight requirements on 𝐸 missT , aplanarity, and 𝐸 missT / 𝑚 eff . Compared to the SR, a tighter 𝑚 eff selection is applied due to higher jet activity.The
4J low-x
SR is optimised for the models where 𝑚 ˜ 𝜒 is fixed to 60 GeV and 𝑥 ≈
0, i.e. 𝑚 ˜ 𝜒 ± is closeto 𝑚 ˜ 𝜒 . The jet multiplicity requirement is the same as in the
4J high-x
SR. In contrast to the high- 𝑥 scenarios, the small mass-splitting between 𝑚 ˜ 𝜒 ± and 𝑚 ˜ 𝜒 tends to produce an off-shell 𝑊 boson, leading tosmall 𝑚 T . To keep this SR orthogonal to the
4J high-x
SR, an upper bound is applied to 𝑚 T . Other thanthat, the requirements on 𝑚 eff , 𝐸 missT , aplanarity, and 𝐸 missT / 𝑚 eff are identical to the ones used in the SR.The SR targets signal scenarios with high gluino/squark mass, and is optimised for models with 𝑥 ≈ / 𝑝 T lepton and at least six jets are selected. Large aplanarity is required, reflecting theheavy gluino/squark produced in the targeted signature. Tight requirements on 𝑚 T and 𝐸 missT are imposedto reduce the SM background. To achieve high sensitivity for a wide range of 𝑚 ˜ 𝑔 / ˜ 𝑞 , four exclusive binsare defined in 𝑚 eff and used in the fit. The lowest mass bin starts from 700 GeV, and the highest from2800 GeV. Table 2: Overview of the selection criteria for the signal regions used for gluino/squark one-step models. Therequirements that only apply to the exclusion (discovery) SRs are marked with ‘excl’ (‘disc’). The 𝑚 eff bins are ofeven width and the ‘+’ indicates that overflow events are included in the last bin. SR 2J 4J high-x 4J low-x 6J 𝑁 ℓ = 𝑝 ℓ T [GeV] > ( ) for 𝑒 ( 𝜇 ) and > > > < min ( · 𝑁 jet , ) 𝑁 jet ≥ ≥ 𝐸 missT [GeV] > > > > 𝑚 T [GeV] > >
520 150–520 > > . > . > . 𝐸 missT / 𝑚 eff > . > . > . 𝑁 𝑏 -jet (excl) = 𝑏 -veto SR, ≥ 𝑏 -tag SR 𝑚 eff [GeV] (excl) 3 bins ∈ [ , +] ∈ [ , +] ∈ [ , +] ∈ [ , +] 𝑁 𝑏 -jet (disc) = 𝑚 eff [GeV] (disc) > ( ) > > > ( ) for gluino (squark) for gluino (squark) Background estimation
Accurate prediction of the SM background event yields in SRs is important in any search like the onepresented in this paper. Different approaches for calculating the SM event yields in the SRs are useddepending on the background process of interest. The yields of 𝑡 ¯ 𝑡 , single-top, and 𝑊 +jets processes areestimated from data using a set of dedicated control regions (CRs), while contributions from 𝑍 +jets, 𝑡 ¯ 𝑡 produced in association with a 𝑊 or 𝑍 boson, and dibosons ( 𝑊𝑊 , 𝑊 𝑍 , 𝑍 𝑍 ) are evaluated from MCsimulation. The details are described below.Three sets of CRs, , , , are defined for estimating the backgrounds in ,
4J high-x ,
4J low-x and signal regions. The CRs satisfy the criteria of high purity for the targeted background process andlow signal contamination from the model of interest. The purity varies from 57% to 88% for the topbackgrounds ( 𝑡 ¯ 𝑡 and single top) in top CRs and from 73% to 92% for 𝑊 +jets in 𝑊 +jets CRs. Each of theCRs is defined with kinematic boundaries close to the corresponding SR in order to reduce the theoreticaland detector uncertainties from the extrapolation. The contributions of the top and 𝑊 +jets backgroundsin the SRs are evaluated with a fit based on the profile likelihood method. The normalised backgroundpredictions are obtained from a simultaneous fit across all control regions, as described in Section 8. Thecontrol regions for top and 𝑊 +jets are presented in Table 3. Events in the top control region require atleast one 𝑏 -tagged signal jet in the event, while 𝑊 +jets control regions are defined by vetoing all eventscontaining any 𝑏 -tagged signal jets. The CRs are crafted in the same way as signal regions, thus each CR isdefined as a function of 𝑚 eff , with the same binning as the corresponding SR. This permits extrapolationfrom each 𝑏 -tag/ 𝑏 -veto and 𝑚 eff bin in CRs to the corresponding bin in the SRs. The extrapolation fromCRs to SRs is performed via the 𝑚 T variable, which is found to be well modelled in simulation as shown inFigure 2.In order to validate the background fit results, cross-checks of the background estimates are performed invalidation regions (VRs) situated between the SRs and the CRs in 𝑚 T , while remaining orthogonal to bothregions. The VRs are also defined as functions of 𝑚 eff in the same way as the corresponding CRs and SRs,to ensure an 𝑚 eff -dependent validation. The highest 𝑚 eff bin in the VR is not used because its signalcontamination would be too large. Similar to the control regions, events in the top VRs require a 𝑏 -tag,while events in the 𝑊 +jets VRs require a 𝑏 -veto. The VRs are not used to constrain the fit; they serve onlyto verify that the normalised background predictions agree with the observed data. The VR definitions andtheir graphical representation are shown in Table 4 and Figure 3.The background contributions from 𝑍 +jets, 𝑡 ¯ 𝑡 + 𝑉 and diboson events are evaluated from simulation. Thesimulated event samples are normalised to the relevant theoretical cross-sections. No dedicated controlregions for the diboson background are used, as the modelling of this background by simulation is found tobe sufficiently good when compared with the data in the validation regions. The data and MC predictionsyield, obtained from the overall background estimate, differ in all validation regions by less than twostandard deviations. The background originating from misidentified leptons, real leptons coming from jetsproduced by heavy-flavour quarks or photons converted to electrons is found to be negligible within thestatistical error of the data due to the stringent requirements on 𝐸 missT .9 bs_x_SR2JNm1BVEM_mt -
10 110 E v en t s / G e V -1 = 13 TeV, 139 fbs ATLAS
SR 2J N-1 b-veto
DataTotal SMttSingle top W+jetsDibosonZ+jets+Vtt )=(900,860,820) GeV c~ , – c~ ,g~m( )=(600,575,550) GeV c~ , – c~ ,q~m(
50 110 170 230 290 350 410 [GeV] T m D a t a / S M obs_x_SR2JNm1BTEM_mt -
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SR 2J N-1 b-tag
DataTotal SMttSingle top W+jetsDibosonZ+jets+Vtt )=(900,860,820) GeV c~ , – c~ ,g~m( )=(600,575,550) GeV c~ , – c~ ,q~m(
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SR 4J N-1 b-veto
DataTotal SMttSingle top W+jetsDibosonZ+jets+Vtt )=(1600,660,60) GeV c~ , – c~ ,g~m( )=(1400,1260,60) GeV c~ , – c~ ,g~m(
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SR 4J N-1 b-tag
DataTotal SMttSingle top W+jetsDibosonZ+jets+Vtt )=(1600,660,60) GeV c~ , – c~ ,g~m( )=(1400,1260,60) GeV c~ , – c~ ,g~m(
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SR 6J N-1 b-veto
DataTotal SMttSingle top W+jetsDibosonZ+jets+Vtt )=(1800,1100,400) GeV c~ , – c~ ,g~m( )=(1000,512,24) GeV c~ , – c~ ,q~m(
50 290 530 770 1010 [GeV] T m D a t a / S M obs_x_SR6JNm1BTEM_mt -
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SR 6J N-1 b-tag
DataTotal SMttSingle top W+jetsDibosonZ+jets+Vtt )=(1800,1100,400) GeV c~ , – c~ ,g~m( )=(1000,512,24) GeV c~ , – c~ ,q~m(
50 290 530 770 1010 [GeV] T m D a t a / S M Figure 2: The 𝑚 T distributions in the signal regions after all of the selection requirements other than the 𝑚 T cut(noted as ‘N-1’ in the figures). Due to the removal of the 𝑚 T requirement, these plots effectively show the CRs, VRsand SRs for each jet multiplicity. The uncertainty bands include all statistical and systematic uncertainties. Overflowevents are included in the last bin. The dashed lines represent benchmark signal points for gluino and squark pairproduction. able 3: Overview of the control region selection criteria. The top and 𝑊 +jets control regions are defined by the 𝑏 -tag and 𝑏 -veto requirements, respectively. The 𝑚 eff bins are of even width and the ‘+’ indicates that overflowevents are included in the last bin. CR 2J 4J 6J 𝑁 ℓ = 𝑝 ℓ T [GeV] > ( ) for 𝑒 ( 𝜇 ) and > > < min ( · 𝑁 jet , ) 𝑁 jet ≥ ≥ 𝐸 missT [GeV] > > > 𝑚 T [GeV] 50–80 50–90 50–100Aplanarity - > . > . 𝐸 missT / 𝑚 eff > . > . 𝑚 eff [GeV] 3 bins ∈ [ , +] ∈ [ , +] ∈ [ , +] 𝑁 𝑏 -jet ≥ = 𝑊 +jets CRTable 4: Overview of the validation region selection criteria. The top and 𝑊 +jets validation regions are defined bythe 𝑏 -tag and 𝑏 -veto requirements, respectively. The 𝑚 eff bins are of even width and the ‘+’ indicates that overflowevents are included in the last bin. VR 2J 4J 6J 𝑁 ℓ = 𝑝 ℓ T [GeV] > ( ) for 𝑒 ( 𝜇 ) and > > < min ( · 𝑁 jet , ) 𝑁 jet ≥ ≥ 𝐸 missT [GeV] > > > 𝑚 T [GeV] 80–100 90–150 100–225Aplanarity - > . > . 𝐸 missT / 𝑚 eff > . > . 𝑚 eff [GeV] 3 bins ∈ [ , +] ∈ [ , +] ∈ [ , +] 𝑁 𝑏 -jet ≥ = 𝑊 +jets VR As a representative example, the 𝑚 eff distributions in the J top and 𝑊 +jets control regions are shown inFigure 4 before and after a fit which constrains only the control regions. The fit strategy is discussed inSection 8. A trend is observed, as it was in previous similar searches [23], whereby the MC overestimatesthe expected yields at large values of 𝑚 eff . This is accounted for by applying different normalisationparameter values for each 𝑚 eff bin in the corresponding fit, which effectively corrects the mismodelling. Inthe post-fit distributions, the data and the background expectation agree well within the uncertainties.11
00 1300 1900 2500 [GeV] eff m5060708090100110120 [ G e V ] T m SR2JCR2JVR2J
ATLAS missT + jets + E m eff m100200300400500600700 [ G e V ] T m SR4Jhigh-xSR4Jlow-xCR4JVR4J
ATLAS missT + jets + E m
700 1400 2100 2800 3500 [GeV] eff m50100150200250300350 [ G e V ] T m SR6JCR6JVR6J
ATLAS missT + jets + E m Figure 3: Graphical illustration of the control and validation region configuration corresponding to the (top left), (top right), and (bottom) regions. The variables shown on the horizontal and vertical axes indicate otherselections that differ between the corresponding control regions, validation regions and signal regions. The dottedlines show the boundaries of the 𝑚 eff binning of the exclusion SRs. bs_x_TR6JEM_meffInc30 -
10 110 E v en t s / G e V -1 = 13 TeV, 139 fbs ATLAS
TR 6J preFit
DataTotal SMttSingle top W+jetsDibosonZ+jets+Vtt
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WR 6J preFit
DataTotal SMttSingle top W+jetsDibosonZ+jets+Vtt
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TR 6J
DataTotal SMttSingle top W+jetsDibosonZ+jets+Vtt
700 1400 2100 2800 3500 [GeV] eff m D a t a / S M obs_x_WR6JEM_meffInc30 -
10 110 E v en t s / G e V -1 = 13 TeV, 139 fbs ATLAS
WR 6J
DataTotal SMttSingle top W+jetsDibosonZ+jets+Vtt
700 1400 2100 2800 3500 [GeV] eff m D a t a / S M Figure 4: The 𝑚 eff distribution in J top (left, labelled as ‘TR’) and 𝑊 +jets (right, labelled as ‘WR’) control regionsbefore (top) and after (bottom) the fit. The uncertainty bands include all statistical and systematic uncertainties.Overflow events are included in the last bin. The expected yields for both the signal and background events are subject to theoretical and experimentalsystematic uncertainties. The theoretical uncertainties for the backgrounds normalised to data influenceonly the transfer factors from CR(s) to VR(s) and from CR(s) to SR(s), while for the other backgrounds,the uncertainties affect the inclusive cross-section of each process and the acceptance of the analysisselection.Following the procedure described in Section 6, both the experimental and the theoretical uncertainties arecomputed separately for each 𝑚 eff bin. For the single-top and 𝑡 ¯ 𝑡 backgrounds, the theoretical uncertaintiesdue to parton shower and hadronisation/fragmentation are estimated by comparing the predictions obtainedwith the Powheg-Box generator interfaced with two different parton shower generators, Pythia 8 and13 able 5: Breakdown of the dominant systematic uncertainties in the background estimates in the various signal regions.The individual uncertainties can be correlated and do not necessarily add in quadrature to the total backgrounduncertainty. The percentages show the size of the uncertainty relative to the total expected background. Uncertainty of channel 2J b-veto 2J b-tag 4J low-x b-veto 4J low-x b-tag
Total background expectation 346 272 449 810Total background systematic uncertainty 8% 25% 7% 13%Jet energy resolution 2 .
5% 4% 2 .
9% 2 . .
8% 1 .
6% 2 .
4% 1 . 𝑏 -tagging 1 .
6% 1 .
7% 2 .
2% 1 . .
0% 0 .
6% 0 .
5% 0 . 𝐸 missT /JVT/pile-up/trigger 1 .
9% 0 .
33% 0 .
5% 0 . 𝑊 +jets theory uncertainties 0 .
8% 1 .
8% 1 .
6% 0 . 𝑡 ¯ 𝑡 theory uncertainties 5% 23% 3 .
1% 12%Single-top theory uncertainties 0 .
7% 4% 0 .
9% 1 . .
7% 0 .
8% 2 .
8% 0 . .
5% 9% 1 .
0% 4%MC statistics 3 .
0% 1 .
5% 1 .
6% 0 . 𝑊𝑡 and 𝑡 ¯ 𝑡 production [89]. In order to evaluate the impact of the uncertainties coming from theemission of initial- and final-state radiation, the renormalisation, and factorisation scales and showeringare varied.Uncertainties for 𝑡 ¯ 𝑡 + 𝑉 , 𝑊 / 𝑍 +jets and dibosons coming from scale variations are evaluated by consideringthe envelope of the seven-point variations of the renormalisation and factorisation scales. The resummationand the CKKW matching variations for 𝑊 / 𝑍 +jets are estimated by varying the corresponding scaleparameters up and down by a factor of two relative to the nominal value for each region. The PDFuncertainties for 𝑊 / 𝑍 +jets are considered following the recommendation in PDF4LHC15 [47], whilethose for 𝑡 ¯ 𝑡 were found to be negligible in all the regions. Systematic uncertainties of 5% and 6% areassigned to the inclusive cross-sections of the 𝑡 ¯ 𝑡 + 𝑉 and diboson processes [90], respectively. For the otherbackground processes such as 𝑍 +jets, a systematic uncertainty in the inclusive cross-section is included atthe 5% level.The theoretical uncertainties in the expected yields for the two signal models are considered and estimatedusing MG5_aMC@NLO + Pythia 8 samples by varying the parameters corresponding to the factorisation,renormalisation and CKKW-L matching scales.Detector-related systematic uncertainties include uncertainties from jet energy scale (JES), jet energyresolution (JER), lepton reconstruction and identification, 𝑏 -tagging, 𝐸 missT modelling, pile-up, and thetrigger efficiency. The dominant experimental systematic uncertainties stem from the JES and JERuncertainties. They are derived as a function of 𝑝 T and 𝜂 of the jet, the pile-up conditions and the jet14 able 6: Breakdown of the dominant systematic uncertainties in the background estimates in the various signal regions.The individual uncertainties can be correlated and do not necessarily add in quadrature to the total backgrounduncertainty. The percentages show the size of the uncertainty relative to the total expected background. Uncertainty of channel 4J high-x b-veto 4J high-x b-tag 6J b-veto 6J b-tag
Total background expectation 117 160 46 196Total background systematic uncertainty 25% 17% 22% 15%Jet energy resolution 12% 2 .
2% 10% 2 . .
0% 1 .
9% 4% 1 . 𝑏 -tagging 1 .
6% 1 .
8% 3 .
4% 0 . .
8% 1 .
2% 0 . 𝐸 missT /JVT/pile-up/trigger 1 .
2% 0 .
8% 0 .
8% 0 . 𝑊 +jets theory uncertainties 19% 7% 13% 0 . 𝑡 ¯ 𝑡 theory uncertainties 5% 14% 17% 13%Single-top theory uncertainties 0 .
4% 3 .
2% 0 .
9% 4%Other theory uncertainties 1 .
8% 0 .
30% 2 .
4% 0 . .
8% 3 .
1% 2 .
9% 4%MC statistics 5% 2 .
2% 4% 1 . 𝑍 → ℓ + ℓ − , 𝐽 / 𝜓 → ℓ + ℓ − and 𝑊 → ℓ𝜈 decays [74, 75]. The 𝐸 missT modelling systematic uncertainties are evaluated by accounting for the uncertainties in the energyand momentum scale of each object used in the calculation, as well as the uncertainties in the soft term’sresolution and scale. The uncertainty due to pile-up modelling is computed by varying the reweightingfactor by ± 𝑏 -tagging efficiency are derived from data-driven measurementsin 𝑡 ¯ 𝑡 events [80, 92], while uncertainties associated with the probability of mistakenly 𝑏 -tagging a jetwhich does not contain a 𝑏 -hadron are determined using dijet samples [93]. The uncertainties in thedominant background normalisation are obtained when performing the fit including the background controlregions.Tables 5 and 6 detail the size of the different systematic uncertainties in the signal regions, summed over all 𝑚 eff bins. The uncertainty in the hard-scattering for 𝑡 ¯ 𝑡 dominates in many regions. The determination withMonte Carlo samples of the 𝑡 ¯ 𝑡 uncertainties reported in the tables includes also the statistical component,arising from limited MC statistics, in the uncertainties for all regions. Jet-related uncertainties dominatethe detector-related systematic uncertainties. The statistical interpretation of the data is based on a profile likelihood method using the HistFitterframework [94, 95]. The likelihood function includes a set of Poisson functions representing the yieldsin each of the control and signal regions. These Poisson functions depend on the observed number ofdata events in the respective region and the expected numbers of signal and background events. Different15 i n ff S R J b - t ag m b i n ff S R J b - t ag m b i n ff S R J b - t ag m b i n ff S R J b - v e t o m b i n ff S R J b - v e t o m b i n ff S R J b - v e t o m b i n ff S R J h i gh - x b - t ag m b i n ff S R J h i gh - x b - t ag m b i n ff S R J h i gh - x b - t ag m b i n ff S R J h i gh - x b - v e t o m b i n ff S R J h i gh - x b - v e t o m b i n ff S R J h i gh - x b - v e t o m b i n ff S R J l o w - x b - t ag m b i n ff S R J l o w - x b - t ag m b i n ff S R J l o w - x b - t ag m b i n ff S R J l o w - x b - v e t o m b i n ff S R J l o w - x b - v e t o m b i n ff S R J l o w - x b - v e t o m b i n ff S R J b - t ag m b i n ff S R J b - t ag m b i n ff S R J b - t ag m b i n ff S R J b - t ag m b i n ff S R J b - v e t o m b i n ff S R J b - v e t o m b i n ff S R J b - v e t o m b i n ff S R J b - v e t o m N u m be r o f e v en t s Data Total SMtt Single topW+jets DibosonZ+jets +VttData Total SMtt Single topW+jets DibosonZ+jets +Vtt
ATLAS missT + 2 - 6 jets + E m -1 = 13 TeV, 139 fbs b i n ff S R J b - t ag m b i n ff S R J b - t ag m b i n ff S R J b - t ag m b i n ff S R J b - v e t o m b i n ff S R J b - v e t o m b i n ff S R J b - v e t o m b i n ff S R J h i gh - x b - t ag m b i n ff S R J h i gh - x b - t ag m b i n ff S R J h i gh - x b - t ag m b i n ff S R J h i gh - x b - v e t o m b i n ff S R J h i gh - x b - v e t o m b i n ff S R J h i gh - x b - v e t o m b i n ff S R J l o w - x b - t ag m b i n ff S R J l o w - x b - t ag m b i n ff S R J l o w - x b - t ag m b i n ff S R J l o w - x b - v e t o m b i n ff S R J l o w - x b - v e t o m b i n ff S R J l o w - x b - v e t o m b i n ff S R J b - t ag m b i n ff S R J b - t ag m b i n ff S R J b - t ag m b i n ff S R J b - t ag m b i n ff S R J b - v e t o m b i n ff S R J b - v e t o m b i n ff S R J b - v e t o m b i n ff S R J b - v e t o m - S i gn i f i c an c e Figure 5: Comparison of the observed and expected event yields in all signal regions in the background-only fit. parameters are included in the likelihood function to control the normalisation of the backgrounds andthe signal or to reflect statistical and systematic uncertainties. The normalisations of the 𝑡 ¯ 𝑡 , single-topand 𝑊 +jets backgrounds are controlled by the respective normalisation factors assigned individuallyfor each 𝑚 eff bin in the SRs. This configuration corrects for the mismodelling of the 𝑚 eff distributionin the Monte Carlo simulation, as discussed in Section 6. An exception is made for the case in the 𝑚 eff > 𝑡 ¯ 𝑡 and single-top backgrounds the same normalisationfactor is used across the two 𝑚 eff bins due to the low statistics in the highest 𝑚 eff bin. The yields in thecorresponding control regions are sufficient to allow for two different normalisation factors for 𝑊 +jets,one in the range 𝑚 eff ∈ [ , ] GeV and one for 𝑚 eff > 𝑡 ¯ 𝑡 and single top and ten normalisation factors for 𝑊 +jets. The normalisationof the signal is controlled by one common normalisation factor applied to all bins included in the fit.Systematic uncertainties are accommodated through the use of nuisance parameters which are constrainedby a Gaussian auxiliary term added to the likelihood.In a background-only fit, only the control regions are used to constrain the likelihood. A signal contributionis neglected in the fit, so the signal normalisation parameter is dropped. The observed yields in the VRs arefound to be compatible with the background expectation obtained from this fit, with the largest deviation ofdata from MC over the 18 bins having a statistical significance of about 2 𝜎 . Background predictions inthe signal regions are compared with the observed data in Tables 7–10 and illustrated in Figures 5–7. Nosignificant excess of events is observed.Using the discovery signal regions defined in Table 2, a test is performed for the presence of beyond-the-SMphysics in a model-independent fit in each signal region. The signal contribution is only considered in the16 bs_x_SR2JBTEM_meffInc30 -
10 110 E v en t s / G e V -1 = 13 TeV, 139 fbs ATLAS
SR 2J b-tag
DataTotal SMttSingle top W+jetsDibosonZ+jets+Vtt )=(900,860,820) GeV c~ , – c~ ,g~m( )=(600,575,550) GeV c~ , – c~ ,q~m(
700 1300 1900 2500 [GeV] eff m D a t a / S M obs_x_SR2JBVEM_meffInc30 -
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SR 2J b-veto
DataTotal SMttSingle top W+jetsDibosonZ+jets+Vtt )=(900,860,820) GeV c~ , – c~ ,g~m( )=(600,575,550) GeV c~ , – c~ ,q~m(
700 1300 1900 2500 [GeV] eff m D a t a / S M obs_x_SR4JlowxBTEM_meffInc30 -
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SR 4J low-x b-tag
DataTotal SMttSingle top W+jetsDibosonZ+jets+Vtt )=(1600,660,60) GeV c~ , – c~ ,g~m( )=(1100,460,60) GeV c~ , – c~ ,q~m( eff m D a t a / S M obs_x_SR4JlowxBVEM_meffInc30 -
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SR 4J low-x b-veto
DataTotal SMttSingle top W+jetsDibosonZ+jets+Vtt )=(1600,660,60) GeV c~ , – c~ ,g~m( )=(1100,460,60) GeV c~ , – c~ ,q~m( eff m D a t a / S M Figure 6: Post-fit 𝑚 eff distributions in the exclusion and
4J low-x signal regions. The uncertainty bands includeall statistical and systematic uncertainties. The dashed lines represent benchmark signal points. Overflow events areincluded in the last bin. bs_x_SR4JhighxBTEM_meffInc30 -
10 110 E v en t s / G e V -1 = 13 TeV, 139 fbs ATLAS
SR 4J high-x b-tag
DataTotal SMttSingle top W+jetsDibosonZ+jets+Vtt )=(1400,1260,60) GeV c~ , – c~ ,g~m( )=(900,850,60) GeV c~ , – c~ ,q~m( eff m D a t a / S M obs_x_SR4JhighxBVEM_meffInc30 -
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SR 4J high-x b-veto
DataTotal SMttSingle top W+jetsDibosonZ+jets+Vtt )=(1400,1260,60) GeV c~ , – c~ ,g~m( )=(900,850,60) GeV c~ , – c~ ,q~m( eff m D a t a / S M obs_x_SR6JBTEM_meffInc30 -
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SR 6J b-tag
DataTotal SMttSingle top W+jetsDibosonZ+jets+Vtt )=(1800,1100,400) GeV c~ , – c~ ,g~m( )=(1000,512,24) GeV c~ , – c~ ,q~m(
700 1400 2100 2800 3500 [GeV] eff m D a t a / S M obs_x_SR6JBVEM_meffInc30 -
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SR 6J b-veto
DataTotal SMttSingle top W+jetsDibosonZ+jets+Vtt )=(1800,1100,400) GeV c~ , – c~ ,g~m( )=(1000,512,24) GeV c~ , – c~ ,q~m(
700 1400 2100 2800 3500 [GeV] eff m D a t a / S M Figure 7: Post-fit 𝑚 eff distributions in the exclusion
4J high-x and signal regions. The uncertainty bands includeall statistical and systematic uncertainties. The dashed lines represent benchmark signal points. Overflow events areincluded in the last bin. able 7: Observed event yields and the background expectation obtained by a background fit in the SRs with anintegrated luminosity of 139 fb − . Each column corresponds to a bin in 𝑚 eff [GeV]. Uncertainties reported for thefitted background estimates combine statistical (in the simulated event yields) and systematic uncertainties. Theuncertainties in this table are symmetrised for error propagation purposes but are truncated at zero to remain withinthe physical boundaries.
2J b-veto
Bin 1 Bin 2 Bin 3 [ , ] [ , ] > ±
22 73 ±
12 12 . ± . 𝑡 ¯ 𝑡 events 19 ±
13 11 ± . ± . 𝑊 +jets events 155 ±
14 28 ± . ± . 𝑍 +jets events 14 ± . ± . . ± . ± . ± . . ± . ± . ± . . ± . 𝑡 ¯ 𝑡 + 𝑉 events 1 . ± .
16 0 . ± .
23 0 . ± .
2J b-tag
Bin 1 Bin 2 Bin 3 [ , ] [ , ] > ±
36 123 ±
33 16 ± 𝑡 ¯ 𝑡 events 74 ±
35 90 ±
32 10 ± 𝑊 +jets events 20 ± . ± . . ± . 𝑍 +jets events 5 . ± . . ± . . ± . ± ± . ± . . ± . . ± . . ± . 𝑡 ¯ 𝑡 + 𝑉 events 8 . ± . . ± . . ± . respective signal region, and not in the CRs, and therefore a conservative background estimate is obtainedin the signal regions. Table 11 shows the observed and expected upper limits ( 𝑆 and 𝑆 , respectively)on the number of signal events, at 95% confidence level (CL) using the CL s prescription [96]. Also reportedis the visible cross-section upper limit ( (cid:104) 𝜖 𝜎 (cid:105) ), which is the upper limit on the cross-section times thereconstruction efficiency and region acceptance. The table also presents the discovery 𝑝 -values ( 𝑝 ), whichquantify the probability to observe at least as many events as expected in the background-only assumption,the CL b value, i.e. the confidence level observed for the background-only hypothesis, and the associatedsignificance.Observed and expected exclusion limits at 95% CL are calculated for the gluino and squark one-step modelsusing all statistically independent binned signal and control regions in a model-dependent fit. For thisexclusion fit, the signal contribution, adjusted using a single floating normalisation factor, is considered inall control and signal regions. The background normalisation factors are simultaneously determined in thesame fit. Specific sparticle masses in the gluino or squark one-step models can be excluded if the upperlimit of the signal normalisation factor is less than unity.Figure 8 shows the expected and observed exclusion limits. Gluino masses up to 2.2 TeV and 2.05 TeV canbe excluded for ˜ 𝜒 masses less than 400 GeV and 1 TeV respectively, while squark masses up to 1.37 TeV19 able 8: Observed event yields and the background expectation obtained by a background fit in the
4J low-x
SRswith an integrated luminosity of 139 fb − . Each column corresponds to a bin in 𝑚 eff [GeV]. Uncertainties reportedfor the fitted background estimates combine statistical (in the simulated event yields) and systematic uncertainties.The uncertainties in this table are symmetrised for error propagation purposes but are truncated at zero to remainwithin the physical boundaries.
4J low-x b-veto
Bin 1 Bin 2 Bin 3 [ , ] [ , ] > ±
27 56 ± . ± . 𝑡 ¯ 𝑡 events 72 ±
15 8 . ± . . ± . 𝑊 +jets events 179 ±
23 23 ± . ± . 𝑍 +jets events 4 . ± . . ± .
19 0 . ± . ± . ± . . + . − . Diboson events 110 ±
15 20 . ± . . ± . 𝑡 ¯ 𝑡 + 𝑉 events 5 . ± . . ± .
22 0 . ± .
4J low-x b-tag
Bin 1 Bin 2 Bin 3 [ , ] [ , ] > ±
90 94 ±
19 15 ± 𝑡 ¯ 𝑡 events 510 ±
90 60 ±
18 9 . ± . 𝑊 +jets events 36 ± . ± . . ± . 𝑍 +jets events 1 . ± . . ± .
08 0 . ± . ±
12 19 ± . ± . . ± . . ± . . ± . 𝑡 ¯ 𝑡 + 𝑉 events 41 . ± . . ± . . ± . can be excluded for low-mass ˜ 𝜒 . Benefiting from the increased integrated luminosity, the current observedlimit exceeds the previous ATLAS limit by about 100 GeV in 𝑚 ˜ 𝑔 and in 𝑚 ˜ 𝑞 for low-mass ˜ 𝜒 . In squarkone-step models in which only a single squark flavour is kinematically accessible, squark masses up toabout 1.0 TeV can be excluded. 20 able 9: Observed event yields and the background expectation obtained by a background fit in the
4J high-x
SRswith an integrated luminosity of 139 fb − . Each column corresponds to a bin in 𝑚 eff [GeV]. Uncertainties reportedfor the fitted background estimates combine statistical (in the simulated event yields) and systematic uncertainties.The uncertainties in this table are symmetrised for error propagation purposes but are truncated at zero to remainwithin the physical boundaries.
4J high-x b-veto
Bin 1 Bin 2 Bin 3 [ , ] [ , ] > ±
32 18 ± . ± . 𝑡 ¯ 𝑡 events 9 ± . ± . . ± . 𝑊 +jets events 61 ±
30 9 ± . ± . 𝑍 +jets events 1 . ± . . ± . . ± . . + . − . . + . − . . ± . . ± . . ± . . ± . 𝑡 ¯ 𝑡 + 𝑉 events 0 . ± .
15 0 . + . − . . ± .
4J high-x b-tag
Bin 1 Bin 2 Bin 3 [ , ] [ , ] > ±
27 25 ± . ± . 𝑡 ¯ 𝑡 events 90 ±
24 13 . ± . . ± . 𝑊 +jets events 18 ± . ± . . ± . 𝑍 +jets events 0 . ± .
10 0 . + . − . . ± . ± . ± . . ± . . ± . . ± .
34 0 . ± . 𝑡 ¯ 𝑡 + 𝑉 events 5 . ± . . ± .
17 0 . ± . able 10: Observed event yields and the background expectation obtained by a background fit in the SRs with anintegrated luminosity of 139 fb − . Each column corresponds to a bin in 𝑚 eff [GeV]. Uncertainties reported for thefitted background estimates combine statistical (in the simulated event yields) and systematic uncertainties. Theuncertainties in this table are symmetrised for error propagation purposes but are truncated at zero to remain withinthe physical boundaries.
6J b-veto
Bin 1 Bin 2 Bin 3 Bin 4 [ , ] [ , ] [ , ] > ± . ± . . ± . . ± . 𝑡 ¯ 𝑡 events 10 ± . ± . . ± .
26 0 . ± . 𝑊 +jets events 7 ± . ± . . ± . . ± . 𝑍 +jets events 0 . + . − . . ± .
07 0 . ± .
05 0 . ± . . + . − . . + . − . . ± . . ± . . ± . . ± . . ± .
26 0 . ± . 𝑡 ¯ 𝑡 + 𝑉 events 0 . ± .
18 0 . ± .
11 0 . ± .
04 0 . + . − .
6J b-tag
Bin 1 Bin 2 Bin 3 Bin 4 [ , ] [ , ] [ , ] > ±
17 70 ±
11 13 . ± . . ± . 𝑡 ¯ 𝑡 events 90 ±
17 52 ±
10 10 . ± . . ± . 𝑊 +jets events 2 . ± . . ± . . ± .
16 0 . ± . 𝑍 +jets events 0 . + . − . . ± .
05 0 . ± .
04 0 . ± . . ± . ± . ± . . + . − . Diboson events 1 . ± .
32 1 . ± .
31 0 . ± .
13 0 . ± . 𝑡 ¯ 𝑡 + 𝑉 events 11 . ± . . ± . . ± .
25 0 . ± . (cid:104) 𝜖 𝜎 (cid:105) and on the numberof signal events 𝑆 are given. The sixth column, 𝑆 , shows the 95% CL upper limit on the number of signal events,given the expected number (and ± 𝜎 excursions of the expectation) of background events. The last two columnsindicate the CL b value, i.e. the confidence level observed for the background-only hypothesis, the discovery 𝑝 -value 𝑝 ( 𝑠 = ) and the significance 𝑍 . In case of fewer events than the fitted background estimate observed, the p-valuesare capped at 0.5. SR disc Observed events Total SM background (cid:104) 𝜖 𝜎 (cid:105) [fb] 𝑆 𝑆 CL b 𝑝 ( 𝑠 = ) ( 𝑍 ) (gluino) 22 12.8 ± .
14 19 . . + . − . .
98 0 . ( . ) (squark) 106 86 ±
12 0 .
34 47 . . + . − . .
90 0 . ( . )
4J high-x
11 7.1 ± .
09 12 . . + . − . .
87 0 . ( . )
4J low-x
10 9.5 ± .
06 8 . . + . − . .
57 0 . ( . ) (gluino) 2 1.8 ± .
03 4 . . + . − . .
59 0 . ( . ) (squark) 5 5.3 ± .
04 6 . . + . − . .
48 0 . ( )
00 800 1000 1200 1400 1600 1800 2000 2200 2400 [GeV] g~ m200400600800100012001400160018002000 ) [ G e V ] c~ m ( c~ < m g ~ m ) exp s – Expected Limit ( )
SUSYtheory s – Observed Limit (PRD 96 (2017) 112010 (obs)
ATLAS ) ) = 1/2 c~ ) - m(g~) ) / ( m( c~ ) - m( – c~ , x = (m( c~ c~ qqqqWW fi g~-g~ , All limits at 95% CL -1 =13 TeV, 139 fbs missT + jets + E m g~ m00.20.40.60.811.21.41.6 ) c~ - m g ~ ) / ( m c~ - m –c~ x = ( m ) exp s – Expected Limit ( )
SUSYtheory s – Observed Limit (PRD 96 (2017) 112010 (obs)
ATLAS ) = 60 GeV c~ , m( c~ c~ qqqqWW fi g~-g~ , All limits at 95% CL -1 =13 TeV, 139 fbs missT + jets + E m
400 600 800 1000 1200 1400 1600 1800 [GeV] q~ m2004006008001000120014001600 ) [ G e V ] c~ m ( c~ < m q ~ m ) exp s – ) (s~,c~,d~,u~( L q~Expected Limit ) SUSYtheory s – ) (s~,c~,d~,u~( L q~Observed Limit ) exp s – ( L q~Expected Limit One Light ) SUSYtheory s – ( L q~Observed Limit One Light PRD 96 (2017) 112010 (obs) ATLAS ) ) = 1/2 c~ ) - m(q~) ) / ( m( c~ ) - m( – c~ , x = (m( c~ c~ qqWW fi q~-q~ ,All limits at 95% CL -1 =13 TeV, 139 fbs missT + jets + E m
600 800 1000 1200 1400 1600 1800 [GeV] q~ m00.20.40.60.811.21.41.6 ) c~ - m q ~ ) / ( m c~ - m –c~ x = ( m ) exp s – ) (s~,c~,d~,u~( L q~Expected Limit ) SUSYtheory s – ) (s~,c~,d~,u~( L q~Observed Limit ) exp s – ( L q~Expected Limit One Light ) SUSYtheory s – ( L q~Observed Limit One Light PRD 96 (2017) 112010 (obs) ATLAS ) = 60 GeV c~ , m( c~ c~ qqWW fi q~-q~ , All limits at 95% CL -1 =13 TeV, 139 fbs missT + jets + E m Figure 8: Exclusion limits for the gluino one-step 𝑥 = / 𝑥 (top right), squarkone-step 𝑥 = / 𝑥 (bottom right) scenarios. The red solid line correspondsto the observed limit, with the red dotted lines indicating the ± 𝜎 variation of the limit due to the effect of theoreticalscale and PDF uncertainties in the signal cross-section, for scenarios where the four left-handed squarks of the firsttwo generations ( ˜ 𝑢 L , ˜ 𝑑 L , ˜ 𝑐 L , ˜ 𝑠 L ) are mass degenerate. The dark grey dashed line indicates the expected limit with theyellow band representing the impact of the ± 𝜎 variation of the median expected limit due to the experimental andtheoretical uncertainties. The orange solid and the dashed lines show the squark one-step 𝑥 = / 𝑥 (right) scenarios for cases in which only a single squark flavour is kinematically accessible. Forreference, exclusion bounds from previous searches with 36.1 fb − of data at 13 TeV centre-of-mass energy [23] areoverlaid as the grey area. Conclusion
A search for gluinos and squarks in events with one isolated lepton, jets and missing transverse momentumis presented. The analysis uses 139 fb − of proton–proton collision data at a centre-of-mass energy of13 TeV collected by the ATLAS experiment at the LHC. Four signal regions requiring from at least two toat least six jets are used to cover a broad spectrum of the targeted SUSY model parameter space. Threesignal regions defined using high- 𝑝 T lepton selections target models with large mass differences betweenthe supersymmetric particles. A separate, low- 𝑝 T lepton region is designed to enhance the sensitivity tomodels with compressed mass spectra. The data agree with the Standard Model background prediction inthe signal regions. For all signal regions, limits on the visible cross-section are derived in models of newphysics within the kinematic requirements of this search. In addition, exclusion limits are placed on modelswith gluino/squark production and subsequent decays via an intermediate chargino to the lightest neutralino.This search extends the exclusion limit by 100 GeV (gluino) and 180 GeV (squark) for a massless LSPwith respect to the previous search [23] owing to a more solid background estimation technique and anincreased statistical sample. Gluino (Squark) masses up to around 2.2 (1.4) TeV are excluded for a ˜ 𝜒 mass lower than 200 GeV, while for scenarios with a single accessible squark flavour, squark masses up toaround 1.04 TeV are excluded. Acknowledgements
We thank CERN for the very successful operation of the LHC, as well as the support staff from ourinstitutions without whom ATLAS could not be operated efficiently.We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF,Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada;CERN; ANID, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPOCR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS and CEA-DRF/IRFU,France; SRNSFG, Georgia; BMBF, HGF and MPG, Germany; GSRT, Greece; RGC and Hong Kong SAR,China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO,Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; MNE/IFA, Romania; JINR; MESof Russia and NRC KI, Russian Federation; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia;DST/NRF, South Africa; MICINN, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF andCantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom; DOEand NSF, United States of America. In addition, individual groups and members have received supportfrom BCKDF, CANARIE, Compute Canada, CRC and IVADO, Canada; Beijing Municipal Science &Technology Commission, China; COST, ERC, ERDF, Horizon 2020 and Marie Skłodowska-Curie Actions,European Union; Investissements d’Avenir Labex, Investissements d’Avenir Idex and ANR, France; DFGand AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF andthe Greek NSRF, Greece; BSF-NSF and GIF, Israel; La Caixa Banking Foundation, CERCA ProgrammeGeneralitat de Catalunya and PROMETEO and GenT Programmes Generalitat Valenciana, Spain; GöranGustafssons Stiftelse, Sweden; The Royal Society and Leverhulme Trust, United Kingdom.The crucial computing support from all WLCG partners is acknowledged gratefully, in particular fromCERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3(France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC24Taiwan), RAL (UK) and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resourceproviders. Major contributors of computing resources are listed in Ref. [97].25 eferences [1] ATLAS Collaboration,
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Gurbuz , G. Gustavino ,M. Guth , P. Gutierrez , L.F. Gutierrez Zagazeta , C. Gutschow , C. Guyot , C. Gwenlan ,C.B. Gwilliam , E.S. Haaland , A. Haas , C. Haber , H.K. Hadavand , A. Hadef , M. Haleem ,J. Haley , J.J. Hall , G. Halladjian , G.D. Hallewell , K. Hamano , H. Hamdaoui , M. Hamer ,G.N. Hamity , K. Han , L. Han , L. Han , S. Han , Y.F. Han , K. Hanagaki , M. Hance ,D.M. Handl , M.D. Hank , R. Hankache , E. Hansen , J.B. Hansen , J.D. Hansen ,M.C. Hansen , P.H. Hansen , E.C. Hanson , K. Hara , T. Harenberg , S. Harkusha ,P.F. Harrison , N.M. Hartman , N.M. Hartmann , Y. Hasegawa , A. Hasib , S. Hassani ,S. Haug , R. Hauser , M. Havranek , C.M. Hawkes , R.J. Hawkings , S. Hayashida ,D. Hayden , C. Hayes , R.L. Hayes , C.P. Hays , J.M. Hays , H.S. Hayward , S.J. Haywood ,F. He , Y. He , M.P. Heath , V. Hedberg , A.L. Heggelund , N.D. Hehir , C. Heidegger ,K.K. Heidegger , W.D. Heidorn , J. Heilman , S. Heim , T. Heim , B. Heinemann ,J.G. Heinlein , J.J. Heinrich , L. Heinrich , J. Hejbal , L. Helary , A. Held , S. Hellesund ,C.M. Helling , S. Hellman , C. Helsens , R.C.W. Henderson , L. Henkelmann ,A.M. Henriques Correia , H. Herde , Y. Hernández Jiménez , H. Herr , M.G. Herrmann ,T. Herrmann , G. Herten , R. Hertenberger , L. Hervas , G.G. Hesketh , N.P. Hessey , H. Hibi ,S. Higashino , E. Higón-Rodriguez , K. Hildebrand , J.C. Hill , K.K. Hill , K.H. Hiller ,S.J. Hillier , M. Hils , I. Hinchliffe , F. Hinterkeuser , M. Hirose , S. Hirose , D. Hirschbuehl ,B. Hiti , O. Hladik , J. Hobbs , R. Hobincu , N. Hod , M.C. Hodgkinson , A. Hoecker ,D. Hohn , D. Hohov , T. Holm , T.R. Holmes , M. Holzbock , L.B.A.H. Hommels , T.M. Hong ,J.C. Honig , A. Hönle , B.H. Hooberman , W.H. Hopkins , Y. Horii , P. Horn , L.A. Horyn ,S. Hou , A. Hoummada , J. Howarth , J. Hoya , M. Hrabovsky , J. Hrivnac , A. Hrynevich ,T. Hryn’ova , P.J. Hsu , S.-C. Hsu , Q. Hu , S. Hu , Y.F. Hu , D.P. Huang , X. Huang ,Y. Huang , Y. Huang , Z. Hubacek , F. Hubaut , M. Huebner , F. Huegging , T.B. Huffman ,35. Huhtinen , R. Hulsken , R.F.H. Hunter , N. Huseynov , J. Huston , J. Huth , R. Hyneman ,S. Hyrych , G. Iacobucci , G. Iakovidis , I. Ibragimov , L. Iconomidou-Fayard , P. Iengo ,R. Ignazzi , R. Iguchi , T. Iizawa , Y. Ikegami , M. Ikeno , N. Ilic , F. Iltzsche , H. Imam ,G. Introzzi , M. Iodice , K. Iordanidou , V. Ippolito , M.F. Isacson , M. Ishino ,W. Islam , C. Issever , S. Istin , J.M. Iturbe Ponce , R. Iuppa , A. Ivina , J.M. Izen ,V. Izzo , P. Jacka , P. Jackson , R.M. Jacobs , B.P. Jaeger , V. Jain , G. Jäkel , K.B. Jakobi ,K. Jakobs , T. Jakoubek , J. Jamieson , K.W. Janas , R. Jansky , M. Janus , P.A. Janus ,G. Jarlskog , A.E. Jaspan , N. Javadov , T. Javůrek , M. Javurkova , F. Jeanneau , L. Jeanty ,J. Jejelava , P. Jenni , N. Jeong , S. Jézéquel , J. Jia , Z. Jia , H. Jiang , Y. Jiang , Z. Jiang ,S. Jiggins , F.A. Jimenez Morales , J. Jimenez Pena , S. Jin , A. Jinaru , O. Jinnouchi ,H. Jivan , P. Johansson , K.A. Johns , C.A. Johnson , E. Jones , R.W.L. Jones , S.D. Jones ,T.J. Jones , J. Jovicevic , X. Ju , J.J. Junggeburth , A. Juste Rozas , A. Kaczmarska ,M. Kado , H. Kagan , M. Kagan , A. Kahn , C. Kahra , T. Kaji , E. Kajomovitz ,C.W. Kalderon , A. Kaluza , A. Kamenshchikov , M. Kaneda , N.J. Kang , S. Kang ,Y. Kano , J. Kanzaki , L.S. Kaplan , D. Kar , K. Karava , M.J. Kareem , I. Karkanias ,S.N. Karpov , Z.M. Karpova , V. Kartvelishvili , A.N. Karyukhin , E. Kasimi , A. Kastanas ,C. Kato , J. Katzy , K. Kawade , K. Kawagoe , T. Kawaguchi , T. Kawamoto , G. Kawamura ,E.F. Kay , F.I. Kaya , S. Kazakos , V.F. Kazanin , J.M. Keaveney , R. Keeler ,J.S. Keller , E. Kellermann , D. Kelsey , J.J. Kempster , J. Kendrick , K.E. Kennedy , O. Kepka ,S. Kersten , B.P. Kerševan , S. Ketabchi Haghighat , F. Khalil-Zada , M. Khandoga ,A. Khanov , A.G. Kharlamov , T. Kharlamova , E.E. Khoda , T.J. Khoo ,G. Khoriauli , E. Khramov , J. Khubua , S. Kido , M. Kiehn , E. Kim , Y.K. Kim ,N. Kimura , A. Kirchhoff , D. Kirchmeier , J. Kirk , A.E. Kiryunin , T. Kishimoto ,D.P. Kisliuk , V. Kitali , C. Kitsaki , O. Kivernyk , T. Klapdor-Kleingrothaus , M. Klassen ,C. Klein , M.H. Klein , M. Klein , U. Klein , K. Kleinknecht , P. Klimek , A. Klimentov ,F. Klimpel , T. Klingl , T. Klioutchnikova , F.F. Klitzner , P. Kluit , S. Kluth , E. Kneringer ,E.B.F.G. Knoops , A. Knue , D. Kobayashi , M. Kobel , M. Kocian , T. Kodama , P. Kodys ,D.M. Koeck , P.T. Koenig , T. Koffas , N.M. Köhler , M. Kolb , I. Koletsou , T. Komarek ,T. Kondo , K. Köneke , A.X.Y. Kong , A.C. König , T. Kono , V. Konstantinides ,N. Konstantinidis , B. Konya , R. Kopeliansky , S. Koperny , K. Korcyl , K. Kordas ,G. Koren , A. Korn , I. Korolkov , E.V. Korolkova , N. Korotkova , O. Kortner , S. Kortner ,V.V. Kostyukhin , A. Kotsokechagia , A. Kotwal , A. Koulouris ,A. Kourkoumeli-Charalampidi , C. Kourkoumelis , E. Kourlitis , V. Kouskoura , R. Kowalewski ,W. Kozanecki , A.S. Kozhin , V.A. Kramarenko , G. Kramberger , D. Krasnopevtsev ,M.W. Krasny , A. Krasznahorkay , D. Krauss , J.A. Kremer , J. Kretzschmar , K. Kreul ,P. Krieger , F. Krieter , S. Krishnamurthy , A. Krishnan , M. Krivos , K. Krizka ,K. Kroeninger , H. Kroha , J. Kroll , J. Kroll , K.S. Krowpman , U. Kruchonak , H. Krüger ,N. Krumnack , M.C. Kruse , J.A. Krzysiak , A. Kubota , O. Kuchinskaia , S. Kuday ,D. Kuechler , J.T. Kuechler , S. Kuehn , T. Kuhl , V. Kukhtin , Y. Kulchitsky , S. Kuleshov ,Y.P. Kulinich , M. Kuna , A. Kupco , T. Kupfer , O. Kuprash , H. Kurashige ,L.L. Kurchaninov , Y.A. Kurochkin , A. Kurova , M.G. Kurth , E.S. Kuwertz , M. Kuze ,A.K. Kvam , J. Kvita , T. Kwan , C. Lacasta , F. Lacava , D.P.J. Lack , H. Lacker ,D. Lacour , E. Ladygin , R. Lafaye , B. Laforge , T. Lagouri , S. Lai , I.K. Lakomiec ,J.E. Lambert , S. Lammers , W. Lampl , C. Lampoudis , E. Lançon , U. Landgraf ,M.P.J. Landon , V.S. Lang , J.C. Lange , R.J. Langenberg , A.J. Lankford , F. Lanni ,K. Lantzsch , A. Lanza , A. Lapertosa , J.F. Laporte , T. Lari , F. Lasagni Manghi ,M. Lassnig , V. Latonova , T.S. Lau , A. Laudrain , A. Laurier , M. Lavorgna ,36.D. Lawlor , M. Lazzaroni , B. Le , E. Le Guirriec , A. Lebedev , M. LeBlanc ,T. LeCompte , F. Ledroit-Guillon , A.C.A. Lee , C.A. Lee , G.R. Lee , L. Lee , S.C. Lee ,S. Lee , B. Lefebvre , H.P. Lefebvre , M. Lefebvre , C. Leggett , K. Lehmann , N. Lehmann ,G. Lehmann Miotto , W.A. Leight , A. Leisos , M.A.L. Leite , C.E. Leitgeb , R. Leitner ,K.J.C. Leney , T. Lenz , S. Leone , C. Leonidopoulos , A. Leopold , C. Leroy , R. Les ,C.G. Lester , M. Levchenko , J. Levêque , D. Levin , L.J. Levinson , D.J. Lewis , B. Li ,B. Li , C-Q. Li , F. Li , H. Li , H. Li , J. Li , K. Li , L. Li , M. Li , Q.Y. Li ,S. Li , X. Li , Y. Li , Z. Li , Z. Li , Z. Li , Z. Li , Z. Liang , M. Liberatore ,B. Liberti , K. Lie , S. Lim , C.Y. Lin , K. Lin , R.A. Linck , R.E. Lindley , J.H. Lindon ,A. Linss , A.L. Lionti , E. Lipeles , A. Lipniacka , T.M. Liss , A. Lister , J.D. Little , B. Liu ,B.X. Liu , H.B. 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Mino , L.M. Mir , M. Mironova , T. Mitani , J. Mitrevski , V.A. Mitsou ,37. Mittal , O. Miu , A. Miucci , P.S. Miyagawa , A. Mizukami , J.U. Mjörnmark ,T. Mkrtchyan , M. Mlynarikova , T. Moa , S. Mobius , K. Mochizuki , P. Moder ,P. Mogg , S. Mohapatra , R. Moles-Valls , K. Mönig , E. Monnier , A. Montalbano ,J. Montejo Berlingen , M. Montella , F. Monticelli , S. Monzani , N. Morange ,A.L. Moreira De Carvalho , D. Moreno , M. Moreno Llácer , C. Moreno Martinez ,P. Morettini , M. Morgenstern , S. Morgenstern , D. Mori , M. Morii , M. Morinaga ,V. Morisbak , A.K. Morley , G. Mornacchi , A.P. Morris , L. Morvaj , P. Moschovakos ,B. Moser , M. Mosidze , T. Moskalets , P. Moskvitina , J. Moss , E.J.W. Moyse ,S. Muanza , J. Mueller , R.S.P. Mueller , D. Muenstermann , G.A. Mullier , J.J. Mullin ,D.P. Mungo , J.L. Munoz Martinez , F.J. Munoz Sanchez , P. Murin , W.J. Murray ,A. Murrone , J.M. Muse , M. Muškinja , C. Mwewa , A.G. Myagkov , A.A. Myers ,G. Myers , J. Myers , M. Myska , B.P. 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Paredes Hernandez , S.R. Paredes Saenz , B. Parida , T.H. Park , A.J. Parker , M.A. Parker ,F. Parodi , E.W. Parrish , J.A. Parsons , U. Parzefall , L. Pascual Dominguez , V.R. Pascuzzi ,J.M.P. Pasner , F. Pasquali , E. Pasqualucci , S. Passaggio , F. Pastore , P. Pasuwan ,S. Pataraia , J.R. Pater , A. Pathak , J. Patton , T. Pauly , J. Pearkes , M. Pedersen ,L. Pedraza Diaz , R. Pedro , T. Peiffer , S.V. Peleganchuk , O. Penc , C. Peng ,H. Peng , B.S. Peralva , M.M. Perego , A.P. Pereira Peixoto , L. Pereira Sanchez ,D.V. Perepelitsa , E. Perez Codina , L. Perini , H. Pernegger , S. Perrella , A. Perrevoort ,K. Peters , R.F.Y. Peters , B.A. Petersen , T.C. Petersen , E. Petit , V. Petousis , C. Petridou ,F. Petrucci , M. Pettee , N.E. Pettersson , K. Petukhova , A. Peyaud , R. Pezoa ,L. Pezzotti , T. Pham , P.W. Phillips , M.W. Phipps , G. Piacquadio , E. Pianori ,A. Picazio , R.H. Pickles , R. Piegaia , D. Pietreanu , J.E. Pilcher , A.D. Pilkington ,M. Pinamonti , J.L. Pinfold , C. Pitman Donaldson , M. Pitt , L. Pizzimento , A. Pizzini ,M.-A. Pleier , V. Plesanovs , V. Pleskot , E. Plotnikova , P. Podberezko , R. Poettgen ,38. Poggi , L. Poggioli , I. Pogrebnyak , D. Pohl , I. Pokharel , G. Polesello , A. Poley ,A. Policicchio , R. Polifka , A. Polini , C.S. Pollard , V. Polychronakos , D. Ponomarenko ,L. Pontecorvo , S. Popa , G.A. Popeneciu , L. Portales , D.M. Portillo Quintero , S. Pospisil ,K. Potamianos , I.N. Potrap , C.J. Potter , H. Potti , T. Poulsen , J. Poveda , T.D. Powell ,G. Pownall , M.E. Pozo Astigarraga , A. Prades Ibanez , P. Pralavorio , M.M. Prapa , S. Prell ,D. Price , M. Primavera , M.L. Proffitt , N. Proklova , K. Prokofiev , F. Prokoshin ,S. Protopopescu , J. Proudfoot , M. Przybycien , D. Pudzha , A. Puri , P. Puzo ,D. Pyatiizbyantseva , J. Qian , Y. Qin , A. Quadt , M. Queitsch-Maitland , G. Rabanal Bolanos ,M. Racko , F. Ragusa , G. Rahal , J.A. Raine , S. Rajagopalan , A. Ramirez Morales ,K. Ran , D.F. Rassloff , D.M. Rauch , F. Rauscher , S. Rave , B. Ravina , I. Ravinovich ,M. Raymond , A.L. Read , N.P. Readioff , M. Reale , D.M. Rebuzzi , G. Redlinger ,K. Reeves , D. Reikher , A. Reiss , A. Rej , C. Rembser , A. Renardi , M. Renda ,M.B. Rendel , A.G. Rennie , S. Resconi , E.D. Resseguie , S. Rettie , B. Reynolds ,E. Reynolds , O.L. Rezanova , P. Reznicek , E. Ricci , R. Richter , S. Richter ,E. Richter-Was , M. Ridel , P. Rieck , O. Rifki , M. Rijssenbeek , A. Rimoldi ,M. Rimoldi , L. Rinaldi , T.T. Rinn , G. Ripellino , I. Riu , P. Rivadeneira ,J.C. Rivera Vergara , F. Rizatdinova , E. Rizvi , C. Rizzi , S.H. Robertson , M. Robin ,D. Robinson , C.M. Robles Gajardo , M. Robles Manzano , A. Robson , A. Rocchi ,C. Roda , S. Rodriguez Bosca , A. Rodriguez Rodriguez , A.M. Rodríguez Vera , S. Roe ,J. Roggel , O. Røhne , R. Röhrig , R.A. Rojas , B. Roland , C.P.A. Roland , J. Roloff ,A. Romaniouk , M. Romano , N. Rompotis , M. Ronzani , L. Roos , S. Rosati , G. Rosin ,B.J. Rosser , E. Rossi , E. Rossi , E. Rossi , L.P. Rossi , L. Rossini , R. Rosten ,M. Rotaru , B. Rottler , D. Rousseau , G. Rovelli , A. Roy , D. Roy , A. Rozanov ,Y. Rozen , X. Ruan , T.A. Ruggeri , F. Rühr , A. Ruiz-Martinez , A. Rummler , Z. Rurikova ,N.A. Rusakovich , H.L. Russell , L. Rustige , J.P. Rutherfoord , E.M. Rüttinger , M. Rybar ,G. Rybkin , E.B. Rye , A. Ryzhov , J.A. Sabater Iglesias , P. Sabatini , L. Sabetta ,S. Sacerdoti , H.F-W. Sadrozinski , R. Sadykov , F. Safai Tehrani , B. Safarzadeh Samani ,M. Safdari , P. Saha , S. Saha , M. Sahinsoy , A. Sahu , M. Saimpert , M. Saito , T. Saito ,H. Sakamoto , D. Salamani , G. Salamanna , A. Salnikov , J. Salt , A. Salvador Salas ,D. Salvatore , F. Salvatore , A. Salvucci , A. Salzburger , J. Samarati , D. Sammel ,D. Sampsonidis , D. Sampsonidou , J. Sánchez , A. Sanchez Pineda , H. Sandaker ,C.O. Sander , I.G. Sanderswood , M. Sandhoff , C. Sandoval , D.P.C. Sankey , M. Sannino ,Y. Sano , A. Sansoni , C. Santoni , H. Santos , S.N. Santpur , A. Santra , K.A. Saoucha ,A. Sapronov , J.G. Saraiva , O. Sasaki , K. Sato , F. Sauerburger , E. Sauvan , P. Savard ,R. Sawada , C. Sawyer , L. Sawyer , I. Sayago Galvan , C. Sbarra , A. Sbrizzi ,T. Scanlon , J. Schaarschmidt , P. Schacht , D. Schaefer , L. Schaefer , U. Schäfer ,A.C. Schaffer , D. Schaile , R.D. Schamberger , E. Schanet , C. Scharf , N. Scharmberg ,V.A. Schegelsky , D. Scheirich , F. Schenck , M. Schernau , C. Schiavi , L.K. Schildgen ,Z.M. Schillaci , E.J. Schioppa , M. Schioppa , K.E. Schleicher , S. Schlenker ,K.R. Schmidt-Sommerfeld , K. Schmieden , C. Schmitt , S. Schmitt , L. Schoeffel ,A. Schoening , P.G. Scholer , E. Schopf , M. Schott , J.F.P. Schouwenberg , J. Schovancova ,S. Schramm , F. Schroeder , A. Schulte , H-C. Schultz-Coulon , M. Schumacher ,B.A. Schumm , Ph. Schune , A. Schwartzman , T.A. Schwarz , Ph. Schwemling ,R. Schwienhorst , A. Sciandra , G. Sciolla , F. Scuri , F. Scutti , L.M. Scyboz ,C.D. Sebastiani , K. Sedlaczek , P. Seema , S.C. Seidel , A. Seiden , B.D. Seidlitz , T. Seiss ,C. Seitz , J.M. Seixas , G. Sekhniaidze , S.J. Sekula , N. Semprini-Cesari , S. Sen ,C. Serfon , L. Serin , L. Serkin , M. Sessa , H. Severini , S. Sevova , F. Sforza ,39. Sfyrla , E. Shabalina , J.D. Shahinian , N.W. Shaikh , D. Shaked Renous , L.Y. Shan ,M. Shapiro , A. Sharma , A.S. Sharma , P.B. Shatalov , K. Shaw , S.M. Shaw , M. Shehade ,Y. Shen , A.D. Sherman , P. Sherwood , L. Shi , C.O. Shimmin , Y. Shimogama ,M. Shimojima , J.D. Shinner , I.P.J. Shipsey , S. Shirabe , M. Shiyakova , J. Shlomi ,A. Shmeleva , M.J. Shochet , J. Shojaii , D.R. Shope , S. Shrestha , E.M. Shrif , M.J. Shroff ,E. Shulga , P. Sicho , A.M. Sickles , E. Sideras Haddad , O. Sidiropoulou , A. Sidoti ,F. Siegert , Dj. Sijacki , M.Jr. Silva , M.V. Silva Oliveira , S.B. Silverstein , S. Simion ,R. Simoniello , C.J. Simpson-allsop , S. Simsek , P. Sinervo , V. Sinetckii , S. Singh ,S. Sinha , M. Sioli , I. Siral , S.Yu. Sivoklokov , J. Sjölin , A. Skaf , E. Skorda ,P. Skubic , M. Slawinska , K. Sliwa , V. Smakhtin , B.H. Smart , J. Smiesko , N. Smirnov ,S.Yu. Smirnov , Y. Smirnov , L.N. Smirnova , O. Smirnova , E.A. Smith , H.A. Smith ,M. Smizanska , K. Smolek , A. Smykiewicz , A.A. Snesarev , H.L. Snoek , I.M. Snyder ,S. Snyder , R. Sobie , A. Soffer , A. Søgaard , F. Sohns , C.A. Solans Sanchez ,E.Yu. Soldatov , U. Soldevila , A.A. Solodkov , A. Soloshenko , O.V. Solovyanov ,V. Solovyev , P. Sommer , H. Son , A. Sonay , W. Song , W.Y. Song , A. Sopczak ,A.L. Sopio , F. Sopkova , S. Sottocornola , R. Soualah , A.M. Soukharev , D. South ,S. Spagnolo , M. Spalla , M. Spangenberg , F. Spanò , D. Sperlich , T.M. Spieker ,G. Spigo , M. Spina , D.P. Spiteri , M. Spousta , A. Stabile , B.L. Stamas , R. Stamen ,M. Stamenkovic , A. Stampekis , E. Stanecka , B. Stanislaus , M.M. Stanitzki , M. Stankaityte ,B. Stapf , E.A. Starchenko , G.H. Stark , J. Stark , P. Staroba , P. Starovoitov , S. Stärz ,R. Staszewski , G. Stavropoulos , M. Stegler , P. Steinberg , A.L. Steinhebel , B. Stelzer ,H.J. Stelzer , O. Stelzer-Chilton , H. Stenzel , T.J. Stevenson , G.A. Stewart , M.C. Stockton ,G. Stoicea , M. Stolarski , S. Stonjek , A. Straessner , J. Strandberg , S. Strandberg ,M. Strauss , T. Strebler , P. Strizenec , R. Ströhmer , D.M. Strom , R. Stroynowski ,A. Strubig , S.A. Stucci , B. Stugu , J. Stupak , N.A. Styles , D. Su , W. Su ,X. Su , N.B. Suarez , V.V. Sulin , M.J. Sullivan , D.M.S. Sultan , S. Sultansoy , T. Sumida ,S. Sun , X. Sun , C.J.E. Suster , M.R. Sutton , S. Suzuki , M. Svatos , M. Swiatlowski ,S.P. Swift , T. Swirski , A. Sydorenko , I. Sykora , M. Sykora , T. Sykora , D. Ta ,K. Tackmann , J. Taenzer , A. Taffard , R. Tafirout , E. Tagiev , R.H.M. Taibah ,R. Takashima , K. Takeda , T. Takeshita , E.P. Takeva , Y. Takubo , M. Talby ,A.A. Talyshev , K.C. Tam , N.M. Tamir , J. Tanaka , R. Tanaka , S. Tapia Araya ,S. Tapprogge , A. Tarek Abouelfadl Mohamed , S. Tarem , K. Tariq , G. Tarna ,G.F. Tartarelli , P. Tas , M. Tasevsky , E. Tassi , G. Tateno , A. Tavares Delgado ,Y. Tayalati , A.J. Taylor , G.N. Taylor , W. Taylor , H. Teagle , A.S. Tee ,R. Teixeira De Lima , P. Teixeira-Dias , H. Ten Kate , J.J. Teoh , K. Terashi , J. Terron ,S. Terzo , M. Testa , R.J. Teuscher , N. Themistokleous , T. Theveneaux-Pelzer , D.W. Thomas ,J.P. Thomas , E.A. Thompson , P.D. Thompson , E. Thomson , E.J. Thorpe , V.O. Tikhomirov ,Yu.A. Tikhonov , S. Timoshenko , P. Tipton , S. Tisserant , K. Todome ,S. Todorova-Nova , S. Todt , J. Tojo , S. Tokár , K. Tokushuku , E. Tolley , R. Tombs ,K.G. Tomiwa , M. Tomoto , L. Tompkins , P. Tornambe , E. Torrence , H. Torres ,E. Torró Pastor , M. Toscani , C. Tosciri , J. Toth , D.R. Tovey , A. Traeet , C.J. Treado ,T. Trefzger , F. Tresoldi , A. Tricoli , I.M. Trigger , S. Trincaz-Duvoid , D.A. Trischuk ,W. Trischuk , B. Trocmé , A. Trofymov , C. Troncon , F. Trovato , L. Truong , M. Trzebinski ,A. Trzupek , F. Tsai , P.V. Tsiareshka , A. Tsirigotis , V. Tsiskaridze , E.G. Tskhadadze ,M. Tsopoulou , I.I. Tsukerman , V. Tsulaia , S. Tsuno , D. Tsybychev , Y. Tu , A. Tudorache ,V. Tudorache , A.N. Tuna , S. Turchikhin , D. Turgeman , I. Turk Cakir , R.J. Turner ,R. Turra , P.M. Tuts , S. Tzamarias , E. Tzovara , K. Uchida , F. Ukegawa , G. Unal ,40. Unal , A. Undrus , G. Unel , F.C. Ungaro , Y. Unno , K. Uno , J. Urban , P. Urquijo ,G. Usai , Z. Uysal , V. Vacek , B. Vachon , K.O.H. Vadla , T. Vafeiadis , A. Vaidya ,C. Valderanis , E. Valdes Santurio , M. Valente , S. Valentinetti , A. Valero , L. Valéry ,R.A. Vallance , A. Vallier , J.A. Valls Ferrer , T.R. Van Daalen , P. Van Gemmeren , S. Van Stroud ,I. Van Vulpen , M. Vanadia , W. Vandelli , M. Vandenbroucke , E.R. Vandewall ,D. Vannicola , R. Vari , E.W. Varnes , C. Varni , T. Varol , D. Varouchas , K.E. Varvell ,M.E. Vasile , G.A. Vasquez , F. Vazeille , D. Vazquez Furelos , T. Vazquez Schroeder , J. Veatch ,V. Vecchio , M.J. Veen , L.M. Veloce , F. Veloso , S. Veneziano , A. Ventura ,A. Verbytskyi , V. Vercesi , M. Verducci , C.M. Vergel Infante , C. Vergis , W. Verkerke ,A.T. Vermeulen , J.C. Vermeulen , C. Vernieri , P.J. Verschuuren , M.C. Vetterli ,N. Viaux Maira , T. Vickey , O.E. Vickey Boeriu , G.H.A. Viehhauser , L. Vigani ,M. Villa , M. Villaplana Perez , E.M. Villhauer , E. Vilucchi , M.G. Vincter , G.S. Virdee ,A. Vishwakarma , C. Vittori , I. Vivarelli , M. Vogel , P. Vokac , J. Von Ahnen ,S.E. von Buddenbrock , E. Von Toerne , V. Vorobel , K. Vorobev , M. Vos , J.H. Vossebeld ,M. Vozak , N. Vranjes , M. Vranjes Milosavljevic , V. Vrba , M. Vreeswijk , N.K. Vu ,R. Vuillermet , I. Vukotic , S. Wada , P. Wagner , W. Wagner , J. Wagner-Kuhr , S. Wahdan ,H. Wahlberg , R. Wakasa , V.M. Walbrecht , J. Walder , R. Walker , S.D. Walker ,W. Walkowiak , V. Wallangen , A.M. Wang , A.Z. Wang , C. Wang , C. Wang , H. Wang ,H. Wang , J. Wang , P. Wang , Q. Wang , R.-J. Wang , R. Wang , R. Wang , S.M. Wang ,T. Wang , W.T. Wang , W. Wang , W.X. Wang , Y. Wang , Z. Wang , C. Wanotayaroj ,A. Warburton , C.P. Ward , R.J. Ward , N. Warrack , A.T. Watson , M.F. Watson , G. Watts ,B.M. Waugh , A.F. Webb , C. Weber , M.S. Weber , S.A. Weber , S.M. Weber , Y. Wei ,A.R. Weidberg , J. Weingarten , M. Weirich , C. Weiser , P.S. Wells , T. Wenaus , B. Wendland ,T. Wengler , S. Wenig , N. Wermes , M. Wessels , T.D. Weston , K. Whalen , A.M. Wharton ,A.S. White , A. White , M.J. White , D. Whiteson , B.W. Whitmore , W. Wiedenmann , C. Wiel ,M. Wielers , N. Wieseotte , C. Wiglesworth , L.A.M. Wiik-Fuchs , H.G. Wilkens , L.J. Wilkins ,D.M. Williams , H.H. Williams , S. Williams , S. Willocq , P.J. Windischhofer ,I. Wingerter-Seez , E. Winkels , F. Winklmeier , B.T. Winter , M. Wittgen , M. Wobisch ,A. Wolf , R. Wölker , J. Wollrath , M.W. Wolter , H. Wolters , V.W.S. Wong ,A.F. Wongel , N.L. Woods , S.D. Worm , B.K. Wosiek , K.W. Woźniak , K. Wraight , S.L. Wu ,X. Wu , Y. Wu , J. Wuerzinger , T.R. Wyatt , B.M. Wynne , S. Xella , L. Xia , J. Xiang ,X. Xiao , X. Xie , I. Xiotidis , D. Xu , H. Xu , H. Xu , L. Xu , R. Xu , T. Xu , W. Xu ,Y. Xu , Z. Xu , Z. Xu , B. Yabsley , S. Yacoob , D.P. Yallup , N. Yamaguchi ,Y. Yamaguchi , A. Yamamoto , M. Yamatani , T. Yamazaki , Y. Yamazaki , J. Yan , Z. Yan ,H.J. Yang , H.T. Yang , S. Yang , T. Yang , X. Yang , X. Yang , Y. Yang , Z. Yang ,W-M. Yao , Y.C. Yap , H. Ye , J. Ye , S. Ye , I. Yeletskikh , M.R. Yexley , E. Yigitbasi , P. Yin ,K. Yorita , K. Yoshihara , C.J.S. Young , C. Young , J. Yu , R. Yuan , X. Yue , M. Zaazoua ,B. Zabinski , G. Zacharis , E. Zaffaroni , J. Zahreddine , A.M. Zaitsev , T. Zakareishvili ,N. Zakharchuk , S. Zambito , D. Zanzi , S.V. Zeißner , C. Zeitnitz , G. Zemaityte , J.C. Zeng ,O. Zenin , T. Ženiš , D. Zerwas , M. Zgubič , B. Zhang , D.F. Zhang , G. Zhang , J. Zhang ,K. Zhang , L. Zhang , L. Zhang , M. Zhang , R. Zhang , S. Zhang , X. Zhang , X. Zhang ,Y. Zhang , Z. Zhang , Z. Zhang , P. Zhao , Y. Zhao , Z. Zhao , A. Zhemchugov ,Z. Zheng , D. Zhong , B. Zhou , C. Zhou , H. Zhou , M. Zhou , N. Zhou , Y. Zhou ,C.G. Zhu , C. Zhu , H.L. Zhu , H. Zhu , J. Zhu , Y. Zhu , X. Zhuang , K. Zhukov ,V. Zhulanov , D. Zieminska , N.I. Zimine , S. Zimmermann , Z. Zinonos , M. Ziolkowski ,L. Živković , G. Zobernig , A. Zoccoli , K. Zoch , T.G. Zorbas , R. Zou , L. Zwalinski .41 Department of Physics, University of Adelaide, Adelaide; Australia. Physics Department, SUNY Albany, Albany NY; United States of America. Department of Physics, University of Alberta, Edmonton AB; Canada. ( 𝑎 ) Department of Physics, Ankara University, Ankara; ( 𝑏 ) Istanbul Aydin University, Application andResearch Center for Advanced Studies, Istanbul; ( 𝑐 ) Division of Physics, TOBB University of Economicsand Technology, Ankara; Turkey. LAPP, Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS/IN2P3, Annecy; France. High Energy Physics Division, Argonne National Laboratory, Argonne IL; United States of America. Department of Physics, University of Arizona, Tucson AZ; United States of America. Department of Physics, University of Texas at Arlington, Arlington TX; United States of America. Physics Department, National and Kapodistrian University of Athens, Athens; Greece. Physics Department, National Technical University of Athens, Zografou; Greece. Department of Physics, University of Texas at Austin, Austin TX; United States of America. ( 𝑎 ) Bahcesehir University, Faculty of Engineering and Natural Sciences, Istanbul; ( 𝑏 ) Istanbul BilgiUniversity, Faculty of Engineering and Natural Sciences, Istanbul; ( 𝑐 ) Department of Physics, BogaziciUniversity, Istanbul; ( 𝑑 ) Department of Physics Engineering, Gaziantep University, Gaziantep; Turkey. Institute of Physics, Azerbaijan Academy of Sciences, Baku; Azerbaijan. Institut de Física d’Altes Energies (IFAE), Barcelona Institute of Science and Technology, Barcelona;Spain. ( 𝑎 ) Institute of High Energy Physics, Chinese Academy of Sciences, Beijing; ( 𝑏 ) Physics Department,Tsinghua University, Beijing; ( 𝑐 ) Department of Physics, Nanjing University, Nanjing; ( 𝑑 ) University ofChinese Academy of Science (UCAS), Beijing; China. Institute of Physics, University of Belgrade, Belgrade; Serbia. Department for Physics and Technology, University of Bergen, Bergen; Norway. Physics Division, Lawrence Berkeley National Laboratory and University of California, Berkeley CA;United States of America. Institut für Physik, Humboldt Universität zu Berlin, Berlin; Germany. Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics, University ofBern, Bern; Switzerland. School of Physics and Astronomy, University of Birmingham, Birmingham; United Kingdom. ( 𝑎 ) Facultad de Ciencias y Centro de Investigaciónes, Universidad Antonio Nariño,Bogotá; ( 𝑏 ) Departamento de Física, Universidad Nacional de Colombia, Bogotá, Colombia; Colombia. ( 𝑎 ) INFN Bologna and Universita’ di Bologna, Dipartimento di Fisica; ( 𝑏 ) INFN Sezione di Bologna; Italy. Physikalisches Institut, Universität Bonn, Bonn; Germany. Department of Physics, Boston University, Boston MA; United States of America. Department of Physics, Brandeis University, Waltham MA; United States of America. ( 𝑎 ) Transilvania University of Brasov, Brasov; ( 𝑏 ) Horia Hulubei National Institute of Physics and NuclearEngineering, Bucharest; ( 𝑐 ) Department of Physics, Alexandru Ioan Cuza University of Iasi,Iasi; ( 𝑑 ) National Institute for Research and Development of Isotopic and Molecular Technologies, PhysicsDepartment, Cluj-Napoca; ( 𝑒 ) University Politehnica Bucharest, Bucharest; ( 𝑓 ) West University in Timisoara,Timisoara; Romania. ( 𝑎 ) Faculty of Mathematics, Physics and Informatics, Comenius University, Bratislava; ( 𝑏 ) Department ofSubnuclear Physics, Institute of Experimental Physics of the Slovak Academy of Sciences, Kosice; SlovakRepublic. Physics Department, Brookhaven National Laboratory, Upton NY; United States of America. Departamento de Física, Universidad de Buenos Aires, Buenos Aires; Argentina. California State University, CA; United States of America.42 Cavendish Laboratory, University of Cambridge, Cambridge; United Kingdom. ( 𝑎 ) Department of Physics, University of Cape Town, Cape Town; ( 𝑏 ) iThemba Labs, WesternCape; ( 𝑐 ) Department of Mechanical Engineering Science, University of Johannesburg,Johannesburg; ( 𝑑 ) University of South Africa, Department of Physics, Pretoria; ( 𝑒 ) School of Physics,University of the Witwatersrand, Johannesburg; South Africa. Department of Physics, Carleton University, Ottawa ON; Canada. ( 𝑎 ) Faculté des Sciences Ain Chock, Réseau Universitaire de Physique des Hautes Energies - UniversitéHassan II, Casablanca; ( 𝑏 ) Faculté des Sciences, Université Ibn-Tofail, Kénitra; ( 𝑐 ) Faculté des SciencesSemlalia, Université Cadi Ayyad, LPHEA-Marrakech; ( 𝑑 ) Moroccan Foundation for Advanced ScienceInnovation and Research (MAScIR), Rabat; ( 𝑒 ) Faculté des Sciences, Université Mohamed Premier andLPTPM, Oujda; ( 𝑓 ) Faculté des sciences, Université Mohammed V, Rabat; Morocco. CERN, Geneva; Switzerland. Enrico Fermi Institute, University of Chicago, Chicago IL; United States of America. LPC, Université Clermont Auvergne, CNRS/IN2P3, Clermont-Ferrand; France. Nevis Laboratory, Columbia University, Irvington NY; United States of America. Niels Bohr Institute, University of Copenhagen, Copenhagen; Denmark. ( 𝑎 ) Dipartimento di Fisica, Università della Calabria, Rende; ( 𝑏 ) INFN Gruppo Collegato di Cosenza,Laboratori Nazionali di Frascati; Italy. Physics Department, Southern Methodist University, Dallas TX; United States of America. Physics Department, University of Texas at Dallas, Richardson TX; United States of America. National Centre for Scientific Research "Demokritos", Agia Paraskevi; Greece. ( 𝑎 ) Department of Physics, Stockholm University; ( 𝑏 ) Oskar Klein Centre, Stockholm; Sweden. Deutsches Elektronen-Synchrotron DESY, Hamburg and Zeuthen; Germany. Lehrstuhl für Experimentelle Physik IV, Technische Universität Dortmund, Dortmund; Germany. Institut für Kern- und Teilchenphysik, Technische Universität Dresden, Dresden; Germany. Department of Physics, Duke University, Durham NC; United States of America. SUPA - School of Physics and Astronomy, University of Edinburgh, Edinburgh; United Kingdom. INFN e Laboratori Nazionali di Frascati, Frascati; Italy. Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg; Germany. II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen; Germany. Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève; Switzerland. ( 𝑎 ) Dipartimento di Fisica, Università di Genova, Genova; ( 𝑏 ) INFN Sezione di Genova; Italy. II. Physikalisches Institut, Justus-Liebig-Universität Giessen, Giessen; Germany. SUPA - School of Physics and Astronomy, University of Glasgow, Glasgow; United Kingdom. LPSC, Université Grenoble Alpes, CNRS/IN2P3, Grenoble INP, Grenoble; France. Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge MA; United States ofAmerica. ( 𝑎 ) Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics,University of Science and Technology of China, Hefei; ( 𝑏 ) Institute of Frontier and Interdisciplinary Scienceand Key Laboratory of Particle Physics and Particle Irradiation (MOE), Shandong University,Qingdao; ( 𝑐 ) School of Physics and Astronomy, Shanghai Jiao Tong University, KLPPAC-MoE, SKLPPC,Shanghai; ( 𝑑 ) Tsung-Dao Lee Institute, Shanghai; China. ( 𝑎 ) Kirchhoff-Institut für Physik, Ruprecht-Karls-Universität Heidelberg, Heidelberg; ( 𝑏 ) PhysikalischesInstitut, Ruprecht-Karls-Universität Heidelberg, Heidelberg; Germany. Faculty of Applied Information Science, Hiroshima Institute of Technology, Hiroshima; Japan. ( 𝑎 ) Department of Physics, Chinese University of Hong Kong, Shatin, N.T., Hong Kong; ( 𝑏 ) Departmentof Physics, University of Hong Kong, Hong Kong; ( 𝑐 ) Department of Physics and Institute for Advanced43tudy, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong; China. Department of Physics, National Tsing Hua University, Hsinchu; Taiwan. IJCLab, Université Paris-Saclay, CNRS/IN2P3, 91405, Orsay; France. Department of Physics, Indiana University, Bloomington IN; United States of America. ( 𝑎 ) INFN Gruppo Collegato di Udine, Sezione di Trieste, Udine; ( 𝑏 ) ICTP, Trieste; ( 𝑐 ) DipartimentoPolitecnico di Ingegneria e Architettura, Università di Udine, Udine; Italy. ( 𝑎 ) INFN Sezione di Lecce; ( 𝑏 ) Dipartimento di Matematica e Fisica, Università del Salento, Lecce; Italy. ( 𝑎 ) INFN Sezione di Milano; ( 𝑏 ) Dipartimento di Fisica, Università di Milano, Milano; Italy. ( 𝑎 ) INFN Sezione di Napoli; ( 𝑏 ) Dipartimento di Fisica, Università di Napoli, Napoli; Italy. ( 𝑎 ) INFN Sezione di Pavia; ( 𝑏 ) Dipartimento di Fisica, Università di Pavia, Pavia; Italy. ( 𝑎 ) INFN Sezione di Pisa; ( 𝑏 ) Dipartimento di Fisica E. Fermi, Università di Pisa, Pisa; Italy. ( 𝑎 ) INFN Sezione di Roma; ( 𝑏 ) Dipartimento di Fisica, Sapienza Università di Roma, Roma; Italy. ( 𝑎 ) INFN Sezione di Roma Tor Vergata; ( 𝑏 ) Dipartimento di Fisica, Università di Roma Tor Vergata,Roma; Italy. ( 𝑎 ) INFN Sezione di Roma Tre; ( 𝑏 ) Dipartimento di Matematica e Fisica, Università Roma Tre, Roma;Italy. ( 𝑎 ) INFN-TIFPA; ( 𝑏 ) Università degli Studi di Trento, Trento; Italy. Institut für Astro- und Teilchenphysik, Leopold-Franzens-Universität, Innsbruck; Austria. University of Iowa, Iowa City IA; United States of America. Department of Physics and Astronomy, Iowa State University, Ames IA; United States of America. Joint Institute for Nuclear Research, Dubna; Russia. ( 𝑎 ) Departamento de Engenharia Elétrica, Universidade Federal de Juiz de Fora (UFJF), Juiz deFora; ( 𝑏 ) Universidade Federal do Rio De Janeiro COPPE/EE/IF, Rio de Janeiro; ( 𝑐 ) Instituto de Física,Universidade de São Paulo, São Paulo; Brazil. KEK, High Energy Accelerator Research Organization, Tsukuba; Japan. Graduate School of Science, Kobe University, Kobe; Japan. ( 𝑎 ) AGH University of Science and Technology, Faculty of Physics and Applied Computer Science,Krakow; ( 𝑏 ) Marian Smoluchowski Institute of Physics, Jagiellonian University, Krakow; Poland. Institute of Nuclear Physics Polish Academy of Sciences, Krakow; Poland. Faculty of Science, Kyoto University, Kyoto; Japan. Kyoto University of Education, Kyoto; Japan. Research Center for Advanced Particle Physics and Department of Physics, Kyushu University, Fukuoka ;Japan. Instituto de Física La Plata, Universidad Nacional de La Plata and CONICET, La Plata; Argentina. Physics Department, Lancaster University, Lancaster; United Kingdom. Oliver Lodge Laboratory, University of Liverpool, Liverpool; United Kingdom. Department of Experimental Particle Physics, Jožef Stefan Institute and Department of Physics,University of Ljubljana, Ljubljana; Slovenia. School of Physics and Astronomy, Queen Mary University of London, London; United Kingdom. Department of Physics, Royal Holloway University of London, Egham; United Kingdom. Department of Physics and Astronomy, University College London, London; United Kingdom. Louisiana Tech University, Ruston LA; United States of America. Fysiska institutionen, Lunds universitet, Lund; Sweden. Centre de Calcul de l’Institut National de Physique Nucléaire et de Physique des Particules (IN2P3),Villeurbanne; France. Departamento de Física Teorica C-15 and CIAFF, Universidad Autónoma de Madrid, Madrid; Spain.
Institut für Physik, Universität Mainz, Mainz; Germany.44 School of Physics and Astronomy, University of Manchester, Manchester; United Kingdom.
CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille; France.
Department of Physics, University of Massachusetts, Amherst MA; United States of America.
Department of Physics, McGill University, Montreal QC; Canada.
School of Physics, University of Melbourne, Victoria; Australia.
Department of Physics, University of Michigan, Ann Arbor MI; United States of America.
Department of Physics and Astronomy, Michigan State University, East Lansing MI; United States ofAmerica.
B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk; Belarus.
Research Institute for Nuclear Problems of Byelorussian State University, Minsk; Belarus.
Group of Particle Physics, University of Montreal, Montreal QC; Canada.
P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow; Russia.
National Research Nuclear University MEPhI, Moscow; Russia.
D.V. Skobeltsyn Institute of Nuclear Physics, M.V. Lomonosov Moscow State University, Moscow;Russia.
Fakultät für Physik, Ludwig-Maximilians-Universität München, München; Germany.
Max-Planck-Institut für Physik (Werner-Heisenberg-Institut), München; Germany.
Nagasaki Institute of Applied Science, Nagasaki; Japan.
Graduate School of Science and Kobayashi-Maskawa Institute, Nagoya University, Nagoya; Japan.
Department of Physics and Astronomy, University of New Mexico, Albuquerque NM; United States ofAmerica.
Institute for Mathematics, Astrophysics and Particle Physics, Radboud University/Nikhef, Nijmegen;Netherlands.
Nikhef National Institute for Subatomic Physics and University of Amsterdam, Amsterdam;Netherlands.
Department of Physics, Northern Illinois University, DeKalb IL; United States of America. ( 𝑎 ) Budker Institute of Nuclear Physics and NSU, SB RAS, Novosibirsk; ( 𝑏 ) Novosibirsk State UniversityNovosibirsk; Russia.
Institute for High Energy Physics of the National Research Centre Kurchatov Institute, Protvino; Russia.
Institute for Theoretical and Experimental Physics named by A.I. Alikhanov of National ResearchCentre "Kurchatov Institute", Moscow; Russia.
Department of Physics, New York University, New York NY; United States of America.
Ochanomizu University, Otsuka, Bunkyo-ku, Tokyo; Japan.
Ohio State University, Columbus OH; United States of America.
Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman OK; UnitedStates of America.
Department of Physics, Oklahoma State University, Stillwater OK; United States of America.
Palacký University, RCPTM, Joint Laboratory of Optics, Olomouc; Czech Republic.
Institute for Fundamental Science, University of Oregon, Eugene, OR; United States of America.
Graduate School of Science, Osaka University, Osaka; Japan.
Department of Physics, University of Oslo, Oslo; Norway.
Department of Physics, Oxford University, Oxford; United Kingdom.
LPNHE, Sorbonne Université, Université de Paris, CNRS/IN2P3, Paris; France.
Department of Physics, University of Pennsylvania, Philadelphia PA; United States of America.
Konstantinov Nuclear Physics Institute of National Research Centre "Kurchatov Institute", PNPI, St.Petersburg; Russia.
Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh PA; United States of45merica. ( 𝑎 ) Laboratório de Instrumentação e Física Experimental de Partículas - LIP, Lisboa; ( 𝑏 ) Departamento deFísica, Faculdade de Ciências, Universidade de Lisboa, Lisboa; ( 𝑐 ) Departamento de Física, Universidadede Coimbra, Coimbra; ( 𝑑 ) Centro de Física Nuclear da Universidade de Lisboa, Lisboa; ( 𝑒 ) Departamento deFísica, Universidade do Minho, Braga; ( 𝑓 ) Departamento de Física Teórica y del Cosmos, Universidad deGranada, Granada (Spain); ( 𝑔 ) Dep Física and CEFITEC of Faculdade de Ciências e Tecnologia,Universidade Nova de Lisboa, Caparica; ( ℎ ) Instituto Superior Técnico, Universidade de Lisboa, Lisboa;Portugal.
Institute of Physics of the Czech Academy of Sciences, Prague; Czech Republic.
Czech Technical University in Prague, Prague; Czech Republic.
Charles University, Faculty of Mathematics and Physics, Prague; Czech Republic.
Particle Physics Department, Rutherford Appleton Laboratory, Didcot; United Kingdom.
IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette; France.
Santa Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz CA; UnitedStates of America. ( 𝑎 ) Departamento de Física, Pontificia Universidad Católica de Chile, Santiago; ( 𝑏 ) Universidad AndresBello, Department of Physics, Santiago; ( 𝑐 ) Instituto de Alta Investigación, Universidad deTarapacá; ( 𝑑 ) Departamento de Física, Universidad Técnica Federico Santa María, Valparaíso; Chile.
Universidade Federal de São João del Rei (UFSJ), São João del Rei; Brazil.
Department of Physics, University of Washington, Seattle WA; United States of America.
Department of Physics and Astronomy, University of Sheffield, Sheffield; United Kingdom.
Department of Physics, Shinshu University, Nagano; Japan.
Department Physik, Universität Siegen, Siegen; Germany.
Department of Physics, Simon Fraser University, Burnaby BC; Canada.
SLAC National Accelerator Laboratory, Stanford CA; United States of America.
Physics Department, Royal Institute of Technology, Stockholm; Sweden.
Departments of Physics and Astronomy, Stony Brook University, Stony Brook NY; United States ofAmerica.
Department of Physics and Astronomy, University of Sussex, Brighton; United Kingdom.
School of Physics, University of Sydney, Sydney; Australia.
Institute of Physics, Academia Sinica, Taipei; Taiwan. ( 𝑎 ) E. Andronikashvili Institute of Physics, Iv. Javakhishvili Tbilisi State University, Tbilisi; ( 𝑏 ) HighEnergy Physics Institute, Tbilisi State University, Tbilisi; Georgia.
Department of Physics, Technion, Israel Institute of Technology, Haifa; Israel.
Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv University, Tel Aviv; Israel.
Department of Physics, Aristotle University of Thessaloniki, Thessaloniki; Greece.
International Center for Elementary Particle Physics and Department of Physics, University of Tokyo,Tokyo; Japan.
Graduate School of Science and Technology, Tokyo Metropolitan University, Tokyo; Japan.
Department of Physics, Tokyo Institute of Technology, Tokyo; Japan.
Tomsk State University, Tomsk; Russia.
Department of Physics, University of Toronto, Toronto ON; Canada. ( 𝑎 ) TRIUMF, Vancouver BC; ( 𝑏 ) Department of Physics and Astronomy, York University, Toronto ON;Canada.
Division of Physics and Tomonaga Center for the History of the Universe, Faculty of Pure and AppliedSciences, University of Tsukuba, Tsukuba; Japan.
Department of Physics and Astronomy, Tufts University, Medford MA; United States of America.46 Department of Physics and Astronomy, University of California Irvine, Irvine CA; United States ofAmerica.
Department of Physics and Astronomy, University of Uppsala, Uppsala; Sweden.
Department of Physics, University of Illinois, Urbana IL; United States of America.
Instituto de Física Corpuscular (IFIC), Centro Mixto Universidad de Valencia - CSIC, Valencia; Spain.
Department of Physics, University of British Columbia, Vancouver BC; Canada.
Department of Physics and Astronomy, University of Victoria, Victoria BC; Canada.
Fakultät für Physik und Astronomie, Julius-Maximilians-Universität Würzburg, Würzburg; Germany.
Department of Physics, University of Warwick, Coventry; United Kingdom.
Waseda University, Tokyo; Japan.
Department of Particle Physics and Astrophysics, Weizmann Institute of Science, Rehovot; Israel.
Department of Physics, University of Wisconsin, Madison WI; United States of America.
Fakultät für Mathematik und Naturwissenschaften, Fachgruppe Physik, Bergische UniversitätWuppertal, Wuppertal; Germany.
Department of Physics, Yale University, New Haven CT; United States of America. 𝑎 Also at Borough of Manhattan Community College, City University of New York, New York NY; UnitedStates of America. 𝑏 Also at Center for High Energy Physics, Peking University; China. 𝑐 Also at Centro Studi e Ricerche Enrico Fermi; Italy. 𝑑 Also at CERN, Geneva; Switzerland. 𝑒 Also at CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille; France. 𝑓 Also at Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève;Switzerland. 𝑔 Also at Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona; Spain. ℎ Also at 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; UnitedStates of America. 𝑗 Also at Department of Physics and Astronomy, University of Louisville, Louisville, KY; United States ofAmerica. 𝑘 Also at Department of Physics, Ben Gurion University of the Negev, Beer Sheva; Israel. 𝑙 Also at Department of Physics, California State University, East Bay; United States of America. 𝑚 Also at Department of Physics, California State University, Fresno; United States of America. 𝑛 Also at Department of Physics, California State University, Sacramento; United States of America. 𝑜 Also at Department of Physics, King’s College London, London; United Kingdom. 𝑝 Also at Department of Physics, St. Petersburg State Polytechnical University, St. Petersburg; Russia. 𝑞 Also at Department of Physics, University of Fribourg, Fribourg; Switzerland. 𝑟 Also at Dipartimento di Matematica, Informatica e Fisica, Università di Udine, Udine; Italy. 𝑠 Also at Faculty of Physics, M.V. Lomonosov Moscow State University, Moscow; Russia. 𝑡 Also at Giresun University, Faculty of Engineering, Giresun; Turkey. 𝑢 Also at Graduate School of Science, Osaka University, Osaka; Japan. 𝑣 Also at Hellenic Open University, Patras; Greece. 𝑤 Also at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona; Spain. 𝑥 Also at Institut für Experimentalphysik, Universität Hamburg, Hamburg; Germany. 𝑦 Also at Institute for Nuclear Research and Nuclear Energy (INRNE) of the Bulgarian Academy ofSciences, Sofia; Bulgaria. 𝑧 Also at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest;Hungary. 47 𝑎 Also at Institute of Particle Physics (IPP); Canada. 𝑎𝑏 Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku; Azerbaijan. 𝑎𝑐 Also at Instituto de Fisica Teorica, IFT-UAM/CSIC, Madrid; Spain. 𝑎𝑑 Also at Istanbul University, Dept. of Physics, Istanbul; Turkey. 𝑎𝑒 Also at Joint Institute for Nuclear Research, Dubna; Russia. 𝑎 𝑓
Also at Moscow Institute of Physics and Technology State University, Dolgoprudny; Russia. 𝑎𝑔 Also at National Research Nuclear University MEPhI, Moscow; Russia. 𝑎ℎ Also at Physics Department, An-Najah National University, Nablus; Palestine. 𝑎𝑖 Also at Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg; Germany. 𝑎 𝑗
Also at The City College of New York, New York NY; United States of America. 𝑎𝑘 Also at TRIUMF, Vancouver BC; Canada. 𝑎𝑙 Also at Universita di Napoli Parthenope, Napoli; Italy. 𝑎𝑚 Also at University of Chinese Academy of Sciences (UCAS), Beijing; China. ∗∗