Search for new phenomena in events with an energetic jet and missing transverse momentum in pp collisions at \sqrt{s} = 13 TeV with the ATLAS detector
EEUROPEAN ORGANISATION FOR NUCLEAR RESEARCH (CERN)
Submitted to: Physical Review D CERN-EP-2020-238February 23, 2021
Search for new phenomena in events with anenergetic jet and missing transverse momentum in 𝒑 𝒑 collisions at √ 𝒔 =
13 TeV with the ATLAS detector
The ATLAS Collaboration
Results of a search for new physics in final states with an energetic jet and large missingtransverse momentum are reported. The search uses proton–proton collision data correspondingto an integrated luminosity of 139 fb − at a center-of-mass energy of 13 TeV collected inthe period 2015–2018 with the ATLAS detector at the Large Hadron Collider. Compared toprevious publications, in addition to an increase of almost a factor of four in the data size, theanalysis implements a number of improvements in the signal selection and the backgrounddetermination leading to enhanced sensitivity. Events are required to have at least one jet withtransverse momentum above 150 GeV and no reconstructed leptons ( 𝑒 , 𝜇 or 𝜏 ) or photons.Several signal regions are considered with increasing requirements on the missing transversemomentum starting at 200 GeV. Overall agreement is observed between the number of eventsin data and the Standard Model predictions. Model-independent 95% confidence-level limitson visible cross sections for new processes are obtained in the range between 736 fb and0.3 fb. Results are also translated into improved exclusion limits in models with pair-producedweakly interacting dark-matter candidates, large extra spatial dimensions, supersymmetricparticles in several compressed scenarios, axion-like particles, and new scalar particles indark-energy-inspired models. In addition, the data are translated into bounds on the invisiblebranching ratio of the Higgs boson. © a r X i v : . [ h e p - e x ] F e b Introduction
This paper presents the results of a new search for new phenomena in events containing an energetic jetand large missing transverse momentum p missT (with magnitude 𝐸 missT ) in proton–proton collisions at acentre-of-mass energy √ 𝑠 =
13 TeV recorded by the ATLAS detector at the Large Hadron Collider (LHC).The final-state monojet signature of at least one energetic jet, large 𝐸 missT and no leptons constitutes adistinctive signature for new physics beyond the Standard Model (SM) at colliders. This signature hasbeen extensively studied at the LHC in the context of searches for large extra spatial dimensions (LED),supersymmetry (SUSY), weakly interacting massive particles (WIMPs) as candidates for dark matter(DM) [1–5], and signals from models inspired by dark energy (DE) with new scalar particles in the finalstate [6]. In addition, experimental results have been reinterpreted in terms of new theoretical scenarioswith axion-like particles [7]. Finally, the monojet final-state results have been used to constrain the invisiblebranching fraction of the Higgs boson [8, 9]. In the following, the different models are discussed briefly.Figure 1 shows diagrams for some of the models. q g ¯ q g q Z A χ ¯ χg χ (a) qq ˜ χ ˜ χ q j ˜ q ˜ q pp (b) (c) Figure 1: (a) Diagram for the pair production of weakly interacting massive particles 𝜒 , with a mediator 𝑍 𝐴 withaxial-vector couplings exchanged in the 𝑠 -channel. (b) A generic diagram for the pair production of squarks with thedecay mode ˜ 𝑞 → 𝑞 + ˜ 𝜒 . The presence of a jet from initial-state radiation is indicated for illustration purposes. (c)Diagram for the pair production of dark-energy scalar fields 𝜑 in association with an energetic jet in the final state. The existence of a non-baryonic form of matter is well established from a number of astronomicalobservations [10–12]. The existence of a new, weakly interacting massive particle is often hypothesized [13],as it can lead to the correct relic density for nonrelativistic matter in the early universe [14] as measuredfrom data from the Planck [15] and WMAP [16] Collaborations. For WIMP masses below 1 TeV, WIMPsmay be pair-produced at the LHC. Traditionally, a monojet final state has been considered a golden channelfor the discovery of WIMPs at colliders. In this case, the WIMP pair is produced in association with a jet ofparticles from initial-state radiation, leading to the signature of a jet and missing transverse momentum (seeFigure 1(a)). Results are presented for simplified DM models [17–19] where Dirac fermion WIMPs ( 𝜒 ) arepair-produced from quarks via 𝑠 -channel exchange of a spin-1 mediator particle ( 𝑍 𝐴 ) or a spin-0 mediatorparticle ( 𝑍 𝑃 ) with axial-vector or pseudoscalar couplings, respectively. In the case of the axial-vectormediator model with couplings of the mediator to WIMPs and SM quarks set to 𝑔 𝜒 = 𝑔 𝑞 = / .
55 TeV have been already excluded at 95% confidence level (CL)for very light WIMPs in previous analyses [4].Supersymmetry is a theory of physics beyond the SM which can solve the hierarchy problem in a naturalway and can provide candidates for dark matter [20–25]. SUSY introduces a new supersymmetric partner(sparticle) for each particle in the SM. Specifically, a new scalar field is associated with each quark chiralitystate. Two squark mass eigenstates ˜ 𝑞 and ˜ 𝑞 result from the mixing of the scalar fields for a particular2avor. In supersymmetric extensions of the SM that assume R-parity conservation [26–28], sparticles areproduced in pairs and the lightest supersymmetric particle (LSP) is stable. The LSP is assumed to bethe lightest neutralino ˜ 𝜒 . The results are interpreted in terms of searches for squark production usingsimplified models in scenarios for which the mass difference Δ 𝑚 ≡ 𝑚 ˜ 𝑞 − 𝑚 ˜ 𝜒 is small (compressed-massscenario). In this case, the 𝑝 T of the resulting quark jets and the 𝐸 missT in the final state are both small,making it difficult to reconstruct the SUSY signal. The monojet signature provides unique access to thisparameter space, for which the presence of jets from initial-state radiation is used to identify signal events,leading to larger 𝐸 missT (see Figure 1(b)). In the case of bottom-squark (sbottom) and top-squark (stop) pairproduction in a compressed-mass supersymmetric scenario, squark masses below about 430 GeV havebeen already excluded at 95% CL [4].The origin of the accelerating expansion of the universe [29, 30] is, together with the nature of the darkmatter, a major open question in cosmology. The theoretical understanding of the accelerating expansionof the universe in terms of fundamental physics, beyond the ad hoc adoption of a cosmological constant ingeneral relativity, often involves the introduction of additional scalars interacting with both the gravityand matter fields [31]. Here an effective field theory implementation of the Horndeski theories [32] isconsidered [33], introducing a new dark-energy scalar field 𝜑 , governed by an effective mass 𝑀 and acoupling 𝑔 ∗ to matter, which is considered universal. For the model relevant for this case, the new scalarparticle is stable and is produced in pairs, leaving the experiment undetected. When they are produced inassociation with an energetic gluon, it leads to a monojet final-state topology (see Figure 1(c)). Previousresults [6] indicate no sensitivity for 𝑔 ∗ ≤ .
8, and values of 𝑀 below 1.2 TeV have been excluded at 95%CL for 𝑔 ∗ ≥ . 𝑂 ( ) GeV and the Planck scale 𝑀 Pl at 𝑂 ( ) GeV. In the Arkani-Hamed,Dimopoulos, and Dvali (ADD) model of LED [34], the presence of 𝑛 extra spatial dimensions of size 𝑅 leads to a fundamental Planck scale in 4 + 𝑛 dimensions given by 𝑀 Pl2 ∼ 𝑀 𝐷 + 𝑛 𝑅 𝑛 , where 𝑀 𝐷 isthe fundamental scale of the 4 + 𝑛 -dimensional theory. The extra spatial dimensions are compactified,resulting in a Kaluza–Klein tower of massive graviton modes (KK graviton). If produced in high-energyproton–proton collisions in association with a jet of hadrons, a KK graviton escaping into the extradimensions can be inferred from 𝐸 missT , and can lead to a monojet event signature. Values of 𝑀 𝐷 below7 . 𝑛 = . 𝑛 = 𝑓 𝑎 ) is considered, in which ALPsare produced in association with a gluon in a final state governed by an ALP–gluon coupling 𝑐 ∼ 𝐺 . Byconstruction, ALP decays are suppressed and the ALP leaves the detector undetected, leading to a monojetfinal-state topology.A variety of models of WIMP dark matter at the LHC involve the Higgs boson acting as a portal betweenthe dark sector and the SM sector, either via direct Yukawa couplings to fermionic dark-matter candidatesor via other mechanisms. The decay of the Higgs boson into dark-matter particles translates into a signature3f 𝐸 missT in the final state. Searches for invisible Higgs boson decays have been carried out at ATLASand CMS, considering different SM Higgs production processes and different center-of-mass energies,leading to a 95% CL upper limit on the invisible Higgs boson branching ratio of 0.26 [37] and 0.19 [38],respectively.In this publication, a data sample corresponding to a total integrated luminosity of 139 fb − is used, andthe analysis strategy closely follows that of the previous publication based on 36 . − [4]. In addition, anumber of improvements are implemented leading to enhanced sensitivity to new phenomena. The 𝑝 T requirements for identifying electrons and muons in the final state are lowered, translating into tighterlepton vetoes and a larger background reduction, which is also complemented with the inclusion of 𝜏 -leptonand photon vetoes. The kinematic range covered by the analysis is extended towards lower values of 𝐸 missT and leading-jet 𝑝 T , and new control regions are defined for a better determination of backgrounds relatedto top-quark and 𝑍 -boson production processes. Finally, the analysis profits from improved theoreticalpredictions for 𝑊 +jets and 𝑍 +jets production, including higher-order corrections at next-to-next-to-leadingorder in QCD and next-to-leading order in electroweak couplings supplemented by Sudakov logarithms attwo loops.The paper is organized as follows. The ATLAS detector is described in the next Section. Section 3 providesdetails of the Monte Carlo simulations used in the analysis for background and signal processes. Section 4discusses the reconstruction and identification of jets, leptons, and missing transverse momentum, whileSection 5 describes the event selection. The estimation of background contributions and the study ofsystematic uncertainties are discussed in Sections 6 and 7. The results are presented in Section 8 and areinterpreted in terms of limits in models of WIMP-pair production, ADD, SUSY in compressed scenarios,axion-like particles, new bosons in DE-inspired models, and limits on the Higgs boson invisible branchingfraction. Finally, Section 9 is devoted to the conclusions. The ATLAS detector [39] at the LHC covers nearly the entire solid angle around the collision point. Itconsists of an inner tracking detector surrounded by a thin superconducting solenoid, electromagneticand hadronic calorimeters, and a muon spectrometer incorporating three large superconducting toroidalmagnets.The inner-detector system is immersed in a 2 T axial magnetic field and provides charged-particle trackingin the range | 𝜂 | < .
5. The high-granularity silicon pixel detector covers the vertex region and typicallyprovides four measurements per track, the first hit normally being in the insertable B-layer installed beforeRun 2 [40, 41]. It is followed by the silicon microstrip tracker, which usually provides eight measurementsper track. These silicon detectors are complemented by the transition radiation tracker (TRT), whichenables radially extended track reconstruction up to | 𝜂 | = .
0. The TRT also provides electron identificationinformation based on the fraction of hits (typically 30 in total) above a higher energy-deposit thresholdcorresponding to transition radiation. ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP) in the center of the detectorand the 𝑧 -axis along the beam pipe. The 𝑥 -axis points from the IP to the center of the LHC ring, and the 𝑦 -axis pointsupwards. Cylindrical coordinates ( 𝑟, 𝜙 ) are used in the transverse plane, 𝜙 being the azimuthal angle around the 𝑧 -axis.The pseudorapidity is defined in terms of the polar angle 𝜃 as 𝜂 = − ln tan ( 𝜃 / ) . Angular distance is measured in units of Δ 𝑅 ≡ √︁ ( Δ 𝜂 ) + ( Δ 𝜙 ) . | 𝜂 | < .
9. Within the region | 𝜂 | < . | 𝜂 | < . | 𝜂 | < .
7, and two copper/LAr hadronic endcap calorimeters.The solid angle coverage is completed with forward copper/LAr and tungsten/LAr calorimeter modulesoptimized for electromagnetic and hadronic measurements respectively.The muon spectrometer comprises separate trigger and high-precision tracking chambers measuring thedeflection of muons in a magnetic field generated by the superconducting air-core toroids. The field integralof the toroids ranges between 2.0 and 6.0 T m across most of the detector. A set of precision chamberscovers the region | 𝜂 | < . | 𝜂 | < . Monte Carlo (MC) simulated event samples are used to compute detector acceptance and reconstructionefficiencies, determine signal and background contributions, and estimate systematic uncertainties in thefinal results. The SM background samples were processed with the full ATLAS detector simulation [43]based on Geant4 [44]. Signal simulated samples, with the exception of those for Higgs production,were processed with a fast simulation using a parameterization of the calorimeter response and Geant4for the other parts of the detector. Simulated events are then reconstructed and analyzed with the sameanalysis chain as for the data, using the same trigger and event selection criteria. The effects of multipleproton–proton interactions in the same or neighboring bunch-crossings (pileup) were taken into account byoverlaying the hard-scattering process with simulated minimum-bias events, distributed according to thefrequency in data and generated by Pythia 8.186 [45] with the A3 set of tuned parameters (tune) [46]and the NNPDF2.3LO parton distribution function (PDF) set [47]. Correction factors are applied to theMonte Carlo simulation to account for differences between simulation and the data in pileup, the energyand momentum scales, and reconstruction and identification efficiencies of physics objects.
Simulated samples for the ADD LED model with different numbers of extra dimensions in the range 𝑛 = 𝑀 𝐷 in the range 3–12 TeV were generated using Pythia 8.205 with theA14 tune [48] and NNPDF2.3LO PDFs. The cross section is computed at next-to-leading order (NLO)accuracy in the strong coupling constant. The renormalization scale was set to the geometric mean of thesquared transverse masses of the two produced particles, √︃ ( 𝑝 ,𝐺 + 𝑚 𝐺 ) ( 𝑝 , 𝑝 + 𝑚 𝑝 ) , where 𝑝 T ,𝐺 and 𝑚 𝐺 ( 𝑝 T , 𝑝 and 𝑚 𝑝 ) denote, respectively, the transverse momentum and the mass of the KK graviton (parton) in5he final state. The factorization scale was set to the smaller of the transverse masses, √︃ 𝑝 + 𝑚 , of theKK graviton and the parton.SUSY signals for squark-pair production were generated with MadGraph5_aMC@NLO v2.2.3 [49]and interfaced to Pythia 8.186 with the A14 tune for modeling of the squark decay, parton showering,hadronization, and the underlying event. The PDF set used for the generation was NNPDF23LO, andthe renormalization and factorization scales were set to 𝜇 = (cid:205) 𝑖 √︃ 𝑚 𝑖 + 𝑝 ,𝑖 , where the sum runs overall final-state particles from the hard-scatter process. The matrix-element calculation was performedat tree level, and includes the emission of up to two additional partons. Matching to parton-showercalculations was accomplished by using the CKKW-L prescription [50], with a matching scale set to onequarter of the pair-produced superpartner mass. All signal cross sections were calculated to approximatenext-to-next-to-leading order (NNLO) in the strong coupling constant, adding the resummation of softgluon emission at next-to-next-to-leading-logarithm accuracy (approximate NNLO+NNLL) [51–54]. Thenominal cross section and its uncertainty were taken from an envelope of cross-section predictions usingdifferent PDF sets and factorization and renormalization scales, as discussed in Ref. [55]. Simulated sampleswere produced with squark masses in the range between 250 GeV and 1 . Δ 𝑚 varying between 5 GeV and 50 GeV.WIMP 𝑠 -channel signal samples were simulated in Powheg-Box v2 [56–58] (revision 3049) using twoimplementations of simplified models, introduced in Ref. [59]. The DMV model of WIMP-pair productionwas used for 𝑠 -channel spin-1 axial-vector mediator exchange at NLO in the strong coupling constant, andthe DMS_tloop model was used for WIMP-pair production with 𝑠 -channel spin-0 pseudoscalar mediatorexchange with the full quark-loop calculation at leading order (LO) [60]. Renormalization and factorizationscales were set to 𝐻 T / 𝐻 T = √︃ 𝑚 𝜒𝜒 + 𝑝 , 𝑗 + 𝑝 T , 𝑗 is defined by theinvariant mass of the WIMP pair ( 𝑚 𝜒𝜒 ) and the transverse momentum of the highest- 𝑝 T parton-level jet( 𝑝 T , 𝑗 ). The mediator propagator is described by a Breit–Wigner distribution. Events were generated usingthe NNPDF30 [47] PDFs and interfaced to Pythia 8.205 with the A14 tune [48] for parton showering,hadronization and the underlying event. Couplings of the mediator to WIMP particles and those of theSM quarks were set to 𝑔 𝜒 = 𝑔 𝑞 = /
4, respectively, for the axial-vector mediator model whereasboth couplings were set to one in the case of the pseudoscalar mediator model, following the conventionsof the LHC DM Working Group [17, 18]. Each model was simulated for a range of possible WIMP andmediator masses, with WIMP masses ranging from 1 GeV to 1 TeV and mediator masses between 10 GeVand 10 TeV.Samples of simulated events for ALP production in association with a jet [36] were generated at leading-order (LO) accuracy in the strong coupling constant with MadGraph5_aMC@NLO v2.6.2 and interfacedto Pythia 8.240 with the A14 tune for modeling of parton showering, hadronization, and the underlyingevent. The PDF set used for the generation was NNPDF23LO, and the renormalization and factorizationscales were set to half of the transverse mass, 0 . × √︃ 𝑝 + 𝑚 , of the ALP and the parton. Other processesrelated to the coupling of the ALP to photons, vector bosons or the Higgs boson are suppressed. Valuesfor the ALP mass up to 𝑚 𝑎 = 𝑐 ∼ 𝐺 = 𝑓 𝑎 in the range between 1 TeV and 10 TeV are explored.Simulated events for the dark-energy model were generated using an effective field theory implementa-tion [31] in MadGraph5_aMC@NLO v2.6.1 at LO accuracy in the strong coupling constant. Followingthe work in Ref. [6], only terms corresponding to the L operator, relevant for the monojet final-statetopology, were considered, with the Wilson coefficient 𝑐 = 𝑐 𝑖 )6et to zero. Electroweak terms were vetoed and only one insertion of a L operator in each diagram wasallowed. The generated events were interfaced to Pythia 8.240 with the A14 tune for modeling of partonshowering, hadronization, and the underlying event. The PDF set used for the generation was NNPDF23LO,and the renormalization and factorization scales were set to 0 . × 𝐻 T = √︃ 𝑚 𝜑𝜑 + 𝑝 , 𝑗 + 𝑝 T , 𝑗 , where 𝑚 𝜑𝜑 is the invariant mass of the two scalar particles in the final state. The dark-energy field mass and thecoupling to gluons were set to 𝑚 𝜑 =
100 MeV and 𝑔 ∗ = 𝜋 , respectively. Effective scales 𝑀 up to 3 TeVare explored.Simulated samples for the production of a 125 GeV Higgs boson were generated, with NLO accuracy inQCD emissions, using the Powheg-Box v2 [61] event generator. The samples include gluon–gluon fusionprocesses ( 𝑔𝑔 → 𝐻 and 𝑔𝑔 → 𝑍 𝐻 ), vector-boson fusion (VBF) processes ( 𝑉𝑉 → 𝐻 ) , the associatedproduction with a 𝑊 / 𝑍 boson in the final state ( 𝑉 𝐻 ), and the associated production with a 𝑡 ¯ 𝑡 pair in the finalstate ( 𝑡 ¯ 𝑡 + 𝐻 ). The simulated events were interfaced with Pythia 8.212 for parton shower, hadronizationand underlying-event modeling using the AZNLO tune [62] with the NNPDF30+CTEQ6L1 PDF in thecase of 𝑔𝑔 → 𝐻 and 𝑔𝑔 → 𝑍 𝐻 , CT10 in the case of
𝑉 𝐻 , and NNPDF30 PDFs in the case of 𝑉𝑉 → 𝐻 and 𝑡 ¯ 𝑡 + 𝐻 processes. The 𝑔𝑔 → 𝐻 sample was normalized such that it reproduces the total cross sectionpredicted by a next-to-next-to-next-to-leading-order (NNNLO) QCD calculation with NLO electroweak(EW) corrections applied, and 𝑉𝑉 → 𝐻 and 𝑉 𝐻 processes were normalized to cross sections calculatedat NNLO in QCD with NLO EW corrections. The 𝑔𝑔 → 𝑍 𝐻 sample was normalized to cross sectionscalculated at NLO in QCD, and the 𝑡 ¯ 𝑡 + 𝐻 sample was normalized to cross sections calculated at NLO inQCD with NLO EW corrections [63]. In all cases, the Higgs boson invisible decay 𝐻 → 𝑍 ∗ 𝑍 → 𝜈 isconsidered because it provides final-state topologies consistent with those from models of new phenomenawith invisibly decaying Higgs bosons. After applying the final-state selection as described in Section 5, the primary SM background contributingto monojet event signatures is 𝑍 → 𝜈𝜈 + jets. There are also significant contributions from 𝑊 + jetsevents, primarily from 𝑊 → 𝜏𝜈 + jets, with unidentified leptons in the final state. Small contributions areexpected from 𝑍 → ℓℓ + jets ( ℓ = 𝑒, 𝜇, 𝜏 ), multijet, 𝑡 ¯ 𝑡 , single-top, and diboson ( 𝑊𝑊, 𝑊 𝑍, 𝑍 𝑍 ) processes.Contributions from top-quark production associated with additional vector bosons ( 𝑡 ¯ 𝑡 + 𝑊 , 𝑡 ¯ 𝑡 + 𝑍 , or 𝑡 + 𝑍 + 𝑞 / 𝑏 processes) are negligible and not considered in this analysis. As discussed in detail in Section 6,the contribution from SM background processes in the signal regions are determined using simulatedsamples constrained with data in control regions. In the following, the generation of the different simulationsamples is described.Events containing 𝑊 or 𝑍 bosons with associated jets were simulated using the Sherpa 2.2.1 [64] eventgenerator. Matrix elements (ME) were calculated for up to two partons at NLO and four partons at LOusing OpenLoops [65] and Comix [66], and merged with the Sherpa parton shower (PS) [67] using theME+PS@NLO prescription [68]. The NNPDF3.0NNLO [47] PDF set was used in conjunction with adedicated parton-shower tuning developed by the authors of Sherpa. The MC predictions were initiallynormalized to NNLO perturbative QCD (pQCD) predictions according to DYNNLO [69, 70] using theMSTW2008 90% CL NNLO PDF set [71].In order to improve the description of 𝑊 +jets and 𝑍 +jets processes, their MC predictions were reweighted toaccount for higher-order QCD and electroweak corrections. The reweighting procedure is based on parton-level predictions for 𝑊 / 𝑍 +jets production from Ref. [72], which include NNLO QCD corrections [73–76]7nd NLO electroweak corrections [77–80] supplemented by Sudakov logarithms at two loops [81–84].These corrections are provided separately for 𝑊 +jets, 𝑍 → ℓ + ℓ − +jets and 𝑍 → 𝜈𝜈 +jets processes, asa function of the vector-boson 𝑝 T , in order to improve the description of the measured 𝑍 -boson 𝑝 T distribution [85]. The reweighting procedure takes into account the difference between the QCD NLOpredictions as included already in Sherpa and as provided by the parton-level calculations. Uncertaintiesin these higher-order corrections and their correlations across processes are described in Section 7.Separate nonoverlapping samples for 𝑊 / 𝑍 +jets production via VBF-driven processes were generated usingHerwig++ (v7.1.3 for electron and 𝜏 -lepton decays and v7.2 for muon decays) [86]. The samples wereproduced at NLO accuracy in pQCD using VBFNLO v3.0.0 [87]. The NNPDF30 PDF set was used alongwith the default set of tuned parameters for parton showering, hadronization and the underlying event. TheEvtGen v1.2.0 program [88] was used to model the decays of the bottom and charm hadrons.For the generation of 𝑡 ¯ 𝑡 and single-top-quark events in the 𝑊𝑡 -channel and 𝑠 -channel, the Powheg-Box v2 [61] event generator was used with CT10 [89] PDFs. Electroweak 𝑡 -channel single-top-quarkevents were generated using the Powheg-Box v1 event generator. This event generator uses the four-flavorscheme to calculate NLO matrix elements, with the CT10 four-flavor PDF set. Interference occurringbeyond tree level between 𝑊𝑡 and 𝑡 ¯ 𝑡 processes was studied, considering both the diagram subtraction (DS)and diagram removal (DR) production schemes [90]; DR was used for the nominal background prediction,DS for the evaluation of systematic uncertainties as described in Section 7. The samples were normalizedto NNLO pQCD predictions. The parton shower, hadronization, and underlying event were simulated usingPythia 8.205 with the A14 tune. The top-quark mass was set to 172 . 𝑊𝑊 , 𝑊 𝑍 , and
𝑍 𝑍 production) were generated using Sherpa 2.2.1 or Sherpa 2.2.2 withNNPDF3.0NNLO, and were normalized to NLO pQCD predictions [91]. The EvtGen v1.2.0 program wasused to model the decays of the bottom and charm hadrons.
Jets are reconstructed from energy deposits in the calorimeters[92] using the anti- 𝑘 𝑡 jet algorithm [93] asprovided by the fastjet [94] toolkit, with the radius parameter 𝑅 = .
4. The measured jet four-momentumis calibrated using information from both simulation and data [95]. In addition, jets are correctedfor contributions from pileup. Jets with 𝑝 T >
20 GeV and | 𝜂 | < . | 𝜂 | < .
5) with 𝑝 T <
120 GeV a significant fraction of the tracks associated with each jet must have anorigin compatible with the primary vertex, as defined by the jet-vertex tagger.Jets with 𝑝 T >
30 GeV and | 𝜂 | < . 𝑏 -hadrons ( 𝑏 -jets) if tagged bya multivariate algorithm which uses information about the impact parameters of inner-detector tracksmatched to the jet, the presence of displaced secondary vertices, and the reconstructed flight paths of 𝑏 - and 𝑐 -hadrons inside the jet [97, 98]. A 60% efficient 𝑏 -tagging working point, as determined in a simulated8ample of 𝑡 ¯ 𝑡 events, is chosen. This corresponds to rejection factors of approximately 1500, 35 and 180 forlight-quark and gluon jets, 𝑐 -jets, and 𝜏 -leptons decaying hadronically, respectively.Electrons are found by combining energy deposits in the calorimeter with tracks found in the inner detector.They are initially required to have 𝑝 T > | 𝜂 | < .
47, and to satisfy the ‘Loose’ electron showershape and track selection criteria described in Ref. [99], including a requirement on the match between thetrack and the primary vertex, which requires the longitudinal impact parameter | 𝑧 | sin 𝜃 to be less than0.5 mm. Overlaps between identified electrons and jets with 𝑝 T >
30 GeV in the final state are resolved.Jets are discarded if they are not 𝑏 -tagged and their separation Δ 𝑅 = √︁ ( Δ 𝜂 ) + ( Δ 𝜙 ) from an identifiedelectron is less than 0 .
2. Otherwise, the electron is removed as it most likely originates from a semileptonic 𝑏 -hadron decay. The electrons separated by Δ 𝑅 between 0 . . 𝑝 T > | 𝜂 | < .
5. As in the case of electrons, the muon track is required to have | 𝑧 | sin 𝜃 < . 𝑝 T >
30 GeV and fewer than three tracks with 𝑝 T >
500 MeV associated with them are discarded iftheir separation Δ 𝑅 from an identified muon is less than 0 .
4. The muon is discarded if it is matched to ajet with 𝑝 T >
30 GeV that has at least three tracks associated with it. If an electron and a muon share thesame inner-detector track, the muon is retained and the electron is discarded in order to remove electroncandidates originating from muon bremsstrahlung followed by photon conversion.Hadronically decaying 𝜏 -lepton candidates are formed by combining information from the calorimetersand inner tracking detectors. The 𝜏 -lepton reconstruction algorithm [101] is seeded by reconstructed jetswith 𝑝 T >
10 GeV and | 𝜂 | < .
5, and the reconstructed energies of the 𝜏 -lepton candidates are corrected tothe 𝜏 -lepton energy scale [102]. They are required to pass ‘Loose’ identification requirements [103], tohave 𝑝 T >
20 GeV and | 𝜂 | < .
5, excluding the transition region between the electromagnetic barrel andendcap calorimeters (1 . < | 𝜂 | < . 𝜏 -leptonsclose to electrons or muons ( Δ 𝑅 < .
2) are removed. Any jet within Δ 𝑅 = . 𝜏 -lepton is removed.Photons are reconstructed from clusters of energy deposited in the electromagnetic calorimeter. They arerequired to pass ‘Tight’ identification requirements [99], and to have 𝑝 T >
10 GeV and | 𝜂 | < .
37. Photonsare discarded if their separation Δ 𝑅 from an identified muon or electron is less than 0 .
4. Jets are insteaddiscarded if their separation Δ 𝑅 from an identified photon is less than 0 . p missT is reconstructed from the negative vectorial sum of thetransverse momenta of electrons, muons, 𝜏 -leptons, photons, and jets with 𝑝 T >
20 GeV and | 𝜂 | < . This analysis is based on data collected by ATLAS during Run 2 of the LHC, corresponding to a totalintegrated luminosity of 139 fb − . The data were collected using a trigger based on a requirement on 𝐸 missT as computed from calorimetry information at the final stage of the two-level trigger system [105]. Afteranalysis selections, the trigger was measured to be fully efficient for events with 𝐸 missT >
200 GeV, asdetermined using a data sample with muons in the final state.9 able 1: Intervals and labels of the 𝐸 missT bins used for the signal region. Details are given in the text. Exclusive (EM) EM0 EM1 EM2 EM3 EM4 EM5 EM6 𝐸 missT [GeV] 200–250 250–300 300–350 350–400 400–500 500–600 600–700EM7 EM8 EM9 EM10 EM11 EM12700–800 800–900 900–1000 1000–1100 1100–1200 > 𝐸 missT [GeV] > > > > > > > > > > > > > Events are required to have at least one reconstructed primary vertex consistent with the beamspotenvelope and containing at least two associated tracks of 𝑝 T >
500 MeV. When more than one suchvertex is found, the vertex with the largest summed 𝑝 of the associated tracks is chosen. Events havingidentified muons, electrons, photons or 𝜏 -leptons in the final state are vetoed. Selected events have 𝐸 missT >
200 GeV, a leading jet with 𝑝 T >
150 GeV and | 𝜂 | < .
4, and up to three additional jets with 𝑝 T >
30 GeV and | 𝜂 | < .
8. Separation in the azimuthal angle of Δ 𝜙 ( jet , p missT ) > . ( . ) between themissing transverse momentum direction and each selected jet is required for events with 𝐸 missT >
250 GeV(200 GeV < 𝐸 missT ≤
250 GeV) to reduce the multijet background contribution, since large 𝐸 missT canoriginate from jet energy mismeasurement. Jet quality criteria [106] are imposed, which involve selectionsbased on quantities such as the pulse shape of the energy depositions measured in the cells of thecalorimeters, electromagnetic energy fraction in the calorimeter, maximum fraction of the jet energycollected by a single calorimeter layer, and the charged-particle fraction. Loose selection criteria areapplied to all jets with 𝑝 T >
30 GeV and | 𝜂 | < .
8, which remove anomalous energy depositions due tocoherent noise and electronic noise bursts in the calorimeter [107]. Events with any jet not satisfying theloose criteria [106] are discarded.Noncollision backgrounds, for example energy depositions in the calorimeters due to muons of beam-induced or cosmic-ray origin, are suppressed by imposing tight selection criteria on the leading jet: theratio of the jet charged-particle fraction to the maximum fraction of the jet energy collected by a singlecalorimeter layer, 𝑓 ch / 𝑓 max , is required to be larger than 0 .
1. Jet quality requirements altogether have anegligible effect on the signal efficiency.The signal region (SR) is divided into different bins of 𝐸 missT , which are listed in Table 1. Inclusive bins areused for a model-independent interpretation of search results, while the full set of exclusive bins are usedfor the interpretation within different models of new physics. A semi-data-driven technique, supported by statistically independent control regions, is used to constrainthe normalization of Standard Model backgrounds. The approach followed is similar to the one used inprevious versions of the analysis [4]. The charged-particle fraction is defined as 𝑓 ch = (cid:205) 𝑝 track,jetT / 𝑝 jetT , where (cid:205) 𝑝 track,jetT is the scalar sum of the transverse momentaof tracks associated with the primary vertex within a cone of size Δ 𝑅 = . 𝑝 jetT is the transversemomentum of the jet as determined from calorimetric measurements. .1 Control regions The estimation of the 𝑍 + jets, 𝑊 + jets, 𝑡 ¯ 𝑡 , and single- 𝑡 backgrounds is performed using five control regions,as described below. These regions are defined in a way similar to the SR: events are selected in terms of aquantity which is – similarly to p missT in the SR – a proxy for the transverse momentum of the system whichrecoils against the hadronic activity in the event. This quantity is denoted in the following by p recoilT , and itsmagnitude by 𝑝 recoilT . The same selection criteria for jet multiplicity and leading jet 𝑝 T as in the SR areapplied in the control regions, with the same requirements on the azimuthal separation of jets from p recoilT .Control regions are binned in terms of 𝑝 recoilT , using the same binning as in the signal region (see Table 1).In the signal region, 𝑝 recoilT is equivalent to 𝐸 missT .A control region enriched in 𝑊 → 𝜇𝜈 events is defined by selecting events that pass the same triggerrequirements as in the signal region, if they have exactly one reconstructed muon and this muon has 𝑝 T >
10 GeV and passes the requirement on the transverse impact parameter significance, 𝑑 / 𝜎 ( 𝑑 ) , tobe less than 3, and if no electrons, 𝜏 -leptons, photons or 𝑏 -jets are reconstructed. In this region, 𝑝 recoilT isdefined as the magnitude of the vector sum of the missing transverse momentum and the muon transversemomentum, | p missT + p T ( 𝜇 )| , and is required to be higher than 200 GeV. An additional requirement on thetransverse mass is applied, 30 GeV < 𝑚 T <
100 GeV, where 𝑚 T = √︁ 𝑝 T ( 𝜇 ) 𝑝 T ( 𝜈 ) [ − cos ( Δ 𝜙 ( 𝜇, 𝜈 ))] and the neutrino transverse momentum, p T ( 𝜈 ) , is taken to be the same as p missT .Similarly, a control region enriched in 𝑍 → 𝜇𝜇 events is defined by selecting events that pass the sametrigger requirements but have exactly two reconstructed muons, where these muons have 𝑝 T >
10 GeV and 𝑑 / 𝜎 ( 𝑑 ) <
3, and the invariant mass of the dimuon system is between 66 and 116 GeV. In this region, 𝑝 recoilT is defined as the magnitude of the vector sum of the missing transverse momentum and the transversemomentum of the dimuon system, | p missT + p T ( 𝜇𝜇 )| , and is required to be higher than 200 GeV. The triggerrequirements used for these two regions do not include muon information in the calculation of 𝐸 missT , andare fully efficient for events satisfying the selection criteria.A control region enriched in 𝑊 → 𝑒𝜈 events is defined by selecting events that pass single-electrontriggers, if they have exactly one reconstructed electron and this electron satisfies tight identification criteriadescribed in Ref. [103], is reconstructed outside the transition region between the electromagnetic barreland endcap calorimeters, has 𝑝 T >
30 GeV and 𝑑 / 𝜎 ( 𝑑 ) <
5, and passes the tight isolation requirementsbased on information from the electromagnetic calorimeter and from tracking detectors, described inRef. [99]. In this region, 𝑝 recoilT is defined as the magnitude of the vector sum of the missing transversemomentum and the electron transverse momentum, | p missT + p T ( 𝑒 )| , and is required to be higher than200 GeV. The transverse mass is required to be 30 GeV < 𝑚 T <
100 GeV. In order to further suppressbackgrounds from multijet processes with jets misidentified as high- 𝑝 T electrons, the events are requiredto have 𝐸 missT >
70 GeV and 𝐸 missT /√ 𝐻 T > / , where 𝐻 T denotes the scalar sum of the 𝑝 T of theidentified jets in the final state.Similarly, a control region enriched in 𝑍 → 𝑒𝑒 events is defined by selecting events with exactly tworeconstructed electrons, where these electrons have 𝑝 T >
30 GeV and 𝑑 / 𝜎 ( 𝑑 ) <
5, and the invariant massof the dielectron system is between 66 and 116 GeV. In this region, 𝑝 recoilT is defined as the magnitude ofthe vector sum of the missing transverse momentum and the transverse momentum of the dielectron system, | p missT + p T ( 𝑒𝑒 )| , and is required to be higher than 200 GeV. The single-electron trigger requirements arefully efficient for events satisfying the selection criteria for these two regions.A control region enriched in 𝑡 ¯ 𝑡 and single- 𝑡 events is defined by selecting events which pass the same cutsas for the 𝑊 → 𝜇𝜈 and 𝑊 → 𝑒𝜈 regions, but which have at least one identified 𝑏 -jet.11 able 2: Event selection criteria for the signal and control regions. Reconstructed objects are defined as explained inSection 4. Requirement SR 𝑾 → 𝝁𝝂 𝒁 → 𝝁𝝁 𝑾 → 𝒆𝝂 𝒁 → 𝒆𝒆 Top
Primary vertex at least one with ≥ 𝑝 T >
500 MeVTrigger 𝐸 missT single-electron 𝐸 missT ,single-electron 𝑝 recoilT cut 𝐸 missT >
200 GeV | p missT + p T ( 𝜇 )| >
200 GeV | p missT + p T ( 𝜇𝜇 )| >
200 GeV | p missT + p T ( 𝑒 )| >
200 GeV | p missT + p T ( 𝑒𝑒 )| >
200 GeV | p missT + p T ( 𝜇 )| >
200 GeV or | p missT + p T ( 𝑒 )| >
200 GeVJets up to 4 with 𝑝 T >
30 GeV , | 𝜂 | < . | Δ 𝜙 ( jets, p recoilT )| > . > . < 𝐸 missT ≤
250 GeV)Leading jet 𝑝 T >
150 GeV , | 𝜂 | < . , 𝑓 ch / 𝑓 max > . 𝑏 -jets any none any none any at least oneElectrons or muons none exactly onemuon, with 𝑝 T >
10 GeV,30 < 𝑚 T <
100 GeV; noelectron exactly twomuons, with 𝑝 T >
10 GeV,66 <𝑚 𝜇𝜇 <
116 GeV; noelectron exactly oneelectron,tight, with 𝑝 T >
30 GeV, | 𝜂 | ∉ ( . , . ) ,tightisolation,30 < 𝑚 T <
100 GeV; nomuon exactly twoelectrons,with 𝑝 T >
30 GeV,66 < 𝑚 𝑒𝑒 <
116 GeV; nomuon same as for 𝑊 → 𝜇𝜈 orsame as for 𝑊 → 𝑒𝜈𝜏 -leptons nonePhotons none Table 2 shows a summary of the selection criteria for all regions.
The multijet background with large 𝐸 missT originates mainly from the misreconstruction of the energy ofa jet in the calorimeter and, to a lesser extent, is due to the presence of neutrinos in the final state fromheavy-flavor hadron decays. In this analysis, the multijet background is determined from data, using the jetsmearing method as described in Ref. [108]. It relies on the assumption that the 𝐸 missT value of multijetevents is dominated by fluctuations in the jet response in the detector, which can be measured in the data.The method was checked using a validation region where events were selected as in the signal region,except for a modified requirement that the minimum azimuthal distance between a jet and p missT is between0.3 and 0.4. After event selection, the multijet background is estimated to be about 1 . . .
4% and0 .
3% of the total background in the exclusive signal region bins EM0, EM1, EM2 and EM3, respectively,12nd it is less than 0 .
1% for the other signal region bins. A conservative 100% uncertainty is assigned to thenormalization of this background.
After event selections are applied, the signal region may contain residual contributions from noncollisionbackgrounds. These backgrounds, which are not included in simulation, mainly arise when beam-haloprotons intercept the LHC collimators, leading to particle cascades which produce muons. The remainingcontributions are estimated following the methods set out in Ref. [107]. In particular, the jet timing, 𝑡 𝑗 ,calculated from the energy-weighted average of the time of the jet energy deposits, defined relative tothe event time in nominal collisions, is used. A dedicated region enhanced in beam-induced background,defined by inverting the tight jet-quality selection imposed on the leading jet, is used to estimate theamount of non-collision background from the fraction of events with a leading-jet timing | 𝑡 𝑗 | > The estimation of backgrounds in the SR is based on a simultaneous, binned likelihood fit to the 𝑝 recoilT distribution of the five control regions described in Section 6.1. The number of events in each region andin each bin is treated as a random variable with a Poisson distribution function, with an expectation valuegiven by the sum of the SM predictions for each background in that bin. The likelihood fit is based on theprofile likelihood method [109]. Systematic uncertainties are represented by Gaussian-distributed nuisanceparameters, and take into account the correlation among systematic variations and across 𝑝 recoilT bins.The normalization of all 𝑊 + jets and 𝑍 + jets processes, excluding those initiated by VBF, is multiplied bya common single floating normalization factor, which is the same across all 𝑝 recoilT bins. As a result, datafrom both 𝑊 and 𝑍 control regions are used simultaneously to constrain the 𝑍 → 𝜈𝜈 background in thesignal region. Systematic uncertainties in 𝑊 + jets and 𝑍 + jets event yields, as described in Section 7, coverthe residual bin-by-bin differences among processes when higher-order calculations are included, takinginto account the correlation of theoretical uncertainties across different processes with the calculationprovided in Ref. [72]. Similarly, one floating normalization factor is used for each of the 𝑡 ¯ 𝑡 and single- 𝑡 backgrounds, resulting in a total of three floating background normalization factors in the fit. Comparedto the previous version of the analysis, the usage of two independent normalization factors for the twomain sources of top-quark backgrounds is introduced to better take into account their different expectedcontribution as a function of 𝑝 recoilT .Table 3 shows the results of the background-only fit to the control regions, when all exclusive bins arefitted simultaneously. As determined in the signal region, the normalizations of the 𝑊 + jets and 𝑍 + jetsbackgrounds get corrected by a multiplicative factor of 1 . ± .
01, while the normalization of the 𝑡 ¯ 𝑡 andsingle- 𝑡 backgrounds gets corrected by a multiplicative factor of 0 . ± . . ± .
4, respectively.Figures 2 and 3 show the expected and observed distributions of the 𝑝 recoilT in the control regions. Theshown expected distributions include the data-driven normalization factors as extracted from the binnedlikelihood fit to the different exclusive 𝑝 recoilT bins in the control regions. Good agreement is observed,within statistical and systematic uncertainties, with data. As an illustration, 𝜒 -statistical tests, using thebinned profile likelihood fit described above, probing potential shape discrepancies between the observed13 able 3: Data and expected events with 𝑝 recoilT >
200 GeV in the five control regions (top: post-fit, bottom: pre-fit).The post-fit predictions for the SM backgrounds are obtained after the simultaneous binned likelihood fit to the fivecontrol regions, performed in the exclusive bins of 𝑝 recoilT (EM0–EM12). The background predictions include boththe statistical and systematic uncertainties. The individual uncertainties are correlated, and do not necessarily add inquadrature to equal the total background uncertainty. The dash “–” denotes contributions of less than 0 .
01% to thetotal background. p recoilT >
200 GeV 𝑊 → 𝜇𝜈 𝑊 → 𝑒𝜈 Top 𝑍 → 𝜇𝜇 𝑍 → 𝑒𝑒 Data events (139 fb − ) 1 364 958 699 674 225 606 196 800 145 531SM prediction (post-fit) 1 364 800 ± ± ± ±
600 145 500 ± 𝑊 → 𝑒𝜈 – 578 800 ± ±
900 – –Fitted 𝑊 → 𝜇𝜈 ± ± 𝑊 → 𝜏𝜈
71 500 ±
800 45 200 ±
500 3380 ±
180 – –Fitted VBF 𝑊 + jets 26 200 ± ± ±
340 – –Fitted 𝑍 → 𝑒𝑒 – – – – 138 100 ± 𝑍 → 𝜇𝜇
21 500 ±
500 – 778 ±
20 185 200 ±
900 –Fitted 𝑍 → 𝜏𝜏 – 1900 ±
50 – – –Fitted 𝑍 → 𝜈𝜈 – – – – –Fitted VBF 𝑍 + jets – – – 3300 ±
400 2530 ± 𝑡
22 000 ± ± ±
10 000 350 ±
170 110 ± 𝑡 ¯ 𝑡
52 000 ± ± ± ±
400 1790 ± ± ± ±
340 4000 ±
700 2900 ± ±
60 000 623 000 ±
32 000 233 000 ±
31 000 175 000 ± ± 𝑊 → 𝑒𝜈 – 509 000 ±
27 000 14 200 ± 𝑊 → 𝜇𝜈 ±
50 000 – 28 000 ± 𝑊 → 𝜏𝜈
63 000 ± ± ±
250 – –Fit input VBF 𝑊 + jets 22 000 ± ± ±
500 – –Fit input 𝑍 → 𝑒𝑒 – – – – 120 000 ± 𝑍 → 𝜇𝜇
18 900 ± ±
23 163 000 ± 𝑍 → 𝜏𝜏 – 1680 ±
60 – – –Fit input 𝑍 → 𝜈𝜈 – – – – –Fit input VBF 𝑍 + jets – – – 2700 ±
500 2000 ± 𝑡
16 000 ± ± ±
13 000 700 ±
500 280 ± 𝑡 ¯ 𝑡
60 000 ± ± ±
27 000 4600 ± ± ± ± ±
400 4100 ±
800 3000 ± and predicted 𝑝 recoilT distributions, give 𝑝 -values in a range from 0.49 (in the 𝑊 → 𝜇𝜈 control region) to0.96 (in the top-quark control region).In order to perform model-independent tests for new physics processes, discussed in Section 8.1, the samefit procedure is repeated in each of the inclusive bins of 𝑝 recoilT for signal and control regions, denotedin Table 1 by IM0–IM12. Since in this case no shape information is available to constrain the separatecontributions of 𝑡 ¯ 𝑡 and single- 𝑡 , a single normalization factor is used for all top-quark-related processes,along with the normalization factor for 𝑊 / 𝑍 +jets, resulting in two free background normalization factorsin the fit. Additionally, the nuisance parameters related to systematic uncertainties refer to the given 𝐸 missT inclusive region. A total of 13 separate fits are therefore performed, based on five control regions each andincluding two free background normalization factors. The results are expected to differ from those of thesimultaneous fit to exclusive bins, due to the lack of 𝑝 recoilT shape information to constrain uncertainties and14
00 400 600 800 1000 1200 -
10 110 E v en t s / G e V ATLAS -1 = 13 TeV, 139 fbs ) Control Region nm fi W( ) > 150 GeV (j T p DataStandard Model w. unc.) + jets n l fi W( ) + jets n l fi VBF W( + single topttDiboson ll) + jets fi Z(
200 400 600 800 1000 1200 [GeV] recoilT p0.80.911.11.2 D a t a / S M Total Uncertainty (a)
200 400 600 800 1000 1200 -
10 110 E v en t s / G e V ATLAS -1 = 13 TeV, 139 fbs ) Control Region n e fi W( ) > 150 GeV (j T p DataStandard Model w. unc.) + jets n l fi W( ) + jets n l fi VBF W( + single topttDiboson ll) + jets fi Z(
200 400 600 800 1000 1200 [GeV] recoilT p0.80.911.11.2 D a t a / S M Total Uncertainty (b)
200 400 600 800 1000 1200 -
10 110 E v en t s / G e V ATLAS -1 = 13 TeV, 139 fbsTop Control Region) > 150 GeV (j T p DataStandard Model w. unc.) + jets n l fi W( ) + jets n l fi VBF W( + single topttDiboson ll) + jets fi Z(
200 400 600 800 1000 1200 [GeV] recoilT p0.80.911.11.2 D a t a / S M Total Uncertainty (c)
Figure 2: The measured 𝑝 recoilT distributions in the (a) 𝑊 → 𝜇𝜈 , (b) 𝑊 → 𝑒𝜈 and (c) top control regions, comparedwith the background predictions as estimated after the simultaneous, binned background-only fit to the data in thecontrol regions. The ratios of data to SM predictions after the CR fit are shown in the lower panels (black dots). Theerror bands in the ratios include the statistical and systematic uncertainties in the background predictions. Eventswith values beyond the range of the histogram are included in the last bin. the normalization of backgrounds. The impact of systematic uncertainties is estimated after performing a background-only fit to data from theexclusive CRs, and evaluating the impact of the uncertainty in the total background yield in each bin of 𝑝 recoilT in the SR. The dominant sources of experimental uncertainty are those related to the electron, muonand jet identification and reconstruction efficiencies, while uncertainties in the 𝑉 + jets predictions give theleading contribution to theory uncertainties. More details are provided in the following sections.15
00 400 600 800 1000 1200 -
10 110 E v en t s / G e V ATLAS -1 = 13 TeV, 139 fbs ) Control Region mm fi Z( ) > 150 GeV (j T p DataStandard Model w. unc. ll) + jets fi Z( ) + jets nn ll / fi VBF Z(Diboson + single toptt
200 400 600 800 1000 1200 [GeV] recoilT p0.80.911.11.2 D a t a / S M Total Uncertainty (a)
200 400 600 800 1000 1200 -
10 110 E v en t s / G e V ATLAS -1 = 13 TeV, 139 fbs ee) Control Region fi Z( ) > 150 GeV (j T p DataStandard Model w. unc. ll) + jets fi Z( ) + jets nn ll / fi VBF Z(Diboson + single toptt
200 400 600 800 1000 1200 [GeV] recoilT p0.80.911.11.2 D a t a / S M Total Uncertainty (b)
Figure 3: The measured 𝑝 recoilT distributions in the (a) 𝑍 → 𝜇𝜇 and (b) 𝑍 → 𝑒𝑒 control regions, compared with thebackground predictions as estimated after the simultaneous, binned background-only fit to the data in the controlregions. The ratios of data to SM predictions after the CR fit are shown in the lower panels (black dots). The errorbands in the ratios include the statistical and systematic uncertainties in the background predictions. Events withvalues beyond the range of the histogram are included in the last bin. The red arrow marker in the ratio panel indicatesthe point falls beyond the vertical axis range of the plot. The uncertainty in the combined 2015–2018 integrated luminosity is 1.7%. It is derived from the calibrationof the luminosity scale using 𝑥 – 𝑦 beam-separation scans, following a methodology similar to that describedin Ref. [110], and using the LUCID-2 detector for the baseline luminosity measurements [111]. Thisuncertainty nearly cancels out in the semi-data-driven background estimation procedure, and translates intoa residual uncertainty in the total background in the SR of less than 0 .
01% (0 . 𝑝 recoilT =
200 GeV(1200 GeV). The uncertainty in the pileup reweighting procedure translates into a residual uncertainty inthe total background in the SR of less than 0 .
4% (0 . 𝑝 recoilT =
200 GeV (1200 GeV).Systematic uncertainties in the jet energy scale (resolution) [95] translate into uncertainties in the totalbackground in the SR which vary between 0 .
17% (0 . ) and 1 .
0% (1 . 𝑝 recoilT between 200 GeVand 1200 GeV. The uncertainty in the modeling of the JVT requirement used to reject jets coming frompileup [112] is below 0 .
03% across the 𝑝 recoilT spectrum. Uncertainties in the flavor-tagging efficiency [113]translate into uncertainties in the total background in the SR between 0 .
1% and 0 .
9% for 𝑝 recoilT between200 GeV and 1200 GeV.Uncertainties in the 𝐸 missT scale (resolution) due to soft contributions to the 𝐸 missT calculation translateinto uncertainties in the total background in the SR between 0 .
5% (0 . .
25% (0 . 𝑝 recoilT between 200 GeV and 1200 GeV.Uncertainties in the electron reconstruction and identification efficiencies are computed following themethod described in Ref. [99]; the latter are treated as uncorrelated between selected and vetoed electrons,since different working points are used for their identification, as described in Section 5. Uncertaintiesin the electron and photon energy scale and resolution are computed following the method described inRef. [114]. Overall, they translate into uncertainties in the total background in the SR between 0 .
7% and1 .
3% for 𝑝 recoilT between 200 GeV and 1200 GeV. Uncertainties due to the electron isolation efficiency16ive a contribution of less than 0 .
2% across the 𝑝 recoilT spectrum. Negligible contributions are givenby the electron trigger efficiency and by the photon identification efficiency. Uncertainties in the muonreconstruction and identification efficiencies and in their momentum measurement are computed followingthe method described in Ref. [100]. In order to take into account the difference between the simulatedand measured identification efficiencies for muons with 𝑝 T above 300 GeV, an additional uncertainty isincluded, conservatively taken as uncorrelated in muon 𝑝 T and 𝜂 . Overall, these translate into uncertaintiesin the total background in the SR between 0 .
4% and 1 .
9% for 𝑝 recoilT between 200 GeV and 1200 GeV.Uncertainties in the 𝜏 -lepton reconstruction and identification efficiencies translate into uncertainties in thetotal background in the SR of 0 .
1% (0 . 𝑝 recoilT =
200 GeV ( > 𝑉 + jets processes not initiated by VBF are calculated following the procedure described inRef. [72]. They are provided in the form of event weights parameterized as a function of vector-boson 𝑝 T ,which are applied to derive shape and normalization uncertainties for simulated 𝑉 + jets processes in signaland control regions. The correlations across 𝑝 recoilT bins are implemented as recommended in Ref. [72].The correlations across processes are implemented as follows.Three sources of pure QCD uncertainties are considered. The uncertainty associated with the truncation ofthe perturbative expansion in the strong coupling constant is estimated by varying the QCD renormalizationand factorization scales both individually and simultaneously by factors 2 and 0.5, and evaluating thechange in differential cross section in bins of the vector-boson 𝑝 T for these seven combinations. The centerof the resulting band is taken as the nominal estimate, and its half width is taken as its systematic uncertainty.Uncertainties in the shape of the vector-boson 𝑝 T distribution, which are relevant for the extrapolation oflow- 𝑝 T measurements to high 𝑝 T , are taken into account by applying an additional uncertainty estimatedfrom a conservative shape distortion of the aforementioned scale uncertainty. These two uncertaintiesare represented by two nuisance parameters, 𝛿 ( ) 𝐾 NNLO and 𝛿 ( ) 𝐾 NNLO , which are taken as correlatedacross 𝑉 + jets processes, assuming that for 𝑝 recoilT (cid:29) 𝑚 𝑊 ,𝑍 the QCD effects on the 𝑊 + jets and 𝑍 + jetspredictions are very similar. Residual differences in QCD corrections between 𝑊 + jets and 𝑍 + jetsprocesses are estimated from the difference in QCD NNLO 𝑘 -factors with respect to 𝑍 + jets production,and taken into account as an additional nuisance parameter, 𝛿 ( ) 𝐾 NNLO .Three sources of pure EW uncertainties and one source of mixed QCD–EW uncertainties are considered.Unknown Sudakov logarithms beyond NNLO are considered as the dominant source of uncertaintyat high 𝑝 T , and are treated as correlated across 𝑉 + jets processes and represented by one nuisanceparameter, 𝛿 ( ) 𝜅 nNLO EW . An additional source of uncertainty is considered to cover possible NNLO effectsnot included in the calculation, conservatively defined as 5% of the absolute full NLO EW correction,and is treated as uncorrelated across 𝑉 + jets processes and hence represented by the three nuisanceparameters 𝛿 ( ) 𝜅 ( 𝑊 ) nNLO EW , 𝛿 ( ) 𝜅 ( 𝑍 → ℓ + ℓ − ) nNLO EW , and 𝛿 ( ) 𝜅 ( 𝑍 → 𝜈𝜈 ) nNLO EW . The uncertainty in the limitations of theSudakov approximation at two loops is estimated as the difference between the NLL Sudakov approximationand the exponentiation of the full NLO EW correction, and is treated as uncorrelated between 𝑊 + jets and 𝑍 + jets processes, resulting in two nuisance parameters, 𝛿 ( ) 𝜅 ( 𝑊 ) nNLO EW and 𝛿 ( ) 𝜅 ( 𝑍 ) nNLO EW . Uncertaintiesdue to the approximation of mixed QCD–EW corrections via a factorized combination of QCD andEW corrections are assumed to be proportional to the difference between the additive and multiplicativecombination of QCD and EW corrections, and are treated as correlated across 𝑉 + jets processes, resultingin a single nuisance parameter, 𝛿𝐾 NNLO mix . This distortion is parameterized as a function of the vector-boson 𝑝 T between 200 GeV and 2 TeV and has the form ( 𝑝 − 𝑝 , )/( 𝑝 + 𝑝 , ) , where 𝑝 T , =
650 GeV. able 4: Uncertainties considered in the reweighting of 𝑉 + jets samples to higher-order QCD and EW parton-levelcalculations. For reference, the correspondence with the nuisance parameters included in Table 3 from Ref. [72] isalso indicated. Source of uncertainty Correlation Nuisance parameter name(s) in Ref. [72]
Truncation of perturbative expan-sion in 𝛼 s Correlated across 𝑝 recoilT bins and 𝑉 + jets processes 𝛿 ( ) 𝐾 NNLO
Shape of the vector-boson dis-tribution and extrapolation fromlow 𝑝 T to high 𝑝 T Correlated across 𝑝 recoilT bins and 𝑉 + jets processes 𝛿 ( ) 𝐾 NNLO
Difference in QCD correctionsbetween 𝑊 + jets and 𝑍 + jets Correlated across 𝑝 recoilT bins and 𝑉 + jets processes 𝛿 ( ) 𝐾 NNLO
Unknown Sudakov logarithmsbeyond NNLO Correlated across 𝑝 recoilT bins and 𝑉 + jets processes 𝛿 ( ) 𝜅 nNLO EW Additional possible NNLO ef-fects Correlated across 𝑝 recoilT bins, un-correlated between 𝑉 + jets pro-cesses 𝛿 ( ) 𝜅 ( 𝑊 ) nNLO EW , 𝛿 ( ) 𝜅 ( 𝑍 → ℓ + ℓ − ) nNLO EW , 𝛿 ( ) 𝜅 ( 𝑍 → 𝜈𝜈 ) nNLO EW Limitations of the Sudakov ap-proximation at two loops Correlated across 𝑝 recoilT bins, un-correlated between 𝑊 + jets and 𝑍 + jets processes 𝛿 ( ) 𝜅 ( 𝑊 ) nNLO EW , 𝛿 ( ) 𝜅 ( 𝑍 ) nNLO EW Interference terms between QCDand EW corrections Correlated across 𝑝 recoilT bins and 𝑉 + jets processes 𝛿𝐾 NNLO mix
PDF uncertainties Correlated across 𝑝 recoilT bins and 𝑉 + jets processes sum in quadrature of 𝛿𝐾 ( 𝑖 ) PDF
Different definition of 𝜏 -leptonsbetween parton-level calculationand simulation Correlated across 𝑝 recoilT bins and 𝑉 + jets processes – Uncertainties in the parton distribution functions are treated as correlated across 𝑉 + jets processes, followingthe prescription of Ref. [72]. They are estimated by the sum in quadrature over the 107 independent HessianPDF replicas provided by the PDF set LUXqed_plus_PDF4LHC15_nnlo , following Eq. (20) of Ref. [115].The resulting nuisance parameter is denoted by 𝛿𝐾 PDF .Table 4 summarizes the considered nuisance parameters and their assumed correlations. Before theCR-only fit, the leading impacts on the signal region background prediction for the EM0 selection comefrom 𝛿 ( ) 𝐾 NNLO (1 . 𝛿 ( ) 𝐾 NNLO (1 . 𝛿𝐾 PDF (0 . 𝛿𝐾 PDF (2 . 𝛿 ( ) 𝐾 NNLO (2 . 𝛿 ( ) 𝜅 ( 𝑍 ) nNLO EW (1 . 𝛿 ( ) 𝐾 NNLO (1 . .
4% and 2% for 𝑝 recoilT between 200 GeV and 1200 GeV, dominated by QCD uncertainties at low 𝑝 recoilT and by EW uncertainties at high 𝑝 recoilT . The leading contributions for the EM0 selection are givenby 𝛿 ( ) 𝐾 NNLO (0 . 𝛿 ( ) 𝐾 NNLO (0 . 𝛿 ( ) 𝜅 ( 𝑍 → 𝜈𝜈 ) nNLO EW (0 . 𝛿 ( ) 𝜅 ( 𝑍 ) nNLO EW (1 . 𝛿 ( ) 𝜅 ( 𝑍 → 𝜈𝜈 ) nNLO EW (1 . 𝛿 ( ) 𝜅 ( 𝑊 ) nNLO EW (1 . 𝜏 -leptons at Monte Carlo generator level and the one used in the theoretical calculation from Ref. [72],which translates into uncertainties in the total background in the SR between 0 .
05% and 0 .
1% for 𝑝 recoilT between 200 GeV and 1200 GeV.Uncertainties in the 𝑉 + jets processes initiated by VBF include scale and PDF uncertainties and thecomparison with Sherpa as an alternative MC generator. They translate into uncertainties in the total18 able 5: Summary of the impact at low and high 𝑝 recoilT of systematic uncertainties on the total background in theSR, as obtained from the CR-only fit. The impact of each source of systematic uncertainty is shown as the sum inquadrature of the individual contributions represented by the corresponding nuisance parameters. The two reportedvalues refer to the first and last bin of 𝑝 recoilT (EM0 and EM12). Only non-negligible contributions are shown.Source of uncertainty and effect on the total SR background estimate [%]Flavor tagging 0.1 − 𝜏 -lepton identification efficiency 0.1 − − − − − − − − − 𝐸 missT resolution 0.34 − − 𝐸 missT scale 0.5 − 𝑡 ¯ 𝑡 theory 0.06 − − 𝑉 +jets 𝜏 -lepton definition 0.04 − − 𝑉 +jets pure QCD corrections 0.24 − − 𝑉 +jets pure EW corrections 0.17 − − 𝑉 +jets mixed QCD–EW corrections 0.02 − − 𝑉 +jets PDF 0.01 − − 𝑉 +jets backgrounds 0.02 − − − − background in the SR between 0 . .
1% for 𝑝 recoilT between 200 GeV and 900 GeV, and between0 .
2% and 1 .
1% for 𝑝 recoilT between 1000 GeV and 1200 GeV.Uncertainties in the theoretical predictions of the 𝑡 ¯ 𝑡 and single- 𝑡 backgrounds are estimated for the twoprocesses separately by varying parton-shower parameters and the amount of initial- and final-state softgluon radiation, by comparing predictions from different MC event generators [116] and by comparingthe degree of interference between single- 𝑡 in the 𝑊𝑡 -channel and 𝑡 ¯ 𝑡 when using the DR and DS schemesdescribed in Ref. [117]. In the case of 𝑡 ¯ 𝑡 (single- 𝑡 ), they translate into uncertainties in the total backgroundin the SR between 0 .
06% (0 . .
7% (0 . 𝑝 recoilT between 200 GeV and 1200 GeV.Uncertainties in the theoretical predictions of diboson backgrounds include uncertainties in the QCDrenormalization, factorization and resummation scales, uncertainties due to the choice of parton distributionfunctions and uncertainties in the modeling of the parton showers. They translate into uncertainties in thetotal background in the SR between 0 .
01% and 0 .
22% for 𝑝 recoilT between 200 GeV and 1200 GeV.Uncertainties in the multijet and noncollision backgrounds translate into uncertainties in the total backgroundin the SR for 𝑝 recoilT =
200 GeV of 1% and 0 . 𝑝 recoilT in the SR, asestimated from the CR-only fit. Sources of systematic uncertainty in the predicted signal yields are considered separately for each model ofnew physics, using a common set of procedures. Experimental uncertainties include those related to thejet and 𝐸 missT reconstruction, energy scales and resolutions, which introduce uncertainties in the signal19ields for the different models that vary in the range between 1% and 3% at low 𝑝 recoilT , and between 4%and 7% at large 𝑝 recoilT , depending on the parameters of the model. The 1.7% uncertainty in the integratedluminosity is also included. Other uncertainties related to the jet quality requirements are negligible.Uncertainties affecting the signal acceptance in the generation of signal samples include: uncertainties inthe modeling of the initial- and final-state radiation and the underlying event, determined using simulatedsamples with modified parton-shower parameters (by factors of two or one half); uncertainties due toPDFs and variations of the 𝛼 s ( 𝑚 𝑍 ) value employed, as computed from the envelope of CT10 or CT14,MMHT2014 [118] and NNPDF30 error sets; and uncertainties due to the choice of renormalization andfactorization scales, which are varied by factors of two or one half. In addition, theoretical uncertainties inthe predicted cross sections, including PDF and renormalization- and factorization-scale uncertainties, areassessed and their effect is shown in terms of variations of the observed results.In the case of WIMP production models, the uncertainty related to the modeling of the initial- and final-stateradiation translates into a 3% to 6% uncertainty in the signal acceptance. The choice of different PDF setsresults in up to a 10% and a 20% uncertainty in the case of axial-vector and pseudoscalar models, respectively.Varying the renormalization and factorization scales introduces 0 .
1% to 21% variations in the signalacceptance, depending on the model and the mediator and WIMP masses considered. Renormalization andfactorization scale uncertainties introduce an uncertainty in the cross-section predictions of about 10% inthe case of the axial-vector mediator model and up to 50% for the pseudoscalar mediator model. Finally,PDF uncertainties translate into cross-section uncertainties of about 5% and 20% for the axial-vector andpseudoscalar mediator models, respectively.Similarly, for SUSY models, the uncertainties related to the modeling of initial- and final-state gluonradiation and the matching between matrix elements and parton showers in the simulation translate into a7% to 8% uncertainty in the signal acceptance. Variations of the renormalization and factorization scalesintroduce an uncertainty of about 3% in the signal acceptance. Uncertainties in the predicted cross sections,including both renormalization/factorization scale and PDF uncertainties, increase with the squark massesand range between 7% for a mass of 100 GeV and about 11% for a mass of about 1 TeV.In the case of dark-energy-inspired models, uncertainties related to renormalization/factorization scales,PDFs, and parton-shower modeling vary the signal acceptance by 0.1% to 3.5%, 1% to 16%, and 0.1%to 5%, respectively, with increasing 𝐸 missT . Renormalization/factorization scale and PDF uncertaintiesintroduce variations in the cross-section predictions of about 30% each.For the ADD model, the uncertainties related to the modeling of the initial- and final-state gluon radiationtranslate into uncertainties in the ADD signal acceptance which vary between 11% and 13% with increasing 𝐸 missT and are approximately independent of 𝑛 . The uncertainties due to the PDFs, affecting both signalnormalization and acceptance, increase from 11% at 𝑛 = 𝑛 =
6. Similarly, the variations of therenormalization and factorization scales introduce a signal yield uncertainty of 23% to 36%, growing withincreasing 𝑛 .For the ALPs production model, theoretical uncertainties related to PDFs, affecting signal normalizationand acceptance, translate into uncertainties in the signal yields that vary in the range between 2% and14%. Variations of the renormalization and factorization scales and matrix-elements to parton-showermatching scales, introduce uncertainties in the signal yields that vary between 5% and 50%. Variations inthe parton-shower modeling translate into uncertainties in the signal acceptance in the range between 1%and 20%, depending on the 𝐸 missT bin considered. 20inally, for the interpretation of an invisibly decaying Higgs boson, uncertainties related to PDFs, affectingboth signal normalization and signal acceptance, translate into 0.4% to 0 .
8% variations in the Higgssignal yields as 𝐸 missT increases. Variations in the renormalization and factorization scales introduce a 10%uncertainty in the signal yields. Uncertainties in the parton-shower modeling translate into uncertainties inthe signal acceptance that vary between 3% and 9% with increasing 𝐸 missT . Uncertainties in the higher-orderelectroweak corrections, especially relevant for VBF and 𝑉 𝐻 processes, translate into uncertainties in thesignal yield that vary between 1 .
4% and 10% with increasing 𝐸 missT . Figure 4 shows several measured distributions in the signal region compared with the SM predictionsobtained from the fit to CRs. As discussed in Section 6, the SM predictions are normalized withnormalization factors determined from the global fit carried out in exclusive 𝑝 recoilT bins. The fittingprocedure also constrains the background uncertainties, resulting in a precise SM prediction in almost thewhole 𝑝 recoilT spectrum. As an example, the SM predictions are determined with a total uncertainty of 1 . . .
1% for the EM0, EM4, and EM12 signal regions, respectively, which include correlationsbetween uncertainties in the individual background contributions. For illustration purposes, the ratios ofdata to SM predictions are shown in the lower panel, both after the CR fit and after a global background-onlyfit when the signal region is also included (“SR+CR fit”).The number of events in the data and the individual background predictions are presented in Tables 6 and 7for inclusive and exclusive 𝑝 recoilT bins, respectively. The results for all the signal regions are summarizedin Table 8. Overall, good agreement between data and SM predictions is observed. The compatibility ofthe data with a SM background hypothesis is tested using the binned profile likelihood fit described above.The resulting statistical tests for a background-only hypothesis, in the presence of different potential signalcontributions, give 𝑝 -values in the range between 0.02 and 1.0, where the minimum corresponds to a signalfor stop-pair production in the ˜ 𝑡 → 𝑐 + ˜ 𝜒 decay channel with 𝑚 ˜ 𝑡 =
500 GeV and 𝑚 ˜ 𝜒 =
420 GeV and adeviation of about 2 𝜎 from the background-only hypothesis.The results are translated into upper limits on the presence of new phenomena, using a simultaneouslikelihood fit in both the control and signal regions, and the CL s modified frequentist approach [119]. Asalready mentioned, inclusive regions with minimum 𝑝 recoilT thresholds are used to set model-independentexclusion limits, and the exclusive regions are used for the interpretation of the results within differentmodels of new physics. For the latter, the presence of a slight excess of events at high 𝑝 recoilT limits thereach of the observed limits, mostly for those models in which the expected signal would accumulate in thetail of the 𝑝 recoilT distribution. Results obtained in inclusive 𝑝 recoilT regions are translated into model-independent observed and expected95% CL upper limits on the visible cross section, defined as the product of the production cross section,acceptance and efficiency 𝜎 × 𝐴 × 𝜖 . The limits are extracted by dividing the 95% CL upper limit on thenumber of signal events by the integrated luminosity, taking into consideration the systematic uncertaintiesin the SM backgrounds and the uncertainty in the integrated luminosity. A likelihood fit is performed21
00 400 600 800 1000 1200 E v en t s / G e V ATLAS -1 = 13 TeV, 139 fbsSignal Region) > 150 GeV (j T p DataStandard Model w. unc.) + jets nn fi Z( ) + jets nn ll / fi VBF Z( ) + jets n l fi W( ) + jets n l fi VBF W( + single topttDibosonMultijet + NCB) = (600, 580) GeV c~ , t~m( ) = (1, 2000) GeV A , Z c m( = 1486 GeV DE, M
200 400 600 800 1000 1200 [GeV] recoilT p0.80.911.11.2 D a t a / S M Total UncertaintyData/SM after CR fit Data/SM after SR+CR fit
Figure 4: Measured distributions of 𝑝 recoilT for the 𝑝 recoilT >
200 GeV selection compared with the SM predictions inthe signal region. The latter are normalized with normalization factors as determined by the global fit that considersexclusive 𝑝 recoilT control regions (“CR fit”). For illustration purposes, the distributions of examples of dark energy(DE), SUSY, and WIMP scenarios are included. The ratios of data to SM predictions after the CR fit are shown inthe lower panel (black dots), and compared with the same quantities when SM predictions are normalized to theresults of the global background-only fit when the signal region is also included (“SR+CR fit”, red dots). The errorbands in the ratio shown in the lower panel include both the statistical and systematic uncertainties in the backgroundpredictions. Events with values beyond the range of the histogram are included in the last bin. separately for each of the inclusive regions IM0–IM12. The results are collected in Table 9. Values of 𝜎 × 𝐴 × 𝜖 above 736 fb (for IM0) and above 0.3 fb (for IM12) are excluded at 95% CL. A simultaneous fit to the signal and control regions in the exclusive 𝑝 recoilT bins is performed, and usedto set observed and expected 95% CL exclusion limits on the parameters of the different models underconsideration. Uncertainties in the signal and background predictions, and in the luminosity are considered,and correlations between experimental systematic uncertainties in signal and background predictions aretaken into account. The contamination of the control regions by signal events is negligible. As discussed in Section 1, simplified models are considered with the exchange of an axial-vector or apseudoscalar mediator in the 𝑠 -channel. In the case of the exchange of an axial-vector mediator, and forWIMP-pair production with 𝑚 𝑍 𝐴 > 𝑚 𝜒 , typical 𝐴 × 𝜖 values for the signal models with a 2 TeV mediator22 able 6: Data and SM background predictions in the signal region for several inclusive 𝑝 recoilT selections, as determinedusing separate one-bin likelihood fits in the control regions. For the SM prediction, both the statistical and systematicuncertainties are included. In each signal region, the individual uncertainties for the different background processescan be correlated, and do not necessarily add in quadrature to equal the total background uncertainty. The dash “–”denotes negligible background contributions. For illustration, the expected event yields for particular signals for newphenomena are provided; in this case, the quoted errors include experimental uncertainties and theory uncertaintieson the signal acceptance, as described in Sec. 7.2. Inclusive Signal Region
IM1 IM3 IM5 IM7 IM10 IM12Data events (139 fb − ) 1357019 290779 46855 7194 807 207SM prediction 1346000 ± ± ± ±
240 720 ±
60 223 ± 𝑊 → 𝑒𝜈 ± ±
800 1400 ±
100 166 ±
12 12.4 ± ± 𝑊 → 𝜇𝜈 ± ±
400 2220 ±
70 305 ±
14 38 ± ± 𝑊 → 𝜏𝜈 ± ±
800 5890 ±
160 790 ±
40 66 ± ± 𝑊 + jets 7900 ± ±
600 450 ±
160 80 ±
40 10 ± ± 𝑍 → 𝑒𝑒 – – – – – – 𝑍 → 𝜇𝜇 ±
130 – – – – – 𝑍 → 𝜏𝜏 ±
110 – – – – – 𝑍 → 𝜈𝜈 ± ± ± ±
250 520 ±
50 157 ± 𝑍 + jets 13600 ± ± ±
350 260 ±
90 35 ±
14 13 ± 𝑡 ¯ 𝑡 and single- 𝑡 ± ±
400 610 ±
70 45 ±
14 – –Diboson 26000 ± ± ±
400 310 ±
80 38 ±
12 13 ± ± ±
500 5.3 ± ± ± ±
160 29 ±
29 6 ± 𝑚 ( ˜ 𝑡, ˜ 𝜒 ) = ( , ) GeV 2840 ±
340 1560 ±
190 640 ±
80 195 ±
24 34 ± ± 𝑚 ( 𝜒, 𝑍 𝐴 ) = ( , ) GeV 3960 ±
160 2150 ±
80 918 ±
34 330 ±
13 82 ± ± 𝑀 = GeV 1740 ±
50 1106 ±
33 558 ±
27 235 ±
16 68 ± ± Table 7: Data and SM background predictions in the signal region for several exclusive 𝑝 recoilT selections, as determinedusing a binned likelihood fit in the control regions. For the SM prediction, both the statistical and systematicuncertainties are included. In each signal region, the individual uncertainties for the different background processescan be correlated, and do not necessarily add in quadrature to equal the total background uncertainty. The dash “–”denotes negligible background contributions. For illustration, the expected event yields for particular signals for newphenomena are provided; in this case, the quoted errors include experimental uncertainties and theory uncertaintieson the signal acceptance, as described in Sec. 7.2. Exclusive Signal Region
EM2 EM4 EM6 EM8 EM9 EM11Data events (139 fb − ) 313912 102888 10203 1663 738 187SM prediction 314000 ± ± ±
180 1640 ±
40 754 ±
20 182 ± 𝑊 → 𝑒𝜈 ± ±
250 280 ±
19 35.8 ± ± ± 𝑊 → 𝜇𝜈 ±
500 5940 ±
120 481 ±
12 66.8 ± ± ± 𝑊 → 𝜏𝜈 ±
800 15430 ±
260 1243 ±
29 167 ± ± ± 𝑊 + jets 2340 ±
300 1010 ±
150 140 ±
27 29 ± ± ± 𝑍 → 𝑒𝑒 – – – – – – 𝑍 → 𝜇𝜇 ±
15 97.4 ± ± ± ± 𝑍 → 𝜏𝜏 ±
14 115.0 ± ± ± ± ± 𝑍 → 𝜈𝜈 ± ± ±
170 1180 ±
40 534 ±
20 126 ± 𝑍 + jets 3900 ±
500 2170 ±
310 370 ±
60 86 ±
17 45 ±
10 13.7 ± 𝑡 ±
700 550 ±
180 15 ± 𝑡 ¯ 𝑡 ±
700 2000 ±
150 100 ± ± ± ± ± ±
500 350 ±
70 71 ±
15 33 ± ± ±
57 0.6 ± ± ±
240 46 ±
46 8 ± ± 𝑚 ( ˜ 𝑡, ˜ 𝜒 ) = ( , ) GeV 562 ±
70 516 ±
60 159 ±
19 44 ± ± ± 𝑚 ( 𝜒, 𝑍 𝐴 ) = ( , ) GeV 770 ±
30 684 ±
27 212 ± ± ± ± 𝑀 = GeV 286 ± ±
11 125 ± ± ± ± range from 13% to less than 1% for the EM0 and EM12 selections, respectively, where the values refer to23 able 8: Data and SM background predictions in the signal region for the different selections, as determined using abinned likelihood fit in the control regions. For the SM predictions both the statistical and systematic uncertaintiesare included. Inclusive Signal Region Exclusive Signal Region
Region Predicted Observed Region Predicted ObservedIM0 3 120 000 ±
40 000 3 148 643 EM0 1 783 000 ±
26 000 1 791 624IM1 1 346 000 ±
16 000 1 357 019 EM1 753 000 ± ± ± ± ± ± ± ± ±
400 29 458IM6 16 800 ±
500 17 397 EM6 10 000 ±
180 10 203IM7 7070 ±
240 7194 EM7 3870 ±
80 3986IM8 3180 ±
130 3208 EM8 1640 ±
40 1663IM9 1560 ±
80 1545 EM9 754 ±
20 738IM10 720 ±
60 807 EM10 359 ±
10 413IM11 407 ±
34 394 EM11 182 ± ±
19 207 EM12 218 ± Table 9: Observed and expected 95% CL upper limits on the number of signal events, 𝑆 and 𝑆 , and on the visiblecross section, defined as the product of cross section, acceptance and efficiency, (cid:104) 𝜎 (cid:105) , for the IM0–IM12 selections. Selection (cid:104) 𝜎 (cid:105) [fb] 𝑆 𝑆 𝑝 recoilT >
200 GeV 736 102 274 83 000 +
22 000 −
23 000 𝑝 recoilT >
250 GeV 296 41 158 33 800 +
11 300 − 𝑝 recoilT >
300 GeV 150 20 893 15 400 + − 𝑝 recoilT >
350 GeV 86 11 937 8300 + − 𝑝 recoilT >
400 GeV 52 7214 4700 + − 𝑝 recoilT >
500 GeV 21 2918 1930 + − 𝑝 recoilT >
600 GeV 10 1391 940 + − 𝑝 recoilT >
700 GeV 4 . + − 𝑝 recoilT >
800 GeV 2 . + − 𝑝 recoilT >
900 GeV 1 . + − 𝑝 recoilT > . + − 𝑝 recoilT > . + − 𝑝 recoilT > . + − an initial simulated sample generated with a minimum transverse momentum of 150 GeV. Similarly, valuesfor 𝐴 × 𝜖 in the range between 13% and less than 1% are computed for the pseudoscalar mediator modelwith 𝑚 𝑍 𝑃 =
350 GeV and 𝑚 𝜒 = 𝑝 recoilT spectrum.Figure 5(a) shows the observed and expected 95% CL exclusion contours in the 𝑚 𝑍 𝐴 – 𝑚 𝜒 parameter plane24or a simplified model with an axial-vector mediator, Dirac WIMPs, and couplings 𝑔 𝑞 = / 𝑔 𝜒 = 𝑚 𝑍 𝐴 > × 𝑚 𝜒 , mediator masses up to about 2 . 𝑚 𝜒 = 𝑚 𝑍 𝐴 ∼ 𝑚 𝜒 ∼
585 GeV. A Z m050010001500 [ G e V ] c m c = m A Z m exp s – Expected limit exp s – Expected limit Expected limit ) scale ¯ PDF theory s – Observed limit ( > 0.12 h c W Relic density, Perturbativity limit -1 = 13 TeV, 36.1 fbsATLAS ATLAS -1 = 13 TeV, 139 fb sAxial-vector mediator = 1.0 c = 0.25, g q gDirac fermion DM95% CL limits (a) P Z m0100200300 [ G e V ] c m c = m P Z m exp s – Expected limit exp s – Expected limit Expected limit ) scale ¯ PDF theory s – Observed limit ( > 0.12 h c W Relic density,
ATLAS -1 = 13 TeV, 139 fb sPseudo-scalar mediator = 1.0 c = 1.0, g q gDirac fermion DM95% CL limits (b) Figure 5: (a) 95% CL exclusion contours in the 𝑚 𝑍 𝐴 – 𝑚 𝜒 parameter plane for the axial-vector mediator model. (b)95% CL exclusion contours in the 𝑚 𝑍 𝑃 – 𝑚 𝜒 parameter plane for the pseudoscalar mediator model. The solid (dashed)curves show the observed (expected) limits, while the bands indicate the ± 𝜎 theory uncertainties in the observedlimit and the ± 𝜎 and ± 𝜎 ranges of the expected limit in the absence of a signal. The red curves correspond to theset of points for which the expected relic density is consistent with the WMAP measurements (i.e. Ω ℎ = . 𝑚 𝑍 𝐴 > 𝑚 𝜒 ) corresponds to predicted values of the relic density abundance inconsistent with the WMAPmeasurements. The region excluded due to perturbativity, defined by 𝑚 𝜒 > √︁ 𝜋 / 𝑚 𝑍 𝐴 , is indicated by the grayhatched area. The dotted lines indicate the kinematic limit for on-shell production 𝑚 𝑍 𝐴,𝑃 = × 𝑚 𝜒 . In the case ofthe pseudoscalar mediator model, the shape of the 2 𝜎 band at 𝑚 𝑍 𝑃 ∼
350 GeV is related to the rapid increase of thesignal cross section at the threshold at which the mediator mass equals twice the mass of the top quark. In the case ofthe axial-vector mediator model, the results are compared with previous results from the ATLAS Collaboration at √ 𝑠 =
13 TeV using 36 . − [4]. Similarly, Figure 5(b) presents observed and expected 95% CL exclusion contours in the 𝑚 𝑍 𝑃 – 𝑚 𝜒 parameterplane for a simplified model with a pseudoscalar mediator, Dirac WIMPs, and couplings 𝑔 𝑞 = 𝑔 𝜒 = 𝜎 SD as a function of the WIMP mass, following theprescriptions from Refs. [19, 120]. Figure 6 shows exclusion limits for WIMP–proton and WIMP–neutron25
10 [GeV] c m - - - - - - - - - - - ] - p r o t on ) [ c m c ( S D s PICO-60Axial-Vector Mediator90% CL limitsDirac Fermion DM = 1.0 c = 0.25, g q g ATLAS -1 = 13 TeV, 139 fbs (a)
10 [GeV] c m - - - - - - - - - - - ] - neu t r on ) [ c m c ( S D s XENON1TLUXAxial-Vector Mediator90% CL limitsDirac Fermion DM = 1.0 c = 0.25, g q g ATLAS -1 = 13 TeV, 139 fbs (b) Figure 6: A comparison of the inferred limits (black line) with the constraints from direct-detection experimentson the spin-dependent (a) WIMP–proton scattering cross section and (b) WIMP–neutron scattering cross sectionas a function of the WIMP mass, in the context of the simplified model with axial-vector couplings. Unlike in the 𝑚 𝑍 𝐴 – 𝑚 𝜒 parameter plane, the limits are shown at 90% CL. The results from this analysis, excluding the region tothe left of the contour, are compared with limits from the PICO [122] (purple line), LUX [123] (orange line), andXENON1T [124] (green line) experiments. The comparison is model-dependent and solely valid in the context ofthis model, assuming minimal mediator width and the coupling values 𝑔 𝑞 = / 𝑔 𝜒 = scattering cross sections as a function of the WIMP mass, compared with the results from the PICO [122]experiment, and from the LUX [123] and XENON1T [124] experiments, respectively. Stringent limitson the scattering cross section of the order of 1 . × − cm for WIMP masses of about 100 GeV, and3 × − cm for WIMP masses below 10 GeV are inferred from this analysis, which complement theresults from direct-detection experiments. As in previous publications, different models of squark-pair production are considered: stop-pair productionwith ˜ 𝑡 → 𝑐 + ˜ 𝜒 , stop-pair production with ˜ 𝑡 → 𝑏 + 𝑓 𝑓 (cid:48) + ˜ 𝜒 , sbottom-pair production with ˜ 𝑏 → 𝑏 + ˜ 𝜒 ,and squark-pair production with ˜ 𝑞 → 𝑞 + ˜ 𝜒 ( 𝑞 = 𝑢, 𝑑, 𝑐, 𝑠 ). In each case separately, the results aretranslated into exclusion limits as a function of the squark mass for different neutralino masses. The regionwith stop–neutralino or sbottom-neutralino mass differences below 5 GeV is not considered in the exclusionsince in this regime the squarks could become long-lived. In such a compressed scenario, and for stopsbottom masses of about 600 GeV, the typical value of 𝐴 × 𝜖 for the selection criteria varies between 11%for EM0 and less than 1% for EM12, as computed using a sample with a minimum missing transversemomentum of 150 GeV. Comparable values for 𝐴 × 𝜖 are obtained in the rest of the squark–neutralinomass plane.Figure 7(a) presents the results in the case of the ˜ 𝑡 → 𝑐 + ˜ 𝜒 decays. In the compressed scenario with stop26nd neutralino nearly degenerate in mass, masses up to 550 GeV are excluded. Similarly, Figure 7(b) showsthe observed and expected 95% CL exclusion limits as a function of the stop and neutralino masses forthe ˜ 𝑡 → 𝑏 + 𝑓 𝑓 (cid:48) + ˜ 𝜒 decay channel, assuming a branching ratio B = 𝑚 ˜ 𝑡 − 𝑚 ˜ 𝜒 ∼ 𝑚 𝑏 , stopmasses up to 550 GeV are also excluded. Figure 8(a) presents the observed and expected 95% CL exclusion [GeV] t~ m300 400 500 600 700 [ G e V ] c~ m -1 =13 TeV, 139 fbs c~ c fi t~ production, t~ t~All limits at 95% CL ATLAS exp s – Expected limit exp s – Expected limit Expected limit ) scale ¯ PDF theory s – Observed limit ( -1 =13 TeV, 36.1 fbsATLAS c + m c~ < m t ~ m W + m b + m c~ > m t ~ m (a) [GeV] t~ m300 400 500 600 700 [ G e V ] c~ m c~ < m t ~ m exp s – Expected limit exp s – Expected limit Expected limit ) scale ¯ PDF theory s – Observed limit ( -1 =13 TeV, 36.1 fbsATLAS ATLAS -1 =13 TeV, 139 fbs c~ bff' fi t~ production, t~ t~All limits at 95% CL (b) Figure 7: Excluded regions at the 95% CL in the (˜ 𝑡 , ˜ 𝜒 ) mass plane for (a) the decay channel ˜ 𝑡 → 𝑐 + ˜ 𝜒 ( B = 𝑡 → 𝑏 + 𝑓 𝑓 (cid:48) + ˜ 𝜒 ( B = ± 𝜎 variations of the NNLO + NNLL SUSY cross-section predictions.The bands around the expected limits indicate the expected ± 𝜎 and ± 𝜎 ranges of limits in the absence of a signal.The results from this analysis are compared with previous results from the ATLAS Collaboration at √ 𝑠 =
13 TeVusing 36 . − [4]. limits as a function of the sbottom and neutralino masses for the ˜ 𝑏 → 𝑏 + ˜ 𝜒 ( B = 𝑚 ˜ 𝑏 − 𝑚 ˜ 𝜒 ∼ 𝑚 𝑏 , this analysis extends the 95% CL exclusion limits up to a sbottommass of 545 GeV. Finally, Figure 8(b) presents the observed and expected 95% CL exclusion limits asa function of the squark mass and the squark–neutralino mass difference for ˜ 𝑞 → 𝑞 + ˜ 𝜒 ( 𝑞 = 𝑢, 𝑑, 𝑐, 𝑠 ).In the compressed scenario, squark masses below 925 GeV are excluded at 95% CL. Altogether, theseresults significantly improve upon the previous exclusion limits based on 36 . − of total integratedluminosity [4]. In the very compressed scenario, the observed limits on the squark masses are extended bymore than 100 GeV. Exclusion limits are computed for the Horndeski dark-energy model (see Section 1) with 𝑚 𝜑 = . 𝑚 𝜑 value considered for light particles up to masses of the orderof 1 GeV. The typical value of 𝐴 × 𝜖 for the selection criteria varies between 8.2% for EM0 and less than1% for EM12. Figure 9 shows the observed and expected contours at 95% CL on the 𝜎 – 𝑀 plane. Values27 [GeV] b~ m400 450 500 550 600 [ G e V ] c~ m -1 =13 TeV, 139 fbs c~ b fi b~ production, b~ b~All limits at 95% CL ATLAS exp s – Expected limit exp s – Expected limit Expected limit ) scale ¯ PDF theory s – Observed limit ( -1 =13 TeV, 36.1 fbsATLAS b + m c~ < m b ~ m (a) [GeV] q~ m200 400 600 800 1000 [ G e V ] c~ - m q ~ m exp s – Expected limit exp s – Expected limit Expected limit ) scale ¯ PDF theory s – Observed limit ( -1 =13 TeV, 36.1 fbsATLAS ATLAS -1 =13 TeV, 139 fbs c~ q fi q~ production, q~ q~All limits at 95% CL)c~,s~,d~,u~ ( R q~+ L q~ (b) Figure 8: (a) Exclusion plane at 95% CL as a function of sbottom and neutralino masses for the decay channel˜ 𝑏 → 𝑏 + ˜ 𝜒 ( B = 𝑞 → 𝑞 + ˜ 𝜒 and ˜ 𝑞 L + ˜ 𝑞 R with ( ˜ 𝑢, ˜ 𝑑, ˜ 𝑐, ˜ 𝑠 ). The dotted lines around the observed limit indicate therange of observed limits corresponding to ± 𝜎 variations of the NNLO + NNLL SUSY cross-section predictions.The bands around the expected limit indicates the expected ± 𝜎 and ± 𝜎 ranges of limits in the absence of a signal.The results from this analysis are compared with previous results from the ATLAS Collaboration at √ 𝑠 =
13 TeVusing 36 . − [4]. for 𝑀 below 1486 GeV are excluded, which represents a significant improvement over the limits previouslyobtained. The validity of the effective implementation of the model at the LHC energies was studiedpreviously [6] by truncating the signal contributions with √ ˆ 𝑠 < 𝑔 ∗ 𝑀 , where √ ˆ 𝑠 is the center-of-massenergy of the hard interaction, leading to a negligible effect on the obtained exclusion limits. The results are translated into limits on the parameters of the ADD model. As in previous analyses, only thesignal regions with 𝑝 recoilT >
400 GeV are employed, with sufficient sensitivity to ADD signal. The typicalvalue of 𝐴 × 𝜖 for the selection criteria, as computed from a simulated sample with missing transversemomentum above 150 GeV, is of the order of 6% for EM4 and is less than 1% for EM12. Figure 10 andTable 10 present the results. Values of 𝑀 𝐷 below 11 . 𝑛 = . 𝑛 = − of 13 TeVdata [4]. As already noted in Ref. [4], the analysis partially probes the phase-space region with ˆ 𝑠 > 𝑀 𝐷 .The suppression of this kinematic region in computing the 95% CL lower limits on 𝑀 𝐷 translates into anegligible effect on the results. 28
000 1200 1400 1600 1800 2000 [GeV] M10 ) [f b ] ff j fi pp ( s exp s – Expected limit exp s – Expected limit Expected limit ) theory Scale ¯ PDF s – Observed limit (Predicted cross section -1 = 13 TeV, 36.1 fbsATLAS ATLAS -1 = 13 TeV, 139 fbs operator LAll limits at 95% CL
Figure 9: Observed (solid line) and expected (dashed line) exclusions at 95% CL on the Horndeski dark-energymodel for 𝑚 𝜙 = . 𝑐 𝑖 ≠ = 𝑐 = 𝑀 . The results are compared with the theoretical predictions. The dotted lines around theobserved limits indicate the range of observed limits corresponding to ± 𝜎 variations of the cross-section predictions.The results from this analysis are compared with previous results from the ATLAS Collaboration at √ 𝑠 =
13 TeVusing 36 . − [6]. Results are expressed in terms of 95% CL limits on the parameters of the ALP model. As in the caseof the ADD model, the kinematic region with 𝑝 recoilT >
400 GeV provides the best sensitivity. Figure 11shows 95% exclusion contours in the the 𝑐 ∼ 𝐺 – 𝑓 𝑎 plane, for an axion mass of 1 MeV. The exclusion does notdepend significantly on the axion mass for masses up to at least 1 GeV. The limits on 𝑐 ∼ 𝐺 increase linearlywith 𝑓 𝑎 . For 𝑓 𝑎 = 𝑐 ∼ 𝐺 above 0.008 are excluded. Expressed in terms of the 𝑐 ∼ 𝐺 / 𝑓 𝑎 ratio,values above 8 × − GeV − are excluded at 95% CL. As in the case of the dark energy and ADD models, Table 10: The 95% CL observed and expected lower limits on the fundamental Planck scale in 4 + 𝑛 dimensions, 𝑀 𝐷 ,as a function of the number of extra dimensions 𝑛 , considering nominal LO signal cross sections. The impact of the ± 𝜎 theoretical uncertainty on the observed limits and the expected ± 𝜎 range of limits in the absence of a signalare also given. ADD Model Limits on 𝑴 𝑫 (95% CL)Expected [TeV] Observed [TeV] 𝑛 = . + . − . . + . − . 𝑛 = . + . − . . + . − . 𝑛 = . + . − . . + . − . 𝑛 = . + . − . . + . − . 𝑛 = . + . − . . + . − . [ T e V ] D Lo w e r li m i t on M exp s – Expected limit exp s – Expected limit Expected limit )
PDF,scaletheory s – Observed limit ( -1 =13 TeV, 36.1 fbsATLAS ATLAS -1 =13 TeV, 139 fbsAll limits at 95% CL Figure 10: Observed and expected 95% CL lower limits on the fundamental Planck scale in 4 + 𝑛 dimensions, 𝑀 𝐷 ,as a function of the number of extra dimensions. The bands indicate the ± 𝜎 theory uncertainties in the observedlimit and the ± 𝜎 and ± 𝜎 ranges of the expected limit in the absence of a signal. The results from this analysis arecompared with previous results from the ATLAS Collaboration using 36 . − of √ 𝑠 =
13 TeV data [4]. the validity of the effective field implementation of the model is challenged for ˆ 𝑠 > 𝑓 𝑎 . For values of 𝑓 𝑎 below 2 TeV, the signal yields are reduced significantly when applying a suppressing weighting factor 𝑓 𝑎 / ˆ 𝑠 for events with ˆ 𝑠 > 𝑓 𝑎 . The effect is reduced to about 5% for 𝑓 𝑎 = 𝑓 𝑎 above 3 TeV. The results are interpreted in terms of 95% CL upper limits on the branching ratio for an invisibly decayingHiggs boson. The signal yields are dominated by gluon–gluon fusion production processes (about 73%),followed by the contributions from VBF (18%),
𝑉 𝐻 (8%), and 𝑡 ¯ 𝑡 + 𝐻 (1%) processes. The low 𝐸 missT region plays an important role in enhancing the sensitivity of the data to the Higgs signal and the full 𝐸 missT spectrum is employed in computing the limits. The observed agreement between data and the SMbackground predictions in the measured 𝐸 missT distribution leads to a 95% CL observed (expected) exclusionlimit on the invisible branching ratio of the Higgs boson of 0 .
34 (0 . + . − . ).30
000 1500 2000 2500 3000 3500 4000 4500 5000 [GeV] a f G ~ C ATLAS -1 = 13 TeV, 139 fbs = 1 MeV a Axion-Like Particles, m95% CL limits exp s – Expected limit exp s – Expected limit Expected limit scale ¯ PDF theory s – Observed limit
Figure 11: Observed and expected 95% CL upper limits on the coupling 𝑐 ∼ 𝐺 as a function of the effective scale 𝑓 𝑎 forALP mass of 1 MeV. The bands indicate the ± 𝜎 theory uncertainties in the observed limit and the ± 𝜎 and ± 𝜎 ranges of the expected limit in the absence of a signal. The 95% CL limits are computed with no suppression of theevents with ˆ 𝑠 > 𝑓 𝑎 . Results are reported from a search for new phenomena in events with an energetic jet and large missingtransverse momentum in proton–proton collisions at √ 𝑠 =
13 TeV at the LHC, based on data correspondingto an integrated luminosity of 139 fb − collected by the ATLAS detector during 2015–2018. Compared toprevious publications, in addition to an increase of almost a factor of four in the data size, the analysisimplements a number of improvements in the signal selection and the background determination leadingto enhanced sensitivity. The measurements are in agreement with the SM predictions. The results aretranslated into model-independent 95% CL upper limits on the visible cross section for new phenomena,and these range from 736 fb to 0.3 fb with increasing missing transverse momentum. Improved bounds onthe parameters for a variety of models for new phenomena have been derived. In the case of simplifiedmodels for WIMP-pair production in the 𝑠 -channel, with Dirac fermions as dark-matter candidates, anaxial-vector mediator with masses below 2.1 TeV is excluded at 95% CL for very light WIMPs and couplingvalues 𝑔 𝑞 = / 𝑔 𝜒 =
1. For the first time, the ATLAS monojet analysis reaches sensitivity forexcluding pseudoscalar mediators with masses below 376 GeV, for very light WIMPs and coupling values 𝑔 𝑞 = 𝑔 𝜒 = 𝑡 → 𝑐 + ˜ 𝜒 or˜ 𝑡 → 𝑏 + 𝑓 𝑓 (cid:48) + ˜ 𝜒 and ˜ 𝑏 → 𝑏 + ˜ 𝜒 , respectively, squark masses below about 550 GeV and 550 GeV areexcluded at 95% CL, thus surpassing previous exclusions by almost 100 GeV. In the case of squark-pairproduction with ˜ 𝑞 → 𝑞 + ˜ 𝜒 ( 𝑞 = 𝑢, 𝑑, 𝑐, 𝑠 ) , squark masses below 925 GeV are excluded.The results are expressed in terms of 95% CL limits on the suppression scale 𝑀 for the Horndeski31ark-energy model with 𝑚 𝜙 = . 𝑐 𝑖 ≠ = 𝑐 =
1. Suppression scales 𝑀 below about1.5 TeV are excluded. In the case of the ADD model with large extra spatial dimensions, 95% CL lowerlimits on the fundamental Planck scale 𝑀 𝐷 in 4 + 𝑛 dimensions vary in the range between 11.2 TeV and5.9 TeV for 𝑛 = 𝑛 =
6, respectively. In models with axion-like particles with coupling to gluons,couplings-to-effective-scale ratios 𝑐 ∼ 𝐺 / 𝑓 𝑎 above 8 × − GeV − are excluded at 95% CL for axion massesup to 1 GeV. Finally, limits are obtained for the branching ratio of an invisibly decaying Higgs boson.Branching fractions above 0 .
34 are excluded at 95% CL.
Acknowledgments
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), ASGC(Taiwan), RAL (UK) and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resourceproviders. Major contributors of computing resources are listed in Ref. [125].32 eferences [1] ATLAS Collaboration,
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Dias ,T. Dias Do Vale , M.A. Diaz , F.G. Diaz Capriles , J. Dickinson , M. Didenko , E.B. Diehl ,J. Dietrich , S. Díez Cornell , C. Diez Pardos , A. Dimitrievska , W. Ding , J. Dingfelder ,S.J. Dittmeier , F. Dittus , F. Djama , T. Djobava , J.I. Djuvsland , M.A.B. Do Vale ,M. Dobre , D. Dodsworth , C. Doglioni , J. Dolejsi , Z. Dolezal , M. Donadelli , B. Dong ,J. Donini , A. D’onofrio , M. D’Onofrio , J. Dopke , A. Doria , M.T. Dova , A.T. Doyle ,E. Drechsler , E. Dreyer , T. Dreyer , A.S. Drobac , D. Du , T.A. du Pree , Y. Duan ,F. Dubinin , M. Dubovsky , A. Dubreuil , E. Duchovni , G. Duckeck , O.A. Ducu ,D. Duda , A. Dudarev , A.C. Dudder , E.M. Duffield , M. D’uffizi , L. Duflot , M. Dührssen ,C. Dülsen , M. Dumancic , A.E. Dumitriu , M. Dunford , S. Dungs , A. Duperrin ,H. Duran Yildiz , M. Düren , A. Durglishvili , D. Duschinger , B. Dutta , D. Duvnjak ,G.I. Dyckes , M. Dyndal , S. Dysch , B.S. Dziedzic , M.G. Eggleston , T. Eifert , G. Eigen ,K. Einsweiler , T. Ekelof , H. El Jarrari , V. Ellajosyula , M. Ellert , F. Ellinghaus ,A.A. Elliot , N. Ellis , J. Elmsheuser , M. Elsing , D. Emeliyanov , A. Emerman , Y. Enari ,M.B. Epland , J. Erdmann , A. Ereditato , P.A. Erland , M. Errenst , M. Escalier , C. Escobar ,O. Estrada Pastor , E. Etzion , G. Evans , H. Evans , M.O. Evans , A. Ezhilov , F. Fabbri ,L. Fabbri , V. Fabiani , G. Facini , R.M. Fakhrutdinov , S. Falciano , P.J. Falke , S. Falke ,J. Faltova , Y. Fang , Y. Fang , G. Fanourakis , M. Fanti , M. Faraj , A. Farbin ,A. Farilla , E.M. Farina , T. Farooque , S.M. Farrington , P. Farthouat , F. Fassi ,P. Fassnacht , D. Fassouliotis , M. Faucci Giannelli , W.J. Fawcett , L. Fayard , O.L. Fedin ,W. Fedorko , A. Fehr , M. Feickert , L. Feligioni , A. Fell , C. Feng , M. Feng ,M.J. Fenton , A.B. Fenyuk , S.W. Ferguson , J. Ferrando , A. Ferrari , P. Ferrari , R. Ferrari ,D.E. Ferreira de Lima , A. Ferrer , D. Ferrere , C. Ferretti , F. Fiedler , A. Filipčič ,F. Filthaut , K.D. Finelli , M.C.N. Fiolhais , L. Fiorini , F. Fischer , J. Fischer ,W.C. Fisher , T. Fitschen , I. Fleck , P. Fleischmann , T. Flick , B.M. Flierl , L. Flores ,L.R. Flores Castillo , F.M. Follega , N. Fomin , J.H. Foo , G.T. Forcolin , B.C. Forland ,A. Formica , F.A. Förster , A.C. Forti , E. Fortin , M.G. Foti , D. Fournier , H. Fox ,P. Francavilla , S. Francescato , M. Franchini , S. Franchino , D. Francis , L. Franco ,L. Franconi , M. Franklin , G. Frattari , A.N. Fray , P.M. Freeman , B. Freund ,W.S. Freund , E.M. Freundlich , D.C. Frizzell , D. Froidevaux , J.A. Frost , M. Fujimoto ,C. Fukunaga , E. Fullana Torregrosa , T. Fusayasu , J. Fuster , A. Gabrielli , A. Gabrielli ,S. Gadatsch , P. Gadow , G. Gagliardi , L.G. Gagnon , G.E. Gallardo , E.J. Gallas ,B.J. Gallop , R. Gamboa Goni , K.K. Gan , S. Ganguly , J. Gao , Y. Gao , Y.S. Gao ,F.M. Garay Walls , C. García , J.E. García Navarro , J.A. García Pascual , C. Garcia-Argos ,43. Garcia-Sciveres , R.W. Gardner , N. Garelli , S. Gargiulo , C.A. Garner , V. Garonne ,S.J. Gasiorowski , P. Gaspar , A. Gaudiello , G. Gaudio , P. Gauzzi , I.L. Gavrilenko ,A. Gavrilyuk , C. Gay , G. Gaycken , E.N. Gazis , A.A. Geanta , C.M. Gee , C.N.P. Gee ,J. Geisen , M. Geisen , C. Gemme , M.H. Genest , C. Geng , S. Gentile , S. George ,T. Geralis , L.O. Gerlach , P. Gessinger-Befurt , G. Gessner , M. Ghasemi Bostanabad ,M. Ghneimat , A. Ghosh , A. Ghosh , B. Giacobbe , S. Giagu , N. Giangiacomi ,P. Giannetti , A. Giannini , G. Giannini , S.M. Gibson , M. Gignac , D.T. Gil , B.J. Gilbert ,D. Gillberg , G. Gilles , N.E.K. Gillwald , D.M. Gingrich , M.P. Giordani , P.F. Giraud ,G. Giugliarelli , D. Giugni , F. Giuli , S. Gkaitatzis , I. Gkialas , E.L. Gkougkousis ,P. Gkountoumis , L.K. Gladilin , C. Glasman , J. Glatzer , P.C.F. Glaysher , A. Glazov ,G.R. Gledhill , I. Gnesi , M. Goblirsch-Kolb , D. Godin , S. Goldfarb , T. Golling ,D. Golubkov , A. Gomes , R. Goncalves Gama , R. Gonçalo , G. Gonella ,L. Gonella , A. Gongadze , F. Gonnella , J.L. Gonski , S. González de la Hoz ,S. Gonzalez Fernandez , R. Gonzalez Lopez , C. Gonzalez Renteria , R. Gonzalez Suarez ,S. Gonzalez-Sevilla , G.R. Gonzalvo Rodriguez , L. Goossens , N.A. Gorasia , P.A. Gorbounov ,H.A. Gordon , B. Gorini , E. Gorini , A. Gorišek , A.T. Goshaw , M.I. Gostkin ,C.A. Gottardo , M. Gouighri , A.G. Goussiou , N. Govender , C. Goy , I. Grabowska-Bold ,E.C. Graham , J. Gramling , E. Gramstad , S. Grancagnolo , M. Grandi , V. Gratchev ,P.M. Gravila , F.G. Gravili , C. Gray , H.M. Gray , C. Grefe , K. Gregersen , I.M. Gregor ,P. Grenier , K. Grevtsov , C. Grieco , N.A. Grieser , A.A. Grillo , K. Grimm , S. Grinstein ,J.-F. Grivaz , S. Groh , E. Gross , J. Grosse-Knetter , Z.J. Grout , C. Grud , A. Grummer ,J.C. Grundy , L. Guan , W. Guan , C. Gubbels , J. Guenther , A. Guerguichon ,J.G.R. Guerrero Rojas , F. Guescini , D. Guest , R. Gugel , A. Guida , T. Guillemin ,S. Guindon , J. Guo , W. Guo , Y. Guo , Z. Guo , R. Gupta , S. Gurbuz , G. Gustavino ,M. Guth , P. Gutierrez , 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 ,44. 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 ,45.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. Liu , J.B. Liu , J.K.K. Liu , K. Liu , M. Liu , M.Y. Liu , P. Liu ,X. Liu , Y. Liu , Y. Liu , Y.L. Liu , Y.W. Liu , M. Livan , A. Lleres ,J. Llorente Merino , S.L. Lloyd , C.Y. Lo , E.M. Lobodzinska , P. Loch , S. Loffredo ,T. Lohse , K. Lohwasser , M. Lokajicek , J.D. Long , R.E. Long , I. Longarini , L. Longo ,I. Lopez Paz , A. Lopez Solis , J. Lorenz , N. Lorenzo Martinez , A.M. Lory , A. Lösle ,X. Lou , X. Lou , A. Lounis , J. Love , P.A. Love , J.J. Lozano Bahilo , M. Lu , Y.J. Lu ,H.J. Lubatti , C. Luci , F.L. Lucio Alves , A. Lucotte , F. Luehring , I. Luise ,L. Luminari , B. Lund-Jensen , N.A. Luongo , M.S. Lutz , D. Lynn , H. Lyons , R. Lysak ,E. Lytken , F. Lyu , V. Lyubushkin , T. Lyubushkina , H. Ma , L.L. Ma , Y. Ma ,D.M. Mac Donell , G. Maccarrone , C.M. Macdonald , J.C. MacDonald , J. Machado Miguens ,R. Madar , W.F. Mader , M. Madugoda Ralalage Don , N. Madysa , J. Maeda , T. Maeno ,M. Maerker , V. Magerl , N. Magini , J. Magro , D.J. Mahon , C. Maidantchik ,A. Maio , K. Maj , O. Majersky , S. Majewski , Y. Makida , N. Makovec ,B. Malaescu , Pa. Malecki , V.P. Maleev , F. Malek , D. Malito , U. Mallik , C. Malone ,S. Maltezos , S. Malyukov , J. Mamuzic , G. Mancini , J.P. Mandalia , I. Mandić ,L. Manhaes de Andrade Filho , I.M. Maniatis , J. Manjarres Ramos , K.H. Mankinen , A. Mann ,A. Manousos , B. Mansoulie , I. Manthos , S. Manzoni , A. Marantis , G. Marceca ,L. Marchese , G. Marchiori , M. Marcisovsky , L. Marcoccia , C. Marcon , M. Marjanovic ,Z. Marshall , M.U.F. Martensson , S. Marti-Garcia , C.B. Martin , T.A. Martin , V.J. Martin ,B. Martin dit Latour , L. Martinelli , M. Martinez , P. Martinez Agullo ,V.I. Martinez Outschoorn , S. Martin-Haugh , V.S. Martoiu , A.C. Martyniuk , A. Marzin ,S.R. Maschek , L. Masetti , T. Mashimo , R. Mashinistov , J. Masik , A.L. Maslennikov ,L. Massa , P. Massarotti , P. Mastrandrea , A. Mastroberardino , T. Masubuchi ,D. Matakias , A. Matic , N. Matsuzawa , P. Mättig , J. Maurer , B. Maček ,D.A. Maximov , R. Mazini , I. Maznas , S.M. Mazza , J.P. Mc Gowan , S.P. Mc Kee ,T.G. McCarthy , W.P. McCormack , E.F. McDonald , A.E. McDougall , J.A. Mcfayden ,G. Mchedlidze , M.A. McKay , K.D. McLean , S.J. McMahon , P.C. McNamara ,C.J. McNicol , R.A. McPherson , J.E. Mdhluli , Z.A. Meadows , S. Meehan , T. Megy ,S. Mehlhase , A. Mehta , B. Meirose , D. Melini , B.R. Mellado Garcia , J.D. Mellenthin ,M. Melo , F. Meloni , A. Melzer , E.D. Mendes Gouveia , A.M. Mendes Jacques Da Costa ,H.Y. Meng , L. Meng , X.T. Meng , S. Menke , E. Meoni , S. Mergelmeyer ,S.A.M. Merkt , C. Merlassino , P. Mermod , L. Merola , C. Meroni , G. Merz ,O. Meshkov , J.K.R. Meshreki , J. Metcalfe , A.S. Mete , C. Meyer , J-P. Meyer ,M. Michetti , R.P. Middleton , L. Mijović , G. Mikenberg , M. Mikestikova , M. Mikuž ,H. Mildner , A. Milic , C.D. Milke , D.W. Miller , L.S. Miller , A. Milov , D.A. Milstead ,A.A. Minaenko , I.A. Minashvili , L. Mince , A.I. Mincer , B. Mindur , M. Mineev ,Y. Minegishi , Y. Mino , L.M. Mir , M. Mironova , T. Mitani , J. Mitrevski , V.A. Mitsou ,46. 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 , 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. Nachman , O. Nackenhorst , A.Nag Nag , K. Nagai , K. Nagano , Y. Nagasaka ,J.L. Nagle , E. Nagy , A.M. Nairz , Y. Nakahama , K. Nakamura , T. Nakamura , H. Nanjo ,F. Napolitano , R.F. Naranjo Garcia , R. Narayan , I. Naryshkin , M. Naseri , T. Naumann ,G. Navarro , P.Y. Nechaeva , F. Nechansky , T.J. Neep , A. Negri , M. Negrini , C. Nellist ,C. Nelson , M.E. Nelson , S. Nemecek , M. Nessi , M.S. Neubauer , F. Neuhaus ,M. Neumann , R. Newhouse , P.R. Newman , C.W. Ng , Y.S. Ng , Y.W.Y. Ng , B. Ngair ,H.D.N. Nguyen , T. Nguyen Manh , E. Nibigira , R.B. Nickerson , R. Nicolaidou ,D.S. Nielsen , J. Nielsen , M. Niemeyer , N. Nikiforou , V. Nikolaenko , I. Nikolic-Audit ,K. Nikolopoulos , P. Nilsson , H.R. Nindhito , A. Nisati , N. Nishu , R. Nisius , I. Nitsche ,T. Nitta , T. Nobe , D.L. Noel , Y. Noguchi , I. Nomidis , M.A. Nomura , M. Nordberg ,J. Novak , T. Novak , O. Novgorodova , R. Novotny , L. Nozka , K. Ntekas , E. Nurse ,F.G. Oakham , J. Ocariz , A. Ochi , I. Ochoa , J.P. Ochoa-Ricoux , K. O’Connor , S. Oda ,S. Odaka , S. Oerdek , A. Ogrodnik , A. Oh , C.C. Ohm , H. Oide , R. Oishi , M.L. Ojeda ,H. Okawa , Y. Okazaki , M.W. O’Keefe , Y. Okumura , A. Olariu , L.F. Oleiro Seabra ,S.A. Olivares Pino , D. Oliveira Damazio , J.L. Oliver , M.J.R. Olsson , A. Olszewski ,J. Olszowska , Ö.O. Öncel , D.C. O’Neil , A.P. O’neill , A. Onofre , P.U.E. Onyisi ,H. Oppen , R.G. Oreamuno Madriz , M.J. Oreglia , G.E. Orellana , D. Orestano ,N. Orlando , R.S. Orr , V. O’Shea , R. Ospanov , G. Otero y Garzon , H. Otono , P.S. Ott ,G.J. Ottino , M. Ouchrif , J. Ouellette , F. Ould-Saada , A. Ouraou , Q. Ouyang , M. Owen ,R.E. Owen , V.E. Ozcan , N. Ozturk , J. Pacalt , H.A. Pacey , K. Pachal , A. Pacheco Pages ,C. Padilla Aranda , S. Pagan Griso , G. Palacino , S. Palazzo , S. Palestini , M. Palka , P. Palni ,C.E. Pandini , J.G. Panduro Vazquez , P. Pani , G. Panizzo , L. Paolozzi , C. Papadatos ,K. Papageorgiou , S. Parajuli , A. Paramonov , C. Paraskevopoulos , D. 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 ,47. 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 ,J.H. Rawling , 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 ,48. 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 ,49. 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 ,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 , 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 .50 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.51 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 ) LPMR, Faculté des Sciences, Université Mohamed Premier,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, Key Laboratory for ParticleAstrophysics and Cosmology (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 Advanced52tudy, 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.53 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 of54merica. ( 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.55 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. 56 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. ∗∗