Search for new phenomena in final states with b-jets and missing transverse momentum in \sqrt{s}=13 TeV pp collisions with the ATLAS detector
EEUROPEAN ORGANISATION FOR NUCLEAR RESEARCH (CERN)
Submitted to: JHEP CERN-EP-2021-0011st February 2021
Search for new phenomena in final states with 𝒃 -jetsand missing transverse momentum in √ 𝒔 =
13 TeV 𝒑 𝒑 collisions with the ATLAS detector
The ATLAS Collaboration
The results of a search for new phenomena in final states with 𝑏 -jets and missing transversemomentum using 139 fb − of proton–proton data collected at a centre-of-mass energy √ 𝑠 =
13 TeV by the ATLAS detector at the LHC are reported. The analysis targets final statesproduced by the decay of a pair-produced supersymmetric bottom squark into a bottom quarkand a stable neutralino. The analysis also seeks evidence for models of pair production ofdark matter particles produced through the decay of a generic scalar or pseudoscalar mediatorstate in association with a pair of bottom quarks, and models of pair production of scalarthird-generation down-type leptoquarks. No significant excess of events over the StandardModel background expectation is observed in any of the signal regions considered by theanalysis. Bottom squark masses below 1270 GeV are excluded at 95% confidence level if theneutralino is massless. In the case of nearly mass-degenerate bottom squarks and neutralinos,the use of dedicated secondary-vertex identification techniques permits the exclusion of bottomsquarks with masses up to 660 GeV for mass splittings between the squark and the neutralinoof 10 GeV. These limits extend substantially beyond the regions of parameter space excludedby similar ATLAS searches performed previously. © a r X i v : . [ h e p - e x ] J a n Introduction
The possible existence of non-luminous matter in the universe, referred to as dark matter (DM), is supportedby a wide variety of astrophysical and cosmological measurements [1–5]. However, the nature and propertiesof the DM remain largely unknown and represent one of the most important unanswered questions in physics.A plausible candidate for cold dark matter [6, 7] is the stable lightest neutralino ( ˜ 𝜒 ) in 𝑅 -parity-conservingmodels [8] of electroweak scale supersymmetry (SUSY) [9–14]. In supersymmetric models that naturallyaddress the gauge hierarchy problem [15–18], the scalar partners of the third-generation quarks are light [19,20]. This may lead to the lighter bottom squark ( ˜ 𝑏 ) and top squark (˜ 𝑡 ) mass eigenstates being significantlylighter than the other squarks and gluinos. As a consequence, the ˜ 𝑏 and ˜ 𝑡 could be pair produced withrelatively large cross-sections in 𝑝 𝑝 collisions at the Large Hadron Collider (LHC [21]). In most SUSYmodels, the ˜ 𝑏 and the ˜ 𝑡 decay into final states incorporating third-generation quarks and invisible ˜ 𝜒 particles.More generically, the dark matter may be composed of weakly interacting massive particles (WIMPs,generically denoted by 𝜒 in the rest of the paper) [22], of which the lightest supersymmetric particle (LSP)is one example. WIMPs can account for the measured relic density of dark matter in the early universeacross a broad portion of parameter space [1, 2, 23]. WIMPs could be produced in pairs at the LHCthrough the decay of a new mediator particle coupling to Standard Model (SM) quarks [24–29]. Shouldthis mediator preferentially couple to third-generation quarks then an excess of events containing suchquarks along with invisible dark matter particles could be observed. Such events can be described in theframework of simplified DM models [28, 30, 31] with model assumptions described in Refs. [28, 29, 32,33].This paper describes a search for the production of invisible dark matter particles in association withbottom quarks. Signal regions (SRs) are developed which target the direct pair production of bottomsquarks, each of which decays into a ˜ 𝜒 and a bottom quark, as shown in Figure 1(a). Additional signalregions target the pair production of DM particles through the decay of a generic scalar ( 𝜙 ) or pseudoscalar( 𝑎 ) mediator state produced in association with a pair of bottom quarks (Figure 1(b)). The results of theanalysis are also interpreted in the context of beyond-the-SM (BSM) scenarios incorporating pair-producedscalar third-generation down-type leptoquarks LQ 𝑑 [34–41] decaying to bottom quarks and neutrinosor top quarks and 𝜏 -leptons (Figure 1(c)). These models are all characterised by events consisting ofjets containing 𝑏 -hadrons (referred to as 𝑏 -jets), missing transverse momentum ( 𝐸 missT ), and no chargedleptons.Previous searches by ATLAS [42–45] and CMS [46, 47] using comparable or smaller datasets have targetedsimilar final states. This analysis extends the regions of parameter space probed by the LHC through theuse of a larger dataset than in previous ATLAS searches, new boosted decision tree (BDT) discriminants,and also new selections maximising the efficiency for reconstructing 𝑏 -jets with low transverse momentumgenerated by, for instance, SUSY models with small mass-splitting between ˜ 𝑏 and ˜ 𝜒 .Section 2 presents a brief overview of the ATLAS detector, Section 3 describes the data and simulationsamples used in the analysis and Section 4 presents the methods used to reconstruct events. An overviewof the analysis strategy, including background estimation, is presented in Section 5. The systematicuncertainties considered in the analysis are described in Section 6. Section 7 presents the results andinterpretation thereof. The conclusions of the analysis are presented in Section 8. The scalar partners of the left-handed and right-handed chiral components of the bottom quark ( ˜ 𝑏 L , ˜ 𝑏 R ) or top quark (˜ 𝑡 L , ˜ 𝑡 R )mix to form two mass eigenstates in each case, of which the ˜ 𝑏 and the ˜ 𝑡 are defined to be the lighter. b ˜ bpp ˜ χ b ˜ χ b (a) φ/agg b χχb (b) LQ d LQ d pp ν, τb, tν, τb, t (c) Figure 1: Diagrams illustrating the processes targeted by this analysis: (a) bottom squark pair production, (b)production of DM particles (indicated with 𝜒 ) through the decay of a scalar or pseudoscalar mediator coupling tobottom quarks, and (c) pair production of scalar third-generation down-type leptoquarks decaying to bottom quarksand neutrinos or top quarks and 𝜏 -leptons. BSM particles are indicated in red, while SM particles are indicated inblack. The ATLAS detector [48–50] is a multipurpose detector with a forward–backward symmetric cylindricalgeometry and nearly 4 𝜋 coverage in solid angle. The inner detector (ID) tracking system consists of pixeland silicon microstrip detectors covering the pseudorapidity region | 𝜂 | < .
5, surrounded by a transitionradiation tracker, which improves electron identification over the region | 𝜂 | < .
0. The ID is surroundedby a thin superconducting solenoid providing an axial 2 T magnetic field and by a fine-granularitylead/liquid-argon (LAr) electromagnetic calorimeter covering | 𝜂 | < .
2. A steel/scintillator-tile calorimeterprovides hadronic coverage in the central pseudorapidity range ( | 𝜂 | < . . < | 𝜂 | < .
9) are made of LAr active layers with either copper or tungsten as the absorbermaterial for electromagnetic and hadronic measurements. The muon spectrometer with an air-core toroidmagnet system surrounds the calorimeters. Three layers of high-precision tracking chambers providecoverage in the range | 𝜂 | < .
7, while dedicated chambers allow triggering in the region | 𝜂 | < . The data analysed in this paper were collected between 2015 and 2018 at a centre-of-mass energy of13 TeV with a 25 ns proton bunch crossing interval. The average number, (cid:104) 𝜇 (cid:105) , of 𝑝 𝑝 interactions per bunchcrossing (pile-up) ranged from 13 in 2015 to around 38 in 2017–2018. Application of beam, detectorand data-quality criteria [51] results in a total integrated luminosity of 139 fb − . The uncertainty in the ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point in the centre of the detector. Thepositive 𝑥 -axis is defined by the direction from the interaction point to the centre of the LHC ring, with the positive 𝑦 -axispointing upwards, while the beam direction defines the 𝑧 -axis. Cylindrical coordinates ( 𝑟, 𝜙 ) are used in the transverse plane, 𝜙 being the azimuthal angle around the 𝑧 -axis. The transverse momentum 𝑝 T , the transverse energy 𝐸 T and the missingtransverse momentum are defined in the 𝑥 – 𝑦 plane unless stated otherwise. The pseudorapidity 𝜂 is defined in terms of thepolar angle 𝜃 by 𝜂 = − ln tan ( 𝜃 / ) and the rapidity is defined as 𝑦 = ( / ) ln [( 𝐸 + 𝑝 𝑧 )/( 𝐸 − 𝑝 𝑧 )] where 𝐸 is the energy and 𝑝 𝑧 the longitudinal momentum of the object of interest. 𝑡 ¯ 𝑡 , 𝑊 + jets and 𝑍 + jets SM processes [56, 57]. These triggers yield an approximately constant efficiency inthe presence of a single isolated electron or muon with transverse momentum ( 𝑝 T ) greater than 27 GeV.Monte Carlo (MC) simulations are used to model SM background processes and the SUSY, dark matterand leptoquark signals considered by the analysis. Samples of bottom squark and dark matter signal eventswere generated with MadGraph5_aMC@NLO 2.6.2 [58] at leading order (LO) in the strong couplingconstant ( 𝛼 S ), with the renormalisation and factorisation scales set to 𝐻 genT / 𝐻 genT is the scalar sumof the transverse momenta of the outgoing partons) and parton distribution function (PDF) NNPDF2.3LO [59]. The matrix element (ME) calculations were performed at tree level and include the emissionof up to two additional partons. Bottom squarks decayed directly into a ˜ 𝜒 and a bottom quark with100% branching ratio, as is the case in 𝑅 -parity-conserving models in which the lighter bottom squark isthe next-to-lightest supersymmetric particle. Leptoquark signal events were generated at next-to-leadingorder (NLO) in 𝛼 S with MadGraph5_aMC@NLO 2.6.0 [58], using the leptoquark model of Ref. [60]that adds parton showers to previous fixed-order NLO QCD calculations [61, 62], and the NNPDF3.0NLO [63] PDF set with 𝛼 S = . 𝛼 S , also adding contributions from the resummation of soft gluon emission at next-to-next-to-leading-logarithm accuracy (approximate NNLO+NNLL) [66–69]. The nominal cross-sections andtheir uncertainties were derived using the PDF4LHC15_mc PDF set, following the recommendations ofRef. [70]. For ˜ 𝑏 masses ranging from 400 GeV to 1.5 TeV, the cross-sections range from 2.1 pb to 0.26 fb,with uncertainties ranging from 7% to 17%. Leptoquark signal cross-sections were obtained from thecalculation of direct top squark pair production, as this process has the same production modes, computedat approximate next-to-next-to-leading order (NNLO) in 𝛼 S with resummation of next-to-next-to-leadinglogarithmic (NNLL) soft gluon terms [66–69]. The cross-sections do not include lepton 𝑡 -channelcontributions, which are neglected in Ref. [60] and may lead to corrections at the percent level [71].The production cross-sections for generic scalar and pseudoscalar mediators were evaluated includingNLO QCD corrections assuming SM Yukawa couplings to quarks, in a five-flavour scheme, followingthe prescriptions of Ref. [72]. They were calculated with renormalisation and factorisation scales set to 𝐻 genT / 𝑝 T threshold (‘ptj’ in Ref. [72]) set to 20 GeV. They range from about 29 pb to about1.5 fb for mediator masses between 10 GeV and 500 GeV.The SM backgrounds considered in this analysis are: 𝑍 + jets production; 𝑊 + jets production; 𝑡 ¯ 𝑡 pairproduction; single-top-quark production; 𝑡 ¯ 𝑡 production in association with electroweak or Higgs bosons( 𝑡 ¯ 𝑡 + 𝑋 ); and diboson production ( 𝑊𝑊 , 𝑍 𝑍 , 𝑍𝑊 , 𝑍 𝐻 and
𝑊 𝐻 ). The events were simulated using differentMC generator programs depending on the process. Details of the generators, PDF set and underlying-eventtuned parameter set (tune) used for each process are listed in Table 1.4 able 1: The SM background MC simulation samples used in this paper. Generator, PDF set, parton shower, tuneused for the underlying event (UE), and order in 𝛼 S of cross-section calculations used for yield normalisation, areshown for each process considered. Process ME event generator PDF PS and UE tune Cross-sectionhadronisation calculation 𝑉 +jets ( 𝑉 = 𝑊 / 𝑍 ) Sherpa 2.2.1 [73] NNPDF3.0 NNLO Sherpa Default NNLO [74] 𝑡 ¯ 𝑡 Powheg-Box v2 [75] NNPDF3.0 NNLO Pythia 8.230 A14 NNLO+NNLL [76–81]Single top Powheg-Box v2 NNPDF3.0 NNLO Pythia 8.230 A14 NNLO+NNLL [82–84]Diboson Sherpa 2.2.1–2.2.2 NNPDF3.0 NNLO Sherpa Default NLO 𝑡 ¯ 𝑡 + 𝑉 aMC@NLO 2.3.3 NNPDF3.0 NLO Pythia 8.210 A14 NLO [58] 𝑡 ¯ 𝑡𝐻 aMC@NLO 2.2.3 NNPDF3.0 NLO Pythia 8.230 A14 NLO [85–88] The EvtGen v1.6.0 program [89] was used to describe the properties of the 𝑏 - and 𝑐 -hadron decays inthe signal samples and in the background samples, except those produced with Sherpa. For all SMbackground samples, the response of the detector to particles was modelled with the full ATLAS detectorsimulation [90] based on Geant4 [91]. Signal samples were prepared using a fast simulation based on aparameterisation of showers in the ATLAS electromagnetic and hadronic calorimeters [92] coupled toGeant4 simulations of particle interactions elsewhere. All simulated events were overlaid with multiple 𝑝 𝑝 collisions simulated with Pythia 8.186 using the A3 tune [93] and the NNPDF2.3 LO PDF set [59].The MC samples were generated with variable levels of pile-up in the same and neighbouring collisions,and were reweighed to match the distribution of the mean number of interactions observed in data in2015–2018. The analysis identifies events with jets containing 𝑏 -hadrons or secondary vertices corresponding to 𝑏 -hadron decays, missing transverse momentum from the 𝜒 or ˜ 𝜒 , and no charged leptons (electrons ormuons). The last requirement is effective in suppressing SM backgrounds arising from 𝑊 → ℓ𝜈 decays,including events containing top quark production.Events are required to have a primary vertex [94, 95] reconstructed from at least two tracks [96] with 𝑝 T > . 𝑘 𝑡 jet algorithm [97, 98] with radius parameter 𝑅 = . | 𝑧 sin 𝜃 | < . 𝑧 is the longitudinal impact parameter, and calorimeter energy clusters surviving an energy subtraction algorithm that removes the calorimeterdeposits of good-quality tracks from any vertex. Jet energy scale corrections, derived from MC simulationand data, are used to calibrate the average energies of jet candidates to the scale of their constituentparticles [101]. Only corrected jet candidates with 𝑝 T >
20 GeV and | 𝜂 | < . | 𝜂 | ≤ . 𝐸 missT . A set of quality criteria is applied to identify jets which arise from non-collision sources The transverse impact parameter is defined as the distance of closest approach of a track to the beam-line, measured in thetransverse plane. The longitudinal impact parameter corresponds to the 𝑧 -coordinate distance between the point along the trackat which the transverse impact parameter is defined and the primary vertex.
5r detector noise [102] and any event which contains a jet failing to satisfy these criteria is removed. Jetscontaining a large particle momentum contribution from pile-up vertices, as measured by the jet vertextagger (JVT) discriminant [103] are rejected if they have 𝑝 T ∈ [ , ] GeV, | 𝜂 | < . < . 𝑏 -jets if they lie within the ID acceptance of | 𝜂 | < . DL1r ) which uses a selection of inputs including information about the impactparameters of ID tracks, the presence of displaced secondary vertices and the reconstructed flight paths of 𝑏 - and 𝑐 -hadrons inside the jet [104]. The 𝑏 -tagging algorithm uses a working point with an efficiency of77%, determined with a sample of simulated 𝑡 ¯ 𝑡 events. The corresponding misidentification (mis-tag) rateis 20% for 𝑐 -jets and 0.9% for light-flavour jets. Differences in efficiency and mis-tag rate between dataand MC simulation are taken into account with correction factors as described in Ref. [104].To enhance sensitivity to models where low- 𝑝 T bottom quarks are present in the final state (e.g. bottomsquark pair production with nearly mass-degenerate ˜ 𝑏 and ˜ 𝜒 ), a dedicated secondary-vertex findingalgorithm (TC-LVT) is used. Documented in Ref. [105], this algorithm reconstructs secondary verticesindependently of the presence of an associated jet. A new loose working point, defined using the sametrack and vertex variables described in Ref. [106] for the medium and tight working points, was optimisedfor this analysis. The efficiency to correctly identify the secondary vertex associated with the decay of a 𝑏 -hadron ( 𝜖 vtx ) ranges from 5% for a 𝑏 -hadron 𝑝 T of 5 GeV to 40% for a 𝑝 T of 15 GeV. The correspondingprobability ( 𝑓 vtx ) to obtain a vertex in an event without a 𝑏 -hadron depends on the event topology andpile-up conditions, and is 1%–5%. Differences in 𝜖 vtx and 𝑓 vtx between data and MC simulation aretaken into account by using correction factors computed in dileptonic 𝑡 ¯ 𝑡 and 𝑊 + jets production events,respectively. The correction factors are compatible with one for 𝜖 vtx and range between 1.2 and 1.5 for 𝑓 vtx .Two different classes (‘baseline’ and ‘high-purity’) of reconstructed lepton candidates (electrons or muons)are used in the analyses presented here. When selecting samples for the search, events containing a‘baseline’ electron or muon are rejected. When selecting events with leptons for the purpose of estimating 𝑊 + jets, 𝑍 + jets and top quark backgrounds, additional requirements are applied to leptons to ensuregreater purity of these backgrounds. These leptons are referred to as ‘high-purity’ leptons in the followingand form a subset of the baseline leptons.Baseline muon candidates are formed by combining information from the muon spectrometer and innerdetector as described in Refs. [107, 108] and are required to possess 𝑝 T > | 𝜂 | < .
7. Baselinemuon candidates must additionally have a significance of the transverse impact parameter relative tothe beam-line | 𝑑 BL0 |/ 𝜎 ( 𝑑 BL0 ) <
3, and a longitudinal impact parameter relative to the primary vertex | 𝑧 sin ( 𝜃 )| < . Medium identificationrequirements described in Refs. [107, 108] and the
FixedCutTightTrackOnly isolation requirements, whichare described in the same references and use tracking-based variables to implement a set of 𝜂 - and 𝑝 T -dependent criteria.Baseline electron candidates are reconstructed from an isolated electromagnetic calorimeter energy depositmatched to an ID track [109] and are required to possess 𝑝 T > | 𝜂 | < .
47, and to satisfy the
Loose likelihood-based identification criteria described in Refs. [109, 110]. High-purity electron candidatesare also required to possess | 𝑑 BL0 |/ 𝜎 ( 𝑑 BL0 ) < | 𝑧 sin ( 𝜃 )| < . Tight isolationrequirements [109, 110]. 6igh-purity muon and electron candidates used to estimate backgrounds in this analysis are requiredto possess 𝑝 T >
20 GeV in order to reduce the impact of misidentified or non-prompt leptons. Inaddition, when using events selected with single-lepton triggers, the leading lepton is required to possess 𝑝 T >
27 GeV in order to ensure that events are selected in the trigger plateau.After the selections described above, a procedure is applied to remove non-isolated leptons and avoiddouble counting of tracks and energy depositions associated with overlapping reconstructed jets, electronsand muons. The procedure applies the following actions to the event. First, baseline electrons are discardedif they share an ID track with a baseline muon. Next, any jet with | 𝜂 | < . Δ 𝑅 ≡ √︁ ( Δ 𝑦 ) + ( Δ 𝜙 ) = . | 𝜂 | < . 𝑁 trk < 𝑁 trk refers to the number of tracks with 𝑝 T >
500 MeV that areassociated with the jet) within Δ 𝑅 ≡ √︁ ( Δ 𝑦 ) + ( Δ 𝜙 ) = . Δ 𝑅 = min ( . , . +
10 GeV / 𝑝 𝑒 / 𝜇 T ) of a remaining jet are discarded.Multiplicative scale factors are applied to simulated events to account for differences between data andsimulation for the lepton trigger, reconstruction, identification and isolation efficiencies, and for the jetmomentum scales and energy resolutions. Similar corrections are also applied to the probability ofmis-tagging jets originating from the hard 𝑝 𝑝 scattering as pile-up jets with the JVT discriminant.The missing transverse momentum p missT of magnitude 𝐸 missT is defined as the negative vector sum of the 𝑝 T of all selected and calibrated physics objects (electrons, muons, photons and jets) in the event, with an extraterm added to account for energy in the event that is not associated with any of these objects [111]. This last‘soft term’ contribution is calculated from the ID tracks with 𝑝 T >
500 MeV associated with the primaryvertex, thus ensuring that it is robust against pile-up contamination [111, 112]. Photons contributing tothe p missT calculation are required to satisfy 𝑝 T >
25 GeV and | 𝜂 | < .
37 (excluding the transition region1 . < | 𝜂 | < .
52 between the barrel and endcap EM calorimeters), to pass photon shower shape andelectron rejection criteria, and to be isolated [109, 113].
In total, four sets of SRs are defined to target bottom squark pair-production or generic WIMP productionin association with 𝑏 -jets and are labelled SRX with X = A to D. Each set of signal regions targets differentvalues of Δ 𝑚 ( ˜ 𝑏 , ˜ 𝜒 ) , the mass separation between the ˜ 𝑏 and ˜ 𝜒 , or low and high WIMP masses. Theevent selections defined for these regions all require the absence of baseline leptons, and exploit differenttechniques to improve the sensitivity to the target signal models. SRA targets large values of Δ 𝑚 ( ˜ 𝑏 , ˜ 𝜒 ) ,and its definition resembles that used in Refs. [42, 43, 114–116]. SRB, whose selection is mutuallyexclusive with that of SRA, is designed to be optimal for 50 GeV < Δ 𝑚 ( ˜ 𝑏 , ˜ 𝜒 ) <
200 GeV, and uses aboosted decision tree (BDT) [117] as the final discriminant. SRC targets signals with Δ 𝑚 ( ˜ 𝑏 , ˜ 𝜒 ) <
50 GeV,and exploits the information from the TC-LVT algorithm about the presence of vertices associated withlow- 𝑝 T 𝑏 -hadrons produced by the bottom squark decays. When deriving mass exclusion limits on bottomsquarks or leptoquarks, SRA and SRB are statistically combined, and the analysis yielding the better of theexpected CL S values [118] from the combined SRA/SRB and SRC is used for each signal point. Finally,SRD is optimised to target the dark matter models with scalar or pseudoscalar mediators by making use ofa BDT. 7or all signal regions, the SM background estimation is performed with a likelihood fit [119] where thenormalisation factors of the MC datasets corresponding to the SM processes expected to contribute themost to the event yields in the SRs ( 𝑍 + jets for all signal regions, 𝑊 + jets and 𝑡 ¯ 𝑡 for SRC) are left free tofloat. To aid their determination, dedicated control regions (CR) select events containing either one ortwo leptons, and having kinematic properties similar to events in the signal regions, but with negligibleexpected signal contributions. The quality of the background estimation is verified in dedicated validationregions (VR), designed to select events as similar as possible to those populating the SRs, while keepingsignal contributions low. The likelihood is built as the product of Poissonian terms for each CR and, whenassessing the discovery and exclusion sensitivity to new phenomena, SR bins. The effect of systematicuncertainties on the Poissonian expectation values is included through nuisance parameters assumed tohave Gaussian probability distributions, as described in Section 6. Several kinematic variables built from the physics objects defined in the previous section are used todiscriminate new physics from known SM background events. Variables which are used in many SRsare described here, while SR-specific variables are described in the corresponding SR sections below.Wherever necessary, final-state objects are labelled following a descending 𝑝 T ordering. • min [ Δ 𝜙 ( jet − 𝑛 , p missT )] : The minimum Δ 𝜙 between any of the leading 𝑛 jets and p missT . Thebackground from multijet processes is characterised by small values of this variable. • 𝐻 T;3 : It is defined as the scalar sum of the 𝑝 T of all jets excluding the leading two: 𝐻 T;3 = ∑︁ 𝑖 ≥ ( 𝑝 jetT ) 𝑖 . The variable is used to reject events with extra-jet activity in signal regions targeting modelscharacterised by small mass-splitting between the bottom squark and the neutralino. • 𝑚 eff : It is defined as the scalar sum of the 𝑝 T of the jets and the 𝐸 missT , i.e.: 𝑚 eff = ∑︁ 𝑖 ( 𝑝 jetT ) 𝑖 + 𝐸 missT . The 𝑚 eff observable is correlated with the mass of the pair-produced SUSY particles and is employedas a discriminating variable, as well as in the computation of other composite observables. • S : The global 𝐸 missT significance, calculated including parameterisations of the resolutions of allselected objects [120]. It is defined as follows: S = (cid:118)(cid:116) | p missT | 𝜎 ( − 𝜌 ) . Here 𝜎 L is the total momentum resolution after being rotated into the longitudinal (parallel tothe p missT ) plane. The total momentum resolution of all jets and leptons, at a given 𝑝 T and | 𝜂 | , isdetermined from parameterised Monte Carlo simulation in which the resolution measured in datais modelled well. The quantity 𝜌 LT is a correlation factor between the longitudinal and transverse8omentum resolution (again with respect to the p missT ) of each jet or lepton. The significance S isused to discriminate between events where the 𝐸 missT arises from invisible particles in the final stateand events where the 𝐸 missT arises from poorly measured particles (and jets). • 𝑚 𝑗 𝑗 : The invariant mass of the two leading jets. In events where at least one of the leading jets is 𝑏 -tagged, this variable helps to reduce the contamination from 𝑡 ¯ 𝑡 events. It is referred to as 𝑚 𝑏𝑏 when the two leading 𝑏 -tagged jets are considered. • 𝑚 T ( ℓ, p missT ) : The transverse mass of the lepton and the missing transverse momentum is defined as: 𝑚 T ( ℓ, p missT ) = √︃ p ℓ T 𝐸 missT − p ℓ T · p missT and is used in the CRs to suppress the contribution from fake and non-prompt leptons, which arenormally characterised by low 𝑚 T ( ℓ, p missT ) values in multijet production events. • 𝑚 CT : The contransverse mass [121] is the main discriminating variable in the SRA signal regions. Itis used to measure the masses of pair-produced heavy particles decaying semi-invisibly. For identicaldecays of two heavy particles (e.g. the bottom squarks decaying exclusively as ˜ 𝑏 → 𝑏 ˜ 𝜒 ) into twovisible particles 𝑣 and 𝑣 (the bottom quarks), and two invisible particles 𝑋 and 𝑋 (the ˜ 𝜒 for thesignal), 𝑚 CT is defined as 𝑚 ( 𝑣 , 𝑣 ) = [ 𝐸 T ( 𝑣 ) + 𝐸 T ( 𝑣 )] − [ p T ( 𝑣 ) − p T ( 𝑣 )] , with 𝐸 T = √︃ 𝑝 + 𝑚 , and it has a kinematic endpoint at 𝑚 maxCT = ( 𝑚 𝐼 − 𝑚 𝑋 )/ 𝑚 𝐼 , where 𝐼 is theinitially pair-produced particle. This variable is extremely effective in suppressing the top quark pairproduction background ( 𝐼 = 𝑡, 𝑋 = 𝑊 ), for which the endpoint is at 135 GeV. • 𝑚 minT ( jet − , p missT ) : This is the minimum of the transverse masses calculated using any of the leadingfour jets and the p missT in the event. For signal scenarios with low values of 𝑚 maxCT , this kinematicvariable is an alternative discriminating variable to reduce the 𝑡 ¯ 𝑡 background. SRA targets bottom squark pair production with large values of Δ 𝑚 ( ˜ 𝑏 , ˜ 𝜒 ) . The selection criteria aresummarised in Table 2. Only events with 𝐸 missT >
250 GeV are retained to ensure full efficiency of theonline trigger selection and comply with the expected signal topology. To discriminate against multijetproduction, events where p missT originates from the mismeasurement of a jet are suppressed with selectionson min [ Δ 𝜙 ( jet − , p missT )] and 𝐸 missT / 𝑚 eff . The final state is expected to contain two 𝑏 -jets from the twobottom squark decays. A veto on large hadronic activity (implemented by rejecting events with a fourthjet of significant 𝑝 T ) is imposed to suppress mostly events from SM 𝑡 ¯ 𝑡 production. SM 𝑊 + jets and 𝑍 + jets production, where 𝑏 -jets are produced mainly via gluon splitting, is suppressed by a selectionon 𝑚 𝑏𝑏 . Finally, selections on 𝑚 eff and 𝑚 CT are applied to maximise the sensitivity to the signal. Whenexcluding specific models of bottom squark production, a two-dimensional binning in 𝑚 CT and 𝑚 eff is applied. Five mutually exclusive regions ( 𝑚 CT ∈ [ , ) , [ , ) , [ , ) , [ , ) and [ , ∞) , with all units in GeV) denoted by SRAmctX, where X is the bin lower bound, are used.SRAmct250 is subdivided into five bins of 𝑚 eff , starting from 𝑚 eff >
500 GeV and increasing in stepsof 200 GeV, with the last bin including all events with 𝑚 eff > 𝑚 eff ( [ . , ) , [ , ∞) and [ , . ) , [ . , ∞) 𝑚 CT bins, a singleselection 𝑚 eff > . ( . ) TeV is applied in SRAmct550 (SRAmct650) respectively. When assessing themodel-independent discovery significance against the background-only hypothesis (see Section 7), fivediscovery regions, named SRAmctXi are defined by removing any binning in 𝑚 eff . Table 2: SRA signal, control and validation region definitions. Pink cells for the control and validation regions’columns indicate which selections ensure that the regions are orthogonal to the SR.
Variable SRA CRzA VR 𝑚 CT A1 VR 𝑚 𝑏𝑏 A1 VR 𝑚 CT A2 VR 𝑚 𝑏𝑏 A2 Number of baseline leptons 0 2 0Number of high-purity leptons – 2 SFOS – 𝑝 T ( ℓ ) [GeV] – >
27 – 𝑝 T ( ℓ ) [GeV] – >
20 – 𝑚 T ( ℓ, p missT ) [GeV] – >
20 – 𝑚 ℓℓ [GeV] – [ , ] –Number of jets ∈ [ , ] Number of 𝑏 -tagged jets 2 𝑗 and 𝑗 𝑏 -tagged (cid:51) 𝑝 T ( 𝑗 ) [GeV] > 𝑝 T ( 𝑗 ) [GeV] > 𝑝 T ( 𝑗 ) [GeV] < [ Δ 𝜙 ( jet − , p missT )] [rad] > 𝐸 missT [GeV] > < > 𝐸 missT [GeV] – >
250 – 𝐸 missT / 𝑚 eff > 𝐸 missT / 𝑚 eff – > .
25 – 𝑚 𝑏𝑏 [GeV] > < > < > 𝑚 CT [GeV] > > [ , ] > [ , ] 𝑚 eff [GeV] > [ , ] > If Δ 𝑚 ( ˜ 𝑏 , ˜ 𝜒 ) <
200 GeV, selections based on the 𝑚 CT and 𝑚 𝑏𝑏 variables are no longer effective anda multivariate approach is preferred to separate the signal from SM production processes. A BDT isimplemented by making use of the XGBoost (XGB) framework [117]. The training procedure used eventsthat pass the selection specified in Table 3 (with the exception of the BDT output score) and are classifiedin four different categories: three corresponding to the main backgrounds processes ( 𝑡 ¯ 𝑡 , 𝑍 + jets, 𝑊 + jetsproduction), and one corresponding to semi-compressed signal samples ( Δ 𝑚 ( ˜ 𝑏 , ˜ 𝜒 ) ≤
200 GeV, wherethe event selection suppresses the acceptance for samples with Δ 𝑚 ( ˜ 𝑏 , ˜ 𝜒 ) ≤
30 GeV ). A one vs rest multi-classification procedure was used: for each classifier, the class is fitted against all the other classesproducing output scores containing the predicted probability of an event being in each class. The outputscore 𝑤 XGB denotes the signal classifier output score and is used in the definition of the signal region.The rotational invariance of event topologies in the transverse plane is exploited by rotating the azimuthalangles of all final-state objects so that 𝐸 missT has 𝜙 ( p missT ) =
0. The variables used in the training are the10omentum vectors of the jets, the 𝑏 -tagging information, and other event-level variables ( 𝑚 eff , S , 𝑚 CT , 𝑚 minT ( jet − , p missT ) and Δ 𝑅 ( 𝑏 , 𝑏 ) ). The highest-ranked variables after training are 𝑚 minT ( jet − , p missT ) and the transverse momenta of the first three jets in the event.The full selection of SRB is defined in Table 3. An upper bound on 𝑚 CT ensures that the selection is ortho-gonal to SRA. When assessing the exclusion sensitivity for the signal-plus-background hypothesis for specificBSM models, four 𝑤 XGB bins are used in the likelihood fit ( [ . , . ) , [ . , . ) , [ . , . ) , [ . , ] ). Table 3: SRB signal, control and validation region definitions. Pink cells for the control and validation regions’columns indicate which selections ensure that the regions are orthogonal to the SR.
Variable SRB CRzB VRzBNumber of baseline leptons 0 2Number of high-purity leptons – 2 SFOS 𝑝 T ( ℓ ) [GeV] – > 𝑝 T ( ℓ ) [GeV] – > 𝑚 ℓℓ [GeV] – [ , ] 𝑚 T ( ℓ, p missT ) [GeV] – > ∈ [ , ] Number of 𝑏 -tagged jets 2 𝑝 T ( 𝑗 ) [GeV] > 𝑝 T ( 𝑗 ) [GeV] > [ Δ 𝜙 ( jet − , p missT )] [rad] > 𝑗 not 𝑏 -tagged – (cid:51) – 𝐸 missT [GeV] > < 𝐸 missT [GeV] – > 𝑚 CT [GeV] < 𝑤 XGB > . [ . , . ] > . SRC targets events where a bottom squark pair is produced recoiling against a high- 𝑝 T initial-state-radiation(ISR) jet and Δ 𝑚 ( ˜ 𝑏 , ˜ 𝜒 ) <
50 GeV. In the boosted bottom squark decay, the boost is mostly transferred to˜ 𝜒 because of its mass. It is therefore thanks to such boost that the 𝐸 missT satisfies the trigger requirements,while the bottom quarks are instead expected to have low 𝑝 T . Three mutually exclusive signal regions,based on the number of 𝑏 -tagged jets and TC-LVT-identified vertices ( 𝑁 vtx ), are defined: SRC-2b, two 𝑏 -jets; SRC-1b1v, one 𝑏 -jet and at least one TC-LVT vertex; and SRC-0b1v, no 𝑏 -jets and at least oneTC-LVT vertex. The three regions offer complementary sensitivity depending on Δ 𝑚 ( ˜ 𝑏 , ˜ 𝜒 ) , and arestatistically combined when stating the sensitivity for exclusion of bottom squark pair production models.They all exploit the topological and kinematic features of the signal by requiring large 𝐸 missT and a high- 𝑝 T ,non- 𝑏 -tagged leading jet, and vetoing on additional hadronic activity by imposing an upper bound on 𝐻 T;3 .The following variables are used to better extract the signal from the SM background:11
The bottom quarks coming from the bottom squark decay are expected to be produced centrally inpseudorapidity, angularly close to each other and nearly back-to-back to the ISR jet. This is exploitedin SRC-1b1v and SRC-0b1v with selections on the angular separation in the transverse plane betweenthe leading jet and the 𝑏 -jet or TC-LVT vertex, and on the pseudorapidity of the TC-LVT vertex, 𝜂 vtx . • The 𝑝 T of the leading ISR jet is expected to be significantly higher than that of the second jet,expected to come from the bottom squark decay. Therefore the variable A = 𝑝 T ( 𝑗 ) − 𝑝 T ( 𝑗 ) 𝑝 T ( 𝑗 ) + 𝑝 T ( 𝑗 ) is expected to take values close to one for the signal, while it is expected to have a wider distributionfor the background. This variable is not used in SRC-0b1v, where a jet coming from the bottomsquark decay cannot be identified. • The vertex mass ( 𝑚 vtx ) and 𝑝 T ( 𝑝 vtxT ) are useful in rejecting events where the vertex is due to a 𝑐 -hadron decay or to a random track crossing. For these fake vertices the values of both variablestend to be lower than for vertices originating from 𝑏 -hadron decays.The full list of selections applied to these variables and to other variables introduced in Section 5.1 isshown in Table 4. To further enhance the exclusion sensitivity, two different bins in 𝐸 missT are defined( 𝐸 missT ∈ [
500 GeV ,
650 GeV ) , [
650 GeV , ∞) for SRC-2b and 𝐸 missT ∈ [
400 GeV ,
600 GeV ) , [
600 GeV , ∞) for SRC-1b1v and SRC-0b1v). Table 4: SRC signal and validation region definitions. Pink cells for the validation regions’ columns indicate whichselections ensure that they are orthogonal to the corresponding SR.
Variable SRC-2b SRC-1b1v SRC-0b1v VRC-2b VRC-1b1v VRC-0b1vNumber of jets ∈ [ , ] 𝑗 not 𝑏 -tagged (cid:51) Number of baseline leptons 0Number of 𝑏 -tagged jets ≥ ≥ 𝑁 vtx ≥ ≥ ≥ ≥ ≥ ≥ 𝑚 vtx [GeV] − > . > . − > . > . 𝑝 vtxT [GeV] − > > − > > 𝑝 T ( 𝑗 ) [GeV] > > > < > > 𝐸 missT [GeV] > > > < > > 𝐻 T;3 [GeV] − < < − < < A > . > . − [ . , . ] > .
86 - 𝑚 𝑗 𝑗 [GeV] > > − [ , ] >
250 - Δ 𝜙 ( 𝑗 , 𝑏 ) [rad] − > . − − < . − Δ 𝜙 ( 𝑗 , vtx ) [rad] − − > . − − < . | 𝜂 vtx | − < . < . − > . > . Two signal regions target low- and high-mediator-mass dark matter signals, and are named SRD-low andSRD-high, respectively: SRD-low is optimised for mediator masses from 10 to 100 GeV, while SRD-high12s optimised for mediator masses from 200 to 500 GeV. A common preselection is applied including therequirement of two 𝑏 -jets in the final state. The thresholds for the missing transverse momentum and the 𝑝 T of the leading jet are kept as low as possible via a two-dimensional requirement selecting events onthe trigger plateau, i.e. ( 𝑝 T ( 𝑗 ) −
20 GeV ) ( 𝐸 missT −
160 GeV ) > . Then BDTs are trained todiscriminate between the three most relevant background processes (top pair production, 𝑊 + jets, 𝑍 + jets)and two sets of kinematically similar signal models which are characterised by either low or high mediatormass. This results in six BDT discriminants, denoted by 𝑤 XY , where X and Y are the background processand signal mass range used in the training. The BDT discriminants have ranges of [− , ] with the morepositive values being more signal-like. In addition to some of the variables listed in Section 5.1, thefollowing variables are used specifically in SRD: • 𝐻 T : the scalar sum of the jet transverse momenta. The ratio of the leading jet 𝑝 T to 𝐻 T is used in thesignal region selection. • 𝛿 + , 𝛿 − : angular variables that exploit the topology of the event [44]. They are defined as two linearcombinations of min [ Δ 𝜙 ( jet − , p missT )] and the azimuthal separation between the 𝑏 -jets, Δ 𝜙 𝑏𝑏 . 𝛿 − = min [ Δ 𝜙 ( jet − , p missT )] − Δ 𝜙 𝑏𝑏 ,𝛿 + = | min [ Δ 𝜙 ( jet − , p missT )] + Δ 𝜙 𝑏𝑏 − 𝜋 | . These variables are used in the training of the different BDTs together with the 𝑝 T of the leading 𝑏 -jetand of the second and third jets in the event, 𝐸 missT , S , min [ Δ 𝜙 ( jet − , p missT )] , and 𝑚 CT computed usingthe two leading jets. The most discriminating variables are min [ Δ 𝜙 ( jet − , p missT )] and the ratio of theleading jet 𝑝 T to 𝐻 T . The signal region selections are detailed in Table 5. A final discriminating variablecos 𝜃 ∗ 𝑏𝑏 [122] is considered: it is defined ascos 𝜃 ∗ 𝑏𝑏 = (cid:12)(cid:12)(cid:12)(cid:12) tanh Δ 𝜂 ( 𝑏 , 𝑏 ) (cid:12)(cid:12)(cid:12)(cid:12) . When excluding models of DM production, the SRDs are further divided into five equal bins of width 0 . [ , ] range of cos 𝜃 ∗ 𝑏𝑏 . When assessing the model-independent discovery significance against thebackground-only hypothesis, a single bin in cos 𝜃 ∗ 𝑏𝑏 defined by cos 𝜃 ∗ 𝑏𝑏 > . ( . ) is used in SRD-low(SRD-high). Event selections kinematically similar to those of the signal regions are defined for the control regions,which are characterised by negligible expected signal contributions for the BSM models considered.Contrary to the SRs, such CRs rely on the presence of either one or two same-flavour opposite-sign (SFOS)high-purity electrons or muons (generically denoted by ℓ ), and are defined such that their event yield isdominated by one specific SM production process. They are part of the likelihood fit, where they are key todetermining the value of the free-floating normalisation parameter associated with the MC prediction ofthe dominant background process.The SM background yield is dominated in most signal regions by 𝑍 + jets production followed by 𝑍 → 𝜈 ¯ 𝜈 .For each signal region, a corresponding control region (CRz) with two SFOS leptons is defined, with aninvariant mass of the lepton pair close the 𝑍 boson mass: the kinematic properties of the events populating13 able 5: SRD signal, control and validation region definitions. Pink cells for the control and validation regions’columns indicate which selections ensure that they are orthogonal to the corresponding SR. Variable SRD-low SRD-high CRzD-low CRzD-high VRzD-low VRzD-highTrigger plateau ( 𝑝 T ( 𝑗 ) −
20 GeV )( 𝐸 missT −
160 GeV ) > 𝑁 jets 𝑁 𝑏 -jets ≥ 𝑝 T ( 𝑗 ) [GeV] > 𝑝 T ( 𝑗 ) [GeV] > [ Δ 𝜙 ( jet − , p missT )] [rad] > . S > 𝑝 T ( 𝑗 )/ 𝐻 T > . 𝑝 T ( ℓ ) [GeV] – >
27 – 𝑝 T ( ℓ ) [GeV] – >
20 – 𝑚 T ( ℓ, p missT ) [GeV] – >
20 – 𝑚 ℓℓ [GeV] – [ , ] –˜ 𝐸 missT [GeV] – >
180 – 𝐸 missT [GeV] > < > 𝑤 𝑡𝑡 D-low > > 𝑤 𝑍 D-low > > [− . , ] – 𝑤 𝑊 D-low > > 𝑤 𝑡𝑡 D-high – > > 𝑤 𝑍 D-high – > − . > − . [− . , − . ] 𝑤 𝑊 D-high – > − .
05 – – > − . such a control region are expected to be very similar to those of events in the signal region. The fulldefinition of the control region selection needs to take into account the lower branching ratio of 𝑍 → ℓℓ relative to 𝑍 → 𝜈 ¯ 𝜈 : the selection is therefore close, but not identical, to that of the signal region. Afterhaving rejected events with high 𝐸 missT values to suppress contributions from dileptonic 𝑡 ¯ 𝑡 production, the 𝑝 T of the leptons is added vectorially to the p missT to mimic the expected missing transverse momentumspectrum of 𝑍 → 𝜈 ¯ 𝜈 events, and is denoted in the following by ˜ 𝐸 missT . All variables constructed from 𝐸 missT are recomputed using ˜ 𝐸 missT instead, including the BDT scores used in regions B and D. The selectionscorresponding to the control regions associated with SRA and SRB, named CRzA and CRzB, are shown inTables 2 and 3, respectively. Those corresponding to the control regions associated with SRD-low andSRD-high, named CRzD-low and CRzD-high, are shown in Table 5. In the case of SRC, one 𝑍 + jets controlregion is defined for each of SRC-2b, SRC-1b1v and SRC-0b1v: they are named CRzC-2b, CRzC-1b1vand CRzC-0b1v respectively, and their selection is shown in Table 6.The production of 𝑊 + jets and, to a lesser extent, top quarks, also results in important backgrounds in SRC.A set of control regions (CRt and CRw) is defined, all containing exactly one high-purity lepton in thefinal state. The zero-lepton signals considered for the signal region optimisation do not contaminate theone-lepton control regions. However, potential signal contributions from possible related BSM signalproduction (e.g. top squark pairs) or from third-generation leptoquarks are rejected by imposing an upperbound on the transverse mass of the lepton and the missing transverse momentum, 𝑚 T ( ℓ, p missT ) .A common top control region containing two 𝑏 -tagged jets and no TC-LVT vertex, named CRtC, and two14 able 6: SRC control region definitions. Pink cells for the control regions’ columns indicate which selections ensurethat they are orthogonal to the corresponding SR. Variable CRtC CRwC-1b1v CRwC-0b1v CRzC-2b CRzC-1b1v CRzC-0b1v 𝑗 not 𝑏 -tagged (cid:51) Number of high-purity leptons 1 2 SFOS 𝐻 T;3 [GeV] < 𝑝 T ( 𝑗 ) [GeV] > > > 𝑚 T ( ℓ, p missT ) [GeV] [ , ] − 𝑚 ℓℓ [GeV] − [ , ] 𝐸 missT [GeV] > < 𝐸 missT [GeV] − > > A > . > . − > . > . − 𝑚 𝑗 𝑗 [GeV] > > − − > − 𝑁 𝑏 -jets ≥ ≥ 𝑁 vtx − ≥ ≥ − ≥ ≥ 𝑚 vtx [GeV] − > . > . − > . > . 𝑝 vtxT [GeV] − > > − > > 𝑊 + jets control regions containing at least one TC-LVT vertex and, respectively, one (CRwC-1b1v) and no(CRwC-0b1v) 𝑏 -tagged jets are defined and summarised in Table 6. The definition of a 𝑊 + jets controlregion containing two 𝑏 -tagged jets was considered, but it was found too difficult to obtain a satisfactory 𝑊 + jets purity because of contamination from top quark production.Finally, a series of validation regions is defined, with the purpose of evaluating the quality of the backgroundestimation after the likelihood fit. They are characterised by an expected signal contamination below 10%,and they are obtained by inverting one or more signal region variable selections. They are defined inTables 2, 3, 4 and 5 The effects of several sources of systematic uncertainty on the signal and background estimates areintroduced in the likelihood fit through nuisance parameters that affect the expectation values of thePoissonian terms for each CR and SR bin. Each nuisance parameter’s probability density function isdescribed by a Gaussian distribution whose standard deviation corresponds to a specific experimental ortheoretical modelling uncertainty. The preferred value of each nuisance parameter is determined as part ofthe likelihood fit. The fits performed do not significantly alter or constrain the nuisance parameter valuesrelative to the fit input.Jet energy scale and resolution uncertainties are derived as a function of the jet 𝑝 T and 𝜂 , jet flavour,and pile-up conditions, using a combination of data and simulated events through measurements of jetresponse asymmetry for several processes, as detailed in Refs. [123, 124]. The impact of uncertainties onthe efficiencies and mis-tag rates of the 𝑏 -tagging algorithm is estimated by varying, as a function of 𝑝 T , 𝜂 and jet flavour, the scale factors used to correct the MC simulation, within a range reflecting the uncertaintyin their measurement [104]. Similarly, the impact of the uncertainty on the MC modelling of the efficiencyand fake rate for the TC-LVT vertex reconstruction is estimated by varying the corresponding scale factors15ithin the uncertainty associated with their determination (about 6% for the efficiency and 30% for thefake rate). Uncertainties connected with the lepton reconstruction and identification are included in the fit,and they are found to have a negligible impact. All uncertainties in the final-state object reconstruction arepropagated to the reconstruction of the 𝐸 missT , including an additional one taking into account uncertaintiesin the scale and resolution of the soft term.Uncertainties in the modelling of the SM background processes from MC simulation are taken into account.They are assumed to be fully correlated across signal regions, but uncorrelated between different processes.An alternative correlation model, where the uncertainties are assumed to be uncorrelated across signalregions, leads to a small increase in the final yield uncertainty, but to no significant change in the mass andcross-section limits obtained.Several contributions to the uncertainty in the theoretical modelling of 𝑡 ¯ 𝑡 and single top production areconsidered. The uncertainty due the choice of hard-scattering generator and matching scheme is evaluatedby comparing the nominal sample with a sample generated with MadGraph5_aMC@NLO and a showerstarting scale 𝜇 q = 𝐻 genT /
2. The uncertainty due to the choice of parton shower and hadronisation model isevaluated by a comparison with a sample generated with Powheg-Box interfaced to Herwig 7 [125, 126],using the H7UE set of tuned parameters [126]. Variations of the renormalisation and factorisation scales,the initial- and final-state radiation parameters and PDF sets are also considered [127]. Uncertainties onthe interference between the single top 𝑊𝑡 and 𝑡 ¯ 𝑡 production have negligible impact on the analysis resultsand are not included.Uncertainties in the modelling of 𝑍 + jets and 𝑊 + jets [128] are evaluated by using 7-point variations ofthe renormalisation and factorisation scales by factors of 0.5 and 2. The matching scale between thematrix element and parton shower calculation, and the resummation scale for soft gluon emission, arealso varied by factors of 0.5 and 2. As no Monte Carlo generator has been found to accurately describe 𝑍 + 𝑏 ¯ 𝑏 production in all observables [129], nor are these discrepancies accounted for by scale variations,an uncertainty due to the choice of generator is evaluated by comparing the nominal samples with thoseproduced using aMC@NLO 2.3.3 + Pythia. After constraints from the control regions these variationsare found to be relevant only in SRD, where modelling uncertainties dominate the systematic effect on theshape of the cos 𝜃 ∗ 𝑏𝑏 distribution.The impact of the most relevant background systematic uncertainties in the different signal regions is shownin Figure 2. Modelling uncertainties of the 𝑍 + jets process dominate the signal regions’ uncertainties,while the most important experimental uncertainties are those related to the jet energy scale. Different likelihood fits are run when assessing the accuracy of the SM background determination( background-only fit), when computing the 𝑝 -value of the SM-only hypothesis ( model-independent fit)and when evaluating the confidence level for excluding a specific BSM hypothesis ( model-dependent fit) [119].In the background-only fit, only the control regions are used in the likelihood, and the predicted post-fitlevel of background is compared with the observed yields in the corresponding VRs and SRs. Distinct fitsare run for the combination of SRA and SRB, for SRC and for SRD. In the SRA/SRB and SRD fits, onlythe normalisation of the 𝑍 + jets MC background prediction is left free to float. For SRC, a combined fitis run including SRC-2b, SRC-1b1v and SRC-0b1v: one common normalisation factor is applied to the16 c t m c t m c t m c t m c t m c t m c t m c t m c t m c t m c t
650 b i n0 b i n1 b i n2 b i n3 0b1 v v v v l o w l o w l o w l o w l o w i gh i gh i gh i gh i gh R e l a t i v e U n c e r t a i n t y TotalMC statisticalCR statisticalExperimentalTheoretical
ATLAS = 13 TeV, 139 fbs SRA SRB SRC SRD
Figure 2: Summary of the post-fit relative systematic uncertainties of the various signal region yields, also split bycomponent. 𝑡 ¯ 𝑡 and single-top contributions; one normalisation factor is applied to the 𝑊 + jets MC predictions in allregions with one or more 𝑏 -tagged jets, while an independent one is applied to those with no 𝑏 -tagged jets;and, finally, three independent normalisation factors are applied to the 𝑍 + jets MC predictions dependingon the number of 𝑏 -tagged jets.The background-only pre-fit event yields are compared with the observation for all CRs in Figure 3,while Figure 4 shows the background-only post-fit prediction compared with the observation for the VRs.Agreement is observed in the validation regions. The corresponding SR yield comparison is shown inFigure 5. The largest background contribution in all SRs arises from 𝑍 + jets production, while 𝑊 + jetsand top quark production contributions are minor, except in SRC. Other background sources are 𝑡 ¯ 𝑡 + 𝑊 / 𝑍 , 𝑡 ¯ 𝑡 + 𝐻 , and diboson production. Multijet production was found to be negligible in every region considered.No significant deviation from the background-only prediction is observed in any of the signal regions.An excess of about one standard deviation, covered by the largely correlated systematic uncertainty, isobserved in the SRD-low bins. Figures 6 and 7 show comparisons between the observed data and thepost-fit background predictions for relevant kinematic distributions for the SRs.The model-independent fit includes also the signal regions of Tables 2, 3, 4 and 5 in the likelihood asadditional constraining bins. To maximise the model-independent sensitivity to new phenomena, noadditional binning of 𝑚 eff (for SRA), 𝑤 XGB (for SRB), 𝐸 missT (SRC) or cos 𝜃 ∗ 𝑏𝑏 (in SRD) is considered. Inthe case of SRA, an additional selection on 𝑚 CT is added with respect to Table 2, corresponding to theSRAmctXi selections described in Section 5.2. A profile-likelihood-ratio statistic [131], where a signalof intensity 𝜇 sig is assumed to contribute to the signal region only, is used to assess the 𝑝 -value of the17 a Z b tt W v W v Z v Z v Z v Z l o w Z h i gh b k g µ E v en t s Z+jets W+jetstt OtherSingle top SM TotalData
ATLAS = 13 TeV, 139 fbs pre fit CRA CRB CRC CRD
Figure 3: Comparison between observed and pre-fit predicted background yields for the control regions. In theratio plot, 𝜇 bkg represents the value (with uncertainty) of the free-floating normalisation parameter for the dominantbackground process in each region obtained with the background-only fit. The “Other” category includes contributionsfrom diboson and 𝑡 ¯ 𝑡 + 𝑊 / 𝑍 / 𝐻 production. background-only hypothesis (corresponding to 𝜇 sig =
0) and to extract 𝑆 and 𝑆 , i.e. the expectedand observed 95% confidence level (CL) limits on 𝜇 sig using the CL S prescription. The limit 𝑆 is alsoconverted to a limit on the visible cross-section 𝜎 vis by dividing by the total integrated luminosity. Theresults are summarised in Table 7.Finally, the model-dependent fit includes the contributions of specific BSM models to all control and signalregions and considers the full binning defined in Sections 5.2, 5.3, 5.4 and 5.5, to determine 95% CLexclusion limits on BSM particle masses and, where relevant, couplings.The exclusion reach for the bottom squark pair production model is obtained by comparing, for each valueof the bottom squark and neutralino masses, the expected CL S value of the combined SRC fit and that of acombined fit to SRA and SRB: the one yielding the smaller expected CL S value is chosen to evaluate theexpected and observed CL S . The result is shown in Figure 8. A deviation of the observed limit from theexpected one is observed at (cid:16) 𝑚 ˜ 𝑏 , 𝑚 ˜ 𝜒 (cid:17) of about ( ,
700 GeV ) in Figure 8(a): it is due to a smalldeficit of events relative to the background prediction in SRAmct350, SRAmct450 and SRAmct550, wherethe signal contributions from models in this region of the parameter space is found to be significant. Thesmall excess of observed events in SRC-2b is instead responsible for the weaker than expected limit for abroad range of values around 𝑚 ˜ 𝑏 =
700 GeV and 𝑚 ˜ 𝜒 >
20 GeV in Figure 8(b). Finally, the transitionbetween regions where SRA, SRB or SRC dominate the sensitivity is responsible for the wiggles in theexpected and observed limits for 650 GeV < 𝑚 ˜ 𝑏 <
850 GeV in Figure 8(a).Bottom squark masses up to 1270 GeV are excluded for massless ˜ 𝜒 . SRC dominates the expected sensitivity18 b m bb m C T m C T m Z v v Z l o w Z h i gh − S i gn i f i c an c e E v en t s Z+jets W+jetstt OtherSingle top SM TotalData
ATLAS = 13 TeV, 139 fbs post fit VRA VRB VRC VRD
Figure 4: Comparison between observed and post-fit predicted background yields for the validation regions. Theratio plot represents the statistical significance [130] of the discrepancy between the observed and predicted value.The “Other” category includes contributions from diboson and 𝑡 ¯ 𝑡 + 𝑊 / 𝑍 / 𝐻 production. The shaded band representsthe total uncertainty of the background prediction.Table 7: Left to right: SM expectation from background-only fit for the model-independent regions, 95% CL upperlimits on the visible cross-section ( (cid:104) 𝜖 𝜎 (cid:105) ), on the observed ( 𝑆 ) and expected ( 𝑆 ) number of signal events.The last two columns indicate the 𝐶 𝐿 𝐵 value, i.e. the confidence level observed for the background-only hypothesis,and the discovery 𝑝 -value ( 𝑝 ( 𝑠 = ) ) capped at a value of 0.5. Signal channel Obs. SM exp. (cid:104) 𝜖 𝜎 (cid:105) [fb] 𝑆 𝑆 𝐶 𝐿 𝐵 𝑝 ( 𝑠 = ) ( 𝑍 )SRAmct250i 552 555 ±
75 0 .
94 131 133 + − .
48 0 . ( . ) SRAmct350i 104 120 ±
16 0 .
17 24 32 + − .
19 0 . ( ) SRAmct450i 23 27 . ± . .
06 8 . . + . − . .
17 0 . ( ) SRAmct550i 7 10 . ± . .
04 5 . . + . − . .
14 0 . ( ) SRAmct650i 8 5 . ± . .
06 8 . . + . − . .
73 0 . ( . ) SRB 22 20 . ± . .
11 15 . . + . − . .
54 0 . ( . ) SRC-2b 58 44 . ± . .
22 30 . . + . − . .
88 0 . ( . ) SRC-1b1v 43 51 ±
10 0 .
13 17 . . + . − . .
28 0 . ( ) SRC-0b1v 151 148 ±
25 0 .
37 51 50 + − .
54 0 . ( . ) SRD-low 497 381 ±
76 1 . + − .
91 0 . ( . ) SRD-high 320 242 ±
66 1 . + − .
82 0 . ( . ) up to Δ 𝑚 ( ˜ 𝑏 , ˜ 𝜒 ) ∼
70 GeV. The use of the TC-LVT algorithm largely contributed to the sensitivity forsmall Δ 𝑚 ( ˜ 𝑏 , ˜ 𝜒 ) , allowing the exclusion of bottom squark masses up to 660 GeV for Δ 𝑚 ( ˜ 𝑏 , ˜ 𝜒 ) =
10 GeV:19 c t m c t m c t m c t m c t m c t m c t m c t m c t m c t m c t
650 b i n0 b i n1 b i n2 b i n3 2b v v v v l o w l o w l o w l o w l o w i gh i gh i gh i gh i gh − S i gn i f i c an c e E v en t s Z+jets W+jetstt OtherSingle top SM TotalData
ATLAS = 13 TeV, 139 fbs post fit SRA SRB SRC SRD
Figure 5: Comparison between observed and background-only post-fit predicted background yields for the signalregions. The ratio plot represents the statistical significance of the discrepancy between the observed and predictedvalue. The “Other” category includes contributions from diboson and 𝑡 ¯ 𝑡 + 𝑊 / 𝑍 / 𝐻 production. The shaded bandrepresents the total uncertainty of the background prediction. for example, the minimum expected exclusion value of Δ 𝑚 ( ˜ 𝑏 , ˜ 𝜒 ) for 𝑚 ˜ 𝑏 =
600 GeV using SRC-2balone would be about 25 GeV.The combined fit to SRA and SRB is also used to set limits on the model where pairs of scalar third-generation down-type leptoquarks are produced. Limits at 95% CL are set on the branching ratio B (cid:16) LQ 𝑑 → 𝑡𝜏 (cid:17) = − B (cid:16) LQ 𝑑 → 𝑏𝜈 𝜏 (cid:17) as a function of the leptoquark mass. The result is shown inFigure 9. LQ 𝑑 masses up to 1260 GeV are excluded for B (cid:16) LQ 𝑑 → 𝑡𝜏 (cid:17) =
0, while the limit decreases to400 GeV if B (cid:16) LQ 𝑑 → 𝑡𝜏 (cid:17) = S value. Limits on the cross-section are provided for a 𝜒 mass of 1 GeVand unitary coupling of the mediator to the dark matter particles, separately for scenarios with a scalar or apseudoscalar mediator. In both cases, cross-sections exceeding between 5 and 300 times the predicted ratefor mediators with masses between 10 and 500 GeV are excluded.20
00 400 600 800 1000 1200 1400 ) [GeV] ,b (b CT m D a t a / S M −
10 110 E v en t s / G e V Z+jets ttW+jets OtherSingle top SM TotalData ) = 1300,1 GeV χ∼ ),m(b~m( ATLAS = 13 TeV, 139 fbs SRA post fit (a)
XGB w D a t a / S M −
10 110 E v en t s Z Wttbar Otherst SM TotalData ) = 700,600 GeV χ∼ ),m(b~m( ATLAS = 13 TeV, 139 fbs SRB post fit (b)
500 550 600 650 700 750 800 [GeV] missT E D a t a / S M −
10 110 E v en t s / G e V Z2b W1btt OtherSingle top SM TotalData ) = 500,485 GeV χ∼ ),m(b~m( ATLAS = 13 TeV, 139 fbs SRC 2b post fit (c)
400 450 500 550 600 650 700 750 800 [GeV] missT E D a t a / S M −
10 110 E v en t s / G e V W1b Z1bOther ttSingle top SM TotalData ) = 500,485 GeV χ∼ ),m(b~m( ATLAS = 13 TeV, 139 fbs SRC 1b1v post fit (d)
400 450 500 550 600 650 700 750 800 [GeV] missT E D a t a / S M −
10 110 E v en t s / G e V W0b Z0btt OtherSingle top SM TotalData ) = 500,485 GeV χ∼ ),m(b~m( ATLAS = 13 TeV, 139 fbs SRC 0b1v post fit (e)
Figure 6: Post-fit distribution of (a) 𝑚 CT in SRA; (b) 𝑤 XGB in SRB; and 𝐸 missT in (c) SRC-2b, (d) SRC-1b1v, (e)SRC-0b1v. Where relevant, the signal region selection is indicated by a black arrow. In each of (a)–(e) the lowerplot shows the ratios of the observed yields to the post-fit predicted background yields, with a red arrow indicatingwhen a ratio value is outside the displayed interval. The “Other” category includes contributions from diboson, and 𝑡 ¯ 𝑡 + 𝑊 / 𝑍 / 𝐻 production. The shaded band represents the total uncertainty of the background prediction. The last binincludes overflow events. .4 − − D lowZ w D a t a / S M −
10 110 E v en t s Z+jets ttW+jets Single topOther SM TotalData ) = (20, 1) GeV χ m(a, ) = (20, 1) GeV χ , φ m( ) = (200, 1) GeV χ , φ m( ATLAS = 13 TeV, 139 fbs post fit SRD low (a) − − − − D highZ w D a t a / S M −
10 110 E v en t s Z+jets W+jetstt OtherSingle top SM TotalData ) = (20, 1) GeV χ , φ m( ) = (20, 1) GeV χ m(a, ) = (200, 1) GeV χ , φ m( ATLAS = 13 TeV, 139 fbs post fit SRD high (b) bb * θ cos D a t a / S M −
10 110 E v en t s Z+jets ttW+jets Single topOther SM TotalData ) = (20, 1) GeV χ m(a, ) = (20, 1) GeV χ , φ m( ) = (200, 1) GeV χ , φ m( ATLAS = 13 TeV, 139 fbs post fit SRD low (c) bb * θ cos D a t a / S M −
10 110 E v en t s Z+jets W+jetstt OtherSingle top SM TotalData ) = (20, 1) GeV χ m(a, ) = (20, 1) GeV χ , φ m( ) = (200, 1) GeV χ , φ m( ATLAS = 13 TeV, 139 fbs post fit SRD high (d)
Figure 7: Post-fit distribution of (a) 𝑤 𝑍 D-low and (c) cos 𝜃 ∗ 𝑏𝑏 in SRD-low and (b) 𝑤 𝑍 D-high and (d) cos 𝜃 ∗ 𝑏𝑏 in SRD-high.Where relevant, the signal region selection is indicated by a black arrow. In each of (a)–(d) the lower plot shows theratios of the observed yields to the post-fit predicted background yields. The “Other” category includes contributionsfrom diboson and 𝑡 ¯ 𝑡 + 𝑊 / 𝑍 / 𝐻 production. The shaded band represents the total uncertainty of the backgroundprediction. The last bin includes the overflow events.
00 600 800 1000 1200 1400 1600 [GeV] b~ m [ G e V ] c~ m c~ = m b ~ m ) exp s – Expected Limit ( )
SUSYtheory s – Observed Limit ( (observed) -1 ATLAS 13 TeV, 36.1 fb c~ b fi b~ production ; b~ b~ , 95% CL -1 =13 TeV, 139 fbs ATLAS (a)
400 450 500 550 600 650 700 750 800 850 900 [GeV] b~ m ) [ G e V ] c~ , b ~ m ( D ) exp s – Expected Limit ( )
SUSYtheory s – Observed Limit ( -1 ATLAS 13 TeV, 36.1 fb not investigated c~ b fi b~ production ; b~ b~ , 95% CL -1 =13 TeV, 139 fbs ATLAS (b)
Figure 8: Exclusion limits at 95% CL on the masses of the ˜ 𝑏 and ˜ 𝜒 displayed in the (a) (cid:16) 𝑚 ˜ 𝑏 , 𝑚 ˜ 𝜒 (cid:17) and (b) (cid:16) 𝑚 ˜ 𝑏 , Δ 𝑚 ( ˜ 𝑏 , ˜ 𝜒 ) (cid:17) planes. The dashed line and the shaded band are the expected limit and its ± 𝜎 uncertainty,respectively. The thick solid line is the observed limit for the central value of the signal cross-section. The expectedand observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dottedlines show the effect on the observed limit of varying the signal cross-section by ± 𝜎 of the theoretical uncertainty.Regions excluded by previous analyses are shaded in light grey, while the region with Δ 𝑚 ( ˜ 𝑏 , ˜ 𝜒 ) <
400 500 600 700 800 900 1000 1100 1200 1300 1400 [GeV] LQ m ) [ % ] τ t → B ( L Q ) exp σ ± Expected Limit ( )
LQtheory σ ± Observed Limit (
ATLAS =13 TeV, 139 fbs pair production d3 LQ ν / b τ t → d3 LQ Figure 9: Exclusion limits at 95% CL on B (cid:16) LQ 𝑑 → 𝑡𝜏 (cid:17) as a function of the LQ 𝑑 mass for a model of LQ 𝑑 pairproduction. The dashed line and the shaded band are the expected limit and its ± 𝜎 uncertainty, respectively. Thethick solid line is the observed limit for the central value of the signal cross-section. ) [GeV] φ m( ( g = . ) σ / σ Limit (4 flav) σ ± Expected Limit σ ± Expected Limit (g=1) σ Theory unc. on
ATLAS = 13 TeV, 139 fbs )=1 GeV, 95% CL χ , m( χχ → φ , φ Scalar
SRD Combined (a) m(a) [GeV] ( g = . ) σ / σ Limit (4 flav) σ ± Expected Limit σ ± Expected Limit (g=1) σ Theory unc. on
ATLAS = 13 TeV, 139 fbs )=1 GeV, 95% CL χ , m( χχ → Pseudoscalar a, a
SRD Combined (b)
Figure 10: 95% CL limits on the cross-section for the models of dark matter production mediated by a (a) scalaror (b) pseudoscalar mediator. The dashed line and the shaded band are the expected limit and its ± 𝜎 and ± 𝜎 uncertainties, respectively. The thick solid line is the observed limit for the central value of the signal cross-section.The grey line shows the limit from previous results [44]. The hatched red band shows the uncertainty of the modelcross-section. Conclusions
The result of a search for an excess of events containing large missing transverse momentum and at leastone jet or decay vertex originating from the hadronisation and fragmentation of a 𝑏 -quark is reported.The analysis uses 139 fb − of 𝑝 𝑝 collisions at √ 𝑠 =
13 TeV collected by the ATLAS experiment at theLHC between 2015 and 2018. No excess above the Standard Model prediction is observed for any ofthe signal regions considered. Limits on the visible cross-section of a generic BSM contribution in thesignal regions have been set and range from 0.04 fb to 1.8 fb, depending on the signal region. The resultsare also used to set exclusion limits on specific BSM scenarios. In 𝑅 -parity-conserving SUSY scenarioswhere bottom squarks decay into a 𝑏 -quark and the lightest neutralino, the results are used to derive 95%CL exclusion limits as a function of the ˜ 𝑏 and ˜ 𝜒 masses. Bottom squark masses up to 1270 GeV areexcluded for massless ˜ 𝜒 , while the use of dedicated techniques to identify the secondary vertex from alow- 𝑝 T 𝑏 -hadron allows the exclusion of bottom squark masses up to 660 GeV for Δ 𝑚 ( ˜ 𝑏 , ˜ 𝜒 ) =
10 GeV.The search is also interpreted to exclude pair-produced LQ 𝑑 with masses up to 1260 GeV (400 GeV) for B (cid:16) LQ 𝑑 → 𝑡𝜏 (cid:17) = 𝑏 -quarks, cross-sections exceeding between 5 and300 times the predicted rate for mediators with masses between 10 and 500 GeV and unitary coupling tothe dark matter particles are excluded. All these limits extend substantially beyond the region of parameterspace excluded by similar searches with the ATLAS detector using 36 . − of 𝑝 𝑝 collisions. This is dueto several improvements in the analysis in addition to the increase in integrated luminosity; in particular theuse of multivariate techniques and the TC-LVT algorithm which provide enhanced sensitivity to modelswith small Δ 𝑚 ( ˜ 𝑏 , ˜ 𝜒 ) . Acknowledgements
We thank CERN for the very successful operation of the LHC, as well as the support staff from ourinstitutions without whom ATLAS could not be operated efficiently.We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF,Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada;CERN; ANID, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPOCR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS and CEA-DRF/IRFU,France; SRNSFG, Georgia; BMBF, HGF and MPG, Germany; GSRT, Greece; RGC and Hong Kong SAR,China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO,Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; MNE/IFA, Romania; JINR; MESof Russia and NRC KI, Russian Federation; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia;DST/NRF, South Africa; MICINN, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF andCantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom; DOEand NSF, United States of America. In addition, individual groups and members have received supportfrom BCKDF, CANARIE, Compute Canada, CRC and IVADO, Canada; Beijing Municipal Science &Technology Commission, China; COST, ERC, ERDF, Horizon 2020 and Marie Skłodowska-Curie Actions,European Union; Investissements d’Avenir Labex, Investissements d’Avenir Idex and ANR, France; DFGand AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF andthe Greek NSRF, Greece; BSF-NSF and GIF, Israel; La Caixa Banking Foundation, CERCA Programme25eneralitat 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. [132].
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De Salvo , U. De Sanctis ,M. De Santis , A. De Santo , J.B. De Vivie De Regie , D.V. Dedovich , A.M. Deiana ,J. Del Peso , Y. Delabat Diaz , F. Deliot , C.M. Delitzsch , M. Della Pietra , D. Della Volpe ,A. Dell’Acqua , L. Dell’Asta , M. Delmastro , C. Delporte , P.A. Delsart , S. Demers ,M. Demichev , G. Demontigny , S.P. Denisov , L. D’Eramo , D. Derendarz , J.E. Derkaoui ,F. Derue , P. Dervan , K. Desch , K. Dette , C. Deutsch , P.O. Deviveiros , F.A. Di Bello ,A. Di Ciaccio , L. Di Ciaccio , C. Di Donato , A. Di Girolamo , G. Di Gregorio ,A. Di Luca , B. Di Micco , R. Di Nardo , R. Di Sipio , C. Diaconu , F.A. 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 , 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 , 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 ,A. El Moussaouy , V. Ellajosyula , M. Ellert , F. Ellinghaus , A.A. Elliot , N. Ellis ,J. Elmsheuser , M. Elsing , D. Emeliyanov , A. Emerman , Y. Enari , 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 , D. Fassouliotis , M. Faucci Giannelli ,W.J. Fawcett , L. Fayard , O.L. Fedin , 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. 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 , P.M. Freeman , B. Freund , W.S. Freund ,E.M. Freundlich , D.C. Frizzell , D. Froidevaux , J.A. Frost , M. Fujimoto ,E. Fullana Torregrosa , T. Fusayasu , J. Fuster , A. Gabrielli , A. Gabrielli , 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 , M. Garcia-Sciveres , R.W. Gardner , S. Gargiulo ,C.A. Garner , V. Garonne , S.J. Gasiorowski , P. Gaspar , 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 ,36.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 , 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. Gramstad ,S. Grancagnolo , M. Grandi , V. Gratchev , P.M. Gravila , F.G. Gravili , C. Gray ,H.M. Gray , C. Grefe , 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 , J.G.R. Guerrero Rojas , F. Guescini , D. Guest , R. Gugel , A. Guida ,T. Guillemin , S. Guindon , J. Guo , Z. Guo , R. Gupta , S. Gurbuz , G. Gustavino , M. Guth ,P. Gutierrez , L.F. Gutierrez Zagazeta , C. Gutschow , C. Guyot , C. Gwenlan , C.B. Gwilliam ,E.S. Haaland , A. Haas , C. Haber , H.K. Hadavand , A. Hadef , M. Haleem , J. Haley ,J.J. Hall , G. Halladjian , G.D. Hallewell , K. Hamano , H. Hamdaoui , M. Hamer ,G.N. Hamity , K. Han , L. Han , L. Han , S. Han , Y.F. Han , K. Hanagaki , M. Hance ,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 , N.P. Hessey , H. Hibi , S. Higashino , E. Higón-Rodriguez , K. Hildebrand ,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 , J. Howarth , J. Hoya , M. Hrabovsky ,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 , M. 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 , N. Ilic , 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 , G. Jäkel , K.B. Jakobi , K. Jakobs ,T. Jakoubek , J. Jamieson , K.W. Janas , P.A. Janus , G. Jarlskog , A.E. Jaspan , N. Javadov ,T. Javůrek , M. Javurkova , F. Jeanneau , L. Jeanty , J. Jejelava , P. Jenni , S. Jézéquel ,J. Jia , Z. Jia , Y. Jiang , S. Jiggins , F.A. Jimenez Morales , J. Jimenez Pena , S. Jin ,37. Jinaru , O. Jinnouchi , H. Jivan , P. Johansson , K.A. Johns , C.A. Johnson , E. Jones ,R.W.L. 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 , D. Kar , K. Karava , M.J. Kareem , I. Karkanias ,S.N. Karpov , Z.M. Karpova , V. Kartvelishvili , A.N. Karyukhin , E. Kasimi , 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 , Y. Ke , J.M. Keaveney , R. Keeler , J.S. Keller ,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 , A. Kilgallon , 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 , L. Klein , M.H. Klein , M. Klein , U. Klein , P. Klimek , A. Klimentov , F. Klimpel ,T. Klingl , T. Klioutchnikova , F.F. Klitzner , P. Kluit , S. Kluth , E. Kneringer , 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 , K. Köneke , A.X.Y. Kong ,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 , R. Kowalewski ,W. Kozanecki , A.S. Kozhin , V.A. Kramarenko , G. Kramberger , D. Krasnopevtsev ,M.W. Krasny , A. Krasznahorkay , 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 , M. Kumar ,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 , S.D. Lawlor , M. Lazzaroni , B. Le ,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 , L.L. Leeuw , 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 , 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 , 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 ,38. Lleres , J. Llorente Merino , S.L. Lloyd , E.M. Lobodzinska , P. Loch , S. Loffredo ,T. Lohse , K. Lohwasser , M. Lokajicek , J.D. Long , R.E. Long , I. Longarini , L. Longo ,R. 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 ,S. 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 , J. Magro , D.J. Mahon , C. Maidantchik , A. Maio ,K. Maj , O. Majersky , S. Majewski , 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 , L. Marchese , G. Marchiori , M. Marcisovsky , L. Marcoccia ,C. Marcon , M. Marjanovic , Z. Marshall , M.U.F. Martensson , S. Marti-Garcia , 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 , T. Mathisen , A. Matic , N. Matsuzawa , J. Maurer , B. Maček ,D.A. Maximov , R. Mazini , I. Maznas , S.M. Mazza , C. Mc Ginn , 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 , 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 , F. Meloni ,A. Melzer , E.D. Mendes Gouveia , A.M. Mendes Jacques Da Costa , H.Y. Meng , L. Meng ,S. Menke , E. Meoni , 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 , M. 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 , G. Mokgatitswane , B. Mondal , S. Mondal , K. Mönig ,E. Monnier , A. Montalbano , J. Montejo Berlingen , M. Montella , F. Monticelli , N. Morange ,A.L. Moreira De Carvalho , M. Moreno Llácer , C. Moreno Martinez , P. Morettini ,M. Morgenstern , S. Morgenstern , D. Mori , M. Morii , M. Morinaga , V. Morisbak ,A.K. Morley , 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 ,D. Muenstermann , G.A. Mullier , J.J. Mullin , D.P. Mungo , J.L. Munoz Martinez ,F.J. Munoz Sanchez , P. Murin , W.J. Murray , A. Murrone , J.M. Muse , M. Muškinja ,C. Mwewa , A.G. Myagkov , A.A. Myers , G. Myers , J. Myers , M. Myska ,B.P. Nachman , O. Nackenhorst , A.Nag Nag , K. Nagai , K. Nagano , J.L. Nagle , E. Nagy ,A.M. Nairz , Y. 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Parsons , U. Parzefall , L. Pascual Dominguez , V.R. Pascuzzi ,J.M.P. Pasner , F. Pasquali , E. Pasqualucci , S. Passaggio , F. Pastore , P. Pasuwan ,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 , M. Penzin ,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 , P. Petroff ,F. Petrucci , M. Pettee , N.E. Pettersson , K. Petukhova , A. Peyaud , R. Pezoa ,L. Pezzotti , G. Pezzullo , T. Pham , P.W. Phillips , M.W. Phipps , G. Piacquadio ,E. Pianori , A. Picazio , R. Piegaia , D. Pietreanu , J.E. Pilcher , A.D. Pilkington ,M. Pinamonti , J.L. Pinfold , C. Pitman Donaldson , L. Pizzimento , A. Pizzini ,M.-A. Pleier , V. Plesanovs , V. Pleskot , E. Plotnikova , P. 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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 ,40. 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.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 ,A. Rozanov , Y. Rozen , X. Ruan , A.J. Ruby , 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 , E.B. Rye , A. Ryzhov , J.A. Sabater Iglesias , P. Sabatini ,L. Sabetta , 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 ,D. Salamani , G. Salamanna , A. Salnikov , J. Salt , A. Salvador Salas , D. Salvatore ,F. Salvatore , A. Salzburger , 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. 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 ,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 ,A. 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 , P. Sherwood , L. Shi , C.O. Shimmin , Y. Shimogama , M. Shimojima ,J.D. Shinner , I.P.J. Shipsey , S. Shirabe , M. Shiyakova , J. Shlomi , 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.V. Silva Oliveira , S.B. Silverstein , S. Simion , R. Simoniello , 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 , 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.Y. Song , A. Sopczak , A.L. Sopio ,F. Sopkova , S. Sottocornola , R. Soualah , A.M. Soukharev , Z. Soumaimi ,D. South , S. Spagnolo , M. Spalla , M. Spangenberg , F. Spanò , D. Sperlich ,41.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 , 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 , M. Svatos , M. Swiatlowski ,S.P. Swift , T. Swirski , A. Sydorenko , I. Sykora , M. Sykora , T. Sykora , D. Ta ,K. Tackmann , 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 , Y. Tayalati , 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 ,A. Tnourji , K. Todome , S. Todorova-Nova , S. Todt , J. Tojo , S. Tokár , K. Tokushuku ,E. Tolley , R. Tombs , 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 , 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 , M. Unal , A. Undrus ,G. Unel , F.C. Ungaro , K. Uno , J. Urban , P. Urquijo , G. Usai , Z. Uysal , V. Vacek ,B. Vachon , K.O.H. Vadla , T. Vafeiadis , 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 ,M. Verducci , C. Vergis , W. Verkerke , A.T. Vermeulen , J.C. Vermeulen , C. Vernieri ,P.J. Verschuuren , M.L. Vesterbacka , 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 , C. Wagner , P. Wagner , W. Wagner , 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 , J. Wang , P. Wang , R.-J. Wang ,42. Wang , R. Wang , S.M. Wang , S. Wang , T. Wang , W.T. 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 ,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 , 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 ,M. Yamatani , H. Yamauchi , 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 , P. Yin , K. Yorita ,K. Yoshihara , C.J.S. Young , C. Young , 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 , S. Zenz , S. Zerradi , 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 , 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 ,A. Zoccoli , K. Zoch , T.G. Zorbas , R. Zou , W. Zou , L. Zwalinski . 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. 43 ( 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. 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.44 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. ( 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 AdvancedStudy, 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.45 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.
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 of46merica.
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 ofAmerica. ( 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.47 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.
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.
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.48
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 Faculty of Physics, Sofia University, ’St. Kliment Ohridski’, Sofia; Bulgaria. 𝑢 Also at Giresun University, Faculty of Engineering, Giresun; Turkey. 𝑣 Also at Graduate School of Science, Osaka University, Osaka; Japan. 𝑤 Also at Hellenic Open University, Patras; Greece. 𝑥 Also at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona; Spain. 𝑦 Also at Institut für Experimentalphysik, Universität Hamburg, Hamburg; Germany. 𝑧 Also at Institute for Nuclear Research and Nuclear Energy (INRNE) of the Bulgarian Academy ofSciences, Sofia; Bulgaria. 𝑎𝑎 Also at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest;Hungary. 𝑎𝑏 Also at Institute of Particle Physics (IPP); Canada. 𝑎𝑐 Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku; Azerbaijan. 𝑎𝑑 Also at Instituto de Fisica Teorica, IFT-UAM/CSIC, Madrid; Spain. 𝑎𝑒 Also at Istanbul University, Dept. of Physics, Istanbul; Turkey. 𝑎 𝑓
Also at Joint Institute for Nuclear Research, Dubna; Russia. 𝑎𝑔 Also at Moscow Institute of Physics and Technology State University, Dolgoprudny; Russia. 𝑎ℎ Also at National Research Nuclear University MEPhI, Moscow; Russia. 𝑎𝑖 Also at Physics Department, An-Najah National University, Nablus; Palestine. 𝑎 𝑗
Also at Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg; Germany. 𝑎𝑘 Also at The City College of New York, New York NY; United States of America. 𝑎𝑙 Also at TRIUMF, Vancouver BC; Canada. 𝑎𝑚 Also at Universita di Napoli Parthenope, Napoli; Italy. 𝑎𝑛 Also at University of Chinese Academy of Sciences (UCAS), Beijing; China. ∗∗