Search for electroweak production of charginos and sleptons decaying into final states with two leptons and missing transverse momentum in √ s = 13 TeV pp collisions using the ATLAS detector

Eur. Phys. J. C (2020) 80:123 https://doi.org/10.1140/epjc/s10052-019-7594-6 Regular Article - Experimental Physics Search for electroweak production of charginos and sleptons decaying into final states with two leptons and missing transverse momentum in √s=13 TeV pp collisions using the ATLAS detector ATLAS Collaboration CERN, 1211 Geneva 23, Switzerland Received: 23 August 2019 / Accepted: 28 December 2019 © CERN for the benefit of the ATLAS collaboration 2020 Abstract A search for the electroweak production of charginos and sleptons decaying into final states with two electrons or muons is presented. The analysis is based on 139fb−1ofproton–protoncollisionsrecordedbytheATLAS detector at the Large Hadron Collider at √s=13 TeV. Three R-parity-conserving scenarios where the lightest neutralino is the lightest supersymmetric particle are considered: the production of chargino pairs with decays via either Wbosons or sleptons, and the direct production of slepton pairs. The analysis is optimised for the first of these scenarios, but the results are also interpreted in the others. No significant deviations from the Standard Model expectations are observed and limits at 95% confidence level are set on the masses of relevant supersymmetric particles in each of the scenarios. For a massless lightest neutralino, masses up to 420 GeV are excluded for the production of the lightest-chargino pairs assuming W-boson-mediated decays and up to 1 TeV for slepton-mediated decays, whereas for slepton-pair production masses up to 700 GeV are excluded assuming three generations of mass-degenerate sleptons. Contents 1 Introduction ...................... 2 SUSY scenarios .................... 3 ATLAS detector .................... 4 Data and simulated event samples .......... 5 Object identification ................. 6 Search strategy .................... 7 Background estimation and validation ........ 8 Systematic uncertainties ............... 9 Results ........................ 10 Conclusion ...................... References ......................... e-mail: [email protected] 1 Introduction Weak-scale supersymmetry (SUSY) [1–7] is a theoretical extension to the Standard Model (SM) that, if realised in nature, would solve the hierarchy problem [8–11] through the introduction of a new fermion (boson) supersymmetric partner for each boson (fermion) in the SM. In SUSY models that conserve R-parity [12], SUSY particles (sparticles) must be produced in pairs. The lightest supersymmetric particle (LSP) is stable and weakly interacting, thus potentially providing a viable candidate for dark matter [13,14]. Due to its stability, any LSP produced at the Large Hadron Collider (LHC) would escape detection and give rise to momentum imbalance in the form of missing transverse momentum (pmiss T) in the final state, which can be used to discriminate SUSY signals from the SM background. The superpartners of the SM Higgs boson and the electroweak gauge bosons, known as the higgsinos, winos and binos, are collectively labelled as electroweakinos. They mix to form chargino ( ˜χ± i,i=1,2) and neutralino ( ˜χ0 j,j= 1,2,3,4) mass eigenstates where the labels iand jrefer to states of increasing mass. Sparticle production cross-sections at the LHC are highly dependent on the sparticle masses as well as on the production mechanism. The coloured sparticles (squarks and gluinos) are strongly produced and have significantly larger production cross-sections than non-coloured sparticles of equal masses, such as the sleptons (superpartners of the SM leptons)andtheelectroweakinos.Ifgluinosandsquarkswere much heavier than low-mass electroweakinos, then SUSY production at the LHC would be dominated by direct electroweakino production. The latest ATLAS and CMS limits on squark and gluino production [15–23] extend well beyond the TeV scale, thus making electroweak production of sparticles a promising and important probe in searches for SUSY at the LHC. 0123456789().: V,-vol 123 123 Page 2 of 33 Eur. Phys. J. C (2020) 80:123 (a) ˜χ± 1 ˜χ∓ 1 ˜ ˜ν ˜ ˜ν p p ˜χ0 1 ˜χ0 1 (b) (c) Fig. 1 Diagrams of the supersymmetric models considered, with two leptons and weakly interacting particles in the final state: a ˜χ+ 1˜χ− 1production with W-boson-mediated decays, b˜χ+ 1˜χ− 1production with slepton/sneutrino-mediated-decays and cslepton pair production. In the model with intermediate sleptons, all three flavours (˜e,˜μ,˜τ) are included, while only ˜eand ˜μare included in the direct slepton model. In the final state, stands for an electron or muon, which can be produced directly or, in the case of a and bonly, via a leptonically decaying τ-lepton with additional neutrinos This paper presents a search for the electroweak production of charginos and sleptons decaying into final states with two charged leptons (electrons and/or muons) using 139 fb−1of proton–proton collision data recorded by the ATLAS detector at the LHC at √s=13 TeV. The analysis is optimised to target the direct production of ˜χ+ 1˜χ− 1, where each chargino decays into the LSP ˜χ0 1and an on-shell Wboson. Signal events are characterised by the presence of exactly two isolated leptons (e,μ) with opposite electric charge, and significant pmiss T(the magnitude of which is referred to as Emiss T), expected from neutrinos and LSPs in the final states. The same analysis strategy is also applied to two other searches. One of them is the search for the direct productionof ˜χ+ 1˜χ− 1,whereeachcharginodecaysintoaslepton (charged slepton ˜ or sneutrino ˜ν) via the emission of a lepton (neutrino νor charged lepton ) and the slepton itself decays into a lepton and the LSP. The other one is the search for the direct pair production of sleptons where each slepton decays into a lepton and the LSP. The search described here significantly extends the areas of the parameter space beyond those excluded by previous searches by ATLAS [24,25] and CMS [26–31]inthesame channels. After a description of the considered SUSY scenarios in Sect. 2and of the ATLAS detector in Sect. 3, the data and simulated Monte Carlo (MC) samples used in the analysis are detailed in Sect. 4. Sections 5and 6present the event reconstruction and the search strategy. The SM background estimation and the systematic uncertainties are discussed in Sects.7and 8,respectively.Finally, theresultsand theirinterpretations are reported in Sect. 9. Section 10 summarises the conclusions. 2 SUSY scenarios The design of the analysis and the interpretation of results are based on simplified models [32], where the masses of relevant sparticles (in this case the ˜χ± 1,˜ ,˜νand ˜χ0 1)are the only free parameters. The ˜χ± 1is assumed to be pure wino and two possible decay modes are considered. The first is a decay into the ˜χ0 1via emission of a Wboson, which may decay into an electron or muon plus neutrino(s) either directly or through the emission of a leptonically decaying τ-lepton (Fig. 1a). The second decay mode proceeds via a slepton–neutrino/sneutrino–lepton pair (Fig. 1b). In this case it is assumed that the scalar partners of the left-handed charged leptons and neutrinos are also light and thus accessible in the sparticle decay chains. It is also assumed they are mass-degenerate, and their masses are chosen to be midway between the mass of the chargino and that of the ˜χ0 1, which is pure bino. Equal branching ratios for the three slepton flavours are assumed and charginos decay into charged sleptons or sneutrinos with a branching ratio of 50% to each. Lepton flavour is conserved in all models. In models with direct ˜ ˜ production (Fig. 1c), each slepton decays into a lepton and a ˜χ0 1with a 100% branching ratio. Only ˜eand ˜μare considered in these models, and different assumptions about the masses of the superpartners of the left-handed and right-handed charged leptons, ˜eL,˜eR,˜μLand ˜μR, are considered. 3 ATLAS detector The ATLAS detector [33] at the LHC is a general-purpose detector with a forward–backward symmetric cylindrical geometry and an almost complete coverage in solid angle 123 Eur. Phys. J. C (2020) 80:123 Page 3 of 33 123 around the collision point.1It consists of an inner tracking detectorsurroundedbyathinsuperconductingsolenoid,electromagnetic and hadronic calorimeters, and a muon spectrometer incorporating three large superconducting toroid magnets. The inner-detector (ID) system is immersed in a 2 T axial magnetic field produced by the solenoid and provides charged-particle tracking in the range |η|<2.5. It consists of a high-granularity silicon pixel detector, a silicon microstrip tracker and a transition radiation tracker, which enables radially extended track reconstruction up to |η|=2.0. The transition radiation tracker also provides electron identification information. During the first LHC long shutdown, a new tracking layer, known as the Insertable B-Layer [34,35], was added with an average sensor radius of 33 mm from the beam pipe to improve tracking and b-tagging performance. The calorimeter system covers the pseudorapidity range |η|<4.9. Within the region |η|<3.2, electromagnetic calorimetry is provided by barrel and endcap highgranularity lead/liquid-argon (LAr) sampling calorimeters. Hadronic calorimetry is provided by an iron/scintillatortile sampling calorimeter for |η|<1.7, and two copper/LAr hadronic endcap calorimeters. The solid angle coverage is completed with forward copper/LAr and tungsten/LAr calorimeter modules optimised for electromagnetic and hadronic measurements, respectively. The muon spectrometer (MS) comprises separate trigger and high-precision tracking chambers measuring the deflection of muons in a magnetic field generated by superconducting air-core toroids. The precision chamber system covers the region |η|<2.7 with three layers of monitored drift tubes, complemented by cathode strip chambers in the forward region, where the background is higher. The muon trigger system covers the range |η|<2.4 with resistive plate chambers in the barrel, and thin gap chambers in the endcap regions. A two-level trigger system is used to select events. There is a low-level hardware trigger implemented in custom electronics, which reduces the incoming data rate to a design value of 100 kHz using a subset of detector information, and ahigh-levelsoftwaretriggerthatselectsinterestingfinal-state events with algorithms accessing the full detector information, and further reduces the rate to about 1 kHz [36]. 1ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP) in the centre of the detector and the z-axis along the beam pipe. The x-axis points from the IP to the centre of the LHC ring, and the y-axis points upwards. Cylindrical coordinates (r,φ) are used in the transverse plane, φbeing the azimuthal angle around the z-axis.The pseudorapidity isdefined in termsof the polarangleθas η= −ln tan(θ/2). Rapidity is defined as y=0.5ln[(E+pz)/(E−pz)], where Eand pzdenote the energy and the component of the particle momentum along the beam direction, respectively. 4 Data and simulated event samples The analysis uses data collected by the ATLAS detector during pp collisions at a centre-of-mass energy of √s=13 TeV from 2015 to 2018. The average number μof additional pp interactions per bunch crossing (pile-up) ranged from 14 in 2015 to about 38 in 2017–2018. After data-quality requirements, the data sample amounts to a total integrated luminosity of 139 fb−1. The uncertainty in the combined 2015– 2018 integrated luminosity is 1.7% [37], obtained using the LUCID-2 detector [38] for the primary luminosity measurements. Candidateeventswereselectedbyatriggerthatrequiredat least two leptons (electrons and/or muons). The trigger-level thresholds for the transverse momentum, pT, of the leptons involved in the trigger decision were different according to the data-taking periods. They were in the range 8–22 GeV for data collected in 2015 and 2016, and 8–24 GeV for data collected in 2017 and 2018. These thresholds are looser than those applied in the lepton offline selection to ensure that trigger efficiencies are constant in the relevant phase space. Simulated event samples are used for the SM background estimate and to model the SUSY signal. The MC samples were processed through a full simulation of the ATLAS detector [39] based on Geant 4[40] or a fast simulation using a parameterisation of the ATLAS calorimeter response and Geant 4 for the other components of the detector [39]. They were reconstructed with the same algorithms as those used for the data. To compensate for differences between data and simulation in the lepton reconstruction efficiency, energy scale, energy resolution and modelling of the trigger [41,42], and in the b-tagging efficiency [43], correction factors are derived from data and applied as weights to the simulated events. All SM backgrounds used are listed in Table 1along with the relevant parton distribution function (PDF) sets, the configuration of underlying-event and hadronisation parameters (tune), and the cross-section order in αsused to normalise the event yields for these samples. Further information on the ATLAS simulations of t¯ t, single top (Wt), multiboson and boson plus jet processes can be found in the relevant public notes [44–47]. The SUSY signal samples were generated from leadingorder (LO) matrix elements with up to two extra partons using MadGraph5_aMC@NLO 2.6.1 [48] interfaced to Pythia 8.186 [49], with the A14 tune [50], for the modelling of the SUSY decay chain, parton showering, hadronisation and the description of the underlying event. Parton luminosities were provided by the NNPDF2.3LO PDF set [51]. Jet–parton matching was performed following the CKKW-L prescription [52], with a matching scale set to one quarter of the mass of the pair-produced SUSY particles. Signal crosssections were calculated to next-to-leading order (NLO) in 123 123 Page 4 of 33 Eur. Phys. J. C (2020) 80:123 αsadding the resummation of soft gluon emission at nextto-leading-logarithm accuracy (NLO+NLL) [53–59]. The nominal cross-sections and their uncertainties were taken from an envelope of cross-section predictions using different PDF sets and factorisation and renormalisation scales, as described in Ref. [60]. The cross-section for ˜χ+ 1˜χ− 1production, each with a mass of 400 GeV, is 58.6±4.7fb, while the cross-section for ˜ ˜ production, each with a mass of 500 GeV, is 0.47 ±0.03 fb for each generation of lefthanded sleptons and 0.18 ±0.01 fb for each generation of right-handed sleptons. Inelastic pp interactions were generated and overlaid onto the hard-scattering process to simulate the effect of multiple proton–proton interactions occurring during the same (in-time) or a nearby (out-of-time) bunch crossing. These were produced using Pythia 8.186 and EvtGen [61] with the NNPDF2.3LO set of PDFs [51] and the A3 tune [62]. The MC samples were reweighted so that the distribution of the average number of interactions per bunch crossing reproduces the observed distribution in the data. 5 Object identification Leptons selected for analysis are categorised as baseline or signal leptons according to various quality and kinematic selection criteria. Baseline objects are used in the calculation of missing transverse momentum, to resolve ambiguities between the analysis objects in the event and in the fake/nonprompt (FNP) lepton background estimation described in Sect. 7. Leptons used for the final event selection must satisfy more stringent signal requirements. Baseline electron candidates are reconstructed using clusters of energy deposits in the electromagnetic calorimeter that are matched to an ID track. They are required to satisfy a Loose likelihood-based identification requirement [41], and to have pT>10 GeV and |η|<2.47. They are also required to be within |z0sin θ|= 0.5 mm of the primary vertex,2where z0isthelongitudinal impact parameterrelativetotheprimary vertex. Signal electrons are required to satisfy a Tight identification requirement [41] and the track associated with the signal electron is required to have |d0|/σ(d0)<5, where d0is the transverse impact parameter relative to the reconstructed primary vertex and σ(d0)is its error. Baseline muon candidates are reconstructed in the pseudorapidity range |η|<2.7 from MS tracks matching ID tracks. They are required to have pT>10 GeV, to be within |z0sin θ|= 0.5 mm of the primary vertex and to satisfy the Medium identification requirements defined in Ref. [42]. The 2The primary vertex is defined as the vertex with the highest scalar sum of the squared transverse momentum of associated tracks with pT >500 MeV. Table 1 Simulated background event samples with the corresponding matrix element and parton shower (PS) generators, cross-section order in αsused to normalise the event yield, underlying-event tune and the generator PDF sets used Physics process Generator Parton shower Normalisation Tune PDF (generator) PDF (PS) t¯ tPowhegBox v2 [63–66]Pythia 8.230 [67] NNLO+NNLL [68]A14[50] NNPDF3.0NLO [69] NNPDF2.3LO [51] t¯ t+V(V=W,Z)MadGraph5_aMC@NLO [48]Pythia 8.210 [67]NLO[48,70] A14 NNPDF3.0NLO NNPDF2.3LO t¯ t+WW MadGraph5_aMC@NLO Pythia 8.186 [49]NLO[48] A14 NNPDF2.3LO NNPDF2.3LO tZ,t¯ tt¯ t,t¯ tt MadGraph5_aMC@NLO Pythia 8.230 NLO [48] A14 NNPDF3.0NLO NNPDF2.3LO Single top (Wt)PowhegBox v2 [64,65,71]Pythia 8.230 NLO+NNLL [72,73] A14 NNPDF3.0NLO NNPDF2.3LO Z/γ ∗(→ll)+jets Sherpa 2.2.1 [74–76]Sherpa 2.2.1 NNLO [77]Sherpa default [76] NNPDF3.0NNLO [69] NNPDF3.0NNLO [69] WW,WZ,ZZ PowhegBox v2 [64,65,78,79]Pythia 8.210 NLO [46,78,79] AZNLO [80] CT10 NLO [81] CTEQ6L1[82] VVV(V=W,Z)Sherpa 2.2.2 [46,74,75]Sherpa 2.2.2 NLO [46,75]Sherpa default [46] NNPDF3.0NNLO NNPDF3.0NNLO Higgs boson PowhegBox v2 [64,65,83–86]Pythia 8.186 NLO [87] AZNLO NNPDF3.0NLOaCTEQ6L1 aThe PDF4LHC15 set have been used for some Higgs production processes, as via gluon-gluon fusion, VBF and VH 123 Eur. Phys. J. C (2020) 80:123 Page 5 of 33 123 Medium identification criterion defines requirements on the number of hits in the different ID and MS subsystems, and on the significance of the charge-to-momentum ratio q/p. Finally, the track associated with the signal muon must have |d0|/σ(d0)<3. Isolationcriteriaareappliedtosignalelectronsandmuons. The scalar sum of the pTof tracks inside a variable-size cone around the lepton (excluding its own track), must be less than 15% of the lepton pT. The track isolation cone size for electrons (muons) R=(η)2+(φ)2is given by the minimum of R=10 GeV/pTand R=0.2(0.3). In addition, for electrons (muons) the sum of the transverse energy of the calorimeter energy clusters in a cone of R= 0.2 around the lepton (excluding the energy from the lepton itself) must be less than 20% (30%) of the lepton pT.For electrons with pT>200 GeV these isolation requirements arenotapplied,andinsteadanupperlimitofmax(0.015×pT, 3.5GeV)is placed on the transverseenergyof the calorimeter energy clusters in a cone of R=0.2 around the electron. Jets are reconstructed from topological clusters of energy in the calorimeter [88] using the anti-ktjet clustering algorithm [89] as implemented in the FastJet package [90], with a radius parameter R=0.4. The reconstructed jets are then calibrated by the application of a jet energy scale derived from 13 TeV data and simulation [91]. Only jet candidates with pT>20 GeV and |η|<2.4 are considered,3although jets with |η|<4.9 are included in the missing transverse momentum calculation and are considered when applying the procedure to remove reconstruction ambiguities, which is described later in this section. To reduce the effects of pile-up, for jets with |η|≤2.5 and pT<120 GeV a significant fraction of the tracks associated with each jet are required to have an origin compatible with the primary vertex, as defined by the jet vertex tagger [92]. This requirement reduces jets from pile-up to 1%, with an efficiency for pure hard-scatter jets of about 90%. For jets with |η|>2.5 and pT<60 GeV, pile-up suppression is achieved through the forward jet vertex tagger [93], which exploits topological correlations between jet pairs. Finally, events containing a jet that does not satisfy the jet-quality requirements [94,95] are rejected to remove events impacted by detector noise and non-collision backgrounds. The MV2C10 boosted decision tree algorithm [43] identifies jets containing b-hadrons (‘b-jets’) by using quantities such as the impact parameters of associated tracks, and wellreconstructed secondary vertices. A selection that provides 85% efficiency for tagging b-jets in simulated t¯ tevents is used. The corresponding rejection factors against jets originating from c-quarks, from τ-leptons, and from light quarks and gluons in the same sample at this working point are 2.7, 6.1 and 25, respectively. 3Hadronic τ-lepton decay products are treated as jets. To avoid the double counting of analysis baseline objects, a procedure to remove reconstruction ambiguities is applied as follows: •jet candidates within R=y2+φ2= 0.2 of an electron candidate are removed; •jetswithfewerthanthreetracksthatliewithinR=0.4 of a muon candidate are removed; •electrons and muons within R=0.4 of the remaining jets are discarded, to reject leptons from the decay of bor c-hadrons; •electron candidates are rejected if they are found to share an ID track with a muon. The missing transverse momentum (pmiss T), which has the magnitude Emiss T, is defined as the negative vector sum of the transverse momenta of all identified physics objects (electrons,photons, muons andjets).Low-momentumtracks from the primary vertex that are not associated with reconstructed analysis objects (the ‘soft term’) are also included in the calculation, and the Emiss Tvalue is adjusted for the calibration of the selected physics objects [96]. Linked to the Emiss Tvalue is the‘object-based Emiss Tsignificance’,referredtoas Emiss Tsignificance in this paper, that helps to separate events with true Emiss T(arising from weakly interacting particles) from those where it is consistent with particle mismeasurement, resolution or identification inefficiencies. On an event-by-event basis, given the full event composition, Emiss Tsignificance evaluates the p-value that the observed Emiss Tis consistent with the null hypothesis of zero real Emiss T, as further detailed in Ref. [97]. 6 Search strategy Events are required to have exactly two oppositely charged signal leptons 1and 2, both with pT>25 GeV. To remove contributions from low-mass resonances and to ensure good modelling of the SM background in all relevant regions, the invariant mass of the two leptons must be m12>100 GeV. Events are further required to have no reconstructed b-jets, to suppress contributions from processes with top quarks. Selected events must also satisfy Emiss T>110 GeV and Emiss T significance >10. The stransverse mass mT2 [98,99] is a kinematic variable used to bound the masses of a pair of particles that are assumed to have each decayed into one visible and one invisible particle. It is defined as mT2(pT,1,pT,2,pmiss T) =min qT,1+qT,2=pmiss T max[mT(pT,1,qT,1), mT(pT,2,qT,2)], 123 123 Page 6 of 33 Eur. Phys. J. C (2020) 80:123 where mTindicates the transverse mass,4pT,1and pT,2are the transverse-momentum vectors of the two leptons, and qT,1and qT,2are vectors with pmiss T=qT,1+qT,2. The minimisation is performed over all the possible decompositions of pmiss T.Fort¯ tor WW decays, assuming an ideal detector with perfect momentum resolution, mT2(pT,1,pT,2,pmiss T) hasakinematicendpointatthemass ofthe Wboson[99].Signal models with significant mass splittings between the ˜χ± 1 and the ˜χ0 1feature mT2 distributions that extend beyond the kinematic endpoint expected from the dominant SM backgrounds. Therefore, events are required to have high mT2 values. Events are separated into ‘same flavour’ (SF) events, i.e. e±e∓and μ±μ∓, and ‘different flavour’ (DF) events, i.e. e±μ∓, since the two classes of events have different background compositions. SF events are required to have a dilepton invariant mass far from the Zpeak, m12>121.2GeV, to reduce diboson and Z+jets backgrounds. Events are further classified by the multiplicity of nonb-tagged jets (nnon-b-tagged jets), i.e. the number of jets not identified as b-jets by the MV2C10 boosted decision tree algorithm. All events are required to have no more than one non-b-tagged jet. Following the classification of the events, twosetsofsignalregions(SRs)aredefined:asetofexclusive, ‘binned’ SRs, to maximise model-dependent search sensitivity, and a set of ‘inclusive’ SRs, to be used for modelindependent results. Among the second set of SRs two are fully inclusive, with a different lower bound on mT2 to target different chargino or slepton mass regions, while two have both lower and upper bounds on mT2 to target models with lower endpoints. The definitions of these regions are shown in Table 2. Each SR is identified by the lepton flavour combination (DF or SF), the number of non-b-tagged jets (0J,1J) and the range of the mT2 interval. 7 Background estimation and validation The SM backgrounds can be classified into irreducible backgrounds, from processes with prompt leptons, and reducible backgrounds, which contain one or more FNP leptons. The main irreducible backgrounds come from SM diboson (WW, WZ,ZZ) and top-quark (t¯ tand Wt) production. These are estimated from simulated events, normalised using a simultaneous likelihood fit to data (as described in Sect. 9) in dedicated control regions (CRs). The CRs are designed to be enriched in the particular background process under study while remaining kinematically similar to the SRs. The nor4The transverse mass is defined as mT= 2×|pT,1|×|pT,2|×(1−cos(φ)),whereφ is the difference in azimuthal angle between the particles with transverse momenta pT,1and pT,2. Table 2 The definitions of the binned and inclusive signal regions. Relevant kinematic variables are defined in the text. The bins labelled ‘DF’ or ‘SF’ refer to signal regions with different lepton flavour or same lepton flavour pair combinations, respectively, and the ‘0J’ and ‘1J’ labels refer to the multiplicity of non-b-tagged jets malisations of the relevant backgrounds are then validated in a set of validation regions (VRs), which are not used to constrain the fit, but are used to verify that the data and predictions, in terms of the yields and of the shapes of the relevant kinematic distributions, agree within uncertainties in regions of the phase space kinematically close to the SRs. Three CRs are used, as defined in Table 3: CR-WW, targeting WW production; CR-VZ, targeting WZand ZZproduction, which are normalised by using a single parameter in the likelihood fit to the data; and CR-top, targeting t¯ tand singletop-quark production, which are also normalised by using a single parameter in the likelihood fit to the data. A single normalisation parameter is used for t¯ tand single-top-quark (Wt) production as the relative amounts of each process are consistent within uncertainties in the CR and SRs. The definitions of the VRs are shown in Table 4.Forthe WW background two validation regions are considered (VRWW-0J and VR-WW-1J), according to the multiplicity of non-b-tagged jets in the event. As contributions from topquark backgrounds in VR-WW-0J and VR-WW-1J are not negligible, three VRs are defined for this background. VRtop-low requires a similar mT2 range as VR-WW-0J and VRWW-1J, thus allowing the modellingoftop-quarkproduction at lower values of mT2 to be validated. VR-top-high requires mT2 >100 GeV and provides validation in the high mT2 region where the SRs are also defined. Finally, VR-top-WW requires the same Emiss T,Emiss Tsignificance and mT2 ranges as CR-WW and provides validation of the modelling of topquark production in this region. 123 Eur. Phys. J. C (2020) 80:123 Page 7 of 33 123 To obtain CRs and VRs of reasonable purity in WW production, CR-WW, VR-WW-0J and VR-WW-1J all require lowermT2 valuesthan theSRs.To validatethetailsof themT2 distribution,amethodsimilartotheonedescribedinRef.[31] is used. Three-lepton events, purely from WZ production, are selected by requiring the absence of b-tagged jets and the presence of one same-flavour opposite-sign (SFOS) lepton pairwithaninvariantmassconsistentwiththatofthe Zboson (|m12−mZ|<10 GeV). To avoid overlaps with portions of the phase space relevant for other searches, three-lepton events are also required to satisfy Emiss T∈[40,170]GeV. To emulate the signal regions, events are also required to have zero or one non-b-tagged jet. The transverse momentum of the lepton in the SFOS pair that has the same charge as the remaining lepton is added to the pmiss Tvector, to mimic a neutrino. The mT2 value can then be calculated using the remaining two leptons in the event. With this selection, there is a good agreement between the shapes of the mT2 distributions observedindata and simulation,andno additional systematic uncertainty is applied to the WW background at high mT2. Sub-dominant irreducible SM background contributions come from Drell–Yan, t¯ t+Vand Higgs boson production. These processes, jointly referred to as ‘Other backgrounds’ (or ‘Others’ in the Figures) are estimated directly from simTable 3 Control region definitions for extracting normalisation factors for the dominant background processes. ‘DF’ or ‘SF’ refer to signal regions with different lepton flavour or same lepton flavour pair combinations, respectively Region CR-WW CR-VZ CR-top Lepton flavour DF SF DF nb-tagged jets =0=0=1 nnon-b-tagged jets =0=0=0 mT2 (GeV) ∈[60, 65] >120 >80 Emiss T(GeV) ∈[60, 100] >110 >110 Emiss Tsignificance ∈[5, 10] >10 >10 m12(GeV) >100 ∈[61.2, 121.2] >100 ulation using the samples described in Sect. 4.Theremaining background from FNP leptons is estimated from data using the matrix method (MM) [100]. This method considerstwotypesof leptonidentificationcriteria:‘signal’leptons, corresponding to leptons passing the full analysis selection, and ‘baseline’ leptons, as defined in Sect. 5. Probabilities for prompt leptons satisfying the baseline selection to also satisfy the signal selection are measured as a function of lepton pTand ηin dedicated regions enriched in Zboson processes. Similar probabilities for FNP leptons are measured in events dominated by leptons from the decays of heavy-flavour hadrons and from photon conversions. These probabilities are used in the MM to extract data-driven estimates for the FNP lepton background in the CRs, VRs, and Table 5 Observed event yields and predicted background yields from the fit in the CRs. For backgrounds with a normalisation extracted from thefit,theyieldexpectedfromthesimulationbeforethefitisalsoshown. ‘Otherbackgrounds’include thenon-dominant backgroundsources, i.e. t¯ t+V, Higgs boson and Drell–Yan events. A ‘–’ symbol indicates that the background contribution is negligible Region CR-WW CR-VZ CR-top Observed events 962 811 321 Fitted backgrounds 962 ±31 811 ±28 321 ±18 Fitted WW 670 ±60 19.1±1.95.5±2.7 Fitted WZ 11.8±0.7 188 ±70.32 ±0.15 Fitted ZZ 0.29 ±0.06 577 ±23 − Fitted t¯ t170 ±50 1.8±1.3 270 ±16 Fitted single top 88 ±80.65 ±0.35 38.6±2.6 Other backgrounds 0.17 ±0.06 19 ±72.21 ±0.20 FNP leptons 21 ±85 +6 −54.2±2.2 Simulated WW 528 15.1 4.3 Simulated WZ 9.9 158 0.27 Simulated ZZ 0.24 487 – Simulated t¯ t210 2.2 327 Simulated single top 107 0.8 46.7 Table 4 Validation region definitions used to study the modelling of the SM backgrounds. ‘DF’ or ‘SF’ refer to regions with different lepton flavour or same lepton flavour pair combinations, respectively Region VR-WW-0J VR-WW-1J VR-VZ VR-top-low VR-top-high VR-top-WW Lepton flavour DF DF SF DF DF DF nb-tagged jets =0=0=0=1=1=1 nnon-b-tagged jets =0=1=0=0=1=1 mT2 (GeV) ∈[65, 100] ∈[65, 100] ∈[100, 120] ∈[80, 100] >100 ∈[60, 65] Emiss T(GeV) >60 >60 >110 >110 >110 ∈[60, 100] Emiss Tsignificance >5>5>10 ∈[5, 10] >10 ∈[5, 10] m12(GeV) >100 >100 ∈[61.2, 121.2] >100 >100 >100 123 123 Page 8 of 33 Eur. Phys. J. C (2020) 80:123 Events / 20 GeV 1 10 2 10 3 10 4 10 5 10 6 10 ATLAS -1 =13 TeV, 139 fbs CR-VZ Data SM WW WZ ZZ tt Single Top FNP leptons Others )=(400,200) GeV 0 1 χ ∼ , ± l ~ m( )=(300,50) GeV 0 1 χ ∼ , ± 1 χ ∼ m( )=(600,300,1) GeV 0 1 χ ∼ , ± l ~ , ± 1 χ ∼ m( [GeV] T2 m 120 140 160 180 200 220 240 260 280 300 Data / SM 0.5 1 1.5 (a)mT2 distribution in CR-VZ Events / 20 GeV 1 10 2 10 3 10 4 10 ATLAS -1 =13 TeV, 139 fbs CR-top Data SM WW WZ tt Single Top FNP leptons Others )=(400,200) GeV 0 1 χ ∼ , ± l ~ m( )=(300,50) GeV 0 1 χ ∼ , ± 1 χ ∼ m( )=(600,300,1) GeV 0 1 χ ∼ , ± l ~ , ± 1 χ ∼ m( [GeV] T2 m 80 100 120 140 160 180 200 Data / SM 1 2 3 (b) mT2 distribution in CR-top Events / 10 GeV 1 10 2 10 3 10 4 10 5 10 6 10 ATLAS -1 =13 TeV, 139 fbs CR-WW Data SM WW WZ ZZ tt Single Top FNP leptons Others )=(400,200) GeV 0 1 χ ∼ , ± l ~ m( )=(300,50) GeV 0 1 χ ∼ , ± 1 χ ∼ m( )=(600,300,1) GeV 0 1 χ ∼ , ± l ~ , ± 1 χ ∼ m( [GeV] miss T E 60 65 70 75 80 85 90 95 100 Data / SM 0.5 1 1.5 2 (c) Emiss Tdistribution in CR-WW Fig. 2 Distributions of mT2 in aCR-VZ and bCR-top and cEmiss Tin CR-WW for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the t¯ t, single-top-quark, WW,WZ and ZZ backgrounds. The FNP lepton background is calculated using the data-driven matrix method. Negligible background contributions are not included in the legends. The uncertainty band includes systematic and statistical errors from all sources and the final bin in each histogram includes the overflow. Distributions for three benchmark signal points are overlaid for comparison. The lower panels show the ratio of data to the SM background estimate SRs, comparing the numbers of events containing a pair of baseline leptons in which one of the two leptons, both or none of them satisfy the signal selection in a given region. To avoid double counting between the simulated samples used for background estimation and the FNP lepton background estimate provided by the MM, all simulated events containing one or more FNP leptons are removed. The number of observed events in each CR, as well as the predicted yield of each SM process, is shown in Table 5. For backgrounds whose normalisation is extracted from the likelihood fit, the yield expected from the simulation before the fit is also shown. After the fit, the central value of the total number of predicted events in each CR matches the data, as expected from the normalisation procedure. The normalisation factors returned by the fit for the WW,t¯ tand single-top-quark backgrounds, and WZ/ZZ backgrounds are 1.25 ±0.11, 0.82 ±0.06 and 1.18 ±0.05 respectively, which for diboson backgrounds are applied to MC samples scaled to NLO cross-sections (as detailed in Table 1). The shapes of kinematic distributions are well reproduced by the simulation in each CR. The distributions of mT2 in CR-VZ and CR-top and of Emiss Tin CR-WW are shown in Fig. 2. The number of observed events and the predicted background in each VR are shown in Table 6. For backgrounds with a normalisation extracted from the fit, the expected yield from simulated samples before the fit is also shown. Figure 3 shows a selection of kinematic distributions for data and the 123 Eur. Phys. J. C (2020) 80:123 Page 9 of 33 123 Table 6 Observed event yields and predicted background yields in the VRs. For backgrounds with a normalisation extracted from the fit in the CRs, the yield expected from the simulation before the fit is also shown. ‘Otherbackgrounds’include thenon-dominant backgroundsources, i.e. t¯ t+V, Higgs boson and Drell–Yan events. A ‘–’ symbol indicates that the background contribution is negligible Regions VR-WW-0J VR-WW-1J VR-VZ VR-top-low VR-top-high VR-top-WW Observed events 2742 2671 464 190 50 953 Fitted backgrounds 2760 ±120 2840 ±250 420 ±40 185 ±17 53 ±7 850 ±80 Fitted WW 1550 ±150 990 ±120 17.6±2.22.1±0.72.6±1.416.1±2.5 Fitted WZ 34.2±2.027.0±2.399±90.05+0.17 −0.05 0.2+0.6 −0.20.53 ±0.13 Fitted ZZ 0.50 ±0.06 0.39 ±0.07 268 ±25 −− 0.01+0.03 −0.01 Fitted t¯ t790 ±110 1400 ±270 10.5±3.2 157 ±15 40 ±7 650 ±70 Fitted single top 336 ±32 380 ±40 2.2±1.424.3±2.64.6±1.4 182 ±15 Other backgrounds 0.92 ±0.30 2.1±0.521 +27 −21 0.28 ±0.06 3.20 ±0.20 0.39 ±0.11 FNP leptons 44 ±23 38 ±21 0.2+2.1 −0.22.3±1.41.8±0.5− Simulated WW 1230 790 14.0 1.6 2.0 12.8 Simulated WZ 28.8 22.8 84 0.04 0.1 0.45 Simulated ZZ 0.42 0.33 226 – – 0.01 Simulated t¯ t960 1700 13 190 49 790 Simulated single top 406 462 2.6 29.4 5.6 220 estimated SM background in the validation regions defined in Table 4. Good agreement is observed in all regions. 8 Systematic uncertainties All relevant sources of experimental and theoretical systematic uncertainty affecting the SM background estimates and the signal predictions are included in the likelihood fit described in Sect. 9. The dominant sources of systematic uncertainty are related to theoretical uncertainties in the MC modelling, while the largest sources of experimental uncertainty are related to the jet energy scale (JES) and jet energy resolution (JER). The statistical uncertainty in the simulated event samples is also accounted for. Since the normalisation of the predictions for the dominant background processes is extracted from dedicated control regions, the systematic uncertainties only affect the extrapolation to the signal regions in these cases. TheJESandJERuncertaintiesareconsideredasafunction of jet pTand η, the pile-up conditions and the flavour composition of the selected jet sample. They are derived using a combination of data and simulation, through measurements of the transverse momentum balance between a jet and a reference object in dijet, Z+jets and γ+jets events [91]. An additional uncertainty in pmiss Tcomes from the soft-term resolution and scale [96]. Uncertainties in the scale factors applied to the simulated samples to account for differences between data and simulation in the b-jet identification efficiency are also included. The remaining experimental systematic uncertainties, such as those in the lepton reconstruction efficiency, lepton energy scale and lepton energy resolution and differences between the trigger efficiencies in data and simulation are included and are found to be a few per mille in all channels. The reweighting procedure (pile-up reweighting) applied to simulation to match the distribution of the number of interactions per bunch crossing observed in data results in a negligible contribution to the total systematic uncertainty. Several sources of theoretical uncertainty in the modelling ofthedominantbackgroundsareconsidered.Uncertaintiesin theMCmodelling of diboson eventsare estimated by varying the PDF sets as well as the renormalisation and factorisation scales used to generate the samples. To account for effects due to the choice of generator, the nominal PowhegBox dibosonsamplesarecomparedwithSherpa dibosonsamples that have a different matrix element calculation and parton shower simulation. For t¯ tproduction, uncertainties in the parton shower simulation are estimated by comparing samples generated with PowhegBox interfaced to either Pythia 8.186 or Herwig 7.04 [101,102]. Another source of uncertainty comes from themodellingofinitial-andfinal-stateradiation,whichiscalculated by comparing the predictions of the nominal sample with two alternative samples generated with PowhegBox interfaced to Pythia 8.186 but with the radiation settings varied [103]. The uncertainty associated with the choice of event generator is estimated by comparing the nominal samples with samples generated with aMC@NLO interfaced to Pythia 8.186 [104]. Finally, for single-top-quark production an uncertainty is assigned to the treatment of the interference between the Wt and t¯ tsamples. This is done by comparing 123 123 Page 16 of 33 Eur. Phys. J. C (2020) 80:123 (a)(b) (c) Fig. 7 Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with aW-boson-mediated decays and bslepton/sneutrino-mediated decays, and cfor slepton-pair production. In ball three slepton flavours (˜e,˜μ,˜τ) are considered, while only ˜eand ˜μare considered in c. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The upper shaded band corresponds to the ±1σvariations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. The blue line in b corresponds to the observed limit for ˜ Lprojected into this model for the chosen slepton mass hypothesis (slepton masses midway between the mass of the chargino and that of the ˜χ0 1). All limits are computed at 95% CL. The observed limits obtained by ATLAS in previous searches are also shown (lower shaded areas) [24,25] degenerate sleptons. These results significantly extend the previous exclusion limits for the same scenarios. Acknowledgements We thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; MNE/IFA, Romania; MES of Russia and NRC KI, Russian Federation;JINR; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, CANARIE, CRC and Compute Canada, Canada; COST, ERC, ERDF, Horizon 2020, and Marie Skłodowska-Curie Actions, European Union; Investissements d’ 123 Eur. Phys. J. C (2020) 80:123 Page 17 of 33 123 (a)(b) Fig. 8 Observed and expected exclusion limits on SUSY simplified models for adirect selectron production and bdirect smuon production. In athe observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined ˜eL,R and for ˜eLand ˜eR.In bthe observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined ˜μL,R and for ˜μLand ˜μR. All limits are computed at 95% CL. The observed limits obtained by ATLAS in previous searches are also shown in the shaded areas [25] Avenir Labex and Idex, ANR, France; DFG and AvH Foundation, Germany;Herakleitos,ThalesandAristeiaprogrammesco-financedbyEUESF and the Greek NSRF, Greece; BSF-NSF and GIF, Israel; CERCA Programme Generalitat de Catalunya, Spain; The Royal Society and Leverhulme Trust, United Kingdom. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark,Norway,Sweden), CC-IN2P3(France),KIT/GridKA(Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (UK) and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resource providers. Major contributors of computing resources are listed in Ref. [108]. Data Availability Statement This manuscript has no associated data or the data will not be deposited. [Authors’ comment: All ATLAS scientific output is published in journals, and preliminary results are made available in Conference Notes. All are openly available, without restriction on use by external parties beyond copyright law and the standard conditions agreed by CERN. Data associated with journal publications are also made available: tables and data from plots (e.g. cross section values, likelihood profiles, selection efficiencies, cross section limits, ...) are stored in appropriate repositories such as HEPDATA (http:// hepdata.cedar.ac.uk/). ATLAS also strives to make additional material related to the paper available that allows a reinterpretation of the data in the context of new theoretical models. For example, an extended encapsulation of the analysis is often provided for measurements in the framework of RIVET (http://rivet.hepforge.org/). This information is taken from the ATLAS Data Access Policy, which is a public document that can be downloaded from http://opendata.cern.ch/record/413 [opendata.cern.ch].] Open Access This article is licensed under a Creative Commons Attribution4.0 InternationalLicense,whichpermits use,sharing,adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. 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C (2020) 80:123 169 Division of Physics and Tomonaga Center for the History of the Universe, Faculty of Pure and Applied Sciences, University of Tsukuba, Tsukuba, Japan 170 Department of Physics and Astronomy, Tufts University, Medford, MA, USA 171 Department of Physics and Astronomy, University of California Irvine, Irvine, CA, USA 172 Department of Physics and Astronomy, University of Uppsala, Uppsala, Sweden 173 Department of Physics, University of Illinois, Urbana, IL, USA 174 Instituto de Física Corpuscular (IFIC), Centro Mixto Universidad de Valencia - CSIC, Valencia, Spain 175 Department of Physics, University of British Columbia, Vancouver, BC, Canada 176 Department of Physics and Astronomy, University of Victoria, Victoria, BC, Canada 177 Fakultät für Physik und Astronomie, Julius-Maximilians-Universität Würzburg, Würzburg, Germany 178 Department of Physics, University of Warwick, Coventry, UK 179 Waseda University, Tokyo, Japan 180 Department of Particle Physics, Weizmann Institute of Science, Rehovot, Israel 181 Department of Physics, University of Wisconsin, Madison, WI, USA 182 Fakultät für Mathematik und Naturwissenschaften, Fachgruppe Physik, Bergische Universität Wuppertal, Wuppertal, Germany 183 Department of Physics, Yale University, New Haven, CT, USA 184 Yerevan Physics Institute, Yerevan, Armenia aAlso at Borough of Manhattan Community College, City University of New York, New York, NY, USA bAlso at Centre for High Performance Computing, CSIR Campus, Rosebank, Cape Town, South Africa cAlso at CERN, Geneva, Switzerland dAlso at CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille, France eAlso at Département de Physique Nucléaire et Corpusculaire, Université de Genève, Geneva, Switzerland fAlso at Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona, Spain gAlso at Departamento de Física, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal hAlso at Department of Applied Physics and Astronomy, University of Sharjah, Sharjah, UAE iAlso at Department of Financial and Management Engineering, University of the Aegean, Chios, Greece jAlso at Department of Physics and Astronomy, Michigan State University, East Lansing, MI, USA kAlso at Department of Physics and Astronomy, University of Louisville, Louisville, KY, USA lAlso at Department of Physics and Astronomy, University of Sheffield, Sheffield, UK mAlso at Department of Physics, California State University, East Bay, USA nAlso at Department of Physics, California State University, Fresno, USA oAlso at Department of Physics, California State University, Sacramento, USA pAlso at Department of Physics, King’s College London, London, UK qAlso at Department of Physics, St. Petersburg State Polytechnical University, St. Petersburg, Russia rAlso at Department of Physics, Stanford University, Stanford, CA, USA sAlso at Department of Physics, University of Adelaide, Adelaide, Australia tAlso at Department of Physics, University of Fribourg, Fribourg, Switzerland uAlso at Department of Physics, University of Michigan, Ann Arbor, MI, USA vAlso at Faculty of Physics, M.V. Lomonosov Moscow State University, Moscow, Russia wAlso at Giresun University, Faculty of Engineering, Giresun, Turkey xAlso at Graduate School of Science, Osaka University, Osaka, Japan yAlso at Hellenic Open University, Patras, Greece zAlso at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona, Spain aa Also at Institut für Experimentalphysik, Universität Hamburg, Hamburg, Germany ab Also at Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen, The Netherlands ac Also at Institute for Nuclear Research and Nuclear Energy (INRNE) of the Bulgarian Academy of Sciences, Sofia, Bulgaria ad Also at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest, Hungary ae Also at Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China af Also at Institute of Particle Physics (IPP), Toronto, Canada 123 Eur. Phys. J. C (2020) 80:123 Page 33 of 33 123 ag Also at Institute of Physics, Academia Sinica, Taipei, Taiwan ah Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan ai Also at Institute of Theoretical Physics, Ilia State University, Tbilisi, Georgia aj Also at Instituto de Fisica Teorica, IFT-UAM/CSIC, Madrid, Spain ak Also at Department of Physics, Istanbul University, Istanbul, Turkey al Also at Joint Institute for Nuclear Research, Dubna, Russia am Also at LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay, France an Also at Louisiana Tech University, Ruston, LA, USA ao Also at LPNHE, Sorbonne Université, Paris Diderot Sorbonne Paris Cité, CNRS/IN2P3, Paris, France ap Also at Manhattan College, New York, NY, USA aq Also at Moscow Institute of Physics and Technology State University, Dolgoprudny, Russia ar Also at National Research Nuclear University MEPhI, Moscow, Russia as Also at Physics Dept, University of South Africa, Pretoria, South Africa at Also at Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany au Also at School of Physics, Sun Yat-sen University, Guangzhou, China av Also at The City College of New York, New York, NY, USA aw Also at The Collaborative Innovation Center of Quantum Matter (CICQM), Beijing, China ax Also at Tomsk State University, Tomsk, and Moscow Institute of Physics and Technology State University, Dolgoprudny, Russia ay Also at TRIUMF, Vancouver, BC, Canada az Also at Universita di Napoli Parthenope, Naples, Italy ∗Deceased 123