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Journal of High Energy Physics. 2024 May 13;2024(5):150
The Author(s)
ATLAS Collaboration
Three searches for the direct production of τ -sleptons or charginos and neutralinos in fnal states with at least two hadronically decaying τ -leptons are presented. For chargino and neutralino production, decays via intermediate τ -sleptons or W and h bosons are considered. The analysis uses a dataset of pp collisions corresponding to an integrated luminosity of 139 fb−1 , recorded with the ATLAS detector at the Large Hadron Collider at a centre-of-mass energy of 13 TeV. No signifcant deviation from the expected Standard Model background is observed and supersymmetric particle mass limits at 95% confdence level are obtained in simplifed models. For direct production of χ˜ + 1 χ˜ − 1 , chargino masses are excluded up to 970 GeV, while χ˜ ± 1 and χ˜ 0 2 masses up to 1160 GeV (330 GeV) are excluded for χ˜ ± 1 χ˜ 0 2 /χ˜ + 1 χ˜ − 1 production with subsequent decays via τ -sleptons (W and h bosons). Masses of τ -sleptons up to 500 GeV are excluded for mass degenerate τ˜L,R scenarios and up to 425 GeV for τ˜L-only scenarios. Sensitivity to τ˜R-only scenarios from the ATLAS experiment is presented here for the frst time, with τ˜R masses excluded up to 350 GeV.
JHEP05(2024)150PuAlished for SISS Ay SpringerReceived: February 5, 2024Accepted: April 23, 2024Published: May 13, 2024Search for electroweak production of supersymmetricparticles in final states with two τ -leptons in√s = 13TeV pp collisions with the ATLAS detectorThe ATLAS collaborationE-mail: atlas.publications@cern.chAbstract: Three searches for the direct production of τ -sleptons or charginos and neutralinosin final states with at least two hadronically decaying τ -leptons are presented. For chargino andneutralino production, decays via intermediate τ -sleptons or W and h bosons are considered.The analysis uses a dataset of pp collisions corresponding to an integrated luminosity of139 fb−1, recorded with the ATLAS detector at the Large Hadron Collider at a centre-of-massenergy of 13TeV. No significant deviation from the expected Standard Model backgroundis observed and supersymmetric particle mass limits at 95% confidence level are obtainedin simplified models. For direct production of χ˜+1 χ˜−1 , chargino masses are excluded up to970GeV, while χ˜±1 and χ˜02 masses up to 1160GeV (330GeV) are excluded for χ˜±1 χ˜02/χ˜+1 χ˜−1production with subsequent decays via τ -sleptons (W and h bosons). Masses of τ -sleptonsup to 500GeV are excluded for mass degenerate τ˜L,R scenarios and up to 425GeV for τ˜L-onlyscenarios. Sensitivity to τ˜R-only scenarios from the ATLAS experiment is presented herefor the first time, with τ˜R masses excluded up to 350GeV.Keywords: Beyond Standard Model, Electroweak Interaction, Hadron-Hadron Scattering,SupersymmetryArXiv ePrint: 2402.00603Open Access, Copyright CERN,for the benefit of the ATLAS Collaboration.Article funded by SCOAP3.https://doi.org/10.1007/JHEP05(2024)150JHEP05(2024)150Contents1 Introduction 12 ATLAS detector 33 Data and simulated event samples 44 Event reconstruction 55 General analysis strategy and event variables 76 Direct stau production 96.1 Event selection 96.2 Background estimate 107 Intermediate stau channel 157.1 Event selection 177.2 Background estimate 188 Intermediate Wh channel 228.1 Event selection 228.2 Background estimate 239 Systematic uncertainties 2710 Results 2810.1 Direct stau production analysis 2810.2 Intermediate stau analysis 2910.3 Intermediate Wh analysis 3511 Summary 38The ATLAS collaboration 461 IntroductionSupersymmetry (SUSY) [1–7] postulates the existence of a bosonic (fermionic) partner foreach fermionic (bosonic) particle of the Standard Model (SM), whose spin differs by one halfunit from each corresponding SM particle. In models that conserve R-parity [8], the lightestsupersymmetric particle (LSP) is stable and can be an excellent dark-matter candidate [9, 10].In the simplified SUSY models considered in this article, the sector of SUSY particleswith only electroweak interactions contains charginos (χ˜±i , i = 1, 2, in order of increasingmasses), neutralinos (χ˜0j , j = 1, 2, 3, 4, in order of increasing masses), charged sleptons (ℓ˜),and sneutrinos (ν˜). Charginos and neutralinos are the mass eigenstates formed from linear– 1 –JHEP05(2024)150superpositions of the superpartners of the Higgs bosons and electroweak gauge bosons. Thecharged sleptons are the superpartners of the charged leptons and are denoted by subscriptsreflecting the chirality of the SM partner fields, referred to as ℓ˜L or ℓ˜R, respectively. Theslepton mass eigenstates are a mixture of ℓ˜L and ℓ˜R, and are labeled as ℓ˜k (k = 1, 2 inorder of increasing mass). In this work, the scalar superpartners of the left-handed τ -lepton(τ˜L) and right-handed τ -lepton (τ˜R) are assumed to be mass degenerate unless explicitlystated, and are referred to as “staus.” All SUSY scenarios considered in this publicationconserve R-parity and the LSP is the χ˜01.Although they are experimentally challenging, final states with τ -leptons are of particularinterest in SUSY searches. Light sleptons could play a role in the co-annihilation of neutralinosin the early universe, and models with light stau decays into light neutralinos can shed lighton the nature of dark matter [11]. Furthermore, should SUSY or any other physics beyondthe Standard Model (BSM) involving leptons be discovered, independent studies of all threelepton flavors are necessary to investigate the coupling structure of the new physics, especiallyconcerning lepton universality.The first SUSY scenario considered is the direct production of stau pairs, either with massdegenerate or non-degenerate τ˜L,R, which decay directly into a τ -lepton and the LSP 100%of the time. The second scenario, referred to as the “Intermediate stau” channel, includes theproduction of mass-degenerate neutralinos and charginos, χ˜±1 χ˜02 and χ˜+1 χ˜−1 , which decay intothe lightest neutralino only through intermediate staus or τ -sneutrinos with equal branchingfraction. The stau and sneutrino masses are assumed to be halfway between the χ˜02/χ˜±1and χ˜01 masses. The search for χ˜±1 χ˜02 production is separated into final states with twosame-sign (SS) or opposite-sign (OS) τ -lepton pairs. The third SUSY scenario, referred to asthe “Intermediate Wh” channel, is the direct production of mass-degenerate neutralinos andcharginos, χ˜±1 χ˜02, which decay via the lightest neutral Higgs boson (h), consistent with the SMHiggs boson with a mass of 125GeV, a W boson and two neutralinos. In this case, the finalstate under consideration contains two hadronically decaying τ -leptons from the Higgs bosondecay and one charged light lepton (e, µ) from the W boson decay. The light lepton may bethe result of a W → τν decay where the τ -lepton decays leptonically. For all three searchespresented in this publication, the final state includes two hadronically decaying τ -leptons,low jet activity and large missing transverse momentum, pmissT , from the neutralinos andneutrinos. Representative diagrams of the targeted signal processes can be found in figure 1.Previous results from the ATLAS experiment have set exclusion limits at 95% confidencelevel on these SUSY models with the Run 1 and partial Run 2 data samples [12–15]. The CMSexperiment also sets comparable exclusion limits [16–18]. This search extends the currentATLAS reach to higher chargino masses and smaller mass differences between χ˜02/χ˜±1 /τ˜ andχ˜01 using the increased statistics of the full Run 2 data sample. It also achieves sensitivityto τ˜R pair production scenarios for the first time from ATLAS, by introducing the use ofmachine learning algorithms.The publication is structured as follows: the ATLAS detector is briefly introduced insection 2 followed by a description of the data and simulated samples used in section 3 andthe reconstruction of events in section 4; the general analysis strategy is outlined in section 5,followed by the details of the Direct stau, Intermediate stau, and Intermediate Wh searches– 2 –JHEP05(2024)150τ˜τ˜ppχ˜01τχ˜01τ(a)χ˜±1χ˜∓1τ˜ /ν˜ττ˜ /ν˜τppντ/ττ/ντχ˜01ντ/ττ/ντχ˜01(b)χ˜±1χ˜02τ˜ /ν˜ττ˜ /ν˜τppντ/ττ/ντχ˜01τ/νττ/ντχ˜01(c)χ˜±1χ˜02Whppχ˜01`νχ˜01ττ(d)Figure 1. Representative diagrams of SUSY scenarios, which are being searched for in this publication.Direct stau production is shown in (a), while (b) and (c) show the processes considered for theIntermediate stau channel. The process for the Intermediate Wh channel is shown in (d). In all cases,the subsequent decays contain a final state with at least two τ -leptons. In the case of χ˜±1 χ˜02 production(c), the final state can contain more than two τ -leptons.in sections 6, 7, and 8, respectively; the systematic uncertainties are discussed in section 9and the results are presented in section 10, before conclusions are drawn in section 11.2 ATLAS detectorThe ATLAS experiment [19] at the Large Hadron Collider (LHC) is a multipurposeparticle detector with a forward-backward symmetric cylindrical geometry and a near 4πcoverage in solid angle.1 It consists of an inner tracking detector (ID) surrounded by athin superconducting solenoid providing a 2T axial magnetic field, electromagnetic andhadron calorimeters, and a muon spectrometer. The ID covers the pseudorapidity range|η| < 2.5. It consists of silicon pixel, silicon microstrip, and transition radiation trackingdetectors. Lead/liquid-argon (LAr) sampling calorimeters provide electromagnetic (EM)energy measurements with high granularity. A steel/scintillator-tile hadron calorimetercovers the central pseudorapidity range (|η| < 1.7). The endcap and forward regions areinstrumented with LAr calorimeters for both the EM and hadronic energy measurements1ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP) in thecenter of the detector and the z-axis along the beam pipe. The x-axis points from the IP to the center of theLHC 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 is defined in terms of the polar angle θ asη = − ln tan(θ/2). Angular distance is measured in units of ∆R ≡√(∆η)2 + (∆ϕ)2.– 3 –JHEP05(2024)150up to |η| = 4.9. The muon spectrometer (MS) surrounds the calorimeters and is based onthree large superconducting air-core toroidal magnets with eight coils each. The field integralprovided by the toroids ranges between 2.0 and 6.0Tm across most of the detector. Themuon spectrometer includes a system of precision tracking chambers and fast detectors fortriggering. A two-level trigger system is used to select events [20]. The first-level trigger isimplemented in hardware and uses a subset of the detector information to accept events at arate below 100 kHz. This is followed by a software-based trigger that reduces the acceptedevent rate to 1 kHz on average depending on the data-taking conditions. An extensive softwaresuite [21] is used in the reconstruction and analysis of real and simulated data, in detectoroperations, and in the trigger and data acquisition systems of the experiment.3 Data and simulated event samplesThe data sample considered in this publication corresponds to 139 fb−1 of proton-proton(pp) LHC collision data collected between 2015 and 2018 with the ATLAS detector, at acenter-of-mass energy of 13TeV. Data quality requirements are imposed to ensure that onlyevents in which the entire ATLAS detector was functioning well are used [22].Simulated events produced with several Monte Carlo (MC) event generators are used topredict yields for background contributions from SM processes and for possible SUSY signals.To account for pileup, all simulated events are overlaid with multiple pp collisions simulatedwith the soft QCD processes of Pythia 8.186 [23] using the A3 set of tuned parameters [24]and the NNPDF2.3lo leading-order (LO) parton distribution functions (PDFs) [25]. For allsamples showered with Pythia 8, EvtGen 1.2.0 [26] is used to simulate the decays of bottomand charmed hadrons. The simulated events are weighted such that the pileup conditionsmatch those of the data and are required to satisfy the trigger selections. The response of thedetector to particles is modeled with an ATLAS detector simulation [27] based on Geant4 [28]for almost all SM background simulation. A few minor electroweak Z+jet processes withvery small yields for these searches use a fast simulation based on a parameterisation of theperformance of the ATLAS EM and hadronic calorimeters [29] and on Geant4 elsewhere.Final states with at least two hadronically decaying τ -leptons, low jet activity and a largepmissT are included in this analysis. As a result, SM background processes containing bothreal and misidentified τ -lepton final state contributions are considered. These backgroundsare summarised in the following paragraphs.The production of top-quark pairs (tt¯) and single top quarks in the Wt and s-channelsis performed with PowhegBox v2 [30–33], with the NNPDF2.3lo PDF set at next-to-leading-order (NLO) in the Matrix element (ME) calculations and the ATLAS underlying-event tune A14 [34]. Electroweak t-channel single-top-quark events are simulated using thePowhegBox v2 event generator. The parton shower (PS), fragmentation, and the underlyingevent are simulated using Pythia 8.186 with the NNPDF2.3lo PDF set and a correspondingset of A14 tuned parameters. The top-quark mass is set to 172.5GeV. The tt¯ sample isnormalized to the cross-section prediction at next-to-next-to-leading-order (NNLO) in QCDincluding the resummation of next-to-next-to-leading-logarithmic (NNLL) soft-gluon termscalculated using Top++ 2.0 [35–41]. The cross-section for single-top-quark is computed forthe Wt-channel at NLO in QCD with NNLL soft gluon corrections [42, 43], and to NLO– 4 –JHEP05(2024)150in QCD for the t- and s-channels. Top-quark pair production with an additional W orZ boson is calculated using aMC@NLO 2.2.2 [44] at NLO in the ME calculations, whilefragmentation and hadronization are simulated with Pythia 8.186. The underlying-eventtune A14 is used with the NNPDF2.3lo PDF set, and the cross-sections are normalizedusing NLO predictions [45, 46].Events with Z/γ∗ → ℓℓ (ℓ = e, µ, τ) and W → ℓν produced in association with jets(including jets initiated by heavy flavor quarks) are simulated with Sherpa 2.2.1 [47, 48].MEs are calculated for up to two additional partons at NLO and four additional partons atLO, using the Comix [49] and OpenLoops [50, 51] generators and merged with the SherpaPS [52] using the MENLOPS prescription. The NNPDF3.0nnlo [53] PDF set is used inconjunction with a dedicated PS tuning developed by the Sherpa authors. The W/Z+jetsevents are normalized using their NNLO cross-sections [54].Fully leptonically and semileptonically decaying diboson and tribsoson samples (V V andV V V , where V =W,Z) are simulated with the Sherpa 2.2.1 and Sherpa 2.2.2 generator atNLO. In this setup, multiple matrix elements are matched and merged with the Sherpa partonshower based on Catani-Seymour dipole factorisation using the MENLOPS prescription [55,56]. The virtual QCD corrections for matrix elements at NLO accuracy are provided by theOpenLoops library. Samples are simulated using the NNPDF3.0nnlo set, along with thededicated set of tuned parton-shower parameters developed by the Sherpa authors.Contributions from Higgs boson events produced by gluon-gluon fusion and vector-bosonfusion are modeled using PowhegBox v2 with the NNPDF3.0nnlo PDF and showeredusing Pythia 8.186. Associated production of a Higgs boson with a vector boson and a Higgsboson in association with two top quarks are simulated using Pythia 8.186 and aMC@NLO,respectively. All Higgs boson samples are normalized to the cross-sections from ref. [57].SUSY signal model samples are simulated to allow the interpretation of the searchresults in terms of SUSY parameters and use the ATLAS fast detector simulation. Signalsamples are simulated using aMC@NLO 2.2.3 interfaced to Pythia 8.186 with the A14tune for the PS modeling, hadronization, and underlying event. The ME calculation isperformed at tree level and includes the emission of up to two additional partons. The PDFset used for the generation is NNPDF2.3lo. The ME-PS merging uses the CKKW-L [58]prescription, with a matching scale set to one quarter of the mass of the pair of producedparticles. Signal cross-sections are calculated with Resummino v2.0.1 to NLO in the strongcoupling constant, adding the resummation of soft gluon emission at next-to-leading-logarithmaccuracy (NLO+NLL) [59, 60]. The nominal cross-section and the uncertainty are takenfrom an envelope of cross-section predictions using different PDF sets and factorisation andrenormalization scales, as described in ref. [61].4 Event reconstructionAfter data quality requirements are applied, events with at least one reconstructed primaryvertex [62] are selected. A primary vertex is defined to have at least two associated charged-particle tracks with transverse momentum pT > 500MeV and be consistent with the beamspot envelope. If there are multiple primary vertices in an event, the one with the largest∑p2T of the associated tracks is chosen.– 5 –JHEP05(2024)150Jets are reconstructed from particle-flow objects calibrated at the EM scale [63] usingthe anti-kt algorithm [64, 65] with a radius parameter of 0.4. Jet energies are correctedfor detector inhomogeneities, the non-compensating response of the calorimeter, and pileupeffects [66, 67]. The impact due to pileup is accounted for using a technique based on jetareas that provides an event-by-event and jet-by-jet correction [68]. Jets that are likely tohave originated from pileup are not considered in the analysis [69]. Jets are required to havepT > 20GeV and |η| < 2.8, and events containing jets that are likely to have arisen fromdetector noise or cosmic rays are removed [70].Jets containing b-hadrons (b-jets) are identified using the DL1r algorithm [71, 72], amultivariate discriminant making use of track impact parameters and reconstructed secondaryvertices. Candidate b-jets are required to have |η| < 2.5. A working point is used that has apT-independent b-tagging efficiency of 77% and light-jet (c-jet) rejection factor of 140 (4),based on studies using simulated tt¯ events.Electron candidates are reconstructed by matching clusters in the EM calorimeter withcharged-particle tracks in the ID. Electrons are required to have pT > 25GeV, |η| < 2.47, andto satisfy the “loose” working point according to a likelihood-based identification algorithmdetailed in ref. [73]. Muon candidates are reconstructed from MS tracks matching ID tracks;they are required to have pT > 25GeV and |η| < 2.7 and satisfy the “medium” qualitycriteria described in ref. [74]. Events containing a muon candidate with a poorly measuredcharge-to-momentum ratio of σ(q/p)|q/p| > 0.2 are rejected. Events are required not to containany candidate muon with large transverse (d0) and longitudinal (z0) impact parameter,|z0| > 1mm or |d0| > 0.2mm, to reduce contributions from those originating from cosmicrays. The efficiencies for electrons and muons to satisfy the reconstruction, identification, andisolation criteria are measured using samples of leptonic Z and J/ψ decays, and correctionsare applied to the simulated samples to reproduce the efficiencies observed in data [73, 74].The reconstruction of hadronically decaying τ -leptons is based on information from tracksin the ID and three-dimensional clusters in the EM and hadronic calorimeters. The τ -leptonreconstruction algorithm is seeded by jets reconstructed from topological clusters of energydeposits in the calorimeter and uses a looser requirement of pT > 10GeV and |η| < 2.5. Thereconstructed energies of the hadronically decaying τ -lepton candidates are corrected fromthe local hadron topocluster scale to the τ -lepton energy scale, which is calibrated basedon simulation and in situ measurements using Z → ττ decays [75]. Hadronically decayingτ -lepton candidates are required to have one or three associated charged-particle tracks(prongs) and the total electric charge of those tracks must be ±1 times the electron charge.To improve the discrimination between hadronically decaying τ -leptons and jets, electrons, ormuons, multivariate algorithms are used [76]. A recurrent neural network discriminant is usedto reject jets that do not originate from a hadronically decaying τ -lepton, with a “medium”or “tight” working point as described in ref. [77]. The medium (tight) working point hasan efficiency of 75% (60%) for 1-prong τ -leptons and 60% (45%) for 3-prong τ -leptons,based on γ∗ → ττ MC simulation. The background rejection factor for the medium (tight)working point is 35 (70) for 1-prong τ -leptons and 240 (700) for 3-prong τ -leptons, basedon dijet MC simulation. A boosted decision tree is used to discriminate 1-prong τ -leptonsagainst electrons. This discriminant is built using information from the EM calorimeter and– 6 –JHEP05(2024)150the tracking detector. This requirement has about 95% efficiency, and a rejection factorfrom 10 to 50 depending on the η range. The τ -leptons are required to have pT > 20GeVand |η| < 2.47, and must lie outside the transition region between the barrel and endcapcalorimeters (1.37 < |η| < 1.52).The MC simulation is corrected for differences in the efficiencies of the τ -leptonidentification at both trigger and reconstruction level between data and simulation. Forhadronically decaying τ -leptons originating from prompt gauge boson decays, the correctionsare calculated with a tag-and-probe method in a sample of Z → ττ events where one τ -leptondecays hadronically and the other leptonically into a muon and two neutrinos [78].The measured pmissT , and its magnitude EmissT , is defined as the negative vectorial sumof the pT of all identified jets, τ -leptons, electrons, photons, muons, and an additional softterm. The soft term is constructed from all tracks that are associated with the primaryvertex but not with any identified particle or jet [79, 80].To avoid the possible double counting of reconstructed objects, an overlap removalprocedure is used, following these steps. The τ -leptons that are close to electron or muoncandidates (∆R < 0.2, where ∆R =√(∆y)2 + (∆ϕ)2 ) are removed, as are electrons thatshare a track with a muon. For electrons close to a jet (∆R < 0.4), the electron is removed,except when ∆R < 0.2 and the jet is not b-tagged, in which case the jet is removed. Anyremaining jet close to a muon or τ -lepton (∆R < 0.4) is removed.5 General analysis strategy and event variablesEvents for all scenarios are required to have at least two hadronically decaying τ -leptons.Different signal regions (SRs) are defined to target the specific SUSY scenario, using kinematicvariables that provide a good signal-to-background separation, described in this section. Forτ -leptons, kinematic variables are calculated from the visible decay products. The eventselections and background estimates are described for Direct stau production SRs in section 6,for the Intermediate stau channel SRs in section 7, and for the Intermediate Wh channelSRs in section 8.The main SM backgrounds are estimated by normalizing MC simulation samples to datain dedicated control regions (CRs); backgrounds resulting from non-prompt and misidentifiedleptons are derived from data, while sub-dominant backgrounds are estimated by using MCsimulation only. To validate the modelling of the SM backgrounds, the yields and shapesof key kinematic variables are compared with data in dedicated validation regions (VRs).SRs are designed for the best expected sensitivity to the simplified SUSY signal modelsstudied. Where appropriate, looser, or merged SRs are used to enhance discovery prospectsor to set model-independent limits.The observed number of events in the CRs and SRs are used in a combined profilelikelihood fit to determine the expected SM background yields. The statistical interpretationof the results is performed using the profile likelihood method implemented in the HistFitterframework [81]. Systematic uncertainties are included as nuisance parameters in the likelihoodfits and are assumed to follow a Gaussian distribution with a width determined from thesize of the uncertainty. Correlations of systematic uncertainties between control and signalregions, and between background processes are taken into account with common nuisance– 7 –JHEP05(2024)150parameters. The fit parameters are determined by maximising the product of the Poissonprobability functions and the constraints for the nuisance parameters.To constrain the SM backgrounds normalized to data in CRs, a background-only fit isused. This uses the observed yields in the CRs with the expected SM contributions (otherthan multi-jet) in the CRs and SRs, and the corresponding background transfer factorsdescribed in section 6.2.1. The free parameters in the fit are the normalizations of the SMprocesses. To estimate the SM background in the SRs (or VRs), a combined fit is performedthat includes the observed data in the CRs and SRs (or VRs) with the SM backgroundestimates, and accounts for correlations between CRs and SRs (or VRs), as well as betweenbackground processes. The presence of BSM signal in any CR, SR, or VR is assumed tobe zero in the combined and background-only fits.To assess the possibility of the presence of any BSM events in each SR, a model-independentfit is used. This uses the observed yields in both the CRs and SRs with the SM backgroundestimates to test whether any BSM events could be present in the SR. The presence of BSMsignal in any CR is assumed to be zero in the model-independent fit. The significance ofa possible excess of observed events over the SM prediction is quantified by the one-sidedprobability, p(signal = 0) denoted by p0, of the background alone to fluctuate to the observednumber of events or higher using the asymptotic formula described in ref. [82]. The upperlimit on the visible cross-section of BSM events in an SR, σ95vis, is also calculated, whichincludes the acceptance and efficiency effect of any BSM signal possibly present.Finally, to assess the compatibility of the signal scenarios with the data observation, amodel-dependent fit is used, which accounts for the SUSY signal in all CRs and SRs scaledby a floating signal normalization factor. The background normalization factors are alsodetermined simultaneously in the fit. A SUSY scenario is rejected if the upper limit at 95%confidence level (CL) of the signal normalization factor obtained in this fit is smaller thanthe predicted cross-section of the scenario [83].The following variables are used to discriminate SUSY signals from the SM background:• mT, the transverse mass values obtained from a reconstructed lepton with the pmissT ,defined bymT(pT,pmissT ) =√2(|pT||pmissT | − pT · pmissT ),where pT is the transverse momenta of the lepton. The transverse mass calculatedusing light leptons only (e or µ) is denoted by mT,ℓ.• mTsum, the sum of the transverse mass values of the two highest-pT τ -lepton candidateswith the pmissT . For Intermediate Wh scenarios, mT,ℓ is also added to mTsum.• mT2, the “stransverse mass,” which has a kinematic endpoint for events where twomassive particles are pair produced, then each particle decays into a detected object(the lepton) and an undetected object (the neutralino) [84, 85]. It is defined as:mT2 = minqT[max(mT(pT1,qT),mT(pT2,pmissT − qT))],where pT1 and pT2 are the transverse momenta of the two leptons and qT is thetransverse vector chosen to minimise the larger of the two transverse masses. In this– 8 –JHEP05(2024)150case, qT or pmissT − qT replaces pmissT in the calculation of mT. In events with morethan two τ -lepton candidates, the pair that maximises mT2 is used. Similarly, in theIntermediate Wh analysis, the pairing of eτ , µτ , or ττ that maximises mT2 is used.For tt¯ and WW events, the mT2 distribution has a kinematic endpoint at the W bosonmass, but the distribution for SUSY scenarios extends significantly beyond this endpointif the mass difference between the produced SUSY particle and the χ˜01 is large. The χ˜01is assumed to be massless in the calculation of mT2.• meff , the effective mass, is defined as the scalar sum of the EmissT and the pT of the twohighest-pT τ -leptons. The effective mass for SUSY processes is typically higher thanfor SM processes.• ∆R(τ1, τ2) =√(∆η(τ1, τ2)2 +∆ϕ(τ1, τ2)2, the angular distance between the two highest-pT τ -leptons. An upper requirement on this variable is used to discriminate againstback-to-back objects in SM events.• m(τ1, τ2): the invariant mass of the two highest-pT τ -leptons. A similar variable is alsoused for the invariant mass of a τ -lepton and a muon, m(τ, µ).• |∆ϕ(τ1, τ2)|: the absolute value of the difference of azimuthal angle around the z-axisbetween the two highest-pT τ -lepton candidates. A similar variable is also used for thepmissT and τ -leptons, e.g., |∆ϕ(τ,pmissT )|.• |∆η(τ1, τ2)|: the absolute value of the difference of pseudorapidity between the twohighest-pT τ -leptons.6 Direct stau productionThe Direct stau analysis targets the production of τ˜Lτ˜L and τ˜Rτ˜R, with the stau decaying intoa τ -lepton and a χ˜01, as shown in figure 1(a). This analysis aims to improve upon previousresults, particularly for moderate mass splittings between the stau and χ˜01, and for τ˜Rτ˜Rproduction. Multiple Boosted Decision Trees (BDTs) are trained for sensitivity to differentareas of the τ˜ − χ˜01 phase space. The event selection and BDT training are described insection 6.1, followed by the background estimate in section 6.2.6.1 Event selectionEvents are selected using an asymmetric di-τ trigger, where the first τ -lepton must satisfypT > 95GeV and the second τ -lepton must satisfy pT > 60 (75)GeV for 2015–2017 (2018)data-taking. The τ -lepton pT thresholds applied are to ensure the trigger efficiencies arein the plateau region.Four BDTs are trained using the LightGBM [86] package on four groupings of signalscenarios chosen for their different τ˜ masses and ∆m(τ˜ , χ˜01). Events used in training have atleast two OS medium τ -leptons, no electron, muon, or b-tagged jet candidates and satisfyloose selections on kinematic variables, as shown in table 1. Three BDT SRs (SR-BDT1,SR-BDT2, SR-BDT3) have two bins in their BDT score, while the fourth BDT has only onebin (SR-BDT4) due to the low statistics available. The binned regions are used for setting– 9 –JHEP05(2024)150BDT Training PreselectionN medium τ ≥ 2Charge combination OSTrigger asymm. di-τN e/µ = 0N b-jets = 0EmissT [GeV] > 20mT2 [GeV] > 30m(τ1, τ2) [GeV] > 120∆R(τ1, τ2) < 4SR-BDT1 SR-BDT2 SR-BDT3 SR-BDT4Bin 1 Bin 2 Bin 1 Bin 2 Bin 1 Bin 2Target Low m(τ˜) Mid m(τ˜) Mid m(τ˜) High m(τ˜)scenario Small ∆m(τ˜ , χ˜01) Large ∆m(τ˜ , χ˜01) Small ∆m(τ˜ , χ˜01)N medium τ = 2BDT1 score ∈ (0.73, 0.78) > 0.78 — — — — —BDT2 score — — ∈ (0.78, 0.82) > 0.82 — — —BDT3 score — — — — ∈ (0.79, 0.86) > 0.86 —BDT4 score — — — — — — > 0.64Table 1. Summary of the selection requirements for the stau pair production SRs.exclusion limits in simplified models, while inclusive regions that merge each of the two binsin the binned regions are used to enhance discovery prospects and set model-independentlimits. The single-bin region, SR-BDT4, is unchanged when used for setting exclusion limitsand model-independent limits. The events selected by the four BDT SRs significantly overlap,thus the SR with the best expected sensitivity is chosen for interpretations.The BDT training uses inputs including EmissT , the pT, and mT of the two τ -leptons,∆ϕ(τ1,pmissT ), ∆ϕ(τ2,pmissT ), ∆η(τ1, τ2), m(τ1, τ2), meff , and mTsum. Cross-validation is usedwith three equal folds for a training, validation, and test set. To improve the reliability of thebackground modelling during training, input variables are binned such that the statisticalerror on the MC simulated background is less than 30% per bin. Furthermore, the maximumdepth of the individual decision trees is restricted to one so that each tree makes only oneselection on a variable. To avoid over-fitting, early-stopping is used, where trees cease tobe added during training if performance on the relevant validation set does not improveafter ten trees. The fitting procedure is further constrained to avoid over-fitting by usingregularisation techniques, where BDT2 and BDT4 use a higher amount of regularisationthan BDT1 and BDT3, and consequently, BDT2 and BDT4 occupy a smaller fraction ofthe total BDT score range compared with the others.6.2 Background estimateThe main backgrounds contributing to the Direct stau SRs are from multi-jet productionwith misidentified τ -leptons, W and Z boson production in association with jets, multi-bosonproduction, and events containing at least one top quark, referred to as Top background. Top– 10 –JHEP05(2024)150quark background events originate mostly from tt¯ production in association with additionaljets or an additional W or Z boson. The dominant SM backgrounds, W+jets, Z+jets,and top quark processes, are estimated by using MC simulation normalized to data indedicated control regions. The multi-jet background yield is estimated from data using theso-called ABCD method, described below, and MC simulation is used for all other minorSM backgrounds. The normalization factors obtained from control regions are applied forbackgrounds in the BDT training, as is the data-driven multi-jet estimate.6.2.1 Multi-jet background estimateBackground events contain a combination of ‘real’ τ -leptons, defined as correctly identifiedτ -leptons, or ‘misidentified’ τ -leptons, which can originate from a misidentified light-flavorquark or gluon jet, an electron, or a muon. Selected events from multi-jet production containmostly misidentified τ -leptons originating from misidentified jets.The multi-jet contribution is estimated by using a data-driven ABCD method, whichis common to both the Direct stau channel and the Intermediate stau channel described insection 7. Orthogonal regions are defined using two approximately uncorrelated discriminatingvariables, as shown schematically in figure 2. The number of multi-jet events in region D, ND,can be calculated from that in region A, NA, multiplied by the transfer factor T = NC/NB,where region D corresponds to one of the SRs and regions A–C are CRs. Intermediate VRs aredefined to verify the reliability of the transfer factor obtained from the ABCD estimate and toestimate the systematic uncertainty from the residual correlation between the discriminatingvariables. Non-multi-jet SM contributions are subtracted from data in each region using MCsimulation, and in the case of the Direct stau channel, the W+jets, Z+jets, and top quarkbackgrounds are subtracted after their normalization to data in their dedicated CRs.The discriminating variables used here are the τ -lepton identification (“very loose”τ -leptons as described in ref. [77], that fail to meet either the medium criterion or OSrequirement) and mT2 (10 < mT2 < 20GeV for regions B and C, 20 < mT2 < 30GeV forregions E and F, mT2 > 30GeV for A and D). The τ -lepton pT thresholds to ensure hightriggering efficiency are not applied, effectively lowering the τ -lepton pT thresholds to theonline thresholds of 80GeV and 50GeV (60GeV) for 2015–2017 (2018) data-taking. Thisincreases the statistics available and reduces the statistical uncertainty without affectingthe transfer factor within statistical uncertainties.Agreement between data and the estimated SM background is found in VR-F, withinstatistical uncertainties. A validation region (MJVR), with higher multi-jet purity andwith the τ -lepton pT thresholds applied (see table 2), is also checked. Good agreement isseen, as shown in figure 3, and a discussion of the systematic uncertainties of the total SMbackground can be seen in section 9. The correlation between the τ -lepton identificationand the kinematic variables is verified by studying the variation of the transfer factor as afunction of the kinematic variables used and is found to be negligible.The signal contamination in a certain region is defined as the ratio of the number ofsignal events to the sum of the number of signal events and SM background processes. Asignificant signal contamination in SM CRs can affect the model-dependent fit and reducethe sensitivity to SUSY scenarios. Thus the CRs (and VRs) are designed to have negligible– 11 –JHEP05(2024)150 dm 2 or m sum [GeV] ulti-jetVR−E ulti-jetVR−- sed for validation and systematic uncertainty estimate ery loose ad medium or tight ad rth g nal t SR ulti-jet CR−A sed for nominal ABCD method ulti-jet CR−B ulti-jet CR−CSR-D Figure 2. Illustration of the ABCD method for the multi-jet background determination. The controlregions A, B, and C and signal region D are drawn as light blue boxes. Shown in green and labeledas VR are the regions E and F, which are used to validate the ABCD method and to estimate thesystematic uncertainty.signal contamination for the SUSY scenarios considered in this paper, particularly for theSUSY particle mass ranges not excluded by previous searches.6.2.2 W+jets background estimateThe production of W+jets events with at least one misidentified τ -lepton is an importantbackground, composing up to 50% of the expected SM background in the Direct stau SRs.To correct the misidentified τ -lepton MC modelling and reduce the theoretical uncertaintyfrom the W+jets background, dedicated control regions pure in W bosons decaying into µν(WCR) are used to normalize the W+jets MC estimate to data.Events are required to satisfy a single-muon trigger with increasing pT thresholds of21 − 27GeV throughout data-taking to ensure the trigger efficiencies are in the plateauregion [87]. Events must contain exactly one isolated µ matching the trigger signature andone τ -lepton with the same charge selection as the signal regions. The τ -lepton is required tosatisfy the medium ID criterion, but fail to meet the tight criterion, to allow future searchestargeting direct stau production using one leptonically decaying τ -lepton and one hadronicallydecaying τ -lepton. The contribution from events with top quarks is suppressed by rejectingevents containing b-tagged jets. The contributions from Z+jets, top-quark and multi-bosonproduction are reduced with mT requirements.Thresholds on EmissT and lepton pT are applied to select events with kinematics similarto the SR definition. Events in the WCR are selected by requiring all four BDT scores tobe low, while the modelling is checked using a WVR with any one of the four BDT scoresbeing high. The definitions of the WCR and WVR are given in table 2. The purity ofthe selection in W+jets events is around 83% in the control and validation regions. The– 12 –JHEP05(2024)150010203040506070Events / 0.1 ATLAS1− = 13 TeV, 139 fbsMJVR Post-FitData Multi-jet Z+jetsSM Total W+jets TopMulti-boson Higgs) = [80, 1] GeV0χ∼, τ∼m() = [400, 1] GeV0χ∼, τ∼m(0 0.1 0.2 0.3 0.4 0.5 0.6BDT 1 score00.511.52Data / SM(a)1−10110210310Events / 0.025 ATLAS1− = 13 TeV, 139 fbsMJVR Post-FitData Multi-jet Z+jetsSM Total W+jets TopMulti-boson Higgs) = [80, 1] GeV0χ∼, τ∼m() = [400, 1] GeV0χ∼, τ∼m(0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65BDT 2 score00.511.52Data / SM(b)1−10110210310Events / 0.05 ATLAS1− = 13 TeV, 139 fbsMJVR Post-FitData Multi-jet Z+jetsSM Total W+jets TopMulti-boson Higgs) = [80, 1] GeV0χ∼, τ∼m() = [400, 1] GeV0χ∼, τ∼m(0 0.1 0.2 0.3 0.4 0.5 0.6BDT 3 score00.511.52Data / SM(c)1−10110210310Events / 0.005 ATLAS1− = 13 TeV, 139 fbsMJVR Post-FitData Multi-jet Z+jetsSM Total W+jets TopMulti-boson Higgs) = [80, 1] GeV0χ∼, τ∼m() = [400, 1] GeV0χ∼, τ∼m(0.35 0.36 0.37 0.38 0.39 0.4 0.41 0.42BDT 4 score00.511.52Data / SM(d)Figure 3. The BDT score distributions for the Direct stau multi-jet background in MJVR afterthe background-only fit, showing the scores for (a) BDT1, (b) BDT2, (c) BDT3, and (d) BDT4. Areduced range of BDT2 in (b) and BDT4 score in (d) are shown as they populate only a narrow rangeof the full score allowed. Representative SUSY scenarios are overlaid for illustration. The hatchedbands represent the combined statistical and systematic uncertainties of the total SM background.The lower panels show the ratio of data to the total SM background estimate.– 13 –JHEP05(2024)150Process W+jets TopRegion WCR WVR TCR TVRCharge combination OSN medium τ = 1 = 1 = 2N tight τ = 0 — —N e/µ = 1 µ = 1 µ = 0N b-jets = 0 ≥ 1 ≥ 1Trigger single µ single µ asymm. di-τpT(τ1) [GeV] - — > 95pT(τ2) [GeV] - — > 65max[pT(τ), pT(µ)] [GeV] > 95 > 95 —min[pT(τ), pT(µ)] [GeV] > 60 > 60 —EmissT [GeV] > 20 > 20 > 20mT,µ [GeV] ∈ (50, 150] ∈ (50, 150] —mT2 [GeV] > 30 > 30 > 30m(τ, µ) [GeV] > 120 > 120 —m(τ1, τ2) [GeV] — — > 120BDT score All < 0.5 Any > 0.5 -Process Z+jets Multi-boson Multi-jet InclusiveRegion ZCR ZVR MBVR MJVR InclVRCharge combination OSN medium τ = 2 = 2 = 2 = 2N e/µ = 0 = 0 = 0 = 0N b-jets = 0 = 0 = 0 = 0Trigger asymm. di-τ asymm. di-τ asymm. di-τ asymm. di-τEmissT [GeV] - > 20 < 50 > 20mT2 [GeV] > 30 > 30 > 30 > 30m(τ1, τ2) [GeV] < 120 < 120 > 120 > 120∆R(τ1, τ2) < 4 < 4 > 3 < 4BDT1 score ≤ 0.10 > 0.10 — ≤ 0.60BDT2 score — — — ≤ 0.70BDT3 score — — — ≤ 0.70BDT4 score ≤ 0.60 ≤ 0.60 > 0.61 ≤ 0.60Table 2. The definition of the control and validation regions for the Direct stau channel.signal contamination in the WCR and WVR is negligible due to the requirement of anisolated muon in these regions.6.2.3 Z+jets background estimateThe production of Z+jets where the Z boson decays into two τ -leptons is an irreduciblebackground in the Direct stau SRs, composing 7− 50% of the total SM background. TheZ+jets background is estimated by using MC simulation normalized to data in a controlregion, ZCR, which is similar to the SRs, but reverses the selection on m(τ1, τ2). Events with– 14 –JHEP05(2024)150a low BDT4 score are selected to avoid overlap with the validation region for multi-bosons(section 6.2.5). A selection on the score for BDT1 is used to create an orthogonal validationregion ZVR to check the modelling of the normalized Z+jets background. The purity of theselection in Z+jets events is around 85 − 90% in the control and validation regions. Thedefinitions of the ZCR and ZVR are shown in table 2.6.2.4 Top quark background estimateEvents containing one or more top quarks also contribute significantly to the total backgroundin the Direct stau SRs at 7 − 30%. The top quark background is estimated by using MCsimulation normalized to data in a control region, TCR, which, like the WCR, containsone isolated muon and one medium τ -lepton, but additionally requires a b-tagged jet. Avalidation region, TVR, is used to check the modelling of the top quark background in eventscloser to the signal regions with two medium τ -leptons and a b-tagged jet. The purity ofthe selection in top quark events is around 80− 92% in the control and validation regions.The definitions of the TCR and TVR are shown in table 2.6.2.5 Multiboson background estimateEvents with more than one SM W/Z boson are the dominant background in SR-BDT2 andSR-BDT4, with very small contributions from processes involving Higgs bosons in all SRs.These processes produce two real τ -leptons and EmissT , and this irreducible background istaken from MC simulation. The modelling is checked using two validation regions. The firsttargets multi-boson production (MBVR) using a similar selection to SR-BDT4 but with theselection on m(τ1, τ2) reversed. The second is a more inclusive validation region (InclVR)that checks the overall background estimate strategy and the modelling of the BDT scoredistributions. The definitions of these regions are shown in table 2. The background estimateis seen to model the data well in these two regions and the agreement in the BDT scoredistributions in InclVR is shown in figure 4.Overall, the background estimate strategy is seen to model the data well in all validationregions used for the Direct stau channel. The yields for the estimated SM background and dataare shown in figure 5 after the background-only fit to data is applied, as described in section 10.7 Intermediate stau channelThe Intermediate stau channel targets two different production mechanisms, mass-degenerateχ˜±1 χ˜02 (C1N2) and χ˜+1 χ˜−1 (C1C1), with decays into the lightest neutralino only throughintermediate stau and τ -sneutrinos, as shown in figure 1(b) and figure 1(c). The C1N2analysis is then sub-divided into final states where the two highest-pT τ -lepton candidateshave opposite sign (OS) charge (C1N2OS) or have same-sign (SS) charge (C1N2SS). TheSRs are separated into low-mass (LM) and high-mass (HM) regions to target respectivelylow or high χ˜±1 /χ˜02 mass regions. The high-mass regions target SUSY scenarios with massesabove that probed by the partial Run 2 result from the ATLAS Collaboration [14], and thelow-mass regions target SUSY scenarios with smaller mass splittings. The event selectionsof C1C1, C1N2OS and C1N2SS analyses are described in section 7.1, and the backgroundestimates are described in section 7.2.– 15 –JHEP05(2024)150020406080100120140160Events / 0.1 ATLAS1− = 13 TeV, 139 fbsInclVR Post-FitData Multi-jet Z+jetsSM Total W+jets TopMulti-boson Higgs) = [80, 1] GeV0χ∼, τ∼m() = [400, 1] GeV0χ∼, τ∼m(0 0.1 0.2 0.3 0.4 0.5 0.6BDT 1 score00.511.52Data / SM(a)1−10110210310410510Events / 0.1 ATLAS1− = 13 TeV, 139 fbsInclVR Post-FitData Multi-jet Z+jetsSM Total W+jets TopMulti-boson Higgs) = [80, 1] GeV0χ∼, τ∼m() = [400, 1] GeV0χ∼, τ∼m(0.1 0.2 0.3 0.4 0.5 0.6 0.7BDT 2 score00.511.52Data / SM(b)1−10110210310410510Events / 0.1 ATLAS1− = 13 TeV, 139 fbsInclVR Post-FitData Multi-jet Z+jetsSM Total W+jets TopMulti-boson Higgs) = [80, 1] GeV0χ∼, τ∼m() = [400, 1] GeV0χ∼, τ∼m(0 0.1 0.2 0.3 0.4 0.5 0.6 0.7BDT 3 score00.511.52Data / SM(c)1−10110210310410Events / 0.02 ATLAS1− = 13 TeV, 139 fbsInclVR Post-FitData Multi-jet Z+jetsSM Total W+jets TopMulti-boson Higgs) = [80, 1] GeV0χ∼, τ∼m() = [400, 1] GeV0χ∼, τ∼m(0.35 0.4 0.45 0.5 0.55 0.6BDT 4 score00.511.52Data / SM(d)Figure 4. The BDT score distributions for the Direct stau channel in InclVR after the background-only fit, showing the scores for (a) BDT1, (b) BDT2, (c) BDT3, and (d) BDT4. RepresentativeSUSY scenarios are overlaid for illustration. The hatched bands represent the combined statisticaland systematic uncertainties of the total SM background. Large uncertainties are seen in some binsdue to a few highly weighted Z+jets MC simulation events migrating across bins when consideringsystematic variations. The lower panels show the ratio of data to the total SM background estimate.– 16 –JHEP05(2024)1501−10110210310410510610Number of eventsData SM Total Multi-bosonW+jets Top Z+jetsHiggs Multi-jet) = (80, 1) GeV 01χ∼, τm() = (400, 1) GeV 01χ∼, τm(ATLAS-1 = 13 TeV, 139 fbsDirect stau channelVRs SRsTVR WVR ZVR MJVRMBVRInclVRSR-BDT1SR-BDT2SR-BDT3SR-BDT42−1−012totσ) / pred - nobs(nFigure 5. Comparison of the observed and expected event yields in all VRs and SRs after thebackground-only fit for the Direct stau channel. Representative SUSY scenarios are overlaid forillustration. The hatched band represents the combined statistical and systematic uncertainties of thetotal SM background. The lower panel shows the significance of any difference between the data andtotal SM background estimate yields.7.1 Event selectionThe SRs are optimised by varying the kinematic selection criteria resulting in six SRs definedto cover LM and HM regions for C1C1, C1N2OS and C1N2SS channels. Events used inthis channel must satisfy the same di-τ trigger described in section 6.1, or a combineddi-τ+EmissT trigger. To ensure the trigger efficiencies are in the plateau region, events thatsatisfy the di-τ + EmissT trigger for 2015–2017 (2018) data sample must have a τ -lepton withpT > 50 (75)GeV, a second τ -lepton with pT > 40GeV (both matching the trigger signature),and the reconstructed EmissT > 150GeV.For the C1N2OS (C1N2SS) channels, events are required to have at least two mediumτ -leptons with OS (SS), while for the C1C1 channel, events are required to have exactly twomedium τ -leptons with OS. In the LM signal regions, SR-C1C1-LM and SR-C1N2OS-LM,at least one of the τ -leptons must satisfy a tighter identification criteria, referred to as atight τ -lepton [77], to suppress quark or gluon jets misidentified as τ -leptons in the lowerEmissT region. Additionally, EmissT > 60GeV is required in these two SRs to further suppressbackground from misidentified τ -leptons.To discriminate the SUSY signal events from SM background processes, additionalrequirements are applied, as outlined in table 3. Background processes producing τ -leptonpairs from low-mass resonances, or from Z or Higgs bosons, are suppressed using high m(τ1, τ2)selections, while top quark processes are suppressed with a b-jet veto. Contributions from tt¯and WW events are reduced using lower bounds on mT2 and mTsum.– 17 –JHEP05(2024)150SR- C1C1-LM C1N2OS-LM C1N2SS-LM C1C1-HM C1N2OS-HM C1N2SS-HMTrigger asymm. di-τ di-τ + EmissTEmissT [GeV] < 150 > 150N medium τ =2 ≥ 2 ≥ 2 =2 ≥ 2 ≥ 2N tight τ ≥ 1 ≥ 1 — — — —Charge combination OS OS SS OS OS SSN b-jets =0 =0 =0 =0 =0 =0N jets — < 3 < 3 — — —|∆ϕ(τ1, τ2)| > 1.6 — > 1.5 — — —m(τ1, τ2) [GeV] > 120 > 120 — > 120 > 120 —EmissT [GeV] > 60 > 60 — — — —mTsum [GeV] — — > 200 > 400 > 400 > 450mT2 [GeV] > 80 > 70 > 80 > 85 > 85 > 80Table 3. Summary of the selection requirements for the χ˜+1 χ˜−1 /χ˜±1 χ˜02 pair production SRs for theIntermediate stau channel.7.2 Background estimateThe dominant backgrounds in the Intermediate stau SRs are multi-jet production withmisidentified τ -leptons, W+jets and Z+jets, multi-boson production, and top quarkbackgrounds. The multi-jet background accounts for 28–48% (<17%) of the total SMyield in high-mass SRs (low-mass SRs) for all three scenarios, while W+jets accounts for 4–16% of the total background. The multi-jet and W+jets background estimates are presentedin section 7.2.1 and section 7.2.2, respectively, and use the same methods described insections 6.2.1 and 6.2.2. A dedicated CR is used to estimate the top quark backgroundsfor the SS final state, where misidentified τ -lepton contributions are a dominant source,as described in section 7.2.3.Multi-boson production contributes mainly through events containing real τ -leptonsresulting from WW and ZZ decaying into a ττνν final state in C1C1 and C1N2OS scenarios,while in the C1N2SS scenario, the main process is WZ decaying into a τττν final state.The contribution from real τ -leptons exceeds 85–90% in Z+jets and diboson production.Additionally, the real τ -lepton contribution exceeds 80% in backgrounds containing topquarks in OS final states. The estimation of the Top, multiboson, and Z+jets backgroundsis described in section 7.2.4.7.2.1 Multi-jet background estimateThe same approach for the multi-jet background estimate described in section 6.2.1 is used forthe Intermediate stau channels, with the following changes. The sign of the electric charge ofthe two τ -leptons (OS or SS), and mT2 and mTsum are used to define the control regions andvalidation regions, as shown in table 4. In the C1C1 and C1N2OS scenarios, the mT2 variableis used to distinguish the regions of the ABCD method, while mTsum is used for the C1N2SSchannel. In all validation regions and both sets of CR-B and CR-C, the events are requiredto satisfy a di-τ trigger, instead of the di-τ + EmissT trigger in the Intermediate stau channel– 18 –JHEP05(2024)150Channel variable CR-B / CR-C VR-E / VR-F CR-A / SRC1C1-LM mT2 [GeV] ∈ (15, 35] ∈ (35, 80] > 80EmissT [GeV] ∈ (10, 150] ∈ (10, 150] ∈ (60, 150]C1C1-HM mT2 [GeV] ∈ (35, 60] ∈ (60, 85] > 85mTsum [GeV] ∈ (100, 300] ∈ (200, 400] > 400EmissT [GeV] > 50 > 50 > 150C1N2OS-LM mT2 [GeV] ∈ (15, 35] ∈ (35, 70] > 70EmissT [GeV] ∈ (10, 150] ∈ (10, 150] ∈ (60, 150]C1N2OS-HM mT2 [GeV] ∈ (35, 60] ∈ (60, 85] > 85mTsum [GeV] ∈ (150, 300] ∈ (200, 400] > 400EmissT [GeV] > 50 > 50 > 150C1N2SS-LM mTsum [GeV] < 100 ∈ (100, 200] > 200|∆ϕ(τ1, τ2)| < 1.5 < 1.5 > 1.5C1N2SS-HM mTsum [GeV] ∈ (100, 200] ∈ (200, 450] > 450EmissT [GeV] > 50 > 50 > 150Table 4. The definition of the ABCD regions for all channels in the Intermediate stau scenarios.Only those requirements that differ between the CRs/VRs and the SRs are listed.to increase the statistics from the lower EmissT requirements. The offline EmissT > 150GeVrequirement is also removed. The di-τ trigger requires the identification of two hadronicallydecaying τ -leptons with transverse momenta exceeding the same set of thresholds for thedi-τ + EmissT trigger, such that no bias on the τ -leptons is introduced.The estimated SM background is found to agree with the data for the mT2 and mTsumdistributions in the validation regions, as shown in figure 6. Several signal reference pointstargeting sensitivity to LM and HM SRs are also shown to highlight the small signalcontamination in the VRs.7.2.2 W+jets background estimateThe W+jets background is an important background for the Intermediate stau channel. Asimilar approach as in section 6.2.2 is used and definitions for the W+jet CRs and VRs (WCRand WVR) for OS/SS selections are shown in table 5. Top quark background events in theOS final state are labeled as “top-tagged” if they satisfy a dedicated selection; these eventsare vetoed in the WCR to suppress top quark background processes. Events are top-taggedusing the contransverse mass variable [88], mCT, to identify events that are kinematicallycompatible with tt¯ pair production. Furthermore, top-tagged events must have at least twojets and the scalar sum of the pT of at least one combination of two jets and the two leptonsin the event must exceed 100GeV. The orthogonality of the WCRs and WVRs is ensuredusing mT2(τ, µ) selections. The purity of the selection in W+jets events is 73–85% in all Wcontrol and validation regions. The signal contamination in the WCR and WVR is negligibledue to the requirement of a muon in the event.The multi-jet contribution in the WCRs and WVRs is small and is estimated using thelack of correlation of the charge of the faked muon and τ -lepton in multi-jet production,– 19 –JHEP05(2024)150020406080100Events / 5 GeV-1 = 13 TeV, 139 fbsMJVR-C1C1-HM post-fitATLAS Data SM TotalMulti-jet Multi-bosonTop HiggsW+jets Z+jets) = (700, 400) GeV (x20)01χ∼, ±1χ∼m() = (1100, 0) GeV (x500)01χ∼, ±1χ∼m(60 65 70 75 80 85 [GeV]T2m012Data / SM (a)020406080100Events / 5 GeV-1 = 13 TeV, 139 fbsMJVR-C1N2OS-HM post-fitATLAS Data SM TotalMulti-jet Multi-bosonTop HiggsW+jets Z+jets) = (700, 400) GeV (x20)01χ∼, 02χ∼/±1χ∼m() = (1100, 0) GeV (x500)01χ∼, 02χ∼/±1χ∼m(60 65 70 75 80 85 [GeV]T2m012Data / SM (b)051015202530Entries / 25 GeV [GeV]T summ210Data / SM100 110 120 130 140 150 160 170 180 190 200ATLASs = 13 TeV, 139 fb-1MJVR-C1N2SS-LM post-fit) = (375, 175) GeV (x20)010, ∼χ2±/∼χ1m(∼χData SM TotalMulti-jet Multi-bosonTop HiggsW+jets Z+jets(c)Figure 6. The kinematic distributions of mT2 and mTsum in the multi-jet background VR-F after thebackground-only fit for (a) SR-C1C1-HM (MJVR-C1C1-HM), (b) SR-C1N2OS-HM (MJVR-C1N2OS-HM) and (c) SR-C1N2SS-LM (MJVR-C1N2SS-LM), respectively. Representative SUSY scenarios areoverlaid for illustration and scaled appropriately for improved visibility. The hatched bands representthe combined statistical and systematic uncertainties of the total SM background. The lower panelsshow the ratio of data to the total SM background estimate.resulting in equal SS and OS lepton contributions. This is not the case for other processeslike W+jets production, which is dominated by gu/gd-initiated processes that often give riseto a jet originating from a quark, the charge of which is anti-correlated with the W -bosoncharge. The contribution from multi-jet production in the WCRs and WVRs is estimatedusing data in regions selected with the same requirements as the CR/VR but requiring theelectric charge of the two leptons to be different, i.e. SS for OS CR/VR, and OS for SSCR/VR. Event yields from SM processes other than multi-jet production are subtracted fromthe data in these regions using MC simulation, leaving only the multi-jet estimate, whichis assumed to be equal to that in the CR/VR. Based on studies with simulated samples,a conservative systematic uncertainty of 100% is assigned to the estimate of the multi-jetevent yield in the W+jets CRs and VRs.– 20 –JHEP05(2024)150Process W+jets TopRegion WCR-OS WVR-OS WCR-SS WVR-SS TCR-SS-HM TVR-SS-HM TVR-OS-LM TVR-OS-HMCharge combination OS SS SS OSTrigger single µ di-τ + EmissT asymm. di-τ di-τ + EmissTN medium τ = 1 < 2 ≥ 2N tight τ - - ≥ 1N loose τ - ≥ 1 -N “very loose” τ - ≥ 2 -N e/µ = 1 µ - -N b-jets = 0 ≥ 1 ≥ 1 = 0pT(τ) [GeV] > 50 - -pT(µ) [GeV] > 40 - -Top tagged veto - - -mT,µ [GeV] < 140 ∈ (50, 150] - -mT,µ +mT,τ [GeV] - > 80 - -EmissT [GeV] > 60 > 50 > 150 ∈ (20, 150] > 150m(τ1, τ2) [GeV] — — — — — — > 120 > 120mT2 [GeV] ∈ (40, 70] > 70 < 60 > 60 — — > 40 > 30mTsum [GeV] — — — — < 400 > 400 > 150 > 150|∆ϕ(τ1, τ2)| — — — — — — > 1.0 > 1.0Process Z+jets Multi-bosonsRegion ZVR-OS-LM ZVR-OS-HM MBVR-OS-LM MBVR-OS-HM MBVR-SSCharge combination OS OS SSTrigger asymm. di-τ di-τ + EmissT asymm. di-τ di-τ + EmissT single µN medium τ ≥ 2 = 1N tight τ ≥ 1 —N µ - = 2N b-jets = 0 = 0EmissT [GeV] ∈ (40, 150] > 150 ∈ (70, 150] > 150 > 100m(τ1, τ2) [GeV] < 70 < 60 < 80 < 90 —∆R(τ1, τ2) < 1.0 < 1.0 < 1.2 < 1.2 —|∆ϕ(τ1, τ2)| — — < 1.0 < 1.0 —|∆ϕ(τ1,pmissT )| — — — — ≤ 1.75mTsum [GeV] — — > 180 > 180 —mT2 [GeV] < 60 < 60 > 60 > 60 —Table 5. The definition of the control and validation regions for the Intermediate stau channel.7.2.3 Top quark background estimate for C1N2SSThe top quark background in SR-C1N2SS-LM is very small (<1%) and mostly composedof two real τ -leptons, and hence is estimated from MC simulation. However, the top quarkbackground is a dominant contribution in SR-C1N2SS-HM and mostly consists of one ortwo misidentified τ -leptons from tt¯ and Wt production. To estimate this background inSR-C1N2SS-HM, a data-driven approach is used to normalize the top quark backgroundMC simulation to data using a dedicated top-enriched CR (TCR-SS-HM) and validated in atop-enriched VR (TVR-SS-HM), described in table 5. The τ -lepton identification workingpoint was loosened to increase the statistics in these regions, while high EmissT is requiredto suppress the contribution from multi-jet processes. The top quark background purityin the top quark CR and VR for SR-C1N2SS-HM (TCR-SS-HM and TVR-SS-HM) is highand exceeds 83% in both regions.– 21 –JHEP05(2024)1507.2.4 Top, multiboson, and Z+jets background estimatesAdditional irreducible SM backgrounds are estimated from MC simulation and checked indedicated VRs. The top quark background contributions in OS final states are small andamount to about 7–14% of the total background in all SRs. Two regions enriched in top-quark events are defined to validate the top quark modelling in OS events, TVR-OS-LM andTVR-OS-HM for the low and high-mass SR kinematics, respectively, and are defined in table 5.The Z+jets contribution is 16–21% of the total background in all OS SRs and mainlyarises from Z → ττ decays. The multi-boson background accounts for 25–50% of the totalSM contribution in the SRs and mainly arises from WW → τντν and ZZ → ττνν events.Over 96% of τ -leptons from Z+jets and multi-bosons events in the SRs are real. To validatethe MC modelling and normalization of the Z+jets and multi-boson processes, four dedicatedVRs are defined: ZVR-OS-LM (MBVR-OS-LM) is defined to validate Z+jets (multi-boson)MC modelling in the low-mass SRs, while ZVR-OS-HM (MBVR-OS-HM) is defined tovalidate the MC modelling in the high-mass SRs, as shown in table 5.The purity of the selection in tt¯ and Z+jets events is in the range of 81–99% in therespective validation regions, and the purity of the selection in multi-boson events is 41–68%in the OSMBVRs. The signal contamination in the VRs is small due to the b-jet requirementin the top-quark VRs and the m(τ1, τ2) upper thresholds in the Z+jets and multi-boson VRs.In the SS final state, the multi-boson background is estimated from MC simulation andvalidated in a dedicated VR, MBVR-SS, also defined in table 5. The selection is enriched inmulti-boson production, resulting in a multi-boson purity of 73%.The agreement between data and the SM prediction is shown in all validation and signalregions for the Intermediate stau channels in figure 7 after the background-only fit to datais applied, as described in section 10.8 Intermediate Wh channelThe search for the production of mass-degenerate χ˜±1 χ˜02 decaying via an intermediate Wand h boson, as shown in figure 1(d), is described in this section. The analysis targets theleptonic decay of the W boson to an electron or muon, and the decay of the Higgs bosonto two OS τ -leptons. The event selection of the Intermediate Wh channel is described insection 8.1 and the background estimates are described in section 8.2.8.1 Event selectionEvents for the Intermediate Wh channel must have at least two hadronically decaying τ -leptons with OS and exactly one light lepton (e or µ). The selected light lepton must satisfythe signal electron or muon requirements described in section 4 and also satisfy the singleelectron or single muon trigger with a threshold of pT > 27GeV to ensure the triggeringefficiency is in the plateau region. Two SRs are defined to cover low-mass (SR-Wh-LM) andhigh-mass (SR-Wh-HM) χ˜±1 χ˜02 production, with an overlapping selection, as shown in table 6.To set limits in a SUSY scenario, the SR with the best expected sensitivity is used. Theinvariant mass of the two τ -leptons, m(τ1, τ2), is required to be compatible with the Higgsboson mass, while the b-jet veto and |∆R(τ1, τ2)| requirements suppress the top quark and– 22 –JHEP05(2024)150WVR-OSWVR-SSZVR-OS-LMZVR-OS-HMTVR-OS-LMTVR-OS-HMTVR-SS-HMMBVR-OS-LMMBVR-OS-HMMBVR-SSSR-C1C1-LMSR-C1C1-HMSR-C1N2OS-LMSR-C1N2OS-HMSR-C1N2SS-LMSR-C1N2SS-HM110210310410510Number of eventsData SM Total Multi-bosonW+jets Top quark Z+jetsHiggs Multi-jet) = (300, 150) GeV 01χ∼, ±1χ∼m( ) = (700, 400) GeV 01χ∼, ±1χ∼m() = (157, 92) GeV 01χ∼, 02χ∼/±1χ∼m( ) = (1100, 0) GeV 01χ∼, 02χ∼/±1χ∼m(ATLAS-1 = 13 TeV, 139 fbsIntermediate stau channelWVR-OSWVR-SSZVR-OS-LMZVR-OS-HMTVR-OS-LMTVR-OS-HMTVR-SS-HMMBVR-OS-LMMBVR-OS-HMMBVR-SSSR-C1C1-LMSR-C1C1-HMSR-C1N2OS-LMSR-C1N2OS-HMSR-C1N2SS-LMSR-C1N2SS-HM2−1−012totσ) / pred - nobs(nFigure 7. Comparison of the observed and expected event yields in all VRs and SRs after thebackground-only fit for the signal regions targeting chargino/neutralino production and decay viaintermediate staus. Representative SUSY scenarios are overlaid for illustration. The hatched bandrepresents the combined statistical and systematic uncertainties of the total SM background. The lowerpanel shows the significance of any difference between the data and total SM background estimate yields.SR-Wh-LM SR-Wh-HMTrigger Single e or µN medium τ ≥ 2N e/µ = 1Charge combination OSN b-jets = 0|∆ϕ(τ1, τ2)| < 3∆R(τ1, τ2) — < 2.2m(τ1, τ2) [GeV] ∈ [90, 130] ∈ [80, 160]mT2 [GeV] > 100 > 80mT,ℓ [GeV] — > 80mTsum [GeV] — > 450Table 6. Summary of selection requirements for the SRs of χ˜±1 χ˜02 pair production decaying into anintermediate Wh for low-mass and high-mass regions. The two SRs are not orthogonal.fake τ -lepton backgrounds, respectively. High mT2, mT,ℓ and mTsum requirements providegood discrimination between SUSY signal events and SM background.8.2 Background estimateThe SM backgrounds for a final state with two hadronically decaying τ -leptons from aHiggs boson decay and one light lepton from a W -boson decay can be separated into twogroups. The first group is composed of events with a real light lepton and two real τ -leptons,– 23 –JHEP05(2024)150and is dominated by multi-boson processes that are estimated by using MC simulation, asdescribed in section 8.2.3. The second group includes processes with one or two τ -leptonsfrom misidentified jets. Events with a single misidentified τ -lepton are dominated by eventswith a top quark, which is estimated by using MC normalized to data in a dedicated CRand described in section 8.2.2. Events with two misidentified τ -leptons are mostly fromW+jets events and are estimated by using a data-driven technique — the fake factor method— as described in section 8.2.1. All other SM backgrounds are estimated directly from MCsimulation. Overall, the dominant background contributions in both SRs are from top quarkand multi-boson processes, and account for 89%–90% of the total background.8.2.1 Misidentified τ -lepton background estimateThe W+jets process dominates the background with two misidentified τ -leptons, with lessthan 7% contribution from other processes. The fake factor method estimates all processeswith two misidentified τ -leptons using a control data sample (FFCR) with τ -leptons thatfail to meet the nominal τ -lepton identification requirement. This estimate is obtained asthe product of the number of FFCR events and the fake factor (FF), which relates thenumber of events with looser τ -lepton candidates to the number where τ -leptons meet thenominal identification criteria.To compute the FF, an anti-τ -lepton (T¯ ) is defined that satisfies a looser set ofidentification criteria, but fails to meet the medium identification criteria of τ -leptons (T ).The FF value is the ratio of T events to T¯ events. To estimate the two misidentified τ -leptoncontributions, three control regions are defined using the identification criteria applied to thetwo highest-pT τ -leptons: T¯ T¯ , T T¯ , and TT . The estimate of the contribution from processeswith two misidentified τ -leptons (Nfakes) can be written as the product of the two fake factors(FFCRτi ) and the number of events from the T¯ T¯ region (NT¯T¯, fake bkg):Nfakes = NT¯T¯, fakes × FFCRτ1 × FFCRτ2 , (8.1)where the individual fake factors for the two τ -leptons are written as:FFCRτ1 =Ndata,TT¯ −N≥1 truth τMC,TT¯Ndata,T¯T¯ −N≥1 truth τMC,T¯T¯and (8.2)FFCRτ2 =Ndata,TT −N≥1 truth τMC,TTNdata,TT¯ −N≥1 truth τMC,TT¯. (8.3)The contamination from events with at least one real τ -lepton (N≥1 truth tauMC ) is estimatedfrom MC simulation and subtracted when calculating the ratio.The fake factors are calculated in a W -enriched control region (FFCR-Wh), whichmaximises available statistics by loosening kinematic selection requirements and remainsorthogonal to the SRs by inverting the OS requirement, as summarised in table 7.The fake factor dependencies on the parameters of the τ -leptons, such as the numberof tracks, pT and |η|, are studied and are found to be minimal except for the number oftracks (1-prong or 3-prong τ -leptons). The fake factors are measured in bins of pT and|η|, separately for 1-prong and 3-prong τ -leptons, with the binning optimised based on the– 24 –JHEP05(2024)150FFCR-Wh FFVR-WhN medium τ — ≥ 2N “very loose” τ ≥ 2 —Charge combination SS OSN e/µ = 1N b-jets = 0|∆ϕ(τ1, τ2)| < 3m(τ1, τ2) [GeV] > 20 ∈ [40, 160]mT2 [GeV] > 20 > 30Table 7. The definition of the fake factor control and validation regions, FFCR-Wh and FFVR-Wh,respectively.1−10110210310410Events / 10 GeVData SM TotalτMis-ID Multi-bosonTop quark Z+jetsHiggs W+jets) = (225, 75) GeV01χ∼, 02χ∼/±1χ∼m(ATLAS-1 = 13 TeV, 139 fbsFFVR-Wh, post-fit20 40 60 80 100 120 140 160 180 [GeV]τTp00.511.52Data / SM(a)1−10110210310410Events / 10 GeVData SM TotalτMis-ID Multi-bosonTop quark Z+jetsHiggs W+jets) = (225, 75) GeV01χ∼, 02χ∼/±1χ∼m(ATLAS-1 = 13 TeV, 139 fbsFFVR-Wh, post-fit40 60 80 100 120 140 160 180 [GeV]T2m00.511.52Data / SM(b)Figure 8. The distributions of (a) the highest-pT τ -lepton transverse momentum pτT and (b) mT2variables in FFVR-Wh after the background-only fit. The misidentified contribution with at least twomisidentified τ -leptons (Mis-ID τ) is estimated from data using the fake factor method. RepresentativeSUSY scenarios are overlaid for illustration. The hatched bands represent the combined statisticaland systematic uncertainties of the total SM background. The lower panels show the ratio of data tothe total SM background estimate.available statistics. The fake factor for the two highest-pT τ -leptons is similar at around0.4 (0.1) for the 1-prong (3-prong) τ -leptons. The fake factor estimate is validated in amisidentified τ -lepton dominated VR (FFVR-Wh) with a selection similar to the SR-Wh-LM with loosened selections on m(τ1, τ2) and mT2, as shown in table 7. The kinematicdistributions in FFVR-Wh are shown in figure 8 and good agreement between data andSM prediction is observed.8.2.2 Top quark background estimateThe top quark background is small in SR-Wh-HM and is accounted for in the estimate withthe FF method since it is dominated by two misidentified τ -leptons. However, in SR-Wh-LMthe top quark background is more important and is comprised mainly of tt¯ events with one– 25 –JHEP05(2024)150Process Top Multi-bosonRegion TCR-Wh TVR-Wh MBVR-WhN medium τ ≥ 2Charge combination OSN e/µ = 1Trigger single e/µ|∆ϕ(τ1, τ2)| < 3N b-jets ∈ [1, 2] = 0pTτ2 [GeV] - > 30mT,l [GeV] - > 70m(τ1, τ2) [GeV] ∈ (40, 160] ∈ (40, 70]mTsum [GeV] > 250 —mT2 [GeV] ∈ (20, 80] > 80 < 80Table 8. The definition of the top quark and multi-boson control and validation regions for theIntermediate Wh channel.W -boson decaying into an electron or muon, and the other into a τ -lepton — the secondτ -lepton typically originates from a misidentified jet. The top quark background is estimatedfrom MC and normalized to data using a top quark enriched control region (TCR-Wh) andvalidated in a top-quark VR (TVR-Wh), as defined in table 8. MC simulation shows thetop quark background composition is similar across the CR, VR and SR. The selectionfor the control and validation region are similar to the SR selection, but with one or twob-jets required to be orthogonal to the SR. To increase the statistics, the OS requirementis removed and the m(τ1, τ2) requirement is also loosened, and to improve the purity ofthe top quark background, high mTsum is required. The top quark background purity isbetween 73%–81% in the CR and VR.8.2.3 Multi-boson background estimateMulti-boson production is the dominant SM contribution in both the Intermediate Wh SRs.The main contribution is WZ production with both the bosons decaying leptonically, givingone light lepton and two real τ -leptons in the SRs. Smaller contributions in SR-Wh-LMstem from ZZ or WW production decaying into one light lepton, one real τ -lepton, andone misidentified τ -lepton.The multi-boson background is estimated from MC simulation and validated in a multi-boson enriched region, MBVR-Wh, defined in table 8. The selection on the invariant mass ofthe τ -leptons is lowered compared with the SRs, and an upper threshold on mT2 of 80GeV isrequired. The multi-boson purity is found to be 61% in MBVR-Wh. The good agreementbetween data and the SM prediction is shown in the validation and signal regions for theIntermediate Wh channels in figure 9.– 26 –JHEP05(2024)150TVR-Wh MBVR-Wh SR-Wh-LM SR-Wh-HM1−10110210310Number of eventsData SM Total Multi-bosonTop quark Z+jets HiggsτMis-ID ) = (225, 75) GeV 01χ∼, 02χ∼/±1χ∼m(ATLAS-1 = 13 TeV, 139 fbsIntermediate Wh channelTVR-WhMBVR-WhSR-Wh-LMSR-Wh-HM2−1−012totσ) / pred - nobs(nFigure 9. Comparison of the observed and expected event yields in the TVRs and MBVRs andtwo SRs after the background-only fit. Representative SUSY scenarios are overlaid for illustration.The hatched band represents the combined statistical and systematic uncertainties of the total SMbackground. The lower panel shows the significance of any difference between the data and total SMbackground estimate yields.9 Systematic uncertaintiesSystematic uncertainties have an impact on the background and signal estimates in thecontrol and signal regions. Uncertainties arising from experimental effects and theoreticalsources are considered. The main sources of experimental systematic uncertainty in the SMbackground estimates include τ -lepton and jet energy calibrations and resolution, τ -leptonidentification, systematic effects due to the presence of pileup events, and uncertaintiesrelated to the modelling of EmissT in the simulation. The uncertainties in the energy andmomentum scale of each of the objects entering the EmissT calculation are estimated, as wellas the uncertainties in the soft-term resolution and scale [89]. A variation in the pileupreweighting of the MC simulated event samples is included to cover the uncertainty in theratio of the predicted and measured inelastic cross-section [90]. The uncertainty in thecombined 2015–2018 integrated luminosity was measured to be 1.7% [91], obtained usingthe LUCID-2 detector [92] for the primary luminosity measurements.Theoretical uncertainties affecting the main irreducible backgrounds W+jets, Z+jets,top quark processes, and dibosons, are estimated by varying the generator parameters:renormalization and factorisation scales, as well as PDFs, following the PDF4LHCrecommendations [93]. Uncertainties due to the choice of renormalization and factorisationscales are included by varying the scales from their nominal values by a factor of two or onehalf — the two scale variations are taken as uncorrelated and the additional coherent up/downvariation of the two scales is also considered. Additionally, cross-section uncertainties areassigned to be included in the normalization of the signal and the background processestaken directly from MC simulation.– 27 –JHEP05(2024)150Several sources of uncertainty are considered for the ABCD method used to determinethe multi-jet background estimate for Direct stau channel and the Intermediate stau channel,they include: the correlation between the τ -lepton identification and the kinematic variablesmT2, the limited number of events in the CRs, and the subtraction of other SM backgrounds.The systematic uncertainty in the correlation is estimated by using the transfer factor fromVR-E to VR-F instead of that from CR-B to CR-C. The systematic uncertainty in thenon-multi-jet background subtraction in the control regions is estimated by consideringthe total uncertainties of the MC estimates of the non-multi-jet background in the CRs.The systematic uncertainty due to the limited number of events in the control regions isestimated by taking the statistical uncertainty of the event yields in these control regions.The statistical uncertainty from the data yields in every CR is propagated to the uncertaintyon the background estimation in the SRs.The different sources of uncertainty considered for the fake factor method used todetermine the misidentified background with at least two misidentified τ -leptons in theIntermediate Wh channel are as follows. The fake factor values are varied up and down bytheir statistical uncertainties and the difference is used as a source of uncertainty. A further30% systematic uncertainty in the subtracted MC processes is used as a conservative estimateon the systematic uncertainty from MC subtractions in the FFCR-Wh. The differencebetween the quark/gluon contributions in the fake factor control regions and signal regionswas studied and found to be negligible compared with the uncertainties placed on the overallnormalization and statistical contributions. The systematic uncertainties and their sizesin each SR are summarized in figure 10.The dominant contributions of systematic uncertainties in all scenarios are mainly fromthe statistics of the MC samples, the normalization uncertainties of the multi-jet background,the τ -lepton identification and the energy scale, jet energy scale and resolution. In theIntermediate stau channel, uncertainties in the multi-jet estimate are also important. Inthe Direct stau and Intermediate Wh channels, multi-boson theory uncertainties representa major contribution to the systematics.10 ResultsThe results of the Direct stau, Intermediate stau, and Intermediate Wh channels are presentedin this section as background-only combined fits to the control and signal regions, along withmodel-dependent and model-independent fits for BSM signal exclusion.10.1 Direct stau production analysisThe expected and observed numbers of events in the Direct stau signal regions are shown intable 9, where the observations are consistent with the SM expectations. The distributions ofthe four BDT scores are shown in figure 11. All the SR-BDT strongly overlap and show acommon deficit of significance 0.7− 1.3σ. For example, the single event in data selected bySR-BDT4 is also selected by the other three SR-BDT, while the four events in SR-BDT2 arealso selected by SR-BDT3. The W+jets, Z+jets, and top quark backgrounds are normalizedto data in their respective control regions, obtaining normalization factors of 0.93 ± 0.11,0.91 ± 0.07, and 0.85 ± 0.05, respectively, as shown in table 10.– 28 –JHEP05(2024)150SR-BDT1SR-BDT2SR-BDT3SR-BDT4SR-C1C1-LMSR-C1C1-HMSR-C1N2OS-LMSR-C1N2OS-HMSR-C1N2SS-LMSR-C1N2SS-HMSR-Wh-LMSR-Wh-HM00.20.40.60.81Relative uncertainty-1 = 13 TeV, 139 fbsATLAS Direct stau channel Intermediate stau channel Intermediate Wh channelTotal uncertaintyMC Statistical uncertainty NormalisationTau identification and energy scale MET soft-term resolutionMulti-jet background Multi-boson theory uncertaintyFake Tau estimation Jet energy scale and resolutionFigure 10. Summary of the total uncertainty in the predictions of the background event yieldsof each SR in the three search channels. The dominant systematic contributions are indicated byindividual dashed/dot-dashed/dotted lines. The total uncertainty in each SR is denoted by the solidblack line. For simplicity, the individual uncertainties are added in quadrature for each category,without accounting for correlations. Theoretical uncertainties in the multiboson MC simulation-basedestimates are grouped under the “Multi-boson theory uncertainty” category, while the “Normalisation”category includes the statistical uncertainties of the data counts in the CRs and the uncertainty fromthe fitted normalization factors.The model-dependent fits using the results from the signal and control regions are usedto place exclusion limits at 95% CL on Direct stau production. SR-BDT4 has a low predictedyield, so 10,000 pseudoexperiments are used to calculate the exclusion limits. Since thefour main SR-BDT overlap, the SR with the lowest expected CLs value for each signalscenario is used to set the limit, statistically combining the two bins each within SR-BDT1,SR-BDT2, and SR-BDT3 as two distinct regions. The exclusion limits for mass-degenerateτ˜L,R production are shown in figure 12(a), where stau masses up to 500GeV are excludedfor massless χ˜01. The limits are improved relative to previous results, particularly towardssmaller τ˜ -χ˜01 mass splittings, as well as at higher τ˜ masses. The observed limits are strongerthan the expected limit due to the small observed deficit. The feature in the observed limitaround stau masses of 250 − 300GeV is due to a transition from one SR-BDT to anotherbeing used to set the limit (a similar effect is also seen for figures 12(b)–12(c)).The exclusion limits for τ˜L and τ˜R production separately are shown in figure 12(b) andfigure 12(c), respectively. Similar improvements are seen in the sensitivity to τ˜L productionas in the mass-degenerate case, with stau masses excluded up to 425GeV. Sensitivity to τ˜Rproduction is obtained for the first time at ATLAS, with masses excluded up to 350GeV.10.2 Intermediate stau analysisThe observed number of events in each SR and the expected contributions from SM processesare given in table 11. The contributions of multi-jet, W+jets and top quark events are– 29 –JHEP05(2024)1500102030405060708090100Events / 0.05 ATLAS1− = 13 TeV, 139 fbsBDT_Preselection Post-FitData Multi-jet Z+jetsSM Total W+jets TopMulti-boson Higgs) = [80, 1] GeV0χ∼, τ∼m() = [140, 60] GeV0χ∼, τ∼m(0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9BDT 1 score00.511.52Data / SM(a)1−10110210310410Events / 0.03 ATLAS1− = 13 TeV, 139 fbsBDT_Preselection Post-FitData Multi-jet Z+jetsSM Total W+jets TopMulti-boson Higgs) = [160, 1] GeV0χ∼, τ∼m() = [240, 80] GeV0χ∼, τ∼m(0.2 0.3 0.4 0.5 0.6 0.7 0.8BDT 2 score00.511.52Data / SM(b)1−10110210310410510Events / 0.07 ATLAS1− = 13 TeV, 139 fbsBDT_Preselection Post-FitData Multi-jet Z+jetsSM Total W+jets TopMulti-boson Higgs) = [200, 100] GeV0χ∼, τ∼m() = [280, 160] GeV0χ∼, τ∼m(0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9BDT 3 score00.511.52Data / SM(c)1−10110210310410Events / 0.02 ATLAS1− = 13 TeV, 139 fbsBDT_Preselection Post-FitData Multi-jet Z+jetsSM Total W+jets TopMulti-boson Higgs) = [400, 1] GeV0χ∼, τ∼m() = [400, 160] GeV0χ∼, τ∼m(0.35 0.4 0.45 0.5 0.55 0.6 0.65BDT 4 score00.511.52Data / SM(d)Figure 11. The BDT score distributions for the Direct stau channel after the background-onlyfit, showing the scores for (a) BDT1, (b) BDT2, (c) BDT3, and (d) BDT4, before the selections onthe BDT scores are made. The black arrow depicts the BDT score selection for the SR-BDT. Afew example SUSY scenarios targeted by each BDT are overlaid for illustration. The hashed bandsrepresent the combined statistical and systematic uncertainties of the total SM background. The lowerpanels show the ratio of data to the total SM background estimate.– 30 –JHEP05(2024)150SM process SR-BDT1 SR-BDT1_bin0 SR-BDT1_bin1 SR-BDT2 SR-BDT2_bin0 SR-BDT2_bin1Multi-boson 6.6±3.1 3.3±1.9 3.3±1.7 4.1±2.0 1.7±0.9 2.3±1.2W+jets 23±10 12±7 11±4 1.6+1.7−1.6 1.6+1.6−1.6 0.09+0.09−0.09Top 7.8±2.6 3.3±1.7 4.5±1.9 2.1±1.2 1.0±0.9 1.0±0.7Z+jets 7±7 4±4 2.8±2.6 2.0±0.9 1.6±0.8 0.40±0.20Higgs − 0.004+0.006−0.004 − 0.02+0.14−0.02 0.02+0.13−0.02 0.004+0.018−0.004Multi-jet 4.6±2.8 2.2±1.6 2.4±2.3 < 1.0 < 1.0 < 0.16SM total 49±15 25±10 24±8 10±4 5.9±2.8 3.9±1.6Observed 36 22 14 4 3 1m(τ˜ , χ˜01)= (80,1)GeV 40±9 14±4 27±6 4.2±2.0 3.4±1.4 0.7±0.7m(τ˜ , χ˜01)= (400,1)GeV 4.6±0.9 1.2±0.4 3.4±0.8 9.5±1.1 2.1±0.4 7.4±0.9p0 0.5 — — 0.5 — —Expected σ95vis [fb] 0.22 — — 0.06 — —Observed σ95vis [fb] 0.18 — — 0.04 — —SM process SR-BDT3 SR-BDT3_bin0 SR-BDT3_bin1 SR-BDT4Multi-boson 4.6± 2.2 2.0± 1.2 2.5± 1.3 1.8± 1.0W+jets 2+4−2 2+4−2 0.5± 0.5 < 0.7Top 3.7± 1.3 2.7± 1.1 1.0± 0.9 0.16+0.19−0.16Z+jets 6± 4 1.9+2.7−1.9 4.1± 2.6 0.2+0.9−0.2Higgs 0.13+0.15−0.13 0.13+0.14−0.13 0.001+0.012−0.001 < 0.015Multi-jet < 1.1 < 1.0 < 0.26 0.20+0.28−0.20SM total 17± 7 9± 6 8.2± 3.3 2.4± 1.4Observed 7 6 1 1m(τ˜ , χ˜01) = (80, 1)GeV 11± 4 8.6± 3.0 2.2± 1.4 0.13+0.22−0.13m(τ˜ , χ˜01) = (400, 1)GeV 9.4± 1.4 3.7± 0.7 5.7± 1.1 7.3± 0.9p0 0.5 — — 0.5Expected σ95vis [fb] 0.07 — — 0.03Observed σ95vis [fb] 0.04 — — 0.03Table 9. Observed and expected numbers of events after the background-only fit in the signalregions targeting direct stau production. The uncertainties correspond to the sum of statistical andsystematic uncertainties. The correlation of systematic uncertainties among control regions and amongbackground processes is taken into account. The one-sided p0-value, and the observed and expected95% CL upper limits on the visible non-SM cross-section (σ95vis) from the model-independent fit aregiven for the unbinned SRs. Values of p0 > 0.5 are truncated to p0 = 0.5.scaled with the normalization factors obtained from the background-only fit. The multi-jetnormalization with respect to the prediction from the ABCD method in all SRs is compatiblewith unity and has an uncertainty of 29–40% (4%), due to the small number of observedevents in the multi-jet CR-A in C1C1 and C1N2OS (C1N2SS) scenarios. The W+jetsnormalization factor is measured to be 0.98 ± 0.12 (1.04 ± 0.09) in C1C1 and C1N2OS(C1N2SS) scenarios and the top quark background normalization factor is found to be 0.71± 0.11 in the C1N2SS scenario. The normalization factors are summarised in table 10.– 31 –JHEP05(2024)150Channel Direct stau Intermediate stau Intermediate WhNormalization factor τ˜ τ˜ C1C1 C1N2OS C1N2SS C1N2WhµW+jets 0.93± 0.11 0.98± 0.12 0.98± 0.12 1.04± 0.09 —µZ+jets 0.91± 0.07 — — — —µTop 0.85± 0.05 — — 0.71± 0.11 1.00± 0.14µMulti-jet — 1.0± 0.4 1.00± 0.29 1.00± 0.04 —Table 10. Normalization factors from the background-only fit in each scenario for the Direct stau,Intermediate stau, and Intermediate Wh channels. The normalization factors include corrections tothe misidentified τ -lepton efficiency in addition to the cross-section and acceptance effects.100 150 200 250 300 350 400 450 500 550) [GeV]L,Rτ∼m(050100150200250300350) [GeV]10χ∼m()τ∼) > m(10χ∼m()expσ1 ±Expected Limit ()SUSYtheoryσ1 ±Observed Limit (ATLAS (Observed) Phys. Rev. D 101 (2020) 032009LEP observed10χ∼τ 2 x →L,Rτ∼L,Rτ∼-1 = 13 TeV, 139 fbsAll limits at 95% CLATLAS(a)100 150 200 250 300 350 400 450) [GeV]Lτ∼m(050100150200250300) [GeV]10χ∼m()τ∼) > m(10χ∼m()expσ1 ±Expected Limit ()SUSYtheoryσ1 ±Observed Limit (ATLAS (Observed) Phys. Rev. D 101 (2020) 03200910χ∼τ 2 x →Lτ∼Lτ∼-1 = 13 TeV, 139 fbsAll limits at 95% CLATLAS(b)100 150 200 250 300 350 400) [GeV]Rτ∼m(050100150200250) [GeV]10χ∼m()τ∼) > m(10χ∼m()expσ1 ±Expected Limit ()SUSYtheoryσ1 ±Observed Limit (10χ∼τ 2 x →Rτ∼Rτ∼-1 = 13 TeV, 139 fbsAll limits at 95% CLATLAS(c)Figure 12. The 95% CL exclusion contours for simplified models of (a) τ˜L,Rτ˜L,R production, (b) τ˜Lτ˜Lproduction, and (c) τ˜Rτ˜R production. The solid (dashed) lines show the observed (expected) exclusioncontours. The band around the expected limit shows the ±1σ variations, including all uncertaintiesexcept theoretical uncertainties in the signal cross-section. The expected exclusion contour from theprevious ATLAS result in ref. [15] is shown as a gray-filled contour in (a) and (b). The observedcontour from LEP in refs. [94, 95] is shown as a brown-filled contour in (a).– 32 –JHEP05(2024)150SM process SR-C1C1-LM SR-C1C1-HM SR-C1N2OS-LM SR-C1N2OS-HMMulti-boson 1.6 ± 0.6 2.2 ± 1.6 3.2 ± 1.2 2.4 ± 1.6W+jets 0.4 ± 0.4 0.29+0.35−0.29 0.6+2.2−0.6 0.29+0.35−0.29Top quark 1.0 ± 0.5 0.36 ± 0.13 1.1+1.2−1.1 0.36 ± 0.14Z+jets 1.4+1.5−1.4 0.78 ± 0.34 2.5 ± 1.7 0.9 ± 0.4Higgs 0.27 ± 0.06 0.01+0.13−0.01 0.40 ± 0.22 0.73 ± 0.23Multi-jet 1.5 ± 0.5 0.37 ± 0.21 4.5 ± 1.0 0.31 ± 0.17SM total 6.2 ± 2.0 4.0 ± 1.8 12.2 ± 4.8 5.0 ± 2.0Observed 1 4 14 4m(χ˜±1 , χ˜01) = (700, 400)GeV 3.0± 0.6 7.8± 1.6 4.7± 1.0 14.1± 2.8m(χ˜±1 /χ˜02, χ˜01) = (1100, 0)GeV 0.20± 0.05 3.1± 0.6 0.39± 0.11 4.6± 1.0p0 0.5 0.5 0.4 0.5Expected σ95vis [fb] 0.04 0.05 0.10 0.05Observed σ95vis [fb] 0.02 0.05 0.10 0.05SM process SR-C1N2SS-LM SR-C1N2SS-HMMulti-boson 0.47 ± 0.20 0.8 ± 0.4W+jets 0.33 ± 0.25 0.10 ± 0.05Top quark 0.01+0.02−0.01 0.59 ± 0.20Z+jets 0.20 ± 0.15 0.6+0.8−0.6Higgs < 0.01 0.02 ± 0.01Multi-jet 0.9 ± 0.5 0.00 ± 0.00SM total 2.0 ± 0.7 2.1 ± 1.1Observed 2 3m(χ˜±1 /χ˜02, χ˜01) = (157, 92)GeV 4.6± 1.3 0.00± 0.00m(χ˜±1 /χ˜02, χ˜01) = (900, 300)GeV 0.84± 0.07 6.23± 0.21p0 0.4 0.3Expected σ95vis [fb] 0.03 0.04Observed σ95vis [fb] 0.03 0.04Table 11. Observed and expected numbers of events for the background-only fit in the signal regionstargeting chargino/neutralino production and decay via intermediate staus. Expected event yields fora few SUSY reference points are also shown. The uncertainties correspond to the sum in quadratureof statistical and systematic uncertainties. The correlation of systematic uncertainties among controlregions and among background processes is taken into account. The one-sided p0-values, and theobserved and expected 95% CL upper limits on the visible non-SM cross-section (σ95vis) from themodel-independent fit are given.The mT2 distributions of events in the signal regions are shown in figure 13. In all SRs,observations and background predictions are found to be compatible within uncertainties.The one-sided p0-values, and the observed and expected 95% CL upper limits on the visiblenon-SM cross-section (σ95vis) are shown in table 11.– 33 –JHEP05(2024)15040 60 80 100 120 1402−101−10110210310410510Events/10 GeV-1 = 13 TeV, 139 fbsATLAS Data Total SMMulti-jet Multi-bosonTop HiggsW+jets Z+jets(300, 150) GeV(700, 400) GeV(1000, 0) GeV) =01χ∼, 02χ∼/±1χ∼m(SR-C1C1-LM40 60 80 100 120 140 [GeV]T2m012Data/SM(a)40 60 80 100 120 1402−101−10110210310410510Events/10 GeV-1 = 13 TeV, 139 fbsATLAS Data Total SMMulti-jet Multi-bosonTop HiggsW+jets Z+jets(275, 125) GeV(750, 450) GeV(1100, 0) GeV) =01χ∼, 02χ∼/±1χ∼m(SR-C1N2OS-LM40 60 80 100 120 140 [GeV]T2m012Data/SM(b)2−101−10110210310410Entries / 20 GeVATLASs = 13 TeV, 139 fb-10 20 40 60 80 100 120 140 160 180 200 [GeV]T2m012Data / SMDataMulti-jetTopW+jetsTotal SMMulti-bosonHiggsZ+jets(375,175)GeV (900,300)GeV (157, 92)GeV) =010, ∼χ2/∼χ±1m(∼χSR-C1N2SS-LM(c)Figure 13. The kinematic distributions for the Intermediate stau channel after the background-onlyfit, showing the mT2 distribution in (a) SR-C1C1-LM, (b) SR-C1N2OS-LM, and (c) SR-C1N2SS-LMbefore the selection on mT2 is made. The black arrow depicts the selection for the signal region.An example SUSY scenario is overlaid for illustration. The hashed bands represent the combinedstatistical and systematic uncertainties of the total SM background. The lower panels show the ratioof data to the total SM background estimate.In the absence of a significant excess over the expected SM background, the observed andexpected numbers of events in the signal regions are used to place exclusion limits at 95% CLusing the model-dependent fit. SR-C1C1-LM and SR-C1C1-HM are statistically combined toderive limits on χ˜+1 χ˜−1 production, and SR-C1N2OS-LM, SR-C1N2OS-HM, SR-C1N2SS-LMand SR-C1N2SS-HM are combined to derive limits for the production of χ˜+1 χ˜−1 and χ˜±1 χ˜02.The exclusion limits for simplified models are shown in figure 14. Only χ˜+1 χ˜−1 production isassumed for figure 14 (a), whereas both production processes are considered simultaneouslyfor the figure 14 (b) and (c). The C1N2SS channel contributes significantly to the combinationin the lower mass regions where this channel does not contain significant SM backgrounds.Chargino masses up to 970GeV are excluded for decays into a massless neutralino inthe direct production of chargino pairs. For production of chargino pairs of mass-degeneratecharginos and next-to-lightest neutralinos, chargino masses up to 1160GeV are excluded for– 34 –JHEP05(2024)1500 200 400 600 800 1000 [GeV]±1χ∼m0100200300400500600700800 [GeV]10χ∼m)1±χ∼) < m(10χ∼m()expσ1 ±Expected Limit (Observed Limit01χ∼ντ × 2 →) τν∼(ντ∼ × 2 → ±1χ∼±1χ∼ATLAS-1=13 TeV, 139 fbs)/2±1χ∼+m01χ∼=(mτ∼mAll limits at 95% CLSR-C1C1-combined(a)0 200 400 600 800 1000 1200 1400 [GeV]02χ∼,m±1χ∼m020040060080010001200[GeV]0 1χ∼m01χ∼ < m±1χ∼m)expσ1 ±Expected Comb. Limit (Combined observedSS observed SS expectedOS observed OS expected01χ∼ντ × 2 →) τν∼(ντ∼ × 2→±1χ∼±1χ∼ 01χ∼)νν(ττ01χ∼ντ →) νν∼(ττ∼ν∼τ),νν∼(ττ∼ντ∼ →02χ∼±1χ∼02χ∼= m±1χ∼m)/2±1χ∼+ m01χ∼= (mτ∼mAll limits at 95 % CLATLAS s =13 TeV, 139 fb-1(b)100 150 200 250 300 350 400 450 500 550 [GeV]02χ∼,m±1χ∼m50100150200250300350)[GeV]0 1χ∼,m0 2χ∼(m∆±1χ∼) > m01χ∼,m02χ∼(m∆)expσ1 ±Expected Comb. Limit (Combined observed SS observed SS expectedOS observed OS expected01χ∼ντ × 2 →) τν∼(ντ∼ × 2→±1χ∼±1χ∼ 01χ∼)νν(ττ01χ∼ντ →) νν∼(ττ∼ν∼τ),νν∼(ττ∼ντ∼ →02χ∼±1χ∼02χ∼= m±1χ∼m)/2±1χ∼+ m01χ∼= (mτ∼mAll limits at 95 % CLATLAS s=13 TeV, 139 fb-1(c)Figure 14. The 95% CL exclusion contours for simplified models of (a) χ˜+1 χ˜−1 production, and of(b-c) χ˜+1 χ˜−1 and χ˜±1 χ˜02 production. The solid (dashed) lines show the observed (expected) exclusioncontours. The band around the expected limit shows the ±1σ variations, including all uncertaintiesexcept theoretical uncertainties in the signal cross-section. The green curves are from the contributionof C1N2SS scenario, while the blue curves are from the contribution of C1C1 and C1N2OS scenarios,and the red curves are the combination of the channels. The gray solid area in (c) shows the forbiddenarea where m(χ˜01) > m(χ˜02).a massless neutralino. Both the limits apply to scenarios where the neutralinos and charginosdecay solely via intermediate staus and τ -sneutrinos. These limits significantly extend previousresults [14, 18] in the high χ˜±1 /χ˜02 mass region. The improvement at compressed and lowχ˜±1 /χ˜02 masses is mainly driven by the C1N2SS analysis.10.3 Intermediate Wh analysisThe observed number of events in the two SRs and the expected contributions from SMprocesses are given in table 12. The contribution of top quark background events is scaled withthe normalization factor obtained from the background-only fit. The top quark backgroundnormalization factor is fitted to be 1.00 ± 0.14. Kinematic distributions of events in thesignal regions are shown in figure 15. In all SRs, the observed number of events from– 35 –JHEP05(2024)150SM process SR-Wh-LM SR-Wh-HMMulti-boson 1.85 ± 0.5 1.1 ± 0.4Misidentified processes 1.4 ± 0.6 0.06 ± 0.03Top quark 1.9 ± 0.6 0.04+0.06−0.04Z+jets 0.05 ± 0.02 0.03 ± 0.01Higgs 0.13+0.99−0.13 0.06 ± 0.02SM total 5.3 ± 1.4 1.3 ± 0.4Observed 4 2m(χ˜±1 /χ˜02, χ˜01) = (225, 75)GeV 5.8± 1.5 3.3± 0.9p0 0.5 0.3Expected σ95vis [fb] 0.05 0.03Observed σ95vis [fb] 0.04 0.03Table 12. Observed and expected numbers of events for the background-only fit in the signalregions targeting chargino-neutralino production and decay via Wh. Expected event yields for afew SUSY reference points are also shown. The uncertainties correspond to the sum in quadratureof statistical and systematic uncertainties. The correlation of systematic uncertainties among controlregions and among background processes is fully taken into account. The one-sided p0-values, andthe observed and expected 95% CL upper limits on the visible non-SM cross-section (σ95vis) from themodel-independent fit are given.data and the background predictions are found to be compatible within uncertainties. Theone-sided p0-values, the observed and expected 95% CL upper limits on the visible non-SMcross-section (σ95vis) are shown in table 12.Since no significant excess over the expected SM background is observed, the observed andexpected number of events in the SRs are used to place exclusion limits at 95% CL using themodel-dependent fit. The SR with the best expected limit from SR-Wh-LM and SR-Wh-HM isused to derive limits on χ˜±1 χ˜02 production decaying via an intermediate Wh, and are shown infigure 16. The slightly weaker observed limits than expected for χ˜±1 /χ˜02 masses above 250GeVare driven by the results in SR-Wh-HM, as seen in table 12. Chargino and next-to-lightestneutralino masses up to 330GeV are excluded for a massless lightest neutralino.– 36 –JHEP05(2024)1502−101−10110210310410Events / BinData SM TotalMulti-boson W+jetsTop quark τMis-ID Higgs Z+jets) = (225, 75) GeV01χ∼, 02χ∼/±1χ∼m(-1 = 13 TeV, 139 fbsATLASWh, Post-FitSR-Wh-LM20 40 60 80 100 120 140 160 180 200 220 240 [GeV]T2m00.511.52Data / SM(a)2−101−10110210Events / BinData SM TotalMulti-boson W+jetsTop quark τMis-ID Higgs Z+jets) = (225, 75) GeV01χ∼, 02χ∼/±1χ∼m(-1 = 13 TeV, 139 fbsATLASWh, Post-FitSR-Wh-HM300 400 500 600 700 800 900 [GeV]Tsumm00.511.52Data / SM(b)Figure 15. The kinematic distributions for the Intermediate Wh channel after the background-onlyfit, showing (a) mT2 in SR-Wh-LM and (b) mTsum in SR-Wh-HM, before the selection on thatkinematic is made. The black arrow depicts the selection for the signal region. An example SUSYscenario is overlaid for illustration. The hashed bands represent the combined statistical and systematicuncertainties of the total SM background. The lower panels show the ratio of data to the total SMbackground estimate.100 150 200 250 300 350 400 450 [GeV]02χ∼,m±1χ∼m050100150200250 [GeV]10χ∼m) + 125 GeV10χ∼) < m(02χ∼/±1χ∼m()expσ1 ±Expected Limit (Observed Limit01χ∼ × Wh + 2 → 02χ∼±1χ∼ATLAS-1=13 TeV, 139 fbs02χ∼=m±1χ∼mAll limits at 95% CLSR-Wh-combinedFigure 16. The 95% CL exclusion contours for simplified models of χ˜±1 χ˜02 production decayingvia an intermediate Wh. The solid (dashed) lines show the observed (expected) exclusion contours.The band around the expected limit shows the ±1σ variations, including all uncertainties excepttheoretical uncertainties in the signal cross-section. The best expected limits for SR-Wh-LM andSR-Wh-HM are used.– 37 –JHEP05(2024)15011 SummarySearches for direct τ -slepton (stau) production and direct wino pair production decaying viaan intermediate stau or Wh with at least two hadronically decaying τ -leptons in the finalstate are presented. The searches use 139 fb−1 of integrated luminosity of pp collisions at√s = 13TeV collected by the ATLAS detector from 2015 to 2018. Agreement between dataand SM expectation is observed in all signal regions and the results are used to set limits onthe visible cross-section for processes beyond the Standard Model. Exclusion limits at 95% CLare also placed on simplified models of direct stau production, excluding mass-degenerate τ˜L,Rup to 500GeV, τ˜L up to 425GeV, and τ˜R up to 350GeV. The sensitivity to τ˜Rτ˜R productionobtained here is the first time for this process reported by ATLAS, achieved with a BoostedDecision Tree for improved signal-background separation.In the scenario of direct production of wino-like chargino pairs decaying into the lightestneutralino via an intermediate on-shell stau, exclusion limits are placed for chargino massesup to 970GeV for a massless lightest neutralino. In the case of the associated production ofpairs of charginos and of mass-degenerate charginos and next-to-lightest neutralinos, massesup to 1160GeV are excluded for a massless lightest neutralino. These limits improve uponprevious results by 340–400GeV, mainly due to an increased amount of integrated luminosityand improvements in the recurrent neural network τ -lepton identification. The sensitivity formore compressed mass scenarios is also improved by the addition of the same-sign τ -leptonchannel. For pairs of degenerate charginos and next-to-lightest neutralinos decaying viaintermediate W and h bosons, chargino and next-to-lightest neutralino masses up to 330GeVare excluded for a massless lightest neutralino.AcknowledgmentsWe thank CERN for the very successful operation of the LHC and its injectors, as wellas the support staff at CERN and at our institutions worldwide without whom ATLAScould not be operated efficiently.The crucial computing support from all WLCG partners is acknowledged gratefully, inparticular from CERN, the ATLAS Tier-1 facilities at TRIUMF/SFU (Canada), NDGF(Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF(Italy), NL-T1 (Netherlands), PIC (Spain), RAL (U.K.) and BNL (U.S.A.), the Tier-2 facilitiesworldwide and large non-WLCG resource providers. Major contributors of computingresources are listed in ref. [96].We gratefully acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC,Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; CNPq and FAPESP, Brazil;NSERC, NRC and CFI, Canada; CERN; ANID, Chile; CAS, MOST and NSFC, China;Minciencias, Colombia; MEYS CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS and CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF and MPG, Germany;GSRI, Greece; RGC and Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN,Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MEiN,Poland; FCT, Portugal; MNE/IFA, Romania; MESTD, Serbia; MSSR, Slovakia; ARRS andMIZŠ, Slovenia; DSI/NRF, South Africa; MICINN, Spain; SRC and Wallenberg Foundation,– 38 –JHEP05(2024)150Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taipei;TENMAK, Türkiye; STFC, United Kingdom; DOE and NSF, United States of America.Individual groups and members have received support from BCKDF, CANARIE, CRCand DRAC, Canada; COST, ERC, ERDF, Horizon 2020, ICSC-NextGenerationEU and MarieSkłodowska-Curie Actions, European Union; Investissements d’Avenir Labex, Investissementsd’Avenir Idex and ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thalesand Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSFand MINERVA, Israel; Norwegian Financial Mechanism 2014-2021, Norway; NCN and NAWA,Poland; La Caixa Banking Foundation, CERCA Programme Generalitat de Catalunya andPROMETEO and GenT Programmes Generalitat Valenciana, Spain; Göran GustafssonsStiftelse, Sweden; The Royal Society and Leverhulme Trust, United Kingdom.In addition, individual members wish to acknowledge support from Chile: AgenciaNacional de Investigación y Desarrollo (FONDECYT 1190886, FONDECYT 1210400,FONDECYT 1230987); China: National Natural Science Foundation of China (NSFC— 12175119, NSFC 12275265); European Union: European Research Council (ERC —948254), Horizon 2020 Framework Programme (MUCCA — CHIST-ERA-19-XAI-00), ItalianCenter for High Performance Computing, Big Data and Quantum Computing (ICSC,NextGenerationEU), Marie Sklodowska-Curie Actions (EU H2020 MSC IF GRANT NO101033496); France: Agence Nationale de la Recherche (ANR-20-CE31-0013, ANR-21-CE31-0013, ANR-21-CE31-0022), Investissements d’Avenir Idex (ANR-11-LABX-0012),Investissements d’Avenir Labex (ANR-11-LABX-0012); Germany: Baden-WürttembergStiftung (BW Stiftung-Postdoc Eliteprogramme), Deutsche Forschungsgemeinschaft (DFG— CR 312/5-1); Italy: Istituto Nazionale di Fisica Nucleare (FELLINI G.A. n. 754496,ICSC, NextGenerationEU); Japan: Japan Society for the Promotion of Science (JSPSKAKENHI 22H01227, JSPS KAKENHI JP21H05085, JSPS KAKENHI JP22H04944);Netherlands: Netherlands Organisation for Scientific Research (NWO Veni 2020 —VI.Veni.202.179); Norway: Research Council of Norway (RCN-314472); Poland: PolishNational Agency for Academic Exchange (PPN/PPO/2020/1/00002/U/00001), PolishNational Science Centre (NCN 2021/42/E/ST2/00350, NCN UMO-2019/34/E/ST2/00393,UMO-2020/37/B/ST2/01043, UMO-2021/40/C/ST2/00187); Slovenia: Slovenian ResearchAgency (ARIS grant J1-3010); Spain: BBVA Foundation (LEO22-1-603), GeneralitatValenciana (Artemisa, FEDER, IDIFEDER/2018/048), La Caixa Banking Foundation(LCF/BQ/PI20/11760025), Ministry of Science and Innovation (RYC2019-028510-I, RYC2020-030254-I), PROMETEO and GenT Programmes Generalitat Valenciana(CIDEGENT/2019/023, CIDEGENT/2019/027); Sweden: Swedish Research Council (VR2022-03845, VR 2022-04683), Knut and Alice Wallenberg Foundation (KAW 2017.0100,KAW 2018.0157, KAW 2019.0447); Switzerland: Swiss National Science Foundation (SNSF —PCEFP2_194658); United Kingdom: Leverhulme Trust (Leverhulme Trust RPG-2020-004);United States of America: Neubauer Family Foundation.Open Access. 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Agheorghiesei 27c, A. Ahmad 36, F. Ahmadov 38,y,W.S. Ahmed 104, S. Ahuja 95, X. Ai 62a, G. Aielli 76a,76b, A. Aikot 163, M. Ait Tamlihat 35e,B. Aitbenchikh 35a, I. Aizenberg 169, M. Akbiyik 100, T.P.A. Åkesson 98, A.V. Akimov 37,D. Akiyama 168, N.N. Akolkar 24, K. Al Khoury 41, G.L. Alberghi 23b, J. Albert 165,P. Albicocco 53, G.L. Albouy 60, S. Alderweireldt 52, M. Aleksa 36, I.N. Aleksandrov 38,C. Alexa 27b, T. Alexopoulos 10, F. Alfonsi 23b, M. Algren 56, M. Alhroob 120, B. Ali 132,H.M.J. Ali 91, S. Ali 148, S.W. Alibocus 92, M. Aliev 145, G. Alimonti 71a, W. Alkakhi 55,C. Allaire 66, B.M.M. Allbrooke 146, J.F. Allen 52, C.A. Allendes Flores 137f , P.P. Allport 20,A. Aloisio 72a,72b, F. Alonso 90, C. Alpigiani 138, M. Alvarez Estevez 99,A. Alvarez Fernandez 100, M. Alves Cardoso 56, M.G. Alviggi 72a,72b, M. Aly 101,Y. Amaral Coutinho 83b, A. Ambler 104, C. Amelung36, M. Amerl 101, C.G. Ames 109,D. Amidei 106, S.P. Amor Dos Santos 130a, K.R. Amos 163, V. Ananiev 125,C. Anastopoulos 139, T. Andeen 11, J.K. Anders 36, S.Y. Andrean 47a,47b,A. Andreazza 71a,71b, S. Angelidakis 9, A. Angerami 41,ab, A.V. Anisenkov 37, A. Annovi 74a,C. Antel 56, M.T. Anthony 139, E. Antipov 145, M. Antonelli 53, F. Anulli 75a, M. Aoki 84,T. Aoki 153, J.A. Aparisi Pozo 163, M.A. Aparo 146, L. Aperio Bella 48, C. Appelt 18,A. Apyan 26, N. Aranzabal 36, C. Arcangeletti 53, A.T.H. Arce 51, E. Arena 92,J-F. Arguin 108, S. Argyropoulos 54, J.-H. Arling 48, O. Arnaez 4, H. Arnold 114,G. Artoni 75a,75b, H. Asada 111, K. Asai 118, S. Asai 153, N.A. Asbah 61, K. Assamagan 29,R. Astalos 28a, S. Atashi 160, R.J. Atkin 33a, M. Atkinson162, H. Atmani35f ,P.A. Atmasiddha 106, K. Augsten 132, S. Auricchio 72a,72b, A.D. Auriol 20, V.A. Austrup 101,G. Avolio 36, K. Axiotis 56, G. Azuelos 108,ag, D. Babal 28b, H. Bachacou 135, K. Bachas 152,p,A. Bachiu 34, F. Backman 47a,47b, A. Badea 61, P. Bagnaia 75a,75b, M. Bahmani 18,A.J. Bailey 163, V.R. Bailey 162, J.T. Baines 134, L. Baines 94, C. Bakalis 10, O.K. Baker 172,E. Bakos 15, D. Bakshi Gupta 8, V. Balakrishnan 120, R. Balasubramanian 114, E.M. Baldin 37,P. Balek 86a, E. Ballabene 23b,23a, F. Balli 135, L.M. Baltes 63a, W.K. Balunas 32, J. Balz 100,E. Banas 87, M. Bandieramonte 129, A. Bandyopadhyay 24, S. Bansal 24, L. Barak 151,M. Barakat 48, E.L. Barberio 105, D. Barberis 57b,57a, M. Barbero 102, M.Z. Barel 114,K.N. Barends 33a, T. Barillari 110, M-S. Barisits 36, T. Barklow 143, P. Baron 122,D.A. Baron Moreno 101, A. Baroncelli 62a, G. Barone 29, A.J. Barr 126, J.D. Barr 96,L. Barranco Navarro 47a,47b, F. Barreiro 99, J. Barreiro Guimarães da Costa 14a, U. Barron 151,M.G. Barros Teixeira 130a, S. Barsov 37, F. Bartels 63a, R. Bartoldus 143, A.E. Barton 91,P. Bartos 28a, A. Basan 100, M. Baselga 49, A. Bassalat 66,b, M.J. Basso 156a,C.R. Basson 101, R.L. Bates 59, S. Batlamous35e, J.R. Batley 32, B. Batool 141,M. Battaglia 136, D. Battulga 18, M. Bauce 75a,75b, M. Bauer 36, P. Bauer 24,L.T. Bazzano Hurrell 30, J.B. Beacham 51, T. Beau 127, P.H. Beauchemin 158, F. Becherer 54,P. Bechtle 24, H.P. Beck 19,o, K. Becker 167, A.J. Beddall 82, V.A. Bednyakov 38,C.P. Bee 145, L.J. Beemster 15, T.A. Beermann 36, M. Begalli 83d, M. Begel 29,– 46 –JHEP05(2024)150A. Behera 145, J.K. Behr 48, J.F. Beirer 55, F. Beisiegel 24, M. Belfkir 159, G. Bella 151,L. Bellagamba 23b, A. Bellerive 34, P. Bellos 20, K. Beloborodov 37, D. Benchekroun 35a,F. Bendebba 35a, Y. Benhammou 151, M. Benoit 29, J.R. Bensinger 26, S. Bentvelsen 114,L. Beresford 48, M. Beretta 53, E. Bergeaas Kuutmann 161, N. Berger 4, B. Bergmann 132,J. Beringer 17a, G. Bernardi 5, C. Bernius 143, F.U. Bernlochner 24, F. Bernon 36,102,T. Berry 95, P. Berta 133, A. Berthold 50, I.A. Bertram 91, S. Bethke 110, A. Betti 75a,75b,A.J. Bevan 94, M. Bhamjee 33c, S. Bhatta 145, D.S. Bhattacharya 166, P. Bhattarai 143,V.S. Bhopatkar 121, R. Bi29,ai, R.M. Bianchi 129, G. Bianco 23b,23a, O. Biebel 109,R. Bielski 123, M. Biglietti 77a, M. Bindi 55, A. Bingul 21b, C. Bini 75a,75b, A. Biondini 92,C.J. Birch-sykes 101, G.A. Bird 20,134, M. Birman 169, M. Biros 133, S. Biryukov 146,T. Bisanz 49, E. Bisceglie 43b,43a, J.P. Biswal 134, D. Biswas 141, A. Bitadze 101,K. Bjørke 125, I. Bloch 48, C. Blocker 26, A. Blue 59, U. Blumenschein 94, J. Blumenthal 100,G.J. Bobbink 114, V.S. Bobrovnikov 37, M. Boehler 54, B. Boehm 166, D. Bogavac 36,A.G. Bogdanchikov 37, C. Bohm 47a, V. Boisvert 95, P. Bokan 48, T. Bold 86a, M. Bomben 5,M. Bona 94, M. Boonekamp 135, C.D. Booth 95, A.G. Borbély 59, I.S. Bordulev 37,H.M. Borecka-Bielska 108, G. Borissov 91, D. Bortoletto 126, D. Boscherini 23b, M. Bosman 13,J.D. Bossio Sola 36, K. Bouaouda 35a, N. Bouchhar 163, J. Boudreau 129,E.V. Bouhova-Thacker 91, D. Boumediene 40, R. Bouquet 5, A. Boveia 119, J. Boyd 36,D. Boye 29, I.R. Boyko 38, J. Bracinik 20, N. Brahimi 62d, G. Brandt 171, O. Brandt 32,F. Braren 48, B. Brau 103, J.E. Brau 123, R. Brener 169, L. Brenner 114, R. Brenner 161,S. Bressler 169, D. Britton 59, D. Britzger 110, I. Brock 24, G. Brooijmans 41,W.K. Brooks 137f , E. Brost 29, L.M. Brown 165, L.E. Bruce 61, T.L. Bruckler 126,P.A. Bruckman de Renstrom 87, B. Brüers 48, A. Bruni 23b, G. Bruni 23b, M. Bruschi 23b,N. Bruscino 75a,75b, T. Buanes 16, Q. Buat 138, D. Buchin 110, A.G. Buckley 59,O. Bulekov 37, B.A. Bullard 143, S. Burdin 92, C.D. Burgard 49, A.M. Burger 40,B. Burghgrave 8, O. Burlayenko 54, J.T.P. Burr 32, C.D. Burton 11, J.C. Burzynski 142,E.L. Busch 41, V. Büscher 100, P.J. Bussey 59, J.M. Butler 25, C.M. Buttar 59,J.M. Butterworth 96, W. Buttinger 134, C.J. Buxo Vazquez 107, A.R. Buzykaev 37,S. Cabrera Urbán 163, L. Cadamuro 66, D. Caforio 58, H. Cai 129, Y. Cai 14a,14e,V.M.M. Cairo 36, O. Cakir 3a, N. Calace 36, P. Calafiura 17a, G. Calderini 127, P. Calfayan 68,G. Callea 59, L.P. Caloba83b, D. Calvet 40, S. Calvet 40, T.P. Calvet 102, M. Calvetti 74a,74b,R. Camacho Toro 127, S. Camarda 36, D. Camarero Munoz 26, P. Camarri 76a,76b,M.T. Camerlingo 72a,72b, D. Cameron 36, C. Camincher 165, M. Campanelli 96, A. Camplani 42,V. Canale 72a,72b, A. Canesse 104, J. Cantero 163, Y. Cao 162, F. Capocasa 26,M. Capua 43b,43a, A. Carbone 71a,71b, R. Cardarelli 76a, J.C.J. Cardenas 8, F. Cardillo 163,T. Carli 36, G. Carlino 72a, J.I. Carlotto 13, B.T. Carlson 129,q, E.M. Carlson 165,156a,L. Carminati 71a,71b, A. Carnelli 135, M. Carnesale 75a,75b, S. Caron 113, E. Carquin 137f ,S. Carrá 71a, G. Carratta 23b,23a, F. Carrio Argos 33g, J.W.S. Carter 155, T.M. Carter 52,M.P. Casado 13,i, M. Caspar 48, E.G. Castiglia 172, F.L. Castillo 4, L. Castillo Garcia 13,V. Castillo Gimenez 163, N.F. Castro 130a,130e, A. Catinaccio 36, J.R. Catmore 125,V. Cavaliere 29, N. Cavalli 23b,23a, V. Cavasinni 74a,74b, Y.C. Cekmecelioglu 48, E. Celebi 21a,F. Celli 126, M.S. Centonze 70a,70b, V. Cepaitis 56, K. Cerny 122, A.S. Cerqueira 83a,A. Cerri 146, L. Cerrito 76a,76b, F. Cerutti 17a, B. Cervato 141, A. Cervelli 23b, G. Cesarini 53,– 47 –JHEP05(2024)150S.A. Cetin 82, Z. Chadi 35a, D. Chakraborty 115, J. Chan 170, W.Y. Chan 153,J.D. Chapman 32, E. Chapon 135, B. Chargeishvili 149b, D.G. Charlton 20, T.P. Charman 94,M. Chatterjee 19, C. Chauhan 133, S. Chekanov 6, S.V. Chekulaev 156a, G.A. Chelkov 38,a,A. Chen 106, B. Chen 151, B. Chen 165, H. Chen 14c, H. Chen 29, J. Chen 62c, J. Chen 142,M. Chen 126, S. Chen 153, S.J. Chen 14c, X. Chen 62c,135, X. Chen 14b,af , Y. Chen 62a,C.L. Cheng 170, H.C. Cheng 64a, S. Cheong 143, A. Cheplakov 38, E. Cheremushkina 48,E. Cherepanova 114, R. Cherkaoui El Moursli 35e, E. Cheu 7, K. Cheung 65, L. Chevalier 135,V. Chiarella 53, G. Chiarelli 74a, N. Chiedde 102, G. Chiodini 70a, A.S. Chisholm 20,A. Chitan 27b, M. Chitishvili 163, M.V. Chizhov 38, K. Choi 11, A.R. Chomont 75a,75b,Y. Chou 103, E.Y.S. Chow 114, T. Chowdhury 33g, K.L. Chu 169, M.C. Chu 64a,X. Chu 14a,14e, J. Chudoba 131, J.J. Chwastowski 87, D. Cieri 110, K.M. Ciesla 86a,V. Cindro 93, A. Ciocio 17a, F. Cirotto 72a,72b, Z.H. Citron 169,k, M. Citterio 71a,D.A. Ciubotaru27b, B.M. Ciungu 155, A. Clark 56, P.J. Clark 52, J.M. Clavijo Columbie 48,S.E. Clawson 48, C. Clement 47a,47b, J. Clercx 48, Y. Coadou 102, M. Cobal 69a,69c,A. Coccaro 57b, R.F. Coelho Barrue 130a, R. Coelho Lopes De Sa 103, S. Coelli 71a,H. Cohen 151, A.E.C. Coimbra 71a,71b, B. Cole 41, J. Collot 60, P. Conde Muiño 130a,130g,M.P. Connell 33c, S.H. Connell 33c, I.A. Connelly 59, E.I. Conroy 126, F. Conventi 72a,ah,H.G. Cooke 20, A.M. Cooper-Sarkar 126, A. Cordeiro Oudot Choi 127, F. Cormier 164,L.D. Corpe 40, M. Corradi 75a,75b, F. Corriveau 104,w, A. Cortes-Gonzalez 18, M.J. Costa 163,F. Costanza 4, D. Costanzo 139, B.M. Cote 119, G. Cowan 95, K. Cranmer 170,D. Cremonini 23b,23a, S. Crépé-Renaudin 60, F. Crescioli 127, M. Cristinziani 141,M. Cristoforetti 78a,78b, V. Croft 114, J.E. Crosby 121, G. Crosetti 43b,43a, A. Cueto 99,T. Cuhadar Donszelmann 160, H. Cui 14a,14e, Z. Cui 7, W.R. Cunningham 59,F. Curcio 43b,43a, P. Czodrowski 36, M.M. Czurylo 63b,M.J. Da Cunha Sargedas De Sousa 57b,57a, J.V. Da Fonseca Pinto 83b, C. Da Via 101,W. Dabrowski 86a, T. Dado 49, S. Dahbi 33g, T. Dai 106, D. Dal Santo 19, C. Dallapiccola 103,M. Dam 42, G. D’amen 29, V. D’Amico 109, J. Damp 100, J.R. Dandoy 128, M.F. Daneri 30,M. Danninger 142, V. Dao 36, G. Darbo 57b, S. Darmora 6, S.J. Das 29,ai, S. D’Auria 71a,71b,C. David 156b, T. Davidek 133, B. Davis-Purcell 34, I. Dawson 94, H.A. Day-hall 132, K. De 8,R. De Asmundis 72a, N. De Biase 48, S. De Castro 23b,23a, N. De Groot 113, P. de Jong 114,H. De la Torre 115, A. De Maria 14c, A. De Salvo 75a, U. De Sanctis 76a,76b, A. De Santo 146,J.B. De Vivie De Regie 60, D.V. Dedovich38, J. Degens 114, A.M. Deiana 44,F. Del Corso 23b,23a, J. Del Peso 99, F. Del Rio 63a, F. Deliot 135, C.M. Delitzsch 49,M. Della Pietra 72a,72b, D. Della Volpe 56, A. Dell’Acqua 36, L. Dell’Asta 71a,71b,M. Delmastro 4, P.A. Delsart 60, S. Demers 172, M. Demichev 38, S.P. Denisov 37,L. D’Eramo 40, D. Derendarz 87, F. Derue 127, P. Dervan 92, K. Desch 24, C. Deutsch 24,F.A. Di Bello 57b,57a, A. Di Ciaccio 76a,76b, L. Di Ciaccio 4, A. Di Domenico 75a,75b,C. Di Donato 72a,72b, A. Di Girolamo 36, G. Di Gregorio 36, A. Di Luca 78a,78b,B. Di Micco 77a,77b, R. Di Nardo 77a,77b, C. Diaconu 102, M. Diamantopoulou 34,F.A. Dias 114, T. Dias Do Vale 142, M.A. Diaz 137a,137b, F.G. Diaz Capriles 24, M. Didenko 163,E.B. Diehl 106, L. Diehl 54, S. Díez Cornell 48, C. Diez Pardos 141, C. Dimitriadi 161,24,161,A. Dimitrievska 17a, J. Dingfelder 24, I-M. Dinu 27b, S.J. Dittmeier 63b, F. Dittus 36,F. Djama 102, T. Djobava 149b, J.I. Djuvsland 16, C. Doglioni 101,98, A. Dohnalova 28a,– 48 –JHEP05(2024)150J. Dolejsi 133, Z. Dolezal 133, K.M. Dona 39, M. Donadelli 83c, B. Dong 107, J. Donini 40,A. D’Onofrio 77a,77b, M. D’Onofrio 92, J. Dopke 134, A. Doria 72a,N. Dos Santos Fernandes 130a, P. Dougan 101, M.T. Dova 90, A.T. Doyle 59, M.A. Draguet 126,E. Dreyer 169, I. Drivas-koulouris 10, A.S. Drobac 158, M. Drozdova 56, D. Du 62a,T.A. du Pree 114, F. Dubinin 37, M. Dubovsky 28a, E. Duchovni 169, G. Duckeck 109,O.A. Ducu 27b, D. Duda 52, A. Dudarev 36, E.R. Duden 26, M. D’uffizi 101, L. Duflot 66,M. Dührssen 36, C. Dülsen 171, A.E. Dumitriu 27b, M. Dunford 63a, S. Dungs 49,K. Dunne 47a,47b, A. Duperrin 102, H. Duran Yildiz 3a, M. Düren 58, A. Durglishvili 149b,B.L. Dwyer 115, G.I. Dyckes 17a, M. Dyndal 86a, S. Dysch 101, B.S. Dziedzic 87,Z.O. Earnshaw 146, G.H. Eberwein 126, B. Eckerova 28a, S. Eggebrecht 55,E. Egidio Purcino De Souza 127, L.F. Ehrke 56, G. Eigen 16, K. Einsweiler 17a, T. Ekelof 161,P.A. Ekman 98, S. El Farkh 35b, Y. El Ghazali 35b, H. El Jarrari 35e,148, A. El Moussaouy 108,V. Ellajosyula 161, M. Ellert 161, F. Ellinghaus 171, A.A. Elliot 94, N. Ellis 36,J. Elmsheuser 29, M. Elsing 36, D. Emeliyanov 134, Y. Enari 153, I. Ene 17a, S. Epari 13,J. Erdmann 49, P.A. Erland 87, M. Errenst 171, M. Escalier 66, C. Escobar 163, E. Etzion 151,G. Evans 130a, H. Evans 68, L.S. Evans 95, M.O. Evans 146, A. Ezhilov 37, S. Ezzarqtouni 35a,F. Fabbri 59, L. Fabbri 23b,23a, G. Facini 96, V. Fadeyev 136, R.M. Fakhrutdinov 37,S. Falciano 75a, L.F. Falda Ulhoa Coelho 36, P.J. Falke 24, J. Faltova 133, C. Fan 162,Y. Fan 14a, Y. Fang 14a,14e, M. Fanti 71a,71b, M. Faraj 69a,69b, Z. Farazpay 97, A. Farbin 8,A. Farilla 77a, T. Farooque 107, S.M. Farrington 52, F. Fassi 35e, D. Fassouliotis 9,M. Faucci Giannelli 76a,76b, W.J. Fawcett 32, L. Fayard 66, P. Federic 133, P. Federicova 131,O.L. Fedin 37,a, G. Fedotov 37, M. Feickert 170, L. Feligioni 102, D.E. Fellers 123, C. Feng 62b,M. Feng 14b, Z. Feng 114, M.J. Fenton 160, A.B. Fenyuk37, L. Ferencz 48, R.A.M. Ferguson 91,S.I. Fernandez Luengo 137f , M.J.V. Fernoux 102, J. Ferrando 48, A. Ferrari 161,P. Ferrari 114,113, R. Ferrari 73a, D. Ferrere 56, C. Ferretti 106, F. Fiedler 100, P. Fiedler 132,A. Filipčič 93, E.K. Filmer 1, F. Filthaut 113, M.C.N. Fiolhais 130a,130c,c, L. Fiorini 163,W.C. Fisher 107, T. Fitschen 101, P.M. Fitzhugh135, I. Fleck 141, P. Fleischmann 106,T. Flick 171, M. Flores 33d,ac, L.R. Flores Castillo 64a, L. Flores Sanz De Acedo 36,F.M. Follega 78a,78b, N. Fomin 16, J.H. Foo 155, B.C. Forland68, A. Formica 135, A.C. Forti 101,E. Fortin 36, A.W. Fortman 61, M.G. Foti 17a, L. Fountas 9,j , D. Fournier 66, H. Fox 91,P. Francavilla 74a,74b, S. Francescato 61, S. Franchellucci 56, M. Franchini 23b,23a,S. Franchino 63a, D. Francis36, L. Franco 113, V. Franco Lima 36, L. Franconi 48,M. Franklin 61, G. Frattari 26, A.C. Freegard 94, W.S. Freund 83b, Y.Y. Frid 151, J. Friend 59,N. Fritzsche 50, A. Froch 54, D. Froidevaux 36, J.A. Frost 126, Y. Fu 62a, M. Fujimoto 118,ad,E. Fullana Torregrosa 163,∗, K.Y. Fung 64a, E. Furtado De Simas Filho 83b, M. Furukawa 153,J. Fuster 163, A. Gabrielli 23b,23a, A. Gabrielli 155, P. Gadow 36, G. Gagliardi 57b,57a,L.G. Gagnon 17a, E.J. Gallas 126, B.J. Gallop 134, K.K. Gan 119, S. Ganguly 153, J. Gao 62a,Y. Gao 52, F.M. Garay Walls 137a,137b, B. Garcia29, C. García 163, A. Garcia Alonso 114,A.G. Garcia Caffaro 172, J.E. García Navarro 163, M. Garcia-Sciveres 17a, G.L. Gardner 128,R.W. Gardner 39, N. Garelli 158, D. Garg 80, R.B. Garg 143,n, J.M. Gargan52, C.A. Garner155,C.M. Garvey 33a, S.J. Gasiorowski 138, P. Gaspar 83b, G. Gaudio 73a, V. Gautam13,P. Gauzzi 75a,75b, I.L. Gavrilenko 37, A. Gavrilyuk 37, C. Gay 164, G. Gaycken 48,E.N. Gazis 10, A.A. Geanta 27b, C.M. Gee 136, C. Gemme 57b, M.H. Genest 60,– 49 –JHEP05(2024)150S. Gentile 75a,75b, A.D. Gentry 112, S. George 95, W.F. George 20, T. Geralis 46,P. Gessinger-Befurt 36, M.E. Geyik 171, M. Ghani 167, M. Ghneimat 141, K. Ghorbanian 94,A. Ghosal 141, A. Ghosh 160, A. Ghosh 7, B. Giacobbe 23b, S. Giagu 75a,75b, T. Giani 114,P. Giannetti 74a, A. Giannini 62a, S.M. Gibson 95, M. Gignac 136, D.T. Gil 86b,A.K. Gilbert 86a, B.J. Gilbert 41, D. Gillberg 34, G. Gilles 114, N.E.K. Gillwald 48,L. Ginabat 127, D.M. Gingrich 2,ag, M.P. Giordani 69a,69c, P.F. Giraud 135,G. Giugliarelli 69a,69c, D. Giugni 71a, F. Giuli 36, I. Gkialas 9,j , L.K. Gladilin 37,C. Glasman 99, G.R. Gledhill 123, G. Glemža 48, M. Glisic123, I. Gnesi 43b,f , Y. Go 29,ai,M. Goblirsch-Kolb 36, B. Gocke 49, D. Godin108, B. Gokturk 21a, S. Goldfarb 105,T. Golling 56, M.G.D. Gololo 33g, D. Golubkov 37, J.P. Gombas 107, A. Gomes 130a,130b,G. Gomes Da Silva 141, A.J. Gomez Delegido 163, R. Gonçalo 130a,130c, G. Gonella 123,L. Gonella 20, A. Gongadze 149c, F. Gonnella 20, J.L. Gonski 41, R.Y. González Andana 52,S. González de la Hoz 163, S. Gonzalez Fernandez 13, R. Gonzalez Lopez 92,C. Gonzalez Renteria 17a, M.V. Gonzalez Rodrigues 48, R. Gonzalez Suarez 161,S. Gonzalez-Sevilla 56, G.R. Gonzalvo Rodriguez 163, L. Goossens 36, B. Gorini 36,E. Gorini 70a,70b, A. Gorišek 93, T.C. Gosart 128, A.T. Goshaw 51, M.I. Gostkin 38,S. Goswami 121, C.A. Gottardo 36, S.A. Gotz 109, M. Gouighri 35b, V. Goumarre 48,A.G. Goussiou 138, N. Govender 33c, I. Grabowska-Bold 86a, K. Graham 34, E. Gramstad 125,S. Grancagnolo 70a,70b, M. Grandi 146, C.M. Grant1,135, P.M. Gravila 27f , F.G. Gravili 70a,70b,H.M. Gray 17a, M. Greco 70a,70b, C. Grefe 24, I.M. Gregor 48, P. Grenier 143, C. Grieco 13,A.A. Grillo 136, K. Grimm 31, S. Grinstein 13,s, J.-F. Grivaz 66, E. Gross 169,J. Grosse-Knetter 55, C. Grud106, J.C. Grundy 126, L. Guan 106, W. Guan 29, C. Gubbels 164,J.G.R. Guerrero Rojas 163, G. Guerrieri 69a,69c, F. Guescini 110, R. Gugel 100,J.A.M. Guhit 106, A. Guida 18, T. Guillemin 4, E. Guilloton 167,134, S. Guindon 36,F. Guo 14a,14e, J. Guo 62c, L. Guo 48, Y. Guo 106, R. Gupta 48, S. Gurbuz 24,S.S. Gurdasani 54, G. Gustavino 36, M. Guth 56, P. Gutierrez 120, L.F. Gutierrez Zagazeta 128,C. Gutschow 96, C. Gwenlan 126, C.B. Gwilliam 92, E.S. Haaland 125, A. Haas 117,M. Habedank 48, C. Haber 17a, H.K. Hadavand 8, A. Hadef 100, S. Hadzic 110, J.J. Hahn 141,E.H. Haines 96, M. Haleem 166, J. Haley 121, J.J. Hall 139, G.D. Hallewell 102, L. Halser 19,K. Hamano 165, M. Hamer 24, G.N. Hamity 52, E.J. Hampshire 95, J. Han 62b, K. Han 62a,L. Han 14c, L. Han 62a, S. Han 17a, Y.F. Han 155, K. Hanagaki 84, M. Hance 136,D.A. Hangal 41,ab, H. Hanif 142, M.D. Hank 128, R. Hankache 101, J.B. Hansen 42,J.D. Hansen 42, P.H. Hansen 42, K. Hara 157, D. Harada 56, T. Harenberg 171,S. Harkusha 37, M.L. Harris 103, Y.T. Harris 126, J. Harrison 13, N.M. Harrison 119,P.F. Harrison167, N.M. Hartman 110, N.M. Hartmann 109, Y. Hasegawa 140, R. Hauser 107,C.M. Hawkes 20, R.J. Hawkings 36, Y. Hayashi 153, S. Hayashida 111, D. Hayden 107,C. Hayes 106, R.L. Hayes 114, C.P. Hays 126, J.M. Hays 94, H.S. Hayward 92, F. He 62a,M. He 14a,14e, Y. He 154, Y. He 48, N.B. Heatley 94, V. Hedberg 98, A.L. Heggelund 125,N.D. Hehir 94,∗, C. Heidegger 54, K.K. Heidegger 54, W.D. Heidorn 81, J. Heilman 34,S. Heim 48, T. Heim 17a, J.G. Heinlein 128, J.J. Heinrich 123, L. Heinrich 110,ae, J. Hejbal 131,L. Helary 48, A. Held 170, S. Hellesund 16, C.M. Helling 164, S. Hellman 47a,47b,R.C.W. Henderson91, L. Henkelmann 32, A.M. Henriques Correia36, H. Herde 98,Y. Hernández Jiménez 145, L.M. Herrmann 24, T. Herrmann 50, G. Herten 54,– 50 –JHEP05(2024)150R. Hertenberger 109, L. Hervas 36, M.E. Hesping 100, N.P. Hessey 156a, H. Hibi 85, E. Hill 155,S.J. Hillier 20, J.R. Hinds 107, F. Hinterkeuser 24, M. Hirose 124, S. Hirose 157,D. Hirschbuehl 171, T.G. Hitchings 101, B. Hiti 93, J. Hobbs 145, R. Hobincu 27e, N. Hod 169,M.C. Hodgkinson 139, B.H. Hodkinson 32, A. Hoecker 36, J. Hofer 48, T. Holm 24,M. Holzbock 110, L.B.A.H. Hommels 32, B.P. Honan 101, J. Hong 62c, T.M. Hong 129,B.H. Hooberman 162, W.H. Hopkins 6, Y. Horii 111, S. Hou 148, A.S. Howard 93,J. Howarth 59, J. Hoya 6, M. Hrabovsky 122, A. Hrynevich 48, T. Hryn’ova 4, P.J. Hsu 65,S.-C. Hsu 138, Q. Hu 62a, Y.F. Hu 14a,14e, S. Huang 64b, X. Huang 14c, Y. Huang 139,Y. Huang 14a, Z. Huang 101, Z. Hubacek 132, M. Huebner 24, F. Huegging 24,T.B. Huffman 126, C.A. Hugli 48, M. Huhtinen 36, S.K. Huiberts 16, R. Hulsken 104,N. Huseynov 12, J. Huston 107, J. Huth 61, R. Hyneman 143, G. Iacobucci 56, G. Iakovidis 29,I. Ibragimov 141, L. Iconomidou-Fayard 66, P. Iengo 72a,72b, R. Iguchi 153, T. Iizawa 126,Y. Ikegami 84, N. Ilic 155, H. Imam 35a, M. Ince Lezki 56, T. Ingebretsen Carlson 47a,47b,G. Introzzi 73a,73b, M. Iodice 77a, V. Ippolito 75a,75b, R.K. Irwin 92, M. Ishino 153,W. Islam 170, C. Issever 18,48, S. Istin 21a,ak, H. Ito 168, J.M. Iturbe Ponce 64a,R. Iuppa 78a,78b, A. Ivina 169, J.M. Izen 45, V. Izzo 72a, P. Jacka 131,132, P. Jackson 1,R.M. Jacobs 48, B.P. Jaeger 142, C.S. Jagfeld 109, G. Jain 156a, P. Jain 54, G. Jäkel 171,K. Jakobs 54, T. Jakoubek 169, J. Jamieson 59, K.W. Janas 86a, M. Javurkova 103,F. Jeanneau 135, L. Jeanty 123, J. Jejelava 149a,z, P. Jenni 54,g, C.E. Jessiman 34,S. Jézéquel 4, C. Jia62b, J. Jia 145, X. Jia 61, X. Jia 14a,14e, Z. Jia 14c, Y. Jiang62a,S. Jiggins 48, J. Jimenez Pena 13, S. Jin 14c, A. Jinaru 27b, O. Jinnouchi 154,P. Johansson 139, K.A. Johns 7, J.W. Johnson 136, D.M. Jones 32, E. Jones 48, P. Jones 32,R.W.L. Jones 91, T.J. Jones 92, H.L. Joos 55,36, R. Joshi 119, J. Jovicevic 15, X. Ju 17a,J.J. Junggeburth 103, T. Junkermann 63a, A. Juste Rozas 13,s, M.K. Juzek 87, S. Kabana 137e,A. Kaczmarska 87, M. Kado 110, H. Kagan 119, M. Kagan 143, A. Kahn41, A. Kahn 128,C. Kahra 100, T. Kaji 153, E. Kajomovitz 150, N. Kakati 169, I. Kalaitzidou 54,C.W. Kalderon 29, A. Kamenshchikov 155, N.J. Kang 136, D. Kar 33g, K. Karava 126,M.J. Kareem 156b, E. Karentzos 54, I. Karkanias 152, O. Karkout 114, S.N. Karpov 38,Z.M. Karpova 38, V. Kartvelishvili 91, A.N. Karyukhin 37, E. Kasimi 152, J. Katzy 48,S. Kaur 34, K. Kawade 140, M.P. Kawale 120, C. Kawamoto 88, T. Kawamoto 135,E.F. Kay 36, F.I. Kaya 158, S. Kazakos 107, V.F. Kazanin 37, Y. Ke 145, J.M. Keaveney 33a,R. Keeler 165, G.V. Kehris 61, J.S. Keller 34, A.S. Kelly96, J.J. Kempster 146,K.E. Kennedy 41, P.D. Kennedy 100, O. Kepka 131, B.P. Kerridge 167, S. Kersten 171,B.P. Kerševan 93, S. Keshri 66, L. Keszeghova 28a, S. Ketabchi Haghighat 155,M. Khandoga 127, A. Khanov 121, A.G. Kharlamov 37, T. Kharlamova 37, E.E. Khoda 138,M. Kholodenko 37, T.J. Khoo 18, G. Khoriauli 166, J. Khubua 149b, Y.A.R. Khwaira 66,A. Kilgallon 123, D.W. Kim 47a,47b, Y.K. Kim 39, N. Kimura 96, M.K. Kingston 55,A. Kirchhoff 55, C. Kirfel 24, F. Kirfel 24, J. Kirk 134, A.E. Kiryunin 110, C. Kitsaki 10,O. Kivernyk 24, M. Klassen 63a, C. Klein 34, L. Klein 166, M.H. Klein 106, M. Klein 92,S.B. Klein 56, U. Klein 92, P. Klimek 36, A. Klimentov 29, T. Klioutchnikova 36, P. Kluit 114,S. Kluth 110, E. Kneringer 79, T.M. Knight 155, A. Knue 49, R. Kobayashi 88,D. Kobylianskii 169, S.F. Koch 126, M. Kocian 143, P. Kodyš 133, D.M. Koeck 123,P.T. Koenig 24, T. Koffas 34, M. Kolb 135, I. Koletsou 4, T. Komarek 122, K. Köneke 54,– 51 –JHEP05(2024)150A.X.Y. Kong 1, T. Kono 118, N. Konstantinidis 96, B. Konya 98, R. Kopeliansky 68,S. Koperny 86a, K. Korcyl 87, K. Kordas 152,e, G. Koren 151, A. Korn 96, S. Korn 55,I. Korolkov 13, N. Korotkova 37, B. Kortman 114, O. Kortner 110, S. Kortner 110,W.H. Kostecka 115, V.V. Kostyukhin 141, A. Kotsokechagia 135, A. Kotwal 51, A. Koulouris 36,A. Kourkoumeli-Charalampidi 73a,73b, C. Kourkoumelis 9, E. Kourlitis 110,ae, O. Kovanda 146,R. Kowalewski 165, W. Kozanecki 135, A.S. Kozhin 37, V.A. Kramarenko 37, G. Kramberger 93,P. Kramer 100, M.W. Krasny 127, A. Krasznahorkay 36, J.W. Kraus 171, J.A. Kremer 48,T. Kresse 50, J. Kretzschmar 92, K. Kreul 18, P. Krieger 155, S. Krishnamurthy 103,M. Krivos 133, K. Krizka 20, K. Kroeninger 49, H. Kroha 110, J. Kroll 131, J. Kroll 128,K.S. Krowpman 107, U. Kruchonak 38, H. Krüger 24, N. Krumnack81, M.C. Kruse 51,J.A. Krzysiak 87, O. Kuchinskaia 37, S. Kuday 3a, S. Kuehn 36, R. Kuesters 54, T. Kuhl 48,V. Kukhtin 38, Y. Kulchitsky 37,a, S. Kuleshov 137d,137b, M. Kumar 33g, N. Kumari 48,A. Kupco 131, T. Kupfer49, A. Kupich 37, O. Kuprash 54, H. Kurashige 85,L.L. Kurchaninov 156a, O. Kurdysh 66, Y.A. Kurochkin 37, A. Kurova 37, M. Kuze 154,A.K. Kvam 103, J. Kvita 122, T. Kwan 104, N.G. Kyriacou 106, L.A.O. Laatu 102,C. Lacasta 163, F. Lacava 75a,75b, H. Lacker 18, D. Lacour 127, N.N. Lad 96, E. Ladygin 38,B. Laforge 127, T. Lagouri 137e, F.Z. Lahbabi 35a, S. Lai 55, I.K. Lakomiec 86a, N. Lalloue 60,J.E. Lambert 165, S. Lammers 68, W. Lampl 7, C. Lampoudis 152,e, A.N. Lancaster 115,E. Lançon 29, U. Landgraf 54, M.P.J. Landon 94, V.S. Lang 54, R.J. Langenberg 103,O.K.B. Langrekken 125, A.J. Lankford 160, F. Lanni 36, K. Lantzsch 24, A. Lanza 73a,A. Lapertosa 57b,57a, J.F. Laporte 135, T. Lari 71a, F. Lasagni Manghi 23b, M. Lassnig 36,V. Latonova 131, A. Laudrain 100, A. Laurier 150, S.D. Lawlor 139, Z. Lawrence 101,M. Lazzaroni 71a,71b, B. Le101, E.M. Le Boulicaut 51, B. Leban 93, A. Lebedev 81,M. LeBlanc 101, F. Ledroit-Guillon 60, A.C.A. Lee96, S.C. Lee 148, S. Lee 47a,47b, T.F. Lee 92,L.L. Leeuw 33c, H.P. Lefebvre 95, M. Lefebvre 165, C. Leggett 17a, G. Lehmann Miotto 36,M. Leigh 56, W.A. Leight 103, W. Leinonen 113, A. Leisos 152,r, M.A.L. Leite 83c,C.E. Leitgeb 48, R. Leitner 133, K.J.C. Leney 44, T. Lenz 24, S. Leone 74a,C. Leonidopoulos 52, A. Leopold 144, C. Leroy 108, R. Les 107, C.G. Lester 32,M. Levchenko 37, J. Levêque 4, D. Levin 106, L.J. Levinson 169, M.P. Lewicki 87,D.J. Lewis 4, A. Li 5, B. Li 62b, C. Li62a, C-Q. Li 62c, H. Li 62a, H. Li 62b, H. Li 14c,H. Li 14b, H. Li 62b, K. Li 138, L. Li 62c, M. Li 14a,14e, Q.Y. Li 62a, S. Li 14a,14e,S. Li 62d,62c,d, T. Li 5, X. Li 104, Z. Li 126, Z. Li 104, Z. Li 92, Z. Li 14a,14e, S. Liang14a,14e,Z. Liang 14a, M. Liberatore 135, B. Liberti 76a, K. Lie 64c, J. Lieber Marin 83b, H. Lien 68,K. Lin 107, R.E. Lindley 7, J.H. Lindon 2, E. Lipeles 128, A. Lipniacka 16, A. Lister 164,J.D. Little 4, B. Liu 14a, B.X. Liu 142, D. Liu 62d,62c, J.B. Liu 62a, J.K.K. Liu 32,K. Liu 62d,62c, M. Liu 62a, M.Y. Liu 62a, P. Liu 14a, Q. Liu 62d,138,62c, X. Liu 62a,Y. Liu 14d,14e, Y.L. Liu 62b, Y.W. Liu 62a, J. Llorente Merino 142, S.L. Lloyd 94,E.M. Lobodzinska 48, P. Loch 7, S. Loffredo 76a,76b, T. Lohse 18, K. Lohwasser 139,E. Loiacono 48, M. Lokajicek 131,∗, J.D. Lomas 20, J.D. Long 162, I. Longarini 160,L. Longo 70a,70b, R. Longo 162, I. Lopez Paz 67, A. Lopez Solis 48, J. Lorenz 109,N. Lorenzo Martinez 4, A.M. Lory 109, G. Löschcke Centeno 146, O. Loseva 37, X. Lou 47a,47b,X. Lou 14a,14e, A. Lounis 66, J. Love 6, P.A. Love 91, G. Lu 14a,14e, M. Lu 80, S. Lu 128,Y.J. Lu 65, H.J. Lubatti 138, C. Luci 75a,75b, F.L. Lucio Alves 14c, A. Lucotte 60,– 52 –JHEP05(2024)150F. Luehring 68, I. Luise 145, O. Lukianchuk 66, O. Lundberg 144, B. Lund-Jensen 144,N.A. Luongo 123, M.S. Lutz 151, A.B. Lux 25, D. Lynn 29, H. Lyons92, R. Lysak 131,E. Lytken 98, V. Lyubushkin 38, T. Lyubushkina 38, M.M. Lyukova 145, H. Ma 29, K. Ma62a,L.L. Ma 62b, Y. Ma 121, D.M. Mac Donell 165, G. Maccarrone 53, J.C. MacDonald 100,P.C. Machado De Abreu Farias 83b, R. Madar 40, W.F. Mader 50, T. Madula 96, J. Maeda 85,T. Maeno 29, H. Maguire 139, V. Maiboroda 135, A. Maio 130a,130b,130d, K. Maj 86a,O. Majersky 48, S. Majewski 123, N. Makovec 66, V. Maksimovic 15, B. Malaescu 127,Pa. Malecki 87, V.P. Maleev 37, F. Malek 60, M. Mali 93, D. Malito 95, U. Mallik 80,S. Maltezos10, S. Malyukov38, J. Mamuzic 13, G. Mancini 53, G. Manco 73a,73b, J.P. Mandalia 94,I. Mandić 93, L. Manhaes de Andrade Filho 83a, I.M. Maniatis 169, J. Manjarres Ramos 102,aa,D.C. Mankad 169, A. Mann 109, B. Mansoulie 135, S. Manzoni 36, A. Marantis 152,r,G. Marchiori 5, M. Marcisovsky 131, C. Marcon 71a, M. Marinescu 20, M. Marjanovic 120,E.J. Marshall 91, Z. Marshall 17a, S. Marti-Garcia 163, T.A. Martin 167, V.J. Martin 52,B. Martin dit Latour 16, L. Martinelli 75a,75b, M. Martinez 13,s, P. Martinez Agullo 163,V.I. Martinez Outschoorn 103, P. Martinez Suarez 13, S. Martin-Haugh 134, V.S. Martoiu 27b,A.C. Martyniuk 96, A. Marzin 36, D. Mascione 78a,78b, L. Masetti 100, T. Mashimo 153,J. Masik 101, A.L. Maslennikov 37, L. Massa 23b, P. Massarotti 72a,72b, P. Mastrandrea 74a,74b,A. Mastroberardino 43b,43a, T. Masubuchi 153, T. Mathisen 161, J. Matousek 133,N. Matsuzawa153, J. Maurer 27b, B. Maček 93, D.A. Maximov 37, R. Mazini 148, I. Maznas 152,M. Mazza 107, S.M. Mazza 136, E. Mazzeo 71a,71b, C. Mc Ginn 29, J.P. Mc Gowan 104,S.P. Mc Kee 106, E.F. McDonald 105, A.E. McDougall 114, J.A. Mcfayden 146,R.P. McGovern 128, G. Mchedlidze 149b, R.P. Mckenzie 33g, T.C. Mclachlan 48,D.J. Mclaughlin 96, S.J. McMahon 134, P.C. McNamara 105, C.M. Mcpartland 92,R.A. McPherson 165,w, S. Mehlhase 109, A. Mehta 92, D. Melini 150, B.R. Mellado Garcia 33g,A.H. Melo 55, F. Meloni 48, A.M. Mendes Jacques Da Costa 101, H.Y. Meng 155, L. Meng 91,S. Menke 110, M. Mentink 36, E. Meoni 43b,43a, C. Merlassino 126, L. Merola 72a,72b,C. Meroni 71a,71b, G. Merz106, O. Meshkov 37, J. Metcalfe 6, A.S. Mete 6, C. Meyer 68,J-P. Meyer 135, R.P. Middleton 134, L. Mijović 52, G. Mikenberg 169, M. Mikestikova 131,M. Mikuž 93, H. Mildner 100, A. Milic 36, C.D. Milke 44, D.W. Miller 39, L.S. Miller 34,A. Milov 169, D.A. Milstead47a,47b, T. Min14c, A.A. Minaenko 37, I.A. Minashvili 149b,L. Mince 59, A.I. Mincer 117, B. Mindur 86a, M. Mineev 38, Y. Mino 88, L.M. Mir 13,M. Miralles Lopez 163, M. Mironova 17a, A. Mishima153, M.C. Missio 113, A. Mitra 167,V.A. Mitsou 163, Y. Mitsumori 111, O. Miu 155, P.S. Miyagawa 94, T. Mkrtchyan 63a,M. Mlinarevic 96, T. Mlinarevic 96, M. Mlynarikova 36, S. Mobius 19, P. Moder 48,P. Mogg 109, A.F. Mohammed 14a,14e, S. Mohapatra 41, G. Mokgatitswane 33g, L. Moleri 169,B. Mondal 141, S. Mondal 132, K. Mönig 48, E. Monnier 102, L. Monsonis Romero163,J. Montejo Berlingen 13, M. Montella 119, F. Montereali 77a,77b, F. Monticelli 90,S. Monzani 69a,69c, N. Morange 66, A.L. Moreira De Carvalho 130a, M. Moreno Llácer 163,C. Moreno Martinez 56, P. Morettini 57b, S. Morgenstern 36, M. Morii 61, M. Morinaga 153,A.K. Morley 36, F. Morodei 75a,75b, L. Morvaj 36, P. Moschovakos 36, B. Moser 36,M. Mosidze 149b, T. Moskalets 54, P. Moskvitina 113, J. Moss 31,l, E.J.W. Moyse 103,O. Mtintsilana 33g, S. Muanza 102, J. Mueller 129, D. Muenstermann 91, R. Müller 19,G.A. Mullier 161, A.J. Mullin32, J.J. Mullin128, D.P. Mungo 155, D. Munoz Perez 163,– 53 –JHEP05(2024)150F.J. Munoz Sanchez 101, M. Murin 101, W.J. Murray 167,134, A. Murrone 71a,71b,J.M. Muse 120, M. Muškinja 17a, C. Mwewa 29, A.G. Myagkov 37,a, A.J. Myers 8,A.A. Myers129, G. Myers 68, M. Myska 132, B.P. Nachman 17a, O. Nackenhorst 49, A. Nag 50,K. Nagai 126, K. Nagano 84, J.L. Nagle 29,ai, E. Nagy 102, A.M. Nairz 36, Y. Nakahama 84,K. Nakamura 84, K. Nakkalil 5, H. Nanjo 124, R. Narayan 44, E.A. Narayanan 112,I. Naryshkin 37, M. Naseri 34, S. Nasri 159, C. Nass 24, G. Navarro 22a,J. Navarro-Gonzalez 163, R. Nayak 151, A. Nayaz 18, P.Y. Nechaeva 37, F. Nechansky 48,L. Nedic 126, T.J. Neep 20, A. Negri 73a,73b, M. Negrini 23b, C. Nellist 114, C. Nelson 104,K. Nelson 106, S. Nemecek 131, M. Nessi 36,h, M.S. Neubauer 162, F. Neuhaus 100,J. Neundorf 48, R. Newhouse 164, P.R. Newman 20, C.W. Ng 129, Y.W.Y. Ng 48,B. Ngair 35e, H.D.N. Nguyen 108, R.B. Nickerson 126, R. Nicolaidou 135, J. Nielsen 136,M. Niemeyer 55, J. Niermann 55,36, N. Nikiforou 36, V. Nikolaenko 37,a, I. Nikolic-Audit 127,K. Nikolopoulos 20, P. Nilsson 29, I. Ninca 48, H.R. Nindhito 56, G. Ninio 151, A. Nisati 75a,N. Nishu 2, R. Nisius 110, J-E. Nitschke 50, E.K. Nkadimeng 33g, T. Nobe 153, D.L. Noel 32,T. Nommensen 147, M.B. Norfolk 139, R.R.B. Norisam 96, B.J. Norman 34, J. Novak 93,T. Novak 48, L. Novotny 132, R. Novotny 112, L. Nozka 122, K. Ntekas 160,N.M.J. Nunes De Moura Junior 83b, E. Nurse96, J. Ocariz 127, A. Ochi 85, I. Ochoa 130a,S. Oerdek 48,t, J.T. Offermann 39, A. Ogrodnik 133, A. Oh 101, C.C. Ohm 144, H. Oide 84,R. Oishi 153, M.L. Ojeda 48, M.W. O’Keefe92, Y. Okumura 153, L.F. Oleiro Seabra 130a,S.A. Olivares Pino 137d, D. Oliveira Damazio 29, D. Oliveira Goncalves 83a, J.L. Oliver 160,A. Olszewski 87, Ö.O. Öncel 54, A.P. O’Neill 19, A. Onofre 130a,130e, P.U.E. Onyisi 11,M.J. Oreglia 39, G.E. Orellana 90, D. Orestano 77a,77b, N. Orlando 13, R.S. Orr 155,V. O’Shea 59, L.M. Osojnak 128, R. Ospanov 62a, G. Otero y Garzon 30, H. Otono 89,P.S. Ott 63a, G.J. Ottino 17a, M. Ouchrif 35d, J. Ouellette 29, F. Ould-Saada 125,M. Owen 59, R.E. Owen 134, K.Y. Oyulmaz 21a, V.E. Ozcan 21a, N. Ozturk 8, S. Ozturk 82,H.A. Pacey 126, A. Pacheco Pages 13, C. Padilla Aranda 13, G. Padovano 75a,75b,S. Pagan Griso 17a, G. Palacino 68, A. Palazzo 70a,70b, S. Palestini 36, J. Pan 172, T. Pan 64a,D.K. Panchal 11, C.E. Pandini 114, J.G. Panduro Vazquez 95, H.D. Pandya 1, H. Pang 14b,P. Pani 48, G. Panizzo 69a,69c, L. Paolozzi 56, C. Papadatos 108, S. Parajuli 44,A. Paramonov 6, C. Paraskevopoulos 10, D. Paredes Hernandez 64b, T.H. Park 155,M.A. Parker 32, F. Parodi 57b,57a, E.W. Parrish 115, V.A. Parrish 52, J.A. Parsons 41,U. Parzefall 54, B. Pascual Dias 108, L. Pascual Dominguez 151, E. Pasqualucci 75a,S. Passaggio 57b, F. Pastore 95, P. Pasuwan 47a,47b, P. Patel 87, U.M. Patel 51, J.R. Pater 101,T. Pauly 36, J. Pearkes 143, M. Pedersen 125, R. Pedro 130a, S.V. Peleganchuk 37, O. Penc 36,E.A. Pender 52, H. Peng 62a, K.E. Penski 109, M. Penzin 37, B.S. Peralva 83d,A.P. Pereira Peixoto 60, L. Pereira Sanchez 47a,47b, D.V. Perepelitsa 29,ai, E. Perez Codina 156a,M. Perganti 10, L. Perini 71a,71b,∗, H. Pernegger 36, O. Perrin 40, K. Peters 48,R.F.Y. Peters 101, B.A. Petersen 36, T.C. Petersen 42, E. Petit 102, V. Petousis 132,C. Petridou 152,e, A. Petrukhin 141, M. Pettee 17a, N.E. Pettersson 36, A. Petukhov 37,K. Petukhova 133, R. Pezoa 137f , L. Pezzotti 36, G. Pezzullo 172, T.M. Pham 170,T. Pham 105, P.W. Phillips 134, G. Piacquadio 145, E. Pianori 17a, F. Piazza 71a,71b,R. Piegaia 30, D. Pietreanu 27b, A.D. Pilkington 101, M. Pinamonti 69a,69c, J.L. Pinfold 2,B.C. Pinheiro Pereira 130a, A.E. Pinto Pinoargote 100,135, L. Pintucci 69a,69c, K.M. Piper 146,– 54 –JHEP05(2024)150A. Pirttikoski 56, D.A. Pizzi 34, L. Pizzimento 64b, A. Pizzini 114, M.-A. Pleier 29,V. Plesanovs54, V. Pleskot 133, E. Plotnikova38, G. Poddar 4, R. Poettgen 98, L. Poggioli 127,I. Pokharel 55, S. Polacek 133, G. Polesello 73a, A. Poley 142,156a, R. Polifka 132, A. Polini 23b,C.S. Pollard 167, Z.B. Pollock 119, V. Polychronakos 29, E. Pompa Pacchi 75a,75b,D. Ponomarenko 113, L. Pontecorvo 36, S. Popa 27a, G.A. Popeneciu 27d, A. Poreba 36,D.M. Portillo Quintero 156a, S. Pospisil 132, M.A. Postill 139, P. Postolache 27c,K. Potamianos 167, P.A. Potepa 86a, I.N. Potrap 38, C.J. Potter 32, H. Potti 1, T. Poulsen 48,J. Poveda 163, M.E. Pozo Astigarraga 36, A. Prades Ibanez 163, J. Pretel 54, D. Price 101,M. Primavera 70a, M.A. Principe Martin 99, R. Privara 122, T. Procter 59, M.L. Proffitt 138,N. Proklova 128, K. Prokofiev 64c, G. Proto 110, S. Protopopescu 29, J. Proudfoot 6,M. Przybycien 86a, W.W. Przygoda 86b, J.E. Puddefoot 139, D. Pudzha 37,D. Pyatiizbyantseva 37, J. Qian 106, D. Qichen 101, Y. Qin 101, T. Qiu 52, A. Quadt 55,M. Queitsch-Maitland 101, G. Quetant 56, R.P. Quinn 164, G. Rabanal Bolanos 61,D. Rafanoharana 54, F. Ragusa 71a,71b, J.L. Rainbolt 39, J.A. Raine 56, S. Rajagopalan 29,E. Ramakoti 37, K. Ran 48,14e, N.P. Rapheeha 33g, H. Rasheed 27b, V. Raskina 127,D.F. Rassloff 63a, S. Rave 100, B. Ravina 55, I. Ravinovich 169, M. Raymond 36,A.L. Read 125, N.P. Readioff 139, D.M. Rebuzzi 73a,73b, G. Redlinger 29, A.S. Reed 110,K. Reeves 26, J.A. Reidelsturz 171, D. Reikher 151, A. Rej 141, C. Rembser 36, A. Renardi 48,M. Renda 27b, M.B. Rendel110, F. Renner 48, A.G. Rennie 160, A.L. Rescia 48, S. Resconi 71a,M. Ressegotti 57b,57a, S. Rettie 36, J.G. Reyes Rivera 107, E. Reynolds 17a, O.L. Rezanova 37,P. Reznicek 133, N. Ribaric 91, E. Ricci 78a,78b, R. Richter 110, S. Richter 47a,47b,E. Richter-Was 86b, M. Ridel 127, S. Ridouani 35d, P. Rieck 117, P. Riedler 36,E.M. Riefel 47a,47b, M. Rijssenbeek 145, A. Rimoldi 73a,73b, M. Rimoldi 48, L. Rinaldi 23b,23a,T.T. Rinn 29, M.P. Rinnagel 109, G. Ripellino 161, I. Riu 13, P. Rivadeneira 48,J.C. Rivera Vergara 165, F. Rizatdinova 121, E. Rizvi 94, B.A. Roberts 167, B.R. Roberts 17a,S.H. Robertson 104,w, D. Robinson 32, C.M. Robles Gajardo137f , M. Robles Manzano 100,A. Robson 59, A. Rocchi 76a,76b, C. Roda 74a,74b, S. Rodriguez Bosca 63a,Y. Rodriguez Garcia 22a, A. Rodriguez Rodriguez 54, A.M. Rodríguez Vera 156b, S. Roe36,J.T. Roemer 160, A.R. Roepe-Gier 136, J. Roggel 171, O. Røhne 125, R.A. Rojas 103,C.P.A. Roland 68, J. Roloff 29, A. Romaniouk 37, E. Romano 73a,73b, M. Romano 23b,A.C. Romero Hernandez 162, N. Rompotis 92, L. Roos 127, S. Rosati 75a, B.J. Rosser 39,E. Rossi 126, E. Rossi 72a,72b, L.P. Rossi 57b, L. Rossini 54, R. Rosten 119, M. Rotaru 27b,B. Rottler 54, C. Rougier 102,aa, D. Rousseau 66, D. Rousso 32, A. Roy 162,S. Roy-Garand 155, A. Rozanov 102, Y. Rozen 150, X. Ruan 33g, A. Rubio Jimenez 163,A.J. Ruby 92, V.H. Ruelas Rivera 18, T.A. Ruggeri 1, A. Ruggiero 126, A. Ruiz-Martinez 163,A. Rummler 36, Z. Rurikova 54, N.A. Rusakovich 38, H.L. Russell 165, G. Russo 75a,75b,J.P. Rutherfoord 7, S. Rutherford Colmenares 32, K. Rybacki91, M. Rybar 133, E.B. Rye 125,A. Ryzhov 44, J.A. Sabater Iglesias 56, P. Sabatini 163, L. Sabetta 75a,75b,H.F-W. Sadrozinski 136, F. Safai Tehrani 75a, B. Safarzadeh Samani 134, M. Safdari 143,S. Saha 165, M. Sahinsoy 110, M. Saimpert 135, M. Saito 153, T. Saito 153, D. Salamani 36,A. Salnikov 143, J. Salt 163, A. Salvador Salas 13, D. Salvatore 43b,43a, F. Salvatore 146,A. Salzburger 36, D. Sammel 54, D. Sampsonidis 152,e, D. Sampsonidou 123, J. Sánchez 163,A. Sanchez Pineda 4, V. Sanchez Sebastian 163, H. Sandaker 125, C.O. Sander 48,– 55 –JHEP05(2024)150J.A. Sandesara 103, M. Sandhoff 171, C. Sandoval 22b, D.P.C. Sankey 134, T. Sano 88,A. Sansoni 53, L. Santi 75a,75b, C. Santoni 40, H. Santos 130a,130b, S.N. Santpur 17a,A. Santra 169, K.A. Saoucha 116b, J.G. Saraiva 130a,130d, J. Sardain 7, O. Sasaki 84,K. Sato 157, C. Sauer63b, F. Sauerburger 54, E. Sauvan 4, P. Savard 155,ag, R. Sawada 153,C. Sawyer 134, L. Sawyer 97, I. Sayago Galvan163, C. Sbarra 23b, A. Sbrizzi 23b,23a,T. Scanlon 96, J. Schaarschmidt 138, P. Schacht 110, U. Schäfer 100, A.C. Schaffer 66,44,D. Schaile 109, R.D. Schamberger 145, C. Scharf 18, M.M. Schefer 19, V.A. Schegelsky 37,D. Scheirich 133, F. Schenck 18, M. Schernau 160, C. Scheulen 55, C. Schiavi 57b,57a,E.J. Schioppa 70a,70b, M. Schioppa 43b,43a, B. Schlag 143,n, K.E. Schleicher 54, S. Schlenker 36,J. Schmeing 171, M.A. Schmidt 171, K. Schmieden 100, C. Schmitt 100, S. Schmitt 48,L. Schoeffel 135, A. Schoening 63b, P.G. Scholer 54, E. Schopf 126, M. Schott 100,J. Schovancova 36, S. Schramm 56, F. Schroeder 171, T. Schroer 56, H-C. Schultz-Coulon 63a,M. Schumacher 54, B.A. Schumm 136, Ph. Schune 135, A.J. Schuy 138, H.R. Schwartz 136,A. Schwartzman 143, T.A. Schwarz 106, Ph. Schwemling 135, R. Schwienhorst 107,A. Sciandra 136, G. Sciolla 26, F. Scuri 74a, C.D. Sebastiani 92, K. Sedlaczek 115, P. Seema 18,S.C. Seidel 112, A. Seiden 136, B.D. Seidlitz 41, C. Seitz 48, J.M. Seixas 83b,G. Sekhniaidze 72a, S.J. Sekula 44, L. Selem 60, N. Semprini-Cesari 23b,23a, D. Sengupta 56,V. Senthilkumar 163, L. Serin 66, L. Serkin 69a,69b, M. Sessa 76a,76b, H. Severini 120,F. Sforza 57b,57a, A. Sfyrla 56, E. Shabalina 55, R. Shaheen 144, J.D. Shahinian 128,D. Shaked Renous 169, L.Y. Shan 14a, M. Shapiro 17a, A. Sharma 36, A.S. Sharma 164,P. Sharma 80, S. Sharma 48, P.B. Shatalov 37, K. Shaw 146, S.M. Shaw 101,A. Shcherbakova 37, Q. Shen 62c,5, P. Sherwood 96, L. Shi 96, X. Shi 14a, C.O. Shimmin 172,J.D. Shinner 95, I.P.J. Shipsey 126, S. Shirabe 56,h, M. Shiyakova 38,u, J. Shlomi 169,M.J. Shochet 39, J. Shojaii 105, D.R. Shope 125, B. Shrestha 120, S. Shrestha 119,aj ,E.M. Shrif 33g, M.J. Shroff 165, P. Sicho 131, A.M. Sickles 162, E. Sideras Haddad 33g,A. Sidoti 23b, F. Siegert 50, Dj. Sijacki 15, R. Sikora 86a, F. Sili 90, J.M. Silva 20,M.V. Silva Oliveira 29, S.B. Silverstein 47a, S. Simion66, R. Simoniello 36, E.L. Simpson 59,H. Simpson 146, L.R. Simpson 106, N.D. Simpson98, S. Simsek 82, S. Sindhu 55, P. Sinervo 155,S. Singh 155, S. Sinha 48, S. Sinha 101, M. Sioli 23b,23a, I. Siral 36, E. Sitnikova 48,S.Yu. Sivoklokov 37,∗, J. Sjölin 47a,47b, A. Skaf 55, E. Skorda 20, P. Skubic 120,M. Slawinska 87, V. Smakhtin169, B.H. Smart 134, J. Smiesko 36, S.Yu. Smirnov 37,Y. Smirnov 37, L.N. Smirnova 37,a, O. Smirnova 98, A.C. Smith 41, E.A. Smith 39,H.A. Smith 126, J.L. Smith 92, R. Smith143, M. Smizanska 91, K. Smolek 132,A.A. Snesarev 37, S.R. Snider 155, H.L. Snoek 114, S. Snyder 29, R. Sobie 165,w, A. Soffer 151,C.A. Solans Sanchez 36, E.Yu. Soldatov 37, U. Soldevila 163, A.A. Solodkov 37, S. Solomon 26,A. Soloshenko 38, K. Solovieva 54, O.V. Solovyanov 40, V. Solovyev 37, P. Sommer 36,A. Sonay 13, W.Y. Song 156b, J.M. Sonneveld 114, A. Sopczak 132, A.L. Sopio 96,F. Sopkova 28b, V. Sothilingam63a, S. Sottocornola 68, R. Soualah 116b, Z. Soumaimi 35e,D. South 48, N. Soybelman 169, S. Spagnolo 70a,70b, M. Spalla 110, D. Sperlich 54,G. Spigo 36, S. Spinali 91, D.P. Spiteri 59, M. Spousta 133, E.J. Staats 34, A. Stabile 71a,71b,R. Stamen 63a, A. Stampekis 20, M. Standke 24, E. Stanecka 87, M.V. Stange 50,B. Stanislaus 17a, M.M. Stanitzki 48, B. Stapf 48, E.A. Starchenko 37, G.H. Stark 136,J. Stark 102,aa, D.M. Starko156b, P. Staroba 131, P. Starovoitov 63a, S. Stärz 104,– 56 –JHEP05(2024)150R. Staszewski 87, G. Stavropoulos 46, J. Steentoft 161, P. Steinberg 29, B. Stelzer 142,156a,H.J. Stelzer 129, O. Stelzer-Chilton 156a, H. Stenzel 58, T.J. Stevenson 146, G.A. Stewart 36,J.R. Stewart 121, M.C. Stockton 36, G. Stoicea 27b, M. Stolarski 130a, S. Stonjek 110,A. Straessner 50, J. Strandberg 144, S. Strandberg 47a,47b, M. Stratmann 171, M. Strauss 120,T. Strebler 102, P. Strizenec 28b, R. Ströhmer 166, D.M. Strom 123, L.R. Strom 48,R. Stroynowski 44, A. Strubig 47a,47b, S.A. Stucci 29, B. Stugu 16, J. Stupak 120,N.A. Styles 48, D. Su 143, S. Su 62a, W. Su 62d, X. Su 62a,66, K. Sugizaki 153, V.V. Sulin 37,M.J. Sullivan 92, D.M.S. Sultan 78a,78b, L. Sultanaliyeva 37, S. Sultansoy 3b, T. Sumida 88,S. Sun 106, S. Sun 170, O. Sunneborn Gudnadottir 161, N. Sur 102, M.R. Sutton 146,H. Suzuki 157, M. Svatos 131, M. Swiatlowski 156a, T. Swirski 166, I. Sykora 28a,M. Sykora 133, T. Sykora 133, D. Ta 100, K. Tackmann 48,t, A. Taffard 160, R. Tafirout 156a,J.S. Tafoya Vargas 66, E.P. Takeva 52, Y. Takubo 84, M. Talby 102, A.A. Talyshev 37,K.C. Tam 64b, N.M. Tamir151, A. Tanaka 153, J. Tanaka 153, R. Tanaka 66, M. Tanasini 57b,57a,Z. Tao 164, S. Tapia Araya 137f , S. Tapprogge 100, A. Tarek Abouelfadl Mohamed 107,S. Tarem 150, K. Tariq 14a, G. Tarna 102,27b, G.F. Tartarelli 71a, P. Tas 133, M. Tasevsky 131,E. Tassi 43b,43a, A.C. Tate 162, G. Tateno 153, Y. Tayalati 35e,v, G.N. Taylor 105,W. Taylor 156b, H. Teagle92, A.S. Tee 170, R. Teixeira De Lima 143, P. Teixeira-Dias 95,J.J. Teoh 155, K. Terashi 153, J. Terron 99, S. Terzo 13, M. Testa 53, R.J. Teuscher 155,w,A. Thaler 79, O. Theiner 56, N. Themistokleous 52, T. Theveneaux-Pelzer 102,O. Thielmann 171, D.W. Thomas95, J.P. Thomas 20, E.A. Thompson 17a, P.D. Thompson 20,E. Thomson 128, Y. Tian 55, V. Tikhomirov 37,a, Yu.A. Tikhonov 37, S. Timoshenko37,D. Timoshyn 133, E.X.L. Ting 1, P. Tipton 172, S.H. Tlou 33g, A. Tnourji 40, K. Todome 154,S. Todorova-Nova 133, S. Todt50, M. Togawa 84, J. Tojo 89, S. Tokár 28a, K. Tokushuku 84,O. Toldaiev 68, R. Tombs 32, M. Tomoto 84,111, L. Tompkins 143,n, K.W. Topolnicki 86b,E. Torrence 123, H. Torres 102,aa, E. Torró Pastor 163, M. Toscani 30, C. Tosciri 39,M. Tost 11, D.R. Tovey 139, A. Traeet16, I.S. Trandafir 27b, T. Trefzger 166, A. Tricoli 29,I.M. Trigger 156a, S. Trincaz-Duvoid 127, D.A. Trischuk 26, B. Trocmé 60, C. Troncon 71a,L. Truong 33c, M. Trzebinski 87, A. Trzupek 87, F. Tsai 145, M. Tsai 106, A. Tsiamis 152,e,P.V. Tsiareshka37, S. Tsigaridas 156a, A. Tsirigotis 152,r, V. Tsiskaridze 155,E.G. Tskhadadze 149a, M. Tsopoulou 152,e, Y. Tsujikawa 88, I.I. Tsukerman 37, V. Tsulaia 17a,S. Tsuno 84, O. Tsur150, K. Tsuri 118, D. Tsybychev 145, Y. Tu 64b, A. Tudorache 27b,V. Tudorache 27b, A.N. Tuna 36, S. Turchikhin 57b,57a, I. Turk Cakir 3a, R. Turra 71a,T. Turtuvshin 38,x, P.M. Tuts 41, S. Tzamarias 152,e, P. Tzanis 10, E. Tzovara 100,F. Ukegawa 157, P.A. Ulloa Poblete 137c,137b, E.N. Umaka 29, G. Unal 36, M. Unal 11,A. Undrus 29, G. Unel 160, J. Urban 28b, P. Urquijo 105, G. Usai 8, R. Ushioda 154,M. Usman 108, Z. Uysal 21b, L. Vacavant 102, V. Vacek 132, B. Vachon 104, K.O.H. Vadla 125,T. Vafeiadis 36, A. Vaitkus 96, C. Valderanis 109, E. Valdes Santurio 47a,47b, M. Valente 156a,S. Valentinetti 23b,23a, A. Valero 163, E. Valiente Moreno 163, A. Vallier 102,aa,J.A. Valls Ferrer 163, D.R. Van Arneman 114, T.R. Van Daalen 138, A. Van Der Graaf 49,P. Van Gemmeren 6, M. Van Rijnbach 125,36, S. Van Stroud 96, I. Van Vulpen 114,M. Vanadia 76a,76b, W. Vandelli 36, M. Vandenbroucke 135, E.R. Vandewall 121,D. Vannicola 151, L. Vannoli 57b,57a, R. Vari 75a, E.W. Varnes 7, C. Varni 17b, T. Varol 148,D. Varouchas 66, L. Varriale 163, K.E. Varvell 147, M.E. Vasile 27b, L. Vaslin40,– 57 –JHEP05(2024)150G.A. Vasquez 165, A. Vasyukov 38, F. Vazeille 40, T. Vazquez Schroeder 36, J. Veatch 31,V. Vecchio 101, M.J. Veen 103, I. Veliscek 126, L.M. Veloce 155, F. Veloso 130a,130c,S. Veneziano 75a, A. Ventura 70a,70b, S. Ventura Gonzalez 135, A. Verbytskyi 110,M. Verducci 74a,74b, C. Vergis 24, M. Verissimo De Araujo 83b, W. Verkerke 114,J.C. Vermeulen 114, C. Vernieri 143, M. Vessella 103, M.C. Vetterli 142,ag, A. Vgenopoulos 152,e,N. Viaux Maira 137f , T. Vickey 139, O.E. Vickey Boeriu 139, G.H.A. Viehhauser 126,L. Vigani 63b, M. Villa 23b,23a, M. Villaplana Perez 163, E.M. Villhauer52, E. Vilucchi 53,M.G. Vincter 34, G.S. Virdee 20, A. Vishwakarma 52, A. Visibile114, C. Vittori 36,I. Vivarelli 146, E. Voevodina 110, F. Vogel 109, P. Vokac 132, Yu. Volkotrub 86a,J. Von Ahnen 48, E. Von Toerne 24, B. Vormwald 36, V. Vorobel 133, K. Vorobev 37,M. Vos 163, K. Voss 141, J.H. Vossebeld 92, M. Vozak 114, L. Vozdecky 94, N. Vranjes 15,M. Vranjes Milosavljevic 15, M. Vreeswijk 114, R. Vuillermet 36, O. Vujinovic 100, I. Vukotic 39,S. Wada 157, C. Wagner103, J.M. Wagner 17a, W. Wagner 171, S. Wahdan 171, H. Wahlberg 90,M. Wakida 111, J. Walder 134, R. Walker 109, W. Walkowiak 141, A. Wall 128,T. Wamorkar 6, A.Z. Wang 170, C. Wang 100, C. Wang 62c, H. Wang 17a, J. Wang 64a,R.-J. Wang 100, R. Wang 61, R. Wang 6, S.M. Wang 148, S. Wang 62b, T. Wang 62a,W.T. Wang 80, W. Wang 14a, X. Wang 14c, X. Wang 162, X. Wang 62c, Y. Wang 62d,Y. Wang 14c, Z. Wang 106, Z. Wang 62d,51,62c, Z. Wang 106, A. Warburton 104, R.J. Ward 20,N. Warrack 59, A.T. Watson 20, H. Watson 59, M.F. Watson 20, E. Watton 59,134,G. Watts 138, B.M. Waugh 96, C. Weber 29, H.A. Weber 18, M.S. Weber 19, S.M. Weber 63a,C. Wei 62a, Y. Wei 126, A.R. Weidberg 126, E.J. Weik 117, J. Weingarten 49, M. Weirich 100,C. Weiser 54, C.J. Wells 48, T. Wenaus 29, B. Wendland 49, T. Wengler 36, N.S. Wenke110,N. Wermes 24, M. Wessels 63a, A.M. Wharton 91, A.S. White 61, A. White 8, M.J. White 1,D. Whiteson 160, L. Wickremasinghe 124, W. Wiedenmann 170, C. Wiel 50, M. Wielers 134,C. Wiglesworth 42, D.J. Wilbern120, H.G. Wilkens 36, D.M. Williams 41, H.H. Williams128,S. Williams 32, S. Willocq 103, B.J. Wilson 101, P.J. Windischhofer 39, F.I. Winkel 30,F. Winklmeier 123, B.T. Winter 54, J.K. Winter 101, M. Wittgen143, M. Wobisch 97,Z. Wolffs 114, J. Wollrath160, M.W. Wolter 87, H. Wolters 130a,130c, A.F. Wongel 48,S.D. Worm 48, B.K. Wosiek 87, K.W. Woźniak 87, S. Wozniewski 55, K. Wraight 59, C. Wu 20,J. Wu 14a,14e, M. Wu 64a, M. Wu 113, S.L. Wu 170, X. Wu 56, Y. Wu 62a, Z. Wu 135,J. Wuerzinger 110,ae, T.R. Wyatt 101, B.M. Wynne 52, S. Xella 42, L. Xia 14c, M. Xia 14b,J. Xiang 64c, M. Xie 62a, X. Xie 62a, S. Xin 14a,14e, A. Xiong 123, J. Xiong 17a, D. Xu 14a,H. Xu 62a, L. Xu 62a, R. Xu 128, T. Xu 106, Y. Xu 14b, Z. Xu 52, Z. Xu 14a, B. Yabsley 147,S. Yacoob 33a, Y. Yamaguchi 154, E. Yamashita 153, H. Yamauchi 157, T. Yamazaki 17a,Y. Yamazaki 85, J. Yan62c, S. Yan 126, Z. Yan 25, H.J. Yang 62c,62d, H.T. Yang 62a,S. Yang 62a, T. Yang 64c, X. Yang 62a, X. Yang 14a, Y. Yang 44, Y. Yang62a, Z. Yang 62a,W-M. Yao 17a, Y.C. Yap 48, H. Ye 14c, H. Ye 55, J. Ye 14a, S. Ye 29, X. Ye 62a, Y. Yeh 96,I. Yeletskikh 38, B.K. Yeo 17b, M.R. Yexley 96, P. Yin 41, K. Yorita 168, S. Younas 27b,C.J.S. Young 36, C. Young 143, C. Yu 14a,14e, Y. Yu 62a, J. Yuan 14a,14e, M. Yuan 106,R. Yuan 62b, L. Yue 96, M. Zaazoua 62a, B. Zabinski 87, E. Zaid52, T. Zakareishvili 149b,N. Zakharchuk 34, S. Zambito 56, J.A. Zamora Saa 137d,137b, J. Zang 153, D. Zanzi 54,O. Zaplatilek 132, C. Zeitnitz 171, H. Zeng 14a, J.C. Zeng 162, D.T. Zenger Jr 26, O. Zenin 37,T. Ženiš 28a, S. Zenz 94, S. Zerradi 35a, D. Zerwas 66, M. Zhai 14a,14e, B. Zhang 14c,– 58 –JHEP05(2024)150D.F. Zhang 139, J. Zhang 62b, J. Zhang 6, K. Zhang 14a,14e, L. Zhang 14c, P. Zhang 14a,14e,R. Zhang 170, S. Zhang 106, T. Zhang 153, X. Zhang 62c, X. Zhang 62b, Y. Zhang 62c,5,Y. Zhang 96, Z. Zhang 17a, Z. Zhang 66, H. Zhao 138, P. Zhao 51, T. Zhao 62b, Y. Zhao 136,Z. Zhao 62a, A. Zhemchugov 38, J. Zheng 14c, K. Zheng 162, X. Zheng 62a, Z. Zheng 143,D. Zhong 162, B. Zhou 106, H. Zhou 7, N. Zhou 62c, Y. Zhou7, C.G. Zhu 62b, J. Zhu 106,Y. Zhu 62c, Y. Zhu 62a, X. Zhuang 14a, K. Zhukov 37, V. Zhulanov 37, N.I. Zimine 38,J. Zinsser 63b, M. Ziolkowski 141, L. Živković 15, A. Zoccoli 23b,23a, K. Zoch 61,T.G. Zorbas 139, O. Zormpa 46, W. Zou 41, L. Zwalinski 361Department of Physics, University of Adelaide, Adelaide; Australia2Department of Physics, University of Alberta, Edmonton AB; Canada3 (a)Department of Physics, Ankara University, Ankara;(b)Division of Physics, TOBB University ofEconomics and Technology, Ankara; Türkiye4 LAPP, Université Savoie Mont Blanc, CNRS/IN2P3, Annecy; France5APC, Université Paris Cité, CNRS/IN2P3, Paris; France6High Energy Physics Division, Argonne National Laboratory, Argonne IL; United States of America7Department of Physics, University of Arizona, Tucson AZ; United States of America8Department of Physics, University of Texas at Arlington, Arlington TX; United States of America9 Physics Department, National and Kapodistrian University of Athens, Athens; Greece10 Physics Department, National Technical University of Athens, Zografou; Greece11Department of Physics, University of Texas at Austin, Austin TX; United States of America12 Institute of Physics, Azerbaijan Academy of Sciences, Baku; Azerbaijan13 Institut de Física d’Altes Energies (IFAE), Barcelona Institute of Science and Technology, Barcelona;Spain14 (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)School of Science,Shenzhen Campus of Sun Yat-sen University;(e)University of Chinese Academy of Science (UCAS),Beijing; China15 Institute of Physics, University of Belgrade, Belgrade; Serbia16Department for Physics and Technology, University of Bergen, Bergen; Norway17 (a)Physics Division, Lawrence Berkeley National Laboratory, Berkeley CA;(b)University of California,Berkeley CA; United States of America18 Institut für Physik, Humboldt Universität zu Berlin, Berlin; Germany19Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics, University ofBern, Bern; Switzerland20 School of Physics and Astronomy, University of Birmingham, Birmingham; United Kingdom21 (a)Department of Physics, Bogazici University, Istanbul;(b)Department of Physics Engineering, GaziantepUniversity, Gaziantep;(c)Department of Physics, Istanbul University, Istanbul; Türkiye22 (a)Facultad de Ciencias y Centro de Investigaciónes, Universidad Antonio Nariño,Bogotá;(b)Departamento de Física, Universidad Nacional de Colombia, Bogotá; Colombia23 (a)Dipartimento di Fisica e Astronomia A. Righi, Università di Bologna, Bologna;(b)INFN Sezione diBologna; Italy24 Physikalisches Institut, Universität Bonn, Bonn; Germany25Department of Physics, Boston University, Boston MA; United States of America26Department of Physics, Brandeis University, Waltham MA; United States of America27 (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)NationalInstitute for Research and Development of Isotopic and Molecular Technologies, Physics Department,Cluj-Napoca;(e)National University of Science and Technology Politechnica, Bucharest;(f)West Universityin Timisoara, Timisoara;(g)Faculty of Physics, University of Bucharest, Bucharest; Romania28 (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– 59 –JHEP05(2024)15029 Physics Department, Brookhaven National Laboratory, Upton NY; United States of America30Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Física, yCONICET, Instituto de Física de Buenos Aires (IFIBA), Buenos Aires; Argentina31California State University, CA; United States of America32Cavendish Laboratory, University of Cambridge, Cambridge; United Kingdom33 (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)National Institute of Physics, University of the Philippines Diliman(Philippines);(e)University of South Africa, Department of Physics, Pretoria;(f)University of Zululand,KwaDlangezwa;(g)School of Physics, University of the Witwatersrand, Johannesburg; South Africa34Department of Physics, Carleton University, Ottawa ON; Canada35 (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)LPMR, Faculté des Sciences, UniversitéMohamed Premier, Oujda;(e)Faculté des sciences, Université Mohammed V, Rabat;(f)Institute of AppliedPhysics, Mohammed VI Polytechnic University, Ben Guerir; Morocco36CERN, Geneva; Switzerland37Affiliated with an institute covered by a cooperation agreement with CERN38Affiliated with an international laboratory covered by a cooperation agreement with CERN39 Enrico Fermi Institute, University of Chicago, Chicago IL; United States of America40 LPC, Université Clermont Auvergne, CNRS/IN2P3, Clermont-Ferrand; France41Nevis Laboratory, Columbia University, Irvington NY; United States of America42Niels Bohr Institute, University of Copenhagen, Copenhagen; Denmark43 (a)Dipartimento di Fisica, Università della Calabria, Rende;(b)INFN Gruppo Collegato di Cosenza,Laboratori Nazionali di Frascati; Italy44 Physics Department, Southern Methodist University, Dallas TX; United States of America45 Physics Department, University of Texas at Dallas, Richardson TX; United States of America46National Centre for Scientific Research “Demokritos”, Agia Paraskevi; Greece47 (a)Department of Physics, Stockholm University;(b)Oskar Klein Centre, Stockholm; Sweden48Deutsches Elektronen-Synchrotron DESY, Hamburg and Zeuthen; Germany49 Fakultät Physik, Technische Universität Dortmund, Dortmund; Germany50 Institut für Kern- und Teilchenphysik, Technische Universität Dresden, Dresden; Germany51Department of Physics, Duke University, Durham NC; United States of America52 SUPA — School of Physics and Astronomy, University of Edinburgh, Edinburgh; United Kingdom53 INFN e Laboratori Nazionali di Frascati, Frascati; Italy54 Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg; Germany55 II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen; Germany56Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève; Switzerland57 (a)Dipartimento di Fisica, Università di Genova, Genova;(b)INFN Sezione di Genova; Italy58 II. Physikalisches Institut, Justus-Liebig-Universität Giessen, Giessen; Germany59 SUPA — School of Physics and Astronomy, University of Glasgow, Glasgow; United Kingdom60 LPSC, Université Grenoble Alpes, CNRS/IN2P3, Grenoble INP, Grenoble; France61 Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge MA; United States ofAmerica62 (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; China63 (a)Kirchhoff-Institut für Physik, Ruprecht-Karls-Universität Heidelberg, Heidelberg;(b)PhysikalischesInstitut, Ruprecht-Karls-Universität Heidelberg, Heidelberg; Germany64 (a)Department of Physics, Chinese University of Hong Kong, Shatin, N.T., Hong Kong;(b)Department ofPhysics, University of Hong Kong, Hong Kong;(c)Department of Physics and Institute for Advanced Study,Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong; China– 60 –JHEP05(2024)15065Department of Physics, National Tsing Hua University, Hsinchu; Taiwan66 IJCLab, Université Paris-Saclay, CNRS/IN2P3, 91405, Orsay; France67Centro Nacional de Microelectrónica (IMB-CNM-CSIC), Barcelona; Spain68Department of Physics, Indiana University, Bloomington IN; United States of America69 (a)INFN Gruppo Collegato di Udine, Sezione di Trieste, Udine;(b)ICTP, Trieste;(c)DipartimentoPolitecnico di Ingegneria e Architettura, Università di Udine, Udine; Italy70 (a)INFN Sezione di Lecce;(b)Dipartimento di Matematica e Fisica, Università del Salento, Lecce; Italy71 (a)INFN Sezione di Milano;(b)Dipartimento di Fisica, Università di Milano, Milano; Italy72 (a)INFN Sezione di Napoli;(b)Dipartimento di Fisica, Università di Napoli, Napoli; Italy73 (a)INFN Sezione di Pavia;(b)Dipartimento di Fisica, Università di Pavia, Pavia; Italy74 (a)INFN Sezione di Pisa;(b)Dipartimento di Fisica E. Fermi, Università di Pisa, Pisa; Italy75 (a)INFN Sezione di Roma;(b)Dipartimento di Fisica, Sapienza Università di Roma, Roma; Italy76 (a)INFN Sezione di Roma Tor Vergata;(b)Dipartimento di Fisica, Università di Roma Tor Vergata, Roma;Italy77 (a)INFN Sezione di Roma Tre;(b)Dipartimento di Matematica e Fisica, Università Roma Tre, Roma; Italy78 (a)INFN-TIFPA;(b)Università degli Studi di Trento, Trento; Italy79Universität Innsbruck, Department of Astro and Particle Physics, Innsbruck; Austria80University of Iowa, Iowa City IA; United States of America81Department of Physics and Astronomy, Iowa State University, Ames IA; United States of America82 Istinye University, Sariyer, Istanbul; Türkiye83 (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;(d)Rio de Janeiro State University, Rio de Janeiro; Brazil84KEK, High Energy Accelerator Research Organization, Tsukuba; Japan85Graduate School of Science, Kobe University, Kobe; Japan86 (a)AGH University of Krakow, Faculty of Physics and Applied Computer Science, Krakow;(b)MarianSmoluchowski Institute of Physics, Jagiellonian University, Krakow; Poland87 Institute of Nuclear Physics Polish Academy of Sciences, Krakow; Poland88 Faculty of Science, Kyoto University, Kyoto; Japan89Research Center for Advanced Particle Physics and Department of Physics, Kyushu University, Fukuoka;Japan90 Instituto de Física La Plata, Universidad Nacional de La Plata and CONICET, La Plata; Argentina91 Physics Department, Lancaster University, Lancaster; United Kingdom92Oliver Lodge Laboratory, University of Liverpool, Liverpool; United Kingdom93Department of Experimental Particle Physics, Jožef Stefan Institute and Department of Physics,University of Ljubljana, Ljubljana; Slovenia94 School of Physics and Astronomy, Queen Mary University of London, London; United Kingdom95Department of Physics, Royal Holloway University of London, Egham; United Kingdom96Department of Physics and Astronomy, University College London, London; United Kingdom97 Louisiana Tech University, Ruston LA; United States of America98 Fysiska institutionen, Lunds universitet, Lund; Sweden99Departamento de Física Teorica C-15 and CIAFF, Universidad Autónoma de Madrid, Madrid; Spain100 Institut für Physik, Universität Mainz, Mainz; Germany101 School of Physics and Astronomy, University of Manchester, Manchester; United Kingdom102CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille; France103Department of Physics, University of Massachusetts, Amherst MA; United States of America104Department of Physics, McGill University, Montreal QC; Canada105 School of Physics, University of Melbourne, Victoria; Australia106Department of Physics, University of Michigan, Ann Arbor MI; United States of America107Department of Physics and Astronomy, Michigan State University, East Lansing MI; United States ofAmerica108Group of Particle Physics, University of Montreal, Montreal QC; Canada109 Fakultät für Physik, Ludwig-Maximilians-Universität München, München; Germany– 61 –JHEP05(2024)150110Max-Planck-Institut für Physik (Werner-Heisenberg-Institut), München; Germany111Graduate School of Science and Kobayashi-Maskawa Institute, Nagoya University, Nagoya; Japan112Department of Physics and Astronomy, University of New Mexico, Albuquerque NM; United States ofAmerica113 Institute for Mathematics, Astrophysics and Particle Physics, Radboud University/Nikhef, Nijmegen;Netherlands114Nikhef National Institute for Subatomic Physics and University of Amsterdam, Amsterdam; Netherlands115Department of Physics, Northern Illinois University, DeKalb IL; United States of America116 (a)New York University Abu Dhabi, Abu Dhabi;(b)University of Sharjah, Sharjah; United Arab Emirates117Department of Physics, New York University, New York NY; United States of America118Ochanomizu University, Otsuka, Bunkyo-ku, Tokyo; Japan119Ohio State University, Columbus OH; United States of America120Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman OK; UnitedStates of America121Department of Physics, Oklahoma State University, Stillwater OK; United States of America122 Palacký University, Joint Laboratory of Optics, Olomouc; Czech Republic123 Institute for Fundamental Science, University of Oregon, Eugene, OR; United States of America124Graduate School of Science, Osaka University, Osaka; Japan125Department of Physics, University of Oslo, Oslo; Norway126Department of Physics, Oxford University, Oxford; United Kingdom127 LPNHE, Sorbonne Université, Université Paris Cité, CNRS/IN2P3, Paris; France128Department of Physics, University of Pennsylvania, Philadelphia PA; United States of America129Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh PA; United States of America130 (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, Universidade deCoimbra, 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)Departamento de Física, Instituto Superior Técnico, Universidade de Lisboa,Lisboa; Portugal131 Institute of Physics of the Czech Academy of Sciences, Prague; Czech Republic132Czech Technical University in Prague, Prague; Czech Republic133Charles University, Faculty of Mathematics and Physics, Prague; Czech Republic134 Particle Physics Department, Rutherford Appleton Laboratory, Didcot; United Kingdom135 IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette; France136 Santa Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz CA; UnitedStates of America137 (a)Departamento de Física, Pontificia Universidad Católica de Chile, Santiago;(b)Millennium Institute forSubatomic physics at high energy frontier (SAPHIR), Santiago;(c)Instituto de InvestigaciónMultidisciplinario en Ciencia y Tecnología, y Departamento de Física, Universidad de LaSerena;(d)Universidad Andres Bello, Department of Physics, Santiago;(e)Instituto de Alta Investigación,Universidad de Tarapacá, Arica;(f)Departamento de Física, Universidad Técnica Federico Santa María,Valparaíso; Chile138Department of Physics, University of Washington, Seattle WA; United States of America139Department of Physics and Astronomy, University of Sheffield, Sheffield; United Kingdom140Department of Physics, Shinshu University, Nagano; Japan141Department Physik, Universität Siegen, Siegen; Germany142Department of Physics, Simon Fraser University, Burnaby BC; Canada143 SLAC National Accelerator Laboratory, Stanford CA; United States of America144Department of Physics, Royal Institute of Technology, Stockholm; Sweden145Departments of Physics and Astronomy, Stony Brook University, Stony Brook NY; United States ofAmerica146Department of Physics and Astronomy, University of Sussex, Brighton; United Kingdom147 School of Physics, University of Sydney, Sydney; Australia– 62 –JHEP05(2024)150148 Institute of Physics, Academia Sinica, Taipei; Taiwan149 (a)E. Andronikashvili Institute of Physics, Iv. Javakhishvili Tbilisi State University, Tbilisi;(b)High EnergyPhysics Institute, Tbilisi State University, Tbilisi;(c)University of Georgia, Tbilisi; Georgia150Department of Physics, Technion, Israel Institute of Technology, Haifa; Israel151Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv University, Tel Aviv; Israel152Department of Physics, Aristotle University of Thessaloniki, Thessaloniki; Greece153 International Center for Elementary Particle Physics and Department of Physics, University of Tokyo,Tokyo; Japan154Department of Physics, Tokyo Institute of Technology, Tokyo; Japan155Department of Physics, University of Toronto, Toronto ON; Canada156 (a)TRIUMF, Vancouver BC;(b)Department of Physics and Astronomy, York University, Toronto ON;Canada157Division of Physics and Tomonaga Center for the History of the Universe, Faculty of Pure and AppliedSciences, University of Tsukuba, Tsukuba; Japan158Department of Physics and Astronomy, Tufts University, Medford MA; United States of America159United Arab Emirates University, Al Ain; United Arab Emirates160Department of Physics and Astronomy, University of California Irvine, Irvine CA; United States ofAmerica161Department of Physics and Astronomy, University of Uppsala, Uppsala; Sweden162Department of Physics, University of Illinois, Urbana IL; United States of America163 Instituto de Física Corpuscular (IFIC), Centro Mixto Universidad de Valencia — CSIC, Valencia; Spain164Department of Physics, University of British Columbia, Vancouver BC; Canada165Department of Physics and Astronomy, University of Victoria, Victoria BC; Canada166 Fakultät für Physik und Astronomie, Julius-Maximilians-Universität Würzburg, Würzburg; Germany167Department of Physics, University of Warwick, Coventry; United Kingdom168Waseda University, Tokyo; Japan169Department of Particle Physics and Astrophysics, Weizmann Institute of Science, Rehovot; Israel170Department of Physics, University of Wisconsin, Madison WI; United States of America171 Fakultät für Mathematik und Naturwissenschaften, Fachgruppe Physik, Bergische Universität Wuppertal,Wuppertal; Germany172Department of Physics, Yale University, New Haven CT; United States of AmericaaAlso Affiliated with an institute covered by a cooperation agreement with CERNbAlso at An-Najah National University, Nablus; PalestinecAlso at Borough of Manhattan Community College, City University of New York, New York NY; UnitedStates of AmericadAlso at Center for High Energy Physics, Peking University; ChinaeAlso at Center for Interdisciplinary Research and Innovation (CIRI-AUTH), Thessaloniki; Greecef Also at Centro Studi e Ricerche Enrico Fermi; ItalygAlso at CERN, Geneva; SwitzerlandhAlso at Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève; SwitzerlandiAlso at Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona; Spainj Also at Department of Financial and Management Engineering, University of the Aegean, Chios; GreecekAlso at Department of Physics, Ben Gurion University of the Negev, Beer Sheva; IsraellAlso at Department of Physics, California State University, Sacramento; United States of AmericamAlso at Department of Physics, King’s College London, London; United KingdomnAlso at Department of Physics, Stanford University, Stanford CA; United States of AmericaoAlso at Department of Physics, University of Fribourg, Fribourg; SwitzerlandpAlso at Department of Physics, University of Thessaly; GreeceqAlso at Department of Physics, Westmont College, Santa Barbara; United States of AmericarAlso at Hellenic Open University, Patras; GreecesAlso at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona; SpaintAlso at Institut für Experimentalphysik, Universität Hamburg, Hamburg; Germany– 63 –JHEP05(2024)150uAlso at Institute for Nuclear Research and Nuclear Energy (INRNE) of the Bulgarian Academy ofSciences, Sofia; BulgariavAlso at Institute of Applied Physics, Mohammed VI Polytechnic University, Ben Guerir; MoroccowAlso at Institute of Particle Physics (IPP); CanadaxAlso at Institute of Physics and Technology, Mongolian Academy of Sciences, Ulaanbaatar; MongoliayAlso at Institute of Physics, Azerbaijan Academy of Sciences, Baku; AzerbaijanzAlso at Institute of Theoretical Physics, Ilia State University, Tbilisi; GeorgiaaaAlso at L2IT, Université de Toulouse, CNRS/IN2P3, UPS, Toulouse; FranceabAlso at Lawrence Livermore National Laboratory, Livermore; United States of AmericaacAlso at National Institute of Physics, University of the Philippines Diliman (Philippines); PhilippinesadAlso at Ochanomizu University, Otsuka, Bunkyo-ku, Tokyo; JapanaeAlso at Technical University of Munich, Munich; Germanyaf Also at The Collaborative Innovation Center of Quantum Matter (CICQM), Beijing; ChinaagAlso at TRIUMF, Vancouver BC; CanadaahAlso at Università di Napoli Parthenope, Napoli; ItalyaiAlso at University of Colorado Boulder, Department of Physics, Colorado; United States of Americaaj Also at Washington College, Chestertown, MD; United States of AmericaakAlso at Yeditepe University, Physics Department, Istanbul; Türkiye∗Deceased– 64 –
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Beyond Standard Model
Electroweak Interaction
Hadron-Hadron Scattering
Supersymmetry
Search for electroweak production of supersymmetric particles in fnal states with two τ -leptons in √s = 13 TeV pp collisions with the ATLAS detector
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