Science, Faculty of
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Non UBC
Physics and Astronomy, Department of
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Journal of High Energy Physics. 2024 May 23;2024(5):263
The Author(s)
ATLAS Collaboration
A search for events with one top quark and missing transverse momentum in the fnal state is presented. The fully hadronic decay of the top quark is explored by selecting events with a reconstructed boosted top-quark topology produced in association with large missing transverse momentum. The analysis uses 139 fb−1 of proton-proton collision data at a centre-of-mass energy of √ s = 13 TeV recorded during 2015-2018 by the ATLAS detector at the Large Hadron Collider. The results are interpreted in the context of simplifed models for Dark Matter particle production and the single production of a vector-like T quark. Without signifcant excess relative to the Standard Model expectations, 95% confdence-level upper limits on the corresponding cross-sections are obtained. The production of Dark Matter particles in association with a single top quark is excluded for masses of a scalar (vector) mediator up to 4.3 (2.3) TeV, assuming mχ = 1 GeV and the model couplings λq = 0.6 and λχ = 0.4 (a = 0.5 and gχ = 1). The production of a single vector-like T quark is excluded for masses below 1.8 TeV assuming a coupling to the top quark κT = 0.5 and a branching ratio for T → Zt of 25%.
JHEP05(2024)263PuAlished for SISS Ay SpringerReceived: February 27, 2024Accepted: May 5, 2024Published: May 23, 2024Search for new particles in final states with a boostedtop quark and missing transverse momentum inproton-proton collisions at √s = 13TeV with theATLAS detectorThe ATLAS collaborationE-mail: atlas.publications@cern.chAbstract: A search for events with one top quark and missing transverse momentum in thefinal state is presented. The fully hadronic decay of the top quark is explored by selectingevents with a reconstructed boosted top-quark topology produced in association with largemissing transverse momentum. The analysis uses 139 fb−1 of proton-proton collision data ata centre-of-mass energy of√s = 13TeV recorded during 2015-2018 by the ATLAS detector atthe Large Hadron Collider. The results are interpreted in the context of simplified models forDark Matter particle production and the single production of a vector-like T quark. Withoutsignificant excess relative to the Standard Model expectations, 95% confidence-level upperlimits on the corresponding cross-sections are obtained. The production of Dark Matterparticles in association with a single top quark is excluded for masses of a scalar (vector)mediator up to 4.3 (2.3)TeV, assuming mχ = 1GeV and the model couplings λq = 0.6and λχ = 0.4 (a = 0.5 and gχ = 1). The production of a single vector-like T quark isexcluded for masses below 1.8TeV assuming a coupling to the top quark κT = 0.5 and abranching ratio for T → Zt of 25%.Keywords: Hadron-Hadron ScatteringArXiv ePrint: 2402.16561Open Access, © The Authors.Article funded by SCOAP3. https://doi.org/10.1007/JHEP05(2024)263JHEP05(2024)263Contents1 Introduction 12 Signal phenomenology 32.1 Dark Matter production in association with top quarks 42.2 Production of a single vector-like T quark 43 ATLAS detector 54 Data and simulated samples 65 Event reconstruction and object selection 96 Event selection and background estimate 106.1 Signal region definition 116.2 Background estimate 147 Systematic uncertainties 148 Results 179 Conclusions 27The ATLAS collaboration 381 IntroductionDespite its success in predicting the phenomenology of fundamental particle physics, theStandard Model (SM) is still far from being considered a complete description of nature atthe smallest length scales due to experimental observations such as the evidence for DarkMatter (DM) [1–3] and theoretical arguments, one of these being the hierarchy problem inthe Higgs sector [4]. The top quark, being the heaviest fundamental particle in the SM,plays an important role in the resolution of these questions in the context of many Beyondthe Standard Model (BSM) extensions. This paper focuses on the mono-top experimentalsignature and presents a search for an excess of events relative to the SM prediction in whicha single top quark is produced together with significant missing transverse momentum (EmissT ).Data from proton-proton (pp) collisions at the Large Hadron Collider (LHC) correspondingto an integrated luminosity of 139 fb−1 at a centre-of-mass energy of√s = 13 TeV are used.The mono-top signature can arise from the production of DM in association with a top quark,where the DM candidate is identified as missing transverse momentum in the detector [5–8],or from the production of a single new vector-like T quark [9–11], when T decays into a topquark and a Z boson, with the Z boson decaying into neutrinos.– 1 –JHEP05(2024)263Strong evidence of non-luminous gravitating matter, commonly known as DM, arisesfrom measurements of astrophysical phenomena such as the cosmic microwave backgroundand gravitational lensing. Through its gravitational interactions, it is suggested that DMconstitutes up to five times the ordinary matter contained in the universe [12, 13]. Its natureremains however unknown and is one of the major questions in physics. Assuming that DMis a weakly interacting massive particle [14], these particles may be produced in pp collisionsat the LHC via new mediator particles that couple both to SM and DM particles. Whilesuch candidates are not expected to interact significantly with the detector, the momentumimbalance of SM particles produced in association with the unobserved DM particles couldallow these processes to be detected.The ATLAS and CMS Collaborations have carried out several searches for DM productionin association with jets [15, 16], photons [17, 18], vector bosons [19–22], Higgs bosons [23,24, 24, 25] and pairs of b-quarks [26, 27] and top quarks [28–33]. Searches for same-chargetop-quark pairs also probe the production of DM mediator particles [34].The mono-top signature targeted in this paper has already been explored by the CDFCollaboration in pp¯ collisions at√s = 1.96 TeV [35] and more recently by both the ATLASand CMS Collaborations in pp collisions at√s = 8 TeV [36, 37] and√s = 13 TeV [38, 39].BSM models that predict a mono-top signature are typically characterised by the violationof the baryon number or by the inclusion of flavour-changing neutral currents (FCNC) [6].To consistently explore all the possible scenarios, an effective model is usually considered inwhich new mediators connect the SM particles and the DM candidates, encompassing all thetree-level production mechanisms of mono-top events [5, 6]. Two mechanisms are expecteddepending on the nature of the mediator particle. One case consists of the production of anew scalar mediator ϕ decaying into a top quark and a DM candidate χ. The latest analysesexclude such production for masses of the mediator particle below 3.5 TeV. The secondmechanism is characterised by the production of a vector mediator V that couples with SMparticles via an FCNC interaction and decays into DM particles χ. Masses of the mediator Vbelow 2 TeV are excluded by the latest analyses targeting this model. This analysis focuseson the high mass region beyond the excluded phase space.Vector-like quarks (VLQ) are colour-triplet spin-1/2 fermions in which the left- and right-handed components have the same properties under transformations of the SU(2)L ×U(1)Yelectroweak symmetry group. Such particles are predicted in many BSM extensions, such asLittle Higgs [40, 41] and Composite Higgs [42, 43] models, to cancel out the quadraticallydivergent contributions to the Higgs boson mass caused by radiative corrections from theSM particles. They are expected to mix with SM quarks and modify their Yukawa couplingsdepending on the specific VLQ model [44, 45]. To preserve the gauge invariance, only alimited set of possible representations exist [45, 46]. In this document, only the productionof a single 2/3e-charged vector-like T quark in the weak-isospin singlet is considered. Eventhough the coupling of T with quarks from the first two generations is not excluded [47, 48],it is common to assume T quarks couple only with the third-generation quarks [9].Vector-like quarks can be produced singly via the electroweak interaction or in pairsvia the strong interaction in pp collisions. While the cross-section for pair production isgiven by quantum chromodynamics, the single-production cross-section explicitly depends– 2 –JHEP05(2024)263on the coupling of the VLQs to SM vector bosons. There have been numerous searches forthe pair production of VLQs [49–66] that have excluded T -quark masses below 1.37 TeV at95% confidence level (CL) for a variety of decay modes. For T -quark masses above ∼1 TeV,VLQs would mainly be produced singly if the couplings to SM particles are sufficiently large.Searches for single production of T quarks have placed limits on T -quark production cross-sections for T -quark masses between 1 and 2 TeV at 95% CL for various couplings [67–77].For these higher masses, where single VLQ production is expected to dominate [78], thecross-section depends on the VLQ mass as well as the couplings to SM particles. In thisstudy, the coupling of T quarks with top quarks is described by the generalised couplingκT [10, 11]. The T quarks can decay both via charged and neutral currents into Wb, Zt, orHt. A singlet T with a branching ratio B(T → Zt) = 25% is assumed. The T → Zt→ νν¯qq¯′bfinal state is the one considered in this search.This paper follows a methodology similar to that used in the previous search based onthe 36 fb−1√s = 13 TeV data sample [39]. It considers the channel in which the top quarkdecays hadronically, found to be the most sensitive in the previous analysis. Signal regionsare defined to maximise the discovery potential, introducing an extreme gradient-boosted(XGBoost) decision tree (BDT) [79] to enhance the signal discrimination against the SMbackground. The output score of the XGBoost algorithm is also used as the discriminatingvariable in the signal regions. Improvements in the reconstruction and calibration of thefinal-state particles are also incorporated, in particular, related to jets and their flavouridentification. Regions enriched in the main sources of background events are identified andreferred to as control regions. A simultaneous fit to the data yields in the control regionsand to the XGBoost output discriminant distribution in the signal regions is performedto constrain the background prediction and determine the possible signal contribution.Systematic uncertainties are considered and incorporated as nuisance parameters in the fit.A set of validation regions is defined to assess the robustness of the extrapolation on thebackground prediction from the control regions to the signal regions.This paper is organised as follows. The signal models are introduced in section 2. A briefdescription of the ATLAS detector is given in section 3. The data and the simulated samplesused in the analysis are described in section 4. The algorithms used for the reconstructionand identification of the final-state particles are summarised in section 5. The selectioncriteria for the events considered in the analysis and the control, validation and signal regiondefinitions are described in section 6. An introduction to the XGBoost classifier, used toseparate the background from the signal and to define the signal regions, is also given inthis section. The experimental and systematic uncertainties, summarised in section 7, areaccounted for in the statistical interpretation of data. The results are presented in section 8.Conclusions are given in section 9.2 Signal phenomenologyThis section contains the description of the models considered in this paper. Details ofthe model predicting DM production in association with a single top quark are given insection 2.1. The production of a singlet vector-like T quark model is presented in section 2.2.– 3 –JHEP05(2024)263uχχ¯ qq¯′bugW+tV(a)u Vχχ¯qq¯′btgtW+(b) (c)Figure 1. Representative Feynman diagrams for the DM production in association with a singletop-quark decaying hadronically in the (a,b) vector mediator (non-resonant) and (c) scalar mediator(resonant) cases.2.1 Dark Matter production in association with top quarksThe DM production in association with top quarks is considered for a scalar or a vectorDM mediator particle [5, 6, 80, 81].The vector-mediated production, also referred to in the literature as non-resonant, consistsof an FCNC interaction producing a top quark and a new vector particle V decaying intoa pair of invisible DM particles, as shown in the diagrams in figures 1(a) and 1(b). Thisprocess is described by the following Lagrangian [5, 6, 80, 81]:L = aVµu¯γµPRt+ gχVµχ¯γµχ+ h.c., (2.1)where the massive vector boson V is coupled to the DM particles χ. The strength ofthis coupling is controlled by the parameter gχ, while the PR operator is the right-handedchirality projector. The parameter a stands for the coupling constant of the vector bosonV to the top-quark t and up-type quarks u, and γµ are the Dirac matrices.The scalar-mediated case, also referred to as resonant, corresponds to the production of acoloured 2/3e-charged scalar ϕ that decays into a top quark and a spin-1/2 DM particle χ [80].A representative Feynman diagram of this process is shown in figure 1(c). The Lagrangianthat describes this process is the following [5, 6, 80, 81]:L = λqϕd¯cPRs+ yχϕt¯PRχ+ h.c., (2.2)where λq is the coupling strength of the ϕ scalar with d- and s-quarks, yχ is the couplingstrength of the scalar ϕ with the DM particle χ and the top quark, and the superscriptc stands for the charge conjugate.2.2 Production of a single vector-like T quarkThe production of a single vector-like T quark can occur via WTb and ZTt vertices. However,the contribution via ZTt vertex is highly suppressed by the requirement of a top quark inthe initial state. Therefore, this paper considers only WTb production of the vector-like Tquark. The dominant process in the WTb associated mode is the resonant production. Thenon-resonant production is also considered. Vector-like T quarks decay into Wb, tZ andtH with a branching ratio that depends on the considered model [9, 10, 82]. The respectivediagrams are shown in figure 2.– 4 –JHEP05(2024)263νν¯tTb¯bWqq′gZbW+qq¯′(a)νν¯t¯Tb¯bWqq′gZtW−qq¯′(b)Figure 2. Representative Feynman diagrams for the (a) resonant and (b) non-resonant production ofa single vector-like T quark.The mass of the T quark, mT , and the overall coupling factor, κT , to the SM W boson,Z boson, and Higgs boson are unknown parameters [10, 11]. The overall coupling factorcontrols both the production cross-section and the resonance width of the T quark, ΓT . Fora vector-like T quark with mass mT , the relative width (ΓT /mT ) of the VLQ resonancescales quadratically with both κT and mT [11]. There are also three additional parameters,ξW , ξZ and ξH , which determine the T -quark branching ratios to each of the SM bosons —B(T → Wb), B(T → tZ) and B(T → tH), respectively. The relation ξW + ξZ + ξH = 1 isassumed, with ξZ = ξH . Consequently, any value of ξW fully determines the value of ξZ andthe branching ratio of the T → tZ decay, targeted by the analysis. Since the ξW < 0.5 regionis dominated by the suppressed ZTt production vertex, only the ξW > 0.5 space is explored.In case of a T → tZ decay, with a subsequent decay of the Z boson into a pair of neutrinos,the event would have the mono-top signature. Differently from the production of the top quarkin association with DM particles, the single vector-like T quark production expects additionalquarks in the final state, featuring at least one jet emitted at a small angle to the beam line.3 ATLAS detectorThe ATLAS detector [83] at the LHC covers nearly the entire solid angle around the collisionpoint.1 It consists of an inner tracking detector surrounded by a thin superconductingsolenoid, electromagnetic and hadronic calorimeters, and a muon spectrometer incorporatingthree large superconducting air-core toroidal magnets.The inner-detector system (ID) is immersed in a 2T axial magnetic field and providescharged-particle tracking in the range |η| < 2.5. The high-granularity silicon pixel detectorcovers the vertex region and typically provides four measurements per track, the first hitgenerally being in the insertable B-layer (IBL) installed before Run 2 [84, 85]. It is followed1ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP) in thecentre of the detector and the z-axis along the beam pipe. The x-axis points from the IP to the centre ofthe LHC ring, and the y-axis points upwards. Cylindrical coordinates (r, ϕ) are used in the transverse plane,ϕ being the azimuthal angle around the z-axis. The pseudorapidity is defined in terms of the polar angle θas η = − ln tan(θ/2). Rapidity is defined as y = 0.5 ln [(E + pz)/E − pz)], where E denotes the energy andpz is the component of the momentum along the beam direction. Angular distance is measured in units of∆R ≡√(∆η)2 + (∆ϕ)2.– 5 –JHEP05(2024)263by the SemiConductor Tracker (SCT), which usually provides eight measurements per track.These silicon detectors are complemented by the transition radiation tracker (TRT), whichenables radially extended track reconstruction up to |η| = 2.0. The TRT also provideselectron identification information based on the fraction of hits (typically 30 in total) above ahigher energy-deposit threshold corresponding to transition radiation.The calorimeter system covers the pseudorapidity range |η| < 4.9. Within the region|η| < 3.2, electromagnetic calorimetry is provided by barrel and endcap high-granularitylead/liquid-argon (LAr) calorimeters, with an additional thin LAr presampler covering|η| < 1.8 to correct for energy loss in material upstream of the calorimeters. Hadroniccalorimetry is provided by the steel/scintillator-tile calorimeter, segmented into three barrelstructures within |η| < 1.7, and two copper/LAr hadronic endcap calorimeters. The solidangle coverage is completed with forward copper/LAr and tungsten/LAr calorimeter modulesoptimised for electromagnetic and hadronic energy measurements respectively.The muon spectrometer (MS) comprises separate trigger and high-precision trackingchambers measuring the deflection of muons in a magnetic field generated by the supercon-ducting air-core toroidal magnets. The field integral of the toroids ranges between 2.0 and6.0Tm across most of the detector. Three layers of precision chambers, each consisting oflayers of monitored drift tubes, cover the region |η| < 2.7, complemented by cathode-stripchambers in the forward region, where the background is highest. The muon trigger systemcovers the range |η| < 2.4 with resistive-plate chambers in the barrel, and thin-gap chambersin the endcap regions.The luminosity is measured mainly by the LUCID-2 [86] detector that records Cherenkovlight produced in the quartz windows of photomultipliers located close to the beampipe.Events are selected by the first-level trigger system implemented in custom hardware,followed by selections made by algorithms implemented in software in the high-level trigger [87].The first-level trigger accepts events from the 40MHz bunch crossings at a rate below 100 kHz,which the high-level trigger further reduces in order to record complete events to disk atabout 1 kHz.A software suite [88] is used in data simulation, in the reconstruction and analysis ofreal and simulated data, in detector operations, and in the trigger and data acquisitionsystems of the experiment.4 Data and simulated samplesThis analysis uses data from pp collisions at a centre-of-mass energy of√s = 13 TeV collectedby the ATLAS detector during the LHC Run 2 from 2015 to 2018. In this data takingperiod, the LHC operated with 25 ns proton bunch spacing with an average number ofcollisions per bunch crossing ⟨µ⟩ of 34. Only data-taking periods in which all the necessarycomponents for the analysis were functional are included, corresponding to an integratedluminosity of 139 fb−1.Events are required to pass at least one of the triggers that select events with high missingtransverse momentum, with thresholds between 90 and 120 GeV depending on the datataking year [89]. All the triggers are fully efficient for events with offline EmissT > 250 GeV,as selected for analysis.– 6 –JHEP05(2024)263Samples of simulated signal and background processes are produced using different MonteCarlo (MC) event generators including parton shower and hadronisation models.Signal events for both the scalar and vector mediator DM scenarios are generated withthe simplified model described in section 2, using MadGraph5_aMC@NLO v2.8.1 andv2.9.5 [90] with FeynRules 2.0 [91]. The generation is done at leading-order (LO) accuracyin QCD using the NNPDF3.0LO parton distribution function (PDF) set [92]. The generatoris interfaced with Pythia8.245 [93] using the A14 set of tuned parameters (tune) [94] andthe NNPDF2.3LO PDF set [95].A total number of 40 (19) samples are simulated to cover the four dimensions in theparameter space — two couplings plus two masses — of the scalar (vector) mediator DMproduction. The larger number of simulations of the scalar mediator DM production is dueto the non-negligible dependence of the event kinematics on mϕ and λq that required theproduction of more samples to properly control and validate the signal predictions. The scalarDM samples were simulated in a grid of the parameter space encompassed by the followingranges: mϕ ∈ [2500, 6000] GeV, mχ ∈ [500, 5500] GeV, λq ∈ [0.2, 1] and yχ ∈ [0.2, 0.6]. Forthe vector-mediated signals, samples were simulated with the following parameter range:mV ∈ [1250, 3500] GeV, mχ ∈ [400, 1200] GeV, a ∈ [0.1, 0.5] and gχ ∈ [0.2, 1]. The parametersof the DM mediators and the VLQ signals are chosen to scan masses higher than the previousexcluded limits [39].The signal predictions in points of the parameter space that are not simulated areobtained through a reweighting procedure that exploits the mild dependence of the eventkinematics on the other parameters. The reweighting procedure consists of assigning weightsto the available simulated samples (called reference) to reproduce the expected kinematics andyields in a different (but close) point of the model parameter space, the target. This methodmakes use of an extensive set of samples simulated at particle-level that cover the four modelparameteres for both the scalar and vector mediator DM production with a higher granularitythan the set of reconstruction-level samples. The mentioned weights wrw, evaluated entirelywith particle-level simulations, reproduce the target kinematics from the reference sample.They take into account the differences in acceptance, cross-sections at LO and kinematicshapes between the reference and target samples, as summarised in the equation:wirw =Acceptance︷ ︸︸ ︷ϵtargetϵreference×Cross-section︷ ︸︸ ︷σtargetσreference×Shapes︷ ︸︸ ︷yitargetyireference. (4.1)The acceptance term is determined by applying the event preselection, defined in section 6,on particle-level simulation.2 It is measured as the ratio of the preselection efficiencies for thetarget sample (ϵtarget) and the reference sample (ϵreference). The change in the cross-sectionbetween the target (σtarget) and the reference (σreference) is accounted for by the ratio of thetwo values. The change in event kinematics is estimated with the ratio of the yields of thenormalised binned EmissT distribution for the reference (yireference) and target (yitarget) samples,2Particle-level objects in Monte Carlo simulation are reconstructed from stable particles (with properlifetimes cτ ≥ 10 mm). Particle-level jets are clustered from visible stable final-state particles, excludingprompt leptons, using the anti-kt clustering. Particle-level top jets are reconstructed using the anti-kt algorithmwith radius parameter R = 1.0 and are required to be close to a top-quark (∆R < 1).– 7 –JHEP05(2024)263where i is the bin corresponding to the truth EmissT (see section 5) of the reference and targetevents. The reweighting based on the EmissT observable has shown to be enough to accuratelyreproduce the distributions of the other kinematic variables relevant to the analysis.The single production of a singlet vector-like T quark is simulated at LO inQCD using the corresponding model [11] implemented in FeynRules 2.0 with Mad-Graph5_aMC@NLO v.2.8.1 using the NNPDF3.0LO PDF set. The simulation comprisesall the tree-level processes, including the non-resonant production. The generator is interfacedwith Pythia 8.244 using the NNPDF2.3LO PDF set with the A14 tune. The samples aregenerated for masses of the vector-like T quark ranging from 1.1 to 2.7 TeV in steps of 0.2 TeV,assuming κT = 0.5. Internal weights provided by MadGraph5_aMC@NLO are used toobtain predictions at masses 100 GeV smaller than the generated ones and at different valuesof the coupling, ranging from 0.1 to 1.6 in steps of 0.05 for κT < 0.5 and 0.1 for larger κT .The mass of the vector-like quark, mT , strongly affects the boost of the top quark, while small,but non-negligible, changes of the event kinematics are observed for different values of theκT coupling. Signal samples are normalised to next-to-leading-order (NLO) cross-sections inQCD that assume the narrow-width approximation for the T -quark decay [96]. Finite-widtheffects on the cross-sections are accounted for by applying a correction factor [97], rangingfrom a few per cent up to approximately 30% at large values of the width.The production of a top-antitop-quark pair (tt¯) is simulated at NLO usingPowhegBox v2 [98–100], with the NNPDF3.0NNLO PDF set, interfaced with Pythia 8.210using NNPDF2.3LO PDF set and the A14 set of tuned parameters. The events are normalisedto the next-to-next-to-leading-order (NNLO) QCD cross-section, including resummation ofsoft gluon emissions at next-to-next-to-leading logarithmic (NNLL) accuracy calculated usingthe Top++2.0 [101] software.The production of a vector boson (V = W,Z) in association with jets (V+jets) issimulated with the Sherpa v2.2.1 [102] generator in which the matrix element is accurate atNLO up to two emitted partons while at LO up to four additional partons. These calculationsare performed with the Comix [103] and OpenLoops [104] libraries. The matching ofthe parton-shower and hadronisation algorithm with the matrix-element generator [105] isemployed for different jet multiplicities, which are then merged into an inclusive sampleusing an improved CKKW matching procedure [106, 107] that is extended to NLO accuracyusing the MEPS@NLO prescription [108] via a set of parameters provided by the authors.The NNPDF3.0NNLO PDF set is used [92]. Both processes are normalised to the NNLOcross-section [109].Single-top tW production is simulated using the PowhegBox v2 generator at NLOin QCD using the five-flavour scheme and the NNPDF3.0NNLO PDF set. The diagramremoval scheme [110] is used to remove the overlap with tt¯ production. Single-top t-channelproduction is modelled with PowhegBox v2 generator at NLO in QCD using the four-flavour scheme. The NNPDF3.0NLOnf4 PDF set is used. Single-top s-channel production issimulated using the PowhegBox v2 generator at NLO in QCD using the five-flavour scheme.The NNPDF3.0NNLO PDF set is used. In all the single-top-quark processes, the generator isinterfaced with Pythia 8.230 using the A14 tune and the NNPDF2.3LO PDF set. Simulatedsamples are normalised to the NLO cross-section in QCD including the resummation ofsoft-gluon emission corrections [111–116].– 8 –JHEP05(2024)263The production of tt¯ in association with a W or Z boson is simulated with Mad-Graph5_aMC@NLO v2.3.3 [117] at NLO QCD accuracy using the NNPDF3.0NNLO PDFset. The generator is interfaced with Pythia 8.230 using the A14 tune and the NNPDF2.3LOPDF set. The samples are normalised to NLO QCD and electroweak (EW) cross-sections.The tt¯Z cross-section is additionally corrected by Z boson off-shell contributions.Events from tt¯H production are simulated at NLO QCD accuracy with PowhegBox v2generator with the NNPDF3.0NNLO PDF set. The generator is interfaced with Pythia 8.230using the A14 tune and the NNPDF2.3LO PDF set. The cross-section is calculated at NLOQCD and NLO EW accuracy.Diboson events are simulated with the Sherpa v2.2.1 generator, using the same prescrip-tion as in the production of single bosons in association with jets.The production of tZq is simulated with MadGraph5_aMC@NLO v2.3.3 at NLOQCD accuracy using the NNPDF3.0NNLO PDF set. The production of tWZ with Z →νν¯ is simulated at NLO QCD accuracy with MadGraph5_aMC@NLO v2.6.7 using theNNPDF2.3LO PDF.The simulation of bottom and charm hadron decays is done using EvtGen [118] in allsignal samples and all background samples with the exception V+jets and dibosons (generatedwith Sherpa v2.2.1). The generation also includes the effect of multiple pp interactions perbunch crossing (pile-up), and the effect on the detector response due to interactions frombunch crossings before or after the one containing the hard interaction [119]. All thesimulated samples are processed with a detailed simulation of the ATLAS detector [120]using Geant4 [121].5 Event reconstruction and object selectionAll events are required to contain a primary vertex with at least two associated tracks withtransverse momentum pT > 0.5 GeV. The vertex with the highest∑p2T of the associatedtracks is taken as the hard-scatter primary vertex.Electron candidates are identified from high-quality inner-detector tracks matched tocalorimeter energy deposits consistent with an electromagnetic shower. The energy depositshave to form a cluster with transverse energy ET > 25 GeV and |η| < 2.47, and be outsidethe transition region 1.37 ≤ |η| ≤ 1.52 between the barrel and endcap calorimeters. A tightlikelihood-based requirement is used to reject fake-electron candidates [122]. Electrons arenot required to be isolated to maximise the rejection of background events when applyingthe lepton veto preselection described in the next section.Muon candidates are reconstructed using high-quality inner-detector tracks combined withtracks reconstructed in the muon spectrometer. Only muon candidates satisfying ‘medium’identification criteria [123], with pT > 25 GeV and |η| < 2.5, are considered. No isolationcriteria are applied to improve the background rejection with the lepton veto (see section 6).Jet candidates are reconstructed using the anti-kt [124] jet algorithm with radius param-eter R = 0.4 (1.0) for small-R (large-R) jets, as implemented in the FastJet [125] package.The large-R jets are formed from topological clusters in the calorimeter calibrated usingthe local calibration method described in ref. [126], while the small-R jets are reconstructed– 9 –JHEP05(2024)263from particle-flow objects [127]. Both are calibrated by applying a jet energy scale derivedfrom 13 TeV data and simulation [128, 129].After calibration, small-R jets are considered if they fulfil pT > 25 GeV and |η| < 4.5.Jets in the region 2.5 < |η| < 4.5 are considered forward jets. To suppress jets originatingfrom pile-up collisions, a requirement on the jet-vertex tagger (JVT) [130] discriminant isapplied for jets with pT below 60 GeV and |η| < 2.4. Jets that are close to an electron with adistance ∆Ry,ϕ ≡√(∆y)2 + (∆ϕ)2 < 0.2 are removed to avoid double counting the energyof the electron. Jets with less than three tracks are removed if their distance to a muon is∆Ry,ϕ < 0.2 or one of their tracks is part of the muon. Electrons or muons with a distance∆Ry,ϕ < 0.4 from any of the remaining jets are removed.Small-R jets that contain b-hadrons (b-jets) are identified by the use of the DL1r multi-variate algorithm [131]. These jets are hereafter referred to as b-tagged jets. The selectedworking point results in an efficiency of 77% per b-jet and rejection factors of 6 and 200 for c-and light-flavour jets, respectively, as measured in simulated tt¯ events.A trimming algorithm [132] with parameters Rsub = 0.2 and fcut = 0.05 is applied to thelarge-R jets to mitigate the impact of gluon radiation and pileup effects. Trimmed large-R jetsare considered if they fulfil pT > 250 GeV and |η| < 2.0. To identify a large-R jet originatedfrom hadronically decaying top quarks produced with a large Lorentz boost (top-tagged), thecontained (similar to medium) top-quark tagging algorithm is used [133, 134]. The top-quarktagging relies on a deep neural network (DNN) that uses jet kinematics and substructurevariables (e.g., energy flow) as inputs [133, 134]. The pT-dependent requirements on theDNN score provide 50% top-quark-tagging efficiency, as measured in inclusive tt¯ events wherethe top-quark decay products are considered to be contained within the large-R jet, and acorresponding background rejection up to 70 (95) for multijet (γ+jets) events dependingon the jet pT [133, 134].The missing transverse momentum vector pmissT is reconstructed from the negative vectorsum of momenta of calibrated leptons, small-R jets and a soft term built from all tracks thatare associated with the primary vertex but not with these objects [135]. Its magnitude isdenoted by EmissT . The truth EmissT used in the reweighting procedure described in section 4is calculated from the truth pT of invisible particles.6 Event selection and background estimateThe experimental signature expected in the considered DM and vector-like T -quark models isthe presence of a top quark and significant missing transverse momentum. As the top quarkis expected to be produced with a large Lorentz boost, its hadronic decay products can becollimated and reconstructed into a large-R jet. Preselected events are required to containzero leptons and at least one large-R jet. The leading large-R jet (J) is then required tobe top-tagged and have a pT between 350 GeV and 2500 GeV, and a mass between 40 GeVand 600 GeV, corresponding to the region where the top-tagging algorithm is calibrated. Toreduce the number of multijet background events to a negligible level, the EmissT is requiredto be larger than 250 GeV. Quality criteria are imposed to reject events that contain anyjets arising from non-collision sources or detector noise [136]. To remove the contribution– 10 –JHEP05(2024)263Nb-tagged jets ∆ϕmin(j, EmissT ) XGBoost score Nforward jetsTCR ≥ 2 ∈ [0.2, 1] — —TVR1bLPhi 1 ∈ [0.2, 1] — —TVR1bHPhi (1f) 1 ≥ 1 < 0.5 — (≥ 1)TVR2bHPhi ≥ 2 ≥ 1 — —VCR 0 ∈ [0.2, 1] — —VVR (1f) 0 ≥ 1 < 0.5 — (≥ 1)SR0b (1f) 0 ≥ 1 ≥ 0.5 — (≥ 1)SR1b (1f) 1 ≥ 1 ≥ 0.5 — (≥ 1)Table 1. Summary of the event selections used to define the signal, control and validation regions.The signal regions are denoted by SR0b and SR1b, the tt¯ (V+jets) dominated control regions aredenoted by TCR (VCR) and the validation regions enhanced in tt¯ (V+jets) are labelled as TVR1bLPhi,TVR1bHPhi and TVR2bHPhi (VVR). The “(1f)” notation in the signal and validation region rowsindicates the additional requirement of at least one forward jet in the event, which is applied for thesearch of a single vector-like T quark. All regions are required in addition to contain zero leptons in thefinal state, EmissT ≥ 250 GeV and at least one top-tagged large-R jets with pT ∈ [350, 2500] GeV and amass ∈ [40, 600] GeV. The number of b-tagged (forward) jets required is indicated by Nb-tagged jets(Nforward-jets). The symbol - indicates that no requirement on the variable is applied.from mis-reconstructed EmissT aligned to badly reconstructed jets, the minimum distance inthe transverse plane between any reconstructed small-R jet (j) and the missing transversemomentum, ∆ϕmin(j, EmissT ), is required to be larger than 0.2.Additional requirements are used to define several orthogonal regions: signal regions(SRs) optimised to maximise the sensitivity to the target signal models; control regions (CRs)designed to measure the normalisation of the main contributing background processes; andvalidation regions (VRs) to check the background modelling in regions kinematically closerto the signal regions. The control and validation regions are defined to have a negligiblesignal contribution. The requirements that define the analysis regions are listed in table 1,sketched in figure 3 and described as follows.6.1 Signal region definitionDifferent SRs are defined for the three signal scenarios considered to maximise the analysissensitivity to each model. Each signal region is defined by the output score of an XGBoostclassifier [79] specifically trained to improve the sensitivity to each signal.The XGBoost algorithm [79] combines several input observables into an extreme gradientBDT. Gradient boosting improves over a single decision tree classifier by combining a numberof classifiers iteratively enhanced. Three XGBoost classifiers are trained separately withpreselected simulated background and signal events for each considered model — scalar andvector DM, and VLQ. In the training of the classifier targeting the separation of eventsfrom scalar (vector) mediator DM production, the simulated sample with a mediator massof mϕ = 4 TeV (mV = 1.75 TeV) is used, corresponding to an intermediate value of the– 11 –JHEP05(2024)263Figure 3. Schematic representation of the control, validation and signal regions. Regions are definedin terms of b-tagged jet multiplicity Nb-tagged jets and the minimum distance in the azimuthal anglebetween a jet and EmissT ∆ϕmin(j, EmissT ). The notation “XGB<0.5” and “XGB>0.5” indicates therequirement on the XGBoost score of the validation and signal regions, respectively. These regionsare schematically separated by the curly vertical line. The “1f” label stands for requiring at least oneforward jet in the event. The selections used to define the regions are described in the text and in table 1.explored masses. The classifier targeting the identification of single vector-like T productionis trained using a set of samples with mT ranging from 1.5 to 1.9 TeV. This choice providesstable performances for larger masses while for lower masses, which are mostly excludedalready, some degradation is observed.The hyperparameters of each XGBoost model are optimised to maximise the integralunder the receiver operating characteristic curve. Similarly, the set of variables used in thetraining of the classifier, listed in table 2, are selected based on their discrimination power, andgood data and simulation agreement. The training of the XGBoost classifier targeting theDM scalar production required fewer input variables, as signal events are mostly characterisedby large EmissT values, of the order of the mediator mass. For the remaining signal models, thekinematic properties of signal events are more similar to those from background processes, andtherefore more input features are required for the event classification. The EmissT is the mostdiscriminating variable for all considered models, as it is expected to be significantly largerthan for background events. The reconstructed transverse mass of the system composed ofthe EmissT and the closest b-tagged jet plays an important role in the discrimination against tt¯events with a top quark decaying leptonically, for which the distribution is expected to peak ataround the top-quark mass. Variables based on angular distances of the reconstructed objectsand energy balance between EmissT and the jets (e.g., Ω) also help in the event classification.For signal events, the top quark is expected to recoil against the missing transversemomentum, thus the requirement of ∆ϕmin(j, EmissT )> 1 is applied. This requirement rejects– 12 –JHEP05(2024)263Variable Description Scalar Vector VLQDM mediator DM mediatorEmissT Missing transverse momentum Ω EmissT and large-R jet pT balance:EmissT −pT(J)EmissT +pT(J) Njets Small-R jet multiplicity ∆Rmax Maximum ∆R between two small-R jets mT,min(EmissT , b-tagged jet) Transverse mass of EmissT and the closest b-tagged jet mtop-tagged jet Mass of the large-R top-tagged jet ∆pT (J , jets)Scalar difference of large-R jet pT and the sumof pT of all small-R jets. HT Sum of all small-R jet pT HT/EmissT Ratio of HT and EmissT ∆E(EmissT , J) Energy difference between EmissT and the large-R jet ∆ϕ(EmissT , J)Angular distance in the transverse plane betweenEmissT and large-R jet pT(J) Large-R jet pT mT(EmissT , J) Transverse mass of the EmissT and large-R jet ∆ϕ(b-tagged jet, J) Angular distance in the transverse plane between thelarge-R jet and the leading b-tagged jet Table 2. List of variables used in the training of the XGBoost classifier for the scalar and vectorDM mediator, and VLQ models. The symbol indicates that the corresponding variable is includedin the training.tt¯ events with a boosted top quark decaying hadronically and recoiling against a b-jet fromthe leptonic decay of the other top quark. The signal regions for a given model are definedby requiring the corresponding XGBoost score to be larger than 0.5. The resulting eventsare separated into two orthogonal signal regions (SR0b,SR1b) by applying criteria based onb-tagged jet multiplicity (see figure 3). The SR1b (SR0b) signal region must contain exactlyone (zero) b-tagged jet. Signal events are expected to have one b-jet from the top-quark decayin the final state, but the SR0b is expected to account for b-tagging inefficiencies. The signalefficiencies of the SRs targeting each DM model depend on the specific signal parameters andare within 14%–27% and 3%–9% for the scalar and vector DM, respectively.The signal regions targeting the search for the vector-like T quark production requireadditionally at least one forward jet since final states with jets at a small angle relative tothe beam pipe are expected. The VLQ signal selection efficiency in these SRs is 1%–2%depending on the model parameters.In summary, the analysis employs six distinct regions to target the three signal modelswith two SRs each: SR0b and SR1b region for the DM scalar search, SR0b and SR1b regionfor the DM vector, and SR0b 1f and SR1b 1f targeting single vector-like T -quarks.– 13 –JHEP05(2024)2636.2 Background estimateDedicated control regions enriched in the dominant background processes are defined toconstrain their normalisation to data in a profile-likelihood fit described in section 8, whilethe shape distributions are taken from simulation. The rest of the background processesare estimated completely from the simulation.The main contributing background sources to the signal region are tt¯ and V+jetsproduction. The former represents approximately 65% of the background events in SR1b,consistent across all the defined signal regions with one b-tagged jet requirement. The othermain sources of background in this region are V+jets (20%) and single top (10%), consistingmostly of tW production. The SR0b is dominated by V+jets production (up to 85%) across allthe inspected models, with minor contributions from diboson production (10%) and tt¯ (< 8%).Control regions enhanced in the dominant tt¯ and V+jets backgrounds are then definedby requiring 0.2 < ∆ϕmin(j, EmissT ) < 1 to reduce the signal contribution below 5% for all theconsidered models. The tt¯ control region (referred to as TCR) is defined by requiring, inaddition, at least two b-tagged jets. This region is enriched in tt¯ production with at least onetop quark decaying into leptons that are not reconstructed. This provides a significant sourceof EmissT recoiling against the top quark, similar to what is found in the SR1b region, wherethis source of background is dominant. The control region enriched in V+jets (referred to asVCR) requires zero b-tagged jets in the final state. In this region, the fractions of W+jetsprocesses in which the W boson decays into τ -leptons, and of Z+jets processes with the Zboson decaying into neutrinos, both leading to a hadronic final state with significant EmissT ,are similar to those expected in the SR0b signal region.Validation regions are defined to check the modelling of the main background processesin regions kinematically closer to the signal regions, maintaining low signal contamination (<10%). The tt¯ modelling is checked in three validation regions, approaching the SR1b from twodifferent paths in the plane shown in figure 3. The TVR2bHPhi region extends the TCR (withat least two b-tagged jets) to higher values of ∆ϕmin(j, EmissT ), by requiring ∆ϕmin(j, EmissT ) > 1.The TVR1bLPhi region is defined with events fulfilling 0.2 < ∆ϕmin(j, EmissT ) < 1 but with asingle b-tagged jet in the final state to validate the tt¯ modelling with a reduced fraction ofadditional jets originated from heavy flavour quarks, as in SR1b. Events in these two regionsare not required to fulfil any requirement in the XGBoost score. Finally, the TVR1bHPhiregion extends the TVR1bLPhi to ∆ϕmin(j, EmissT ) > 1, but XGBoost score < 0.5 is requiredto not overlap with SR1b. The V+jets modelling is tested in the VVR region, which requiresno b-tagged jets in the final state, ∆ϕmin(j, EmissT ) > 1 and XGBoost score < 0.5 to ensureorthogonality with the SR0b. Two specific validation regions for the search targeting thevector-like T quark production are defined by adding the requirement of at least one forwardjet in the final state to the selections that define the VVR and TVR1bHPhi, called VVR1fand TVR1bHPhi1f, respectively.7 Systematic uncertaintiesSystematic uncertainties of theoretical and instrumental sources affect the predictions ofbackground and signal in the analysis regions. The effect of these uncertainties is included in– 14 –JHEP05(2024)263the likelihood fit as additional nuisance parameters (NP) that are measured simultaneouslywith the normalisations of the main background processes and the signal strength.Several sources of instrumental uncertainties are considered. These include systematicuncertainties in the online event selection efficiency using the high-EmissT trigger, and also inthe reconstruction and calibration of the objects analysed. Moreover, the normalisation ofthe simulated samples to the integrated luminosity collected in Run 2 has an uncertainty of1.7% [137], obtained using the LUCID-2 detector [86] for the primary luminosity measurements.Among all the detector-related uncertainties, the most significant arise from the measurementsof jet properties and tagging efficiencies.Uncertainties associated with jets are due to the jet energy scale (JES) and jet energyresolution (JER) [128, 129]. For large-R jets, uncertainties arising from the jet mass scale(JMS), and jet mass resolution (JMR) are also considered. They are derived from observationsof the W boson and top-quark masses in semileptonic tt¯ events and by a double-ratio methodthat compares the calorimeter-to-tracker response ratio between data and simulation [128]. Forsmall-R jets, additional uncertainties related to the JVT requirement are also evaluated, arisingfrom the correction factors used to match the efficiencies in the MC samples to data [130].The b-quark tagging efficiencies in simulation, and the charm and light jet mistag rates,are corrected to match the efficiencies in data [138–140]. The efficiency for tagging b-jetsis measured in data using tt¯ events [138]. Uncertainties arising in the evaluation of theefficiencies are propagated to the correction factors.The efficiency and rejection power of the DNN top-quark tagger is measured in dataand correction factors are applied to MC events to match the measured efficiencies [134].These corrections take into account the correlations between the tagging efficiencies andother jet observables such as the jet energy and mass. The uncertainties in these correctionsare treated as systematic uncertainties.A set of uncertainties that parametrise the lack of knowledge on the background predictionof theoretical nature are considered. These uncertainties are evaluated either from variationsof parameter settings in the event generation or from a direct comparison to alternativesimulated samples.Uncertainties in the modelling of the tt¯ background come from the choice of NLO-matchingmethod, the parton shower and hadronisation modelling, the amount of additional gluonradiation, missing higher orders in the generation and the choice of PDF. The NLO-matchinguncertainty is estimated by a direct comparison of the tt¯ simulation with an alternativesample using MadGraph5_aMC@NLO. Similarly, the uncertainty in the parton showerand hadronisation model is estimated from an alternative sample using Herwig7.1 [141]. Theuncertainty associated with the effects of missing QCD higher orders is estimated by inde-pendently varying the renormalisation and factorisation scales by factors of 2.0 and 0.5. Theimpact of initial-state radiation (ISR) is estimated by varying αs in the A14 tune. Similarly,the uncertainty related to final-state radiation (FSR) is assessed by varying the renormalisationscale for the final-state radiation by a factor of 2.0 and 0.5 in the parton shower algorithm.The uncertainties in the modelling of additional gluon radiation and missing higherorders are also estimated for all single-top processes using the same procedure as in the tt¯background. The corresponding NPs are treated as uncorrelated among single-top and tt¯– 15 –JHEP05(2024)263processes. The choice of the scheme to account for the interference between tW and tt¯ isanother source of uncertainty in the background prediction and is estimated by comparingpredictions using diagram removal and diagram subtraction schemes [110].Uncertainties in the modelling of weak boson production in association with jets, W+jetsand Z+jets, arise from missing higher orders in perturbation theory, resummation of thegluon radiation, matching of the parton shower, modelling of heavy-flavour quark productionand the choice of PDF. The effect of the modelling uncertainties in W+jets and Z+jets aretreated as uncorrelated NPs in the profile likelihood fit. The uncertainty due to missing QCDhigher orders is estimated by independently varying the renormalisation and factorisationscales by a factor of two and taking the largest observed deviation from the nominal prediction.A similar procedure is used to assess the uncertainties associated to the resummation ofgluon radiation and matching with the parton shower, as they are estimated by varying by afactor of two the corresponding scales. Two normalisation uncertainties of 30% are assignedto V+jets events with b-jets and c-jets, respectively, to cover possible discrepancies fromsimulations in case of heavy-flavour production [142]. The presence of b-jet (c-jets) in thefinal state is determined by the presence of B-hadrons (D-hadrons) in the truth record ofthe simulated events, which are associated with reconstructed jets. The same procedure isused to estimate the modelling uncertainties in the generation of diboson production (exceptfor the resummation and parton shower matching uncertainties).Uncertainties due to the PDF choice in the simulations on tt¯, V+jets, single-top and dibo-son production simulations are estimated by following the PDF4LHC [143] recommendation.Uncertainties in the cross-sections of the background processes whose normalisationsare not measured in the control regions are also included. These background processesare single-top [144–146], diboson [147] and tt¯+X [148, 149]. The respective uncertaintiesare 5%, 6% and 15%.Uncertainties in the signal prediction from the scalar and vector DM mediator productionsare also considered. Missing higher-order QCD corrections are estimated by varying therenormalisation and factorisation scale by a factor of 0.5 and 2 relative to the value used in thebaseline simulation. When the signal prediction is obtained with the reweighting procedure,two additional sources of uncertainty are considered. The first is a shape uncertainty, estimatedby comparing the normalised XGBoost distributions at particle and reweighted level for thetarget point in the model parameter space. The second is a 10% normalisation uncertaintyestimated as the largest difference between the event yields at particle and reconstructionlevels for all the reference points.Representative values for the impact of the considered sources of uncertainties in thebackground processes in the signal regions are shown in table 3. Generally, the dominantuncertainties in the background prediction consist of modelling uncertainties. The mostimportant instrumental uncertainties are related to large-R jet momentum and mass cali-bration, which significantly impacts the V+jets background expectation, and to top-taggingcalibration, mostly affecting the tt¯ prediction.– 16 –JHEP05(2024)263tt¯ Z+jets W+jets tW Diboson tt¯VSR0b SR1b SR0b SR1b SR0b SR1b SR0b SR1b SR0b SR1b SR0b SR1bb-tagging efficiency 5 < 1 < 1 2 < 1 2 5 < 1 < 1 3 6 1Jet calibration 50 7 15 30 18 13 50 13 13 20 40 12EmissT calibration 3 < 1 2 6 1 < 1 2 1 < 1 2 4 1Top-tagging efficiency 13 14 5 6 5 6 13 14 11 11 13 13Other instrumental 3 2 2 2 3 3 5 3 3 4 5 3Modelling 30 23 23 33 20 30 65 45 10 35 15 15Table 3. Values of the relative post-fit uncertainty (in %) on the background prediction in thesignal regions SR0b and SR1b for the different sources of systematic uncertainties. The category “jetcalibration” includes all the sources of uncertainty related to the reconstruction and calibration ofsmall- and large-R jets. The quoted values are obtained by averaging the post-fit uncertainties of thethree fits performed assuming the background-only hypothesis, corresponding to signal regions andBDTs targeting the scalar and vector mediator DM signals and the vector-like T signal. The sum inquadrature of the individual uncertainties is not expected to be equal to the total background post-fituncertainty computed taking into account the correlations among the sources of uncertainties.8 ResultsFor each signal model, the presence of the signal in data is tested via a profile-likelihood fit tothe observed event yields in the control regions and to the corresponding XGBoost score dis-tribution in the signal regions. The binning is chosen as a compromise between the maximumseparation of the signal from the background and statistics of simulated background events.The likelihood function used to construct the test statistic consists of a product of Poissonprobabilities of the yields in each bin of the fitted distributions and constraint functions forNPs describing the systematic uncertainties. The impact of statistical uncertaities from thedata and MC simulation are parametrised by a Poisson distribution while the remaining un-certainties are parametrised by Gaussian distributions. Additionally, the normalisation factorsof V+jets (NFV+jets) and tt¯ (NFtt¯) background processes are included as unconstrained NPs.Only systematic uncertainties impacting the shape or the normalisation of the expectedbackground distribution for more than 1% are accounted for in the systematic model. Incase a systematic variation leads to significant bin-to-bin statistical fluctuations in theXGBoost score distribution in the signal regions, the shape of the systematic effect issmoothed. Systematic uncertainties that are estimated via a direct comparison of a singlevariation with the nominal prediction are symmetrised. Some systematic uncertainties that areevaluated via the comparison of two opposite variations with respect to the nominal prediction,may show both variations above or below the nominal expectation with at least one variationcompatible with the nominal prediction within the associated statistical uncertainty. In thiscase, the maximum distance from the nominal prediction is considered and symmetrised. Atest statistic based on a profile-likelihood ratio implemented in RooStats [150] is used forthe evaluation of confidence intervals and hypothesis testing. Exclusion limits are derivedwith the CLs frequentist method [151, 152] using the asymptotic approximation [153].The result of the fit under the background-only hypothesis leads to the determination ofthe normalisation factors for the main sources of background. The values obtained by the dif-– 17 –JHEP05(2024)2630 2 4 6 8 10ttNFV+jetsNF 0.22±0.85 0.21±0.83 0.20±0.82 0.18±0.92 0.15±0.82 0.15±0.70 Scalar Vector VLQATLASFigure 4. Comparison of the fitted normalisation factors of the tt¯ and V+jets background processesin the fits of data in control and signal regions under the background-only hypothesis. An independentfit is performed for each signal model, using the respective signal regions.300 400 500 600 700 800 900 1000 [GeV]missTE0.50.7511.25 Data / Bkg. 110210310410510EventsATLAS-1 = 13 TeV, 139 fbsMonotopTCRPost-FitData TopZ+jets W+jetsSingle top DibosonttV UncertaintyPre-Fit Bkg.(a)300 400 500 600 700 800 900 1000 [GeV]missTE0.50.7511.25 Data / Bkg. 110210310410EventsATLAS-1 = 13 TeV, 139 fbsMonotopVCRPost-FitData TopZ+jets W+jetsSingle top DibosonttV UncertaintyPre-Fit Bkg.(b)Figure 5. Comparison of data and SM prediction for the EmissT distribution in control regions targeting(a) tt¯ and (b) V+jets processes. The background predictions with the corresponding uncertaintiesresult from the simultaneous fit to data in control and signal regions under the background-onlyhypothesis (Post-Fit). The signal regions included in the fit correspond to those targeting the scalarDM mediator production. The dashed line indicates the pre-fit total background prediction. The lastbin of the distribution contains the overflow.ferent fits are shown in figure 4. They are consistent with unity within two standard deviations.The discrepancy observed in NFV+jets between the fits targeting DM and vector-like T signalsis explained by the different phase spaces of the corresponding signal regions (in particular dueto the requirement of at least one forward jet in the VLQ signal regions). The deviation fromthe unity of the normalisation factors is mainly related to the highly boosted regime exploredin this analysis with respect to the phase space in which the top-quark tagging calibration wasperformed. The good description of data in the control regions of the post-fit background modelis shown in figure 5 for the EmissT distribution. Despite that only the event yield informationis used as fit input for the CRs, a very good modelling of the EmissT distribution is observed.The extrapolation of the background model from the control region to the signal regionis tested in the validation regions. These regions are not included in the likelihood fitbut are used to validate the background expectation, obtained from the results of the fit– 18 –JHEP05(2024)263in the control and signal regions, in regions kinematically close to the signal phase space.Kinematical properties of tt¯ events are validated in adjacent regions to the tt¯ control regionand common to all considered models, namely TVR1bLPhi and TVR2bHPhi, shown infigures 6(a) and 6(b) for the EmissT distribution. The validation regions that are closest tothe signal regions are VVR and TVR1bHPhi, which only differ by the XGBoost scorerequirement with the SR0b and SR1b regions, respectively. A comparison of the observedand expected distribution for the XGBoost score variable is shown in figures 6(c) and 6(d),respectively. No significant mismodelling of data is observed in these regions, meaning thatthe lower tail of the XGBoost score distribution in Nb-tagged jets-∆ϕmin(j, EmissT ) phase spaceis well modelled. The agreement of the event yields in data with the background model in allthe validation regions considered in the analysis is shown in figure 7 for each signal modeltargeted. Since no significant discrepancy between data and the background expectationwas observed in any of the validation regions, no additional non-closure uncertainties areincluded in the systematic model of the profile-likelihood fit.The distribution of the XGBoost score in the signal regions for data and the fitted SMexpectation under the background-only hypothesis are shown in figure 8. No significant excessabove the SM expectation is found in any of the signal regions. The results are thereforeinterpreted in terms of expected and observed upper limits on the signal cross-section asa function of the model parameters.The upper limit on the signal cross-sections at 95% confidence level is shown in figure 9,together with the theoretical signal cross-section prediction for the considered benchmarks.The limit on the cross-section of the scalar-mediated DM production as a function of themediator mass mϕ is shown in figure 9(a). A degradation of the cross-section limit at high mϕmasses is observed, justified by a general decrease in the event selection efficiency. Assumingthe couplings λq = 0.6 and yχ = 0.4, and the mass of the DM candidate mχ = 1 GeV, themodel is excluded for masses of the mediator scalar particle mϕ < 4.3 TeV, improving thelimits with respect to the previous search with mono-top events by 800 GeV [39]. The limiton the cross-section of the vector-mediated DM production as a function of the mass of thevector particle mV is shown in figure 9(b). The predictions of the signal distribution for amass of the vector mediator mV different from 1.75 TeV are obtained using the weightingprocedure described in section 4. Assuming the couplings a = 0.5 and gX = 1, and themass of the DM candidate mχ = 1 GeV, the model is excluded for masses of the vectorparticle mV < 2.3 TeV, which corresponds to an 300 GeV improvement from the previousresult of the mono-top channel [39].The limit on the cross-section of the vector-like T quark production as a function ofits mass mT is shown in figure 9(c). Assuming the coupling κT = 0.5 and the branchingratio B(T → Zt) = 25%, the singlet model is excluded for mT < 1.8 TeV. This constitutesan improvement of 400 GeV in the excluded mass when comparing to the previous similaranalysis [39]. The cross-section limit is decreased by a factor 10, mainly due to improvedobject reconstruction algorithms, calibrations and event selection, the use of XGBoost forenhanced signal sensitivity and increased data statistics. This result is competitive withthe 1–2 TeV exclusion limits obtained analysing different final state events in searches forsingle vector-like T -quarks [67–77], as discussed in section 1.– 19 –JHEP05(2024)263300 400 500 600 700 800 900 1000 [GeV]missTE0.50.7511.25 Data / Bkg. 110210310410510EventsATLAS-1 = 13 TeV, 139 fbsMonotopTVR1bLPhiPost-FitData TopZ+jets W+jetsSingle top DibosonttV UncertaintyPre-Fit Bkg.(a)300 400 500 600 700 800 900 1000 [GeV]missTE0.50.7511.25 Data / Bkg. 110210310EventsATLAS-1 = 13 TeV, 139 fbsMonotopTVR2bHPhiPost-FitData TopZ+jets W+jetsSingle top DibosonttV UncertaintyPre-Fit Bkg.(b)0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5ScalarXGB0.50.7511.25 Data / Bkg. 110210310410EventsATLAS-1 = 13 TeV, 139 fbsMonotopVVR ScalarPost-FitData TopZ+jets W+jetsSingle top DibosonttV UncertaintyPre-Fit Bkg.(c)0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5ScalarXGB0.50.7511.25 Data / Bkg. 110210310410EventsATLAS-1 = 13 TeV, 139 fbsMonotopTVR1bHPhi ScalarPost-FitData TopZ+jets W+jetsSingle top DibosonttV UncertaintyPre-Fit Bkg.(d)Figure 6. Comparison of data and SM prediction in the validation regions. The EmissT distributionis shown in the tt¯ validation regions (a) TVR1bLPhi and (b) TVR2bHPhi. The XGBoost scoreis shown in the validation regions (c) VVR and (d) TVR1bHPhi, which are inclusive in forwardjet multiplicity. The background predictions with the corresponding uncertainties result from thesimultaneous fit to data in control and signal regions under the background-only hypothesis (Post-Fit).The signal regions included in the fit correspond to those targeting the scalar DM mediator production.The dashed line indicate the pre-fit total background prediction. The last bin of the distributions in(a) and (b) contains the overflow.Contours of the observed and expected upper limits in four dimensions of the parameterspace of the scalar and vector mediator DM models are produced using the set of simulationsand reweighting procedure developed for this analysis. These are shown in figures 10 and 11,respectively. The limit in the scalar mediator mass mϕ of the DM production appears tobe almost constant for different values of λq and yχ, except for very low values associatedwith tiny cross-sections, and all values of λq (yχ) are excluded for mϕ up to 3.4 (2.5) TeV,improving the results of the previous analysis. The mϕ limits are also constant in the (mϕ,mχ)plane, for the lower region of the DM candidate mass, and the mχ reach is 2.2 TeV. Thisanalysis is not sensitive to the region of the parameter space where (mϕ −mχ) < 500 GeV asit does not result in a boosted top-quark topology. For the vector DM mediator productionmodel, the exclusion limits obtained are improved with respect to the previous analysis, allvalues of gχ (a) are excluded for mV up to 1.1 (1.5) TeV, and the reach in mχ is improved– 20 –JHEP05(2024)263TVR1bLPhiTVR2bHPhiVVRScalarTVR1bHPhiScalar0.50.7511.25 Data / Bkg. 110210310410510EventsATLAS-1 = 13 TeV, 139 fbsMonotop (Scalar)Post-FitData Top Z+jetsW+jets Single top DibosonttV Uncertainty Pre-Fit Bkg.(a)TVR1bLPhiTVR2bHPhiVVRVectorTVR1bHPhiVector0.50.7511.25 Data / Bkg. 110210310410510EventsATLAS-1 = 13 TeV, 139 fbsMonotop (Vector)Post-FitData Top Z+jetsW+jets Single top DibosonttV Uncertainty Pre-Fit Bkg.(b)TVR1bLPhiTVR2bHPhiVVRVLQTVR1bHPhiVLQ0.50.7511.25 Data / Bkg. 110210310410510EventsATLAS-1 = 13 TeV, 139 fbsMonotop (VLQ)Post-FitData Top Z+jetsW+jets Single top DibosonttV Uncertainty Pre-Fit Bkg.(c)Figure 7. Comparison of data and SM predictions for the event yields in each validation regiondefined for the (a) DM scalar mediator, (b) DM vector mediator and (c) vector-like T search. Thebackground predictions with the corresponding uncertainties result from the simultaneous fit to datain control and signal regions under the background-only hypothesis (Post-Fit). The signal regionsincluded in each fit correspond to those targeting the respective signal model. The dashed line indicatethe pre-fit total background prediction.by approximately 100 GeV. These results are complementary to the ones obtained in asearch for same-charge top-quark pair production [34], providing sensitivity to lower valuesof the a coupling parameter.The two-dimensional exclusion contours in the plane (mT , κT ) of the single vector-like Tquark production, shown in figure 12, were similarly obtained using the internal weights ofthe generated signal samples. Figure 12(a) provides exclusion limits on κT and the T quarkmass, while figure 12(b) shows the exclusion limits on the signal cross-section normalisedto the theoretical value, derived also as a function of the mass and coupling. Masses of thevector-like T quark below 1.6 TeV are excluded for a value of the coupling κT > 0.4. ForκT > 0.5, the model is mostly excluded for masses mT < 1.8 TeV.The exclusion limits on the T quark mass can be given in a more generalised representationof the parameter space. Figure 13 displays the largest excluded mass as a function of therelative resonance width ΓT /mT and the relative coupling parameter ξW , which, as discussed– 21 –JHEP05(2024)2630.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1ScalarXGB0.50.7511.25 Data / Bkg. 110210310EventsATLAS-1 = 13 TeV, 139 fbsMonotopSR0b ScalarPost-FitData 5×Scalar Top Z+jetsW+jets Single topDiboson ttVUncertainty Pre-Fit Bkg.(a)0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1ScalarXGB0.50.7511.25 Data / Bkg. 110210310EventsATLAS-1 = 13 TeV, 139 fbsMonotopSR1b ScalarPost-FitData 5×Scalar Top Z+jetsW+jets Single topDiboson ttVUncertainty Pre-Fit Bkg.(b)0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1VectorXGB0.50.7511.25 Data / Bkg. 110210310410EventsATLAS-1 = 13 TeV, 139 fbsMonotopSR0b VectorPost-FitData 5×Vector Top Z+jetsW+jets Single topDiboson ttVUncertainty Pre-Fit Bkg.(c)0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1VectorXGB0.50.7511.25 Data / Bkg. 110210310410EventsATLAS-1 = 13 TeV, 139 fbsMonotopSR1b VectorPost-FitData 5×Vector Top Z+jetsW+jets Single topDiboson ttVUncertainty Pre-Fit Bkg.(d)0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1VLQXGB0.50.7511.25 Data / Bkg. 110210310EventsATLAS-1 = 13 TeV, 139 fbsMonotopSR0b1f VLQPost-FitData 5×VLQ Top Z+jetsW+jets Single topDiboson ttVUncertainty Pre-Fit Bkg.(e)0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1VLQXGB0.50.7511.25 Data / Bkg. 110210310EventsATLAS-1 = 13 TeV, 139 fbsMonotopSR1b1f VLQPost-FitData 5×VLQ Top Z+jetsW+jets Single topDiboson ttVUncertainty Pre-Fit Bkg.(f)Figure 8. Comparison of data and fitted expectation for the XGBoost score distribution in thesignal regions targeting the three considered signal models: (a) SR0b and (b) SR1b for the scalarDM mediator production, (c) SR0b and (d) SR1b for the vector DM mediator production and (d)SR0b (e) SR1b for the single vector-like T quark production. The background predictions with thecorresponding uncertainties result from the simultaneous fit to data in control and signal regionsunder the background-only hypothesis (Post-Fit). The signal regions included in each fit correspondto those targeting the respective signal model. The dashed line indicates the pre-fit total backgroundprediction. The overlayed signal distributions correspond to scalar DM mediator production withmϕ = 4 TeV (Scalar), vector DM mediator production with mV = 1.75 TeV (Vector) and singlevector-like T production with mT = 1.7 TeV (VLQ) scaled by a factor 5.– 22 –JHEP05(2024)2632500 3000 3500 4000 4500 5000 5500 6000 [GeV]φm1−10110210310410) [fb]χ t→(pp σTheory (LO)95% C.L. Obs. Limit95% C.L. Exp. Limitσ1±95% C.L. Exp. σ2±95% C.L. Exp. ATLAS 1− = 13 TeV, 139 fbs Scalar DM mediator = 0.4χ = 0.6, yqλ = 1 GeV χ m(a)1500 2000 2500 3000 3500 [GeV]Vm110210310410510 tV) [fb]→(pp σTheory (LO)95% C.L. Obs. Limit95% C.L. Exp. Limitσ1±95% C.L. Exp. σ2±95% C.L. Exp. ATLAS 1− = 13 TeV, 139 fbs Vector DM mediator = 1 GeVχ = 1, mχ a = 0.5, g(b)1000 1200 1400 1600 1800 2000 2200 2400 2600 2800 [GeV]Tm110210310410510 Zt) [fb]→ T →(pp σTheory (NLO)95% C.L. Obs. Limit95% C.L. Exp. Limitσ1±95% C.L. Exp. σ2±95% C.L. Exp. ATLAS 1− = 13 TeV, 139 fbs Single-T Production = 0.5, singletTκ Zt) = 0.25→ BR(T(c)Figure 9. 95% CL upper limits on the cross-section of the considered signal models as a function of:(a) the DM scalar mediator ϕ mass (for fixed model parameters of λq = 0.6, yχ = 0.4 and mχ = 1 GeV),(b) the DM vector mediator V mass (for a = 0.5, gχ = 1 and mχ = 1 GeV) and (c) the vector-like Tquark mass (for κT = 0.5).in section 2, controls the branching ratio B(T → Wb) and fully contrains B(T → tZ). Asexpected, the exclusion limits on the T quark mass are degraded for larger values of ξW ,corresponding to lower values of the branching ratio associated with the decay exploredin this analysis, B(T → Zt).– 23 –JHEP05(2024)2633−102−101−10110210theoryσ/Obs. 95% CLσ2500 3000 3500 4000 4500 5000 5500 6000 [GeV] φm0.10.20.30.40.50.60.70.80.91qλ ATLAS-1 = 13 TeV, 139 fbsScalar DM mediator = 1 GeVχ = 0.4, mχyObs. 95% CL σExp. +1 σExp. +2Exp. 95% CL σExp. -1 σExp. -2 (a)3−102−101−10110210theoryσ/Obs. 95% CLσ2500 3000 3500 4000 4500 5000 5500 6000 [GeV] φm0.10.20.30.40.50.60.70.80.91χ yATLAS-1 = 13 TeV, 139 fbsScalar DM mediator = 1 GeVχ = 0.2, mqλObs. 95% CL σExp. +1 σExp. +2Exp. 95% CL σExp. -1 σExp. -2 (b)3−102−101−10110210theoryσ/Obs. 95% CLσ2500 3000 3500 4000 4500 5000 5500 6000 [GeV] φm500100015002000250030003500400045005000 [GeV]χ m ATLAS-1 = 13 TeV, 139 fbsScalar DM mediator = 0.4χ = 0.2, yqλObs. 95% CL σExp. +1 σExp. +2Exp. 95% CL σExp. -1 σExp. -2(c)Figure 10. Observed 95% CL upper limits on the scalar-mediated DM signal cross-section dividedby the theoretical value in three planes of the model parameters space: (a) (mϕ, λq), (b) (mϕ, yχ) and(c) (mϕ,mχ). The observed (expected) 95% CL exclusion limits on the parameters are drawn as solid(dashed) lines. The ±1 and ±2 standard deviations around the expected limit are also shown.– 24 –JHEP05(2024)2633−102−101−10110210theoryσ/Obs. 95% CLσ1000 1500 2000 2500 3000 3500 [GeV] Vm0.20.30.40.50.60.70.80.91χ gATLAS-1 = 13 TeV, 139 fbsVector DM mediator = 1 GeVχa = 0.5, mObs. 95% CL σExp. +1 σExp. +2Exp. 95% CL σExp. -1 σExp. -2 (a)3−102−101−10110210theoryσ/Obs. 95% CLσ1000 1500 2000 2500 3000 3500 [GeV] Vm0.10.150.20.250.30.350.40.450.5 aATLAS-1 = 13 TeV, 139 fbsVector DM mediator = 1 GeVχ = 1, mχgObs. 95% CL σExp. +1 σExp. +2Exp. 95% CL σExp. -1 σExp. -2 (b)3−102−101−10110210theoryσ/Obs. 95% CLσ1000 1500 2000 2500 3000 3500 [GeV] Vm4005006007008009001000110012001300 [GeV]χ m ATLAS-1 = 13 TeV, 139 fbsVector DM mediator = 1χa = 0.5, gObs. 95% CL σExp. +1 σExp. +2Exp. 95% CL σExp. -1 σExp. -2(c)Figure 11. Observed 95% CL upper limits on the vector-mediated DM signal cross-section dividedby the theoretical value in three planes of the model parameters space: (a) (mV , gχ), (b) (mV , a) and(c) (mV ,mχ). The observed (expected) 95% CL exclusion limits on the parameters are drawn as solid(dashed) lines. The ±1 and ±2 standard deviations around the expected limit are also shown.– 25 –JHEP05(2024)2631000 1200 1400 1600 1800 2000 2200 2400 [GeV] Tm0.20.40.60.811.2Tκ = 5%T/mTΓ = 10%T/mTΓ = 20%T/mTΓ = 50%T/mTΓ > 50%T/mTΓATLAS-1 = 13 TeV, 139 fbs Zt)qb)→T singlet (T(Obs. 95% CL σ 1±Exp. Exp. 95% CL σ 2±Exp. (a)3−102−101−10110210theoryσ/Obs. 95% CLσ1000 1200 1400 1600 1800 2000 2200 2400 [GeV] Tm0.20.40.60.811.2Tκ > 50%T/mTΓATLAS-1 = 13 TeV, 139 fbs Zt)qb)→T singlet (T(Obs. 95% CL σExp. +1 σExp. +2Exp. 95% CL σExp. -1 σExp. -2(b)Figure 12. Exclusion limits in terms of the universal coupling constant κT as a function of the T quarkmass in the singlet SU(2) scenario, in the regime where ΓT /mT ≤ 50%, for which the theory calculationsare known to be valid. (a) Expected (dashed line) and observed (solid line) 95% CL exclusion limitson κT as a function of the T quark mass. Different ΓT /mT hypotheses are shown as dashed lines. Theshaded bands correspond to ±1 and ±2 standard deviations around the expected limit. (b) Observed95% CL upper limits on the T quark signal cross-section divided by the theoretical value as a functionof κT and the T quark mass. The observed (expected) 95% CL exclusion limits on the parametersare drawn as solid (dashed) lines, with all values of κT above the contour line being excluded at eachmass point. The ±1 and ±2 standard deviations around the expected limit are also shown.0.5 0.6 0.7 0.8 0.9Wξ1020304050 (%)T / mTΓ1200140016001800Observed mass limit [GeV]16001800ATLAS-1 = 13 TeV, 139 fbsLargest excluded mass at 95% CLObserved ExpectedFigure 13. Observed 95% CL exclusion limits on the T quark mass in the singlet SU(2) scenario asa function of the relative resonance width ΓT /mT and the relative coupling parameter ξW . The solid(dashed) contour lines indicate observed (expected) exclusion limits of equal mass in units of GeV.– 26 –JHEP05(2024)2639 ConclusionsThis paper reports the search for anomalous production of events with a single top quark andlarge missing transverse momentum using the 139 fb−1 dataset of pp collisions at√s = 13 TeVcollected by ATLAS at the LHC during the Run 2 data-taking.No deviations from the SM predictions are observed and the results are interpreted interms of upper limits on the cross-sections of BSM models expected to populate the consideredphase space. The models are the production of DM in association with a single top quarkvia a scalar or vector mediator, and the production of a single vector-like T quark in thesinglet scenario decaying into tZ(→ νν¯). The observed limits on cross-sections are used toexclude ranges of values of model parameters: the scalar (vector) mediated production of DMin association with a single top quark is excluded for masses of the scalar (vector) particleup to 4.3 (2.3) TeV for mχ = 1 GeV and couplings λq = 0.6 and yχ = 0.4 (a = 0.5 andgχ = 1). This result improves the limits on the mediator mass of the scalar (vector) modelby approximately 800 (300) GeV when compared to the previous analysis of mono-top finalstates. The production of a single vector-like T quark decaying into tZ(→ νν¯) is excludedfor masses of the singlet T quark up to 1.8 TeV, assuming κT = 0.5. This limit outperformsprevious results using the mono-top topology by approximately 400 GeV. This significantimprovement partially comes from the refined object reconstruction and calibration, as well asthe analysis strategy, optimising the event preselection and applying a XGBoost algorithmto improve the background discrimination. The increased dataset statistics also play asignificant role in the improved sensitivity.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. [154].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,Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taipei;TENMAK, Türkiye; STFC, United Kingdom; DOE and NSF, United States of America.– 27 –JHEP05(2024)263Individual groups and members have received support from BCKDF, CANARIE, CRCand DRAC, Canada; CERN-CZ, PRIMUS 21/SCI/017 and UNCE SCI/013, Czech Republic;COST, ERC, ERDF, Horizon 2020, ICSC-NextGenerationEU and Marie Skłodowska-CurieActions, European Union; Investissements d’Avenir Labex, Investissements d’Avenir Idexand ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeiaprogrammes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and MINERVA,Israel; Norwegian Financial Mechanism 2014-2021, Norway; NCN and NAWA, Poland; LaCaixa Banking Foundation, CERCA Programme Generalitat de Catalunya and PROMETEOand GenT Programmes Generalitat Valenciana, Spain; Göran Gustafssons Stiftelse, Sweden;The Royal Society and Leverhulme Trust, United Kingdom.In addition, individual members wish to acknowledge support from Chile: Agencia Na-cional de Investigación y Desarrollo (FONDECYT 1190886, FONDECYT 1210400, FONDE-CYT 1230987); China: National Natural Science Foundation of China (NSFC — 12175119,NSFC 12275265, NSFC-12075060); 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, NextGen-erationEU), Marie Sklodowska-Curie Actions (EU H2020 MSC IF GRANT NO 101033496);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’AvenirLabex (ANR-11-LABX-0012); Germany: Baden-Württemberg Stiftung (BW Stiftung-PostdocEliteprogramme), Deutsche Forschungsgemeinschaft (DFG — 469666862, DFG — CR312/5-1); Italy: Istituto Nazionale di Fisica Nucleare (FELLINI G.A. n. 754496, ICSC,NextGenerationEU); Japan: Japan Society for the Promotion of Science (JSPS KAKENHI22H01227, JSPS KAKENHI 22KK0227, JSPS KAKENHI JP21H05085, JSPS KAKENHIJP22H04944); Netherlands: Netherlands Organisation for Scientific Research (NWO Veni 2020— VI.Veni.202.179); Norway: Research Council of Norway (RCN-314472); Poland: Polish Na-tional Agency for Academic Exchange (PPN/PPO/2020/1/00002/U/00001), Polish NationalScience Centre (NCN 2021/42/E/ST2/00350, NCN OPUS nr 2022/47/B/ST2/03059, NCNUMO-2019/34/E/ST2/00393, UMO-2020/37/B/ST2/01043, UMO-2021/40/C/ST2/00187);Slovenia: Slovenian Research Agency (ARIS grant J1-3010); Spain: BBVA Foundation(LEO22-1-603), Generalitat Valenciana (Artemisa, FEDER, IDIFEDER/2018/048), LaCaixa Banking Foundation (LCF/BQ/PI20/11760025), Ministry of Science and Innovation(RYC2019-028510-I, RYC2020-030254-I), PROMETEO and GenT Programmes GeneralitatValenciana (CIDEGENT/2019/023, CIDEGENT/2019/027); Sweden: Swedish ResearchCouncil (VR 2018-00482, VR 2022-03845, VR 2022-04683), Knut and Alice WallenbergFoundation (KAW 2017.0100, KAW 2018.0157, KAW 2018.0458, KAW 2019.0447); Switzer-land: Swiss National Science Foundation (SNSF — PCEFP2_194658); United Kingdom:Leverhulme Trust (Leverhulme Trust RPG-2020-004); United States of America: NeubauerFamily Foundation.Open Access. 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Alegria 121,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,ac, 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, S.J. Arbiol Val 87, 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 159, R.J. Atkin 33a, M. Atkinson162, H. Atmani35f ,P.A. Atmasiddha 128, 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,q,A. Bachiu 34, F. Backman 47a,47b, A. Badea 61, T.M. Baer 106, P. Bagnaia 75a,75b,M. Bahmani 18, D. Bahner 54, A.J. Bailey 163, V.R. Bailey 162, J.T. Baines 134, L. Baines 94,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,J.Y. Beaucamp 90, P.H. Beauchemin 158, P. Bechtle 24, H.P. Beck 19,p, K. Becker 167,A.J. Beddall 82, V.A. Bednyakov 38, C.P. Bee 145, L.J. Beemster 15, T.A. Beermann 36,– 38 –JHEP05(2024)263M. Begalli 83d, M. Begel 29, A. Behera 145, J.K. Behr 48, J.F. Beirer 36, F. Beisiegel 24,M. Belfkir 116b, 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, A. Berrocal Guardia 13, T. Berry 95,P. Berta 133, A. Berthold 50, I.A. Bertram 91, S. Bethke 110, A. Betti 75a,75b, A.J. Bevan 94,N.K. Bhalla 54, M. Bhamjee 33c, S. Bhatta 145, D.S. Bhattacharya 166, P. Bhattarai 143,V.S. Bhopatkar 121, R. Bi29,aj , 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, 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 165, 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, Y. Cai 14c,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, 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, G. Carducci 43b,43a, T. Carli 36, G. Carlino 72a, J.I. Carlotto 13,B.T. Carlson 129,r, 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,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,– 39 –JHEP05(2024)263K. 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, S.A. Cetin 82, D. Chakraborty 115,J. Chan 170, W.Y. Chan 153, J.D. Chapman 32, E. Chapon 135, B. Chargeishvili 149b,D.G. Charlton 20, 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 113, 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, A. Clark 56, P.J. Clark 52, C. Clarry 155,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, 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, L.D. Corpe 40,M. Corradi 75a,75b, F. Corriveau 104,x, 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 159,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 34,M. Danninger 142, V. Dao 36, G. Darbo 57b, S. Darmora 6, S.J. Das 29,aj , 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,F. De Santis 70a,70b, 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,L. Delagrange 127, 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, A. Dimitrievska 17a, J. Dingfelder 24, I-M. Dinu 27b,S.J. Dittmeier 63b, F. Dittus 36, F. Djama 102, T. Djobava 149b, C. Doglioni 101,98,– 40 –JHEP05(2024)263A. Dohnalova 28a, J. Dolejsi 133, Z. Dolezal 133, K.M. Dona 39, M. Donadelli 83c,B. Dong 107, J. Donini 40, A. D’Onofrio 72a,72b, 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, M. Drnevich 117, 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, 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, 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 36, A. El Moussaouy 108, V. Ellajosyula 161, M. Ellert 161,F. Ellinghaus 171, N. Ellis 36, J. Elmsheuser 29, M. Elsing 36, D. Emeliyanov 134, Y. Enari 153,I. Ene 17a, S. Epari 13, 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, D. Fakoudis 100, 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 159, A.B. Fenyuk37, L. Ferencz 48, R.A.M. Ferguson 91, S.I. Fernandez Luengo 137f ,P. Fernandez Martinez 13, M.J.V. Fernoux 102, J. Ferrando 91, 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,ad, 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,S. Fuenzalida Garrido 137f , M. Fujimoto 102, 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, 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, P. Gaspar 83b, V.K. Gassmann158,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, A. Gekow119,– 41 –JHEP05(2024)263C. Gemme 57b, M.H. Genest 60, S. 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 159, 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,aj , 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, 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, S.G. Grewe110, C. Grieco 13, A.A. Grillo 136,K. Grimm 31, S. Grinstein 13,t, 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,E. Guilloton 167,134, S. Guindon 36, F. Guo 14a,14e, J. Guo 62c, L. Guo 48, Y. Guo 106,R. Gupta 48, R. Gupta 129, S. Gurbuz 24, S.S. Gurdasani 54, G. Gustavino 36, M. Guth 56,P. Gutierrez 120, L.F. Gutierrez Zagazeta 128, M. Gutsche 50, 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 50, S. Hadzic 110, A.I. Hagan 91, 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,ac,H. Hanif 142, M.D. Hank 128, 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,R. Hertenberger 109, L. Hervas 36, M.E. Hesping 100, N.P. Hessey 156a, H. Hibi 85, E. Hill 155,– 42 –JHEP05(2024)263S.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, D.D. Hofer 106, 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,X. Huang 14a,14e, 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,al, 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, 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,aa, 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, 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,t, 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 62a, 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, R.A. Khan 129, 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 44, 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, O. Kolay 50,I. Koletsou 4, T. Komarek 122, K. Köneke 54, A.X.Y. Kong 1, T. Kono 118,N. Konstantinidis 96, P. Kontaxakis 56, B. Konya 98, R. Kopeliansky 68, S. Koperny 86a,– 43 –JHEP05(2024)263K. Korcyl 87, K. Kordas 152,e, 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, 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, P. Kumari 156b, 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 159, 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, R. Lazaridou167, 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,s, 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 110, H. Li 62a, H. Li 62b,H. Li 14c, H. Li 14b, H. Li 62b, J. Li 62c, 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 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, X. Liu 62b, 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, T. Lohse 18, K. Lohwasser 139,E. Loiacono 48, M. Lokajicek 131,∗, J.D. Lomas 20, J.D. Long 162, I. Longarini 159,L. Longo 70a,70b, R. Longo 162, I. Lopez Paz 67, A. Lopez Solis 48, 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, F. Luehring 68,I. Luise 145, O. Lukianchuk 66, O. Lundberg 144, B. Lund-Jensen 144, N.A. Luongo 6,M.S. Lutz 151, A.B. Lux 25, D. Lynn 29, H. Lyons92, R. Lysak 131, E. Lytken 98,– 44 –JHEP05(2024)263V. Lyubushkin 38, T. Lyubushkina 38, M.M. Lyukova 145, H. Ma 29, K. Ma 62a, L.L. Ma 62b,W. Ma 62a, 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,o, 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,ab, D.C. Mankad 169, A. Mann 109, B. Mansoulie 135, S. Manzoni 36,L. Mao 62c, X. Mapekula 33c, A. Marantis 152,s, G. Marchiori 5, M. Marcisovsky 131,C. Marcon 71a, M. Marinescu 20, S. Marium 48, 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,t, 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, 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, C.C. McCracken 164,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, C.M. Mcpartland 92, R.A. McPherson 165,x, S. Mehlhase 109, A. Mehta 92,D. Melini 163, 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, G. Mercado 115, C. Merlassino 69a,69c, L. Merola 72a,72b, C. Meroni 71a,71b,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, E.H. Miller 143, 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, M.H. Mohamed Farook 112, 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, F.J. Munoz Sanchez 101, M. Murin 101,– 45 –JHEP05(2024)263W.J. Murray 167,134, A. Murrone 71a,71b, M. Muškinja 17a, C. Mwewa 29, A.G. Myagkov 37,a,A.J. Myers 8, 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,aj , 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 116b, 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 116a, 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, M. Noury 35a,J. Novak 93, T. Novak 48, L. Novotny 132, R. Novotny 112, L. Nozka 122, K. Ntekas 159,N.M.J. Nunes De Moura Junior 83b, E. Nurse96, J. Ocariz 127, A. Ochi 85, I. Ochoa 130a,S. Oerdek 48,u, J.T. Offermann 39, A. Ogrodnik 133, A. Oh 101, C.C. Ohm 144, H. Oide 84,R. Oishi 153, M.L. Ojeda 48, Y. Okumura 153, L.F. Oleiro Seabra 130a, S.A. Olivares Pino 137d,D. Oliveira Damazio 29, D. Oliveira Goncalves 83a, J.L. Oliver 159, 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, F. Ozturk 87, 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, 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 162, A. Paramonov 6, C. Paraskevopoulos 10,D. Paredes Hernandez 64b, K.R. Park 41, 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,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,aj , 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 123, 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,A. Pirttikoski 56, D.A. Pizzi 34, L. Pizzimento 64b, A. Pizzini 114, M.-A. Pleier 29,– 46 –JHEP05(2024)263V. 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, A. Psallidas 46, 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, I.A. Ramirez-Berend 34, K. Ran 48,14e, N.P. Rapheeha 33g, H. Rasheed 27b,V. Raskina 127, D.F. Rassloff 63a, A. Rastogi 17a, 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 49,C. Rembser 36, A. Renardi 48, M. Renda 27b, M.B. Rendel110, F. Renner 48, A.G. Rennie 159,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, J.O. Rieger 114, M. Rijssenbeek 145,A. Rimoldi 73a,73b, M. Rimoldi 36, 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,x, 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 159, A.R. Roepe-Gier 136, J. Roggel 171,O. Røhne 125, R.A. Rojas 103, C.P.A. Roland 127, 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,ab, D. Rousseau 66, D. Rousso 32,A. Roy 162, S. Roy-Garand 155, A. Rozanov 102, Z.M.A. Rozario 59, 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, H.F-W. Sadrozinski 136, F. Safai Tehrani 75a, B. Safarzadeh Samani 134,M. Safdari 143, S. Saha 165, M. Sahinsoy 110, A. Saibel 163, M. Saimpert 135, M. Saito 153,T. Saito 153, D. Salamani 36, A. Salnikov 143, J. Salt 163, A. Salvador Salas 151,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, J.A. Sandesara 103, M. Sandhoff 171, C. Sandoval 22b,– 47 –JHEP05(2024)263D.P.C. Sankey 134, T. Sano 88, A. Sansoni 53, L. Santi 75a,75b, C. Santoni 40,H. Santos 130a,130b, A. Santra 169, K.A. Saoucha 160, 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, 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 159, 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, N. 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, 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, D.J. Sheppard 142, 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,v,J. Shlomi 169, M.J. Shochet 39, J. Shojaii 105, D.R. Shope 125, B. Shrestha 120,S. Shrestha 119,ak, 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, 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, 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,x, 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,J.D. Sorenson 112, I.R. Sotarriva Alvarez 154, V. Sothilingam63a, O.J. Soto Sandoval 137c,137b,S. Sottocornola 68, R. Soualah 160, 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,ab, P. Staroba 131,P. Starovoitov 63a, S. Stärz 104, R. Staszewski 87, G. Stavropoulos 46, J. Steentoft 161,– 48 –JHEP05(2024)263P. 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, 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,u, A. Taffard 159,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,w, G.N. Taylor 105, W. Taylor 156b, 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,x, 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,ab, 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,s,V. Tsiskaridze 155, E.G. Tskhadadze 149a, M. Tsopoulou 152,e, Y. Tsujikawa 88,I.I. Tsukerman 37, V. Tsulaia 17a, S. Tsuno 84, K. Tsuri 118, D. Tsybychev 145, Y. Tu 64b,A. Tudorache 27b, V. Tudorache 27b, A.N. Tuna 61, S. Turchikhin 57b,57a, I. Turk Cakir 3a,R. Turra 71a, T. Turtuvshin 38,y, 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 159, J. Urban 28b, P. Urquijo 105, P. Urrejola 137a,G. Usai 8, R. Ushioda 154, M. Usman 108, Z. Uysal 82, 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,ab,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. Vaslin84,G.A. Vasquez 165, A. Vasyukov 38, F. Vazeille 40, T. Vazquez Schroeder 36, J. Veatch 31,– 49 –JHEP05(2024)263V. 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, J.C. Voigt 50, 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, N.K. Vu 62d,62c, 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 136, 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 159,L. Wickremasinghe 124, W. Wiedenmann 170, 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. Wollrath159,M.W. Wolter 87, H. Wolters 130a,130c, A.F. Wongel 48, E.L. Woodward 41, 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. Xu14c, 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 36, 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,ai, Y. Yu 62a, M. Yuan 106, R. Yuan 62b,L. Yue 96, M. Zaazoua 62a, B. Zabinski 87, E. Zaid52, Z.K. Zak 87, 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,– 50 –JHEP05(2024)263D.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, S. Zhang 44, T. Zhang 153, X. Zhang 62c, X. Zhang 62b,Y. Zhang 62c,5, Y. Zhang 96, Y. Zhang 14c, Z. 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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– 51 –JHEP05(2024)26329 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;(e)Schoolof Physics and Microelectronics, Zhengzhou University; China63 (a)Kirchhoff-Institut für Physik, Ruprecht-Karls-Universität Heidelberg, Heidelberg;(b)PhysikalischesInstitut, Ruprecht-Karls-Universität Heidelberg, Heidelberg; Germany– 52 –JHEP05(2024)26364 (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; China65Department 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 ofAmerica– 53 –JHEP05(2024)263108Group of Particle Physics, University of Montreal, Montreal QC; Canada109 Fakultät für Physik, Ludwig-Maximilians-Universität München, München; Germany110Max-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)United Arab Emirates University, Al Ain; United ArabEmirates117Department 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 ofAmerica– 54 –JHEP05(2024)263146Department of Physics and Astronomy, University of Sussex, Brighton; United Kingdom147 School of Physics, University of Sydney, Sydney; Australia148 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 America159Department of Physics and Astronomy, University of California Irvine, Irvine CA; United States ofAmerica160University of Sharjah, Sharjah; United Arab Emirates161Department 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, Stellenbosch University; South AfricapAlso at Department of Physics, University of Fribourg, Fribourg; SwitzerlandqAlso at Department of Physics, University of Thessaly; GreecerAlso at Department of Physics, Westmont College, Santa Barbara; United States of AmericasAlso at Hellenic Open University, Patras; Greece– 55 –JHEP05(2024)263tAlso at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona; SpainuAlso at Institut für Experimentalphysik, Universität Hamburg, Hamburg; GermanyvAlso at Institute for Nuclear Research and Nuclear Energy (INRNE) of the Bulgarian Academy ofSciences, Sofia; BulgariawAlso at Institute of Applied Physics, Mohammed VI Polytechnic University, Ben Guerir; MoroccoxAlso at Institute of Particle Physics (IPP); CanadayAlso at Institute of Physics and Technology, Mongolian Academy of Sciences, Ulaanbaatar; MongoliazAlso at Institute of Physics, Azerbaijan Academy of Sciences, Baku; AzerbaijanaaAlso at Institute of Theoretical Physics, Ilia State University, Tbilisi; GeorgiaabAlso at L2IT, Université de Toulouse, CNRS/IN2P3, UPS, Toulouse; FranceacAlso at Lawrence Livermore National Laboratory, Livermore; United States of AmericaadAlso at National Institute of Physics, University of the Philippines Diliman (Philippines); PhilippinesaeAlso 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 Chinese Academy of Sciences (UCAS), Beijing; Chinaaj Also at University of Colorado Boulder, Department of Physics, Colorado; United States of AmericaakAlso at Washington College, Chestertown, MD; United States of AmericaalAlso at Yeditepe University, Physics Department, Istanbul; Türkiye∗Deceased– 56 –
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Hadron-Hadron Scattering
Search for new particles in fnal states with a boosted top quark and missing transverse momentum in proton-proton collisions at √s = 13 TeV with the ATLAS detector
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