{"@context":{"@language":"en","Affiliation":"http:\/\/vivoweb.org\/ontology\/core#departmentOrSchool","AggregatedSourceRepository":"http:\/\/www.europeana.eu\/schemas\/edm\/dataProvider","Citation":"https:\/\/open.library.ubc.ca\/terms#identifierCitation","CopyrightHolder":"https:\/\/open.library.ubc.ca\/terms#rightsCopyright","Creator":"http:\/\/purl.org\/dc\/terms\/creator","DateAvailable":"http:\/\/purl.org\/dc\/terms\/issued","DateIssued":"http:\/\/purl.org\/dc\/terms\/issued","Description":"http:\/\/purl.org\/dc\/terms\/description","DigitalResourceOriginalRecord":"http:\/\/www.europeana.eu\/schemas\/edm\/aggregatedCHO","FullText":"http:\/\/www.w3.org\/2009\/08\/skos-reference\/skos.html#note","Genre":"http:\/\/www.europeana.eu\/schemas\/edm\/hasType","IsShownAt":"http:\/\/www.europeana.eu\/schemas\/edm\/isShownAt","Language":"http:\/\/purl.org\/dc\/terms\/language","PeerReviewStatus":"https:\/\/open.library.ubc.ca\/terms#peerReviewStatus","Provider":"http:\/\/www.europeana.eu\/schemas\/edm\/provider","Publisher":"http:\/\/purl.org\/dc\/terms\/publisher","PublisherDOI":"https:\/\/open.library.ubc.ca\/terms#publisherDOI","Rights":"http:\/\/purl.org\/dc\/terms\/rights","RightsURI":"https:\/\/open.library.ubc.ca\/terms#rightsURI","ScholarlyLevel":"https:\/\/open.library.ubc.ca\/terms#scholarLevel","Subject":"http:\/\/purl.org\/dc\/terms\/subject","Title":"http:\/\/purl.org\/dc\/terms\/title","Type":"http:\/\/purl.org\/dc\/terms\/type","URI":"https:\/\/open.library.ubc.ca\/terms#identifierURI","SortDate":"http:\/\/purl.org\/dc\/terms\/date"},"Affiliation":[{"@value":"Science, Faculty of","@language":"en"},{"@value":"TRIUMF","@language":"en"},{"@value":"Non UBC","@language":"en"},{"@value":"Physics and Astronomy, Department of","@language":"en"}],"AggregatedSourceRepository":[{"@value":"DSpace","@language":"en"}],"Citation":[{"@value":"Journal of High Energy Physics. 2023 Oct 02;2023(10):1","@language":"en"}],"CopyrightHolder":[{"@value":"The Author(s)","@language":"en"}],"Creator":[{"@value":"ATLAS Collaboration","@language":"en"}],"DateAvailable":[{"@value":"2023-11-08T19:38:31Z","@language":"en"}],"DateIssued":[{"@value":"2023-10-02","@language":"en"}],"Description":[{"@value":"A search for leptoquarks decaying into the b\u03c4 fnal state is performed using\r\nRun 2 proton-proton collision data from the Large Hadron Collider, corresponding to an\r\nintegrated luminosity of 139 fb\u22121\r\nat \u221a\r\ns = 13 TeV recorded by the ATLAS detector. The\r\nbenchmark models considered in this search are vector leptoquarks with electric charge of\r\n2\/3e and scalar leptoquarks with an electric charge of 4\/3e. No signifcant excess above the\r\nStandard Model prediction is observed, and 95% confdence level upper limits are set on\r\nthe cross-section times branching fraction of leptoquarks decaying into b\u03c4 . For the vector\r\nleptoquark production two models are considered: the Yang-Mills and Minimal coupling\r\nmodels. In the Yang-Mills (Minimal coupling) scenario, vector leptoquarks with a mass\r\nbelow 1.58 (1.35) TeV are excluded for a gauge coupling of 1.0 and below 2.05 (1.99) TeV\r\nfor a gauge coupling of 2.5. In the case of scalar leptoquarks, masses below 1.28 (1.53) TeV\r\nare excluded for a Yukawa coupling of 1.0 (2.5). Finally, an interpretation of the results\r\nwith minimal model dependence is performed for each of the signal region categories, and\r\nlimits on the visible cross-section for beyond the Standard Model processes are provided.","@language":"en"}],"DigitalResourceOriginalRecord":[{"@value":"https:\/\/circle.library.ubc.ca\/rest\/handle\/2429\/86479?expand=metadata","@language":"en"}],"FullText":[{"@value":"JHEP10(2023)001Published for SISSA by SpringerReceived: May 26, 2023Accepted: September 2, 2023Published: October 2, 2023Search for leptoquarks decaying into the b\u03c4 final statein pp collisions at \u221as = 13TeV with the ATLASdetectorThe ATLAS collaborationE-mail: atlas.publications@cern.chAbstract: A search for leptoquarks decaying into the b\u03c4 final state is performed usingRun 2 proton-proton collision data from the Large Hadron Collider, corresponding to anintegrated luminosity of 139 fb\u22121 at\u221as = 13TeV recorded by the ATLAS detector. Thebenchmark models considered in this search are vector leptoquarks with electric charge of2\/3e and scalar leptoquarks with an electric charge of 4\/3e. No significant excess above theStandard Model prediction is observed, and 95% confidence level upper limits are set onthe cross-section times branching fraction of leptoquarks decaying into b\u03c4 . For the vectorleptoquark production two models are considered: the Yang-Mills and Minimal couplingmodels. In the Yang-Mills (Minimal coupling) scenario, vector leptoquarks with a massbelow 1.58 (1.35)TeV are excluded for a gauge coupling of 1.0 and below 2.05 (1.99)TeVfor a gauge coupling of 2.5. In the case of scalar leptoquarks, masses below 1.28 (1.53)TeVare excluded for a Yukawa coupling of 1.0 (2.5). Finally, an interpretation of the resultswith minimal model dependence is performed for each of the signal region categories, andlimits on the visible cross-section for beyond the Standard Model processes are provided.Keywords: Beyond Standard Model, Hadron-Hadron ScatteringArXiv ePrint: 2305.15962Open Access, Copyright CERN,for the benefit of the ATLAS Collaboration.Article funded by SCOAP3.https:\/\/doi.org\/10.1007\/JHEP10(2023)001JHEP10(2023)001Contents1 Introduction 12 The ATLAS detector 43 Data and Monte Carlo samples 54 Object reconstruction and identification 75 Event selection 96 Background estimation 116.1 \u03c4lep\u03c4had channel 116.2 \u03c4had\u03c4had channel 157 Systematic uncertainties 188 Results 209 Conclusion 25The ATLAS collaboration 351 IntroductionThe existing similarities between the structure of the quark and lepton sectors in theStandard Model (SM) suggest the possibility of a new underlying symmetry in particlephysics. Leptoquarks (LQs) that couple to both quarks and leptons, with non-zero baryonand lepton numbers, and fractional electric charges are predicted by several beyond theSM theories that attempt to unify the fundamental interactions, such as technicolour [1\u20133],composite models [4], and grand unification [5\u20137].Recent results reported by BaBar [8, 9], Belle [10] and LHCb [11] show hints of devia-tions from lepton-flavour universality in B-meson decays into final states with D(\u2217) mesons,which could be caused by the existence of LQs. The 4.2 standard deviation disagreementwith respect to the SM prediction observed in the anomalous muon magnetic momentmeasurement [12], though significantly reduced when updated lattice quantum chromody-namics (QCD) calculations [13] are considered, could be caused by LQ contributions to themuon magnetic moment [14].In light of the lepton-flavour universality anomalies observed in the B-meson decaysinto D(\u2217)\u03c4\u03bd final states, the couplings of LQs to third-generation quarks and leptons areexpected to be large [15]. At the LHC, third-generation LQs can be produced singlyvia quark-gluon fusion and quark-gluon scattering or in pairs via the gluon-gluon fusionprocess, as shown in the Feynman diagrams in figure 1. The search presented in this paperis optimised for the single production of third-generation LQ via the bg \u2192 LQ\u03c4 \u2192 b\u03c4\u03c4channel, while LQ pair and non-resonant production processes are also considered sincethey can also contribute to the b\u03c4\u03c4 final state. The single LQ production contribution\u2013 1 \u2013JHEP10(2023)001(a) (b)(c) (d)Figure 1. Illustrative Feynman diagrams of (a), (b) single LQ production, (c) non-resonant LQproduction, and (d) LQ pair production.becomes larger than that from LQ pair production at high LQ mass and coupling values.The results are obtained from proton-proton collision data at a centre-of-mass energy of\u221as = 13TeV collected by the ATLAS detector [16, 17] at the LHC [18] during Run 2between 2015 and 2018, corresponding to a total integrated luminosity of 139 fb\u22121.The vector LQ model chosen for this search is the U1 model [19], a SU(2)L singletwith fermion number F = 3B+L = 0, where B and L are the baryon and lepton numbersrespectively, and an electric charge of 2\/3e. The interaction part of U1 model Lagrangian is:LU1 \u2283 \u2212igs(1\u2212 \u03ba)U\u20201\u00b5TaU1\u03bdGa\u00b5\u03bd + gU\u221a2[U\u00b51 (\u03b2ijL q\u00afiL\u03b3\u00b5\u2113jL + \u03b2ijR d\u00afiR\u03b3\u00b5ejR) + h.c.],where T a = \u03bba\/2 with \u03bba (a = 1, \u00b7 \u00b7 \u00b7 , 8) are the Gell-Mann matrices, gs is the QCDcoupling, qL (\u2113L) denotes the left-handed quark (lepton) doublets and dR (eR) denotes theright-handed down-type quark (charged-lepton) singlets. The i and j indices representthe flavour generation. A summation over the colour indices is performed and omittedfor clarity. The term \u2212igs(1 \u2212 \u03ba)U \u20201\u00b5T aU1\u03bdGa\u00b5\u03bd describes the interaction between U1leptoquarks and SM gluon gauge fields Ga\u00b5\u03bd . In this analysis, two vector LQ scenariosare considered: the Yang-Mills (UYM1 ) coupling scenario, \u03ba = 0, and the Minimal (UMIN1 )coupling scenario, \u03ba = 1. The \u03b2ijL and \u03b2ijR parameters describe the coupling between U1leptoquarks and left-handed or right-handed charged leptons and quarks, respectively. Inthe framework of the UYM1 and UMIN1 scenarios, the probability to decay into the b-quarkand \u03c4 -lepton final state is predicted to be the same as to decay into the top-quark andneutrino final state. Hence, the branching fraction B of the LQ decays into a b-quark and a\u2013 2 \u2013JHEP10(2023)001\u03c4 -lepton is set to 0.5. In this search, all of \u03b2ijR are set to zero, \u03b233L is set to one and other \u03b2ijLare set to zero, such that each LQ decays into a b-quark and a \u03c4 -lepton or into a top-quarkand a neutrino. Due to these choices, the gauge coupling (\u03bb) between U1 leptoquarks andthird-generation charged leptons and quarks can be written as \u03bb = gU\u03b233L \/\u221a2.The scalar LQ model S\u02dc1 is also considered, with F = 3B+L = \u22122 and electric chargeof 4\/3e [20, 21]. There are three parameters in this model: the branching fraction B intocharged leptons, the LQ to \u03c4b Yukawa coupling parameter \u03bb, and the mass term of theLQ. Following ref. [21], the Lagrangian terms for S\u02dc1 LQs related to this analysis are:LS\u02dc1\u2283 +\u03bbij d\u00afCiR S\u02dc1ejR + h.c.,where C in the superscript stands for the charge conjugation operation. The terms eRand dR are the right-handed charged leptons and down-type quarks and \u03bbij representsthe Yukawa couplings between S\u02dc1, charged leptons, and quarks, where the ij refers tothe generations of the quark and charged lepton. In the framework of the S\u02dc1 model, theonly non-zero Yukawa coupling considered in this paper is the coupling to a b-quark anda \u03c4 -lepton. Since only the coupling to the third-generation charged lepton and quark isconsidered, \u03bb33 = \u03bb is assumed to be different from zero, while the rest of the \u03bbij are setto zero.Most of the previous searches for LQs performed by the ATLAS [22\u201328] and CMS [29\u201332] collaborations have been conducted on different final states compared to this search.For third generation LQs, the CMS collaboration has recently published results of searchesfor LQs decaying into t\u03bd and b\u03c4 [33]. The ATLAS collaboration performed a search forpair produced scalar LQs in b\u03c4b\u03c4 final states with 36 fb\u22121 of proton-proton collision dataat\u221as = 13TeV that excluded scalar LQs with masses below 1TeV, assuming a LQ to b\u03c4branching fraction equal to one [34].The analysis described in this paper is the first search by the ATLAS collaborationfor singly produced LQs decaying into b\u03c4 . The search is performed over a LQ mass (mLQ)in the range of 0.4TeV to 2.5TeV. The \u03bb range is chosen to be between 0.5 and 2.5 tocover possible regions where LQs could explain the anomalies observed in the B-mesondecay and is extended to large \u03bb where the single LQ production channel provides a signif-icant contribution compared to the pair-production process. In the case of the vector LQproduction, the contribution from LQs decaying into t\u03bd is neglected.The analysis starts from the selection of a pair of oppositely charged \u03c4 -leptons producedin association with a jet identified as containing a b-hadron (b-jet). The main backgroundsto the search are the tt\u00af and tW production processes. Two signatures are considered,containing either a \u03c4lep\u03c4had or \u03c4had\u03c4had pair, where \u03c4had (\u03c4lep) refers to a \u03c4 -lepton decayinginto hadrons and a neutrino (two neutrinos and an electron or a muon). In each of thesetwo analysis channels, events are classified, based on the transverse momentum (pT) of theb-jet, in two categories of low and high b-jet pT. The search for LQs is only performedin the high b-jet pT category, where the effect from the interference of non-resonant LQproduction with SM processes is expected to be small [35]. The non-resonant contributioncan be significantly modified by the interference contribution, which depends on the signalmodel parameters [35, 36]. The effect of the interference with SM diagrams, such as those\u2013 3 \u2013JHEP10(2023)001from Z\/\u03b3\u2217(\u2192 \u03c4\u03c4)+b-jet, is neglected. Due to the lack of detailed studies of the interferenceeffect, an additional search is performed considering both high and low b-jet pT categoriesand not relying on a specific LQ model choice for its signal description (henceforth called\u2018model-independent\u2019), and covering a wider range of beyond-SM signatures. For this search,the results are expressed in terms of the visible cross-section of the beyond-SM signal.The next sections discuss the ATLAS detector in section 2, data and simulated samplesin section 3, followed by the object reconstruction and definitions in section 4. Section 5discusses the overall analysis strategy and event selection, then section 6 goes into moredetails of the background estimation methods. The systematic uncertainties are discussedin section 7 followed by the results in section 8, with the conclusion in section 9.2 The ATLAS detectorThe ATLAS detector [16] at the LHC covers nearly the entire solid angle around the colli-sion point.1 It consists of an inner tracking detector surrounded by a thin superconductingsolenoid, electromagnetic and hadron 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 of |\u03b7| < 2.5. The high-granularity silicon pixeldetector covers the vertex region and typically provides four measurements per track, thefirst hit normally being in the insertable B-layer installed before Run 2 [17, 37]. It isfollowed by the silicon microstrip tracker, which usually provides eight measurements pertrack. These silicon detectors are complemented by the transition radiation tracker (TRT),which enables radially extended track reconstruction up to |\u03b7| = 2.0. The TRT alsoprovides electron identification information based on the fraction of hits (typically 30 intotal) above a higher energy-deposit threshold corresponding to transition radiation.The calorimeter system covers the pseudorapidity range of |\u03b7| < 4.9. Within the region|\u03b7| = 3.2, electromagnetic calorimetry is provided by barrel and endcap high-granularitylead\/liquid-argon (LAr) calorimeters, with an additional thin LAr presampler covering|\u03b7| < 1.8 to correct for energy loss in material upstream of the calorimeters. Hadroncalorimetry is provided by the steel\/scintillator-tile calorimeter, segmented into three barrelstructures within |\u03b7| = 1.7, and two copper\/LAr hadron endcap calorimeters. The solidangle coverage is completed by 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. A set of precision chambers covers the region |\u03b7| < 2.71ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP) inthe centre of the detector and the z-axis along the beam pipe. The x-axis points from the IP to the centreof the LHC ring, and the y-axis points upwards. Cylindrical coordinates (r, \u03d5) are used in the transverseplane, \u03d5 being the azimuthal angle around the z-axis. The pseudorapidity is defined in terms of the polarangle \u03b8 as \u03b7 = \u2212 ln tan(\u03b8\/2). Angular distance is measured in units of \u2206R \u2261\u221a(\u2206\u03b7)2 + (\u2206\u03d5)2.\u2013 4 \u2013JHEP10(2023)001with three layers of monitored drift tubes, complemented by cathode-strip chambers inthe forward region, where the background is highest. The muon trigger system covers therange of |\u03b7| < 2.4 with resistive-plate chambers in the barrel, and thin-gap chambers inthe endcap regions.Interesting events are selected by the first-level trigger system implemented in customhardware, followed by selections made by algorithms implemented in software in the high-level trigger [38]. The first-level trigger accepts events from the 40MHz bunch crossings ata rate below 100 kHz, which the high-level trigger reduces in order to record events to diskat about 1 kHz.An extensive software suite [39] is used in data simulation, in the reconstruction andanalysis of real and simulated data, in detector operations, and in the trigger and dataacquisition systems of the experiment.3 Data and Monte Carlo samplesThe data were collected using unprescaled single-lepton and single \u03c4had triggers. A moredetailed description of the triggers used in the analysis for each data-taking period is givenin section 5. Quality criteria are applied to events to ensure that the data were not affectedby any hardware- or software-related issues [40].Monte Carlo (MC) simulated events of single LQs decaying into b\u03c4 were produced formasses ranging from 0.4TeV to 2.5TeV. The signal samples were produced at leading order(LO) in QCD in the five-flavour scheme using the MadGraph5_aMC@NLO 2.8.1 [41]generator with the NNPDF3.0nnlo [42] parton distribution function (PDF) followed byparton shower (PS) and hadronisation with Pythia 8.244 [43] using the A14 set of tunedparameters (tune) [44] and the NNPDF2.3lo PDF set. Single scalar and vector LQsignal samples were produced with coupling parameters \u03bb from 0.5 to 2.5. The intrinsicwidth of the LQs increases quadratically with \u03bb and linearly as a function of mLQ. In theconsidered range of parameters, the LQ width is 16% or less of the LQ mass. The simulatedsignal events do not include interference effects with the SM processes. For the vector LQsignal two samples were produced for each \u03bb, one with Yang-Mills coupling (\u03ba = 0) andthe other with minimal coupling (\u03ba = 1). The implementation of the signal model is basedon that described in refs. [20, 21, 45].Simulated events with pair produced scalar LQs were generated at next-to-leading or-der (NLO) in QCD with MadGraph5_aMC@NLO 2.6.0, using the LQ model describedin ref. [46], which adds PS to the fixed-order NLO QCD calculations [47, 48] interfacedto Pythia 8.230 for the PS and hadronisation. Parton luminosities are provided by thefive-flavour scheme NNPDF3.0nlo PDF set with a value of the strong coupling con-stant \u03b1s = 0.118, and the underlying event was modelled with the A14 tune. The LQpair-production cross-sections were obtained from the calculation of direct top-squark pairproduction assuming that all other supersymmetric particles are heavier, since the pro-duction modes of this process are the same as the LQ pair production. The cross-sectionswere computed at approximate next-to-next-to-leading order (NNLO) in QCD with re-summation of next-to-next-to-leading logarithmic (NNLL) soft gluon terms [49\u201352]. The\u2013 5 \u2013JHEP10(2023)001cross-sections do not include lepton t-channel contributions, which are neglected in ref. [46]and may lead to corrections at the percent level [53].Simulated events with pair-produced vector LQs were generated with Mad-Graph5_aMC@NLO 2.6.0 at LO in QCD, using the LQ model of ref. [19] and theNNPDF3.0nlo PDF set with \u03b1s = 0.118. Decays of the LQs were performed withMadSpin, while PS and hadronisation were simulated using Pythia 8.244 with the A14tune. Since no higher-order cross-sections are available for this model, the LO Mad-Graph5_aMC@NLO cross-sections were used.Several simulation samples are used to model the expected background processes.These include tt\u00af, single top-quark, Z and W bosons produced in association with jets(Z+jets and W+jets), and diboson events.The production of tt\u00af simulated events was performed with the PowhegBox v2 [54\u201357]generator at NLO with the NNPDF3.0nlo PDF set [58] and the hdamp parameter2 setto 1.5mtop [59], with mtop = 172.5GeV. The events were interfaced to Pythia 8.230 [43]to model the PS, hadronisation, and underlying event, with parameters set according to theA14 tune and using the NNPDF2.3lo set of PDFs. The tt\u00af sample was normalised to thecross-section prediction at NNLO in QCD including the resummation of NNLL calculatedusing Top++ 2.0 [60\u201366].Single top-quark s-channel (t-channel) production was simulated using thePowhegBox v2 generator at NLO in QCD in the five-flavour (four-flavour) scheme withthe NNPDF3.0nlo set of PDFs. The events were interfaced with Pythia 8.230 using theA14 tune and the NNPDF2.3lo PDF set. The samples were normalised to the theoryprediction calculated at NLO in QCD with Hathor 2.1 [67, 68]. Similarly, the associ-ated production of top quarks with W bosons (tW ) was modelled by the PowhegBox v2generator at NLO in QCD using the five-flavour scheme and the NNPDF3.0nlo setof PDFs. The diagram removal scheme [69] was used to remove interference and overlapwith tt\u00af production. The related uncertainty is estimated by comparison with an alter-native sample generated using the diagram subtraction scheme [59, 69]. The events wereinterfaced to Pythia 8.230 using the A14 tune and the NNPDF2.3lo set of PDFs.For the production of Z\/\u03b3\u2217 sample, the PowhegBox v1 [55\u201357, 70] generator wasused for the simulation at NLO accuracy of the hard-scattering processes of Z bosonproduction and decay into the electron, muon, and \u03c4 -lepton channels. It was interfaced toPythia 8.186 [71] for the modelling of the PS, hadronisation, and underlying event, withparameters set according to the AZNLO tune [72]. The CT10nlo PDF set [73] was usedfor the hard-scattering processes, whereas the CTEQ6L1 PDF set [74] was used for thePS. The effect of QED final-state radiation was simulated with Photos++ 3.52 [75, 76].The production ofW+jets events was generated with Sherpa 2.2.1 [77]. In this set-up,NLO-accurate matrix elements for up to two partons and LO-accurate matrix elements forup to four partons were calculated with the Comix [78] and OpenLoops [79\u201381] libraries.The default Sherpa PS [82] based on Catani-Seymour dipole factorisation and the cluster2The hdamp parameter is a resummation damping factor and one of the parameters that controls thematching of Powheg matrix elements to the PS and thus effectively regulates the high-pT radiation againstwhich the tt\u00af system recoils.\u2013 6 \u2013JHEP10(2023)001Process Generator PDF set Tune NormalisationME PS ME PSLQ\u2192 b\u03c4 MadGraph5_aMC@NLO Pythia 8.244 NNPDF3.0nnlo NNPDF2.3lo A14 LOScalar LQLQ\u2192 b\u03c4b\u03c4 MadGraph5_aMC@NLO Pythia 8.230 NNPDF3.0nnlo NNPDF2.3lo A14 NNLO + NNLLVector LQLQ\u2192 b\u03c4b\u03c4 MadGraph5_aMC@NLO Pythia 8.244 NNPDF3.0nnlo NNPDF2.3lo A14 LOtt\u00af PowhegBox v2 Pythia 8.230 NNPDF3.0nnlo NNPDF2.3lo A14 NNLO + NNLLSingle top PowhegBox v2 Pythia 8.230 NNPDF3.0nnlo NNPDF2.3lo A14 NLOZ\/\u03b3\u2217 PowhegBox v1 Pythia 8.186 CT10nlo CTEQ6L1 AZNLO NLOW+jets Sherpa 2.2.1 NNPDF3.0nnlo Sherpa NNLODiboson Sherpa 2.2.1\/Sherpa 2.2.2 NNPDF3.0nnlo Sherpa NLOTable 1. Overview of the MC generators used for the main signal and background samples. Thelast column specifies the order in QCD for the cross-section calculation used for the normalisationof the simulated samples.hadronisation model [83] were used. They employed the dedicated set of tuned parametersdeveloped by the Sherpa authors and the NNPDF3.0nnlo PDF set [58]. The NLOmatrix elements for a given jet multiplicity were matched to the PS using a colour-exactvariant of the MC@NLO algorithm [84]. Different jet multiplicities were then merged intoan inclusive sample using an improved CKKWmatching procedure [85, 86] that is extendedto NLO accuracy using the MEPS@NLO prescription [87].Diboson production was simulated with the Sherpa 2.2.1 or 2.2.2 generator dependingon the process. Fully leptonic final states and semileptonic final states, where one bosondecays leptonically and the other hadronically, were generated using matrix elements atNLO accuracy in QCD for up to one additional parton emission and at LO accuracy for upto three additional parton emissions. Samples for the loop-induced processes gg \u2192 V V weregenerated using LO-accurate matrix elements for up to one additional parton emission forboth the fully leptonic and semileptonic final states. The matrix element calculations werematched and merged with the Sherpa PS based on Catani-Seymour dipole factorisationusing the MEPS@NLO prescription. The virtual QCD corrections were provided by theOpenLoops library. The NNPDF3.0nnlo set of PDFs were used, along with thededicated set of tuned PS parameters developed by the Sherpa authors. The sampleswere normalised to a NLO prediction.A summary of all the features used for the simulation of the signal and backgroundprocesses is shown in table 1. In all samples except those produced with Sherpa 2.2.1or Sherpa 2.2.2, decays of heavy-flavour hadrons were modelled with EvtGen 1.2.0 orEvtGen 1.6.0 program [88], depending on the process. All samples of simulated eventswere processed through the ATLAS detector simulation [89] based on Geant4 [90]. Theeffects of multiple interactions in the same and nearby bunch crossings (pile-up) weremodelled by overlaying minimum-bias events simulated using the soft QCD processes ofPythia 8.186 [71] with the A3 tune [91] and the NNPDF2.3lo PDF set.4 Object reconstruction and identificationTracks measured in the ID are used to reconstruct the interaction vertices [92]. The primaryvertex of the hard interaction is chosen as the proton-proton vertex candidate with thehighest sum of the squared transverse momenta of the associated tracks.\u2013 7 \u2013JHEP10(2023)001Electrons are reconstructed from topological clusters of energy deposits in the elec-tromagnetic calorimeter that are matched to a track reconstructed in the ID [93]. In the\u03c4lep\u03c4had (\u03c4had\u03c4had) final state, the selected (rejected) electrons are required to satisfy the\u2018medium\u2019 (\u2018loose\u2019) identification criteria and have pT > 20GeV (15GeV). Moreover, elec-trons are required to be within |\u03b7cluster| = 2.47 with the exclusion of the region betweenthe barrel and endcap calorimeters (1.37 < |\u03b7cluster| < 1.52). An additional \u2018loose\u2019 iso-lation criterion [93] is also required, which has an efficiency of 90% for candidates withpT > 15GeV, increasing to more than 98% for candidates with pT > 30GeV.Muons are reconstructed from signals in the MS matched with tracks inside the ID. Inthe \u03c4lep\u03c4had final state, the selected muons are required to satisfy the \u2018medium\u2019 identificationcriteria with an average efficiency of 97%, and have pT > 25GeV and |\u03b7| < 2.5. Inthe \u03c4had\u03c4had chanel, muons having pT > 7GeV are rejected if they satisfy the \u2018loose\u2019identification criteria. A \u2018tight\u2019 isolation criterion [94] based on track information andhaving an average efficiency of 89% is also applied.Jets are reconstructed with a particle-flow algorithm, which combines energy depositsin the calorimeter with ID tracks [95], using the anti-kt algorithm [96, 97] with a radiusparameter R = 0.4. Only jets with |\u03b7| < 2.5 and pT > 25GeV are considered. The \u2018tight\u2019working point of the jet vertex tagger (JVT) [98] algorithm is selected to remove jets withpT < 60GeV and |\u03b7| < 2.4 that are identified as not being associated with the primaryvertex of the hard interaction. Jets containing b-hadrons are identified using the DL1rb-tagging algorithm [99, 100]. A 70% efficiency working point is used, with the efficienciesbeing measured in simulated tt\u00af events. The corresponding rejection factors (defined as thereciprocal of the efficiency values) for b-tagged jets initiated by c-quarks and light partonsare 9.4 and 390 respectively.The \u03c4had decays are composed of a neutrino and a set of visible decay products, mostfrequently one or three charged pions and up to two neutral pions. The visible decay prod-ucts of the \u03c4had decay are denoted by \u03c4had-vis. The reconstruction of the \u03c4had-vis is seeded byjets reconstructed by the anti-kt algorithm [96], using calibrated topological clusters [101]as inputs, with a radius parameter of R = 0.4 [102]. Reconstructed tracks are matched to\u03c4had-vis candidates and a multivariate discriminant is used to assess whether these tracksare likely to have been produced by the charged \u03c4had decay products, rejecting tracks origi-nating from other interactions, nearby jets, photon conversions or misreconstructed tracks.The \u03c4had-vis objects are required to have one or three associated charged-particle tracks se-lected by this discriminant. Their charge (q) is defined as the sum of the measured electriccharges of these associated tracks and is required to be |q| = 1. The \u03c4had-vis objects arealso required to satisfy pT > 20GeV and |\u03b7| < 2.5, excluding the region 1.37 < |\u03b7| < 1.52.To separate the \u03c4had-vis candidates produced by hadronic \u03c4 -lepton decays from those dueto jets initiated by quarks or gluons, a recurrent neural network (RNN) identification algo-rithm [103] (\u03c4had-ID) is constructed using information from reconstructed charged-particletracks and calorimeter-energy clusters associated with \u03c4had-vis candidates. This analysisuses two \u03c4had-ID working points: \u2018medium\u2019, which has a 75% (60%) acceptance efficiencyand a background rejection of 35 (240) and \u2018loose\u2019, which has a 85% (75%) acceptanceefficiency and a background rejection of 21 (90) for \u03c4had with one (three) charged-particle\u2013 8 \u2013JHEP10(2023)001Object to keep Object to remove CriteriaElectron Electron If they share the same track, the electron with thehighest transverse momentum is kept.Electron \u03c4had-vis If \u2206R < 0.2, the electron is kept.Muon \u03c4had-vis If \u2206R < 0.2, the muon is kept.Muon Electron If they share a track, the electron is removed ifthe muon is associated with a signature in the MS,otherwise the muon is removed.Electron Jet Any jet within \u2206R = 0.2 of an electron is removed.Muon Jet Any jet within \u2206R = 0.2 of a muon is removed ifit has fewer than three associated tracks.Jet Electron Any electron within \u2206R = 0.4 of a jet is removed.Jet Muon Any muon within \u2206R = 0.4 of a jet is removed.\u03c4had-vis Jet Any jet within \u2206R = 0.2 of a \u03c4had-vis is removed.Table 2. Criteria applied to overlapping reconstructed objects. The criteria are listed in the orderthey are applied.tracks. A \u2018very loose\u2019 working point, having a 95% acceptance efficiency, is also used forbackground estimation. A separate boosted decision tree discriminant (\u2018eBDT\u2019) is alsoused to reject backgrounds arising from electrons misidentified as \u03c4had-vis. This discrimi-nant is built using information from the calorimeter and the ID, most notably transitionradiation information from the TRT system and variables sensitive to the ratio of theenergy deposited in the calorimeter to the visible momentum measured from the recon-structed tracks.The reconstructed objects used in this analysis are not built from disjoint sets of tracksor calorimetric clusters. It is therefore possible that two different objects share most oftheir constituents. An overlap removal procedure is applied to resolve this ambiguity. Thisprocedure is summarised in table 2.The missing transverse momentum vector, E\u20d7missT , is reconstructed as the negative vec-tor sum of the transverse momenta of leptons, \u03c4had-vis and jets, and a \u201csoft-term\u201d [104].The soft-term is calculated as the vectorial sum of the p\u20d7T of tracks matched to the primaryvertex but not associated with a reconstructed lepton, \u03c4had-vis or jet. The magnitude ofE\u20d7missT is referred to as the missing transverse energy, EmissT .5 Event selectionEvents are required to contain at least one primary vertex with at least two associatedtracks.For the \u03c4lep\u03c4had channel events were selected by single-lepton triggers. In 2015 single-electron triggers were simultaneously active with pT thresholds of 24, 60 and 120GeV [105].For data from 2016 onward the pT thresholds are 26, 60 and 140GeV. Similarly to thesingle-electron triggers, the single-muon triggers had pT thresholds of 20 and 50GeV for\u2013 9 \u2013JHEP10(2023)0012015, and 26 and 50GeV from 2016 [106]. The trigger thresholds were raised to keep thetrigger rates sufficiently low as the luminosity was increased. The lowest pT thresholdelectron and muon triggers also have an isolation requirement. The lepton isolation andidentification requirements loosen as the trigger pT thresholds increase. Events must con-tain at least one \u03c4had candidate and exactly one electron or one muon. The electron ormuon must be isolated and satisfy the medium lepton identification. Events with morethan one lepton satisfying the medium identification are rejected, considering electrons(muons) with a pT greater than 15 (7)GeV. This helps to reject Z\/\u03b3\u2217 \u2192 ee\/\u00b5\u00b5 eventsand Z\/\u03b3\u2217 \u2192 \u03c4lep\u03c4lep. Furthermore, the electron and muon candidates are required to havepT > 30GeV, and be matched to the trigger object that caused the event to be selected.The \u03c4had candidate is required to have pT > 50GeV, satisfy the medium \u03c4had-ID selectionand have |\u03b7| < 2.3. The pseudorapidity selection requirement rejects events with \u03c4had can-didates in a region with a higher background contamination and large uncertainties in thedetermination of the rate of electrons misidentified as \u03c4had.In the \u03c4had\u03c4had channel, events were selected by a single \u03c4had trigger [107]. For 2015 and2016, three single \u03c4had triggers were available with pT thresholds of 80, 125 and 160GeV.In 2017 and 2018, due to higher instantaneous luminosity, only the pT > 160GeV triggerthreshold was used. The \u03c4had identification requirements become less stringent as thetrigger pT thresholds rise. Events must contain at least two \u03c4had candidates where theleading \u03c4had candidate in pT must be matched to the trigger within an angular distance of\u2206R = 0.2 and have pT that is at least 5GeV above the trigger threshold. The subleading-pT \u03c4had candidate is required to have pT > 65GeV. Identification requirements are appliedto both \u03c4had candidates; the leading-pT \u03c4had must satisfy the medium selection and thesubleading-pT \u03c4had the loose selection. Events that contain any electron or muon thatsatisfies the loose identification requirements are rejected, which ensures orthogonality tothe \u03c4lep\u03c4had channel.Events passing the previous requirements are then selected with criteria that are similarbetween the two channels. The two \u03c4had or the electron\/muon (denoted by \u2113) and \u03c4hadmust have opposite electric charges and at least one b-tagged jet is required. The invariantmass of the visible decay products of the two \u03c4 -leptons, mvis(\u2113, \u03c4had) or mvis(\u03c4had, \u03c4had), isrequired to be above 100GeV, which is effective at reducing the Z\/\u03b3\u2217 \u2192 \u03c4\u03c4 background.An additional requirement \u2206\u03d5(\u2113, EmissT ) < 1.5 is applied in the \u03c4lep\u03c4had channel to reducesingle top and tt\u00af events.The variable ST is defined as the scalar pT sum of the two \u03c4had-vis (or \u2113 and \u03c4had-vis)and the leading-pT b-jet. A minimum requirement of ST > 300GeV is applied, as there isalmost no improvement in the expected results of the analysis, discussed in section 8, byadding events with lower ST values.The selection criteria described above define the signal region (SR) of the analysis.The signal acceptance times efficiency of the event selection varies between 3% and 10%,depending on the LQ mass and coupling. The efficiency is defined as the ratio of eventspassing the selection in each channel with respect to the signal events of the b\u03c4lep\u03c4hadand b\u03c4had\u03c4had final states, respectively. Events in the SR of each channel are assignedto two categories of low (< 200GeV) and high (> 200GeV) transverse momentum of the\u2013 10 \u2013JHEP10(2023)001\u03c4lep\u03c4had Signal Regions SelectionSR \u2113 (trigger, isolated), \u03c4had-vis (medium \u03c4had-ID), q(\u2113)\u00d7 q(\u03c4had-vis) < 0,\u2206\u03d5(\u2113, EmissT ) < 1.5, mvis(\u2113, \u03c4had-vis) > 100GeV, ST > 300GeV,at least one b-jetHigh b-jet pT SR SR selection, leading b-jet pT > 200GeVLow b-jet pT SR SR selection, leading b-jet pT < 200GeV\u03c4had\u03c4had Signal Regions SelectionSR \u03c41 (trigger, medium \u03c4had-ID), \u03c42 (loose \u03c4had-ID), q(\u03c41)\u00d7 q(\u03c42) < 0, mvis(\u03c41, \u03c42) > 100GeV,ST > 300GeV, at least one b-jetHigh b-jet pT SR SR selection, leading b-jet pT > 200GeVLow b-jet pT SR SR selection, leading b-jet pT < 200GeVTable 3. Definition of signal regions (SR) used in the \u03c4lep\u03c4had and \u03c4had\u03c4had channel. The symbol\u2113 represents the selected electron or muon candidate and \u03c4had-vis represents the leading \u03c4had-viscandidate. The symbol \u03c41 (\u03c42) represents the leading (sub-leading) \u03c4had-vis candidate.leading-pT b-jet. The two categories are called high and low b-jet pT SRs, respectively. Thehigh b-jet pT SR is found to perform better for low-mass singly produced LQs, where theresonant contribution is dominant. Conversely, the low b-jet pT SR has a better acceptancefor high mass signals, where the non-resonant contribution is dominant for signals withmLQ \u2265 0.9TeV. This split into two categories improves the expected results of the analysis,discussed in section 8, by up to 30%.Alternative selections define the control regions (CR), used to evaluate the contributionof the main background processes in the SR, and the validation regions (VR), used to verifythe good modelling of the backgrounds. The selection requirements used for the signalregions are summarised in table 3. The use of the control and validation regions in thebackground estimation methods is discussed in section 6.6 Background estimation6.1 \u03c4lep\u03c4had channelControl and validation regions are used in the analysis to estimate and study the modellingof the main background processes. The selection requirements used for the CR and VR inthe \u03c4lep\u03c4had channel are summarised in table 4.In the \u03c4lep\u03c4had channel the dominant background contributions are from tt\u00af and singletop-quark events. Processes involving top quarks can produce real \u03c4 -leptons, or jets that aremisidentified as \u03c4had, and are estimated by using simulation with data-driven corrections.The tt\u00af and tW contributions are treated as one combined top-quark background due totheir similar kinematics and final states. In the low (high) b-jet pT SR, tt\u00af accounts for 90%(86%) of all top-quark processes and 96% (97%) of the single top-quarks are from tW . Toensure that this background is accurately modelled, a top-quark control region (Top-CR) isdefined. With respect to the SR selection, the requirements on the leading b-jet pT and theST are removed, and the condition \u2206\u03d5(\u2113, EmissT ) < 1.5 is replaced by \u2206\u03d5(\u2113, EmissT ) > 2.5.This results in a region with a purity of 91% in top-quark processes and negligible signalcontamination. Out of all top-quark events in the Top-CR, 91% are from tt\u00af processes and\u2013 11 \u2013JHEP10(2023)001\u03c4lep\u03c4had Control\/Validation Selection PurposeRegionsMultijet-CR \u2113 (trigger, pass\/fail offline isolation), mT(\u2113, EmissT ) < 30GeV, Measure leptonone b-jet, \u03c4had-ID score < 0.01, EmissT < 50GeV fake-factorTop-CR Satisfy SR except: \u2206\u03d5(\u2113, EmissT ) > 2.5, no ST and lead. b-jet pT req. Derive top correctionSS-CR Satisfy SR except: q(\u2113)\u00d7 q(\u03c4had-vis) > 0, no \u2206\u03d5(\u2113, EmissT ), Measure jet\u2192 \u03c4 backgroundand ST req. scale factorHigh b-jet pT VR Satisfy high b-jet pT SR except: 1.5 < \u2206\u03d5(\u2113, EmissT ) < 2.5, Background modelling validation300GeV < ST < 600GeVLow b-jet pT VR Satisfy low b-jet pT SR except: 1.5 < \u2206\u03d5(\u2113, EmissT ) < 2.5, Background modelling validation300GeV < ST < 600GeVb-jet Z-CR Satisfy SR except: 45GeV < mvis(\u2113, \u03c4had-vis) < 80GeV, Z+heavy-flavour jetspT(\u2113)\/pT(b-jet) > 0.8, |\u2206\u03d5(\u2113, \u03c4had-vis)| > 2.4, no ST req. normalisation factorTable 4. Definition of the background-enriched control regions (CR) and validation regions (VR)used in the \u03c4lep\u03c4had channel. The symbol \u2113 represents the selected electron or muon candidate and\u03c4had-vis represents the leading \u03c4had-vis candidate.\u223c97% of the single top-quark events are from tW , which is compatible with the compositionof the SRs.A discrepancy between the data and simulation prediction is observed in the Top-CR,with the simulation overestimating the background contribution. Recent measurements ofdifferential cross-sections have demonstrated that the current simulations of tt\u00af processesoverestimate the upper tail of the top-quark pT spectrum [108, 109]. The discrepancyvaries depending on ST; for this reason, a correction is derived as a function of ST in thisregion based on the ratio between data and simulation. A top-quark correction scale factoris defined in eq. (6.1) and is applied to all tt\u00af and single top-quark simulated events. Thecomparison between data and the background prediction in the Top-CR and the derivedcorrection as a function of ST are shown in figure 2, where tt\u00af and tW events with agenerated lepton reconstructed as a lepton (a \u2018true\u2019 lepton) and a jet misidentified as a\u03c4had are included under the Jet\u2192 \u03c4 fake contribution. This demonstrates that the Top-CRis dominated by tt\u00af and tW events with true leptons and \u03c4had in the final state, thus thiscorrection does not account for mismodelling due to jets being misidentified as \u03c4had. Themodelling of events with a true lepton and jet misidentified as a \u03c4had in the final state isdiscussed later in this section.The top-quark correction scale factor is defined as a function of ST:SFTop(ST) =(Ndata \u2212Nnon-Top)(ST)NTop(ST), (6.1)where Ndata and NTop represent respectively the number of data events and of tt\u00af plussingle top-quark events predicted by simulation, NTop includes events with both true andmisidentified \u03c4had in the final state and Nnon-Top includes all the other backgrounds es-timated by using simulation. The resulting correction is well fitted by a linear function,which is used to derive the correction scale factors. The correction is also derived withan alternative logarithmic function: SFTop(ST) = a ln(ST) + b, and the difference betweenthe two corrections is taken as an uncertainty on the correction. Additional uncertaintiesrelated to the cross-section and acceptance of the top-quark processes, as well as the sta-\u2013 12 \u2013JHEP10(2023)001200 400 600 800 1000 [GeV]TS0.60.811.21.4TopData - Non-Top110210310410510610  EventsDatatttW fake\u03c4\u2192JetOthersUncertaintyATLAS-1=13 TeV, 139 fbshad\u03c4lep\u03c4Pre-Fit, Top-CR(a)200 400 600 800 1000 [GeV]TS0.60.811.21.4Data\/Pred. 110210310410510610  EventsDatatttW fake\u03c4\u2192JetOthersUncertaintyATLAS-1=13 TeV, 139 fbshad\u03c4lep\u03c4Pre-Fit, Top-CR corrected(b)Figure 2. (a) Comparison between data and the background prediction for the ST distributionin the Top-CR in the \u03c4lep\u03c4had channel. The tt\u00af and tW contributions only include events with trueleptons and \u03c4had in the final state. The label Jet\u2192 \u03c4 fake corresponds to events with a leptonand a quark- or gluon-initiated jet misidentified as \u03c4had; this contribution is estimated by usingsimulation. The bottom panel shows the ratio of the data to the prediction where the uncertaintyshown by both the points and hatched band includes the statistical uncertainty in the data andbackground predictions, the theoretical uncertainty in the MC simulation predictions, and the MCsubtraction uncertainty. Finally, the line and the cross dashed band show the resulting fit and theassociated uncertainty. The label \u2018Top\u2019 in the bottom panel denotes the sum of tt\u00af and tW processes,while \u2018Non-Top\u2019 refers to all other processes considered. Entries with values above the x-axis rangeare included in the last bin of the distribution. (b) Shows the same distribution after the top-quarkcorrection scale factor is applied to the tt\u00af and tW simulated events. Only the uncertainty associatedto the top-quark correction and the statistical uncertainty on data and simulation are considered.tistical and cross-section uncertainties related to the subtraction of the contribution fromthe other processes, are applied to account for the slight difference between the fractionsof top-quark events that are due to tt\u00af production in the Top-CR and SRs and for theextrapolation to the SR. The scale factor is applied at the per-event level to the tt\u00af plussingle top-quark events passing the selections of the signal, control or validation regions.The total uncertainty in the scale factor varies between 4% and 7% for ST in the rangeof 300\u2013700GeV. Different binning choices for the ST distribution were also considered,but the impact on the SFTop(ST) uncertainty is found to be below 5% and therefore notconsidered as an additional source of uncertainty.Another source of background in the \u03c4lep \u03c4had channel stems from multi-jet events,where jets can mimic both the \u03c4lep and \u03c4had. This type of background from multi-jet eventsis estimated via a data-driven fake-factor method by deriving a lepton fake-factor. Thelepton fake-factor is measured in the multi-jet control region (multijet-CR) that is enrichedin multi-jet events, but is similar kinematically to the SR. The events are still requiredto satisfy the single lepton trigger and to have exactly one b-jet, but the identificationalgorithm to reject jets misidentified as \u03c4had is instead used to select multi-jet events by\u2013 13 \u2013JHEP10(2023)001requiring an extremely low value for \u03c4had RNN identification score (corresponding to only1% acceptance for true \u03c4had). Additional selection criteria on mT(\u2113, EmissT ) < 30GeV andEmissT < 50GeV are applied to increase the purity of multi-jet events relative to otherbackgrounds. The fake-factor is measured with a requirement on the leading b-jet pT >25GeV and is defined as:FFlep(pT(\u03c4lep), \u03b7(\u03c4lep)) =(Ndata \u2212NMC)pass-iso(pT(\u03c4lep), \u03b7(\u03c4lep))(Ndata \u2212NMC)fail-iso(pT(\u03c4lep), \u03b7(\u03c4lep)).The variable Ndata is the total number of data events and NMC is the number ofbackground events predicted by simulation that contain a true \u03c4lep. Events are split betweenthe numerator and denominator based on whether the \u03c4lep satisfied the lepton isolationrequirement or not. The fake-factor is parameterised as a function of the \u03c4lep pT and splitinto central (|\u03b7| < 1.52) and forward (|\u03b7| > 1.52) regions. The statistical uncertaintyon the FFlep(pT(\u03c4lep), \u03b7(\u03c4lep)) fake-factor and simulation-related uncertainties on NMC areconsidered as systematic uncertainties and propagated to the estimate of the multi-jetbackground. The uncertainties are in the range of 6\u2013230% as a function of the \u03c4had-vis\u03b7 and pT. A control region is defined by having the same selection as the SR, exceptthat the lepton isolation requirement inverted. Applying the fake-factor at the per-eventlevel, the multi-jet estimate in each SR is then obtained by scaling the distribution in thecorresponding control region where the isolation criteria are not satisfied.An additional source of background are events where a lepton is produced in associationwith a jet that is misidentified as a \u03c4had (Jet \u2192 \u03c4 fake). These contribute approximately20% to the expected background in the SR and are mostly from tt\u00af with contributions fromW+jets, Z+jets, and diboson events. To ensure that these are well modelled, a \u2018same-sign\u2019 control region (SS-CR) is defined by taking the same selection as the SR, but witha light lepton with the same electric charge as \u03c4had. The requirements on \u2206\u03d5(\u2113, EmissT ),ST and the leading b-jet pT are removed to increase the number of events in the CR. Thetop-quark correction scale factor derived in eq. (6.1) is applied to top-quark events in thisregion (approximately 81% of the total). As the Top-CR used to derive that scale factor isdominated by tt\u00af and tW events with true \u03c4 -leptons in the final state, it does not correct formismodelling of jets that are misidentified as a \u03c4had. As a difference between the simulationprediction and the data is still observed, another scale factor is derived to account forany remaining differences from those backgrounds with a lepton and misidentified \u03c4had(approximately 60% of the events in this region). The remaining events contain true \u03c4hadand are subtracted, before calculating the scale factor, by applying the top-quark correctionscale factor. Then, the scale factor for events with a lepton and a jet misidentified as a\u03c4had is defined as:SFfake-\u03c4 (pT(\u03c4had-vis), ntrack) =(Ndata \u2212Ntrue-\u03c4 )(pT(\u03c4had-vis), ntrack)Nfake-\u03c4 (pT(\u03c4had-vis), ntrack),where Ntrue-\u03c4 is the total number of events predicted by simulation where both the \u03c4hadand \u03c4lep are true and Nfake-\u03c4 is the number of predicted events with a jet misidentifiedas a \u03c4had and a true \u03c4lep. The scale factor is parameterised as a function of pT(\u03c4had-vis)\u2013 14 \u2013JHEP10(2023)001and the number of charged-particle tracks (ntrack). It is applied to any MC backgroundevent with a true lepton and a jet misidentified as a \u03c4had. The correction is derived inthe SS-CR of the \u03c4\u00b5\u03c4had channel and then applied to both \u03c4e\u03c4had and \u03c4\u00b5\u03c4had, because the\u03c4e\u03c4had SS-CR contains events with misidentified electrons, which are not well modelled bysimulation. The SFfake-\u03c4 correction values are in the range of 1\u20131.2 (1\u20131.5) for \u03c4had withone (three) charged-particle tracks. The statistical uncertainty on the SFfake-\u03c4 correctionand the simulation-related uncertainties affecting Ntrue-\u03c4 and Nfake-\u03c4 are propagated tothe background estimate as systematic uncertainties. As a function of the \u03c4had-vis pT,the uncertainties amount to 15\u201320% (22\u2013140%) for \u03c4had-vis candidates with one (three)associated charged-particle track.To validate the background modelling in a region depleted in signal, high and lowb-jet pT validation regions (high and low b-jet pT VR) are defined by applying the SRrequirements, with the exceptions of the \u2206\u03d5(\u2113, EmissT ) < 1.5 and the ST > 300GeV criteria,that are modified into 1.5 < \u2206\u03d5(\u2113, EmissT ) < 2.5 and 300 < ST < 600GeV. The low (high)b-jet pT VR consists of 82% (80%) tt\u00af events, of 8% (10%) single top-quark events, and of9% (9%) of events where a jet is misidentified as a \u03c4had. Good modelling of the backgroundis found in the validation regions; the background estimate agrees with data within thetotal uncertainty, as shown in figure 3.6.2 \u03c4had\u03c4had channelIn the \u03c4had\u03c4had channel, the main background sources are Z\/\u03b3\u2217 \u2192 \u03c4had\u03c4had events, as wellas top-quark processes, with W bosons decaying to \u03c4had, or to electrons, muons or jetsmisidentified as \u03c4had. Both Z\/\u03b3\u2217 \u2192 \u03c4had\u03c4had and top-quark backgrounds are estimatedusing simulation with data-driven corrections, which are discussed further below. The se-lection requirements used to define the CR and VR in the \u03c4had\u03c4had channel are summarisedin table 5.As the mismodelling of the kinematic distributions observed in the \u03c4lep\u03c4had channeloriginates from the underlying top-quark process rather than the \u03c4had decay, it is alsoexpected to be present in the \u03c4had\u03c4had channel. However, due to small number of events inthe \u03c4had\u03c4had channel the statistical uncertainty in the top-quark processes is comparablewith the expected mismodelling. This makes it difficult to select a \u03c4had\u03c4had-only controlregion to quantify this mismodelling. Therefore, the ST-dependent top-quark correctionscale factor from eq. (6.1) derived in the \u03c4lep\u03c4had channel is also applied to the \u03c4had\u03c4hadchannel. The shape of the ST distribution is checked and found to be compatible betweenthe \u03c4lep\u03c4had and \u03c4had\u03c4had channels.The Z\/\u03b3\u2217 \u2192 \u03c4had\u03c4had background is also modelled using simulation. Due to a knowndiscrepancy in the simulation compared with the data for Z(\u2192 \u03c4\u03c4)+ heavy-flavour jetswith at least one b- or c-jet (Z+HF) [110], a correction factor for the normalisation ofthis background is derived in the \u03c4lep \u03c4had b-jet Z-CR, defined in table 4, which has apurity of around 60% for the Z+HF processes and is inclusive in pT of the leading b-jet.A comparison between the data and the prediction from the simulation in the b-jet Z-CRbefore deriving the correction factor is shown in figure 4.\u2013 15 \u2013JHEP10(2023)00150 100 150 200 250 300) [GeV]\u03c4(Tp0.60.811.21.4Data\/Pred. 110210310410510  EventsDatatttW fake\u03c4\u2192JetOthersUncertaintyATLAS-1=13 TeV, 139 fbshad\u03c4lep\u03c4Post-Fit,  VRTLow b-jet p(a)300 350 400 450 500 550 600 [GeV]TS0.60.811.21.4Data\/Pred. 110210310410510  EventsDatatttW fake\u03c4\u2192JetOthersUncertaintyATLAS-1=13 TeV, 139 fbshad\u03c4lep\u03c4Post-Fit,  VRTLow b-jet p(b)50 100 150 200 250 300) [GeV]\u03c4(Tp0.60.811.21.4Data\/Pred. 110210310410  EventsDatatttW fake\u03c4\u2192JetOthersUncertaintyATLAS-1=13 TeV, 139 fbshad\u03c4lep\u03c4Post-Fit,  VRTHigh b-jet p(c)300 350 400 450 500 550 600 [GeV]TS0.60.811.21.4Data\/Pred. 110210310410  EventsDatatttW fake\u03c4\u2192JetOthersUncertaintyATLAS-1=13 TeV, 139 fbshad\u03c4lep\u03c4Post-Fit,  VRTHigh b-jet p(d)Figure 3. Comparison between data and the background prediction for the \u03c4lep \u03c4had channelvalidation regions after applying the scale factors discussed in section 6.1. (a) and (b) show thepT(\u03c4) and ST respectively for the low b-jet pT category, (c) and (d) show the same for the high b-jetpT category. The uncertainty band includes both statistical and systematic uncertainties evaluatedin the fit described in section 8. Entries with values above the x-axis range are included in the lastbin of each distribution. The lower panels show the ratio of the data to the predictions.The scale factor is derived by subtracting backgrounds estimated from simulation thatare not from the Z+HF process (Nnon\u2212ZHF):SFZHF =Ndata \u2212Nnon\u2212ZHFNZHF,where NZHF is the number of Z+HF events predicted by simulation.\u2013 16 \u2013JHEP10(2023)001\u03c4had\u03c4had Control\/Validation Selection PurposeRegionsDijet-CR Satisfy SR except: \u03c41 and \u03c42 satisfy very loose \u03c4had-ID, Measure \u03c4had-vis fake-factor\u03c41 fail medium \u03c4had-IDCR-1 Satisfy SR except: \u03c42 fail loose \u03c4had-ID Apply \u03c4had-vis fake-factorSS-VR Satisfy SR except: q(\u03c41)\u00d7 q(\u03c42) > 0 Multijet modelling checkZ+light flavour jets VR Satisfy SR except: 0 b-jets, \u2206\u03d5(\u03c41, \u03c42) > 0.25, Z+light jetsmvis(\u03c41, \u03c42) < 100GeV, EmissT > 60GeV modellingTable 5. Definition of the background-enriched control regions (CR) and validation regions (VR)used in the \u03c4had\u03c4had channel. The symbol \u03c41 (\u03c42) represents the leading (sub-leading) \u03c4had-viscandidate.80 90 100 110 120 130 140 150 [GeV]TS0.511.5Data\/Pred.00.511.5310\u00d7  EventsData)+HF\u03c4\u03c4\u2192*(\u03b3\/ZtttW fake\u03c4\u2192JetOthersUncertaintyATLAS-1=13 TeV, 139 fbshad\u03c4lep\u03c4Pre-Fit, b-tag Z-CRFigure 4. Comparison between data and the background prediction for the ST distribution in thecontrol region used for correcting the Z(\u2192 \u03c4\u03c4)+ heavy-flavour jets process. The uncertainty bandincludes both statistical and systematic components. Entries with values above the x-axis rangeare included in the last bin of the distribution. The lower panel shows the ratio of the data to thepredictions.The scale factor is applied as a normalisation to the total Z+HF contribution, witha value of 1.13 \u00b1 0.23 obtained from the control region. The uncertainty includes thestatistical uncertainty, the uncertainty in the subtraction of the simulation events and theextrapolation uncertainty from the control region to the SRs. The extrapolation uncer-tainty is obtained by repeating the scale factor calculation in the \u03c4lep\u03c4had channel usingselection criteria for the control and signal regions equivalent to the ones used in the\u03c4had\u03c4had channel.For Z(\u2192 \u03c4\u03c4)+ light-flavour jets (Z+LF, no b- or c-jets), the modelling is validated ina b-veto region (Z+LF VR). This region has the same event selection as the SR, except thatzero b-jets are required. In addition, the requirements mvis < 100GeV, EmissT > 60GeVand \u2206\u03d5(\u03c4, \u03c4) > 0.25 are applied to ensure a high Z+LF purity. The data is found to be inagreement with the simulation within the statistical uncertainty in the data.\u2013 17 \u2013JHEP10(2023)001Finally the background originating from multi-jet events, where jets are misidentifiedas \u03c4had, is estimated by using a data-driven fake-factor method. A control region domi-nated by multi-jet events, called Dijet-CR, is defined by taking events that satisfy one ofthe single-jet triggers (with thresholds between 15 and 420GeV). The leading \u03c4had-vis can-didate is required to not satisfy the medium \u03c4had identification and the subleading \u03c4had-viscandidate is used as a probe. Both \u03c4had-vis candidates are still required to pass the veryloose \u03c4had identification requirement. As for the \u03c4lep\u03c4had channel, the fake-factor is mea-sured inclusively in the leading b-jet pT. The leading and subleading \u03c4had-vis candidatesare required to have opposite electric charges and have a pT > 65GeV. At least one addi-tional b-tagged jet is required, but no selection is made on the leading b-jet pT. Then, thefake-factor is defined as:f\u03c4had-ID(pT, Ntrack) \u2261(Ndata \u2212NMC)pass \u03c4had-ID(pT, Ntrack)(Ndata \u2212NMC)fail \u03c4had-ID(pT, Ntrack)\u2223\u2223\u2223\u2223\u2223dijet,where NMC includes all simulated background events. The pass or fail \u03c4had-ID superscriptrefers to whether the subleading \u03c4had-vis candidate satisfies the loose \u03c4had-ID or not, whilestill satisfying the very loose requirement. For each of the SRs, the multi-jet estimate isthen obtained from the a control region, called CR-1, composed of events in which thesubleading \u03c4had-vis candidate fails the loose \u03c4had-ID, using the fake-factor:Nmulti-jet(pT, Ntrack) = f\u03c4had-ID(pT, Ntrack)\u00d7 (Ndata \u2212NMC)fail \u03c4had-ID(pT, Ntrack).The fake-factor is parameterised as a function of the pT and number of charged-particle tracks of the subleading \u03c4had-vis candidate. The statistical uncertainty on thef\u03c4had-ID(pT, Ntrack) fake-factor is considered as systematic uncertainty, and it varies in therange of 4\u201315% as a function of the \u03c4had-vis pT, for \u03c4had-vis candidates with both one andthree associated charged-particle tracks. For this method to be accurate, it is importantthat the fail-\u03c4had-ID and multi-jet control regions have a similar composition of quark- andgluon-initiated jets. This is obtained by inspecting the shape of subleading \u03c4had identi-fication scores in the two regions, which depends on the quark-gluon fraction. A lowerthreshold than the very loose requirement is applied on this score, which ensures that theshapes of the distributions are compatible.After the selection, the multi-jet contribution to the SR is expected to be small. Themodelling of the multi-jet background is verified in the same-sign validation regions (SS-VR). The SS-VR has the same selection as the SR, but the electric charges of the \u03c4hadcandidates are required to be the same. For key distributions in the low b-jet pT category,the data is found to agree with the background prediction, with approximately half of theevents being from tt\u00af and half from multi-jet background. The selection in the high b-jetpT SS-VR leads to low statistics with 2.8 expected events (mostly from tt\u00af) and 4 observeddata events.7 Systematic uncertaintiesSystematic uncertainties arise from the reconstruction of the various physics objects andfrom theoretical or modelling uncertainties affecting the predictions for both the back-\u2013 18 \u2013JHEP10(2023)001grounds and signals. These uncertainties manifest themselves in both the overall yield andshape of the final observable, and can be divided into two main groups: the experimentaluncertainties and the modelling uncertainties.The experimental uncertainties include the uncertainties related to the trigger, re-construction, calibration and identification of electrons [93], muons [94], taus [102] andjets [98, 99, 111]; for electron and muons, additional uncertainties in the lepton isola-tion are considered. Uncertainties related to background with misidentified \u03c4 -leptons aredescribed in section 6. Another source of experimental uncertainties is given by the lu-minosity measurement, whose primary measurement is obtained using the LUCID-2 de-tector [112]. An uncertainty value of 1.7% [113] is assigned for the combined 2015\u20132018integrated luminosity.Among the experimental uncertainties, the ones with the highest impact on the analysissensitivity are the \u03c4had-vis related uncertainties, with an impact on the results in the rangeof 30\u201340% depending on the LQ coupling and mass values considered. The uncertainties inthe \u03c4had-vis identification efficiency are in the range of 2% to 6%, while the eBDT efficiencyuncertainties are of the order of 1% to 2%. These uncertainties are parameterised as afunction of the \u03c4had-vis pT and the number of associated tracks for the \u03c4had-vis identificationefficiency, and as a function of the \u03c4had decay mode for the eBDT efficiency. In both cases,the uncertainties are derived in dedicated tag and probe measurements [102]. The \u03c4had-visreconstruction efficiency uncertainty is derived from comparisons between simulations usingdifferent detector geometries or Geant4 physics lists; this uncertainty is parameterisedas a function of true \u03c4had-vis pT and is between 1% and 1.5%. For the \u03c4had-vis energyscale, the total uncertainty is in the range of 1% to 4% of the \u03c4had-vis pT, arising from acombination of measurements: a direct measurement with Z \u2192 \u03c4\u03c4 \u2192 \u00b5\u03c4had-vis+3 \u03bd events,measurements of the calorimeter response to single particles, and comparisons betweensimulations using different detector geometries or Geant4 physics lists. This uncertaintyis also parameterised as a function of the \u03c4had-vis pT and the number of associated tracks.The uncertainties in the background modelling include uncertainties in the top-quark,Z+jets and diboson backgrounds, as well as multijet events in which quark- or gluon-initiated jets are misidentified as a \u03c4had. Among the background modelling uncertainties,the ones related to the top-quark background have the largest impact on the analysis sensi-tivity, with an impact on the results in the range of 40\u201350% depending on the LQ couplingand mass values. This uncertainty is extracted by comparing nominal and alternative tt\u00afand single top-quark MC samples in the phase space of the SR and Top-CR. For eachsample, a dedicated data-driven ST-dependent correction is applied before the comparison.The difference between the nominal and alternative samples in the ST distribution is takenas the uncertainty in the top-quark processes. The alternative samples have variations ofthe initial\/final-state radiation, matrix element and PS compared to the nominal sample.To derive the initial\/final-state radiation uncertainty, the generator parameters used toproduce the nominal samples are varied. The matrix element to PS NLO matching uncer-tainty is derived by comparing the MadGraph5_aMC@NLO and Powheg predictionswhile keeping the same generator for the PS component. For the PS, the uncertainty isderived by a comparison with an alternative sample generated by using Herwig for the\u2013 19 \u2013JHEP10(2023)001PS while keeping the same generator for the hard-scattering simulation component. Theuncertainties in the background modelling originating from the PDF and \u03b1S uncertain-ties are found to be less than 1% and are neglected. Finally, an uncertainty in the tWinterference for the single top-quark background is estimated by comparing the nominalsample, where the diagram removal scheme is applied, to an alternative sample that usesthe diagram subtraction scheme [114].The uncertainties in the signal modelling include those from the signal cross-sectionand acceptance due to renormalisation scale (\u00b5R) and factorisation scale (\u00b5F ) variations,PDF and \u03b1S . The \u00b5R and \u00b5F uncertainties are estimated through an envelope of thevariations obtained from scaling \u00b5R and \u00b5F by a factor between 0.5 and 2, while keepingtheir ratio between 0.5 and 2. The uncertainties due to the NNPDF3.0nlo PDF setand \u03b1S are evaluated following the PDF4LHC recommendation [115].8 ResultsThe distribution of the ST variable for the events of the signal regions defined in table 3for the \u03c4lep\u03c4had and \u03c4had\u03c4had channels, is used as final discriminant between the leptoquarksignal and the background. The statistical analysis of the data is performed using the profilelikelihood ratio method [116], to test whether a model can be rejected given the observeddata. As the model under test is a signal plus background hypothesis, the chosen parameterof interest is the signal strength, \u00b5, defined as the ratio of the observed to the predictedvalue of the signal cross-section times branching fraction. The likelihood function L(\u00b5, \u03b8) isthen constructed as a product of Poisson probability terms for each bin of the distributions.It depends on \u00b5 and on the nuisance parameters \u03b8, which encode systematic uncertaintiesthat can affect the signal and background distributions and are constrained using Gaussianprobability density functions. The asymptotic approximation is used when constructingthe test statistic q\u02dcu [117] from the likelihood ratio, defined as q\u02dc\u00b5 = \u22122 ln(L(\u00b5, \u02c6\u02c6\u03b8)\/L(\u00b5\u02c6, \u03b8\u02c6))where \u00b5\u02c6 and \u03b8\u02c6 are the parameters that define the global maximum-likelihood function and\u02c6\u02c6\u03b8 are the nuisance parameters that give the maximum likelihood for a given value of \u00b5.To ensure a reliable estimation of the backgrounds in the fit model, the binning in STis optimised so that sufficient background events (greater than 10) are present in eachbin of the pre-fit distribution. No significant excess above the background expectations isobserved and corresponding limits on production cross-sections of the LQ signals are set.For the LQ results interpretation, only the high b-jet pT signal regions from the \u03c4lep\u03c4hadand \u03c4had\u03c4had channels are considered and fit simultaneously. For the high b-jet pT signalregions, the contribution from the non-resonant LQ production process is small. There-fore the interference between the LQ non-resonant processes and the SM processes is notexpected to be substantial in these SRs, and it is neglected. By setting \u00b5 = 0 in theprofile likelihood ratio, the test statistic can be used to check for compatibility with thebackground-only hypothesis. The data are first fit under the background-only hypothesisand the resulting post-fit distributions are found to be in good agreement with the data,as shown in figure 5. Table 6 shows the yields for the \u03c4lep\u03c4had and \u03c4had\u03c4had channels,respectively.\u2013 20 \u2013JHEP10(2023)001400 600 800 1000 [GeV]TS0.60.811.21.4Data\/Pred.110210310410  EventsDatatttW fake\u03c4\u2192JetOthersUncertainty)=1.0\u03bb0.9 TeV (1S~10\u00d7) =1.0\u03bb1.6 TeV (YM1U10\u00d7) =1.0\u03bb1.6 TeV (MIN1UATLAS-1=13 TeV, 139 fbshad\u03c4lep\u03c4Post-Fit,  SRTHigh b-jet p(a)300 400 500 600 700 800 900 1000 [GeV]TS0.511.5Data\/Pred.110210310410  EventsDatatttW fake\u03c4\u2192Two Jet)+HF\u03c4\u03c4\u2192*(\u03b3\/Z fake\u03c4\u2192JetOthersUncertainty)=1.0\u03bb0.9 TeV (1S~10\u00d7) =1.0\u03bb1.6 TeV (YM1U10\u00d7) =1.0\u03bb1.6 TeV (MIN1UATLAS-1=13 TeV, 139 fbshad\u03c4had\u03c4Post-Fit,  SRTHigh b-jet p(b)Figure 5. Post-fit distributions of the discriminating variable ST in the high b-jet pT signalregion for the (a) \u03c4lep\u03c4had and (b) \u03c4had\u03c4had channels. The two channels are fit simultaneouslyconsidering the background-only hypothesis. The lower panels show the ratio of the data to thepredictions, where the uncertainty band includes both statistical and systematic post-fit errors.Entries with values above the x-axis range are included in the last bin of each distribution. Forillustrative purposes, the dotted lines show the expectation from three singly produced scalar andvector LQ signals.Process \u03c4lep\u03c4had \u03c4had\u03c4hadtt\u00af 764 \u00b1 82 9.9 \u00b1 2.6Single top 65 \u00b1 35 3.9 \u00b1 1.0Jet\u2192 \u03c4 fake 215 \u00b1 79 3.9 \u00b1 1.0Two jet\u2192 \u03c4 fake \u2014 1.34\u00b1 0.27Z(\u2192 \u03c4\u03c4)+HF jets 5.5\u00b1 0.4 4.6 \u00b1 1.1Others 9.7\u00b1 1.0 1.75\u00b1 0.30Total 1059 \u00b1 51 25.4 \u00b1 4.9Data 1053 29Table 6. Post-fit background yields in the high b-jet pT signal region of \u03c4lep\u03c4had and \u03c4had\u03c4hadchannels. \u2018Jet\u2192 \u03c4 fake\u2019 indicates the events with a true lepton and a quark- or gluon-initiated jetmisidentified as a \u03c4had. The \u2018Two jet\u2192 \u03c4 fake\u2019 indicates the events where two jets are misidentifiedas \u03c4had. \u2018Others\u2019 in \u03c4lep\u03c4had includes Z(\u2192 \u03c4\u03c4)+LF jets, diboson, W+jets and Z(\u2192 ee, \u00b5\u00b5)+jetswhile \u2018Others\u2019 in \u03c4had\u03c4had includes Z(\u2192 \u03c4\u03c4)+LF jets, diboson and W+jets. The results are ex-tracted from a fit assuming the background-only hypothesis.As good agreement is found between the data and the background expectation, upperlimits are set on the cross-section assuming that the branching fraction B(LQ \u2192 b\u03c4) is100% in the case of the S\u02dc1 model and 50% for the UYM1 and UMIN1 scenarios. This isperformed using the frequentist CLs method [116]. A production cross-section for a givensignal scenario is excluded at the 95% confidence level (CL) when CLs < 0.05.\u2013 21 \u2013JHEP10(2023)001500 1000 1500 2000 2500 [GeV]YM1Um4\u2212103\u2212102\u2212101\u221210110210310 [pb]vectortot\u03c3  ATLAS-1=13 TeV, 139 fbs95% CL onlyTHigh b-jet pInterference with SM neglectedObs. limitExp. limit\u03c3 1\u00b1Exp. \u03c3 2\u00b1Exp. theorytot,vector\u03c3=1.0\u03bb, YM1U      (a)500 1000 1500 2000 2500 [GeV]YM1Um4\u2212103\u2212102\u2212101\u221210110210310 [pb]vectortot\u03c3  ATLAS-1=13 TeV, 139 fbs95% CL onlyTHigh b-jet pInterference with SM neglectedObs. limitExp. limit\u03c3 1\u00b1Exp. \u03c3 2\u00b1Exp. theorytot,vector\u03c3=1.7\u03bb, YM1U      (b)500 1000 1500 2000 2500 [GeV]YM1Um4\u2212103\u2212102\u2212101\u221210110210310 [pb]vectortot\u03c3  ATLAS-1=13 TeV, 139 fbs95% CL onlyTHigh b-jet pInterference with SM neglectedObs. limitExp. limit\u03c3 1\u00b1Exp. \u03c3 2\u00b1Exp. theorytot,vector\u03c3=2.5\u03bb, YM1U      (c)500 1000 1500 2000 2500 [GeV]MIN1Um4\u2212103\u2212102\u2212101\u221210110210 [pb]vectortot\u03c3  ATLAS-1=13 TeV, 139 fbs95% CL onlyTHigh b-jet pInterference with SM neglectedObs. limitExp. limit\u03c3 1\u00b1Exp. \u03c3 2\u00b1Exp. theorytot,vector\u03c3=1.0\u03bb, MIN1U      (d)500 1000 1500 2000 2500 [GeV]MIN1Um4\u2212103\u2212102\u2212101\u221210110210 [pb]vectortot\u03c3  ATLAS-1=13 TeV, 139 fbs95% CL onlyTHigh b-jet pInterference with SM neglectedObs. limitExp. limit\u03c3 1\u00b1Exp. \u03c3 2\u00b1Exp. theorytot,vector\u03c3=1.7\u03bb, MIN1U      (e)500 1000 1500 2000 2500 [GeV]MIN1Um4\u2212103\u2212102\u2212101\u221210110210310 [pb]vectortot\u03c3  ATLAS-1=13 TeV, 139 fbs95% CL onlyTHigh b-jet pInterference with SM neglectedObs. limitExp. limit\u03c3 1\u00b1Exp. \u03c3 2\u00b1Exp. theorytot,vector\u03c3=2.5\u03bb, MIN1U      (f)Figure 6. Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of single plus non-resonant plus pair vector LQ production from the combination of thehigh b-jet pT signal region for the \u03c4lep\u03c4had and \u03c4had\u03c4had channels. The dotted curve indicates thetotal theoretical predictions for singly, non-resonant and pair-produced vector LQ at LO. The toprow shows the UYM1 model (\u03ba = 0) with (a) \u03bb = 1.0, (b) \u03bb = 1.7 and (c) \u03bb = 2.5. The bottom rowshows the UMIN1 model (\u03ba = 1) with (d) \u03bb = 1.0, (e) \u03bb = 1.7 and (f) \u03bb = 2.5. The interferenceof the non-resonant LQ production with SM processes is expected to be small in the high b-jet pTcategory and it is neglected.The results are interpreted considering all LQ production modes in the U1 model.Several values of the coupling \u03bb are considered, each one with a value of the couplingparameter \u03ba of 0 or 1. The exclusion limits for the single plus non-resonant plus pair vectorLQ production are shown in figure 6. The behaviour of the upper limits as a function ofmLQ reflects the signal acceptance times efficiency of the analysis. Figure 7 shows thevector LQ limits in the \u03bb\u2212mLQ plane for each of the \u03ba coupling values considered.The same procedure is used to interpret the results for single, non-resonant and pairproduction of scalar LQs from the S\u02dc1 model. The single S\u02dc1 production and the combinedsingle plus non-resonant plus pair S\u02dc1 production are considered. The 95% CLs limits on theS\u02dc1 production cross-section are derived as a function of LQ mass for various assumptionson the coupling \u03bb value. The single plus non-resonant plus pair S\u02dc1 production result isshown in figure 8. The exclusion limits in the \u03bb\u2212mLQ plane are shown in figure 9.The observed and expected limits on the LQ mass for the various signal productionmodes considered are reported in table 7. This analysis is the first ATLAS result for the\u2013 22 \u2013JHEP10(2023)0011000 1500 2000 2500 3000 [GeV]YM1Um00.511.522.533.54   \u03bbCoupling   ATLAS-1=13 TeV, 139 fbs95% CL onlyT model, High b-jet pYM1UInterference with SM neglected)\u03c3 1\u00b1Single + Non-res. (Obs.limit )\u03c3 1\u00b1Single + Non-res. (Exp.limit )\u03c3 1\u00b1Total (Obs.limit )\u03c3 1\u00b1Total (Exp.limit Preferred by B anomaliesExcluded region(a)1000 1500 2000 2500 3000 [GeV]MIN1Um00.511.522.533.54   \u03bbCoupling   ATLAS-1=13 TeV, 139 fbs95% CL onlyT model, High b-jet pMIN1UInterference with SM neglected)\u03c3 1\u00b1Single + Non-res. (Obs.limit )\u03c3 1\u00b1Single + Non-res. (Exp.limit )\u03c3 1\u00b1Total (Obs.limit )\u03c3 1\u00b1Total (Exp.limit Preferred by B anomaliesExcluded region(b)Figure 7. The two-dimensional 95% CL exclusion limits in the \u03bb \u2212 mLQ plane for singly plusnon-resonant produced vector LQ (green lines) and for the sum, referred as Total, of single plusnon-resonant plus pair vector LQ production (blue lines), with (a) showing the case with \u03ba = 0and (b) the case with \u03ba = 1. Regions to the left of the lines are excluded. The dotted area showsthe preferred region where the chosen LQ model can explain observed B anomalies [118]. Theinterference of the non-resonant LQ production with SM processes is expected to be small in thehigh b-jet pT category and it is neglected.500 1000 1500 [GeV]1S~m4\u2212103\u2212102\u2212101\u221210110210 [pb]scalartot\u03c3  ATLAS-1=13 TeV, 139 fbs95% CL onlyTHigh b-jet pInterference with SM neglectedObs. limitExp. limit\u03c3 1\u00b1Exp. \u03c3 2\u00b1Exp. theorytot,scalar\u03c3=1.0\u03bb , 1S~      (a)500 1000 1500 [GeV]1S~m4\u2212103\u2212102\u2212101\u221210110210 [pb]scalartot\u03c3  ATLAS-1=13 TeV, 139 fbs95% CL onlyTHigh b-jet pInterference with SM neglectedObs. limitExp. limit\u03c3 1\u00b1Exp. \u03c3 2\u00b1Exp. theorytot,scalar\u03c3=1.7\u03bb , 1S~      (b)500 1000 1500 [GeV]1S~m4\u2212103\u2212102\u2212101\u221210110210310 [pb]scalartot\u03c3  ATLAS-1=13 TeV, 139 fbs95% CL onlyTHigh b-jet pInterference with SM neglectedObs. limitExp. limit\u03c3 1\u00b1Exp. \u03c3 2\u00b1Exp. theorytot,scalar\u03c3=2.5\u03bb , 1S~      (c)Figure 8. Observed (solid line) and expected (dashed line) 95% CL upper limits for (a) \u03bb = 1.0,(b) \u03bb = 1.7 and (c) \u03bb = 2.5 on the cross-section of single plus non-resonant plus pair S\u02dc1 productionhypotheses from the combination of the high b-jet pT signal region for the \u03c4lep\u03c4had and \u03c4had\u03c4hadchannels. The dotted curve indicates the total theoretical predictions for singly, non-resonant andpair-produced scalar LQ. The prediction for singly plus non-resonant produced S\u02dc1 (pair-producedS\u02dc1) is calculated at LO (NNLO+NNLL). The interference of the non-resonant LQ production withSM processes is expected to be small in the high b-jet pT category and it is neglected.search of singly produced LQs in the b\u03c4\u03c4 final state. Vector LQs in the U1 Yang-Mills(Minimal coupling) model are excluded below masses of 1.56 (1.29) TeV for all \u03bb values; S\u02dc1masses below 1.26TeV are excluded for all \u03bb values. The observed limits obtained are lessstringent than the expected limits, which is mostly driven by the higher data yields relativeto the predicted yields in the highest ST bin in the \u03c4had\u03c4had channel. Overall the \u03c4had\u03c4had\u2013 23 \u2013JHEP10(2023)001600 800 1000 1200 1400 1600 1800 2000 2200 [GeV]1S~m00.511.522.533.54   \u03bbCoupling   ATLAS-1=13 TeV, 139 fbs95% CL onlyT model, High b-jet p1S~Interference with SM neglected)\u03c3 1\u00b1Single + Non-res. (Obs.limit )\u03c3 1\u00b1Single + Non-res. (Exp.limit )\u03c3 1\u00b1Total (Obs.limit )\u03c3 1\u00b1Total (Exp.limit Excluded regionFigure 9. The two-dimensional 95% CL exclusion limits in the \u03bb\u2212mLQ plane for singly plus non-resonant produced S\u02dc1 (green lines) and for the sum, referred as Total, of single plus non-resonantplus pair vector LQ production (blue lines). Regions to the left of the lines are excluded. Theinterference of the non-resonant LQ production with SM processes is expected to be small in thehigh b-jet pT category and it is neglected.Model \u03bb = 1.0 \u03bb = 1.7 \u03bb = 2.5Single+non-resonant UYM1 production 1.31 (1.43) 1.59 (1.73) 2.03 (2.27)Single+non-resonant UMIN1 production 1.15 (1.24) 1.45 (1.58) 1.98 (2.26)Single+non-resonant+pair UYM1 production 1.58 (1.64) 1.70 (1.81) 2.05 (2.28)Single+non-resonant+pair UMIN1 production 1.35 (1.44) 1.52 (1.63) 1.99 (2.26)Single+non-resonant S\u02dc1 production 1.04 (1.11) 1.26 (1.38) 1.49 (1.62)Single+non-resonant+pair S\u02dc1 production 1.28 (1.37) 1.38 (1.49) 1.53 (1.67)Table 7. Observed (expected) 95% lower limits on the LQ mass in high b-jet pT signal region forthe singly plus non-resonant and singly plus non-resonant plus pair produced LQs. All limits arereported in TeV.channel is more sensitive than the \u03c4lep\u03c4had channel due to the smaller background and thelarger signal to background ratio in the last ST bin. This difference arises from the largertt\u00af background for the b\u03c4lep\u03c4had final state in the most sensitive part of the ST spectrum.An additional model-independent search considering both the high and low b-jet pTsignal regions in the \u03c4lep\u03c4had and \u03c4had\u03c4had channels is performed. For each of these regions,the events with ST < 600GeV form a sideband region, while a signal region is definedby counting the number of events with a ST value above a variable threshold. First thefour sideband regions, one for each channel and for each b-jet pT signal region, are fitsimultaneously considering the background-only hypothesis. Then, the fit results are usedto scale the predicted background contribution in the signal regions. In each signal region,the signal is obtained by counting the number of observed data events after subtracting\u2013 24 \u2013JHEP10(2023)001the background prediction. Figure 10 shows the post-fit distributions of the ST variable inthe sideband region and the background composition in each channel as a function of theST lower bound threshold used to define the signal regions.Since no significant excess is observed in any of the signal regions, a signal-plus-background fit is performed considering a generic signal in the signal region. As for the LQssearch, the parameter of interest of the statistical analysis is the signal strength \u00b5, and theresults are translated into upper limits on the number of signal events and, dividing themby the integrated luminosity, they can be expressed in terms of upper limits on the visiblecross-section, \u03c3vis. Figure 11 shows the limit values of the visible cross-section as a func-tion of ST lower bound threshold in each signal category. The visible cross-section limitscan be reinterpreted as limits on specific physics models as long as the selection efficiencyand acceptance of the model (including any uncertainties in these values) for a specificsignal region definition used in this analysis is known. By dividing the visible cross-sectionlimits given here by this efficiency and acceptance, upper limits on the cross-section canbe derived.9 ConclusionA search for scalar and vector leptoquarks is performed in the b\u03c4\u03c4 final state using ppcollision data at\u221as = 13TeV recorded by the ATLAS detector at the LHC from 2015to 2018 corresponding to an integrated luminosity of 139 fb\u22121. Final states including oneleptonic and one hadronic \u03c4 -lepton decay or two hadronic \u03c4 -leptons decays are considered.In each of these two final states, events are classified, based on the pT of the b-jet, in twosignal regions of low and high b-jet pT. The benchmark model is U1 for vector leptoquarksin the Yang-Mills or Minimal coupling scenarios with \u03bb between 0.5 and 2.5. For scalarleptoquarks the benchmark model is S\u02dc1, with values of the \u03bb parameter ranging between0.5 and 2.5.Upper limits at 95% CL on the cross-section for leptoquarks produced via either singleplus non-resonant production, or considering all production modes (including pair pro-duction), and decaying into b\u03c4 are set. The results have been extracted considering onlythe high b-jet signal region and the combination of both final states. For the Yang-Millscoupling, the observed (expected) lower limits on the leptoquark mass are 1.58 (1.64) TeVfor \u03bb = 1.0, 1.70 (1.81) TeV for \u03bb = 1.7, and 2.05 (2.28) TeV for \u03bb = 2.5, considering allleptoquark production modes. In the Minimal coupling case, considering all leptoquarkproduction modes, the lower limits are 1.35 (1.44) TeV for \u03bb = 1.0, 1.52 (1.63) TeV for\u03bb = 1.7 and 1.99 (2.26) TeV for \u03bb = 2.5. The observed (expected) lower limits, consid-ering all leptoquark production modes in the S\u02dc1 model, are 1.28 (1.37) TeV for \u03bb = 1.0,1.38 (1.49) TeV for \u03bb = 1.7 and 1.53 (1.67) TeV for \u03bb = 2.5.An interpretation of the results in a model-independent scenario is also performed foreach of the signal region categories. The 95% confidence level limits on the visible cross-section vary between 0.17 fb and 4.8 \u00b710\u22122 fb as a function of the event variable ST rangingfrom ST > 600GeV to ST > 950GeV.\u2013 25 \u2013JHEP10(2023)001300-350350-400400-450450-500500-550550-600300-350350-400400-450450-500500-550550-600300-350350-400400-450450-500500-600300-600 [GeV]TS0.511.5Data\/Pred.110210310410510610  EventsDatatttW)+HF\u03c4\u03c4\u2192*(\u03b3\/Z fake\u03c4\u2192Two Jet fake\u03c4\u2192JetOthersUncertaintyATLAS-1=13 TeV, 139 fbsPost-Fit sidebandshad\u03c4lep\u03c4TLow b-jet phad\u03c4lep\u03c4THigh b-jet phad\u03c4had\u03c4TLow b-jet phad\u03c4had\u03c4THigh b-jet p(a)>600>650>700>600>650>700>750>800>850>900>950>600>600 [GeV]TS0.511.5Data\/Pred.110210310410510  EventsDatatttW)+HF\u03c4\u03c4\u2192*(\u03b3\/Z fake\u03c4\u2192Two Jet fake\u03c4\u2192JetOthersUncertaintyATLAS-1=13 TeV, 139 fbsPost-Fit SRshad\u03c4lep\u03c4TLow b-jet phad\u03c4lep\u03c4THigh b-jet phad\u03c4had\u03c4TLow b-jet phad\u03c4had\u03c4THigh b-jet p(b)Figure 10. (a) Post-fit distributions of the discriminating variable ST in the sideband regions forthe high and low b-jet pT signal regions for the \u03c4lep\u03c4had and \u03c4had\u03c4had channels. The distributions arefit simultaneously considering the background-only hypothesis. (b) Observed and predicted yieldsof the background as a function of the ST threshold used to define the signal regions for the highand low b-jet pT signal regions of the \u03c4lep\u03c4had and \u03c4had\u03c4had channels. The background predictionsin the signal regions have been extracted by projecting the results from the fit of the sidebandregions, assuming the background-only hypothesis in the context of the model-independent search.The lower panel shows the ratio of the data to the background predictions.\u2013 26 \u2013JHEP10(2023)001>600>650>700>600>650>700>750>800>850>900>950>600>600 [GeV]TS2\u2212101\u221210110) limit [fb]vis\u03c3Cross-section (ATLAS-1 = 13 TeV, 139.0 fbs95% CLhad\u03c4lep\u03c4TLow b-jet phad\u03c4lep\u03c4THigh b-jet phad\u03c4had\u03c4TLow b-jet phad\u03c4had\u03c4THigh b-jet pObs. limit Exp. limit\u03c3 1\u00b1Exp. \u03c3 2\u00b1Exp. Figure 11. Observed (solid line) and expected (dashed line) 95% upper limits on the visible cross-section, \u03c3vis, obtained from the model-independent search by a signal-plus-background fit in thehigh and low b-jet pT signal regions for the \u03c4lep\u03c4had and \u03c4had\u03c4had channels.AcknowledgmentsWe thank CERN for the very successful operation of the LHC, as well as the support stafffrom our institutions without whom ATLAS could not be operated efficiently.We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Aus-tralia; 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, Ger-many; GSRI, Greece; RGC and Hong Kong SAR, China; ISF and Benoziyo Center, Is-rael; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, The Netherlands;RCN, Norway; MEiN, Poland; FCT, Portugal; MNE\/IFA, Romania; MESTD, Serbia;MSSR, Slovakia; ARRS and MIZ\u0160, Slovenia; DSI\/NRF, South Africa; MICINN, Spain;SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva,Switzerland; MOST, Taiwan; TENMAK, T\u00fcrkiye; STFC, United Kingdom; DOE andNSF, United States of America. In addition, individual groups and members have re-ceived support from BCKDF, CANARIE, Compute Canada and CRC, Canada; PRIMUS21\/SCI\/017 and UNCE SCI\/013, Czech Republic; COST, ERC, ERDF, Horizon 2020 andMarie Sk\u0142odowska-Curie Actions, European Union; Investissements d\u2019Avenir Labex, In-vestissements d\u2019Avenir Idex and ANR, France; DFG and AvH Foundation, Germany; Her-akleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF,Greece; BSF-NSF and MINERVA, Israel; Norwegian Financial Mechanism 2014\u20132021, Nor-way; NCN and NAWA, Poland; La Caixa Banking Foundation, CERCA Programme Gen-eralitat de Catalunya and PROMETEO and GenT Programmes Generalitat Valenciana,Spain; G\u00f6ran Gustafssons Stiftelse, Sweden; The Royal Society and Leverhulme Trust,United Kingdom.\u2013 27 \u2013JHEP10(2023)001The crucial computing support from all WLCG partners is acknowledged gratefully,in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF(Denmark, Norway, Sweden), CC-IN2P3 (France), KIT\/GridKA (Germany), INFN-CNAF(Italy), NL-T1 (The Netherlands), PIC (Spain), ASGC (Taiwan), RAL (U.K.) and BNL(U.S.A.), the Tier-2 facilities worldwide and large non-WLCG resource providers. Majorcontributors of computing resources are listed in ref. [119].Open Access. This article is distributed under the terms of the Creative CommonsAttribution License (CC-BY 4.0), which permits any use, distribution and reproduction inany medium, provided the original author(s) and source are credited.References[1] S. Dimopoulos and L. Susskind, Mass Without Scalars, Nucl. Phys. B 155 (1979) 237[INSPIRE].[2] S. Dimopoulos, Technicolored Signatures, Nucl. Phys. B 168 (1980) 69 [INSPIRE].[3] E. Farhi and L. Susskind, Technicolor, Phys. Rep. 74 (1981) 277 [INSPIRE].[4] B. Schrempp and F. Schrempp, Light leptoquarks, Phys. Lett. B 153 (1985) 101 [INSPIRE].[5] J.C. Pati and A. Salam, Unified Lepton-Hadron Symmetry and a Gauge Theory of theBasic Interactions, Phys. Rev. D 8 (1973) 1240 [INSPIRE].[6] J.C. Pati and A. Salam, Lepton Number as the Fourth Color, Phys. Rev. D 10 (1974) 275[INSPIRE].[7] H. Georgi and S.L. Glashow, Unity of All Elementary Particle Forces, Phys. Rev. Lett. 32(1974) 438 [INSPIRE].[8] BaBar collaboration, Evidence for an excess of B\u00af \u2192 D(\u2217)\u03c4\u2212\u03bd\u00af\u03c4 decays, Phys. Rev. Lett.109 (2012) 101802 [arXiv:1205.5442] [INSPIRE].[9] BaBar collaboration, Measurement of an Excess of B\u00af \u2192 D(\u2217)\u03c4\u2212\u03bd\u00af\u03c4 Decays and Implicationsfor Charged Higgs Bosons, Phys. Rev. D 88 (2013) 072012 [arXiv:1303.0571] [INSPIRE].[10] Belle collaboration, Measurement of the branching ratio of B\u00af \u2192 D(\u2217)\u03c4\u2212\u03bd\u00af\u03c4 relative toB\u00af \u2192 D(\u2217)\u2113\u2212\u03bd\u00af\u2113 decays with hadronic tagging at Belle, Phys. Rev. D 92 (2015) 072014[arXiv:1507.03233] [INSPIRE].[11] LHCb collaboration, Measurement of the ratio of branching fractionsB(B\u00af0 \u2192 D\u2217+\u03c4\u2212\u03bd\u00af\u03c4 )\/B(B\u00af0 \u2192 D\u2217+\u00b5\u2212\u03bd\u00af\u00b5), Phys. Rev. Lett. 115 (2015) 111803 [Erratum ibid.115 (2015) 159901] [arXiv:1506.08614] [INSPIRE].[12] Muon g \u2212 2 collaboration, Measurement of the Positive Muon Anomalous MagneticMoment to 0.46 ppm, Phys. Rev. Lett. 126 (2021) 141801 [arXiv:2104.03281] [INSPIRE].[13] S. Borsanyi et al., Leading hadronic contribution to the muon magnetic moment from latticeQCD, Nature 593 (2021) 51 [arXiv:2002.12347] [INSPIRE].[14] A. Greljo, P. Stangl and A.E. Thomsen, A model of muon anomalies, Phys. Lett. B 820(2021) 136554 [arXiv:2103.13991] [INSPIRE].[15] D. Buttazzo, A. Greljo, G. Isidori and D. Marzocca, B-physics anomalies: a guide tocombined explanations, JHEP 11 (2017) 044 [arXiv:1706.07808] [INSPIRE].\u2013 28 \u2013JHEP10(2023)001[16] ATLAS collaboration, The ATLAS Experiment at the CERN Large Hadron Collider, 2008JINST 3 S08003 [INSPIRE].[17] ATLAS IBL collaboration, Production and Integration of the ATLAS Insertable B-Layer,2018 JINST 13 T05008 [arXiv:1803.00844] [INSPIRE].[18] L. Evans and P. Bryant, LHC Machine, 2008 JINST 3 S08001 [INSPIRE].[19] M.J. Baker, J. Fuentes-Mart\u00edn, G. Isidori and M. K\u00f6nig, High-pT signatures invector-leptoquark models, Eur. Phys. J. C 79 (2019) 334 [arXiv:1901.10480] [INSPIRE].[20] W. Buchmuller, R. Ruckl and D. Wyler, Leptoquarks in Lepton-Quark Collisions, Phys.Lett. B 191 (1987) 442 [INSPIRE].[21] I. Dor\u0161ner, S. Fajfer, A. Greljo, J.F. Kamenik and N. Ko\u0161nik, Physics of leptoquarks inprecision experiments and at particle colliders, Phys. Rep. 641 (2016) 1[arXiv:1603.04993] [INSPIRE].[22] ATLAS collaboration, Search for a scalar partner of the top quark in the all-hadronic tt\u00afplus missing transverse momentum final state at\u221as = 13TeV with the ATLAS detector,Eur. Phys. J. C 80 (2020) 737 [arXiv:2004.14060] [INSPIRE].[23] ATLAS collaboration, Search for new phenomena in final states with b-jets and missingtransverse momentum in\u221as = 13TeV pp collisions with the ATLAS detector, JHEP 05(2021) 093 [arXiv:2101.12527] [INSPIRE].[24] ATLAS collaboration, Search for new phenomena in pp collisions in final states with tauleptons, b-jets, and missing transverse momentum with the ATLAS detector, Phys. Rev. D104 (2021) 112005 [arXiv:2108.07665] [INSPIRE].[25] ATLAS collaboration, Search for pairs of scalar leptoquarks decaying into quarks andelectrons or muons in\u221as = 13TeV pp collisions with the ATLAS detector, JHEP 10 (2020)112 [arXiv:2006.05872] [INSPIRE].[26] ATLAS collaboration, Search for pair production of third-generation scalar leptoquarksdecaying into a top quark and a \u03c4 -lepton in pp collisions at\u221as = 13TeV with the ATLASdetector, JHEP 06 (2021) 179 [arXiv:2101.11582] [INSPIRE].[27] ATLAS collaboration, Search for pair production of scalar leptoquarks decaying into first-or second-generation leptons and top quarks in proton-proton collisions at\u221as = 13TeVwith the ATLAS detector, Eur. Phys. J. C 81 (2021) 313 [arXiv:2010.02098] [INSPIRE].[28] ATLAS collaboration, Search for pair production of third-generation leptoquarks decayinginto a bottom quark and a \u03c4 -lepton with the ATLAS detector, arXiv:2303.01294 [INSPIRE].[29] CMS collaboration, Search for leptoquarks coupled to third-generation quarks inproton-proton collisions at\u221as = 13TeV, Phys. Rev. Lett. 121 (2018) 241802[arXiv:1809.05558] [INSPIRE].[30] CMS collaboration, Search for third-generation scalar leptoquarks decaying to a top quarkand a \u03c4 lepton at\u221as = 13TeV, Eur. Phys. J. C 78 (2018) 707 [arXiv:1803.02864][INSPIRE].[31] CMS collaboration, Search for dark matter in events with a leptoquark and missingtransverse momentum in proton-proton collisions at 13TeV, Phys. Lett. B 795 (2019) 76[arXiv:1811.10151] [INSPIRE].[32] CMS collaboration, Search for heavy neutrinos and third-generation leptoquarks in hadronicstates of two \u03c4 leptons and two jets in proton-proton collisions at\u221as = 13TeV, JHEP 03(2019) 170 [arXiv:1811.00806] [INSPIRE].\u2013 29 \u2013JHEP10(2023)001[33] CMS collaboration, Search for singly and pair-produced leptoquarks coupling tothird-generation fermions in proton-proton collisions at\u221as = 13TeV, Phys. Lett. B 819(2021) 136446 [arXiv:2012.04178] [INSPIRE].[34] ATLAS collaboration, Searches for third-generation scalar leptoquarks in\u221as = 13TeV ppcollisions with the ATLAS detector, JHEP 06 (2019) 144 [arXiv:1902.08103] [INSPIRE].[35] T. Mandal, S. Mitra and S. Raz, RD(\u2217) motivated S1 leptoquark scenarios: Impact ofinterference on the exclusion limits from LHC data, Phys. Rev. D 99 (2019) 055028[arXiv:1811.03561] [INSPIRE].[36] A. Bessaa and S. Davidson, Constraints on t-channel leptoquark exchange from LHCcontact interaction searches, Eur. Phys. J. C 75 (2015) 97 [arXiv:1409.2372] [INSPIRE].[37] ATLAS collaboration, ATLAS Insertable B-Layer: Technical Design Report,CERN-LHCC-2010-013 (2010) [ATLAS-TDR-19].[38] ATLAS collaboration, Performance of the ATLAS Trigger System in 2015, Eur. Phys. J.C 77 (2017) 317 [arXiv:1611.09661] [INSPIRE].[39] ATLAS collaboration, The ATLAS collaboration Software and Firmware,ATL-SOFT-PUB-2021-001 (2021).[40] ATLAS collaboration, ATLAS data quality operations and performance for 2015\u20132018data-taking, 2020 JINST 15 P04003 [arXiv:1911.04632] [INSPIRE].[41] J. Alwall et al., The automated computation of tree-level and next-to-leading orderdifferential cross sections, and their matching to parton shower simulations, JHEP 07(2014) 079 [arXiv:1405.0301] [INSPIRE].[42] NNPDF collaboration, Parton distributions with LHC data, Nucl. Phys. B 867 (2013) 244[arXiv:1207.1303] [INSPIRE].[43] T. Sj\u00f6strand et al., An introduction to PYTHIA 8.2, Comput. Phys. Commun. 191 (2015)159 [arXiv:1410.3012] [INSPIRE].[44] ATLAS collaboration, ATLAS Pythia 8 tunes to 7TeV data, ATL-PHYS-PUB-2014-021(2014).[45] I. Dor\u0161ner and A. Greljo, Leptoquark toolbox for precision collider studies, JHEP 05 (2018)126 [arXiv:1801.07641] [INSPIRE].[46] T. Mandal, S. Mitra and S. Seth, Pair Production of Scalar Leptoquarks at the LHC to NLOParton Shower Accuracy, Phys. Rev. D 93 (2016) 035018 [arXiv:1506.07369] [INSPIRE].[47] M. Kr\u00e4mer, T. Plehn, M. Spira and P.M. Zerwas, Pair production of scalar leptoquarks atthe CERN LHC, Phys. Rev. D 71 (2005) 057503 [hep-ph\/0411038] [INSPIRE].[48] M. Kr\u00e4mer, T. Plehn, M. Spira and P.M. Zerwas, Pair production of scalar leptoquarks atthe Tevatron, Phys. Rev. Lett. 79 (1997) 341 [hep-ph\/9704322] [INSPIRE].[49] W. Beenakker, C. Borschensky, M. Kr\u00e4mer, A. Kulesza and E. Laenen, NNLL-fast:predictions for coloured supersymmetric particle production at the LHC with threshold andCoulomb resummation, JHEP 12 (2016) 133 [arXiv:1607.07741] [INSPIRE].[50] W. Beenakker, M. Kr\u00e4mer, T. Plehn, M. Spira and P.M. Zerwas, Stop production at hadroncolliders, Nucl. Phys. B 515 (1998) 3 [hep-ph\/9710451] [INSPIRE].[51] W. Beenakker, S. Brensing, M. Kr\u00e4mer, A. Kulesza, E. Laenen and I. Niessen,Supersymmetric top and bottom squark production at hadron colliders, JHEP 08 (2010) 098[arXiv:1006.4771] [INSPIRE].\u2013 30 \u2013JHEP10(2023)001[52] W. Beenakker, C. Borschensky, R. Heger, M. Kr\u00e4mer, A. Kulesza and E. Laenen, NNLLresummation for stop pair-production at the LHC, JHEP 05 (2016) 153[arXiv:1601.02954] [INSPIRE].[53] C. Borschensky, B. Fuks, A. Kulesza and D. Schwartl\u00e4nder, Scalar leptoquark pairproduction at hadron colliders, Phys. Rev. D 101 (2020) 115017 [arXiv:2002.08971][INSPIRE].[54] S. Frixione, G. Ridolfi and P. Nason, A Positive-weight next-to-leading-order Monte Carlofor heavy flavour hadroproduction, JHEP 09 (2007) 126 [arXiv:0707.3088] [INSPIRE].[55] P. Nason, A New method for combining NLO QCD with shower Monte Carlo algorithms,JHEP 11 (2004) 040 [hep-ph\/0409146] [INSPIRE].[56] S. Frixione, P. Nason and C. Oleari, Matching NLO QCD computations with Parton Showersimulations: the POWHEG method, JHEP 11 (2007) 070 [arXiv:0709.2092] [INSPIRE].[57] S. Alioli, P. Nason, C. Oleari and E. Re, A general framework for implementing NLOcalculations in shower Monte Carlo programs: the POWHEG BOX, JHEP 06 (2010) 043[arXiv:1002.2581] [INSPIRE].[58] NNPDF collaboration, Parton distributions for the LHC Run II, JHEP 04 (2015) 040[arXiv:1410.8849] [INSPIRE].[59] ATLAS collaboration, Studies on top-quark Monte Carlo modelling for Top2016,ATL-PHYS-PUB-2016-020 (2016).[60] M. Beneke, P. Falgari, S. Klein and C. Schwinn, Hadronic top-quark pair production withNNLL threshold resummation, Nucl. Phys. B 855 (2012) 695 [arXiv:1109.1536] [INSPIRE].[61] M. Cacciari, M. Czakon, M. Mangano, A. Mitov and P. Nason, Top-pair production athadron colliders with next-to-next-to-leading logarithmic soft-gluon resummation, Phys.Lett. B 710 (2012) 612 [arXiv:1111.5869] [INSPIRE].[62] P. B\u00e4rnreuther, M. Czakon and A. Mitov, Percent Level Precision Physics at the Tevatron:First Genuine NNLO QCD Corrections to qq\u00af \u2192 tt\u00af+X, Phys. Rev. Lett. 109 (2012) 132001[arXiv:1204.5201] [INSPIRE].[63] M. Czakon and A. Mitov, NNLO corrections to top-pair production at hadron colliders: theall-fermionic scattering channels, JHEP 12 (2012) 054 [arXiv:1207.0236] [INSPIRE].[64] M. Czakon and A. Mitov, NNLO corrections to top pair production at hadron colliders: thequark-gluon reaction, JHEP 01 (2013) 080 [arXiv:1210.6832] [INSPIRE].[65] M. Czakon, P. Fiedler and A. Mitov, Total Top-Quark Pair-Production Cross Section atHadron Colliders Through O(\u03b14S), Phys. Rev. Lett. 110 (2013) 252004 [arXiv:1303.6254][INSPIRE].[66] M. Czakon and A. Mitov, Top++: A Program for the Calculation of the Top-PairCross-Section at Hadron Colliders, Comput. Phys. Commun. 185 (2014) 2930[arXiv:1112.5675] [INSPIRE].[67] M. Aliev, H. Lacker, U. Langenfeld, S. Moch, P. Uwer and M. Wiedermann, HATHOR:HAdronic Top and Heavy quarks crOss section calculatoR, Comput. Phys. Commun. 182(2011) 1034 [arXiv:1007.1327] [INSPIRE].[68] P. Kant et al., HatHor for single top-quark production: Updated predictions and uncertaintyestimates for single top-quark production in hadronic collisions, Comput. Phys. Commun.191 (2015) 74 [arXiv:1406.4403] [INSPIRE].\u2013 31 \u2013JHEP10(2023)001[69] S. Frixione, E. Laenen, P. Motylinski, C. White and B.R. Webber, Single-tophadroproduction in association with a W boson, JHEP 07 (2008) 029 [arXiv:0805.3067][INSPIRE].[70] S. Alioli, P. Nason, C. Oleari and E. Re, NLO vector-boson production matched with showerin POWHEG, JHEP 07 (2008) 060 [arXiv:0805.4802] [INSPIRE].[71] T. Sj\u00f6strand, S. Mrenna and P.Z. Skands, A Brief Introduction to PYTHIA 8.1, Comput.Phys. Commun. 178 (2008) 852 [arXiv:0710.3820] [INSPIRE].[72] ATLAS collaboration, Measurement of the Z\/\u03b3\u2217 boson transverse momentum distributionin pp collisions at\u221as = 7TeV with the ATLAS detector, JHEP 09 (2014) 145[arXiv:1406.3660] [INSPIRE].[73] H.-L. Lai et al., New parton distributions for collider physics, Phys. Rev. D 82 (2010)074024 [arXiv:1007.2241] [INSPIRE].[74] J. Pumplin et al., New generation of parton distributions with uncertainties from globalQCD analysis, JHEP 07 (2002) 012 [hep-ph\/0201195] [INSPIRE].[75] P. Golonka and Z. Was, PHOTOS Monte Carlo: A Precision tool for QED corrections in Zand W decays, Eur. Phys. J. C 45 (2006) 97 [hep-ph\/0506026] [INSPIRE].[76] N. Davidson, T. Przedzinski and Z. Was, PHOTOS interface in C++: Technical andPhysics Documentation, Comput. Phys. Commun. 199 (2016) 86 [arXiv:1011.0937][INSPIRE].[77] E. Bothmann et al., Event Generation with Sherpa 2.2, SciPost Phys. 7 (2019) 034[arXiv:1905.09127] [INSPIRE].[78] T. Gleisberg and S. H\u00f6che, Comix, a new matrix element generator, JHEP 12 (2008) 039[arXiv:0808.3674] [INSPIRE].[79] F. Buccioni et al., OpenLoops 2, Eur. Phys. J. C 79 (2019) 866 [arXiv:1907.13071][INSPIRE].[80] F. Cascioli, P. Maierh\u00f6fer and S. Pozzorini, Scattering Amplitudes with Open Loops, Phys.Rev. Lett. 108 (2012) 111601 [arXiv:1111.5206] [INSPIRE].[81] A. Denner, S. Dittmaier and L. Hofer, Collier: a fortran-based Complex One-Loop LIbraryin Extended Regularizations, Comput. Phys. Commun. 212 (2017) 220 [arXiv:1604.06792][INSPIRE].[82] S. Schumann and F. Krauss, A Parton shower algorithm based on Catani-Seymour dipolefactorisation, JHEP 03 (2008) 038 [arXiv:0709.1027] [INSPIRE].[83] J.-C. Winter, F. Krauss and G. Soff, A Modified cluster hadronization model, Eur. Phys. J.C 36 (2004) 381 [hep-ph\/0311085] [INSPIRE].[84] S. H\u00f6che, F. Krauss, M. Sch\u00f6nherr and F. Siegert, A critical appraisal of NLO+PSmatching methods, JHEP 09 (2012) 049 [arXiv:1111.1220] [INSPIRE].[85] S. Catani, F. Krauss, B.R. Webber and R. Kuhn, QCD matrix elements + parton showers,JHEP 11 (2001) 063 [hep-ph\/0109231] [INSPIRE].[86] S. H\u00f6che, F. Krauss, S. Schumann and F. Siegert, QCD matrix elements and truncatedshowers, JHEP 05 (2009) 053 [arXiv:0903.1219] [INSPIRE].[87] S. H\u00f6che, F. Krauss, M. Sch\u00f6nherr and F. Siegert, QCD matrix elements + parton showers:The NLO case, JHEP 04 (2013) 027 [arXiv:1207.5030] [INSPIRE].\u2013 32 \u2013JHEP10(2023)001[88] D.J. Lange, The EvtGen particle decay simulation package, Nucl. Instrum. Meth. A 462(2001) 152 [INSPIRE].[89] ATLAS collaboration, The ATLAS Simulation Infrastructure, Eur. Phys. J. C 70 (2010)823 [arXiv:1005.4568] [INSPIRE].[90] GEANT4 collaboration, GEANT4 \u2014 a simulation toolkit, Nucl. Instrum. Meth. A 506(2003) 250 [INSPIRE].[91] ATLAS collaboration, The Pythia 8 A3 tune description of ATLAS minimum bias andinelastic measurements incorporating the Donnachie-Landshoff diffractive model,ATL-PHYS-PUB-2016-017 (2016).[92] ATLAS collaboration, Vertex Reconstruction Performance of the ATLAS Detector at\u221as = 13TeV, ATL-PHYS-PUB-2015-026 (2015).[93] ATLAS collaboration, Electron and photon performance measurements with the ATLASdetector using the 2015\u20132017 LHC proton-proton collision data, 2019 JINST 14 P12006[arXiv:1908.00005] [INSPIRE].[94] ATLAS collaboration, Muon reconstruction and identification efficiency in ATLAS usingthe full Run 2 pp collision data set at\u221as = 13TeV, Eur. Phys. J. C 81 (2021) 578[arXiv:2012.00578] [INSPIRE].[95] ATLAS collaboration, Jet reconstruction and performance using particle flow with theATLAS Detector, Eur. Phys. J. C 77 (2017) 466 [arXiv:1703.10485] [INSPIRE].[96] M. Cacciari, G.P. Salam and G. Soyez, The anti-kt jet clustering algorithm, JHEP 04(2008) 063 [arXiv:0802.1189] [INSPIRE].[97] M. Cacciari, G.P. Salam and G. Soyez, FastJet User Manual, Eur. Phys. J. C 72 (2012)1896 [arXiv:1111.6097] [INSPIRE].[98] ATLAS collaboration, Performance of pile-up mitigation techniques for jets in pp collisionsat\u221as = 8TeV using the ATLAS detector, Eur. Phys. J. C 76 (2016) 581[arXiv:1510.03823] [INSPIRE].[99] ATLAS collaboration, ATLAS flavour-tagging algorithms for the LHC Run 2 pp collisiondataset, Eur. Phys. J. C 83 (2023) 681 [arXiv:2211.16345] [INSPIRE].[100] ATLAS collaboration, Optimisation and performance studies of the ATLAS b-taggingalgorithms for the 2017\u201318 LHC run, ATL-PHYS-PUB-2017-013 (2017).[101] ATLAS collaboration, Topological cell clustering in the ATLAS calorimeters and itsperformance in LHC Run 1, Eur. Phys. J. C 77 (2017) 490 [arXiv:1603.02934] [INSPIRE].[102] ATLAS collaboration, Measurement of the tau lepton reconstruction and identificationperformance in the ATLAS experiment using pp collisions at\u221as = 13TeV,ATLAS-CONF-2017-029 (2017).[103] ATLAS collaboration, Identification of hadronic tau lepton decays using neural networks inthe ATLAS experiment, ATL-PHYS-PUB-2019-033 (2019).[104] ATLAS collaboration, Performance of missing transverse momentum reconstruction withthe ATLAS detector using proton-proton collisions at\u221as = 13TeV, Eur. Phys. J. C 78(2018) 903 [arXiv:1802.08168] [INSPIRE].[105] ATLAS collaboration, Performance of electron and photon triggers in ATLAS during LHCRun 2, Eur. Phys. J. C 80 (2020) 47 [arXiv:1909.00761] [INSPIRE].\u2013 33 \u2013JHEP10(2023)001[106] ATLAS collaboration, Performance of the ATLAS muon triggers in Run 2, 2020 JINST15 P09015 [arXiv:2004.13447] [INSPIRE].[107] ATLAS collaboration, The ATLAS Tau Trigger in Run 2, ATLAS-CONF-2017-061 (2017).[108] ATLAS collaboration, Measurements of top-quark pair differential and double-differentialcross-sections in the \u2113+jets channel with pp collisions at\u221as = 13TeV using the ATLASdetector, Eur. Phys. J. C 79 (2019) 1028 [Erratum ibid. 80 (2020) 1092][arXiv:1908.07305] [INSPIRE].[109] ATLAS collaboration, Measurement of the tt\u00af production cross-section and leptondifferential distributions in e\u00b5 dilepton events from pp collisions at\u221as = 13TeV with theATLAS detector, Eur. Phys. J. C 80 (2020) 528 [arXiv:1910.08819] [INSPIRE].[110] ATLAS collaboration, ATLAS simulation of boson plus jets processes in Run 2,ATL-PHYS-PUB-2017-006 (2017).[111] ATLAS collaboration, Jet energy scale and resolution measured in proton-proton collisionsat\u221as = 13TeV with the ATLAS detector, Eur. Phys. J. C 81 (2021) 689[arXiv:2007.02645] [INSPIRE].[112] G. Avoni et al., The new LUCID-2 detector for luminosity measurement and monitoring inATLAS, 2018 JINST 13 P07017 [INSPIRE].[113] ATLAS collaboration, Luminosity determination in pp collisions at\u221as = 13TeV using theATLAS detector at the LHC, ATLAS-CONF-2019-021 (2019).[114] C.D. White, S. Frixione, E. Laenen and F. Maltoni, Isolating Wt production at the LHC,JHEP 11 (2009) 074 [arXiv:0908.0631] [INSPIRE].[115] J. Butterworth et al., PDF4LHC recommendations for LHC Run II, J. Phys. G 43 (2016)023001 [arXiv:1510.03865] [INSPIRE].[116] A.L. Read, Presentation of search results: The CLs technique, J. Phys. G 28 (2002) 2693[INSPIRE].[117] G. Cowan, K. Cranmer, E. Gross and O. Vitells, Asymptotic formulae for likelihood-basedtests of new physics, Eur. Phys. J. C 71 (2011) 1554 [Erratum ibid. 73 (2013) 2501][arXiv:1007.1727] [INSPIRE].[118] J. Aebischer, G. Isidori, M. Pesut, B.A. Stefanek and F. Wilsch, Confronting the vectorleptoquark hypothesis with new low- and high-energy data, Eur. Phys. J. C 83 (2023) 153[arXiv:2210.13422] [INSPIRE].[119] ATLAS collaboration, ATLAS Computing Acknowledgements, ATL-SOFT-PUB-2021-003(2021).\u2013 34 \u2013JHEP10(2023)001The ATLAS collaborationG. Aad 102, B. Abbott 120, K. Abeling 55, N.J. Abicht 49, S.H. Abidi 29,A. Aboulhorma 35e, H. Abramowicz 151, H. Abreu 150, Y. Abulaiti 117,A.C. Abusleme Hoffman 137a, B.S. Acharya 69a,69b,p, C. Adam Bourdarios 4,L. Adamczyk 85a, L. Adamek 155, S.V. Addepalli 26, M.J. Addison 101, J. Adelman 115,A. Adiguzel 21c, T. Adye 134, A.A. Affolder 136, Y. Afik 36, M.N. Agaras 13,J. Agarwala 73a,73b, A. Aggarwal 100, C. Agheorghiesei 27c, A. Ahmad 36,F. Ahmadov 38,ad, W.S. Ahmed 104, S. Ahuja 95, X. Ai 62a, G. Aielli 76a,76b,M. Ait Tamlihat 35e, B. Aitbenchikh 35a, I. Aizenberg 169, M. Akbiyik 100,T.P.A. \u00c5kesson 98, A.V. Akimov 37, D. Akiyama 168, N.N. Akolkar 24, K. Al Khoury 41,G.L. Alberghi 23b, J. Albert 165, P. Albicocco 53, G.L. Albouy 60, S. Alderweireldt 52,M. Aleksa 36, I.N. Aleksandrov 38, C. Alexa 27b, T. Alexopoulos 10, A. Alfonsi 114,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 37, 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.G. Alviggi 72a,72b, M. Aly 101, Y. Amaral Coutinho 82b,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,ag, A.V. Anisenkov 37, A. Annovi 74a, C. Antel 56, M.T. Anthony 139,E. Antipov 145, M. Antonelli 53, D.J.A. Antrim 17a, F. Anulli 75a, M. Aoki 83, T. Aoki 153,J.A. Aparisi Pozo 163, M.A. Aparo 146, L. Aperio Bella 48, C. Appelt 18, N. Aranzabal 36,C. Arcangeletti 53, A.T.H. Arce 51, E. Arena 92, J-F. Arguin 108, S. Argyropoulos 54,J.-H. Arling 48, A.J. Armbruster 36, O. Arnaez 4, H. Arnold 114, Z.P. Arrubarrena Tame109,G. Artoni 75a,75b, H. Asada 111, K. Asai 118, S. Asai 153, N.A. Asbah 61, J. Assahsah 35d,K. Assamagan 29, R. Astalos 28a, S. Atashi 160, R.J. Atkin 33a, M. Atkinson162,N.B. Atlay 18, H. Atmani62b, P.A. Atmasiddha 106, K. Augsten 132, S. Auricchio 72a,72b,A.D. Auriol 20, V.A. Austrup 101, G. Avolio 36, K. Axiotis 56, G. Azuelos 108,ak,D. Babal 28b, H. Bachacou 135, K. Bachas 152,t, A. Bachiu 34, F. Backman 47a,47b,A. Badea 61, P. Bagnaia 75a,75b, M. Bahmani 18, A.J. Bailey 163, V.R. Bailey 162,J.T. Baines 134, L. Baines 94, C. Bakalis 10, O.K. Baker 172, E. Bakos 15,D. Bakshi Gupta 8, R. Balasubramanian 114, E.M. Baldin 37, P. Balek 85a,E. Ballabene 23b,23a, F. Balli 135, L.M. Baltes 63a, W.K. Balunas 32, J. Balz 100,E. Banas 86, 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, G. Barbour96,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 Guimar\u00e3es 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,\u2013 35 \u2013JHEP10(2023)001B. Batool 141, M. Battaglia 136, D. Battulga 18, M. Bauce 75a,75b, M. Bauer 36,P. Bauer 24, L.T. Bazzano Hurrell 30, J.B. Beacham 51, T. Beau 127, P.H. Beauchemin 158,F. Becherer 54, P. Bechtle 24, H.P. Beck 19,s, K. Becker 167, A.J. Beddall 21d,V.A. Bednyakov 38, C.P. Bee 145, L.J. Beemster15, T.A. Beermann 36, M. Begalli 82d,M. Begel 29, A. Behera 145, J.K. Behr 48, J.F. Beirer 55, F. Beisiegel 24, M. Belfkir 159,G. Bella 151, L. Bellagamba 23b, A. Bellerive 34, P. Bellos 20, K. Beloborodov 37,N.L. Belyaev 37, D. Benchekroun 35a, F. Bendebba 35a, Y. Benhammou 151, M. Benoit 29,J.R. Bensinger 26, S. Bentvelsen 114, L. Beresford 48, M. Beretta 53,E. Bergeaas Kuutmann 161, N. Berger 4, B. Bergmann 132, J. Beringer 17a, G. Bernardi 5,C. Bernius 143, F.U. Bernlochner 24, F. Bernon 36,102, T. Berry 95, P. Berta 133,A. Berthold 50, I.A. Bertram 91, S. Bethke 110, A. Betti 75a,75b, A.J. Bevan 94,M. Bhamjee 33c, S. Bhatta 145, D.S. Bhattacharya 166, P. Bhattarai 26, V.S. Bhopatkar 121,R. Bi29,am, R.M. Bianchi 129, G. Bianco 23b,23a, O. Biebel 109, R. Bielski 123,M. Biglietti 77a, T.R.V. Billoud 132, 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,T. Bisanz 49, E. Bisceglie 43b,43a, D. Biswas 141, A. Bitadze 101, K. Bj\u00f8rke 125, I. Bloch 48,C. Blocker 26, A. Blue 59, U. Blumenschein 94, J. Blumenthal 100, G.J. Bobbink 114,V.S. Bobrovnikov 37, M. Boehler 54, B. Boehm 166, D. Bogavac 36, A.G. Bogdanchikov 37,C. Bohm 47a, V. Boisvert 95, P. Bokan 48, T. Bold 85a, M. Bomben 5, M. Bona 94,M. Boonekamp 135, C.D. Booth 95, A.G. Borb\u00e9ly 59, I.S. Bordulev 37,H.M. Borecka-Bielska 108, L.S. Borgna 96, G. Borissov 91, D. Bortoletto 126,D. Boscherini 23b, M. Bosman 13, J.D. Bossio Sola 36, K. Bouaouda 35a, N. Bouchhar 163,J. Boudreau 129, E.V. Bouhova-Thacker 91, D. Boumediene 40, R. Bouquet 5,A. Boveia 119, J. Boyd 36, D. Boye 29, I.R. Boyko 38, J. Bracinik 20, N. Brahimi 62d,G. Brandt 171, O. Brandt 32, F. Braren 48, B. Brau 103, J.E. Brau 123, R. Brener 169,L. Brenner 114, R. Brenner 161, S. Bressler 169, D. Britton 59, D. Britzger 110, I. Brock 24,G. Brooijmans 41, W.K. Brooks 137f , E. Brost 29, L.M. Brown 165,m, L.E. Bruce 61,T.L. Bruckler 126, P.A. Bruckman de Renstrom 86, B. Br\u00fcers 48, D. Bruncko 28b,\u2217,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, M.K. Bugge 125, 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. B\u00fcscher 100,P.J. Bussey 59, J.M. Butler 25, C.M. Buttar 59, J.M. Butterworth 96, W. Buttinger 134,C.J. Buxo Vazquez107, A.R. Buzykaev 37, G. Cabras 23b, S. Cabrera Urb\u00e1n 163,L. Cadamuro 66, D. Caforio 58, H. Cai 129, Y. Cai 14a,14e, V.M.M. Cairo 36, O. Cakir 3a,N. Calace 36, P. Calafiura 17a, G. Calderini 127, P. Calfayan 68, G. Callea 59,L.P. Caloba82b, D. Calvet 40, S. Calvet 40, T.P. Calvet 102, M. Calvetti 74a,74b,R. Camacho Toro 127, S. Camarda 36, D. Camarero Munoz 26, P. Camarri 76a,76b,M.T. Camerlingo 72a,72b, D. Cameron 125, C. Camincher 165, M. Campanelli 96,A. Camplani 42, V. Canale 72a,72b, A. Canesse 104, M. Cano Bret 80, J. Cantero 163,Y. Cao 162, F. Capocasa 26, M. Capua 43b,43a, A. Carbone 71a,71b, R. Cardarelli 76a,J.C.J. Cardenas 8, F. Cardillo 163, T. Carli 36, G. Carlino 72a, J.I. Carlotto 13,B.T. Carlson 129,u, E.M. Carlson 165,156a, L. Carminati 71a,71b, A. Carnelli 135,\u2013 36 \u2013JHEP10(2023)001M. Carnesale 75a,75b, S. Caron 113, E. Carquin 137f , S. Carr\u00e1 71a,71b, G. Carratta 23b,23a,F. Carrio Argos 33g, J.W.S. Carter 155, T.M. Carter 52, M.P. Casado 13,j , M. Caspar 48,E.G. Castiglia 172, F.L. Castillo 4, L. Castillo Garcia 13, V. Castillo Gimenez 163,N.F. Castro 130a,130e, A. Catinaccio 36, J.R. Catmore 125, V. Cavaliere 29,N. Cavalli 23b,23a, V. Cavasinni 74a,74b, Y.C. Cekmecelioglu 48, E. Celebi 21a, F. Celli 126,M.S. Centonze 70a,70b, K. Cerny 122, A.S. Cerqueira 82a, A. Cerri 146, L. Cerrito 76a,76b,F. Cerutti 17a, B. Cervato 141, A. Cervelli 23b, G. Cesarini 53, S.A. Cetin 21d, Z. Chadi 35a,D. Chakraborty 115, M. Chala 130f , J. Chan 170, W.Y. Chan 153, J.D. Chapman 32,E. Chapon 135, B. Chargeishvili 149b, D.G. Charlton 20, T.P. Charman 94, M. Chatterjee 19,C. Chauhan 133, Y. Che 14c, 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, X. Chen 14b,aj ,Y. Chen 62a, C.L. Cheng 170, H.C. Cheng 64a, S. Cheong 143, A. Cheplakov 38,E. Cheremushkina 48, E. Cherepanova 114, R. Cherkaoui El Moursli 35e, E. Cheu 7,K. Cheung 65, L. Chevalier 135, V. Chiarella 53, G. Chiarelli 74a, N. Chiedde 102,G. Chiodini 70a, A.S. Chisholm 20, A. Chitan 27b, M. Chitishvili 163, M.V. Chizhov 38,K. Choi 11, A.R. Chomont 75a,75b, Y. Chou 103, E.Y.S. Chow 114, T. Chowdhury 33g,K.L. Chu169, M.C. Chu 64a, X. Chu 14a,14e, J. Chudoba 131, J.J. Chwastowski 86,D. Cieri 110, K.M. Ciesla 85a, V. Cindro 93, A. Ciocio 17a, F. Cirotto 72a,72b,Z.H. Citron 169,n, M. Citterio 71a, D.A. Ciubotaru27b, B.M. Ciungu 155, A. Clark 56,P.J. Clark 52, J.M. Clavijo Columbie 48, S.E. Clawson 48, C. Clement 47a,47b, J. Clercx 48,L. Clissa 23b,23a, Y. Coadou 102, M. Cobal 69a,69c, A. Coccaro 57b, R.F. Coelho Barrue 130a,R. Coelho Lopes De Sa 103, S. Coelli 71a, H. Cohen 151, A.E.C. Coimbra 71a,71b, B. Cole 41,J. Collot 60, P. Conde Mui\u00f1o 130a,130g, M.P. Connell 33c, S.H. Connell 33c, I.A. Connelly 59,E.I. Conroy 126, F. Conventi 72a,al, H.G. Cooke 20, A.M. Cooper-Sarkar 126,A. Cordeiro Oudot Choi 127, F. Cormier 164, L.D. Corpe 40, M. Corradi 75a,75b,F. Corriveau 104,ab, 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. Cr\u00e9p\u00e9-Renaudin 60,F. Crescioli 127, M. Cristinziani 141, M. Cristoforetti 78a,78b, V. Croft 114, J.E. Crosby 121,G. Crosetti 43b,43a, A. Cueto 99, T. Cuhadar Donszelmann 160, H. Cui 14a,14e, Z. Cui 7,W.R. Cunningham 59, F. Curcio 43b,43a, P. Czodrowski 36, M.M. Czurylo 63b,M.J. Da Cunha Sargedas De Sousa 62a, J.V. Da Fonseca Pinto 82b, C. Da Via 101,W. Dabrowski 85a, T. Dado 49, S. Dahbi 33g, T. Dai 106, C. Dallapiccola 103, M. Dam 42,G. D\u2019amen 29, V. D\u2019Amico 109, J. Damp 100, J.R. Dandoy 128, M.F. Daneri 30,M. Danninger 142, V. Dao 36, G. Darbo 57b, S. Darmora 6, S.J. Das 29,am,S. D\u2019Auria 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 107, A. De Maria 14c, A. De Salvo 75a,U. De Sanctis 76a,76b, A. De Santo 146, J.B. De Vivie De Regie 60, D.V. Dedovich38,J. Degens 114, A.M. Deiana 44, F. Del Corso 23b,23a, J. Del Peso 99, F. Del Rio 63a,F. Deliot 135, C.M. Delitzsch 49, M. Della Pietra 72a,72b, D. Della Volpe 56,A. Dell\u2019Acqua 36, L. Dell\u2019Asta 71a,71b, M. Delmastro 4, P.A. Delsart 60, S. Demers 172,M. Demichev 38, S.P. Denisov 37, L. D\u2019Eramo 40, D. Derendarz 86, F. Derue 127,\u2013 37 \u2013JHEP10(2023)001P. 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 5, A. Di Luca 78a,78b, B. Di Micco 77a,77b, R. Di Nardo 77a,77b,C. Diaconu 102, 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. D\u00edez Cornell 48,C. Diez Pardos 141, C. Dimitriadi 24,161, A. Dimitrievska 17a, J. Dingfelder 24,I-M. Dinu 27b, S.J. Dittmeier 63b, F. Dittus 36, F. Djama 102, T. Djobava 149b,J.I. Djuvsland 16, C. Doglioni 101,98, J. Dolejsi 133, Z. Dolezal 133, M. Donadelli 82c,B. Dong 107, J. Donini 40, A. D\u2019Onofrio 77a,77b, M. D\u2019Onofrio 92, J. Dopke 134,A. Doria 72a, N. Dos Santos Fernandes 130a, M.T. Dova 90, A.T. Doyle 59,M.A. Draguet 126, E. Dreyer 169, I. Drivas-koulouris 10, A.S. Drobac 158, M. Drozdova 56,D. Du 62a, T.A. du Pree 114, F. Dubinin 37, M. Dubovsky 28a, E. Duchovni 169,G. Duckeck 109, O.A. Ducu 27b, D. Duda 52, A. Dudarev 36, E.R. Duden 26,M. D\u2019uffizi 101, L. Duflot 66, M. D\u00fchrssen 36, C. D\u00fclsen 171, A.E. Dumitriu 27b,M. Dunford 63a, S. Dungs 49, K. Dunne 47a,47b, A. Duperrin 102, H. Duran Yildiz 3a,M. D\u00fcren 58, A. Durglishvili 149b, B.L. Dwyer 115, G.I. Dyckes 17a, M. Dyndal 85a,S. Dysch 101, B.S. Dziedzic 86, Z.O. Earnshaw 146, G.H. Eberwein 126, B. Eckerova 28a,S. Eggebrecht 55, M.G. Eggleston51, E. Egidio Purcino De Souza 127, L.F. Ehrke 56,G. Eigen 16, K. Einsweiler 17a, T. Ekelof 161, P.A. Ekman 98, S. El Farkh 35b,Y. El Ghazali 35b, H. El Jarrari 35e,148, A. El Moussaouy 35a, V. Ellajosyula 161,M. Ellert 161, F. Ellinghaus 171, A.A. Elliot 94, N. Ellis 36, J. Elmsheuser 29, M. Elsing 36,D. Emeliyanov 134, Y. Enari 153, I. Ene 17a, S. Epari 13, J. Erdmann 49, P.A. Erland 86,M. Errenst 171, M. Escalier 66, C. Escobar 163, E. Etzion 151, G. Evans 130a, H. Evans 68,L.S. Evans 95, M.O. Evans 146, A. Ezhilov 37, S. Ezzarqtouni 35a, F. Fabbri 59,L. Fabbri 23b,23a, G. Facini 96, V. Fadeyev 136, R.M. Fakhrutdinov 37, S. Falciano 75a,L.F. Falda Ulhoa Coelho 36, P.J. Falke 24, J. Faltova 133, C. Fan 162, Y. Fan 14a,Y. Fang 14a,14e, M. Fanti 71a,71b, M. Faraj 69a,69b, Z. Farazpay97, 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, A. Fell 139,D.E. Fellers 123, C. Feng 62b, M. Feng 14b, Z. Feng 114, M.J. Fenton 160, A.B. Fenyuk37,L. Ferencz 48, R.A.M. Ferguson 91, S.I. Fernandez Luengo 137f , M.J.V. Fernoux 102,J. Ferrando 48, A. Ferrari 161, P. Ferrari 114,113, R. Ferrari 73a, D. Ferrere 56,C. Ferretti 106, F. Fiedler 100, A. Filip\u010di\u010d 93, E.K. Filmer 1, F. Filthaut 113,M.C.N. Fiolhais 130a,130c,d, L. Fiorini 163, W.C. Fisher 107, T. Fitschen 101,P.M. Fitzhugh135, I. Fleck 141, P. Fleischmann 106, T. Flick 171, L. Flores 128,M. Flores 33d,ah, 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,k, 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, L. Franconi 48, M. Franklin 61, G. Frattari 26,A.C. Freegard 94, W.S. Freund 82b, Y.Y. Frid 151, N. Fritzsche 50, A. Froch 54,D. Froidevaux 36, J.A. Frost 126, Y. Fu 62a, M. Fujimoto 118, E. Fullana Torregrosa 163,\u2217,\u2013 38 \u2013JHEP10(2023)001K.Y. Fung 64a, E. Furtado De Simas Filho 82b, M. Furukawa 153, J. Fuster 163,A. Gabrielli 23b,23a, A. Gabrielli 155, P. Gadow 48, G. Gagliardi 57b,57a, L.G. Gagnon 17a,E.J. Gallas 126, B.J. Gallop 134, K.K. Gan 119, S. Ganguly 153, J. Gao 62a, Y. Gao 52,F.M. Garay Walls 137a,137b, B. Garcia29,am, C. Garc\u00eda 163, A. Garcia Alonso 114,A.G. Garcia Caffaro 172, J.E. Garc\u00eda Navarro 163, M. Garcia-Sciveres 17a, G.L. Gardner 128,R.W. Gardner 39, N. Garelli 158, D. Garg 80, R.B. Garg 143,r, J.M. Gargan52,C.A. Garner155, S.J. Gasiorowski 138, P. Gaspar 82b, G. Gaudio 73a, V. Gautam13,P. Gauzzi 75a,75b, I.L. Gavrilenko 37, A. Gavrilyuk 37, C. Gay 164, G. Gaycken 48,E.N. Gazis 10, A.A. Geanta 27b, C.M. Gee 136, C. Gemme 57b, M.H. Genest 60,S. Gentile 75a,75b, S. George 95, W.F. George 20, T. Geralis 46, P. Gessinger-Befurt 36,M.E. Geyik 171, M. Ghneimat 141, K. Ghorbanian 94, A. Ghosal 141, A. Ghosh 160,A. Ghosh 7, B. Giacobbe 23b, S. Giagu 75a,75b, P. Giannetti 74a, A. Giannini 62a,S.M. Gibson 95, M. Gignac 136, D.T. Gil 85b, A.K. Gilbert 85a, B.J. Gilbert 41,D. Gillberg 34, G. Gilles 114, N.E.K. Gillwald 48, L. Ginabat 127, D.M. Gingrich 2,ak,M.P. Giordani 69a,69c, P.F. Giraud 135, G. Giugliarelli 69a,69c, D. Giugni 71a, F. Giuli 36,I. Gkialas 9,k, L.K. Gladilin 37, C. Glasman 99, G.R. Gledhill 123, M. Glisic123,I. Gnesi 43b,g, Y. Go 29,am, M. Goblirsch-Kolb 36, B. Gocke 49, D. Godin108,B. Gokturk 21a, S. Goldfarb 105, T. Golling 56, M.G.D. Gololo33g, D. Golubkov 37,J.P. Gombas 107, A. Gomes 130a,130b, G. Gomes Da Silva 141, A.J. Gomez Delegido 163,R. Gon\u00e7alo 130a,130c, G. Gonella 123, L. Gonella 20, A. Gongadze 38, F. Gonnella 20,J.L. Gonski 41, R.Y. Gonz\u00e1lez Andana 52, S. Gonz\u00e1lez de la Hoz 163,S. Gonzalez Fernandez 13, R. Gonzalez Lopez 92, C. Gonzalez Renteria 17a,R. Gonzalez Suarez 161, S. Gonzalez-Sevilla 56, G.R. Gonzalvo Rodriguez 163,L. Goossens 36, P.A. Gorbounov 37, B. Gorini 36, E. Gorini 70a,70b, A. Gori\u0161ek 93,T.C. Gosart 128, A.T. Goshaw 51, M.I. Gostkin 38, S. Goswami 121, C.A. Gottardo 36,M. Gouighri 35b, V. Goumarre 48, A.G. Goussiou 138, N. Govender 33c,I. Grabowska-Bold 85a, K. Graham 34, E. Gramstad 125, S. Grancagnolo 70a,70b,M. Grandi 146, V. Gratchev37,\u2217, P.M. Gravila 27f , F.G. Gravili 70a,70b, H.M. Gray 17a,M. Greco 70a,70b, C. Grefe 24, I.M. Gregor 48, P. Grenier 143, C. Grieco 13,A.A. Grillo 136, K. Grimm 31, S. Grinstein 13,x, 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,69b, F. Guescini 110,R. Gugel 100, J.A.M. Guhit 106, A. Guida 18, T. Guillemin 4, E. Guilloton 167,134,S. Guindon 36, F. Guo 14a,14e, J. Guo 62c, L. Guo 48, Y. Guo 106, R. Gupta 48,S. Gurbuz 24, S.S. Gurdasani 54, G. Gustavino 36, M. Guth 56, P. Gutierrez 120,L.F. Gutierrez Zagazeta 128, C. Gutschow 96, C. Gwenlan 126, C.B. Gwilliam 92,E.S. Haaland 125, A. Haas 117, M. Habedank 48, C. Haber 17a, H.K. Hadavand 8,A. Hadef 100, S. Hadzic 110, J.J. Hahn 141, E.H. Haines 96, M. Haleem 166, J. Haley 121,J.J. Hall 139, G.D. Hallewell 102, L. Halser 19, K. Hamano 165, H. Hamdaoui 35e,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 83, M. Hance 136, D.A. Hangal 41,ag,H. Hanif 142, M.D. Hank 128, R. Hankache 101, J.B. Hansen 42, J.D. Hansen 42,P.H. Hansen 42, K. Hara 157, D. Harada 56, T. Harenberg 171, S. Harkusha 37,\u2013 39 \u2013JHEP10(2023)001M.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, A. Hasib 52, S. Haug 19,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 127, 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,ai, J. Hejbal 131, L. Helary 48, A. Held 170,S. Hellesund 16, C.M. Helling 164, S. Hellman 47a,47b, C. Helsens 36, R.C.W. Henderson91,L. Henkelmann 32, A.M. Henriques Correia36, H. Herde 98, Y. Hern\u00e1ndez Jim\u00e9nez 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 84, S.J. Hillier 20, J.R. Hinds 107,F. Hinterkeuser 24, M. Hirose 124, S. Hirose 157, D. Hirschbuehl 171, T.G. Hitchings 101,B. Hiti 93, J. Hobbs 145, R. Hobincu 27e, N. Hod 169, M.C. Hodgkinson 139,B.H. Hodkinson 32, A. Hoecker 36, J. Hofer 48, T. Holm 24, M. Holzbock 110,L.B.A.H. Hommels 32, B.P. Honan 101, J. Hong 62c, T.M. Hong 129, B.H. Hooberman 162,W.H. Hopkins 6, Y. Horii 111, S. Hou 148, A.S. Howard 93, J. Howarth 59, J. Hoya 6,M. Hrabovsky 122, A. Hrynevich 48, T. Hryn\u2019ova 4, P.J. Hsu 65, S.-C. Hsu 138, Q. Hu 41,Y.F. Hu 14a,14e, S. Huang 64b, X. Huang 14c, Y. Huang 62a, 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,a, 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 83, Y. Ikegami 83,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,ao, 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, P. Jain 54, G. J\u00e4kel 171, K. Jakobs 54,T. Jakoubek 169, J. Jamieson 59, K.W. Janas 85a, A.E. Jaspan 92, M. Javurkova 103,F. Jeanneau 135, L. Jeanty 123, J. Jejelava 149a,ae, P. Jenni 54,h, C.E. Jessiman 34,S. J\u00e9z\u00e9quel 4, C. Jia62b, J. Jia 145, X. Jia 61, X. Jia 14a,14e, Z. Jia 14c, Y. Jiang62a,S. Jiggins 48, J. Jimenez Pena 13, S. Jin 14c, A. Jinaru 27b, O. Jinnouchi 154,P. Johansson 139, K.A. Johns 7, J.W. Johnson 136, D.M. Jones 32, E. Jones 48,P. Jones 32, R.W.L. Jones 91, T.J. Jones 92, R. Joshi 119, J. Jovicevic 15, X. Ju 17a,J.J. Junggeburth 36, T. Junkermann 63a, A. Juste Rozas 13,x, M.K. Juzek 86,S. Kabana 137e, A. Kaczmarska 86, M. Kado 110, H. Kagan 119, M. Kagan 143, A. Kahn41,A. Kahn 128, C. Kahra 100, T. Kaji 168, E. Kajomovitz 150, N. Kakati 169,I. Kalaitzidou 54, C.W. Kalderon 29, A. Kamenshchikov 155, S. Kanayama 154,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,T. Kawamoto 135, E.F. Kay 36, F.I. Kaya 158, S. Kazakos 107, V.F. Kazanin 37, Y. Ke 145,J.M. Keaveney 33a, R. Keeler 165, G.V. Kehris 61, J.S. Keller 34, A.S. Kelly96,\u2013 40 \u2013JHEP10(2023)001J.J. Kempster 146, K.E. Kennedy 41, P.D. Kennedy 100, O. Kepka 131, B.P. Kerridge 167,S. Kersten 171, B.P. Ker\u0161evan 93, S. Keshri 66, L. Keszeghova 28a,S. Ketabchi Haghighat 155, M. Khandoga 127, A. Khanov 121, A.G. Kharlamov 37,T. Kharlamova 37, E.E. Khoda 138, T.J. Khoo 18, G. Khoriauli 166, J. Khubua 149b,Y.A.R. Khwaira 66, M. Kiehn 36, A. Kilgallon 123, D.W. Kim 47a,47b, Y.K. Kim 39,N. Kimura 96, A. Kirchhoff 55, C. Kirfel 24, F. Kirfel 24, J. Kirk 134, A.E. Kiryunin 110,C. Kitsaki 10, O. Kivernyk 24, M. Klassen 63a, C. Klein 34, L. Klein 166, M.H. Klein 106,M. Klein 92, S.B. Klein 56, U. Klein 92, P. Klimek 36, A. Klimentov 29,T. Klioutchnikova 36, P. Kluit 114, S. Kluth 110, E. Kneringer 79, T.M. Knight 155,A. Knue 54, R. Kobayashi 87, S.F. Koch 126, M. Kocian 143, P. Kody\u0161 133,D.M. Koeck 123, P.T. Koenig 24, T. Koffas 34, M. Kolb 135, I. Koletsou 4, T. Komarek 122,K. K\u00f6neke 54, A.X.Y. Kong 1, T. Kono 118, N. Konstantinidis 96, B. Konya 98,R. Kopeliansky 68, S. Koperny 85a, K. Korcyl 86, K. Kordas 152,f , G. Koren 151,A. Korn 96, S. Korn 55, I. Korolkov 13, N. Korotkova 37, B. Kortman 114, O. Kortner 110,S. Kortner 110, W.H. Kostecka 115, V.V. Kostyukhin 141, A. Kotsokechagia 135,A. Kotwal 51, A. Koulouris 36, A. Kourkoumeli-Charalampidi 73a,73b, C. Kourkoumelis 9,E. Kourlitis 6, 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 100, 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. Kr\u00fcger 24, N. Krumnack81, M.C. Kruse 51, J.A. Krzysiak 86,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 102, A. Kupco 131,T. Kupfer49, A. Kupich 37, O. Kuprash 54, H. Kurashige 84, 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, S. Lai 55, I.K. Lakomiec 85a, N. Lalloue 60, J.E. Lambert 165,m,S. Lammers 68, W. Lampl 7, C. Lampoudis 152,f , A.N. Lancaster 115, E. Lan\u00e7on 29,U. Landgraf 54, M.P.J. Landon 94, V.S. Lang 54, R.J. Langenberg 103,O.K.B. Langrekken 125, A.J. Lankford 160, F. Lanni 36, K. Lantzsch 24, A. Lanza 73a,A. Lapertosa 57b,57a, J.F. Laporte 135, T. Lari 71a, F. Lasagni Manghi 23b, M. Lassnig 36,V. Latonova 131, A. Laudrain 100, A. Laurier 150, S.D. Lawlor 95, Z. Lawrence 101,M. Lazzaroni 71a,71b, B. Le101, E.M. Le Boulicaut 51, B. Leban 93, A. Lebedev 81,M. LeBlanc 36, 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,w,M.A.L. Leite 82c, 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. Lev\u00eaque 4, D. Levin 106, L.J. Levinson 169,M.P. Lewicki 86, D.J. Lewis 4, A. Li 5, B. Li 62b, C. Li62a, C-Q. Li 62c, H. Li 62a,H. Li 62b, H. Li 14c, H. Li 62b, K. Li 138, L. Li 62c, M. Li 14a,14e, Q.Y. Li 62a,\u2013 41 \u2013JHEP10(2023)001S. Li 14a,14e, S. Li 62d,62c,e, T. Li 5,c, X. Li 104, Z. Li 126, Z. Li 104, Z. Li 92,Z. Li 14a,14e, Z. Liang 14a, M. Liberatore 48, B. Liberti 76a, K. Lie 64c,J. Lieber Marin 82b, H. Lien 68, K. Lin 107, R.E. Lindley 7, J.H. Lindon 2, A. Linss 48,E. Lipeles 128, A. Lipniacka 16, A. Lister 164, J.D. Little 4, B. Liu 14a, B.X. Liu 142,D. Liu 62d,62c, J.B. Liu 62a, J.K.K. Liu 32, K. Liu 62d,62c, M. Liu 62a, M.Y. Liu 62a,P. Liu 14a, Q. Liu 62d,138,62c, X. Liu 62a, Y. Liu 14d,14e, Y.L. Liu 106, Y.W. Liu 62a,J. Llorente Merino 142, S.L. Lloyd 94, E.M. Lobodzinska 48, P. Loch 7, S. Loffredo 76a,76b,T. Lohse 18, K. Lohwasser 139, E. Loiacono 48, M. Lokajicek 131,\u2217, J.D. Lomas 20,J.D. Long 162, I. Longarini 160, L. Longo 70a,70b, R. Longo 162, I. Lopez Paz 67,A. Lopez Solis 48, J. Lorenz 109, N. Lorenzo Martinez 4, A.M. Lory 109, 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 123, M.S. Lutz 151, D. Lynn 29, H. Lyons92, R. Lysak 131,E. Lytken 98, V. Lyubushkin 38, T. Lyubushkina 38, M.M. Lyukova 145, H. Ma 29,K. Ma62a, L.L. Ma 62b, Y. Ma 121, D.M. Mac Donell 165, G. Maccarrone 53,J.C. MacDonald 100, R. Madar 40, W.F. Mader 50, J. Maeda 84, T. Maeno 29,M. Maerker 50, H. Maguire 139, V. Maiboroda 135, A. Maio 130a,130b,130d, K. Maj 85a,O. Majersky 48, S. Majewski 123, N. Makovec 66, V. Maksimovic 15, B. Malaescu 127,Pa. Malecki 86, V.P. Maleev 37, F. Malek 60, M. Mali 93, D. Malito 95,q, U. Mallik 80,S. Maltezos10, S. Malyukov38, J. Mamuzic 13, G. Mancini 53, G. Manco 73a,73b,J.P. Mandalia 94, I. Mandi\u0107 93, L. Manhaes de Andrade Filho 82a, I.M. Maniatis 169,J. Manjarres Ramos 102,af , D.C. Mankad 169, A. Mann 109, B. Mansoulie 135,S. Manzoni 36, A. Marantis 152,w, G. Marchiori 5, M. Marcisovsky 131, C. Marcon 71a,71b,M. Marinescu 20, M. Marjanovic 120, E.J. Marshall 91, Z. Marshall 17a, S. Marti-Garcia 163,T.A. Martin 167, V.J. Martin 52, B. Martin dit Latour 16, L. Martinelli 75a,75b,M. Martinez 13,x, P. Martinez Agullo 163, V.I. Martinez Outschoorn 103,P. Martinez Suarez 13, S. Martin-Haugh 134, V.S. Martoiu 27b, A.C. Martyniuk 96,A. Marzin 36, D. Mascione 78a,78b, L. Masetti 100, T. Mashimo 153, J. Masik 101,A.L. Maslennikov 37, L. Massa 23b, P. Massarotti 72a,72b, P. Mastrandrea 74a,74b,A. Mastroberardino 43b,43a, T. Masubuchi 153, T. Mathisen 161, J. Matousek 133,N. Matsuzawa153, J. Maurer 27b, B. Ma\u010dek 93, D.A. Maximov 37, R. Mazini 148,I. Maznas 152, M. Mazza 107, S.M. Mazza 136, E. Mazzeo 71a,71b, C. Mc Ginn 29,J.P. Mc Gowan 104, S.P. Mc Kee 106, E.F. McDonald 105, A.E. McDougall 114,J.A. Mcfayden 146, R.P. McGovern 128, G. Mchedlidze 149b, R.P. Mckenzie 33g,T.C. Mclachlan 48, D.J. Mclaughlin 96, K.D. McLean 165, S.J. McMahon 134,P.C. McNamara 105, C.M. Mcpartland 92, R.A. McPherson 165,ab, S. Mehlhase 109,A. Mehta 92, D. Melini 150, B.R. Mellado Garcia 33g, A.H. Melo 55, F. Meloni 48,A.M. Mendes Jacques Da Costa 101, H.Y. Meng 155, L. Meng 91, S. Menke 110,M. Mentink 36, E. Meoni 43b,43a, C. Merlassino 126, L. Merola 72a,72b, C. Meroni 71a,71b,G. Merz106, O. Meshkov 37, J. Metcalfe 6, A.S. Mete 6, C. Meyer 68, J-P. Meyer 135,R.P. Middleton 134, L. Mijovi\u0107 52, G. Mikenberg 169, M. Mikestikova 131, M. Miku\u017e 93,H. Mildner 100, A. Milic 36, C.D. Milke 44, D.W. Miller 39, L.S. Miller 34, A. Milov 169,\u2013 42 \u2013JHEP10(2023)001D.A. Milstead47a,47b, T. Min14c, A.A. Minaenko 37, I.A. Minashvili 149b, L. Mince 59,A.I. Mincer 117, B. Mindur 85a, M. Mineev 38, Y. Mino 87, L.M. Mir 13,M. Miralles Lopez 163, M. Mironova 17a, A. Mishima153, M.C. Missio 113, T. Mitani 168,A. Mitra 167, V.A. Mitsou 163, O. Miu 155, P.S. Miyagawa 94, Y. Miyazaki89,A. Mizukami 83, T. Mkrtchyan 63a, M. Mlinarevic 96, T. Mlinarevic 96, M. Mlynarikova 36,S. Mobius 19, K. Mochizuki 108, P. Moder 48, P. Mogg 109, A.F. Mohammed 14a,14e,S. Mohapatra 41, G. Mokgatitswane 33g, L. Moleri 169, B. Mondal 141, S. Mondal 132,G. Monig 146, K. M\u00f6nig 48, E. Monnier 102, L. Monsonis Romero163,J. Montejo Berlingen 13,83, 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 Ll\u00e1cer 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. Mosidze149b, T. Moskalets 54, P. Moskvitina 113, J. Moss 31,o, E.J.W. Moyse 103,O. Mtintsilana 33g, S. Muanza 102, J. Mueller 129, D. Muenstermann 91, R. M\u00fcller 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, W.J. Murray 167,134, A. Murrone 71a,71b,J.M. Muse 120, M. Mu\u0161kinja 17a, C. Mwewa 29, A.G. Myagkov 37,a, A.J. Myers 8,A.A. Myers129, G. Myers 68, M. Myska 132, B.P. Nachman 17a, O. Nackenhorst 49,A. Nag 50, K. Nagai 126, K. Nagano 83, J.L. Nagle 29,am, E. Nagy 102, A.M. Nairz 36,Y. Nakahama 83, K. Nakamura 83, K. Nakkalil 5, H. Nanjo 124, R. Narayan 44,E.A. Narayanan 112, I. Naryshkin 37, M. Naseri 34, S. Nasri 159, C. Nass 24,G. Navarro 22a, J. Navarro-Gonzalez 163, R. Nayak 151, A. Nayaz 18, P.Y. Nechaeva 37,F. Nechansky 48, L. Nedic 126, T.J. Neep 20, A. Negri 73a,73b, M. Negrini 23b,C. Nellist 114, C. Nelson 104, K. Nelson 106, S. Nemecek 131, M. Nessi 36,i,M.S. Neubauer 162, F. Neuhaus 100, J. Neundorf 48, R. Newhouse 164, P.R. Newman 20,C.W. Ng 129, Y.W.Y. Ng 48, B. Ngair 35e, H.D.N. Nguyen 108, R.B. Nickerson 126,R. Nicolaidou 135, J. Nielsen 136, M. Niemeyer 55, J. Niermann 55,36, N. Nikiforou 36,V. Nikolaenko 37,a, I. Nikolic-Audit 127, K. Nikolopoulos 20, P. Nilsson 29, I. Ninca 48,H.R. Nindhito 56, G. Ninio 151, A. Nisati 75a, N. Nishu 2, R. Nisius 110, J-E. Nitschke 50,E.K. Nkadimeng 33g, S.J. Noacco Rosende 90, T. Nobe 153, D.L. Noel 32,T. Nommensen 147, M.B. Norfolk 139, R.R.B. Norisam 96, B.J. Norman 34, J. Novak 93,T. Novak 48, L. Novotny 132, R. Novotny 112, L. Nozka 122, K. Ntekas 160,N.M.J. Nunes De Moura Junior 82b, E. Nurse96, J. Ocariz 127, A. Ochi 84, I. Ochoa 130a,S. Oerdek 161, J.T. Offermann 39, A. Ogrodnik 133, A. Oh 101, C.C. Ohm 144, H. Oide 83,R. Oishi 153, M.L. Ojeda 48, Y. Okazaki 87, M.W. O\u2019Keefe92, Y. Okumura 153,L.F. Oleiro Seabra 130a, S.A. Olivares Pino 137d, D. Oliveira Damazio 29,D. Oliveira Goncalves 82a, J.L. Oliver 160, M.J.R. Olsson 160, A. Olszewski 86,\u00d6.O. \u00d6ncel 54, D.C. O\u2019Neil 142, A.P. O\u2019Neill 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\u2019Shea 59, L.M. Osojnak 128, R. Ospanov 62a, G. Otero y Garzon 30, H. Otono 89,P.S. Ott 63a, G.J. Ottino 17a, M. Ouchrif 35d, J. Ouellette 29, F. Ould-Saada 125,M. Owen 59, R.E. Owen 134, K.Y. Oyulmaz 21a, V.E. Ozcan 21a, N. Ozturk 8,S. Ozturk 21d, H.A. Pacey 32, A. Pacheco Pages 13, C. Padilla Aranda 13,\u2013 43 \u2013JHEP10(2023)001G. Padovano 75a,75b, S. Pagan Griso 17a, G. Palacino 68, A. Palazzo 70a,70b, S. Palestini 36,J. Pan 172, T. Pan 64a, D.K. Panchal 11, C.E. Pandini 114, J.G. Panduro Vazquez 95,H. Pang 14b, P. Pani 48, G. Panizzo 69a,69c, L. Paolozzi 56, C. Papadatos 108,S. Parajuli 44, A. Paramonov 6, C. Paraskevopoulos 10, D. Paredes Hernandez 64b,T.H. Park 155, M.A. Parker 32, F. Parodi 57b,57a, E.W. Parrish 115, V.A. Parrish 52,J.A. Parsons 41, U. Parzefall 54, B. Pascual Dias 108, L. Pascual Dominguez 151,F. Pasquali 114, E. Pasqualucci 75a, S. Passaggio 57b, F. Pastore 95, P. Pasuwan 47a,47b,P. Patel 86, U.M. Patel 51, J.R. Pater 101, T. Pauly 36, J. Pearkes 143, M. Pedersen 125,R. Pedro 130a, S.V. Peleganchuk 37, O. Penc 36, E.A. Pender 52, H. Peng 62a,K.E. Penski 109, M. Penzin 37, B.S. Peralva 82d, A.P. Pereira Peixoto 60,L. Pereira Sanchez 47a,47b, D.V. Perepelitsa 29,am, E. Perez Codina 156a, M. Perganti 10,L. Perini 71a,71b,\u2217, H. Pernegger 36, A. Perrevoort 113, 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,f , A. Petrukhin 141, M. Pettee 17a, N.E. Pettersson 36, A. Petukhov 37,K. Petukhova 133, A. Peyaud 135, R. Pezoa 137f , L. Pezzotti 36, G. Pezzullo 172,T.M. Pham 170, T. Pham 105, P.W. Phillips 134, G. Piacquadio 145, E. Pianori 17a,F. Piazza 71a,71b, R. Piegaia 30, D. Pietreanu 27b, A.D. Pilkington 101, M. Pinamonti 69a,69c,J.L. Pinfold 2, B.C. Pinheiro Pereira 130a, A.E. Pinto Pinoargote 135, K.M. Piper 146,A. Pirttikoski 56, C. Pitman Donaldson96, D.A. Pizzi 34, L. Pizzimento 76a,76b,A. Pizzini 114, M.-A. Pleier 29, V. Plesanovs54, V. Pleskot 133, E. Plotnikova38, G. Poddar 4,R. Poettgen 98, L. Poggioli 127, I. Pokharel 55, S. Polacek 133, G. Polesello 73a,A. Poley 142,156a, R. Polifka 132, A. Polini 23b, C.S. Pollard 167, Z.B. Pollock 119,V. Polychronakos 29, E. Pompa Pacchi 75a,75b, D. Ponomarenko 113, L. Pontecorvo 36,S. Popa 27a, G.A. Popeneciu 27d, A. Poreba 36, D.M. Portillo Quintero 156a, S. Pospisil 132,M.A. Postill 139, P. Postolache 27c, K. Potamianos 167, P.A. Potepa 85a, 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 85a,W.W. Przygoda 85b, 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, G. Rabanal Bolanos 61, D. Rafanoharana 54, F. Ragusa 71a,71b,J.L. Rainbolt 39, J.A. Raine 56, S. Rajagopalan 29, E. Ramakoti 37, K. Ran 48,14e,N.P. Rapheeha 33g, H. Rasheed 27b, V. Raskina 127, D.F. Rassloff 63a, S. Rave 100,B. Ravina 55, I. Ravinovich 169, M. Raymond 36, A.L. Read 125, N.P. Readioff 139,D.M. Rebuzzi 73a,73b, G. Redlinger 29, A.S. Reed 110, K. Reeves 26, J.A. Reidelsturz 171,v,D. Reikher 151, A. Rej 141, C. Rembser 36, A. Renardi 48, M. Renda 27b, M.B. Rendel110,F. Renner 48, A.G. Rennie 59, S. Resconi 71a, M. Ressegotti 57b,57a, S. Rettie 36,J.G. Reyes Rivera 107, B. Reynolds119, 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 85b,M. Ridel 127, S. Ridouani 35d, P. Rieck 117, P. Riedler 36, M. Rijssenbeek 145,A. Rimoldi 73a,73b, M. Rimoldi 48, L. Rinaldi 23b,23a, T.T. Rinn 29, M.P. Rinnagel 109,G. Ripellino 161, I. Riu 13, P. Rivadeneira 48, J.C. Rivera Vergara 165, F. Rizatdinova 121,\u2013 44 \u2013JHEP10(2023)001E. Rizvi 94, B.A. Roberts 167, B.R. Roberts 17a, S.H. Robertson 104,ab, M. Robin 48,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. Rodr\u00edguez Vera 156b, S. Roe36, J.T. Roemer 160,A.R. Roepe-Gier 136, J. Roggel 171, O. R\u00f8hne 125, R.A. Rojas 103, C.P.A. Roland 68,J. Roloff 29, A. Romaniouk 37, E. Romano 73a,73b, M. Romano 23b,A.C. Romero Hernandez 162, N. Rompotis 92, L. Roos 127, S. Rosati 75a, B.J. Rosser 39,E. Rossi 126, E. Rossi 72a,72b, L.P. Rossi 57b, L. Rossini 48, R. Rosten 119, M. Rotaru 27b,B. Rottler 54, C. Rougier 102,af , D. Rousseau 66, D. Rousso 32, A. Roy 162,S. Roy-Garand 155, A. Rozanov 102, Y. Rozen 150, X. Ruan 33g, A. Rubio Jimenez 163,A.J. Ruby 92, V.H. Ruelas Rivera 18, T.A. Ruggeri 1, A. Ruggiero 126,A. Ruiz-Martinez 163, A. Rummler 36, Z. Rurikova 54, N.A. Rusakovich 38,H.L. Russell 165, G. Russo 75a,75b, J.P. Rutherfoord 7, S. Rutherford Colmenares 32,K. Rybacki91, M. Rybar 133, E.B. Rye 125, A. Ryzhov 44, J.A. Sabater Iglesias 56,P. Sabatini 163, L. Sabetta 75a,75b, H.F-W. Sadrozinski 136, F. Safai Tehrani 75a,B. Safarzadeh Samani 146, M. Safdari 143, S. Saha 165, M. Sahinsoy 110, M. Saimpert 135,M. Saito 153, T. Saito 153, D. Salamani 36, A. Salnikov 143, J. Salt 163,A. Salvador Salas 13, D. Salvatore 43b,43a, F. Salvatore 146, A. Salzburger 36, D. Sammel 54,D. Sampsonidis 152,f , D. Sampsonidou 123, J. S\u00e1nchez 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, D.P.C. Sankey 134, T. Sano 87, A. Sansoni 53,L. Santi 75a,75b, C. Santoni 40, H. Santos 130a,130b, S.N. Santpur 17a, A. Santra 169,K.A. Saoucha 139, J.G. Saraiva 130a,130d, J. Sardain 7, O. Sasaki 83, K. Sato 157,C. Sauer63b, F. Sauerburger 54, E. Sauvan 4, P. Savard 155,ak, R. Sawada 153,C. Sawyer 134, L. Sawyer 97, I. Sayago Galvan163, C. Sbarra 23b, A. Sbrizzi 23b,23a,T. Scanlon 96, J. Schaarschmidt 138, P. Schacht 110, D. Schaefer 39, U. Sch\u00e4fer 100,A.C. Schaffer 66,44, D. Schaile 109, R.D. Schamberger 145, C. Scharf 18, M.M. Schefer 19,V.A. Schegelsky 37, D. Scheirich 133, F. Schenck 18, M. Schernau 160, C. Scheulen 55,C. Schiavi 57b,57a, E.J. Schioppa 70a,70b, M. Schioppa 43b,43a, B. Schlag 143,r,K.E. Schleicher 54, S. Schlenker 36, J. Schmeing 171, M.A. Schmidt 171, K. Schmieden 100,C. Schmitt 100, S. Schmitt 48, L. Schoeffel 135, A. Schoening 63b, P.G. Scholer 54,E. Schopf 126, M. Schott 100, J. Schovancova 36, S. Schramm 56, F. Schroeder 171,T. Schroer 56, H-C. Schultz-Coulon 63a, M. Schumacher 54, B.A. Schumm 136,Ph. Schune 135, A.J. Schuy 138, H.R. Schwartz 136, A. Schwartzman 143, T.A. Schwarz 106,Ph. Schwemling 135, R. Schwienhorst 107, A. Sciandra 136, G. Sciolla 26, F. Scuri 74a,C.D. Sebastiani 92, K. Sedlaczek 115, P. Seema 18, S.C. Seidel 112, A. Seiden 136,B.D. Seidlitz 41, C. Seitz 48, J.M. Seixas 82b, G. Sekhniaidze 72a, S.J. Sekula 44,L. Selem 60, N. Semprini-Cesari 23b,23a, D. Sengupta 56, V. Senthilkumar 163, L. Serin 66,L. Serkin 69a,69b, M. Sessa 76a,76b, H. Severini 120, F. Sforza 57b,57a, A. Sfyrla 56,E. Shabalina 55, R. Shaheen 144, J.D. Shahinian 128, D. Shaked Renous 169, L.Y. Shan 14a,M. Shapiro 17a, A. Sharma 36, A.S. Sharma 164, P. Sharma 80, S. Sharma 48,P.B. Shatalov 37, K. Shaw 146, S.M. Shaw 101, A. Shcherbakova 37, Q. Shen 62c,5,P. Sherwood 96, L. Shi 96, X. Shi 14a, C.O. Shimmin 172, Y. Shimogama 168,\u2013 45 \u2013JHEP10(2023)001J.D. Shinner 95, I.P.J. Shipsey 126, S. Shirabe 56,i, M. Shiyakova 38,z, J. Shlomi 169,M.J. Shochet 39, J. Shojaii 105, D.R. Shope 125, S. Shrestha 119,an, E.M. Shrif 33g,M.J. Shroff 165, P. Sicho 131, A.M. Sickles 162, E. Sideras Haddad 33g, A. Sidoti 23b,F. Siegert 50, Dj. Sijacki 15, R. Sikora 85a, 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 21d, 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,\u2217,J. Sj\u00f6lin 47a,47b, A. Skaf 55, E. Skorda 98, P. Skubic 120, M. Slawinska 86, V. Smakhtin169,B.H. Smart 134, J. Smiesko 36, S.Yu. Smirnov 37, Y. Smirnov 37, L.N. Smirnova 37,a,O. Smirnova 98, A.C. Smith 41, E.A. Smith 39, H.A. Smith 126, J.L. Smith 92, R. Smith143,M. Smizanska 91, K. Smolek 132, A.A. Snesarev 37, S.R. Snider 155, H.L. Snoek 114,S. Snyder 29, R. Sobie 165,ab, A. Soffer 151, C.A. Solans Sanchez 36, E.Yu. Soldatov 37,U. Soldevila 163, A.A. Solodkov 37, S. Solomon 26, A. Soloshenko 38, K. Solovieva 54,O.V. Solovyanov 40, V. Solovyev 37, P. Sommer 36, A. Sonay 13, W.Y. Song 156b,J.M. Sonneveld 114, A. Sopczak 132, A.L. Sopio 96, F. Sopkova 28b, V. Sothilingam63a,S. Sottocornola 68, R. Soualah 116b, Z. Soumaimi 35e, D. South 48, S. Spagnolo 70a,70b,M. Spalla 110, D. Sperlich 54, G. Spigo 36, M. Spina 146, S. Spinali 91, D.P. Spiteri 59,M. Spousta 133, E.J. Staats 34, A. Stabile 71a,71b, R. Stamen 63a, M. Stamenkovic 114,A. Stampekis 20, M. Standke 24, E. Stanecka 86, 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,af ,D.M. Starko156b, P. Staroba 131, P. Starovoitov 63a, S. St\u00e4rz 104, R. Staszewski 86,G. Stavropoulos 46, J. Steentoft 161, P. Steinberg 29, B. Stelzer 142,156a, H.J. Stelzer 129,O. Stelzer-Chilton 156a, H. Stenzel 58, T.J. Stevenson 146, G.A. Stewart 36,J.R. Stewart 121, M.C. Stockton 36, G. Stoicea 27b, M. Stolarski 130a, S. Stonjek 110,A. Straessner 50, J. Strandberg 144, S. Strandberg 47a,47b, M. Strauss 120, T. Strebler 102,P. Strizenec 28b, R. Str\u00f6hmer 166, D.M. Strom 123, L.R. Strom 48, R. Stroynowski 44,A. Strubig 47a,47b, S.A. Stucci 29, B. Stugu 16, J. Stupak 120, N.A. Styles 48, D. Su 143,S. Su 62a, W. Su 62d, X. Su 62a,66, K. Sugizaki 153, V.V. Sulin 37, M.J. Sullivan 92,D.M.S. Sultan 78a,78b, L. Sultanaliyeva 37, S. Sultansoy 3b, T. Sumida 87, S. Sun 106,S. Sun 170, O. Sunneborn Gudnadottir 161, 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,y, A. Taffard 160, R. Tafirout 156a, J.S. Tafoya Vargas 66,R. Takashima 88, E.P. Takeva 52, Y. Takubo 83, 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 62b, 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,aa, G.N. Taylor 105, W. Taylor 156b, H. Teagle92,A.S. Tee 170, R. Teixeira De Lima 143, P. Teixeira-Dias 95, J.J. Teoh 155, K. Terashi 153,J. Terron 99, S. Terzo 13, M. Testa 53, R.J. Teuscher 155,ab, 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,\u2013 46 \u2013JHEP10(2023)001P. Tipton 172, S.H. Tlou 33g, A. Tnourji 40, K. Todome 23b,23a, S. Todorova-Nova 133,S. Todt50, M. Togawa 83, J. Tojo 89, S. Tok\u00e1r 28a, K. Tokushuku 83, O. Toldaiev 68,R. Tombs 32, M. Tomoto 83,111, L. Tompkins 143,r, K.W. Topolnicki 85b, E. Torrence 123,H. Torres 102,af , E. Torr\u00f3 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. Trocm\u00e9 60, C. Troncon 71a,L. Truong 33c, M. Trzebinski 86, A. Trzupek 86, F. Tsai 145, M. Tsai 106, A. Tsiamis 152,f ,P.V. Tsiareshka37, S. Tsigaridas 156a, A. Tsirigotis 152,w, V. Tsiskaridze 155,E.G. Tskhadadze149a, M. Tsopoulou 152,f , Y. Tsujikawa 87, I.I. Tsukerman 37,V. Tsulaia 17a, S. Tsuno 83, O. Tsur150, K. Tsuri118, D. Tsybychev 145, Y. Tu 64b,A. Tudorache 27b, V. Tudorache 27b, A.N. Tuna 36, S. Turchikhin 38, I. Turk Cakir 3a,R. Turra 71a, T. Turtuvshin 38,ac, P.M. Tuts 41, S. Tzamarias 152,f , P. Tzanis 10,E. Tzovara 100, K. Uchida153, F. Ukegawa 157, P.A. Ulloa Poblete 137c,137b, E.N. Umaka 29,G. Unal 36, M. Unal 11, A. Undrus 29, G. Unel 160, J. Urban 28b, P. Urquijo 105,G. Usai 8, R. Ushioda 154, M. Usman 108, Z. Uysal 21b, L. Vacavant 102, V. Vacek 132,B. Vachon 104, K.O.H. Vadla 125, T. Vafeiadis 36, A. Vaitkus 96, C. Valderanis 109,E. Valdes Santurio 47a,47b, M. Valente 156a, S. Valentinetti 23b,23a, A. Valero 163,E. Valiente Moreno 163, A. Vallier 102,af , 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 17a, T. Varol 148, D. Varouchas 66, L. Varriale 163,K.E. Varvell 147, M.E. Vasile 27b, L. Vaslin40, G.A. Vasquez 165, F. Vazeille 40,T. Vazquez Schroeder 36, J. Veatch 31, V. Vecchio 101, M.J. Veen 103, I. Veliscek 126,L.M. Veloce 155, F. Veloso 130a,130c, S. Veneziano 75a, A. Ventura 70a,70b, A. Verbytskyi 110,M. Verducci 74a,74b, C. Vergis 24, M. Verissimo De Araujo 82b, W. Verkerke 114,J.C. Vermeulen 114, C. Vernieri 143, P.J. Verschuuren 95, M. Vessella 103,M.C. Vetterli 142,ak, A. Vgenopoulos 152,f , 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, V. Vladimirov167,E. Voevodina 110, F. Vogel 109, P. Vokac 132, J. Von Ahnen 48, E. Von Toerne 24,B. Vormwald 36, V. Vorobel 133, K. Vorobev 37, M. Vos 163, K. Voss 141,J.H. Vossebeld 92, M. Vozak 114, L. Vozdecky 94, N. Vranjes 15,M. Vranjes Milosavljevic 15, M. Vreeswijk 114, R. Vuillermet 36, O. Vujinovic 100,I. Vukotic 39, S. Wada 157, C. Wagner103, J.M. Wagner 17a, W. Wagner 171,S. Wahdan 171, H. Wahlberg 90, R. Wakasa 157, M. Wakida 111, J. Walder 134,R. Walker 109, W. Walkowiak 141, A. Wall 128, T. Wamorkar 6, A.Z. Wang 170,C. Wang 100, C. Wang 62c, H. Wang 17a, J. Wang 64a, R.-J. Wang 100, R. Wang 61,R. Wang 6, S.M. Wang 148, S. Wang 62b, T. Wang 62a, W.T. Wang 80, W. Wang 14a,X. Wang 14c, X. Wang 162, X. Wang 62c, Y. Wang 62d, Y. Wang 14c, Z. Wang 106,Z. Wang 62d,51,62c, Z. Wang 106, A. Warburton 104, R.J. Ward 20, N. Warrack 59,A.T. Watson 20, H. Watson 59, M.F. Watson 20, E. Watton 59,134, G. Watts 138,\u2013 47 \u2013JHEP10(2023)001B.M. Waugh 96, C. Weber 29, H.A. Weber 18, M.S. Weber 19, S.M. Weber 63a, C. Wei62a,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, K. Whalen 123, A.M. Wharton 91, A.S. White 61,A. White 8, M.J. White 1, D. Whiteson 160, L. Wickremasinghe 124, W. Wiedenmann 170,C. Wiel 50, M. Wielers 134, C. Wiglesworth 42, D.J. Wilbern120, H.G. Wilkens 36,D.M. Williams 41, H.H. Williams128, S. Williams 32, S. Willocq 103, B.J. Wilson 101,P.J. Windischhofer 39, F.I. Winkel 30, F. Winklmeier 123, B.T. Winter 54, J.K. Winter 101,M. Wittgen143, M. Wobisch 97, Z. Wolffs 114, R. W\u00f6lker 126, J. Wollrath160, M.W. Wolter 86,H. Wolters 130a,130c, A.F. Wongel 48, S.D. Worm 48, B.K. Wosiek 86, K.W. Wo\u017aniak 86,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, T.R. Wyatt 101,B.M. Wynne 52, S. Xella 42, L. Xia 14c, M. Xia 14b, J. Xiang 64c, X. Xiao 106,M. Xie 62a, X. Xie 62a, S. Xin 14a,14e, J. Xiong 17a, D. Xu 14a, H. Xu 62a, L. Xu 62a,R. Xu 128, T. Xu 106, Y. Xu 14b, Z. Xu 52, Z. Xu 14a, B. Yabsley 147, S. Yacoob 33a,N. Yamaguchi 89, Y. Yamaguchi 154, E. Yamashita 153, H. Yamauchi 157, T. Yamazaki 17a,Y. Yamazaki 84, J. Yan62c, S. Yan 126, Z. Yan 25, H.J. Yang 62c,62d, H.T. Yang 62a,S. Yang 62a, T. Yang 64c, X. Yang 62a, X. Yang 14a, Y. Yang 44, Y. Yang62a, Z. Yang 62a,W-M. Yao 17a, Y.C. Yap 48, H. Ye 14c, H. Ye 55, J. Ye 44, S. Ye 29, X. Ye 62a,Y. Yeh 96, I. Yeletskikh 38, B.K. Yeo 17a, M.R. Yexley 96, P. Yin 41, K. Yorita 168,S. Younas 27b, C.J.S. Young 54, C. Young 143, Y. Yu 62a, M. Yuan 106, R. Yuan 62b,l,L. Yue 96, M. Zaazoua 62a, B. Zabinski 86, E. Zaid52, T. Zakareishvili 149b,N. Zakharchuk 34, S. Zambito 56, J.A. Zamora Saa 137d,137b, J. Zang 153, D. Zanzi 54,O. Zaplatilek 132, C. Zeitnitz 171, H. Zeng 14a, J.C. Zeng 162, D.T. Zenger Jr 26,O. Zenin 37, T. \u017deni\u0161 28a, S. Zenz 94, S. Zerradi 35a, D. Zerwas 66, M. Zhai 14a,14e,B. Zhang 14c, D.F. Zhang 139, J. Zhang 62b, J. Zhang 6, K. Zhang 14a,14e, L. Zhang 14c,P. Zhang14a,14e, R. Zhang 170, S. Zhang 106, T. Zhang 153, X. Zhang 62c, X. Zhang 62b,Y. Zhang 62c,5, Y. Zhang 96, Z. Zhang 17a, Z. Zhang 66, H. Zhao 138, P. Zhao 51,T. Zhao 62b, Y. Zhao 136, Z. Zhao 62a, A. Zhemchugov 38, K. Zheng 162, X. Zheng 62a,Z. Zheng 143, D. Zhong 162, B. Zhou106, H. Zhou 7, N. Zhou 62c, Y. Zhou7, C.G. Zhu 62b,J. Zhu 106, Y. Zhu 62c, Y. Zhu 62a, X. Zhuang 14a, K. Zhukov 37, V. Zhulanov 37,N.I. Zimine 38, J. Zinsser 63b, M. Ziolkowski 141, L. \u017divkovi\u0107 15, A. Zoccoli 23b,23a,K. Zoch 56, T.G. Zorbas 139, O. Zormpa 46, W. Zou 41, L. Zwalinski 361 Department of Physics, University of Adelaide, Adelaide, Australia2 Department 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, T\u00fcrkiye4 LAPP, Universit\u00e9 Savoie Mont Blanc, CNRS\/IN2P3, Annecy, France5 APC, Universit\u00e9 Paris Cit\u00e9, CNRS\/IN2P3, Paris, France6 High Energy Physics Division, Argonne National Laboratory, Argonne IL, United States of America7 Department of Physics, University of Arizona, Tucson AZ, United States of America8 Department 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, Greece\u2013 48 \u2013JHEP10(2023)00111 Department of Physics, University of Texas at Austin, Austin TX, United States of America12 Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan13 Institut de F\u00edsica d\u2019Altes 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 ofScience, Shenzhen Campus of Sun Yat-sen University; (e)University of Chinese Academy of Science(UCAS), Beijing, China15 Institute of Physics, University of Belgrade, Belgrade, Serbia16 Department 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 f\u00fcr Physik, Humboldt Universit\u00e4t zu Berlin, Berlin, Germany19 Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics, Universityof Bern, 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,Gaziantep University, Gaziantep; (c)Department of Physics, Istanbul University, Istanbul; (d)IstinyeUniversity, Sariyer, Istanbul, T\u00fcrkiye22 (a)Facultad de Ciencias y Centro de Investigaci\u00f3nes, Universidad Antonio Nari\u00f1o, Bogot\u00e1;(b)Departamento de F\u00edsica, Universidad Nacional de Colombia, Bogot\u00e1; (c)Pontificia UniversidadJaveriana, Bogota, Colombia23 (a)Dipartimento di Fisica e Astronomia A. Righi, Universit\u00e0 di Bologna, Bologna; (b)INFN Sezione diBologna, Italy24 Physikalisches Institut, Universit\u00e4t Bonn, Bonn, Germany25 Department of Physics, Boston University, Boston MA, United States of America26 Department of Physics, Brandeis University, Waltham MA, United States of America27 (a)Transilvania University of Brasov, Brasov; (b)Horia Hulubei National Institute of Physics andNuclear Engineering, Bucharest; (c)Department of Physics, Alexandru Ioan Cuza University of Iasi,Iasi; (d)National Institute for Research and Development of Isotopic and Molecular Technologies,Physics Department, Cluj-Napoca; (e)University Politehnica Bucharest, 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)Departmentof Subnuclear Physics, Institute of Experimental Physics of the Slovak Academy of Sciences, Kosice,Slovak Republic29 Physics Department, Brookhaven National Laboratory, Upton NY, United States of America30 Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de F\u00edsica, yCONICET, Instituto de F\u00edsica de Buenos Aires (IFIBA), Buenos Aires, Argentina31 California State University, CA, United States of America32 Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom33 (a)Department of Physics, University of Cape Town, Cape Town; (b)iThemba Labs, Western Cape;(c)Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg;(d)National Institute of Physics, University of the Philippines Diliman (Philippines); (e)University ofSouth Africa, Department of Physics, Pretoria; (f)University of Zululand, KwaDlangezwa; (g)School ofPhysics, University of the Witwatersrand, Johannesburg, South Africa34 Department of Physics, Carleton University, Ottawa ON, Canada35 (a)Facult\u00e9 des Sciences Ain Chock, R\u00e9seau Universitaire de Physique des Hautes Energies - Universit\u00e9Hassan II, Casablanca; (b)Facult\u00e9 des Sciences, Universit\u00e9 Ibn-Tofail, K\u00e9nitra; (c)Facult\u00e9 des SciencesSemlalia, Universit\u00e9 Cadi Ayyad, LPHEA-Marrakech; (d)LPMR, Facult\u00e9 des Sciences, Universit\u00e9Mohamed Premier, Oujda; (e)Facult\u00e9 des sciences, Universit\u00e9 Mohammed V, Rabat; (f)Institute ofApplied Physics, Mohammed VI Polytechnic University, Ben Guerir, Morocco36 CERN, Geneva, Switzerland\u2013 49 \u2013JHEP10(2023)00137 Affiliated with an institute covered by a cooperation agreement with CERN38 Affiliated with an international laboratory covered by a cooperation agreement with CERN39 Enrico Fermi Institute, University of Chicago, Chicago IL, United States of America40 LPC, Universit\u00e9 Clermont Auvergne, CNRS\/IN2P3, Clermont-Ferrand, France41 Nevis Laboratory, Columbia University, Irvington NY, United States of America42 Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark43 (a)Dipartimento di Fisica, Universit\u00e0 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 America46 National Centre for Scientific Research \u201cDemokritos\u201d, Agia Paraskevi, Greece47 (a)Department of Physics, Stockholm University; (b)Oskar Klein Centre, Stockholm, Sweden48 Deutsches Elektronen-Synchrotron DESY, Hamburg and Zeuthen, Germany49 Fakult\u00e4t Physik, Technische Universit\u00e4t Dortmund, Dortmund, Germany50 Institut f\u00fcr Kern- und Teilchenphysik, Technische Universit\u00e4t Dresden, Dresden, Germany51 Department 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-Universit\u00e4t Freiburg, Freiburg, Germany55 II. Physikalisches Institut, Georg-August-Universit\u00e4t G\u00f6ttingen, G\u00f6ttingen, Germany56 D\u00e9partement de Physique Nucl\u00e9aire et Corpusculaire, Universit\u00e9 de Gen\u00e8ve, Gen\u00e8ve, Switzerland57 (a)Dipartimento di Fisica, Universit\u00e0 di Genova, Genova; (b)INFN Sezione di Genova, Italy58 II. Physikalisches Institut, Justus-Liebig-Universit\u00e4t Giessen, Giessen, Germany59 SUPA - School of Physics and Astronomy, University of Glasgow, Glasgow, United Kingdom60 LPSC, Universit\u00e9 Grenoble Alpes, CNRS\/IN2P3, Grenoble INP, Grenoble, France61 Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge MA,United States of America62 (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 InterdisciplinaryScience and Key Laboratory of Particle Physics and Particle Irradiation (MOE), ShandongUniversity, Qingdao; (c)School of Physics and Astronomy, Shanghai Jiao Tong University, KeyLaboratory for Particle Astrophysics and Cosmology (MOE), SKLPPC, Shanghai; (d)Tsung-Dao LeeInstitute, Shanghai, China63 (a)Kirchhoff-Institut f\u00fcr Physik, Ruprecht-Karls-Universit\u00e4t Heidelberg, Heidelberg; (b)PhysikalischesInstitut, Ruprecht-Karls-Universit\u00e4t Heidelberg, Heidelberg, Germany64 (a)Department of Physics, Chinese University of Hong Kong, Shatin, N.T., Hong Kong;(b)Department of Physics, University of Hong Kong, Hong Kong; (c)Department of Physics andInstitute for Advanced Study, Hong Kong University of Science and Technology, Clear Water Bay,Kowloon, Hong Kong, China65 Department of Physics, National Tsing Hua University, Hsinchu, Taiwan66 IJCLab, Universit\u00e9 Paris-Saclay, CNRS\/IN2P3, 91405, Orsay, France67 Centro Nacional de Microelectr\u00f3nica (IMB-CNM-CSIC), Barcelona, Spain68 Department 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, Universit\u00e0 di Udine, Udine, Italy70 (a)INFN Sezione di Lecce; (b)Dipartimento di Matematica e Fisica, Universit\u00e0 del Salento, Lecce, Italy71 (a)INFN Sezione di Milano; (b)Dipartimento di Fisica, Universit\u00e0 di Milano, Milano, Italy72 (a)INFN Sezione di Napoli; (b)Dipartimento di Fisica, Universit\u00e0 di Napoli, Napoli, Italy73 (a)INFN Sezione di Pavia; (b)Dipartimento di Fisica, Universit\u00e0 di Pavia, Pavia, Italy74 (a)INFN Sezione di Pisa; (b)Dipartimento di Fisica E. Fermi, Universit\u00e0 di Pisa, Pisa, Italy75 (a)INFN Sezione di Roma; (b)Dipartimento di Fisica, Sapienza Universit\u00e0 di Roma, Roma, Italy76 (a)INFN Sezione di Roma Tor Vergata; (b)Dipartimento di Fisica, Universit\u00e0 di Roma Tor Vergata,Roma, Italy\u2013 50 \u2013JHEP10(2023)00177 (a)INFN Sezione di Roma Tre; (b)Dipartimento di Matematica e Fisica, Universit\u00e0 Roma Tre, Roma,Italy78 (a)INFN-TIFPA; (b)Universit\u00e0 degli Studi di Trento, Trento, Italy79 Universit\u00e4t Innsbruck, Department of Astro and Particle Physics, Innsbruck, Austria80 University of Iowa, Iowa City IA, United States of America81 Department of Physics and Astronomy, Iowa State University, Ames IA, United States of America82 (a)Departamento de Engenharia El\u00e9trica, Universidade Federal de Juiz de Fora (UFJF), Juiz de Fora;(b)Universidade Federal do Rio De Janeiro COPPE\/EE\/IF, Rio de Janeiro; (c)Instituto de F\u00edsica,Universidade de S\u00e3o Paulo, S\u00e3o Paulo; (d)Rio de Janeiro State University, Rio de Janeiro, Brazil83 KEK, High Energy Accelerator Research Organization, Tsukuba, Japan84 Graduate School of Science, Kobe University, Kobe, Japan85 (a)AGH University of Krakow, Faculty of Physics and Applied Computer Science, Krakow; (b)MarianSmoluchowski Institute of Physics, Jagiellonian University, Krakow, Poland86 Institute of Nuclear Physics Polish Academy of Sciences, Krakow, Poland87 Faculty of Science, Kyoto University, Kyoto, Japan88 Kyoto University of Education, Kyoto, Japan89 Research Center for Advanced Particle Physics and Department of Physics, Kyushu University,Fukuoka, Japan90 Instituto de F\u00edsica La Plata, Universidad Nacional de La Plata and CONICET, La Plata, Argentina91 Physics Department, Lancaster University, Lancaster, United Kingdom92 Oliver Lodge Laboratory, University of Liverpool, Liverpool, United Kingdom93 Department of Experimental Particle Physics, Jo\u017eef Stefan Institute and Department of Physics,University of Ljubljana, Ljubljana, Slovenia94 School of Physics and Astronomy, Queen Mary University of London, London, United Kingdom95 Department of Physics, Royal Holloway University of London, Egham, United Kingdom96 Department of Physics and Astronomy, University College London, London, United Kingdom97 Louisiana Tech University, Ruston LA, United States of America98 Fysiska institutionen, Lunds universitet, Lund, Sweden99 Departamento de F\u00edsica Teorica C-15 and CIAFF, Universidad Aut\u00f3noma de Madrid, Madrid, Spain100 Institut f\u00fcr Physik, Universit\u00e4t Mainz, Mainz, Germany101 School of Physics and Astronomy, University of Manchester, Manchester, United Kingdom102 CPPM, Aix-Marseille Universit\u00e9, CNRS\/IN2P3, Marseille, France103 Department of Physics, University of Massachusetts, Amherst MA, United States of America104 Department of Physics, McGill University, Montreal QC, Canada105 School of Physics, University of Melbourne, Victoria, Australia106 Department of Physics, University of Michigan, Ann Arbor MI, United States of America107 Department of Physics and Astronomy, Michigan State University, East Lansing MI,United States of America108 Group of Particle Physics, University of Montreal, Montreal QC, Canada109 Fakult\u00e4t f\u00fcr Physik, Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen, M\u00fcnchen, Germany110 Max-Planck-Institut f\u00fcr Physik (Werner-Heisenberg-Institut), M\u00fcnchen, Germany111 Graduate School of Science and Kobayashi-Maskawa Institute, Nagoya University, Nagoya, Japan112 Department of Physics and Astronomy, University of New Mexico, Albuquerque NM,United States of America113 Institute for Mathematics, Astrophysics and Particle Physics, Radboud University\/Nikhef, Nijmegen,The Netherlands114 Nikhef National Institute for Subatomic Physics and University of Amsterdam, Amsterdam,The Netherlands115 Department of Physics, Northern Illinois University, DeKalb IL, United States of America116 (a)New York University Abu Dhabi, Abu Dhabi; (b)University of Sharjah, Sharjah,United Arab Emirates117 Department of Physics, New York University, New York NY, United States of America\u2013 51 \u2013JHEP10(2023)001118 Ochanomizu University, Otsuka, Bunkyo-ku, Tokyo, Japan119 Ohio State University, Columbus OH, United States of America120 Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman OK,United States of America121 Department of Physics, Oklahoma State University, Stillwater OK, United States of America122 Palack\u00fd University, Joint Laboratory of Optics, Olomouc, Czech Republic123 Institute for Fundamental Science, University of Oregon, Eugene, OR, United States of America124 Graduate School of Science, Osaka University, Osaka, Japan125 Department of Physics, University of Oslo, Oslo, Norway126 Department of Physics, Oxford University, Oxford, United Kingdom127 LPNHE, Sorbonne Universit\u00e9, Universit\u00e9 Paris Cit\u00e9, CNRS\/IN2P3, Paris, France128 Department of Physics, University of Pennsylvania, Philadelphia PA, United States of America129 Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh PA,United States of America130 (a)Laborat\u00f3rio de Instrumenta\u00e7\u00e3o e F\u00edsica Experimental de Part\u00edculas - LIP, Lisboa; (b)Departamentode F\u00edsica, Faculdade de Ci\u00eancias, Universidade de Lisboa, Lisboa; (c)Departamento de F\u00edsica,Universidade de Coimbra, Coimbra; (d)Centro de F\u00edsica Nuclear da Universidade de Lisboa, Lisboa;(e)Departamento de F\u00edsica, Universidade do Minho, Braga; (f)Departamento de F\u00edsica Te\u00f3rica y delCosmos, Universidad de Granada, Granada (Spain); (g)Departamento de F\u00edsica, Instituto SuperiorT\u00e9cnico, Universidade de Lisboa, Lisboa, Portugal131 Institute of Physics of the Czech Academy of Sciences, Prague, Czech Republic132 Czech Technical University in Prague, Prague, Czech Republic133 Charles University, Faculty of Mathematics and Physics, Prague, Czech Republic134 Particle Physics Department, Rutherford Appleton Laboratory, Didcot, United Kingdom135 IRFU, CEA, Universit\u00e9 Paris-Saclay, Gif-sur-Yvette, France136 Santa Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz CA,United States of America137 (a)Departamento de F\u00edsica, Pontificia Universidad Cat\u00f3lica de Chile, Santiago; (b)MillenniumInstitute for Subatomic physics at high energy frontier (SAPHIR), Santiago; (c)Instituto deInvestigaci\u00f3n Multidisciplinario en Ciencia y Tecnolog\u00eda, y Departamento de F\u00edsica, Universidad deLa Serena; (d)Universidad Andres Bello, Department of Physics, Santiago; (e)Instituto de AltaInvestigaci\u00f3n, Universidad de Tarapac\u00e1, Arica; (f)Departamento de F\u00edsica, Universidad T\u00e9cnicaFederico Santa Mar\u00eda, Valpara\u00edso, Chile138 Department of Physics, University of Washington, Seattle WA, United States of America139 Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom140 Department of Physics, Shinshu University, Nagano, Japan141 Department Physik, Universit\u00e4t Siegen, Siegen, Germany142 Department of Physics, Simon Fraser University, Burnaby BC, Canada143 SLAC National Accelerator Laboratory, Stanford CA, United States of America144 Department of Physics, Royal Institute of Technology, Stockholm, Sweden145 Departments of Physics and Astronomy, Stony Brook University, Stony Brook NY,United States of America146 Department 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)HighEnergy Physics Institute, Tbilisi State University, Tbilisi; (c)University of Georgia, Tbilisi, Georgia150 Department of Physics, Technion, Israel Institute of Technology, Haifa, Israel151 Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv University, Tel Aviv, Israel152 Department of Physics, Aristotle University of Thessaloniki, Thessaloniki, Greece153 International Center for Elementary Particle Physics and Department of Physics, University ofTokyo, Tokyo, Japan\u2013 52 \u2013JHEP10(2023)001154 Department of Physics, Tokyo Institute of Technology, Tokyo, Japan155 Department of Physics, University of Toronto, Toronto ON, Canada156 (a)TRIUMF, Vancouver BC; (b)Department of Physics and Astronomy, York University, Toronto ON,Canada157 Division of Physics and Tomonaga Center for the History of the Universe, Faculty of Pure andApplied Sciences, University of Tsukuba, Tsukuba, Japan158 Department of Physics and Astronomy, Tufts University, Medford MA, United States of America159 United Arab Emirates University, Al Ain, United Arab Emirates160 Department of Physics and Astronomy, University of California Irvine, Irvine CA,United States of America161 Department of Physics and Astronomy, University of Uppsala, Uppsala, Sweden162 Department of Physics, University of Illinois, Urbana IL, United States of America163 Instituto de F\u00edsica Corpuscular (IFIC), Centro Mixto Universidad de Valencia - CSIC, Valencia,Spain164 Department of Physics, University of British Columbia, Vancouver BC, Canada165 Department of Physics and Astronomy, University of Victoria, Victoria BC, Canada166 Fakult\u00e4t f\u00fcr Physik und Astronomie, Julius-Maximilians-Universit\u00e4t W\u00fcrzburg, W\u00fcrzburg, Germany167 Department of Physics, University of Warwick, Coventry, United Kingdom168 Waseda University, Tokyo, Japan169 Department of Particle Physics and Astrophysics, Weizmann Institute of Science, Rehovot, Israel170 Department of Physics, University of Wisconsin, Madison WI, United States of America171 Fakult\u00e4t f\u00fcr Mathematik und Naturwissenschaften, Fachgruppe Physik, Bergische Universit\u00e4tWuppertal, Wuppertal, Germany172 Department of Physics, Yale University, New Haven CT, United States of Americaa Also Affiliated with an institute covered by a cooperation agreement with CERNb Also at An-Najah National University, Nablus, Palestinec Also at APC, Universit\u00e9 Paris Cit\u00e9, CNRS\/IN2P3, Paris, Franced Also at Borough of Manhattan Community College, City University of New York, New York NY,United States of Americae Also at Center for High Energy Physics, Peking University, Chinaf Also at Center for Interdisciplinary Research and Innovation (CIRI-AUTH), Thessaloniki, Greeceg Also at Centro Studi e Ricerche Enrico Fermi, Italyh Also at CERN, Geneva, Switzerlandi Also at D\u00e9partement de Physique Nucl\u00e9aire et Corpusculaire, Universit\u00e9 de Gen\u00e8ve, Gen\u00e8ve,Switzerlandj Also at Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona, Spaink Also at Department of Financial and Management Engineering, University of the Aegean, Chios,Greecel Also at Department of Physics and Astronomy, Michigan State University, East Lansing MI,United States of Americam Also at Department of Physics and Astronomy, University of Victoria, Victoria BC, Canadan Also at Department of Physics, Ben Gurion University of the Negev, Beer Sheva, Israelo Also at Department of Physics, California State University, Sacramento, United States of Americap Also at Department of Physics, King\u2019s College London, London, United Kingdomq Also at Department of Physics, Royal Holloway University of London, Egham, United Kingdomr Also at Department of Physics, Stanford University, Stanford CA, United States of Americas Also at Department of Physics, University of Fribourg, Fribourg, Switzerlandt Also at Department of Physics, University of Thessaly, Greeceu Also at Department of Physics, Westmont College, Santa Barbara, United States of Americav Also at Fakult\u00e4t f\u00fcr Mathematik und Naturwissenschaften, Fachgruppe Physik, Bergische Universit\u00e4tWuppertal, Wuppertal, Germanyw Also at Hellenic Open University, Patras, Greece\u2013 53 \u2013JHEP10(2023)001x Also at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona, Spainy Also at Institut f\u00fcr Experimentalphysik, Universit\u00e4t Hamburg, Hamburg, Germanyz Also at Institute for Nuclear Research and Nuclear Energy (INRNE) of the Bulgarian Academy ofSciences, Sofia, Bulgariaaa Also at Institute of Applied Physics, Mohammed VI Polytechnic University, Ben Guerir, Moroccoab Also at Institute of Particle Physics (IPP), Canadaac Also at Institute of Physics and Technology, Ulaanbaatar, Mongoliaad Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijanae Also at Institute of Theoretical Physics, Ilia State University, Tbilisi, Georgiaaf Also at L2IT, Universit\u00e9 de Toulouse, CNRS\/IN2P3, UPS, Toulouse, Franceag Also at Lawrence Livermore National Laboratory, Livermore, United States of Americaah Also at National Institute of Physics, University of the Philippines Diliman (Philippines), Philippinesai Also at Technical University of Munich, Munich, Germanyaj Also at The Collaborative Innovation Center of Quantum Matter (CICQM), Beijing, Chinaak Also at TRIUMF, Vancouver BC, Canadaal Also at Universit\u00e0 di Napoli Parthenope, Napoli, Italyam Also at University of Colorado Boulder, Department of Physics, Colorado, United States of Americaan Also at Washington College, Chestertown, MD, United States of Americaao Also at Yeditepe University, Physics Department, Istanbul, T\u00fcrkiye\u2217 Deceased\u2013 54 \u2013","@language":"en"}],"Genre":[{"@value":"Article","@language":"en"}],"IsShownAt":[{"@value":"10.14288\/1.0437568","@language":"en"}],"Language":[{"@value":"eng","@language":"en"}],"PeerReviewStatus":[{"@value":"Reviewed","@language":"en"}],"Provider":[{"@value":"Vancouver : University of British Columbia Library","@language":"en"}],"Publisher":[{"@value":"Springer Berlin Heidelberg","@language":"en"}],"PublisherDOI":[{"@value":"10.1007\/JHEP10(2023)001","@language":"en"}],"Rights":[{"@value":"Attribution 4.0 International (CC BY 4.0)","@language":"en"}],"RightsURI":[{"@value":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/","@language":"en"}],"ScholarlyLevel":[{"@value":"Faculty","@language":"en"}],"Subject":[{"@value":"Beyond Standard Model","@language":"en"},{"@value":"Hadron-Hadron Scattering","@language":"en"}],"Title":[{"@value":"Search for leptoquarks decaying into the b\u03c4 final state in pp collisions at \u221as = 13 TeV with the ATLAS detector","@language":"en"}],"Type":[{"@value":"Text","@language":"en"}],"URI":[{"@value":"http:\/\/hdl.handle.net\/2429\/86479","@language":"en"}],"SortDate":[{"@value":"2023-10-02 AD","@language":"en"}],"@id":"doi:10.14288\/1.0437568"}