Search for leptonic charge asymmetry in tt¯ W production in final states with three leptons at √s = 13 TeV

JHEP07(2023)033 Published for SISSA by Springer Received:January 12, 2023 Revised:May 26, 2023 Accepted:June 17, 2023 Published:July 5, 2023 Search for leptonic charge asymmetry in t¯ tW production in final states with three leptons at √s= 13 TeV The ATLAS collaboration E-mail: [email protected] Abstract: A search for the leptonic charge asymmetry ( A` c ) of top-quark-antiquark pair production in association with a W boson ( t¯ tW ) is presented. The search is performed using final states with exactly three charged light leptons (electrons or muons) and is based on √s = 13 TeV proton-proton collision data collected with the ATLAS detector at the Large Hadron Collider at CERN during the years 2015–2018, corresponding to an integrated luminosity of 139fb −1 . A profile-likelihood fit to the event yields in multiple regions corresponding to positive and negative differences between the pseudorapidities of the charged leptons from top-quark and top-antiquark decays is used to extract the charge asymmetry. At reconstruction level, the asymmetry is found to be − 0 . 12 ± 0 . 14 (stat.) ± 0 . 05 (syst.). An unfolding procedure is applied to convert the result at reconstruction level into a charge-asymmetry value in a fiducial volume at particle level with the result of − 0 . 11 ± 0 . 17 (stat.) ± 0 . 05 (syst.). The Standard Model expectations for these two observables are calculated using Monte Carlo simulations with next-to-leading-order plus parton shower precision in quantum chromodynamics and including next-to-leading-order electroweak corrections. They are − 0 . 084 +0.005 −0.003 (scale) ± 0 . 006 (MC stat.) and − 0 . 063 +0.007 −0.004 (scale) ±0.004 (MC stat.) respectively, and in agreement with the measurements. Keywords: Hadron-Hadron Scattering , Top Physics ArXiv ePrint: 2301.04245 Open Access, Copyright CERN, for the benefit of the ATLAS Collaboration. Article funded by SCOAP3. https://doi.org/10.1007/JHEP07(2023)033 JHEP07(2023)033 Contents 1 Introduction 1 2 The ATLAS detector 4 3 Data and simulated event samples 5 4 Event reconstruction 8 5 Event selection and definitions of control and signal regions 10 6 Lepton–top-quark matching 11 7 Systematic uncertainties in background and signal estimation 12 7.1 Detector-related uncertainties 12 7.2 Signal and background modelling uncertainties 13 8 Extraction of the charge asymmetry at reconstruction level 14 9 Unfolding and extraction of the charge asymmetry at particle level 22 9.1 Particle-level objects 22 9.2 Particle-level fiducial volume 23 9.3 Unfolding procedure and charge-asymmetry extraction 23 10 Conclusions 26 The ATLAS collaboration 35 1 Introduction The production of a top-quark–antiquark ( t¯ t ) pair in association with a W boson, commonly referred to as t¯ tW , is a rare process in the Standard Model (SM) that can be produced at the Large Hadron Collider (LHC). State-of-the-art cross-section calculations for the t¯ tW process are especially complex, as large corrections arise from higher powers of both the strong and weak couplings [ 1 ]. Thus, measurements of the t¯ tW process represent a sensitive test of the predictions of quantum chromodynamics (QCD) and the electroweak (EW) sector of the SM, as well as their interplay. Both the inclusive and differential cross-section measurements are very relevant, as they can provide indirect hints of new physics beyond the SM (BSM) in scenarios where at least one of the SM couplings is modified [ 2 ]. Furthermore, the t¯ tW process can be one of the main backgrounds in searches for BSM phenomena, such as supersymmetric squark or gluino production or vector-like quarks [ 3 , 4 ]. It also represents – 1 – JHEP07(2023)033 t ¯ t W± ¯q q′ g t ¯ t W± ¯q q′ Z/γ t ¯ t ¯q′ W± ¯q g W± t ¯ t ¯q′ ¯q g H (a) (b) (c) (d) Figure 1. Examples of Feynman diagrams of t¯ tW production at (a,b) LO and (c,d) NLO with one extra parton. The diagrams show (a,c) QCD and (b,d) EW t¯ tW production. an irreducible background in many measurements of SM processes such as t¯ t production in association with a Higgs boson ( t¯ tH ) or the production of four top quarks ( t¯ tt¯ t ) [ 5 , 6 ]. The inclusive cross-section of t¯ tW production has been measured by both the ATLAS and CMS collaborations at √s = 13 TeV using partial and full LHC Run 2 datasets [ 7 , 8 ], respectively. Illustrative Feynman diagrams contributing to t¯ tW production at leading order (LO) and next-to-leading order (NLO) for both QCD and EW production are shown in figure 1 where q0 indicates a quark of different flavour from that of the other initial-state quark. At LO, only the q¯q0 initial state is present (figure 1a,b). At NLO, the quark-gluon ( qg ) channels open up (figure 1c,d), whereas gluon-gluon ( gg ) fusion production does not contribute until next-to-next-to-leading-order (NNLO) corrections are included. In t¯ t production, the top quark (top antiquark) is preferentially produced in the direction of the incoming quark (antiquark). This is due to the interference effects between amplitudes in the q¯q initial state and results in a difference in the rapidity distribution between top quarks and top antiquarks. 1 In proton-proton ( pp ) collisions at the LHC, this production asymmetry results in a central-forward rapidity charge asymmetry as top quarks (antiquarks) are produced with more forward (central) rapidities. Given that t¯ t production at the LHC is dominated by the charge-symmetric gg initial state, such asymmetry is a subtle (order of 1%) effect. This is different from the situation at the Tevatron collider ( p¯p collisions), where a forward-backward asymmetry can be defined with respect to the proton beam, and q¯qcollisions dominate over gg, yielding a more sizable signal (10%) [9]. The top-quark-based rapidity charge asymmetry (At c,y) is defined by At c,y =N(∆yt>0) −N(∆yt<0) N(∆yt>0) + N(∆yt<0),(1.1) where ∆ yt = |yt|−|y¯ t| is the difference between the absolute rapidities of the top quark ( |yt| ) and top antiquark (|y¯ t|), respectively. In t¯ tW production, the relative dominance of the q¯q0 initial state leads to a larger rapidity charge asymmetry than in t¯ t production [ 10 , 11 ]. Furthermore, the W boson present 1 ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point in the centre of the detector and the z -axis along the beam pipe. The x -axis points from the interaction point to the centre of the LHC ring, and the y -axis points upwards. Cylindrical coordinates ( r, φ )are used in the transverse plane, φ being the azimuthal angle around the z -axis. The rapidity ( y ) of a particle is given by y = 1 / 2 ln ( E + pz ) / ( E−pz ). The pseudorapidity ( η ) is defined in terms of the polar angle θ as η=−ln tan(θ/2). The angular distance is measured in units of ∆R≡p(∆η)2+ (∆φ)2. – 2 – JHEP07(2023)033 in t¯ tW production is typically radiated from the initial q¯q0 state and, therefore, serves as a polarity filter of the initial q¯q0 state and in turn the final t¯ t state. This polarisation further enhances the asymmetry between the decay products of the top quarks and top antiquarks. The prospects for experimental observation of these asymmetries are greatest in the case of the charged leptons originating from the top-quark (antiquark) decays. This is due to the precision with which the lepton kinematics can be reconstructed and the power with which reducible background processes can be suppressed. The leptonic charge asymmetry ( A` c ), in the following just referred to as “charge asymmetry”, is defined analogously to eq. (1.1), but based on the pseudorapidities of the leptons from the top-quark and top-antiquark decays: A` c=N(∆η`>0) −N(∆η`<0) N(∆η`>0) + N(∆η`<0),(1.2) where ∆ η` = |η`|−|η¯ `| is the difference between the absolute pseudorapidities of the leptons that originate from the top quark (|η`|) and top antiquark (|η¯ `|), respectively. Reference [ 10 ] gives a comparison of NLO QCD matrix elements (MEs) matched to parton shower (PS) calculations of the top-quark-based and leptonic charge asymmetries of t¯ t and t¯ tW production in the full phase space at √s = 13 TeV . The charge asymmetry for t¯ tW is larger than for t¯ t production at the expense of a smaller cross-section for the process. In addition to being sensitive to BSM physics, such as axigluons and Standard Model Effective Field Theory (SMEFT) scenarios corresponding to four-fermion operators (examples given in refs. [ 10 ] and [ 12 ]), charge asymmetry measurements have the potential to discriminate between new physics signals with different chiral structures that would be indistinguishable using only cross-section observables. At the Tevatron, forward-backward asymmetries in t¯ t production have been measured, with results found to be in agreement with SM calculations that include higher-order corrections [ 9 , 13 ]. The ATLAS and CMS collaborations performed measurements of the top-quark-based charge asymmetry for t¯ t production. A combination of these ATLAS and CMS results at √s = 7 TeV and 8 TeV for the top-quark-based charge asymmetry is reported in ref. [ 14 ] and updated measurements have been published by ATLAS and CMS using √s = 13 TeV data [ 15 , 16 ]. The measurements reported by CMS in ref. [ 17 ] include an extraction of the leptonic charge asymmetry for t¯ t production in a particle-level fiducial volume. A measurement of the top-quark-based charge asymmetry for t¯ t production in association with a photon has been reported by ATLAS in ref. [ 18 ]. None of these measurements show significant deviations from the SM expectations. In ref. [ 11 ], NLO QCD calculations of A` c have been performed including top-quark off-shell effects, which also include the impact of different renormalisation and factorisation scale choices on A` c in the multi-lepton channel at the LHC at √s= 13 TeV.2 This paper presents a search for the leptonic charge asymmetry in t¯ tW production using pp collision data at √s = 13 TeV in the trilepton (3 ` ) channel with the full Run 2 data sample, corresponding to an integrated luminosity of 139 fb−1 . The paper is organised as follows. Section 2provides a brief description of the ATLAS detector. In section 3, the 2These results are given in terms of the rapidities of the leptons (A` c,y) and not the pseudorapidities. – 3 – JHEP07(2023)033 data sample as well as the simulated signal and background processes are discussed. The reconstructed particle candidates are defined in section 4. Section 5gives an overview of the event selection and of the definitions of the control and signal regions. The algorithm used to identify reconstructed leptons originating from top quarks (antiquarks) is explained in section 6. In section 7, the sources of systematic uncertainties that affect the search are discussed. The result for the charge asymmetry measurement at reconstruction level is presented in section 8. The unfolding procedure and the extraction of the charge asymmetry at particle level are presented in section 9. In section 10, the conclusions are drawn. 2 The ATLAS detector The ATLAS detector [ 19 ] at the LHC covers nearly the entire solid angle around the collision point. It consists of an inner tracking detector surrounded by a thin superconducting solenoid, electromagnetic and hadronic calorimeters, and a muon spectrometer incorporating three sets of large superconducting toroidal magnets, each consisting of eight separate coils. The inner-detector system is immersed in a 2 T axial magnetic field and provides charged-particle tracking in the range |η|<2.5. The high-granularity silicon pixel detector covers the vertex region and typically provides four measurements per track, with the first hit typically being detected in the insertable B-layer installed before Run 2 [ 20 , 21 ]. It is followed by the silicon microstrip tracker, which usually provides eight measurements per track. These silicon detectors are complemented by the transition radiation tracker (TRT), which enables radially extended track reconstruction up to |η| = 2 . 5. The TRT also provides electron identification information based on the fraction of hits above a higher energy-deposit threshold corresponding to transition radiation. Typically, around 30 TRT hits are measured in total per track. The calorimeter system covers the pseudorapidity range |η|< 4 . 9. In the region |η|< 3 . 2, electromagnetic calorimetry is provided by barrel and endcap high-granularity lead/liquid-argon (LAr) calorimeters, with an additional thin LAr presampler covering |η|< 1 . 8to correct for energy loss in material upstream of the calorimeters. Hadronic calorimetry is provided by the steel/scintillator-tile calorimeter, segmented into three barrel structures with |η|< 1 . 7, and two copper/LAr hadronic endcap calorimeters. The solid angle coverage is extended with forward copper/LAr and tungsten/LAr calorimeter modules optimised for electromagnetic and hadronic measurements respectively. The muon spectrometer comprises separate trigger and high-precision tracking chambers measuring the deflection of muons in a magnetic field generated by the superconducting air-core toroids. The field integral of the toroids ranges between 2.0 and 6.0 Tm across most of the detector. A set of precision chambers covers the region |η|< 2 . 7with three layers of monitored drift tubes, complemented by cathode-strip chambers in the forward region, where the background rates are highest. The muon trigger system covers the range |η|< 2 . 4 with resistive-plate chambers in the barrel, and thin-gap chambers in the endcap regions. Relevant events are selected to be recorded by the first-level trigger system implemented in custom hardware, followed by selections made by algorithms implemented in software in the high-level trigger [ 22 ]. The first-level trigger accepts events from the 40 MHz bunch – 4 – JHEP07(2023)033 crossings at a rate below 100 kHz , which the high-level trigger reduces to record events to disk at about 1 kHz. An extensive software suite [ 23 ] is used in data simulation, in the reconstruction and analysis of real and simulated data, in detector operations, and in the trigger and data acquisition systems of the experiment. 3 Data and simulated event samples The analysis is performed on data from pp collisions at √s = 13 TeV delivered by the LHC and recorded by the ATLAS detector in the years 2015–2018. The bunch spacing for this data-taking period was 25 ns with a typical number of pp interactions per bunch crossing (“pile-up”) that varies by year and LHC beam conditions and was in the range from 10 to 70 for almost all events. After requirements on the stability of the beams, the operational status of all ATLAS detector components, and the quality of the recorded data, the total integrated luminosity of the data sample corresponds to 139 fb−1 with an uncertainty of 1.7%. This value is derived from the calibration of the luminosity scale using x – y beam-separation scans, following a methodology similar to that detailed in ref. [ 24 ], and using the LUCID-2 detector [25] for the baseline luminosity measurements. Simulated Monte Carlo (MC) samples are used to model the contributions from the various SM processes. The MC generators used for the hard-scattering, as well as the PS, underlying event and hadronisation, are explained in the following. For some processes, in addition to the nominal simulation, alternative MC samples are available that are used to evaluate the effects of different MC modelling uncertainties (see section 7.2). All MC samples were generated using a 25 ns bunch-spacing configuration. The effect of pile-up was modelled by overlaying the hard-scattering event with simulated minimum-bias events generated with Pythia 8.186 [ 26 ] using the NNPDF2.3lo [ 27 ] set of parton distribution functions (PDFs) and the A3 set of tuned MC parameters [ 28 ]. Separate MC production campaigns were used to model the different pile-up distributions observed in data for the years 2015/16, 2017 and 2018. The simulated samples were reweighted to reproduce the observed distribution of the average number of collisions per bunch crossing. The simulation of detector effects was performed with either a full ATLAS detector simulation based on the Geant4 [ 29 ] framework or a fast simulation (AtlFast-II) using a parameterisation of the performance of the electromagnetic and hadronic calorimeters and Geant4 for the other detector components [30]. The signal process ( t¯ tW ) was simulated at NLO precision in QCD with Sherpa 2.2.10 [ 31 ] and the NNPDF3.0nnlo PDF set [ 32 ]. In this set-up, multiple MEs were matched and merged with the Sherpa PS model based on the Catani-Seymour dipole factorisation scheme [ 33 , 34 ]. The virtual QCD corrections for MEs at NLO accuracy were provided by the OpenLoops library [ 35 , 36 ]. Up to one additional parton was included in the NLO ME, and two, three or four additional partons were included at LO in QCD. The merging scale parameter, which sets a threshold to determine what part of the phase-space is filled by the PS or the ME generator, was set to an energy of 30 GeV . Additional partons beyond ME-level accuracy and below the merging scale threshold were therefore described – 5 – JHEP07(2023)033 by the PS. The choice of renormalisation and factorisation scales was µR = µF = HT /2, where HT is defined as the scalar sum of the transverse masses qp2 T+m2 of all final state particles. The masses of the top quark and the W boson were set to 172.5 GeV and 80.4 GeV , respectively [ 37 ]. In addition to the nominal prediction at NLO in QCD (order of αα3 s ), 3 higher-order corrections related to EW t¯ tW contributions were also added as part of the signal definition. The α3 and α2α2 s corrections were added through MC event weights derived using the virtual additive corrections in the formalism described in ref. [38]. An alternative t¯ tW sample uses MadGraph5_aMC@NLO 2.9.3 [ 39 , 40 ] (in the following denoted by MG5_aMC@NLO) for the ME and was interfaced to Pythia 8.245 [ 41 ] for the PS, underlying event and hadronisation modelling. This sample was generated with the FxFx algorithm [ 42 ] with up to one additional parton at NLO accuracy and up to two additional partons at LO accuracy in QCD. The expected accuracy of this sample is similar to that of the nominal Sherpa 2.2.10 sample. This multi-leg configuration makes use of complex functional forms for the renormalisation and factorisation scales that are chosen dynamically and depend on the kinematics of the event after the merging of the core process with the additional partons following the FxFx merging prescription [ 42 – 44 ]. They depend on the phase-space configuration and are related to the clustering scales of the additional partons and on the core process. The merging scale parameter was set to 30 GeV . The sample was simulated using the NNPDF3.0nlo PDF set and the A14 set of tuned MC parameters [ 45 ], henceforth referred to as the “A14 MC tune”. Top-quark decays were simulated at LO using the MadSpin program [ 46 , 47 ]. Further alternative t¯ tW samples were simulated with the Powheg [ 48 ] generator providing ME calculations at NLO in αs with the NNPDF3.0nlo PDF set and the A14 MC tune. These Powheg t¯ tW samples were interfaced either with Pythia 8.245 or with Herwig 7.2.1 [ 49 – 51 ] for the simulation of the PS, underlying event and hadronisation. All the alternative t¯ tW samples were normalised to the same cross-section as the nominal Sherpa 2.2.10 sample in order not to be sensitive to overall normalisation differences when comparing the two simulations. The t¯ tW EW corrections at the order of α3αs were simulated by an independent Sherpa 2.2.10 sample, produced at LO in QCD with the same configuration as the nominal signal sample. Since the charge asymmetry from these processes is negligible compared to the nominal signal contribution, this MC sample is treated as a background in the analysis. The production of a t¯ t pair in association with a Z boson ( t¯ tZ ) was simulated at NLO precision with the MG5_aMC@NLO 2.8.1 generator for the ME and Pythia 8.244 for the PS, underlying event and hadronisation, together with the NNPDF3.0nlo PDF set and the A14 MC tune. The mass of the Z boson was set to 91.2 GeV [ 37 ]. The t¯ tγ∗ contribution and Z/γ∗ interference effects were taken into account, with the samples including events with dilepton invariant masses ( m`` ) down to 1 GeV , where ` is an electron or muon. Additional t¯ tZ samples using MG5_aMC@NLO 2.8.1 for the ME, but Herwig 7.2.1 for the PS along with the Herwig standard set of tuned parameters and the NNPDF3.0nlo PDF set were used for the evaluation of systematic uncertainties associated with the PS and hadronisation. Further alternative t¯ tZ samples with the same settings as the nominal samples, but using 3αand αsdenote the EW and strong coupling constants, respectively. – 6 – JHEP07(2023)033 the A14 eigentune variation Var3c [ 45 ], are used to evaluate the uncertainty associated with the initial-state radiation (ISR). Similarly to t¯ tW , the alternative t¯ tZ samples were normalised to the same cross-section as the nominal sample. The production of t¯ t , t¯ tH and tW events was simulated at NLO with the Powheg generator for the ME, together with the NNPDF3.0nlo PDF set and the A14 MC tune. The hdamp parameter, which controls the matching in Powheg and regulates the highpT radiation against which the t¯ t system recoils, was set to 1.5 times the nominal top-quark mass [ 52 ]. The events were interfaced to Pythia 8.230 for the PS, underlying event and hadronisation. The t¯ t cross-section was normalised to next-to-next-to-leading-logarithmic order (NNLL) in QCD, including the resummation of NNLL soft-gluon terms (NNLO + NNLL) [ 53 , 54 ]. The t¯ tH samples were normalised to NLO (QCD and EW) using the calculations documented in ref. [ 55 ]. The tW sample was normalised to NLO in QCD including NNLL soft-gluon corrections [ 56 ]. An alternative t¯ t simulation was used with the same set-up for the ME, but the events were interfaced to Herwig 7.1.3 [ 57 ] for the PS, underlying event and hadronisation modelling. The Herwig standard set of tuned parameters and the NNPDF3.0nlo PDF set were used. Alternative t¯ tH samples were used, where either the ME generator (MG5_aMC@NLO 2.6.0) or the PS algorithm (Herwig 7.2.1) was changed with respect to the nominal t¯ tH simulation. A MC sample featuring the production of t¯ t events in association with photons ( t¯ tγ ) was simulated at LO in QCD with MG5_aMC@NLO 2.3.3 and interfaced to Pythia 8.212, together with the NNPDF3.0nlo PDF set and the A14 MC tune. This sample is, however, only used to assign an extra uncertainty to additional photon radiation in the nominal t¯ t prediction. Details of this procedure can be found in section 7.2. The production of a single top quark (or antiquark) in association with a Z boson and one extra parton ( tZq ) was simulated using the MG5_aMC@NLO 2.3.3 generator at NLO with the NNPDF3.0nnlo PDF set. The events were interfaced to Pythia 8.245 using the A14 MC tune. The tZq simulation also includes off-shell Z boson decays into dilepton pairs with invariant masses in the range m`` >5 GeV . Single top quark (antiquark) production in association with both a W and a Z boson ( tWZ ) was simulated at NLO with MG5_aMC@NLO 2.2.2 and the NNPDF3.0nnlo PDF set, using Pythia 8.235 for the PS simulation. The interference between t¯ tZ and tWZ was removed following a diagram-removal (DR) approach referred to as the “DR1 scheme” [58]. The MC samples featuring Z+jets production were simulated at NLO with the Powheg generator for the ME and interfaced to Pythia 8.186 for the PS. The AZNLO [ 59 ] set of tuned parameters and the NNPDF3.0nnlo PDF set were used. An alternative Z+jets simulation was done with the Sherpa 2.2.11 generator where the default Sherpa PS set-up was used along with the NNPDF3.0nnlo PDF set. The Z+jets samples feature events with m`` down to 10 GeV . The sample cross-sections were normalised to NNLO predictions [ 60 ]. The Powheg +Pythia 8 sample used Photos [ 61 ] for final-state radiation (FSR). For the simulation of Z boson production in association with a photon ( Zγ ), Sherpa 2.2.11 was used with the NNPDF3.0nnlo PDF set. The events were simulated at NLO precision. – 7 – JHEP07(2023)033 Diboson processes featuring the production of three charged leptons and one neutrino or four charged leptons (denoted by WZ +jets or ZZ +jets , respectively) were simulated using the Sherpa 2.2.2 generator, with a similar set-up to that described for Z+jets . Events with up to one extra parton were simulated at NLO, and with two or three partons at LO precision. MC samples featuring Higgs boson production in association with a W or Z boson ( H+W/Z ) were generated at NLO using Powheg interfaced to Pythia 8.230/8.235 for the PS, together with the NNPDF3.0nlo PDF set and the AZNLO MC tune. The production of four top quarks ( t¯ tt¯ t ) was modelled at NLO with Sherpa 2.2.11 together with the NNPDF3.0nnlo PDF set. The production of three top quarks ( tt¯ t ) and the production of a t¯ t pair with two W bosons ( t¯ tWW ) were simulated at LO using MG5_aMC@NLO 2.2.2 interfaced to Pythia 8.186 with the A14 MC tune and the NNPDF2.3lo PDF set. Fully leptonically decaying triboson processes ( WWW , WWZ , WZZ and ZZZ ) with up to six leptons in the final states were simulated with Sherpa 2.2.2 and the NNPDF3.0nlo PDF set. Final states with no additional partons were calculated at NLO, whereas final states with one, two or three additional partons were calculated at LO. For all MC samples except the Sherpa ones, the decays of b - and c -hadrons were simulated using the EvtGen 1.2.0 program [62]. 4 Event reconstruction Electron candidates are reconstructed from clusters of energy deposits in the electromagnetic calorimeter that are matched to tracks in the inner detector. They are required to satisfy pT>10 GeV , |η|< 2 . 47 and need to pass a “Tight” working point (WP), defined by a likelihood-based electron identification (ID) requirement [ 63 ]. To reject non-prompt electrons, the reconstructed track associated with the electron must satisfy the requirements |z0sin ( θ ) |<0.5 mm and |d0|/σ ( d0 ) < 5, where z0 describes the longitudinal impact parameter relative to the reconstructed primary vertex, 4d0 is the transverse impact parameter relative to the beam axis, and σ ( d0 )is the uncertainty in d0 . Electron candidates are excluded if their calorimeter energy clusters lie within 1 . 37 <|η|< 1 . 52, the transition region between the barrel and the endcap of the electromagnetic calorimeter. Additional requirements are applied to the electron candidates to suppress the contribution of electrons originating from converted photons ( γ -conversions). Electrons can be identified as internalor material-conversion candidates by checking for additional tracks close to the calorimeter energy clusters associated with the electrons and the existence of conversion vertices. Electrons that are identified as either internalor material-conversion candidates are rejected. These requirements are referred to in the following as “ e/γ ambiguity requirements”. Furthermore, the electrons selected for the signal regions (SRs) of the analysis have to satisfy an isolation requirement. An isolation WP is defined using a multivariate likelihood 4 The primary vertex is defined as the vertex (at least two associated tracks with pT>500 MeV ) with the highest scalar sum of the squared transverse momenta of the associated tracks. – 8 – JHEP07(2023)033 according to the MC event records of the selected leptons. The variables used as input to the binned likelihood fit are the pT of the third (softest) lepton in CRHFe and CRHFµ , as well as the scalar sum of the pT of the selected jets in the event ( HT ) in CRt¯ tZ , since their distributions show a sizeable shape difference between the targeted processes and the other SM backgrounds. In the SRs and CR-γ-conv, the total numbers of events are used. Each of the four SRs is separated into ∆ η` BDT ≤ 0(∆ η− ) and ∆ η` BDT > 0(∆ η+ ) regions. For the ∆ η− (∆ η+ ) set of regions, a single factor N∆η− ( N∆η+ ) models the normalisations of the signal yields (relatively to the SM cross-section) across the four SRs. Accordingly, the A` c value is extracted as a function of these normalisation factors. Similarly, separate normalisation factors in the ∆ η− and ∆ η+ sets of regions for the major background processes are allowed to float freely in the fit to avoid a bias from an assumption of SM asymmetries for these processes in data. 5 An “injection test” is performed to verify that the fit result matches an injected non-SM A` c value and the fit can deal correctly with the fact that the different SRs have different charge asymmetries. The predicted and observed numbers of events in the SRs and CRs before performing the simultaneous fit (“pre-fit”) are shown in table 2. The indicated uncertainties consider statistical as well as all experimental and theoretical systematic uncertainties described in section 7. The numbers of events in the SRs and CRs after the fit to data (“post-fit”) are given in table 3. Comparisons between data and the post-fit predictions for ∆ η− and ∆ η+ in the four SRs are shown in figure 2. Data and the post-fit SM predictions for the variables that are used for the binned likelihood fit are depicted in figure 3for CRHFe and CR-HFµ, and in figure 4for CR-t¯ tZ and CR-γ-conv. The normalisation factors for the major background processes, Nt¯ tZ , Ne γ-conv , Ne HF and Nµ HF (all obtained separately for ∆ η− and ∆ η+ ), together with N∆η− and the A` c value for the t¯ tW signal, are given in figure 5. The normalisation factor for the t¯ tW process was checked and found to be (within its uncertainty) compatible with the latest ATLAS and CMS t¯ tW cross-section measurements [ 7 , 8 ]. Tests using MC simulation were also performed to validate that the extracted A` c value is not biased by the absolute normalisation of the t¯ tW process. The normalisation factors for some of the background processes (in particular Nt¯ tZ and Ne γ-conv ) show small differences between ∆ η− and ∆ η+ . As these processes are not expected to have significant charge asymmetries in the SM at this level of precision, there is an uncertainty on how best to model this data. In the nominal fit, due to the independent normalisation factors for ∆ η− and ∆ η+ in the CRs, the observed background asymmetries are precisely modelled. To account for the possibility that the observed asymmetry is due to a statistical fluctuation, an alternative fit is performed where only one normalisation factor is assigned to each of these processes (thus fixing their asymmetries to the SM expectation). The difference between the results of these two fit set-ups is assigned as an extra systematic uncertainty in the extracted A` c value. This uncertainty (denoted as ∆ η± CR-dependency) is found to be 0.05 and is one of the leading systematic uncertainties. 5 The inclusive charge asymmetries at parton level for the simulated t¯ tZ and t¯ t samples are A` c = − 0 . 015 and 0.004, respectively. – 15 – JHEP07(2023)033 Process CR-t¯ tZ CR-HFeCR-HFµCR-γ-conv ∆η−∆η+∆η−∆η+∆η−∆η+∆η−∆η+ t¯ tW (QCD) 1.8±0.4 1.49 ±0.19 1.18 ±0.19 1.13 ±0.18 1.72 ±0.20 1.37 ±0.28 4.1±0.7 2.92 ±0.18 t¯ tW (EW) 0.18 ±0.07 0.16 ±0.06 0.10 ±0.04 0.09 ±0.04 0.09 ±0.04 0.14 ±0.05 0.23 ±0.08 0.36 ±0.12 t¯ tZ 107 ±6 107 ±6 1.42 ±0.23 1.5±0.4 2.20 ±0.23 2.00 ±0.14 4.04 ±0.19 3.65 ±0.32 HFe– – 350 ±40 362 ±27 0.18 ±0.11 0.20 ±0.09 1.0±0.6 0.67 ±0.35 HFµ0.14 ±0.08 0.19 ±0.09 0.20 ±0.09 0.28 ±0.10 520 ±40 530 ±50 0.9±0.5 1.1±0.9 γ-conv. 0.55 ±0.14 0.41 ±0.13 3.8±2.5 4.7±2.9 2.6±2.4 3.3±2.5 18.8±1.4 17.5±1.3 t¯ tH 3.3±0.4 3.20 ±0.32 0.87 ±0.13 0.89 ±0.11 1.18 ±0.11 1.22 ±0.22 1.48 ±0.20 1.5±0.4 tZq 12.6±2.2 11.0±1.9 0.48 ±0.11 0.43 ±0.09 0.95 ±0.18 0.81 ±0.15 0.68 ±0.12 0.70 ±0.13 WZ/ZZ +jets 12 ±4 12 ±4 3.0±0.9 3.3±1.0 7.2±2.4 7.9±2.5 3.1±0.9 2.9±0.8 Other 10.7±3.3 10.2±3.3 14 ±4 13 ±5 17 ±7 17 ±6 1.6±0.8 1.5±0.6 SM total 148 ±10 146 ±10 380 ±40 387 ±28 550 ±40 560 ±50 35.9±2.4 32.9±2.3 Data 156 176 315 373 551 592 34 40 Process SR-1b-lowNjets SR-1b-highNjets SR-2b-lowNjets SR-2b-highNjets ∆η−∆η+∆η−∆η+∆η−∆η+∆η−∆η+ t¯ tW (QCD) 19.0±2.8 17 ±4 9.2±1.1 8.2±1.1 25 ±7 21 ±6 14.7±3.4 12.2±1.9 t¯ tW (EW) 1.06 ±0.34 1.3±0.4 1.05 ±0.34 1.07 ±0.34 1.2±0.4 1.3±0.4 1.8±0.6 1.6±0.5 t¯ tZ 12.0±1.0 12.1±1.1 15.5±1.4 15.5±1.1 11.4±1.4 10.8±1.4 26.2±1.8 25.8±1.7 HFe7.2±1.2 7.5±1.5 1.7±0.7 1.6±0.6 0.7±0.5 0.6±0.5 0.69 ±0.35 0.37 ±0.19 HFµ12.5±2.0 13 ±4 3.2±0.8 3.5±1.3 1.35 ±0.34 1.11 ±0.33 1.0±0.4 0.9±0.5 γ-conv. 6.7±0.9 6.1±1.0 3.1±0.5 3.4±0.8 6.1±0.8 6.9±0.8 4.4±0.7 4.6±0.6 t¯ tH 5.5±0.8 5.6±0.8 8.6±0.8 8.7±0.9 5.5±1.1 5.5±1.0 14.1±1.8 14.2±1.7 tZq 5.1±0.9 4.2±0.7 1.40 ±0.31 1.15 ±0.27 2.8±0.5 2.3±0.4 1.92 ±0.34 1.64 ±0.30 WZ/ZZ +jets 15 ±4 14 ±4 8.0±2.8 7.6±2.5 2.9±0.9 2.2±0.7 2.2±0.7 2.2±0.7 Other 5.6±2.0 5.1±1.6 4.5±2.4 4.7±1.5 2.6±1.1 2.9±1.3 10 ±6 9 ±5 SM total 89 ±6 85 ±7 56 ±6 56 ±6 59 ±9 55 ±7 77 ±8 73 ±7 Data 94 89 50 69 84 81 89 81 Table 2. The predicted and observed numbers of events in the control and signal regions. The predictions are shown before the fit to data. The indicated uncertainties consider statistical as well as all experimental and theoretical systematic uncertainties, with the exception of the ∆ η± CR-dependency uncertainty. Background categories with event yields shown as “—” do contribute less than 0.01 to a region. The leptonic charge asymmetry in t¯ tW is found to be A` c(t¯ tW) = −0.12 ±0.14 (stat.) ±0.05 (syst.). This is consistent with the SM expectation of A` c(t¯ tW)SM =−0.084 +0.005 −0.003 (scale) ±0.006 (MC stat.), calculated using the nominal t¯ tW Sherpa simulation. The contributions from the most relevant uncertainties are summarised in table 4. The uncertainties are symmetrised and grouped into several type-related categories and are shown together with the total systematic and statistical uncertainties. The dominant systematic uncertainties are the ∆ η± CR-dependency, the JER, as well as the modelling uncertainties of the t¯ tW and t¯ tZ MC processes detailed in section 7. Overall, the result is limited by the statistical uncertainty of the data. – 16 – JHEP07(2023)033 Process CR-t¯ tZ CR-HFeCR-HFµCR-γ-conv ∆η−∆η+∆η−∆η+∆η−∆η+∆η−∆η+ t¯ tW (QCD) 3.2±0.7 2.2±0.7 1.8±0.5 1.7±0.5 2.6±0.8 1.8±0.8 7.0±1.3 4.4±1.3 t¯ tW (EW) 0.18 ±0.06 0.16 ±0.05 0.10 ±0.03 0.09 ±0.03 0.09 ±0.03 0.14 ±0.04 0.23 ±0.07 0.36 ±0.11 t¯ tZ 114 ±13 138 ±14 1.45 ±0.27 1.7±0.4 2.3±0.4 2.55 ±0.35 4.3±0.6 4.6±0.6 HFe– – 290 ±18 346 ±20 0.15 ±0.02 0.19 ±0.02 0.59 ±0.27 0.52 ±0.17 HFµ0.133 ±0.012 0.201 ±0.020 0.195 ±0.018 0.277 ±0.029 516 ±25 556 ±25 0.8±0.4 1.3±0.8 γ-conv. 0.40 ±0.18 0.52 ±0.16 2.8±2.2 6 ±4 1.9±2.0 4.2±3.4 14 ±6 22 ±7 t¯ tH 3.3±0.4 3.23 ±0.31 0.86 ±0.13 0.87 ±0.10 1.16 ±0.11 1.19 ±0.22 1.49 ±0.20 1.6±0.4 tZq 12.6±2.2 11.0±1.9 0.47 ±0.10 0.42 ±0.08 0.95 ±0.17 0.79 ±0.14 0.68 ±0.11 0.70 ±0.12 WZ/ZZ +jets 10.2±2.9 10.6±3.1 2.6±0.7 2.8±0.7 6.3±1.7 6.7±1.8 2.6±0.7 2.5±0.6 Other 10.8±3.2 10.0±2.9 14 ±4 13 ±5 18 ±7 18 ±6 1.7±0.8 1.7±0.6 SM total 155 ±12 175 ±13 315 ±18 373 ±19 550 ±23 591 ±24 33 ±6 40 ±6 Data 156 176 315 373 551 592 34 40 Process SR-1b-lowNjets SR-1b-highNjets SR-2b-lowNjets SR-2b-highNjets ∆η−∆η+∆η−∆η+∆η−∆η+∆η−∆η+ t¯ tW (QCD) 32 ±6 27 ±6 14 ±4 12.1±3.4 46 ±9 36 ±8 26 ±6 19 ±5 t¯ tW (EW) 1.04 ±0.32 1.3±0.4 1.04 ±0.32 1.05 ±0.32 1.2±0.4 1.3±0.4 1.8±0.5 1.6±0.5 t¯ tZ 12.4±2.0 15.0±2.2 16.0±2.2 19.6±2.3 12.3±2.3 14.3±2.6 27.6±3.3 33.2±3.5 HFe6.4±1.0 6.8±0.8 1.5±0.5 1.7±0.4 0.40 ±0.20 0.79 ±0.35 0.45 ±0.14 0.39 ±0.14 HFµ12.5±1.5 13.6±2.5 3.1±0.6 3.6±0.9 1.30 ±0.23 1.19 ±0.19 1.04 ±0.29 0.9±0.5 γ-conv. 4.9±2.3 7.7±2.6 2.3±1.1 4.3±1.6 4.6±2.1 8.8±2.9 3.3±1.5 5.9±1.9 t¯ tH 5.4±0.8 5.5±0.8 8.4±0.8 8.6±0.8 5.5±1.1 5.6±1.0 14.3±1.7 14.4±1.7 tZq 5.0±0.9 4.1±0.7 1.38 ±0.27 1.16 ±0.24 2.8±0.5 2.3±0.4 1.93 ±0.33 1.65 ±0.29 WZ/ZZ +jets 12.6±3.0 12.3±3.0 6.7±2.0 6.5±1.8 2.5±0.7 1.9±0.5 1.9±0.6 1.9±0.5 Other 6.0±2.1 5.2±1.6 3.6±1.8 4.6±1.4 2.9±1.2 3.3±1.3 8 ±4 8 ±4 SM total 99 ±6 98 ±6 58 ±4 63 ±4 80 ±8 75 ±7 85 ±6 86 ±5 Data 94 89 50 69 84 81 89 81 Table 3. The predicted and observed numbers of events in the control and signal regions. The predictions are shown after the fit to data. The indicated uncertainties consider statistical as well as all experimental and theoretical systematic uncertainties, with the exception of the ∆ η± CR-dependency uncertainty. Background categories with event yields shown as “—” do contribute less than 0.01 to a region. – 17 – JHEP07(2023)033 − η ∆ , jets N -low b SR-1 + η ∆ , jets N -low b SR-1 − η ∆ , jets N -high b SR-1 + η ∆ , jets N -high b SR-1 − η ∆ , jets N -low b SR-2 + η ∆ , jets N -low b SR-2 − η ∆ , jets N -high b SR-2 + η ∆ , jets N -high b SR-2 0.6 0.8 1 1.2 1.4 Data / Pred. 20 40 60 80 100 120 140 160 180 200 Events ATLAS -1 = 13 TeV, 139 fbs SR summary Post-fit Data (QCD)Wtt (EW)Wtt Ztt e HF µ HF -conv.γHtt tZq +jetsWZ/ZZ Other Uncertainty Figure 2. Comparison between data and the post-fit predictions for ∆ η` BDT ≤ 0(∆ η− ) and ∆ η` BDT > 0(∆ η+ ) in the four SRs. The error band includes the total uncertainties of the post-fit predictions, with the exception of the ∆ η± CR-dependency uncertainty. The ratio of the data to the total post-fit predictions is shown in the lower panel. – 18 – JHEP07(2023)033 15 20 25 30 35 40 45 50 [GeV] T 3rd Leading Lepton p 0.5 0.75 1 1.25 Data / Pred. 0 50 100 150 200 250 Events ATLAS -1 = 13 TeV, 139 fbs − η∆CR-HFe, Post-fit Data (QCD)Wtt (EW)Wtt Ztt e HF µ HF -conv.γHtt tZq +jetsWZ/ZZ Other Uncertainty (a) 15 20 25 30 35 40 45 50 [GeV] T 3rd Leading Lepton p 0.5 0.75 1 1.25 Data / Pred. 0 50 100 150 200 250 300 350 400 Events ATLAS -1 = 13 TeV, 139 fbs + η∆CR-HFe, Post-fit Data (QCD)Wtt (EW)Wtt Ztt e HF µ HF -conv.γHtt tZq +jetsWZ/ZZ Other Uncertainty (b) 15 20 25 30 35 40 45 50 [GeV] T 3rd Leading Lepton p 0.5 0.75 1 1.25 Data / Pred. 0 50 100 150 200 250 300 350 400 Events ATLAS -1 = 13 TeV, 139 fbs − η∆, µCR-HF Post-fit Data (QCD)Wtt (EW)Wtt Ztt e HF µ HF -conv.γHtt tZq +jetsWZ/ZZ Other Uncertainty (c) 15 20 25 30 35 40 45 50 [GeV] T 3rd Leading Lepton p 0.5 0.75 1 1.25 Data / Pred. 0 50 100 150 200 250 300 350 400 Events ATLAS -1 = 13 TeV, 139 fbs + η∆, µCR-HF Post-fit Data (QCD)Wtt (EW)Wtt Ztt e HF µ HF -conv.γHtt tZq +jetsWZ/ZZ Other Uncertainty (d) Figure 3. Comparison between data and the post-fit predictions in (a,b) CRHFe and (c,d) CRHFµ . The distributions show the pT of the third lepton (electron or muon), which is the variable that is used for the binned likelihood fit. The regions are separated between ∆ η` BDT ≤ 0(∆ η− ) and ∆ η` BDT > 0(∆ η+ ). The error bands include the total uncertainties in the post-fit predictions, with the exception of the ∆ η± CR-dependency uncertainty. The ratios of the data to the total post-fit predictions are shown in the lower panels. Events with the pT of the third lepton above 50 GeV are included in the rightmost bins. – 19 – JHEP07(2023)033 200 300 400 500 600 700 800 900 1000 [GeV] T H 0.5 0.75 1 1.25 Data / Pred. 0 20 40 60 80 100 Events ATLAS -1 = 13 TeV, 139 fbs − η∆Z, t tCRPost-fit Data (QCD)Wtt (EW)Wtt Ztt µ HF -conv.γ Htt tZq +jetsWZ/ZZ Other Uncertainty (a) 200 300 400 500 600 700 800 900 1000 [GeV] T H 0.5 0.75 1 1.25 Data / Pred. 0 20 40 60 80 100 120 Events ATLAS -1 = 13 TeV, 139 fbs + η∆Z, t tCRPost-fit Data (QCD)Wtt (EW)Wtt Ztt µ HF -conv.γ Htt tZq +jetsWZ/ZZ Other Uncertainty (b) − η ∆ + η ∆ 0.6 0.8 1 1.2 1.4 Data / Pred. 10 20 30 40 50 60 70 80 90 Events ATLAS -1 = 13 TeV, 139 fbs -convγCRPost-fit Data (QCD)Wtt (EW)Wtt Ztt e HF µ HF -conv.γHtt tZq +jetsWZ/ZZ Other Uncertainty (c) Figure 4. Comparison between data and the post-fit predictions in (a,b) CRt¯ tZ and (c) CRγ -conv. The distributions are shown for the variables that are used for the binned likelihood fit: HT for CRt¯ tZ and the total event yields for CRγ -conv. The regions are separated between ∆ η` BDT ≤ 0(∆ η− ) and ∆ η` BDT > 0(∆ η+ ). The error bands include the total uncertainties in the post-fit predictions, with the exception of the ∆ η± CR-dependency uncertainty. The ratios of the data to the total post-fit predictions are shown in the lower panels. Events with an HT above 1 TeV are included in the rightmost bins of (a) and (b). – 20 – JHEP07(2023)033 0 0.5 1 1.5 2 2.5 3 3.5 ATLAS -1 = 13 TeV, 139 fbs )Wtt ( l c A 0.14±-0.12 ) − η∆ ( e -conv γ N 0.34±0.74 ) + η∆ ( e -conv γ N 0.40±1.27 ) − η∆ ( e HF N 0.09±0.83 ) + η∆ ( e HF N 0.08±0.98 ) − η∆ ( µ HF N 0.09±0.98 ) + η∆ ( µ HF N 0.10±1.04 ) − η∆ ( Zt t N 0.14±1.05 ) + η∆ ( Zt t N 0.15±1.28 ) − η∆ ( Wt t N 0.40±1.59 Figure 5. Normalisation factors for the major background processes, together with N∆η− for t¯ tW and the A` c value extracted from the fit to data in the CRs and SRs at detector level. The normalisation factors, Nt¯ tZ , Ne γ-conv , Ne HF and Nµ HF , are obtained separately for ∆ η` BDT ≤ 0(∆ η− ) and ∆ η` BDT > 0(∆ η+ ). The indicated uncertainties consider statistical as well as systematic uncertainties, with the exception of the ∆ η± CR-dependency uncertainty. The solid vertical line in the last entry shows the A` cSM expectation, calculated using the t¯ tW Sherpa simulation. – 21 – JHEP07(2023)033 9 Unfolding and extraction of the charge asymmetry at particle level To obtain the charge asymmetry at particle level in a specific fiducial volume, an unfolding procedure is performed to correct for detector effects, as well as for signal efficiency and acceptance effects. The procedure and the relevant definitions are explained in the following. 9.1 Particle-level objects Particle-level objects in simulated events are defined using quasi-stable particles (with a mean lifetime greater than 30 ps ) originating from pp collisions. They are selected after hadronisation but before the interaction with the various detector components or consideration of pile-up effects. Particle-level electrons or muons are required to not originate from a hadron in the MC generator event record, whether directly or through a τ -lepton decay. This ensures that they originate from a Z or W boson (where the W boson can come either from prompt W production or a top-quark decay), without requiring a direct match with the parent particle. The four-momenta of the bare leptons are modified (“dressed”) by adding the four-momenta of all radiated photons within a cone of size ∆ R = 0 . 1, excluding photons from hadron decays, to take into account FSR photons. ∆A` c(t¯ tW) Experimental uncertainties Jet energy resolution 0.013 Pile-up 0.007 b-tagging 0.005 Leptons 0.004 Emiss T0.004 Jet energy scale 0.0032 Luminosity 0.0006 MC modelling uncertainties t¯ tW modelling 0.013 t¯ tZ modelling 0.010 HFe/µ modelling 0.006 t¯ tH modelling 0.005 Other uncertainties ∆η±CR-dependency 0.05 MC statistical uncertainty 0.019 Data statistical uncertainty 0.14 Total uncertainty 0.15 Table 4. List of the most relevant systematic and statistical uncertainties in the extracted leptonic charge asymmetry A` c ( t¯ tW )from the simultaneous fit. For this table, the uncertainties are symmetrised and grouped into categories. The sum in quadrature of the individual uncertainties is not necessarily equal to the total uncertainty due to correlations introduced by the fit. – 22 – JHEP07(2023)033 Particle-level jets are reconstructed with the antikt algorithm with a radius parameter of R = 0 . 4applied to all stable particles, but excluding the neutrinos originating from W or Z bosons and the selected electrons, muons and photons used in the definition of the charged leptons. If b -hadrons with pT>5 GeV are found in the MC event record, they are clustered into stable-particle jets with their energies set to negligible positive values (referred to as “ghost-matching”) [ 86 ]. Particle-level jets containing at least one of these b -hadrons are considered as b -jets. The particle-level missing transverse momentum is defined as the vectorial sum of the transverse momenta of all neutrinos found in the MC simulation history of the event, excluding those originating from hadron decays. 9.2 Particle-level fiducial volume The particle-level fiducial volume is defined by the following requirements on the particlelevel objects, as defined in section 9.1: •Three electrons or muons with pT>15 GeV and |η|<2.5. •The invariant mass of all OSSF lepton pairs has to be larger than 25 GeV. •No Z-candidate (as defined in section 5) among the leptons. • At least two jets with pT>20 GeV , |η|< 2 . 5and least one of them identified as a b-jet. 9.3 Unfolding procedure and charge-asymmetry extraction The unfolding procedure is applied to the observed number of data events in the SRs. Analogously to the method used at detector level, described in section 6, a method of matching leptons to top quarks (antiquarks) is required to obtain the response matrix, essential to the unfolding procedure. To reproduce the particle-level fiducial volume, a simpler scheme is adopted that is independent of the generator-specific MC event record and any multivariate algorithm. Each lepton is combined with the closest b -jet in the ∆ R space. The ` – b system that yields a mass closest to the most probable mass for a ` – b system originating from a top-quark decay (according to the nominal t¯ tW simulation) is used to select the even and odd leptons. This procedure has an efficiency of approximately 65% to identify the correct leptons. The following formula is used for the unfolding: Nfolded i=1 αiX j εjMij | {z } Rij Nfid jwith Mij =N(reco ∩fid) ij N(reco ∩fid) j , αi=N(reco ∩fid) i Nreco i , εj=N(reco ∩fid) j Nfid j , (9.1) with the number Nfid j representing the content of bin j in the fiducial volume, Nreco i being the events in bin i that satisfy the detector level selection and the symbol ∩ represents the logical intersection of the two regions. The Nfolded i represents the bin content ( i ) after the folding of the particle level bins ( j ) has been performed through the response matrix ( Rij ). – 23 – JHEP07(2023)033 This matrix is constructed from the migration matrix ( Mij ) and the acceptance and efficiency correction terms ( αi and εj ) for each bin. The entries in the migration matrix represent the fractions of events at particle level in a y -axis bin that are reconstructed at detector level in an x -axis bin. They are normalised such that the sum of entries in each row is equal to one. The acceptance corrections αi account for events that are generated outside the fiducial volume but satisfy the selection at detector level, as described in section 5. The efficiency corrections εj account for events that are in the fiducial volume but fail to satisfy the detector-level selection. The migration matrices, as well as the acceptance and efficiency correction terms, are built separately for each of the SRs defined in table 1. As an example, figure 6shows (a) the migration matrix, as well as (b) the efficiency and (c) the acceptance correction factors that are used for SR-2 b -low Njets , which is the region with the highest t¯ tW purity. The fraction of events in the diagonal elements of the migration matrix shows the quality of the resolution for ∆ η` , which is around 90%. The efficiency corrections are at a level of 11%–12% and the acceptance corrections are around 95%. None show any notable dependence on ∆η`. The unfolding procedure is the same as in ref. [ 18 ] and based on a profile-likelihood approach (“profile-likelihood unfolding”). With this approach, the unfolding problem is transformed into a standard problem of fitting normalisations of distributions. Each bin in the particle-level distribution is “folded” through the response matrix via eq. (9.1), resulting in the same numbers of bins at detector level. The particle-level bins are treated as separate subsamples that are multiplied by their respective entries in the response matrix and freely floating parameters are assigned to each of these subsamples at detector level. Analogously to the fit described in section 8, the freely floating parameters are assigned to the major backgrounds in the SRs: Nt¯ tZ , Ne γ-conv , Ne HF and Nµ HF . These normalisations and the analysis regions are split into ∆ η+ and ∆ η− , in the same way as the detector-level results. Thus, the detector-level distributions are scaled by some factors, determined by fitting the data, and these factors are then used to scale the corresponding particle-level bins, which gives the desired unfolded result. The charge asymmetry is defined as the parameter of interest and is related to the normalisation factors in the unfolded bins. For the CRs, no response matrices are built. However, as the signal contamination in these regions is very small compared with the total event yields, an approximation is made whereby the signal is treated as an additional background. An exception is CRγ -conv where, due to the high signal contamination, response matrices are also built. No regularisation is applied in the unfolding. The systematic uncertainties in the signal and background processes considered for the unfolded results are the same as for the results at detector level (described in section 7). Systematic uncertainties in the background processes are propagated to the unfolded distributions by varying the detector-level distributions within their uncertainties and repeating the unfolding procedure. The modelling uncertainties of the t¯ tW signal are propagated through the unfolding procedure, using variations of the response matrices. An injection test is performed to verify that non-SM A` c values can be recovered in the unfolding procedure. This is done by injecting the non-SM A` c values into the particle-level predictions, which are propagated to detector level and treated as pseudo-data in the fit. – 24 – JHEP07(2023)033 [35] F. Cascioli, P. Maierhöfer and S. Pozzorini, Scattering Amplitudes with Open Loops,Phys. Rev. Lett. 108 (2012) 111601 [arXiv:1111.5206] [INSPIRE]. [36] A. Denner, S. Dittmaier and L. Hofer, Collier: A fortran-based complex one-loop library in extended regularizations,Comput. Phys. Commun. 212 (2017) 220 [arXiv:1604.06792] [INSPIRE]. 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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’amen 29, V. D’Amico 109, J. Damp 100, J.R. Dandoy 128, M.F. Daneri 30, M. Danninger 142, V. Dao 36, G. Darbo 57b, S. Darmora 6, S.J. Das 29, S. D’Auria 71a,71b, C. David 156b, T. Davidek 133, D.R. Davis 51, B. Davis-Purcell 34, I. Dawson 94, K. De 8, R. De Asmundis 72a , M. De Beurs 114 , 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. Dedovich 38 , J. Degens 114 , A.M. Deiana 44 , F. Del Corso 23b,23a, J. Del Peso 99, F. Del Rio 63a, F. Deliot 135, C.M. Delitzsch 49, M. Della Pietra 72a,72b, D. Della Volpe 56, A. Dell’Acqua 36, L. Dell’Asta 71a,71b, M. Delmastro 4, P.A. Delsart 60, S. Demers 172, M. Demichev 38, S.P. Denisov 37, L. D’Eramo 115, D. Derendarz 86, F. Derue 127, P. Dervan 92, K. Desch 24, K. Dette 155, 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, – 37 – JHEP07(2023)033 E.B. Diehl 106, L. Diehl 54, S. Díez 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’Onofrio 77a,77b, M. D’Onofrio 92, J. Dopke 134, A. Doria 72a, M.T. Dova 90, A.T. Doyle 59, M.A. Draguet 126, E. Drechsler 142, 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 110, A. Dudarev 36, E.R. Duden 26, M. D’uffizi 101, L. Duflot 66, M. Dührssen 36, C. Dülsen 171, A.E. Dumitriu 27b, M. Dunford 63a, S. Dungs 49, K. Dunne 47a,47b, A. Duperrin 102, H. Duran Yildiz 3a, M. Düren 58, A. Durglishvili 149b, B.L. Dwyer 115, G.I. Dyckes 17a, M. Dyndal 85a, S. Dysch 101, B.S. Dziedzic 86, Z.O. Earnshaw 146, 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, 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, A. Emerman 41, 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, 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, S. Falke 36, J. Faltova 133, Y. Fan 14a, Y. Fang 14a,14d, G. Fanourakis 46, M. Fanti 71a,71b, M. Faraj 69a,69b, Z. Farazpay 97 , A. Farbin 8 , A. Farilla 77a , T. Farooque 107 , S.M. Farrington 52 , F. Fassi 35e , D. Fassouliotis 9, M. Faucci Giannelli 76a,76b, W.J. Fawcett 32, L. Fayard 66, P. 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. Fenyuk 37 , L. Ferencz 48 , R.A.M. Ferguson 91 , S.I. Fernandez Luengo 137f , J. Ferrando 48 , A. Ferrari 161 , P. Ferrari 114,113 , R. Ferrari 73a , D. Ferrere 56 , C. Ferretti 106 , F. Fiedler 100 , A. Filipčič 93, E.K. Filmer 1, F. Filthaut 113, M.C.N. Fiolhais 130a,130c,c, L. Fiorini 163, F. Fischer 141, W.C. Fisher 107, T. Fitschen 101, I. Fleck 141, P. Fleischmann 106, T. Flick 171, L. Flores 128, M. Flores 33d, L.R. Flores Castillo 64a, F.M. Follega 78a,78b, N. Fomin 16, J.H. Foo 155, B.C. Forland68, A. Formica 135, A.C. Forti 101, E. Fortin 102, A.W. Fortman 61, M.G. Foti 17a, L. Fountas 9, D. Fournier 66, H. Fox 91, P. Francavilla 74a,74b, S. Francescato 61, S. Franchellucci 56, M. Franchini 23b,23a, S. Franchino 63a , D. Francis 36 , L. Franco 113 , L. Franconi 19 , M. Franklin 61 , G. Frattari 26 , A.C. Freegard 94, P.M. Freeman20, W.S. Freund 82b, N. Fritzsche 50, A. Froch 54, D. Froidevaux 36, J.A. Frost 126, Y. Fu 62a, M. Fujimoto 118, E. Fullana Torregrosa 163,∗, J. Fuster 163, A. Gabrielli 23b,23a, A. Gabrielli 155, P. Gadow 48, G. Gagliardi 57b,57a, L.G. Gagnon 17a, G.E. Gallardo 126, E.J. Gallas 126, B.J. Gallop 134, R. Gamboa Goni 94, K.K. Gan 119, S. Ganguly 153, J. Gao 62a, Y. Gao 52, F.M. Garay Walls 137a,137b, B. Garcia29,ag, C. García 163, J.E. García Navarro 163, M. Garcia-Sciveres 17a, R.W. Gardner 39, D. Garg 80, R.B. Garg 143, C.A. Garner155, V. Garonne 29, C.M. Garvey 33a, S.J. Gasiorowski 138, P. Gaspar 82b, G. Gaudio 73a, V. Gautam13, – 38 – JHEP07(2023)033 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,27e, C.M. Gee 136, J. Geisen 98, C. Gemme 57b, M.H. Genest 60, S. Gentile 75a,75b, S. George 95, W.F. George 20, T. Geralis 46, L.O. Gerlach55, P. Gessinger-Befurt 36, M.E. Geyik 171, M. Ghasemi Bostanabad 165, 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,ad, 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,ag, M. Goblirsch-Kolb 26, 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. Goncalves Gama 55 , R. Gonçalo 130a,130c , G. Gonella 123, L. Gonella 20, A. Gongadze 38, F. Gonnella 20, J.L. Gonski 41, R.Y. González Andana 52, S. González de la Hoz 163, S. Gonzalez Fernandez 13, R. Gonzalez Lopez 92, C. Gonzalez Renteria 17a, R. Gonzalez Suarez 161, S. Gonzalez-Sevilla 56, G.R. Gonzalvo Rodriguez 163, L. Goossens 36, N.A. Gorasia 20, P.A. Gorbounov 37, B. Gorini 36, E. Gorini 70a,70b, A. Gorišek 93, 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, C. Goy 4, I. Grabowska-Bold 85a, K. Graham 34, E. Gramstad 125, S. Grancagnolo 18, M. Grandi 146, V. Gratchev37,∗, 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,n, S. Grinstein 13,u, J.-F. Grivaz 66, E. Gross 169, J. Grosse-Knetter 55, C. Grud106, J.C. Grundy 126, L. Guan 106, W. Guan 170, 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 48, T. Guillemin 4, E. Guilloton 167,134, S. Guindon 36, F. Guo 14a,14d, J. Guo 62c, L. Guo 66, 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. Guyot 135, 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, 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, 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,ab, H. Hanif 142, M.D. Hank 39, 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, Y.T. Harris 126 , N.M. Harrison 119 , P.F. Harrison 167 , N.M. Hartman 143 , N.M. Hartmann 109 , Y. Hasegawa 140, A. Hasib 52, S. Haug 19, R. Hauser 107, M. Havranek 132, C.M. Hawkes 20, R.J. Hawkings 36, S. Hayashida 111, D. Hayden 107, C. Hayes 106, R.L. Hayes 164, C.P. Hays 126, J.M. Hays 94, H.S. Hayward 92, F. He 62a, Y. He 154, Y. He 127, M.P. Heath 52, 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 , J. Hejbal 131 , – 39 – JHEP07(2023)033 L. Helary 48, A. Held 170, S. Hellesund 125, C.M. Helling 164, S. Hellman 47a,47b, C. Helsens 36 , R.C.W. Henderson 91 , L. Henkelmann 32 , A.M. Henriques Correia 36 , H. Herde 98 , Y. Hernández Jiménez 145, L.M. Herrmann 24, T. Herrmann 50, G. Herten 54, R. Hertenberger 109, L. Hervas 36, N.P. Hessey 156a, H. Hibi 84, E. Higón-Rodriguez 163, S.J. Hillier 20, I. Hinchliffe 17a, 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, D. Hohn 54, T. Holm 24, M. Holzbock 110, L.B.A.H. Hommels 32, B.P. Honan 101, J. Hong 62c, T.M. Hong 129, J.C. Honig 54, B.H. Hooberman 162, W.H. Hopkins 6, Y. Horii 111, S. Hou 148, A.S. Howard 93, J. Howarth 59, J. Hoya 6, M. Hrabovsky 122, A. Hrynevich 48, T. Hryn’ova 4, P.J. Hsu 65, S.-C. Hsu 138, Q. Hu 41, Y.F. Hu 14a,14d,af , D.P. Huang 96, 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, M. Huhtinen 36, S.K. Huiberts 16, R. Hulsken 104, N. Huseynov 12,a, J. Huston 107, J. Huth 61, R. Hyneman 143, S. Hyrych 28a, G. Iacobucci 56, G. Iakovidis 29, I. Ibragimov 141, L. Iconomidou-Fayard 66, P. Iengo 72a,72b, R. Iguchi 153, T. Iizawa 56, Y. Ikegami 83, A. Ilg 19, N. Ilic 155, H. Imam 35a, T. Ingebretsen Carlson 47a,47b, G. Introzzi 73a,73b, M. Iodice 77a, V. Ippolito 75a,75b, M. Ishino 153, W. Islam 170, C. Issever 18,48, S. Istin 21a, 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. Jäkel 171, K. Jakobs 54, T. Jakoubek 169, J. Jamieson 59, K.W. Janas 85a, G. Jarlskog 98, A.E. Jaspan 92, M. Javurkova 103, F. Jeanneau 135, L. Jeanty 123, J. Jejelava 149a,aa, P. Jenni 54,h, C.E. Jessiman 34, S. Jézéquel 4, C. Jia62b, J. Jia 145, X. Jia 61, X. Jia 14a,14d, Z. Jia 14c, Y. Jiang62a, S. Jiggins 52, J. Jimenez Pena 110, 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 167 , 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,u, S. Kabana 137e, A. Kaczmarska 86, M. Kado 75a,75b, H. Kagan 119, M. Kagan 143, A. Kahn41, A. Kahn 128, C. Kahra 100, T. Kaji 168, E. Kajomovitz 150, N. Kakati 169, 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,f , S.N. Karpov 38, Z.M. Karpova 38, V. Kartvelishvili 91, A.N. Karyukhin 37, E. Kasimi 152,f , C. Kato 62d, J. Katzy 48, S. Kaur 34, K. Kawade 140, K. Kawagoe 89, T. Kawamoto 135, G. Kawamura55, E.F. Kay 165, F.I. Kaya 158, S. Kazakos 13, V.F. Kazanin 37, Y. Ke 145, J.M. Keaveney 33a , R. Keeler 165 , G.V. Kehris 61 , J.S. Keller 34 , A.S. Kelly 96 , D. Kelsey 146 , J.J. Kempster 146, K.E. Kennedy 41, P.D. Kennedy 100, O. Kepka 131, B.P. Kerridge 167, S. Kersten 171 , B.P. Kerševan 93 , S. Keshri 66 , L. Keszeghova 28a , S. Ketabchi Haghighat 155 , M. Khandoga 127, A. Khanov 121, A.G. Kharlamov 37, T. Kharlamova 37, E.E. Khoda 138, 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, E. Kim 154, Y.K. Kim 39, N. Kimura 96, A. Kirchhoff 55, D. Kirchmeier 50, C. Kirfel 24, J. Kirk 134, A.E. Kiryunin 110, T. Kishimoto 153 , D.P. Kisliuk 155 , 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, – 40 – JHEP07(2023)033 P.M. Tuts 41 , S. Tzamarias 152,f , P. Tzanis 10 , E. Tzovara 100 , K. Uchida 153 , F. Ukegawa 157 , P.A. Ulloa Poblete 137c , 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, A. Vallier 102, J.A. Valls Ferrer 163, D.R. Van Arneman 114, T.R. Van Daalen 138, 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,ad, 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, 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. Wagner 103 , W. Wagner 171 , S. Wahdan 171, H. Wahlberg 90, R. Wakasa 157, M. Wakida 111, V.M. Walbrecht 110, J. Walder 134, R. Walker 109, W. Walkowiak 141, A.M. Wang 61, 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, 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 , G. Watts 138 , B.M. Waugh 96 , A.F. Webb 11 , 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, L.A.M. Wiik-Fuchs 54, D.J. Wilbern120, H.G. Wilkens 36, D.M. Williams 41, H.H. Williams128, S. Williams 32, S. Willocq 103, P.J. Windischhofer 126, F. Winklmeier 123, B.T. Winter 54, J.K. Winter 101, M. Wittgen143, M. Wobisch 97, R. Wölker 126, J. Wollrath160, M.W. Wolter 86, H. Wolters 130a,130c, V.W.S. Wong 164, A.F. Wongel 48, S.D. Worm 48, B.K. Wosiek 86, K.W. Woźniak 86, K. Wraight 59, J. Wu 14a,14d, M. Wu 64a, M. Wu 113, S.L. Wu 170, X. Wu 56, Y. Wu 62a, Z. Wu 135,62a, J. Wuerzinger 126, T.R. Wyatt 101, B.M. Wynne 52, S. Xella 42, L. Xia 14c, M. Xia14b, J. Xiang 64c , X. Xiao 106 , M. Xie 62a , X. Xie 62a , S. Xin 14a,14d , J. Xiong 17a , I. Xiotidis 146 , – 47 – JHEP07(2023)033 D. Xu 14a, H. Xu62a, H. Xu 62a, L. Xu 62a, R. Xu 128, T. Xu 106, W. Xu 106, Y. Xu 14b, Z. Xu 62b, Z. Xu 14a, B. Yabsley 147, S. Yacoob 33a, N. Yamaguchi 89, Y. Yamaguchi 154, 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,106, 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 91, 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, X. Yue 63a, M. Zaazoua 35e, 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, S.V. Zeißner 49, C. Zeitnitz 171, J.C. Zeng 162, D.T. Zenger Jr 26, O. Zenin 37, T. Ženiš 28a, S. Zenz 94, S. Zerradi 35a, D. Zerwas 66, M. Zhai 14a,14d, B. Zhang 14c, D.F. Zhang 139, J. Zhang 62b, J. Zhang 6, K. Zhang 14a,14d, L. Zhang 14c, P. Zhang14a,14d, R. Zhang 170, S. Zhang 106, T. Zhang 153, X. Zhang 62c, X. Zhang 62b, Y. Zhang 62c,5, Z. Zhang 17a, Z. Zhang 66, H. Zhao 138, P. Zhao 51, T. Zhao 62b, Y. Zhao 136, Z. Zhao 62a, A. Zhemchugov 38, X. Zheng 62a, Z. Zheng 143, D. Zhong 162, B. Zhou106, C. Zhou 170, H. Zhou 7, N. Zhou 62c, Y. Zhou7, C.G. Zhu 62b, C. Zhu 14a,14d, H.L. Zhu 62a, J. Zhu 106, Y. Zhu 62c, Y. Zhu 62a, X. Zhuang 14a, K. Zhukov 37, V. Zhulanov 37, N.I. Zimine 38, J. Zinsser 63b, M. Ziolkowski 141, L. Živković 15, A. Zoccoli 23b,23a, K. Zoch 56, T.G. Zorbas 139, O. Zormpa 46, W. Zou 41, L. Zwalinski 36 1Department of Physics, University of Adelaide, Adelaide; Australia 2Department of Physics, University of Alberta, Edmonton AB; Canada 3 (a)Department of Physics, Ankara University, Ankara;(b)Division of Physics, TOBB University of Economics and Technology, Ankara; Türkiye 4LAPP, Univ. Savoie Mont Blanc, CNRS/IN2P3, Annecy; France 5APC, Université Paris Cité, CNRS/IN2P3, Paris; France 6High Energy Physics Division, Argonne National Laboratory, Argonne IL; United States of America 7Department of Physics, University of Arizona, Tucson AZ; United States of America 8Department of Physics, University of Texas at Arlington, Arlington TX; United States of America 9Physics Department, National and Kapodistrian University of Athens, Athens; Greece 10 Physics Department, National Technical University of Athens, Zografou; Greece 11 Department of Physics, University of Texas at Austin, Austin TX; United States of America 12 Institute of Physics, Azerbaijan Academy of Sciences, Baku; Azerbaijan 13 Institut de Física d’Altes Energies (IFAE), Barcelona Institute of Science and Technology, Barcelona; Spain 14 (a)Institute of High Energy Physics, Chinese Academy of Sciences, Beijing;(b)Physics Department, Tsinghua University, Beijing;(c)Department of Physics, Nanjing University, Nanjing;(d)University of Chinese Academy of Science (UCAS), Beijing; China 15 Institute of Physics, University of Belgrade, Belgrade; Serbia 16 Department for Physics and Technology, University of Bergen, Bergen; Norway 17 (a)Physics Division, Lawrence Berkeley National Laboratory, Berkeley CA;(b)University of California, Berkeley CA; United States of America 18 Institut für Physik, Humboldt Universität zu Berlin, Berlin; Germany 19 Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics, University of Bern, Bern; Switzerland 20 School of Physics and Astronomy, University of Birmingham, Birmingham; United Kingdom – 48 – JHEP07(2023)033 21 (a)Department of Physics, Bogazici University, Istanbul;(b)Department of Physics Engineering, Gaziantep University, Gaziantep;(c)Department of Physics, Istanbul University, Istanbul;(d)Istinye University, Sariyer, Istanbul; Türkiye 22 (a)Facultad de Ciencias y Centro de Investigaciónes, Universidad Antonio Nariño, Bogotá;(b)Departamento de Física, Universidad Nacional de Colombia, Bogotá; Colombia 23 (a)Dipartimento di Fisica e Astronomia A. Righi, Università di Bologna, Bologna;(b)INFN Sezione di Bologna; Italy 24 Physikalisches Institut, Universität Bonn, Bonn; Germany 25 Department of Physics, Boston University, Boston MA; United States of America 26 Department of Physics, Brandeis University, Waltham MA; United States of America 27 (a) Transilvania University of Brasov, Brasov; (b) Horia Hulubei National Institute of Physics and Nuclear 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 University in Timisoara, Timisoara;(g)Faculty of Physics, University of Bucharest, Bucharest; Romania 28 (a) Faculty of Mathematics, Physics and Informatics, Comenius University, Bratislava; (b) Department of Subnuclear Physics, Institute of Experimental Physics of the Slovak Academy of Sciences, Kosice; Slovak Republic 29 Physics Department, Brookhaven National Laboratory, Upton NY; United States of America 30 Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Física, y CONICET, Instituto de Física de Buenos Aires (IFIBA), Buenos Aires; Argentina 31 California State University, CA; United States of America 32 Cavendish Laboratory, University of Cambridge, Cambridge; United Kingdom 33 (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 of South Africa, Department of Physics, Pretoria;(f)University of Zululand, KwaDlangezwa;(g)School of Physics, University of the Witwatersrand, Johannesburg; South Africa 34 Department of Physics, Carleton University, Ottawa ON; Canada 35 (a) Faculté des Sciences Ain Chock, Réseau Universitaire de Physique des Hautes Energies — Université Hassan II, Casablanca;(b)Faculté des Sciences, Université Ibn-Tofail, Kénitra;(c)Faculté des Sciences Semlalia, Université Cadi Ayyad, LPHEA-Marrakech;(d)LPMR, Faculté des Sciences, Université Mohamed Premier, Oujda;(e)Faculté des sciences, Université Mohammed V, Rabat;(f)Institute of Applied Physics, Mohammed VI Polytechnic University, Ben Guerir; Morocco 36 CERN, Geneva; Switzerland 37 Affiliated with an institute covered by a cooperation agreement with CERN 38 Affiliated with an international laboratory covered by a cooperation agreement with CERN 39 Enrico Fermi Institute, University of Chicago, Chicago IL; United States of America 40 LPC, Université Clermont Auvergne, CNRS/IN2P3, Clermont-Ferrand; France 41 Nevis Laboratory, Columbia University, Irvington NY; United States of America 42 Niels Bohr Institute, University of Copenhagen, Copenhagen; Denmark 43 (a)Dipartimento di Fisica, Università della Calabria, Rende;(b)INFN Gruppo Collegato di Cosenza, Laboratori Nazionali di Frascati; Italy 44 Physics Department, Southern Methodist University, Dallas TX; United States of America 45 Physics Department, University of Texas at Dallas, Richardson TX; United States of America 46 National Centre for Scientific Research “Demokritos”, Agia Paraskevi; Greece 47 (a)Department of Physics, Stockholm University;(b)Oskar Klein Centre, Stockholm; Sweden 48 Deutsches Elektronen-Synchrotron DESY, Hamburg and Zeuthen; Germany 49 Fakultät Physik, Technische Universität Dortmund, Dortmund; Germany 50 Institut für Kernund Teilchenphysik, Technische Universität Dresden, Dresden; Germany 51 Department of Physics, Duke University, Durham NC; United States of America 52 SUPA — School of Physics and Astronomy, University of Edinburgh, Edinburgh; United Kingdom – 49 – JHEP07(2023)033 53 INFN e Laboratori Nazionali di Frascati, Frascati; Italy 54 Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg; Germany 55 II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen; Germany 56 Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève; Switzerland 57 (a)Dipartimento di Fisica, Università di Genova, Genova;(b)INFN Sezione di Genova; Italy 58 II. Physikalisches Institut, Justus-Liebig-Universität Giessen, Giessen; Germany 59 SUPA — School of Physics and Astronomy, University of Glasgow, Glasgow; United Kingdom 60 LPSC, Université Grenoble Alpes, CNRS/IN2P3, Grenoble INP, Grenoble; France 61 Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge MA; United States of America 62 (a)Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei;(b)Institute of Frontier and Interdisciplinary Science and Key Laboratory of Particle Physics and Particle Irradiation (MOE), Shandong University, Qingdao;(c)School of Physics and Astronomy, Shanghai Jiao Tong University, Key Laboratory for Particle Astrophysics and Cosmology (MOE), SKLPPC, Shanghai; (d) Tsung-Dao Lee Institute, Shanghai; China 63 (a)Kirchhoff-Institut für Physik, Ruprecht-Karls-Universität Heidelberg, Heidelberg;(b)Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg; Germany 64 (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 and Institute for Advanced Study, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong; China 65 Department of Physics, National Tsing Hua University, Hsinchu; Taiwan 66 IJCLab, Université Paris-Saclay, CNRS/IN2P3, 91405, Orsay; France 67 Centro Nacional de Microelectrónica (IMB-CNM-CSIC), Barcelona; Spain 68 Department of Physics, Indiana University, Bloomington IN; United States of America 69 (a)INFN Gruppo Collegato di Udine, Sezione di Trieste, Udine;(b)ICTP, Trieste;(c)Dipartimento Politecnico di Ingegneria e Architettura, Università di Udine, Udine; Italy 70 (a)INFN Sezione di Lecce;(b)Dipartimento di Matematica e Fisica, Università del Salento, Lecce; Italy 71 (a)INFN Sezione di Milano;(b)Dipartimento di Fisica, Università di Milano, Milano; Italy 72 (a)INFN Sezione di Napoli;(b)Dipartimento di Fisica, Università di Napoli, Napoli; Italy 73 (a)INFN Sezione di Pavia;(b)Dipartimento di Fisica, Università di Pavia, Pavia; Italy 74 (a)INFN Sezione di Pisa;(b)Dipartimento di Fisica E. Fermi, Università di Pisa, Pisa; Italy 75 (a)INFN Sezione di Roma;(b)Dipartimento di Fisica, Sapienza Università di Roma, Roma; Italy 76 (a)INFN Sezione di Roma Tor Vergata;(b)Dipartimento di Fisica, Università di Roma Tor Vergata, Roma; Italy 77 (a)INFN Sezione di Roma Tre;(b)Dipartimento di Matematica e Fisica, Università Roma Tre, Roma; Italy 78 (a)INFN-TIFPA;(b)Università degli Studi di Trento, Trento; Italy 79 Universität Innsbruck, Department of Astro and Particle Physics, Innsbruck; Austria 80 University of Iowa, Iowa City IA; United States of America 81 Department of Physics and Astronomy, Iowa State University, Ames IA; United States of America 82 (a)Departamento de Engenharia Elétrica, 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 Física, Universidade de São Paulo, São Paulo;(d)Rio de Janeiro State University, Rio de Janeiro; Brazil 83 KEK, High Energy Accelerator Research Organization, Tsukuba; Japan 84 Graduate School of Science, Kobe University, Kobe; Japan 85 (a)AGH University of Science and Technology, Faculty of Physics and Applied Computer Science, Krakow;(b)Marian Smoluchowski Institute of Physics, Jagiellonian University, Krakow; Poland 86 Institute of Nuclear Physics Polish Academy of Sciences, Krakow; Poland 87 Faculty of Science, Kyoto University, Kyoto; Japan 88 Kyoto University of Education, Kyoto; Japan – 50 – JHEP07(2023)033 89 Research Center for Advanced Particle Physics and Department of Physics, Kyushu University, Fukuoka; Japan 90 Instituto de Física La Plata, Universidad Nacional de La Plata and CONICET, La Plata; Argentina 91 Physics Department, Lancaster University, Lancaster; United Kingdom 92 Oliver Lodge Laboratory, University of Liverpool, Liverpool; United Kingdom 93 Department of Experimental Particle Physics, Jožef Stefan Institute and Department of Physics, University of Ljubljana, Ljubljana; Slovenia 94 School of Physics and Astronomy, Queen Mary University of London, London; United Kingdom 95 Department of Physics, Royal Holloway University of London, Egham; United Kingdom 96 Department of Physics and Astronomy, University College London, London; United Kingdom 97 Louisiana Tech University, Ruston LA; United States of America 98 Fysiska institutionen, Lunds universitet, Lund; Sweden 99 Departamento de Física Teorica C-15 and CIAFF, Universidad Autónoma de Madrid, Madrid; Spain 100 Institut für Physik, Universität Mainz, Mainz; Germany 101 School of Physics and Astronomy, University of Manchester, Manchester; United Kingdom 102 CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille; France 103 Department of Physics, University of Massachusetts, Amherst MA; United States of America 104 Department of Physics, McGill University, Montreal QC; Canada 105 School of Physics, University of Melbourne, Victoria; Australia 106 Department of Physics, University of Michigan, Ann Arbor MI; United States of America 107 Department of Physics and Astronomy, Michigan State University, East Lansing MI; United States of America 108 Group of Particle Physics, University of Montreal, Montreal QC; Canada 109 Fakultät für Physik, Ludwig-Maximilians-Universität München, München; Germany 110 Max-Planck-Institut für Physik (Werner-Heisenberg-Institut), München; Germany 111 Graduate School of Science and Kobayashi-Maskawa Institute, Nagoya University, Nagoya; Japan 112 Department of Physics and Astronomy, University of New Mexico, Albuquerque NM; United States of America 113 Institute for Mathematics, Astrophysics and Particle Physics, Radboud University/Nikhef, Nijmegen; Netherlands 114 Nikhef National Institute for Subatomic Physics and University of Amsterdam, Amsterdam; Netherlands 115 Department of Physics, Northern Illinois University, DeKalb IL; United States of America 116 (a) New York University Abu Dhabi, Abu Dhabi; (b) University of Sharjah, Sharjah; United Arab Emirates 117 Department of Physics, New York University, New York NY; United States of America 118 Ochanomizu University, Otsuka, Bunkyo-ku, Tokyo; Japan 119 Ohio State University, Columbus OH; United States of America 120 Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman OK; United States of America 121 Department of Physics, Oklahoma State University, Stillwater OK; United States of America 122 Palacký University, Joint Laboratory of Optics, Olomouc; Czech Republic 123 Institute for Fundamental Science, University of Oregon, Eugene, OR; United States of America 124 Graduate School of Science, Osaka University, Osaka; Japan 125 Department of Physics, University of Oslo, Oslo; Norway 126 Department of Physics, Oxford University, Oxford; United Kingdom 127 LPNHE, Sorbonne Université, Université Paris Cité, CNRS/IN2P3, Paris; France 128 Department of Physics, University of Pennsylvania, Philadelphia PA; United States of America 129 Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh PA; United States of America 130 (a) Laboratório de Instrumentação e Física Experimental de Partículas — LIP, Lisboa; (b) Departamento de Física, Faculdade de Ciências, Universidade de Lisboa, Lisboa;(c)Departamento de Física, Universidade de Coimbra, Coimbra;(d)Centro de Física Nuclear da Universidade de Lisboa, Lisboa; (e) Departamento de Física, Universidade do Minho, Braga; (f) Departamento de Física Teórica y – 51 – JHEP07(2023)033 del Cosmos, Universidad de Granada, Granada (Spain);(g)Departamento de Física, Instituto Superior Técnico, Universidade de Lisboa, Lisboa; Portugal 131 Institute of Physics of the Czech Academy of Sciences, Prague; Czech Republic 132 Czech Technical University in Prague, Prague; Czech Republic 133 Charles University, Faculty of Mathematics and Physics, Prague; Czech Republic 134 Particle Physics Department, Rutherford Appleton Laboratory, Didcot; United Kingdom 135 IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette; France 136 Santa Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz CA; United States of America 137 (a)Departamento de Física, Pontificia Universidad Católica de Chile, Santiago;(b)Millennium Institute for Subatomic physics at high energy frontier (SAPHIR), Santiago;(c)Instituto de Investigación Multidisciplinario en Ciencia y Tecnología, y Departamento de Física, Universidad de La Serena; (d) Universidad Andres Bello, Department of Physics, Santiago; (e) Instituto de Alta Investigación, Universidad de Tarapacá, Arica; (f) Departamento de Física, Universidad Técnica Federico Santa María, Valparaíso; Chile 138 Department of Physics, University of Washington, Seattle WA; United States of America 139 Department of Physics and Astronomy, University of Sheffield, Sheffield; United Kingdom 140 Department of Physics, Shinshu University, Nagano; Japan 141 Department Physik, Universität Siegen, Siegen; Germany 142 Department of Physics, Simon Fraser University, Burnaby BC; Canada 143 SLAC National Accelerator Laboratory, Stanford CA; United States of America 144 Department of Physics, Royal Institute of Technology, Stockholm; Sweden 145 Departments of Physics and Astronomy, Stony Brook University, Stony Brook NY; United States of America 146 Department of Physics and Astronomy, University of Sussex, Brighton; United Kingdom 147 School of Physics, University of Sydney, Sydney; Australia 148 Institute of Physics, Academia Sinica, Taipei; Taiwan 149 (a)E. Andronikashvili Institute of Physics, Iv. Javakhishvili Tbilisi State University, Tbilisi;(b)High Energy Physics Institute, Tbilisi State University, Tbilisi;(c)University of Georgia, Tbilisi; Georgia 150 Department of Physics, Technion, Israel Institute of Technology, Haifa; Israel 151 Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv University, Tel Aviv; Israel 152 Department of Physics, Aristotle University of Thessaloniki, Thessaloniki; Greece 153 International Center for Elementary Particle Physics and Department of Physics, University of Tokyo, Tokyo; Japan 154 Department of Physics, Tokyo Institute of Technology, Tokyo; Japan 155 Department of Physics, University of Toronto, Toronto ON; Canada 156 (a)TRIUMF, Vancouver BC;(b)Department of Physics and Astronomy, York University, Toronto ON; Canada 157 Division of Physics and Tomonaga Center for the History of the Universe, Faculty of Pure and Applied Sciences, University of Tsukuba, Tsukuba; Japan 158 Department of Physics and Astronomy, Tufts University, Medford MA; United States of America 159 United Arab Emirates University, Al Ain; United Arab Emirates 160 Department of Physics and Astronomy, University of California Irvine, Irvine CA; United States of America 161 Department of Physics and Astronomy, University of Uppsala, Uppsala; Sweden 162 Department of Physics, University of Illinois, Urbana IL; United States of America 163 Instituto de Física Corpuscular (IFIC), Centro Mixto Universidad de Valencia — CSIC, Valencia; Spain 164 Department of Physics, University of British Columbia, Vancouver BC; Canada 165 Department of Physics and Astronomy, University of Victoria, Victoria BC; Canada 166 Fakultät für Physik und Astronomie, Julius-Maximilians-Universität Würzburg, Würzburg; Germany 167 Department of Physics, University of Warwick, Coventry; United Kingdom 168 Waseda University, Tokyo; Japan – 52 – JHEP07(2023)033 169 Department of Particle Physics and Astrophysics, Weizmann Institute of Science, Rehovot; Israel 170 Department of Physics, University of Wisconsin, Madison WI; United States of America 171 Fakultät für Mathematik und Naturwissenschaften, Fachgruppe Physik, Bergische Universität Wuppertal, Wuppertal; Germany 172 Department of Physics, Yale University, New Haven CT; United States of America aAlso Affiliated with an institute covered by a cooperation agreement with CERN bAlso at An-Najah National University, Nablus; Palestine c Also at Borough of Manhattan Community College, City University of New York, New York NY; United States of America dAlso at Bruno Kessler Foundation, Trento; Italy eAlso at Center for High Energy Physics, Peking University; China fAlso at Center for Interdisciplinary Research and Innovation (CIRI-AUTH), Thessaloniki; Greece gAlso at Centro Studi e Ricerche Enrico Fermi; Italy hAlso at CERN, Geneva; Switzerland iAlso at Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève; Switzerland jAlso at Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona; Spain k Also at Department of Financial and Management Engineering, University of the Aegean, Chios; Greece lAlso at Department of Physics and Astronomy, Michigan State University, East Lansing MI; United States of America mAlso at Department of Physics, Ben Gurion University of the Negev, Beer Sheva; Israel nAlso at Department of Physics, California State University, East Bay; United States of America oAlso at Department of Physics, California State University, Sacramento; United States of America pAlso at Department of Physics, King’s College London, London; United Kingdom qAlso at Department of Physics, University of Fribourg, Fribourg; Switzerland rAlso at Department of Physics, University of Thessaly; Greece sAlso at Department of Physics, Westmont College, Santa Barbara; United States of America tAlso at Hellenic Open University, Patras; Greece uAlso at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona; Spain vAlso at Institut für Experimentalphysik, Universität Hamburg, Hamburg; Germany wAlso at Institute of Applied Physics, Mohammed VI Polytechnic University, Ben Guerir; Morocco xAlso at Institute of Particle Physics (IPP); Canada yAlso at Institute of Physics and Technology, Ulaanbaatar; Mongolia zAlso at Institute of Physics, Azerbaijan Academy of Sciences, Baku; Azerbaijan aa Also at Institute of Theoretical Physics, Ilia State University, Tbilisi; Georgia ab Also at Lawrence Livermore National Laboratory, Livermore; United States of America ac Also at The Collaborative Innovation Center of Quantum Matter (CICQM), Beijing; China ad Also at TRIUMF, Vancouver BC; Canada ae Also at Università di Napoli Parthenope, Napoli; Italy af Also at University of Chinese Academy of Sciences (UCAS), Beijing; China ag Also at University of Colorado Boulder, Department of Physics, Colorado; United States of America ah Also at Washington College, Maryland; United States of America ∗Deceased – 53 –