Measurement of the nuclear modification factor for muons from charm and bottom hadrons in Pb+Pb collisions at 5.02 TeV with the ATLAS detector

Physics Letters B 829 (2022) 137077 Contents lists available at ScienceDirect Physics Letters B www.elsevier.com/locate/physletb Measurement of the nuclear modification factor for muons from charm and bottom hadrons in Pb+Pb collisions at 5.02 TeV with the ATLAS detector .The ATLAS Collaboration a r t i c l e i n f o a b s t r a c t Article history: Received 2 September 2021 Received in revised form 16 February 2022 Accepted 2 April 2022 Available online 6 April 2022 Editor: M. Doser Heavy-flavour hadron production provides information about the transport properties and microscopic structure of the quark–gluon plasma created in ultra-relativistic heavy-ion collisions. A measurement of the muons from semileptonic decays of charm and bottom hadrons produced in Pb+Pb and pp collisions at a nucleon–nucleon centre-of-mass energy of 5.02 TeV with the ATLAS detector at the Large Hadron Collider is presented. The Pb+Pb data were collected in 2015 and 2018 with sampled integrated luminosities of 208 μb−1and 38 μb−1, respectively, and pp data with a sampled integrated luminosity of 1.17 pb−1were collected in 2017. Muons from heavy-flavour semileptonic decays are separated from the light-flavour hadronic background using the momentum imbalance between the inner detector and muon spectrometer measurements, and muons originating from charm and bottom decays are further separated via the muon track’s transverse impact parameter. Differential yields in Pb+Pb collisions and differential cross sections in pp collisions for such muons are measured as a function of muon transverse momentum from 4GeV to 30 GeV in the absolute pseudorapidity interval |η| <2. Nuclear modification factors for charm and bottom muons are presented as a function of muon transverse momentum in intervals of Pb+Pb collision centrality. The bottom muon results are the most precise measurement of b quark nuclear modification at low transverse momentum where reconstruction of B hadrons is challenging. The measured nuclear modification factors quantify a significant suppression of the yields of muons from decays of charm and bottom hadrons, with stronger effects for muons from charm hadron decays. ©2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Funded by SCOAP3. 1. Introduction Quark–gluon plasma (QGP) is a state of matter in which the quarks and gluons are deconfined from colour-neutral hadronic states. Ultra-relativistic collisions of large nuclei create nuclei-sized droplets of QGP at temperatures in excess of 300–500 MeV [1,2]. These droplets exist for a mere 10−23 seconds and hence there is no way to fire an external probe at the droplet to investigate its properties. Instead, the probes must be generated in the collision itself and then interact with the droplet. Interactions with the QGP, both radiative and collisional, may provide key information regarding the properties and constituents of the QGP [3]. Specifically, the balance of radiative and collisional energy transfer depends on the mass of the constituents [4,5]. Heavy quarks, charm and bottom, have masses much larger than the droplet temperature. Thus, they are produced in the initial collision via high-momentum-transfer interactions between incident quarks and gluons. The strong-force interactions conserve the quantum numbers associated with the E-mail address: atlas .publications @cern .ch. charm and bottom quarks. Thus, once created, these quarks can have substantial modifications to their momentum distributions when traversing the QGP, but they cannot be destroyed. In addition, radiative energy loss is suppressed for heavy quarks by the so-called ‘dead-cone effect’ [6], i.e. gluon radiation is suppressed at angles smaller than the quark’s mass to energy ratio. A key to constraining the relative contribution of radiative energy loss is to measure the modification of the momentum distributions for charm and bottom quarks separately, since the dead-cone effect will be more pronounced for bottom quarks than for charm quarks at the same momentum. There are numerous publications detailing the modifications of momentum distributions of heavy-flavour hadrons measured in heavy-ion collisions via direct reconstruction and via decay leptons in heavy-ion collisions at the Relativistic Heavy Ion Collider (RHIC) [7] and the Large Hadron Collider (LHC) [8]– current measurements and theory calculations are reviewed in Refs. [9,10]. In nucleus–nucleus (A+A) collisions, each event is described by its centrality, which reflects the overlap of the colliding nuclei. The geometry of each event is calculated using a Monte Carlo (MC) Glauber model – for details see Ref. [11]. The modification to parhttps://doi.org/10.1016/j.physletb.2022.137077 0370-2693/©2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Funded by SCOAP3. The ATLAS Collaboration Physics Letters B 829 (2022) 137077 ticle yields in A+A collisions relative to pp collisions is quantified by a nuclear modification factor RAA defined as: RAA =NAA/Nevt TAA×σpp ,(1) where NAA is the number of observed particles of interest in Pb+Pb collisions, Nevt is the number of minimum-bias Pb+Pb events, TAAis the average value of the nuclear thickness function, and σpp is the particle production cross section in pp collisions at the same collision energy. If RAA equals unity, the production in A+A collisions is the same as in pp collisions but scaled up by the larger parton–parton luminosity, while RAA <1 indicates a suppression. The nuclear modification factors for inclusive ‘heavy-flavour muons’ (mostly muons from Dand Bmeson semileptonic decays) have been measured in Pb+Pb collisions at √sNN =2.76 TeV by the ATLAS experiment [12] and the ALICE experiment [13]. The ALICE experiment measured the nuclear modification factor for inclusive heavy-flavour electrons at the same energy [14,15] and also at √sNN =5.02 TeV [16]. Nuclear modification factors for charm hadrons D0, Ds, D∗, and chave been measured by the CMS [17] and ALICE [18,19] experiments in Pb+Pb collisions at √sNN =5.02 TeV, and by the STAR [20–23] experiment in Au+Au collisions at a lower energy of √sNN =200 GeV. These measurements indicate significant suppression for heavy-flavour hadrons in Pb+Pb collisions. At transverse momentum (pT) greater than 4GeV, the prompt-D0RAA is found to be consistent within the uncertainties with the RAA of inclusive charged particles (dominated by π), while at lower pTvalues D0mesons have a smaller suppression (larger RAA) compared to charged particles, as expected theoretically from the dead-cone effect. The measurement presented here follows the previous ATLAS measurement of muons originating from heavy-flavour hadron decays in Pb+Pb collisions at √sNN =2.76 TeV [12]. This Letter, based on the higher number of events in the combined 2015 and 2018 Pb+Pb datasets and the 2017 pp dataset at 5.02 TeV, extends results to the transverse momentum range 4 <pT<30 GeV, and more importantly, further separates inclusive heavy-flavour muons into contributions from charm hadron decays (charm muons) and bottom hadron decays (bottom muons). The charm and bottom contribution separation is based on the muon track’s transverse impact parameter, similar to the method used in previous ATLAS measurements [24,25]. Results for charm and bottom muon cross sections in pp collisions are shown as a function of muon pTand compared with perturbative QCD calculations. The nuclear modification factor is presented as a function of muon pTin various Pb+Pb centrality intervals. Finally, the RAA measurements, along with a previous measurement of the heavy-flavour muon momentum anisotropies [25], are compared with the expectations from theoretical calculations. The RAA value quantifies the average energy loss, and the azimuthal anisotropy, v2[25], at high pT, quantifies the azimuthal angle dependence of energy loss. Simultaneous constraints on RAA and v2for the same final state are important in distinguishing the relative impacts of different heavy-quark energy loss mechanisms and in understanding the influence of the initial QGP droplet geometry on the resulting evolution of kinematics of heavy-flavour quarks in the medium. 2. ATLAS detector The ATLAS detector [26–28]at the LHC covers nearly the entire solid angle around the collision point.1It consists of an inner 1ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP) in the centre of the detector and the z-axis along the beam pipe. The x-axis points from the IP to the centre of the LHC ring, and the y-axis tracking detector surrounded by a thin superconducting solenoid, electromagnetic and hadronic calorimeters, and a muon spectrometer incorporating three large superconducting toroidal magnets with eight coils each. The inner-detector system (ID) is immersed in a 2T 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 in the insertable B-layer installed before Run 2 [27,28]. 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| =2.0. The calorimeter system covers the pseudorapidity range |η| < 4.9. Within the region |η| <3.2, electromagnetic calorimetry is provided by barrel and endcap high-granularity lead/liquidargon (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 within |η| <1.7, and two copper/LAr hadronic endcap calorimeters. The solid angle coverage is completed with forward copper/LAr and tungsten/LAr calorimeter modules (FCal), covering the forward regions of 3.1 <|η| <4.9, optimized for electromagnetic and hadronic measurements respectively. The minimum-bias trigger scintillators detect charged particles over 2.07 <|η| <3.86 using two hodoscopes of 12 counters positioned at z=±3.6 m. The zero-degree calorimeters (ZDC) measure neutral particles at pseudorapidities |η| ≥8.3 and consist of layers of alternating quartz rods and tungsten plates. The muon spectrometer (MS) comprises separate trigger and high-precision tracking chambers measuring the deflection of muons in a magnetic field generated by superconducting air-core toroids. The 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 is highest. The muon trigger system covers the range |η| <2.4with resistive-plate chambers in the barrel, and thin-gap chambers in the endcap regions. Events of interest are selected to be recorded by the first-level trigger (L1) system implemented in custom hardware, followed by selections made by algorithms implemented in software in the high-level trigger (HLT) [29]. The first-level trigger selects events from the 40 MHz bunch crossings at a rate below 100 kHz (75 kHz) for pp (Pb+Pb) collisions, and the high-level trigger reduces the average event output rate to about 1.2 kHz for recording. An extensive software suite [30]is used for real and simulated data reconstruction and analysis, for operation and in the trigger and data acquisition systems of the experiment. 3. Event selection The pp data used in this analysis were recorded with the ATLAS detector in 2017, while the Pb+Pb data were recorded in 2015 and 2018. Both the pp and Pb+Pb events were selected online using a trigger that requires a muon at the L1 and HLT with a pTlarger than 4GeV[29,31]. After selecting run periods when the detector subsystems were operational and taking into account the fraction of the total luminosity sampled by the triggers, the datasets used points upwards. Cylindrical coordinates (r, φ) are used in the transverse plane, φ being the azimuthal angle around the z-axis. The pseudorapidity is defined in terms of the polar angle θas η=− lntan(θ/2). Angular distance is measured in units of R ≡(η)2+(φ)2. 2 The ATLAS Collaboration Physics Letters B 829 (2022) 137077 Fig. 1. Fit results of the ρdistribution for muons with 6 <pT<7GeVin pp collisions (left) and in Pb+Pb collisions with 20–30% centrality (right). The ratios of the data to fit results are shown in the lower panels. The prompt-muon background contributions are very small in the fitted muon kinematic region. The grey bands in the lower panels indicate the statistical and systematic uncertainties combined in quadrature. in the analysis correspond to integrated luminosities of 1.17 pb−1 for pp data, 208 μb−1for 2015 Pb+Pb data, and 38 μb−1for 2018 Pb+Pb data. The 2017 pp data, with a small average number of interactions per bunch crossing in the range from 0.4to 4, were collected to serve as the baseline for Pb+Pb collision measurements at the same centre-of-mass energy per nucleon pair. Only a small fraction of events from the 2018 Pb+Pb data was recorded by the low pTmuon trigger used in this analysis. Other muon triggers in the 2018 Pb+Pb data were studied and improved statistical uncertainties while increasing systematic uncertainties, and are thus not incorporated. The 2015 and 2018 results are consistent and thus combined in these results. The selected Pb+Pb events are further required to satisfy offline minimum-bias Pb+Pb collision criteria, identical to those used in Ref. [25]. This additional requirement identifies and rejects 0.2% of the selected events as pile-up events, based on a combination of the total transverse energy measured in the FCal, denoted by EFCal T, and the ZDC energy. The centrality of each Pb+Pb event is characterized by its EFCal T value. For the results shown here, the minimum-bias EFCal Tdistribution is divided into percentiles ordered from the most central (large EFCal T, small impact parameter) to the most peripheral (small EFCal T, large impact parameter): 0–10%, 10–20%, 20–30%, 30–40%, and 40–60%. The interval 0–100% corresponds to the total Pb+Pb inelastic cross section [32]. An MC Glauber [11]model is used to calculate TAAfor each centrality interval [33]. Muons with 4 <pT<30 GeV and |η| <2 reconstructed in both the ID and the MS are selected and required to pass ‘medium’ selection requirements, detailed in Ref. [34]. Selected muons are required to be matched with an online muon candidate that fires the event trigger. Each muon is assigned a weight which is the inverse of the product of the reconstruction and trigger efficiencies, evaluated for muons as a function of their kinematic variables, and in the case of Pb+Pb data as a function of centrality as well. The muon reconstruction and identification efficiency is factorized as the product of the individual reconstruction efficiencies in the ID and MS, where the ID and MS matching efficiency is included in the MS efficiency. The ID and MS efficiencies in pp collisions are determined in the large pp dataset collected in 2017 at √s=13 TeV, using the tag-and-probe method on J/ψ →μ+μ− events as detailed in Ref. [34]. They are applied to the pp data at √s=5.02 TeV used in this analysis, in fine intervals of muon pT and η. The difference between the muon reconstruction efficiencies at √s=5.02 TeV and √s=13 TeV due to different pile-up contributions and multiplicities is found to be negligible [34]. The MS efficiencies obtained from pp and Pb+Pb data collected in the same year show no significant difference. Thus, the MS efficiencies for 2015 and 2018 Pb+Pb data are obtained from the large pp datasets at √s=13 TeV in the corresponding years in fine intervals of muon pTand η. The resulting MS efficiency plateaus at 97% at pT>7GeV. The ID efficiency in Pb+Pb events is obtained from Pb+Pb data using the same J/ψ →μ+μ−tag-and-probe method in intervals of muon pTand η. The measured Pb+Pb ID efficiency is about 98% with the efficiency in 2018 being 3% lower than that in 2015 at 1 <|η| <2 independent of pT, while no difference between 2015 and 2018 is observed at |η| <1. No centrality dependence is observed for MS and ID efficiencies for muons in Pb+Pb collisions. The initial estimations of the muon trigger efficiency are obtained from J/ψ →μ+μ−Pythia 8 [35] simulations in fine intervals of muon pTand ηusing the tag-and-probe method [31]. All generated events were passed through aGeant4 simulation [36,37] of the ATLAS detector under the same conditions as present during data-taking and were digitized and reconstructed in the same way as the data. The same simulated trigger efficiency is used in pp and Pb+Pb data. Relative efficiency differences between simulations and data and between pp and Pb+Pb collisions are covered by additional corrections described as follows. Mis-modelling of the trigger performance in simulation, quantified by the ratio of measured efficiencies in data and the simulations, is accounted for by applying a multiplicative correction not exceeding 10%. To account for the different online muon momentum scale in pp and Pb+Pb data, as well as the slightly different trigger performance in 2015 and 2018, an additional correction factor, determined by the Pb+Pb to pp data-driven efficiency ratio, is applied to Pb+Pb data as a function of muon pTand η, the centrality, and the year of Pb+Pb data-taking. 4. Signal extraction As detailed in previous ATLAS publications [12,24,25,38], the background contributions in the selected muon samples (labelled ‘bkg’ in Figs. 1and 2) have three components. The first one is called the ‘prompt-muon background’ and includes contributions from decays of non-open–heavy-flavour particles such as direct quarkonia, low-mass resonances, τ-leptons, and massive electroweak W/Zbosons. The second component is the ‘hadronic background’ resulting from πand Kdecaying into muons in the volume of the ID or punching through the calorimeter. The last 3 The ATLAS Collaboration Physics Letters B 829 (2022) 137077 Fig. 2. (Top) d0templates for different background contributions, and data d0distributions before (solid points) and after (open points) background subtraction for muons with 6 <pT<7GeVin pp collisions (left) and in Pb+Pb collisions with 20–30% centrality (right). (Bottom) Fit results of the background-subtracted d0distribution for muons with 6 <pT<7GeVin pp collisions (left) and in Pb+Pb collisions with 20–30% centrality (right). The vertical dashed lines indicate the d0range, |d0| <0.5mm, used in the fit procedure. Data to fitted result ratios are shown in the bottom panels. The grey bands indicate the statistical and systematic uncertainties combined in quadrature. component is from random combinations of uncorrelated track segments from the ID and MS, called the ‘fake-muon background’. The prompt-muon background, expected to be small compared to signal muons, is estimated in simulations. These simulations are scaled to match existing measurements of different background sources under consistent fiducial selections. The main promptmuon background for muons with 20 <pT<30 GeV is from W decays, and is approximately 3% in pp collisions at 10% (5%) in 0-10% (40-60%) Pb+Pb collisions based on previous ATLAS measurements [39,40]. Hadronic and fake-muon backgrounds are subtracted from the signal muons by fitting the muon momentum imbalance, ρ=(pID −pMS)/pID, where pID is the muon momentum measured in the ID, and pMS is that measured in the MS corrected for the energy loss inside the calorimeter. The ρdistribution shapes of hadronic and fake-muon backgrounds are extracted from simulations while their yields are determined from the fit procedure. The prompt-muon background contribution in pp events is estimated from Pythia 8 simulations of prompt J/ψ, ψ(2S), and Υ(nS)production based on a non-relativistic QCD colour-octet model [41], and from Wand Zproduction simulated with the Powheg Box v2 generator [42]interfaced to the Pythia 8 parton shower model. The CT10 PDF set [43]was used in the matrix element, while the CTEQ6L1 PDF set [44]was used for the modelling of non-perturbative effects in the initial-state parton shower. The simulated prompt-muon background processes are all scaled by process-dependent single scaling factors to match previous ATLAS measurements in pp collisions at √s=5.02 TeV [39,45]. Other contributions from low-mass resonances and τ-leptons in the measured muon pTrange are found to be less than 1% [24,38] and are neglected in this analysis. In Pb+Pb collisions, the estimated prompt-muon background rates take into account nuclear modifications measured in Refs. [40,46–48]. Muons from hard scattering have a symmetric ρdistribution peaked at zero, while the hadronic background has a broader ρdistribution and the peak shifted toward higher values. This change in shape is due to differences between the actual energy loss of this background and the estimated energy loss based on muon simulations. Only energy loss of muons is properly corrected for and added to the MS momentum measurement. The different shapes of the ρdistributions for the hadronic background and the other muons allow the hadronic background to be isolated using a template-fitting procedure [24,25]. The yields of inclusive heavy-flavour muons and hadronic background muons are extracted from the ρtemplate fit. The templates for the charm and bottom muon ρdistributions are determined from multijet hardscattering Pythia 8 pp collision events at √s=5.02 TeV filtered for the presence of a generator-level muon produced with parameter values as in the A14 tune [49] and using the NNPDF23lo parton distribution functions [50]. The templates for the charm and bottom muon ρdistributions (and track transverse impact parameter, d0, distributions, described below) in multijet hardscattering QCD Pythia 8 samples are found to be identical to those from non-diffractive QCD Pythia 8 samples, while hard-scattering QCD Pythia 8 samples have much higher muon filter efficiency. The ρtemplates for the prompt-muon background are obtained from the simulation procedure described in the previous paragraph. The hadronic background and fake-muon ρtemplates are obtained from non-diffractive QCD simulations of pp collisions at √s=5.02 TeV in Pythia 8, with the A14 tune and NNPDF23lo parton distribution functions. The fake-muon contribution is fixed relative to the hadronic background, with the ratio obtained from 4 The ATLAS Collaboration Physics Letters B 829 (2022) 137077 simulations. The momenta of the reconstructed muons selected in Pythia 8 simulations are calibrated to match the muon momentum response in pp and Pb+Pb data. The calibration is performed via shift and smearing parameters [25]determined from the invariant mass response in J/ψ →μ+μ−events. The same calibration is applied to all muon candidates including those from background contributions. Alternative calibrations for background contributions are used for the systematic uncertainty evaluation. Examples of the ρtemplate fit are shown in Fig. 1for muons with 6 <pT<7GeVin pp collisions and 20–30% centrality Pb+Pb collisions. The signal muon ρdistribution shape shows no obvious dependence on muon pT, but is found to be broader in the more forward pseudorapidity region and more central Pb+Pb collisions, both due to poorer muon momentum resolution in the ID. The hadronic background ρdistribution becomes broader at higher pT and in more central collisions. Charm and bottom muons are further separated using the muon track’s transverse impact parameter, d0, which is calculated relative to the beam spot [51]. Due to the different lifetimes of charm and bottom hadrons (approximately 1.5 ×10−12 s for B mesons, 1.0 ×10−12 s for D+and 0.4 ×10−12 s for D0mesons), the corresponding muons have different d0distributions, and their fractional contributions can be extracted using a template-fitting procedure. Background contributions are subtracted from data distributions of d0as shown in the upper panels in Fig. 2. For each of the three background sources, the d0shape is determined in simulations. In pp data analysis, the d0shape templates of various background sources are obtained from the Pythia 8 simulations used to build the ρtemplates. In Pb+Pb data analysis, the same Pythia 8 events overlaid with minimum-bias Pb+Pb events collected in 2015 are used to build the background d0templates to approximate background distributions in Pb+Pb collisions. The d0distributions from high-quality prompt tracks in simulations and 2018 Pb+Pb data are smeared to match those in 2015 Pb+Pb data. The prompt-muon background d0distribution normalization is constrained by the yield estimates from MC simulations. The hadronic and fake-muon background d0distribution normalization factors are extracted from the ρtemplate fit. The signal muon d0 distribution in Pb+Pb data is narrower than in pp data because of a smaller transverse beam size. The background d0distribution becomes moderately narrower with increasing pTand shows no evident centrality dependence. After subtraction, the remaining d0 distribution in data contains only contributions from heavy-flavour muons. The d0fit is performed in the range of |d0| <0.5mmas events with |d0| >0.5mmare statistically limited in both data and simulations and have little sensitivity to the charm muon contribution. For pp data, the charm and bottom muon d0templates are obtained from the muon-filtered multijet Pythia 8 simulations at √s=5.02 TeV, as done for ρtemplates. Bottom muons contain the b →c→μcascade contribution. The d0distributions of signal muons show no obvious dependence on the muon pT, but they become broader with increasing parent Band Dmeson pT. The simulated samples from Pythia 8 are reweighted to match the inclusive Band Dmeson pTspectra from fixed-order next-toleading-log (FONLL) resummation calculations [52,53]. The charm and bottom baryon-to-meson ratios in the simulations are corrected to match the measured values in Refs. [54,55]. The baryonto-meson ratio is treated the same in pp and Pb+Pb, and allowed to vary independently for each system by a factor of two, based on values reported in Ref. [56], in determining systematic uncertainties. The yield of D+relative to D0is corrected to match the measured value in Refs. [57,58]. In the Pb+Pb analysis, the charm and bottom muon d0templates are obtained from the pp Pythia 8 simulations overlaid with minimum-bias Pb+Pb events from 2015, similar to what is done for the background d0templates. Besides the FONLL resummation and baryon-to-meson corrections as applied in pp collisions, an additional correction is applied to match the modified charm and bottom hadron pTspectra measured in Pb+Pb collisions by ALICE [18] and CMS [17]. Examples of d0template fits for muons with 6 <pT<7GeVare shown in Fig. 2for pp collisions and 20–30% centrality Pb+Pb collisions. The relative fractions of charm and bottom muons are extracted from the d0 template fit. 5. Systematic uncertainties Systematic uncertainties associated with the various steps of the analysis are assessed. The measured cross section in pp collisions, per-event yields in Pb+Pb collisions and RAA are recalculated by systematically varying the effect of each source of uncertainty and then compared with the nominal results. The resulting difference is assigned as a systematic uncertainty. Each group of systematic uncertainties described in the following subsections are considered as uncorrelated, and are therefore summed in quadrature. Some sources of systematic uncertainties that are correlated between pp and Pb+Pb collisions partially cancel out in RAA. 5.1. Muon correction uncertainties The systematic uncertainties from the muon reconstruction efficiency and muon trigger efficiency corrections for pp collisions are dominated by the uncertainty in determining these efficiencies in data with the tag-and-probe method. These are evaluated following the procedures in previous ATLAS measurements [31, 34], including variations in the tag-and-probe efficiency extraction method, online–offline matching requirement, and muon purity in the selected sample. The Pb+Pb efficiency is affected by the systematic uncertainty sources mentioned above, due to the use of the pp efficiency in the factorized treatment. An additional uncertainty in Pb+Pb is associated with the determination of the ID reconstruction efficiency in data using the tag-and-probe method. Uncertainties in the trigger efficiency correction are determined from the Pb+Pb to pp efficiency ratio and residual discrepancies between fully corrected Pb+Pb muon spectra measured in the 2015 and 2018 data-taking periods. Apart from specific Pb+Pb uncertainties, other uncertainties are correlated between collision systems and thus cancel out in RAA. 5.2. Background removal uncertainties The systematic uncertainty in the momentum imbalance templates includes the effect of the uncertainty in the muon momentum calibration parameters, the uncertainty due to the dedicated hadronic-background calibration, and the uncertainty due to ρ–d0 correlation in the hadronic background. Charm muon yields are more sensitive to the background removal procedure as charm muons have narrower d0distributions around 0 where the background contamination is large. The systematic uncertainties in the calibration parameters, which originate from the uncertainty in the determination of J/ψ →μ+μ−invariant mass [59], contribute 3% relative uncertainty to the final charm muon yields and 1% to the bottom muon yields. Since the hadronic background could have a different momentum scale than that for real muons, the results are also examined using a data-driven hadronic-background momentum calibration in the background-dominated region ρ>0.2. The difference is included as a systematic uncertainty which is about 10% (4%) for charm (bottom) muon yields at low pTand decreases with increasing pT. To account for the small ρ–d0correlation in hadronic background, the corresponding ρtemplates in different d0selections are used and the resulting difference is assigned as an additional systematic uncertainty. The relative uncertainty due 5 The ATLAS Collaboration Physics Letters B 829 (2022) 137077 Table 1 Contributions to systematic uncertainties given in percent for the cross section in pp, yields in Pb+Pb, and nuclear modification factor of charm and bottom muons. Ranges indicate the minimum and maximum systematic uncertainties found in all muon pTbins and centralities for a given source. Source σpp [%] NAA [%] RAA [%] c→μb→μc→μb→μc→μb→μ Muon efficiency 0.5–1.0 0.4–0.6 0.6–16 0.3–16 0.3–16 0.2–16 Background removal 4.3–12 0.8–3.8 2.5–30 1.0–5.1 1.9–27 0.5–4.7 Charm–bottom separation 4.5–9.8 3.2–8.0 9.2–37 6.2–16 5.1–23 4.1–13 Global normalization 1.61.6 0.9–4.6 0.9–4.6 1.8–4.9 1.8–4.9 Total systematic uncertainty 5.8–13 3.1–7.4 10–47 6.9–19 6.5–35 5.4–18 to the background ρ–d0correlation is about 3% for charm muon yields and less than 1% for bottom muon yields. The ρ-templaterelated systematic uncertainties are treated as correlated between pp and Pb+Pb data, and partially cancel out in RAA. In the analysis, the size of each prompt-muon background contribution is held at a fixed value obtained from Pythia 8 simulations scaled to match existing measurements. To assess the associated uncertainty, the pp and Pb+Pb analyses are repeated while varying the estimated sizes of the different prompt-muon contributions by the corresponding experimental uncertainties in their production rates [39,45] and RAA values [40,46–48]. The sensitivity to the fake-muon rate estimation is evaluated by varying the fakemuon candidate definition in simulations with different truth-level and reconstruction-level objects matching criteria. The resulting variation of the fake-muon rate is about 20–40%, and produces 5% variations, on average, in the measured charm and bottom yields. The fake-muon systematic uncertainty is assumed to be uncorrelated between the pp and Pb+Pb results. 5.3. Charm–bottom separation uncertainties The systematic uncertainties in the impact parameter template, that are common for pp and Pb+Pb results, include several components. Uncertainties in the FONLL calculations are evaluated based on Ref. [52,53]. Uncertainties coming from baryon-to-meson ratio mis-modelling correction use measurements published in Ref. [54,55]. Uncertainties in D+/D0mis-modelling correction are based on reported uncertainties in Ref. [60,61]. They are propagated to the pp and Pb+Pb results, and are treated as correlated between the pp and Pb+Pb results. The muon pTspectra predicted by FONLL calculations are weighted to match the measured charm and bottom muon spectra reported in this Letter. The resulting weighting factors are used to adjust signal d0templates to quantify the bias due to observed mis-modelling in the FONLL calculations. The resulting difference of 1–5% in the muon yields is assigned as an additional uncertainty and is treated as correlated between the pp and Pb+Pb results. Uncertainties in the nuclear modification factor for parent hadrons in Pb+Pb are propagated using the experimental uncertainties in Dand Bmeson RAA values from Refs. [17,18]. Minimum-bias Pb+Pb events collected in 2018, instead of 2015 events, are used to overlay with Pythia 8 simulations to test the sensitivity to slightly different overlay conditions. Resulting changes in the muon yields due to different overlay conditions are assigned as a systematic uncertainty in the Pb+Pb results. Uncertainties in the determination of d0shift and smearing parameters are found to have a negligible impact, less than 0.5%, on the extracted charm and bottom yields. 5.4. Global normalization uncertainties In the 2017 pp data, the LUCID-2 detector [62]is used for the primary luminosity measurement. The uncertainty in the integrated luminosity is derived using the methods described in Ref. [63], and is 1.6%. For Pb+Pb collisions, the systematic uncertainty in TAAis estimated by varying the MC Glauber model parameters as detailed in Ref. [33]. 5.5. Uncertainty summary Table 1summarizes relative uncertainties in the measurement of charm and bottom muon production in pp and Pb+Pb collisions, and in the nuclear modification factor RAA. The leading sources of uncertainty in all muon pTbins and Pb+Pb collision centralities are the background removal and charm–bottom separation uncertainties, and at low muon pTin central Pb+Pb collisions the evaluation of the muon efficiency. 6. Results Fig. 3shows the differential cross section for muons from charm and bottom hadron decays within |η|<2as a function of muon pTin pp collisions at √s=5.02 TeV. The measurements are compared with theoretical calculations for muons from Dand Bmeson decays in the FONLL resummation framework [64]. Uncertainties affecting the FONLL calculations include uncertainties in the parton distribution functions, heavy-flavour quark masses, and the renormalization and factorization scales. For muons from charm quarks, the FONLL calculation reaches the experimental data with the upper edge of its uncertainty band at pT<10 GeV, but underestimates the data at higher pT. Similar differences between FONLL calculations and prompt-charm measurements were observed in previous measurements at LHC energies, for example, in ALICE measurements of prompt Dmesons [65] and inclusive heavy-flavour leptons [16,66], and in an LHCb measurement of prompt Dmesons [67]. The measured cross section for muons from bottom quarks is a factor of 1.3–1.4 higher than the FONLLcalculated central value (including b →c→μ) but still inside the FONLL calculation’s uncertainty band at low pT, while the calculated central value agrees with the data within experimental uncertainties for pT>10 GeV, similar to observations in a previous ATLAS measurement of non-prompt charmonium [59] and an ALICE measurement of non-prompt Dmesons [60]. Fig. 4shows the differential per-event invariant yields for muons from charm and bottom hadron decays, in Pb+Pb collisions at √sNN =5.02 TeV as a function of muon pT. To quantify the modification of the momentum distribution between pp and Pb+Pb collisions the nuclear modification factor is calculated according to Eq. (1)in several centrality intervals. The resulting charm and bottom muon RAA values are shown in Fig. 5as a function of muon pT. There is substantial suppression of muons from both charm and bottom hadron decays for all analysed Pb+Pb centrality intervals. The suppression increases monotonically from the 40–60% interval to the most central 0–10% interval. The monotonic centrality dependence follows expectations as the heavy quarks spend a longer time in the hotter and larger QGP droplet formed in collisions that have larger nuclear overlap, i.e. the more central inter6 The ATLAS Collaboration Physics Letters B 829 (2022) 137077 Fig. 3. Differential cross section of charm (left) and bottom (right) muons as a function of muon pT, plotted at the centres of the pTintervals, in pp collisions at √s=5.02 TeV in comparison with FONLL calculations. Data results and FONLL calculations for bottom muons both include the b →c→μcontribution. Statistical uncertainties in the data are shown as vertical lines and systematic uncertainties in the data and calculation are shown as boxes. Fig. 4. Differential per-event invariant yields of muons from charm hadron decays (left) and bottom hadron decays (right) as a function of pT, plotted at the centres of the pTintervals, for different centrality intervals in Pb+Pb collisions at √sNN =5.02 TeV. For each centrality interval from peripheral to central, an additional scaling factor of 2 is applied to the plotted points for visual clarity. Statistical uncertainties are shown as vertical lines and systematic uncertainties as boxes. vals. Charm muon RAA shows weak pTdependence in all centrality intervals, while bottom muon RAA first decreases with increasing muon pTup to 10 GeV and then remains mostly unchanged in all centralities. Muons from charm decays have a stronger suppression than muons from bottom decays at low pTin all centrality intervals. This difference in suppression is highlighted in Fig. 6, which overlays the 0–10% and 40–60% centrality intervals already presented in Fig. 5for both charm and bottom muon RAA. The mass ordering of the measured RAA follows expectations, as the charm quarks, being lighter than the bottom quarks, are expected to lose more energy in the QGP. Thus the charm quarks are pushed further to lower pT, and emerge more strongly suppressed than bottom quarks when compared with the cross section in pp collisions. The decay muon pTspectrum depends on the pTspectra of various charm and bottom hadrons in pp and Pb+Pb collisions. A portion of the difference found in the charm and bottom muon RAA results could be attributed to the difference between charm and bottom hadron spectra, and thus full model comparisons are necessary. Fig. 6also compares the experimental data with theoretical calculations referred to as dreena-b [68] and dab-mod [69,70]. The dreena-b calculation includes radiative and collisional energy loss of the heavy quarks traversing the QGP, the latter modelled via a 1+1D Bjorken expansion [71]with path-length distributions calculated following the procedure described in Ref. [72]. The width of the band corresponding to the dreena-b theoretical uncertainties reflects the range of the ratio of magnetic to electric screening masses as constrained by non-perturbative calculations [71]. As discussed in Ref. [68], the predicted RAA is higher for Bmesons than for Dmesons, converging to the same value at pT≈25 GeV as is expected when the particle pTbecomes much larger than the mass of the heavier b-quark. The corresponding RAA for muons shown for direct comparison with the experimental data is calculated using Pythia 8, which simulates meson decay kinematics. The dreena-b prediction is in reasonable agreement with the experimental data. The dab-mod framework used here includes calculations with only Langevin drag and diffusion contributions for the heavy quarks in the QGP. The curves shown here are obtained with Trento geometric initial conditions [73], heavy-quark Langevin dynamics with the Moore and Teaney parameterization [74], and coupling values for charm (bottom) of D/2πT=2.23 (2.79), where D is the spatial diffusion coefficient and Tis the temperature. The temperature at which heavy quarks decouple from the medium is T=160 MeV and both coalescence and fragmentation are implemented for hadronization. The dab-mod predictions with only 7 The ATLAS Collaboration Physics Letters B 829 (2022) 137077 Fig. 5. Nuclear modification factor, RAA, for muons from charm hadron decays (top panels) and bottom hadron decays (bottom panels) as a function of pTfor five different centrality intervals. The centrality intervals are separated for clarity into the left (0–10%, 20–30%, 40–60%) and right (10–20%, 30–40%) panels. Statistical uncertainties are shown as vertical lines and uncorrelated systematic uncertainties as boxes around the points. Correlated fractional systematic uncertainties, including TAA and pp luminosity uncertainties, are isolated as coloured boxes around unity for different centrality intervals. Langevin dynamics shown in Fig. 6as coloured solid lines are in qualitative agreement with the experimental data, but have a stronger pTdependence than the experimental data, particularly in the most central collisions. No uncertainties are included for dab-mod calculations shown here. It is notable that both of these calculations also predict the azimuthal anisotropies of the heavy-flavour muons. ATLAS has previously published azimuthal anisotropies quantified by the elliptic flow coefficient, v2, for muons from charm and bottom hadron decays [25]. The lower panels of Fig. 6show those ATLAS measurements of v2as a function of pTin comparison with both the dreena-b and dab-mod calculations. The dreena-b calculations agree qualitatively with both v2and RAA for both charm and bottom muons, while the previously described implementation of dab-mod underestimates the charm muon v2even though it qualitatively matches the RAA. In all theoretical implementations, a larger coupling of charm and bottom quarks to the QGP results in a reduced RAA (i.e. more suppression) and an increased v2(i.e. larger anisotropy). Thus, increasing the coupling of charm to the QGP in dab-mod, for example, could bring the predicted v2into closer agreement with data but would simultaneously decrease RAA, pushing the calculation further below the data. That said, another key component of these calculations is the modelling of the QGP space-time evolution, and thus it could be instructive in the future to compare the different theory calculations with a common QGP model to test whether the differences in RAA and v2arise from the QGP modelling or the energy-loss implementation. Fig. 7shows the measured ratio of charm muon RAA to bottom muon RAA as a function of pTin comparison with dreena-b and dab-mod calculations. The large uncertainty in the measured ratio is due to a strong negative correlation between the charm and bottom muon RAA uncertainties. As indicated by the measured RAA ratios, charm muons are significantly more suppressed than bottom muons in the pT<8 GeV range. However, no strong conclusion about the relative strength of their suppression can be drawn at higher pTwith existing large uncertainties. Compared with the ratios measured in data, the calculations underestimate the RAA ratios for 0–10% centrality, while they mostly capture the magnitude and pTdependence of the ratio for 40–60% centrality. As shown in Fig. 6, the discrepancy between data and the models in the 0–10% centrality interval is primarily due to the underestimation of charm muon RAA. 7. Conclusion The ATLAS experiment at the LHC has measured the production rates and nuclear modification factors, RAA, of muons from semileptonic decays of heavy-flavour hadrons in pp and Pb+Pb collisions at 5.02 TeV. The measurement uses 2017 pp data and combined 2015 and 2018 Pb+Pb data corresponding to integrated luminosities of 1.17 pb−1and 246 μb−1respectively. Compared to 8 The ATLAS Collaboration Physics Letters B 829 (2022) 137077 Fig. 6. Nuclear modification factor, RAA, (top) and elliptic flow, v2, results taken from Ref. [25](bottom) for muons from bottom hadron decays and charm hadron decays for 0–10% (left) and 40–60% (right) centrality intervals as a function of pT. Statistical uncertainties are shown as vertical lines and systematic uncertainties as boxes. Also shown are theoretical calculations from the dreena-b and dab-mod models. See text regarding the uncertainty band of dreena-b model calculations. Fig. 7. The ratio of charm muon RAA to bottom muon RAA, Rcharm AA /Rbottom AA , for 0–10% (left) and 40–60% (right) Pb+Pb centrality intervals as a function of muon pT. Statistical uncertainties are shown as vertical lines and systematic uncertainties as boxes. Also shown are theoretical calculations for the decay muons from dreena-b and dab-mod in the same centrality intervals. a previous ATLAS measurement of heavy-flavour muons, this Letter reports separate results for charm and bottom muons and covers a wider pTrange. The differential cross section measured in pp collisions for muons from decays of hadrons containing a bottom quark is reproduced with FONLL calculations. For muons from decays of hadrons containing a charm quark, the FONLL calculation is lower than the data at all measured pTbut agrees with it within the systematic uncertainties of the calculations below 10 GeV. The RAA measurements indicate a significant suppression of the yield of muons from both charm and bottom hadron decays, with a suppression that increases monotonically from peripheral to central collisions. The suppression is stronger for charm quarks than for bottom quarks, as seen via muons at low pT<10 GeV. The relative difference between charm and bottom suppression is consistent with theoretical expectations for 10-60% Pb+Pb collisions, while the difference is smaller in data compared to theory for 0-10% Pb+Pb collisions. The simultaneous constraints imposed by the measurements of RAA presented here and the flow measurements previously published by ATLAS could provide important information for understanding heavy-quark transport and QGP properties. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. 9 The ATLAS Collaboration Physics Letters B 829 (2022) 137077 C. Li58a, C-Q. Li 58c,58d, H. Li58a, H. Li58b, J. Li 58c, K. Li 144, L. Li58c, M. Li 13a,13d, Q.Y. Li58a, S. Li 58d,58c,c, X. Li44, Y. Li 44, Z. Li 58b, Z. Li130, Z. Li101, Z. Li 88, Z. Liang 13a, M. Liberatore44, B. Liberti 71a, K. Lie 60c, K. Lin104, R.A. Linck63, R.E. 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Ziolkowski 147, L. Živkovi´ c14, A. Zoccoli 21b,21a, K. Zoch52, T.G. Zorbas 145, O. Zormpa42, W. Zou 37, L. Zwalinski34 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)Istanbul Aydin University, Application and Research Center for Advanced Studies, Istanbul; (c)Division of Physics, TOBB University of Economics and Technology, Ankara; Turkey 4LAPP, Univ. Savoie Mont Blanc, CNRS/IN2P3, Annecy; France 5High Energy Physics Division, Argonne National Laboratory, Argonne IL; United States of America 6Department of Physics, University of Arizona, Tucson AZ; United States of America 7Department of Physics, University of Texas at Arlington, Arlington TX; United States of America 8Physics Department, National and Kapodistrian University of Athens, Athens; Greece 9Physics Department, National Technical University of Athens, Zografou; Greece 10 Department of Physics, University of Texas at Austin, Austin TX; United States of America 11 (a)Bahcesehir University, Faculty of Engineering and Natural Sciences, Istanbul; (b)Istanbul Bilgi University, Faculty of Engineering and Natural Sciences, Istanbul; (c)Department of Physics, Bogazici University, Istanbul; (d)Department of Physics Engineering, Gaziantep University, Gaziantep; Turkey 12 Institut de Física d’Altes Energies (IFAE), Barcelona Institute of Science and Technology, Barcelona; Spain 13 (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 14 Institute of Physics, University of Belgrade, Belgrade; Serbia 15 Department for Physics and Technology, University of Bergen, Bergen; Norway 16 Physics Division, Lawrence Berkeley National Laboratory and University of California, Berkeley CA; United States of America 17 Institut für Physik, Humboldt Universität zu Berlin, Berlin; Germany 18 Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics, University of Bern, Bern; Switzerland 19 School of Physics and Astronomy, University of Birmingham, Birmingham; United Kingdom 20 (a)Facultad de Ciencias y Centro de Investigaciónes, Universidad Antonio Nariño, Bogotá; (b)Departamento de Física, Universidad Nacional de Colombia, Bogotá; Colombia 21 (a)Dipartimento di Fisica e Astronomia A. Righi, Università di Bologna, Bologna; (b)INFN Sezione di Bologna; Italy 22 Physikalisches Institut, Universität Bonn, Bonn; Germany 23 Department of Physics, Boston University, Boston MA; United States of America 24 Department of Physics, Brandeis University, Waltham MA; United States of America 25 (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; Romania 26 (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 27 Physics Department, Brookhaven National Laboratory, Upton NY; United States of America 28 Departamento de Física (FCEN) and IFIBA, Universidad de Buenos Aires and CONICET, Buenos Aires; Argentina 29 California State University, CA; United States of America 30 Cavendish Laboratory, University of Cambridge, Cambridge; United Kingdom 31 (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)School of Physics, University of the Witwatersrand, Johannesburg; South Africa 32 Department of Physics, Carleton University, Ottawa ON; Canada 33 (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; Morocco 34 CERN, Geneva; Switzerland 35 Enrico Fermi Institute, University of Chicago, Chicago IL; United States of America 36 LPC, Université Clermont Auvergne, CNRS/IN2P3, Clermont-Ferrand; France 37 Nevis Laboratory, Columbia University, Irvington NY; United States of America 38 Niels Bohr Institute, University of Copenhagen, Copenhagen; Denmark 39 (a)Dipartimento di Fisica, Università della Calabria, Rende; (b)INFN Gruppo Collegato di Cosenza, Laboratori Nazionali di Frascati; Italy 40 Physics Department, Southern Methodist University, Dallas TX; United States of America 41 Physics Department, University of Texas at Dallas, Richardson TX; United States of America 42 National Centre for Scientific Research “Demokritos”, Agia Paraskevi; Greece 43 (a)Department of Physics, Stockholm University; (b)Oskar Klein Centre, Stockholm; Sweden 44 Deutsches Elektronen-Synchrotron DESY, Hamburg and Zeuthen; Germany 45 Fakultät Physik, Technische Universität Dortmund, Dortmund; Germany 20 The ATLAS Collaboration Physics Letters B 829 (2022) 137077 46 Institut für Kernund Teilchenphysik, Technische Universität Dresden, Dresden; Germany 47 Department of Physics, Duke University, Durham NC; United States of America 48 SUPA – School of Physics and Astronomy, University of Edinburgh, Edinburgh; United Kingdom 49 INFN e Laboratori Nazionali di Frascati, Frascati; Italy 50 Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg; Germany 51 II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen; Germany 52 Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève; Switzerland 53 (a)Dipartimento di Fisica, Università di Genova, Genova; (b)INFN Sezione di Genova; Italy 54 II. Physikalisches Institut, Justus-Liebig-Universität Giessen, Giessen; Germany 55 SUPA – School of Physics and Astronomy, University of Glasgow, Glasgow; United Kingdom 56 LPSC, Université Grenoble Alpes, CNRS/IN2P3, Grenoble INP, Grenoble; France 57 Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge MA; United States of America 58 (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 59 (a)Kirchhoff-Institut für Physik, Ruprecht-Karls-Universität Heidelberg, Heidelberg; (b)Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg; Germany 60 (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 61 Department of Physics, National Tsing Hua University, Hsinchu; Taiwan 62 IJCLab, Université Paris-Saclay, CNRS/IN2P3, 91405, Orsay; France 63 Department of Physics, Indiana University, Bloomington IN; United States of America 64 (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 65 (a)INFN Sezione di Lecce; (b)Dipartimento di Matematica e Fisica, Università del Salento, Lecce; Italy 66 (a)INFN Sezione di Milano; (b)Dipartimento di Fisica, Università di Milano, Milano; Italy 67 (a)INFN Sezione di Napoli; (b)Dipartimento di Fisica, Università di Napoli, Napoli; Italy 68 (a)INFN Sezione di Pavia; (b)Dipartimento di Fisica, Università di Pavia, Pavia; Italy 69 (a)INFN Sezione di Pisa; (b)Dipartimento di Fisica E. Fermi, Università di Pisa, Pisa; Italy 70 (a)INFN Sezione di Roma; (b)Dipartimento di Fisica, Sapienza Università di Roma, Roma; Italy 71 (a)INFN Sezione di Roma Tor Vergata; (b)Dipartimento di Fisica, Università di Roma Tor Vergata, Roma; Italy 72 (a)INFN Sezione di Roma Tre; (b)Dipartimento di Matematica e Fisica, Università Roma Tre, Roma; Italy 73 (a)INFN-TIFPA; (b)Università degli Studi di Trento, Trento; Italy 74 Institut für Astround Teilchenphysik, Leopold-Franzens-Universität, Innsbruck; Austria 75 University of Iowa, Iowa City IA; United States of America 76 Department of Physics and Astronomy, Iowa State University, Ames IA; United States of America 77 Joint Institute for Nuclear Research, Dubna; Russia 78 (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; Brazil 79 KEK, High Energy Accelerator Research Organization, Tsukuba; Japan 80 Graduate School of Science, Kobe University, Kobe; Japan 81 (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 82 Institute of Nuclear Physics Polish Academy of Sciences, Krakow; Poland 83 Faculty of Science, Kyoto University, Kyoto; Japan 84 Kyoto University of Education, Kyoto; Japan 85 Research Center for Advanced Particle Physics and Department of Physics, Kyushu University, Fukuoka ; Japan 86 Instituto de Física La Plata, Universidad Nacional de La Plata and CONICET, La Plata; Argentina 87 Physics Department, Lancaster University, Lancaster; United Kingdom 88 Oliver Lodge Laboratory, University of Liverpool, Liverpool; United Kingdom 89 Department of Experimental Particle Physics, Jožef Stefan Institute and Department of Physics, University of Ljubljana, Ljubljana; Slovenia 90 School of Physics and Astronomy, Queen Mary University of London, London; United Kingdom 91 Department of Physics, Royal Holloway University of London, Egham; United Kingdom 92 Department of Physics and Astronomy, University College London, London; United Kingdom 93 Louisiana Tech University, Ruston LA; United States of America 94 Fysiska institutionen, Lunds universitet, Lund; Sweden 95 Centre de Calcul de l’Institut National de Physique Nucléaire et de Physique des Particules (IN2P3), Villeurbanne; France 96 Departamento de Física Teorica C-15 and CIAFF, Universidad Autónoma de Madrid, Madrid; Spain 97 Institut für Physik, Universität Mainz, Mainz; Germany 98 School of Physics and Astronomy, University of Manchester, Manchester; United Kingdom 99 CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille; France 100 Department of Physics, University of Massachusetts, Amherst MA; United States of America 101 Department of Physics, McGill University, Montreal QC; Canada 102 School of Physics, University of Melbourne, Victoria; Australia 103 Department of Physics, University of Michigan, Ann Arbor MI; United States of America 104 Department of Physics and Astronomy, Michigan State University, East Lansing MI; United States of America 105 B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk; Belarus 106 Research Institute for Nuclear Problems of Byelorussian State University, Minsk; Belarus 107 Group of Particle Physics, University of Montreal, Montreal QC; Canada 108 P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow; Russia 109 National Research Nuclear University MEPhI, Moscow; Russia 110 D.V. Skobeltsyn Institute of Nuclear Physics, M.V. Lomonosov Moscow State University, Moscow; Russia 111 Fakultät für Physik, Ludwig-Maximilians-Universität München, München; Germany 112 Max-Planck-Institut für Physik (Werner-Heisenberg-Institut), München; Germany 113 Graduate School of Science and Kobayashi-Maskawa Institute, Nagoya University, Nagoya; Japan 114 Department of Physics and Astronomy, University of New Mexico, Albuquerque NM; United States of America 115 Institute for Mathematics, Astrophysics and Particle Physics, Radboud University/Nikhef, Nijmegen; Netherlands 116 Nikhef National Institute for Subatomic Physics and University of Amsterdam, Amsterdam; Netherlands 117 Department of Physics, Northern Illinois University, DeKalb IL; United States of America 118 (a)Budker Institute of Nuclear Physics and NSU, SB RAS, Novosibirsk; (b)Novosibirsk State University Novosibirsk; Russia 119 Institute for High Energy Physics of the National Research Centre Kurchatov Institute, Protvino; Russia 120 Institute for Theoretical and Experimental Physics named by A.I. Alikhanov of National Research Centre “Kurchatov Institute”, Moscow; Russia 21 The ATLAS Collaboration Physics Letters B 829 (2022) 137077 121 Department of Physics, New York University, New York NY; United States of America 122 Ochanomizu University, Otsuka, Bunkyo-ku, Tokyo; Japan 123 Ohio State University, Columbus OH; United States of America 124 Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman OK; United States of America 125 Department of Physics, Oklahoma State University, Stillwater OK; United States of America 126 Palacký University, Joint Laboratory of Optics, Olomouc; Czech Republic 127 Institute for Fundamental Science, University of Oregon, Eugene, OR; United States of America 128 Graduate School of Science, Osaka University, Osaka; Japan 129 Department of Physics, University of Oslo, Oslo; Norway 130 Department of Physics, Oxford University, Oxford; United Kingdom 131 LPNHE, Sorbonne Université, Université de Paris, CNRS/IN2P3, Paris; France 132 Department of Physics, University of Pennsylvania, Philadelphia PA; United States of America 133 Konstantinov Nuclear Physics Institute of National Research Centre “Kurchatov Institute”, PNPI, St. Petersburg; Russia 134 Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh PA; United States of America 135 (a)Laboratório de Instrumentac¸ão 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 del Cosmos, Universidad de Granada, Granada (Spain); (g)Dep Física and CEFITEC of Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica; (h)Instituto Superior Técnico, Universidade de Lisboa, Lisboa; Portugal 136 Institute of Physics of the Czech Academy of Sciences, Prague; Czech Republic 137 Czech Technical University in Prague, Prague; Czech Republic 138 Charles University, Faculty of Mathematics and Physics, Prague; Czech Republic 139 Particle Physics Department, Rutherford Appleton Laboratory, Didcot; United Kingdom 140 IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette; France 141 Santa Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz CA; United States of America 142 (a)Departamento de Física, Pontificia Universidad Católica de Chile, Santiago; (b)Universidad Andres Bello, Department of Physics, Santiago; (c)Instituto de Alta Investigación, Universidad de Tarapacá, Arica; (d)Departamento de Física, Universidad Técnica Federico Santa María, Valparaíso; Chile 143 Universidade Federal de São João del Rei (UFSJ), São João del Rei; Brazil 144 Department of Physics, University of Washington, Seattle WA; United States of America 145 Department of Physics and Astronomy, University of Sheffield, Sheffield; United Kingdom 146 Department of Physics, Shinshu University, Nagano; Japan 147 Department Physik, Universität Siegen, Siegen; Germany 148 Department of Physics, Simon Fraser University, Burnaby BC; Canada 149 SLAC National Accelerator Laboratory, Stanford CA; United States of America 150 Department of Physics, Royal Institute of Technology, Stockholm; Sweden 151 Departments of Physics and Astronomy, Stony Brook University, Stony Brook NY; United States of America 152 Department of Physics and Astronomy, University of Sussex, Brighton; United Kingdom 153 School of Physics, University of Sydney, Sydney; Australia 154 Institute of Physics, Academia Sinica, Taipei; Taiwan 155 (a)E. Andronikashvili Institute of Physics, Iv. Javakhishvili Tbilisi State University, Tbilisi; (b)High Energy Physics Institute, Tbilisi State University, Tbilisi; Georgia 156 Department of Physics, Technion, Israel Institute of Technology, Haifa; Israel 157 Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv University, Tel Aviv; Israel 158 Department of Physics, Aristotle University of Thessaloniki, Thessaloniki; Greece 159 International Center for Elementary Particle Physics and Department of Physics, University of Tokyo, Tokyo; Japan 160 Department of Physics, Tokyo Institute of Technology, Tokyo; Japan 161 Tomsk State University, Tomsk; Russia 162 Department of Physics, University of Toronto, Toronto ON; Canada 163 (a)TRIUMF, Vancouver BC; (b)Department of Physics and Astronomy, York University, Toronto ON; Canada 164 Division of Physics and Tomonaga Center for the History of the Universe, Faculty of Pure and Applied Sciences, University of Tsukuba, Tsukuba; Japan 165 Department of Physics and Astronomy, Tufts University, Medford MA; United States of America 166 Department of Physics and Astronomy, University of California Irvine, Irvine CA; United States of America 167 Department of Physics and Astronomy, University of Uppsala, Uppsala; Sweden 168 Department of Physics, University of Illinois, Urbana IL; United States of America 169 Instituto de Física Corpuscular (IFIC), Centro Mixto Universidad de Valencia – CSIC, Valencia; Spain 170 Department of Physics, University of British Columbia, Vancouver BC; Canada 171 Department of Physics and Astronomy, University of Victoria, Victoria BC; Canada 172 Fakultät für Physik und Astronomie, Julius-Maximilians-Universität Würzburg, Würzburg; Germany 173 Department of Physics, University of Warwick, Coventry; United Kingdom 174 Waseda University, Tokyo; Japan 175 Department of Particle Physics and Astrophysics, Weizmann Institute of Science, Rehovot; Israel 176 Department of Physics, University of Wisconsin, Madison WI; United States of America 177 Fakultät für Mathematik und Naturwissenschaften, Fachgruppe Physik, Bergische Universität Wuppertal, Wuppertal; Germany 178 Department of Physics, Yale University, New Haven CT; United States of America aAlso at Borough of Manhattan Community College, City University of New York, New York NY; United States of America. bAlso at Bruno Kessler Foundation, Trento; Italy. cAlso at Center for High Energy Physics, Peking University; China. dAlso at Centro Studi e Ricerche Enrico Fermi; Italy. eAlso at CERN, Geneva; Switzerland. fAlso at CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille; France. gAlso at Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève; Switzerland. hAlso at Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona; Spain. iAlso at Department of Financial and Management Engineering, University of the Aegean, Chios; Greece. jAlso at Department of Physics and Astronomy, Michigan State University, East Lansing MI; United States of America. kAlso at Department of Physics and Astronomy, University of Louisville, Louisville, KY; United States of America. lAlso at Department of Physics, Ben Gurion University of the Negev, Beer Sheva; Israel. mAlso at Department of Physics, California State University, East Bay; United States of America. nAlso at Department of Physics, California State University, Fresno; United States of America. oAlso at Department of Physics, California State University, Sacramento; United States of America. 22 The ATLAS Collaboration Physics Letters B 829 (2022) 137077 pAlso at Department of Physics, King’s College London, London; United Kingdom. qAlso at Department of Physics, St. Petersburg State Polytechnical University, St. Petersburg; Russia. rAlso at Department of Physics, University of Fribourg, Fribourg; Switzerland. sAlso at Faculty of Physics, M.V. Lomonosov Moscow State University, Moscow; Russia. tAlso at Faculty of Physics, Sofia University, ‘St. Kliment Ohridski’, Sofia; Bulgaria. uAlso at Giresun University, Faculty of Engineering, Giresun; Turkey. vAlso at Graduate School of Science, Osaka University, Osaka; Japan. wAlso at Hellenic Open University, Patras; Greece. xAlso at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona; Spain. yAlso at Institut für Experimentalphysik, Universität Hamburg, Hamburg; Germany. zAlso at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest; Hungary. aa Also at Institute of Particle Physics (IPP); Canada. ab Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku; Azerbaijan. ac Also at Institute of Theoretical Physics, Ilia State University, Tbilisi; Georgia. ad Also at Instituto de Fisica Teorica, IFT-UAM/CSIC, Madrid; Spain. ae Also at Istanbul University, Dept. of Physics, Istanbul; Turkey. af Also at Joint Institute for Nuclear Research, Dubna; Russia. ag Also at Moscow Institute of Physics and Technology State University, Dolgoprudny; Russia. ah Also at National Research Nuclear University MEPhI, Moscow; Russia. ai Also at Physics Department, An-Najah National University, Nablus; Palestine. aj Also at Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg; Germany. ak Also at The City College of New York, New York NY; United States of America. al Also at TRIUMF, Vancouver BC; Canada. am Also at Universita di Napoli Parthenope, Napoli; Italy. an Also at University of Chinese Academy of Sciences (UCAS), Beijing; China. ao Also at Yeditepe University, Physics Department, Istanbul; Turkey. ∗Deceased. 23