PHYSICAL REVIEW C 100, 064901 (2019) Measurement of angular and momentum distributions of charged particles within and around jets √ in Pb + Pb and pp collisions at sNN = 5.02 TeV with the ATLAS detector G. Aad et al.∗ (ATLAS Collaboration) (Received 17 August 2019; published 2 December 2019) Studies of the fragmentation of jets into charged particles in heavy-ion collisions can provide information about the mechanism of jet quenching by the hot and dense QCD matter created in such collisions, the quark- gluon plasma. This paper presents a measurement of the angular distribution of charged particles around the jet √ axis in sNN = 5.02 TeV Pb + Pb and pp collisions, using the ATLAS detector at the LHC. The Pb + Pb and pp data sets have integrated luminosities of 0.49 nb−1 and 25 pb−1 , respectively. The measurement is performed for jets reconstructed with the anti-kt algorithm with radius parameter R = 0.4 and is extended to an angular distance of r = 0.8 from the jet axis. Results are presented as a function of Pb + Pb collision centrality and distance from the jet axis for charged particles with transverse momenta in the 1- to 63-GeV range, matched to jets with transverse momenta in the 126- to 316-GeV range and an absolute value of jet rapidity of less than 1.7. Modifications to the measured distributions are quantified by taking a ratio to the measurements in pp collisions. Yields of charged particles with transverse momenta below 4 GeV are observed to be increasingly enhanced as a function of angular distance from the jet axis, reaching a maximum at r = 0.6. Charged particles with transverse momenta above 4 GeV have an enhanced yield in Pb + Pb collisions in the jet core for angular distances up to r = 0.05 from the jet axis, with a suppression at larger distances. DOI: 10.1103/PhysRevC.100.064901 I. INTRODUCTION Complementary measurements look at how the structure of jets in Pb + Pb collisions is modified relative to that in Ultrarelativistic nuclear collisions at the Large Hadron pp collisions. Previous measurements have shown a broad- Collider (LHC) produce hot, dense matter called a quark- ening of jets in Pb + Pb [13–16], as well as an excess of gluon plasma, QGP (see Refs. [1,2] for recent reviews). Jets low- and high-momentum charged particles and a depletion from hard-scattering processes in these collisions traverse and of intermediate-momentum charged particles associated with interact with the QGP, losing energy via a process called jet these jets [17–20]. Particles carrying a large fraction of the quenching. The rates and characteristics of these jets in heavy- jet momentum are generally closely aligned with the jet axis, ion collisions can be compared with the same quantities in pp whereas low-momentum particles are observed to have a collisions, where the production of a QGP is not expected. much broader angular distribution extending outside the jet This comparison can provide information about the properties [9,21–24]. These observations suggest that the energy lost via of the QGP and how it interacts with partons from the hard jet quenching is being transferred to soft particles around the scatter. jet axis via soft gluon emission [25–31]. Measurements of Jets with large transverse momenta, pjetT , in central lead- yields of these particles as a function of transverse momen- lead (Pb + Pb) collisions at the LHC are measured at ap- tum, pT , and angular distance between the particle and the proximately half the rates in pp collisions when the nuclear jet axis have the potential to provide further insight into the overlap function of Pb + Pb collisions is taken into account structure of jets in the QGP, as well as provide information [3–7]. Similarly, back-to-back dijet [8–10] and photon-jet about how the medium is affected by the presence of the jet. pairs [11,12] are observed to have less-balanced transverse This paper presents charged-particle pT distributions at a momenta in Pb + Pb collisions compared to pp collisions. distance r around the jet axis1 that have been corrected for These observations suggest that some of the energy from the hard-scattered parton may be transferred outside of the jet through its interaction with the QGP medium. 1 ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP) in the center of the detector and the z axis along the beam pipe. The x axis points from the ∗ Full author list given at the end of the article. IP to the center of the LHC ring, and the y axis points upward. Cylindrical coordinates (r, φ) are used in the transverse plane, with Published by the American Physical Society under the terms of the φ being the azimuthal angle around the z axis. The pseudorapidity Creative Commons Attribution 4.0 International license. Further is defined in terms of the polar angle θ as η = − ln tan(θ /2). The distribution of this work must maintain attribution to the author(s) rapidity is defined as y = 0.5ln[(E + pz )/(E − pz )] where E and and the published article’s title, journal citation, and DOI. pz are the energy and z component of the momentum along the 2469-9985/2019/100(6)/064901(29) 064901-1 ©2019 CERN, for the ATLAS Collaboration G. AAD et al. PHYSICAL REVIEW C 100, 064901 (2019) detector effects. The measured yields are defined as follows: collisions, the ZDCs primarily measure spectator neutrons. 1 1 dnch (pT , r) These are neutrons that do not interact hadronically when D(pT , r) = , the incident nuclei collide. A ZDC coincidence trigger is Njet 2π rdr d pT implemented by requiring the pulse height from both ZDCs where Njet is the number of jets in consideration and nch (pT , r) to be above a threshold that accepts the signal corresponding is the number of charged particles with a given pT at a distance to the energy deposition from a single neutron. r from the jet axis. The ratios of the charged-particle yields This analysis uses the same trigger setup used in Ref. [20] measured in Pb + Pb and pp collisions, and is briefly described below. A two-level trigger system was used to select the Pb + Pb and pp collisions. The first level, D(pT , r)Pb+Pb RD(pT ,r) = , L1, is based on custom electronics, while the second level, the D(pT , r) pp high-level trigger (HLT), is based on software [35]. Minimum- quantify the modifications of the yields due to the QGP bias (MB) events were recorded using a logical OR of two medium. Furthermore, the differences between the D(pT , r) triggers: (1) a total-energy L1 trigger selecting more-central distributions in Pb + Pb and pp collisions, collisions and (2) a ZDC coincidence trigger at L1 and a veto on the total-energy trigger, with the additional requirement of D(pT , r) = D(pT , r)Pb+Pb − D(pT , r) pp , at least one track in the HLT, selecting peripheral collisions. allow the absolute differences in charged-particle yields The total-energy trigger required the total transverse energy between the two collision systems to be measured. measured in the calorimeter system to be greater than 50 GeV. Jet events were selected by the HLT, seeded by a jet identified by the L1 jet trigger in pp collisions or by the total-energy II. ATLAS DETECTOR trigger with a threshold of 50 GeV in Pb + Pb collisions. The measurements presented here are performed using the The L1 jet trigger utilized in pp collisions required a jet ATLAS [32] calorimeter, inner detector, trigger, and data- with transverse momentum greater than 20 GeV. The HLT jet acquisition systems. trigger uses a jet reconstruction procedure similar to that in The calorimeter system consists of a sampling liquid-argon the offline analysis as discussed in Sec. IV. It selected events (LAr) electromagnetic (EM) calorimeter covering |η| < 3.2, containing jets with a transverse energy of at least 75 GeV a steel-scintillator sampling hadronic calorimeter covering in Pb + Pb collisions and at least 85 GeV in pp collisions. |η| < 1.7, LAr hadronic calorimeters covering 1.5 < |η| < The measurement is performed in the jet transverse mo- 3.2, and two LAr forward calorimeters (FCal) covering 3.1 < mentum range where the trigger efficiencies are greater than |η| < 4.9. 99%. The EM calorimeters are segmented longitudinally in shower depth into three layers with an additional presampler III. DATA SETS AND EVENT SELECTION layer. They have segmentation that varies with layer and pseu- dorapidity. The hadronic calorimeters have three sampling The Pb + Pb and pp data used in this analysis were layers longitudinal in shower depth. recorded in 2015. The data samples consist of 25 pb−1 of √ √ The inner detector measures charged particles within the s = 5.02 TeV pp and 0.49 nb−1 of sNN = 5.02 TeV pseudorapidity interval |η| < 2.5 using a combination of sil- Pb + Pb data. In both samples, events are required to have icon pixel detectors, silicon microstrip detectors (SCT), and a reconstructed vertex within 150 mm of the nominal IP a straw-tube transition radiation tracker (TRT), all immersed along the beam axis. Events with multiple interactions in in a 2-T axial magnetic field. Each of the three detectors is the same bunch crossing are referred to as pileup. This is composed of a barrel and two symmetric endcap sections. negligible in the Pb + Pb data, and the pp data was collected The pixel detector is composed of four layers, including the in low-pileup mode. The average number of interactions per insertable B layer [33,34] added in 2014. The SCT barrel bunch crossing in the pp collisions ranged from 0.6 to 1.3. section contains four layers of modules with sensors on both Only events taken during stable beam conditions and satis- sides, and each endcap consists of nine layers of double- fying detector and data-quality requirements that include the sided modules with radial strips. The TRT contains layers detector subsystems being in normal operating condition are of staggered straws interleaved with the transition radiation considered. material. In Pb + Pb collisions, the event centrality reflects the over- The zero-degree calorimeters (ZDCs) are located symmet- lap area of the two colliding nuclei and is characterized by rically at z = ±140 m and cover |η| > 8.3. The ZDCs use ETFCal , the total transverse energy deposited in the FCal [36]. tungsten plates as absorbers, and quartz rods are sandwiched The six centrality intervals used in this analysis are defined between the tungsten plates as the active medium. In Pb + Pb according to successive percentiles of the ETFCal distribution obtained in MB collisions, ordered from the most-central (highest ETFCal ) to the most-peripheral (lowest ETFCal ) col- beam direction respectively. Transverse momentum and transverse lisions: 0–10%, 10–20%, 20–30%, 30–40%, 40–60%, and energy are defined as pT = p sin θ and ET = E sin θ , respectively. 60–80%. The angular distance between two objects, r, with relative differences The pp Monte Carlo (MC) sample consists of 1.8 × η  and φ in pseudorapidity and azimuth, respectively, is given by 107 5.02-TeV hard-scattering dijet pp events generated with (η)2 + (φ)2 . POWHEG+PYTHIA8 [37–41] using the A14 tune of parameter 064901-2 MEASUREMENT OF ANGULAR AND MOMENTUM … PHYSICAL REVIEW C 100, 064901 (2019) values [42] and the NNPDF23LO PDF set [43]. The Pb + Pb Charged-particle tracks in Pb + Pb collisions are recon- MC sample was generated by overlaying an additional sample structed from hits in the inner detector using the track recon- of MB Pb + Pb data events onto a separate set of 1.8 × 107 struction algorithm that was optimized for the high hit density 5.02-TeV hard-scattering dijet pp events generated with the in heavy-ion collisions [51]. Tracks used in this analysis have same tune and PDFs as the pp MC sample. This MC overlay |η| < 2.5 and are required to have at least 9 (11) total hits in sample was reweighted on an event-by-event basis such that the silicon detectors for charged particles with pseudorapidity it has the same centrality distribution as the jet-triggered |ηch |  1.65(|ηch | > 1.65). At least one hit is required in one data sample. Another sample of MB Pb + Pb events was of the two innermost pixel layers. If the track trajectory passes generated using HIJING (version 1.38b) [44] and was only through an active module in the innermost layer, then a hit in used to evaluate the track reconstruction performance. The this layer is required. Additionally, a track must have no more detector response in all MC samples was simulated using than two holes in the pixel and SCT detectors together, where GEANT4 [45,46]. These MC samples are used to evaluate a hole is defined by the absence of a hit predicted by the track the performance of the detector and analysis procedure and trajectory. All charged-particle tracks used in this analysis are correct the measured distributions for detector effects. required to have reconstructed transverse momentum pch T > 1.0 GeV. In order to suppress the contribution from secondary particles,2 the distance of closest approach of the track to IV. JET AND TRACK SELECTION the primary vertex is required to be less than a value that varies from 0.45 mm at pch T = 4 GeV to 0.2 mm at pT = ch The jet reconstruction procedure is identical to that used 20 GeV in the transverse plane and less than 1.0 mm in the in Ref. [7]. The anti-kt algorithm [47,48] is first run in four- longitudinal direction. The primary vertex is determined using momentum recombination mode on η × φ = 0.1 × 0.1 vertex finding and fitting algorithms described in Ref. [52]. calorimeter towers with two anti-kt radius parameter values The precision is better than 20 μm in the transverse plane in (R = 0.2 and R = 0.4). The energies in the towers are ob- peripheral collisions and improves inversely proportional to tained by summing the energies of calorimeter cells at the the square root of the number of reconstructed primary tracks electromagnetic energy scale. Then, an iterative procedure is in central collisions. used to estimate the η-dependent underlying event (UE) trans- The efficiency, ε, for reconstructing charged particles in verse energy density, while excluding the regions populated Pb + Pb and pp collisions is determined using the MC sam- by jets. The estimate of the UE contribution is performed ples described above. It is evaluated as a function of the on an event-by-event basis. Furthermore, the background in generator-level primary particle transverse momentum, ptruth T , Pb + Pb collisions is modulated to account for the azimuthal and pseudorapidity, ηtruth , by matching tracks to generator- anisotropy in particle production [49]. The modulation in- level primary particles [46]. In both collision systems, the cludes the contributions of the second-, third-, and fourth- efficiency increases slowly with ptruth T and is seen to be inde- order azimuthal anisotropy harmonics. The UE transverse energy is subtracted from calorimeter towers included in the pendent of pjet T in the measurement’s phase space. For Pb + Pb jet and the four-momentum of the jet is updated accordingly. collisions, the efficiency for |η| < 0.3 is ≈80% at 1 GeV and Then, a jet η- and pT -dependent correction factor to the pjet rises to ≈85% at 10 GeV. For 1.0 < |η| < 2.0, the efficiency derived from the pp MC sample is applied to correct for T is ≈67% to ≈72% over the same pT range, with the variation the calorimeter energy response [50]. The same calibration in efficiency between the most-central and most-peripheral factors are applied in both the pp and Pb + Pb collisions. Pb + Pb collisions being approximately 3% in both η ranges. An additional correction based on in situ studies of jets For pp collisions, the efficiency for |η| < 0.3 is ≈85% at recoiling against photons, Z bosons, and jets in other regions 1 GeV and rises to ≈88% at 10 GeV, remaining relatively con- of the calorimeter is applied [12]. The same jet reconstruction stant thereafter. For 1.0 < |η| < 2.0, the efficiency is ≈82% procedure without the azimuthal modulation of the UE is also to ≈86% over the same pT range. Further details about the applied to pp collisions. The UE subtraction in pp collisions tracking efficiency can be found in Ref. [19]. removes the pileup contribution to the jet. In this analysis, jets The contribution of reconstructed tracks that cannot be matched to a generated primary particle in the pp MC samples are required to have pjetT in the 126- to 316-GeV range, with is less than 2% in the entire pch T range under study in both rapidity |yjet | < 1.7. The pjet T requirement is chosen in order to the pp and Pb + Pb collisions. This contribution includes exclude the contribution of UE jets generated by fluctuations fakes and secondaries, where fakes originate from randomly in the UE, while the rapidity requirement is based on the matched hits in the detector layers that do not correspond to acceptance of the tracking system. To prevent nearby jets from the passage of charged particles. Both of these contributions distorting the measurement of D(pT , r) distributions, jets are are corrected for as described in the next section. rejected if there is a neighboring jet with higher pjet T within an angular distance of R = 1.0. This isolation requirement re- moves approximately 0.01% of jets. Additionally, generator- level jets are reconstructed by applying the anti-kt algorithm with radius parameter R = 0.4 to stable final-state particles 2 Primary particles are defined as particles with a mean lifetime from MC generators. These particles are required to have τ > 0.3 × 10−10 s either directly produced in pp interactions or from a lifetime of τ > 0.3 × 10−10 s and do not include muons, subsequent decays of particles with a shorter lifetime. All other neutrinos, and particles from pileup activity. particles are considered to be secondary. 064901-3 G. AAD et al. PHYSICAL REVIEW C 100, 064901 (2019) / dnsub 3 10 ATLAS 0−10% 10−20% 20−30% ch Pb+Pb sNN = 5.02 TeV, 0.49 nb -1 anti-kt R=0.4 dnmeas jet ch 102 126 < p T < 158 GeV 10 1 / dnsub 30− 40% 40−60% 60−80% ch 102 1.0 < p ch < 1.6 GeV 4.0 < p ch < 6.3 GeV T T dnmeas 1.6 < p ch < 2.5 GeV 6.3 < p ch < 10.0 GeV ch T T 2.5 < p ch < 4.0 GeV 10.0 < p ch < 25.1 GeV T T 10 1 0 0.2 0.4 0.6 0.8 0 0.2 0.4 0.6 0.8 0 0.2 0.4 0.6 0.8 r r r FIG. 1. Ratio of the measured charged-particle distributions to those after the subtraction of the UE, fake tracks, and secondaries as a jet function of r for different pch T intervals for pT in the range 126–158 GeV. The different panels represent the six centrality selections. V. ANALYSIS PROCEDURE two-step process: First, the MC overlay sample is used to generate ηjet versus φ jet maps of the average number of The analysis procedure is similar to that in Ref. [20], except charged particles in a given annulus around a reconstructed it is also performed differentially in r. Measured tracks are jet. This is done for charged particles without an associated considered to be associated with a reconstructed jet if their angular distance from the jet axis is less than 0.8. Their generated primary particle and as a function of pjet T , η , φ , jet jet multiplicity distribution is given by  jet , r, pT , and centrality. Here  jet is the azimuthal angle ch     between the jet and the second-order event plane 2 and d 2 nch pT , r meas ch 1 nch pch T ,r is given by  jet = φ jet − 2 .3 In the second step, the ηjet =  ch ch  , versus φ jet maps are used to construct the UE distribution in d pch T dr ε pT , η pch T r the data as a function of pjet T , η , φ ,  jet , and centrality. jet jet where nch (pch T , r) represents the number of tracks within a This distribution includes fakes and tracks from secondary given pch r range. The efficiency correction is applied T , r)/d pT dr. The T and particles and is given by d 2 nch UE+Fake (pch ch as a 1/ε(pch T , η ch ) weight on a track-by-track basis, assuming yields decrease with decreasing collision centrality, increasing pch = truth T , and increasing  2 . The subtracted distributions are then T pT . While that assumption is not strictly valid, the pch efficiency varies sufficiently slowly with ptruth T that the error given by introduced by this assumption is less than 1% and is further       corrected for by the Bayesian unfolding procedure described d 2 nch pT , r sub ch d 2 nch pT , r meas ch d 2 nch UE+Fake pch T ,r = − . later in this section. d pch T dr d pch T dr d pch T dr The measured track yields need to be corrected for the con- tributions from the UE, fake tracks, and secondary particles. Figure 1 shows the ratio of the charged-particle distributions In pp collisions, the UE contribution from hard scatterings before and after the subtraction of the UE, fake tracks, and not associated with jet production is negligible. The contri- secondaries, as a function of r for different pch T intervals butions from fake tracks and secondary charged particles are estimated from MC samples and subtracted. This procedure is similar to that applied in previous measurements [20,53]. 3 The second-order event plane angle 2 is determined on an For Pb + Pb collisions, contributions from the UE, fake event-by-event basis by a standard method using the φ variation of tracks, and secondary particles are estimated together in a transverse energy in the FCal [49]. 064901-4 MEASUREMENT OF ANGULAR AND MOMENTUM … PHYSICAL REVIEW C 100, 064901 (2019) and 126 < pjet with pT < 10 GeV in both the pp and Pb + Pb collision T < 158 GeV for six centrality selections. The largest UE contribution is for 1.0-GeV charged particles at systems. The nonclosure is taken as an additional systematic large values of r in central collisions, with the background-to- uncertainty as discussed in Sec. VI. One important effect is signal ratio being approximately 100 and slowly decreasing that adding or removing particles carrying a large fraction of with increasing pjet the jet momentum near the edge of the jet can significantly al- T . It rapidly decreases for more-peripheral collisions, larger pch ter its reconstructed momentum and direction; this instability T , and smaller r. To remove the effects of bin migration due to the jet energy contributes to the nonclosure mentioned above for particles and track momentum resolution, the subtracted d 2 nch sub /d pch with pT > 10 GeV in jets with pjetT < 200 GeV. Results are T dr distributions are corrected by a two-dimensional Bayesian un- presented only where the nonclosure in the pp MC sample is folding [54] in pch jet less than 5%. T and pT as implemented in the ROOUNFOLD package [55]. Two-dimensional unfolding is used because the calorimetric jet energy response depends on the fragmentation pattern of the jet [56]. Four-dimensional response matrices VI. SYSTEMATIC UNCERTAINTIES are created from the pp and Pb + Pb MC samples using the The following sources of systematic uncertainty are con- generator-level and reconstructed pjet T and the generator-level sidered: the jet energy scale (JES), the jet energy resolu- and reconstructed charged-particle pch T . They are corrected for tion (JER), the sensitivity of the unfolding to the prior, tracking efficiencies and are evaluated in bins of r and central- the UE contribution, the residual nonclosure of the analy- ity. The Bayesian procedure requires a choice in the number sis procedure, and tracking-related uncertainties. For each of iterations. Additional iterations reduce the sensitivity to variation accounting for a source of systematic uncertainty, the choice of prior but may amplify statistical fluctuations the D(pT , r) distributions along with their ratios and dif- in the distributions. After four iterations, the charged-particle ferences are re-evaluated. The difference between the var- distributions are found to be stable within 2–4% for both the ied and nominal distributions is used as an estimate of the Pb + Pb and pp data. A separate one-dimensional Bayesian uncertainty. unfolding is used to correct the measured pjet T spectra that are The systematic uncertainty associated with the JES in Pb + used to normalize the unfolded charged-particle distributions. Pb collisions is due to jets having a different structure and The response matrices for both the one- and two-dimensional possibly a different detector response that is not modeled by unfolding are reweighted such that the D(pT , r) and pjet T the MC simulation. It is composed of two parts: a centrality- distributions match the shapes of the corresponding quantities independent baseline component and a centrality-dependent in the reconstructed data. component. Only the centrality-independent baseline compo- An independent bin-by-bin unfolding procedure is used nent is used in pp collisions; it is determined from in situ to correct for migrations originating from the jet and track studies of the calorimeter response [50,56,57] and the relative angular resolutions. Two corresponding D(pT , r) distributions energy scale difference between the jet reconstruction proce- are evaluated in MC samples, one using generator-level jets dures in heavy-ion [57] and pp collisions [50]. The centrality- and primary particles, and the other using reconstructed jets dependent uncertainty reflects a modification of parton show- and charged particles with their reconstructed pT replaced ers by the Pb + Pb environment. It is evaluated by comparing by generator-level transverse momentum, ptruth T . The ratio of the ratio of the transverse momentum of calorimeter jets to these two MC distributions provides a correction factor which the vectorial sum of the transverse momentum of charged is then applied to the data. These factors are at the level of particles within these jet in data and MC events. More details approximately 5% with variations up to 15% for particles with on this procedure can be found in Ref. [7]. The size of the pT > 4 GeV, particularly near the edge of the jet. For 126- to centrality-dependent uncertainty in the JES reaches 0.5% in 158-GeV jets in Pb + Pb collisions, the full unfolding correc- the most-central collisions. Each component that contributes tion is 8–14% (4–7%) for 1-GeV (6-GeV) tracks, depending to the JES uncertainty is varied separately by ±1 standard on centrality. deviation for each interval in pjetT , and the response matrix The final particle-level corrected distributions, normalized is recomputed accordingly. The data are then unfolded with by the area of the annulus being studied, are defined as the modified matrices. The resulting uncertainty from the   JES increases with increasing charged-particle pT at fixed 1 1 dnch pT , r unfolded ch D(pT , r) = unfolded , pjet jet T , decreases with increasing pT , and is at the level of Njet 2π rdr d pT 2–4%. unfolded The uncertainty in the D(pT , r) distributions due to the where Njet is the unfolded number of jets in a given JER is evaluated by repeating the unfolding procedure with jet unfolded pT interval and nch is the unfolded yield of charged modified response matrices, where an additional contribution particles with a given pT matched to a jet with given pjet T , at a is added to the resolution of the reconstructed pjetT using a distance r. Gaussian smearing procedure. The smearing factor is eval- The performance of the full analysis procedure is validated uated using an in situ technique in 13-TeV pp data that in the MC samples by comparing the fully corrected charged- involves studies of dijet energy balance [58,59]. An addi- particle distributions to the generator-level distributions. Good tional uncertainty is included to account for differences be- recovery of the generator-level distributions (closure) is ob- tween the tower-based heavy-ion jet reconstruction and that served, with a variation of less than 4% for charged particles used in analyses of 13-TeV pp data [50,57]. The resulting 064901-5 G. AAD et al. PHYSICAL REVIEW C 100, 064901 (2019) δ D (p , r )pp [%] jet jet 126 < p < 158 GeV 126 < p < 158 GeV 40 T T 1.0 < p < 1.6 GeV 6.3 < p < 10.0 GeV T T T 20 0 −20 anti-k t R=0.4 JES JER pp s = 5.02 TeV, 25 pb -1 Tracking Unfolding −40 Pb+Pb s = 5.02 TeV, 0.49 nb-1 MC non-closure UE NN Total [%] jet jet 126 < p < 158 GeV 126 < p < 158 GeV 40 T T PbPb 1.0 < p < 1.6 GeV 6.3 < p < 10.0 GeV T T δ D (p , r ) 20 0−10% 0−10% T 0 −20 −40 ATLAS [%] jet jet 126 < p < 158 GeV 126 < p < 158 GeV 40 1.0 < p T < 1.6 GeV 6.3 < p T < 10.0 GeV PbPb T T 60−80% 60−80% δ D (p , r ) 20 T 0 −20 −40 0 0.2 0.4 0.6 0.8 0 0.2 0.4 0.6 0.8 r r FIG. 2. Relative size of the systematic uncertainties for D(pT , r) distributions in pp (top), central 0–10% Pb + Pb (middle), and peripheral 60–80% Pb + Pb (bottom) collisions for tracks with 1.0 < pT < 1.6 GeV (left) and 6.3 < pT < 10 GeV (right) in jets with 126 < pjet T < 158 GeV. The systematic uncertainties due to JES, JER, tracking, unfolding, MC nonclosure, and UE contribution (for Pb + Pb) are shown along with the total systematic uncertainty from all sources. uncertainty from the JER is symmetrized to account for The uncertainties related to track reconstruction and selec- negative variations of the JER. The size of the resulting un- tion originate from several sources. Uncertainties related to certainty in the D(pT , r) distributions due to the JER typically the detector material description in simulation and the track reaches 4–5% for the highest charged-particle pT intervals transverse momentum resolution are obtained from studies in and decreases to 2–3% with decreasing charged-particle pT at data and simulation described in Ref. [60]. The sensitivity fixed pjet T . of the tracking efficiency to the description of the inactive 064901-6 MEASUREMENT OF ANGULAR AND MOMENTUM … PHYSICAL REVIEW C 100, 064901 (2019) [%] jet jet 126 < p < 158 GeV 126 < p < 158 GeV 40 1.0 < p T < 1.6 GeV 6.3 < p T < 10.0 GeV ,r ) T T − 0 − 10% T 20 0 10% δR D (p 0 − 20 − 40 ATLAS [%] jet jet 126 < p < 158 GeV 126 < p < 158 GeV 40 1.0 < p T < 1.6 GeV 6.3 < p T < 10.0 GeV ,r ) T T 60− 80% 60− 80% T 20 δR D (p 0 −20 anti- k t R=0.4 JES JER pp s = 5.02 TeV, 25 pb-1 −40 Tracking Unfolding Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 MC non-closure UE 0 0.2 0.4 0.6 0.8 0 0.2 0.4 0.6 0.8 r r FIG. 3. Relative size of the systematic uncertainties for RD(pT ,r) distributions for 0–10% (top) and 60–80% (bottom) Pb + Pb collisions, for tracks with 1.0 < pT < 1.6 GeV (left) and 6.3 < pT < 10.0 GeV (right), in jets with 126 < pjet T < 158 GeV. The systematic uncertainties due to JES, JER, tracking, unfolding, MC nonclosure, and UE contribution are shown along with the total systematic uncertainty from all sources. material in the MC samples is evaluated by varying the resulting uncertainty typically varies between 1% and 2%. material description. This resulting uncertainty in the track Finally, the track-to-particle matching requirements are var- reconstruction efficiency is between 0.5% and 2% in the track ied. This variation affects the track reconstruction efficiency, pT range used in the analysis. The systematic uncertainty track momentum resolution, and rate of fake tracks. The associated with the rate of fakes and secondary tracks is 30% resulting systematic uncertainty is 0.1% for the D(pT , r) sub in both collision systems [60]. The contamination of the nch distributions. All track-related systematic uncertainties are from fakes and secondary tracks is approximately 20% in the added in quadrature and presented as the total tracking jet core for tracks with 1 < pT < 1.6 GeV. It rapidly decreases uncertainty. as a function of pT and r and is less than 2% at larger distances The systematic uncertainty associated with the UE subtrac- from the jet axis. The resulting uncertainty in the D(pT , r) tion has two components: the limited number of charged par- distributions is at most ≈7% in the jet core and decreases ticles associated with a jet without a corresponding generator as a function of pT and r. An additional uncertainty takes particle in the Pb + Pb MC overlay sample and a comparison into account a possible residual misalignment of the tracking with the result of an alternative UE estimation using the detectors in pp and Pb + Pb data collection. The resulting cone method. The cone method uses jet-triggered events to uncertainties in the D(pT , r) distributions are typically less estimate the background and is adapted from Refs. [19,20]. than 0.1%. An additional uncertainty in the tracking efficiency A regular grid of nine cones of size R = 0.8 is used to due to the high local track density in the core of jets is 0.4% cover the inner-detector region. Cones are excluded if the [61] for all pjet T ranges in this analysis. The uncertainty due angular distance to any reconstructed jet in the event with to the track selection is evaluated by repeating the analysis pjet T > 90 GeV is less than 1.6 or if they contain a charged with an additional 3σ requirement on the significance of the particle with pT > 10 GeV. This exclusion reduces biases distance of closest approach of the track to the primary vertex. from any hard processes. The resulting UE charged-particle This uncertainty affects the track reconstruction efficiencies, yields dnchUE,Cone /d pch T are evaluated over the 1- to 10-GeV track momentum resolution, and rate of fake tracks. The jet range as a function of pch T , pT , centrality, and r, and are 064901-7 G. AAD et al. PHYSICAL REVIEW C 100, 064901 (2019) D (p , r ) [GeV-1] 0−10% 10−20% 10 1 T 10−1 10−2 10−3 anti-k t R=0.4 pp s = 5.02 TeV, 25 pb-1 10−4 ATLAS jet 126 < p < 158 GeV T Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 D (p , r ) [GeV-1] 20−30% 30−40% 10 1 T 10−1 10−2 10−3 D (p , r ) [GeV-1] 10 40−60% 60−80% 1 10−1 T 10−2 pp PbPb pp PbPb 10−3 1.0 < p < 1.6 GeV 6.3 < p < 10.0 GeV 1.6 < p T < 2.5 GeV 10.0 < p T < 25.1 GeV 10−4 2.5 < p T < 4.0 GeV 25.1 < p T < 63.1 GeV T 4.0 < p T < 6.3 GeV −5 T 10 0 0.2 0.4 0.6 0.8 0 0.2 0.4 0.6 0.8 r r FIG. 4. The D(pT , r) distributions in pp (open symbols) and Pb + Pb (closed symbols) as a function of angular distance r for pjet T of 126 to 158 GeV. The symbols represent different track pT ranges, and each panel is a different centrality selection. The vertical bars on the data points indicate statistical uncertainties, while the shaded boxes indicate systematic uncertainties. The widths of the boxes are not indicative of the bin size, and the points are shifted horizontally for better visibility. The distributions for pT > 6.3 GeV are restricted to smaller r values as discussed in Sec. V. subsequently averaged over all cones. Both of these sources largest angular distances from the jet axis. It is the dominant of uncertainty are combined as uncorrelated uncertainties. The source of systematic uncertainty for low-pT charged particles combined UE uncertainty in the D(pT , r) distributions is less at large r and decreases sharply with increasing charged- than 10% for r < 0.4 and reaches a maximum of 40% at the particle pT . In particular, the component from the limited 064901-8 MEASUREMENT OF ANGULAR AND MOMENTUM … PHYSICAL REVIEW C 100, 064901 (2019) RRDD (p(p, r ), r ) R D (p , r ) T ATLAS jet 126 < p T < 158 GeV ATLAS jet 200 < p T < 251 GeV T T Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 0−10% Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 0−10% 4 pp s = 5.02 TeV, 25 pb-1 anti-kt R=0.4 4 pp s = 5.02 TeV, 25 pb-1 anti-kt R=0.4 1.0 < p < 1.6 GeV 1.6 < p < 2.5 GeV 1.0 < p < 1.6 GeV 1.6 < p < 2.5 GeV T T T T 2.5 < p < 4.0 GeV 4.0 < p < 6.3 GeV 2.5 < p < 4.0 GeV 4.0 < p < 6.3 GeV T T T T 6.3 < p < 10.0 GeV 10.0 < p < 25.1 GeV 6.3 < p < 10.0 GeV 10.0 < p < 25.1 GeV T T T T 25.1 < p < 63.1 GeV 25.1 < p < 63.1 GeV T T 2 2 0 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 R DRD(p(p ,,r )r ) R D (p , r ) ATLAS 126 < p jet < 158 GeV r ATLAS 200 < p jet < 251 GeV r T T T T T Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 30−40% Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 30−40% -1 -1 4 pp s = 5.02 TeV, 25 pb anti-kt R=0.4 4 pp s = 5.02 TeV, 25 pb anti-kt R=0.4 1.0 < p < 1.6 GeV 1.6 < p < 2.5 GeV 1.0 < p < 1.6 GeV 1.6 < p < 2.5 GeV T T T T 2.5 < p < 4.0 GeV 4.0 < p < 6.3 GeV 2.5 < p < 4.0 GeV 4.0 < p < 6.3 GeV T T T T 6.3 < p < 10.0 GeV 10.0 < p < 25.1 GeV 6.3 < p < 10.0 GeV 10.0 < p < 25.1 GeV T T T T 25.1 < p < 63.1 GeV 25.1 < p < 63.1 GeV T T 2 2 0 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 R DR(pD (p, ,rr)) R D (p , r ) ATLAS jet 126 < p T < 158 GeV r ATLAS jet 200 < p T < 251 GeV r T T T Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 60−80% Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 60−80% 4 pp s = 5.02 TeV, 25 pb-1 anti-kt R=0.4 4 pp s = 5.02 TeV, 25 pb-1 anti-kt R=0.4 1.0 < p < 1.6 GeV 1.6 < p < 2.5 GeV 1.0 < p < 1.6 GeV 1.6 < p < 2.5 GeV T T T T 2.5 < p < 4.0 GeV 4.0 < p < 6.3 GeV 2.5 < p < 4.0 GeV 4.0 < p < 6.3 GeV T T T T 6.3 < p < 10.0 GeV 10.0 < p < 25.1 GeV 6.3 < p < 10.0 GeV 10.0 < p < 25.1 GeV T T T T 25.1 < p < 63.1 GeV 25.1 < p < 63.1 GeV T T 2 2 0 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 r r FIG. 5. Ratios of D(pT , r) distributions in Pb + Pb and pp collisions as a function of angular distance r for 126 < pjet T < 158 GeV (left) and 200 < pjet T < 251 GeV (right) for seven pT selections. Different centrality selections are shown: 0–10% (top), 30–40% (middle), and 60–80% (bottom). The vertical bars on the data points indicate statistical uncertainties, while the shaded boxes indicate systematic uncertainties. The widths of the boxes are not indicative of the bin size, and the points are shifted horizontally for better visibility. sample size dominates in the most-central collisions, while the of the charged-particle and jet distributions in data. The 5–7% component from the alternative estimation method dominates difference between the nominal D(pT , r) distribution and that elsewhere. unfolded with the unreweighted response matrix is taken as The systematic uncertainty in the unfolding procedure the systematic uncertainty. is estimated by generating response matrices from the MC An additional uncertainty to account for possible residual distributions without the reweighting that matched the shapes limitations in the analysis procedure is assigned by evaluating 064901-9 G. AAD et al. PHYSICAL REVIEW C 100, 064901 (2019) R D (p , r ) R D (p , r ) p p p p ATLAS T,1 T,2 ATLAS T,1 T,2 T T -1 0−10% -1 0−10% Pb+Pb sNN = 5.02 TeV, 0.49 nb 10−20% Pb+Pb sNN = 5.02 TeV, 0.49 nb 10−20% pp s = 5.02 TeV, 25 pb-1 20−30% pp s = 5.02 TeV, 25 pb-1 20−30% 4 200 < p jet < 251 GeV 30−40% 4 126 < p jet < 158 GeV 30−40% T T anti-kt R=0.4 40−60% anti-kt R=0.4 40−60% 1.6 < p < 2.5 GeV 60−80% 1.6 < p < 2.5 GeV 60−80% T,1 T,1 6.3 < p T,2 < 10.0 GeV 6.3 < p T,2 < 10.0 GeV 2 2 0 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 r r FIG. 6. The RD(pT ,r) distributions for pjet T of 126–158 GeV (left) and 200–251 GeV (right) as a function of angular distance r for two pT selections, 1.6–2.5 GeV (closed symbols) and 6.3–10.0 GeV (open symbols), and six centrality intervals. The vertical bars on the data points indicate statistical uncertainties, while the shaded boxes indicate systematic uncertainties. The widths of the boxes are not indicative of the bin size, and the points are shifted horizontally for better visibility. the nonclosure of the unfolded distributions in simulations. the jet axis. The rate of fall-off increases sharply for higher pT This is typically about 4%. particles, with most of these being concentrated near the jet The correlations between the various systematic compo- axis. The distributions exhibit a difference in shape between nents are considered in evaluating the RD(pT ,r) and D(pT , r) Pb + Pb and pp collisions, with the Pb + Pb distributions distributions. The unfolding and nonclosure uncertainties are being broader at low pT (pT < 4 GeV) and narrower at high pT taken to be uncorrelated between pp and Pb + Pb collisions, (pT > 4 GeV) in 0–10% central collisions. This modification while all others are taken to be correlated. For these, the is centrality dependent and is smaller for peripheral Pb + Pb RD(pT ,r) and D(pT , r) distributions are re-evaluated by ap- collisions. plying the variation to both collision systems; the resulting variations of the ratios from their central values are used as B. RD(pT ,r) distributions the correlated systematic uncertainty. Examples of systematic uncertainties in the D(pT , r) dis- In order to quantify the differences seen in Fig. 4, ratios of the D(pT , r) distributions in Pb + Pb collisions to those tributions for jets in the 126- to 158-GeV pjetT range measured in pp and Pb + Pb collision systems are shown in Fig. 2. The measured in pp collisions for 126 < pjet T < 158 GeV and uncertainties in the RD(pT ,r) distributions are shown in Fig. 3. 200 < pjetT < 251 GeV jets are presented in Fig. 5. They It can be seen that the dominant systematic uncertainty in the are shown as a function of r for different pT and centrality Pb + Pb and the RD(pT ,r) distributions is from the UE subtrac- selections. In 0–10% central collisions, RD(pT ,r) is greater tion. While it is less than 5% for r < 0.3, it is approximately than unity for r < 0.8 for charged particles with pT less 40% for charged particles with pT = 1 GeV at r = 0.8. The than 4.0 GeV for both pjet T selections. For these particles, uncertainties in the pp system are smaller, with the dominant the enhancement of yields in Pb + Pb collisions compared systematic uncertainty at low pT due to the tracking. This is to those in pp collisions grows with increasing r up to approximately 10% for r < 0.1 and decreases to less than 5% approximately r = 0.3, with RD(pT ,r) reaching values up at larger distances. to two for 1.0 < pT < 2.5 GeV. The value of RD(pT ,r) is approximately constant for r in the interval 0.3–0.6 and de- creases for r > 0.6. For charged particles with pT > 4.0 GeV, VII. RESULTS RD(pT ,r) shows a depletion outside the jet core for r > 0.05. The D(pT , r) distributions are studied as a function of pjet T The magnitude of this depletion increases with increasing for pp data and Pb + Pb collisions with different centralities. r up to r = 0.3 and is approximately constant thereafter. The interplay between the hot and dense matter and the parton For 30–40% midcentral collisions, the enhancement in the shower is explored by evaluating the ratios and differences yield of particles with pT < 4.0 GeV has trends similar to between the D(pT , r) distributions in Pb + Pb and pp colli- those in the most central collisions, but the depletion of sions. Some selected moments of these distributions are also particles with pT > 4.0 GeV is not as strong. For 60–80% investigated. peripheral collisions, RD(pT ,r) has no significant r dependence and the values of RD(pT ,r) are within approximately 50% of unity. A. D(pT , r) distributions The observed behavior inside the jet cone, r < 0.4, agrees The D(pT , r) distributions evaluated in pp and Pb + Pb with the measurement of the inclusive jet fragmentation func- collisions for 126 < pjet T < 158 GeV are shown in Fig. 4. tions [10,19,20], where yields of fragments with pT < 4 GeV These distributions decrease as a function of distance from are observed to be enhanced and yields of charged particles 064901-10 MEASUREMENT OF ANGULAR AND MOMENTUM … PHYSICAL REVIEW C 100, 064901 (2019) R D (p , r ) R D (p , r ) jet 126 < p T < 158 GeV ATLAS jet 200 < p T < 251 GeV ATLAS T T 3 0−10% Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 3 0−10% Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 pp s = 5.02 TeV, 25 pb-1 pp s = 5.02 TeV, 25 pb-1 0.00 < r < 0.05 anti-kt R=0.4 0.00 < r < 0.05 anti-kt R=0.4 0.15 < r < 0.20 0.15 < r < 0.20 2 0.30 < r < 0.40 2 0.30 < r < 0.40 0.50 < r < 0.60 0.50 < r < 0.60 1 1 0 0 1 10 1 10 R D (p , r ) R D (p , r ) jet 126 < p < 158 GeV p trk [GeV] ATLAS jet 200 < p < 251 GeV ATLAS trk p [GeV] T T T T T T 3 30−40% Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 3 30−40% Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 pp s = 5.02 TeV, 25 pb-1 pp s = 5.02 TeV, 25 pb-1 0.00 < r < 0.05 anti-kt R=0.4 0.00 < r < 0.05 anti-kt R=0.4 0.15 < r < 0.20 0.15 < r < 0.20 2 0.30 < r < 0.40 2 0.30 < r < 0.40 0.50 < r < 0.60 0.50 < r < 0.60 1 1 0 0 1 10 1 10 R D (p , r ) R D (p , r ) trk trk jet 126 < p T < 158 GeV ATLAS p [GeV] jet 200 < p T < 251 GeV ATLAS p [GeV] T T 3 T 3 T 60−80% Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 60−80% Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 -1 pp s = 5.02 TeV, 25 pb pp s = 5.02 TeV, 25 pb-1 0.00 < r < 0.05 anti-kt R=0.4 0.00 < r < 0.05 anti-kt R=0.4 0.15 < r < 0.20 0.15 < r < 0.20 2 0.30 < r < 0.40 2 0.30 < r < 0.40 0.50 < r < 0.60 0.50 < r < 0.60 1 1 0 0 1 10 1 10 p trk [GeV] p trk [GeV] T T FIG. 7. RD(pT ,r) as a function of pT for 0–10% (top), 30–40% (middle), and 60–80% (bottom) Pb + Pb collisions in two different pjet T selections: 126–158 GeV (left) and 200–251 GeV (right). The different colors indicate different angular distances from the jet axis. The vertical bars on the data points indicate statistical uncertainties, while the shaded boxes indicate systematic uncertainties. The widths of the boxes are not indicative of the bin size, and the points are shifted horizontally for better visibility. with intermediate pT are suppressed in Pb + Pb collisions response of the medium is smaller than that predicted in compared to those in pp collisions. The wake left in the Ref. [31]. medium from the passage of the jet compensates for some of The centrality dependence of RD(pT ,r) for two charged- the energy it loses [30,31]. The plateau and slight decrease particle pT intervals (1.6–2.5 GeV and 6.3–10.0 GeV) and seen in Fig. 5 for the RD(pT ,r) distributions in central Pb + Pb two different pjet T ranges (126–158 GeV and 200–251 GeV) collisions beyond r = 0.6 from the jet axis suggests that this is presented in Fig. 6. For both pjet T selections, the magnitude 064901-11 G. AAD et al. PHYSICAL REVIEW C 100, 064901 (2019) 6 of the excess for 1.6–2.5 GeV charged particles increases R D (p , r ) ATLAS 0−10% for more-central events and for r < 0.3. The magnitude of T Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 the excess is approximately a factor of 2 in the most-central pp s = 5.02 TeV, 25 pb-1 p T,1 p T,2 jet collisions for r > 0.3. A continuous centrality-dependent sup- 126 < p < 158 GeV anti-kt R=0.4 T jet pression of yields of charged particles with 6.3 < pT < 10.0 4 1.6 < p < 2.5 GeV 158 < p < 200 GeV T T,1 jet 200 < p < 251 GeV GeV is observed. The magnitude of the modification decreases 6.3 < p < 10.0 GeV for more-peripheral collisions in both pT intervals and pjet T jet T,2 251 < p < 316 GeV T T selections. Figure 7 shows the charged-particle pT dependence of 2 RD(pT ,r) for selections in r for jets at 126–158 GeV and 200–251 GeV in the following centrality intervals: 0–10%, 30–40%, and 60–80%. Interestingly, there is no significant suppression of the yields in Pb + Pb collisions for r < 0.05 at 0 all measured pT . For larger r values, the yields are enhanced 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 for charged particles with pT < 4 GeV and suppressed for r higher-pT charged particles in both the 0–10% and 30–40% FIG. 8. RD(pT ,r) as a function of r for 0–10% central collisions centrality selections and both pjet T ranges presented here. The for charged particles with 1.6 < pT < 2.5 GeV (closed symbols) and magnitude of the enhancement increases for decreasing pT 6.3 < pT <10.0 GeV (open symbols) for different pjet T selections. The below 4 GeV while the suppression is enhanced with in- vertical bars on the data points indicate statistical uncertainties, while creasing pT for 4–10 GeV, after which it is approximately the shaded boxes indicate systematic uncertainties. The widths of the constant. At fixed pT the magnitude of the deviation from boxes are not indicative of the bin size, and the points are shifted unity increases for larger distances from the jet axis. In the horizontally for better visibility. Δ D (p , r ) [GeV-1] Δ D (p , r ) [GeV-1] 15 ATLAS 126 < p T < 158 GeV jet 15 ATLAS jet 158 < p T < 200 GeV Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 0−10% Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 0−10% pp s = 5.02 TeV, 25 pb-1 1.0 < p < 1.6 GeV pp s = 5.02 TeV, 25 pb-1 1.0 < p < 1.6 GeV T T anti-kt R=0.4 1.6 < p < 2.5 GeV anti-kt R=0.4 1.6 < p < 2.5 GeV T T 10 T 2.5 < p < 4.0 GeV 10 T 2.5 < p < 4.0 GeV T T 4.0 < p < 6.3 GeV 4.0 < p < 6.3 GeV T T 6.3 < p < 10.0 GeV 6.3 < p < 10.0 GeV T T 10.0 < p < 25.1 GeV 10.0 < p < 25.1 GeV 5 T 5 T 25.1 < p < 63.1 GeV 25.1 < p < 63.1 GeV T T 0 0 0 0.1 0.2 0.3 0.4 0.5 0.60.8 0 0.7 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Δ D (p , r ) [GeV-1] Δ D (p , r ) [GeV-1] 15 ATLAS jet 200 < p T < 251 GeV r 15 ATLAS jet 251 < p T < 316 GeV r Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 0−10% Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 0−10% pp s = 5.02 TeV, 25 pb-1 1.0 < p < 1.6 GeV pp s = 5.02 TeV, 25 pb-1 1.0 < p < 1.6 GeV T T anti-kt R=0.4 1.6 < p < 2.5 GeV anti-kt R=0.4 1.6 < p < 2.5 GeV T T 10 T 2.5 < p < 4.0 GeV 10 T 2.5 < p < 4.0 GeV T T 4.0 < p < 6.3 GeV 4.0 < p < 6.3 GeV T T 6.3 < p < 10.0 GeV 6.3 < p < 10.0 GeV T T 10.0 < p < 25.1 GeV 10.0 < p < 25.1 GeV 5 T 5 T 25.1 < p < 63.1 GeV 25.1 < p < 63.1 GeV T T 0 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 r r FIG. 9. D(pT , r) as a function of r in central collisions for all pT ranges in four pjet T selections: 126–158, 158–200, 200–251, and 251–316 GeV. The vertical bars on the data points indicate statistical uncertainties, while the shaded boxes indicate systematic uncertainties. The widths of the boxes are not indicative of the bin size, and the points are shifted horizontally for better visibility. 064901-12 MEASUREMENT OF ANGULAR AND MOMENTUM … PHYSICAL REVIEW C 100, 064901 (2019) 6 6 Δ Θ ( r) Δ Θ ( r) ATLAS 0−10% ATLAS 30−40% Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 pp s = 5.02 TeV, 25 pb-1 anti-k t R=0.4 pp s = 5.02 TeV, 25 pb-1 anti-k t R=0.4 4 126 < p jet < 158 GeV 4 126 < p jet < 158 GeV T T jet jet 158 < p < 200 GeV 158 < p < 200 GeV T T jet jet 200 < p < 251 GeV 200 < p < 251 GeV 2 T 2 T jet jet 251 < p < 316 GeV 251 < p < 316 GeV T T 0 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 r r 6 Δ Θ ( r) ATLAS 60−80% Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 pp s = 5.02 TeV, 25 pb-1 anti-k t R=0.4 4 126 < p jet < 158 GeV T jet 158 < p < 200 GeV T jet 200 < p < 251 GeV 2 T jet 251 < p < 316 GeV T 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 r FIG. 10.  (r) as a function of r for charged particles with pT < 4 GeV in four pjet T selections, 126–158, 158–200, 200–251, and 251– 316 GeV, and three centrality selections, 0–10% (top left), 30–40% (top right), and 60–80% (bottom). The vertical bars on the data points indicate statistical uncertainties, while the shaded boxes indicate systematic uncertainties. The widths of the boxes are not indicative of the bin size, and the points are shifted horizontally for better visibility. 60–80% peripheral collisions, the same trend is seen (but particle distribution around the jet direction for particles with with smaller-magnitude modifications) for 126 < pjet T < 158 pT > 4.0 GeV observed here. GeV; for the higher-pjet selection, the larger uncertainties The RD(pT ,r) distributions for low- and high-pT particles T do not allow a clear conclusion to be drawn for peripheral in the different pjet T selections are directly overlaid in Fig. 8. collisions. These distributions are for the 0–10% most-central collisions The enhancement of the charged-particle yield in the kine- and show a hint of enhancement in RD(pT ,r) with increasing pjet T matic region of pT < 4 GeV has two possible explanations. for r < 0.25 for low-pT charged particles. No significant pjet T First, gluon radiation from the hard-scattered parton as it dependence is seen at larger r values or for high-pT charged propagates through the QGP would lead to extra soft particles particles at any r. This pjet T dependence is further explored by [62,63]. Second, the interactions of a jet with the QGP and defining an integral over the low-pT excess and is discussed in its hydrodynamic response could induce a wake that manifests Sec. VII D. itself as an enhancement in the number of low-pT particles [31]. The observed modification at pT > 4 GeV can be ex- C. D(pT , r) distributions plained on the basis of the larger expected energy loss of In addition to the ratios of the D(pT , r) distributions, gluon-initiated jets, resulting in a relative enhancement in the differences between the unfolded charged-particle yields are number of quark jets in Pb + Pb collisions compared to pp also evaluated as D(pT , r) to quantify the modification in collisions at a given pjet T value [20,64]. Since gluon jets have a terms of the particle density. broader distribution of particle momentum transverse to the jet These differences are presented as a function of r for direction compared to quark-initiated jets [65], the enhanced different pT selections in 0–10% central collisions in Fig. 9. quark-jet contribution could describe the narrowing of the These distributions show an excess in the charged-particle 064901-13 G. AAD et al. PHYSICAL REVIEW C 100, 064901 (2019) R Θ (Θr()r) R P( r) R P( r) jet jet 126 < p T < 158 GeV 0−10% 126 < p T < 158 GeV 0−10% R 158 < p jet < 200 GeV 2 158 < p jet < 200 GeV T T 3 200 < p jet < 251 GeV 200 < p jet < 251 GeV T T jet jet 251 < p < 316 GeV 251 < p < 316 GeV T T 1.5 2 1 1 ATLAS ATLAS Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 pp s = 5.02 TeV, 25 pb-1 anti-k t R=0.4 pp s = 5.02 TeV, 25 pb-1 anti-k t R=0.4 0 0.5 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 R ΘΘ( (rr)) R P( r) R P( r) jet jet 126 < p T < 158 GeV 30−40% r 126 < p T < 158 GeV 30−40% r R 158 < p jet < 200 GeV 2 158 < p jet < 200 GeV T T 3 200 < p jet < 251 GeV 200 < p jet < 251 GeV T T jet jet 251 < p < 316 GeV 251 < p < 316 GeV T T 1.5 2 1 1 ATLAS ATLAS Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 pp s = 5.02 TeV, 25 pb-1 anti-k t R=0.4 pp s = 5.02 TeV, 25 pb-1 anti-k t R=0.4 0 0.5 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 R ΘΘ ((rr) ) R P( r) R P( r) jet jet 126 < p T < 158 GeV 60−80% r 126 < p T < 158 GeV 60−80% r R 158 < p jet < 200 GeV 2 158 < p jet < 200 GeV T T 3 200 < p jet < 251 GeV 200 < p jet < 251 GeV T T jet jet 251 < p < 316 GeV 251 < p < 316 GeV T T 1.5 2 1 1 ATLAS ATLAS Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 Pb+Pb sNN = 5.02 TeV, 0.49 nb-1 pp s = 5.02 TeV, 25 pb-1 anti-k t R=0.4 pp s = 5.02 TeV, 25 pb-1 anti-k t R=0.4 0 0.5 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 r r FIG. 11. R (r) (left) and RP(r) (right) as a function of r for charged particles with pT < 4 GeV ranges in four pjet T selections, 126–158, 158–200, 200–251, and 251–316 GeV, and three centrality selections, 0–10% (top), 30–40% (middle), and 60–80% (bottom). The vertical bars on the data points indicate statistical uncertainties, while the shaded boxes indicate systematic uncertainties. The widths of the boxes are not indicative of the bin size, and the points are shifted horizontally for better visibility. yield density for Pb + Pb collisions compared to pp collisions higher-pT particles of up to approximately 0.5 particles per for charged particles with pT < 4.0 GeV. This ranges from unit area per GeV is seen for 126- to 158-GeV jets in 0–10% 0.5 to 4 particles per unit area per GeV for charged particles central Pb + Pb collisions. The magnitude of this depletion with 1 < pT < 1.6 GeV in jets with 126 < pjet T < 158 GeV increases for higher pjet T . A minimum in the D(pT , r) for 0–10% central Pb + Pb collisions and increases with distributions for charged particles with 4.0 < pT < 25.1 increasing pjet T . The largest excess for charged particles with GeV at 0.05 < r < 0.10 is observed. The magnitudes of the pT < 4.0 GeV is within the jet cone. For large r values, the excesses and deficits discussed here depend on the selected difference decreases but remains positive. A depletion for charged-particle pT . 064901-14 MEASUREMENT OF ANGULAR AND MOMENTUM … PHYSICAL REVIEW C 100, 064901 (2019) D. pT integrated distributions VIII. SUMMARY Motivated by similar studies of the enhancement of soft This paper presents a measurement of the yields of charged fragments in jet fragmentation functions in Pb + Pb com- particles, D(pT , r), inside and around R = 0.4 anti-kt jets with pared to pp collisions from Ref. [20], the unfolded D(pT , r) |yjet | < 1.7 up to an angular distance of r = 0.8 from the distributions are integrated for charged particles with pT < 4 jet axis, using the ATLAS detector at the LHC. The yields GeV to construct the quantities (r) and P(r) defined as are measured in intervals of pjet from 126 to 316 GeV in √T  4 GeV Pb + Pb and pp collisions at sNN = 5.02 TeV as a function (r) = D(pT , r)d pT , of charged-particle pT and the angular distance r between 1 GeV the jet axis and charged particle. The integrated luminosities  r 4 GeV of the Pb + Pb and pp data sets are 0.49 nb−1 and 25 pb−1 , P(r) = D(pT , r  )d pT dr  . respectively. 0 1 GeV The measurements show a broadening of the D(pT , r) dis- tribution for low-pT particles inside the jet in central Pb + Pb The (r) values are integrated over the charged-particle pT collisions compared to those in pp collisions, while for higher- interval of 1–4 GeV to provide a concise look at the pT region pT particles the angular distributions are narrower in Pb + Pb of enhancement discussed above. The P(r) values further add collisions than in pp collisions. These modifications are cen- a running integral over r and provide information about the jet trality dependent and decrease for more-peripheral collisions. shape. Both of these quantities are compared between the pp The Pb + Pb-to-pp ratio of the D(pT , r) distributions, RD(pT ,r) , and Pb + Pb systems to give the following distributions: is also examined. The RD(pT ,r) distributions for charged particles with pT < 4 GeV are above unity and grow with  (r ) = (r)Pb+Pb − (r) pp , increasing angular separation up to r ∼ 0.3, showing weak (r)Pb+Pb to no dependence on r in the interval 0.3 < r < 0.6 followed R (r ) = , (r) pp with a small decrease in the enhancement for 0.6 < r < 0.8. For charged particles with pT > 4 GeV, a suppression in P(r)Pb+Pb RP(r ) = . RD(pT ,r) is observed and the size of the modification increases P(r) pp with increasing r for 0.05 < r < 0.3 with no r dependence for r > 0.3. For all charged-particle pT values, the RD(pT ,r) values These integrated quantities are intended to provide aggregate are greater than or equal to unity for r < 0.05. Between information about the variation with angular distance from 0.1 < r < 0.25, a statistically significant trend of increasing the jet axis, magnitude, and pjet T dependence of the low-pT RD(pT ,r) with increasing pjet T is observed for low-pT particles. charged-particle excess discussed above. The ratio quantities jet No significant pT dependence is seen for particles with pT > are useful for comparisons with other Pb + Pb measurements 4 GeV.  (r ) is comparable to D(pT , r), but it is integrated over This measurement provides information about the modifi- charged-particle pT in the 1- to 4-GeV interval [20]. cation of the jet at large distances from the jet axis that can Figure 10 shows the  (r) distributions as a function be used to constrain models of how the jet is modified by the of r for the following centrality intervals: 0–10%, 30–40%, presence of the quark-gluon plasma and how the quark-gluon and 60–80%. In the most-central collisions, a significant pjet T plasma responds to the jet. dependence of  (r) is observed; for r < 0.4 (particles within the jet cone)  (r) increases with increasing pjet T . The value of ACKNOWLEDGMENTS  (r) decreases in more-peripheral collisions, where its pjet T dependence is also no longer significant. We thank CERN for the very successful operation of the Figure 11 shows the R (r) and RP(r) distributions as a LHC. We acknowledge the support of ANPCyT, Argentina; function of r for the 0–10%, 30–40%, and 60–80% centrality YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Aus- intervals. The R (r) distributions in the most-central collisions tria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, show a maximum for r ∼ 0.4 and a flattening or a decrease for Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, larger r. However, since R (r) remains at or above unity for the Chile; CAS, MOST, and NSFC, China; COLCIENCIAS, full range of r values presented, RP(r) shows no suppression Colombia; MSMT CR, MPO CR, and VSC CR, Czech Re- with increasing r over the entire measured range. A significant public; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA- pjet T dependence is seen in the RP(r) distributions for the most- DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF, and central Pb + Pb collisions. A slow increase in RP(r) is clearly MPG, Germany; GSRT, Greece; RGC, Hong Kong SAR, observed in 30–40% central collisions. In more-peripheral China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT collisions, the magnitude of the excess is reduced and the and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; trends in R (r) are less clear, although RP(r) is still seen to RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; be above unity. The flattening of the RP(r) distributions at MNE/IFA, Romania; MES of Russia and NRC KI, Russian large distances suggests that while wider jets have a softer Federation; JINR; MESTD, Serbia; MSSR, Slovakia; ARRS fragmentation and contain more particles with less pT in and MIZŠ, Slovenia; DST/NRF, South Africa; MINECO, Pb + Pb collisions than in pp collisions [66,67], this effect Spain; SRC and Wallenberg Foundation, Sweden; SERI, plateaus for jets with radius larger than 0.6. SNSF, and Cantons of Bern and Geneva, Switzerland; MOST, 064901-15 G. AAD et al. PHYSICAL REVIEW C 100, 064901 (2019) Taiwan; TAEK, Turkey; STFC, United Kingdom; and DOE and the Royal Society and Leverhulme Trust, United King- and NSF, United States of America. In addition, individual dom. 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Zeng,173 O. Zenin,123 T. Ženiš,28a D. Zerwas,132 M. Zgubič,135 B. Zhang,15c D. F. Zhang,15b G. Zhang,15b H. Zhang,15c J. Zhang,6 L. Zhang,15c L. Zhang,60a M. Zhang,173 R. Zhang,24 X. Zhang,60b Y. Zhang,15a,15d Z. Zhang,63a Z. Zhang,132 P. Zhao,49 Y. Zhao,60b Z. Zhao,60a A. Zhemchugov,79 Z. Zheng,105 D. Zhong,173 B. Zhou,105 C. Zhou,181 M. S. Zhou,15a,15d M. Zhou,155 N. Zhou,60c Y. Zhou,7 C. G. Zhu,60b C. Zhu,15a H. L. Zhu,60a H. Zhu,15a J. Zhu,105 Y. Zhu,60a X. Zhuang,15a K. Zhukov,110 V. Zhulanov,122b,122a D. Zieminska,65 N. I. Zimine,79 S. Zimmermann,52 Z. Zinonos,115 M. Ziolkowski,151 L. Živković,16 G. Zobernig,181 A. Zoccoli,23b,23a K. Zoch,53 T. G. Zorbas,149 R. Zou,37 and L. Zwalinski36 (ATLAS Collaboration) 1 Department of Physics, University of Adelaide, Adelaide, Australia 2 Physics Department, SUNY Albany, Albany, New York, USA 3 Department of Physics, University of Alberta, Edmonton, Alberta, Canada 4a Department of Physics, Ankara University, Ankara, Turkey 4b Istanbul Aydin University, Istanbul, Turkey 064901-24 MEASUREMENT OF ANGULAR AND MOMENTUM … PHYSICAL REVIEW C 100, 064901 (2019) 4c Division of Physics, TOBB University of Economics and Technology, Ankara, Turkey 5 LAPP, Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS/IN2P3, Annecy, France 6 High Energy Physics Division, Argonne National Laboratory, Argonne, Illinois, USA 7 Department of Physics, University of Arizona, Tucson, Arizona, USA 8 Department of Physics, University of Texas at Arlington, Arlington, Texas, USA 9 Physics 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, Texas, USA 12a Bahcesehir University, Faculty of Engineering and Natural Sciences, Istanbul, Turkey 12b Istanbul Bilgi University, Faculty of Engineering and Natural Sciences, Istanbul, Turkey 12c Department of Physics, Bogazici University, Istanbul, Turkey 12d Department of Physics Engineering, Gaziantep University, Gaziantep, Turkey 13 Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan 14 Institut de Física d’Altes Energies (IFAE), Barcelona Institute of Science and Technology, Barcelona, Spain 15a Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China 15b Physics Department, Tsinghua University, Beijing, China 15c Department of Physics, Nanjing University, Nanjing, China 15d University of Chinese Academy of Science (UCAS), Beijing, China 16 Institute of Physics, University of Belgrade, Belgrade, Serbia 17 Department for Physics and Technology, University of Bergen, Bergen, Norway 18 Physics Division, Lawrence Berkeley National Laboratory and University of California, Berkeley, California, USA 19 Institut für Physik, Humboldt Universität zu Berlin, Berlin, Germany 20 Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics, University of Bern, Bern, Switzerland 21 School of Physics and Astronomy, University of Birmingham, Birmingham, United Kingdom 22 Facultad de Ciencias y Centro de Investigaciónes, Universidad Antonio Nariño, Bogota, Colombia 23a INFN Bologna and Universita’ di Bologna, Dipartimento di Fisica, Bologna, Italy 23b INFN Sezione di Bologna, Bologna, Italy 24 Physikalisches Institut, Universität Bonn, Bonn, Germany 25 Department of Physics, Boston University, Boston, Massachusetts, USA 26 Department of Physics, Brandeis University, Waltham, Massachusetts, USA 27a Transilvania University of Brasov, Brasov, Romania 27b Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest, Romania 27c Department of Physics, Alexandru Ioan Cuza University of Iasi, Iasi, Romania 27d National Institute for Research and Development of Isotopic and Molecular Technologies, Physics Department, Cluj-Napoca, Romania 27e University Politehnica Bucharest, Bucharest, Romania 27f West University in Timisoara, Timisoara, Romania 28a Faculty of Mathematics, Physics and Informatics, Comenius University, Bratislava, Slovac Republic 28b Department of Subnuclear Physics, Institute of Experimental Physics of the Slovak Academy of Sciences, Kosice, Slovak Republic 29 Physics Department, Brookhaven National Laboratory, Upton, New York, USA 30 Departamento de Física, Universidad de Buenos Aires, Buenos Aires, Argentina 31 California State University, California, USA 32 Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom 33a Department of Physics, University of Cape Town, Cape Town, South Africa 33b Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg, South Africa 33c School of Physics, University of the Witwatersrand, Johannesburg, South Africa 34 Department of Physics, Carleton University, Ottawa, Ontario, Canada 35a Faculté des Sciences Ain Chock, Réseau Universitaire de Physique des Hautes Energies-Université Hassan II, Casablanca, Morocco 35b Faculté des Sciences, Université Ibn-Tofail, Kénitra, Morocco 35c Faculté des Sciences Semlalia, Université Cadi Ayyad, LPHEA-Marrakech, Morocco 35d Faculté des Sciences, Université Mohamed Premier and LPTPM, Oujda, Morocco 35e Faculté des sciences, Université Mohammed V, Rabat, Morocco 36 CERN, Geneva, Switzerland 37 Enrico Fermi Institute, University of Chicago, Chicago, Illinois, USA 38 LPC, Université Clermont Auvergne, CNRS/IN2P3, Clermont-Ferrand, France 39 Nevis Laboratory, Columbia University, Irvington, New York, USA 40 Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark 41a Dipartimento di Fisica, Università della Calabria, Rende, Italy 41b INFN Gruppo Collegato di Cosenza, Laboratori Nazionali di Frascati, Italy 42 Physics Department, Southern Methodist University, Dallas, Texas, USA 064901-25 G. AAD et al. PHYSICAL REVIEW C 100, 064901 (2019) 43 Physics Department, University of Texas at Dallas, Richardson, Texas, USA 44 National Centre for Scientific Research “Demokritos”, Agia Paraskevi, Greece 45a Department of Physics, Stockholm University, Stockholm, Sweden 45b Oskar Klein Centre, Stockholm, Sweden 46 Deutsches Elektronen-Synchrotron DESY, Hamburg and Zeuthen, Germany 47 Lehrstuhl für Experimentelle Physik IV, Technische Universität Dortmund, Dortmund, Germany 48 Institut für Kern- und Teilchenphysik, Technische Universität Dresden, Dresden, Germany 49 Department of Physics, Duke University, Durham, North Carolina, USA 50 SUPA (School of Physics and Astronomy), University of Edinburgh, Edinburgh, United Kingdom 51 INFN e Laboratori Nazionali di Frascati, Frascati, Italy 52 Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany 53 II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen, Germany 54 Département de Physique Nucléaire et Corpusculaire, Université de Genève, Geneva, Switzerland 55a Dipartimento di Fisica, Università di Genova, Genova, Italy 55b INFN Sezione di Genova, Italy 56 II. Physikalisches Institut, Justus-Liebig-Universität Giessen, Giessen, Germany 57 SUPA (School of Physics and Astronomy), University of Glasgow, Glasgow, United Kingdom 58 LPSC, Université Grenoble Alpes, CNRS/IN2P3, Grenoble INP, Grenoble, France 59 Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge, Massachusetts, USA 60a Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei, China 60b Institute of Frontier and Interdisciplinary Science and Key Laboratory of Particle Physics and Particle Irradiation (MOE), Shandong University, Qingdao, China 60c School of Physics and Astronomy, Shanghai Jiao Tong University, KLPPAC-MoE, SKLPPC, Shanghai, China 60d Tsung-Dao Lee Institute, Shanghai, China 61a Kirchhoff-Institut für Physik, Ruprecht-Karls-Universität Heidelberg, Heidelberg, Germany 61b Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg, Germany 62 Faculty of Applied Information Science, Hiroshima Institute of Technology, Hiroshima Japan 63a Department of Physics, Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China 63b Department of Physics, University of Hong Kong, Hong Kong, China 63c Department of Physics and Institute for Advanced Study, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China 64 Department of Physics, National Tsing Hua University, Hsinchu, Taiwan 65 Department of Physics, Indiana University, Bloomington, Indiana, USA 66a INFN Gruppo Collegato di Udine, Sezione di Trieste, Udine, Italy 66b ICTP, Trieste, Italy 66c Dipartimento Politecnico di Ingegneria e Architettura, Università di Udine, Udine, Italy 67a INFN Sezione di Lecce, Lecce, Italy 67b Dipartimento di Matematica e Fisica, Università del Salento, Lecce, Italy 68a INFN Sezione di Milano, Milan, Italy 68b Dipartimento di Fisica, Università di Milano, Milan, Italy 69a INFN Sezione di Napoli, Napoli, Italy 69b Dipartimento di Fisica, Università di Napoli, Napoli, Italy 70a INFN Sezione di Pavia, Pavia, Italy 70b Dipartimento di Fisica, Università di Pavia, Pavia, Italy 71a INFN Sezione di Pisa, Pisa, Italy 71b Dipartimento di Fisica E. Fermi, Università di Pisa, Pisa, Italy 72a INFN Sezione di Roma, Rome, Italy 72b Dipartimento di Fisica, Sapienza Università di Roma, Rome, Italy 73a INFN Sezione di Roma Tor Vergata, Rome, Italy 73b Dipartimento di Fisica, Università di Roma Tor Vergata, Rome, Italy 74a INFN Sezione di Roma Tre, Rome, Italy 74b Dipartimento di Matematica e Fisica, Università Roma Tre, Rome, Italy 75a INFN-TIFPA, Trento, Italy 75b Università degli Studi di Trento, Trento, Italy 76 Institut für Astro- und Teilchenphysik, Leopold-Franzens-Universität, Innsbruck, Austria 77 University of Iowa, Iowa City, Iowa, USA 78 Department of Physics and Astronomy, Iowa State University, Ames, Iowa, USA 79 Joint Institute for Nuclear Research, Dubna, Russia 064901-26 MEASUREMENT OF ANGULAR AND MOMENTUM … PHYSICAL REVIEW C 100, 064901 (2019) 80a Departamento de Engenharia Elétrica, Universidade Federal de Juiz de Fora (UFJF), Juiz de Fora, Brazil 80b Universidade Federal do Rio De Janeiro COPPE/EE/IF, Rio de Janeiro, Brazil 80c Universidade Federal de São João del Rei (UFSJ), São João del Rei, Brazil 80d Instituto de Física, Universidade de São Paulo, São Paulo, Brazil 81 KEK, High Energy Accelerator Research Organization, Tsukuba, Japan 82 Graduate School of Science, Kobe University, Kobe, Japan 83a AGH University of Science and Technology, Faculty of Physics and Applied Computer Science, Krakow, Poland 83b Marian Smoluchowski Institute of Physics, Jagiellonian University, Krakow, Poland 84 Institute of Nuclear Physics Polish Academy of Sciences, Krakow, Poland 85 Faculty of Science, Kyoto University, Kyoto, Japan 86 Kyoto University of Education, Kyoto, Japan 87 Research Center for Advanced Particle Physics and Department of Physics, Kyushu University, Fukuoka, Japan 88 Instituto de Física La Plata, Universidad Nacional de La Plata and CONICET, La Plata, Argentina 89 Physics Department, Lancaster University, Lancaster, United Kingdom 90 Oliver Lodge Laboratory, University of Liverpool, Liverpool, United Kingdom 91 Department of Experimental Particle Physics, Jožef Stefan Institute and Department of Physics, University of Ljubljana, Ljubljana, Slovenia 92 School of Physics and Astronomy, Queen Mary University of London, London, United Kingdom 93 Department of Physics, Royal Holloway University of London, Egham, United Kingdom 94 Department of Physics and Astronomy, University College London, London, United Kingdom 95 Louisiana Tech University, Ruston, Louisiana, USA 96 Fysiska institutionen, Lunds universitet, Lund, Sweden 97 Centre de Calcul de l’Institut National de Physique Nucléaire et de Physique des Particules (IN2P3), Villeurbanne, France 98 Departamento de Física Teorica C-15 and CIAFF, Universidad Autónoma de Madrid, Madrid, Spain 99 Institut für Physik, Universität Mainz, Mainz, Germany 100 School of Physics and Astronomy, University of Manchester, Manchester, United Kingdom 101 CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille, France 102 Department of Physics, University of Massachusetts, Amherst, Massachusetts, USA 103 Department of Physics, McGill University, Montreal, Quebec, Canada 104 School of Physics, University of Melbourne, Victoria, Australia 105 Department of Physics, University of Michigan, Ann Arbor, Michigan, USA 106 Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan, USA 107 B. I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk, Belarus 108 Research Institute for Nuclear Problems of Byelorussian State University, Minsk, Belarus 109 Group of Particle Physics, University of Montreal, Montreal, Quebec, Canada 110 P. N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow, Russia 111 Institute for Theoretical and Experimental Physics of the National Research Centre Kurchatov Institute, Moscow, Russia 112 National Research Nuclear University MEPhI, Moscow, Russia 113 D. V. Skobeltsyn Institute of Nuclear Physics, M. V. Lomonosov Moscow State University, Moscow, Russia 114 Fakultät für Physik, Ludwig-Maximilians-Universität München, München, Germany 115 Max-Planck-Institut für Physik (Werner-Heisenberg-Institut), München, Germany 116 Nagasaki Institute of Applied Science, Nagasaki, Japan 117 Graduate School of Science and Kobayashi-Maskawa Institute, Nagoya University, Nagoya, Japan 118 Department of Physics and Astronomy, University of New Mexico, Albuquerque, New Mexico, USA 119 Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen, Netherlands 120 Nikhef National Institute for Subatomic Physics and University of Amsterdam, Amsterdam, Netherlands 121 Department of Physics, Northern Illinois University, DeKalb, Illinois, USA 122a Budker Institute of Nuclear Physics and NSU, SB RAS, Novosibirsk, Russia 122b Novosibirsk State University, Novosibirsk, Russia 123 Institute for High Energy Physics of the National Research Centre Kurchatov Institute, Protvino, Russia 124 Department of Physics, New York University, New York, New York, USA 125 Ochanomizu University, Otsuka, Bunkyo-ku, Tokyo, Japan 126 Ohio State University, Columbus, Ohio, USA 127 Faculty of Science, Okayama University, Okayama, Japan 128 Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman, Oklahoma, USA 129 Department of Physics, Oklahoma State University, Stillwater, Oklahoma, USA 130 Palacký University, RCPTM, Joint Laboratory of Optics, Olomouc, Czech Republic 131 Center for High Energy Physics, University of Oregon, Eugene, Oregon, USA 132 LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay, France 133 Graduate School of Science, Osaka University, Osaka, Japan 064901-27 G. AAD et al. PHYSICAL REVIEW C 100, 064901 (2019) 134 Department of Physics, University of Oslo, Oslo, Norway 135 Department of Physics, Oxford University, Oxford, United Kingdom 136 LPNHE, Sorbonne Université, Université de Paris, CNRS/IN2P3, Paris, France 137 Department of Physics, University of Pennsylvania, Philadelphia, Pennsylvania, USA 138 Konstantinov Nuclear Physics Institute of National Research Centre “Kurchatov Institute”, PNPI, St. Petersburg, Russia 139 Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, Pennsylvania, USA 140a Laboratório de Instrumentação e Física Experimental de Partículas (LIP), Lisbon, Portugal 140b Departamento de Física, Faculdade de Ciências, Universidade de Lisboa, Lisbon, Portugal 140c Departamento de Física, Universidade de Coimbra, Coimbra, Portugal 140d Centro de Física Nuclear da Universidade de Lisboa, Lisbon, Portugal 140e Departamento de Física, Universidade do Minho, Braga, Portugal 140f Universidad de Granada, Granada, Spain 140g Dep Física and CEFITEC of Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal 140h Av. Rovisco Pais, 1 1049-001 Lisbon, Portugal 141 Institute of Physics of the Czech Academy of Sciences, Prague, Czech Republic 142 Czech Technical University in Prague, Prague, Czech Republic 143 Charles University, Faculty of Mathematics and Physics, Prague, Czech Republic 144 Particle Physics Department, Rutherford Appleton Laboratory, Didcot, United Kingdom 145 IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France 146 Santa Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz, California, USA 147a Departamento de Física, Pontificia Universidad Católica de Chile, Santiago, Chile 147b Departamento de Física, Universidad Técnica Federico Santa María, Valparaíso, Chile 148 Department of Physics, University of Washington, Seattle, Washington, USA 149 Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom 150 Department of Physics, Shinshu University, Nagano, Japan 151 Department Physik, Universität Siegen, Siegen, Germany 152 Department of Physics, Simon Fraser University, Burnaby, British Columbia, Canada 153 SLAC National Accelerator Laboratory, Stanford, California, USA 154 Physics Department, Royal Institute of Technology, Stockholm, Sweden 155 Departments of Physics and Astronomy, Stony Brook University, Stony Brook, New York, USA 156 Department of Physics and Astronomy, University of Sussex, Brighton, United Kingdom 157 School of Physics, University of Sydney, Sydney, Australia 158 Institute of Physics, Academia Sinica, Taipei, Taiwan. 159a E. Andronikashvili Institute of Physics, Iv. Javakhishvili Tbilisi State University, Tbilisi, Georgia 159b High Energy Physics Institute, Tbilisi State University, Tbilisi, Georgia 160 Department of Physics, Technion, Israel Institute of Technology, Haifa, Israel 161 Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv University, Tel Aviv, Israel 162 Department of Physics, Aristotle University of Thessaloniki, Thessaloniki, Greece 163 International Center for Elementary Particle Physics and Department of Physics, University of Tokyo, Tokyo, Japan 164 Graduate School of Science and Technology, Tokyo Metropolitan University, Tokyo, Japan 165 Department of Physics, Tokyo Institute of Technology, Tokyo, Japan 166 Tomsk State University, Tomsk, Russia 167 Department of Physics, University of Toronto, Toronto, Ontario, Canada 168a TRIUMF, Vancouver, British Columbia, Canada 168b Department of Physics and Astronomy, York University, Toronto, Ontario, Canada 169 Division of Physics and Tomonaga Center for the History of the Universe, Faculty of Pure and Applied Sciences, University of Tsukuba, Tsukuba, Japan 170 Department of Physics and Astronomy, Tufts University, Medford, Massachusetts, USA 171 Department of Physics and Astronomy, University of California Irvine, Irvine, California, USA 172 Department of Physics and Astronomy, University of Uppsala, Uppsala, Sweden 173 Department of Physics, University of Illinois, Urbana, Illinois, USA 174 Instituto de Física Corpuscular (IFIC), Centro Mixto Universidad de Valencia-CSIC, Valencia, Spain 175 Department of Physics, University of British Columbia, Vancouver, British Columbia, Canada 176 Department of Physics and Astronomy, University of Victoria, Victoria, British Columbia, Canada 177 Fakultät für Physik und Astronomie, Julius-Maximilians-Universität Würzburg, Würzburg, Germany 178 Department of Physics, University of Warwick, Coventry, United Kingdom 179 Waseda University, Tokyo, Japan 180 Department of Particle Physics, Weizmann Institute of Science, Rehovot, Israel 181 Department of Physics, University of Wisconsin, Madison, Wisconsin, USA 064901-28 MEASUREMENT OF ANGULAR AND MOMENTUM … PHYSICAL REVIEW C 100, 064901 (2019) 182 Fakultät für Mathematik und Naturwissenschaften, Fachgruppe Physik, Bergische Universität Wuppertal, Wuppertal, Germany 183 Department of Physics, Yale University, New Haven, Connecticut, USA 184 Yerevan Physics Institute, Yerevan, Armenia a Also at Borough of Manhattan Community College, City University of New York, New York, New York, USA. b Also at CERN, Geneva, Switzerland. c Also at CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille, France. d Also at Département de Physique Nucléaire et Corpusculaire, Université de Genève, Geneva, Switzerland. e Also at Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona, Spain. f Also at Departamento de Física, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal. g Also at Department of Applied Physics and Astronomy, University of Sharjah, Sharjah, United Arab Emirates. h Also at Department of Financial and Management Engineering, University of the Aegean, Chios, Greece. i Also at Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan, USA. j Also at Department of Physics and Astronomy, University of Louisville, Louisville, Kentucky, USA. k Also at Department of Physics, Ben Gurion University of the Negev, Beer Sheva, Israel. l Also at Department of Physics, California State University, East Bay, California, USA. m Also at Department of Physics, California State University, Fresno, California, USA. n Also at Department of Physics, California State University, Sacramento, California, USA. o Also at Department of Physics, King’s College London, London, United Kingdom. p Also at Department of Physics, St. Petersburg State Polytechnical University, St. Petersburg, Russia. q Also at Department of Physics, Stanford University, Stanford, California, USA. r Also at Department of Physics, University of Adelaide, Adelaide, Australia. s Also at Department of Physics, University of Fribourg, Fribourg, Switzerland. t Also at Department of Physics, University of Michigan, Ann Arbor, Michigan, USA. u Also at Dipartimento di Matematica, Informatica e Fisica, Università di Udine, Udine, Italy. v Also at Faculty of Physics, M.V. Lomonosov Moscow State University, Moscow, Russia. w Also at Giresun University, Faculty of Engineering, Giresun, Turkey. x Also at Graduate School of Science, Osaka University, Osaka, Japan. y Also at Hellenic Open University, Patras, Greece. z Also at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona, Spain. aa Also at Institut für Experimentalphysik, Universität Hamburg, Hamburg, Germany. ab Also at Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen, Netherlands. ac Also at Institute for Nuclear Research and Nuclear Energy (INRNE) of the Bulgarian Academy of Sciences, Sofia, Bulgaria. ad Also at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest, Hungary. ae Also at Institute of Particle Physics (IPP), Vancouver, Canada. af Also at Institute of Physics, Academia Sinica, Taipei, Taiwan. ag Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan. ah Also at Institute of Theoretical Physics, Ilia State University, Tbilisi, Georgia. ai Also at Instituto de Fisica Teorica, IFT-UAM/CSIC, Madrid, Spain. aj Also at Joint Institute for Nuclear Research, Dubna, Russia. ak Also at LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay, France. al Also at Louisiana Tech University, Ruston, Louisiana, USA. am Also at LPNHE, Sorbonne Université, Université de Paris, CNRS/IN2P3, Paris, France. an Also at Manhattan College, New York, New York, USA. ao Also at Moscow Institute of Physics and Technology State University, Dolgoprudny, Russia. ap Also at National Research Nuclear University MEPhI, Moscow, Russia. aq Also at Physics Department, An-Najah National University, Nablus, Palestine. ar Also at Physics Department, University of South Africa, Pretoria, South Africa. as Also at Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany. at Also at School of Physics, Sun Yat-sen University, Guangzhou, China. au Also at The City College of New York, New York, New York, USA. av Also at The Collaborative Innovation Center of Quantum Matter (CICQM), Beijing, China. aw Also at Tomsk State University, Tomsk, and Moscow Institute of Physics and Technology State University, Dolgoprudny, Russia. ax Also at TRIUMF, Vancouver, British Columbia, Canada. ay Also at Universita di Napoli Parthenope, Napoli, Italy. * Deceased. 064901-29