Evolution of the longitudinal and azimuthal structure of the near-side jet peak in Pb-Pb collisions at √sNN = 2.76 TeV

This is an electronic reprint of the original article. This reprint may differ from the original in pagination and typographic detail. Author(s): Title: Year: Version: Please cite the original version: All material supplied via JYX is protected by copyright and other intellectual property rights, and duplication or sale of all or part of any of the repository collections is not permitted, except that material may be duplicated by you for your research use or educational purposes in electronic or print form. You must obtain permission for any other use. Electronic or print copies may not be offered, whether for sale or otherwise to anyone who is not an authorised user. Evolution of the longitudinal and azimuthal structure of the near-side jet peak in PbPb collisions at √sNN = 2.76 TeV ALICE Collaboration ALICE Collaboration. (2017). Evolution of the longitudinal and azimuthal structure of the near-side jet peak in Pb-Pb collisions at √sNN = 2.76 TeV. Physical Review C, 96(3), Article 034904. https://doi.org/10.1103/PhysRevC.96.034904 2017 PHYSICAL REVIEW C 96, 034904 (2017) Evolution of the longitudinal and azimuthal structure of the near-side jet peak in Pb-Pb collisions at √sNN =2.76 TeV J. Adam et al.∗ (ALICE Collaboration) (Received 28 September 2016; published 8 September 2017) In two-particle angular correlation measurements, jets give rise to a near-side peak, formed by particles associated to a higher-pTtrigger particle. Measurements of these correlations as a function of pseudorapidity (η) and azimuthal (ϕ) differences are used to extract the centrality and pTdependence of the shape of the near-side peak in the pTrange 1 <p T<8 GeV/c in Pb-Pb and pp collisions at √sNN =2.76 TeV. A combined fit of the near-side peak and long-range correlations is applied to the data and the peak shape is quantified by the variance of the distributions. While the width of the peak in the ϕ direction is almost independent of centrality, a significant broadening in the η direction is found from peripheral to central collisions. This feature is prominent for the low-pTregion and vanishes above 4 GeV/c. The widths measured in peripheral collisions are equal to those in pp collisions in the ϕ direction and above 3 GeV/c in the η direction. Furthermore, for the 10% most central collisions and 1 <p T,assoc <2 GeV/c,1<p T,trig <3 GeV/c, a departure from a Gaussian shape is found: a depletion develops around the center of the peak. The results are compared to A Multi-Phase Transport (AMPT) model simulation as well as other theoretical calculations indicating that the broadening and the development of the depletion are connected to the strength of radial and longitudinal flow. DOI: 10.1103/PhysRevC.96.034904 I. INTRODUCTION In elementary interactions with large momentum transfer (Q22 QCD), partons with high transverse momentum (pT) are produced. Carrying net color charge, they cannot exist freely and, instead, evolve from high to low virtuality, producing parton showers. These eventually hadronize into a spray of collimated hadrons called jets. High-pTpartons are produced at the early stages of heavy-ion collisions. They propagate and evolve through the dense and hot medium created in these collisions and are expected to lose energy due to induced gluon radiation and elastic scatterings, a process commonly referred to as jet quenching. The transfer of energy from the leading parton to the medium and/or into additional gluon radiation leads to effects that can be exploited to characterize the color density and scattering power of the medium. Experimental methods to study high-pTparton production differ in their capability to reconstruct the original parton momentum and to characterize the angular and momentum distribution of jet fragments. Furthermore, their sensitivity to experimental bias, most particularly the bias associated with the large underlying-event background encountered in heavy-ion collisions, is different. Inclusive hadron spectra are unbiased observables, mainly sensitive to the hadronic fragments with the largest momentum fraction (leading particles). Partonic energy loss suppresses high-pTparticle yields relative to their production in more elementary pp and p-A collisions ∗Full author list given at the end of the article. Published by the American Physical Society under the terms of the Creative Commons Attribution 3.0 License. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. which was observed at RHIC and LHC energies. The largest suppression is observed in central Pb-Pb collisions at the LHC at pT≈7GeV/c [1,2]. Jet reconstruction algorithms have the objective to recombine a maximum of jet fragments within a certain area in the pseudorapidity-azimuth (η-ϕ) plane in order to obtain the original parton energy and direction. In heavy-ion collisions, due to the large fluctuating energy from particles uncorrelated to the jets, the underlying event, jet reconstruction is limited to high transverse energy and small areas (cone size) around the parton direction. An inclusive jet suppression commensurable to that of hadrons has been observed at the LHC [3–5] together with a large dijet energy asymmetry [6,7], suggesting that a large fraction of the lost energy is radiated outside the typical jet cone sizes of R=0.3–0.5. Detailed studies of the energy balance in events with high-energy jets show that the lost energy reappears primarily at low to intermediate pT(0.5–3 GeV/c) outside the jet cone [7]. Studies of the momentum and angular distributions of jet fragments show that the jet core is almost unmodified [8–10]. Dihadron angular correlations represent a powerful complementary tool to study jet quenching and the redistribution of energy in an energy region where jets cannot be identified event-by-event over the fluctuating background and where quenchingeffectsareexpectedtobelarge.Suchstudiesinvolve measuring the distributions of the relative azimuthal angle ϕ and pseudorapidity η between particle pairs. The pairs consist of a trigger particle in a certain transverse momentum pT,trig intervaland anassociated particle ina pT,assoc interval.In these correlations, jets manifest themselves as a peak centered around (ϕ =0,η =0) (near-side peak) and a structure elongated in η at ϕ =π(the away side or recoil region). At low pT, resonance decays as well as femtoscopic correlations also contribute to the near-side peak. The advantage of using dihadron correlations is that an event-averaged 2469-9985/2017/96(3)/034904(18) 034904-1 ©2017 CERN, for the ALICE Collaboration J. ADAM et al. PHYSICAL REVIEW C 96, 034904 (2017) subtraction of the background from particles uncorrelated to the jet can be performed. This advantage is shared with the analysis of hadron-jet correlations recently reported in Refs. [11,12]. At RHIC, the near-side associated particle yield and peak shape have been studied for different systems and collision energies [13–15]. Small modifications of the yields with respect to a pp reference from PYTHIA are observed and there is remarkably little dependence on the collision system at the center-of-mass energies of √sNN =62.4 and 200 GeV. An exception is the measurement in central Au-Au collisions at √sNN =200 GeV where the jetlike correlation is substantially broader and the momentum spectrum softer than in peripheral collisions and than those in collisions of other systems in this kinematic regime. In Ref. [14], the broadening observed in central Au-Au collisions at √sNN =200 GeV is seen as an indication of a modified jet fragmentation function. At the LHC, the measurement of the yield of particles associatedtoa high-pTtrigger particle(8–15GeV/c)in central Pb-Pb collisions relative to the pp reference at pT,assoc > 3GeV/c shows a suppression on the away side and a moderate enhancement on the near side indicating that medium-induced modifications can also be expected on the near side [16]. Much stronger modifications are observed for lower trigger and associated particle pT(3 <p T,trig <3.5GeV/c and 1<p T,assoc <1.5GeV/c)[17,18]. In the most central Pb-Pb collisions, the near-side yield is enhanced by a factor of 1.7. The present paper expands these studies at the LHC to the characterization of the angular distribution of the associated particles with respect to the trigger particle. The angular distribution is sensitive to the broadening of the jet due to the degradation of its energy and the distribution of radiated energy. Moreover, possible interactions of the parton shower with the collective longitudinal expansion [19–21] or with turbulent color fields [22] in the medium would result in near-side peak shapes that are broader in the η thanin the ϕ direction. Results from the study of the near-side peak shape of charged particles as a function of centrality and for different combinations of trigger and associated particle pTare discussed. The paper is organized in the following way: the ALICE subsystems used in the analysis are described in Sec. II and the data samples, event, and track selection in Sec. III. Section IV describes the analysis methods, and the systematic uncertainties are discussed in Sec. V. Results are presented in Sec. VI and conclusions are drawn in Sec. VII.Thekey results of the presented analysis are also reported in a short companion paper [23]. II. EXPERIMENTAL SETUP A detailed description of the ALICE detector can be found in Ref. [24]. The main subsystems used in the present analysis are the Inner Tracking System (ITS) and the Time Projection Chamber (TPC). These have a common acceptance of |η|<0.9 and are operated inside a solenoidal magnetic field of 0.5 T. The ITS consists of six layers of silicon detectors for vertex finding and tracking. The two outermost layers of the ITS are composed of the Silicon Strip Detector (SSD), the two middle layers the Silicon Drift Detector (SDD), and the two innermost layers the Silicon Pixel Detector (SPD) with the last also used for triggering. The TPC is the main tracking detector measuring up to 159 space points per track. The V0 detector, consisting of two arrays of 32 scintillator tiles each, and covering 2.8<η<5.1 (V0-A) and −3.7< η<−1.7 (V0-C), was used for triggering and centrality determination [25,26]. All these detector systems have full azimuthal coverage. Data from the 2010 and 2011 Pb-Pb runs of the LHC at √sNN =2.76 TeV and the 2011 pp run at the same energy are combined in the present analysis. From the 2010 sample, about 1.6×107minimum-bias Pb-Pb events are considered, while in the 2011 Pb-Pb run about 2.0×106minimum-bias events and about 2.1×107centrality-triggered events enhancing the 0–50% centrality range are used. The pp event sample consists of 3.0×107minimum-bias events. In Pb-Pb collisions, the trigger required a coincidence of signals in both V0-A and V0-C. In addition, two zero degree calorimeters (ZDCs) for neutron detection located ±114 m from the interaction point are used to suppress electromagnetic interactions. More details about the event selection can be found in Ref. [27]. The events are characterized into five collision-centrality classes based on the sum of amplitudes in the V0 detectors [26] [0–10% (most central), 10–20%, 20–30%, 30–50% and 50–80%]. In pp collisions, the trigger required a signal in either of the V0 detectors or the SPD [28]. In both collision systems, these triggers are fully efficient for events entering the two-particle correlation analysis presented in this work. III. EVENT AND TRACK SELECTION The collision-vertex position is determined with tracks reconstructed in the ITS and TPC as described in Ref. [1]. The vertexreconstructionalgorithmis fullyefficient for eventswith at least one reconstructed primary track within |η|<1.4[29]. The position of the reconstructed vertex along the beam direction (zvtx) is required to be within 7 cm of the detector center. This value is reduced to 3 cm in the study of systematic uncertainties. The analysis uses tracks reconstructed in the ITS and TPC with 1 <p T<8GeV/c and in a fiducial region of |η|<0.8. As a first step in the track selection, criteria on the number of space points (at least 70) and the quality of the track fit (χ2/ndf <2, where ndf is number of degrees of freedom) in the TPC are applied. Tracks are further required to have a distanceof closestapproach tothe reconstructedvertex smaller than 2.4 and 3.2 cm in the transverse and the longitudinal directions, respectively. Two classes of tracks are combined in order to avoid an azimuthally dependent tracking efficiency due to inactive SPD modules [30]. The first class requires for tracks to have at least one hit in the SPD. For tracks which do not fulfill this criterion, in the second class, the primary vertex position is used as additional constraint in the global track fit. An alternative track selection [31], where a tighter pT-dependent cut on the distance of closest approach to the reconstructed vertex is applied, is used for the assignment of a systematic uncertainty. Furthermore, the tracks in the second class are required to have a hit in the first layer of the SDD. This 034904-2 EVOLUTION OF THE LONGITUDINAL AND AZIMUTHAL . . . PHYSICAL REVIEW C 96, 034904 (2017) TABLE I. Centrality classes and corresponding number of accepted events in pp and Pb-Pb collisions at √sNN =2.76 TeV used in this analysis. Collision system Centrality class Accepted events (×106) Pb-Pb 0–10% 7.7 10–20% 2.9 20–30% 2.9 30–50% 5.9 50–80% 3.9 pp 24.0 modified selection has a less uniform azimuthal acceptance, but includes a smaller number of secondary particles produced by interactions in the detector material or weak decays. The efficiency and purity of the primary charged-particle selection are estimated from a Monte Carlo (MC) simulation using the HIJING 1.383 event generator [32] (for Pb-Pb) and the PYTHIA 6.4 event generator [33] with the tune Perugia-0 [34] (for pp) with particle transport through the detector carried out with GEANT3 [35]. The combined efficiency and acceptance of the track reconstruction in |η|<0.8 is about 82–85% at pT=1GeV/c and decreases to about 76–80% at pT= 8GeV/c depending on collision system, data sample, and event centrality. The contamination from secondary particles resulting from weak decays and due to interactions in the detector material decreases from 2.5–4.5% to 0.5–1% in the pTrange from 1 to 8 GeV/c. The contribution from fake tracks, arising from improperly associated hits, is negligible. The alternative track selection (see above) has 3–6% lower combined efficiency and acceptance and about two-thirds of the secondary contamination. Owing to the combination of different event samples (see Sec. II), the number of accepted events per centrality class is not uniform, as is shown in Table I. IV. ANALYSIS The correlation between two charged particles (denoted trigger and associated particle) is measured as a function of the azimuthal angle difference ϕ (defined within −π/2 and 3π/2) and pseudorapidity difference η [36]. The correlation is expressed in terms of the associated yield per trigger particle for intervals of trigger and associated transverse momentum, pT,trig and pT,assoc, respectively. The pTintervals can be different or identical, in which case only pairs of particles with pT,assoc <p T,trig are considered to avoid double counting. The per-trigger yield can be measured experimentally if the particle distribution is independent of pseudorapidity [37]in the following way: 1 Ntrig d2Nassoc dηdϕ =S(η,ϕ) B(η,ϕ)(1) where Ntrig is the total number of trigger particles in the centrality class and pT,trig interval, ranging from 0.18 to 36 per event. The signal distribution S(η,ϕ)= 1/Ntrig d2Nsame/dη dϕ is the associated yield per trigger particle for particle pairs from the same event. The background distribution B(η,ϕ)=αd2Nmixed/dη dϕ corrects for finite pair acceptance and pair efficiency. It is constructed by correlating the trigger particles in one event with the associated particles from other events in the same centrality class and within the same 2-cm-wide zvtx interval (each event is mixed with 5–20 events depending on the number of tracks per event). The background distribution is scaled by a factor αwhich is chosen such that B(0,0) is unity for pairs where both particles travel in approximately the same direction (i.e., ϕ ≈0, η ≈0), and thus the efficiency and acceptance for the two particles are identical by construction. The yield defined by Eq. (1) is constructed for each zvtx interval to account for differences in pair acceptance and efficiency, depending on the vertex position zvtx. The trigger particles and the pairs are corrected for single-particle efficiency, described below, before the final per-trigger yield is obtained by calculating the average of the zvtx intervals weighted by Ntrig. A minimum opening angle of the particle pairs is required for both signal and background to avoid a bias due to the reduced efficiency for pairs with small separation. Pairs are required to have a separation of |ϕ∗ min|>0.02 rad or |η|>0.02, where ϕ∗ min is the minimal azimuthal distance at the same radius between the two tracks within the active detector volume. Furthermore, correlations induced by secondary particles from long-lived neutral-particle decays (K0 sand ) and γconversions are suppressed by cutting on the invariant mass (minv) of the particle pair. Pairs are removed which are likely to stem from a γconversion (minv < 4MeV/c2), a K0 sdecay (|minv −m(K0 s)|<5MeV/c2), or a  decay (|minv −m()|<5MeV/c2). Weak decays of heavier particles give a negligible contribution. Each trigger and each associated particle is weighted with a correction factor that accounts for detector acceptance, reconstruction efficiencies, and contamination from secondary particles. These corrections are applied as a function of η, pT,zvtx, and event centrality. The shape parameters extracted below are expected to be insensitive to these single-particle corrections which was confirmed in the analysis. The obtained per-trigger yields as a function of relative angle are integrated over particles produced within |η|<0.8. As mentioned above, the method requires that the distribution of sources contributing to the correlation are independent of pseudorapidity, which is approximately the case for the inclusive particle distribution [25] as well as the anisotropic flow [38]. It can be easily shown (analytically or in a toy Monte Carlo), that such a pseudorapidity dependence results in distortions as a function of η of the per-trigger yields which are independent of ϕ. In addition, the finite centrality and zvtx bin width in the event mixing has been found to cause η-dependent effects due to the dependence of particle production on centrality and the zvtx-dependent detector efficiency, respectively. In the data, such distortions in η, of the order of 0.1%, have been observed. While small, these distortions are still relevant compared to the jetlike peak which is on top of the large combinatorial background. To suppress distortions of the peak in the η direction, a correction factor is calculated such that the away side, which is outsideofthe rangestudiedby this work,becomesindependent 034904-3 J. ADAM et al. PHYSICAL REVIEW C 96, 034904 (2017) of η. This correction factor is then applied consistently to all ϕ bins. The correctness of this procedure is supported by the fact that the goodness of the fit (see following section) is substantially improved. To characterize the near-side peak shape, a simultaneous fit of the peak, the combinatorial background, and the long-range correlation background stemming from collective effects is performed. This exploits that in two-particle correlations the near-side peakis centered around ϕ =0,η =0while longrange correlation structures are approximately independent of η [38]. This strategy limits the analysis to the near side, as the away-side peak is elongated in η. The fit function used is a combination of a constant, a generalized two-dimensional Gaussian function, and cos(nϕ)termsforn=2,3,4: F(ϕ,η)=C1+ 4  n=2 2Vn cos(nϕ) +C2Gγϕ ,wϕ (ϕ)Gγη,wη (η),(2) Gγx,wx(x)=γx 2wx(1/γx)exp −|x| wxγx.(3) Thus, in Pb-Pb collisions, the background is characterized by four parameters (C1,Vn) where Vn are the Fourier componentsof the long-range correlations [39],and it should be noted that the inclusion of orders higher than 4 does not significantly changethefitresults. In ppcollisions,however,thebackground consists effectively only of the pedestal C1. The peak magnitude is characterized by C2, and the shape which is the focus of the present analysis by four parameters (γϕ,wϕ,γη,wη). Note that for γ=2 the generalized Gaussian function Gis a Gaussian, and for γ=1 it is a Laplace distribution, which is an exponential where the absolute value of the argument is taken [exp(−|x|)]. The aim of using this fit function is to allow for a compact description of the data rather than attempting to give a physical meaning to each parameter. A further reduced description of the peak shape is provided by the variances (σϕ and ση) of the generalized Gaussian. The evolution of the peak shape from peripheral to central collisions is described by the ratio of the width in the central bin (0–10%) and the peripheral bin (50–80%), denoted by σCP ϕ and σCP η . In the data, a depletion around ϕ =0, η =0 is observed at low pT; however, the fit function does not include such a depletion. Several bins in the central region are excluded from the fit, avoiding a bias on the extracted peak width. The size of the excluded region varies with pTand collision centrality reflecting both the width of the peak and the area of the depletion. The exclusion region is largest (0.3) in the lowest pTbin and most central Pb-Pb collisions and vanishes for higher pTand peripheral Pb-Pb collisions. The sensitivity of the result to the size of the exclusion region was studied (see Sec. V). Thus, by definition, the peak width describes the shape of the peak outside of the central region. The depletion in the central region is quantified by the near-side depletion yield in Sec. VI C by computing the difference between the fit and the per-trigger yield within the exclusion region. Figure 1illustrates the fit procedure. Shown are the data as well as the background and peak components of the fit. The bottom right panel shows the difference between the data and the fit where only minor deviations less than 0.5% can be observed. Figure 2shows the ϕ and η projections of the data overlaid with the obtained fit functions. The comparison with the background illustrates the magnitude of the peak. In Pb-Pb collisions, the χ2/ndf values of the fits are found in the range 1.0–2.5; most are around 1.5. In the highest two pTbins (i.e., in 3 <p T,assoc <8GeV/c and 4 <p T,trig < 8GeV/c) the values increase up to about 2.5 showing that at high pTthe peak shape starts to depart from the generalized Gaussian description. In pp collisions, the χ2/ndf values are in the range 1.3–2.0. Different fitting strategies have been tried using a twodimensional Gaussian to describe the peak, which is found to not describe the data satisfactorily (conversely, the χ2/ndf is too large). A superposition of two two-dimensional Gaussians describes the data well but is found unstable compared to the generalized Gaussian. In general, the fit with a single two-dimensional Gaussian results in smaller peak widths than the generalized Gaussian case which in turn has smaller peak widths than the two two-dimensional Gaussian fit. V. SYSTEMATIC UNCERTAINTIES Systematic uncertainties connected to the measurement are determinedby modifyingthe selection criteria discussed above and repeating the analysis. The difference in the extracted parameters is studied as a function of pT, centrality, and collision system, but these dependencies are rather weak and one uncertainty value can be quoted for each source of systematic uncertainty in most cases. Finally, the contributions fromthedifferent sources ofsystematicuncertaintiesareadded in quadrature. The extracted peak widths are rather insensitive to changes in the selections (total uncertainty of about 2–4.5%) while the near-side depletion yield defined in Sec. VI C is more sensitive (about 24–45% uncertainty). Table II summarizes the different sources of systematic uncertainties which have been considered. Changes of vertex range and track selection have already been detailed in Sec. III. The selection criterion on pairs with small opening angles (see Sec. IV) is increased by a factor of 2 and the mass range in the cut removing neutral-particle decays is modified by 50%. The size of the exclusion region around ϕ =0, η =0(see Sec.IV) is enlarged by 0.17 (0.2) in the ϕ (η) direction.The sensitivity of the analysis results to the pseudorapidity range used is assessed by changing it by ±0.1. This uncertainty includes effects of the pseudorapidity dependence of the anisotropic flow as well as the particle production in general. Trigger particles in positive and negative ηdirections are studied separately to exclude any detector effects related to the trigger-particle direction. No dependence of the results presented in this paper on the polarity of the magnetic field was observed. The influence of resonance decays on the observations presented below was investigated by performing the analysis separately for like-sign and unlike-sign pairs. While the numerical values change, which is not unexpected, the qualitative conclusions presented below are unchanged. In particular, the reported broadening and depletion are larger in the like-sign 034904-4 EVOLUTION OF THE LONGITUDINAL AND AZIMUTHAL . . . PHYSICAL REVIEW C 96, 034904 (2017) FIG. 1. Illustration of the fitting procedure for the 10% most central Pb-Pb events at √sNN =2.76 TeV in 2 <p T,assoc <3 GeV/c and 3<p T,trig <4 GeV/c. (a) The two-dimensional azimuthal and pseudorapidity total per-trigger yield, (b) the background distribution and (c) the signal peak component from the fit by Eq. (2), and (d) the relative difference between the data and the fit. FIG. 2. Projections of Fig. 1(a) to the (a) ϕ and (b) η directions. The projections integrated over |η|<1.6and|ϕ|<π/2, respectively, present per-trigger yields (and not densities) and therefore the level of the background is different than in Fig. 1. The fit and the background component of the fit are overlaid with the data. 034904-5 J. ADAM et al. PHYSICAL REVIEW C 96, 034904 (2017) TABLE II. Summary of the systematic uncertainties of the analysis. Ranges indicate a dependence on centrality. Source σϕ ση σCP ϕ σCP η Depletion yield Track selection and 1.0% 1.3% 20% efficiencies Small opening angle cut 0.7% 1.3% 5–10% Neutral-particle decay cut 0.1% 0.2% 8–20% Vertex range 1.0% 1.0% 5–10% Pseudorapidity 1.7% 4.1% 0.6% 2.5% 5–15% dependence Exclusion region 0.1% 1.0% 0.1% 1.5% 7–28% Total 2.3% 4.5% 2.2% 3.6% 24–45% case, suggesting that resonance decays do not play a significant role for these phenomena. VI. RESULTS The top row of Fig. 3shows the near-side peak in 1<p T,trig <2GeV/c and 1 <p T,assoc <2GeV/c after subtraction of the background estimated with Eq. (2). The peak has a similar shape in pp collisions and in peripheral (50– 80% centrality) Pb-Pb collisions, where it is approximately symmetric in ϕ and η. In the 10% most central collisions a different picture is observed: the near-side peak is broader than in peripheral collisions and wider in η than in ϕ. Furthermore, a depletion around ϕ =0, η =0 develops which is discussed in more detail further below. At higher pT(bottom row of Fig. 3), the near-side peak is also found broader in central collisions than in peripheral or pp collisions, although it is visually less pronounced, but the asymmetry between ϕ and η disappears at the two highest pTbins included in the analysis. In addition, the amplitude of the peak is smaller in central collisions. Figure 4shows the projections of the two-dimensional histogram shown in Fig. 3(c), where the depletion is largest, together with the fitted function. A. Peak widths Weexamineandquantifytheevolutionofthenear-sidepeak shape and width with the fit procedure described in Sec. IV. The extracted shape parameters σϕ and ση are presented in Fig. 5.Inpp collisions, the σvalues range from 0.14 to 0.43 showing the expected pTdependence: due to the boost of the evolving parton shower at larger pTthe peak is narrower. In the ϕ direction (left panel) the values obtained in pp collisions are consistent with those in peripheral Pb-Pb collisions. The peak width increases toward central events which is most pronounced in the lowest pTbin (20% increase). In the higher FIG. 3. Associated yield per trigger particle as a function of ϕ and η in pp collisions (left panels) and Pb-Pb collisions at √sNN = 2.76 TeV in the 50–80% centrality class (middle panels) and in the 0–10% centrality class (right panels). The top row shows 1 <p T,assoc < 2 GeV/c and 1 <p T,trig <2 GeV/c and the bottom row shows 2 <p T,assoc <3 GeV/c and 3 <p T,trig <4 GeV/c. The background obtained from the fit function has been subtracted in order to emphasize the near-side peak. 034904-6 EVOLUTION OF THE LONGITUDINAL AND AZIMUTHAL . . . PHYSICAL REVIEW C 96, 034904 (2017) FIG. 4. Projections of Fig. 3(c) to the (a) ϕ and (b) η directions. The depletion around ϕ =0, η =0 is clearly visible in both directions. pTbins no significant width increase can be observed. In the η direction (right panel) a much larger broadening toward central collisions is found. Already in peripheral collisions the width is larger than in pp collisions, and from peripheral to central collisions the width increases further up to ση =0.67 in the lowest pTbin. The largest relative increase of about 85% is observed for 2 <p T,trig <3GeV/c and 2 <p T,assoc < 3GeV/c. A significant broadening can be observed for all but the two largest pTbins. This increase is quantified for all pT bins in Fig. 6by σCP ϕ and σCP η . The increase is quantified with respect to peripheral Pb-Pb instead of pp to facilitate the MC comparisons discussed below. In pp collisions, the peak shows circular symmetry in the η-ϕ plane for all pT. In Pb-Pb collisions, the peak becomes asymmetric toward central collisions for all but the twohighestpTbins.The magnitude ofthis asymmetrydepends on pTand is largest with about 70% (ση >σ ϕ) in the range 2<p T,trig <3GeV/c and 2 <p T,assoc <3GeV/c. B. Model comparison The interplay of longitudinal flow with a fragmenting high-pTparton was suggested in Ref. [19] as a possible source for the observed asymmetric peak shape. The authors argue that hard partons are interacting with a medium which shows collective behavior. This is confronted with the simpler picture where the parton propagates through an isotropic medium with respect to the parton direction. In their calculation the scattering centers are Lorentz boosted by applying a momentum shift depending on the collective component transverse to the parton-propagation direction. The calculation in Ref. [19]for Au-Au collisions at √sNN =200 GeV expects a 20% increase from peripheral to central events for the ϕ direction and a 60% increase for the η direction. Despite the different centerof-mass energy and collision system, the calculation is in quantitative agreement with the results presented in this paper. Further studies on the possibility that the effect can be caused by an interplay of flow and jets have been done FIG. 5. Shape parameters σϕ (left panel) and ση (right panel) as a function of centrality in different pTranges for Pb-Pb collisions at √sNN =2.76 TeV and pp collisions (rightmost points in each panel). Lines indicate statistical uncertainties (mostly smaller than the marker size), while boxes denote systematic uncertainties. The markers are placed at the center of the centrality bins. 034904-7 J. ADAM et al. PHYSICAL REVIEW C 96, 034904 (2017) FIG. 6. Ratio of the peak widths in ϕ (left panel) and η (right panel) observed in central (0–10%) and peripheral (50–80%) collisions as a function of pT,trig and pT,assoc ranges. The data are compared to the different settings in A Multi-Phase Transport (AMPT) model. Note that the x-axis combines the pT,assoc and pT,trig axis, and, therefore, a uniform trend of the values is not expected. Lines indicate statistical uncertainties (mostly smaller than the marker size), while boxes (only for data) denote systematic uncertainties. comparing the data to generator-level results from A MultiPhase Transport (AMPT) model [40,41], which has been shown to feature a longitudinal broadening of the near-side peak [42]. Two mechanisms in AMPT produce collective effects: partonic and hadronic rescattering. Before partonic rescattering, the initially produced strings may be broken into smaller pieces by the so-called string melting. Three different AMPT settings are considered, having either string melting or hadronic rescattering or both activated.1About 1.0×107 events were generated for each of the cases with string melting activated, and about 4.7×107events for the case with string melting disabled. The results obtained in pp collisions are compared to PYTHIA 8.1 simulations [44] with the Monash tune [45] with about 5.0×108generated events. The peak widths and σCP ϕ and σCP η are extracted from particle level AMPT simulations in the same way as for the data. Figure 6compares these ratios to the data. In the ϕ direction, the setting with string melting deactivated and hadronic rescattering active follows the trend of the data closest. The two other settings show a more uniform distribution across pTand only differ in the two lowest pTbins. In the η direction, the setting with string melting deactivated and hadronic rescattering active quite remarkably follows the trend of the data including the large increase for intermediate pT. The two other settings show qualitatively a similar trend but miss the data quantitatively. In addition to the relative increase, it is interesting to compare the absolute widths. Figure 7presents the ratio of 1AMPT versions v1.25t3 (without string melting, parameter isoft =1) and v2.25t3 (with string melting, parameter isoft =4) are used. In addition, in one sample the use of rescattering in the hadronic phase is disabled by setting the parameter ntmax to 3 (the default is 150). See Ref. [43] for more details on these settings. the widths in the three AMPT settings to the width measured inPb-Pb collisions as well asthe onesfrom PYTHIA simulations with the Monash tune to the ones measured in pp collisions. In general, none of the AMPT settings provides an accurate description of the data. The setting that matches best the relative width increase (string melting deactivated, hadronic rescattering active) overestimates the width by on average 20–30% with a mild pTdependence. The two settings with string melting show a decreasing (increasing) trend as a function of pTin central (peripheral) collisions in the ϕ direction. In the η direction, in central collisions, they both overand underestimate the data depending on pT, while there is about 10% overestimation in peripheral collisions mostly independent of pT. The width in pp collisions is well described by PYTHIA at high pTin both directions, while the width in ϕ (η) is overestimated by 10% (25%) at low pT. C. Near-side depletion The results presented in the previous section focused on the overall shape of the near-side peak. In addition to the broadening, a distinct feature in central collisions and at low pTisobserved:adepletionaround ϕ =0, η =0[Figs.3(c) and 4]. An extensive set of studies was carried out to determine whether this depletion could arise from detector effects. Studies focused, in particular, on two-track effects: tracks with similar momenta which overlap in parts of the detector volume may suffer from efficiency losses and reconstruction imperfections; e.g., a splitting of a particle’s trajectory into two tracks may cause distortions of the two-particle correlation around ϕ =0, η =0. It was shown that such detectorrelated effects are present but only in a very limited region of where both |ϕ|and |η|are smaller than 0.04–0.05. The depletion discussed in this section extends out to |η| well beyond 0.3, which is significantly larger than the detector 034904-8 EVOLUTION OF THE LONGITUDINAL AND AZIMUTHAL . . . PHYSICAL REVIEW C 96, 034904 (2017) M. Ippolitov,82,77 M. Irfan,18 V. Isakov,53 M. S. Islam,49 M. Ivanov,100,35 V. Ivanov,88 V. Izucheev,114 B. Jacak,76 N. Jacazio,27 P. M. Jacobs,76 M. B. Jadhav,48 S. Jadlovska,118 J. Jadlovsky,118 C. Jahnke,123,36 M. J. Jakubowska,138 M. A. Janik,138 P. H. S. Y. Jayarathna,126 C. Jena,81 S. Jena,126 R. T. Jimenez Bustamante,100 P. G. Jones,104 A. Jusko,104 P. Kalinak,56 A. Kalweit,35 J. H. Kang,142 V. Kaplin,77 S. Kar,137 A. Karasu Uysal,71 O. Karavichev,53 T. Karavicheva,53 L. Karayan,100,96 E. Karpechev,53 U. Kebschull,60 R. Keidel,143 D. L. D. Keijdener,54 M. Keil,35 M. Mohisin Khan,18,‡P. Khan,103 S. A. Khan,137 A. Khanzadeev,88 Y. Kharlov,114 A. Khatun,18 A. Khuntia,49 B. Kileng,37 D. W. Kim,43 D. J. Kim,127 D. Kim,142 H. Kim,142 J. S. Kim,43 J. Kim,96 M. Kim,51 M. Kim,142 S. Kim,20 T. Kim,142 S. Kirsch,42 I. Kisel,42 S. Kiselev,55 A. Kisiel,138 G. Kiss,140 J. L. Klay,6C. Klein,61 J. Klein,35 C. Klein-Bösing,62 S. Klewin,96 A. Kluge,35 M. L. Knichel,96 A. G. Knospe,121,126 C. Kobdaj,117 M. Kofarago,35 T. Kollegger,100 A. Kolojvari,136 V. Kondratiev,136 N. Kondratyeva,77 E. Kondratyuk,114 A. Konevskikh,53 M. Kopcik,118 M. Kour,93 C. Kouzinopoulos,35 O. Kovalenko,79 V. Kovalenko,136 M. Kowalski,120 G. Koyithatta Meethaleveedu,48 I. Králik,56 A. Kravˇ cáková,40 M. Krivda,56,104 F. Krizek,86 E. Kryshen,35,88 M. Krzewicki,42 A. M. Kubera,19 V. Ku ˇ cera,86 C. Kuhn,66 P. G. Kuijer,84 A. Kumar,93 J. Kumar,48 L. Kumar,90 S. Kumar,48 S. Kundu,81 P. Kurashvili,79 A. Kurepin,53 A. B. Kurepin,53 A. Kuryakin,102 S. Kushpil,86 M. J. Kweon,51 Y. Kwon,142 S. L. La Pointe,42 P. La Rocca,28 C. Lagana Fernandes,123 I. Lakomov,35 R. Langoy,41 K. Lapidus,36,141 C. Lara,60 A. Lardeux,15 A. Lattuca,26 E. Laudi,35 L. Lazaridis,35 R. Lea,25 L. Leardini,96 S. Lee,142 F. Lehas,84 S. Lehner,115 J. Lehrbach,42 R. C. Lemmon,85 V. Lenti,106 E. Leogrande,54 I. León Monzón,122 P. Lévai,140 S. Li,7X. Li,14 J. Lien,41 R. Lietava,104 S. Lindal,21 V. Lindenstruth,42 C. Lippmann,100 M. A. Lisa,19 H. M. Ljunggren,34 W. Llope,139 D. F. Lodato,54 P. I. Loenne,22 V. Loginov,77 C. Loizides,76 X. Lopez,72 E. López Torres,9A. Lowe,140 P. Luettig,61 M. Lunardon,29 G. Luparello,25 M. Lupi,35 T. H. Lutz,141 A. Maevskaya,53 M. Mager,35 S. Mahajan,93 S. M. Mahmood,21 A. Maire,66 R. D. Majka,141 M. Malaev,88 I. Maldonado Cervantes,63 L. Malinina,68,§D. Mal’Kevich,55 P. Malzacher,100 A. Mamonov,102 V. Manko,82 F. Manso,72 V. Manzari,106 Y. Mao,7M. Marchisone,130,67 J. Mareš,57 G. V. Margagliotti,25 A. Margotti,107 J. Margutti,54 A. Marín,100 C. Markert,121 M. Marquard,61 N. A. Martin,100 P. Martinengo,35 M. I. Martínez,2G. Martínez García,116 M. Martinez Pedreira,35 A. Mas,123 S. Masciocchi,100 M. Masera,26 A. Masoni,108 A. Mastroserio,33 A. Matyja,129,120 C. Mayer,120 J. Mazer,129 M. Mazzilli,33 M. A. Mazzoni,111 F. Meddi,23 Y. Melikyan,77 A. Menchaca-Rocha,65 E. Meninno,30 J. Mercado Pérez,96 M. Meres,38 S. Mhlanga,92 Y. Miake,132 M. M. Mieskolainen,46 K. Mikhaylov,55,68 L. Milano,76 J. Milosevic,21 A. Mischke,54 A. N. Mishra,49 T. Mishra,58 D. Mi´ skowiec,100 J. Mitra,137 C. M. Mitu,59 N. Mohammadi,54 B. Mohanty,81 L. Molnar,116 E. Montes,10 D. A. Moreira De Godoy,62 L. A. P. Moreno,2S. Moretto,29 A. Morreale,116 A. Morsch,35 V. Muccifora,74 E. Mudnic,119 D. Mühlheim,62 S. Muhuri,137 M. Mukherjee,137 J. D. Mulligan,141 M. G. Munhoz,123 K. Münning,45 R. H. Munzer,97,36,61 H. Murakami,131 S. Murray,67 L. Musa,35 J. Musinsky,56 C. J. Myers,126 B. Naik,48 R. Nair,79 B. K. Nandi,48 R. Nania,107 E. Nappi,106 M. U. Naru,16 H. Natal da Luz,123 C. Nattrass,129 S. R. Navarro,2 K. Nayak,81 R. Nayak,48 T. K. Nayak,137 S. Nazarenko,102 A. Nedosekin,55 R. A. Negrao De Oliveira,35 L. Nellen,63 F. Ng,126 M. Nicassio,100 M. Niculescu,59 J. Niedziela,35 B. S. Nielsen,83 S. Nikolaev,82 S. Nikulin,82 V. Nikulin,88 F. Noferini,12,107 P. Nomokonov,68 G. Nooren,54 J. C. C. Noris,2J. Norman,128 A. Nyanin,82 J. Nystrand,22 H. Oeschler,96 S. Oh,141 A. Ohlson,35 T. Okubo,47 L. Olah,140 J. Oleniacz,138 A. C. Oliveira Da Silva,123 M. H. Oliver,141 J. Onderwaater,100 C. Oppedisano,113 R. Orava,46 M. Oravec,118 A. Ortiz Velasquez,63 A. Oskarsson,34 J. Otwinowski,120 K. Oyama,78 M. Ozdemir,61 Y. Pachmayer,96 V. Pacik,83 D. Pagano,26,135 P. Pagano,30 G. Pai´ c,63 S. K. Pal,137 P. Palni,7J. Pan,139 A. K. Pandey,48 V. Papikyan,1G. S. Pappalardo,109 P. Pareek,49 J. Park,51 W. J. Park,100 S. Parmar,90 A. Passfeld,62 V. Paticchio,106 R. N. Patra,137 B. Paul,113 H. Pei,7T. Peitzmann,54 X. Peng,7H. Pereira Da Costa,15 D. Peresunko,82,77 E. Perez Lezama,61 V. Peskov,61 Y. Pestov,5V. Petrᡠcek,39 V. Petrov,114 M. Petrovici,80 C. Petta,28 S. Piano,112 M. Pikna,38 P. Pillot,116 L. O. D. L. Pimentel,83 O. Pinazza,107,35 L. Pinsky,126 D. B. Piyarathna,126 M. Płosko´ n,76 M. Planinic,133 J. Pluta,138 S. Pochybova,140 P. L. M. Podesta-Lerma,122 M. G. Poghosyan,87 B. Polichtchouk,114 N. Poljak,133 W. Poonsawat,117 A. Pop,80 H. Poppenborg,62 S. Porteboeuf-Houssais,72 J. Porter,76 J. Pospisil,86 S. K. Prasad,4R. Preghenella,107,35 F. Prino,113 C. A. Pruneau,139 I. Pshenichnov,53 M. Puccio,26 G. Puddu,24 P. Pujahari,139 V. Punin,102 J. Putschke,139 H. Qvigstad,21 A. Rachevski,112 S. Raha,4S. Rajput,93 J. Rak,127 A. Rakotozafindrabe,15 L. Ramello,32 F. Rami,66 D. B. Rana,126 R. Raniwala,94 S. Raniwala,94 S. S. Räsänen,46 B. T. Rascanu,61 D. Rathee,90 V. Ratza,45 I. Ravasenga,26 K. F. Read,129,87 K. Redlich,79 A. Rehman,22 P. Reichelt,61 F. Reidt,96,35 X. Ren,7R. Renfordt,61 A. R. Reolon,74 A. Reshetin,53 K. Reygers,96 V. Riabov,88 R. A. Ricci,75 T. Richert,34,54 M. Richter,21 P. Riedler,35 W. Riegler,35 F. Riggi,28 C. Ristea,59 M. Rodríguez Cahuantzi,2K. Røed,21 E. Rogochaya,68 D. Rohr,42 D. Röhrich,22 F. Ronchetti,74,35 L. Ronflette,116 P. Rosnet,72 A. Rossi,29 F. Roukoutakis,91 A. Roy,49 C. Roy,66 P. Roy,103 A. J. Rubio Montero,10 R. Rui,25 R. Russo,26 E. Ryabinkin,82 Y. Ryabov,88 A. Rybicki,120 S. Saarinen,46 S. Sadhu,137 S. Sadovsky,114 K. Šafaˇ rík,35 B. Sahlmuller,61 B. Sahoo,48 P. Sahoo,49 R. Sahoo,49 S. Sahoo,58 P. K. Sahu,58 J. Saini,137 S. Sakai,132,74 M. A. Saleh,139 J. Salzwedel,19 S. Sambyal,93 V. Samsonov,88,77 A. Sandoval,65 M. Sano,132 D. Sarkar,137 N. Sarkar,137 P. Sarma,44 M. H. P. Sas,54 E. Scapparone,107 F. Scarlassara,29 R. P. Scharenberg,98 C. Schiaua,80 R. Schicker,96 C. Schmidt,100 H. R. Schmidt,95 M. Schmidt,95 J. Schukraft,35 Y. Schutz,35,66,116 K. Schwarz,100 K. Schweda,100 G. Scioli,27 E. Scomparin,113 R. Scott,129 M. Šefˇ cík,40 J. E. Seger,89 Y. Sekiguchi,131 D. Sekihata,47 I. Selyuzhenkov,100 K. Senosi,67 S. Senyukov,3,35 E. Serradilla,10,65 P. Sett,48 A. Sevcenco,59 A. Shabanov,53 A. Shabetai,116 O. Shadura,3R. Shahoyan,35 A. Shangaraev,114 A. Sharma,93 A. Sharma,90 M. Sharma,93 M. Sharma,93 N. Sharma,90,129 A. I. Sheikh,137 K. Shigaki,47 Q. Shou,7K. Shtejer,26,9Y. Sibiriak,82 S. Siddhanta,108 K. M. Sielewicz,35 T. Siemiarczuk,79 D. Silvermyr,34 C. Silvestre,73 G. Simatovic,133 G. Simonetti,35 R. Singaraju,137 034904-15 J. ADAM et al. PHYSICAL REVIEW C 96, 034904 (2017) R. Singh,81 V. Singhal,137 T. Sinha,103 B. Sitar,38 M. Sitta,32 T. B. Skaali,21 M. Slupecki,127 N. Smirnov,141 R. J. M. Snellings,54 T. W. Snellman,127 J. Song,99 M. Song,142 Z. Song,7F. Soramel,29 S. Sorensen,129 F. Sozzi,100 E. Spiriti,74 I. Sputowska,120 B. K. Srivastava,98 J. Stachel,96 I. Stan,59 P. Stankus,87 E. Stenlund,34 G. Steyn,67 J. H. Stiller,96 D. Stocco,116 P. Strmen,38 A. A. P. Suaide,123 T. Sugitate,47 C. Suire,52 M. Suleymanov,16 M. Suljic,25 R. Sultanov,55 M. Šumbera,86 S. Sumowidagdo,50 K. Suzuki,115 S. Swain,58 A. Szabo,38 I. Szarka,38 A. Szczepankiewicz,138 M. Szymanski,138 U. Tabassam,16 J. Takahashi,124 G. J. Tambave,22 N. Tanaka,132 M. Tarhini,52 M. Tariq,18 M. G. Tarzila,80 A. Tauro,35 G. Tejeda Muñoz,2A. Telesca,35 K. Terasaki,131 C. Terrevoli,29 B. Teyssier,134 D. Thakur,49 D. Thomas,121 R. Tieulent,134 A. Tikhonov,53 A. R. Timmins,126 A. Toia,61 S. Tripathy,49 S. Trogolo,26 G. Trombetta,33 V. Trubnikov,3W. H. Trzaska,127 T. Tsuji,131 A. Tumkin,102 R. Turrisi,110 T. S. Tveter,21 K. Ullaland,22 E. N. Umaka,126 A. Uras,134 G. L. Usai,24 A. Utrobicic,133 M. Vala,56 J. Van Der Maarel,54 J. W. Van Hoorne,35 M. van Leeuwen,54 T. Vanat,86 P. Vande Vyvre,35 D. Varga,140 A. Vargas,2M. Vargyas,127 R. Varma,48 M. Vasileiou,91 A. Vasiliev,82 A. Vauthier,73 O. Vázquez Doce,97,36 V. Vechernin,136 A. M. Veen,54 A. Velure,22 E. Vercellin,26 S. Vergara Limón,2R. Vernet,8R. Vértesi,140 L. Vickovic,119 S. Vigolo,54 J. Viinikainen,127 Z. Vilakazi,130 O. Villalobos Baillie,104 A. Villatoro Tello,2A. Vinogradov,82 L. Vinogradov,136 T. Virgili,30 V. Vislavicius,34 A. Vodopyanov,68 M. A. Völkl,96 K. Voloshin,55 S. A. Voloshin,139 G. Volpe,33,140 B. von Haller,35 I. Vorobyev,36,97 D. Voscek,118 D. Vranic,35,100 J. Vrláková,40 B. Wagner,22 J. Wagner,100 H. Wang,54 M. Wang,7D. Watanabe,132 Y. Watanabe,131 M. Weber,115 S. G. Weber,100 D. F. Weiser,96 J. P. Wessels,62 U. Westerhoff,62 A. M. Whitehead,92 J. Wiechula,61 J. Wikne,21 G. Wilk,79 J. Wilkinson,96 G. A. Willems,62 M. C. S. Williams,107 B. Windelband,96 M. Winn,96 S. Yalcin,71 P. Yang,7S. Yano,47 Z. Yin,7 H. Yokoyama,73,132 I.-K. Yoo,35,99 J. H. Yoon,51 V. Yurchenko,3V. Zaccolo,83 A. Zaman,16 C. Zampolli,35,107 H. J. C. Zanoli,123 S. Zaporozhets,68 N. Zardoshti,104 A. Zarochentsev,136 P. Závada,57 N. Zaviyalov,102 H. Zbroszczyk,138 M. Zhalov,88 H. Zhang,7,22 X. Zhang,76,7Y. Zhang,7C. Zhang,54 Z. Zhang,7C. Zhao,21 N. Zhigareva,55 D. Zhou,7Y. Zhou,83 Z. Zhou,22 H. Zhu,22,7J. Zhu,116,7A. Zichichi,27,12 A. Zimmermann,96 M. B. Zimmermann,35,62 G. Zinovjev,3and J. Zmeskal115 (ALICE Collaboration) 1A. I. Alikhanyan National Science Laboratory (Yerevan Physics Institute) Foundation, Yerevan, Armenia 2Benemérita Universidad Autónoma de Puebla, Puebla, Mexico 3Bogolyubov Institute for Theoretical Physics, Kiev, Ukraine 4Bose Institute, Department of Physics and Centre for Astroparticle Physics and Space Science (CAPSS), Kolkata, India 5Budker Institute for Nuclear Physics, Novosibirsk, Russia 6California Polytechnic State University, San Luis Obispo, California 93407, USA 7Central China Normal University, Wuhan, China 8Centre de Calcul de l’IN2P3, Villeurbanne, Lyon, France 9Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN), Havana, Cuba 10Centro de Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain 11Centro de Investigación y de Estudios Avanzados (CINVESTAV), Mexico City and Mérida, Mexico 12Centro Fermi-Museo Storico della Fisica e Centro Studi e Ricerche “Enrico Fermi,” Rome, Italy 13Chicago State University, Chicago, Illinois 60628, USA 14China Institute of Atomic Energy, Beijing, China 15Commissariat à l’Energie Atomique, IRFU, Saclay, France 16COMSATS Institute of Information Technology (CIIT), Islamabad, Pakistan 17Departamento de Física de Partículas and IGFAE, Universidad de Santiago de Compostela, Santiago de Compostela, Spain 18Department of Physics, Aligarh Muslim University, Aligarh, India 19Department of Physics, Ohio State University, Columbus, Ohio 43210, USA 20Department of Physics, Sejong University, Seoul, South Korea 21Department of Physics, University of Oslo, Oslo, Norway 22Department of Physics and Technology, University of Bergen, Bergen, Norway 23Dipartimento di Fisica dell’Università “La Sapienza” and Sezione INFN, Rome, Italy 24Dipartimento di Fisica dell’Università and Sezione INFN, Cagliari, Italy 25Dipartimento di Fisica dell’Università and Sezione INFN, Trieste, Italy 26Dipartimento di Fisica dell’Università and Sezione INFN, Turin, Italy 27Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN, Bologna, Italy 28Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN, Catania, Italy 29Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN, Padova, Italy 30Dipartimento di Fisica “E. R. Caianiello” dell’Università and Gruppo Collegato INFN, Salerno, Italy 31Dipartimento DISAT del Politecnico and Sezione INFN, Turin, Italy 32Dipartimento di Scienze e Innovazione Tecnologica dell’Università del Piemonte Orientale and INFN Sezione di Torino, Alessandria, Italy 33Dipartimento Interateneo di Fisica “M. Merlin” and Sezione INFN, Bari, Italy 34Division of Experimental High Energy Physics, University of Lund, Lund, Sweden 034904-16 EVOLUTION OF THE LONGITUDINAL AND AZIMUTHAL . . . PHYSICAL REVIEW C 96, 034904 (2017) 35European Organization for Nuclear Research (CERN), Geneva, Switzerland 36Excellence Cluster Universe, Technische Universität München, Munich, Germany 37Faculty of Engineering, Bergen University College, Bergen, Norway 38Faculty of Mathematics, Physics and Informatics, Comenius University, Bratislava, Slovakia 39Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University in Prague, Prague, Czech Republic 40Faculty of Science, P.J. Šafárik University, Košice, Slovakia 41Faculty of Technology, Buskerud and Vestfold University College, Tonsberg, Norway 42Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe-Universität Frankfurt, Frankfurt, Germany 43Gangneung-Wonju National University, Gangneung, South Korea 44Gauhati University, Department of Physics, Guwahati, India 45Helmholtz-Institut für Strahlenund Kernphysik, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany 46Helsinki Institute of Physics (HIP), Helsinki, Finland 47Hiroshima University, Hiroshima, Japan 48Indian Institute of Technology Bombay (IIT), Mumbai, India 49Indian Institute of Technology Indore, Indore, India 50Indonesian Institute of Sciences, Jakarta, Indonesia 51Inha University, Incheon, South Korea 52Institut de Physique Nucléaire d’Orsay (IPNO), Université Paris-Sud, CNRS-IN2P3, Orsay, France 53Institute for Nuclear Research, Academy of Sciences, Moscow, Russia 54Institute for Subatomic Physics of Utrecht University, Utrecht, Netherlands 55Institute for Theoretical and Experimental Physics, Moscow, Russia 56Institute of Experimental Physics, Slovak Academy of Sciences, Košice, Slovakia 57Institute of Physics, Academy of Sciences of the Czech Republic, Prague, Czech Republic 58Institute of Physics, Bhubaneswar, India 59Institute of Space Science (ISS), Bucharest, Romania 60Institut für Informatik, Johann Wolfgang Goethe-Universität Frankfurt, Frankfurt, Germany 61Institut für Kernphysik, Johann Wolfgang Goethe-Universität Frankfurt, Frankfurt, Germany 62Institut für Kernphysik, Westfälische Wilhelms-Universität Münster, Münster, Germany 63Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Mexico City, Mexico 64Instituto de Física, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil 65Instituto de Física, Universidad Nacional Autónoma de México, Mexico City, Mexico 66Institut Pluridisciplinaire Hubert Curien (IPHC), Université de Strasbourg, CNRS-IN2P3, Strasbourg, France 67iThemba LABS, National Research Foundation, Somerset West, South Africa 68Joint Institute for Nuclear Research (JINR), Dubna, Russia 69Konkuk University, Seoul, South Korea 70Korea Institute of Science and Technology Information, Daejeon, South Korea 71KTO Karatay University, Konya, Turkey 72Laboratoire de Physique Corpusculaire (LPC), Clermont Université, Université Blaise Pascal, CNRS-IN2P3, Clermont-Ferrand, France 73Laboratoire de Physique Subatomique et de Cosmologie, Université Grenoble-Alpes, CNRS-IN2P3, Grenoble, France 74Laboratori Nazionali di Frascati, INFN, Frascati, Italy 75Laboratori Nazionali di Legnaro, INFN, Legnaro, Italy 76Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA 77Moscow Engineering Physics Institute, Moscow, Russia 78Nagasaki Institute of Applied Science, Nagasaki, Japan 79National Centre for Nuclear Studies, Warsaw, Poland 80National Institute for Physics and Nuclear Engineering, Bucharest, Romania 81National Institute of Science Education and Research, Bhubaneswar, India 82National Research Centre Kurchatov Institute, Moscow, Russia 83Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark 84Nikhef, Nationaal instituut voor subatomaire fysica, Amsterdam, Netherlands 85Nuclear Physics Group, STFC Daresbury Laboratory, Daresbury, United Kingdom 86Nuclear Physics Institute, Academy of Sciences of the Czech Republic, ˇ Rež u Prahy, Czech Republic 87Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA 88Petersburg Nuclear Physics Institute, Gatchina, Russia 89Physics Department, Creighton University, Omaha, Nebraska 68102, USA 90Physics Department, Panjab University, Chandigarh, India 91Physics Department, University of Athens, Athens, Greece 92Physics Department, University of Cape Town, Cape Town, South Africa 93Physics Department, University of Jammu, Jammu, India 034904-17 J. ADAM et al. PHYSICAL REVIEW C 96, 034904 (2017) 94Physics Department, University of Rajasthan, Jaipur, India 95Physikalisches Institut, Eberhard Karls Universität Tübingen, Tübingen, Germany 96Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg, Germany 97Physik Department, Technische Universität München, Munich, Germany 98Purdue University, West Lafayette, Indiana 47907, USA 99Pusan National University, Pusan, South Korea 100Research Division and ExtreMe Matter Institute EMMI, GSI Helmholtzzentrum für Schwerionenforschung, Darmstadt, Germany 101Rudjer Boškovi´ c Institute, Zagreb, Croatia 102Russian Federal Nuclear Center (VNIIEF), Sarov, Russia 103Saha Institute of Nuclear Physics, Kolkata, India 104School of Physics and Astronomy, University of Birmingham, Birmingham, United Kingdom 105Sección Física, Departamento de Ciencias, Pontificia Universidad Católica del Perú, Lima, Peru 106Sezione INFN, Bari, Italy 107Sezione INFN, Bologna, Italy 108Sezione INFN, Cagliari, Italy 109Sezione INFN, Catania, Italy 110Sezione INFN, Padova, Italy 111Sezione INFN, Rome, Italy 112Sezione INFN, Trieste, Italy 113Sezione INFN, Turin, Italy 114SSC IHEP of NRC Kurchatov institute, Protvino, Russia 115Stefan Meyer Institut für Subatomare Physik (SMI), Vienna, Austria 116SUBATECH, Ecole des Mines de Nantes, Université de Nantes, CNRS-IN2P3, Nantes, France 117Suranaree University of Technology, Nakhon Ratchasima, Thailand 118Technical University of Košice, Košice, Slovakia 119Technical University of Split FESB, Split, Croatia 120The Henryk Niewodniczanski Institute of Nuclear Physics, Polish Academy of Sciences, Cracow, Poland 121Physics Department, The University of Texas at Austin, Austin, Texas 78712, USA 122Universidad Autónoma de Sinaloa, Culiacán, Mexico 123Universidade de São Paulo (USP), São Paulo, Brazil 124Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil 125Universidade Federal do ABC, Santo Andre, Brazil 126University of Houston, Houston, Texas 77004, USA 127University of Jyväskylä, Jyväskylä, Finland 128University of Liverpool, Liverpool, United Kingdom 129University of Tennessee, Knoxville, Tennessee 37996, USA 130University of the Witwatersrand, Johannesburg, South Africa 131University of Tokyo, Tokyo, Japan 132University of Tsukuba, Tsukuba, Japan 133University of Zagreb, Zagreb, Croatia 134Université de Lyon, Université Lyon 1, CNRS/IN2P3, IPN-Lyon, Villeurbanne, Lyon, France 135Università di Brescia, Brescia, Italy 136V. Fock Institute for Physics, St. Petersburg State University, St. Petersburg, Russia 137Variable Energy Cyclotron Centre, Kolkata, India 138Warsaw University of Technology, Warsaw, Poland 139Wayne State University, Detroit, Michigan 48202, USA 140Wigner Research Centre for Physics, Hungarian Academy of Sciences, Budapest, Hungary 141Yale University, New Haven, Connecticut 06520, USA 142Yonsei University, Seoul, South Korea 143Zentrum für Technologietransfer und Telekommunikation (ZTT), Fachhochschule Worms, Worms, Germany *Deceased. †Also at Georgia State University, Atlanta, Georgia, USA. ‡Also at Department of Applied Physics, Aligarh Muslim University, Aligarh, India. §Also at M. V. Lomonosov Moscow State University, D. V. Skobeltsyn Institute of Nuclear Physics, Moscow, Russia. 034904-18