Multiplicity dependence of charged pion, kaon, and (anti)proton production at large transverse momentum in p–Pb collisions at √sNN = 5.02 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. Multiplicity dependence of charged pion, kaon, and (anti)proton production at large transverse momentum in p–Pb collisions at √sNN = 5.02 TeV ALICE Collaboration ALICE Collaboration. (2016). Multiplicity dependence of charged pion, kaon, and (anti)proton production at large transverse momentum in p–Pb collisions at √sNN = 5.02 TeV. Physics Letters B, 760, 720-735. https://doi.org/10.1016/j.physletb.2016.07.050 2016 Physics Letters B 760 (2016) 720–735 Contents lists available at ScienceDirect Physics Letters B www.elsevier.com/locate/physletb Multiplicity dependence of charged pion, kaon, and (anti)proton production at large transverse momentum in p–Pb collisions at √sNN =5.02 TeV .ALICE Collaboration a r t i c l e i n f o a b s t r a c t Article history: Received 16 January 2016 Received in revised form 13 July 2016 Accepted 20 July 2016 Available online 22 July 2016 Editor: L. Rolandi The production of charged pions, kaons and (anti)protons has been measured at mid-rapidity (−0.5 < y <0) in p–Pb collisions at √sNN =5.02 TeV using the ALICE detector at the LHC. Exploiting particle identification capabilities at high transverse momentum (pT), the previously published pTspectra have been extended to include measurements up to 20 GeV/cfor seven event multiplicity classes. The pT spectra for pp collisions at √s=7 TeV, needed to interpolate a pp reference spectrum, have also been extended up to 20 GeV/cto measure the nuclear modification factor (RpPb) in non-single diffractive p–Pb collisions. At intermediate transverse momentum (2 <pT<10 GeV/c) the proton-to-pion ratio increases with multiplicity in p–Pb collisions, a similar effect is not present in the kaon-to-pion ratio. The pTdependent structure of such increase is qualitatively similar to those observed in pp and heavy-ion collisions. At high pT(>10 GeV/c), the particle ratios are consistent with those reported for pp and Pb–Pb collisions at the LHC energies. At intermediate pTthe (anti)proton RpPb shows a Cronin-like enhancement, while pions and kaons show little or no nuclear modification. At high pTthe charged pion, kaon and (anti)proton RpPb are consistent with unity within statistical and systematic uncertainties. ©2016 The Author. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Funded by SCOAP3. 1. Introduction In heavy-ion collisions at ultra-relativistic energies, it is well established that a strongly coupled Quark–Gluon-Plasma (sQGP) is formed [1–5]. Some of the characteristic features of the sQGP are strong collective flow and opacity to jets. The collective behavior is observed both as an azimuthal anisotropy of produced particles [6], where the magnitude is described by almost ideal (reversible) hydrodynamics, and as a hardening of pTspectra for heavier hadrons, such as protons, by radial flow [7]. Jet quenching is observed as a reduction of both high pTparticles [8,9] and also fully reconstructed jets [10]. The interpretation of these sQGP properties requires comparisons with reference measurements like pp and p–A collisions. Recent measurements in high multiplicity pp, p–A and d–A collisions at different energies have revealed strong flow-like effects even in these small systems [11–20]. The origin of these phenomena is debated [21–29] and the data reported here provide further inputs to this discussion. E-mail address: [email protected]. In a previous work, we reported the evidence of radial flowlike patterns in p–Pb collisions [30]. This effect was found to increase with increasing event multiplicity and to be qualitatively consistent with calculations which incorporate the hydrodynamical evolution of the system. It was also discussed that in small systems, mechanisms like color-reconnection may produce radial flow-like effects. The present paper reports complementary measurements covering the intermediate pTregion (2–10 GeV/c) and the high-pTregion (10–20GeV/c) exploiting the capabilities of the High Momentum Particle Identification Detector (HMPID) and the Time Projection Chamber (TPC). In this way, high precision measurements are achieved in the intermediate pTregion where cold nuclear matter effects like the Cronin enhancement [31,32] have been reported by previous experiments [33,34], and where the particle ratios, e.g., the proton (kaon) production relative to that of pions, are affected by large final state effects in central Pb–Pb collisions [35]. Particle ratios are expected to be modified by flow, but hydrodynamics is typically expected to be applicable only up to a few GeV/c[36]. At higher pT, ideas such as parton recombination have been proposed leading to baryon–meson effects [37]. In this way the new dataset complements the lower pTresults. http://dx.doi.org/10.1016/j.physletb.2016.07.050 0370-2693/©2016 The Author. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Funded by SCOAP3. ALICE Collaboration / Physics Letters B 760 (2016) 720–735 721 In addition, particle identification at large transverse momenta in p–Pb collisions provides new constraints on the nuclear parton distribution functions (nPDF) which are key inputs in interpreting a large amount of experimental data like d–Au and deep inelastic scattering [38]. Finally, the measurement is also important to study the particle species dependency of the nuclear modification factor (RpPb), to better understand parton energy loss mechanisms in heavy-ion collisions. In this paper, the charged pion, kaon and (anti)proton RpPb are reported for non-single diffractive (NSD) p–Pb collisions. The pp reference spectra for this measurement were obtained using interpolations of data at different collision energies. The already published pTspectra for inelastic (INEL) pp collisions at √s=7TeV[39] were extended up to 20 GeV/cand the results are presented here for the first time. These measurements together with the results for INEL pp collisions at √2=2.76 TeV (pT<20 GeV/c)[35] were used to determine pp reference spectra at √s=5.02 TeV using the interpolation method described in [40]. The paper is organized as follows. In Sec. 2the ALICE detector as well as the event and track selections are discussed. The analysis procedures for particle identification using the HMPID and TPC detectors are outlined in Sec. 3and Sec. 4, respectively. Section 5 presents the results and discussions. Finally, Sec. 6summarizes the main results. 2. Data sample, event and track selection The results are obtained using data collected with the ALICE detector during the 2013 p–Pb run at √sNN =5.02 TeV. The detailed description of the ALICE detector can be found in [41] and the performance during run 1 (2009–2013) is described in [42]. Because of the LHC 2-in-1 magnet design, it is impossible to adjust the energy of the proton and lead-ion beams independently. They are 4TeVper Zwhich gives different energies due to the different Z/Aof the colliding protons and lead ions. The nucleon– nucleon center-of-mass system is moving in the laboratory frame with a rapidity of yNN =−0.465 in the direction of the proton beam rapidity. In the following, ylab (ηlab) are used to indicate the (pseudo)rapidity in the laboratory reference frame, whereas y(η) denotes the (pseudo)rapidity in the center-of-mass reference system where the Pb beam is assigned positive rapidity. In the analysis of the p–Pb data, the event selection follows that used in the analysis of inclusive charged particle production [43]. The minimum bias (MB) trigger signal was provided by the V0 counters [44], which contain two arrays of 32 scintillator tiles each covering the full azimuth within 2.8 <ηlab <5.1(V0A) and −3.7 <ηlab <−1.7(V0C). The signal amplitude and arrival time collected in each tile were recorded. A coincidence of signals in both V0A and V0C detectors was required to remove contamination from single diffractive and electromagnetic events. In the offline analysis, background events were further suppressed by requiring the arrival time of signals on the neutron Zero Degree Calorimeter A, which is positioned in the Pb-going direction, to be compatible with a nominal p–Pb collision occurring close to the nominal interaction point. The estimated mean number of interactions per bunch crossing was below 1% in the sample chosen for this analysis. Due to the weak correlation between collision geometry and multiplicity, the particle production in p–Pb collisions is studied in event multiplicity classes instead of centralities [45]. The multiplicity classes are defined using the total charge deposited in the V0A detector as in [30], where V0A is positioned in the Pb-going direction. The MB results have been normalized to the total number of NSD events using a trigger and vertex reconstruction efficiency correction which amounts to 3.6% ±3.1% [46]. The multiplicity dependent results have been normalized to the visible Table 1 Transverse momentum ranges (GeV/c) covered by the individual and combined analyses for pp collisions at √s=7TeVand p–Pb collisions at √sNN =5.02 TeV. Analysis π++π−K++K−p+¯ p pp Published [39]a0.1–3.0 0.2–6.0 0.3–6.0 TPC dE/dxrel. rise 2–20 3–20 3–20 p–Pb Published [30]b0.1–3.0 0.2–2.5 0.3–4.0 HMPID 1.5–4.0 1.5–4.0 1.5–6.0 TPC dE/dxrel. rise 2–20 3–20 3–20 aIncluded detectors: ITS, TPC, Time-of-Flight (TOF), HMPID. The results also include the kink-topology identification of the weak decays of charged kaons. bIncluded detectors: ITS, TPC, TOF. (triggered) cross-section correcting for the vertex reconstruction efficiency (this was not done in [30]). This correction is of the order of 5% for the lowest V0A multiplicity class (80–100%) and negligible for the other multiplicity classes (<1%). In the √s=7TeVpp analysis the MB trigger required a hit in the two innermost layers of the Inner Tracking System (ITS), the Silicon Pixel Detector (SPD), or in at least one of the V0 scintillator arrays in coincidence with the arrival of proton bunches from both directions. The offline analysis to eliminate background was done using the time information provided by the V0 detectors in correlation with the number of clusters and tracklets1in the SPD. Tracks are required to be reconstructed in both the ITS and the TPC. Additional track selection criteria are the same as in [47] and based on the number of space points, the quality of the track fit, and the distance of closest approach to the reconstructed collision vertex. Charged tracks where the identity of the particle has changed due to a weak decay, e.g., K−→μ−+¯ νμ, are identified by the tracking algorithm due to their distinct kink topologies [48] and rejected in this analysis. The remaining contamination is negligible (1%). In order to have the same kinematic coverage as used in the p–Pb low pTanalysis [30], the tracks were selected in the pseudorapidity interval −0.5 <η<0. In addition, for the HMPID analysis it is required that the tracks are propagated and matched to a primary ionization cluster in the Multi-Wire Proportional Chamber (MWPC) gap of the HMPID detector [39,47]. The published results of charged pion, kaon and (anti)proton production at low pTfor pp [39] and p–Pb [30] collisions at √s=7 TeV and √sNN =5.02 TeV, respectively, used different Particle IDentification (PID) detectors and techniques. A summary of the pTranges covered by the published analyses and the analyses presented in this paper can be found in Table 1. In the following, the analysis techniques used to obtain the identified particle pTspectra in the intermediate and high-pT ranges using HMPID and TPC will be discussed. 3. HMPID analysis The HMPID detector [49] is located about 5 m from the beam axis, covering a limited acceptance of |ηlab| <0.5 and 1.2◦< φ<58.5◦, that corresponds to ∼5% of the TPC geometrical acceptance (2πin azimuthal angle and the pseudo-rapidity interval |η| <0.9[50]) for high pTtracks. The HMPID analysis uses ∼9 ×107minimum-bias p–Pb events at √sNN =5.02 TeV. The event and track selection and the analysis technique are similar to those described in [39,47]. It is required that tracks are propagated and matched to a primary ionization cluster in the Multi-Wire Proportional Chamber (MWPC) gap of the HMPID detector. The PID in the HMPID is done by measuring the Cherenkov angle, θCh [49]: 1Tracklets are pairs of hits from the two layers of the SPD which make a line pointing back to the collision vertex. 722 ALICE Collaboration / Physics Letters B 760 (2016) 720–735 Fig. 1. (Color online.) Cherenkov angle measured in the HMPID as a function of the track momentum in p–Pb collisions at √sNN =5.02 TeV for the 0–5% V0A multiplicity class (see the text for further details). The dashed lines represent the expected curves calculated using Eq. (1) for each particle species. cosθCh =1 nβ=⇒ θCh =arccosp2+m2 np ,(1) where nis the refractive index of the radiator used (liquid C6F14 with n =1.29 at Eph =6.68 eV and temperature T=20 ◦C), pand mare the momentum and the mass of the given particle, respectively. The measurement of the single photon θCh angle in the HMPID requires the knowledge of the track parameters, which are estimated by the track extrapolation from the central tracking detectors up to the radiator volume, where the Cherenkov photons are emitted. Only one charged particle cluster is associated to each extrapolated track, selected as the closest cluster to the extrapolated track point on the cathode plane. To reject the fake cluster-match associations in the detector, a selection on the distance d(track-MIP)computed on the cathode plane between the track extrapolation point and the reconstructed charged-particle cluster position is applied. The distance has to be less than 5 cm, independent of track momentum. Starting from the photon cluster coordinates on the photocathode, a back-tracking algorithm calculates the corresponding emission angle. The Cherenkov photons are selected by the Hough Transform Method (HTM) [51] that discriminates the signal from the background. For a given track, the Cherenkov angle θCh is then computed as the weighted mean of the single photon angles selected by the HTM. Fig. 1 shows the θCh as a function of the track momentum. The reconstructed angle distribution for a given momentum interval is fitted by a sum of three Gaussian distributions, corresponding to the signals from pions, kaons, and protons. The fitting is done in two steps. In the first step the initial values of fit parameters are set to the expected values. The mean values, θChi, are obtained from Eq. (1), tuning the refractive index to match the observed Cherenkov angles, and the resolution values are taken from a Monte Carlo simulation of the detector response. After this first step, the pTdependences of the mean and width are fitted with the function given by Eq. (1) and a polynomial one, respectively. In the second step, the fitting is repeated with the yields as the only free parameters, constraining the mean and resolution values to the fitted value. The second iteration is particularly important at high pTwhere the separation between different species is reduced. Fig. 2 gives examples of fits to the reconstructed Cherenkov angle distributions in two narrow pTintervals for the 0–5% multiplicity class. The raw yields are then corrected by the total reconstruction efficiency given by the convolution of the tracking, PID efficiency, and distance cut correction. The tracking efficiency, convoluted with the geometrical Fig. 2. (Color online.) Distributions of the Cherenkov angle measured in the HMPID for positive tracks having pTbetween 2.5–2.6 GeV/c(left) and between 3.8–4.0 GeV/c(right), in p–Pb collisions at √sNN =5.02 TeV for the 0–5% V0A multiplicity class (see the text for further details). acceptance of the detector, has been evaluated using Monte Carlo simulations. For all three particle species this efficiency increases from ∼5% at 1.5 GeV/cup to ∼6% at high pT. The PID efficiency is determined by the Cherenkov angle reconstruction efficiency. It has been computed by means of Monte-Carlo simulations and it reaches ∼90% for particles with velocity β∼1, with no significant difference between positive and negative tracks. The distance cut correction, defined as the ratio between the number of the tracks that pass the cut on d(track-MIP)and all the tracks in the detector acceptance, has been evaluated from data. It is momentum dependent, and it is equal to ∼53% at 1.5 GeV/c, reaches ∼70% for particles with velocity β∼1. A small difference between positive and negative tracks is present; negative tracks having a distance correction ∼2% lower than the positive ones. This effect is caused by a radial residual misalignment of the HMPID chambers and an imperfect estimation of the energy loss in the material traversed by the track. Tracking efficiency, PID efficiency and distance cut correction do not show variation with the event track multiplicity. 3.1. Systematic uncertainties The systematic uncertainty on the results of the HMPID analysis has contributions from tracking, PID and tracks association [39, 47]. The uncertainties related to the tracking have been estimated by changing the track selection cuts individually, e.g. the number of crossed readout rows in the TPC and the value of the track’s χ2normalized to the number of TPC clusters. To estimate the PID contribution, the parameters (mean and resolution) of the fit function used to extract the raw yields were varied by a reasonable quantity, leaving them free in a given range; the range chosen for the mean values is [θCh −σ, θCh +σ] and for the resolution [σ−0.1σ, σ+0.1σ]. A variation of 10% of the resolution corresponds to its maximum expected variation when taking into account the different running conditions of the detector during data taking which have an impact on its performance. When the means are changed, the resolution values are fixed to the default value and vice versa. The variation of parameters is done for the three Gaussians (corresponding to the three particle species) simultaneously. In addition, the uncertainty of the association of the track to the charged particle signal is obtained by varying the default value of the distance cut required for the match by ±1cm. These contributions do not vary with the collision multiplicity. A summary of the different contributions to the systematic uncertainty for the HMPID p–Pb analysis is shown in Table 2. 4. TPC dE/dxrelativistic rise analysis The relativistic rise regime of the specific energy loss, dE/dx, measured by the TPC allows identification of charged pions, kaons, ALICE Collaboration / Physics Letters B 760 (2016) 720–735 723 Table 2 Main sources of systematic uncertainties for the HMPID p–Pb analysis. Effect π++π−K++K−p+¯ p pTvalue (GeV/c) 2.5 4 2.5 4 2.5 4 PID 6% 12% 6% 12% 4% 5% Tracking efficiency 6% 6% 7% Distance cut correction 6% 2% 6% 2% 4% 2% Fig. 3. (Color online.) Specific energy loss, dE/dx, as a function of momentum pin the pseudorapidity range −0.5 <η<−0.375 for minimum bias p–Pb collisions. In each momentum bin the dE/dxspectra have been normalized to have unit integrals and only bins with more than 2% of the counts are shown (making electrons not visible in the figure, except at very low momentum). The curves show the dE/dx response for pions, kaons, protons and electrons. and (anti)protons up to pT=20 GeV/c. The results presented in this paper were obtained using the method detailed in [47]. In this analysis, around 8 ×107(4.7 ×107) p–Pb (pp) MB triggered events were used. The event and track selection has already been discussed in Section 2. As discussed in [47], the dE/dxis calibrated taking into account chamber gain variations, track curvature and diffusion, to obtain a response that essentially only depends on βγ. Inherently, tracks at forward rapidity will have better resolution due to longer integrated track-lengths, so in order to analyze homogeneous samples the analysis is performed in four ηintervals. Samples of topologically identified pions (from K0 Sdecays), protons (from decays) and electrons (from γconversions) were used to parametrize the Bethe–Bloch response, dE/dx(βγ), and the relative resolution, σdE/dx(dE/dx)[47]. For the p–Pb data, these response functions are found to be slightly multiplicity dependent (the dE/dx changes by ∼0.4% and the sigma by ∼2.0%). However, a single set of functions is used for all multiplicity intervals, and the dependence is included in the systematic uncertainties. Fig. 3 shows dE/dxas a function of momentum for p–Pb events. The characteristic separation power between particle species in number of standard deviations (Sσ) as a function of p, is shown in Fig. 4 for minimum bias p–Pb collisions. For example, Sσfor pions and kaons is calculated as: Sσ=dE dxπ++π−−dE dxK++K− 0.5σπ++π−+σK++K−.(2) The separation in number of standard deviations is the largest (smallest) between pions and protons (kaons and protons) and it is nearly constant at large momenta. The main part of this analysis is the determination of the relative particle abundances, hereafter called particle fractions, which are defined as the π++π−, K++K−, p +¯ p and e++e−yields normalized to that for inclusive charged particles. Since the TPC dE/dxsignal is Gaussian distributed as illustrated in [47], particle fractions are obtained using four-Gaussian fits to dE/dxdistributions in ηand pintervals. The parameters (mean and width) of the fits are fixed using the parametrized Bethe–Bloch and resolution curves mentioned earlier. Examples of these fits can be seen in Fig. 5 for two momentum intervals, 3.4 <p <3.6GeV/cand 8 <p <9GeV/c. The particle fractions in a pTrange, are obtained as the weighted average of the contributing pintervals. Since the particle fractions as a function of pTare found to be independent of η, they are averaged. The particle fractions measured in p–Pb and pp collisions are corrected for relative efficiency differences using DPMJET [52] and PHOJET [53] Monte Carlo (MC) generators, respectively. Furthermore, the relative pion and proton abundances were corrected for the contamination of secondary particles (feeddown), more details of the method can be found in [47]. The invariant yields, 1/(2πpT)d2N/dydpT, are constructed using two components: the corrected particle fractions and the corrected invariant charged particle yields. For the pp analysis at √s=7TeV, the latter component was taken directly from the published results for inclusive charged particles [40]. However, analogous results for p–Pb data are neither available for neither the kinematic range −0.5 <y <0nor for the different multiplicity classes [54], they were therefore measured here and the results used to determine the invariant yields. 4.1. Systematic uncertainties The systematic uncertainties mainly consist of two components: the first is due to the event and track selection, and the second one is due to the PID. The first component was obtained from the analysis of inclusive charged particles [40,54]. For INEL pp collisions at 7 TeV, the systematic uncertainties have been taken from [40]. For p–Pb collisions, there are no measurements in the ηinterval reported here (−0.5 <η<0); however, it has been shown that the systematic uncertainty exhibits a negligible dependence on ηand multiplicity [45]. Therefore, the systematic uncertainties reported Fig. 4. Separation in number of standard deviations between: pions and protons (left panel), pions and kaons (middle panel), and kaons and protons (right panel). Results for minimum bias p–Pb data and for two specific pseudorapidity intervals are shown. More details can be found in [47]. 724 ALICE Collaboration / Physics Letters B 760 (2016) 720–735 Fig. 5. (Color online.) Four-Gaussian fits (lines) to the dE/dxspectra (markers) for tracks having momentum 3.4 <p <3.6GeV/c(top row) and 8.0 <p <9.0GeV/c(bottom row) within −0.125 <η<0. All of the spectra are normalized to have unit integrals. Columns refer to different V0A multiplicity classes. Individual signals of charged pions, kaons, and (anti)protons are shown as red, green, and blue dashed areas, respectively. The contribution of electrons is not visible and is negligible (<1%). Table 3 Summary of the systematic uncertainties for the charged pion, kaon, and (anti)proton spectra and for the particle ratios. Note that K/π=(K++K−)/(π++π−)and p/π=(p +¯ p)/(π++π−). pT(GeV/c)π++π−K++K−p+¯ pK/πp/π 2.0 10 3.0 10 3.0 10 3.0 10 3.0 10 pp collisions Uncertainty Event and track selectiona7.3% 7.3% 7.3% – – Feed-down correction 0.2% – 1.2% 0.2% 1.2% Efficiency correction 3.2% 3.2% 3.2% 4.5% 4.5% Correction for muons 0.3% 0.5% – – 0.3% 0.5% 0.3% 0.5% Parametrization of Bethe–Bloch and resolution curves 1.8% 1.9% 20% 6.9% 24% 15% 17% 9.0% 17% 19% p–Pb collisions Uncertainty Event and track selectiona3.3% 3.6% 3.3% 3.6% 3.3% 3.6% – – Feed-down correction ≤0.2% – 2.6% 0.7% ≤0.2% 2.6% 0.7% Efficiency correction 3.2% 3.2% 3.2% 4.5% 4.5% Correction for muonsb0.3% 0.4% – – 0.3% 0.4% 0.3% 0.4% Parametrization of Bethe–Bloch and resolution curves Multiplicity classes 0–5% 1.7% 1.9% 17% 8.0% 15% 13% 16% 10.4% 12% 11% 5–10% 1.7% 2.0% 17% 5.6% 16% 12% 18% 7.2% 14% 24% 10–20% 1.6% 1.9% 16% 7.2% 16% 12% 18% 9.5% 16% 15% 20–40% 1.6% 2.0% 16% 6.7% 17% 15% 18% 8.0% 17% 18% 40–60% 1.5% 1.9% 15% 6.5% 17% 12% 18% 8.3% 18% 13% 60–80% 1.6% 1.8% 16% 6.3% 20% 13% 21% 8.3% 22% 18% 80–100% 1.4% 1.5% 13% 5.9% 20% 13% 16% 7.3% 23% 21% aCommon to all species, values taken from [40,54]. bFound to be multiplicity independent. in [54] have been assigned to the identified charged hadron pT spectra for all the V0A multiplicity classes. The second component was measured following the procedure described in [47], where the largest contribution is attributed to the uncertainties in the parameterization of the Bethe–Bloch and resolution curves used to constrain the fits. The uncertainty is calculated by varying the dE/dxand σdE/dxin the particle fraction fits (Fig. 5) within the precision of the dE/dxresponse calibration, ∼1% and 5% for dE/dxand σdE/dx, respectively. A small fraction of this uncertainty was found to be multiplicity dependent, it was estimated as done in the previous ALICE publication [30]. A summary of the main systematic uncertainties on the pT spectra and the particle ratios for p–Pb and pp collisions can be found in Table 3 for two pTintervals. For pions, the main contribution is related to event and track selection and the associated common corrections. In the case of kaons and protons the largest uncertainty is attributed to the parametrization of the dE/dxresponse. For kaons, the uncertainty decreases with pTand increases with multiplicity while for protons the multiplicity dependence is opposite. This variation mainly reflects the changes in the particle ratios with pTand multiplicity. 5. Results and discussions The total systematic uncertainty for all the spectra for a given particle species is factorized for each pTinterval into a multiplic- ALICE Collaboration / Physics Letters B 760 (2016) 720–735 725 Fig. 6. (Color online.) The ratio of individual spectra to the combined spectrum as a function of pTfor pions (left), kaons (middle), and protons (right). From top-to-bottom the rows show the V0A multiplicity class 0–5%, 20–40% and 60–80%. Statistical and uncorrelated systematic uncertainties are shown as vertical error bars and error bands, respectively. Only the pTranges where individual analysis overlap are shown. See the text for further details. Fig. 7. (Color online.) Transverse momentum spectra of charged pions (left), kaons (middle), and (anti)protons (right) measured in p–Pb collisions at √sNN =5.02 TeV. Statistical and systematic uncertainties are plotted as vertical error bars and boxes, respectively. The spectra (measured for NSD events and for different V0A multiplicity classes) have been scaled by the indicated factors in the legend for better visibility. ity independent and multiplicity dependent systematic uncertainty. The transverse momentum distributions obtained from the different analyses are combined in the overlapping pTregion using a weighted average. The weight for the combinations was done according to the total systematic uncertainty to obtain the best overall precision. Since the systematic uncertainties due to normalization and tracking are common to all the analyses, they were added directly to the final combined results. The statistical uncertainties are much smaller and therefore neglected in the combination weights. The multiplicity dependent systematic uncertainty for the combined spectra is also propagated using the same weights. For the results shown in this paper the full systematic uncertainty is always used, but the multiplicity correlated and uncorrelated systematic uncertainties are made available at HepData. Fig. 6 shows examples of the comparisons among the individual analyses and the combined pTspectra, focusing on the overlapping pTregion. 726 ALICE Collaboration / Physics Letters B 760 (2016) 720–735 Fig. 8. (Color online.) Transverse momentum spectra of charged pions (left), kaons (middle), and (anti)protons (right) measured in INEL pp collisions at √s=2.76 TeV and at √s=7TeV. Statistical and systematic uncertainties are plotted as vertical error bars and boxes, respectively. The spectrum at √s=5.02 TeV represents the reference in INEL pp collisions, constructed from measured spectra at √s=2.76 TeV and at √s=7TeV. See the text for further details. Panels on the bottom show the ratio of the measured yields to the interpolated spectra. Only uncertainties of the interpolated spectra are shown. Within systematic and statistical uncertainties the new high-pTre- sults, measured with HMPID and TPC, agree with the published results [30]. Similar agreement is obtained for the pTspectra in INEL pp collisions at 7TeV[39]. 5.1. Transverse momentum spectra and nuclear modification factor The combined charged pion, kaon and (anti)proton pTspectra in p–Pb collisions for different V0A multiplicity classes are shown in Fig. 7. As reported in [30], for pTbelow 2–3 GeV/cthe spectra behave like in Pb–Pb collisions, i.e., the pTdistributions become harder as the multiplicity increases and the change is most pronounced for protons and lambdas. In heavy-ion collisions this effect is commonly attributed to radial flow. For larger momenta, the spectra follow a power-law shape as expected from perturbative QCD. In order to quantify any particle species dependence of the nuclear effects in p–Pb collisions, comparisons to reference pT spectra in pp collisions are needed. In the absence of pp data at √s=5.02 TeV, the reference spectra are obtained by interpolating data measured at √s=2.76 TeV and at √s=7TeV. The invariant cross section for identified hadron production in INEL pp collisions, 1/(2πpT)d2σINEL pp /dydpT, is interpolated in each pTinterval, assuming a power law dependence as a function of √s. The method was cross-checked using events simulated by Pythia 8.201 [55], where the difference between the interpolated and the simulated reference was found to be negligible. The maximum relative systematic uncertainty of the spectra at √s=2.76 TeV and at √s= 7 TeV has been assigned as a systematic uncertainty to the reference. In the transverse momentum interval 3 <pT<10 GeV/c, the total systematic uncertainties for pions and kaons are below 8.6% and 10%, respectively. While for (anti)protons it is 7.7% and 18% at 3GeV/cand 10GeV/c, respectively. The invariant yields are shown in Fig. 8, where the interpolated pTspectra are compared to those measured in INEL pp collisions at 2.76 TeV and 7 TeV. The nuclear modification factor is then constructed as: RpPb =d2NpPb/dydpT TpPbd2σINEL pp /dydpT (3) Fig. 9. (Color online.) The nuclear modification factor RpPb as a function of transverse momentum pTfor different particle species. The statistical and systematic uncertainties are shown as vertical error bars and boxes, respectively. The total normalization uncertainty is indicated by a vertical scale of the empty box at pT=0GeV/cand RpPb =1. The result for inclusive charged hadrons [54] is also shown. where, for minimum bias (NSD) p–Pb collisions the average nuclear overlap function, TpPb, is 0.0983 ±0.0035 mb−1[43]. In absence of nuclear effects the RpPb is expected to be one. Fig. 9 shows the identified hadron RpPb compared to that for inclusive charged particles (h±)[54] in NSD p–Pb events. At high pT(>10 GeV/c), all nuclear modification factors are consistent with unity within systematic and statistical uncertainties. Around 4GeV/c, where a prominent Cronin enhancement has been seen at lower energies [33,34], the unidentified charged hadron RpPb is above unity, albeit barely significant within systematic uncertainties [54]. Remarkably, the (anti)proton enhancement is ∼3 times larger than that for charged particles, while for charged pions and kaons the enhancement is below that of charged particles. The STAR and PHENIX Collaborations have observed a similar pattern at RHIC, where the nuclear modification factor for MB d–Au col- ALICE Collaboration / Physics Letters B 760 (2016) 720–735 727 Fig. 10. (Color online.) Kaon-to-pion (upper panel) and proton-to-pion (bottom panel) ratios as a function of pTfor different V0A multiplicity classes. Results for p–Pb collisions (full markers) are compared to the ratios measured in INEL pp collisions at 2.76 TeV [35] (empty circles) and at 7 TeV [39] (full circles). The statistical and systematic uncertainties are plotted as vertical error bars and boxes, respectively. lisions, RdAu, in the range 2 <pT<5GeV/c, is 1.24 ±0.13 and 1.49 ±0.17 for charged pions and (anti)protons, respectively [20]. An enhancement of protons in the same pTrange is also observed in heavy-ion collisions [35,47], where it commonly is interpreted as radial-flow and has a strong centrality dependence. In the next section, we study the multiplicity dependence of the invariant yield ratios to see whether protons are more enhanced as a function of multiplicity than pions. 5.2. Transverse momentum and multiplicity dependence of particle ratios The kaon-to-pion and the proton-to-pion ratios as a function of pTfor different V0A multiplicity classes are shown in Fig. 10. The results for p–Pb collisions are compared to those measured for INEL pp collisions at 2.76 TeV [35] and at 7 TeV [39]. Within systematic and statistical uncertainties, the pTdifferential kaon-to- pion ratios do not show any multiplicity dependence. In fact, the results are similar to those for INEL pp collisions at both energies. The pTdifferential proton-to-pion ratios show a clear multiplicity evolution at low and intermediate pT(<10 GeV/c). This multiplicity evolution is qualitatively similar to the centrality evolution observed in Pb–Pb collisions [35,47]. It is worth noting that the average multiplicities at mid-rapidity for peripheral Pb–Pb collisions (60–80%) and high multiplicity p–Pb collisions (0–5% V0A multiplicity class) are very similar, dNch/dη ∼50. Even if the physical mechanisms for particle production could be different, it seems interesting to compare these systems with similar underlying activity as done in Fig. 11, where INEL √s=7TeVpp results are included as an approximate baseline. Within systematic and statistical uncertainties, the kaon-to- pion ratios are the same for all systems. On the other hand, the proton-to-pion ratios exhibit similar flow-like features for the p–Pb and Pb–Pb systems, namely, the ratios are below the pp baseline for pT<1GeV/cand above for pT>1.5GeV/c. Quantitative differences are observed between p–Pb and Pb–Pb results, but they 734 ALICE Collaboration / Physics Letters B 760 (2016) 720–735 46 Helsinki Institute of Physics (HIP), Helsinki, Finland 47 Hiroshima University, Hiroshima, Japan 48 Indian Institute of Technology Bombay (IIT), Mumbai, India 49 Indian Institute of Technology, Indore (IITI), Indore, India 50 Inha University, Incheon, South Korea 51 Institut de Physique Nucléaire d’Orsay (IPNO), Université Paris-Sud, CNRS–IN2P3, Orsay, France 52 Institut für Informatik, Johann Wolfgang Goethe-Universität Frankfurt, Frankfurt, Germany 53 Institut für Kernphysik, Johann Wolfgang Goethe-Universität Frankfurt, Frankfurt, Germany 54 Institut für Kernphysik, Westfälische Wilhelms-Universität Münster, Münster, Germany 55 Institut Pluridisciplinaire Hubert Curien (IPHC), Université de Strasbourg, CNRS–IN2P3, Strasbourg, France 56 Institute for Nuclear Research, Academy of Sciences, Moscow, Russia 57 Institute for Subatomic Physics of Utrecht University, Utrecht, Netherlands 58 Institute for Theoretical and Experimental Physics, Moscow, Russia 59 Institute of Experimental Physics, Slovak Academy of Sciences, Košice, Slovakia 60 Institute of Physics, Academy of Sciences of the Czech Republic, Prague, Czech Republic 61 Institute of Physics, Bhubaneswar, India 62 Institute of Space Science (ISS), Bucharest, Romania 63 Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Mexico City, Mexico 64 Instituto de Física, Universidad Nacional Autónoma de México, Mexico City, Mexico 65 iThemba LABS, National Research Foundation, Somerset West, South Africa 66 Joint Institute for Nuclear Research (JINR), Dubna, Russia 67 Konkuk University, Seoul, South Korea 68 Korea Institute of Science and Technology Information, Daejeon, South Korea 69 KTO Karatay University, Konya, Turkey 70 Laboratoire de Physique Corpusculaire (LPC), Clermont Université, Université Blaise Pascal, CNRS–IN2P3, Clermont-Ferrand, France 71 Laboratoire de Physique Subatomique et de Cosmologie, Université Grenoble-Alpes, CNRS–IN2P3, Grenoble, France 72 Laboratori Nazionali di Frascati, INFN, Frascati, Italy 73 Laboratori Nazionali di Legnaro, INFN, Legnaro, Italy 74 Lawrence Berkeley National Laboratory, Berkeley, CA, United States 75 Moscow Engineering Physics Institute, Moscow, Russia 76 Nagasaki Institute of Applied Science, Nagasaki, Japan 77 National Centre for Nuclear Studies, Warsaw, Poland 78 National Institute for Physics and Nuclear Engineering, Bucharest, Romania 79 National Institute of Science Education and Research, Bhubaneswar, India 80 National Research Centre Kurchatov Institute, Moscow, Russia 81 Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark 82 Nikhef, Nationaal instituut voor subatomaire fysica, Amsterdam, Netherlands 83 Nuclear Physics Group, STFC Daresbury Laboratory, Daresbury, United Kingdom 84 Nuclear Physics Institute, Academy of Sciences of the Czech Republic, ˇ Rež u Prahy, Czech Republic 85 Oak Ridge National Laboratory, Oak Ridge, TN, United States 86 Petersburg Nuclear Physics Institute, Gatchina, Russia 87 Physics Department, Creighton University, Omaha, NE, United States 88 Physics Department, Panjab University, Chandigarh, India 89 Physics Department, University of Athens, Athens, Greece 90 Physics Department, University of Cape Town, Cape Town, South Africa 91 Physics Department, University of Jammu, Jammu, India 92 Physics Department, University of Rajasthan, Jaipur, India 93 Physik Department, Technische Universität München, Munich, Germany 94 Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg, Germany 95 Purdue University, West Lafayette, IN, United States 96 Pusan National University, Pusan, South Korea 97 Research Division and ExtreMe Matter Institute EMMI, GSI Helmholtzzentrum für Schwerionenforschung, Darmstadt, Germany 98 Rudjer Boškovi´c Institute, Zagreb, Croatia 99 Russian Federal Nuclear Center (VNIIEF), Sarov, Russia 100 Saha Institute of Nuclear Physics, Kolkata, India 101 School of Physics and Astronomy, University of Birmingham, Birmingham, United Kingdom 102 Sección Física, Departamento de Ciencias, Pontificia Universidad Católica del Perú, Lima, Peru 103 Sezione INFN, Bari, Italy 104 Sezione INFN, Bologna, Italy 105 Sezione INFN, Cagliari, Italy 106 Sezione INFN, Catania, Italy 107 Sezione INFN, Padova, Italy 108 Sezione INFN, Rome, Italy 109 Sezione INFN, Trieste, Italy 110 Sezione INFN, Turin, Italy 111 SSC IHEP of NRC Kurchatov institute, Protvino, Russia 112 Stefan Meyer Institut für Subatomare Physik (SMI), Vienna, Austria 113 SUBATECH, Ecole des Mines de Nantes, Université de Nantes, CNRS–IN2P3, Nantes, France 114 Suranaree University of Technology, Nakhon Ratchasima, Thailand 115 Technical University of Košice, Košice, Slovakia 116 Technical University of Split FESB, Split, Croatia 117 The Henryk Niewodniczanski Institute of Nuclear Physics, Polish Academy of Sciences, Cracow, Poland 118 The University of Texas at Austin, Physics Department, Austin, TX, USA 119 Universidad Autónoma de Sinaloa, Culiacán, Mexico 120 Universidade de São Paulo (USP), São Paulo, Brazil 121 Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil 122 University of Houston, Houston, TX, United States 123 University of Jyväskylä, Jyväskylä, Finland 124 University of Liverpool, Liverpool, United Kingdom ALICE Collaboration / Physics Letters B 760 (2016) 720–735 735 125 University of Tennessee, Knoxville, TN, United States 126 University of the Witwatersrand, Johannesburg, South Africa 127 University of Tokyo, Tokyo, Japan 128 University of Tsukuba, Tsukuba, Japan 129 University of Zagreb, Zagreb, Croatia 130 Université de Lyon, Université Lyon 1, CNRS/IN2P3, IPN-Lyon, Villeurbanne, France 131 V. Fock Institute for Physics, St. Petersburg State University, St. Petersburg, Russia 132 Variable Energy Cyclotron Centre, Kolkata, India 133 Warsaw University of Technology, Warsaw, Poland 134 Wayne State University, Detroit, MI, United States 135 Wigner Research Centre for Physics, Hungarian Academy of Sciences, Budapest, Hungary 136 Yale University, New Haven, CT, United States 137 Yonsei University, Seoul, South Korea 138 Zentrum für Technologietransfer und Telekommunikation (ZTT), Fachhochschule Worms, Worms, Germany iDeceased. ii Also at: Georgia State University, Atlanta, Georgia, United States. iii Also at: Department of Applied Physics, Aligarh Muslim University, Aligarh, India. iv Also at: M.V. Lomonosov Moscow State University, D.V. Skobeltsyn Institute of Nuclear, Physics, Moscow, Russia.