Long- and short-range correlations and their event-scale dependence in high-multiplicity pp collisions at \boldsymbol{\sqrt{\textit s}}=13 TeV
EEUROPEAN ORGANIZATION FOR NUCLEAR RESEARCH
CERN-EP-2021-0066 January 2021© 2021 CERN for the benefit of the ALICE Collaboration.Reproduction of this article or parts of it is allowed as specified in the CC-BY-4.0 license.
Long- and short-range correlations and their event-scale dependence inhigh-multiplicity pp collisions at √ s = TeV
ALICE Collaboration * Abstract
Two-particle angular correlations are measured in high-multiplicity proton–proton collisions at √ s =
13 TeV by the ALICE Collaboration. The yields of particle pairs at short-( ∆ η ∼
0) and long-range(1 . < | ∆ η | < .
8) in pseudorapidity are extracted on the near-side ( ∆ ϕ ∼ p T ) in the range 1 < p T < c . Furthermore, the event-scaledependence is studied for the first time by requiring the presence of high- p T leading particles and jetsfor varying p T thresholds. The results demonstrate that the long-range “ridge” yield, possibly relatedto the collective behavior of the system, is present in events with high- p T processes. The magnitudesof the short- and long-range yields are found to grow with the event scale. The results are comparedto EPOS LHC and PYTHIA 8 calculations, with and without string-shoving interactions. It is foundthat while both models describe the qualitative trends in the data, calculations from EPOS LHC showa better quantitative agreement, in particular for the p T and event-scale dependencies. * See Appendix A for the list of collaboration members a r X i v : . [ nu c l - e x ] J a n ong-range correlations in pp collisions at √ s =
13 TeV ALICE Collaboration
In high-energy nucleus–nucleus collisions at RHIC [1–4] and LHC [5–7], significant correlations areobserved between particles emitted over a wide pseudorapidity range. The origin of these observationsare collective effects, which are related to the formation of a strongly interacting quark–gluon plasma(QGP), which exhibits hydrodynamic behavior (see the reviews [8–10]). Recent theoretical [11–13] andexperimental [14–17] advancements have contributed significantly to the understanding of the transportproperties of the QGP. Similar long-range correlations are also observed in high-multiplicity proton–proton (pp) [18–21], proton–nucleus (p–A) [22–25], and light nucleus–nucleus collisions [26, 27]. Thefact that these correlations extend over a large range in pseudorapidity implies that they originate fromearly times in these collisions and thus suggest that hydrodynamic behavior is present even in thesesmall systems, although the volume and lifetime of the medium produced in such a collision system areexpected to be small, and there are other mechanisms which can produce similar flow-like signals [28,29].Measurements of two-particle angular correlations provide information on many physical effects, includ-ing collectivity, hadronization, fragmentation, and femtoscopic effects [30], and are typically quantifiedas a function of ∆ η , the relative pseudorapidity, and ∆ ϕ , the separation in azimuthal angle, of particlepairs. The long-range structure of two-particle angular correlations is well suited to analyze collectiveeffects, since it is not created by resonance decays nor fragmentation of high-momentum partons. Atypical source of long-range correlations in Monte Carlo pp generators is the momentum conservation.The enhancement in the yield of two-particle correlations at small ∆ ϕ that extends over a large ∆ η isdubbed “ridge” due to its characteristic shape in the ∆ η – ∆ ϕ plane. The shape of these ∆ ϕ correlationscan be studied via a Fourier decomposition [31, 32]. The second and third order terms are the dominantharmonic coefficients. In heavy-ion collisions, harmonic coefficients can be related to the collision ge-ometry and density fluctuations of the colliding nuclei [33–35] and to transport properties of the QGP inrelativistic viscous hydrodynamic models [11–13, 36, 37].The ridge structures in high-multiplicity pp and p–Pb events have been attributed to initial-state or final-state effects. Initial-state effects, usually attributed to gluon saturation [38, 39], can form long-rangecorrelations along the longitudinal direction. The final-state effects might be parton-induced interac-tions [40] or collective phenomena due to hydrodynamic behavior of the produced matter arising in ahigh-density system possibly formed in these collisions [41, 42]. Hybrid models implementing botheffects are generally used in hydrodynamic simulations [43, 44]. EPOS LHC describes collectivity insmall systems with a parameterized hydrodynamic evolution of the high-energy density region, so called“core”, formed by many color string fields [45]. The proton shape and its fluctuations are also importantto model small systems [44]. To understand the influence of initial- or final-state effects, and to possiblydisentangle the two, a quantitative description of the measurements in small systems [46, 47] needs toaccount for details of the initial state. Systematic studies of these correlation effects from small to largesystems are being performed, both experimentally [21] and theoretically [47]. However, the quantita-tive description of the full set of experimental data has not been achieved yet. A summary of variousexplanations for the observed correlations in small systems is given in [29, 48, 49, 49].Besides the hybrid models mentioned above, alternative approaches were developed to describe col-lectivity in small systems. A microscopic model for collectivity was implemented in the PYTHIA 8event generator, which is based on interacting strings (string shoving) and is called the “string shov-ing model” [50]. In this model, strings repel each other in the transverse direction, which results inmicroscopic transverse pressure and, consequently, in long-range correlations. PYTHIA 8 with stringshoving can qualitatively reproduce the near-side ( ∆ ϕ ∼
0) ridge yield measured by the CMS Collabora-tion [20]. This challenges the hydrodynamic picture and predicts modifications of the jet fragmentationproperties [51]. 2ong-range correlations in pp collisions at √ s =
13 TeV ALICE CollaborationIt is expected that final-state interactions affect also produced jets if they are the source of collectivityin small systems. Proving the presence of jet quenching [52, 53] would be another crucial evidenceof the existence of a high-density strongly-interacting system, possibly a QGP, in high-multiplicity ppcollisions. However, there is no evidence observed so far for the jet quenching effect in high-multiplicitypp and p–Pb collisions [54–57]. Jet fragmentation can be studied in two-particle angular correlations inshort-range correlations around ( ∆ η , ∆ ϕ ) = ( , ) [58].To further investigate the interplay of jet production and collective effects in small systems, long- andshort-range correlations are studied simultaneously in high-multiplicity pp collisions at √ s =
13 TeVusing the ALICE LHC Run 2 data collected with the high-multiplicity event trigger in 2016–2018. Inthis article, the near-side per-trigger yield at large pseudorapidity separation is presented as a functionof transverse momentum. The results are compared with previous measurements by the CMS Collabo-ration [19]. In addition, the ridge yield and near-side jet-like correlations with the event-scale selectionare reported. The event-scale selection is done by requiring a minimum transverse momentum of theleading particle or the reconstructed jet at midrapidity, which is expected to bias the impact parame-ter of pp collisions to be smaller on average [59, 60]. At the same time, the transverse momentum ofthe leading particle or the reconstructed jet is a measure of the momentum transfer in the hard partonscattering [61, 62].The experimental setup and analysis method are described in Sec. 2 and 3, respectively. The sources ofsystematic uncertainties are discussed in Sec. 4. The results and comparisons with model calculations ofthe measurements are presented in Sec. 5. Finally, results are summarized in Sec. 6.
The analysis is carried out with data samples of pp collisions at √ s =
13 TeV collected from 2016 to2018 during the LHC Run 2 period. The full description of the ALICE detector and its performance inthe LHC Run 2 can be found in [63, 64]. The present analysis utilizes the V0 [65], the Inner TrackingSystem (ITS) [66], and the Time Projection Chamber (TPC) [67] detectors.The V0 detector consists of stations placed on both sides of the interaction point, V0A and V0C, eachmade of 32 scintillator tiles, covering the full azimuthal angle within the pseudorapidity intervals 2 . < η < . − . < η < − .
7, respectively. The V0 is used to provide a minimum bias (MB) and ahigh-multiplicity (HM) trigger. The minimum bias trigger is obtained by a time coincidence of V0Aand V0C signals. The event activity selection is done on the sum of the V0A and V0C signals, which isdenoted as V0M. The high-multiplicity trigger requires that the V0M signal exceeds 5 times the meanvalue measured in minimum bias collisions, selecting the 0.1% of MB events that have the largest V0multiplicity. The analyzed data samples of minimum bias and high-multiplicity pp events at √ s = − and 11 pb − , respectively [68].The primary vertex position is reconstructed from the measured signals in the Silicon Pixel Detector(SPD), which forms the innermost two layers of the ITS. Reconstructed primary vertices of selectedevents are required to be located within 8 cm from the center of the detector along the beam direction.The probability of pileup events is about 0.6% in MB events. Pileup events can be resolved and arerejected if the longitudinal displacement of their primary vertices is larger than 0.8 cm.Charged-particle tracks are reconstructed by the ITS and TPC, which are operated in a uniform solenoidalmagnetic field of 0.5 T along the beam direction. The ITS is a silicon tracker with six layers of siliconsensors where the two innermost ones are formed by the SPD [69], the next two layers called the SiliconDrift Detector (SDD), and the outermost layers named the Silicon Strip Detector (SSD). The ITS andTPC, covering the full azimuthal region, have acceptances up to | η | < . z vtx ) along the3ong-range correlations in pp collisions at √ s =
13 TeV ALICE Collaborationbeam direction. The tracking of charged particles is done with the combined information of the ITSand TPC that enables the reconstruction of tracks down to 0.15 GeV/ c with about 65% efficiency. Theefficiency reaches 80% for intermediate transverse momentum, 1 to 5 GeV/ c . The transverse momentumresolution is around 1% for primary tracks with p T < c , and linearly increases up to 6% at p T ∼
40 GeV/ c [70].The charged particle selection criteria are optimized to make the efficiency uniform over the full TPCvolume to mitigate the effect of small regions where some of the ITS layers are inactive. The selectionconsists of two track classes. Those belonging to the first class are required to have at least one hit in theSPD. Tracks from the second class do not have any SPD associated hit and their initial point is insteadconstrained to the primary vertex [71]. The two-particle correlation function is measured as a function of the relative pseudorapidity ( ∆ η ) andthe azimuthal angle difference ( ∆ ϕ ) between the trigger and the associated particles,1 N trig d N pair d ∆ η d ∆ ϕ = B ( , ) S ( ∆ η , ∆ ϕ ) B ( ∆ η , ∆ ϕ ) (cid:12)(cid:12)(cid:12) p T , trig , p T , assoc , (1)where p T , trig and p T , assoc ( p T , trig > p T , assoc ) are the transverse momenta of the trigger and associated parti-cles, respectively, N trig is the number of trigger particles, and N pair is the number of trigger-associated par-ticle pairs. The average number of pairs in the same event and in mixed events are denoted as S ( ∆ η , ∆ ϕ ) and B ( ∆ η , ∆ ϕ ) , respectively. Normalization of B ( ∆ η , ∆ ϕ ) is done with its value at ∆ η and ∆ ϕ = B ( , ) . Acceptance effects are corrected by dividing S ( ∆ η , ∆ ϕ ) with B ( ∆ η , ∆ ϕ ) / B ( , ) .The right-hand side of Eq. (1) is corrected for the track reconstruction efficiency, which is mainly rel-evant for the associated particles, as a function of transverse momentum and pseudorapidity. Primaryvertices of events to be mixed are required to be within the same, 2 cm wide, z vtx interval [58, 72] foreach multiplicity class. The final per-trigger yield is constructed by averaging correlation functions overthese primary vertex bins.Ridge yields at large ∆ η are extracted for various multiplicity classes and transverse momentum inter-vals. The large ∆ η range is selected as 1 . < | ∆ η | < .
8, which is the range where the tracking quality– efficiency and precision – is the best. The ridge yield is only reported for p T > c . Below1 GeV/ c , the jet-like contribution to the correlation function extends into the region where the ridge yieldis measured, 1.6 < | ∆ η | < ∆ ϕ distribution, or the so-called per-trigger yield, isexpressed as 1 N trig d N pair d ∆ ϕ = (cid:90) . < | ∆ η | < . (cid:18) N trig d N pair d ∆ η d ∆ ϕ (cid:19) δ ∆ η d ∆ η − C ZYAM , (2)where δ ∆ η = ( C ZYAM ) at ∆ ϕ = ∆ ϕ min in the ∆ ϕ projection (note that the value of ∆ ϕ min can be different in data and in models) is obtained from a fit function, which fits the data witha Fourier series up to the third harmonic. By construction, the yield at ∆ ϕ min is zero after subtracting C ZYAM from the ∆ ϕ projection. The ridge yield ( Y ridge ) is obtained by integrating the near-side peak ofthe ∆ ϕ projection over | ∆ ϕ | < | ∆ ϕ min | after the ZYAM procedure, Y ridge = (cid:90) | ∆ ϕ | < | ∆ ϕ min | N trig d N pair d ∆ ϕ d ∆ ϕ . (3)4ong-range correlations in pp collisions at √ s =
13 TeV ALICE CollaborationThe ridge yield is further studied in events having a hard jet or a high- p T leading particle in the midra-pidity region. Such a requirement is expected to bias the impact parameter of pp collisions to be smalleron average [59, 60]. This event scale is set by requiring a minimum transverse momentum of the leadingtrack ( p T , LP ) or the reconstructed jet ( p chT , jet ) at midrapidity. The leading track is selected within | η | < . k T algorithm [74, 75] and the resolution parameter R = p T scheme. Jets are selected in | η jet | < . p chT , jet is corrected for the underlying event density that is measured usingthe k T algorithm with R = p T , LP or p chT , jet , the near-side jet-like peak yield is extracted from the near-side ∆ η correlations. The near-sideis defined as | ∆ ϕ | < ∆ η axis. The projectionrange, 1.28, is chosen to fully cover ∆ ϕ min . The near-side ∆ η correlations are then constructed as1 N trig d N pair d ∆ η = (cid:90) | ∆ ϕ | < . (cid:18) N trig d N pair d ∆ η d ∆ ϕ (cid:19) δ ∆ ϕ d ∆ ϕ − D ZYAM , (4)where δ ∆ ϕ = ( D ZYAM ) of the ∆ η correlations is found within | ∆ η | < ∆ η correlations, which results in zero-yield at the minimum. The near-side jet-like peak yield( Y near ) is measured by integrating the ∆ η correlations over | ∆ η | < Y near = (cid:90) | ∆ η | < . (cid:18) N trig d N pair d ∆ η (cid:19) d ∆ η (5). The systematic uncertainties of Y ridge and Y near are estimated by varying the analysis selection criteriaand corrections and are summarized in Tab. 1. Table 1:
The relative systematic uncertainty of Y ridge and Y near . Numbers given in ranges correspond to minimumand maximum uncertainties. Sources Systematic uncertainty (%) Y ridge Y near Pileup rejection ± ± ± ± ± ± ± ± ± ± ± ± − p T < c ) N.A.Total (in quadrature) + . . − . . ± D ZYAM (see below),as expected, since the multiplicity is weakly dependent on the event scale and the ALICE detector isoptimized for much higher multiplicities (Pb–Pb collisions), this is in agreement with our expectations.The uncertainty associated to the pileup rejection is estimated by measuring the changes of results withdifferent rejection criteria from the default one. It is mainly estimated by varying the minimal number5ong-range correlations in pp collisions at √ s =
13 TeV ALICE Collaborationof track contributors required for reconstruction of pileup event vertices from 3 to 5. The estimateduncertainty of Y ridge is 0.8-3.9%. The corresponding uncertainty of Y near is estimated to be 0.2–2.2%.Another source of systematic uncertainty is related to the selected range of the primary vertex. Theaccepted range is changed from | z vtx | < | z vtx | < Y ridge is 0.5–2.4%. The uncertainty for Y near is estimated to be 1.1%.An additional source of systematic uncertainty is related to the track selection criteria. The correspondinguncertainty is estimated by employing other track selection criteria, denoted global tracks, which areoptimized for particle identification. The selection criteria of the global tracks are almost identical to thehybrid tracks. Each global track is required to have at least one SPD hit. Due to inefficient parts of theSPD, the azimuthal distribution of global tracks is not uniform. The uncertainties associated with thetrack selection are estimated to be 2.0–4.0% and 1.5–3.4% for Y ridge and Y near , respectively.The systematic uncertainty of Y ridge resulting from the ZYAM procedure is estimated by varying therange of the fit, which is used to find the minimum, from | ∆ ϕ | < π / | ∆ ϕ | < .
2. The estimateduncertainty of Y ridge is 2.1–5.1%. The corresponding uncertainty on Y near is estimated by varying therange from | ∆ η | < | ∆ η | < Y near is 2.2% for the unbiasedcase and increases to 4.8% for the largest event-scale selections. This is the only systematic uncertaintyfor which a significant dependence on the event scale is observed, reflecting a non-negligible dependenceof the near-side magnitude and shape on the event-scale selection.The source of systematic uncertainty is associated to the choice of the width of z vtx bins that are usedin the event mixing method. The default value of 2 cm is changed to 1 cm. The resulting uncertaintyof Y ridge is 1.0–4.4%. The uncertainty for Y near is about 0.5–1.7%. The uncertainty from the efficiencycorrection for charged particles is estimated by comparing correlation functions of true particles withcorrelations functions of reconstructed tracks with the efficiency correction in simulation. The estimateduncertainties are 2.5% and 3.1% for Y ridge and Y near , respectively.In the limited η -acceptance of ALICE, the ridge structure is not flat in ∆ η suggesting that jet-like correla-tions (non-flow) could contribute, implying that they would impact the ridge-yield extraction. We stressthat the models used for comparisons also contain such a non-flow effect, but differences in jet-like cor-relations between data and MC models could influence the interpretation. To account for the relateduncertainty, the variation of the yield with ∆ η between 1.5 and 1.8, which should be an upper limit of theresidual jet-like contamination, is used as a systematic uncertainty of the ridge yield. The estimated upperlimit of the uncertainty is − < p T < c range, − < p T < c range, − < p T < c range, and negligible for p T > c . Thisuncertainty is considered only for the measured ridge yields. Figure 1 shows the per-trigger yield obtained from Eq. (1) for 1 < p T , trig ( p T , assoc ) < c in ppcollisions at √ s =
13 TeV for minimum bias events (left) and high-multiplicity events (right). It is worthnoting that the z -axes for the yield of the correlations is properly scaled in order to zoom in the ridgeyield, as a result, the jet peaks are sheared off in both figures. The ridge structure is clearly observed inthe high-multiplicity class while it is less significant in the minimum bias events. The away-side yield ispopulated mostly by back-to-back jet correlations.Figure 2 shows ∆ ϕ projections of the two-particle correlation functions obtained in the range 1.6 < | ∆ η | < p T intervals after the ZYAM subtraction (see Eq. (2)). The results are shown6ong-range correlations in pp collisions at √ s =
13 TeV ALICE Collaborationfor various p T intervals in the minimum bias class (upper) and the high-multiplicity class (lower) downto 1 GeV/ c where the non-flow contamination is negligible. The near-side ( ∆ ϕ ∼
0) ridge in the high-multiplicity class is clearly observed for p T < c while there is no definitive signal in the minimumbias class. Within the range of analyzed particle p T , the yield in the near-side ridge decreases withincreasing p T in the high-multiplicity class.The measurements in the high-multiplicity class are compared with the results published by the CMSCollaboration [19]. In case of the CMS measurement, the charged particle multiplicity was obtainedby counting the number of particles satisfying p T > . c in | η | < | η | < η acceptance between the multiplicityselection and the correlation function measurement.In Fig. 2, the ALICE measurements are also compared with model predictions where a comparable high-multiplicity selection and ∆ η projection range are applied. The selection of high-multiplicity events inthe models is done by requiring a minimal number of charged particles emitted within the V0M detectoracceptance. In case of PYTHIA 8 Tune 4C, the 0–0.1% centrality threshold is 105 charged particles. Thethreshold for EPOS LHC and PYTHIA 8 String Shoving are 110 and 108, respectively. The magnitudeof string shoving ( g ) is set to 3.0 in this study. The statistical uncertainties due to the limited numberof events for the model calculations are shown as bands in each figure. The PYTHIA 8 String Shovingprovides good estimates of the near-side ridge yield and slightly overestimates the away-side yield forthe interval 1 < p T < c . However, the PYTHIA 8 String Shoving model underestimates the near-side ridge yield for p T > c . The PYTHIA 8 Tune 4C model does not show any near-side ridgeas expected. It slightly underestimates the away-side peak for 1 < p T < c and provides goodestimates for p T > c . On the other hand, EPOS LHC describes the shape of the ridge yieldquantitatively better in the 2 < p T , trig ( assoc ) < c range, while overestimating the near-side ridgeyield for p T , trig ( assoc ) < c range.Figure 3 shows the near-side ridge yield measured in high-multiplicity events as a function of p T , trig ( assoc ) .The measurement is compared with the result from CMS [19]. Considering the differences in acceptanceand the chosen multiplicity estimator of both measurements, perfect agreement between the two sets of - hD - (r ad . ) jD ) jD d hD / d pa i r N ) ( d t r i g N ( / = 13 TeV s ALICE, pp 100% V0M - c < 2 GeV/ T,trig(assoc) p - hD - (r ad . ) jD ) jD d hD / d pa i r N ) ( d t r i g N ( / = 13 TeV s ALICE, pp 0.1% V0M - c < 2 GeV/ T,trig(assoc) p Fig. 1:
Two-particle correlation functions as functions of ∆ η and ∆ ϕ in minimum-bias events (0–100%, left) andhigh-multiplicity (0–0.1%, right). Note that the near-side jet peaks exceed the chosen range of the z -axis. Theintervals of p T , trig and p T , assoc are 1 < p T < c in both cases. √ s =
13 TeV ALICE Collaboration N t r i g d N p a i r d < p T,trig(assoc) < / c < p T,trig(assoc) < / c < p T,trig(assoc) < / c N t r i g d N p a i r d (rad. ) < p T,trig(assoc) < / c (rad. ) < p T,trig(assoc) < / c ∼ < | ∆ η | < (rad. ) < p T,trig(assoc) < / c PYTHIA 8 String Shoving g = 3PYTHIA 8 Tune 4CEPOS LHC ALICE pp √ s = 13 TeV < | ∆ η | < Fig. 2:
One-dimensional ∆ ϕ distribution in the large ∆ η projection for three transverse momentum intervalsin minimum bias (upper panels) and high-multiplicity (lower panels) events after ZYAM subtraction. Trans-verse momentum intervals of the trigger particles and associated particles are 1 < p T < < p T < < p T < c (right), respectively. The presented model predictions were calculated usingPYTHIA 8 String Shoving, PYTHIA 8 Tune 4C, and EPOS LHC. p T, trig(assoc) (GeV/ c ) Y r i dg e ALICE, 0–0.1%PYTHIA 8 String Shoving g = 3PYTHIA 8 Tune 4CEPOS LHCCMS, ∼ < | ∆ η | < pp √ s = 13 TeV1.6 < | ∆ η | < Fig. 3:
Fully corrected near-side ridge yield as a function transverse momentum. The open blue boxes denotethe measurement by ALICE. The statistical and systematic uncertainties are shown as vertical bars and boxes,respectively. The CMS measurement [19] is represented by filled circles and extends down to lower p T due tothe larger ∆ η acceptance. The three lines show model predictions from PYTHIA 8 Tune 4C (blue dotted line),PYTHIA 8 String Shoving (orange line), and EPOS LHC (green dashed line). √ s =
13 TeV ALICE Collaborationresults is not expected. The measurement is also compared with model calculations. As expected, thePYTHIA 8 model with Tune 4C does not produce a near-side ridge because it is not designed to accountfor this effect. The PYTHIA 8 String Shoving model describes the yield qualitatively, however the pre-dicted yield decreases more rapidly than the measured one for increasing p T , trig ( assoc ) . The EPOS LHCmodel, unlike the PYTHIA 8 String Shoving model, describes well the p T dependence of the ridge yieldfor the range p T > c , while predicting larger yields for p T < c . - hD - (r ad . ) jD ) jD d hD / d pa i r N ) ( d t r i g N ( / = 13 TeV s ALICE, pp 0.1% V0M - c < 2 GeV/ T,trig(assoc) p c > 9 GeV/ T,LP p - hD - (r ad . ) jD ) jD d hD / d pa i r N ) ( d t r i g N ( / = 13 TeV s ALICE, pp 0.1% V0M - c < 2 GeV/ T,trig(assoc) p c > 10 GeV/ chT,jet p Fig. 4:
Two-dimensional correlation functions as a function of ∆ η and ∆ ϕ in high-multiplicity events includinga selection on the event-scale. The interval of p T , trig and p T , assoc is 1 < p T , trig ( assoc ) < c . Left: HM eventswith a p T , LP > c leading track. Right: HM events with a p chT , jet >
10 GeV/ c . The ridge yield is further studied with respect to two different event-scales. In the first measurement,the event-scale is set by requiring a minimum p T cutoff on the leading particle in each event (denoted as p T , LP ), while in the second measurement, a minimum p T cutoff is imposed on the leading jet (denotedas p chT , jet ).Figure 4 shows that the ridge structure for 1 < p T , trig ( p T , assoc ) < c still persists in high-multiplicitypp collisions with p T , LP > c (left) and p chT , jet >
10 GeV/ c (right). It is worth noting that the corre-lation function obtained with the minimum p chT , jet selection has a double peak structure which is orientedalong the ∆ η axis at ∆ ϕ = π . This structure emerges due to the restricted acceptance of the jet tagging, | η jet | < ∆ ϕ distributions of the correlation functions in 1.6 < | ∆ η | < p T , LP (lower) and p chT , jet (upper) requirement. Even with the event-scale selection, the ridgeis still visible on the near-side. The near-side ridge peak increases as the thresholds of p T , LP and p chT , jet increase compared to the one measured in unbiased events in Sec. 5.1. The results are compared withPYTHIA 8 String Shoving, PYTHIA 8 Tune 4C, and EPOS LHC calculations. The near-side ridge peaksare qualitatively reproduced by PYTHIA 8 String Shoving and EPOS LHC models. On the other hand,the PYTHIA 8 Tune 4C does not show the near-side ridge peak for neither of the two event-scale se-lections, but it gives compatible results for the away-side yield just like the PYTHIA 8 String Shovingmodel.The ridge yields as function of the minimum p T , LP ( p LPT , min ) and p chT , jet ( p jetT , min ) selections are shownin Fig. 6. High-multiplicity events with imposed event-scale bias exhibit increased ridge yields whencompared to unbiased HM events. A small increase of the ridge yields as a function of p T , LP or p chT , jet is observed and there is no difference between the two event-scale selections within the uncertainties.Comparisons to model calculations show that PYTHIA 8 String Shoving provides a comparable trendwith data, but underestimates the ridge yield. On the other hand, EPOS LHC overestimates the ridge9ong-range correlations in pp collisions at √ s =
13 TeV ALICE Collaboration N t r i g d N p a i r d Unbiased p chT,jet >
10 GeV / c ALICEPYTHIA 8 String Shoving g = 3PYTHIA 8 Tune 4CEPOS LHC p chT,jet >
20 GeV / c N t r i g d N p a i r d (rad. ) p T,LP > / c (rad. ) p T,LP > / c (rad. ) p T,LP >
13 GeV / c pp √ s = 13 TeV, 0–0.1 %1 < p T,trig(assoc) < / c < | ∆ η | < Fig. 5:
One-dimensional ∆ ϕ projections of the correlation functions constrained to 1.6 < | ∆ η | < p T , bottom: with an imposedselection on the leading particle p T . ALICE data are compared with prediction of models. Y r i dg e Leading Particle | η | < ALICE Near-sidePYTHIA 8 String Shoving g = 3PYTHIA 8 Tune 4CEPOS LHC Jet, anti- k T R = 0.4 | η | < R a t i o p LPT, min (GeV/ c ) 0 10 20 30 40 p jetT, min (GeV/ c ) pp √ s = 13 TeV0–0.1% < p T,trig(assoc) < / c < | ∆ η | < Fig. 6:
Near-side ridge yield as a function of the p LPT , min (left) and p JetT , min (right). Data points (filled circles) showthe ALICE measurement. The statistical and systematic uncertainties are shown as vertical bars and boxes, re-spectively. As the ridge yield is obtained in the same operational way for data and models, the upper limit ofthe systematic uncertainty due to jet contamination, which is 18.9%, is not included in the figure. The data arecompared with predictions of models which are represented by colored bands. The bottom panel shows a ratio ofthe models to the data. The uncertainty of the data is represented by the gray band centered around unity. yield while providing a trend comparable with the data. The origin of the enhanced ridge yields forhigher momentum jet-tagged events is not clear to date but it might be related to the expected smaller10ong-range correlations in pp collisions at √ s =
13 TeV ALICE Collaborationimpact parameters for dijet or multi-jet production events as studied in [60]. Y n e a r Leading Particle | η | < ALICE Near-sidePYTHIA8 String Shoving g = 3PYTHIA8 Tune 4CEPOS LHC Jet, anti- k T R = 0.4 | η | < R a t i o s p LPT, min (GeV/ c ) 0 10 20 30 40 50 60 p JetT, min (GeV/ c ) pp √ s = 13 TeV, 0–0.1% 1 < p T,trig(assoc) < / c Fig. 7:
Near-side jet-like peak yield as a function of the p LPT , min (left) and p jetT , min (right). The filled cir-cles show measurement with ALICE. The statistical and systematic uncertainties are shown as vertical barsand boxes, respectively. The measurements are compared with model descriptions from PYTHIA 8 Tune 4C,PYTHIA 8 String Shoving, and EPOS LHC for both selections. The total uncertainty of the ratio is represented bythe gray band centered around unity. Finally, the near-side jet-like peak yield is measured as a function of minimum p T , LP and p chT , jet in Fig. 7to further test the models that aim to describe the near-side ridge. EPOS LHC provides comparableestimates of the near-side jet-like peak yield, while PYTHIA 8 Tune 4C and PYTHIA 8 String Shovingoverestimate the near-side yields for both event selections.In all models if the ridge is due to final-state interactions, e.g., EPOS LHC and PYTHIA 8 String Shov-ing, one also expects the near-side jet-like peak yield to be affected. This can be observed when compar-ing the measured near-side jet yields with PYTHIA 8 calculations with and without String Shoving. Thenew ALICE results therefore provide constraints beyond traditional ridge measurements that challengeexisting models. Long- and short-range correlations for pairs of charged particles with 1 < p T < c are studied inpp collisions at √ s =
13 TeV with a focus on high-multiplicity events. The ridge and near-side jet yieldsare extracted and their event scale dependence have been studied. The obtained long-range ridge yieldsare compatible to those observed by the CMS Collaboration [19]. The PYTHIA 8 String Shoving modeldescribes the observed yields qualitatively but the yields it predicts decrease more rapidly with increasing p T , trig ( assoc ) than those measured. On the other hand, the EPOS LHC model gives a better description forthe p T , trig ( assoc ) dependence while overestimating the ridge yield for p T , trig ( assoc ) < c . Finally, nolong-range ridge is formed in the PYTHIA 8 Tune 4C model.The ridge yields are further studied in high-multiplicity events biased with additional event-scale se-lections, which impose a minimum transverse momentum cutoff on a leading track or jet. The ridgestructure still persists with both selection criteria. The ridge yield increases as p T , LP and p chT , jet increase.11ong-range correlations in pp collisions at √ s =
13 TeV ALICE CollaborationPYTHIA 8 String Shoving and EPOS LHC estimate qualitatively the trends for the event-scale selec-tions. However, the former underestimates and the latter overestimates it. The model predictions are alsocompared with the yield of the near-side jet-like correlation measured in the biased events. The evolu-tion of the near-side jet yield as a function of event-scale p T is better captured by EPOS LHC, while thePYTHIA 8 String Shoving calculation tends to overshoot the data. The results might open a new way ofstudying the impact parameter dependence of small systems with jet tagged events in the future and willhelp to constrain the physical origins of long-range correlations. Acknowledgements
The ALICE Collaboration would like to thank Christian Bierlich for providing the PYTHIA8 StringShoving configurations.The ALICE Collaboration would like to thank all its engineers and technicians for their invaluable con-tributions to the construction of the experiment and the CERN accelerator teams for the outstandingperformance of the LHC complex. The ALICE Collaboration gratefully acknowledges the resources andsupport provided by all Grid centres and the Worldwide LHC Computing Grid (WLCG) collaboration.The ALICE Collaboration acknowledges the following funding agencies for their support in buildingand running the ALICE detector: A. I. Alikhanyan National Science Laboratory (Yerevan Physics In-stitute) Foundation (ANSL), State Committee of Science and World Federation of Scientists (WFS),Armenia; Austrian Academy of Sciences, Austrian Science Fund (FWF): [M 2467-N36] and National-stiftung für Forschung, Technologie und Entwicklung, Austria; Ministry of Communications and HighTechnologies, National Nuclear Research Center, Azerbaijan; Conselho Nacional de DesenvolvimentoCientífico e Tecnológico (CNPq), Financiadora de Estudos e Projetos (Finep), Fundação de Amparo àPesquisa do Estado de São Paulo (FAPESP) and Universidade Federal do Rio Grande do Sul (UFRGS),Brazil; Ministry of Education of China (MOEC) , Ministry of Science & Technology of China (MSTC)and National Natural Science Foundation of China (NSFC), China; Ministry of Science and Educationand Croatian Science Foundation, Croatia; Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear(CEADEN), Cubaenergía, Cuba; Ministry of Education, Youth and Sports of the Czech Republic, CzechRepublic; The Danish Council for Independent Research | Natural Sciences, the VILLUM FONDEN andDanish National Research Foundation (DNRF), Denmark; Helsinki Institute of Physics (HIP), Finland;Commissariat à l’Energie Atomique (CEA) and Institut National de Physique Nucléaire et de Physiquedes Particules (IN2P3) and Centre National de la Recherche Scientifique (CNRS), France; Bundesmin-isterium für Bildung und Forschung (BMBF) and GSI Helmholtzzentrum für SchwerionenforschungGmbH, Germany; General Secretariat for Research and Technology, Ministry of Education, Researchand Religions, Greece; National Research, Development and Innovation Office, Hungary; Departmentof Atomic Energy Government of India (DAE), Department of Science and Technology, Governmentof India (DST), University Grants Commission, Government of India (UGC) and Council of Scientificand Industrial Research (CSIR), India; Indonesian Institute of Science, Indonesia; Istituto Nazionaledi Fisica Nucleare (INFN), Italy; Institute for Innovative Science and Technology , Nagasaki Instituteof Applied Science (IIST), Japanese Ministry of Education, Culture, Sports, Science and Technology(MEXT) and Japan Society for the Promotion of Science (JSPS) KAKENHI, Japan; Consejo Nacionalde Ciencia (CONACYT) y Tecnología, through Fondo de Cooperación Internacional en Ciencia y Tec-nología (FONCICYT) and Dirección General de Asuntos del Personal Academico (DGAPA), Mexico;Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO), Netherlands; The Research Coun-cil of Norway, Norway; Commission on Science and Technology for Sustainable Development in theSouth (COMSATS), Pakistan; Pontificia Universidad Católica del Perú, Peru; Ministry of Science andHigher Education, National Science Centre and WUT ID-UB, Poland; Korea Institute of Science andTechnology Information and National Research Foundation of Korea (NRF), Republic of Korea; Min-istry of Education and Scientific Research, Institute of Atomic Physics and Ministry of Research and12ong-range correlations in pp collisions at √ s =
13 TeV ALICE CollaborationInnovation and Institute of Atomic Physics, Romania; Joint Institute for Nuclear Research (JINR), Min-istry of Education and Science of the Russian Federation, National Research Centre Kurchatov Institute,Russian Science Foundation and Russian Foundation for Basic Research, Russia; Ministry of Educa-tion, Science, Research and Sport of the Slovak Republic, Slovakia; National Research Foundation ofSouth Africa, South Africa; Swedish Research Council (VR) and Knut & Alice Wallenberg Founda-tion (KAW), Sweden; European Organization for Nuclear Research, Switzerland; Suranaree Universityof Technology (SUT), National Science and Technology Development Agency (NSDTA) and Office ofthe Higher Education Commission under NRU project of Thailand, Thailand; Turkish Atomic EnergyAgency (TAEK), Turkey; National Academy of Sciences of Ukraine, Ukraine; Science and TechnologyFacilities Council (STFC), United Kingdom; National Science Foundation of the United States of Amer-ica (NSF) and United States Department of Energy, Office of Nuclear Physics (DOE NP), United Statesof America.
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S. Acharya , D. Adamová , A. Adler , J. Adolfsson , G. Aglieri Rinella , M. Agnello , N. Agrawal ,Z. Ahammed , S. Ahmad , S.U. Ahn , Z. Akbar , A. Akindinov , M. Al-Turany ,D.S.D. Albuquerque , D. Aleksandrov , B. Alessandro , H.M. Alfanda , R. Alfaro Molina , B. Ali ,Y. Ali , A. Alici , N. Alizadehvandchali , A. Alkin , J. Alme , T. Alt , L. Altenkamper , I. Altsybeev ,M.N. Anaam , C. Andrei , D. Andreou , A. Andronic , V. Anguelov , T. Antiˇci´c , F. Antinori ,P. Antonioli , C. Anuj , N. Apadula , L. Aphecetche , H. Appelshäuser , S. Arcelli , R. Arnaldi ,M. Arratia , I.C. Arsene , M. Arslandok , , A. Augustinus , R. Averbeck , S. Aziz , M.D. Azmi ,A. Badalà , Y.W. Baek , X. Bai , R. Bailhache , R. Bala , A. Balbino , A. Baldisseri , M. Ball ,D. Banerjee , R. Barbera , L. Barioglio , M. Barlou , G.G. Barnaföldi , L.S. Barnby , V. Barret ,C. Bartels , K. Barth , E. Bartsch , F. Baruffaldi , N. Bastid , S. Basu , , G. Batigne , B. Batyunya ,D. Bauri , J.L. Bazo Alba , I.G. Bearden , C. Beattie , I. Belikov , A.D.C. Bell Hechavarria ,F. Bellini , R. Bellwied , S. Belokurova , V. Belyaev , G. Bencedi , , S. Beole , A. Bercuci ,Y. Berdnikov , A. Berdnikova , D. Berenyi , L. Bergmann , M.G. Besoiu , L. Betev , P.P. Bhaduri ,A. Bhasin , I.R. Bhat , M.A. Bhat , B. Bhattacharjee , P. Bhattacharya , A. Bianchi , L. Bianchi ,N. Bianchi , J. Bielˇcík , J. Bielˇcíková , A. Bilandzic , G. Biro , S. Biswas , J.T. Blair , D. Blau ,M.B. Blidaru , C. Blume , G. Boca , F. Bock , A. Bogdanov , S. Boi , J. Bok , L. Boldizsár ,A. Bolozdynya , M. Bombara , P.M. Bond , G. Bonomi , H. Borel , A. Borissov , , H. Bossi ,E. Botta , L. Bratrud , P. Braun-Munzinger , M. Bregant , M. Broz , G.E. Bruno , , M.D. Buckland ,D. Budnikov , H. Buesching , S. Bufalino , O. Bugnon , P. Buhler , P. Buncic , Z. Buthelezi , ,J.B. Butt , S.A. Bysiak , D. Caffarri , A. Caliva , E. Calvo Villar , J.M.M. Camacho , R.S. Camacho ,P. Camerini , F.D.M. Canedo , A.A. Capon , F. Carnesecchi , R. Caron , J. Castillo Castellanos ,E.A.R. Casula , F. Catalano , C. Ceballos Sanchez , P. Chakraborty , S. Chandra , W. Chang ,S. Chapeland , M. Chartier , S. Chattopadhyay , S. Chattopadhyay , A. Chauvin , T.G. Chavez ,C. Cheshkov , B. Cheynis , V. Chibante Barroso , D.D. Chinellato , S. Cho , P. Chochula ,P. Christakoglou , C.H. Christensen , P. Christiansen , T. Chujo , C. Cicalo , L. Cifarelli , F. Cindolo ,M.R. Ciupek , G. Clai II , , J. Cleymans , F. Colamaria , J.S. Colburn , D. Colella , , A. Collu ,M. Colocci , , M. Concas III , , G. Conesa Balbastre , Z. Conesa del Valle , G. Contin , J.G. Contreras ,T.M. Cormier , P. Cortese , M.R. Cosentino , F. Costa , S. Costanza , P. Crochet , E. Cuautle , P. Cui ,L. Cunqueiro , A. Dainese , F.P.A. Damas , , M.C. Danisch , A. Danu , I. Das , P. Das , P. Das ,S. Das , S. Dash , S. De , A. De Caro , G. de Cataldo , L. De Cilladi , J. de Cuveland , A. De Falco ,D. De Gruttola , N. De Marco , C. De Martin , S. De Pasquale , S. Deb , H.F. Degenhardt , K.R. Deja ,L. Dello Stritto , S. Delsanto , W. Deng , P. Dhankher , D. Di Bari , A. Di Mauro , R.A. Diaz , T. Dietel ,Y. Ding , R. Divià , D.U. Dixit , Ø. Djuvsland , U. Dmitrieva , J. Do , A. Dobrin , B. Dönigus ,O. Dordic , A.K. Dubey , A. Dubla , , S. Dudi , M. Dukhishyam , P. Dupieux , T.M. Eder ,R.J. Ehlers , V.N. Eikeland , D. Elia , B. Erazmus , F. Ercolessi , F. Erhardt , A. Erokhin ,M.R. Ersdal , B. Espagnon , G. Eulisse , D. Evans , S. Evdokimov , L. Fabbietti , M. Faggin ,J. Faivre , F. Fan , A. Fantoni , M. Fasel , P. Fecchio , A. Feliciello , G. Feofilov , A. Fernández Téllez ,A. Ferrero , A. Ferretti , A. Festanti , V.J.G. Feuillard , J. Figiel , S. Filchagin , D. Finogeev ,F.M. Fionda , G. Fiorenza , F. Flor , A.N. Flores , S. Foertsch , P. Foka , S. Fokin , E. Fragiacomo ,U. Fuchs , N. Funicello , C. Furget , A. Furs , M. Fusco Girard , J.J. Gaardhøje , M. Gagliardi ,A.M. Gago , A. Gal , C.D. Galvan , P. Ganoti , C. Garabatos , J.R.A. Garcia , E. Garcia-Solis ,K. Garg , C. Gargiulo , A. Garibli , K. Garner , P. Gasik , E.F. Gauger , M.B. Gay Ducati ,M. Germain , J. Ghosh , P. Ghosh , S.K. Ghosh , M. Giacalone , P. Gianotti , P. Giubellino , ,P. Giubilato , A.M.C. Glaenzer , P. Glässel , V. Gonzalez , L.H. González-Trueba , S. Gorbunov ,L. Görlich , S. Gotovac , V. Grabski , L.K. Graczykowski , K.L. Graham , L. Greiner , A. Grelli ,C. Grigoras , V. Grigoriev , A. Grigoryan I , , S. Grigoryan , , O.S. Groettvik , F. Grosa ,J.F. Grosse-Oetringhaus , R. Grosso , R. Guernane , M. Guilbaud , M. Guittiere , K. Gulbrandsen ,T. Gunji , A. Gupta , R. Gupta , I.B. Guzman , R. Haake , M.K. Habib , C. Hadjidakis ,H. Hamagaki , G. Hamar , M. Hamid , R. Hannigan , M.R. Haque , , A. Harlenderova ,J.W. Harris , A. Harton , J.A. Hasenbichler , H. Hassan , D. Hatzifotiadou , P. Hauer , L.B. Havener ,S. Hayashi , S.T. Heckel , E. Hellbär , H. Helstrup , T. Herman , E.G. Hernandez , G. Herrera Corral ,F. Herrmann , K.F. Hetland , H. Hillemanns , C. Hills , B. Hippolyte , B. Hohlweger ,J. Honermann , G.H. Hong , D. Horak , S. Hornung , R. Hosokawa , P. Hristov , C. Huang ,C. Hughes , P. Huhn , T.J. Humanic , H. Hushnud , L.A. Husova , N. Hussain , D. Hutter ,J.P. Iddon , , R. Ilkaev , H. Ilyas , M. Inaba , G.M. Innocenti , M. Ippolitov , A. Isakov , , √ s =
13 TeV ALICE Collaboration
M.S. Islam , M. Ivanov , V. Ivanov , V. Izucheev , B. Jacak , N. Jacazio , , P.M. Jacobs ,S. Jadlovska , J. Jadlovsky , S. Jaelani , C. Jahnke , M.J. Jakubowska , M.A. Janik , T. Janson ,M. Jercic , O. Jevons , M. Jin , F. Jonas , , P.G. Jones , J. Jung , M. Jung , A. Junique ,A. Jusko , P. Kalinak , A. Kalweit , V. Kaplin , S. Kar , A. Karasu Uysal , D. Karatovic ,O. Karavichev , T. Karavicheva , P. Karczmarczyk , E. Karpechev , A. Kazantsev , U. Kebschull ,R. Keidel , M. Keil , B. Ketzer , Z. Khabanova , A.M. Khan , S. Khan , A. Khanzadeev , Y. Kharlov ,A. Khatun , A. Khuntia , B. Kileng , B. Kim , D. Kim , D.J. Kim , E.J. Kim , H. Kim , J. Kim ,J.S. Kim , J. Kim , J. Kim , J. Kim , M. Kim , S. Kim , T. Kim , S. Kirsch , I. Kisel , S. Kiselev ,A. Kisiel , J.L. Klay , J. Klein , , S. Klein , C. Klein-Bösing , M. Kleiner , T. Klemenz , A. Kluge ,A.G. Knospe , C. Kobdaj , M.K. Köhler , T. Kollegger , A. Kondratyev , N. Kondratyeva ,E. Kondratyuk , J. Konig , S.A. Konigstorfer , P.J. Konopka , , G. Kornakov , S.D. Koryciak ,L. Koska , O. Kovalenko , V. Kovalenko , M. Kowalski , I. Králik , A. Kravˇcáková , L. Kreis ,M. Krivda , , F. Krizek , K. Krizkova Gajdosova , M. Kroesen , M. Krüger , E. Kryshen ,M. Krzewicki , V. Kuˇcera , C. Kuhn , P.G. Kuijer , T. Kumaoka , L. Kumar , S. Kundu ,P. Kurashvili , A. Kurepin , A.B. Kurepin , A. Kuryakin , S. Kushpil , J. Kvapil , M.J. Kweon ,J.Y. Kwon , Y. Kwon , S.L. La Pointe , P. La Rocca , Y.S. Lai , A. Lakrathok , M. Lamanna ,R. Langoy , K. Lapidus , P. Larionov , E. Laudi , L. Lautner , R. Lavicka , T. Lazareva , R. Lea ,J. Lee , J. Lehrbach , R.C. Lemmon , I. León Monzón , E.D. Lesser , M. Lettrich , P. Lévai , X. Li ,X.L. Li , J. Lien , R. Lietava , B. Lim , S.H. Lim , V. Lindenstruth , A. Lindner , C. Lippmann ,A. Liu , J. Liu , I.M. Lofnes , V. Loginov , C. Loizides , P. Loncar , J.A. Lopez , X. Lopez , E. LópezTorres , J.R. Luhder , M. Lunardon , G. Luparello , Y.G. Ma , A. Maevskaya , M. Mager ,S.M. Mahmood , T. Mahmoud , A. Maire , R.D. Majka I , , M. Malaev , Q.W. Malik , L. Malinina IV , ,D. Mal’Kevich , N. Mallick , P. Malzacher , G. Mandaglio , , V. Manko , F. Manso , V. Manzari ,Y. Mao , J. Mareš , G.V. Margagliotti , A. Margotti , A. Marín , C. Markert , M. Marquard ,N.A. Martin , P. Martinengo , J.L. Martinez , M.I. Martínez , G. Martínez García , S. Masciocchi ,M. Masera , A. Masoni , L. Massacrier , A. Mastroserio , , A.M. Mathis , O. Matonoha ,P.F.T. Matuoka , A. Matyja , C. Mayer , A.L. Mazuecos , F. Mazzaschi , M. Mazzilli , ,M.A. Mazzoni , A.F. Mechler , F. Meddi , Y. Melikyan , A. Menchaca-Rocha , C. Mengke , ,E. Meninno , , A.S. Menon , M. Meres , S. Mhlanga , Y. Miake , L. Micheletti , L.C. Migliorin ,D.L. Mihaylov , K. Mikhaylov , , A.N. Mishra , , D. Mi´skowiec , A. Modak , N. Mohammadi ,A.P. Mohanty , B. Mohanty , M. Mohisin Khan , Z. Moravcova , C. Mordasini , D.A. Moreira DeGodoy , L.A.P. Moreno , I. Morozov , A. Morsch , T. Mrnjavac , V. Muccifora , E. Mudnic ,D. Mühlheim , S. Muhuri , J.D. Mulligan , A. Mulliri , M.G. Munhoz , R.H. Munzer , H. Murakami ,S. Murray , L. Musa , J. Musinsky , C.J. Myers , J.W. Myrcha , B. Naik , R. Nair , B.K. Nandi ,R. Nania , E. Nappi , M.U. Naru , A.F. Nassirpour , C. Nattrass , S. Nazarenko , A. Neagu ,L. Nellen , S.V. Nesbo , G. Neskovic , D. Nesterov , B.S. Nielsen , S. Nikolaev , S. Nikulin ,V. Nikulin , F. Noferini , S. Noh , P. Nomokonov , J. Norman , N. Novitzky , P. Nowakowski ,A. Nyanin , J. Nystrand , M. Ogino , A. Ohlson , J. Oleniacz , A.C. Oliveira Da Silva , M.H. Oliver ,A. Onnerstad , C. Oppedisano , A. Ortiz Velasquez , T. Osako , A. Oskarsson , J. Otwinowski ,K. Oyama , Y. Pachmayer , S. Padhan , D. Pagano , G. Pai´c , A. Palasciano , J. Pan ,S. Panebianco , P. Pareek , J. Park , J.E. Parkkila , S. Parmar , S.P. Pathak , B. Paul , J. Pazzini ,H. Pei , T. Peitzmann , X. Peng , L.G. Pereira , H. Pereira Da Costa , D. Peresunko , G.M. Perez ,S. Perrin , Y. Pestov , V. Petráˇcek , M. Petrovici , R.P. Pezzi , S. Piano , M. Pikna , P. Pillot ,O. Pinazza , , L. Pinsky , C. Pinto , S. Pisano , M. Płosko´n , M. Planinic , F. Pliquett ,M.G. Poghosyan , B. Polichtchouk , N. Poljak , A. Pop , S. Porteboeuf-Houssais , J. Porter ,V. Pozdniakov , S.K. Prasad , R. Preghenella , F. Prino , C.A. Pruneau , I. Pshenichnov , M. Puccio ,S. Qiu , L. Quaglia , R.E. Quishpe , S. Ragoni , A. Rakotozafindrabe , L. Ramello , F. Rami ,S.A.R. Ramirez , A.G.T. Ramos , R. Raniwala , S. Raniwala , S.S. Räsänen , R. Rath , I. Ravasenga ,K.F. Read , , A.R. Redelbach , K. Redlich V , , A. Rehman , P. Reichelt , F. Reidt , R. Renfordt ,Z. Rescakova , K. Reygers , A. Riabov , V. Riabov , T. Richert , , M. Richter , P. Riedler ,W. Riegler , F. Riggi , C. Ristea , S.P. Rode , M. Rodríguez Cahuantzi , K. Røed , R. Rogalev ,E. Rogochaya , T.S. Rogoschinski , D. Rohr , D. Röhrich , P.F. Rojas , P.S. Rokita , F. Ronchetti ,A. Rosano , , E.D. Rosas , A. Rossi , A. Rotondi , A. Roy , P. Roy , N. Rubini , O.V. Rueda ,R. Rui , B. Rumyantsev , A. Rustamov , E. Ryabinkin , Y. Ryabov , A. Rybicki , H. Rytkonen ,W. Rzesa , O.A.M. Saarimaki , R. Sadek , S. Sadovsky , J. Saetre , K. Šafaˇrík , S.K. Saha , S. Saha ,B. Sahoo , P. Sahoo , R. Sahoo , S. Sahoo , D. Sahu , P.K. Sahu , J. Saini , S. Sakai , S. Sambyal , √ s =
13 TeV ALICE Collaboration
V. Samsonov I , , , D. Sarkar , N. Sarkar , P. Sarma , V.M. Sarti , M.H.P. Sas , , J. Schambach , ,H.S. Scheid , C. Schiaua , R. Schicker , A. Schmah , C. Schmidt , H.R. Schmidt , M.O. Schmidt ,M. Schmidt , N.V. Schmidt , , A.R. Schmier , R. Schotter , J. Schukraft , Y. Schutz , K. Schwarz ,K. Schweda , G. Scioli , E. Scomparin , J.E. Seger , Y. Sekiguchi , D. Sekihata , I. Selyuzhenkov , ,S. Senyukov , J.J. Seo , D. Serebryakov , L. Šerkšnyt˙e , A. Sevcenco , A. Shabanov , A. Shabetai ,R. Shahoyan , W. Shaikh , A. Shangaraev , A. Sharma , H. Sharma , M. Sharma , N. Sharma ,S. Sharma , O. Sheibani , A.I. Sheikh , K. Shigaki , M. Shimomura , S. Shirinkin , Q. Shou ,Y. Sibiriak , S. Siddhanta , T. Siemiarczuk , T.F.D. Silva , D. Silvermyr , G. Simatovic , G. Simonetti ,B. Singh , R. Singh , R. Singh , R. Singh , V.K. Singh , V. Singhal , T. Sinha , B. Sitar , M. Sitta ,T.B. Skaali , G. Skorodumovs , M. Slupecki , N. Smirnov , R.J.M. Snellings , C. Soncco , J. Song ,A. Songmoolnak , F. Soramel , S. Sorensen , I. Sputowska , J. Stachel , I. Stan , P.J. Steffanic ,S.F. Stiefelmaier , D. Stocco , M.M. Storetvedt , C.P. Stylianidis , A.A.P. Suaide , T. Sugitate ,C. Suire , M. Suljic , R. Sultanov , M. Šumbera , V. Sumberia , S. Sumowidagdo , S. Swain ,A. Szabo , I. Szarka , U. Tabassam , S.F. Taghavi , G. Taillepied , J. Takahashi , G.J. Tambave ,S. Tang , , Z. Tang , M. Tarhini , M.G. Tarzila , A. Tauro , G. Tejeda Muñoz , A. Telesca ,L. Terlizzi , C. Terrevoli , G. Tersimonov , S. Thakur , D. Thomas , R. Tieulent , A. Tikhonov ,A.R. Timmins , M. Tkacik , A. Toia , N. Topilskaya , M. Toppi , F. Torales-Acosta , S.R. Torres ,A. Trifiró , , S. Tripathy , T. Tripathy , S. Trogolo , G. Trombetta , L. Tropp , V. Trubnikov ,W.H. Trzaska , T.P. Trzcinski , B.A. Trzeciak , A. Tumkin , R. Turrisi , T.S. Tveter , K. Ullaland ,E.N. Umaka , A. Uras , M. Urioni , G.L. Usai , M. Vala , N. Valle , S. Vallero , N. van der Kolk ,L.V.R. van Doremalen , M. van Leeuwen , P. Vande Vyvre , D. Varga , Z. Varga , M. Varga-Kofarago ,A. Vargas , M. Vasileiou , A. Vasiliev , O. Vázquez Doce , V. Vechernin , E. Vercellin , S. VergaraLimón , L. Vermunt , R. Vértesi , M. Verweij , L. Vickovic , Z. Vilakazi , O. Villalobos Baillie ,G. Vino , A. Vinogradov , T. Virgili , V. Vislavicius , A. Vodopyanov , B. Volkel , M.A. Völkl ,K. Voloshin , S.A. Voloshin , G. Volpe , B. von Haller , I. Vorobyev , D. Voscek , J. Vrláková ,B. Wagner , M. Weber , A. Wegrzynek , S.C. Wenzel , J.P. Wessels , J. Wiechula , J. Wikne ,G. Wilk , J. Wilkinson , G.A. Willems , E. Willsher , B. Windelband , M. Winn , W.E. Witt ,J.R. Wright , Y. Wu , R. Xu , S. Yalcin , Y. Yamaguchi , K. Yamakawa , S. Yang , S. Yano , ,Z. Yin , H. Yokoyama , I.-K. Yoo , J.H. Yoon , S. Yuan , A. Yuncu , V. Yurchenko , V. Zaccolo ,A. Zaman , C. Zampolli , H.J.C. Zanoli , N. Zardoshti , A. Zarochentsev , P. Závada , N. Zaviyalov ,H. Zbroszczyk , M. Zhalov , S. Zhang , X. Zhang , Y. Zhang , V. Zherebchevskii , Y. Zhi , D. Zhou ,Y. Zhou , J. Zhu , , Y. Zhu , A. Zichichi , G. Zinovjev , N. Zurlo Affiliation notes I Deceased II Also at: Italian National Agency for New Technologies, Energy and Sustainable Economic Development(ENEA), Bologna, Italy
III
Also at: Dipartimento DET del Politecnico di Torino, Turin, Italy IV Also at: M.V. Lomonosov Moscow State University, D.V. Skobeltsyn Institute of Nuclear, Physics, Moscow,Russia V Also at: Institute of Theoretical Physics, University of Wroclaw, Poland
Collaboration Institutes A.I. Alikhanyan National Science Laboratory (Yerevan Physics Institute) Foundation, Yerevan, Armenia AGH University of Science and Technology, Cracow, Poland Bogolyubov Institute for Theoretical Physics, National Academy of Sciences of Ukraine, Kiev, Ukraine Bose Institute, Department of Physics and Centre for Astroparticle Physics and Space Science (CAPSS),Kolkata, India Budker Institute for Nuclear Physics, Novosibirsk, Russia California Polytechnic State University, San Luis Obispo, California, United States Central China Normal University, Wuhan, China Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN), Havana, Cuba Centro de Investigación y de Estudios Avanzados (CINVESTAV), Mexico City and Mérida, Mexico Chicago State University, Chicago, Illinois, United States √ s =
13 TeV ALICE Collaboration China Institute of Atomic Energy, Beijing, China Chungbuk National University, Cheongju, Republic of Korea Comenius University Bratislava, Faculty of Mathematics, Physics and Informatics, Bratislava, Slovakia COMSATS University Islamabad, Islamabad, Pakistan Creighton University, Omaha, Nebraska, United States Department of Physics, Aligarh Muslim University, Aligarh, India Department of Physics, Pusan National University, Pusan, Republic of Korea Department of Physics, Sejong University, Seoul, Republic of Korea Department of Physics, University of California, Berkeley, California, United States Department of Physics, University of Oslo, Oslo, Norway Department of Physics and Technology, University of Bergen, Bergen, Norway Dipartimento di Fisica dell’Università ’La Sapienza’ and Sezione INFN, Rome, Italy Dipartimento di Fisica dell’Università and Sezione INFN, Cagliari, Italy Dipartimento di Fisica dell’Università and Sezione INFN, Trieste, Italy Dipartimento di Fisica dell’Università and Sezione INFN, Turin, Italy Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN, Bologna, Italy Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN, Catania, Italy Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN, Padova, Italy Dipartimento di Fisica e Nucleare e Teorica, Università di Pavia and Sezione INFN, Pavia, Italy Dipartimento di Fisica ‘E.R. Caianiello’ dell’Università and Gruppo Collegato INFN, Salerno, Italy Dipartimento DISAT del Politecnico and Sezione INFN, Turin, Italy Dipartimento di Scienze e Innovazione Tecnologica dell’Università del Piemonte Orientale and INFN Sezionedi Torino, Alessandria, Italy Dipartimento di Scienze MIFT, Università di Messina, Messina, Italy Dipartimento Interateneo di Fisica ‘M. Merlin’ and Sezione INFN, Bari, Italy European Organization for Nuclear Research (CERN), Geneva, Switzerland Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, Split,Croatia Faculty of Engineering and Science, Western Norway University of Applied Sciences, Bergen, Norway Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University in Prague, Prague, CzechRepublic Faculty of Science, P.J. Šafárik University, Košice, Slovakia Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe-Universität Frankfurt, Frankfurt, Germany Fudan University, Shanghai, China Gangneung-Wonju National University, Gangneung, Republic of Korea Gauhati University, Department of Physics, Guwahati, India Helmholtz-Institut für Strahlen- und Kernphysik, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn,Germany Helsinki Institute of Physics (HIP), Helsinki, Finland High Energy Physics Group, Universidad Autónoma de Puebla, Puebla, Mexico Hiroshima University, Hiroshima, Japan Hochschule Worms, Zentrum für Technologietransfer und Telekommunikation (ZTT), Worms, Germany Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest, Romania Indian Institute of Technology Bombay (IIT), Mumbai, India Indian Institute of Technology Indore, Indore, India Indonesian Institute of Sciences, Jakarta, Indonesia INFN, Laboratori Nazionali di Frascati, Frascati, Italy INFN, Sezione di Bari, Bari, Italy INFN, Sezione di Bologna, Bologna, Italy INFN, Sezione di Cagliari, Cagliari, Italy INFN, Sezione di Catania, Catania, Italy INFN, Sezione di Padova, Padova, Italy INFN, Sezione di Roma, Rome, Italy INFN, Sezione di Torino, Turin, Italy INFN, Sezione di Trieste, Trieste, Italy Inha University, Incheon, Republic of Korea √ s =
13 TeV ALICE Collaboration Institute for Gravitational and Subatomic Physics (GRASP), Utrecht University/Nikhef, Utrecht, Netherlands Institute for Nuclear Research, Academy of Sciences, Moscow, Russia Institute of Experimental Physics, Slovak Academy of Sciences, Košice, Slovakia Institute of Physics, Homi Bhabha National Institute, Bhubaneswar, India Institute of Physics of the Czech Academy of Sciences, Prague, Czech Republic Institute of Space Science (ISS), Bucharest, Romania Institut für Kernphysik, Johann Wolfgang Goethe-Universität Frankfurt, Frankfurt, Germany Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Mexico City, Mexico Instituto de Física, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil Instituto de Física, Universidad Nacional Autónoma de México, Mexico City, Mexico iThemba LABS, National Research Foundation, Somerset West, South Africa Jeonbuk National University, Jeonju, Republic of Korea Johann-Wolfgang-Goethe Universität Frankfurt Institut für Informatik, Fachbereich Informatik undMathematik, Frankfurt, Germany Joint Institute for Nuclear Research (JINR), Dubna, Russia Korea Institute of Science and Technology Information, Daejeon, Republic of Korea KTO Karatay University, Konya, Turkey Laboratoire de Physique des 2 Infinis, Irène Joliot-Curie, Orsay, France Laboratoire de Physique Subatomique et de Cosmologie, Université Grenoble-Alpes, CNRS-IN2P3, Grenoble,France Lawrence Berkeley National Laboratory, Berkeley, California, United States Lund University Department of Physics, Division of Particle Physics, Lund, Sweden Moscow Institute for Physics and Technology, Moscow, Russia Nagasaki Institute of Applied Science, Nagasaki, Japan Nara Women’s University (NWU), Nara, Japan National and Kapodistrian University of Athens, School of Science, Department of Physics , Athens, Greece National Centre for Nuclear Research, Warsaw, Poland National Institute of Science Education and Research, Homi Bhabha National Institute, Jatni, India National Nuclear Research Center, Baku, Azerbaijan National Research Centre Kurchatov Institute, Moscow, Russia Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark Nikhef, National institute for subatomic physics, Amsterdam, Netherlands NRC Kurchatov Institute IHEP, Protvino, Russia NRC «Kurchatov»Institute - ITEP, Moscow, Russia NRNU Moscow Engineering Physics Institute, Moscow, Russia Nuclear Physics Group, STFC Daresbury Laboratory, Daresbury, United Kingdom Nuclear Physics Institute of the Czech Academy of Sciences, ˇRež u Prahy, Czech Republic Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States Ohio State University, Columbus, Ohio, United States
Petersburg Nuclear Physics Institute, Gatchina, Russia
Physics department, Faculty of science, University of Zagreb, Zagreb, Croatia
Physics Department, Panjab University, Chandigarh, India
Physics Department, University of Jammu, Jammu, India
Physics Department, University of Rajasthan, Jaipur, India
Physikalisches Institut, Eberhard-Karls-Universität Tübingen, Tübingen, Germany
Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg, Germany
Physik Department, Technische Universität München, Munich, Germany
Politecnico di Bari and Sezione INFN, Bari, Italy
Research Division and ExtreMe Matter Institute EMMI, GSI Helmholtzzentrum für SchwerionenforschungGmbH, Darmstadt, Germany
Rudjer Boškovi´c Institute, Zagreb, Croatia
Russian Federal Nuclear Center (VNIIEF), Sarov, Russia
Saha Institute of Nuclear Physics, Homi Bhabha National Institute, Kolkata, India
School of Physics and Astronomy, University of Birmingham, Birmingham, United Kingdom
Sección Física, Departamento de Ciencias, Pontificia Universidad Católica del Perú, Lima, Peru
St. Petersburg State University, St. Petersburg, Russia √ s =
13 TeV ALICE Collaboration
Stefan Meyer Institut für Subatomare Physik (SMI), Vienna, Austria
SUBATECH, IMT Atlantique, Université de Nantes, CNRS-IN2P3, Nantes, France
Suranaree University of Technology, Nakhon Ratchasima, Thailand
Technical University of Košice, Košice, Slovakia
The Henryk Niewodniczanski Institute of Nuclear Physics, Polish Academy of Sciences, Cracow, Poland
The University of Texas at Austin, Austin, Texas, United States
Universidad Autónoma de Sinaloa, Culiacán, Mexico
Universidade de São Paulo (USP), São Paulo, Brazil
Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil
Universidade Federal do ABC, Santo Andre, Brazil
University of Cape Town, Cape Town, South Africa
University of Houston, Houston, Texas, United States
University of Jyväskylä, Jyväskylä, Finland
University of Liverpool, Liverpool, United Kingdom
University of Science and Technology of China, Hefei, China
University of South-Eastern Norway, Tonsberg, Norway
University of Tennessee, Knoxville, Tennessee, United States
University of the Witwatersrand, Johannesburg, South Africa
University of Tokyo, Tokyo, Japan
University of Tsukuba, Tsukuba, Japan
Université Clermont Auvergne, CNRS/IN2P3, LPC, Clermont-Ferrand, France
Université de Lyon, CNRS/IN2P3, Institut de Physique des 2 Infinis de Lyon , Lyon, France
Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000 Strasbourg, France, Strasbourg, France
Université Paris-Saclay Centre d’Etudes de Saclay (CEA), IRFU, Départment de Physique Nucléaire (DPhN),Saclay, France
Università degli Studi di Foggia, Foggia, Italy
Università di Brescia and Sezione INFN, Brescia, Italy
Variable Energy Cyclotron Centre, Homi Bhabha National Institute, Kolkata, India
Warsaw University of Technology, Warsaw, Poland
Wayne State University, Detroit, Michigan, United States
Westfälische Wilhelms-Universität Münster, Institut für Kernphysik, Münster, Germany
Wigner Research Centre for Physics, Budapest, Hungary
Yale University, New Haven, Connecticut, United States