Measurement of jet radial profiles in Pb − Pb collisions at s NN − − − √ = 2.76 TeV
aa r X i v : . [ nu c l - e x ] N ov EUROPEAN ORGANIZATION FOR NUCLEAR RESEARCH
CERN-EP-2019-07930 April 2019c (cid:13)
Measurement of jet radial profilesin Pb–Pb collisions at √ s NN = 2.76 TeV ALICE Collaboration ∗ Abstract
The jet radial structure and particle transverse momentum ( p T ) composition within jetsare presented in centrality-selected Pb–Pb collisions at √ s NN = .
76 TeV. Track-basedjets, which are also called charged jets, were reconstructed with a resolution parameter of R = . | η chjet | < . p T , chjet = c . Jet–hadron correlations in relative azimuth and pseudorapidity space ( ∆ϕ , ∆η ) are measuredto study the distribution of the associated particles around the jet axis for different p T , assoc -ranges between 1 and 20 GeV/ c . The data in Pb–Pb collisions are compared to referencedistributions for pp collisions, obtained using embedded PYTHIA simulations. The num-ber of high- p T associate particles (4 < p T , assoc <
20 GeV/ c ) in Pb–Pb collisions is found tobe suppressed compared to the reference by 30 to 10%, depending on centrality. The radialparticle distribution relative to the jet axis shows a moderate modification in Pb–Pb col-lisions with respect to PYTHIA. High- p T associate particles are slightly more collimatedin Pb–Pb collisions compared to the reference, while low- p T associate particle tend to bebroadened. The results, which are presented for the first time down to p T , chjet =
30 GeV/ c in Pb–Pb collisions, are compatible with both previous jet–hadron-related measurementsfrom the CMS Collaboration and jet shape measurements from the ALICE Collaboration athigher p T , and add further support for the established picture of in-medium parton energyloss. ∗ See Appendix A for the list of collaboration members et radial profiles in Pb–Pb collisions ALICE Collaboration
At energy densities above approximately 0 . and temperatures above approximately160 MeV [1], Quantum Chromodynamics (QCD) calculations on the lattice predict the ex-istence of a phase transition from normal nuclear matter to a new state of matter called theQuark–Gluon Plasma (QGP), where the partonic constituents, quarks and gluons, are no longerconfined in hadrons. There is compelling evidence from observations reported by experimentsat the Relativistic Heavy Ion Collider (RHIC) [2–5] and at the Large Hadron Collider (LHC) [6–17] that the QGP is created in nuclear collisions at high collisions energies.A unique way to characterize the properties of the QGP is to utilize jets as a probe of themedium. Hard scatterings are expected to occur early in the collision evolution, producinghigh transverse momentum ( p T ) partons that propagate through the expanding medium andeventually fragment into jets of hadrons. High- p T partons lose energy in interactions with themedium due to elastic scattering and induced gluon radiation [18, 19]. Besides a reduction ofthe jet energy, this can result in a broadening of the transverse jet profile and a softening of thefragmentation [20].Jet quenching has been observed at RHIC [21–34] and at the LHC [8, 16, 17, 35–47], e.g. viainclusive yield and correlation measurements of high- p T hadrons and reconstructed jets. Thesemeasurements provide insights into the mechanisms of parton energy loss in the medium andeventually into the medium itself.More differential measurements of the jet modification in a medium, i.e. measurements of mod-ifications of jet angular profile and particle composition, can provide complementary informa-tion to observables that focus on the overall yield change like nuclear modification factors.Measurements of correlated associated particle production relative to jets or high- p T particlesallow for a detailed measurement of the redistribution of quenched energy around the jet. Anexcess of low- p T particles in and around the jet up to large distances, as well as a suppressionof high- p T particles, have been reported [17, 48–50]. Two-particle correlations and jet–hadroncorrelations show an angular broadening of low- p T particles below 3 GeV/ c in heavy-ion col-lisions with respect to pp collisions [50]. For low- p T two-particle correlations, measurementsalso indicate an asymmetry in the shape of the near-side jet peaks: they are broader in ∆η compared to ∆ϕ [48, 49]. The variables ∆η and ∆ϕ are the distance in pseudorapidity η andazimuth ϕ relative to the near-side jet. At the same time, measurements of the radial momentof jets point to a general collimation of jets in Pb–Pb collisions [51].Using jets instead of high- p T particles as a reference (trigger) to study angular correlations—as done in this analysis—should have the advantage that jet properties better reflect the initialparton energy. This analysis extends the study of jet–hadron correlations into a regime of lowtrack-based jet p T , chjet not yet explored with these techniques at the LHC.In this paper, we study the correlation of charged particles (associates) with the direction ofreconstructed track-based jets (triggers) in the ∆ϕ - ∆η plane in the same event. The jets arereconstructed using charged particles above a certain transverse momentum p T , const . The anal-ysis focuses on two aspects of the modification of jets within the medium created in Pb–Pbcollisions compared to a PYTHIA [52] reference. First, the overall modification of the asso-ciated particle yield and its jet-energy dependence is studied. Second, the modification of theradial distribution of associated particles with respect to the jet axis is studied by comparingthe Pb–Pb results to the PYTHIA reference. Both aspects are analyzed in detail for several jet2et radial profiles in Pb–Pb collisions ALICE Collaborationtransverse momenta p T , chjet and low and high p T of associated charged particles. PYTHIA isused as vacuum baseline, because the size of the pp dataset at √ s = .
76 TeV is insufficient forthis analysis.The paper is structured as follows. In Sec. 2, details on the detector and general data reconstruc-tion will be given. The correlation analysis, which serves as basis for this paper, is presentedin Sec. 3. Subsequently, jet reconstruction will be described in Sec. 4, followed by a discussionon the embedded PYTHIA reference in Sec. 5. Before the results will be presented in Sec. 8,the observables are introduced in Sec. 6 and systematic uncertainties are discussed in Sec. 7. Asummary concludes the paper in Sec. 9.
For a complete description of the ALICE detector and its performance see Refs. [53] and [54],respectively.The data were recorded in 2011 for Pb–Pb collisions at √ s NN = .
76 TeV using a set of cen-trality triggers based on the hit multiplicity measured by the V0 detector, which consists of seg-mented scintillators covering the full azimuth over 2 . < η < . − . < η < − . . . . < p T <
100 GeV/ c in | η | < .
9, and to have at least 70 TPC space-points and no less than 80% ofthe geometrically findable space-points in the TPC.The single-track tracking efficiency was estimated from the detector response of HIJING [57]events reconstructed to detector level using GEANT3 [58] for the particle transport. In the 0–10% centrality class, it is about 56% at 0 .
15 GeV/ c , about 83% at 1 . c and then decreasesto 81% at 3 GeV/ c , after which it increases and levels off to about 83% at above 6.5 GeV/ c . Forthe 10–30% most central collisions, the tracking efficiency follows a similar p T -dependencepattern, with absolute values of the efficiency that are 1 to 2% higher compared to the 0–10%most central collisions. The momentum resolution, which was estimated on a track-by-trackbasis using the covariance matrix of the track fit, is about 1% at 1 GeV/ c and about 3% at3et radial profiles in Pb–Pb collisions ALICE Collaboration50 GeV/ c . The contamination by secondary particles [59] produced in particle-material inter-actions, conversions, and weak-decay products of long-lived particles is on the level of fewpercent. The two-dimensional associated per-trigger yield Y ( ∆ϕ , ∆η ) measures the distribution of parti-cles relative to the jet axes in bins of ∆ϕ , ∆η , event centrality, and trigger and associate trans-verse momenta p T , assoc [60]. This distribution serves as the basis of the analysis and is formedusing so-called same and mixed event correlations. Correlations from the same event are theactual correlations of trigger jets and associated particles, calculated for each selected event.In the mixed event technique, jets are correlated with particles from a pool containing tracksfrom different events with similar trigger jet p T , vertex z , and centralities. For vertex z , thereare six bins in this pool, whose boundaries are given by ( − , − , − , , , , ) in cm. Theboundaries for the centrality percentile binning are given by ( , , , , , , , , , , ) .The mixed-event-corrected associated per-trigger yield for given jet p T -range, associate p T -range, and centrality selection is defined as Y ( ∆ϕ , ∆η ) = N trig d N assoc d ∆η d ∆ϕ = N trig ∑ cent , z (cid:18) d N same d ∆η d ∆ϕ (cid:30) α d N mixed d ∆η d ∆ϕ (cid:19) , (1)where the ratios in the sum are formed differentially in bins of centrality and vertex z .The factor α in Eq. 1 is chosen such that the mixed-event correlations are normalized to unityin the region | ∆η | < . | ∆ϕ | < . η , p T , centrality, and vertex z for sameand mixed event correlations in Eq. 1. The efficiency maps were created using Monte Carlosimulations for the same track definition and detector conditions. However, this correction turnsout to be negligible for all observables except for the absolute jet-associated yields, because itseffect mostly cancels in the used relative observables, which will be defined in Sec. 6.In addition to the correction for detector inhomogenities and acceptance effects, the correlationalso needs to be corrected for background. The underlying background for the chosen observ-ables mainly consists of the uncorrelated particle background baseline from soft processes andthe flow modulation in the correlation function. The background was found to be independent of ∆η within | η | < . ∆ϕ for the whole ∆η -rangeas B ( ∆ϕ ) . To avoid including parts of the jet signal, B ( ∆ϕ ) is calculated in 1 . < | ∆η | < . Y corr ( ∆ϕ , ∆η ) = Y ( ∆ϕ , ∆η ) − B ( ∆ϕ ) . (2)4et radial profiles in Pb–Pb collisions ALICE Collaboration ϕ ∆ − η ∆ − − ) η ∆ d ϕ ∆ / ( d a ss o c N d t r i g N / c = 4-20 GeV/ T, assoc p c = 60-80 GeV/
T, ch jet p c > 0.15 GeV/
T, const p ϕ ∆ − η ∆ − − ) η ∆ d ϕ ∆ / ( d a ss o c N d t r i g N / c = 1-2 GeV/ T, assoc p c = 30-40 GeV/
T, ch jet p c ≥ T, const p = 0.3 R jets T k Charged anti-ALICE 0-10% Pb-Pb 2.76 TeV
Fig. 1:
Illustration of per-trigger yields for the two different jet definitions (further discussed below):high- p T associates of jets with p T , const ≥ .
15 GeV/ c and p T , chjet = c (left) and low- p T associates of jets with p T , const ≥ . c and p T , chjet = c (right). No background sub-traction was applied. To illustrate the impact of the background on the per-trigger yields, the uncorrected per-triggeryields can be found in Fig. 1 for high- and low- p T associates. The background is nearly negli-gible for high- p T associates and it is sizeable for low- p T associates. In the illustrated examplefor low- p T associates, the signal to signal+background ratio, i.e. the percentage of the signal inthe measured observable, is roughly 0.1 within a radius of r < . ∆η -independent correlations, includingthe away-side ridge which is not investigated in the presented analysis. The measurement of jets in heavy-ion collisions is challenging since a single event can con-tain multiple, possibly overlapping, jets from independent hard nucleon–nucleon scatterings. Inaddition, low transverse momentum particles originating from soft processes lead to a fluctuat-ing background which strongly influences the jet reconstruction. The relative effect is largestfor low- p T jets and most central events. Consequently, jet reconstruction in heavy-ion colli-sions requires a robust jet definition, and a procedure to correct for the presence of the largebackground [62].Jets were reconstructed using the anti- k T or the k T algorithms [63] in the FastJet package [64]with a resolution parameter of R = .
3. Only those jets whose axis was reconstructed within | η | < . | η | < .
9. This limits the effect of the acceptance boundaries on themeasured jet spectrum. Jets reconstructed by the anti- k T algorithm were used to quantify signaljets, while jets reconstructed by the k T algorithm were used to quantify the contribution fromthe underlying event [65].Two different jet definitions are used in this analysis: for measurements at high associate- p T ,jets are measured with a constituent cut p T , const ≥ .
15 GeV/ c , measurements at low associate- p T are performed for jets measured with a constituent cut p T , const ≥ . c . Jets with p T , const ≥ .
15 GeV/ c are reconstructed using all charged particles available for jet reconstruc-5et radial profiles in Pb–Pb collisions ALICE Collaborationtion and, thus, the fragmentation bias is as small as possible. This bias is caused by onlyincluding certain particles of the jet and could lead to a sample of harder fragmenting jets whenleaving out particles at low p T . On the other hand, using all charged particles available for jetreconstruction also includes particles in the correlation analysis which were already used in thejet finding process. The jet finding algorithm selects regions in momentum space with largeenergy flow. This implies that the distribution of charged particles inside the jet is biased. Forexample, the radial distribution of particles with respect to the jet axis will show a small de-pletion at distances just outside the jet cone radius R . This particularly affects the shape of thejet, i.e. how the constituents are distributed relative to the jet axis, leading to an autocorrelationbias.Therefore, the jets themselves and in particular their shapes are intimately connected to the jetdefinition. For high- p T associates, the autocorrelation bias cannot be avoided and has to beaccepted as a part of the jet definition.Low- p T associates are broadly distributed up to large distances relative to the jet. Since thejet finding algorithm clusters the jets roughly into cones with a nominal radius of R = . p T associates, weavoid the autocorrelation bias by adapting the jet definition: Trigger jets and associates canbe decoupled by using jets with constituents above a certain threshold and associates below the threshold. Therefore, for measurements at low associate- p T , jets are reconstructed with p T , const ≥ c . Using a geometrical matching procedure that is performed on two col-lections of the differently defined jets which are reconstructed in each event it was checkedthat the jet axes for both jet definitions do not strongly change. For instance, for jets with p T , const ≥ c and p T , chjet >
30 GeV/ c the mean and standard deviation of the matchedjet distance distribution are approximately given by 0 .
016 and 0 . .
15 GeV/ c isaffected by the contribution from the underlying event. In order to suppress the contribution ofsuch background to the measurement of the jet momentum, we followed the approach describedin Refs. [65, 66], which addresses the average additive contribution to the jet momentum on ajet-by-jet basis. The underlying background momentum density ρ was estimated event-by-event using the median of p rawT , jet / A jet , where p rawT , jet is the uncorrected jet transverse momentumand A jet is the area of jets reconstructed with the k T algorithm.The average raw background momentum density h ρ i decreases towards more peripheral colli-sions. It is h ρ i ≈ ,
65, and 25 GeV/ c in the 0–10%, 10–30%, and 30–50% most centralPb–Pb collisions, respectively. The background momentum density is a detector-level quan-tity that depends on the tracking efficiency and track definition. For signal jets reconstructedwith the anti- k T algorithm and constituents above 0 .
15 GeV/ c , the background density scaledby the area of the reconstructed signal jet was subtracted from the raw reconstructed transversemomentum ( p rawT , jet ) of the signal jet according to p T , chjet = p rawT , jet − ρ · A jet .Due to region-to-region variations of the background, the background-corrected jet transversemomenta are affected by residual fluctuations. To give an estimate for these fluctuations for thejet definition used, cones with radius R = . δ p T : δ p T = ∑ cone p T , track − ρ · A , (3)where A is the area of the cone.For the 0–10%, 10–30%, and 30–50% most central collisions, the standard deviation of the δ p T -distribution as a measure for the magnitude of the fluctuations has been evaluated to 6 . .
1, and 3 . c , respectively. Since the δ p T -distribution also contains the jet signal, thestandard deviation of the full distribution is impacted by it. A lower limit of these fluctuationsis given by performing a Gaussian fit of the left-hand side of the δ p T -distribution. The Gaussianwidths were evaluated to 5 .
5, 4 .
0, and 2 . c for the 0–10%, 10–30%, and 30–50% mostcentral collisions. The sample of jets that only uses constituents above 3 GeV/ c is not correctedfor the underlying event as the constituent cut already strongly suppresses the contribution fromthe background such that it is negligible.In addition to background fluctuations, also the finite detector resolution and single particleefficiency influence the measurement. To quantify both effects, the ratio of reconstructed jetmomentum p T , rec and true jet momentum p T , true was calculated taking into account the de-tector resolution by using a response matrix and background fluctuations given by the δ p T distributions. The response matrix was created from Monte Carlo simulations for which thetrue jet momentum is known by geometrically matching particle-level PYTHIA jets with thecorresponding detector-level jets reconstructed using a full detector model in GEANT3. Moredetailed studies have been performed for jets on the same dataset in Ref. [66].There are two effects contributing to the jet momentum resolution: detector effects and under-lying event fluctuations. The detector effects lead to a jet momentum response that is peakedat p T , rec = p T , true , but has a tail to lower values of detector level momentum due to trackinginefficiency. The tracking efficiency changes by only a few percent from peripheral to centralevents. Background fluctuations produce an approximately Gaussian response, with a widththat depends strongly on centrality. The combined effect leads to a standard deviation in the jetmomentum resolution of 30% (20%) for jets with p T , chjet =
30 GeV/ c and 27% (27%) for jetswith p T , chjet =
120 GeV/ c for the 0–10% (10–30 and 30–50%) most central events.It should be emphasized that p T , chjet refers to the jet transverse momentum at detector level,corrected for background only. Since within-event fluctuations of the background are not cor-rected for, the mean of the given p T , chjet -range is slightly higher than that of the underlying true p T distribution for more central collisions where fluctations are dominant. Hence, due tothe steeply-falling jet spectrum, fluctuations lead to a shift of the spectrum to larger values.For more peripheral collisions where detector effects are dominant, there is the opposite effect,i.e. the spectrum is shifted to smaller values. The fraction of purely combinatorial jets in themomentum ranges used in the analysis was found to be negligible.To give a rough estimate of the true jet populations for a given reconstructed jet momentumrange, projections of the response matrices, introduced above, are used [67]. For measured p T , chjet -distributions, approximate ranges are given in Tab. 1 as a measure for the true jet mo-mentum distributions. The true populations are defined as the smallest possible ranges aroundthe p T , chjet -range in which at least 68% of the jet population can be found.7et radial profiles in Pb–Pb collisions ALICE Collaboration Table 1:
True jet populations p T , true in GeV/ c corresponding to given p T , chjet -ranges for different eventcentrality classes. The ranges are given such that they contain at least 68% of the jet population. Themost probable values of the distributions are given in brackets. p T , const -cut 0.15 GeV/ c cp T , chjet (GeV/ c ) 40–60 60–80 80–120 30–40 40–600–5% 11–87 (44) 22–111 (64) 49–144 (94) 7–59 (32) 21–88 (46)5–10% 11–86 (46) 24–112 (66) 52–146 (94) 8–61 (32) 22–89 (46)0–10% 11–86 (46) 25–113 (68) 54–147 (94) 10–63 (32) 24–91 (48)10–30% 13–86 (50) 33–117 (70) 63–149 (98) 15–69 (32) 30–94 (48)30–50% 25–91 (52) 47–118 (82) 75–147 (98) 23–73 (32) 36–95 (52) In this analysis, reconstructed detector-level PYTHIA-jets serve as vacuum baseline, becausethe size of the pp dataset at √ s = .
76 TeV is insufficient for this purpose.To account for the fluctuations of the underlying event in Pb–Pb collisions, PYTHIA jets em-bedded in real Pb–Pb collisions are used as a reference. Jets reconstructed in this referencedataset still show the same baseline jet properties but also include the effect of backgroundfluctuations from the Pb–Pb event. To create this reference dataset, the following procedure isapplied. Events are simulated with PYTHIA6 (Perugia-0 [68], version 6.421) followed by trans-port in the detector using GEANT3 and full response simulation and reconstruction simulatingthe same detector conditions as in the Pb–Pb dataset. The reconstructed tracks are embeddedinto Pb–Pb events, i.e. they are combined with tracks from Pb–Pb events. In order to simulatethe same conditions as in Pb–Pb, the tracking efficiency in pp is decreased to the level expectedin Pb–Pb. Since the tracking efficiency in pp is higher than in Pb–Pb, 2% of the PYTHIA tracksare randomly discarded before they are embedded [54]. Jet finding algorithms are applied to thePYTHIA event and also to the combined PYTHIA + Pb–Pb event. Jets found in the combinedevent are only accepted for the reference dataset if they can be matched geometrically withthose in the PYTHIA event. A matched embedded jet needs to be less than R = . p T PYTHIA jets.Two approaches have been tested which ensure that the jet sample shows Pb–Pb-event-like fluc-tuations of a PYTHIA jet, and not jets from the Pb–Pb event. The analysis baseline techniqueuses a cut on the fraction of the jet p T that originates from the matched jet in PYTHIA. Theapplied cut values are motivated by the underlying true jet distribution that shows two sepa-rated populations: jets mostly consisting of particles from PYTHIA or from Pb–Pb. The cutvalue was chosen to achieve the best separation of the two distributions. In the 0–10% mostcentral collisions, it is required that at least 20% of the jet constituents’ p T originate from thePYTHIA jet. For more peripheral collisions, this fraction is increased to 25%. For jets with p T , const ≥ c , which were measured down to 30 GeV/ c , a cut of 50% is applied. However,this procedure might impose a bias on the implicitly accepted background fluctuations. There-fore, variations around these nominal values were considered for the evaluation of systematic8et radial profiles in Pb–Pb collisions ALICE Collaborationuncertainties. Alternatively, a jet veto technique has been used: an embedded jet is not acceptedif it overlaps with an already existing jet of sizeable transverse momentum p T , chjet in the Pb–Pbevent. Several veto cut values between 15 and 40 GeV/ c were tested. Eventually, it turns outthat both approaches yield very similar results. The reconstructed jets which survive the MCpercentage cut serve as an input to the next analysis steps which are the same as in the dataanalysis. In this analysis, two features of particle jets are probed in Pb–Pb collisions: changes in theparticle p T composition of jets and their radial distribution relative to the jet axis.To probe relative changes in the charged particle p T composition of jets in a surrounding conewith R = .
3, the jet-associated yield ratio is measured. The ratio is formed from the integratedjet-associated per-trigger yields Y PbPb and Y emb which represent the integrals of the per-triggeryield in the jet cone for a given p T , assoc -range as introduced in Eq. 2. Technically, the integral isthe sum over the entries of all ( ∆η , ∆ϕ )-bins whose center is within distances of up to R = . R Y = Y PbPb / Y emb . It directly compares integratedjet-associated per-trigger yields in Pb–Pb to the same yields for embedded PYTHIA jets. Anenhancement or suppression in associated yields is directly seen as a deviation from unity in theratio.The relative radial particle distribution around the jet is directly derived from the jet-associatedyields. It shows the relative distribution of particle yields inside the jet cone. Thus, it is ameasure for the broadening or collimation of constituents with certain momenta in or around thejet cone. As for the jet-associated yield ratio, this measurement is performed for high- and low- p T jet-associated yields. The radial shape is normalized to represent a probability distribution. Itis defined in bins of r = p ∆η + ∆ϕ , the distance to the jet axis, to exploit the radial symmetryof the jet peak. In Refs. [48, 49], an asymmetric broadening of the near-side jet peak is observedin two-particle correlations. It is strongest for low associate and trigger momenta and vanishesfor higher momenta. Therefore, in the analysis presented here, the influence of this asymmetryon jet–hadron correlations was tested to check the radial symmetry of the jet peak. Even forthe lowest accessible jet and associated track momenta, no jet peak asymmetry was observed.Measurements in ∆η and ∆ϕ lead to the same conclusions within statistical precision, whichjustifies the presentation of the jet radial shape in bins of r . The correlation function which isused to obtain the shape is originally binned in η and ϕ . The binning was chosen fine enoughto avoid significant binning effects.For a given centrality-bin, and trigger and associate p T , it is defined by the following formula: S ( r min , r max ) = A Z r max r min Y corr ( r ) d r , (4)where Y corr ( r ) represents the background-corrected per-trigger yield, r min and r max the binedges, and A = R r range Y corr ( r ) d r the integral for the self-normalization of the radial shape. Theupper limit in the integral used for the self-normalization is chosen to reflect the differentranges of the shown radial shape and is r range = . p T , const ≥ .
15 GeV/ c Table 2:
Table of systematic uncertainties for jet-associated yields in Pb–Pb, embedded PYTHIA, andtheir ratio for high- p T associates (4–20 GeV/ c ) and low- p T associates (1–2 GeV/ c ) and for the 0–10%most central collisions. Uncertainties are given as relative uncertainties in percentages. p T , assoc (GeV/ c ) 4–20 1–2 p T , chjet (GeV/ c ) Observable 40–60 60–80 80–120 30–40 40–60Background (%) Pb–Pb 0.3–0.6 0.7–1.5 1.5–2.0 6.9 8.0Embedded 0.3–0.7 0.7–1.0 1.0–1.1 6.8 6.7Ratio 0.4–0.7 0.1–0.7 0.4–1.6 6.9 9.6Mixed event correction (%) Pb–Pb 0.2 0.3 0.5 0.2 0.2Embedded 0.7 0.4 0.4 0.1 < Table 3:
Table of systematic uncertainties for jet radial shapes for high- p T associates (4–20 GeV/ c ) inPb–Pb and embedded PYTHIA for the 0–10% most central collisions. Uncertainties are given as relativeuncertainties in percentages. Note that relative uncertainties grow for higher r values. Data sample Pb–Pb Embedded PYTHIA p T , chjet (GeV/ c ) 40–60 60–80 80–120 40–60 60–80 80–120Background (%) 0.1–6.5 0.1–13.0 0.1–19.2 0.0–6.9 0.0–10.8 0.0–14.5Mixed event corr. (%) < < < < < < r range = . p T , const ≥ c . The statistical uncertainty is calculated takinginto account the self-normalization. Several sources of systematic uncertainties contribute to the full uncertainty of the measurementand the evaluated individual uncertainties are combined using a quadratic sum, assuming theyare uncorrelated. Uncertainties for the following analysis aspects have been taken into account:10et radial profiles in Pb–Pb collisions ALICE Collaboration
Table 4:
Table of systematic uncertainties for jet radial shapes for low- p T associates (1–2 GeV/ c , 2–3 GeV/ c ) in Pb–Pb and embedded PYTHIA for jets with p T , chjet = c and for the 0–10%most central collisions. Uncertainties are given as relative uncertainties in percentages. Note that relativeuncertainties grow for higher r values. Data sample Pb–Pb Embedded PYTHIA p T , assoc (GeV/ c ) 1–2 2–3 1–2 2–3Background (%) 1.6–7.5 0.4–8.8 2.2–11.9 1.0–4.2Mixed event corr. (%) < < < < ∆ϕ , as described in Sec. 3. Different underlyingbackground methods for the correlation functions have been tested: for systematic uncertainties,the definition of the sideband range was varied to 1 . < | ∆η | < . . < | ∆η | < . B ( ∆ϕ = const ) ) has been used.The mixed-event acceptance/inhomogenity correction is a small correction. Two variations areconsidered for systematic uncertainties. First, the mixed-event correction is calculated inclu-sively for all ∆ϕ . Second, the normalization of the mixed-event correlations is performed for | ∆η | < . | ∆ϕ | instead of using the plateau in | ∆η | < . | ∆ϕ | < . p T originating from the PYTHIA event, as described in Sec. 5. Instead ofcutting at 20% for 0–10% centrality, and 25% for other centralities, the cut is varied to 15% and25% for 0–10% centrality, and to 20% and 30% for other centralities. As described above, forjets with p T , const ≥ c a baseline cut value of 50% is used. For systematic variation, thecut is performed at 15% and 60% for 0–10% centrality, 20% and 60% for other centralities.The detector has a finite single track reconstruction efficiency, which is only known with finiteprecision. Since all observables are corrected for the tracking efficiency, they are all directlyaffected by its uncertainty. Detailed studies of the tracking efficiency uncertainty have beenperformed to evaluate the size of its systematic uncertainty [54, 66]. The studies indicate thatthe (absolute) uncertainty is 4% for Pb–Pb collisions, mainly due to an imperfect description ofthe ITS-TPC matching efficiency. Another uncertainty from the tracking efficiency correctionenters this analysis due to the usage of PYTHIA simulations. The tracking efficiency of thePYTHIA data is artificially lowered by 2% before embedding to account for the lower trackingefficiency in Pb–Pb collisions. As a conservative estimate, a relative uncertainty of 100% isassigned to this value. Both components of the tracking efficiency uncertainty are taken intoaccount as independent contributions to the uncertainty, i.e. added in quadrature to the fulluncertainty. These uncertainties are directly used as uncertainties for the yields, see Tab. 2.For the jet-associated yield ratio, the uncertainty on the tracking efficiency in Pb–Pb cancels,11et radial profiles in Pb–Pb collisions ALICE Collaborationbecause it is correlated in Pb–Pb and the embedded PYTHIA reference. For the radial shapedistribution, a change in the tracking efficiency has no impact either, since these observables arerelative quantities that do not depend on the global magnitude of the tracking efficiency. As analternative approach to estimate the impact of these two uncertainties of the tracking efficiencieson the observables, the full analysis was redone using corrections that assume the above givenlower tracking efficiencies. There was no significant impact on the presented results.Finally, an uncertainty is assigned since PYTHIA is used as a baseline instead of a measuredpp reference. Including this uncertainty, the conclusions are also valid for a pp reference andnot only for an embedded PYTHIA reference. In order to do so, the presented observables werecalculated and compared for PYTHIA events and pp collisions at 7 TeV. Within the statisticalprecision of this comparison, it is only possible to give an estimate for the inclusive p T , chjet -range. The relative deviations of each observable between both datasets enter directly as asystematic uncertainty and are on the level of a few percent, cf. Tabs. 2–4. Centrality (%) 0 - 5 5 - 10 10 - 30 30 - 50 e m b Y , P b P b Y = 0.3 R jets T k Charged anti-Embedded PYTHIA6, 2.76 TeVALICE Pb-Pb 2.76 TeV c = 4-20 GeV/ T, assoc p c > 0.15 GeV/
T, const p ) c (GeV/ T, ch jet p Pb-Pb:40-6060-8080-120 Embedded:40-6060-8080-120
Centrality (%) 0 - 5 5 - 10 10 - 30 30 - 50 e m b Y / P b P b Y = 0.3 R jets T k Charged anti-Embedded PYTHIA6, 2.76 TeVALICE Pb-Pb 2.76 TeV c = 4-20 GeV/ T, assoc p c > 0.15 GeV/
T, const p ) c (GeV/ T, ch jet p Fig. 2:
Centrality dependence of jet-associated yields (left) and yield ratios (right) for high- p T associates.Boxes represent systematic uncertainties, error bars represent statistical uncertainties. Observables arecorrected for acceptance and background effects. Figures 2 and 3 depict the jet-associated yields (left) and yield ratios (right) for high- p T and low- p T associated particles, respectively. Both quantities are shown as a function of event centralityand for several selected jet transverse momenta.The jet-associated yield ratio shows a suppression with a significance of several standard de-viations in the centrality range 0–50% for the considered high- p T associated particles. In theprobed jet momentum range, no significant p T , chjet -dependence is observed. The centrality-dependent linear slope of the distribution for p T , chjet = c is more than one standarddeviation away from zero, taking into account statistical and systematic uncertainties added inquadrature, indicating that there is a slightly stronger suppression for more central collisions inthis case. As a cross check, the same observable was also measured for jets with several higherminimum p T , const -cuts, i.e. 1, 2, and 3 GeV/ c , which are less affected by the underlying event.They lead to similar conclusions.The jet-associated yield ratio for low- p T associates has much larger statistical and systematic12et radial profiles in Pb–Pb collisions ALICE Collaboration Centrality (%) 0 - 5 5 - 10 10 - 30 30 - 50 e m b Y , P b P b Y = 0.3 R jets T k Charged anti-Embedded PYTHIA6, 2.76 TeVALICE Pb-Pb 2.76 TeV c = 1-2 GeV/ T, assoc p c > 3 GeV/
T, const p ) c (GeV/ T, ch jet p Pb-Pb:30-4040-60 Embedded:30-4040-60
Centrality (%) 0 - 5 5 - 10 10 - 30 30 - 50 e m b Y / P b P b Y = 0.3 R jets T k Charged anti-Embedded PYTHIA6, 2.76 TeVALICE Pb-Pb 2.76 TeV c = 1-2 GeV/ T, assoc p c > 3 GeV/
T, const p ) c (GeV/ T, ch jet p Fig. 3:
Centrality dependence of jet-associated yields (left) and yield ratios (right) for low- p T associates.Boxes represent systematic uncertainties, error bars represent statistical uncertainties. Observables arecorrected for acceptance and background effects. uncertainties than the ratio of high- p T constituents, thus it is not possible to draw a definiteconclusion.The measured jet relative radial shapes are presented in Figs. 4 and 5. The top panels show theself-normalized distributions, the difference and the ratio of the shapes in Pb–Pb and embeddedPYTHIA can be found in the two lower panels. The jet radial shapes of high- p T associatesare measured for p T , chjet = c , 60–80 GeV/ c , and 80–120 GeV/ c . Shapes of low- p T associates are presented for jets with p T , chjet = c and p T , const > c forassociates with p T , assoc = c and p T , assoc = c .In general, the radial shape measurements indicate that all jet-associated yields are similarlydistributed relative to the jet axis in Pb–Pb and embedded PYTHIA. The yields of high- p T associates appear to be slightly more collimated near the core for jets in Pb–Pb, though theabsolute effect is small. While the shape is not significantly changed for jet transverse momentabetween 40 and 60 GeV/ c in Pb–Pb compared to the reference, there is a visible collimationfor higher jet momenta above 60 GeV/ c . This can be seen best in the difference distributions ∆ PbPb − emb of Fig. 4 which show that a larger fraction of the associated yield can be found nearthe core in Pb–Pb collisions.The ratio distributions show that the collimation effect persists up to r = .
2, which is bestvisible for jets with p T , chjet = c . In the CMS measurement [50], no significantchange of the near-side jet peak width is observed in Pb–Pb for high- p T associates and jetsabove 120 GeV/ c . However, the magnitude of the effect observed here is compatible withthe observations within uncertainties. Also note that the CMS data hints as well to a smallcollimation of the peak for higher- p T associates (4–8 GeV/ c ). Possible effects which mightlead to a collimation include a relative change in the quark/gluon content in Pb–Pb comparedto the reference [69], as well as a suppression of large-angle soft radiation in the coherent jetenergy loss picture [70, 71]. Low- p T jet-associated yields presented in Fig. 5 are measured upto a distance of r = . p T , assoc = c , a hint of a broadening of the radial shape is observed for jets with13et radial profiles in Pb–Pb collisions ALICE Collaboration R e l a t i v e r ad i a l d i s t r i bu t i on Pb-PbEmbeddedEmbedded PYTHIA6 2.76 TeVALICE 0-10% Pb-Pb 2.76 TeV trigger jet c c = 4-20 GeV/ T, assoc p c > 0.15 GeV/
T, const p = 0.3 R jets T k Charged anti- P b P b - e m b ∆ − r R a t i o R e l a t i v e r ad i a l d i s t r i bu t i on Pb-PbEmbeddedEmbedded PYTHIA6 2.76 TeVALICE 0-10% Pb-Pb 2.76 TeV trigger jet c c = 4-20 GeV/ T, assoc p c > 0.15 GeV/
T, const p = 0.3 R jets T k Charged anti- P b P b - e m b ∆ − r R a t i o R e l a t i v e r ad i a l d i s t r i bu t i on Pb-PbEmbeddedEmbedded PYTHIA6 2.76 TeVALICE 0-10% Pb-Pb 2.76 TeV trigger jet c c = 4-20 GeV/ T, assoc p c > 0.15 GeV/
T, const p = 0.3 R jets T k Charged anti- P b P b - e m b ∆ − r R a t i o Fig. 4:
Jet relative radial shape distributions, differences, and ratios for the 0–10% most central colli-sions for high- p T constituents, shown for different jet transverse momenta. Boxes represent systematicuncertainties, shaded boxes include uncertainties from PYTHIA/pp comparison, and error bars representstatistical uncertainties. Observables are corrected for acceptance and background effects. momenta between 30 and 40 GeV/ c for the given definition. The broadening is visible in thedifference distribution of the left plot in Fig. 5: in Pb–Pb collisions, a smaller fraction of par-ticles can be found directly next to the jet axis. For higher associate transverse momenta, i.e. p T , assoc = c , there is no significant modification of the low- p T radial shape of jets inPb–Pb collisions within the large current experimental uncertainties. A robust measurement ofthis observable for p T , chjet = c or higher momenta is not possible due to the insuffi-cient size of the dataset. For higher jet momenta above 120 GeV/ c , CMS measures a significantbroadening of the near-side jet peak. 14et radial profiles in Pb–Pb collisions ALICE Collaboration R e l a t i v e r ad i a l d i s t r i bu t i on Pb-PbEmbeddedEmbedded PYTHIA6 2.76 TeVALICE 0-10% Pb-Pb 2.76 TeV trigger jet c c = 1-2 GeV/ T, assoc p c > 3.0 GeV/
T, const p = 0.3 R jets T k Charged anti- P b P b - e m b ∆ − r R a t i o R e l a t i v e r ad i a l d i s t r i bu t i on Pb-PbEmbeddedEmbedded PYTHIA6 2.76 TeVALICE 0-10% Pb-Pb 2.76 TeV trigger jet c c = 2-3 GeV/ T, assoc p c > 3.0 GeV/
T, const p = 0.3 R jets T k Charged anti- P b P b - e m b ∆ − r R a t i o Fig. 5:
Jet relative radial shape distributions, differences, and ratios for the 0–10% most central collisionsfor two different low- p T constituent ranges. Boxes represent systematic uncertainties, shaded boxesinclude uncertainties from PYTHIA/pp comparison, and error bars represent statistical uncertainties.Observables are corrected for acceptance and background effects. The y -axis scale of the ratio is chosento focus on r < .
3, where the deviation of the ratio from unity is significant.
The presented results constitute the first attempt to study jet–hadron correlations with track-based jets down to transverse momenta of 30 GeV/ c in Pb–Pb collisions — a challenging regimedue to the large underlying event and its fluctuations. The jet radial shapes and the change inthe particle p T composition were measured in Pb–Pb collisions at √ s NN = .
76 TeV for high-and low- p T associates and compared to embedded PYTHIA simulations. The number of high- p T associates in Pb–Pb collisions is suppressed compared to the reference by roughly 30 to10%, depending on centrality. The radial particle distribution relative to the jet axis shows amoderate modification in Pb–Pb collisions with respect to PYTHIA. High- p T associate parti-cles are slightly more collimated in Pb–Pb collisions compared to the reference. For jets with p T , const ≥ c , the radial distributions of low- p T associates were measured. A hint of abroadening of the low- p T radial shapes is observed for p T , assoc = c . The shape for p T , assoc = c does not show a significant modification within its large uncertainties.The results are in line with both previous jet–hadron-related measurements from the CMS Col-laboration and jet shape measurements from the ALICE Collaboration at higher p T and addfurther support for the established picture of in-medium parton energy loss. Acknowledgements
The ALICE Collaboration would like to thank all its engineers and technicians for theirinvaluable contributions to the construction of the experiment and the CERN accelerator teamsfor the outstanding performance of the LHC complex. The ALICE Collaboration gratefullyacknowledges the resources and support provided by all Grid centres and the Worldwide LHCComputing Grid (WLCG) collaboration. The ALICE Collaboration acknowledges the15et radial profiles in Pb–Pb collisions ALICE Collaborationfollowing funding agencies for their support in building and running the ALICE detector: A. I.Alikhanyan National Science Laboratory (Yerevan Physics Institute) Foundation (ANSL),State Committee of Science and World Federation of Scientists (WFS), Armenia; AustrianAcademy of Sciences, Austrian Science Fund (FWF): [M 2467-N36] and Nationalstiftung fürForschung, Technologie und Entwicklung, Austria; Ministry of Communications and HighTechnologies, National Nuclear Research Center, Azerbaijan; Conselho Nacional deDesenvolvimento Científico e Tecnológico (CNPq), Universidade Federal do Rio Grande doSul (UFRGS), Financiadora de Estudos e Projetos (Finep) and Fundação de Amparo àPesquisa do Estado de São Paulo (FAPESP), Brazil; Ministry of Science & Technology ofChina (MSTC), National Natural Science Foundation of China (NSFC) and Ministry ofEducation of China (MOEC) , China; Croatian Science Foundation and Ministry of Scienceand Education, Croatia; Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear(CEADEN), Cubaenergía, Cuba; Ministry of Education, Youth and Sports of the CzechRepublic, Czech Republic; The Danish Council for Independent Research | Natural Sciences,the Carlsberg Foundation and Danish National Research Foundation (DNRF), Denmark;Helsinki Institute of Physics (HIP), Finland; Commissariat à l’Energie Atomique (CEA),Institut National de Physique Nucléaire et de Physique des Particules (IN2P3) and CentreNational de la Recherche Scientifique (CNRS) and Rlégion des Pays de la Loire, France;Bundesministerium für Bildung, Wissenschaft, Forschung und Technologie (BMBF) and GSIHelmholtzzentrum für Schwerionenforschung GmbH, Germany; General Secretariat forResearch and Technology, Ministry of Education, Research and Religions, Greece; NationalResearch, Development and Innovation Office, Hungary; Department of Atomic EnergyGovernment of India (DAE), Department of Science and Technology, Government of India(DST), University Grants Commission, Government of India (UGC) and Council of Scientificand Industrial Research (CSIR), India; Indonesian Institute of Science, Indonesia; CentroFermi - Museo Storico della Fisica e Centro Studi e Ricerche Enrico Fermi and IstitutoNazionale di Fisica Nucleare (INFN), Italy; Institute for Innovative Science and Technology ,Nagasaki Institute of Applied Science (IIST), Japan Society for the Promotion of Science(JSPS) KAKENHI and Japanese Ministry of Education, Culture, Sports, Science andTechnology (MEXT), Japan; Consejo Nacional de Ciencia (CONACYT) y Tecnología,through Fondo de Cooperación Internacional en Ciencia y Tecnología (FONCICYT) andDirección General de Asuntos del Personal Academico (DGAPA), Mexico; NederlandseOrganisatie voor Wetenschappelijk Onderzoek (NWO), Netherlands; The Research Council ofNorway, Norway; Commission on Science and Technology for Sustainable Development inthe South (COMSATS), Pakistan; Pontificia Universidad Católica del Perú, Peru; Ministry ofScience and Higher Education and National Science Centre, Poland; Korea Institute of Scienceand Technology Information and National Research Foundation of Korea (NRF), Republic ofKorea; Ministry of Education and Scientific Research, Institute of Atomic Physics andMinistry of Research and Innovation and Institute of Atomic Physics, Romania; Joint Institutefor Nuclear Research (JINR), Ministry of Education and Science of the Russian Federation,National Research Centre Kurchatov Institute, Russian Science Foundation and RussianFoundation for Basic Research, Russia; Ministry of Education, Science, Research and Sport ofthe Slovak Republic, Slovakia; National Research Foundation of South Africa, South Africa;Swedish Research Council (VR) and Knut & Alice Wallenberg Foundation (KAW), Sweden;European Organization for Nuclear Research, Switzerland; National Science and TechnologyDevelopment Agency (NSDTA), Suranaree University of Technology (SUT) and Office of theHigher Education Commission under NRU project of Thailand, Thailand; Turkish Atomic16et radial profiles in Pb–Pb collisions ALICE CollaborationEnergy Agency (TAEK), Turkey; National Academy of Sciences of Ukraine, Ukraine; Scienceand Technology Facilities Council (STFC), United Kingdom; National Science Foundation ofthe United States of America (NSF) and United States Department of Energy, Office ofNuclear Physics (DOE NP), United States of America.
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S. Acharya , D. Adamová , S.P. Adhya , A. Adler , J. Adolfsson , M.M. Aggarwal ,G. Aglieri Rinella , M. Agnello , N. Agrawal , Z. Ahammed , S. Ahmad , S.U. Ahn ,S. Aiola , A. Akindinov , M. Al-Turany , S.N. Alam , D.S.D. Albuquerque ,D. Aleksandrov , B. Alessandro , H.M. Alfanda , R. Alfaro Molina , B. Ali , Y. Ali ,A. Alici
10 ,53 ,27 , A. Alkin , J. Alme , T. Alt , L. Altenkamper , I. Altsybeev , M.N. Anaam ,C. Andrei , D. Andreou , H.A. Andrews , A. Andronic , M. Angeletti , V. Anguelov ,C. Anson , T. Antiˇci´c , F. Antinori , P. Antonioli , R. Anwar , 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 , S. Bagnasco , X. Bai , R. Bailhache , R. Bala , A. Baldisseri , M. Ball ,R.C. Baral , R. Barbera , L. Barioglio , G.G. Barnaföldi , L.S. Barnby , V. Barret ,P. Bartalini , K. Barth , E. Bartsch , F. Baruffaldi , N. Bastid , S. Basu , G. Batigne ,B. Batyunya , P.C. Batzing , D. Bauri , J.L. Bazo Alba , I.G. Bearden , C. Bedda ,N.K. Behera , I. Belikov , F. Bellini , R. Bellwied , V. Belyaev , G. Bencedi , S. Beole ,A. Bercuci , Y. Berdnikov , D. Berenyi , R.A. Bertens , D. Berzano , M.G. Besoiu ,L. Betev , A. Bhasin , I.R. Bhat , H. Bhatt , B. Bhattacharjee , A. Bianchi , L. Bianchi
126 ,26 ,N. Bianchi , J. Bielˇcík , J. Bielˇcíková , A. Bilandzic
117 ,103 , G. Biro , R. Biswas , S. Biswas ,J.T. Blair , D. Blau , C. Blume , G. Boca , F. Bock
94 ,34 , A. Bogdanov , L. Boldizsár ,A. Bolozdynya , M. Bombara , G. Bonomi , H. Borel , A. Borissov
144 ,91 , M. Borri ,H. Bossi , E. Botta , C. Bourjau , L. Bratrud , P. Braun-Munzinger , M. Bregant ,T.A. Broker , M. Broz , E.J. Brucken , E. Bruna , G.E. Bruno
33 ,104 , M.D. Buckland ,D. Budnikov , H. Buesching , S. Bufalino , O. Bugnon , P. Buhler , P. Buncic ,Z. Buthelezi , J.B. Butt , J.T. Buxton , D. Caffarri , A. Caliva , E. Calvo Villar ,R.S. Camacho , P. Camerini , A.A. Capon , F. Carnesecchi , J. Castillo Castellanos ,A.J. Castro , E.A.R. Casula , F. Catalano , C. Ceballos Sanchez , P. Chakraborty ,S. Chandra , B. Chang , W. Chang , S. Chapeland , M. Chartier , S. Chattopadhyay ,S. Chattopadhyay , A. Chauvin , C. Cheshkov , B. Cheynis , V. Chibante Barroso ,D.D. Chinellato , S. Cho , P. Chochula , T. Chowdhury , P. Christakoglou ,C.H. Christensen , P. Christiansen , T. Chujo , C. Cicalo , L. Cifarelli
10 ,27 , F. Cindolo ,J. Cleymans , F. Colamaria , D. Colella , A. Collu , M. Colocci , M. Concas
58 ,ii , G. ConesaBalbastre , Z. Conesa del Valle , G. Contin
59 ,128 , J.G. Contreras , T.M. Cormier , Y. CorralesMorales
58 ,26 , P. Cortese , M.R. Cosentino , F. Costa , S. Costanza , J. Crkovská ,P. Crochet , E. Cuautle , L. Cunqueiro , D. Dabrowski , T. Dahms
103 ,117 , A. Dainese ,F.P.A. Damas
137 ,114 , S. Dani , M.C. Danisch , A. Danu , D. Das , I. Das , S. Das ,A. Dash , S. Dash , A. Dashi , S. De
85 ,49 , A. De Caro , G. de Cataldo , C. de Conti , J. deCuveland , A. De Falco , D. De Gruttola , N. De Marco , S. De Pasquale , R.D. De Souza ,S. Deb , H.F. Degenhardt , K.R. Deja , A. Deloff , S. Delsanto
131 ,26 , P. Dhankher , D. DiBari , A. Di Mauro , R.A. Diaz , T. Dietel , P. Dillenseger , Y. Ding , R. Divià ,Ø. Djuvsland , U. Dmitrieva , A. Dobrin
34 ,68 , B. Dönigus , O. Dordic , A.K. Dubey ,A. Dubla , S. Dudi , M. Dukhishyam , P. Dupieux , R.J. Ehlers , D. Elia , H. Engel ,E. Epple , B. Erazmus , F. Erhardt , A. Erokhin , M.R. Ersdal , B. Espagnon , G. Eulisse ,J. Eum , D. Evans , S. Evdokimov , L. Fabbietti
117 ,103 , M. Faggin , J. Faivre , A. Fantoni ,M. Fasel , P. Fecchio , L. Feldkamp , 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 , S. Foertsch , P. Foka , S. Fokin ,E. Fragiacomo , U. Frankenfeld , G.G. Fronze , U. Fuchs , C. Furget , A. Furs , M. FuscoGirard , J.J. Gaardhøje , M. Gagliardi , A.M. Gago , A. Gal , C.D. Galvan , P. Ganoti ,C. Garabatos , E. Garcia-Solis , K. Garg , C. Gargiulo , K. Garner , P. Gasik
103 ,117 , E.F. Gauger , M.B. Gay Ducati , M. Germain , J. Ghosh , P. Ghosh , S.K. Ghosh ,P. Gianotti , P. Giubellino
105 ,58 , P. Giubilato , P. Glässel , D.M. Goméz Coral , A. GomezRamirez , V. Gonzalez , P. González-Zamora , S. Gorbunov , L. Görlich , S. Gotovac ,V. Grabski , L.K. Graczykowski , K.L. Graham , L. Greiner , A. Grelli , C. Grigoras ,V. Grigoriev , A. Grigoryan , S. Grigoryan , O.S. Groettvik , J.M. Gronefeld , F. Grosa ,J.F. Grosse-Oetringhaus , R. Grosso , R. Guernane , B. Guerzoni , M. Guittiere ,K. Gulbrandsen , T. Gunji , A. Gupta , R. Gupta , I.B. Guzman , R. Haake
34 ,146 ,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
10 ,53 , P. Hauer , S. Hayashi , S.T. Heckel , E. Hellbär , H. Helstrup ,A. Herghelegiu , E.G. Hernandez , G. Herrera Corral , F. Herrmann , K.F. Hetland ,T.E. Hilden , H. Hillemanns , C. Hills , B. Hippolyte , B. Hohlweger , D. Horak ,S. Hornung , R. Hosokawa , P. Hristov , C. Huang , C. Hughes , P. Huhn , T.J. Humanic ,H. Hushnud , L.A. Husova , N. Hussain , S.A. Hussain , T. Hussain , D. Hutter ,D.S. Hwang , J.P. Iddon
128 ,34 , R. Ilkaev , M. Inaba , M. Ippolitov , M.S. Islam ,M. Ivanov , V. Ivanov , V. Izucheev , B. Jacak , N. Jacazio , P.M. Jacobs , M.B. Jadhav ,S. Jadlovska , J. Jadlovsky , S. Jaelani , C. Jahnke , M.J. Jakubowska , M.A. Janik ,M. Jercic , O. Jevons , R.T. Jimenez Bustamante , M. Jin , F. Jonas
144 ,94 , P.G. Jones ,A. Jusko , P. Kalinak , A. Kalweit , J.H. Kang , V. Kaplin , S. Kar , A. Karasu Uysal ,O. Karavichev , T. Karavicheva , P. Karczmarczyk , E. Karpechev , U. Kebschull , R. Keidel ,M. Keil , B. Ketzer , Z. Khabanova , A.M. Khan , S. Khan , S.A. Khan , A. Khanzadeev ,Y. Kharlov , A. Khatun , A. Khuntia
118 ,49 , B. Kileng , B. Kim , 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 , T. Kim , S. Kirsch , I. Kisel , S. Kiselev , A. Kisiel ,J.L. Klay , C. Klein , J. Klein , S. Klein , C. Klein-Bösing , S. Klewin , A. Kluge ,M.L. Knichel , A.G. Knospe , C. Kobdaj , M.K. Köhler , T. Kollegger , A. Kondratyev ,N. Kondratyeva , E. Kondratyuk , P.J. Konopka , L. Koska , O. Kovalenko , V. Kovalenko ,M. Kowalski , I. Králik , A. Kravˇcáková , L. Kreis , M. Krivda
109 ,65 , F. Krizek ,K. Krizkova Gajdosova , M. Krüger , E. Kryshen , M. Krzewicki , A.M. Kubera , V. Kuˇcera ,C. Kuhn , P.G. Kuijer , L. Kumar , S. Kumar , S. Kundu , P. Kurashvili , A. Kurepin ,A.B. Kurepin , S. Kushpil , J. Kvapil , M.J. Kweon , J.Y. Kwon , Y. Kwon , S.L. LaPointe , P. La Rocca , Y.S. Lai , R. Langoy , K. Lapidus
34 ,146 , A. Lardeux , P. Larionov ,E. Laudi , R. Lavicka , T. Lazareva , R. Lea , L. Leardini , S. Lee , F. Lehas ,S. Lehner , 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. Lindal , V. Lindenstruth ,S.W. Lindsay , C. Lippmann , M.A. Lisa , V. Litichevskyi , A. Liu , S. Liu , W.J. Llope ,I.M. Lofnes , V. Loginov , C. Loizides , P. Loncar , X. Lopez , E. López Torres , P. Luettig ,J.R. Luhder , M. Lunardon , G. Luparello , M. Lupi , A. Maevskaya , M. Mager ,S.M. Mahmood , T. Mahmoud , A. Maire , R.D. Majka , M. Malaev , Q.W. Malik ,L. Malinina
75 ,iii , D. Mal’Kevich , P. Malzacher , A. Mamonov , V. Manko , F. Manso ,V. Manzari , Y. Mao , M. Marchisone , J. Mareš , G.V. Margagliotti , A. Margotti ,J. Margutti , A. Marín , C. Markert , M. Marquard , N.A. Martin , P. Martinengo ,J.L. Martinez , M.I. Martínez , G. Martínez García , M. Martinez Pedreira , S. Masciocchi ,M. Masera , A. Masoni , L. Massacrier , E. Masson , A. Mastroserio
52 ,138 ,A.M. Mathis
103 ,117 , P.F.T. Matuoka , A. Matyja , C. Mayer , M. Mazzilli , M.A. Mazzoni ,A.F. Mechler , F. Meddi , Y. Melikyan , A. Menchaca-Rocha , E. Meninno , M. Meres ,S. Mhlanga , Y. Miake , L. Micheletti , M.M. Mieskolainen , D.L. Mihaylov ,K. Mikhaylov
64 ,75 , A. Mischke
63 ,i , A.N. Mishra , D. Mi´skowiec , C.M. Mitu ,N. Mohammadi , A.P. Mohanty , B. Mohanty , M. Mohisin Khan
17 ,iv , M. Mondal ,M.M. Mondal , C. Mordasini , D.A. Moreira De Godoy , L.A.P. Moreno , S. Moretto , A. Morreale , A. Morsch , T. Mrnjavac , V. Muccifora , E. Mudnic , D. Mühlheim ,S. Muhuri , J.D. Mulligan
79 ,146 , M.G. Munhoz , K. Münning , 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
10 ,53 , E. Nappi , M.U. Naru , A.F. Nassirpour , H. Natal daLuz , C. Nattrass , R. Nayak , T.K. Nayak
85 ,141 , S. Nazarenko , R.A. Negrao De Oliveira ,L. Nellen , S.V. Nesbo , G. Neskovic , B.S. Nielsen , S. Nikolaev , S. Nikulin , V. Nikulin ,F. Noferini
10 ,53 , P. Nomokonov , G. Nooren , J. Norman , P. Nowakowski , A. Nyanin ,J. Nystrand , M. Ogino , A. Ohlson , J. Oleniacz , A.C. Oliveira Da Silva , M.H. Oliver ,C. Oppedisano , R. Orava , A. Ortiz Velasquez , A. Oskarsson , J. Otwinowski , K. Oyama ,Y. Pachmayer , V. Pacik , D. Pagano , G. Pai´c , P. Palni , J. Pan , A.K. Pandey ,S. Panebianco , V. Papikyan , P. Pareek , J. Park , J.E. Parkkila , S. Parmar , A. Passfeld ,S.P. Pathak , R.N. Patra , B. Paul
24 ,58 , H. Pei , T. Peitzmann , X. Peng , L.G. Pereira ,H. Pereira Da Costa , D. Peresunko , G.M. Perez , E. Perez Lezama , V. Peskov , Y. Pestov ,V. Petráˇcek , M. Petrovici , R.P. Pezzi , S. Piano , M. Pikna , P. Pillot , L.O.D.L. Pimentel ,O. Pinazza
53 ,34 , L. Pinsky , S. Pisano , D.B. Piyarathna , M. Płosko´n , M. Planinic ,F. Pliquett , J. Pluta , S. Pochybova , M.G. Poghosyan , B. Polichtchouk , N. Poljak ,W. Poonsawat , A. Pop , H. Poppenborg , S. Porteboeuf-Houssais , V. Pozdniakov ,S.K. Prasad , R. Preghenella , F. Prino , C.A. Pruneau , I. Pshenichnov , M. Puccio
34 ,26 ,V. Punin , K. Puranapanda , J. Putschke , R.E. Quishpe , S. Ragoni , S. Raha ,S. Rajput , J. Rak , A. Rakotozafindrabe , L. Ramello , F. Rami , R. Raniwala ,S. Raniwala , S.S. Räsänen , B.T. Rascanu , R. Rath , V. Ratza , I. Ravasenga ,K.F. Read
130 ,94 , K. Redlich
84 ,v , A. Rehman , P. Reichelt , F. Reidt , X. Ren , R. Renfordt ,A. Reshetin , J.-P. Revol , K. Reygers , V. Riabov , T. Richert
80 ,88 , M. Richter , P. Riedler ,W. Riegler , F. Riggi , C. Ristea , S.P. Rode , M. Rodríguez Cahuantzi , K. Røed ,R. Rogalev , E. Rogochaya , D. Rohr , D. Röhrich , P.S. Rokita , F. Ronchetti ,E.D. Rosas , K. Roslon , P. Rosnet , A. Rossi , A. Rotondi , F. Roukoutakis , A. Roy ,P. Roy , O.V. Rueda , R. Rui , B. Rumyantsev , A. Rustamov , E. Ryabinkin , Y. Ryabov ,A. Rybicki , H. Rytkonen , S. Saarinen , S. Sadhu , S. Sadovsky , K. Šafaˇrík
37 ,34 ,S.K. Saha , B. Sahoo , P. Sahoo , R. Sahoo , S. Sahoo , P.K. Sahu , J. Saini , S. Sakai ,S. Sambyal , V. Samsonov
96 ,91 , A. Sandoval , A. Sarkar , D. Sarkar
141 ,143 , N. Sarkar ,P. Sarma , V.M. Sarti , M.H.P. Sas , E. Scapparone , B. Schaefer , J. Schambach ,H.S. Scheid , C. Schiaua , R. Schicker , A. Schmah , C. Schmidt , H.R. Schmidt ,M.O. Schmidt , M. Schmidt , N.V. Schmidt
94 ,69 , A.R. Schmier , J. Schukraft
34 ,88 ,Y. Schutz
34 ,136 , K. Schwarz , K. Schweda , G. Scioli , E. Scomparin , M. Šefˇcík ,J.E. Seger , Y. Sekiguchi , D. Sekihata , I. Selyuzhenkov
105 ,91 , S. Senyukov ,D. Serebryakov , E. Serradilla , P. Sett , A. Sevcenco , A. Shabanov , A. Shabetai ,R. Shahoyan , W. Shaikh , A. Shangaraev , A. Sharma , A. Sharma , M. Sharma ,N. Sharma , A.I. Sheikh , K. Shigaki , M. Shimomura , S. Shirinkin , Q. Shou ,Y. Sibiriak , S. Siddhanta , T. Siemiarczuk , D. Silvermyr , G. Simatovic , G. Simonetti
103 ,34 ,R. Singh , R. Singh , V.K. Singh , V. Singhal , T. Sinha , B. Sitar , M. Sitta ,T.B. Skaali , M. Slupecki , N. Smirnov , R.J.M. Snellings , T.W. Snellman , J. Sochan ,C. Soncco , J. Song
60 ,126 , A. Songmoolnak , F. Soramel , S. Sorensen , I. Sputowska ,J. Stachel , I. Stan , P. Stankus , P.J. Steffanic , E. Stenlund , D. Stocco ,M.M. Storetvedt , P. Strmen , A.A.P. Suaide , T. Sugitate , C. Suire , M. Suleymanov ,M. Suljic , R. Sultanov , M. Šumbera , S. Sumowidagdo , K. Suzuki , S. Swain ,A. Szabo , I. Szarka , U. Tabassam , G. Taillepied , J. Takahashi , G.J. Tambave ,S. Tang
134 ,6 , M. Tarhini , M.G. Tarzila , A. Tauro , G. Tejeda Muñoz , A. Telesca ,C. Terrevoli
126 ,29 , D. Thakur , S. Thakur , D. Thomas , F. Thoresen , R. Tieulent ,A. Tikhonov , A.R. Timmins , A. Toia , N. Topilskaya , M. Toppi , F. Torales-Acosta ,S.R. Torres , S. Tripathy , T. Tripathy , S. Trogolo
26 ,29 , G. Trombetta , L. Tropp , V. Trubnikov , W.H. Trzaska , T.P. Trzcinski , B.A. Trzeciak , T. Tsuji , A. Tumkin ,R. Turrisi , T.S. Tveter , K. Ullaland , E.N. Umaka , A. Uras , G.L. Usai , A. Utrobicic ,M. Vala
116 ,38 , N. Valle , S. Vallero , N. van der Kolk , L.V.R. van Doremalen , M. vanLeeuwen , P. Vande Vyvre , D. Varga , M. Varga-Kofarago , A. Vargas , M. Vargyas ,R. Varma , M. Vasileiou , A. Vasiliev , O. Vázquez Doce
117 ,103 , V. Vechernin , A.M. Veen ,E. Vercellin , S. Vergara Limón , L. Vermunt , R. Vernet , R. Vértesi , L. Vickovic ,J. Viinikainen , Z. Vilakazi , O. Villalobos Baillie , A. Villatoro Tello , 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
103 ,117 , D. Voscek ,J. Vrláková , B. Wagner , Y. Watanabe , M. Weber , S.G. Weber , A. Wegrzynek ,D.F. Weiser , S.C. Wenzel , J.P. Wessels , E. Widmann , J. Wiechula , J. Wikne ,G. Wilk , J. Wilkinson , G.A. Willems , E. Willsher , B. Windelband , W.E. Witt ,Y. Wu , R. Xu , S. Yalcin , K. Yamakawa , S. Yang , S. Yano , Z. Yin , H. Yokoyama ,I.-K. Yoo , J.H. Yoon , S. Yuan , A. Yuncu , V. Yurchenko , V. Zaccolo
58 ,25 , A. Zaman ,C. Zampolli , H.J.C. Zanoli , N. Zardoshti , A. Zarochentsev , P. Závada , N. Zaviyalov ,H. Zbroszczyk , M. Zhalov , X. Zhang , Z. Zhang , C. Zhao , V. Zherebchevskii ,N. Zhigareva , D. Zhou , Y. Zhou , Z. Zhou , J. Zhu , Y. Zhu , A. Zichichi
27 ,10 ,M.B. Zimmermann , G. Zinovjev , N. Zurlo , Affiliation notes i Deceased ii Dipartimento DET del Politecnico di Torino, Turin, Italy iii
M.V. Lomonosov Moscow State University, D.V. Skobeltsyn Institute of Nuclear, Physics,Moscow, Russia iv Department of Applied Physics, Aligarh Muslim University, Aligarh, India v Institute of Theoretical Physics, University of Wroclaw, Poland
Collaboration Institutes A.I. Alikhanyan National Science Laboratory (Yerevan Physics Institute) Foundation, Yerevan,Armenia 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 Centre de Calcul de l’IN2P3, Villeurbanne, Lyon, France Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN), Havana, Cuba Centro de Investigación y de Estudios Avanzados (CINVESTAV), Mexico City and Mérida,Mexico Centro Fermi - Museo Storico della Fisica e Centro Studi e Ricerche “Enrico Fermi’, Rome, Italy Chicago State University, Chicago, Illinois, United States China Institute of Atomic Energy, Beijing, China Chonbuk National University, Jeonju, 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.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 andINFN Sezione di Torino, Alessandria, 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 ofSplit, 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, Czech Republic Faculty of Science, P.J. Šafárik University, Košice, Slovakia Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe-Universität Frankfurt,Frankfurt, Germany Gangneung-Wonju National University, Gangneung, Republic of Korea Gauhati University, Department of Physics, Guwahati, India Helmholtz-Institut für Strahlen- und Kernphysik, Rheinische Friedrich-Wilhelms-UniversitätBonn, 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 Institut de Physique Nucléaire d’Orsay (IPNO), Institut National de Physique Nucléaire et dePhysique des Particules (IN2P3/CNRS), Université de Paris-Sud, Université Paris-Saclay, Orsay,France Institute for Nuclear Research, Academy of Sciences, Moscow, Russia Institute for Subatomic Physics, Utrecht University/Nikhef, Utrecht, Netherlands Institute for Theoretical and Experimental Physics, 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 Johann-Wolfgang-Goethe Universität Frankfurt Institut für Informatik, Fachbereich Informatikund Mathematik, 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 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 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 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, Bari, Italy
Research Division and ExtreMe Matter Institute EMMI, GSI Helmholtzzentrum fürSchwerionenforschung GmbH, 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
Shanghai Institute of Applied Physics, Shanghai, China
St. Petersburg State University, St. Petersburg, Russia
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
Technische Universität München, Excellence Cluster ’Universe’, Munich, Germany
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 College of Southeast Norway, Tonsberg, Norway
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 Techonology of China, Hefei, China
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, Université Lyon 1, CNRS/IN2P3, IPN-Lyon, Villeurbanne, 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 PhysiqueNucléaire (DPhN), Saclay, France
Università degli Studi di Foggia, Foggia, Italy
Università degli Studi di Pavia, Pavia, Italy
Università di Brescia, 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, Hungarian Academy of Sciences, Budapest, Hungary
Yale University, New Haven, Connecticut, United States