Measurement of isolated photon-hadron correlations in s NN − − − √ = 5.02 TeV pp and p-Pb collisions
EEUROPEAN ORGANIZATION FOR NUCLEAR RESEARCH
CERN-EP-2020-09729 May 2020© 2020 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.
Measurement of isolated photon–hadron correlations in √ s NN = 5.02 TeVpp and p–Pb collisions ALICE Collaboration * Abstract
This paper presents isolated photon–hadron correlations using pp and p–Pb data collected by theALICE detector at the LHC. For photons with | η | < .
67 and 12 < p T <
40 GeV/ c , the associatedyield of charged particles in the range | η | < .
80 and 0 . < p T <
10 GeV/ c is presented. Thesemomenta are much lower than previous measurements at the LHC. No significant difference betweenpp and p–Pb is observed, with P YTHIA * See Appendix A for the list of collaboration members a r X i v : . [ nu c l - e x ] M a y solated photon–hadron correlations in 5.02 TeV pp and p–Pb collisions ALICE Collaboration Understanding the dynamics of quarks and gluons in nucleons and nuclei is a key goal of modern nuclearphysics. Proton − nucleus (pA) collisions at high energies provide information about the parton structureof nuclei, parton − nucleus interactions, and parton fragmentation in a nuclear medium [1]. The energy ofthe Large Hadron Collider (LHC) available for pA collisions is a factor of 25 larger than at the RelativisticHeavy Ion Collider (RHIC), and thus it provides unprecedented reach in longitudinal momentum fractionBjorken- x and Q [2].Parton fragmentation may be modified in the nucleus, offering a way to explore the dynamics of QCDin nuclei including elastic, inelastic, and coherent multiple scattering of partons. Moreover, the knownspatial dimensions of nuclei provide a filter possibly shedding light on the timescale of the fragmentationprocess, which remains unknown [1, 3]. Additionally, because photons produced in hard scatterings donot strongly interact, they constrain the parton kinematics from the same scattering before any modi-fication. Thus, measurements of photon-tagged jet fragmentation in pA collisions serve as a powerfultool to study multiple-scattering effects in cold nuclear matter [4], which serve as a control for effects ofthe quark − gluon plasma (QGP) in nucleus − nucleus collisions, where modifications of the jet spectrum,fragmentation, and substructure have been observed [5].Traditionally, the effects attributed to the QGP were expected to be absent in pA collisions. However,recent measurements show evidence for collective behavior [6], which might hint that a small droplet ofQGP forms in pA collisions, yet no significant modification of jet production or fragmentation has beenfound.In di-hadron and direct photon-hadron correlations, no significant modification of the jet fragmentationwas observed in measurements by the PHENIX collaboration in d–Au collisions at a center-of-mass en-ergy of 200 GeV [7] and the ALICE collaboration in p–Pb collisions at 5.02 TeV [8, 9] at mid rapidity.At forward rapidity, a strong-modification was observed by the PHENIX collaboration in d-Au colli-sions [10]. A recent measurement by the PHENIX collaboration with pp, p–Al, and p–Au data revealeda transverse momentum broadening consistent with a path-length dependent effect [11]. However, a re-cent ATLAS measurement of the jet fragmentation function in p–Pb collisions showed no evidence formodification of jet fragmentation for jets with 45 < p T <
206 GeV/ c [12]. Measurements of the frag-mentation of jets with much lower momentum are necessary to limit the Lorentz boost to the timescalesof fragmentation, as such a boost may result in fragmentation outside the nucleus. These measurementswould test the Q evolution of fragmentation functions in cold nuclear matter, testing factorization theo-rems that are neither proven nor expected to hold in general for collisions involving nuclei [13].In this work, azimuthal correlations of charged hadrons with isolated photons, γ iso , are analyzed inp–Pb and pp collisions with a center-of-mass energy of √ s NN = 5.02 TeV. Isolated photons are measuredat midrapidity, | η | < .
67, and with transverse momenta in the range 12 < p T <
40 GeV/ c , which yieldsthe scaling variable x T = p T / √ s NN = Q than other LHC experiments, which is where the largest nuclear effects can beexpected, and to a similar x T range as RHIC measurements at forward rapidity [10].The measurement of the transverse momentum of γ iso constrains the recoiling parton kinematics in away that is not possible with inclusive jet production and provides an effective way to probe the nuclearmodification of the fragmentation function. Moreover, the per-trigger yield is the ratio of a semi-inclusivecross-section (photon + jet) and inclusive cross-section (photon). Both quantities are sensitive to thenuclear parton distribution functions (PDF) in the same way [14, 15]. Thus, by measuring per-photonquantities, sensitivity to the nuclear PDF is eliminated.This paper is organized as follows: Section 2 covers the experimental setup; the datasets and simulationsare presented in Section 3; isolated photon and charged hadron reconstructions are detailed in Sections 42solated photon–hadron correlations in 5.02 TeV pp and p–Pb collisions ALICE Collaborationand 5; the purity measurement is reported in Section 6; Section 7 describes the correlation measurements;Section 8 reports the systematic uncertainties of the measurement; Section 9 presents the results; and theconclusions are discussed in Section 10. A comprehensive description of the ALICE experiment and its performance is provided in Refs. [16, 17].The detector elements most relevant for this study are the electromagnetic calorimeter system, which isused to measure and trigger on high p T photons, and the inner tracking system, which is used for trackingand determination of the interaction vertex. Both are located inside a large solenoidal magnet with a fieldstrength of 0.5 T along the beam direction.The Electromagnetic Calorimeter (EMCal) is a sampling calorimeter composed of 77 alternating layersof 1.4 mm lead and 1.7 mm polystyrene scintillators. It has a cellular structure made up of square cellswith a transverse size of 6 × . Wavelength shifting fibers attached to the perpendicular faces ofeach cell collect the scintillation light. These fibers are then connected to Avalanche Photodiodes (APDs)which amplify the generated scintillation light.The EMCal is located at a radial distance of approximately 428 cm from the nominal interaction point,and its cell granularity is ∆ η × ∆ ϕ = 14.3 × σ E / E = A ⊕ B / √ E ⊕ C / E where A = 1.7%, B = 11.3%, C = 4.8%, and the energy E is given in units of GeV [18]. The linearity ofthe response of the detector and electronics has been measured with electron test beams to a precision ofa few percent for the momentum range probed in this analysis. The non-linearity is negligible for clusterenergies between 3 and 50 GeV, which is the relevant range for this analysis. The geometrical acceptanceof the EMCal is | η | < . ◦ < ϕ < ◦ .The Di-jet Calorimeter (DCal) is an extension of the EMCal. It is back-to-back in azimuth with respectto the EMCal and uses the same technology and material as the EMCal [19]. Thus, it has identicalgranularity and intrinsic energy resolution. It covers 0 . < | η | < . ◦ < ϕ < ◦ , and anadditional region between | η | < ◦ < ϕ < ◦ . It was installed and commissioned duringthe first long shutdown of the LHC and therefore was operational during the 2017 pp run but not duringthe 2013 p–Pb run. Thus, both the EMCal and the DCal are used in the trigger and analysis of the ppcollisions, while only the EMCal was used in p–Pb.The inner tracking system (ITS) consists of six layers of silicon detectors and is located directly aroundthe interaction point. The two innermost layers consist of silicon pixel detectors positioned at radialdistances of 3.9 cm and 7.6 cm, followed by two layers of silicon drift detectors at 15.0 cm and 23.9 cm,and two layers of silicon strip detectors at 38.0 cm and 43.0 cm. The ITS covers | η | < . z = +
340 cm and z = −
90 cm and covering 2 . < η < . − . < η < − . The data used for this analysis were collected during the 2013 p–Pb run and the 2017 pp run, both at acenter-of-mass energy of √ s NN = .
02 TeV. Photon events were selected by the ALICE EMCal trigger.The EMCal issues triggers at two different levels, Level 0 (L0) and Level 1 (L1). The events that pass L0selection are further processed at L1. The L0 decision, issued at most 1.2 µ s after the collision, is basedon the analog charge sum of 4 × ×
48 cells in coincidence with a minimum bias trigger.The L1 trigger decision, which must be taken within 6.2 µ s after the collision, can incorporate additionalinformation from different TRUs, as well as other triggers or detectors. Additionally, the L1 extends the4 × .
56 TeV = ( Z / A ) × Z =
82 is the atomic number oflead and A =
208 is the nuclear mass number of the lead isotope used. This energy asymmetry results ina rapidity boost of the nucleon − nucleon center-of-mass frame by 0.465 units relative to the ALICE restframe in the direction of the proton beam.Full detector simulations are used in the study of the tracking performance described in Section 4, in thepurity measurement with template fits described in Section 6, and for comparisons with data describedin Section 9. The simulations of hard processes are based on the PYTHIA 8.2 event generator, 2013Monash Tune [21]. In PYTHIA, the signal events are included via 2 → gq → γ q and qq → γ g hard scatterings, defined at the leading order, followed by the leading-logarithm approx-imation of the parton shower and hadronization. To simulate p–Pb events, the pp dijet and gamma-jetevents simulated with PYTHIA 8.2 are embedded into p–Pb inelastic collision events generated withDPMJET [22] to reproduce the experimentally measured global p–Pb event properties. The simulateddata include only those events with a calorimeter cluster above threshold, and are boosted by 0.465 unitsof rapidity in the nucleon-nucleon center-of-mass frame.The detector response is simulated with GEANT3 [23] where the generated events are processed throughthe same reconstruction chain as the data. Following Ref. [24], a correction is applied to the GEANTsimulation to mimic the observed cross-talk between calorimeter cells, which is attributed to the readoutelectronics. This correction leads to a good description of the electromagnetic showers observed in data.To ensure a uniform acceptance and reconstruction efficiency in the pseudorapidity region | η | < .
8, onlyevents with a reconstructed vertex within ±
10 cm of the center of the detector along the beam directionare used.
The data taking approach during part of the 2017 pp run was to read out only a subset of the ALICEdetector systems. This enhanced the sampled luminosity by reading out at a higher rate. This lightweightreadout approach included the EMCal and the ITS but excluded the Time Projection Chamber. As aresult, ITS-only tracking is used for both pp and p–Pb data in this measurement. This approach differsfrom the standard ALICE tracking, but it has also been used for dedicated analyses of low momentumparticles that do not reach the TPC [25]. Previous studies using standalone ITS tracking used a maximumtrack p T of 0.8 GeV/ c [26]. What is novel in this analysis is the use of an extended range of p T in theITS-only tracking from 0.5 to 10 GeV/ c .All tracks are required to fulfill the following conditions: at least 4 hits in the ITS detector, a distanceof closest approach to the primary vertex in the transverse plane less than 2.4 cm, a distance of closestapproach along the beam axis less than 3.2 cm, and a track fit quality cut for ITS track points whichsatisfy χ / N hitsITS <
36. 4solated photon–hadron correlations in 5.02 TeV pp and p–Pb collisions ALICE CollaborationMonte Carlo simulations are used to determine the efficiency and purity for primary charged particles[27]. In p–Pb collisions, the tracking efficiency is 87% for tracks with 1 < p T <
10 GeV/ c , decreasingto roughly 85% at p T = 0.5 GeV/c; the momentum resolution is 6.6% for p T = 0.5 GeV/ c and 13% for p T = 10 GeV/ c . In pp collisions, the tracking efficiency is 85% for tracks at 1 < p T <
10 GeV/ c decreasingto roughly 83% at p T = 0.5 GeV/ c , with a momentum resolution of 6.6% for p T = 0.5 GeV/ c and 15% for p T = 10 GeV/ c . The fake track rate in p–Pb is 1.9% at 0.5 GeV/ c , growing linearly with p T , reaching 19%at 10 GeV/ c . For tracks in pp, the fake rate is 2.6% at 0.5 GeV/ c and grows linearly to 18% at 10 GeV/ c .The following check on the simulation was performed to ensure that it reproduces minimum − bias data.As the yield of charged particles in minimum − bias data is generally independent of ϕ , any dips inthe ϕ distribution are clearly visible in both simulation and data. After efficiency corrections, the ϕ distribution is flat within ± ϕ and η detector-dependent effects on the cluster-track pair acceptanceare corrected with the event mixing technique described in Section 7.To validate the combined effect of tracking efficiency, fake rate, and track momentum smearing cor-rections obtained from simulation of ITS-only tracking, the published charged-particle spectrum inp–Pb collisions at √ s NN = ±
8% for p T < .
85 GeV/ c and ±
5% for 0 . < p T <
10 GeV/ c . This difference is taken into account in thesystematic uncertainty assigned to tracking corrections. The signal for this analysis is isolated prompt photons. At the lowest order in pQCD, prompt photonsare produced via two processes: (i) quark-gluon Compton scattering, qg → q γ , (ii) quark-antiquarkannihilation, qq → g γ , and, with a much smaller contribution, qq → γγ . In addition, prompt photons areproduced by higher-order processes, such as fragmentation or bremsstrahlung [29]. The collinear part ofsuch processes has been shown to contribute effectively also at lowest order. At leading order in pQCD, prompt photons are produced in 2 → R = (cid:112) ( ∆ ϕ ) + ( ∆ η ) = .
4, around the cluster direction. In contrastwith a previous ALICE isolated photon measurement, Ref. [24], the isolation variable does not includeneutral particles. This enables us to use the full acceptance of the EMCal and reduces biases arising fromcorrelation with the opening angle of π decays. However, it does result in a slightly lower purity of theisolated single photon signal.For the determination of the isolation criterium, p isoT , the background due to the underlying event isestimated with the Voronoi method from the F AST J ET jet area/median package [31] on an event-by-event basis and subtracted according to: p isoT = ∑ track ∈ ∆ R < . p trackT − ρ × π × . . (1)The charged-particle density, ρ , is calculated for each event; average values are 3.2 GeV/ c in photon-triggered events in p–Pb and 1.6 GeV/ c in pp collisions. A requirement of p isoT < . c is used,5solated photon–hadron correlations in 5.02 TeV pp and p–Pb collisions ALICE Collaborationwhich results in a signal efficiency of about 90% that does not significantly depend on the photon p T .For photons near the edge of the detector, the isolation energy requirement is scaled to account for anymissing area in the isolation cone. Given that the results presented in this analysis are normalized to thenumber of reconstructed photons, the γ iso efficiency does not affect the measurement. Effects from ϕ and η dependence of the tracking performance on the isolation cut were found to be negligible. The photon reconstruction closely follows the method described in Ref. [24]. Clusters are obtained bygrouping all adjacent cells with common sides whose energy is above 100 MeV, starting from a seedcell with at least 500 MeV. Furthermore, a cluster must contain at least two cells to remove single-cellelectronic noise fluctuations. Clusters are required to have a minimum p T of p γ T ≥
12 GeV/ c . The timeof the highest-energy cell in the clusters relative to the main bunch crossing must satisfy ∆ t <
20 nsto reduce out-of-bunch pileup. In order to limit spurious signals caused by particles hitting the EMCalAPDs, clusters are required to have E cross / E cluster > .
05, where E cross is the sum of the energy in the cellsadjacent to, but not including, the the leading cell, and E cluster is the total energy of the entire cluster. Thenumber of local maxima in the cluster is required to be less than three to reduce hadronic background.Clusters originating from isolated, prompt photons are separated from background arising from neu-tral meson decays by means of the distinct shape of the electromagnetic shower that is encoded in the σ variable, which represents the extent of the cluster. The σ variable is defined as the square of thelarger eigenvalue of the energy distribution in the η – ϕ plane: σ = ( σ ϕϕ + σ ηη ) / + (cid:113) ( σ ϕϕ − σ ηη ) / + σ ϕη , (2)where σ i j = (cid:104) i j (cid:105) − (cid:104) i (cid:105)(cid:104) j (cid:105) are the covariance matrix elements; the integers i , j are cell indices in η and ϕ axes; (cid:104) i j (cid:105) and (cid:104) i (cid:105) , (cid:104) j (cid:105) are the second and the first moments of the cluster position cell. The positionis weighted by max ( log ( E cell / E cluster ) − w , ) . Following previous work [32], the cutoff in the log-weighting is chosen to be w = − .
5. Cells that contain less than e − . = σ calculation. Thus, σ discriminates between clusters belonging to singlephotons, having a σ distribution which is narrow and symmetric, and merged photons from neutralmeson decays, which are asymmetric and have a distribution dominated by a long tail towards highervalues.Most single-photon clusters yield σ ≈ .
25, as shown in Figure 1 where the signal is displayed inblue. Consequently, a cluster selection of σ < .
30 is applied irrespective of p T . Simulations indicatethis results in a signal efficiency of about 90% with no significant p T dependence.The main background remaining after the cluster and isolation cuts arises from multijet events where onejet typically contains a π or η that carries most of the jet energy and the decay photons are misidentifiedas single photons. The magnitude of this background is quantified in Section 6. The purity of the γ iso candidate sample is measured using a two-component template fit. The σ distribution for the isolated cluster sample is fit with a linear combination of the signal distribution,determined from a photon-jet simulation, and the background distribution, determined from data usingan anti-isolated sideband (5 . < p isoT < . c ) and corrected using a dijet simulation.The MINUIT [33] package is used for χ minimization and the MIGRAD package for uncertaintyestimation. The only free parameter in the fit is the number of signal clusters, N sig , because the overall6solated photon–hadron correlations in 5.02 TeV pp and p–Pb collisions ALICE Collaboration A r b i t r a r y un i t s ALICEp-Pb s NN = 5.02 TeVData, isoSignalBkg /dof = 125.3/99
12 < p T < 15 GeV/ c Purity = % ( F i t - D a t a ) / E rr o r Average A r b i t r a r y un i t s ALICEp-Pb s NN = 5.02 TeVData, isoSignalBkg /dof = 145.8/99
20 < p T < 25 GeV/ c Purity = % ( F i t - D a t a ) / E rr o r Average A r b i t r a r y un i t s ALICEp-Pb s NN = 5.02 TeVData, isoSignalBkg /dof = 99.4/99
25 < p T < 40 GeV/ c Purity = % ( F i t - D a t a ) / E rr o r Average
Figure 1: σ distribution of isolated clusters (black) and template fit results for p–Pb data in various p T ranges.The stacked histograms (yellow for background, blue for signal) show the predicted counts corresponding to thebest fit. The bottom panels show the normalized residuals of the fit, with the statistical uncertainty on the isolatedcluster data and the background template added in quadrature. The gray shaded region indicates the signal regionfor the isolated-photon selection. See text for additional details. normalization, N , is fixed to the total number of isolated clusters: N observed ( σ ) = N sig × S ( σ ) + ( N − N sig ) × B ( σ ) , (3)where S ( σ ) and B ( σ ) are the normalized signal and background templates. Examples of templatefits are shown in Figure 1. The peaks observed in the background templates originate mostly fromcollinear or very asymmetric π → γγ decays. Photons from η decays also contribute to the peaks in thebackground template.The background template is corrected for a bias due to correlations between the shower-shape and isola-tion variables [34]. This correlation leads to clusters in the isolation sideband having a somewhat higherhadronic activity than the true isolated background. Consequently, a background template constructedfrom this sideband region has an increased number of background-like clusters and purity values obtainedusing this systematically overestimate the true purity. A correction for this bias, R ( σ ) , is determinedusing dijet simulated events which also contain the correlation between trigger photon shower-shape andisolation cut. The ratio of the shower-shape distributions of clusters in the signal (Iso, p isoT < . c )region and sideband (Anti-iso, 5 . < p isoT < . c ) region is constructed via R ( σ ) = Iso MC ( σ ) Anti-iso MC ( σ ) . (4)This ratio of shower shape distributions is applied as a multiplicative correction to the background tem-plate: B corr. ( σ ) = Anti-iso data ( σ ) × R ( σ ) . (5)This background template correction results in an absolute correction on the purity of 8%–14% depend-ing on the cluster p T . The purities as a function of the cluster p T are shown in Figure 2. They arecompatible between the pp and p–Pb datasets within the uncertainties. A three-parameter error functionis fit to the data. The fits have been checked with several bin variations to ensure that they accuratelyrepresent the quickly rising purity at low p T . 7solated photon–hadron correlations in 5.02 TeV pp and p–Pb collisions ALICE Collaboration
15 20 25 30 35 40 p T (GeV/ c ) P u r i t y ( % ) ALICE s NN = 5.02 TeVppp-Pbpp Erf fitp-Pb Erf fit
Figure 2:
Purity of the γ iso sample as a function of transverse momentum for pp (red) and p–Pb (blue) data.The error bars represent statistical uncertainties only. The red shaded area represents systematic uncertainties inpp, while the blue empty boxes represent systematic uncertainties in p–Pb. The smooth lines correspond to athree-parameter error function fit to the data. The analysis of the correlation functions proceeds as follows: the angular correlation of γ iso candidateswith charged particles is constructed, requiring photons within | η | < .
67 and 12 < p T <
40 GeV/ c andassociated charged particles within | η | < .
80 and 0 . < p T <
10 GeV/ c . Geometrical acceptance effectsare corrected using a mixed-event correlation function, as described in detail below. The contribution of γ decay –hadron correlations is subtracted using the γ decay –hadron correlation function determined by in-verting the cluster shower-shape selection to select clusters with large values of σ . The γ decay –hadroncorrelation is scaled and subtracted from the isolated photon-hadron correlation function. Next, the re-maining contribution from the underlying event is subtracted. This uncorrelated background is estimatedusing the zero-yield-at-minimum (ZYAM) method. The ZYAM background level is cross-checked usinga control region at large | η h − η γ | . The away-side of each fully subtracted and corrected correlation func-tion is then integrated to measure the conditional yield of away-side hadrons. This analysis is performedin intervals of z T ≡ p h T / p γ T for charged particles, such that the measurement of the away-side yield issensitive to the parton fragmentation function.Event mixing is used as a data-driven approach to correct for detector acceptance effects. By constructingobservables with particles from different events, true physics correlations are removed from the corre-lation functions, leaving only the detector effects resulting from limited acceptance in η and detectorinhomogeneities in η and ϕ . Events are classified in bins of multiplicity (V0 amplitude, sum of V0A andV0C signals) and primary vertex z -position. Typically, event mixing uses event pairs within these bins.In this analysis, however, events are paired that are on-average closer in multiplicity and z -position thanthe standard binning method. This is accomplished using the Gale-Shapley stable matching algorithm[35] that removes the need for binning. The same-event correlation function in each z T bin is then dividedby the corresponding mixed-event correlation function.The pair-acceptance corrected correlation function is given by:8solated photon–hadron correlations in 5.02 TeV pp and p–Pb collisions ALICE Collaboration C ( ∆ ϕ , ∆ η ) = S ( ∆ ϕ , ∆ η ) M ( ∆ ϕ , ∆ η ) , (6)where S ( ∆ ϕ , ∆ η ) is the same-event correlation, and M ( ∆ ϕ , ∆ η ) is the mixed-event correlation. S ( ∆ ϕ , ∆ η ) is calculated by: S ( ∆ ϕ , ∆ η ) = N γ iso d N same ( ∆ ϕ , ∆ η ) d ∆ ϕ d ∆ η , (7)with N γ iso as the number of clusters that pass the isolation and shower shape cuts, and N same as thenumber of same event cluster-track pairs. d N same / d ∆ ϕ d ∆ η is found by pairing trigger particles withtracks from the same event. The mixed-event distribution, M ( ∆ ϕ , ∆ η ) , is given by M ( ∆ ϕ , ∆ η ) = α d N mixed ( ∆ ϕ , ∆ η ) d ∆ ϕ d ∆ η , (8)where α is the normalization constant that sets the maximum value of the mixed event correlation tounity, and N mixed is the number of mixed event cluster-track pairs. The term d N mixed / d ∆ ϕ d ∆ η is ob-tained by pairing trigger particles from γ -triggered events with tracks from minimum bias events matchedin z -vertex and multiplicity. The number of events was chosen such that any uncertainty from event mix-ing is negligible.The tracks used in the same-event correlation functions, S ( ∆ ϕ , ∆ η ) , are corrected for single track ac-ceptance, efficiency, and p trackT bin-to-bin migration calculated from the simulations. The corrections areimplemented using track-by-track weighting when filling the correlation histograms. The weights aregiven by: w tracking ( p trackT ) = ε × ( − f ) × b , (9)where ε is the track efficiency and f is the fake rate. b is the bin-to-bin migration factor that correctsfor p T smearing arising from the finite p trackT resolution and is determined by taking the ratio of thereconstructed p T and the true p T for all true tracks as a function of p trueT . The efficiency, fake rate, andbin migration corrections are applied in bins of p trackT .After this correction, the contribution to the signal region correlation function from decay photons thatpass the cluster selection is subtracted. The shower signal region photons correspond to isolated clusterswith σ < .
3. The subtraction of the correlated background starts by inverting the shower shapecriteria ( σ > .
4) to select isolated clusters that arise primarily from neutral meson decays. Thecorrelation of these shower background region clusters and associated hadrons is measured ( C BR ). This γ decay –hadron correlation function is scaled by (1 − Purity) and subtracted from the shower signal regioncorrelation function ( C SR ) according to: C S = C SR − ( − P ) C BR P , (10)where P is the purity and C S is the signal correlation function we aim to measure. ( − P ) C BR correspondsto the contribution of decay photons to the signal region correlation function after isolation and showershape cuts. The quantities C SR and ( − P ) C BR are shown in Fig. 3. The overall factor of 1/ P in Eq. 10is used to obtain the correct per-trigger yields after the γ decay –hadron contribution has been subtracted.The scaling of the correlations is done cluster-by-cluster, with the shower signal and shower background9solated photon–hadron correlations in 5.02 TeV pp and p–Pb collisions ALICE Collaboration Figure 3: γ iso –hadron signal region (black circles) and background region (grey squares) correlations in pp col-lisions at √ s = 5.02 TeV as measured by the ALICE detector. The shower signal region photons correspond toisolated clusters with σ < .
3, while the shower background region photons correspond to isolated clusters with σ > .
4. The vertical bars represent statistical uncertainty only. The horizontal bars represent the bin width in | ∆ ϕ | . The background correlation is subtracted from the signal correlation according to the numerator in Eq. 10. region clusters scaled by 1/ P and − PP , respectively, according to Eq. 10. The purity used in the cluster-by-cluster weighing procedure is determined by fitting the purity values from Fig. 2 to a three-parametererror function in order to avoid bin-edge effects and capture the quickly-rising behavior of the purity atlow cluster p T .To ensure that the shower background region correlations properly estimate the decay photons within theshower signal region, the background region cluster p T distribution is weighted to match the signal regioncluster p T distribution. This has no significant effect on the background subtraction, indicating that thebackground shape varies slowly with p T and discrepancies between p T distributions for background andsignal triggers have no significant effect on the correlations.The uncorrelated background from the underlying event is estimated in two ways. In the ZYAM pro-cedure, the average of the correlation function in the range 0 . < | ∆ ϕ | < π is taken as the uncorrelatedbackground estimate. This range takes advantage of the fact that there is no near-side jet peak in isolatedphoton-hadron correlations. As a result, the correlation function for | ∆ ϕ | < π should contain minimalsignal. The correlation function for | ∆ ϕ | < . . < ∆ η < . . < | ∆ ϕ | < .
2. Both methods yieldbackground estimates compatible within statistical uncertainties. The ZYAM method is used in the finalpedestal subtraction due to the method’s smaller statistical uncertainty.
The following sources of systematic uncertainty in the γ iso –hadron measurement have been considered:uncertainty on the purity measurement, underlying event subtraction, ITS-only tracking performance,acceptance mismatch due to the boost in p–Pb relative to pp, the γ iso p T spectra, and the photon energyscale. The systematic uncertainties in the γ iso –hadron and fragmentation measurements are described inmore detail in this section and are summarized in Table 1.10solated photon–hadron correlations in 5.02 TeV pp and p–Pb collisions ALICE Collaboration Table 1:
Summary of uncertainties in γ iso -hadron correlations, which are reported as per-trigger yields of cor-related hadrons. The ranges shown encompass the relative uncertainties for hadron z T in two ranges: Low- z T (0 . < z T < .
18) and High- z T (0 . < z T < . pp (Low- z T ) pp (High- z T ) p–Pb (Low- z T ) p–Pb (High- z T )Statistical Uncertainty 19–40% 28–49% 16–23% 27–44%Photon Purity 18% 18% 11% 11%Underlying Event 8%–15% 7%–12% 7%–9% 8%–9%Tracking performance 5.6% 5.6% 5.6% 5.6%Acceptance mismatch – – 2% 2%Photon Energy Scale < < < < < < < < < < < < The three sources of systematic uncertainty on the purity are the background template correction, con-struction of the signal template, and the choice of the anti-isolation region. These sources of systematicuncertainty on the purity measurement are summarized in Table 2. No single source of uncertainty dom-inates across p T ranges or collision systems. These are summed in quadrature to get an absolute overallsystematic uncertainty on the purity of 2–8%.To estimate the uncertainty on the background template correction, the ratio in Eq. 4 is also constructedin data and combined to create a double ratio:Double ratio = Iso data / Anti-iso data
Iso MC / Anti-iso MC . (11)In the signal region of the shower shape distribution (0 . < σ < . σ if the dijet MC reproduces thebackground shower-shape of the data. A linear function is fit to this double ratio in the background-dominated region of the shower shape distribution. The linear function is then extrapolated back intothe signal region. To estimate the systematic uncertainty on the background template correction, thatlinear fit and its variation within its fit uncertainty are used as additional multiplicative factors in Eq. 4.The purities calculated with these modified background template corrections are used to estimate thesystematic uncertainty on the purity from the background template correction.To estimate the uncertainty on the signal template, a background-only template fit is performed andcompared to the full template fit. For the background-only fit, the background template is fit to the datain the background-dominated region of the shower shape distribution. This fixes the normalization of thebackground template. Then, in the signal region, the difference between the data and background is usedto calculate the purity, with no contribution from the signal template. The difference between this purityand the purity as calculated with the signal template is taken to be the uncertainty on the signal template.To estimate the uncertainty from the anti-isolation selection, a template fit is performed with back-ground templates built from different overlapping anti-isolation selections. This identifies a nominalanti-isolation sideband selection where the template fits are good and the purities are stable. The un-11solated photon–hadron correlations in 5.02 TeV pp and p–Pb collisions ALICE Collaboration Table 2:
Summary of the purity and its systematic uncertainties (absolute quantities) on the γ iso selection. Therange spans the uncertainties on the purity in different p γ T bins. pp p–PbPurity 20-49% 21-53%Background template correction 2.9–3.4% 1.2–2.1%Signal distribution 0.8–5.9% 1.1–2.3%Anti-isolation selection 1.2–4.0% 0.8–2.4%Total 3.7–7.9% 2.0–3.9%certainty is estimated from the spread of the purities calculated from the template fits for which theanti-isolation selection falls within the nominal anti-isolation selection (5 < p isoT <
10 GeV/ c ).The uncertainty in the purity measurement is propagated to the correlation function measurement fol-lowing Eq. 10. The resulting uncertainty on the correlation function is ±
18% for pp data and ± γ -hadron analysis. To be conservative, theyare taken to be totally uncorrelated. The uncertainty on the purity in pp is larger than in p–Pb due tothe pp dataset having lower statistics: the background templates are directly obtained from data, and theuncertainty on the signal template is evaluated using data as well. The uncertainty in the underlying event subtraction originates from statistical fluctuations in the ZYAMestimate and propagates directly to the per-trigger hadron yields. This uncertainty ranges from 7% to15% depending on the z T bin and data set. The uncertainty is fully correlated in ∆ ϕ for a given z T bin,but totally uncorrelated among z T bins. It is also uncorrelated between the pp and p–Pb datasets. The uncertainty due to charged-particle p trackT reconstruction determined by comparing the stand-aloneITS p trackT specta with published ALICE p trackT spectra using standard ITS+TPC tracking [28]. As de-scribed in Section 4, the combined uncertainty due to tracking efficiency, fake rate, and bin-to-bin mi-gration corrections amounts to ±
5% added in quadrature with the total systematic uncertainty of thereference p T spectra. This systematic effect in the reference p T spectra is 1.6% − − . < p trackT <
10 GeV/ c [28].Systematic uncertainties due to secondary-particle contamination and from modeling of the particle com-position in Monte Carlo simulations are small ( < . < p T <
10 GeV/ c . These werealready estimated in Ref. [28] for the pp and p–Pb datasets and are already included in the referencespectrum systematic uncertainty estimate described above. The tracking performances in the pp andp–Pb datasets are very similar, but as a conservative approach these systematic uncertainties are treatedas completely uncorrelated. The difference between the energy of the proton and the energy of the nucleons in the Pb nucleusyields a boost of the center-of-mass of ∆ y = .
465 in the proton-going direction. This means that inp–Pb collisions, the acceptance for photons of − . < η < .
67 corresponds to − . < η < .
14 inthe center-of-mass frame, whereas the charged-particle acceptance of − . < η < . − . < η < .
27 in the center-of-mass frame. P
YTHIA γ iso –hadron cor-relations for isolated photons within − . < η < .
14 and charged particles within − . < η < . γ iso –hadron correlations using the nominal ranges of − . < η < .
67 and − . < η < . γ iso –hadroncorrelations show that the impact of an acceptance mismatch between pp and p–Pb data is about 5%, in-dependent of z T . This estimate is subject to PDF uncertainties, which dictate the shape of the differentialcross section in pseudorapidity of photons and associated hadrons. A correction is applied for this effectand an additional 2% systematic uncertainty on the per-trigger hadron yields is assigned. This systematicuncertainty is taken to be completely correlated with z T and is assigned only to the p–Pb measurements. The uncertainties related to overall normalization of the γ iso p T spectra (such as luminosity scale, vertexreconstruction efficiency, trigger efficiency, and photon reconstruction efficiency) cancel completely be-cause the observable is normalized per measured photon. Consequently, no systematic uncertainty fromthese sources is assigned.Sources of systematic uncertainty related to the photon energy scale, photon energy resolution and ma-terial budget are negligible. While the measurement is, by construction, totally insensitive to overallnormalization, it is, in principle, sensitive to bin-migration or scale uncertainties that affect the shape ofthe photon p T spectra. This potential systematic uncertainty is reduced by integrating over a large photon p T range (12–40 GeV/ c ). Moreover, the EMCal performance is such that these effects are small; for a12 GeV cluster, the resolution σ / E = . ⊕ . / √ E ⊕ . / E yields σ E / E = . σ E / E = . π → γγ events in data and simulation [37]. The calorimeteruncertainty is 0.8%. The uncertainties due to photon energy scale, resolution, and material budget havebeen estimated for the isolated photon cross section measurement with 7 TeV pp and are less than 3%in the p T range covered in this analysis [24]. The effects on the trigger-normalized correlation functionswould be even smaller, as explained earlier in this section. Given that this level of uncertainty is muchsmaller than other sources of systematic uncertainties for this measurement, it is neglected. The final γ iso -hadron correlations are reported in z T bins for each trigger-photon p T bin, where z T is theratio of the associated hadron, p hT , to isolated photon transverse momentum, z T = p hT / p γ iso T . The fullysubtracted azimuthal correlations as a function of ∆ ϕ , the azimuthal angle between the photon and thehadron, are shown in Fig. 4 for pp and p–Pb data. With the measured γ iso constraining the partonkinematics, the distribution of away-side associated hadrons with momentum fraction z T represents thefragmentation function of the parton.The darker colored bands at zero represents the uncertainty from the uncorrelated background estimate.The vertical bars indicate the statistical uncertainty only. The final correlation functions in each collisionsystem demonstrate similar behavior: both show a signal consistent with zero at small ∆ ϕ , and a risingaway-side peak at large ∆ ϕ arising predominantly from the hard-scattered parton opposite to the triggerphoton.Agreement within uncertainties between pp, p–Pb, and the PYTHIA 8.2 Monash Tune is observed. Bymeasuring associated hadrons, correlations can be observed for much larger angles than would otherwisebe possible for hadrons within a reconstructed jet. A χ test between pp and p–Pb data and a p-value iscalculated in each z T bin for the null hypothesis that pp and p–Pb data follow the same true correlationfunction. In each bin, the null hypothesis cannot be rejected, indicating that there is no significantdifference between the correlation functions in the two collision systems.13solated photon–hadron correlations in 5.02 TeV pp and p–Pb collisions ALICE Collaboration | | (rad) / N d N / dd || = 1.3, ndf = 7, p = 0.99 z T < 0.08 p h T < 3.2 GeV/ c
12 < p T < 40 GeV/ c ppp PbPYTHIA 8.2 Monashpp UE Errorp Pb UE Error | | (rad) / N d N / dd || = 3.8, ndf = 7, p = 0.81 z T < 0.19 p h T < 7.6 GeV/ c
12 < p T < 40 GeV/ c | | (rad) / N d N / dd || = 2.4, ndf = 7, p = 0.94 z T < 0.60 p h T < 10.0 GeV/ c
12 < p T < 40 GeV/ c ALICE p s NN = 5.02 TeV Figure 4: γ iso –hadron correlation functions for pp (red) and p–Pb (blue) data at √ s NN = 5.02 TeV as measured bythe ALICE detector. The different panels represent three different z T bins. The correlation functions are projectedover the range | ∆ η | < .
2. The darker bands at zero represents the uncertainty from the underlying event estimationin pp and p–Pb. The underlying event was estimated over the range 0 . < | ∆ ϕ | < .
6. The vertical bars representstatistical uncertainties only. The boxes indicate the systematic uncertainties. The dashed green line represents the γ iso –hadron correlation function obtained with PYTHIA 8.2 Monash Tune. “ p " is the p-value for the hypothesisthat the pp and p–Pb data follow the same true correlation function. The correlation functions from Fig. 4 are then integrated in the region | ∆ ϕ | > π for each z T bin to obtainthe γ iso -tagged fragmentation function shown in Fig. 5. This range roughly corresponds to the azimuthalangle consistent with the commonly used radius of R = z T bin is calculated from the statistical uncer-tainty in the fully subtracted correlation functions, along with the statistical uncertainty arising from theuncorrelated background subtraction. A maximum charged hadron p T of 10 GeV/ c and a photon trigger p T up to 40 GeV/ c could result in a potential bias of the associated z T spectrum. However, by repeatingthe analysis in different photon trigger p T bins, it was found that any such effects were negligible com-pared to other uncertainties. The two largest sources of systematic uncertainty are from the purity andthe single track correction factors. For the chosen p trackT interval, there is no strong p T dependence forthe uncertainty of the charged tracking efficiency.The ratio of the fragmentation functions in p–Pb and pp collisions is shown in the lower panel of Fig. 5.The fit yields a constant factor of 0 . ± . ( stat ) ± . ( sys ) . Thus, within total uncertainties, the p–Pbto pp ratio is consistent with unity.
10 Conclusions
We report a measurement of azimuthal correlations between isolated photons and associated chargedhadrons in p–Pb and pp collisions at 5.02 TeV per nucleon. We observe no difference in the z T distributionbetween pp and p–Pb data within a z T -integrated statistical uncertainty of 13% on the ratio. PYTHIA8.2 Monash Tune describes both data sets within the current precision. This measurement providesa constraint on the impact of cold nuclear matter effects on parton fragmentation, and indicates thatmodifications in the z T distributions observed in Pb–Pb collisions larger than the overall uncertainty onthis measurement of approximately 25% must be due to hot medium modifications. Analysis of isolatedphoton-hadron correlations in Pb–Pb collisions will allow hot nuclear matter effects to be quantified.Furthermore, the next LHC run will significantly improve sensitivity to cold nuclear matter effects dueto upgrades of the ALICE tracker and readout.This measurement significantly extends previous LHC results by focusing on the fragmentation of photon-14solated photon–hadron correlations in 5.02 TeV pp and p–Pb collisions ALICE Collaboration N d N d z T d || d ALICE, p s NN = 5.02 TeV 12 < p T < 40 GeV/ c p h T < 10.0 GeV/ c /ndf = 29.1/7, p = 0.76p PbppPYTHIA 8.2 Monash z T = p hT / p T p P b pp c = 0.84 ± 0.11 ± 0.19 p = 0.55 Figure 5: γ iso -tagged fragmentation function for pp (red) and p–Pb data (blue) at √ s NN = 5.02 TeV as measured bythe ALICE detector. The boxes represent the systematic uncertainties while the vertical bars indicate the statisticaluncertainties. The dashed green line corresponds to PYTHIA 8.2. The χ test for the comparison of pp andp–Pb data incorporates correlations among different z T intervals. A constant that was fit to the ratio includingstatistical and systematic uncertainties is shown as grey band, with the width indicating the uncertainty on the fit. tagged low- p T jets that probe values of x T = p T / √ s NN = x [38]. Acknowledgements
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, Czech15solated photon–hadron correlations in 5.02 TeV pp and p–Pb collisions ALICE CollaborationRepublic; 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; Centro Fermi - MuseoStorico della Fisica e Centro Studi e Ricerche Enrico Fermi and Istituto Nazionale di Fisica Nucleare(INFN), Italy; Institute for Innovative Science and Technology , Nagasaki Institute of Applied Science(IIST), Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) and Japan So-ciety for the Promotion of Science (JSPS) KAKENHI, 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; Nederlandse Organisatievoor Wetenschappelijk Onderzoek (NWO), Netherlands; The Research Council of Norway, Norway;Commission on Science and Technology for Sustainable Development in the South (COMSATS), Pak-istan; Pontificia Universidad Católica del Perú, Peru; Ministry of Science and Higher Education, NationalScience Centre and WUT ID-UB, Poland; Korea Institute of Science and Technology Information andNational Research Foundation of Korea (NRF), Republic of Korea; Ministry of Education and ScientificResearch, Institute of Atomic Physics and Ministry of Research and Innovation and Institute of AtomicPhysics, Romania; Joint Institute for Nuclear Research (JINR), Ministry of Education and Science ofthe Russian Federation, National Research Centre Kurchatov Institute, Russian Science Foundation andRussian Foundation for Basic Research, Russia; Ministry of Education, Science, Research and Sport ofthe Slovak Republic, Slovakia; National Research Foundation of South Africa, South Africa; SwedishResearch Council (VR) and Knut & Alice Wallenberg Foundation (KAW), Sweden; European Organi-zation for Nuclear Research, Switzerland; Suranaree University of Technology (SUT), National Scienceand Technology Development Agency (NSDTA) and Office of the Higher Education Commission underNRU project of Thailand, Thailand; Turkish Atomic Energy Agency (TAEK), Turkey; National Academyof Sciences of Ukraine, Ukraine; Science and Technology Facilities Council (STFC), United Kingdom;National Science Foundation of the United States of America (NSF) and United States Department ofEnergy, Office of Nuclear Physics (DOE NP), United States of America.
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59 ,iii , G. ConesaBalbastre , Z. Conesa del Valle , G. Contin
24 ,60 , J.G. Contreras , T.M. Cormier , Y. Corrales Morales ,P. Cortese , M.R. Cosentino , F. Costa , S. Costanza , P. Crochet , E. Cuautle , P. Cui ,L. Cunqueiro , D. Dabrowski , T. Dahms , A. Dainese , F.P.A. Damas
115 ,137 , M.C. Danisch ,A. Danu , D. Das , I. Das , P. Das , P. Das , S. Das , A. Dash , S. Dash , S. De , A. De Caro ,G. de Cataldo , J. de Cuveland , A. De Falco , D. De Gruttola , N. De Marco , S. De Pasquale ,S. Deb , H.F. Degenhardt , K.R. Deja , A. Deloff , S. Delsanto
25 ,131 , W. Deng , P. Dhankher , D. DiBari , A. Di Mauro , R.A. Diaz , T. Dietel , P. Dillenseger , Y. Ding , R. Divià , D.U. Dixit ,Ø. Djuvsland , U. Dmitrieva , A. Dobrin , B. Dönigus , O. Dordic , A.K. Dubey , A. Dubla
90 ,107 ,S. Dudi , M. Dukhishyam , P. Dupieux , R.J. Ehlers , V.N. Eikeland , D. Elia , B. Erazmus ,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. Frankenfeld , U. Fuchs , 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
105 ,107 , E.F. Gauger , M.B. Gay Ducati , M. Germain , J. Ghosh , P. Ghosh , S.K. Ghosh ,M. Giacalone , P. Gianotti , P. Giubellino
59 ,107 , P. Giubilato , A.M.C. Glaenzer , P. Glässel , A. GomezRamirez , V. Gonzalez
107 ,143 , L.H. González-Trueba , S. Gorbunov , L. Görlich , A. Goswami ,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 , F. Grosa
30 ,59 , J.F. Grosse-Oetringhaus ,R. Grosso , R. Guernane , 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
63 ,86 , A. Harlenderova , J.W. Harris , A. Harton , J.A. Hasenbichler ,H. Hassan , Q.U. Hassan , D. Hatzifotiadou
10 ,54 , P. Hauer , L.B. Havener , S. Hayashi ,S.T. Heckel , E. Hellbär , H. Helstrup , A. Herghelegiu , T. Herman , E.G. Hernandez , G. HerreraCorral , F. Herrmann , K.F. Hetland , H. Hillemanns , C. Hills , B. Hippolyte , B. Hohlweger , J. Honermann , D. Horak , A. Hornung , S. Hornung , R. Hosokawa
15 ,133 , P. Hristov , C. Huang ,C. Hughes , P. Huhn , T.J. Humanic , H. Hushnud , L.A. Husova , N. Hussain , S.A. Hussain ,D. Hutter , J.P. Iddon
34 ,127 , R. Ilkaev , H. Ilyas , M. Inaba , G.M. Innocenti , M. Ippolitov ,A. Isakov , M.S. Islam , M. Ivanov , V. Ivanov , V. Izucheev , B. Jacak , N. Jacazio
34 ,54 ,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
96 ,144 , P.G. Jones , J. Jung ,M. Jung , 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 , 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
34 ,59 ,S. Klein , C. Klein-Bösing , M. Kleiner , A. Kluge , M.L. Knichel , 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 , L. Koska , O. Kovalenko , V. Kovalenko ,M. Kowalski , I. Králik , A. Kravˇcáková , L. Kreis , M. Krivda
64 ,111 , F. Krizek ,K. Krizkova Gajdosova , M. Krüger , E. Kryshen , M. Krzewicki , A.M. Kubera , V. Kuˇcera
34 ,61 ,C. Kuhn , P.G. Kuijer , 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. LaRocca , Y.S. Lai , M. Lamanna , R. Langoy , K. Lapidus , A. Lardeux , P. Larionov , E. Laudi ,R. Lavicka , T. Lazareva , R. Lea , L. Leardini , J. Lee , S. Lee , 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 , V. Lindenstruth , A. Lindner , C. Lippmann , M.A. Lisa , A. Liu , J. Liu ,S. Liu , W.J. Llope , I.M. Lofnes , V. Loginov , C. Loizides , P. Loncar , J.A. Lopez , X. Lopez ,E. López Torres , J.R. Luhder , M. Lunardon , G. Luparello , Y.G. Ma , A. Maevskaya , M. Mager ,S.M. Mahmood , T. Mahmoud , A. Maire , R.D. Majka
146 ,i , M. Malaev , Q.W. Malik , L. Malinina
75 ,iv ,D. Mal’Kevich , P. Malzacher , G. Mandaglio
32 ,56 , V. Manko , F. Manso , V. Manzari , Y. Mao ,M. Marchisone , J. Mareš , G.V. Margagliotti , A. Margotti , A. Marín , C. Markert ,M. Marquard , C.D. Martin , N.A. Martin , P. Martinengo , J.L. Martinez , M.I. Martínez ,G. Martínez García , S. Masciocchi , M. Masera , A. Masoni , L. Massacrier , E. Masson ,A. Mastroserio
53 ,138 , A.M. Mathis , O. Matonoha , P.F.T. Matuoka , A. Matyja , C. Mayer ,F. Mazzaschi , M. Mazzilli , M.A. Mazzoni , A.F. Mechler , F. Meddi , Y. Melikyan
62 ,93 ,A. Menchaca-Rocha , C. Mengke , E. Meninno
29 ,114 , A.S. Menon , M. Meres , S. Mhlanga ,Y. Miake , L. Micheletti , L.C. Migliorin , D.L. Mihaylov , K. Mikhaylov
75 ,92 , A.N. Mishra ,D. Mi´skowiec , A. Modak , N. Mohammadi , A.P. Mohanty , B. Mohanty , M. Mohisin Khan
16 ,v ,Z. Moravcova , C. Mordasini , D.A. Moreira De Godoy , L.A.P. Moreno , I. Morozov , A. Morsch ,T. Mrnjavac , V. Muccifora , E. Mudnic , D. Mühlheim , S. Muhuri , J.D. Mulligan , A. Mulliri
23 ,55 ,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
10 ,54 , E. Nappi , M.U. Naru ,A.F. Nassirpour , C. Nattrass , R. Nayak , T.K. Nayak , S. Nazarenko , A. Neagu , R.A. Negrao DeOliveira , L. Nellen , S.V. Nesbo , G. Neskovic , D. Nesterov , L.T. Neumann , B.S. Nielsen ,S. Nikolaev , S. Nikulin , V. Nikulin , F. Noferini
10 ,54 , P. Nomokonov , J. Norman
79 ,127 , N. Novitzky ,P. Nowakowski , A. Nyanin , J. Nystrand , M. Ogino , A. Ohlson
81 ,104 , J. Oleniacz , A.C. Oliveira DaSilva , M.H. Oliver , C. Oppedisano , A. Ortiz Velasquez , A. Oskarsson , J. Otwinowski ,K. Oyama , Y. Pachmayer , V. Pacik , S. Padhan , D. Pagano , G. Pai´c , J. Pan , S. Panebianco ,P. Pareek
50 ,141 , 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
34 ,54 ,L. Pinsky , C. Pinto , S. Pisano
10 ,52 , D. Pistone , M. Płosko´n , M. Planinic , F. Pliquett ,M.G. Poghosyan , B. Polichtchouk , N. Poljak , A. Pop , S. Porteboeuf-Houssais , V. Pozdniakov ,S.K. Prasad , R. Preghenella , F. Prino , C.A. Pruneau , I. Pshenichnov , M. Puccio , J. Putschke ,S. Qiu , L. Quaglia , R.E. Quishpe , S. Ragoni , S. Raha , S. Rajput , J. Rak ,A. Rakotozafindrabe , L. Ramello , F. Rami , S.A.R. Ramirez , R. Raniwala , S. Raniwala ,S.S. Räsänen , R. Rath , V. Ratza , I. Ravasenga , K.F. Read
96 ,130 , A.R. Redelbach , K. Redlich
85 ,vi ,A. Rehman , P. Reichelt , F. Reidt , X. Ren , R. Renfordt , Z. Rescakova , K. Reygers , A. Riabov ,V. Riabov , T. Richert
81 ,89 , 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.F. Rojas ,P.S. Rokita , F. Ronchetti , A. Rosano , E.D. Rosas , K. Roslon , A. Rossi
28 ,57 , A. Rotondi ,A. Roy , P. Roy , O.V. Rueda , R. Rui , B. Rumyantsev , A. Rustamov , E. Ryabinkin , Y. Ryabov ,A. Rybicki , H. Rytkonen , O.A.M. Saarimaki , R. Sadek , S. Sadhu , S. Sadovsky , K. Šafaˇrík ,S.K. Saha , B. Sahoo , P. Sahoo , R. Sahoo , S. Sahoo , P.K. Sahu , J. Saini , S. Sakai ,S. Sambyal , V. Samsonov
93 ,98 , D. Sarkar , N. Sarkar , P. Sarma , V.M. Sarti , M.H.P. Sas ,E. Scapparone , J. Schambach , H.S. Scheid , C. Schiaua , R. Schicker , A. Schmah , C. Schmidt ,H.R. Schmidt , M.O. Schmidt , M. Schmidt , N.V. Schmidt
68 ,96 , A.R. Schmier , J. Schukraft ,Y. Schutz , K. Schwarz , K. Schweda , G. Scioli , E. Scomparin , J.E. Seger , Y. Sekiguchi ,D. Sekihata , I. Selyuzhenkov
93 ,107 , S. Senyukov , D. Serebryakov , A. Sevcenco , A. Shabanov ,A. Shabetai , R. Shahoyan , W. Shaikh , A. Shangaraev , A. Sharma , A. Sharma , H. Sharma ,M. Sharma , N. Sharma , S. Sharma , O. Sheibani , K. Shigaki , M. Shimomura , S. Shirinkin ,Q. Shou , Y. Sibiriak , S. Siddhanta , T. Siemiarczuk , 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 , 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 ,E. Stenlund , S.F. Stiefelmaier , D. Stocco , M.M. Storetvedt , L.D. Stritto , A.A.P. Suaide ,T. Sugitate , C. Suire , M. Suleymanov , 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 , M. Tarhini , M.G. Tarzila , A. Tauro , G. Tejeda Muñoz ,A. Telesca , L. Terlizzi , C. Terrevoli , 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 , A. Trifiró
32 ,56 , S. Tripathy
50 ,69 , T. Tripathy , S. Trogolo , G. Trombetta , L. Tropp ,V. Trubnikov , W.H. Trzaska , T.P. Trzcinski , B.A. Trzeciak
37 ,63 , A. Tumkin , R. Turrisi ,T.S. Tveter , K. Ullaland , E.N. Umaka , A. Uras , 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. Vergara Limón , L. Vermunt , R. Vernet , R. Vértesi , 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 , S.G. Weber , A. Wegrzynek , S.C. Wenzel ,J.P. Wessels , J. Wiechula , J. Wikne , G. Wilk , J. Wilkinson
10 ,54 , 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 ,Z. Zhang , V. Zherebchevskii , Y. Zhi , D. Zhou , Y. Zhou , Z. Zhou , J. Zhu , Y. Zhu ,A. Zichichi
10 ,26 , G. Zinovjev , N. Zurlo , Affiliation notes i Deceased ii Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA),Bologna, Italy iii
Dipartimento DET del Politecnico di Torino, Turin, Italy iv M.V. Lomonosov Moscow State University, D.V. Skobeltsyn Institute of Nuclear, Physics, Moscow, Russia v Department of Applied Physics, Aligarh Muslim University, Aligarh, India vi 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 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 and INFNSezione di 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,Czech Republic 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 Institute for Nuclear Research, Academy of Sciences, Moscow, Russia Institute for Subatomic Physics, Utrecht University/Nikhef, Utrecht, Netherlands 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 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, 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
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
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, 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 Physique Nucléaire(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, Budapest, Hungary
Yale University, New Haven, Connecticut, United States