arxiv.org · 2017. 6. 12. · european organisation for nuclear research (cern) submitted to: phys....

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EUROPEAN ORGANISATION FOR NUCLEAR RESEARCH (CERN) Nucl. Phys. A 978 (2018) 65 DOI: 10.1016/j.nuclphysa.2018.07.006 CERN-EP-2017-065 6th September 2018 Measurement of jet fragmentation in 5.02 TeV proton–lead and proton–proton collisions with the ATLAS detector The ATLAS Collaboration A measurement of the fragmentation functions of jets into charged particles in p+Pb colli- sions and pp collisions is presented. The analysis utilizes 28 nb -1 of p+Pb data and 26 pb -1 of pp data, both at s NN = 5.02 TeV, collected in 2013 and 2015, respectively, with the ATLAS detector at the LHC. The measurement is reported in the centre-of-mass frame of the nucleon–nucleon system for jets in the rapidity range |y * | <1.6 and with transverse mo- mentum 45 < p T < 260 GeV. Results are presented both as a function of the charged-particle transverse momentum and as a function of the longitudinal momentum fraction of the particle with respect to the jet. The pp fragmentation functions are compared with results from Monte Carlo event generators and two theoretical models. The ratios of the p+Pb to pp fragmenta- tion functions are found to be consistent with unity. c 2018 CERN for the benefit of the ATLAS Collaboration. Reproduction of this article or parts of it is allowed as specified in the CC-BY-4.0 license. arXiv:1706.02859v2 [hep-ex] 4 Sep 2018

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Page 1: arxiv.org · 2017. 6. 12. · EUROPEAN ORGANISATION FOR NUCLEAR RESEARCH (CERN) Submitted to: Phys. Lett. B. CERN-EP-2017-065 12th June 2017 Measurement of jet fragmentation in 5.02

EUROPEAN ORGANISATION FOR NUCLEAR RESEARCH (CERN)

Nucl. Phys. A 978 (2018) 65DOI: 10.1016/j.nuclphysa.2018.07.006

CERN-EP-2017-0656th September 2018

Measurement of jet fragmentation in 5.02 TeVproton–lead and proton–proton collisions with the

ATLAS detector

The ATLAS Collaboration

A measurement of the fragmentation functions of jets into charged particles in p+Pb colli-sions and pp collisions is presented. The analysis utilizes 28 nb−1 of p+Pb data and 26 pb−1

of pp data, both at √sNN = 5.02 TeV, collected in 2013 and 2015, respectively, with theATLAS detector at the LHC. The measurement is reported in the centre-of-mass frame ofthe nucleon–nucleon system for jets in the rapidity range |y∗| <1.6 and with transverse mo-mentum 45 < pT < 260 GeV. Results are presented both as a function of the charged-particletransverse momentum and as a function of the longitudinal momentum fraction of the particlewith respect to the jet. The pp fragmentation functions are compared with results from MonteCarlo event generators and two theoretical models. The ratios of the p+Pb to pp fragmenta-tion functions are found to be consistent with unity.

c© 2018 CERN for the benefit of the ATLAS Collaboration.Reproduction of this article or parts of it is allowed as specified in the CC-BY-4.0 license.

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1 Introduction

Heavy-ion collisions at the Large Hadron Collider (LHC) are performed in order to produce and studythe quark–gluon plasma (QGP), a phase of strongly interacting matter which emerges at very high energydensities; a recent review can be found in Ref. [1]. Measurements of jets and jet properties in heavy-ioncollisions are sensitive to the properties of the QGP. In order to quantify jet modifications in heavy-ioncollisions, proton–proton (pp) collisions are often used as a reference system. Using this reference, ratesof jet production in Pb+Pb collisions are observed to be reduced compared to that expected from therates in pp collisions, appropriately scaled to account for the nuclear thickness in Pb+Pb collisions [2, 3].Charged-particle fragmentation functions are also observed to be modified in Pb+Pb collisions comparedto pp collisions [4–6]. Both of these effects are interpreted as arising predominantly from the modificationof the parton showering process in the final stages of the collision.

In addition to final-state differences emerging from the presence of the hot and dense matter, jet produc-tion in Pb+Pb collisions may also differ from that in pp collisions due to effects arising from the presenceof the large nucleus. For example, nucleons bound in a nucleus are expected to have a modified struc-ture compared to the free nucleon [7], and partons may lose energy in the nuclear environment beforescattering [8]. Proton–nucleus collisions are used to differentiate between initial- and final-state effectsin Pb+Pb collisions. The inclusive jet production rate in proton–lead (p+Pb) collisions at 5.02 TeV wasmeasured [9–11] at the LHC and found to be only slightly modified after normalization by the nuclearthickness function. Measurements made at the Relativistic Heavy Ion Collider with deuteron–gold col-lisions yield similar results [12] (interestingly, Refs. [9, 12] observe a centrality dependence to inclusivejet production). High transverse momentum (pT) charged hadrons originate from the fragmentation ofjets and provide a complementary observable to that of jet production. The CMS Collaboration observeda small excess in the charged-particle spectrum measured in p+Pb collisions for pT > 20 GeV particlescompared to that expected from pp collisions [13]. Measurements of charged-particle fragmentationfunctions for jets in different pT intervals in p+Pb and pp collisions are crucial for connecting the jetand charged-particle results. Therefore, the measurements reported here are necessary both to establish areference for jet fragmentation measurements in Pb+Pb collisions and to determine any modifications tojet fragmentation in p+Pb collisions due to the presence of a large nucleus.

In recent years many of the features of Pb+Pb collisions which were interpreted as final state effects dueto hot nuclear matter were also observed in p+Pb collisions at the LHC and in d+Au collisions at RHIC.These features include long-range hadron correlations [14–17] and a centrality-dependent reduction inthe quarkonia yields [18–21]. There is considerable debate about whether these features arise from thesame source as in Pb+Pb collisions [22] or from other effects such as initial state gluon saturation [23].Measurements of jets in p+Pb collisions showed no effects that would be attributable to hot nuclearmatter, however additional measurements of jet properties in these collisions could help to constrain thesource of the modifications observed in other observables.

In this paper, the jet momentum structure in pp and p+Pb collisions is studied using the distributions ofcharged particles associated with jets which have a transverse momentum pjet

T in the range 45 to 260 GeV.Jets are reconstructed with the anti-kt algorithm [24] using a radius parameter R = 0.4. Charged particlesare assigned to jets via an angular matching ∆R < 0.4,1 where ∆R is the angular distance between the

1 ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP) in the centre of thedetector and the z-axis along the beam pipe. The x-axis points from the IP to the centre of the LHC ring, and the y-axis pointsupward. Cylindrical coordinates (r, φ) are used in the transverse plane, φ being the azimuthal angle around the beam pipe.The pseudorapidity is defined in terms of the polar angle θ as η = − ln tan(θ/2). Rapidity is defined as y = 0.5 ln E+pz

E−pzwhere E

2

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jet axis and the charged-particle position. Results on the fragmentation functions are presented bothas a function of the ratio between the component of the particle transverse momentum parallel to thejet direction, and the jet pT, z ≡ pT cos ∆R / pjet

T ,2 and as a function of the charged-particle transversemomentum with respect to the beam direction, pT:

D(z) ≡1

Njet

dNch

dz, (1)

andD(pT) ≡

1Njet

dNch

dpT. (2)

The quantity Nch is the number of charged particles and Njet is the number of jets under consideration.The fragmentation functions are per-jet normalized.

The fragmentation functions are compared in p+Pb and pp collisions at a centre-of-mass energy of5.02 TeV. In order to quantify any difference between p+Pb and pp collisions, the ratios of the frag-mentation functions are measured:

RD(z) ≡D(z)pPb

D(z)pp. (3)

In Pb+Pb collisions, such measurements are also presented as a function of charged-particle pT [4, 6]to explore the absolute pT scale of the modifications and to reduce jet-related uncertainties. Thus, inaddition to the more commonly used fragmentation functions as a function of z, this Letter also presentsthe analogous distributions and their ratios as a function of charged particle pT:

RD(pT) ≡D(pT)pPb

D(pT)pp. (4)

2 Experimental set-up

The measurements presented here are performed using the ATLAS calorimeter, inner detector, trigger,and data acquisition systems [25]. The calorimeter system consists of a sampling liquid argon (LAr)electromagnetic (EM) calorimeter covering |η| < 3.2, a steel–scintillator sampling hadronic calorimetercovering |η| < 1.7, a LAr hadronic calorimeter covering 1.5 < |η| < 3.2, and two LAr forward calori-meters (FCal) covering 3.2 < |η| < 4.9. The hadronic calorimeter has three sampling layers longitudinalin shower depth. The EM calorimeters are segmented longitudinally in shower depth into three layersplus an additional pre-sampler layer. The EM calorimeter has a granularity that varies with layer andpseudorapidity, but which is generally much finer than that of the hadronic calorimeter. The minimum-bias trigger scintillators (MBTS) [25] detect charged particles over 2.1 < |η| < 3.9 using two segmentedcounters placed at z = ±3.6 m. Each counter provides measurements of both the pulse heights and thearrival times of ionization energy deposits.

A two-level trigger system was used to select the p+Pb and pp collisions analysed here. The first, thehardware-based trigger stage Level-1, is implemented with custom electronics. The second level is thesoftware-based High Level Trigger (HLT). Jet events were selected by the HLT with Level-1 seeds from

and pz are the energy and the component of the momentum along the beam direction. Angular distance is measured in unitsof ∆R ≡

√(∆η)2 + (∆φ)2.

2 The ∆R is an approximation of the opening angle√

(∆θ)2 + (∆φ)2.

3

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jet, minimum-bias, and total-energy triggers. The total-energy trigger required a total transverse energymeasured in the calorimeter of greater than 5 GeV. The HLT jet trigger operated a jet reconstructionalgorithm similar to that applied in the offline analysis and selected events containing jets with transverseenergy thresholds ranging from 20 GeV to 75 GeV in p+Pb collisions and up to 85 GeV in pp collisions.In both the pp and p+Pb collisions, the highest-threshold jet trigger sampled the full delivered luminosity.Minimum-bias p+Pb events were required to have at least one hit in a counter on each side of the MBTSdetector at the Level-1 trigger.

The inner detector measures charged-particle tracks within the pseudorapidity interval |η| < 2.5 usinga combination of silicon pixel detectors, silicon microstrip detectors (SCT), and a straw-tube transitionradiation tracker (TRT), all immersed in a 2 T axial magnetic field [25]. Each of the three detectors iscomposed of a barrel and two symmetric end-cap sections. The pixel detector is composed of three layersof sensors with a nominal pixel size of 50 µm × 400 µm. Following the p+Pb data-taking and prior tothe 5 TeV pp data-taking an additional silicon tracking layer, the “insertable B-layer” (IBL) [26], wasinstalled closer to the interaction point than the other three layers. The SCT barrel section contains fourlayers of modules with 80 µm pitch sensors on both sides, and each end-cap consists of nine layers ofdouble-sided modules with radial strips having a mean pitch of 80 µm. The two sides of each SCT layerin both the barrel and the end-caps have a relative stereo angle of 40 mrad. The TRT contains up to 73(160) layers of staggered straws interleaved with fibres in the barrel (end-cap).

3 Event selection and data sets

The p+Pb data used in this analysis were recorded in 2013. The LHC was configured with a 4 TeV protonbeam and a 1.57 TeV per nucleon Pb beam producing collisions with √sNN = 5.02 TeV and a rapidityshift of the centre-of-mass frame, ∆y = 0.465, relative to the laboratory frame. The data collection wassplit into two periods with opposite beam configurations. The first period consists of approximately 55%of the integrated luminosity with the Pb beam travelling toward positive rapidity and the proton beam tonegative rapidity. The remaining data were taken with the beams of protons and Pb nuclei swapped. Thetotal p+Pb integrated luminosity is 28 nb−1. Approximately 26 pb−1 of

√s = 5.02 TeV pp data from

2015 was used. The instantaneous luminosity conditions provided by the LHC resulted in an averagenumber of p+Pb interactions per bunch crossing of 0.03. During pp data-taking, the average number ofinteractions per bunch crossing varied from 0.6 to 1.3.

The p+Pb events selected are required to have a reconstructed vertex, at least one hit in each MBTSdetector, and a time difference measured between the two MBTS sides of less than 10 ns. The pp eventsused in this analysis are required to have a reconstructed vertex; no requirement on the signal in the MBTSdetector is imposed. In p+Pb collisions the event centrality is determined by the FCal in the Pb-goingdirection as in Ref. [9]. The p+Pb events used here belong to the 0–90% centrality interval.

The performance of the ATLAS detector and offline analysis in measuring fragmentation functions inp+Pb collisions is evaluated using a sample of Monte Carlo (MC) events obtained by overlaying simu-lated hard-scattering pp events generated with Pythia version 6.423 (Pythia6) [27] onto minimum-biasp+Pb events recorded during the same data-taking period. A sample consisting of 2.4×107 pp events isgenerated with Pythia6 using parameter values from the AUET2B tune [28] and the CTEQ6L1 partondistribution function (PDF) set [29], at

√s = 5.02 TeV and with a rapidity shift equivalent to that in the

p+Pb collisions is used in the overlay procedure. About half of the events are simulated with one beamconfiguration and the second half with the other. The detector response is simulated using GEANT4 [30,

4

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31], and the simulated hits are combined with those from the data event. An additional sample of 2.6×107

pp hard-scattering events simulated with Pythia version 8.212 (Pythia8) [32] at√

s = 5.02 TeV with theA14 tune [33] and NNPDF23LO PDF set [34] is used to evaluate the performance for measuring frag-mentation functions in the 2015 pp data. Finally, fragmentation functions at generator-level evaluatedfrom 1.5×107 5.02 TeV pp events [35] generated with Herwig++ using the UEEE5 tune [36] and theCTEQ6L1 PDFs [29] are compared to the fragmentation function measured in 5.02 TeV pp data.

4 Jet and track selection

Jets are reconstructed with the same heavy-ion jet reconstruction algorithm used in previous measure-ments in p+Pb collisions [9]. The anti-kt algorithm [24] is first run in four-momentum recombinationmode using as input the signal in ∆η×∆φ = 0.1×0.1 calorimeter towers with the anti-kt radius parameterR set to 0.4 and 0.2 (R = 0.4 jets are used for the main analysis and the R = 0.2 jets are used to improvethe jet position resolution as discussed below). The energies in the towers are obtained by summing theenergies of calorimeter cells at the electromagnetic energy scale within the tower boundaries. Then, aniterative procedure is used to estimate the layer- and η-dependent underlying event (UE) transverse en-ergy density, while excluding the regions populated by jets. The UE transverse energy is subtracted fromeach calorimeter cell and the four-momentum of the jet is updated accordingly. Then, a jet η- and pT-dependent correction factor derived from the simulation samples is applied to correct the jet momentumfor the calorimeter response. Additionally, the jet energies were corrected by a multiplicative factor de-rived in in situ studies of the transverse momentum balance of jets recoiling against photons, Z bosons,and jets in other regions of the calorimeter [37, 38]. This in situ calibration, which typically differed fromunity by a few percent, accounts for differences between the simulated detector response and data.

Jets are required to have jet centre-of-mass rapidity, |y∗jet| < 1.6,3 which is the largest symmetric overlapbetween the two collision systems for which there is full charged-particle tracking coverage within a jetcone of size R = 0.4. To prevent neighbouring jets from distorting the measurement of the fragmentationfunctions, jets are rejected if there is another jet with higher pT within a distance δR = 1.0, where δR is thedistance between the two jet axes. To reduce the effects of the broadening of the jet position measurementdue to the UE, for R = 0.4 jets, the jet direction is taken from that of the closest matching R = 0.2 jetwithin δR = 0.3 when such a matching jet is found (this procedure has been previously used in Ref. [5]).All jets included in the analysis are required to have pT sufficiently large for the jet trigger efficiencyto be higher than 99%. Reconstructed jets which consist only of isolated high-pT electrons [39] fromelectroweak bosons are excluded from this analysis.

The MC samples are used to evaluate the jet reconstruction performance and to correct the measureddistributions for detector effects. The p+Pb jet reconstruction performance is described in Ref. [9]; the jetreconstruction performance in pp collisions is found to be similar to that in p+Pb collisions. In the MCsamples, the kinematics of the particle-level jets are reconstructed from primary particles4 with the anti-kt

algorithm with radius parameter R = 0.4. In these studies, particle-level jets are matched to reconstructedjets with a ∆R < 0.2.

3 The jet centre-of-mass rapidity y∗jet is defined as y∗jet ≡ yjet − ∆y where yjet is the jet rapidity in the ATLAS rest frame and ∆y

is the rapidity shift of the centre-of-mass frame.4 Primary particles are defined as particles with a mean lifetime τ > 0.3 × 10−10 s either directly produced in pp interactions or

from subsequent decays of particles with a shorter lifetime. All other particles are considered to be secondary.

5

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Tracks used in the analysis of p+Pb collisions are required to have at least one hit in the pixel detectorand at least six hits in the SCT. Tracks used in the analysis of pp collisions are required to have at least9 or 11 total silicon hits for |η| < 1.65 or |η| > 1.65, respectively, including both the pixel layers and theSCT. This includes a hit in the first (first or second) pixel layer if expected from the track trajectory for thep+Pb (pp) data. All tracks used in this analysis are required to have pT > 1 GeV. In order to suppress thecontribution of secondary particles, the distance of closest approach of the track to the primary vertex isrequired to be less than 1.5 mm along the beam axis and less than a value which varies from approximately0.6 mm at pT = 1 GeV to approximately 0.2 mm at pT = 20 GeV in the transverse plane.

[GeV]truthT

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< -2.0truthη-2.5 <

< -1.0truthη-2.0 <

< 1.0truthη-1.0 <

< 2.0truthη1.0 <

Figure 1: Tracking efficiency as a function the primary particle momentum at generation level, ptruthT , in pp collisions

(left) and in p+Pb collisions for one of the two beam configurations (right). The different sets of points show theprimary particle pseudorapidity, ηtruth, intervals in which the track reconstruction efficiency has been performed.The different ηtruth intervals in pp and p+Pb plots reflect the different regions of the tracking system used in the twocases due to the boosted p+Pb system. The solid curves show parameterizations of efficiencies.

The efficiency for reconstructing charged particles within jets in p+Pb and pp collisions is evaluated usingPythia6 and Pythia8 MC samples, respectively, and is computed by matching the reconstructed tracksto generator-level primary particles. The association is done based on contributions of generator-levelparticles to the hits in the detector layers. A reconstructed track is matched to a generator-level particle ifit contains hits produced primarily by this particle [31]. The efficiencies are determined separately for thetwo p+Pb running configurations because the η regions of the detector used for the track measurement aredifferent for the two beam configurations. The charged-particle reconstruction efficiencies as a functionof the primary particle’s transverse momentum, ptruth

T , in coarse ηtruth intervals, are shown in Figure 1 inpp and p+Pb collisions. The ptruth

T dependence of the efficiencies is parameterized using a fifth-orderpolynomial in log(ptruth

T ) which describes the efficiency behaviour in the range of particle ptruthT from 1.0

to 150 GeV. The tracking efficiency is observed to be constant above 150 GeV and a constant efficiencyvalue is used for particles with ptruth

T > 150 GeV due to the limited size of the MC samples in thatphase space region. To account for finer scale variations of the tracking efficiency with pseudorapidity,the parameterizations are multiplied by an η-dependent scale factor evaluated in ηtruth intervals of 0.1units in coarse ptruth

T intervals. The dependence of the charged-particle efficiency on pjetT is found to be

negligible for the pjetT selections used here. The measured D(z) and D(pT) distributions are corrected for

the contribution of reconstructed “fake” tracks which cannot be matched to a generated primary particlein the MC samples produced without minimum bias interactions overlaid and the residual contribution oftracks matched to secondary particles. The fraction of secondary and fake tracks is found to be below 2%of the tracks that pass the selection in any track and jet kinematic region. The contribution from thesetracks to the fragmentation functions is subtracted from the measured fragmentation functions in both the

6

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pp and p+Pb collisions.

5 Analysis procedure

Reconstructed charged particle tracks are associated with a reconstructed jet if they fall within ∆R =

0.4 of the jet axis. For each of these particles the momentum fraction, z, is calculated. The measuredfragmentation functions are constructed as:

D(z)meas ≡1

Njet

1ε(η, pT)

∆Nch(z)∆z

(5)

andD(pT)meas ≡

1Njet

1ε(η, pT)

∆Nch(pT)∆pT

, (6)

where ε(η, pT) is the track reconstruction efficiency, and Njet is the total number of jets in a given pjetT

bin. The quantities ∆Nch(z) and ∆Nch(pT) are the numbers of associated tracks within the given z or pTrange, respectively. The efficiency correction is applied on a track-by-track basis, assuming pT = ptruth

T .While that assumption is not strictly valid, the efficiency varies sufficiently slowly with ptruth

T that the errorintroduced by this assumption is negligible.

In p+Pb collisions the UE contribution to the fragmentation functions from charged particles not asso-ciated with the jet constitutes a background that needs to be subtracted. It originates in soft interactionsthat accompany the hard process in the same p+Pb collision and depends on charged-particle pT and η.This background is determined event by event for each measured jet by using a grid of ∆R = 0.4 conesthat span the full coverage of the inner detector. The cones have a fixed distance between their centreschosen such that the coverage of the inner detector is maximized while the cones do not overlap eachother. Any such cone containing a charged particle with pT > 3.5 GeV is assumed to be associated witha real jet and is excluded from the UE contribution. The 3.5 GeV threshold is derived from studies ofUE contribution in MC samples. The estimated contribution from UE particles in each cone is correctedto account for differences in the average UE particle yield at a given pT between the η position of thecone and the η position of the jet. The correction is based on a parameterization of the pT and η depend-ence of charged-particle yields in minimum-bias collisions. The resulting UE contribution is evaluatedfor charged particles in the transverse momentum interval of 1 < pT < 3.5 GeV and averaged over allcones. The UE contribution is further corrected for the correlation between the actual UE yield withinthe jet cone and the jet energy resolution discussed in Ref. [5]. This effect is corrected by a multiplicativecorrection factor, dependent on the track pT (or z) and the jet pT. The correction is estimated in MCsamples as the ratio of the UE contribution calculated from tracks within the area of a jet that do not havean associated generator-level particle to the UE contribution estimated by the cone method. Corrected UEcontributions are then subtracted from measured distributions. The maximum size of the UE contributionis 20% for the lowest track pT (or z). The UE from the cone method is compared to an alternative UEestimation and the difference is found to be negligible. The subtracted UE contribution has no azimuthalvariation in p+Pb collisions and no UE subtraction is performed for the pp measurement due to negligibleUE contribution (less than 2% over the entire kinematic range measured).

The measured D(z) and D(pT) distributions are corrected for detector effects by means of a two-dimensionalBayesian unfolding procedure [40] using the RooUnfold package [41]. The unfolding procedure removes

7

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the effect of bin migration due to the jet energy and the track momentum resolutions. Using the MCsamples, four-dimensional response matrices are created using the particle-level and reconstructed pjet

T ,and generator-level and reconstructed track pT (z). Separate unfolding matrices are constructed for thep+Pb and pp data. An independent bin-by-bin unfolding procedure is used to correct the measured pjet

Tspectra, which is used to normalize the unfolded fragmentation functions by the number of jets. Theresponse matrices are reweighted such that the shapes of the measured fragmentation functions and jetspectra in the simulation match those in the data. The number of iterations in the Bayesian unfoldingis selected to be the minimum number for which the relative change in the fragmentation function atz = 0.1 is smaller than 0.2% per additional iteration in all pjet

T bins. This condition ensures the stabilityof the unfolding and minimizes statistical fluctuations due to the unfolding in the high z and pT regions.The resulting number of iterations is driven by the low pjet

T intervals, which require the most iterations toconverge. The systematic uncertainty due to the unfolding is typically much larger than the impact of thestability requirement, especially for the lowest pjet

T values used in this analysis (discussed in Section 6).Following this criterion, 14 iterations are used for both the p+Pb and pp data sets. The analysis procedureis tested by dividing the MC event sample in half and using one half to generate response matrices withwhich the other half is unfolded. Good recovery of the generator-level distributions is observed for theunfolded events and the deviations from perfect closure are incorporated into the systematic uncertain-ties.

6 Systematic uncertainties

The systematic uncertainties in the measurement of the fragmentation functions and their ratios are de-scribed in this section. The following sources of systematic uncertainty in the measurement of the frag-mentation functions and their ratios are considered: the jet energy scale (JES), the jet energy resolution(JER), the dependence of the unfolded results on the choice of the starting MC distributions, the residualnon-closure of the unfolding and the tracking-related uncertainties. For each variation reflecting a sys-tematic uncertainty the fragmentation functions are re-evaluated and the difference between the variedand nominal fragmentation functions is used as an estimate of the uncertainty. The systematic uncertain-ties in the D(z) and D(pT) measurements in both collision systems are summarized in Figures 2 and 3,respectively, for two different jet pT bins. The systematic uncertainties from each source are taken asuncorrelated and combined in quadrature to obtain the total systematic uncertainty.

The JES uncertainty is determined from in situ studies of the calorimeter response [37, 42, 43], and studiesof the relative energy-scale difference between the jet reconstruction procedure in heavy-ion collisions andthe procedure used in pp collisions [44]. The impact of the JES uncertainty on the measured distributionsis evaluated by constructing new response matrices where all reconstructed jet transverse momenta areshifted by ±1 standard deviation (±1σ) of the JES uncertainty. The data are then unfolded with thesematrices. Each component that contributes to the JES uncertainty is varied separately. In total, 45 and51 independent systematic components constitute the full JES uncertainty in the analysis of p+Pb andpp collisions, respectively. These components are uncorrelated among each other within the data set andfully correlated across pT and η. The JES uncertainty increases with increasing z and particle pT at fixedpjet

T and decreases with increasing pjetT .

The uncertainty in the fragmentation functions due to the JER is estimated by repeating the unfoldingprocedure with modified response matrices, where the resolution of the reconstructed jet pjet

T is broadenedby Gaussian smearing. The smearing factor is evaluated using an in situ technique involving studies of

8

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z-110 1

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Figure 2: Summary of the systematic uncertainties in the fragmentation function, D(z), in p+Pb collisions (top) andpp collisions (bottom) for jets in the 45–60 GeV pjet

T interval (left) and in the 160–210 GeV pjetT interval (right). The

systematic uncertainties due to JES, JER, unfolding, MC non-closure and tracking are shown along with the totalsystematic uncertainty from all sources.

dijet energy balance [45, 46]. The systematic uncertainty due to the JER increases with increasing z andparticle pT at fixed pjet

T and decreases with increasing pjetT .

The unfolding uncertainty is estimated by generating the response matrices from the MC distributionswithout reweighting to match the shapes of the reconstructed data in pjet

T and D(z) or D(pT). Conser-vatively, an additional uncertainty to account for possible residual limitations in the analysis procedurewas assigned by evaluating the non-closure of the unfolded distributions in simulations, as described inSection 5. The magnitude of both of these uncertainties is typically below 5% except for the highest zand track pT bins.

The uncertainties related to the track reconstruction and selection originate from several sources. Uncer-tainties related to the rate of secondary and fake tracks, the material description in the simulation, and thetrack’s transverse momentum were obtained from studies in data and simulation described in Ref. [47].The systematic uncertainty in the secondary-track and fake-track rate is 30% in pp collisions and 50%in p+Pb. The contamination by secondary and fake tracks is at most 2%, the resulting uncertainty in thefragmentation functions is at most 1%. The sensitivity of the tracking efficiency to the description of theinactive material in the MC samples is evaluated by varying the material description. This uncertainty isbetween 0.5 and 2% (depending on track η) in the track pT range used in the analysis. Uncertainty in thetracking efficiency due to the high local track density in the cores of jets is 0.4% [48] for all pjet

T selections

9

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[GeV]T

p1 10

) [%

]T

p(Dδ

-40

-20

0

20

40

60JESJERUnfoldingMC non-closureTrackingTotal

*|<1.6jet

y|

ATLAS= 5.02 TeVNNs

-1+Pb 2013, 28 nbp

< 60 GeVjet

Tp45 <

[GeV]T

p1 10 210

) [%

]T

p(Dδ

-40

-20

0

20

40

60JESJERUnfoldingMC non-closureTrackingTotal

*|<1.6jet

y|

ATLAS= 5.02 TeVNNs

-1+Pb 2013, 28 nbp

< 210 GeVjet

Tp160 <

[GeV]T

p1 10

) [%

]T

p(Dδ

-40

-20

0

20

40

60JESJERUnfoldingMC non-closureTrackingTotal

*|<1.6jet

y|

ATLAS= 5.02 TeVNNs

-1 2015, 25 pbpp

< 60 GeVjet

Tp45 <

[GeV]T

p1 10 210

) [%

]T

p(Dδ

-40

-20

0

20

40

60JESJERUnfoldingMC non-closureTrackingTotal

*|<1.6jet

y|

ATLAS= 5.02 TeVNNs

-1 2015, 25 pbpp

< 210 GeVjet

Tp160 <

Figure 3: Summary of the systematic uncertainties in the fragmentation function, D(pT), in p+Pb collisions (top)and pp collisions (bottom) for jets in the 45–60 GeV pjet

T interval (left) and in the 160–210 GeV pjetT interval (right).

The systematic uncertainties due to JES, JER, unfolding, MC non-closure and tracking are shown along with thetotal systematic uncertainty from all sources.

in this analysis. The uncertainty due to the track selection criteria is evaluated by repeating the analysiswith an additional requirement on the significance of the distance of closest approach of the track to theprimary vertex. This uncertainty affects both the track reconstruction efficiency and the rate of secondaryand fake tracks. The resulting uncertainty typically varies from 1% at low track pT and low z to 5% at hightrack pT and high z. The systematic uncertainties in the fragmentation functions due to the parameteriza-tion of the efficiency corrections is less than 1%. An additional uncertainty takes into account a possibleresidual misalignment of the tracking detectors in pp data-taking. The alignment in this data was checkedin situ with Z → µ+µ− events, and thus a track-pT dependent uncertainty arises from the finite size of thissample. The resulting uncertainties in the fragmentation functions are typically smaller than 1% exceptat large z where they are as large as 4%. Finally, the track-to-particle matching requirements are varied.This variation affects the track reconstruction efficiency, the track momentum resolution, and the rate ofsecondary and fake tracks. The resulting uncertainties in the fragmentation functions are smaller than 1%.After deriving new response matrices and efficiency corrections, the resulting systematic uncertainty inthe fragmentation functions is found to be less than 0.5%. The tracking uncertainties shown in Figures 2and 3 include all the above explained track-related systematic uncertainties added in quadrature.

The correlations between the various systematic components in the two collision systems are consideredwhen taking the ratios of p+Pb to pp fragmentation functions. For the JES uncertainty, each sourceof uncertainty is classified as either correlated or uncorrelated between the two systems depending on

10

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z-110 1

[%]

)z(D

R δ

-40

-20

0

20

40

60JESJERUnfoldingMC non-closureTrackingTotal

*|<1.6jet

y|

ATLAS -1= 5.02 TeV, 28 nbNNs+Pb, p-1= 5.02 TeV, 25 pbs, pp

< 60 GeVjet

Tp45 <

z-210 -110 1

[%]

)z(D

R δ

-40

-20

0

20

40

60JESJERUnfoldingMC non-closureTrackingTotal

*|<1.6jet

y|

ATLAS -1= 5.02 TeV, 28 nbNNs+Pb, p-1= 5.02 TeV, 25 pbs, pp

< 210 GeVjet

Tp160 <

Figure 4: Summary of the systematic uncertainties for RD(z) ratios, for jets in the 45–60 GeV pT interval (left) andin the 160–210 GeV pT interval (right). The systematic uncertainties due to JES, JER, unfolding, MC non-closureand tracking are shown along with the total systematic uncertainty from all sources.

[GeV]T

p1 10

[%]

)T

p(D

R δ

-40

-20

0

20

40

60JESJERUnfoldingMC non-closureTrackingTotal

*|<1.6jet

y|

ATLAS -1= 5.02 TeV, 28 nbNNs+Pb, p-1= 5.02 TeV, 25 pbs, pp

< 60 GeVjet

Tp45 <

[GeV]T

p1 10 210

[%]

)T

p(D

R δ

-40

-20

0

20

40

60JESJERUnfoldingMC non-closureTrackingTotal

*|<1.6jet

y|

ATLAS -1= 5.02 TeV, 28 nbNNs+Pb, p-1= 5.02 TeV, 25 pbs, pp

< 210 GeVjet

Tp160 <

Figure 5: Summary of the systematic uncertainties for RD(pT) ratios, for jets in the 45–60 GeV pT interval (left) andin the 160–210 GeV pT interval (right). The systematic uncertainties due to JES, JER, unfolding, MC non-closureand tracking are shown along with the total systematic uncertainty from all sources.

its origin. The JER, unfolding and MC non-closure uncertainties are taken to be uncorrelated. For thetracking-related uncertainties the variation in the selection requirements, tracking in dense environments,secondary-track and fake-track rates, and parameterization of the efficiency corrections are taken as un-correlated. The first three of these are conservatively considered as uncorrelated because the trackingsystem was augmented with the IBL and the tracking algorithm changed between the p+Pb and pp data-taking periods. The uncertainties due to the track-to-particle matching and the inactive material in theMC samples are taken as correlated between p+Pb and pp collisions. For the correlated uncertaintiesthe ratios are re-evaluated applying the variation to both collision systems; the resulting variations ofthe ratios from their central values is used as the correlated systematic uncertainty. The total systematicuncertainties in the RD(z) and RD(pT) distributions are shown in Figures 4 and 5, respectively, for two pjet

Tintervals.

11

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z

2−10 1−10 1

)

z(D

4−10

2−10

1

210

410

610

810 -1 = 5.02 TeV, 26 pbs, pp

|<1.6jet

*y|

ATLAS

z

2−10 1−10 1

)5 < 260 GeV (x 10 jet

Tp210 <

)4 < 210 GeV (x 10 jet

Tp160 <

)3 < 160 GeV (x 10 jet

Tp110 <

)2 < 110 GeV (x 10 jet

Tp80 <

)1 < 80 GeV (x 10 jet

Tp60 <

)0 < 60 GeV (x 10 jet

Tp45 <

-1 = 5.02 TeV, 28 nbNNs+Pb, p0-90%

|<1.6jet

*y|

ATLAS

Figure 6: Fragmentation functions as a function of the charged particle z in pp (left) and p+Pb collisions (right)for the pjet

T intervals used in this analysis. The fragmentation functions in both collision systems are offset bymultiplicative factors for clarity as noted in the legend. The statistical uncertainties are shown as error bars and thesystematic uncertainties are shown as shaded boxes. In many cases the statistical uncertainties are smaller than themarker size.

7 Results

The D(z) and D(pT) distributions in both collision systems are shown in Figures 6 and 7, respectively.Figure 8 compares the D(z) distribution in pp collisions at 5.02 TeV to the predictions from three eventgenerators (Pythia6, Pythia8, and Herwig++) using the parameter-value tunes and PDF sets describedin Section 3 for the six pjet

T intervals. The Pythia8 generator provides the best description of the data,generally agreeing within about 5 to 10% over the kinematic range used here. Pythia6 agrees withinapproximately 25% when compared to the data and Herwig++ agrees within approximately 20% exceptfor the highest z region, where there are some larger deviations. Similar agreement with Pythia6 andHerwig++ generators with different tunes than used in this analysis was reported by ATLAS in the meas-urement of fragmentation functions in 7 TeV pp collisions [49]. The tunes of Pythia6 and Pythia8 usedhere include the results from that measurement.

Figure 9 shows the pp fragmentation functions compared to two theoretical calculations. These predic-tions use a slightly different definition of z compared to the definition used in this measurement. Thiscan introduce a difference between the fragmentation functions of approximately 1%. The calculation inRefs. [50, 51] provides fragmentation functions with next-to-leading-order (NLO) accuracy as well as aresummation of logarithms in the jet cone size. The calculation in Ref. [52] is at NLO and uses the ap-

12

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[GeV] T

p1 10 210

] -1

) [G

eVT

p(D

4−10

2−10

1

210

410

610

810

|<1.6jet

*y|

ATLAS

= 5.02 TeVs, pp -125 pb

) 5 < 260 GeV (x 10 jet

Tp210 <

) 4 < 210 GeV (x 10 jet

Tp160 <

) 3 < 160 GeV (x 10 jet

Tp110 <

) 2 < 110 GeV (x 10 jet

Tp80 <

) 1 < 80 GeV (x 10 jet

Tp60 <

) 0 < 60 GeV (x 10 jet

Tp45 <

[GeV] T

p1 10 210

) T

pD

(|<1.6

jet*y|

ATLAS

= 5.02 TeV, 0-90%NNs+Pb, p -128 nb

Figure 7: Fragmentation functions as a function of the charged particle pT in pp (left) and p+Pb collisions (right)for the pjet

T intervals used in this analysis. The fragmentation functions in both collision systems are offset bymultiplicative factors for clarity as noted in the legend. The statistical uncertainties are shown as error bars and thesystematic uncertainties are shown as shaded boxes. In many cases the statistical uncertainties are smaller than themarker size.

proximation that the jet cone is narrow. For the parton-to-charged-hadron fragmentation functions, bothcalculations use DSS07 fragmentation functions [53]. The uncertainties in the theoretical calculation arenot estimated, including the uncertainty in DSS07, which is common to both calculations. The calcula-tions are systematically higher than the data and generally agree within 20–30%. Larger deviations areobserved at the low and high z regions. The DSS07 fragmentation functions have a minimum z of 0.05and the calculations use extrapolated fragmentation functions in the region below z = 0.05.

Figures 10 and 11 show the ratios of fragmentation functions in p+Pb collisions to those in pp collisions,as a function of z and pT respectively for pjet

T from 45 to 260 GeV. Over the kinematic range selectedhere, the RD(z) and RD(pT) distributions show deviations from unity of up to approximately 5% (up to 10%for 60–80 GeV jet selections) for z < 0.1 and pT < 10 GeV. The deviations are larger than the reportedsystematic uncertainties by at most a couple of percent and always less than 1.5σ of the systematicuncertainties. At higher z and pT values the ratios are consistent with unity. At the highest z points for the160–210 GeV and 210–260 GeV jet selections, deviations from unity of approximately 0.9σ and 1.3σ ofcombined statistical and systematic uncertainties, respectively, are observed. This is not observed in theD(pT) distributions. In most pjet

T bins there is a slight decrease of the central values of RD(z) and RD(pT)with increasing z and pT; however the size of the effect is smaller than the systematic uncertainties.

13

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z 1−10 1

Sim

ulat

ion

/ dat

a

0.5

1

1.5 PYTHIA6 AUET2B CTEQ6L1

< 60 GeV jet

Tp45 <

ATLAS

-1 = 5.02 TeV, 25 pbs pp

z 1−10 1

Sim

ulat

ion

/ dat

a

PYTHIA8 A14 NNPDF23LO

< 80 GeV jet

Tp60 <

| < 1.6jet *y|

ATLAS

z 1−10 1

Sim

ulat

ion

/ dat

a

HERWIG++ UEEE5 CTEQ6L1

< 110 GeV jet

Tp80 <

ATLAS

z 2−10 1−10 1

Sim

ulat

ion

/ dat

a

0.5

1

1.5 PYTHIA6 AUET2B CTEQ6L1

< 160 GeV jet

Tp110 <

ATLAS

-1 = 5.02 TeV, 25 pbs pp

z 2−10 1−10 1

Sim

ulat

ion

/ dat

a

PYTHIA8 A14 NNPDF23LO

< 210 GeV jet

Tp160 <

| < 1.6jet *y|

ATLAS

z 2−10 1−10 1

Sim

ulat

ion

/ dat

a

HERWIG++ UEEE5 CTEQ6L1

< 260 GeV jet

Tp210 <

ATLAS

Figure 8: Ratios of the particle-level D(z) distributions from Pythia6, Pythia8, and Herwig++ to the unfolded ppdata for the six pjet

T intervals used in this analysis. The statistical uncertainties are shown as error bars and thesystematic uncertainties in the data are shown as the shaded region around unity. In many cases the statisticaluncertainties are smaller than the marker size.

z 1−10 1

The

ory

/ dat

a

0.5

1

1.5 < 60 GeV jet

Tp45 <

ATLAS

-1 = 5.02 TeV, 25 pbs pp

z 1−10 1

The

ory

/ dat

a

< 80 GeV jet

Tp60 <

| < 1.6jet *y|

ATLAS

z 1−10 1

The

ory

/ dat

a

Kang et al. Kaufmann et al.

< 110 GeV jet

Tp80 <

ATLAS

z 2−10 1−10 1

The

ory

/ dat

a

0.5

1

1.5 < 160 GeV jet

Tp110 <

ATLAS

-1 = 5.02 TeV, 25 pbs pp

z 2−10 1−10 1

The

ory

/ dat

a

< 210 GeV jet

Tp160 <

| < 1.6jet *y|

ATLAS

z 2−10 1−10 1

The

ory

/ dat

a

Kang et al. Kaufmann et al.

< 260 GeV jet

Tp210 <

ATLAS

Figure 9: Ratios of theoretical calculations from Refs. [50, 51] (solid points) and Ref. [52] (open points) to the un-folded pp D(z) distributions for the six pjet

T intervals used in this analysis. The statistical uncertainties are shown aserror bars and the systematic uncertainties in the data are shown as the shaded region around unity. The uncertaintiesin the theoretical calculations are not shown.

14

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z1−10 1

)z(

DR

0.6

0.8

1

1.2

1.4 < 60 GeV jet

Tp45 <

|<1.6jet *y|ATLAS

z1−10 1

)z(

DR

< 80 GeV jet

Tp60 <

ATLAS

, 0-90%-1 = 5.02 TeV, 28 nbNNs+Pb, p-1 = 5.02 TeV, 25 pbs , pp

z1−10 1

)z(

DR

< 110 GeV jet

Tp80 <

ATLAS

z2−10 1−10 1

)z(

DR

0.6

0.8

1

1.2

1.4 < 160 GeV jet

Tp110 <

|<1.6jet *y|ATLAS

z2−10 1−10 1

)z(

DR

< 210 GeV jet

Tp160 <

ATLAS

, 0-90%-1 = 5.02 TeV, 28 nbNNs+Pb, p-1 = 5.02 TeV, 25 pbs , pp

z2−10 1−10 1

)z(

DR

< 260 GeV jet

Tp210 <

ATLAS

Figure 10: Ratios of fragmentation functions as a function of the charged particle z in p+Pb collisions to those inpp collisions for the six pjet

T intervals. The statistical uncertainties are shown as error bars and the total systematicuncertainties are shown as shaded boxes.

[GeV] T

p1 10

)T

p(D

R

0.6

0.8

1

1.2

1.4 < 60 GeV jet

Tp45 <

|<1.6jet *y|ATLAS

[GeV] T

p1 10

)T

p(D

R

< 80 GeV jet

Tp60 <

ATLAS

, 0-90%-1 = 5.02 TeV, 28 nbNNs+Pb, p-1 = 5.02 TeV, 25 pbs , pp

[GeV] T

p1 10

)T

p(D

R

< 110 GeV jet

Tp80 <

ATLAS

[GeV] T

p1 10 210

)T

p(D

R

0.6

0.8

1

1.2

1.4 < 160 GeV jet

Tp110 <

|<1.6jet *y|ATLAS

[GeV] T

p1 10 210

)T

p(D

R

< 210 GeV jet

Tp160 <

ATLAS

, 0-90%-1 = 5.02 TeV, 28 nbNNs+Pb, p-1 = 5.02 TeV, 25 pbs , pp

[GeV] T

p1 10 210

)T

p(D

R

< 260 GeV jet

Tp210 <

ATLAS

Figure 11: Ratios of fragmentation functions as a function of the charged particle pT in p+Pb collisions to those inpp collisions for the six pjet

T intervals. The statistical uncertainties are shown as error bars and the total systematicuncertainties are shown as shaded boxes.

15

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8 Summary

This paper presents the first measurement of the jet charged-particle fragmentation functions in a p+Acollisions system. The jet charged-particle fragmentation functions are reported for |y∗jet| < 1.6 and pjet

Tfrom 45 to 260 GeV in √sNN = 5.02 TeV p+Pb and pp collisions with the ATLAS detector at the LHC.The measurement utilizes 28 nb−1 of p+Pb data and 26 pb−1 of pp data. The pp fragmentation func-tions are compared to predictions from the Pythia6, Pythia8 and Herwig++ generators. The generatorsshow deviations from the pp data of up to approximately 25%, depending on z and the choice of gen-erator. Pythia8 with the A14 tune and NNPDF23LO PDF set matches the data most closely. The ppD(z) distributions are also compared to two theoretical calculations based on next-to-leading-order QCDand DSS07 fragmentation functions. The calculations are systematically higher than the data and agreegenerally within 20–30%, with larger deviations at small and large values of z. These measurements helpconstrain jet fragmentation in pp collisions. The ratios of fragmentation functions in p+Pb collisions tothose in pp collisions show no evidence for modification of jet fragmentation in p+Pb collisions. Thismeasurement provides new constraints on the modifications to jets in p+Pb collisions at the LHC andis directly relevant to the current investigations into the properties of small collision systems. Finally,these measurements of jet fragmentation functions for different intervals of jet transverse momentumprovide necessary baseline measurements for quantifying the effects of the quark-gluon plasma in Pb+Pbcollisions.

16

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Acknowledgments

We thank CERN for the very successful operation of the LHC, as well as the support staff from ourinstitutions without whom ATLAS could not be operated efficiently.

We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFWand FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC andCFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia;MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS,CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC,Hong Kong SAR, China; ISF, I-CORE and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Ja-pan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal;MNE/IFA, Romania; MES of Russia and NRC KI, Russian Federation; JINR; MESTD, Serbia; MSSR,Slovakia; ARRS and MIZŠ, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wallen-berg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan;TAEK, Turkey; STFC, United Kingdom; DOE and NSF, United States of America. In addition, indi-vidual groups and members have received support from BCKDF, the Canada Council, CANARIE, CRC,Compute Canada, FQRNT, and the Ontario Innovation Trust, Canada; EPLANET, ERC, ERDF, FP7,Horizon 2020 and Marie Skłodowska-Curie Actions, European Union; Investissements d’Avenir Labexand Idex, ANR, Région Auvergne and Fondation Partager le Savoir, France; DFG and AvH Foundation,Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF;BSF, GIF and Minerva, Israel; BRF, Norway; CERCA Programme Generalitat de Catalunya, GeneralitatValenciana, Spain; the Royal Society and Leverhulme Trust, United Kingdom.

The crucial computing support from all WLCG partners is acknowledged gratefully, in particular fromCERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC(Taiwan), RAL (UK) and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resource pro-viders. Major contributors of computing resources are listed in Ref. [54].

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S. Shojaii66a, D.R. Shope124, S. Shrestha122, E. Shulga110, M.A. Shupe7, P. Sicho137, A.M. Sickles170,P.E. Sidebo151, E. Sideras Haddad32c, O. Sidiropoulou174, D. Sidorov125, A. Sidoti23b,23a, F. Siegert46,Dj. Sijacki16, J. Silva136a,136d, S.B. Silverstein43a, V. Simak138, L. Simic16, S. Simion128, E. Simioni97,B. Simmons92, M. Simon97, P. Sinervo164, N.B. Sinev127, M. Sioli23b,23a, G. Siragusa174, I. Siral103,S.Yu. Sivoklokov111, J. Sjölin43a,43b, M.B. Skinner87, P. Skubic124, M. Slater21, T. Slavicek138,M. Slawinska118, K. Sliwa167, R. Slovak139, V. Smakhtin177, B.H. Smart5, J. Smiesko28a, N. Smirnov110,S.Yu. Smirnov110, Y. Smirnov110, L.N. Smirnova111, O. Smirnova94, J.W. Smith51, M.N.K. Smith38,R.W. Smith38, M. Smizanska87, K. Smolek138, A.A. Snesarev108, I.M. Snyder127, S. Snyder29,R. Sobie173,ag, F. Socher46, A. Soffer158, D.A. Soh155, G. Sokhrannyi89, C.A. Solans Sanchez35,M. Solar138, E.Yu. Soldatov110, U. Soldevila171, A.A. Solodkov140, A. Soloshenko77,O.V. Solovyanov140, V. Solovyev134, P. Sommer50, H. Son167, H.Y. Song58a, A. Sopczak138, D. Sosa59b,C.L. Sotiropoulou69a,69b, R. Soualah64a,64c,k, A.M. Soukharev120b,120a, D. South44, B.C. Sowden91,S. Spagnolo65a,65b, M. Spalla69a,69b, M. Spangenberg175, F. Spanò91, D. Sperlich19, F. Spettel113,T.M. Spieker59a, R. Spighi23b, G. Spigo35, L.A. Spiller102, M. Spousta139, R.D. St. Denis55,*,A. Stabile66a,66b, R. Stamen59a, S. Stamm19, E. Stanecka82, R.W. Stanek6, C. Stanescu72a,M.M. Stanitzki44, S. Stapnes130, E.A. Starchenko140, G.H. Stark36, J. Stark56, S.H Stark39, P. Staroba137,P. Starovoitov59a, S. Stärz35, R. Staszewski82, P. Steinberg29, B. Stelzer149, H.J. Stelzer35,O. Stelzer-Chilton165a, H. Stenzel54, G.A. Stewart55, M.C. Stockton127, M. Stoebe101, G. Stoicea27b,P. Stolte51, S. Stonjek113, A.R. Stradling8, A. Straessner46, M.E. Stramaglia20, J. Strandberg151,S. Strandberg43a,43b, A. Strandlie130, M. Strauss124, P. Strizenec28b, R. Ströhmer174, D.M. Strom127,R. Stroynowski41, A. Strubig117, S.A. Stucci29, B. Stugu17, N.A. Styles44, D. Su150, J. Su135,S. Suchek59a, Y. Sugaya129, M. Suk138, V.V. Sulin108, S. Sultansoy4c, T. Sumida83, S. Sun57, X. Sun3,K. Suruliz153, C.J.E. Suster154, M.R. Sutton153, S. Suzuki79, M. Svatos137, M. Swiatlowski36,S.P. Swift2, I. Sykora28a, T. Sykora139, D. Ta50, K. Tackmann44,ac, J. Taenzer158, A. Taffard168,R. Tafirout165a, N. Taiblum158, H. Takai29, R. Takashima84, T. Takeshita147, Y. Takubo79, M. Talby99,A.A. Talyshev120b,120a, J. Tanaka160, M. Tanaka162, R. Tanaka128, S. Tanaka79, R. Tanioka80,B.B. Tannenwald122, S. Tapia Araya144b, S. Tapprogge97, S. Tarem157, G.F. Tartarelli66a, P. Tas139,M. Tasevsky137, T. Tashiro83, E. Tassi40b,40a, A. Tavares Delgado136a,136b, Y. Tayalati34e, A.C. Taylor116,G.N. Taylor102, P.T.E. Taylor102, W. Taylor165b, P. Teixeira-Dias91, D. Temple149, H. Ten Kate35,P.K. Teng155, J.J. Teoh129, F. Tepel179, S. Terada79, K. Terashi160, J. Terron96, S. Terzo14, M. Testa49,R.J. Teuscher164,ag, T. Theveneaux-Pelzer99, J.P. Thomas21, J. Thomas-Wilsker91, A.S. Thompson55,P.D. Thompson21, L.A. Thomsen180, E. Thomson133, M.J. Tibbetts18, R.E. Ticse Torres99,V.O. Tikhomirov108,ap, Yu.A. Tikhonov120b,120a, S. Timoshenko110, P. Tipton180, S. Tisserant99,K. Todome162, S. Todorova-Nova5, J. Tojo85, S. Tokár28a, K. Tokushuku79, E. Tolley57, L. Tomlinson98,M. Tomoto115, L. Tompkins150,s, K. Toms116, B. Tong57, P. Tornambe50, E. Torrence127, H. Torres149,E. Torró Pastor145, J. Toth99,ae, F. Touchard99, D.R. Tovey146, C.J. Treado121, T. Trefzger174,F. Tresoldi153, A. Tricoli29, I.M. Trigger165a, S. Trincaz-Duvoid132, M.F. Tripiana14, W. Trischuk164,B. Trocmé56, A. Trofymov44, C. Troncon66a, M. Trottier-McDonald18, M. Trovatelli173, L. Truong64a,64c,M. Trzebinski82, A. Trzupek82, K.W. Tsang61a, J.C-L. Tseng131, P.V. Tsiareshka105, G. Tsipolitis10,N. Tsirintanis9, S. Tsiskaridze14, V. Tsiskaridze50, E.G. Tskhadadze156a, K.M. Tsui61a,I.I. Tsukerman109, V. Tsulaia18, S. Tsuno79, D. Tsybychev152, Y. Tu61b, A. Tudorache27b,V. Tudorache27b, T.T. Tulbure27a, A.N. Tuna57, S.A. Tupputi23b,23a, S. Turchikhin77, D. Turgeman177,I. Turk Cakir4b,w, R. Turra66a, P.M. Tuts38, G. Ucchielli23b,23a, I. Ueda79, M. Ughetto43a,43b,F. Ukegawa166, G. Unal35, A. Undrus29, G. Unel168, F.C. Ungaro102, Y. Unno79, C. Unverdorben112,J. Urban28b, P. Urquijo102, P. Urrejola97, G. Usai8, J. Usui79, L. Vacavant99, V. Vacek138, B. Vachon101,C. Valderanis112, E. Valdes Santurio43a,43b, S. Valentinetti23b,23a, A. Valero171, L. Valéry14, S. Valkar139,A. Vallier5, J.A. Valls Ferrer171, W. Van Den Wollenberg118, H. Van der Graaf118, N. van Eldik157,

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P. Van Gemmeren6, J. Van Nieuwkoop149, I. Van Vulpen118, M.C. van Woerden118, M. Vanadia71a,71b,W. Vandelli35, R. Vanguri133, A. Vaniachine163, P. Vankov118, G. Vardanyan181, R. Vari70a,E.W. Varnes7, C. Varni53b,53a, T. Varol41, D. Varouchas128, A. Vartapetian8, K.E. Varvell154,G.A. Vasquez144b, J.G. Vasquez180, F. Vazeille37, T. Vazquez Schroeder101, J. Veatch51,V. Veeraraghavan7, L.M. Veloce164, F. Veloso136a,136c, S. Veneziano70a, A. Ventura65a,65b, M. Venturi173,N. Venturi164, A. Venturini26, V. Vercesi68a, M. Verducci72a,72b, W. Verkerke118, J.C. Vermeulen118,M.C. Vetterli149,ax, N. Viaux Maira144b, O. Viazlo94, I. Vichou170,*, T. Vickey146, O.E. Vickey Boeriu146,G.H.A. Viehhauser131, S. Viel18, L. Vigani131, M. Villa23b,23a, M. Villaplana Perez66a,66b, E. Vilucchi49,M.G. Vincter33, V.B. Vinogradov77, A. Vishwakarma44, C. Vittori23b,23a, I. Vivarelli153, S. Vlachos10,M. Vlasak138, M. Vogel179, P. Vokac138, G. Volpi69a,69b, H. von der Schmitt113, E. Von Toerne24,V. Vorobel139, K. Vorobev110, M. Vos171, R. Voss35, J.H. Vossebeld88, N. Vranjes16,M. Vranjes Milosavljevic16, V. Vrba138, M. Vreeswijk118, T. Šfiligoj89, R. Vuillermet35, I. Vukotic36,T. Ženiš28a, L. Živkovic16, P. Wagner24, W. Wagner179, J. Wagner-Kuhr112, H. Wahlberg86,S. Wahrmund46, J. Wakabayashi115, J. Walder87, R. Walker112, W. Walkowiak148, V. Wallangen43a,43b,C. Wang15c, C. Wang58b,f, F. Wang178, H. Wang18, H. Wang3, J. Wang154, J. Wang44, Q. Wang124,R. Wang6, S.M. Wang155, T. Wang38, W. Wang155,q, W.X. Wang58a,ah, Z. Wang58c, C. Wanotayaroj127,A. Warburton101, C.P. Ward31, D.R. Wardrope92, A. Washbrook48, P.M. Watkins21, A.T. Watson21,M.F. Watson21, G. Watts145, S. Watts98, B.M. Waugh92, A.F. Webb11, S. Webb97, M.S. Weber20,S.A. Weber33, S.W. Weber174, J.S. Webster6, A.R. Weidberg131, B. Weinert63, J. Weingarten51,C. Weiser50, H. Weits118, P.S. Wells35, T. Wenaus29, T. Wengler35, S. Wenig35, N. Wermes24,M.D. Werner76, P. Werner35, M. Wessels59a, K. Whalen127, N.L. Whallon145, A.M. Wharton87,A. White8, M.J. White1, R. White144b, D. Whiteson168, F.J. Wickens141, W. Wiedenmann178,M. Wielers141, C. Wiglesworth39, L.A.M. Wiik-Fuchs24, A. Wildauer113, F. Wilk98, H.G. Wilkens35,H.H. Williams133, S. Williams31, C. Willis104, S. Willocq100, J.A. Wilson21, I. Wingerter-Seez5,E. Winkels153, F. Winklmeier127, O.J. Winston153, B.T. Winter24, M. Wittgen150, M. Wobisch93,T.M.H. Wolf118, R. Wolff99, M.W. Wolter82, H. Wolters136a,136c, V.W.S. Wong172, S.D. Worm21,B.K. Wosiek82, J. Wotschack35, K.W. Wozniak82, M. Wu36, S.L. Wu178, X. Wu52, Y. Wu103,T.R. Wyatt98, B.M. Wynne48, S. Xella39, Z. Xi103, L. Xia15b, D. Xu15a, L. Xu29, B. Yabsley154,S. Yacoob32a, D. Yamaguchi162, Y. Yamaguchi129, A. Yamamoto79, S. Yamamoto160, T. Yamanaka160,K. Yamauchi115, Y. Yamazaki80, Z. Yan25, H.J. Yang58c,58d, H.T. Yang18, Y. Yang155, Z. Yang17,W-M. Yao18, Y.C. Yap132, Y. Yasu79, E. Yatsenko5, K.H. Yau Wong24, J. Ye41, S. Ye29, I. Yeletskikh77,E. Yigitbasi25, E. Yildirim97, K. Yorita176, K. Yoshihara133, C.J.S. Young35, C. Young150, D.R. Yu18,J. Yu8, J. Yu76, S.P.Y. Yuen24, I. Yusuff31,a, B. Zabinski82, G. Zacharis10, R. Zaidan14, A.M. Zaitsev140,ao,N. Zakharchuk44, J. Zalieckas17, A. Zaman152, S. Zambito57, D. Zanzi102, C. Zeitnitz179, M. Zeman138,A. Zemla81a, J.C. Zeng170, Q. Zeng150, O. Zenin140, D. Zerwas128, D. Zhang103, F. Zhang178,G. Zhang58a,ah, H. Zhang15c, J. Zhang6, L. Zhang50, L. Zhang58a, M. Zhang170, R. Zhang58a,f,R. Zhang24, X. Zhang58b, Y. Zhang15d, Z. Zhang128, X. Zhao41, Y. Zhao58b,128,ak, Z. Zhao58a,A. Zhemchugov77, J. Zhong131, B. Zhou103, C. Zhou178, L. Zhou41, M.S. Zhou15d, M. Zhou152,N. Zhou15b, C.G. Zhu58b, H. Zhu15a, J. Zhu103, Y. Zhu58a, X. Zhuang15a, K. Zhukov108, A. Zibell174,D. Zieminska63, N.I. Zimine77, C. Zimmermann97, S. Zimmermann50, Z. Zinonos113, M. Zinser97,M. Ziolkowski148, G. Zobernig178, A. Zoccoli23b,23a, R. Zou36, M. Zur Nedden19, L. Zwalinski35.

1Department of Physics, University of Adelaide, Adelaide; Australia.2Physics Department, SUNY Albany, Albany NY; United States of America.3Department of Physics, University of Alberta, Edmonton AB; Canada.4(a)Department of Physics, Ankara University, Ankara;(b)Istanbul Aydin University, Istanbul;(c)Divisionof Physics, TOBB University of Economics and Technology, Ankara; Turkey.

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5LAPP, Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS/IN2P3, Annecy; France.6High Energy Physics Division, Argonne National Laboratory, Argonne IL; United States of America.7Department of Physics, University of Arizona, Tucson AZ; United States of America.8Department of Physics, University of Texas at Arlington, Arlington TX; United States of America.9Physics Department, National and Kapodistrian University of Athens, Athens; Greece.10Physics Department, National Technical University of Athens, Zografou; Greece.11Department of Physics, University of Texas at Austin, Austin TX; United States of America.12(a)Bahcesehir University, Faculty of Engineering and Natural Sciences, Istanbul;(b)Istanbul BilgiUniversity, Faculty of Engineering and Natural Sciences, Istanbul;(c)Department of Physics, BogaziciUniversity, Istanbul;(d)Department of Physics Engineering, Gaziantep University, Gaziantep; Turkey.13Institute of Physics, Azerbaijan Academy of Sciences, Baku; Azerbaijan.14Institut de Física d’Altes Energies (IFAE), Barcelona Institute of Science and Technology, Barcelona;Spain.15(a)Institute of High Energy Physics, Chinese Academy of Sciences, Beijing;(b)Physics Department,Tsinghua University, Beijing;(c)Department of Physics, Nanjing University, Nanjing;(d)University ofChinese Academy of Science (UCAS), Beijing; China.16Institute of Physics, University of Belgrade, Belgrade; Serbia.17Department for Physics and Technology, University of Bergen, Bergen; Norway.18Physics Division, Lawrence Berkeley National Laboratory and University of California, Berkeley CA;United States of America.19Institut für Physik, Humboldt Universität zu Berlin, Berlin; Germany.20Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics, Universityof Bern, Bern; Switzerland.21School of Physics and Astronomy, University of Birmingham, Birmingham; United Kingdom.22Centro de Investigaciónes, Universidad Antonio Nariño, Bogota; Colombia.23(a)Dipartimento di Fisica e Astronomia, Università di Bologna, Bologna;(b)INFN Sezione di Bologna;Italy.24Physikalisches Institut, Universität Bonn, Bonn; Germany.25Department of Physics, Boston University, Boston MA; United States of America.26Department of Physics, Brandeis University, Waltham MA; United States of America.27(a)Transilvania University of Brasov, Brasov;(b)Horia Hulubei National Institute of Physics andNuclear Engineering, Bucharest;(c)Department of Physics, Alexandru Ioan Cuza University of Iasi,Iasi;(d)National Institute for Research and Development of Isotopic and Molecular Technologies, PhysicsDepartment, Cluj-Napoca;(e)University Politehnica Bucharest, Bucharest;( f )West University inTimisoara, Timisoara; Romania.28(a)Faculty of Mathematics, Physics and Informatics, Comenius University, Bratislava;(b)Department ofSubnuclear Physics, Institute of Experimental Physics of the Slovak Academy of Sciences, Kosice;Slovak Republic.29Physics Department, Brookhaven National Laboratory, Upton NY; United States of America.30Departamento de Física, Universidad de Buenos Aires, Buenos Aires; Argentina.31Cavendish Laboratory, University of Cambridge, Cambridge; United Kingdom.32(a)Department of Physics, University of Cape Town, Cape Town;(b)Department of MechanicalEngineering Science, University of Johannesburg, Johannesburg;(c)School of Physics, University of theWitwatersrand, Johannesburg; South Africa.33Department of Physics, Carleton University, Ottawa ON; Canada.34(a)Faculté des Sciences Ain Chock, Réseau Universitaire de Physique des Hautes Energies - UniversitéHassan II, Casablanca;(b)Centre National de l’Energie des Sciences Techniques Nucleaires (CNESTEN),

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Rabat;(c)Faculté des Sciences Semlalia, Université Cadi Ayyad, LPHEA-Marrakech;(d)Faculté desSciences, Université Mohamed Premier and LPTPM, Oujda;(e)Faculté des sciences, UniversitéMohammed V, Rabat; Morocco.35CERN, Geneva; Switzerland.36Enrico Fermi Institute, University of Chicago, Chicago IL; United States of America.37LPC, Université Clermont Auvergne, CNRS/IN2P3, Clermont-Ferrand; France.38Nevis Laboratory, Columbia University, Irvington NY; United States of America.39Niels Bohr Institute, University of Copenhagen, Copenhagen; Denmark.40(a)Dipartimento di Fisica, Università della Calabria, Rende;(b)INFN Gruppo Collegato di Cosenza,Laboratori Nazionali di Frascati; Italy.41Physics Department, Southern Methodist University, Dallas TX; United States of America.42Physics Department, University of Texas at Dallas, Richardson TX; United States of America.43(a)Department of Physics, Stockholm University;(b)Oskar Klein Centre, Stockholm; Sweden.44Deutsches Elektronen-Synchrotron DESY, Hamburg and Zeuthen; Germany.45Lehrstuhl für Experimentelle Physik IV, Technische Universität Dortmund, Dortmund; Germany.46Institut für Kern- und Teilchenphysik, Technische Universität Dresden, Dresden; Germany.47Department of Physics, Duke University, Durham NC; United States of America.48SUPA - School of Physics and Astronomy, University of Edinburgh, Edinburgh; United Kingdom.49INFN e Laboratori Nazionali di Frascati, Frascati; Italy.50Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg; Germany.51II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen; Germany.52Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève; Switzerland.53(a)Dipartimento di Fisica, Università di Genova, Genova;(b)INFN Sezione di Genova; Italy.54II. Physikalisches Institut, Justus-Liebig-Universität Giessen, Giessen; Germany.55SUPA - School of Physics and Astronomy, University of Glasgow, Glasgow; United Kingdom.56LPSC, Université Grenoble Alpes, CNRS/IN2P3, Grenoble INP, Grenoble; France.57Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge MA; United States ofAmerica.58(a)Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics,University of Science and Technology of China, Hefei;(b)Institute of Frontier and InterdisciplinaryScience and Key Laboratory of Particle Physics and Particle Irradiation (MOE), Shandong University,Qingdao;(c)School of Physics and Astronomy, Shanghai Jiao Tong University, KLPPAC-MoE, SKLPPC,Shanghai;(d)Tsung-Dao Lee Institute, Shanghai; China.59(a)Kirchhoff-Institut für Physik, Ruprecht-Karls-Universität Heidelberg, Heidelberg;(b)PhysikalischesInstitut, Ruprecht-Karls-Universität Heidelberg, Heidelberg;(c)ZITI Institut für technische Informatik,Ruprecht-Karls-Universität Heidelberg, Mannheim; Germany.60Faculty of Applied Information Science, Hiroshima Institute of Technology, Hiroshima; Japan.61(a)Department of Physics, Chinese University of Hong Kong, Shatin, N.T., Hong Kong;(b)Departmentof Physics, University of Hong Kong, Hong Kong;(c)Department of Physics and Institute for AdvancedStudy, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong;China.62Department of Physics, National Tsing Hua University, Hsinchu; Taiwan.63Department of Physics, Indiana University, Bloomington IN; United States of America.64(a)INFN Gruppo Collegato di Udine, Sezione di Trieste, Udine;(b)ICTP, Trieste;(c)Dipartimento diChimica, Fisica e Ambiente, Università di Udine, Udine; Italy.65(a)INFN Sezione di Lecce;(b)Dipartimento di Matematica e Fisica, Università del Salento, Lecce; Italy.66(a)INFN Sezione di Milano;(b)Dipartimento di Fisica, Università di Milano, Milano; Italy.

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67(a)INFN Sezione di Napoli;(b)Dipartimento di Fisica, Università di Napoli, Napoli; Italy.68(a)INFN Sezione di Pavia;(b)Dipartimento di Fisica, Università di Pavia, Pavia; Italy.69(a)INFN Sezione di Pisa;(b)Dipartimento di Fisica E. Fermi, Università di Pisa, Pisa; Italy.70(a)INFN Sezione di Roma;(b)Dipartimento di Fisica, Sapienza Università di Roma, Roma; Italy.71(a)INFN Sezione di Roma Tor Vergata;(b)Dipartimento di Fisica, Università di Roma Tor Vergata,Roma; Italy.72(a)INFN Sezione di Roma Tre;(b)Dipartimento di Matematica e Fisica, Università Roma Tre, Roma;Italy.73(a)INFN-TIFPA;(b)Università degli Studi di Trento, Trento; Italy.74Institut für Astro- und Teilchenphysik, Leopold-Franzens-Universität, Innsbruck; Austria.75University of Iowa, Iowa City IA; United States of America.76Department of Physics and Astronomy, Iowa State University, Ames IA; United States of America.77Joint Institute for Nuclear Research, Dubna; Russia.78(a)Departamento de Engenharia Elétrica, Universidade Federal de Juiz de Fora (UFJF), Juiz deFora;(b)Universidade Federal do Rio De Janeiro COPPE/EE/IF, Rio de Janeiro;(c)Universidade Federalde São João del Rei (UFSJ), São João del Rei;(d)Instituto de Física, Universidade de São Paulo, SãoPaulo; Brazil.79KEK, High Energy Accelerator Research Organization, Tsukuba; Japan.80Graduate School of Science, Kobe University, Kobe; Japan.81(a)AGH University of Science and Technology, Faculty of Physics and Applied Computer Science,Krakow;(b)Marian Smoluchowski Institute of Physics, Jagiellonian University, Krakow; Poland.82Institute of Nuclear Physics Polish Academy of Sciences, Krakow; Poland.83Faculty of Science, Kyoto University, Kyoto; Japan.84Kyoto University of Education, Kyoto; Japan.85Research Center for Advanced Particle Physics and Department of Physics, Kyushu University,Fukuoka ; Japan.86Instituto de Física La Plata, Universidad Nacional de La Plata and CONICET, La Plata; Argentina.87Physics Department, Lancaster University, Lancaster; United Kingdom.88Oliver Lodge Laboratory, University of Liverpool, Liverpool; United Kingdom.89Department of Experimental Particle Physics, Jožef Stefan Institute and Department of Physics,University of Ljubljana, Ljubljana; Slovenia.90School of Physics and Astronomy, Queen Mary University of London, London; United Kingdom.91Department of Physics, Royal Holloway University of London, Egham; United Kingdom.92Department of Physics and Astronomy, University College London, London; United Kingdom.93Louisiana Tech University, Ruston LA; United States of America.94Fysiska institutionen, Lunds universitet, Lund; Sweden.95Centre de Calcul de l’Institut National de Physique Nucléaire et de Physique des Particules (IN2P3),Villeurbanne; France.96Departamento de Física Teorica C-15 and CIAFF, Universidad Autónoma de Madrid, Madrid; Spain.97Institut für Physik, Universität Mainz, Mainz; Germany.98School of Physics and Astronomy, University of Manchester, Manchester; United Kingdom.99CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille; France.100Department of Physics, University of Massachusetts, Amherst MA; United States of America.101Department of Physics, McGill University, Montreal QC; Canada.102School of Physics, University of Melbourne, Victoria; Australia.103Department of Physics, University of Michigan, Ann Arbor MI; United States of America.104Department of Physics and Astronomy, Michigan State University, East Lansing MI; United States of

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America.105B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk; Belarus.106Research Institute for Nuclear Problems of Byelorussian State University, Minsk; Belarus.107Group of Particle Physics, University of Montreal, Montreal QC; Canada.108P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow; Russia.109Institute for Theoretical and Experimental Physics (ITEP), Moscow; Russia.110National Research Nuclear University MEPhI, Moscow; Russia.111D.V. Skobeltsyn Institute of Nuclear Physics, M.V. Lomonosov Moscow State University, Moscow;Russia.112Fakultät für Physik, Ludwig-Maximilians-Universität München, München; Germany.113Max-Planck-Institut für Physik (Werner-Heisenberg-Institut), München; Germany.114Nagasaki Institute of Applied Science, Nagasaki; Japan.115Graduate School of Science and Kobayashi-Maskawa Institute, Nagoya University, Nagoya; Japan.116Department of Physics and Astronomy, University of New Mexico, Albuquerque NM; United Statesof America.117Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef,Nijmegen; Netherlands.118Nikhef National Institute for Subatomic Physics and University of Amsterdam, Amsterdam;Netherlands.119Department of Physics, Northern Illinois University, DeKalb IL; United States of America.120(a)Budker Institute of Nuclear Physics, SB RAS, Novosibirsk;(b)Novosibirsk State UniversityNovosibirsk; Russia.121Department of Physics, New York University, New York NY; United States of America.122Ohio State University, Columbus OH; United States of America.123Faculty of Science, Okayama University, Okayama; Japan.124Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman OK;United States of America.125Department of Physics, Oklahoma State University, Stillwater OK; United States of America.126Palacký University, RCPTM, Joint Laboratory of Optics, Olomouc; Czech Republic.127Center for High Energy Physics, University of Oregon, Eugene OR; United States of America.128LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay; France.129Graduate School of Science, Osaka University, Osaka; Japan.130Department of Physics, University of Oslo, Oslo; Norway.131Department of Physics, Oxford University, Oxford; United Kingdom.132LPNHE, Sorbonne Université, Paris Diderot Sorbonne Paris Cité, CNRS/IN2P3, Paris; France.133Department of Physics, University of Pennsylvania, Philadelphia PA; United States of America.134Konstantinov Nuclear Physics Institute of National Research Centre "Kurchatov Institute", PNPI, St.Petersburg; Russia.135Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh PA; United States ofAmerica.136(a)Laboratório de Instrumentação e Física Experimental de Partículas - LIP;(b)Departamento deFísica, Faculdade de Ciências, Universidade de Lisboa, Lisboa;(c)Departamento de Física, Universidadede Coimbra, Coimbra;(d)Centro de Física Nuclear da Universidade de Lisboa, Lisboa;(e)Departamentode Física, Universidade do Minho, Braga;( f )Departamento de Física Teorica y del Cosmos, Universidadde Granada, Granada (Spain);(g)Dep Física and CEFITEC of Faculdade de Ciências e Tecnologia,Universidade Nova de Lisboa, Caparica; Portugal.137Institute of Physics, Academy of Sciences of the Czech Republic, Prague; Czech Republic.

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138Czech Technical University in Prague, Prague; Czech Republic.139Charles University, Faculty of Mathematics and Physics, Prague; Czech Republic.140State Research Center Institute for High Energy Physics, NRC KI, Protvino; Russia.141Particle Physics Department, Rutherford Appleton Laboratory, Didcot; United Kingdom.142IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette; France.143Santa Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz CA; UnitedStates of America.144(a)Departamento de Física, Pontificia Universidad Católica de Chile, Santiago;(b)Departamento deFísica, Universidad Técnica Federico Santa María, Valparaíso; Chile.145Department of Physics, University of Washington, Seattle WA; United States of America.146Department of Physics and Astronomy, University of Sheffield, Sheffield; United Kingdom.147Department of Physics, Shinshu University, Nagano; Japan.148Department Physik, Universität Siegen, Siegen; Germany.149Department of Physics, Simon Fraser University, Burnaby BC; Canada.150SLAC National Accelerator Laboratory, Stanford CA; United States of America.151Physics Department, Royal Institute of Technology, Stockholm; Sweden.152Departments of Physics and Astronomy, Stony Brook University, Stony Brook NY; United States ofAmerica.153Department of Physics and Astronomy, University of Sussex, Brighton; United Kingdom.154School of Physics, University of Sydney, Sydney; Australia.155Institute of Physics, Academia Sinica, Taipei; Taiwan.156(a)E. Andronikashvili Institute of Physics, Iv. Javakhishvili Tbilisi State University, Tbilisi;(b)HighEnergy Physics Institute, Tbilisi State University, Tbilisi; Georgia.157Department of Physics, Technion, Israel Institute of Technology, Haifa; Israel.158Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv University, Tel Aviv;Israel.159Department of Physics, Aristotle University of Thessaloniki, Thessaloniki; Greece.160International Center for Elementary Particle Physics and Department of Physics, University of Tokyo,Tokyo; Japan.161Graduate School of Science and Technology, Tokyo Metropolitan University, Tokyo; Japan.162Department of Physics, Tokyo Institute of Technology, Tokyo; Japan.163Tomsk State University, Tomsk; Russia.164Department of Physics, University of Toronto, Toronto ON; Canada.165(a)TRIUMF, Vancouver BC;(b)Department of Physics and Astronomy, York University, Toronto ON;Canada.166Division of Physics and Tomonaga Center for the History of the Universe, Faculty of Pure andApplied Sciences, University of Tsukuba, Tsukuba; Japan.167Department of Physics and Astronomy, Tufts University, Medford MA; United States of America.168Department of Physics and Astronomy, University of California Irvine, Irvine CA; United States ofAmerica.169Department of Physics and Astronomy, University of Uppsala, Uppsala; Sweden.170Department of Physics, University of Illinois, Urbana IL; United States of America.171Instituto de Física Corpuscular (IFIC), Centro Mixto Universidad de Valencia - CSIC, Valencia;Spain.172Department of Physics, University of British Columbia, Vancouver BC; Canada.173Department of Physics and Astronomy, University of Victoria, Victoria BC; Canada.174Fakultät für Physik und Astronomie, Julius-Maximilians-Universität Würzburg, Würzburg; Germany.

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175Department of Physics, University of Warwick, Coventry; United Kingdom.176Waseda University, Tokyo; Japan.177Department of Particle Physics, Weizmann Institute of Science, Rehovot; Israel.178Department of Physics, University of Wisconsin, Madison WI; United States of America.179Fakultät für Mathematik und Naturwissenschaften, Fachgruppe Physik, Bergische UniversitätWuppertal, Wuppertal; Germany.180Department of Physics, Yale University, New Haven CT; United States of America.181Yerevan Physics Institute, Yerevan; Armenia.a Also at Department of Physics, University of Malaya, Kuala Lumpur; Malaysia.b Also at Academia Sinica Grid Computing, Institute of Physics, Academia Sinica, Taipei; Taiwan.c Also at Borough of Manhattan Community College, City University of New York, NY; United Statesof America.d Also at Centre for High Performance Computing, CSIR Campus, Rosebank, Cape Town; South Africa.e Also at CERN, Geneva; Switzerland.f Also at CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille; France.g Also at Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève;Switzerland.h Also at Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona; Spain.i Also at Departamento de Física Teorica y del Cosmos, Universidad de Granada, Granada (Spain);Spain.j Also at Departamento de Física, Pontificia Universidad Católica de Chile, Santiago; Chile.k Also at Department of Applied Physics and Astronomy, University of Sharjah, Sharjah; United ArabEmirates.l Also at Department of Financial and Management Engineering, University of the Aegean, Chios;Greece.m Also at Department of Physics and Astronomy, University of Louisville, Louisville, KY; United Statesof America.n Also at Department of Physics, California State University, Fresno CA; United States of America.o Also at Department of Physics, California State University, Sacramento CA; United States of America.p Also at Department of Physics, King’s College London, London; United Kingdom.q Also at Department of Physics, Nanjing University, Nanjing; China.r Also at Department of Physics, St. Petersburg State Polytechnical University, St. Petersburg; Russia.s Also at Department of Physics, Stanford University; United States of America.t Also at Department of Physics, University of Fribourg, Fribourg; Switzerland.u Also at Department of Physics, University of Michigan, Ann Arbor MI; United States of America.v Also at Dipartimento di Fisica E. Fermi, Università di Pisa, Pisa; Italy.w Also at Giresun University, Faculty of Engineering, Giresun; Turkey.x Also at Graduate School of Science, Osaka University, Osaka; Japan.y Also at Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest; Romania.z Also at II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen; Germany.aa Also at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona; Spain.ab Also at Institut de Física d’Altes Energies (IFAE), Barcelona Institute of Science and Technology,Barcelona; Spain.ac Also at Institut für Experimentalphysik, Universität Hamburg, Hamburg; Germany.ad Also at Institute for Mathematics, Astrophysics and Particle Physics, Radboud UniversityNijmegen/Nikhef, Nijmegen; Netherlands.ae Also at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest;

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Hungary.a f Also at Institute of Frontier and Interdisciplinary Science and Key Laboratory of Particle Physics andParticle Irradiation (MOE), Shandong University, Qingdao; China.ag Also at Institute of Particle Physics (IPP); Canada.ah Also at Institute of Physics, Academia Sinica, Taipei; Taiwan.ai Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku; Azerbaijan.a j Also at Institute of Theoretical Physics, Ilia State University, Tbilisi; Georgia.ak Also at LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay; France.al Also at Louisiana Tech University, Ruston LA; United States of America.am Also at LPNHE, Sorbonne Université, Paris Diderot Sorbonne Paris Cité, CNRS/IN2P3, Paris;France.an Also at Manhattan College, New York NY; United States of America.ao Also at Moscow Institute of Physics and Technology State University, Dolgoprudny; Russia.ap Also at National Research Nuclear University MEPhI, Moscow; Russia.aq Also at Novosibirsk State University, Novosibirsk; Russia.ar Also at Ochadai Academic Production, Ochanomizu University, Tokyo; Japan.as Also at Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg; Germany.at Also at School of Physics, Sun Yat-sen University, Guangzhou; China.au Also at The City College of New York, New York NY; United States of America.av Also at The Collaborative Innovation Center of Quantum Matter (CICQM), Beijing; China.aw Also at Tomsk State University, Tomsk, and Moscow Institute of Physics and Technology StateUniversity, Dolgoprudny; Russia.ax Also at TRIUMF, Vancouver BC; Canada.ay Also at Universita di Napoli Parthenope, Napoli; Italy.∗ Deceased

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