KS0- and (anti-)Λ-hadron correlations in pp collisions at √s = 13 TeV

This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. Author(s): Title: Year: Version: Copyright: Rights: Rights url: Please cite the original version: CC BY 4.0 https://creativecommons.org/licenses/by/4.0/ KS0and (anti-)Λ-hadron correlations in pp collisions at √s = 13 TeV © 2021 the Authors Published version ALICE Collaboration ALICE Collaboration. (2021). KS0and (anti-)Λ-hadron correlations in pp collisions at √s = 13 TeV. European Physical Journal C, 81(10), Article 945. https://doi.org/10.1140/epjc/s10052-02109678-5 2021 Eur. Phys. J. C (2021) 81:945 https://doi.org/10.1140/epjc/s10052-021-09678-5 Regular Article - Experimental Physics KS0and (anti-)-hadron correlations in pp collisions at √s=13 TeV ALICE Collaboration CERN, 1211 Geneva 23, Switzerland Received: 4 August 2021 / Accepted: 21 September 2021 © CERN for the benefit of the ALICE collaboration 2021 Abstract Two-particle Azimuthal correlations are measured with the ALICE apparatus in pp collisions at √s=13 TeV to explore strangenessand multiplicity-related effects in the fragmentation of jets and the transition regime between bulk and hard production, probed with the condition that a strange meson (KS0) or baryon () with transverse momentum pT>3GeV/cis produced. Azimuthal correlations between kaons or hyperons with other hadrons are presented at midrapidity for a broad range of the trigger (3 < ptrigg T<20 GeV/c) and associated particle pT(1 GeV/c <passoc T<ptrigg T), for minimum-bias events and as a function of the event multiplicity. The nearand away-side peak yields are compared for the case of either KS0or () being the trigger particle with that of inclusive hadrons (a sample dominated by pions). In addition, the measurements are compared with predictions from PYTHIA 8 and EPOS LHC event generators. 1 Introduction Particleproductionas afunction ofthe eventcharged-particle multiplicity in proton–proton (pp) collisions at the LHC has revealed interesting patterns. Clearly, in the soft (bulk) particleproductiondomainwithlowtransversemomentum(pT 4GeV/c), several experimental measurements indicate features in high-multiplicity pp collisions similar to those observed in nucleus–nucleus collisions. These include longrange correlations in pseudorapidity [1,2], large azimuthal anisotropies [3,4] and strangeness production [5,6]. These measurements are theoretically interpreted in terms of a combination of initial-state collective dynamics (colourglass condensate) [7] or as a hydrodynamic-like (final-state) collective flow [8]. Quantifying the relative contributions of initialand final-state phenomena is a challenge, both experSee Appendix A for the list of collaboration members. e-mail: [email protected] imentally and theoretically (see reviews [9,10]). These phenomena are also modelled in Monte Carlo (MC) event generators, like PYTHIA8 [11]orEPOSLHC[12]. For example, a basic experimental finding in pp collisions, the increase of the average transverse momentum with the event multiplicity is realized in these two models very differently. In PYTHIA 8, in events with several partonic scatterings, termed Multiple Parton Interactions (MPI), the respective color strings cut (reconnect) each other, leading to a redistribution of energy from particle production to transverse momentum. In the EPOS LHC model, a parametrised hydrodynamic evolution of a small volume with high density of thermalised matter (core) is used. In both models the respective parameters were tuned using the Run 1 data at the LHC, without explicit inclusion of particle correlations [12,13]. In PYTHIA8, correlations among the final state hadrons are realized through transversely extended strings, exerting on each other transverse shoves [14] that mimic collective dynamics,akintothatof a(long-lived)quark–gluonmedium. The shoving model of hadronisation was recently used to discern within a PYTHIA8 study [15] possible effects of jet quenching in pp collisions. This prominent characteristic of nucleus–nucleus collisions, remains undetected in highmultiplicity pp or p–Pb collisions [16], perhaps not surprisingly, given the much smaller spatial extension of the dense system, compared to the nucleus–nucleus case. Experimentally, it was recently shown that in pp collisions the near-side long-range (in pseudorapidity) ridge yield (of bulk particles) in high-multiplicity events remains present for events which are additionally biased, through either a Zboson [17], a leading high-pTparticle or a jet [18]. These findings are interesting per se and also motivate the quest to find or exclude jet quenching in high-multiplicity events in small collision systems, with differences in the observed effects on gluon, light and heavy quark jets. At LEP, differences between quarkand gluon-initiated jets in e+–e−annihilations have been revealed in several measurements. Gluon jets are characterised by a larger charged-particle multiplicity than quark jets [19,20]. More0123456789().: V,-vol 123 945 Page 2 of 21 Eur. Phys. J. C (2021) 81:945 over, in the relative production of KS0mesons and hyperons to charged particles, it was found that the relative production of is ≈30% higher in gluon than in quark jets, while the relative KS0production was found to be approximately the same [21]. In the present article, such studies of particle production andcorrelationsare continued, exploring theeffectofa strangeness bias, both in form of a meson (KS0) or a baryon () with pT>3GeV/c. Thecorrelationsbetweenkaonsor() hyperons with other hadrons are studied at midrapidity in pp collisions at √s=13 TeV for a broad range of the trigger (3 <ptrigg T<20 GeV/c)andassociated particle pT(1GeV/c <passoc T<ptrigg T),forminimumbiaseventsand asafunction of the event multiplicity measured at forward rapidities. Such correlations encode effects of fragmentation, hadronisation and parton showering as well as possible collectivity and jet quenching. The complex overlap of these aspects is probed through the experimental handles of particle species and pT, inducing different kinematic and flavour biases. The nearand away-side peak yields are compared for the case of either KS0or (anti-)as a trigger particle with that of inclusive hadrons (a sample dominated by pions). The measurements are, in addition, compared with the PYTHIA 8 and EPOS LHC event generators. The article is organised as follows: Sect. 2outlines the experimental setup and the data sample; Sect. 3describes the analysis, while Sect. 4presents the results; a summary and an outlook are given in Sect. 5. 2 Experiment and data sample The inclusive charged hadron, KS0meson and (anti-) hyperon identification at midrapidity is performed using the tracking detectors of the ALICE central barrel located in a solenoidal magnet, which provides a magnetic field of 0.5 T oriented along the beam direction. A detailed description of the ALICE experiment and its performance can be found in [22,23]. 2.1 Event selection For the data taking, a minimum bias (MB) trigger is employed, provided by the V0 detector, which consists of two forward scintillator arrays covering the pseudorapidity ranges −3.7<η<−1.7 and 2.8<η<5.1. The MB trigger signal consists of a coincident signal in both arrays. All events selected in this analysis are required to have a reconstructed primary collision vertex (PV) within the longitudinal interval |zvtx|<10 cm from the nominal interaction point in order to ensure uniform detector performance. Beam-gas events are rejected using timing cuts with the V0 Table 1 Selection criteria for V0candidates based on the topological variables Selection criterion K0 S() Absolute value of rapidity <0.5<0.5 Decay radius (cm) >0.5>0.5 DCAxy of daughter track to PV (cm) >0.06 >0.06 DCAxy between daughter tracks (nσ)<1<1 cos(θPA )>0.97 >0.995 Proper lifetime (cm) <20 <30 Competing rejection (GeV/c2)>0.005 >0.01 Invariant mass (GeV/c2)m0 KS±3σm() ±3σ detector. Moreover pile-up events are rejected based on the Silicon Pixel Detector (SPD) information. The total number of analysed pp collisions at √s=13 TeV, measured during the LHC Run 2 data-taking period in years 2016–2018 by ALICE is 1.58×109corresponding to integrated luminosity of about 27 nb−1. 2.2 Multiplicity selection The correlation functions are calculated for six event classes (0–1%, 1–3%, 3–7%, 7–15%, 15–50%, 50–100%), selected on the event activity via the multiplicity in the forward and backwarddirection,measuredwiththeV0detectorwithinthe acceptance described above. The events are selected based on percentiles of the summed signal in the two V0 detectors (V0M), for instance the 0–1% and 50–100% classes are the events with the highest and lowest range of the V0M signal. The trigger efficiency is not accounted for in the above multiplicity ranges. The intervals corrected for the trigger efficiencyare:respectively;0–0.92%,0.92–2.74%,2.74–6.40%, 6.40–13.44%, 13.44–46.12%, 46.12–100% [24]. For the MC event generators, the multiplicity classes are selected with the trigger-corrected percentile calculation, applied to the distribution of charged primary particles produced in the ηacceptance of the V0 detectors. 2.3 Primary hadron and V0selection Primary charged tracks (denoted as h) are reconstructed in the pseudorapidity range |η|<0.8 using the Inner Tracking System (ITS), which consists of six layers of silicon detectors around the beam pipe, and the Time Projection Chamber (TPC), consisting of a large cylindrical drift volume filled with nearly 90m3either of Ar/CO2(88/12, in 2016 and 2018) or Ne/CO2/N2(90/10/5 in 2017) and read out by multi-wire proportional chambers. Combining the information from these two detectors, the primary charged-track sample is created by applying selection criteria in order to 123 Eur. Phys. J. C (2021) 81:945 Page 3 of 21 945 suppress the contamination from secondary particles following previous studies [25]. The number of crossed pad rows in the TPC is required to be at least 70 (out of a maximum of 159) and the minimal ratio to the number of findable clusters (geometrically possible assignable clusters to a track) is 0.8. Only tracks with a fraction of shared clusters with other tracks smaller than 0.4 are accepted. The distance of closest approach (DCA) to the PV is required to be within an elipsoid with semi-axes of 2.4 cm and 3.2 cm in the xy-plane and z-direction, respectively. Every track is required to have a fit quality for both TPC and ITS, characterised by goodness-offit values χ2per cluster smaller than 4 and 36 for the TPC and ITS, respectively. Only tracks with a hit in the two most inner layers of ITS are selected. The kink topologies produced by decays are rejected. The selected sample of primary charged particles is dominated by hadrons. The electrons constitute less than 1%. The K0 Smesons and () baryons (V0particles) are reconstructed in the rapidity range |y|<0.5 via their most probable decay channels [26] and exploiting their characteristic (V0) decay topology: KS0→π++π−(69.2%), →p+π−(63.9%), →p+π+(63.9%). The identification and reconstruction follows previous measurements presented in [27,28]. The identification of the daughter tracks is performed via specific energy loss dE/dx in the TPC, which is required to be within ±3σfrom the expected mean value for pions or protons (for more details see [23]). The track quality criteria are the same as for the primary global tracks described above. The pairs of identified daughter tracks are combined to V0candidates, which are accepted if their invariant mass is within 3σ(1σfor KS0 is in the range 0.0039–0.0075 GeV/c2and for in 0.0021– 0.0033 GeV/c2depending on pT) from the nominal value. The combinatorial contribution is suppressed by applying selection criteria based on the topological variables summarisedinTable1. Here, the V0decay radius is the distance between the point where the V0decays (secondary vertex) and the PV. The DCAxy to PV is the distance of closest approach between the daughter track and the PV. The θPA refers to the pointing angle, which is the angle between the momentum vector of the V0candidate and the line connecting the primary and secondary vertex. The reconstructed proper lifetime of an individual particle is defined as mL/p, where mis the particle mass, Lis the distance between primary and secondary vertex and pis the particle momentum. The mean life cτis listed in [26] and its value is 2.68 cm and 7.89 cm for KS0and (), respectively. It can happen that a certain pair reconstructed as K0 Scandidate can have an invariant mass of () under the pπassumption for the daughter tracks. Such pairs are not accepted neither as KS0 nor as () candidates. Table 1quotes under the competing rejection entry the mass on which this criterion is applied for both KS0and . Besides the topological selections, a bunchoff pile-up (by the high frequency collisions, some tracks from previous bunch-crossing remain in TPC when current collision happen) removal criterion is required where at least one of the V0daughter tracks is reconstructed both in ITS and TPC or has a signal in the Time-Of-Flight detector. 3 Analysis 3.1 The correlation function In the dihadron correlation approach, the first hadron is the trigger particle, here either a primary charged particle (hadron) or an identified KS0meson or () hyperon with pTin range 3–20 GeV/c. Since the –h and –h correlation functions are compatible, as expected for this collision energy,theresultsarecombinedandreportedinthefollowing as ( +)–h. The second particle is the associated particle, in this case, always a primary charged particle with a kinematic requirement 1 GeV/c<passoc T<ptrigg T. By calculating the differences in the azimuthal angle and pseudorapidity for each of such pairs, three types of correlation functions are constructed: h–h, KS0-h and ( +)–h. For h–h correlations, pairs with invariant mass (IM) within ±5MeV/c2 of the mass of KS0or ()orfromγconversions are not accepted. The contribution from decays of the K∗(892) and φmesons, resonances and D mesons was checked and found negligible. In the case of ( +)–h correlations, this restriction is applied to pairs with IM of a cascade (,,). An example of a raw KS0–h correlation function is shown in Fig. 1(left panel). At (ϕ, η) =(0,0), one can observe the near-side peak, which originates mostly from particle pairs fragmented within the same jet. Bose-Einstein correlations, strong decays of high-mass resonances and final state interactions may have also a small contribution for the hh case. Due to momentum conservation, jets are produced back-to-back in the transverse plane. Thus, a second peak around πin ϕ is expected, which is smeared in the η direction, because the particles can obtain an additional longitudinal boost related to the varied center-of-mass frame of the partonic collision. In the selection of the trigger particle, the near-side jet is fully reconstructed in the longitudinal direction, but the away-side jet is not necessarily (fully) withinthedetectoracceptance.Theprocedureofgettingfully corrected 2-dimensional per-trigger yield is schematically written in Eq. 1. Here, d2Nraw pair dϕdη (ϕ, η) is the uncorrected correlation function, εtrigg,εassoc and εpair are correction factors further described in Sect. 3.2 and Ntrigg is the number 123 945 Page 4 of 21 Eur. Phys. J. C (2021) 81:945 1 −0.5−00.5 1 η Δ 1− 0 1 2 3 4 ϕ Δ 0 10 20 30 40 50 60 1000 1 ϕΔ dηΔd assoc N 2 d ALICE =13 TeVs pp, -h correlations 0 S K 1−0.5 −00.5 1 η Δ 1 − 0 1 2 3 4 ϕ Δ 0 0.2 0.4 0.6 0.8 1 1−0.5 −00.5 1 η Δ 1 − 0 1 2 3 4 ϕ Δ 20 30 40 50 60 1000 1 ϕΔ dηΔd assoc N 2 d c < 4 GeV/ trigg T p3 < trigg T p < assoc T p < c1 GeV/ Fig. 1 An example of the raw same-event (left), mixed-event (middle) and final (mixed-event scaled, right) two-dimensional correlation function for KS0-hadrons. The correlation functions were scaled with 1/1000 for better visibility. The plateau in the left and middle plot is caused by non-equal selection in ηof the trigger and associated particle of the trigger particles. Afterwards, the 2-dimensional pertrigger yield is projected on the ϕ axis and integrated (see Eq. 2) in the intervals |ϕ|<0.9 and |ϕ −π|<1.4 to obtain the near-side and away-side yield, respectively, denoted as Yϕ in Eq. 2. d2Npair dϕdη (ϕ, η) =1 Ntrigg 1 εtrigg 1 εassoc d2Nraw pair dϕdη (ϕ, η) 1 εpair (1) Yϕ =ϕ2 ϕ1 dN dϕ dϕ (2) 3.2 Corrections The corrections are described in the same order as they were applied to the data. All MC-based corrections are calculated using events from PYTHIA8.210 (Monash 2013 tune) [13,29], with particle propagation through the detector by means of GEANT3 [30]. The detection inefficiencies are corrected with the single particle efficiency factor, calculated in MC and applied as weight (1/εtrigg ×1/εassoc) for each pair. This factor was calculated separately for trigger and associated particles as afunctionofpT,η,ϕand PV position. In the case of primary charged particles, a pT-dependent contamination factor is also part of the weight to account for the amount of secondary particles in the sample. This is defined as a ratio of only primary tracks to all reconstructed ones. Imperfect detector acceptance within |η|<0.8 range is corrected with the mixed-event method, where trigger particles from one event are correlated with associated particles from different events. Thus, no physical correlations are present. The mixed-event correlation function has a typical triangularshape determinedby theηacceptance.Anexample of this function is shown in the middle plot of Fig. 1where a plateau is visible. This is caused by different ranges in ηfor trigger (KS0) and associated particles (h). The mixed-event correlation is already scaled to unity with a scaling factor equal to the average of bins with η = 0. In the following, the actual correlation function is divided by the mixed-event one to eliminate the detector acceptance effects as illustrated in Fig. 1. This correction is schematically written as 1/εpair in Eq. 1. In some cases, due to the finite binning in multiplicity and PV position in z-direction, the mixed-event correlation does not match the shape of the background perfectly. For this reason, a so called “wing“ correction is performed. Here the correlation function is scaled once more with a 2D distribution constant in ϕ and dependent on η in order to get a flat distribution in η at the away-side. This correction is never larger than 2% and only affects the h-h correlation function. A similar effect was observed also in a previous analysis [31]. For the reconstruction of KS0mesons and () baryons, some of the candidates selected with the topological criteria are in fact combinatorial background. Since the shape of the correlation function does not need to be the same for the signal and background, a second correlation function is calculated,wherecandidatesfromtwointervalsfromoutsidethe invariant mass peak (mV0−9σto mV0−6σand mV0+6σto mV0+9σ) are taken as trigger particles. These give the same width as the signal region in the invariant mass spectrum. The second “side-band“ correlation function is subtracted from the signal one. The number of trigger particles is in addition corrected for purity, defined as a ratio of number of signal 123 Eur. Phys. J. C (2021) 81:945 Page 5 of 21 945 Table 2 Summary of the main sources and values of the relative systematic uncertainties (expressed in %) for the per-trigger yields in the MBsample.Theabbreviation“negl.“standsfornegligible (smaller than 0.1%)and“rej.“meansthatthisvariation wasrejectedduetothe Barlow criterion h-h K0 S-h ()-h Near Away Near Away Near Away ϕ window 0.3 0.4 0.5 0.7 0.7 0.5 PV along the z-axis (zvtx) Negl. Negl. 1.2 1.7 0.6 0.7 Binning in zvtx Negl. 0.4 0.8 1.6 0.5 1.2 Yield calculation 1.0 Negl. 1.1 0.7 0.3 0.4 Pedestal subtraction 0.8 1.9 0.4 1.6 1.0 2.0 η range 0.5 – 1.2 – 1.0 – Mixing scale Negl. Negl. 0.7 0.9 0.3 0.5 Topological variables – – 1.5 3.5 3.0 3.1 Invariant mass range – – Rej. Rej. 1.2 1.8 Primary track selection 0.3 0.7 1.1 1.8 2.2 0.4 Wing correction 1.2 1.8 – – 0.7 0.8 topological variables – – – – 0.4 1.6 MC closure Negl. Negl. Negl. Negl. 2.5 Negl. Total 1.9 2.7 3.1 5.1 5.1 4.8 V0candidates over all candidates within the invariant mass acceptance region. In the case of () being the trigger particle, the feeddown contribution from decays of baryons (reconstructed following[6])baryonsissubtractedinasimilarwayasforthe combinatorial background. For this case, the (−++)-h correlation function in every pTand multiplicity bin is calculated, scaled with the detection efficiency of ()from decays and subtracted from the ( +)-h correlation function. Similarly, the feed-down fraction is subtracted from the number of trigger particles. It is assumed that the production rates of charged and neutral baryons are equal and the feed-down fraction from is negligible. This correction has an effect of 5% on the final near-side yields for low pTand smaller than 1% for high pT. After projecting the per-trigger yield on the ϕ axis, the underlying event background is subtracted with the ZYAM (Zero Yield At Minimum) method [32]. The background is assumed to be flat and estimated as the average value of six bins outside the jet peaks to reduce the statistical fluctuations. 3.3 Systematic uncertainties The sources of systematic uncertainties of the per-trigger yields in the minimum bias sample are listed in Table 2. These are estimated by varying track-selection criteria and other parameters in the analysis. The significance of each source of systematic uncertainty was checked according to the Barlow criterion [33]. Within this procedure a threshold value (1 σ) is set, based on which each variation can be checked, whether it is within statistical fluctuations or a real systematic difference. If a certain variation did not pass the test, this contribution was not accounted for in the total systematic uncertainty, which was calculated as a quadrature sum of the individual contributions. For the ratios of yields, the systematic uncertainties are calculated separately which causes cancellation of correlated uncertainties. For the uncertainty related to the ϕ integration window, the window is varied around the nominal values (|ϕ|<0.9 and |ϕ −π|<1.4) within ±0.1. For the yields for the h-h correlations, on both nearand away-side, the contribution to the total uncertainty is around 0.4% for all multiplicity classes. For the yields for KS0-h and (+)-h correlations, the value varies within 0.4–2% for both nearand away-side. The PV selection along the z-axis (zvtx) is decreased from ±10 cm to ±7 cm from the interaction point in order to estimate the uncertainty connected to the detector acceptance effects. The uncertainty is smaller than 0.3% in all multiplicity classes for the yields from h-h correlation function. It is in the range 0.7–2.3% and 0.7–2.7% for the near-side yield in case of KS0-h and ( +)-h yields, respectively. For the away-side, this source contributes with 1.7–4.5% and 0.7–4.9%incaseofKS0-hand(+)-hyields,respectively. The number of bins in zvtx used for the event-mixing classes is changed from 9 to 7 to account for the uncertainty connected with the detector acceptance. For the yields triggered with an unidentified hadron, the contribution from this source is smaller than 0.5% at both sides for all multiplicity classes. This uncertainty is in the range 0.5–2.7% and 0.4– 1.5% for the near-side yield triggered with KS0and (+), 123 945 Page 6 of 21 Eur. Phys. J. C (2021) 81:945 respectivelyandwithin1.2–5.2%and0.8–2.8%fortheawayside. The contribution to the systematic uncertainty resulting from the yield calculation method is estimated by fitting each jet peak with a double-gaussian function and integrating the fit function to calculate the per-trigger yield instead of calculatingtheyielddirectlybythebincountingmethodasdefault. This leads to an uncertainty around 1% for the near-side and to a value smaller than 0.2% for the away-side for the h-h yieldsinallmultiplicityclasses. For mostmultiplicity classes this source was rejected by the Barlow criterion for the KS0 trigger. The non-rejected contribution is 1.1% and 0.7% for the nearand away-side, respectively. The accounted contribution to the uncertainty of yields triggered with ( +) is in the range 0.3–0.8% and 0.2–3.4% for the near-side and away-side yields, respectively. For the variation of the underlying event subtraction method, which takes the average value of 6 bins from the left and right side of the near-side peak, a constant fit in ranges [−π/2,−1]and [1,π/2]is used, leading to an estimated uncertainty around 0.6% (1.5%), 2% (2.2%) and 1.8% (4.5%) for the near- (away- ) side yield from the unidentified hadron-, KS0-, and ( +)-triggered correlation functions, respectively. Theη range isvariedwithin0.1 arounditsnominalvalue |η|<1 in order to estimate the uncertainty related to the near-side jet acceptance. This is estimated to be within 0.3– 0.9%, 0.6–1.9%, 0.4–2.4% for h–h, KS0–h and ( +)–h yields in all multiplicity classes, respectively. The scale factor for the mixed-event correlation function is varied, which gives a negligible contribution to the total systematic uncertainty for h–h yields for both sides. This contribution for KS0–h (( +)–h) yields is estimated as 0.7–1.5% (0.2–0.4%) and 0.9–2% (0.2–0.5%) for the near and away-side yields, respectively, in different multiplicity classes. In order to estimate the systematic uncertainty connected to the V0reconstruction, the values for the topological selection are varied around the nominal values. Its value is, for different multiplicity classes, in the range 1.5–5.8% (1.9–5.6%) and 2.2–7.5% (2–5.5%) for the KS0(+) triggered yields at the nearand away-side, respectively. The ranges for the signal and for background in the invariant mass distributions are varied in order to estimate the uncertainty related to the subtraction of the contribution from misidentified KS0or ( +). This source is rejected by the Barlow criterion for the KS0–h yields and has a value in therange0.5–3.9%and1.1–4.3%forthe(+)–htriggered yields, for the nearand away-side, respectively. The systematic uncertainty associated with the primary track selections is estimated by selecting tracks with slightly varied criteria. These are the same as the ones used for global tracks, but there is a tighter and pT-dependent DCA requirement in the xy-plane, which means that tracks with a DCA in the xy-plane larger than 0.0105 +0.0350/p1.1 Tare rejected. This uncertainty is smaller than 0.7% for both the nearand away-side yield for h–h for all multiplicity classes. The uncertainty intervals for KS0(( +)) triggered yields are estimated as 0.9–2.4% (0.4–3.5%) and 1.3–3.9% (0.2–3.1%) for the nearand away-side yields, respectively. The range used for the estimation of the wing correction scaling factor is varied in order to calculate the uncertainty related to this method. This contribution is not dependent on the event multiplicity. The −(+)reconstruction uncertainty contributes to the uncertainty of yields triggered by (+). This contribution is estimated by varying the topological selection of −(¯ +) hyperons around their nominal values. This uncertainty is in the range 0.2–4% (0.2–3.9%) for the near(away)-side yields for events in all multiplicity classes. The correction procedure is checked with a Monte Carlo closuretest.Twocorrelationfunctionsarecalculated,the first onewithgenerated MCparticlesand thesecondone withMC particles reconstructed after GEANT3 propagation using the full reconstruction and correction chain as for the experimental data. The ratio of these two correlation functions is expected to be unity. This is the case for the h–h and KS0–h correlation functions, but there is a residual departure from unity for ( +)–h correlation function at the near-side of up to 2.5%, which is accounted as a systematic uncertainty. 4 Results and discussion The ϕ projections of the correlation functions for the three different trigger particles are shown for two ptrigg Tintervals, 3<ptrigg T<4GeV/cand 9 <ptrigg T<11 GeV/c,inFig.2. Included are also the correlation functions predicted by MC event generators widely used by the LHC collaborations: PYTHIA8 with the standard Monash tune, which includes colour re-connection as final-state effects [13], PYTHIA8 Monash tune with shoving [14] and EPOS LHC [12]. It is importanttonotethatthePYTHIA8MonashandEPOSLHC tunings were based on single-particle spectra and underlying event observables, but did not include particle correlations in azimuth. The shoving strength parameter g is here set to g = 3 and in addition the upper pTcut for the shoving mechanism is turned off. None of the models describes quantitatively the correlation functions consistently for the three trigger particle species. For the low ptrigg T, both PYTHIA8 tunes overestimate the peaks on the nearand away-side, while EPOS LHC underestimates them significantly for all trigger particles except for the KS0. In the high ptrigg Tinterval, the shoving tune of PYTHIA8 is underestimating the near-side peak for all trigger particles except for KS0–h case, 123 Eur. Phys. J. C (2021) 81:945 Page 7 of 21 945 h-h correlations 3 GeV/c<pT trigg < 4 GeV/c 1 GeV/c<pT assoc <pT trigg |Δη|<1 9 GeV/c<pT trigg < 11 GeV/c 1 GeV/c<pT assoc <pT trigg KS-h correlations (Λ+Λ)-h correlations ALICE pp min. bias, s=13TeV PYTHIA8 Monash CR EPOS LHC PYTHIA8 Shoving g3 0 −10 1 2 3 4 −10 1 2 3 4 −10 1 2 3 4 Δϕ (rad)Δϕ (rad)Δϕ (rad) 0 0.2 0.4 0.6 0.8 1 1.2 1.4 0 1 2 3 4 5 dN/d ϕ(rad-1)1/Ntrigg dN/dϕ(rad-1)1/Ntrigg Fig. 2 ϕ projection of the h–h (left), KS0–h (middle) and ( +)–h (right) correlation functions compared with MC event generators for low (top) and high (bottom) ptrigg T.Error bars and colored boxes represent statistical and systematic uncertainties, respectively. The data are compared with MC event generators 46810 12 14 16 18 20 )c (GeV/ trigg T p 1 10 2 10 3 10 ϕΔ Y ALICE = 13 TeVs pp, trigg T p < assoc T p < c1 GeV/ h-h correlations | < 0.9ϕ Δ| -h correlations 0 S K | < 0.9 ϕ Δ| )-h correlationsΛ + Λ( | < 0.9ϕΔ| 2468 10 12 14 16 18 20 )c (GeV/ trigg T p 1 10 2 10 3 10 ϕΔ Y | < 1.4πϕ Δ | MB ) 6 0-1% (x2 ) 5 1-3% (x2 ) 4 3-7% (x2 ) 3 7-15% (x2 ) 2 15-50% (x2 ) 1 50-100% (x2 246810 12 14 16 18 20 )c (GeV/ trigg T p | < 1.4πϕΔ | 24681012 14 16 18 20 ) c (GeV/ trigg T p | < 1.4π-ϕΔ | Fig. 3 Per-trigger yields of h–h (left), KS0-h (middle) and ( + )-h (right) correlation functions as a function of ptrigg Ton the near-side (upper row) and away-side (lower row) for different multiplicity classes. For visibility, the values in the various event classes are scaled with the factors indicated in the legend. Error bars and colored boxes represent statistical and systematic uncertainties, respectively, which are in most cases within the data points 123 945 Page 8 of 21 Eur. Phys. J. C (2021) 81:945 246810 12 14 16 18 20 )c (GeV/ trigg T p 0.6 0.8 1 1.2 1.4 1.6 Ratio to MB ALICE = 13 TeV s pp, trigg T p < assoc T p < c1 GeV/ h-h correlations | < 0.9 ϕ Δ | -h correlations 0 S K | < 0.9 ϕΔ | )-h correlationsΛ +Λ( | < 0.9 ϕ Δ | 2 4 6 8 10 12 14 16 18 20 )c (GeV/ trigg T p 0.6 0.8 1 1.2 1.4 1.6 Ratio to MB | < 1.4π-ϕΔ| 0-1% 1-3% 3-7% 7-15% 15-50% 50-100% 2 4 6 8 10 12 14 16 18 20 ) c (GeV/ trigg T p | < 1.4 π-ϕΔ| 246 8 10 12 14 16 18 20 )c (GeV/ trigg T p | < 1.4π - ϕΔ| Fig. 4 Ratio of the per-trigger yields in different multiplicity classes to the corresponding minimum bias yield for h–h (left), KS0-h (middle) and (+)-h (right) correlations on the near-side (upper row) and away-side (lower row).Errorbarsand coloredboxesrepresentstatistical and systematic uncertainties, respectively but describes well the away-side peak. The description of EPOS LHC and PYTHIA8 Monash is similar in both ptrigg T intervals, where EPOS LHC is underestimating both peaks of h–h and ( +)–h correlation functions and can reasonablywell describethe ϕ projectionof theKS0–hcorrelation function. PYTHIA8 Monash tune overestimates both peaks for all three types of correlation functions. Theper-triggeryields,obtainedbyintegratingtheϕ projections of the correlation function for the intervals |ϕ|< 0.9 (near-side) and |ϕ −π|<1.4 (away-side) are studied as a function of ptrigg T,passoc Tand event-activity class for the three trigger particle species and compared with the MC event generators. The results are described in the following sections. 4.1 Per-trigger yields The per-trigger yields are shown in Fig. 3as a function of the ptrigg Tfor different event-activity classes. An increasing trend with ptrigg Tis observed, as expected, as higher energetic jets have increasingly more associated particles. For a more quantitative inspection of the event-activity dependence, the ratio between the yield in each event class and the yield for minimum bias is given in Fig. 4.Different trends are visible for the nearand away-side peaks. A clear multiplicity ordering for the near-side can be observed, events with higher multiplicity exhibiting the highest yields. This behaviour is most obvious for the h–h correlations, but it issignificanton thenear-sidealsofor theV0-triggeredyields. For the away-side this ordering is reverted, in particular with the increase of the pTof the trigger particle. Given the uncertainties, this trend is less significant for the KS0h and ( +)-h correlations. The finding is qualitatively reproduced in PYTHIA8 simulations and can be understood considering that the location of the away-side jet is not fixed in η. The requirement of a low (high) multiplicity in the V0 detectorsatlargerrapidity,biasesthe eventstowards configurations where the away-side jet is within (outside) the central acceptance, thus increasing (decreasing) the per-trigger yield at the away-side. The near-side jet is by construction in the central pseudorapidity acceptance, though the multiplicity measurement in the V0 detectors may still be influenced by long range correlations (flow-like) and fragmentation biases. This jet bias, although expected and roughly understood, is interesting, as it gives insights on particle production mechanisms. It is further investigated through the comparison with 123 Eur. Phys. J. C (2021) 81:945 Page 15 of 21 945 sions. Nature Phys. 13, 535–539 (2017). https://doi.org/10.1038/ nphys4111.arXiv:1606.07424 [nucl-ex] 6. ALICE Collaboration, S. Acharya et al., Multiplicity dependence of (multi-)strange hadron production in proton–proton collisions at sqrts = 13 TeV. Eur. Phys. J. C 80(2), 167 (2020). https://doi.org/ 10.1140/epjc/s10052-020-7673-8.arXiv:1908.01861 [nucl-ex] 7. K. Dusling, R. Venugopalan, Evidence for BFKL and saturation dynamics from dihadron spectra at the LHC. Phys. Rev. D87(5), 051502 (2013). https://doi.org/10.1103/PhysRevD.87. 051502.arXiv:1210.3890 [hep-ph] 8. B. Schenke, C. Shen, P. Tribedy, Running the gamut of high energy nuclear collisions. Phys. Rev. C 102(4), 044905 (2020). https://doi. org/10.1103/PhysRevC.102.044905.arXiv:2005.14682 [nucl-th] 9. K. Dusling, W. Li, B. Schenke, Novel collective phenomena in high-energy proton–proton and proton–nucleus collisions. Int. J. Mod. Phys. E 25(01), 1630002 (2016). https://doi.org/10.1142/ S0218301316300022.arXiv:1509.07939 [nucl-ex] 10. B. Schenke, The smallest fluid on earth (2021). arXiv:2102.11189 [nucl-th] 11. T. Sjöstrand, S. Ask, J.R. Christiansen, R. Corke, N. Desai, P. Ilten, S. Mrenna, S. Prestel, C.O. Rasmussen, P.Z. Skands, An Introduction to PYTHIA 8.2. Comput. Phys. Commun. 191, 159–177 (2015). https://doi.org/10.1016/j.cpc.2015.01.024. arXiv:1410.3012 [hep-ph] 12. T. Pierog, I. Karpenko, J.M. Katzy, E. Yatsenko, K. Werner, EPOS LHC: Test of collective hadronization with data measured at the CERN Large Hadron Collider. Phys. Rev. C92(3), 034906 (2015). https://doi.org/10.1103/PhysRevC.92. 034906.arXiv:1306.0121 [hep-ph] 13. P. Skands, S. Carrazza, J. Rojo, Tuning PYTHIA 8.1: the Monash 2013 Tune. Eur. Phys. J. C 74(8), 3024 (2014). https://doi.org/10. 1140/epjc/s10052-014-3024-y.arXiv:1404.5630 [hep-ph] 14. C. Bierlich, G. Gustafson, L. Lönnblad, Collectivity without plasma in hadronic collisions. Phys. Lett. B 779, 58– 63 (2018). https://doi.org/10.1016/j.physletb.2018.01.069. arXiv:1710.09725 [hep-ph] 15. C. Bierlich, Soft modifications to jet fragmentation in high energy proton–proton collisions. Phys. Lett. B 795, 194– 199 (2019). https://doi.org/10.1016/j.physletb.2019.06.018. arXiv:1901.07447 [hep-ph] 16. J. Adam, D. Adamová, M. Aggarwal, G. Aglieri Rinella, M. Agnello, N. Agrawal, Z. Ahammed, S. Ahn, I. Aimo, S. Aiola et al., Measurement of charged jet production cross sections and nuclear modification in p-pb collisions at snn=5.02 tev. Phys. Lett. B749, 68–81 (2015). https://doi.org/10.1016/j.physletb.2015.07. 054 17. ATLAS Collaboration, M. Aaboud et al., Measurement of long-range two-particle Azimuthal correlations in Z-boson tagged pp collisions at sqrts =8 and 13 TeV. Eur. Phys. J. C 80(1), 64 (2020). https://doi.org/10.1140/epjc/ s10052-020-7606-6.arXiv:1906.08290 [nucl-ex] 18. ALICE Collaboration, S. Acharya et al., Longand shortrange correlations and their event-scale dependence in highmultiplicity pp collisions at √s=13 TeV. JHEP 05, 290 (2021). arXiv:2101.03110 [nucl-ex] 19. OPAL Collaboration, G. Abbiendi et al., Particle multiplicity of unbiased gluon jets from e+ethree-jet events. Eur. Phys. J. C23, 597–613 (2002). https://doi.org/10.1007/s100520200926. arXiv:hep-ex/0111013 20. DELPHI Collaboration, Energy dependence of the differences between the quark and gluon jet fragmentation. Z Phys. C Part. Fields 70, (1996). https://doi.org/10.1007/s002880050095 21. OPAL Collaboration, K. Ackerstaff et al., Production of K0 S and in quark and gluon jets from Z0decay. Eur. Phys. J. C8, 241–254 (1999). https://doi.org/10.1007/s100529901058. arXiv:hep-ex/9805025 22. ALICE Collaboration, B. Abelev et al., The ALICE experiment at the CERN LHC. JINST 3, S08002 (2008). https://doi.org/10. 1088/1748-0221/3/08/s08002 23. ALICE Collaboration, B. Abelev et al., Performance of the ALICE Experiment at the CERN LHC. Int. J. Mod. Phys. A 29, 1430044 (2014). https://doi.org/10.1142/S0217751X14300440. arXiv:1402.4476 [nucl-ex] 24. ALICE Collaboration, S. Acharya et al., Pseudorapidity distributions of charged particles as a function of mid and forward rapidity mutiplicities in pp collisions at √s= 5.02, 7 and 13 TeV (2020). arXiv:2009.09434 [nucl-ex] 25. ALICE Collaboration, S. Acharya et al., Transverse momentum spectra and nuclear modification factors of charged particles in pp, p-Pband Pb-Pbcollisions atthe LHC.JHEP 11, 013(2018).https:// doi.org/10.1007/JHEP11(2018)013.arXiv:1802.09145 [nucl-ex] 26. Particle Data Group Collaboration, M. Tanabashi, K. Hagiwara, K. Hikasa, et al., Review of particle physics. Phys. Rev. D [online] 98, 030001 (2018). https://link.aps.org/doi/10.1103/PhysRevD. 98.030001 27. ALICE Collaboration, S. Acharya et al., Production of light-flavor hadrons in pp collisions at √s=7and√s= 13 TeV. Eur. Phys. J. C81, 256 (2021). arXiv:2005.11120 [nucl-ex] 28. ALICE Collaboration, K. Aamodt et al., Strange particle production in proton–proton collisions at sqrts=0.9 TeV with ALICE at the LHC. Eur. Phys. J. C (2011). https://doi.org/10.1140/epjc/ s10052-011-1594-5.arXiv:1012.3257 [nucl-ex] 29. T. Sjöstrand, S. Mrenna, P.Z. Skands, A brief introduction to PYTHIA 8.1. Comput. Phys. Commun. 178, 852–867 (2008). https://doi.org/10.1016/j.cpc.2008.01.036.arXiv:0710.3820 [hepph] 30. R. Brun et al., GEANT Detector Description and Simulation Tool. CERN-W-5013 , 1 (1994). https://doi.org/10.17181/CERN. MUHF.DMJ1 31. ALICE Collaboration, J. Adam et al., Evolution of the longitudinal andazimuthalstructure of thenear-side jet peakinPb–Pbcollisions at sqrtsmNN =2.76 TeV. Phys. Rev. C 96(3), 034904 (2017). https://doi.org/10.1103/PhysRevC.96.034904.arXiv:1609.06667 [nucl-ex] 32. T.A. Trainor,Zeroyield atminimum(zyam) methodandv2: Underestimating jet yields from dihadron azimuth correlations. Phys. Rev. C 81, 014905 (2010). https://doi.org/10.1103/PhysRevC.81. 014905.arXiv:0904.1733 [hep-ph] 33. R. Barlow, Systematic errors: facts and fictions (2002). arXiv:hep-ex/0207026 34. C. Bierlich, S. Chakraborty, G. Gustafson, L. Lönnblad, Setting the string shoving picture in a new frame. JHEP 03, 270 (2021). https:// doi.org/10.1007/JHEP03(2021)270.arXiv:2010.07595 [hep-ph] 35. ALICE Collaboration, S. Acharya et al., Production of and K0 S in jets in p-Pb collisions at √sNN =5TeVandppcollisionsat √s=7 TeV (2021). arXiv:2105.04890 [nucl-ex] 123 945 Page 16 of 21 Eur. Phys. J. C (2021) 81:945 ALICE Collaboration S. Acharya141, D. Adamová96, A. Adler74, G. Aglieri Rinella34, M. Agnello30, N. Agrawal54, Z. Ahammed141, S. Ahmad16, S. U. Ahn76, I. Ahuja38,Z. Akbar51, A. Akindinov93,M.Al-Turany108,S.N.Alam16,40,D. Aleksandrov89,B. Alessandro59, H. M. Alfanda7, R. Alfaro Molina71,B.Ali 16,Y.Ali 14, A. Alici25, N. Alizadehvandchali125, A. Alkin34,J.Alme 21, T. Alt68, L. Altenkamper21, I. Altsybeev113, M. N. Anaam7, C. Andrei48, D. Andreou91, A. Andronic144, M. Angeletti34, V. Anguelov105, F. Antinori57, P. Antonioli54, C. Anuj16, N. Apadula80, L. Aphecetche115, H. Appelshäuser68, S. Arcelli25, R. Arnaldi59, I.C.Arsene 20, M. Arslandok105,146, A. Augustinus34, R. Averbeck108,S.Aziz 78, M.D.Azmi 16, A. Badalà56, Y. W. Baek41,X.Bai 129,108, R. Bailhache68, Y. Bailung50,R.Bala 102, A. Balbino30, A. Baldisseri138, B. Balis2,M.Ball 43, D. Banerjee4, R. Barbera26, L. Barioglio106,M.Barlou 85, G. G. Barnaföldi145, L. S. Barnby95, V. Barret135, C. Bartels128,K.Barth 34, E. Bartsch68, F. Baruffaldi27, N. Bastid135,S.Basu 81, G. Batigne115, B. Batyunya75, D. Bauri49, J. L. Bazo Alba112, I. G. Bearden90, C. Beattie146, I. Belikov137, A. D. C. Bell Hechavarria144, F. Bellini25, R. Bellwied125, S. Belokurova113, V. Belyaev94, G. Bencedi69, S. Beole24, A. Bercuci48, Y. Berdnikov99, A. Berdnikova105, L. Bergmann105,M.G.Besoiu 67,L.Betev 34, P. P. Bhaduri141, A. Bhasin102,I.R.Bhat 102,M.A.Bhat 4, B. Bhattacharjee42, P. Bhattacharya22, L. Bianchi24, N. Bianchi52,J.Bielˇcík37,J.Bielˇcíková96, J. Biernat118, A. Bilandzic106,G.Biro 145, S. Biswas4, J. T. Blair119,D.Blau 89, M. B. Blidaru108,C.Blume 68, G. Boca28,58, F. Bock97, A. Bogdanov94, S. Boi22,J.Bok 61, L. Boldizsár145, A. Bolozdynya94, M. Bombara38, P. M. Bond34, G. Bonomi58,140, H. Borel138, A. Borissov82, H. Bossi146, E. Botta24,L.Bratrud 68, P. Braun-Munzinger108, M. Bregant121,M.Broz 37, G. E. Bruno33,107, M. D. Buckland128, D. Budnikov109, H. Buesching68, S. Bufalino30, O. Bugnon115, P. Buhler114, Z. Buthelezi72,132, J. B. Butt14, S.A.Bysiak 118,M.Cai 7,27, H. Caines146,A.Caliva 108, E. Calvo Villar112, J. M. M. Camacho120, R. S. Camacho45, P. Camerini23, F. D. M. Canedo121, F. Carnesecchi25,34, R. Caron138, J. Castillo Castellanos138, E. A. R. Casula22, F. Catalano30, C. Ceballos Sanchez75, P. Chakraborty49, S. Chandra141, S. Chapeland34, M. Chartier128, S. Chattopadhyay141, S. Chattopadhyay110, A. Chauvin22,T.G.Chavez 45, T. Cheng7, C. Cheshkov136, B. Cheynis136, V. Chibante Barroso34, D. D. Chinellato122,S.Cho 61, P. Chochula34, P. Christakoglou91, C. H. Christensen90, P. Christiansen81, T. Chujo134, C. Cicalo55, L. Cifarelli25, F. Cindolo54, M. R. Ciupek108,G.Clai 54,a, J. Cleymans124,e, F. Colamaria53,J.S.Colburn 111, D. Colella33,53,107,145, A. Collu80, M. Colocci34, M. Concas59,b, G. Conesa Balbastre79, Z. Conesa del Valle78, G. Contin23,J.G.Contreras 37, M. L. Coquet138, T. M. Cormier97,P.Cortese 31, M. R. Cosentino123, F. Costa34, S. Costanza28,58, P. Crochet135, R. Cruz-Torres80, E. Cuautle69,P.Cui 7, L. Cunqueiro97, A. Dainese57, M. C. Danisch105, A. Danu67,I.Das 110,P.Das 87,P.Das 4,S.Das 4,S.Dash 49,S.De 87,A.DeCaro 29, G. de Cataldo53, L. De Cilladi24, J. de Cuveland39, A. De Falco22, D. De Gruttola29, N. De Marco59, C. De Martin23, S. De Pasquale29, S. Deb50, H. F. Degenhardt121, K.R.Deja 142, L. Dello Stritto29, S. Delsanto24, W. Deng7, P. Dhankher19,D.DiBari 33, A. Di Mauro34, R.A.Diaz 8, T. Dietel124,Y.Ding 7,136,R.Divià 34, D.U.Dixit 19, Ø. Djuvsland21, U. Dmitrieva63, J. Do61, A. Dobrin67, B. Dönigus68, O. Dordic20, A.K.Dubey 141, A. Dubla91,108, S. Dudi101, M. Dukhishyam87, P. Dupieux135, N. Dzalaiova13, T. M. Eder144, R.J.Ehlers 97, V. N. Eikeland21, F. Eisenhut68, D. Elia53, B. Erazmus115, F. Ercolessi25, F. Erhardt100, A. Erokhin113, M.R.Ersdal 21, B. Espagnon78, G. Eulisse34, D. Evans111, S. Evdokimov92, L. Fabbietti106, M. Faggin27, J. Faivre79,F.Fan 7, A. Fantoni52, M. Fasel97, P. Fecchio30, A. Feliciello59, G. Feofilov113, A. Fernández Téllez45, A. Ferrero138, A. Ferretti24, V. J. G. Feuillard105, J. Figiel118, S. Filchagin109, D. Finogeev63, F. M. Fionda21,55, G. Fiorenza34,107,F.Flor 125,A.N.Flores 119, S. Foertsch72, P. Foka108, S. Fokin89, E. Fragiacomo60, E. Frajna145, U. Fuchs34, N. Funicello29, C. Furget79, A. Furs63, J. J. Gaardhøje90, M. Gagliardi24, A. M. Gago112, A. Gal137,C.D.Galvan 120, P. Ganoti85, C. Garabatos108,J.R.A.Garcia 45, E. Garcia-Solis10,K.Garg 115, C. Gargiulo34, A. Garibli88, K. Garner144,P.Gasik 108, E. F. Gauger119, A. Gautam127, M. B. Gay Ducati70,M.Germain 115, P. Ghosh141, S. K. Ghosh4, M. Giacalone25, P. Gianotti52, P. Giubellino59,108, P. Giubilato27, A. M. C. Glaenzer138, P. Glässel105, D. J. Q. Goh83, V. Gonzalez143, L. H. González-Trueba71, S. Gorbunov39, M. Gorgon2, L. Görlich118, S. Gotovac35, V. Grabski71, L. K. Graczykowski142, L. Greiner80, A. Grelli62, C. Grigoras34, V. Grigoriev94, A. Grigoryan1,e, S. Grigoryan1,75, O. S. Groettvik21, F. Grosa34,59, J. F. Grosse-Oetringhaus34, R. Grosso108, G. G. Guardiano122, R. Guernane79, M. Guilbaud115, K. Gulbrandsen90, T. Gunji133,W.Guo 7, A. Gupta102, R. Gupta102, S. P. Guzman45, L. Gyulai145, M. K. Habib108, C. Hadjidakis78, G. Halimoglu68, H. Hamagaki83, G. Hamar145,M.Hamid 7, R. Hannigan119, M. R. Haque87,142, A. Harlenderova108,J.W.Harris 146,A.Harton 10, J. A. Hasenbichler34, H. Hassan97, D. Hatzifotiadou54, P. Hauer43, L. B. Havener146, S. Hayashi133, S. T. Heckel106, E. Hellbär108,H.Helstrup 36,T.Herman 37, E. G. Hernandez45, G. Herrera Corral9, F. Herrmann144, K. F. Hetland36, H. Hillemanns34, C. Hills128, B. Hippolyte137,B.Hofman 62, B. Hohlweger91, J. Honermann144, G.H.Hong 147, D. Horak37, S. Hornung108, A. Horzyk2, R. Hosokawa15,Y.Hou 7, P. Hristov34, C. Hughes131, P. Huhn68, T. J. Humanic98, H. Hushnud110,A.Hutson 125, D. Hutter39, J. P. Iddon34,128, R. Ilkaev109, H. Ilyas14, M. Inaba134, G. M. Innocenti34, M. Ippolitov89, A. Isakov37,96, M.S.Islam 110, M. Ivanov108, 123 Eur. Phys. J. C (2021) 81:945 Page 17 of 21 945 V. Ivanov99, V. Izucheev92, M. Jablonski2, B. Jacak80, N. Jacazio34, P. M. Jacobs80, S. Jadlovska117, J. Jadlovsky117, S. Jaelani62, C. Jahnke121,122, M. J. Jakubowska142, A. Jalotra102, M. A. Janik142, T. Janson74, M. Jercic100, O. Jevons111, A. A. P. Jimenez69, F. Jonas97,144, P. G. Jones111, J.M.Jowett34,108, J. Jung68, M. Jung68, A. Junique34,A.Jusko 111, J. Kaewjai116, P. Kalinak64,A.Kalweit 34, V. Kaplin94,S.Kar 7, A. Karasu Uysal77, D. Karatovic100, O. Karavichev63, T. Karavicheva63, P. Karczmarczyk142, E. Karpechev63, A. Kazantsev89, U. Kebschull74, R. Keidel47, D. L. D. Keijdener62, M. Keil34, B. Ketzer43, Z. Khabanova91, A. M. Khan7, S. Khan16, A. Khanzadeev99, Y. Kharlov92, A. Khatun16, A. Khuntia118, B. Kileng36,B.Kim 17,61,C.Kim 17,D.J.Kim 126,E.J.Kim 73,J.Kim 147,J.S.Kim 41,J.Kim 105,J.Kim 147, J. Kim73,M.Kim 105,S.Kim 18,T.Kim 147,S.Kirsch 68,I.Kisel 39,S.Kiselev 93, A. Kisiel142,J.P.Kitowski 2,J.L.Klay 6, J. Klein34, S. Klein80, C. Klein-Bösing144, M. Kleiner68, T. Klemenz106, A. Kluge34, A. G. Knospe125, C. Kobdaj116, M. K. Köhler105, T. Kollegger108, A. Kondratyev75, N. Kondratyeva94, E. Kondratyuk92, J. Konig68, S. A. Konigstorfer106, P. J. Konopka34,2, G. Kornakov142, S. D. Koryciak2, L. Koska117, A. Kotliarov96, O. Kovalenko86, V. Kovalenko113, M. Kowalski118, I. Králik64,A.Kravˇcáková38,L.Kreis 108, M. Krivda64,111, F. Krizek96, K. Krizkova Gajdosova37, M. Kroesen105, M. Krüger68, E. Kryshen99, M. Krzewicki39,V.Kuˇcera34, C. Kuhn137, P. G. Kuijer91, T. Kumaoka134, D. Kumar141, L. Kumar101, N. Kumar101, S. Kundu34,87, P. Kurashvili86, A. Kurepin63, A. B. Kurepin63, A. Kuryakin109, S. Kushpil96, J. Kvapil111, M.J.Kweon 61,J.Y.Kwon 61,Y.Kwon 147, S. L. La Pointe39, P. La Rocca26,Y.S.Lai 80, A. Lakrathok116, M. Lamanna34, R. Langoy130, K. Lapidus34, P. Larionov34,52, E. Laudi34, L. Lautner34,106, R. Lavicka37, T. Lazareva113,R.Lea 23,58,140, J. Lehrbach39, R.C.Lemmon 95, I. León Monzón120, E. D. Lesser19, M. Lettrich34,106, P. Lévai145,X.Li 11, X.L.Li 7,J.Lien 130, R. Lietava111,B.Lim 17, S.H.Lim 17, V. Lindenstruth39, A. Lindner48, C. Lippmann108,A.Liu 19,D.H.Liu 7,J.Liu 128, I. M. Lofnes21, V. Loginov94, C. Loizides97, P. Loncar35, J. A. Lopez105, X. Lopez135, E. López Torres8, J. R. Luhder144, M. Lunardon27, G. Luparello60,Y.G.Ma 40, A. Maevskaya63, M. Mager34, T. Mahmoud43,A.Maire 137, M. Malaev99, N.M.Malik 102, Q.W.Malik 20, L. Malinina75,c,D.Mal’Kevich 93, N. Mallick50, P. Malzacher108, G. Mandaglio32,56, V. Manko89, F. Manso135, V. Manzari53,Y.Mao 7, J. Mareš66, G. V. Margagliotti23, A. Margotti54,A.Marín 108,C.Markert 119, M. Marquard68, N. A. Martin105, P. Martinengo34, J. L. Martinez125, M. I. Martínez45, G. Martínez García115, S. Masciocchi108, M. Masera24, A. Masoni55, L. Massacrier78, A. Mastroserio139,53,A.M.Mathis 106, O. Matonoha81, P. F. T. Matuoka121, A. Matyja118, C. Mayer118, A. L. Mazuecos34, F. Mazzaschi24, M. Mazzilli34, J. E. Mdhluli132, A. F. Mechler68, Y. Melikyan63, A. Menchaca-Rocha71, E. Meninno29,114, A. S. Menon125, M. Meres13, S. Mhlanga72,124,Y.Miake 134, L. Micheletti24,59, L. C. Migliorin136, D. L. Mihaylov106, K. Mikhaylov75,93,A.N.Mishra 145,D.Mi´skowiec108, A. Modak4, A. P. Mohanty62, B. Mohanty87, M. Mohisin Khan16,d, M. A. Molander44, Z. Moravcova90, C. Mordasini106, D. A. Moreira De Godoy144, L. A. P. Moreno45, I. Morozov63, A. Morsch34,T.Mrnjavac 34, V. Muccifora52, E. Mudnic35, D. Mühlheim144, S. Muhuri141, J. D. Mulligan80, A. Mulliri22, M. G. Munhoz121, R. H. Munzer68, H. Murakami133,S.Murray 124,L.Musa 34,J.Musinsky 64, J. W. Myrcha142, B. Naik49,132,R.Nair 86, B. K. Nandi49, R. Nania54, E. Nappi53,M.U.Naru 14, A. F. Nassirpour81,A.Nath 105, C. Nattrass131, A. Neagu20, L. Nellen69, S. V. Nesbo36, G. Neskovic39,D.Nesterov 113, B. S. Nielsen90, S. Nikolaev89, S. Nikulin89, V. Nikulin99, F. Noferini54,S.Noh 12, P. Nomokonov75,J.Norman 128, N. Novitzky134, P. Nowakowski142, A. Nyanin89, J. Nystrand21, M. Ogino83,A.Ohlson 81, V. A. Okorokov94, J. Oleniacz142, A. C. Oliveira Da Silva131, M. H. Oliver146, A. Onnerstad126, C. Oppedisano59, A. Ortiz Velasquez69,T.Osako 46, A. Oskarsson81, J. Otwinowski118, M. Oya46, K. Oyama83, Y. Pachmayer105, S. Padhan49, D. Pagano58,140,G.Pai´c69, A. Palasciano53,J.Pan 143, S. Panebianco138, P. Pareek141,J.Park 61, J. E. Parkkila126, S. P. Pathak125,R.N.Patra 34,102, B. Paul22, H. Pei7, T. Peitzmann62, X. Peng7, L. G. Pereira70, H. Pereira Da Costa138, D. Peresunko89, G. M. Perez8, S. Perrin138, Y. Pestov5, V. Petráˇcek37, M. Petrovici48, R. P. Pezzi70,115, S. Piano60, M. Pikna13, P. Pillot115, O. Pinazza34,54,L.Pinsky 125, C. Pinto26, S. Pisano52,M.Płosko´n80, M. Planinic100, F. Pliquett68, M. G. Poghosyan97, B. Polichtchouk92, S. Politano30, N. Poljak100, A. Pop48, S. Porteboeuf-Houssais135, J. Porter80, V. Pozdniakov75, S. K. Prasad4, R. Preghenella54, F. Prino59, C. A. Pruneau143, I. Pshenichnov63, M. Puccio34,S.Qiu 91, L. Quaglia24, R. E. Quishpe125, S. Ragoni111, A. Rakotozafindrabe138, L. Ramello31,F.Rami 137,S.A.R.Ramirez 45,A.G.T.Ramos 33, T. A. Rancien79, R. Raniwala103, S. Raniwala103, S. S. Räsänen44,R.Rath 50, I. Ravasenga91, K.F.Read 97,131, A. R. Redelbach39, K. Redlich86,e, A. Rehman21, P. Reichelt68, F. Reidt34, H. A. Reme-ness36, R. Renfordt68, Z. Rescakova38, K. Reygers105, A. Riabov99, V. Riabov99, T. Richert81, M. Richter20, W. Riegler34, F. Riggi26, C. Ristea67, M. Rodríguez Cahuantzi45, K. Røed20, R. Rogalev92, E. Rogochaya75, T. S. Rogoschinski68, D. Rohr34, D. Röhrich21,P.F.Rojas 45, P. S. Rokita142, F. Ronchetti52, A. Rosano32,56, E. D. Rosas69, A. Rossi57, A. Rotondi28,58,A.Roy 50,P.Roy 110,S.Roy 49, N. Rubini25, O. V. Rueda81, R. Rui23, B. Rumyantsev75, P. G. Russek2,A.Rustamov 88, E. Ryabinkin89, Y. Ryabov99, A. Rybicki118, H. Rytkonen126, W. Rzesa142, O. A. M. Saarimaki44, R. Sadek115, S. Sadovsky92, J. Saetre21, K. Šafaˇrík37, S. K. Saha141, S. Saha87, B. Sahoo49, P. Sahoo49, R. Sahoo50, S. Sahoo65, D. Sahu50, P. K. Sahu65, J. Saini141, S. Sakai134, S. Sambyal102, V. Samsonov94,99,e, D. Sarkar143, N. Sarkar141, P. Sarma42, V. M. Sarti106, M.H.P.Sas 146, J. Schambach97,119, 123 945 Page 18 of 21 Eur. Phys. J. C (2021) 81:945 H. S. Scheid68, C. Schiaua48, R. Schicker105, A. Schmah105, C. Schmidt108, H. R. Schmidt104, M. O. Schmidt34, M. Schmidt104, N. V. Schmidt68,97, A. R. Schmier131, R. Schotter137, J. Schukraft34, Y. Schutz137, K. Schwarz108, K. Schweda108, G. Scioli25, E. Scomparin59, J. E. Seger15, Y. Sekiguchi133, D. Sekihata133, I. Selyuzhenkov94,108, S. Senyukov137, J. J. Seo61, D. Serebryakov63, L. Šerkšnyt˙e106, A. Sevcenco67, T. J. Shaba72, A. Shabanov63, A. Shabetai115, R. Shahoyan34, W. Shaikh110, A. Shangaraev92, A. Sharma101, H. Sharma118, M. Sharma102, N. Sharma101, S. Sharma102, U. Sharma102, O. Sheibani125, K. Shigaki46, M. Shimomura84, S. Shirinkin93, Q. Shou40, Y. Sibiriak89, S. Siddhanta55, T. Siemiarczuk86, T.F.Silva 121, D. Silvermyr81, G. Simonetti34, B. Singh106, R. Singh87, R. Singh102, R. Singh50, V. K. Singh141, V. Singhal141, T. Sinha110, B. Sitar13, M. Sitta31, T. B. Skaali20, G. Skorodumovs105, M. Slupecki44,N.Smirnov 146, R. J. M. Snellings62, C. Soncco112, J. Song125, A. Songmoolnak116, F. Soramel27, S. Sorensen131, I. Sputowska118,J. Stachel105,I.Stan67, P. J. Steffanic131,S. F. Stiefelmaier105, D. Stocco115,I. Storehaug20, M. M. Storetvedt36, C. P. Stylianidis91, A. A. P. Suaide121, T. Sugitate46, C. Suire78, M. Sukhanov63, M. Suljic34, R. Sultanov93, M. Šumbera96, V. Sumberia102, S. Sumowidagdo51,S.Swain 65, A. Szabo13, I. Szarka13, U. Tabassam14, S. F. Taghavi106, G. Taillepied135, J. Takahashi122, G.J.Tambave 21, S. Tang7,135, Z. Tang129, L. A. Tarasoviˇcová144, M. Tarhini115,M.G.Tarzila 48, A. Tauro34, G. Tejeda Muñoz45, A. Telesca34, L. Terlizzi24,C.Terrevoli 125, G. Tersimonov3, S. Thakur141, D. Thomas119, R. Tieulent136, A. Tikhonov63, A. R. Timmins125, M. Tkacik117,A.Toia 68, N. Topilskaya63, M. Toppi52, F. Torales-Acosta19,T.Tork 78,S.R.Torres 37,A.Trifiró 32,56, S. Tripathy54,69, T. Tripathy49, S. Trogolo27,34, G. Trombetta33, V. Trubnikov3, W. H. Trzaska126, T. P. Trzcinski142, B. A. Trzeciak37, A. Tumkin109,R.Turrisi 57, T. S. Tveter20, K. Ullaland21,A.Uras 136, M. Urioni58,140,G.L.Usai 22,M.Vala 38, N. Valle28,58, S. Vallero59, N. van der Kolk62, L.V.R.vanDoremalen 62, M. van Leeuwen91, P. Vande Vyvre34,D.Varga 145,Z.Varga 145, M. Varga-Kofarago145,A.Vargas 45, M. Vasileiou85, A. Vasiliev89, O. Vázquez Doce52,106, V. Vechernin113, E. Vercellin24, S. Vergara Limón45, L. Vermunt62,R.Vértesi 145,M.Verweij 62,L.Vickovic 35, Z. Vilakazi132, O. Villalobos Baillie111, G. Vino53, A. Vinogradov89, T. Virgili29, V. Vislavicius90, A. Vodopyanov75,B.Volkel 34, M. A. Völkl105, K. Voloshin93, S. A. Voloshin143, G. Volpe33, B. von Haller34, I. Vorobyev106, D. Voscek117, N. Vozniuk63,J.Vrláková 38, B. Wagner21, C. Wang40, D. Wang40, M. Weber114, R. J. G. V. Weelden91, A. Wegrzynek34, S. C. Wenzel34, J.P.Wessels 144, J. Wiechula68, J. Wikne20, G. Wilk86, J. Wilkinson108, G. A. Willems144, B. Windelband105,M.Winn 138, W. E. Witt131, J. R. Wright119,W.Wu 40,Y.Wu 129,R.Xu 7, A. K. Yadav141, S. Yalcin77, Y. Yamaguchi46, K. Yamakawa46, S. Yang21, S. Yano46,Z.Yin 7, H. Yokoyama62,I.-K.Yoo 17, J.H.Yoon 61, S. Yuan21, A. Yuncu105, V. Zaccolo23, A. Zaman14, C. Zampolli34, H. J. C. Zanoli62, N. Zardoshti34, A. Zarochentsev113, P. Závada66, N. Zaviyalov109, M. Zhalov99, B. Zhang7, S. Zhang40, X. Zhang7, Y. Zhang129, V. Zherebchevskii113,Y.Zhi 11, N. Zhigareva93, D. Zhou7, Y. Zhou90,J.Zhu 7,108, Y. Zhu7, A. Zichichi25, G. Zinovjev3,N.Zurlo 58,140 1A.I. Alikhanyan National Science Laboratory (Yerevan Physics Institute) Foundation, Yerevan, Armenia 2AGH University of Science and Technology, Cracow, Poland 3Bogolyubov Institute for Theoretical Physics, National Academy of Sciences of Ukraine, Kiev, Ukraine 4Department of Physics and Centre for Astroparticle Physics and Space Science (CAPSS), Bose Institute, Kolkata, India 5Budker Institute for Nuclear Physics, Novosibirsk, Russia 6California Polytechnic State University, San Luis Obispo, CA, USA 7Central China Normal University, Wuhan, China 8Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN), Havana, Cuba 9Centro de Investigación y de Estudios Avanzados (CINVESTAV), Mexico City and Mérida, Mexico 10 Chicago State University, Chicago, IL, USA 11 China Institute of Atomic Energy, Beijing, China 12 Chungbuk National University, Cheongju, Republic of Korea 13 Faculty of Mathematics, Physics and Informatics, Comenius University Bratislava, Bratislava, Slovakia 14 COMSATS University Islamabad, Islamabad, Pakistan 15 Creighton University, Omaha, NE, USA 16 Department of Physics, Aligarh Muslim University, Aligarh, India 17 Department of Physics, Pusan National University, Pusan, Republic of Korea 18 Department of Physics, Sejong University, Seoul, Republic of Korea 19 Department of Physics, University of California, Berkeley, CA, USA 20 Department of Physics, University of Oslo, Oslo, Norway 21 Department of Physics and Technology, University of Bergen, Bergen, Norway 22 Dipartimento di Fisica dell’Università and Sezione INFN, Cagliari, Italy 123 Eur. Phys. J. C (2021) 81:945 Page 19 of 21 945 23 Dipartimento di Fisica dell’Università and Sezione INFN, Trieste, Italy 24 Dipartimento di Fisica dell’Università and Sezione INFN, Turin, Italy 25 Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN, Bologna, Italy 26 Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN, Catania, Italy 27 Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN, Padua, Italy 28 Dipartimento di Fisica e Nucleare e Teorica, Università di Pavia, Pavia, Italy 29 Dipartimento di Fisica ‘E.R. Caianiello’ dell’Università and Gruppo Collegato INFN, Salerno, Italy 30 Dipartimento DISAT del Politecnico and Sezione INFN, Turin, Italy 31 Dipartimento di Scienze e Innovazione Tecnologica dell’Università del Piemonte Orientale and INFN Sezione di Torino, Alessandria, Italy 32 Dipartimento di Scienze MIFT, Università di Messina, Messina, Italy 33 Dipartimento Interateneo di Fisica ‘M. Merlin’ and Sezione INFN, Bari, Italy 34 European Organization for Nuclear Research (CERN), Geneva, Switzerland 35 Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, Split, Croatia 36 Faculty of Engineering and Science, Western Norway University of Applied Sciences, Bergen, Norway 37 Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University in Prague, Prague, Czech Republic 38 Faculty of Science, P.J. Šafárik University, Košice, Slovakia 39 Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe-Universität Frankfurt, Frankfurt, Germany 40 Fudan University, Shanghai, China 41 Gangneung-Wonju National University, Gangneung, Republic of Korea 42 Department of Physics, Gauhati University, Guwahati, India 43 Helmholtz-Institut für Strahlenund Kernphysik, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany 44 Helsinki Institute of Physics (HIP), Helsinki, Finland 45 High Energy Physics Group, Universidad Autónoma de Puebla, Puebla, Mexico 46 Hiroshima University, Hiroshima, Japan 47 Hochschule Worms, Zentrum für Technologietransfer und Telekommunikation (ZTT), Worms, Germany 48 Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest, Romania 49 Indian Institute of Technology Bombay (IIT), Mumbai, India 50 Indian Institute of Technology Indore, Indore, India 51 Indonesian Institute of Sciences, Jakarta, Indonesia 52 INFN, Laboratori Nazionali di Frascati, Frascati, Italy 53 INFN, Sezione di Bari, Bari, Italy 54 INFN, Sezione di Bologna, Bologna, Italy 55 INFN, Sezione di Cagliari, Cagliari, Italy 56 INFN, Sezione di Catania, Catania, Italy 57 INFN, Sezione di Padova, Padua, Italy 58 INFN, Sezione di Pavia, Pavia, Italy 59 INFN, Sezione di Torino, Turin, Italy 60 INFN, Sezione di Trieste, Trieste, Italy 61 Inha University, Incheon, Republic of Korea 62 Institute for Gravitational and Subatomic Physics (GRASP), Utrecht University/Nikhef, Utrecht, The Netherlands 63 Institute for Nuclear Research, Academy of Sciences, Moscow, Russia 64 Institute of Experimental Physics, Slovak Academy of Sciences, Košice, Slovakia 65 Institute of Physics, Homi Bhabha National Institute, Bhubaneswar, India 66 Institute of Physics of the Czech Academy of Sciences, Prague, Czech Republic 67 Institute of Space Science (ISS), Bucharest, Romania 68 Institut für Kernphysik, Johann Wolfgang Goethe-Universität Frankfurt, Frankfurt, Germany 69 Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Mexico City, Mexico 70 Instituto de Física, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil 71 Instituto de Física, Universidad Nacional Autónoma de México, Mexico City, Mexico 72 iThemba LABS, National Research Foundation, Somerset West, South Africa 73 Jeonbuk National University, Jeonju, Republic of Korea 123 945 Page 20 of 21 Eur. Phys. J. C (2021) 81:945 74 Johann-Wolfgang-Goethe Universität Frankfurt Institut für Informatik, Fachbereich Informatik und Mathematik, Frankfurt, Germany 75 Joint Institute for Nuclear Research (JINR), Dubna, Russia 76 Korea Institute of Science and Technology Information, Daejeon, Republic of Korea 77 KTO Karatay University, Konya, Turkey 78 Laboratoire de Physique des 2 Infinis, Irène Joliot-Curie, Orsay, France 79 Laboratoire de Physique Subatomique et de Cosmologie, Université Grenoble-Alpes, CNRS-IN2P3, Grenoble, France 80 Lawrence Berkeley National Laboratory, Berkeley, CA, USA 81 Division of Particle Physics, Department of Physics, Lund University, Lund, Sweden 82 Moscow Institute for Physics and Technology, Moscow, Russia 83 Nagasaki Institute of Applied Science, Nagasaki, Japan 84 Nara Women’s University (NWU), Nara, Japan 85 Department of Physics, School of Science, National and Kapodistrian University of Athens, Athens, Greece 86 National Centre for Nuclear Research, Warsaw, Poland 87 National Institute of Science Education and Research, Homi Bhabha National Institute, Jatni, India 88 National Nuclear Research Center, Baku, Azerbaijan 89 National Research Centre Kurchatov Institute, Moscow, Russia 90 Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark 91 Nikhef, National institute for subatomic physics, Amsterdam, The Netherlands 92 NRC Kurchatov Institute IHEP, Protvino, Russia 93 NRC «Kurchatov»Institute, ITEP, Moscow, Russia 94 NRNU Moscow Engineering Physics Institute, Moscow, Russia 95 Nuclear Physics Group, STFC Daresbury Laboratory, Daresbury, UK 96 Nuclear Physics Institute of the Czech Academy of Sciences, ˇ Rež u Prahy, Czech Republic 97 Oak Ridge National Laboratory, Oak Ridge, TN, USA 98 Ohio State University, Columbus, OH, USA 99 Petersburg Nuclear Physics Institute, Gatchina, Russia 100 Physics Department, Faculty of science, University of Zagreb, Zagreb, Croatia 101 Physics Department, Panjab University, Chandigarh, India 102 Physics Department, University of Jammu, Jammu, India 103 Physics Department, University of Rajasthan, Jaipur, India 104 Physikalisches Institut, Eberhard-Karls-Universität Tübingen, Tübingen, Germany 105 Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg, Germany 106 Physik Department, Technische Universität München, Munich, Germany 107 Politecnico di Bari and Sezione INFN, Bari, Italy 108 Research Division and ExtreMe Matter Institute EMMI, GSI Helmholtzzentrum für Schwerionenforschung GmbH, Darmstadt, Germany 109 Russian Federal Nuclear Center (VNIIEF), Sarov, Russia 110 Saha Institute of Nuclear Physics, Homi Bhabha National Institute, Kolkata, India 111 School of Physics and Astronomy, University of Birmingham, Birmingham, UK 112 Sección Física, Departamento de Ciencias, Pontificia Universidad Católica del Perú, Lima, Peru 113 St. Petersburg State University, St. Petersburg, Russia 114 Stefan Meyer Institut für Subatomare Physik (SMI), Vienna, Austria 115 SUBATECH, IMT Atlantique, Université de Nantes, CNRS-IN2P3, Nantes, France 116 Suranaree University of Technology, Nakhon Ratchasima, Thailand 117 Technical University of Košice, Košice, Slovakia 118 The Henryk Niewodniczanski Institute of Nuclear Physics, Polish Academy of Sciences, Kraków, Poland 119 The University of Texas at Austin, Austin, TX, USA 120 Universidad Autónoma de Sinaloa, Culiacán, Mexico 121 Universidade de São Paulo (USP), São Paulo, Brazil 122 Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil 123 Universidade Federal do ABC, Santo Andre, Brazil 124 University of Cape Town, Cape Town, South Africa 123 Eur. Phys. J. C (2021) 81:945 Page 21 of 21 945 125 University of Houston, Houston, TX, USA 126 University of Jyväskylä, Jyväskylä, Finland 127 University of Kansas, Lawrence, KS, USA 128 University of Liverpool, Liverpool, UK 129 University of Science and Technology of China, Hefei, China 130 University of South-Eastern Norway, Tonsberg, Norway 131 University of Tennessee, Knoxville, TN, USA 132 University of the Witwatersrand, Johannesburg, South Africa 133 University of Tokyo, Tokyo, Japan 134 University of Tsukuba, Tsukuba, Japan 135 Université Clermont Auvergne, CNRS/IN2P3, LPC, Clermont-Ferrand, France 136 Université de Lyon, CNRS/IN2P3, Institut de Physique des 2 Infinis de Lyon , Lyon, France 137 Université de Strasbourg, CNRS, IPHC UMR 7178, 67000 Strasbourg, France 138 Départment de Physique Nucléaire (DPhN), Université Paris-Saclay Centre d’Etudes de Saclay (CEA), IRFU, Saclay, France 139 Università degli Studi di Foggia, Foggia, Italy 140 Università di Brescia, Brescia, Italy 141 Variable Energy Cyclotron Centre, Homi Bhabha National Institute, Kolkata, India 142 Warsaw University of Technology, Warsaw, Poland 143 Wayne State University, Detroit, MI, USA 144 Westfälische Wilhelms-Universität Münster, Institut für Kernphysik, Münster, Germany 145 Wigner Research Centre for Physics, Budapest, Hungary 146 Yale University, New Haven, CT, USA 147 Yonsei University, Seoul, Republic of Korea aAlso at: Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Bologna, Italy bAlso at: Dipartimento DET del Politecnico di Torino, Turin, Italy cAlso at: M.V. Lomonosov Moscow State University, D.V. Skobeltsyn Institute of Nuclear Physics, Moscow, Russia dAlso at: Department of Applied Physics, Aligarh Muslim University, Aligarh, India eAlso at: Institute of Theoretical Physics, University of Wroclaw, Poland fDeceased 123