2022 059 22 March

High-$p_{\rm T}$ charged-particle production using event topology in pp, p–Pb
and Pb–Pb ALICE Collaboration††thanks: See Appendix A for the list of
collaboration members ALICE Collaboration

This letter reports measurements which characterize the underlying event
associated with hard scatterings at mid-pseudorapidity ($|\eta|<0.8$) in pp,
p–Pb and Pb–Pb collisions at centre-of-mass energy per nucleon pair,
$\sqrt{s_{\rm NN}}=5.02$ TeV. The measurements are performed with ALICE at the
LHC. Different multiplicity classes are defined based on the event activity
measured at forward rapidities. The hard scatterings are identified by the
leading particle defined as the charged particle with the largest transverse
momentum ($p_{\rm T}$) in the collision and having $8$ $<p_{\rm T}<15$
GeV/$c$. The $p_{\rm T}$ spectra of associated particles ($0.5$ $\leq p_{\rm
T}<6$ GeV/$c$) are measured in different azimuthal regions defined with
respect to the leading particle direction: toward, transverse, and away. The
associated charged particle yields in the transverse region are subtracted
from those of the away and toward regions. The remaining jet-like yields are
reported as a function of the multiplicity measured in the transverse region.
The measurements show a suppression of the jet-like yield in the away region
and an enhancement of high-$p_{\rm T}$ associated particles in the toward
region in central Pb–Pb collisions, as compared to minimum-bias pp collisions.
These observations are consistent with previous measurements that used two-
particle correlations, and with an interpretation in terms of parton energy
loss in a high-density quark gluon plasma. These yield modifications vanish in
peripheral Pb–Pb collisions and are not observed in either high-multiplicity
pp or p–Pb collisions.

##  1 Introduction

In proton-proton (pp) collisions, jets, originating from partonic scatterings
with large momentum transfer, are accompanied by particles produced by
initial- and final-state radiation (ISR and FSR, respectively), as well as, by
a plethora of other mechanisms. These include proton break-up, and, in a
scenario incorporating multi-parton interactions (MPI) [1, 2], several semi-
hard parton-parton scatterings in a single pp collision. These jet-
accompanying particles experimentally make up the underlying event (UE) and
are commonly studied via azimuthal separations from the jets to minimise the
influence of hard scatterings. The present study follows the strategy
originally introduced by the CDF collaboration [3]. First, the leading charged
particle in the event is found, i.e., the charged particle with the highest
transverse momentum in the collision ($p_{\mathrm{T}}^{\rm trig}$). Secondly,
the associated particles ($p_{\mathrm{T}}~{}$<$p_{\mathrm{T}}^{\rm trig}$) are
measured in three topological regions depending on their azimuthal angle
relative to the leading particle,
$|\Delta\varphi|=|\varphi^{\mathrm{assoc}}-\varphi^{\mathrm{trig}}|$, see Fig.
1.

Figure 1: (colour online) Illustration of toward, away and transverse regions
with respect to the leading particle in a collision.

The toward region contains the primary jet within the acceptance of the
detector, while the away region contains the back-scattered particles of the
recoil jet [4]. In contrast, the transverse region is dominated by the
underlying-event dynamics, but it also includes contributions from ISR and FSR
[5].

The measurements performed at RHIC and LHC in small systems (pp, p–A, and d–A
collisions) have shown for high particle multiplicities similar phenomena as
were originally observed only in A–A collisions and have been attributed there
to the formation of the strongly interacting quark gluon plasma [6, 7],
namely, long range angular correlations and collectivity [8]. The origin of
these effects in small systems is still an open question; on one hand,
hydrodynamical calculations describe some aspects of the data [9]; on the
other hand, mechanisms like colour reconnection [10], rope hadronisation [11],
and string shoving [12] can produce collective-like effects in Monte Carlo
event generators such as PYTHIA 8 [13]. Thus, investigating pp collisions as a
function of the charged particle multiplicity has become ever more pertinent
[9, 14, 15, 16, 17, 18]. The interpretation of the results from the analysis
of high-multiplicity pp collisions is challenging due to the selection biases
of the sample towards events in which partonic scatterings with large momentum
transfer (hard scatterings) occurred. To mitigate this inherent bias, Martin
_et al._ [19] suggested to use the charged-particle multiplicity in the
transverse region ($N_{\mathrm{ch}}^{\mathrm{T}}$) as a classifier of the
activity in the collisions, since the correlation between
$N_{\mathrm{ch}}^{\mathrm{T}}$ and the hardest scattering in the collision is
small. The ALICE collaboration has reported the first
$N_{\mathrm{ch}}^{\mathrm{T}}$ spectra measured in pp collisions at centre-of-
mass energy, $\sqrt{s}=13$ TeV [20]. Event generators, such as PYTHIA 8 [13]
and EPOS-LHC [21], do not provide a good description of the measured
distribution of the ratio $N_{\mathrm{ch}}^{\mathrm{T}}$/$\langle
N_{\mathrm{ch}}^{\mathrm{T}}\rangle$, where $\langle
N_{\mathrm{ch}}^{\mathrm{T}}\rangle$ is the event-averaged charged-particle
multiplicity in the transverse region, underestimating in particular the
number of collisions with large $N_{\mathrm{ch}}^{\mathrm{T}}$
$\big{(}>3\times\langle N_{\mathrm{ch}}^{\mathrm{T}}\rangle\big{)}$. In the
framework of MPI-based models, like those implemented in PYTHIA 8 and HERWIG 7
[22], the probability for a hard scattering in the collision increases with
decreasing impact parameter111In event generators like PYTHIA 8 the impact
parameter profile is described by an overlap matter distribution of the two
incoming hadrons. between the colliding protons. Thus, requiring a
high-$p_{\mathrm{T}}~{}$particle (e.g., $p_{\mathrm{T}}^{\rm trig}>8$ GeV/$c$)
in a given pp collision biases the selection of collisions towards those with
a smaller impact parameter [23], which in turn biases the selection towards pp
collisions with more MPI [20]. This feature of the
$N_{\mathrm{ch}}^{\mathrm{T}}$-based analysis is important for the isolation
of potential MPI and colour reconnection effects, which according to PYTHIA 8,
produce effects resembling collective behaviour [10]. By construction, MPI and
colour reconnection effects are expected to be more relevant in the transverse
region than in the away and toward regions [24]. It is worth mentioning that
the MPI picture has been used to explain the $p_{\mathrm{T}}~{}$spectra in
p–Pb collisions and peripheral Pb–Pb collisions [25, 26, 27]. Studies, as a
function of $N_{\rm ch}^{\rm T}$, are therefore important to the understanding
of the effects observed in high-multiplicity pp collisions. Last but not
least, measurements of UE observables are also important to tune event
generators [28] that include hard partonic scatterings and MPI.

This letter reports the inclusive charged-particle transverse momentum spectra
in pp, p–Pb and Pb–Pb collisions at centre-of-mass energy per nucleon pair
$\sqrt{s_{\rm NN}}=5.02$ TeV containing a high-$p_{\mathrm{T}}~{}$leading
particle within the kinematic intervals $8$ $\leq~{}p_{\mathrm{T}}^{\rm
trig}<15$ GeV/$c$ and $|\eta|<0.8$. This guarantees the selection of
collisions in which the average activity in the transverse region is roughly
flat as a function of $p_{\mathrm{T}}^{\rm trig}$ [20], and therefore, any
additional selection on the charged particle multiplicity will only modulate
the UE activity. The measurements are performed considering different event
classes defined in terms of the multiplicity registered in the forward
detectors. The $p_{\mathrm{T}}~{}$spectra of associated charged particles
($0.5\leq p_{\rm T}<6$ GeV/$c$ and $|\eta|<0.8$) are measured in the toward,
away, and transverse regions as a function of the average charged particle
multiplicity in the transverse region. To further investigate the possible
modification of the particles produced in the hard scattering in pp, p–Pb, and
Pb–Pb collisions, the $p_{\mathrm{T}}~{}$distributions in the toward
(${\rm{d}}N_{\rm{ch}}^{\rm{t}}/{\rm{d}}p_{\rm T}$) and away
(${\rm{d}}N_{\rm{ch}}^{\rm{a}}/{\rm{d}}p_{\rm T}$) regions obtained after the
subtraction of the $p_{\mathrm{T}}~{}$spectra in the transverse region
(${\rm{d}}N_{\rm{ch}}^{\rm T}/{\rm{d}}p_{\rm T}$) are also reported. The
subtracted yields (${\rm{d}}N_{\rm{ch}}^{\rm{st,sa}}/{\rm{d}}p_{\rm T}$) are
further normalised to those measured in minimum-bias (MB) pp collisions,

$I_{X}^{\rm{t,a}}\equiv\frac{({\rm{d}}N_{\rm{ch}}^{\rm{t,a}}/{\rm{d}}p_{\rm
T}-{\rm{d}}N_{\rm{ch}}^{\rm T}/{\rm{d}}p_{\rm
T})|_{X}}{({\rm{d}}N_{\rm{ch}}^{\rm{t,a}}/{\rm{d}}p_{\rm
T}-{\rm{d}}N_{\rm{ch}}^{\rm T}/{\rm{d}}p_{\rm
T})|_{\rm{pp,MB}}}=\frac{({\rm{d}}N_{\rm{ch}}^{\rm{st,sa}}/{\rm{d}}p_{\rm
T})|_{X}}{({\rm{d}}N_{\rm{ch}}^{\rm{st,sa}}/{\rm{d}}p_{\rm
T})|_{\rm{pp,MB}}},$ (1)

where $X$ indicates the collision system and the event multiplicity class. In
this way, the hard process $p_{\mathrm{T}}~{}$spectra in the toward and away
regions are isolated, and thus allowing us to study possible modifications to
the produced particles due to medium effects in high-multiplicity pp, p–Pb,
and Pb–Pb collisions. In heavy-ion collisions, this ratio is sensitive to the
same effects which were studied using the $I_{\rm AA}$ quantity [29, 30, 31],
where jets produced in the early stage of the collision propagate through the
hot and dense quark–gluon plasma. Their interaction with the coloured medium
lead to parton-energy loss (jet quenching) [32] which, for example, results in
the suppression of the charged-particle yield at high $p_{\mathrm{T}}~{}$
[33], and the suppression of the high-$p_{\mathrm{T}}~{}$yield in the away
region [29, 30]. It is worth mentioning that jet quenching effects have not
been observed so far in small systems [33, 34].

##  2 Experiment and data analysis

This analysis is based on the data recorded by the ALICE apparatus during the
pp and Pb–Pb runs at $\sqrt{s_{\mathrm{NN}}}~{}$= 5.02 TeV in 2015, and the
p–Pb run at $\sqrt{s_{\mathrm{NN}}}~{}$= 5.02 TeV in 2016. The present study
uses the V0 detector, and the Silicon Pixel Detector (SPD) for triggering and
background rejection. The V0 consists of two arrays of scintillating tiles
placed on each side of the interaction point covering the full azimuthal
acceptance and the pseudorapidity intervals of 2.8 $<\eta<$ 5.1 (V0A) and -3.7
$<\eta<$ -1.7 (V0C). The SPD is the innermost part of the Inner Tracking
System (ITS) and it is the closest detector to the interaction point. It
consists of two cylindrical silicon pixel layers at radial distances of 3.9
and 7.6 cm from the beam line and the pseudorapidity coverages of the two
layers are $|\eta|<2$ and $|\eta|<1.4$, respectively. The data were collected
using a minimum-bias trigger, which required a signal in both V0A and V0C
detectors. The offline event selection was optimised to reject beam-induced
background in all collision systems by utilising the timing signals in the two
V0 detectors. In Pb–Pb collisions, the beam-induced background is further
suppressed by correlating the timing signals of the neutron zero degree
calorimeters, which are positioned on both sides of the interaction point at
112.5 m distance along the beam axis [35]. The signals from the zero degree
calorimeters are also used to suppress the contamination from electromagnetic
interactions. This is performed by requesting the coincidence of the signals
coming from both side zero degree calorimeters by which the background due to
single nucleus electromagnetic dissociation processes is excluded. A criterion
based on the offline reconstruction of multiple primary vertices in the SPD is
applied to reduce the pileup caused by multiple interactions in the same bunch
crossing [36]. The results presented in this letter are for minimum-bias
triggered pp collisions having at least one charged particle in the
pseudorapidity interval $|\eta|<1$ (INEL$>$0). The INEL$>$0 event class
corresponds to about 75% of the total inelastic cross section [37]. For pp and
Pb–Pb collisions, the sample is subdivided into different multiplicity classes
based on the total charge deposited in both V0 sub-detectors, which is termed
as V0M amplitude [38]. For p–Pb collisions, the sample is subdivided based on
the total charge deposited in V0A sub-detector (V0A amplitude) [39], which is
located in the Pb-going direction. The V0A estimator has been implemented in
previous measurements that used p–Pb data (see e.g. [40]). This allows for
comparisons with other observables for similar V0A multiplicity classes. To
ensure that a hard scattering took place in the collision, events are required
to have a trigger particle within $8\leq p_{\rm T}^{\rm trig}<15$ GeV/$c$. In
this $p_{\mathrm{T}}^{\rm trig}$ interval, the momentum resolution effects are
negligible on the extracted yields, and therefore, no $p_{\mathrm{T}}^{\rm
trig}$ resolution correction is applied. The total number of analysed
collisions before the trigger particle selection are about $10^{8}$, $10^{8}$,
and $10^{7}$ for pp, p–Pb, and Pb–Pb collisions, respectively.

The transverse momentum of particles is determined from measurements in the
central barrel with the ITS and the Time Projection Chamber (TPC). The ITS is
a tracking detector which consists of six cylindrical layers of silicon
detectors. The TPC is a cylindrical drift detector which covers a radial
distance of 85-247 cm from the beam axis and it has longitudinal dimension
extending from about -250 cm to +250 cm around the nominal interaction point.
Primary charged particles are measured in the pseudorapidity range of
$|\eta|<0.8$ and with $p_{\rm T}>0.5$ GeV/$c$, where $\eta$ is measured in the
laboratory frame for the three collision systems. The configuration for p–Pb
collisions with protons at 4 TeV energy colliding with Pb ions that have per-
nucleon energies of ($Z/A$) $\times$ 4 TeV $\sim$ 1.58 TeV results in a shift
in the rapidity of the nucleon–nucleon centre-of-mass system by 0.465 in the
direction of the proton beam (negative z-direction). Here $Z$ and $A$ are the
atomic and mass numbers of the Pb ion, respectively. Therefore, the detector
coverage $|\eta|<0.8$ corresponds to roughly $-0.3<|\eta_{\rm{cms}}|<1.3$ for
p–Pb collisions. The particles with mean proper lifetime larger than 1 cm/$c$,
which are either produced directly in the interaction or from decays of
particles with mean proper lifetime smaller than 1 cm/$c$ are termed as
primary particles [41]. The track selection follows a procedure similar to the
one described in Ref. [42] and only few specific details are reported here.
Tracks ($N_{\rm{tracks}}$) are required to have two hits in the ITS, out of
which at least one should be in either of the two innermost layers. The
geometrical track length $L$ is calculated in the TPC readout plane, excluding
the information from the pads at the sector boundaries ($\approx 3$ cm from
the sector edges). The trajectory lengths built from radial segments, i.e. the
crossed TPC pad rows, traversed in the TPC by a particle are required to be
larger than 85% of the geometrical track length. The pad rows are made of at
least 3 neighbouring individual observations (clusters), and their height
varies from 7.5 mm to 15 mm [43]. The trajectory lengths built from clusters
(one cluster per pad row) is required to be larger than $0.7\times L$. The
fraction of TPC clusters shared with another track is required to be lower
than 0.4. The fit quality for the ITS and TPC track points must satisfy
$\chi^{2}_{\mathrm{ITS}}/N_{\mathrm{hits}}<36$ and
$\chi^{2}_{\mathrm{TPC}}/N_{\mathrm{clusters}}<4$, respectively, where
$N_{\mathrm{hits}}$ and $N_{\mathrm{clusters}}$ are the numbers of hits in the
ITS and the number of clusters in the TPC, respectively. Only tracks with
$\chi^{2}_{{\rm TPC}-{\rm ITS}}<36$ are included in the analysis, where
$\chi^{2}_{{\rm TPC}-{\rm ITS}}$ is calculated comparing the track parameters
from the combined ITS and TPC track reconstruction to that derived only from
the TPC and constrained to the interaction point. The definition of
$\chi^{2}_{{\rm TPC}-{\rm ITS}}$ can be found in Ref. [44]. To reduce the
contamination from secondary particles, tracks are accepted if their distance-
of-closest-approach (DCA) to the reconstructed primary interaction vertex
satisfies in the longitudinal ($d_{\rm z}$) and transverse ($d_{\rm xy}$)
directions the conditions $d_{\rm z}<2$ cm and $d_{\rm{xy}}<0.018$ cm +
$0.035$ (cm$\times$GeV/$c$)$/p_{\rm T}$.

The measurement of the transverse momentum spectra of charged particles
follows the standard procedure of the ALICE collaboration [45, 42]. The raw
yields are corrected for efficiency and contamination from secondary
particles. The efficiency correction is calculated from Monte Carlo
simulations with GEANT3 [46] transport code, which made use of PYTHIA 8
(Monash) [28], EPOS-LHC [21] and HIJING [47] event generators for pp, p–Pb and
Pb–Pb collisions, respectively and incorporated a detailed description of the
detector material, geometry and response. Since the event generators do not
reproduce the relative abundances of different particle species in the real
data, the efficiency obtained from the simulations is re-weighted considering
the particle composition from data as outlined in [42]. A multi-component
template fit based on the DCA distributions from the simulation is used for
the estimation of secondary contamination [42].

The $p_{\mathrm{T}}~{}$spectra for the toward and away regions include
contributions from the jet fragmentation, ISR, and FSR, as well as, the
contribution from the underlying event. In order to increase the sensitivity
to the hardest process of the event, the particle yields measured in the
transverse region are subtracted from the corresponding yields in both the
toward and away regions: ${\rm{d}}N_{\rm{ch}}^{\rm{t,a}}/{\rm{d}}p_{\rm
T}-{\rm{d}}N_{\rm{ch}}^{\rm T}/{\rm{d}}p_{\rm T}$. This approach assumes that
the background (UE, ISR, and FSR) in the toward and away regions is similar to
the activity in the transverse region. However, one has to keep in mind that
in Pb–Pb collisions two-particle correlations are affected by anisotropic
transverse flow. In particular, the main contribution is due to the elliptic
flow, $v_{2}$, which is the second order coefficient in the Fourier expansion
of the azimuthal distribution of the particle momenta [48]. This elliptic
azimuthal anisotropy modulates the background according to:

$B(\Delta\varphi)=B_{0}\big{(}1+2V_{2}\cos{(2\Delta\varphi)}\big{)},$ (2)

where $V_{2}$ is approximately given by the product of anisotropic flow
coefficients for trigger and associated particles at their respective momenta
i.e. $V_{2}\approx v_{2}^{\rm trig}v_{2}^{\rm assoc}$. The existing $v_{2}$
measurements over a broad transverse momentum range [49] suggest that the
effect of the $v_{2}$ modulation of background should be more relevant in
semi-central Pb–Pb collisions. The effect is expected to be important at low
and intermediate transverse momenta and decreases for high transverse momentum
particles [30]. In the high-$p_{\mathrm{T}}~{}$region of interest for the jet
quenching studies, namely $p_{\mathrm{T}}~{}$$>4$ GeV/$c$, the effect of the
$v_{2}$ modulation is estimated to be small (about 5%) for Pb–Pb collisions.
Given that the $v_{2}$ effect is larger in Pb–Pb collisions than in pp and
p–Pb collisions, no correction for the $v_{2}$ modulation is applied for pp
and p–Pb collisions since its effect is smaller than the other sources of
systematic uncertainty.

The results are shown as a function of the average number of charged particles
in the transverse region $\langle N_{\rm ch}^{\rm T}\rangle$. The values of
$\langle N_{\rm ch}^{\rm T}\rangle$ are extracted in each multiplicity class
from the $N_{\rm{tracks}}$ distributions in the transverse region that are
corrected for detector effects using a Bayesian unfolding [50]. The Bayesian
unfolding requires the multiplicity response matrix, which is built from the
correlation between the measured multiplicity and the multiplicity at
generator level (without detector effects) in the transverse region. This has
been obtained from MC simulations which include the propagation of particles
through the detector using GEANT 3. As a crosscheck, the $\langle N_{\rm
ch}^{\rm T}\rangle$ values are also calculated by integrating the transverse
momentum distributions in the interval $0.5\leq p_{\rm T}<8$ GeV/$c$. The
difference between the results from the two strategies is assigned as the
systematic uncertainty on $\langle N_{\rm ch}^{\rm T}\rangle$, where the
effects related to the discrepancy between data and MC in the particle
composition and secondary contamination are considered. This uncertainty
amounts up to 3.5%, 4% and 6.5% for pp, p–Pb and Pb–Pb collisions,
respectively.

The systematic uncertainties related to the track selection criteria were
studied by repeating the analysis varying one-by-one the track selection
criteria [42, 45]. In particular, the upper limits of the track fit quality
parameters in the ITS ($\chi^{2}_{\rm{ITS}}/N_{\rm{hits}}$) and in the TPC
($\chi^{2}_{\rm{TPC}}/N_{\rm{clusters}}$) were varied in the ranges of 25–49
and 3–5, respectively. The maximum fraction of shared TPC clusters was varied
between 0.2 to 1 and the maximum $d_{\rm z}$ was varied between 1 and 5 cm
[42]. We have also quantified the impact of not including the ITS hit
requirement in the track selection. The systematic uncertainty on the primary
particle composition was estimated using a procedure similar to the one
described in [42]. To quantify the uncertainty due to the imperfect simulation
of the detector response, the track matching between the TPC and the ITS
information in the data and in the simulation were compared. To achieve this,
the fraction of secondary particles was rescaled according to fits to the
measured DCA distributions. After this rescaling, the agreement between data
and model was found to be within 3% for all collision systems. This value was
assigned as an additional systematic uncertainty [42].

Table 1: Contributions to the relative (%) systematic uncertainty on the $p_{\mathrm{T}}~{}$spectra of primary charged particles in pp, p–Pb, and Pb–Pb collisions at $\sqrt{s_{\mathrm{NN}}}~{}$$=$ 5.02 TeV. Just for illustration, the range in the table corresponds to the lowest and highest relative systematic uncertainty in the considered $p_{\mathrm{T}}~{}$range. The individual contributions are summed in quadrature to obtain the total uncertainty.  Source of uncertainty | pp | p–Pb | Pb–Pb
---|---|---|---
Track selection | 2.1–8.2 | 2.4–5.8 | 3.0–9.9
Particle composition | 0.3–1.8 | 0.5–1.9 | 0.3–2.4
Secondary particles | 0.0–0.4 | 0.0–2.4 | 0.0–1.9
Matching efficiency | 2.0–4.2 | 0.7–3.7 | 0.6–3.7
Total | 3.2–8.8 | 3.6–6.3 | 3.5–10.0
Total ($N_{\rm ch}$-dependent) | 2.0–4.5 | 1.7–4.0 | 1.1–3.7

The systematic uncertainty on the secondary particle contamination considers
the imperfection of the method (multi-component template fit) used to extract
the correction. The fit ranges were varied and the fit was repeated using
templates with two (primaries, secondaries) or three (primaries, secondaries
from material, secondaries from weak decays) components. The maximum spread
among these variations was assigned as the systematic uncertainty on the
secondary contamination. This contribution dominates at low $p_{\rm T}$. The
density of materials used in simulations of the experimental setup was varied
by $\pm$ 4.5% [35], resulting in a negligible systematic uncertainty in the
considered $p_{\rm T}$ range of 0.5 to 6.0 GeV/$c$. For the estimation of
total systematic uncertainty, all the above listed contributions were summed
in quadrature. The systematic uncertainties are independent of the difference
between the azimuthal angle of the associated particle and that of the trigger
particle. The estimated systematic uncertainties on the
$p_{\mathrm{T}}~{}$spectra significantly depend on $p_{\rm T}$, while the
dependence on the multiplicity classes is mild. The ranges of systematic
uncertainties in the three considered collision systems are reported in Table
1 for the various sources described above.

##  3 Results and discussion

The $p_{\mathrm{T}}~{}$spectra measured in the transverse region for pp, p–Pb,
and Pb–Pb collisions are shown in Fig. 2 (top panel). Results are presented
for different multiplicity classes. The ratios between the spectra in the
individual multiplicity classes and the MB (0$-$100%) one are shown in the
bottom panel. In the $p_{\mathrm{T}}~{}$range $0.5-6$ GeV/$c$, the ratios for
the highest multiplicity class (0$-$5%) are larger than unity and show an
increasing trend with increasing $p_{\mathrm{T}}~{}$at low
$p_{\mathrm{T}}~{}$($<2-3$ GeV/$c$) followed at higher $p_{\mathrm{T}}~{}$by a
slow decrease. Instead, for the lowest multiplicity classes (40$-$60% and
60$-$90%) the ratios are lower than unity and follow an opposite trend with
$p_{\rm T}$, decreasing at low $p_{\mathrm{T}}~{}$and increasing for
$p_{\mathrm{T}}~{}$$>3$ GeV/$c$. The behaviour of the ratios as a function of
the event activity is reminiscent of analogous ratios as a function of the
number of MPI in pp collisions simulated with PYTHIA 8, including colour
reconnection [51]. In particular, at $p_{\rm T}\approx 2-3$ GeV/$c$ the
$p_{\mathrm{T}}~{}$spectrum of pp collisions with large MPI activity exhibits
an enhancement with respect to the $p_{\mathrm{T}}~{}$spectrum of MB pp
collisions. The effect was not observed before in data because, in contrast to
the present analysis, the jet contribution was included in the
$p_{\mathrm{T}}~{}$spectra [45].

Figure 2: (colour online) Top panels: transverse momentum spectra of charged
particles in the transverse region for different multiplicity classes in pp
(left), p–Pb (middle) and Pb–Pb (right) collisions at $\sqrt{s_{\rm NN}}=5.02$
TeV. The $p_{\mathrm{T}}~{}$spectra are measured at mid pseudorapidity
($|\eta|<0.8$). Lower panels: Ratio of $p_{\mathrm{T}}~{}$spectra in different
multiplicity classes to the $p_{\mathrm{T}}~{}$spectrum in the 0$-$100%
multiplicity class for the corresponding collision systems. The statistical
and systematic uncertainties are shown by bars and boxes, respectively.

Figure 3: (colour online) Transverse momentum spectra of charged particles in
Toward-Transverse, ${\rm{d}}N_{\rm{ch}}^{\rm{st}}/{\rm{d}}p_{\rm T}$ (top
plot) and Away-Transverse, ${\rm{d}}N_{\rm{ch}}^{\rm{sa}}/{\rm{d}}p_{\rm T}$
(bottom plot) regions for different multiplicity classes in pp (left), p–Pb
(middle) and Pb–Pb (right) collisions at $\sqrt{s_{\rm NN}}=5.02$ TeV. The
$p_{\mathrm{T}}~{}$spectra are measured at mid pseudorapidity ($|\eta|<0.8$).
The lower panels of both plots show the ratio to minimum bias pp collisions.
The statistical and systematic uncertainties are shown by bars and boxes,
respectively.

The top (bottom) panel of Fig. 3 shows the charged particle yields for the
toward (away) region after the subtraction of the yields measured in the
transverse region in pp, p–Pb and Pb–Pb collisions. Results are compared with
the $p_{\mathrm{T}}~{}$spectra measured for MB pp collisions (0$-$100% V0M pp
event class) quantified with the ratio $I_{X}^{\rm{t,a}}$, as defined in Eq.
1. At low transverse momenta, $p_{\rm T}<4$ GeV/$c$, $I_{X}^{\rm{t,a}}$ is
close to unity in pp and p–Pb collisions. In contrast, $I_{X}^{\rm{t,a}}$ in
Pb–Pb collisions exhibits a strong multiplicity dependence over the whole
measured $p_{\mathrm{T}}~{}$interval. The $I_{X}^{\rm{t,a}}$ magnitude is
larger for semi-peripheral Pb–Pb collisions, the maximum is observed for
20$-$40% Pb–Pb collisions, and is smaller for the most central and most
peripheral classes. Given that the $v_{2}$ contribution is not subtracted from
the jet-like yields reported in Fig. 3, the centrality dependence of
$I_{X}^{\rm{t,a}}$ follows the behaviour of $v_{2}$ as a function of collision
centrality and particle $p_{\mathrm{T}}~{}$in Pb–Pb collisions at LHC energies
[52].

Figure 4: (colour online) The $I_{X}^{\rm t}$ (left) and $I_{X}^{\rm a}$
(right) as a function of $\langle N_{\rm ch}^{\rm T}\rangle$ in 4 $<p_{\rm
T}<$ 6 GeV/$c$ for different multiplicity classes in pp, p–Pb and Pb–Pb
collisions at $\sqrt{s_{\mathrm{NN}}}~{}$$=$ 5.02 TeV. Pb–Pb results are shown
assuming a flat background (filled markers), and assuming a $v_{2}$-modulated
background (empty markers). The statistical and systematic uncertainties are
shown by bars and boxes, respectively.

Figure 4 shows the measured values of $I_{\rm{X}}^{\rm{t,a}}$ in the
transverse momentum interval $4<p_{\rm T}<6$ GeV/$c$ as a function of the
average multiplicity in the transverse region for all the multiplicity classes
considered in pp, p–Pb and Pb–Pb collisions. The figure shows that, within
uncertainties, the $I_{\rm{X}}^{\rm{t,a}}$ values are close to unity for all
the multiplicity classes measured in pp and p–Pb collisions. This indicates
that effects induced by possible energy loss in these systems are not observed
within uncertainties. This result is consistent with previous studies of
nuclear modification factor [33] and hadron-jet recoil measurements [34]. By
contrast, for Pb–Pb collisions the $I_{\rm{X}}^{\rm{t,a}}$ values are
compatible to unity for peripheral collisions, and show a gradual enhancement
(reduction) with the increase in multiplicity for the toward (away) region.
The behaviour is the same for the $I_{\rm{X}}^{\rm{t,a}}$ values measured
either assuming a flat background or a $v_{2}$-modulated background. The
$v_{2}$-modulated background was estimated following the approach depicted in
Eq. 2 and using the $v_{2}$ data reported in [49]. This behaviour is
qualitatively similar to the di-hadron correlation results reported by the
STAR and ALICE collaborations [29, 30]. In Pb–Pb collisions,
$I_{\rm{X}}^{\rm{t}}$ provides information about the fragmenting jet leaving
the medium, while on the away side, $I_{\rm{X}}^{\rm{a}}$ reflects the
survival probability of the recoiling parton during passage through the
medium. Thus a suppression of $I_{\rm{X}}^{\rm{a}}$ would indicate that fewer
partons survive the passage through the medium and is expected from the strong
in-medium energy loss. On the other hand, the enhancement observed in the
toward region is also subject to medium effects. The ratio is sensitive to a)
a possible change of the fragmentation functions, b) a possible modification
of the quark to gluon jet ratio in the final state due to different coupling
with medium, and c) a possible bias on the parton spectrum due to trigger
particle selection. Moreover, given that $I_{X}^{\rm{t,a}}$ is sensitive to
the same effects as $I_{\rm AA}$, the interpretation of the results is similar
to that reported in [30]. It is likely that all three effects play a role
[30]. A detailed quantification of the contribution of each effect is beyond
the scope of the present paper.

Figure 5: (colour online) Comparison of the measured the $I_{X}^{\rm t}$
(left) and $I_{X}^{\rm a}$ (right) in 4 $<p_{\rm T}<$ 6 GeV/$c$ with model
predictions. The results are shown as a function of $\langle N_{\rm ch}^{\rm
T}\rangle$ for different multiplicity classes in pp (top panel), p–Pb (middle
panel) and Pb–Pb (bottom panel) collisions at $\sqrt{s_{\mathrm{NN}}}~{}$$=$
5.02 TeV. The red and magenta lines show the PYTHIA 8 (Monash) [28] and PYTHIA
8/Angantyr [28] predictions, respectively. The blue lines show the EPOS-LHC
[21] results. The statistical and systematic uncertainties are shown by bars
and boxes, respectively.

In order to get further insight into the effect, the measured
$I_{X}^{\rm{t,a}}$ values are compared in Fig. 5 with model predictions.
Following the similar treatment of the experimental data, for the models, the
total sample is subdivided into different V0M classes and the $\langle N_{\rm
ch}^{\rm T}\rangle$ is calculated for each class. For high-multiplicity pp
collisions, although $I_{X}^{\rm{t,a}}$ is close to unity, a small trend with
multiplicity is visible, which is not seen at similar multiplicities (20$-$90%
V0A) in p–Pb data. To understand the source of these slight deviations from
unity, the data are compared with the predictions from the PYTHIA 8 (Monash
tune [28]) and EPOS-LHC [21] event generators. In PYTHIA, the hadronization of
quarks is simulated using the Lund string fragmentation model [53]. Various
PYTHIA tunes have been developed through extensive comparison of Monte Carlo
distributions with the minimum-bias data from different experiments. The
Monash tune of PYTHIA 8 is tuned to LHC data and uses an updated set of
hadronization parameters compared to the previous tunes [28]. EPOS-LHC is
built on the Parton-Based Gribov Regge Theory. Utilising the colour exchange
mechanism of string excitation, the model is tuned to LHC data [21]. In this
model, a part of the collision system which has high parton densities becomes
a “core" region that evolves hydrodynamically as a quark–gluon plasma and it
is surrounded by a more dilute “corona" for which fragmentation occurs in the
vacuum. The upper panel of Fig. 5 shows $I_{X}^{\rm{t,a}}$ for different
multiplicity classes. The observed deviations from unity are reproduced by
PYTHIA 8 for both the toward and away regions. Given that PYTHIA 8 does not
incorporate any jet quenching mechanism, the origin of the effect in high
$\langle N_{\rm ch}^{\rm T}\rangle$ collisions is related to a remaining bias
towards harder fragmentation and more activity from initial and final state
radiation [54]. These effects enhance the high-$p_{\mathrm{T}}~{}$yield in the
toward region, and produce a broadening in the away region [55]. The EPOS-LHC
results in the away region are similar to both data and PYTHIA 8\. However,
for $I_{X}^{\rm{t}}$ EPOS-LHC exhibits a trend with a maximum at intermediate
multiplicity and a reduction toward low and high multiplicities, which is not
consistent with the measurements.

The middle and bottom panels of Fig. 5 show $I_{X}^{\rm{t,a}}$ measured for
p–Pb and Pb–Pb collisions, respectively. The data are compared to PYTHIA
8/Angantyr [56] and EPOS-LHC predictions. The Angantyr model in PYTHIA 8
extrapolates the dynamics from pp collisions to p–Pb and Pb–Pb collisions,
generalising the formalism adopted for pp collisions by including a
description of the nucleon positions within the colliding nuclei and utilising
the Glauber model to calculate the number of interacting nucleons and binary
nucleon–nucleon collisions. PYTHIA 8/Angantyr, which does not include jet
quenching effects, predicts $I_{X}^{\rm{t,a}}$ values consistent with unity
for all the multiplicity classes in Pb–Pb collisions. Whereas for p–Pb
collisions $I_{X}^{\rm{a}}$ is consistent with unity, and $I_{X}^{\rm{t}}$ is
slightly below unity. In EPOS-LHC, a certain $p_{\mathrm{T}}~{}$cutoff is
defined in such a way that, above this cutoff, a particle loses part of its
momentum in the core but survives as an independent particle produced by a
flux tube. Soft particles, which are below the $p_{\mathrm{T}}~{}$cutoff, get
completely absorbed and form the core. This sort of energy loss mechanism
implemented in EPOS-LHC depends on the system size [21, 57, 58]. Figure 5
(middle) shows that for p–Pb collisions, EPOS-LHC does not describe either the
magnitude or the trend of the multiplicity dependence of the measured ratio in
the toward region, $I_{X}^{\rm{t}}$. However, the model is in reasonable
agreement with data in the away region. For Pb–Pb collisions, EPOS-LHC
predicts a significant enhancement of $I_{X}^{\rm{t,a}}$ for low $\langle
N_{\rm ch}^{\rm T}\rangle$ ranges and deviates significantly from the
experimental results.

In summary, while the data from Pb–Pb collisions are in qualitative agreement
with expectations from parton energy loss due to the presence of a hot and
dense medium, pp and p–Pb data do not show any hint of medium effects in the
multiplicity range which is reported.

##  4 Summary

The transverse momentum spectra ($0.5\leq p_{\rm T}<6$ GeV/$c$) of primary
charged particles in three azimuthal regions (toward, away and transverse)
defined with respect to the direction of the particle with the highest
transverse momentum in the event ($8\leq p_{\rm T}^{\rm trig}<15$ GeV/$c$) are
reported. The spectra are studied in intervals of the multiplicity measured at
forward pseudorapidities for pp, p–Pb, and Pb–Pb collisions at $\sqrt{s_{\rm
NN}}=5.02$ TeV. The $p_{\mathrm{T}}~{}$spectra in the transverse region are
subtracted from those of the away and toward regions. This is based on the
assumption that the transverse side provides a good estimation of the
underlying event contribution in both the toward and away regions. However,
for the interpretation of the results one has to keep in mind that $v_{2}$
modulates the background and this effect is important for semi-central Pb–Pb
collisions and for $p_{\rm T}>4$ GeV/$c$ the effect is less than 5% in central
and peripheral Pb–Pb collisions. Ratios to MB pp ($I_{X}^{\rm{t,a}}$), i.e.,
the multiplicity dependent yields normalised to the yield measured in MB pp
collisions, are reported. At low transverse momentum ($p_{\rm T}<2$ GeV/$c$),
within 20%, the $I_{X}^{\rm{t,a}}$ values are multiplicity independent for
both the toward and away regions in pp and p–Pb collisions. In contrast, in
Pb–Pb collisions for both toward and away regions the $I_{X}^{\rm{t,a}}$
values exhibit a centrality dependence which is expected given the residual
presence of elliptic flow. In the highest transverse momentum interval
($4<p_{\rm T}<6$ GeV/$c$), the $I_{X}^{\rm{t,a}}$ values in pp collisions are
closer to unity but they exhibit a small reduction (increase) towards high V0
activity in pp collisions. This trend is well reproduced by PYTHIA 8\. In the
model, it is due to a selection bias towards pp collisions with harder
fragmentation and larger activity from initial and final state radiation. For
p–Pb collisions, within uncertainties, the $I_{X}^{\rm{t,a}}$ values are
consistent with unity and do not show a multiplicity dependence. PYTHIA
8/Angantyr fairly describes $I_{X}^{\rm{a}}$, but it underestimates by about
10% the $I_{X}^{\rm{t}}$ values in the low multiplicity classes (40$-$90% V0A
event class). For Pb–Pb collisions, the $I_{X}^{\rm{t,a}}$ values are close to
unity for peripheral collisions, and show a gradual increase (reduction) in
the toward (away) region with increasing multiplicity. A similar observable,
$I_{\rm{AA}}$, based on the per-trigger yield of associated particles in di-
hadron correlation has been studied for central and peripheral Pb–Pb
collisions at $\sqrt{s_{\rm NN}}=2.76$ TeV. The behaviour of
$I_{X}^{\rm{t,a}}$ exhibits the same features as $I_{\rm{AA}}$: in central
collisions, on the away-side, a suppression is observed as expected from
strong in-medium energy loss. In the toward region, an enhancement is
observed. PYTHIA 8/Angantyr predicts $I_{X}^{\rm{t,a}}\approx 1$ for all
multiplicity intervals, and it does not reproduce the observed away-side
suppression or toward-side enhancement. Generally, EPOS-LHC does not describe
the measured $I_{X}^{\rm{t,a}}$ ratios.

In summary, within the multiplicity reach reported in this paper, no jet
quenching effects are observed in pp and p–Pb collisions within uncertainties.
Further studies are required to extend the present analysis to higher
multiplicities, which are currently limited by the event selection based on
the forward V0 detector. The analysis of future pp and p–Pb collisions with
much larger integrated luminosity may remove this limitation.

## Acknowledgements

The ALICE Collaboration would like to thank all its engineers and technicians for their invaluable contributions to the construction of the experiment and the CERN accelerator teams for the outstanding performance of the LHC complex. The ALICE Collaboration gratefully acknowledges the resources and support provided by all Grid centres and the Worldwide LHC Computing Grid (WLCG) collaboration. The ALICE Collaboration acknowledges the following funding agencies for their support in building and running the ALICE detector: A. I. Alikhanyan National Science Laboratory (Yerevan Physics Institute) Foundation (ANSL), State Committee of Science and World Federation of Scientists (WFS), Armenia; Austrian Academy of Sciences, Austrian Science Fund (FWF): [M 2467-N36] and Nationalstiftung für Forschung, Technologie und Entwicklung, Austria; Ministry of Communications and High Technologies, National Nuclear Research Center, Azerbaijan; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Financiadora de Estudos e Projetos (Finep), Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) and Universidade Federal do Rio Grande do Sul (UFRGS), Brazil; Bulgarian Ministry of Education and Science, within the National Roadmap for Research Infrastructures 2020-2027 (object CERN), Bulgaria; Ministry of Education of China (MOEC) , Ministry of Science & Technology of China (MSTC) and National Natural Science Foundation of China (NSFC), China; Ministry of Science and Education and Croatian Science Foundation, Croatia; Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN), Cubaenergía, Cuba; Ministry of Education, Youth and Sports of the Czech Republic, Czech Republic; The Danish Council for Independent Research | Natural Sciences, the VILLUM FONDEN and Danish National Research Foundation (DNRF), Denmark; Helsinki Institute of Physics (HIP), Finland; Commissariat à l’Energie Atomique (CEA) and Institut National de Physique Nucléaire et de Physique des Particules (IN2P3) and Centre National de la Recherche Scientifique (CNRS), France; Bundesministerium für Bildung und Forschung (BMBF) and GSI Helmholtzzentrum für Schwerionenforschung GmbH, Germany; General Secretariat for Research and Technology, Ministry of Education, Research and Religions, Greece; National Research, Development and Innovation Office, Hungary; Department of Atomic Energy Government of India (DAE), Department of Science and Technology, Government of India (DST), University Grants Commission, Government of India (UGC) and Council of Scientific and Industrial Research (CSIR), India; National Research and Innovation Agency - BRIN, Indonesia; Istituto Nazionale di Fisica Nucleare (INFN), Italy; Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) and Japan Society for the Promotion of Science (JSPS) KAKENHI, Japan; Consejo Nacional de Ciencia (CONACYT) y Tecnología, through Fondo de Cooperación Internacional en Ciencia y Tecnología (FONCICYT) and Dirección General de Asuntos del Personal Academico (DGAPA), Mexico; Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO), Netherlands; The Research Council of Norway, Norway; Commission on Science and Technology for Sustainable Development in the South (COMSATS), Pakistan; Pontificia Universidad Católica del Perú, Peru; Ministry of Education and Science, National Science Centre and WUT ID-UB, Poland; Korea Institute of Science and Technology Information and National Research Foundation of Korea (NRF), Republic of Korea; Ministry of Education and Scientific Research, Institute of Atomic Physics, Ministry of Research and Innovation and Institute of Atomic Physics and University Politehnica of Bucharest, Romania; Ministry of Education, Science, Research and Sport of the Slovak Republic, Slovakia; National Research Foundation of South Africa, South Africa; Swedish Research Council (VR) and Knut & Alice Wallenberg Foundation (KAW), Sweden; European Organization for Nuclear Research, Switzerland; Suranaree University of Technology (SUT), National Science and Technology Development Agency (NSTDA), Thailand Science Research and Innovation (TSRI) and National Science, Research and Innovation Fund (NSRF), Thailand; Turkish Energy, Nuclear and Mineral Research Agency (TENMAK), Turkey; National Academy of Sciences of Ukraine, Ukraine; Science and Technology Facilities Council (STFC), United Kingdom; National Science Foundation of the United States of America (NSF) and United States Department of Energy, Office of Nuclear Physics (DOE NP), United States of America. In addition, individual groups or members have received support from: Marie Skłodowska Curie, Strong 2020 - Horizon 2020, European Research Council (grant nos. 824093, 896850, 950692), European Union; Academy of Finland (Center of Excellence in Quark Matter) (grant nos. 346327, 346328), Finland; Programa de Apoyos para la Superación del Personal Académico, UNAM, Mexico.

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##  Appendix A The ALICE Collaboration

S. Acharya 124,131, D. Adamová 86, A. Adler69, G. Aglieri Rinella 32, M.
Agnello 29, N. Agrawal 50, Z. Ahammed 131, S. Ahmad 15, S.U. Ahn 70, I. Ahuja
37, A. Akindinov 139, M. Al-Turany 98, D. Aleksandrov 139, B. Alessandro 55,
H.M. Alfanda 6, R. Alfaro Molina 66, B. Ali 15, Y. Ali13, A. Alici 25, N.
Alizadehvandchali 113, A. Alkin 32, J. Alme 20, G. Alocco 51, T. Alt 63, I.
Altsybeev 139, M.N. Anaam 6, C. Andrei 45, A. Andronic 134, V. Anguelov 95, F.
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136, A. Augustinus 32, R. Averbeck 98, S. Aziz 72, M.D. Azmi 15, A. Badalà 52,
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Bratrud 63, P. Braun-Munzinger 98, M. Bregant 109, M. Broz 35, G.E. Bruno
97,31, M.D. Buckland 116, D. Budnikov 139, H. Buesching 63, S. Bufalino 29, O.
Bugnon103, P. Buhler 102, Z. Buthelezi 67,120, J.B. Butt13, A. Bylinkin 115,
S.A. Bysiak106, M. Cai 27,6, H. Caines 136, A. Caliva 98, E. Calvo Villar 101,
J.M.M. Camacho 108, R.S. Camacho44, P. Camerini 23, F.D.M. Canedo 109, M.
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V. Chibante Barroso 32, D.D. Chinellato 110, E.S. Chizzali II,96, J. Cho 57,
S. Cho 57, P. Chochula 32, P. Christakoglou 84, C.H. Christensen 83, P.
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73, Z. Conesa del Valle 72, G. Contin 23, J.G. Contreras 35, M.L. Coquet 127,
T.M. CormierI,87, P. Cortese 129,55, M.R. Cosentino 111, F. Costa 32, S.
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55, C. De Martin 23, S. De Pasquale 28, S. Deb 47, H.F. Degenhardt109, K.R.
Deja132, R. Del Grande 96, L. Dello Stritto 28, W. Deng 6, P. Dhankher 18, D.
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C. Furget 73, A. Furs 139, J.J. Gaardhøje 83, M. Gagliardi 24, A.M. Gago 101,
A. Gal126, C.D. Galvan 108, P. Ganoti 78, C. Garabatos 98, J.R.A. Garcia 44,
E. Garcia-Solis 9, K. Garg 103, C. Gargiulo 32, A. Garibli81, K. Garner134,
E.F. Gauger 107, A. Gautam 115, M.B. Gay Ducati 65, M. Germain 103, S.K.
Ghosh4, M. Giacalone 25, P. Gianotti 48, P. Giubellino 98,55, P. Giubilato 27,
A.M.C. Glaenzer 127, P. Glässel 95, E. Glimos 119, D.J.Q. Goh76, V. Gonzalez
133, L.H. González-Trueba 66, S. Gorbunov38, M. Gorgon 2, L. Görlich 106, S.
Gotovac33, V. Grabski 66, L.K. Graczykowski 132, E. Grecka 86, L. Greiner 74,
A. Grelli 58, C. Grigoras 32, V. Grigoriev 139, S. Grigoryan 140,1, F. Grosa
32, J.F. Grosse-Oetringhaus 32, R. Grosso 98, D. Grund 35, G.G. Guardiano 110,
R. Guernane 73, M. Guilbaud 103, K. Gulbrandsen 83, T. Gunji 121, W. Guo 6, A.
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136, S.T. Heckel 96, E. Hellbär 98, H. Helstrup 34, T. Herman 35, G. Herrera
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32, C. Hughes 119, P. Huhn63, L.M. Huhta 114, C.V. Hulse 72, T.J. Humanic 88,
H. Hushnud99, A. Hutson 113, D. Hutter 38, J.P. Iddon 116, R. Ilkaev139, H.
Ilyas 13, M. Inaba 122, G.M. Innocenti 32, M. Ippolitov 139, A. Isakov 86, T.
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Jercic89, O. Jevons100, A.A.P. Jimenez 64, F. Jonas 87,134, P.G. Jones100,
J.M. Jowett 32,98, J. Jung 63, M. Jung 63, A. Junique 32, A. Jusko 100, M.J.
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B. Ketzer 42, A.M. Khan 6, S. Khan 15, A. Khanzadeev 139, Y. Kharlov 139, A.
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106, I. Králik 59, A. Kravčáková 37, L. Kreis98, M. Krivda 100,59, F. Krizek
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79, A. Kurepin 139, A.B. Kurepin 139, S. Kushpil 86, J. Kvapil 100, M.J. Kweon
57, J.Y. Kwon 57, Y. Kwon 137, S.L. La Pointe 38, P. La Rocca 26, Y.S. Lai74,
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P.F.T. Matuoka109, A. Matyja 106, C. Mayer 106, A.L. Mazuecos 32, F. Mazzaschi
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L. Musa 32, J. Musinsky 59, J.W. Myrcha 132, B. Naik 120, R. Nair 79, B.K.
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Zhou 83, J. Zhu 98,6, Y. Zhu6, G. ZinovjevI,3, N. Zurlo 130,54

## Affiliation Notes

I Deceased
II Also at: Max-Planck-Institut für Physik, Munich, Germany
III Also at: Italian National Agency for New Technologies, Energy and
Sustainable Economic Development (ENEA), Bologna, Italy
IV Also at: Dipartimento DET del Politecnico di Torino, Turin, Italy
V Also at: Department of Applied Physics, Aligarh Muslim University, Aligarh,
India
VI Also at: Institute of Theoretical Physics, University of Wroclaw, Poland
VII Also at: An institution covered by a cooperation agreement with CERN

## Collaboration Institutes

1 A.I. Alikhanyan National Science Laboratory (Yerevan Physics Institute)
Foundation, Yerevan, Armenia
2 AGH University of Science and Technology, Cracow, Poland
3 Bogolyubov Institute for Theoretical Physics, National Academy of Sciences
of Ukraine, Kiev, Ukraine
4 Bose Institute, Department of Physics and Centre for Astroparticle Physics
and Space Science (CAPSS), Kolkata, India
5 California Polytechnic State University, San Luis Obispo, California, United
States
6 Central China Normal University, Wuhan, China
7 Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN), Havana,
Cuba
8 Centro de Investigación y de Estudios Avanzados (CINVESTAV), Mexico City and
Mérida, Mexico
9 Chicago State University, Chicago, Illinois, United States
10 China Institute of Atomic Energy, Beijing, China
11 Chungbuk National University, Cheongju, Republic of Korea
12 Comenius University Bratislava, Faculty of Mathematics, Physics and
Informatics, Bratislava, Slovak Republic
13 COMSATS University Islamabad, Islamabad, Pakistan
14 Creighton University, Omaha, Nebraska, United States
15 Department of Physics, Aligarh Muslim University, Aligarh, India
16 Department of Physics, Pusan National University, Pusan, Republic of Korea
17 Department of Physics, Sejong University, Seoul, Republic of Korea
18 Department of Physics, University of California, Berkeley, California,
United States
19 Department of Physics, University of Oslo, Oslo, Norway
20 Department of Physics and Technology, University of Bergen, Bergen, Norway
21 Dipartimento di Fisica, Università di Pavia, Pavia, Italy
22 Dipartimento di Fisica dell’Università and Sezione INFN, Cagliari, Italy
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,
Padova, Italy
28 Dipartimento di Fisica ‘E.R. Caianiello’ dell’Università and Gruppo
Collegato INFN, Salerno, Italy
29 Dipartimento DISAT del Politecnico and Sezione INFN, Turin, Italy
30 Dipartimento di Scienze MIFT, Università di Messina, Messina, Italy
31 Dipartimento Interateneo di Fisica ‘M. Merlin’ and Sezione INFN, Bari,
Italy
32 European Organization for Nuclear Research (CERN), Geneva, Switzerland
33 Faculty of Electrical Engineering, Mechanical Engineering and Naval
Architecture, University of Split, Split, Croatia
34 Faculty of Engineering and Science, Western Norway University of Applied
Sciences, Bergen, Norway
35 Faculty of Nuclear Sciences and Physical Engineering, Czech Technical
University in Prague, Prague, Czech Republic
36 Faculty of Physics, Sofia University, Sofia, Bulgaria
37 Faculty of Science, P.J. Šafárik University, Košice, Slovak Republic
38 Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe-
Universität Frankfurt, Frankfurt, Germany
39 Fudan University, Shanghai, China
40 Gangneung-Wonju National University, Gangneung, Republic of Korea
41 Gauhati University, Department of Physics, Guwahati, India
42 Helmholtz-Institut für Strahlen- und Kernphysik, Rheinische Friedrich-
Wilhelms-Universität Bonn, Bonn, Germany
43 Helsinki Institute of Physics (HIP), Helsinki, Finland
44 High Energy Physics Group, Universidad Autónoma de Puebla, Puebla, Mexico
45 Horia Hulubei National Institute of Physics and Nuclear Engineering,
Bucharest, Romania
46 Indian Institute of Technology Bombay (IIT), Mumbai, India
47 Indian Institute of Technology Indore, Indore, India
48 INFN, Laboratori Nazionali di Frascati, Frascati, Italy
49 INFN, Sezione di Bari, Bari, Italy
50 INFN, Sezione di Bologna, Bologna, Italy
51 INFN, Sezione di Cagliari, Cagliari, Italy
52 INFN, Sezione di Catania, Catania, Italy
53 INFN, Sezione di Padova, Padova, Italy
54 INFN, Sezione di Pavia, Pavia, Italy
55 INFN, Sezione di Torino, Turin, Italy
56 INFN, Sezione di Trieste, Trieste, Italy
57 Inha University, Incheon, Republic of Korea
58 Institute for Gravitational and Subatomic Physics (GRASP), Utrecht
University/Nikhef, Utrecht, Netherlands
59 Institute of Experimental Physics, Slovak Academy of Sciences, Košice,
Slovak Republic
60 Institute of Physics, Homi Bhabha National Institute, Bhubaneswar, India
61 Institute of Physics of the Czech Academy of Sciences, Prague, Czech
Republic
62 Institute of Space Science (ISS), Bucharest, Romania
63 Institut für Kernphysik, Johann Wolfgang Goethe-Universität Frankfurt,
Frankfurt, Germany
64 Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México,
Mexico City, Mexico
65 Instituto de Física, Universidade Federal do Rio Grande do Sul (UFRGS),
Porto Alegre, Brazil
66 Instituto de Física, Universidad Nacional Autónoma de México, Mexico City,
Mexico
67 iThemba LABS, National Research Foundation, Somerset West, South Africa
68 Jeonbuk National University, Jeonju, Republic of Korea
69 Johann-Wolfgang-Goethe Universität Frankfurt Institut für Informatik,
Fachbereich Informatik und Mathematik, Frankfurt, Germany
70 Korea Institute of Science and Technology Information, Daejeon, Republic of
Korea
71 KTO Karatay University, Konya, Turkey
72 Laboratoire de Physique des 2 Infinis, Irène Joliot-Curie, Orsay, France
73 Laboratoire de Physique Subatomique et de Cosmologie, Université Grenoble-
Alpes, CNRS-IN2P3, Grenoble, France
74 Lawrence Berkeley National Laboratory, Berkeley, California, United States
75 Lund University Department of Physics, Division of Particle Physics, Lund,
Sweden
76 Nagasaki Institute of Applied Science, Nagasaki, Japan
77 Nara Women’s University (NWU), Nara, Japan
78 National and Kapodistrian University of Athens, School of Science,
Department of Physics , Athens, Greece
79 National Centre for Nuclear Research, Warsaw, Poland
80 National Institute of Science Education and Research, Homi Bhabha National
Institute, Jatni, India
81 National Nuclear Research Center, Baku, Azerbaijan
82 National Research and Innovation Agency - BRIN, Jakarta, Indonesia
83 Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark
84 Nikhef, National institute for subatomic physics, Amsterdam, Netherlands
85 Nuclear Physics Group, STFC Daresbury Laboratory, Daresbury, United Kingdom
86 Nuclear Physics Institute of the Czech Academy of Sciences, Husinec-Řež,
Czech Republic
87 Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States
88 Ohio State University, Columbus, Ohio, United States
89 Physics department, Faculty of science, University of Zagreb, Zagreb,
Croatia
90 Physics Department, Panjab University, Chandigarh, India
91 Physics Department, University of Jammu, Jammu, India
92 Physics Department, University of Rajasthan, Jaipur, India
93 Physics Program and International Institute for Sustainability with Knotted
Chiral Meta Matter (SKCM2), Hiroshima University, Hiroshima, Japan
94 Physikalisches Institut, Eberhard-Karls-Universität Tübingen, Tübingen,
Germany
95 Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg,
Germany
96 Physik Department, Technische Universität München, Munich, Germany
97 Politecnico di Bari and Sezione INFN, Bari, Italy
98 Research Division and ExtreMe Matter Institute EMMI, GSI Helmholtzzentrum
für Schwerionenforschung GmbH, Darmstadt, Germany
99 Saha Institute of Nuclear Physics, Homi Bhabha National Institute, Kolkata,
India
100 School of Physics and Astronomy, University of Birmingham, Birmingham,
United Kingdom
101 Sección Física, Departamento de Ciencias, Pontificia Universidad Católica
del Perú, Lima, Peru
102 Stefan Meyer Institut für Subatomare Physik (SMI), Vienna, Austria
103 SUBATECH, IMT Atlantique, Nantes Université, CNRS-IN2P3, Nantes, France
104 Suranaree University of Technology, Nakhon Ratchasima, Thailand
105 Technical University of Košice, Košice, Slovak Republic
106 The Henryk Niewodniczanski Institute of Nuclear Physics, Polish Academy of
Sciences, Cracow, Poland
107 The University of Texas at Austin, Austin, Texas, United States
108 Universidad Autónoma de Sinaloa, Culiacán, Mexico
109 Universidade de São Paulo (USP), São Paulo, Brazil
110 Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil
111 Universidade Federal do ABC, Santo Andre, Brazil
112 University of Cape Town, Cape Town, South Africa
113 University of Houston, Houston, Texas, United States
114 University of Jyväskylä, Jyväskylä, Finland
115 University of Kansas, Lawrence, Kansas, United States
116 University of Liverpool, Liverpool, United Kingdom
117 University of Science and Technology of China, Hefei, China
118 University of South-Eastern Norway, Kongsberg, Norway
119 University of Tennessee, Knoxville, Tennessee, United States
120 University of the Witwatersrand, Johannesburg, South Africa
121 University of Tokyo, Tokyo, Japan
122 University of Tsukuba, Tsukuba, Japan
123 University Politehnica of Bucharest, Bucharest, Romania
124 Université Clermont Auvergne, CNRS/IN2P3, LPC, Clermont-Ferrand, France
125 Université de Lyon, CNRS/IN2P3, Institut de Physique des 2 Infinis de
Lyon, Lyon, France
126 Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000 Strasbourg, France,
Strasbourg, France
127 Université Paris-Saclay Centre d’Etudes de Saclay (CEA), IRFU, Départment
de Physique Nucléaire (DPhN), Saclay, France
128 Università degli Studi di Foggia, Foggia, Italy
129 Università del Piemonte Orientale, Vercelli, Italy
130 Università di Brescia, Brescia, Italy
131 Variable Energy Cyclotron Centre, Homi Bhabha National Institute, Kolkata,
India
132 Warsaw University of Technology, Warsaw, Poland
133 Wayne State University, Detroit, Michigan, United States
134 Westfälische Wilhelms-Universität Münster, Institut für Kernphysik,
Münster, Germany
135 Wigner Research Centre for Physics, Budapest, Hungary
136 Yale University, New Haven, Connecticut, United States
137 Yonsei University, Seoul, Republic of Korea
138 Zentrum für Technologie und Transfer (ZTT), Worms, Germany
139 Affiliated with an institute covered by a cooperation agreement with CERN
140 Affiliated with an international laboratory covered by a cooperation
agreement with CERN