2021 144 18 July

Very forward energy in pp and p–Pb collisions

ALICE Collaboration††thanks: See Appendix A for the list of collaboration
members ALICE Collaboration

The energy deposited at very forward rapidities (very forward energy) is a
powerful tool for characterising proton fragmentation in pp and p–Pb
collisions. The correlation of very forward energy with particle production at
midrapidity provides direct insights into the initial stages and the
subsequent evolution of the collision. Furthermore, the correlation with the
production of particles with large transverse momenta at midrapidity provides
information complementary to the measurements of the underlying event, which
are usually interpreted in the framework of models implementing centrality-
dependent multiple parton interactions.

Results about very forward energy, measured by the ALICE zero degree
calorimeters (ZDCs), and its dependence on the activity measured at
midrapidity in pp collisions at $\sqrt{s}=13$ TeV and in p–Pb collisions at
$\sqrt{s_{\rm{NN}}}=8.16$ TeV are discussed. The measurements performed in pp
collisions are compared with the expectations of three hadronic interaction
event generators: PYTHIA 6 (Perugia 2011 tune), PYTHIA 8 (Monash tune), and
EPOS LHC. These results provide new constraints on the validity of models in
describing the beam remnants at very forward rapidities, where perturbative
QCD cannot be used.

##  1 Introduction

During the last decade, the study of bulk properties of proton–proton (pp) and
proton–nucleus (pA) collisions at LHC energies has attracted increasing
interest. Effects expected to occur only in heavy-ion collisions, such as
collective fluid-like behaviour [1, 2] and strangeness enhancement [3], are
already seen in pp collisions. In particular, strangeness enhancement already
occurs at small multiplicity values. The strength of these effects increases
steadily with the final state multiplicity going from pp to p–Pb up to
peripheral Pb–Pb collisions. As a consequence, minimum-bias (MB) pp collisions
are currently being studied, focusing on the dependence of experimental
observables on the charged-particle multiplicity measured at midrapidity. In
phenomenological models inspired by quantum chromodynamics (QCD), high-
multiplicity pp and pA events are generated in collisions with smaller than
average impact parameter, $b$ (the distance between the centres of the two
colliding hadrons). In these central collisions, the number of partonic
interactions and, hence, the probability for partonic scatterings with large
momentum transfer, is enhanced. On the other hand, by requesting the
production of a particle with large transverse momentum, events with larger
than average multiplicity are selected [4]. In order to constrain the initial
state of pp and p–Pb collisions, the correlation between observables measured
in rapidity regions that are causally disconnected in the evolution of the
system following the collision are studied. In particular, this is the case
for the very forward (“zero degree”) energy and central rapidity particle
production. The study of these correlations also addresses the fundamental
question of how the energy of the colliding protons is transferred from beam
to central rapidities. In models where the initial state is described by the
impact parameter or initial matter overlap, an increased energy transfer
results naturally from the increased number of parton–parton scatterings.

The processes involved in forward hadron production at high energies are
crucial for simulations of high-energy cosmic-ray interactions [5].
Predictions from different models describing hadronic interactions suffer from
large uncertainties. Experimental results on the production of forward baryons
have therefore a key role in the simulation of cosmic-ray showers.
Measurements at colliders can provide unique information for the tuning of the
models. In particular, baryon production and remnant break-up have been
addressed as possible mechanism to explain the observed muon production at
ground level [6, 7].

At LHC energies, forward neutron production has been measured by the LHCf
collaboration [8, 9, 10]. In ALICE, the zero degree calorimeters (ZDCs)
measure the energy emitted at rapidities close to that of the beam, covering
the beam fragmentation regions. The very forward energy measured by the ZDCs
can be correlated with the charged-particle multiplicity and the probability
of producing a particle with a large transverse momentum, $p_{\rm T}$, at
midrapidity. Measurements of very forward energy as a function of the $p_{\rm
T}$ of the leading particle (the charged particle with the highest transverse
momentum) at midrapidity complement the studies of the underlying event (UE).
In the first case, particle production is related to an observable separated
in pseudorapidity, while in the UE measurement particle production is measured
in a region separated in azimuthal angle (“transverse region").

This article presents the first measurements of the dependence of the very
forward energy on midrapidity particle production in pp collisions at a
centre-of-mass energy $\sqrt{s}=13$ TeV and in p–Pb collisions at a centre-of-
mass-energy per nucleon pair $\sqrt{s_{\rm{NN}}}=8.16$ TeV. The article is
organised as follows: in Sec. 2 the main ALICE subsystems used for this
analysis are concisely described. The data sample, the event and track
selection criteria are discussed in Sec. 3. Section 4 presents results about
the production of energy at forward and backward rapidities in pp collisions.
In Sec. 5 results on the correlation between very forward energy and particle
production at midrapidity in pp and in p–Pb collisions are presented and
discussed, together with results on the forward leading-baryon production in
connection with the UE measurements in pp collisions.

##  2 ALICE detectors

A detailed description of the ALICE detector and its performance can be found
in Refs. [11, 12]. The sub-detectors used for the present analysis are the
inner tracking system (ITS), the time projection chamber (TPC) and the V0
detectors, all located inside a 0.5 T uniform magnetic field, and the ZDCs.

The silicon pixel detector (SPD) [11] makes up the two cylindrical innermost
layers of the ITS and consists of hybrid silicon pixel assemblies covering the
pseudorapidity range $|\eta|<2$ for the inner layer and $|\eta|<1.4$ for the
outer layer for collisions occurring at the nominal interaction point (IP).
The SPD is used to measure the charged-particle multiplicity at midrapidity
using tracklets, short track segments formed using information on the position
of the primary vertex and two hits, one on each of the SPD layers. To exploit
the full particle tracking, the four external layers of the ITS, composed by
two layers of silicon drift detectors (SDD) and two layers of double-sided
silicon micro-strip detectors (SSD), were also used. The TPC [13] is the main
tracking detector and it covers a pseudorapidity range of about $|\eta|<0.9$.
In order to avoid border effects, in this analysis the fiducial pseudorapidity
region has been restricted to $|\eta|<0.8$. Charged-particle tracks are formed
by combining the hits in the ITS and the reconstructed clusters in the TPC.
The trigger signal is provided by the V0 [14] counters, two arrays of 32
scintillator tiles each, covering the full azimuth within $-3.7<\eta<-1.7$ for
V0C, located on the same side as for the ALICE dimuon arm (C-side), and
$2.8<\eta<5.1$ for V0A, placed on the opposite side (A-side). An alternative
trigger condition can be provided by the ALICE diffractive (AD) detector [15],
a hodoscope of plastic scintillators covering the pseudorapidity ranges
$-7.0<\eta<-4.9$ and $4.8<\eta<6.3$.

The main detectors used in this analysis are the ZDCs. Two identical systems,
each comprising a neutron (ZN) and a proton (ZP) calorimeter of the
“spaghetti” type, are placed at $\pm$112.5 m from the ALICE IP, on both sides.
In nucleus–nucleus collisions, the ZDCs detect the energy carried by the non-
interacting (spectator) nucleons and they are used to estimate the centrality
of the collision [16]. In proton–nucleus collisions the ZDCs provide an
unbiased centrality selection [17]. In proton–proton collisions, the ZDCs are
usually switched off, not only to prevent their aging but also because the
typical beam conditions in pp data taking are characterised by large crossing
angles that drastically affect the ZDC acceptance. However, the acceptance of
ZN is not affected provided that the vertical half-crossing angle is smaller
than $+60\ \mu$rad for a nominal vertex vertical position on the LHC axis
($y_{\rm{vtx}}=0$ mm).

In pp collisions, the energy detected by ZN is mainly due to neutrons with a
contribution from photons at low energies, while the ZP signal is essentially
due to protons with a smaller contribution due to positive pions. The ZN
calorimeters cover the pseudorapidity range $|\eta|>8.8$ and within this range
they have a flat efficiency. For the ZP calorimeters the purely geometric
coverage, $6.5<|\eta|<7.4$, is not significant since the actual pseudorapidity
interval covered by ZP depends strongly on the LHC beam optics settings. The
covered pseudorapidity range has been studied through fast Monte Carlo (MC)
simulations taking into account the magnetic field settings and the
geometrical apertures of the LHC beam pipe element for pp collisions at
$\sqrt{s}=13$ TeV and found to be $7.8<|\eta|<12.9$. In Pb–Pb collisions and
in p–Pb collisions in the Pb-fragmentation region, the energy calibrations of
ZN and ZP spectra are performed using the narrow peaks from the detection of
single nucleons. Contrarily, in pp collisions and in p–Pb collisions in the
p-fragmentation region, there are no peaks in the spectra and there is no
reliable way to calibrate the spectra in energy units without introducing
model dependencies and large uncertainties. The use of self-normalised
quantities, namely signals normalised to their average minimum-bias value,
allows one to overcome this issue, since they coincide with the self-
normalised energy ratios and are therefore directly comparable to model
predictions.

The ZDCs are equipped with time-to-digital converters (TDCs) that register the
arrival time of particles depositing energy in the detectors, allowing the
rejection of events without signal in the calorimeters (noise). The event
selection fractions for both ZN and ZP are defined as the ratios between the
number of events with a signal in the corresponding TDC and the number of MB
events triggered by ALICE. The event selection fractions values calculated for
the two colliding systems are given in Table 1.

Table 1: ZN and ZP event selection fractions (see text for details) in pp and p–Pb collisions. For the p–Pb colliding system, both the Pb-fragmentation (Pb) and the p-fragmentation (p) sides are reported. [.5]() | pp $\sqrt{s}=$ 13 TeV | p–Pb $\sqrt{s_{\rm{NN}}}=8.16$ TeV
---|---|---
ZN | 61% | 96% (Pb) 43% (p)
ZP | 23% | 82% (Pb) 15% (p)

##  3 Data samples, event selection and models

During the 2015 pp data taking at $\sqrt{s}=13$ TeV, the ZDCs were switched on
when a limited half-crossing angle of $+45~{}\mu$rad in the vertical plane was
applied. As discussed in the previous section, this configuration guaranteed
that all the neutrons emitted at very forward rapidities were within the ZN
geometric acceptance. Data from p–Pb collisions, collected in 2016 at centre-
of-mass energy $\sqrt{s_{\rm{NN}}}=8.16$ TeV, were used to study the forward
energy on the p-fragmentation side in pA collisions. The proton beam energy
was the same as in pp collisions, therefore comparing the very forward energy
in the p-fragmentation side in p–Pb collision to the one detected in pp
collisions provides useful information on the proton breakup.

In both collision systems, a MB trigger condition, requiring at least one hit
in both V0 detectors, was applied. The V0 timing information was used offline
to reject beam–gas interactions. Events with more than one reconstructed
primary interaction vertex (pile-up) were rejected. The selected events were
required to have a reconstructed collision vertex with a position along the
beam axis $|z_{\rm{vtx}}|<10$ cm to ensure a uniform performance for
midrapidity detectors. After applying these selections, about 4$\times 10^{7}$
MB events in pp collisions and 8.3$\times 10^{7}$ MB events in p–Pb collisions
were retained.

In the analysis of pp collisions, to study the transverse momentum of the
leading particle, tracks were reconstructed in $|\eta|<0.8$ (to guarantee that
all tracks have the maximal length) and more stringent selection criteria were
applied. In order to ensure good track momentum resolution, the reconstructed
tracks were required to have at least 70 reconstructed points (out of a
maximum of 159) in the TPC, and two hits in the ITS, with at least one in the
SPD. Finally, the $\chi^{2}$ per TPC reconstructed point was required to be
less than 4, and tracks originating from kink topologies of weak decays were
rejected. These conditions selected tracks with a transverse momentum $p_{\rm
T}$ $>0.15$ GeV/$c$.

The very forward energy was studied as a function of the charged-particle
multiplicity measured at midrapidity in two units of pseudorapidity. A primary
particle is a particle with a mean proper lifetime $\tau$ larger than 1
cm/$c$, which is either produced directly in the interaction, or from decays
of particles with $\tau$ smaller than 1 cm/$c$, excluding particles produced
in interactions with material [18]. In pp collisions the interval $|\eta|<1$,
centered around midrapidity, was considered. In p–Pb collisions, the
nucleon–nucleon centre-of-mass system moves with respect to the ALICE
laboratory system with a rapidity of $-0.465$ in the direction of the proton
beam. Therefore the pseudorapidity interval $-1.465<\eta<0.535$, covering two
units of pseudorapidity around midrapidity in the centre-of-mass system, is
used. The multiplicity selection is based on the number of tracklets measured
in the SPD in both collision systems, as described in Refs. [19, 20]. The
average charged-particle multiplicity values,
$\langle\mathrm{d}N_{\mathrm{ch}}/\mathrm{d}\eta\rangle$, are listed in Table
2 for each selected multiplicity interval.

Table 2: Charged-particle multiplicity classes based on the SPD tracklet
estimator and corresponding
$\langle\mathrm{d}N_{\mathrm{ch}}/\mathrm{d}\eta\rangle$ values in 2 units of
pseudorapidity around midrapidity, $|\eta|<1$ in pp collisions at 13 TeV [19]
and $-1.465<\eta<0.535$ in p–Pb collisions at 8.16 TeV [20]). The MB values
for the two colliding systems are given in the bottom rows.

Multiplicity | pp 13 TeV
---|---
[.5]() class | $\langle{\rm d}N_{\rm ch}/{\rm d}\eta\rangle_{|\eta|<1}$
[.5]() 00–1% | 33.29${}^{+0.57}_{-0.51}$
[.5]() 01–5% | 23.44${}^{+0.37}_{-0.33}$
[.5]() 05–10% | 18.25${}^{+0.28}_{-0.25}$
[.5]() 10–15% | 15.13${}^{+0.22}_{-0.20}$
[.5]() 15–20% | 12.88${}^{+0.19}_{-0.17}$
[.5]() 20–30% | 10.50${}^{+0.16}_{-0.14}$
[.5]() 30–40% |  08.18${}^{+0.12}_{-0.11}$
[.5]() 40–50% |  06.30${}^{+0.10}_{-0.09}$
[.5]() 50–70% |  04.13 $\pm$ 0.06
[.5]() 70–100% |  01.87 $\pm$ 0.04
[.5]() MB values |  07.47 $\pm$ 0.11

Multiplicity | p–Pb 8.16 TeV
---|---
[.5]() class | $\langle{\rm d}N_{\rm ch}/{\rm d}\eta\rangle_{-1.465<\eta<0.535}$
[.5]() 00–1% | 73.40 $\pm$ 1.95
[.5]() 01–5% | 56.00 $\pm$ 1.46
[.5]() 05–10% | 45.99 $\pm$ 1.20
[.5]() 10–15% | 39.93 $\pm$ 1.03
[.5]() 15–20% | 35.50 $\pm$ 0.93
[.5]() 20–30% | 30.35 $\pm$ 0.79
[.5]() 30–40% | 24.84 $\pm$ 0.65
[.5]() 40–50% | 20.13 $\pm$ 0.53
[.5]() 50–60% | 15.89 $\pm$ 0.31
[.5]() 60–70% | 11.81 $\pm$ 0.41
[.5]() 70–100% |  04.82 $\pm$ 0.15
[.5]() MB values | 20.79 $\pm$ 0.61

In addition, for p–Pb collisions a centrality selection based on ZN energy,
that is the most unbiased selection available [17], was used to compare data
at the two available centre-of-mass energies, $\sqrt{s_{\rm{NN}}}=$ 5.02 and
8.16 TeV.

Data from pp collisions are compared with MC simulations using PYTHIA 6
(Perugia 2011 tune) [21], PYTHIA 8 (Monash 2013 tune) [22] and EPOS LHC [23]
as event generators. The GEANT 3 [24] particle transport code was used to
track particles through the ALICE experimental set-up. PYTHIA 6.4 Perugia 2011
has a particular tune of the initial, final state showers and UE modelling. In
particular, the tuning of the beam remnant is done using MB observables such
as charged-particle multiplicity and transverse momentum spectra measured by
CDF. In this tune, some early LHC data were used for the tuning of beam
remnants. PYTHIA 8 Monash is the default tune of PYTHIA 8.1 which uses UE data
from the LHC, SPS and Tevatron to tune the parameters relevant for multi-
partonic interactions (MPI). No particular tune of the beam remnant is
implemented. EPOS LHC uses early LHC data for tuning. The particle production
has two main components: the strings composed of pomerons at midrapidity,
while the remnants carry the remaining energy covering mostly the
fragmentation region.

##  4 Forward–backward energy asymmetry in pp collisions

The emission of very forward energy can be investigated over a pseudorapidity
gap of more than 18 units using both ZDC systems, placed on the two sides
relative to the IP. The correlation between the energy emitted at forward and
backward rapidities in MB collisions is shown in Fig. 1, separately for ZN and
ZP. For both detectors the signals increase linearly with the detected energy,
without showing saturation or non-linear effects for large deposited energies.
In both cases, the detected energies show asymmetric features, namely a high
energy deposit on one side corresponds to a very low energy deposition on the
opposite side. In addition, a subset of the event sample is correlated, in
particular for neutron emission. The origin of the observed asymmetry in
energy at forward and backward rapidities was further investigated in MC
generators, without considering any tracking through the experimental set-up,
but selecting solely on particle kinematics. It was found that the energy
emitted at large rapidities becomes asymmetric once the phase space is
restricted to the pseudorapidity ranges covered by ZN and ZP detectors. In
conclusion, the observed asymmetry is an effect due to the limited and not
overlapping pseudorapidity ranges covered by the neutron and the proton
detectors.

Figure 1: A- vs. C-side signal in ZN (left) and ZP (right). The maximum at
(0,0) is normalised to unity, while the minimum is limited to $10^{-4}$.

Another way to gain insight into the correlation between energy emitted at
backward and forward rapidities is to study the average signal on one side as
a function of the signal on the other side. Results are shown in Fig. 2,
together with comparisons to model calculations. The energies carried by
leading protons in the two sides are not correlated, as was already observed
at lower energies at the ISR [25]. In contrast to this, the data indicate the
presence of a correlation between the energies carried by leading neutrons on
opposite sides, in particular at high energies. According to all the models
used for comparison, the background contribution from photons is relevant only
at very low energies (up to 1 TeV), while for higher energies the signal is
only due to leading neutrons. Models predict a flat behaviour for leading
protons in good agreement with data, while for neutrons, even though they show
some degree of correlation between the neutron energies, none of them is able
to reproduce quantitatively the measured dependence over the whole range.

Figure 2: Average A-side ZN (left) and ZP (right) signals as a function of the
C-side signals in pp collisions at $\sqrt{s}=$ 13 TeV. Data (red full circles)
are compared with model predictions from PYTHIA 6 (azure line), PYTHIA 8
(dashed blue line) and EPOS (dotted green line).

##  5 Forward energy as a function of charged-particle production at
midrapidity

From phenomenological models, one expects that selecting events characterised
by a larger than average multiplicity, or by the emission of a large
transverse momentum particle, corresponds to selecting collisions with a
smaller than average impact parameter [26, 27], and a larger than average
number of MPI [28]. The forward energy detected by the ZDCs was studied as a
function of the charged-particle multiplicity produced at midrapidity (in
$|\eta|<1$ for pp collisions at $\sqrt{s}=13$ TeV and $-1.465<\eta<0.535$ for
p–Pb collisions at $\sqrt{s_{\rm{NN}}}$ = 8.16 TeV), and as a function of the
leading particle transverse momentum, $p_{\rm T}^{\rm leading}$, in
$|\eta|<0.8$ in pp collisions. To study the interaction of a proton either
with another proton or with a Pb nucleus, the dependence of the very forward
energy on charged particle production at midrapidity was studied in both pp
and p–Pb collisions.

###  5.1 Very forward energy in p–Pb collisions

In p–Pb collisions, the p-fragmentation and the Pb-fragmentation sides show a
complementary behaviour as a function of centrality, as already described for
$\sqrt{s_{\rm{NN}}}=$ 5.02 TeV p–Pb collisions [17]. In Fig. 3, the self-
normalised ZN signals as a function of centrality, estimated through the
energy measured by the neutron calorimeter in the Pb-fragmentation region as
described in Ref. [17], are shown for the Pb-fragmentation and for the
p-fragmentation sides. Events characterised by a large multiplicity
(corresponding to central events) have a large forward energy deposit in the
Pb-fragmentation side and a small energy deposit in the p-fragmentation side.
This behaviour does not show a strong dependence on the collision energy.

Figure 3: ZN energy normalised to the average MB value in the Pb-fragmentation
(left) and in the p-fragmentation (right) regions as a function of centrality
estimated from ZN [17] in p–Pb collisions at $\sqrt{s_{\rm{NN}}}=5.02$ TeV
(pink circles) and $8.16$ TeV (blue squares). The boxes represent the
systematic uncertainty.

Figure 4: ZN energy normalised to the average MB value in the Pb-fragmentation
(left) and in the p-fragmentation (right) regions as a function of the average
$N_{\rm coll}$ in p–Pb collisions at $\sqrt{s_{\rm{NN}}}=5.02$ TeV (pink
circles) and $8.16$ TeV (blue squares). The boxes represent the systematic
uncertainty.

In Fig. 4, the normalised energies in the two fragmentation regions are shown
as a function of the number of binary nucleon–nucleon collisions, $N_{\rm
coll}$, calculated as described in Ref. [17]. The $N_{\rm coll}$ values are
included in Ref. [29] for both p–Pb colliding energies. It is interesting to
notice how the very forward energy in the p-fragmentation region is, not only
inversely dependent on centrality, but also decreases linearly with the number
of binary collisions over a wide range of centralities.

###  5.2 Forward energy dependence on charged-particle multiplicity at
midrapidity

The normalised ZN and ZP signals are compared, as a function of the self-
normalised charged-particle multiplicity measured at midrapidity in pp and in
the p-fragmentation region in p–Pb collisions, in Fig. 5. In pp collisions the
ZDC self-normalised values are averaged between the two p-fragmentation sides,
while for p–Pb collisions two different data taking periods with inverted beam
directions were averaged.

Figure 5: ZN (left) and ZP (right) self-normalised signals as a function of
the normalised multiplicity measured in 2 units of $\eta$ around the centre-
of-mass midrapidity in pp (red circles) collisions and in the p-fragmentation
region in p–Pb (blue squares) collisions. The boxes represent systematic
uncertainties.

For pp collisions, two sources of systematic uncertainty were considered: the
trigger selection and the difference between the measurements performed on
both sides. The first contribution was estimated using a different trigger
selection based on the AD detector, which removed some residual contribution
from single-diffractive events (estimated to be below 3‰ at 8 TeV[30]). This
uncertainty ranges from $2\%$ to $5\%$ for ZN and from $2\%$ to $6\%$ for ZP.
The uncertainty coming from considering the energy measured in two sides
ranges from $0.3\%$ to $1\%$ for ZN and from $0.1\%$ to $1\%$ for ZP. The
total uncertainty is calculated as the sum in quadrature of the two
contributions, and ranges from 2% to 5% for ZN and from 2% to 6% for ZP. In
p–Pb collisions, the difference between the two beam configurations was
considered as a source of systematic uncertainty, and it ranges from $0.4\%$
to $4\%$ for ZN and $0.1\%$ to $28\%$ for ZP. The higher uncertainty values
correspond to higher multiplicity bins, where the ZP signal is small, and this
leads to a small absolute uncertainty value. The dependence of the detected
forward energy on midrapidity multiplicity shows similar features in pp and in
the p-fragmentation region in p–Pb collisions: the higher is the activity
measured at midrapidity, the smaller is the forward energy.

The self-normalised forward energy as a function of the average multiplicity
in a certain interval, normalised to the MB average,
$\langle\rm{d}N/\rm{d}\eta\rangle/\langle\rm{d}N/\rm{d}\eta\rangle_{\rm{MB}}$,
was compared with MC simulations for pp collisions. All models are able to
describe the overall decreasing trend, and PYTHIA 6 (Perugia 2011) is the one
showing the best degree of agreement, as shown in Fig. 6. However, none of the
models is able to reproduce the experimental results quantitatively. Moreover,
they are not able to satisfactorily describe the measured forward energy
spectra in multiplicity bins.

Figure 6: Self-normalised ZN (left) and ZP (right) signals as a function of
the normalised charged-particle multiplicity produced in $|\eta|<1$ in pp
collisions. Data (red markers) are compared with PYTHIA 6 (blue solid line),
PYTHIA 8 (blue dashed line) and EPOS LHC (green dotted line).

The PYTHIA event generator includes MPI modelling, which is needed to
reproduce the energy flow measurements at LHC energies at smaller rapidities
[31, 32]. The correlation between the very forward energy and the number of
MPIs was studied using PYTHIA. Figure 7 shows the simulated ZN and ZP self-
normalised responses as a function of the number of MPIs, normalised to their
MB average value ($\langle N_{\rm MPI}\rangle=$ 4.0 for PYTHIA 6 Perugia 2011
and $\langle N_{\rm MPI}\rangle=$ 5.0 for PYTHIA 8 Monash). Both models
predict a clear relationship between the very forward energy and $N_{\rm
MPI}$, showing a decrease in the average very forward energy for an increasing
number of MPIs, albeit with different slopes due to the different treatment of
MPIs in the two generators. This pattern resembles the observed dependence on
charged-particle multiplicity (see Fig. 6), as can be expected in an impact-
parameter dependent MPI picture [33].

Figure 7: Self-normalised ZN (left) and ZP (right) signal as a function of the
number of self-normalised MPI extracted from PYTHIA 6 Perugia 2011 (solid
line) and PYTHIA 8 Monash (dashed line) tunes.

The shape of the ZN spectrum also showed a dependence on the charged-particle
multiplicity at midrapidity. To characterise these modifications, three narrow
multiplicity intervals were selected, corresponding to high (0–2%),
intermediate (20–30%) and low (50–80%) multiplicities, and the ZN spectrum was
compared to the MB distribution in these intervals. Figure 8 shows the
spectrum modifications in the considered multiplicity intervals. In
particular, as predicted in Refs. [27, 34], the forward leading neutron energy
is suppressed when a higher activity is measured at midrapidity.

Figure 8: Left: ZN spectrum in pp collisions at $\sqrt{s}=$13 TeV for the MB
sample (blue circles) and in three multiplicity intervals: high (magenta
squares), intermediate (orange squares) and low (azure squares) multiplicity.
Right: ratio of the spectra, normalised to the number of events in each bin,
in the three multiplicity intervals to the MB spectrum.

###  5.3 Correlation between forward energy and leading particle transverse
momentum

The forward energy was studied as a function of the leading particle
transverse momentum, $p_{\rm T}^{{\rm leading}}$, defined event by event as
the track with the largest transverse momentum in $|\eta|<0.8$. Events with
large forward energies are characterised by smaller values of the leading
particle $p_{\rm T}$, as already observed in measurements at smaller
pseudorapidities at the LHC [35]. The self-normalised ZN and ZP signals as a
function of the leading particle $p_{\rm T}$ are shown in Fig. 9. The total
systematic uncertainty was estimated as the sum in quadrature of three
contributions: the first one comes from the trigger selection, the second is
due to the differences between the measurements performed on the two sides,
and the third contribution takes into account the misidentification of the
leading particle, which is corrected using a data-driven procedure, as
detailed in Ref. [36]. The total uncertainty ranges from 0.8% to 4.4% for ZN
and from 0.8% to 5.5% for ZP, the dominant contribution coming from the
difference between the two sides. A large forward energy is measured for very
low values of the leading particle $p_{\rm T}$ ($p_{\rm T}^{{\rm leading}}<1$
GeV/$c$). For larger leading particle $p_{\rm T}$ values, ZN and ZP energies
rapidly decrease and saturate for $p_{\rm T}^{{\rm leading}}\gtrsim 5$
GeV/$c$. The same trend was reported by the CMS collaboration when measuring
the energy at smaller rapidities ($-6.6<\eta<-5.2$) [31].

Figure 9: Self-normalised ZN (left) and ZP (right) signals as a function of
the leading particle $p_{\rm T}$ measured in $|\eta|<0.8$ in pp collisions at
$\sqrt{s}=$13 TeV. Data (red markers) are compared to PYTHIA 6 (blue solid
line), PYTHIA 8 (blue dashed line) and EPOS LHC (green dotted line).

The self-normalised ZN and ZP signals as a function of the leading particle
$p_{\rm T}$ are also compared to the three models under consideration, as
shown in Fig. 9. The trend predicted by PYTHIA 6 is qualitatively in agreement
with data, even if, for a leading particle $p_{\rm T}$ larger than $2$
GeV/$c$, PYTHIA 6 overestimates the forward energy by almost $20\%$. In
contrast, the leading particle $p_{\rm T}$ dependence predicted by PYTHIA 8 is
different for intermediate $p_{\rm T}$ values (2–8 GeV/$c$). This seems to
indicate that the treatment of colour reconnections and beam remnants in the
Perugia tunes of PYTHIA 6 is more realistic than the one in the default Monash
tune of PYTHIA 8. The core–corona EPOS LHC event generator also predicts a
quite different pattern, in particular it shows a depletion for intermediate
$p_{\rm T}$ values (2–8 GeV/$c$), where collective expansion (flow) included
in the core part of the model might play a major role.

###  5.4 Very forward energy and event properties in pp collisions

The energy carried forward by leading baryons has been proposed as a tool to
select events with smaller than average impact parameter. In Ref. [37] a
double veto on leading baryon production is suggested as an effective way to
select events characterised by a narrower impact-parameter distribution and
harder particle spectra. To test this hypothesis, the energy detected by the
ZDCs was used as a veto, requesting that neither ZN nor ZP have a signal on
one or on both sides, thus defining a single-side and a double-side veto
condition on leading baryon production, respectively. The charged-particle
multiplicity in $|\eta|<1$ and the total transverse momentum in $|\eta|<0.8$,
${p_{\rm T}}^{\rm{TOT}}$, were compared applying these conditions. The charged
particle distributions are corrected using MC simulations with different
generators, and the systematic uncertainty is estimated using EPOS LHC and
PYTHIA 8. The correction factors for the total $p_{\rm T}$ distributions, to
account for tracking efficiency and secondary contamination, were extracted
from [38], and the systematic uncertainty is estimated varying the $p_{\rm T}$
within the obtained boundaries. The distributions are corrected only for
inefficiencies and not for effects related to resolution. However, they
provide a clear indication of the effect due to the different applied
conditions. In Fig. 10, $N_{\rm ch}$ and ${p_{\rm T}}^{\rm{TOT}}$
distributions for the MB and for the two vetoed samples are shown. The average
values of $N_{\rm ch}$ are a factor $\sim$1.2 and $\sim$1.5 higher than in the
MB sample for the single and double veto selection, respectively. The analysis
of the simulated samples provided similar results, yielding to similar
increases for the average values of $N_{\rm ch}$, namely a factor (1.1) 1.3
for PYTHIA 6, (1.2) 1.6 for to PYTHIA 8 and (1.2) 1.4 using EPOS LHC, applying
the (single) double veto condition. In conclusion, a double-side veto
condition selects a larger than average multiplicity and a harder $p_{\rm T}$
distribution at midrapidity. This measurement supports the prediction that a
double-side veto on baryon production leads to a narrower impact-parameter
distribution.

Figure 10: Distributions of the (not fully corrected) number of charged
particles in $|\eta|<1$ (left) and of the total transverse momentum in
$|\eta|<0.8$ (right) for MB interactions (blue circles), single-side (azure
empty squares) and double-side (red full squares) veto conditions on leading
baryon production in pp collisions at $\sqrt{s}=$13 TeV.

The measurement of the forward energy as a function of the leading particle
$p_{\rm T}$ measured at midrapidity is complementary to the UE, defined
through the charged-particle multiplicity produced in the azimuthal region
transverse to the emitted leading particle
($60^{\circ}<|\Delta\varphi|<120^{\circ}$) [36]. The charged-particle
multiplicity in the transverse region rapidly reaches its maximum value and
then remains constant for increasing $p_{\rm T}$ (pedestal effect), while the
forward energy (both for neutrons and protons) reaches its minimum value and
then remains constant for increasing particle $p_{\rm T}$ at midrapidity.
These two saturation effects occur at the same leading particle $p_{\rm T}$
scale, around $p_{\rm T}$ $\sim 5$ GeV/$c$, as can be seen in Fig. 11, where
UE published results [38] and ZN normalised energy are compared for pp
collisions at $\sqrt{s}=13$ TeV. In the MPI approach, collisions producing
high-$p_{\rm T}$ particles have a lower than average impact parameter and
consequently a larger underlying event activity [28]. Above a leading particle
$p_{\rm T}$ of about 5 GeV/$c$ the impact parameter bias reaches its maximum
value. The strong anti-correlation between the leading particle $p_{\rm T}$
and the forward energy seen at low $p_{\rm T}^{\rm leading}$ can only be built
in the initial stages of the collisions, since the two observables are
causally disconnected in the following evolution stages.

Figure 11: Self-normalised ZN signal (red circles) and number density $N_{ch}$
(azure squares) distribution in the transverse region (published in Ref. [38])
as a function of $p_{\rm T}^{\rm leading}$ measured in $|\eta|<$0.8. Tracks
have $p_{\rm T}$ $>$0.15 GeV/c, markers are placed at the centre and not at
the average of the $p_{\rm T}$ leading bin.

##  6 Conclusions

First results on the very forward energy measured by the ALICE ZDCs in pp
collisions at $\sqrt{s}=13$ TeV and in p–Pb collisions at
$\sqrt{s_{\rm{NN}}}=8.16$ TeV have been presented.

In pp collisions, the energy carried by leading protons at large forward and
backward rapidities is found to be uncorrelated, confirming results from
hadronic collisions at lower energies, while for neutrons a weak correlation
between the energy released at forward and backward rapidities is observed.

The very forward energy was studied as a function of the charged-particle
production at midrapidity to gain insight in the particle production
mechanisms. The self-normalised forward energy decreases with increasing
charged-particle multiplicity at midrapidity, both in pp and in p–Pb
collisions with the same proton beam energy, as expected from energy
conservation.

The very forward energy decreases with increasing leading particle $p_{\rm T}$
at midrapidity until about 5 GeV/$c$ where it saturates. Similarly, the
charged-particle multiplicity in the transverse region (UE) as a function of
the leading particle $p_{\rm T}$ first rises and then saturates at about the
same $p_{\rm T}$ value. In the case of the UE this is commonly interpreted as
a bias to an on average smaller pp impact parameter with consequently larger
number of MPIs leading to higher multiplicity at midrapidity. The results of
this paper corroborate this interpretation since the correlation between
central and forward rapidity can only be attributed to the initial stage of
the collisions.

The hadronic interaction models used for comparison, PYTHIA 6 Perugia 2011,
PYTHIA 8 Monash, and EPOS-LHC, are not able to reproduce quantitatively the
measurements at large rapidities as a function of particle production at
midrapidity. These measurements provide constraints to improve the model
description of beam remnants and very forward energy.

Finally, it was shown that the very forward energy can be effectively used in
pp collisions as a veto to select events characterised by higher than total
average multiplicity and total transverse momentum, in agreement with
expectations from models including centrality dependent particle production.

## 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; 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; Indonesian Institute of Science, Indonesia; Istituto Nazionale di Fisica Nucleare (INFN), Italy; Institute for Innovative Science and Technology , Nagasaki Institute of Applied Science (IIST), Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) and Japan 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 and Ministry of Research and Innovation and Institute of Atomic Physics, Romania; Joint Institute for Nuclear Research (JINR), Ministry of Education and Science of the Russian Federation, National Research Centre Kurchatov Institute, Russian Science Foundation and Russian Foundation for Basic Research, Russia; 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 (NSDTA) and Office of the Higher Education Commission under NRU project of Thailand, 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.

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##  Appendix A The ALICE Collaboration

S. Acharya143, D. Adamová98, A. Adler76, G. Aglieri Rinella35, M. Agnello31,
N. Agrawal55, Z. Ahammed143, S. Ahmad16, S.U. Ahn78, I. Ahuja39, Z. Akbar52,
A. Akindinov95, M. Al-Turany110, S.N. Alam16,41, D. Aleksandrov91, B.
Alessandro61, H.M. Alfanda7, R. Alfaro Molina73, B. Ali16, Y. Ali14, A.
Alici26, N. Alizadehvandchali127, A. Alkin35, J. Alme21, T. Alt70, L.
Altenkamper21, I. Altsybeev115, M.N. Anaam7, C. Andrei49, D. Andreou93, A.
Andronic146, M. Angeletti35, V. Anguelov107, F. Antinori58, P. Antonioli55, C.
Anuj16, N. Apadula82, L. Aphecetche117, H. Appelshäuser70, S. Arcelli26, R.
Arnaldi61, I.C. Arsene20, M. Arslandok148,107, A. Augustinus35, R.
Averbeck110, S. Aziz80, M.D. Azmi16, A. Badalà57, Y.W. Baek42, X. Bai131,110,
R. Bailhache70, Y. Bailung51, R. Bala104, A. Balbino31, A. Baldisseri140, B.
Balis2, M. Ball44, D. Banerjee4, R. Barbera27, L. Barioglio108, M. Barlou87,
G.G. Barnaföldi147, L.S. Barnby97, V. Barret137, C. Bartels130, K. Barth35, E.
Bartsch70, F. Baruffaldi28, N. Bastid137, S. Basu83, G. Batigne117, B.
Batyunya77, D. Bauri50, J.L. Bazo Alba114, I.G. Bearden92, C. Beattie148, I.
Belikov139, A.D.C. Bell Hechavarria146, F. Bellini26, R. Bellwied127, S.
Belokurova115, V. Belyaev96, G. Bencedi71, S. Beole25, A. Bercuci49, Y.
Berdnikov101, A. Berdnikova107, L. Bergmann107, M.G. Besoiu69, L. Betev35,
P.P. Bhaduri143, A. Bhasin104, I.R. Bhat104, M.A. Bhat4, B. Bhattacharjee43,
P. Bhattacharya23, L. Bianchi25, N. Bianchi53, J. Bielčík38, J. Bielčíková98,
J. Biernat120, A. Bilandzic108, G. Biro147, S. Biswas4, J.T. Blair121, D.
Blau91, M.B. Blidaru110, C. Blume70, G. Boca29,59, F. Bock99, A. Bogdanov96,
S. Boi23, J. Bok63, L. Boldizsár147, A. Bolozdynya96, M. Bombara39, P.M.
Bond35, G. Bonomi142,59, H. Borel140, A. Borissov84, H. Bossi148, E. Botta25,
L. Bratrud70, P. Braun-Munzinger110, M. Bregant123, M. Broz38, G.E.
Bruno109,34, M.D. Buckland130, D. Budnikov111, H. Buesching70, S. Bufalino31,
O. Bugnon117, P. Buhler116, Z. Buthelezi74,134, J.B. Butt14, S.A. Bysiak120,
M. Cai28,7, H. Caines148, A. Caliva110, E. Calvo Villar114, J.M.M. Camacho122,
R.S. Camacho46, P. Camerini24, F.D.M. Canedo123, F. Carnesecchi35,26, R.
Caron140, J. Castillo Castellanos140, E.A.R. Casula23, F. Catalano31, C.
Ceballos Sanchez77, P. Chakraborty50, S. Chandra143, S. Chapeland35, M.
Chartier130, S. Chattopadhyay143, S. Chattopadhyay112, A. Chauvin23, T.G.
Chavez46, T. Cheng7, C. Cheshkov138, B. Cheynis138, V. Chibante Barroso35,
D.D. Chinellato124, S. Cho63, P. Chochula35, P. Christakoglou93, C.H.
Christensen92, P. Christiansen83, T. Chujo136, C. Cicalo56, L. Cifarelli26, F.
Cindolo55, M.R. Ciupek110, G. ClaiII,55, J. CleymansI,126, F. Colamaria54,
J.S. Colburn113, D. Colella109,54,34,147, A. Collu82, M. Colocci35, M.
ConcasIII,61, G. Conesa Balbastre81, Z. Conesa del Valle80, G. Contin24, J.G.
Contreras38, M.L. Coquet140, T.M. Cormier99, P. Cortese32, M.R. Cosentino125,
F. Costa35, S. Costanza29,59, P. Crochet137, R. Cruz-Torres82, E. Cuautle71,
P. Cui7, L. Cunqueiro99, A. Dainese58, M.C. Danisch107, A. Danu69, I. Das112,
P. Das89, P. Das4, S. Das4, S. Dash50, S. De89, A. De Caro30, G. de Cataldo54,
L. De Cilladi25, J. de Cuveland40, A. De Falco23, D. De Gruttola30, N. De
Marco61, C. De Martin24, S. De Pasquale30, S. Deb51, H.F. Degenhardt123, K.R.
Deja144, L. Dello Stritto30, S. Delsanto25, W. Deng7, P. Dhankher19, D. Di
Bari34, A. Di Mauro35, R.A. Diaz8, T. Dietel126, Y. Ding138,7, R. Divià35,
D.U. Dixit19, Ø. Djuvsland21, U. Dmitrieva65, J. Do63, A. Dobrin69, B.
Dönigus70, O. Dordic20, A.K. Dubey143, A. Dubla110,93, S. Dudi103, M.
Dukhishyam89, P. Dupieux137, N. Dzalaiova13, T.M. Eder146, R.J. Ehlers99, V.N.
Eikeland21, F. Eisenhut70, D. Elia54, B. Erazmus117, F. Ercolessi26, F.
Erhardt102, A. Erokhin115, M.R. Ersdal21, B. Espagnon80, G. Eulisse35, D.
Evans113, S. Evdokimov94, L. Fabbietti108, M. Faggin28, J. Faivre81, F. Fan7,
A. Fantoni53, M. Fasel99, P. Fecchio31, A. Feliciello61, G. Feofilov115, A.
Fernández Téllez46, A. Ferrero140, A. Ferretti25, V.J.G. Feuillard107, J.
Figiel120, S. Filchagin111, D. Finogeev65, F.M. Fionda56,21, G.
Fiorenza35,109, F. Flor127, A.N. Flores121, S. Foertsch74, P. Foka110, S.
Fokin91, E. Fragiacomo62, E. Frajna147, U. Fuchs35, N. Funicello30, C.
Furget81, A. Furs65, J.J. Gaardhøje92, M. Gagliardi25, A.M. Gago114, A.
Gal139, C.D. Galvan122, P. Ganoti87, C. Garabatos110, J.R.A. Garcia46, E.
Garcia-Solis10, K. Garg117, C. Gargiulo35, A. Garibli90, K. Garner146, P.
Gasik110, E.F. Gauger121, A. Gautam129, M.B. Gay Ducati72, M. Germain117, P.
Ghosh143, S.K. Ghosh4, M. Giacalone26, P. Gianotti53, P. Giubellino110,61, P.
Giubilato28, A.M.C. Glaenzer140, P. Glässel107, D.J.Q. Goh85, V. Gonzalez145,
L.H. González-Trueba73, S. Gorbunov40, M. Gorgon2, L. Görlich120, S.
Gotovac36, V. Grabski73, L.K. Graczykowski144, L. Greiner82, A. Grelli64, C.
Grigoras35, V. Grigoriev96, A. GrigoryanI,1, S. Grigoryan77,1, O.S.
Groettvik21, F. Grosa35,61, J.F. Grosse-Oetringhaus35, R. Grosso110, G.G.
Guardiano124, R. Guernane81, M. Guilbaud117, K. Gulbrandsen92, T. Gunji135, W.
Guo7, A. Gupta104, R. Gupta104, S.P. Guzman46, L. Gyulai147, M.K. Habib110, C.
Hadjidakis80, G. Halimoglu70, H. Hamagaki85, G. Hamar147, M. Hamid7, R.
Hannigan121, M.R. Haque144,89, A. Harlenderova110, J.W. Harris148, A.
Harton10, J.A. Hasenbichler35, H. Hassan99, D. Hatzifotiadou55, P. Hauer44,
L.B. Havener148, S. Hayashi135, S.T. Heckel108, E. Hellbär110, H. Helstrup37,
T. Herman38, E.G. Hernandez46, G. Herrera Corral9, F. Herrmann146, K.F.
Hetland37, H. Hillemanns35, C. Hills130, B. Hippolyte139, B. Hofman64, B.
Hohlweger93, J. Honermann146, G.H. Hong149, D. Horak38, S. Hornung110, A.
Horzyk2, R. Hosokawa15, Y. Hou7, P. Hristov35, C. Hughes133, P. Huhn70, T.J.
Humanic100, H. Hushnud112, L.A. Husova146, A. Hutson127, D. Hutter40, J.P.
Iddon35,130, R. Ilkaev111, H. Ilyas14, M. Inaba136, G.M. Innocenti35, M.
Ippolitov91, A. Isakov38,98, M.S. Islam112, M. Ivanov110, V. Ivanov101, V.
Izucheev94, M. Jablonski2, B. Jacak82, N. Jacazio35, P.M. Jacobs82, S.
Jadlovska119, J. Jadlovsky119, S. Jaelani64, C. Jahnke124,123, M.J.
Jakubowska144, A. Jalotra104, M.A. Janik144, T. Janson76, M. Jercic102, O.
Jevons113, A.A.P. Jimenez71, F. Jonas99,146, P.G. Jones113, J.M. Jowett
35,110, J. Jung70, M. Jung70, A. Junique35, A. Jusko113, J. Kaewjai118, P.
Kalinak66, A. Kalweit35, V. Kaplin96, S. Kar7, A. Karasu Uysal79, D.
Karatovic102, O. Karavichev65, T. Karavicheva65, P. Karczmarczyk144, E.
Karpechev65, A. Kazantsev91, U. Kebschull76, R. Keidel48, D.L.D. Keijdener64,
M. Keil35, B. Ketzer44, Z. Khabanova93, A.M. Khan7, S. Khan16, A.
Khanzadeev101, Y. Kharlov94, A. Khatun16, A. Khuntia120, B. Kileng37, B.
Kim17,63, C. Kim17, D.J. Kim128, E.J. Kim75, J. Kim149, J.S. Kim42, J. Kim107,
J. Kim149, J. Kim75, M. Kim107, S. Kim18, T. Kim149, S. Kirsch70, I. Kisel40,
S. Kiselev95, A. Kisiel144, J.P. Kitowski2, J.L. Klay6, J. Klein35, S.
Klein82, C. Klein-Bösing146, M. Kleiner70, T. Klemenz108, A. Kluge35, A.G.
Knospe127, C. Kobdaj118, M.K. Köhler107, T. Kollegger110, A. Kondratyev77, N.
Kondratyeva96, E. Kondratyuk94, J. Konig70, S.A. Konigstorfer108, P.J.
Konopka35,2, G. Kornakov144, S.D. Koryciak2, L. Koska119, A. Kotliarov98, O.
Kovalenko88, V. Kovalenko115, M. Kowalski120, I. Králik66, A. Kravčáková39, L.
Kreis110, M. Krivda113,66, F. Krizek98, K. Krizkova Gajdosova38, M.
Kroesen107, M. Krüger70, E. Kryshen101, M. Krzewicki40, V. Kučera35, C.
Kuhn139, P.G. Kuijer93, T. Kumaoka136, D. Kumar143, L. Kumar103, N. Kumar103,
S. Kundu35,89, P. Kurashvili88, A. Kurepin65, A.B. Kurepin65, A. Kuryakin111,
S. Kushpil98, J. Kvapil113, M.J. Kweon63, J.Y. Kwon63, Y. Kwon149, S.L. La
Pointe40, P. La Rocca27, Y.S. Lai82, A. Lakrathok118, M. Lamanna35, R.
Langoy132, K. Lapidus35, P. Larionov35,53, E. Laudi35, L. Lautner35,108, R.
Lavicka38, T. Lazareva115, R. Lea142,24,59, J. Lehrbach40, R.C. Lemmon97, I.
León Monzón122, E.D. Lesser19, M. Lettrich35,108, P. Lévai147, X. Li11, X.L.
Li7, J. Lien132, R. Lietava113, B. Lim17, S.H. Lim17, V. Lindenstruth40, A.
Lindner49, C. Lippmann110, A. Liu19, D.H. Liu7, J. Liu130, I.M. Lofnes21, V.
Loginov96, C. Loizides99, P. Loncar36, J.A. Lopez107, X. Lopez137, E. López
Torres8, J.R. Luhder146, M. Lunardon28, G. Luparello62, Y.G. Ma41, A.
Maevskaya65, M. Mager35, T. Mahmoud44, A. Maire139, M. Malaev101, N.M.
Malik104, Q.W. Malik20, L. MalininaIV,77, D. Mal’Kevich95, N. Mallick51, P.
Malzacher110, G. Mandaglio33,57, V. Manko91, F. Manso137, V. Manzari54, Y.
Mao7, J. Mareš68, G.V. Margagliotti24, A. Margotti55, A. Marín110, C.
Markert121, M. Marquard70, N.A. Martin107, P. Martinengo35, J.L. Martinez127,
M.I. Martínez46, G. Martínez García117, S. Masciocchi110, M. Masera25, A.
Masoni56, L. Massacrier80, A. Mastroserio141,54, A.M. Mathis108, O.
Matonoha83, P.F.T. Matuoka123, A. Matyja120, C. Mayer120, A.L. Mazuecos35, F.
Mazzaschi25, M. Mazzilli35, M.A. MazzoniI,60, J.E. Mdhluli134, A.F. Mechler70,
F. Meddi22, Y. Melikyan65, A. Menchaca-Rocha73, E. Meninno116,30, A.S.
Menon127, M. Meres13, S. Mhlanga126,74, Y. Miake136, L. Micheletti61,25, L.C.
Migliorin138, D.L. Mihaylov108, K. Mikhaylov77,95, A.N. Mishra147, D.
Miśkowiec110, A. Modak4, A.P. Mohanty64, B. Mohanty89, M. Mohisin KhanV,16,
M.A. Molander45, Z. Moravcova92, C. Mordasini108, D.A. Moreira De Godoy146,
L.A.P. Moreno46, I. Morozov65, A. Morsch35, T. Mrnjavac35, V. Muccifora53, E.
Mudnic36, D. Mühlheim146, S. Muhuri143, J.D. Mulligan82, A. Mulliri23, M.G.
Munhoz123, R.H. Munzer70, H. Murakami135, S. Murray126, L. Musa35, J.
Musinsky66, J.W. Myrcha144, B. Naik134,50, R. Nair88, B.K. Nandi50, R.
Nania55, E. Nappi54, M.U. Naru14, A.F. Nassirpour83, A. Nath107, C.
Nattrass133, A. Neagu20, L. Nellen71, S.V. Nesbo37, G. Neskovic40, D.
Nesterov115, B.S. Nielsen92, S. Nikolaev91, S. Nikulin91, V. Nikulin101, F.
Noferini55, S. Noh12, P. Nomokonov77, J. Norman130, N. Novitzky136, P.
Nowakowski144, A. Nyanin91, J. Nystrand21, M. Ogino85, A. Ohlson83, V.A.
Okorokov96, J. Oleniacz144, A.C. Oliveira Da Silva133, M.H. Oliver148, A.
Onnerstad128, C. Oppedisano61, A. Ortiz Velasquez71, T. Osako47, A.
Oskarsson83, J. Otwinowski120, M. Oya47, K. Oyama85, Y. Pachmayer107, S.
Padhan50, D. Pagano142,59, G. Paić71, A. Palasciano54, J. Pan145, S.
Panebianco140, P. Pareek143, J. Park63, J.E. Parkkila128, S.P. Pathak127, R.N.
Patra104,35, B. Paul23, H. Pei7, T. Peitzmann64, X. Peng7, L.G. Pereira72, H.
Pereira Da Costa140, D. Peresunko91, G.M. Perez8, S. Perrin140, Y. Pestov5, V.
Petráček38, M. Petrovici49, R.P. Pezzi117,72, S. Piano62, M. Pikna13, P.
Pillot117, O. Pinazza55,35, L. Pinsky127, C. Pinto27, S. Pisano53, M.
Płoskoń82, M. Planinic102, F. Pliquett70, M.G. Poghosyan99, B. Polichtchouk94,
S. Politano31, N. Poljak102, A. Pop49, S. Porteboeuf-Houssais137, J. Porter82,
V. Pozdniakov77, S.K. Prasad4, R. Preghenella55, F. Prino61, C.A. Pruneau145,
I. Pshenichnov65, M. Puccio35, S. Qiu93, L. Quaglia25, R.E. Quishpe127, S.
Ragoni113, A. Rakotozafindrabe140, L. Ramello32, F. Rami139, S.A.R. Ramirez46,
A.G.T. Ramos34, T.A. Rancien81, R. Raniwala105, S. Raniwala105, S.S.
Räsänen45, R. Rath51, I. Ravasenga93, K.F. Read99,133, A.R. Redelbach40, K.
RedlichVI,88, A. Rehman21, P. Reichelt70, F. Reidt35, H.A. Reme-ness37, R.
Renfordt70, Z. Rescakova39, K. Reygers107, A. Riabov101, V. Riabov101, T.
Richert83, M. Richter20, W. Riegler35, F. Riggi27, C. Ristea69, M. Rodríguez
Cahuantzi46, K. Røed20, R. Rogalev94, E. Rogochaya77, T.S. Rogoschinski70, D.
Rohr35, D. Röhrich21, P.F. Rojas46, P.S. Rokita144, F. Ronchetti53, A.
Rosano33,57, E.D. Rosas71, A. Rossi58, A. Rotondi29,59, A. Roy51, P. Roy112,
S. Roy50, N. Rubini26, O.V. Rueda83, R. Rui24, B. Rumyantsev77, P.G. Russek2,
A. Rustamov90, E. Ryabinkin91, Y. Ryabov101, A. Rybicki120, H. Rytkonen128, W.
Rzesa144, O.A.M. Saarimaki45, R. Sadek117, S. Sadovsky94, J. Saetre21, K.
Šafařík38, S.K. Saha143, S. Saha89, B. Sahoo50, P. Sahoo50, R. Sahoo51, S.
Sahoo67, D. Sahu51, P.K. Sahu67, J. Saini143, S. Sakai136, S. Sambyal104, V.
SamsonovI,101,96, D. Sarkar145, N. Sarkar143, P. Sarma43, V.M. Sarti108,
M.H.P. Sas148, J. Schambach99,121, H.S. Scheid70, C. Schiaua49, R.
Schicker107, A. Schmah107, C. Schmidt110, H.R. Schmidt106, M.O. Schmidt35, M.
Schmidt106, N.V. Schmidt99,70, A.R. Schmier133, R. Schotter139, J.
Schukraft35, Y. Schutz139, K. Schwarz110, K. Schweda110, G. Scioli26, E.
Scomparin61, J.E. Seger15, Y. Sekiguchi135, D. Sekihata135, I.
Selyuzhenkov110,96, S. Senyukov139, J.J. Seo63, D. Serebryakov65, L.
Šerkšnytė108, A. Sevcenco69, T.J. Shaba74, A. Shabanov65, A. Shabetai117, R.
Shahoyan35, W. Shaikh112, A. Shangaraev94, A. Sharma103, H. Sharma120, M.
Sharma104, N. Sharma103, S. Sharma104, U. Sharma104, O. Sheibani127, K.
Shigaki47, M. Shimomura86, S. Shirinkin95, Q. Shou41, Y. Sibiriak91, S.
Siddhanta56, T. Siemiarczuk88, T.F. Silva123, D. Silvermyr83, G. Simonetti35,
B. Singh108, R. Singh89, R. Singh104, R. Singh51, V.K. Singh143, V.
Singhal143, T. Sinha112, B. Sitar13, M. Sitta32, T.B. Skaali20, G.
Skorodumovs107, M. Slupecki45, N. Smirnov148, R.J.M. Snellings64, C.
Soncco114, J. Song127, A. Songmoolnak118, F. Soramel28, S. Sorensen133, I.
Sputowska120, J. Stachel107, I. Stan69, P.J. Steffanic133, S.F.
Stiefelmaier107, D. Stocco117, I. Storehaug20, M.M. Storetvedt37, C.P.
Stylianidis93, A.A.P. Suaide123, T. Sugitate47, C. Suire80, M. Sukhanov65, M.
Suljic35, R. Sultanov95, M. Šumbera98, V. Sumberia104, S. Sumowidagdo52, S.
Swain67, A. Szabo13, I. Szarka13, U. Tabassam14, S.F. Taghavi108, G.
Taillepied137, J. Takahashi124, G.J. Tambave21, S. Tang137,7, Z. Tang131, M.
Tarhini117, M.G. Tarzila49, A. Tauro35, G. Tejeda Muñoz46, A. Telesca35, L.
Terlizzi25, C. Terrevoli127, G. Tersimonov3, S. Thakur143, D. Thomas121, R.
Tieulent138, A. Tikhonov65, A.R. Timmins127, M. Tkacik119, A. Toia70, N.
Topilskaya65, M. Toppi53, F. Torales-Acosta19, T. Tork80, S.R. Torres38, A.
Trifiró33,57, S. Tripathy55,71, T. Tripathy50, S. Trogolo35,28, G.
Trombetta34, V. Trubnikov3, W.H. Trzaska128, T.P. Trzcinski144, B.A.
Trzeciak38, A. Tumkin111, R. Turrisi58, T.S. Tveter20, K. Ullaland21, A.
Uras138, M. Urioni59,142, G.L. Usai23, M. Vala39, N. Valle59,29, S. Vallero61,
N. van der Kolk64, L.V.R. van Doremalen64, M. van Leeuwen93, R.J.G. van
Weelden93, P. Vande Vyvre35, D. Varga147, Z. Varga147, M. Varga-Kofarago147,
A. Vargas46, M. Vasileiou87, A. Vasiliev91, O. Vázquez Doce53,108, V.
Vechernin115, E. Vercellin25, S. Vergara Limón46, L. Vermunt64, R. Vértesi147,
M. Verweij64, L. Vickovic36, Z. Vilakazi134, O. Villalobos Baillie113, G.
Vino54, A. Vinogradov91, T. Virgili30, V. Vislavicius92, A. Vodopyanov77, B.
Volkel35, M.A. Völkl107, K. Voloshin95, S.A. Voloshin145, G. Volpe34, B. von
Haller35, I. Vorobyev108, D. Voscek119, N. Vozniuk65, J. Vrláková39, B.
Wagner21, C. Wang41, D. Wang41, M. Weber116, A. Wegrzynek35, S.C. Wenzel35,
J.P. Wessels146, J. Wiechula70, J. Wikne20, G. Wilk88, J. Wilkinson110, G.A.
Willems146, B. Windelband107, M. Winn140, W.E. Witt133, J.R. Wright121, W.
Wu41, Y. Wu131, R. Xu7, A.K. Yadav143, S. Yalcin79, Y. Yamaguchi47, K.
Yamakawa47, S. Yang21, S. Yano47, Z. Yin7, H. Yokoyama64, I.-K. Yoo17, J.H.
Yoon63, S. Yuan21, A. Yuncu107, V. Zaccolo24, A. Zaman14, C. Zampolli35,
H.J.C. Zanoli64, N. Zardoshti35, A. Zarochentsev115, P. Závada68, N.
Zaviyalov111, M. Zhalov101, B. Zhang7, S. Zhang41, X. Zhang7, Y. Zhang131, V.
Zherebchevskii115, Y. Zhi11, N. Zhigareva95, D. Zhou7, Y. Zhou92, J. Zhu7,110,
Y. Zhu7, A. Zichichi26, G. Zinovjev3, N. Zurlo142,59

## Affiliation notes

I Deceased
II Also at: Italian National Agency for New Technologies, Energy and
Sustainable Economic Development (ENEA), Bologna, Italy
III Also at: Dipartimento DET del Politecnico di Torino, Turin, Italy
IV Also at: M.V. Lomonosov Moscow State University, D.V. Skobeltsyn Institute
of Nuclear, Physics, Moscow, Russia
V Also at: Department of Applied Physics, Aligarh Muslim University, Aligarh,
India
VI Also at: Institute of Theoretical Physics, University of Wroclaw, Poland

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