2015 196 23 July Atmospheric muons in ALICE ALICE Collaboration††thanks: See
Appendix A for the list of collaboration members ALICE Collaboration

ALICE is one of four large experiments at the CERN Large Hadron Collider near
Geneva, specially designed to study particle production in ultra-relativistic
heavy-ion collisions. Located 52 meters underground with 28 meters of
overburden rock, it has also been used to detect muons produced by cosmic ray
interactions in the upper atmosphere. In this paper, we present the
multiplicity distribution of these atmospheric muons and its comparison with
Monte Carlo simulations. This analysis exploits the large size and excellent
tracking capability of the ALICE Time Projection Chamber. A special emphasis
is given to the study of high multiplicity events containing more than 100
reconstructed muons and corresponding to a muon areal density
$\rho_{\mu}>5.9~{}$m-2. Similar events have been studied in previous
underground experiments such as ALEPH and DELPHI at LEP. While these
experiments were able to reproduce the measured muon multiplicity distribution
with Monte Carlo simulations at low and intermediate multiplicities, their
simulations failed to describe the frequency of the highest multiplicity
events. In this work we show that the high multiplicity events observed in
ALICE stem from primary cosmic rays with energies above $10^{16}$ eV and that
the frequency of these events can be successfully described by assuming a
heavy mass composition of primary cosmic rays in this energy range. The
development of the resulting air showers was simulated using the latest
version of QGSJET to model hadronic interactions. This observation places
significant constraints on alternative, more exotic, production mechanisms for
these events.

##  1 Introduction

ALICE (A Large Ion Collider Experiment) [1] designed to study Quark-Gluon
Plasma (QGP) formation in ultra-relativistic heavy-ion collisions at the CERN
Large Hadron Collider (LHC), has also been used to perform studies that are of
relevance to astro-particle physics. The use of high-energy physics detectors
for cosmic ray physics was pioneered by ALEPH [2], DELPHI [3] and L3 [4]
during the Large Electron-Positron (LEP) collider era at CERN. An extension of
these earlier studies is now possible at the LHC, where experiments can
operate under stable conditions for many years. ALICE undertook a programme of
cosmic ray data taking between 2010 and 2013 during pauses in collider
operations when there was no beam circulating in the LHC.

Cosmic ray muons are created in Extensive Air Showers (EAS) following the
interaction of cosmic ray primaries (protons and heavier nuclei) with nuclei
in the upper atmosphere. Primary cosmic rays span a broad energy range,
starting at approximately $10^{9}$ eV and extending to more than $10^{20}$ eV.
In this study, we find that events containing more than four reconstructed
muons in the ALICE Time Projection Chamber (TPC), which we refer to as multi-
muon events, stem from primaries with energy $E>10^{14}$ eV. The detection of
EAS originating from interactions above this energy, in particular around the
energy of the knee in the primary spectrum ($E_{k}\sim 3\times 10^{15}$ eV),
has been performed by several large-area arrays at ground level (e.g. [5, 6,
7]), while deep underground detectors (e.g. [8, 9, 10]) have studied the high
energy muonic component of EAS. The main aims of these experiments were to
explore the mass composition and energy spectrum of primary cosmic rays.

The muon multiplicity distribution (MMD) was measured at LEP with the ALEPH
detector [11]. This study concluded that the bulk of the data can be
successfully described using standard hadronic production mechanisms, but that
the highest multiplicity events, containing around 75-150 muons, occur with a
frequency which is almost an order of magnitude above expectation, even when
assuming that the primary cosmic rays are purely composed of iron nuclei. A
similar study was carried out with the DELPHI detector, which also found that
Monte Carlo simulations were unable to account for the abundance of high muon
multiplicity events [12]. Several proposals have been put forward in the
scientific literature to explain this discrepancy. Some authors suggest that
hypothetical strangelets form a small percentage of very energetic cosmic rays
[13], while others have tried to explain the excess of high muon multiplicity
events by the creation of the QGP in interactions involving high mass primary
cosmic rays (iron nuclei) with nuclei in the atmosphere [14].

In this paper, we exploit the large size and excellent tracking capability of
the ALICE TPC [15] to study the muonic component of EAS. We describe the
analysis of the muon multiplicity distribution with particular emphasis on
high muon multiplicity events containing more than 100 muons in a single event
and corresponding to an areal density $\rho_{\mu}>5.9$ m-2. We employ a
description of the shower based upon the latest version of QGSJET [16, 17], a
hadronic interaction model commonly used in EAS simulations.

Details of the environment of ALICE and the detectors used for this analysis
are described in the following section, while the selection of the data and
the algorithm adopted to reconstruct atmospheric muons are discussed in
Section 3. The muon multiplicity distribution and the study of high muon
multiplicity events are described in Section 4. The results are presented in
Section 5 and, finally, in Section 6 we make some concluding remarks.

##  2 The ALICE experiment

ALICE is located at Point 2 of the LHC accelerator complex, approximately 450
m above sea level in a cavern 52 m underground with 28 m of overburden rock.
The rock absorbs all of the electromagnetic and hadronic components of the
observed EAS, so that only muons with an energy $E$, at the surface, larger
than $16$ GeV reach the detectors [18]. The geometry of ALICE is typical of a
collider experiment. A large solenoidal magnet forms a central barrel that
houses several detectors, including a large, cylindrical TPC. Outside the
solenoid, and on one end, there is a single-arm, forward spectrometer, which
was not used in this analysis. A complete description of the apparatus is
given in [1].

The ALICE TPC is the largest detector of its type ever built. It was used to
reconstruct the trajectory of cosmic ray muons passing through the active
volume of the detector, which comprises a cylindrical gas volume divided into
two halves by a central membrane. The TPC has an inner radius of 80 cm, an
outer radius of 280 cm and a total length of 500 cm along the LHC beam
direction. At each end of the cylindrical volume there are multi-wire
proportional chambers with pad readout. For the purpose of detecting cosmic
ray muons, the total area of the detector due to its horizontal cylindrical
geometry is approximately 26 m2. However, after placing a cut on the minimum
length required to reconstruct a cosmic ray track the maximum effective area
reduces to approximately 17 m2. The apparent area of the detector also varies
with the zenith angle of the incident muons. Track selection is discussed in
more detail in Section 3. An example of a single atmospheric muon event is
shown in Fig. 1.

Figure 1: A single atmospheric muon event. The thin outer cylinder is the Time
Of Flight detector (1). The large inner cylinder is the Time Projection
Chamber (2) and the smaller cylinder at the centre is the silicon Inner
Tracking System (3). Muons are reconstructed as two TPC tracks, one in the
upper half of the detector (_up_ track) and the other in the lower half
(_down_ track), which are then joined to create a single muon track.

Three detector subsystems were used to provide dedicated triggers for this
study: ACORDE (Alice COsmic Ray DEtector) [19], SPD (Silicon Pixel Detector)
[20] and TOF (Time Of Flight detector) [21].

ACORDE is an array of 60 scintillator modules located on the three upper faces
of the octagonal yoke of the solenoid, covering $10\%$ of its surface area. A
trigger was formed by the coincidence of signals in two different modules (a
two-fold coincidence), although the trigger can also be configured to select
events when a single module fires or when more than two modules fire.

The SPD is part of the Inner Tracking System located inside the inner field
cage of the TPC. It is composed of two layers of silicon pixel modules located
at a distance of 39 mm and 76 mm from the LHC beam axis, respectively. The
layers have an active length of 28.3 cm, centred upon the nominal interaction
point of the LHC beams. The SPD was incorporated into the trigger by requiring
a coincidence between signals in the top and bottom halves of the outermost
layer.

The TOF is a cylindrical array of multi-gap resistive-plate chambers that
completely surrounds the outer radius of the TPC. The TOF trigger requires a
signal in a pad corresponding to a cluster of readout channels covering an
area of 500 cm2 in the upper part of the detector and another signal in a pad
in the opposite lower part forming a back-to-back coincidence with respect to
the central axis of the detector. The configuration of the pads involved in
the trigger can be changed via software. In some periods of data taking, this
flexibility has been exploited to require a signal in an upper pad and in the
opposing pad plus the two adjacent pads forming a back-to-back $\pm$1
coincidence.

Cosmic ray data were acquired with a combination (logical OR) of at least two
out of the three trigger conditions (ACORDE, SPD and TOF) depending on the run
period. The trigger efficiency was studied with a detailed Monte Carlo
simulation, which is discussed in Section 4. Most events were classified as
either single muon events or multi-muon events, with a small percentage of
“interaction” events where very energetic muons have interacted with the iron
yoke of the magnet producing a shower of particles that pass through the TPC.

##  3 Event reconstruction and data selection

The TPC tracking algorithm [22] was designed to reconstruct tracks produced in
the interaction region of the two LHC beams. It finds tracks by working
inwards from the outer radius of the detector where, during collider
operation, the track density is lowest. The present analysis used the same
tracking algorithm but removed any requirement that tracks should pass through
a central interaction point. However, the tracking algorithm has not been
optimised for very inclined (quasi horizontal) tracks. Therefore, to avoid
reconstruction inaccuracies associated with the most inclined showers, we
restricted the zenith angle of all events to the range
$0^{\circ}<\theta<50^{\circ}$.

As a consequence of reconstructing tracks from the outer radius of the TPC
inwards, cosmic ray muons are typically reconstructed as two separate tracks
in the upper and lower halves of the TPC as shown in Fig. 1. We refer to these
tracks as _up_ and _down_ tracks. Following this first pass of the
reconstruction a new algorithm was applied to match each _up_ track with its
corresponding _down_ track to reconstruct the full trajectory of the muons and
to eliminate double counting. Starting with single muon events (producing two
TPC tracks), where the matching of tracks is straightforward, the
reconstruction has been tuned to handle events containing hundreds of muons.
High multiplicity Monte Carlo events have been used to optimise the matching
performance.

Each TPC track can be reconstructed with up to 159 individual space points. In
order to maximise the detector acceptance for this analysis, tracks were
required to have a minimum of 50 space points and, in events where the
magnetic field was on, a momentum greater than 0.5 GeV/$c$ to eliminate all
possible background from electrons and positrons. In multi-muon events,
accepted tracks were required to be approximately parallel since atmospheric
muons coming from the same EAS arrive almost parallel at ground level. The
parallelism cut involves forming the scalar product of the direction of the
analysed track $\vec{t_{a}}$ with a reference track $\vec{t_{r}}$, requiring
that $\vec{t_{a}}\cdot\vec{t_{r}}=\cos(\Delta\Psi)>0.990$ to accept the
analysed track. The reference track was chosen to give the largest number of
tracks satisfying the parallelism cut. This requirement introduces an
additional momentum cut due to the bending of muon tracks in the magnetic
field. The momentum cut is a function of the azimuth angle of the muon track
and varies between 1 and 2 GeV/$c$. Finally, each up track was matched to the
nearest down track if the distance of closest approach between them at the
horizontal mid plane of the TPC was $d_{xz}<3$ cm. This value was chosen to be
large enough to maximise the matching efficiency in high multiplicity Monte
Carlo events, while keeping combinatorial background to a minimum.

A muon reconstructed with two TPC tracks (up and down) is called a “matched
muon”. When a TPC track fulfils all the criteria to be a muon track: number of
space points, momentum and parallelism, but does not have a corresponding
track within $d_{xz}<3$ cm in the opposite side of the TPC, this track is
still accepted as a muon candidate but flagged as a “single-track muon”. Most
single-track muons are found to cross the TPC near its ends where part of the
muon trajectory falls outside the detector.

To quantify the performance of the tracking and matching algorithms, we
studied the multiplicity dependence of the reconstruction efficiency using
Monte Carlo simulated events. We generated 1000 events for 20 discrete values
of the muon multiplicity, varying between 1 and 300, which were then
reconstructed using the same algorithms applied to real events. In each event,
muons were generated parallel to each other like in EAS and cross the whole
TPC volume. Fig. 2 shows the mean values (MEAN) and root-mean-square (RMS) of
the relative difference between the number of generated and reconstructed
muons,

$\left(\\#~{}\text{generated muons}-\\#~{}\text{reconstructed
muons}\right)/\left(\\#~{}\text{generated muons}\right),$ (1)

as a function of the number of generated muons. The root-mean-square
represents the resolution on the number of reconstructed muons and is
typically less than $4\%$, while for the highest multiplicities it is around
$2\%$. The mean value is less than $1\%$ up to $N_{\mu}\approx 50$, increasing
to $5\%$ at high muon multiplicities ($N_{\mu}\approx 300$).

Figure 2: Root-mean-square and mean values of the relative difference between
the number of generated and reconstructed muons for events simulated with
different muon multiplicities.

To illustrate the similarity of the data and the Monte Carlo simulation, Fig.
3 shows the ratio of the number of muons reconstructed as single tracks
(either up or down tracks) to the total number of reconstructed muons (both
single and matched tracks) for different multiplicities. The ratio obtained
from the data is compared with the ratios obtained from simulated samples of
pure proton primary cosmic rays and pure iron primaries. Over the range of
intermediate muon multiplicities shown, the ratio varies between 0.2 and 0.4
with good agreement between data and simulations. There is no significant
difference between the simulated proton and iron samples.

Figure 3: The ratio of muons reconstructed as single tracks to the total
number of reconstructed muons (both single and matched tracks) in the data and
simulations with proton and iron primaries.

Data were recorded between 2010 and 2013 during pauses in collider operations
when no beam was circulating in the LHC. The total accumulated run time
amounted to 30.8 days, resulting in approximately 22.6 million events with at
least one reconstructed muon (single-track or matched) in the TPC. Only multi-
muon events are discussed further in this paper. We define multi-muon events
as those events with more than four reconstructed muons in the TPC
($N_{\mu}>4$). In total, we collected a sample of 7487 multi-muon events.

##  4 Analysis of the data and simulation

To obtain the MMD we have corrected the measured distribution for the
efficiency of the trigger. The correction was calculated from a Monte Carlo
simulation that is described later in this section. Given the complementary
coverage of the TOF barrel to the TPC, the TOF trigger was mainly responsible
for selecting events in the low-to-intermediate range of muon multiplicities
($7~{}\leq~{}N_{\mu}~{}\leq~{}70$). The efficiency of the TOF trigger as a
function of the muon multiplicity is shown in Fig. 4. The efficiency is lower
at low muon multiplicity due to the back-to-back coincidence requirement of
the TOF trigger. The efficiency of the ACORDE trigger has a similar,
increasing trend with the muon multiplicity. The multiplicities at which the
two triggers reach full (100%) efficiency are $N_{\mu}>10$ (TOF) and
$N_{\mu}>15$ (ACORDE). Given the much smaller area of the SPD in comparison
with the TPC, the efficiency of the SPD trigger is significantly lower than
both ACORDE and TOF. It makes only a minor contribution to the MMD in the low-
to-intermediate range of muon multiplicities.

Figure 4: TOF trigger efficiency as a function of muon multiplicity.

The MMD obtained from the whole data sample and corrected for trigger
efficiency is shown in Fig. 5. Values for the systematic uncertainty in the
number of events as a function of multiplicity have been estimated by varying
the parameters of the track reconstruction and matching algorithms. We find a
smooth distribution up to a muon multiplicity of around 70 and then 5 events
with a muon multiplicity greater than 100. We define the events with
$N_{\mu}>100$ high muon multiplicity (HMM) events. Given the nature and
topology of high multiplicity events, all trigger conditions contributed to
this sample with close to 100% efficiency. The aim of the following analysis
is to model the MMD at low-to-intermediate multiplicities and to explore the
origin of the HMM events.

Figure 5: Muon multiplicity distribution of the whole sample of data
(2010-2013) corresponding to 30.8 days of data taking.

The difficulty in describing EAS, and consequently the number of muons
reaching ground level, mainly arises from uncertainties in the properties of
multi-particle production in hadron-air interactions. These interactions are
often described phenomenologically within Monte Carlo event generators. Model
parameters, such as total and inelastic hadron-proton cross sections,
inelastic scattering slopes and diffractive structure functions, are
constrained by measurements obtained from accelerator experiments.

In this analysis we have adopted the CORSIKA [23] event generator
incorporating QGSJET [16] for the hadronic interaction model to simulate the
generation and development of EAS. CORSIKA version 6990 incorporating QGSJET
II-03 has been used to study the MMD distribution and HMM events; CORSIKA
version 7350 incorporating QGSJET II-04 has been used to check and confirm the
results for HMM events. The significant differences between the two versions
of QGSJET are the inclusion of Pomeron loops in the formalism of QGSJET II-04
and a retuning of the model parameters using early LHC data for the first time
[24]. Most relevant to the present study is that pion exchange is assumed to
dominate forward neutral hadron production in the QGSJET II-04, which has been
shown to enhance the production of $\rho^{0}$ mesons resulting in an
enhancement of the muon content of EAS by about 20% [25].

In previous studies of cosmic ray muon events at LEP, QGSJET 01 was used to
model hadronic interactions. Apart from the way in which nonlinear effects are
modelled, another significant difference between this earlier version of the
model and QGSJET II-03/04 is the deeper shower maximum, $X_{max}$, used in the
later versions. This results in a steeper lateral muon distribution and an
associated increase of the muon density close to the core of the shower, which
can also have an impact on the observed rate of HMM events.

When generating cosmic ray events, the core of each shower was scattered
randomly at ground level over an area covering $205\times 205$ m2 centred upon
the nominal LHC beam crossing point. This area was chosen to minimise the
number of events to be generated without creating any bias on the final
results. We found that, when the core was located outside this area, only a
very small number of events gave rise to muons crossing the TPC and these
events were always of low multiplicity ($N_{\mu}<4$). Therefore, neglecting
these events does not affect the results reported in this paper.

To have a fast and flexible method of estimating several important parameters
and observables involved in the analysis, we started with a simplified Monte
Carlo simulation. This simulation did not explicitly model interactions in the
rock above the experiment. Instead, the trajectories of the muons arriving at
the surface were simply extrapolated as straight lines to the depth of ALICE
while imposing an energy cut $E_{\mu}>16~{}\text{GeV}/\cos(\theta)$, where
$\theta$ is the zenith angle of the muon. All muons passing this cut and
crossing an area of 17 m2, corresponding to the horizontal cross-sectional
area of the TPC, were considered to be detected.

To understand the complete sample of the recorded data, including the origin
of low muon multiplicity events, we generated events initiated by the
interaction of proton and iron (56Fe) primaries with energies $E>10^{12}$ eV.
This revealed that most single muon events stem from primaries in the energy
range $10^{12}<E<10^{13}$ eV, while primaries in the energy range
$10^{13}<E<10^{14}$ eV produce muon multiplicities typically in the range from
1 to 4, independent of the mass of the primary cosmic rays. Primaries with
energies below $10^{14}$ eV therefore produce a negligible contribution to
multi-muon events ($N_{\mu}>4$) that are of interest in this study.
Consequently, only energies $E>10^{14}$ eV were considered in the full
simulation.

The first step in the analysis was to attempt to reproduce the measured MMD in
the low-intermediate range of multiplicity ($7\leq N_{\mu}\leq 70$). Samples
of proton and iron primary cosmic rays were generated in the energy range
$10^{14}<E<10^{18}$ eV and with zenith angles in the interval
$0^{\circ}<\theta<50^{\circ}$. The composition of cosmic rays in this energy
range is a mixture of many species of nuclei in a ratio that is not well-known
and which varies with energy. To simplify the analysis and interpretation of
the data we have modelled the primary cosmic ray flux using a pure proton
sample, representing a composition dominated by light nuclei, and a pure iron
sample, representing a composition dominated by heavy nuclei. In relation to
the MMD, the proton sample provides a lower limit on the number of events for
a given multiplicity, while the iron sample provides an upper limit. A typical
power law energy spectrum, $E^{-\gamma}$, has been adopted with a spectral
index $\gamma=2.7\pm 0.03$ for energies below the knee ($E{{}_{k}}=3\times
10^{15}$ eV) and $\gamma_{k}=3.0\pm 0.03$ for energies above the knee. The
total (all particle) flux of cosmic rays has been calculated by summing the
individual fluxes of the main chemical elements at 1 TeV [26] where
measurements are most precise. The flux was estimated to be $F(1\
$TeV$)=0.225\pm 0.005$ (m2 s sr TeV)-1.

All events generated with energies $E>10^{14}$ eV were subsequently considered
for a complete analysis using a detailed simulation taking into account all
possible interactions in matter surrounding the experiment. In each event, all
muons were extrapolated to the horizontal mid-plane of the experiment and
flagged if they hit an enlarged area of 36 m2 centred upon the TPC with no
restriction on the energy of the muons. All flagged muons were recorded along
with their position and momentum at ground level and used as input to the
ALICE simulation framework. In this framework, the ALICE experimental hall and
the environment above and around the apparatus as well as all the detectors
are accurately described. Flagged muons were propagated through this
environment with GEANT3 [27]. Any muon that crossed the detector apparatus was
treated by a detector response simulation that produced pseudo-raw data, which
was then processed with the same reconstruction code that was applied to real
data, including the TPC tracking algorithm and the track matching algorithm
developed for this analysis.

###  4.1 The muon multiplicity distribution

We generated simulated events equivalent to 30.8 days live time to permit
direct comparison with the data without the need to apply an arbitrary
normalisation factor. A comparison of the trigger corrected, measured MMD with
the simulations is shown in Fig. 6. For ease of comparison, the points
obtained with the simulations were fitted with a power-law function to obtain
the curves for proton and iron.

At lower multiplicities, corresponding to lower primary energies, we find that
the data approach the proton curve, which represents a light ion composition
of the primary cosmic ray flux, while higher multiplicity data lie closer to
the iron curve, representing a heavier composition. The limited statistics in
the range $N_{\mu}>30$ does not allow for a precise, quantitative study of the
composition but suggests that the average mass of the primary cosmic ray flux
increases with increasing energy, a finding consistent with several previous
experiments [28, 29, 30, 31].

The errors in Fig. 6 are shown separately (statistical and systematic) for
data, while for Monte Carlo they are the quadrature sum of the statistical and
systematic uncertainties. The systematic errors in the simulations take into
account uncertainties in the flux of cosmic rays at 1 TeV, the slope of the
energy spectrum below and above the knee, the description of the rock above
the experiment and the uncertainty in the the number of days of data taking
(detector live time). The largest contribution to the systematic error is due
to the uncertainty in the spectral index below the knee ($\gamma=2.7\pm
0.03$), which results in an uncertainty of approximately $15\%$ in the MMD.
The error in the description of the rock above the experiment corresponds to
an uncertainty in the energy threshold of the muons reaching the detector,
which results in a systematic error of approximately $4\%$. Each of the other
uncertainties gives a contribution of around $2\%$ to the systematic error.
For muon multiplicities $N_{\mu}>30$, statistical uncertainties are dominant.

Following success in describing the magnitude and shape of the MMD over this
intermediate range of multiplicities ($7\leq N_{\mu}\leq 70$) we have used the
same simulation framework to study the frequency of HMM events. Since these
are particularly rare events, a very high statistics sample of simulated HMM
events was required to permit a meaningful quantitative comparison.

Figure 6: The measured muon multiplicity distribution compared with the values
and fits obtained from CORSIKA simulations with proton and iron primary cosmic
rays for 30.8 days of data taking. The errors are shown separately
(statistical and systematic) for data, while for Monte Carlo they are the
quadrature sum of the statistical and systematic uncertainties.

###  4.2 High muon multiplicity events

Taking the dataset as a whole, corresponding to 30.8 days and a mixture of
running conditions, we find 5 HMM events with muon multiplicities
$N_{\mu}>100$ (as can be seen in Fig. 5) giving a rate of $1.9\times 10^{-6}$
Hz. Each of these events were examined closely to exclude the possibility of
“interaction” events. The highest multiplicity event reconstructed in the TPC
was found to contain 276 muons, which corresponds to a muon areal density of
18.1 m-2. For illustration, a display of this event is shown in Fig. 7. The
zenithal and azimuthal angular distributions of the muons from the same HMM
event are shown in Fig. 8, while the spatial distribution of matched and
single-track muons at the TPC mid plane is shown in Fig. 9. We note that the
majority of single-track muons are reconstructed near the ends of the TPC
where muons may enter or leave the active volume without producing a track
either the upper or lower halves of the detector.

Figure 7: Event display of a multi-muon event with 276 reconstructed muons
crossing the TPC. Figure 8: Zenithal and azimuthal distribution of the multi-
muon event with 276 reconstructed muons. Figure 9: Spatial distribution of the
276 recostructed muons indicating matched and single-track muons.

One of the aims with this study is to compare the rate of HMM events obtained
from simulations to the measured rate. To limit the effect of fluctuations in
the number of simulated HMM events, we have simulated a live time equivalent
to one year with CORSIKA 6990 using QGSJET II-03 for the hadronic interaction
model. The simplified Monte Carlo used as a first step of the analysis
demonstrated that only primaries with energy $E>10^{16}$ eV contribute to
these events. Therefore, only events in the range of primary energy
$10^{16}<E<10^{18}$ eV have been generated to achieve an equivalent of 365
days exposure for both proton and iron primaries.

The estimated maximum fiducial area of the TPC due to its horizontal
cylindrical geometry and cut on the minimum number of TPC space points is
$17\pm 0.5$ m2. The estimated error in the number of reconstructed muons,
$N_{\mu}$, counting both matched and single-track muons, is around $5\%$ for
$N_{\mu}>100$. HMM events are therefore events with a muon areal density
$\rho_{\mu}>5.9\pm 0.4$ m-2 and correspond to a rate of $1.9\times 10^{-6}$ Hz
at the underground location of ALICE. Based upon the number of observed HMM
events, the estimated relative statistical uncertainty is 45%, giving an error
in the rate of $\pm 0.9\times 10^{-6}$ Hz.

The rate of HMM events obtained with the Monte Carlo can be compared with the
observed rate. Since we have simulated samples of HMM events corresponding to
one year live time, the statistical uncertainty in the simulated rate will be
lower than that in the measured rate. Results obtained for the number of HMM
events expected in one year from both the simplified Monte Carlo and the full
simulation (the first of five statistically independent simulations) are shown
in the first row of Table 1. Comparison of the results demonstrates that the
detailed modelling of the underground environment has about a 30% effect on
the number of HMM events. Due to the small numbers of HMM events we reused the
same simulated EAS sample to perform four additional simulations by randomly
assigning the core of each shower over the usual surface level area of
$205\times 205$ m2. Given that the acceptance of the TPC is almost 3000 times
smaller, this ensures that the samples are statistically independent. A
summary of the results obtained for all five simulations is presented in Table
1 for both CORSIKA 6990 with QGSJET II-03 and CORSIKA 7350 with QGSJET II-04.

| CORSIKA 6990 | CORSIKA 7350
---|---|---
| QGSJET II-03 | QGSJET II-04
| Simple MC | Full MC | Simple MC | Full MC
Run | proton | iron | proton | iron | proton | iron | proton | iron
1 | 40 | 61 | 27 | 51 | 41 | 72 | 30 | 52
2 | 40 | 64 | 24 | 42 | 42 | 88 | 32 | 71
3 | 31 | 43 | 25 | 31 | 48 | 78 | 29 | 62
4 | 26 | 52 | 20 | 34 | 46 | 84 | 35 | 61
5 | 33 | 64 | 22 | 53 | 36 | 83 | 31 | 58
Table 1: Number of HMM events for each run obtained with the simplified Monte
Carlo and the full simulation. Each run is equivalent to 365 days of data
taking. The events have been generated using CORSIKA 6990 with QGSJET II-03
and CORSIKA 7350 with QGSJET II-04.

Final values for the HMM event rate for proton and iron primaries were
calculated by taking the average value obtained from the five simulations,
while the statistical uncertainty was estimated from the standard deviation of
the 5 values from the mean. Table 2 summarises the mean number of HMM events
expected in one year for each primary ion calculated from the full simulation.

| CORSIKA 6990 | CORSIKA 7350
---|---|---
| QGSJET II-03 | QGSJET II-04
| proton | iron | proton | iron
$<N>$ | 23.6 | 42.2 | 31.4 | 60.8
$~{}~{}~{}\sigma$ | 1.3 ($5.5\%$) | 5.0 ($12\%$) | 1.1 ($3.7\%$) | 3.5 ($5.7\%$)
Table 2: Mean value and statistical uncertainty in the number of HMM events
for 365 days live time calculated using the full simulation.

There are two major contributions to the systematic uncertainty on the number
of HMM events. The first contribution stems from the muon reconstruction
algorithm. To estimate its contribution we took the first simulated sample,
corresponding to 365 days of data taking, for each element and each CORSIKA
code version and redetermined the number of HMM events using different tunes
of the track selection and matching algorithms. The second contribution stems
from the uncertainties of the parameters used in the simulations, as discussed
in section 4.1. This was estimated to give an uncertainty in the predicted
rate of HMM events of approximately $20\%$. Due to the large sample used in
the simulations (365 days), the systematic uncertainty is dominant, while in
the data (30.8 days) the statistical uncertainty is dominant. The systematic
uncertainties have been added in quadrature to the statistical uncertainty in
the final comparison of the observed rate of HMM events with that obtained
from the Monte Carlo simulations.

##  5 Results

| CORSIKA 6990 | CORSIKA 7350 |
---|---|---|---
HMM events | QGSJET II-03 | QGSJET II-04 | Data
| proton | iron | proton | iron |
Period [days per event] | 15.5 | 8.6 | 11.6 | 6.0 | 6.2
Rate [$\times 10^{-6}$ Hz] | 0.8 | 1.3 | 1.0 | 1.9 | 1.9
Uncertainty ($\%$) (syst + stat) | 25 | 25 | 22 | 28 | 49
Table 3: Comparison of the HMM event rate obtained with the full simulation
and from measurement.

In Table 3 we present the results of this analysis where we compare the rate
of simulated HMM events with the measured rate. We note that the pure iron
sample simulated with CORSIKA 7350 and QGSJET II-04 produces a HMM event rate
in close agreement with the measured value. The equivalent rate obtained with
CORSIKA 6990 and QGSJET II-03 is lower, although still consistent with the
measured rate. The difference between the two simulations comes primarily from
the hadronic model used to generate the EAS. It is more difficult to reconcile
the measured rate of HMM events with the simulated rate obtained using proton
primaries, independent of the version of the model. However, the large
uncertainty in the measured rate prevents us from drawing a firm conclusion
about the origin of these events, although heavy nuclei appear to be the most
likely candidates. Therefore, an explanation of HMM events in terms of a heavy
primary cosmic ray composition at high energy and EAS described by
conventional hadronic mechanisms appears to be compatible with our
observations. This is consistent with the fact that they stem from primaries
with energies $E>10^{16}$ eV, where recent measurements [32, 33] suggest that
the composition of the primary cosmic ray spectrum is dominated by heavier
elements.

Finally, we have investigated the distribution of simulated EAS core positions
at the location of ALICE for each of the HMM events simulated with iron
primaries using CORSIKA 7350 and QGSJET II-04 in Table 1, equivalent to 5
years of data taking. The distribution is shown in Fig. 10, where the colour
of each point indicates the energy associated with the primary cosmic ray so
as to give a visual representation of the correlation between the distance of
the core from the centre of ALICE at surface level and the energy of the
primary cosmic ray. We note that the shower cores of all HMM events fall
within an area of approximately $140\times 140$ m2 centred upon ALICE, which
is located at the origin in Fig. 10. The average distance of the shower core
from the centre of ALICE for all events is 19 m and the RMS value of the
distribution is 16 m. Primaries with an energy $E>3\times 10^{17}$ eV,
corresponding to the highest energy interval studied in this analysis, produce
larger showers that may give rise to HMM events when the shower core falls
farther from the location of ALICE. In this case, the mean of the shower core
distribution from the centre of ALICE is 37 m and the RMS value of the
distribution is 18 m.

Figure 10: The surface level spatial distribution of the cores of simulated
EAS giving rise to more than 100 muons in the ALICE Time Projection Chamber.
The simulation was for iron primaries in the energy range $10^{16}-10^{18}$ eV
and corresponds to the equivalent of 5 years of data taking.

##  6 Summary

In the period 2010 to 2013, ALICE acquired 30.8 days of dedicated cosmic ray
data recording approximately 22.6 million events containing at least one
reconstructed muon. Comparison of the measured muon multiplicity distribution
with an equivalent sample of Monte Carlo events suggests a mixed-ion primary
cosmic ray composition with an average mass that increases with energy. This
observation is in agreement with most experiments working in the energy range
of the knee. Following the successful description of the magnitude of the MMD
in the low-to-intermediate range of muon multiplicities we used the same
simulation framework to study the frequency of HMM events.

High muon multiplicity events were observed in the past by experiments at LEP
but without satisfactory explanation. Similar high multiplicity events have
been observed in this study with ALICE. Over the 30.8 days of data taking
reported in this paper, 5 events with more than 100 muons and zenith angles
less than $50^{\circ}$ have been recorded. We have found that the observed
rate of HMM events is consistent with the rate predicted by CORSIKA 7350 using
QGSJET II-04 to model the development of the resulting air shower, assuming a
pure iron composition for the primary cosmic rays. Only primary cosmic rays
with an energy $E>10^{16}$ eV were found to give rise to HMM events. This
observation is compatible with a knee in the cosmic ray energy distribution
around $3\times 10^{15}$ eV due to the light component followed by a spectral
steepening, the onset of which depends on the atomic number (Z) of the
primary.

The expected rate of HMM events is sensitive to assumptions made about the
dominant hadronic production mechanisms in air shower development. The latest
version of QGSJET differs from earlier versions in its treatment of forward
neutral meson production resulting in a higher muon yield and has been retuned
taking into account early LHC results on hadron production in 7 TeV proton-
proton collisions. This is the first time that the rate of HMM events,
observed at the relatively shallow depth of ALICE, has been satisfactorily
reproduced using a conventional hadronic model for the description of
extensive air showers; an observation that places significant constraints on
alternative, more exotic, production mechanisms.

Compared to the previous studies at LEP, there are two distinguishing aspects
of this work that have led to these new insights into the origin of HMM
events. The first has been the ability to generate large samples of very
energetic cosmic rays, allowing for a more reliable estimate of the expected
rate of these events. The second, and more important, aspect has been the
recent advances in the hadronic description of EAS. This is a continually
evolving field. We note that in a preparatory study [18] carried out by ALICE
in 2004, using an older version of CORSIKA (version 6031), no HMM events were
observed in the MMD distribution simulated for 30 days of data taking with a
pure iron primary cosmic ray composition. In the present work, Table 3 gives a
quantitative comparison of the rate of HMM events predicted by two more recent
versions of CORSIKA and QGSJET, illustrating the evolution of the hadronic
description of EAS in recent years. Only in the latest version of the model
there has been a significant increase in the rate of HMM events that better
approaches the rate observed in this study.

## 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: State
Committee of Science, World Federation of Scientists (WFS) and Swiss Fonds
Kidagan, Armenia, 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); National Natural Science
Foundation of China (NSFC), the Chinese Ministry of Education (CMOE) and the
Ministry of Science and Technology of China (MSTC); Ministry of Education and
Youth of the Czech Republic; Danish Natural Science Research Council, the
Carlsberg Foundation and the Danish National Research Foundation; The European
Research Council under the European Community’s Seventh Framework Programme;
Helsinki Institute of Physics and the Academy of Finland; French CNRS-IN2P3,
the ‘Region Pays de Loire’, ‘Region Alsace’, ‘Region Auvergne’ and CEA,
France; German Bundesministerium fur Bildung, Wissenschaft, Forschung und
Technologie (BMBF) and the Helmholtz Association; General Secretariat for
Research and Technology, Ministry of Development, Greece; Hungarian Orszagos
Tudomanyos Kutatasi Alappgrammok (OTKA) and National Office for Research and
Technology (NKTH); Department of Atomic Energy and Department of Science and
Technology of the Government of India; Istituto Nazionale di Fisica Nucleare
(INFN) and Centro Fermi - Museo Storico della Fisica e Centro Studi e Ricerche
”Enrico Fermi”, Italy; MEXT Grant-in-Aid for Specially Promoted Research,
Japan; Joint Institute for Nuclear Research, Dubna; National Research
Foundation of Korea (NRF); Consejo Nacional de Cienca y Tecnologia (CONACYT),
Direccion General de Asuntos del Personal Academico(DGAPA), México, :Amerique
Latine Formation academique – European Commission(ALFA-EC) and the EPLANET
Program (European Particle Physics Latin American Network) Stichting voor
Fundamenteel Onderzoek der Materie (FOM) and the Nederlandse Organisatie voor
Wetenschappelijk Onderzoek (NWO), Netherlands; Research Council of Norway
(NFR); National Science Centre, Poland; Ministry of National
Education/Institute for Atomic Physics and Consiliul Naţional al Cercetării
Ştiinţifice - Executive Agency for Higher Education Research Development and
Innovation Funding (CNCS-UEFISCDI) - Romania; Ministry of Education and
Science of Russian Federation, Russian Academy of Sciences, Russian Federal
Agency of Atomic Energy, Russian Federal Agency for Science and Innovations
and The Russian Foundation for Basic Research; Ministry of Education of
Slovakia; Department of Science and Technology, South Africa; Centro de
Investigaciones Energeticas, Medioambientales y Tecnologicas (CIEMAT),
E-Infrastructure shared between Europe and Latin America (EELA), Ministerio de
Economía y Competitividad (MINECO) of Spain, Xunta de Galicia (Consellería de
Educación), Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN),
Cubaenergía, Cuba, and IAEA (International Atomic Energy Agency); Swedish
Research Council (VR) and Knut $\&$ Alice Wallenberg Foundation (KAW); Ukraine
Ministry of Education and Science; United Kingdom Science and Technology
Facilities Council (STFC); The United States Department of Energy, the United
States National Science Foundation, the State of Texas, and the State of Ohio;
Ministry of Science, Education and Sports of Croatia and Unity through
Knowledge Fund, Croatia. Council of Scientific and Industrial Research (CSIR),
New Delhi, India

## References

  * [1] ALICE Collaboration, K. Aamodt et al., “The ALICE experiment at the CERN LHC,” JINST 3 (2008) S08002.
  * [2] C. Grupen, M. Kurt, A. Mailov, A. Muller, A. Putzer, B. Rensch, H. Sander, S. Schmeling, M. Schmelling, H. Wachsmuth, T. Ziegler, and K. Zuber, “Measurements of the muon component of extensive air showers at 320 m.w.e. underground,” Nuclear Instruments and Methods in Physics Research Section A 510 no. 1-2, (2003) 190 – 193. http://www.sciencedirect.com/science/article/pii/S0168900203016978.
  * [3] DELPHI Collaboration, J. Ridky and P. Travnicek, “Detection of muon bundles from cosmic ray showers by the DELPHI experiment,” Nucl. Phys. B, Proc. Suppl. 138 (2005) 295–298. https://cds.cern.ch/record/1073685.
  * [4] L3 Collaboration, P. Achard et al., “Measurement of the atmospheric muon spectrum from 20-GeV to 3000-GeV,” Phys.Lett. B598 (2004) 15–32, arXiv:hep-ex/0408114 [hep-ex].
  * [5] M. Aglietta et al., “The EAS size spectrum and the cosmic ray energy spectrum in the region $10^{15}-10^{16}$ eV,” Astroparticle Physics 10 no. 1, (1999) 1 – 9. http://www.sciencedirect.com/science/article/pii/S0927650598000358.
  * [6] M. Glasmacher et al., “The cosmic ray energy spectrum between $10^{14}$ and $10^{16}$ eV,” Astroparticle Physics 10 no. 4, (1999) 291 – 302. http://www.sciencedirect.com/science/article/pii/S092765059800070X.
  * [7] T. Antoni et al., “Electron, muon, and hadron lateral distributions measured in air showers by the kascade experiment,” Astroparticle Physics 14 no. 4, (2001) 245 – 260. http://www.sciencedirect.com/science/article/pii/S0927650500001250.
  * [8] NUSEX Collaboration, G. Battistoni et al., “Cosmic-muon results from the NUSEX experiment,” Il Nuovo Cimento C 9 no. 2, (1986) 196–209, 0390-5551.
  * [9] M. Ambrosio et al., “Vertical muon intensity measured with MACRO at the Gran Sasso laboratory,” Phys. Rev. D 52 (Oct, 1995) 3793–3802. http://link.aps.org/doi/10.1103/PhysRevD.52.3793.
  * [10] P. Kuusiniemi, L. Bezrukov, T. Enqvist, H. Fynbo, L. Inzhechik, J. Joutsenvaara, T. Kalliokoski, K. Loo, B. Lubsandorzhiev, T. Monto, V. Petkov, T. Raiha, J. Sarkamo, M. Slupecki, W. H. Trzaska, and A. Virkajarvi, “Underground cosmic-ray experiment emma,” Journal of Physics: Conference Series 409 no. 1, (2013) 012067. http://stacks.iop.org/1742-6596/409/i=1/a=012067.
  * [11] V. Avati, L. Dick, K. Eggert, J. Strom, H. Wachsmuth, et al., “Cosmic multi-muon events observed in the underground CERN-LEP tunnel with the ALEPH experiment,” Astropart.Phys. 19 (2003) 513–523.
  * [12] DELPHI Collaboration, J. Abdallah et al., “Study of multi-muon bundles in cosmic ray showers detected with the DELPHI detector at LEP,” Astropart.Phys. 28 (2007) 273–286, arXiv:0706.2561 [astro-ph].
  * [13] M. Rybczynski, Z. Wlodarczyk, and G. Wilk, “Strangelets in cosmic rays,” Nucl.Phys.Proc.Suppl. 151 (2006) 341–344, arXiv:hep-ph/0410064 [hep-ph].
  * [14] J. Ridky, “Can we observe the quark gluon plasma in cosmic ray showers?,” Astropart.Phys. 17 (2002) 355–365, arXiv:hep-ph/0012068 [hep-ph].
  * [15] J. Alme, Y. Andres, H. Appelshauser, S. Bablok, N. Bialas, et al., “The ALICE TPC, a large 3-dimensional tracking device with fast readout for ultra-high multiplicity events,” Nucl.Instrum.Meth. A622 (2010) 316–367, arXiv:1001.1950 [physics.ins-det].
  * [16] S. Ostapchenko, “QGSJET-II: Towards reliable description of very high energy hadronic interactions,” Nucl.Phys.Proc.Suppl. 151 (2006) 143–146, arXiv:hep-ph/0412332 [hep-ph].
  * [17] S. Ostapchenko, “Non-linear screening effects in high energy hadronic interactions,” Phys.Rev. D74 (2006) 014026, arXiv:hep-ph/0505259 [hep-ph].
  * [18] ALICE Collaboration, B. Alessandro et al., “ALICE: Physics performance report, volume II,” J.Phys. G32 (2006) 1295–2040.
  * [19] E. Cuautle, A. Fernandez, et al., “ACORDE, The ALICE cosmic ray detector,” Proceedings of the 30th International Cosmic Ray Conference 5 (2008) 1201–1204.
  * [20] R. Santoro, G. Aglieri Rinella, F. Antinori, A. Badala, F. Blanco, et al., “The ALICE Silicon Pixel Detector: Readiness for the first proton beam,” JINST 4 (2009) P03023.
  * [21] A. Akindinov, A. Alici, A. Agostinelli, P. Antonioli, S. Arcelli, et al., “Performance of the ALICE Time-Of-Flight detector at the LHC,” Eur.Phys.J.Plus 128 (2013) 44.
  * [22] ALICE Collaboration, B. B. Abelev et al., “Performance of the ALICE Experiment at the CERN LHC,” Int.J.Mod.Phys. A29 (2014) 1430044, arXiv:1402.4476 [nucl-ex].
  * [23] D. Heck, G. Schatz, T. Thouw, J. Knapp, and J. Capdevielle, “CORSIKA: A Monte Carlo code to simulate extensive air showers,” FZKA-6019 (1998) .
  * [24] S. Ostapchenko, “Monte Carlo treatment of hadronic interactions in enhanced Pomeron scheme: I. QGSJET-II model,” Phys.Rev. D83 (2011) 014018, arXiv:1010.1869 [hep-ph].
  * [25] S. Ostapchenko, “QGSJET-II: physics, recent improvements, and results for air showers,” EPJ Web Conf. 52 (2013) 02001.
  * [26] J. R. Hoerandel, “On the knee in the energy spectrum of cosmic rays,” Astropart.Phys. 19 (2003) 193–220, arXiv:astro-ph/0210453 [astro-ph].
  * [27] R. Brun, F. Carminati, and S. Giani, “GEANT Detector Description and Simulation Tool,” CERN-W-5013 (1994) .
  * [28] EAS-TOP Collaboration, M. Aglietta et al., “The cosmic ray primary composition in the ’knee’ region through the EAS electromagnetic and muon measurements at EAS-TOP,” Astropart.Phys. 21 (2004) 583–596.
  * [29] M. Glasmacher, M. Catanese, M. Chantell, C. Covault, J. Cronin, et al., “The cosmic ray composition between $10^{14}$ and $10^{16}$ eV,” Astropart.Phys. 12 (1999) 1–17.
  * [30] MACRO, EAS-TOP Collaboration, M. Aglietta et al., “The Primary cosmic ray composition between $10^{15}$ and $10^{16}$ eV from extensive air showers electromagnetic and TeV muon data,” Astropart.Phys. 20 (2004) 641–652, arXiv:astro-ph/0305325 [astro-ph].
  * [31] KASCADE Collaboration, T. Antoni et al., “KASCADE measurements of energy spectra for elemental groups of cosmic rays: Results and open problems,” Astropart.Phys. 24 (2005) 1–25, arXiv:astro-ph/0505413 [astro-ph].
  * [32] W. D. Apel et al., “Kneelike structure in the spectrum of the heavy component of cosmic rays observed with kascade-grande,” Phys. Rev. Lett. 107 (Oct, 2011) 171104. http://link.aps.org/doi/10.1103/PhysRevLett.107.171104.
  * [33] S. Berezhnev et al., “Energy spectrum and mass composition of cosmic rays, by the data of the tunka-133 array,” Bulletin of the Russian Academy of Sciences: Physics 79 no. 3, (2015) 344–347. http://dx.doi.org/10.3103/S1062873815030090.

##  Appendix A ALICE Collaboration

J. Adamorg40&D. Adamováorg83&M.M. Aggarwalorg87&G. Aglieri Rinellaorg36&M.
Agnelloorg110&N. Agrawalorg48&Z. Ahammedorg132&S.U. Ahnorg68&S. Aiolaorg136&A.
Akindinovorg58&S.N. Alamorg132&D. Aleksandrovorg99&B. Alessandroorg110&D.
Alexandreorg101&R. Alfaro Molinaorg64&A. Aliciorg12,org104&A. Alkinorg3&J.R.M.
Almarazorg119&J. Almeorg38&T. Altorg43&S. Altinpinarorg18&I.
Altsybeevorg131&C. Alves Garcia Pradoorg120&C. Andreiorg78&A. Andronicorg96&V.
Anguelovorg93&J. Anielskiorg54&T. Antičićorg97&F. Antinoriorg107&P.
Antonioliorg104&L. Aphecetcheorg113&H. Appelshäuserorg53&S. Arcelliorg28&N.
Armestoorg17&R. Arnaldiorg110&I.C. Arseneorg22&M. Arslandokorg53&B.
Audurierorg113&A. Augustinusorg36&R. Averbeckorg96&M.D. Azmiorg19&M.
Bachorg43&A. Badalàorg106&Y.W. Baekorg44&S. Bagnascoorg110&R.
Bailhacheorg53&R. Balaorg90&A. Baldisseriorg15&F. Baltasar Dos Santos
Pedrosaorg36&R.C. Baralorg61&A.M. Barbanoorg110&R. Barberaorg29&F.
Barileorg33&G.G. Barnaföldiorg135&L.S. Barnbyorg101&V. Barretorg70&P.
Bartaliniorg7&K. Barthorg36&J. Bartkeorg117&E. Bartschorg53&M. Basileorg28&N.
Bastidorg70&S. Basuorg132&B. Bathenorg54&G. Batigneorg113&A. Batista
Camejoorg70&B. Batyunyaorg66&P.C. Batzingorg22&I.G. Beardenorg80&H.
Beckorg53&C. Beddaorg110&I. Belikovorg55&F. Belliniorg28&H. Bello
Martinezorg2&R. Bellwiedorg122&R. Belmontorg134&E. Belmont-Morenoorg64&V.
Belyaevorg76&G. Bencediorg135&S. Beoleorg27&I. Berceanuorg78&A.
Bercuciorg78&Y. Berdnikovorg85&D. Berenyiorg135&R.A. Bertensorg57&D.
Berzanoorg27,org36&L. Betevorg36&A. Bhasinorg90&I.R. Bhatorg90&A.K.
Bhatiorg87&B. Bhattacharjeeorg45&J. Bhomorg128&L. Bianchiorg122&N.
Bianchiorg72&C. Bianchinorg134,org57&J. Bielčíkorg40&J. Bielčíkováorg83&A.
Bilandzicorg80&R. Biswasorg4&S. Biswasorg79&S. Bjelogrlicorg57&J.T.
Blairorg118&F. Blancoorg10&D. Blauorg99&C. Blumeorg53&F. Bockorg93,org74&A.
Bogdanovorg76&H. Bøggildorg80&L. Boldizsárorg135&M. Bombaraorg41&J.
Bookorg53&H. Borelorg15&A. Borissovorg95&M. Borriorg82&F. Bossúorg65&E.
Bottaorg27&S. Böttgerorg52&P. Braun-Munzingerorg96&M. Bregantorg120&T.
Breitnerorg52&T.A. Brokerorg53&T.A. Browningorg94&M. Brozorg40&E.J.
Bruckenorg46&E. Brunaorg110&G.E. Brunoorg33&D. Budnikovorg98&H.
Bueschingorg53&S. Bufalinoorg27,org36&P. Buncicorg36&O. Buschorg128,org93&Z.
Butheleziorg65&J.B. Buttorg16&J.T. Buxtonorg20&D. Caffarriorg36&X. Caiorg7&H.
Cainesorg136&L. Calero Diazorg72&A. Calivaorg57&E. Calvo Villarorg102&P.
Cameriniorg26&F. Carenaorg36&W. Carenaorg36&F. Carnesecchiorg28&J. Castillo
Castellanosorg15&A.J. Castroorg125&E.A.R. Casulaorg25&C. Cavicchioliorg36&C.
Ceballos Sanchezorg9&J. Cepilaorg40&P. Cerelloorg110&J. Cerkalaorg115&B.
Changorg123&S. Chapelandorg36&M. Chartierorg124&J.L. Charvetorg15&S.
Chattopadhyayorg132&S. Chattopadhyayorg100&V. Chelnokovorg3&M. Cherneyorg86&C.
Cheshkovorg130&B. Cheynisorg130&V. Chibante Barrosoorg36&D.D.
Chinellatoorg121&S. Choorg50&P. Chochulaorg36&K. Choiorg95&M.
Chojnackiorg80&S. Choudhuryorg132&P. Christakoglouorg81&C.H.
Christensenorg80&P. Christiansenorg34&T. Chujoorg128&S.U. Chungorg95&Z.
Chunhuiorg57&C. Cicaloorg105&L. Cifarelliorg12,org28&F. Cindoloorg104&J.
Cleymansorg89&F. Colamariaorg33&D. Colellaorg36,org33,org59&A. Colluorg25&M.
Colocciorg28&G. Conesa Balbastreorg71&Z. Conesa del Valleorg51&M.E.
Connorsorg136&J.G. Contrerasorg11,org40&T.M. Cormierorg84&Y. Corrales
Moralesorg27&I. Cortés Maldonadoorg2&P. Corteseorg32&M.R. Cosentinoorg120&F.
Costaorg36&P. Crochetorg70&R. Cruz Albinoorg11&E. Cuautleorg63&L.
Cunqueiroorg36&T. Dahmsorg92,org37&A. Daineseorg107&A. Danuorg62&D.
Dasorg100&I. Dasorg100,org51&S. Dasorg4&A. Dashorg121&S. Dashorg48&S.
Deorg120&A. De Caroorg31,org12&G. de Cataldoorg103&J. de Cuvelandorg43&A. De
Falcoorg25&D. De Gruttolaorg12,org31&N. De Marcoorg110&S. De Pasqualeorg31&A.
Deistingorg96,org93&A. Delofforg77&E. Dénesorg1350&G. D’Erasmoorg33&P.
Dhankherorg48&D. Di Bariorg33&A. Di Mauroorg36&P. Di Nezzaorg72&M.A. Diaz
Corcheroorg10&T. Dietelorg89&P. Dillensegerorg53&R. Diviàorg36&Ø.
Djuvslandorg18&A. Dobrinorg57,org81&T. Dobrowolskiorg770&D. Domenicis
Gimenezorg120&B. Dönigusorg53&O. Dordicorg22&T. Drozhzhovaorg53&A.K.
Dubeyorg132&A. Dublaorg57&L. Ducrouxorg130&P. Dupieuxorg70&R.J.
Ehlersorg136&D. Eliaorg103&H. Engelorg52&E. Eppleorg136&B.
Erazmusorg113,org36&I. Erdemirorg53&F. Erhardtorg129&B. Espagnonorg51&M.
Estienneorg113&S. Esumiorg128&J. Eumorg95&D. Evansorg101&S. Evdokimovorg111&G.
Eyyubovaorg40&L. Fabbiettiorg92,org37&D. Fabrisorg107&J. Faivreorg71&A.
Fantoniorg72&M. Faselorg74&L. Feldkamporg54&D. Feleaorg62&A.
Felicielloorg110&G. Feofilovorg131&J. Ferenceiorg83&A. Fernández
Téllezorg2&E.G. Ferreiroorg17&A. Ferrettiorg27&A. Festantiorg30&V.J.G.
Feuillardorg70,org15&J. Figielorg117&M.A.S. Figueredoorg120,org124&S.
Filchaginorg98&D. Finogeevorg56&F.M. Fiondaorg25&E.M. Fioreorg33&M.G.
Fleckorg93&M. Florisorg36&S. Foertschorg65&P. Fokaorg96&S. Fokinorg99&E.
Fragiacomoorg109&A. Francesconorg36,org30&U. Frankenfeldorg96&U. Fuchsorg36&C.
Furgetorg71&A. Fursorg56&M. Fusco Girardorg31&J.J. Gaardhøjeorg80&M.
Gagliardiorg27&A.M. Gagoorg102&M. Gallioorg27&D.R. Gangadharanorg74&P.
Ganotiorg88,org36&C. Gaoorg7&C. Garabatosorg96&E. Garcia-Solisorg13&C.
Gargiuloorg36&P. Gasikorg37,org92&E.F. Gaugerorg118&M. Germainorg113&A.
Gheataorg36&M. Gheataorg36,org62&P. Ghoshorg132&S.K. Ghoshorg4&P.
Gianottiorg72&P. Giubellinoorg36,org110&P. Giubilatoorg30&E. Gladysz-
Dziadusorg117&P. Glässelorg93&D.M. Goméz Coralorg64&A. Gomez Ramirezorg52&P.
González-Zamoraorg10&S. Gorbunovorg43&L. Görlichorg117&S. Gotovacorg116&V.
Grabskiorg64&L.K. Graczykowskiorg133&K.L. Grahamorg101&A. Grelliorg57&A.
Grigorasorg36&C. Grigorasorg36&V. Grigorievorg76&A. Grigoryanorg1&S.
Grigoryanorg66&B. Grinyovorg3&N. Grionorg109&J.F. Grosse-
Oetringhausorg36&J.-Y. Grossiordorg130&R. Grossoorg36&F. Guberorg56&R.
Guernaneorg71&B. Guerzoniorg28&K. Gulbrandsenorg80&H. Gulkanyanorg1&T.
Gunjiorg127&A. Guptaorg90&R. Guptaorg90&R. Haakeorg54&Ø. Haalandorg18&C.
Hadjidakisorg51&M. Haiducorg62&H. Hamagakiorg127&G. Hamarorg135&J.W.
Harrisorg136&A. Hartonorg13&D. Hatzifotiadouorg104&S. Hayashiorg127&S.T.
Heckelorg53&M. Heideorg54&H. Helstruporg38&A. Herghelegiuorg78&G. Herrera
Corralorg11&B.A. Hessorg35&K.F. Hetlandorg38&T.E. Hildenorg46&H.
Hillemannsorg36&B. Hippolyteorg55&R. Hosokawaorg128&P. Hristovorg36&M.
Huangorg18&T.J. Humanicorg20&N. Hussainorg45&T. Hussainorg19&D.
Hutterorg43&D.S. Hwangorg21&R. Ilkaevorg98&I. Ilkivorg77&M. Inabaorg128&M.
Ippolitovorg76,org99&M. Irfanorg19&M. Ivanovorg96&V. Ivanovorg85&V.
Izucheevorg111&P.M. Jacobsorg74&M.B. Jadhavorg48&S. Jadlovskaorg115&C.
Jahnkeorg120&H.J. Jangorg68&M.A. Janikorg133&P.H.S.Y. Jayarathnaorg122&C.
Jenaorg79,org30&S. Jenaorg122&R.T. Jimenez Bustamanteorg96&P.G. Jonesorg101&H.
Jungorg44&A. Juskoorg101&P. Kalinakorg59&A. Kalweitorg36&J. Kaminorg53&J.H.
Kangorg137&V. Kaplinorg76&S. Karorg132&A. Karasu Uysalorg69&O.
Karavichevorg56&T. Karavichevaorg56&L. Karayanorg93,org96&E. Karpechevorg56&U.
Kebschullorg52&R. Keidelorg138&D.L.D. Keijdenerorg57&M. Keilorg36&M. Mohisin
Khanorg19&P. Khanorg100&S.A. Khanorg132&A. Khanzadeevorg85&Y. Kharlovorg111&B.
Kilengorg38&B. Kimorg137&D.W. Kimorg44&D.J. Kimorg123&H. Kimorg137&J.S.
Kimorg44&M. Kimorg44&M. Kimorg137&S. Kimorg21&T. Kimorg137&S. Kirschorg43&I.
Kiselorg43&S. Kiselevorg58&A. Kisielorg133&G. Kissorg135&J.L. Klayorg6&C.
Kleinorg53&J. Kleinorg36,org93&C. Klein-Bösingorg54&A. Klugeorg36&M.L.
Knichelorg93&A.G. Knospeorg118&T. Kobayashiorg128&C. Kobdajorg114&M.
Kofaragoorg36&T. Kolleggerorg96,org43&A. Kolojvariorg131&V.
Kondratievorg131&N. Kondratyevaorg76&E. Kondratyukorg111&A. Konevskikhorg56&M.
Kopcikorg115&M. Kourorg90&C. Kouzinopoulosorg36&O. Kovalenkoorg3,org77&V.
Kovalenkoorg131&M. Kowalskiorg117&G. Koyithatta Meethaleveeduorg48&J.
Kralorg123&I. Králikorg59&A. Kravčákováorg41&M. Kretzorg43&M.
Krivdaorg101,org59&F. Krizekorg83&E. Kryshenorg36&M. Krzewickiorg43&A.M.
Kuberaorg20&V. Kučeraorg83&T. Kugathasanorg36&C. Kuhnorg55&P.G. Kuijerorg81&A.
Kumarorg90&J. Kumarorg48&L. Kumarorg79,org87&S. Kumarorg48&P.
Kurashviliorg77&A. Kurepinorg56&A.B. Kurepinorg56&A. Kuryakinorg98&S.
Kushpilorg83&M.J. Kweonorg50&Y. Kwonorg137&S.L. La Pointeorg110&P. La
Roccaorg29&C. Lagana Fernandesorg120&I. Lakomovorg36&R. Langoyorg42&C.
Laraorg52&A. Lardeuxorg15&A. Lattucaorg27&E. Laudiorg36&R. Leaorg26&L.
Leardiniorg93&G.R. Leeorg101&S. Leeorg137&I. Legrandorg36&F. Lehasorg81&R.C.
Lemmonorg82&V. Lentiorg103&E. Leograndeorg57&I. León Monzónorg119&M.
Leoncinoorg27&P. Lévaiorg135&S. Liorg7,org70&X. Liorg14&J. Lienorg42&R.
Lietavaorg101&S. Lindalorg22&V. Lindenstruthorg43&C. Lippmannorg96&M.A.
Lisaorg20&H.M. Ljunggrenorg34&D.F. Lodatoorg57&P.I. Loenneorg18&V.
Loginovorg76&C. Loizidesorg74&X. Lopezorg70&E. López Torresorg9&A.
Loweorg135&P. Luettigorg53&M. Lunardonorg30&G. Luparelloorg26&P.H.F.N.D.
Luzorg120&A. Maevskayaorg56&M. Magerorg36&S. Mahajanorg90&S.M. Mahmoodorg22&A.
Maireorg55&R.D. Majkaorg136&M. Malaevorg85&I. Maldonado Cervantesorg63&L.
Malininaidp3805088,org66&D. Mal’Kevichorg58&P. Malzacherorg96&A.
Mamonovorg98&V. Mankoorg99&F. Mansoorg70&V. Manzariorg103,org36&M.
Marchisoneorg27,org89&J. Marešorg60&G.V. Margagliottiorg26&A.
Margottiorg104&J. Marguttiorg57&A. Marínorg96&C. Markertorg118&M.
Marquardorg53&N.A. Martinorg96&J. Martin Blancoorg113&P. Martinengoorg36&M.I.
Martínezorg2&G. Martínez Garcíaorg113&M. Martinez Pedreiraorg36&Y.
Martynovorg3&A. Masorg120&S. Masciocchiorg96&M. Maseraorg27&A. Masoniorg105&L.
Massacrierorg113&A. Mastroserioorg33&H. Masuiorg128&A. Matyjaorg117&C.
Mayerorg117&J. Mazerorg125&M.A. Mazzoniorg108&D. Mcdonaldorg122&F.
Meddiorg24&Y. Melikyanorg76&A. Menchaca-Rochaorg64&E. Meninnoorg31&J. Mercado
Pérezorg93&M. Meresorg39&Y. Miakeorg128&M.M. Mieskolainenorg46&K.
Mikhaylovorg66,org58&L. Milanoorg36&J. Milosevicorg22&L.M.
Minerviniorg23,org103&A. Mischkeorg57&A.N. Mishraorg49&D. Miśkowiecorg96&J.
Mitraorg132&C.M. Mituorg62&N. Mohammadiorg57&B. Mohantyorg132,org79&L.
Molnarorg55&L. Montaño Zetinaorg11&E. Montesorg10&M. Morandoorg30&D.A. Moreira
De Godoyorg113,org54&L.A.P. Morenoorg2&S. Morettoorg30&A. Morrealeorg113&A.
Morschorg36&V. Mucciforaorg72&E. Mudnicorg116&D. Mühlheimorg54&S.
Muhuriorg132&M. Mukherjeeorg132&J.D. Mulliganorg136&M.G. Munhozorg120&R.H.
Munzerorg37,org92&S. Murrayorg65&L. Musaorg36&J. Musinskyorg59&B. Naikorg48&R.
Nairorg77&B.K. Nandiorg48&R. Naniaorg104&E. Nappiorg103&M.U. Naruorg16&C.
Nattrassorg125&K. Nayakorg79&T.K. Nayakorg132&S. Nazarenkoorg98&A.
Nedosekinorg58&L. Nellenorg63&F. Ngorg122&M. Nicassioorg96&M.
Niculescuorg62,org36&J. Niedzielaorg36&B.S. Nielsenorg80&S. Nikolaevorg99&S.
Nikulinorg99&V. Nikulinorg85&F. Noferiniorg104,org12&P. Nomokonovorg66&G.
Noorenorg57&J.C.C. Norisorg2&J. Normanorg124&A. Nyaninorg99&J.
Nystrandorg18&H. Oeschlerorg93&S. Ohorg136&S.K. Ohorg67&A. Ohlsonorg36&A.
Okatanorg69&T. Okuboorg47&L. Olahorg135&J. Oleniaczorg133&A.C. Oliveira Da
Silvaorg120&M.H. Oliverorg136&J. Onderwaaterorg96&C. Oppedisanoorg110&R.
Oravaorg46&A. Ortiz Velasquezorg63&A. Oskarssonorg34&J. Otwinowskiorg117&K.
Oyamaorg93&M. Ozdemirorg53&Y. Pachmayerorg93&P. Paganoorg31&G. Paićorg63&C.
Pajaresorg17&S.K. Palorg132&J. Panorg134&A.K. Pandeyorg48&D. Pantorg48&P.
Papcunorg115&V. Papikyanorg1&G.S. Pappalardoorg106&P. Pareekorg49&W.J.
Parkorg96&S. Parmarorg87&A. Passfeldorg54&V. Paticchioorg103&R.N.
Patraorg132&B. Paulorg100&T. Peitzmannorg57&H. Pereira Da Costaorg15&E.
Pereira De Oliveira Filhoorg120&D. Peresunkoorg99,org76&C.E. Pérez
Laraorg81&E. Perez Lezamaorg53&V. Peskovorg53&Y. Pestovorg5&V.
Petráčekorg40&V. Petrovorg111&M. Petroviciorg78&C. Pettaorg29&S.
Pianoorg109&M. Piknaorg39&P. Pillotorg113&O. Pinazzaorg104,org36&L.
Pinskyorg122&D.B. Piyarathnaorg122&M. Płoskońorg74&M. Planinicorg129&J.
Plutaorg133&S. Pochybovaorg135&P.L.M. Podesta-Lermaorg119&M.G.
Poghosyanorg86,org84&B. Polichtchoukorg111&N. Poljakorg129&W.
Poonsawatorg114&A. Poporg78&S. Porteboeuf-Houssaisorg70&J. Porterorg74&J.
Pospisilorg83&S.K. Prasadorg4&R. Preghenellaorg36,org104&F. Prinoorg110&C.A.
Pruneauorg134&I. Pshenichnovorg56&M. Puccioorg110&G. Pudduorg25&P.
Pujahariorg134&V. Puninorg98&J. Putschkeorg134&H. Qvigstadorg22&A.
Rachevskiorg109&S. Rahaorg4&S. Rajputorg90&J. Rakorg123&A.
Rakotozafindrabeorg15&L. Ramelloorg32&F. Ramiorg55&R. Raniwalaorg91&S.
Raniwalaorg91&S.S. Räsänenorg46&B.T. Rascanuorg53&D. Ratheeorg87&K.F.
Readorg125&J.S. Realorg71&K. Redlichorg77&R.J. Reedorg134&A. Rehmanorg18&P.
Reicheltorg53&F. Reidtorg93,org36&X. Renorg7&R. Renfordtorg53&A.R.
Reolonorg72&A. Reshetinorg56&F. Rettigorg43&J.-P. Revolorg12&K.
Reygersorg93&V. Riabovorg85&R.A. Ricciorg73&T. Richertorg34&M. Richterorg22&P.
Riedlerorg36&W. Rieglerorg36&F. Riggiorg29&C. Risteaorg62&A. Rivettiorg110&E.
Roccoorg57&M. Rodríguez Cahuantziorg2&A. Rodriguez Mansoorg81&K. Røedorg22&E.
Rogochayaorg66&D. Rohrorg43&D. Röhrichorg18&R. Romitaorg124&F.
Ronchettiorg72,org36&L. Ronfletteorg113&P. Rosnetorg70&A. Rossiorg30,org36&F.
Roukoutakisorg88&A. Royorg49&C. Royorg55&P. Royorg100&A.J. Rubio
Monteroorg10&R. Ruiorg26&R. Russoorg27&E. Ryabinkinorg99&Y. Ryabovorg85&A.
Rybickiorg117&S. Sadovskyorg111&K. Šafaříkorg36&B. Sahlmullerorg53&P.
Sahooorg49&R. Sahooorg49&S. Sahooorg61&P.K. Sahuorg61&J. Sainiorg132&S.
Sakaiorg72&M.A. Salehorg134&C.A. Salgadoorg17&J. Salzwedelorg20&S.
Sambyalorg90&V. Samsonovorg85&L. Šándororg59&A. Sandovalorg64&M. Sanoorg128&D.
Sarkarorg132&E. Scapparoneorg104&F. Scarlassaraorg30&R.P. Scharenbergorg94&C.
Schiauaorg78&R. Schickerorg93&C. Schmidtorg96&H.R. Schmidtorg35&S.
Schuchmannorg53&J. Schukraftorg36&M. Schulcorg40&T. Schusterorg136&Y.
Schutzorg36,org113&K. Schwarzorg96&K. Schwedaorg96&G. Scioliorg28&E.
Scomparinorg110&R. Scottorg125&J.E. Segerorg86&Y. Sekiguchiorg127&D.
Sekihataorg47&I. Selyuzhenkovorg96&K. Senosiorg65&J. Seoorg95,org67&E.
Serradillaorg64,org10&A. Sevcencoorg62&A. Shabanovorg56&A. Shabetaiorg113&O.
Shaduraorg3&R. Shahoyanorg36&A. Shangaraevorg111&A. Sharmaorg90&M.
Sharmaorg90&M. Sharmaorg90&N. Sharmaorg125,org61&K. Shigakiorg47&K.
Shtejerorg9,org27&Y. Sibiriakorg99&S. Siddhantaorg105&K.M. Sielewiczorg36&T.
Siemiarczukorg77&D. Silvermyrorg84,org34&C. Silvestreorg71&G.
Simatovicorg129&G. Simonettiorg36&R. Singarajuorg132&R. Singhorg79&S.
Singhaorg132,org79&V. Singhalorg132&B.C. Sinhaorg132&T. Sinhaorg100&B.
Sitarorg39&M. Sittaorg32&T.B. Skaaliorg22&M. Slupeckiorg123&N.
Smirnovorg136&R.J.M. Snellingsorg57&T.W. Snellmanorg123&C. Søgaardorg34&R.
Soltzorg75&J. Songorg95&M. Songorg137&Z. Songorg7&F. Soramelorg30&S.
Sorensenorg125&M. Spacekorg40&E. Spiritiorg72&I. Sputowskaorg117&M.
Spyropoulou-Stassinakiorg88&B.K. Srivastavaorg94&J. Stachelorg93&I.
Stanorg62&G. Stefanekorg77&E. Stenlundorg34&G. Steynorg65&J.H. Stillerorg93&D.
Stoccoorg113&P. Strmenorg39&A.A.P. Suaideorg120&T. Sugitateorg47&C.
Suireorg51&M. Suleymanovorg16&M. Suljicorg260&R. Sultanovorg58&M.
Šumberaorg83&T.J.M. Symonsorg74&A. Szaboorg39&A. Szanto de Toledoorg1200&I.
Szarkaorg39&A. Szczepankiewiczorg36&M. Szymanskiorg133&U. Tabassamorg16&J.
Takahashiorg121&G.J. Tambaveorg18&N. Tanakaorg128&M.A. Tangaroorg33&J.D. Tapia
Takakiidp5973536,org51&A. Tarantola Peloniorg53&M. Tarhiniorg51&M.
Tariqorg19&M.G. Tarzilaorg78&A. Tauroorg36&G. Tejeda Muñozorg2&A.
Telescaorg36&K. Terasakiorg127&C. Terrevoliorg30&B. Teyssierorg130&J.
Thäderorg74,org96&D. Thomasorg118&R. Tieulentorg130&A.R. Timminsorg122&A.
Toiaorg53&S. Trogoloorg110&V. Trubnikovorg3&W.H. Trzaskaorg123&T.
Tsujiorg127&A. Tumkinorg98&R. Turrisiorg107&T.S. Tveterorg22&K.
Ullalandorg18&A. Urasorg130&G.L. Usaiorg25&A. Utrobicicorg129&M.
Vajzerorg83&L. Valencia Palomoorg70&S. Valleroorg27&J. Van Der
Maarelorg57&J.W. Van Hoorneorg36&M. van Leeuwenorg57&T. Vanatorg83&P. Vande
Vyvreorg36&D. Vargaorg135&A. Vargasorg2&M. Vargyasorg123&R. Varmaorg48&M.
Vasileiouorg88&A. Vasilievorg99&A. Vauthierorg71&V. Vecherninorg131&A.M.
Veenorg57&M. Veldhoenorg57&A. Velureorg18&M. Venaruzzoorg73&E.
Vercellinorg27&S. Vergara Limónorg2&R. Vernetorg8&M. Verweijorg134,org36&L.
Vickovicorg116&G. Viestiorg300&J. Viinikainenorg123&Z. Vilakaziorg126&O.
Villalobos Baillieorg101&A. Villatoro Telloorg2&A. Vinogradovorg99&L.
Vinogradovorg131&Y. Vinogradovorg980&T. Virgiliorg31&V. Vislaviciusorg34&Y.P.
Viyogiorg132&A. Vodopyanovorg66&M.A. Völklorg93&K. Voloshinorg58&S.A.
Voloshinorg134&G. Volpeorg135,org36&B. von Hallerorg36&I.
Vorobyevorg92,org37&D. Vranicorg96,org36&J. Vrlákováorg41&B. Vulpescuorg70&A.
Vyushinorg98&B. Wagnerorg18&J. Wagnerorg96&H. Wangorg57&M. Wangorg7,org113&D.
Watanabeorg128&Y. Watanabeorg127&M. Weberorg36,org112&S.G. Weberorg96&J.P.
Wesselsorg54&U. Westerhofforg54&J. Wiechulaorg35&J. Wikneorg22&M.
Wildeorg54&G. Wilkorg77&J. Wilkinsonorg93&M.C.S. Williamsorg104&B.
Windelbandorg93&M. Winnorg93&C.G. Yaldoorg134&H. Yangorg57&P. Yangorg7&S.
Yanoorg47&C. Yasarorg69&Z. Yinorg7&H. Yokoyamaorg128&I.-K. Yooorg95&V.
Yurchenkoorg3&I. Yushmanovorg99&A. Zaborowskaorg133&V. Zaccoloorg80&A.
Zamanorg16&C. Zampolliorg104&H.J.C. Zanoliorg120&S. Zaporozhetsorg66&N.
Zardoshtiorg101&A. Zarochentsevorg131&P. Závadaorg60&N. Zaviyalovorg98&H.
Zbroszczykorg133&I.S. Zguraorg62&M. Zhalovorg85&H. Zhangorg18,org7&X.
Zhangorg74&Y. Zhangorg7&Z. Zhangorg7&C. Zhaoorg22&N. Zhigarevaorg58&D.
Zhouorg7&Y. Zhouorg80&Z. Zhouorg18&H. Zhuorg18,org7&J. Zhuorg7,org113&A.
Zichichiorg28,org12&A. Zimmermannorg93&M.B. Zimmermannorg36,org54&G.
Zinovjevorg3&M. Zyzakorg43

## Affiliation notes

0Deceased

idp3805088Also at: M.V. Lomonosov Moscow State University, D.V. Skobeltsyn
Institute of Nuclear, Physics, Moscow, Russia

idp5973536Also at: University of Kansas, Lawrence, Kansas, United States

## Collaboration Institutes

org1A.I. Alikhanyan National Science Laboratory (Yerevan Physics Institute)
Foundation, Yerevan, Armenia

org2Benemérita Universidad Autónoma de Puebla, Puebla, Mexico

org3Bogolyubov Institute for Theoretical Physics, Kiev, Ukraine

org4Bose Institute, Department of Physics and Centre for Astroparticle Physics
and Space Science (CAPSS), Kolkata, India

org5Budker Institute for Nuclear Physics, Novosibirsk, Russia

org6California Polytechnic State University, San Luis Obispo, California,
United States

org7Central China Normal University, Wuhan, China

org8Centre de Calcul de l’IN2P3, Villeurbanne, France

org9Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN), Havana,
Cuba

org10Centro de Investigaciones Energéticas Medioambientales y Tecnológicas
(CIEMAT), Madrid, Spain

org11Centro de Investigación y de Estudios Avanzados (CINVESTAV), Mexico City
and Mérida, Mexico

org12Centro Fermi - Museo Storico della Fisica e Centro Studi e Ricerche
“Enrico Fermi”, Rome, Italy

org13Chicago State University, Chicago, Illinois, USA

org14China Institute of Atomic Energy, Beijing, China

org15Commissariat à l’Energie Atomique, IRFU, Saclay, France

org16COMSATS Institute of Information Technology (CIIT), Islamabad, Pakistan

org17Departamento de Física de Partículas and IGFAE, Universidad de Santiago
de Compostela, Santiago de Compostela, Spain

org18Department of Physics and Technology, University of Bergen, Bergen,
Norway

org19Department of Physics, Aligarh Muslim University, Aligarh, India

org20Department of Physics, Ohio State University, Columbus, Ohio, United
States

org21Department of Physics, Sejong University, Seoul, South Korea

org22Department of Physics, University of Oslo, Oslo, Norway

org23Dipartimento di Elettrotecnica ed Elettronica del Politecnico, Bari,
Italy

org24Dipartimento di Fisica dell’Università ’La Sapienza’ and Sezione INFN
Rome, Italy

org25Dipartimento di Fisica dell’Università and Sezione INFN, Cagliari, Italy

org26Dipartimento di Fisica dell’Università and Sezione INFN, Trieste, Italy

org27Dipartimento di Fisica dell’Università and Sezione INFN, Turin, Italy

org28Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN,
Bologna, Italy

org29Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN,
Catania, Italy

org30Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN,
Padova, Italy

org31Dipartimento di Fisica ‘E.R. Caianiello’ dell’Università and Gruppo
Collegato INFN, Salerno, Italy

org32Dipartimento di Scienze e Innovazione Tecnologica dell’Università del
Piemonte Orientale and Gruppo Collegato INFN, Alessandria, Italy

org33Dipartimento Interateneo di Fisica ‘M. Merlin’ and Sezione INFN, Bari,
Italy

org34Division of Experimental High Energy Physics, University of Lund, Lund,
Sweden

org35Eberhard Karls Universität Tübingen, Tübingen, Germany

org36European Organization for Nuclear Research (CERN), Geneva, Switzerland

org37Excellence Cluster Universe, Technische Universität München, Munich,
Germany

org38Faculty of Engineering, Bergen University College, Bergen, Norway

org39Faculty of Mathematics, Physics and Informatics, Comenius University,
Bratislava, Slovakia

org40Faculty of Nuclear Sciences and Physical Engineering, Czech Technical
University in Prague, Prague, Czech Republic

org41Faculty of Science, P.J. Šafárik University, Košice, Slovakia

org42Faculty of Technology, Buskerud and Vestfold University College,
Vestfold, Norway

org43Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe-
Universität Frankfurt, Frankfurt, Germany

org44Gangneung-Wonju National University, Gangneung, South Korea

org45Gauhati University, Department of Physics, Guwahati, India

org46Helsinki Institute of Physics (HIP), Helsinki, Finland

org47Hiroshima University, Hiroshima, Japan

org48Indian Institute of Technology Bombay (IIT), Mumbai, India

org49Indian Institute of Technology Indore, Indore (IITI), India

org50Inha University, Incheon, South Korea

org51Institut de Physique Nucléaire d’Orsay (IPNO), Université Paris-Sud,
CNRS-IN2P3, Orsay, France

org52Institut für Informatik, Johann Wolfgang Goethe-Universität Frankfurt,
Frankfurt, Germany

org53Institut für Kernphysik, Johann Wolfgang Goethe-Universität Frankfurt,
Frankfurt, Germany

org54Institut für Kernphysik, Westfälische Wilhelms-Universität Münster,
Münster, Germany

org55Institut Pluridisciplinaire Hubert Curien (IPHC), Université de
Strasbourg, CNRS-IN2P3, Strasbourg, France

org56Institute for Nuclear Research, Academy of Sciences, Moscow, Russia

org57Institute for Subatomic Physics of Utrecht University, Utrecht,
Netherlands

org58Institute for Theoretical and Experimental Physics, Moscow, Russia

org59Institute of Experimental Physics, Slovak Academy of Sciences, Košice,
Slovakia

org60Institute of Physics, Academy of Sciences of the Czech Republic, Prague,
Czech Republic

org61Institute of Physics, Bhubaneswar, India

org62Institute of Space Science (ISS), Bucharest, Romania

org63Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México,
Mexico City, Mexico

org64Instituto de Física, Universidad Nacional Autónoma de México, Mexico
City, Mexico

org65iThemba LABS, National Research Foundation, Somerset West, South Africa

org66Joint Institute for Nuclear Research (JINR), Dubna, Russia

org67Konkuk University, Seoul, South Korea

org68Korea Institute of Science and Technology Information, Daejeon, South
Korea

org69KTO Karatay University, Konya, Turkey

org70Laboratoire de Physique Corpusculaire (LPC), Clermont Université,
Université Blaise Pascal, CNRS–IN2P3, Clermont-Ferrand, France

org71Laboratoire de Physique Subatomique et de Cosmologie, Université
Grenoble-Alpes, CNRS-IN2P3, Grenoble, France

org72Laboratori Nazionali di Frascati, INFN, Frascati, Italy

org73Laboratori Nazionali di Legnaro, INFN, Legnaro, Italy

org74Lawrence Berkeley National Laboratory, Berkeley, California, United
States

org75Lawrence Livermore National Laboratory, Livermore, California, United
States

org76Moscow Engineering Physics Institute, Moscow, Russia

org77National Centre for Nuclear Studies, Warsaw, Poland

org78National Institute for Physics and Nuclear Engineering, Bucharest,
Romania

org79National Institute of Science Education and Research, Bhubaneswar, India

org80Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark

org81Nikhef, Nationaal instituut voor subatomaire fysica, Amsterdam,
Netherlands

org82Nuclear Physics Group, STFC Daresbury Laboratory, Daresbury, United
Kingdom

org83Nuclear Physics Institute, Academy of Sciences of the Czech Republic, Řež
u Prahy, Czech Republic

org84Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States

org85Petersburg Nuclear Physics Institute, Gatchina, Russia

org86Physics Department, Creighton University, Omaha, Nebraska, United States

org87Physics Department, Panjab University, Chandigarh, India

org88Physics Department, University of Athens, Athens, Greece

org89Physics Department, University of Cape Town, Cape Town, South Africa

org90Physics Department, University of Jammu, Jammu, India

org91Physics Department, University of Rajasthan, Jaipur, India

org92Physik Department, Technische Universität München, Munich, Germany

org93Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg,
Heidelberg, Germany

org94Purdue University, West Lafayette, Indiana, United States

org95Pusan National University, Pusan, South Korea

org96Research Division and ExtreMe Matter Institute EMMI, GSI Helmholtzzentrum
für Schwerionenforschung, Darmstadt, Germany

org97Rudjer Bošković Institute, Zagreb, Croatia

org98Russian Federal Nuclear Center (VNIIEF), Sarov, Russia

org99Russian Research Centre Kurchatov Institute, Moscow, Russia

org100Saha Institute of Nuclear Physics, Kolkata, India

org101School of Physics and Astronomy, University of Birmingham, Birmingham,
United Kingdom

org102Sección Física, Departamento de Ciencias, Pontificia Universidad
Católica del Perú, Lima, Peru

org103Sezione INFN, Bari, Italy

org104Sezione INFN, Bologna, Italy

org105Sezione INFN, Cagliari, Italy

org106Sezione INFN, Catania, Italy

org107Sezione INFN, Padova, Italy

org108Sezione INFN, Rome, Italy

org109Sezione INFN, Trieste, Italy

org110Sezione INFN, Turin, Italy

org111SSC IHEP of NRC Kurchatov institute, Protvino, Russia

org112Stefan Meyer Institut für Subatomare Physik (SMI), Vienna, Austria

org113SUBATECH, Ecole des Mines de Nantes, Université de Nantes, CNRS-IN2P3,
Nantes, France

org114Suranaree University of Technology, Nakhon Ratchasima, Thailand

org115Technical University of Košice, Košice, Slovakia

org116Technical University of Split FESB, Split, Croatia

org117The Henryk Niewodniczanski Institute of Nuclear Physics, Polish Academy
of Sciences, Cracow, Poland

org118The University of Texas at Austin, Physics Department, Austin, Texas,
USA

org119Universidad Autónoma de Sinaloa, Culiacán, Mexico

org120Universidade de São Paulo (USP), São Paulo, Brazil

org121Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil

org122University of Houston, Houston, Texas, United States

org123University of Jyväskylä, Jyväskylä, Finland

org124University of Liverpool, Liverpool, United Kingdom

org125University of Tennessee, Knoxville, Tennessee, United States

org126University of the Witwatersrand, Johannesburg, South Africa

org127University of Tokyo, Tokyo, Japan

org128University of Tsukuba, Tsukuba, Japan

org129University of Zagreb, Zagreb, Croatia

org130Université de Lyon, Université Lyon 1, CNRS/IN2P3, IPN-Lyon,
Villeurbanne, France

org131V. Fock Institute for Physics, St. Petersburg State University, St.
Petersburg, Russia

org132Variable Energy Cyclotron Centre, Kolkata, India

org133Warsaw University of Technology, Warsaw, Poland

org134Wayne State University, Detroit, Michigan, United States

org135Wigner Research Centre for Physics, Hungarian Academy of Sciences,
Budapest, Hungary

org136Yale University, New Haven, Connecticut, United States

org137Yonsei University, Seoul, South Korea

org138Zentrum für Technologietransfer und Telekommunikation (ZTT),
Fachhochschule Worms, Worms, Germany