2016 153 11 June

Enhanced production of multi-strange hadrons in high-multiplicity pp

At sufficiently high temperature and energy density, nuclear matter undergoes
a transition to a phase in which quarks and gluons are not confined: the
Quark-Gluon Plasma (QGP) [1]. Such an extreme state of strongly-interacting
QCD (Quantum Chromo-Dynamics) matter is produced in the laboratory with high-
energy collisions of heavy nuclei, where an enhanced production of strange
hadrons is observed [2, 3, 4, 5, 6]. Strangeness enhancement, originally
proposed as a signature of QGP formation in nuclear collisions [7], is more
pronounced for multi-strange baryons. Several effects typical of heavy-ion
phenomenology have been observed in high-multiplicity proton-proton (pp)
collisions [8, 9]. Yet, enhanced production of multi-strange particles has not
been reported so far. Here we present the first observation of strangeness
enhancement in high-multiplicity pp collisions. We find that the integrated
yields of strange and multi-strange particles relative to pions increases
significantly with the event charged-particle multiplicity. The measurements
are in remarkable agreement with p–Pb collision results [10, 11] indicating
that the phenomenon is related to the final system created in the collision.
In high-multiplicity events strangeness production reaches values similar to
those observed in Pb–Pb collisions, where a QGP is formed.

The production of strange hadrons in high-energy hadronic interactions
provides a way to investigate the properties of QCD, the theory of strongly-
interacting matter. Unlike up ($u$) and down ($d$) quarks, which form ordinary
matter, strange ($s$) quarks are not present as valence quarks in the initial
state, yet they are sufficiently light to be abundantly created during the
course of the collisions. In the early stages of high energy collisions,
strangeness is produced in hard (perturbative) 2$\,\to\,$2 partonic scattering
processes by flavour creation ($gg~{}\to~{}s\bar{s}$,
$q\bar{q}~{}\to~{}s\bar{s}$) and flavour excitation ($gs~{}\to~{}gs$,
$qs~{}\to~{}qs$). Strangeness is also created during the subsequent partonic
evolution via gluon splittings ($g~{}\to~{}s\bar{s}$). These processes tend to
dominate the production of high transverse momentum ($p_{\rm T}$) strange
hadrons. At low $p_{\rm T}$ non perturbative processes dominate the production
of strange hadrons. In string fragmentation models the production of strange
hadrons is generally suppressed relative to hadrons containing only light
quarks, as the strange quark is heavier than up and down quarks. The amount of
strangeness suppression in elementary ($e^{+}e^{-}$ and pp) collisions is an
important parameter in Monte Carlo (MC) models. For this reason, measurements
of strange hadron production place constraints on these models.

The abundances of strange particles relative to pions in heavy-ion collisions
from top RHIC (Relativistic Heavy-Ion Collider) to LHC (Large Hadron Collider)
energies do not show a significant dependence on either the initial volume
(collision centrality) or the initial energy density (collision energy). With
the exception of the most peripheral collisions, particle ratios are found to
be compatible with those of a hadron gas in thermal and chemical equilibrium
and can be described using a grand canonical statistical model [12, 13]. In
peripheral collisions, where the overlap of the colliding nuclei becomes very
small, the relative yields of strange particles to pions decrease and tend
toward those observed in pp collisions, for which a statistical-mechanics
approach can also be applied [14, 15]. Extensions of a pure grand-canonical
description of particle production, like statistical models implementing
strangeness canonical suppression [16] and core-corona superposition [17, 18]
models, can effectively produce a suppression of strangeness production in
small systems. However, the microscopic origin of enhanced strangeness
production is not known, and the measurements presented in this Letter may
contribute to its understanding. Several effects, like azimuthal correlations
and mass-dependent hardening of $p_{\rm T}$ distributions, which in nuclear
collisions are typically attributed to the formation of a strongly-interacting
quark-gluon medium, have been observed in high-multiplicity pp and proton-
nucleus collisions at the LHC [8, 19, 20, 21, 22, 23, 10, 24, 11, 25, 9]. Yet,
enhanced production of strange particles as a function of the charged-particle
multiplicity density (${\rm d}N_{\rm ch}/{\rm d}\eta$) has so far not been
observed in pp collisions. The study of pp collisions at high multiplicity is
thus of considerable interest as it opens the exciting possibility of a
microscopic understanding of phenomena known from nuclear reactions.

In this Letter, we present the multiplicity dependence of the production of
primary strange (${\rm K}^{0}_{S}$, $\Lambda$, $\overline{\Lambda}$) and
multi-strange ($\Xi^{-}$, $\overline{\Xi}^{+}$, $\Omega^{-}$,
$\overline{\Omega}^{+}$) hadrons in pp collisions at the centre-of-mass energy
of $\sqrt{s}$ = 7 TeV. Primary particles are defined as all particles created
in the collisions, except those coming from weak decays of light-flavour
hadrons and of muons. The measurements have been performed at
midrapidity111The particle rapidity is defined as
$y=\frac{1}{2}\ln\left(\frac{E+p_{z}c}{E-p_{z}c}\right)$, where $E$ is the
energy and $p_{z}$ is the component of momentum along the beam axis.,
$\left|y\right|<0.5$, with the ALICE detector [26] at the LHC. Similar
measurements of the multiplicity and centrality dependence of strange and
multi-strange hadron production have been performed by ALICE in proton-lead
(p–Pb) collisions at a centre-of-mass energy per nucleon pair $\sqrt{s_{\rm
NN}}$ = 5.02 TeV [10, 11] and in lead-lead (Pb–Pb) collisions at $\sqrt{s_{\rm
NN}}$ = 2.76 TeV [27, 6]. The measurements reported here have been obtained in
pp collisions at $\sqrt{s}$ = 7 TeV for events having at least one charged
particle produced in the pseudorapidity222The particle pseudorapidity is
defined as $\eta=-\ln\left(tan\frac{\theta}{2}\right)$, where $\theta$ is the
angle with respect to the beam axis. interval $\left|\eta\right|<1$
(INEL$>$0), corresponding to about 75% of the total inelastic cross-section.
In order to study the multiplicity dependence of strange and multi-strange
hadron production, the sample is divided into event classes based on the total
ionisation energy deposited in the forward detectors, covering the
pseudorapidity regions $2.8~{}<~{}\eta~{}<~{}5.1$ and
$-3.7~{}<~{}\eta~{}<~{}-1.7$.

Figure 1: $p_{\rm T}$-differential yields of ${\rm K}^{0}_{S}$,
$\Lambda+\overline{\Lambda}$, $\Xi^{-}+\overline{\Xi}^{+}$ and
$\Omega^{-}+\overline{\Omega}^{+}$ measured in $\left|y\right|<0.5$. The
results are shown for a selection of event classes, indicated by roman numbers
in brackets, with decreasing multiplicity. The error bars show the statistical
uncertainty, whereas the empty boxes show the total systematic uncertainty.
The data are scaled by different factors to improve the visibility. The dashed
curves represent Tsallis-Lévy fits to each individual distribution to extract
integrated yields. The indicated uncertainties all represent standard
deviations.

Particle/antiparticle production yields are identical within uncertainties.
The $p_{\rm T}$ distributions of ${\rm K}^{0}_{S}$,
$\Lambda+\overline{\Lambda}$, $\Xi^{-}+\overline{\Xi}^{+}$ and
$\Omega^{-}+\overline{\Omega}^{+}$ (in the following denoted as ${\rm
K}^{0}_{S}$, $\Lambda$, $\Xi$ and $\Omega$) are shown in Figure 1 for a
selection of event classes with progressively decreasing $\langle{\rm d}N_{\rm
ch}/{\rm d}\eta\rangle$. The mean pseudorapidity densities of primary charged
particles $\langle{\rm d}N_{\rm ch}/{\rm d}\eta\rangle$ are measured at
midrapidity, $\left|\eta\right|<0.5$. The $p_{\rm T}$ spectra become harder as
the multiplicity increases, with the hardening being more pronounced for
higher mass particles. A similar observation was reported for p–Pb collisions
[10] where this and several other features common with Pb–Pb collisions are
consistent with the appearance of collective behavior at high-multiplicity [8,
19, 20, 21, 22, 23, 11]. In heavy-ion collisions these observations are
successfully described by models based on relativistic hydrodynamics. In this
framework, the $p_{\rm T}$ distributions are determined by particle emission
from a collectively expanding thermal source [28]. The blast-wave model [29]
is employed to analyse the spectral shapes of ${\rm K}^{0}_{S}$, $\Lambda$ and
$\Xi$ in the common highest multiplicity class (class I). A simultaneous fit
to all particles is performed following the approach discussed in [10] in the
$p_{\rm T}$ ranges 0–1.5, 0.6–2.9 and 0.6–2.9 GeV/$c$, for ${\rm K}^{0}_{S}$,
$\Lambda$ and $\Xi$, respectively. The best-fit describes the data to better
than 5% in the respective fit ranges, consistent with particle production from
a thermal source at temperature $T_{\rm fo}$ expanding with a common
transverse velocity $\langle\beta_{\rm T}\rangle$. The resulting parameters,
$T_{\rm fo}$ = 163 $\pm$ 10 MeV and $\langle\beta_{\rm T}\rangle$ = 0.49 $\pm$
0.02, are remarkably similar to the ones obtained in p–Pb collisions for an
event class with comparable $\langle{\rm d}N_{\rm ch}/{\rm d}\eta\rangle$
[10].

Figure 2: $p_{\rm T}$-integrated yield ratios to pions (${\pi}^{+}+{\pi}^{-}$)
as a function of $\langle{\rm d}N_{\rm ch}/{\rm d}\eta\rangle$ measured in
$\left|y\right|<0.5$. The error bars show the statistical uncertainty, whereas
the empty and dark-shaded boxes show the total systematic uncertainty and the
contribution uncorrelated across multiplicity bins, respectively. The values
are compared to calculations from MC models [30, 31, 32] and to results
obtained in p–Pb and Pb–Pb collisions at the LHC [10, 6, 11]. For Pb–Pb
results the ratio $2\Lambda$ / (${\pi}^{+}+{\pi}^{-}$) is shown. The indicated
uncertainties all represent standard deviations.

The $p_{\rm T}$-integrated yields are computed from the data in the measured
ranges and using extrapolations to the unmeasured regions. In order to
extrapolate to the unmeasured region, the data were fitted with a Tsallis-Lévy
[10] parametrization, which gives the best description of the individual
spectra for all particles and all event classes over the full $p_{\rm T}$
range (Figure 1). Several other fit functions (Boltzmann, $m_{\rm
T}$-exponential, $p_{\rm T}$-exponential, blast-wave, Fermi-Dirac, Bose-
Einstein) are employed to estimate the corresponding systematic uncertainties.
The fraction of the extrapolated yield for the highest(lowest) multiplicity
event class is about 10(25)%, 16(36)%, 27(47)% for $\Lambda$, $\Xi$ and
$\Omega$, respectively, and is negligible for ${\rm K}^{0}_{S}$. The
uncertainty on the extrapolation amounts to about 2(6)%, 3(10)%, 4(13)% of the
total yield for $\Lambda$, $\Xi$ and $\Omega$, respectively, and it is
negligible for ${\rm K}^{0}_{S}$. The total systematic uncertainty on the
$p_{\rm T}$-integrated yields amounts to 5(9)%, 7(12)%, 6(14)% and 9(18)% for
${\rm K}^{0}_{S}$, $\Lambda$, $\Xi$ and $\Omega$, respectively. A significant
fraction of this uncertainty is common to all multiplicity classes and it is
estimated to be about 5%, 6%, 6% and 9% for ${\rm K}^{0}_{S}$, $\Lambda$,
$\Xi$ and $\Omega$, respectively. In Figure 2, the ratios of the yields of
${\rm K}^{0}_{S}$, $\Lambda$, $\Xi$ and $\Omega$ to the pion
($\pi^{+}+\pi^{-}$) yield as a function of $\langle{\rm d}N_{\rm ch}/{\rm
d}\eta\rangle$ are compared to p–Pb and Pb–Pb results at the LHC [10, 11, 6].
A significant enhancement of strange to non-strange hadron production is
observed with increasing particle multiplicity in pp collisions. The behaviour
observed in pp collisions resembles that of p–Pb collisions at a slightly
lower centre-of-mass energy [11], in terms of both the values of the ratios
and their evolution with multiplicity. As no significant dependence on the
centre-of-mass energy is observed at the LHC for inclusive inelastic
collisions, the origin of strangeness production in hadronic collisions is
apparently driven by the characteristics of the final state rather than by the
collision system or energy. At high multiplicity, the yield ratios reach
values similar to the ones observed in Pb–Pb collisions, where no significant
change with multiplicity is observed beyond an initial slight rise. Note that
the final-state average charged-particle density $\langle{\rm d}N_{\rm
ch}/{\rm d}\eta\rangle$, which changes by over three orders of magnitude from
low-multiplicity pp to central Pb–Pb, will in general be related to different
underlying physics in the various reaction systems. For example, under the
assumption that the initial reaction volume in both $\rm pp$ and p–Pb is
determined mostly by the size of the proton, $\langle{\rm d}N_{\rm ch}/{\rm
d}\eta\rangle$ could be used as a proxy for the initial energy density. In
Pb–Pb collisions, on the other hand, both the overlap area as well as the
energy density could increase with $\langle{\rm d}N_{\rm ch}/{\rm
d}\eta\rangle$. Nonetheless, it is a non-trivial observation that particle
ratios in pp and p–Pb are identical at the same ${\rm d}N_{\rm ch}/{\rm
d}\eta$, representing an indication that the final-state particle density
might indeed be a good scaling variable between these two systems.

Figure 3: Particle yield ratios $\Lambda$/${\rm K}^{0}_{S}$ =
($\Lambda+\overline{\Lambda}$)/$2{\rm K}^{0}_{S}$ and $\rm p$/${\pi}$ = ($\rm
p+\overline{\rm p}$)/(${\pi}^{+}+{\pi}^{-}$) as a function of $\langle{\rm
d}N_{\rm ch}/{\rm d}\eta\rangle$. The yield ratios are measured in the
rapidity interval $\left|y\right|<0.5$. The error bars show the statistical
uncertainty, whereas the empty and dark-shaded boxes show the total systematic
uncertainty and the contribution uncorrelated across multiplicity bins,
respectively. The values are compared to calculations from MC models [30, 31,
32] in pp collisions at $\sqrt{s}$ = 7 TeV and to results obtained in p–Pb
collisions at the LHC [10]. The indicated uncertainties all represent standard
deviations.

Figure 3 shows that the yield ratios $\Lambda$/${\rm K}^{0}_{S}$ =
($\Lambda+\overline{\Lambda}$)/$2{\rm K}^{0}_{S}$ and $\rm p$/${\pi}$ = ($\rm
p+\overline{\rm p}$)/(${\pi}^{+}+{\pi}^{-}$) do not change significantly with
multiplicity, demonstrating that the observed enhanced production rates of
strange hadrons with respect to pions is not due to the difference in the
hadron masses. The results in Figures 2 and 3 are compared to calculations
from MC models commonly used for pp collisions at the LHC: PYTHIA8 [30], EPOS
LHC [31] and DIPSY [32]. The kinematic domain and the multiplicity selections
are the same for MC and data, namely, dividing the INEL$>$0 sample into event
classes based on the total charged-particle multiplicity in the forward
region. The observation of a multiplicity-dependent enhancement of the
production of strange hadrons along with the constant production of protons
relative to pions cannot be simultaneously reproduced by any of the MC models
commonly used at the LHC. The model which describes the data best, DIPSY, is a
model where interaction between gluonic strings is allowed to form “color
ropes” which are expected to produce more strange particles and baryons.

Figure 4: Particle yield ratios to pions normalised to the values measured in
the inclusive INEL$>$0 pp sample. The results are shown for pp and p–Pb
collisions, both normalised to the inclusive INEL$>$0 pp sample. The error
bars show the statistical uncertainty. The common systematic uncertainties
cancel in the double-ratio. The empty boxes represent the remaining
uncorrelated uncertainties. The lines represent a simultaneous fit of the
results with the empirical scaling formula in Equation 1. The indicated
uncertainties all represent standard deviations.

To illustrate the evolution of the production of strange hadrons with
multiplicity, Figure 4 presents the yield ratios to pions divided by the
values measured in the inclusive INEL$>$0 pp sample, both for pp and p–Pb
collisions. The observed multiplicity-dependent enhancement with respect to
the INEL$>$0 sample follows a hierarchy determined by the hadron strangeness.
We have attempted to describe the observed strangeness hierarchy by fitting
the data presented in Figure 4 an the empirical function of the form

$\frac{(h/\pi)}{(h/\pi)^{\rm pp}_{\rm INEL>0}}=1~{}+~{}a~{}{\rm
S}^{b}~{}\log{\left[\frac{\langle{\rm d}N_{\rm ch}/{\rm
d}\eta\rangle}{\langle{\rm d}N_{\rm ch}/{\rm d}\eta\rangle^{\rm pp}_{\rm
INEL>0}}\right]},$ (1)

where S is the number of strange or anti-strange valence quarks in the hadron,
(h/$\pi$)${}^{\rm pp}_{\rm INEL>0}$ and $\langle{\rm d}N_{\rm ch}/{\rm
d}\eta\rangle^{\rm pp}_{\rm INEL>0}$ are the measured hadron-to-pion ratio and
the charged-particle multiplicity density in INEL$>$0 pp collisions,
respectively, and $a$ and $b$ are free parameters. The fit describes the data
well, yielding $a~{}=~{}0.083~{}\pm~{}0.006$, $b~{}=~{}1.67~{}\pm~{}0.09$,
with a $\chi^{2}$/ndf of 0.66.

In summary, we have presented the multiplicity dependence of the production of
primary strange (${\rm K}^{0}_{S}$, $\Lambda$, $\overline{\Lambda}$) and
multi-strange ($\Xi^{-}$, $\overline{\Xi}^{+}$, $\Omega^{-}$,
$\overline{\Omega}^{+}$) hadrons in pp collisions at $\sqrt{s}$ = 7 TeV. The
results are obtained as a function of $\langle{\rm d}N_{\rm ch}/{\rm
d}\eta\rangle$ measured at midrapidity for event classes selected on the basis
of the total charge deposited in the forward region. The $p_{\rm T}$ spectra
become harder as the multiplicity increases. The mass and multiplicity
dependences of the spectral shapes are reminiscent of the patterns seen in
p–Pb and Pb–Pb collisions at the LHC, which can be understood assuming a
collective expansion of the system in the final state. The data show for the
first time in pp collisions that the $p_{\rm T}$-integrated yields of strange
and multi-strange particles relative to pions increase significantly with
multiplicity. These particle ratios are similar to those found in p–Pb
collisions at the same multiplicity densities [11]. The observed enhancement
increases with strangeness content rather than with mass or baryon number of
the hadron. Such behaviour cannot be reproduced by any of the MC models
commonly used, suggesting that further developments are needed to obtain a
complete microscopic understanding of strangeness production and indicating
the presence of a phenomenon novel in high-multiplicity pp collisions. The
evolution of strangeness enhancement seen at the LHC steadily increases as a
function of $\langle{\rm d}N_{\rm ch}/{\rm d}\eta\rangle$ from low
multiplicity pp to high multiplicity p–Pb and reaches the values observed in
Pb–Pb collisions. This may point towards a common underlying physics mechanism
which gradually compensates the strangeness suppression in fragmentation.
Further studies extending to higher multiplicity in small systems are
essential, as they would demonstrate whether strangeness production saturates
at the thermal equilibrium values predicted by the grand canonical statistical
model [12, 13] or continues to increase. The remarkable similarity of strange
particle production in pp, p–Pb and Pb–Pb collisions adds to previous
measurements in pp, which also exhibit characteristic features known from
high-energy heavy-ion collisions [8, 19, 20, 21, 22, 23, 10, 11, 25, 9] and
are understood to be connected to the formation of a deconfined QCD phase at
high temperature and energy density.

## 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); Ministry of Science &
Technology of China (MSTC), National Natural Science Foundation of China
(NSFC) and Ministry of Education of China (MOEC)”; Ministry of Science,
Education and Sports of Croatia and Unity through Knowledge Fund, Croatia;
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; National Research, Development and Innovation Office (NKFIH), Hungary;
Council of Scientific and Industrial Research (CSIR), New Delhi; 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; Japan
Society for the Promotion of Science (JSPS) KAKENHI and MEXT, Japan; 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); Pontificia Universidad Católica del Perú; National Science Centre,
Poland; Ministry of National Education/Institute for Atomic Physics and
National Council of Scientific Research in Higher Education (CNCSI-UEFISCDI),
Romania; Joint Institute for Nuclear Research, Dubna; 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); National Science and Technology Development Agency (NSDTA),
Suranaree University of Technology (SUT) and Office of the Higher Education
Commission under NRU project of Thailand; 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.

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##  Appendix A Methods

A detailed description of the ALICE detector and of its performance can be
found in [26, 33]. We briefly outline the main detectors utilized for this
analysis. The V0 detectors are two scintillator hodoscopes employed for
triggering, background suppression and event-class determination. They are
placed on either side of the interaction region at $z~{}=~{}3.3$ m and
$z~{}=~{}-0.9$ m, covering the pseudorapidity regions
$2.8~{}<~{}\eta~{}<~{}5.1$ and $-3.7~{}<~{}\eta~{}<~{}-1.7$, respectively.
Vertex reconstruction, central-barrel tracking and charged-hadron
identification are performed with the Inner Tracking System (ITS) and the
Time-Projection Chamber (TPC), which are located inside a solenoidal magnet
providing a 0.5 T magnetic field. The ITS is composed of six cylindrical
layers of high-resolution silicon tracking detectors. The innermost layers
consist of two arrays of hybrid Silicon Pixel Detectors (SPD) located at
average radii 3.9 and 7.6 cm from the beam axis and covering
$\left|\eta\right|<2.0$ and $\left|\eta\right|<1.4$, respectively. The TPC is
a large cylindrical drift detector of radial and longitudinal size of about
$85~{}<~{}r~{}<~{}250$ cm and $-250~{}<~{}z~{}<~{}250$ cm, respectively. It
provides charged-hadron identification information via ionisation energy loss
in the fill gas.

The data were collected in 2010 using a minimum-bias trigger requiring a hit
in either the V0 scintillators or in the SPD detector, in coincidence with the
arrival of proton bunches from both directions. The contamination from beam-
induced background is removed offline by using the timing information and
correlations in the V0 and SPD detectors, as discussed in details in [33].
Events used for the data analysis are further required to have a reconstructed
vertex within $\left|z\right|~{}<$ 10 cm. Events containing more than one
distinct vertex are tagged as pileup and are discarded. The remaining pileup
fraction is estimated to be negligible, ranging from about $10^{-4}$ to
$10^{-2}$ for the lowest and highest multiplicity classes, respectively. A
total of about 100 million events has been utilised for the analysis.

The mean pseudorapidity densities of primary charged particles $\langle{\rm
d}N_{\rm ch}/{\rm d}\eta\rangle$ are measured at midrapidity,
$\left|\eta\right|<0.5$, for each event class using the technique described in
[34]. The $\langle{\rm d}N_{\rm ch}/{\rm d}\eta\rangle$ values, corrected for
acceptance and efficiency, as well as for contamination from secondary
particles and combinatorial background, are listed in Table 2. The relative
RMS width of the corresponding multiplicity distributions ranges from 68% to
30% for the lowest and highest multiplicity classes, respectively. The
corresponding fractions of the INEL$>$0 cross-section are also summarized in
Table 2.

Strange ${\rm K}^{0}_{S}$, $\Lambda$ and $\overline{\Lambda}$ and multi-
strange $\Xi^{-}$, $\overline{\Xi}^{+}$, $\Omega^{-}$ and
$\overline{\Omega}^{+}$ candidates are reconstructed via topological selection
criteria and invariant-mass analysis of their characteristic weak decays [35]:

${\rm K}^{0}_{S}$ | $\rightarrow$ |  ${\pi}^{+}$ \+ ${\pi}^{-}$ | B.R. = (69.20 $\pm$ 0.05) %
---|---|---|---
$\Lambda$($\overline{\Lambda}$) | $\rightarrow$ |  $\rm p$($\overline{\rm p}$) + ${\pi}^{-}$(${\pi}^{+}$) | B.R. = (63.9 $\pm$ 0.5) %
$\Xi^{-}$($\overline{\Xi}^{+}$) | $\rightarrow$ |  $\Lambda$($\overline{\Lambda}$) + ${\pi}^{-}$(${\pi}^{+}$) | B.R. = (99.887 $\pm$ 0.035) %
$\Omega^{-}$($\overline{\Omega}^{+}$) | $\rightarrow$ |  $\Lambda$($\overline{\Lambda}$) + ${\rm K}^{-}$(${\rm K}^{+}$) | B.R. = (67.8 $\pm$ 0.7) %

Details on the analysis technique are described in [10, 36, 37]. The results
are corrected for detector acceptance and reconstruction efficiency calculated
using events from the PYTHIA6 (tune Perugia 0) MC generator [38] with particle
transport performed via a GEANT3 [39] simulation of the ALICE detector. The
contamination to $\Lambda$ ($\overline{\Lambda}$) yields from weak decays of
charged and neutral $\Xi$ baryons (feed-down) is subtracted using a data-
driven approach [10]. The study of systematic uncertainties follows the
analysis described in [10, 36, 37]. Contributions common to all event classes
($N_{\rm ch}$-independent) are estimated and removed to determine the
remaining uncertainties which are uncorrelated across different multiplicity
intervals. The main sources of systematic uncertainty and their corresponding
values are summarized in Table 2. The results on pion and proton production
have been obtained following the analysis method discussed in [40].

Table 1: Event multiplicity classes, their corresponding fraction of the INEL$>$0 cross-section ($\sigma/\sigma_{\rm INEL>0}$) and their corresponding $\langle{\rm d}N_{\rm ch}/{\rm d}\eta\rangle$ at midrapidity ($\left|\eta\right|<0.5$). The value of $\langle{\rm d}N_{\rm ch}/{\rm d}\eta\rangle$ in the inclusive (INEL$>$0) class is 5.96 $\pm$ 0.23. The uncertainties are the quadratic sum of statistical and systematic contributions and represent standard deviations.  Class name |  I |  II |  III |  IV |  V |  VI |  VII |  VIII |  IX |  X
---|---|---|---|---|---|---|---|---|---|---
$\sigma/\sigma_{\rm INEL>0}$ |  0–0.95% |  0.95–4.7% |  4.7–9.5% |  9.5–14% |  14–19% |  19–28% |  28–38% |  38–48% |  48–68% |  68–100%
$\langle{\rm d}N_{\rm ch}/{\rm d}\eta\rangle$ |  21.3$\pm$0.6 |  16.5$\pm$0.5 |  13.5$\pm$0.4 |  11.5$\pm$0.3 |  10.1$\pm$0.3 |  8.45$\pm$0.25 |  6.72$\pm$0.21 |  5.40$\pm$0.17 |  3.90$\pm$0.14 |  2.26$\pm$0.12

Table 2: Main sources and values of the relative systematic uncertainties (standard deviations expressed in %) of the $p_{\rm T}$-differential yields. The values are reported for low, intermediate and high $p_{\rm T}$. The sums of the contributions common to all event classes are listed separately as $N_{\rm ch}$-independent systematics. Hadron | ${\rm K}^{0}_{S}$ |  $\Lambda$ ($\overline{\Lambda}$) |  $\Xi^{-}$ ($\overline{\Xi}^{+}$) |  $\Omega^{-}$ ($\overline{\Omega}^{+}$)
---|---|---|---|---
$p_{\rm T}$ (GeV/$c$) |  0.05 |  6.2 |  11.0 |  0.5 |  3.7 |  7.2 |  0.8 |  2.1 |  5.8 |  1.2 |  2.8 |  4.7
Material budget |  4.0 |  4.0 |  4.0 |  4.0 |  4.0 |  4.0 |  4.0 |  4.0 |  4.0 |  4.0 |  4.0 |  4.0
Transport code | negligible |  1.0 |  1.0 |  1.0 |  1.0 |  1.0 |  1.0 |  1.0 |  1.0 |  1.0
Track selection |  1.0 |  5.0 |  0.8 |  0.2 |  5.9 |  4.3 |  0.4 |  0.3 |  2.2 |  0.8 |  0.6 |  4.1
Topological selection |  2.6 |  1.1 |  2.3 |  0.8 |  0.6 |  3.2 |  3.1 |  2.0 |  4.0 |  5.0 |  5.6 |  8.1
Particle identification |  0.1 |  0.1 |  0.1 |  0.2 |  0.2 |  3.0 |  1.0 |  0.2 |  1.2 |  1.1 |  1.7 |  3.2
Efficiency determination |  2.0 |  2.0 |  2.0 |  2.0 |  2.0 |  2.0 |  2.0 |  2.0 |  2.0 |  2.0 |  2.0 |  2.0
Signal extraction |  1.5 |  1.2 |  3.6 |  0.6 |  0.7 |  3.0 |  1.5 |  0.2 |  1.0 |  3.2 |  2.5 |  2.3
Proper lifetime |  1.3 |  0.1 |  0.2 |  0.3 |  2.3 |  0.1 |  0.9 |  0.1 |  0.1 |  2.2 |  0.7 |  0.7
Competing decay rejection |  negl. |  0.7 |  1.3 |  negl. |  1.0 |  6.2 | not applicable |  0.2 |  4.2 |  5.2
Feed-down correction | not applicable |  3.3 |  2.1 |  4.3 | negligible | negligible
Total |  5.6 |  6.9 |  6.4 |  5.8 |  8.2 |  11.2 |  5.9 |  5.0 |  6.7 |  7.9 |  9.0 |  12.1
Common ($N_{\rm ch}$-independent) |  5.0 |  5.9 |  4.4 |  5.4 |  7.8 |  9.9 |  5.2 |  4.5 |  6.2 |  7.3 |  8.7 |  11.6

##  Appendix B The ALICE Collaboration

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MolnarB, L. Montaño ZetinaB, E. MontesB, D.A. Moreira De GodoyB, L.A.P.
MorenoB, S. MorettoB, A. MorrealeB, A. MorschB, V. MucciforaB, E. MudnicB, D.
MühlheimB, S. MuhuriB, M. MukherjeeB, J.D. MulliganB, M.G. MunhozB, K.
MünningB, R.H. MunzerB,B,B, H. MurakamiB, S. MurrayB, L. MusaB, J. MusinskyB,
B. NaikB, R. NairB, B.K. NandiB, R. NaniaB, E. NappiB, M.U. NaruB, H. Natal da
LuzB, C. NattrassB, S.R. NavarroB, K. NayakB, R. NayakB, T.K. NayakB, S.
NazarenkoB, A. NedosekinB, R.A. Negrao De OliveiraB, L. NellenB, F. NgB, M.
NicassioB, M. NiculescuB, J. NiedzielaB, B.S. NielsenB, S. NikolaevB, S.
NikulinB, V. NikulinB, F. NoferiniB,B, P. NomokonovB, G. NoorenB, J.C.C.
NorisB, J. NormanB, A. NyaninB, J. NystrandB, H. OeschlerB, S. OhB, S.K. OhB,
A. OhlsonB, A. OkatanB, T. OkuboB, J. OleniaczB, A.C. Oliveira Da SilvaB, M.H.
OliverB, J. OnderwaaterB, C. OppedisanoB, R. OravaB, M. OravecB, A. Ortiz
VelasquezB, A. OskarssonB, J. OtwinowskiB, K. OyamaB,B, M. OzdemirB, Y.
PachmayerB, D. PaganoB, P. PaganoB, G. PaićB, S.K. PalB, P. PalniB, J. PanB,
A.K. PandeyB, V. PapikyanB, G.S. PappalardoB, P. PareekB, W.J. ParkB, S.
ParmarB, A. PassfeldB, V. PaticchioB, R.N. PatraB, B. PaulB, H. PeiB, T.
PeitzmannB, X. PengB, H. Pereira Da CostaB, D. PeresunkoB,B, E. Perez LezamaB,
V. PeskovB, Y. PestovB, V. PetráčekB, V. PetrovB, M. PetroviciB, C. PettaB, S.
PianoB, M. PiknaB, P. PillotB, L.O.D.L. PimentelB, O. PinazzaB,B, L. PinskyB,
D.B. PiyarathnaB, M. PłoskońB, M. PlaninicB, J. PlutaB, S. PochybovaB, P.L.M.
Podesta-LermaB, M.G. PoghosyanB, B. PolichtchoukB, N. PoljakB, W. PoonsawatB,
A. PopB, H. PoppenborgB, S. Porteboeuf-HoussaisB, J. PorterB, J. PospisilB,
S.K. PrasadB, R. PreghenellaB,B, F. PrinoB, C.A. PruneauB, I. PshenichnovB, M.
PuccioB, G. PudduB, P. PujahariB, V. PuninB, J. PutschkeB, H. QvigstadB, A.
RachevskiB, S. RahaB, S. RajputB, J. RakB, A. RakotozafindrabeB, L. RamelloB,
F. RamiB, R. RaniwalaB, S. RaniwalaB, S.S. RäsänenB, B.T. RascanuB, D.
RatheeB, I. RavasengaB, K.F. ReadB,B, K. RedlichB, R.J. ReedB, A. RehmanB, P.
ReicheltB, F. ReidtB,B, X. RenB, R. RenfordtB, A.R. ReolonB, A. ReshetinB, K.
ReygersB, V. RiabovB, R.A. RicciB, T. RichertB, M. RichterB, P. RiedlerB, W.
RieglerB, F. RiggiB, C. RisteaB, M. Rodríguez CahuantziB, A. Rodriguez MansoB,
K. RøedB, E. RogochayaB, D. RohrB, D. RöhrichB, F. RonchettiB,B, L.
RonfletteB, P. RosnetB, A. RossiB, F. RoukoutakisB, A. RoyB, C. RoyB, P. RoyB,
A.J. Rubio MonteroB, R. RuiB, R. RussoB, E. RyabinkinB, Y. RyabovB, A.
RybickiB, S. SaarinenB, S. SadhuB, S. SadovskyB, K. ŠafaříkB, B. SahlmullerB,
P. SahooB, R. SahooB, S. SahooB, P.K. SahuB, J. SainiB, S. SakaiB, M.A.
SalehB, J. SalzwedelB, S. SambyalB, V. SamsonovB,B, L. ŠándorB, A. SandovalB,
M. SanoB, D. SarkarB, N. SarkarB, P. SarmaB, E. ScapparoneB, F. ScarlassaraB,
C. SchiauaB, R. SchickerB, C. SchmidtB, H.R. SchmidtB, M. SchmidtB, S.
SchuchmannB,B, J. SchukraftB, Y. SchutzB,B, K. SchwarzB, K. SchwedaB, G.
ScioliB, E. ScomparinB, R. ScottB, M. ŠefčíkB, J.E. SegerB, Y. SekiguchiB, D.
SekihataB, I. SelyuzhenkovB, K. SenosiB, S. SenyukovB,B, E. SerradillaB,B, A.
SevcencoB, A. ShabanovB, A. ShabetaiB, O. ShaduraB, R. ShahoyanB, A.
ShangaraevB, A. SharmaB, M. SharmaB, M. SharmaB, N. SharmaB, A.I. SheikhB, K.
ShigakiB, Q. ShouB, K. ShtejerB,B, Y. SibiriakB, S. SiddhantaB, K.M.
SielewiczB, T. SiemiarczukB, D. SilvermyrB, C. SilvestreB, G. SimatovicB, G.
SimonettiB, R. SingarajuB, R. SinghB, V. SinghalB, T. SinhaB, B. SitarB, M.
SittaB, T.B. SkaaliB, M. SlupeckiB, N. SmirnovB, R.J.M. SnellingsB, T.W.
SnellmanB, J. SongB, M. SongB, Z. SongB, F. SoramelB, S. SorensenB, F. SozziB,
E. SpiritiB, I. SputowskaB, M. Spyropoulou-StassinakiB, J. StachelB, I. StanB,
P. StankusB, E. StenlundB, G. SteynB, J.H. StillerB, D. StoccoB, P. StrmenB,
A.A.P. SuaideB, T. SugitateB, C. SuireB, M. SuleymanovB, M. SuljicB,B, R.
SultanovB, M. ŠumberaB, S. SumowidagdoB, S. SwainB, A. SzaboB, I. SzarkaB, A.
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N. TanakaB, M. TarhiniB, M. TariqB, M.G. TarzilaB, A. TauroB, G. Tejeda
MuñozB, A. TelescaB, K. TerasakiB, C. TerrevoliB, B. TeyssierB, J. ThäderB, D.
ThakurB, D. ThomasB, R. TieulentB, A. TikhonovB, A.R. TimminsB, A. ToiaB, S.
TrogoloB, G. TrombettaB, V. TrubnikovB, W.H. TrzaskaB, T. TsujiB, A. TumkinB,
R. TurrisiB, T.S. TveterB, K. UllalandB, A. UrasB, G.L. UsaiB, A. UtrobicicB,
M. ValaB, L. Valencia PalomoB, J. Van Der MaarelB, J.W. Van HoorneB,B, M. van
LeeuwenB, T. VanatB, P. Vande VyvreB, D. VargaB, A. VargasB, M. VargyasB, R.
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ZimmermannB,B, G. ZinovjevB, M. ZyzakB

## Affiliation notes

Deceased

Also at: Georgia State University, Atlanta, Georgia, United States

Also at: Also at Department of Applied Physics, Aligarh Muslim University,
Aligarh, India

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

## Collaboration Institutes

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

Benemérita Universidad Autónoma de Puebla, Puebla, Mexico

Bogolyubov Institute for Theoretical Physics, Kiev, Ukraine

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

Budker Institute for Nuclear Physics, Novosibirsk, Russia

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

Central China Normal University, Wuhan, China

Centre de Calcul de l’IN2P3, Villeurbanne, France

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

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

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

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

Chicago State University, Chicago, Illinois, USA

China Institute of Atomic Energy, Beijing, China

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

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

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

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

Department of Physics, Aligarh Muslim University, Aligarh, India

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

Department of Physics, Sejong University, Seoul, South Korea

Department of Physics, University of Oslo, Oslo, Norway

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

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

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

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

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

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

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

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

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

Dipartimento DISAT del Politecnico and Sezione INFN, Turin, Italy

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

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

Eberhard Karls Universität Tübingen, Tübingen, Germany

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

Excellence Cluster Universe, Technische Universität München, Munich, Germany

Faculty of Engineering, Bergen University College, Bergen, Norway

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

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

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

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

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

Gangneung-Wonju National University, Gangneung, South Korea

Gauhati University, Department of Physics, Guwahati, India

Helmholtz-Institut für Strahlen- und Kernphysik, Rheinische Friedrich-
Wilhelms-Universität Bonn, Bonn, Germany

Helsinki Institute of Physics (HIP), Helsinki, Finland

Hiroshima University, Hiroshima, Japan

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

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

Indonesian Institute of Sciences, Jakarta, Indonesia

Inha University, Incheon, South Korea

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

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

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

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

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

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

Institute for Subatomic Physics of Utrecht University, Utrecht, Netherlands

Institute for Theoretical and Experimental Physics, Moscow, Russia

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

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

Institute of Physics, Bhubaneswar, India

Institute of Space Science (ISS), Bucharest, Romania

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

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

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

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

Konkuk University, Seoul, South Korea

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

KTO Karatay University, Konya, Turkey

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

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

Laboratori Nazionali di Frascati, INFN, Frascati, Italy

Laboratori Nazionali di Legnaro, INFN, Legnaro, Italy

Lawrence Berkeley National Laboratory, Berkeley, California, United States

Moscow Engineering Physics Institute, Moscow, Russia

Nagasaki Institute of Applied Science, Nagasaki, Japan

National Centre for Nuclear Studies, Warsaw, Poland

National Institute for Physics and Nuclear Engineering, Bucharest, Romania

National Institute of Science Education and Research, Bhubaneswar, India

National Research Centre Kurchatov Institute, Moscow, Russia

Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark

Nikhef, Nationaal instituut voor subatomaire fysica, Amsterdam, Netherlands

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

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

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

Petersburg Nuclear Physics Institute, Gatchina, Russia

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

Physics Department, Panjab University, Chandigarh, India

Physics Department, University of Athens, Athens, Greece

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

Physics Department, University of Jammu, Jammu, India

Physics Department, University of Rajasthan, Jaipur, India

Physik Department, Technische Universität München, Munich, Germany

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

Purdue University, West Lafayette, Indiana, United States

Pusan National University, Pusan, South Korea

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

Rudjer Bošković Institute, Zagreb, Croatia

Russian Federal Nuclear Center (VNIIEF), Sarov, Russia

Saha Institute of Nuclear Physics, Kolkata, India

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

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

Sezione INFN, Bari, Italy

Sezione INFN, Bologna, Italy

Sezione INFN, Cagliari, Italy

Sezione INFN, Catania, Italy

Sezione INFN, Padova, Italy

Sezione INFN, Rome, Italy

Sezione INFN, Trieste, Italy

Sezione INFN, Turin, Italy

SSC IHEP of NRC Kurchatov institute, Protvino, Russia

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

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

Suranaree University of Technology, Nakhon Ratchasima, Thailand

Technical University of Košice, Košice, Slovakia

Technical University of Split FESB, Split, Croatia

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

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

Universidad Autónoma de Sinaloa, Culiacán, Mexico

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

Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil

University of Houston, Houston, Texas, United States

University of Jyväskylä, Jyväskylä, Finland

University of Liverpool, Liverpool, United Kingdom

University of Tennessee, Knoxville, Tennessee, United States

University of the Witwatersrand, Johannesburg, South Africa

University of Tokyo, Tokyo, Japan

University of Tsukuba, Tsukuba, Japan

University of Zagreb, Zagreb, Croatia

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

Università di Brescia, Brescia, Italy

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

Variable Energy Cyclotron Centre, Kolkata, India

Warsaw University of Technology, Warsaw, Poland

Wayne State University, Detroit, Michigan, United States

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

Yale University, New Haven, Connecticut, United States

Yonsei University, Seoul, South Korea

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