2024 148 27 May

Measurement of ${}_{\Lambda}^{3}\mathrm{H}$ production in Pb–Pb collisions at
$\sqrt{s_{\mathrm{NN}}}~{}=~{}5.02$ TeV

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

The first measurement of ${}_{\Lambda}^{3}\mathrm{H}$ and
${}^{3}_{\overline{\Lambda}}\overline{\mathrm{H}}$ differential production
with respect to transverse momentum and centrality in Pb–Pb collisions at
$\sqrt{s_{\mathrm{NN}}}~{}=~{}5.02$ TeV is presented. The
${}_{\Lambda}^{3}\mathrm{H}$ has been reconstructed via its two-charged-body
decay channel, i.e.,
${}_{\Lambda}^{3}\mathrm{H}\rightarrow{}^{3}\mathrm{He}+\pi^{-}$. A Blast-Wave
model fit of the $p_{\rm T}$-differential spectra of all nuclear species
measured by the ALICE collaboration suggests that the
${}_{\Lambda}^{3}\mathrm{H}$ kinetic freeze-out surface is consistent with
that of other nuclei. The ratio between the integrated yields of
${}_{\Lambda}^{3}\mathrm{H}$ and ${}^{3}\mathrm{He}$ is compared to
predictions from the statistical hadronisation model and the coalescence
model, with the latter being favoured by the presented measurements.

##  1 Introduction

Relativistic heavy-ion collisions provide a rich environment for the study of
nuclei, hypernuclei, and their charge conjugates. Hypernuclei are nuclei that
have at least one hyperon among their constituents. The additional strange
baryon leads to a unique nuclear system that can help to benchmark the
interactions among hyperons and nucleons. Understanding such interactions has
become particularly relevant in recent years due to their important
connections with the modeling of the equation-of-state of dense astrophysical
objects, such as the neutron stars [1, 2]. In fact, a precise knowledge of the
two-body (Y–N) and three-body (Y–N–N) hyperon–nucleon forces allows for
determining whether the presence of hyperons in the innermost core of neutron
stars, which is known to be energetically favourable, reconciles with the
recent observations of large-mass neutron stars [3, 4]. Multiple studies
analysing particle momentum correlations [5, 6] play a direct role in
establishing these interactions. In a complementary approach, the lifetime and
the binding energy of a hypernucleus reflect the strength of the Y–N and Y–N–N
forces [7, 8, 9].

The lightest known hypernucleus is the hypertriton
(${}_{\Lambda}^{3}\mathrm{H}$), composed of a proton, a neutron, and a
$\Lambda$ hyperon. As such, it represents the simplest system to study the
interaction among $\Lambda$ hyperons and nucleons. Early experiments studied
${}_{\Lambda}^{3}\mathrm{H}$ using nuclear emulsions and helium bubble
chambers [10, 11, 12, 13, 14]. These experiments obtained results with large
statistical uncertainties. In recent years, more precise measurements have
been performed by ALICE [15, 16, 17, 18] and STAR [19, 20, 21] Collaborations
in relativistic heavy-ion collisions at the CERN LHC and BNL RHIC colliders.
Such measurements contributed in determining that the
${}_{\Lambda}^{3}\mathrm{H}$ is a loosely bound state with a $\Lambda$
separation energy, $B_{\Lambda}$, of the order of one hundred keV, and has an
average lifetime very close to the free $\Lambda$ one [22]. With such
properties, the hypertriton wave function is expected to have a radial
extension of approximately 5 fm [23, 24, 25], considerably larger than the
other nuclei with a mass number equal to three and comparable in size to the
fireball created in Pb–Pb collisions.

There are two main classes of models used to explain the formation of nuclei
in Pb–Pb collisions: the statistical hadronisation model (SHM) and the
coalescence model. While the SHM is insensitive to the structure of the
particle being produced [26, 27, 28, 29], the coalescence model relies on the
knowledge of the particle wave function to produce predictions [30, 31, 32,
33, 34, 35, 36]. There is a wealth of variations for each class of models but
based on similar approach. In the SHM, the production cross section of a
specific particle is determined solely by a temperature, denoted as chemical
freeze-out temperature, the volume of the system created in the collision, the
quantum numbers, and the mass of the particle. In Pb–Pb collisions, the grand
canonical formulation of the SHM has proven to be very successful in
describing the yields of light flavoured hadrons [26]. Based on the two
parameters from the analysis of light hadrons, the SHM then provides a
parameter-free prediction of the yields of (hyper)nuclei. In the coalescence
model, the production rate of nuclei is given by the convolution between the
phase space of the nucleons produced in the collision and the nuclear wave
function, according to the Wigner function formalism [37]. These two models
give similar predictions for the yield ratios of most ordinary nuclei (e.g.
d/p) [33, 32, 34] and qualitatively describe the available experimental data
at the LHC [38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49]. However, when it
comes to a tight configuration or a loosely-bound state, the prediction of the
SHM and the coalescence model for particle ratios diverge significantly in all
collision systems. For example, recent studies on the yield of
${}^{4}\mathrm{He}$ in Pb–Pb collisions show an agreement with the SHM while
the coalescence model failed to explain it [49]. Conversely, the
${}_{\Lambda}^{3}\mathrm{H}$/$\Lambda$ ratio in p–Pb collisions [17] is only
well-described by the coalescence predictions. This discrepancy indicates that
the nucleosynthesis mechanism [50, 51] still needs further investigation with
new experimental measurements.

This letter presents the first measurement of the ${}_{\Lambda}^{3}\mathrm{H}$
production in Pb–Pb collisions at a center-of-mass energy per nucleon pair
$\sqrt{s_{\mathrm{NN}}}~{}=~{}5.02$ TeV. In Sec. 2 the ALICE apparatus and the
analysis method are described, whereas the results are discussed in Sec. 3.

##  2 The ALICE detector and analysis details

The ALICE apparatus is composed of several specialised detectors, as detailed
in [52]. In this analysis, ${}_{\Lambda}^{3}\mathrm{H}$ are reconstructed
using both the Inner Tracking System (ITS) [53] and the Time Projection
Chamber (TPC) [54] detectors. The ITS is the closest central-barrel detector
to the beam pipe and comprises six cylindrical layers. The primary role of ITS
is to reconstruct charged-particle trajectories and to measure precisely the
position of the interaction vertices. The TPC is a gaseous detector employed
as the primary tracking and particle identification (PID) device in ALICE. The
TPC is used to identify charged particles by measuring their specific energy
loss. Both ITS and TPC are placed in a homogeneous magnetic field of 0.5 T
produced by a solenoidal magnet. These two detectors cover the entire azimuth
in the pseudorapidity range $|\eta|<$ 0.9. The centrality determination and
trigger are provided by a pair of forward (2.8 $<\eta<$ 5.1) and backward
($-$3.7 $<\eta<$ $-$1.7) detectors called V0A and V0C [55], respectively. The
coincidence of a signal in the V0A and a signal in the V0C is used as a
minimum-bias trigger. Additionally, two thresholds on the minimum amount of
charge deposited on the V0 detector are implemented to trigger online on
central and semi-central Pb–Pb collisions. These thresholds are defined by the
Glauber model fit to the V0 detector signal amplitudes [55, 56].

The data sample employed in this analysis has been collected during the LHC
2018 Pb–Pb run at $\sqrt{s_{\mathrm{NN}}}~{}=~{}5.02$ TeV. Based on the signal
amplitudes of the V0 detectors, three centrality classes are considered (from
central to peripheral collisions): 0–10%, 10–30%, and 30–50%. The centrality
classes are labeled according to the corresponding percentiles of the Pb–Pb
hadronic interaction cross section. The stored events, categorized into the
0–10% and 30–50% classes, are enriched by the online trigger on central and
semi-central collisions. In total, approximately 210 million events are
studied. At the LHC energies, approximately the same number of
${}_{\Lambda}^{3}\mathrm{H}$ and
${}^{3}_{\overline{\Lambda}}\overline{\mathrm{H}}$ are produced [57].
Therefore, the results of ${}_{\Lambda}^{3}\mathrm{H}$ and
${}^{3}_{\overline{\Lambda}}\overline{\mathrm{H}}$ are averaged. In the
following, we use the notation ${}_{\Lambda}^{3}\mathrm{H}$ for both particle
and antiparticle.

A dedicated Monte Carlo (MC) simulated sample has been employed for optimising
the ${}_{\Lambda}^{3}\mathrm{H}$ selection and evaluating the efficiency
corrections. The MC sample consists of ${}_{\Lambda}^{3}\mathrm{H}$ signal
injected on top of underlying Pb–Pb collisions, which are simulated with the
HIJING event generator [58]. In each MC event, 80 ${}_{\Lambda}^{3}\mathrm{H}$
are injected. The transverse momentum ($p_{\rm T}$) distribution of the
injected signal is given by the Blast-Wave [59] function, with parameters
taken from fit to the ${}^{3}\mathrm{He}$ $p_{\rm T}$ spectra [48]. The
particle transport through the detector material is done using Geant4 [60],
which simulates both the interaction with the material and the weak decay
kinematics of the ${}_{\Lambda}^{3}\mathrm{H}$.

In this analysis, ${}_{\Lambda}^{3}\mathrm{H}$ candidates are reconstructed
via the two-charged-body mesonic decay channel
${}_{\Lambda}^{3}\mathrm{H}\rightarrow{}^{3}\mathrm{He}+\pi^{-}$ (and the
related charge conjugated process). Firstly, a preselection method is
performed. Tracks that have specific energy loss in the TPC compatible within
5$\sigma$ to that of ${}^{3}\mathrm{He}$ or $\pi$ tracks are employed to
reconstruct the ${}_{\Lambda}^{3}\mathrm{H}$ decay topology with the algorithm
used in previous analyses [15, 16, 17]. The reconstruction of
${}_{\Lambda}^{3}\mathrm{H}$ candidates employed the ALICE secondary vertex
finder method which pairs opposite-sign ${}^{3}\mathrm{He}$ and $\pi$
candidate tracks. The tracks are required to have more than 50 hits in TPC
($N^{\mathrm{TPC}}_{\mathrm{cls}}$) and good fit quality
($\chi^{2}/N^{\mathrm{TPC}}_{\mathrm{cls}}<4$). In order to mitigate the
contamination from ${}^{3}\mathrm{He}$ produced in the interaction with
materials, an additional selection $p_{\rm T}>1.2$
$\mathrm{Ge\kern-1.00006ptV/}c$ is imposed for ${}^{3}\mathrm{He}$. Additional
selection criteria are used by combining data on the decay kinematics and the
position of the decay vertex. The selections include the maximum distance-of-
closest-approach (DCA) of the decay products to the primary vertex
($\mathrm{DCA_{toPV}}$ $<$ 8 cm) and among the daughter tracks themselves
($\mathrm{DCA_{tracks}}$ $<$ 1.6 cm), and the cosine of the angle between the
${}_{\Lambda}^{3}\mathrm{H}$ momentum vector and the straight line connecting
the primary and secondary vertices ($\cos\mathrm{\theta_{P}}$). The selection
on $\cos\mathrm{\theta_{P}}$ is set as a function of the proper decay time of
the candidates such to ensure a 95% efficiency for reconstructing true
${}_{\Lambda}^{3}\mathrm{H}$.

Figure 1:  Invariant-mass distribution of selected
${}_{\Lambda}^{3}\mathrm{H}$ candidates in the centrality class 0–10% and
$p_{\rm T}$ interval 3 $<$ $p_{\rm T}$ $<$ 3.5 $\mathrm{Ge\kern-1.00006ptV/}c$
fitted with a function which is the sum of a double-sided Crystal Ball signal
and an exponential background. Vertical lines represent the statistical
uncertainties.

The main selection step consists of combining the candidate features in a
gradient-boosted decision tree classifier (BDT) [61, 62] that is employed for
the ${}_{\Lambda}^{3}\mathrm{H}$ signal selection. The BDT is a supervised
learning algorithm that determines how to differentiate between two or more
classes, specifically signal and background in this context, by analysing sets
of examples referred to as the training sets. In this analysis, the training
sets consist of ${}_{\Lambda}^{3}\mathrm{H}$ signal candidates obtained from
the MC sample and background candidates from paired like-sign
$\mathrm{{}^{3}He}$ and $\mathrm{\pi}$ tracks from the data. For each
${}_{\Lambda}^{3}\mathrm{H}$ candidate, the BDT combines a set of topological
and single-track variables to produce a score, which serves to separate signal
and background. The variables do not exhibit correlation with the
${}^{3}\mathrm{He}$-$\pi$ invariant mass and are: the decay length in the rest
frame $ct$, the $\cos\theta_{\mathrm{P}}$, the PID information for
${}^{3}\mathrm{He}$, the DCA to the primary vertex for both
${}^{3}\mathrm{He}$ and $\pi$ tracks, the DCA between ${}^{3}\mathrm{He}$ and
$\pi$, and the number of clusters of the ${}^{3}\mathrm{He}$ track in the TPC.
Candidates with a BDT score exceeding a specified threshold are classified as
signal. This threshold is determined to optimise the expected signal
significance, taking into account the predicted production yield according to
the SHM for the ${}_{\Lambda}^{3}\mathrm{H}$, as well as the background rate
observed from like-sign ${}^{3}\mathrm{He}$ and $\pi$ pairs.

The BDT training and testing steps and the ${}_{\Lambda}^{3}\mathrm{H}$ yield
computation have been performed in different centrality and $p_{\rm T}$
intervals independently. The ${}_{\Lambda}^{3}\mathrm{H}$ signal is extracted
from the invariant-mass distribution after rejecting candidates whose score is
lower than the BDT model threshold. An unbinned maximum-likelihood fit is
performed to the ${}_{\Lambda}^{3}\mathrm{H}$ invariant-mass distribution,
employing a double-sided Crystal Ball (DSCB) [63] function and an exponential
function to model the signal and the background components of the spectrum,
respectively. The parameters of the DSCB function are fixed using the MC
sample leaving only the mean and the normalisation of the DSCB free. Figure 1
shows an example of the invariant-mass fit in the most central collisions and
in the $p_{\rm T}$ interval $3<p_{\rm T}<3.5$ $\mathrm{Ge\kern-1.00006ptV/}c$.
The number of detected ${}_{\Lambda}^{3}\mathrm{H}$ is obtained from the
integral of the DSCB function. However, this number has to be corrected to
account for the detection efficiency, the branching ratio (B.R.), and the
absorption of the ${}_{\Lambda}^{3}\mathrm{H}$ in the ALICE detector material.
The detection efficiency comprises several components, including the
acceptance of the ALICE detector, the absorption of daughter tracks, and the
selection efficiency. It can be directly computed using the MC sample in
different centrality and $p_{\rm T}$ intervals. The detection efficiency
increases with the ${}_{\Lambda}^{3}\mathrm{H}$ $p_{\rm T}$ and ranges from
10% to 38%. The branching ratio is set to 0.25 $\pm$ 0.023 according to Ref.
[7]. Finally, the absorption correction ($C_{\mathrm{abs}}$) is computed by
simulating the interaction of ${}_{\Lambda}^{3}\mathrm{H}$ with the ALICE
detector material with Geant4, and evaluating the probability
($P_{\mathrm{abs}}$) of the ${}_{\Lambda}^{3}\mathrm{H}$ to be absorbed before
decaying. The absorption cross section employed for the simulation has been
extracted from Ref. [64], which accounts for the extension of the
${}_{\Lambda}^{3}\mathrm{H}$ wave function, and amounts to about 1.5 times
that of the ${}^{3}\mathrm{He}$. The probability of
${}_{\Lambda}^{3}\mathrm{H}$ to be absorbed is found to be increasing as a
function of $p_{\rm T}$ due to the larger amount of material crossed by the
high-momentum particle. The corresponding correction, computed as
$C_{\mathrm{abs}}=1-P_{\mathrm{abs}}$, ranges from 0.96 to 0.93.

The main systematic uncertainties on the measurement of the
${}_{\Lambda}^{3}\mathrm{H}$ $p_{\rm T}$ spectra are due to the
${}_{\Lambda}^{3}\mathrm{H}$ decay reconstruction, the BDT selection, and the
invariant-mass fit in each $p_{\rm T}$ interval. These systematic
uncertainties are estimated as an envelope by employing a multi-trial
approach. In this approach, the following elements of the analysis are varied:
two different weak-decay vertex-reconstruction methods, two different
background datasets for the BDT training, two different fit functions for the
${}_{\Lambda}^{3}\mathrm{H}$ signal (a Kernel Density Estimator [65] and the
DSCB), three different fit functions for the combinatorial background
modelling (polynomial of the first and second order, and an exponential
function), and different BDT selection thresholds (giving rise to a $\pm 10\%$
variation of the efficiency around its nominal value). These elements are
varied incoherently to populate a distribution of different yields that
constitute our trial distribution in each $p_{\rm T}$ and centrality interval.
The systematic uncertainty is then estimated as the standard deviation of the
obtained distributions and varies from 8% to 34% in different intervals. Since
the absorption cross section of ${}_{\Lambda}^{3}\mathrm{H}$ is uncertain, an
additional uncertainty due to the absorption is evaluated by changing the
interaction cross section in the simulation to three times the
${}^{3}\mathrm{He}$ inelastic cross section with the detector materials. This
results in systematic uncertainties of 4%–6%, depending on the $p_{\rm T}$
interval. Another source of the uncertainty originates from the uncertainty on
the branching ratio, which amounts to 9% and is common to all the $p_{\rm T}$
and centrality classes.

##  3 Results and Discussions

The ${}_{\Lambda}^{3}\mathrm{H}$ $p_{\rm T}$-differential spectra in different
centrality intervals, defined as the average of particles and antiparticles,
are shown in Fig. 2 along with the spectra of deuterons, antitritons, and
${}^{3}\mathrm{He}$ in the corresponding centrality ranges, as measured in
Ref. [48]. A simultaneous fit with the Blast-Wave model parameterisation [59]
is done with all the shown spectra. The parameters of the combined Blast-Wave
fit are listed in Table 1. Notably, the temperature and velocity in the Blast-
Wave fit are compatible with those obtained by fitting only light nuclei (d,
t, ${}^{3}\mathrm{He}$, ${}^{4}\mathrm{He}$) [49], suggesting a similar
kinetic freeze-out surface for light-flavoured nuclei.

Individual Blast-Wave fits are employed to extrapolate the
${}_{\Lambda}^{3}\mathrm{H}$ spectrum in the unmeasured $p_{\rm T}$ range and
obtain the total yield ($\mathrm{d}N/\mathrm{d}y$) in the three centrality
classes. The variation intervals of the fit parameters are restricted to an
interval of $\pm 1\sigma$ around the parameters obtained from the combined
fits shown in Fig. 2. The resulting $\mathrm{d}N/\mathrm{d}y$ values are
reported in Table 1. The fraction of extrapolated yield using the Blast-Wave
fit is 13%, 39%, and 27% for the 0–10%, 10–30%, and 30–50% centrality classes,
respectively. The total uncertainties on the integrated yields
$\sigma(\mathrm{BW_{tot}})$ are computed by fitting the spectra considering
both statistical and systematic uncertainties. To separate the statistical and
systematic components of the uncertainty which originates from the Blast-Wave
extrapolation, a fit considering only statistical uncertainty of the
${}_{\Lambda}^{3}\mathrm{H}$ spectra is used to estimate the statistical
component ($\sigma(\mathrm{BW_{stat}})$). The systematic uncertainty due to
the fitting procedure is extracted using the relation
$\sigma(\mathrm{BW_{syst}})=\sqrt{\sigma(\mathrm{BW_{tot}})^{2}-\mathrm{\sigma(BW_{stat})^{2}}}$.
An additional source of systematic uncertainty to the measured yield arises
from the unknown $p_{\rm T}$ distribution of ${}_{\Lambda}^{3}\mathrm{H}$. As
the fits performed with other functions, namely $m_{\mathrm{T}}$-exponential
and Boltzmann, have not passed the Pearson $\chi^{2}$ test for the goodness of
the fit and since the $p_{\rm T}$ distribution of ${}_{\Lambda}^{3}\mathrm{H}$
should be very similar to ${}^{3}\mathrm{He}$ according to the Blast-Wave
model [59], the related uncertainty is inherited from the previous
${}^{3}\mathrm{He}$ production analysis [48] and corresponds to 1.8%, 3.3%,
and 0.3% of the measured integrated yield in 0–10%, 10–30%, 30–50%,
respectively.

Figure 2: Deuteron (d), antitriton ($\mathrm{\overline{t}}$), ${}^{3}\mathrm{He}$ [48], and ${}_{\Lambda}^{3}\mathrm{H}$ spectra measured in Pb–Pb collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV. Each panel shows a centrality interval and different nuclei are reported with different colours. For ${}_{\Lambda}^{3}\mathrm{H}$, the average spectra between particles and antiparticles is employed. The boxes represent the systematic uncertainties, while the vertical lines are the statistical ones. The combined Blast-Wave fit parameters for d, $\mathrm{\overline{t}}$, ${}^{3}\mathrm{He}$, and ${}_{\Lambda}^{3}\mathrm{H}$ are listed in Table 1. Table 1: Parameters of the combined Blast-Wave fits and integrated (${}_{\Lambda}^{3}\mathrm{H}$ \+ ${}^{3}_{\overline{\Lambda}}\overline{\mathrm{H}}$)/2 yields in different centrality intervals. The fits include deuteron, antitriton, ${}^{3}\mathrm{He}$, and ${}_{\Lambda}^{3}\mathrm{H}$ as shown in Fig. 2. The ${}_{\Lambda}^{3}\mathrm{H}$ yields are obtained with an individual Blast-Wave fit whose parameters are restricted in 1$\sigma$ region of the parameters shown in the table.  Centrality | $\langle\beta_{\mathrm{T}}\rangle$ | T (GeV) | n |  $\chi^{2}$ / ndf |  $\mathrm{d}N/\mathrm{d}y\times 10^{-5}$ (B.R. = 0.25)
---|---|---|---|---|---
0–10% | 0.694 $\pm$ 0.003 | 0.103 $\pm$ 0.005 | 0.498 $\pm$ 0.009 | 43.4 / 39 | 4.83 $\pm$ 0.23(stat) $\pm$ 0.57(syst)
10–30% | 0.666 $\pm$ 0.003 | 0.132 $\pm$ 0.008 | 0.507 $\pm$ 0.012 | 19.1 / 34 | 2.62 $\pm$ 0.25(stat) $\pm$ 0.40(syst)
30–50% | 0.598 $\pm$ 0.005 | 0.152 $\pm$ 0.010 | 0.660 $\pm$ 0.022 | 21.8 / 33 | 1.27 $\pm$ 0.10(stat) $\pm$ 0.14(syst)

The production yield of ${}_{\Lambda}^{3}\mathrm{H}$ provides a powerful tool
to investigate the mechanism of nuclear production in relativistic hadronic
collisions [18]. The measured ${}_{\Lambda}^{3}\mathrm{H}$ yield in all the
centrality intervals is directly compared with the predictions from the grand-
canonical SHM [66] with T=155 MeV. The predicted ${}_{\Lambda}^{3}\mathrm{H}$
$\mathrm{d}N/\mathrm{d}y$ ($9.5\times 10^{-5}$) is approximately two times
higher than the measured one in central Pb–Pb collisions, suggesting that the
SHM, as applied, may lack certain elements necessary for accurately describing
the generation of this weakly bound state.

On the other hand, while the SHM is able to calculate directly the absolute
yields of hadrons, in the coalescence model only the yield ratios among
particles can be computed without any further knowledge of the momentum
spectra of the nucleons. To compare with both the models, SHM and coalescence,
the ${}_{\Lambda}^{3}\mathrm{H}/^{3}\mathrm{He}$ ratio is considered. The
produced charged-particle multiplicties per unit of pseudorapidity
$\langle\mathrm{d}N_{\mathrm{ch}}/\mathrm{d}\eta\rangle$, which are related to
the centrality of the collision and can reflect the size of the fireball, may
have effects on the ratios of particle yields and need to be taken into
account. In this case, the grand-canonical SHM predicts no multiplicity
dependence. A deviation from the grand-canonical ensemble prediction is
present in the canonical SHM only for
$\langle\mathrm{d}N_{\mathrm{ch}}/\mathrm{d}\eta\rangle_{|\eta|<0.5}<100$
[27], which corresponds to peripheral collisions comparatively and is not
covered by the presented results. The coalescence model formulation here
considered [67] uses the Wigner function formalism and a parametrisation of
the wave function of the ${}_{\Lambda}^{3}\mathrm{H}$ that depends on its
$\Lambda$ separation energy. Three different coalescence predictions are shown
by setting $B_{\Lambda}$ to the latest ALICE and STAR experimental values and
to the world average of the $B_{\Lambda}$ measurements [18, 20, 22]. The
uncertainty due to the $B_{\Lambda}$ value is asymmetric as the
${}_{\Lambda}^{3}\mathrm{H}$ wave function width is not a linear function of
$B_{\Lambda}$. Furthermore, the coalescence model predicts a suppression of
the ${}_{\Lambda}^{3}\mathrm{H}/^{3}\mathrm{He}$ ratio with decreasing
multiplicities due to the interplay between the smaller hadron emission source
in peripheral Pb–Pb collisions and the wide wave function of the
${}_{\Lambda}^{3}\mathrm{H}$. In Fig. 3, the model predictions are compared
with the measured ${}_{\Lambda}^{3}\mathrm{H}/^{3}\mathrm{He}$ yield ratio as
a function of the average charged-particle multiplicity of the analysed
centrality intervals. The measured
${}_{\Lambda}^{3}\mathrm{H}/^{3}\mathrm{He}$ yield ratios are well described
by the coalescence prediction using the current world average of $B_{\Lambda}$
(solid blue line). In addition, the recent STAR measurements [21] suggest a
similar suppression of the ${}_{\Lambda}^{3}\mathrm{H}/^{3}\mathrm{He}$ ratio
going from large (Au–Au and U–U) to smaller (Zr–Zr and Ru–Ru) collision
systems. For larger values of $B_{\Lambda}$, the predictions from the
coalescence model approach that of the SHM, but they are not compatible with
the measured ratios. The results from a prior ALICE analysis [15] in Pb–Pb
collisions at $\sqrt{s_{\mathrm{NN}}}$ = 2.76 TeV are included in Fig. 3 for
comparison. The results presented in this Letter remain consistent with the
previous study within a 2$\sigma$ confidence interval, but uncertainties are
twice as small as those obtained from the smaller data sample at lower
collision energy.

Figure 3: Yield ratio of ${}_{\Lambda}^{3}\mathrm{H}$ to ${}^{3}\mathrm{He}$
together with theoretical predictions as a function of multiplicity. In the
left panel, the results of this analysis are compared with the ALICE
measurement at $\sqrt{s_{\mathrm{NN}}}$ = 2.76 TeV [15]. Vertical lines are
used for the statistical uncertainties and boxes for the systematic ones. For
each centrality interval the
$\langle\mathrm{d}N_{\mathrm{ch}}/\mathrm{d}\eta\rangle$ is taken from Ref.
[68] and the ${}^{3}\mathrm{He}$ yield from Ref. [48]. The dense orange dashed
line represents the expectation of SHM, while the other three sets of lines
stand for coalescence model with different $B_{\Lambda}$ hypotheses. The
coalescence prediction with world average $B_{\Lambda}$ is displayed with a
1$\sigma$ uncertainty as the filled area, both lines and shadowed areas are
linear interpolations of the available model calculations [67]. In the right
panel, the results of recent STAR measurement are shown for comparison [21].

In Fig. 4, the ${}_{\Lambda}^{3}\mathrm{H}/^{3}\mathrm{He}$ yield ratio as a
function of $p_{\rm T}$ in the three different centrality intervals is shown.
While the SHM does not infer the expected $p_{\rm T}$ shape of the particles,
the coalescence mechanism implies a decrease of the
${}_{\Lambda}^{3}\mathrm{H}/^{3}\mathrm{He}$ ratio for increasing $p_{\rm T}$.
Conversely, in a simple hydrodynamic picture like the Blast-Wave model, the
radial flow boosts the high $p_{\rm T}$ production of heavier particles such
as the ${}_{\Lambda}^{3}\mathrm{H}$. Consequently, within the Blast-Wave
framework, the ${}_{\Lambda}^{3}\mathrm{H}/^{3}\mathrm{He}$ ratio is expected
to increase as a function of $p_{\rm T}$. However, the current experimental
uncertainties do not allow for a definitive conclusion on the trend of the
${}_{\Lambda}^{3}\mathrm{H}$/ ${}^{3}\mathrm{He}$ ratio as a function of
$p_{\rm T}$.

Figure 4: The ${}_{\Lambda}^{3}\mathrm{H}/^{3}\mathrm{He}$ yield ratio
together with theoretical predictions in different centrality intervals as a
function of $p_{\rm T}$. The vertical lines and boxes represent the
statistical and systematic uncertainties, respectively. The pink solid lines
are calculated as the ratios of the Blast-Wave fit functions for
${}^{3}\mathrm{He}$ and ${}_{\Lambda}^{3}\mathrm{H}$. The other three curves
stand for the predictions of the coalescence model with different
$B_{\Lambda}$ hypotheses. The coalescence prediction with world average
$B_{\Lambda}$ is displayed with a 1$\sigma$ uncertainty band [67].

##  4 Conclusions

This Letter presents the first $p_{\rm T}$-differential measurement of the
${}_{\Lambda}^{3}\mathrm{H}$ production in Pb–Pb collisions at
$\sqrt{s_{\mathrm{NN}}}~{}=~{}5.02$ TeV. The $p_{\rm T}$ distribution of
${}_{\Lambda}^{3}\mathrm{H}$ is well described by a simultaneous Blast-Wave
fit with other light nuclei. The fit temperature and velocity profiles are
compatible with those found for other light-flavoured nuclei, hinting to a
common kinetic freeze-out surface for hypernuclei and ordinary nuclei produced
in Pb–Pb collisions. The $p_{\rm T}$-integrated yields show a significant
discrepancy with respect to the predictions of the SHM tuned to fit the other
light-flavoured particles. Furthermore, the yield ratio
${}_{\Lambda}^{3}\mathrm{H}/^{3}\mathrm{He}$ was calculated to test the
predictions of the coalescence model, that is able to describe the measured
ratios when assuming the correct binding energy of the
${}_{\Lambda}^{3}\mathrm{H}$. Finally, both the coalescence and the Blast-Wave
models describe the experimental data for the
${}_{\Lambda}^{3}\mathrm{H}/^{3}\mathrm{He}$ ratios as a function of $p_{\rm
T}$. However, their predictions have a different $p_{\rm T}$ trend. Presently,
the large experimental uncertainties preclude a definitive interpretation;
however, the forthcoming data from LHC Run 3 will allow the ALICE
Collaboration to measure this quantity with unprecedented precision.

## Acknowledgements

The ALICE Collaboration would like to thank all its engineers and technicians for their invaluable contributions to the construction of the experiment and the CERN accelerator teams for the outstanding performance of the LHC complex. The ALICE Collaboration gratefully acknowledges the resources and support provided by all Grid centres and the Worldwide LHC Computing Grid (WLCG) collaboration. The ALICE Collaboration acknowledges the following funding agencies for their support in building and running the ALICE detector: A. I. Alikhanyan National Science Laboratory (Yerevan Physics Institute) Foundation (ANSL), State Committee of Science and World Federation of Scientists (WFS), Armenia; Austrian Academy of Sciences, Austrian Science Fund (FWF): [M 2467-N36] and Nationalstiftung für Forschung, Technologie und Entwicklung, Austria; Ministry of Communications and High Technologies, National Nuclear Research Center, Azerbaijan; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Financiadora de Estudos e Projetos (Finep), Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) and Universidade Federal do Rio Grande do Sul (UFRGS), Brazil; Bulgarian Ministry of Education and Science, within the National Roadmap for Research Infrastructures 2020-2027 (object CERN), Bulgaria; Ministry of Education of China (MOEC) , Ministry of Science & Technology of China (MSTC) and National Natural Science Foundation of China (NSFC), China; Ministry of Science and Education and Croatian Science Foundation, Croatia; Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN), Cubaenergía, Cuba; Ministry of Education, Youth and Sports of the Czech Republic, Czech Republic; The Danish Council for Independent Research | Natural Sciences, the VILLUM FONDEN and Danish National Research Foundation (DNRF), Denmark; Helsinki Institute of Physics (HIP), Finland; Commissariat à l’Energie Atomique (CEA) and Institut National de Physique Nucléaire et de Physique des Particules (IN2P3) and Centre National de la Recherche Scientifique (CNRS), France; Bundesministerium für Bildung und Forschung (BMBF) and GSI Helmholtzzentrum für Schwerionenforschung GmbH, Germany; General Secretariat for Research and Technology, Ministry of Education, Research and Religions, Greece; National Research, Development and Innovation Office, Hungary; Department of Atomic Energy Government of India (DAE), Department of Science and Technology, Government of India (DST), University Grants Commission, Government of India (UGC) and Council of Scientific and Industrial Research (CSIR), India; National Research and Innovation Agency - BRIN, Indonesia; Istituto Nazionale di Fisica Nucleare (INFN), Italy; Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) and Japan Society for the Promotion of Science (JSPS) KAKENHI, Japan; Consejo Nacional de Ciencia (CONACYT) y Tecnología, through Fondo de Cooperación Internacional en Ciencia y Tecnología (FONCICYT) and Dirección General de Asuntos del Personal Academico (DGAPA), Mexico; Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO), Netherlands; The Research Council of Norway, Norway; Pontificia Universidad Católica del Perú, Peru; Ministry of Science and Higher Education, National Science Centre and WUT ID-UB, Poland; Korea Institute of Science and Technology Information and National Research Foundation of Korea (NRF), Republic of Korea; Ministry of Education and Scientific Research, Institute of Atomic Physics, Ministry of Research and Innovation and Institute of Atomic Physics and Universitatea Nationala de Stiinta si Tehnologie Politehnica Bucuresti, Romania; Ministry of Education, Science, Research and Sport of the Slovak Republic, Slovakia; National Research Foundation of South Africa, South Africa; Swedish Research Council (VR) and Knut & Alice Wallenberg Foundation (KAW), Sweden; European Organization for Nuclear Research, Switzerland; Suranaree University of Technology (SUT), National Science and Technology Development Agency (NSTDA) and National Science, Research and Innovation Fund (NSRF via PMU-B B05F650021), Thailand; Turkish Energy, Nuclear and Mineral Research Agency (TENMAK), Turkey; National Academy of Sciences of Ukraine, Ukraine; Science and Technology Facilities Council (STFC), United Kingdom; National Science Foundation of the United States of America (NSF) and United States Department of Energy, Office of Nuclear Physics (DOE NP), United States of America. In addition, individual groups or members have received support from: Czech Science Foundation (grant no. 23-07499S), Czech Republic; European Research Council (grant no. 950692), European Union; ICSC - Centro Nazionale di Ricerca in High Performance Computing, Big Data and Quantum Computing, European Union - NextGenerationEU; Academy of Finland (Center of Excellence in Quark Matter) (grant nos. 346327, 346328), Finland.

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##  Appendix A The ALICE Collaboration

S. Acharya 127, D. Adamová 86, A. Agarwal135, G. Aglieri Rinella 32, L.
Aglietta24, M. Agnello 29, N. Agrawal 25, Z. Ahammed 135, S. Ahmad 15, S.U.
Ahn 71, I. Ahuja 37, A. Akindinov 141, V. Akishina38, M. Al-Turany 97, D.
Aleksandrov 141, B. Alessandro 56, H.M. Alfanda 6, R. Alfaro Molina 67, B. Ali
15, A. Alici 25, N. Alizadehvandchali 116, A. Alkin 104, J. Alme 20, G. Alocco
52, T. Alt 64, A.R. Altamura 50, I. Altsybeev 95, J.R. Alvarado 44, M.N. Anaam
6, C. Andrei 45, N. Andreou 115, A. Andronic 126, E. Andronov 141, V. Anguelov
94, F. Antinori 54, P. Antonioli 51, N. Apadula 74, L. Aphecetche 103, H.
Appelshäuser 64, C. Arata 73, S. Arcelli 25, M. Aresti 22, R. Arnaldi 56,
J.G.M.C.A. Arneiro 110, I.C. Arsene 19, M. Arslandok 138, A. Augustinus 32, R.
Averbeck 97, D. Averyanov 141, M.D. Azmi 15, H. Baba124, A. Badalà 53, J. Bae
104, Y.W. Baek 40, X. Bai 120, R. Bailhache 64, Y. Bailung 48, R. Bala 91, A.
Balbino 29, A. Baldisseri 130, B. Balis 2, D. Banerjee 4, Z. Banoo 91, V.
Barbasova37, F. Barile 31, L. Barioglio 56, M. Barlou78, B. Barman41, G.G.
Barnaföldi 46, L.S. Barnby 115, E. Barreau 103, V. Barret 127, L. Barreto 110,
C. Bartels 119, K. Barth 32, E. Bartsch 64, N. Bastid 127, S. Basu 75, G.
Batigne 103, D. Battistini 95, B. Batyunya 142, D. Bauri47, J.L. Bazo Alba
101, I.G. Bearden 83, C. Beattie 138, P. Becht 97, D. Behera 48, I. Belikov
129, A.D.C. Bell Hechavarria 126, F. Bellini 25, R. Bellwied 116, S.
Belokurova 141, L.G.E. Beltran 109, Y.A.V. Beltran 44, G. Bencedi 46, A.
Bensaoula116, S. Beole 24, Y. Berdnikov 141, A. Berdnikova 94, L. Bergmann 94,
M.G. Besoiu 63, L. Betev 32, P.P. Bhaduri 135, A. Bhasin 91, B. Bhattacharjee
41, L. Bianchi 24, N. Bianchi 49, J. Bielčík 35, J. Bielčíková 86, A.P. Bigot
129, A. Bilandzic 95, G. Biro 46, S. Biswas 4, N. Bize 103, J.T. Blair 108, D.
Blau 141, M.B. Blidaru 97, N. Bluhme38, C. Blume 64, G. Boca 21,55, F. Bock
87, T. Bodova 20, J. Bok 16, L. Boldizsár 46, M. Bombara 37, P.M. Bond 32, G.
Bonomi 134,55, H. Borel 130, A. Borissov 141, A.G. Borquez Carcamo 94, H.
Bossi 138, E. Botta 24, Y.E.M. Bouziani 64, L. Bratrud 64, P. Braun-Munzinger
97, M. Bregant 110, M. Broz 35, G.E. Bruno 96,31, V.D. Buchakchiev 36, M.D.
Buckland 23, D. Budnikov 141, H. Buesching 64, S. Bufalino 29, P. Buhler 102,
N. Burmasov 141, Z. Buthelezi 68,123, A. Bylinkin 20, S.A. Bysiak107, J.C.
Cabanillas Noris 109, M.F.T. Cabrera116, M. Cai 6, H. Caines 138, A. Caliva
28, E. Calvo Villar 101, J.M.M. Camacho 109, P. Camerini 23, F.D.M. Canedo
110, S.L. Cantway 138, M. Carabas 113, A.A. Carballo 32, F. Carnesecchi 32, R.
Caron 128, L.A.D. Carvalho 110, J. Castillo Castellanos 130, M. Castoldi 32,
F. Catalano 32, S. Cattaruzzi 23, C. Ceballos Sanchez 142, R. Cerri24, I.
Chakaberia 74, P. Chakraborty 136,47, S. Chandra 135, S. Chapeland 32, M.
Chartier 119, S. Chattopadhay135, S. Chattopadhyay 135, S. Chattopadhyay 99,
M. Chen39, T. Cheng 97,6, C. Cheshkov 128, V. Chibante Barroso 32, D.D.
Chinellato 111, E.S. Chizzali II,95, J. Cho 58, S. Cho 58, P. Chochula 32,
Z.A. Chochulska136, D. Choudhury41, P. Christakoglou 84, C.H. Christensen 83,
P. Christiansen 75, T. Chujo 125, M. Ciacco 29, C. Cicalo 52, M.R. Ciupek97,
G. ClaiIII,51, F. Colamaria 50, J.S. Colburn100, D. Colella 31, M. Colocci 25,
M. Concas 32, G. Conesa Balbastre 73, Z. Conesa del Valle 131, G. Contin 23,
J.G. Contreras 35, M.L. Coquet 103,130, P. Cortese 133,56, M.R. Cosentino 112,
F. Costa 32, S. Costanza 21,55, C. Cot 131, J. Crkovská 94, P. Crochet 127, R.
Cruz-Torres 74, P. Cui 6, M.M. Czarnynoga136, A. Dainese 54, G. Dange38, M.C.
Danisch 94, A. Danu 63, P. Das 80, P. Das 4, S. Das 4, A.R. Dash 126, S. Dash
47, A. De Caro 28, G. de Cataldo 50, J. de Cuveland38, A. De Falco 22, D. De
Gruttola 28, N. De Marco 56, C. De Martin 23, S. De Pasquale 28, R. Deb 134,
R. Del Grande 95, L. Dello Stritto 32, W. Deng 6, K.C. Devereaux18, P.
Dhankher 18, D. Di Bari 31, A. Di Mauro 32, B. Diab 130, R.A. Diaz 142,7, T.
Dietel 114, Y. Ding 6, J. Ditzel 64, R. Divià 32, Ø. Djuvsland20, U. Dmitrieva
141, A. Dobrin 63, B. Dönigus 64, J.M. Dubinski 136, A. Dubla 97, P. Dupieux
127, N. Dzalaiova13, T.M. Eder 126, R.J. Ehlers 74, F. Eisenhut 64, R.
Ejima92, D. Elia 50, B. Erazmus 103, F. Ercolessi 25, B. Espagnon 131, G.
Eulisse 32, D. Evans 100, S. Evdokimov 141, L. Fabbietti 95, M. Faggin 23, J.
Faivre 73, F. Fan 6, W. Fan 74, A. Fantoni 49, M. Fasel 87, A. Feliciello 56,
G. Feofilov 141, A. Fernández Téllez 44, L. Ferrandi 110, M.B. Ferrer 32, A.
Ferrero 130, C. Ferrero IV,56, A. Ferretti 24, V.J.G. Feuillard 94, V. Filova
35, D. Finogeev 141, F.M. Fionda 52, E. Flatland32, F. Flor 138,116, A.N.
Flores 108, S. Foertsch 68, I. Fokin 94, S. Fokin 141, U. FolloIV,56, E.
Fragiacomo 57, E. Frajna 46, U. Fuchs 32, N. Funicello 28, C. Furget 73, A.
Furs 141, T. Fusayasu 98, J.J. Gaardhøje 83, M. Gagliardi 24, A.M. Gago 101,
T. Gahlaut47, C.D. Galvan 109, D.R. Gangadharan 116, P. Ganoti 78, C.
Garabatos 97, J.M. Garcia44, T. García Chávez 44, E. Garcia-Solis 9, C.
Gargiulo 32, P. Gasik 97, H.M. Gaur38, A. Gautam 118, M.B. Gay Ducati 66, M.
Germain 103, R.A. Gernhaeuser95, C. Ghosh135, M. Giacalone 51, G. Gioachin 29,
S.K. Giri135, P. Giubellino 97,56, P. Giubilato 27, A.M.C. Glaenzer 130, P.
Glässel 94, E. Glimos 122, D.J.Q. Goh76, V. Gonzalez 137, P. Gordeev 141, M.
Gorgon 2, K. Goswami 48, S. Gotovac33, V. Grabski 67, L.K. Graczykowski 136,
E. Grecka 86, A. Grelli 59, C. Grigoras 32, V. Grigoriev 141, S. Grigoryan
142,1, F. Grosa 32, J.F. Grosse-Oetringhaus 32, R. Grosso 97, D. Grund 35,
N.A. Grunwald94, G.G. Guardiano 111, R. Guernane 73, M. Guilbaud 103, K.
Gulbrandsen 83, J.J.W.K. Gumprecht102, T. Gündem 64, T. Gunji 124, W. Guo 6,
A. Gupta 91, R. Gupta 91, R. Gupta 48, K. Gwizdziel 136, L. Gyulai 46, C.
Hadjidakis 131, F.U. Haider 91, S. Haidlova 35, M. Haldar4, H. Hamagaki 76, A.
Hamdi 74, Y. Han 139, B.G. Hanley 137, R. Hannigan 108, J. Hansen 75, M.R.
Haque 97, J.W. Harris 138, A. Harton 9, M.V. Hartung 64, H. Hassan 117, D.
Hatzifotiadou 51, P. Hauer 42, L.B. Havener 138, E. Hellbär 97, H. Helstrup
34, M. Hemmer 64, T. Herman 35, S.G. Hernandez116, G. Herrera Corral 8, S.
Herrmann 128, K.F. Hetland 34, B. Heybeck 64, H. Hillemanns 32, B. Hippolyte
129, F.W. Hoffmann 70, B. Hofman 59, G.H. Hong 139, M. Horst 95, A. Horzyk 2,
Y. Hou 6, P. Hristov 32, P. Huhn64, L.M. Huhta 117, T.J. Humanic 88, A. Hutson
116, D. Hutter 38, M.C. Hwang 18, R. Ilkaev141, M. Inaba 125, G.M. Innocenti
32, M. Ippolitov 141, A. Isakov 84, T. Isidori 118, M.S. Islam 99, S.
Iurchenko141, M. Ivanov 97, M. Ivanov13, V. Ivanov 141, K.E. Iversen 75, M.
Jablonski 2, B. Jacak 18,74, N. Jacazio 25, P.M. Jacobs 74, S. Jadlovska106,
J. Jadlovsky106, S. Jaelani 82, C. Jahnke 110, M.J. Jakubowska 136, M.A. Janik
136, T. Janson70, S. Ji 16, S. Jia 10, F. Jonas 74, D.M. Jones 119, J.M.
Jowett 32,97, J. Jung 64, M. Jung 64, A. Junique 32, A. Jusko 100, J.
Kaewjai105, P. Kalinak 60, A. Kalweit 32, A. Karasu Uysal V,72, D. Karatovic
89, N. Karatzenis100, O. Karavichev 141, T. Karavicheva 141, E. Karpechev 141,
M.J. Karwowska 32,136, U. Kebschull 70, R. Keidel 140, M. Keil 32, B. Ketzer
42, S.S. Khade 48, A.M. Khan 120, S. Khan 15, A. Khanzadeev 141, Y. Kharlov
141, A. Khatun 118, A. Khuntia 35, Z. Khuranova 64, B. Kileng 34, B. Kim 104,
C. Kim 16, D.J. Kim 117, E.J. Kim 69, J. Kim 139, J. Kim 58, J. Kim 32,69, M.
Kim 18, S. Kim 17, T. Kim 139, K. Kimura 92, A. Kirkova36, S. Kirsch 64, I.
Kisel 38, S. Kiselev 141, A. Kisiel 136, J.P. Kitowski 2, J.L. Klay 5, J.
Klein 32, S. Klein 74, C. Klein-Bösing 126, M. Kleiner 64, T. Klemenz 95, A.
Kluge 32, C. Kobdaj 105, R. Kohara124, T. Kollegger97, A. Kondratyev 142, N.
Kondratyeva 141, J. Konig 64, S.A. Konigstorfer 95, P.J. Konopka 32, G.
Kornakov 136, M. Korwieser 95, S.D. Koryciak 2, C. Koster84, A. Kotliarov 86,
N. Kovacic89, V. Kovalenko 141, M. Kowalski 107, V. Kozhuharov 36, I. Králik
60, A. Kravčáková 37, L. Krcal 32,38, M. Krivda 100,60, F. Krizek 86, K.
Krizkova Gajdosova 32, C. Krug 66, M. Krüger 64, D.M. Krupova 35, E. Kryshen
141, V. Kučera 58, C. Kuhn 129, P.G. Kuijer 84, T. Kumaoka125, D. Kumar135, L.
Kumar 90, N. Kumar90, S. Kumar 31, S. Kundu 32, P. Kurashvili 79, A. Kurepin
141, A.B. Kurepin 141, A. Kuryakin 141, S. Kushpil 86, V. Kuskov 141, M.
Kutyla136, A. Kuznetsov142, M.J. Kweon 58, Y. Kwon 139, S.L. La Pointe 38, P.
La Rocca 26, A. Lakrathok105, M. Lamanna 32, A.R. Landou 73, R. Langoy 121, P.
Larionov 32, E. Laudi 32, L. Lautner 32,95, R.A.N. Laveaga109, R. Lavicka 102,
R. Lea 134,55, H. Lee 104, I. Legrand 45, G. Legras 126, J. Lehrbach 38, A.M.
Lejeune35, T.M. Lelek2, R.C. Lemmon 85, I. León Monzón 109, M.M. Lesch 95,
E.D. Lesser 18, P. Lévai 46, M. Li6, X. Li10, B.E. Liang-gilman 18, J. Lien
121, R. Lietava 100, I. Likmeta 116, B. Lim 24, S.H. Lim 16, V. Lindenstruth
38, A. Lindner45, C. Lippmann 97, D.H. Liu 6, J. Liu 119, G.S.S. Liveraro 111,
I.M. Lofnes 20, C. Loizides 87, S. Lokos 107, J. Lömker 59, X. Lopez 127, E.
López Torres 7, C. Lotteau128, P. Lu 97,120, F.V. Lugo 67, J.R. Luhder 126, M.
Lunardon 27, G. Luparello 57, Y.G. Ma 39, M. Mager 32, A. Maire 129, E.M.
Majerz2, M.V. Makariev 36, M. Malaev 141, G. Malfattore 25, N.M. Malik 91,
Q.W. Malik19, S.K. Malik 91, L. Malinina I,VIII,142, D. Mallick 131, N.
Mallick 48, G. Mandaglio 30,53, S.K. Mandal 79, A. Manea 63, V. Manko 141, F.
Manso 127, V. Manzari 50, Y. Mao 6, R.W. Marcjan 2, G.V. Margagliotti 23, A.
Margotti 51, A. Marín 97, C. Markert 108, P. Martinengo 32, M.I. Martínez 44,
G. Martínez García 103, M.P.P. Martins 110, S. Masciocchi 97, M. Masera 24, A.
Masoni 52, L. Massacrier 131, O. Massen 59, A. Mastroserio 132,50, O. Matonoha
75, S. Mattiazzo 27, A. Matyja 107, A.L. Mazuecos 32, F. Mazzaschi 32,24, M.
Mazzilli 116, J.E. Mdhluli 123, Y. Melikyan 43, A. Menchaca-Rocha 67, J.E.M.
Mendez 65, E. Meninno 102, A.S. Menon 116, M.W. Menzel32,94, M. Meres 13, Y.
Miake125, L. Micheletti 32, D.L. Mihaylov 95, K. Mikhaylov 142,141, N. Minafra
118, D. Miśkowiec 97, A. Modak 134,4, B. Mohanty80, M. Mohisin Khan VI,15,
M.A. Molander 43, S. Monira 136, C. Mordasini 117, D.A. Moreira De Godoy 126,
I. Morozov 141, A. Morsch 32, T. Mrnjavac 32, V. Muccifora 49, S. Muhuri 135,
J.D. Mulligan 74, A. Mulliri 22, M.G. Munhoz 110, R.H. Munzer 64, H. Murakami
124, S. Murray 114, L. Musa 32, J. Musinsky 60, J.W. Myrcha 136, B. Naik 123,
A.I. Nambrath 18, B.K. Nandi 47, R. Nania 51, E. Nappi 50, A.F. Nassirpour 17,
A. Nath 94, S. Nath135, C. Nattrass 122, M.N. Naydenov 36, A. Neagu19, A.
Negru113, E. Nekrasova141, L. Nellen 65, R. Nepeivoda 75, S. Nese 19, G.
Neskovic 38, N. Nicassio 50, B.S. Nielsen 83, E.G. Nielsen 83, S. Nikolaev
141, S. Nikulin 141, V. Nikulin 141, F. Noferini 51, S. Noh 12, P. Nomokonov
142, J. Norman 119, N. Novitzky 87, P. Nowakowski 136, A. Nyanin 141, J.
Nystrand 20, S. Oh 17, A. Ohlson 75, V.A. Okorokov 141, J. Oleniacz 136, A.
Onnerstad 117, C. Oppedisano 56, A. Ortiz Velasquez 65, J. Otwinowski 107, M.
Oya92, K. Oyama 76, Y. Pachmayer 94, S. Padhan 47, D. Pagano 134,55, G. Paić
65, S. Paisano-Guzmán 44, A. Palasciano 50, S. Panebianco 130, H. Park 125, H.
Park 104, J. Park 125, J.E. Parkkila 32, Y. Patley 47, R.N. Patra50, B. Paul
135, M.M.D.M. Paulino 110, H. Pei 6, T. Peitzmann 59, X. Peng 11, M. Pennisi
24, S. Perciballi 24, D. Peresunko 141, G.M. Perez 7, Y. Pestov141, M.T.
Petersen83, V. Petrov 141, M. Petrovici 45, S. Piano 57, M. Pikna 13, P.
Pillot 103, O. Pinazza 51,32, L. Pinsky116, C. Pinto 95, S. Pisano 49, M.
Płoskoń 74, M. Planinic89, F. Pliquett64, D.K. Plociennik2, M.G. Poghosyan 87,
B. Polichtchouk 141, S. Politano 29, N. Poljak 89, A. Pop 45, S. Porteboeuf-
Houssais 127, V. Pozdniakov I,142, I.Y. Pozos 44, K.K. Pradhan 48, S.K. Prasad
4, S. Prasad 48, R. Preghenella 51, F. Prino 56, C.A. Pruneau 137, I.
Pshenichnov 141, M. Puccio 32, S. Pucillo 24, S. Qiu 84, L. Quaglia 24, S.
Ragoni 14, A. Rai 138, A. Rakotozafindrabe 130, L. Ramello 133,56, F. Rami
129, M. Rasa 26, S.S. Räsänen 43, R. Rath 51, M.P. Rauch 20, I. Ravasenga 32,
K.F. Read 87,122, C. Reckziegel 112, A.R. Redelbach 38, K. Redlich VII,79,
C.A. Reetz 97, H.D. Regules-Medel44, A. Rehman20, F. Reidt 32, H.A. Reme-Ness
34, Z. Rescakova37, K. Reygers 94, A. Riabov 141, V. Riabov 141, R. Ricci 28,
M. Richter 20, A.A. Riedel 95, W. Riegler 32, A.G. Riffero 24, C. Ripoli28, C.
Ristea 63, M.V. Rodriguez 32, M. Rodríguez Cahuantzi 44, S.A. Rodríguez
Ramírez 44, K. Røed 19, R. Rogalev 141, E. Rogochaya 142, T.S. Rogoschinski
64, D. Rohr 32, D. Röhrich 20, S. Rojas Torres 35, P.S. Rokita 136, G.
Romanenko 25, F. Ronchetti 49, E.D. Rosas65, K. Roslon 136, A. Rossi 54, A.
Roy 48, S. Roy 47, N. Rubini 51,25, J.A. Rudolph84, D. Ruggiano 136, R. Rui
23, P.G. Russek 2, R. Russo 84, A. Rustamov 81, E. Ryabinkin 141, Y. Ryabov
141, A. Rybicki 107, J. Ryu 16, W. Rzesa 136, B. Sabiu51, S. Sadovsky 141, J.
Saetre 20, K. Šafařík 35, S.K. Saha 4, S. Saha 80, B. Sahoo 48, R. Sahoo 48,
S. Sahoo61, D. Sahu 48, P.K. Sahu 61, J. Saini 135, K. Sajdakova37, S. Sakai
125, M.P. Salvan 97, S. Sambyal 91, D. Samitz 102, I. Sanna 32,95, T.B.
Saramela110, D. Sarkar 83, P. Sarma 41, V. Sarritzu 22, V.M. Sarti 95, M.H.P.
Sas 32, S. Sawan 80, E. Scapparone 51, J. Schambach 87, H.S. Scheid 64, C.
Schiaua 45, R. Schicker 94, F. Schlepper 94, A. Schmah97, C. Schmidt 97, H.R.
Schmidt93, M.O. Schmidt 32, M. Schmidt93, N.V. Schmidt 87, A.R. Schmier 122,
R. Schotter 129, A. Schröter 38, J. Schukraft 32, K. Schweda 97, G. Scioli 25,
E. Scomparin 56, J.E. Seger 14, Y. Sekiguchi124, D. Sekihata 124, M. Selina
84, I. Selyuzhenkov 97, S. Senyukov 129, J.J. Seo 94, D. Serebryakov 141, L.
Serkin 65, L. Šerkšnytė 95, A. Sevcenco 63, T.J. Shaba 68, A. Shabetai 103, R.
Shahoyan32, A. Shangaraev 141, B. Sharma 91, D. Sharma 47, H. Sharma 54, M.
Sharma 91, S. Sharma 76, S. Sharma 91, U. Sharma 91, A. Shatat 131, O.
Sheibani116, K. Shigaki 92, M. Shimomura77, J. Shin12, S. Shirinkin 141, Q.
Shou 39, Y. Sibiriak 141, S. Siddhanta 52, T. Siemiarczuk 79, T.F. Silva 110,
D. Silvermyr 75, T. Simantathammakul105, R. Simeonov 36, B. Singh91, B. Singh
95, K. Singh 48, R. Singh 80, R. Singh 91, R. Singh 97, S. Singh 15, V.K.
Singh 135, V. Singhal 135, T. Sinha 99, B. Sitar 13, M. Sitta 133,56, T.B.
Skaali19, G. Skorodumovs 94, N. Smirnov 138, R.J.M. Snellings 59, E.H. Solheim
19, J. Song 16, C. Sonnabend 32,97, J.M. Sonneveld 84, F. Soramel 27, A.B.
Soto-hernandez 88, R. Spijkers 84, I. Sputowska 107, J. Staa 75, J. Stachel
94, I. Stan 63, P.J. Steffanic 122, S.F. Stiefelmaier 94, D. Stocco 103, I.
Storehaug 19, N.J. Strangmann 64, P. Stratmann 126, S. Strazzi 25, A.
Sturniolo 30,53, C.P. Stylianidis84, A.A.P. Suaide 110, C. Suire 131, M.
Sukhanov 141, M. Suljic 32, R. Sultanov 141, V. Sumberia 91, S. Sumowidagdo
82, I. Szarka 13, M. Szymkowski 136, S.F. Taghavi 95, G. Taillepied 97, J.
Takahashi 111, G.J. Tambave 80, S. Tang 6, Z. Tang 120, J.D. Tapia Takaki 118,
N. Tapus113, L.A. Tarasovicova 126, M.G. Tarzila 45, G.F. Tassielli 31, A.
Tauro 32, A. Tavira García 131, G. Tejeda Muñoz 44, A. Telesca 32, L. Terlizzi
24, C. Terrevoli 50, S. Thakur 4, D. Thomas 108, A. Tikhonov 141, N. Tiltmann
32,126, A.R. Timmins 116, M. Tkacik106, T. Tkacik 106, A. Toia 64, R.
Tokumoto92, S. Tomassini25, K. Tomohiro92, N. Topilskaya 141, M. Toppi 49,
V.V. Torres 103, A.G. Torres Ramos 31, A. Trifiró 30,53, T. Triloki96, A.S.
Triolo 32,30,53, S. Tripathy 32, T. Tripathy 47, V. Trubnikov 3, W.H. Trzaska
117, T.P. Trzcinski 136, C. Tsolanta19, R. Tu39, A. Tumkin 141, R. Turrisi 54,
T.S. Tveter 19, K. Ullaland 20, B. Ulukutlu 95, A. Uras 128, M. Urioni 134,
G.L. Usai 22, M. Vala37, N. Valle 55, L.V.R. van Doremalen59, M. van Leeuwen
84, C.A. van Veen 94, R.J.G. van Weelden 84, P. Vande Vyvre 32, D. Varga 46,
Z. Varga 46, P. Vargas Torres65, M. Vasileiou 78, A. Vasiliev 141, O. Vázquez
Doce 49, O. Vazquez Rueda 116, V. Vechernin 141, E. Vercellin 24, S. Vergara
Limón44, R. Verma47, L. Vermunt 97, R. Vértesi 46, M. Verweij 59, L.
Vickovic33, Z. Vilakazi123, O. Villalobos Baillie 100, A. Villani 23, A.
Vinogradov 141, T. Virgili 28, M.M.O. Virta 117, A. Vodopyanov 142, B. Volkel
32, M.A. Völkl 94, S.A. Voloshin 137, G. Volpe 31, B. von Haller 32, I.
Vorobyev 32, N. Vozniuk 141, J. Vrláková 37, J. Wan39, C. Wang 39, D. Wang39,
Y. Wang 39, Y. Wang 6, A. Wegrzynek 32, F.T. Weiglhofer38, S.C. Wenzel 32,
J.P. Wessels 126, J. Wiechula 64, J. Wikne 19, G. Wilk 79, J. Wilkinson 97,
G.A. Willems 126, B. Windelband 94, M. Winn 130, J.R. Wright 108, W. Wu39, Y.
Wu 120, Z. Xiong120, R. Xu 6, A. Yadav 42, A.K. Yadav 135, Y. Yamaguchi 92, S.
Yang20, S. Yano 92, E.R. Yeats18, Z. Yin 6, I.-K. Yoo 16, J.H. Yoon 58, H.
Yu12, S. Yuan20, A. Yuncu 94, V. Zaccolo 23, C. Zampolli 32, M. Zang6, F.
Zanone 94, N. Zardoshti 32, A. Zarochentsev 141, P. Závada 62, N.
Zaviyalov141, M. Zhalov 141, B. Zhang 6, C. Zhang 130, L. Zhang 39, M.
Zhang127,6, S. Zhang 39, X. Zhang 6, Y. Zhang120, Z. Zhang 6, M. Zhao 10, V.
Zherebchevskii 141, Y. Zhi10, D. Zhou 6, Y. Zhou 83, J. Zhu 54,6, S. Zhu120,
Y. Zhu6, S.C. Zugravel 56, N. Zurlo 134,55

## Affiliation Notes

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

## Collaboration Institutes

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