# STUDY OF GAS PURIFIERS FOR THE CMS RPC DETECTOR

L. Benussi  S. Bianco  S.Colafranceschi  F.L. Fabbri  F. Felli  M. Ferrini  M.
Giardoni  T. Greci  A. Paolozzi  L. Passamonti  D. Piccolo  D. Pierluigi  A.
Russo  G. Saviano  S. Buontempo  A. Cimmino  M. de Gruttola  F Fabozzi  A.O.M.
Iorio  L. Lista  P. Paolucci  P. Baesso  G. Belli  D. Pagano  S.P. Ratti  A.
Vicini  P. Vitulo  C. Viviani  R. Guida  A. Sharma  INFN Laboratori Nazionali
di Frascati, Via E. Fermi 40, I-00044 Fr ascati, Italy  Sapienza Università
degli Studi di Roma ”La Sapienza”, Piazzale A. Moro, Roma, Italy  CERN CH-1211
Genéve 23 F-01631 Switzerland  INFN Sezione di Napoli, Complesso Universitario
di Monte Sant’Angelo, edificio 6, 80126 Napoli, Italy  Università di Napoli
Federico II, Complesso Universitario di Monte Sant’Angelo, edificio 6, 80126
Napoli, Italy  INFN Sezione di Pavia and Università degli studi di Pavia, Via
Bassi 6, 27100 Pavia, Italy

###### Abstract

The CMS RPC muon detector utilizes a gas recirculation system called closed
loop (CL) to cope with large gas mixture volumes and costs. A systematic study
of CL gas purifiers has been carried out over 400 days between July 2008 and
August 2009 at CERN in a low-radiation test area, with the use of RPC chambers
with currents monitoring, and gas analysis sampling points. The study aimed to
fully clarify the presence of pollutants, the chemistry of purifiers used in
the CL, and the regeneration procedure. Preliminary results on contaminants
release and purifier characterization are reported.

###### keywords:

RPC , CMS , gas , purifier detectors HEP muon

††thanks: Corresponding author: Giovanna Saviano
E-mail address<EMAIL_ADDRESS>
##  1 Introduction

The Resistive Plate Chamber (RPC) [1] muon detector of the Compact Muon
Solenoid (CMS) experiment[2] utilizes a gas recirculation system called closed
loop (CL) [3], [4] to cope with large gas mixture volumes and costs. A
systematic study of Closed Loop gas purifiers has been carried out in 2008 and
2009 at the ISR experimental area of CERN with the use of RPC chambers exposed
to cosmic rays with currents monitoring and gas analysis sampling points.
Goals of the study [5] were to observe the release of contaminants in
correlation with the dark current increase in RPC detectors, to measure the
purifier lifetime, to observe the presence of pollutants and to study the
regeneration procedure. Previous results had shown the presence of metallic
contaminants, and an incomplete regeneration of purifiers [6],[7].

The basic function of the CMS CL system is to mix and purify the gas
components in the appropriate proportions and to distribute the mixture to the
individual chambers. The gas mixture used is 95.2% of C2H2F4 in its
environmental-friendly version R137a, 4.5% of $i$C4H10, and 0.3% SF6 to
suppress streamers and operate in saturated avalanche mode. Gas mixture is
humidified at the 45% RH (Relative Humidity) level typically to balance
ambient humidity, which affects the resistivity of highly hygroscopic
bakelite, and to improve efficiency at lower operating voltage. The CL is
operated with a fraction of fresh mixture continuously injected into the
system. Baseline design fresh mixture fraction for CMS is 2%, the test CL
system was operated at 10% fresh mixture. The fresh mixture fraction is the
fraction of the total gas content continuously replaced in the CL system with
fresh mixture. The filter configuration is identical to the CMS experiment.

##  2 Experimental setup and data sample

In the CL system gas purity is guaranteed by a multistage purifier system:

  * •

The purifier-1 consisting of a cartridge filled with 5Å (10%) and 3Å (90%)
Type LINDE[12] molecular sieve[11] based on Zeolite manufactured by
ZEOCHEM[8];

  * •

The purifier-2 consisting of a cartridge filled with 50% Cu-Zn filter type R12
manufactured by BASF[9] and 50% Cu filter type R3-11G manufactured by BASF;

  * •

The purifier-3 consisting of a cartridge filled with Ni AlO3 filter type 6525
manufactured by LEUNA[10].

The experimental setup (Fig. 1) is composed of a CL system and an open mode
gas system. A detailed description of the CL, the experimental setup, and the
filters studied can be found in [7]. The CL is composed of mixer, purifiers
(in the subunit called “filters“ in the Fig. 1) , recirculation pump and
distribution to the RPC detectors. Eleven double-gap RPC detectors are
installed, nine in CL and two in open mode. Each RPC detector has two gaps
(upstream and downstream) whose gas lines are serially connected. The the gas
flows first in the upstream gap and then in the downstream gap. The detectors
are operated at a 9.2 kV power supply. The anode dark current drawn because of
the high bakelite resistivity is approximately 1-2 $\mu$A. Gas sampling points
before and after each filter in the closed loop allow gas sampling for
chemical and gaschromatograph analysis. The system is located in a temperature
and humidity controlled hut, with online monitoring of environmental
parameters.

Figure 1: Test setup with CL and open loop.

Chemical analyses have been performed in order to study the dynamical
behaviour of dark currents increase in the double-gap experimental setup and
correlate to the presence of contaminants, measure lifetime of unused
purifiers, and identify contaminant(s) in correlation with the increase of
currents. In the chemical analysis set-up (Fig. 2) the gas is sampled before
and after each CL purifier, and bubbled into a set of PVC flasks. The first
flask is empty and acts as a buffer, the second and third flasks contain 250
ml solution of LiOH (0.001 mole/l corresponding to 0.024 g/l, optimized to
keep the pH of the solution at 11). The bubbling of gas mixture into the two
flasks allows one to capture a wide range of elements that are likely to be
released by the system, such as Ca, Na, K, Cu, Zn, Cu, Ni, F. At the end of
each sampling line the flow is measured in order to have the total gas amount
for the whole period of sampling. Tygon filters ($0.45\mu$m) have been
installed upstream the flasks.

Figure 2: Chemical setup

The sampling points (Fig. 3) are located before the whole filters unit at
position HV61, after purifier-1 (Zeolite) at HV62, after purifier-2 (Cu/Zn
filter) at HV64 and after the Ni filter at position HV66. RPC are very
sensitive to environmental parameters (atmospheric pressure, humidity,
temperature), this study has been performed in environmentally controlled hut
with pressure, temperature and relative humidity online monitoring. The
comparison of temperature and humidity inside and outside the hut is displayed
in Fig. 4 and Fig. 5, respectively, over the whole time range of the test. The
inside temperature shows a variation of less than $\pm 0.5\,^{\circ}{\rm C}$;
the inside humidity still reveals seasonal structures between 35% and 50%, it
is, however, much smaller than the variation outside.

Gas mixture composition was monitored twice a day by gaschromatography, which
also provided the amount of air contamination, stable over the entire data
taking run and below 300 (100) ppm in closed (open) loop. Purifiers were
operated with unused filter material.

Figure 3: Chemical setup sampling points

Figure 4: Temperature distribution inside and outside the experimental hut.

Figure 5: Relative humidity inside and outside the experimental hut.

##  3 Results and discussion

The data-taking run was divided into cycles where different phenomena were
expected. We have four cycles (Fig. 6), i.e., initial stable currents (cycles
1 and 2), at the onset of the raise of currents (cycle 3), in the full
increase of currents (cycle 4). Cycle 4 was terminated in order not to damage
permanently the RPC detectors. The currents of all RPC detectors in open loop
were found stable over the four cycles. Fig. 6 shows the typical behaviour of
one RPC detector in CL. While the current of the downstream gap is stable
throughout the run, the current of the upstream gap starts increasing after
about seven months. Such behaviour is suggestive of the formation of
contaminants in the CL which are retained in the upstream gap, thus causing
its current to increase, and leaving the downstream gap undisturbed. While the
production of F- is constant during the run period, significant excess of K
and Ca is found in the gas mixture in cycles 3 and 4. The production of F- is
efficiently depressed by the zeolite purifier (Fig. 7). The observed excess of
K and Ca could be explained by a damaging effect of HF (continuously produced
by the system) on the zeolite filter whose structure contains such elements.
Further studies are in progress to confirm this model.

Figure 6: Dark currents increase in the upstream gap and not in the downstream
gap, correlated to the detection of contaminants in gas.

Figure 7: Concentration of F- in gas as measured by the chemical setup.
Sampling point HV61 is before the zeolite purifier, the others after each
purifier.

##  4 Conclusions

Preliminary results show that the lifetime of purifiers using unused material
is approximately seven months. Contaminants (K, Ca) are released in the gas in
correlation with the dark currents increase. The currents increase is observed
only in the upstream gap. The study suggests that contaminants produced in the
system stop in the upstream gap and affect its noise behaviour, leaving the
downstream gap undisturbed. The presence of an excess production of K and Ca
in coincidence with the currents increase suggests a damaging effect of HF
produced in the system on the framework of zeolites which is based on K and
Ca. Further studies are in progress to fully characterize the system over the
four cycles from the physical and the chemical point of view. The main goal is
to better schedule the operation and maintenance of filters for the CMS
experiment, where for a safe and reliable operation the filter regeneration is
presently performed several times per week. A second run is being started with
regenerated filter materials to measure their lifetime and confirm the
observation of contaminants. Finally, studies in high-radiation environment at
the CERN gamma irradiation facility are being planned.

Acknowledgements

The technical support of the CERN gas group is gratefully acknowledged. Thanks
are due to F. Hahn for discussions, and to Nadeesha M. Wickramage, Yasser
Assran for help in data taking shifts. This research was supported in part by
the Italian Istituto Nazionale di Fisica Nucleare and Ministero dell’
Istruzione, Università e Ricerca.

## References

  * [1] R. Santonico and R. Cardarelli, “Development Of Resistive Plate Counters,” Nucl. Instrum. Meth. 187 (1981) 377.
  * [2] CMS Collaboration, “The CMS experiment at the CERN LHC”, JINST 3 (2008) S08004.
  * [3] M. Bosteels et al., “CMS Gas System Proposal”, CMS Note 1999/018.
  * [4] L. Besset et al., “Experimental Tests with a Standard Closed Loop Gas Circulation System”, CMS Note 2000/040.
  * [5] M. Abbrescia et al., “Proposal for a Systematic Study of the CERN Closed Loop Gas System Used by the RPC Muon Detectors in CMS”, Frascati preprint LNF-06/27(IR), available at http://www.lnf.infn.it/sis/preprint/ .
  * [6] G. Saviano et al., “Materials studies for the RPC detector in CMS ”, presented at the RPC07 Conference, Mumbai (India), January 2008.
  * [7] S.Bianco et al., “Chemical analyses of materials used in the CMS RPC muon detector”, CMS NOTE 2010/006.
  * [8] Manufactured by ZEOCHEM, 8708 Uetikon (Switzerland).
  * [9] BASF Technical Bulletin.
  * [10] LEUNA Data Sheet September 9, 2003, Catalyst KL6526-T.
  * [11] GRACE Davison Molecular Sieves data sheet.
  * [12] LINDE Technical Bullettin.
  * [13] L. Benussi et al., “Sensitivity and environmental response of the CMS RPC gas gain monitoring system,” JINST 4 (2009) DOI:10.1088 1748-0221 4 08 P08006 [arXiv:0812.1710 [physics.ins-det]].
  * [14] M. Abbrescia et al., “HF Production In Cms-Resistive Plate Chambers,” Nucl. Phys. Proc. Suppl. 158 (2006) 30. NUPHZ,158,30;
  * [15] G. Aielli et al., “Fluoride production in RPCs operated with F-compound gases”, 8th Workshop on Resistive Plate Chambers and Related Detectors, Seoul, Korea, 10-12 Oct 2005. Published in Nucl.Phys.Proc.Suppl. 158 (2006) 143.


2023 046 20 March

Measurement of angle between jet axes in $\sqrt{s_{\mathrm{NN}}}=5.02$ TeV
Pb–Pb collisions

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

This letter presents the first measurement of the angle between different jet
axes (denoted as $\Delta R_{\mathrm{axis}}$) in Pb–Pb collisions. The
measurement is carried out in the 0$\textendash$10% most-central events at
$\sqrt{s_{\mathrm{NN}}}=5.02$ TeV. Jets are assembled by clustering charged
particles at midrapidity using the $\mathrm{anti\mathchar
45\relax}k_{\mathrm{T}}$ algorithm with resolution parameters $R=0.2$ and
$0.4$ and transverse momenta in the intervals
$40<p_{\mathrm{T}}^{\mathrm{ch\;jet}}<140\
\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ and
$80<p_{\mathrm{T}}^{\mathrm{ch\;jet}}<140\
\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$, respectively. Measurements at
these low transverse momenta enhance the sensitivity to
quark$\textendash$gluon plasma (QGP) effects. A comparison to models
implementing various mechanisms of jet energy loss in the QGP shows that the
observed narrowing of the Pb–Pb distribution relative to pp can be explained
if quark-initiated jets are more likely to emerge from the medium than gluon-
initiated jets. These new measurements discard intra-jet $p_{\mathrm{T}}$
broadening as described in a model calculation with the BDMPS formalism as the
main mechanism of energy loss in the QGP. The data are sensitive to the
angular scale at which the QGP can resolve two independent splittings,
favoring mechanisms that incorporate incoherent energy loss.

The strongly interacting, deconfined state of matter of our universe a few
microseconds after the Big Bang can be recreated in ultrarelativistic heavy-
ion collisions at the Large Hadron Collider (LHC) [1, 2]. Studying the
microscopic structure of this quark$\textendash$gluon plasma (QGP) can
elucidate the physics of many-body strongly coupled systems [3]. Because
droplets of QGP created at colliders are small and short-lived, studying
interactions within those droplets requires auto-generated probes. In this
study, jets of energetic hadrons, which arise from high-momentum-transfer
(hard) collisions between quarks and gluons (partons) in the incoming nuclei,
are used. These hard-scattered particles produce showers of secondary partons,
which give rise to jets of multiple correlated hadrons (see Fig. 1, left).

Figure 1: Left: schematic of how energetic partons split or fragment into
lower-energy prongs or branches of partons down to a scale in which hadrons
emerge. An algorithm can be run over final-state hadrons to cluster them into
jets. An inverse declustering algorithm can be used to recursively explore the
jet substructure. Right: schematic showing that different jet axes (solid
arrows) can be selected from a jet to construct the $\Delta R_{\mathrm{axis}}$
observable. The Standard axis (represented by a black arrow) is constrained by
all the jet constituents (represented by dashed arrows). The SD axis
(represented by a dark blue arrow) is determined by the particles left in the
jet after grooming (blue and dark red arrows). Finally, the WTA axis
(represented by a pink arrow) tends to be aligned with the most energetic
constituent.

When traversing the QGP, jets interact with the medium, lose energy, and are
modified relative to their structure in elementary (e.g., ee or pp)
collisions. Thus, measuring the substructure of jets can provide sensitivity
to different scales within the jet modification process. The direction of a
jet in rapidity ($y$) and azimuth ($\varphi$), referred to as the jet axis, is
affected by transverse modification of the partonic shower, with varying
sensitivity to soft radiation, depending on how the axis is defined [4].

This letter presents the first measurement in heavy-ion collisions of the
angle between pairs of jet axes, $\Delta R_{\mathrm{axis}}$ (see Fig. 1,
right). This observable shows how well the QGP resolves the angular structure
of the parton shower [4] and is defined as

$\Delta R_{\rm axis}\equiv\sqrt{(y_{\rm axis,\,1}-y_{\rm
axis,\,2})^{2}+(\varphi_{\rm axis,\,1}-\varphi_{\rm axis,\,2})^{2}},$ (1)

where $y_{{\rm axis},\,i}$ and $\varphi_{{\rm axis},\,i}$ are the rapidity and
azimuthal coordinates of the axes, respectively. The axes considered in this
analysis are:

  * •

“Standard”: coordinates in $y\textendash\varphi$ of the 4-vector resulting
from clustering jets with the $\mathrm{anti\mathchar 45\relax}k_{\mathrm{T}}$
algorithm [5] using the $E$ recombination scheme (two branches combined into
one by adding their 4-momenta). In this case, all jet constituents including
soft (low-transverse-momentum) and hard radiation contribute to the axis.

  * •

“Soft Drop” (SD): coordinates in $y\textendash\varphi$ of jet after soft wide-
angle radiation is removed using the Soft Drop grooming procedure [6] with the
Cambridge$\textendash$Aachen (C/A) reclustering algorithm [7, 8]. The
procedure stops when a splitting is found that satisfies the condition

$\frac{\mathrm{min}(p_{\rm T,1},p_{\rm T,2})}{p_{\rm T,1}+p_{\rm
T,2}}>z_{\mathrm{cut}}\left(\frac{\Delta R_{1,2}}{R}\right)^{\beta},$ (2)

where $p_{{\rm T},i}$ are the transverse momenta of each of the two branches
in the splitting, $\Delta R_{1,2}$ is the distance between them in the
$y\textendash\varphi$ plane, $R$ is the jet resolution parameter, and
$z_{\mathrm{cut}}$ and $\beta$ are user-set parameters.

  * •

“Winner-Takes-All” (WTA): coordinates in $y\textendash\varphi$ of jet after
reclustering its constituents using the C/A algorithm and the WTA
$p_{\mathrm{T}}$ recombination scheme [9], which combines two jet branches
into one by giving the merged branch the total $p_{\mathrm{T}}$ of the two
sub-branches and the direction of the hardest sub-branch. The WTA axis is
often consistent with the direction of the hardest constituent of the jet and
is insensitive to soft radiation at the leading power of the observable [4].

Measurements of $\Delta R_{\mathrm{axis}}$ are sensitive to medium-induced
effects. For example, an increase in the relative fraction of quark- vs.
gluon-initiated jets due to medium-induced radiative energy loss can narrow
the angular distribution, while multiple scattering of the hard-scattered
parton off medium partons can broaden it [10]. Reference 11 reported a net
narrowing of the distribution in Pb–Pb collisions, quantitatively consistent
with the former. This can be expected if the broadening was primarily in the
wide-angle radiation that grooming removes from the jet. This is tested by
looking for broadening effects in an ungroomed angular observable, such as the
angle between the Standard and WTA axes.

Measurements of $\Delta R_{\mathrm{axis}}$ are also sensitive to the wake
created by a jet imparting some of its momentum to the QGP. This wake is often
referred to as medium response [12] and is expected to dominate at large
angles from the Standard axis. Consequently, progressively increasing the
grooming intensity, while simultaneously varying the jet resolution parameter
$R$ can uncover the medium response effect. Comparing experimental results
with different models is expected to disentangle medium response and medium-
induced large-angle radiation.

The medium resolution length, $L_{\rm res}$, is a property of the QGP
proportional to the inverse of its local temperature [13]. It characterizes
the minimum separation distance at which two color charges within the same jet
interact independently with the QGP. Certain groomed substructure observables
are sensitive to this scale [14]. In this analysis, the sensitivity of $\Delta
R_{\mathrm{axis}}$ to $L_{\rm res}$ is investigated.

The measured $\Delta R_{\mathrm{axis}}$ distributions in pp collisions at
$\sqrt{s}=5.02\ {\rm TeV}$ reported in Ref. 15 are used as the reference for
QGP-induced effects reported here. Perturbative QCD calculations [4] were
found to agree with the measurements in pp collisions within the experimental
uncertainties, demonstrating good theoretical control of the observables. The
data were collected in 2018 from Pb–Pb collisions at a center-of-mass energy
per nucleon$\textendash$nucleon pair of $\sqrt{s_{\mathrm{NN}}}=5.02$ TeV with
the ALICE detector [2]. A detailed description of the detector and its
performance can be found in Refs. 16 and 17. A trigger based on the charged-
particle multiplicity in the forward region [18] was used to select events in
the 0$\textendash$10% centrality class [19, 20]. The events were required to
have a reconstructed primary vertex within $\pm 10$ cm of the nominal
interaction point in the longitudinal direction. Beam-induced background
events were removed using two Zero Degree Calorimeters and pileup effects were
removed by discarding events that contained multiple reconstructed vertices
[21]. These selection criteria yield a data sample with 92 million events,
corresponding to an integrated luminosity of $\approx 0.12\ {\rm nb}^{-1}$.

Charged-particle tracks reconstructed in the Inner Tracking System (ITS) [22]
and Time Projection Chamber (TPC) [23] used in the analysis were required to
have a transverse momentum $p_{\mathrm{T}}>0.15\
\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ and a pseudorapidity
$|\eta|<0.9$. See the supplemental materials [24] for details. The detector
performance was estimated by propagating simulated events through a GEANT 3
[25] model of the ALICE detector. The transverse-momentum resolution
$\sigma(p_{\mathrm{T}})/p_{\mathrm{T}}$ increases linearly from $\approx 1\%$
at $p_{\mathrm{T}}=1\ \mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ to
$\approx 4\%$ at $p_{\mathrm{T}}=50\
\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ [17]. The tracking efficiency
rapidly increases from $\approx 65\%$ at $p_{\mathrm{T}}=0.15\
\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ to $\approx 85\%$ at
$p_{\mathrm{T}}=1\ \mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$, and remains
above $\approx 75\%$ at higher $p_{\mathrm{T}}$. The large uncorrelated
background from the underlying event (UE) [26] in high-multiplicity heavy-ion
collisions is subtracted before jet finding using the event-wide constituent
subtraction procedure from Refs. 27 and 28. The parameters used are
$\alpha=0$, $A_{\rm g}=0.01$, and $\Delta R^{\rm max}=0.1$ (0.25) when the
track sample is used to cluster jets of $R=0.2$ (0.4).

Tracks included in jet clustering are assigned the charged-pion mass. Charged-
particle jets are clustered with the $\mathrm{anti\mathchar
45\relax}k_{\mathrm{T}}$ algorithm, the $E$ recombination scheme, and
resolution parameters $R=0.2$ and 0.4, using FastJet [29]. Jets containing a
track with $p_{\mathrm{T}}>100\ \mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$
and jets with their Standard axis not pointing inside the fiducial volume of
the TPC ($|\eta_{\mathrm{jet}}|<0.9-R$) are discarded.

The measured distributions are unfolded to correct for detector effects as
well as residual UE fluctuations using an iterative Bayesian procedure [30,
31]. The procedure uses a 4D response matrix (RM) that captures the
correspondence between $\Delta R_{\mathrm{axis}}$ and jet transverse momentum
($p_{\mathrm{T}}^{\mathrm{ch\;jet}}$) at the generator and detector levels.
The generator-level component of the RM is modeled using generated PYTHIA 8
[32] Monash 2013 [33] events. The detector-level component of the RM is
modeled by propagating those events through a GEANT 3 [25] model of the ALICE
detector and embedding the smeared events into measured Pb–Pb events.

Systematic uncertainties arise from the tracking inefficiency, unfolding
procedure, unfolding model dependence, UE subtraction procedure, and residual
effects from combinatorial jets. The tracking-inefficiency uncertainty is
determined by repeating the analysis with an RM based on a track sample with
4% of all tracks randomly rejected. This number corresponds to the uncertainty
in the tracking efficiency, determined by varying the track selection
parameters and ITS$\textendash$TPC matching criteria.

The unfolding-procedure uncertainty is determined by extending the lower and
upper bounds of the $p_{\mathrm{T}}^{\mathrm{ch\;jet}}$ spectrum by 5
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$, changing the detector-level
$\Delta R_{\mathrm{axis}}$ binning, changing the number of unfolding
iterations, and scaling the prior distribution. The four categories of
variations are carried out individually and combined into an unfolding
uncertainty using their standard deviation. The uncertainty from the model
dependence in the unfolding is determined by repeating the analysis with
response matrices based on different event generators including Herwig 7 [34]
and JEWEL [35] with and without the inclusion of medium partons recoiling
after interactions with the jet.

Potential bias introduced by the event-wide UE subtraction [27, 28] is
quantified as the maximum difference between the nominal result and the
results obtained by repeating the procedure with parameters $\Delta R^{\rm
max}=0.05$ (0.1), which lead to an under-subtraction, and $\Delta R^{\rm
max}=0.5$ (0.7), which lead to an over-subtraction of the background, for jets
of $R=0.2$ (0.4). Deviations between the generator-level and unfolded
distributions due to residual combinatorial jets are determined with a closure
test. PYTHIA 8 events are embedded into background events with no jets and
analyzed identically to the measured data. Deviations between the unfolded and
PYTHIA 8 generator-level spectra are assigned as the uncertainty.

The systematic uncertainties are added in quadrature. The total systematic
uncertainty is in the range of 2–61% depending on $\Delta R_{\mathrm{axis}}$
and $p_{\mathrm{T}}^{\mathrm{ch\;jet}}$. The large variation comes primarily
from the background subtraction procedure at low
$p_{\mathrm{T}}^{\mathrm{ch\;jet}}$ (where background effects are largest). It
is small at low values of $\Delta R_{\mathrm{axis}}$, and smoothly grows in
the tails of the distributions. See the supplemental materials [24] for
details. The measured distributions are normalized to the total number of jets
in a given $p_{\mathrm{T}}^{\mathrm{ch\;jet}}$ interval, $N$, which is
equivalent to reporting the self-normalized cross section:

$\frac{1}{N(p_{\mathrm{T}}^{\mathrm{ch\;jet}})}\frac{{\rm d}N}{{\rm d}\Delta
R_{\mathrm{axis}}}\left(p_{\mathrm{T}}^{\mathrm{ch\;jet}}\right)\equiv\frac{1}{\sigma(p_{\mathrm{T}}^{\mathrm{ch\;jet}})}\frac{{\rm
d}\sigma}{{\rm d}\Delta
R_{\mathrm{axis}}}\left(p_{\mathrm{T}}^{\mathrm{ch\;jet}}\right).$ (3)

This normalization choice causes the Pb–Pb/pp ratios to go above unity at low
$\Delta R_{\mathrm{axis}}$. In an absolute cross section measurement, the
ratio would be below unity as a result of jet suppression in heavy-ion
collisions. The suppression factor was measured in Ref. 36. Thus, only the
shape and not the absolute scale of the $\Delta R_{\mathrm{axis}}$ spectra is
reported.

Figure 2: Top panels: fully corrected Pb–Pb and pp $\Delta
R_{\mathrm{axis}}^{\rm WTA-Standard}$ distributions in the
$p_{\mathrm{T}}^{\mathrm{ch\;jet}}$ intervals $[40,60]$ (left), and $[60,80]$
(right) $\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ for jets of $R=0.2$.
The pp baseline is taken from Ref. 15. Central and bottom panels: measured
Pb–Pb/pp ratio in black, as well as predictions from a selection of jet
quenching models.

The measured WTA$\textendash$Standard distributions are shown in Fig. 2 for
$R=0.2$ jets in the $p_{\mathrm{T}}^{\mathrm{ch\;jet}}$ ranges $[40,60]$ and
$[60,80]$ $\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$. The top panels show
$\Delta R_{\mathrm{axis}}$ spectra from Pb–Pb and pp collisions. The vertical
error bars represent the statistical uncertainties and the rectangles
represent the total systematic uncertainties. The central and bottom panels
show the Pb–Pb/pp ratio, with all uncertainties assumed uncorrelated and added
in quadrature when calculating the ratio. The equivalent results for other
$p_{\mathrm{T}}^{\mathrm{ch\;jet}}$ ranges, jet resolution parameters, and
grooming settings are included in the supplemental materials [24].

The data are compared with several jet quenching models. These models have
different implementations of the microscopic properties of the medium, its
evolution, and the jet–medium interaction. The JEWEL event generator [35]
models the medium with a boost-invariant longitudinally expanding ideal
quark$\textendash$gluon gas [37]. Parameters from Ref. 38, which are adequate
for the kinematics of this measurement, are used. The medium partons recoiling
after interacting with jet constituents can be discarded from the event
(recoils off) or allowed to hadronize together with the jet (recoils on).
“MATTER+LBT” is from the JETSCAPE event generator [39, 40], implementing an
in-medium parton shower with interactions of high- (low-) virtuality partons
with the medium described by the MATTER [41] (Linear Boltzmann Transport [42])
model. The curve labeled “medium q/g” corresponds to a phenomenological model
in which the only difference between the Pb–Pb and pp results comes from a
modification of the fraction of quarks and gluons that initiate the jets [43,
44], highlighting that these two jet populations lose energy differently in
the medium. The “$\bm{p_{\rm T}}$ broadening” calculation adds to the previous
model a $p_{\mathrm{T}}$ broadening caused by incoherent multiple scatterings
with the medium partons [10] following the BDMPS approach [45, 46, 47]. This
calculation uses a mean square momentum transfer coefficient between the jet
and medium constituents $\langle\hat{q}L\rangle=5$ GeV2. “Hybrid” is from the
hybrid model [48], which describes the weakly coupled jet showering process
using the DGLAP formalism and the strongly coupled interaction between the jet
constituents and medium partons via holographic calculations of energy loss
based on AdS/CFT. The case $L_{\rm res}=0$ corresponds to fully incoherent
energy loss, where the medium is able to resolve the splitting immediately
after the parton fragments, resulting in higher energy loss [13]. The case
$L_{\rm res}=\infty$ corresponds to fully coherent energy loss, where the
medium is not able to resolve splittings, and the energy loss is lower. The
intermediate case $L_{\rm res}=2/\uppi T$, where $T$ is the medium local
temperature, is also included. All “Hybrid” curves include medium-response
effects from Ref. 49.

The measured $R=0.2$ distributions are narrower than those measured in pp
collisions. Results with $R=0.4$, presented in the supplemental materials
[24], are consistent with this narrowing, but also with no modification within
statistical and systematic uncertainties. The narrowing may be due to a
selection bias, as jets selected using $p_{\mathrm{T}}^{\mathrm{ch\;jet}}$
(rather than the initial momentum before the jet-medium interactions, which is
not accessible experimentally) tend to lose little energy in the QGP [50].
Similarly, the experimental result is also consistent with a quark-enhanced
mixture of jets surviving the interaction with the medium relative to the
vacuum case, as expected since gluon-initiated jets couple more strongly to
partons of the QGP and thus lose more energy [43, 51, 11]. The MATTER+LBT
model overall describes the data for all considered kinematical regions.

In contrast with $R=0.2$, for larger $R$ there are significant differences in
JEWEL predictions with and without recoils. This is expected, as the medium
response populates larger angles away from the Standard jet axis. However,
grooming reduces the sensitivity to the medium response. The Hybrid model does
not predict a significant effect from the medium response. See the
supplemental materials [24] for details. The inclusion of other models in
which the medium response can be turned on and off (e.g. Co-LBT [52, 53])
could help clarify the sensitivity of $\Delta R_{\mathrm{axis}}$ to the
properties and magnitude of this effect. Narrowing of the distributions
relative to those measured in pp collisions for jets of $R=0.2$ is
qualitatively predicted by all models except for “$p_{\rm T}$ broadening”.
This excludes the hypothesis that intra-jet $p_{\mathrm{T}}$ broadening
manifests in the groomed radiation in previous measurements [11].

The data are closest to incoherent energy loss of jets in the Hybrid model
($L_{\rm res}=0$). The fully coherent case ($L_{\rm res}=\infty$) predicts
significantly less narrowing. Fully incoherent energy loss better reproduces
the data than the intermediate case of $L_{\rm res}=2/\uppi T$. In holographic
calculations of the Debye screening length, the intermediate case is expected
to be closer to the true medium resolution scale [13].

Figure 3: Top panels: fully corrected Pb–Pb $\Delta R_{\mathrm{axis}}^{\rm
WTA-Standard}/R$ (left), and $\Delta R_{\mathrm{axis}}^{\rm WTA-SD}/R$ with
$(z_{\mathrm{cut}}=0.2,\beta=0)$ (right) distributions in the
$p_{\mathrm{T}}^{\mathrm{ch\;jet}}$ interval $[100,140]$
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$. Central and bottom panels:
measured $\mbox{Pb--Pb}(R=0.4)/\mbox{Pb--Pb}(R=0.2)$ ratio in black, as well
as predictions from a selection of jet quenching models.

The precision of the data at higher $p_{\mathrm{T}}^{\mathrm{ch\;jet}}$ is
limited by the integrated luminosity of the pp dataset, which only allows for
an extraction of the Pb–Pb/pp results up to 100
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$. However, in heavy-ion
collisions, larger $p_{\mathrm{T}}^{\mathrm{ch\;jet}}$ can be studied through
the ratio of $(R=0.4)/(R=0.2)$ spectra, where the systematic uncertainties
partially cancel. This kinematic range is also important for future
comparisons with results from other experiments which cannot access the
low-$p_{\mathrm{T}}$ regime of this measurement. The ratio is reported as a
function of the jet angular scale $\Delta R_{\mathrm{axis}}/R$ that, by
construction, is independent of $R$. Figure 3 shows the ratio for
$p_{\mathrm{T}}^{\mathrm{ch\;jet}}\in[100,140]$
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ together with theoretical
predictions. The ungroomed WTA$\textendash$Standard result is challenging to
models, as can be seen in Fig. 3 (left). Grooming improves the agreement
between the models and the data (see Fig. 3 (right)), suggesting that the
ungroomed result captures significantly more of the non-perturbative aspects
of jet quenching.

Comparing $\Delta R_{\mathrm{axis}}^{\rm WTA-Standard}$ to $\Delta
R_{\mathrm{axis}}^{\rm WTA-SD}$ with different grooming settings shows that
grooming does not significantly impact the experimental results. This is
similar to pp collisions, where the Standard and SD axes were found more
aligned with each other than either of them with the WTA axis. While the
Standard axis is influenced by the soft wide-angle radiation groomed away in
the SD-axis case, it is dominated by the hard radiation that remains in the SD
case.

In summary, the first measurement of the angle between the WTA and Standard or
Soft Drop groomed charged-particle jet axes in Pb–Pb collisions is reported.
The measurement was carried out using 0$\textendash$10% most-central
collisions at $\sqrt{s_{\mathrm{NN}}}=5.02$ TeV with the ALICE detector and
for $p_{\mathrm{T}}^{\mathrm{ch\;jet}}\in[40,140]$ ([80,140])
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ for jets of $R=0.2$ ($0.4$).

Narrowing of the $\Delta R_{\mathrm{axis}}$ distribution relative to the
vacuum case is found. The narrowing may be explained if the Pb–Pb distribution
is dominated by quark-initiated jets, since gluon-initiated jets are expected
to interact more with the medium. This is consistent with the prediction from
the “medium q/g” model. The measurement disfavors intra-jet $p_{\mathrm{T}}$
broadening, as implemented in Ref. 10.

The $\Delta R_{\mathrm{axis}}$ observables exhibit sensitivity to the medium
resolution length. The measurement favors incoherent energy loss of jets,
where the medium resolves a splitting immediately after it happens, regardless
of the angular separation between the prongs. Future measurements of $\Delta
R_{\mathrm{axis}}$ in photon- or Z-boson-tagged jets could provide a way to
experimentally vary the fraction of quark- vs. gluon-initiated jets.

## Acknowledgements

We gratefully acknowledge Felix Ringer, Daniel Pablos, and the JETSCAPE
collaboration for providing theoretical predictions. We also acknowledge Xin-
Nian Wang and Feng Yuan for fruitful discussions.

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

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##  Appendix A The ALICE Collaboration

S. Acharya 125, D. Adamová 86, A. Adler69, G. Aglieri Rinella 32, M. Agnello
29, N. Agrawal 50, Z. Ahammed 132, S. Ahmad 15, S.U. Ahn 70, I. Ahuja 37, A.
Akindinov 140, M. Al-Turany 97, D. Aleksandrov 140, B. Alessandro 55, H.M.
Alfanda 6, R. Alfaro Molina 66, B. Ali 15, A. Alici 25, N. Alizadehvandchali
114, A. Alkin 32, J. Alme 20, G. Alocco 51, T. Alt 63, I. Altsybeev 140, M.N.
Anaam 6, C. Andrei 45, A. Andronic 135, V. Anguelov94, F. Antinori 53, P.
Antonioli 50, N. Apadula 74, L. Aphecetche 103, H. Appelshäuser 63, C. Arata
73, S. Arcelli 25, M. Aresti 51, R. Arnaldi 55, J.G.M.C.A. Arneiro 110, I.C.
Arsene 19, M. Arslandok 137, A. Augustinus 32, R. Averbeck 97, M.D. Azmi 15,
A. Badalà 52, J. Bae 104, Y.W. Baek 40, X. Bai 118, R. Bailhache 63, Y.
Bailung 47, A. Balbino 29, A. Baldisseri 128, B. Balis 2, D. Banerjee 4, Z.
Banoo 91, R. Barbera 26, F. Barile 31, L. Barioglio 95, M. Barlou78, G.G.
Barnaföldi 136, L.S. Barnby 85, V. Barret 125, L. Barreto 110, C. Bartels 117,
K. Barth 32, E. Bartsch 63, N. Bastid 125, S. Basu 75, G. Batigne 103, D.
Battistini 95, B. Batyunya 141, D. Bauri46, J.L. Bazo Alba 101, I.G. Bearden
83, C. Beattie 137, P. Becht 97, D. Behera 47, I. Belikov 127, A.D.C. Bell
Hechavarria 135, F. Bellini 25, R. Bellwied 114, S. Belokurova 140, G. Bencedi
136, S. Beole 24, A. Bercuci 45, Y. Berdnikov 140, A. Berdnikova 94, L.
Bergmann 94, M.G. Besoiu 62, L. Betev 32, P.P. Bhaduri 132, A. Bhasin 91, M.A.
Bhat 4, B. Bhattacharjee 41, L. Bianchi 24, N. Bianchi 48, J. Bielčík 35, J.
Bielčíková 86, J. Biernat 107, A.P. Bigot 127, A. Bilandzic 95, G. Biro 136,
S. Biswas 4, N. Bize 103, J.T. Blair 108, D. Blau 140, M.B. Blidaru 97, N.
Bluhme38, C. Blume 63, G. Boca 21,54, F. Bock 87, T. Bodova 20, A.
Bogdanov140, S. Boi 22, J. Bok 57, L. Boldizsár 136, M. Bombara 37, P.M. Bond
32, G. Bonomi 131,54, H. Borel 128, A. Borissov 140, H. Bossi 137, E. Botta
24, Y.E.M. Bouziani 63, L. Bratrud 63, P. Braun-Munzinger 97, M. Bregant 110,
M. Broz 35, G.E. Bruno 96,31, M.D. Buckland 23, D. Budnikov140, H. Buesching
63, S. Bufalino 29, P. Buhler 102, Z. Buthelezi 67,121, A. Bylinkin 20, S.A.
Bysiak107, M. Cai 6, H. Caines 137, A. Caliva 28, E. Calvo Villar 101, J.M.M.
Camacho 109, P. Camerini 23, F.D.M. Canedo 110, M. Carabas 124, A.A. Carballo
32, A.G.B. Carcamo 94, F. Carnesecchi 32, R. Caron 126, L.A.D. Carvalho 110,
J. Castillo Castellanos 128, F. Catalano 32,24, C. Ceballos Sanchez 141, I.
Chakaberia 74, P. Chakraborty 46, S. Chandra 132, S. Chapeland 32, M. Chartier
117, S. Chattopadhyay 132, S. Chattopadhyay 99, T.G. Chavez 44, T. Cheng 97,6,
C. Cheshkov 126, B. Cheynis 126, V. Chibante Barroso 32, D.D. Chinellato 111,
E.S. Chizzali 95, J. Cho 57, S. Cho 57, P. Chochula 32, P. Christakoglou 84,
C.H. Christensen 83, P. Christiansen 75, T. Chujo 123, M. Ciacco 29, C. Cicalo
51, F. Cindolo 50, M.R. Ciupek97, G. ClaiII,50, F. Colamaria 49, J.S.
Colburn100, D. Colella 96,31, M. Colocci 25, G. Conesa Balbastre 73, Z. Conesa
del Valle 72, G. Contin 23, J.G. Contreras 35, M.L. Coquet 128, T.M.
CormierI,87, P. Cortese 130,55, M.R. Cosentino 112, F. Costa 32, S. Costanza
21,54, C. Cot 72, J. Crkovská 94, P. Crochet 125, R. Cruz-Torres 74, P. Cui 6,
A. Dainese 53, M.C. Danisch 94, A. Danu 62, P. Das 80, P. Das 4, S. Das 4,
A.R. Dash 135, S. Dash 46, A. De Caro 28, G. de Cataldo 49, J. de Cuveland38,
A. De Falco 22, D. De Gruttola 28, N. De Marco 55, C. De Martin 23, S. De
Pasquale 28, R. Deb131, S. Deb 47, K.R. Deja133, R. Del Grande 95, L. Dello
Stritto 28, W. Deng 6, P. Dhankher 18, D. Di Bari 31, A. Di Mauro 32, B. Diab
128, R.A. Diaz 141,7, T. Dietel 113, Y. Ding 6, R. Divià 32, D.U. Dixit 18, Ø.
Djuvsland20, U. Dmitrieva 140, A. Dobrin 62, B. Dönigus 63, J.M. Dubinski133,
A. Dubla 97, S. Dudi 90, P. Dupieux 125, M. Durkac106, N. Dzalaiova12, T.M.
Eder 135, R.J. Ehlers 74, F. Eisenhut 63, D. Elia 49, B. Erazmus 103, F.
Ercolessi 25, F. Erhardt 89, M.R. Ersdal20, B. Espagnon 72, G. Eulisse 32, D.
Evans 100, S. Evdokimov 140, L. Fabbietti 95, M. Faggin 27, J. Faivre 73, F.
Fan6, W. Fan 74, A. Fantoni 48, M. Fasel 87, P. Fecchio29, A. Feliciello 55,
G. Feofilov 140, A. Fernández Téllez 44, L. Ferrandi 110, M.B. Ferrer 32, A.
Ferrero 128, C. Ferrero 55, A. Ferretti 24, V.J.G. Feuillard 94, V. Filova35,
D. Finogeev 140, F.M. Fionda 51, F. Flor 114, A.N. Flores 108, S. Foertsch 67,
I. Fokin 94, S. Fokin 140, E. Fragiacomo 56, E. Frajna 136, U. Fuchs 32, N.
Funicello 28, C. Furget73, A. Furs 140, T. Fusayasu 98, J.J. Gaardhøje 83, M.
Gagliardi 24, A.M. Gago 101, C.D. Galvan 109, D.R. Gangadharan 114, P. Ganoti
78, C. Garabatos 97, J.R.A. Garcia44, E. Garcia-Solis 9, C. Gargiulo 32, A.
Garibli81, K. Garner135, P. Gasik 97, A. Gautam 116, M.B. Gay Ducati 65, M.
Germain 103, A. Ghimouz123, C. Ghosh132, M. Giacalone 50,25, P. Giubellino
97,55, P. Giubilato 27, A.M.C. Glaenzer 128, P. Glässel 94, E. Glimos120,
D.J.Q. Goh76, V. Gonzalez 134, S. Gorbunov38, M. Gorgon 2, K. Goswami 47, S.
Gotovac33, V. Grabski 66, L.K. Graczykowski 133, E. Grecka 86, A. Grelli 58,
C. Grigoras 32, V. Grigoriev140, S. Grigoryan 141,1, F. Grosa 32, J.F. Grosse-
Oetringhaus 32, R. Grosso 97, D. Grund 35, G.G. Guardiano 111, R. Guernane 73,
M. Guilbaud 103, K. Gulbrandsen 83, T. Gundem 63, T. Gunji 122, W. Guo 6, A.
Gupta 91, R. Gupta 91, R. Gupta 47, S.P. Guzman44, K. Gwizdziel 133, L. Gyulai
136, M.K. Habib97, C. Hadjidakis 72, F.U. Haider 91, H. Hamagaki 76, A. Hamdi
74, M. Hamid6, Y. Han 138, B.G. Hanley 134, R. Hannigan 108, J. Hansen 75,
M.R. Haque 133, J.W. Harris 137, A. Harton 9, H. Hassan 87, D. Hatzifotiadou
50, P. Hauer 42, L.B. Havener 137, S.T. Heckel 95, E. Hellbär 97, H. Helstrup
34, M. Hemmer 63, T. Herman 35, G. Herrera Corral 8, F. Herrmann135, S.
Herrmann 126, K.F. Hetland 34, B. Heybeck 63, H. Hillemanns 32, B. Hippolyte
127, F.W. Hoffmann 69, B. Hofman 58, B. Hohlweger 84, G.H. Hong 138, M. Horst
95, A. Horzyk 2, Y. Hou6, P. Hristov 32, C. Hughes 120, P. Huhn63, L.M. Huhta
115, T.J. Humanic 88, L.A. Husova 135, A. Hutson 114, R. Ilkaev140, H. Ilyas
13, M. Inaba 123, G.M. Innocenti 32, M. Ippolitov 140, A. Isakov 86, T.
Isidori 116, M.S. Islam 99, M. Ivanov12, M. Ivanov97, V. Ivanov 140, K.E.
Iversen 75, M. Jablonski 2, B. Jacak74, N. Jacazio 25, P.M. Jacobs 74, S.
Jadlovska106, J. Jadlovsky106, S. Jaelani 82, C. Jahnke111, M.J. Jakubowska
133, M.A. Janik 133, T. Janson69, M. Jercic89, S. Ji 16, S. Jia10, A.A.P.
Jimenez 64, F. Jonas 87, J.M. Jowett 32,97, J. Jung 63, M. Jung 63, A. Junique
32, A. Jusko 100, M.J. Kabus 32,133, J. Kaewjai105, P. Kalinak 59, A.S.
Kalteyer 97, A. Kalweit 32, V. Kaplin 140, A. Karasu Uysal 71, D. Karatovic
89, O. Karavichev 140, T. Karavicheva 140, P. Karczmarczyk 133, E. Karpechev
140, U. Kebschull 69, R. Keidel 139, D.L.D. Keijdener58, M. Keil 32, B. Ketzer
42, S.S. Khade 47, A.M. Khan 6, S. Khan 15, A. Khanzadeev 140, Y. Kharlov 140,
A. Khatun 116, A. Khuntia 107, M.B. Kidson113, B. Kileng 34, B. Kim 104, C.
Kim 16, D.J. Kim 115, E.J. Kim 68, J. Kim 138, J.S. Kim 40, J. Kim 57, J. Kim
68, M. Kim 18, S. Kim 17, T. Kim 138, K. Kimura 92, S. Kirsch 63, I. Kisel 38,
S. Kiselev 140, A. Kisiel133, J.P. Kitowski 2, J.L. Klay 5, J. Klein 32, S.
Klein 74, C. Klein-Bösing 135, M. Kleiner 63, T. Klemenz 95, A. Kluge 32, A.G.
Knospe 114, C. Kobdaj 105, T. Kollegger97, A. Kondratyev 141, N. Kondratyeva
140, E. Kondratyuk140, J. Konig 63, S.A. Konigstorfer 95, P.J. Konopka 32, G.
Kornakov 133, S.D. Koryciak 2, A. Kotliarov 86, V. Kovalenko 140, M. Kowalski
107, V. Kozhuharov 36, I. Králik 59, A. Kravčáková 37, L. Krcal 32,38, M.
Krivda 100,59, F. Krizek 86, K. Krizkova Gajdosova 32, M. Kroesen 94, M.
Krüger 63, D.M. Krupova 35, E. Kryshen 140, V. Kučera 57, C. Kuhn 127, P.G.
Kuijer 84, T. Kumaoka123, D. Kumar132, L. Kumar 90, N. Kumar90, S. Kumar 31,
S. Kundu 32, P. Kurashvili 79, A. Kurepin 140, A.B. Kurepin 140, A.
Kuryakin140, S. Kushpil 86, J. Kvapil 100, M.J. Kweon 57, Y. Kwon 138, S.L. La
Pointe 38, P. La Rocca 26, A. Lakrathok105, M. Lamanna 32, R. Langoy 119, P.
Larionov 32, E. Laudi 32, L. Lautner 32,95, R. Lavicka 102, R. Lea 131,54, H.
Lee 104, I. Legrand 45, G. Legras 135, J. Lehrbach 38, T.M. Lelek2, R.C.
Lemmon 85, I. León Monzón 109, M.M. Lesch 95, E.D. Lesser 18, P. Lévai 136, X.
Li10, X.L. Li6, J. Lien 119, R. Lietava 100, I. Likmeta 114, B. Lim 24, S.H.
Lim 16, V. Lindenstruth 38, A. Lindner45, C. Lippmann 97, A. Liu 18, D.H. Liu
6, J. Liu 117, G.S.S. Liveraro111, I.M. Lofnes 20, C. Loizides 87, S. Lokos
107, J. Lomker 58, P. Loncar 33, J.A. Lopez 94, X. Lopez 125, E. López Torres
7, P. Lu 97,118, J.R. Luhder 135, M. Lunardon 27, G. Luparello 56, Y.G. Ma 39,
M. Mager 32, A. Maire 127, M.V. Makariev 36, M. Malaev 140, G. Malfattore 25,
N.M. Malik 91, Q.W. Malik19, S.K. Malik 91, L. Malinina VI,141, D. Mallick 80,
N. Mallick 47, G. Mandaglio 30,52, S.K. Mandal 79, V. Manko 140, F. Manso 125,
V. Manzari 49, Y. Mao 6, R.W. Marcjan 2, G.V. Margagliotti 23, A. Margotti 50,
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 51,
L. Massacrier 72, A. Mastroserio 129,49, O. Matonoha 75, S. Mattiazzo 27,
P.F.T. Matuoka110, A. Matyja 107, C. Mayer 107, A.L. Mazuecos 32, F. Mazzaschi
24, M. Mazzilli 32, J.E. Mdhluli 121, A.F. Mechler63, Y. Melikyan 43,140, A.
Menchaca-Rocha 66, E. Meninno 102,28, A.S. Menon114, M. Meres 12, S.
Mhlanga113,67, Y. Miake123, L. Micheletti 32, L.C. Migliorin126, D.L. Mihaylov
95, K. Mikhaylov 141,140, A.N. Mishra 136, D. Miśkowiec 97, A. Modak 4, A.P.
Mohanty 58, B. Mohanty 80, M. Mohisin Khan III,15, M.A. Molander 43, Z.
Moravcova 83, C. Mordasini 95, D.A. Moreira De Godoy135, I. Morozov 140, A.
Morsch 32, T. Mrnjavac 32, V. Muccifora 48, S. Muhuri 132, J.D. Mulligan 74,
A. Mulliri22, M.G. Munhoz 110, R.H. Munzer 63, H. Murakami 122, S. Murray 113,
L. Musa 32, J. Musinsky 59, J.W. Myrcha133, B. Naik 121, A.I. Nambrath 18,
B.K. Nandi46, R. Nania 50, E. Nappi 49, A.F. Nassirpour 17,75, A. Nath 94, C.
Nattrass 120, M.N. Naydenov 36, A. Neagu19, A. Negru124, L. Nellen 64, G.
Neskovic 38, B.S. Nielsen 83, E.G. Nielsen 83, S. Nikolaev 140, S. Nikulin
140, V. Nikulin 140, F. Noferini 50, S. Noh 11, P. Nomokonov 141, J. Norman
117, N. Novitzky 123, P. Nowakowski 133, A. Nyanin 140, J. Nystrand 20, M.
Ogino76, A. Ohlson 75, V.A. Okorokov 140, J. Oleniacz 133, A.C. Oliveira Da
Silva 120, M.H. Oliver 137, A. Onnerstad 115, C. Oppedisano 55, A. Ortiz
Velasquez 64, J. Otwinowski 107, M. Oya92, K. Oyama 76, Y. Pachmayer 94, S.
Padhan46, D. Pagano 131,54, G. Paić 64, A. Palasciano 49, S. Panebianco 128,
H. Park 123, H. Park 104, J. Park 57, J.E. Parkkila 32, R.N. Patra91, B. Paul
22, H. Pei 6, T. Peitzmann 58, X. Peng 6, M. Pennisi 24, D. Peresunko 140,
G.M. Perez 7, S. Perrin 128, Y. Pestov140, V. Petrov 140, M. Petrovici 45,
R.P. Pezzi 103,65, S. Piano 56, M. Pikna 12, P. Pillot 103, O. Pinazza 50,32,
L. Pinsky114, C. Pinto 95, S. Pisano 48, M. Płoskoń 74, M. Planinic89, F.
Pliquett63, M.G. Poghosyan 87, B. Polichtchouk 140, S. Politano 29, N. Poljak
89, A. Pop 45, S. Porteboeuf-Houssais 125, V. Pozdniakov 141, I.Y. Pozos44,
K.K. Pradhan 47, S.K. Prasad 4, S. Prasad 47, R. Preghenella 50, F. Prino 55,
C.A. Pruneau 134, I. Pshenichnov 140, M. Puccio 32, S. Pucillo 24, Z.
Pugelova106, S. Qiu 84, L. Quaglia 24, R.E. Quishpe114, S. Ragoni 14, A.
Rakotozafindrabe 128, L. Ramello 130,55, F. Rami 127, S.A.R. Ramirez44, T.A.
Rancien73, M. Rasa 26, S.S. Räsänen 43, R. Rath 50, M.P. Rauch20, I. Ravasenga
84, K.F. Read 87,120, C. Reckziegel112, A.R. Redelbach 38, K. Redlich IV,79,
C.A. Reetz 97, A. Rehman20, F. Reidt 32, H.A. Reme-Ness 34, Z. Rescakova37, K.
Reygers 94, A. Riabov 140, V. Riabov 140, R. Ricci 28, M. Richter19, A.A.
Riedel 95, W. Riegler 32, C. Ristea 62, M.V. Rodriguez 32, M. Rodríguez
Cahuantzi 44, K. Røed 19, R. Rogalev 140, E. Rogochaya 141, T.S. Rogoschinski
63, D. Rohr 32, D. Röhrich 20, P.F. Rojas44, S. Rojas Torres 35, P.S. Rokita
133, G. Romanenko 141, F. Ronchetti 48, A. Rosano 30,52, E.D. Rosas64, K.
Roslon 133, A. Rossi 53, A. Roy 47, S. Roy46, N. Rubini 25, O.V. Rueda 114, D.
Ruggiano133, R. Rui 23, P.G. Russek 2, R. Russo 84, A. Rustamov 81, E.
Ryabinkin 140, Y. Ryabov 140, A. Rybicki 107, H. Rytkonen 115, J. Ryu 16, W.
Rzesa133, O.A.M. Saarimaki 43, R. Sadek 103, S. Sadhu 31, S. Sadovsky 140, J.
Saetre 20, K. Šafařík 35, P. Saha41, S.K. Saha 4, S. Saha 80, B. Sahoo 46, B.
Sahoo 47, R. Sahoo 47, S. Sahoo60, D. Sahu 47, P.K. Sahu 60, J. Saini 132, K.
Sajdakova37, S. Sakai 123, M.P. Salvan 97, S. Sambyal 91, I. Sanna 32,95, T.B.
Saramela110, D. Sarkar 134, N. Sarkar132, P. Sarma41, V. Sarritzu 22, V.M.
Sarti 95, M.H.P. Sas 137, J. Schambach 87, H.S. Scheid 63, C. Schiaua 45, R.
Schicker 94, A. Schmah94, C. Schmidt 97, H.R. Schmidt93, M.O. Schmidt 32, M.
Schmidt93, N.V. Schmidt 87, A.R. Schmier 120, R. Schotter 127, A. Schröter 38,
J. Schukraft 32, K. Schwarz97, K. Schweda 97, G. Scioli 25, E. Scomparin 55,
J.E. Seger 14, Y. Sekiguchi122, D. Sekihata 122, I. Selyuzhenkov 97, S.
Senyukov 127, J.J. Seo 57, D. Serebryakov 140, L. Šerkšnytė 95, A. Sevcenco
62, T.J. Shaba 67, A. Shabetai 103, R. Shahoyan32, A. Shangaraev 140, A.
Sharma90, B. Sharma 91, D. Sharma46, H. Sharma53,107, M. Sharma 91, S. Sharma
76, S. Sharma 91, U. Sharma 91, A. Shatat 72, O. Sheibani114, K. Shigaki 92,
M. Shimomura77, J. Shin11, S. Shirinkin140, Q. Shou 39, Y. Sibiriak 140, S.
Siddhanta 51, T. Siemiarczuk 79, T.F. Silva 110, D. Silvermyr 75, T.
Simantathammakul105, R. Simeonov 36, B. Singh91, B. Singh 95, K. Singh 47, R.
Singh 80, R. Singh 91, R. Singh 47, S. Singh 15, V.K. Singh 132, V. Singhal
132, T. Sinha 99, B. Sitar 12, M. Sitta 130,55, T.B. Skaali19, G. Skorodumovs
94, M. Slupecki 43, N. Smirnov 137, R.J.M. Snellings 58, E.H. Solheim 19, J.
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hernandez88, R. Spijkers 84, I. Sputowska 107, J. Staa 75, J. Stachel 94, I.
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19, P. Stratmann 135, S. Strazzi 25, C.P. Stylianidis84, A.A.P. Suaide 110, C.
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N. Zurlo 131,54

## Affiliation Notes

I Deceased
II Also at: Italian National Agency for New Technologies, Energy and
Sustainable Economic Development (ENEA), Bologna, Italy
III Also at: Department of Applied Physics, Aligarh Muslim University,
Aligarh, India
IV Also at: Institute of Theoretical Physics, University of Wroclaw, Poland
V Also at: University of Kansas, Lawrence, Kansas, United States
VI Also at: An institution covered by a cooperation agreement with CERN

## Collaboration Institutes

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