2023 148 24 July

Non-prompt $\rm D^{0}$-meson Elliptic Flow in Pb–Pb Collisions at
$\sqrt{s_{\rm NN}}=5.02$ TeV

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

The elliptic flow ($v_{2}$) of $\rm D^{0}$ mesons from beauty-hadron decays
(non-prompt $\rm D^{0}$) was measured in midcentral (30–50%) Pb–Pb collisions
at a centre-of-mass energy per nucleon pair $\sqrt{s_{\rm NN}}=5.02$ TeV with
the ALICE detector at the LHC. The $\rm D^{0}$ mesons were reconstructed at
midrapidity ($|y|<0.8$) from their hadronic decay $\mathrm{D^{0}\to
K^{-}\uppi^{+}}$, in the transverse momentum interval $2<p_{\rm T}<12$
GeV$/c$. The result indicates a positive $v_{2}$ for non-prompt $\rm D^{0}$
mesons with a significance of 2.7$\sigma$. The non-prompt $\rm D^{0}$-meson
$v_{2}$ is lower than that of prompt non-strange D mesons with 3.2$\sigma$
significance in $2<p_{\mathrm{T}}<8~{}\mathrm{GeV}/c$, and compatible with the
$v_{2}$ of beauty-decay electrons. Theoretical calculations of beauty-quark
transport in a hydrodynamically expanding medium describe the measurement
within uncertainties.

##  1 Introduction

A phase of matter made of deconfined quarks and gluons, called the quark–gluon
plasma (QGP), is created in ultrarelativistic heavy-ion collisions, as
supported by several measurements at the SPS, RHIC, and LHC particle
accelerators [1, 2, 3, 4, 5, 6, 7, 8, 9]. The QGP formed in such extreme
conditions is considered to be a nearly perfect fluid [10]. Heavy quarks
(charm and beauty), mostly produced via hard partonic scattering processes on
a timescale shorter than the QGP formation time [11, 12], are effective probes
of the properties and dynamics of the QGP. They interact with the medium
constituents, losing energy via radiative and collisional processes [13]. The
significant suppression of charm- and beauty-hadron production yields at
intermediate and high transverse momentum ($p_{\mathrm{T}}>$
6$~{}\mathrm{GeV}/c$) observed in heavy-ion collisions at both RHIC [14, 15,
16, 17, 18] and LHC [19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32,
33], compared to appropriately scaled yields from proton–proton (pp)
collisions, indicates a substantial energy loss of heavy quarks in the QGP.

The azimuthal anisotropy in momentum space of final-state hadrons acts as an
additional observable to probe the properties of the QGP. In non-central
nucleus–nucleus collisions, the spatial anisotropy in the initial matter
distribution due to the asymmetry of the nuclear overlap region is transferred
to the final-state particle momentum distribution via multiple collisions, a
phenomenon referred to as anisotropic flow [34, 35]. The anisotropic flow is
quantified by the harmonic coefficients
$v_{\mathrm{n}}=\langle\cos[\mathrm{n}(\varphi-\Psi_{\mathrm{n}})]\rangle$ of
the Fourier expansion of the particle azimuthal angle ($\varphi$) relative to
the collision symmetry planes with angles $\Psi_{\mathrm{n}}$ for the $\rm
n^{\rm th}$ harmonic. The second harmonic, $v_{2}$, also known as elliptic
flow, is the largest coefficient in non-central heavy-ion collisions. At low
$p_{\mathrm{T}}$ ($p_{\mathrm{T}}<6~{}\mathrm{GeV}/c$), the heavy-flavour
$v_{2}$ can help to quantify the extent to which charm and beauty quarks
participate in the collective expansion of the medium [36] and the fraction of
heavy quarks hadronising via recombination with light quarks in the QGP medium
in the intermediate $p_{\mathrm{T}}$ region
($6<p_{\mathrm{T}}<10~{}\mathrm{GeV}/c$) [37, 38]. In addition, at high
$p_{\mathrm{T}}$ ($p_{\mathrm{T}}>10~{}\mathrm{GeV}/c$), the $v_{2}$ of heavy-
flavour hadrons can constrain the path-length dependence of energy loss in the
medium for heavy quarks [39, 40].

D mesons and charm-hadron decay leptons show a positive $v_{2}$ in
nucleus–nucleus collisions at both RHIC [41, 14, 42, 43] and LHC [44, 45, 46,
47, 48, 49, 50, 51, 52, 53] energies. The comparison of experimental
measurements with theoretical models indicates that charm quarks participate
in the collective expansion of the medium, and both collisional processes and
the hadronisation of charm quarks via coalescence with light quarks are
important to describe the observed elliptic flow [54, 55, 56, 57, 58, 59, 60,
61, 62, 63]. In particular, the D-meson $v_{2}$ has a magnitude similar to the
$v_{2}$ of charged pions for $3<p_{\mathrm{T}}<6~{}\mathrm{GeV}/c$, suggesting
that low-$p_{\mathrm{T}}$ charm quarks have a relaxation time comparable to
the QGP lifetime [64]. Due to their higher mass, beauty quarks are unlikely to
reach thermalisation in the medium, therefore their azimuthal anisotropy can
give further insight into the interactions of heavy quarks with the medium
[65, 66, 67, 68]. The experimental information is still poor for the beauty-
hadron $v_{2}$ at low momentum. The elliptic flow of $\mathrm{J}/\uppsi$
mesons originating from beauty-hadron decays (non-prompt) measured by the CMS
and ATLAS Collaborations is consistent with zero within large uncertainties
for $p_{\mathrm{T}}>3~{}\mathrm{GeV}/c$ [69, 70]. The $v_{2}$ of leptons from
beauty-hadron decays measured by ALICE and ATLAS is found to be positive [71,
72]. However, due to the small lepton masses, correlations between the
kinematic variables ($p_{\mathrm{T}}$ and direction) of the beauty hadrons and
the decay leptons are broad. This is improved when choosing a decay into a
heavier particle. A measurement of the non-prompt $\mathrm{D^{0}}$-meson
$v_{2}$ has been recently submitted for publication by CMS [73].

In this letter, the measurement of the non-prompt $\mathrm{D^{0}}$-meson
$v_{2}$ at midrapidty ($|y|<0.8$) in Pb–Pb collisions at a centre-of-mass
energy per nucleon pair $\sqrt{s_{\rm\scriptscriptstyle NN}}=5.02$ TeV with
the ALICE detector is reported. The $\mathrm{D^{0}}$-meson $v_{2}$ is measured
with the Scalar Product (SP) method [74, 75] in midcentral collisions (30–50%
centrality class). The non-prompt $\mathrm{D^{0}}$-meson $v_{2}$ is extracted
and compared with previous measurements of the prompt non-strange D-meson
$v_{2}$ (average of $\rm D^{0}$, $\rm D^{+}$, and $\rm D^{*+}$) and the
$v_{2}$ of electrons from beauty-hadron decays, as well as with theoretical
models based on beauty-quark transport in the QGP.

##  2 Experimental Apparatus and Data Analysis

A description of the ALICE detector and its performance can be found in Refs.
[76, 77, 9]. The main detectors used for this analysis are the Inner Tracking
System (ITS) [78] for track and vertex reconstruction, the Time Projection
Chamber (TPC) [79] for track reconstruction and particle identification (PID)
via the measurement of the specific energy loss, and the Time-Of-Flight (TOF)
[80] detector for PID via the measurement of the particle flight time from the
interaction point to the detector. These detectors are located inside a large
solenoidal magnet providing a magnetic field of up to 0.5 T parallel to the
LHC beam direction and cover the pseudorapidity interval $|\eta|<0.9$. A
minimum-bias interaction trigger was used, requiring coincident signals in the
V0A and V0C detectors [81], two scintillator arrays covering the full azimuth
in the pseudorapidity intervals $2.8<\eta<5.1$ (V0A) and $-3.7<\eta<-1.7$
(V0C). An online selection based on the V0 signal amplitudes was also applied
in order to enhance the sample of midcentral collisions as an additional
trigger class. Background events from beam–gas interactions were rejected
offline using the timing information provided by the V0 and the neutron Zero-
Degree Calorimeter (ZDC) [82]. Events used in the analysis were required to
have a primary vertex reconstructed within $\pm 10~{}\rm{cm}$ from the nominal
interaction point along the beam axis. Centrality intervals for events were
defined in terms of percentiles of the hadronic Pb–Pb cross section based on
the signal amplitude of the V0 detectors [83]. After the aforementioned
selections, a sample of about $85\times 10^{6}$ events in the 30–50%
centrality class was utilised for further analysis, corresponding to an
integrated luminosity of $\mathcal{L}_{\mathrm{int}}$ $\simeq
56~{}\mu\mathrm{b}^{-1}$ [84].

The $\mathrm{D^{0}}$ mesons and their charge conjugates were reconstructed via
the hadronic decay channel $\mathrm{D^{0}\to K^{-}}$ $\mathrm{\uppi^{+}}$ with
branching ratio $\mathrm{BR}=(3.947\pm 0.030)\%$ [85]. The
$\mathrm{D^{0}}$-meson candidates were selected combining pairs of tracks with
opposite charge signs, each with $p_{\mathrm{T}}>0.3~{}\mathrm{GeV}/c$ and
$|\eta|<0.8$. The selection criteria require at least 70 (out of 159)
associated space points in the TPC, a minimum of two (out of six) measured
clusters in the ITS, with at least one in either of the two innermost layers,
and a fit quality $\chi^{2}/\mathrm{ndf}<1.25$ in the TPC. These track
selection criteria reduce the $\mathrm{D^{0}}$-meson acceptance in rapidity,
which falls steeply to zero for $|y|>0.5$ at low $p_{\mathrm{T}}$ and for
$|y|>0.8$ for $p_{\mathrm{T}}>5~{}\mathrm{GeV}/c$. Thus, a fiducial acceptance
selection $|y|<y_{\rm fid}(p_{\mathrm{T}})$ was applied to grant a uniform
acceptance inside the rapidity range considered. The
$y_{\mathrm{fid}}(p_{\mathrm{T}})$ value was defined as a second-order
polynomial function, increasing from 0.5 to 0.8 in
$0<p_{\mathrm{T}}<5~{}\mathrm{GeV}/c$, and as a constant term,
$y_{\mathrm{fid}}=0.8$, for $p_{\mathrm{T}}>5~{}\mathrm{GeV}/c$.

A machine-learning approach with multi-class classification based on Boosted
Decision Trees (BDT) was adopted to simultaneously suppress the large
combinatorial background and separate the contributions of prompt and non-
prompt $\mathrm{D^{0}}$ mesons. The implementation of the BDT algorithm
provided by the XGBoost [86] library was employed. Samples of prompt and non-
prompt $\mathrm{D^{0}}$ mesons for the BDT training were obtained from Monte
Carlo (MC) samples, which simulated the Pb–Pb events at $\sqrt{s_{\rm
NN}}=5.02$ TeV with the HIJING v1.383 generator [87]. Additional
$\mathrm{c\overline{c}}$ or $\mathrm{b\overline{b}}$ quark pairs were injected
in each simulated event using the PYTHIA 8.243 event generator [88, 89]
(Monash 2013 tune [90]) to enrich the MC sample of prompt and non-prompt
$\mathrm{D^{0}}$-meson signals. The generated particles were transported
through the experimental apparatus using the GEANT3 transport package [91].
Samples for the combinatorial background were obtained from candidates in the
sideband region in the data, i.e. $5\sigma<|\Delta M|<9\sigma$ in the
invariant mass distribution, where $\Delta M$ is the difference between the
invariant mass and the mean of signal distribution, and $\sigma$ is the
invariant-mass resolution. Before the training, loose selections on kinematic
and topological variables were applied to the $\mathrm{D^{0}}$-meson
candidates to reduce the computation time. The training variables provided to
the BDTs were mainly based on the displacement of the $\rm D^{0}$ decay vertex
from the primary vertex of the collision. These included the impact parameter
of the $\mathrm{D^{0}}$-meson daughter tracks, the distance between the
$\mathrm{D^{0}}$-meson decay vertex and the primary vertex, and the cosine of
the pointing angle between the $\mathrm{D^{0}}$-meson candidate line of flight
(the vector connecting the primary and secondary vertices) and its
reconstructed momentum vector, as well as the PID information of the decay
tracks. A detailed description of the training procedure is reported in Ref.
[92]. Independent BDTs were trained in the different $p_{\mathrm{T}}$
intervals of the analysis. Subsequently, the BDTs were applied to the
experimental data sample to obtain the BDT scores related to the candidate
probability to be a non-prompt $\mathrm{D^{0}}$ meson or to belong to the
combinatorial background. Selections were applied on the scores to reduce the
large combinatorial background and to obtain different fractions of non-prompt
$\rm D^{0}$ candidates ($f_{\mathrm{non\text{-}prompt}}$). The
$\mathrm{D^{0}}$-meson $v_{2}$ coefficient was measured with the Scalar
Product (SP) method [75, 74, 93],

$v_{\mathrm{2}}\\{\mathrm{SP}\\}=\langle\langle\boldsymbol{u}_{\mathrm{2}}\cdot\frac{\boldsymbol{Q}_{\mathrm{2}}^{\rm
V0C*}}{M^{\rm
V0C}}\rangle\rangle\bigg{/}\sqrt{\frac{\langle\frac{\boldsymbol{Q}_{\mathrm{2}}^{\rm
V0C}}{M^{\rm V0C}}\cdot\frac{\boldsymbol{Q}_{\mathrm{2}}^{\rm V0A*}}{M^{\rm
V0A}}\rangle\langle\frac{\boldsymbol{Q}_{\mathrm{2}}^{\rm V0C}}{M^{\rm
V0C}}\cdot\frac{\boldsymbol{Q}_{\mathrm{2}}^{\rm TPC*}}{M^{\rm
TPC}}\rangle}{\langle\frac{\boldsymbol{Q}_{\mathrm{2}}^{\rm V0A}}{M^{\rm
V0A}}\cdot\frac{\boldsymbol{Q}_{\mathrm{2}}^{\rm TPC*}}{M^{\rm
TPC}}\rangle}}=\langle\langle\boldsymbol{u}_{\mathrm{2}}\cdot\frac{\boldsymbol{Q}_{\mathrm{2}}^{\rm
V0C*}}{M^{\rm V0C}}\rangle\rangle\big{/}R_{\rm 2},$ (1)

where u${}_{\mathrm{2}}=e^{i\mathrm{2}\varphi_{\mathrm{D^{0}}}}$ is the unit
flow vector of the $\mathrm{D^{0}}$-meson candidate with azimuthal angle
$\varphi_{\mathrm{D^{0}}}$. $\boldsymbol{Q}^{k}_{\mathrm{2}}$ and $M^{k}$ are
the subevent $\mathrm{2}^{\mathrm{nd}}$ harmonic flow vector and multiplicity
for the subevent $k$, respectively. The denominator, called the resolution
($R_{\rm 2}$), is calculated with the formula introduced in Ref. [75], where
the three subevents are defined by the particles measured in the V0C, V0A, and
TPC detectors, respectively. For the TPC detector, the azimuthal angles of
charged tracks reconstructed with $|\eta|<0.8$ and the number of measured
tracks were used to calculate the $Q_{\mathrm{2}}$ vector and $M$. For the V0A
and V0C detectors, the $Q_{\mathrm{2}}$ vectors were calculated from the
azimuthal distribution of the energy deposition in the detector scintillators
and $M$ is the sum of the amplitudes measured in each channel [52]. The
$Q_{\mathrm{2}}$ vectors are recalibrated using a recentering procedure [94]
to correct for effects of non-uniform acceptance. The nonflow effects are
supressed by the pseudorapidity gaps between the TPC, V0A, and V0C detectors
[95]. The single bracket $\langle\rangle$ in Eq. 1 refers to an average over
all the events, while the double brackets $\langle\langle\rangle\rangle$
denote the average over all particles in the considered $p_{\mathrm{T}}$
interval and all events. The $R_{\rm 2}$ is extracted as a function of the
collision centrality. The centrality-integrated $R_{\rm 2}$ value is 0.0438
for the 30–50% centrality class.

The $\mathrm{D^{0}}$-meson $v_{2}$ cannot be measured directly using Eq. 1
since $\mathrm{D^{0}}$ mesons cannot be identified on a particle-by-particle
basis. Therefore, a simultaneous fit to the invariant-mass spectrum and the
$v_{2}$ distribution as a function of the invariant mass ($M_{\mathrm{K\pi}}$)
was performed for $\mathrm{D^{0}}$ candidates in each $p_{\mathrm{T}}$
interval, in order to measure the raw yields and the $v_{2}$ coefficients. The
measured total elliptic flow coefficient, $v^{\mathrm{tot}}_{\mathrm{2}}$, can
be written as a weighted sum of the $v_{2}$ of the $\mathrm{D^{0}}$-meson
candidates ($v^{\mathrm{sig}}_{\mathrm{2}}$), and that of background
($v^{\mathrm{bkg}}_{\mathrm{2}}$) [96] as

$v^{\mathrm{tot}}_{\mathrm{2}}(M_{\mathrm{K\pi}})=v^{\mathrm{sig}}_{\mathrm{2}}\frac{N^{\mathrm{sig}}}{N^{\mathrm{sig}}+N^{\mathrm{bkg}}}(M_{\mathrm{K\pi}})+v^{\mathrm{bkg}}_{\mathrm{2}}(M_{\mathrm{K\pi}})\frac{N^{\mathrm{bkg}}}{N^{\mathrm{sig}}+N^{\mathrm{bkg}}}(M_{\mathrm{K\pi}}),$
(2)

where $N^{\mathrm{sig}}$ and $N^{\mathrm{bkg}}$ are the raw signal and
background yields, respectively. The fit function for the
$\mathrm{D^{0}}$-candidate invariant-mass distribution was composed of a
Gaussian term to describe the signal and an exponential distribution for the
background. The contribution of signal candidates with the reflected K–$\pi$
mass assignment was taken into account with an additional term, which is small
thanks to the good PID capability. It was parameterised by fitting the
simulated invariant-mass distribution with a double Gaussian function. To
improve the stability of the fits, the widths of the signal peaks were fixed
to the values extracted from the fits of the invariant-mass distributions in
the prompt enhanced sample, given the naturally larger abundance of prompt
compared to non-prompt candidates. In the simultaneous fit, the
$v_{\mathrm{2}}$ parameter for the candidates with wrong K–$\pi$ mass
assignment was set to be equal to $v^{\mathrm{sig}}_{\mathrm{2}}$, provided
that the origin of these candidates are real $\mathrm{D^{0}}$ mesons. The
$v^{\mathrm{sig}}_{\mathrm{2}}$ was measured from the fit to the
$v^{\mathrm{tot}}_{\mathrm{2}}$ distribution with the function of Eq. 2, where
$v^{\mathrm{bkg}}_{\mathrm{2}}$ is a linear as a function of
$M_{\mathrm{K\pi}}$ for $p_{\mathrm{T}}>3~{}\mathrm{GeV}/c$. For
$p_{\mathrm{T}}<3~{}\mathrm{GeV}/c$, a second-order polynomial function was
used to parametrise $v^{\mathrm{bkg}}_{\mathrm{2}}$($M_{\mathrm{K\pi}}$).
Figure 1 shows an example of the simultaneous fit to the invariant-mass
spectrum and $v_{2}^{\mathrm{tot}}$ as a function of $M_{\mathrm{K\pi}}$ with
low (left panel) and high (right panel) non-prompt $\mathrm{D^{0}}$-meson
candidate BDT score selections in $3<p_{\mathrm{T}}<4~{}\mathrm{GeV}/c$ in the
30–50$\%$ centrality class.

Figure 1: Simultaneous fits of the invariant-mass distribution and
$v_{2}^{\mathrm{tot}}(M_{\mathrm{K\pi}})$ of $\mathrm{D^{0}}$ mesons in
$3<p_{\mathrm{T}}<4~{}\mathrm{GeV}/c$. Left panel: fits using
$\mathrm{D^{0}}$-meson candidates with low probability to be a non-prompt
$\mathrm{D^{0}}$ meson. Right panel: fits using $\mathrm{D^{0}}$-meson
candidates with high probability to be a non-prompt $\mathrm{D^{0}}$ meson.
The corresponding BDT score selection for the measured raw yield is reported.
The blue lines, the dotted red curves, and the green solid lines represent the
total fit function, the combinatorial-background fit function, and the
contribution of the reflected signal, respectively.

The reconstructed $\mathrm{D^{0}}$-meson signals are a mixture of prompt and
non-prompt $\mathrm{D^{0}}$ mesons. The $v^{\mathrm{sig}}_{\mathrm{2}}$ is
therefore a linear combination of prompt ($v^{\mathrm{prompt}}_{\mathrm{2}}$)
and non-prompt ($v^{\mathrm{non\text{-}prompt}}_{\mathrm{2}}$) contributions,
which can be expressed as

$v^{\mathrm{sig}}_{\mathrm{2}}=(1-f_{\mathrm{non\text{-}prompt}})v^{\mathrm{prompt}}_{\mathrm{2}}+f_{\mathrm{non\text{-}prompt}}v^{\mathrm{non\text{-}prompt}}_{\mathrm{2}},$
(3)

where $f_{\mathrm{non\text{-}prompt}}$ is estimated as a function of
$p_{\mathrm{T}}$ with a data-driven method, which is based on the construction
of data samples with different abundances of prompt and non-prompt candidates.
A set of raw yields $Y_{i}$ (index $i$ refers to a given selection on the BDT
scores) can be obtained by varying the selection on the BDT score, which is
related to the candidate probability to be a non-prompt $\mathrm{D^{0}}$
meson. These raw yields are related to the corresponding acceptance times
efficiency $(\mathrm{Acc}\times\epsilon)$ of prompt and non-prompt
$\mathrm{D^{0}}$ mesons according to the equation

$(\mathrm{Acc}\times\epsilon)^{\mathrm{prompt}}_{i}\,N_{\mathrm{prompt}}+(\mathrm{Acc}\times\epsilon)^{\mathrm{non\text{-}prompt}}_{i}\,N_{\mathrm{non\text{-}prompt}}-Y_{i}=\delta_{i},$
(4)

where $\delta_{i}$ represents a residual that accounts for the equation not
summing exactly to 0 due to the uncertainties on $Y_{i}$,
$(\mathrm{Acc}\times\epsilon)^{\mathrm{non\text{-}prompt}}_{i}$, and
$(\mathrm{Acc}\times\epsilon)^{\mathrm{prompt}}_{i}$. By applying at least two
different BDT selections and extracting the yields, the corrected yields of
prompt ($N_{\mathrm{prompt}}$) and non-prompt
($N_{\mathrm{non\text{-}prompt}}$) $\mathrm{D^{0}}$ mesons can be obtained
from Eq. 4 via a $\chi^{2}$ minimisation. More details can be found in Ref.
[92]. The left panel of Fig. 2 shows an example of the raw-yield distributions
as a function of the minimum non-prompt $\mathrm{D^{0}}$-meson BDT score
threshold used in such a $\chi^{2}$-minimisation procedure in
$3<p_{\mathrm{T}}<4~{}\mathrm{GeV}/c$ for the 30–50% centrality class. The raw
yield decreases with the increasing minimum threshold for the score to be a
non-prompt $\mathrm{D^{0}}$ meson, corresponding to an increasing non-prompt
$\mathrm{D^{0}}$-meson fraction. The prompt and non-prompt components of the
raw yields for each BDT-based selection obtained from the
$\chi^{2}$-minimisation approach,
$(\mathrm{Acc}\times\epsilon)^{\mathrm{prompt}}_{i}\times N_{\mathrm{prompt}}$
and $(\mathrm{Acc}\times\epsilon)^{\mathrm{non\text{-}prompt}}_{i}\times
N_{\mathrm{non\text{-}prompt}}$, are shown in the histograms with red and blue
colour, respectively, and their sum is reported by the green line. The values
of $N_{\mathrm{non\text{-}prompt}}$ and $N_{\mathrm{prompt}}$ can be used to
estimate the non-prompt $\mathrm{D^{0}}$-meson fraction in the raw yield for
any set of selections $i$ using

$f_{\mathrm{non\text{-}prompt}}^{i}=\frac{(\mathrm{Acc}\times\epsilon)^{\mathrm{non\text{-}prompt}}_{i}\,N_{\mathrm{non\text{-}prompt}}}{(\mathrm{Acc}\times\epsilon)^{\mathrm{non\text{-}prompt}}_{i}\,N_{\mathrm{non\text{-}prompt}}+(\mathrm{Acc}\times\epsilon)^{\mathrm{prompt}}_{i}\,N_{\mathrm{prompt}}}.$
(5)

The $v^{\mathrm{sig}}_{\mathrm{2}}$ was determined for three or four non-
overlapping intervals of BDT score to be non-prompt $\mathrm{D^{0}}$ mesons,
depending on the number of candidates in each $p_{\rm T}$ interval. The result
was extrapolated to $f_{\mathrm{non\text{-}prompt}}$ = 0 and
$f_{\mathrm{non\text{-}prompt}}$ = 1 using a linear fit according to Eq. 3 in
order to estimate the $v_{2}$ values for prompt and non-prompt
$\mathrm{D^{0}}$ mesons, respectively. A similar approach was adopted in Ref.
[97]. The right panel of Fig. 2 shows the linear fit of
$v^{\mathrm{sig}}_{\mathrm{2}}$ as a function of
$f_{\mathrm{non\text{-}prompt}}$ in $3<p_{\mathrm{T}}<4~{}\mathrm{GeV}/c$. The
blue band represents the 1$\sigma$ confidence interval obtained from the
linear fit, which is considered as the statistical uncertainty of the
$v^{\mathrm{sig}}_{\mathrm{2}}$. As a crosscheck about the correlation of the
statistical uncertainties on $v^{\mathrm{sig}}_{\mathrm{2}}$ between different
values of $f_{\mathrm{non\text{-}prompt}}$, the statistical uncertainty was
also calculated with the Jackknife method [98] and found to be consistent with
the fit method.

Figure 2: Left panel: example of the raw-yield distribution as a function of
the minimum non-prompt $\mathrm{D^{0}}$-meson BDT score threshold to determine
the non-prompt $\mathrm{D^{0}}$-meson fraction in
$3<p_{\mathrm{T}}<4~{}\mathrm{GeV}/c$. Right panel:
$v^{\mathrm{sig}}_{\mathrm{2}}$ as a function of
$f_{\mathrm{non\text{-}prompt}}$ in $3<p_{\mathrm{T}}<4~{}\mathrm{GeV}/c$. The
blue band represents the 1$\sigma$ confidence interval obtained from the
linear fit.

##  3 Systematic Uncertainties

Four major sources of systematic uncertainties were considered for the
measurement of the non-prompt $\mathrm{D^{0}}$-meson $v_{2}$: (i) the signal
extraction from the invariant-mass and $v_{2}^{\rm tot}$ distributions; (ii)
the non-prompt fraction estimation; (iii) the D-meson $p_{\mathrm{T}}$ shape
in the simulation; and (iv) the centrality dependence of the SP denominator
($R_{\rm 2}$). All sources of systematic uncertainties were treated as
uncorrelated and added in quadrature to obtain the total systematic
uncertainties. Table 1 summarises the estimated values of the systematic
uncertainties for each $p_{\mathrm{T}}$ interval.

Table 1: Summary of the systematic uncertainties on the measurement of the non-prompt $\mathrm{D^{0}}$-meson $v_{2}$. The ranges of the uncertainties are quoted as absolute uncertainties, except those on the $R_{\rm 2}$ as relative uncertainty. $p_{\mathrm{T}}~{}(\mathrm{GeV}/c)$ |  $2\mbox{--}3$ | $3\mbox{--}4$ |  $4\mbox{--}5$ | $5\mbox{--}6$ |  $6\mbox{--}8$ | $8\mbox{--}12$
---|---|---|---|---|---|---
Signal extraction |  0.011 | 0.012 |  0.011 | 0.011 |  0.012 | 0.013
Non-prompt fraction estimation |  0.005 | 0.002 |  0.002 | 0.001 |  0.001 | 0.001
MC D-meson $p_{\mathrm{T}}$ distribution |  0.004 | 0.004 |  0.002 | 0.001 |  0.001 | 0.001
$R_{\rm 2}$ determination |  0.5% | 0.5% |  0.5% | 0.5% |  0.5% | 0.5%

The systematic uncertainty of the signal extraction from the invariant-mass
and $v_{2}^{\rm tot}$ distributions is due to a possible imperfect modelling
of the signal and background distributions. It was evaluated by repeating the
simultaneous fit with different configurations. In particular, the fit range,
signal width within the statistical uncertainties obtained with prompt
enhanced sample, and background fit functions used for the invariant-mass and
$v^{\mathrm{tot}}_{\mathrm{2}}$ distributions were varied. The systematic
uncertainty was defined as the RMS of the distribution of the resulting
$v^{\mathrm{non\text{-}prompt}}_{\mathrm{2}}$ obtained from all these
variations. The second source of systematic uncertainty arises from the
uncertainty on the determination of the $f_{\mathrm{non\text{-}prompt}}$ of
$\mathrm{D^{0}}$ mesons with the minimisation method described in Section 2.
In this method, the raw yields and the efficiencies obtained with several sets
of selections are used in order to extract the prompt and non-prompt
components. It is therefore sensitive to possible imperfections of the data
description in the MC simulations. They were therefore evaluated by using
alternative sets of selections for the aforementioned $\chi^{2}$-minimisation
approach [92]; the RMS of the resulting
$v^{\mathrm{non\text{-}prompt}}_{\mathrm{2}}$ distribution was considered as
the systematic uncertainty. The systematic effects due to possible differences
between the real and simulated $p_{\mathrm{T}}$ spectra were estimated by
applying different weights to the $p_{\mathrm{T}}$ distributions of prompt
$\mathrm{D^{0}}$ mesons and of the parent beauty hadrons in the case of non-
prompt $\mathrm{D^{0}}$ mesons. In the default analysis procedure, the weights
were defined to match the shape given by FONLL in pp collisions [99, 100]
multiplied by the nuclear modification factor ($R_{\mathrm{AA}}$) prediction
from the TAMU model [55]. The FONLL spectrum multiplied by the
$R_{\mathrm{AA}}$ from the LIDO model [101] was used as an alternative shape
for the systematic evaluation. The effect due to flow-related modifications of
the parent beauty-hadron $p_{\rm T}$ spectra was found to be negligible with
respect to the assigned $p_{\rm T}$-shape systematic uncertainty. The
contribution of the SP denominator $R_{\rm 2}$ to the systematic uncertainty
is due to the centrality dependence. It was evaluated as the difference of the
centrality-integrated $R_{\rm 2}$ values with those obtained from weighted
average $R_{\rm 2}$ values in narrow centrality intervals using the
$\mathrm{D^{0}}$-meson yields as weights [52].

##  4 Results

Figure 3: Left panel: Elliptic flow $v_{2}$ of non-prompt $\mathrm{D^{0}}$
mesons (blue points) and average of prompt non-strange D mesons [52] (red
points) as a function of $p_{\mathrm{T}}$ in 30–50% Pb–Pb collisions at
$\sqrt{s_{\rm\scriptscriptstyle NN}}=5.02~{}\mathrm{TeV}$. The symbols are
positioned at the average $p_{\mathrm{T}}$ of the reconstructed
$\mathrm{D^{0}}$ mesons. Statistical uncertainties are shown as vertical lines
and systematic uncertainties as boxes. Right panel: non-prompt
$\mathrm{D^{0}}$-meson $v_{2}$ compared with model calculations [102, 103, 62,
104, 105, 106, 107, 101].

The measured non-prompt $\mathrm{D^{0}}$-meson elliptic flow at midrapidity
($|y|<0.8$) in the 30–50% centrality class is shown in Fig. 3 as a function of
$p_{\mathrm{T}}$. The weighted mean of the non-prompt $\mathrm{D^{0}}$-meson
$v_{2}$ in the measured $p_{\mathrm{T}}$ range
($2<p_{\mathrm{T}}<12~{}\mathrm{GeV}/c$) is 2.7$\sigma$ above 0. No
significant $p_{\mathrm{T}}$ dependence of the $v_{2}$ is observed. The
results obtained are compatible within uncertainties with those submitted for
publication by CMS [73], which have smaller statistical uncertainty. In the
left panel of Fig. 3, the non-prompt $\mathrm{D^{0}}$-meson $v_{2}$ is
compared with the average $v_{2}$ of prompt $\rm D^{0}$, $\rm D^{+}$, and $\rm
D^{*+}$ mesons [52]. The non-prompt $\rm D^{0}$-meson $v_{2}$ is lower than
that of prompt non-strange D mesons with 3.2$\sigma$ significance in
$2<p_{\mathrm{T}}<8~{}\mathrm{GeV}/c$, indicating a different degree of
participation to the collective motion of the medium between charm and beauty
quarks.

The measured $v_{2}$ of non-prompt $\mathrm{D^{0}}$ mesons is compared with
several theoretical models implementing beauty-quark transport in a
hydrodynamically expanding QGP phase [102, 103, 62, 104, 105, 106, 107, 101]
in the right panel of Fig. 3. All of the considered calculations include
collisional interactions between beauty quarks and medium constituents. In
addition, the LBT [62, 103], LIDO [107, 101], LGR [104], and Langevin [105,
106] models also include radiative processes. Beauty-quark hadronisation via
coalescence is considered for all models in addition to the fragmentation
mechanism. Although the models are implemented with different assumptions on
the interactions in the QGP and hadronic phases, and on the medium expansion,
all of them provide a reasonable description of the measurement within
uncertainties. More precise measurements will further constrain model
parameters, especially on the spatial diffusion coefficient of beauty quarks,
which are implemented differently in the various models.

Figure 4 shows the comparison between the $v_{2}$ of electrons from beauty-
hadron decays ($\mathrm{b}(\to\mathrm{c})\to\mathrm{e}$) [71] and the non-
prompt $\mathrm{D^{0}}$-meson $v_{2}$ measurements. They are compatible in the
common $p_{\mathrm{T}}$ interval within uncertainties. The LIDO model provides
reasonable descriptions for these measurements and is consistent with the
$p_{\mathrm{T}}$ shape in the data. Note that, the $p_{\mathrm{T}}$ of beauty-
decay hadrons is not the same $p_{\mathrm{T}}$ of B mesons due to the decay
kinematics. The good agreement between the predictions for B-meson and non-
prompt $\mathrm{D^{0}}$-meson $v_{2}$ from LIDO indicates that the decay
kinematics do not play a significant role in the beauty-hadron $v_{2}$
measurements.

Figure 4: Elliptic flow $v_{2}$ of non-prompt $\mathrm{D^{0}}$ mesons (blue
points) and electrons from beauty-hadron decays [71] (red points) as a
function of $p_{\mathrm{T}}$ in 30–50% Pb–Pb collisions at
$\sqrt{s_{\rm\scriptscriptstyle NN}}=5.02~{}\mathrm{TeV}$, compared with the
LIDO model predictions [107, 101].

##  5 Conclusions

The measurement of the non-prompt $\mathrm{D^{0}}$-meson $v_{2}$ in midcentral
Pb–Pb collisions (30–50% centrality class) at $\sqrt{s_{\rm NN}}=5.02$ TeV is
presented in the transverse momentum interval 2 $<p_{\rm T}<$12 GeV$/c$. The
non-prompt $\mathrm{D^{0}}$-meson $v_{2}$ is found to be positive with a
significance of 2.7$\sigma$ and it is lower by 3.2$\sigma$ than the prompt
non-strange D-meson $v_{2}$ (average of $\rm D^{0}$, $\rm D^{+}$, and $\rm
D^{*+}$) in the range $2<p_{\mathrm{T}}<8$ GeV$/c$. The measurement is
important for the understanding of the degree of thermalisation of beauty
quarks in the QGP. Future data samples to be collected with the upgraded ALICE
detector in Run 3 will allow for higher-precision measurements of the non-
prompt $\mathrm{D^{0}}$-meson $v_{2}$ and $R_{\rm AA}$ [108]. These
measurements will provide important constraints to model predictions, and
allow for accurate extraction of the spatial diffusion coefficient of beauty
quarks.

## 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; 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.

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##  Appendix A The ALICE Collaboration

S. Acharya 126, D. Adamová 86, G. Aglieri Rinella 33, M. Agnello 30, N.
Agrawal 51, Z. Ahammed 134, S. Ahmad 16, S.U. Ahn 71, I. Ahuja 38, A.
Akindinov 142, M. Al-Turany 97, D. Aleksandrov 142, B. Alessandro 56, H.M.
Alfanda 6, R. Alfaro Molina 67, B. Ali 16, A. Alici 26, N. Alizadehvandchali
115, A. Alkin 33, J. Alme 21, G. Alocco 52, T. Alt 64, A.R. Altamura 50, I.
Altsybeev 95, M.N. Anaam 6, C. Andrei 46, N. Andreou 114, A. Andronic 137, V.
Anguelov 94, F. Antinori 54, P. Antonioli 51, N. Apadula 74, L. Aphecetche
103, H. Appelshäuser 64, C. Arata 73, S. Arcelli 26, M. Aresti 23, R. Arnaldi
56, J.G.M.C.A. Arneiro 110, I.C. Arsene 20, M. Arslandok 139, A. Augustinus
33, R. Averbeck 97, M.D. Azmi 16, H. Baba123, A. Badalà 53, J. Bae 104, Y.W.
Baek 41, X. Bai 119, R. Bailhache 64, Y. Bailung 48, A. Balbino 30, A.
Baldisseri 129, B. Balis 2, D. Banerjee 4, Z. Banoo 91, R. Barbera 27, F.
Barile 32, L. Barioglio 95, M. Barlou78, B. Barman42, G.G. Barnaföldi 138,
L.S. Barnby 85, V. Barret 126, L. Barreto 110, C. Bartels 118, K. Barth 33, E.
Bartsch 64, N. Bastid 126, S. Basu 75, G. Batigne 103, D. Battistini 95, B.
Batyunya 143, D. Bauri47, J.L. Bazo Alba 101, I.G. Bearden 83, C. Beattie 139,
P. Becht 97, D. Behera 48, I. Belikov 128, A.D.C. Bell Hechavarria 137, F.
Bellini 26, R. Bellwied 115, S. Belokurova 142, Y.A.V. Beltran 45, G. Bencedi
138, S. Beole 25, Y. Berdnikov 142, A. Berdnikova 94, L. Bergmann 94, M.G.
Besoiu 63, L. Betev 33, P.P. Bhaduri 134, A. Bhasin 91, M.A. Bhat 4, B.
Bhattacharjee 42, L. Bianchi 25, N. Bianchi 49, J. Bielčík 36, J. Bielčíková
86, J. Biernat 107, A.P. Bigot 128, A. Bilandzic 95, G. Biro 138, S. Biswas 4,
N. Bize 103, J.T. Blair 108, D. Blau 142, M.B. Blidaru 97, N. Bluhme39, C.
Blume 64, G. Boca 22,55, F. Bock 87, T. Bodova 21, A. Bogdanov142, S. Boi 23,
J. Bok 58, L. Boldizsár 138, M. Bombara 38, P.M. Bond 33, G. Bonomi 133,55, H.
Borel 129, A. Borissov 142, A.G. Borquez Carcamo 94, H. Bossi 139, E. Botta
25, Y.E.M. Bouziani 64, L. Bratrud 64, P. Braun-Munzinger 97, M. Bregant 110,
M. Broz 36, G.E. Bruno 96,32, M.D. Buckland 24, D. Budnikov 142, H. Buesching
64, S. Bufalino 30, P. Buhler 102, N. Burmasov 142, Z. Buthelezi 68,122, A.
Bylinkin 21, S.A. Bysiak107, M. Cai 6, H. Caines 139, A. Caliva 29, E. Calvo
Villar 101, J.M.M. Camacho 109, P. Camerini 24, F.D.M. Canedo 110, M. Carabas
125, A.A. Carballo 33, F. Carnesecchi 33, R. Caron 127, L.A.D. Carvalho 110,
J. Castillo Castellanos 129, F. Catalano 33,25, C. Ceballos Sanchez 143, I.
Chakaberia 74, P. Chakraborty 47, S. Chandra 134, S. Chapeland 33, M. Chartier
118, S. Chattopadhyay 134, S. Chattopadhyay 99, T.G. Chavez 45, T. Cheng 97,6,
C. Cheshkov 127, B. Cheynis 127, V. Chibante Barroso 33, D.D. Chinellato 111,
E.S. Chizzali I,95, J. Cho 58, S. Cho 58, P. Chochula 33, D. Choudhury42, P.
Christakoglou 84, C.H. Christensen 83, P. Christiansen 75, T. Chujo 124, M.
Ciacco 30, C. Cicalo 52, F. Cindolo 51, M.R. Ciupek97, G. ClaiII,51, F.
Colamaria 50, J.S. Colburn100, D. Colella 96,32, M. Colocci 26, M. Concas
III,33, G. Conesa Balbastre 73, Z. Conesa del Valle 130, G. Contin 24, J.G.
Contreras 36, M.L. Coquet 129, P. Cortese 132,56, M.R. Cosentino 112, F. Costa
33, S. Costanza 22,55, C. Cot 130, J. Crkovská 94, P. Crochet 126, R. Cruz-
Torres 74, P. Cui 6, A. Dainese 54, M.C. Danisch 94, A. Danu 63, P. Das 80, P.
Das 4, S. Das 4, A.R. Dash 137, S. Dash 47, R.M.H. David45, A. De Caro 29, G.
de Cataldo 50, J. de Cuveland39, A. De Falco 23, D. De Gruttola 29, N. De
Marco 56, C. De Martin 24, S. De Pasquale 29, R. Deb 133, R. Del Grande 95, L.
Dello Stritto 29, W. Deng 6, P. Dhankher 19, D. Di Bari 32, A. Di Mauro 33, B.
Diab 129, R.A. Diaz 143,7, T. Dietel 113, Y. Ding 6, J. Ditzel 64, R. Divià
33, D.U. Dixit 19, Ø. Djuvsland21, U. Dmitrieva 142, A. Dobrin 63, B. Dönigus
64, J.M. Dubinski 135, A. Dubla 97, S. Dudi 90, P. Dupieux 126, M. Durkac106,
N. Dzalaiova13, T.M. Eder 137, R.J. Ehlers 74, F. Eisenhut 64, R. Ejima92, D.
Elia 50, B. Erazmus 103, F. Ercolessi 26, F. Erhardt 89, M.R. Ersdal21, B.
Espagnon 130, G. Eulisse 33, D. Evans 100, S. Evdokimov 142, L. Fabbietti 95,
M. Faggin 28, J. Faivre 73, F. Fan 6, W. Fan 74, A. Fantoni 49, M. Fasel 87,
P. Fecchio30, A. Feliciello 56, G. Feofilov 142, A. Fernández Téllez 45, L.
Ferrandi 110, M.B. Ferrer 33, A. Ferrero 129, C. Ferrero 56, A. Ferretti 25,
V.J.G. Feuillard 94, V. Filova 36, D. Finogeev 142, F.M. Fionda 52, F. Flor
115, A.N. Flores 108, S. Foertsch 68, I. Fokin 94, S. Fokin 142, E. Fragiacomo
57, E. Frajna 138, U. Fuchs 33, N. Funicello 29, C. Furget 73, A. Furs 142, T.
Fusayasu 98, J.J. Gaardhøje 83, M. Gagliardi 25, A.M. Gago 101, T. Gahlaut47,
C.D. Galvan 109, D.R. Gangadharan 115, P. Ganoti 78, C. Garabatos 97, A.T.
Garcia 130, J.R.A. Garcia 45, E. Garcia-Solis 9, C. Gargiulo 33, P. Gasik 97,
A. Gautam 117, M.B. Gay Ducati 66, M. Germain 103, A. Ghimouz124, C. Ghosh134,
M. Giacalone 51, G. Gioachin 30, P. Giubellino 97,56, P. Giubilato 28, A.M.C.
Glaenzer 129, P. Glässel 94, E. Glimos 121, D.J.Q. Goh76, V. Gonzalez 136, M.
Gorgon 2, K. Goswami 48, S. Gotovac34, V. Grabski 67, L.K. Graczykowski 135,
E. Grecka 86, A. Grelli 59, C. Grigoras 33, V. Grigoriev 142, S. Grigoryan
143,1, F. Grosa 33, J.F. Grosse-Oetringhaus 33, R. Grosso 97, D. Grund 36,
N.A. Grunwald94, G.G. Guardiano 111, R. Guernane 73, M. Guilbaud 103, K.
Gulbrandsen 83, T. Gundem 64, T. Gunji 123, W. Guo 6, A. Gupta 91, R. Gupta
91, R. Gupta 48, S.P. Guzman 45, K. Gwizdziel 135, L. Gyulai 138, C.
Hadjidakis 130, F.U. Haider 91, S. Haidlova 36, H. Hamagaki 76, A. Hamdi 74,
Y. Han 140, B.G. Hanley 136, R. Hannigan 108, J. Hansen 75, M.R. Haque 135,
J.W. Harris 139, A. Harton 9, H. Hassan 116, D. Hatzifotiadou 51, P. Hauer 43,
L.B. Havener 139, S.T. Heckel 95, E. Hellbär 97, H. Helstrup 35, M. Hemmer 64,
T. Herman 36, G. Herrera Corral 8, F. Herrmann137, S. Herrmann 127, K.F.
Hetland 35, B. Heybeck 64, H. Hillemanns 33, B. Hippolyte 128, F.W. Hoffmann
70, B. Hofman 59, G.H. Hong 140, M. Horst 95, A. Horzyk 2, Y. Hou 6, P.
Hristov 33, C. Hughes 121, P. Huhn64, L.M. Huhta 116, T.J. Humanic 88, A.
Hutson 115, D. Hutter 39, R. Ilkaev142, H. Ilyas 14, M. Inaba 124, G.M.
Innocenti 33, M. Ippolitov 142, A. Isakov 84,86, T. Isidori 117, M.S. Islam
99, M. Ivanov13, M. Ivanov 97, V. Ivanov 142, K.E. Iversen 75, M. Jablonski 2,
B. Jacak 74, N. Jacazio 26, P.M. Jacobs 74, S. Jadlovska106, J. Jadlovsky106,
S. Jaelani 82, C. Jahnke 111, M.J. Jakubowska 135, M.A. Janik 135, T.
Janson70, S. Ji 17, S. Jia 10, A.A.P. Jimenez 65, F. Jonas 87, D.M. Jones 118,
J.M. Jowett 33,97, J. Jung 64, M. Jung 64, A. Junique 33, A. Jusko 100, M.J.
Kabus 33,135, J. Kaewjai105, P. Kalinak 60, A.S. Kalteyer 97, A. Kalweit 33,
V. Kaplin 142, A. Karasu Uysal 72, D. Karatovic 89, O. Karavichev 142, T.
Karavicheva 142, P. Karczmarczyk 135, E. Karpechev 142, U. Kebschull 70, R.
Keidel 141, D.L.D. Keijdener59, M. Keil 33, B. Ketzer 43, S.S. Khade 48, A.M.
Khan 119,6, S. Khan 16, A. Khanzadeev 142, Y. Kharlov 142, A. Khatun 117, A.
Khuntia 36, B. Kileng 35, B. Kim 104, C. Kim 17, D.J. Kim 116, E.J. Kim 69, J.
Kim 140, J.S. Kim 41, J. Kim 58, J. Kim 69, M. Kim 19, S. Kim 18, T. Kim 140,
K. Kimura 92, S. Kirsch 64, I. Kisel 39, S. Kiselev 142, A. Kisiel 135, J.P.
Kitowski 2, J.L. Klay 5, J. Klein 33, S. Klein 74, C. Klein-Bösing 137, M.
Kleiner 64, T. Klemenz 95, A. Kluge 33, A.G. Knospe 115, C. Kobdaj 105, T.
Kollegger97, A. Kondratyev 143, N. Kondratyeva 142, E. Kondratyuk 142, J.
Konig 64, S.A. Konigstorfer 95, P.J. Konopka 33, G. Kornakov 135, S.D.
Koryciak 2, A. Kotliarov 86, V. Kovalenko 142, M. Kowalski 107, V. Kozhuharov
37, I. Králik 60, A. Kravčáková 38, L. Krcal 33,39, M. Krivda 100,60, F.
Krizek 86, K. Krizkova Gajdosova 33, M. Kroesen 94, M. Krüger 64, D.M. Krupova
36, E. Kryshen 142, V. Kučera 58, C. Kuhn 128, P.G. Kuijer 84, T. Kumaoka124,
D. Kumar134, L. Kumar 90, N. Kumar90, S. Kumar 32, S. Kundu 33, P. Kurashvili
79, A. Kurepin 142, A.B. Kurepin 142, A. Kuryakin 142, S. Kushpil 86, M.J.
Kweon 58, Y. Kwon 140, S.L. La Pointe 39, P. La Rocca 27, A. Lakrathok105, M.
Lamanna 33, R. Langoy 120, P. Larionov 33, E. Laudi 33, L. Lautner 33,95, R.
Lavicka 102, R. Lea 133,55, H. Lee 104, I. Legrand 46, G. Legras 137, J.
Lehrbach 39, T.M. Lelek2, R.C. Lemmon 85, I. León Monzón 109, M.M. Lesch 95,
E.D. Lesser 19, P. Lévai 138, X. Li10, J. Lien 120, R. Lietava 100, I. Likmeta
115, B. Lim 25, S.H. Lim 17, V. Lindenstruth 39, A. Lindner46, C. Lippmann 97,
D.H. Liu 6, J. Liu 118, G.S.S. Liveraro 111, I.M. Lofnes 21, C. Loizides 87,
S. Lokos 107, J. Lomker 59, P. Loncar 34, X. Lopez 126, E. López Torres 7, P.
Lu 97,119, J.R. Luhder 137, M. Lunardon 28, G. Luparello 57, Y.G. Ma 40, M.
Mager 33, A. Maire 128, M.V. Makariev 37, M. Malaev 142, G. Malfattore 26,
N.M. Malik 91, Q.W. Malik20, S.K. Malik 91, L. Malinina VI,143, D. Mallick
130,80, N. Mallick 48, G. Mandaglio 31,53, S.K. Mandal 79, V. Manko 142, F.
Manso 126, V. Manzari 50, Y. Mao 6, R.W. Marcjan 2, G.V. Margagliotti 24, A.
Margotti 51, A. Marín 97, C. Markert 108, P. Martinengo 33, M.I. Martínez 45,
G. Martínez García 103, M.P.P. Martins 110, S. Masciocchi 97, M. Masera 25, A.
Masoni 52, L. Massacrier 130, O. Massen 59, A. Mastroserio 131,50, O. Matonoha
75, S. Mattiazzo 28, A. Matyja 107, C. Mayer 107, A.L. Mazuecos 33, F.
Mazzaschi 25, M. Mazzilli 33, J.E. Mdhluli 122, Y. Melikyan 44, A. Menchaca-
Rocha 67, E. Meninno 102,29, A.S. Menon 115, M. Meres 13, S. Mhlanga113,68, Y.
Miake124, L. Micheletti 33, D.L. Mihaylov 95, K. Mikhaylov 143,142, A.N.
Mishra 138, D. Miśkowiec 97, A. Modak 4, B. Mohanty80, M. Mohisin Khan IV,16,
M.A. Molander 44, S. Monira 135, C. Mordasini 116, D.A. Moreira De Godoy 137,
I. Morozov 142, A. Morsch 33, T. Mrnjavac 33, V. Muccifora 49, S. Muhuri 134,
J.D. Mulligan 74, A. Mulliri23, M.G. Munhoz 110, R.H. Munzer 64, H. Murakami
123, S. Murray 113, L. Musa 33, J. Musinsky 60, J.W. Myrcha 135, B. Naik 122,
A.I. Nambrath 19, B.K. Nandi 47, R. Nania 51, E. Nappi 50, A.F. Nassirpour 18,
A. Nath 94, C. Nattrass 121, M.N. Naydenov 37, A. Neagu20, A. Negru125, L.
Nellen 65, R. Nepeivoda 75, S. Nese 20, G. Neskovic 39, N. Nicassio 50, B.S.
Nielsen 83, E.G. Nielsen 83, S. Nikolaev 142, S. Nikulin 142, V. Nikulin 142,
F. Noferini 51, S. Noh 12, P. Nomokonov 143, J. Norman 118, N. Novitzky 124,
P. Nowakowski 135, A. Nyanin 142, J. Nystrand 21, M. Ogino 76, S. Oh 18, A.
Ohlson 75, V.A. Okorokov 142, J. Oleniacz 135, A.C. Oliveira Da Silva 121, A.
Onnerstad 116, C. Oppedisano 56, A. Ortiz Velasquez 65, J. Otwinowski 107, M.
Oya92, K. Oyama 76, Y. Pachmayer 94, S. Padhan 47, D. Pagano 133,55, G. Paić
65, A. Palasciano 50, S. Panebianco 129, H. Park 124, H. Park 104, J. Park 58,
J.E. Parkkila 33, Y. Patley 47, R.N. Patra91, B. Paul 23, H. Pei 6, T.
Peitzmann 59, X. Peng 11, M. Pennisi 25, S. Perciballi 25, D. Peresunko 142,
G.M. Perez 7, Y. Pestov142, V. Petrov 142, M. Petrovici 46, R.P. Pezzi 103,66,
S. Piano 57, M. Pikna 13, P. Pillot 103, O. Pinazza 51,33, L. Pinsky115, C.
Pinto 95, S. Pisano 49, M. Płoskoń 74, M. Planinic89, F. Pliquett64, M.G.
Poghosyan 87, B. Polichtchouk 142, S. Politano 30, N. Poljak 89, A. Pop 46, S.
Porteboeuf-Houssais 126, V. Pozdniakov 143, I.Y. Pozos 45, K.K. Pradhan 48,
S.K. Prasad 4, S. Prasad 48, R. Preghenella 51, F. Prino 56, C.A. Pruneau 136,
I. Pshenichnov 142, M. Puccio 33, S. Pucillo 25, Z. Pugelova106, S. Qiu 84, L.
Quaglia 25, S. Ragoni 15, A. Rai 139, A. Rakotozafindrabe 129, L. Ramello
132,56, F. Rami 128, S.A.R. Ramirez 45, T.A. Rancien73, M. Rasa 27, S.S.
Räsänen 44, R. Rath 51, M.P. Rauch 21, I. Ravasenga 84, K.F. Read 87,121, C.
Reckziegel 112, A.R. Redelbach 39, K. Redlich V,79, C.A. Reetz 97, A.
Rehman21, F. Reidt 33, H.A. Reme-Ness 35, Z. Rescakova38, K. Reygers 94, A.
Riabov 142, V. Riabov 142, R. Ricci 29, M. Richter 20, A.A. Riedel 95, W.
Riegler 33, A.G. Riffero 25, C. Ristea 63, M.V. Rodriguez 33, M. Rodríguez
Cahuantzi 45, K. Røed 20, R. Rogalev 142, E. Rogochaya 143, T.S. Rogoschinski
64, D. Rohr 33, D. Röhrich 21, P.F. Rojas45, S. Rojas Torres 36, P.S. Rokita
135, G. Romanenko 26, F. Ronchetti 49, A. Rosano 31,53, E.D. Rosas65, K.
Roslon 135, A. Rossi 54, A. Roy 48, S. Roy 47, N. Rubini 26, O.V. Rueda 115,
D. Ruggiano 135, R. Rui 24, P.G. Russek 2, R. Russo 84, A. Rustamov 81, E.
Ryabinkin 142, Y. Ryabov 142, A. Rybicki 107, H. Rytkonen 116, J. Ryu 17, W.
Rzesa 135, O.A.M. Saarimaki 44, S. Sadhu 32, S. Sadovsky 142, J. Saetre 21, K.
Šafařík 36, P. Saha42, S.K. Saha 4, S. Saha 80, B. Sahoo 47, B. Sahoo 48, R.
Sahoo 48, S. Sahoo61, D. Sahu 48, P.K. Sahu 61, J. Saini 134, K. Sajdakova38,
S. Sakai 124, M.P. Salvan 97, S. Sambyal 91, D. Samitz 102, I. Sanna 33,95,
T.B. Saramela110, P. Sarma 42, V. Sarritzu 23, V.M. Sarti 95, M.H.P. Sas 139,
J. Schambach 87, H.S. Scheid 64, C. Schiaua 46, R. Schicker 94, A. Schmah97,
C. Schmidt 97, H.R. Schmidt93, M.O. Schmidt 33, M. Schmidt93, N.V. Schmidt 87,
A.R. Schmier 121, R. Schotter 128, A. Schröter 39, J. Schukraft 33, K. Schweda
97, G. Scioli 26, E. Scomparin 56, J.E. Seger 15, Y. Sekiguchi123, D. Sekihata
123, M. Selina 84, I. Selyuzhenkov 97, S. Senyukov 128, J.J. Seo 94,58, D.
Serebryakov 142, L. Šerkšnytė 95, A. Sevcenco 63, T.J. Shaba 68, A. Shabetai
103, R. Shahoyan33, A. Shangaraev 142, A. Sharma90, B. Sharma 91, D. Sharma
47, H. Sharma 54,107, M. Sharma 91, S. Sharma 76, S. Sharma 91, U. Sharma 91,
A. Shatat 130, O. Sheibani115, K. Shigaki 92, M. Shimomura77, J. Shin12, S.
Shirinkin 142, Q. Shou 40, Y. Sibiriak 142, S. Siddhanta 52, T. Siemiarczuk
79, T.F. Silva 110, D. Silvermyr 75, T. Simantathammakul105, R. Simeonov 37,
B. Singh91, B. Singh 95, K. Singh 48, R. Singh 80, R. Singh 91, R. Singh 48,
S. Singh 16, V.K. Singh 134, V. Singhal 134, T. Sinha 99, B. Sitar 13, M.
Sitta 132,56, T.B. Skaali20, G. Skorodumovs 94, M. Slupecki 44, N. Smirnov
139, R.J.M. Snellings 59, E.H. Solheim 20, J. Song 115, C. Sonnabend 33,97, F.
Soramel 28, A.B. Soto-hernandez 88, R. Spijkers 84, I. Sputowska 107, J. Staa
75, J. Stachel 94, I. Stan 63, P.J. Steffanic 121, S.F. Stiefelmaier 94, D.
Stocco 103, I. Storehaug 20, P. Stratmann 137, S. Strazzi 26, A. Sturniolo
31,53, C.P. Stylianidis84, A.A.P. Suaide 110, C. Suire 130, M. Sukhanov 142,
M. Suljic 33, R. Sultanov 142, V. Sumberia 91, S. Sumowidagdo 82, S. Swain61,
I. Szarka 13, M. Szymkowski 135, S.F. Taghavi 95, G. Taillepied 97, J.
Takahashi 111, G.J. Tambave 80, S. Tang 6, Z. Tang 119, J.D. Tapia Takaki 117,
N. Tapus125, L.A. Tarasovicova 137, M.G. Tarzila 46, G.F. Tassielli 32, A.
Tauro 33, G. Tejeda Muñoz 45, A. Telesca 33, L. Terlizzi 25, C. Terrevoli 115,
S. Thakur 4, D. Thomas 108, A. Tikhonov 142, A.R. Timmins 115, M. Tkacik106,
T. Tkacik 106, A. Toia 64, R. Tokumoto92, K. Tomohiro92, N. Topilskaya 142, M.
Toppi 49, T. Tork 130, V.V. Torres 103, A.G. Torres Ramos 32, A. Trifiró
31,53, A.S. Triolo 33,31,53, S. Tripathy 51, T. Tripathy 47, S. Trogolo 33, V.
Trubnikov 3, W.H. Trzaska 116, T.P. Trzcinski 135, A. Tumkin 142, R. Turrisi
54, T.S. Tveter 20, K. Ullaland 21, B. Ulukutlu 95, A. Uras 127, G.L. Usai 23,
M. Vala38, N. Valle 22, L.V.R. van Doremalen59, M. van Leeuwen 84, C.A. van
Veen 94, R.J.G. van Weelden 84, P. Vande Vyvre 33, D. Varga 138, Z. Varga 138,
M. Vasileiou 78, A. Vasiliev 142, O. Vázquez Doce 49, V. Vechernin 142, E.
Vercellin 25, S. Vergara Limón45, R. Verma47, L. Vermunt 97, R. Vértesi 138,
M. Verweij 59, L. Vickovic34, Z. Vilakazi122, O. Villalobos Baillie 100, A.
Villani 24, A. Vinogradov 142, T. Virgili 29, M.M.O. Virta 116, V.
Vislavicius75, A. Vodopyanov 143, B. Volkel 33, M.A. Völkl 94, K. Voloshin142,
S.A. Voloshin 136, G. Volpe 32, B. von Haller 33, I. Vorobyev 95, N. Vozniuk
142, J. Vrláková 38, J. Wan40, C. Wang 40, D. Wang40, Y. Wang 40, Y. Wang 6,
A. Wegrzynek 33, F.T. Weiglhofer39, S.C. Wenzel 33, J.P. Wessels 137, S.L.
Weyhmiller 139, J. Wiechula 64, J. Wikne 20, G. Wilk 79, J. Wilkinson 97, G.A.
Willems 137, B. Windelband 94, M. Winn 129, J.R. Wright 108, W. Wu40, Y. Wu
119, R. Xu 6, A. Yadav 43, A.K. Yadav 134, S. Yalcin 72, Y. Yamaguchi 92, S.
Yang21, S. Yano 92, Z. Yin 6, I.-K. Yoo 17, J.H. Yoon 58, H. Yu12, S. Yuan21,
A. Yuncu 94, V. Zaccolo 24, C. Zampolli 33, F. Zanone 94, N. Zardoshti 33, A.
Zarochentsev 142, P. Závada 62, N. Zaviyalov142, M. Zhalov 142, B. Zhang 6, C.
Zhang 129, L. Zhang 40, S. Zhang 40, X. Zhang 6, Y. Zhang119, Z. Zhang 6, M.
Zhao 10, V. Zherebchevskii 142, Y. Zhi10, D. Zhou 6, Y. Zhou 83, J. Zhu 54,6,
Y. Zhu6, S.C. Zugravel 56, N. Zurlo 133,55

## Affiliation Notes

I Also at: Max-Planck-Institut für Physik, Munich, Germany
II Also at: Italian National Agency for New Technologies, Energy and
Sustainable Economic Development (ENEA), Bologna, Italy
III Also at: Dipartimento DET del Politecnico di Torino, Turin, Italy
IV Also at: Department of Applied Physics, Aligarh Muslim University, Aligarh,
India
V Also at: Institute of Theoretical Physics, University of Wroclaw, Poland
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 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 COMSATS University Islamabad, Islamabad, Pakistan
15 Creighton University, Omaha, Nebraska, United States
16 Department of Physics, Aligarh Muslim University, Aligarh, India
17 Department of Physics, Pusan National University, Pusan, Republic of Korea
18 Department of Physics, Sejong University, Seoul, Republic of Korea
19 Department of Physics, University of California, Berkeley, California,
United States
20 Department of Physics, University of Oslo, Oslo, Norway
21 Department of Physics and Technology, University of Bergen, Bergen, Norway
22 Dipartimento di Fisica, Università di Pavia, Pavia, Italy
23 Dipartimento di Fisica dell’Università and Sezione INFN, Cagliari, Italy
24 Dipartimento di Fisica dell’Università and Sezione INFN, Trieste, Italy
25 Dipartimento di Fisica dell’Università and Sezione INFN, Turin, Italy
26 Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN,
Bologna, Italy
27 Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN,
Catania, Italy
28 Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN,
Padova, Italy
29 Dipartimento di Fisica ‘E.R. Caianiello’ dell’Università and Gruppo
Collegato INFN, Salerno, Italy
30 Dipartimento DISAT del Politecnico and Sezione INFN, Turin, Italy
31 Dipartimento di Scienze MIFT, Università di Messina, Messina, Italy
32 Dipartimento Interateneo di Fisica ‘M. Merlin’ and Sezione INFN, Bari,
Italy
33 European Organization for Nuclear Research (CERN), Geneva, Switzerland
34 Faculty of Electrical Engineering, Mechanical Engineering and Naval
Architecture, University of Split, Split, Croatia
35 Faculty of Engineering and Science, Western Norway University of Applied
Sciences, Bergen, Norway
36 Faculty of Nuclear Sciences and Physical Engineering, Czech Technical
University in Prague, Prague, Czech Republic
37 Faculty of Physics, Sofia University, Sofia, Bulgaria
38 Faculty of Science, P.J. Šafárik University, Košice, Slovak Republic
39 Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe-
Universität Frankfurt, Frankfurt, Germany
40 Fudan University, Shanghai, China
41 Gangneung-Wonju National University, Gangneung, Republic of Korea
42 Gauhati University, Department of Physics, Guwahati, India
43 Helmholtz-Institut für Strahlen- und Kernphysik, Rheinische Friedrich-
Wilhelms-Universität Bonn, Bonn, Germany
44 Helsinki Institute of Physics (HIP), Helsinki, Finland
45 High Energy Physics Group, Universidad Autónoma de Puebla, Puebla, Mexico
46 Horia Hulubei National Institute of Physics and Nuclear Engineering,
Bucharest, Romania
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 University of Cape Town, Cape Town, South Africa
114 University of Derby, Derby, United Kingdom
115 University of Houston, Houston, Texas, United States
116 University of Jyväskylä, Jyväskylä, Finland
117 University of Kansas, Lawrence, Kansas, United States
118 University of Liverpool, Liverpool, United Kingdom
119 University of Science and Technology of China, Hefei, China
120 University of South-Eastern Norway, Kongsberg, Norway
121 University of Tennessee, Knoxville, Tennessee, United States
122 University of the Witwatersrand, Johannesburg, South Africa
123 University of Tokyo, Tokyo, Japan
124 University of Tsukuba, Tsukuba, Japan
125 University Politehnica of Bucharest, Bucharest, Romania
126 Université Clermont Auvergne, CNRS/IN2P3, LPC, Clermont-Ferrand, France
127 Université de Lyon, CNRS/IN2P3, Institut de Physique des 2 Infinis de
Lyon, Lyon, France
128 Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000 Strasbourg, France,
Strasbourg, France
129 Université Paris-Saclay, Centre d’Etudes de Saclay (CEA), IRFU, Départment
de Physique Nucléaire (DPhN), Saclay, France
130 Université Paris-Saclay, CNRS/IN2P3, IJCLab, Orsay, France
131 Università degli Studi di Foggia, Foggia, Italy
132 Università del Piemonte Orientale, Vercelli, Italy
133 Università di Brescia, Brescia, Italy
134 Variable Energy Cyclotron Centre, Homi Bhabha National Institute, Kolkata,
India
135 Warsaw University of Technology, Warsaw, Poland
136 Wayne State University, Detroit, Michigan, United States
137 Westfälische Wilhelms-Universität Münster, Institut für Kernphysik,
Münster, Germany
138 Wigner Research Centre for Physics, Budapest, Hungary
139 Yale University, New Haven, Connecticut, United States
140 Yonsei University, Seoul, Republic of Korea
141 Zentrum für Technologie und Transfer (ZTT), Worms, Germany
142 Affiliated with an institute covered by a cooperation agreement with CERN
143 Affiliated with an international laboratory covered by a cooperation
agreement with CERN.