2018 090 30 April

Anisotropic flow in Xe–Xe collisions at $\sqrt{s_{\rm{NN}}}=5.44$ TeV

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

The first measurements of anisotropic flow coefficients $v_{\rm{n}}$ for mid-
rapidity charged particles in Xe–Xe collisions at $\sqrt{s_{\rm{NN}}}=5.44$
TeV are presented. Comparing these measurements to those from Pb–Pb collisions
at $\sqrt{s_{\rm{NN}}}=5.02$ TeV, $v_{2}$ is found to be suppressed for mid-
central collisions at the same centrality, and enhanced for central
collisions. The values of $v_{3}$ are generally larger in Xe–Xe than in Pb–Pb
at a given centrality. These observations are consistent with expectations
from hydrodynamic predictions. When both $v_{2}$ and $v_{3}$ are divided by
their corresponding eccentricities for a variety of initial state models, they
generally scale with transverse density when comparing Xe–Xe and Pb–Pb, with
some deviations observed in central Xe–Xe and Pb–Pb collisions. These results
assist in placing strong constraints on both the initial state geometry and
medium response for relativistic heavy-ion collisions.

##  1 Introduction

Relativistic heavy-ion collisions are believed to create a Quark–Gluon Plasma
(QGP), a state of matter consisting of deconfined color charges. The pressure
gradients in the QGP medium convert spatial anisotropies in initial conditions
of the collision to momentum anisotropies of produced particles via multiple
interactions, a phenomenon referred to as anisotropic flow [1]. The magnitude
of anisotropic flow can be characterized by the flow coefficients
($v_{\rm{n}}$), which are obtained from a Fourier expansion of the angular
distribution of produced particles [2]

$\frac{\rm{d}\it{N}}{\rm{d}\varphi}\propto
1+2\sum_{\rm{n}=1}^{\infty}v_{\rm{n}}\cos[\rm{n}(\varphi-\Psi_{\rm{n}})],$ (1)

where $\varphi$ is the azimuthal angle of the produced particle, n is the flow
harmonic, and $\Psi_{\rm{n}}$ is the corresponding symmetry plane angle. For
the second and third order flow coefficients ($v_{2}$ and $v_{3}$), various
hydrodynamical calculations have demonstrated the approximate relation [3, 4,
5, 6, 7]

$v_{\rm{n}}\approx\kappa_{\rm{n}}\,\varepsilon_{\rm{n}},$ (2)

where $\varepsilon_{\rm{n}}$ is the corresponding eccentricity coefficient,
which governs the shape of the initial state. The variable $\kappa_{\rm{n}}$
encodes the response of the medium, and in particular is sensitive to the
shear viscosity over entropy density ratio ($\eta/s$) and the lifetime of the
system. When values of $\eta/s$ are finite, this inhibits the development of
momentum anisotropies. It has also received a broader interest, as its lower
bound is different for perturbative QCD [8] and AdS/CFT [9]. Experimental data
from both the Relativistic Heavy-Ion Collider (RHIC) and the Large Hadron
Collider (LHC) [10, 11, 12, 13, 14, 15, 16], have implied values of $\eta/s$
close to the AdS/CFT minimum of $1/4\pi$ [9], suggesting that the QGP behaves
as a near perfect fluid. However, uncertainties in the modeling of the initial
state have prevented the extraction of more precise information [17, 18, 19].

The data set from the LHC Xe–Xe run completed in 2017 may provide an
opportunity to further constrain $\eta/s$. For mid-central collisions, various
initial state models predict Xe–Xe collisions at $\sqrt{s_{\rm{NN}}}=5.44$ TeV
and Pb–Pb collisions at $\sqrt{s_{\rm{NN}}}=5.02$ TeV have similar values of
$\varepsilon_{2}$ at a given centrality [20, 21]. However, at the same
centrality the Xe–Xe system size is smaller than Pb–Pb, and the impact of a
finite $\eta/s$ suppresses $\kappa_{2}$ by $1/R$, where $R$ corresponds to the
transverse size of the system [21]. Therefore, ratios of Xe–Xe/Pb–Pb $v_{2}$
coefficients in the mid-centrality range could be directly sensitive to
$\eta/s$, with the influence of the initial state largely cancelling out.
Furthermore, hydrodynamical calculations have shown that
$v_{\rm{n}}/\varepsilon_{\rm{n}}$ increases monotonically with the transverse
density $1/S$ d$N_{\rm{ch}}$/d$\eta$ (d$N_{\rm{ch}}$/d$\eta$ is the charged
particle density and $S$ is the transverse area) across different collision
energies and systems [22, 23, 17]. Both $\varepsilon_{\rm{n}}$ and $S$ are
quantities that are obtained from an initial state model. A violation of the
scaling can be the result of incorrect modeling of the density ($S$) or the
azimuthal geometry ($\varepsilon_{\rm{n}}$). That being the case, such an
exercise where one compares $v_{\rm{n}}/\varepsilon_{\rm{n}}$ as a function of
$1/S$ d$N_{\rm{ch}}$/d$\eta$ for both Xe–Xe and Pb–Pb collisions can further
constrain the initial state. Similar investigations using RHIC data from Cu–Cu
and Au–Au collisions led to important refinements in this regard, such as the
relevance of initial state fluctuations [24, 25, 26] and realization of finite
values of $\varepsilon_{\rm{n}}$ for higher order odd values of n ($\rm{n}\geq
3$) [27]. On the other hand, an observed violation of this scaling using
experimental data (assuming the initial state predictions are accurate) may
reveal deficiencies in the aforementioned hydrodynamical modeling. Addressing
how the information from Xe–Xe collisions can shed more light on both the
medium response and initial state, is the central goal of this Letter.

##  2 Analysis details

The two data sets analyzed were recorded by the ALICE detector at the LHC
during the Xe–Xe (2017) and Pb–Pb (2015) runs at the center of mass energies
of $\sqrt{s_{\rm NN}}=5.44$ TeV and $\sqrt{s_{\rm NN}}=5.02$ TeV,
respectively. A more detailed description of the ALICE detector and its
performance can be found elsewhere [28, 29, 30]. Charged-particle tracks at
mid-rapidity are reconstructed using the Time Projection Chamber (TPC) [28,
31], the primary tracking detector. Information from the Inner Tracking System
(ITS) [28, 32] is used to improve the spatial and momentum resolution of the
TPC tracks. This helps to reject the background from secondaries, which
originate from weak decays, conversions, secondary hadronic interactions in
the detector material, and pile-up. The two innermost layers of the ITS, the
Silicon Pixel Detector (SPD), are employed for triggering and event selection.
The two V0 counters [28, 33], each containing 32 scintillator tiles and
covering $2.8<\eta<5.1$ (V0A) and $-3.7<\eta<-1.7$ (V0C), provide information
for triggering, event selection, the determination of centrality and the
symmetry plane angle [34]. The trigger conditions and the event selection
criteria are described elsewhere [29]. An offline event selection is applied
to remove beam-induced background (i.e., beam-gas events) and pile-up events,
which are rejected using information from the ITS and V0 detectors. Primary
vertex information is provided by tracks reconstructed in the ITS and TPC.
Only events with a reconstructed primary vertex within 10 cm from the center
of the detector along the beam axis (that position is denoted by $PV_{z}$) are
used in the analysis to ensure a uniform acceptance in $\eta$. The resulting
event sample available for analysis consisted of $\sim 1.0$M Xe–Xe events in
the 0–70% centrality range, and $\sim 67$M events for Pb–Pb collisions in the
same centrality interval.

The charged tracks at mid-rapidity used to determine the flow coefficients
have the kinematic values $0.2<p_{\rm{T}}<10$ GeV/$c$ and $|\eta|<0.8$. The
track fit uses an SPD hit if one exists within the trajectory, if not, they
are constrained to the primary vertex. Such a configuration leads to a
relatively flat azimuthal acceptance. Track quality is ensured by requiring
tracks to have at least 70 TPC space points out of a maximum of 159 with an
average $\chi^{2}$ per degree-of-freedom for the track fit lower than 2. In
addition, the distances of closest approach to the primary vertex in the $xy$
plane and $z$ direction are required to be less than 2.4 cm and 3.2 cm,
respectively. The charged particle track reconstruction efficiency is
estimated from HIJING simulations [35, 36] combined with a GEANT3 [37]
transport model.

In order to extract the flow coefficients from charged particles produced in
either Xe–Xe or Pb–Pb collisions, the Scalar Product [38] and Generic
Framework [39, 40] methods are used, which evaluate $m$ particle flow
coefficients $v_{\rm n}\\{m\\}$. The $v_{\rm n}\\{m\\}$ coefficients
characterize flow fluctuations, and are sensitive to correlations not related
to the common symmetry planes $\Psi_{\rm n}$ (“non-flow”), such as those due
to resonances and jets. The contribution from flow fluctuations was shown to
decrease $v_{\rm n}\\{m\geq 4\\}$ and increase $v_{\rm n}\\{2\\}$ relative to
$\langle v_{\rm n}\rangle$ [41]. In the absence of flow fluctuations and non-
flow, $v_{\rm n}\\{m\\}$ is independent of $m$. Both methods feature
calculations involving the ${\bf Q}_{\rm n}$-vector which is defined as

${\bf Q}_{\rm{n}}=\sum_{i}^{M}e^{\rm{in}\varphi_{\it{i}}},$ (3)

where $M$ is the number of particles used to build the ${\bf Q}_{\rm
n}$-vector in a single event, and $\varphi_{i}$ is the azimuthal angle of
particle $i$. For the Scalar Product method, the flow coefficients $v_{\rm n}$
(denoted as $v_{\rm n}\\{2,|\Delta\eta|>2\\}$) are measured using

$v_{\rm{n}}\\{{\rm SP}\\}=\langle\langle{\bf u}_{{\rm{n}},k}{\bf
Q}_{\rm{n}}^{*}\rangle\rangle\Bigg{/}\sqrt{\frac{\langle{\bf Q}_{\rm{n}}{\bf
Q}_{\rm{n}}^{\rm A*}\rangle\langle{\bf Q}_{\rm{n}}{\bf Q}_{\rm{n}}^{\rm
B*}\rangle}{\langle{\bf Q}_{\rm{n}}^{\rm A}{\bf Q}_{\rm{n}}^{\rm
B*}\rangle}},$ (4)

where ${\bf u}_{{\rm{n}},k}=\exp({\rm{in}}\varphi_{k})$ is the unit flow
vector of the particle of interest $k$. The brackets $\langle\cdots\rangle$
denote an average over all events, the double brackets
$\langle\langle\cdots\rangle\rangle$ an average over all particles in all
events, and ∗ the complex conjugate. The vector ${\bf Q}_{\rm{n}}$ is
calculated from the azimuthal distribution of the energy deposition measured
in the V0A. Its $x$ and $y$ components are given by

$Q_{{\rm n},x}=\sum_{j}w_{j}\cos({\rm n}\varphi_{j}),\;Q_{{\rm
n},y}=\sum_{j}w_{j}\sin({\rm n}\varphi_{j}),$ (5)

where the sum runs over all channels $j$ of the V0A detector ($j=1-32$),
$\varphi_{j}$ is the azimuthal angle of channel $j$, and $w_{j}$ is the
amplitude measured in channel $j$. The vectors ${\bf Q}_{\rm{n}}^{\rm A}$ and
${\bf Q}_{\rm{n}}^{\rm B}$ are determined from the azimuthal distribution of
the energy deposition measured in the V0C and the azimuthal distribution of
the tracks reconstructed in the ITS and TPC, respectively. The large gap in
pseudo-rapidity ($|\Delta\eta|>2.0$) between the charged particles in the TPC
used to determine $v_{\rm n}$ and those in the V0A greatly suppresses non-flow
effects. The course $\varphi$ segmentation of the V0 leads to a deterioration
of resolution for higher order flow coefficients ($\rm{n}\geq 4$), and
prevents their measurements.

The flow coefficients $v_{\rm{n}}\\{m\\}$ from two- and multi-particle
cumulants can also be obtained using the Generic Framework. The calculations
using the ${\bf Q}_{\rm n}$-vector are generally much more complex than those
shown in Eq. 4, and can be found elsewhere [40]. This approach provides a
capability for the necessary corrections of systematic biases from non-uniform
detector acceptance and tracking inefficiencies, and it has been used in other
measurements [16, 42, 43]. It can also be used to suppress non-flow by placing
an $\eta$-gap between various ${\bf Q}_{\rm n}$-vectors. The non-flow
contribution to $v_{\rm n}\\{m\geq 4\\}$ in this framework is strongly
suppressed by construction without the use of an $\eta$-gap. The newly
developed sub-event methods [44, 45], provide additional means of suppressing
any residual non-flow contributions for $v_{\rm n}\\{m\geq 4\\}$. The Generic
Framework is used for measurements of $v_{\rm n}\\{2,|\Delta\eta|>1\\}$ and
$v_{\rm n}\\{m\geq 4\\}$ (including $v_{2}\\{4,\text{3 sub-event}\\}$) from
charged tracks in the TPC acceptance only.

When constructing Eq. 3 from charged particles to determine
$v_{\rm{n}}\\{m\\}$, particle-wise weights are placed to account for non-
uniformities in the $\varphi$ acceptance and $p_{\rm{T}}$ dependent
efficiencies. The systematic uncertainties for $v_{\rm{n}}\\{m\\}$ have three
sources: event selection, track type/selection, and the ${\bf
Q}_{\rm{n}}$-vector correction procedure. The event selection contributions
were determined by varying the $PV_{z}$ ranges, not applying the pile-up
rejection criteria, and using a different detector system (ITS) for centrality
determination. The track type/selection uncertainties were determined by using
tracks with TPC information only or tracks that always have an ITS hit (which
changes the contributions from secondary particles), changing the track
quality cuts (such as the minimum number of TPC space points), and comparing
any differences between determining ${\bf Q}_{\rm{n}}$ or ${\bf u}_{n,k}$ from
positive or negative only TPC tracks (both charge signs are used to build a
flow vector for the final results). Finally, the uncertainties in ${\bf
Q}_{\rm{n}}$-vector correction procedure contribution are due to uncertainties
in the $p_{\rm{T}}$ dependent efficiencies. The individual sources of
systematic uncertainty are assumed uncorrelated and are added in quadrature to
obtain the overall estimated systematic uncertainties. For the
$p_{\rm{T}}$-integrated $v_{\rm{n}}\\{m\\}$ coefficients, the total systematic
uncertainties are typically 2–3%, and smaller than the marker size in the
corresponding figures. The systematic uncertainties for the
$p_{\rm{T}}$-differential coefficients can be larger, and are denoted by boxes
in the relevant figures.

Figure 1: Top panel: Charged particle $v_{\rm n}$ integrated over the
transverse momentum range $0.2<p_{\rm{T}}<3.0$ GeV/$c$ as a function of
centrality from Xe–Xe collisions. The various techniques are explained in the
text. Only statistical uncertainties are visible (thin vertical lines). Bottom
panel: Ratios of $v_{2}\\{4\\}$/$v_{2}\\{2\\}$ compared to some theoretical
predictions. The hydrodynamic predictions use a shear viscosity over entropy
ratio $\eta/s=0.047$ and initial conditions from the TRENTo model [21, 46].
For $v_{2}\\{2\\}$, the ALICE measurements implement a $|\Delta\eta|>2.0$ gap
which is not used in the models.

##  3 Results

The top panel of Fig. 1 shows two- and multi-particle $p_{\rm{T}}$-integrated
$v_{\rm{n}}\\{m\\}$ coefficients from Xe–Xe collisions at
$\sqrt{s_{\rm{NN}}}=5.44$ TeV as a function of centrality. A stronger
dependence of $v_{2}$ with centrality compared with $v_{3}$ or $v_{4}$, also
observed in Pb–Pb collisions at LHC energies [13, 14, 15, 16], is expected
based on simple considerations of how the almond shaped overlap region changes
with centrality for A–A collisions. Given that near-side non-flow correlations
(where the particles involved have similar values of $\varphi$ and $\eta$) are
expected to be the largest non-flow contribution, the similarities observed
for $v_{\rm{n}}\\{2,|\Delta\eta|>2\\}$ and $v_{\rm{n}}\\{2,|\Delta\eta|>1\\}$
indicate non-flow is strongly suppressed by a gap of one unit of
pseudorapidity. The extracted values of $v_{2}\\{m\geq 4\\}$ use ${\bf
Q}_{\rm{n}}$-vectors without any $\eta$ gaps. The $v_{2}\\{4,\text{3 sub-
event}\\}$ results have $\eta$ gaps between the ${\bf Q}_{\rm{n}}$-vectors to
suppress non-flow. The sub-event regions are $-0.8<\eta\leq-0.4$,
$-0.4<\eta\leq 0.4$ and $0.4<\eta\leq 0.8$. The equivalence with
$v_{2}\\{4\\}$ (no $\eta$ separation) demonstrates that such a gap is actually
not required for these flow coefficients. Given all those observations
regarding non-flow, one can interpret differences between $v_{2}\\{2\\}$ and
$v_{2}\\{4\\}$, $v_{2}\\{6\\}$, $v_{2}\\{8\\}$ to be largely driven by flow
fluctuations [41]. To quantify these differences, in the bottom panel of Fig.
1, the ratio $v_{2}\\{4\\}$/$v_{2}\\{2,|\Delta\eta|>2\\}$ is shown, which is
found to decrease for central collisions. The results are compared to a
hydrodynamic calculation in the same panel, which uses an $\eta/s=0.047$ to
model the medium response [21]. For these hydrodynamic calculations, the
TRENTo initial condition model [46] is used to determine the eccentricities.
The justification for using $\rm{p}=0$ is described later in the Letter. The
initial condition model implements a 129Xe $\beta_{2}$ deformation
($\beta_{2}=0.162$), which is predicted for the 129Xe nucleus [47], but has
never been measured directly. It modifies the Woods-Saxon distribution as
follows [48]

$\rho(r,\theta)=\frac{\rho_{0}}{1+e^{(r-R_{0}-R_{0}\beta_{2}Y_{20}(\theta))/a}},$
(6)

where $\rho_{0}$ is the density at the center of the nucleus, $R_{0}$ the
nuclear radius, $r$ is the distance away from the center, $Y_{20}$ is a Bessel
function of the second kind, and $a$ is the skin depth. According to Eq. 2,
the ratio of flow coefficients $v_{2}\\{4\\}$/$v_{2}\\{2\\}$ should be
identical to the ratio of initial state eccentricities
$\varepsilon_{2}\\{4\\}/\varepsilon_{2}\\{2\\}$. To test this relation, the
bottom panel of Fig. 1 also shows the flow coefficient ratios and the
eccentricity ratios from the same model. The difference between the two curves
shows that Eq. 2 only holds approximately. The hydrodynamic calculations
generally predict lower ratios compared to the data, with the largest
deviations being in the semi-central region (10–50%).

Figure 2: Top panel: Comparisons of charged particle $v_{\rm n}\\{2\\}$
integrated over the transverse momentum range $0.2<p_{\rm{T}}<3.0$ GeV/$c$ as
a function of centrality from Xe–Xe and Pb–Pb collisions. Middle panel: Ratio
of $v_{\rm n}\\{2\\}$(Xe–Xe/Pb–Pb) coefficients. Bottom panel: Double ratio of
data and theory. Hydrodynamical model predictions from EKRT [20] and
V-USPHYDRO [21] are shown. In all cases, only statistical uncertainties are
visible (thin vertical lines). Figure 3: Top panel: Comparisons of charged
particle $v_{\rm n}\\{2\\}$ integrated over the transverse momentum range
$0.2<p_{\rm{T}}<3.0$ GeV/$c$ from Xe–Xe and Pb–Pb collisions for finer
centrality bins in central collisions. Statistical and systematic
uncertainties are shown as lines and boxes, respectively. Bottom panel:
Corresponding ratio of $v_{\rm n}\\{2\\}$(Xe–Xe/Pb–Pb) coefficients.

Figure 2 shows comparisons of two-particle $p_{\rm{T}}$-integrated
$v_{\rm{n}}\\{2\\}$ coefficients from Xe–Xe and Pb–Pb collisions as a function
of centrality. The differences between the two systems are typically within
10% except for $v_{2}\\{2\\}$ in central 0–5% collisions where the Xe–Xe
values are $\sim$ 35% higher. For the V-USPHYDRO and EKRT models [20, 21]
shown, both sets of the used initial condition models demonstrate
$\varepsilon_{2}\\{2\\}$(Xe–Xe)/$\varepsilon_{2}\\{2\\}$(Pb–Pb) $\sim$ 1 for
the semi-central range 20–60% (not shown in the figure). However,
$v_{2}\\{2\\}$(Xe–Xe)/$v_{2}\\{2\\}$(Pb–Pb) $\sim$ 0.9 from the data, which
might be the result of the viscous effects described in the Introduction. When
implementing the hydrodynamical response, both models also show a similar
suppression for the smaller Xe–Xe system, albeit with differences of up to
$\sim$ 5% compared to the data. On the other hand, despite using different
values of $\eta/s$, both models predict similar ratios in the semi-central
range. Some assumptions used in each of the models (such as the freeze-out
temperature) are different, and investigating the impact of those assumptions
on $v_{2}\\{2\\}$(Xe–Xe)/$v_{2}\\{2\\}$(Pb–Pb) ratio should be a topic of
further theoretical investigations.

Both sets of model predictions (V-USPHYDRO and EKRT) implement a 129Xe
deformation using $\beta_{2}=0.162$. The value of $\beta_{2}$ is zero for the
208Pb nucleus, as it is a double magic nucleus. The deformation for the Xe–Xe
V-USPHYDRO predictions contributes $\sim$ 20% to the observed $v_{2}\\{2\\}$
for central collisions (compared with the case where no deformation is
implemented), and has no impact on $v_{2}\\{2\\}$ for centralities above 15%.
Regarding $v_{3}\\{2\\}$, it is generally larger in Xe–Xe, which reflects the
fact that the initial conditions from both models show
$\varepsilon_{3}\\{2\\}$(Xe–Xe) $>$ $\varepsilon_{3}\\{2\\}$(Pb–Pb) at a given
centrality for the entire centrality range presented. The hydrodynamic
predictions for $v_{3}\\{2\\}$ are similar for the two models, with maximum
deviations of $\sim 5$ % from the data. The $\beta_{3}$ deformation for both
the Xe and Pb nuclei is zero [47], with both models assuming such a value.

In Fig. 3, similar comparisons are made in finer centrality bins as compared
with Fig. 2 for central collisions. The transition where Xe–Xe
$v_{\rm{2}}\\{2\\}$ becomes larger than the Pb–Pb values occurs for a
centrality of $\sim$ 15%. For 0–1% central collisions, where the overlap
geometry is expected to play a minimal role for both systems,
$v_{\rm{2}}\\{2\\}$ is $\sim$ 60% larger for Xe–Xe collisions. In terms of the
initial state, this is expected for two reasons. The first relates to the fact
that the 129Xe nucleus is deformed while the 208Pb nucleus is not, and the
second relates to the role of initial state fluctuations and the number of
sources that contribute to $\varepsilon_{n}\\{2\\}$. It has been previously
shown that $\varepsilon_{n}\\{2\\}$ decreases as the number of sources
increases for a spherical system [49], and if the number of sources were
infinite, then $\varepsilon_{n}\\{2\\}$ would be zero in this centrality
range. Given that a very central Pb–Pb collision is expected to have more
sources than a very central Xe–Xe collision, fluctuations would be expected to
give rise to larger values of $\varepsilon_{2}\\{2\\}$ for the latter. The
same line of reasoning can explain why $v_{\rm{3}}\\{2\\}$ is observed to be
larger in Xe–Xe compared to Pb–Pb in the same centrality interval.

Figure 4: The $p_{\rm{T}}$-differential $v_{2}$ for charged particles from
Xe–Xe collisions at $\sqrt{s_{\rm{NN}}}=5.44$ TeV and Pb–Pb collisions at
$\sqrt{s_{\rm{NN}}}=5.02$ TeV for various centrality classes. Statistical and
systematic uncertainties are shown as lines and boxes, respectively. Figure 5:
The $p_{\rm{T}}$-differential $v_{3}$ for charged particles from Xe–Xe
collisions at $\sqrt{s_{\rm{NN}}}=5.44$ TeV and Pb–Pb collisions at
$\sqrt{s_{\rm{NN}}}=5.02$ TeV for various centrality classes. Statistical and
systematic uncertainties are shown as lines and boxes, respectively.

Figure 4 shows comparisons of two-particle $p_{\rm{T}}$-differential
$v_{\rm{2}}\\{2,|\Delta\eta|>2\\}$ coefficients from Xe–Xe and Pb–Pb
collisions in various centrality bins. As mentioned, the larger $|\Delta\eta|$
gap measurements use both the TPC and the V0 detectors, which maximizes the
number of particles used to build the ${\bf Q}_{\rm{n}}$-vectors. The
corresponding reduction in statistical uncertainties is particularly useful
for the higher $p_{\rm{T}}$ measurements. As expected, the centrality
dependence of $v_{2}\\{2,|\Delta\eta|>2\\}$ from Xe–Xe collisions follows that
observed in Fig. 1. Compared with Pb–Pb collisions in the semi-central bins,
it appears the differences observed in Fig. 2 are larger in the
mid-$p_{\rm{T}}$ region, and this will be investigated more quantitatively.
Figure 5 shows the same comparison for $p_{\rm{T}}$-differential
$v_{\rm{3}}\\{2,|\Delta\eta|>2\\}$ coefficients. The Xe–Xe coefficients are
typically larger than from Pb–Pb collisions at a given centrality at low
$p_{\rm{T}}$, whereas the larger statistical uncertainties for the Xe–Xe
coefficients at higher $p_{\rm{T}}$ make it difficult to establish whether
there are any differences between the two systems.

Figure 6: Comparisons of $v_{\rm{n}}\\{2\\}/\varepsilon_{\rm{n}}\\{2\\}$
integrated over the transverse momentum range $0.2<p_{\rm{T}}<3.0$ GeV/$c$ as
a function of $1/S$ d$N_{\rm{ch}}$/d$\eta$ in Xe–Xe and Pb–Pb collisions,
where $S$ and $\varepsilon_{\rm{n}}\\{2\\}$ are from various initial state
models [46, 50, 51]. The models are explained in the text. The 129Xe
deformation implemented is $\beta_{2}=0.18\pm 0.02$, with the box errors
representing the uncertainty in $\beta_{2}$. Measurements of
d$N_{\rm{ch}}$/d$\eta$ ($|\eta|<0.5$) from Xe–Xe and Pb–Pb collisions were
obtained from separate studies [30, 52].

Figure 6 shows the $p_{\rm{T}}$-integrated
$v_{\rm{n}}\\{2\\}/\varepsilon_{\rm{n}}\\{2\\}$ ratios as a function of $1/S$
d$N_{\rm{ch}}$/d$\eta$ in Xe–Xe and Pb–Pb collisions, where $S$ and
$\varepsilon_{\rm{n}}\\{2\\}$ are obtained using various initial state models.
The $v_{\rm{n}}\\{2\\}/\varepsilon_{\rm{n}}\\{2\\}$ ratio provides estimates
of $\kappa_{\rm{n}}$ as per Eq. 2. As mentioned, when comparing
$v_{\rm{n}}/\varepsilon_{\rm{n}}$ from different systems, a violation of the
scaling with $1/S$ d$N_{\rm{ch}}$/d$\eta$ (which increases with centrality),
maybe indicative of shortcomings in the modeling of the initial state (and its
fluctuations). Regarding the model parameters used for this exercise, in the
transverse plane for a single event, both the eccentricities and areas are
calculated in the center of mass frame respectively according to

$\displaystyle\varepsilon_{\rm{n}}$ $\displaystyle=\frac{\sqrt{\langle
r^{\prime\rm{n}}\cos(\rm{n}\phi^{\prime})\rangle^{2}+\langle
r^{\prime\rm{n}}\sin(\rm{n}\phi^{\prime})\rangle^{2}}}{\langle
r^{\prime\rm{n}}\rangle},$ (7) $\displaystyle S$
$\displaystyle=4\pi\sigma_{x^{\prime}}\sigma_{y^{\prime}},$ (8)

which is defined such that the sources that contribute to the eccentricity and
area have the property $\langle x^{\prime}\rangle=\langle
y^{\prime}\rangle=0$, where $x^{\prime},y^{\prime}$ and
$\varphi^{\prime},r^{\prime}$ are the cartesian and the polar coordinates of
the source, respectively. The quantities $\sigma_{x^{\prime}}$ and
$\sigma_{y^{\prime}}$ represent the standard deviations of the source
distributions. The event averages used for Fig. 6 are
$\varepsilon_{\rm{n}}\\{2\\}=\sqrt{\langle\varepsilon_{\rm{n}}\rangle^{2}+\sigma_{\varepsilon_{\rm{n}}}^{2}}$
and $\langle S\rangle$. The normalization of the area is chosen such that for
a Gaussian distribution the average density coincides with $N_{part}/S$
($N_{part}$ is the number of participating nucleons), and was used in a
previous ALICE publication [53]. A deformation of $\beta_{2}=0.18\pm 0.02$ for
the 129Xe nucleus is used [30, 54]. The value was obtained from extrapolating
measurements of $\beta_{2}$ from nearby isotopes (128Xe and 130Xe), and
theoretical calculations [55, 56, 47], with the uncertainty reflecting the
different values obtained from each approach. The box errors in the figure
represent the corresponding uncertainties on the ratio. For the Monte Carlo
(MC) Glauber and KLN models, the values of $\varepsilon_{\rm{n}}\\{2\\}$ and
$S$ for a given V0 based centrality class were extracted using a method
described in a previous publication [34]. The multiplicity of charged
particles in the acceptance of the V0 detector is generated according to a
negative binomial distribution, based on the number of participant nucleons
and binary collisions from each initial state model. The parameters used for
this approach can be found elsewhere [52, 54], and were optimized to describe
the multiplicity distribution from the data. Regarding the TRENTo model,
following other approaches [21, 46], the multiplicity in the acceptance of the
V0 detector was modeled by scaling the entropy production, again to match the
multiplicity distribution from the data.

The top left panel shows an investigation of such a scaling with the MC
Glauber model [57, 58], which uses nucleon positions as the sources. In
particular, for $v_{2}\\{2\\}$ in central Xe–Xe and Pb–Pb collisions, this
model does not provide a clear scaling, and was already observed for $v_{2}$
from Au–Au and U–U collisions at RHIC using the same model [59]. The scaling
using the MC KLN model (version 32) [51, 60], which assumes gluon sources and
uses a Color Glass Condensate approach to determine the gluon spatial
distribution, is shown in the top middle panel. The MC KLN scaling appears to
work well for $v_{3}\\{2\\}$, but fails for $v_{2}\\{2\\}$ with the Xe–Xe
points being above Pb–Pb for more central collisions. A sudden rise is also
observed for central Pb–Pb collisions. This behavior is in contrast to the MC
Glauber nucleon model, where the Xe–Xe points are below Pb–Pb for central
collisions. The top right panel investigates the scaling using the TRENTo
initial state model [46]. In this model, the distribution of nuclear matter
within the collision zone of A–A collisions is controlled by the p parameter,
with $\rm{p}=0$ mimicking IP-Glasma initial conditions [61, 62]. The choice of
parameter was determined using Bayesian statistics from a simultaneous fit of
charged hadron multiplicity distributions, mean transverse momentum
measurements, and integrated flow coefficients $v_{\rm n}$ in Pb–Pb collisions
at $\sqrt{s_{\rm{NN}}}=2.76$ TeV [63]. The IP-Glasma approach uses Color Glass
Condensate calculations to determine the distribution of gluons in the initial
state. This model provides a better scaling compared with the previous two
other models. However for central Pb–Pb collisions, a drop is observed for
$v_{2}\\{2\\}/\varepsilon_{\rm{2}}\\{2\\}$. The drop is also observed in the
MC Glauber nucleon model, and appears to be present for the central Xe–Xe
data. Such a drop is unexpected from hydrodynamic calculations [23, 17], which
show a continuous increase of $v_{\rm{2}}/\varepsilon_{\rm{2}}$ with $1/S$
d$N_{\rm{ch}}$/d$\eta$. It may point to deficiencies in the initial state
modeling of the regions in Xe–Xe and Pb–Pb collisions where initial state
fluctuations play the largest role in generating second order eccentricities.

The bottom panels show ratios derived from constituent quark MC Glauber
calculations, which use quarks contained in nucleons as the sources which
contribute to the eccentricity [50]. The parameter q refers to the number of
constituent quarks per nucleon. All implementations of quark sources (3, 5, or
7) appear to give a reasonable scaling for $v_{2}$ and $v_{3}$, however some
deviations are observed in central Xe–Xe and Pb–Pb collisions. The value
$\rm{q}=5$ was found to describe the charged particle yields better than
$\rm{q}=3$ at LHC energies (assuming the yields should scale with the total
number of quarks) [50], and there are hints of a slightly better scaling with
$\rm{q}=5$ for $v_{2}\\{2\\}$ in central Xe–Xe collisions compared to
$\rm{q}=3$. These model implementations again show a drop for central Pb–Pb
collisions, which is least pronounced for $\rm{q}=7$. This suggests initial
state models need a higher number of sources per nucleon in order to achieve a
continuous increase of $v_{\rm{2}}\\{2\\}/\varepsilon_{\rm{2}}\\{2\\}$ for
more central Pb–Pb collisions, and a transverse density scaling when comparing
Xe–Xe to Pb–Pb.

Figure 7: Top panel: Comparison of $p_{\rm{T}}$-differential
$v_{\rm{2}}\\{2\\}/\varepsilon_{\rm{2}}\\{2\\}$ from Xe–Xe and Pb–Pb
collisions for a selection of centrality bins. Statistical and systematic
uncertainties are shown as lines and boxes, respectively. Bottom panel: Ratios
of the scaled coefficients from the top panel. The Pb–Pb points are
interpolated in order to determine the ratio. The circle markers show Xe–Xe
20–30%/Pb–Pb 30–40% while the square makers show Xe–Xe 30–40%/Pb–Pb 30–40%.

Finally, in Fig. 7, an investigation of whether the transverse density scaling
holds as a function of $p_{\rm{T}}$ is shown. Two Xe–Xe and Pb–Pb centrality
bins with similar transverse densities ($1/S$ d$N_{\rm{ch}}$/d$\eta\sim 10$
fm-2) are selected, and the $p_{\rm{T}}$-differential values of
$v_{\rm{2}}\\{2\\}/\varepsilon_{\rm{2}}\\{2\\}$ are shown. The
$p_{\rm{T}}$-integrated values for the constituent quark MC Glauber model
chosen ($\rm{q}=3$) are observed to be similar in the left bottom panel of
Fig. 6. In that figure, the Xe–Xe centrality bin corresponds to the fourth
point going left to right, while the Pb–Pb centrality bin corresponds to the
third point. The ratio in the bottom panel of Fig. 7 uses an interpolation of
the Pb–Pb data points. The ratio is independent of the initial state model
used, as all give very similar values of
$\varepsilon_{\rm{2}}\\{2\\}$(Xe–Xe)/$\varepsilon_{\rm{2}}\\{2\\}$(Pb–Pb).
Additionally, the transverse sizes ($R=\sqrt{S/\pi}$) are very similar, so the
previously mentioned viscous corrections should cancel. The influence of
radial flow should be very similar as $\langle p_{T}\rangle=0.710\pm 0.004$
GeV/$c$ (Xe–Xe) and $\langle p_{T}\rangle=0.716\pm 0.004$ GeV/$c$ (Pb–Pb) for
charged hadrons [64]. The ratio is close to 1 and shows no significant
$p_{\rm{T}}$ dependence. This indicates when such a scaling holds, it does so
over the $p_{\rm{T}}$ range presented. This may show the
$p_{\rm{T}}$-differential medium response ($\kappa_{2}(p_{\rm{T}})$) is
controlled by the transverse density and size, independent of the collision
system. A comparison of the scaled $p_{\rm{T}}$-differential coefficients for
the same 30–40% centrality bin from Xe–Xe and Pb–Pb collisions is also shown.
In this case, the eccentricities are similar (the differences are within 1%),
however the transverse size and density of the Xe–Xe system is smaller. The
ratio appears to mildly decrease with increasing $p_{\rm{T}}$. Whether this is
the result of viscous effects related to the transverse size of the system
influencing the mid-$p_{\rm{T}}$ region more, or a smaller radial flow in
Xe–Xe, remains an open question.

##  4 Summary

The first measurements of anisotropic flow coefficients $v_{\rm{n}}$ in Xe–Xe
collisions at $\sqrt{s_{\rm{NN}}}=5.44$ TeV collisions from the ALICE detector
at the LHC have been presented. Hydrodynamical predictions reproduce
measurements of $v_{2}\\{4\\}$/$v_{2}\\{2\\}$ ratios from Xe–Xe collisions to
within $\sim$ 15% (Fig. 1). In semi-central collisions, it is found that the
$v_{2}\\{2\\}$ coefficient is lower in Xe–Xe collisions at
$\sqrt{s_{\rm{NN}}}=5.44$ TeV compared with Pb–Pb collisions at
$\sqrt{s_{\rm{NN}}}=5.02$ TeV at the same centrality. The $v_{3}\\{2\\}$
coefficient is larger, consistent with expectations from hydrodynamical models
that reproduce the differences for both systems within $\sim$ 5% (Figs. 2 and
3). The differences for $v_{2}\\{2\\}$ are predicted to be driven largely by
the hydrodynamical response of the system. For central collisions,
$v_{2}\\{2\\}$ is found to be larger in Xe–Xe collisions, which agrees with
predictions from hydrodynamic models, but the deviations tend to be larger
than $\sim$ 5% with respect to these models. The differences between two-
particle $p_{\rm{T}}$-differential $v_{\rm{2}}\\{2\\}$ coefficients from Xe–Xe
compared to Pb–Pb are found to be larger at mid-$p_{\rm{T}}$ compared to
low-$p_{\rm{T}}$, whereas no such trend is observed for $v_{\rm{3}}\\{2\\}$
within uncertainties (Figs. 4 and 5). The studies of the modeling of the
initial state via eccentricity scaling with transverse density (Fig. 6) have
demonstrated that both the MC Glauber (constituent quarks) and the TRENTo
models provide the most satisfactory descriptions. However, the drop observed
for $v_{\rm{2}}\\{2\\}/\varepsilon_{\rm{2}}\\{2\\}$ in central Xe–Xe and Pb–Pb
collisions is not expected from hydrodynamic calculations. In the case of the
MC Glauber implementations, the drop is more pronounced for nucleon and
constituent quark ($\rm{q}=3$) sources, and may require some improvements in
the initial state modeling for the region in Xe–Xe and Pb–Pb collisions where
$\varepsilon_{\rm{2}}\\{2\\}$ has the largest contribution from initial state
fluctuations. Finally, for two Xe–Xe and Pb–Pb centrality bins with a similar
transverse density and size, it is found that the double ratio
[$v_{\rm{2}}\\{2\\}/\varepsilon_{\rm{2}}\\{2\\}$(Xe–Xe)]/[$v_{\rm{2}}\\{2\\}/\varepsilon_{\rm{2}}\\{2\\}$(Pb–Pb)]
is largely independent of $p_{\rm{T}}$ (Fig. 7). This may indicate the
$p_{\rm{T}}$-differential medium response is controlled by the transverse
density and size, independent of the collision system.

## 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 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), Universidade Federal do
Rio Grande do Sul (UFRGS), Financiadora de Estudos e Projetos (Finep) and
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), Brazil;
Ministry of Science & Technology of China (MSTC), National Natural Science
Foundation of China (NSFC) and Ministry of Education of China (MOEC) , China;
Ministry of Science and Education, Croatia; Ministry of Education, Youth and
Sports of the Czech Republic, Czech Republic; The Danish Council for
Independent Research — Natural Sciences, the Carlsberg Foundation 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, Wissenschaft, Forschung und Technologie (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; Indonesian Institute of Science, Indonesia; Centro Fermi -
Museo Storico della Fisica e Centro Studi e Ricerche Enrico Fermi and Istituto
Nazionale di Fisica Nucleare (INFN), Italy; Institute for Innovative Science
and Technology , Nagasaki Institute of Applied Science (IIST), Japan Society
for the Promotion of Science (JSPS) KAKENHI and Japanese Ministry of
Education, Culture, Sports, Science and Technology (MEXT), 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 Science and Higher Education and National Science Centre, 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 and Romanian National Agency
for Science, Technology and Innovation, Romania; Joint Institute for Nuclear
Research (JINR), Ministry of Education and Science of the Russian Federation
and National Research Centre Kurchatov Institute, Russia; Ministry of
Education, Science, Research and Sport of the Slovak Republic, Slovakia;
National Research Foundation of South Africa, South Africa; Centro de
Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN), Cubaenergía, Cuba and
Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas
(CIEMAT), Spain; Swedish Research Council (VR) and Knut & Alice Wallenberg
Foundation (KAW), Sweden; European Organization for Nuclear Research,
Switzerland; National Science and Technology Development Agency (NSDTA),
Suranaree University of Technology (SUT) and Office of the Higher Education
Commission under NRU project of Thailand, Thailand; Turkish Atomic Energy
Agency (TAEK), 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.

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##  Appendix A The ALICE Collaboration

S. Acharyaorg138&F.T.-. Acostaorg22&D. Adamováorg94&J. Adolfssonorg81&M.M.
Aggarwalorg98&G. Aglieri Rinellaorg36&M. Agnelloorg33&N. Agrawalorg49&Z.
Ahammedorg138&S.U. Ahnorg77&S. Aiolaorg143&A. Akindinovorg65&M. Al-
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Tikhonovorg63&A.R. Timminsorg124&A. Toiaorg70&N. Topilskayaorg63&M.
Toppiorg52&S.R. Torresorg118&S. Tripathyorg50&S. Trogoloorg28&G.
Trombettaorg35&L. Tropporg40&V. Trubnikovorg3&W.H. Trzaskaorg125&T.P.
Trzcinskiorg139&B.A. Trzeciakorg64&T. Tsujiorg129&A. Tumkinorg106&R.
Turrisiorg57&T.S. Tveterorg23&K. Ullalandorg24&E.N. Umakaorg124&A.
Urasorg132&G.L. Usaiorg26&A. Utrobicicorg97&M. Valaorg114&J.W. Van
Hoorneorg36&M. van Leeuwenorg64&P. Vande Vyvreorg36&D. Vargaorg142&A.
Vargasorg2&M. Vargyasorg125&R. Varmaorg49&M. Vasileiouorg84&A.
Vasilievorg88&A. Vauthierorg79&O. Vázquez Doceorg103,org115&V.
Vecherninorg137&A.M. Veenorg64&E. Vercellinorg28&S. Vergara Limónorg2&L.
Vermuntorg64&R. Vernetorg8&R. Vértesiorg142&L. Vickovicorg37&J.
Viinikainenorg125&Z. Vilakaziorg128&O. Villalobos Baillieorg108&A. Villatoro
Telloorg2&A. Vinogradovorg88&T. Virgiliorg32&V. Vislaviciusorg89,org81&A.
Vodopyanovorg76&M.A. Völklorg101&K. Voloshinorg65&S.A. Voloshinorg140&G.
Volpeorg35&B. von Hallerorg36&I. Vorobyevorg115,org103&D. Voscekorg114&D.
Vranicorg104,org36&J. Vrlákováorg40&B. Wagnerorg24&H. Wangorg64&M. Wangorg7&Y.
Watanabeorg130&M. Weberorg111&S.G. Weberorg104&A. Wegrzynekorg36&D.F.
Weiserorg102&S.C. Wenzelorg36&J.P. Wesselsorg141&U. Westerhofforg141&A.M.
Whiteheadorg123&J. Wiechulaorg70&J. Wikneorg23&G. Wilkorg85&J.
Wilkinsonorg54&G.A. Willemsorg141,org36&M.C.S. Williamsorg54&E.
Willsherorg108&B. Windelbandorg102&W.E. Wittorg127&R. Xuorg7&S. Yalcinorg78&K.
Yamakawaorg46&S. Yanoorg46&Z. Yinorg7&H. Yokoyamaorg79,org130&I.-K.
Yooorg20&J.H. Yoonorg61&V. Yurchenkoorg3&V. Zaccoloorg59&A. Zamanorg16&C.
Zampolliorg36&H.J.C. Zanoliorg119&N. Zardoshtiorg108&A. Zarochentsevorg137&P.
Závadaorg68&N. Zaviyalovorg106&H. Zbroszczykorg139&M. Zhalovorg96&X.
Zhangorg7&Y. Zhangorg7&Z. Zhangorg7,org131&C. Zhaoorg23&V.
Zherebchevskiiorg137&N. Zhigarevaorg65&D. Zhouorg7&Y. Zhouorg89&Z.
Zhouorg24&H. Zhuorg7&J. Zhuorg7&Y. Zhuorg7&A. Zichichiorg29,org11&M.B.
Zimmermannorg36&G. Zinovjevorg3&J. Zmeskalorg111&S. Zouorg7&

## Affiliation notes

org*Deceased

orgIDipartimento DET del Politecnico di Torino, Turin, Italy

orgIIM.V. Lomonosov Moscow State University, D.V. Skobeltsyn Institute of
Nuclear, Physics, Moscow, Russia

orgIIIDepartment of Applied Physics, Aligarh Muslim University, Aligarh, India

orgIVInstitute of Theoretical Physics, University of Wroclaw, Poland

## Collaboration Institutes

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

org2Benemérita Universidad Autónoma de Puebla, Puebla, Mexico

org3Bogolyubov Institute for Theoretical Physics, National Academy of Sciences
of Ukraine, Kiev, Ukraine

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

org5Budker Institute for Nuclear Physics, Novosibirsk, Russia

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

org7Central China Normal University, Wuhan, China

org8Centre de Calcul de l’IN2P3, Villeurbanne, Lyon, France

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

org10Centro de Investigación y de Estudios Avanzados (CINVESTAV), Mexico City
and Mérida, Mexico

org11Centro Fermi - Museo Storico della Fisica e Centro Studi e Ricerche
“Enrico Fermi’, Rome, Italy

org12Chicago State University, Chicago, Illinois, United States

org13China Institute of Atomic Energy, Beijing, China

org14Chonbuk National University, Jeonju, Republic of Korea

org15Comenius University Bratislava, Faculty of Mathematics, Physics and
Informatics, Bratislava, Slovakia

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

org17Creighton University, Omaha, Nebraska, United States

org18Department of Physics, Aligarh Muslim University, Aligarh, India

org19Department of Physics, Ohio State University, Columbus, Ohio, United
States

org20Department of Physics, Pusan National University, Pusan, Republic of
Korea

org21Department of Physics, Sejong University, Seoul, Republic of Korea

org22Department of Physics, University of California, Berkeley, California,
United States

org23Department of Physics, University of Oslo, Oslo, Norway

org24Department of Physics and Technology, University of Bergen, Bergen,
Norway

org25Dipartimento di Fisica dell’Università ’La Sapienza’ and Sezione INFN,
Rome, Italy

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

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

org28Dipartimento di Fisica dell’Università and Sezione INFN, Turin, Italy

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

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

org31Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN,
Padova, Italy

org32Dipartimento di Fisica ‘E.R. Caianiello’ dell’Università and Gruppo
Collegato INFN, Salerno, Italy

org33Dipartimento DISAT del Politecnico and Sezione INFN, Turin, Italy

org34Dipartimento di Scienze e Innovazione Tecnologica dell’Università del
Piemonte Orientale and INFN Sezione di Torino, Alessandria, Italy

org35Dipartimento Interateneo di Fisica ‘M. Merlin’ and Sezione INFN, Bari,
Italy

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

org37Faculty of Electrical Engineering, Mechanical Engineering and Naval
Architecture, University of Split, Split, Croatia

org38Faculty of Engineering and Science, Western Norway University of Applied
Sciences, Bergen, Norway

org39Faculty of Nuclear Sciences and Physical Engineering, Czech Technical
University in Prague, Prague, Czech Republic

org40Faculty of Science, P.J. Šafárik University, Košice, Slovakia

org41Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe-
Universität Frankfurt, Frankfurt, Germany

org42Gangneung-Wonju National University, Gangneung, Republic of Korea

org43Gauhati University, Department of Physics, Guwahati, India

org44Helmholtz-Institut für Strahlen- und Kernphysik, Rheinische Friedrich-
Wilhelms-Universität Bonn, Bonn, Germany

org45Helsinki Institute of Physics (HIP), Helsinki, Finland

org46Hiroshima University, Hiroshima, Japan

org47Hochschule Worms, Zentrum für Technologietransfer und Telekommunikation
(ZTT), Worms, Germany

org48Horia Hulubei National Institute of Physics and Nuclear Engineering,
Bucharest, Romania

org49Indian Institute of Technology Bombay (IIT), Mumbai, India

org50Indian Institute of Technology Indore, Indore, India

org51Indonesian Institute of Sciences, Jakarta, Indonesia

org52INFN, Laboratori Nazionali di Frascati, Frascati, Italy

org53INFN, Sezione di Bari, Bari, Italy

org54INFN, Sezione di Bologna, Bologna, Italy

org55INFN, Sezione di Cagliari, Cagliari, Italy

org56INFN, Sezione di Catania, Catania, Italy

org57INFN, Sezione di Padova, Padova, Italy

org58INFN, Sezione di Roma, Rome, Italy

org59INFN, Sezione di Torino, Turin, Italy

org60INFN, Sezione di Trieste, Trieste, Italy

org61Inha University, Incheon, Republic of Korea

org62Institut de Physique Nucléaire d’Orsay (IPNO), Institut National de
Physique Nucléaire et de Physique des Particules (IN2P3/CNRS), Université de
Paris-Sud, Université Paris-Saclay, Orsay, France

org63Institute for Nuclear Research, Academy of Sciences, Moscow, Russia

org64Institute for Subatomic Physics, Utrecht University/Nikhef, Utrecht,
Netherlands

org65Institute for Theoretical and Experimental Physics, Moscow, Russia

org66Institute of Experimental Physics, Slovak Academy of Sciences, Košice,
Slovakia

org67Institute of Physics, Bhubaneswar, India

org68Institute of Physics of the Czech Academy of Sciences, Prague, Czech
Republic

org69Institute of Space Science (ISS), Bucharest, Romania

org70Institut für Kernphysik, Johann Wolfgang Goethe-Universität Frankfurt,
Frankfurt, Germany

org71Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México,
Mexico City, Mexico

org72Instituto de Física, Universidade Federal do Rio Grande do Sul (UFRGS),
Porto Alegre, Brazil

org73Instituto de Física, Universidad Nacional Autónoma de México, Mexico
City, Mexico

org74iThemba LABS, National Research Foundation, Somerset West, South Africa

org75Johann-Wolfgang-Goethe Universität Frankfurt Institut für Informatik,
Fachbereich Informatik und Mathematik, Frankfurt, Germany

org76Joint Institute for Nuclear Research (JINR), Dubna, Russia

org77Korea Institute of Science and Technology Information, Daejeon, Republic
of Korea

org78KTO Karatay University, Konya, Turkey

org79Laboratoire de Physique Subatomique et de Cosmologie, Université
Grenoble-Alpes, CNRS-IN2P3, Grenoble, France

org80Lawrence Berkeley National Laboratory, Berkeley, California, United
States

org81Lund University Department of Physics, Division of Particle Physics,
Lund, Sweden

org82Nagasaki Institute of Applied Science, Nagasaki, Japan

org83Nara Women’s University (NWU), Nara, Japan

org84National and Kapodistrian University of Athens, School of Science,
Department of Physics , Athens, Greece

org85National Centre for Nuclear Research, Warsaw, Poland

org86National Institute of Science Education and Research, HBNI, Jatni, India

org87National Nuclear Research Center, Baku, Azerbaijan

org88National Research Centre Kurchatov Institute, Moscow, Russia

org89Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark

org90Nikhef, National institute for subatomic physics, Amsterdam, Netherlands

org91NRC Kurchatov Institute IHEP, Protvino, Russia

org92NRNU Moscow Engineering Physics Institute, Moscow, Russia

org93Nuclear Physics Group, STFC Daresbury Laboratory, Daresbury, United
Kingdom

org94Nuclear Physics Institute of the Czech Academy of Sciences, Řež u Prahy,
Czech Republic

org95Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States

org96Petersburg Nuclear Physics Institute, Gatchina, Russia

org97Physics department, Faculty of science, University of Zagreb, Zagreb,
Croatia

org98Physics Department, Panjab University, Chandigarh, India

org99Physics Department, University of Jammu, Jammu, India

org100Physics Department, University of Rajasthan, Jaipur, India

org101Physikalisches Institut, Eberhard-Karls-Universität Tübingen, Tübingen,
Germany

org102Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg,
Heidelberg, Germany

org103Physik Department, Technische Universität München, Munich, Germany

org104Research Division and ExtreMe Matter Institute EMMI, GSI
Helmholtzzentrum für Schwerionenforschung GmbH, Darmstadt, Germany

org105Rudjer Bošković Institute, Zagreb, Croatia

org106Russian Federal Nuclear Center (VNIIEF), Sarov, Russia

org107Saha Institute of Nuclear Physics, Kolkata, India

org108School of Physics and Astronomy, University of Birmingham, Birmingham,
United Kingdom

org109Sección Física, Departamento de Ciencias, Pontificia Universidad
Católica del Perú, Lima, Peru

org110Shanghai Institute of Applied Physics, Shanghai, China

org111Stefan Meyer Institut für Subatomare Physik (SMI), Vienna, Austria

org112SUBATECH, IMT Atlantique, Université de Nantes, CNRS-IN2P3, Nantes,
France

org113Suranaree University of Technology, Nakhon Ratchasima, Thailand

org114Technical University of Košice, Košice, Slovakia

org115Technische Universität München, Excellence Cluster ’Universe’, Munich,
Germany

org116The Henryk Niewodniczanski Institute of Nuclear Physics, Polish Academy
of Sciences, Cracow, Poland

org117The University of Texas at Austin, Austin, Texas, United States

org118Universidad Autónoma de Sinaloa, Culiacán, Mexico

org119Universidade de São Paulo (USP), São Paulo, Brazil

org120Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil

org121Universidade Federal do ABC, Santo Andre, Brazil

org122University College of Southeast Norway, Tonsberg, Norway

org123University of Cape Town, Cape Town, South Africa

org124University of Houston, Houston, Texas, United States

org125University of Jyväskylä, Jyväskylä, Finland

org126University of Liverpool, Department of Physics Oliver Lodge Laboratory ,
Liverpool, United Kingdom

org127University of Tennessee, Knoxville, Tennessee, United States

org128University of the Witwatersrand, Johannesburg, South Africa

org129University of Tokyo, Tokyo, Japan

org130University of Tsukuba, Tsukuba, Japan

org131Université Clermont Auvergne, CNRS/IN2P3, LPC, Clermont-Ferrand, France

org132Université de Lyon, Université Lyon 1, CNRS/IN2P3, IPN-Lyon,
Villeurbanne, Lyon, France

org133Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000 Strasbourg,
France, Strasbourg, France

org134 Université Paris-Saclay Centre d¿Études de Saclay (CEA), IRFU,
Department de Physique Nucléaire (DPhN), Saclay, France

org135Università degli Studi di Pavia, Pavia, Italy

org136Università di Brescia, Brescia, Italy

org137V. Fock Institute for Physics, St. Petersburg State University, St.
Petersburg, Russia

org138Variable Energy Cyclotron Centre, Kolkata, India

org139Warsaw University of Technology, Warsaw, Poland

org140Wayne State University, Detroit, Michigan, United States

org141Westfälische Wilhelms-Universität Münster, Institut für Kernphysik,
Münster, Germany

org142Wigner Research Centre for Physics, Hungarian Academy of Sciences,
Budapest, Hungary

org143Yale University, New Haven, Connecticut, United States

org144Yonsei University, Seoul, Republic of Korea