2019 125 08 June

ALICE Collaboration

D-meson production in p–Pb collisions at $\sqrt{s_{\scriptscriptstyle\rm
NN}}=5.02\leavevmode\nobreak\ \mathrm{TeV}$

The measurement of the production of prompt ${\rm D^{0}}$, ${\rm D^{+}}$,
${\rm D^{*+}}$, and ${\rm D^{+}_{s}}$ mesons in proton–lead (p–Pb) collisions
at the centre-of-mass energy per nucleon pair of
$\sqrt{s_{\scriptscriptstyle\rm NN}}=5.02\leavevmode\nobreak\ \mathrm{TeV}$,
with an integrated luminosity of $292\pm 11$ $\mu$b-1, are reported.
Differential production cross sections are measured at mid-rapidity
($-0.96<y_{\rm cms}<0.04$) as a function of transverse momentum ($p_{\rm T}$)
in the intervals $0<p_{\rm T}<36\leavevmode\nobreak\ \mathrm{GeV}/c$ for ${\rm
D^{0}}$, $1<p_{\rm T}<36\leavevmode\nobreak\ \mathrm{GeV}/c$ for ${\rm D^{+}}$
and ${\rm D^{*+}}$, and $2<p_{\rm T}<24\leavevmode\nobreak\ \mathrm{GeV}/c$
for ${\rm D^{+}_{s}}$ mesons. For each species, the nuclear modification
factor $R_{\rm pPb}$ is calculated as a function of $p_{\rm T}$ using a
proton-proton (pp) reference measured at the same collision energy. The
results are compatible with unity in the whole $p_{\rm T}$ range. The average
of the non-strange D mesons $R_{\rm pPb}$ is compared with theoretical model
predictions that include initial-state effects and parton transport model
predictions. The $p_{\rm T}$ dependence of the ${\rm D^{0}}$, ${\rm D^{+}}$,
and ${\rm D^{*+}}$ nuclear modification factors is also reported in the
interval $1<p_{\rm T}<36\leavevmode\nobreak\ \mathrm{GeV}/c$ as a function of
the collision centrality, and the central-to-peripheral ratios are computed
from the D-meson yields measured in different centrality classes. The results
are further compared with charged-particle measurements and a similar trend is
observed in all the centrality classes. The ratios of the $p_{\rm
T}$-differential cross sections of ${\rm D^{0}}$, ${\rm D^{+}}$, ${\rm
D^{*+}}$, and ${\rm D^{+}_{s}}$ mesons are also reported. The ${\rm
D^{+}_{s}}$ and ${\rm D^{+}}$ yields are compared as a function of the
charged-particle multiplicity for several $p_{\rm T}$ intervals. No
modification in the relative abundances of the four species is observed with
respect to pp collisions within the statistical and systematic uncertainties.

##  1 Introduction

Measurements of heavy-flavour hadron production in proton–nucleus collisions
allow for an assessment of the various effects related to the presence of
nuclei in the colliding system, denoted as cold-nuclear-matter (CNM) effects.
Heavy quarks (charm and beauty) are primarily produced in hard-scattering
processes with large momentum transfer ($Q^{2}$) due to their large masses.
Their inclusive production cross sections can therefore be calculated
perturbatively in Quantum Chromodynamics (QCD) utilizing the factorisation
approach. In this scheme, the $p_{\rm T}$ differential production cross
sections of hadrons containing charm or beauty quarks are calculated as a
convolution of three terms: (i) the parton distribution functions (PDFs) of
the incoming nucleons, (ii) the partonic scattering cross section, calculated
as a perturbative series in powers of the strong coupling constant
$\alpha_{\rm s}$, and (iii) the fragmentation function, which parametrises the
non-perturbative evolution of a heavy quark into a given heavy-flavour hadron
species. Theoretical predictions based on perturbative QCD (pQCD) calculations
at next-to-leading order accuracy with all-order resummation of next-to-
leading logarithms, such as FONLL [1, 2] and GM-VFNS [3, 4, 5, 6], can
describe within uncertainties the production cross sections of D and B mesons
measured in pp and ${\rm p\overline{p}}$ collisions in different kinematic
regions at centre-of-mass energies from 0.2 to 13 TeV (see e.g. Ref. [7, 8]
and references therein). In proton–nucleus collisions, various effects in the
initial and final state could modify the D-meson production cross sections per
nucleon–nucleon collision as compared to pp interactions. In the initial
state, the production is affected by the modification of the PDFs in bound
nucleons compared to those of free nucleons, depending on the parton momentum
fraction $x$, the momentum transfer $Q^{2}$ in the hard scattering process,
and the nucleus mass number $A$ [9, 10]. At LHC energies and at mid-rapidity,
the most relevant effect on the PDFs is shadowing: a reduction of the parton
densities at low $x$ (below $10^{-2}$), which becomes stronger when $Q^{2}$
decreases and the nucleus mass number $A$ increases. This effect can be
described by means of phenomenological parametrisations of the PDF
modifications, denoted as nuclear PDFs (nPDFs) [11, 12, 13, 14]. As
demonstrated in Refs. [15, 16], measurements of heavy-flavour and quarkonium
production at the LHC can significantly reduce the uncertainties on the gluon
nPDFs at small $x$. If the parton phase-space reaches saturation, the
appropriate theoretical description is the Colour Glass Condensate effective
theory (CGC) [17, 18, 19, 20, 21]. The modification of the small-$x$ parton
dynamics can significantly reduce the D-meson yield at low $p_{\rm T}$.
Furthermore, the multiple scattering of partons in the nucleus, before and/or
after the hard scattering, can modify the kinematic distribution of the
produced hadrons. Partons can lose energy in the initial stages of the
collision via initial-state radiation [22], or experience transverse momentum
broadening due to multiple soft collisions before the heavy-quark pair is
produced [23, 24, 25]. These effects can also induce a significant
modification of D-meson production at low $p_{\rm T}$. In addition, final-
state effects may also be responsible for a modification of heavy-flavour
hadron yields and momentum distributions. The presence of significant final-
state effects in p–Pb collisions with large multiplicities of produced
particles is suggested by different observations, e.g. the presence of long-
range structures in two-particle angular correlations of charged hadrons [26,
27, 28, 29, 30, 31], the studies of azimuthal anisotropies in multi-particle
correlations [32, 33], the evolution with multiplicity of the identified-
hadron transverse-momentum distributions [34, 35], and the suppression of the
$\psi{\rm(2S)}$ production with respect to that of ${\rm J}/\psi$ mesons [36,
37, 38]. In particular, the angular correlations in high-multiplicity p–Pb
collisions were found to have similar properties (e.g. particle mass and
$p_{\rm T}$ dependence [34, 35]) as those observed in Pb–Pb collisions, where
they are commonly interpreted as indications of a collective particle flow
produced during the hydrodynamic evolution of the Quark-Gluon Plasma (QGP)
[39, 40, 41, 42]. The interpretation of the aforementioned results is highly
debated, with the outstanding open question being whether small droplets of a
fluid-like QGP are created in small collision systems (see e.g. [43] for a
recent review). Hydrodynamic calculations, that assume the formation of a
medium with some degree of collectivity (see e.g. [44, 45, 46]), can describe
the angular correlations measured in p–Pb collisions, which suggests a common
hydrodynamic origin of the experimental observations from small to large
collision systems. However, alternative explanations exist, based on gluon
saturation (CGC) in the initial state [47, 48], the anisotropic escape
probability of partons from the collision zone [49], or interactions between
string-like colour fields in dense configurations of confined QCD flux tubes
[50, 51]. If a collective expansion in the final state of the collision
occurs, the medium could also impart a flow to heavy-flavour quarks or
hadrons, and modify the hadronisation dynamics of heavy quarks. Detailed
calculations were performed in the framework of transport models, assuming
that in p–Pb collisions at LHC energies a QGP is formed, which affects the
propagation and hadronisation of heavy quarks [52, 53]. These models predict a
significant modification of the $p_{\rm T}$ distributions of heavy-flavour
hadrons in high-multiplicity p–Pb collisions as compared to pp interactions,
accompanied by the presence of anisotropies in their azimuthal distributions.
Recent measurements of angular correlations in p–Pb collisions involving
J/$\psi$ mesons [54], ${\rm D^{0}}$ mesons [55], and heavy-flavour decay
electrons [56] provided a clear indication that long-range anisotropies are
present also in the heavy-flavour sector.

In the presence of a QGP, a modification of the hadronisation is predicted:
hadrons can be produced not only via the fragmentation mechanism, but also via
(re)combination of charm quarks with other quarks from the medium during the
deconfined phase or at the phase boundary [57, 58, 59, 60]. Given the observed
increase of strangeness production with increasing particle multiplicity in
p–Pb and pp collisions [34, 61, 62], the modified hadronisation could result
in an enhancement of the relative yield of ${\rm D^{+}_{s}}$ mesons with
respect to non-strange charmed mesons in high-multiplicity p–Pb collisions.

In this paper, we report the measurements of the $p_{\rm T}$-differential
production cross sections and nuclear modification factors of prompt ${\rm
D^{0}}$, ${\rm D^{+}}$, ${\rm D^{*+}}$, and ${\rm D^{+}_{s}}$ mesons in p–Pb
collisions at $\sqrt{s_{\scriptscriptstyle\rm NN}}=5.02\leavevmode\nobreak\
\mathrm{TeV}$ recorded with the ALICE detector in 2016. The sample used for
these analyses is larger by a factor of about six with respect to the sample
collected in 2013, which was used in previous publications of these
observables [63, 64, 65]. Therefore, it is possible to obtain lower
statistical and systematic uncertainties by a factor 1.5–2 and extend the
$p_{\rm T}$ reach of the measurements. The ratios of the production cross
sections of the different D-meson species are also reported and are compared
with those measured in pp collisions at the same centre-of-mass energy. The
nuclear modification factor, $R_{\rm pPb}$, is defined as the ratio of the
cross section in p–Pb collisions to that in pp interactions scaled by the mass
number of the Pb nucleus. This ratio is sensitive to cold-nuclear-matter and
hot-medium effects on D-meson production in p–Pb collisions. In addition, the
measurement of the nuclear modification factor for non-strange D mesons is
carried out in intervals of collision centrality, called in the following as
$Q_{\mathrm{pPb}}$. The $Q_{\mathrm{pPb}}$ is calculated as the ratio of the
D-meson yield in p–Pb collisions to the cross section in pp interactions
scaled by the nuclear overlap function $\langle T_{\mathrm{pPb}}\rangle$,
which accounts for the average number of nucleon-nucleon interactions in the
considered centrality class. The $Q_{\mathrm{pPb}}$ measurements are performed
in finer intervals of collision centrality, enabling in particular the
measurements of D-meson production in the 10% most central collisions, in
which possible final-state effects are expected to be stronger. Further
insight into the centrality dependence of prompt D-meson $p_{\rm T}$
distributions is provided by the measurements of the ratios of D-meson yields
in various centrality classes. Finally, the ratio of ${\rm D^{+}_{s}}$-meson
yield to that of non-strange ${\rm D^{+}}$ is presented as a function of the
multiplicity of charged particles produced in p–Pb collisions and is compared
with results measured in pp and Pb–Pb collisions at the same centre-of-mass
energy.

##  2 Experimental apparatus and data sample

The ALICE apparatus [66] is composed of a central barrel comprising various
detectors for particle reconstruction and identification at mid-rapidity
($|\eta|<0.9$), a forward muon spectrometer ($-4<\eta<-2.5$), and a set of
forward-backward detectors for triggering and event characterisation. Typical
detector performance in pp, p–Pb, and Pb–Pb collisions is presented in [67].
The main detector components used in this analysis are the V0 detector, the
Inner Tracking System (ITS), the Time Projection Chamber (TPC), and the Time-
Of-Flight (TOF) detector, which are located inside a large solenoidal magnet
providing a maximum uniform magnetic field of 0.5 T parallel to the LHC beam
direction ($z$-axis in the ALICE reference system), and the Zero-Degree
Calorimeter (ZDC), located at $\pm 112.5$ m from the interaction point.

Proton–lead collisions at $\sqrt{s_{\scriptscriptstyle\rm
NN}}=5.02\leavevmode\nobreak\ \mathrm{TeV}$ were recorded with a minimum-bias
(MB) interaction trigger that required coincident signals in both scintillator
arrays of the V0 detector, which cover the full azimuth in the pseudorapidity
intervals $-3.7<\eta<-1.7$ and $2.8<\eta<5.1$. The V0 timing information was
used together with that from the ZDCs for offline rejection of beam–beam or
beam–gas interactions happening outside of the nominal colliding bunches.

The MB trigger was sensitive to about 96.4% of the p–Pb inelastic cross
section [68]. Only collision events with a primary vertex reconstructed within
$\pm 10$ cm from the centre of the detector along the beam axis were
considered. Events with several interactions per bunch crossing, whose
probability was below 0.5%, were rejected using an algorithm based on track
segments, defined within the Silicon Pixel Detector (SPD, the two innermost
ITS layers), to detect multiple interaction vertices.

The number of events passing these selection criteria was about $6\times
10^{8}$. The corresponding integrated luminosity, ${L}_{\mathrm{int}}=N_{\rm
MB}/\sigma_{\rm MB}$, is equal to $292\pm 11\leavevmode\nobreak\ {\mathrm{\mu
b}}^{-1}$, $\sigma_{\rm MB}=2.09$ b being the MB-trigger (i.e. visible) cross
section measured via a van der Meer scan, with negligible statistical
uncertainty and a systematic uncertainty of 3.7% [68]. During the p–Pb data-
taking period, the beam energies were 4 TeV for protons and 1.58 TeV per
nucleon for lead nuclei. With this beam configuration, the nucleon–nucleon
centre-of-mass system moves in rapidity by $\Delta y_{\mathrm{cms}}=0.465$ in
the direction of the proton beam. The D-meson analyses were performed in the
laboratory-frame interval $|y_{\mathrm{lab}}|<0.5$, which leads to a shifted
centre-of-mass rapidity coverage of $-0.96<y_{\mathrm{cms}}<0.04$.
Additionally, the p–Pb data sample was divided into centrality classes defined
as percentiles of the visible cross section. The events were classified
according to the energy deposited in the ZDC positioned in the Pb-going side
by the neutrons produced in the interaction by nuclear de-excitation
processes, or knocked out by wounded nucleons. The multiplicity of these
neutrons is expected to grow monotonically with the number of nucleon–nucleon
binary collisions, $N_{\rm coll}$. It was demonstrated in Ref. [69] that this
is the least-biased centrality estimator for p–Pb interactions. The
description of the average nuclear overlap function, as well as the values
corresponding to the measured centrality classes, will be given in section
5.3.

The pp reference for the $R_{\rm pPb}$ and $Q_{\mathrm{pPb}}$ calculation was
taken from the measurements performed on a data sample of about 990 million
minimum-bias pp collisions ($L_{\rm int}=(19.3\pm 0.4)$ nb-1) at
$\sqrt{s}=5.02$ TeV collected with ALICE in 2017, and published in Ref. [70].

##  3 Data analysis

The D-meson yields were extracted using two different analysis methods. The
first method, described in Section 3.1, is based on the reconstruction of
decay vertices displaced from the primary vertex. The second method, described
in Section 3.2, is used only for the ${\rm D^{0}}$ measurement and is based on
the estimation and subtraction of the combinatorial background, without any
selection criteria on the displaced decay-vertex topology. The first method
allows the D-meson yield to be extracted in a $p_{\rm T}$-interval of 1–36
GeV/$c$ for ${\rm D^{0}}$, ${\rm D^{+}}$, and ${\rm D^{*+}}$ and 2–24 GeV/$c$
for ${\rm D^{+}_{s}}$. The second method allows the ${\rm D^{0}}$-meson
production to be measured down to $p_{\rm T}=0$.

###  3.1 Analysis with D-meson decay vertex reconstruction

The D mesons and their charge conjugates were reconstructed in the decay
channels ${\rm D}^{0}\to{\rm K}^{-}\pi^{+}$ (with a branching ratio, BR, of
$3.89\pm 0.04\%$), ${\rm D}^{+}\to{\rm K}^{-}\pi^{+}\pi^{+}$ (BR of $8.98\pm
0.28\%$), ${\rm D}^{*+}\to{\rm D}^{0}\pi^{+}$ (BR of $67.7\pm 0.5\%$), and
${\rm D^{+}_{s}}\to\phi\pi^{+}$ (with $\phi\to\rm K^{+}K^{-}$) (BR of $2.27\pm
0.08\%$) [71]. The analyses were based on the reconstruction of decay vertices
displaced from the interaction vertex, exploiting the separation of a few
hundred microns induced by the weak decays of the ${\rm D^{0}}$, ${\rm
D^{+}}$, and ${\rm D^{+}_{s}}$ mesons. The displacement of the ${\rm
D^{0}}$-meson candidate decay vertex was used to select the ${\rm D^{*+}}$
meson which decays strongly at the primary vertex. This is performed by
combining the ${\rm D^{0}}$ candidates with a soft pion in an invariant-mass
analysis.

The ${\rm D^{0}}$, ${\rm D^{+}}$, and ${\rm D^{+}_{s}}$ candidates were
defined using pairs or triplets of tracks with proper charge sign combinations
with $|\eta|<0.8$, $p_{\rm T}>0.3\leavevmode\nobreak\ \rm{GeV}/\it{c}$, at
least 70 associated space points in the TPC, and at least two space points in
the ITS, with at least one in the SPD. The ${\rm D^{*+}}$ candidates were
formed by combining ${\rm D^{0}}$ candidates with tracks satisfying
$|\eta|<0.8$, $p_{\rm T}>0.1\leavevmode\nobreak\ \mathrm{GeV}/c$ and at least
two space points in the ITS, including at least one in the SPD. The selection
of tracks with $|\eta|<0.8$ limits the D-meson acceptance in rapidity, which,
depending on $p_{\rm T}$, varies from $|y_{\rm lab}|<0.5$ at low $p_{\rm T}$
to $|y_{\rm lab}|<0.8$ at $p_{\rm T}>5\leavevmode\nobreak\ \mathrm{GeV}/c$
[72]. A $p_{\rm T}$-dependent fiducial acceptance region was therefore defined
as $y_{\mathrm{fid}}(p_{\rm T})>|y_{\rm lab}|$, with $y_{\mathrm{fid}}(p_{\rm
T})$ increasing from 0.5 to 0.8 in the transverse momentum range $0<p_{\rm
T}<5\leavevmode\nobreak\ \mathrm{GeV}/c$ according to a second-order
polynomial function, and $y_{\mathrm{fid}}=0.8$ for $p_{\rm
T}>5\leavevmode\nobreak\ \mathrm{GeV}/c$. The selection strategy is the same
as in previous analyses [65]. The main variables used to select the D-meson
candidates are the separation between primary and secondary vertex, the
displacement of the tracks from the primary vertex, and the pointing of the
reconstructed D-meson momentum to the primary vertex. For the ${\rm D^{+}}$, a
selection on the impact parameter of the candidate with respect to the primary
vertex in the transverse plane was also applied. For the ${\rm
D^{+}_{s}}$-candidate selection, one of the two pairs of opposite-sign tracks
is required to have a reconstructed ${\rm K^{+}K^{-}}$ invariant mass
compatible with the PDG world average of the $\phi$ meson mass [71]. Further
background reduction is achieved by applying particle identification to select
charged pions and kaons using information of the TPC and TOF detectors. The
track particle identification (PID) is obtained using a 3$\sigma$ window
around the expected mean values of the specific ionisation energy loss (${\rm
d}E/{\rm d}x$) in the TPC gas and of the time of flight from the interaction
point to the TOF detector. A 2$\sigma$ window around the expected mean values
of the ${\rm d}E/{\rm d}x$ was applied, except for the lowest $p_{\rm T}$
interval, $1.5<p_{\rm T}<2\leavevmode\nobreak\ \mathrm{GeV}/c$, ${\rm D^{*+}}$
meson, and for the ${\rm D^{+}_{s}}$ meson in those cases in which no time-of-
flight information was available.

Figure 1: Examplary invariant-mass distributions for ${\rm D^{0}}$, ${\rm
D^{+}}$, and ${\rm D^{+}_{s}}$ candidates (plus charge conjugates) and the
mass difference $\Delta M=M_{{\rm K}\pi\pi}-M_{{\rm K}\pi}$ for ${\rm D^{*+}}$
candidates (and charge conjugates) in minimum-bias p–Pb collisions at
$\sqrt{s_{\scriptscriptstyle\rm NN}}=5.02\leavevmode\nobreak\ \mathrm{TeV}$.
The dashed curves represent the fit applied to the background, while the solid
lines represent the total fit function. In the case of the ${\rm D^{0}}$
meson, the contribution of signal reflections in the invariant-mass
distribution is shown using a gray dot-dashed line. In the case of the ${\rm
D^{+}_{s}}$ invariant-mass distribution, an additional Gaussian is used in the
fit function in order to describe the ${\rm D^{+}}$ signal peak on the left
side of the ${\rm D^{+}_{s}}$ signal.

The D-meson raw yields were obtained by fitting the candidate invariant-mass
distributions for each D-meson species and the mass difference $\Delta
M=M_{{\rm K}\pi\pi}-M_{{\rm K}\pi}$ for ${\rm D^{*+}}$. Examples of these
distributions are shown in Fig. 1 for ${\rm D^{0}}$, ${\rm D^{+}}$, ${\rm
D^{*+}}$, and ${\rm D^{+}_{s}}$ mesons in different $p_{\rm T}$ intervals. The
${\rm D^{0}}$, ${\rm D^{+}}$, and ${\rm D^{+}_{s}}$ candidate invariant-mass
distributions were fit with a function composed of a Gaussian for the signal
shape and an exponential term to describe the background shape. The $\Delta M$
distribution of the ${\rm D^{*+}}$ candidates was fit with a Gaussian function
for the signal shape and a threshold function multiplied by an exponential for
the background: $a\,\sqrt{\Delta M-m_{\pi}}\cdot{\rm e}^{b(\Delta
M-m_{\pi})}$, where $a$ and $b$ are free parameters. To account for the
contribution of signal candidates that are present in the invariant-mass
distribution of the ${\rm D^{0}}$ meson but were assigned the wrong decay-
particle mass (reflections) an additional term was included in the fit
function. The contribution of the reflections was modelled with a double
Gaussian function parametrised on their invariant-mass distributions from
Monte Carlo simulations.

For the $M_{{\rm KK}\pi}$ distribution, an additional Gaussian was used to
describe the ${\rm D^{+}}\to\rm{K}^{+}\rm{K}^{-}\pi^{+}$ signal peak present
on the left side of the ${\rm D^{+}_{s}}$ signal. The extracted signal is
denoted as $S$ and the background level under the signal peak is denoted as
$B$. The statistical significance of the observed signals, here defined as
($S/\sqrt{S+B}$), varies from 3 to 62, depending on the meson species, the
centrality and the $p_{\rm T}$ interval.

The D-meson raw yields extracted in each $p_{\rm T}$ interval were corrected
to obtain the prompt D-meson cross sections according to

$\frac{{\rm d^{2}}\sigma^{\rm prompt\,D}}{{\rm d}p_{\rm T}{\rm
d}y}=\frac{1}{\Delta p_{\rm T}}\cdot\frac{f_{\rm prompt}(p_{\rm
T})\cdot\frac{1}{2}\cdot N^{\rm D+\overline{D},raw}(p_{\rm T})}{c_{\Delta
y}(p_{\rm T})}\cdot\frac{1}{({\rm Acc}\times\epsilon)_{\rm prompt}(p_{\rm
T})}\cdot\frac{1}{{\rm BR}\cdot{L}_{\mathrm{int}}}\,.$ (1)

In the formula, $N^{\rm D+\overline{D},raw}$ is the raw yield (sum of
particles and antiparticles) in the laboratory rapidity interval $|y_{\rm
lab}|<y_{\rm fid}(p_{\rm T})$ in a $p_{\rm T}$ interval of width $\Delta
p_{\rm T}$. The raw yield includes contributions from prompt and non-prompt D
mesons. Non-prompt D mesons originating from beauty-hadron decays are labeled
as ‘feed-down’ in the following. The $f_{\rm prompt}$ term is the fraction of
prompt D mesons in the raw yield. The rapidity acceptance correction factor
$c_{\Delta y}$ was computed using the PYTHIA v6.4.21 event generator [73] with
the Perugia-2011 tune as the ratio between the generated D-meson yield in
$\Delta y=2\,y_{\rm fid}$, and that in $|y_{\rm lab}|<0.5$. The $c_{\Delta y}$
correction factor has a uniform D-meson rapidity distribution in $|y_{\rm
lab}|<y_{\rm fid}$ in the range $|y_{\rm lab}|<0.8$ as shown in [65]. The
factor $1/2$ accounts for the fact that the measured yields include particles
and antiparticles while the cross sections are given for particles only. The
$({\rm Acc}\times\epsilon)_{\rm prompt}$ is the product of the acceptance of
the detectors and the efficiency of prompt D mesons, where $\epsilon$ accounts
for primary vertex reconstruction, D-meson decay track reconstruction and
selection, as well as for D-meson candidate selection efficiencies. Finally,
BR is the branching ratio of the considered decay channel.

The acceptance and the efficiency were obtained by means of Monte Carlo
simulations, that include a detailed description of the apparatus geometry,
the detector response, as well as the LHC beam conditions. Proton–proton
collisions requiring a $\rm{c\overline{c}}$ or $\rm{b\overline{b}}$ pair
satisfying $|y|<1$ were generated using a PYTHIA v6.4.21 event generator [73]
with the Perugia-2011 tune. An underlying p–Pb collision, generated with
HIJING 1.36 [74], was superimposed to each PYTHIA event in order to describe
the charged-particle multiplicity and detector occupancy observed in data. To
reproduce the primary vertex resolution found in data which improves with
increasing multiplicity, generated events were weighted on the basis of their
charged particle multiplicity. The shape of the generated D-meson $p_{\rm T}$
distribution is consistent with that of FONLL pQCD calculations [1] at
$\sqrt{s}=5.02$ TeV. The results from FONLL calculations are found to be
consistent with pp data at $\sqrt{s}=5.02$ TeV though at upper edge of
uncertainties as described in [70].

Figure 2 shows the product of acceptance and efficiency $({\rm
Acc}\times\varepsilon)$ for prompt and feed-down D mesons with rapidity
$|y_{\rm lab}|<y_{\rm fid}(p_{\rm T})$. The ${\rm D^{0}}$, ${\rm D^{*+}}$, and
${\rm D^{+}_{s}}$ distributions are overall higher for the feed-down
contribution compared to that of the prompt D mesons, while the opposite is
true for the ${\rm D^{+}}$ efficiency because of the topological selection.

Figure 2: The product of acceptance and efficiency for ${\rm D^{0}}$, ${\rm
D^{+}}$, ${\rm D^{*+}}$, and ${\rm D^{+}_{s}}$ mesons as a function of
transverse momentum in p–Pb collisions at $\sqrt{s_{\scriptscriptstyle\rm
NN}}=5.02\leavevmode\nobreak\ \mathrm{TeV}$. The values for prompt (solid
line) and feed-down (dashed line) D mesons are shown.

The correction factor $f_{\mathrm{prompt}}$ was calculated per $p_{\rm T}$
interval using a FONLL-based method as described in [75]. The procedure uses
the B-meson production cross section in pp collisions at
$\sqrt{s}=5.02\leavevmode\nobreak\ \mathrm{TeV}$ estimated utilising FONLL
calculations, the $\mathrm{B}\rightarrow\mathrm{D}+X$ decay kinematics from
the EvtGen package [76], the efficiencies for D mesons from beauty-hadron
decays and a hypothesis on the nuclear modification factor
$R_{\mathrm{pPb}}^{\text{feed-down}}$ of D mesons from B decays. The $R_{\rm
pPb}$ of prompt and feed-down D mesons were assumed to be equal on the basis
of calculations including initial-state effects via the EPS09 nPDF
parametrisations [11] or the Colour Glass Condensate formalism [21], as well
as the measurements of the $\rm B^{0}$-meson production in p–Pb collisions at
$\sqrt{s_{\scriptscriptstyle\rm NN}}=5.02\leavevmode\nobreak\ \mathrm{TeV}$
published by the CMS Collaboration [77]. Further details are given in Sec. 4.
The resulting $f_{\rm prompt}$ values vary between 0.8 to 0.96 in the $|y_{\rm
lab}|<y_{\mathrm{fid}}(p_{\rm T})$ interval depending on the $p_{\rm T}$ range
and the D-meson species.

###  3.2 Analysis without D-meson decay-vertex reconstruction

In order to extend the cross section measurement down to $p_{\rm T}=0$, a
different analysis method, which does not employ geometrical selections on the
displaced decay-vertex topology, was utilized for the two-body decay ${\rm
D}^{0}\to{\rm K}^{-}\pi^{+}$ (and its charge conjugate) [65]. This analysis
technique is based on particle identification and on the estimation and
subtraction of the combinatorial background of K$\pi$ pairs. Tracks with
$|\eta|<0.8$ and $p_{\rm T}>0.4\leavevmode\nobreak\ \mathrm{GeV}/c$ were
selected by applying the same track-quality cuts and pion and kaon
identification criteria described above for the analysis with decay-vertex
reconstruction. The ${\rm D^{0}}$ and $\overline{\rm D}{}^{0}$ candidates were
formed by combining kaon and pion tracks with opposite charge sign (UnLike
Sign, ULS). The resulting candidates were selected by applying the $p_{\rm
T}$-dependent fiducial acceptance selection, $|y_{\rm lab}|<y_{\rm fid}(p_{\rm
T})$, adopted for the analyses with decay-vertex reconstruction. No selections
based on secondary-vertex displacement were applied because at very low
$p_{\rm T}$ the D-meson decay topology cannot be efficiently resolved due to
the insufficient resolution of the track impact parameter and the small
Lorentz boost. The combinatorial background was estimated with the track-
rotation technique. For each ${\rm D^{0}}$ (and $\overline{\rm D}{}^{0}$)
candidate, up to 19 combinatorial-background-like candidates were created by
rotating the kaon track by different angles in the range between
$\frac{\pi}{10}$ and $\frac{19\pi}{10}$ radians in azimuth. The invariant-mass
distribution of ULS K$\pi$ pairs in the transverse momentum interval $0<p_{\rm
T}<1\leavevmode\nobreak\ \mathrm{GeV}/c$ is shown in the left panel of Fig. 3
together with the one of the background estimated with the track-rotation
technique, which was normalised to match the yield of ULS pairs at one edge of
the invariant-mass interval considered for the extraction of the ${\rm D^{0}}$
signal.

The invariant-mass distribution of background candidates was subtracted from
the one of ULS K$\pi$ pairs and the resulting distribution, which contains the
${\rm D^{0}}$ signal and the remaining background, is shown in the right panel
of Fig. 3. The ${\rm D^{0}}$-meson raw signal (sum of particle and
antiparticle contributions) was extracted via a fit to the background-
subtracted invariant-mass distribution. The fit function is composed of a
Gaussian term to describe the signal, a second-order polynomial function to
model the remaining background, and a term describing the contribution of
signal candidates passing the selection criteria with swapped mass hypotheses
of the final-state kaon and pion (reflections), whose invariant-mass
distribution was taken from simulation. The signal-to-background ratio
increases from $6\cdot 10^{-4}$ to $3\cdot 10^{-2}$ with increasing $p_{\rm
T}$ and the statistical significance is about 9 in $0<p_{\rm
T}<1\leavevmode\nobreak\ \mathrm{GeV}/c$ and is greater than 15 for $p_{\rm
T}>2\leavevmode\nobreak\ \mathrm{GeV}/c$.

Figure 3: Invariant-mass distributions of ${\rm D}^{0}\to{\rm K}^{-}\pi^{+}$
candidates (and charge conjugates) for $0<p_{\rm T}<1\leavevmode\nobreak\
\mathrm{GeV}/c$. The left panel displays the invariant-mass distribution of
all ULS K$\pi$ pairs together with the background distribution estimated with
the track-rotation technique. The right panel shows the invariant-mass
distribution after subtracting the background estimated with the track-
rotation technique. The fit function is superimposed.

The acceptance and efficiency were determined from the same Monte Carlo
simulations used for the analysis with decay-vertex reconstruction. The
resulting $({\rm Acc}\times\epsilon)$ of prompt ${\rm D^{0}}$ mesons is shown
as a function of $p_{\rm T}$ in Fig. 4. Compared to the analysis with decay-
vertex reconstruction, the efficiency is higher by a factor of about 20 (3) at
low (high) $p_{\rm T}$ and it demonstrates a less steep $p_{\rm T}$
dependence. Note that for the analysis without decay-vertex reconstruction the
efficiency $\epsilon$ is almost independent of $p_{\rm T}$ and the increase of
the $({\rm Acc}\times\epsilon)$ with increasing $p_{\rm T}$ is mainly
determined by the geometrical acceptance of the apparatus. Unlike in the
analysis with decay-vertex reconstruction, the efficiency is the same for
prompt ${\rm D^{0}}$ mesons and ${\rm D^{0}}$ mesons from beauty-hadron
decays.

Figure 4:  Product of acceptance and efficiency of ${\rm D}^{0}\to{\rm
K}^{-}\pi^{+}$ (and charge conjugates) in p–Pb collisions for the analyses
with and without reconstruction of decay vertex.

The prompt contribution to the ${\rm D^{0}}$-meson raw yield, $f_{\rm
prompt}$, was estimated with the same FONLL-based method used for the analysis
with decay-vertex reconstruction. The resulting $f_{\rm prompt}$ values
decrease with increasing $p_{\rm T}$ (from about 0.96 for $p_{\rm
T}<3\leavevmode\nobreak\ \mathrm{GeV}/c$ to about 0.9 in the interval
$8<p_{\rm T}<12\leavevmode\nobreak\ \mathrm{GeV}/c$) and are larger than in
the analysis with decay-vertex reconstruction, since the feed-down component
is not enhanced by the selection criteria.

###  3.3 Measurement of the prompt D-meson fraction based on a data-driven
method

Figure 5: Left: Exemplary fits to the impact-parameter distributions of ${\rm
D^{0}}$, ${\rm D^{+}}$, and ${\rm D^{*+}}$ candidates. The curves show the fit
functions describing the prompt, feed-down, and background contributions as
well as their sum, as described in the text. Right: fraction of prompt ${\rm
D^{0}}$, ${\rm D^{+}}$, and ${\rm D^{*+}}$ raw yield as a function of
transverse momentum $p_{\rm T}$ compared with the values obtained with the
FONLL-based approach. The results from the data-driven method are shown as
square markers with the error bars (boxes) representing the statistical
(systematic) uncertainty. The central values of $f_{\rm prompt}$ from the
FONLL-based approach are shown as the dashed lines and the uncertainty as red
boxes.

The prompt fractions of ${\rm D^{0}}$, ${\rm D^{+}}$, and ${\rm D^{*+}}$
mesons, calculated via the FONLL-based method, were cross-checked for the
analysis with decay vertex reconstruction utilizing a data-driven method that
exploits the different shapes of the transverse-plane impact parameter to the
primary vertex ($d_{0}$) of prompt and feed-down D mesons. The D-meson
candidates were selected using the same criteria described in Section 3.1,
with the exception that for ${\rm D^{+}}$ the impact-parameter selection
criteria were not applied. An additional selection was based on the candidate
invariant-mass fits. The ${\rm D^{0}}$ and ${\rm D^{+}}$ mesons candidates
were selected to have an invariant mass $|M-M_{\mathrm{D}}|<1.5\sigma$, while
for ${\rm D^{*+}}$-meson candidates a $|\Delta M-\Delta
M_{\mathrm{D^{*+}}}|<2.5\sigma$ selection was applied, where $\sigma$ is the
standard deviation of the Gaussian function describing the D-meson invariant-
mass signal. The prompt fraction was estimated via an unbinned likelihood fit
of the $d_{0}$ distribution of the D-meson candidates using the fit function

$F(d_{0})=S\cdot\left[(1-f_{\rm prompt})F^{\rm feed\mbox{-}down}(d_{0})+f_{\rm
prompt}F^{\rm prompt}(d_{0})\right]+B\cdot F^{\rm backgr}(d_{0})\,.$ (2)

In this function, $F^{\rm prompt}(d_{0})$, $F^{\rm feed\mbox{-}down}(d_{0})$
and $F^{\rm backgr}(d_{0})$ are functions describing the impact-parameter
distributions of prompt and feed-down D mesons and of background candidates.
The function $F^{\rm prompt}$ consists of a detector resolution term modeled
with a Gaussian function and a symmetric exponential term,
$\frac{1}{2\lambda}\exp{\left(-\frac{\lvert d_{0}\rvert}{\lambda}\right)}$
(with $\lambda$ as a free parameter), with the latter describing the tails of
the impact-parameter distribution of prompt D mesons. The $F^{\rm
feed\mbox{-}down}$ is the convolution of the detector resolution term with a
symmetric double-exponential function ($F^{\rm feed\mbox{-}down}_{\rm true}$)
that describes the intrinsic impact-parameter distribution of D mesons from
B-meson decays, which is determined by the decay length and decay kinematics
of B mesons. The parameters of the $F^{\rm prompt}$ and $F^{\rm
feed\mbox{-}down}_{\rm true}$ functions were fixed to the values obtained by
fitting the distributions from Monte Carlo simulations, with the exception of
the Gaussian width of the detector-resolution term, which was kept free when
applying the fit to the data in order to compensate for a possible imperfect
description of the impact-parameter resolution in the simulation. The function
$F^{\rm backgr}$ was parametrised on the impact-parameter distribution of
background candidates, which were selected from side bands relative to the
signal peak in the invariant-mass distributions, and in the case of ${\rm
D^{*+}}$, the mass-difference distribution. The function consists of a double
Gaussian and a symmetric exponential term, which describes the tails, as
reported in Ref. [65]. In the case of the ${\rm D^{+}}$, the function presents
a double-peak structure with a depletion around zero that is induced by the
selections applied.

The left panels of Fig. 5 show examples of fits to the impact-parameter
distributions of ${\rm D^{0}}$, ${\rm D^{+}}$, and ${\rm D^{*+}}$ mesons in
the transverse-momentum intervals $2<p_{\rm T}<3\leavevmode\nobreak\
\mathrm{GeV}/c$, $3<p_{\rm T}<4\leavevmode\nobreak\ \mathrm{GeV}/c$, and
$5<p_{\rm T}<6\leavevmode\nobreak\ \mathrm{GeV}/c$, respectively. The prompt
fraction estimated using the data-driven approach has systematic uncertainties
due to (i) the impact-parameter distribution assumed for prompt and feed-down
D mesons and background candidates; (ii) the uncertainty on the signal and
background yields extracted from the invariant-mass fits; and (iii) the
consistency of the procedure, evaluated via a Monte Carlo closure test. These
uncertainties were estimated using the procedures described in Ref. [65]. The
total systematic uncertainty on $f_{\rm prompt}$ based on the data-driven
approach for the three D-meson species is about 2–3% in the interval $3<p_{\rm
T}<16\leavevmode\nobreak\ \mathrm{GeV}/c$ and about 5% in the interval
$2<p_{\rm T}<3\leavevmode\nobreak\ \mathrm{GeV}/c$ and above 16 GeV/$c$.

The prompt fraction of ${\rm D^{0}}$, ${\rm D^{+}}$, and ${\rm D^{*+}}$ mesons
measured utilizing the data-driven method is compared with the one calculated
with the FONLL-based approach in the right panels of Fig. 5. For ${\rm
D^{0}}$, ${\rm D^{+}}$, and ${\rm D^{*+}}$ in $1<p_{\rm
T}<2\leavevmode\nobreak\ \mathrm{GeV}/c$ and for the ${\rm D^{*+}}$ in
$24<p_{\rm T}<36\leavevmode\nobreak\ \mathrm{GeV}/c$, given the poor precision
of the impact-parameter fit, it was not possible to determine $f_{\rm prompt}$
with the data-driven approach. The prompt fraction measured with the impact-
parameter fits is compatible with the FONLL-based estimation within 1$\sigma$
for almost all points.

##  4 Systematic uncertainties

Table 1: Summary of relative systematic uncertainties on ${\rm D^{0}}$, ${\rm D^{+}}$, ${\rm D^{*+}}$, and ${\rm D^{+}_{s}}$ production cross sections. The event centrality-dependent uncertainties are marked by the symbol $\diamond$. | ${\rm D^{0}}$ | ${\rm D^{+}}$ | ${\rm D^{*+}}$ | ${\rm D^{+}_{s}}$
---|---|---|---|---
$p_{\rm T}$ ($\mathrm{GeV}/c$) | 0–1 | 2–2.5 | 10–12 | 2–2.5 | 10–12 | 2–2.5 | 10–12 | 2–4 | 8–12
Signal yield $\diamond$ | 5% | 3% | 3% | 2% | 3% | 7% | 2% | 3% | 2%
Tracking efficiency | 2.5% | 2.5% | 2.5% | 3.7% | 4% | 3.2% | 4.5% | 3.7% | 4%
Selection efficiency | negl. | 3% | 3% | 7% | 4% | 2% | 2% | 6% | 4%
PID efficiency | negl. | negl. | negl. | negl. | negl. | negl. | negl. | 1% | 1%
$p_{\rm T}$ shape in MC | negl. | negl. | negl. | negl. | negl. | negl. | negl. | negl. | negl.
Feed-down $\diamond$ |  ${}^{+1.3}_{-1.7}$% |  ${}^{+4.2}_{-4.9}$% |  ${}^{+4.1}_{-5.6}$% |  ${}^{+1.8}_{-2.1}$% |  ${}^{+2.3}_{-3.2}$% |  ${}^{+3.0}_{-3.5}$% |  ${}^{+1.9}_{-2.6}$% |  ${}^{+3.6}_{-4.2}$% |  ${}^{+4.4}_{-5.6}$%
Branching ratio | 1.0% | 3.1% | 1.3% | 3.5%
Normalisation | 3.7%

Systematic uncertainties on the D-meson production cross sections were
estimated considering the following sources:
(i) extraction of the raw yield from the invariant-mass distributions; (ii)
track reconstruction efficiency; (iii) D-meson selection efficiency; (iv) PID
efficiency; (v) the assumption on the shape of the D-meson $p_{\rm T}$
spectrum generated in the simulation; (vi) subtraction of the feed-down from
beauty-hadron decays.
In addition, the $p_{\rm T}$-differential cross sections have a systematic
uncertainty on the overall normalisation induced by the uncertainties on the
integrated luminosity of 3.7% [68] and on the branching ratios of the
considered D-meson decays [71]. The estimated values of the relative
systematic uncertainties are summarised in Table 1. The contributions of the
different sources were summed in quadrature to obtain the total systematic
uncertainty.

The systematic uncertainties on the raw yield extraction were evaluated for
each D-meson species by repeating the invariant-mass distribution fits, for
each $p_{\rm T}$ and centrality interval, varying the lower and upper limits
of the fit range and the functional form of the background fit function. In
addition, the same approach was used with a bin-counting method, in which the
signal yield was obtained by integrating the invariant-mass distribution after
subtracting the background estimated from a fit to the side bands. For ${\rm
D^{0}}$ mesons, an additional contribution due to the description of signal
reflections in the invariant-mass distribution was estimated by varying the
ratio of the integral of the reflections over the integral of the signal and
the shape of the templates used in the invariant-mass fits. The systematic
uncertainty was defined as the root mean square of the distribution of the
signal yields obtained from the described variations. The uncertainty ranges
between 1% and 15% depending on the D-meson species, $p_{\rm T}$, event
centrality and charged-particle multiplicity intervals of the measurement. An
increase in the raw yield extraction uncertainties was observed in the most
central collisions due to the lower $S$/$B$ ratio. For the ${\rm D^{0}}$-meson
analysis without decay-vertex reconstruction, different configurations of the
rotation angle were used to estimate the background with the track-rotation
technique. Furthermore, three alternative approaches were tested to estimate
the background distribution: like-sign (LS) pairs, event mixing, and side-band
fit [65]. The raw yield values obtained subtracting these alternative
background distributions were found to be consistent with those from the
default configuration of the track-rotation method within the uncertainty
estimated by varying the fit conditions and therefore no additional systematic
uncertainty was assigned. The systematic uncertainty on the track
reconstruction efficiency was estimated by varying the track-quality selection
criteria and by comparing the probability to match the tracks from the TPC to
the hits in the ITS, in the data and simulation. The comparison of the
matching efficiency in the data and simulation was made after weighting the
relative abundances of primary and secondary particles in the simulation to
match those in the data, which were estimated via fits to the track impact-
parameter distributions [78]. The estimated uncertainty depends on the D-meson
$p_{\rm T}$ and it ranges from 2.5% to 4% for the two-body decay of ${\rm
D^{0}}$ mesons and from 3.7% to 4.5% for the three-body decays of ${\rm
D^{+}}$, ${\rm D^{*+}}$, and ${\rm D^{+}_{s}}$ mesons.

The uncertainty on the selection efficiency originates from imperfections in
the description of the D-meson kinematic and decay properties and of the
detector resolution and alignment in the simulation. For the analyses based on
the decay-vertex reconstruction, the uncertainty was estimated by comparing
the corrected yields obtained by repeating the analysis with different sets of
selection criteria, resulting in a significant modification of efficiencies,
raw yield, and background estimates.

The assigned uncertainty for non-strange D mesons is 2–3% in most of the
$p_{\rm T}$ intervals and it increases to 7% at low $p_{\rm T}$, where the
efficiencies are low and steeply fall with decreasing $p_{\rm T}$, because of
the tighter geometrical selections. A larger uncertainty (ranging from 7% at
high $p_{\rm T}$ to 14% at low $p_{\rm T}$) was estimated for the ${\rm
D^{+}_{s}}$ mesons, for which more stringent selection criteria were used in
the analysis, as compared to non-strange D mesons. In the case of the ${\rm
D^{0}}$-meson analysis without decay-vertex reconstruction, the stability of
the corrected yield was tested against variations of the single-track $p_{\rm
T}$ selection and no systematic effect was observed.

In addition, the efficiency values could also be sensitive to the generated
shapes of the D-meson transverse-momentum distributions and to the
multiplicity of particles produced in the collision. The systematic
uncertainty due to the generated D-meson $p_{\rm T}$ spectrum shape was
estimated by considering different input distributions (PYTHIA, FONLL) and was
found to be negligible. The effect of possible differences between the
charged-particle multiplicity distributions in data and multiplicity-weighted
simulation, used to compute the efficiencies in the different centrality
classes, as explained in section 3.1, varied between 0 and 2% depending on the
D-meson species, $p_{\rm T}$, event centrality, and charged-particle
multiplicity intervals.

To estimate the uncertainty on the PID-selection efficiency the analysis was
repeated without PID selection, or with less stringent criteria in the cases
where the signal extraction was not reliable without PID, as for example for
the ${\rm D^{+}_{s}}$ and the ${\rm D^{0}}$-meson analysis without decay-
vertex reconstruction. In addition, the pion and kaon PID selection
efficiencies were compared in the data and in simulation using high purity
samples of pions from the decay of $\rm K^{0}_{s}$ and kaons identified with
the TOF combined with the D-meson decay kinematics. The PID uncertainty was
found to vary between 0 and 1.5% depending on the PID selection criteria used
for each D-meson species.

The systematic uncertainty on the subtraction of feed-down from beauty-hadron
decays (i.e. the calculation of the $f_{\rm prompt}$ fraction) was estimated
by varying the FONLL parameters (b-quark mass, factorisation and
renormalisation scales) as described in [2] and by varying the hypothesis on
the nuclear modification factor of feed-down D mesons in the range
$0.9<R(Q)^{\text{feed-
down}}_{\mathrm{pPb}}/R(Q)^{\mathrm{prompt}}_{\mathrm{pPb}}<1.3$ for the
integrated centrality interval and central collisions, and between
$0.9<Q^{\text{feed-
down}}_{\mathrm{pPb}}/Q^{\mathrm{prompt}}_{\mathrm{pPb}}<1.1$ for the
peripheral collisions, where the possible differences of the D-meson
production mechanisms in p–Pb with respect to pp collisions are expected to be
reduced as observed for both charmed mesons and charged particles. The
uncertainty ranges between $2\%$ and $5\%$ depending on the D-meson species,
$p_{\rm T}$, event centrality and charged-particle multiplicity intervals.

##  5 Results

###  5.1 $p_{\rm T}$-differential cross sections

Figure 6:  Left: inclusive ${\rm D^{0}}$-meson production cross sections from
the analysis without decay-vertex reconstruction in p–Pb collisions and pp
collisions, both at $\sqrt{s_{\scriptscriptstyle\rm
NN}}=5.02\leavevmode\nobreak\ \mathrm{TeV}$. The cross section measured in pp
collision [70] is scaled by the Pb mass number ($A=208$) and corrected for the
rapidity shift in p–Pb collisions using FONLL calculations. Right: $p_{\rm
T}$-differential production cross section of prompt ${\rm D^{0}}$ mesons with
$-0.96<y_{\rm cms}<0.04$ in p–Pb collisions at $\sqrt{s_{\scriptscriptstyle\rm
NN}}=5.02\leavevmode\nobreak\ \mathrm{TeV}$, measured with and without decay-
vertex reconstruction. The vertical bars and the empty boxes represent the
statistical and systematic uncertainties. The inset shows the ratio of the
measurements in their common $p_{\rm T}$ range.

The analysis without decay-vertex reconstruction allows for a direct
measurement of the inclusive ${\rm D^{0}}$-meson cross section because no
selections that alter the fraction of prompt and feed-down D mesons are
applied. The inclusive ${\rm D^{0}}$-meson cross section in p–Pb collisions is
shown in the left panel of Fig. 6 and is compared with the measurement in pp
collisions at the same centre-of-mass energy, published in [70]. The cross
section in pp collisions was scaled by the Pb mass number $A=208$ and
corrected for the rapidity shift in p–Pb collisions using FONLL calculations.
The correction for the rapidity shift is a $p_{\rm T}$-dependent factor of the
order of 1–3%. The uncertainty assigned on this correction is evaluated
varying the quark mass and the perturbative scale parameters and including the
PDFs uncertainty, and is 1% at low $p_{\rm T}$ and negligible at high $p_{\rm
T}$.
The total cross section for inclusive ${\rm D^{0}}$-meson production in p–Pb
collisions per unit of rapidity in $-0.96<y_{\rm cms}<0.04$ was obtained by
integrating the $p_{\rm T}$-differential cross section shown in the left panel
of Fig. 6. The systematic uncertainty was defined by propagating the yield
extraction uncertainty as uncorrelated among the $p_{\rm T}$ intervals and all
the other uncertainties as correlated. The cross section was then extrapolated
to the whole $p_{\rm T}$ range using FONLL calculations in order to take into
account the fraction of cross section not measured for $p_{\rm T}>12$ GeV/$c$.
An uncertainty was estimated for the extrapolation varying the quark mass and
the perturbative scale parameters and including the PDFs uncertainty. The
resulting cross section is

${\rm d}\sigma^{\rm inclusive\,D^{0}}_{\rm p-Pb,\,5.02\,TeV}/{\rm d}y=91.2\pm
3.4\,({\rm stat.})\pm 3.2\,({\rm syst.})\pm 3.4\,({\rm lumi.})\pm 0.9\,({\rm
BR})^{+0.4}_{-0.2}\,({\rm extrap.})\,\leavevmode\nobreak\ {\rm mb}.$ (3)

The right panel of Fig. 6 shows the comparison of the $p_{\rm T}$-differential
production cross sections for prompt ${\rm D^{0}}$ mesons with $-0.96<y_{\rm
cms}<0.04$ in p–Pb collisions at $\sqrt{s_{\scriptscriptstyle\rm
NN}}=5.02\leavevmode\nobreak\ \mathrm{TeV}$ obtained from the analysis with
and without decay-vertex reconstruction. The results are consistent within
statistical uncertainties.

Figure 7:  $p_{\rm T}$-differential production cross sections of prompt ${\rm
D^{0}}$, ${\rm D^{+}}$, ${\rm D^{*+}}$, and ${\rm D^{+}_{s}}$ mesons with
$-0.96<y_{\rm cms}<0.04$ in p–Pb collisions at $\sqrt{s_{\scriptscriptstyle\rm
NN}}=5.02\leavevmode\nobreak\ \mathrm{TeV}$ compared with the respective pp
reference cross sections [70] scaled by the Pb mass number ($A=208$) and
corrected for the rapidity shift. For the ${\rm D^{0}}$ meson, the results in
the range $0<p_{\rm T}<1\leavevmode\nobreak\ \mathrm{GeV}/c$ are obtained from
the analysis that was performed without decay-vertex reconstruction, while
those in the range $1<p_{\rm T}<36\leavevmode\nobreak\ \mathrm{GeV}/c$ are
taken from the analysis with decay-vertex reconstruction. The vertical bars
and the empty boxes represent the statistical and systematic uncertainties.

Considering the statistical and systematic uncertainties obtained in the two
analyses, the most precise measurement of the prompt ${\rm D^{0}}$ production
cross section is obtained using the results from the analysis without decay-
vertex reconstruction in the interval $0<p_{\rm T}<1\leavevmode\nobreak\
\mathrm{GeV}/c$ and the analysis with decay-vertex reconstruction for $p_{\rm
T}>1\leavevmode\nobreak\ \mathrm{GeV}/c$. The resulting cross section is shown
in the top-left panel of Fig. 7.

The total cross section for prompt ${\rm D^{0}}$-meson production per unit of
rapidity in $-0.96<y_{\rm cms}<0.04$ was also calculated by integrating the
$p_{\rm T}$-differential measurement reported in the top-left panel of Fig. 7,
obtained combining the methods with and without decay-vertex reconstruction.
The systematic uncertainties were propagated as described above for the total
cross section of inclusive ${\rm D^{0}}$ mesons. The resulting value is

${\rm d}\sigma^{\rm prompt\,D^{0}}_{\rm p-Pb,\,5.02\,TeV}/{\rm d}y=88.5\pm
2.7\,({\rm stat.})^{+5.3}_{-6.1}\,({\rm syst.})\pm 3.3\,({\rm lumi.})\pm
0.9\,({\rm BR})\leavevmode\nobreak\ {\rm mb}.$ (4)

In Ref. [65], the ${\rm c\overline{c}}$ production cross section in the
rapidity interval $-0.96<y_{\rm cms}<0.04$ was reported. This calculation used
the fraction of charm quarks hadronising into ${\rm D^{0}}$ mesons to be $f$(c
$\rightarrow{\rm D^{0}}$) = $0.542\pm 0.024$ which was derived in Ref. [79] by
averaging the measurements in $e^{+}e^{-}$ collisions at LEP. Recent
measurements of the $\Lambda_{c}$-baryon production cross section in pp
collisions at $\sqrt{s}=7$ TeV and in p–Pb collisions at $\sqrt{s_{\rm
NN}}=5.02$ TeV [80, 81] suggest that the fragmentation fractions of charm
quarks into charmed baryons in pp collisions at LHC energies might differ
significantly from the LEP results. Therefore, more precise measurements of
charmed-baryon production cross sections are needed for an accurate
calculation of the charm production cross section.

The average transverse momentum ${\langle p_{{\mathrm{T}}}\rangle}$ of prompt
${\rm D^{0}}$ mesons was obtained by fitting the cross section reported in the
top-left panel of Fig. 7 with a power-law function $f(p_{\rm T})=C\,p_{\rm
T}/(1+(p_{\rm T}/p_{0})^{2})^{n}$, where $C$, $p_{0}$ and $n$ are the free
parameters. The result is:

${\langle p_{{\mathrm{T}}}\rangle}^{\rm prompt\,D^{0}}_{\rm
p-Pb,\,5.02\,TeV}=2.07\pm 0.02\,({\rm stat.})\,\pm 0.04\,({\rm
syst.})\leavevmode\nobreak\ \mathrm{GeV}/c\,.$ (5)

where the systematic uncertainties were estimated with the procedure described
in Ref. [65]. The result is compatible within statistical uncertainties with
the one obtained in pp collisions at the same centre-of-mass energy: ${\langle
p_{{\mathrm{T}}}\rangle}^{\rm prompt\,D^{0}}_{\rm pp,\,5.02\,TeV}=2.06\pm
0.03\,({\rm stat.})\,\pm 0.03\,({\rm syst.})\leavevmode\nobreak\
\mathrm{GeV}/c$ [70].

The $p_{\rm T}$-differential cross sections for the other three D-meson
species (${\rm D^{+}}$, ${\rm D^{*+}}$, and ${\rm D^{+}_{s}}$) are shown in
the other panels of Fig. 7. The cross sections measured in p–Pb collisions are
compatible with the measurements published using the 2013 p–Pb data sample
[63, 64], while having a factor 1.5–2 smaller statistical and systematic
uncertainties and an extended $p_{\rm T}$ reach. The cross sections in p–Pb
collisions are compared with the corresponding pp reference cross sections at
the same centre-of-mass energy [70] and rapidity interval.

###  5.2 The $p_{\rm T}$-differential nuclear modification factor

The nuclear modification factor is computed as:

$R_{\rm pPb}=\frac{1}{A}\,\frac{{\rm d^{2}}\sigma_{\rm p-Pb}^{\rm
prompt\,D}/{\rm d}p_{\rm T}{\rm d}y}{{\rm d^{2}}\sigma^{\rm prompt\,D}_{\rm
pp}/{\rm d}p_{\rm T}{\rm d}y},$ (6)

where ${\rm d^{2}}\sigma_{\rm p-Pb}^{\rm prompt\,D}/{\rm d}p_{\rm T}{\rm d}y$
is the D-meson $p_{\rm T}$-differential cross section in $-0.96<y_{\rm
cms}<0.04$ in p–Pb collisions at $\sqrt{s_{\scriptscriptstyle\rm
NN}}=5.02\leavevmode\nobreak\ \mathrm{TeV}$, $A$ is the mass number of the Pb
nucleus and ${\rm d^{2}}\sigma^{\rm prompt\,D}_{\rm pp}/{\rm d}p_{\rm T}{\rm
d}y$ is the cross section in pp collisions at the same centre-of-mass energy
from [70] corrected for the rapidity shift in p–Pb collisions. The systematic
uncertainties of the p–Pb and pp measurements were considered to be
independent and were propagated quadratically, with the exception for the BR
uncertainty, which cancels out in the ratio, and the uncertainty on the feed-
down correction, which was recalculated for the ratio of cross sections by
consistently varying the FONLL calculation parameters in the numerator and the
denominator.

Figure 8 shows the nuclear modification factors $R_{\rm pPb}$ of prompt ${\rm
D^{0}}$, ${\rm D^{+}}$, and ${\rm D^{*+}}$ mesons in the left panel and their
average, along with the $R_{\rm pPb}$ of ${\rm D^{+}_{s}}$ mesons, in the
right panel.

With the current uncertainties it is not possible to disentangle a possible
mass dependent effect originating from a collective expansion of the system
that would modify the ${\rm D^{*+}}$ spectrum differently with respect to the
${\rm D^{0}}$ and ${\rm D^{+}}$ spectra. Therefore, the average of the nuclear
modification factors of the three non-strange D-meson species is considered
and it was calculated using the inverse of the relative statistical
uncertainties as weights. The systematic uncertainty of the average was
calculated by propagating the uncertainties through the weighted average,
while considering the contributions from tracking efficiency and beauty feed-
down correction as fully correlated among the three species. The D-meson
$R_{\rm pPb}$ is compatible with unity over the entire measured $p_{\rm T}$
interval within 2 standard deviations. The $R_{\rm pPb}$ of strange and non-
strange D mesons are compatible among each other within statistical and
systematic uncertainties.

Figure 8:  Nuclear modification factors $R_{\rm pPb}$ of prompt D mesons in
p–Pb collisions at $\sqrt{s_{\scriptscriptstyle\rm
NN}}=5.02\leavevmode\nobreak\ \mathrm{TeV}$. Left: $R_{\rm pPb}$ of ${\rm
D^{0}}$, ${\rm D^{+}}$, and ${\rm D^{*+}}$ mesons. Right: average $R_{\rm
pPb}$ of non-strange D-meson species in the interval $1<p_{\rm
T}<36\leavevmode\nobreak\ \mathrm{GeV}/c$ [63], shown together with the ${\rm
D^{0}}$ $R_{\rm pPb}$ in $0<p_{\rm T}<1\leavevmode\nobreak\ \mathrm{GeV}/c$
and the $R_{\rm pPb}$ of ${\rm D^{+}_{s}}$ mesons in the interval $2<p_{\rm
T}<24\leavevmode\nobreak\ \mathrm{GeV}/c$. The vertical bars and the empty
boxes represent the statistical and systematic uncertainties. The black-filled
box at $R_{\rm pPb}=1$ represents the normalisation uncertainty.

The D-meson nuclear modification factor is also compared with theoretical
calculations, shown in Fig. 9. In the left panel, four theoretical
calculations that include only CNM effects are displayed. A calculation based
on the Colour Glass Condensate formalism [21, 82] describes the data within a
2$\sigma$ uncertainty in the entire $p_{\rm T}$ range, although the model
underestimates systematically the measured points at low $p_{\rm T}$ ($p_{\rm
T}<6$ GeV/$c$). A FONLL calculation with CTEQ6M PDFs [83] and EPPS16 NLO
nuclear modification [14] is compatible with the data within the
uncertainties. The measurement lies on the upper limit of the EPPS16 nPDF
uncertainty band, while this is not the case for the D-meson $R_{\rm pPb}$ at
forward rapidity measured by LHCb [84, 15]. The data are also described within
the uncertainties by a LO pQCD calculation with intrinsic $k_{\rm T}$
broadening, nuclear shadowing, and energy loss of the charm quarks in cold
nuclear matter (Vitev et al.) [85]. The calculation by Kang et al., that
consists of a higher-twist calculation based on incoherent multiple
scatterings, has a different trend with respect to the other models and it is
excluded by the data for $p_{\rm T}<4\leavevmode\nobreak\ \mathrm{GeV}/c$.

In the right panel of Fig. 9, the measurements are compared with the
calculations of two transport models, Duke [52] and POWLANG [53], both of
which assume that a QGP is formed in p–Pb collisions. These models are both
based on the Langevin approach for the transport of heavy quarks through an
expanding deconfined medium described by relativistic viscous hydrodynamics.
The Duke model includes both collisional and radiative energy loss. The
POWLANG model considers only collisional processes with two choices for the
transport coefficients, based on hard-thermal-loop (HTL) and lattice-QCD
(lQCD) calculations. For both the Duke and the HTL based POWLANG estimates,
the D-meson nuclear modification factor distribution has a peak structure,
with the maximum at $p_{\rm T}\approx 2.5\leavevmode\nobreak\ \mathrm{GeV}/c$
and $p_{\rm T}\approx 3.5\leavevmode\nobreak\ \mathrm{GeV}/c$, respectively,
possibly followed by a moderate ($<20$–30%) suppression at higher $p_{\rm T}$,
resulting from the interplay of CNM effects and interactions of charm quarks
with the radially expanding medium. The trend suggested by these models is not
supported by the data. The strong enhancement at $p_{\rm T}\sim 3-4$ GeV/$c$
observed in the model calculations is not consistent with the measured $R_{\rm
pPb}$, and a suppression larger than 10% for $p_{\rm T}>8$ GeV/$c$ is excluded
by the data with a 98% confidence level.

Figure 9:  Nuclear modification factor $R_{\rm pPb}$ of prompt non-strange D
mesons in p–Pb collisions at $\sqrt{s_{\scriptscriptstyle\rm
NN}}=5.02\leavevmode\nobreak\ \mathrm{TeV}$. In the left panel, the data are
compared with calculations of theoretical models that include only CNM
effects: CGC [82], FONLL [2] with EPPS16 nPDFs [14], a LO pQCD calculation
(Vitev et al.) [85], and a calculation based on incoherent multiple
scatterings (Kang et al.) [86]. In the right panel, the predictions of the
Duke [52] and POWLANG [53] transport models are compared with the measured
D-meson $R_{\rm pPb}$. The vertical bars and the empty boxes represent the
statistical and systematic uncertainties. The black-filled box at $R_{\rm
pPb}=1$ represents the normalisation uncertainty.

The $p_{\rm T}$-integrated nuclear modification factor of prompt ${\rm D^{0}}$
mesons in $-0.96<y_{\rm cms}<0.04$ was obtained from Eq. 6 by integrating the
$p_{\rm T}$-differential cross sections in pp and p–Pb collisions. The result
is

$R_{\rm pPb}^{\rm prompt\,D^{0}}(p_{\rm T}>0,\,-0.96<y_{\rm cms}<0.04)=0.96\pm
0.05\,({\rm stat.})\,^{+0.07}_{-0.07}({\rm syst.})\,$ (7)

and it is consistent with the atomic mass number scaling of the total charm
cross section.

###  5.3 The $p_{\rm T}$ and centrality-dependent nuclear modification factor

The measurement of the nuclear modification factor was also computed in
various centrality intervals, where the centrality is defined using the energy
deposited by neutrons in the ZDC positioned in the Pb-going side (ZN energy),
as described in Section 2. For each centrality class the nuclear modification
factor, $Q_{\mathrm{pPb}}$, is defined as

$Q_{\mathrm{pPb}}=\frac{({\rm d}^{2}N^{\rm prompt\,D}/{\rm d}p_{\rm T}{\rm
d}y)^{\mathrm{i}}_{\mathrm{p-Pb}}}{\langle T_{\mathrm{pPb}}\rangle_{\rm
i}\,\times\,(\mathrm{d}^{2}\sigma^{\rm
prompt\,D}_{\mathrm{pp}}/\mathrm{d}p_{\rm T}{\rm d}y)}\,,$ (8)

where $({\rm d}^{2}N^{\rm prompt\,D}/{\rm d}p_{\rm T}{\rm
d}y)^{\mathrm{i}}_{\mathrm{p-Pb}}$ is the yield of prompt D mesons in p–Pb
collisions and $\langle T_{\mathrm{pPb}}\rangle_{\rm i}$ is the average
nuclear overlap function in a given centrality class.

The $\langle T_{\mathrm{pPb}}\rangle_{\rm i}$ is estimated with the hybrid
approach described in Ref. [69] and is based on the assumption that the
charged-particle multiplicity measured at mid-rapidity ($-1<\eta_{\rm cms}<0$)
scales with the number of participant nucleons, $N_{\rm part}$. The average
nuclear overlap function is defined as $\langle T_{\mathrm{pPb}}\rangle_{\rm
i}=\frac{\langle N_{\rm coll}\rangle_{\rm i}}{\sigma_{\rm NN}}\,$ where
$\sigma_{\rm NN}=(67.6\pm 0.6)\leavevmode\nobreak\ \mathrm{mb}$ is the
interpolated inelastic nucleon–nucleon cross section at
$\sqrt{s_{\scriptscriptstyle\rm NN}}=5.02\leavevmode\nobreak\ \mathrm{TeV}$
[87] and $\langle N_{\rm coll}\rangle_{\rm i}$ is the average number of binary
nucleon–nucleon collisions in a given centrality class. The latter is obtained
as

$\langle N_{\rm coll}\rangle_{\rm i}=\langle N_{\rm part}\rangle_{\rm
i}-1=\langle N_{\rm part}^{\rm MB}\rangle\cdot\bigg{(}\frac{\langle{\rm
d}N_{\rm ch}/{\rm d}\eta\rangle_{\rm i}}{\langle{\rm d}N_{\rm ch}/{\rm
d}\eta\rangle^{\rm MB}}\bigg{)}_{-1<\eta<0}-1\,,$ (9)

where $\langle N_{\rm part}^{\rm MB}\rangle=7.7$ [88] is the average number of
participants in minimum bias collisions. The values of $\langle
T_{\mathrm{pPb}}\rangle$ used for the analyses are reported in Table 2 [88].

Table 2:  $\langle T_{\mathrm{pPb}}\rangle$ and relative uncertainties for each centrality class considered in the analysis. Centrality classes | 0–10% | 10–20% | 20–40% | 40–60% | 60–100%
---|---|---|---|---|---
$\langle T_{\mathrm{pPb}}\rangle$ (1/mb) | 0.172 | 0.158 | 0.137 | 0.102 | 0.046
Rel. unc. | 6.9% | 3.7% | 1.7% | 4.8% | 5.2%

The average of prompt ${\rm D^{0}}$, ${\rm D^{+}}$, and ${\rm D^{*+}}$ meson
$Q_{\mathrm{pPb}}$ was calculated as a function of $p_{\rm T}$ in the interval
$1<p_{\rm T}<36\leavevmode\nobreak\ \mathrm{GeV}/c$ in 0–10%, 10–20%, 20–40%,
40–60%, and 60–100% centrality classes, and is shown in Fig. 10. The D-meson
$Q_{\mathrm{pPb}}$ measurement shows a hint of suppression in the interval
$1<p_{\rm T}<2$ GeV/$c$. The observed suppression is strongest in the most
central collisions. This is qualitatively expected from a stronger shadowing
at low Bjorken-$x$ in central collisions. There is also a hint of enhancement
at $2<p_{\rm T}<6$ GeV/$c$ in the most central classes (0–40% centrality). The
results are also compared with the charged-particle $Q_{\mathrm{pPb}}$ [69]
111The $\langle T_{\mathrm{pPb}}\rangle$ values used to compute the charged-
particles $Q_{\mathrm{pPb}}$ were updated with respect to [69] according to
the values in [88]. in each centrality class. A similar trend is observed for
prompt D mesons and charged particles in each centrality class.

Figure 10:  Nuclear modification factors of prompt D mesons as a function of
$p_{\rm T}$ in 0–10%, 10–20%, 20–40%, 40–60%, and 60–100% centrality classes
compared with those of charged particles [69]. The vertical bars represent the
statistical uncertainties while the empty boxes and the shaded boxes represent
the systematic uncertainties for the prompt D mesons and for the charged
particles. The colour-filled boxes at $Q_{\mathrm{pPb}}$ $=1$ represent the
normalisation uncertainties on the $\langle T_{\mathrm{pPb}}\rangle$ [88].
Figure 11: D-meson $Q_{\mathrm{pPb}}$ measured in the 0–10% centrality class
compared with the predictions of the Duke [52] and POWLANG [53] transport
models. The vertical bars and the empty boxes represent the statistical and
systematic uncertainties. The colour-filled boxes at $Q_{\mathrm{pPb}}$ $=1$
represent the normalisation uncertainties.

The D-meson $Q_{\mathrm{pPb}}$ in the 0–10% centrality class is compared with
the predictions of the Duke [52] and POWLANG [53] transport models in Fig. 11.
The POWLANG model predicts a pronounced bump in the nuclear modification
factor at intermediate $p_{\rm T}$ ($3<p_{\rm T}<6$ GeV/$c$), which is not
supported by the data, considering that the systematic uncertainties are
mostly correlated among the $p_{\rm T}$ intervals of the measurement. At
higher $p_{\rm T}$ ($p_{\rm T}>7$ GeV/$c$), POWLANG simulations with the HTL
transport coefficients and the Duke model predict a suppression of the D-meson
yield which is not observed in the data.

The ratio of the D-meson yield in a given centrality class with respect to
yield in the most peripheral centrality class (60–100%), defined as

$Q_{\mathrm{CP}}=\frac{({\rm d}^{2}N^{\rm prompt\,D}/{\rm d}p_{\rm T}{\rm
d}y)^{\mathrm{i}}_{\mathrm{p-Pb}}\big{/}\langle
T_{\mathrm{pPb}}\rangle_{\mathrm{i}}}{({\rm d}^{2}N^{\rm prompt\,D}/{\rm
d}p_{\rm T}{\rm d}y)^{\mathrm{60-100\%}}_{\mathrm{p-Pb}}\big{/}\langle
T_{\mathrm{pPb}}\rangle_{\mathrm{60-100\%}}},$ (10)

was also calculated. The $Q_{\mathrm{CP}}$ observable is independent of the pp
cross section and uses the yields in peripheral p–Pb collisions as a
reference. Since the contributions from the track reconstruction, selection
and PID efficiency cancel out in the ratio, the $Q_{\mathrm{CP}}$ has reduced
systematic uncertainties with respect to the $Q_{\mathrm{pPb}}$ ratio. The
systematic uncertainties on the yield extraction were estimated by applying
the fit variation procedure described in Section 4 directly on the signal
yield ratio obtained from the invariant-mass distributions of the two
centrality classes. To estimate the feed-down correction uncertainty, the
contributions from the hypothesis on the nuclear modification factor of D
mesons from B-hadron decays were considered as uncorrelated in each centrality
class and were added in quadrature.
In Fig. 12, the average D-meson $Q_{\mathrm{CP}}$ is shown for different
centrality classes: 0–10%, 10–20%, 20–40% and 40–60%. The results are
superimposed to those obtained for charged particles in the same centrality
classes [69]. A similar trend is observed for both measurements: when the
results from the most central classes are used as the numerator, the
$Q_{\mathrm{CP}}$ increases in the interval 1–5 GeV/$c$, reaching values of
about 1.3 and then shows a decreasing trend with increasing $p_{\rm T}$. A
$Q_{\mathrm{CP}}>1$ with a significance of 3$\sigma$ is observed in the range
$3<p_{\rm T}<7$ GeV/$c$ when the 20–40% centrality class is used as numerator.
In this case, the normalisation uncertainty is smaller than the one of more
central collisions due to the smaller separation between the centrality
classes used in the calculation of $Q_{\mathrm{CP}}$. When the 0–10% and
10–20% centrality classes are used as numerators, a $Q_{\mathrm{CP}}>1$ is
observed in the same $p_{\rm T}$ interval, with a significance of 1.5$\sigma$
and 2$\sigma$ due to the larger $\langle T_{\mathrm{pPb}}\rangle$
uncertainties. A milder $p_{\rm T}$ dependence is observed when the yields
from more peripheral collisions are used as the numerator. A possible radial
flow arising from a hydrodynamic evolution could modify the hadronisation
dynamics of heavy quarks and potentially be the cause of the enhancement at
intermediate $p_{\rm T}$.

Figure 12:  Average D-meson and charged-particles [69] $Q_{\mathrm{CP}}$ using
the yields measured in 0–10%, 10–20%, 20–40%, and 40–60% as numerators and the
yield in 60–100% as the denominator. The vertical bars and the empty boxes
represent the statistical and systematic uncertainties. The colour-filled
boxes at $Q_{\mathrm{CP}}$ $=1$ represent the normalisation uncertainties on
the $\langle T_{\mathrm{pPb}}\rangle$.

###  5.4 D-meson ratios

The ratios of the $p_{\rm T}$-differential cross sections of ${\rm D^{0}}$,
${\rm D^{+}}$, ${\rm D^{*+}}$, and ${\rm D^{+}_{s}}$ mesons in the minimum
bias sample are reported in Fig. 13. In the evaluation of the systematic
uncertainties of the ratios, the contributions of the yield extraction and
selection efficiency were considered as uncorrelated, while those of the feed-
down from beauty-hadron decays and the tracking efficiency were treated as
fully correlated among the different D-meson species. The measurements are
compared to the ratios of D-meson cross sections in pp collisions at
$\sqrt{s}=5\leavevmode\nobreak\ \mathrm{TeV}$ [70]. The relative abundances of
the four species are unmodified in p–Pb with respect to pp collisions within
statistical and systematic uncertainties.

Figure 13: Ratios of prompt D-meson production cross sections as a function of
$p_{\rm T}$ in p–Pb collisions at $\sqrt{s_{\scriptscriptstyle\rm
NN}}=5.02\leavevmode\nobreak\ \mathrm{TeV}$. The results are compared with
those of pp collisions at the same centre-of-mass energy [70]. The vertical
bars and the empty boxes represent the statistical and systematic
uncertainties.

The ratios of the ${\rm D^{+}_{s}}/{\rm D^{+}}$-meson yields were also studied
in different $p_{\rm T}$ intervals as a function the multiplicity of charged
particles produced in the collision. The charged-particle multiplicity,
$N_{\rm ch}$, was estimated at mid-rapidity by measuring the number of
tracklets, $N_{\rm tracklets}$ as in Refs. [89, 72]. The ${\rm D^{+}_{s}}/{\rm
D^{+}}$ ratios were extracted in three multiplicity classes defined as 1–40,
40–70, 70–200 tracklets. A tracklet is defined as a track segment that joins
the reconstructed primary vertex with a pair of space points on the two SPD
layers within the pseudorapidity range $|\eta|<1.0$. The measured $N_{\rm
tracklets}$ distribution is affected by the position of the interaction vertex
along the beam axis and by the evolution of the detector conditions. The
former is due to the collision system asymmetry and the limited SPD rapidity
coverage, while the latter is a consequence of a variation in active SPD
channels over time. To account for these effects, the $N_{\rm tracklets}$
distributions were corrected offline on an event-by-event basis. The
correlation between the measured $N_{\rm tracklets}$ and $N_{\rm ch}$,
equivalent to the number of generated “physical primaries”, was obtained from
a Monte Carlo simulation and parametrised with a linear function. Here,
physical primaries are defined as prompt particles produced in the collision,
along with their decay products, but excluding those from weak decays of
strange particles [78]. The systematic uncertainty on the conversion from
$N_{\rm tracklets}$ to $N_{\rm ch}$ was calculated using different Monte Carlo
generators and using different parameterisations of the correlation. The total
systematic uncertainty varies from 2% in the highest multiplicity class to 7%
in the lowest multiplicity class.

The ratios of the ${\rm D^{+}_{s}}/{\rm D^{+}}$-meson yields are shown in Fig.
14 as a function of the number of primary charged particles per unity of
pseudorapidity (d$N_{\rm ch}$/d$\eta$$|_{|\eta|<0.5}$) in five $p_{\rm T}$
intervals ranging from 2 to 16 $\mathrm{GeV}/c$. As a comparison, the measured
ratios in pp collisions [70] and in Pb–Pb collisions [90] at $\sqrt{s_{\rm
NN}}=$ 5.02 TeV are also shown in the figure. Within uncertainties, there is
no indication of a modification of the ${\rm D^{+}_{s}}/{\rm D^{+}}$-yield
ratios in pp and p–Pb collisions, up to the highest multiplicities that could
be studied with the current p–Pb sample, which are similar to those of
peripheral Pb–Pb collisions (60–80% centrality class). A hint of an
enhancement of the ${\rm D^{+}_{s}}/{\rm D^{+}}$-yield ratios in Pb–Pb
collisions in $4<p_{\rm T}<8$ GeV/$c$ is observed, as already shown in [90].
The larger data sample of Pb–Pb collisions collected by ALICE in 2018 will
provide a more precise measurement.

Figure 14: ${\rm D^{+}_{s}}/{\rm D^{+}}$-meson yield ratios, as a function of
primary charged particles per unity of pseudorapidity in pp [70], p–Pb, and
Pb–Pb [90] collisions at $\sqrt{s_{\scriptscriptstyle\rm
NN}}=5.02\leavevmode\nobreak\ \mathrm{TeV}$ in five different $p_{\rm T}$
intervals from 2 to 16 $\mathrm{GeV}/c$.

##  6 Summary

The production cross sections of the prompt charmed mesons (${\rm D^{0}}$,
${\rm D^{+}}$, ${\rm D^{*+}}$, and ${\rm D^{+}_{s}}$) in p–Pb collisions at a
centre-of-mass energy per nucleon pair of $\sqrt{s_{\scriptscriptstyle\rm
NN}}=5.02\leavevmode\nobreak\ \mathrm{TeV}$ were measured as a function of
$p_{\rm T}$ in the rapidity interval $-0.96<y_{\rm cms}<0.04$ with luminosity
of ${L}_{\mathrm{int}}=292\pm 11\leavevmode\nobreak\ \mu$b-1. The $p_{\rm
T}$-differential production cross sections were reported in the transverse
momentum range $0<p_{\rm T}<36\leavevmode\nobreak\ \mathrm{GeV}/c$ for ${\rm
D^{0}}$ mesons, $1<p_{\rm T}<36\leavevmode\nobreak\ \mathrm{GeV}/c$ for ${\rm
D^{+}}$ mesons, $1.5<p_{\rm T}<36\leavevmode\nobreak\ \mathrm{GeV}/c$ for
${\rm D^{*+}}$ mesons, and $2<p_{\rm T}<24\leavevmode\nobreak\ \mathrm{GeV}/c$
for ${\rm D^{+}_{s}}$ mesons. The larger sample used for this analysis, with
respect to that collected in 2013, allowed for a significant reduction, by a
factor 1.5–2, of the statistical and systematic uncertainties, along with an
extension of the $p_{\rm T}$ reach.

The $p_{\rm T}$-differential nuclear modification factor $R_{\rm pPb}$ of D
mesons, calculated by using the pp reference measured at the same centre-of-
mass energy, was found to be compatible with unity for $0<p_{\rm
T}<36\leavevmode\nobreak\ \mathrm{GeV}/c$. The $R_{\rm pPb}$ results are
described within uncertainties by theoretical calculations that include
initial-state effects. The $R_{\rm pPb}$ is also compared with parton-
transport model based calculations that assume the formation of a deconfined
QCD medium in p–Pb collisions. The trend predicted by these models is not
supported by the data. The strong enhancement at $p_{\rm T}\sim$3–4 GeV/$c$
observed in the calculations is not consistent with the measured $R_{\rm
pPb}$, and a suppression larger than 10% for $p_{\rm T}>8$ GeV/$c$ is excluded
by the data at 98% confidence level.

The centrality dependence of the D-meson yields was also studied in different
centrality classes, from most central to peripheral collisions, in the
interval $1<p_{\rm T}<36\leavevmode\nobreak\ \mathrm{GeV}/c$. The average
$Q_{\mathrm{pPb}}$ of prompt ${\rm D^{0}}$, ${\rm D^{+}}$, and ${\rm D^{*+}}$
mesons is consistent with unity within the uncertainties for $p_{\rm T}>2$
GeV/$c$. The measurements show a hint of suppression in $1<p_{\rm T}<2$
GeV/$c$ stronger in the most central collisions with respect to the peripheral
ones, as qualitatively expected from a stronger shadowing at low Bjorken-$x$
in central collisions [91, 92]. There is also a hint of enhancement in the
intermediate $p_{\rm T}$ region in the most central collision classes (0–40%
centrality). The same trend is observed for the charged-particles
$Q_{\mathrm{pPb}}$. The average D-meson $Q_{\mathrm{CP}}$ has been computed.
For the most central collision classes, the $Q_{\mathrm{CP}}$ increases in the
$p_{\rm T}$ interval 1–5 GeV/$c$, reaching values of about 1.3. Above a
$p_{\rm T}$ of 5 GeV/$c$ the distribution tends to decrease with increasing
$p_{\rm T}$. A milder $p_{\rm T}$ dependence is observed for more peripheral
collisions. A similar trend is observed for both charmed mesons and charged
particles in all the centrality classes considered. A possible radial flow
arising from hydrodynamic evolution could modify the hadronisation dynamics of
heavy quarks and give rise to the enhancement measured in the intermediate
$p_{\rm T}$ interval [52, 53].

The ratios of the $p_{\rm T}$-differential cross sections of ${\rm D^{0}}$,
${\rm D^{+}}$, ${\rm D^{*+}}$, and ${\rm D^{+}_{s}}$ mesons were evaluated and
compared to those measured in pp collisions at
$\sqrt{s}=5.02\leavevmode\nobreak\ \mathrm{TeV}$. The relative abundances of
the four species are unmodified in p–Pb collisions with respect to pp
collisions, within the uncertainties. The ratios of ${\rm D^{+}_{s}}/{\rm
D^{+}}$-meson yields, as a function of the number of primary charged particles
per unit of pseudorapidity, show no evidence of modifications in pp and p–Pb
collisions, within the uncertainties.

##  7 Appendix

Figure 15 presents the $Q_{\mathrm{pPb}}$ results for ${\rm D^{0}}$, ${\rm
D^{+}}$, and ${\rm D^{*+}}$ as a function of $p_{\rm T}$ for the 0–10% and
60–100% centrality classes. Figure 16 shows the $Q_{\mathrm{CP}}$ for the
three non-strange D mesons, obtained using 0–10% as central class and 60–100%
as peripheral class. The results are compatible within uncertainties between
the three D–meson species.

Figure 15:  ${\rm D^{0}}$, ${\rm D^{+}}$, and ${\rm D^{*+}}$ meson nuclear
modification factors as a function of $p_{\rm T}$ in the 0–10% (left) and
60–100% (right) centrality classes. The vertical bars and the empty boxes
represent the statistical and systematic uncertainties. The colour-filled
boxes at $Q_{\mathrm{pPb}}$ $=1$ represent the normalisation uncertainties.
Figure 16:  ${\rm D^{0}}$, ${\rm D^{+}}$, and ${\rm D^{*+}}$ meson
$Q_{\mathrm{CP}}$, obtained using 0–10% as the central class and 60–100% as
the peripheral class. The vertical bars and the empty boxes represent the
statistical and systematic uncertainties, respectively. The colour-filled
boxes at $Q_{\mathrm{CP}}$$=1$ represent the normalisation uncertainties.

————————————————

## 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), 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; Croatian Science Foundation and Ministry of Science and Education, 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 Carlsberg Foundation and Danish National Research Foundation (DNRF), Denmark; Helsinki Institute of Physics (HIP), Finland; Commissariat à l’Energie Atomique (CEA), Institut National de Physique Nucléaire et de Physique des Particules (IN2P3) and Centre National de la Recherche Scientifique (CNRS) and Région des Pays de la Loire, 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; 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 Ministry of Research and Innovation and Institute of Atomic Physics, Romania; Joint Institute for Nuclear Research (JINR), Ministry of Education and Science of the Russian Federation, National Research Centre Kurchatov Institute, Russian Science Foundation and Russian Foundation for Basic Research, Russia; 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; 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.

## References

  * [1] M. Cacciari, M. Greco, and P. Nason, “The $p_{\rm T}$ spectrum in heavy flavor hadroproduction,” JHEP 9805 (1998) 007, arXiv:hep-ph/9803400 [hep-ph].
  * [2] M. Cacciari, S. Frixione, N. Houdeau, M. L. Mangano, P. Nason, and G. Ridolfi, “Theoretical predictions for charm and bottom production at the LHC,” JHEP 1210 (2012) 137, arXiv:1205.6344 [hep-ph].
  * [3] B. A. Kniehl, G. Kramer, I. Schienbein, and H. Spiesberger, “Inclusive $\rm D^{*+}$\- production in p anti-p collisions with massive charm quarks,” Phys. Rev. D71 (2005) 014018, arXiv:hep-ph/0410289 [hep-ph].
  * [4] B. A. Kniehl, G. Kramer, I. Schienbein, and H. Spiesberger, “Collinear subtractions in hadroproduction of heavy quarks,” Eur. Phys. J. C41 (2005) 199–212, arXiv:hep-ph/0502194 [hep-ph].
  * [5] B. A. Kniehl, G. Kramer, I. Schienbein, and H. Spiesberger, “Inclusive Charmed-Meson Production at the CERN LHC,” Eur. Phys. J. C72 (2012) 2082, arXiv:1202.0439 [hep-ph].
  * [6] I. Helenius and H. Paukkunen, “Revisiting the D-meson hadroproduction in general-mass variable flavour number scheme,” JHEP 05 (2018) 196, arXiv:1804.03557 [hep-ph].
  * [7] A. Andronic et al., “Heavy-flavour and quarkonium production in the LHC era: from proton-proton to heavy-ion collisions,” Eur. Phys. J. C76 no. 3, (2016) 107, arXiv:1506.03981 [nucl-ex].
  * [8] F. Prino and R. Rapp, “Open Heavy Flavor in QCD Matter and in Nuclear Collisions,” J. Phys. G43 no. 9, (2016) 093002, arXiv:1603.00529 [nucl-ex].
  * [9] M. Arneodo, “Nuclear effects in structure functions,” Phys. Rept. 240 (1994) 301–393.
  * [10] S. Malace, D. Gaskell, D. W. Higinbotham, and I. Cloet, “The Challenge of the EMC Effect: existing data and future directions,” Int. J. Mod. Phys. E23 (2014) 1430013, arXiv:1405.1270 [nucl-ex].
  * [11] K. Eskola, H. Paukkunen, and C. Salgado, “EPS09: A New Generation of NLO and LO Nuclear Parton Distribution Functions,” JHEP 0904 (2009) 065, arXiv:0902.4154 [hep-ph].
  * [12] M. Hirai, S. Kumano, and T. H. Nagai, “Determination of nuclear parton distribution functions and their uncertainties in next-to-leading order,” Phys. Rev. C76 (2007) 065207, arXiv:0709.3038 [hep-ph].
  * [13] D. de Florian and R. Sassot, “Nuclear parton distributions at next-to-leading order,” Phys. Rev. D69 (2004) 074028, arXiv:hep-ph/0311227 [hep-ph].
  * [14] K. J. Eskola, P. Paakkinen, H. Paukkunen, and C. A. Salgado, “EPPS16: Nuclear parton distributions with LHC data,” Eur. Phys. J. C77 no. 3, (2017) 163, arXiv:1612.05741 [hep-ph].
  * [15] A. Kusina, J.-P. Lansberg, I. Schienbein, and H.-S. Shao, “Gluon Shadowing in Heavy-Flavor Production at the LHC,” Phys. Rev. Lett. 121 no. 5, (2018) 052004, arXiv:1712.07024 [hep-ph].
  * [16] K. J. Eskola, I. Helenius, P. Paakkinen, and H. Paukkunen, “A QCD analysis of LHCb D-meson data in p+Pb collisions,” arXiv:1906.02512 [hep-ph].
  * [17] F. Gelis, E. Iancu, J. Jalilian-Marian, and R. Venugopalan, “The Color Glass Condensate,” Ann. Rev. Nucl. Part. Sci. 60 (2010) 463–489, arXiv:1002.0333 [hep-ph].
  * [18] P. Tribedy and R. Venugopalan, “QCD saturation at the LHC: Comparisons of models to pp and A A data and predictions for p–Pb collisions,” Phys. Lett. B710 (2012) 125–133, arXiv:1112.2445 [hep-ph]. [Erratum: Phys. Lett.B718,1154(2013)].
  * [19] J. L. Albacete, A. Dumitru, H. Fujii, and Y. Nara, “CGC predictions for p–Pb collisions at the LHC,” Nucl. Phys. A897 (2013) 1–27, arXiv:1209.2001 [hep-ph].
  * [20] A. H. Rezaeian, “CGC predictions for p–A collisions at the LHC and signature of QCD saturation,” Phys. Lett. B718 (2013) 1058–1069, arXiv:1210.2385 [hep-ph].
  * [21] H. Fujii and K. Watanabe, “Heavy quark pair production in high energy pA collisions: Open heavy flavors,” Nucl. Phys. A920 (2013) 78–93, arXiv:1308.1258 [hep-ph].
  * [22] I. Vitev, “Non-Abelian energy loss in cold nuclear matter,” Phys. Rev. C75 (2007) 064906, arXiv:hep-ph/0703002 [hep-ph].
  * [23] M. Lev and B. Petersson, “Nuclear Effects at Large Transverse Momentum in a QCD Parton Model,” Z. Phys. C21 (1983) 155.
  * [24] X.-N. Wang, “Systematic study of high $p_{T}$ hadron spectra in $pp$, $p$A and AA collisions from SPS to RHIC energies,” Phys.Rev. C61 (2000) 064910, arXiv:nucl-th/9812021 [nucl-th].
  * [25] B. Z. Kopeliovich, J. Nemchik, A. Schafer, and A. V. Tarasov, “Cronin effect in hadron production off nuclei,” Phys. Rev. Lett. 88 (2002) 232303, arXiv:hep-ph/0201010 [hep-ph].
  * [26] CMS Collaboration, S. Chatrchyan et al., “Observation of long-range near-side angular correlations in proton-lead collisions at the LHC,” Phys. Lett. B718 (2013) 795–814, arXiv:1210.5482 [nucl-ex].
  * [27] ALICE Collaboration, B. Abelev et al., “Long-range angular correlations on the near and away side in $p$-Pb collisions at $\sqrt{s_{\rm NN}}=5.02$ TeV,” Phys. Lett. B719 (2013) 29–41, arXiv:1212.2001 [nucl-ex].
  * [28] ALICE Collaboration, B. Abelev et al., “Long-range angular correlations of $\rm\pi$, K and p in p–Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV,” Phys. Lett. B726 (2013) 164–177, arXiv:1307.3237 [nucl-ex].
  * [29] ATLAS Collaboration, G. Aad et al., “Observation of Associated Near-Side and Away-Side Long-Range Correlations in $\sqrt{s_{\rm NN}}$=5.02 TeV Proton-Lead Collisions with the ATLAS Detector,” Phys. Rev. Lett. 110 no. 18, (2013) 182302, arXiv:1212.5198 [hep-ex].
  * [30] ALICE Collaboration, J. Adam et al., “Forward-central two-particle correlations in p–Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV,” Phys. Lett. B753 (2016) 126–139, arXiv:1506.08032 [nucl-ex].
  * [31] LHCb Collaboration, R. Aaij et al., “Measurements of long-range near-side angular correlations in $\sqrt{s_{\text{NN}}}=5$ TeV proton-lead collisions in the forward region,” Phys. Lett. B762 (2016) 473–483, arXiv:1512.00439 [nucl-ex].
  * [32] CMS Collaboration, V. Khachatryan et al., “Evidence for Collective Multiparticle Correlations in p–Pb Collisions,” Phys. Rev. Lett. 115 no. 1, (2015) 012301, arXiv:1502.05382 [nucl-ex].
  * [33] ATLAS Collaboration, M. Aaboud et al., “Measurement of long-range multiparticle azimuthal correlations with the subevent cumulant method in $pp$ and p–Pb collisions with the ATLAS detector at the CERN Large Hadron Collider,” Phys. Rev. C97 no. 2, (2018) 024904, arXiv:1708.03559 [hep-ex].
  * [34] ALICE Collaboration, B. Abelev et al., “Multiplicity Dependence of Pion, Kaon, Proton and Lambda Production in p–Pb Collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV,” Phys. Lett. B728 (2014) 25–38, arXiv:1307.6796 [nucl-ex].
  * [35] CMS Collaboration, S. Chatrchyan et al., “Study of the production of charged pions, kaons, and protons in p–Pb collisions at $\sqrt{s_{NN}}=$ 5.02 TeV,” Eur. Phys. J. C74 no. 6, (2014) 2847, arXiv:1307.3442 [hep-ex].
  * [36] ALICE Collaboration, B. Abelev et al., “Suppression of $\psi$(2S) production in p–Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV,” JHEP 12 (2014) 073, arXiv:1405.3796 [nucl-ex].
  * [37] LHCb Collaboration, R. Aaij et al., “Study of $\psi(2S)$ production and cold nuclear matter effects in p–Pb collisions at $\sqrt{s_{NN}}=5\leavevmode\nobreak\ \mathrm{TeV}$,” JHEP 03 (2016) 133, arXiv:1601.07878 [nucl-ex].
  * [38] ALICE Collaboration, J. Adam et al., “Centrality dependence of $\mathbf{\psi}$(2S) suppression in p–Pb collisions at $\mathbf{\sqrt{{\textit{s}}_{\rm NN}}}$ = 5.02 TeV,” JHEP 06 (2016) 050, arXiv:1603.02816 [nucl-ex].
  * [39] Wuppertal-Budapest Collaboration, S. Borsanyi et al., “Is there still any $T_{c}$ mystery in lattice QCD? Results with physical masses in the continuum limit III,” JHEP 1009 (2010) 073, arXiv:1005.3508 [hep-lat].
  * [40] A. Bazavov, T. Bhattacharya, M. Cheng, C. DeTar, H. Ding, et al., “The chiral and deconfinement aspects of the QCD transition,” Phys.Rev. D85 (2012) 054503, arXiv:1111.1710 [hep-lat].
  * [41] A. Jaiswal and V. Roy, “Relativistic hydrodynamics in heavy-ion collisions: general aspects and recent developments,” Adv. High Energy Phys. 2016 (2016) 9623034, arXiv:1605.08694 [nucl-th].
  * [42] W. Busza, K. Rajagopal, and W. van der Schee, “Heavy Ion Collisions: The Big Picture, and the Big Questions,” Ann. Rev. Nucl. Part. Sci. 68 (2018) 339–376, arXiv:1802.04801 [hep-ph].
  * [43] J. L. Nagle and W. A. Zajc, “Small System Collectivity in Relativistic Hadronic and Nuclear Collisions,” Ann. Rev. Nucl. Part. Sci. 68 (2018) 211–235, arXiv:1801.03477 [nucl-ex].
  * [44] P. Bozek and W. Broniowski, “Correlations from hydrodynamic flow in p–Pb collisions,” Phys. Lett. B718 (2013) 1557–1561, arXiv:1211.0845 [nucl-th].
  * [45] P. Bozek and W. Broniowski, “Collective dynamics in high-energy proton-nucleus collisions,” Phys. Rev. C88 no. 1, (2013) 014903, arXiv:1304.3044 [nucl-th].
  * [46] R. D. Weller and P. Romatschke, “One fluid to rule them all: viscous hydrodynamic description of event-by-event central pp, p–Pb and Pb–Pb collisions at $\sqrt{s}=5.02$ TeV,” Phys. Lett. B774 (2017) 351–356, arXiv:1701.07145 [nucl-th].
  * [47] K. Dusling and R. Venugopalan, “Evidence for BFKL and saturation dynamics from dihadron spectra at the LHC,” Phys. Rev. D87 no. 5, (2013) 051502, arXiv:1210.3890 [hep-ph].
  * [48] K. Dusling, W. Li, and B. Schenke, “Novel collective phenomena in high-energy proton-proton and proton-nucleus collisions,” Int. J. Mod. Phys. E25 no. 01, (2016) 1630002, arXiv:1509.07939 [nucl-ex].
  * [49] L. He, T. Edmonds, Z.-W. Lin, F. Liu, D. Molnar, and F. Wang, “Anisotropic parton escape is the dominant source of azimuthal anisotropy in transport models,” Phys. Lett. B753 (2016) 506–510, arXiv:1502.05572 [nucl-th].
  * [50] C. Bierlich, G. Gustafson, L. Lönnblad, and A. Tarasov, “Effects of Overlapping Strings in pp Collisions,” JHEP 03 (2015) 148, arXiv:1412.6259 [hep-ph].
  * [51] C. Bierlich, G. Gustafson, and L. Lönnblad, “Collectivity without plasma in hadronic collisions,” Phys. Lett. B779 (2018) 58–63, arXiv:1710.09725 [hep-ph].
  * [52] Y. Xu, S. Cao, G.-Y. Qin, W. Ke, M. Nahrgang, J. Auvinen, and S. A. Bass, “Heavy-flavor dynamics in relativistic p–Pb collisions at $\sqrt{S_{NN}}=5.02$ TeV,” Nucl. Part. Phys. Proc. 276-278 (2016) 225–228, arXiv:1510.07520 [nucl-th].
  * [53] A. Beraudo, A. De Pace, M. Monteno, M. Nardi, and F. Prino, “Heavy-flavour production in high-energy d-Au and p–Pb collisions,” JHEP 03 (2016) 123, arXiv:1512.05186 [hep-ph].
  * [54] ALICE Collaboration, S. Acharya et al., “Search for collectivity with azimuthal J/$\psi$-hadron correlations in high multiplicity p–Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 and 8.16 TeV,” Phys. Lett. B780 (2018) 7–20, arXiv:1709.06807 [nucl-ex].
  * [55] CMS Collaboration, A. M. Sirunyan et al., “Elliptic flow of charm and strange hadrons in high-multiplicity p–Pb collisions at $\sqrt{s_{{}_{\mathrm{NN}}}}=$ 8.16 TeV,” Phys. Rev. Lett. 121 no. 8, (2018) 082301, arXiv:1804.09767 [hep-ex].
  * [56] ALICE Collaboration, S. Acharya et al., “Azimuthal anisotropy of heavy-flavour decay electrons in p–Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV,” Phys. Rev. Lett. 122 no. 7, (2019) 072301, arXiv:1805.04367 [nucl-ex].
  * [57] V. Greco, C. M. Ko, and P. Levai, “Parton coalescence at RHIC,” Phys. Rev. C68 (2003) 034904, arXiv:nucl-th/0305024 [nucl-th].
  * [58] V. Greco, C. M. Ko, and R. Rapp, “Quark coalescence for charmed mesons in ultrarelativistic heavy ion collisions,” Phys. Lett. B595 (2004) 202–208, arXiv:nucl-th/0312100 [nucl-th].
  * [59] A. Andronic, P. Braun-Munzinger, K. Redlich, and J. Stachel, “Charmonium and open charm production in nuclear collisions at SPS/FAIR energies and the possible influence of a hot hadronic medium,” Phys. Lett. B659 (2008) 149–155, arXiv:0708.1488 [nucl-th].
  * [60] M. He, R. J. Fries, and R. Rapp, “$\mathbf{D_{s}}$-Meson as Quantitative Probe of Diffusion and Hadronization in Nuclear Collisions,” Phys. Rev. Lett. 110 no. 11, (2013) 112301, arXiv:1204.4442 [nucl-th].
  * [61] ALICE Collaboration, J. Adam et al., “Multi-strange baryon production in p–Pb collisions at $\sqrt{s_{\mathbf{NN}}}=5.02$ TeV,” Phys. Lett. B758 (2016) 389–401, arXiv:1512.07227 [nucl-ex].
  * [62] ALICE Collaboration, J. Adam et al., “Enhanced production of multi-strange hadrons in high-multiplicity proton-proton collisions,” Nature Phys. 13 (2017) 535–539, arXiv:1606.07424 [nucl-ex].
  * [63] ALICE Collaboration, B. Abelev et al., “Measurement of prompt D-meson production in p–Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV,” Phys.Rev.Lett. 113 no. 23, (2014) 232301, arXiv:1405.3452 [nucl-ex].
  * [64] ALICE Collaboration, J. Adam et al., “Measurement of D-meson production versus multiplicity in p–Pb collisions at $\sqrt{s_{\mathrm{NN}}}=5.02$ TeV,” JHEP 08 (2016) 078, arXiv:1602.07240 [nucl-ex].
  * [65] ALICE Collaboration, J. Adam et al., “D-meson production in p–Pb collisions at $\sqrt{s_{\rm NN}}=$5.02 TeV and in pp collisions at $\sqrt{s}=$7 TeV,” Phys. Rev. C94 no. 5, (2016) 054908, arXiv:1605.07569 [nucl-ex].
  * [66] ALICE Collaboration, K. Aamodt et al., “The ALICE experiment at the CERN LHC,” JINST 3 (2008) S08002.
  * [67] ALICE Collaboration, B. Abelev et al., “Performance of the ALICE Experiment at the CERN LHC,” Int.J.Mod.Phys. A29 (2014) 1430044, arXiv:1402.4476 [nucl-ex].
  * [68] ALICE Collaboration, B. Abelev et al., “Measurement of visible cross sections in proton-lead collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV in van der Meer scans with the ALICE detector,” JINST 9 no. 11, (2014) P11003, arXiv:1405.1849 [nucl-ex].
  * [69] ALICE Collaboration, J. Adam et al., “Centrality dependence of particle production in p–Pb collisions at $\sqrt{s_{\rm NN}}$= 5.02 TeV,” Phys.Rev. C91 (2015) 064905, arXiv:1412.6828 [nucl-ex].
  * [70] ALICE Collaboration, S. Acharya et al., “Measurement of ${{\mathrm{D}}^{0}}$ , ${{\mathrm{D}}^{+}}$ , ${{\mathrm{D}}^{*+}}$ and ${{\mathrm{D}}^{+}_{\mathrm{s}}}$ production in pp collisions at ${\sqrt{{\textit{s}}}\leavevmode\nobreak\ =\leavevmode\nobreak\ 5.02\leavevmode\nobreak\ {\text{TeV}}}$ with ALICE,” Eur. Phys. J. C79 no. 5, (2019) 388, arXiv:1901.07979 [nucl-ex].
  * [71] Particle Data Group Collaboration, M. Tanabashi et al., “Review of Particle Physics,” Phys. Rev. D 98 (2018) 030001. https://link.aps.org/doi/10.1103/PhysRevD.98.030001.
  * [72] ALICE Collaboration, J. Adam et al., “Measurement of charm and beauty production at central rapidity versus charged-particle multiplicity in proton-proton collisions at $\mathbf{\sqrt{{\textit{s}}}}=7$ TeV,” JHEP 09 (2015) 148, arXiv:1505.00664 [nucl-ex].
  * [73] T. Sjostrand, S. Mrenna, and P. Z. Skands, “PYTHIA 6.4 Physics and Manual,” JHEP 0605 (2006) 026, arXiv:hep-ph/0603175 [hep-ph].
  * [74] X.-N. Wang and M. Gyulassy, “HIJING: A Monte Carlo model for multiple jet production in pp, pA and AA collisions,” Phys.Rev. D44 (1991) 3501–3516.
  * [75] ALICE Collaboration, S. Acharya et al., “Measurement of D-meson production at mid-rapidity in pp collisions at $\mathbf{\sqrt{s}=7}$ TeV,” arXiv:1702.00766 [hep-ex].
  * [76] A. Ryd, D. Lange, N. Kuznetsova, S. Versille, M. Rotondo, D. P. Kirkby, F. K. Wuerthwein, and A. Ishikawa, “EvtGen: A Monte Carlo Generator for B-Physics,”.
  * [77] CMS Collaboration, V. Khachatryan et al., “Study of B meson production in p–Pb collisions at $\sqrt{s_{\rm NN}}=5.02$ TeV using exclusive hadronic decays,” Phys. Rev. Lett. 116 no. 3, (2016) 032301, arXiv:1508.06678 [nucl-ex].
  * [78] ALICE Collaboration, “The ALICE definition of primary particles,” Jun, 2017.  https://cds.cern.ch/record/2270008. ALICE-PUBLIC-2017-005.
  * [79] L. Gladilin, “Fragmentation fractions of $c$ and $b$ quarks into charmed hadrons at LEP,” Eur. Phys. J. C75 no. 1, (2015) 19, arXiv:1404.3888 [hep-ex].
  * [80] ALICE Collaboration, “$\Lambda_{c}^{+}$ production in pp collisions at $\sqrt{s}=7$ and in p–Pb collisions at $\sqrt{s_{\mathrm{NN}}}=5.02$ TeV,” JHEP 2018 no. 4, (Apr, 2018) 108. https://doi.org/10.1007/JHEP04(2018)108.
  * [81] LHCb Collaboration, R. Aaij et al., “Prompt $\Lambda^{+}_{c}$ production in $p\mathrm{Pb}$ collisions at $\sqrt{s_{NN}}=5.02$ TeV,” JHEP 02 (2019) 102, arXiv:1809.01404 [hep-ex].
  * [82] H. Fujii and K. Watanabe, “Nuclear modification of forward $D$ production in p–Pb collisions at the LHC,” arXiv:1706.06728 [hep-ph].
  * [83] J. Pumplin, D. R. Stump, J. Huston, H. L. Lai, P. M. Nadolsky, and W. K. Tung, “New generation of parton distributions with uncertainties from global QCD analysis,” JHEP 07 (2002) 012, arXiv:hep-ph/0201195 [hep-ph].
  * [84] LHCb Collaboration, R. Aaij et al., “Study of prompt D0 meson production in $p$Pb collisions at $\sqrt{s_{\mathrm{NN}}}=5$ TeV,” JHEP 10 (2017) 090, arXiv:1707.02750 [hep-ex].
  * [85] R. Sharma, I. Vitev, and B.-W. Zhang, “Light-cone wave function approach to open heavy flavor dynamics in QCD matter,” Phys.Rev. C80 (2009) 054902, arXiv:0904.0032 [hep-ph].
  * [86] Z.-B. Kang, I. Vitev, E. Wang, H. Xing, and C. Zhang, “Multiple scattering effects on heavy meson production in p–A collisions at backward rapidity,” Phys. Lett. B740 (2015) 23–29, arXiv:1409.2494 [hep-ph].
  * [87] C. Loizides, J. Kamin, and D. d’Enterria, “Improved Monte Carlo Glauber predictions at present and future nuclear colliders. Precision Monte Carlo Glauber predictions at present and future nuclear colliders,” Phys. Rev. C 97 no. arXiv:1710.07098, (Oct, 2017) 054910. 23 p. http://cds.cern.ch/record/2295119.
  * [88] ALICE Collaboration, S. Acharya et al., “Centrality determination in heavy ion collisions,”. http://cds.cern.ch/record/2636623.
  * [89] ALICE Collaboration, B. Abelev et al., “${\rm J}/\psi$ production as a function of charged particle multiplicity in pp collisions at $\sqrt{s}=7$ TeV,” Phys.Lett. B712 (2012) 165, arXiv:1202.2816 [hep-ex].
  * [90] ALICE Collaboration, S. Acharya et al., “Measurement of D0, D+, D∗+ and D${}_{s}^{+}$ production in Pb–Pb collisions at $\sqrt{s_{\mathrm{NN}}}=5.02$ TeV,” JHEP 10 (2018) 174, arXiv:1804.09083 [nucl-ex].
  * [91] K. J. Eskola, “Shadowing effects on quark and gluon production in ultrarelativistic heavy ion collisions,” Z. Phys. C51 (1991) 633–642.
  * [92] I. Helenius, K. J. Eskola, H. Honkanen, and C. A. Salgado, “Impact-Parameter Dependent Nuclear Parton Distribution Functions: EPS09s and EKS98s and Their Applications in Nuclear Hard Processes,” JHEP 07 (2012) 073, arXiv:1205.5359 [hep-ph].

##  Appendix A The ALICE Collaboration

S. Acharyaorg141&D. Adamováorg93&S.P. Adhyaorg141&A. Adlerorg73&J.
Adolfssonorg79&M.M. Aggarwalorg98&G. Aglieri Rinellaorg34&M. Agnelloorg31&N.
Agrawalorg10,org48,org53&Z. Ahammedorg141&S. Ahmadorg17&S.U. Ahnorg75&A.
Akindinovorg90&M. Al-Turanyorg105&S.N. Alamorg141&D.S.D. Albuquerqueorg122&D.
Aleksandrovorg86&B. Alessandroorg58&H.M. Alfandaorg6&R. Alfaro Molinaorg71&B.
Aliorg17&Y. Aliorg15&A. Aliciorg10,org27,org53&A. Alkinorg2&J. Almeorg22&T.
Altorg68&L. Altenkamperorg22&I. Altsybeevorg112&M.N. Anaamorg6&C.
Andreiorg47&D. Andreouorg34&H.A. Andrewsorg109&A. Andronicorg144&M.
Angelettiorg34&V. Anguelovorg102&C. Ansonorg16&T. Antičićorg106&F.
Antinoriorg56&P. Antonioliorg53&R. Anwarorg125&N. Apadulaorg78&L.
Aphecetcheorg114&H. Appelshäuserorg68&S. Arcelliorg27&R. Arnaldiorg58&M.
Arratiaorg78&I.C. Arseneorg21&M. Arslandokorg102&A. Augustinusorg34&R.
Averbeckorg105&S. Azizorg61&M.D. Azmiorg17&A. Badalàorg55&Y.W. Baekorg40&S.
Bagnascoorg58&X. Baiorg105&R. Bailhacheorg68&R. Balaorg99&A.
Baldisseriorg137&M. Ballorg42&S. Balouzaorg103&R.C. Baralorg84&R.
Barberaorg28&L. Barioglioorg26&G.G. Barnaföldiorg145&L.S. Barnbyorg92&V.
Barretorg134&P. Bartaliniorg6&K. Barthorg34&E. Bartschorg68&F.
Baruffaldiorg29&N. Bastidorg134&S. Basuorg143&G. Batigneorg114&B.
Batyunyaorg74&P.C. Batzingorg21&D. Bauriorg48&J.L. Bazo Albaorg110&I.G.
Beardenorg87&C. Beddaorg63&N.K. Beheraorg60&I. Belikovorg136&F.
Belliniorg34&R. Bellwiedorg125&V. Belyaevorg91&G. Bencediorg145&S.
Beoleorg26&A. Bercuciorg47&Y. Berdnikovorg96&D. Berenyiorg145&R.A.
Bertensorg130&D. Berzanoorg58&M.G. Besoiuorg67&L. Betevorg34&A.
Bhasinorg99&I.R. Bhatorg99&M.A. Bhatorg3&H. Bhattorg48&B.
Bhattacharjeeorg41&A. Bianchiorg26&L. Bianchiorg26,org125&N. Bianchiorg51&J.
Bielčíkorg37&J. Bielčíkováorg93&A. Bilandzicorg103,org117&G. Biroorg145&R.
Biswasorg3&S. Biswasorg3&J.T. Blairorg119&D. Blauorg86&C. Blumeorg68&G.
Bocaorg139&F. Bockorg34,org94&A. Bogdanovorg91&L. Boldizsárorg145&A.
Bolozdynyaorg91&M. Bombaraorg38&G. Bonomiorg140&H. Borelorg137&A.
Borissovorg91,org144&M. Borriorg127&H. Bossiorg146&E. Bottaorg26&L.
Bratrudorg68&P. Braun-Munzingerorg105&M. Bregantorg121&T.A. Brokerorg68&M.
Brozorg37&E.J. Bruckenorg43&E. Brunaorg58&G.E. Brunoorg33,org104&M.D.
Bucklandorg127&D. Budnikovorg107&H. Bueschingorg68&S. Bufalinoorg31&O.
Bugnonorg114&P. Buhlerorg113&P. Buncicorg34&Z. Butheleziorg72&J.B.
Buttorg15&J.T. Buxtonorg95&S.A. Bysiakorg118&D. Caffarriorg88&A.
Calivaorg105&E. Calvo Villarorg110&R.S. Camachoorg44&P. Cameriniorg25&A.A.
Caponorg113&F. Carnesecchiorg10&J. Castillo Castellanosorg137&A.J.
Castroorg130&E.A.R. Casulaorg54&F. Catalanoorg31&C. Ceballos Sanchezorg52&P.
Chakrabortyorg48&S. Chandraorg141&B. Changorg126&W. Changorg6&S.
Chapelandorg34&M. Chartierorg127&S. Chattopadhyayorg141&S.
Chattopadhyayorg108&A. Chauvinorg24&C. Cheshkovorg135&B. Cheynisorg135&V.
Chibante Barrosoorg34&D.D. Chinellatoorg122&S. Choorg60&P. Chochulaorg34&T.
Chowdhuryorg134&P. Christakoglouorg88&C.H. Christensenorg87&P.
Christiansenorg79&T. Chujoorg133&C. Cicaloorg54&L. Cifarelliorg10,org27&F.
Cindoloorg53&J. Cleymansorg124&F. Colamariaorg52&D. Colellaorg52&A.
Colluorg78&M. Colocciorg27&M. Concasorg58orgI&G. Conesa Balbastreorg77&Z.
Conesa del Valleorg61&G. Continorg59,org127&J.G. Contrerasorg37&T.M.
Cormierorg94&Y. Corrales Moralesorg26,org58&P. Corteseorg32&M.R.
Cosentinoorg123&F. Costaorg34&S. Costanzaorg139&J. Crkovskáorg61&P.
Crochetorg134&E. Cuautleorg69&L. Cunqueiroorg94&D. Dabrowskiorg142&T.
Dahmsorg103,org117&A. Daineseorg56&F.P.A. Damasorg114,org137&S. Daniorg65&M.C.
Danischorg102&A. Danuorg67&D. Dasorg108&I. Dasorg108&P. Dasorg3&S. Dasorg3&A.
Dashorg84&S. Dashorg48&A. Dashiorg103&S. Deorg49,org84&A. De Caroorg30&G. de
Cataldoorg52&C. de Contiorg121&J. de Cuvelandorg39&A. De Falcoorg24&D. De
Gruttolaorg10&N. De Marcoorg58&S. De Pasqualeorg30&R.D. De Souzaorg122&S.
Deborg49&H.F. Degenhardtorg121&K.R. Dejaorg142&A. Delofforg83&S.
Delsantoorg26,org131&P. Dhankherorg48&D. Di Bariorg33&A. Di Mauroorg34&R.A.
Diazorg8&T. Dietelorg124&P. Dillensegerorg68&Y. Dingorg6&R. Diviàorg34&Ø.
Djuvslandorg22&U. Dmitrievaorg62&A. Dobrinorg34,org67&B. Dönigusorg68&O.
Dordicorg21&A.K. Dubeyorg141&A. Dublaorg105&S. Dudiorg98&M. Dukhishyamorg84&P.
Dupieuxorg134&R.J. Ehlersorg146&D. Eliaorg52&H. Engelorg73&E. Eppleorg146&B.
Erazmusorg114&F. Erhardtorg97&A. Erokhinorg112&M.R. Ersdalorg22&B.
Espagnonorg61&G. Eulisseorg34&J. Eumorg18&D. Evansorg109&S. Evdokimovorg89&L.
Fabbiettiorg103,org117&M. Fagginorg29&J. Faivreorg77&A. Fantoniorg51&M.
Faselorg94&P. Fecchioorg31&A. Felicielloorg58&G. Feofilovorg112&A. Fernández
Téllezorg44&A. Ferreroorg137&A. Ferrettiorg26&A. Festantiorg34&V.J.G.
Feuillardorg102&J. Figielorg118&S. Filchaginorg107&D. Finogeevorg62&F.M.
Fiondaorg22&G. Fiorenzaorg52&F. Flororg125&S. Foertschorg72&P. Fokaorg105&S.
Fokinorg86&E. Fragiacomoorg59&U. Frankenfeldorg105&G.G. Fronzeorg26&U.
Fuchsorg34&C. Furgetorg77&A. Fursorg62&M. Fusco Girardorg30&J.J.
Gaardhøjeorg87&M. Gagliardiorg26&A.M. Gagoorg110&A. Galorg136&C.D.
Galvanorg120&P. Ganotiorg82&C. Garabatosorg105&E. Garcia-Solisorg11&K.
Gargorg28&C. Gargiuloorg34&A. Garibliorg85&K. Garnerorg144&P.
Gasikorg103,org117&E.F. Gaugerorg119&M.B. Gay Ducatiorg70&M. Germainorg114&J.
Ghoshorg108&P. Ghoshorg141&S.K. Ghoshorg3&P. Gianottiorg51&P.
Giubellinoorg58,org105&P. Giubilatoorg29&P. Glässelorg102&D.M. Goméz
Coralorg71&A. Gomez Ramirezorg73&V. Gonzalezorg105&P. González-Zamoraorg44&S.
Gorbunovorg39&L. Görlichorg118&S. Gotovacorg35&V. Grabskiorg71&L.K.
Graczykowskiorg142&K.L. Grahamorg109&L. Greinerorg78&A. Grelliorg63&C.
Grigorasorg34&V. Grigorievorg91&A. Grigoryanorg1&S. Grigoryanorg74&O.S.
Groettvikorg22&J.M. Gronefeldorg105&F. Grosaorg31&J.F. Grosse-
Oetringhausorg34&R. Grossoorg105&R. Guernaneorg77&B. Guerzoniorg27&M.
Guittiereorg114&K. Gulbrandsenorg87&T. Gunjiorg132&A. Guptaorg99&R.
Guptaorg99&I.B. Guzmanorg44&R. Haakeorg34,org146&M.K. Habiborg105&C.
Hadjidakisorg61&H. Hamagakiorg80&G. Hamarorg145&M. Hamidorg6&R.
Hanniganorg119&M.R. Haqueorg63&A. Harlenderovaorg105&J.W. Harrisorg146&A.
Hartonorg11&J.A. Hasenbichlerorg34&H. Hassanorg77&D.
Hatzifotiadouorg10,org53&P. Hauerorg42&S. Hayashiorg132&A.D.L.B.
Hechavarriaorg144&S.T. Heckelorg68&E. Hellbärorg68&H. Helstruporg36&A.
Herghelegiuorg47&E.G. Hernandezorg44&G. Herrera Corralorg9&F.
Herrmannorg144&K.F. Hetlandorg36&T.E. Hildenorg43&H. Hillemannsorg34&C.
Hillsorg127&B. Hippolyteorg136&B. Hohlwegerorg103&D. Horakorg37&S.
Hornungorg105&R. Hosokawaorg133&P. Hristovorg34&C. Huangorg61&C.
Hughesorg130&P. Huhnorg68&T.J. Humanicorg95&H. Hushnudorg108&L.A.
Husovaorg144&N. Hussainorg41&S.A. Hussainorg15&T. Hussainorg17&D.
Hutterorg39&D.S. Hwangorg19&J.P. Iddonorg34,org127&R. Ilkaevorg107&M.
Inabaorg133&M. Ippolitovorg86&M.S. Islamorg108&M. Ivanovorg105&V.
Ivanovorg96&V. Izucheevorg89&B. Jacakorg78&N. Jacazioorg27&P.M.
Jacobsorg78&M.B. Jadhavorg48&S. Jadlovskaorg116&J. Jadlovskyorg116&S.
Jaelaniorg63&C. Jahnkeorg121&M.J. Jakubowskaorg142&M.A. Janikorg142&M.
Jercicorg97&O. Jevonsorg109&R.T. Jimenez Bustamanteorg105&M. Jinorg125&F.
Jonasorg94,org144&P.G. Jonesorg109&A. Juskoorg109&P. Kalinakorg64&A.
Kalweitorg34&J.H. Kangorg147&V. Kaplinorg91&S. Karorg6&A. Karasu Uysalorg76&O.
Karavichevorg62&T. Karavichevaorg62&P. Karczmarczykorg34&E. Karpechevorg62&U.
Kebschullorg73&R. Keidelorg46&M. Keilorg34&B. Ketzerorg42&Z.
Khabanovaorg88&A.M. Khanorg6&S. Khanorg17&S.A. Khanorg141&A.
Khanzadeevorg96&Y. Kharlovorg89&A. Khatunorg17&A. Khuntiaorg49,org118&B.
Kilengorg36&B. Kimorg60&B. Kimorg133&D. Kimorg147&D.J. Kimorg126&E.J.
Kimorg13&H. Kimorg147&J. Kimorg147&J.S. Kimorg40&J. Kimorg102&J. Kimorg147&J.
Kimorg13&M. Kimorg102&S. Kimorg19&T. Kimorg147&T. Kimorg147&S. Kirschorg39&I.
Kiselorg39&S. Kiselevorg90&A. Kisielorg142&J.L. Klayorg5&C. Kleinorg68&J.
Kleinorg58&S. Kleinorg78&C. Klein-Bösingorg144&S. Klewinorg102&A.
Klugeorg34&M.L. Knichelorg34&A.G. Knospeorg125&C. Kobdajorg115&M.K.
Köhlerorg102&T. Kolleggerorg105&A. Kondratyevorg74&N. Kondratyevaorg91&E.
Kondratyukorg89&P.J. Konopkaorg34&L. Koskaorg116&O. Kovalenkoorg83&V.
Kovalenkoorg112&M. Kowalskiorg118&I. Králikorg64&A. Kravčákováorg38&L.
Kreisorg105&M. Krivdaorg64,org109&F. Krizekorg93&K. Krizkova Gajdosovaorg37&M.
Krügerorg68&E. Kryshenorg96&M. Krzewickiorg39&A.M. Kuberaorg95&V.
Kučeraorg60&C. Kuhnorg136&P.G. Kuijerorg88&L. Kumarorg98&S. Kumarorg48&S.
Kunduorg84&P. Kurashviliorg83&A. Kurepinorg62&A.B. Kurepinorg62&S.
Kushpilorg93&J. Kvapilorg109&M.J. Kweonorg60&J.Y. Kwonorg60&Y. Kwonorg147&S.L.
La Pointeorg39&P. La Roccaorg28&Y.S. Laiorg78&R. Langoyorg129&K.
Lapidusorg34,org146&A. Lardeuxorg21&P. Larionovorg51&E. Laudiorg34&R.
Lavickaorg37&T. Lazarevaorg112&R. Leaorg25&L. Leardiniorg102&S. Leeorg147&F.
Lehasorg88&S. Lehnerorg113&J. Lehrbachorg39&R.C. Lemmonorg92&I. León
Monzónorg120&E.D. Lesserorg20&M. Lettrichorg34&P. Lévaiorg145&X. Liorg12&X.L.
Liorg6&J. Lienorg129&R. Lietavaorg109&B. Limorg18&S. Lindalorg21&V.
Lindenstruthorg39&S.W. Lindsayorg127&C. Lippmannorg105&M.A. Lisaorg95&V.
Litichevskyiorg43&A. Liuorg78&S. Liuorg95&W.J. Llopeorg143&I.M. Lofnesorg22&V.
Loginovorg91&C. Loizidesorg94&P. Loncarorg35&X. Lopezorg134&E. López
Torresorg8&P. Luettigorg68&J.R. Luhderorg144&M. Lunardonorg29&G.
Luparelloorg59&M. Lupiorg73&A. Maevskayaorg62&M. Magerorg34&S.M.
Mahmoodorg21&T. Mahmoudorg42&A. Maireorg136&R.D. Majkaorg146&M.
Malaevorg96&Q.W. Malikorg21&L. Malininaorg74orgII&D. Mal’Kevichorg90&P.
Malzacherorg105&A. Mamonovorg107&G. Mandaglioorg55&V. Mankoorg86&F.
Mansoorg134&V. Manzariorg52&Y. Maoorg6&M. Marchisoneorg135&J. Marešorg66&G.V.
Margagliottiorg25&A. Margottiorg53&J. Marguttiorg63&A. Marínorg105&C.
Markertorg119&M. Marquardorg68&N.A. Martinorg102&P. Martinengoorg34&J.L.
Martinezorg125&M.I. Martínezorg44&G. Martínez Garcíaorg114&M. Martinez
Pedreiraorg34&S. Masciocchiorg105&M. Maseraorg26&A. Masoniorg54&L.
Massacrierorg61&E. Massonorg114&A. Mastroserioorg138&A.M.
Mathisorg103,org117&O. Matonohaorg79&P.F.T. Matuokaorg121&A. Matyjaorg118&C.
Mayerorg118&M. Mazzilliorg33&M.A. Mazzoniorg57&A.F. Mechlerorg68&F.
Meddiorg23&Y. Melikyanorg91&A. Menchaca-Rochaorg71&E. Meninnoorg30&M.
Meresorg14&S. Mhlangaorg124&Y. Miakeorg133&L. Michelettiorg26&M.M.
Mieskolainenorg43&D.L. Mihaylovorg103&K. Mikhaylovorg74,org90&A.
Mischkeorg63org*&A.N. Mishraorg69&D. Miśkowiecorg105&C.M. Mituorg67&A.
Modakorg3&N. Mohammadiorg34&A.P. Mohantyorg63&B. Mohantyorg84&M. Mohisin
Khanorg17orgIII&M. Mondalorg141&M.M. Mondalorg65&C. Mordasiniorg103&D.A.
Moreira De Godoyorg144&L.A.P. Morenoorg44&S. Morettoorg29&A. Morrealeorg114&A.
Morschorg34&T. Mrnjavacorg34&V. Mucciforaorg51&E. Mudnicorg35&D.
Mühlheimorg144&S. Muhuriorg141&J.D. Mulliganorg78,org146&M.G. Munhozorg121&K.
Münningorg42&R.H. Munzerorg68&H. Murakamiorg132&S. Murrayorg72&L. Musaorg34&J.
Musinskyorg64&C.J. Myersorg125&J.W. Myrchaorg142&B. Naikorg48&R.
Nairorg83&B.K. Nandiorg48&R. Naniaorg10,org53&E. Nappiorg52&M.U.
Naruorg15&A.F. Nassirpourorg79&H. Natal da Luzorg121&C. Nattrassorg130&R.
Nayakorg48&T.K. Nayakorg84,org141&S. Nazarenkoorg107&R.A. Negrao De
Oliveiraorg68&L. Nellenorg69&S.V. Nesboorg36&G. Neskovicorg39&B.S.
Nielsenorg87&S. Nikolaevorg86&S. Nikulinorg86&V. Nikulinorg96&F.
Noferiniorg10,org53&P. Nomokonovorg74&G. Noorenorg63&J. Normanorg77&P.
Nowakowskiorg142&A. Nyaninorg86&J. Nystrandorg22&M. Oginoorg80&A.
Ohlsonorg102&J. Oleniaczorg142&A.C. Oliveira Da Silvaorg121&M.H.
Oliverorg146&C. Oppedisanoorg58&R. Oravaorg43&A. Ortiz Velasquezorg69&A.
Oskarssonorg79&J. Otwinowskiorg118&K. Oyamaorg80&Y. Pachmayerorg102&V.
Pacikorg87&D. Paganoorg140&G. Paićorg69&P. Palniorg6&J. Panorg143&A.K.
Pandeyorg48&S. Panebiancoorg137&V. Papikyanorg1&P. Pareekorg49&J.
Parkorg60&J.E. Parkkilaorg126&S. Parmarorg98&A. Passfeldorg144&S.P.
Pathakorg125&R.N. Patraorg141&B. Paulorg24,org58&H. Peiorg6&T.
Peitzmannorg63&X. Pengorg6&L.G. Pereiraorg70&H. Pereira Da Costaorg137&D.
Peresunkoorg86&G.M. Perezorg8&E. Perez Lezamaorg68&V. Peskovorg68&Y.
Pestovorg4&V. Petráčekorg37&M. Petroviciorg47&R.P. Pezziorg70&S. Pianoorg59&M.
Piknaorg14&P. Pillotorg114&L.O.D.L. Pimentelorg87&O. Pinazzaorg34,org53&L.
Pinskyorg125&C. Pintoorg28&S. Pisanoorg51&D.B. Piyarathnaorg125&M.
Płoskońorg78&M. Planinicorg97&F. Pliquettorg68&J. Plutaorg142&S.
Pochybovaorg145&M.G. Poghosyanorg94&B. Polichtchoukorg89&N. Poljakorg97&W.
Poonsawatorg115&A. Poporg47&H. Poppenborgorg144&S. Porteboeuf-
Houssaisorg134&V. Pozdniakovorg74&S.K. Prasadorg3&R. Preghenellaorg53&F.
Prinoorg58&C.A. Pruneauorg143&I. Pshenichnovorg62&M. Puccioorg26,org34&V.
Puninorg107&K. Puranapandaorg141&J. Putschkeorg143&R.E. Quishpeorg125&S.
Ragoniorg109&S. Rahaorg3&S. Rajputorg99&J. Rakorg126&A.
Rakotozafindrabeorg137&L. Ramelloorg32&F. Ramiorg136&R. Raniwalaorg100&S.
Raniwalaorg100&S.S. Räsänenorg43&B.T. Rascanuorg68&R. Rathorg49&V.
Ratzaorg42&I. Ravasengaorg31&K.F. Readorg94,org130&K. Redlichorg83orgIV&A.
Rehmanorg22&P. Reicheltorg68&F. Reidtorg34&X. Renorg6&R. Renfordtorg68&A.
Reshetinorg62&J.-P. Revolorg10&K. Reygersorg102&V. Riabovorg96&T.
Richertorg79,org87&M. Richterorg21&P. Riedlerorg34&W. Rieglerorg34&F.
Riggiorg28&C. Risteaorg67&S.P. Rodeorg49&M. Rodríguez Cahuantziorg44&K.
Røedorg21&R. Rogalevorg89&E. Rogochayaorg74&D. Rohrorg34&D. Röhrichorg22&P.S.
Rokitaorg142&F. Ronchettiorg51&E.D. Rosasorg69&K. Roslonorg142&P.
Rosnetorg134&A. Rossiorg29&A. Rotondiorg139&F. Roukoutakisorg82&A. Royorg49&P.
Royorg108&O.V. Ruedaorg79&R. Ruiorg25&B. Rumyantsevorg74&A. Rustamovorg85&E.
Ryabinkinorg86&Y. Ryabovorg96&A. Rybickiorg118&H. Rytkonenorg126&S.
Sadhuorg141&S. Sadovskyorg89&K. Šafaříkorg34,org37&S.K. Sahaorg141&B.
Sahooorg48&P. Sahooorg48,org49&R. Sahooorg49&S. Sahooorg65&P.K. Sahuorg65&J.
Sainiorg141&S. Sakaiorg133&S. Sambyalorg99&V. Samsonovorg91,org96&A.
Sandovalorg71&A. Sarkarorg72&D. Sarkarorg143&N. Sarkarorg141&P.
Sarmaorg41&V.M. Sartiorg103&M.H.P. Sasorg63&E. Scapparoneorg53&B.
Schaeferorg94&J. Schambachorg119&H.S. Scheidorg68&C. Schiauaorg47&R.
Schickerorg102&A. Schmahorg102&C. Schmidtorg105&H.R. Schmidtorg101&M.O.
Schmidtorg102&M. Schmidtorg101&N.V. Schmidtorg68,org94&A.R. Schmierorg130&J.
Schukraftorg34,org87&Y. Schutzorg34,org136&K. Schwarzorg105&K.
Schwedaorg105&G. Scioliorg27&E. Scomparinorg58&M. Šefčíkorg38&J.E.
Segerorg16&Y. Sekiguchiorg132&D. Sekihataorg45,org132&I.
Selyuzhenkovorg91,org105&S. Senyukovorg136&D. Serebryakovorg62&E.
Serradillaorg71&P. Settorg48&A. Sevcencoorg67&A. Shabanovorg62&A.
Shabetaiorg114&R. Shahoyanorg34&W. Shaikhorg108&A. Shangaraevorg89&A.
Sharmaorg98&A. Sharmaorg99&H. Sharmaorg118&M. Sharmaorg99&N. Sharmaorg98&A.I.
Sheikhorg141&K. Shigakiorg45&M. Shimomuraorg81&S. Shirinkinorg90&Q.
Shouorg111&Y. Sibiriakorg86&S. Siddhantaorg54&T. Siemiarczukorg83&D.
Silvermyrorg79&C. Silvestreorg77&G. Simatovicorg88&G. Simonettiorg34,org103&R.
Singhorg84&R. Singhorg99&V.K. Singhorg141&V. Singhalorg141&T. Sinhaorg108&B.
Sitarorg14&M. Sittaorg32&T.B. Skaaliorg21&M. Slupeckiorg126&N.
Smirnovorg146&R.J.M. Snellingsorg63&T.W. Snellmanorg126&J. Sochanorg116&C.
Sonccoorg110&J. Songorg60,org125&A. Songmoolnakorg115&F. Soramelorg29&S.
Sorensenorg130&I. Sputowskaorg118&J. Stachelorg102&I. Stanorg67&P.
Stankusorg94&P.J. Steffanicorg130&E. Stenlundorg79&D. Stoccoorg114&M.M.
Storetvedtorg36&P. Strmenorg14&A.A.P. Suaideorg121&T. Sugitateorg45&C.
Suireorg61&M. Suleymanovorg15&M. Suljicorg34&R. Sultanovorg90&M.
Šumberaorg93&S. Sumowidagdoorg50&K. Suzukiorg113&S. Swainorg65&A.
Szaboorg14&I. Szarkaorg14&U. Tabassamorg15&G. Taillepiedorg134&J.
Takahashiorg122&G.J. Tambaveorg22&S. Tangorg6,org134&M. Tarhiniorg114&M.G.
Tarzilaorg47&A. Tauroorg34&G. Tejeda Muñozorg44&A. Telescaorg34&C.
Terrevoliorg29,org125&D. Thakurorg49&S. Thakurorg141&D. Thomasorg119&F.
Thoresenorg87&R. Tieulentorg135&A. Tikhonovorg62&A.R. Timminsorg125&A.
Toiaorg68&N. Topilskayaorg62&M. Toppiorg51&F. Torales-Acostaorg20&S.R.
Torresorg120&A. Trifiroorg55&S. Tripathyorg49&T. Tripathyorg48&S.
Trogoloorg26,org29&G. Trombettaorg33&L. Tropporg38&V. Trubnikovorg2&W.H.
Trzaskaorg126&T.P. Trzcinskiorg142&B.A. Trzeciakorg63&T. Tsujiorg132&A.
Tumkinorg107&R. Turrisiorg56&T.S. Tveterorg21&K. Ullalandorg22&E.N.
Umakaorg125&A. Urasorg135&G.L. Usaiorg24&A. Utrobicicorg97&M.
Valaorg38,org116&N. Valleorg139&S. Valleroorg58&N. van der Kolkorg63&L.V.R.
van Doremalenorg63&M. van Leeuwenorg63&P. Vande Vyvreorg34&D. Vargaorg145&Z.
Vargaorg145&M. Varga-Kofaragoorg145&A. Vargasorg44&M. Vargyasorg126&R.
Varmaorg48&M. Vasileiouorg82&A. Vasilievorg86&O. Vázquez Doceorg103,org117&V.
Vecherninorg112&A.M. Veenorg63&E. Vercellinorg26&S. Vergara Limónorg44&L.
Vermuntorg63&R. Vernetorg7&R. Vértesiorg145&M.G.D.L.C. Vicencioorg9&L.
Vickovicorg35&J. Viinikainenorg126&Z. Vilakaziorg131&O. Villalobos
Baillieorg109&A. Villatoro Telloorg44&G. Vinoorg52&A. Vinogradovorg86&T.
Virgiliorg30&V. Vislaviciusorg87&A. Vodopyanovorg74&B. Volkelorg34&M.A.
Völklorg101&K. Voloshinorg90&S.A. Voloshinorg143&G. Volpeorg33&B. von
Hallerorg34&I. Vorobyevorg103&D. Voscekorg116&J. Vrlákováorg38&B.
Wagnerorg22&Y. Watanabeorg133&M. Weberorg113&S.G. Weberorg105,org144&A.
Wegrzynekorg34&D.F. Weiserorg102&S.C. Wenzelorg34&J.P. Wesselsorg144&E.
Widmannorg113&J. Wiechulaorg68&J. Wikneorg21&G. Wilkorg83&J.
Wilkinsonorg53&G.A. Willemsorg34&E. Willsherorg109&B. Windelbandorg102&W.E.
Wittorg130&Y. Wuorg128&R. Xuorg6&S. Yalcinorg76&K. Yamakawaorg45&S.
Yangorg22&S. Yanoorg137&Z. Yinorg6&H. Yokoyamaorg63,org133&I.-K. Yooorg18&J.H.
Yoonorg60&S. Yuanorg22&A. Yuncuorg102&V. Yurchenkoorg2&V.
Zaccoloorg25,org58&A. Zamanorg15&C. Zampolliorg34&H.J.C. Zanoliorg63,org121&N.
Zardoshtiorg34&A. Zarochentsevorg112&P. Závadaorg66&N. Zaviyalovorg107&H.
Zbroszczykorg142&M. Zhalovorg96&X. Zhangorg6&Z. Zhangorg6&C. Zhaoorg21&V.
Zherebchevskiiorg112&N. Zhigarevaorg90&D. Zhouorg6&Y. Zhouorg87&Z.
Zhouorg22&J. Zhuorg6&Y. Zhuorg6&A. Zichichiorg10,org27&M.B. Zimmermannorg34&G.
Zinovjevorg2&N. Zurloorg140&

## 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

org2Bogolyubov Institute for Theoretical Physics, National Academy of Sciences
of Ukraine, Kiev, Ukraine

org3Bose Institute, Department of Physics and Centre for Astroparticle Physics
and Space Science (CAPSS), Kolkata, India

org4Budker Institute for Nuclear Physics, Novosibirsk, Russia

org5California Polytechnic State University, San Luis Obispo, California,
United States

org6Central China Normal University, Wuhan, China

org7Centre de Calcul de l’IN2P3, Villeurbanne, Lyon, France

org8Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN), Havana,
Cuba

org9Centro de Investigación y de Estudios Avanzados (CINVESTAV), Mexico City
and Mérida, Mexico

org10Centro Fermi - Museo Storico della Fisica e Centro Studi e Ricerche
“Enrico Fermi’, Rome, Italy

org11Chicago State University, Chicago, Illinois, United States

org12China Institute of Atomic Energy, Beijing, China

org13Chonbuk National University, Jeonju, Republic of Korea

org14Comenius University Bratislava, Faculty of Mathematics, Physics and
Informatics, Bratislava, Slovakia

org15COMSATS University Islamabad, Islamabad, Pakistan

org16Creighton University, Omaha, Nebraska, United States

org17Department of Physics, Aligarh Muslim University, Aligarh, India

org18Department of Physics, Pusan National University, Pusan, Republic of
Korea

org19Department of Physics, Sejong University, Seoul, Republic of Korea

org20Department of Physics, University of California, Berkeley, California,
United States

org21Department of Physics, University of Oslo, Oslo, Norway

org22Department of Physics and Technology, University of Bergen, Bergen,
Norway

org23Dipartimento di Fisica dell’Università ’La Sapienza’ and Sezione INFN,
Rome, Italy

org24Dipartimento di Fisica dell’Università and Sezione INFN, Cagliari, Italy

org25Dipartimento di Fisica dell’Università and Sezione INFN, Trieste, Italy

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

org27Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN,
Bologna, Italy

org28Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN,
Catania, Italy

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

org30Dipartimento di Fisica ‘E.R. Caianiello’ dell’Università and Gruppo
Collegato INFN, Salerno, Italy

org31Dipartimento DISAT del Politecnico and Sezione INFN, Turin, Italy

org32Dipartimento di Scienze e Innovazione Tecnologica dell’Università del
Piemonte Orientale and INFN Sezione di Torino, Alessandria, Italy

org33Dipartimento Interateneo di Fisica ‘M. Merlin’ and Sezione INFN, Bari,
Italy

org34European Organization for Nuclear Research (CERN), Geneva, Switzerland

org35Faculty of Electrical Engineering, Mechanical Engineering and Naval
Architecture, University of Split, Split, Croatia

org36Faculty of Engineering and Science, Western Norway University of Applied
Sciences, Bergen, Norway

org37Faculty of Nuclear Sciences and Physical Engineering, Czech Technical
University in Prague, Prague, Czech Republic

org38Faculty of Science, P.J. Šafárik University, Košice, Slovakia

org39Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe-
Universität Frankfurt, Frankfurt, Germany

org40Gangneung-Wonju National University, Gangneung, Republic of Korea

org41Gauhati University, Department of Physics, Guwahati, India

org42Helmholtz-Institut für Strahlen- und Kernphysik, Rheinische Friedrich-
Wilhelms-Universität Bonn, Bonn, Germany

org43Helsinki Institute of Physics (HIP), Helsinki, Finland

org44High Energy Physics Group, Universidad Autónoma de Puebla, Puebla, Mexico

org45Hiroshima University, Hiroshima, Japan

org46Hochschule Worms, Zentrum für Technologietransfer und Telekommunikation
(ZTT), Worms, Germany

org47Horia Hulubei National Institute of Physics and Nuclear Engineering,
Bucharest, Romania

org48Indian Institute of Technology Bombay (IIT), Mumbai, India

org49Indian Institute of Technology Indore, Indore, India

org50Indonesian Institute of Sciences, Jakarta, Indonesia

org51INFN, Laboratori Nazionali di Frascati, Frascati, Italy

org52INFN, Sezione di Bari, Bari, Italy

org53INFN, Sezione di Bologna, Bologna, Italy

org54INFN, Sezione di Cagliari, Cagliari, Italy

org55INFN, Sezione di Catania, Catania, Italy

org56INFN, Sezione di Padova, Padova, Italy

org57INFN, Sezione di Roma, Rome, Italy

org58INFN, Sezione di Torino, Turin, Italy

org59INFN, Sezione di Trieste, Trieste, Italy

org60Inha University, Incheon, Republic of Korea

org61Institut 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

org62Institute for Nuclear Research, Academy of Sciences, Moscow, Russia

org63Institute for Subatomic Physics, Utrecht University/Nikhef, Utrecht,
Netherlands

org64Institute of Experimental Physics, Slovak Academy of Sciences, Košice,
Slovakia

org65Institute of Physics, Homi Bhabha National Institute, Bhubaneswar, India

org66Institute of Physics of the Czech Academy of Sciences, Prague, Czech
Republic

org67Institute of Space Science (ISS), Bucharest, Romania

org68Institut für Kernphysik, Johann Wolfgang Goethe-Universität Frankfurt,
Frankfurt, Germany

org69Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México,
Mexico City, Mexico

org70Instituto de Física, Universidade Federal do Rio Grande do Sul (UFRGS),
Porto Alegre, Brazil

org71Instituto de Física, Universidad Nacional Autónoma de México, Mexico
City, Mexico

org72iThemba LABS, National Research Foundation, Somerset West, South Africa

org73Johann-Wolfgang-Goethe Universität Frankfurt Institut für Informatik,
Fachbereich Informatik und Mathematik, Frankfurt, Germany

org74Joint Institute for Nuclear Research (JINR), Dubna, Russia

org75Korea Institute of Science and Technology Information, Daejeon, Republic
of Korea

org76KTO Karatay University, Konya, Turkey

org77Laboratoire de Physique Subatomique et de Cosmologie, Université
Grenoble-Alpes, CNRS-IN2P3, Grenoble, France

org78Lawrence Berkeley National Laboratory, Berkeley, California, United
States

org79Lund University Department of Physics, Division of Particle Physics,
Lund, Sweden

org80Nagasaki Institute of Applied Science, Nagasaki, Japan

org81Nara Women’s University (NWU), Nara, Japan

org82National and Kapodistrian University of Athens, School of Science,
Department of Physics , Athens, Greece

org83National Centre for Nuclear Research, Warsaw, Poland