2015 040 24 February Charged jets in p–Pb

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

Charged jet production cross sections in p–Pb collisions at
$\sqrt{s_{\textnormal{NN}}}=5.02\textnormal{ TeV}$ measured with the ALICE
detector at the LHC are presented. Using the anti-$k_{\textnormal{T}}$
algorithm, jets have been reconstructed in the central rapidity region from
charged particles with resolution parameters $R=0.2$ and $R=0.4$. The
reconstructed jets have been corrected for detector effects and the underlying
event background. To calculate the nuclear modification factor,
$R_{\mathrm{pPb}}$, of charged jets in p–Pb collisions, a pp reference was
constructed by scaling previously measured charged jet spectra at
$\sqrt{s}=7\textnormal{ TeV}$. In the transverse momentum range $20\leq
p_{\mathrm{T,\,ch\;jet}}\leq 120\textnormal{ GeV}$/$c$, $R_{\mathrm{pPb}}$ is
found to be consistent with unity, indicating the absence of strong nuclear
matter effects on jet production. Major modifications to the radial jet
structure are probed via the ratio of jet production cross sections
reconstructed with the two different resolution parameters. This ratio is
found to be similar to the measurement in pp collisions at $\sqrt{s}=7$ TeV
and to the expectations from PYTHIA pp simulations and NLO pQCD calculations
at $\sqrt{s_{\textnormal{NN}}}=5.02\textnormal{ TeV}$.

##  1 Introduction

Jets are the observable final state of a fragmenting parton produced e.g. in
scattering of partons in nuclei with a large momentum transfer, $Q^{2}$. At
sufficiently large $Q^{2}$, the jet production cross section is computable
since it can be factorized into the non-perturbative parton distribution and
fragmentation functions and the cross section of partonic scatterings, which
is calculable in perturbative QCD (pQCD) [1]. Jet measurements in p–Pb and
their comparison to pp provide a tool to better constrain effects of (cold)
nuclear matter on these factors. In particular, they can be used to examine
the role of a modification of the initial distribution of quarks and gluons,
e.g. shadowing effects and gluon saturation [2, 3], and the impact of multiple
scatterings and hadronic re-interactions in the initial and final state [4,
5].

In central heavy-ion collisions, the production of jets and
high-$p_{\textnormal{T}}$ particles is strongly modified: in Pb–Pb collisions
at the LHC, the observed hadron yields are suppressed by up to a factor of
seven compared to pp collisions, approaching a factor of two suppression at
high $p_{\textnormal{T}}$ [6, 7, 8]. A similar suppression is also observed
for reconstructed jets in central Pb–Pb [9, 10, 11, 12, 13]. This phenomenon,
referred to as _jet quenching_ , has also been observed previously in
high-$p_{\textnormal{T}}$ particle production in central Au–Au collisions at
RHIC [14, 15, 16, 17, 18, 19]. It is attributed to the creation of a quark-
gluon plasma (QGP) in the final state, where hard scattered partons radiate
gluons in strong interactions with the medium as first predicted in [20, 21].
This results in an radiative energy loss of the leading parton and a modified
fragmentation pattern.

Initially, p–Pb collisions have been seen as the testing ground for isolated
cold nuclear matter effects, without the formation of a hot and dense medium.
However, recent results on low-$p_{\textnormal{T}}$ particle production and
long range correlations in p–Pb collisions at $\sqrt{s_{\mathrm{NN}}}=5.02$
TeV [22, 23, 24, 25] exhibit features of collective behavior, similar to those
found in Pb–Pb collisions, where they are attributed to the creation of a QGP.
At high $p_{\textnormal{T}}$, results on the production of unidentified
charged particles [26, 27, 28, 29] and jets [30, 31] in p–Pb collisions at
$\sqrt{s_{\mathrm{NN}}}=5.02$ TeV are consistent with the absence of a strong
final state suppression. The question to what extent other nuclear effects
lead to an enhancement of particle production at high $p_{\textnormal{T}}$ is
still open, a possible enhancement in p–Pb collisions has been reported for
single charged hadrons [28]. The measurement of jets in p–Pb collisions
compared to single hadrons tests the parton fragmentation beyond the leading
particle with the inclusion of low-$p_{\textnormal{T}}$ and large-angle
fragments.

A jet is defined experimentally by the algorithm that combines the measured
detector information such as tracks and/or calorimeter cells into jet objects
and by the parameters of the algorithm. The desired properties of such
algorithms in $\mbox{p}\mbox{p}(\bar{\mathrm{p}})$ collisions and in the
corresponding theoretical framework have been discussed e.g. in [32]. In
general, jet algorithms aim to reconstruct the kinematic properties of the
initial parton with as little dependence on the details of its fragmentation
process as possible, i.e. the algorithms should yield consistent results when
applied in a theoretical calculation at any stage of a parton shower and at
final state particle level. A particularly well suited class of algorithms in
this context are those using sequential recombination schemes, which are
infrared and collinear safe, in contrast to many conceptually simpler cone
algorithms. The computationally optimized implementation of sequential
recombination algorithms in the FastJet package [33] facilitates their
applicability also in collision systems with high multiplicity and thereby the
comparison of results obtained with the same jet algorithms in pp, p–Pb, and
Pb–Pb collisions. An additional complication in the context of jet
reconstruction in high-multiplicity events arises from the large background
particle density, i.e. particles in the same aperture as the jet that are not
related to the initial hard scattering. This background can be subtracted on
an event-by-event basis and the impact on the reconstructed jet observable
needs to be evaluated carefully [34, 12, 35].

In this paper, jets reconstructed from charged particles (_charged jets_) with
the anti-$k_{\textnormal{T}}$ algorithm measured with the ALICE detector in
p–Pb collisions at $\sqrt{s_{\textnormal{NN}}}=5.02$ TeV are reported for
different resolution parameters, $R$. Section 2 describes in detail the
correction steps needed in the analysis, including the effect of the event
background and its fluctuations on the jet observables and the unfolding
procedure to account for background as well as detector effects. The results
are presented and discussed in Sec. 3.

##  2 Data Analysis

###  2.1 Event and Track Selection

The data used for this analysis were taken with the ALICE detector [36] during
the p–Pb run of the LHC at $\sqrt{s_{\mathrm{NN}}}=5.02\textnormal{ TeV}$ at
the beginning of 2013. Minimum bias events have been selected requiring at
least one hit in both of the scintillator trigger detectors (V0A and V0C)
covering the pseudorapidity $2.8<\eta_{\mathrm{lab}}<5.1$ and
$-3.7<\eta_{\mathrm{lab}}<-1.7$, respectively [37]. Here and in the following,
$\eta_{\mathrm{lab}}$ denotes the pseudorapidity in the ALICE laboratory
frame. Compared to this frame (with positive $\eta$ in the direction of the
V0A), the nucleon-nucleon center-of-mass system moves in rapidity by
$y_{\mathrm{NN}}=-0.465$ in the direction of the proton beam [38].

The event sample used in the analyses presented in this manuscript was
collected exclusively for the beam configuration where the proton travels from
V0A to V0C (clockwise). A van-der-Meer scan was used to measure the visible
cross section $\sigma_{V0}=2.09\pm 0.07$ b for this case [39]. Monte Carlo
studies show that the sample consists mainly of non-single diffractive (NSD)
interactions and a negligible contribution from single diffractive and
electromagnetic interactions (for more details see [38, 40]). The trigger is
not fully efficient for NSD events. This inefficiency affects only events
without a reconstructed vertex, i.e. with no particles reconstructed within
the acceptance of the SPD. The loss of efficiency is estimated to be 2.3% with
a large systematic uncertainty of 3.1% [38]. In this paper, the normalization
to NSD events is only used for the construction of the nuclear modification
factor.

In addition to the trigger selection, timing and vertex-quality cuts are used
to suppress pile-up and bad quality events. The analysis requires a
reconstructed vertex, which is the case for 98.2% of the events selected by
the trigger. In addition, events with a reconstructed vertex
$|z|>10~{}\mathrm{cm}$ along the beam axis are rejected. In total, about 96M
events are used for the analysis.

Charged particles are reconstructed as tracks in the Inner Tracking System
(ITS) [41] and the Time Projection Chamber (TPC) which cover the full azimuth
and $|\eta_{\mathrm{lab}}|<0.9$ [42]. For tracks with reconstructed track
points close to the vertex (from the two inner Silicon Pixel Detector (SPD)
layers of the ITS), a momentum resolution of 0.8% (3.8%) for
$p_{\textnormal{T}}=1$ GeV/$c$ (50 GeV/$c$) is reached [36]. The azimuthal
distribution of these high quality tracks is not completely uniform due to
inefficient regions in the SPD. This can be compensated by considering in
addition tracks without reconstructed track points in the SPD. For those
tracks, the primary vertex is used as an additional constraint in the track
fitting to improve the momentum resolution. This approach yields a very
uniform tracking efficiency within the acceptance, which is needed to avoid
geometrical biases of the jet reconstruction algorithm caused by a non-uniform
density of reconstructed tracks. The procedure is described in detail in the
context of jet reconstruction with ALICE in Pb–Pb events [12]. For the
analyzed data, the additional tracks (without SPD track points) constitute
approximately 4.3% of the used track sample. Tracks with
$p_{\textnormal{T}}>0.15\mathrm{~{}GeV}/c$ and within a pseudorapidity
interval $|\eta_{\mathrm{lab}}|<0.9$ are used as input to the jet
reconstruction. The overall efficiency for charged particle detection,
including the effect of tracking efficiency as well as the geometrical
acceptance, is 70% at $p_{\textnormal{T}}=0.15\mbox{~{}GeV}/c$ and increases
to 85% at $p_{\textnormal{T}}=1\mbox{~{}GeV}/c$ and above.

###  2.2 Jet reconstruction and background corrections

For the present analysis, the anti-$k_{\mathrm{T}}$ algorithm from the FastJet
package [43] has been used to reconstruct jets from measured tracks with
resolution parameters of $R=0.2$ and $R=0.4$. In general, jets are only
considered for further analysis if the jet-axis is separated from the edge of
the track acceptance in $\eta_{\mathrm{lab}}$ by at least the resolution
parameter $R$ used in the jet finding, e.g. jets reconstructed with $R=0.4$
are accepted within $|\eta_{\mathrm{jet,\,lab}}|<0.9-0.4=0.5$. The jet
transverse momentum is calculated by FastJet using the $p_{\textnormal{T}}$
recombination scheme. To enable background corrections, the area $A$ for each
jet is determined internally by distributing _ghost particles_ into the area
that is clustered [44]. Ghost particles have vanishing momentum and therefore
do not influence the jet finding procedure. By construction, the number of
ghost particles in a jet is a direct measure for the jet area. A ghost
particle density of 200 per unit area (0.005 area per ghost particle) was used
to obtain a good area resolution with a reasonable computing time.

Figure 1: (Color online) Left: Probability distribution of the event-by-event
transverse momentum background density (see Eq. 1). The mean and variance for
two event classes are indicated in the figure.
$p_{\mathrm{T,\,ch\;jet}}^{\mathrm{raw}}$ represents uncorrected jet
$p_{\textnormal{T}}$. Right: Probability distribution of background
fluctuations calculated with the random cone approach and defined via Eq. 4
(resolution parameter $R=0.4$).

In Pb–Pb collisions, the background from particles not from the same hard
scattering as the jet has a significant impact on the reconstructed jet
momentum [12, 35]. The transverse momentum density of this background is
estimated with a statistically robust method by using the median of all jet
$p_{\mathrm{T,\,ch\;jet}}$ per area within one event for jets reconstructed
with the $k_{\textnormal{T}}$ algorithm. In p–Pb collisions, the multiplicity
density is two orders of magnitude smaller than in central Pb–Pb collisions
[40], so a corresponding reduction of the jet background is expected. To
obtain a reliable estimate for the more sparse environment of p–Pb events a
modified version of the approach described in [45] for pp collisions is
employed. It uses the same method as in Pb–Pb, but contains an additional
correction factor, $C$, to account for regions without particles, which
otherwise would not contribute to the overall area estimate. The background
density for each event is then given by

$\rho_{\mathrm{ch}}=\mathrm{median}\left\\{\frac{p_{\mathrm{T},\,i}}{A_{i}}\right\\}\cdot
C,$ (1)

where $i$ runs over all reconstructed $k_{\textnormal{T}}$ jets in the event
with momentum $p_{\mathrm{T},\,i}$ and area $A_{i}$. $C$ is defined by

$C=\frac{\sum_{j}{A_{j,\,{k_{\mathrm{T}}}}}}{A_{\textnormal{acc}}}.$ (2)

Here, the numerator is the area of all $k_{\mathrm{T}}$ jets containing tracks
and the denominator, $A_{\textnormal{acc}}$, is the acceptance in which
charged particles are considered as input to the jet finding ($2\times
0.9\times 2\pi$). The probability distribution for the background density in
this method, with the same track selection criteria as the signal jet
reconstruction and a radius of 0.4, is shown in Fig. 1 (left). The background
density obtained with $R=0.4$ is used both for the correction of signal jets
with $R=0.4$ and $R=0.2$ to avoid event-by-event fluctuations in the
difference of the momenta for the two radii.

The probability distribution of $\rho_{\mathrm{ch}}$ decreases approximately
exponentially. It is smaller than $4$ GeV/$c$ for $98.6$% of all events. The
mean background density and its variance for all events is
$\langle\rho_{\mathrm{ch}}\rangle=1.02$ GeV/$c$ (with negligible statistical
uncertainty) and $\sigma(\rho_{\mathrm{ch}})=0.91\pm 0.01$ GeV/$c$. For events
containing a jet with uncorrected transverse momentum
$p_{\mathrm{T,\,ch\;jet}}>20$ GeV/$c$, it is
$\langle\rho_{\mathrm{ch}}\rangle=2.2\pm 0.01$ GeV/$c$ and
$\sigma(\rho_{\mathrm{ch}})=1.47\pm 0.09$ GeV/$c$, respectively. The observed
increase of the underlying event activity for events that contain a
high-$p_{\textnormal{T}}$ jet is expected. This increase is already present in
pp collisions and has been quantified in detail and with more differential
observables than the background density, e.g. in [46].

The background density estimate provides an event-by-event correction for each
jet with reconstructed transverse momentum $p_{\mathrm{T,\,ch\;jet}}$ and jet
area $A_{\mathrm{ch\;jet}}$:

$p_{\mathrm{T,\,ch\;jet}}=p_{\mathrm{T,\,ch\;jet}}^{\mathrm{raw}}-A_{\mathrm{ch\;jet}}\cdot\rho_{\mathrm{ch}}.$
(3)

However, this approach neglects that the background for a given event is not
uniformly distributed in the ($\eta_{\mathrm{lab}},\varphi$)-plane but
fluctuates from region to region. These fluctuations are mainly Poissonian,
but also encode correlated region-to-region variations of the particle
multiplicity and the mean $p_{\textnormal{T}}$ [35]. The effect of these
fluctuations can be accounted for on a statistical basis in the unfolding of
the measured jet $p_{\mathrm{T,\,ch\;jet}}$-distributions. The distribution of
region-to-region density fluctuations around the event-wise background density
estimate can be evaluated for the full event sample by a Random Cone (RC)
approach as described in [35]. Cones with a radius $R$ corresponding to the
resolution parameter of the jet finding algorithm are placed randomly in the
($\eta_{\mathrm{lab}},\varphi$) jet-acceptance and the transverse momenta for
all tracks (charged particles) falling into this cone are summed and compared
to the background estimate:

$\delta
p_{\mathrm{T,\,ch}}=\sum_{\mathrm{i}}{p_{\mathrm{T,\,i}}-\rho_{\mathrm{ch}}A},~{}~{}~{}A=\pi
R^{2}.$ (4)

The distribution of the residuals, $\delta p_{\mathrm{T,\,ch}}$, as shown in
Fig. 1 (right) for $R=0.4$, is a direct measure for all intra-event
fluctuations of the background and can be used directly in the unfolding
procedure. In Fig. 1 (right), a clear asymmetry of the distribution is
visible. It is caused by the fact that the $\delta p_{\mathrm{T,\,ch}}$
distribution of single particles sampled in the cone is asymmetric. Since the
number of particles within a cone increases with its size, statistical
fluctuations of the background estimate also increase (see also [35]).
Furthermore, the randomly placed cones can also overlap with jets. In p–Pb
collisions, there is the possibility for multiple hard collisions within one
p–Pb event, so a jet can also be the background to a jet from another hard
collision and contribute as an upward fluctuation. Therefore, an overlap of
random cones with possible signal jets should not be a-priori excluded in the
fluctuation estimate, but is part of its systematic uncertainty.

###  2.3 Detector effects and unfolding

Figure 2: (Color online) Left: Projection of the combined unfolding matrix for
jets with particle-level momentum
$45<p_{\mathrm{T,\,ch\;jet}}^{\mathrm{part}}<50$ GeV/$c$. The matrix is
obtained from the combination of the detector response and background
fluctuation matrices, which are also shown as projections (see text for
details). Right: Probability distribution of the relative difference between
particle-level (generated true) and detector-level charged jet transverse
momentum for jets with different momenta. The effect of background
fluctuations is included for the jets reconstructed at detector level.
Characteristic values of the distributions are summarized in Table 1.

The main detector-related effects on the reconstructed jet are the
reconstruction efficiency and the momentum resolution for single charged
particles. To determine the correction for these, a full detector simulation
of pp jet events generated with PYTHIA6 (Perugia 2011, version 6.425) [47] and
GEANT3 particle transport [48] is performed. In the simulation, two jet
collections are matched geometrically (closeness in
($\eta_{\mathrm{lab}},\varphi$)-plane) with a one-to-one correspondence [12]:
jets reconstructed at the charged particle level (_part_) without detector
effects and jets reconstructed from tracks after particle transport through
the ALICE detector (_det_). In the simulation, the particle level
reconstruction includes charged primary particles produced in the collision
with $p_{\textnormal{T}}>0.15$ GeV/$c$. Charged decay products from primary
particle decays, excluding those from weak decays of strange particles, are
included with the same $p_{\textnormal{T}}$ threshold. The response matrix is
populated with matched particle- and detector-level jets. It relates the
particle-level to the detector-level charged jet momentum and encodes the
effects of single-particle momentum resolution and reconstruction efficiency
on the reconstructed jet momentum. A correction for the missing energy of
neutral jet-constituents is not applied. The response is shown on a
logarithmic scale in Fig. 2 (left) for charged jets with $R=0.4$ and particle-
level momentum between $45<p_{\mathrm{T,\,ch\;jet}}^{\mathrm{part}}<50$
GeV/$c$. It can be seen that the most probable value for the reconstructed
momentum is the particle-level momentum, but the distribution has large tails
to the left and right. It is more probable that jets are reconstructed with a
lower momentum than the truth, which is due to the dominating effect of the
single-particle reconstruction efficiency that reduces the number of
reconstructed particles in a jet. The tail to the right-hand side is mainly
due to the single-particle momentum resolution, where a fraction of tracks is
reconstructed with higher momentum than the truth, causing an upward shift of
the jet momentum.

In addition, Fig. 2 (left) shows the effect of the background fluctuations on
the reconstructed jet momentum and the combination of detector effects and
background fluctuations. Even though the background fluctuations show a strong
tail to the right-hand side, it is seen that in the combined unfolding matrix
the effects of single-particle momentum resolution play the dominant role in
reconstructing a jet with momentum higher than the truth. The default
algorithm for the unfolding of the measured jet spectrum is based on the
Singular Value Decomposition (SVD) approach [49] as implemented in the
RooUnfold package [50]. The default prior in the unfolding procedure is a
smoothed version of the uncorrected jet spectrum itself. In addition to the
SVD unfolding approach, Bayesian [51, 52] and $\chi^{2}$ [53] unfolding have
been used for systematic comparisons and validity checks. The unfolded
spectrum is also corrected for unmatched jets using a jet reconstruction
efficiency obtained from generated–reconstructed comparison. This jet
reconstruction efficiency is larger than 96% in the considered momentum range.

$p_{\mathrm{T,\,ch\;jet}}^{\mathrm{part}}$ | $20-25\mbox{~{}GeV/}c$ | $45-50\mbox{~{}GeV/}c$ | $80-90\mbox{~{}GeV/}c$
---|---|---|---
MPV (Gaussian Fit) |  $0.006$$\,\pm$ | $0.002$ |  $-0.001$$\,\pm$ | $0.002$ |  $-0.010$$\,\pm$ | $0.004$
id. w/o bkg. fluct. |  $0.007$$\,\pm$ | $0.001$ |  $-0.003$$\,\pm$ | $0.002$ |  $-0.013$$\,\pm$ | $0.004$
Mean |  $0.149$$\,\pm$ | $0.030$ |  $-0.181$$\,\pm$ | $0.030$ |  $-0.222$$\,\pm$ | $0.030$
id. w/o bkg. fluct. |  $-0.163$$\,\pm$ | $0.030$ |  $-0.188$$\,\pm$ | $0.030$ |  $-0.226$$\,\pm$ | $0.030$
Width $\sigma$ |  $0.238$$\,\pm$ | $0.030$ |  $0.246$$\,\pm$ | $0.030$ |  $0.259$$\,\pm$ | $0.030$
id. w/o bkg. fluct. |  $0.233$$\,\pm$ | $0.009$ |  $0.245$$\,\pm$ | $0.005$ |  $0.258$$\,\pm$ | $0.003$
Quartile, 25% above |  $0.01$$\,\pm$ | $0.01$ |  $-0.01$$\,\pm$ | $0.02$ |  $-0.01$$\,\pm$ | $0.02$
id. w/o bkg. fluct. |  $0.01$$\,\pm$ | $0.01$ |  $-0.01$$\,\pm$ | $0.02$ |  $-0.03$$\,\pm$ | $0.02$
Quartile, 50% above |  $-0.05$$\,\pm$ | $0.04$ |  $-0.09$$\,\pm$ | $0.01$ |  $-0.13$$\,\pm$ | $0.04$
id. w/o bkg. fluct. |  $-0.07$$\,\pm$ | $0.04$ |  $-0.09$$\,\pm$ | $0.04$ |  $-0.13$$\,\pm$ | $0.04$
Quartile, 75% above |  $-0.25$$\,\pm$ | $0.06$ |  $-0.29$$\,\pm$ | $0.05$ |  $-0.37$$\,\pm$ | $0.04$
id. w/o bkg. fluct. |  $-0.27$$\,\pm$ | $0.04$ |  $-0.29$$\,\pm$ | $0.06$ |  $-0.37$$\,\pm$ | $0.04$
Table 1:  Characteristic values for the distribution of residuals of the total
charged jet response shown in Fig. 2 (right), including the effect of
background fluctuations and without: most probable value (MPV) determined via
a Gaussian fit to the central peak region, first and second moment (mean and
width $\sigma$), and quartiles. The precision of the quartiles is limited by
the finite bin width of 0.01.

The influence of these detector effects and background fluctuations on the jet
momentum is shown for three transverse momentum intervals in Fig. 2 (right)
via the probability distribution of the relative difference of the detector-
level and particle-level charged jet transverse momentum. For all momentum
bins the distribution is asymmetric. The most probable response was determined
using Gaussian fits to the peak region. It can be seen in Tab. 1 that it is
close to zero ($\leq 1\%$) with a mild $p_{\textnormal{T}}$ dependence. To
further quantify the distributions, numerical values for their mean and width
are also given in Tab. 1. Since the width is not a well-defined measure of the
jet momentum resolution for these asymmetric distributions, the quartiles of
the distribution are provided in addition. Approximately, 25% of the jets have
a larger momentum than the generated. The 50% (median) correction is only 5%
for $p_{\mathrm{T,\,ch\;jet}}^{\mathrm{part}}=20-25$ GeV/$c$ and increases
towards larger jet momenta. In Tab. 1 the values for the respective
distributions without background fluctuations are also given (not shown in
Fig. 2). Clearly, the instrumental response dominates the jet response as
already seen in Fig. 2 (left). The main effect of the background fluctuations
is a broadening of the jet response and an upward shift of the average
reconstructed energy due to the asymmetric shape of the fluctuations as seen
in Fig. 1 (right). The most probable value remains unaffected within the
uncertainties when background fluctuations are included.

###  2.4 Nuclear modification factor

The nuclear modification factor compares a $p_{\textnormal{T}}$-differential
yield in p–Pb collisions to the differential production cross section in pp
collisions at the same $\sqrt{s_{\textnormal{NN}}}$ to quantify nuclear
effects:

$R_{\mathrm{pPb}}=\frac{\mathrm{d^{2}}N_{\mathrm{pPb}}/\mathrm{d}\eta\mathrm{d}p_{\mathrm{T}}}{\left<T_{\mathrm{pPb}}\right>\cdot\mathrm{d^{2}}\sigma_{\mathrm{pp}}/\mathrm{d}\eta\mathrm{d}p_{\mathrm{T}}}.$
(5)

Here, $\left<T_{\mathrm{pPb}}\right>$ is the nuclear overlap function which
accounts for the increased parton flux in p–Pb compared to pp collisions. It
is related to the number of binary nucleon-nucleon collisions via
$\left<T_{\mathrm{pPb}}\right>=\left<N_{\mathrm{coll}}\right>/\sigma_{\mathrm{INEL}}^{\mathrm{pp}}$
and has been calculated in a Glauber Monte Carlo, as described in [38]. Here,
$\sigma_{\mathrm{INEL}}^{\mathrm{pp}}$ represents the total inelastic cross
section in pp collisions. For minimum bias p–Pb collisions, the nuclear
overlap function is $\left<T_{\mathrm{pPb}}\right>=(0.0983\pm
0.0034)\,\mathrm{mb}^{-1}$ and $\left<N_{\mathrm{coll}}\right>=6.87\pm 0.56$.
In this paper, the reference differential production cross section in pp is
constructed from the ALICE charged jet measurement at 7 TeV [54] by a pQCD
based scaling. In the nuclear modification factor, the invariant yield for NSD
events in p–Pb is compared to inelastic pp collisions. Hence, the additional
correction of $(2.3\pm 3.1)\%$ is applied as discussed above.

###  2.5 NLO calculations and pp reference

Perturbative QCD calculations are used for two purposes in this paper: for
comparison to the measurement of jet production in p–Pb, and as additional
input to the construction of the pp reference. The calculations have been
performed within the POWHEG box framework [55, 56], which facilitates next-to-
leading order (NLO) precision in calculating parton scattering cross sections
in an event-by-event Monte Carlo. Event-by-event the outgoing partons from
POWHEG are passed to PYTHIA8 [57] where the subsequent parton shower is
handled. For this, a POWHEG version matched to the PYTHIA8 fragmentation is
used to avoid double counting of NLO effects already considered in the PYTHIA8
code. The Monte Carlo approach has the advantage that the same selection
criteria and jet finding algorithm can be used on final state particle level,
as in the analysis of the real data, in particular, the limitation to charged
constituents of a jet. The dominant uncertainty in the parton level
calculation is given by the choice of renormalization scale,
$\mu_{\mathrm{R}}$, and factorization scale, $\mu_{\mathrm{F}}$. The default
value has been chosen to be
$\mu_{\mathrm{R}}=\mu_{\mathrm{F}}=p_{\textnormal{T}}$ and independent
variations by a factor of two around the central value are considered as the
systematic uncertainty. In addition, the uncertainty on the parton
distribution functions has been taken into account by the variation of the
final results for the respective error sets of the parton density functions
(PDFs).

For the comparison with the measured p–Pb data, proton PDFs corrected for
nuclear effects (CTEQ6.6 [58] with EPS09 [59]) have been used. Prior to
passing the scattered partons to PYTHIA8 for showering, they can be boosted
into the same reference frame as the p–Pb reaction by $y_{\mathrm{NN}}=0.465$.

The construction of the pp reference at $\sqrt{s_{\textnormal{NN}}}=5.02$ TeV
is based on the ALICE measurement of charged jets in pp collisions at 7 TeV,
described in detail in [54]. For the purpose of the reference scaling, the
same analysis chain has been used as for p–Pb. The same binning in
pseudorapidity and transverse momentum allows for a partial cancellation of
common systematic uncertainties in the pp and p–Pb data sets. In addition, the
same background subtraction approach as in the p–Pb analysis is used for the
pp data. In the present analysis, the scaling is done with a factor which is
determined for each $p_{\mathrm{T,\,ch\;jet}}$ bin by the NLO pQCD
calculations (POWHEG+PYTHIA8) at the two energies. For the pp reference
scaling the parton distribution functions in the POWHEG calculation have been
replaced by the free proton PDF from CTEQ6.6. The scaling factor is given by

$F(p_{\textnormal{T}})=\frac{\left.\mathrm{yield}(p_{\mathrm{T,\,ch\;jet}})\right|^{5.02\textnormal{
TeV},\,\mathrm{boosted}}_{\mathrm{pp,\,NLO}}}{\left.\mathrm{yield}(p_{\mathrm{T,\,ch\;jet}})\right|^{7\textnormal{
TeV}}_{\mathrm{pp,\,NLO}}}.$ (6)

The factor decreases monotonically from $F\approx 0.65$ to $0.45$ in the
reported $p_{\textnormal{T}}$ range. As already described above, the
laboratory frame is not the center-of-mass frame of the collision as is the
case for pp collisions. Therefore, the numerator of the scaling factor $F$ in
Eq. 6 is determined in the NLO calculation where the additional Lorentz-boost
is applied to the hard scattered partons prior to fragmentation. The resulting
reduction of the observed jets for $|\eta_{\mathrm{lab}}|<0.5$ is smaller than
5% in the relevant momentum range.

###  2.6 Jet production cross section ratio

The broadening or narrowing of the parton shower with respect to the original
parton direction can have a direct impact on the jet production cross section
reconstructed with different resolution parameters. This can be tested via the
ratio of yields or cross sections in common rapidity interval, here
$|\eta_{\mathrm{lab}}|<0.5$ for $R=0.2$ and $0.4$:

$\mathscr{R}(0.2,\,0.4)=\frac{\mathrm{d}\sigma_{\mathrm{pPb,\,R=0.2}}/\mathrm{d}p_{\mathrm{T}}}{\mathrm{d}\sigma_{\mathrm{pPb,\,R=0.4}}/\mathrm{d}p_{\mathrm{T}}}.$
(7)

Considering the extreme scenario that all fragments are already contained
within $R=0.2$ this ratio is unity. In this case, also the statistical
uncertainties between $R=0.2$ and $R=0.4$ are fully correlated and cancel
completely in the ratio, when the jets are reconstructed from the same data
set. In the case the jets are less collimated, the ratio decreases and the
statistical uncertainties only cancel partially. For the analysis presented in
this paper, the conditional probability for reconstructing a $R=0.2$ jet in
the same $p_{\textnormal{T}}$-bin as a geometrically close $R=0.4$ jet is
$25-50$%, which leads to a reduction of the statistical uncertainty of the
ratio of $5-10\%$ compared to the case of no correlation.

###  2.7 Systematic uncertainties

The various sources of systematic uncertainties are listed in Tab. 2 for the
full $p_{\textnormal{T}}$-range of the three observables presented in this
paper: jet production cross section, nuclear modification factor, and cross
section ratio. The most important sources will be discussed in the following.

The dominant source of uncertainty for the $p_{\textnormal{T}}$-differential
jet production cross section is the imperfect knowledge of the single-particle
tracking efficiency that has a direct impact on the correction of the jet
momentum in the unfolding, as discussed above. In p–Pb collisions, the single-
particle efficiency is known with a relative accuracy of 4%, which is
equivalent to a 4% uncertainty on the jet momentum scale. To estimate the
effect of the tracking efficiency uncertainty on the jet yield, the tracking
efficiency is artificially lowered by randomly discarding a certain fraction
(4% in p–Pb) of tracks used as input for the jet finding. Depending on the
shape of the spectrum, the uncertainty on the single particle efficiency (jet
momentum scale) translates into an uncertainty of 8 to 15% on the yield.

To estimate the uncertainty on the p–Pb nuclear modification factor, the
uncertainty on the single-particle tracking efficiency in the two collision
systems (pp and p–Pb) has to be evaluated. This uncertainty on the efficiency
is correlated between the data sets, since the correction is determined with
the same underlying Monte Carlo description of the ALICE detector and for
similar track quality cuts. Only variations of detector conditions between run
periods may reduce the degree of correlation. The uncorrelated uncertainty has
been estimated to be 2%, and the uncertainty for the nuclear modification
factor has been determined by artificially introducing such a difference in
the tracking efficiency between the two collision systems.

The uncertainty on the spectra induced by the underlying event subtraction has
been estimated by comparing the results with various methods for background
subtraction; ranging from purely track-based to jet-based density estimates,
including an $\eta_{\mathrm{lab}}$-dependent correction. As seen in Fig. 1, a
typical correction $\pi R^{2}\rho_{\mathrm{ch}}$ for a jet with $R=0.4$ is
about 1 GeV/$c$. The uncertainty on this correction can be treated similar to
an uncertainty on the jet momentum scale. For the final spectrum, the
uncertainty on the yields from the background correction method is
approximately $2$%.

In the determination of the fluctuations of the underlying event, the main
uncertainty is given by the exclusion of reconstructed jets in the random cone
sampling of the event. The probability for a random cone to overlap with
reconstructed jets is higher than for the jets itself. On average, a jet can
overlap with $N_{\mathrm{coll}}-1$ jets in one event. The random cone can
overlap with $N_{\mathrm{coll}}$ jets. To account for this, the $\delta
p_{\mathrm{T,\,ch}}$ calculation can be modified to discard on a statistical
basis random cones that overlap with signal jets. This lowers the average
overlap probability. However, since this modified $\delta p_{\mathrm{T,\,ch}}$
calculation strongly depends on the signal jet definition and also on how an
overlap is defined, it is not used by default but considered for systematic
uncertainties. The effect of this partial signal exclusion approach on the
fully corrected jet yields is of the order of 0.1%.

Figure 3: (Color online) Top panel: $p_{\textnormal{T}}$-differential
production cross section of charged jet production in p–Pb collisions at
$5.02$ TeV for $R=0.4$. Bottom panel: Ratio of data and NLO pQCD calculations.
The global uncertainty from the measurement of the visible cross section of
$3.5\%$ is not shown. The uncertainties on the pQCD calculation are only shown
in the ratio plot as dashed lines. The pQCD calculations take into account the
rapidity shift of the nucleon-nucleon center-of-mass system in p–Pb with a
boosted parton system.

The uncertainty of the scaling procedure to obtain the reference spectrum is
estimated by determining the scaling factors F($p_{\textnormal{T}}$) after
varying the scales $\mu_{\mathrm{R}}$ and $\mu_{\mathrm{F}}$ in the POWHEG NLO
generation, and by using different tunes in the outgoing fragmentation handled
by PYTHIA8. Furthermore, standalone calculations with PYTHIA6 and PYTHIA8
using different generator tunes and with HERWIG at the two energies have been
performed to obtain scaling factors according to Eq. 6. A general uncertainty
for how well LO generators and NLO calculations can describe the
$\sqrt{s}$-dependence of particle production is also considered: in ALICE
measurements of the $\pi^{0}$ production in pp collisions, it has been
observed that pQCD calculations predict a stronger increase of the production
cross section when going from $0.9$ to 7 TeV than supported by the data [60].
A similar effect is also seen in unidentified charged hadrons measured with
ALICE at 0.9, 2.76, and 7 TeV [61]. Furthermore, the $\sqrt{s}$-dependence of
the jet production cross section has been cross checked internally with an
interpolation between 7 and 2.76 TeV, using preliminary ALICE results on
charged jets at $\sqrt{s}=2.76$ TeV. In total, these studies yield an
additional uncertainty on the pp reference of $10\%$ for the extrapolation
from 7 to 5.02 TeV. It is reported as an independent normalization
uncertainty, similar to the uncertainty on the nuclear overlap function.

Observable | Jet cross section | $R_{\mathrm{pPb}}$ | $\mathscr{R}$
---|---|---|---
Resolution parameter | $R=0.2$ | $R=0.4$ | $R=0.2$ | $R=0.4$ | 0.2/0.4
Uncertainty source |
Single-particle efficiency (%) | $7.9-12.8$ | $10.2-14.2$ | $4.1-5.9$ | $4.9-6.3$ | $2.1-2.1$
Unfolding (%) | 2.2 | 1.7 | 2.8 | 2.2 | 1.5
Unfolding prior steepness (%) | $1.4-4.8$ | $0.5-4.0$ | $2.9-8.0$ | $0.9-4.4$ | $1.1-1.5$
Regularization strength (%) | $3.1-3.9$ | $2.3-4.4$ | $3.6-5.8$ | $2.3-5.6$ | $1.1-4.7$
Minimum $p_{\textnormal{T}}$ cut-off (%) | $1.1-0.3$ | $2.3-0.1$ | $1.3-1.4$ | $2.8-4.1$ | $1.2-0.4$
Background estimate (%) | $1.8-0.6$ | $3.7-1.5$ | $1.8-0.6$ | $3.7-1.5$ | $2.0-0.9$
$\delta p_{\mathrm{T,\,ch}}$ estimate (%) | $0.0-0.0$ | $0.1-0.0$ | $0.0-0.0$ | $0.1-0.0$ | $0.1-0.0$
Combined uncertainty (%) | $9.2-14.4$ | $11.5-15.5$ | $7.1-11.9$ | $7.5-10.7$ | $3.8-5.7$
$\left<T_{\mathrm{pPb}}\right>$ (%) | - | - | 3.4 | 3.4 | -
pp cross section (%) | - | - | 3.5 | 3.5 | -
Reference scaling pp 7 TeV (%) | - | - | 10.0 | 10.0 | -
NSD selection efficiency p–Pb (%) | - | - | 3.1 | 3.1 | -
Combined scaling uncertainty (%) | - | - | 11.6 | 11.6 | -
Table 2:  Summary of systematic uncertainties on the fully corrected jet
spectrum, the corresponding nuclear modification factor, and the jet
production cross section ratio for the resolution parameters $R=0.2$ and
$R=0.4$. The percentages are given for the whole shown transverse momentum
range $20-120$ GeV/$c$

##  3 Results

Figure 4: (Color online) Top panel: $p_{\textnormal{T}}$-differential
production cross section of charged jet production in p–Pb collisions at
$5.02$ TeV for $R=0.2$. Bottom panel: Ratio of data and NLO pQCD calculations.
The global uncertainty from the measurement of the visible cross section of
$3.5\%$ is not shown. The uncertainties on the pQCD calculation are only shown
in the ratio plot as dashed lines. The pQCD calculations take into account the
rapidity shift of the nucleon-nucleon center-of-mass system in p–Pb with a
boosted parton system.

The $p_{\textnormal{T}}$-differential production cross sections for jets
reconstructed from charged particles in minimum bias p–Pb collisions at
$\sqrt{s_{\textnormal{NN}}}=5.02$ TeV are shown in Figs. 3 and 4 for the
resolution parameters $R=0.4$ and $R=0.2$. The spectra are found to agree well
with scaled NLO pQCD calculations (POWHEG+PYTHIA8) using nuclear PDFs
(CTEQ6.6+EPS09) as seen best in the ratio data over calculation in the lower
panels. However, the effect of the nuclear PDFs on the jet production in the
reported kinematic regime is almost negligible, as seen in the comparison to
calculations with only proton PDFs (CTEQ6.6).

Figure 4 also shows the jet spectra for $-0.65<\eta_{\mathrm{lab}}<-0.25$ and
$0.25<\eta_{\mathrm{lab}}<0.65$ compared to the results from the symmetric
selection $|\eta_{\mathrm{lab}}|<0.5$. Here, $\eta_{\mathrm{lab}}$ denotes the
pseudorapidity of the jet axis. The first selection roughly corresponds to a
small window around mid-rapidity for the nucleon-nucleon center-of-mass
system, while the second is separated from it by about one unit in rapidity.
No significant change of the jet spectra is observed for these two
$\eta_{\mathrm{lab}}$ regions centered at $-0.45$ and $0.45$. Thus, the jet
measurement has no strong sensitivity to the rapidity shift and the
pseudorapidity dependent variation of the multiplicity (underlying event)
within the statistical and systematic uncertainties of the measurement.

The nuclear modification factor $R_{\mathrm{pPb}}$ is constructed based on the
$p_{\textnormal{T}}$-differential yields and the extrapolated pp production
cross section at $5.02$ TeV for $R=0.2$ and $0.4$. It is shown in the left and
right panel of Fig. 5, respectively. In the reported
$p_{\textnormal{T}}$-range, it is consistent with unity, indicating the
absence of a large modification of the initial parton distributions or a
strong final state effect on jet production. Before comparing these results to
the measured single-particle results for $R_{\mathrm{pPb}}$, one has to
consider that the same reconstructed $p_{\textnormal{T}}$ corresponds to a
different underlying parton transverse momentum. Assuming that all spectra
should obey the same power law behavior at high $p_{\textnormal{T}}$, an
effective conversion between the spectra can be derived at a given energy via
the POWHEG+PYTHIA8 simulations described above. To match the single charged
particle spectra in the simulation to charged jets with $R=0.4$, a
transformation $p_{\mathrm{T}}^{h^{\pm}}\rightarrow
2.28p_{\mathrm{T}}^{h^{\pm}}$ is needed. Thus, the reported nuclear
modification factor for charged jets probes roughly the same parton
$p_{\textnormal{T}}$-region as the ALICE measurement of single charged
particles that shows a nuclear modification factor in agreement with unity in
the measured high-$p_{\textnormal{T}}$ range up to 50 GeV/$c$ [27].

Since the jet measurements integrate the final state particles, they have a
smaller sensitivity to the fragmentation pattern of partons than single
particles. Differences between the nuclear modification factor for jets and
single high-$p_{\textnormal{T}}$ particles, as suggested by measurements in
[28, 29], could point to a modified fragmentation pattern or differently
biased jet selection in p–Pb collisions.

Figure 5: (Color online) Nuclear modification factors $R_{\mathrm{pPb}}$ of
charged jets for $R=0.2$ (left) and $R=0.4$ (right). The combined global
normalization uncertainty from $\left<T_{\mathrm{pPb}}\right>$, the correction
to NSD events, the measured pp cross section, and the reference scaling is
depicted by the box around unity. Figure 6: (Color online) Charged jet
production cross section ratio for different resolution parameters as defined
in Eq. 7. The data in p–Pb collisions at
$\sqrt{s_{\textnormal{NN}}}=5.02\textnormal{ TeV}$ are compared to PYTHIA6
(tune: Perugia 2011, no uncertainties shown) and POWHEG+PYTHIA8 (combined
stat. and syst. uncertainties shown) at the same energy, and to pp collisions
at 7 TeV (only stat. uncertainties shown).

A modified fragmentation pattern may be also reflected in the collimation or
transverse structure of jets. A first step in testing possible cold nuclear
matter effects on the jet structure is the ratio of jet production cross
sections for two different resolution parameters. It is shown for $R=0.2$ and
$R=0.4$ in p–Pb in Fig. 6 and compared to PYTHIA6 (Tune Perugia 2011) and
POWHEG+PYTHIA8 at $\sqrt{s_{\textnormal{NN}}}=5.02$ TeV and to ALICE results
in pp collisions at $\sqrt{s}=7$ TeV [54]. All data show the expected increase
of the ratio from the increasing collimation of jets for higher transverse
momentum and agree well within the uncertainties. No significant energy
dependence or change with collision species is observed. The data for p–Pb
collisions is well described by the NLO calculation as well as by the
simulation of pp collisions with PYTHIA6 at the same energy. It should be
noted that the ratio for charged jets is, in general, above the ratio obtained
for fully reconstructed jets, containing charged and neutral constituents.
This can be understood from the contribution from neutral pions that decay
already at the collision vertex and lead to an effective broadening of the jet
profile when including the neutral component in the jet reconstruction, mainly
in the form of decay photons. For the same reason, the inclusion of the
hadronization in the NLO pQCD calculation is essential to describe the ratio
of jet production cross section as also discussed in [62].

##  4 Summary

In this paper, $p_{\textnormal{T}}$-differential charged jet production cross
sections in p–Pb collisions at $\sqrt{s_{\mathrm{NN}}}=5.02$ TeV have been
shown up to $p_{\mathrm{T,\,ch\;jet}}$ of 120 $\mbox{~{}GeV/}c$ for resolution
parameters $R=0.2$ and $R=0.4$. The charged jet production is found to be
compatible with scaled pQCD calculations at the same energy using nuclear
PDFs. At the same time, the nuclear modification factor $R_{\mathrm{pPb}}$
(using a scaled measurement of jets in pp collisions at $\sqrt{s}=7$ TeV as a
reference) does not show strong nuclear effects on jet production and is
consistent with unity for $R=0.4$ and $R=0.2$ in the measured
$p_{\textnormal{T}}$-range between 20 and 120 GeV/$c$. The jet cross section
ratio of $R=0.2/0.4$ is compatible with 7 TeV pp data and also with the
predictions from PYTHIA6 Perugia 2011 and POWHEG+PYTHIA8 calculations at 5.02
TeV. No indication of a strong nuclear modification of the jet radial profile
is observed, comparing jets with different resolution parameters $R=0.2$ and
$R=0.4$.

## 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: State
Committee of Science, World Federation of Scientists (WFS) and Swiss Fonds
Kidagan, Armenia, Conselho Nacional de Desenvolvimento Científico e
Tecnológico (CNPq), Financiadora de Estudos e Projetos (FINEP), Fundação de
Amparo à Pesquisa do Estado de São Paulo (FAPESP); National Natural Science
Foundation of China (NSFC), the Chinese Ministry of Education (CMOE) and the
Ministry of Science and Technology of China (MSTC); Ministry of Education and
Youth of the Czech Republic; Danish Natural Science Research Council, the
Carlsberg Foundation and the Danish National Research Foundation; The European
Research Council under the European Community’s Seventh Framework Programme;
Helsinki Institute of Physics and the Academy of Finland; French CNRS-IN2P3,
the ‘Region Pays de Loire’, ‘Region Alsace’, ‘Region Auvergne’ and CEA,
France; German Bundesministerium fur Bildung, Wissenschaft, Forschung und
Technologie (BMBF) and the Helmholtz Association; General Secretariat for
Research and Technology, Ministry of Development, Greece; Hungarian Orszagos
Tudomanyos Kutatasi Alappgrammok (OTKA) and National Office for Research and
Technology (NKTH); Department of Atomic Energy and Department of Science and
Technology of the Government of India; Istituto Nazionale di Fisica Nucleare
(INFN) and Centro Fermi - Museo Storico della Fisica e Centro Studi e Ricerche
”Enrico Fermi”, Italy; MEXT Grant-in-Aid for Specially Promoted Research,
Japan; Joint Institute for Nuclear Research, Dubna; National Research
Foundation of Korea (NRF); Consejo Nacional de Cienca y Tecnologia (CONACYT),
Direccion General de Asuntos del Personal Academico(DGAPA), México, :Amerique
Latine Formation academique – European Commission(ALFA-EC) and the EPLANET
Program (European Particle Physics Latin American Network) Stichting voor
Fundamenteel Onderzoek der Materie (FOM) and the Nederlandse Organisatie voor
Wetenschappelijk Onderzoek (NWO), Netherlands; Research Council of Norway
(NFR); National Science Centre, Poland; Ministry of National
Education/Institute for Atomic Physics and Consiliul Naţional al Cercetării
Ştiinţifice - Executive Agency for Higher Education Research Development and
Innovation Funding (CNCS-UEFISCDI) - Romania; Ministry of Education and
Science of Russian Federation, Russian Academy of Sciences, Russian Federal
Agency of Atomic Energy, Russian Federal Agency for Science and Innovations
and The Russian Foundation for Basic Research; Ministry of Education of
Slovakia; Department of Science and Technology, South Africa; Centro de
Investigaciones Energeticas, Medioambientales y Tecnologicas (CIEMAT),
E-Infrastructure shared between Europe and Latin America (EELA), Ministerio de
Economía y Competitividad (MINECO) of Spain, Xunta de Galicia (Consellería de
Educación), Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN),
Cubaenergía, Cuba, and IAEA (International Atomic Energy Agency); Swedish
Research Council (VR) and Knut $\&$ Alice Wallenberg Foundation (KAW); Ukraine
Ministry of Education and Science; United Kingdom Science and Technology
Facilities Council (STFC); The United States Department of Energy, the United
States National Science Foundation, the State of Texas, and the State of Ohio;
Ministry of Science, Education and Sports of Croatia and Unity through
Knowledge Fund, Croatia. Council of Scientific and Industrial Research (CSIR),
New Delhi, India

## References

  * [1] J. C. Collins et al., “Factorization for short distance hadron-hadron scattering,” Nucl. Phys. B261 (1985) 104.
  * [2] L. D. McLerran, “The Color glass condensate and small x physics: Four lectures,” Lect. Notes Phys. 583 (2002) 291–334, arXiv:hep-ph/0104285 [hep-ph].
  * [3] C. Salgado et al., “Proton-Nucleus Collisions at the LHC: Scientific Opportunities and Requirements,” J. Phys. G39 (2012) 015010, arXiv:1105.3919 [hep-ph].
  * [4] A. Krzywicki, J. Engels, B. Petersson, and U. Sukhatme, “Does a Nucleus Act Like a Gluon Filter?,” Phys. Lett. B85 (1979) 407.
  * [5] A. Accardi, “Final state interactions and hadron quenching in cold nuclear matter,” Phys. Rev. C76 (2007) 034902, arXiv:0706.3227 [nucl-th].
  * [6] ALICE Collaboration, K. Aamodt et al., “Suppression of Charged Particle Production at Large Transverse Momentum in Central Pb–Pb Collisions at $\sqrt{s_{{}_{NN}}}=2.76$ TeV,” Phys. Lett. B696 (2011) 30–39, arXiv:1012.1004 [nucl-ex].
  * [7] ALICE Collaboration, K. Aamodt et al., “Particle-yield modification in jet-like azimuthal di-hadron correlations in Pb-Pb collisions at $\sqrt{s_{NN}}=2.76$ TeV,” Phys. Rev. Lett. 108 (2012) 092301, arXiv:1110.0121 [nucl-ex].
  * [8] CMS Collaboration, S. Chatrchyan et al., “Study of high-$p_{T}$ charged particle suppression in PbPb compared to pp collisions at $\sqrt{s_{NN}}=$2.76 TeV,” Eur. Phys. J. C72 (2012) 1945, arXiv:1202.2554 [nucl-ex].
  * [9] ATLAS Collaboration, G. Aad et al., “Observation of a Centrality-Dependent Dijet Asymmetry in Lead-Lead Collisions at $\sqrt{s_{NN}}$= 2.76 TeV with the ATLAS Detector at the LHC,” Phys. Rev. Lett. 105 (2010) 252303, arXiv:1011.6182 [hep-ex].
  * [10] CMS Collaboration, S. Chatrchyan et al., “Jet momentum dependence of jet quenching in PbPb collisions at $\sqrt{s_{NN}}=2.76$ TeV,” Phys. Lett. B712 (2012) 176–197, arXiv:1202.5022 [nucl-ex].
  * [11] ATLAS Collaboration, G. Aad et al., “Measurement of the jet radius and transverse momentum dependence of inclusive jet suppression in lead-lead collisions at $\sqrt{s_{NN}}=2.76$ TeV with the ATLAS detector,” Phys. Lett. B719 (2013) 220–241, arXiv:1208.1967 [hep-ex].
  * [12] ALICE Collaboration, B. Abelev et al., “Measurement of charged jet suppression in Pb-Pb collisions at $\sqrt{s_{NN}}$=2.76 TeV,” JHEP 1403 (2014) 013, arXiv:1311.0633 [nucl-ex].
  * [13] ATLAS Collaboration, G. Aad et al., “Measurements of the Nuclear Modification Factor for Jets in Pb+Pb Collisions at $\sqrt{s_{\mathrm{NN}}}=2.76$ TeV with the ATLAS Detector,” arXiv:1411.2357 [hep-ex].
  * [14] PHENIX Collaboration, K. Adcox et al., “Suppression of Hadrons with Large Transverse Momentum in Central Au+Au Collisions at $\sqrt{s_{NN}}$ = 130 GeV,” Phys. Rev. Lett. 88 (2002) 022301, arXiv:nucl-ex/0109003.
  * [15] PHENIX Collaboration, S. S. Adler et al., “Suppressed $\pi^{0}$ Production at Large Transverse Momentum in Central Au+Au Collisions at $\sqrt{s_{NN}}=200$ GeV,” Phys. Rev. Lett. 91 (2003) 072301, arXiv:nucl-ex/0304022.
  * [16] STAR Collaboration, J. Adams et al., “Transverse Momentum and Collision Energy Dependence of High $p_{T}$ Hadron Suppression in Au+Au Collisions at Ultrarelativistic Energies,” Phys. Rev. Lett. 91 (2003) 172302, nucl-ex/0305015.
  * [17] STAR Collaboration, J. Adams et al., “Evidence from d+Au measurements for final-state suppression of high $p_{T}$ hadrons in Au+Au collisions at RHIC,” Phys. Rev. Lett. 91 (2003) 072304, arXiv:nucl-ex/0306024.
  * [18] BRAHMS Collaboration, I. Arsene et al., “Transverse momentum spectra in Au+Au and d+Au collisions at $\sqrt{s}=200$ GeV and the pseudorapidity dependence of high $p_{T}$ suppression,” Phys. Rev. Lett. 91 (2003) 072305, arXiv:nucl-ex/0307003 [nucl-ex].
  * [19] PHOBOS Collaboration, B. B. Back et al., “Charged hadron transverse momentum distributions in Au + Au collisions at $\sqrt{s_{NN}}$ = 200 GeV,” Phys. Lett. B578 (2004) 297–303, arXiv:nucl-ex/0302015.
  * [20] M. Gyulassy and M. Plumer, “Jet quenching in dense matter,” Phys. Lett. B243 (1990) 432–438.
  * [21] R. Baier et al., “Induced gluon radiation in a qcd medium,” Phys. Lett. B345 (1995) 277–286, hep-ph/9411409.
  * [22] 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].
  * [23] ALICE Collaboration, B. Abelev et al., “Long-range angular correlations on the near and away side in $p$-Pb collisions at $\sqrt{s_{NN}}=5.02$ TeV,” Phys. Lett. B 719 (2013) 29–41, arXiv:1212.2001 [nucl-ex].
  * [24] ATLAS Collaboration, G. Aad et al., “Measurement with the ATLAS detector of multi-particle azimuthal correlations in p+Pb collisions at $\sqrt{s_{NN}}$ =5.02 TeV,” Phys. Lett. B725 (2013) 60–78, arXiv:1303.2084 [hep-ex].
  * [25] ALICE Collaboration, B. B. Abelev et al., “Long-range angular correlations of pi, K and p in p–Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV,” Phys. Lett. B726 (2013) 164–177, arXiv:1307.3237 [nucl-ex].
  * [26] ALICE Collaboration, B. Abelev et al., “Transverse Momentum Distribution and Nuclear Modification Factor of Charged Particles in $p$-Pb Collisions at $\sqrt{s_{NN}}=5.02$ TeV,” Phys. Rev. Lett. 110 (2013) 082302, arXiv:1210.4520 [nucl-ex].
  * [27] ALICE Collaboration, B. B. Abelev et al., “Transverse momentum dependence of inclusive primary charged-particle production in p-Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV,” Eur. Phys. J. C74 (2014) 3054, arXiv:1405.2737 [nucl-ex].
  * [28] CMS Collaboration, V. Khachatryan et al., “Nuclear effects on the transverse momentum spectra of charged particles in pPb collisions at a nucleon-nucleon center-of-mass energy of 5.02 TeV,” arXiv:1502.05387 [nucl-ex].
  * [29] ATLAS Collaboration, “Charged hadron production in $p$+Pb collisions at $\sqrt{s_{\mathrm{NN}}}=5.02$ TeV measured at high transverse momentum by the ATLAS experiment,”. http://cds.cern.ch/record/1704978.
  * [30] ATLAS Collaboration, G. Aad et al., “Centrality and rapidity dependence of inclusive jet production in $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV proton–lead collisions with the ATLAS detector,” arXiv:1412.4092 [hep-ex].
  * [31] CMS Collaboration, S. Chatrchyan et al., “Studies of dijet transverse momentum balance and pseudorapidity distributions in pPb collisions at $\sqrt{s_{\mathrm{NN}}}=5.02$ TeV,” Eur. Phys. J. C74 no. 7, (2014) 2951, arXiv:1401.4433 [nucl-ex].
  * [32] J. E. Huth et al., “Toward a standardization of jet definitions,”. Presented at Summer Study on High Energy Physics, Research Directions for the Decade, Snowmass, CO, Jun 25 - Jul 13, 1990.
  * [33] M. Cacciari and G. P. Salam, “Dispelling the $N^{3}$ myth for the $k_{t}$ jet-finder,” Phys. Lett. B641 (2006) 57–61, arXiv:hep-ph/0512210.
  * [34] M. Cacciari et al., “Fluctuations and asymmetric jet events in PbPb collisions at the LHC,” Eur. Phys. J. C71 (2011) 1692, arXiv:1101.2878 [hep-ph].
  * [35] ALICE Collaboration, B. Abelev et al., “Measurement of Event Background Fluctuations for Charged Particle Jet Reconstruction in Pb-Pb collisions at $\sqrt{s_{NN}}=2.76$ TeV,” JHEP 1203 (2012) 053, arXiv:1201.2423 [hep-ex].
  * [36] ALICE Collaboration, B. Abelev et al., “Performance of the ALICE Experiment at the CERN LHC,” Int. J. Mod. Phys. A29 no. 24, (2014) 1430044, arXiv:1402.4476 [nucl-ex].
  * [37] ALICE Collaboration, K. Aamodt et al., “Charged-particle multiplicity density at mid-rapidity in central Pb-Pb collisions at $\sqrt{s_{NN}}$ = 2.76 TeV,” Phys. Rev. Lett. 105 no. 25, (December, 2010) 252301, arXiv:1011.3916 [nucl-ex].
  * [38] ALICE Collaboration, J. Adam et al., “Centrality dependence of particle production in p-Pb collisions at $\sqrt{s_{\rm NN}}$= 5.02 TeV,” arXiv:1412.6828 [nucl-ex].
  * [39] ALICE Collaboration, B. B. Abelev et al., “Measurement of visible cross sections in proton-lead collisions at $\sqrt{s_{NN}}$ = 5.02 TeV in van der Meer scans with the ALICE detector,” JINST 9 no. 11, (2014) P11003, arXiv:1405.1849 [nucl-ex].
  * [40] ALICE Collaboration, B. Abelev et al., “Pseudorapidity density of charged particles $p$-Pb collisions at $\sqrt{s_{NN}}=5.02$ TeV,” Phys. Rev. Lett. 110 (2013) 032301, arXiv:1210.3615 [nucl-ex].
  * [41] ALICE Collaboration, K. Aamodt et al., “Alignment of the ALICE Inner Tracking System with cosmic-ray tracks,” JINST 5 (2010) P03003, arXiv:1001.0502 [physics.ins-det].
  * [42] J. Alme et al., “The ALICE TPC, a large 3-dimensional tracking device with fast readout for ultra-high multiplicity events,” Nucl. Instrum. Meth. A622 (2010) 316–367, arXiv:1001.1950 [physics.ins-det].
  * [43] M. Cacciari et al., “The anti-$k_{t}$ jet clustering algorithm,” JHEP 0804 (2008) 063, arXiv:0802.1189 [hep-ph].
  * [44] M. Cacciari, G. P. Salam, and G. Soyez, “The Catchment Area of Jets,” JHEP 04 (2008) 005, arXiv:0802.1188 [hep-ph].
  * [45] CMS Collaboration, S. Chatrchyan et al., “Measurement of the underlying event activity in $pp$ collisions at $\sqrt{s}=0.9$ and 7 TeV with the novel jet-area/median approach,” JHEP 1208 (2012) 130, arXiv:1207.2392 [hep-ex].
  * [46] ALICE Collaboration, B. Abelev et al., “Underlying Event measurements in pp collisions at $\sqrt{s}=0.9$ and 7 TeV with the ALICE experiment at the LHC,” JHEP 1207 (2012) 116, arXiv:1112.2082 [hep-ex].
  * [47] T. Sjöstrand et al., “PYTHIA 6.4 physics and manual,” JHEP 05 (2006) 026, hep-ph/0603175.
  * [48] R. Brun and F. Carminati, “GEANT, Detector Description and Simulation Tool.” CERN Program Library Long Writeup W5013, 1993.
  * [49] A. Hocker and V. Kartvelishvili, “SVD approach to data unfolding,” Nucl. Instrum. Meth. A372 (1996) 469–481, arXiv:hep-ph/9509307 [hep-ph].
  * [50] T. Adye, “Unfolding algorithms and tests using RooUnfold,” arXiv:1105.1160 [physics.data-an].
  * [51] V. Blobel, “An Unfolding method for high-energy physics experiments ,” arXiv:hep-ex/0208022 [hep-ex].
  * [52] G. D’Agostini, “Bayesian Inference in Processing Experimental Data Principles and Basic Applications ,” arXiv:physics/0304102.
  * [53] V. Blobel, 8th CERN School of Computing - CSC ’84, Aiguablava, Spain 9–22 Sep., 1984.
  * [54] ALICE Collaboration, B. Abelev, “Charged jet cross sections and properties in proton-proton collisions at $\sqrt{s}=7$ TeV,” arXiv:1411.4969 [nucl-ex].
  * [55] P. Nason, “A New method for combining NLO QCD with shower Monte Carlo algorithms,” JHEP 0411 (2004) 040, arXiv:hep-ph/0409146 [hep-ph].
  * [56] S. Frixione, P. Nason, and G. Ridolfi, “A Positive-weight next-to-leading-order Monte Carlo for heavy flavour hadroproduction,” JHEP 0709 (2007) 126, arXiv:0707.3088 [hep-ph].
  * [57] T. Sjöstrand, S. Mrenna, and P. Z. Skands, “A Brief Introduction to PYTHIA 8.1,” Comput. Phys. Commun. 178 (2008) 852–867, arXiv:0710.3820 [hep-ph].
  * [58] P. M. Nadolsky, H.-L. Lai, Q.-H. Cao, J. Huston, J. Pumplin, et al., “Implications of CTEQ global analysis for collider observables,” Phys. Rev. D78 (2008) 013004, arXiv:0802.0007 [hep-ph].
  * [59] K. J. Eskola, H. Paukkunen, and C. A. Salgado, “EPS09 - a New Generation of NLO and LO Nuclear Parton Distribution Functions,” JHEP 04 (2009) 065, arXiv:0902.4154 [hep-ph].
  * [60] ALICE Collaboration, B. Abelev et al., “Neutral pion and $\eta$ meson production in proton-proton collisions at $\sqrt{s}=0.9$ TeV and $\sqrt{s}=7$ TeV,” Phys. Lett. B717 (2012) 162–172, arXiv:1205.5724 [hep-ex].
  * [61] ALICE Collaboration, B. B. Abelev et al., “Energy Dependence of the Transverse Momentum Distributions of Charged Particles in pp Collisions Measured by ALICE,” Eur. Phys. J. C73 (2013) 2662, arXiv:1307.1093 [nucl-ex].
  * [62] ALICE Collaboration, B. Abelev et al., “Measurement of the inclusive differential jet cross section in pp collisions at $\sqrt{s}$ = 2.76 TeV,” Phys. Lett. B 722 no. 4-5, (2013) 262–272, arXiv:1301.3475 [nucl-ex].

##  Appendix A The ALICE Collaboration

J. Adamorg39&D. Adamováorg82&M.M. Aggarwalorg86&G. Aglieri Rinellaorg36&M.
Agnelloorg110&N. Agrawalorg47&Z. Ahammedorg130&S.U. Ahnorg67&I.
Aimoorg93,org110&S. Aiolaorg135&M. Ajazorg16&A. Akindinovorg57&S.N.
Alamorg130&D. Aleksandrovorg99&B. Alessandroorg110&D. Alexandreorg101&R.
Alfaro Molinaorg63&A. Aliciorg104,org12&A. Alkinorg3&J. Almeorg37&T.
Altorg42&S. Altinpinarorg18&I. Altsybeevorg129&C. Alves Garcia Pradoorg118&C.
Andreiorg77&A. Andronicorg96&V. Anguelovorg92&J. Anielskiorg53&T.
Antičićorg97&F. Antinoriorg107&P. Antonioliorg104&L. Aphecetcheorg112&H.
Appelshäuserorg52&S. Arcelliorg28&N. Armestoorg17&R. Arnaldiorg110&T.
Aronssonorg135&I.C. Arseneorg22&M. Arslandokorg52&A. Augustinusorg36&R.
Averbeckorg96&M.D. Azmiorg19&M. Bachorg42&A. Badalàorg106&Y.W. Baekorg43&S.
Bagnascoorg110&R. Bailhacheorg52&R. Balaorg89&A. Baldisseriorg15&F. Baltasar
Dos Santos Pedrosaorg36&R.C. Baralorg60&A.M. Barbanoorg110&R. Barberaorg29&F.
Barileorg33&G.G. Barnaföldiorg134&L.S. Barnbyorg101&V. Barretorg69&P.
Bartaliniorg7&J. Bartkeorg115&E. Bartschorg52&M. Basileorg28&N. Bastidorg69&S.
Basuorg130&B. Bathenorg53&G. Batigneorg112&A. Batista Camejoorg69&B.
Batyunyaorg65&P.C. Batzingorg22&I.G. Beardenorg79&H. Beckorg52&C.
Beddaorg110&N.K. Beheraorg48,org47&I. Belikovorg54&F. Belliniorg28&H. Bello
Martinezorg2&R. Bellwiedorg120&R. Belmontorg133&E. Belmont-Morenoorg63&V.
Belyaevorg75&G. Bencediorg134&S. Beoleorg27&I. Berceanuorg77&A.
Bercuciorg77&Y. Berdnikovorg84&D. Berenyiorg134&R.A. Bertensorg56&D.
Berzanoorg36,org27&L. Betevorg36&A. Bhasinorg89&I.R. Bhatorg89&A.K.
Bhatiorg86&B. Bhattacharjeeorg44&J. Bhomorg126&L. Bianchiorg27,org120&N.
Bianchiorg71&C. Bianchinorg133,org56&J. Bielčíkorg39&J. Bielčíkováorg82&A.
Bilandzicorg79&S. Biswasorg78&S. Bjelogrlicorg56&F. Blancoorg10&D.
Blauorg99&C. Blumeorg52&F. Bockorg73,org92&A. Bogdanovorg75&H. Bøggildorg79&L.
Boldizsárorg134&M. Bombaraorg40&J. Bookorg52&H. Borelorg15&A. Borissovorg95&M.
Borriorg81&F. Bossúorg64&M. Botjeorg80&E. Bottaorg27&S. Böttgerorg51&P. Braun-
Munzingerorg96&M. Bregantorg118&T. Breitnerorg51&T.A. Brokerorg52&T.A.
Browningorg94&M. Brozorg39&E.J. Bruckenorg45&E. Brunaorg110&G.E. Brunoorg33&D.
Budnikovorg98&H. Bueschingorg52&S. Bufalinoorg110,org36&P. Buncicorg36&O.
Buschorg92,org126&Z. Butheleziorg64&J.T. Buxtonorg20&D. Caffarriorg36,org30&X.
Caiorg7&H. Cainesorg135&L. Calero Diazorg71&A. Calivaorg56&E. Calvo
Villarorg102&P. Cameriniorg26&F. Carenaorg36&W. Carenaorg36&J. Castillo
Castellanosorg15&A.J. Castroorg123&E.A.R. Casulaorg25&C. Cavicchioliorg36&C.
Ceballos Sanchezorg9&J. Cepilaorg39&P. Cerelloorg110&B. Changorg121&S.
Chapelandorg36&M. Chartierorg122&J.L. Charvetorg15&S. Chattopadhyayorg130&S.
Chattopadhyayorg100&V. Chelnokovorg3&M. Cherneyorg85&C. Cheshkovorg128&B.
Cheynisorg128&V. Chibante Barrosoorg36&D.D. Chinellatoorg119&P.
Chochulaorg36&K. Choiorg95&M. Chojnackiorg79&S. Choudhuryorg130&P.
Christakoglouorg80&C.H. Christensenorg79&P. Christiansenorg34&T.
Chujoorg126&S.U. Chungorg95&Z. Chunhuiorg56&C. Cicaloorg105&L.
Cifarelliorg12,org28&F. Cindoloorg104&J. Cleymansorg88&F. Colamariaorg33&D.
Colellaorg33&A. Colluorg25&M. Colocciorg28&G. Conesa Balbastreorg70&Z. Conesa
del Valleorg50&M.E. Connorsorg135&J.G. Contrerasorg39,org11&T.M.
Cormierorg83&Y. Corrales Moralesorg27&I. Cortés Maldonadoorg2&P.
Corteseorg32&M.R. Cosentinoorg118&F. Costaorg36&P. Crochetorg69&R. Cruz
Albinoorg11&E. Cuautleorg62&L. Cunqueiroorg36&T. Dahmsorg91&A.
Daineseorg107&A. Danuorg61&D. Dasorg100&I. Dasorg100,org50&S. Dasorg4&A.
Dashorg119&S. Dashorg47&S. Deorg118&A. De Caroorg31,org12&G. de
Cataldoorg103&J. de Cuvelandorg42&A. De Falcoorg25&D. De
Gruttolaorg12,org31&N. De Marcoorg110&S. De Pasqualeorg31&A.
Deistingorg96,org92&A. Delofforg76&E. Dénesorg134&G. D’Erasmoorg33&D. Di
Bariorg33&A. Di Mauroorg36&P. Di Nezzaorg71&M.A. Diaz Corcheroorg10&T.
Dietelorg88&P. Dillensegerorg52&R. Diviàorg36&Ø. Djuvslandorg18&A.
Dobrinorg56,org80&T. Dobrowolskiorg760&D. Domenicis Gimenezorg118&B.
Dönigusorg52&O. Dordicorg22&A.K. Dubeyorg130&A. Dublaorg56&L. Ducrouxorg128&P.
Dupieuxorg69&R.J. Ehlersorg135&D. Eliaorg103&H. Engelorg51&B.
Erazmusorg112,org36&F. Erhardtorg127&D. Eschweilerorg42&B. Espagnonorg50&M.
Estienneorg112&S. Esumiorg126&J. Eumorg95&D. Evansorg101&S. Evdokimovorg111&G.
Eyyubovaorg39&L. Fabbiettiorg91&D. Fabrisorg107&J. Faivreorg70&A.
Fantoniorg71&M. Faselorg73&L. Feldkamporg53&D. Feleaorg61&A.
Felicielloorg110&G. Feofilovorg129&J. Ferenceiorg82&A. Fernández
Téllezorg2&E.G. Ferreiroorg17&A. Ferrettiorg27&A. Festantiorg30&J.
Figielorg115&M.A.S. Figueredoorg122&S. Filchaginorg98&D. Finogeevorg55&F.M.
Fiondaorg103&E.M. Fioreorg33&M.G. Fleckorg92&M. Florisorg36&S.
Foertschorg64&P. Fokaorg96&S. Fokinorg99&E. Fragiacomoorg109&A.
Francesconorg36,org30&U. Frankenfeldorg96&U. Fuchsorg36&C. Furgetorg70&A.
Fursorg55&M. Fusco Girardorg31&J.J. Gaardhøjeorg79&M. Gagliardiorg27&A.M.
Gagoorg102&M. Gallioorg27&D.R. Gangadharanorg73&P. Ganotiorg87&C. Gaoorg7&C.
Garabatosorg96&E. Garcia-Solisorg13&C. Gargiuloorg36&P. Gasikorg91&M.
Germainorg112&A. Gheataorg36&M. Gheataorg61,org36&P. Ghoshorg130&S.K.
Ghoshorg4&P. Gianottiorg71&P. Giubellinoorg36&P. Giubilatoorg30&E. Gladysz-
Dziadusorg115&P. Glässelorg92&A. Gomez Ramirezorg51&P. González-Zamoraorg10&S.
Gorbunovorg42&L. Görlichorg115&S. Gotovacorg114&V. Grabskiorg63&L.K.
Graczykowskiorg132&A. Grelliorg56&A. Grigorasorg36&C. Grigorasorg36&V.
Grigorievorg75&A. Grigoryanorg1&S. Grigoryanorg65&B. Grinyovorg3&N.
Grionorg109&J.F. Grosse-Oetringhausorg36&J.-Y. Grossiordorg128&R.
Grossoorg36&F. Guberorg55&R. Guernaneorg70&B. Guerzoniorg28&K.
Gulbrandsenorg79&H. Gulkanyanorg1&T. Gunjiorg125&A. Guptaorg89&R.
Guptaorg89&R. Haakeorg53&Ø. Haalandorg18&C. Hadjidakisorg50&M. Haiducorg61&H.
Hamagakiorg125&G. Hamarorg134&L.D. Hanrattyorg101&A. Hansenorg79&J.W.
Harrisorg135&H. Hartmannorg42&A. Hartonorg13&D. Hatzifotiadouorg104&S.
Hayashiorg125&S.T. Heckelorg52&M. Heideorg53&H. Helstruporg37&A.
Herghelegiuorg77&G. Herrera Corralorg11&B.A. Hessorg35&K.F. Hetlandorg37&T.E.
Hildenorg45&H. Hillemannsorg36&B. Hippolyteorg54&P. Hristovorg36&M.
Huangorg18&T.J. Humanicorg20&N. Hussainorg44&T. Hussainorg19&D.
Hutterorg42&D.S. Hwangorg21&R. Ilkaevorg98&I. Ilkivorg76&M. Inabaorg126&C.
Ionitaorg36&M. Ippolitovorg75,org99&M. Irfanorg19&M. Ivanovorg96&V.
Ivanovorg84&V. Izucheevorg111&P.M. Jacobsorg73&C. Jahnkeorg118&H.J.
Jangorg67&M.A. Janikorg132&P.H.S.Y. Jayarathnaorg120&C. Jenaorg30&S.
Jenaorg120&R.T. Jimenez Bustamanteorg62&P.G. Jonesorg101&H. Jungorg43&A.
Juskoorg101&P. Kalinakorg58&A. Kalweitorg36&J. Kaminorg52&J.H. Kangorg136&V.
Kaplinorg75&S. Karorg130&A. Karasu Uysalorg68&O. Karavichevorg55&T.
Karavichevaorg55&E. Karpechevorg55&U. Kebschullorg51&R. Keidelorg137&D.L.D.
Keijdenerorg56&M. Keilorg36&K.H. Khanorg16&M.M. Khanorg19&P. Khanorg100&S.A.
Khanorg130&A. Khanzadeevorg84&Y. Kharlovorg111&B. Kilengorg37&B.
Kimorg136&D.W. Kimorg43,org67&D.J. Kimorg121&H. Kimorg136&J.S. Kimorg43&M.
Kimorg43&M. Kimorg136&S. Kimorg21&T. Kimorg136&S. Kirschorg42&I. Kiselorg42&S.
Kiselevorg57&A. Kisielorg132&G. Kissorg134&J.L. Klayorg6&C. Kleinorg52&J.
Kleinorg92&C. Klein-Bösingorg53&A. Klugeorg36&M.L. Knichelorg92&A.G.
Knospeorg116&T. Kobayashiorg126&C. Kobdajorg113&M. Kofaragoorg36&M.K.
Köhlerorg96&T. Kolleggerorg42,org96&A. Kolojvariorg129&V. Kondratievorg129&N.
Kondratyevaorg75&E. Kondratyukorg111&A. Konevskikhorg55&C.
Kouzinopoulosorg36&O. Kovalenkoorg76&V. Kovalenkoorg129&M.
Kowalskiorg36,org115&S. Koxorg70&G. Koyithatta Meethaleveeduorg47&J.
Kralorg121&I. Králikorg58&A. Kravčákováorg40&M. Krelinaorg39&M. Kretzorg42&M.
Krivdaorg101,org58&F. Krizekorg82&E. Kryshenorg36&M. Krzewickiorg96,org42&A.M.
Kuberaorg20&V. Kučeraorg82&T. Kugathasanorg36&C. Kuhnorg54&P.G. Kuijerorg80&I.
Kulakovorg42&J. Kumarorg47&L. Kumarorg78,org86&P. Kurashviliorg76&A.
Kurepinorg55&A.B. Kurepinorg55&A. Kuryakinorg98&S. Kushpilorg82&M.J.
Kweonorg49&Y. Kwonorg136&S.L. La Pointeorg110&P. La Roccaorg29&C. Lagana
Fernandesorg118&I. Lakomovorg36,org50&R. Langoyorg41&C. Laraorg51&A.
Lardeuxorg15&A. Lattucaorg27&E. Laudiorg36&R. Leaorg26&L. Leardiniorg92&G.R.
Leeorg101&S. Leeorg136&I. Legrandorg36&R.C. Lemmonorg81&V. Lentiorg103&E.
Leograndeorg56&I. León Monzónorg117&M. Leoncinoorg27&P. Lévaiorg134&S.
Liorg7,org69&X. Liorg14&J. Lienorg41&R. Lietavaorg101&S. Lindalorg22&V.
Lindenstruthorg42&C. Lippmannorg96&M.A. Lisaorg20&H.M. Ljunggrenorg34&D.F.
Lodatoorg56&P.I. Loenneorg18&V.R. Logginsorg133&V. Loginovorg75&C.
Loizidesorg73&X. Lopezorg69&E. López Torresorg9&A. Loweorg134&P.
Luettigorg52&M. Lunardonorg30&G. Luparelloorg26,org56&P.H.F.N.D. Luzorg118&A.
Maevskayaorg55&M. Magerorg36&S. Mahajanorg89&S.M. Mahmoodorg22&A.
Maireorg54&R.D. Majkaorg135&M. Malaevorg84&I. Maldonado Cervantesorg62&L.
Malininaorg65&D. Mal’Kevichorg57&P. Malzacherorg96&A. Mamonovorg98&L.
Manceauorg110&V. Mankoorg99&F. Mansoorg69&V. Manzariorg103,org36&M.
Marchisoneorg27&J. Marešorg59&G.V. Margagliottiorg26&A. Margottiorg104&J.
Marguttiorg56&A. Marínorg96&C. Markertorg116&M. Marquardorg52&N.A.
Martinorg96&J. Martin Blancoorg112&P. Martinengoorg36&M.I. Martínezorg2&G.
Martínez Garcíaorg112&M. Martinez Pedreiraorg36&Y. Martynovorg3&A.
Masorg118&S. Masciocchiorg96&M. Maseraorg27&A. Masoniorg105&L.
Massacrierorg112&A. Mastroserioorg33&H. Masuiorg126&A. Matyjaorg115&C.
Mayerorg115&J. Mazerorg123&M.A. Mazzoniorg108&D. Mcdonaldorg120&F.
Meddiorg24&A. Menchaca-Rochaorg63&E. Meninnoorg31&J. Mercado Pérezorg92&M.
Meresorg38&Y. Miakeorg126&M.M. Mieskolainenorg45&K. Mikhaylovorg57,org65&L.
Milanoorg36&J. Milosevicorg22,org131&L.M. Minerviniorg103,org23&A.
Mischkeorg56&A.N. Mishraorg48&D. Miśkowiecorg96&J. Mitraorg130&C.M.
Mituorg61&N. Mohammadiorg56&B. Mohantyorg130,org78&L. Molnarorg54&L. Montaño
Zetinaorg11&E. Montesorg10&M. Morandoorg30&D.A. Moreira De Godoyorg112&S.
Morettoorg30&A. Morrealeorg112&A. Morschorg36&V. Mucciforaorg71&E.
Mudnicorg114&D. Mühlheimorg53&S. Muhuriorg130&M. Mukherjeeorg130&H.
Müllerorg36&J.D. Mulliganorg135&M.G. Munhozorg118&S. Murrayorg64&L.
Musaorg36&J. Musinskyorg58&B.K. Nandiorg47&R. Naniaorg104&E. Nappiorg103&M.U.
Naruorg16&C. Nattrassorg123&K. Nayakorg78&T.K. Nayakorg130&S.
Nazarenkoorg98&A. Nedosekinorg57&L. Nellenorg62&F. Ngorg120&M.
Nicassioorg96&M. Niculescuorg61,org36&J. Niedzielaorg36&B.S. Nielsenorg79&S.
Nikolaevorg99&S. Nikulinorg99&V. Nikulinorg84&F. Noferiniorg104,org12&P.
Nomokonovorg65&G. Noorenorg56&J. Normanorg122&A. Nyaninorg99&J.
Nystrandorg18&H. Oeschlerorg92&S. Ohorg135&S.K. Ohorg66&A. Ohlsonorg36&A.
Okatanorg68&T. Okuboorg46&L. Olahorg134&J. Oleniaczorg132&A.C. Oliveira Da
Silvaorg118&M.H. Oliverorg135&J. Onderwaaterorg96&C. Oppedisanoorg110&A. Ortiz
Velasquezorg62&A. Oskarssonorg34&J. Otwinowskiorg96,org115&K. Oyamaorg92&M.
Ozdemirorg52&Y. Pachmayerorg92&P. Paganoorg31&G. Paićorg62&C.
Pajaresorg17&S.K. Palorg130&J. Panorg133&A.K. Pandeyorg47&D. Pantorg47&V.
Papikyanorg1&G.S. Pappalardoorg106&P. Pareekorg48&W.J. Parkorg96&S.
Parmarorg86&A. Passfeldorg53&V. Paticchioorg103&B. Paulorg100&T.
Peitzmannorg56&H. Pereira Da Costaorg15&E. Pereira De Oliveira Filhoorg118&D.
Peresunkoorg75,org99&C.E. Pérez Laraorg80&V. Peskovorg52&Y. Pestovorg5&V.
Petráčekorg39&V. Petrovorg111&M. Petroviciorg77&C. Pettaorg29&S.
Pianoorg109&M. Piknaorg38&P. Pillotorg112&O. Pinazzaorg104,org36&L.
Pinskyorg120&D.B. Piyarathnaorg120&M. Płoskońorg73&M. Planinicorg127&J.
Plutaorg132&S. Pochybovaorg134&P.L.M. Podesta-Lermaorg117&M.G.
Poghosyanorg85&B. Polichtchoukorg111&N. Poljakorg127&W. Poonsawatorg113&A.
Poporg77&S. Porteboeuf-Houssaisorg69&J. Porterorg73&J. Pospisilorg82&S.K.
Prasadorg4&R. Preghenellaorg36,org104&F. Prinoorg110&C.A. Pruneauorg133&I.
Pshenichnovorg55&M. Puccioorg110&G. Pudduorg25&P. Pujahariorg133&V.
Puninorg98&J. Putschkeorg133&H. Qvigstadorg22&A. Rachevskiorg109&S.
Rahaorg4&S. Rajputorg89&J. Rakorg121&A. Rakotozafindrabeorg15&L.
Ramelloorg32&R. Raniwalaorg90&S. Raniwalaorg90&S.S. Räsänenorg45&B.T.
Rascanuorg52&D. Ratheeorg86&K.F. Readorg123&J.S. Realorg70&K.
Redlichorg76&R.J. Reedorg133&A. Rehmanorg18&P. Reicheltorg52&M.
Reicherorg56&F. Reidtorg92,org36&X. Renorg7&R. Renfordtorg52&A.R.
Reolonorg71&A. Reshetinorg55&F. Rettigorg42&J.-P. Revolorg12&K.
Reygersorg92&V. Riabovorg84&R.A. Ricciorg72&T. Richertorg34&M. Richterorg22&P.
Riedlerorg36&W. Rieglerorg36&F. Riggiorg29&C. Risteaorg61&A. Rivettiorg110&E.
Roccoorg56&M. Rodríguez Cahuantziorg11,org2&A. Rodriguez Mansoorg80&K.
Røedorg22&E. Rogochayaorg65&D. Rohrorg42&D. Röhrichorg18&R. Romitaorg122&F.
Ronchettiorg71&L. Ronfletteorg112&P. Rosnetorg69&A. Rossiorg36&F.
Roukoutakisorg87&A. Royorg48&C. Royorg54&P. Royorg100&A.J. Rubio
Monteroorg10&R. Ruiorg26&R. Russoorg27&E. Ryabinkinorg99&Y. Ryabovorg84&A.
Rybickiorg115&S. Sadovskyorg111&K. Šafaříkorg36&B. Sahlmullerorg52&P.
Sahooorg48&R. Sahooorg48&S. Sahooorg60&P.K. Sahuorg60&J. Sainiorg130&S.
Sakaiorg71&M.A. Salehorg133&C.A. Salgadoorg17&J. Salzwedelorg20&S.
Sambyalorg89&V. Samsonovorg84&X. Sanchez Castroorg54&L. Šándororg58&A.
Sandovalorg63&M. Sanoorg126&G. Santagatiorg29&D. Sarkarorg130&E.
Scapparoneorg104&F. Scarlassaraorg30&R.P. Scharenbergorg94&C. Schiauaorg77&R.
Schickerorg92&C. Schmidtorg96&H.R. Schmidtorg35&S. Schuchmannorg52&J.
Schukraftorg36&M. Schulcorg39&T. Schusterorg135&Y. Schutzorg112,org36&K.
Schwarzorg96&K. Schwedaorg96&G. Scioliorg28&E. Scomparinorg110&R.
Scottorg123&K.S. Seederorg118&J.E. Segerorg85&Y. Sekiguchiorg125&I.
Selyuzhenkovorg96&K. Senosiorg64&J. Seoorg66,org95&E. Serradillaorg10,org63&A.
Sevcencoorg61&A. Shabanovorg55&A. Shabetaiorg112&O. Shaduraorg3&R.
Shahoyanorg36&A. Shangaraevorg111&A. Sharmaorg89&N. Sharmaorg60,org123&K.
Shigakiorg46&K. Shtejerorg9,org27&Y. Sibiriakorg99&S. Siddhantaorg105&K.M.
Sielewiczorg36&T. Siemiarczukorg76&D. Silvermyrorg83,org34&C.
Silvestreorg70&G. Simatovicorg127&G. Simonettiorg36&R. Singarajuorg130&R.
Singhorg78&S. Singhaorg78,org130&V. Singhalorg130&B.C. Sinhaorg130&T.
Sinhaorg100&B. Sitarorg38&M. Sittaorg32&T.B. Skaaliorg22&M. Slupeckiorg121&N.
Smirnovorg135&R.J.M. Snellingsorg56&T.W. Snellmanorg121&C. Søgaardorg34&R.
Soltzorg74&J. Songorg95&M. Songorg136&Z. Songorg7&F. Soramelorg30&S.
Sorensenorg123&M. Spacekorg39&E. Spiritiorg71&I. Sputowskaorg115&M.
Spyropoulou-Stassinakiorg87&B.K. Srivastavaorg94&J. Stachelorg92&I.
Stanorg61&G. Stefanekorg76&M. Steinpreisorg20&E. Stenlundorg34&G.
Steynorg64&J.H. Stillerorg92&D. Stoccoorg112&P. Strmenorg38&A.A.P.
Suaideorg118&T. Sugitateorg46&C. Suireorg50&M. Suleymanovorg16&R.
Sultanovorg57&M. Šumberaorg82&T.J.M. Symonsorg73&A. Szaboorg38&A. Szanto de
Toledoorg118&I. Szarkaorg38&A. Szczepankiewiczorg36&M. Szymanskiorg132&J.
Takahashiorg119&N. Tanakaorg126&M.A. Tangaroorg33&J.D. Tapia
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Tarzilaorg77&A. Tauroorg36&G. Tejeda Muñozorg2&A. Telescaorg36&K.
Terasakiorg125&C. Terrevoliorg30,org25&B. Teyssierorg128&J.
Thäderorg96,org73&D. Thomasorg116&R. Tieulentorg128&A.R. Timminsorg120&A.
Toiaorg52&S. Trogoloorg110&V. Trubnikovorg3&W.H. Trzaskaorg121&T.
Tsujiorg125&A. Tumkinorg98&R. Turrisiorg107&T.S. Tveterorg22&K.
Ullalandorg18&A. Urasorg128&G.L. Usaiorg25&A. Utrobicicorg127&M.
Vajzerorg82&M. Valaorg58&L. Valencia Palomoorg69&S. Valleroorg27&J. Van Der
Maarelorg56&J.W. Van Hoorneorg36&M. van Leeuwenorg56&T. Vanatorg82&P. Vande
Vyvreorg36&D. Vargaorg134&A. Vargasorg2&M. Vargyasorg121&R. Varmaorg47&M.
Vasileiouorg87&A. Vasilievorg99&A. Vauthierorg70&V. Vecherninorg129&A.M.
Veenorg56&M. Veldhoenorg56&A. Velureorg18&M. Venaruzzoorg72&E.
Vercellinorg27&S. Vergara Limónorg2&R. Vernetorg8&M. Verweijorg133&L.
Vickovicorg114&G. Viestiorg300&J. Viinikainenorg121&Z. Vilakaziorg124&O.
Villalobos Baillieorg101&A. Vinogradovorg99&L. Vinogradovorg129&Y.
Vinogradovorg98&T. Virgiliorg31&V. Vislaviciusorg34&Y.P. Viyogiorg130&A.
Vodopyanovorg65&M.A. Völklorg92&K. Voloshinorg57&S.A. Voloshinorg133&G.
Volpeorg36,org134&B. von Hallerorg36&I. Vorobyevorg91&D. Vranicorg96,org36&J.
Vrlákováorg40&B. Vulpescuorg69&A. Vyushinorg98&B. Wagnerorg18&J.
Wagnerorg96&H. Wangorg56&M. Wangorg7,org112&Y. Wangorg92&D. Watanabeorg126&M.
Weberorg36&S.G. Weberorg96&J.P. Wesselsorg53&U. Westerhofforg53&J.
Wiechulaorg35&J. Wikneorg22&M. Wildeorg53&G. Wilkorg76&J.
Wilkinsonorg92&M.C.S. Williamsorg104&B. Windelbandorg92&M. Winnorg92&C.G.
Yaldoorg133&Y. Yamaguchiorg125&H. Yangorg56&P. Yangorg7&S. Yanoorg46&Z.
Yinorg7&H. Yokoyamaorg126&I.-K. Yooorg95&V. Yurchenkoorg3&I. Yushmanovorg99&A.
Zaborowskaorg132&V. Zaccoloorg79&A. Zamanorg16&C. Zampolliorg104&H.J.C.
Zanoliorg118&S. Zaporozhetsorg65&A. Zarochentsevorg129&P. Závadaorg59&N.
Zaviyalovorg98&H. Zbroszczykorg132&I.S. Zguraorg61&M. Zhalovorg84&H.
Zhangorg7&X. Zhangorg73&Y. Zhangorg7&C. Zhaoorg22&N. Zhigarevaorg57&D.
Zhouorg7&Y. Zhouorg56&Z. Zhouorg18&H. Zhuorg7&J. Zhuorg7,org112&X. Zhuorg7&A.
Zichichiorg12,org28&A. Zimmermannorg92&M.B. Zimmermannorg53,org36&G.
Zinovjevorg3&M. Zyzakorg42

## Affiliation notes

0Deceased

idp5842272Also at: University of Kansas, Lawrence, Kansas, United States

## Collaboration Institutes

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

org2Benemérita Universidad Autónoma de Puebla, Puebla, Mexico

org3Bogolyubov Institute for Theoretical Physics, Kiev, Ukraine

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

org5Budker Institute for Nuclear Physics, Novosibirsk, Russia

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

org7Central China Normal University, Wuhan, China

org8Centre de Calcul de l’IN2P3, Villeurbanne, France

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

org10Centro de Investigaciones Energéticas Medioambientales y Tecnológicas
(CIEMAT), Madrid, Spain

org11Centro de Investigación y de Estudios Avanzados (CINVESTAV), Mexico City
and Mérida, Mexico

org12Centro Fermi - Museo Storico della Fisica e Centro Studi e Ricerche
“Enrico Fermi”, Rome, Italy

org13Chicago State University, Chicago, Illinois, USA

org14China Institute of Atomic Energy, Beijing, China

org15Commissariat à l’Energie Atomique, IRFU, Saclay, France

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

org17Departamento de Física de Partículas and IGFAE, Universidad de Santiago
de Compostela, Santiago de Compostela, Spain

org18Department of Physics and Technology, University of Bergen, Bergen,
Norway

org19Department of Physics, Aligarh Muslim University, Aligarh, India

org20Department of Physics, Ohio State University, Columbus, Ohio, United
States

org21Department of Physics, Sejong University, Seoul, South Korea

org22Department of Physics, University of Oslo, Oslo, Norway

org23Dipartimento di Elettrotecnica ed Elettronica del Politecnico, Bari,
Italy

org24Dipartimento di Fisica dell’Università ’La Sapienza’ and Sezione INFN
Rome, Italy

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

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

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

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

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

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

org31Dipartimento di Fisica ‘E.R. Caianiello’ dell’Università and Gruppo
Collegato INFN, Salerno, Italy

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

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

org34Division of Experimental High Energy Physics, University of Lund, Lund,
Sweden

org35Eberhard Karls Universität Tübingen, Tübingen, Germany

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

org37Faculty of Engineering, Bergen University College, Bergen, Norway

org38Faculty of Mathematics, Physics and Informatics, Comenius University,
Bratislava, Slovakia

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

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

org41Faculty of Technology, Buskerud and Vestfold University College,
Vestfold, Norway

org42Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe-
Universität Frankfurt, Frankfurt, Germany

org43Gangneung-Wonju National University, Gangneung, South Korea

org44Gauhati University, Department of Physics, Guwahati, India

org45Helsinki Institute of Physics (HIP), Helsinki, Finland

org46Hiroshima University, Hiroshima, Japan

org47Indian Institute of Technology Bombay (IIT), Mumbai, India

org48Indian Institute of Technology Indore, Indore (IITI), India

org49Inha University, Incheon, South Korea

org50Institut de Physique Nucléaire d’Orsay (IPNO), Université Paris-Sud,
CNRS-IN2P3, Orsay, France

org51Institut für Informatik, Johann Wolfgang Goethe-Universität Frankfurt,
Frankfurt, Germany

org52Institut für Kernphysik, Johann Wolfgang Goethe-Universität Frankfurt,
Frankfurt, Germany

org53Institut für Kernphysik, Westfälische Wilhelms-Universität Münster,
Münster, Germany

org54Institut Pluridisciplinaire Hubert Curien (IPHC), Université de
Strasbourg, CNRS-IN2P3, Strasbourg, France

org55Institute for Nuclear Research, Academy of Sciences, Moscow, Russia

org56Institute for Subatomic Physics of Utrecht University, Utrecht,
Netherlands

org57Institute for Theoretical and Experimental Physics, Moscow, Russia

org58Institute of Experimental Physics, Slovak Academy of Sciences, Košice,
Slovakia

org59Institute of Physics, Academy of Sciences of the Czech Republic, Prague,
Czech Republic

org60Institute of Physics, Bhubaneswar, India

org61Institute of Space Science (ISS), Bucharest, Romania

org62Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México,
Mexico City, Mexico

org63Instituto de Física, Universidad Nacional Autónoma de México, Mexico
City, Mexico

org64iThemba LABS, National Research Foundation, Somerset West, South Africa

org65Joint Institute for Nuclear Research (JINR), Dubna, Russia

org66Konkuk University, Seoul, South Korea

org67Korea Institute of Science and Technology Information, Daejeon, South
Korea

org68KTO Karatay University, Konya, Turkey

org69Laboratoire de Physique Corpusculaire (LPC), Clermont Université,
Université Blaise Pascal, CNRS–IN2P3, Clermont-Ferrand, France

org70Laboratoire de Physique Subatomique et de Cosmologie, Université
Grenoble-Alpes, CNRS-IN2P3, Grenoble, France

org71Laboratori Nazionali di Frascati, INFN, Frascati, Italy

org72Laboratori Nazionali di Legnaro, INFN, Legnaro, Italy

org73Lawrence Berkeley National Laboratory, Berkeley, California, United
States

org74Lawrence Livermore National Laboratory, Livermore, California, United
States

org75Moscow Engineering Physics Institute, Moscow, Russia

org76National Centre for Nuclear Studies, Warsaw, Poland

org77National Institute for Physics and Nuclear Engineering, Bucharest,
Romania

org78National Institute of Science Education and Research, Bhubaneswar, India

org79Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark

org80Nikhef, National Institute for Subatomic Physics, Amsterdam, Netherlands

org81Nuclear Physics Group, STFC Daresbury Laboratory, Daresbury, United
Kingdom

org82Nuclear Physics Institute, Academy of Sciences of the Czech Republic, Řež
u Prahy, Czech Republic

org83Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States

org84Petersburg Nuclear Physics Institute, Gatchina, Russia

org85Physics Department, Creighton University, Omaha, Nebraska, United States

org86Physics Department, Panjab University, Chandigarh, India

org87Physics Department, University of Athens, Athens, Greece

org88Physics Department, University of Cape Town, Cape Town, South Africa

org89Physics Department, University of Jammu, Jammu, India

org90Physics Department, University of Rajasthan, Jaipur, India

org91Physik Department, Technische Universität München, Munich, Germany

org92Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg,
Heidelberg, Germany

org93Politecnico di Torino, Turin, Italy

org94Purdue University, West Lafayette, Indiana, United States

org95Pusan National University, Pusan, South Korea

org96Research Division and ExtreMe Matter Institute EMMI, GSI Helmholtzzentrum
für Schwerionenforschung, Darmstadt, Germany

org97Rudjer Bošković Institute, Zagreb, Croatia

org98Russian Federal Nuclear Center (VNIIEF), Sarov, Russia

org99Russian Research Centre Kurchatov Institute, Moscow, Russia

org100Saha Institute of Nuclear Physics, Kolkata, India

org101School of Physics and Astronomy, University of Birmingham, Birmingham,
United Kingdom

org102Sección Física, Departamento de Ciencias, Pontificia Universidad
Católica del Perú, Lima, Peru

org103Sezione INFN, Bari, Italy

org104Sezione INFN, Bologna, Italy

org105Sezione INFN, Cagliari, Italy

org106Sezione INFN, Catania, Italy

org107Sezione INFN, Padova, Italy

org108Sezione INFN, Rome, Italy

org109Sezione INFN, Trieste, Italy

org110Sezione INFN, Turin, Italy

org111SSC IHEP of NRC Kurchatov institute, Protvino, Russia

org112SUBATECH, Ecole des Mines de Nantes, Université de Nantes, CNRS-IN2P3,
Nantes, France

org113Suranaree University of Technology, Nakhon Ratchasima, Thailand

org114Technical University of Split FESB, Split, Croatia

org115The Henryk Niewodniczanski Institute of Nuclear Physics, Polish Academy
of Sciences, Cracow, Poland

org116The University of Texas at Austin, Physics Department, Austin, Texas,
USA

org117Universidad Autónoma de Sinaloa, Culiacán, Mexico

org118Universidade de São Paulo (USP), São Paulo, Brazil

org119Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil

org120University of Houston, Houston, Texas, United States

org121University of Jyväskylä, Jyväskylä, Finland

org122University of Liverpool, Liverpool, United Kingdom

org123University of Tennessee, Knoxville, Tennessee, United States

org124University of the Witwatersrand, Johannesburg, South Africa

org125University of Tokyo, Tokyo, Japan

org126University of Tsukuba, Tsukuba, Japan

org127University of Zagreb, Zagreb, Croatia

org128Université de Lyon, Université Lyon 1, CNRS/IN2P3, IPN-Lyon,
Villeurbanne, France

org129V. Fock Institute for Physics, St. Petersburg State University, St.
Petersburg, Russia

org130Variable Energy Cyclotron Centre, Kolkata, India

org131Vinča Institute of Nuclear Sciences, Belgrade, Serbia

org132Warsaw University of Technology, Warsaw, Poland

org133Wayne State University, Detroit, Michigan, United States

org134Wigner Research Centre for Physics, Hungarian Academy of Sciences,
Budapest, Hungary

org135Yale University, New Haven, Connecticut, United States

org136Yonsei University, Seoul, South Korea

org137Zentrum für Technologietransfer und Telekommunikation (ZTT),
Fachhochschule Worms, Worms, Germany