2019 200 18 September

Measurements of jet spectra in pp and Pb–Pb collisions at
$\sqrt{s_{\mathrm{NN}}}=5.02$ TeV

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

This article reports measurements of the $p_{\mathrm{T}}$-differential
inclusive jet cross-section in pp collisions at $\sqrt{s}=5.02$ TeV and the
$p_{\mathrm{T}}$-differential inclusive jet yield in Pb–Pb 0–10% central
collisions at $\sqrt{s_{\mathrm{NN}}}=5.02$ TeV. Jets were reconstructed at
mid-rapidity with the ALICE tracking detectors and electromagnetic calorimeter
using the anti-$k_{\mathrm{T}}$ algorithm. For pp collisions, we report jet
cross-sections for jet resolution parameters $R=0.1-0.6$ over the range
$20<p_{\mathrm{T,jet}}<140$ $\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$, as
well as the jet cross-section ratios of different $R$, and comparisons to two
next-to-leading-order (NLO)-based theoretical predictions. For Pb–Pb
collisions, we report the $R=0.2$ and $R=0.4$ jet spectra for
$40<p_{\mathrm{T,jet}}<140$ $\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ and
$60<p_{\mathrm{T,jet}}<140$ $\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$,
respectively. The scaled ratio of jet yields observed in Pb–Pb to pp
collisions, $R_{\mathrm{AA}}$, is constructed, and exhibits strong jet
quenching and a clear $p_{\mathrm{T}}$-dependence for $R=0.2$. No significant
$R$-dependence of the jet $R_{\mathrm{AA}}$ is observed within the
uncertainties of the measurement. These results are compared to several
theoretical predictions.

##  1 Introduction

A deconfined state of strongly interacting matter described by Quantum
Chromodynamics (QCD) is produced in ultra-relativistic heavy-ion collisions at
the Relativistic Heavy Ion Collider (RHIC) and the Large Hadron Collider (LHC)
[1, 2, 3, 4, 5, 6, 7, 8]. Numerous observables including high-$p_{\mathrm{T}}$
hadron suppression, anisotropic flow, and $J/\psi$ suppression and
recombination provide evidence that the hot QCD state produced in these
collisions consists of sub-nucleonic degrees of freedom.

One of the major strategies to investigate this hot QCD state is the study of
jet modification in heavy-ion collisions. Partons often traverse a significant
pathlength of the hot QCD medium, and the effect that the medium has on the
resulting jets can be deduced by comparing jet properties in heavy-ion
collisions to those in pp collisions. Since the jet production cross-section
can be computed in perturbative QCD, and since jets are sensitive to a wide
range of momentum exchanges with the medium, jet physics is an appealing tool
to investigate the medium at a wide range of resolution scales.

Previous measurements demonstrate suppression of the jet transverse momentum
($p_{\mathrm{T}}$) spectrum in heavy-ion collisions relative to pp collisions
scaled by the number of incoherent binary nucleon-nucleon collisions,
indicating that jets transfer energy to the hot QCD medium [9, 10, 11, 12, 13,
14, 15]. Furthermore, jet substructure measurements indicate that in heavy-ion
collisions, the jet core is more collimated and fragments harder [16], while
at wide angles from the jet axis there is an excess of soft particles [17,
18]. Jet modification in heavy-ion collisions is described by several
different theoretical approaches typically based on energy loss via medium-
induced gluon radiation and elastic scattering [19, 20, 21, 22, and references
therein]; however, there remains no clear consensus of the precise nature of
the interaction of jets with the medium. New measurements of the absolute
level of jet suppression and its $p_{\mathrm{T}}$-dependence will directly
test models, and serve as a key constraint for global analyses of
high-$p_{\mathrm{T}}$ observables. Additionally, the evolution of jet
suppression with the jet resolution parameter, $R$, can constrain competing
effects between the recovery of out-of-cone radiation and the changing
selection of the jet population (such as reduction of the quark/gluon
fraction) as $R$ increases [23, 24, 25].

The inclusive jet cross-section in pp collisions contains important QCD
physics itself. In recent years, the inclusive jet cross-section in pp
collisions was computed at NLO with resummation of logarithms of the jet
resolution parameter [26, 27, 28, 29] and threshold logarithms [30, 31], and
also to NNLO in the leading color approximation [32]. Measurements of the
inclusive pp jet cross-section have been made at the SPS [33, 34], the
Tevatron [35, 36], RHIC [37], and the LHC [38, 39, 40, 41, 42, 43, 44, 45,
46], and the latest comparisons of these measurements with theoretical
predictions demonstrate the importance of contributions beyond NLO fixed-order
calculations, namely resummations or matched parton showers. However, the
precise contributions of the perturbative aspect of the jet, as well as the
hadronization and underlying event (UE) effects, remain under investigation.
Inclusive jet measurements at low-$p_{\mathrm{T}}$ as a function of $R$
(including ratios of jet cross sections, which allow partial cancellation of
experimental and theoretical uncertainties) will help clarify these
contributions, and provide tests for both the perturbative and non-
perturbative contributions to the inclusive jet cross-section. Moreover, these
measurements can be used to constrain parton distribution functions (PDFs) and
the strong coupling constant $\alpha_{\mathrm{s}}$ [47, 48, 49, 42, 44].

This article reports measurements of inclusive jet $p_{\mathrm{T}}$ spectra in
pp and central Pb–Pb collisions at $\sqrt{s_{\mathrm{NN}}}=5.02$ TeV with the
ALICE detector. Jets were reconstructed in the pseudo-rapidity range
$|\eta_{\mathrm{jet}}|<0.7-R$ for jet resolution parameters $R=0.1-0.6$ in pp
collisions and $R=0.2$ and $R=0.4$ in Pb–Pb collisions. In Pb–Pb collisions,
we required jets to contain at least one charged track with
$p_{\mathrm{T}}>5-7$ GeV$/c$ (depending on the jet $R$) in order to identify
hard jet candidates (arising from large momentum-transfer scatterings) in the
large background from combinatorial jets. In pp collisions, we report the
cross-section both with and without this bias. The relative jet yields
observed in Pb–Pb and pp collisions are reported using their scaled ratio,
$R_{\mathrm{AA}}$, and compared to several theoretical predictions.

##  2 Experimental Setup and Datasets

The ALICE detector [50, 51] is a dedicated heavy-ion experiment located at the
Large Hadron Collider [52]. The analysis relied on the central tracking system
and the electromagnetic calorimeter (EMCal), as well as detectors for event
triggering and centrality determination. The tracking system consists of a
six-layer silicon inner tracking system (ITS) with radial distance 3.9 – 43 cm
from the beamline, and a gas time projection chamber (TPC) with radial
distance 85 – 247 cm from the beamline. The combined tracking system spans
$\left|\eta\right|<0.9$ and full azimuth, and tracks were measured in the
range
$150\;\mathrm{MeV}\kern-0.50003pt/\kern-0.20004ptc<p_{\mathrm{T,track}}<100\;\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$.
The EMCal consists of a Pb-scintillator sampling calorimeter spanning
$\left|\eta\right|<0.7$ and $80^{\circ}<\varphi<188.1^{\circ}$ in azimuth,
located a radial distance 4.36 m from the beamline [53]. The EMCal contains
12,288 cells organized in an approximately projective geometry relative to the
interaction point. The EMCal has a Moliere radius of $r_{\mathrm{M}}=3.2$ cm,
and its cells have a transverse size of approximately $6.0$ cm$\times 6.0$ cm
($\Delta\eta\times\Delta\varphi\approx 0.014\times 0.014$). Each cell has a
depth of 24.6 cm, corresponding to approximately 20 electromagnetic radiation
lengths and one hadronic interaction length.

The reported Pb–Pb (pp) data were recorded in 2015 (2017) at
$\sqrt{s_{\mathrm{NN}}}=5.02$ TeV. The events were collected using a minimum
bias (MB) trigger requiring a coincidence hit in both of the V0 scintillators,
located at $2.8<\eta<5.1$ (V0-A) and $-3.7<\eta<-1.7$ (V0-C) [54]. An accepted
event was required to have a primary vertex successfully reconstructed within
$-10\;\mathrm{cm}<z<10\;\mathrm{cm}$ of the interaction point, and to satisfy
several vertex quality criteria. In Pb–Pb collisions, the centrality was
determined using the V0 multiplicities [55, 56, 57]. Additionally, out-of-
bunch pileup was rejected using timing cuts as well as correlating track
multiplicities between several subdetectors. We utilized a sample of
approximately 4.6M 0–10% most central Pb–Pb accepted events (6.0
$\mu\mathrm{b}^{-1}$) and 760M pp accepted events (15.7 nb-1).

Reconstructed tracks were generally required to include at least one hit in
the Silicon Pixel Detector (SPD) comprising the first two layers of the ITS,
and to have at least 70 TPC space-points and at least 80% of the geometrically
findable space-points in the TPC. Tracks without any hits in the SPD, but
otherwise satisfying the tracking criteria, were re-fit with a constraint to
the primary vertex of the event. Including this second class of tracks ensured
approximately uniform acceptance in $\varphi$, while preserving similar
$p_{\mathrm{T}}$ resolution to tracks with SPD hits. Tracks with
$p_{\mathrm{T,track}}{}>150$ $\mathrm{MeV}\kern-0.50003pt/\kern-0.20004ptc$
were accepted over $-0.9<\eta<0.9,\;0<\varphi<2\pi$. The performance of the
detector was estimated with a model of the ALICE detector and its response to
particles using GEANT3. The tracking efficiency in pp collisions, as estimated
by PYTHIA8 Monash 2013 [58] and the ALICE GEANT3 detector simulation, is
approximately 67% at $p_{\mathrm{T,track}}=150$
$\mathrm{MeV}\kern-0.50003pt/\kern-0.20004ptc$, and rises to approximately 84%
at $p_{\mathrm{T,track}}=1$ $\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ and
remains above 75% at higher $p_{\mathrm{T}}$. The tracking efficiency in 0–10%
Pb–Pb collisions was estimated by comparing central to peripheral HIJING [59]
events, which shows an approximately 2% reduction in the tracking efficiency
in 0-10% central events, approximately independent of $p_{\mathrm{T,track}}$.
The momentum resolution $\delta p_{\mathrm{T}}/p_{\mathrm{T}}$ was estimated
from the covariance matrix of the track fit [51] using PYTHIA8 Monash 2013,
and was approximately 1% at $p_{\mathrm{T,track}}=1$
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ and 4% at
$p_{\mathrm{T,track}}=50$ $\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$.

Reconstructed EMCal clusters were built by clustering EMCal cells with
$E_{\mathrm{cell}}>100$ MeV around a seed cell with $E_{\mathrm{seed}}>300$
MeV, using a clustering algorithm that allows each cluster to have only a
single local maximum. The highest-energy cell in a cluster was required to
satisfy a timing cut. Clusters with large apparent energy but anomalously
small number of contributing cells were removed from the analysis, since they
are believed to be due to interactions of slow neutrons or highly ionizing
particles in the avalanche photodiodes [9]. The linearity of the energy
response of the EMCal was determined from electron test beam data, and a
correction of about 7% at $E_{\mathrm{cluster}}=0.5$ GeV but negligible above
$E_{\mathrm{cluster}}=3$ GeV was applied to the cluster energies. A study
using the photon conversion method demonstrated that with this non-linearity
correction, the $\pi^{0}$ mass in Monte Carlo (MC) simulations matches that in
pp data within 1%. For pp collisions, an additional correction obtained from a
photon conversion analysis was used to reduce the small remaining offset of
the energy scale in data and MC simulations [60]. The energy resolution
obtained from electron test beam data was about 15% at
$E_{\mathrm{cluster}}=0.5$ GeV and better than 5% above
$E_{\mathrm{cluster}}=3$ GeV.

Since the jet energy is reconstructed by combining tracks and clusters, one
needs to account for the fact that charged particles deposit energy in both
the tracking system and the EMCal, as in Ref. [39]. In particular, all
accepted tracks were propagated to the average shower depth of the EMCal,
$r=440$ cm, and allowed to match geometrically to at most one cluster;
clusters were allowed to have multiple matching tracks. If a track was matched
within $p_{\mathrm{T}}$-dependent thresholds ranging from
$(\Delta\eta,\Delta\varphi)\approx(0.037,0.084)$ at
$p_{\mathrm{T}}=0.15\;\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ to
$(\Delta\eta,\Delta\varphi)\approx(0.010,0.015)$ at
$p_{\mathrm{T}}=100\;\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$, then a
hadronic correction was applied to the cluster:
$E_{\mathrm{cluster}}^{\mathrm{hadcorr}}=E_{\mathrm{cluster}}^{\mathrm{nonlincorr}}-\Delta
E$, where $E_{\mathrm{cluster}}^{\mathrm{nonlincorr}}$ is the non-linearity
corrected cluster energy, and $\Delta
E=c\sum_{i}p_{\mathrm{i}}^{\mathrm{track}}$, where $i$ spans all tracks
matched to the cluster, $p_{\mathrm{i}}^{\mathrm{track}}$ is the track
3-momentum, and $c$ is the speed of light. After the above cuts and
corrections were performed, clusters with
$E_{\mathrm{cluster}}^{\mathrm{hadcorr}}>300\;\mathrm{MeV}$ were accepted.

##  3 Jet Reconstruction

Jets were reconstructed with $R=0.1-0.6$ in pp collisions and $R=0.2,0.4$ in
Pb–Pb collisions using the anti-$k_{\mathrm{T}}$ sequential recombination
algorithm implemented in FastJet 3.2.1 [61, 62] from the combination of
charged particle tracks and hadronically corrected EMCal clusters. We used the
$p_{\mathrm{T}}$ recombination scheme, assuming EMCal clusters are massless:
$p_{\mathrm{T,jet}}^{\mathrm{raw}}=\sum_{i}p_{\mathrm{T,track}}^{i}+\sum_{j}p_{\mathrm{T,cluster}}^{j}$,
where $p_{\mathrm{T,cluster}}=E_{\mathrm{cluster}}^{\mathrm{hadcorr}}/c$.

In Pb–Pb collisions, we subtracted the average combinatorial background
following the approach in Ref. [9]. The background density $\rho$ was
determined each event, and used to subtract the average background from each
jet in that event:
$p_{\mathrm{T,jet}}^{\mathrm{reco}}=p_{\mathrm{T,jet}}^{\mathrm{raw}}-\rho A,$
where $A$ is the jet area. The average background density in 0–10% central
events is typically $\left<\rho\right>\approx 220-280$
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$, corresponding to $\approx
110-140$ $\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ for a $R=0.4$ jet. In
pp collisions, we did not subtract the background due to the underlying event.

Jets selected for the measurement were required to satisfy several criteria in
order to be accepted: (i) the center of the jet must be within the fiducial
volume of the EMCal, i.e. a distance $\Delta
R\equiv\sqrt{\left(\Delta\eta\right)^{2}+\left(\Delta\varphi\right)^{2}}$ from
any edge of the EMCal, (ii) the jet must not contain any tracks with
$p_{\mathrm{T,track}}>100$ $\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$,
(iii) in Pb–Pb and applicable pp results, the jet must contain a track with
$p_{\mathrm{T,track}}>5-7$ GeV/$c$, depending on $R$, and (iv) in Pb–Pb
collisions, the area of the jet must be $A>0.6\pi R^{2}$. The
$p_{\mathrm{T,track}}<100$ GeV/c requirement removed only a small number of
jets at large $p_{\mathrm{T,jet}}^{\mathrm{reco}}$, and has negligible bias
for the $p_{\mathrm{T,jet}}^{\mathrm{reco,max}}$ selected in this analysis.
The leading track requirement introduces a small fragmentation bias in the jet
sample, which may lead to a bias in the measured jet suppression. This effect
is discussed in Section 6, and is estimated to have only a small effect on the
reported $R_{\mathrm{AA}}$. A larger leading track requirement is needed for
larger $R$ since the magnitude of background fluctuations increases with $R$.
The area cut in Pb–Pb collisions was negligible except at very low
$p_{\mathrm{T,jet}}^{\mathrm{reco}}$, where it rejects combinatorial jets.

In Pb–Pb collisions, local fluctuations in the background smear the
reconstructed jet momentum. To study jet-by-jet fluctuations in the
background, we generated a random $\left(\eta,\varphi\right)$ within the
fiducial calorimeter acceptance in each event, and compared the sum of
constituents in a cone of radius $R$ to the expected average background in
that cone:
$\delta_{p_{\mathrm{T}}}=\sum_{\mathrm{cone}}\left(p_{\mathrm{T,track}}+p_{\mathrm{T,cluster}}\right)-\rho\pi
R^{2}$. The width of the $\delta_{p_{\mathrm{T}}}$ distribution is a measure
of the size of the background fluctuations [63]. For $R=0.2$, the standard
deviation of the $\delta_{p_{\mathrm{T}}}$ distribution is
$\sigma_{\delta_{p_{\mathrm{T}}}}=6.5$
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$, which grows to
$\sigma_{\delta_{p_{\mathrm{T}}}}=16.1$
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ for $R=0.4$. In the present
analysis the $\delta_{p_{\mathrm{T}}}$ distributions were not explicitly used
except to determine the $p_{\mathrm{T,jet}}^{\mathrm{reco}}$ range to utilize
in the analysis.

We evaluated the performance of our jet reconstruction strategy by estimating
the mean jet energy scale shift,
$\Delta_{\mathrm{JES}}=\left<\left(p_{\mathrm{T,jet}}^{\mathrm{reco}}-p_{\mathrm{T,jet}}^{\mathrm{true}}\right)/p_{\mathrm{T,jet}}^{\mathrm{true}}\right>$,
the jet energy resolution,
$\mathrm{JER}=\sigma\left(p_{\mathrm{T,jet}}^{\mathrm{reco}}\right)\left/p_{\mathrm{T,jet}}^{\mathrm{true}}\right.$,
and the jet reconstruction efficiency, $\varepsilon_{\mathrm{reco}}$, from
PYTHIA8 Monash 2013 and the ALICE detector simulation. Table 1 shows
approximate values of
$\Delta_{\mathrm{JES}},\;\mathrm{JER},\;\varepsilon_{\mathrm{reco}}$ for
$R=0.2$ in pp and Pb–Pb collisions. The jet energy scale shift is a long-
tailed asymmetric distribution due to reconstruction inefficiency (such as
tracking inefficiency) [10], and $\Delta_{\mathrm{JES}}$ should be understood
only as a rough characterization of this distribution. When a leading track
requirement is imposed, the jet reconstruction efficiency and jet energy scale
shift are primarily due to this requirement in combination with the tracking
efficiency. Note that the pp response approximately, but not exactly,
describes the detector effects in jet reconstruction relevant for Pb–Pb
collisions. In Pb–Pb collisions, the jet reconstruction performance (including
the effect of background fluctuations) was determined by embedding pp MC
events into Pb–Pb data, as described in detail in Section 4. The JER is
approximately constant at $\approx 23\%$ above
$p_{\mathrm{T,jet}}^{\mathrm{true}}=60$
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ for $R=0.2$, and deteriorates
at lower $p_{\mathrm{T,jet}}^{\mathrm{true}}$ due to background fluctuations.
As $R$ increases, the JER deteriorates due to the increased influence of
background fluctuations.

Table 1: Approximate values characterizing the jet reconstruction performance for $R=0.2$ and $R=0.4$ in pp and Pb–Pb collisions. For cases with a leading track requirement, $p_{\mathrm{T}}^{\mathrm{lead,ch}}=5\;\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ is used for $R=0.2$ and $p_{\mathrm{T}}^{\mathrm{lead,ch}}=7\;\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ for $R=0.4$ | pp $(p_{\mathrm{T}}^{\mathrm{lead,ch}}>0\;\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc)$ | pp $(p_{\mathrm{T}}^{\mathrm{lead,ch}}>5/7\;\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc)$ | $\mbox{Pb--Pb}{}\;(p_{\mathrm{T}}^{\mathrm{lead,ch}}>5/7\;\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc)$
---|---|---|---
$p_{\mathrm{T,jet}}$ | $20\;\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ | $100\;\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ | $20\;\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ | $100\;\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ | $20\;\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ | $100\;\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$
$R=0.2$ |  |  |  |  |  |
$\Delta_{\mathrm{JES}}$ | –29% | –30% | –18% | –28% | –23% | –35%
$\mathrm{JER}$ | 27% | 21% | 19% | 19% | 35% | 23%
$\varepsilon_{\mathrm{reco}}$ | 98% | 100% | 86% | 96% | 86% | 96%
$R=0.4$ |  |  |  |  |  |
$\Delta_{\mathrm{JES}}$ | –30% | –31% | –14% | –27% | –6% | –33%
$\mathrm{JER}$ | 23% | 18% | 15% | 16% | 77% | 25%
$\varepsilon_{\mathrm{reco}}$ | 99% | 100% | 82% | 92% | 82% | 92%

##  4 Corrections

The reconstructed $p_{\mathrm{T,jet}}^{\mathrm{reco}}$ spectrum includes
fluctuations in the underlying background (in Pb–Pb collisions) and a variety
of detector effects, including tracking inefficiency, missing long-lived
neutral particles (n, $\mathrm{K}_{\mathrm{L}}^{0}$), and particle-material
interactions. We therefore deconvoluted the reconstructed jet spectrum with a
response matrix (RM) describing the correlation between
$p_{\mathrm{T,jet}}^{\mathrm{reco}}$ and $p_{\mathrm{T,jet}}^{\mathrm{true}}$
in order to recover the “truth"-level jet spectrum at the hadron-level.

In pp collisions, we generated a RM using PYTHIA 8 Monash 2013 with the full
GEANT3 ALICE detector simulation, based on the detector performance in the
relevant 2017 pp data-taking period. In Pb–Pb collisions, we generated a RM by
embedding PYTHIA events (with detector simulation based on the detector
performance in the 2015 Pb–Pb data-taking period) into Pb–Pb data after the
detector-level reconstruction was run individually on both. The set of tracks
in the “hybrid" event was taken as the sum of all tracks in both events
individually, while the set of EMCal clusters were re-clustered from a
combined pool of cells from both events. This embedding-based approach, which
uses real background, ensures that the detector response accurately reflects
the Pb–Pb response of the calorimeter, including particle overlaps in the
calorimeter as well as the Pb–Pb particle composition, and ensures the effect
of the hadronic correction is equivalent in data and in the response.
Moreover, it ensures that the correlation between the local background and the
reconstructed jet due to local detector inefficiencies is accounted for.

The truth-level jet was constructed from the primary particles of the PYTHIA
event, defined as all particles with a proper decay length longer than 1 cm,
excluding daughters of these particles [64]. We correct the jet
$p_{\mathrm{T}}$ to include the “missing" long-lived neutral particles.

The detector-level jet in pp collisions was constructed from the PYTHIA tracks
and clusters at detector level. In Pb–Pb collisions, the detector-level jet
was constructed from the “hybrid" event consisting of both PYTHIA and Pb–Pb
tracks and clusters at detector level. Studies of the centrality-dependence of
tracking efficiency in a HIJING simulation demonstrated that the tracking
efficiency is approximately 2% lower in 0-10% central Pb–Pb collisions
compared to pp collisions; accordingly, we randomly rejected 2% of the PYTHIA
tracks in the Pb–Pb case, independent of $p_{\mathrm{T}}$. The average
combinatorial background was subtracted as in 0-10% central Pb–Pb MB data: we
computed the event-by-event $\rho_{\mathrm{charged}}$ using only Pb–Pb tracks,
and we applied the background scale factor obtained in Pb–Pb MB data; we
assume that the combinatorial background from the pp event is negligible.

In order to fill the RM, we matched truth-level jets to detector-level jets by
a geometrical matching procedure. In pp collisions, if an accepted detector-
level jet and an accepted PYTHIA jet were within $\Delta R<0.6R$, and they
were both the closest jets to each other, then the jets were matched, and
contribute to the RM. In Pb–Pb collisions, if an accepted hybrid jet and an
accepted PYTHIA jet were within $\Delta R<1.5R$, and they were both the
closest jets to each other, then the jets were matched, and contribute to the
RM. The leading track requirement nullifies the need in Pb–Pb collisions for
further criteria such as a shared momentum fraction requirement in order to
generate accurate matches. The RM was generated with 5
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ bin widths for
$p_{\mathrm{T,jet}}^{\mathrm{reco}}$ and 10
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ widths for
$p_{\mathrm{T,jet}}^{\mathrm{true}}$, and was normalized so as to preserve the
number of jets upon unfolding.

To perform the deconvolution, we employed the SVD unfolding algorithm [65]
using the RooUnfold package [66]. The regularization parameter $k$ suppresses
high-frequency variations in the unfolded result, and was selected by
examining the so-called $d$-vector distribution. Statistical uncertainties
were computed according to MC pseudo-experiments within RooUnfold. The
reconstructed spectrum was input to the unfolding procedure over a fixed
window of
$p_{\mathrm{T,jet}}^{\mathrm{reco}}\in\left[p_{\mathrm{T,jet}}^{\mathrm{reco,min}},p_{\mathrm{T,jet}}^{\mathrm{reco,max}}\right]$,
as illustrated in Table 2. In Pb–Pb collisions, each of these
$p_{\mathrm{T,jet}}^{\mathrm{reco,min}}$ corresponds to $\approx
2-3\times\sigma_{\delta_{p_{\mathrm{T}}}}$, which, in combination with the
leading charged hadron requirement, results in a sample largely free of
combinatorial jets. A larger value of $p_{\mathrm{T,jet}}^{\mathrm{reco,min}}$
was used in Pb–Pb collisions in order to minimize the impact of the
combinatorial background, which can de-stabilize the unfolding process. Any
residual combinatorial jets will still be unfolded to low $p_{\mathrm{T}}$ by
the RM. Since truncating the RM in $p_{\mathrm{T,jet}}^{\mathrm{reco}}$ loses
the information of the fraction of truth-level jets that migrate outside of
the measured detector-level window, we corrected for this kinematic
efficiency. The unfolded result is then reported in a range over which the
input data provides meaningful constraints; that is, a region unaffected by
combinatorial jets, and where the kinematic efficiency is larger than
approximately 80%.

Table 2: Minimum and maximum reconstructed jet $p_{\mathrm{T}}$ used in the analysis as input to the deconvolution procedure. | pp ($\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$) |  Pb–Pb ($\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$)
---|---|---
| $p_{\mathrm{T,jet}}^{\mathrm{reco,min}}$ | $p_{\mathrm{T,jet}}^{\mathrm{reco,max}}$ | $p_{\mathrm{T,jet}}^{\mathrm{reco,min}}$ | $p_{\mathrm{T,jet}}^{\mathrm{reco,max}}$
$R=0.2$ | 7 | 130 | 20 | 120
$R=0.4$ | 10 | 130 | 35 | 120

We corrected the unfolded spectrum for the fact that the jet finding procedure
failed to reconstruct a certain fraction of jets. We computed the jet
reconstruction efficiency as:

$\varepsilon_{\mathrm{reco}}\left(p_{\mathrm{T,jet}}^{\mathrm{true}}\right)=N_{\mathrm{matched}}\left(p_{\mathrm{T,jet}}^{\mathrm{true}}\right)/N_{\mathrm{truth}}\left(p_{\mathrm{T,jet}}^{\mathrm{true}}\right),$

where $N_{\mathrm{matched}}$ is the number of accepted detector-level jets
matched to PYTHIA truth-level jets out of $N_{\mathrm{truth}}$ accepted truth-
level jets. In order that $\varepsilon_{\mathrm{reco}}$ also includes the
false positive rate of accepted detector-level jets that have no matching
truth-level jet (which can occur if the truth-level jet was generated slightly
outside of our geometrical acceptance), the numerator also contains matches to
truth-level jets outside of the EMCal fiducial acceptance. Note that
$\varepsilon_{\mathrm{reco}}$ does not explicitly include the bias of the
leading charged hadron requirement, but only the probability to reconstruct an
accepted jet given a truth-level jet satisfying the leading charged hadron
requirement (when applicable). In order for $\varepsilon_{\mathrm{reco}}$ to
be the jet reconstruction efficiency, the jet matching efficiency must be
100%. However, in the Pb–Pb embedding environment, this is difficult to
achieve, since some criteria need to be imposed to suppress combinatorial jets
(in our case, the leading track requirement). Therefore, in the Pb–Pb case we
used the jet reconstruction efficiency as determined from a pp simulation
alone (with 2% reduced tracking efficiency).

The unfolded solution was verified to be mathematically robust by performing a
re-folding test and a “self-closure" test. The re-folding test consisted of
generating a RM (from half of the MC data sample runs) and unfolding the
measured distribution, then applying a RM (from the other half of the MC data
sample) to the unfolded result, and comparing the re-folded solution to the
measured distribution. The self-closure test consisted of taking the matched
detector-level jet spectrum in the full embedded sample, and smearing each
data point with a Gaussian according to the statistical uncertainties of the
measured data. This spectrum was then unfolded using the RM, and compared the
result to the truth-level PYTHIA jet spectrum. In both cases, consistency was
achieved within statistical uncertainties.

In Pb–Pb collisions, the unfolded solution is verified to be physically
correct by a thermal model closure test similar to that in Ref. [9]. The
closure test consisted of performing the entire analysis on “hybrid" events
containing a PYTHIA event and a thermal background, in which “hybrid" jets
were clustered from the combination of PYTHIA detector-level particles and
thermal background particles. The background was modeled by generating $N$
particles from a Gaussian, with $p_{\mathrm{T}}$ taken from a Gamma
distribution, $f_{\Gamma}\left(p_{\mathrm{T}};\beta\right)\sim
p_{\mathrm{T}}e^{-p_{\mathrm{T}}/\beta}$, where the free parameters
$\overline{N},\sigma_{N},\beta$ were fixed to roughly fit the
$\delta_{p_{\mathrm{T}}}$ distribution in 0–10% Pb–Pb data. The test consisted
of constructing the hybrid detector-level jet spectrum, building the RM, and
unfolding the hybrid jets – and comparing the spectrum to the truth-level
PYTHIA spectrum. Since the background does not have any jet component, this
test is able to verify whether the analysis procedure indeed recovers the jet
spectrum, and is not contaminated by combinatorial jets. These tests validated
the analysis procedure within approximately 5% for $R=0.2$ with
$p_{\mathrm{T}}^{\mathrm{lead,ch}}=5$ GeV/$c$, and $R=0.4$ with
$p_{\mathrm{T}}^{\mathrm{lead,ch}}=7$ GeV/$c$.

##  5 Systematic Uncertainties

Following Ref. [9], we categorized two classes of systematic uncertainties:
correlated uncertainties and shape uncertainties. Correlated uncertainties
encompass detector effects such as uncertainty on the tracking efficiency and
uncertainty on the EMCal response, which are approximately fully positively
correlated among all $p_{\mathrm{T,jet}}$ bins. Shape uncertainties refer to
systematic unfolding uncertainties, which alter the shape of the final
$p_{\mathrm{T,jet}}$ spectrum. The dominant systematic uncertainties in this
analysis are the uncertainty in the tracking efficiency and the systematic
uncertainty in the unfolding procedure. Note that in general the following
uncertainties describe uncertainties on the jet yield, not on the jet
$p_{\mathrm{T}}$ scale.

###  5.1 Correlated uncertainties

The dominant correlated uncertainty is the uncertainty on the modeling of the
tracking efficiency, since correcting for unmeasured tracks has a major effect
on the unfolding procedure. For the track selection described in Section 2,
the uncertainty on the tracking efficiency is approximately 4%, as estimated
from variation in the track selection parameters and variation in the ITS-TPC
matching requirements. In order to assign a systematic uncertainty to the
final result, we constructed a RM using the same techniques as for the final
result except with an additional 4% of PYTHIA tracks randomly rejected in jet
finding (for Pb–Pb, this is in addition to the 2% rejection used for the main
result). The jet reconstruction efficiency was also computed with this extra
4% suppression applied. This modified RM was then used to unfold the same
measured spectrum as used for the main result. This varied result was
corrected for the jet reconstruction efficiency, and compared to the main
result, with the differences in each bin taken as the uncertainty.
Additionally, the uncertainty due to the tracking $p_{\mathrm{T}}$ resolution
was approximately 1%.

Table 3: Summary of correlated systematic uncertainties on the pp and Pb–Pb jet spectra, for select $R$ and $p_{\mathrm{T}}^{\mathrm{lead,ch}}$ thresholds. The columns $p_{\mathrm{T,jet}}^{\mathrm{min}}$ and $p_{\mathrm{T,jet}}^{\mathrm{max}}$ are the uncertainties at the minimum and maximum $p_{\mathrm{T,jet}}$ bin. | Relative uncertainty (%)
---|---
pp |  $R=0.2,0$ $\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ |  $R=0.6,0$ $\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$
| $p_{\mathrm{T,jet}}^{\mathrm{min}}$ | $p_{\mathrm{T,jet}}^{\mathrm{max}}$ | Avg. | $p_{\mathrm{T,jet}}^{\mathrm{min}}$ | $p_{\mathrm{T,jet}}^{\mathrm{max}}$ | Avg.
Tracking efficiency | 5.9 | 9.1 | 7.7 | 9.4 | 8.9 | 9.0
Track $p_{\mathrm{T}}$ resolution | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0
EMCal nonlinearity | 0.5 | 0.5 | 0.5 | 1.0 | 0.9 | 1.0
Hadronic correction | 0.2 | 1.2 | 0.5 | 1.2 | 2.1 | 0.9
Jet matching | 0.1 | 0.0 | 0.0 | 0.2 | 0.2 | 0.2
PYTHIA fragmentation | 0.5 | 1.0 | 0.4 | 3.1 | 5.6 | 5.8
Total corr. uncertainty | 6.0 | 9.3 | 7.8 | 10.1 | 10.8 | 10.8
Pb–Pb |  $R=0.2,5$ $\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ |  $R=0.4,7$ $\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$
| $p_{\mathrm{T,jet}}^{\mathrm{min}}$ | $p_{\mathrm{T,jet}}^{\mathrm{max}}$ | Avg. | $p_{\mathrm{T,jet}}^{\mathrm{min}}$ | $p_{\mathrm{T,jet}}^{\mathrm{max}}$ | Avg.
Tracking efficiency | 5.8 | 8.9 | 8.0 | 9.9 | 9.8 | 9.8
Track $p_{\mathrm{T}}$ resolution | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0
EMCal nonlinearity | 2.1 | 1.1 | 1.6 | 11.4 | 7.9 | 9.5
Hadronic correction | 0.8 | 5.9 | 2.0 | 12.8 | 9.9 | 12.4
Jet matching | 2.0 | 2.0 | 2.0 | 6.0 | 2.0 | 2.8
PYTHIA fragmentation | 0.8 | 3.6 | 2.0 | 2.8 | 5.1 | 3.8
Total corr. uncertainty | 6.7 | 11.6 | 9.2 | 20.9 | 16.9 | 19.5

Systematic uncertainties due to the modeling of the EMCal response were
included in several ways. In order to describe the uncertainty in the MC
description of the EMCal hadronic response, the subtracted energy in the
hadronic correction was varied from 100% to 70% of the matched track momentum.
Moreover, a systematic uncertainty associated with the track-matching criteria
was included by changing the $p_{\mathrm{T}}$-dependent track-matching
criteria to $p_{\mathrm{T}}$-independent criteria
$\Delta\eta<0.015,\;\Delta\varphi<0.03$. These two uncertainties were combined
in quadrature to form the uncertainty on the EMCal hadronic correction
procedure. In order to describe the uncertainty in the MC description of the
EMCal electromagnetic response, in the pp case the photon conversion based
non-linearity correction was switched off. These variations were individually
performed both in the RM and the data, and the systematic uncertainty was
evaluated by comparing the modified unfolded result to the main result. In the
Pb–Pb case, there is an additional uncertainty due to the fact that the MC
does not exactly describe the cluster energy nonlinearity. To account for
this, different cluster non-linearity corrections are typically applied to
data and MC; however, in the Pb–Pb embedding procedure, the clusters are
mixtures of data and MC cells. The main result was computed by applying the
data non-linearity parameterization to the mixed data and MC cells in the
embedding procedure. Therefore, the systematic variation to this result
applied the MC non-linearity parameterization. In Pb–Pb collisions for
$R=0.4$, the uncertainties on the EMCal non-linearity correction and track
matching procedure are large, primarily due to unfolding effects, which we do
not de-couple in the evaluation of the correlated uncertainties.

We included also a systematic uncertainty associated with the choice of jet
matching procedure. For pp, the geometrical matching distance was varied from
$0.4R$ to $0.8R$ (except for $R=0.1$ from $0.2R$ to $0.9R$), which resulted in
an uncertainty of less than 1% (1.5%). For Pb–Pb, we varied from a pure
geometrical matching to an MC-fraction based approach, in which a shared
momentum fraction requirement ensures that the matched jet contains more than
50% of the $p_{\mathrm{T}}$ of the MC jet. This gave an uncertainty of 2–6%.

We included also a systematic uncertainty associated with the model-dependent
reliance on PYTHIA to unfold the spectra. In pp collisions, we re-weighted the
response matrix according to the jet angularity
($g=\sum_{i}p_{\mathrm{T},i}r_{i}/p_{\mathrm{T,jet}}$, where
$r_{i}=\sqrt{\Delta\eta^{2}+\Delta\varphi^{2}}$ is the distance of the
$i^{\mathrm{th}}$ constituent from the jet axis) at truth-level. Specifically,
we re-weighted the response matrix such that the 50% largest angularity jets
were weighted an additional $\pm 30\%$ relative to the 50% lowest angularity
jets. This contributed an uncertainty ranging from $\approx 2\%-7\%$ depending
on the jet $R$, and roughly independent of $p_{\mathrm{T}}$. The same
uncertainties were taken for Pb–Pb collisions.

Table 3 illustrates the contributions of the various correlated uncertainties
for Pb–Pb and pp collisions. These uncertainties are expected to be largely
independent, so we summed their uncertainties in quadrature.

###  5.2 Shape uncertainties

Table 4: Summary of shape systematic uncertainties on the pp and Pb–Pb jet spectra, for select $R$ and $p_{\mathrm{T}}^{\mathrm{lead,ch}}$ thresholds. The columns $p_{\mathrm{T,jet}}^{\mathrm{min}}$ and $p_{\mathrm{T,jet}}^{\mathrm{max}}$ are the uncertainties at the minimum and maximum $p_{\mathrm{T,jet}}$ bin. | Relative uncertainty (%)
---|---
pp |  $R=0.2,0$ $\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ |  $R=0.6,0$ $\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$
| $p_{\mathrm{T,jet}}^{\mathrm{min}}$ | $p_{\mathrm{T,jet}}^{\mathrm{max}}$ | Avg. | $p_{\mathrm{T,jet}}^{\mathrm{min}}$ | $p_{\mathrm{T,jet}}^{\mathrm{max}}$ | Avg.
Unfolding method | 0.0 | 16.0 | 3.4 | 2.6 | 16.0 | 4.5
Reg. parameter | 0.7 | 2.4 | 1.3 | 1.0 | 3.5 | 2.1
Prior | 1.3 | 0.8 | 0.9 | 0.9 | 3.7 | 2.0
Input $p_{\mathrm{T}}$ range | 0.8 | 3.3 | 1.3 | 0.4 | 3.2 | 1.4
Total shape uncertainty | 0.8 | 8.3 | 2.2 | 1.5 | 8.5 | 3.0
Pb–Pb |  $R=0.2,5$ $\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ |  $R=0.4,7$ $\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$
| $p_{\mathrm{T,jet}}^{\mathrm{min}}$ | $p_{\mathrm{T,jet}}^{\mathrm{max}}$ | Avg. | $p_{\mathrm{T,jet}}^{\mathrm{min}}$ | $p_{\mathrm{T,jet}}^{\mathrm{max}}$ | Avg.
Unfolding method | 7.7 | 10.0 | 5.4 | 30.3 | 2.5 | 18.2
Reg. parameter | 4.2 | 8.7 | 4.4 | 24.9 | 20.6 | 23.1
Prior | 1.5 | 6.7 | 2.4 | 2.3 | 8.3 | 4.2
Input $p_{\mathrm{T}}$ range | 0.4 | 0.9 | 0.6 | 1.5 | 1.7 | 1.4
Total shape uncertainty | 4.4 | 7.4 | 3.8 | 19.6 | 11.2 | 15.5

In order to assign a shape uncertainty arising from the unfolding
regularization procedure, we performed several systematic variations:

  * •

Variation of the unfolding algorithm: We unfolded with a Bayes-inspired
iterative unfolding algorithm [67].

  * •

Variation of the regularization parameter: In the SVD unfolding, we varied the
regularization parameter $k$ one unit above and below the nominal solution.

  * •

Variation of the prior: The SVD algorithm requires a prior distribution as
input, which for the main result is the projection of the RM onto the truth
axis (before normalization). We varied this input prior either by scaling the
main prior by $p_{\mathrm{T}}^{\pm 0.5}$ or replacing it with a jet cross-
section produced by POWHEG or the unfolded main result itself.

  * •

Variation of the input range: For Pb–Pb (pp) collisions, we varied the
measured input range $\pm 5$ (${}^{+5}_{-3}$)
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ around the nominal value for
each $R$.

The total shape uncertainty is then the standard deviation of the variations,
$\sqrt{\sum_{i=1}^{3}\sigma_{i}^{2}/4}$, where $\sigma_{i}$ is the systematic
due to a single variation, since they each comprise independent measurements
of the same underlying systematic uncertainty in the regularization. Table 4
illustrates the contributions of the various shape uncertainties for Pb–Pb and
pp collisions.

###  5.3 Uncertainties on the jet cross-section ratio

We computed the correlated systematic uncertainties on the pp jet cross-
section ratio by making the same variations as in Section 5.1 on both spectra
simultaneously, and compared the varied jet cross-section ratio to the main
result. This resulted in significant cancellation of the correlated
uncertainties between the numerator and denominator, as can be seen in Section
6. We computed the shape systematic uncertainties by adding the single spectra
shape uncertainties in quadrature.

It is important to note that the statistical uncertainties of the numerator
and denominator are partially correlated, due to error propagation through the
unfolding procedure. We did not, however, take this into account. This may
result in a slightly conservative statistical uncertainty estimation, since
there may be significant cancellation between the two radii. Additionally, we
did not use statistically independent samples to form the ratio, and so the
numerator and denominator are statistically correlated with each other, which
may lead to further slight overestimation of the statistical uncertainties.

##  6 Results

###  6.1 Inclusive Jet Spectra

####  6.1.1 pp

We report the pp full jet cross-section for $R=0.1,0.2,0.3,0.4,0.5,0.6$ in
Fig. 1 left. The cross-sections are reported differentially in
$p_{\mathrm{T,jet}}$ and $\eta_{\mathrm{jet}}$ as:
$\frac{\mathrm{d}^{2}\sigma_{jet}}{\mathrm{d}p_{\mathrm{T,jet}}\mathrm{d}\eta_{\mathrm{jet}}}=\frac{1}{\mathcal{L}}\frac{\mathrm{d}^{2}N}{\mathrm{d}p_{\mathrm{T,jet}}\mathrm{d}\eta_{\mathrm{jet}}},$
where we experimentally measured the yield
$\frac{\mathrm{d}^{2}N}{\mathrm{d}p_{\mathrm{T,jet}}\mathrm{d}\eta_{\mathrm{jet}}}$
and the integrated luminosity $\mathcal{L}$ [54]. The uncertainty on the
luminosity is 2.1%. The measured jet cross-sections were unfolded for detector
and background effects, and are reported at the hadron-level. The cross-
sections were corrected for the kinematic efficiency and jet reconstruction
efficiency, as well as the partial azimuthal acceptance of the EMCal and the
vertex efficiency. Note that a leading track requirement was not imposed for
the results in Fig. 1.

Figure 1: Left: Unfolded pp full jet cross-section at $\sqrt{s}=5.02$ TeV for
$R=0.1-0.6$. No leading track requirement is imposed. Right: Ratio of
NLO+NLL+NP and POWHEG+PYTHIA8 tune A14 predictions to the measured data. The
systematic uncertainties in the ratio are denoted by boxes, and are the
quadratic sum of the systematic uncertainties in data and the predictions.
Note that no systematic uncertainties for the non-perturbative correction in
the NLO+NLL+NP prediction were included.

We compare the pp inclusive jet cross-section to two theoretical calculations
in Fig. 1 right. The predictions denoted NLO+NLL+NP are analytical predictions
at NLO with resummation of jet $R$ logarithms and threshold logarithms to NLL
accuracy, performed in a rigorous QCD factorization scheme [28, 30, 31]. The
effect of unaccounted higher-order corrections was evaluated by various scale
variations, and is included as a systematic uncertainty. A correction for
hadronization and multi-parton interaction (MPI) effects is applied to this
prediction, based on PYTHIA 8 tune A14, and is shown in Fig. 2. These non-
perturbative (NP) effects become large for low $p_{\mathrm{T,jet}}$ at both
small and large $R$, where systematic uncertainties in this correction (beyond
the scope of this article) are likely critical. The predictions use PDF set
CT14nlo. These predictions are seen to be generally consistent with the data,
except at low-$p_{\mathrm{T}}$ and small-$R$. This tension may be due to the
model-dependent NP correction, which is large in this region. The experimental
data presented in Fig. 1, which cover a large range of $R$ down to low
$p_{\mathrm{T}}$, and therefore span a wide range of NP effects (from
hadronization-dominated at small $R$ to MPI-dominated at large $R$, as seen in
Fig. 2), can be used to further constrain NP effects in pp collisions. This is
of relevance both for pp QCD physics and for interpreting modifications in
heavy-ion collisions, which are typically strongest at low pT.

The predictions denoted POWHEG+PYTHIA8 consist of a MC parton-shower based
model using NLO calculations from POWHEG [68] matched to a parton shower and
hadronization from PYTHIA 8 tune A14.111The POWHEG reference was produced by
POWHEG-BOX-V2 at $\sqrt{s}=5.02$ TeV via the jet pair production process [68,
69, 70]. PDF set CT14nlo was used, along with the settings bornktmin$=1$ and
bornsuppfact$=70$. PYTHIA 8.2 tune A14 NNPDF2.3LO was used for the parton
shower, which is tuned with ATLAS pp collisions at $\sqrt{s_{\mathrm{NN}}}=7$
TeV using underlying event observables, jet substructure observables, and
several other observables, not including the inclusive jet cross-section [71].
Merging with PYTHIA was done as in Ref. [72]. The same set of primary
particles was used as described earlier [64]. Two theoretical uncertainties
were computed for these predictions, both in regard to the POWHEG event
generation: PDF uncertainty, computed as in Ref. [72], and scale uncertainty,
which was computed by varying the renormalization and factorization scales.
The total theoretical uncertainty on the cross-section was obtained by adding
these two contributions in quadrature. Note that large non-perturbative
effects, similar to Fig. 2, are implicitly present in this prediction as well.
The POWHEG+PYTHIA8 predictions are consistent with the measured data for all
$R$ and $p_{\mathrm{T,jet}}$. Figure 1 does not include predictions by PYTHIA
alone, since it is well-established that NLO contributions are necessary to
obtain the pp inclusive jet cross-section [38, 32].

Figure 2: Non-perturbative correction factor applied to parton-level NLO+NLL
predictions, obtained from PYTHIA 8 tune A14 as the ratio of the inclusive jet
spectrum at hadron-level with MPI compared to parton-level without MPI.

Figure 3: Unfolded pp jet cross-section ratios for various $R$. Top panels:
ratios of $R=0.2$ to other radii. Bottom panels: ratios of $R=0.1$ to other
radii. The left panels include comparisons to POWHEG + PYTHIA8, and the right
panels include comparisons to NLO+NLL+NP. The experimental correlated
systematic uncertainties and shape systematic uncertainties were combined in
quadrature into a single systematic uncertainty. Note that no systematic
uncertainties for the non-perturbative correction in the NLO+NLL+NP prediction
were included.

Figure 3 shows the pp jet cross section ratio for various $R$, built from the
spectra in Fig. 1. The top two panels show the ratios of $R=0.2$ to other
radii, and the bottom two panels show the ratios of $R=0.1$ to other radii.
The left panels also include comparisons to POWHEG + PYTHIA8, and the right
panels include comparisons to NLO+NLL+NP. Correlated uncertainties largely
cancel [39, 73], which allows this observable to elucidate higher-precision
effects compared to the inclusive jet cross-section. The systematic
uncertainties on the POWHEG + PYTHIA8 prediction largely cancel as well, and
the resulting high-precision comparisons show that the cross-section ratios
are generally well-described by POWHEG + PYTHIA8. The systematic uncertainties
in the NLO+NLL+NP prediction, however, do not substantially cancel, due to the
fact that the scale variations include variation of softer scales which are
sensitive to non-perturbative effects; the NLO+NLL+NP predictions are
consistent with the measured data within the size of these large theoretical
uncertainties.

####  6.1.2 Pb–Pb

We report the 0–10% central Pb–Pb jet spectra for $R=0.2$ and $R=0.4$ in Fig.
4. The spectra are reported differentially in $p_{\mathrm{T,jet}}$ and
$\eta_{\mathrm{jet}}$ as:
$\frac{1}{\left<T_{\mathrm{AA}}\right>}\frac{1}{N_{event}}\frac{\mathrm{d}^{2}N_{jet}^{AA}}{\mathrm{d}p_{\mathrm{T,jet}}\mathrm{d}\eta_{\mathrm{jet}}},$
where
$\left<T_{\mathrm{AA}}\right>\equiv\frac{\left<N_{\mathrm{coll}}\right>}{\sigma_{inel}^{NN}}$
is the ratio of the number of binary nucleon-nucleon collisions to the
inelastic nucleon-nucleon cross-section, computed in a Glauber model to be
$\left<T_{\mathrm{AA}}\right>=23.07\pm 0.44\;\mathrm{(sys)\;mb^{-1}}$ for
0–10% centrality. The jet spectra were unfolded for detector and background
effects, and are reported at the hadron-level. The spectra were corrected for
the kinematic efficiency and jet reconstruction efficiency, as well as the
partial azimuthal acceptance of the EMCal. The $R=0.2$ jets are reported for
the range $p_{\mathrm{T,jet}}\in[40,140]$
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$. The $R=0.4$ jets are reported
for the range $p_{\mathrm{T,jet}}\in[60,140]$
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$. The reported intervals were
selected based on being insensitive to the combinatorial background, as well
as having kinematic efficiency above approximately 80%. Note that the reported
$p_{\mathrm{T,jet}}$ intervals extend higher than the measured
$p_{\mathrm{T,jet}}^{\mathrm{reco}}$ range because the kinematic efficiency
remains high at larger $p_{\mathrm{T,jet}}$ due to the JES shift. A leading
track bias of 5 $\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ was required
for the $R=0.2$ spectra, while a 7
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ bias was required for the
$R=0.4$ spectra (both pp reference and Pb–Pb) in order to suppress
combinatorial jets in Pb–Pb collisions. We did not attempt to correct to a
fully inclusive spectrum, in order to avoid model-dependence. The pp cross-
sections with leading track biases of 5
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ and 7
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ are plotted alongside the Pb–Pb
spectra in Fig. 4.

Figure 4: Unfolded pp and Pb–Pb full jet spectra at
$\sqrt{s_{\mathrm{NN}}}=5.02$ TeV for $R=0.2$ (left), with 5
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ leading track requirement, and
$R=0.4$ (right), with 7 $\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ leading
track requirement. The pp data points correspond to
$\frac{\mathrm{d}^{2}\sigma}{\mathrm{d}p_{\mathrm{T,jet}}\mathrm{d}\eta_{\mathrm{jet}}}$.

###  6.2 Jet $R_{\mathrm{AA}}$

We report the jet $R_{\mathrm{AA}}$ as:

$R_{\mathrm{AA}}=\frac{\left.{\frac{1}{N_{\mathrm{event}}}\frac{\mathrm{d}^{2}N}{\mathrm{d}p_{\mathrm{T,jet}}\mathrm{d}\eta_{\mathrm{jet}}}}\right|_{\mathrm{AA}}}{\left<T_{\mathrm{AA}}\right>\left.{\frac{\mathrm{d}^{2}\sigma}{\mathrm{d}p_{\mathrm{T,jet}}\mathrm{d}\eta_{\mathrm{jet}}}}\right|_{\mathrm{pp}}},$

namely the ratio of the Pb–Pb and pp spectra plotted above. While the measured
Pb–Pb spectra only report jets satisfying the leading charged hadron
requirement, one can choose whether or not to apply the same requirement for
the pp reference, despite that the bias may be different in pp and Pb–Pb
collisions. To examine the effect of this bias, in Fig. 5 we plot the ratio of
the $R=0.2$ pp cross-section with either a 0, 5, or 7
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ leading track requirement, as
well as the ratio of the $R=0.2$ Pb–Pb jet spectrum with either a 5 or 7
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ leading track requirement.
Figure 5 shows that the relative bias between a 5 and 7
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ leading track requirement is
very similar in pp and Pb–Pb collisions, suggesting that the overall bias in
the reported $R_{\mathrm{AA}}$ may be small compared to the measurement
uncertainties. Nevertheless, we report the $R_{\mathrm{AA}}$ both with and
without a leading track requirement on the pp reference.

Figure 5: Left: Ratio of the pp jet cross-section with various leading charged
particle requirements. Right: Ratio of the $R=0.2$ Pb–Pb jet cross-section
with a 7 $\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ leading charged
particle requirement compared to a 5
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ leading charged particle
requirement.

Figure 6 shows the unfolded full jet $R_{\mathrm{AA}}$ for $R=0.2$ and $R=0.4$
jets, both with and without a leading track requirement on the pp reference.
The uncertainties in the Pb–Pb and pp spectra were combined in quadrature. The
jet $R_{\mathrm{AA}}$ exhibits strong suppression, and constitutes the first
0–10% jet $R_{\mathrm{AA}}$ measurements at $\sqrt{s_{\mathrm{NN}}}=5.02$ TeV
at low jet $p_{\mathrm{T}}$ (i.e. $p_{\mathrm{T,jet}}<100$
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$), and the first inclusive jet
$R_{\mathrm{AA}}$ measurements by ALICE extending to $R=0.4$ at any collision
energy. There is visible $p_{\mathrm{T,jet}}$-dependence in the $R=0.2$ case,
with stronger suppression at lower $p_{\mathrm{T,jet}}$. There is no
significant $R$-dependence of the jet $R_{\mathrm{AA}}$ within the
experimental uncertainties. We do not report the jet cross-section ratio for
different $R$ in Pb–Pb collisions due to the fact that we found minimal
cancellation of uncertainties (due to large unfolding uncertainties for
$R=0.4$), and it therefore does not convey additional information beyond the
reported $R_{\mathrm{AA}}$.

Figure 6: Jet $R_{\mathrm{AA}}$ at $\sqrt{s_{\mathrm{NN}}}=5.02$ TeV for
$R=0.2$ (left) and $R=0.4$ (right). In the top panel a leading track
requirement is imposed on the pp reference, while in the bottom panel no such
requirement is imposed on the pp reference. The combined
$\left<T_{\mathrm{AA}}\right>$ uncertainty and pp luminosity uncertainty of
2.8% is illustrated as a band on the dashed line at $R_{\mathrm{AA}}=1$.

We compare these results to four theoretical predictions: the Linear Boltzmann
Transport (LBT) model [74, 25], Soft Collinear Effective Theory with Glauber
gluons (SCETG) [75, 76, 29, 77], the Hybrid model [78, 79, 80, 81], and JEWEL
[82, 83]. The $R_{\mathrm{AA}}$ predictions of these models are compared to
the measured data (with the leading track requirements imposed) in Fig. 7 for
$R=0.2$ and $R=0.4$. The predictions were all computed using the
anti-$k_{\mathrm{T}}$ jet algorithm with $|\eta_{\mathrm{jet}}|<0.7-R$.
Leading track requirements were only applied by JEWEL (as in data) and the
Hybrid model (with 5 $\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ for both
radii), for both pp and Pb–Pb collisions.

JEWEL is a Monte Carlo implementation of BDMPS jet energy loss with a parton
shower, and allows the option to include the recoiling thermal medium
particles in the jet energy (“recoil on"), or to ignore the recoiling medium
particles (“recoil off") [24]. In the case of including the recoils, the
recoil particles free stream and do not interact again with the medium. If
recoils are included, we perform background subtraction according to the
recommended option “4MomSub". JEWEL contains several free parameters that are
fixed by independent measurements, none of which use high-$p_{\mathrm{T}}$ LHC
measurements; we take $T=590$ MeV and $t_{0}=0.4$ fm/c [83]. Note that these
predictions do not include systematic uncertainties, but rather only
statistical uncertainties.

The Linear Boltzmann Transport (LBT) model implements pQCD energy loss based
on a Higher Twist gluon radiation spectrum induced by elastic scattering, and
describes the evolution of jet and recoiling medium particles through the
thermal medium with linear Boltzmann equations. An effective strong coupling
constant $\alpha_{s}$ is taken as a free parameter fit to experimental data.
The model calculations are performed according to the methods in Ref. [25]. No
systematic uncertainties were provided for this calculation.

Figure 7: Jet $R_{\mathrm{AA}}$ at $\sqrt{s_{\mathrm{NN}}}=5.02$ TeV for
$R=0.2$ (left) and $R=0.4$ (right) compared to LBT, SCETG, Hybrid model, and
JEWEL predictions. The combined $\left<T_{\mathrm{AA}}\right>$ uncertainty and
pp luminosity uncertainty of 2.8% is illustrated as a band on the dashed line
at $R_{\mathrm{AA}}=1$. Systematic uncertainties are only included for the
SCETG and Hybrid model predictions; see text for details.

Soft Collinear Effective Theory with Glauber gluons (SCETG) builds on the
approach of Soft Collinear Effective Theory (SCET), in which the jet cross-
section is factorized into a “hard function" corresponding to the initial
scattering, and a “jet function" corresponding to the fragmentation of a hard-
scattered parton into a jet. In SCETG, jet energy loss in heavy-ion collisions
is implemented by interactions of jet partons with the hot QCD medium in an
effective field theory via the exchange of “Glauber" gluons, encapsulated in
an in-medium jet function. The predictions were performed according to Ref.
[29] but with minor differences. The pp jet cross-section was computed to NLO
in $\alpha_{s}$, and with a LL resummation in jet $R$. Medium effects were
computed at NLO, but without a resummation in jet $R$ (resulting in large
systematic uncertainties for $R=0.2$). The in-medium splitting functions
described above include radiative processes evaluated using 2+1D viscous
hydrodynamics, but these predictions do not include collisional energy loss.
Note that this could have significant impact particularly on the larger radius
jets, where it may increase suppression. The EFT coupling constant between the
medium and jets is $g=2.0$. For pp collisions the CT14nlo PDF was used, and
for Pb–Pb collisions, the nCTEQ15FullNuc PDF was used. Energy loss in cold
nuclear matter was also taken into account. The plotted error band represents
the systematic uncertainty obtained by scale variations.

In the Hybrid model, partons are produced by vacuum pQCD, and shower according
to vacuum pQCD – but in between these hard splittings, parton energy loss is
modeled according to a gauge-gravity duality computation in $N=4$
Supersymmetric Yang-Mills at infinitely strong coupling and large $N_{c}$.
Model predictions were provided with two values of $L_{res}$, which describes
the scale at which the medium can resolve two split partons. The medium
evolution was modeled by a hydrodynamic expansion. The plotted error bands
represent the combination of statistical and systematic uncertainties.

All models exhibit strong suppression, and produce the same qualitative trend
of $R_{\mathrm{AA}}$ as a function of $p_{\mathrm{T,jet}}$. In the case
$R=0.2$, JEWEL under-predicts the jet $R_{\mathrm{AA}}$, and appears to be
inconsistent with the data regardless of whether medium recoils are included,
while for $R=0.4$ the “recoils on" prediction is more consistent with the
data. There is no significant difference between the “recoil on" or “recoil
off" option in JEWEL for $R=0.2$; one expects in general a smaller impact from
medium recoil in smaller radius jets. The LBT model describes the data better,
although it has slight tension with the data. Note that the dominant
systematic uncertainties in the data are positively correlated between
$p_{\mathrm{T,jet}}$ bins. Neither the JEWEL nor LBT predictions include
systematic uncertainties. The SCETG predictions are consistent with the data,
although the $R=0.2$ prediction has large systematic uncertainties due to a
lack of in-medium $\ln R$ re-summation in this calculation. Additionally, the
SCETG calculation did not include collisional energy loss, which may under-
estimate suppression for $R=0.4$. The Hybrid model describes the trend of the
data reasonably well, although like the LBT model, exhibits slight tension
particularly in the $p_{\mathrm{T,jet}}<100$
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$ range. The shapes of the
$p_{\mathrm{T,jet}}$-dependence differ between the model predictions, most
notably between SCETG and the others. While the experimental uncertainties are
larger for $R=0.4$, the model predictions span a wider range of
$R_{\mathrm{AA}}$ than in the case of $R=0.2$, which highlights the importance
of measuring the $R$-dependence of the jet $R_{\mathrm{AA}}$.

Figure 8: Jet $R_{\mathrm{AA}}$ in 0-10% central Pb–Pb collisions for $R=0.2$
(left) and $R=0.4$ (right) for all currently published experimental results.
Closed markers denote $\sqrt{s_{\mathrm{NN}}}=5.02$ TeV, and open markers
denote $\sqrt{s_{\mathrm{NN}}}=2.76$ TeV.

The predictions typically use different strategies for each of the “non jet
energy loss" pieces (initial state, expansion, hadronization, pp reference
spectrum), and do not attempt to incorporate these differences in a systematic
uncertainty, which makes a strict quantitative comparison to data difficult.
Moreover, the models fix their free parameters in different ways; JEWEL has
not been fit to high-$p_{\mathrm{T,jet}}$ LHC data, and so it faces the
strictest test of all the models presented. This necessitates investigation of
complementary jet observables and global analyses, but it also highlights the
need to standardize the ingredients of jet energy loss calculations [84]. The
data presented here provide important constraints at low-$p_{\mathrm{T,jet}}$
on current models as well as for future global analyses.

Figure 8 shows a comparison of the results in Fig. 6 (top) to all currently
published experimental results of 0-10% central jet $R_{\mathrm{AA}}$ for
$R=0.2$ and $R=0.4$. This comparison broadly illustrates that there is no
clear $R$-dependence or $\sqrt{s}$-dependence of the jet $R_{\mathrm{AA}}$
within current experimental precision. We do not attempt to comment on the
comparison of theoretical models with global experimental results, which is
beyond the scope of this article.

##  7 Conclusion

We measured the transverse momentum ($p_{\mathrm{T}}$) spectrum of jets in pp
collisions at $\sqrt{s}=5.02$ TeV and Pb–Pb collisions at
$\sqrt{s_{\mathrm{NN}}}=5.02$ TeV, as well as the jet nuclear modification
factor ($R_{\mathrm{AA}}$), using charged particles from the tracking system
combined with particle information from the electromagnetic calorimeter. We
measured the inclusive jet cross-section in pp collisions for jet resolution
parameters $R=0.1-0.6$, which is the largest collection of full jet $R$
measured by ALICE to date. We compared these measurements to theoretical
predictions at next-to-leading-order (NLO) including either a resummation of
large logarithms or a matched parton shower. Both predictions describe the
data well except with slight tension at low-$p_{\mathrm{T,jet}}$ for the
resummation-based prediction, which may be due to either the perturbative
calculation or the large non-perturbative corrections at
low-$p_{\mathrm{T,jet}}$. We also presented the ratios of jet cross-sections
of various $R$, which leverage partial cancellation of systematic
uncertainties to obtain high-precision constraints on the $R$-dependence of
the cross-section; the two models considered generally describe these ratios
well. These data, spanning a large range of $R$ down to low-$p_{\mathrm{T}}$,
contain sensitivities to different non-perturbative effects (from
hadronization dominated at small $R$ to underlying event dominated at large
$R$) and can be used to constrain the contributions of pQCD, hadronization,
and underlying event effects on the inclusive jet cross-section. These data
can further be used to constrain parton distribution functions and the strong
coupling constant.

We measured the jet spectrum in Pb–Pb collisions for $R=0.2$ and $R=0.4$,
which constitutes the first 0–10% jet $R_{\mathrm{AA}}$ measurements at
$\sqrt{s_{\mathrm{NN}}}=5.02$ TeV at $p_{\mathrm{T,jet}}<100$
$\mathrm{GeV}\kern-0.50003pt/\kern-0.20004ptc$, and the first inclusive jet
$R_{\mathrm{AA}}$ measurements by ALICE extending to $R=0.4$ at any collision
energy. The measured jet spectrum in Pb–Pb collisions exhibits strong
suppression compared to pp collisions, and for $R=0.2$ the data show stronger
suppression at lower $p_{\mathrm{T,jet}}$ than at higher $p_{\mathrm{T,jet}}$.
There is no significant $R$-dependence of the jet $R_{\mathrm{AA}}$ within the
uncertainties of the measurement. Models are able to generally describe the
trends of the data, but several models exhibit hints of disagreement with the
measurements. These data provide additional constraints on jet quenching
models in heavy-ion collisions, which can be used to extract medium properties
such as the transverse momentum diffusion parameter, $\hat{q}$, as a function
of the medium temperature and the jet $p_{\mathrm{T}}$.

## Acknowledgements

The ALICE Collaboration would like to thank all its engineers and technicians for their invaluable contributions to the construction of the experiment and the CERN accelerator teams for the outstanding performance of the LHC complex. The ALICE Collaboration gratefully acknowledges the resources and support provided by all Grid centres and the Worldwide LHC Computing Grid (WLCG) collaboration. The ALICE Collaboration acknowledges the following funding agencies for their support in building and running the ALICE detector: A. I. Alikhanyan National Science Laboratory (Yerevan Physics Institute) Foundation (ANSL), State Committee of Science and World Federation of Scientists (WFS), Armenia; Austrian Academy of Sciences, Austrian Science Fund (FWF): [M 2467-N36] and Nationalstiftung für Forschung, Technologie und Entwicklung, Austria; Ministry of Communications and High Technologies, National Nuclear Research Center, Azerbaijan; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Financiadora de Estudos e Projetos (Finep), Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) and Universidade Federal do Rio Grande do Sul (UFRGS), Brazil; Ministry of Education of China (MOEC) , Ministry of Science & Technology of China (MSTC) and National Natural Science Foundation of China (NSFC), China; Ministry of Science and Education and Croatian Science Foundation, Croatia; Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN), Cubaenergía, Cuba; Ministry of Education, Youth and Sports of the Czech Republic, Czech Republic; The Danish Council for Independent Research | Natural Sciences, the VILLUM FONDEN and Danish National Research Foundation (DNRF), Denmark; Helsinki Institute of Physics (HIP), Finland; Commissariat à l’Energie Atomique (CEA), 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), Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) and Japan Society for the Promotion of Science (JSPS) KAKENHI, Japan; Consejo Nacional de Ciencia (CONACYT) y Tecnología, through Fondo de Cooperación Internacional en Ciencia y Tecnología (FONCICYT) and Dirección General de Asuntos del Personal Academico (DGAPA), Mexico; Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO), Netherlands; The Research Council of Norway, Norway; Commission on Science and Technology for Sustainable Development in the South (COMSATS), Pakistan; Pontificia Universidad Católica del Perú, Peru; Ministry of 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; Suranaree University of Technology (SUT), National Science and Technology Development Agency (NSDTA) 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. We gratefully acknowledge Hai Tao Li, Xiaohui Liu, Daniel Pablos, Felix Ringer, Ivan Vitev, and Xin-Nian Wang for providing theoretical predictions.

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##  Appendix A The ALICE Collaboration

S. Acharyaorg141&D. Adamováorg93&A. Adlerorg73&J. Adolfssonorg79&M.M.
Aggarwalorg98&G. Aglieri Rinellaorg34&M. Agnelloorg31&N. Agrawalorg10,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. 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&D. Bauriorg48&J.L. Bazo Albaorg110&I.G. Beardenorg87&C.
Beddaorg63&N.K. Beheraorg60&I. Belikovorg136&A.D.C. Bell Hechavarriaorg144&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&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&H. Bossiorg146&E. Bottaorg26&L. Bratrudorg68&P. Braun-
Munzingerorg105&M. Bregantorg121&T.A. Brokerorg68&M. Brozorg37&E.J.
Bruckenorg43&E. Brunaorg58&G.E. Brunoorg104&M.D. Bucklandorg127&D.
Budnikovorg107&H. Bueschingorg68&S. Bufalinoorg31&O. Bugnonorg114&P.
Buhlerorg113&P. Buncicorg34&Z. Butheleziorg72,org131&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,org27&R. Caronorg137&J. Castillo Castellanosorg137&A.J.
Castroorg130&E.A.R. Casulaorg54&F. Catalanoorg31&C. Ceballos Sanchezorg52&P.
Chakrabortyorg48&S. Chandraorg141&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&P. Crochetorg134&E. Cuautleorg69&P. Cuiorg6&L.
Cunqueiroorg94&D. Dabrowskiorg142&T. Dahmsorg103,org117&A. Daineseorg56&F.P.A.
Damasorg114,org137&M.C. Danischorg102&A. Danuorg67&D. Dasorg108&I.
Dasorg108&P. Dasorg84&P. Dasorg3&S. Dasorg3&A. Dashorg84&S. Dashorg48&A.
Dashiorg103&S. Deorg84&A. De Caroorg30&G. de Cataldoorg52&C. de Contiorg121&J.
de Cuvelandorg39&A. De Falcoorg24&D. De Gruttolaorg10&N. De Marcoorg58&S. De
Pasqualeorg30&S. Deborg49&B. Debjaniorg3&H.F. Degenhardtorg121&K.R.
Dejaorg142&A. Delofforg83&S. Delsantoorg26,org131&D. Devetakorg105&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&V.N. Eikelandorg22&D. Eliaorg52&H.
Engelorg73&E. Eppleorg146&B. Erazmusorg114&F. Erhardtorg97&A.
Erokhinorg112&M.R. Ersdalorg22&B. Espagnonorg61&G. Eulisseorg34&D.
Evansorg109&S. Evdokimovorg89&L. Fabbiettiorg103,org117&M. Fagginorg29&J.
Faivreorg77&F. Fanorg6&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&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&F. Grosaorg31&J.F. Grosse-Oetringhausorg34&R. Grossoorg105&R.
Guernaneorg77&M. Guittiereorg114&K. Gulbrandsenorg87&T. Gunjiorg132&A.
Guptaorg99&R. Guptaorg99&I.B. Guzmanorg44&R. Haakeorg146&M.K. Habiborg105&C.
Hadjidakisorg61&H. Hamagakiorg80&G. Hamarorg145&M. Hamidorg6&R.
Hanniganorg119&M.R. Haqueorg63,org84&A. Harlenderovaorg105&J.W.
Harrisorg146&A. Hartonorg11&J.A. Hasenbichlerorg34&D.
Hatzifotiadouorg10,org53&P. Hauerorg42&S. Hayashiorg132&S.T.
Heckelorg68,org103&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&A. Hornungorg68&S. Hornungorg105&R.
Hosokawaorg16,org133&P. Hristovorg34&C. Huangorg61&C. Hughesorg130&P.
Huhnorg68&T.J. Humanicorg95&H. Hushnudorg108&L.A. Husovaorg144&N.
Hussainorg41&S.A. Hussainorg15&D. Hutterorg39&J.P. Iddonorg34,org127&R.
Ilkaevorg107&M. Inabaorg133&G.M. Innocentiorg34&M. Ippolitovorg86&A.
Isakovorg93&M.S. Islamorg108&M. Ivanovorg105&V. Ivanovorg96&V.
Izucheevorg89&B. Jacakorg78&N. Jacazioorg27,org53&P.M. Jacobsorg78&M.B.
Jadhavorg48&S. Jadlovskaorg116&J. Jadlovskyorg116&S. Jaelaniorg63&C.
Jahnkeorg121&M.J. Jakubowskaorg142&M.A. Janikorg142&M. Jercicorg97&O.
Jevonsorg109&M. Jinorg125&F. Jonasorg94,org144&P.G. Jonesorg109&J.
Jungorg68&M. Jungorg68&A. Juskoorg109&P. Kalinakorg64&A. Kalweitorg34&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.
Khuntiaorg118&B. Kilengorg36&B. Kimorg60&B. Kimorg133&D. Kimorg147&D.J.
Kimorg126&E.J. Kimorg13&H. Kimorg18,org147&J. Kimorg147&J.S. Kimorg40&J.
Kimorg102&J. Kimorg147&J. Kimorg13&M. Kimorg102&S. Kimorg19&T. Kimorg147&T.
Kimorg147&S. Kirschorg39,org68&I. Kiselorg39&S. Kiselevorg90&A.
Kisielorg142&J.L. Klayorg5&C. Kleinorg68&J. Kleinorg58&S. Kleinorg78&C. Klein-
Bösingorg144&M. Kleinerorg68&S. Klewinorg102&A. Klugeorg34&M.L.
Knichelorg34&A.G. Knospeorg125&C. Kobdajorg115&M.K. Köhlerorg102&T.
Kolleggerorg105&A. Kondratyevorg74&N. Kondratyevaorg91&E. Kondratyukorg89&J.
Konigorg68&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&A.
Kuryakinorg107&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&A. Lardeuxorg21&P. Larionovorg51&E. Laudiorg34&R.
Lavickaorg37&T. Lazarevaorg112&R. Leaorg25&L. Leardiniorg102&J. Leeorg133&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&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&J.R. Luhderorg144&M. Lunardonorg29&G. Luparelloorg59&Y. Maorg111&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&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. Mastroserioorg52,org138&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. Melikyanorg62,org91&A. Menchaca-Rochaorg71&C. Mengkeorg6&E.
Meninnoorg30,org113&M. Meresorg14&S. Mhlangaorg124&Y. Miakeorg133&L.
Michelettiorg26&D.L. Mihaylovorg103&K. Mikhaylovorg74,org90&A.
Mischkeorg63org*&A.N. Mishraorg69&D. Miśkowiecorg105&A. Modakorg3&N.
Mohammadiorg34&A.P. Mohantyorg63&B. Mohantyorg84&M. Mohisin Khanorg17orgIII&C.
Mordasiniorg103&D.A. Moreira De Godoyorg144&L.A.P. Morenoorg44&I.
Morozovorg62&A. Morschorg34&T. Mrnjavacorg34&V. Mucciforaorg51&E.
Mudnicorg35&D. Mühlheimorg144&S. Muhuriorg141&J.D. Mulliganorg78&M.G.
Munhozorg121&K. Münningorg42&R.H. Munzerorg68&H. Murakamiorg132&S.
Murrayorg124&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&C. Nattrassorg130&R.
Nayakorg48&T.K. Nayakorg84&S. Nazarenkoorg107&A. Neaguorg21&R.A. Negrao De
Oliveiraorg68&L. Nellenorg69&S.V. Nesboorg36&G. Neskovicorg39&D.
Nesterovorg112&L.T. Neumannorg142&B.S. Nielsenorg87&S. Nikolaevorg86&S.
Nikulinorg86&V. Nikulinorg96&F. Noferiniorg10,org53&P. Nomokonovorg74&J.
Normanorg77&N. Novitzkyorg133&P. Nowakowskiorg142&A. Nyaninorg86&J.
Nystrandorg22&M. Oginoorg80&A. Ohlsonorg79,org102&J. Oleniaczorg142&A.C.
Oliveira Da Silvaorg121,org130&M.H. Oliverorg146&C. Oppedisanoorg58&R.
Oravaorg43&A. Ortiz Velasquezorg69&A. Oskarssonorg79&J. Otwinowskiorg118&K.
Oyamaorg80&Y. Pachmayerorg102&V. Pacikorg87&D. Paganoorg140&G. Paićorg69&J.
Panorg143&A.K. Pandeyorg48&S. Panebiancoorg137&P. Pareekorg49,org141&J.
Parkorg60&J.E. Parkkilaorg126&S. Parmarorg98&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. Pisanoorg10,org51&D. Pistoneorg55&M. Płoskońorg78&M.
Planinicorg97&F. Pliquettorg68&J. Plutaorg142&S. Pochybovaorg145org*&M.G.
Poghosyanorg94&B. Polichtchoukorg89&N. Poljakorg97&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&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&R. Rathorg49&V. Ratzaorg42&I.
Ravasengaorg31&K.F. Readorg94,org130&K. Redlichorg83orgIV&A. Rehmanorg22&P.
Reicheltorg68&F. Reidtorg34&X. Renorg6&R. Renfordtorg68&Z.
Rescakovaorg38&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&A.
Rossiorg29,org56&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&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. Schukraftorg87&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&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&G.
Simatovicorg88&G. Simonettiorg34,org103&R. Singhorg84&R. Singhorg99&R.
Singhorg49&V.K. Singhorg141&V. Singhalorg141&T. Sinhaorg108&B. Sitarorg14&M.
Sittaorg32&T.B. Skaaliorg21&M. Slupeckiorg126&N. Smirnovorg146&R.J.M.
Snellingsorg63&T.W. Snellmanorg43,org126&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&L.D.
Strittoorg30&A.A.P. Suaideorg121&T. Sugitateorg45&C. Suireorg61&M.
Suleymanovorg15&M. Suljicorg34&R. Sultanovorg90&M. Šumberaorg93&S.
Sumowidagdoorg50&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. Terrevoliorg125&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. Torresorg9,org120&A. Trifiroorg55&S.
Tripathyorg49&T. Tripathyorg48&S. Trogoloorg29&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&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&M. Vasileiouorg82&A. Vasilievorg86&O. Vázquez
Doceorg103,org117&V. Vecherninorg112&A.M. Veenorg63&E. Vercellinorg26&S.
Vergara Limónorg44&L. Vermuntorg63&R. Vernetorg7&R. Vértesiorg145&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&M. Weberorg113&S.G. Weberorg105,org144&A. Wegrzynekorg34&D.F.
Weiserorg102&S.C. Wenzelorg34&J.P. Wesselsorg144&J. Wiechulaorg68&J.
Wikneorg21&G. Wilkorg83&J. Wilkinsonorg10,org53&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&I.-K. Yooorg18&J.H. Yoonorg60&S. Yuanorg22&A. Yuncuorg102&V.
Yurchenkoorg2&V. Zaccoloorg25&A. Zamanorg15&C. Zampolliorg34&H.J.C.
Zanoliorg63,org121&N. Zardoshtiorg34&A. Zarochentsevorg112&P. Závadaorg66&N.
Zaviyalovorg107&H. Zbroszczykorg142&M. Zhalovorg96&S. Zhangorg111&X.
Zhangorg6&Z. Zhangorg6&V. Zherebchevskiiorg112&N. Zhigarevaorg90&D.
Zhouorg6&Y. Zhouorg87&Z. Zhouorg22&J. Zhuorg6,org105&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

org84National Institute of Science Education and Research, Homi Bhabha
National Institute, Jatni, India

org85National Nuclear Research Center, Baku, Azerbaijan

org86National Research Centre Kurchatov Institute, Moscow, Russia

org87Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark

org88Nikhef, National institute for subatomic physics, Amsterdam, Netherlands

org89NRC Kurchatov Institute IHEP, Protvino, Russia

org90NRC «Kurchatov Institute» - ITEP, Moscow, Russia

org91NRNU Moscow Engineering Physics Institute, Moscow, Russia

org92Nuclear Physics Group, STFC Daresbury Laboratory, Daresbury, United
Kingdom

org93Nuclear Physics Institute of the Czech Academy of Sciences, Řež u Prahy,
Czech Republic

org94Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States

org95Ohio State University, Columbus, Ohio, United States

org96Petersburg Nuclear Physics Institute, Gatchina, Russia

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

org98Physics Department, Panjab University, Chandigarh, India

org99Physics Department, University of Jammu, Jammu, India

org100Physics Department, University of Rajasthan, Jaipur, India

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

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

org103Physik Department, Technische Universität München, Munich, Germany

org104Politecnico di Bari, Bari, Italy

org105Research Division and ExtreMe Matter Institute EMMI, GSI
Helmholtzzentrum für Schwerionenforschung GmbH, Darmstadt, Germany

org106Rudjer Bošković Institute, Zagreb, Croatia

org107Russian Federal Nuclear Center (VNIIEF), Sarov, Russia

org108Saha Institute of Nuclear Physics, Homi Bhabha National Institute,
Kolkata, India

org109School of Physics and Astronomy, University of Birmingham, Birmingham,
United Kingdom

org110Sección Física, Departamento de Ciencias, Pontificia Universidad
Católica del Perú, Lima, Peru

org111Shanghai Institute of Applied Physics, Shanghai, China

org112St. Petersburg State University, St. Petersburg, Russia

org113Stefan Meyer Institut für Subatomare Physik (SMI), Vienna, Austria

org114SUBATECH, IMT Atlantique, Université de Nantes, CNRS-IN2P3, Nantes,
France

org115Suranaree University of Technology, Nakhon Ratchasima, Thailand

org116Technical University of Košice, Košice, Slovakia

org117Technische Universität München, Excellence Cluster ’Universe’, Munich,
Germany

org118The Henryk Niewodniczanski Institute of Nuclear Physics, Polish Academy
of Sciences, Cracow, Poland

org119The University of Texas at Austin, Austin, Texas, United States

org120Universidad Autónoma de Sinaloa, Culiacán, Mexico

org121Universidade de São Paulo (USP), São Paulo, Brazil

org122Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil

org123Universidade Federal do ABC, Santo Andre, Brazil

org124University of Cape Town, Cape Town, South Africa

org125University of Houston, Houston, Texas, United States

org126University of Jyväskylä, Jyväskylä, Finland

org127University of Liverpool, Liverpool, United Kingdom

org128University of Science and Techonology of China, Hefei, China

org129University of South-Eastern Norway, Tonsberg, Norway

org130University of Tennessee, Knoxville, Tennessee, United States

org131University of the Witwatersrand, Johannesburg, South Africa

org132University of Tokyo, Tokyo, Japan

org133University of Tsukuba, Tsukuba, Japan

org134Université Clermont Auvergne, CNRS/IN2P3, LPC, Clermont-Ferrand, France

org135Université de Lyon, Université Lyon 1, CNRS/IN2P3, IPN-Lyon,
Villeurbanne, Lyon, France

org136Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000 Strasbourg,
France, Strasbourg, France

org137Université Paris-Saclay Centre d’Etudes de Saclay (CEA), IRFU,
Départment de Physique Nucléaire (DPhN), Saclay, France

org138Università degli Studi di Foggia, Foggia, Italy

org139Università degli Studi di Pavia, Pavia, Italy

org140Università di Brescia, Brescia, Italy

org141Variable Energy Cyclotron Centre, Homi Bhabha National Institute,
Kolkata, India

org142Warsaw University of Technology, Warsaw, Poland

org143Wayne State University, Detroit, Michigan, United States

org144Westfälische Wilhelms-Universität Münster, Institut für Kernphysik,
Münster, Germany

org145Wigner Research Centre for Physics, Budapest, Hungary

org146Yale University, New Haven, Connecticut, United States

org147Yonsei University, Seoul, Republic of Korea