Measurement of the underlying event activity in inclusive Z boson production in proton-proton collisions at $ \sqrt{s}=13 $ TeV

(1)

CERN-EP-2017-249 2018/07/11

CMS-FSQ-16-008

Measurement of the underlying event activity in inclusive

Z boson production in proton-proton collisions at

_√

s

=

13 TeV

The CMS Collaboration

∗

Abstract

This paper presents a measurement of the underlying event activity in proton-proton collisions at a center-of-mass energy of 13 TeV, performed using inclusive Z boson production events collected with the CMS experiment at the LHC. The analyzed data correspond to an integrated luminosity of 2.1 fb−1. The underlying event activity is quantified in terms of the charged particle multiplicity, as well as of the scalar sum of the charged particles’ transverse momenta in different topological regions defined with respect to the Z boson direction. The distributions are unfolded to the stable particle level and compared with predictions from various Monte Carlo event gener-ators, as well as with similar CDF and CMS measurements at center-of-mass energies of 1.96 and 7 TeV respectively.

Published in the Journal of High Energy Physics as doi:10.1007/JHEP07(2018)032.

c

2018 CERN for the benefit of the CMS Collaboration. CC-BY-4.0 license

∗_{See Appendix A for the list of collaboration members}

(2)

(3)

1 Introduction

The production of particles in a hadron-hadron collision includes contributions from parton-parton scatterings, initial-state radiation (ISR), final-state radiation (FSR), and beam-beam rem-nant (BBR) interactions. The large parton densities accessible in proton-proton (pp) collisions at the CERN LHC result in a significant probability of more than one parton-parton scattering in the same pp collision, a phenomenon known as multiple parton interactions (MPI). The combi-nation of particle production from MPI (excluding the parton-parton scattering with the highest momentum transfer) and BBR interactions is commonly called the underlying event (UE). The

UE usually produces particles at low transverse momentum (pT) that cannot be experimentally

distinguished from the particles produced from ISR and FSR. These processes cannot be com-pletely described by perturbative quantum chromodynamics (QCD) calculations, and require phenomenological models, whose parameters are tuned by means of fits to data.

The experimental measurement of the UE is often based on a process that defines the scale of the hardest parton-parton scattering, along with a phase space region with enhanced sensitiv-ity to particle production associated with the UE activsensitiv-ity. A number of measurements [1–9] have been performed by the Tevatron and LHC experiments at various center-of-mass ener-gies, ranging from 0.3 TeV to 13 TeV, and using a variety of hard processes including events with high-pTcharged particles or jets, Z+jets, and tt+jets. Measurements of the UE associated

with different hard processes are useful to test the level of universality of the underlying MPI dynamics. Events with a harder scale are expected to correspond, on average, to proton-proton interactions with a smaller impact parameter and therefore with more MPI [10]. Such increased UE activity is observed to plateau at high energy scales, which indicates that the smallest im-pact parameters have been reached and hence maximum matter overlap in the pp collision [11].

This paper presents a measurement of the UE activity based on events with inclusive Z →

µ+µ−production at √

s =13 TeV. Underlying event measurements based on Z boson

produc-tion have been carried out previously at √s = 1.96 TeV [9] and 7 TeV [3, 8] by Tevatron and

LHC experiments. Z boson production is a process with a clean experimental signature and well understood theoretically, allowing clear identification of the UE activity. Measurements with Z bosons also make it possible to partially distinguish the MPI and ISR/FSR contribu-tions [3, 12]. In this paper, the properties of the UE are measured as a function of conventional observables related to the impact parameter of the pp collision, such as the number of charged particles and the scalar sum of their pT. The data are corrected for detector effects and

com-pared to Monte Carlo (MC) event generators, as well as with earlier results at√s=1.96 TeV [9] and 7 TeV [3].

The outline of the paper is as follows. Section 2 describes the data and simulated samples used for the validation and unfolding studies. Section 3 gives a brief description of the CMS detector, whereas Section 4 describes the event and track selection criteria, and the observables used for quantification of the UE. The unfolding procedure and systematic effects are discussed in Section 5, and the final results are presented in Section 6. Finally, the analysis is summarized in Section 7.

2 Data and simulated samples

The analysis is performed on a sample of pp collisions at √s = 13 TeV, corresponding to an

integrated luminosity of 2.1 fb−1. Data were collected with the CMS detector in 2015 when the average number of inelastic collisions per bunch crossing (pileup) was about 20.

(4)

For the evaluation of the event and track selection efficiencies, signal and background pro-cesses are simulated at next-to-leading order (NLO) accuracy withMC@NLO2.2.2 [13] and, for

single top production, withPOWHEG 2.0 [14, 15]. To study the model dependence, the Z+jets

events are also simulated at leading order (LO) with MADGRAPH5 2.2.2 [16, 17] combined with

PYTHIA8 [18] using the CUET8PM1 [19] tune. Diboson (WW, WZ and ZZ) as well as

multiple-jet production, via strong interaction processes, are generated at LO withPYTHIA8 standalone. The NNPDF3.0 [20] set is used as the default set of parton distribution functions (PDFs) for all generated LO and NLO samples.

These simulated samples are processed and reconstructed in the same manner as the collision

data. The detector response is simulated in detail by using the GEANT4 package [21]. The

samples include additional pileup pp interactions, with a multiplicity distribution matching that observed in data.

The measured UE distributions are unfolded to correct for detector effects and selection effi-ciencies, and compared to various MC simulation predictions:

• MADGRAPH+PYTHIA8: Z+jets events are generated with MADGRAPH, followed by

parton showering and hadronization withPYTHIA8 (CUET8PM1 tune). The MAD

-GRAPHgenerator includes up to 4 partons in the matrix element calculations, while

additional jets can be generated byPYTHIA8 during parton showering.

• POWHEG + PYTHIA8: Z+jets events are produced up to NLO accuracy with the

POWHEG ‘Multiscale-improved NLO’ method [15]. ThePYTHIA8 generator assumes

pT-ordered parton showers, and the latter are interleaved with MPI. Tune CUET8PM1

is used for hadronization and parton showering. To quantify the effect of MPI, events are also simulated without MPI. To study the impact of color-reconnection (CR) between final state partons,PYTHIA8 events are also simulated without CR.

• POWHEG+HERWIG++: To further investigate the model dependence,POWHEG

events are also hadronized using HERWIG++ [22] with tune EE5C [19]. HERWIG++,

unlike PYTHIA8, generates angular-ordered parton showers. It simulates MPI

ac-cording to a model similar to that ofPYTHIA8, with tunable parameters for the reg-ularization of the parton-parton cross section at very low momentum transfers, but without the interleaving with parton showers. In most models, the number of MPI follows a Poission distribution with a mean that depends on the overlap of the mat-ter distributions of the hadrons.

Monte Carlo events are generated at√s= 7 and 13 TeV, as well as for proton-antiproton colli-sions at√s=1.96 TeV.

3 The CMS detector

The central feature of the CMS apparatus is a superconducting solenoid of 6 m internal diam-eter. Within the solenoid volume are a silicon pixel and strip tracker, a lead tungstate crystal electromagnetic calorimeter, and a brass and scintillator hadron calorimeter, each composed of a barrel and two endcap sections. Forward calorimeters extend the pseudorapidity coverage provided by the barrel and endcap detectors. Muons are measured in gas-ionization detec-tors embedded in the steel flux-return yoke outside the solenoid, covering the pseudorapidity range|η| < 2.4, with detection planes based on three technologies: drift tubes, cathode strip chambers, and resistive-plate chambers.

(5)

silicon pixel and 15 148 silicon strip detector modules and is located in the 3.8 T field of the superconducting solenoid. For nonisolated particles of 1 < pT < 10 GeV and |η| < 1.4, the track resolutions are typically 1.5% in pTand 25–90 (45–150) µm in the transverse (longitudinal)

impact parameter [23]. Matching muons to tracks measured in the silicon tracker results in a relative pT resolution for muons with 20 < pT < 100 GeV of 1.3–2.0% in the barrel and better

than 6% in the endcaps. The pT resolution in the barrel is better than 10% for muons with pT

up to 1 TeV [24].

A more detailed description of the CMS detector, together with a definition of the coordinate system used and the relevant kinematic variables, can be found in Ref. [25].

4 Experimental methods

4.1 Event selection

Events are selected online by requiring the presence of at least two isolated muon candidates with pT >17(8)GeV for the leading (subleading) muon. Offline, events are required to have at

least one well-reconstructed vertex [23] within±24 cm of the nominal interaction point along the z-direction. At least five tracks are required to be associated with the vertex, which should be at most 2 cm from the beam axis in the transverse plane. Muons are reconstructed with the particle-flow algorithm [26] and are required to satisfy identification criteria based on the number of hits in the muon detectors and tracker, the transverse impact parameter with respect

to the beam axis, and the normalized χ2 of the global muon track fit. The backgrounds from

jets misidentified as muons and from semileptonic decays of heavy quarks are suppressed by applying an isolation condition on the muon candidates. The relative isolation variable, Irel, for

muons is defined as: Irel=

[∑ p_Tcharged+max(0.,∑ E_Tneutral+∑ Eγ

T−0.5∑ pPUT )]

pµ_T . (1)

Here ∑ E_Tneutral and ∑ Eγ_T are the sums of the transverse energies of neutral

hadrons and photons, respectively, in a pseudorapidity-azimuth cone of size ∆R ≡

√

(ηµ−ηneutral,γ)2+ (φµ−φneutral,γ)2 < 0.4 around the muon direction. The quantity

∑ pcharged

T represents the pT sum of the charged hadrons, in the same cone around the muon,

associated with the selected vertex. Finally,∑ pPU_T is the pTsum of the charged hadrons, in the

same cone around the muon, not associated with the selected vertex. A muon is considered

isolated if Irel < 0.15. Misalignment in the detector geometry affects the measurement of

muons in a different manner for data and simulation. To account for this effect, different muon momentum corrections [27] are applied to data and simulated events.

Offline, the leading and subleading muons are required to have a pT larger than 20 and

10 GeV, respectively, so as to be in the region where the trigger efficiency is highest and pT

-independent [28]. These muons are required to be associated to the vertex with the largest value of the p2_T sum of the tracks belonging to it. Events with two oppositely charged muons

are further required to have an invariant mass (Mµµ) in the window 81–101 GeV. After all

the selections, a high-purity sample of Z candidates is extracted with estimated background contributions, mainly from top quark and diboson processes, below 1%. About 1.3 million Z candidate events are left in the data, which is in agreement within 5% with the NLO simulation predictions.

(6)

4.2 Track selection

All charged particles, except the selected muons, with pT > 0.5 GeV and |η| < 2 are consid-ered for the UE study. To reduce the number of incorrectly reconstructed tracks, a high-purity reconstruction algorithm [29] is used.

The distance of closest approach between the track and the selected vertex in the transverse plane and in the longitudinal direction are required to be less than three times the respective uncertainties. These requirements help reduce contamination of secondary tracks from decays of long-lived particles, photon conversions, and pileup. Tracks with poorly measured mo-menta are removed by requiring σ(pT)/pT < 5%, where σ(pT) is the uncertainty in the pT

measurement. The track selection efficiencies in the data and simulated samples agree within 4–5%.

These selected charged particle tracks are used to construct the relevant UE observables, namely the particle density andΣpT density, which are defined as follows:

• Particle density: The average number of charged particles in an event per unit∆η∆φ

area.

• Σp_Tdensity: The average of the scalar pTsum of all selected charged particles in an

event per unit∆η∆φ area.

Here,∆η = |ηZ−ηch|and∆φ = |φZ−φch|are the pseudorapidity and azimuthal separation between each charged particle and the Z boson. In order to enhance the sensitivity to the UE, observables are calculated in different phase-space regions defined with respect to the φ direction of the Z boson. These regions are classified as:

• towards region: ∆φ<60◦,

• transverse region: 60◦ <∆φ<120◦,

• away region: ∆φ>120◦.

The UE observables are studied as a function of the transverse momentum of the dimuon sys-tem (pµµ_T ).

5 Unfolding and systematic uncertainties

In order to compare data and predictions, the UE distributions are corrected to the stable parti-cle level (lifetime cτ >10 mm) with the iterative D’Agostini method [30], which also accounts for bin-to-bin migrations. In the present analysis, two-dimensional distributions are unfolded

with a response matrix constructed from events simulated with MADGRAPH+PYTHIA8.

The unfolded measured distributions may be distorted by a variety of systematic effects, as discussed below.

• Model dependence: The events simulated with MADGRAPH+PYTHIA8 reproduce

the measured pµµ_T distribution within 10–20%. The effect of this discrepancy on the final UE distributions is evaluated by reweighting the simulated sample so that it describes the measured pµµ_T distribution. These weights are applied to the re-sponse matrix used for the unfolding. The difference between the unfolded dis-tributions with and without these weight factors is 2–5%. An additional cross-check is performed by using response matrices constructed with events simulated with

the MADGRAPH + PYTHIA8 and the MC@NLO + PYTHIA8 event generators. The

(7)

constructed with these two generators is found to be less than 0.5%.

• Tracking efficiency: The tracking efficiency is known with an uncertainty of 4% [23, 31]. To estimate the effect of this uncertainty on the UE distribution, 4% of the tracks are randomly removed in the simulated events while constructing the response ma-trix. The effect on the unfolded distributions is approximately 4–6%.

• Pileup: Pileup events produce low-pTparticles that can contribute to the UE activity.

However, the effect of pileup is expected to be small in the present analysis because all tracks are required to originate from the same primary vertex. The effect of pileup is further reduced by the unfolding procedure because the simulated samples also include pileup. Any possible residual effect is evaluated by varying the pp inelastic cross section used in the simulation by 5%. The bias on the unfolded distributions is less than 0.5%.

• Trigger: The triggers used in the analysis require that the muons be isolated, which may bias the UE distributions. The effect of this requirement is evaluated by com-paring UE distributions obtained with and without the trigger requirement in the simulation. This affects the results by up to 0.1%.

• Physics background: The Z boson production events are required to be in the mass

window 81–101 GeV. In this region, there is a small (about 0.3%) contribution of dimuons from diboson and top quark decays. These background processes may bias the UE distributions because of the different event topologies and parton radi-ation patterns as compared to the Z boson events. The effect of these background processes is evaluated, using simulations, by comparing the UE distributions for the Z-boson events and for the Z-boson events combined with background processes. The UE distributions change by 0.5–1%.

• Muon momentum correction: The effect of the muon momentum corrections [27] is

studied by comparing the corrected data distributions with the ones without correc-tions. The resulting effect on the particle density is up to 0.4%, and up to 0.7% for theΣpTdensity distribution.

Table 1 summarizes the dominant systematic uncertainties in the particle and ΣpT densities.

Adding all aforementioned sources in quadrature results in a total systematic uncertainty of 4.8–7.8%, depending on the UE observable and particular bin.

Table 1: Summary of the systematic uncertainties in the particle andΣpT densities.

Observable Uncertainty (%) Model dependence 2–5 Tracking efficiency 4–6 Pileup 0.5 Trigger 0.1 Physics background 0.5–1

Muon momentum correction 0.4–0.7

Total Uncertainty 4.8–7.8

6 Results and discussion

Figure 1 shows the comparison of the measured UE activity in the towards, transverse, and away regions. The activity in the away region increases sharply with pµµ_T , but more slowly in the towards and transverse regions. This is expected as particle production in the away region is

(8)

mostly dominated by the hadronic recoil system, which is highly correlated with pµµ_T . Because of the large spatial separation, the contribution of the hadronic recoil is small in the transverse region, and becomes even smaller in the towards region. The activity in the three regions be-comes similar as pµµ_T approaches zero; this observation again corroborates the hypothesis that differences in the UE activity for the three regions are due to varying parton radiation contri-butions. Unlike the UE measurement with leading jet/track [3, 6], in the present analysis the UE activity is not zero when p_Tµµapproaches zero. This behavior reflects the fact that the initial scale in the Z boson events, given by the lepton pair invariant mass in the range 81–101 GeV, is already large enough to determine a significant overlap between the transverse parton den-sities of the colliding protons, and hence a large number of MPI. From the UE measurements using the leading charged particle (jet) approach [3, 6], it is observed that the MPI contribution reaches its maximal value at an energy scale of 5 (12–15) GeV. Above this energy, there is a slow rise in the number of particles produced, which is mainly attributed to the increase in the parton radiation contributions. In the present measurement, the minimum scale is set by the dimuon mass (81–101 GeV), which is larger than the energy where the MPI contribution satu-rates. Therefore, the increase in UE activity with pµµ_T should be mainly ascribed to the rise in the recoil hadronic contribution and associated ISR/FSR [3].

0 20 40 60 80 100 [GeV] µ µ T p 0.5 1 1.5 2 2.5 3 ] -1 [rad 〉 ch N 〈 )] φ∆ ( ∆η ∆ 1/[ CMS (13 TeV) -1 2.1 fb (GeV) < 101 µ µ 81 < M Charged particles | < 2) η > 0.5 GeV, | T (p + X -µ + µ → Z + X → pp Data (towards) Data (transverse) Data (away) 0 20 40 60 80 100 [GeV] µ µ T p 2 4 6 8 10 [GeV/rad] 〉 T p Σ 〈 )] φ∆ ( ∆η ∆ 1/[ CMS (13 TeV) -1 2.1 fb (GeV) < 101 µ µ 81 < M Charged particles | < 2) η > 0.5 GeV, | T (p + X -µ + µ → Z + X → pp Data (towards) Data (transverse) Data (away)

Figure 1: Unfolded distributions of particle density (left) andΣpTdensity (right) in Z events, as

a function of pµµ_T in the towards (∆φ<60◦), transverse (60◦ <∆φ<120◦), and away (∆φ>120◦) regions. Error bars represent the statistical and systematic uncertainties added in quadrature. Figures 2–4 present data-model comparisons of the UE distributions as a function of the Z boson pT in the away, transverse, and towards regions, respectively. The bottom panel of each

plot presents the ratio of the simulated to the measured distributions. ThePOWHEG sample,

which usesHERWIG++ for parton showering and hadronization, overestimates the UE activity

by 10–15% in all topological regions, whereas when PYTHIA8 is used the measured

distribu-tions are reproduced within 5%. The MADGRAPH sample in combination with PYTHIA8 also

reproduces the measurement within 5%. TheMC@NLOpredictions (not shown in the figures)

have the same level of agreement with the data as MADGRAPH. Color reconnection between

the produced partons influences the multiplicity and pT of final-state particles. Its global

im-pact in the measured UE observables is evaluated by comparing thePYTHIA8 predictions with

and without CR, and is found to be negligible.

To understand the evolution of the UE activity with√s, the present measurement is compared

with results obtained at√s = 1.96 TeV at the Tevatron and at 7 TeV at the LHC. As the away

(9)

considered for this specific study. Figures 5–8 show the UE activity as a function of p_Tµµ at

√

s=1.96, 7, and 13 TeV. The predictions ofPOWHEGwithPYTHIA8 as well as withHERWIG++

are also shown. The ratios of the simulations to the measurements are plotted in the bottom

panel of each plot. ThePOWHEG +PYTHIA8 predictions reproduce the measurements within

10% at√s of 1.96 TeV and 7 TeV, and within 5% at 13 TeV. The combination of POWHEGand

HERWIG++ describes the measurements within 10–15, 10–20, and 20–40% at√s of 1.96, 7, and

13 TeV, respectively.

The data show a significant increase in the UE activity with√s, which is qualitatively described by the model predictions. The collision energy evolution is quantified in Fig. 9, which shows the ratio of the UE activities at 13 and 7 TeV, and at 1.96 and 7 TeV, for the data and the simula-tions. An increase of 25–30% in particle andΣpTdensities is observed as the collision energy

in-creases from 7 to 13 TeV. This behavior is quantitatively well described byPOWHEG+PYTHIA8

andPOWHEG+HERWIG++. As the collision energy increases from 1.96 to 7 TeV, the UE activity

increases by 60–80% for both the particle andΣpT densities. Event generators predict a slower

rise, but the agreement improves at higher values of pµµ_T . The increase in particle andΣpT

den-sities from 7 to 13 TeV is consistent with that observed in the leading jet/track analyses [3, 6]. To further quantify the energy dependence of the UE activity, events with a pµµ_T smaller than

5 GeV are studied. Setting an upper limit on pµµ_T reduces the ISR and FSR contributions and

the remaining UE activity stems mainly from MPI. With the requirement pµµ_T <5 GeV, the UE activity is similar in the towards and transverse regions. Therefore, the UE activity is combined in these two regions. Figure 10 shows the UE activity, with the pµµ_T < 5 GeV requirement, as a function of√s for data compared to model predictions. There is a significant increase, by a factor 2–2.5, as the collision energy rises from 1.96 to 13 TeV, which is qualitatively reproduced

by POWHEG. The energy evolution is better described by POWHEG with PYTHIA8, whereas

hadronization withHERWIG++ overestimates the UE activity at all collision energies. The

com-parison of the distributions with and without MPI indicates that the ISR and FSR contributions, which increase slowly with center-of-mass energy, are small.

The CUETP8M1 and EE5C tunes employed here are mostly obtained from fits to minimum-bias measurements and UE measurements with leading jets or leading tracks. The fact that these tunes reproduce globally well the present data supports the hypothesis that the UE activity is independent of the hard process. The present study also confirms that the collision energy dependence of the UE activity is similar for different hard processes. Unlike UE studies with a leading track/jet, the present measurements provide new handles to better understand the evolution of ISR, FSR, and MPI contributions separately, as functions of the event energy scale and the collision energy.

7 Summary

This paper presents a measurement of the underlying event (UE) activity using inclusive Z boson production events in proton-proton collisions at a center-of-mass energy of 13 TeV. The data correspond to an integrated luminosity of 2.1 fb−1. The UE activity, quantified in terms

of charged particle and ΣpT densities, is measured as a function of the pT of the muon pair

from the Z boson decay. The distributions are corrected for detector effects and compared to

various model predictions. The MADGRAPHandPOWHEGgenerators, with parton showering

and hadronization modeled withPYTHIA8 using the CUET8PM1 tune, reproduce the

measure-ments within 5%. The combination ofPOWHEGandHERWIG++ (tune EE5C) overestimates the

(10)

at 1.96 and 7 TeV. The UE activity almost doubles as the collision energy increases from 1.96 to 13 TeV. Monte Carlo event generators provide a reasonable description of the evolution of the UE activity as the collision energy rises from 1.96 to 13 TeV, although they tend to under-estimate its increase in the 1.96–7 TeV range. The overall good description of the UE activity in Z boson events by Monte Carlo generators previously tuned to minimum-bias and leading track/jet UE measurements confirms the universality of the physical processes producing the underlying event in pp collisions at high energies.

0 20 40 60 80 100 [GeV] µ µ T p 0.8 0.9 1 1.1 1.2

MC / Data Total uncertainty

0 20 40 60 80 100 [GeV] µ µ T p 0.8 0.9 1 1.1 1.2

0 20 40 60 80 100 [GeV] µ µ T p 1 2 3 4 5 6 7 ] -1 [rad 〉 ch N 〈 )] φ∆ ( ∆η ∆ 1/[ Data MADGRAPH + PYTHIA8 POWHEG + PYTHIA8 POWHEG + HERWIG++ CMS (13 TeV) -1 2.1 fb (GeV) < 101 µ µ 81 < M Charged particles | < 2, away) η > 0.5 GeV, | T (p + X -µ + µ → Z + X → pp 0 20 40 60 80 100 [GeV] µ µ T p 0.8 0.9 1 1.1 1.2

0 20 40 60 80 100 [GeV] µ µ T p 0.8 0.9 1 1.1 1.2

0 20 40 60 80 100 [GeV] µ µ T p 2 4 6 8 10 12 14 16 18 20 [GeV/rad] 〉 T p Σ 〈 )] φ∆ ( ∆η ∆ 1/[ Data MADGRAPH + PYTHIA8 POWHEG + PYTHIA8 POWHEG + HERWIG++ CMS (13 TeV) -1 2.1 fb (GeV) < 101 µ µ 81 < M Charged particles | < 2, away) η > 0.5 GeV, | T (p + X -µ + µ → Z + X → pp

Figure 2: Unfolded distributions of particle density (left) andΣpT density (right) in Z events

in the away region as a function of pµµ_T , compared to various model predictions: MAD

-GRAPH+PYTHIA8 (dashed line),POWHEG+PYTHIA8 (solid line), andPOWHEG+HERWIG++

(dashed-dotted line). The bottom panels of each plot show the ratios of the simulations to the measured distributions. The bands in the bottom panels represent the statistical and systematic uncertainties added in quadrature.

(11)

0 20 40 60 80 100 [GeV] µ µ T p 0.8 0.9 1 1.1 1.2

0 20 40 60 80 100 [GeV] µ µ T p 0.5 1 1.5 2 2.5 3 3.5 ] -1 [rad 〉 ch N 〈 )] φ∆ ( ∆η ∆ 1/[ Data MADGRAPH + PYTHIA8 POWHEG + PYTHIA8 POWHEG + HERWIG++ CMS (13 TeV) -1 2.1 fb (GeV) < 101 µ µ 81 < M Charged particles | < 2, transverse) η > 0.5 GeV, | T (p + X -µ + µ → Z + X → pp 0 20 40 60 80 100 [GeV] µ µ T p 0.8 0.9 1 1.1 1.2

0 20 40 60 80 100 [GeV] µ µ T p 0.8 0.9 1 1.1 1.2

0 20 40 60 80 100 [GeV] µ µ T p 1 2 3 4 5 6 [GeV/rad] 〉 T p Σ 〈 )] φ∆ ( ∆η ∆ 1/[ Data MADGRAPH + PYTHIA8 POWHEG + PYTHIA8 POWHEG + HERWIG++ CMS (13 TeV) -1 2.1 fb (GeV) < 101 µ µ 81 < M Charged particles | < 2, transverse) η > 0.5 GeV, | T (p + X -µ + µ → Z + X → pp

in the transverse region as a function of pµµ_T , compared to various model predictions: MAD

(12)

0 20 40 60 80 100 [GeV] µ µ T p 0.8 0.9 1 1.1 1.2

0 20 40 60 80 100 [GeV] µ µ T p 0.5 1 1.5 2 2.5 3 ] -1 [rad 〉 ch N 〈 )] φ∆ ( ∆η ∆ 1/[ Data MADGRAPH + PYTHIA8 POWHEG + PYTHIA8 POWHEG + HERWIG++ CMS (13 TeV) -1 2.1 fb (GeV) < 101 µ µ 81 < M Charged particles | < 2, towards) η > 0.5 GeV, | T (p + X -µ + µ → Z + X → pp 0 20 40 60 80 100 [GeV] µ µ T p 0.8 0.9 1 1.1 1.2

0 20 40 60 80 100 [GeV] µ µ T p 0.8 0.9 1 1.1 1.2

0 20 40 60 80 100 [GeV] µ µ T p 0.5 1 1.5 2 2.5 3 3.5 4 4.5 [GeV/rad] 〉 T p Σ 〈 )] φ∆ ( ∆η ∆ 1/[ Data MADGRAPH + PYTHIA8 POWHEG + PYTHIA8 POWHEG + HERWIG++ CMS (13 TeV) -1 2.1 fb (GeV) < 101 µ µ 81 < M Charged particles | < 2, towards) η > 0.5 GeV, | T (p + X -µ + µ → Z + X → pp

in the towards region as a function of p_Tµµ, compared to various model predictions: MAD

(13)

0 20 40 60 80 100 [GeV] µ µ T p 0.6 0.8 1 1.2 1.4 MC / Data Total uncertainty 0 20 40 60 80 100 [GeV] µ µ T p 0.6 0.8 1 1.2 1.4

0 20 40 60 80 100 [GeV] µ µ T p 0.6 0.8 1 1.2 1.4

0 20 40 60 80 100

[GeV]

µ

T

p

0.4 0.6 0.8 1 1.2 1.4

]

-1

[rad

〉

ch

N

〈

)]

φ∆

(

∆η

∆

1/[

CMS

+ X -µ + µ → Z + X → ) p pp( Charged particles Towards pp, s = 13 TeV CMS, = 7 TeV s pp, CMS, = 1.96 TeV s , p p CDF, = 13 TeV s pp, POWHEG + PYTHIA8, = 7 TeV s pp, POWHEG + PYTHIA8, = 1.96 TeV s , p p POWHEG + PYTHIA8 = 13 TeV s pp, POWHEG + HERWIG++, = 7 TeV s pp, POWHEG + HERWIG++, = 1.96 TeV s , p p POWHEG + HERWIG++,

Figure 5: Comparison of the particle density measured in Z events at√s=13 TeV with that at 7 (CMS) [3] and 1.96 TeV (CDF) [9] in the towards region as a function of pµµ_T . The data are also

compared with the model predictions ofPOWHEG+PYTHIA8 (solid line) andPOWHEG+HER

-WIG++ (dashed-dotted line). The bottom panels of each plot show the ratios of the model

predictions to the measurements. The bands in the bottom panels represent the statistical and systematic uncertainties added in quadrature.

(14)

0 20 40 60 80 100 [GeV] µ µ T p 0.6 0.8 1 1.2 1.4

0 20 40 60 80 100

[GeV]

µ

T

p

0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2

[GeV/rad]

〉

T

p

Σ

〈

)]

φ∆

(

∆η

∆

1/[

CMS

+ X -µ + µ → Z + X → ) p pp( Charged particles Towards pp, s = 13 TeV CMS, = 7 TeV s pp, CMS, = 1.96 TeV s , p p CDF, = 13 TeV s pp, POWHEG + PYTHIA8, = 7 TeV s pp, POWHEG + PYTHIA8, = 1.96 TeV s , p p POWHEG + PYTHIA8 = 13 TeV s pp, POWHEG + HERWIG++, = 7 TeV s pp, POWHEG + HERWIG++, = 1.96 TeV s , p p POWHEG + HERWIG++,

Figure 6: Comparison of theΣpT density measured in Z events at

√

s = 13 TeV with that at 7 (CMS) [3] and 1.96 TeV (CDF) [9] in the towards region as a function of pµµ_T . The data are also

-WIG++ (dashed-dotted line). The bottom panels of each plot show the ratios of the model

predictions to the measurements. The bands in the bottom panels represent the statistical and systematic uncertainties added in quadrature.

(15)

0 20 40 60 80 100 [GeV] µ µ T p 0.6 0.8 1 1.2 1.4

0 20 40 60 80 100

[GeV]

µ

T

p

0.4 0.6 0.8 1 1.2 1.4 1.6

]

-1

[rad

〉

ch

N

〈

)]

φ∆

(

∆η

∆

1/[

CMS

+ X -µ + µ → Z + X → ) p pp( Charged particles Transverse pp, s = 13 TeV CMS, = 7 TeV s pp, CMS, = 1.96 TeV s , p p CDF, = 13 TeV s pp, POWHEG + PYTHIA8, = 7 TeV s pp, POWHEG + PYTHIA8, = 1.96 TeV s , p p POWHEG + PYTHIA8 = 13 TeV s pp, POWHEG + HERWIG++, = 7 TeV s pp, POWHEG + HERWIG++, = 1.96 TeV s , p p POWHEG + HERWIG++,

Figure 7: Comparison of the particle density measured in Z events at√s= 13 TeV with that at 7 (CMS) [3] and 1.96 TeV (CDF) [9] in the transverse region as a function of p_Tµµ. The data are also

-WIG++ (dashed-dotted line). The bottom panels of each plot show the ratios of model

pre-dictions to the measurements. The bands in the bottom panels represent the statistical and systematic uncertainties added in quadrature.

(16)

0 20 40 60 80 100 [GeV] µ µ T p 0.6 0.8 1 1.2 1.4

0 20 40 60 80 100

[GeV]

µ

T

p

0.5 1 1.5 2 2.5

[GeV/rad]

〉

T

p

Σ

〈

)]

φ∆

(

∆η

∆

1/[

CMS

+ X -µ + µ → Z + X → ) p pp( Charged particles Transverse pp, s = 13 TeV CMS, = 7 TeV s pp, CMS, = 1.96 TeV s , p p CDF, = 13 TeV s pp, POWHEG + PYTHIA8, = 7 TeV s pp, POWHEG + PYTHIA8, = 1.96 TeV s , p p POWHEG + PYTHIA8 = 13 TeV s pp, POWHEG + HERWIG++, = 7 TeV s pp, POWHEG + HERWIG++, = 1.96 TeV s , p p POWHEG + HERWIG++,

Figure 8: Comparison of theΣpTdensity measured in Z events at

√

s = 13 TeV with that at 7 (CMS) [3] and 1.96 TeV (CDF) [9] in the transverse region as a function of pµµ_T . The data are also

compared with the predictions ofPOWHEG+PYTHIA8 (solid line) andPOWHEG+HERWIG++

(dashed-dotted line). The bottom panels of each plot show the ratios of the model predictions to the measurements. The bands in the bottom panels represent the statistical and systematic uncertainties added in quadrature.

(17)

0 10 20 30 40 50 60 70 [GeV] µ µ T p 1 1.2 1.4 1.6 1.8 2 2.2 2.4 2.6 2.8 ] ) -1 [rad 〉 ch N 〈 )] φ∆ ( ∆η ∆ Ratio ( 1/[ CMS Charged particles towards + X -µ + µ → Z + X → ) p pp(

Data (13 TeV/7 TeV)

POWHEG + PYTHIA8 (13 TeV/7 TeV) POWHEG + HERWIG++ (13 TeV/7 TeV) Data (7 TeV/1.96 TeV)

POWHEG + PYTHIA8 (7 TeV/1.96 TeV) POWHEG + HERWIG++ (7 TeV/1.96 TeV)

0 10 20 30 40 50 60 70 [GeV] µ µ T p 1 1.2 1.4 1.6 1.8 2 2.2 2.4 2.6 2.8 [GeV/rad] ) 〉 T p Σ 〈 )] φ∆ ( ∆η ∆ Ratio ( 1/[ CMS Charged particles towards + X -µ + µ → Z + X → ) p pp(

Data (13 TeV/7 TeV)

0 10 20 30 40 50 60 70 [GeV] µ µ T p 1 1.2 1.4 1.6 1.8 2 2.2 2.4 2.6 2.8 ] ) -1 [rad 〉 ch N 〈 )] φ∆ ( ∆η ∆ Ratio ( 1/[ CMS Charged particles transverse + X -µ + µ → Z + X → ) p pp(

Data (13 TeV/7 TeV)

0 10 20 30 40 50 60 70 [GeV] µ µ T p 1 1.2 1.4 1.6 1.8 2 2.2 2.4 2.6 2.8 [GeV/rad] ) 〉 T p Σ 〈 )] φ∆ ( ∆η ∆ Ratio ( 1/[ CMS Charged particles transverse + X -µ + µ → Z + X → ) p pp(

Data (13 TeV/7 TeV)

Figure 9: Comparison of the increase in UE activity in Z events, from√s= 1.96 TeV (CDF) [9]

to 7 TeV (CMS) [3], with that from√s = 7 TeV (CMS) to 13 TeV (CMS) in the towards (top) and

transverse (bottom) regions. Panels on the left show the particle density, whereas panels on the right show theΣpTdensity as a function of pµµT . The data distributions are also compared with

predictions ofPOWHEG+PYTHIA8 (dashed-dotted line) andPOWHEG+HERWIG++ (solid line).

(18)

2 4 6 8 10 12 [TeV] s 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 ] -1 [rad 〉 ch N 〈 )] φ∆ ( ∆η ∆ 1/[ CMS < 5 GeV µ µ T p + X -µ + µ → Z + X → ) p pp( Charged particles ) o | < 120 φ ∆ towards+transverse (| Data POWHEG + PYTHIA8 POWHEG + HERWIG++ POWHEG + PYTHIA8, MPI OFF

2 4 6 8 10 12 [TeV] s 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 [GeV/rad] 〉 T p Σ 〈 )] φ∆ ( ∆η ∆ 1/[ CMS < 5 GeV µ µ T p + X -µ + µ → Z + X → ) p pp( Charged particles ) o | < 120 φ ∆ towards+transverse (| Data POWHEG + PYTHIA8 POWHEG + HERWIG++ POWHEG + PYTHIA8, MPI OFF

Figure 10: Average particle density (left) and average ΣpT density (right) for Z events with

p_Tµµ < 5 GeV as a function of the center-of-mass energy, measured by CMS and CDF [9] in

the combined towards + transverse regions, compared to predictions fromPOWHEG+PYTHIA8,

POWHEG + HERWIG++, and POWHEG + PYTHIA8 without MPI. The error bars represent the

statistical and systematic uncertainties added in quadrature.

Acknowledgments

We congratulate our colleagues in the CERN accelerator departments for the excellent perfor-mance of the LHC and thank the technical and administrative staffs at CERN and at other CMS institutes for their contributions to the success of the CMS effort. In addition, we grate-fully acknowledge the computing centers and personnel of the Worldwide LHC Computing Grid for delivering so effectively the computing infrastructure essential to our analyses. Fi-nally, we acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies: the Austrian Federal Min-istry of Science, Research and Economy and the Austrian Science Fund; the Belgian Fonds de la Recherche Scientifique, and Fonds voor Wetenschappelijk Onderzoek; the Brazilian Fund-ing Agencies (CNPq, CAPES, FAPERJ, and FAPESP); the Bulgarian Ministry of Education and Science; CERN; the Chinese Academy of Sciences, Ministry of Science and Technology, and Na-tional Natural Science Foundation of China; the Colombian Funding Agency (COLCIENCIAS); the Croatian Ministry of Science, Education and Sport, and the Croatian Science Foundation; the Research Promotion Foundation, Cyprus; the Secretariat for Higher Education, Science, Technology and Innovation, Ecuador; the Ministry of Education and Research, Estonian Re-search Council via IUT23-4 and IUT23-6 and European Regional Development Fund, Estonia; the Academy of Finland, Finnish Ministry of Education and Culture, and Helsinki Institute of Physics; the Institut National de Physique Nucléaire et de Physique des Particules / CNRS, and Commissariat à l’ Énergie Atomique et aux Énergies Alternatives / CEA, France; the Bundes-ministerium f ür Bildung und Forschung, Deutsche Forschungsgemeinschaft, and Helmholtz-Gemeinschaft Deutscher Forschungszentren, Germany; the General Secretariat for Research and Technology, Greece; the National Scientific Research Foundation, and National Innova-tion Office, Hungary; the Department of Atomic Energy and the Department of Science and Technology, India; the Institute for Studies in Theoretical Physics and Mathematics, Iran; the Science Foundation, Ireland; the Istituto Nazionale di Fisica Nucleare, Italy; the Ministry of

(19)

Science, ICT and Future Planning, and National Research Foundation (NRF), Republic of Ko-rea; the Lithuanian Academy of Sciences; the Ministry of Education, and University of Malaya (Malaysia); the Mexican Funding Agencies (BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI); the Ministry of Business, Innovation and Employment, New Zealand; the Pak-istan Atomic Energy Commission; the Ministry of Science and Higher Education and the Na-tional Science Centre, Poland; the Fundação para a Ciência e a Tecnologia, Portugal; JINR, Dubna; the Ministry of Education and Science of the Russian Federation, the Federal Agency of Atomic Energy of the Russian Federation, Russian Academy of Sciences, the Russian Foun-dation for Basic Research and the Russian Competitiveness Program of NRNU “MEPhI”; the Ministry of Education, Science and Technological Development of Serbia; the Secretar´ıa de Es-tado de Investigaci ón, Desarrollo e Innovaci ón, Programa Consolider-Ingenio 2010, Plan de Ciencia, Tecnolog´ıa e Innovaci ón 2013-2017 del Principado de Asturias and Fondo Europeo de Desarrollo Regional, Spain; the Swiss Funding Agencies (ETH Board, ETH Zurich, PSI, SNF, UniZH, Canton Zurich, and SER); the Ministry of Science and Technology, Taipei; the Thailand Center of Excellence in Physics, the Institute for the Promotion of Teaching Science and Tech-nology of Thailand, Special Task Force for Activating Research and the National Science and Technology Development Agency of Thailand; the Scientific and Technical Research Council of Turkey, and Turkish Atomic Energy Authority; the National Academy of Sciences of Ukraine, and State Fund for Fundamental Researches, Ukraine; the Science and Technology Facilities Council, UK; the US Department of Energy, and the US National Science Foundation.

Individuals have received support from the Marie-Curie program and the European Research Council and Horizon 2020 Grant, contract No. 675440 (European Union); the Leventis Foun-dation; the A. P. Sloan FounFoun-dation; the Alexander von Humboldt FounFoun-dation; the Belgian Fed-eral Science Policy Office; the Fonds pour la Formation `a la Recherche dans l’Industrie et dans l’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Council of Scientific and Industrial Research, India; the HOMING PLUS program of the Foun-dation for Polish Science, cofinanced from European Union, Regional Development Fund, the Mobility Plus program of the Ministry of Science and Higher Education, the National Science Center (Poland), contracts Harmonia 2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543, 2014/15/B/ST2/03998, and 2015/19/B/ST2/02861, Sonata-bis 2012/07/E/ST2/01406; the National Priorities Research Program by Qatar National Research Fund; the Programa Severo Ochoa del Principado de Asturias; the Thalis and Aristeia programs cofinanced by EU-ESF and the Greek NSRF; the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University and the Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand); the Welch Foundation, contract C-1845; and the Weston Havens Foundation (USA).

(20)

References

[1] CMS Collaboration, “Measurement of the underlying event activity at the LHC with_√

s =7 TeV and comparison with√s=0.9 TeV”, JHEP 09 (2011) 109,

doi:10.1007/JHEP09(2011)109, arXiv:1107.0330.

[2] CMS Collaboration, “Measurement of the underlying event activity using

charged-particle jets in proton-proton collisions at√s=2.76 TeV”, JHEP 09 (2015) 137, doi:10.1007/JHEP09(2015)137, arXiv:1507.07229.

[3] CMS Collaboration, “Measurement of the underlying event in the Drell–Yan process in proton-proton collisions at√s=7 TeV”, Eur. Phys. J. C 72 (2012) 2080,

doi:10.1140/epjc/s10052-012-2080-4, arXiv:1204.1411.

[4] ALICE Collaboration, “Underlying event measurements in pp collisions at√s=0.9 and

7 TeV with the ALICE experiment at the LHC”, JHEP 07 (2012) 116, doi:10.1007/JHEP07(2012)116, arXiv:1112.2082.

[5] ATLAS Collaboration, “Measurement of underlying event characteristics using charged particles in pp collisions at√s=900 GeV and 7 TeV with the ATLAS detector”, Phys. Rev. D 83 (2011) 112001, doi:10.1103/PhysRevD.83.112001, arXiv:1012.0791. [6] ATLAS Collaboration, “Measurements of underlying-event properties using neutral and

charged particles in pp collisions at 900 GeV and 7 TeV with the ATLAS detector at the LHC”, Eur. Phys. J. C 71 (2011) 1636, doi:10.1140/epjc/s10052-011-1636-z, arXiv:1103.1816.

[7] ATLAS Collaboration, “Measurement of the dependence of transverse energy production at large pseudorapidity on the hard-scattering kinematics of proton-proton collisions at_√

s =2.76 TeV with ATLAS”, Phys. Lett. B 756 (2016) 10,

doi:10.1016/j.physletb.2016.02.056, arXiv:1512.00197.

[8] ATLAS Collaboration, “Measurement of distributions sensitive to the underlying event in inclusive Z-boson production in pp collisions at√s=7 TeV with the ATLAS

detector”, Eur. Phys. J. C 74 (2014) 3195, doi:10.1140/epjc/s10052-014-3195-6,

arXiv:1409.3433.

[9] CDF Collaboration, “Studying the underlying event in Drell–Yan and high transverse momentum jet production at the Tevatron”, Phys. Rev. D 82 (2010) 034001,

doi:10.1103/PhysRevD.82.034001, arXiv:1003.3146.

[10] T. Sj ¨ostrand and M. Van Zijl, “A multiple interaction model for the event structure in hadron collisions”, Phys. Rev. D 36 (1987) 2019, doi:10.1103/PhysRevD.36.2019. [11] L. Frankfurt, M. Strikman, and C. Weiss, “Transverse nucleon structure and diagnostics

of hard parton-parton processes at LHC”, Phys. Rev. D 83 (2011) 054012,

doi:10.1103/PhysRevD.83.054012, arXiv:1009.2559.

[12] R. Kumar, M. Bansal, S. Bansal, and J. B. Singh, “New observables for multiple-parton interactions measurements using Z+jets processes at the LHC”, Phys. Rev. D 93 (2016) 054019, doi:10.1103/PhysRevD.93.054019, arXiv:1602.05392.

[13] J. Alwall et al., “The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations”, JHEP 07 (2014) 079, doi:10.1007/JHEP07(2014)079, arXiv:1405.0301.

(21)

[14] S. Frixione, P. Nason, and C. Oleari, “Matching NLO QCD computations with parton shower simulations: the powheg method”, JHEP 11 (2007) 070,

doi:10.1088/1126-6708/2007/11/070, arXiv:0709.2092.

[15] K. Hamilton, P. Nason, and G. Zanderighi, “MINLO: multi-scale improved NLO”, JHEP

10(2012) 155, doi:10.1007/JHEP10(2012)155, arXiv:1206.3572.

[16] F. Maltoni and T. Stelzer, “MadEvent: automatic event generation with MadGraph”, JHEP 02 (2003) 027, doi:10.1088/1126-6708/2003/02/027,

arXiv:hep-ph/0208156.

[17] J. Alwall et al., “MadGraph 5: going beyond”, JHEP 06 (2011) 128,

doi:10.1007/JHEP06(2011)128, arXiv:1106.0522.

[18] T. Sj ¨ostrand, S. Mrenna, and P. Z. Skands, “A brief introduction to PYTHIA 8.1”, Comput. Phys. Commun. 178 (2008) 852, doi:10.1016/j.cpc.2008.01.036,

arXiv:0710.3820.

[19] CMS Collaboration, “Event generator tunes obtained from underlying event and multiparton scattering measurements”, Eur. Phys. J. C 76 (2016) 155,

doi:10.1140/epjc/s10052-016-3988-x, arXiv:1512.00815.

[20] NNPDF Collaboration, “Parton distributions for the LHC Run II”, JHEP 04 (2015) 040, doi:10.1007/JHEP04(2015)040, arXiv:1410.8849.

[21] GEANT4 Collaboration, “GEANT4—a simulation toolkit”, Nucl. Instrum. Meth. A 506 (2003) 250, doi:10.1016/S0168-9002(03)01368-8.

[22] M. B¨ahr et al., “Herwig++ physics and manual”, Eur. Phys. J. C 58 (2008) 639, doi:10.1140/epjc/s10052-008-0798-9, arXiv:0803.0883.

[23] CMS Collaboration, “Description and performance of track and primary-vertex reconstruction with the CMS tracker”, JINST 9 (2014) P10009,

doi:10.1088/1748-0221/9/10/P10009, arXiv:1405.6569.

[24] CMS Collaboration, “Performance of CMS muon reconstruction in pp collision events at_√

s =7 TeV”, JINST 7 (2012) P10002, doi:10.1088/1748-0221/7/10/P10002,

arXiv:1206.4071.

[25] CMS Collaboration, “The CMS experiment at the CERN LHC”, JINST 3 (2008) S08004,

doi:10.1088/1748-0221/3/08/S08004.

[26] CMS Collaboration, “Particle-flow reconstruction and global event description with the CMS detector”, JINST 12 (2017) P10003, doi:10.1088/1748-0221/12/10/P10003, arXiv:1706.04965.

[27] A. Bodek et al., “Extracting muon momentum scale corrections for hadron collider experiments”, Eur. Phys. J. C 72 (2012) 2194,

doi:10.1140/epjc/s10052-012-2194-8, arXiv:1208.3710.

[28] CMS Collaboration, “The CMS trigger system”, J. Instrum. 12 (2017) P01020,

doi:10.1088/1748-0221/12/01/P01020.

[29] CMS Collaboration, “CMS tracking performance results from early LHC operation”, Eur. Phys. J. C 70 (2010) 1165, doi:10.1140/epjc/s10052-010-1491-3,

(22)

[30] G. D’Agostini, “A multidimensional unfolding method based on Bayes’ theorem”, Nucl. Instrum. Meth. A 362 (1995) 487, doi:10.1016/0168-9002(95)00274-X.

[31] CMS Collaboration, “Measurement of tracking efficiency”, CMS Physics Analysis Summary CMS-PAS-TRK-10-002, 2010.

(23)

A

The CMS Collaboration

Yerevan Physics Institute, Yerevan, Armenia

A.M. Sirunyan, A. Tumasyan

Institut f ¨ur Hochenergiephysik, Wien, Austria

W. Adam, F. Ambrogi, E. Asilar, T. Bergauer, J. Brandstetter, E. Brondolin, M. Dragicevic, J. Er ö, M. Flechl, M. Friedl, R. Fr ühwirth1, V.M. Ghete, J. Grossmann, J. Hrubec, M. Jeitler1, A. K önig, N. Krammer, I. Krätschmer, D. Liko, T. Madlener, I. Mikulec, E. Pree, D. Rabady, N. Rad, H. Rohringer, J. Schieck1, R. Sch öfbeck, M. Spanring, D. Spitzbart, J. Strauss, W. Waltenberger, J. Wittmann, C.-E. Wulz1, M. Zarucki

Institute for Nuclear Problems, Minsk, Belarus

V. Chekhovsky, V. Mossolov, J. Suarez Gonzalez

Universiteit Antwerpen, Antwerpen, Belgium

E.A. De Wolf, D. Di Croce, X. Janssen, J. Lauwers, M. Van De Klundert, H. Van Haevermaet, P. Van Mechelen, N. Van Remortel

Vrije Universiteit Brussel, Brussel, Belgium

S. Abu Zeid, F. Blekman, J. D’Hondt, I. De Bruyn, J. De Clercq, K. Deroover, G. Flouris, D. Lontkovskyi, S. Lowette, S. Moortgat, L. Moreels, A. Olbrechts, Q. Python, K. Skovpen, S. Tavernier, W. Van Doninck, P. Van Mulders, I. Van Parijs

Universit´e Libre de Bruxelles, Bruxelles, Belgium

H. Brun, B. Clerbaux, G. De Lentdecker, H. Delannoy, G. Fasanella, L. Favart, R. Goldouzian, A. Grebenyuk, G. Karapostoli, T. Lenzi, J. Luetic, T. Maerschalk, A. Marinov, A. Randle-conde, T. Seva, C. Vander Velde, P. Vanlaer, D. Vannerom, R. Yonamine, F. Zenoni, F. Zhang2

Ghent University, Ghent, Belgium

A. Cimmino, T. Cornelis, D. Dobur, A. Fagot, M. Gul, I. Khvastunov, D. Poyraz, C. Roskas, S. Salva, M. Tytgat, W. Verbeke, N. Zaganidis

Universit´e Catholique de Louvain, Louvain-la-Neuve, Belgium

H. Bakhshiansohi, O. Bondu, S. Brochet, G. Bruno, A. Caudron, S. De Visscher, C. Delaere, M. Delcourt, B. Francois, A. Giammanco, A. Jafari, M. Komm, G. Krintiras, V. Lemaitre, A. Magitteri, A. Mertens, M. Musich, K. Piotrzkowski, L. Quertenmont, M. Vidal Marono, S. Wertz

Universit´e de Mons, Mons, Belgium

N. Beliy

Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil

W.L. Ald´a J ´unior, F.L. Alves, G.A. Alves, L. Brito, M. Correa Martins Junior, C. Hensel, A. Moraes, M.E. Pol, P. Rebello Teles

Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil

E. Belchior Batista Das Chagas, W. Carvalho, J. Chinellato3_{, A. Cust ´odio, E.M. Da Costa,}

G.G. Da Silveira4, D. De Jesus Damiao, S. Fonseca De Souza, L.M. Huertas Guativa,

H. Malbouisson, M. Melo De Almeida, C. Mora Herrera, L. Mundim, H. Nogima, A. Santoro, A. Sznajder, E.J. Tonelli Manganote3, F. Torres Da Silva De Araujo, A. Vilela Pereira

Universidade Estadual Paulistaa, Universidade Federal do ABCb, S˜ao Paulo, Brazil

S. Ahujaa, C.A. Bernardesa, T.R. Fernandez Perez Tomeia, E.M. Gregoresb, P.G. Mercadanteb, S.F. Novaesa, Sandra S. Padulaa, D. Romero Abadb, J.C. Ruiz Vargasa

(24)

Institute for Nuclear Research and Nuclear Energy, Bulgarian Academy of Sci-ences, Sofia, Bulgaria

A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, M. Misheva, M. Rodozov, M. Shopova, S. Stoykova, G. Sultanov

University of Sofia, Sofia, Bulgaria

A. Dimitrov, I. Glushkov, L. Litov, B. Pavlov, P. Petkov

Beihang University, Beijing, China

W. Fang5, X. Gao5

Institute of High Energy Physics, Beijing, China

M. Ahmad, J.G. Bian, G.M. Chen, H.S. Chen, M. Chen, Y. Chen, C.H. Jiang, D. Leggat, H. Liao, Z. Liu, F. Romeo, S.M. Shaheen, A. Spiezia, J. Tao, C. Wang, Z. Wang, E. Yazgan, H. Zhang, J. Zhao

State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, China

Y. Ban, G. Chen, Q. Li, S. Liu, Y. Mao, S.J. Qian, D. Wang, Z. Xu

Universidad de Los Andes, Bogota, Colombia

C. Avila, A. Cabrera, L.F. Chaparro Sierra, C. Florez, C.F. Gonz´alez Hern´andez, J.D. Ruiz Al-varez

University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Ar-chitecture, Split, Croatia

B. Courbon, N. Godinovic, D. Lelas, I. Puljak, P.M. Ribeiro Cipriano, T. Sculac

University of Split, Faculty of Science, Split, Croatia

Z. Antunovic, M. Kovac

Institute Rudjer Boskovic, Zagreb, Croatia

V. Brigljevic, D. Ferencek, K. Kadija, B. Mesic, A. Starodumov6, T. Susa

University of Cyprus, Nicosia, Cyprus

M.W. Ather, A. Attikis, G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos, P.A. Razis, H. Rykaczewski

Charles University, Prague, Czech Republic

M. Finger7, M. Finger Jr.7

Universidad San Francisco de Quito, Quito, Ecuador

E. Carrera Jarrin

Academy of Scientific Research and Technology of the Arab Republic of Egypt, Egyp-tian Network of High Energy Physics, Cairo, Egypt

Y. Assran8,9, M.A. Mahmoud10,9, A. Mahrous11

National Institute of Chemical Physics and Biophysics, Tallinn, Estonia

R.K. Dewanjee, M. Kadastik, L. Perrini, M. Raidal, A. Tiko, C. Veelken

Department of Physics, University of Helsinki, Helsinki, Finland

P. Eerola, J. Pekkanen, M. Voutilainen

Helsinki Institute of Physics, Helsinki, Finland

J. Härk önen, T. Järvinen, V. Karimäki, R. Kinnunen, T. Lampén, K. Lassila-Perini, S. Lehti, T. Lindén, P. Luukka, E. Tuominen, J. Tuominiemi, E. Tuovinen

(25)

Lappeenranta University of Technology, Lappeenranta, Finland

J. Talvitie, T. Tuuva

IRFU, CEA, Universit´e Paris-Saclay, Gif-sur-Yvette, France

M. Besancon, F. Couderc, M. Dejardin, D. Denegri, J.L. Faure, F. Ferri, S. Ganjour, S. Ghosh, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry, I. Kucher, E. Locci, M. Machet, J. Malcles, G. Negro, J. Rander, A. Rosowsky, M. ¨O. Sahin, M. Titov

Laboratoire Leprince-Ringuet, Ecole polytechnique, CNRS/IN2P3, Universit´e Paris-Saclay, Palaiseau, France

A. Abdulsalam, I. Antropov, S. Baffioni, F. Beaudette, P. Busson, L. Cadamuro, C. Charlot, R. Granier de Cassagnac, M. Jo, S. Lisniak, A. Lobanov, J. Martin Blanco, M. Nguyen, C. Ochando, G. Ortona, P. Paganini, P. Pigard, S. Regnard, R. Salerno, J.B. Sauvan, Y. Sirois, A.G. Stahl Leiton, T. Strebler, Y. Yilmaz, A. Zabi, A. Zghiche

Universit´e de Strasbourg, CNRS, IPHC UMR 7178, F-67000 Strasbourg, France

J.-L. Agram12, J. Andrea, D. Bloch, J.-M. Brom, M. Buttignol, E.C. Chabert, N. Chanon,

C. Collard, E. Conte12, X. Coubez, J.-C. Fontaine12, D. Gel´e, U. Goerlach, M. Jansov´a, A.-C. Le Bihan, N. Tonon, P. Van Hove

Centre de Calcul de l’Institut National de Physique Nucleaire et de Physique des Partic-ules, CNRS/IN2P3, Villeurbanne, France

S. Gadrat

Université de Lyon, Université Claude Bernard Lyon 1, CNRS-IN2P3, Institut de Physique Nucléaire de Lyon, Villeurbanne, France

S. Beauceron, C. Bernet, G. Boudoul, R. Chierici, D. Contardo, P. Depasse, H. El Mamouni, J. Fay, L. Finco, S. Gascon, M. Gouzevitch, G. Grenier, B. Ille, F. Lagarde, I.B. Laktineh,

M. Lethuillier, L. Mirabito, A.L. Pequegnot, S. Perries, A. Popov13, V. Sordini,

M. Vander Donckt, S. Viret

Georgian Technical University, Tbilisi, Georgia

A. Khvedelidze7

Tbilisi State University, Tbilisi, Georgia

D. Lomidze

RWTH Aachen University, I. Physikalisches Institut, Aachen, Germany

C. Autermann, S. Beranek, L. Feld, M.K. Kiesel, K. Klein, M. Lipinski, M. Preuten, C. Schomakers, J. Schulz, T. Verlage

RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany

A. Albert, E. Dietz-Laursonn, D. Duchardt, M. Endres, M. Erdmann, S. Erdweg, T. Esch, R. Fischer, A. G ¨uth, M. Hamer, T. Hebbeker, C. Heidemann, K. Hoepfner, S. Knutzen, M. Merschmeyer, A. Meyer, P. Millet, S. Mukherjee, M. Olschewski, K. Padeken, T. Pook, M. Radziej, H. Reithler, M. Rieger, F. Scheuch, D. Teyssier, S. Th ¨uer

RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany

G. Fl ügge, B. Kargoll, T. Kress, A. K ünsken, J. Lingemann, T. M üller, A. Nehrkorn, A. Nowack, C. Pistone, O. Pooth, A. Stahl14

Deutsches Elektronen-Synchrotron, Hamburg, Germany

M. Aldaya Martin, T. Arndt, C. Asawatangtrakuldee, K. Beernaert, O. Behnke, U. Behrens,

A. Berm ´udez Mart´ınez, A.A. Bin Anuar, K. Borras15, V. Botta, A. Campbell, P. Connor,

(26)

E. Eren, E. Gallo16, J. Garay Garcia, A. Geiser, A. Gizhko, J.M. Grados Luyando, A. Grohsjean,

P. Gunnellini, A. Harb, J. Hauk, M. Hempel17, H. Jung, A. Kalogeropoulos, M. Kasemann,

J. Keaveney, C. Kleinwort, I. Korol, D. Kr ¨ucker, W. Lange, A. Lelek, T. Lenz, J. Leonard,

K. Lipka, W. Lohmann17_{, R. Mankel, I.-A. Melzer-Pellmann, A.B. Meyer, G. Mittag, J. Mnich,}

A. Mussgiller, E. Ntomari, D. Pitzl, R. Placakyte, A. Raspereza, B. Roland, M. Savitskyi, P. Saxena, R. Shevchenko, S. Spannagel, N. Stefaniuk, G.P. Van Onsem, R. Walsh, Y. Wen, K. Wichmann, C. Wissing, O. Zenaiev

University of Hamburg, Hamburg, Germany

S. Bein, V. Blobel, M. Centis Vignali, T. Dreyer, E. Garutti, D. Gonzalez, J. Haller, A. Hinzmann, M. Hoffmann, A. Karavdina, R. Klanner, R. Kogler, N. Kovalchuk, S. Kurz, T. Lapsien, I. Marchesini, D. Marconi, M. Meyer, M. Niedziela, D. Nowatschin, F. Pantaleo14_{, T. Peiffer,}

A. Perieanu, C. Scharf, P. Schleper, A. Schmidt, S. Schumann, J. Schwandt, J. Sonneveld, H. Stadie, G. Steinbr ¨uck, F.M. Stober, M. St ¨over, H. Tholen, D. Troendle, E. Usai, L. Vanelderen, A. Vanhoefer, B. Vormwald

Institut f ¨ur Experimentelle Kernphysik, Karlsruhe, Germany

M. Akbiyik, C. Barth, S. Baur, E. Butz, R. Caspart, T. Chwalek, F. Colombo, W. De Boer, A. Dierlamm, B. Freund, R. Friese, M. Giffels, A. Gilbert, D. Haitz, F. Hartmann14, S.M. Heindl, U. Husemann, F. Kassel14_{, S. Kudella, H. Mildner, M.U. Mozer, Th. M ¨uller, M. Plagge, G. Quast,}

K. Rabbertz, M. Schr ¨oder, I. Shvetsov, G. Sieber, H.J. Simonis, R. Ulrich, S. Wayand, M. Weber, T. Weiler, S. Williamson, C. W ¨ohrmann, R. Wolf

Institute of Nuclear and Particle Physics (INPP), NCSR Demokri-tos, Aghia Paraskevi, Greece

G. Anagnostou, G. Daskalakis, T. Geralis, V.A. Giakoumopoulou, A. Kyriakis, D. Loukas, I. Topsis-Giotis

National and Kapodistrian University of Athens, Athens, Greece

S. Kesisoglou, A. Panagiotou, N. Saoulidou

University of Io´annina, Io´annina, Greece

I. Evangelou, C. Foudas, P. Kokkas, S. Mallios, N. Manthos, I. Papadopoulos, E. Paradas, J. Strologas, F.A. Triantis

MTA-ELTE Lend ület CMS Particle and Nuclear Physics Group, E ötv ös Loránd Univer-sity, Budapest, Hungary

M. Csanad, N. Filipovic, G. Pasztor

Wigner Research Centre for Physics, Budapest, Hungary

G. Bencze, C. Hajdu, D. Horvath18, ´A. Hunyadi, F. Sikler, V. Veszpremi, G. Vesztergombi19, A.J. Zsigmond

Institute of Nuclear Research ATOMKI, Debrecen, Hungary

N. Beni, S. Czellar, J. Karancsi20, A. Makovec, J. Molnar, Z. Szillasi

Institute of Physics, University of Debrecen, Debrecen, Hungary

M. Bart ´ok19, P. Raics, Z.L. Trocsanyi, B. Ujvari

Indian Institute of Science (IISc), Bangalore, India

S. Choudhury, J.R. Komaragiri

National Institute of Science Education and Research, Bhubaneswar, India

(27)

Panjab University, Chandigarh, India

S. Bansal, S.B. Beri, V. Bhatnagar, U. Bhawandeep, R. Chawla, N. Dhingra, R. Gupta, A.K. Kalsi, A. Kaur, M. Kaur, R. Kumar, P. Kumari, A. Mehta, J.B. Singh, G. Walia

University of Delhi, Delhi, India

A. Bhardwaj, S. Chauhan, B.C. Choudhary, R.B. Garg, S. Keshri, A. Kumar, Ashok Kumar, S. Malhotra, M. Naimuddin, K. Ranjan, Aashaq Shah, R. Sharma, V. Sharma

Saha Institute of Nuclear Physics, HBNI, Kolkata, India

R. Bhardwaj, R. Bhattacharya, S. Bhattacharya, S. Dey, S. Dutt, S. Dutta, S. Ghosh, N. Majumdar, A. Modak, K. Mondal, S. Mukhopadhyay, S. Nandan, A. Purohit, A. Roy, D. Roy, S. Roy Chowdhury, S. Sarkar, M. Sharan, S. Thakur

Indian Institute of Technology Madras, Madras, India

P.K. Behera

Bhabha Atomic Research Centre, Mumbai, India

R. Chudasama, D. Dutta, V. Jha, V. Kumar, A.K. Mohanty14, P.K. Netrakanti, L.M. Pant,

P. Shukla, A. Topkar

Tata Institute of Fundamental Research-A, Mumbai, India

T. Aziz, S. Dugad, B. Mahakud, S. Mitra, G.B. Mohanty, N. Sur, B. Sutar

Tata Institute of Fundamental Research-B, Mumbai, India

S. Banerjee, S. Bhattacharya, S. Chatterjee, P. Das, M. Guchait, Sa. Jain, S. Kumar, M. Maity23,

G. Majumder, K. Mazumdar, T. Sarkar23_{, N. Wickramage}24

Indian Institute of Science Education and Research (IISER), Pune, India

S. Chauhan, S. Dube, V. Hegde, A. Kapoor, K. Kothekar, S. Pandey, A. Rane, S. Sharma

Institute for Research in Fundamental Sciences (IPM), Tehran, Iran

S. Chenarani25, E. Eskandari Tadavani, S.M. Etesami25, M. Khakzad, M. Mohammadi

Na-jafabadi, M. Naseri, S. Paktinat Mehdiabadi26, F. Rezaei Hosseinabadi, B. Safarzadeh27,

M. Zeinali

University College Dublin, Dublin, Ireland

M. Felcini, M. Grunewald

INFN Sezione di Baria, Universit`a di Barib, Politecnico di Baric, Bari, Italy

M. Abbresciaa,b, C. Calabriaa,b, C. Caputoa,b, A. Colaleoa, D. Creanzaa,c, L. Cristellaa,b, N. De Filippisa,c, M. De Palmaa,b, F. Erricoa,b, L. Fiorea, G. Iasellia,c, S. Lezkia,b, G. Maggia,c, M. Maggia_{, G. Miniello}a,b_{, S. My}a,b_{, S. Nuzzo}a,b_{, A. Pompili}a,b_{, G. Pugliese}a,c_{, R. Radogna}a,b_,

A. Ranieria, G. Selvaggia,b, A. Sharmaa, L. Silvestrisa,14, R. Vendittia, P. Verwilligena

INFN Sezione di Bolognaa, Universit`a di Bolognab, Bologna, Italy

G. Abbiendia, C. Battilanaa,b, D. Bonacorsia,b, S. Braibant-Giacomellia,b, R. Campaninia,b, P. Capiluppia,b, A. Castroa,b, F.R. Cavalloa, S.S. Chhibraa, G. Codispotia,b, M. Cuffiania,b, G.M. Dallavallea, F. Fabbria, A. Fanfania,b, D. Fasanellaa,b, P. Giacomellia, C. Grandia, L. Guiduccia,b, S. Marcellinia, G. Masettia, A. Montanaria, F.L. Navarriaa,b, A. Perrottaa, A.M. Rossia,b_{, T. Rovelli}a,b_{, G.P. Siroli}a,b_{, N. Tosi}a

INFN Sezione di Cataniaa, Universit`a di Cataniab, Catania, Italy

(28)

INFN Sezione di Firenzea, Universit`a di Firenzeb, Firenze, Italy

G. Barbaglia, K. Chatterjeea,b, V. Ciullia,b, C. Civininia, R. D’Alessandroa,b, E. Focardia,b, P. Lenzia,b, M. Meschinia, S. Paolettia, L. Russoa,28, G. Sguazzonia, D. Stroma, L. Viliania,b,14

INFN Laboratori Nazionali di Frascati, Frascati, Italy

L. Benussi, S. Bianco, F. Fabbri, D. Piccolo, F. Primavera14

INFN Sezione di Genovaa, Universit`a di Genovab, Genova, Italy

V. Calvellia,b, F. Ferroa, E. Robuttia, S. Tosia,b

INFN Sezione di Milano-Bicoccaa, Universit`a di Milano-Bicoccab, Milano, Italy

L. Brianzaa,b_{, F. Brivio}a,b_{, V. Ciriolo}a,b_{, M.E. Dinardo}a,b_{, S. Fiorendi}a,b_{, S. Gennai}a_,

A. Ghezzia,b, P. Govonia,b, M. Malbertia,b, S. Malvezzia, R.A. Manzonia,b, D. Menascea, L. Moronia, M. Paganonia,b, K. Pauwelsa,b, D. Pedrinia, S. Pigazzinia,b,29, S. Ragazzia,b, T. Tabarelli de Fatisa,b

INFN Sezione di Napoli a, Università di Napoli ’Federico II’ b, Napoli, Italy, Univer-sità della Basilicatac, Potenza, Italy, Università G. Marconid, Roma, Italy

S. Buontempoa, N. Cavalloa,c, S. Di Guidaa,d,14, F. Fabozzia,c, F. Fiengaa,b, A.O.M. Iorioa,b, W.A. Khana_{, L. Lista}a_{, S. Meola}a,d,14_{, P. Paolucci}a,14_{, C. Sciacca}a,b_{, F. Thyssen}a

INFN Sezione di Padova a, Universit`a di Padova b, Padova, Italy, Univer-sit`a di Trentoc, Trento, Italy

P. Azzia,14, N. Bacchettaa, L. Benatoa,b, D. Biselloa,b, A. Bolettia,b, R. Carlina,b,

A. Carvalho Antunes De Oliveiraa,b, P. Checchiaa, P. De Castro Manzanoa, T. Dorigoa,

F. Gasparinia,b, U. Gasparinia,b, A. Gozzelinoa, S. Lacapraraa, P. Lujan, M. Margonia,b, A.T. Meneguzzoa,b_{, N. Pozzobon}a,b_{, P. Ronchese}a,b_{, R. Rossin}a,b_{, F. Simonetto}a,b_{, E. Torassa}a_,

S. Venturaa_{, P. Zotto}a,b_{, G. Zumerle}a,b

INFN Sezione di Paviaa, Universit`a di Paviab, Pavia, Italy

A. Braghieria, F. Fallavollitaa,b, A. Magnania,b, P. Montagnaa,b, S.P. Rattia,b, V. Rea, M. Ressegotti, C. Riccardia,b, P. Salvinia, I. Vaia,b, P. Vituloa,b

INFN Sezione di Perugiaa, Universit`a di Perugiab, Perugia, Italy

L. Alunni Solestizia,b_{, M. Biasini}a,b_{, G.M. Bilei}a_{, C. Cecchi}a,b_{, D. Ciangottini}a,b_{, L. Fan `o}a,b_,

P. Laricciaa,b, R. Leonardia,b, E. Manonia, G. Mantovania,b, V. Mariania,b, M. Menichellia, A. Rossia,b, A. Santocchiaa,b, D. Spigaa

INFN Sezione di Pisaa, Universit`a di Pisab, Scuola Normale Superiore di Pisac, Pisa, Italy

K. Androsova, P. Azzurria,14, G. Bagliesia, J. Bernardinia, T. Boccalia, L. Borrello, R. Castaldia, M.A. Cioccia,b, R. Dell’Orsoa, G. Fedia, L. Gianninia,c, A. Giassia, M.T. Grippoa,28, F. Ligabuea,c, T. Lomtadzea, E. Mancaa,c, G. Mandorlia,c, L. Martinia,b, A. Messineoa,b, F. Pallaa, A. Rizzia,b, A. Savoy-Navarroa,30_{, P. Spagnolo}a_{, R. Tenchini}a_{, G. Tonelli}a,b_{, A. Venturi}a_{, P.G. Verdini}a

INFN Sezione di Romaa, Sapienza Universit`a di Romab, Rome, Italy

L. Baronea,b, F. Cavallaria, M. Cipriania,b, N. Dacia, D. Del Rea,b,14, M. Diemoza, S. Gellia,b, E. Longoa,b, F. Margarolia,b, B. Marzocchia,b, P. Meridiania, G. Organtinia,b, R. Paramattia,b, F. Preiatoa,b, S. Rahatloua,b, C. Rovellia, F. Santanastasioa,b

INFN Sezione di Torinoa, Universit`a di Torinob, Torino, Italy, Universit`a del Piemonte Ori-entalec, Novara, Italy

N. Amapanea,b, R. Arcidiaconoa,c, S. Argiroa,b, M. Arneodoa,c, N. Bartosika, R. Bellana,b, C. Biinoa, N. Cartigliaa, F. Cennaa,b, M. Costaa,b, R. Covarellia,b, A. Deganoa,b, N. Demariaa, B. Kiania,b, C. Mariottia, S. Masellia, E. Migliorea,b, V. Monacoa,b, E. Monteila,b, M. Montenoa,

(29)

M.M. Obertinoa,b, L. Pachera,b, N. Pastronea, M. Pelliccionia, G.L. Pinna Angionia,b, F. Raveraa,b, A. Romeroa,b, M. Ruspaa,c, R. Sacchia,b, K. Shchelinaa,b, V. Solaa, A. Solanoa,b, A. Staianoa, P. Traczyka,b

INFN Sezione di Triestea, Universit`a di Triesteb, Trieste, Italy

S. Belfortea, M. Casarsaa, F. Cossuttia, G. Della Riccaa,b, A. Zanettia

Kyungpook National University, Daegu, Korea

D.H. Kim, G.N. Kim, M.S. Kim, J. Lee, S. Lee, S.W. Lee, C.S. Moon, Y.D. Oh, S. Sekmen, D.C. Son, Y.C. Yang

Chonbuk National University, Jeonju, Korea

A. Lee

Chonnam National University, Institute for Universe and Elementary Parti-cles, Kwangju, Korea

H. Kim, D.H. Moon, G. Oh

Hanyang University, Seoul, Korea

J.A. Brochero Cifuentes, J. Goh, T.J. Kim

Korea University, Seoul, Korea

S. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, Y. Jo, Y. Kim, K. Lee, K.S. Lee, S. Lee, J. Lim, S.K. Park, Y. Roh

Seoul National University, Seoul, Korea

J. Almond, J. Kim, J.S. Kim, H. Lee, K. Lee, K. Nam, S.B. Oh, B.C. Radburn-Smith, S.h. Seo, U.K. Yang, H.D. Yoo, G.B. Yu

University of Seoul, Seoul, Korea

M. Choi, H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park, G. Ryu

Sungkyunkwan University, Suwon, Korea

Y. Choi, C. Hwang, J. Lee, I. Yu

Vilnius University, Vilnius, Lithuania

V. Dudenas, A. Juodagalvis, J. Vaitkus

National Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Malaysia

I. Ahmed, Z.A. Ibrahim, M.A.B. Md Ali31, F. Mohamad Idris32, W.A.T. Wan Abdullah,

M.N. Yusli, Z. Zolkapli

Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico

Duran-Osuna, M. C., H. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-De La Cruz33,

R. Lopez-Fernandez, J. Mejia Guisao, R.I. Rabad´an-Trejo, G. Ramirez-Sanchez, R. Reyes-Almanza, A. Sanchez-Hernandez

Universidad Iberoamericana, Mexico City, Mexico

S. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia

Benemerita Universidad Autonoma de Puebla, Puebla, Mexico

I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada

Universidad Aut ´onoma de San Luis Potos´ı, San Luis Potos´ı, Mexico