Measurement of neutral strange particle production in the underlying event in
proton-proton collisions at
p
ffiffiffi
s
¼ 7 TeV
S. Chatrchyan et al.* (CMS Collaboration)
(Received 26 May 2013; published 3 September 2013)
Measurements are presented of the production of primary K0S and particles in proton-proton
collisions atpffiffiffis¼ 7 TeV in the region transverse to the leading charged-particle jet in each event. The average multiplicity and average scalar transverse momentum sum of KS0 and particles measured at
pseudorapidities jj < 2 rise with increasing charged-particle jet pT in the range 1–10 GeV=c and saturate in the region10–50 GeV=c. The rise and saturation of the strange-particle yields and transverse momentum sums in the underlying event are similar to those observed for inclusive charged particles, which confirms the impact-parameter picture of multiple parton interactions. The results are compared to recent tunes of thePYTHIAMonte Carlo event generator. ThePYTHIAsimulations underestimate the data by 15%–30% for K0S mesons and by about 50% for baryons, a deficit similar to that observed for the
inclusive strange-particle production in non-single-diffractive proton-proton collisions. The constant strange- to charged-particle activity ratios with respect to the leading jet pTand similar trends for mesons
and baryons indicate that the multiparton-interaction dynamics is decoupled from parton hadronization, which occurs at a later stage.
DOI:10.1103/PhysRevD.88.052001 PACS numbers: 12.38.Aw, 13.85.Ni
I. INTRODUCTION
This paper describes a measurement of the production of primary K0S mesons, and and baryons in the
under-lying event in proton-proton (pp) collisions at a center-of-mass energy of 7 TeV with the Compact Muon Solenoid (CMS) detector at the Large Hadron Collider (LHC).
In the presence of a hard process, characterized by parti-cles or clusters of partiparti-cles with large transverse momentum pT with respect to the beam direction, the final state of
hadron-hadron interactions can be described as the super-position of several contributions: the partonic hard scatter-ing, initial- and final-state radiation, additional ‘‘multiple partonic interactions’’ (MPI), and ‘‘beam-beam remnants’’ (BBR) interactions. The products of initial- and final-state radiation, MPI and BBR, form the ‘‘underlying event’’ (UE). In this paper, the UE properties are analyzed with refer-ence to the direction of the highest-pT jet reconstructed
from charged primary particles (leading charged-particle jet). This leading jet is expected to reflect the direction of the parton produced with the highest transverse momentum in the hard interaction. Three distinct topological regions in the hadronic final state are defined in terms of the azimuthal angle between the directions of the leading jet and that of any particle in the event. Particle production in the ‘‘toward’’ region,jj < 60, and in the ‘‘away’’ region,
jj>120, is expected to be dominated by the hard
parton-parton scattering. The UE structure can be best studied in the ‘‘transverse’’ region,60<jj<120[1,2]. Studies of the UE activity in charged primary particles in proton-proton collisions at different center-of-mass ener-gies have been published by the ATLAS [3] and CMS [1,4,5] collaborations. Observables such as the average multiplicity of charged primary particles per event, here-after referred to as ‘‘average rate,’’ and the average scalar sum of primary particle pTper event, hereafter referred to
as ‘‘average pT sum,’’ have been measured in the
trans-verse region. These quantities exhibit a steep rise with increasing charged-particle jet pT up to a value that
depends on the proton-proton center-of-mass energy (around 10 GeV=c for pp collisions at 7 TeV), followed by a slow rise. Within the MPI framework, a hard jet is likely to be produced in collisions with a small impact parameter between the colliding protons, consequently resulting in large MPI activity [6,7]. The MPI activity saturates at values of the hard scale typical of central collisions.
The present analysis considers identified neutral strange particles (KS0,, and ) as additional probes to study the underlying event. Unless stated otherwise, and baryon data are merged and referred to as baryon data. The production of primary KS0and particles in the transverse
region atpffiffiffis¼ 7 TeV is studied as a function of the scale of the hard process. Fully corrected average rates and pT
sums of primary K0S mesons and baryons, as well as
ratios to the charged primary-particle rates and pT sums,
are compared to simulations. This analysis complements the studies of strangeness production in minimum-bias events at pffiffiffis¼ 7 TeV published by the ALICE [8,9],
*Full author list given at the end of the article.
Published by the American Physical Society under the terms of the Creative Commons Attribution 3.0 License. Further distri-bution of this work must maintain attridistri-bution to the author(s) and the published article’s title, journal citation, and DOI.
ATLAS [10], and CMS [11] collaborations. Comparisons of nonsingle diffractive data [11] with predictions made with the PYTHIA 6 [12] and PYTHIA 8 [13] Monte Carlo event generators have shown that the latter largely under-estimate the data, e.g., by 30% for K0Sproduction and 50% for production at pffiffiffis¼ 7 TeV for PYTHIA6 tune D6T [2,14], with little improvement for more recent tunes.
The simulations are performed with versions ofPYTHIA that include MPI. The most recent versions have been tuned to reproduce the UE activity observed with primary charged particles at the LHC at 0.9 TeV and 7 TeV center-of-mass energies. The parameters describing strangeness production, however, have not been tuned to LHC data yet. All Monte Carlo samples used in this paper have been generated with the default values of these parameters.
Recent literature [15–17] discussing the tuning of the strangeness suppression parameters in commonly available generators is limited. A tuning of thePYTHIA6 parameters to LEP, SLAC Linear Collider, and Tevatron data per-formed with thePROFESSORprogram [15] produced best-fit parameters in disagreement with the current PYTHIA default parameters. The resulting predicted strange meson and baryon production rates given in the Appendix of Ref. [15], however, do not agree well with the data used for the tuning. Other attempts to describe strange-particle production in pp collisions are discussed in Refs. [16,17]. The present paper focuses on the comparison withPYTHIA. The outline of this paper is the following. In Sec.II, the experimental conditions are described, along with the data sets, the simulation, and the analysis technique. In Sec.III, the systematic uncertainties are summarized. The results are discussed in Sec. IV, and conclusions are drawn in Sec.V.
II. EXPERIMENTAL SETUP, DATA SETS, AND DATA ANALYSIS
The central feature of CMS is a superconducting sole-noid of 6 m internal diameter. Within the superconducting solenoid volume are a silicon pixel and strip tracker, a lead tungstate crystal electromagnetic calorimeter, and a brass and scintillator hadron calorimeter. Muons are measured in gas-ionization detectors embedded in the flux-return yoke. Extensive forward calorimetry complements the coverage provided by the barrel and endcap detectors. CMS uses a right-handed coordinate system, with the origin at the nominal interaction point, the x axis pointing to the center of the LHC, the y axis pointing up (perpendicular to the LHC plane), and the z axis along the anticlockwise-beam direction. The polar angle is measured from the positive z axis, and the azimuthal angle is measured in the x y plane. The tracker measures charged particles within the pseudorapidity range jj < 2:5, where ¼ ln ðtan ð=2ÞÞ. It consists of 1440 silicon pixel and 15 148 silicon strip detector modules and is located in the 3.8 T field of the superconducting solenoid. For the
charged particles of interest in this analysis, the transverse momentum resolution is relatively constant with pT,
vary-ing from 0.7% at ¼ 0 to 2% at jj ¼ 2. The transverse and longitudinal impact-parameter resolutions, d0 and dz, respectively, depend on pT and on , ranging from d0¼400m and dz¼1000m at pT¼ 0:3 GeV=c and jj > 1:4 to d0¼ 10 m and dz ¼ 30 m at pT¼ 100 GeV=c and jj < 0:9. A more detailed description of the CMS detector can be found in Ref. [18].
A. Event selection, data sets, and Monte Carlo simulation
The event selection is identical to the one described in [1], unless explicitly stated otherwise. Minimum-bias events were triggered by requiring coincident signals in beam scintillator counters located on both sides of the experiment and covering the pseudorapidity range3:23 < jj < 4:65, and in the beam pickup devices [18]. Events were then recorded with a prescaled trigger requiring the presence of at least one track segment in the pixel detector with pT> 200 MeV=c. The trigger conditions are applied
to both data and simulated samples. The trigger efficiency for the events selected in the analysis is close to 100%, and no bias from the trigger selection is found.
The data used in this analysis were collected in early 2010 when pileup (multiple pp collisions per proton bunch crossing) was very low. Selected events are required to contain a single reconstructed primary vertex, a condition that rejects about 1% of the events satisfying all the other selection criteria. The primary vertex is fit with an adaptive algorithm [19] and must have at least four tracks, a trans-verse distance to the beam line smaller than 2 cm, and a z coordinate within 10 cm of the nominal interaction point.
Events are required to contain a track jet with recon-structed pT> 1 GeV=c and jj < 2. Track jets are
recon-structed from the tracks of charged particles, with the anti-kT algorithm [20,21] and a clustering radius R ¼
0:5, where R¼pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiðÞ2þðÞ2. The tracks are required
to be well reconstructed, to have pT> 500 MeV=c, jj <
2:5, and to be consistent with originating from the primary vertex. More details on the track selection can be found in [1]. The reconstructed track jet pTis the magnitude of the
vector sum of the transverse momenta of the tracks in the jet. The leading track jet pT is corrected for detector
response (track finding efficiency and pT measurement)
with detailed simulations based on GEANT4 [22], which have been extensively validated with data [23–25]. This correction is approximately independent of the track jet pT
and , and its average value is 1.01. The leading corrected track jet is referred to as the leading charged-particle jet.
The PYTHIAversions we consider all include MPI. The tunes used are thePYTHIA6 D6T tune [2,14] and thePYTHIA 8 tune 1 [13], which have not been tuned to the LHC data, and the PYTHIA 6 Z1 [26] andZ2 tunes. The two latter
PYTHIA6 tunes, as well asPYTHIA8, include pTordering of the parton showers, and a new model [27] where MPI are interleaved with parton showering.PYTHIA8 includes hard diffraction in addition to the new MPI model. The parton distribution functions used forPYTHIA6 D6T andPYTHIA8 tune 1 are the CTEQ6L1 and CTEQ5L sets, respectively. The Z1 tune uses the CTEQ5L parton distribution set, whereasZ2 is updated to CTEQ6L1 [28] and retuned to the underlying event activity at 7 TeV from Ref. [1] with the PROFESSORtool [15]. The simulated data are generated with PYTHIA6 version 6.422 for tunes D6T and Z1, version 6.424 for tuneZ2, and version 8.135 forPYTHIA8 tune 1.
Simulated primary stable charged particles with a proper lifetime c > 1 cm are clustered into jets with the anti-kT
algorithm (R ¼ 0:5). The average rates and scalar pT sums of simulated primary KS0 and particles are
com-puted within the transverse region of the leading simulated charged-particle jet.
A data sample of 11 106 events with at least one charged-particle jet with pT> 1 GeV=c and jj < 2 is
analyzed. The corresponding numbers of simulated events are22 106 forPYTHIA6 D6T and5 106 forPYTHIA6 Z1, Z2 and PYTHIA 8 tune 1. Corrections for detector effects and background are estimated with the PYTHIA 6 D6T sample, while the modeling of the underlying event is studied with all the tunes mentioned.
The reconstruction of the leading charged-particle jet results in a bias in the measured average rates and pTsums
in the transverse region. The value of this bias ranges from þ5% to þ10% for charged-particle jet pT below 10 GeV=c, and is consistent with zero for larger pTvalues.
It is caused by events in which the leading jet formed by primary charged particles is not reconstructed as the lead-ing charged-particle jet because of tracklead-ing inefficiencies, and a subleading jet is thus reconstructed as the leading jet. This results in a reconstructed transverse region shifted in . The correction for this bias is obtained from the detailed Monte Carlo simulations of the detector response de-scribed above.
The primary vertex selection causes a small overesti-mate of the UE strangeness activity at low charged-particle jet pT, at most 5% for charged-particle jet pT¼ 1 GeV=c.
This is because the requirement that at least four tracks be associated to the primary vertex enriches the sample in events with higher UE activity when the charged-particle jets have very low multiplicity. This bias is corrected by means of detailed simulations as described in Sec.III.
B. Selection of primaryV0 candidates and analysis strategy
The neutral strange particles K0S, , and , hereafter generically called V0s, are identified by means of their characteristic decay topology: a flight distance of several centimeters before decay, two tracks of opposite charge emerging from a secondary vertex, and an invariant mass
consistent with that of a KS0meson or a baryon. The V0 momentum vector is further required to be collinear with the vector joining the primary and secondary vertices, in order to select primary particles.
The V0 candidates are reconstructed by the standard CMS offline event reconstruction program [25]. Pairs of oppositely charged tracks with at least 3 hits in the CMS tracker and with a nonzero transverse impact parameter with respect to the beam line are selected (the transverse impact parameter divided by its uncertainty is required to be larger than 1.5). Pairs of tracks with a distance of closest approach to each other smaller than 1 cm are fit to a common secondary vertex, and those with a vertex fit 2 smaller than 7 and a significant distance between the beam line and the secondary vertex (transverse flight distance divided by its uncertainty larger than 8) are retained.
Well-reconstructed V0candidates are selected by apply-ing cuts on the pseudorapidity and transverse momentum of the decay tracks (jj < 2:5, pT> 300 MeV=c), of the
V0 candidate (jj < 2; pT> 600 MeV=c for KS0 mesons,
pT> 1:5 GeV=c for baryons), and on the V0 transverse
flight distance (>1 cm from the beam line). A kinematic fit is then performed on the candidates to further purify the sample of primary strange particles. The fit includes a secondary vertex constraint, a mass constraint, as well as the constraint that the V0 momentum points away from the primary vertex. All three hypotheses (KS0 ! þ,
! p, and ! pþ) are tested for each candidate
and the most probable hypothesis is considered. Candidates with a kinematic-fit probability larger than 5% are retained.
Since simulations enter in the determination of the V0 selection efficiency and purity, a good description of the distributions of the kinematic-fit input variables is impor-tant. The distributions of the invariant mass of the V0 candidates for the most probable particle-type hypothesis are shown in Fig.1, together with the distributions of the invariant-mass pull. The invariant-mass pull is the differ-ence between the reconstructed mass and the accepted V0 mass value [29], divided by the uncertainty on the recon-structed mass calculated from the decay track parameter uncertainties. The signal and background fractions are shown as predicted byPYTHIA6 D6T. The backgrounds in the K0S sample are mostly misidentified baryons. Backgrounds in the sample are mostly nonprimary baryons from cascade decays of and baryons, plus contributions from misidentified KS0mesons and converted photons. In general, the simulation agrees with the data. As an example, the average mass values for KS0 mesons ( baryons) are0:4981 GeV=c2(1:116 GeV=c2) in the simu-lation and0:4977 GeV=c2 (1:116 GeV=c2) in the data; the corresponding rms values for the mass pull distributions are 1.17 (0.512) in the simulation and 1.23 (0.531) in the data. For K0Scandidates, the data show larger tails than the simu-lation at mass pull values below (2). The presence of a
similar tail in the component shown as the hatched histogram of the simulated distribution indicates that this excess is due to a larger contribution from misidentified baryons in the data compared to the simulation. This is accounted for in the background estimation as described below.
The pointing requirement constrains the signed impact parameter dipof the V0with respect to the primary vertex.
This variable is defined as the distance of closest approach of the V0 trajectory to the primary vertex, and its sign is that of the scalar product of the V0 momentum and the vector pointing from the primary vertex to the point of closest approach. The distributions of the signed impact parameter are shown in Fig.2 together with the distribu-tions of the corresponding pull, defined as dipdivided by its
uncertainty dipcalculated from the decay track parameter uncertainties. The quality of the description of the data by the simulation is good, including the tails at positive impact-parameter values. The large pulls for secondary baryons from cascade decays allow the suppression of this background by means of the kinematic fit.
The uncorrected average rates of reconstructed V0 can-didates passing the selection cuts per unit pseudorapidity
are shown in Fig. 3 as a function of the difference in azimuthal angle jj between the V0 candidate and the leading charged-particle jet. Uncorrected data are com-pared toPYTHIAevents passed through the detailed detec-tor simulation. The dependence of the rates on jj is qualitatively described by the PYTHIA tunes considered. The simulation underestimates significantly the V0 rates in the transverse region. The peak at jj 0 is more pronounced for baryons than for K0S mesons. The
simula-tion indicates that the harder pTcut applied to the baryon
candidates is responsible for this feature; the distributions are similar when the same pT cut is applied to both V0
types.
The backgrounds to the KS0and samples are estimated with two methods. The first is based on simulation. Candidates not matched to a generated primary V0 of the corresponding type are counted as background. The PYTHIA 6 D6T sample is used. To account for the known deficit of strange particles in the simulation (see Sec.I), the contribution from K0Smesons misidentified as baryons is weighted by the ratio of K0S rates measured in nonsingle diffractive events to those in PYTHIA 6 D6T, 1.39 [11]. Similarly, the contribution from misidentified baryons
] 2 mass [GeV/c 0.4 0.45 0.5 0.55 2 Candidates / 3 MeV/c 1 10 2 10 3 10 4 10 5 10 0 S K = 7 TeV s CMS, pp, Data 0 S Primary K 0 Misidentified V Other sources ] 2 mass [GeV/c 1.08 1.1 1.12 1.14 2 Candidates / 1 MeV/c 1 10 2 10 3 10 4 10
Λ
= 7 TeV s CMS, pp, Data Λ Primary Cascade decays 0 Misidentified V Other sources mass σ )/ PDG (mass - mass -5 0 5 Candidates 1 10 2 10 3 10 4 10 0 S K = 7 TeV s CMS, pp, mass σ )/ PDG (mass - mass -4 -2 0 2 4 Candidates 1 10 2 10 3 10 4 10Λ
= 7 TeV s CMS, pp,FIG. 1 (color online). Distributions of invariant mass and invariant-mass pull for the most probable particle-type hypothesis determined by the kinematic fit. The accepted K0S and mass values from Ref. [29] are denoted as massPDG. The black
points indicate the data. The histograms show the backgrounds (hatched: misidentified V0; green: nonprimary from and cascade decays; grey: other sources) and the signal (yellow) as predicted byPYTHIA6 D6T. The PYTHIAprediction is normalized to the data.
is weighted by a factor of 1.85, and the contribution arising from nonprimary baryons from and decays is weighted by the ratio of the measured and simulated production rates, 2.67 [11].
The second method is based on data. The signal and background contributions are extracted from a fit to the distribution of the kinematic-fit 2probability, with signal and background shapes obtained from simulation. Apart from the background normalization, the measured and simulated pull distributions of the constrained variables (Figs. 1 and 2), as well as the measured and simulated 2-probability distributions (not shown), are in good agreement. These facts, as well as goodness-of-fit tests, validate the approach.
In both methods, the background is estimated as a function of the charged-particle jet pT for the rate
mea-surements, and as a function of the V0 pT for the V0 pT
spectra and the pT sum measurements. The background
estimations from the two methods are in reasonable agree-ment, and they exhibit the same dependence on the charged-particle jet and V0pT. The final background
esti-mates are computed as the average of the results of the two methods, and the corresponding systematic uncertainties are taken as half the difference of the two results. The
background fraction for KS0increases fromð1:5 1:1Þ% at charged-particle jet pT¼ 1 GeV=c to ð3:3 1:7Þ% at
charged-particle jet pT¼ 10 GeV=c and remains constant
at higher charged-particle jet pT. The background is
ð8 2Þ% for baryons, independent of the charged-particle jet pT.
The K0S and raw yields are corrected for purity (defined as 1—background fraction) as well as for accep-tance and reconstruction efficiency. Each V0 candidate is weighted by the product of the purity timesA 1 , where A denotes the acceptance of the cuts on the V0 transverse flight distance and on the pT, of the decay particles, and
denotes the reconstruction and selection efficiency for accepted V0 candidates. The product of acceptance times efficiency is computed in V0ðpT; Þ bins from a sample of
50 106 PYTHIA 6 D6T minimum-bias events passed
through the detailed detector simulation. The average val-ues of the product of acceptance and efficiency in this sample for K0S mesons, and and baryons within the
kinematic cuts (jj < 2; pT> 600 MeV=c for K0S, pT>
1:5 GeV=c for and ) are 11.3%, 8.4%, and 6.6%, respectively, including the branching fractions BðK0S! þÞ ¼ 69:2% and Bð ! pÞ ¼ Bð ! pþÞ ¼ 63:9% [29]. The acceptance depends strongly on the V0
[cm] ip d -5 0 5 Candidates / 0.2 cm 1 10 2 10 3 10 4 10 5 10 = 7 TeV s CMS, pp, 0 S K Data 0 S Primary K 0 Misidentified V Other sources [cm] ip d -2 -1 0 1 2 Candidates / 0.05 cm 1 10 2 10 3 10 4 10 Data Λ Primary Cascade decays 0 Misidentified V Other sources
Λ
= 7 TeV s CMS, pp, ip d σ / ip d -40 -20 0 20 40 Candidates 1 10 2 10 3 10 4 10 5 10 0 S K = 7 TeV s CMS, pp, ip d σ / ip d -40 -20 0 20 40 Candidates 1 10 2 10 3 10 4 10Λ
= 7 TeV s CMS, pp,FIG. 2 (color online). Distributions of the signed impact parameter dipwith respect to the primary vertex, and the corresponding pull
distributions, for the most probable particle-type hypothesis determined by the kinematic fit. The black points indicate the data. The histograms show the backgrounds (hatched: misidentified V0; green: nonprimary from and cascade decays; grey: other sources) and the signal (yellow) as predicted byPYTHIA6 D6T. ThePYTHIA prediction is normalized to the data.
pT, while the efficiency varies by a factor of about 2 in
the V0 pT and ranges selected. The smaller efficiency
for baryons than for baryons reflects the higher interaction cross section of antiprotons with the detector material compared to that of protons. The corrected and yields are found to be compatible when accounting for the systematic uncertainty due to the modeling of the antiproton cross section in the GEANT4version used [30] (see Sec.III).
The consistency of the correction method was checked by applying it to all other Monte Carlo samples and com-paring the results to the known generated values. Further support to the correction procedure is provided by the fact that the simulation reproduces well several key aspects of the data, most notably the reconstruction efficiency [23,24] and the angular distributions of the V0 decay tracks as a function of the V0pT. The reliability of the simulation for
KS0 and reconstruction was checked by comparing the lifetimes obtained from fits to the corrected proper time distributions with the world averages [11]. The stability of the results when varying the V0 selection cuts was also checked. The resulting overall contribution of the V0 reconstruction to the systematic uncertainty is given in Sec.III.
III. SYSTEMATIC UNCERTAINTIES
The main sources of systematic uncertainties are described below, with numerical values summarized in TableI.
Leading charged-particle jet selection: The bias in rates and pTsums due to mismatches between the reconstructed
and the simulated leading charged-particle jets is corrected by means of detailed simulations. The systematic uncer-tainty is estimated from the residual difference in rates and pTsums when the reconstructed and the simulated leading
charged-particle jets are matched withinR ¼ 0:3. Primary vertex selection: The bias caused by the require-ment of a minimum track multiplicity at the primary vertex is corrected by means of detailed simulations of minimum-bias events with the PYTHIA 6 Z1 tune. The primary charged-particle multiplicity in 7 TeV pp collisions is well described by this tune [1]. The corresponding uncer-tainty is estimated from the spread of the corrections com-puted withPYTHIA6 tunes D6T, Z1 andPYTHIA8 tune 1.
Modeling of V0reconstruction efficiency: The systematic uncertainty on the V0 reconstruction efficiency is estimated from closure tests and from the stability of the results with respect to the V0 selection cuts, as described in Sec.II B.
0.05 0.1 0.15 0.2 0.25 0.3 Data PYTHIA 6 Z1 PYTHIA 6 D6T PYTHIA 8 Tune 1 = 7 TeV s CMS, pp, 0 s K | [deg] φ ∆ | 0 20 40 60 80 100 120 140 160 180 0.02 0.04 0.06 0.08 0.1 Λ ] -1 |) [degφ ∆ /d(|〉0 s K N〈 d× η∆ / 3 10 ] -1 |) [degφ ∆ /d(|〉 Λ N〈 d× η∆ / 3 10
FIG. 3 (color online). Uncorrected average rate of selected V0 candidates per event, per degree, and per unit pseudora-pidity withinjj < 2, as a function of the difference in azimuthal anglejj between the V0candidate and the leading charged-particle jet. Data and detailed simulation of minimum-bias events with different PYTHIA tunes are shown for recon-structed charged-particle jet pT> 1 GeV=c. Top: KS0candidates
with pT> 600 MeV=c; bottom: candidates with pT>
1:5 GeV=c.
TABLE I. Systematic uncertainties on the measured average V0 rates and pTsums.
Average rates
Source K0S(%) (%)
Leading charged-particle jet selection 3 7
Primary vertex selection 1 1
Modeling of V0efficiency
Charged-particle jet pT 2:5 GeV=c 3 10
Charged-particle jet pT> 2:5 GeV=c 3 3
Detector material 3 3
GEANT4cross sections 5
Statistical uncertainty on V0weights 600 MeV=c < pV0 T < 700 MeV=c 0.1 1:5 GeV=c < pV0 T < 1:6 GeV=c 0.03 0.33 6 GeV=c < pV0 T < 8 GeV=c 1.4 8.3 Background estimation
Charged-particle jet pT¼ 1 GeV=c 1.1 2
Charged-particle jet pT¼ 10 GeV=c 1.7 2
Total
Charged-particle jet pT¼ 1 GeV=c 6 14
Charged-particle jet pT¼ 10 GeV=c 6 10
Average pTsums Source K0S(%) (%) Background estimation pV0 T ¼ 600 MeV=c 0.1 pV0 T ¼ 1:5 GeV=c 0.8 0.3 pV0 T ¼ 8 GeV=c 3.6 4.0
Other sources as rates as rates
Detector material: The overall mass of the tracker and the relative fractions of the different tracker materials are varied in the simulations, with the requirement that the resulting predicted tracker weight be consistent with the measured weight [31]. The difference between the results thus obtained and the nominal results is taken as a contri-bution to the systematic uncertainty.
GEANT4cross sections: A 5% systematic uncertainty is assigned to the baryon yields, as a result of the known imperfect modeling of the low-energy antiproton interac-tion cross secinterac-tion in theGEANT4version used [30].
Statistical uncertainty on the V0 yield correction: A small contribution to the total uncertainty stems from the finite size of the sample of minimum-bias events passed through the full detector simulation (50 106 events),
from which the correction is computed.
Estimation of V0 background: The uncertainty on the background remaining after V0 identification by means of the kinematic fit is taken as half the difference between the results of the two background estimation methods used.
The uncertainty on the beam spot position and size gives a negligible contribution to the total uncertainty.
IV. RESULTS
The V0 production rates in the transverse region are shown in Fig. 4 as a function of the leading charged-particle jet pT, and the V0scalar pTsums in the transverse
region are shown in Fig.5.
The rates and pTsums exhibit a rise with increasing hard
scale, followed by a plateau. The turn-on of the plateau is located at charged-particle jet pT’ 10 GeV=c for both
primary mesons and baryons. Above the turn-on, the rates and pT sums are essentially constant, implying also a
constant strange-particle average pT above the turn-on.
A comparison can be made with the trends observed for charged primary particles [1] in spite of the different jet reconstruction algorithm used in Ref. [1] (SISCone). The dependence of the UE activity on the charged-particle jet pT is very similar to that observed for charged primary
particles [1,3,4]. The most striking feature is that the pT
scale at which the plateau starts, around10 GeV=c in pp collisions at pffiffiffis¼ 7 TeV, is independent of the type of primary particle used to probe the UE activity. These observations are consistent with the impact-parameter pic-ture of particle production in hadron collisions [6,7], in which the MPI contribution saturates at scales typical of central collisions.
ThePYTHIA6 Z1 andZ2tunes qualitatively reproduce the dependence of the KS0rate and pTsum on the
charged-particle jet pT, but exhibit a 10%–15% deficit in the yield,
independent of the charged-particle jet pT.PYTHIA8 tune 1 underestimates the activity by about 30%. For the bary-ons,PYTHIA6 tunes Z1,Z2 andPYTHIA8 tune 1 under-estimate the rates by about 50%. After being tuned to the charged-particle data, PYTHIA 6 Z2 models strangeness
0 10 20 30 40 50 |φ ∆ |∆ η∆ /〉0 s K N〈 20 40 60 80 100 120 140 -3 10 × Data PYTHIA 6 Z2* PYTHIA 6 Z1 PYTHIA 6 D6T PYTHIA 8 Tune 1 = 7 TeV s CMS, pp, 0 S Primary K > 0.6 GeV/c T , p o | < 120 φ ∆ < | o 60 [GeV/c] T leading charged-particle jet p
0 10 20 30 40 50 〉 Data 0Ks N〈/〉 MC 0Ks N〈 0.6 0.8 1 1.2 1.4 Syst. uncertainty Total uncertainty |φ ∆ |∆ η∆ /〉Λ N〈 5 10 15 20 25 30 35 40 45 -3 10 × Data PYTHIA 6 Z2* PYTHIA 6 Z1 PYTHIA 6 D6T PYTHIA 8 Tune 1 = 7 TeV s CMS, pp, Λ Primary > 1.5 GeV/c T , p o | < 120 φ ∆ < | o 60 T 0 10 20 30 40 50 〉 Data Λ N〈/〉 MC Λ N〈 0.5 1 1.5 Syst. uncertainty Total uncertainty [GeV/c] leading charged-particle jet p
FIG. 4 (color online). Average multiplicity per unit of pseu-dorapidity and per radian in the transverse region (jj < 2, 60< jj < 120), as a function of the p
T of the leading
charged-particle jet: (top) KS0 with pT> 0:6 GeV=c; (bottom)
with pT> 1:5 GeV=c. Predictions of PYTHIA tunes are compared to the data, and the ratios of simulations to data are shown in the bottom panels. For the data, the statistical uncer-tainties (error bars) and the quadratic sum of statistical and systematic uncertainties (error band) are shown, while for simu-lations the uncertainty is only shown forPYTHIA6 tuneZ2, for clarity.
production in the UE in a very similar way as Z1, in spite of the different parton distribution set used.
PYTHIA6 D6T shows a dependence of the activity on the charged-particle jet pTthat differs from that of the data and
of the other tunes. In addition, the V0 pT distributions
predicted by PYTHIA 6 D6T in the transverse region are in strong disagreement with the data. As an illustration, the pT spectra are shown in Fig. 6 for events with a
[GeV/c]
T
leading charged-particle jet p
0 10 20 30 40 50 | [GeV/c]φ ∆ |∆ η∆ /〉 0s K T pΣ〈 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 Data PYTHIA 6 Z2* PYTHIA 6 Z1 PYTHIA 6 D6T PYTHIA 8 Tune 1 = 7 TeV s CMS, pp, 0 S Primary K > 0.6 GeV/c T , p o | < 120 φ ∆ < | o 60 [GeV/c] T leading charged-particle jet p
0 10 20 30 40 50 〉 Data 0 s T, K pΣ〈 /〉 MC 0 s T, K pΣ〈 0.60.8 1 1.2 1.4 Syst. uncertainty Total uncertainty [GeV/c] T
leading charged-particle jet p
0 10 20 30 40 50 | [GeV/c]φ ∆ |∆ η∆ /〉 Λ T pΣ〈 0.02 0.04 0.06 0.08 0.1 0.12 0.14 Data PYTHIA 6 Z2* PYTHIA 6 Z1 PYTHIA 6 D6T PYTHIA 8 Tune 1 = 7 TeV s CMS, pp, Λ Primary > 1.5 GeV/c T , p o | < 120 φ ∆ < | o 60 0 10 20 30 40 50 〉 Data ΛT, pΣ〈 /〉 MC ΛT, pΣ〈 0.5 1 1.5 Syst. uncertainty Total uncertainty [GeV/c] T leading charged-particle jet p
FIG. 5 (color online). Average scalar pT sum per unit of
pseudorapidity and per radian in the transverse region (jj<2, 60< jj < 120), as a function of the p
T of the leading
charged-particle jet: (top) K0S with pT> 0:6 GeV=c; (bottom)
with pT> 1:5 GeV=c. Predictions of PYTHIA tunes are compared to the data, and the ratios of simulations to data are shown in the bottom panels. For the data, the statistical uncer-tainties (error bars) and the quadratic sum of statistical and systematic uncertainties (error band) are shown, while for simulations the uncertainty is only shown for PYTHIA 6 tune Z2, for clarity. [GeV/c] T p 0 s K 0 2 4 6 8 Candidates / GeV/c 3 10 4 10 5 10 6 10 Data PYTHIA 6 Z1 (x0.98) PYTHIA 6 D6T (x1.54) PYTHIA 8 Tune 1 (x1.33) = 7 TeV s s CMS, pp, 0 S Primary K > 3 GeV/c jet T p o | < 120 φ ∆ < | o 60 [GeV/c] T p Λ 0 2 4 6 8 Candidates / GeV/c 3 10 4 10 5 10 6 10 = 7 TeV CMS, pp, Data PYTHIA 6 Z1 (x1.88) PYTHIA 6 D6T (x1.97) PYTHIA 8 Tune 1 (x2.32) Λ Primary > 3 GeV/c jet T p o | < 120 φ ∆ < | o 60
FIG. 6 (color online). V0pTdistributions corrected for
selec-tion efficiency and background without a correcselec-tion to the leading charged-particle jet, in the region transverse to a leading reconstructed charged-particle jet with pT> 3 GeV=c,
com-pared to predictions from different PYTHIA tunes (top: K0S; bottom: ). Error bars indicate the quadratic sum of the statis-tical and systematic uncertainties. Simulations are normalized to the first pT bin in the data, with normalization factors given in
parentheses.
reconstructed charged-particle jet pT> 3 GeV=c (without
a correction to the leading charged hadron jet). For the K0S
case, in the pTrange observed (pT> 600 MeV=c),PYTHIA 6 tune D6T shows a much harder spectrum than the data, while tune Z1 shows a softer spectrum andPYTHIA8 tune 1 reproduces the shape well. For the case, in the pT> 1:5 GeV=c range, PYTHIA 6 D6T shows a much harder spectrum than the data, while the other simulations describe the data reasonably well.
The ratios of the rates and pT sums of primary V0
mesons to the rates and pT sums of primary charged
particles from Ref. [1] are shown in Fig. 7. The data are integrated over the same pseudorapidity range for strange and charged particles,jj < 2. The K0Sto charged-particle activity ratios are constant in the charged-particle jet pT
range3–50 GeV=c, i.e. almost throughout the whole range studied and, specifically, across the turn-on of the plateau
around 10 GeV=c. An increase is seen below 3 GeV=c. This feature is also present in the simulations but is not as pronounced as in the data, and not in all tunes studied.
The to charged-particle activity ratios exhibit a rise for charged-particle jet pT< 10 GeV=c, followed by a
plateau. A similar dependence is visible in PYTHIA. Simulations indicate that the rise is related to the observed hardening of the baryon pT spectrum as the
charged-particle jet pT increases, combined with the 1:5 GeV=c
pTcut applied to the baryon sample. When the baryon pT
cut is decreased to 0:5 GeV=c as for charged particles, constant ratios are predicted.
Constant strange- to charged-particle activity ratios have thus been measured for K0Smesons for charged-particle jet pT> 3 GeV=c and for baryons for charged-particle jet
pT> 10 GeV=c. In addition, as just discussed, when
accounting for the acceptance of the baryon pT cut, a [GeV/c]
T leading charged-particle jet p
0 10 20 30 40 50 〉 charged N〈 / 〉0 s K N〈 0.02 0.04 0.06 0.08 0.1 0.12 0.14 = 7 TeV s CMS, pp, Data PYTHIA 6 Z2* PYTHIA 6 Z1 PYTHIA 6 D6T PYTHIA 8 Tune 1 o | < 120 φ ∆ < | o 60 > 0.5 GeV/c charged T > 0.6 GeV/c, p 0 S K T p [GeV/c] T leading charged-particle jet p
0 10 20 30 40 50 〉 charged T pΣ〈 / 〉 0 s K T pΣ〈 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 = 7 TeV s CMS, pp, Data PYTHIA 6 Z2* PYTHIA 6 Z1 PYTHIA 6 D6T PYTHIA 8 Tune 1 o | < 120 φ ∆ < | o 60 > 0.5 GeV/c charged T > 0.6 GeV/c, p 0 S K T p [GeV/c] T leading charged-particle jet p
0 10 20 30 40 50 〉 charged N〈 / 〉Λ N〈 5 10 15 20 25 30 35 40 -3 10 × CMS, pp, s = 7 TeV Data PYTHIA 6 Z2* PYTHIA 6 Z1 PYTHIA 6 D6T PYTHIA 8 Tune 1 o | < 120 φ ∆ < | o 60 > 0.5 GeV/c charged T > 1.5 GeV/c, p Λ T p [GeV/c] T leading charged-particle jet p
0 10 20 30 40 50 〉 charged T pΣ〈 / 〉 Λ T pΣ〈 0.02 0.04 0.06 0.08 0.1 = 7 TeV s CMS, pp, Data PYTHIA 6 Z2* PYTHIA 6 Z1 PYTHIA 6 D6T PYTHIA 8 Tune 1 o | < 120 φ ∆ < | o 60 > 0.5 GeV/c charged T > 1.5 GeV/c, p Λ T p
FIG. 7 (color online). Ratios of the average multiplicities and scalar pTsums for primary V0 in the transverse region to the same
quantities for primary charged particles [1] as a function of charged-particle jet pT. The error bars indicate the quadratic sum of the
statistical and systematic uncertainties.
constant ratio is also predicted for baryons at charged-particle jet pT< 10 GeV=c. Since the trends observed are
very similar for charged and strange particles, as well as for mesons and baryons, the present measurements suggest that hadronization and MPI are decoupled.
V. CONCLUSIONS
This paper describes measurements of the underlying event activity in pp collisions at pffiffiffis¼ 7 TeV, probed through the production of primary KS0 mesons and
baryons. The production of KS0 mesons and baryons in the kinematic range pK0S
T > 0:6 GeV=c, pT > 1:5 GeV=c
andjj < 2 is analyzed in the transverse region, defined as60< jj < 120, with the difference in azimu-thal angle between the leading charged-particle jet and the strange-particle directions. The average multiplicity and the average scalar pT sum of primary particles per
event are studied as a function of the leading charged-particle jet pT.
A steep rise of the underlying event activity is seen with increasing leading jet pT, followed by a ‘‘saturation’’
region for jet pT> 10 GeV=c. This trend and the pTscale
above which saturation occurs are very similar to those observed with charged primary particles. The similarity of the behavior for strange and charged particles is consistent with the impact-parameter picture of multiple parton inter-actions in pp collisions, in which the centrality of the pp collision and the MPI activity are correlated.
The results are compared to recent tunes of thePYTHIA Monte Carlo event generator. The PYTHIA simulations underestimate the data by 15%–30% for KS0 mesons and by about 50% for baryons, a MC deficit similar to that observed for the inclusive strange-particle production in pp collisions.
The constant strange- to charged-particle activity ratios and the similar trends for mesons and baryons indicate that the MPI dynamics is decoupled from parton hadronization, with the latter occurring at a later stage.
ACKNOWLEDGMENTS
We congratulate our colleagues in the CERN accelerator departments for the excellent performance 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 gratefully acknowledge the computing centers and personnel of the Worldwide LHC Computing Grid for delivering so effec-tively the computing infrastructure essential to our analy-ses. Finally, 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 Ministry of Science and Research and the Austrian Science Fund; the Belgian Fonds de la Recherche Scientifique, and Fonds voor Wetenschappelijk
Onderzoek; the Brazilian Funding Agencies (CNPq, CAPES, FAPERJ, and FAPESP); the Bulgarian Ministry of Education, Youth and Science; CERN; the Chinese Academy of Sciences, Ministry of Science and Technology, and National Natural Science Foundation of China; the Colombian Funding Agency (COLCIENCIAS); the Croatian Ministry of Science, Education and Sport; the Research Promotion Foundation, Cyprus; the Ministry of Education and Research, Recurrent financing Contract No. SF0690030s09 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 Nucle´aire et de Physique des Particules/CNRS, and Commissariat a` l’E´ nergie Atomique et aux E´ nergies Alternatives/CEA, France; the Bundesministerium fu¨r 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 Office for Research and Technology, 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 Korean Ministry of Education, Science and Technology and the World Class University program of NRF, Republic of Korea; the Lithuanian Academy of Sciences; the Mexican Funding Agencies (CINVESTAV, CONACYT, SEP, and UASLP-FAI); the Ministry of Science and Innovation, New Zealand; the Pakistan Atomic Energy Commission; the Ministry of Science and Higher Education and the National Science Centre, Poland; the Fundac¸a˜o para a Cieˆncia e a Tecnologia, Portugal; JINR (Armenia, Belarus, Georgia, Ukraine, Uzbekistan); the Ministry of Education and Science of the Russian Federation, the Federal Agency of Atomic Energy of the Russian Federation, Russian Academy of Sciences, and the Russian Foundation for Basic Research; the Ministry of Science and Technological Development of Serbia; the Secretarı´a de Estado de Investigacio´n, Desarrollo e Innovacio´n and Programa Consolider-Ingenio 2010, Spain; the Swiss Funding Agencies (ETH Board, ETH Zurich, PSI, SNF, UniZH, Canton Zurich, and SER); the National Science Council, Taipei; the Thailand Center of Excellence in Physics, the Institute for the Promotion of Teaching Science and Technology of Thailand and the National Science and Technology Development Agency of Thailand; the Scientific and Technical Research Council of Turkey, and Turkish Atomic Energy Authority; the Science and Technology Facilities Council, UK; and the US Department of Energy and National Science Foundation. Individuals have received support from the Marie-Curie programme and the European Research Council and EPLANET (European Union); the Leventis Foundation;
the A. P. Sloan Foundation; the Alexander von Humboldt Foundation; the Belgian Federal 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
Czech Republic; the Council of Science and Industrial Research, India; the Compagnia di San Paolo (Torino); the HOMING PLUS programme of Foundation for Polish Science, cofinanced by EU, Regional Development Fund; and the Thalis and Aristeia programmes cofinanced by EU-ESF and the Greek NSRF.
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A. Schmidt,38M. Schro¨der,38T. Schum,38M. Seidel,38J. Sibille,38,tV. Sola,38H. Stadie,38G. Steinbru¨ck,38 J. Thomsen,38D. Troendle,38L. Vanelderen,38C. Barth,39C. Baus,39J. Berger,39C. Bo¨ser,39T. Chwalek,39 W. De Boer,39A. Descroix,39A. Dierlamm,39M. Feindt,39M. Guthoff,39,cC. Hackstein,39F. Hartmann,39,c T. Hauth,39,cM. Heinrich,39H. Held,39K. H. Hoffmann,39U. Husemann,39I. Katkov,39,fJ. R. Komaragiri,39
A. Kornmayer,39,cP. Lobelle Pardo,39D. Martschei,39S. Mueller,39Th. Mu¨ller,39M. Niegel,39A. Nu¨rnberg,39 O. Oberst,39J. Ott,39G. Quast,39K. Rabbertz,39F. Ratnikov,39S. Ro¨cker,39F.-P. Schilling,39G. Schott,39
H. J. Simonis,39F. M. Stober,39R. Ulrich,39J. Wagner-Kuhr,39S. Wayand,39T. Weiler,39M. Zeise,39 G. Anagnostou,40G. Daskalakis,40T. Geralis,40S. Kesisoglou,40A. Kyriakis,40D. Loukas,40A. Markou,40 C. Markou,40E. Ntomari,40L. Gouskos,41T. J. Mertzimekis,41A. Panagiotou,41N. Saoulidou,41E. Stiliaris,41
X. Aslanoglou,42I. Evangelou,42G. Flouris,42C. Foudas,42P. Kokkas,42N. Manthos,42I. Papadopoulos,42 E. Paradas,42G. Bencze,43C. Hajdu,43P. Hidas,43D. Horvath,43,uB. Radics,43F. Sikler,43V. Veszpremi,43 G. Vesztergombi,43,vA. J. Zsigmond,43N. Beni,44S. Czellar,44J. Molnar,44J. Palinkas,44Z. Szillasi,44J. Karancsi,45
P. Raics,45Z. L. Trocsanyi,45B. Ujvari,45S. B. Beri,46V. Bhatnagar,46N. Dhingra,46R. Gupta,46M. Kaur,46 M. Z. Mehta,46M. Mittal,46N. Nishu,46L. K. Saini,46A. Sharma,46J. B. Singh,46Ashok Kumar,47Arun Kumar,47
S. Ahuja,47A. Bhardwaj,47B. C. Choudhary,47S. Malhotra,47M. Naimuddin,47K. Ranjan,47P. Saxena,47 V. Sharma,47R. K. Shivpuri,47S. Banerjee,48S. Bhattacharya,48K. Chatterjee,48S. Dutta,48B. Gomber,48Sa. Jain,48
Sh. Jain,48R. Khurana,48A. Modak,48S. Mukherjee,48D. Roy,48S. Sarkar,48M. Sharan,48A. Abdulsalam,49 D. Dutta,49S. Kailas,49V. Kumar,49A. K. Mohanty,49,cL. M. Pant,49P. Shukla,49A. Topkar,49T. Aziz,50 R. M. Chatterjee,50S. Ganguly,50S. Ghosh,50M. Guchait,50,wA. Gurtu,50,xG. Kole,50S. Kumar,50M. Maity,50,y G. Majumder,50K. Mazumdar,50G. B. Mohanty,50B. Parida,50K. Sudhakar,50N. Wickramage,50,zS. Banerjee,51
S. Dugad,51H. Arfaei,52,aaH. Bakhshiansohi,52S. M. Etesami,52,bbA. Fahim,52,aaH. Hesari,52A. Jafari,52 M. Khakzad,52M. Mohammadi Najafabadi,52S. Paktinat Mehdiabadi,52B. Safarzadeh,52,ccM. Zeinali,52 M. Grunewald,53M. Abbrescia,54a,54bL. Barbone,54a,54bC. Calabria,54a,54bS. S. Chhibra,54a,54bA. Colaleo,54a
D. Creanza,54a,54cN. De Filippis,54a,54c,cM. De Palma,54a,54bL. Fiore,54aG. Iaselli,54a,54cG. Maggi,54a,54c M. Maggi,54aB. Marangelli,54a,54bS. My,54a,54cS. Nuzzo,54a,54bN. Pacifico,54aA. Pompili,54a,54bG. Pugliese,54a,54c G. Selvaggi,54a,54bL. Silvestris,54aG. Singh,54a,54bR. Venditti,54a,54bP. Verwilligen,54aG. Zito,54aG. Abbiendi,55a A. C. Benvenuti,55aD. Bonacorsi,55a,55bS. Braibant-Giacomelli,55a,55bL. Brigliadori,55a,55bR. Campanini,55a,55b
P. Capiluppi,55a,55bA. Castro,55a,55bF. R. Cavallo,55aM. Cuffiani,55a,55bG. M. Dallavalle,55aF. Fabbri,55a A. Fanfani,55a,55bD. Fasanella,55a,55bP. Giacomelli,55aC. Grandi,55aL. Guiducci,55a,55bS. Marcellini,55a G. Masetti,55a,cM. Meneghelli,55a,55bA. Montanari,55aF. L. Navarria,55a,55bF. Odorici,55aA. Perrotta,55a F. Primavera,55a,55bA. M. Rossi,55a,55bT. Rovelli,55a,55bG. P. Siroli,55a,55bN. Tosi,55a,55bR. Travaglini,55a,55b
S. Albergo,56a,56bM. Chiorboli,56a,56bS. Costa,56a,56bF. Giordano,56a,cR. Potenza,56a,56bA. Tricomi,56a,56b C. Tuve,56a,56bG. Barbagli,57aV. Ciulli,57a,57bC. Civinini,57aR. D’Alessandro,57a,57bE. Focardi,57a,57b S. Frosali,57a,57bE. Gallo,57aS. Gonzi,57a,57bV. Gori,57a,57bP. Lenzi,57a,57bM. Meschini,57aS. Paoletti,57a G. Sguazzoni,57aA. Tropiano,57a,57bL. Benussi,58S. Bianco,58F. Fabbri,58D. Piccolo,58P. Fabbricatore,59a R. Musenich,59aS. Tosi,59a,59bA. Benaglia,60aF. De Guio,60a,60bL. Di Matteo,60a,60bS. Fiorendi,60a,60bS. Gennai,60a
A. Ghezzi,60a,60bP. Govoni,60aM. T. Lucchini,60a,cS. Malvezzi,60aR. A. Manzoni,60a,60b,cA. Martelli,60a,60b,c A. Massironi,60a,60bD. Menasce,60aL. Moroni,60aM. Paganoni,60a,60bD. Pedrini,60aS. Ragazzi,60a,60bN. Redaelli,60a
T. Tabarelli de Fatis,60a,60bS. Buontempo,61aN. Cavallo,61a,61cA. De Cosa,61a,61bF. Fabozzi,61a,61c A. O. M. Iorio,61a,61bL. Lista,61aS. Meola,61a,61d,cM. Merola,61aP. Paolucci,61a,cP. Azzi,62aN. Bacchetta,62a D. Bisello,62a,62bA. Branca,62a,62bR. Carlin,62a,62bP. Checchia,62aT. Dorigo,62aU. Dosselli,62aM. Galanti,62a,62b,c
F. Gasparini,62a,62bU. Gasparini,62a,62bP. Giubilato,62a,62bA. Gozzelino,62aK. Kanishchev,62a,62cS. Lacaprara,62a I. Lazzizzera,62a,62cM. Margoni,62a,62bA. T. Meneguzzo,62a,62bM. Passaseo,62aJ. Pazzini,62a,62bM. Pegoraro,62a
N. Pozzobon,62a,62bP. Ronchese,62a,62bF. Simonetto,62a,62bE. Torassa,62aM. Tosi,62a,62bS. Ventura,62a P. Zotto,62a,62bA. Zucchetta,62a,62bG. Zumerle,62a,62bM. Gabusi,63a,63bS. P. Ratti,63a,63bC. Riccardi,63a,63b
P. Vitulo,63a,63bM. Biasini,64a,64bG. M. Bilei,64aL. Fano`,64a,64bP. Lariccia,64a,64bG. Mantovani,64a,64b M. Menichelli,64aA. Nappi,64a,64b,aF. Romeo,64a,64bA. Saha,64aA. Santocchia,64a,64bA. Spiezia,64a,64b
K. Androsov,65a,ddP. Azzurri,65aG. Bagliesi,65aT. Boccali,65aG. Broccolo,65a,65cR. Castaldi,65a
R. T. D’Agnolo,65a,65c,cR. Dell’Orso,65aF. Fiori,65a,65cL. Foa`,65a,65cA. Giassi,65aA. Kraan,65aF. Ligabue,65a,65c T. Lomtadze,65aL. Martini,65a,ddA. Messineo,65a,65bF. Palla,65aA. Rizzi,65a,65bA. T. Serban,65aP. Spagnolo,65a P. Squillacioti,65aR. Tenchini,65aG. Tonelli,65a,65bA. Venturi,65aP. G. Verdini,65aC. Vernieri,65a,65cL. Barone,66a,66b
F. Cavallari,66aD. Del Re,66a,66bM. Diemoz,66aM. Grassi,66a,66b,cE. Longo,66a,66bF. Margaroli,66a,66b P. Meridiani,66aF. Micheli,66a,66bS. Nourbakhsh,66a,66bG. Organtini,66a,66bR. Paramatti,66aS. Rahatlou,66a,66b
L. Soffi,66a,66bN. Amapane,67a,67bR. Arcidiacono,67a,67cS. Argiro,67a,67bM. Arneodo,67a,67cC. Biino,67a N. Cartiglia,67aS. Casasso,67a,67bM. Costa,67a,67bP. De Remigis,67aN. Demaria,67aC. Mariotti,67aS. Maselli,67a
E. Migliore,67a,67bV. Monaco,67a,67bM. Musich,67aM. M. Obertino,67a,67cN. Pastrone,67aM. Pelliccioni,67a,c A. Potenza,67a,67bA. Romero,67a,67bM. Ruspa,67a,67cR. Sacchi,67a,67bA. Solano,67a,67bA. Staiano,67aU. Tamponi,67a
S. Belforte,68aV. Candelise,68a,68bM. Casarsa,68aF. Cossutti,68a,cG. Della Ricca,68a,68bB. Gobbo,68a C. La Licata,68a,68bM. Marone,68a,68bD. Montanino,68a,68bA. Penzo,68aA. Schizzi,68a,68bA. Zanetti,68aT. Y. Kim,69
S. K. Nam,69S. Chang,70D. H. Kim,70G. N. Kim,70J. E. Kim,70D. J. Kong,70Y. D. Oh,70H. Park,70D. C. Son,70 J. Y. Kim,71Zero J. Kim,71S. Song,71S. Choi,72D. Gyun,72B. Hong,72M. Jo,72H. Kim,72T. J. Kim,72K. S. Lee,72 S. K. Park,72Y. Roh,72M. Choi,73J. H. Kim,73C. Park,73I. C. Park,73S. Park,73G. Ryu,73Y. Choi,74Y. K. Choi,74 J. Goh,74M. S. Kim,74E. Kwon,74B. Lee,74J. Lee,74S. Lee,74H. Seo,74I. Yu,74I. Grigelionis,75A. Juodagalvis,75
H. Castilla-Valdez,76E. De La Cruz-Burelo,76I. Heredia-de La Cruz,76,eeR. Lopez-Fernandez,76 J. Martı´nez-Ortega,76A. Sanchez-Hernandez,76L. M. Villasenor-Cendejas,76S. Carrillo Moreno,77 F. Vazquez Valencia,77H. A. Salazar Ibarguen,78E. Casimiro Linares,79A. Morelos Pineda,79M. A. Reyes-Santos,79
D. Krofcheck,80A. J. Bell,81P. H. Butler,81R. Doesburg,81S. Reucroft,81H. Silverwood,81M. Ahmad,82 M. I. Asghar,82J. Butt,82H. R. Hoorani,82S. Khalid,82W. A. Khan,82T. Khurshid,82S. Qazi,82M. A. Shah,82
M. Shoaib,82H. Bialkowska,83B. Boimska,83T. Frueboes,83M. Go´rski,83M. Kazana,83K. Nawrocki,83 K. Romanowska-Rybinska,83M. Szleper,83G. Wrochna,83P. Zalewski,83G. Brona,84K. Bunkowski,84M. Cwiok,84
W. Dominik,84K. Doroba,84A. Kalinowski,84M. Konecki,84J. Krolikowski,84M. Misiura,84W. Wolszczak,84 N. Almeida,85P. Bargassa,85A. David,85P. Faccioli,85P. G. Ferreira Parracho,85M. Gallinaro,85 J. Rodrigues Antunes,85J. Seixas,85,cJ. Varela,85P. Vischia,85P. Bunin,86M. Gavrilenko,86I. Golutvin,86 I. Gorbunov,86A. Kamenev,86V. Karjavin,86V. Konoplyanikov,86G. Kozlov,86A. Lanev,86A. Malakhov,86 V. Matveev,86P. Moisenz,86V. Palichik,86V. Perelygin,86S. Shmatov,86N. Skatchkov,86V. Smirnov,86A. Zarubin,86 S. Evstyukhin,87V. Golovtsov,87Y. Ivanov,87V. Kim,87P. Levchenko,87V. Murzin,87V. Oreshkin,87I. Smirnov,87
V. Sulimov,87L. Uvarov,87S. Vavilov,87A. Vorobyev,87An. Vorobyev,87Yu. Andreev,88A. Dermenev,88 S. Gninenko,88N. Golubev,88M. Kirsanov,88N. Krasnikov,88A. Pashenkov,88D. Tlisov,88A. Toropin,88 V. Epshteyn,89M. Erofeeva,89V. Gavrilov,89N. Lychkovskaya,89V. Popov,89G. Safronov,89S. Semenov,89 A. Spiridonov,89V. Stolin,89E. Vlasov,89A. Zhokin,89V. Andreev,90M. Azarkin,90I. Dremin,90M. Kirakosyan,90
A. Leonidov,90G. Mesyats,90S. V. Rusakov,90A. Vinogradov,90A. Belyaev,91E. Boos,91M. Dubinin,91,h L. Dudko,91A. Ershov,91A. Gribushin,91V. Klyukhin,91O. Kodolova,91I. Lokhtin,91A. Markina,91S. Obraztsov,91 S. Petrushanko,91V. Savrin,91A. Snigirev,91I. Azhgirey,92I. Bayshev,92S. Bitioukov,92V. Kachanov,92A. Kalinin,92
D. Konstantinov,92V. Krychkine,92V. Petrov,92R. Ryutin,92A. Sobol,92L. Tourtchanovitch,92S. Troshin,92 N. Tyurin,92A. Uzunian,92A. Volkov,92P. Adzic,93,ffM. Ekmedzic,93D. Krpic,93,ffJ. Milosevic,93 M. Aguilar-Benitez,94J. Alcaraz Maestre,94C. Battilana,94E. Calvo,94M. Cerrada,94M. Chamizo Llatas,94,c
N. Colino,94B. De La Cruz,94A. Delgado Peris,94D. Domı´nguez Va´zquez,94C. Fernandez Bedoya,94 J. P. Ferna´ndez Ramos,94A. Ferrando,94J. Flix,94M. C. Fouz,94P. Garcia-Abia,94O. Gonzalez Lopez,94 S. Goy Lopez,94J. M. Hernandez,94M. I. Josa,94G. Merino,94E. Navarro De Martino,94J. Puerta Pelayo,94 A. Quintario Olmeda,94I. Redondo,94L. Romero,94J. Santaolalla,94M. S. Soares,94C. Willmott,94C. Albajar,95
J. F. de Troco´niz,95H. Brun,96J. Cuevas,96J. Fernandez Menendez,96S. Folgueras,96I. Gonzalez Caballero,96 L. Lloret Iglesias,96J. Piedra Gomez,96J. A. Brochero Cifuentes,97I. J. Cabrillo,97A. Calderon,97S. H. Chuang,97
J. Duarte Campderros,97M. Fernandez,97G. Gomez,97J. Gonzalez Sanchez,97A. Graziano,97C. Jorda,97 A. Lopez Virto,97J. Marco,97R. Marco,97C. Martinez Rivero,97F. Matorras,97F. J. Munoz Sanchez,97T. Rodrigo,97
A. Y. Rodrı´guez-Marrero,97A. Ruiz-Jimeno,97L. Scodellaro,97I. Vila,97R. Vilar Cortabitarte,97D. Abbaneo,98 E. Auffray,98G. Auzinger,98M. Bachtis,98P. Baillon,98A. H. Ball,98D. Barney,98J. Bendavid,98J. F. Benitez,98
C. Bernet,98,iG. Bianchi,98P. Bloch,98A. Bocci,98A. Bonato,98O. Bondu,98C. Botta,98H. Breuker,98 T. Camporesi,98G. Cerminara,98T. Christiansen,98J. A. Coarasa Perez,98S. Colafranceschi,98,ggD. d’Enterria,98
A. Dabrowski,98A. De Roeck,98S. De Visscher,98S. Di Guida,98M. Dobson,98N. Dupont-Sagorin,98 A. Elliott-Peisert,98J. Eugster,98W. Funk,98G. Georgiou,98M. Giffels,98D. Gigi,98K. Gill,98D. Giordano,98
M. Girone,98M. Giunta,98F. Glege,98R. Gomez-Reino Garrido,98S. Gowdy,98R. Guida,98J. Hammer,98 M. Hansen,98P. Harris,98C. Hartl,98B. Hegner,98A. Hinzmann,98V. Innocente,98P. Janot,98E. Karavakis,98 K. Kousouris,98K. Krajczar,98P. Lecoq,98Y.-J. Lee,98C. Lourenc¸o,98N. Magini,98M. Malberti,98L. Malgeri,98
M. Mannelli,98L. Masetti,98F. Meijers,98S. Mersi,98E. Meschi,98R. Moser,98M. Mulders,98P. Musella,98 E. Nesvold,98L. Orsini,98E. Palencia Cortezon,98E. Perez,98L. Perrozzi,98A. Petrilli,98A. Pfeiffer,98M. Pierini,98
M. Pimia¨,98D. Piparo,98M. Plagge,98G. Polese,98L. Quertenmont,98A. Racz,98W. Reece,98G. Rolandi,98,hh
