Charged particle transverse momentum spectra in pp collisions at sqrt(s) = 0.9 and 7 TeV
EEUROPEAN ORGANIZATION FOR NUCLEAR RESEARCH (CERN)
CERN-PH-EP/2011-0492011/09/30
CMS-QCD-10-008
Charged particle transverse momentum spectrain pp collisions at √ s = 0.9 and 7 TeV The CMS Collaboration ∗ Abstract
The charged particle transverse momentum ( p T ) spectra are presented for pp colli-sions at √ s = µ b − and 2.96 pb − ,respectively. Calorimeter-based high-transverse-energy triggers are employed to en-hance the statistical reach of the high- p T measurements. The results are comparedwith leading and next-to-leading order QCD and with an empirical scaling of mea-surements at different collision energies using the scaling variable x T ≡ p T / √ s overthe p T range up to 200 GeV/ c . Using a combination of x T scaling and direct inter-polation at fixed p T , a reference transverse momentum spectrum at √ s = p T particle suppression in thedense QCD medium produced in heavy-ion collisions at that centre-of-mass energy. Submitted to the Journal of High Energy Physics ∗ See Appendix A for the list of collaboration members a r X i v : . [ h e p - e x ] S e p The charged particle transverse momentum ( p T ) spectrum is an important observable for un-derstanding the fundamental quantum chromodynamic (QCD) interactions involved in proton-proton collisions. While the energy dependence of the bulk of particle production with p T be-low a few GeV/ c is typically described either empirically or with phenomenological models, therest of the spectrum can be well described by a convolution of parton distribution functions,the hard-scattering cross section from perturbative calculations, and fragmentation functions.Such a prescription has been generally successful over a large range of lower energy pp and p ¯pcollisions [1–7]. Along with measurements of the jet production cross section and fragmenta-tion functions, measurements of high- p T spectra provide a test of factorised perturbative QCD(pQCD) [8] at the highest collision energy to date.In addition to its relevance to the understanding of pQCD, the charged particle spectrum in ppcollisions will be an important reference for measurements of high- p T particle suppression inthe dense QCD medium produced in heavy-ion collisions. At the Relativistic Heavy Ion Col-lider (RHIC), the sizable suppression of high- p T particle production, compared to the spectrumexpected from a superposition of a corresponding number of pp collisions, was one of the firstindications of strong final-state medium effects [9–12]. A similar measurement of nuclear mod-ification to charged particle p T spectra has been one of the first heavy-ion results at the LargeHadron Collider (LHC) [13]. The reference spectrum for the PbPb collisions at √ s NN = √ s = 0.9and 7 TeV.In this paper, the phase-space-invariant differential yield E d N ch / dp is presented for primarycharged particles with energy ( E ) and momentum ( p ), averaged over the pseudorapidity accep-tance of the Compact Muon Solenoid (CMS) tracking system ( | η | < θ /2)], with θ being the polar angle of the charged particle with respectto the counterclockwise beam direction. The number of primary charged particles ( N ch ) is de-fined to include decay products of particles with proper lifetimes less than 1 cm. Using theintegrated luminosities calculated in Refs. [14, 15] with an estimated uncertainty of 11% and4% at √ s = x T ≡ p T / √ s . Such a scaling has already been observedfor p ¯p measurements at lower collision energies [4, 5, 16, 17]. For consistency with the CDFmeasurements at √ s = x T distributionshas been restricted to | η | < √ s = √ s = A detailed description of the CMS experiment can be found in Ref. [18]. The central fea-ture of the CMS apparatus is a superconducting solenoid of 6 m internal diameter, provid-ing an axial magnetic field of 3.8 T. Immersed in the magnetic field are the pixel tracker, thesilicon strip tracker, the lead tungstate crystal electromagnetic calorimeter (ECAL), and thebrass/scintillator hadron calorimeter (HCAL). Muons are measured in gas ionisation detectorsembedded in the steel return yoke.The CMS experiment uses a right-handed coordinate system, with the origin at the nominalinteraction point, the x axis pointing to the centre of the LHC ring, the y axis pointing up per-pendicular to the plane of the LHC, and the z axis along the counterclockwise beam direction.The azimuthal angle, φ , is measured in the ( x , y ) plane.The tracker consists of 1440 silicon pixel and 15 148 silicon strip detector modules and measurescharged particle trajectories within the nominal pseudorapidity range | η | < µ m and a transverse momentum resolution of about0.7 % for 1 GeV/ c charged particles at normal incidence ( η =
0) [19].The tracker was aligned as described in Ref. [20] using cosmic ray data prior to the LHC com-missioning. The precision achieved for the positions of the detector modules with respect toparticle trajectories is 3–4 µ m in the barrel for the coordinate in the bending plane ( φ ).Two elements of the CMS detector monitoring system, the beam scintillator counters (BSC)[18, 21] and the beam pick-up timing for the experiments devices (BPTX) [18, 22], were usedto trigger the detector readout. The BSCs are located at a distance of 10.86 m from the nominalinteraction point (IP), one on each side, and are sensitive in the | η | range from 3.23 to 4.65.Each BSC is a set of 16 scintillator tiles. The BSC elements have a time resolution of 3 ns, anaverage minimum ionising particle detection efficiency of 95.7%, and are designed to providehit and coincidence rates. The two BPTX devices, located around the beam pipe at a positionof z = ±
175 m from the IP, are designed to provide precise information on the bunch structureand timing of the incoming beam, with better than 0.2 ns time resolution.The two steel/quartz-fibre forward calorimeters (HF), which extend the calorimetric coveragebeyond the barrel and endcap detectors to the | η | region between 2.9 and 5.2, were used forfurther offline selection of collision events.The detailed Monte Carlo (MC) simulation of the CMS detector response is based on GEANT
This analysis uses data samples collected from 0.9 and 7 TeV pp collisions in the first monthsof the 2010 LHC running, corresponding to integrated luminosities of ( ± ) µ b − and ( ± ) pb − , respectively [14, 15]. This section gives a brief description of the require-ments imposed to select good events for this analysis. A more detailed description of the CMStrigger selections can be found in Ref. [24].First, a minimum bias trigger was used to select events with a signal in any of the BSC tiles,coincident with a signal from either of the two BPTX detectors, indicating the presence of at least one proton bunch crossing the interaction point. From this sample, collision events wereselected offline by requiring a coincidence of BPTX signals, indicating the presence of bothbeams.To select preferentially non-single-diffractive (NSD) events, at least one forward calorimeter(HF) tower with energy deposition E > highPurity criterion. This criterion, described in Ref. [25], consistsof numerous selections on the properties of the tracks, including the normalised χ , the com-patibility with the beamline and primary vertices, the number of hit layers, the number of ‘3D’layers, and the number of lost layers. The selection on the fraction of highPurity tracks wasonly applied to events with more than 10 tracks, providing a clean separation between real ppcollisions and beam backgrounds. The remaining non-collision event fraction, determined byapplying the same selections to events where only a single beam was crossing the interactionpoint, is estimated to be less than 2 x 10 − . Events were required to have at least one primaryvertex, reconstructed according to the description in the following section from triplets of pixelhits. A further requirement, namely at least one vertex found from fully reconstructed tracks(see next section for details) with number of degrees of freedom ( Ndo f ) greater than four, wasimposed to improve the robustness against triggered events containing multiple pp collisions,i.e., “event pileup”. The loss in event selection efficiency from the fully-reconstructed-trackvertex compared to the pixel vertex alone was determined entirely from data, based on a sub-set of early runs with negligible event pileup. The percentage of events remaining after eachselection step is presented in Table 1.For a large part of the 7 TeV data collection, the minimum bias trigger paths had to be prescaledby large factors because of the increasing instantaneous luminosity of the LHC. In order to max-imise the p T reach of the charged particle transverse momentum measurement at this centre-of-mass energy, two high-level trigger (HLT) paths were used that selected events with minimumuncorrected transverse jet energies ( E T ) of 15 and 50 GeV, based only on information from thecalorimeters. While the higher threshold path was not prescaled during the 7 TeV data-takingperiod corresponding to the 2.96 pb − used in this analysis, the lower threshold path had tobe prescaled for a significant fraction of this sample. The 0.9 TeV data sample consists of 6.8million minimum bias triggered events, while the 7 TeV sample is composed of 18.7 millionminimum bias events, and 1.4 (5.6) million events selected with the HLT minimum- E T valuesof 15 (50) GeV.The selection efficiency for NSD events was determined based on simulated events from the PYTHIA [26] event generator (version 6.420, tune D6T [27]) that were subsequently passedthrough a Monte Carlo simulation of the CMS detector response. The resulting event selectionefficiency as a function of the multiplicity of reconstructed charged particles is shown for 7 TeVcollisions in Fig. 1a. The corresponding event selection efficiency is calculated by the sametechnique for the 0.9 TeV data (not shown). Based on events simulated with
PHOJET [28, 29]and
PYTHIA , the remaining fraction of single-diffractive (SD) events in the selected sample wasestimated to be (5 ± ± Table 1: Summary of event selection steps applied to the 0.9 and 7 TeV collision data sets andthe percentage of events from the original minimum bias samples that remain after each step.Collision energy 0.9 TeV 7 TeVSelection Percentage passing each selection cutOne BSC + one BPTX 100.0 100.0BPTX coincidence 94.49 90.05Beam halo rejection 94.08 89.83HF coincidence 73.27 83.32Beam background rejection 73.26 83.32Valid pixel-track vertex 70.14 82.48Quality full-track vertex 64.04 77.35
In this analysis, two separate algorithms are employed to determine the primary vertex po-sition. The first is a highly efficient algorithm based on pixel triplet tracks that requires aminimum of just a single track consistent with the beam-spot position. The position of thebeam-spot, taken as the centre of the region where the LHC beams collide, is calculated foreach LHC fill based on the average over many events of the three-dimensional fitted vertex po-sitions [25]. The second vertex-finding algorithm, based on fully reconstructed tracks with hitsalso in the silicon strip tracker, is less efficient in selecting low-multiplicity events, but morerobust in discriminating against event pileup. Since pileup is significant over the majority ofthe analysed data sample, only the fully-reconstructed-track vertex is used to construct the rawcharged particle momentum spectra. The raw spectra are subsequently corrected for the frac-tion of events with fewer than four tracks (and the fraction of tracks in such low-multiplicityevents), based on a subset of the event sample selected with the more efficient pixel-track vertexrequirement during collision runs with negligible event pileup.To determine the z position of the pixel vertex in each event, tracks consisting of three pixelhits are constructed with a minimum p T of 75 MeV/ c from a region within a transverse distanceof 0.2 cm from the beam axis. The x and y positions of the pixel vertex are taken from thetransverse position of the beam axis. Fitted tracks are selected based on the requirement thatthe transverse impact parameter is less than three times the quadratic sum of the transverseerrors on the track impact parameter and the beam axis position. The selected tracks are thenpassed to an agglomerative algorithm [30], which iteratively clusters the tracks into vertex-candidates. The procedure is halted when the distance between nearest clusters, normalisedby their respective position uncertainties, reaches 12. Only vertices consisting of at least twotracks are kept, except when the event contains a single reconstructed track, which occurs in1.67% (0.99%) of the events at √ s = z position to the vertex with the most associated tracks. These characteristics imply that therejected vertices are not from event pileup, but rather from tracks in the tails of the impactparameter distribution that are not agglomerated into the primary vertex.The fully-reconstructed-track vertex algorithm begins from a set of tracks selected according totheir transverse impact parameter to the beam-spot ( < > χ ( < Charged particle multiplicity s e l e c t ed S D o r f s e l e c t ed N S D e CMS Simulation
PYTHIA 7 TeVNSD selection efficiencypixel vertex (NSD)track vertex (NSD)Selected event SD fractionpixel vertex (SD)track vertex (SD) (a) [cm] z -15 -10 -5 0 5 10 15 [ c m ] PV z -15-10-5051015 110 -1 Ldt = 10.2 nb (cid:242) = 7 TeVsCMS (b)
Figure 1: (a) The efficiency ( ε selectedNSD in Eq. (2)) for selecting non-single-diffractive (NSD) eventsas a function of the multiplicity of reconstructed charged particles in the tracker acceptance( | η | < Ndo f > f selectedSD in Eq. (2)) as a function of charged particle multiplicity for the same selec-tions (solid and dashed lines). (b) Correlation between the z positions, z and z , of thetwo vertices with the most associated tracks for measured events with more than one fully-reconstructed-track vertex satisfying the quality selections.signed a weight between 0 and 1 according to their compatibility with the common vertex [25].Quality vertices are further required to have more than four degrees of freedom ( Ndo f ), corre-sponding to at least four tracks with weights of approximately one. For events with multiplereconstructed vertices passing the quality selection, the correlation between the z positions ofthe two vertices with the most associated tracks is shown in Fig. 1b. Other than the diago-nal region without multiple vertices, expected from the algorithmic parameter of at least a 1 cmseparation, the uncorrelated positions of the two vertices are indicative of random event pileup.The event pileup rate is estimated from the fraction of events with multiple reconstructed ver-tices, after correcting for vertices that are not found because of their proximity. The beamconditions varied over the analysed minimum bias data samples, such that the corrected frac-tion of pileup events is in the range (0.4–7.5)%. The uncertainty on the event pileup fraction,determined from the largest correction to the multiple-vertex fraction, is a constant factor of0.2% and 1.2% for the 0.9 and 7 TeV data, respectively. This analysis uses tracks from the standard CMS reconstruction algorithm, which consists ofmultiple iterations of a combinatorial track finder based on various seeding layer patterns [31].After each iteration, hits belonging unambiguously to tracks in the previous step are removedfrom consideration for subsequent steps. h -2 -1 0 1 2 A l go r i t h m i c e ff i c i en cy PYTHIA 7 TeV > 0.4 GeV/c T p > 2.0 GeV/c T p CMS Simulation (a) [GeV/c] T p t r e · A PYTHIA 7 TeV<20 GeV T T T T T T T T Fake rate
Figure 2: (a) The algorithmic tracking efficiency for two different momentum ranges as a func-tion of η . (b) The product of geometrical acceptance (A) with tracking efficiency ( ε tr ) (upperpoints) and the misidentification (‘fake’) rate (lower points) as a function of transverse momen-tum for tracks with | η | < highPurity selec-tion mentioned in Section 3, the requirement of at least five hits on the track, the normalized χ per degree of freedom divided by the number of tracker layers used in the fit less than a maxi-mum value which varies from 0.48 and 0.07 depending on η and p T , and a relative momentumuncertainty of less than 20%. Furthermore, to reject non-primary tracks (i.e., the products ofweak decays and secondary interactions with detector material), only the pixel-seeded trackingiterations are used, and selections are placed on the impact parameter of the tracks with respectto the primary vertex position. Specifically, the transverse and longitudinal impact parametersare required to be less than 0.2 cm and also less than 3 times the sum in quadrature of the uncer-tainties on the impact parameter and the corresponding vertex position. In the case of multiplequality reconstructed vertices in the minimum bias event samples, tracks that pass the impactparameter selections with respect to any vertex are used in the analysis. The number of events,by which the track p T distribution is normalised, is then scaled by a factor to account for theevent pileup fraction. In contrast, for the jet-triggered samples, tracks are selected based onthe impact parameter with respect to the single vertex responsible for the trigger. The primaryvertex of the hard-scattering process is identified as the vertex with the largest value of ∑ p for the associated fitted tracks.With the above-mentioned selections applied to the reconstructed tracks, the algorithmic ef-ficiency determined from simulated PYTHIA events is greater than 85% (80%) for tracks withtransverse momentum above 2.0 (0.4) GeV/ c averaged over | η | < All events in this analysis are classified according to the transverse energy of the most energeticreconstructed jet, defined as the leading jet. Jets are reconstructed from calorimeter depositsalone using the anti- k T algorithm [32] with cone radius R = (cid:112) ( ∆ φ ) + ( ∆ η ) = p T tracking performance (e.g.,inside a jet) can be parametrised according to this variable. Based on events simulated with PYTHIA in minimum bias and QCD samples with various thresholds on the hard-scatteringscale ( ˆ p T ), the efficiency and misidentification rates of the selected tracks are estimated as afunction of transverse momentum in bins of leading-jet transverse energy (see Fig. 2b). Sec-ond, as discussed in Section 3, calorimeter-based triggers with leading-jet transverse energythresholds of 15 GeV (Jet15U) and 50 GeV (Jet50U) were used to extend the p T reach of the 7 TeVmeasurement.To avoid potential biases from the jet-trigger selection, it is desirable to operate in a regionwhere the trigger is fully efficient. The region above which the jet trigger with an uncorrectedenergy threshold of 15 GeV becomes fully efficient is determined by first plotting the leading-jet E T distribution for a sample of events selected with the prescaled minimum bias trigger andthe offline selections described in Section 3. This distribution is then compared to the subset ofthose events which also fire the 15 GeV jet trigger as a function of corrected transverse energy.The resulting ratio is the trigger efficiency curve presented in the lower panel of Fig. 3a. The15 GeV jet trigger achieves more than 99% efficiency at a corrected energy of E T =
45 GeV. Theanalogous procedure is repeated on a sample of events selected by the 15 GeV jet trigger todetermine that the 50 GeV jet trigger becomes fully efficient above E T =
95 GeV. For the triggerefficiency study, an early subset of the data (10.2 nb − ) was used, because the minimum biasand lower-threshold jet triggers were highly prescaled in the later runs. In the upper panelof Fig. 3a, the E T distributions from the jet-triggered sample are normalised per equivalentminimum bias event by matching their integrals in the regions where the triggers are fullyefficient.For the 7 TeV analysis, events are divided into three classes based on leading-jet E T : below60 GeV, between 60 and 120 GeV, and above 120 GeV. Since each event is uniquely assignedto one such leading-jet E T range, the overall dN ch / dp T distribution is simply the sum of thespectra from the three ranges, each corresponding to a fully-efficient HLT selection (i.e., min-imum bias, 15 GeV jet trigger, and 50 GeV jet trigger). The contributions to the spectra fromthe jet-triggered events are normalised per selected minimum bias event; the fraction of min-imum bias events containing a leading jet with greater than either 60 or 120 GeV is calculatedas shown in Fig. 3a by matching the fully-efficient regions of the leading-jet E T distributions.The three contributions to the combined charged particle transverse momentum spectrum areshown in Fig. 3b. The lower panel of that figure compares the combined spectrum first to theminimum bias spectrum alone and then to a spectrum constructed with the addition of only thelower-threshold jet trigger. These are all in good agreement within their respective statisticaluncertainties. A p T -dependent systematic uncertainty of 0–4% is attributed to the normalisa-tion of the contributions from the triggered samples. This value is determined by changing theleading-jet E T ranges that separate the three samples (e.g., to E T =
40 and 100 GeV), by basingthe normalisation directly on the HLT prescale values, and by comparing the normalisationsdetermined from different subsets of the full data sample. [GeV] corr jetT E ) [ / G e V ] T / d E L ea d i ng Je t ) ( d N E v t M B ( / N -9 -7 -5 -3 -1 ) -1 b m MinBias trigger (413 + Jet15U ) -1 Jet15U trigger (10.2 nb + Jet50U ) -1 Jet50U trigger (2.96 pb = 7 TeVs(a) CMS [GeV] corr jetT E T r i gg e r E ff i c . Jet15U / MinBiasJet50U / Jet15U T p ] - [ ( G e V / c ) T ) d N / dp e v t ( / N -12 -10 -8 -6 -4 -2
10 1 < 60 GeV) T HLT MB (E < 120 GeV) T E £ HLT Jet15U (60 120 GeV) ‡ T HLT Jet50U (E -1 Ldt = 2.96 pb (cid:242) |<2.4 h = 7 TeV |s CMS Combined samples) T MB (all E < 60 GeV) T MB (E 60 GeV) ‡ T + Jet15U (E (b) [GeV/c] T p R a t i o Combined/MBCombined/[MB + Jet15U]
Figure 3: (a) Upper panel: distributions of the corrected transverse energy of leading jets nor-malised by the number of selected minimum bias events N EvtMB . Lower panel: the efficiencyturn-on curves for the jet triggers with uncorrected energy thresholds of 15 and 50 GeV. (b)Upper panel: the three contributions to the charged particle transverse momentum spectrumand their sum (solid circles). Open squares show the minimum bias spectrum for all values ofleading-jet E T ; open triangles show the spectrum with the addition of only the lower thresh-old jet trigger. Lower panel: the ratio of the combined spectrum to minimum bias only (solidcircles) and with the addition of only the lower threshold jet trigger (open triangles). To obtain the final phase-space-invariant charged particle differential momentum distribution,a number of corrections must be applied to the raw distributions of reconstructed chargedparticles, according to the following equation:
E d N ch dp ( p T , η ) = ∑ M , E jetT N rawtrack ( M , E jetT , p T , η ) · w tr ( p T , η , E jetT ) · w ev ( M ) π p T · ∆ p T · ∆ η · ∑ M N selected ( M ) · ( − f ) − · ( + f pileup ) · w ev ( M ) , (1)where N rawtrack is the raw number of tracks in a bin with transverse momentum width ∆ p T andpseudorapidity width ∆ η , and N selected is the number of selected events. An event weight w ev (see Eq. (2)) is applied as a function of the multiplicity of reconstructed charged particles ( M ),while a track weight w tr (see Eq. (3)) is applied for each M and leading-jet transverse energy( E jetT ), as a function of p T ; the final results are summed over M and E jetT . The number of selectedevents is corrected for the fraction of NSD events ( f ) that have zero reconstructed tracks inthe tracker acceptance of | η | < f pileup ).The multiplicity-dependent event weight w ev accounts for the efficiency of the event selectionfor accepting NSD events ( ε selectedNSD ) and for the fraction of SD events ( f selectedSD ) that contaminate Table 2: Summary of the various contributions to the estimated systematic uncertainty.Source Uncertainty [%]Collision energy 0.9 TeV 7 TeVEvent selection 3.2 3.5Pileup effect on vertexing 0.2 1.2Acceptance 1.5 1.5Reconstruction efficiency 2.2 2.2Occupancy effect on efficiency 0.0–0.5 0.0–2.8Misidentified track rate 0.3–1.0 0.3–3.0Correction for secondary particles 1.0 1.0Momentum resolution and binning 0.3–1.5 0.3–2.7Normalisation of jet-triggered spectra – 0.0–4.0Total 4.3–4.7 4.7–7.9Total excluding event selection uncertainty 2.9–3.4 3.1–7.1Total including luminosity uncertainty 11.4–11.6 5.1–8.1the selected sample (about 5% overall): w ev ( M ) = ε selectedNSD ( − f selectedSD ) . (2)The correction factor w tr , by which each track is weighted, is calculated for each bin in trans-verse momentum, pseudorapidity, and leading-jet transverse energy. This factor accounts forthe geometric detector acceptance ( A ) and algorithmic tracking efficiency ( ε tr ), as well as thefraction of tracks corresponding to the same, multiply reconstructed charged particle ( D ), thefraction of tracks corresponding to a non-primary charged particle ( S ), and the fraction ofmisidentified (‘fake’) tracks that do not correspond to any charged particle ( F ): w tr ( p T , η , E jetT ) = ( − F ) · ( − S ) A · ε tr · ( + D ) . (3)The common uncertainty related to the triggering and event selection efficiency is discussed indetail in Ref. [34]. Contributions from uncertain diffractive-event fractions and detector ineffi-ciencies in the BSC and HF combine to contribute a scale error of ± √ s = √ s = ± PYTHIA tune D6T, the various terms in Eq. (3) are esti-mated by matching selected reconstructed tracks to simulated tracks based on the requirementthat they share 75% of their hits. As an example, the algorithmic efficiency ( ε tr ) versus η ispresented in Fig. 2a. The slight asymmetry between the positive and negative hemispheres isattributed to a slightly displaced beam-spot and the distribution of dead channels in the tracker.The systematic uncertainties assigned to the various tracking corrections are discussed belowand are summarised, along with the total systematic uncertainty, in Table 2.The uncertainty on the geometrical acceptance of the tracker was estimated from three sources.First, the efficiency of the pixel hit reconstruction was estimated from a data-driven technique involving the projection of two-hit combinations (called tracklets) onto the third layer in searchof a compatible hit. The observed efficiency of ( ± ) % leads to a 0.3% uncertainty onthe acceptance of pixel-seeded tracks. Second, the variation of the geometrical acceptance wasestimated for a variety of generator tunes including PYTHIA
PYTHIA . Third, the variation was estimated after shifting the generated beam-spot and modi-fying the width of the generated z vertex distribution. The latter two effects each contribute a1% shift in the acceptance.In a similar fashion, using the different generator tunes results in a 2% shift in the reconstruc-tion efficiency. An additional series of checks was performed by varying the cuts imposed dur-ing the track selection and in the determination of the corresponding MC-based corrections.The resulting variation in the corrected results contributes another 1% to the reconstructionefficiency uncertainty.Since the dependence of the reconstruction efficiency on local hit density has been parametrisedin terms of leading-jet transverse energy, both the uncertainty on the jet energy scale and theaccuracy of the jet-fragmentation description become relevant. The former contribution is es-timated by convolving the dependence of the tracking efficiency on the leading-jet transverseenergy (see Fig. 2b) with a 4% uncertainty in the jet energy scale [33]. The latter contributionis estimated by comparing the PYTHIA -based corrections to
HERWIG ++ [37]. The resulting p T -dependent uncertainty on the occupancy is in the range (0.0–2.8)%.Based on studies of different generator tunes and MC samples with different hard-scatteringscales, the assigned uncertainty to the misidentified-track correction grows linearly as a func-tion of p T from 0.3 to 3.0%. An additional check was performed for tracks with p T above10 GeV/ c to correlate the reconstructed track momentum with the deposited energy in the pro-jected ECAL and HCAL cells. For the selected tracks in this analysis, there is no evidence of anyexcess of high- p T misidentified tracks characterised by atypically little energy deposited in thecalorimeters. The correction for secondaries and feed-down from weak decays is assigned a 1%systematic uncertainty, which is large compared to the scale of the contributions, but intendedto account for the uncertainties in the K and Λ fractions [38].The tendency for finite bin widths (up to 40 GeV/ c ) and a finite transverse momentum resolu-tion (rising from 1 to 5% in the range p T = 10–150 GeV/ c ) to deform a steeply falling spectrum iscorrected based on the shape of the p T spectrum and the MC-based p T response matrix. The ef-fect of momentum resolution alone is 0.5–2.5%, while the wide binning results in an additionalcorrection ranging from a fraction of a percent up to approximately 20% in the widest high- p T bins. The correction for the two effects is determined by fitting an empirical function to the dif-ferential yield, smearing it with the MC-based momentum resolution, re-binning into the binsof the final invariant yield, and dividing by the original fitted form. The quoted systematic un-certainty of 0.3–2.7% is estimated by varying the fitted form of the spectrum and by performingmultiple iterations of the unsmearing with successively more accurate input spectra.In addition to the uncertainties from the event selection efficiency weighting and the trackingcorrections described above, the total systematic uncertainty contains a contribution from theuncertainty on the estimation of the event pileup fraction of 0.2 and 1.2% for the 0.9 and 7 TeVdata, respectively. In the cases where the total integrated luminosity is used to normalise theresults, this contributes an additional 4% (11%) scale uncertainty [14, 15] for √ s = 7 (0.9) TeV.Assuming that the various p T -dependent contributions are uncorrelated, the total systematicuncertainty is determined from their sum in quadrature, as indicated in Table 2. [GeV/c] T p ] c - [ G e V N / dp E d -4 -3 -2 -1
10 110 |<2.4 h = 0.9 TeV, |s -1 b m Ldt = 231 (cid:242)
CMS CMS (JHEP 02 (2010) 041)Tsallis fit (JHEP 02 (2010) 041) (a) [GeV/c] T p D a t a / F i t [GeV/c] T p ] c - [ G e V N / dp E d -5 -4 -3 -2 -1
10 110 |<2.4 h = 7 TeV, |s -1 Ldt = 2.96 pb (cid:242)
CMS CMS (PRL 105, 022002)Tsallis fit (PRL 105, 022002) (b) [GeV/c] T p D a t a / F i t Figure 4: (a) Upper panel: the invariant charged particle differential yield from the presentanalysis (solid circles) and the previous CMS measurements at √ s = p T range of the earlier result. Lower panel: the ratio of the new (solid circles) and pre-vious (stars) CMS results to a Tsallis fit of the earlier measurement. Error bars on the earliermeasurement are the statistical plus systematic uncertainties added in quadrature. The sys-tematic uncertainty band around the new measurement consists of all contributions, except forthe common event selection uncertainty. (b) The same for √ s = After applying the corrections described in the previous section, the resulting invariant differ-ential yields for charged particles within | η | < p T range in Figs. 4aand 4b in order to quantify the agreement with previous CMS measurements at √ s = p T range. Below p T = c for the 0.9 TeV sam-ple and below p T = c at √ s = 7 TeV, which are the limits of the previously published CMSspectra, the new results are in reasonable agreement with the earlier measurements. However,the measured spectra do deviate from the Tsallis fits in the earlier papers by as much as 20% atlow p T . The origin of the small difference between the two CMS measurements at √ s = PYTHIA tunes used to determine the tracking corrections.In the upper plots of Figs. 5a and 5b, the charged particle differential transverse momentumyields from this analysis are displayed for √ s = 0.9 and 7 TeV, respectively. The latter distribu-tion covers the p T range up to 200 GeV/ c , the largest range ever measured in a colliding beam [GeV/c] T p ] c - [ G e V N / dp E d -14 -12 -10 -8 -6 -4 -2
10 110 |<2.4 h = 0.9 TeV, |s -1 b m Ldt = 231 (cid:242)
CMS PYTHIA D6TPYTHIA Perugia0PYTHIA ProQ20PYTHIA 8 (a) [GeV/c] T p D A T A / M C [GeV/c] T p ] c - [ G e V N / dp E d -17 -15 -13 -11 -9 -7 -5 -3 -1 |<2.4 h = 7 TeV, |s -1 Ldt = 2.96 pb (cid:242)
CMS PYTHIA D6TPYTHIA Perugia0PYTHIA ProQ20PYTHIA 8 (b) [GeV/c] T p D A T A / M C Figure 5: (a) Upper panel: the invariant charged particle differential yield at √ s = PYTHIA
MC generator. Lower panel: theratio of the new CMS measurement to the four
PYTHIA tunes. The grey band corresponds tothe statistical and systematic uncertainties added in quadrature. (b) The same for √ s = p T < c particles in thepredicted 7 TeV spectra for several of the popular PYTHIA tunes. For the whole p T range above1 GeV/ c , PYTHIA √ s = x T : E d σ dp = F ( x T ) / p n ( x T , √ s ) T = F (cid:48) ( x T ) / √ s n ( x T , √ s ) , (4)where F and F (cid:48) are independent of √ s , and the slow evolution of the power-law exponent n with x T and √ s ( n (cid:39) α s and changes in the parton distributionand fragmentation functions. In the upper plot of Fig. 6a, the 0.9 and 7 TeV pp measurementsfrom this analysis are compared to the empirical scaling observed from measurements over arange of lower p ¯p collision energies by plotting √ s n E d σ / dp . For the purpose of reportingthe CMS results as differential cross sections, the integrated luminosities for the analysed datasamples were measured according to the descriptions in Ref. [14, 15]. Also, to compare with thepublished results from the CDF experiment at √ s = range has been restricted to | η | < n = √ s = x T scaling presented in this paper is optimised for use in an interpolation between the CDF andCMS measurements from √ s = n = ± x T range with the empirical x T scaling givenby Eq. (4) and established at lower energies. This quality of the scaling is more easily seen in theupper panel of Fig. 6b, where the points show the ratio of the various differential cross sections,scaled by √ s , to the result of a global power-law fit to the CDF and CMS data from Fig. 6a.The fitting function is of the form F (cid:48) ( x T ) = p · [ + ( x T / p )] p , where p , p , and p are freeparameters, and the region below p T = c has been excluded to avoid complicationsfrom soft-particle production. Considering the somewhat na¨ıve power-law function and theexpected non-scaling effects [45], the new measurement is in reasonable agreement with theglobal power-law fit result (within roughly 50%) over its full x T range. In order to construct a predicted reference charged particle differential cross section at √ s =2.76 TeV for comparison with the measured PbPb heavy-ion spectrum, two different techniquesare used in partially overlapping transverse momentum regimes. In the high- p T range from5.0–200 GeV/ c , where approximate x T scaling is expected to hold, the estimated 2.76 TeV crosssection is derived from a common x T -scaling curve, based on the CDF and CMS measurementsshown in Fig. 6a. In the low- p T range from 1.0–20 GeV/ c , it is possible to interpolate directlybetween the several measured cross section values as a function of √ s at each fixed p T value.As discussed in the previous section, the upper panel of Fig. 6b shows the residual differencefrom perfect x T scaling with exponent n = √ s and x T dependence of the residuals are notunexpected, since this behaviour is predicted by NLO calculations. This can be seen in thelower panel of Fig. 6b, which shows the predicted deviation from perfect x T scaling for calcu-lated NLO cross sections at several collision energies with respect to a reference centre-of-massenergy of 2.75 TeV [42]. The calculations were performed using the CTEQ66 parton distributionfunctions [46], DSS fragmentation [47], and a factorisation scale µ = p T [42]. Taking the mag-nitude of the x T -scaling violation from NLO (ranging from 0–20%), each of the three measure-ments in data (i.e., 0.9, 1.96, and 7 TeV) can be corrected separately to arrive at an expectationfor the 2.76 TeV cross section. The three independent interpolations based on NLO-corrected x T scaling are shown as solid blue lines in the upper panel of Fig. 6b. The combined ‘best es-timate’ (shown as a shaded band) has an associated uncertainty that covers the deviations ofup to 12% observed by varying the factorisation scale from µ = p T to µ = p T for eachof the three collision energies. The error band is expanded below p T ≈ c to include thefull difference between the 1.96 and 7 TeV results, since the evolution of the spectra below thisvalue — corresponding to x T = x T scaling and the NLO-based corrections. In addition to the12% contribution from the uncertainty on the NLO-based correction, the final uncertainty on T x -4 -3 -2 -1 ] c - [ m b G e V / dp s E d . / G e V ) s ( |<1.0) h ) + X (| - +h + fi ) p pp( ) -1 CMS 7 TeV (2.96 pb ) -1 b m CMS 0.9 TeV (231 CDF 1.96 TeVCDF 1.8 TeVCDF 0.63 TeVGlobal power-law fit (a) T x -4 -3 -2 -1 D a t a / N L O = 0.9 TeVs = 1.96 TeVs = 7 TeVs T x / F i t / dp s E d . / G e V ) s ( = 2.76 TeVs (GeV/c) for T p10 20 30 40 50 60 70 80 90 (b) ) + fit -1 CMS 7 TeV (2.96 pb ) + fit -1 b m CMS 0.9 TeV (231 CDF 1.96 TeV + fit interpolations T T x N L O r a t i o = 2.75 TeV)s = 0.9, 1.96, 7 TeV / s ( /dp s Ed )s Ratio of ( = 0.9 TeVs = 1.96 TeVs = 7 TeVs Figure 6: (a) Upper panel: inclusive charged particle invariant differential cross sections, scaledby √ s , for | η | < x T . The result is the average ofthe positive and negative charged particles. Lower panel: ratios of differential cross sectionsmeasured at 0.9, 1.96, and 7 TeV to those predicted by NLO calculations for factorisation scalesranging from 0.5–2.0 p T . (b) Upper panel: ratios of the scaled differential cross sections tothe global power-law x T fit described in the text (coloured markers) and fits to these ratios(similarly coloured thin lines). The expected ratio for √ s = x T to p T for √ s = √ s , to the cross section calculated at √ s = p T is done using CDF measurementsat √ s = √ s = √ s = PYTHIA . Ateach energy, an empirical fit to the p T distribution is first constructed to provide a continuousestimation independent of different binning. Then, in arbitrarily small p T bins, these empiricalfits are evaluated and the evolution of the cross section with √ s is parametrised by a second-order polynomial. Two examples of these fits are shown in Fig. 7a for p T = c .The uncertainty on the value of the fit evaluated at √ s = To arrive at a single interpolated spectrum over the full p T range, a linear combination ofthe two techniques is used with weights that vary linearly across the overlap range from p T = c (only direct interpolation at fixed p T ) to p T =
20 GeV/ c (only x T scaling withNLO-based residual correction). In the p T range where the two techniques overlap, the differ-ent methods agree to within their respective systematic uncertainties. (The fixed- p T interpo-lation value is typically around 8% lower than the x T interpolation.) The resulting predicted2.76 TeV differential cross section is shown in the upper panel of Fig. 7b, and its ratio with re-spect to various PYTHIA tunes at that centre-of-mass energy in the lower panel. The uncertaintyon the predicted cross section, shown by the grey band in the lower panel, is the weighted sum(where applicable) of the uncertainties derived from the two methods described in the preced-ing paragraphs. Also shown in the lower panel of Fig. 7b is the ratio of the predicted 2.76 TeVcross section to that found by simply scaling the CMS measured 7 TeV result by the expected2.75 TeV to 7 TeV ratio from NLO calculations [42]. The interpolation used in the recent ALICEpublication [13] is a few percent lower than the result quoted in this paper, but consistent withinthe respective systematic uncertainties. The behavior of the various generators compared to theinterpolated 2.76 TeV cross section is broadly similar to the 0.9 TeV invariant yields presented inFig. 7b. The ProQ20 tune agrees most closely (within 15%) with the interpolated cross sectionabove 2 GeV/ c . Future analysis of a recently recorded 2.76 TeV pp collision sample will provideverification of this result and a reduction in the systematic uncertainties.
10 Summary
In this paper, measurements of the phase-space-invariant differential yield
E d N ch / dp at √ s = 0.9 and 7 TeV have been presented for primary charged particles, averaged over the pseu-dorapidity acceptance of the CMS tracking system ( | η | < √ s = 0.9and 7 TeV [24, 34] and, except for the surplus of tracks at very low transverse momentum, with PYTHIA leading-order pQCD. The 7 TeV data are most consistent with
PYTHIA
8, which agrees atthe 10% level over the full p T range of the measurement. In contrast, the 0.9 TeV data are consid-erably better described by the ProQ20 tune. Additionally, the consistency of the 0.9 and 7 TeVspectra has been demonstrated with an empirical x T scaling that unifies the differential crosssections from a wide range of collision energies onto a common curve. Furthermore, withinthe theoretical uncertainties of the NLO calculations, the residual breaking of x T scaling above p T ≈ c is consistent between the measured cross sections and the NLO calculations.This result has removed a large uncertainty from an important ingredient of existing and futurePbPb measurements, namely the pp reference spectrum corresponding to the energy of the2010 PbPb run: 2.76 TeV per nucleon. By employing a combination of techniques to interpolatebetween the results presented here at √ s = √ s = √ s = p T = 1–100 GeV/ c ) with systematicuncertainties of less than 13%. Acknowledgements
We wish to congratulate our colleagues in the CERN accelerator departments for the excellentperformance of the LHC machine. We thank the technical and administrative staff at CERN andother CMS institutes, and acknowledge support from: FMSR (Austria); FNRS and FWO (Bel-gium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and
10 Summary [TeV]s ] c - [ m b G e V / dp s E d -2 -1 (a) = 3 GeV/c T p |<1.0) h ) + X (| - +h + fi ) p pp( ) -1 CMS 7 TeV (2.96 pb CDF 1.96 TeV) -1 b m CMS 2.36 TeV (0.2 CDF 1.8 TeV) -1 b m CMS 0.9 TeV (231 CDF 0.63 TeV [TeV]s ] x c - [ m b G e V / dp s E d -5 -4 = 9 GeV/c T p = 2.76 TeV interpolated values scaling interp. T x [GeV/c] T p ] c - [ m b G e V / dp s E d -14 -12 -10 -8 -6 -4 -2
10 1 |<1.0 h = 2.76 TeV, |s CMS InterpolationPYTHIA D6TPYTHIA Perugia0PYTHIA ProQ20PYTHIA 8NLO rescaled CMS 7 TeV (F. Arleo et al.) = 64 mb) mb s ALICE (scaled by (b) [GeV/c] T p I n t e r p . / O t he r s Figure 7: (a) Interpolations between measured charged particle differential cross sections atdifferent √ s for the two example values of p T = c . Second-order polynomialfits to the measured data are shown by the solid lines. The open squares show the resultinginterpolated cross sections for √ s = x T -scaling approach in the overlap region where both canbe estimated. (b) Upper panel: the predicted 2.76 TeV charged particle differential transversemomentum cross section, based on the combined direct p T interpolation and NLO-corrected x T -scaling techniques described in the text. Lower panel: ratios of combined interpolation topredictions from several PYTHIA tunes, an NLO-based rescaling approach [42], and the ALICEinterpolation used in Ref. [13].NSFC (China); COLCIENCIAS (Colombia); MSES (Croatia); RPF (Cyprus); Academy of Sci-ences and NICPB (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3(France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NKTH (Hungary);DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); NRF and WCU (Korea); LAS(Lithuania); CINVESTAV, CONACYT, SEP, and UASLP-FAI (Mexico); PAEC (Pakistan); SCSR(Poland); FCT (Portugal); JINR (Armenia, Belarus, Georgia, Ukraine, Uzbekistan); MST andMAE (Russia); MSTD (Serbia); MICINN and CPAN (Spain); Swiss Funding Agencies (Switzer-land); NSC (Taipei); TUBITAK and TAEK (Turkey); STFC (United Kingdom); DOE and NSF(USA). Individuals have received support from the Marie-Curie programme and the EuropeanResearch Council (European Union); the Leventis Foundation; the A. P. Sloan Foundation; theAlexander von Humboldt Foundation; the Associazione per lo Sviluppo Scientifico e Tecno-logico del Piemonte (Italy); the Belgian Federal Science Policy Office; the Fonds pour la Forma-tion `a la Recherche dans l’Industrie et dans l’Agriculture (FRIA-Belgium); and the Agentschapvoor Innovatie door Wetenschap en Technologie (IWT-Belgium). References [1] F. Arleo and D. d’Enterria, “Single inclusive pion p T -spectra in proton-proton collisionsat √ s = 22.4 GeV: data versus perturbative QCD calculations”, Phys. Rev.
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D75 (2007) 114010, arXiv:hep-ph/0703242 . doi:10.1103/PhysRevD.75.114010 . A The CMS Collaboration
Yerevan Physics Institute, Yerevan, Armenia
S. Chatrchyan, V. Khachatryan, A.M. Sirunyan, A. Tumasyan
Institut f ¨ur Hochenergiephysik der OeAW, Wien, Austria
W. Adam, T. Bergauer, M. Dragicevic, J. Er ¨o, C. Fabjan, M. Friedl, R. Fr ¨uhwirth, V.M. Ghete,J. Hammer , S. H¨ansel, M. Hoch, N. H ¨ormann, J. Hrubec, M. Jeitler, W. Kiesenhofer,M. Krammer, D. Liko, I. Mikulec, M. Pernicka, H. Rohringer, R. Sch ¨ofbeck, J. Strauss, A. Taurok,F. Teischinger, P. Wagner, W. Waltenberger, G. Walzel, E. Widl, C.-E. Wulz National Centre for Particle and High Energy Physics, Minsk, Belarus
V. Mossolov, N. Shumeiko, J. Suarez Gonzalez
Universiteit Antwerpen, Antwerpen, Belgium
L. Benucci, E.A. De Wolf, X. Janssen, J. Maes, T. Maes, L. Mucibello, S. Ochesanu, B. Roland,R. Rougny, M. Selvaggi, H. Van Haevermaet, P. Van Mechelen, N. Van Remortel
Vrije Universiteit Brussel, Brussel, Belgium
F. Blekman, S. Blyweert, J. D’Hondt, O. Devroede, R. Gonzalez Suarez, A. Kalogeropoulos,M. Maes, W. Van Doninck, P. Van Mulders, G.P. Van Onsem, I. Villella
Universit´e Libre de Bruxelles, Bruxelles, Belgium
O. Charaf, B. Clerbaux, G. De Lentdecker, V. Dero, A.P.R. Gay, G.H. Hammad, T. Hreus,P.E. Marage, L. Thomas, C. Vander Velde, P. Vanlaer
Ghent University, Ghent, Belgium
V. Adler, A. Cimmino, S. Costantini, M. Grunewald, B. Klein, J. Lellouch, A. Marinov,J. Mccartin, D. Ryckbosch, F. Thyssen, M. Tytgat, L. Vanelderen, P. Verwilligen, S. Walsh,N. Zaganidis
Universit´e Catholique de Louvain, Louvain-la-Neuve, Belgium
S. Basegmez, G. Bruno, J. Caudron, L. Ceard, E. Cortina Gil, J. De Favereau De Jeneret,C. Delaere , D. Favart, A. Giammanco, G. Gr´egoire, J. Hollar, V. Lemaitre, J. Liao, O. Militaru,S. Ovyn, D. Pagano, A. Pin, K. Piotrzkowski, N. Schul Universit´e de Mons, Mons, Belgium
N. Beliy, T. Caebergs, E. Daubie
Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil
G.A. Alves, D. De Jesus Damiao, M.E. Pol, M.H.G. Souza
Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil
W. Carvalho, E.M. Da Costa, C. De Oliveira Martins, S. Fonseca De Souza, L. Mundim,H. Nogima, V. Oguri, W.L. Prado Da Silva, A. Santoro, S.M. Silva Do Amaral, A. Sznajder,F. Torres Da Silva De Araujo
Instituto de Fisica Teorica, Universidade Estadual Paulista, Sao Paulo, Brazil
F.A. Dias, T.R. Fernandez Perez Tomei, E. M. Gregores , C. Lagana, F. Marinho,P.G. Mercadante , S.F. Novaes, Sandra S. Padula Institute for Nuclear Research and Nuclear Energy, Sofia, Bulgaria
N. Darmenov , L. Dimitrov, V. Genchev , P. Iaydjiev , S. Piperov, M. Rodozov, S. Stoykova,G. Sultanov, V. Tcholakov, R. Trayanov, I. Vankov A The CMS Collaboration
University of Sofia, Sofia, Bulgaria
A. Dimitrov, R. Hadjiiska, A. Karadzhinova, V. Kozhuharov, L. Litov, M. Mateev, B. Pavlov,P. Petkov
Institute of High Energy Physics, Beijing, China
J.G. Bian, G.M. Chen, H.S. Chen, C.H. Jiang, D. Liang, S. Liang, X. Meng, J. Tao, J. Wang,J. Wang, X. Wang, Z. Wang, H. Xiao, M. Xu, J. Zang, Z. Zhang
State Key Lab. of Nucl. Phys. and Tech., Peking University, Beijing, China
Y. Ban, S. Guo, Y. Guo, W. Li, Y. Mao, S.J. Qian, H. Teng, L. Zhang, B. Zhu, W. Zou
Universidad de Los Andes, Bogota, Colombia
A. Cabrera, B. Gomez Moreno, A.A. Ocampo Rios, A.F. Osorio Oliveros, J.C. Sanabria
Technical University of Split, Split, Croatia
N. Godinovic, D. Lelas, K. Lelas, R. Plestina , D. Polic, I. Puljak University of Split, Split, Croatia
Z. Antunovic, M. Dzelalija
Institute Rudjer Boskovic, Zagreb, Croatia
V. Brigljevic, S. Duric, K. Kadija, S. Morovic
University of Cyprus, Nicosia, Cyprus
A. Attikis, M. Galanti, J. Mousa, C. Nicolaou, F. Ptochos, P.A. Razis
Charles University, Prague, Czech Republic
M. Finger, M. Finger Jr.
Academy of Scientific Research and Technology of the Arab Republic of Egypt, EgyptianNetwork of High Energy Physics, Cairo, Egypt
Y. Assran , S. Khalil , M.A. Mahmoud National Institute of Chemical Physics and Biophysics, Tallinn, Estonia
A. Hektor, M. Kadastik, M. M ¨untel, M. Raidal, L. Rebane
Department of Physics, University of Helsinki, Helsinki, Finland
V. Azzolini, P. Eerola, G. Fedi
Helsinki Institute of Physics, Helsinki, Finland
S. Czellar, J. H¨ark ¨onen, A. Heikkinen, V. Karim¨aki, R. Kinnunen, M.J. Kortelainen, T. Lamp´en,K. Lassila-Perini, S. Lehti, T. Lind´en, P. Luukka, T. M¨aenp¨a¨a, E. Tuominen, J. Tuominiemi,E. Tuovinen, D. Ungaro, L. Wendland
Lappeenranta University of Technology, Lappeenranta, Finland
K. Banzuzi, A. Korpela, T. Tuuva
Laboratoire d’Annecy-le-Vieux de Physique des Particules, IN2P3-CNRS, Annecy-le-Vieux,France
D. Sillou
DSM/IRFU, CEA/Saclay, Gif-sur-Yvette, France
M. Besancon, S. Choudhury, M. Dejardin, D. Denegri, B. Fabbro, J.L. Faure, F. Ferri, S. Ganjour,F.X. Gentit, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry, E. Locci, J. Malcles,M. Marionneau, L. Millischer, J. Rander, A. Rosowsky, I. Shreyber, M. Titov, P. Verrecchia Laboratoire Leprince-Ringuet, Ecole Polytechnique, IN2P3-CNRS, Palaiseau, France
S. Baffioni, F. Beaudette, L. Benhabib, L. Bianchini, M. Bluj , C. Broutin, P. Busson, C. Charlot,T. Dahms, L. Dobrzynski, S. Elgammal, R. Granier de Cassagnac, M. Haguenauer, P. Min´e,C. Mironov, C. Ochando, P. Paganini, D. Sabes, R. Salerno, Y. Sirois, C. Thiebaux, B. Wyslouch ,A. Zabi Institut Pluridisciplinaire Hubert Curien, Universit´e de Strasbourg, Universit´e de HauteAlsace Mulhouse, CNRS/IN2P3, Strasbourg, France
J.-L. Agram , J. Andrea, D. Bloch, D. Bodin, J.-M. Brom, M. Cardaci, E.C. Chabert, C. Collard,E. Conte , F. Drouhin , C. Ferro, J.-C. Fontaine , D. Gel´e, U. Goerlach, S. Greder, P. Juillot,M. Karim , A.-C. Le Bihan, Y. Mikami, P. Van Hove Centre de Calcul de l’Institut National de Physique Nucleaire et de Physique desParticules (IN2P3), Villeurbanne, France
F. Fassi, D. Mercier
Universit´e de Lyon, Universit´e Claude Bernard Lyon 1, CNRS-IN2P3, Institut de PhysiqueNucl´eaire de Lyon, Villeurbanne, France
C. Baty, S. Beauceron, N. Beaupere, M. Bedjidian, O. Bondu, G. Boudoul, D. Boumediene,H. Brun, J. Chasserat, R. Chierici, D. Contardo, P. Depasse, H. El Mamouni, J. Fay, S. Gascon,B. Ille, T. Kurca, T. Le Grand, M. Lethuillier, L. Mirabito, S. Perries, V. Sordini, S. Tosi, Y. Tschudi,P. Verdier
Institute of High Energy Physics and Informatization, Tbilisi State University, Tbilisi,Georgia
D. Lomidze
RWTH Aachen University, I. Physikalisches Institut, Aachen, Germany
G. Anagnostou, M. Edelhoff, L. Feld, N. Heracleous, O. Hindrichs, R. Jussen, K. Klein, J. Merz,N. Mohr, A. Ostapchuk, A. Perieanu, F. Raupach, J. Sammet, S. Schael, D. Sprenger, H. Weber,M. Weber, B. Wittmer
RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany
M. Ata, W. Bender, E. Dietz-Laursonn, M. Erdmann, J. Frangenheim, T. Hebbeker,A. Hinzmann, K. Hoepfner, T. Klimkovich, D. Klingebiel, P. Kreuzer, D. Lanske † , C. Magass,M. Merschmeyer, A. Meyer, P. Papacz, H. Pieta, H. Reithler, S.A. Schmitz, L. Sonnenschein,J. Steggemann, D. Teyssier RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany
M. Bontenackels, M. Davids, M. Duda, G. Fl ¨ugge, H. Geenen, M. Giffels, W. Haj Ahmad,D. Heydhausen, T. Kress, Y. Kuessel, A. Linn, A. Nowack, L. Perchalla, O. Pooth, J. Rennefeld,P. Sauerland, A. Stahl, M. Thomas, D. Tornier, M.H. Zoeller
Deutsches Elektronen-Synchrotron, Hamburg, Germany
M. Aldaya Martin, W. Behrenhoff, U. Behrens, M. Bergholz , A. Bethani, K. Borras, A. Cakir,A. Campbell, E. Castro, D. Dammann, G. Eckerlin, D. Eckstein, A. Flossdorf, G. Flucke,A. Geiser, J. Hauk, H. Jung , M. Kasemann, I. Katkov , P. Katsas, C. Kleinwort, H. Kluge,A. Knutsson, M. Kr¨amer, D. Kr ¨ucker, E. Kuznetsova, W. Lange, W. Lohmann , R. Mankel,M. Marienfeld, I.-A. Melzer-Pellmann, A.B. Meyer, J. Mnich, A. Mussgiller, J. Olzem, D. Pitzl,A. Raspereza, A. Raval, M. Rosin, R. Schmidt , T. Schoerner-Sadenius, N. Sen, A. Spiridonov,M. Stein, J. Tomaszewska, R. Walsh, C. Wissing University of Hamburg, Hamburg, Germany
C. Autermann, V. Blobel, S. Bobrovskyi, J. Draeger, H. Enderle, U. Gebbert, K. Kaschube, A The CMS Collaboration
G. Kaussen, R. Klanner, J. Lange, B. Mura, S. Naumann-Emme, F. Nowak, N. Pietsch, C. Sander,H. Schettler, P. Schleper, M. Schr ¨oder, T. Schum, J. Schwandt, H. Stadie, G. Steinbr ¨uck,J. Thomsen
Institut f ¨ur Experimentelle Kernphysik, Karlsruhe, Germany
C. Barth, J. Bauer, V. Buege, T. Chwalek, W. De Boer, A. Dierlamm, G. Dirkes, M. Feindt,J. Gruschke, C. Hackstein, F. Hartmann, M. Heinrich, H. Held, K.H. Hoffmann, S. Honc,J.R. Komaragiri, T. Kuhr, D. Martschei, S. Mueller, Th. M ¨uller, M. Niegel, O. Oberst, A. Oehler,J. Ott, T. Peiffer, G. Quast, K. Rabbertz, F. Ratnikov, N. Ratnikova, M. Renz, C. Saout,A. Scheurer, P. Schieferdecker, F.-P. Schilling, M. Schmanau, G. Schott, H.J. Simonis, F.M. Stober,D. Troendle, J. Wagner-Kuhr, T. Weiler, M. Zeise, V. Zhukov , E.B. Ziebarth Institute of Nuclear Physics ”Demokritos”, Aghia Paraskevi, Greece
G. Daskalakis, T. Geralis, S. Kesisoglou, A. Kyriakis, D. Loukas, I. Manolakos, A. Markou,C. Markou, C. Mavrommatis, E. Ntomari, E. Petrakou
University of Athens, Athens, Greece
L. Gouskos, T.J. Mertzimekis, A. Panagiotou, E. Stiliaris
University of Io´annina, Io´annina, Greece
I. Evangelou, C. Foudas, P. Kokkas, N. Manthos, I. Papadopoulos, V. Patras, F.A. Triantis
KFKI Research Institute for Particle and Nuclear Physics, Budapest, Hungary
A. Aranyi, G. Bencze, L. Boldizsar, C. Hajdu , P. Hidas, D. Horvath , A. Kapusi, K. Krajczar ,F. Sikler , G.I. Veres , G. Vesztergombi Institute of Nuclear Research ATOMKI, Debrecen, Hungary
N. Beni, J. Molnar, J. Palinkas, Z. Szillasi, V. Veszpremi
University of Debrecen, Debrecen, Hungary
P. Raics, Z.L. Trocsanyi, B. Ujvari
Panjab University, Chandigarh, India
S. Bansal, S.B. Beri, V. Bhatnagar, N. Dhingra, R. Gupta, M. Jindal, M. Kaur, J.M. Kohli,M.Z. Mehta, N. Nishu, L.K. Saini, A. Sharma, A.P. Singh, J.B. Singh, S.P. Singh
University of Delhi, Delhi, India
S. Ahuja, S. Bhattacharya, B.C. Choudhary, B. Gomber, P. Gupta, S. Jain, S. Jain, R. Khurana,A. Kumar, K. Ranjan, R.K. Shivpuri
Bhabha Atomic Research Centre, Mumbai, India
R.K. Choudhury, D. Dutta, S. Kailas, V. Kumar, A.K. Mohanty , L.M. Pant, P. Shukla Tata Institute of Fundamental Research - EHEP, Mumbai, India
T. Aziz, M. Guchait , A. Gurtu, M. Maity , D. Majumder, G. Majumder, K. Mazumdar,G.B. Mohanty, A. Saha, K. Sudhakar, N. Wickramage Tata Institute of Fundamental Research - HECR, Mumbai, India
S. Banerjee, S. Dugad, N.K. Mondal
Institute for Research and Fundamental Sciences (IPM), Tehran, Iran
H. Arfaei, H. Bakhshiansohi , S.M. Etesami, A. Fahim , M. Hashemi, A. Jafari , M. Khakzad,A. Mohammadi , M. Mohammadi Najafabadi, S. Paktinat Mehdiabadi, B. Safarzadeh,M. Zeinali INFN Sezione di Bari a , Universit`a di Bari b , Politecnico di Bari c , Bari, Italy M. Abbrescia a , b , L. Barbone a , b , C. Calabria a , b , A. Colaleo a , D. Creanza a , c , N. De Filippis a , c ,1 ,M. De Palma a , b , L. Fiore a , G. Iaselli a , c , L. Lusito a , b , G. Maggi a , c , M. Maggi a , N. Manna a , b ,B. Marangelli a , b , S. My a , c , S. Nuzzo a , b , N. Pacifico a , b , G.A. Pierro a , A. Pompili a , b , G. Pugliese a , c ,F. Romano a , c , G. Roselli a , b , G. Selvaggi a , b , L. Silvestris a , R. Trentadue a , S. Tupputi a , b , G. Zito a INFN Sezione di Bologna a , Universit`a di Bologna b , Bologna, Italy G. Abbiendi a , A.C. Benvenuti a , D. Bonacorsi a , S. Braibant-Giacomelli a , b , L. Brigliadori a ,P. Capiluppi a , b , A. Castro a , b , F.R. Cavallo a , M. Cuffiani a , b , G.M. Dallavalle a , F. Fabbri a ,A. Fanfani a , b , D. Fasanella a , P. Giacomelli a , M. Giunta a , C. Grandi a , S. Marcellini a , G. Masetti b ,M. Meneghelli a , b , A. Montanari a , F.L. Navarria a , b , F. Odorici a , A. Perrotta a , F. Primavera a ,A.M. Rossi a , b , T. Rovelli a , b , G. Siroli a , b , R. Travaglini a , b INFN Sezione di Catania a , Universit`a di Catania b , Catania, Italy S. Albergo a , b , G. Cappello a , b , M. Chiorboli a , b ,1 , S. Costa a , b , A. Tricomi a , b , C. Tuve a INFN Sezione di Firenze a , Universit`a di Firenze b , Firenze, Italy G. Barbagli a , V. Ciulli a , b , C. Civinini a , R. D’Alessandro a , b , E. Focardi a , b , S. Frosali a , b , E. Gallo a ,S. Gonzi a , b , P. Lenzi a , b , M. Meschini a , S. Paoletti a , G. Sguazzoni a , A. Tropiano a ,1 INFN Laboratori Nazionali di Frascati, Frascati, Italy
L. Benussi, S. Bianco, S. Colafranceschi , F. Fabbri, D. Piccolo INFN Sezione di Genova, Genova, Italy
P. Fabbricatore, R. Musenich
INFN Sezione di Milano-Biccoca a , Universit`a di Milano-Bicocca b , Milano, Italy A. Benaglia a , b , F. De Guio a , b ,1 , L. Di Matteo a , b , S. Gennai , A. Ghezzi a , b , S. Malvezzi a ,A. Martelli a , b , A. Massironi a , b , D. Menasce a , L. Moroni a , M. Paganoni a , b , D. Pedrini a ,S. Ragazzi a , b , N. Redaelli a , S. Sala a , T. Tabarelli de Fatis a , b INFN Sezione di Napoli a , Universit`a di Napoli ”Federico II” b , Napoli, Italy S. Buontempo a , C.A. Carrillo Montoya a ,1 , N. Cavallo a ,20 , A. De Cosa a , b , F. Fabozzi a ,20 ,A.O.M. Iorio a ,1 , L. Lista a , M. Merola a , b , P. Paolucci a INFN Sezione di Padova a , Universit`a di Padova b , Universit`a di Trento (Trento) c , Padova,Italy P. Azzi a , N. Bacchetta a , P. Bellan a , b , D. Bisello a , b , A. Branca a , R. Carlin a , b , P. Checchia a , M. DeMattia a , b , T. Dorigo a , U. Dosselli a , F. Fanzago a , F. Gasparini a , b , U. Gasparini a , b , A. Gozzelino,S. Lacaprara a ,21 , I. Lazzizzera a , c , M. Margoni a , b , M. Mazzucato a , A.T. Meneguzzo a , b ,M. Nespolo a ,1 , L. Perrozzi a ,1 , N. Pozzobon a , b , P. Ronchese a , b , F. Simonetto a , b , E. Torassa a ,M. Tosi a , b , S. Vanini a , b , P. Zotto a , b , G. Zumerle a , b INFN Sezione di Pavia a , Universit`a di Pavia b , Pavia, Italy P. Baesso a , b , U. Berzano a , S.P. Ratti a , b , C. Riccardi a , b , P. Torre a , b , P. Vitulo a , b , C. Viviani a , b INFN Sezione di Perugia a , Universit`a di Perugia b , Perugia, Italy M. Biasini a , b , G.M. Bilei a , B. Caponeri a , b , L. Fan `o a , b , P. Lariccia a , b , A. Lucaroni a , b ,1 ,G. Mantovani a , b , M. Menichelli a , A. Nappi a , b , F. Romeo a , b , A. Santocchia a , b , S. Taroni a , b ,1 ,M. Valdata a , b INFN Sezione di Pisa a , Universit`a di Pisa b , Scuola Normale Superiore di Pisa c , Pisa, Italy P. Azzurri a , c , G. Bagliesi a , J. Bernardini a , b , T. Boccali a ,1 , G. Broccolo a , c , R. Castaldi a ,R.T. D’Agnolo a , c , R. Dell’Orso a , F. Fiori a , b , L. Fo`a a , c , A. Giassi a , A. Kraan a , F. Ligabue a , c , A The CMS Collaboration
T. Lomtadze a , L. Martini a ,22 , A. Messineo a , b , F. Palla a , G. Segneri a , A.T. Serban a , P. Spagnolo a ,R. Tenchini a , G. Tonelli a , b ,1 , A. Venturi a ,1 , P.G. Verdini a INFN Sezione di Roma a , Universit`a di Roma ”La Sapienza” b , Roma, Italy L. Barone a , b , F. Cavallari a , D. Del Re a , b , E. Di Marco a , b , M. Diemoz a , D. Franci a , b , M. Grassi a ,1 ,E. Longo a , b , S. Nourbakhsh a , G. Organtini a , b , F. Pandolfi a , b ,1 , R. Paramatti a , S. Rahatlou a , b ,C. Rovelli INFN Sezione di Torino a , Universit`a di Torino b , Universit`a del Piemonte Orientale (No-vara) c , Torino, Italy N. Amapane a , b , R. Arcidiacono a , c , S. Argiro a , b , M. Arneodo a , c , C. Biino a , C. Botta a , b ,1 ,N. Cartiglia a , R. Castello a , b , M. Costa a , b , N. Demaria a , A. Graziano a , b ,1 , C. Mariotti a ,M. Marone a , b , S. Maselli a , E. Migliore a , b , G. Mila a , b , V. Monaco a , b , M. Musich a , b ,M.M. Obertino a , c , N. Pastrone a , M. Pelliccioni a , b , A. Romero a , b , M. Ruspa a , c , R. Sacchi a , b ,V. Sola a , b , A. Solano a , b , A. Staiano a , A. Vilela Pereira a INFN Sezione di Trieste a , Universit`a di Trieste b , Trieste, Italy S. Belforte a , F. Cossutti a , G. Della Ricca a , b , B. Gobbo a , D. Montanino a , b , A. Penzo a Kangwon National University, Chunchon, Korea
S.G. Heo, S.K. Nam
Kyungpook National University, Daegu, Korea
S. Chang, J. Chung, D.H. Kim, G.N. Kim, J.E. Kim, D.J. Kong, H. Park, S.R. Ro, D. Son, D.C. Son,T. Son
Chonnam National University, Institute for Universe and Elementary Particles, Kwangju,Korea
Zero Kim, J.Y. Kim, S. Song
Korea University, Seoul, Korea
S. Choi, B. Hong, M.S. Jeong, M. Jo, H. Kim, J.H. Kim, T.J. Kim, K.S. Lee, D.H. Moon, S.K. Park,H.B. Rhee, E. Seo, S. Shin, K.S. Sim
University of Seoul, Seoul, Korea
M. Choi, S. Kang, H. Kim, C. Park, I.C. Park, S. Park, G. Ryu
Sungkyunkwan University, Suwon, Korea
Y. Choi, Y.K. Choi, J. Goh, M.S. Kim, E. Kwon, J. Lee, S. Lee, H. Seo, I. Yu
Vilnius University, Vilnius, Lithuania
M.J. Bilinskas, I. Grigelionis, M. Janulis, D. Martisiute, P. Petrov, T. Sabonis
Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico
H. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-de La Cruz, R. Lopez-Fernandez,R. Maga ˜na Villalba, A. S´anchez-Hern´andez, L.M. Villasenor-Cendejas
Universidad Iberoamericana, Mexico City, Mexico
S. Carrillo Moreno, F. Vazquez Valencia
Benemerita Universidad Autonoma de Puebla, Puebla, Mexico
H.A. Salazar Ibarguen
Universidad Aut ´onoma de San Luis Potos´ı, San Luis Potos´ı, Mexico
E. Casimiro Linares, A. Morelos Pineda, M.A. Reyes-Santos University of Auckland, Auckland, New Zealand
D. Krofcheck, J. Tam, C.H. Yiu
University of Canterbury, Christchurch, New Zealand
P.H. Butler, R. Doesburg, H. Silverwood
National Centre for Physics, Quaid-I-Azam University, Islamabad, Pakistan
M. Ahmad, I. Ahmed, M.I. Asghar, H.R. Hoorani, W.A. Khan, T. Khurshid, S. Qazi
Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Warsaw, Poland
G. Brona, M. Cwiok, W. Dominik, K. Doroba, A. Kalinowski, M. Konecki, J. Krolikowski
Soltan Institute for Nuclear Studies, Warsaw, Poland
T. Frueboes, R. Gokieli, M. G ´orski, M. Kazana, K. Nawrocki, K. Romanowska-Rybinska,M. Szleper, G. Wrochna, P. Zalewski
Laborat ´orio de Instrumenta¸c˜ao e F´ısica Experimental de Part´ıculas, Lisboa, Portugal
N. Almeida, P. Bargassa, A. David, P. Faccioli, P.G. Ferreira Parracho, M. Gallinaro, P. Musella,A. Nayak, P.Q. Ribeiro, J. Seixas, J. Varela
Joint Institute for Nuclear Research, Dubna, Russia
S. Afanasiev, I. Belotelov, P. Bunin, I. Golutvin, A. Kamenev, V. Karjavin, G. Kozlov, A. Lanev,P. Moisenz, V. Palichik, V. Perelygin, S. Shmatov, V. Smirnov, A. Volodko, A. Zarubin
Petersburg Nuclear Physics Institute, Gatchina (St Petersburg), Russia
V. Golovtsov, Y. Ivanov, V. Kim, P. Levchenko, V. Murzin, V. Oreshkin, I. Smirnov, V. Sulimov,L. Uvarov, S. Vavilov, A. Vorobyev, A. Vorobyev
Institute for Nuclear Research, Moscow, Russia
Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, M. Kirsanov, N. Krasnikov, V. Matveev,A. Pashenkov, A. Toropin, S. Troitsky
Institute for Theoretical and Experimental Physics, Moscow, Russia
V. Epshteyn, V. Gavrilov, V. Kaftanov † , M. Kossov , A. Krokhotin, N. Lychkovskaya, V. Popov,G. Safronov, S. Semenov, V. Stolin, E. Vlasov, A. Zhokin Moscow State University, Moscow, Russia
E. Boos, M. Dubinin , L. Dudko, A. Ershov, O. Kodolova, V. Korotkikh, I. Lokhtin, A. Markina,S. Obraztsov, M. Perfilov, S. Petrushanko, L. Sarycheva, V. Savrin, A. Snigirev P.N. Lebedev Physical Institute, Moscow, Russia
V. Andreev, M. Azarkin, I. Dremin, M. Kirakosyan, A. Leonidov, S.V. Rusakov, A. Vinogradov
State Research Center of Russian Federation, Institute for High Energy Physics, Protvino,Russia
I. Azhgirey, S. Bitioukov, V. Grishin , V. Kachanov, D. Konstantinov, A. Korablev, V. Krychkine,V. Petrov, R. Ryutin, S. Slabospitsky, A. Sobol, L. Tourtchanovitch, S. Troshin, N. Tyurin,A. Uzunian, A. Volkov University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade,Serbia
P. Adzic , M. Djordjevic, D. Krpic , J. Milosevic Centro de Investigaciones Energ´eticas Medioambientales y Tecnol ´ogicas (CIEMAT),Madrid, Spain
M. Aguilar-Benitez, J. Alcaraz Maestre, P. Arce, C. Battilana, E. Calvo, M. Cepeda, M. Cerrada, A The CMS Collaboration
M. Chamizo Llatas, N. Colino, B. De La Cruz, A. Delgado Peris, C. Diez Pardos, D. Dom´ınguezV´azquez, C. Fernandez Bedoya, J.P. Fern´andez Ramos, A. Ferrando, J. Flix, M.C. Fouz,P. Garcia-Abia, O. Gonzalez Lopez, S. Goy Lopez, J.M. Hernandez, M.I. Josa, G. Merino,J. Puerta Pelayo, I. Redondo, L. Romero, J. Santaolalla, M.S. Soares, C. Willmott
Universidad Aut ´onoma de Madrid, Madrid, Spain
C. Albajar, G. Codispoti, J.F. de Troc ´oniz
Universidad de Oviedo, Oviedo, Spain
J. Cuevas, J. Fernandez Menendez, S. Folgueras, I. Gonzalez Caballero, L. Lloret Iglesias,J.M. Vizan Garcia
Instituto de F´ısica de Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, Spain
J.A. Brochero Cifuentes, I.J. Cabrillo, A. Calderon, S.H. Chuang, J. Duarte Campderros,M. Felcini , M. Fernandez, G. Gomez, J. Gonzalez Sanchez, C. Jorda, P. Lobelle Pardo, A. LopezVirto, J. Marco, R. Marco, C. Martinez Rivero, F. Matorras, F.J. Munoz Sanchez, J. PiedraGomez , T. Rodrigo, A.Y. Rodr´ıguez-Marrero, A. Ruiz-Jimeno, L. Scodellaro, M. SobronSanudo, I. Vila, R. Vilar Cortabitarte CERN, European Organization for Nuclear Research, Geneva, Switzerland
D. Abbaneo, E. Auffray, G. Auzinger, P. Baillon, A.H. Ball, D. Barney, A.J. Bell , D. Benedetti,C. Bernet , W. Bialas, P. Bloch, A. Bocci, S. Bolognesi, M. Bona, H. Breuker, K. Bunkowski,T. Camporesi, G. Cerminara, J.A. Coarasa Perez, B. Cur´e, D. D’Enterria, A. De Roeck, S. DiGuida, N. Dupont-Sagorin, A. Elliott-Peisert, B. Frisch, W. Funk, A. Gaddi, G. Georgiou,H. Gerwig, D. Gigi, K. Gill, D. Giordano, F. Glege, R. Gomez-Reino Garrido, M. Gouzevitch,P. Govoni, S. Gowdy, L. Guiducci, M. Hansen, C. Hartl, J. Harvey, J. Hegeman, B. Hegner,H.F. Hoffmann, A. Honma, V. Innocente, P. Janot, K. Kaadze, E. Karavakis, P. Lecoq,C. Lourenc¸o, T. M¨aki, M. Malberti, L. Malgeri, M. Mannelli, L. Masetti, A. Maurisset, F. Meijers,S. Mersi, E. Meschi, R. Moser, M.U. Mozer, M. Mulders, E. Nesvold , M. Nguyen, T. Orimoto,L. Orsini, E. Perez, A. Petrilli, A. Pfeiffer, M. Pierini, M. Pimi¨a, D. Piparo, G. Polese, A. Racz,J. Rodrigues Antunes, G. Rolandi , T. Rommerskirchen, M. Rovere, H. Sakulin, C. Sch¨afer,C. Schwick, I. Segoni, A. Sharma, P. Siegrist, M. Simon, P. Sphicas , M. Spiropulu , M. Stoye,M. Tadel, P. Tropea, A. Tsirou, P. Vichoudis, M. Voutilainen, W.D. Zeuner Paul Scherrer Institut, Villigen, Switzerland
W. Bertl, K. Deiters, W. Erdmann, K. Gabathuler, R. Horisberger, Q. Ingram, H.C. Kaestli,S. K ¨onig, D. Kotlinski, U. Langenegger, F. Meier, D. Renker, T. Rohe, J. Sibille ,A. Starodumov Institute for Particle Physics, ETH Zurich, Zurich, Switzerland
P. Bortignon, L. Caminada , N. Chanon, Z. Chen, S. Cittolin, G. Dissertori, M. Dittmar,J. Eugster, K. Freudenreich, C. Grab, A. Herv´e, W. Hintz, P. Lecomte, W. Lustermann,C. Marchica , P. Martinez Ruiz del Arbol, P. Meridiani, P. Milenovic , F. Moortgat, C. N¨ageli ,P. Nef, F. Nessi-Tedaldi, L. Pape, F. Pauss, T. Punz, A. Rizzi, F.J. Ronga, M. Rossini, L. Sala,A.K. Sanchez, M.-C. Sawley, B. Stieger, L. Tauscher † , A. Thea, K. Theofilatos, D. Treille,C. Urscheler, R. Wallny, M. Weber, L. Wehrli, J. Weng Universit¨at Z ¨urich, Zurich, Switzerland
E. Aguil ´o, C. Amsler, V. Chiochia, S. De Visscher, C. Favaro, M. Ivova Rikova, B. Millan Mejias,P. Otiougova, C. Regenfus, P. Robmann, A. Schmidt, H. Snoek
National Central University, Chung-Li, Taiwan Y.H. Chang, K.H. Chen, S. Dutta, C.M. Kuo, S.W. Li, W. Lin, Z.K. Liu, Y.J. Lu, D. Mekterovic,R. Volpe, J.H. Wu, S.S. Yu
National Taiwan University (NTU), Taipei, Taiwan
P. Bartalini, P. Chang, Y.H. Chang, Y.W. Chang, Y. Chao, K.F. Chen, W.-S. Hou, Y. Hsiung,K.Y. Kao, Y.J. Lei, R.-S. Lu, J.G. Shiu, Y.M. Tzeng, M. Wang
Cukurova University, Adana, Turkey
A. Adiguzel, M.N. Bakirci , S. Cerci , C. Dozen, I. Dumanoglu, E. Eskut, S. Girgis,G. Gokbulut, I. Hos, E.E. Kangal, A. Kayis Topaksu, G. Onengut, K. Ozdemir, S. Ozturk,A. Polatoz, K. Sogut , D. Sunar Cerci , B. Tali , H. Topakli , D. Uzun, L.N. Vergili, M. Vergili Middle East Technical University, Physics Department, Ankara, Turkey
I.V. Akin, T. Aliev, S. Bilmis, M. Deniz, H. Gamsizkan, A.M. Guler, K. Ocalan, A. Ozpineci,M. Serin, R. Sever, U.E. Surat, E. Yildirim, M. Zeyrek
Bogazici University, Istanbul, Turkey
M. Deliomeroglu, D. Demir , E. G ¨ulmez, B. Isildak, M. Kaya , O. Kaya , S. Ozkorucuklu ,N. Sonmez National Scientific Center, Kharkov Institute of Physics and Technology, Kharkov, Ukraine
L. Levchuk
University of Bristol, Bristol, United Kingdom
F. Bostock, J.J. Brooke, T.L. Cheng, E. Clement, D. Cussans, R. Frazier, J. Goldstein, M. Grimes,M. Hansen, D. Hartley, G.P. Heath, H.F. Heath, L. Kreczko, S. Metson, D.M. Newbold ,K. Nirunpong, A. Poll, S. Senkin, V.J. Smith, S. Ward Rutherford Appleton Laboratory, Didcot, United Kingdom
L. Basso , K.W. Bell, A. Belyaev , C. Brew, R.M. Brown, B. Camanzi, D.J.A. Cockerill,J.A. Coughlan, K. Harder, S. Harper, J. Jackson, B.W. Kennedy, E. Olaiya, D. Petyt,B.C. Radburn-Smith, C.H. Shepherd-Themistocleous, I.R. Tomalin, W.J. Womersley, S.D. Worm Imperial College, London, United Kingdom
R. Bainbridge, G. Ball, J. Ballin, R. Beuselinck, O. Buchmuller, D. Colling, N. Cripps, M. Cutajar,G. Davies, M. Della Negra, W. Ferguson, J. Fulcher, D. Futyan, A. Gilbert, A. Guneratne Bryer,G. Hall, Z. Hatherell, J. Hays, G. Iles, M. Jarvis, G. Karapostoli, L. Lyons, B.C. MacEvoy, A.-M. Magnan, J. Marrouche, B. Mathias, R. Nandi, J. Nash, A. Nikitenko , A. Papageorgiou,M. Pesaresi, K. Petridis, M. Pioppi , D.M. Raymond, S. Rogerson, N. Rompotis, A. Rose,M.J. Ryan, C. Seez, P. Sharp, A. Sparrow, A. Tapper, S. Tourneur, M. Vazquez Acosta, T. Virdee,S. Wakefield, N. Wardle, D. Wardrope, T. Whyntie Brunel University, Uxbridge, United Kingdom
M. Barrett, M. Chadwick, J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, D. Leslie, W. Martin,I.D. Reid, L. Teodorescu
Baylor University, Waco, USA
K. Hatakeyama, H. Liu
Boston University, Boston, USA
T. Bose, E. Carrera Jarrin, C. Fantasia, A. Heister, J. St. John, P. Lawson, D. Lazic, J. Rohlf,D. Sperka, L. Sulak
Brown University, Providence, USA
A. Avetisyan, S. Bhattacharya, J.P. Chou, D. Cutts, A. Ferapontov, U. Heintz, S. Jabeen, A The CMS Collaboration
G. Kukartsev, G. Landsberg, M. Luk, M. Narain, D. Nguyen, M. Segala, T. Sinthuprasith,T. Speer, K.V. Tsang
University of California, Davis, Davis, USA
R. Breedon, M. Calderon De La Barca Sanchez, S. Chauhan, M. Chertok, J. Conway, P.T. Cox,J. Dolen, R. Erbacher, E. Friis, W. Ko, A. Kopecky, R. Lander, H. Liu, S. Maruyama, T. Miceli,M. Nikolic, D. Pellett, J. Robles, S. Salur, T. Schwarz, M. Searle, J. Smith, M. Squires, M. Tripathi,R. Vasquez Sierra, C. Veelken
University of California, Los Angeles, Los Angeles, USA
V. Andreev, K. Arisaka, D. Cline, R. Cousins, A. Deisher, J. Duris, S. Erhan, C. Farrell, J. Hauser,M. Ignatenko, C. Jarvis, C. Plager, G. Rakness, P. Schlein † , J. Tucker, V. Valuev University of California, Riverside, Riverside, USA
J. Babb, A. Chandra, R. Clare, J. Ellison, J.W. Gary, F. Giordano, G. Hanson, G.Y. Jeng,S.C. Kao, F. Liu, H. Liu, O.R. Long, A. Luthra, H. Nguyen, B.C. Shen † , R. Stringer, J. Sturdy,S. Sumowidagdo, R. Wilken, S. Wimpenny University of California, San Diego, La Jolla, USA
W. Andrews, J.G. Branson, G.B. Cerati, E. Dusinberre, D. Evans, F. Golf, A. Holzner, R. Kelley,M. Lebourgeois, J. Letts, B. Mangano, S. Padhi, C. Palmer, G. Petrucciani, H. Pi, M. Pieri,R. Ranieri, M. Sani, V. Sharma, S. Simon, Y. Tu, A. Vartak, S. Wasserbaech , F. W ¨urthwein,A. Yagil, J. Yoo University of California, Santa Barbara, Santa Barbara, USA
D. Barge, R. Bellan, C. Campagnari, M. D’Alfonso, T. Danielson, K. Flowers, P. Geffert,J. Incandela, C. Justus, P. Kalavase, S.A. Koay, D. Kovalskyi, V. Krutelyov, S. Lowette, N. Mccoll,V. Pavlunin, F. Rebassoo, J. Ribnik, J. Richman, R. Rossin, D. Stuart, W. To, J.R. Vlimant
California Institute of Technology, Pasadena, USA
A. Apresyan, A. Bornheim, J. Bunn, Y. Chen, M. Gataullin, Y. Ma, A. Mott, H.B. Newman,C. Rogan, K. Shin, V. Timciuc, P. Traczyk, J. Veverka, R. Wilkinson, Y. Yang, R.Y. Zhu
Carnegie Mellon University, Pittsburgh, USA
B. Akgun, R. Carroll, T. Ferguson, Y. Iiyama, D.W. Jang, S.Y. Jun, Y.F. Liu, M. Paulini, J. Russ,H. Vogel, I. Vorobiev
University of Colorado at Boulder, Boulder, USA
J.P. Cumalat, M.E. Dinardo, B.R. Drell, C.J. Edelmaier, W.T. Ford, A. Gaz, B. Heyburn, E. LuiggiLopez, U. Nauenberg, J.G. Smith, K. Stenson, K.A. Ulmer, S.R. Wagner, S.L. Zang
Cornell University, Ithaca, USA
L. Agostino, J. Alexander, D. Cassel, A. Chatterjee, S. Das, N. Eggert, L.K. Gibbons, B. Heltsley,W. Hopkins, A. Khukhunaishvili, B. Kreis, G. Nicolas Kaufman, J.R. Patterson, D. Puigh,A. Ryd, E. Salvati, X. Shi, W. Sun, W.D. Teo, J. Thom, J. Thompson, J. Vaughan, Y. Weng,L. Winstrom, P. Wittich
Fairfield University, Fairfield, USA
A. Biselli, G. Cirino, D. Winn
Fermi National Accelerator Laboratory, Batavia, USA
S. Abdullin, M. Albrow, J. Anderson, G. Apollinari, M. Atac, J.A. Bakken, S. Banerjee,L.A.T. Bauerdick, A. Beretvas, J. Berryhill, P.C. Bhat, I. Bloch, F. Borcherding, K. Burkett,J.N. Butler, V. Chetluru, H.W.K. Cheung, F. Chlebana, S. Cihangir, W. Cooper, D.P. Eartly,V.D. Elvira, S. Esen, I. Fisk, J. Freeman, Y. Gao, E. Gottschalk, D. Green, K. Gunthoti, O. Gutsche, J. Hanlon, R.M. Harris, J. Hirschauer, B. Hooberman, H. Jensen, M. Johnson,U. Joshi, R. Khatiwada, B. Klima, K. Kousouris, S. Kunori, S. Kwan, C. Leonidopoulos,P. Limon, D. Lincoln, R. Lipton, J. Lykken, K. Maeshima, J.M. Marraffino, D. Mason, P. McBride,T. Miao, K. Mishra, S. Mrenna, Y. Musienko , C. Newman-Holmes, V. O’Dell, R. Pordes,O. Prokofyev, N. Saoulidou, E. Sexton-Kennedy, S. Sharma, W.J. Spalding, L. Spiegel, P. Tan,L. Taylor, S. Tkaczyk, L. Uplegger, E.W. Vaandering, R. Vidal, J. Whitmore, W. Wu, F. Yang,F. Yumiceva, J.C. Yun University of Florida, Gainesville, USA
D. Acosta, P. Avery, D. Bourilkov, M. Chen, M. De Gruttola, G.P. Di Giovanni, D. Dobur,A. Drozdetskiy, R.D. Field, M. Fisher, Y. Fu, I.K. Furic, J. Gartner, B. Kim, J. Konigsberg,A. Korytov, A. Kropivnitskaya, T. Kypreos, K. Matchev, G. Mitselmakher, L. Muniz, C. Prescott,R. Remington, M. Schmitt, B. Scurlock, P. Sellers, N. Skhirtladze, M. Snowball, D. Wang,J. Yelton, M. Zakaria
Florida International University, Miami, USA
C. Ceron, V. Gaultney, L. Kramer, L.M. Lebolo, S. Linn, P. Markowitz, G. Martinez, D. Mesa,J.L. Rodriguez
Florida State University, Tallahassee, USA
T. Adams, A. Askew, J. Bochenek, J. Chen, B. Diamond, S.V. Gleyzer, J. Haas,S. Hagopian, V. Hagopian, M. Jenkins, K.F. Johnson, H. Prosper, L. Quertenmont, S. Sekmen,V. Veeraraghavan
Florida Institute of Technology, Melbourne, USA
M.M. Baarmand, B. Dorney, S. Guragain, M. Hohlmann, H. Kalakhety, R. Ralich,I. Vodopiyanov
University of Illinois at Chicago (UIC), Chicago, USA
M.R. Adams, I.M. Anghel, L. Apanasevich, Y. Bai, V.E. Bazterra, R.R. Betts, J. Callner,R. Cavanaugh, C. Dragoiu, L. Gauthier, C.E. Gerber, S. Hamdan, D.J. Hofman, S. Khalatyan,G.J. Kunde , F. Lacroix, M. Malek, C. O’Brien, C. Silvestre, A. Smoron, D. Strom, N. Varelas The University of Iowa, Iowa City, USA
U. Akgun, E.A. Albayrak, B. Bilki, W. Clarida, F. Duru, C.K. Lae, E. McCliment, J.-P. Merlo,H. Mermerkaya , A. Mestvirishvili, A. Moeller, J. Nachtman, C.R. Newsom, E. Norbeck,J. Olson, Y. Onel, F. Ozok, S. Sen, J. Wetzel, T. Yetkin, K. Yi Johns Hopkins University, Baltimore, USA
B.A. Barnett, B. Blumenfeld, A. Bonato, C. Eskew, D. Fehling, G. Giurgiu, A.V. Gritsan, Z.J. Guo,G. Hu, P. Maksimovic, S. Rappoccio, M. Swartz, N.V. Tran, A. Whitbeck
The University of Kansas, Lawrence, USA
P. Baringer, A. Bean, G. Benelli, O. Grachov, R.P. Kenny Iii, M. Murray, D. Noonan, S. Sanders,J.S. Wood, V. Zhukova
Kansas State University, Manhattan, USA
A.f. Barfuss, T. Bolton, I. Chakaberia, A. Ivanov, S. Khalil, M. Makouski, Y. Maravin, S. Shrestha,I. Svintradze, Z. Wan
Lawrence Livermore National Laboratory, Livermore, USA
J. Gronberg, D. Lange, D. Wright
University of Maryland, College Park, USA
A. Baden, M. Boutemeur, S.C. Eno, D. Ferencek, J.A. Gomez, N.J. Hadley, R.G. Kellogg, M. Kirn, A The CMS Collaboration
Y. Lu, A.C. Mignerey, K. Rossato, P. Rumerio, F. Santanastasio, A. Skuja, J. Temple, M.B. Tonjes,S.C. Tonwar, E. Twedt
Massachusetts Institute of Technology, Cambridge, USA
B. Alver, G. Bauer, J. Bendavid, W. Busza, E. Butz, I.A. Cali, M. Chan, V. Dutta, P. Everaerts,G. Gomez Ceballos, M. Goncharov, K.A. Hahn, P. Harris, Y. Kim, M. Klute, Y.-J. Lee, W. Li,C. Loizides, P.D. Luckey, T. Ma, S. Nahn, C. Paus, D. Ralph, C. Roland, G. Roland, M. Rudolph,G.S.F. Stephans, F. St ¨ockli, K. Sumorok, K. Sung, E.A. Wenger, S. Xie, M. Yang, Y. Yilmaz,A.S. Yoon, M. Zanetti
University of Minnesota, Minneapolis, USA
S.I. Cooper, P. Cushman, B. Dahmes, A. De Benedetti, P.R. Dudero, G. Franzoni, J. Haupt,K. Klapoetke, Y. Kubota, J. Mans, V. Rekovic, R. Rusack, M. Sasseville, A. Singovsky
University of Mississippi, University, USA
L.M. Cremaldi, R. Godang, R. Kroeger, L. Perera, R. Rahmat, D.A. Sanders, D. Summers
University of Nebraska-Lincoln, Lincoln, USA
K. Bloom, S. Bose, J. Butt, D.R. Claes, A. Dominguez, M. Eads, J. Keller, T. Kelly, I. Kravchenko,J. Lazo-Flores, H. Malbouisson, S. Malik, G.R. Snow
State University of New York at Buffalo, Buffalo, USA
U. Baur, A. Godshalk, I. Iashvili, S. Jain, A. Kharchilava, A. Kumar, S.P. Shipkowski, K. Smith
Northeastern University, Boston, USA
G. Alverson, E. Barberis, D. Baumgartel, O. Boeriu, M. Chasco, S. Reucroft, J. Swain, D. Trocino,D. Wood, J. Zhang
Northwestern University, Evanston, USA
A. Anastassov, A. Kubik, N. Odell, R.A. Ofierzynski, B. Pollack, A. Pozdnyakov, M. Schmitt,S. Stoynev, M. Velasco, S. Won
University of Notre Dame, Notre Dame, USA
L. Antonelli, D. Berry, M. Hildreth, C. Jessop, D.J. Karmgard, J. Kolb, T. Kolberg, K. Lannon,W. Luo, S. Lynch, N. Marinelli, D.M. Morse, T. Pearson, R. Ruchti, J. Slaunwhite, N. Valls,M. Wayne, J. Ziegler
The Ohio State University, Columbus, USA
B. Bylsma, L.S. Durkin, J. Gu, C. Hill, P. Killewald, K. Kotov, T.Y. Ling, M. Rodenburg,G. Williams
Princeton University, Princeton, USA
N. Adam, E. Berry, P. Elmer, D. Gerbaudo, V. Halyo, P. Hebda, A. Hunt, J. Jones, E. Laird,D. Lopes Pegna, D. Marlow, T. Medvedeva, M. Mooney, J. Olsen, P. Pirou´e, X. Quan, H. Saka,D. Stickland, C. Tully, J.S. Werner, A. Zuranski
University of Puerto Rico, Mayaguez, USA
J.G. Acosta, X.T. Huang, A. Lopez, H. Mendez, S. Oliveros, J.E. Ramirez Vargas,A. Zatserklyaniy
Purdue University, West Lafayette, USA
E. Alagoz, V.E. Barnes, G. Bolla, L. Borrello, D. Bortoletto, A. Everett, A.F. Garfinkel, L. Gutay,Z. Hu, M. Jones, O. Koybasi, M. Kress, A.T. Laasanen, N. Leonardo, C. Liu, V. Maroussov,P. Merkel, D.H. Miller, N. Neumeister, I. Shipsey, D. Silvers, A. Svyatkovskiy, H.D. Yoo,J. Zablocki, Y. Zheng Purdue University Calumet, Hammond, USA
P. Jindal, N. Parashar
Rice University, Houston, USA
C. Boulahouache, V. Cuplov, K.M. Ecklund, F.J.M. Geurts, B.P. Padley, R. Redjimi, J. Roberts,J. Zabel
University of Rochester, Rochester, USA
B. Betchart, A. Bodek, Y.S. Chung, R. Covarelli, P. de Barbaro, R. Demina, Y. Eshaq, H. Flacher,A. Garcia-Bellido, P. Goldenzweig, Y. Gotra, J. Han, A. Harel, D.C. Miner, D. Orbaker,G. Petrillo, D. Vishnevskiy, M. Zielinski
The Rockefeller University, New York, USA
A. Bhatti, R. Ciesielski, L. Demortier, K. Goulianos, G. Lungu, S. Malik, C. Mesropian, M. Yan
Rutgers, the State University of New Jersey, Piscataway, USA
O. Atramentov, A. Barker, D. Duggan, Y. Gershtein, R. Gray, E. Halkiadakis, D. Hidas, D. Hits,A. Lath, S. Panwalkar, R. Patel, A. Richards, K. Rose, S. Schnetzer, S. Somalwar, R. Stone,S. Thomas
University of Tennessee, Knoxville, USA
G. Cerizza, M. Hollingsworth, S. Spanier, Z.C. Yang, A. York
Texas A&M University, College Station, USA
R. Eusebi, J. Gilmore, A. Gurrola, T. Kamon, V. Khotilovich, R. Montalvo, I. Osipenkov,Y. Pakhotin, J. Pivarski, A. Safonov, S. Sengupta, A. Tatarinov, D. Toback, M. Weinberger
Texas Tech University, Lubbock, USA
N. Akchurin, C. Bardak, J. Damgov, C. Jeong, K. Kovitanggoon, S.W. Lee, P. Mane, Y. Roh,A. Sill, I. Volobouev, R. Wigmans, E. Yazgan
Vanderbilt University, Nashville, USA
E. Appelt, E. Brownson, D. Engh, C. Florez, W. Gabella, M. Issah, W. Johns, P. Kurt, C. Maguire,A. Melo, P. Sheldon, B. Snook, S. Tuo, J. Velkovska
University of Virginia, Charlottesville, USA
M.W. Arenton, M. Balazs, S. Boutle, B. Cox, B. Francis, R. Hirosky, A. Ledovskoy, C. Lin, C. Neu,R. Yohay
Wayne State University, Detroit, USA
S. Gollapinni, R. Harr, P.E. Karchin, P. Lamichhane, M. Mattson, C. Milst`ene, A. Sakharov
University of Wisconsin, Madison, USA