Decomposing transverse momentum balance contributions for quenched jets in PbPb collisions at \( \sqrt{s_{\mathrm{N}\;\mathrm{N}}}=2.76 \) TeV

Journal of High Energy Physics, Nov 2016

Interactions between jets and the quark-gluon plasma produced in heavy ion collisions are studied via the angular distributions of summed charged-particle transverse momenta (p T) with respect to both the leading and subleading jet axes in high-p T dijet events. The contributions of charged particles in different momentum ranges to the overall event p T balance are decomposed into short-range jet peaks and a long-range azimuthal asymmetry in charged-particle p T. The results for PbPb collisions are compared to those in pp collisions using data collected in 2011 and 2013, at collision energy \( \sqrt{s_{\mathrm{N}\;\mathrm{N}}}=2.76 \) TeV with integrated luminosities of 166 μb−1 and 5.3 pb−1, respectively, by the CMS experiment at the LHC. Measurements are presented as functions of PbPb collision centrality, charged-particle p T, relative azimuth, and radial distance from the jet axis for balanced and unbalanced dijets.

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Decomposing transverse momentum balance contributions for quenched jets in PbPb collisions at \( \sqrt{s_{\mathrm{N}\;\mathrm{N}}}=2.76 \) TeV

Received: September Decomposing transverse momentum balance contributions for quenched jets in PbPb collisions at M. Gouzevitch 0 1 3 4 5 6 7 G. Grenier 0 1 3 4 5 6 7 B. Ille 0 1 3 4 5 6 7 F. Lagarde 0 1 3 4 5 6 7 I.B. Laktineh 0 1 3 4 5 6 7 M. Lethuillier 0 1 3 4 5 6 7 L. Mirabito 0 1 3 4 5 6 7 0 Open Access , Copyright CERN 1 INFN Sezione di Milano-Bicocca 2 , Universita di Milano-Bicocca 3 University of Auckland , Auckland , New Zealand 4 Northeastern University , Boston , U.S.A 5 University , Budapest , Hungary 6 19: Also at Brandenburg University of Technology , Cottbus , Germany 7 63: Also at School of Physics and Astronomy, University of Southampton , Southampton, United Interactions between jets and the quark-gluon plasma produced in heavy ion collisions are studied via the angular distributions of summed charged-particle transverse momenta (pT) with respect to both the leading and subleading jet axes in high-pT dijet events. The contributions of charged particles in di erent momentum ranges to the overall event pT balance are decomposed into short-range jet peaks and a long-range azimuthal asymmetry in charged-particle pT. The results for PbPb collisions are compared to those in pp collisions using data collected in 2011 and 2013, at collision energy psNN = 2:76 TeV with integrated luminosities of 166 b 1 and 5.3 pb 1, respectively, by the CMS experiment at the LHC. Measurements are presented as functions of PbPb collision centrality, charged-particle pT, relative azimuth, and radial distance from the jet axis for balanced and unbalanced dijets. plasma balance; The CMS collaboration; Jet substructure; Heavy Ion Experiments; Heavy-ion collision; Quark gluon 1 Introduction The CMS detector Event selection Analysis procedure The CMS collaboration Introduction 3 Jet and track reconstruction Pair-acceptance correction Separation of correlations into jet-peak and long-range components Corrections and systematic uncertainties Measurement of radial jet momentum density pro le Azimuthal distribution of charged-particle transverse momentum 6.3 Integrated hemisphere momentum balance 1 3 3 High transverse momentum (pT) jets originating from partons produced in the initial hard scatterings in ultra-relativistic heavy ion collisions have been used successfully to study the properties of the quark-gluon plasma (QGP) [1]. The observation of the jet quenching rst at the BNL RHIC [2, 3] and then at the CERN LHC [4{7], began the era of detailed experimental studies trying to assess both the redistribution of energy from the parton as it interacts with the QGP, and the possible QGP response to the propagating parton. In these studies, a suppression of strongly interacting hard probes has been observed, including suppression of charged-particle yields associated with jets when compared with pp data at the same center-of-mass energy. The dependence of jet quenching on the collision centrality (i.e. the degree of the overlap of the two colliding nuclei, with fully-overlapping nuclei de ned as \0% central"), has also been established, with stronger quenching e ects reported for more central collisions. Detailed studies at CMS and ATLAS report that not only the suppression of jet yields, but also the relative di erences between the momenta of the leading and subleading jets in dijet events increase in more central collisions, indicating that the jet quenching e ect depends on the path length of the parton traversing the medium [4{6]. Corresponding measurements from the most peripheral (i.e. least central) PbPb data in these studies and from pPb collisions [8] are found to be similar to those in pp collisions, implying that the jet quenching phenomenon is caused by hot nuclear matter e ects. Recently, CMS reported results showing the di erence in the distribution of charged-particle pT between the subleading and leading jet hemispheres in PbPb events with asymmetric dijets [9]. In these results, it is found that low-pT particles extending to large angles away from the dijet axis in the subleading hemisphere must be considered in order to recover the momentum balance in these events. In addition to these momentum balance studies, precise measurements of the fragmentation pattern [10] and the distribution of charged-particle pT as a function of radial distance from the jet axis [11], have also shown that the jet structure is modi ed by the medium. These modi cations extend to large distances in relative pseudorapidity ( ) and relative azimuth ( respect to the jet axis [12]. These studies have found softening of the jet fragmentation in PbPb collisions with respect to pp events, with the most signi cant excess of soft-hadron yields observed in more central PbPb events. The analysis presented in this paper probes the details of the momentum distribution in dijet events, taking advantage of the high production rates for dijet events at the LHC, and the CMS detector's ability to measure charged-particle tracks over an extended range. Two-dimensional correlations between the reconstructed jets and charged-particle tracks (jet-track correlations) are constructed in . These correlations are used to decompose the overall event pT distribution into three components: two 2D Gaussian-like peaks associated with the leading and subleading jets, and an azimuthal asymmetry in the distribution of momentum under the jet peaks. Results for each component are presented as a function of , and the jet momentum density pro le (\jet shape") is also presented as a function of the radial distance from the jet axis in the plane. Measurements are performed di erentially in collision centrality, charged-particle transverse momentum (ptTrk), and dijet asymmetry. These detailed di erential studies provide input for theoretical models that attempt to describe the patterns of energy loss by a highly-energetic probe passing through the QGP. The data used in this analysis are from PbPb collisions at a nucleon-nucleon centerof-mass energy of 2.76 TeV, corresponding to an integrated luminosity of 166 b 1 the reference measurement, pp data taken in 2013 at the same energy corresponding to an integrated luminosity of 5.3 pb 1 are used. These studies allow for a detailed characterization of the two-dimensional (in ) ptTrk distributions for charged-particle tracks with respect to the jet axes, providing information about the topology of the event from the jet perspective and details about the ptTrk ow modi cation in dijet events. In this paper, section 2 gives general information about the CMS detector, and section 3 outlines jet and track reconstruction procedures for PbPb and pp data. Section 4 describes the selection of events, while section 5 details the procedure applied to analyze these events and evaluate systematic uncertainties. Section 6 presents results as a function of r (section 6.1), (section 6.2), and integrated transverse momentum balance over the whole event (section 6.3). Finally, section 7 summarizes and concludes the paper. The central feature of the CMS apparatus is a superconducting solenoid of 6 m internal diameter, providing a magnetic eld of 3.8 T. Within the solenoid volume are a silicon pixel and strip tracker, a lead tungstate crystal electromagnetic calorimeter (ECAL), and a brass and scintillator hadron calorimeter (HCAL), each composed of a barrel and two endcap sections. Two hadronic forward (HF) steel and quartz- ber calorimeters complement the barrel and endcap detectors, providing coverage up to j j < 5:2. In this analysis, the collision centrality is determined using the total sum of transverse energy (ET) from calorimeter towers in the HF region (covering 2:9 < j j < 5:2). The ET distribution is used to divide the event sample into bins, each representing 0.5% of the total nucleus-nucleus hadronic interaction cross section. A detailed description of centrality determination can be found in ref. [6]. Jet reconstruction for this analysis relies on calorimeter information from the ECAL and HCAL. For the central region (j j < 1:74) from which jets are selected for this analysis, the HCAL cells have widths of 0.087 in both and . In the { plane, and for j j < 1:48, the HCAL cells map on to 5 5 ECAL crystal arrays to form calorimeter towers projecting radially outwards from close to the nominal interaction point. Within each tower, the energy deposits in ECAL and HCAL cells are summed to de ne the calorimeter tower energies, subsequently used to provide the energies and directions of hadronic jets [13]. Accurate particle tracking is critical for measurements of charged-hadron yields. The CMS silicon tracker measures charged particles within the range j j < 2:5. It consists of 1,440 silicon pixel and 15,148 silicon strip detector modules. For nonisolated particles of 1 < pT < 10 GeV and j j < 1:4, the track resolutions are typically 1.5% in pT and 25{90 (45{150) m in the transverse (longitudinal) impact parameter [14]. Performance of the track reconstruction in pp and PbPb collisions will be discussed in section 3. A detailed description of the CMS detector, together with a de nition of the coordinate system used and the relevant kinematic variables, can be found in [15]. Jet and track reconstruction For both pp and PbPb collisions, jet reconstruction in CMS is performed with the anti-kT algorithm, as implemented in the FastJet framework [16, 17], using a distance parameter deposits in the CMS calorimeters. Raw jet energies are obtained from the sum of the tower energies and raw jet momenta from the vectorial sum of the tower momenta, and are corrected to establish a relative uniform response of the calorimeter in and a calibrated absolute response in pT. For PbPb collisions, the CMS algorithm \HF/Voronoi" is used to estimate and subtract the heavy-ion underlying event based on information from HF energy measurements as well as Voronoi decomposition of particle ow [9, 18]. For pp collisions, the contribution from the underlying event is negligible and no underlying event subtraction is employed. Monte Carlo (MC) event generators have been used for evaluation of the jet and track reconstruction performance. Jet events are generated by the pythia MC generator [19] (version 6.423, tune Z2 [20]). Simulated events are further propagated through the CMS detector using the Geant4 package [21] to simulate the detector response. In order to account for the in uence of the underlying PbPb event, the pythia events are embedded into fully simulated PbPb events, generated by hydjet [22] (version 1.8) that is tuned to reproduce the total particle multiplicities, charged-hadron spectra, and elliptic ow at all centralities. The embedding is done by mixing the simulated signal information from pythia and hydjet, hereafter referred to as pythia+hydjet. These events are then propagated through the same jet and track reconstruction and analysis procedures as pp and PbPb data. The jet energy scale (JES) is established for pp using pythia events and for PbPb using pythia+hydjet events in classes of event centrality. The accuracy of the reconstruction and correction procedure is tested as a function of jet pT and , by comparing a sample of reconstructed and corrected jets to the jets originally simulated in that sample. To account for the dependence of the JES on the fragmentation of jets, an additional correction is applied as a function of reconstructed jet pT and as a function of the number of tracks with pT > 2 GeV within a radius r < 0:3 around the jet axis. This correction is derived separately for pp and PbPb data, as described in ref. [9]. For studies of pp data and pythia simulation, tracks are reconstructed using the same iterative method [14] as in the previous CMS analyses of pp collisions. For PbPb data and pythia+hydjet simulation, a dedicated heavy-ion iterative track reconstruction method [11, 23] is employed. Tracking e ciency for charged particles in pp collisions ranges from approximately 80% at pT 0:5 GeV to 90% or better at pT 10 GeV and higher. Track reconstruction is more di cult in the heavy-ion environment due to the high track multiplicity, and tracking e ciency for PbPb collisions ranges from approximately 30% at 0.5 GeV to about 70% at 10 GeV . Detailed studies of tracking e ciency and of tracking e ciency corrections (derived as a function of centrality, ptTrk, , , and local charged particle density) can be found in ref. [9]. Event selection The events for this analysis are selected using the CMS high-level trigger (HLT), with an inclusive single-jet trigger with a threshold of pT > 80 GeV [24]. This trigger is fully e cient in both PbPb and pp data for events containing o ine reconstructed jets with pT > 120 GeV . In order to suppress noncollision-related noise due to sources such as cosmic rays and beam backgrounds, the events used in this analysis are also required to satisfy o ine selection criteria as documented in refs. [6, 25]. These include restricting PbPb events to those containing a reconstructed vertex with at least two tracks and a z position within 15 cm of the detector center, and in which at least 3 GeV energy is deposited in at least three HF calorimeter towers on each side of the interaction point. A dijet sample is selected using criteria matched to those of previous CMS analyses measuring dijet energy balance and correlated yields to high-pT jets [5, 9, 12]. In this selection, events are rst required to contain a leading calorimeter jet with pT;1 > 120 GeV in the range of j jetj < 2, and a subleading jet of pT;2 > 50 GeV, also in j jetj < 2. Once the leading and subleading jets in the event have been identi ed, a tighter j jetj selection is applied to ensure stable jet reconstruction performance and good tracker acceptance for tracks on all sides of each jet: only events in which both leading and subleading jets fall within j jetj < 1:6 are included in the nal selected data sample. The azimuthal requirement is made either on the presence or absence of a third jet in the event. This jet sample is further divided based on the asymmetry between the leading and subleading jets, AJ = (pT;1 balanced part (de ned by AJ < 0:22) of the total dijet sample, and the more unbalanced with previous CMS analyses [5, 9]. In this analysis, 52% of PbPb events are balanced, while 67% of pp events are balanced. For the PbPb data, the centrality of the collisions is also considered and results are compared for central events (with centrality 0{30%) versus peripheral events (with centrality 50-100%). Analysis procedure Dijet events in this analysis are studied di erentially in collision centrality, with the following bins: 0{30% (most central), 30{50% (not shown), and 50{100% (most peripheral). This analysis follows the procedure established in refs. [12, 26]: two-dimensional correlations with respect to the measured subleading and leading jet axes are constructed for charged-particle tracks in the event with ptrk 0:5 GeV and j trackj < 2:4, in several ptTrk bins. These correlations are weighted by ptrk on a per-track basis, and normalized by the number of jets in the sample. This produces two-dimensional average per-jet distributions of ptTrk with respect to the leading and subleading jets. After the construction of the initial two-dimensional correlations described above, the remaining analysis procedure consists of the following steps, which will be discussed in detail below: A pair-acceptance correction, derived by the \mixed event" method [12, 26]; The separation of correlations into jet-peak and long-range components; Corrections for jet reconstruction biases: a full simulation-based analysis is conducted to determine and subtract the correlated yield produced by jet selection bias. Pair-acceptance correction With jet acceptance of j jetj < 1:6, many tracks within j j < 2:5 of a jet will fall outside of the track acceptance of j trackj < 2:4, resulting in correlation geometry that falls with . To correct for this pair-acceptance e ect, a mixed-event distribution is constructed by correlating jets from the jet-triggered event sample with tracks from a sample of minimum bias events, matched in vertex position (within 1 cm) and collision centrality (within 2.5%), following the technique used in refs. [27{29]. In the following, Njets denotes the number of dijet events selected as described in a given data sample. The per-jet associated yield, weighted per-track by ptTrk is de ned as: The signal pair distribution, S( normalized by Njets from the same event: ), represents the ptTrk-weighted yield of jet-track pairs ) = ) = The mixed-event pair distribution, is constructed to account for pair-acceptance e ects, with N mix denoting the number of mixed-event jet-track pairs. Signal and mixed event correlations are both corrected for tracking e ciencies on a per-track basis, using the e ciency parametrization de ned as a function of centrality, ptTrk, establishes the correction normalization, with M E(0; 0) representing the mixed-event associated yield for jet-track pairs going in approximately the same direction and thus having full pair acceptance. Separation of correlations into jet-peak and long-range components After the mixed-event correction, correlations to the leading and subleading jets show a Gaussian-like peak con ned to the region j torial and long-range-correlated background. j < 1:5, on top of a signi cant combinaTo separate the long-range azimuthallycorrelated and uncorrelated distributions under the peaks from jets, the \sideband" regions j < 2:5 of both the leading and subleading jet acceptance-corrected correlations are projected into . Previous studies have found no -dependence of the long-range underlying event distributions in this j j range [12, 30]. Figure 1 illustrates these longrange distributions in for pp, most peripheral PbPb, and most central PbPb data for representative bins at low (upper panels) and high (lower panels) ptrk of the tracks in unbalanced dijet events (with AJ > 0:22). For illustration, the range j the leading and subleading long-range distributions are shown as a combined 2 =2 of tribution, with the subleading jet distribution shifted by to show the full underlying event correlation with respect to the leading jet direction. The visible asymmetry in this long-range distribution in pp data is attributed to the presence of additional jets and other contributions that must, by momentum conservation, be present on the subleading side of the unbalanced dijet system. To isolate the Gaussian-like leading and subleading jet peaks, this long-range distribution is propagated over the full range j j < 2:5 and subtracted in 2D from the )25 PbPb cent. 50-100% j <1. and overlaid with a long-range distribution projected over 1:5 < j j < 2:5. The =2 < < 3 =2 is while the bottom row shows the high ptTrk bin 4 < ptTrk < 8 GeV . Statistical uncertainties are shown with vertical bars. mixed-event-corrected signal correlation. In addition, the leading side of the long-range distribution is subtracted from the subleading side (in the illustration shown, the distribu=2 is subtracted from the distribution for =2 < < 3 =2) to obtain a measurement of subleading-to-leading asymmetry in the long-range correlated background. With this, the three contributions to the dijet hemisphere momentum balance have been identi ed: leading jet peak, subleading jet peak, and subleading-to-leading two-dimensional underlying event asymmetry. Corrections and systematic uncertainties Simulation-based corrections are applied to correlations to account for two biases in jet reconstruction: a bias toward selecting jets that are found on upward uctuations in the background (relevant for PbPb only), and a bias toward selecting jets with harder fragmentation (a ecting PbPb and pp similarly). For the former, to estimate and subtract the contribution to the excess yield due to background uctuation bias in jet reconstruction, a similar procedure to that outlined in previous CMS studies [10] is followed. Simulations are performed in pythia+hydjet samples with reconstructed jets, and correlations are constructed excluding particles generated with the embedded pythia hard-scattering process. A Gaussian t to the excess is subtracted as a correction from the data results, and half its magnitude is assigned as the associated systematic uncertainty. The second bias is toward the selection of jets with fewer associated tracks in both pp and PbPb data for all ptTrk selections studied, due to the fact that jets with harder fragmentation are more likely to be successfully reconstructed than jets with softer fragmentation. Following the method used in refs. [9, 12], corrections are derived for this jet fragmentation function (JFF) bias and for the related possible e ect of \jet swapping" between leading, subleading, and additional jets by comparing correlated per-trigger particle yields for all reconstructed jets versus all generated jets. This correction is derived for each jet selection in a pythia-only simulation, and also in pythia+hydjet events, excluding hydjet tracks from the correction determination. The variation between the JFF and jet swapping correction derived from pythia embedded into hydjet simulation at di erent centralities is assigned as a systematic uncertainty in this correction. This uncertainty is less than 2% for all ptTrk selections, and converges to zero at high ptTrk. Jet reconstruction-related sources of systematic uncertainty in this analysis include the two reconstruction biases as discussed above, as well as a residual JES uncertainty that accounts for possible di erences of calorimeter response in data and simulation. In simulation, for example, there is a di erence in the JES between quark and gluon jets (about 2% at 120 GeV [9]), meaning that medium-induced changes in jet result in either over-correction or under-correction of jet energy, and a resulting bias in jet selection. To evaluate this residual JES uncertainty, we vary the leading jet selection threshold by 3% to account for possible di erences in data versus simulated calorimeter response. The resulting maximum variations in total correlated particle yield are found to be within 3% in all cases, and we conservatively assign 3% to account for this systematic uncertainty source. tracks (ptTrk > 2 GeV). The tracking e ciency correction uncertainty is estimated from the ratio of corrected reconstructed yields and generated yields in pythia and pythia+hydjet simulated events, by using generator-level charged particles as a reference. This uncertainty is found to be 2{4% for PbPb and pp collisions, with the greater value corresponding to a higher multiplicity and lower momentum range of selected tracks. To account for possible track reconstruction di erences in data and simulation, a residual uncertainty in track reconstruction e ciency and misidenti cation rate corrections is estimated to be 5% [9]. The uncertainty arising from pair acceptance e ects is estimated by considering the sideband asymmetry after dividing by the mixed-event correlation. Each sideband region of the nal background-subtracted distribution ( 2:5 < 1:5 and 1:5 < is separately t with a constant. The greater of these two deviations from zero is assigned as systematic uncertainty, and is found to be within 5{9% for the lowest ptrk bin. The uncertainty resulting from the event decomposition is determined by evaluating pointto-point variations in the side-band projections used to estimate long-range correlation contributions. The event decomposition uncertainty is found to be within 2{5% for 0{30% central PbPb data in the the lowest ptrk bin where the background is most signi cant compared to the signal level, and decreases for less central collisions and for higher ptrk The systematic uncertainties from the sources discussed above are added in quadrature for the nal result. Table 1 lists the upper limits on the estimated contributions from the individual sources described above. Balanced jet selection (AJ < 0:22): Background uctuations JFF bias and jet swapping Tracking e ciency Residual track e ciency corr. Pair acceptance corrections Event decomposition Unbalanced jet selection (AJ > 0:22): Background uctuations JFF bias and jet swapping Tracking e ciency Residual track e ciency corr. Pair acceptance corrections Event decomposition correlations in PbPb and pp collisions. Upper and lower limits are shown as a function of collision centrality. Upper values correspond to the uncertainties at lowest ptTrk. In this analysis, two-dimensional momentum distributions with respect to high-pT leading and subleading jets are studied di erentially in centrality and ptTrk. First, the jet momentum density pro le is measured as a function of r = p( )2 for all dijet events, comparing PbPb to pp jet shapes up to r = 1. Next, the sample is divided into balanced (AJ < 0:22) and unbalanced (AJ > 0:22) dijet events, and the overall subleadingto-leading hemisphere momentum balance is evaluated by subtracting the distribution of ptTrk about the leading jet from the distribution of ptTrk about the subleading jet. This overall hemisphere momentum balance is then further decomposed into contributions from the leading and subleading jet peaks and from the underlying event-wide long-range asymmetry. The jet peak shapes are quite similar in , as reported in ref. [12], but the long-range \ridge-like" distribution is independent of ducial acceptance and uncertainties, while showing a clear dependence, as is visible in gure 1. To avoid convolving these two di erent trends, we present the results that follow as a function of including the overall subleading-to-leading hemisphere momentum balance and respective contributions from the leading and subleading peaks and underlying long-range asymmetry as a function of . Finally, we summarize our ndings by presenting the total momentum in each ptTrk bin, integrated over each hemisphere. Measurement of radial jet momentum density pro le After subtraction of the long-range background, ptrk correlations in used to obtain measurements of jet shape as a function of r by direct integration. Jet shape ( r) is de ned as: ( r) = The jet shape ( r) is extracted by integrating 2D jet-peak momentum distributions r=2 and the jet cone radius are normalized to integrate to unity within the radius r < 0:3. In gure 2, the leading jet shape measured with this correlation technique is compared to the published CMS measurement [11]. The new jet shape measurement is performed di erentially in ptTrk, in bins ranging from 0:5 < ptrk < 1 GeV to ptrk > 8 GeV . With the advantages provided by the correlation technique, the radial jet momentum density pro le measurements are also extended in this analysis to r = 1. The r = 1 limit is driven by the pp data, which has no correlated yields within our sample at larger r. The leading jet shape is found to be very similar to that in the previous measurement for an inclusive jet selection of all jets with pT > 100 GeV, despite small di erences in the jet selection. A new measurement of subleading jet shape is presented in gure 3. Signi cant jet shape modi cations are evident in central PbPb events for both leading and subleading jets with respect to the pp reference measurement, while in peripheral PbPb events the jet shapes are similar to the pp reference. Broadening of the jet structure is an expected consequence of jet quenching in theoretical models [31]. Here it is important to note that the broadening in central PbPb collisions is relative to the jets of the same type (leading or subleading) in pp collisions. The subleading jets are of lower pT by selection in both PbPb and pp, and signi cantly broader than leading jets in pp data. Thus, although subleading jets in central PbPb collisions are softer and broader than leading jets in these collisions, the relative jet shape modi cation (expressed via a ratio to pp data) is greater for leading jets since these are compared to the narrower pp leading jets. Azimuthal distribution of charged-particle transverse momentum To investigate in detail how the modi cation of the jet peaks contributes to the overall redistribution of ptTrk the event via ow reported in [9], we measure the transverse momentum balance in ptrk correlations to subleading and leading jets. First, we present the hemisphere-wide balancing distribution of ptTrk around the subleading versus the leading 00 0.5 ≤ ptrk< 1 GeV 1≤ ptTrk< 2 GeV 2 ≤ ptTrk< 3 GeV 3 ≤ ptTrk< 4 GeV 4 ≤ ptTrk< 8 GeV 101 (Δ 4 ρ Leading jet shape PbPb cent. 50-100% PbPb cent. 0-30% PLB 730 (2014) 243 denoted by di erent color shading). Shapes are normalized to unity over the region comparison with the published reference shown (ref. [11]). Bottom row: leading jet shape ratio vertical bars, and systematic uncertainties are shown with shaded boxes. ptrk > 8 GeV are not included in these low-ptTrk structures and modi cations. jets in gures 4 and 5, for balanced and unbalanced dijet events, respectively. These gures show the per-event azimuthal distribution of ptTrk about the leading or subleading jet axis, denoted P = 1=Nevt d pT=d , with the subleading-to-leading hemisphere di erence of this distribution denoted P. For display, all distributions are symmetrized in both balanced and unbalanced dijet events, a broad excess of soft particles is evident in the subleading versus leading hemisphere in central PbPb collisions relative to the pp reference data. This re ects the greater quenching of the subleading jet. In the unbalanced selection, as required by the momentum conservation, the signal is enhanced in both pp and PbPb data: in pp data a large excess of particles with ptrk > 3 GeV is present on the subleading side. This excess compensates for the smaller contribution of the highest pT particles in the jet itself. In peripheral PbPb data the distribution is quite similar to the pp reference, while in central PbPb data this balancing distribution consists mostly of soft particles with ptrk < 3 GeV, consistent with the ndings of the previous CMS study [9]. To demonstrate these medium modi cations more clearly, the di erence in yield between PbPb and pp collisions is shown in the bottom panels of gures 4 and 5. For presentation, tracks with gures, so that it is possible to zoom in on the 00 0.5 ≤ ptrk< 1 GeV 1≤ ptTrk< 2 GeV 2 ≤ ptTrk< 3 GeV 3 ≤ ptTrk< 4 GeV 4 ≤ ptTrk< 8 GeV 101 (Δ 4 ρ Subleading jet shape PbPb cent. 50-100% PbPb cent. 0-30% di erent color shading), normalized to unity over the region r < 0:3. Bottom row: subleading jet shape ratio systematic uncertainties are shown with shaded boxes. To elucidate the redistribution of ptTrk within the QGP, the distributions are separated into three components as stated above: the two Gaussian-like peaks about the leading and subleading jet axes, and a third component accounting for overall subleading-to-leading hemisphere asymmetry of the long-range side-band distributions (measured in the region j < 2:5). In gures 6 and 7, the jet peak components are shown for balanced and unbalanced jets, respectively, presenting subleading results as positive and leading results as negative (in line with the hemisphere di erence measurements in gures 4 and 5). Jet peak distributions after decomposition are projected over the full range j for consistency with the hemisphere di erence measurements. The top row of each panel rst shows the overall distribution of momentum carried by particles with ptrk < 8 GeV associated with the jet peak. The middle two panels then assess modi cations to the subleading and leading jets for each ptrk bin. Here, again, there is evidence of quenching of both the subleading and leading jets in central PbPb collisions relative to the pp reference data. There is an excess of low-pT particles correlated with the leading and subleading jet axes in both the balanced and unbalanced dijet selections, in agreement with results presented in the CMS study [12]. In unbalanced dijet events, this enhancement of soft particles turns into a depletion at higher ptTrk, and is greater on the subleading than the leading side. The pp subleading jet peak is broader than the pp leading jet peak and, pp 5.3 pb-1 (2.76 TeV) 0.5 ≤ ptTrk < 1 GeV 1 ≤ ptTrk < 2 GeV 2 ≤ ptTrk < 3 GeV 3 ≤ ptTrk < 4 GeV 4 ≤ ptTrk < 8 GeV 0.5 ≤ ptTrk < 8 GeV PbPb cent. 50-100% PbPb cent. 0-30% 11 1110..55-1.5PbP-1b - p-0.5p V e 5 pp 0 P -1.5 -1 -0.5 0 1 1-.15.5 -1 -0.5 0 hemispheres, projected on , for balanced dijet events with AJ < 0:22 shown di erentially by ptrk for pp reference, peripheral PbPb, and central PbPb data. Bottom row: PbPb-pp di erence T momentum distributions. Statistical uncertainties are shown with vertical bars, and systematic uncertainties are shown with shaded boxes. while both subleading and leading jet peaks are broader in central PbPb than pp data, the PbPb-pp excess is wider on the leading than on the subleading side. To assess the jet peak contributions to the overall hemisphere momentum balance, the double-di erential (PbPb-pp, subleading-leading) result is presented in the bottom panel. Here it is evident that the low-ptTrk excess in central PbPb collisions is greater on the subleading than the leading side of the dijet system, but the larger subleading-to-leading excess only accounts for a portion of the total momentum redistribution in unbalanced dijet events. It is also clear that the high-ptTrk large-angle depletion observed in the overall hemisphere momentum balance distribution is not produced by the Gaussian-like jet peaks. To uncover the missing part of the total transverse momentum balance, these jetrelated studies are complemented by an analysis of the long-range subleading-to-leading hemisphere asymmetry, presented in gures 8 and 9 for balanced and unbalanced jets, respectively. The long-range correlated background in balanced dijet events is approximately symmetric in pp and peripheral PbPb data, while in central PbPb data there is a small excess of low-pT particles. In unbalanced dijet events, however, there is already signi cant asymmetry in the pp reference data, with a large correlated excess of particles in all ptTrk classes less than 8 GeV on the subleading relative to the leading side of the underlying event. This asymmetry re ects the presence of other hard-scattering products in the subleading pp 5.3 pb-1 (2.76 TeV) 0.5 ≤ ptTrk < 1 GeV 1 ≤ ptTrk < 2 GeV 2 ≤ ptTrk < 3 GeV 3 ≤ ptTrk < 4 GeV 4 ≤ ptTrk < 8 GeV 0.5 ≤ ptTrk < 8 GeV PbPb cent. 50-100% PbPb cent. 0-30% 11 1110..55-1.5PbP-1b - p-0.5p V e 5 pp 0 P -1.5 -1 -0.5 0 1 1-.15.5 -1 -0.5 0 0.5 hemispheres, projected on , for unbalanced dijet events with AJ > 0:22, shown di erentially by ptrk for the pp reference data, peripheral PbPb, and central PbPb data. Bottom row: PbPb-pp T di erence in these momentum distributions. Statistical uncertainties are shown with vertical bars, and systematic uncertainties are shown with shaded boxes. hemisphere of dijet events (e.g. additional jets), as required by the momentum conservation for asymmetric dijet events in pp collisions. In the presence of the strongly interacting medium, however, this underlying event asymmetry in asymmetric dijet events changes notably. In peripheral PbPb collisions, an onset of some depletion of momentum carried by high-pT particles can be seen, and in central PbPb data, subleading-to-leading underlying event excesses with ptrk > 2 GeV nearly vanish. The signi cance of the contribution of this long-range asymmetry to the total hemisphere imbalance is further assessed by the double di erence (PbPb-pp, subleading-leading), which is shown on the bottom panel. The absence of a high-ptTrk component in the long-range part of the correlation suggests that events containing additional jets constitute a smaller fraction of unbalanced dijet events in PbPb than pp data. A likely explanation for this e ect is that while momentum conservation requires the presence of additional jets in unbalanced pp dijet events, in PbPb data the sample of unbalanced dijet events also includes events in which the dijet asymmetry is due to the greater quenching of the subleading jet. Integrated hemisphere momentum balance To summarize all contributions to the overall ptrk ow in the dijet events, we rst present the hemisphere integral P represents the subleading-to-leading di erence pp 5.3 pb-1 (2.76 TeV) 100 pp reference PbPb cent. 50-100% PbPb cent. 0-30% -1.5 -1 -0.5 0 1 115.5-1.5Sub-1lea d-0.i5ng P0bP b0.5 - pp1 0.5 ≤ ptrk < 1 GeV 1 ≤ ptTrk < 2 GeV 2 ≤ ptTrk < 3 GeV 3 ≤ ptTrk < 4 GeV 4 ≤ ptTrk < 8 GeV 0.5 ≤ ptrk < 8 GeV eG 5 ( V e 5 p 0 p P -1.5 -1 -0.5 0 1-.15.5 -1 -0.5 0 of ptTrk about the subleading (plotted positive) and leading (plotted negative) jets for balanced dijet events with AJ < 0:22. Middle rows: PbPb-pp momentum distribution di erences for subleading and leading jets. Bottom row: PbPb-pp, subleading-leading double di erence in these momentum distributions. Statistical uncertainties are shown with vertical bars, and systematic uncertainties are shown with Leading PbPb - pp Subleading - leading pp 5.3 pb-1 (2.76 TeV) 100 pp reference PbPb cent. 50-100% PbPb cent. 0-30% -1.5 -1 -0.5 0 1 115.5-1.5Sub-1lea d-0.i5ng P0bP b0.5 - pp1 0.5 ≤ ptrk < 1 GeV 1 ≤ ptTrk < 2 GeV 2 ≤ ptTrk < 3 GeV 3 ≤ ptTrk < 4 GeV 4 ≤ ptTrk < 8 GeV 0.5 ≤ ptrk < 8 GeV eG 5 ( V e 5 p 0 p P -1.5 -1 -0.5 0 1-.15.5 -1 -0.5 0 of ptTrk about the subleading (plotted positive) and leading (plotted negative) jets for unbalanced dijet events with AJ > 0:22. Middle rows: PbPb-pp momentum distribution di erences for subleading and leading jets. Bottom row: PbPb-pp, subleading-leading double di erence in these momentum distributions. Statistical uncertainties are shown with vertical bars, and systematic uncertainties are shown with Leading PbPb - pp Subleading - leading pp 5.3 pb-1 (2.76 TeV) 15 pp reference PbPb cent. 50-100% PbPb cent. 0-30% 11 1110..55-1.5PbP-1b - p-0.5p 0.5 ≤ ptTrk < 1 GeV 1 ≤ ptTrk < 2 GeV 2 ≤ ptTrk < 3 GeV 3 ≤ ptTrk < 4 GeV 4 ≤ ptTrk < 8 GeV 0.5 ≤ ptTrk < 8 GeV -1.5 -1 -0.5 0 1 1-.15.5 -1 -0.5 0 of excess ptrk in the subleading relative to T leading sides for balanced dijet events with AJ < 0:22. Bottom row: PbPb-pp di erence in these long-range momentum distributions. Statistical uncertainties are shown with vertical bars, and systematic uncertainties are shown with shaded boxes. distribution of ptTrk in the event) for this long-range asymmetry, measured in =2 and j j < 2:5, in gure 10. For balanced dijet events, the PbPb and pp integrals follow similar ptrk dependences. For unbalanced dijet events, the overall asymmetry rises with ptTrk in the pp reference data, but falls with ptTrk in central PbPb data, indicating the presence of di erent sources for the long-range momentum correlations. Finally, a summary of hemisphere-integrated excess (PbPb-pp) yields from all assessed sources for balanced and unbalanced dijet events is shown in gures 11 and 12. The top panels of gure 11 present total central PbPb-pp di erences in ptrk associated with the subleading (plotted positive) and leading (plotted negative) jets. The leading and subleading jet peak modi cations o set each other, so the total jet-peak-related modi cation, constructed from these two distributions, is also presented. The total jet peak modi cations in central PbPb collisions are not signi cantly di erent in unbalanced versus balanced dijet events. The bottom panels of gure 11 present these jet-peak modi cations together with the long-range modi cations evident in gure 10 to show the decomposed hemisphere-wide di erences in associated pT in each track pT range. Unlike the jet peak contributions, the long-range PbPb versus pp modi cations are greater than their uncertainties between balanced and unbalanced dijet events. Here the depletion of high-pT tracks in unbalanced PbPb versus pp dijet events corresponds to the reduced contribution from additional jets (which pp 5.3 pb-1 (2.76 TeV) 15 pp reference PbPb cent. 50-100% PbPb cent. 0-30% 11 1110..55-1.5PbP-1b - p-0.5p 0.5 ≤ ptTrk < 1 GeV 1 ≤ ptTrk < 2 GeV 2 ≤ ptTrk < 3 GeV 3 ≤ ptTrk < 4 GeV 4 ≤ ptTrk < 8 GeV 0.5 ≤ ptTrk < 8 GeV -1.5 -1 -0.5 0 1 1-.15.5 -1 -0.5 0 of excess ptrk in the subleading relative to T leading sides for unbalanced dijet events with AJ > 0:22. Bottom row: PbPb-pp di erence in these long-range momentum distributions. Statistical uncertainties are shown with vertical bars, and systematic uncertainties are shown with shaded boxes. are prominently evident in the long-range distribution for pp unbalanced dijet events) in central PbPb unbalanced dijet events. Figure 12 presents the same hemisphere-integrated PbPb-pp excess for peripheral collisions for comparison to the central results shown in gure 11. Some possible small modi cations are already evident in this 50{100% centrality range, but these di erences between peripheral PbPb and pp results are in most cases smaller than systematic uncertainties. Summary In this analysis, the redistribution of momentum in dijet events is studied via twousing data sets with integrated luminosities of 166 b 1 and 5.3 pb 1, respectively. Events are selected to include a leading jet with pT;1 > 120 GeV and subleading jet with pT;2 > 50 GeV, with an azimuthal separation of at least 1;2 > 5 =6. Subtracting the long-range part of the correlation from the jet peaks, this work extends the studies of jet shape modi cations in PbPb events relative to pp collisions to large radial distances 1) from the jet axis. These modi cations are found to extend out to the largest radial distance studied in central PbPb events for both leading and subleading jets. The jet modi cations are further studied di erentially for balanced and unbalanced dijet events, and as pp 5.3 pb-1 (2.76 TeV) -correlated distribution as a function of track-ptTrk integrated over j =2 and j j < 2:5 for pp reference, peripheral PbPb and central PbPb data for balanced compared to unbalanced dijet events. Statistical uncertainties are shown with vertical bars, and systematic uncertainties are shown with shaded boxes. a function of ptTrk and collision centrality for each of these selections in PbPb and pp reference data. Transverse momentum redistribution around the subleading and leading jets, as well as di erences in long-range correlated background asymmetry, are separately analyzed. An excess of transverse momentum carried by soft particles (ptTrk < 2 GeV) is found for both leading and subleading jets in central PbPb collisions relative to the pp reference, consistent with previous studies of charged-particle yields correlated to high-pT jets. For unbalanced dijet events, this low-ptTrk excess is greater on the subleading-jet side than on the leading-jet side. However, the di erence in ptTrk contained in the Gaussian-like jet peaks is found only partially to account for the total ptTrk redistribution in the most central PbPb collisions with dijet events. In the long-range correlated distribution of ptrk under the jet subleading side relative to the leading side, which is observed in asymmetric pp collisions and mainly attributed to three-jet events, is absent in most central PbPb collisions. This indicates that the fraction of events with additional jets in the asymmetric dijet sample is signi cantly lower than in an identical selection of dijet events in pp data. A long-range asymmetry in the low-pT particles in dijet events is also observed, providing further input for the theoretical understanding of jet-medium coupling. We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative sta s at CERN and at other CMS institutes for their contributions to the success of the CMS e ort. In addition, we gratefully acknowledge the computing centres and personnel of the Worldwide ( p 5 PΣ 0 ΣΔ 0 Subleading and leading jets Subleading and leading jets 50-100% peripheral ptrk (GeV) ptrk (GeV) to the pp reference data, integrated over j =2 and j Top row: subleading and leading jet peaks PbPb-pp. Bottom row: relative contributions from jet peaks and twodimensional asymmetry to the double di erence PbPb-pp, subleading-leading in total hemisphere ptTrk. Statistical uncertainties are shown with vertical bars, and systematic uncertainties are shown with shaded boxes. NSTDA (Thailand); TUBITAK and TAEK (Turkey); NASU and SFFR (Ukraine); STFC (United Kingdom); DOE and NSF (U.S.A.). IIndividuals 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 O ce; the Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Council of Science and Industrial Research, India; the HOMING PLUS programme of the Foundation for Polish Science, co nanced from European Union, Regional Development Fund, the Mobility Plus programme of the Ministry of Science and Higher Education, the National Science Center (Poland), contracts Harmonia 2014/14/M/ST2/00428, Opus 2013/11/B/ST2/04202, 2014/13/B/ST2/02543 and grammes co nanced by EU-ESF and the Greek NSRF; the National Priorities Research Program by Qatar National Research Fund; the Programa Clar n-COFUND del Principado de Asturias; the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University and the Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand); and the Welch Foundation, contract C-1845. 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Dreyer, E. Garutti, D. Gonzalez, J. Haller, M. Ho mann, A. Junkes, R. Klanner, R. Kogler, N. Kovalchuk, T. Lapsien, T. Lenz, I. Marchesini, D. Marconi, M. Meyer, M. Niedziela, D. Nowatschin, F. Pantaleo14, T. Pei er, A. Perieanu, J. Poehlsen, C. Sander, C. Scharf, P. Schleper, A. Schmidt, S. Schumann, J. Schwandt, H. Stadie, G. Steinbruck, F.M. Stober, M. Stover, H. Tholen, D. Troendle, E. Usai, L. Vanelderen, A. Vanhoefer, B. Vormwald Institut fur Experimentelle Kernphysik, Karlsruhe, Germany C. Barth, C. Baus, J. Berger, E. Butz, T. Chwalek, F. Colombo, W. De Boer, A. Dierlamm, S. Fink, R. Friese, M. Gi els, A. Gilbert, P. Goldenzweig, D. Haitz, F. Hartmann14, Paraskevi, Greece I. Topsis-Giotis M.U. Mozer, T. Muller, Th. Muller, M. Plagge, G. Quast, K. Rabbertz, S. Rocker, F. Roscher, M. Schroder, I. Shvetsov, G. Sieber, H.J. Simonis, R. Ulrich, J. Wagner-Kuhr, S. Wayand, M. Weber, T. Weiler, S. Williamson, C. Wohrmann, R. Wolf Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia G. Anagnostou, G. Daskalakis, T. Geralis, V.A. Giakoumopoulou, A. Kyriakis, D. Loukas, National and Kapodistrian University of Athens, Athens, Greece A. Agapitos, S. Kesisoglou, A. Panagiotou, N. Saoulidou, E. Tziaferi University of Ioannina, Ioannina, Greece I. Evangelou, G. Flouris, C. Foudas, P. Kokkas, N. Loukas, N. Manthos, I. Papadopoulos, E. Paradas University, Budapest, Hungary N. Filipovic MTA-ELTE Lendulet CMS Particle and Nuclear Physics Group, Eotvos Lorand Wigner Research Centre for Physics, Budapest, Hungary G. Bencze, C. Hajdu, P. Hidas, D. Horvath20, F. Sikler, V. Veszpremi, G. Vesztergombi21, Institute of Nuclear Research ATOMKI, Debrecen, Hungary N. Beni, S. Czellar, J. Karancsi22, A. Makovec, J. Molnar, Z. Szillasi University of Debrecen, Debrecen, Hungary M. Bartok21, P. Raics, Z.L. Trocsanyi, B. Ujvari National Institute of Science Education and Research, Bhubaneswar, India S. Bahinipati, S. Choudhury23, P. Mal, K. Mandal, A. Nayak24, D.K. Sahoo, N. Sahoo, Panjab University, Chandigarh, India S. Bansal, S.B. Beri, V. Bhatnagar, R. Chawla, U.Bhawandeep, A.K. Kalsi, A. Kaur, M. Kaur, R. Kumar, A. Mehta, M. Mittal, J.B. Singh, G. Walia University of Delhi, Delhi, India Ashok Kumar, A. Bhardwaj, B.C. Choudhary, R.B. Garg, S. Keshri, S. Malhotra, M. Naimuddin, N. Nishu, K. Ranjan, R. Sharma, V. Sharma Saha Institute of Nuclear Physics, Kolkata, India R. Bhattacharya, S. Bhattacharya, K. Chatterjee, S. Dey, S. Dutt, S. Dutta, S. Ghosh, N. Majumdar, A. Modak, K. Mondal, S. Mukhopadhyay, S. Nandan, A. Purohit, A. Roy, D. Roy, S. Roy Chowdhury, S. Sarkar, M. Sharan, S. Thakur Indian Institute of Technology Madras, Madras, India Bhabha Atomic Research Centre, Mumbai, India R. Chudasama, D. Dutta, V. Jha, V. Kumar, A.K. Mohanty14, P.K. Netrakanti, L.M. Pant, P. Shukla, A. Topkar Tata Institute of Fundamental Research-A, Mumbai, India T. Aziz, S. Dugad, G. Kole, B. Mahakud, S. Mitra, G.B. Mohanty, B. Parida, N. Sur, Tata Institute of Fundamental Research-B, Mumbai, India S. Banerjee, S. Bhowmik25, R.K. Dewanjee, S. Ganguly, M. Guchait, Sa. Jain, S. Kumar, M. Maity25, G. Majumder, K. Mazumdar, T. Sarkar25, N. Wickramage26 Indian Institute of Science Education and Research (IISER), Pune, India S. Chauhan, S. Dube, V. Hegde, A. Kapoor, K. Kothekar, A. Rane, S. Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran H. Behnamian, S. Chenarani27, E. Eskandari Tadavani, S.M. Etesami27, A. Fahim28, M. Khakzad, M. Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi, F. Rezaei Hosseinabadi, B. Safarzadeh29, M. Zeinali University College Dublin, Dublin, Ireland M. Felcini, M. Grunewald INFN Sezione di Bari a, Universita di Bari b, Politecnico di Bari c, Bari, Italy M. Abbresciaa;b, C. Calabriaa;b, C. Caputoa;b, A. Colaleoa, D. Creanzaa;c, L. Cristellaa;b, N. De Filippisa;c, M. De Palmaa;b, L. Fiorea, G. Iasellia;c, G. Maggia;c, M. 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Thyssen Trento c, Trento, Italy INFN Sezione di Padova a, Universita di Padova b, Padova, Italy, Universita di P. Azzia;14, N. Bacchettaa, L. Benatoa;b, D. Biselloa;b, A. Bolettia;b, R. Carlina;b, A. Carvalho Antunes De Oliveiraa;b, P. Checchiaa, M. Dall'Ossoa;b, P. De Castro Manzanoa, T. Dorigoa, U. Dossellia, F. Gasparinia;b, U. Gasparinia;b, A. Gozzelinoa, S. Lacapraraa, M. Margonia;b, A.T. Meneguzzoa;b, J. Pazzinia;b;14, N. Pozzobona;b, P. Ronchesea;b, F. Simonettoa;b, E. Torassaa, M. Zanetti, P. Zottoa;b, A. Zucchettaa;b, G. Zumerlea;b INFN Sezione di Pavia a, Universita di Pavia b, Pavia, Italy A. Braghieria, A. Magnania;b, P. Montagnaa;b, S.P. Rattia;b, V. Rea, C. Riccardia;b, P. Salvinia, I. Vaia;b, P. Vituloa;b INFN Sezione di Perugia a, Universita di Perugia b, Perugia, Italy L. Alunni Solestizia;b, G.M. Bileia, D. Ciangottinia;b, L. Fanoa;b, P. Laricciaa;b, R. Leonardia;b, G. Mantovania;b, M. Menichellia, A. Sahaa, A. Santocchiaa;b INFN Sezione di Pisa a, Universita di Pisa b, Scuola Normale Superiore di Pisa c, Pisa, Italy K. Androsova;30, P. Azzurria;14, G. Bagliesia, J. Bernardinia, T. Boccalia, R. Castaldia, M.A. Cioccia;30, R. Dell'Orsoa, S. Donatoa;c, G. Fedi, A. Giassia, M.T. Grippoa;30, F. Ligabuea;c, T. Lomtadzea, L. Martinia;b, A. Messineoa;b, F. Pallaa, A. Rizzia;b, A. Savoy-Navarroa;31, P. Spagnoloa, R. Tenchinia, G. Tonellia;b, A. Venturia, P.G. Verdinia INFN Sezione di Roma a, Universita di Roma b, Roma, Italy L. Baronea;b, F. Cavallaria, M. Cipriania;b, G. D'imperioa;b;14, D. Del Rea;b;14, M. Diemoza, S. Gellia;b, C. Jordaa, E. Longoa;b, F. Margarolia;b, P. Meridiania, G. Organtinia;b, R. Paramattia, F. Preiatoa;b, S. Rahatloua;b, C. Rovellia, F. Santanastasioa;b INFN Sezione di Torino a, Universita di Torino b, Torino, Italy, Universita del Piemonte Orientale c, Novara, Italy N. Amapanea;b, R. Arcidiaconoa;c;14, S. Argiroa;b, M. Arneodoa;c, N. Bartosika, R. Bellana;b, C. Biinoa, N. Cartigliaa, F. Cennaa;b, M. Costaa;b, R. Covarellia;b, A. Deganoa;b, N. Demariaa, L. Fincoa;b, B. Kiania;b, C. Mariottia, S. Masellia, E. Migliorea;b, V. Monacoa;b, E. Monteila;b, M.M. Obertinoa;b, L. Pachera;b, N. Pastronea, R. Sacchia;b, K. Shchelinaa;b, V. Solaa, A. Solanoa;b, A. Staianoa, P. Traczyka;b INFN Sezione di Trieste a, Universita di Trieste b, Trieste, Italy S. Belfortea, M. Casarsaa, F. Cossuttia, G. Della Riccaa;b, C. La Licataa;b, A. Schizzia;b, Kyungpook National University, Daegu, Korea D.H. Kim, G.N. Kim, M.S. Kim, S. Lee, S.W. Lee, Y.D. Oh, S. Sekmen, D.C. Son, A. Zanettia Chonbuk National University, Jeonju, Korea Hanyang University, Seoul, Korea J.A. Brochero Cifuentes, T.J. Kim Korea University, Seoul, Korea S. Lee, J. Lim, S.K. Park, Y. Roh Seoul National University, Seoul, Korea S. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, Y. Jo, Y. Kim, B. Lee, K. Lee, K.S. Lee, J. Almond, J. Kim, S.B. Oh, S.h. Seo, U.K. Yang, H.D. Yoo, G.B. Yu University of Seoul, Seoul, Korea M. Choi, H. Kim, H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park, G. Ryu, M.S. Ryu Sungkyunkwan University, Suwon, Korea Y. Choi, J. Goh, C. Hwang, J. Lee, I. Yu Vilnius University, Vilnius, Lithuania V. Dudenas, A. Juodagalvis, J. Vaitkus National Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Malaysia I. Ahmed, Z.A. Ibrahim, J.R. Komaragiri, M.A.B. Md Ali32, F. Mohamad Idris33, W.A.T. Wan Abdullah, M.N. Yusli, Z. Zolkapli Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico H. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-De La Cruz34, A. Hernandez-Almada, R. Lopez-Fernandez, R. Magan~a Villalba, J. Mejia Guisao, A. Sanchez-Hernandez Universidad Iberoamericana, Mexico City, Mexico S. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia Benemerita Universidad Autonoma de Puebla, Puebla, Mexico S. Carpinteyro, I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad Autonoma de San Luis Potos , San Luis Potos , Mexico A. Morelos Pineda { 31 { D. Krofcheck University of Canterbury, Christchurch, New Zealand National Centre for Physics, Quaid-I-Azam University, Islamabad, Pakistan A. Ahmad, M. Ahmad, Q. Hassan, H.R. Hoorani, W.A. Khan, M.A. Shah, M. Shoaib, National Centre for Nuclear Research, Swierk, Poland H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Gorski, M. Kazana, K. Nawrocki, K. Romanowska-Rybinska, M. Szleper, P. Zalewski Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Warsaw, Poland K. Bunkowski, A. Byszuk35, K. Doroba, A. Kalinowski, M. Konecki, J. Krolikowski, M. Misiura, M. Olszewski, M. Walczak Laboratorio de Instrumentac~ao e F sica Experimental de Part culas, Lisboa, Joint Institute for Nuclear Research, Dubna, Russia S. Afanasiev, P. Bunin, I. Golutvin, A. Kamenev, V. Karjavin, V. Korenkov, A. Lanev, A. Malakhov, V. Matveev36;37, V.V. Mitsyn, P. Moisenz, V. Palichik, V. Perelygin, S. Shmatov, N. Skatchkov, V. Smirnov, E. Tikhonenko, B.S. Yuldashev38, A. Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia L. Chtchipounov, V. Golovtsov, Y. Ivanov, V. Kim39, E. Kuznetsova40, V. Murzin, V. Oreshkin, V. Sulimov, A. Vorobyev Institute for Nuclear Research, Moscow, Russia Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov, N. Krasnikov, A. Pashenkov, D. Tlisov, A. Toropin Institute for Theoretical and Experimental Physics, Moscow, Russia V. Epshteyn, V. Gavrilov, N. Lychkovskaya, V. Popov, I. Pozdnyakov, G. Safronov, A. Spiridonov, M. Toms, E. Vlasov, A. Zhokin Moscow Institute of Physics and Technology A. Bylinkin37 tute' (MEPhI), Moscow, Russia R. Chistov41, M. Danilov41, V. Rusinov National Research Nuclear University 'Moscow Engineering Physics InstiV. Andreev, M. Azarkin37, I. Dremin37, M. Kirakosyan, A. Leonidov37, S.V. Rusakov, Moscow, Russia Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, A. Baskakov, A. Belyaev, E. Boos, A. Demiyanov, A. Ershov, A. Gribushin, O. Kodolova, Novosibirsk State University (NSU), Novosibirsk, Russia V. Blinov42, Y.Skovpen42 State Research Center of Russian Federation, Institute for High Energy Physics, Protvino, Russia I. Azhgirey, I. Bayshev, S. Bitioukov, D. Elumakhov, V. Kachanov, A. Kalinin, D. Konstantinov, V. Krychkine, V. Petrov, R. Ryutin, A. Sobol, S. Troshin, N. Tyurin, A. Uzunian, A. Volkov University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia P. Adzic43, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic, V. Rekovic Centro de Investigaciones Energeticas Medioambientales y Tecnologicas (CIEMAT), Madrid, Spain J. Alcaraz Maestre, M. Barrio Luna, E. Calvo, M. Cerrada, M. Chamizo Llatas, N. Colino, B. De La Cruz, A. Delgado Peris, A. Escalante Del Valle, C. Fernandez Bedoya, J.P. Fernandez Ramos, J. Flix, M.C. Fouz, P. Garcia-Abia, O. Gonzalez Lopez, S. Goy Lopez, J.M. Hernandez, M.I. Josa, E. Navarro De Martino, A. Perez-Calero Yzquierdo, J. Puerta Pelayo, A. Quintario Olmeda, I. Redondo, L. Romero, M.S. Soares Universidad Autonoma de Madrid, Madrid, Spain J.F. de Troconiz, M. Missiroli, D. Moran Universidad de Oviedo, Oviedo, Spain J. Cuevas, J. Fernandez Menendez, I. Gonzalez Caballero, J.R. Gonzalez Fernandez, E. Palencia Cortezon, S. Sanchez Cruz, I. Suarez Andres, J.M. Vizan Garcia Instituto de F sica de Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, Spain I.J. Cabrillo, A. Calderon, J.R. Castin~eiras De Saa, E. Curras, M. Fernandez, J. Garcia-Ferrero, G. Gomez, A. Lopez Virto, J. Marco, C. Martinez Rivero, F. Matorras, J. Piedra Gomez, T. Rodrigo, A. Ruiz-Jimeno, L. Scodellaro, N. Trevisani, I. Vila, R. Vilar CERN, European Organization for Nuclear Research, Geneva, Switzerland D. Abbaneo, E. Au ray, G. Auzinger, M. Bachtis, P. Baillon, A.H. Ball, D. Barney, P. Bloch, A. Bocci, A. Bonato, C. Botta, T. Camporesi, R. Castello, M. Cepeda, Gruttola, F. De Guio, A. De Roeck, E. Di Marco44, M. Dobson, B. Dorney, T. du Pree, D. Duggan, M. Dunser, N. Dupont, A. Elliott-Peisert, S. Fartoukh, G. Franzoni, J. Fulcher, W. Funk, D. Gigi, K. Gill, M. Girone, F. Glege, D. Gulhan, S. Gundacker, M. Gutho , J. Hammer, P. Harris, J. Hegeman, V. Innocente, P. Janot, H. Kirschenmann, V. Knunz, A. Kornmayer14, M.J. Kortelainen, K. Kousouris, M. Krammer1, P. Lecoq, C. Lourenco, M.T. Lucchini, L. Malgeri, M. Mannelli, A. Martelli, F. Meijers, S. Mersi, E. Meschi, F. Moortgat, S. Morovic, M. Mulders, H. Neugebauer, S. Orfanelli, L. Orsini, L. Pape, Paul Scherrer Institut, Villigen, Switzerland W. Bertl, K. Deiters, W. Erdmann, R. Horisberger, Q. Ingram, H.C. Kaestli, D. Kotlinski, U. Langenegger, T. Rohe Institute for Particle Physics, ETH Zurich, Zurich, Switzerland F. Bachmair, L. Bani, L. Bianchini, B. Casal, G. Dissertori, M. Dittmar, M. Donega, P. Eller, C. Grab, C. Heidegger, D. Hits, J. Hoss, G. Kasieczka, P. Lecomtey, W. Lustermann, B. Mangano, M. Marionneau, M. Masciovecchio, M.T. Meinhard, D. Meister, F. Micheli, P. Musella, F. Nessi-Tedaldi, F. Pandol , J. Pata, F. Pauss, G. Perrin, L. Perrozzi, M. Quittnat, M. Rossini, M. Schonenberger, A. Starodumov48, V.R. Tavolaro, K. Theo latos, R. Wallny Universitat Zurich, Zurich, Switzerland T.K. Aarrestad, C. Amsler49, L. Caminada, M.F. Canelli, A. De Cosa, C. Galloni, A. Hinzmann, T. Hreus, B. Kilminster, C. Lange, J. Ngadiuba, D. Pinna, G. Rauco, P. Robmann, D. Salerno, Y. Yang National Central University, Chung-Li, Taiwan V. Candelise, T.H. Doan, Sh. Jain, R. Khurana, M. Konyushikhin, C.M. Kuo, W. Lin, Y.J. Lu, A. Pozdnyakov, S.S. Yu National Taiwan University (NTU), Taipei, Taiwan Arun Kumar, P. Chang, Y.H. Chang, Y.W. Chang, Y. Chao, K.F. Chen, P.H. Chen, C. Dietz, F. Fiori, W.-S. Hou, Y. Hsiung, Y.F. Liu, R.-S. Lu, M. Min~ano Moya, E. Paganis, A. Psallidas, J.f. Tsai, Y.M. Tzeng Chulalongkorn University, Faculty of Science, Department of Physics, Bangkok, B. Asavapibhop, G. Singh, N. Srimanobhas, N. Suwonjandee Cukurova University, Adana, Turkey A. Adiguzel, S. Cerci50, S. Damarseckin, Z.S. Demiroglu, C. Dozen, I. Dumanoglu, S. Girgis, G. Gokbulut, Y. Guler, E. Gurpinar, I. Hos, E.E. Kangal51, O. Kara, A. Kayis Topaksu, U. Kiminsu, M. Oglakci, G. Onengut52, K. Ozdemir53, D. Sunar Cerci50, H. Topakli54, S. Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East Technical University, Physics Department, Ankara, Turkey B. Bilin, S. Bilmis, B. Isildak55, G. Karapinar56, M. Yalvac, M. Zeyrek Bogazici University, Istanbul, Turkey E. Gulmez, M. Kaya57, O. Kaya58, E.A. Yetkin59, T. Yetkin60 Istanbul Technical University, Istanbul, Turkey A. Cakir, K. Cankocak, S. Sen61 Institute for Scintillation Materials of National Academy of Science of Ukraine, Kharkov, Ukraine B. Grynyov Kharkov, Ukraine L. Levchuk, P. Sorokin National Scienti c Center, Kharkov Institute of Physics and Technology, University of Bristol, Bristol, United Kingdom R. Aggleton, F. Ball, L. Beck, J.J. Brooke, D. Burns, E. Clement, D. Cussans, H. Flacher, J. Goldstein, M. Grimes, G.P. Heath, H.F. Heath, J. Jacob, L. Kreczko, C. Lucas, D.M. Newbold62, S. Paramesvaran, A. Poll, T. Sakuma, S. Seif El Nasr-storey, D. Smith, Rutherford Appleton Laboratory, Didcot, United Kingdom D. Barducci, A. Belyaev63, C. Brew, R.M. Brown, L. Calligaris, D. Cieri, D.J.A. Cockerill, J.A. Coughlan, K. Harder, S. Harper, E. Olaiya, D. Petyt, C.H. Shepherd-Themistocleous, A. Thea, I.R. Tomalin, T. Williams Imperial College, London, United Kingdom M. Baber, R. Bainbridge, O. Buchmuller, A. Bundock, D. Burton, S. Casasso, M. Citron, D. Colling, L. Corpe, P. Dauncey, G. Davies, A. De Wit, M. Della Negra, R. Di Maria, P. Dunne, A. Elwood, D. Futyan, Y. Haddad, G. Hall, G. Iles, T. James, R. Lane, C. Laner, R. Lucas62, L. Lyons, A.-M. Magnan, S. Malik, L. Mastrolorenzo, J. Nash, A. Nikitenko48, J. Pela, B. Penning, M. Pesaresi, D.M. Raymond, A. Richards, A. Rose, C. Seez, S. Summers, A. Tapper, K. Uchida, M. Vazquez Acosta64, T. Virdee14, J. Wright, Brunel University, Uxbridge, United Kingdom J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, D. Leslie, I.D. Reid, P. Symonds, L. Teodorescu, M. Turner Baylor University, Waco, U.S.A. A. Borzou, K. Call, J. Dittmann, K. Hatakeyama, H. Liu, N. Pastika The University of Alabama, Tuscaloosa, U.S.A. O. Charaf, S.I. Cooper, C. Henderson, P. Rumerio Brown University, Providence, U.S.A. University of California, Davis, Davis, U.S.A. R. Breedon, G. Breto, D. Burns, M. Calderon De La Barca Sanchez, S. Chauhan, M. Chertok, J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk, M. Gardner, W. Ko, R. Lander, C. Mclean, M. Mulhearn, D. Pellett, J. Pilot, F. Ricci-Tam, S. Shalhout, J. Smith, M. Squires, D. Stolp, M. Tripathi, S. Wilbur, R. 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Yelton Florida International University, Miami, U.S.A. S. Linn, P. Markowitz, G. Martinez, J.L. Rodriguez Florida State University, Tallahassee, U.S.A. A. Ackert, J.R. Adams, T. Adams, A. Askew, S. Bein, B. Diamond, S. Hagopian, V. Hagopian, K.F. Johnson, A. Khatiwada, H. Prosper, A. Santra, M. Weinberg Florida Institute of Technology, Melbourne, U.S.A. M.M. Baarmand, V. Bhopatkar, S. Colafranceschi67, M. Hohlmann, D. Noonan, T. Roy, University of Illinois at Chicago (UIC), Chicago, U.S.A. M.R. Adams, L. Apanasevich, D. Berry, R.R. Betts, I. Bucinskaite, R. Cavanaugh, O. Evdokimov, L. Gauthier, C.E. Gerber, D.J. Hofman, P. Kurt, C. O'Brien, I.D. Sandoval Gonzalez, H. Trauger, P. Turner, N. Varelas, H. Wang, Z. Wu, M. Zakaria, J. Zhang The University of Iowa, Iowa City, U.S.A. B. Bilki68, W. Clarida, K. Dilsiz, S. Durgut, R.P. Gandrajula, M. Haytmyradov, V. Khristenko, J.-P. Merlo, H. Mermerkaya69, A. Mestvirishvili, A. Moeller, J. Nachtman, H. Ogul, Y. Onel, F. Ozok70, A. Penzo, C. 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D. Abercrombie, B. Allen, A. Apyan, R. Barbieri, A. Baty, R. Bi, K. Bierwagen, S. Brandt, W. Busza, I.A. Cali, Z. Demiragli, L. Di Matteo, G. Gomez Ceballos, M. Goncharov, D. Hsu, Y. Iiyama, G.M. Innocenti, M. Klute, D. Kovalskyi, K. Krajczar, Y.S. Lai, Y.-J. Lee, A. Levin, P.D. Luckey, A.C. Marini, C. Mcginn, C. Mironov, S. Narayanan, X. Niu, C. Paus, C. Roland, G. Roland, J. Salfeld-Nebgen, G.S.F. Stephans, K. Sumorok, K. Tatar, M. Varma, D. Velicanu, J. Veverka, J. Wang, T.W. Wang, B. Wyslouch, M. Yang, University of Minnesota, Minneapolis, U.S.A. A.C. Benvenuti, R.M. Chatterjee, A. Evans, A. Finkel, A. Gude, P. Hansen, S. Kalafut, S.C. Kao, Y. Kubota, Z. Lesko, J. Mans, S. Nourbakhsh, N. Ruckstuhl, R. Rusack, N. Tambe, J. Turkewitz University of Mississippi, Oxford, U.S.A. J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, U.S.A. E. Avdeeva, R. Bartek, K. Bloom, D.R. Claes, A. Dominguez, C. Fangmeier, R. Gonzalez Suarez, R. Kamalieddin, I. Kravchenko, A. Malta Rodrigues, F. Meier, J. Monroy, J.E. Siado, G.R. Snow, B. Stieger State University of New York at Bu alo, Bu alo, U.S.A. M. Alyari, J. Dolen, J. George, A. Godshalk, C. Harrington, I. Iashvili, J. Kaisen, A. Kharchilava, A. Kumar, A. Parker, S. Rappoccio, B. Roozbahani G. Alverson, E. Barberis, D. Baumgartel, A. Hortiangtham, B. Knapp, A. Massironi, D.M. Morse, D. Nash, T. Orimoto, R. Teixeira De Lima, D. Trocino, R.-J. Wang, D. Wood Northwestern University, Evanston, U.S.A. S. Bhattacharya, K.A. Hahn, A. Kubik, A. Kumar, J.F. Low, N. Mucia, N. Odell, B. Pollack, M.H. Schmitt, K. Sung, M. Trovato, M. Velasco University of Notre Dame, Notre Dame, U.S.A. N. Dev, M. Hildreth, K. Hurtado Anampa, C. Jessop, D.J. Karmgard, N. Kellams, K. Lannon, N. Marinelli, F. Meng, C. Mueller, Y. Musienko36, M. Planer, A. Reinsvold, R. Ruchti, G. Smith, S. Taroni, N. Valls, M. Wayne, M. Wolf, A. Woodard The Ohio State University, Columbus, U.S.A. J. Alimena, L. Antonelli, J. Brinson, B. Bylsma, L.S. Durkin, S. Flowers, B. Francis, A. Hart, C. Hill, R. Hughes, W. Ji, B. Liu, W. Luo, D. Puigh, B.L. Winer, H.W. Wulsin Princeton University, Princeton, U.S.A. S. Cooperstein, O. Driga, P. Elmer, J. Hardenbrook, P. Hebda, D. Lange, J. Luo, D. Marlow, T. Medvedeva, K. Mei, M. Mooney, J. Olsen, C. Palmer, P. Piroue, D. Stickland, C. Tully, A. Zuranski University of Puerto Rico, Mayaguez, U.S.A. Purdue University, West Lafayette, U.S.A. A. Barker, V.E. Barnes, S. Folgueras, L. Gutay, M.K. Jha, M. Jones, A.W. Jung, K. Jung, D.H. Miller, N. Neumeister, B.C. Radburn-Smith, X. Shi, J. Sun, A. Svyatkovskiy, F. Wang, W. Xie, L. Xu Purdue University Calumet, Hammond, U.S.A. N. Parashar, J. Stupak Rice University, Houston, U.S.A. A. Adair, B. Akgun, Z. Chen, K.M. Ecklund, F.J.M. Geurts, M. Guilbaud, W. Li, B. Michlin, M. Northup, B.P. Padley, R. Redjimi, J. Roberts, J. Rorie, Z. Tu, J. Zabel University of Rochester, Rochester, U.S.A. B. Betchart, A. Bodek, P. de Barbaro, R. Demina, Y.t. Duh, T. Ferbel, M. Galanti, A. Garcia-Bellido, J. Han, O. Hindrichs, A. Khukhunaishvili, K.H. Lo, P. Tan, M. Verzetti Rutgers, The State University of New Jersey, Piscataway, U.S.A. J.P. Chou, E. Contreras-Campana, Y. Gershtein, T.A. Gomez Espinosa, E. Halkiadakis, M. Heindl, D. Hidas, E. Hughes, S. Kaplan, R. Kunnawalkam Elayavalli, S. Kyriacou, A. Lath, K. Nash, H. Saka, S. Salur, S. Schnetzer, D. She eld, S. Somalwar, R. Stone, S. Thomas, P. Thomassen, M. Walker University of Tennessee, Knoxville, U.S.A. M. Foerster, J. Heideman, G. Riley, K. Rose, S. Spanier, K. Thapa O. Bouhali71, A. Celik, M. Dalchenko, M. De Mattia, A. Delgado, S. Dildick, R. Eusebi, J. Gilmore, T. Huang, E. Juska, T. Kamon72, R. Mueller, Y. Pakhotin, R. Patel, A. Perlo , L. Pernie, D. Rathjens, A. Rose, A. Safonov, A. Tatarinov, K.A. Ulmer Texas Tech University, Lubbock, U.S.A. N. Akchurin, C. Cowden, J. Damgov, C. Dragoiu, P.R. Dudero, J. Faulkner, S. Kunori, K. Lamichhane, S.W. Lee, T. Libeiro, S. Undleeb, I. Volobouev, Z. Wang Vanderbilt University, Nashville, U.S.A. A.G. Delannoy, S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, P. Sheldon, S. Tuo, J. Velkovska, Q. Xu University of Virginia, Charlottesville, U.S.A. M.W. Arenton, P. Barria, B. Cox, J. Goodell, R. Hirosky, A. Ledovskoy, H. Li, C. Neu, T. Sinthuprasith, X. Sun, Y. Wang, E. Wolfe, F. Xia Wayne State University, Detroit, U.S.A. C. Clarke, R. Harr, P.E. Karchin, P. Lamichhane, J. Sturdy University of Wisconsin - Madison, Madison, WI, U.S.A. D.A. Belknap, S. Dasu, L. Dodd, S. Duric, B. Gomber, M. Grothe, M. Herndon, A. Herve, P. Klabbers, A. Lanaro, A. Levine, K. Long, R. Loveless, I. Ojalvo, T. Perry, G.A. Pierro, G. Polese, T. Ruggles, A. Savin, A. Sharma, N. Smith, W.H. Smith, D. Taylor, N. Woods 1: Also at Vienna University of Technology, Vienna, Austria 2: Also at State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, 3: Also at Institut Pluridisciplinaire Hubert Curien, Universite de Strasbourg, Universite de Haute Alsace Mulhouse, CNRS/IN2P3, Strasbourg, France 4: Also at Universidade Estadual de Campinas, Campinas, Brazil 5: Also at Universidade Federal de Pelotas, Pelotas, Brazil 6: Also at Universite Libre de Bruxelles, Bruxelles, Belgium 7: Also at Deutsches Elektronen-Synchrotron, Hamburg, Germany 8: Also at Joint Institute for Nuclear Research, Dubna, Russia 9: Also at Cairo University, Cairo, Egypt 10: Also at Fayoum University, El-Fayoum, Egypt 11: Now at British University in Egypt, Cairo, Egypt 12: Now at Ain Shams University, Cairo, Egypt 13: Also at Universite de Haute Alsace, Mulhouse, France 14: Also at CERN, European Organization for Nuclear Research, Geneva, Switzerland 15: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, 16: Also at Tbilisi State University, Tbilisi, Georgia 17: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany 18: Also at University of Hamburg, Hamburg, Germany 20: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary 21: Also at MTA-ELTE Lendulet CMS Particle and Nuclear Physics Group, Eotvos Lorand 22: Also at University of Debrecen, Debrecen, Hungary 23: Also at Indian Institute of Science Education and Research, Bhopal, India 24: Also at Institute of Physics, Bhubaneswar, India 25: Also at University of Visva-Bharati, Santiniketan, India 26: Also at University of Ruhuna, Matara, Sri Lanka 27: Also at Isfahan University of Technology, Isfahan, Iran (MEPhI), Moscow, Russia 28: Also at University of Tehran, Department of Engineering Science, Tehran, Iran 29: Also at Plasma Physics Research Center, Science and Research Branch, Islamic Azad University, Tehran, Iran 30: Also at Universita degli Studi di Siena, Siena, Italy 31: Also at Purdue University, West Lafayette, U.S.A. 32: Also at International Islamic University of Malaysia, Kuala Lumpur, Malaysia 33: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia 34: Also at Consejo Nacional de Ciencia y Tecnolog a, Mexico city, Mexico 35: Also at Warsaw University of Technology, Institute of Electronic Systems, Warsaw, Poland 36: Also at Institute for Nuclear Research, Moscow, Russia 37: Now at National Research Nuclear University 'Moscow Engineering Physics Institute' 38: Also at Institute of Nuclear Physics of the Uzbekistan Academy of Sciences, Tashkent, 39: Also at St. Petersburg State Polytechnical University, St. Petersburg, Russia 40: Also at University of Florida, Gainesville, U.S.A. 41: Also at P.N. Lebedev Physical Institute, Moscow, Russia 42: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia 43: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia 44: Also at INFN Sezione di Roma; Universita di Roma, Roma, Italy 45: Also at Scuola Normale e Sezione dell'INFN, Pisa, Italy 46: Also at National and Kapodistrian University of Athens, Athens, Greece 47: Also at Riga Technical University, Riga, Latvia 48: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia 49: Also at Albert Einstein Center for Fundamental Physics, Bern, Switzerland 50: Also at Adiyaman University, Adiyaman, Turkey 51: Also at Mersin University, Mersin, Turkey 52: Also at Cag University, Mersin, Turkey 53: Also at Piri Reis University, Istanbul, Turkey 54: Also at Gaziosmanpasa University, Tokat, Turkey 55: Also at Ozyegin University, Istanbul, Turkey 56: Also at Izmir Institute of Technology, Izmir, Turkey 57: Also at Marmara University, Istanbul, Turkey 58: Also at Kafkas University, Kars, Turkey 59: Also at Istanbul Bilgi University, Istanbul, Turkey 60: Also at Yildiz Technical University, Istanbul, Turkey 61: Also at Hacettepe University, Ankara, Turkey 62: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom 64: Also at Instituto de Astrof sica de Canarias, La Laguna, Spain 65: Also at Utah Valley University, Orem, U.S.A. 66: Also at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, 67: Also at Facolta Ingegneria, Universita di Roma, Roma, Italy 68: Also at Argonne National Laboratory, Argonne, U.S.A. 69: Also at Erzincan University, Erzincan, Turkey 70: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey 71: Also at Texas A&M University at Qatar, Doha, Qatar 72: Also at Kyungpook National University, Daegu, Korea [1] J.D. 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V. Khachatryan, A. M. Sirunyan, A. Tumasyan, W. Adam. Decomposing transverse momentum balance contributions for quenched jets in PbPb collisions at \( \sqrt{s_{\mathrm{N}\;\mathrm{N}}}=2.76 \) TeV, Journal of High Energy Physics, 2016, 55, DOI: 10.1007/JHEP11(2016)055