Top-quark mass measurement in the all-hadronic \( t\overline{t} \) decay channel at \( \sqrt{s}=8 \) TeV with the ATLAS detector

Journal of High Energy Physics, Sep 2017

The top-quark mass is measured in the all-hadronic top-antitop quark decay channel using proton-proton collisions at a centre-of-mass energy of \( \sqrt{s}=8 \) TeV with the ATLAS detector at the CERN Large Hadron Collider. The data set used in the analysis corresponds to an integrated luminosity of 20.2 fb−1. The large multi-jet background is modelled using a data-driven method. The top-quark mass is obtained from template fits to the ratio of the three-jet to the dijet mass. The three-jet mass is obtained from the three jets assigned to the top quark decay. From these three jets the dijet mass is obtained using the two jets assigned to the W boson decay. The top-quark mass is measured to be 173.72 ± 0.55 (stat.) ± 1.01 (syst.) GeV.

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Top-quark mass measurement in the all-hadronic \( t\overline{t} \) decay channel at \( \sqrt{s}=8 \) TeV with the ATLAS detector

HJE 8 TeV with the ATLAS detector The top-quark mass is measured in the all-hadronic top-antitop quark decay ATLAS detector at the CERN Large Hadron Collider. The data set used in the analysis corresponds to an integrated luminosity of 20:2 fb 1 modelled using a data-driven method. The top-quark mass is obtained from template ts to the ratio of the three-jet to the dijet mass. The three-jet mass is obtained from the three jets assigned to the top quark decay. From these three jets the dijet mass is obtained using the two jets assigned to the W boson decay. The top-quark mass is measured to be Hadron-Hadron scattering (experiments); Top physics 1 Introduction 2 ATLAS detector 4 Event selection 5 tt reconstruction 3 Data and Monte Carlo simulation 6 Multi-jet background estimation 7 Top-quark mass determination 8 Method validation and template closure 9 Systematic uncertainties 9.1 9.2 9.3 Theory and modelling uncertainties Method-dependent uncertainties Calibration- and detector-related uncertainties 10 Measurement of mtop 11 Conclusion The ATLAS collaboration 1 Introduction Of all known fundamental particles, the top quark has the largest mass. Its existence was predicted in 1973 by Kobayashi and Maskawa [ 1 ], and it was not observed directly until 1995, by the CDF and D0 experiments at the Tevatron [ 2, 3 ]. Since 2010, top quarks have also been observed at the Large Hadron Collider (LHC) [4] at CERN. Due to the higher centre-of-mass energy, top quark production at the LHC is an order of magnitude larger than at the Tevatron. The large data sets of top-antitop quark (tt) pairs allow many precision studies and measurements of top quark properties. The Yukawa coupling of the top quark is predicted to be close to unity [ 5, 6 ], suggesting that it may play a special role in electroweak symmetry breaking. In the Standard Model (SM), the top quark dominantly contributes to the quantum corrections to the Higgs self coupling [ 7, 8 ]. Precise measurements of the top-quark mass (mtop) are therefore very important in probing the stability of the vacuum [ 9, 10 ], and contribute to searches for signs of physics beyond the SM. { 1 { Today the most precise individual measurement of mtop is in the single-lepton decay channel of top-antitop quark pairs, where one top quark decays into a b-quark, a charged lepton and a neutrino and the other top quark decays into a b-quark and two u/d/c/s-quarks, performed by the CMS Collaboration, yielding a value of mtop = 172:35 0:16 (stat.) The most precise measurement of mtop in the dileptonic tt decay channel, where each of the top quarks decays into a bquark, a charged lepton and its neutrino, is from the ATLAS Collaboration, yielding a value of mtop = 172:99 available in refs. [13{15]. 0:41 (stat.) 0:74 (syst.) GeV [12]. Further mtop results are The top-quark mass measurement in the all-hadronic tt channel takes advantage of the largest branching ratio (46%) among the possible top quark decay channels [16]. The all-hadronic channel involves six jets at leading order, two originating from b-quarks and four originating from the two W boson hadronic decays. It is a challenging measurement because of the large multi-jet background arising from various quantum chromodynamics (QCD) processes, which can exceed the tt production by several orders of magnitude. However, all-hadronic tt events pro t from having no neutrinos among the decay products, so that all four-momenta can be measured directly. The multi-jet background for the allhadronic tt channel, while large, leads to di erent systematic uncertainties than in the case of the single- and dileptonic tt channels. Thus, all-hadronic analyses o er an opportunity to cross-check top-quark mass measurements performed in the other channels. The most recent measurements of mtop in the all-hadronic channel were performed by the CMS Collaboration with mtop = 172.32 Collaboration with mtop = 175:1 0.25 (stat.) 0:59 (syst.) GeV [11], and the ATLAS 1:4 (stat.) 1:2 (syst.) GeV [17]. This paper presents a top-quark mass measurement in the tt all-hadronic channel using similarly to a previous measurement at p data collected by the ATLAS experiment in 2012. The mtop measurement is obtained from template ts to the distribution of the ratio of three-jet to dijet masses (R3/2 = mjjj =mjj ), s = 7 TeV [17]. The three-jet mass is obtained from the three jets assigned to the top quark decay. From the selected three jets the dijet mass is obtained using the two jets assigned to the W boson decay. The jet assignment is accomplished by using a 2 t to the tt system, so there are two values of R3/2 measured in each event. The observable R3/2 employed in this analysis achieves a partial cancellation of systematic e ects common to the masses of the reconstructed top quark and associated W boson, notably the signi cant uncertainty on the jet energy scale. Datadriven techniques are used to estimate the contribution from multi-jet background events. Data events are divided into several disjoint regions using two uncorrelated observables. The region containing the largest relative fraction of tt events is labeled the signal region. The background is estimated from the other regions, which determine the shape of the background distribution in the signal region. The paper is organised as follows. After a brief description of the ATLAS detector in section 2, the data and Monte Carlo (MC) samples used in the analysis are described in section 3. The analysis event selection is further detailed in section 4. Section 5 describes the method used to select the candidate four-momenta that comprise the reconstructed tt system. The estimation of the multi-jet background is detailed in section 6. The method { 2 { used to measure the top-quark mass and its uncertainties are reported in sections 7, 8, and 9. The results of the measurement are presented in section 10, and the analysis is summarised in section 11. 2 ATLAS detector The ATLAS detector [18] is a multi-purpose particle physics experiment with a forwardbackward symmetric cylindrical geometry and near 4 coverage in solid angle.1 The inner tracking detector (ID) covers the pseudorapidity range j j < 2:5, and consists of a silicon pixel detector, a silicon microstrip detector, and, for j j < 2:0, a transition radiation tracker. The ID is surrounded by a thin superconducting solenoid providing a 2 T magnetic eld. A high-granularity lead/liquid-argon (LAr) sampling electromagnetic calorimeter covers the region j j < 3:2. A steel/scintillator-tile calorimeter provides hadronic coverage in the range j j < 1:7. LAr technology is also used for the hadronic calorimeters in the endcap region 1:5 < j j < 3:2 and for electromagnetic and hadronic measurements in the forward region up to j j = 4:9. The muon spectrometer surrounds the calorimeters. It consists of three large air-core superconducting toroid systems, precision tracking chambers providing accurate muon tracking for j j < 2:7, and additional detectors for triggering in the region j j < 2:4. 3 Data and Monte Carlo simulation This analysis is performed using the proton-proton (pp) collision data set at a centre-of-mass energy of p s = 8 TeV collected with the ATLAS detector at the LHC. The data correspond to an integrated luminosity of 20:2 fb 1. Samples of simulated MC events are used to optimise the analysis, to study the detector response and the e ciency to reconstruct tt events, to build signal template distributions used for tting the top-quark mass, and to estimate systematic uncertainties. Most of the MC samples used in the analysis are based on a full simulation of the ATLAS detector [19] obtained using GEANT4 [20]. Some of the systematic uncertainties are studied using alternative tt samples processed through a faster ATLAS simulation (AFII) using parameterised showers in the calorimeters [21]. Additional simulated pp collisions generated with Pythia [ 22 ] are overlaid to model the e ects of additional collisions in the same and nearby bunch crossings (pile-up). All simulated events are processed using the same reconstruction algorithms and analysis chain as used for the data. The nominal tt simulation sample is generated using the next-to-leading-order (NLO) MC program POWHEG-BOX [23{25] with the NLO parton distribution function (PDF) set CT10 [ 26, 27 ], interfaced to Pythia 6.427 [28] with a set of tuned parameters called 1The coordinate system used to describe the ATLAS detector is brie y summarised here. The nominal interaction point is de ned as the origin of the coordinate system, while the beam direction de nes the erated events, and is used as the nominal signal sample. The hdamp parameter [30], which regulates the high-pT radiation in POWHEG-BOX, is set to the same mtop value as used in each of the generated POWHEG-BOX samples. All the simulated samples used to estimate systematic uncertainties are further described in section 9. All MC samples are normalised using the predicted top-antitop quark pair cross-section s = 8 TeV. For mtop = 172:5 GeV, the next-to-next-to-leading-order cross-section of tt = 253+1135 pb is calculated using the program Top++2.0 [31], which includes resummation of next-to-next-to-leading logarithmic soft gluon terms. 4 Event selection Events in this analysis are selected by a trigger that requires at least ve jets with pT > 55 GeV. Only events with a well-reconstructed primary vertex formed by at least ve tracks with pT > 400 MeV are considered for the analysis. Events with isolated electrons (muons) with ET > 25 GeV (pT > 20 GeV) and reconstructed in the central region of the detector within j j < 2:5 are rejected. Both lepton types are identi ed using the tight working points as speci ed in refs. [32, 33]. Jets (j) are reconstructed using the anti-kt algorithm with radius parameter R = 0:4 [34] employing topological clusters [35] in the calorimeter. These jets are calibrated to the hadronic energy scale as described in refs. [36{38]. The four-vector of the highest-energy muon ( ) from among those matched within R(j; ) < 0:3 to a reconstructed jet, is added to the reconstructed jet four-vector. This is done to compensate for the energy losses in the calorimeter arising from semimuonic quark decays. In simulation this correction slightly improves both the jet energy response and resolution across the full range of jet energies. To ensure that the selected events are in the plateau region of the trigger e ciency curve where the trigger e ciency in data is greater than 90%, at least ve of the reconstructed central jets (within j j < 2:5) are required to have pT > 60 GeV. Any additional jet is required to have pT > 25 GeV and j j < 2:5. All selected jets in an event must be isolated; any pairing of two jets (ji and jk) reconstructed with the above criteria are required to not overlap within R(ji; jk) < 0:6. Events with jets failing this isolation requirement are rejected. Events containing neutrinos are removed by requiring ETmiss < 60 GeV. The ETmiss in an event is computed as the sum of a number of di erent terms [39, 40]. Muons, electrons and jets are accounted for using the appropriate calibrations for each object. For each term considered, the missing transverse momentum is calculated as the negative sum of the calibrated reconstructed objects, projected onto the x and y directions. For the nal selection, events are kept if at least two of the six leading transverse momentum jets are identi ed as originating from a b-quark. Such jets are said to be b-tagged. A neural network trained on decay vertex properties [41] is used to identify these b-tagged jets. Because of the large number of c-quarks originating from the W boson { 4 { Cut Initial NPV>4 tracks & no isolated e/ Trigger: 5 jets with pT > 55 GeV & 6 good jets No 2 good jets (ji; jk) within R(ji; jk) < 0:6 5 good jets with pT > 60 GeV ETmiss < 60 GeV (bi; bj ) > 1:5 2 < 11 Nbtag h 2 (b; W )i < 2 Event yields (thousands) Data tt all-hadronic (MC) uncertainty). The tt contribution is after scaling to the theoretical cross-section and integrated luminosity. NPV>4 tracks is the number of primary vertices with > 4 tracks. Good jets have pT > 25 GeV and j j < 2:5. decays in this analysis (on average one c-quark per tt event) a b-tagger trained to reject u/d/s-jets but also a large fraction of c-jets is used. Events with fewer than two b-tagged jets are used for the background estimate described in section 6. The chosen working point for the b-tagging neural network has an identi cation e ciency of about 57% [42] for jets from b-quarks, with a rejection factor of about 330 for jets arising from u/d/s-quarks, and a factor of about 13 for jets arising from c-quarks. In each event the two jets with leading b-tag weights (bi and bj ) are required to satisfy (bi; bj ) > 1:5. The quantities bi and bj represent here the 4-vectors of the i-th and j-th jet. This cut is very powerful in rejecting combinatorial background events; most of these are true tt events where the incorrect jets are associated with the top quark. Finally, a cut is applied based on the azimuthal angle between b-jets and their associated W boson candidate: the average of the two angular separations for each event is required to satisfy h (b; W )i < 2. Here the b, and the W are the 4-vectors of a b-jet and a W , identi ed by means of the three-jet combination that best ts the tt event hypothesis described in section 5. This cut rejects a large fraction of events from the multi-jet and combinatorial backgrounds, as well as events from non-all-hadronic tt decays. Events failing this nal selection cut are, however retained for the purpose of modelling the multi-jet background, as detailed in section 6. 2 cut listed in table 1 is described in section 5. The number of b-tagged jets (Nbtag ) and h (b; W )i are the two observables used for the data-driven multi-jet background estimation, further detailed in section 6. { 5 { correctly reconstructed top quarks relative to the number of the sum of both correctly and incorrectly reconstructed top quarks. It is evaluated in simulation, and based on the matching of reconstructed jets to truth-record quarks from the top quark decays. 5 tt reconstruction In each event the tt nal state is reconstructed using all the jets from the all-hadronic tt event, a minimum- 2 approach is adopted, with the 2 de ned as: decay chain: tt ! bW bW ! b1j1j2 b2j3j4. To determine the top-quark mass in each tt Here, two of the reconstructed jets are associated with the bottom-type quarks produced directly from the top quark and antitop quark decays (b1 and b2), the other four jets are assumed to be u/d/c/s-quark jets from the W boson hadronic decay (ji, where i = 1; : : : ; 4), and mbjj = mb1j1j2 mb2j3j4 . This method considers all possible permutations of the six or more reconstructed jets in each event. The permutation resulting in the lowest 2 value is kept. A low 2 value indicates a permutation of jets consistent with the tt hypothesis. No explicit b-tagging information is used in eq. (5.1). In each combination the reconstructed masses of the two hadronically decaying W bosons (mj1 j2 and mj3 j4 ) in data are compared to the mean of the mass distribution of correctly reconstructed W bosons in simulated signal MC events (mMWC). The correct reconstruction of the top quarks and the W bosons in a simulated event is achieved by matching parton-level particles to the event's jets. The widths ( mMWC and used in the denominators of eq. (5.1) are obtained from ts to a single Gaussian funcmbjj ) tion to the mass distributions of the correctly reconstructed top quarks and W bosons: mbjj = 21:60 0:16 (stat.) GeV and mMWC = 7:89 0:05 (stat.) GeV. The mMWC mean value used in eq. (5.1) is determined to be 81:18 0:04 (stat.) GeV. To reduce the multi-jet background in the analysis and to eliminate events where the top quarks and the W bosons in an event are not reconstructed correctly, a minimum 2 < 11 is required. 6 Multi-jet background estimation The available MC generators for multi-jet production include only leading-order theory calculations for nal states with up to six partons. Therefore, the dominant multi-jet background in this analysis is determined directly from the data. Two largely uncorrelated variables are used to divide the data events into four di erent regions, such that the background is determined in the control regions and extrapolated to the signal region. The two chosen observables are the Nbtag in an event, and the h (b; W )i variable, both described in section 4. These have a linear correlation measured in data of = 0:038. The value of Nbtag in each event is determined from the leading six jets ordered by pT. { 6 { ABCD region and de nition Estimated signal fraction number of observed data events in each region. The four regions, labelled ABCD, are identi ed by de ning two bins in the number of b-tagged jets, Nbtag < 2, Nbtag h (b; W )i < 2:0, h 2, and two ranges of the h (b; W )i variable, 2:0, as detailed in table 2. The R3/2 distributions are studied for each of the de ned regions. Region D represents the signal region (SR), and contains the largest fraction of tt events (34:05%). Regions A, B, and C are the control regions (CR), and are dominated by multi-jet background events. Table 2 summarises the expected fractions of signal events in each of the four regions. Each signal fraction is estimated by comparing the total predicted number of signal events from tt simulation to the number of observed data events in each region. To obtain an unbiased estimate of the number of background events in each considered CR, the signal contamination is removed using simulated tt events with mtop = 172:5 GeV. The method validation and the template closure described in section 8 show that the mtop dependence of this signal subtraction is signi cantly smaller than other uncertainties on the method, and is ignored. The estimated background in a given bin i of R3/2 for SR D (NbSaRckDground;i) is given by: NbCaRckCground NbCaRckAground ! NbSaRckDground;i = NbCaRckBground;i : (6.1) This corresponds to the background in a given bin i of the R3/2 spectrum of CR B (NbCaRckBground;i), estimated after subtraction of the signal contamination, and scaled by the ratio of the number of events in control regions C (NbCaRckCground) and A (NbCaRckAground), also after signal removal. The signal contamination present in CR C comes from improperly reconstructed tt events which form a smoothly varying distribution in R3/2. This signal contribution in CR C is not relevant in the analysis, as this region only a ects the normalisation of the distribution obtained for the multi-jet background, which is not used in the t for mtop described in section 7. Figure 1 shows the distributions of the masses of the W boson (mjj ) and top quark (mjjj ) after applying the event selection, the 2 approach de ned in eq. (5.1), and using the data-driven multi-jet background method. In the gure, the reconstruction using MC events is said to be correct for one (or both) top quark(s) if each of the three jets (j) { 7 { e icde 1 r P /a0.5 60 t a 3 / invariant mass, mjjj, for top quark candidates (right) in data compared to the sum of tt simulation and multi-jet background. The ratio comparing data to prediction is shown below each distribution. The hatched bands re ect the sum of the statistical and systematic errors added in quadrature. The tt simulation corresponds to mtop = 172:5 GeV. selected by the reconstruction algorithm matches to each of the three quarks (q) within a R(j; q) < 0:3, modulo the interchange of the two jets assigned to the hadronically decaying W boson. If at least one of the jets selected by the algorithm is not one of the three jets matched to the quarks, the top quark reconstruction is classi ed as incorrect. Finally, cases where at least one quark is not matched uniquely to a reconstructed jet are classi ed as non-matched. The R3/2 distribution obtained after using the data-driven multi-jet background estimation methods to determine the shape and normalisation is shown in gure 2. In general, good agreement between data and prediction is observed in all the distributions. 7 Top-quark mass determination To extract a measurement of the top-quark mass, a template method with a binned minimum- 2 approach is employed. For each tt event, two R3/2 values are obtained, one for each top-quark mass measurement. To properly correct for the linear correlation between nal 2 t described later in this section is scaled up by a factor p 1 + the two R3/2 values in each event, the statistical uncertainty of mtop returned from the = 1:26, where = 0:59 is the correlation factor as obtained from data. Signal and background templates binned in R3/2 are created using the simulated tt events described in section 3, and the data-driven background distribution. The top quark contribution is parameterised by a probability distribution function (pdf) which is the sum of a Novosibirsk function [43] and a Landau function [44]. These describe, respectively, the signal and the combinatorial background. e i E 800 600 400 200 the 2 t is applied. The ratio comparing data to prediction is shown below the gure. The hatched bands re ect the sum of the statistical and systematic errors added in quadrature. The tt simulation corresponds to mtop = 172:5 GeV. the R3/2 distributions from the ve tt simulation samples with di ering mtop are tted separately to determine the six parameters for each template mass. The MC simulation shows that each of these parameters depends linearly on the input mtop. In the next step, the parameters are tted to obtain the o sets and slopes of the linear mtop dependencies. These values are then used as inputs to a combined, simultaneous t to all ve R3/2 distributions. In total 12 parameters are derived by the combined t to determine the pdf. Figure 3 shows the R3/2 distributions obtained using the tt MC samples based on the full simulation of the ATLAS detector and generated at three top-quark mass points: 167:5, 172:5, and 175 GeV. Results from the combined, simultaneous t to all ve R3/2 distributions are superimposed. Shown are the functions describing the signal and combinatorial background, respectively, and their sum. The Novosibirsk mean and width parameters o er the strongest sensitivity to mtop. Template distributions obtained simultaneously for three separate input values of mtop (167:5, 172:5, and 177:5 GeV), highlighting the R3/2 shape sensitivity to mtop, are shown in gure 4. The multi-jet background template distribution obtained from the output of the datadriven method described in section 6 can be parameterised in a similar fashion. In this case the sum of a Gaussian function and a Landau function was found to be a suitable choice for the functional form. The background pdf requires ve parameters. As a nal step in the parameterisation, in order to take properly into account the uncertainties and the correlations between the various signal and background shape parameters, a more generalised version of the 2 function is used. The nal 2 t, which uses { 9 { / e i Novosibirsk Landau Total Fit (Global) mtgoepn = 172.5 GeV e i tr nE8000 /.010000 ATLAS Simulation 0 167:5, 172:5, and 177:5 GeV, respectively. Results from the combined, simultaneous t to all ve R3/2 distributions are superimposed (black line with blue lled area). For each distribution it consists of a Novosibirsk function (red line) describing the signal part and a Landau function (green dashed-line) describing the combinatorial background part. Their parameters are assumed to depend linearly on mtop. The 2 per degree of freedom obtained for each of the three template distribution corresponds to 1:22, 3:98, and 1:96 respectively. The plot under each distribution shows the residuals obtained from calculating the di erence between the combined t and the simulated R3/2 distribution normalised to the statistical uncertainty for each bin individually. matrix algebra to include non-diagonal covariance matrices, has the form: 2 = X k) [Vdata + Vsignal(mtop; Fbkgd) + Vbkgd(Fbkgd)]ik1: (7.1) Here mtop and Fbkgd are the two parameters which are left to oat. The shape of the tted multi-jet background parameterisation is assumed to be independent of mtop 0.6 0.4 0.2 0 V1.5 e G .52 1 7 R (167:5, 172:5, and 177:5 GeV), highlighting the sensitivity of the R3/2 shape to mtop. The plot under the distribution shows the ratio of mtop at 167:5, and 177:5 GeV to mtop at 172:5 GeV. while the normalisation, controlled by a background fraction parameter, Fbkgd, is obtained by tting the data distribution. The Fbkgd is de ned within the t range of the R3/2 distribution: 1:5 R3/2 < 3:5. The term ni in eq. (7.1) corresponds to the number of entries in bin i in the R3/2 data distribution, whereas i corresponds to the estimated total number of signal and background entries. The term Vdata is the Nbin Nbin diagonal data covariance matrix with Vik = ikni, which accounts for the statistical uncertainty in each bin i. Similarly, Vsignal and Vbkgd are Nbin Nbin non-diagonal covariance matrices which account for the signal and background shape parameterisation uncertainties and their correlations. In the R3/2 distribution which has a total number of data entries Nd, and a given bin width wbin, the number of estimated entries in bin i, i, is given by: i (mtop; Fbkgd) = wbinNd (1 Fbkgd) PS R3/2;ijmtop + FbkgdPB R3/2;i (7.2) where PS and PB are the probability density functions for the signal and background, respectively. 8 Method validation and template closure To validate the method employed to extract mtop from the R3/2 data distribution and to check for any potential bias, a series of pseudo experiments are performed. For each of the ve simulated mtop samples a total of 2500 pseudo experiments generating a distribution of the R3/2 variable are produced.2 Two scenarios are investigated: in the rst one, events are drawn randomly from template R3/2 distributions; in the second scenario, events are drawn directly from the signal and background shapes. In each scenario the nominal values 2This value of 2500 is also used when performing pseudo experiments to estimate the systematic Fit Δ mtop = 0.08 ± 0.06 GeV χ2/ndf = 4.00/4 = 1.00 Pseudo Data Drawn from: Template Histograms Associated Fit Template Parameterisations 168 170 172 174 176 178 HJEP09(217)8 Generator mtop [GeV] mtgoepn , based on the results of a t to a single Gaussian function. The black markers correspond to cases where the pseudo events were drawn from the R3/2 histograms, and the open marker points where pseudo events were drawn from the parameterisations. The solid blue line corresponds to a polynomial t to the ve black markers and their corrected uncertainties. of all signal and background shape parameters are used, and only two parameter values, mtop and Fbkgd, are returned from the minimisation procedure. For all ve top-quark mass MC samples, the same multi-jet background distribution is used for drawing pseudo events. The value of mtop obtained from each pseudo experiment (mtmoepas) is used to ll a distribution of the di erence between these values and the values mtgoepn used for event generation. This distribution is then tted with a Gaussian function, giving estimators for the Gaussian mean and width parameters, each with their respective uncertainties. The uncertainty in the tted mean is corrected for the oversampling that is induced by drawing from template distributions produced using a nite number of MC events [45]. The tted mean mtmoepas mtgoepn , referred to as the \di erence mean", is shown in gure 5. Fitting ve top-quark mass samples with a linear function gives an 0:06 GeV. The treatment of this small bias is further the di erence mean for the mtgoepn-independent bias of 0:08 discussed in section 9.2. pseudo experiment is de ned as: Pull (z-score) distributions are constructed in an analogous way, where the pull in each Pull = mtmoepas mtgoepn = mtop ; (8.1) where mtop is the statistical uncertainty of the mtop parameter obtained from the t of the pseudo experiment. The correction that takes into account the correlation between two R3/2 values in each event, described in section 7, is not applied here, as the values of R3/2 drawn for pseudo experiments are uncorrelated. The pull distribution for an unbiased measurement has a mean of zero and a standard deviation of unity. A tted pull mean value of 0:19 0:13 and a tted pull width of 0:98 0:01 are obtained, which shows that the uncertainty determination is unbiased. Systematic uncertainties This section outlines the various sources of systematic uncertainty in mtop which are summarised in table 3. All sources are treated as uncorrelated. Individual contributions are symmetrised and the total uncertainty is taken as the sum in quadrature of all contributions. The majority of the systematic uncertainties are assessed by varying the tt MC sample to re ect the uncertainty from each of these sources. Pseudo experiments are constructed from the varied sample, which are then passed through the analysis chain; the change in the result relative to that obtained from the nominal MC sample is evaluated. Exceptions HJEP09(217)8 to this are described in the following subsections. To facilitate a combination with other results, each systematic uncertainty is assigned a statistical uncertainty, taking into account the statistical correlation of the considered samples. Following ref. [46], the systematic uncertainties listed in table 3 are calculated independently of the statistical uncertainties of the values. In what follows, each source of systematic uncertainty is brie y described. These are broken down into three categories. The rst category, theory and modelling uncertainties, is associated with the simulation of the signal events. The second set of uncertainties is related to the analysis method. These involve uncertainties due to the way that the analysis was performed, including the choice of a template method, the background modelling, and the nal mtop extraction procedure. Finally a third category, calibration- and detector-related uncertainties involves uncertainties coming from the standard calibrations of physics objects. 9.1 Theory and modelling uncertainties Monte Carlo generator. In order to assess the impact on the mtop measurement due to the choice of MC generator, the results of pseudo experiments using two di erent AFII simulated samples are compared: one sample produced using POWHEG-BOX as the MC generator and a second sample using MC@NLO [47]. Both samples use Herwig 6.520.2 [48] with the AUET2 tune to model the parton shower, hadronisation and underlying event, in contrast with the nominal signal MC where Pythia 6.427 is used. The absolute di erence of 0:18 GeV between the resulting average mtop parameter returned from the ts is accounted for as the uncertainty. Hadronisation modelling. To quantify the expected change in the measured mtop value due to a di erent choice of hadronisation model, pseudo experiments are performed for two independent MC samples both employing POWHEG-BOX AFII simulation to generate the all-hadronic tt events but di ering in their choice of hadronisation model. In the rst case, Pythia 6.427 [ 28 ] is used to model the parton shower, hadronisation and underlying event with the Perugia 2012 tunes [ 29 ], while in the second case, Herwig 6.520.2 with the AUET2 tune [48] is used. The absolute di erence of 0:64 GeV between the average mtop values obtained in the two cases is accounted for as the systematic uncertainty. Source of uncertainty Monte Carlo generator Hadronisation modelling Parton distribution functions Initial/ nal-state radiation Underlying event Colour reconnection Bias in template method Signal and bkgd parameterisation Non all-hadronic tt contribution ABCD method vs. ABCDEF method Trigger e ciency Lepton/ETmiss calibration Overall avour-tagging Jet energy scale (JES) b-jet energy scale (bJES) Jet energy resolution Jet vertex fraction Total systematic uncertainty Total statistical uncertainty Total uncertainty 0:18 0:64 0:04 0:10 0:13 0:12 0:08 0:02 0:10 0:60 0:34 0:10 0:03 0:21 0:15 0:00 0:28 0:16 0:16 0:01 0:01 0:00 0:05 0:02 0:04 0:01 0:06 0:09 0:06 0:16 1:01 0:55 1:15 Totals are evaluated by means of a sum in quadrature and assuming that all contributions are uncorrelated. The uncertainties are subdivided into three categories: theory and modelling uncertainties, method-related uncertainties, and calibration- or detectorrelated uncertainties, as described in the text. Adjacent to each of the quoted systematic variations in mtop is its associated statistical uncertainty. The ABCDEF method is further described in section 9.2 and in ref. [17]. The quoted statistical uncertainty is corrected for the correlation between the two R3/2 measurements of each event. Parton distribution functions A variety of PDF sets are investigated in order to assess the impact of the choice of CTEQ10 [ 26, 27 ], the default PDF set used in the nominal measurement. There are a total of 53 distinct sets for the CTEQ PDFs. In addition there are 101 distinct NNPDF23 [49] PDF sets and 41 distinct MSTW2008 [ 50, 51 ] PDF sets to consider, giving a total of 195 distinct sets to compare. Simulated POWHEGBOX+Herwig [23{25, 48] events are used for the comparison. The individual PDF uncertainty contributions are evaluated according to set-dependent procedures as described in ref. [52] for CT10 [ 26, 27 ], for MSTW [49], and for NNPDF [ 50, 51 ]. To determine the nal systematic uncertainty, the quantities mtop mtop are calculated for each of the three sets, where mtop is the measured value from the central reference sample of the corresponding PDF set, and mtop is the associated set-dependent uncertainty. Half of the di erence between the largest and the smallest of these values is quoted as the symmetrised nal uncertainty, and is 0:04 GeV. Initial-state and nal-state radiation. Varying the amount of initial- and nal-state radiation (ISR and FSR) can have an impact on the number of reconstructed jets, which in turn can a ect the overall measurement of the top-quark mass. In order to quantify the sensitivity of the measurement to ISR/FSR, two alternative POWHEG-BOX plus Pythia 6.427 [ 28 ] AFII samples are used. The rst sample has the hdamp parameter [30] set to 2mtop, the factorisation and renormalisation scale3 decreased by a factor of 0:5 and uses the Perugia 2012 radHi tune [ 29 ], giving more parton shower radiation. The second sample has the Perugia 2012 radLo tune, hdamp = mtop and the factorisation and renormalisation scale increased by a factor of 2, giving less parton shower radiation. Half of the absolute di erence between the measured mtop values from the pseudo experiments is quoted as the corresponding systematic uncertainty and is 0:10 GeV. Underlying event. Additional semi-hard multiple parton interactions (MPI) present in the hard-scattering can change the kinematics of the underlying event. The number of such additional semi-hard MPI is a Perugia 2012 tunable parameter [ 29 ] in the Pythia 6.427 generator [ 28 ]. Simulated tt AFII events were produced with an increased number of semi-hard MPI (Perugia 2012 mpiHi) in order to assess the potential impact on the nal measurement. The absolute di erence between the results of these pseudo experiments and the one using the nominal simulated AFII sample is quoted as the systematic uncertainty and is 0:13 GeV. Colour reconnection. When simulating AFII signal events using Pythia 6.427 [ 28 ] for the parton shower and hadronisation modelling, there is a tunable parameter associated with the colour reconnection strength due to the colour ow along parton lines in the strong-interaction hard-scattering process. An alternative AFII tt sample uses the Pythia Perugia 2012 loCR tune [ 29 ], which corresponds to reduced colour reconnection strength. The absolute di erence of 0:12 GeV between the results of these pseudo experiments and the average mtop value obtained using the nominal Pythia 6.427 tt events is quoted as the systematic uncertainty. 9.2 Method-dependent uncertainties Bias in template method. Based on the results of the closure tests, a small bias is observed in the extracted top-quark mass. By drawing pseudo events from the parameterisations an o set of about 80 MeV in the mass di erence (mtmoepas mtgoepn) is present (see gure 5). The o set does not exhibit a dependence on the generator's mtop value. For this reason the parameter value returned from a t to the average bias from pseudo experiments across mtgoepn is subtracted from the nal mtop value as measured in data. The nal value of mtop quoted in this analysis includes this subtraction. The uncertainty in this tted o set is then quoted as the systematic uncertainty of 0:06 GeV associated with the template method's non-closure. 3The default POWHEG-BOX factorisation and renormalisation scales are set to qmt2op + p2T. Signal and background parameterisation. To extract mtop as described in section 7, the uncertainties in the shape parameters of the R3/2 observable for the signal contributions are included in the Nbin Nbin covariance matrices which enter into the 2 minimisation used to extract mtop (see eq. (7.1)). Omitting these contributions would yield a simpli ed de nition of the 2 variable: which can be recognised as the standard de nition of the 2 variable for a least-squares t assuming only a diagonal covariance matrix. The t to the data distribution is repeated using this simpli ed de nition of the 2 variable. This results in a slightly modi ed re turned value of the mtop parameter and a smaller statistical uncertainty. The di erence in quadrature of 0:09 GeV between the nal statistical uncertainty returned from the original minimisation and this modi ed value is quoted as the uncertainty in the signal and background parameterisation. Inclusion of non-all-hadronic tt background. A number of event selection requirements, such as the lepton veto and the requirement that ETmiss < 60 GeV, result in a large suppression of background contributions arising from non-all-hadronic tt events. The estimated fractional contribution from such events in the nal signal region is below 3%, and is not considered in the nominal case. Pseudo experiments are performed by drawing events from the nominal signal distribution but from a modi ed background, now consisting of QCD events and tt events with at least one leptonic W boson decay. The absolute di erence of 0:06 GeV between the average mtop value obtained in this way and that from the nominal case is quoted as a systematic uncertainty. Variation in the number of control regions. A variation of the background estimation procedure is considered in which six distinct regions, rather than four, are de ned to estimate the multi-jet background. This is done by allowing three di erent values of Nbtag : 0, 1, or 2. Events can then be separated into the six di ering regions as in the nominal analysis. As in the nominal case the number of b-tagged jets in an event considers only the leading six jets, ordered by pT. The values of the second ABCD variable, h (b; W )i, are unchanged from the nominal case. One reason for considering this alternative is that the inclusion of a larger number of control regions could potentially provide sensitivity to di erent physics processes. Additionally, the systematic uncertainty contribution arising from uncertainties in the b-tagging scale factors could di er between these methods. With a total of six regions shown in table 4 the background estimation technique remains similar to that using four regions. The nal SR is labelled F. The new region D, together with region B, is now used to predict the shape of the multi-jet background in SR F, whereas CR A, C, and E set the multi-jet background normalisation [17]. Pseudo experiments are performed by drawing background events from the modi ed multi-jet distribution in the nal signal region. The absolute di erence of 0:16 GeV between this and the nominal case is quoted as the systematic uncertainty. Nbtag h Calibration- and detector-related uncertainties Trigger e ciency. The trigger e ciency obtained using simulated signal events [23{ 25, 28, 29] is compared to an equivalent distribution obtained using data, which results in a small observed discrepancy. For the 5th jet pT > 68 GeV the e ciencies for both simulation and data agree and are larger than 99%. In the 5th jet pT region between 60 GeV and 68 GeV the signal simulation (data) e ciency is larger than 97% (90%) and rising with pT. The data here are expected to consist primarily of multi-jet events. It is expected that some true kinematic di erences give rise to the di erence observed between the data and MC trigger e ciencies. In order to obtain a conservative uncertainty, it is assumed that the di erence represents a mis-modelling of the data by the trigger simulation. The simulated events are assigned a pT-dependent trigger e ciency correction such that the corrected MC and data trigger e ciencies agree. Pseudo experiments are performed by drawing signal events from the modi ed R3/2 distribution with the trigger SFs applied, and the 0:08 GeV absolute di erence from the nominal case is quoted as a conservative uncertainty on mtop due to the trigger e ciency. Pile-up reweighting scale. The distribution of the average number of interactions per bunch crossing, denoted by h i, is known to di er between data and simulation. Simulated events are reweighted so that h i matches the value observed in data. In order to assess the impact on the nal result, pseudo experiments are performed in which the reweighting scale is shifted up and down according to its uncertainty, and the t procedure is repeated. A negligible maximum change of 0:01 GeV in mtop is found as the symmetrised up/down uncertainty. Lepton and ETmiss soft-term calibrations. Uncertainties in the calibration scales and in the resolutions of the lepton (e= ) four-vector objects [33, 53, 54] can potentially lead to small di erences in the event selection or the jet-quark assignment in the top reconstruction algorithm. Similarly, small uncertainties in mtop can be expected due to the uncertainties in the scale and resolution of the ETmiss soft term [39, 40]. The ETmiss soft term is varied according to these uncertainties and pseudo experiments are performed with the modi ed MC events. In the case of the muon-related uncertainties, Gaussian smearing is performed to assess the impact on the nal result. The maximum absolute deviation from the reference mtop value is taken as the uncertainty in each case, and these are added in quadrature to obtain a single value of 0:02 GeV for all lepton- and ETmiss-related scale and resolution di erences between tagging e ciencies and mis-tag rates evaluated in data and simulation are removed by applying scale factor (SF) weights to the simulated events. The uncertainties in the avour-tagging SFs are calculated separately for the b-tagging SFs, the c= -tagging SFs, and the overall mis-tag SFs [42]. The uncertainties in the avour-tagging SFs are split into various components. The full covariance matrix between the various bins of jet transverse momentum is built and decomposed into eigenvectors. Each eigenvector corresponds to an independent source of uncertainty, each with an upward and a downward uctuation, and the resulting total systematic uncertainty is 0:10 GeV. Jet energy scale. The di erent contributions to the total JES uncertainty are estimated individually as described in ref. [36]. For each component the resulting di erences from the up and down variations, corresponding to one-standard-deviation relative to the nominal JES, are quoted separately. The total uncertainty for each contribution is taken as half of the absolute di erence between the up and down variation. In case both the up and down variations result in a change in the parameter in the same direction, the largest absolute di erence (either from the up or down variation) is taken as the symmetrised uncertainty. The total JES uncertainty is the sum in quadrature of all subcontributions, and is 0:60 GeV. This includes all but the b-jet energy scale contribution, which is quoted separately and discussed below. b-jet energy scale. The reconstructed top quark four-momenta are sensitive to the energy scale of jets initiated by b-quarks, particularly as a result of choices in the fragmentation modelling. Based on the uncertainties associated with the b-jet energy scale [55], a similar up/down variation procedure is performed using pseudo experiments and the quoted systematic uncertainty of 0:34 GeV is half the absolute di erence between the two variations. Jet energy resolution. An eigenvector decomposition strategy similar to that followed for the JES and the avour-tagging systematic uncertainties is used for the determination of jet energy resolution (JER) systematic uncertainties [56]. The nal quoted JER systematic uncertainty is 0:10 GeV. Jet reconstruction e ciency. A small di erence between the jet reconstruction efciencies measured in data and simulation was observed [37], and as this di erence can a ect the nal measured mtop value, a set of pseudo experiments are performed in which jets from simulated events are removed at random. The frequency of this is chosen such that the modi ed jet reconstruction e ciency in simulation matches the value measured in data. The analysis is repeated with this change and no signi cant di erence is observed. 10 Measurement of mtop After applying the method described in section 7 the top-quark mass is measured to be: mtop = 173:72 1:01 (syst.) GeV: (10.1) . /01000 s e i r t nE800 600 400 200 ATLAS 0.61 0.6 χ2 2-σ Stat. Contour HJEP09(217)8 decomposition into signal (in red) and the multi-jet background (in blue). The errors shown are statistical only. The right plot shows the ellipses corresponding to the 1- (solid line) and 2- (dashed line) statistical uncertainty. The central point in the gure indicates the values obtained for mtop on the x-axis, and the tted background fraction, Fbkgd, obtained within the t range of the R3/2 distribution on the y-axis. The plots do not take into account the small bias correction described in section 9.2. The top-quark mass, after this correction, is 173:72 The statistical error quoted in eq. (10.1) is corrected for the correlation between the two R3/2 measurements of each event, as discussed in section 7. The systematic uncertainty quoted above is the sum in quadrature of all the systematic uncertainties described in section 9 and summarised in table 3. Figure 6 shows the R3/2 distribution (left plot) with the corresponding total t as well as its decomposition into signal and the multijet background. The right plot in this gure shows the ellipses corresponding to 1(solid line) and 2- (dashed line) variations in statistical uncertainty. This measurement agrees with the previous all-hadronic mtop measurement performed by ATLAS in 7 TeV [17] data, with the mtop measurements performed in the single-lepton and dileptonic decay channels [11, 12, 14, 15] and with the results of combining the Tevatron and LHC measurements [13]. 11 Conclusion From the analysis of 20:2 fb 1 of data recorded with the ATLAS detector at the LHC at a pp centre-of-mass energy of 8 TeV, the top-quark mass has been measured in the all-hadronic decay channel of top-antitop quark pairs to be mtop = 173:72 1:01 (syst.) GeV: (11.1) This measurement is obtained from template ts to the R3/2 observable, which is chosen due to its reduced dependence on the jet energy scale uncertainty. The dominant remaining sources of systematic uncertainty, despite the usage of the R3/2 observable, come from the jet energy scale, hadronisation modelling and the b-jet energy scale. This measurement agrees with the previous Tevatron and LHC mtop measurements, and with the results of measurement performed by ATLAS in the all-hadronic channel at p s = 7 TeV. Tevatron and LHC combinations. It is about 40% more precise than the previous mtop Acknowledgments We thank CERN for the very successful operation of the LHC, as well as the support sta from our institutions without whom ATLAS could not be operated e ciently. We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DSM/IRFU, France; SRNSF, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, Hong Kong SAR, China; ISF, I-CORE and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; MNE/IFA, Romania; MES of Russia and NRC KI, Russian Federation; JINR; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZS, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, the Canada Council, CANARIE, CRC, Compute Canada, FQRNT, and the Ontario Innovation Trust, Canada; EPLANET, ERC, ERDF, FP7, Horizon 2020 and Marie Sklodowska-Curie Actions, European Union; Investissements davenir Labex and Idex, ANR, Region Auvergne and Fondation Partager le Savoir, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co- nanced by EU-ESF and the Greek NSRF; BSF, GIF and Minerva, Israel; BRF, Norway; CERCA Programme Generalitat de Catalunya, Generalitat Valenciana, Spain; the Royal Society and Leverhulme Trust, United Kingdom. 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Benekos10, Y. Benhammou155, E. Benhar Noccioli179, J. Benitez66, D.P. Benjamin48, J.R. Bensinger25, S. Bentvelsen109, L. Beresford122, M. Beretta50, D. Berge109, E. Bergeaas Kuutmann168, N. Berger5, J. Beringer16, S. Berlendis58, N.R. Bernard89, C. Bernius112, F.U. Bernlochner23, T. Berry80, P. Berta131, C. Bertella86, G. Bertoli148a,148b, F. Bertolucci126a,126b, I.A. Bertram75, C. Bertsche45, D. Bertsche115, G.J. Besjes39, O. Bessidskaia Bylund148a,148b, M. Bessner45, N. Besson138, C. Betancourt51, A. Bethani58, S. Bethke103, A.J. Bevan79, R.M. Bianchi127, M. Bianco32, O. Biebel102, D. Biedermann17, R. Bielski87, N.V. Biesuz126a,126b, M. Biglietti136a, J. Bilbao De Mendizabal52, T.R.V. Billoud97, H. Bilokon50, M. Bindi57, A. Bingul20b, C. Bini134a,134b, S. Biondi22a,22b, T. Bisanz57, HJEP09(217)8 T. Blazek146a, I. Bloch45, C. Blocker25, A. Blue56, W. Blum86; , U. Blumenschein57, HJEP09(217)8 D. Britton56, D. Britzger45, F.M. Brochu30, I. Brock23, R. Brock93, G. Brooijmans38, T. Brooks80, W.K. Brooks34b, J. Brosamer16, E. Brost110, J.H Broughton19, P.A. Bruckman de Renstrom42, D. Bruncko146b, R. Bruneliere51, A. Bruni22a, G. Bruni22a, L.S. Bruni109, BH Brunt30, M. Bruschi22a, N. Bruscino23, P. Bryant33, L. Bryngemark84, T. Buanes15, Q. Buat144, P. Buchholz143, A.G. Buckley56, I.A. Budagov68, F. Buehrer51, M.K. Bugge121, O. Bulekov100, D. Bullock8, H. Burckhart32, S. Burdin77, C.D. Burgard51, B. Burghgrave110, K. Burka42, S. Burke133, I. Burmeister46, J.T.P. Burr122, E. Busato37, D. Buscher51, V. Buscher86, P. Bussey56, J.M. Butler24, C.M. Buttar56, J.M. Butterworth81, P. Butti109, W. Buttinger27, A. Buzatu56, A.R. Buzykaev111;c, S. Cabrera Urban170, D. Caforio130, V.M. Cairo40a,40b, O. Cakir4a, N. Calace52, P. Cala ura16, A. Calandri88, G. Calderini83, P. Calfayan64, G. Callea40a,40b, L.P. Caloba26a, S. Calvente Lopez85, D. Calvet37, S. Calvet37, T.P. Calvet88, R. Camacho Toro33, S. Camarda32, P. Camarri135a,135b, D. Cameron121, R. Caminal Armadans169, C. Camincher58, S. Campana32, M. Campanelli81, A. Camplani94a,94b, A. Campoverde143, V. Canale106a,106b, A. Canepa163a, M. Cano Bret36c, J. Cantero116, T. Cao43, M.D.M. Capeans Garrido32, I. Caprini28b, M. Caprini28b, M. Capua40a,40b, R.M. Carbone38, R. Cardarelli135a, F. Cardillo51, I. Carli131, T. Carli32, G. Carlino106a, L. Carminati94a,94b, R.M.D. Carney148a,148b, S. Caron108, E. Carquin34b, G.D. Carrillo-Montoya32, J.R. Carter30, J. Carvalho128a,128c, D. Casadei19, M.P. Casado13;i, M. Casolino13, D.W. Casper166, E. Castaneda-Miranda147a, R. Castelijn109, A. Castelli109, V. Castillo Gimenez170, N.F. Castro128a;j , A. Catinaccio32, J.R. Catmore121, A. Cattai32, J. Caudron23, V. Cavaliere169, E. Cavallaro13, D. Cavalli94a, M. Cavalli-Sforza13, V. Cavasinni126a,126b, F. Ceradini136a,136b, L. Cerda Alberich170, A.S. Cerqueira26b, A. Cerri151, L. Cerrito135a,135b, F. Cerutti16, A. Cervelli18, S.A. Cetin20d, A. Chafaq137a, D. Chakraborty110, S.K. Chan59, Y.L. Chan62a, P. Chang169, J.D. Chapman30, D.G. Charlton19, A. Chatterjee52, C.C. Chau161, C.A. Chavez Barajas151, S. Che113, S. Cheatham167a,167c, A. Chegwidden93, S. Chekanov6, S.V. Chekulaev163a, G.A. Chelkov68;k, M.A. Chelstowska92, C. Chen67, H. Chen27, K. Chen150, S. Chen35b, S. Chen157, X. Chen35c, Y. Chen70, H.C. Cheng92, H.J. Cheng35a, Y. Cheng33, A. Cheplakov68, E. Cheremushkina132, R. Cherkaoui El Moursli137e, V. Chernyatin27; , E. Cheu7, L. Chevalier138, V. Chiarella50, G. Chiarelli126a,126b, G. Chiodini76a, A.S. Chisholm32, A. Chitan28b, M.V. Chizhov68, K. Choi64, A.R. Chomont37, S. Chouridou9, B.K.B. Chow102, V. Christodoulou81, D. Chromek-Burckhart32, J. Chudoba129, A.J. Chuinard90, J.J. Chwastowski42, L. Chytka117, G. Ciapetti134a,134b, A.K. Ciftci4a, D. Cinca46, V. Cindro78, I.A. Cioara23, C. Ciocca22a,22b, A. Ciocio16, F. Cirotto106a,106b, Z.H. Citron175, M. Citterio94a, M. Ciubancan28b, A. Clark52, B.L. Clark59, M.R. Clark38, P.J. Clark49, R.N. Clarke16, C. Clement148a,148b, Y. Coadou88, M. Cobal167a,167c, A. Coccaro52, J. Cochran67, L. Colasurdo108, B. Cole38, A.P. Colijn109, J. Collot58, T. Colombo166, G. Compostella103, P. Conde Muin~o128a,128b, E. Coniavitis51, S.H. Connell147b, I.A. Connelly80, V. Consorti51, S. Constantinescu28b, G. Conti32, F. Conventi106a;l, M. Cooke16, B.D. Cooper81, A.M. Cooper-Sarkar122, F. Cormier171, K.J.R. Cormier161, T. Cornelissen178, M. Corradi134a,134b, F. Corriveau90;m, A. Cortes-Gonzalez32, G. Cortiana103, G. Costa94a, M.J. Costa170, D. Costanzo141, G. Cottin30, G. Cowan80, B.E. Cox87, K. Cranmer112, S.J. Crawley56, G. Cree31, S. Crepe-Renaudin58, F. Crescioli83, W.A. Cribbs148a,148b, M. Crispin Ortuzar122, M. Cristinziani23, V. Croft108, G. Crosetti40a,40b, A. Cueto85, T. Cuhadar Donszelmann141, J. Cummings179, M. Curatolo50, J. Cuth86, H. Czirr143, P. Czodrowski3, G. D'amen22a,22b, S. D'Auria56, M. D'Onofrio77, M.J. Da Cunha Sargedas De Sousa128a,128b, C. Da Via87, W. Dabrowski41a, T. Dado146a, T. Dai92, O. Dale15, F. Dallaire97, C. Dallapiccola89, M. Dam39, J.R. Dandoy33, N.P. Dang51, A.C. Daniells19, N.S. Dann87, M. Danninger171, M. Dano Ho mann138, V. Dao51, G. Darbo53a, S. Darmora8, J. Dassoulas3, A. Dattagupta118, W. Davey23, C. David172, T. Davidek131, M. Davies155, P. Davison81, E. Dawe91, I. Dawson141, K. De8, R. de Asmundis106a, A. De Benedetti115, S. De Castro22a,22b, S. De Cecco83, N. De Groot108, P. de Jong109, H. De la Torre93, F. De Lorenzi67, A. De Maria57, D. De Pedis134a, A. De Salvo134a, U. De Sanctis151, A. De Santo151, J.B. De Vivie De Regie119, W.J. Dearnaley75, R. Debbe27, C. Debenedetti139, D.V. Dedovich68, N. Dehghanian3, I. Deigaard109, M. Del Gaudio40a,40b, J. Del Peso85, T. Del Prete126a,126b, D. Delgove119, F. Deliot138, C.M. Delitzsch52, A. Dell'Acqua32, L. Dell'Asta24, M. Dell'Orso126a,126b, M. Della Pietra106a;l, D. della Volpe52, M. Delmastro5, P.A. Delsart58, D.A. DeMarco161, S. Demers179, M. Demichev68, A. Demilly83, S.P. Denisov132, D. Denysiuk138, D. Derendarz42, J.E. Derkaoui137d, F. Derue83, P. Dervan77, K. Desch23, C. Deterre45, K. Dette46, P.O. Deviveiros32, A. Dewhurst133, S. Dhaliwal25, A. Di Ciaccio135a,135b, L. Di Ciaccio5, W.K. Di Clemente124, C. Di Donato106a,106b, A. Di Girolamo32, B. Di Girolamo32, B. Di Micco136a,136b, R. Di Nardo32, A. Di Simone51, R. Di Sipio161, D. Di Valentino31, C. Diaconu88, M. Diamond161, F.A. Dias49, M.A. Diaz34a, E.B. Diehl92, J. Dietrich17, S. D ez Cornell45, A. Dimitrievska14, J. Dingfelder23, P. Dita28b, S. Dita28b, F. Dittus32, F. Djama88, T. Djobava54b, J.I. Djuvsland60a, M.A.B. do Vale26c, D. Dobos32, M. Dobre28b, C. Doglioni84, J. Dolejsi131, Z. Dolezal131, M. Donadelli26d, S. Donati126a,126b, P. Dondero123a,123b, J. Donini37, J. Dopke133, A. Doria106a, M.T. Dova74, A.T. Doyle56, E. Drechsler57, M. Dris10, Y. Du36b, J. Duarte-Campderros155, E. Duchovni175, G. Duckeck102, O.A. Ducu97;n, D. Duda109, A. Dudarev32, A.Chr. Dudder86, E.M. Du eld16, L. Du ot119, M. Duhrssen32, M. Dumancic175, A.K. Duncan56, M. Dunford60a, H. Duran Yildiz4a, M. Duren55, A. Durglishvili54b, D. Duschinger47, B. Dutta45, M. Dyndal45, C. Eckardt45, K.M. Ecker103, R.C. Edgar92, N.C. Edwards49, T. Eifert32, G. Eigen15, K. Einsweiler16, T. Ekelof168, M. El Kacimi137c, V. Ellajosyula88, M. Ellert168, S. Elles5, F. Ellinghaus178, A.A. Elliot172, N. Ellis32, J. Elmsheuser27, M. Elsing32, D. Emeliyanov133, Y. Enari157, O.C. Endner86, J.S. Ennis173, J. Erdmann46, A. Ereditato18, G. Ernis178, J. Ernst2, M. Ernst27, S. Errede169, E. Ertel86, M. Escalier119, H. Esch46, C. Escobar127, B. Esposito50, A.I. Etienvre138, E. Etzion155, H. Evans64, A. Ezhilov125, M. Ezzi137e, F. Fabbri22a,22b, L. Fabbri22a,22b, G. Facini33, R.M. Fakhrutdinov132, S. Falciano134a, R.J. Falla81, J. Faltova32, Y. Fang35a, M. Fanti94a,94b, A. Farbin8, A. Farilla136a, C. Farina127, E.M. Farina123a,123b, T. Farooque13, S. Farrell16, S.M. Farrington173, P. Farthouat32, F. Fassi137e, P. Fassnacht32, D. Fassouliotis9, M. Faucci Giannelli80, A. Favareto53a,53b, W.J. Fawcett122, L. Fayard119, O.L. Fedin125;o, W. Fedorko171, S. Feigl121, L. Feligioni88, C. Feng36b, E.J. Feng32, H. Feng92, A.B. Fenyuk132, L. Feremenga8, P. Fernandez Martinez170, S. Fernandez Perez13, J. Ferrando45, A. Ferrari168, P. Ferrari109, R. Ferrari123a, D.E. Ferreira de Lima60b, A. Ferrer170, D. Ferrere52, C. Ferretti92, F. Fiedler86, A. Filipcic78, M. Filipuzzi45, F. Filthaut108, M. Fincke-Keeler172, K.D. Finelli152, M.C.N. Fiolhais128a,128c, L. Fiorini170, A. Fischer2, C. Fischer13, J. Fischer178, HJEP09(217)8 R.R.M. Fletcher124, T. Flick178, B.M. Flierl102, L.R. Flores Castillo62a, M.J. Flowerdew103, A. Glazov45, M. Goblirsch-Kolb25, J. Godlewski42, S. Goldfarb91, T. Golling52, D. Golubkov132, A. Gomes128a,128b,128d, R. Goncalo128a, J. Goncalves Pinto Firmino Da Costa138, G. Gonella51, L. Gonella19, A. Gongadze68, S. Gonzalez de la Hoz170, S. Gonzalez-Sevilla52, L. Goossens32, P.A. Gorbounov99, H.A. Gordon27, I. Gorelov107, B. Gorini32, E. Gorini76a,76b, A. Gorisek78, E. Gornicki42, A.T. Goshaw48, C. Gossling46, M.I. Gostkin68, C.R. Goudet119, D. Goujdami137c, A.G. Goussiou140, N. Govender147b;q, E. Gozani154, L. Graber57, I. Grabowska-Bold41a, P.O.J. Gradin58, P. Grafstrom22a,22b, J. Gramling52, E. Gramstad121, S. Grancagnolo17, V. Gratchev125, P.M. Gravila28e, H.M. Gray32, E. Graziani136a, Z.D. Greenwood82;r, C. Grefe23, K. Gregersen81, I.M. Gregor45, P. Grenier145, K. Grevtsov5, J. Gri ths8, A.A. Grillo139, K. Grimm75, S. Grinstein13;s, Ph. Gris37, J.-F. Grivaz119, S. Groh86, E. Gross175, J. Grosse-Knetter57, G.C. Grossi82, Z.J. Grout81, L. Guan92, W. Guan176, J. Guenther65, F. Guescini52, D. Guest166, O. Gueta155, B. Gui113, E. Guido53a,53b, T. Guillemin5, S. Guindon2, U. Gul56, C. Gumpert32, J. Guo36c, Y. Guo36a;p, R. Gupta43, S. Gupta122, G. Gustavino134a,134b, P. Gutierrez115, N.G. Gutierrez Ortiz81, C. Gutschow81, C. Guyot138, C. Gwenlan122, C.B. Gwilliam77, A. Haas112, C. Haber16, H.K. Hadavand8, N. Haddad137e, A. Hadef88, S. Hagebock23, M. Hagihara164, Z. Hajduk42, H. Hakobyan180; , M. Haleem45, J. Haley116, G. Halladjian93, G.D. Hallewell88, K. Hamacher178, P. Hamal117, K. Hamano172, A. Hamilton147a, G.N. Hamity141, P.G. Hamnett45, L. Han36a, K. Hanagaki69;t, K. Hanawa157, M. Hance139, B. Haney124, P. Hanke60a, R. Hanna138, J.B. Hansen39, J.D. Hansen39, M.C. Hansen23, P.H. Hansen39, K. Hara164, A.S. Hard176, T. Harenberg178, F. Hariri119, S. Harkusha95, R.D. Harrington49, P.F. Harrison173, F. Hartjes109, N.M. Hartmann102, M. Hasegawa70, Y. Hasegawa142, A. Hasib115, S. Hassani138, S. Haug18, R. Hauser93, L. Hauswald47, M. Havranek129, C.M. Hawkes19, R.J. Hawkings32, D. Hayakawa159, D. Hayden93, C.P. Hays122, J.M. Hays79, H.S. Hayward77, S.J. Haywood133, S.J. Head19, T. Heck86, V. Hedberg84, L. Heelan8, S. Heim124, T. Heim16, B. Heinemann16, J.J. Heinrich102, L. Heinrich112, C. Heinz55, J. Hejbal129, L. Helary32, S. Hellman148a,148b, C. Helsens32, J. Henderson122, R.C.W. Henderson75, Y. Heng176, S. Henkelmann171, A.M. Henriques Correia32, HJEP09(217)8 G. Herten51, R. Hertenberger102, L. Hervas32, G.G. Hesketh81, N.P. Hessey109, J.W. Hetherly43, E. Kajomovitz48, C.W. Kalderon122, A. Kaluza86, S. Kama43, A. Kamenshchikov132, N. Kanaya157, S. Kaneti30, L. Kanjir78, V.A. Kantserov100, J. Kanzaki69, B. Kaplan112, L.S. Kaplan176, A. Kapliy33, D. Kar147c, K. Karakostas10, A. Karamaoun3, N. Karastathis10, M.J. Kareem57, E. Karentzos10, M. Karnevskiy86, S.N. Karpov68, Z.M. Karpova68, K. Karthik112, V. Kartvelishvili75, A.N. Karyukhin132, K. Kasahara164, L. Kashif176, R.D. Kass113, A. Kastanas149, Y. Kataoka157, C. Kato157, A. Katre52, J. Katzy45, K. Kawade105, K. Kawagoe73, T. Kawamoto157, G. Kawamura57, V.F. Kazanin111;c, R. Keeler172, R. Kehoe43, J.S. Keller45, J.J. Kempster80, H. Keoshkerian161, O. Kepka129, B.P. Kersevan78, S. Kersten178, R.A. Keyes90, M. Khader169, F. Khalil-zada12, A. Khanov116, A.G. Kharlamov111;c, T. Kharlamova111;c, T.J. Khoo52, V. Khovanskiy99, E. Khramov68, J. Khubua54b;y, S. Kido70, C.R. Kilby80, H.Y. Kim8, S.H. Kim164, Y.K. Kim33, N. Kimura156, O.M. Kind17, B.T. King77, M. King170, J. Kirk133, A.E. Kiryunin103, T. Kishimoto157, D. Kisielewska41a, F. Kiss51, K. Kiuchi164, O. Kivernyk138, E. Kladiva146b, M.H. Klein38, M. Klein77, U. Klein77, K. Kleinknecht86, P. Klimek110, A. Klimentov27, R. Klingenberg46, T. Klioutchnikova32, E.-E. Kluge60a, P. Kluit109, S. Kluth103, J. Knapik42, E. Kneringer65, E.B.F.G. Knoops88, A. Knue103, A. Kobayashi157, D. Kobayashi159, T. Kobayashi157, M. Kobel47, M. Kocian145, P. Kodys131, T. Ko as31, E. Ko eman109, N.M. Kohler103, T. Koi145, H. Kolanoski17, M. Kolb60b, I. Koletsou5, A.A. Komar98; , Y. Komori157, T. Kondo69, N. Kondrashova36c, K. Koneke51, A.C. Konig108, T. Kono69;z, R. Konoplich112;aa, N. Konstantinidis81, R. Kopeliansky64, S. Koperny41a, L. Kopke86, A.K. Kopp51, K. Korcyl42, K. Kordas156, A. Korn81, A.A. Korol111;c, I. Korolkov13, E.V. Korolkova141, O. Kortner103, S. Kortner103, T. Kosek131, V.V. Kostyukhin23, A. Kotwal48, A. Koulouris10, A. Kourkoumeli-Charalampidi123a,123b, C. Kourkoumelis9, V. Kouskoura27, A.B. Kowalewska42, HJEP09(217)8 V.A. Kramarenko101, G. Kramberger78, D. Krasnopevtsev100, M.W. Krasny83, A. Krasznahorkay32, A. Kravchenko27, M. Kretz60c, J. Kretzschmar77, K. Kreutzfeldt55, P. Krieger161, K. Krizka33, K. Kroeninger46, H. Kroha103, J. Kroll124, J. Kroseberg23, J. Krstic14, U. Kruchonak68, H. Kruger23, N. Krumnack67, M.C. Kruse48, M. Kruskal24, T. Kubota91, H. Kucuk81, S. Kuday4b, J.T. Kuechler178, S. Kuehn51, A. Kugel60c, F. Kuger177, T. Kuhl45, V. Kukhtin68, R. Kukla138, Y. Kulchitsky95, S. Kuleshov34b, M. Kuna134a,134b, T. Kunigo71, A. Kupco129, H. Kurashige70, Y.A. Kurochkin95, M.G. Kurth44, V. Kus129, E.S. Kuwertz172, M. Kuze159, J. Kvita117, T. Kwan172, D. Kyriazopoulos141, A. La Rosa103, J.L. La Rosa Navarro26d, L. La Rotonda40a,40b, C. Lacasta170, F. Lacava134a,134b, J. Lacey31, H. Lacker17, D. Lacour83, V.R. Lacuesta170, E. Ladygin68, R. Lafaye5, B. Laforge83, T. Lagouri179, S. Lai57, S. Lammers64, W. Lampl7, E. Lancon138, U. Landgraf51, M.P.J. Landon79, M.C. Lanfermann52, V.S. Lang60a, J.C. Lange13, A.J. Lankford166, F. Lanni27, K. Lantzsch23, A. Lanza123a, S. Laplace83, C. Lapoire32, J.F. Laporte138, T. Lari94a, F. Lasagni Manghi22a,22b, M. Lassnig32, P. Laurelli50, W. Lavrijsen16, A.T. Law139, P. Laycock77, T. Lazovich59, M. Lazzaroni94a,94b, B. Le91, O. Le Dortz83, E. Le Guirriec88, E.P. Le Quilleuc138, M. LeBlanc172, T. LeCompte6, F. Ledroit-Guillon58, C.A. Lee27, S.C. Lee153, L. Lee1, B. Lefebvre90, G. Lefebvre83, M. Lefebvre172, F. Legger102, C. Leggett16, A. Lehan77, G. Lehmann Miotto32, X. Lei7, W.A. Leight31, A.G. Leister179, M.A.L. Leite26d, R. Leitner131, D. Lellouch175, B. Lemmer57, K.J.C. Leney81, T. Lenz23, B. Lenzi32, R. Leone7, S. Leone126a,126b, C. Leonidopoulos49, S. Leontsinis10, G. Lerner151, C. Leroy97, A.A.J. Lesage138, C.G. Lester30, M. Levchenko125, J. Lev^eque5, D. Levin92, L.J. Levinson175, M. Levy19, D. Lewis79, A.M. Leyko23, M. Leyton44, B. Li36a;p, C. Li36a, H. Li150, L. Li48, L. Li36c, Q. Li35a, S. Li48, X. Li87, Y. Li143, Z. Liang35a, B. Liberti135a, A. Liblong161, P. Lichard32, K. Lie169, J. Liebal23, W. Liebig15, A. Limosani152, S.C. Lin153;ab, T.H. Lin86, B.E. Lindquist150, A.E. Lionti52, E. Lipeles124, A. Lipniacka15, M. Lisovyi60b, T.M. Liss169, A. Lister171, A.M. Litke139, B. Liu153;ac, D. Liu153, H. Liu92, H. Liu27, J. Liu36b, J.B. Liu36a, K. Liu88, L. Liu169, M. Liu36a, Y.L. Liu36a, Y. Liu36a, M. Livan123a,123b, A. Lleres58, J. Llorente Merino35a, S.L. Lloyd79, F. Lo Sterzo153, E.M. Lobodzinska45, P. Loch7, F.K. Loebinger87, K.M. Loew25, A. Loginov179; , T. Lohse17, K. Lohwasser45, M. Lokajicek129, B.A. Long24, J.D. Long169, R.E. Long75, L. Longo76a,76b, K.A. Looper113, J.A. Lopez Lopez34b, D. Lopez Mateos59, B. Lopez Paredes141, I. Lopez Paz13, A. Lopez Solis83, J. Lorenz102, N. Lorenzo Martinez64, M. Losada21, P.J. Losel102, X. Lou35a, A. Lounis119, J. Love6, P.A. Love75, H. Lu62a, N. Lu92, H.J. Lubatti140, C. Luci134a,134b, A. Lucotte58, C. Luedtke51, F. Luehring64, W. Lukas65, L. Luminari134a, O. Lundberg148a,148b, B. Lund-Jensen149, P.M. Luzi83, D. Lynn27, R. Lysak129, E. Lytken84, V. Lyubushkin68, H. Ma27, L.L. Ma36b, Y. Ma36b, G. Maccarrone50, A. Macchiolo103, C.M. Macdonald141, B. Macek78, J. Machado Miguens124,128b, D. Mada ari88, R. Madar37, H.J. Maddocks168, W.F. Mader47, A. Madsen45, J. Maeda70, S. Maeland15, T. Maeno27, A. Maevskiy101, E. Magradze57, J. Mahlstedt109, C. Maiani119, C. Maidantchik26a, A.A. Maier103, T. Maier102, A. Maio128a,128b,128d, S. Majewski118, Y. Makida69, N. Makovec119, B. Malaescu83, Pa. Malecki42, V.P. Maleev125, F. Malek58, U. Mallik66, D. Malon6, C. Malone145, C. Malone30, S. Maltezos10, S. Malyukov32, J. Mamuzic170, G. Mancini50, L. Mandelli94a, I. Mandic78, J. Maneira128a,128b, L. Manhaes de Andrade Filho26b, J. Manjarres Ramos163b, A. Mann102, A. Manousos32, B. Mansoulie138, J.D. Mansour35a, R. Mantifel90, M. Mantoani57, S. Manzoni94a,94b, L. Mapelli32, G. Marceca29, L. March52, G. Marchiori83, M. Marcisovsky129, M. Marjanovic14, D.E. Marley92, F. Marroquim26a, S.P. Marsden87, Z. Marshall16, S. Marti-Garcia170, B. Martin93, T.A. Martin173, V.J. Martin49, B. Martin dit Latour15, HJEP09(217)8 A.C. Martyniuk81, A. Marzin32, L. Masetti86, T. Mashimo157, R. Mashinistov98, J. Masik87, A.L. Maslennikov111;c, I. Massa22a,22b, L. Massa22a,22b, P. Mastrandrea5, A. Mastroberardino40a,40b, T. Masubuchi157, P. Mattig178, J. Mattmann86, J. Maurer28b, K. Mochizuki97, P. Mogg51, S. Mohapatra38, S. Molander148a,148b, R. Moles-Valls23, R. Monden71, M.C. Mondragon93, K. Monig45, J. Monk39, E. Monnier88, A. Montalbano150, J. Montejo Berlingen32, F. Monticelli74, S. Monzani94a,94b, R.W. Moore3, N. Morange119, D. Moreno21, M. Moreno Llacer57, P. Morettini53a, S. Morgenstern32, D. Mori144, T. Mori157, M. Morii59, M. Morinaga157, V. Morisbak121, S. Moritz86, A.K. Morley152, G. Mornacchi32, J.D. Morris79, S.S. Mortensen39, L. Morvaj150, M. Mosidze54b, H.J. Moss141, J. Moss145;ad, K. Motohashi159, R. Mount145, E. Mountricha27, E.J.W. Moyse89, S. Muanza88, R.D. Mudd19, F. Mueller103, J. Mueller127, R.S.P. Mueller102, T. Mueller30, D. Muenstermann75, P. Mullen56, G.A. Mullier18, F.J. Munoz Sanchez87, J.A. Murillo Quijada19, W.J. Murray173,133, H. Musheghyan57, M. Muskinja78, A.G. Myagkov132;ae, M. Myska130, B.P. Nachman145, O. Nackenhorst52, K. Nagai122, R. Nagai69;z, K. Nagano69, Y. Nagasaka61, K. Nagata164, M. Nagel51, E. Nagy88, A.M. Nairz32, Y. Nakahama105, K. Nakamura69, T. Nakamura157, I. Nakano114, R.F. Naranjo Garcia45, R. Narayan11, D.I. Narrias Villar60a, I. Naryshkin125, T. Naumann45, G. Navarro21, R. Nayyar7, H.A. Neal92, P.Yu. Nechaeva98, T.J. Neep87, A. Negri123a,123b, M. Negrini22a, S. Nektarijevic108, C. Nellist119, A. Nelson166, S. Nemecek129, P. Nemethy112, A.A. Nepomuceno26a, M. Nessi32;af , M.S. Neubauer169, M. Neumann178, R.M. Neves112, P. Nevski27, P.R. Newman19, D.H. Nguyen6, T. Nguyen Manh97, R.B. Nickerson122, R. Nicolaidou138, J. Nielsen139, A. Nikiforov17, V. Nikolaenko132;ae, I. Nikolic-Audit83, K. Nikolopoulos19, J.K. Nilsen121, P. Nilsson27, Y. Ninomiya157, A. Nisati134a, R. Nisius103, T. Nobe157, M. Nomachi120, I. Nomidis31, T. Nooney79, S. Norberg115, M. Nordberg32, N. Norjoharuddeen122, O. Novgorodova47, S. Nowak103, M. Nozaki69, L. Nozka117, K. Ntekas166, E. Nurse81, F. Nuti91, F. O'grady7, D.C. O'Neil144, A.A. O'Rourke45, V. O'Shea56, F.G. Oakham31;d, H. Oberlack103, T. Obermann23, J. Ocariz83, A. Ochi70, I. Ochoa38, J.P. Ochoa-Ricoux34a, S. Oda73, S. Odaka69, H. Ogren64, A. Oh87, S.H. Oh48, C.C. Ohm16, H. Ohman168, H. Oide53a,53b, H. Okawa164, Y. Okumura157, T. Okuyama69, A. Olariu28b, L.F. Oleiro Seabra128a, S.A. Olivares Pino49, D. Oliveira Damazio27, A. Olszewski42, J. Olszowska42, A. Onofre128a,128e, K. Onogi105, P.U.E. Onyisi11;v, M.J. Oreglia33, Y. Oren155, D. Orestano136a,136b, N. Orlando62b, R.S. Orr161, B. Osculati53a,53b; , R. Ospanov87, G. Otero y Garzon29, H. Otono73, M. Ouchrif137d, F. Ould-Saada121, A. Ouraou138, K.P. Oussoren109, Q. Ouyang35a, M. Owen56, R.E. Owen19, HJEP09(217)8 C. Padilla Aranda13, M. Pagacova51, S. Pagan Griso16, M. Paganini179, F. Paige27, P. Pais89, K. Pajchel121, G. Palacino64, S. Palazzo40a,40b, S. Palestini32, M. Palka41b, D. Pallin37, E.St. Panagiotopoulou10, I. Panagoulias10, C.E. Pandini83, J.G. Panduro Vazquez80, P. Pani148a,148b, S. Panitkin27, D. Pantea28b, L. Paolozzi52, Th.D. Papadopoulou10, K. Papageorgiou156, A. Paramonov6, D. Paredes Hernandez179, A.J. Parker75, M.A. Parker30, K.A. Parker141, F. Parodi53a,53b, J.A. Parsons38, U. Parzefall51, V.R. Pascuzzi161, E. Pasqualucci134a, S. Passaggio53a, Fr. Pastore80, G. Pasztor31;ag, S. Pataraia178, J.R. Pater87, T. Pauly32, J. Pearce172, B. Pearson115, L.E. Pedersen39, M. Pedersen121, S. Pedraza Lopez170, R. Pedro128a,128b, S.V. Peleganchuk111;c, O. Penc129, C. Peng35a, H. Peng36a, J. Penwell64, B.S. Peralva26b, M.M. Perego138, D.V. Perepelitsa27, E. Perez Codina163a, L. Perini94a,94b, H. Pernegger32, S. Perrella106a,106b, R. Peschke45, V.D. Peshekhonov68, K. Peters45, R.F.Y. Peters87, B.A. Petersen32, T.C. Petersen39, E. Petit58, A. Petridis1, C. Petridou156, P. Petro 119, E. Petrolo134a, M. Petrov122, F. Petrucci136a,136b, N.E. Pettersson89, A. Peyaud138, R. Pezoa34b, P.W. Phillips133, G. Piacquadio145;ah, E. Pianori173, A. Picazio89, E. Piccaro79, M. Piccinini22a,22b, M.A. Pickering122, R. Piegaia29, J.E. Pilcher33, A.D. Pilkington87, A.W.J. Pin87, M. Pinamonti167a,167c;ai, J.L. Pinfold3, A. Pingel39, S. Pires83, H. Pirumov45, M. Pitt175, L. Plazak146a, M.-A. Pleier27, V. Pleskot86, E. Plotnikova68, D. Pluth67, R. Poettgen148a,148b, L. Poggioli119, D. Pohl23, G. Polesello123a, A. Poley45, A. Policicchio40a,40b, R. Polifka161, A. Polini22a, C.S. Pollard56, V. Polychronakos27, K. Pommes32, L. Pontecorvo134a, B.G. Pope93, G.A. Popeneciu28c, A. Poppleton32, S. Pospisil130, K. Potamianos16, I.N. Potrap68, C.J. Potter30, C.T. Potter118, G. Poulard32, J. Poveda32, V. Pozdnyakov68, M.E. Pozo Astigarraga32, P. Pralavorio88, A. Pranko16, S. Prell67, D. Price87, L.E. Price6, M. Primavera76a, S. Prince90, K. Proko ev62c, F. Prokoshin34b, S. Protopopescu27, J. Proudfoot6, M. Przybycien41a, D. Puddu136a,136b, M. Purohit27;aj , P. Puzo119, J. Qian92, G. Qin56, Y. Qin87, A. Quadt57, W.B. Quayle167a,167b, M. Queitsch-Maitland45, D. Quilty56, S. Raddum121, V. Radeka27, V. Radescu122, S.K. Radhakrishnan150, P. Radlo 118, P. Rados91, F. Ragusa94a,94b, G. Rahal181, J.A. Raine87, S. Rajagopalan27, M. Rammensee32, C. Rangel-Smith168, M.G. Ratti94a,94b, D.M. Rauch45, F. Rauscher102, S. Rave86, T. Ravenscroft56, I. Ravinovich175, M. Raymond32, A.L. Read121, N.P. Readio 77, M. Reale76a,76b, D.M. Rebuzzi123a,123b, A. Redelbach177, G. Redlinger27, R. Reece139, R.G. Reed147c, K. Reeves44, L. Rehnisch17, J. Reichert124, A. Reiss86, C. Rembser32, H. Ren35a, M. Rescigno134a, S. Resconi94a, O.L. Rezanova111;c, P. Reznicek131, R. Rezvani97, R. Richter103, S. Richter81, E. Richter-Was41b, O. Ricken23, M. Ridel83, P. Rieck17, C.J. Riegel178, J. Rieger57, O. Rifki115, M. Rijssenbeek150, A. Rimoldi123a,123b, M. Rimoldi18, L. Rinaldi22a, B. Ristic52, E. Ritsch32, I. Riu13, F. Rizatdinova116, E. Rizvi79, C. Rizzi13, S.H. Robertson90;m, A. Robichaud-Veronneau90, D. Robinson30, J.E.M. Robinson45, A. Robson56, C. Roda126a,126b, Y. Rodina88;ak, A. Rodriguez Perez13, D. Rodriguez Rodriguez170, S. Roe32, C.S. Rogan59, O. R hne121, J. Rolo 59, A. Romaniouk100, M. Romano22a,22b, S.M. Romano Saez37, E. Romero Adam170, N. Rompotis140, M. Ronzani51, L. Roos83, E. Ros170, S. Rosati134a, K. Rosbach51, P. Rose139, N.-A. Rosien57, V. Rossetti148a,148b, E. Rossi106a,106b, L.P. Rossi53a, J.H.N. Rosten30, R. Rosten140, M. Rotaru28b, I. Roth175, J. Rothberg140, D. Rousseau119, A. Rozanov88, Y. Rozen154, X. Ruan147c, F. Rubbo145, M.S. Rudolph161, F. Ruhr51, A. Ruiz-Martinez31, Z. Rurikova51, N.A. Rusakovich68, A. Ruschke102, H.L. Russell140, J.P. Rutherfoord7, N. Ruthmann32, Y.F. Ryabov125, M. Rybar169, G. Rybkin119, S. Ryu6, A. Ryzhov132, G.F. Rzehorz57, A.F. Saavedra152, G. Sabato109, S. Sacerdoti29, H.F-W. Sadrozinski139, R. Sadykov68, F. Safai Tehrani134a, P. Saha110, M. Sahinsoy60a, M. Saimpert138, T. Saito157, H. Sakamoto157, Y. Sakurai174, G. Salamanna136a,136b, HJEP09(217)8 A. Salnikov145, J. Salt170, D. Salvatore40a,40b, F. Salvatore151, A. Salvucci62a,62b,62c, A. Salzburger32, D. Sammel51, D. Sampsonidis156, J. Sanchez170, V. Sanchez Martinez170, A. Sanchez Pineda106a,106b, H. Sandaker121, R.L. Sandbach79, M. Sandho 178, C. Sandoval21, D.P.C. Sankey133, M. Sannino53a,53b, A. Sansoni50, C. Santoni37, R. Santonico135a,135b, H. Santos128a, I. Santoyo Castillo151, K. Sapp127, A. Sapronov68, J.G. Saraiva128a,128d, B. Sarrazin23, O. Sasaki69, K. Sato164, E. Sauvan5, G. Savage80, P. Savard161;d, N. Savic103, C. Sawyer133, L. Sawyer82;r, J. Saxon33, C. Sbarra22a, A. Sbrizzi22a,22b, T. Scanlon81, D.A. Scannicchio166, M. Scarcella152, V. Scarfone40a,40b, J. Schaarschmidt175, P. Schacht103, B.M. Schachtner102, D. Schaefer32, L. Schaefer124, R. Schaefer45, J. Schae er86, S. Schaepe23, S. Schaetzel60b, U. Schafer86, A.C. Scha er119, D. Schaile102, R.D. Schamberger150, V. Scharf60a, V.A. Schegelsky125, D. Scheirich131, M. Schernau166, C. Schiavi53a,53b, S. Schier139, C. Schillo51, M. Schioppa40a,40b, S. Schlenker32, K.R. Schmidt-Sommerfeld103, K. Schmieden32, C. Schmitt86, S. Schmitt45, S. Schmitz86, B. Schneider163a, U. Schnoor51, L. Schoe el138, A. Schoening60b, B.D. Schoenrock93, E. Schopf23, M. Schott86, J.F.P. Schouwenberg108, J. Schovancova8, S. Schramm52, M. Schreyer177, N. Schuh86, A. Schulte86, M.J. Schultens23, H.-C. Schultz-Coulon60a, H. Schulz17, M. Schumacher51, B.A. Schumm139, Ph. Schune138, A. Schwartzman145, T.A. Schwarz92, H. Schweiger87, Ph. Schwemling138, R. Schwienhorst93, J. Schwindling138, T. Schwindt23, G. Sciolla25, F. Scuri126a,126b, F. Scutti91, J. Searcy92, P. Seema23, S.C. Seidel107, A. Seiden139, F. Seifert130, J.M. Seixas26a, G. Sekhniaidze106a, K. Sekhon92, S.J. Sekula43, D.M. Seliverstov125; , N. Semprini-Cesari22a,22b, C. Serfon121, L. Serin119, L. Serkin167a,167b, M. Sessa136a,136b, R. Seuster172, H. Severini115, T. S ligoj78, F. Sforza32, A. Sfyrla52, E. Shabalina57, N.W. Shaikh148a,148b, L.Y. Shan35a, R. Shang169, J.T. Shank24, M. Shapiro16, P.B. Shatalov99, K. Shaw167a,167b, S.M. Shaw87, A. Shcherbakova148a,148b, C.Y. Shehu151, P. Sherwood81, L. Shi153;al, S. Shimizu70, C.O. Shimmin166, M. Shimojima104, S. Shirabe73, M. Shiyakova68;am, A. Shmeleva98, D. Shoaleh Saadi97, M.J. Shochet33, S. Shojaii94a, D.R. Shope115, S. Shrestha113, E. Shulga100, M.A. Shupe7, P. Sicho129, A.M. Sickles169, P.E. Sidebo149, E. Sideras Haddad147c, O. Sidiropoulou177, D. Sidorov116, A. Sidoti22a,22b, F. Siegert47, Dj. Sijacki14, J. Silva128a,128d, S.B. Silverstein148a, V. Simak130, Lj. Simic14, S. Simion119, E. Simioni86, B. Simmons81, D. Simon37, M. Simon86, P. Sinervo161, N.B. Sinev118, M. Sioli22a,22b, G. Siragusa177, S.Yu. Sivoklokov101, J. Sjolin148a,148b, M.B. Skinner75, H.P. Skottowe59, P. Skubic115, M. Slater19, T. Slavicek130, M. Slawinska109, K. Sliwa165, R. Slovak131, V. Smakhtin175, B.H. Smart5, L. Smestad15, J. Smiesko146a, S.Yu. Smirnov100, Y. Smirnov100, L.N. Smirnova101;an, O. Smirnova84, J.W. Smith57, M.N.K. Smith38, R.W. Smith38, M. Smizanska75, K. Smolek130, A.A. Snesarev98, I.M. Snyder118, S. Snyder27, R. Sobie172;m, F. Socher47, A. So er155, D.A. Soh153, G. Sokhrannyi78, C.A. Solans Sanchez32, M. Solar130, E.Yu. Soldatov100, U. Soldevila170, A.A. Solodkov132, A. Soloshenko68, O.V. Solovyanov132, V. Solovyev125, P. Sommer51, H. Son165, H.Y. Song36a;ao, A. Sood16, A. Sopczak130, V. Sopko130, V. Sorin13, D. Sosa60b, C.L. Sotiropoulou126a,126b, R. Soualah167a,167c, A.M. Soukharev111;c, D. South45, B.C. Sowden80, S. Spagnolo76a,76b, M. Spalla126a,126b, M. Spangenberg173, F. Spano80, D. Sperlich17, F. Spettel103, R. Spighi22a, G. Spigo32, L.A. Spiller91, M. Spousta131, R.D. St. Denis56; , A. Stabile94a, R. Stamen60a, S. Stamm17, E. Stanecka42, R.W. Stanek6, C. Stanescu136a, M. Stanescu-Bellu45, M.M. Stanitzki45, S. Stapnes121, E.A. Starchenko132, G.H. Stark33, J. Stark58, P. Staroba129, P. Starovoitov60a, S. Starz32, R. Staszewski42, P. Steinberg27, B. Stelzer144, H.J. Stelzer32, O. Stelzer-Chilton163a, H. Stenzel55, G.A. Stewart56, J.A. Stillings23, M.C. Stockton90, M. Stoebe90, G. Stoicea28b, P. Stolte57, S. Stonjek103, A.R. Stradling8, A. Straessner47, M.E. Stramaglia18, J. Strandberg149, S. Strandberg148a,148b, HJEP09(217)8 R. Stroynowski43, A. Strubig108, S.A. Stucci27, B. Stugu15, N.A. Styles45, D. Su145, J. Su127, S. Suchek60a, Y. Sugaya120, M. Suk130, V.V. Sulin98, S. Sultansoy4c, T. Sumida71, S. Sun59, X. Sun35a, J.E. Sundermann51, K. Suruliz151, C.J.E. Suster152, M.R. Sutton151, S. Suzuki69, M. Svatos129, M. Swiatlowski33, S.P. Swift2, I. Sykora146a, T. Sykora131, D. Ta51, C. Taccini136a,136b, K. Tackmann45, J. Taenzer161, A. Ta ard166, R. Ta rout163a, N. Taiblum155, H. Takai27, R. Takashima72, T. Takeshita142, Y. Takubo69, M. Talby88, A.A. Talyshev111;c, K.G. Tan91, J. Tanaka157, M. Tanaka159, R. Tanaka119, S. Tanaka69, R. Tanioka70, B.B. Tannenwald113, S. Tapia Araya34b, S. Tapprogge86, S. Tarem154, G.F. Tartarelli94a, P. Tas131, M. Tasevsky129, T. Tashiro71, E. Tassi40a,40b, A. Tavares Delgado128a,128b, Y. Tayalati137e, A.C. Taylor107, G.N. Taylor91, P.T.E. Taylor91, W. Taylor163b, F.A. Teischinger32, P. Teixeira-Dias80, K.K. Temming51, D. Temple144, H. Ten Kate32, P.K. Teng153, J.J. Teoh120, F. Tepel178, S. Terada69, K. Terashi157, J. Terron85, S. Terzo13, M. Testa50, R.J. Teuscher161;m, T. Theveneaux-Pelzer88, J.P. Thomas19, J. Thomas-Wilsker80, P.D. Thompson19, A.S. Thompson56, L.A. Thomsen179, E. Thomson124, M.J. Tibbetts16, R.E. Ticse Torres88, V.O. Tikhomirov98;ap, Yu.A. Tikhonov111;c, S. Timoshenko100, P. Tipton179, S. Tisserant88, K. Todome159, T. Todorov5; , S. Todorova-Nova131, J. Tojo73, S. Tokar146a, K. Tokushuku69, E. Tolley59, L. Tomlinson87, M. Tomoto105, L. Tompkins145;aq, K. Toms107, B. Tong59, P. Tornambe51, E. Torrence118, H. Torres144, E. Torro Pastor140, J. Toth88;ar, F. Touchard88, D.R. Tovey141, T. Trefzger177, A. Tricoli27, I.M. Trigger163a, S. Trincaz-Duvoid83, M.F. Tripiana13, W. Trischuk161, B. Trocme58, A. Trofymov45, C. Troncon94a, M. Trottier-McDonald16, M. Trovatelli172, L. Truong167a,167c, M. Trzebinski42, A. Trzupek42, J.C-L. Tseng122, P.V. Tsiareshka95, G. Tsipolitis10, N. Tsirintanis9, S. Tsiskaridze13, V. Tsiskaridze51, E.G. Tskhadadze54a, K.M. Tsui62a, I.I. Tsukerman99, V. Tsulaia16, S. Tsuno69, D. Tsybychev150, Y. Tu62b, A. Tudorache28b, V. Tudorache28b, T.T. Tulbure28a, A.N. Tuna59, S.A. Tupputi22a,22b, S. Turchikhin68, D. Turgeman175, I. Turk Cakir4b;as, R. Turra94a,94b, P.M. Tuts38, G. Ucchielli22a,22b, I. Ueda157, M. Ughetto148a,148b, F. Ukegawa164, G. Unal32, A. Undrus27, G. Unel166, F.C. Ungaro91, Y. Unno69, C. Unverdorben102, J. Urban146b, P. Urquijo91, P. Urrejola86, G. Usai8, J. Usui69, L. Vacavant88, V. Vacek130, B. Vachon90, C. Valderanis102, E. Valdes Santurio148a,148b, N. Valencic109, S. Valentinetti22a,22b, A. Valero170, L. Valery13, S. Valkar131, J.A. Valls Ferrer170, W. Van Den Wollenberg109, P.C. Van Der Deijl109, H. van der Graaf109, N. van Eldik154, P. van Gemmeren6, J. Van Nieuwkoop144, I. van Vulpen109, M.C. van Woerden109, M. Vanadia134a,134b, W. Vandelli32, R. Vanguri124, A. Vaniachine160, P. Vankov109, G. Vardanyan180, R. Vari134a, E.W. Varnes7, T. Varol43, D. Varouchas83, A. Vartapetian8, K.E. Varvell152, J.G. Vasquez179, G.A. Vasquez34b, F. Vazeille37, T. Vazquez Schroeder90, J. Veatch57, V. Veeraraghavan7, L.M. Veloce161, F. Veloso128a,128c, S. Veneziano134a, A. Ventura76a,76b, M. Venturi172, N. Venturi161, A. Venturini25, V. Vercesi123a, M. Verducci134a,134b, W. Verkerke109, J.C. Vermeulen109, A. Vest47;at, M.C. Vetterli144;d, O. Viazlo84, I. Vichou169; , T. Vickey141, O.E. Vickey Boeriu141, G.H.A. Viehhauser122, S. Viel16, L. Vigani122, M. Villa22a,22b, M. Villaplana Perez94a,94b, E. Vilucchi50, M.G. Vincter31, V.B. Vinogradov68, C. Vittori22a,22b, I. Vivarelli151, S. Vlachos10, M. Vlasak130, M. Vogel178, P. Vokac130, G. Volpi126a,126b, M. Volpi91, H. von der Schmitt103, E. von Toerne23, V. Vorobel131, K. Vorobev100, M. Vos170, R. Voss32, J.H. Vossebeld77, N. Vranjes14, M. Vranjes Milosavljevic14, V. Vrba129, M. Vreeswijk109, R. Vuillermet32, I. Vukotic33, P. Wagner23, W. Wagner178, H. Wahlberg74, S. Wahrmund47, J. Wakabayashi105, J. Walder75, R. Walker102, W. Walkowiak143, V. Wallangen148a,148b, C. Wang35b, C. Wang36b,88, F. Wang176, H. Wang16, H. Wang43, J. Wang45, J. Wang152, K. Wang90, R. Wang6, S.M. Wang153, T. Wang23, T. Wang38, W. Wang36a, C. Wanotayaroj118, A. Warburton90, C.P. Ward30, HJEP09(217)8 G. Watts140, S. Watts87, B.M. Waugh81, S. Webb86, M.S. Weber18, S.W. Weber177, S.A. Weber31, J.S. Webster6, A.R. Weidberg122, B. Weinert64, J. Weingarten57, C. Weiser51, H. Weits109, P.S. Wells32, T. Wenaus27, T. Wengler32, S. Wenig32, N. Wermes23, M.D. Werner67, P. Werner32, M. Wessels60a, J. Wetter165, K. Whalen118, N.L. Whallon140, A.M. Wharton75, A. White8, M.J. White1, R. White34b, D. Whiteson166, F.J. Wickens133, W. Wiedenmann176, M. Wielers133, C. Wiglesworth39, L.A.M. Wiik-Fuchs23, A. Wildauer103, F. Wilk87, H.G. Wilkens32, H.H. Williams124, S. Williams109, C. Willis93, S. Willocq89, J.A. Wilson19, I. Wingerter-Seez5, F. Winklmeier118, O.J. Winston151, B.T. Winter23, M. Wittgen145, T.M.H. Wolf109, R. Wol 88, M.W. Wolter42, H. Wolters128a,128c, S.D. Worm133, B.K. Wosiek42, J. Wotschack32, M.J. Woudstra87, K.W. Wozniak42, M. Wu58, M. Wu33, S.L. Wu176, X. Wu52, Y. Wu92, T.R. Wyatt87, B.M. Wynne49, S. Xella39, Z. Xi92, D. Xu35a, L. Xu27, B. Yabsley152, S. Yacoob147a, D. Yamaguchi159, Y. Yamaguchi120, A. Yamamoto69, S. Yamamoto157, T. Yamanaka157, K. Yamauchi105, Y. Yamazaki70, Z. Yan24, H. Yang36c, H. Yang176, Y. Yang153, Z. Yang15, W-M. Yao16, Y.C. Yap83, Y. Yasu69, E. Yatsenko5, K.H. Yau Wong23, J. Ye43, S. Ye27, I. Yeletskikh68, E. Yildirim86, K. Yorita174, R. Yoshida6, K. Yoshihara124, C. Young145, C.J.S. Young32, S. Youssef24, D.R. Yu16, J. Yu8, J.M. Yu92, J. Yu67, L. Yuan70, S.P.Y. Yuen23, I. Yusu 30;au, B. Zabinski42, R. Zaidan66, A.M. Zaitsev132;ae, N. Zakharchuk45, J. Zalieckas15, A. Zaman150, S. Zambito59, L. Zanello134a,134b, D. Zanzi91, C. Zeitnitz178, M. Zeman130, A. Zemla41a, J.C. Zeng169, Q. Zeng145, O. Zenin132, T. Zenis146a, D. Zerwas119, D. Zhang92, F. Zhang176, G. Zhang36a;ao, H. Zhang35b, J. Zhang6, L. Zhang51, L. Zhang36a, M. Zhang169, R. Zhang23, R. Zhang36a;av, X. Zhang36b, Z. Zhang119, X. Zhao43, Y. Zhao36b;aw, Z. Zhao36a, A. Zhemchugov68, J. Zhong122, B. Zhou92, C. Zhou176, L. Zhou38, L. Zhou43, M. Zhou150, N. Zhou35c, C.G. Zhu36b, H. Zhu35a, J. Zhu92, Y. Zhu36a, X. Zhuang35a, K. Zhukov98, A. Zibell177, D. Zieminska64, N.I. Zimine68, C. Zimmermann86, S. Zimmermann51, Z. Zinonos57, M. Zinser86, M. Ziolkowski143, L. Zivkovic14, G. Zobernig176, A. Zoccoli22a,22b, M. zur Nedden17, L. Zwalinski32 1 Department of Physics, University of Adelaide, Adelaide, Australia 2 Physics Department, SUNY Albany, Albany NY, United States of America 3 Department of Physics, University of Alberta, Edmonton AB, Canada 4 (a) Department of Physics, Ankara University, Ankara; (b) Istanbul Aydin University, Istanbul; (c) Division of Physics, TOBB University of Economics and Technology, Ankara, Turkey 5 LAPP, CNRS/IN2P3 and Universite Savoie Mont Blanc, Annecy-le-Vieux, France 6 High Energy Physics Division, Argonne National Laboratory, Argonne IL, United States of America 7 Department of Physics, University of Arizona, Tucson AZ, United States of America 8 Department of Physics, The University of Texas at Arlington, Arlington TX, United States of America 9 Physics Department, National and Kapodistrian University of Athens, Athens, Greece 10 Physics Department, National Technical University of Athens, Zografou, Greece 11 Department of Physics, The University of Texas at Austin, Austin TX, United States of America 12 Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan 13 Institut de F sica d'Altes Energies (IFAE), The Barcelona Institute of Science and Technology, Barcelona, Spain 14 Institute of Physics, University of Belgrade, Belgrade, Serbia 15 Department for Physics and Technology, University of Bergen, Bergen, Norway 16 Physics Division, Lawrence Berkeley National Laboratory and University of California, Berkeley CA, United States of America University of Bern, Bern, Switzerland 17 Department of Physics, Humboldt University, Berlin, Germany 18 Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics, HJEP09(217)8 Istanbul, Turkey, Turkey Bologna, Italy 20 (a) Department of Physics, Bogazici University, Istanbul; (b) Department of Physics Engineering, Gaziantep University, Gaziantep; (d) Istanbul Bilgi University, Faculty of Engineering and Natural Sciences, Istanbul,Turkey; (e) Bahcesehir University, Faculty of Engineering and Natural Sciences, 21 Centro de Investigaciones, Universidad Antonio Narino, Bogota, Colombia 22 (a) INFN Sezione di Bologna; (b) Dipartimento di Fisica e Astronomia, Universita di Bologna, 23 Physikalisches Institut, University of Bonn, Bonn, Germany 24 Department of Physics, Boston University, Boston MA, United States of America 25 Department of Physics, Brandeis University, Waltham MA, United States of America 26 (a) Universidade Federal do Rio De Janeiro COPPE/EE/IF, Rio de Janeiro; (b) Electrical Circuits Department, Federal University of Juiz de Fora (UFJF), Juiz de Fora; (c) Federal University of Sao Joao del Rei (UFSJ), Sao Joao del Rei; (d) Instituto de Fisica, Universidade de Sao Paulo, Sao Paulo, Brazil 27 Physics Department, Brookhaven National Laboratory, Upton NY, United States of America 28 (a) Transilvania University of Brasov, Brasov, Romania; (b) Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest; (c) National Institute for Research and Development of Isotopic and Molecular Technologies, Physics Department, Cluj Napoca; (d) University Politehnica Bucharest, Bucharest; (e) West University in Timisoara, Timisoara, Romania 29 Departamento de F sica, Universidad de Buenos Aires, Buenos Aires, Argentina 30 Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom 31 Department of Physics, Carleton University, Ottawa ON, Canada 32 CERN, Geneva, Switzerland 33 Enrico Fermi Institute, University of Chicago, Chicago IL, United States of America 34 (a) Departamento de F sica, Ponti cia Universidad Catolica de Chile, Santiago; (b) Departamento de F sica, Universidad Tecnica Federico Santa Mar a, Valpara so, Chile 35 (a) Institute of High Energy Physics, Chinese Academy of Sciences, Beijing; (b) Department of Physics, Nanjing University, Jiangsu; (c) Physics Department, Tsinghua University, Beijing 100084, China 36 (a) Department of Modern Physics, University of Science and Technology of China, Anhui; (b) School of Physics, Shandong University, Shandong; (c) Department of Physics and Astronomy, Shanghai Key Laboratory for Particle Physics and Cosmology, Shanghai Jiao Tong University, Shanghai; (also a liated with PKU-CHEP), China CNRS/IN2P3, Clermont-Ferrand, France 37 Laboratoire de Physique Corpusculaire, Universite Clermont Auvergne, Universite Blaise Pascal, 38 Nevis Laboratory, Columbia University, Irvington NY, United States of America 39 Niels Bohr Institute, University of Copenhagen, Kobenhavn, Denmark 40 (a) INFN Gruppo Collegato di Cosenza, Laboratori Nazionali di Frascati; (b) Dipartimento di Fisica, Universita della Calabria, Rende, Italy 41 (a) AGH University of Science and Technology, Faculty of Physics and Applied Computer Science, Krakow; (b) Marian Smoluchowski Institute of Physics, Jagiellonian University, Krakow, Poland 42 Institute of Nuclear Physics Polish Academy of Sciences, Krakow, Poland 43 Physics Department, Southern Methodist University, Dallas TX, United States of America 44 Physics Department, University of Texas at Dallas, Richardson TX, United States of America 45 DESY, Hamburg and Zeuthen, Germany 46 Lehrstuhl fur Experimentelle Physik IV, Technische Universitat Dortmund, Dortmund, Germany 47 Institut fur Kern- und Teilchenphysik, Technische Universitat Dresden, Dresden, Germany 48 Department of Physics, Duke University, Durham NC, United States of America 49 SUPA - School of Physics and Astronomy, University of Edinburgh, Edinburgh, United Kingdom 50 INFN Laboratori Nazionali di Frascati, Frascati, Italy 51 Fakultat fur Mathematik und Physik, Albert-Ludwigs-Universitat, Freiburg, Germany 53 (a) INFN Sezione di Genova; (b) Dipartimento di Fisica, Universita di Genova, Genova, Italy 54 (a) E. Andronikashvili Institute of Physics, Iv. Javakhishvili Tbilisi State University, Tbilisi; (b) High Energy Physics Institute, Tbilisi State University, Tbilisi, Georgia 55 II Physikalisches Institut, Justus-Liebig-Universitat Giessen, Giessen, Germany 56 SUPA - School of Physics and Astronomy, University of Glasgow, Glasgow, United Kingdom 57 II Physikalisches Institut, Georg-August-Universitat, Gottingen, Germany 58 Laboratoire de Physique Subatomique et de Cosmologie, Universite Grenoble-Alpes, CNRS/IN2P3, Grenoble, France 59 Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge MA, United States of America 60 (a) Kirchho -Institut fur Physik, Ruprecht-Karls-Universitat Heidelberg, Heidelberg; (b) Physikalisches Institut, Ruprecht-Karls-Universitat Heidelberg, Heidelberg; (c) ZITI Institut fur technische Informatik, Ruprecht-Karls-Universitat Heidelberg, Mannheim, Germany 61 Faculty of Applied Information Science, Hiroshima Institute of Technology, Hiroshima, Japan 62 (a) Department of Physics, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong; (b) Department of Physics, The University of Hong Kong, Hong Kong; (c) Department of Physics and Institute for Advanced Study, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China 63 Department of Physics, National Tsing Hua University, Taiwan, Taiwan 64 Department of Physics, Indiana University, Bloomington IN, United States of America 65 Institut fur Astro- und Teilchenphysik, Leopold-Franzens-Universitat, Innsbruck, Austria 66 University of Iowa, Iowa City IA, United States of America 67 Department of Physics and Astronomy, Iowa State University, Ames IA, United States of America 68 Joint Institute for Nuclear Research, JINR Dubna, Dubna, Russia 69 KEK, High Energy Accelerator Research Organization, Tsukuba, Japan 70 Graduate School of Science, Kobe University, Kobe, Japan 71 Faculty of Science, Kyoto University, Kyoto, Japan 72 Kyoto University of Education, Kyoto, Japan 73 Department of Physics, Kyushu University, Fukuoka, Japan 74 Instituto de F sica La Plata, Universidad Nacional de La Plata and CONICET, La Plata, Argentina 75 Physics Department, Lancaster University, Lancaster, United Kingdom 76 (a) INFN Sezione di Lecce; (b) Dipartimento di Matematica e Fisica, Universita del Salento, 77 Oliver Lodge Laboratory, University of Liverpool, Liverpool, United Kingdom 78 Department of Experimental Particle Physics, Jozef Stefan Institute and Department of Physics, University of Ljubljana, Ljubljana, Slovenia 79 School of Physics and Astronomy, Queen Mary University of London, London, United Kingdom 80 Department of Physics, Royal Holloway University of London, Surrey, United Kingdom 81 Department of Physics and Astronomy, University College London, London, United Kingdom 82 Louisiana Tech University, Ruston LA, United States of America 83 Laboratoire de Physique Nucleaire et de Hautes Energies, UPMC and Universite Paris-Diderot and CNRS/IN2P3, Paris, France 84 Fysiska institutionen, Lunds universitet, Lund, Sweden 85 Departamento de Fisica Teorica C-15, Universidad Autonoma de Madrid, Madrid, Spain 86 Institut fur Physik, Universitat Mainz, Mainz, Germany 87 School of Physics and Astronomy, University of Manchester, Manchester, United Kingdom 88 CPPM, Aix-Marseille Universite and CNRS/IN2P3, Marseille, France 89 Department of Physics, University of Massachusetts, Amherst MA, United States of America 90 Department of Physics, McGill University, Montreal QC, Canada 91 School of Physics, University of Melbourne, Victoria, Australia 92 Department of Physics, The University of Michigan, Ann Arbor MI, United States of America United States of America Republic of Belarus Republic of Belarus 94 (a) INFN Sezione di Milano; (b) Dipartimento di Fisica, Universita di Milano, Milano, Italy 95 B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk, 96 Research Institute for Nuclear Problems of Byelorussian State University, Minsk, 97 Group of Particle Physics, University of Montreal, Montreal QC, Canada 98 P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow, Russia 99 Institute for Theoretical and Experimental Physics (ITEP), Moscow, Russia 100 National Research Nuclear University MEPhI, Moscow, Russia 101 D.V. Skobeltsyn Institute of Nuclear Physics, M.V. Lomonosov Moscow State University, Moscow, Russia 102 Fakultat fur Physik, Ludwig-Maximilians-Universitat Munchen, Munchen, Germany 103 Max-Planck-Institut fur Physik (Werner-Heisenberg-Institut), Munchen, Germany 104 Nagasaki Institute of Applied Science, Nagasaki, Japan 105 Graduate School of Science and Kobayashi-Maskawa Institute, Nagoya University, Nagoya, Japan 106 (a) INFN Sezione di Napoli; (b) Dipartimento di Fisica, Universita di Napoli, Napoli, Italy 107 Department of Physics and Astronomy, University of New Mexico, Albuquerque NM, United States of America Nijmegen/Nikhef, Nijmegen, Netherlands Amsterdam, Netherlands 108 Institute for Mathematics, Astrophysics and Particle Physics, Radboud University 109 Nikhef National Institute for Subatomic Physics and University of Amsterdam, 110 Department of Physics, Northern Illinois University, DeKalb IL, United States of America 111 Budker Institute of Nuclear Physics, SB RAS, Novosibirsk, Russia 112 Department of Physics, New York University, New York NY, United States of America 113 Ohio State University, Columbus OH, United States of America 114 Faculty of Science, Okayama University, Okayama, Japan 115 Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman OK, United States of America 116 Department of Physics, Oklahoma State University, Stillwater OK, United States of America 117 Palacky University, RCPTM, Olomouc, Czech Republic 118 Center for High Energy Physics, University of Oregon, Eugene OR, United States of America 119 LAL, Univ. Paris-Sud, CNRS/IN2P3, Universite Paris-Saclay, Orsay, France 120 Graduate School of Science, Osaka University, Osaka, Japan 121 Department of Physics, University of Oslo, Oslo, Norway 122 Department of Physics, Oxford University, Oxford, United Kingdom 123 (a) INFN Sezione di Pavia; (b) Dipartimento di Fisica, Universita di Pavia, Pavia, Italy 124 Department of Physics, University of Pennsylvania, Philadelphia PA, United States of America 125 National Research Centre \Kurchatov Institute" B.P.Konstantinov Petersburg Nuclear Physics Institute, St. Petersburg, Russia United States of America 126 (a) INFN Sezione di Pisa; (b) Dipartimento di Fisica E. Fermi, Universita di Pisa, Pisa, Italy 127 Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh PA, 128 (a) Laboratorio de Instrumentaca~o e F sica Experimental de Part culas - LIP, Lisboa; (b) Faculdade de Ci^encias, Universidade de Lisboa, Lisboa; (c) Department of Physics, University of Coimbra, Coimbra; (d) Centro de F sica Nuclear da Universidade de Lisboa, Lisboa; (e) Departamento de Fisica, Universidade do Minho, Braga; (f) Departamento de Fisica Teorica y del Cosmos and CAFPE, Universidad de Granada, Granada (Spain); (g) Dep Fisica and CEFITEC of Faculdade de Ciencias e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal 129 Institute of Physics, Academy of Sciences of the Czech Republic, Praha, Czech Republic Vergata, Roma, Italy Roma, Italy 131 Faculty of Mathematics and Physics, Charles University in Prague, Praha, Czech Republic 132 State Research Center Institute for High Energy Physics (Protvino), NRC KI, Russia 133 Particle Physics Department, Rutherford Appleton Laboratory, Didcot, United Kingdom 134 (a) INFN Sezione di Roma; (b) Dipartimento di Fisica, Sapienza Universita di Roma, Roma, Italy 135 (a) INFN Sezione di Roma Tor Vergata; (b) Dipartimento di Fisica, Universita di Roma Tor 136 (a) INFN Sezione di Roma Tre; (b) Dipartimento di Matematica e Fisica, Universita Roma Tre, 137 (a) Faculte des Sciences Ain Chock, Reseau Universitaire de Physique des Hautes Energies Universite Hassan II, Casablanca; (b) Centre National de l'Energie des Sciences Techniques Nucleaires, Rabat; (c) Faculte des Sciences Semlalia, Universite Cadi Ayyad, LPHEA-Marrakech; (d) Faculte des Sciences, Universite Mohamed Premier and LPTPM, Oujda; (e) Faculte des sciences, Universite Mohammed V, Rabat, Morocco 138 DSM/IRFU (Institut de Recherches sur les Lois Fondamentales de l'Univers), CEA Saclay (Commissariat a l'Energie Atomique et aux Energies Alternatives), Gif-sur-Yvette, France 139 Santa Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz CA, United States of America 140 Department of Physics, University of Washington, Seattle WA, United States of America 141 Department of Physics and Astronomy, University of She eld, She eld, United Kingdom 142 Department of Physics, Shinshu University, Nagano, Japan 143 Fachbereich Physik, Universitat Siegen, Siegen, Germany 144 Department of Physics, Simon Fraser University, Burnaby BC, Canada 145 SLAC National Accelerator Laboratory, Stanford CA, United States of America 146 (a) Faculty of Mathematics, Physics & Informatics, Comenius University, Bratislava; (b) Department of Subnuclear Physics, Institute of Experimental Physics of the Slovak Academy of Sciences, Kosice, Slovak Republic 147 (a) Department of Physics, University of Cape Town, Cape Town; (b) Department of Physics, University of Johannesburg, Johannesburg; (c) School of Physics, University of the Witwatersrand, Johannesburg, South Africa United States of America 148 (a) Department of Physics, Stockholm University; (b) The Oskar Klein Centre, Stockholm, Sweden 149 Physics Department, Royal Institute of Technology, Stockholm, Sweden 150 Departments of Physics & Astronomy and Chemistry, Stony Brook University, Stony Brook NY, 151 Department of Physics and Astronomy, University of Sussex, Brighton, United Kingdom 152 School of Physics, University of Sydney, Sydney, Australia 153 Institute of Physics, Academia Sinica, Taipei, Taiwan 154 Department of Physics, Technion: Israel Institute of Technology, Haifa, Israel 155 Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv University, Tel Aviv, Israel of Tokyo, Tokyo, Japan 156 Department of Physics, Aristotle University of Thessaloniki, Thessaloniki, Greece 157 International Center for Elementary Particle Physics and Department of Physics, The University 158 Graduate School of Science and Technology, Tokyo Metropolitan University, Tokyo, Japan 159 Department of Physics, Tokyo Institute of Technology, Tokyo, Japan 160 Tomsk State University, Tomsk, Russia, Russia 161 Department of Physics, University of Toronto, Toronto ON, Canada 162 (a) INFN-TIFPA; (b) University of Trento, Trento, Italy, Italy 163 (a) TRIUMF, Vancouver BC; (b) Department of Physics and Astronomy, York University, Toronto ON, Canada and Engineering, University of Tsukuba, Tsukuba, Japan 164 Faculty of Pure and Applied Sciences, and Center for Integrated Research in Fundamental Science 166 Department of Physics and Astronomy, University of California Irvine, Irvine CA, 167 (a) INFN Gruppo Collegato di Udine, Sezione di Trieste, Udine; (b) ICTP, Trieste; (c) Dipartimento di Chimica, Fisica e Ambiente, Universita di Udine, Udine, Italy 168 Department of Physics and Astronomy, University of Uppsala, Uppsala, Sweden 169 Department of Physics, University of Illinois, Urbana IL, United States of America 170 Instituto de Fisica Corpuscular (IFIC) and Departamento de Fisica Atomica, Molecular y Nuclear and Departamento de Ingenier a Electronica and Instituto de Microelectronica de Barcelona (IMB-CNM), University of Valencia and CSIC, Valencia, Spain 171 Department of Physics, University of British Columbia, Vancouver BC, Canada 172 Department of Physics and Astronomy, University of Victoria, Victoria BC, Canada 173 Department of Physics, University of Warwick, Coventry, United Kingdom 174 Waseda University, Tokyo, Japan 175 Department of Particle Physics, The Weizmann Institute of Science, Rehovot, Israel 176 Department of Physics, University of Wisconsin, Madison WI, United States of America 177 Fakultat fur Physik und Astronomie, Julius-Maximilians-Universitat, Wurzburg, Germany 178 Fakultat fur Mathematik und Naturwissenschaften, Fachgruppe Physik, Bergische Universitat Wuppertal, Wuppertal, Germany 179 Department of Physics, Yale University, New Haven CT, United States of America 180 Yerevan Physics Institute, Yerevan, Armenia 181 Centre de Calcul de l'Institut National de Physique Nucleaire et de Physique des Particules (IN2P3), Villeurbanne, France a Also at Department of Physics, King's College London, London, United Kingdom b Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan c Also at Novosibirsk State University, Novosibirsk, Russia d Also at TRIUMF, Vancouver BC, Canada e Also at Department of Physics & Astronomy, University of Louisville, Louisville, KY, United States of America f Also at Physics Department, An-Najah National University, Nablus, Palestine g Also at Department of Physics, California State University, Fresno CA, United States of America h Also at Department of Physics, University of Fribourg, Fribourg, Switzerland i Also at Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona, Spain j Also at Departamento de Fisica e Astronomia, Faculdade de Ciencias, Universidade do Porto, Portugal k Also at Tomsk State University, Tomsk, Russia, Russia l Also at Universita di Napoli Parthenope, Napoli, Italy m Also at Institute of Particle Physics (IPP), Canada Russia United States of America South Africa n Also at Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest, Romania o Also at Department of Physics, St. Petersburg State Polytechnical University, St. Petersburg, p Also at Department of Physics, The University of Michigan, Ann Arbor MI, q Also at Centre for High Performance Computing, CSIR Campus, Rosebank, Cape Town, r Also at Louisiana Tech University, Ruston LA, United States of America s Also at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona, Spain t Also at Graduate School of Science, Osaka University, Osaka, Japan u Also at Institute for Mathematics, Astrophysics and Particle Physics, Radboud University United States of America v Also at Department of Physics, The University of Texas at Austin, Austin TX, Switzerland NY, United States of America United States of America Technology, Barcelona, Spain av Also at CPPM, Aix-Marseille Universite and CNRS/IN2P3, Marseille, France Also at LAL, Univ. Paris-Sud, CNRS/IN2P3, Universite Paris-Saclay, Orsay, France al Also at School of Physics, Sun Yat-sen University, Guangzhou, China Also at Institute for Nuclear Research and Nuclear Energy (INRNE) of the Bulgarian Academy of Sciences, So a, Bulgaria an Also at Faculty of Physics, M.V.Lomonosov Moscow State University, Moscow, Russia ap Also at National Research Nuclear University MEPhI, Moscow, Russia aq Also at Department of Physics, Stanford University, Stanford CA, United States of America ar Also at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest, ai Also at International School for Advanced Studies (SISSA), Trieste, Italy aj Also at Department of Physics and Astronomy, University of South Carolina, Columbia SC, Hungary Deceased x Also at CERN, Geneva, Switzerland y Also at Georgian Technical University (GTU),Tbilisi, Georgia z Also at Ochadai Academic Production, Ochanomizu University, Tokyo, Japan aa Also at Manhattan College, New York NY, United States of America ab Also at Academia Sinica Grid Computing, Institute of Physics, Academia Sinica, Taipei, Taiwan ac Also at School of Physics, Shandong University, Shandong, China ad Also at Department of Physics, California State University, Sacramento CA, ae Also at Moscow Institute of Physics and Technology State University, Dolgoprudny, Russia ag Also at Eotvos Lorand University, Budapest, Hungary ah Also at Departments of Physics & Astronomy and Chemistry, Stony Brook University, Stony Brook [1] M. 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Calvet, S. Calvet. Top-quark mass measurement in the all-hadronic \( t\overline{t} \) decay channel at \( \sqrt{s}=8 \) TeV with the ATLAS detector, Journal of High Energy Physics, 2017, 118, DOI: 10.1007/JHEP09(2017)118