Measurement of the jet mass in highly boosted t t-bar events from pp collisions at sqrt(s) = 8 TeV

TL;DR

This paper reports the first measurement of jet mass in highly boosted top quark events from proton-proton collisions at 8 TeV, using CMS data to test top quark production models and extract the top quark mass.

Contribution

It provides the first measurement of jet mass in boosted top quark events at 8 TeV and assesses its sensitivity to the top quark mass.

Findings

Jet mass distribution measured for highly boosted top quarks.

The distribution's peak position is sensitive to the top quark mass.

Results are used to test and validate modeling of boosted top quark production.

Abstract

The first measurement of the jet mass m[jet] of top quark jets produced in t t-bar events from pp collisions at sqrt(s) = 8 TeV is reported for the jet with the largest transverse momentum pt in highly boosted hadronic top quark decays. The data sample, collected with the CMS detector, corresponds to an integrated luminosity of 19.7 inverse femtobarns. The measurement is performed in the lepton+jets channel in which the products of the semileptonic decay t to bW with W to l nu where l is an electron or muon, are used to select t t-bar events with large Lorentz boosts. The products of the fully hadronic decay t to bW with W to q q'-bar are reconstructed using a single Cambridge-Aachen jet with distance parameter R = 1.2, and pt > 400 GeV. The t t-bar cross section as a function of m[jet] is unfolded at the particle level and is used to test the modelling of highly boosted top quark production. The peak position of the m[jet] distribution is sensitive to the top quark mass m[t], and the data are used to extract a value of m[t] to assess this sensitivity.

Equations

$$m_{\text{jet}}^{2}=\Bigl{(}\sum_{i~{}\text{in jet}}p_{i}\Bigr{)}^{2},$$

$$\text{abs}\Delta \varphi (\{\text{Pe}\text{or}\text{jet}\},\text{ptvecmiss})-1.5<\text{ptmiss}/50\text{GeV},$$

$$m_{\text{PQt}}=$$

$$=$$

Full text

0.1 Introduction

The top quark may play a special role in the standard model (SM) of particle physics owing to its large mass and its possible importance in electroweak symmetry breaking [1, 2]. Measurements of \ttbarproduction provide crucial information about the accuracy of the SM near the electroweak scale [3, 4], and in assessing the predictions of quantum chromodynamics (QCD) at large mass scales. In turn, they can be used to determine the fundamental parameters of the theory, such as the strong coupling constant or the top quark mass [5, 6].

Previous differential measurements of the \ttbarproduction cross section [7, 8, 9, 10, 11, 12, 13, 14, 15] at the Fermilab Tevatron and CERN LHC show excellent agreement with SM predictions. However, investigations of top quarks with very large transverse momenta $\pt$ have proven to be difficult, since in this kinematic range the decays of the top quark to fully hadronic final states become highly collimated and merge into single jets. In this highly boosted regime, the \ttbarreconstruction efficiency deteriorates for previous, more-traditional measurements. Special reconstruction techniques based on jet substructure are often used to improve the measurements [16, 17] or to implement searches for new physics [18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28]. A detailed understanding of jet substructure observables, and especially the jet mass $m_{\text{jet}}$, is crucial for LHC analyses of highly boosted topologies. While measurements of $m_{\text{jet}}$ corrected to the particle level have been carried out for light-quark and gluon jets [29, 30], the $m_{\text{jet}}$ distribution for highly boosted top quarks has not yet been measured.

Apart from testing the simulation of $m_{\text{jet}}$ in fully hadronic top quark decays, the location of the peak of the $m_{\text{jet}}$ distribution is sensitive to the top quark mass $m_{\PQt}$ [31]. This measurement therefore provides an alternative method of determining $m_{\PQt}$ in the boosted regime, independent of previous mass measurements [32, 33, 34, 35, 36, 37]. Calculations from first principles have been performed in soft collinear effective theory [38, 39, 40, 41] for the dijet invariant mass distribution from highly boosted top quark production in $\Pep\Pem$ collisions [42, 43], and work is ongoing to extend this to the LHC environment [44, 45]. Such calculations account for perturbative and nonperturbative effects, and provide particle-level predictions. Once predictions for the LHC become available, the measurement of the $m_{\text{jet}}$ distribution can lead to an extraction of $m_{\PQt}$ without the ambiguities that arise from the unknown relation between $m_{\PQt}$ in a well-defined renormalisation scheme and the top quark mass parameter used in Monte Carlo (MC) simulations [45, 46, 47, 48].

We present the first measurement of the differential \ttbarproduction cross section as a function of the leading-jet mass, where leading refers to the jet with the highest $\pt$. The measurement is based on data from $\Pp\Pp$ collisions at $\sqrt{s}=8\TeV$, recorded by the CMS experiment at the LHC in 2012 and corresponding to an integrated luminosity of 19.7\fbinv. It is performed on \ttbarevents in which the leading jet includes all $\PQt\to\PQb\PWp\to\PQb\qqbar^{\prime}$ decay products. The other top quark is required to decay through the semileptonic mode $\PAQt\to\PAQb\PWm\to\PAQb\ell\PAGn_{\ell}$, where $\ell$ can be either an electron or muon. The use of charge-conjugate modes is implied throughout this article. The semileptonic top quark decay serves as a means for selecting \ttbarevents without biasing the $m_{\text{jet}}$ distribution from the fully hadronic top quark decay. The highly boosted top quark jets used in the measurement are defined through the Cambridge–Aachen (CA) jet-clustering algorithm [49, 50] with a distance parameter $R=1.2$ and $\pt>400\GeV$. The $m_{\text{jet}}$ distribution is unfolded to the particle level and compared to predictions from MC simulations. The measurement is also normalised to a fiducial-region total cross section defined below, and shows the expected sensitivity to the value of $m_{\PQt}$. An extraction of the value of $m_{\PQt}$ is performed to assess the overall sensitivity of the measurement.

0.2 The CMS detector

The central feature of the CMS detector is a superconducting solenoid of 6\unitm internal diameter, providing a magnetic field of 3.8\unitT. A silicon pixel and strip tracker, a lead tungstate crystal electromagnetic calorimeter (ECAL), and a brass and scintillator hadron calorimeter (HCAL), each composed of a barrel and two endcap sections reside within the magnetic volume. In addition to the barrel and endcap detectors, CMS has extensive forward calorimetry. Muons are detected using four layers of gas-ionization detectors embedded in the steel flux-return yoke of the magnet. The inner tracker measures charged particle trajectories within the pseudorapidity range $\abs{\eta}<2.5$. A two-stage trigger system [51] is used to select for analysis $\Pp\Pp$ collisions of scientific interest. A more detailed description of the CMS detector, together with a definition of the coordinate system and relevant kinematic variables, can be found in Ref. [52].

0.3 Event reconstruction

The CMS experiment uses a particle-flow (PF) event reconstruction [53, 54], which aggregates input from all subdetectors. This information includes charged particle tracks from the tracking system and energies deposited in the ECAL and HCAL, taking advantage of the granularity of the subsystems. Particles are classified as electrons, muons, photons, and charged and neutral hadrons. Primary vertices are reconstructed using a deterministic annealing filter algorithm [55]. The vertex with the largest sum in the associated track $\pt^{2}$ values is taken to be the primary event vertex.

Muons are detected and measured in the pseudorapidity range $\abs{\eta}<2.1$ using the information collected in the muon and tracking detectors [56]. Tracks from muon candidates must be consistent with a muon originating from the primary event vertex, and satisfy track-fit quality requirements [57].

Electrons are reconstructed in the range $\abs{\eta}<2.1$, by combining tracking information with energy deposits in the ECAL [58, 59]. Electron candidates are required to originate from the primary event vertex. Electrons are identified through the information on the energy distribution in their shower, the track quality, the spatial match between the track and electromagnetic cluster, and the fraction of total cluster energy in the HCAL. Electron candidates that are consistent with originating from photon conversions in the detector material are rejected.

Since the top quark decay products can be collimated at high values of top quark \pt, no isolation requirements on the leptons are imposed in either the trigger or in the offline selections (see Section 0.4). The imbalance in event $\vec{\pt}$ is quantified as the missing transverse momentum vector \ptvecmiss, defined as the projection on the plane perpendicular to the beams of the negative vector sum of the momenta of all PF candidates in the event. Its magnitude is referred to as \ptmiss.

The PF candidates are clustered into jets by using the \FASTJET3.0 software package [60]. Charged hadrons associated with event vertices other than the primary event vertex are removed prior to jet clustering. Isolated leptons (either electron or muon) are not part of the input list for jet finding [53, 54]. Small-radius jets are clustered with the anti-\ktjet-clustering algorithm [61] with a distance parameter $R=0.5$ (AK5 jets). These small-radius jets are used at the trigger level, in the first steps of the event selection, and for the identification of jets coming from the hadronisation of $\PQb$ quarks. If a nonisolated lepton candidate is found within the angular distance ${\Delta R<0.5}$ of an AK5 jet, its four-momentum is subtracted from that of the jet to avoid double counting of energy and ensure proper jet energy corrections. The angular distance is given by $\Delta R=\sqrt{\smash[b]{(\Delta\phi)^{2}+(\Delta\eta)^{2}}}$, where $\Delta\phi$ and $\Delta\eta$ are the differences in azimuthal angle (in radians) and pseudorapidity, respectively, between the directions of the lepton and jet. Large-radius jets are obtained by using the CA jet-clustering algorithm [49, 50] with $R=1.2$ (CA12 jets). When a lepton candidate is found among the PF candidates clustered into a CA12 jet, its four-momentum is subtracted from that of the CA12 jet. In this paper, the unmodified term ”jet” will refer to the broad CA12 jets.

All jets could contain neutral particles from additional $\Pp\Pp$ collisions in the same or nearby beam crossings (pileup). This extra contribution is subtracted based on the average expectation of the pileup in the jet catchment area [62]. This is done by calculating a correction for the average offset energy density in each event as a function of the number of primary vertices [63, 64]. The AK5 jets are identified as originating from the fragmentation of a $\PQb$ quark with the combined secondary vertex algorithm (CSV) [65]. A tight operating point is used, which has a misidentification probability of 0.1% for tagging light-parton jets with an average \ptof about 80\GeV, and an efficiency of about 50% for a heavy-flavour jet with $\pt$ in the range 50–160\GeV. Above 160\GeV, the efficiency decreases gradually to about 30% for a $\pt$ value of 400\GeV [65]. All jets are required to satisfy quality selections to minimize the impact of calorimeter noise and other sources of misidentified jets [66]. Events are also required to satisfy selection criteria to remove events with large values of $\ptmiss$ from calorimeter noise, as described in Ref. [67].

The jet mass $m_{\text{jet}}$ is calculated from the four-vectors $p_{i}$ of all $i$ PF particles clustered into a jet:

[TABLE]

where the pion mass is assigned to all charged hadrons. The reconstruction of $m_{\text{jet}}$ for CA12 jets is studied by using a sample of highly boosted $\PW\to\PQq\PAQq^{\prime}$ decays merged into a single jet, as described in Section 0.5.5.

0.4 Trigger and data

The data were recorded by using single-lepton triggers with no isolation requirement applied to the leptons. Events in the muon+jets channel use a trigger that requires at least one muon with $\pt>40$\GeVand $\abs{\eta}<2.1$. The efficiency for this trigger, measured in a $\PZ\to\mu^{+}\mu^{-}$ sample, is 95% for muons measured within $\abs{\eta}<0.9$, 85% for muons within $0.9<\abs{\eta}<1.2$, and 83% for $1.2<\abs{\eta}<2.1$.

The trigger for the electron+jets channel requires at least one electron with $\pt>30$\GeVin conjunction with two AK5 jets that have $\pt>100$ and $>25$\GeV, for the leading and next-to-leading AK5 jet, respectively. Events are also included if triggered by a single AK5 jet with $\pt>320\GeV$. The additional events obtained through this single-jet trigger often contain an electron merged into a jet that cannot be resolved at the trigger stage. The resulting combined trigger efficiency is 90% for events with a leading AK5 jet with $\pt<320\GeV$. Above this value, the trigger has a turn-on behaviour and is fully efficient above a value of $350\GeV$. The trigger efficiencies are measured in data and simulation using a tag-and-probe method in \Z/$\gamma^{*}(\to\ell\ell)$+jets and dileptonic \ttbarevents. Small differences between data and simulation are corrected for by applying scale factors to the simulated events.

Top quark events, produced via the strong and electroweak interactions, are simulated with the next-to-leading-order (NLO) generator \POWHEG1.380 [68, 69, 70, 71, 72] with a value of $m_{\PQt}=172.5\GeV$. The $\PW(\to\ell\nu)$+jets and $\Z/\gamma^{*}(\to\ell\ell)$+jets processes are simulated with \MADGRAPH5.1.5.11 [73], where Madspin [74] is used for the decay of heavy resonances. Diboson production processes (\PW\PW, \PW\Z, and $\Z\Z$) are simulated with \PYTHIA 6.424 [75]. Simulated multijet samples are generated in \MADGRAPH, but constitute a negligible background. For the estimation of systematic uncertainties, additional \ttbarsamples are generated with \MCATNLOv3.41 [76] or with \MADGRAPHfor seven values of $m_{\PQt}$ ranging from 166.5 to 178.5\GeV.

All the samples generated in \MADGRAPHand \POWHEGare interfaced with \PYTHIA 6 for parton showering and fragmentation (referred to as \MADGRAPH+\PYTHIAand \POWHEG+\PYTHIA, respectively). The MLM algorithm [77] used in \MADGRAPHis applied during the parton matching to avoid double counting of parton configurations. The \MADGRAPHsamples use the CTEQ6L [78] parton distribution functions (PDFs). The \POWHEG\ttbarsample uses the CT10 [79] PDFs, whereas the single top quark processes use the CTEQ6M [80] PDFs. The \PYTHIA6 Z2* tune [81, 82] is used to model the underlying event. Top quark events produced with \MCATNLOuse the CTEQ6M PDF set and \HERWIG6.520 [83] for parton showering and fragmentation (\MCATNLO+\HERWIG). The default \HERWIGtune is used to model the underlying event.

The normalisations of the simulated event samples are taken from the NLO calculations of their cross sections that contain the next-to-next-to-leading-logarithm (NNLL) soft-gluon resummations for single top quark production [84], the next-to-next-to-leading-order (NNLO) calculations for $\PW(\to\ell\nu)$+jets and $\Z/\gamma^{*}(\to\ell\ell)$+jets [85, 86, 87], and the NLO calculation for diboson production [88]. The normalisation of the \ttbarsimulation is obtained from QCD NNLO calculations, again including resummation of NNLL soft-gluon terms [89, 90, 91, 92, 93, 94, 95].

A detailed simulation of particle propagation through the CMS apparatus and detector response is performed with \GEANTfourv9.2 [96]. For all simulated samples, the hard collision is overlaid with simulated minimum-bias collisions. The resulting events are weighted to reproduce the pileup distribution measured in data. The same event reconstruction software is used for data and simulated events. The resolutions and efficiencies for reconstructed objects are corrected to match those measured in data [58, 56, 65, 97, 64].

0.5 Cross section measurement

0.5.1 Strategy

The measurement is carried out in the $\ell$+jets channel, which allows the selection of a pure \ttbarsample because of its distinct signature at large top quark boosts. The measurement is based on choosing kinematic quantities that do not bias the $m_{\text{jet}}$ distribution from fully hadronic top quark decays. A bias would be introduced by, e.g. selecting the leading jet based on the number of subjets, or requiring a certain maximum value of the $N$-subjettiness [98, 99], as applied in common top quark tagging algorithms [100, 101, 102, 103, 104]. Such a selection would lead to a distinct three-prong structure of the jet and thus reject events with one quark being soft or collinear with respect to the momentum of the top quark decay.

The fiducial region chosen for this investigation is studied through simulations at the particle level (defined by all particles with lifetimes longer than $10^{-8}$ s). The exact selection is detailed below. It relies on having a highly boosted semileptonic top quark decay, where the lepton from $\PW\to\ell\nu_{\ell}$ is close in $\DR$ to the jet from the hadronisation of the accompanying $\PQb$ quark ($\PQb$ jet). A second high-\ptjet is selected, which is assumed to originate from the fully hadronic top quark decay. A veto on additional jets is employed, which ensures that the fully hadronic decay is merged into a single jet. The jet veto is also beneficial for calculating higher-order terms, as it suppresses the size of nonglobal logarithms [105], which appear because of the sensitivity of the jet mass to radiation in only a part of the phase space [106]. The event selection at the reconstruction level is chosen to ensure high efficiency while reducing non-\ttbarbackgrounds. Finally, the $m_{\text{jet}}$ distribution is unfolded for experimental effects and then compared to different MC predictions at the particle level. A measurement of the normalised $m_{\text{jet}}$ distribution is performed as well, where the normalisation is performed by using the total measured \ttbarcross section in the fiducial phase-space region.

0.5.2 Definition of the fiducial phase space

The \ttbarcross section as a function of the mass of the leading jet is unfolded to the particle level, correcting for experimental effects, with the fiducial phase space at the particle level defined through the selection described below.

As mentioned previously, the measurement is performed in the $\ell$+jets channel, where $\ell$ refers to an electron or muon from the $\PW$ boson decay. The $\tau$ lepton decays are not considered as part of the signal. Leptons are required to be within $\abs{\eta}<2.1$ and have $\pt>45\GeV$. Jets are clustered by using the CA algorithm with a distance parameter $R=1.2$ and required to have $\abs{\eta}<2.5$. The value of $R$ is chosen to optimize the relationship between obtaining a sufficient number of events and maintaining a narrow width in the jet-mass distribution. The four-momentum of the leading lepton is subtracted from the four-momentum of a jet if the lepton is found within an angular range of ${\Delta R<1.2}$ of the jet axis. Events are selected if at least one jet has $p_{\mathrm{T,1}}>400\GeV$ and a second jet has $p_{\mathrm{T,2}}>150\GeV$. The leading jet in \ptis assumed to originate from the $\PQt\to\PW\PQb\to\PQq\PAQq^{\prime}\PQb$ decay, merged into a single jet. Consequently, the second jet is considered to originate from the fragmented $\PQb$ quark of the semileptonic top quark decay. To select events with a highly boosted topology, a veto is employed on additional jets with $p_{\text{T,veto}}>150\GeV$. The jet veto removes about 16% of the signal events, but increases the fraction of fully merged top quark decays to about 40%, where an event is called fully merged if the maximum distance in $\DR$ between the leading jet at the particle level and each individual parton from the fully hadronic top quark decay is smaller than $1.2$.

Two additional selection criteria are introduced to ensure that the leading jet includes all particles from the fully hadronic top quark decay. The angular difference $\DR(\ell,\text{j}_{2})$ between the lepton and the second jet has to be smaller than 1.2. This, together with the veto on additional jets, ensures that the top quarks are produced back-to-back in the transverse plane. In addition, the invariant mass of the leading jet has to be greater than the invariant mass of the combination of the second jet and the lepton, $m_{\text{jet},1}>m_{\text{jet},2+\ell}$. This improves the choice of the leading jet as originating from the fully hadronic top quark decay.

The simulated distribution of the jet mass at the particle level after this selection is shown in Fig. 1. The distribution of all jets passing the particle-level selection is compared to distributions in jet mass from fully merged and not merged \ttbardecays. After the selection outlined above, jets that do not originate from fully merged top quark decays with a fully hadronic final state are expected to constitute about 35% of all jets in the final data sample, as determined by using the \POWHEG+\PYTHIAsimulation.

0.5.3 Selection of events at the reconstruction level

A selection is applied at the reconstruction level to obtain an enriched \ttbarsample with high-\pttop quarks, based on leptons without an isolation requirement. As a second step, high-\ptjets are required to be kinematically similar to those selected at the particle level. Comparable kinematic properties between the reconstruction and particle levels lead to small bin-to-bin migrations and therefore to small corrections when unfolding the data.

Selected events must contain exactly one muon or electron with $\pt>45\GeV$ and $\abs{\eta}<2.1$. Events with more than one lepton are vetoed to suppress contributions from dileptonic \ttbardecays. To select highly boosted \ttbarevents, at least one AK5 jet is required to have $\pt>150\GeV$ and another AK5 jet $\pt>50\GeV$, where both jets have to fulfil $\abs{\eta}<2.4$. The suppression of background from multijet production is accomplished by using a two-dimensional (2D) isolation variable that is efficient at large top quark boosts, yet notably reduces multijet background. This 2D isolation requires the angular difference between the lepton and the nearest AK5 jet directions $\DR_{\text{min}}(\text{lepton, jets})$ to be greater than $0.5$, or the perpendicular component of the lepton momentum relative to the nearest AK5 jet $p_{\text{rel,T}}$ to be larger than $25\GeV$. In the calculation of these quantities, only AK5 jets with $\pt>25\GeV$ are considered. The efficiency of the 2D isolation requirement has been studied in data and simulation by using $\Z/\gamma^{*}(\to\ell\ell)$+jets events [26].

A requirement on $\ptmiss>20\GeV$ and on the scalar sum $\ptmiss+\pt^{\ell}>150\GeV$ reduces the contribution from multijet and $\Z/\gamma^{*}(\to\ell\ell)$+jets production, where $\pt^{\ell}$ is the lepton transverse momentum. Given the presence of two $\PQb$ quarks in the events, at least one AK5 jet is required to be identified as originating from the fragmentation of a $\PQb$ quark by using the CSV algorithm, which reduces the contribution from $\PW$+jets production. The electron channel includes an additional topological selection criterion to suppress the remaining residual contribution from multijet production:

[TABLE]

with $\Delta\phi$ measured in radians and \ptmissin \GeV. This criterion rejects events in which $\ptvecmiss$ points along the transverse momentum vector of the leading jet or the lepton. After these requirements, the background contribution from multijet production is negligible.

The selection procedure outlined above results in a \ttbarsample with high purity and selection efficiency at large top quark \pt. In addition, events are selected with kinematic requirements similar to those at the particle level. For each event to pass the selection, at least one jet is required with $\pt>400\GeV$ and another with $\pt>150\GeV$, where both jets have to fulfil $\abs{\eta}<2.5$. Contributions from not fully merged \ttbarevents are suppressed with a veto on additional jets with transverse momentum $\pt>150\GeV$ and $\abs{\eta}<2.5$. The jet veto has an efficiency of $93\%$ for fully-merged signal events. The fraction of fully merged events with a back-to-back topology is further enhanced by selecting events with an angular difference $\DR(\ell,\text{j}_{2})<1.2$ between the directions of the lepton and the subleading jet. To ensure that the leading jet originates from the fully merged top quark decay, its invariant mass is required to be larger than the mass of the subleading jet. With these selection criteria, the reconstruction efficiency for \ttbarevents where one top quark decays semileptonically in the fiducial region of the measurement is 23.2%. Several of the above criteria are relaxed in the unfolding procedure to define sideband regions included as additional bins in the response matrix, increasing thereby the reconstruction efficiency.

After the selection procedure, the contribution of non-signal \ttbarevents from \ttbardecays to the $\tau$+jets, dilepton, and all-jets channels constitute, respectively, $7.3\%$, $11.6\%$, and $0.4\%$ of the selected events. These contributions are accounted for in the unfolding.

The distributions in $\pt$ and $\eta$ for the leading jet in selected events are shown in Fig. 2 from data and simulation. The mass distribution of the leading jet at the reconstruction level is shown in Fig. 3 for the \ptregions of $400<\pt<500\GeV$ (left) and $\pt>500\GeV$ (right). In these plots the $\ttbar$ simulation is scaled such that the number of simulated events matches the number of selected events observed in data. Overall good agreement between data and the predictions is observed. The slight slope in the data/MC ratio of the jet mass distribution in Fig. 3 (left) is covered by the jet energy and mass scale uncertainties, as described below.

Table 0.5.3 shows the total number of events observed in data together with the total number of signal and background events determined from simulation.

0.5.4 Unfolding from the reconstruction level to the particle level

The transformation from the reconstruction to the particle level is carried out through a regularised unfolding based on a least-squares fit, implemented in the TUnfold [107] framework. This procedure suppresses the statistical fluctuations by a regularisation with respect to the count in each bin. The optimal regularisation strength is determined through a minimization of the average global correlation coefficient of the output bins [108]. Contributions from background processes such as $\PW$+jets, single top quark, and multijet production are determined from simulation and subtracted from the data prior to the unfolding. Non-signal \ttbarevents are accounted for in the unfolding by including them in the response matrix, described below.

The response matrix is evaluated by using $\ttbar$ events simulated with $\POWHEG{}+\PYTHIA$. It is obtained for the two regions in the leading-jet \ptof $400<\pt<500\GeV$ and $\pt>500\GeV$. This division is needed to account for the distribution of the $\pt$ spectrum. The response matrix includes three additional sideband regions to account for migrations in and out of the phase-space region of the measurement. These are obtained for a lower leading-jet $\pt$ of $300<\pt<400\GeV$, a lower second-leading-jet $\pt$ of $100<\pt<150\GeV$, and a higher veto-jet $\pt$ of $150<\pt<200\GeV$. Events that are reconstructed, but do not pass the particle-level selections, are also included in the response matrix. The electron and muon channels are combined, and the combined distribution is unfolded to ensure a sufficient number of events in the unfolding procedure. The electron and muon channels are also unfolded separately, and the results are compared to verify their consistency.

0.5.5 Uncertainties

Statistical uncertainties

Statistical uncertainties in the unfolding procedure arise from three sources. The dominant source reflects the statistical fluctuations in the input data. Second are the uncertainties from the finite number of simulated events used to calculate the response matrix. The third source reflects the statistical uncertainties in the simulation of the background processes. After the unfolding, a total statistical uncertainty is obtained for each bin of the $m_{\text{jet}}$ distribution that includes the effects from all three sources, which are correlated among the individual measurement bins.

Experimental systematic uncertainties

Systematic uncertainties related to experimental effects are evaluated by changing calibration factors and corrections to efficiencies within their corresponding uncertainties. The resulting covariance matrix of the unfolded measurement is computed through standard error propagation. The uncertainties are evaluated by unfolding pseudo-data simulated with \MADGRAPH+\PYTHIA. Pseudo-data are preferred over data because of the smaller statistical fluctuations in the estimation of the systematic uncertainties. The change in each parameter that yields the largest variation in the unfolded measurement is taken as the uncertainty owing to that parameter. The following sources of experimental systematic uncertainties are considered.

The applied jet energy corrections (JEC) depend on the $\pt$ and $\eta$ of the individual jets. The JEC are obtained by using anti-\ktjets with $R=0.7$ (AK7) [64], and their use is checked on CA12 jets by using simulated events. Residual differences between generated and reconstructed jet momenta caused by the larger jet size used in this analysis result in increased uncertainties in the JEC by factors of two to four with respect to the AK7 values. Changes of the JEC within their uncertainties are made in the three-momenta of the jets to estimate the effect on the measured cross section. The jet mass is kept fixed to avoid double-counting of uncertainties when including the uncertainty in the jet-mass scale. A smearing is applied in the jet energy resolution (JER) as an $\eta$-dependent correction to all jets in the simulation. The corrections are again changed within their uncertainty to estimate the systematic uncertainty related to the JER smearing. The uncertainties are found to be small compared to the ones from the JEC. The jet-mass scale and the corresponding uncertainty in the CA12 jets have been studied in events that contain a $\PW\to\PQq\PAQq^{\prime}$ decay reconstructed as a single jet in \ttbarproduction. The ratio of the reconstructed jet-mass peak positions in data and simulation is $1.015\pm 0.012$. No correction to the jet-mass scale is applied, but an uncertainty of $1.5\%$ is assigned, corresponding to the difference in peak positions. The widths of the jet mass distributions are about 15\GeV, consistent between data and simulation.

Corrections in $\PQb$ tagging efficiency are applied as $\pt$-dependent scale factors for each jet flavour. The corresponding systematic uncertainties are obtained by changing the scale factors within their uncertainties. Pileup correction factors are applied to match the number of primary interactions to the instantaneous luminosity profile in data. The uncertainty is obtained by changing the total inelastic cross section by ${\pm}5\%$ [109]. Trigger and lepton identification scale factors are used to correct for differences in the lepton selection efficiency between data and simulation. The corresponding uncertainties are computed by changing the scale factors within their uncertainties [58, 56].

Normalisation uncertainties

The effects from uncertainties in background processes are calculated by changing the amount of background subtracted prior to the unfolding and propagating the effect to the output. The uncertainty in the $\PW$+jets cross section is taken to be 19%, as obtained from a measurement of $\PW$+heavy-flavour quark production [110]; an uncertainty of 23% is applied to the single top quark cross section [111]; and an uncertainty of 100% is assumed for multijet production, estimated from the comparison of various kinematic distributions between data and simulation. Uncertainties affecting the overall normalisation are added in quadrature to the total uncertainty after the unfolding. An uncertainty of 2.6% is applied subsequently for the integrated luminosity [112].

Modelling uncertainties

The unfolding is checked for its dependence on the simulation of \ttbarproduction through the use of alternative programs to generate events. The effect on the measurement is estimated by using one simulation as pseudo-data input to the unfolding, and another for the calculation of the response matrix. The unfolded result is then compared to the particle-level distribution from the simulation used as pseudo-data. Differences between the unfolded result and the truth-level distribution are taken as the modelling uncertainties.

The uncertainty from the choice of MC generator is estimated by unfolding pseudo-data simulated with \MADGRAPH+\PYTHIAthrough a response matrix evaluated with \POWHEG+\PYTHIA. The effect from the choice of the parton-shower simulation is estimated from events generated with \MCATNLO+\HERWIG.

The dependence on the choice of $m_{\PQt}$ in the simulation used to correct the data is also checked. While the unfolded measurement is largely independent of the choice of $m_{\PQt}$, residual effects from the kinematic properties of the leptons and jets can lead to additional uncertainties. These uncertainties are evaluated by using events simulated with \MADGRAPH+\PYTHIAfor seven values of $m_{\PQt}$ from 166.5 to 178.5\GeV, as pseudo-data. This range is considered because no measurement of $m_{\PQt}$ in this kinematic regime exists, and a stable result, independent of the specific choice of $m_{\PQt}$, is therefore crucial. For this check, the response matrix is obtained with \MADGRAPH+\PYTHIAand a value of $m_{\PQt}=172.5\GeV$. The envelope of the uncertainty obtained for different values of $m_{\PQt}$ is used to define an additional modelling uncertainty.

The uncertainty from the uncalculated higher-order terms in the simulation is estimated by changing the choice of the factorisation and renormalisation scales $\mu_{\mathrm{F}}$ and $\mu_{\mathrm{R}}$. For this purpose events simulated with \POWHEG+\PYTHIAare used, where the scales are changed up and down by factors of two relative to their nominal value. This is set to $\mu_{\mathrm{F}}^{2}=\mu_{\mathrm{R}}^{2}=Q^{2}$, where the scale of the hard process is defined by $Q^{2}=m_{\PQt}^{2}+\sum\pt^{2}$ with the sum over all additional final-state partons in the matrix-element calculation. Events with varied scales are unfolded through a response matrix obtained with the nominal choice of scales. The uncertainty in the measurement is defined by the largest change found in the study.

Uncertainties from the PDF are evaluated by using the eigenvectors of the CT10 PDF set with the \POWHEG+\PYTHIAsimulation. The resulting differences in the response matrix are propagated to the measurement. The individual uncertainties for each eigenvector are scaled to the 68% confidence level and added in quadrature [79].

Summary of uncertainties

A summary of the relative uncertainties in this measurement is shown in Fig. 4. The largest contribution is from the statistical uncertainties. The experimental systematic uncertainties are far smaller than those from the modelling of \ttbarproduction. The largest uncertainties are expected to improve considerably with more data at higher centre-of-mass energies. Besides a reduction of the statistical uncertainties, an unfolding of the data using finer bins and as a function of more variables will then be possible, which will result in a reduction of the systematic uncertainties from the simulation of \ttbarevents. More data will also allow for a measurement that uses smaller jet sizes, which will reduce the uncertainties coming from the jet energy and jet mass scales.

0.5.6 Cross section results

The particle-level \ttbarcross section for the fiducial phase-space region is measured differentially as a function of the leading-jet mass in the $\ell$+jets channel. The selection criteria defining the fiducial measurement region are summarised in Table 0.5.6 (cf. Section 0.5.2).

The measured differential cross section as a function of the leading-jet mass in this fiducial region is shown in Fig. 5, and the numerical values are given in Table 0.5.6. The full covariance matrices are given in Appendix .8. The data are compared to simulated distributions obtained with \POWHEG+\PYTHIA, \MADGRAPH+\PYTHIA, and \MCATNLO+\HERWIG. The total measured \ttbarcross section for $140<m_{\text{jet}}<350\GeV$ in the fiducial region is $\sigma=101\pm 11\stat\pm 13\syst\pm 9\,(\text{model})\unit{fb}$, where the last uncertainty is from the modelling of the \ttbarsignal. Combining all the uncertainties in quadrature gives a value of $\sigma=101\pm 19\unit{fb}$. The predicted fiducial-region cross sections from the \MADGRAPH+\PYTHIAand \POWHEG+\PYTHIA\ttbarsimulations, assuming a total \ttbarcross section of 253\unitpb [89, 90, 91, 92, 93, 94, 95], are $159\,^{+17}_{-18}$ and $133\,^{+18}_{-28}\unit{fb}$, respectively, where the uncertainties are systematic and come from the variations of $\mu_{\mathrm{R}}$ and $\mu_{\mathrm{F}}$. The predictions exceed the measurements, consistent with previously measured \ttbarcross sections at large top quark \pt [16, 17]. A similar trend is observed when comparing the data to the prediction from \MCATNLO+\HERWIG. Recent NNLO calculations [113] of the top quark \ptspectrum alleviate this discrepancy.

The normalised differential cross section $(1/\sigma)(\rd\sigma/\rd m_{\text{jet}}{})$ is obtained by dividing the differential cross sections by the total cross section in the $m_{\text{jet}}$ range from 140 to 350\GeV. The result is shown in Fig. 6, together with the predictions of \MADGRAPH+\PYTHIAfor three values of $m_{\PQt}$. The numerical values of the measured particle-level cross sections are given in Table 0.5.6, together with the individual and total uncertainties. The covariance matrices of the measurement are given in Appendix .8. The data are well described by the simulation, showing that the overall modelling of the top quark jet mass is acceptable, once the disagreement with the total cross section at large \ptis eliminated by the normalisation. The sensitivity of the measurement to $m_{\PQt}$ is clearly visible, albeit compromised by the overall uncertainties.

0.6 Sensitivity to the top quark mass

Calculations of $m_{\text{jet}}$ for \ttbarproduction from first principles, by using a well-defined definition of $m_{\PQt}$ and not relying on parton shower and hadronisation models, are not yet available for the LHC. Still, a determination of the top quark mass parameter in general-purpose event generators that uses the normalised particle-level cross sections provides a proof of principle for the feasibility of the method, a cross-check on other determinations of $m_{\PQt}$, and an estimate of the current measurement’s sensitivity. The value of $m_{\PQt}$ is determined from the normalised differential cross section measurements given in Table 0.5.6, since only the shape of the $m_{\text{jet}}$ distribution can be reliably calculated. Correlations are taken into account through the full covariance matrix of the measurement, which is given in Appendix .8. Theoretical predictions are obtained from \MADGRAPH+\PYTHIAfor different values of $m_{\PQt}$. A fit is performed based on the $\chi^{2}$ evaluated as $\chi^{2}=d^{T}V^{-1}d$, where $d$ is the vector of differences between the measured normalised cross sections and the predictions, and $V$ is the covariance matrix, which includes the statistical, experimental systematic, modelling, and theoretical uncertainties. The latter are calculated by changing up and down by factors of two the scales $\mu_{\mathrm{R}}$ and $\mu_{\mathrm{F}}$ in the \MADGRAPH+\PYTHIAsimulation. The resulting uncertainties are added to the covariance matrix. The $\chi^{2}$ values obtained for different values of $m_{\PQt}$ are fitted by a second-order polynomial to determine the minimum, and the uncertainty is determined by a change in $\chi^{2}$ of 1.0. The result is

[TABLE]

where the total uncertainty in Eq. (3) is the sum in quadrature of the individual uncertainties in Eq. (2). The fit has a minimum $\chi^{2}$ of $1.6$ for three degrees of freedom. This measurement is the first determination of $m_{\PQt}$ from boosted \ttbarproduction, calibrated to the \MADGRAPH+\PYTHIAsimulation. It is consistent with recent determinations of $m_{\PQt}$ that use MC event generators [33, 35, 36, 37], cross section measurements [114, 34, 6], and indirect constraints from electroweak fits [115].

0.7 Summary and outlook

The first measurement of the differential \ttbarcross section has been performed in the $\ell$+jets channel as a function of the leading-jet mass $m_{\text{jet}}$ in the highly boosted top quark regime. The measurement is carried out in a fiducial region with fully merged top quark decays in hadronic final states, corrected to the particle level. The normalised differential cross section as a function of $m_{\text{jet}}$ agrees with predictions from simulations, indicating the good quality of modelling the jet mass in highly boosted top quark decays. The total fiducial-region cross section for $m_{\text{jet}}$ between 140 and 350\GeVis measured to be $101\pm 19\unit{fb}$, which is below the predicted value. This difference is consistent with earlier measurements of a softer top quark \ptspectrum observed in data than in simulation [16, 17]. This measurement is a first step towards measuring unfolded jet substructure distributions in highly boosted top quark decays. A detailed understanding of these is crucial for measurements and searches for new physics making use of top quark tagging algorithms.

The peak position in the $m_{\text{jet}}$ distribution is sensitive to the top quark mass $m_{\PQt}$. This can be used for an independent determination of $m_{\PQt}$ in the boosted regime, with the prospect of reaching a more reliable correspondence between the top quark mass in any well-defined renormalisation scheme and the top quark mass parameter in general-purpose event generators.

The normalised particle-level \ttbardifferential cross section measurement as a function of $m_{\text{jet}}$ is used to extract a value of $m_{\PQt}$ in order to estimate the current sensitivity of the data. The value obtained, $m_{\PQt}=170.8\pm 9.0\GeV$, is consistent with the current LHC and Tevatron average of $173.34\pm 0.27\stat\pm 0.71\syst\GeV$ [116], albeit with a much larger uncertainty.

New data at higher centre-of-mass energies and with larger integrated luminosities will lead to an improvement in the statistical uncertainty. More data can also lead to reductions in the experimental systematic uncertainties, most notably that from the jet mass scale, which is expected to improve with smaller jet distance parameters. In addition, improvements in the modelling uncertainty are expected because of stronger constraints on the simulation in the highly boosted regime. A reduction in the theoretical uncertainty is also foreseen with the emergence of higher-order calculations. The results obtained in this analysis show the feasibility of the method to obtain the top quark mass in the highly boosted regime. This can provide an important ingredient for studies of the relation between the value of the top quark mass obtained from MC event generators and the one obtained from first-principle calculations.

Acknowledgements.

We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at CERN and at other CMS institutes for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centres and personnel of the Worldwide LHC Computing Grid for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies: BMWFW and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES and CSF (Croatia); RPF (Cyprus); SENESCYT (Ecuador); MoER, ERC IUT, and ERDF (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NIH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MBIE (New Zealand); PAEC (Pakistan); MSHE and NSC (Poland); FCT (Portugal); JINR (Dubna); MON, RosAtom, RAS, RFBR and RAEP (Russia); MESTD (Serbia); SEIDI, CPAN, PCTI and FEDER (Spain); Swiss Funding Agencies (Switzerland); MST (Taipei); ThEPCenter, IPST, STAR, and NSTDA (Thailand); TUBITAK and TAEK (Turkey); NASU and SFFR (Ukraine); STFC (United Kingdom); DOE and NSF (USA). Individuals have received support from the Marie-Curie programme and the European Research Council and EPLANET (European Union); the Leventis Foundation; the A. P. Sloan Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science Policy Office; the Fonds pour la Formation à la Recherche dans l’Industrie et dans l’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Council of Science and Industrial Research, India; the HOMING PLUS programme of the Foundation for Polish Science, cofinanced from European Union, Regional Development Fund, the Mobility Plus programme of the Ministry of Science and Higher Education, the National Science Center (Poland), contracts Harmonia 2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543, 2014/15/B/ST2/03998, and 2015/19/B/ST2/02861, Sonata-bis 2012/07/E/ST2/01406; the National Priorities Research Program by Qatar National Research Fund; the Programa Clarín-COFUND del Principado de Asturias; the Thalis and Aristeia programmes cofinanced by EU-ESF and the Greek NSRF; the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University and the Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand); and the Welch Foundation, contract C-1845.

.8 Covariance matrices

The covariance matrices that involve just the statistical components, and the ones involving the total uncertainty (\iethe statistical, experimental systematic, and modelling uncertainties) are provided in this appendix. All experimental, as well as the PDF and parton-shower uncertainties, are treated as fully correlated in the calculation of the covariance matrices. The uncertainties in the renormalisation and factorisation scale include correlations in the first three bins, and the uncertainties coming from the choice of $m_{\PQt}$ are treated as uncorrelated. Bins 1 to 5 correspond to the following ranges in $m_{\text{jet}}$: 140–170, 170–200, 200–240, 240–290, and 290–350\GeV. The covariance matrices for the differential $m_{\text{jet}}$ measurement are given in Tables .8 and .8 for the statistical and total uncertainties, respectively. The covariance matrices for the normalised measurement are given in Tables .8 and .8. Note that the covariance matrices of the normalised measurement are singular, and only four out of the five measurement bins are used in the determination of $m_{\PQt}$.

.9 The CMS Collaboration

**Yerevan Physics Institute, Yerevan, Armenia

** A.M. Sirunyan, A. Tumasyan \cmsinstskip**Institut für Hochenergiephysik, Wien, Austria

** W. Adam, E. Asilar, T. Bergauer, J. Brandstetter, E. Brondolin, M. Dragicevic, J. Erö, M. Flechl, M. Friedl, R. Frühwirth\cmsAuthorMark1, V.M. Ghete, C. Hartl, N. Hörmann, J. Hrubec, M. Jeitler\cmsAuthorMark1, A. König, I. Krätschmer, D. Liko, T. Matsushita, I. Mikulec, D. Rabady, N. Rad, B. Rahbaran, H. Rohringer, J. Schieck\cmsAuthorMark1, J. Strauss, W. Waltenberger, C.-E. Wulz\cmsAuthorMark1 \cmsinstskip**Institute for Nuclear Problems, Minsk, Belarus

** O. Dvornikov, V. Makarenko, V. Mossolov, J. Suarez Gonzalez, V. Zykunov \cmsinstskip**National Centre for Particle and High Energy Physics, Minsk, Belarus

** N. Shumeiko \cmsinstskip**Universiteit Antwerpen, Antwerpen, Belgium

** S. Alderweireldt, E.A. De Wolf, X. Janssen, J. Lauwers, M. Van De Klundert, H. Van Haevermaet, P. Van Mechelen, N. Van Remortel, A. Van Spilbeeck \cmsinstskip**Vrije Universiteit Brussel, Brussel, Belgium

** S. Abu Zeid, F. Blekman, J. D’Hondt, N. Daci, I. De Bruyn, K. Deroover, S. Lowette, S. Moortgat, L. Moreels, A. Olbrechts, Q. Python, K. Skovpen, S. Tavernier, W. Van Doninck, P. Van Mulders, I. Van Parijs \cmsinstskip**Université Libre de Bruxelles, Bruxelles, Belgium

** H. Brun, B. Clerbaux, G. De Lentdecker, H. Delannoy, G. Fasanella, L. Favart, R. Goldouzian, A. Grebenyuk, G. Karapostoli, T. Lenzi, A. Léonard, J. Luetic, T. Maerschalk, A. Marinov, A. Randle-conde, T. Seva, C. Vander Velde, P. Vanlaer, D. Vannerom, R. Yonamine, F. Zenoni, F. Zhang\cmsAuthorMark2 \cmsinstskip**Ghent University, Ghent, Belgium

** A. Cimmino, T. Cornelis, D. Dobur, A. Fagot, M. Gul, I. Khvastunov, D. Poyraz, S. Salva, R. Schöfbeck, M. Tytgat, W. Van Driessche, E. Yazgan, N. Zaganidis \cmsinstskip**Université Catholique de Louvain, Louvain-la-Neuve, Belgium

** H. Bakhshiansohi, C. Beluffi\cmsAuthorMark3, O. Bondu, S. Brochet, G. Bruno, A. Caudron, S. De Visscher, C. Delaere, M. Delcourt, B. Francois, A. Giammanco, A. Jafari, M. Komm, G. Krintiras, V. Lemaitre, A. Magitteri, A. Mertens, M. Musich, K. Piotrzkowski, L. Quertenmont, M. Selvaggi, M. Vidal Marono, S. Wertz \cmsinstskip**Université de Mons, Mons, Belgium

** N. Beliy \cmsinstskip**Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil

** W.L. Aldá Júnior, F.L. Alves, G.A. Alves, L. Brito, C. Hensel, A. Moraes, M.E. Pol, P. Rebello Teles \cmsinstskip**Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil

** E. Belchior Batista Das Chagas, W. Carvalho, J. Chinellato\cmsAuthorMark4, A. Custódio, E.M. Da Costa, G.G. Da Silveira\cmsAuthorMark5, D. De Jesus Damiao, C. De Oliveira Martins, S. Fonseca De Souza, L.M. Huertas Guativa, H. Malbouisson, D. Matos Figueiredo, C. Mora Herrera, L. Mundim, H. Nogima, W.L. Prado Da Silva, A. Santoro, A. Sznajder, E.J. Tonelli Manganote\cmsAuthorMark4, F. Torres Da Silva De Araujo, A. Vilela Pereira \cmsinstskip**Universidade Estadual Paulista a,  Universidade Federal do ABC b,  São Paulo, Brazil

** S. Ahujaa, C.A. Bernardesa, S. Dograa, T.R. Fernandez Perez Tomeia, E.M. Gregoresb, P.G. Mercadanteb, C.S. Moona, S.F. Novaesa, Sandra S. Padulaa, D. Romero Abadb, J.C. Ruiz Vargasa \cmsinstskip**Institute for Nuclear Research and Nuclear Energy, Sofia, Bulgaria

** A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, M. Rodozov, S. Stoykova, G. Sultanov, M. Vutova \cmsinstskip**University of Sofia, Sofia, Bulgaria

** A. Dimitrov, I. Glushkov, L. Litov, B. Pavlov, P. Petkov \cmsinstskip**Beihang University, Beijing, China

** W. Fang\cmsAuthorMark6 \cmsinstskip**Institute of High Energy Physics, Beijing, China

** M. Ahmad, J.G. Bian, G.M. Chen, H.S. Chen, M. Chen, Y. Chen\cmsAuthorMark7, T. Cheng, C.H. Jiang, D. Leggat, Z. Liu, F. Romeo, M. Ruan, S.M. Shaheen, A. Spiezia, J. Tao, C. Wang, Z. Wang, H. Zhang, J. Zhao \cmsinstskip**State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, China

** Y. Ban, G. Chen, Q. Li, S. Liu, Y. Mao, S.J. Qian, D. Wang, Z. Xu \cmsinstskip**Universidad de Los Andes, Bogota, Colombia

** C. Avila, A. Cabrera, L.F. Chaparro Sierra, C. Florez, J.P. Gomez, C.F. González Hernández, J.D. Ruiz Alvarez, J.C. Sanabria \cmsinstskip**University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Split, Croatia

** N. Godinovic, D. Lelas, I. Puljak, P.M. Ribeiro Cipriano, T. Sculac \cmsinstskip**University of Split, Faculty of Science, Split, Croatia

** Z. Antunovic, M. Kovac \cmsinstskip**Institute Rudjer Boskovic, Zagreb, Croatia

** V. Brigljevic, D. Ferencek, K. Kadija, B. Mesic, T. Susa \cmsinstskip**University of Cyprus, Nicosia, Cyprus

** A. Attikis, G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos, P.A. Razis, H. Rykaczewski, D. Tsiakkouri \cmsinstskip**Charles University, Prague, Czech Republic

** M. Finger\cmsAuthorMark8, M. Finger Jr.\cmsAuthorMark8 \cmsinstskip**Universidad San Francisco de Quito, Quito, Ecuador

** E. Carrera Jarrin \cmsinstskip**Academy of Scientific Research and Technology of the Arab Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt

** A.A. Abdelalim\cmsAuthorMark9*,\cmsAuthorMark10, Y. Mohammed\cmsAuthorMark11, E. Salama\cmsAuthorMark12,*\cmsAuthorMark13 \cmsinstskip**National Institute of Chemical Physics and Biophysics, Tallinn, Estonia

** M. Kadastik, L. Perrini, M. Raidal, A. Tiko, C. Veelken \cmsinstskip**Department of Physics, University of Helsinki, Helsinki, Finland

** P. Eerola, J. Pekkanen, M. Voutilainen \cmsinstskip**Helsinki Institute of Physics, Helsinki, Finland

** J. Härkönen, T. Järvinen, V. Karimäki, R. Kinnunen, T. Lampén, K. Lassila-Perini, S. Lehti, T. Lindén, P. Luukka, J. Tuominiemi, E. Tuovinen, L. Wendland \cmsinstskip**Lappeenranta University of Technology, Lappeenranta, Finland

** J. Talvitie, T. Tuuva \cmsinstskip**IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France

** M. Besancon, F. Couderc, M. Dejardin, D. Denegri, B. Fabbro, J.L. Faure, C. Favaro, F. Ferri, S. Ganjour, S. Ghosh, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry, I. Kucher, E. Locci, M. Machet, J. Malcles, J. Rander, A. Rosowsky, M. Titov \cmsinstskip**Laboratoire Leprince-Ringuet, Ecole Polytechnique, IN2P3-CNRS, Palaiseau, France

** A. Abdulsalam, I. Antropov, S. Baffioni, F. Beaudette, P. Busson, L. Cadamuro, E. Chapon, C. Charlot, O. Davignon, R. Granier de Cassagnac, M. Jo, S. Lisniak, P. Miné, M. Nguyen, C. Ochando, G. Ortona, P. Paganini, P. Pigard, S. Regnard, R. Salerno, Y. Sirois, A.G. Stahl Leiton, T. Strebler, Y. Yilmaz, A. Zabi, A. Zghiche \cmsinstskip**Institut Pluridisciplinaire Hubert Curien (IPHC),  Université de Strasbourg, CNRS-IN2P3

** J.-L. Agram\cmsAuthorMark14, J. Andrea, A. Aubin, D. Bloch, J.-M. Brom, M. Buttignol, E.C. Chabert, N. Chanon, C. Collard, E. Conte\cmsAuthorMark14, X. Coubez, J.-C. Fontaine\cmsAuthorMark14, D. Gelé, U. Goerlach, A.-C. Le Bihan, P. Van Hove \cmsinstskip**Centre de Calcul de l’Institut National de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3, Villeurbanne, France

** S. Gadrat \cmsinstskip**Université de Lyon, Université Claude Bernard Lyon 1,  CNRS-IN2P3, Institut de Physique Nucléaire de Lyon, Villeurbanne, France

** S. Beauceron, C. Bernet, G. Boudoul, C.A. Carrillo Montoya, R. Chierici, D. Contardo, B. Courbon, P. Depasse, H. El Mamouni, J. Fay, S. Gascon, M. Gouzevitch, G. Grenier, B. Ille, F. Lagarde, I.B. Laktineh, M. Lethuillier, L. Mirabito, A.L. Pequegnot, S. Perries, A. Popov\cmsAuthorMark15, D. Sabes, V. Sordini, M. Vander Donckt, P. Verdier, S. Viret \cmsinstskip**Georgian Technical University, Tbilisi, Georgia

** A. Khvedelidze\cmsAuthorMark8 \cmsinstskip**Tbilisi State University, Tbilisi, Georgia

** Z. Tsamalaidze\cmsAuthorMark8 \cmsinstskip**RWTH Aachen University, I. Physikalisches Institut, Aachen, Germany

** C. Autermann, S. Beranek, L. Feld, M.K. Kiesel, K. Klein, M. Lipinski, M. Preuten, C. Schomakers, J. Schulz, T. Verlage \cmsinstskip**RWTH Aachen University, III. Physikalisches Institut A,  Aachen, Germany

** A. Albert, M. Brodski, E. Dietz-Laursonn, D. Duchardt, M. Endres, M. Erdmann, S. Erdweg, T. Esch, R. Fischer, A. Güth, M. Hamer, T. Hebbeker, C. Heidemann, K. Hoepfner, S. Knutzen, M. Merschmeyer, A. Meyer, P. Millet, S. Mukherjee, M. Olschewski, K. Padeken, T. Pook, M. Radziej, H. Reithler, M. Rieger, F. Scheuch, L. Sonnenschein, D. Teyssier, S. Thüer \cmsinstskip**RWTH Aachen University, III. Physikalisches Institut B,  Aachen, Germany

** V. Cherepanov, G. Flügge, B. Kargoll, T. Kress, A. Künsken, J. Lingemann, T. Müller, A. Nehrkorn, A. Nowack, C. Pistone, O. Pooth, A. Stahl\cmsAuthorMark16 \cmsinstskip**Deutsches Elektronen-Synchrotron, Hamburg, Germany

** M. Aldaya Martin, T. Arndt, C. Asawatangtrakuldee, K. Beernaert, O. Behnke, U. Behrens, A.A. Bin Anuar, K. Borras\cmsAuthorMark17, A. Campbell, P. Connor, C. Contreras-Campana, F. Costanza, C. Diez Pardos, G. Dolinska, G. Eckerlin, D. Eckstein, T. Eichhorn, E. Eren, E. Gallo\cmsAuthorMark18, J. Garay Garcia, A. Geiser, A. Gizhko, J.M. Grados Luyando, A. Grohsjean, P. Gunnellini, A. Harb, J. Hauk, M. Hempel\cmsAuthorMark19, H. Jung, A. Kalogeropoulos, O. Karacheban\cmsAuthorMark19, M. Kasemann, J. Keaveney, C. Kleinwort, I. Korol, D. Krücker, W. Lange, A. Lelek, T. Lenz, J. Leonard, K. Lipka, A. Lobanov, W. Lohmann\cmsAuthorMark19, R. Mankel, I.-A. Melzer-Pellmann, A.B. Meyer, G. Mittag, J. Mnich, A. Mussgiller, D. Pitzl, R. Placakyte, A. Raspereza, B. Roland, M.Ö. Sahin, P. Saxena, T. Schoerner-Sadenius, S. Spannagel, N. Stefaniuk, G.P. Van Onsem, R. Walsh, C. Wissing \cmsinstskip**University of Hamburg, Hamburg, Germany

** V. Blobel, M. Centis Vignali, A.R. Draeger, T. Dreyer, E. Garutti, D. Gonzalez, J. Haller, M. Hoffmann, A. Junkes, R. Klanner, R. Kogler, N. Kovalchuk, T. Lapsien, I. Marchesini, D. Marconi, M. Meyer, M. Niedziela, D. Nowatschin, F. Pantaleo\cmsAuthorMark16, T. Peiffer, A. Perieanu, C. Scharf, P. Schleper, A. Schmidt, S. Schumann, J. Schwandt, H. Stadie, G. Steinbrück, F.M. Stober, M. Stöver, H. Tholen, D. Troendle, E. Usai, L. Vanelderen, A. Vanhoefer, B. Vormwald \cmsinstskip**Institut für Experimentelle Kernphysik, Karlsruhe, Germany

** M. Akbiyik, C. Barth, S. Baur, C. Baus, J. Berger, E. Butz, R. Caspart, T. Chwalek, F. Colombo, W. De Boer, A. Dierlamm, S. Fink, B. Freund, R. Friese, M. Giffels, A. Gilbert, P. Goldenzweig, D. Haitz, F. Hartmann\cmsAuthorMark16, S.M. Heindl, U. Husemann, I. Katkov\cmsAuthorMark15, S. Kudella, H. Mildner, M.U. Mozer, Th. Müller, M. Plagge, G. Quast, K. Rabbertz, S. Röcker, F. Roscher, M. Schröder, I. Shvetsov, G. Sieber, H.J. Simonis, R. Ulrich, S. Wayand, M. Weber, T. Weiler, S. Williamson, C. Wöhrmann, R. Wolf \cmsinstskip**Institute of Nuclear and Particle Physics (INPP),  NCSR Demokritos, Aghia Paraskevi, Greece

** G. Anagnostou, G. Daskalakis, T. Geralis, V.A. Giakoumopoulou, A. Kyriakis, D. Loukas, I. Topsis-Giotis \cmsinstskip**National and Kapodistrian University of Athens, Athens, Greece

** S. Kesisoglou, A. Panagiotou, N. Saoulidou, E. Tziaferi \cmsinstskip**University of Ioánnina, Ioánnina, Greece

** I. Evangelou, G. Flouris, C. Foudas, P. Kokkas, N. Loukas, N. Manthos, I. Papadopoulos, E. Paradas \cmsinstskip**MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös Loránd University, Budapest, Hungary

** N. Filipovic, G. Pasztor \cmsinstskip**Wigner Research Centre for Physics, Budapest, Hungary

** G. Bencze, C. Hajdu, D. Horvath\cmsAuthorMark20, F. Sikler, V. Veszpremi, G. Vesztergombi\cmsAuthorMark21, A.J. Zsigmond \cmsinstskip**Institute of Nuclear Research ATOMKI, Debrecen, Hungary

** N. Beni, S. Czellar, J. Karancsi\cmsAuthorMark22, A. Makovec, J. Molnar, Z. Szillasi \cmsinstskip**Institute of Physics, University of Debrecen

** M. Bartók\cmsAuthorMark21, P. Raics, Z.L. Trocsanyi, B. Ujvari \cmsinstskip**Indian Institute of Science (IISc)

** J.R. Komaragiri \cmsinstskip**National Institute of Science Education and Research, Bhubaneswar, India

** S. Bahinipati\cmsAuthorMark23, S. Bhowmik\cmsAuthorMark24, S. Choudhury\cmsAuthorMark25, P. Mal, K. Mandal, A. Nayak\cmsAuthorMark26, D.K. Sahoo\cmsAuthorMark23, N. Sahoo, S.K. Swain \cmsinstskip**Panjab University, Chandigarh, India

** S. Bansal, S.B. Beri, V. Bhatnagar, R. Chawla, U.Bhawandeep, A.K. Kalsi, A. Kaur, M. Kaur, R. Kumar, P. Kumari, A. Mehta, M. Mittal, J.B. Singh, G. Walia \cmsinstskip**University of Delhi, Delhi, India

** Ashok Kumar, A. Bhardwaj, B.C. Choudhary, R.B. Garg, S. Keshri, S. Malhotra, M. Naimuddin, K. Ranjan, R. Sharma, V. Sharma \cmsinstskip**Saha Institute of Nuclear Physics, Kolkata, India

** R. Bhattacharya, S. Bhattacharya, K. Chatterjee, S. Dey, S. Dutt, S. Dutta, S. Ghosh, N. Majumdar, A. Modak, K. Mondal, S. Mukhopadhyay, S. Nandan, A. Purohit, A. Roy, D. Roy, S. Roy Chowdhury, S. Sarkar, M. Sharan, S. Thakur \cmsinstskip**Indian Institute of Technology Madras, Madras, India

** P.K. Behera \cmsinstskip**Bhabha Atomic Research Centre, Mumbai, India

** R. Chudasama, D. Dutta, V. Jha, V. Kumar, A.K. Mohanty\cmsAuthorMark16, P.K. Netrakanti, L.M. Pant, P. Shukla, A. Topkar \cmsinstskip**Tata Institute of Fundamental Research-A, Mumbai, India

** T. Aziz, S. Dugad, G. Kole, B. Mahakud, S. Mitra, G.B. Mohanty, B. Parida, N. Sur, B. Sutar \cmsinstskip**Tata Institute of Fundamental Research-B, Mumbai, India

** S. Banerjee, R.K. Dewanjee, S. Ganguly, M. Guchait, Sa. Jain, S. Kumar, M. Maity\cmsAuthorMark24, G. Majumder, K. Mazumdar, T. Sarkar\cmsAuthorMark24, N. Wickramage\cmsAuthorMark27 \cmsinstskip**Indian Institute of Science Education and Research (IISER),  Pune, India

** S. Chauhan, S. Dube, V. Hegde, A. Kapoor, K. Kothekar, S. Pandey, A. Rane, S. Sharma \cmsinstskip**Institute for Research in Fundamental Sciences (IPM),  Tehran, Iran

** S. Chenarani\cmsAuthorMark28, E. Eskandari Tadavani, S.M. Etesami\cmsAuthorMark28, M. Khakzad, M. Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi\cmsAuthorMark29, F. Rezaei Hosseinabadi, B. Safarzadeh\cmsAuthorMark30, M. Zeinali \cmsinstskip**University College Dublin, Dublin, Ireland

** M. Felcini, M. Grunewald \cmsinstskip**INFN Sezione di Bari a, Università di Bari b, Politecnico di Bari c,  Bari, Italy

** M. Abbresciaa**,b, C. Calabriaa**,b, C. Caputoa**,b, A. Colaleoa, D. Creanzaa**,c, L. Cristellaa**,b, N. De Filippisa**,c, M. De Palmaa**,b, L. Fiorea, G. Iasellia**,c, G. Maggia**,c, M. Maggia, G. Minielloa**,b, S. Mya**,b, S. Nuzzoa**,b, A. Pompilia**,b, G. Pugliesea**,c, R. Radognaa**,b, A. Ranieria, G. Selvaggia**,b, A. Sharmaa, L. Silvestrisa**,\cmsAuthorMark16, R. Vendittia**,b, P. Verwilligena \cmsinstskip**INFN Sezione di Bologna a, Università di Bologna b,  Bologna, Italy

** G. Abbiendia, C. Battilana, D. Bonacorsia**,b, S. Braibant-Giacomellia**,b, L. Brigliadoria**,b, R. Campaninia**,b, P. Capiluppia**,b, A. Castroa**,b, F.R. Cavalloa, S.S. Chhibraa**,b, G. Codispotia**,b, M. Cuffiania**,b, G.M. Dallavallea, F. Fabbria, A. Fanfania**,b, D. Fasanellaa**,b, P. Giacomellia, C. Grandia, L. Guiduccia**,b, S. Marcellinia, G. Masettia, A. Montanaria, F.L. Navarriaa**,b, A. Perrottaa, A.M. Rossia**,b, T. Rovellia**,b, G.P. Sirolia**,b, N. Tosia**,b,\cmsAuthorMark16 \cmsinstskip**INFN Sezione di Catania a, Università di Catania b,  Catania, Italy

** S. Albergoa**,b, S. Costaa**,b, A. Di Mattiaa, F. Giordano*a**,b, R. Potenzaa**,b, A. Tricomia**,b, C. Tuvea**,*b \cmsinstskip**INFN Sezione di Firenze a, Università di Firenze b,  Firenze, Italy

** G. Barbaglia, V. Ciullia**,b, C. Civininia, R. D’Alessandroa**,b, E. Focardia**,b, P. Lenzia**,b, M. Meschinia, S. Paolettia, L. Russoa**,\cmsAuthorMark31, G. Sguazzonia, D. Stroma, L. Viliania**,b,\cmsAuthorMark16 \cmsinstskip**INFN Laboratori Nazionali di Frascati, Frascati, Italy

** L. Benussi, S. Bianco, F. Fabbri, D. Piccolo, F. Primavera\cmsAuthorMark16 \cmsinstskip**INFN Sezione di Genova a, Università di Genova b,  Genova, Italy

** V. Calvellia**,b, F. Ferroa, M.R. Mongea**,b, E. Robuttia, S. Tosi*a**,*b \cmsinstskip**INFN Sezione di Milano-Bicocca a, Università di Milano-Bicocca b,  Milano, Italy

** L. Brianzaa**,b,\cmsAuthorMark16, F. Brivioa**,b, V. Ciriolo, M.E. Dinardoa**,b, S. Fiorendia**,b,\cmsAuthorMark16, S. Gennaia, A. Ghezzia**,b, P. Govonia**,b, M. Malbertia**,b, S. Malvezzia, R.A. Manzonia**,b, D. Menascea, L. Moronia, M. Paganonia**,b, D. Pedrinia, S. Pigazzini*a**,b, S. Ragazzia**,b, T. Tabarelli de Fatisa**,*b \cmsinstskip**INFN Sezione di Napoli a, Università di Napoli ’Federico II’ b, Napoli, Italy, Università della Basilicata c, Potenza, Italy, Università G. Marconi d, Roma, Italy

** S. Buontempoa, N. Cavalloa**,c, G. De Nardo, S. Di Guidaa**,d,\cmsAuthorMark16, M. Espositoa**,b, F. Fabozzia**,c, F. Fiengaa**,b, A.O.M. Iorioa**,b, G. Lanzaa, L. Listaa, S. Meolaa**,d,\cmsAuthorMark16, P. Paoluccia**,\cmsAuthorMark16, C. Sciaccaa**,b, F. Thyssena \cmsinstskip**INFN Sezione di Padova a, Università di Padova b, Padova, Italy, Università di Trento c, Trento, Italy

** P. Azzia**,\cmsAuthorMark16, N. Bacchettaa, L. Benatoa**,b, D. Biselloa**,b, A. Bolettia**,b, R. Carlina**,b, A. Carvalho Antunes De Oliveiraa**,b, P. Checchiaa, M. Dall’Ossoa**,b, P. De Castro Manzanoa, T. Dorigoa, U. Dossellia, F. Gasparinia**,b, U. Gasparinia**,b, A. Gozzelinoa, S. Lacapraraa, M. Margonia**,b, A.T. Meneguzzoa**,b, J. Pazzinia**,b, N. Pozzobona**,b, P. Ronchesea**,b, F. Simonettoa**,b, E. Torassaa, M. Zanetti*a**,b, P. Zottoa**,b, G. Zumerlea**,*b \cmsinstskip**INFN Sezione di Pavia a, Università di Pavia b,  Pavia, Italy

** A. Braghieria, F. Fallavollitaa**,b, A. Magnania**,b, P. Montagnaa**,b, S.P. Rattia**,b, V. Rea, C. Riccardia**,b, P. Salvinia, I. Vai*a**,b, P. Vituloa**,*b \cmsinstskip**INFN Sezione di Perugia a, Università di Perugia b,  Perugia, Italy

** L. Alunni Solestizia**,b, G.M. Bileia, D. Ciangottinia**,b, L. Fanòa**,b, P. Laricciaa**,b, R. Leonardia**,b, G. Mantovania**,b, M. Menichellia, A. Sahaa, A. Santocchia*a**,*b \cmsinstskip**INFN Sezione di Pisa a, Università di Pisa b, Scuola Normale Superiore di Pisa c,  Pisa, Italy

** K. Androsova**,\cmsAuthorMark31, P. Azzurria**,\cmsAuthorMark16, G. Bagliesia, J. Bernardinia, T. Boccalia, R. Castaldia, M.A. Cioccia**,\cmsAuthorMark31, R. Dell’Orsoa, S. Donatoa**,c, G. Fedi, A. Giassia, M.T. Grippoa**,\cmsAuthorMark31, F. Ligabuea**,c, T. Lomtadzea, L. Martinia**,b, A. Messineoa**,b, F. Pallaa, A. Rizzia**,b, A. Savoy-Navarroa**,\cmsAuthorMark32, P. Spagnoloa, R. Tenchinia, G. Tonellia**,b, A. Venturia, P.G. Verdinia \cmsinstskip**INFN Sezione di Roma a, Università di Roma b,  Roma, Italy

** L. Baronea**,b, F. Cavallaria, M. Cipriania**,b, D. Del Rea**,b,\cmsAuthorMark16, M. Diemoza, S. Gellia**,b, E. Longoa**,b, F. Margarolia**,b, B. Marzocchia**,b, P. Meridiania, G. Organtinia**,b, R. Paramattia, F. Preiatoa**,b, S. Rahatloua**,b, C. Rovellia, F. Santanastasio*a**,*b \cmsinstskip**INFN Sezione di Torino a, Università di Torino b, Torino, Italy, Università del Piemonte Orientale c, Novara, Italy

** N. Amapanea**,b, R. Arcidiaconoa**,c,\cmsAuthorMark16, S. Argiroa**,b, M. Arneodoa**,c, N. Bartosika, R. Bellana**,b, C. Biinoa, N. Cartigliaa, F. Cennaa**,b, M. Costaa**,b, R. Covarellia**,b, A. Deganoa**,b, N. Demariaa, L. Fincoa**,b, B. Kiania**,b, C. Mariottia, S. Masellia, E. Migliorea**,b, V. Monacoa**,b, E. Monteila**,b, M. Montenoa, M.M. Obertinoa**,b, L. Pachera**,b, N. Pastronea, M. Pelliccionia, G.L. Pinna Angionia**,b, F. Raveraa**,b, A. Romeroa**,b, M. Ruspaa**,c, R. Sacchia**,b, K. Shchelinaa**,b, V. Solaa, A. Solanoa**,b, A. Staianoa, P. Traczyk*a**,*b \cmsinstskip**INFN Sezione di Trieste a, Università di Trieste b,  Trieste, Italy

** S. Belfortea, M. Casarsaa, F. Cossuttia, G. Della Riccaa**,b, A. Zanettia \cmsinstskip**Kyungpook National University, Daegu, Korea

** D.H. Kim, G.N. Kim, M.S. Kim, S. Lee, S.W. Lee, Y.D. Oh, S. Sekmen, D.C. Son, Y.C. Yang \cmsinstskip**Chonbuk National University, Jeonju, Korea

** A. Lee \cmsinstskip**Chonnam National University, Institute for Universe and Elementary Particles, Kwangju, Korea

** H. Kim \cmsinstskip**Hanyang University, Seoul, Korea

** J.A. Brochero Cifuentes, T.J. Kim \cmsinstskip**Korea University, Seoul, Korea

** S. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, Y. Jo, Y. Kim, K. Lee, K.S. Lee, S. Lee, J. Lim, S.K. Park, Y. Roh \cmsinstskip**Seoul National University, Seoul, Korea

** J. Almond, J. Kim, H. Lee, S.B. Oh, B.C. Radburn-Smith, S.h. Seo, U.K. Yang, H.D. Yoo, G.B. Yu \cmsinstskip**University of Seoul, Seoul, Korea

** M. Choi, H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park, G. Ryu, M.S. Ryu \cmsinstskip**Sungkyunkwan University, Suwon, Korea

** Y. Choi, J. Goh, C. Hwang, J. Lee, I. Yu \cmsinstskip**Vilnius University, Vilnius, Lithuania

** V. Dudenas, A. Juodagalvis, J. Vaitkus \cmsinstskip**National Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Malaysia

** I. Ahmed, Z.A. Ibrahim, M.A.B. Md Ali\cmsAuthorMark33, F. Mohamad Idris\cmsAuthorMark34, W.A.T. Wan Abdullah, M.N. Yusli, Z. Zolkapli \cmsinstskip**Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico

** H. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-De La Cruz\cmsAuthorMark35, A. Hernandez-Almada, R. Lopez-Fernandez, R. Magaña Villalba, J. Mejia Guisao, A. Sanchez-Hernandez \cmsinstskip**Universidad Iberoamericana, Mexico City, Mexico

** S. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia \cmsinstskip**Benemerita Universidad Autonoma de Puebla, Puebla, Mexico

** S. Carpinteyro, I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada \cmsinstskip**Universidad Autónoma de San Luis Potosí,  San Luis Potosí,  Mexico

** A. Morelos Pineda \cmsinstskip**University of Auckland, Auckland, New Zealand

** D. Krofcheck \cmsinstskip**University of Canterbury, Christchurch, New Zealand

** P.H. Butler \cmsinstskip**National Centre for Physics, Quaid-I-Azam University, Islamabad, Pakistan

** A. Ahmad, M. Ahmad, Q. Hassan, H.R. Hoorani, W.A. Khan, A. Saddique, M.A. Shah, M. Shoaib, M. Waqas \cmsinstskip**National Centre for Nuclear Research, Swierk, Poland

** H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Górski, M. Kazana, K. Nawrocki, K. Romanowska-Rybinska, M. Szleper, P. Zalewski \cmsinstskip**Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Warsaw, Poland

** K. Bunkowski, A. Byszuk\cmsAuthorMark36, K. Doroba, A. Kalinowski, M. Konecki, J. Krolikowski, M. Misiura, M. Olszewski, M. Walczak \cmsinstskip**Laboratório de Instrumentação e Física Experimental de Partículas, Lisboa, Portugal

** P. Bargassa, C. Beirão Da Cruz E Silva, B. Calpas, A. Di Francesco, P. Faccioli, P.G. Ferreira Parracho, M. Gallinaro, J. Hollar, N. Leonardo, L. Lloret Iglesias, M.V. Nemallapudi, J. Rodrigues Antunes, J. Seixas, O. Toldaiev, D. Vadruccio, J. Varela \cmsinstskip**Joint Institute for Nuclear Research, Dubna, Russia

** S. Afanasiev, P. Bunin, M. Gavrilenko, I. Golutvin, I. Gorbunov, A. Kamenev, V. Karjavin, A. Lanev, A. Malakhov, V. Matveev\cmsAuthorMark37*,*\cmsAuthorMark38, V. Palichik, V. Perelygin, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, N. Voytishin, A. Zarubin \cmsinstskip**Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg),  Russia

** L. Chtchipounov, V. Golovtsov, Y. Ivanov, V. Kim\cmsAuthorMark39, E. Kuznetsova\cmsAuthorMark40, V. Murzin, V. Oreshkin, V. Sulimov, A. Vorobyev \cmsinstskip**Institute for Nuclear Research, Moscow, Russia

** Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov, N. Krasnikov, A. Pashenkov, D. Tlisov, A. Toropin \cmsinstskip**Institute for Theoretical and Experimental Physics, Moscow, Russia

** V. Epshteyn, V. Gavrilov, N. Lychkovskaya, V. Popov, I. Pozdnyakov, G. Safronov, A. Spiridonov, M. Toms, E. Vlasov, A. Zhokin \cmsinstskip**Moscow Institute of Physics and Technology, Moscow, Russia

** T. Aushev, A. Bylinkin\cmsAuthorMark38 \cmsinstskip**National Research Nuclear University ’Moscow Engineering Physics Institute’ (MEPhI),  Moscow, Russia

** R. Chistov\cmsAuthorMark41, S. Polikarpov, E. Zhemchugov \cmsinstskip**P.N. Lebedev Physical Institute, Moscow, Russia

** V. Andreev, M. Azarkin\cmsAuthorMark38, I. Dremin\cmsAuthorMark38, M. Kirakosyan, A. Leonidov\cmsAuthorMark38, A. Terkulov \cmsinstskip**Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia

** A. Baskakov, A. Belyaev, E. Boos, V. Bunichev, M. Dubinin\cmsAuthorMark42, L. Dudko, A. Ershov, V. Klyukhin, N. Korneeva, I. Lokhtin, I. Miagkov, S. Obraztsov, M. Perfilov, V. Savrin, P. Volkov \cmsinstskip**Novosibirsk State University (NSU),  Novosibirsk, Russia

** V. Blinov\cmsAuthorMark43, Y.Skovpen\cmsAuthorMark43, D. Shtol\cmsAuthorMark43 \cmsinstskip**State Research Center of Russian Federation, Institute for High Energy Physics, Protvino, Russia

** I. Azhgirey, I. Bayshev, S. Bitioukov, D. Elumakhov, V. Kachanov, A. Kalinin, D. Konstantinov, V. Krychkine, V. Petrov, R. Ryutin, A. Sobol, S. Troshin, N. Tyurin, A. Uzunian, A. Volkov \cmsinstskip**University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia

** P. Adzic\cmsAuthorMark44, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic, V. Rekovic \cmsinstskip**Centro de Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT),  Madrid, Spain

** J. Alcaraz Maestre, M. Barrio Luna, E. Calvo, M. Cerrada, M. Chamizo Llatas, N. Colino, B. De La Cruz, A. Delgado Peris, A. Escalante Del Valle, C. Fernandez Bedoya, J.P. Fernández Ramos, J. Flix, M.C. Fouz, P. Garcia-Abia, O. Gonzalez Lopez, S. Goy Lopez, J.M. Hernandez, M.I. Josa, E. Navarro De Martino, A. Pérez-Calero Yzquierdo, J. Puerta Pelayo, A. Quintario Olmeda, I. Redondo, L. Romero, M.S. Soares \cmsinstskip**Universidad Autónoma de Madrid, Madrid, Spain

** J.F. de Trocóniz, M. Missiroli, D. Moran \cmsinstskip**Universidad de Oviedo, Oviedo, Spain

** J. Cuevas, J. Fernandez Menendez, I. Gonzalez Caballero, J.R. González Fernández, E. Palencia Cortezon, S. Sanchez Cruz, I. Suárez Andrés, P. Vischia, J.M. Vizan Garcia \cmsinstskip**Instituto de Física de Cantabria (IFCA),  CSIC-Universidad de Cantabria, Santander, Spain

** I.J. Cabrillo, A. Calderon, E. Curras, M. Fernandez, J. Garcia-Ferrero, G. Gomez, A. Lopez Virto, J. Marco, C. Martinez Rivero, F. Matorras, J. Piedra Gomez, T. Rodrigo, A. Ruiz-Jimeno, L. Scodellaro, N. Trevisani, I. Vila, R. Vilar Cortabitarte \cmsinstskip**CERN, European Organization for Nuclear Research, Geneva, Switzerland

** D. Abbaneo, E. Auffray, G. Auzinger, P. Baillon, A.H. Ball, D. Barney, P. Bloch, A. Bocci, C. Botta, T. Camporesi, R. Castello, M. Cepeda, G. Cerminara, Y. Chen, D. d’Enterria, A. Dabrowski, V. Daponte, A. David, M. De Gruttola, A. De Roeck, E. Di Marco\cmsAuthorMark45, M. Dobson, B. Dorney, T. du Pree, D. Duggan, M. Dünser, N. Dupont, A. Elliott-Peisert, P. Everaerts, S. Fartoukh, G. Franzoni, J. Fulcher, W. Funk, D. Gigi, K. Gill, M. Girone, F. Glege, D. Gulhan, S. Gundacker, M. Guthoff, P. Harris, J. Hegeman, V. Innocente, P. Janot, J. Kieseler, H. Kirschenmann, V. Knünz, A. Kornmayer\cmsAuthorMark16, M.J. Kortelainen, K. Kousouris, M. Krammer\cmsAuthorMark1, C. Lange, P. Lecoq, C. Lourenço, M.T. Lucchini, L. Malgeri, M. Mannelli, A. Martelli, F. Meijers, J.A. Merlin, S. Mersi, E. Meschi, P. Milenovic\cmsAuthorMark46, F. Moortgat, S. Morovic, M. Mulders, H. Neugebauer, S. Orfanelli, L. Orsini, L. Pape, E. Perez, M. Peruzzi, A. Petrilli, G. Petrucciani, A. Pfeiffer, M. Pierini, A. Racz, T. Reis, G. Rolandi\cmsAuthorMark47, M. Rovere, H. Sakulin, J.B. Sauvan, C. Schäfer, C. Schwick, M. Seidel, A. Sharma, P. Silva, P. Sphicas\cmsAuthorMark48, J. Steggemann, M. Stoye, Y. Takahashi, M. Tosi, D. Treille, A. Triossi, A. Tsirou, V. Veckalns\cmsAuthorMark49, G.I. Veres\cmsAuthorMark21, M. Verweij, N. Wardle, H.K. Wöhri, A. Zagozdzinska\cmsAuthorMark36, W.D. Zeuner \cmsinstskip**Paul Scherrer Institut, Villigen, Switzerland

** W. Bertl, K. Deiters, W. Erdmann, R. Horisberger, Q. Ingram, H.C. Kaestli, D. Kotlinski, U. Langenegger, T. Rohe, S.A. Wiederkehr \cmsinstskip**Institute for Particle Physics, ETH Zurich, Zurich, Switzerland

** F. Bachmair, L. Bäni, L. Bianchini, B. Casal, G. Dissertori, M. Dittmar, M. Donegà, C. Grab, C. Heidegger, D. Hits, J. Hoss, G. Kasieczka, W. Lustermann, B. Mangano, M. Marionneau, P. Martinez Ruiz del Arbol, M. Masciovecchio, M.T. Meinhard, D. Meister, F. Micheli, P. Musella, F. Nessi-Tedaldi, F. Pandolfi, J. Pata, F. Pauss, G. Perrin, L. Perrozzi, M. Quittnat, M. Rossini, M. Schönenberger, A. Starodumov\cmsAuthorMark50, V.R. Tavolaro, K. Theofilatos, R. Wallny \cmsinstskip**Universität Zürich, Zurich, Switzerland

** T.K. Aarrestad, C. Amsler\cmsAuthorMark51, L. Caminada, M.F. Canelli, A. De Cosa, C. Galloni, A. Hinzmann, T. Hreus, B. Kilminster, J. Ngadiuba, D. Pinna, G. Rauco, P. Robmann, D. Salerno, C. Seitz, Y. Yang, A. Zucchetta \cmsinstskip**National Central University, Chung-Li, Taiwan

** V. Candelise, T.H. Doan, Sh. Jain, R. Khurana, M. Konyushikhin, C.M. Kuo, W. Lin, A. Pozdnyakov, S.S. Yu \cmsinstskip**National Taiwan University (NTU),  Taipei, Taiwan

** Arun Kumar, P. Chang, Y.H. Chang, Y. Chao, K.F. Chen, P.H. Chen, F. Fiori, W.-S. Hou, Y. Hsiung, Y.F. Liu, R.-S. Lu, M. Miñano Moya, E. Paganis, A. Psallidas, J.f. Tsai \cmsinstskip**Chulalongkorn University, Faculty of Science, Department of Physics, Bangkok, Thailand

** B. Asavapibhop, G. Singh, N. Srimanobhas, N. Suwonjandee \cmsinstskip**Cukurova University - Physics Department, Science and Art Faculty

** A. Adiguzel, M.N. Bakirci\cmsAuthorMark52, S. Damarseckin, Z.S. Demiroglu, C. Dozen, E. Eskut, S. Girgis, G. Gokbulut, Y. Guler, I. Hos\cmsAuthorMark53, E.E. Kangal\cmsAuthorMark54, O. Kara, U. Kiminsu, M. Oglakci, G. Onengut\cmsAuthorMark55, K. Ozdemir\cmsAuthorMark56, S. Ozturk\cmsAuthorMark52, A. Polatoz, D. Sunar Cerci\cmsAuthorMark57, S. Turkcapar, I.S. Zorbakir, C. Zorbilmez \cmsinstskip**Middle East Technical University, Physics Department, Ankara, Turkey

** B. Bilin, S. Bilmis, B. Isildak\cmsAuthorMark58, G. Karapinar\cmsAuthorMark59, M. Yalvac, M. Zeyrek \cmsinstskip**Bogazici University, Istanbul, Turkey

** E. Gülmez, M. Kaya\cmsAuthorMark60, O. Kaya\cmsAuthorMark61, E.A. Yetkin\cmsAuthorMark62, T. Yetkin\cmsAuthorMark63 \cmsinstskip**Istanbul Technical University, Istanbul, Turkey

** A. Cakir, K. Cankocak, S. Sen\cmsAuthorMark64 \cmsinstskip**Institute for Scintillation Materials of National Academy of Science of Ukraine, Kharkov, Ukraine

** B. Grynyov \cmsinstskip**National Scientific Center, Kharkov Institute of Physics and Technology, Kharkov, Ukraine

** L. Levchuk, P. Sorokin \cmsinstskip**University of Bristol, Bristol, United Kingdom

** R. Aggleton, F. Ball, L. Beck, J.J. Brooke, D. Burns, E. Clement, D. Cussans, H. Flacher, J. Goldstein, M. Grimes, G.P. Heath, H.F. Heath, J. Jacob, L. Kreczko, C. Lucas, D.M. Newbold\cmsAuthorMark65, S. Paramesvaran, A. Poll, T. Sakuma, S. Seif El Nasr-storey, D. Smith, V.J. Smith \cmsinstskip**Rutherford Appleton Laboratory, Didcot, United Kingdom

** K.W. Bell, A. Belyaev\cmsAuthorMark66, C. Brew, R.M. Brown, L. Calligaris, D. Cieri, D.J.A. Cockerill, J.A. Coughlan, K. Harder, S. Harper, E. Olaiya, D. Petyt, C.H. Shepherd-Themistocleous, A. Thea, I.R. Tomalin, T. Williams \cmsinstskip**Imperial College, London, United Kingdom

** M. Baber, R. Bainbridge, O. Buchmuller, A. Bundock, D. Burton, S. Casasso, M. Citron, D. Colling, L. Corpe, P. Dauncey, G. Davies, A. De Wit, M. Della Negra, R. Di Maria, P. Dunne, A. Elwood, D. Futyan, Y. Haddad, G. Hall, G. Iles, T. James, R. Lane, C. Laner, R. Lucas\cmsAuthorMark65, L. Lyons, A.-M. Magnan, S. Malik, L. Mastrolorenzo, J. Nash, A. Nikitenko\cmsAuthorMark50, J. Pela, B. Penning, M. Pesaresi, D.M. Raymond, A. Richards, A. Rose, E. Scott, C. Seez, S. Summers, A. Tapper, K. Uchida, M. Vazquez Acosta\cmsAuthorMark67, T. Virdee\cmsAuthorMark16, J. Wright, S.C. Zenz \cmsinstskip**Brunel University, Uxbridge, United Kingdom

** J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, I.D. Reid, P. Symonds, L. Teodorescu, M. Turner \cmsinstskip**Baylor University, Waco, USA

** A. Borzou, K. Call, J. Dittmann, K. Hatakeyama, H. Liu, N. Pastika \cmsinstskip**Catholic University of America

** R. Bartek, A. Dominguez \cmsinstskip**The University of Alabama, Tuscaloosa, USA

** A. Buccilli, S.I. Cooper, C. Henderson, P. Rumerio, C. West \cmsinstskip**Boston University, Boston, USA

** D. Arcaro, A. Avetisyan, T. Bose, D. Gastler, D. Rankin, C. Richardson, J. Rohlf, L. Sulak, D. Zou \cmsinstskip**Brown University, Providence, USA

** G. Benelli, D. Cutts, A. Garabedian, J. Hakala, U. Heintz, J.M. Hogan, O. Jesus, K.H.M. Kwok, E. Laird, G. Landsberg, Z. Mao, M. Narain, S. Piperov, S. Sagir, E. Spencer, R. Syarif \cmsinstskip**University of California, Davis, Davis, USA

** R. Breedon, D. Burns, M. Calderon De La Barca Sanchez, S. Chauhan, M. Chertok, J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk, M. Gardner, W. Ko, R. Lander, C. Mclean, M. Mulhearn, D. Pellett, J. Pilot, S. Shalhout, M. Shi, J. Smith, M. Squires, D. Stolp, K. Tos, M. Tripathi \cmsinstskip**University of California, Los Angeles, USA

** M. Bachtis, C. Bravo, R. Cousins, A. Dasgupta, A. Florent, J. Hauser, M. Ignatenko, N. Mccoll, D. Saltzberg, C. Schnaible, V. Valuev, M. Weber \cmsinstskip**University of California, Riverside, Riverside, USA

** E. Bouvier, K. Burt, R. Clare, J. Ellison, J.W. Gary, S.M.A. Ghiasi Shirazi, G. Hanson, J. Heilman, P. Jandir, E. Kennedy, F. Lacroix, O.R. Long, M. Olmedo Negrete, M.I. Paneva, A. Shrinivas, W. Si, H. Wei, S. Wimpenny, B. R. Yates \cmsinstskip**University of California, San Diego, La Jolla, USA

** J.G. Branson, G.B. Cerati, S. Cittolin, M. Derdzinski, R. Gerosa, A. Holzner, D. Klein, V. Krutelyov, J. Letts, I. Macneill, D. Olivito, S. Padhi, M. Pieri, M. Sani, V. Sharma, S. Simon, M. Tadel, A. Vartak, S. Wasserbaech\cmsAuthorMark68, C. Welke, J. Wood, F. Würthwein, A. Yagil, G. Zevi Della Porta \cmsinstskip**University of California, Santa Barbara - Department of Physics, Santa Barbara, USA

** N. Amin, R. Bhandari, J. Bradmiller-Feld, C. Campagnari, A. Dishaw, V. Dutta, M. Franco Sevilla, C. George, F. Golf, L. Gouskos, J. Gran, R. Heller, J. Incandela, S.D. Mullin, A. Ovcharova, H. Qu, J. Richman, D. Stuart, I. Suarez, J. Yoo \cmsinstskip**California Institute of Technology, Pasadena, USA

** D. Anderson, J. Bendavid, A. Bornheim, J. Bunn, J. Duarte, J.M. Lawhorn, A. Mott, H.B. Newman, C. Pena, M. Spiropulu, J.R. Vlimant, S. Xie, R.Y. Zhu \cmsinstskip**Carnegie Mellon University, Pittsburgh, USA

** M.B. Andrews, T. Ferguson, M. Paulini, J. Russ, M. Sun, H. Vogel, I. Vorobiev, M. Weinberg \cmsinstskip**University of Colorado Boulder, Boulder, USA

** J.P. Cumalat, W.T. Ford, F. Jensen, A. Johnson, M. Krohn, S. Leontsinis, T. Mulholland, K. Stenson, S.R. Wagner \cmsinstskip**Cornell University, Ithaca, USA

** J. Alexander, J. Chaves, J. Chu, S. Dittmer, K. Mcdermott, N. Mirman, G. Nicolas Kaufman, J.R. Patterson, A. Rinkevicius, A. Ryd, L. Skinnari, L. Soffi, S.M. Tan, Z. Tao, J. Thom, J. Tucker, P. Wittich, M. Zientek \cmsinstskip**Fairfield University, Fairfield, USA

** D. Winn \cmsinstskip**Fermi National Accelerator Laboratory, Batavia, USA

** S. Abdullin, M. Albrow, G. Apollinari, A. Apresyan, S. Banerjee, L.A.T. Bauerdick, A. Beretvas, J. Berryhill, P.C. Bhat, G. Bolla, K. Burkett, J.N. Butler, H.W.K. Cheung, F. Chlebana, S. Cihangir${}^{\textrm{\textdagger}}$, M. Cremonesi, V.D. Elvira, I. Fisk, J. Freeman, E. Gottschalk, L. Gray, D. Green, S. Grünendahl, O. Gutsche, D. Hare, R.M. Harris, S. Hasegawa, J. Hirschauer, Z. Hu, B. Jayatilaka, S. Jindariani, M. Johnson, U. Joshi, B. Klima, B. Kreis, S. Lammel, J. Linacre, D. Lincoln, R. Lipton, M. Liu, T. Liu, R. Lopes De Sá, J. Lykken, K. Maeshima, N. Magini, J.M. Marraffino, S. Maruyama, D. Mason, P. McBride, P. Merkel, S. Mrenna, S. Nahn, V. O’Dell, K. Pedro, O. Prokofyev, G. Rakness, L. Ristori, E. Sexton-Kennedy, A. Soha, W.J. Spalding, L. Spiegel, S. Stoynev, J. Strait, N. Strobbe, L. Taylor, S. Tkaczyk, N.V. Tran, L. Uplegger, E.W. Vaandering, C. Vernieri, M. Verzocchi, R. Vidal, M. Wang, H.A. Weber, A. Whitbeck, Y. Wu \cmsinstskip**University of Florida, Gainesville, USA

** D. Acosta, P. Avery, P. Bortignon, D. Bourilkov, A. Brinkerhoff, A. Carnes, M. Carver, D. Curry, S. Das, R.D. Field, I.K. Furic, J. Konigsberg, A. Korytov, J.F. Low, P. Ma, K. Matchev, H. Mei, G. Mitselmakher, D. Rank, L. Shchutska, D. Sperka, L. Thomas, J. Wang, S. Wang, J. Yelton \cmsinstskip**Florida International University, Miami, USA

** S. Linn, P. Markowitz, G. Martinez, J.L. Rodriguez \cmsinstskip**Florida State University, Tallahassee, USA

** A. Ackert, T. Adams, A. Askew, S. Bein, S. Hagopian, V. Hagopian, K.F. Johnson, T. Kolberg, H. Prosper, A. Santra, R. Yohay \cmsinstskip**Florida Institute of Technology, Melbourne, USA

** M.M. Baarmand, V. Bhopatkar, S. Colafranceschi, M. Hohlmann, D. Noonan, T. Roy, F. Yumiceva \cmsinstskip**University of Illinois at Chicago (UIC),  Chicago, USA

** M.R. Adams, L. Apanasevich, D. Berry, R.R. Betts, I. Bucinskaite, R. Cavanaugh, O. Evdokimov, L. Gauthier, C.E. Gerber, D.J. Hofman, K. Jung, I.D. Sandoval Gonzalez, N. Varelas, H. Wang, Z. Wu, M. Zakaria, J. Zhang \cmsinstskip**The University of Iowa, Iowa City, USA

** B. Bilki\cmsAuthorMark69, W. Clarida, K. Dilsiz, S. Durgut, R.P. Gandrajula, M. Haytmyradov, V. Khristenko, J.-P. Merlo, H. Mermerkaya\cmsAuthorMark70, A. Mestvirishvili, A. Moeller, J. Nachtman, H. Ogul, Y. Onel, F. Ozok\cmsAuthorMark71, A. Penzo, C. Snyder, E. Tiras, J. Wetzel, K. Yi \cmsinstskip**Johns Hopkins University, Baltimore, USA

** B. Blumenfeld, A. Cocoros, N. Eminizer, D. Fehling, L. Feng, A.V. Gritsan, P. Maksimovic, J. Roskes, U. Sarica, M. Swartz, M. Xiao, C. You \cmsinstskip**The University of Kansas, Lawrence, USA

** A. Al-bataineh, P. Baringer, A. Bean, S. Boren, J. Bowen, J. Castle, L. Forthomme, R.P. Kenny III, S. Khalil, A. Kropivnitskaya, D. Majumder, W. Mcbrayer, M. Murray, S. Sanders, R. Stringer, J.D. Tapia Takaki, Q. Wang \cmsinstskip**Kansas State University, Manhattan, USA

** A. Ivanov, K. Kaadze, Y. Maravin, A. Mohammadi, L.K. Saini, N. Skhirtladze, S. Toda \cmsinstskip**Lawrence Livermore National Laboratory, Livermore, USA

** F. Rebassoo, D. Wright \cmsinstskip**University of Maryland, College Park, USA

** C. Anelli, A. Baden, O. Baron, A. Belloni, B. Calvert, S.C. Eno, C. Ferraioli, J.A. Gomez, N.J. Hadley, S. Jabeen, G.Y. Jeng, R.G. Kellogg, J. Kunkle, A.C. Mignerey, F. Ricci-Tam, Y.H. Shin, A. Skuja, M.B. Tonjes, S.C. Tonwar \cmsinstskip**Massachusetts Institute of Technology, Cambridge, USA

** D. Abercrombie, B. Allen, A. Apyan, V. Azzolini, R. Barbieri, A. Baty, R. Bi, K. Bierwagen, S. Brandt, W. Busza, I.A. Cali, M. D’Alfonso, Z. Demiragli, G. Gomez Ceballos, M. Goncharov, D. Hsu, Y. Iiyama, G.M. Innocenti, M. Klute, D. Kovalskyi, K. Krajczar, Y.S. Lai, Y.-J. Lee, A. Levin, P.D. Luckey, B. Maier, A.C. Marini, C. Mcginn, C. Mironov, S. Narayanan, X. Niu, C. Paus, C. Roland, G. Roland, J. Salfeld-Nebgen, G.S.F. Stephans, K. Tatar, D. Velicanu, J. Wang, T.W. Wang, B. Wyslouch \cmsinstskip**University of Minnesota, Minneapolis, USA

** A.C. Benvenuti, R.M. Chatterjee, A. Evans, P. Hansen, S. Kalafut, S.C. Kao, Y. Kubota, Z. Lesko, J. Mans, S. Nourbakhsh, N. Ruckstuhl, R. Rusack, N. Tambe, J. Turkewitz \cmsinstskip**University of Mississippi, Oxford, USA

** J.G. Acosta, S. Oliveros \cmsinstskip**University of Nebraska-Lincoln, Lincoln, USA

** E. Avdeeva, K. Bloom, D.R. Claes, C. Fangmeier, R. Gonzalez Suarez, R. Kamalieddin, I. Kravchenko, A. Malta Rodrigues, J. Monroy, J.E. Siado, G.R. Snow, B. Stieger \cmsinstskip**State University of New York at Buffalo, Buffalo, USA

** M. Alyari, J. Dolen, A. Godshalk, C. Harrington, I. Iashvili, J. Kaisen, D. Nguyen, A. Parker, S. Rappoccio, B. Roozbahani \cmsinstskip**Northeastern University, Boston, USA

** G. Alverson, E. Barberis, A. Hortiangtham, A. Massironi, D.M. Morse, D. Nash, T. Orimoto, R. Teixeira De Lima, D. Trocino, R.-J. Wang, D. Wood \cmsinstskip**Northwestern University, Evanston, USA

** S. Bhattacharya, O. Charaf, K.A. Hahn, A. Kumar, N. Mucia, N. Odell, B. Pollack, M.H. Schmitt, K. Sung, M. Trovato, M. Velasco \cmsinstskip**University of Notre Dame, Notre Dame, USA

** N. Dev, M. Hildreth, K. Hurtado Anampa, C. Jessop, D.J. Karmgard, N. Kellams, K. Lannon, N. Marinelli, F. Meng, C. Mueller, Y. Musienko\cmsAuthorMark37, M. Planer, A. Reinsvold, R. Ruchti, N. Rupprecht, G. Smith, S. Taroni, M. Wayne, M. Wolf, A. Woodard \cmsinstskip**The Ohio State University, Columbus, USA

** J. Alimena, L. Antonelli, B. Bylsma, L.S. Durkin, S. Flowers, B. Francis, A. Hart, C. Hill, R. Hughes, W. Ji, B. Liu, W. Luo, D. Puigh, B.L. Winer, H.W. Wulsin \cmsinstskip**Princeton University, Princeton, USA

** S. Cooperstein, O. Driga, P. Elmer, J. Hardenbrook, P. Hebda, D. Lange, J. Luo, D. Marlow, T. Medvedeva, K. Mei, I. Ojalvo, J. Olsen, C. Palmer, P. Piroué, D. Stickland, A. Svyatkovskiy, C. Tully \cmsinstskip**University of Puerto Rico, Mayaguez, USA

** S. Malik \cmsinstskip**Purdue University, West Lafayette, USA

** A. Barker, V.E. Barnes, S. Folgueras, L. Gutay, M.K. Jha, M. Jones, A.W. Jung, A. Khatiwada, D.H. Miller, N. Neumeister, J.F. Schulte, X. Shi, J. Sun, F. Wang, W. Xie \cmsinstskip**Purdue University Northwest, Hammond, USA

** N. Parashar, J. Stupak \cmsinstskip**Rice University, Houston, USA

** A. Adair, B. Akgun, Z. Chen, K.M. Ecklund, F.J.M. Geurts, M. Guilbaud, W. Li, B. Michlin, M. Northup, B.P. Padley, J. Roberts, J. Rorie, Z. Tu, J. Zabel \cmsinstskip**University of Rochester, Rochester, USA

** B. Betchart, A. Bodek, P. de Barbaro, R. Demina, Y.t. Duh, T. Ferbel, M. Galanti, A. Garcia-Bellido, J. Han, O. Hindrichs, A. Khukhunaishvili, K.H. Lo, P. Tan, M. Verzetti \cmsinstskip**Rutgers, The State University of New Jersey, Piscataway, USA

** A. Agapitos, J.P. Chou, Y. Gershtein, T.A. Gómez Espinosa, E. Halkiadakis, M. Heindl, E. Hughes, S. Kaplan, R. Kunnawalkam Elayavalli, S. Kyriacou, A. Lath, K. Nash, M. Osherson, H. Saka, S. Salur, S. Schnetzer, D. Sheffield, S. Somalwar, R. Stone, S. Thomas, P. Thomassen, M. Walker \cmsinstskip**University of Tennessee, Knoxville, USA

** A.G. Delannoy, M. Foerster, J. Heideman, G. Riley, K. Rose, S. Spanier, K. Thapa \cmsinstskip**Texas A&M University, College Station, USA

** O. Bouhali\cmsAuthorMark72, A. Celik, M. Dalchenko, M. De Mattia, A. Delgado, S. Dildick, R. Eusebi, J. Gilmore, T. Huang, E. Juska, T. Kamon\cmsAuthorMark73, R. Mueller, Y. Pakhotin, R. Patel, A. Perloff, L. Perniè, D. Rathjens, A. Safonov, A. Tatarinov, K.A. Ulmer \cmsinstskip**Texas Tech University, Lubbock, USA

** N. Akchurin, C. Cowden, J. Damgov, F. De Guio, C. Dragoiu, P.R. Dudero, J. Faulkner, E. Gurpinar, S. Kunori, K. Lamichhane, S.W. Lee, T. Libeiro, T. Peltola, S. Undleeb, I. Volobouev, Z. Wang \cmsinstskip**Vanderbilt University, Nashville, USA

** S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, P. Sheldon, S. Tuo, J. Velkovska, Q. Xu \cmsinstskip**University of Virginia, Charlottesville, USA

** M.W. Arenton, P. Barria, B. Cox, J. Goodell, R. Hirosky, A. Ledovskoy, H. Li, C. Neu, T. Sinthuprasith, X. Sun, Y. Wang, E. Wolfe, F. Xia \cmsinstskip**Wayne State University, Detroit, USA

** C. Clarke, R. Harr, P.E. Karchin, J. Sturdy \cmsinstskip**University of Wisconsin - Madison, Madison, WI, USA

** D.A. Belknap, J. Buchanan, C. Caillol, S. Dasu, L. Dodd, S. Duric, B. Gomber, M. Grothe, M. Herndon, A. Hervé, P. Klabbers, A. Lanaro, A. Levine, K. Long, R. Loveless, T. Perry, G.A. Pierro, G. Polese, T. Ruggles, A. Savin, N. Smith, W.H. Smith, D. Taylor, N. Woods \cmsinstskip†: Deceased

1:  Also at Vienna University of Technology, Vienna, Austria

2:  Also at State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, China

3:  Also at Institut Pluridisciplinaire Hubert Curien (IPHC), Université de Strasbourg, CNRS/IN2P3, Strasbourg, France

4:  Also at Universidade Estadual de Campinas, Campinas, Brazil

5:  Also at Universidade Federal de Pelotas, Pelotas, Brazil

6:  Also at Université Libre de Bruxelles, Bruxelles, Belgium

7:  Also at Deutsches Elektronen-Synchrotron, Hamburg, Germany

8:  Also at Joint Institute for Nuclear Research, Dubna, Russia

9:  Also at Helwan University, Cairo, Egypt

10: Now at Zewail City of Science and Technology, Zewail, Egypt

11: Now at Fayoum University, El-Fayoum, Egypt

12: Also at British University in Egypt, Cairo, Egypt

13: Now at Ain Shams University, Cairo, Egypt

14: Also at Université de Haute Alsace, Mulhouse, France

15: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia

16: Also at CERN, European Organization for Nuclear Research, Geneva, Switzerland

17: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany

18: Also at University of Hamburg, Hamburg, Germany

19: Also at Brandenburg University of Technology, Cottbus, Germany

20: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary

21: Also at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös Loránd University, Budapest, Hungary

22: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary

23: Also at Indian Institute of Technology Bhubaneswar, Bhubaneswar, India

24: Also at University of Visva-Bharati, Santiniketan, India

25: Also at Indian Institute of Science Education and Research, Bhopal, India

26: Also at Institute of Physics, Bhubaneswar, India

27: Also at University of Ruhuna, Matara, Sri Lanka

28: Also at Isfahan University of Technology, Isfahan, Iran

29: Also at Yazd University, Yazd, Iran

30: Also at Plasma Physics Research Center, Science and Research Branch, Islamic Azad University, Tehran, Iran

31: Also at Università degli Studi di Siena, Siena, Italy

32: Also at Purdue University, West Lafayette, USA

33: Also at International Islamic University of Malaysia, Kuala Lumpur, Malaysia

34: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia

35: Also at Consejo Nacional de Ciencia y Tecnología, Mexico city, Mexico

36: Also at Warsaw University of Technology, Institute of Electronic Systems, Warsaw, Poland

37: Also at Institute for Nuclear Research, Moscow, Russia

38: Now at National Research Nuclear University ’Moscow Engineering Physics Institute’ (MEPhI), Moscow, Russia

39: Also at St. Petersburg State Polytechnical University, St. Petersburg, Russia

40: Also at University of Florida, Gainesville, USA

41: Also at P.N. Lebedev Physical Institute, Moscow, Russia

42: Also at California Institute of Technology, Pasadena, USA

43: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia

44: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia

45: Also at INFN Sezione di Roma; Università di Roma, Roma, Italy

46: Also at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia

47: Also at Scuola Normale e Sezione dell’INFN, Pisa, Italy

48: Also at National and Kapodistrian University of Athens, Athens, Greece

49: Also at Riga Technical University, Riga, Latvia

50: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia

51: Also at Albert Einstein Center for Fundamental Physics, Bern, Switzerland

52: Also at Gaziosmanpasa University, Tokat, Turkey

53: Also at Istanbul Aydin University, Istanbul, Turkey

54: Also at Mersin University, Mersin, Turkey

55: Also at Cag University, Mersin, Turkey

56: Also at Piri Reis University, Istanbul, Turkey

57: Also at Adiyaman University, Adiyaman, Turkey

58: Also at Ozyegin University, Istanbul, Turkey

59: Also at Izmir Institute of Technology, Izmir, Turkey

60: Also at Marmara University, Istanbul, Turkey

61: Also at Kafkas University, Kars, Turkey

62: Also at Istanbul Bilgi University, Istanbul, Turkey

63: Also at Yildiz Technical University, Istanbul, Turkey

64: Also at Hacettepe University, Ankara, Turkey

65: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom

66: Also at School of Physics and Astronomy, University of Southampton, Southampton, United Kingdom

67: Also at Instituto de Astrofísica de Canarias, La Laguna, Spain

68: Also at Utah Valley University, Orem, USA

69: Also at Argonne National Laboratory, Argonne, USA

70: Also at Erzincan University, Erzincan, Turkey

71: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey

72: Also at Texas A&M University at Qatar, Doha, Qatar

73: Also at Kyungpook National University, Daegu, Korea