Measurement of masses in the tt system by kinematic endpoints in pp collisions at √s=7TeV

Eur. Phys. J. C (2013) 73:2494 DOI 10.1140/epjc/s10052-013-2494-7 Regular Article - Experimental Physics Measurement of masses in the tt system by kinematic endpoints in pp collisions at √s=7TeV The CMS Collaboration∗ CERN, Geneva, Switzerland Received: 21 April 2013 / Revised: 18 June 2013 / Published online: 16 July 2013 © CERN for the benefit of the CMS collaboration 2013. This article is published with open access at Springerlink.com Abstract A simultaneous measurement of the top-quark, W-boson, and neutrino masses is reported for tt events selected in the dilepton final state from a data sample corresponding to an integrated luminosity of 5.0 fb−1collected by the CMS experiment in pp collisions at √s=7TeV. The analysis is based on endpoint determinations in kinematic distributions. When the neutrino and W-boson masses are constrained to their world-average values, a top-quark mass value of Mt=173.9±0.9(stat.) +1.7 −2.1(syst.) GeV is obtained. When such constraints are not used, the three particle masses are obtained in a simultaneous fit. In this unconstrained mode the study serves as a test of mass determination methods that may be used in beyond standard model physics scenarios where several masses in a decay chain may be unknown and undetected particles lead to underconstrained kinematics. 1 Introduction The determination of the top-quark mass sets a fundamental benchmark for the standard model (SM), and is one of the precision measurements that defines electroweak constraints on possible new physics beyond the SM [1]. With the recent observations [2,3] of a Higgs boson candidate at a mass of approximately 125 GeV, existing data can now overconstrain the SM. The top quark plays an important role in such constraints because its large mass, appearing quadratically in loop corrections to many SM observables, dominates other contributions. It is also key to the quartic term in the Higgs potential at high energy, and therefore to the question of stability of the electroweak vacuum [4,5]. For these reasons, precise top-quark mass determinations are essential to characterize and probe the SM. Recent results obtained at the Large Hadron Collider (LHC) ∗e-mail: [email protected] for the top-quark mass in tt events include those reported by ATLAS [6], Mt=174.5±0.6(stat.)±2.3 (syst.) GeV, and by the Compact Muon Solenoid (CMS) [7], Mt= 173.49 ±0.43 (stat.) ±0.98 (syst.) GeV, using the semileptonic decay channel of the tt pair. The CMS Collaboration has also reported a measurement [8] in the dilepton channel, Mt=172.5±0.4(stat.)±1.5 (syst.) GeV. A recent summary of top-quark mass measurements conducted by the CDF and D0 Collaborations [9] reports a combined result Mt=173.18 ±0.56 (stat.) ±0.75 (syst.) GeV. In parallel with recent measurements of the properties of the top quark at the LHC, there has been a great deal of theoretical progress on methods using endpoints of kinematic variables to measure particle masses with minimal input from simulation. These methods are generally aimed at measuring the masses of new particles, should they be discovered, but can also be applied to measure the masses of standard model particles such as the top quark. Such an application acts as both a test of the methods and a measurement of the top-quark mass utilizing technique very different from those used in previous studies. Indeed, top-quark pair production provides a good match to these new methods, as dilepton decays of top-quark pairs (tt→(b+ν)(b−¯ν)) provide challenges in mass measurement very similar to the ones that these methods were designed to solve. A key feature of many current theories of physics beyond the standard model is the existence of a candidate for dark matter, such as a weakly interacting massive particle (WIMP). These particles are usually stabilized in a theory by a conserved parity, often introduced ad hoc, under which SM particles are even and new-physics particles are odd. Examples include R-parity in supersymmetry (SUSY) and T-parity in little-Higgs models. One consequence of this parity is that new physics particles must be produced in pairs. Each of the pair-produced particles will then decay to a cascade of SM particles, terminating with the lightest odd-parity particle of the new theory. In such cases, there Page 2 of 28 Eur. Phys. J. C (2013) 73:2494 Fig. 1 Top-quark pair dilepton decays, with two jets, two leptons, and two unobserved particles (left) exhibit a signature similar to some SUSY modes (right). In the figure, u,χ±,ν,andχ0denote the u-squark, chargino, sneutrino, and neutralino respectively; an asterisk indicates the antiparticle of the corresponding SUSY particle will be two particles which do not interact with the detector, yielding events where the observable kinematics are underconstrained. Mass measurements in these events are further complicated by the presence of multiple new particles with unknown masses. The dilepton decays of tt events at the LHC offer a rich source of symmetric decay chains terminating in two neutrinos. With their combination of jets, leptons, and undetected particles, these tt events bear close kinematic and topological resemblance to new-physics scenarios such as the supersymmetric decay chain illustrated in Fig. 1. This correspondence has motivated [10] the idea to use the abundant ttsamples of the LHC as a testbed for the new methods and novel observables that have been proposed to handle mass measurement in new-physics events [11]. A simultaneous measurement of the top-quark, W-boson, and neutrino masses in dilepton tt decays closely mimics the strategies needed for studies of new physics. The analysis presented here focuses on the MT2 variable and its variants [11,12]. These kinematic observables are mass estimators that will be defined in Sect. 4. The goals of this analysis are two-fold: to demonstrate the performance of a new mass measurement technique, and to make a precise measurement of the top-quark mass. To demonstrate the performance of the method, we apply it to the tt system assuming no knowledge of the W-boson or neutrino masses. This allows us to measure the masses of all three undetected particles involved in the dilepton decay: the top quark, W boson, and neutrino. This “unconstrained” fit provides a test of the method under conditions similar to what one might expect to find when attempting to measure the masses of new particles. In order to make a precise measurement of the topquark mass, on the other hand, we assume the world-average values for the W boson and neutrino masses. This “doublyconstrained” fit achieves a precision in the top-quark mass determination similar to that obtained by traditional methods. The MT2 observable has been previously suggested [13] or used [14] in top-quark mass measurements. In considering any top-quark mass measurement, however, it is critical to confront the fact that deep theoretical problems complicate the interpretation of the measurement. The issues arise because a top quark is a colored object while the W boson and hadronic jet observed in the final state are not. In the transition t →Wb, a single color charge must come from elsewhere to neutralize the final-state b jet, with the inevitable consequence that the observed energy and momentum of the final state differ from that of the original top quark. The resulting difference between measured mass and top-quark mass is therefore at least at the level at which soft color exchanges occur, i.e. ∼ΛQCD [15,16]. In the current state of the art, a Monte Carlo (MC) generator is normally used to fix a relationship between the experimentally measured mass of the final state and a top-quark mass parameter of the simulation; but model assumptions upon which the simulation of nonperturbative physics depend further limit the precision of such interpretative statements to about 1GeV[17]. We therefore take care in this measurement to distinguish between the interpretive use of MC simulation described above, which is inherently model dependent, and experimental procedures, which can be made clear and model independent. A distinctive feature of the top-quark mass measurement reported here is its limited dependence on MC simulation. There is no reliance on MC templates [14], and the endpoint method gives a result which is consistent with the kinematic mass in MC without further tuning or correction. For this reason, the measurement outlined here complements the set of conventional top-quark mass measurements, and is applicable to new-physics scenarios where MC simulation is used sparingly. 2 The CMS detector and event reconstruction The central feature of the CMS apparatus is a superconducting solenoid of 6 m internal diameter, providing a magnetic field of 3.8 T. Inside the superconducting solenoid volume are silicon pixel and strip trackers, a lead tungstate crystal electromagnetic calorimeter, and a brass/scintillator hadron calorimeter. Muons are measured in gas-ionization detectors embedded in the steel flux return yoke. Extensive forward calorimetry complements the coverage provided by the barrel and endcap detectors. A more detailed description of the CMS detector can be found in Ref. [18]. Jets, electrons, muons, and missing transverse momentum are reconstructed using a global event reconstruction technique, also called particle-flow event reconstruction [19, 20]. Hadronic jets are clustered from the reconstructed particles with the infrared and collinear-safe anti-kTalgorithm [21], using a size parameter 0.5. The jet momentum is determined as the vectorial sum of all particle momenta in this jet, and is found in the simulation to be within 5 % to 10 % of the true momentum over the whole transverse momentum (pT) spectrum and detector acceptance. Jet energy corrections are derived from the simulation, and are confirmed in measurements on data with the energy balance of Eur. Phys. J. C (2013) 73:2494 Page 3 of 28 dijet and photon +jet events [22]. The jet energy resolution amounts typically to 15 % at jet pTof 10 GeV, 8 % at 100 GeV, and 4 % at 1 TeV. The missing transverse momentum vector is defined by /pT≡−pTwhere the sum is taken over all particle-flow objects in the event; and missing transverse “energy” is given by Emiss T≡|/pT|. 3 Event selection The data set used for this analysis corresponds to an integrated luminosity of 5.0 fb−1of proton-proton collisions at √s=7 TeV recorded by the CMS detector in 2011. We apply an event selection to isolate a dilepton sample that is largely free of backgrounds. We require two wellidentified and isolated opposite-sign leptons (electrons or muons) passing dilepton trigger requirements; the minimum pTrequirements for the triggers are 17 GeV and 8 GeV for the leading and sub-leading leptons. In addition we require at least two b-tagged jets, subsequently used in the topquark reconstruction, and missing transverse energy. Here and throughout this paper, we use (and “lepton”) to denote an electron or muon; the signal decays of interest are t→bν. Leptons must satisfy pT>20 GeV and the event is vetoed if the leptons have the same flavor and their dilepton invariant mass is within 15 GeV of the Z boson mass. If three leptons are found, the two highest-pTleptons forming an opposite-sign pair are selected. Jets must satisfy pT> 30 GeV after correcting for additive effects of pileup (multiple proton collisions in a single crossing) and multiplicative effects of jet energy scale calibration. Jets are further required to lie within |η|<2.5, where ηis the pseudorapidity variable, η≡−ln[tan(θ/2)]. The b-tagging algorithm is the Combined Secondary Vertex (CSV) tagger of Ref. [23], deployed here with an operating point that yields a tagging efficiency of 85 % and mistag rate of 10 %. The mistag rate measures the probability for a light quark or gluon jet to be misidentified as a b jet. In the subsample of events passing all selection requirements of this analysis the b-jet purity is 91 %. Jet masses are required to satisfy a very loose requirement mjet <40 GeV to assure the existence of kinematic solutions and reject poorly reconstructed jets. The missing transverse energy must satisfy Emiss T>30 GeV for e+e− and μ+μ−events and Emiss T>20 GeV for e±μ∓events, where Drell–Yan backgrounds are smaller. With the exception of the b-tagging criteria and the b-jet mass requirement, all selection requirements summarized here are discussed in more detail in [24,25]. The sample of events in data meeting all of the signal selection criteria contains 8700 events. 4 Kinematic variables The endpoint method of mass extraction is based on several variables that are designed for use in the kinematically complex environment of events with two cascade decays, each ending in an invisible particle. The challenge here is twofold, combining the complications of a many-body decay with the limitations of an underconstrained system. In a twobody decay A→BC, the momentum of either daughter in the parent rest frame exhibits a simple and direct relationship to the parent mass. In a three-body decay, A→BCD, the relationship is less direct, encoded not in a delta function of momentum but in the kinematic boundary of the daughters’ phase space. In general, the parent mass may be determined from the endpoints of the observable daughter momenta in the parent rest frame. To carry out this program, however, the daughter masses must be known and enough of the momenta be measurable or constrained by conservation laws to solve the kinematic equations. Applying this program to the measurement of the topquark mass in the decay t →bν, one immediately encounters a number of obstacles. At a hadron collider, the ttsystem is produced with unknown center-of-mass energy and has an event-dependent pT-boost due to recoil from the initialstate radiation (ISR). Furthermore, in pp collisions we can apply constraints of momentum conservation only in the two dimensions transverse to the beam direction. Since top quarks are normally produced in pairs, the individual neutrino momenta are indeterminate, adding further complication. These obstacles seem daunting but can be overcome by the use of “designer” kinematic variables MT2 [12] and MCT [26], which, by construction, address precisely these issues. In this paper we use MT2. Because the transverse momentum of the tt system varies from event to event, the pT-insensitive version [27,28], MT2⊥, is particularly useful. To measure the masses of the top-quark, W-boson, and neutrino, we measure the endpoints of three kinematic distributions, μ,μbb, and Mb, as discussed in the following subsections. 4.1 MT2 and subsystem variables 4.1.1 The MT2 observable The variable MT2 is based on the transverse mass, MT, which was first introduced to measure the W-boson mass in the decay W →ν. In this case, MTis defined by M2 T≡m2 ν+m2 +2Eν TE T−pν T·p T.(4.1) The observable MTrepresents the smallest mass the W boson could have and still give rise to the observed transverse momenta p Tand pν T=/pT. The utility of MTlies in the fact that MT≤MWis guaranteed for W bosons with low transverse momentum. For a single W →ν decay such a lower limit is only marginally informative, but in an ensemble of events, the maximum value achieved, i.e. the endpoint of the MTdistribution, directly reveals the W boson mass. This Page 4 of 28 Eur. Phys. J. C (2013) 73:2494 observation suggests a “min-max” strategy which is generalized by the invention of MT2. The MT2 observable is useful for finding the minimum parent mass that is consistent with observed kinematics when two identical decay chains aand beach terminate in a missing particle. Figure 1shows both a SM and a new physics example. If one knew the two missing transverse momenta separately, a value of MTcould be calculated for either or both of the twin decay chains and the parent mass Mwould satisfy the relationship max(Ma T,Mb T)≤M.In practice the two missing momenta cannot be known separately, and are observable only in the combination pa T+pb T= /pT. This compels one to consider all possible partitions of /pTinto two hypothetical constituents pa Tand pb T, evaluating within this ensemble of partitions the minimum parent mass Mconsistent with the observed event kinematics. With this extension of the MTconcept, the variable is now called MT2: MT2 ≡min pa T+pb T=/pTmaxMa T,Mb T.(4.2) As with MT, the endpoint of the MT2 distribution has a quantifiable relationship to the parent mass, and the endpoint of an MT2 distribution is therefore a measure of the unseen parent mass in events with two identical decay chains. The observable MT2 requires some care in its use. The presence of ET=p2 T+m2in Eq. (4.1) implies that one must either know (as in the case of W →ν)orassume(as in the case of unknown new physics) a value of the mass m of the undetected particle(s). In this paper we will refer to an assumed mass as the “test mass” and distinguish it with a tilde (i.e. m); the actual mass of the missing particle, whether known or not, will be referred to as the “true mass”, and written without the tilde. Both the value of MT2 in any event and the value of the endpoint of the MT2 distribution in an ensemble of events are in the end functions of the test mass. Even when a test mass has been chosen, however, the endpoint of the MT2 distribution may not be unique because it is in general sensitive to transverse momentum PT=|PT| of the underlying two-parent system, which varies from event to event. The sensitivity vanishes if the test mass can be set equal to the true mass, but such an option will not be immediately available in a study of new physics where the true mass is not known. The PTproblem is instead addressed by introducing MT2⊥[27,28], which uses only momentum components transverse to the PTboost direction. In this way, MT2⊥ achieves invariance under PTboosts of the underlying twoparent system. The construction of MT2⊥is identical to that of MT2 except that pTvalues that appear explicitly or implicitly in Eq. (4.1) are everywhere replaced by pT⊥values, where pT⊥is defined to be the component of pTin the direction perpendicular to the PTof the two-parent system. Formally, pT⊥≡ˆ nT×(pT׈ nT), (4.3) where ˆ nT=PT/|PT|is the unit vector parallel to the transverse momentum of the two-parent system. 4.1.2 Subsystem variables A further investigation of MT2 and MT2⊥reveals the full range of kinematic information contained in multistep decay chains by splitting and grouping the elements of the decay chain in independent ways. The MT2 variable classifies the particles in an event into three categories: “upstream”, “visible”, and “child”. The child particles are those at the end of the decay chain that are unobservable or simply treated as unobservable; the visible particles are those whose transverse momenta are measured and used in the calculations; and the upstream particles are those from further up the decay chain, including any ISR accompanying the hard collision. In general, the child, visible, and upstream objects may actually be collections of objects, and the subsystem observables introduced in Ref. [10] parcel out the kinematic information in as many independent groupings as possible. Figure 2shows two of the three possible ways of classifying the tt daughters for MT2 calculations. The μ variable, known Fig. 2 Att dilepton decay with the two subsystems for computing μ and μbb indicated. The “upstream” and “child” objects are enclosed in dashed rectangles, while the visible objects, which enter into the computation, are enclosed in solid rectangles.Theμ and μbb variables used here are identical to M210 T2⊥and M221 T2⊥of Ref. [10] Eur. Phys. J. C (2013) 73:2494 Page 5 of 28 as M210 T2⊥in Ref. [10], uses the two leptons of the tt dilepton decays, treating the neutrinos as lost child particles (which they are), and combining the b jets with all other “upstream” momentum in the event. The μbb variable, known as M221 T2⊥ in Ref. [10], uses the b jets, and treats the W bosons as lost child particles (ignoring the fact that their charged daughter leptons are in fact observable). It considers only ISR jets as generators of upstream momentum. For completeness, we note that a third MT2⊥subsystem can be constructed by combining the b jet and the lepton as a single visible system. This variable, known as M220 T2⊥ in the nomenclature of Ref. [10], exhibits significant correlation with Mb, the invariant mass of the b jet and lepton. A third observable is needed to solve the underlying system of equations, and for this we choose Mb. 4.2 Observables used in this analysis This analysis is based on two MT2⊥variables, μ and μbb as described above, and one invariant mass, Mb,theinvariant mass of a b jet and lepton from the same top-quark decay. These three quantities have been selected from a larger set of possibilities based on the low correlation we observe among them and the generally favorable shapes of the distributions in their endpoint regions. The observables can be summarized by the underlying kinematics from which they are derived, and the endpoint relations which include the top-quark, W-boson, and neutrino masses. For the μ variable, the shape of the distribution is known analytically [27]. In terms of the value x=μ and its kinematic endpoint xmax, the normalized distribution can be written: dN dx=αδ(x) +(1−α) 4x x2 max ln xmax x,(4.4) where the parameter αis treated as an empirical quantity to be measured. In practice, α∼0.6, and the zero bin of μ histograms will be suppressed to better show the features of the endpoint region. The origin of the delta function is geometric: for massless leptons, μ vanishes when the two lepton pT⊥vectors lie on opposite sides of the axis defined by the upstream PTvector, and is equal to 2(p+ T⊥p− T⊥)1/2 otherwise. For a test mass of the child particle mν, the endpoint is related to the masses via [10,27]: μmax  ≡xmax =MW 21−m2 ν M2 W +M2 W 41−m2 ν M2 W2 +m2 ν.(4.5) In the tt case, we set the test mass to mν=0. We then expect the endpoint at μmax  =MW(1−m2 ν/M2 W)=MW= 80.4 GeV. Note that mνis the true mass of the child and MW is the true parent mass; these should be viewed as variables in a function for which mνis a parameter. In a new-physics application, the analogs of MWand mνare not known; but given Eq. (4.5), the measurement of the endpoint, and an arbitrary choice of child mass mν, one can fix a relationship between the two unknown masses. We emphasize that the equality expressed by Eq. (4.5) holds regardless of the value of the test mass, because the test mass enters into both sides of the equation (see discussion in Sect. 4.1.1). This applies below to Eq. (4.6)also. In the case of μbb, the visible particles are the two b jets, the child particles are the charged leptons and neutrinos (combined), and ISR radiation generates the upstream transverse momentum. We take the visible particle masses to be the observed jet masses, which are typically ∼10 GeV. The endpoint is unaffected by nonzero jet masses provided the test mass is set to the true mass, and is affected only at the ±0.1 GeV level over a large range of test masses, 0< MW<2MW. For an assumed child mass  MW, the endpoint is given by [10,27]: μmax bb =Mt 21−M2 W M2 t+M2 t 41−M2 W M2 t2 + M2 W.(4.6) In the tt case, we set the test mass to  MW=MW= 80.4 GeV. We then expect the endpoint at μmax bb =Mt.As in the previous case, in a new-physics application where the analogs of Mtand MWare not known, the measurement of the endpoint together with an arbitrary choice of the child mass  MWyields a relationship between the two unknown masses. As noted above, a third variable is needed, and we adopt Mb, the invariant mass formed out of jet-lepton pairs emerging from the top-quark decay. Two values of Mbcan be computed in a tt event, one for each top decay. In practice four are calculated because one does not know a priori how to associate the b jets and leptons; we discuss later an algorithm for mitigating the combinatorial effects on the endpoint. The shape of the distribution is known for correct combinations but is not used here since correct combinations cannot be guaranteed (see Sect. 5.3). The endpoint is given by: Mmax b=m2 b+1−m2 ν M2 WE∗ W+p∗E∗ b+p∗,(4.7) where E∗ W,E∗ b, and p∗are energies and momenta of the daughters of t →bW in the top-quark rest frame. In these formulae the charged-lepton mass is neglected but the observed b-jet mass mbis finite and varies event-to-event. Page 6 of 28 Eur. Phys. J. C (2013) 73:2494 Fig. 3 Distributions of the three kinematic distributions μ,μbb, and Mb.Data(5.0fb −1) are shown with error bars. MC simulation is overlaid in solid color to illustrate the approximate tt signal and background content of the distributions. The backgrounds contained in “Other” are listed in Table 1. The zero-bin of the μ plot is suppressed for clarity. The Mbplot contains multiple entries per event (see Sect. 5.3 for details). In all cases, the simulation is normalized to an integrated luminosity of 5.0 fb−1with next-to-leading-order (NLO) cross sections as described in the text We can now summarize the mass measurement strategy. If the masses Mt,MW, and mνwere unknown, one would measure the two endpoints and the invariant mass that appear on the left-hand sides of Eqs. (4.5)–(4.7), using arbitrary test mass values for the first two, to obtain three independent equations for the three unknown masses. Then, in principle, one solves for the three masses. In practice, the measurements carry uncertainties and an optimum solution must be determined by a fit. In the case when one or more of the masses is known, a constrained fit can improve the determination of the remaining unknown mass(es). In Fig. 3we show distributions for the three observables μ,μbb, and Mb. Here and throughout this paper, the zero bin of the μ distribution, corresponding to the delta function of Eq. (4.4), is suppressed to emphasize the kinematically interesting component of the shape. In the μbb plot shown here, the prominent peak that dominates the figure is an analog of the delta function in μ, its substantial width being due to the variable mass of the jets that enter into the μbb calculation. As with the μ delta function, the peak arises from events where the axis of the upstream PTfalls between the two visible-object pTvectors. In later plots this μbb peak will be suppressed to better reveal the behavior of the distribution in the endpoint region. The agreement between data and MC is generally good, but the comparisons are for illustration only and the analysis and results that follow do not depend strongly on the MC simulation or its agreement with observation. 5 Backgrounds The two-lepton requirement at the core of the event selection ensures an exceptionally clean sample. Nevertheless a Table 1 Estimate of signal and background composition in MC simulation, normalized to an integrated luminosity of 5.0 fb−1and NLO cross sections as described in the text Process Number of events tt signal (no τ) 7000 ttsignal(τ→ν) 1100 Single top (tW,¯ tW) 270 Drell–Yan 77 Hadronic/Semileptonic tt with misreconstructed lepton(s) 55 Dibosons (WW, ZZ, WZ) 14 W+jets 9 few types of background must be considered, including topquark decays with τ-lepton daughters, pp →tW events, and sub-percent contributions from other sources. 5.1 Physics backgrounds The physics backgrounds consist of tt decays that do not conform to the dilepton topology of interest, as well as nontt decays. Table 1shows the estimation of signal and background events in MC simulation. The MC generators used throughout this study are MC@NLO 3.41 [29] for all ttsamples, PYTHIA 6.4 [30] for the diboson samples, and MADGRAPH 5.1.1.0 [31] for all others. The simulated data samples are normalized to 7 TeV NLO cross sections and an integrated luminosity of 5.0 fb−1. Events in which a top quark decays through a τlepton (e.g. t →bτ+ντ→b+ν¯ντντ), constitute about 13 % of the events surviving all selection requirements. From the point of view of event selection, these events are back- Eur. Phys. J. C (2013) 73:2494 Page 7 of 28 ground. The unobserved momentum carried by the extra neutrinos, however, ensures that these events reconstruct to MT2 and Mbvalues below their true values and hence fall below the endpoint of signal events with direct decays to e or μfinal states. We therefore include these events among the signal sample. This leaves in principle a small distortion to the kinematic shapes, but the distortion is far from the endpoint and its impact on the mass extraction is negligible. 5.2 Modelling the mistag background In addition to the backgrounds discussed above, which fall within the bulk the distributions, it is essential also to treat events that lie beyond the nominal signal endpoint. In this analysis, the main source of such events comes from genuine tt events where one of the jets not originating from a top-quark decay is mistagged as a b jet. An event in which a light-quark or gluon jet is treated as coming from a top quark can result in events beyond the endpoint in the μbb and Mbdistributions, as can be seen in Fig. 4. The measurement of μ, on the other hand, depends primarily on the two leptons and is unaffected by mistags. To determine the shape of the mistag background in μbb and Mb, we select a control sample with one b-tagged jet and one antitagged jet, where the antitagging identifies jets that are more likely to be light-quark or gluon jets than b jets. Antitagging uses the same algorithm as combined secondary vertex algorithm, but selects jets with a low discriminator value to obtain a sample dominated by light-quark and gluon jets. We classify event samples by the b-tag values of the two selected jets, and identify three samples of interest: a signal sample where both jets are b-tagged; a background sample where one jet is b-tagged and the other antitagged; and another background sample where both jets are antitagged. Table 2shows the composition of these samples as determined in MC simulation. We select the sample consisting of pairs with one tagged and one antitagged jet to be the control sample and use it to determine the shape of the background lying beyond the signal endpoint. It contains a significant fraction of signal events, 27 %, but these all lie below the endpoint and categorizing them as background does not change the endpoint fit. The control sample is used to generate distributions in μbb and Mb, whose shapes are then characterized with an adaptive kernel density estimation (AKDE) method [32]. The underlying KDE method is a non-parametric shape characterization that uses the actual control sample to estimate the probability distribution function (PDF) for the background by summing event-by-event Gaussian kernels. In the AKDE algorithm, on the other hand, the Gaussian widths depend on the local density of events; empirically this algorithm yields lower bias in the final mass determination than alternative algorithms. Figure 5shows the performance of the background shape determination; the set of Fig. 4 Composition of MC event samples, illustrating that signal events with light-quark and gluon jet contamination dominate the region beyond the endpoint. The top and bottom Mbdistributions contain the same information plotted with different vertical scales. The backgrounds contained in “Other” are listed in Table 1 Table 2 Composition of b-tagged, dijet samples as determined in MC simulation. Each column is an independently selected sample; columns sum to 100 % 2 b-tags b-tag, antitag 2 antitags bjet,bjet 86% 27% 7.1% b jet, non b jet 14 % 70 % 53 % nonbjet,nonbjet 0.3% 3% 40% control sample events are taken from MC simulation in order to illustrate the composition of the background and signal. 5.3 Suppressing the combinatorial background Even if the b-tagging algorithm selected only b jets, there would remain a combinatorics problem in tt dilepton events. In the case of the Mbdistribution the matching prob- Page 8 of 28 Eur. Phys. J. C (2013) 73:2494 Fig. 5 Background PDF shapes determined by the AKDE method, on MC samples. All events pass the signal selection criteria. Top:Mb; bottom:μbb.Theheavy black curve is the AKDE shape lem arises in pairing the b jet to the lepton: for b jets j1 and j2, and leptons +and −, two pairings are possible: j1+,j2−and j1−,j2+. Four values of Mbwill thus be available in every event, but only two of them are correct. The two incorrect pairings can (but do not have to) generate values of Mbbeyond the kinematic endpoint of Mbin top-quark decay. To minimize the unwanted background of incorrect pairings while maximizing the chance of retaining the highest values of Mbin correct bpairings, which do respect the endpoint, we employ the following algorithm. Let Aand adenote the two Mbvalues calculated from one of the two possible bpairings, and let Band bdenote the Mbvalues calculated from the other pairing. Choose the labeling such that a<Aand b<B. Without making any assumptions about which pairing is correct, one can order the Mbvalues from smallest to largest; there are six possible orderings. For example the ordering b,B,a,A means that the bB pairing has Mbvalues which are both smaller than the Mbvalues in the aA pairing. In this case, while we Table 3 Mborderings: in each column the left-to-right sequencing of the a,A,b,B labels is from lowest Mbvalue to highest. The left column lists the six possible Mborderings; the right column indicates for each ordering which values are selected for inclusion in the Mb plot Ordering Selection bBaA b,B aAbB a,A baBA b,a,B baAB b,a,A abBA a,b,B abAB a,b,A do not know which pairing is correct, we can be certain that both Mbvalues of the bB pairing must respect the true endpoint since either (a) bB is a correct pairing, in which case its Mbvalues naturally lie below the endpoint, or (b) aA is the correct pairing, so its Mbvalues lie below the true endpoint, with the bB values falling at yet lower values. Similar arguments apply to each of the other possible orderings. Table 3shows the six possibilities. For each mass ordering shown in the left column, the right column shows the mass values that will be selected for use in the Mbfit. For any given event only one row of the table applies. For an event falling in one of the first two rows, two values of Mb enter in the subsequent fits; for an event falling in the last four rows, three values enter the fits. This selection algorithm ensures that all masses used in the fits that can be guaranteed to be below the endpoint will be used, while any that could exceed the endpoint because of wrong pairings will be ignored. Note that it does not guarantee that the masses that are used are all from correct b pairings; in practice, however, we find that 83 % of the entries in the fit region are correct bpairings, and that this fraction rises to over 90 % within 10 GeV of the endpoint. 6 Fit strategy The kinematic observables μ,μbb, and Mb, along with their endpoint relations (Sect. 4.2) and background mitigation techniques (Sects. 5.2,5.3), are combined in an unbinned event-by-event maximum likelihood fit. The likelihood function is given by a product over all events of individual event likelihoods defined on each of the kinematic variables: L(M)= N  i=1Lμ i(ui|M)·Lμbb i(ui|M)·LMb i(ui|M). (6.1) The vector M=(Mt,MW,m2 ν)contains the mass parameters to be determined by the fit, and each uicomprises Eur. Phys. J. C (2013) 73:2494 Page 9 of 28 the set of transverse momentum vectors, reconstructed object masses, and missing-particle test masses from which the kinematic observables μ,μbb, and Mbof the event iare computed. We fit for m2 νrather than mνbecause only m2 νappears in the endpoint formulae (Eqs. (4.5) and (4.7)); we do not constrain m2 νto be positive. As will be described more fully below, only the endpoint region of each variable is used in the fit. If an event idoes not fall within the endpoint region of a given variable, the corresponding likelihood component (Lμ i,Lμbb i,orLMb i) defaults to unity. For each observable x∈{μ,μbb,Mb}, the likelihood component Liin Eq. (6.1) can be expressed in terms of the value of the observable itself, xi=x(ui), and its kinematic endpoint, xmax =xmax(M). Explicit formulae for xmax(M) are given in Eqs. (4.5), (4.6), and (4.7); in the first two cases there is additional dependence on the missing-particle test mass. Letting the label a ∈{, bb,b}index the three flavors of observables, we can write the signal, background, and resolution shapes as S(x|xa max),Ba(x), and Ra i(x). While the form of the signal shape S(x) iscommontoall three fits, the background shape Ba(x) is specific to each observable and the resolution function Ra i(x) is specific to both the observable and the individual event. Then each function La iappearing on the right-hand side of Eq. (6.1) is given by the general form: La ixi|xa max=βSy|xa maxRa i(xi−y)dy+(1−β)Ba(xi). (6.2) The fit parameter βdetermines the relative contribution of signal and mistag background. For the common signal shape S(x|xa max)we use an approximation consisting of a kinked-line shape, constructed piecewise from a descending straight line in the region just below the endpoint and a constant zero value above the endpoint. The kinked-line function is defined over a range from xlo to xhi. The generic form is: S(x|xmax)≡N(xmax −x) xlo ≤x≤xmax; 0xmax ≤x≤xhi.(6.3) The parameter Nis fixed by normalization. The fidelity of this first-order approximation to the underlying shape depends on both the shape and the value of xlo. The range of the fit, (xlo,xhi), is chosen to minimize the dependence of the fit results on the range, and then the values of xlo and xhi are subsequently varied to estimate the corresponding systematic uncertainties. The following paragraphs discuss the forms of Ba(x) and Ra(x) for each of the three kinematic distributions. 6.1 μ In the case of μ, the visible particles are the two leptons, which are well measured. The projection of their vectors onto the axis orthogonal to the upstream PT, however, necessarily involves the direction of the upstream PT, which is not nearly as well determined. The resolution function is therefore wholly dominated by the angular uncertainty in PT, and it varies substantially from event to event depending on the particular configuration of jets found in each event. Although jet resolutions are known to have small nonGaussian tails, their impact on the μ resolution function and the subsequent fit procedure is small and we treat only the Gaussian core. A far more important feature of the resolution arises when the PTdirection uncertainty is propagated into the μ variable to derive R i(x). In this procedure a sharp Jacobian peak appears wherever the PTsmearing can cause μ to pass through a local maximum or minimum value. These peaks depend only on azimuthal angles and occur at any value of μ. The detailed shape of the highly nonGaussian μ resolution and its convolution with the underlying signal shape, as specified in Eq. (6.2), are handled by exact formulae derived analytically (see the Appendix). The background in the μ distribution is vanishingly small, so we set B(x) =0. 6.2 μbb For μbb, the visible particles are the b jets, and since the resolution smearing of both the b jets and the upstream jets defining PTare large and of comparable magnitudes, the event-by-event resolution is more complicated than in the μ case. As a result, no analytic calculation is possible and we instead determine the μbb resolution function, Rbb i(x), numerically in each event, using the known pTand φresolution functions for the jets. As with the μ resolutions, Jacobian peaks appear in the μbb resolutions. The mistag background is included by scaling the shape Bbb(x) obtained from the AKDE procedure as discussed in Sect. 5.2. 6.3 Mb In the Mbcase, the theoretical shape S(x) is well-known, but the combinatorics of bmatching, together with the method of selecting bpairs from the available choices (see Sect. 5.3), sculpt the distribution to the degree that the theoretical shape is no longer useful. Therefore we use the kinked-line shape of Eq. (6.3) to model the signal near the endpoint. In contrast to the μ and μbb variables, numerical studies confirm that linearly propagated Gaussian resolutions accurately reflect the smearing Rb i(x) of Mb, as one expects in this case. The background shape Bb(x) is given by the AKDE procedure as discussed in Sect. 5.2. Page 16 of 28 Eur. Phys. J. C (2013) 73:2494 sharply peaked. In the latter case the delta function R0δ(μ) is not plotted. 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D 82, 074018 (2010). doi:10.1103/PhysRevD.82. 074018,arXiv:1005.3457 (Updated 2011 in arXiv:1005.3457v4) 39. S. Chang, A. de Gouvêa, Neutrino alternatives for missing energy events at colliders. Phys. Rev. D 80, 015008 (2009). doi:10.1103/ PhysRevD.80.015008,arXiv:0901.4796 The CMS Collaboration Yerevan Physics Institute, Yerevan, Armenia S. Chatrchyan, V. Khachatryan, A.M. Sirunyan, A. Tumasyan Institut für Hochenergiephysik der OeAW, Wien, Austria W. Adam, T. Bergauer, M. Dragicevic, J. Erö, C. Fabjan1, M. Friedl, R. Frühwirth1, V.M. Ghete, N. Hörmann, J. Hrubec, M. Jeitler1, W. Kiesenhofer, V. Knünz, M. Krammer1, I. Krätschmer, D. Liko, I. Mikulec, D. Rabady2, B. Rahbaran, C. Rohringer, H. Rohringer, R. Schöfbeck, J. Strauss, A. Taurok, W. Treberer-Treberspurg, W. Waltenberger, C.-E. Wulz1 National Centre for Particle and High Energy Physics, Minsk, Belarus V. Mossolov, N. Shumeiko, J. Suarez Gonzalez Universiteit Antwerpen, Antwerpen, Belgium S. Alderweireldt, M. Bansal, S. Bansal, T. Cornelis, E.A. De Wolf, X. Janssen, A. Knutsson, S. Luyckx, L. Mucibello, S. Ochesanu, B. Roland, R. Rougny, H. Van Haevermaet, P. Van Mechelen, N. Van Remortel, A. Van Spilbeeck Vrije Universiteit Brussel, Brussel, Belgium F. Blekman, S. Blyweert, J. D’Hondt, A. Kalogeropoulos, J. Keaveney, M. Maes, A. Olbrechts, S. Tavernier, W. Van Doninck, P. Van Mulders, G.P. Van Onsem, I. Villella Université Libre de Bruxelles, Bruxelles, Belgium B. Clerbaux, G. De Lentdecker, A.P.R. Gay, T. Hreus, A. Léonard, P.E. Marage, A. Mohammadi, T. Reis, L. Thomas, C. Vander Velde, P. Vanlaer, J. Wang Ghent University, Ghent, Belgium V. Adler, K. Beernaert, L. Benucci, A. Cimmino, S. Costantini, S. Dildick, G. Garcia, B. Klein, J. Lellouch, A. Marinov, J. Mccartin, A.A. Ocampo Rios, D. Ryckbosch, M. Sigamani, N. Strobbe, F. Thyssen, M. Tytgat, S. Walsh, E. Yazgan, N. Zaganidis Université Catholique de Louvain, Louvain-la-Neuve, Belgium S. Basegmez, G. Bruno, R. Castello, A. Caudron, L. Ceard, C. Delaere, T. du Pree, D. Favart, L. Forthomme, A. Giammanco3, J. Hollar, V. Lemaitre, J. Liao, O. Militaru, C. Nuttens, D. Pagano, A. Pin, K. Piotrzkowski, A. Popov4, M. Selvaggi, J.M. Vizan Garcia Université de Mons, Mons, Belgium N. Beliy, T. Caebergs, E. Daubie, G.H. Hammad Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil G.A. Alves, M. Correa Martins Junior, T. Martins, M.E. Pol, M.H.G. Souza Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil W.L. Aldá Júnior, W. Carvalho, J. Chinellato5, A. Custódio, E.M. Da Costa, D. De Jesus Damiao, C. De Oliveira Martins, S. Fonseca De Souza, H. Malbouisson, M. Malek, D. Matos Figueiredo, L. Mundim, H. Nogima, W.L. Prado Da Silva, A. Santoro, L. Soares Jorge, A. Sznajder, E.J. Tonelli Manganote5, A. Vilela Pereira Universidade Estadual Paulistaa, Universidade Federal do ABCb, São Paulo, Brazil T.S. Anjosb, C.A. Bernardesb,F.A.Dias a,6, T.R. Fernandez Perez Tomeia, E.M. Gregoresb, C. Laganaa, F. Marinhoa, P.G. Mercadanteb, S.F. Novaesa, S.S. Padulaa Page 18 of 28 Eur. Phys. J. C (2013) 73:2494 Institute for Nuclear Research and Nuclear Energy, Sofia, Bulgaria V. Genchev2, P. Iaydjiev2, S. Piperov, M. Rodozov, S. Stoykova, G. Sultanov, V. Tcholakov, R. Trayanov, M. Vutova University of Sofia, Sofia, Bulgaria A. Dimitrov, R. Hadjiiska, V. Kozhuharov, L. Litov, B. Pavlov, P. Petkov Institute of High Energy Physics, Beijing, China J.G. Bian, G.M. Chen, H.S. Chen, C.H. Jiang, D. Liang, S. Liang, X. Meng, J. Tao, J. Wang, X. Wang, Z. Wang, H. Xiao, M. Xu State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, China C. Asawatangtrakuldee, Y. Ban, Y. Guo, Q. Li, W. Li, S. Liu, Y. Mao, S.J. Qian, D. Wang, L. Zhang, W. Zou Universidad de Los Andes, Bogota, Colombia C. Avila, C.A. Carrillo Montoya, J.P. Gomez, B. Gomez Moreno, J.C. Sanabria Technical University of Split, Split, Croatia N. Godinovic, D. Lelas, R. Plestina7, D. Polic, I. Puljak University of Split, Split, Croatia Z. Antunovic, M. Kovac Institute Rudjer Boskovic, Zagreb, Croatia V. Brigljevic, S. Duric, K. Kadija, J. Luetic, D. Mekterovic, S. Morovic, L. Tikvica University of Cyprus, Nicosia, Cyprus A. Attikis, G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos, P.A. Razis Charles University, Prague, Czech Republic M. Finger, M. Finger Jr. Academy of Scientific Research and Technology of the Arab Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt Y. Assran8, A. Ellithi Kamel9, M.A. Mahmoud10, A. Mahrous11, A. Radi12,13 National Institute of Chemical Physics and Biophysics, Tallinn, Estonia M. Kadastik, M. Müntel, M. Murumaa, M. Raidal, L. Rebane, A. Tiko Department of Physics, University of Helsinki, Helsinki, Finland P. Eerola, G. Fedi, M. Voutilainen Helsinki Institute of Physics, Helsinki, Finland J. Härkönen, V. Karimäki, R. Kinnunen, M.J. Kortelainen, T. Lampén, K. Lassila-Perini, S. Lehti, T. Lindén, P. Luukka, T. Mäenpää, T. Peltola, E. Tuominen, J. Tuominiemi, E. Tuovinen, L. Wendland Lappeenranta University of Technology, Lappeenranta, Finland A. Korpela, T. Tuuva DSM/IRFU, CEA/Saclay, Gif-sur-Yvette, France M. Besancon, S. Choudhury, F. Couderc, M. Dejardin, D. Denegri, B. Fabbro, J.L. Faure, F. Ferri, S. Ganjour, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry, E. Locci, J. Malcles, L. Millischer, A. Nayak, J. Rander, A. Rosowsky, M. Titov Laboratoire Leprince-Ringuet, Ecole Polytechnique, IN2P3-CNRS, Palaiseau, France S. Baffioni, F. Beaudette, L. Benhabib, L. Bianchini, M. Bluj14, P. Busson, C. Charlot, N. Daci, T. Dahms, M. Dalchenko, L. Dobrzynski, A. Florent, R. Granier de Cassagnac, M. Haguenauer, P. Miné, C. Mironov, I.N. Naranjo, M. Nguyen, C. Ochando, P. Paganini, D. Sabes, R. Salerno, Y. Sirois, C. Veelken, A. Zabi Institut Pluridisciplinaire Hubert Curien, Université de Strasbourg, Université de Haute Alsace Mulhouse, CNRS/IN2P3, Strasbourg, France J.-L. Agram15, J. Andrea, D. Bloch, D. Bodin, J.-M. Brom, E.C. Chabert, C. Collard, E. Conte15, F. Drouhin15, J.-C. Fontaine15, D. Gelé, U. Goerlach, C. Goetzmann, P. Juillot, A.-C. Le Bihan, P. Van Hove Eur. Phys. J. C (2013) 73:2494 Page 19 of 28 Université de Lyon, Université Claude Bernard Lyon 1, Institut de Physique Nucléaire de Lyon, CNRS-IN2P3, Villeurbanne, France S. Beauceron, N. Beaupere, G. Boudoul, S. Brochet, J. Chasserat, R. Chierici2, D. Contardo, P. Depasse, H. El Mamouni, J. Fay, S. Gascon, M. Gouzevitch, B. Ille, T. Kurca, M. Lethuillier, L. Mirabito, S. Perries, L. Sgandurra, V. Sordini, Y. Tschudi, M. Vander Donckt, P. Verdier, S. Viret Institute of High Energy Physics and Informatization, Tbilisi State University, Tbilisi, Georgia Z. Tsamalaidze16 RWTH Aachen University, I. Physikalisches Institut, Aachen, Germany C. Autermann, S. Beranek, B. Calpas, M. Edelhoff, L. Feld, N. Heracleous, O. Hindrichs, K. Klein, J. Merz, A. Ostapchuk, A. Perieanu, F. Raupach, J. Sammet, S. Schael, D. Sprenger, H. Weber, B. Wittmer, V. Zhukov4 RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany M. Ata, J. Caudron, E. Dietz-Laursonn, D. Duchardt, M. Erdmann, R. Fischer, A. Güth, T. Hebbeker, C. Heidemann, K. Hoepfner, D. Klingebiel, P. Kreuzer, M. Merschmeyer, A. Meyer, M. Olschewski, K. Padeken, P. Papacz, H. Pieta, H. Reithler, S.A. Schmitz, L. Sonnenschein, J. Steggemann, D. Teyssier, S. Thüer, M. Weber RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany V. Cherepanov, Y. Erdogan, G. Flügge, H. Geenen, M. Geisler, W. Haj Ahmad, F. Hoehle, B. Kargoll, T. Kress, Y. Kuessel, J. Lingemann2, A. Nowack, I.M. Nugent, L. Perchalla, O. Pooth, A. Stahl Deutsches Elektronen-Synchrotron, Hamburg, Germany M. Aldaya Martin, I. Asin, N. Bartosik, J. Behr, W. Behrenhoff, U. Behrens, M. Bergholz17, A. Bethani, K. Borras, A. Burgmeier, A. Cakir, L. Calligaris, A. Campbell, F. Costanza, D. Dammann, C. Diez Pardos, T. Dorland, G. Eckerlin, D. Eckstein, G. Flucke, A. Geiser, I. Glushkov, P. Gunnellini, S. Habib, J. Hauk, G. Hellwig, H. Jung, M. Kasemann, P. Katsas, C. Kleinwort, H. Kluge, M. Krämer, D. Krücker, E. Kuznetsova, W. Lange, J. Leonard, K. Lipka, W. Lohmann17, B. Lutz, R. Mankel, I. Marfin, M. Marienfeld, I.-A. Melzer-Pellmann, A.B. Meyer, J. Mnich, A. Mussgiller, S. NaumannEmme, O. Novgorodova, F. Nowak, J. Olzem, H. Perrey, A. Petrukhin, D. Pitzl, A. Raspereza, P.M. Ribeiro Cipriano, C. Riedl, E. Ron, M. Rosin, J. Salfeld-Nebgen, R. Schmidt17, T. Schoerner-Sadenius, N. Sen, M. Stein, R. Walsh, C. Wissing University of Hamburg, Hamburg, Germany V. Blobel, H. Enderle, J. Erfle, U. Gebbert, M. Görner, M. Gosselink, J. Haller, K. Heine, R.S. Höing, G. Kaussen, H. Kirschenmann, R. Klanner, J. Lange, T. Peiffer, N. Pietsch, D. Rathjens, C. Sander, H. Schettler, P. Schleper, E. Schlieckau, A. Schmidt, M. Schröder, T. Schum, M. Seidel, J. Sibille18, V. Sola, H. Stadie, G. Steinbrück, J. Thomsen, L. Vanelderen Institut für Experimentelle Kernphysik, Karlsruhe, Germany C. Barth, C. Baus, J. Berger, C. Böser, T. Chwalek, W. De Boer, A. Descroix, A. Dierlamm, M. Feindt, M. Guthoff2, C. Hackstein, F. Hartmann2,T.Hauth 2, M. Heinrich, H. Held, K.H. Hoffmann, U. Husemann, I. Katkov4, J.R. Komaragiri, A. Kornmayer2, P. Lobelle Pardo, D. Martschei, S. Mueller, Th. Müller, M. Niegel, A. Nürnberg, O. Oberst, J. Ott, G. Quast, K. Rabbertz, F. Ratnikov, N. Ratnikova, S. Röcker, F.-P. Schilling, G. Schott, H.J. Simonis, F.M. Stober, D. Troendle, R. Ulrich, J. Wagner-Kuhr, S. Wayand, T. Weiler, M. Zeise Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece G. Anagnostou, G. Daskalakis, T. Geralis, S. Kesisoglou, A. Kyriakis, D. Loukas, A. Markou, C. Markou, E. Ntomari University of Athens, Athens, Greece L. Gouskos, T.J. Mertzimekis, A. Panagiotou, N. Saoulidou, E. Stiliaris University of Ioánnina, Ioánnina, Greece X. Aslanoglou, I. Evangelou, G. Flouris, C. Foudas, P. Kokkas, N. Manthos, I. Papadopoulos, E. Paradas KFKI Research Institute for Particle and Nuclear Physics, Budapest, Hungary G. Bencze, C. Hajdu, P. Hidas, D. Horvath19, B. Radics, F. Sikler, V. Veszpremi, G. Vesztergombi20, A.J. Zsigmond Institute of Nuclear Research ATOMKI, Debrecen, Hungary N. Beni, S. Czellar, J. Molnar, J. Palinkas, Z. Szillasi Page 20 of 28 Eur. Phys. J. C (2013) 73:2494 University of Debrecen, Debrecen, Hungary J. Karancsi, P. Raics, Z.L. Trocsanyi, B. Ujvari Panjab University, Chandigarh, India S.B. Beri, V. Bhatnagar, N. Dhingra, R. Gupta, M. Kaur, M.Z. Mehta, M. Mittal, N. Nishu, L.K. Saini, A. Sharma, J.B. Singh University of Delhi, Delhi, India Ashok Kumar, Arun Kumar, S. Ahuja, A. Bhardwaj, B.C. Choudhary, S. Malhotra, M. Naimuddin, K. Ranjan, P. Saxena, V. Sharma, R.K. Shivpuri Saha Institute of Nuclear Physics, Kolkata, India S. Banerjee, S. Bhattacharya, K. Chatterjee, S. Dutta, B. Gomber, Sa. Jain, Sh. Jain, R. Khurana, A. Modak, S. Mukherjee, D. Roy, S. Sarkar, M. Sharan Bhabha Atomic Research Centre, Mumbai, India A. Abdulsalam, D. Dutta, S. Kailas, V. Kumar, A.K. Mohanty2, L.M. Pant, P. Shukla, A. Topkar Tata Institute of Fundamental Research - EHEP, Mumbai, India T. Aziz, R.M. Chatterjee, S. Ganguly, M. Guchait21,A.Gurtu 22, M. Maity23, G. Majumder, K. Mazumdar, G.B. Mohanty, B. Parida, K. Sudhakar, N. Wickramage Tata Institute of Fundamental Research - HECR, Mumbai, India S. Banerjee, S. Dugad Institute for Research in Fundamental Sciences (IPM), Tehran, Iran H. Arfaei24, H. Bakhshiansohi, S.M. Etesami25,A.Fahim 24, H. Hesari, A. Jafari, M. Khakzad, M. Mohammadi Najafabadi, S. Paktinat Mehdiabadi, B. Safarzadeh26, M. Zeinali University College Dublin, Dublin, Ireland M. Grunewald INFN Sezione di Baria, Università di Barib, Politecnico di Baric, Bari, Italy M. Abbresciaa,b, L. Barbonea,b, C. Calabriaa,b,2, S.S. Chhibraa,b, A. Colaleoa, D. Creanzaa,c, N. De Filippisa,c,2, M. De Palmaa,b,L.Fiore a,G.Iaselli a,c, G. Maggia,c, M. Maggia, B. Marangellia,b,S.My a,c, S. Nuzzoa,b, N. Pacificoa, A. Pompilia,b,G.Pugliese a,c, G. Selvaggia,b, L. Silvestrisa, G. Singha,b, R. Vendittia,b, P. Verwilligena, G. Zitoa INFN Sezione di Bolognaa, Università di Bolognab, Bologna, Italy G. Abbiendia, A.C. Benvenutia, D. Bonacorsia,b, S. Braibant-Giacomellia,b, L. Brigliadoria,b, R. Campaninia,b, P. Capiluppia,b,A.Castro a,b, F.R. Cavalloa, 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, M. Meneghellia,b,2, A. Montanaria,F.L.Navarria a,b, F. Odoricia, A. Perrottaa, F. Primaveraa,b,A.M.Rossi a,b,T.Rovelli a,b,G.P.Siroli a,b,N.Tosi a,b,R.Travaglini a,b INFN Sezione di Cataniaa, Università di Cataniab, Catania, Italy S. Albergoa,b, M. Chiorbolia,b,S.Costa a,b, R. Potenzaa,b, A. Tricomia,b,C.Tuve a,b INFN Sezione di Firenzea, Università di Firenzeb, Firenze, Italy G. Barbaglia, V. Ciullia,b, C. Civininia, R. D’Alessandroa,b, E. Focardia,b,S.Frosali a,b, E. Galloa, S. Gonzia,b, P. Lenzia,b, M. Meschinia, S. Paolettia, G. Sguazzonia, A. Tropianoa,b INFN Laboratori Nazionali di Frascati, Frascati, Italy L. Benussi, S. Bianco, F. Fabbri, D. Piccolo INFN Sezione di Genovaa, Università di Genovab, Genova, Italy P. Fabbricatorea, R. Musenicha,S.Tosi a,b INFN Sezione di Milano-Bicoccaa, Università di Milano-Bicoccab, Milano, Italy A. Benagliaa,F.DeGuio a,b,L.DiMatteo a,b,2, S. Fiorendia,b, S. Gennaia,2, A. Ghezzia,b, P. Govonia,b, M.T. Lucchinia,b,2, S. Malvezzia, R.A. Manzonia,b, A. Martellia,b,A.Massironi a,b, D. Menascea, L. Moronia, M. Paganonia,b, D. Pedrinia, S. Ragazzia,b, N. Redaellia, T. Tabarelli de Fatisa,b Eur. Phys. J. C (2013) 73:2494 Page 21 of 28 INFN Sezione di Napolia, Università di Napoli ’Federico II’b, Università della Basilicata (Potenza)c,Università G. Marconi (Roma)d, Napoli, Italy S. Buontempoa, N. Cavalloa,c,A.DeCosa a,b,2, F. Fabozzia,c, A.O.M. Iorioa,b, L. Listaa, S. Meolaa,d,2, M. Merolaa, P. Paoluccia,2 INFN Sezione di Padovaa, Università di Padovab, Università di Trento (Trento)c,Padova,Italy P. Azzia, N. Bacchettaa,2,P.Bellan a,b, D. Biselloa,b, A. Brancaa,b,R.Carlin a,b, P. Checchiaa,T.Dorigo a, M. Galantia,b, F. Gasparinia,b, U. Gasparinia,b, P. Giubilatoa,b, A. Gozzelinoa, K. Kanishcheva,c, S. Lacapraraa, I. Lazzizzeraa,c, M. Margonia,b, A.T. Meneguzzoa,b, M. Michelottoa, F. Montecassianoa, M. Nespoloa, J. Pazzinia,b, M. Pegoraroa, N. Pozzobona,b, P. Ronchesea,b, F. Simonettoa,b,E.Torassa a,M.Tosi a,b,P.Zotto a,b, G. Zumerlea,b INFN Sezione di Paviaa, Università di Paviab,Pavia,Italy M. Gabusia,b, S.P. Rattia,b, C. Riccardia,b, P. Vituloa,b INFN Sezione di Perugiaa, Università di Perugiab, Perugia, Italy M. Biasinia,b, G.M. Bileia, L. Fanòa,b, P. Laricciaa,b, G. Mantovania,b, M. Menichellia, A. Nappia,b,†, F. Romeoa,b, A. Sahaa, A. Santocchiaa,b, A. Spieziaa,b INFN Sezione di Pisaa, Università di Pisab, Scuola Normale Superiore di Pisac, Pisa, Italy K. Androsova,27,P.Azzurri a, G. Bagliesia, T. Boccalia, G. Broccoloa,c, R. Castaldia, R.T. D’Agnoloa,c,2, R. Dell’Orsoa, F. Fioria,c,2,L.Foà a,c, A. Giassia, A. Kraana, F. Ligabuea,c, T. Lomtadzea,L.Martini a,27, A. Messineoa,b, F. Pallaa, A. Rizzia,b, A.T. Serbana, P. Spagnoloa, P. Squillaciotia, R. Tenchinia, G. Tonellia,b, A. Venturia, P.G. Verdinia, C. Vernieria,c INFN Sezione di Romaa, Università di Romab, Roma, Italy L. Baronea,b,F.Cavallari a,D.DelRe a,b,M.Diemoz a, C. Fanellia,b, M. Grassia,b,2, E. Longoa,b,F.Margaroli a,b, P. Meridiania,2, F. Michelia,b, S. Nourbakhsha,b, G. Organtinia,b, R. Paramattia, S. Rahatloua,b, L. Soffia,b INFN Sezione di Torinoa, Università di Torinob, Università del Piemonte Orientale (Novara)c, Torino, Italy N. Amapanea,b, R. Arcidiaconoa,c,S.Argiro a,b, M. Arneodoa,c,C.Biino a, N. Cartigliaa,S.Casasso a,b,M.Costa a,b, P. De Remigisa, N. Demariaa, C. Mariottia,2, S. Masellia, E. Migliorea,b, V. Monacoa,b,M.Musich a,2,M.M.Obertino a,c, N. Pastronea, M. Pelliccionia, A. Potenzaa,b, A. Romeroa,b, M. Ruspaa,c, R. Sacchia,b, A. Solanoa,b, A. Staianoa, U. Tamponia INFN Sezione di Triestea, Università di Triesteb, Trieste, Italy S. Belfortea, V. Candelisea,b, M. Casarsaa,F.Cossutti a,2,G.DellaRicca a,b, B. Gobboa, C. La Licataa,b, M. Maronea,b,2, D. Montaninoa,b, A. Penzoa, A. Schizzia,b, A. Zanettia Kangwon National University, Chunchon, Korea T.Y. Kim, S.K. Nam Kyungpook National University, Daegu, Korea S. Chang, D.H. Kim, G.N. Kim, J.E. Kim, D.J. Kong, Y.D. Oh, H. Park, D.C. Son Chonnam National University, Institute for Universe and Elementary Particles, Kwangju, Korea J.Y. Kim, Z.J. Kim, S. Song Korea University, Seoul, Korea S. Choi, D. Gyun, B. Hong, M. Jo, H. Kim, T.J. Kim, K.S. Lee, D.H. Moon, S.K. Park, Y. Roh University of Seoul, Seoul, Korea M. Choi, J.H. Kim, C. Park, I.C. Park, S. Park, G. Ryu Sungkyunkwan University, Suwon, Korea Y. Choi, Y.K. Choi, J. Goh, M.S. Kim, E. Kwon, B. Lee, J. Lee, S. Lee, H. Seo, I. Yu Vilnius University, Vilnius, Lithuania I. Grigelionis, A. Juodagalvis Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico H. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-de La Cruz, R. Lopez-Fernandez, J. Martínez-Ortega, A. SanchezHernandez, L.M. Villasenor-Cendejas Page 22 of 28 Eur. Phys. J. C (2013) 73:2494 Universidad Iberoamericana, Mexico City, Mexico S. Carrillo Moreno, F. Vazquez Valencia Benemerita Universidad Autonoma de Puebla, Puebla, Mexico H.A. Salazar Ibarguen Universidad Autónoma de San Luis Potosí, San Luis Potosí, Mexico E. Casimiro Linares, A. Morelos Pineda, M.A. Reyes-Santos University of Auckland, Auckland, New Zealand D. Krofcheck University of Canterbury, Christchurch, New Zealand A.J. Bell, P.H. Butler, R. Doesburg, S. Reucroft, H. Silverwood National Centre for Physics, Quaid-I-Azam University, Islamabad, Pakistan M. Ahmad, M.I. Asghar, J. Butt, H.R. Hoorani, S. Khalid, W.A. Khan, T. Khurshid, S. Qazi, M.A. Shah, M. Shoaib National Centre for Nuclear Research, Swierk, Poland H. Bialkowska, B. Boimska, T. Frueboes, M. Górski, M. Kazana, K. Nawrocki, K. Romanowska-Rybinska, M. Szleper, G. Wrochna, P. Zalewski Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Warsaw, Poland G. Brona, K. Bunkowski, M. Cwiok, W. Dominik, K. Doroba, A. Kalinowski, M. Konecki, J. Krolikowski, M. Misiura, W. Wolszczak Laboratório de Instrumentação e Física Experimental de Partículas, Lisboa, Portugal N. Almeida, P. Bargassa, A. David, P. Faccioli, P.G. Ferreira Parracho, M. Gallinaro, J. Seixas2, J. Varela, P. Vischia Joint Institute for Nuclear Research, Dubna, Russia P. Bunin, M. Gavrilenko, I. Golutvin, I. Gorbunov, A. Kamenev, V. Karjavin, V. Konoplyanikov, G. Kozlov, A. Lanev, A. Malakhov, P. Moisenz, V. Palichik, V. Perelygin, S. Shmatov, V. Smirnov, A. Volodko, A. Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia S. Evstyukhin, V. Golovtsov, Y. Ivanov, V. Kim, P. Levchenko, V. Murzin, V. Oreshkin, I. Smirnov, V. Sulimov, L. Uvarov, S. Vavilov, A. Vorobyev, An. Vorobyev Institute for Nuclear Research, Moscow, Russia Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, M. Kirsanov, N. Krasnikov, V. Matveev, A. Pashenkov, D. Tlisov, A. Toropin Institute for Theoretical and Experimental Physics, Moscow, Russia V. Epshteyn, M. Erofeeva, V. Gavrilov, N. Lychkovskaya, V. Popov, G. Safronov, S. Semenov, A. Spiridonov, V. Stolin, E. Vlasov, A. Zhokin P.N. Lebedev Physical Institute, Moscow, Russia V. Andreev, M. Azarkin, I. Dremin, M. Kirakosyan, A. Leonidov, G. Mesyats, S.V. Rusakov, A. Vinogradov Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia A. Belyaev, E. Boos, V. Bunichev, M. Dubinin6, L. Dudko, A. Ershov, A. Gribushin, V. Klyukhin, I. Lokhtin, A. Markina, S. Obraztsov, M. Perfilov, V. Savrin, N. Tsirova State Research Center of Russian Federation, Institute for High Energy Physics, Protvino, Russia I. Azhgirey, I. Bayshev, S. Bitioukov, V. Kachanov, A. Kalinin, D. Konstantinov, V. Krychkine, V. Petrov, R. Ryutin, A. Sobol, L. Tourtchanovitch, S. Troshin, N. Tyurin, A. Uzunian, A. Volkov University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia P. Adzic28, M. Ekmedzic, D. Krpic28,J.Milosevic Centro de Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain M. Aguilar-Benitez, J. Alcaraz Maestre, C. Battilana, E. Calvo, M. Cerrada, M. Chamizo Llatas2, N. Colino, B. De La Cruz, A. Delgado Peris, D. Domínguez Vázquez, C. Fernandez Bedoya, J.P. Fernández Ramos, A. Ferrando, J. Flix, M.C. Fouz, P. Garcia-Abia, O. Gonzalez Lopez, S. Goy Lopez, J.M. Hernandez, M.I. Josa, G. Merino, E. Navarro De Martino, J. Puerta Pelayo, A. Quintario Olmeda, I. Redondo, L. Romero, J. Santaolalla, M.S. Soares, C. Willmott Eur. Phys. J. C (2013) 73:2494 Page 23 of 28 Universidad Autónoma de Madrid, Madrid, Spain C. Albajar, J.F. de Trocóniz Universidad de Oviedo, Oviedo, Spain H. Brun, J. Cuevas, J. Fernandez Menendez, S. Folgueras, I. Gonzalez Caballero, L. Lloret Iglesias, J. Piedra Gomez Instituto de Física de Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, Spain J.A. Brochero Cifuentes, I.J. Cabrillo, A. Calderon, S.H. Chuang, J. Duarte Campderros, M. Fernandez, G. Gomez, J. Gonzalez Sanchez, A. Graziano, C. Jorda, A. Lopez Virto, J. Marco, R. Marco, C. Martinez Rivero, F. Matorras, F.J. Munoz Sanchez, T. Rodrigo, A.Y. Rodríguez-Marrero, A. Ruiz-Jimeno, L. Scodellaro, I. Vila, R. Vilar Cortabitarte CERN, European Organization for Nuclear Research, Geneva, Switzerland D. Abbaneo, E. Auffray, G. Auzinger, M. Bachtis, P. Baillon, A.H. Ball, D. Barney, J. Bendavid, J.F. Benitez, C. Bernet7, G. Bianchi, P. Bloch, A. Bocci, A. Bonato, O. Bondu, C. Botta, H. Breuker, T. Camporesi, G. Cerminara, T. Christiansen, J.A. Coarasa Perez, S. Colafranceschi29, D. d’Enterria, A. Dabrowski, A. De Roeck, S. De Visscher, S. Di Guida, M. Dobson, N. Dupont-Sagorin, A. Elliott-Peisert, J. Eugster, W. Funk, G. Georgiou, M. Giffels, D. Gigi, K. Gill, D. Giordano, M. Girone, M. Giunta, F. Glege, R. Gomez-Reino Garrido, S. Gowdy, R. Guida, J. Hammer, M. Hansen, P. Harris, C. Hartl, B. Hegner, A. Hinzmann, V. Innocente, P. Janot, K. Kaadze, E. Karavakis, K. Kousouris, K. Krajczar, P. Lecoq, Y.-J. Lee, C. Lourenço, N. Magini, M. Malberti, L. Malgeri, M. Mannelli, L. Masetti, F. Meijers, S. Mersi, E. Meschi, R. Moser, M. Mulders, P. Musella, E. Nesvold, L. Orsini, E. Palencia Cortezon, E. Perez, L. Perrozzi, A. Petrilli, A. Pfeiffer, M. Pierini, M. Pimiä, D. Piparo, G. Polese, L. Quertenmont, A. Racz, W. Reece, J. Rodrigues Antunes, G. Rolandi30, C. Rovelli31, M. Rovere, H. Sakulin, F. Santanastasio, C. Schäfer, C. Schwick, I. Segoni, S. Sekmen, A. Sharma, P. Siegrist, P. Silva, M. Simon, P. Sphicas32, D. Spiga, M. Stoye, A. Tsirou, G.I. Veres20, J.R. Vlimant, H.K. Wöhri, S.D. Worm33, W.D. Zeuner Paul Scherrer Institut, Villigen, Switzerland W. Bertl, K. Deiters, W. Erdmann, K. Gabathuler, R. Horisberger, Q. Ingram, H.C. Kaestli, S. König, D. Kotlinski, U. Langenegger, F. Meier, D. Renker, T. Rohe Institute for Particle Physics, ETH Zurich, Zurich, Switzerland F. Bachmair, L. Bäni, P. Bortignon, M.A. Buchmann, B. Casal, N. Chanon, A. Deisher, G. Dissertori, M. Dittmar, M. Donegà, M. Dünser, P. Eller, C. Grab, D. Hits, P. Lecomte, W. Lustermann, A.C. Marini, P. Martinez Ruiz del Arbol, N. Mohr, F. Moortgat, C. Nägeli34, P. Nef, F. Nessi-Tedaldi, F. Pandolfi, L. Pape, F. Pauss, M. Peruzzi, F.J. Ronga, M. Rossini, L. Sala, A.K. Sanchez, A. Starodumov35, B. Stieger, M. Takahashi, L. Tauscher†, A. Thea, K. Theofilatos, D. Treille, C. Urscheler, R. Wallny, H.A. Weber Universität Zürich, Zurich, Switzerland C. Amsler36, V. Chiochia, C. Favaro, M. Ivova Rikova, B. Kilminster, B. Millan Mejias, P. Otiougova, P. Robmann, H. Snoek, S. Taroni, S. Tupputi, M. Verzetti National Central University, Chung-Li, Taiwan M. Cardaci, K.H. Chen, C. Ferro, C.M. Kuo, S.W. Li, W. Lin, Y.J. Lu, R. Volpe, S.S. Yu National Taiwan University (NTU), Taipei, Taiwan P. Bartalini, P. Chang, Y.H. Chang, Y.W. Chang, Y. Chao, K.F. Chen, C. Dietz, U. Grundler, W.-S. Hou, Y. Hsiung, K.Y. Kao, Y.J. Lei, R.-S. Lu, D. Majumder, E. Petrakou, X. Shi, J.G. Shiu, Y.M. Tzeng, M. Wang Chulalongkorn University, Bangkok, Thailand B. Asavapibhop, N. Suwonjandee Cukurova University, Adana, Turkey A. Adiguzel, M.N. Bakirci37,S.Cerci 38, C. Dozen, I. Dumanoglu, E. Eskut, S. Girgis, G. Gokbulut, E. Gurpinar, I. Hos, E.E. Kangal, A. Kayis Topaksu, G. Onengut, K. Ozdemir, S. Ozturk39, A. Polatoz, K. Sogut40, D. Sunar Cerci38,B.Tali 38, H. Topakli37,M.Vergili Middle East Technical University, Physics Department, Ankara, Turkey I.V. Akin, T. Aliev, B. Bilin, S. Bilmis, M. Deniz, H. Gamsizkan, A.M. Guler, G. Karapinar41, K. Ocalan, A. Ozpineci, M. Serin, R. Sever, U.E. Surat, M. Yalvac, M. Zeyrek Bogazici University, Istanbul, Turkey E. Gülmez, B. Isildak42,M.Kaya 43, O. Kaya43, S. Ozkorucuklu44, N. Sonmez45 Page 24 of 28 Eur. Phys. J. C (2013) 73:2494 Istanbul Technical University, Istanbul, Turkey H. Bahtiyar46, E. Barlas, K. Cankocak, Y.O. Günaydin47, F.I. Vardarlı, M. Yücel National Scientific Center, Kharkov Institute of Physics and Technology, Kharkov, Ukraine L. Levchuk, P. Sorokin University of Bristol, Bristol, United Kingdom J.J. Brooke, E. Clement, D. Cussans, H. Flacher, R. Frazier, J. Goldstein, M. Grimes, G.P. Heath, H.F. Heath, L. Kreczko, S. Metson, D.M. Newbold33, K. Nirunpong, A. Poll, S. Senkin, V.J. Smith, T. Williams Rutherford Appleton Laboratory, Didcot, United Kingdom L. Basso48, K.W. Bell, A. 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Turner Baylor University, Waco, USA J. Dittmann, K. Hatakeyama, A. Kasmi, H. Liu, T. Scarborough The University of Alabama, Tuscaloosa, USA O. Charaf, S.I. Cooper, C. Henderson, P. Rumerio Boston University, Boston, USA A. Avetisyan, T. Bose, C. Fantasia, A. Heister, P. Lawson, D. Lazic, J. Rohlf, D. Sperka, J. St. John, L. Sulak Brown University, Providence, USA J. Alimena, S. Bhattacharya, G. Christopher, D. Cutts, Z. Demiragli, A. Ferapontov, A. Garabedian, U. Heintz, G. Kukartsev, E. Laird, G. Landsberg, M. Luk, M. Narain, M. Segala, T. Sinthuprasith, T. Speer University of California, Davis, Davis, USA R. Breedon, G. Breto, M. Calderon De La Barca Sanchez, S. Chauhan, M. Chertok, J. Conway, R. Conway, P.T. Cox, R. Erbacher, M. Gardner, R. Houtz, W. Ko, A. Kopecky, R. Lander, O. Mall, T. Miceli, R. Nelson, D. Pellett, F. Ricci-Tam, B. Rutherford, M. Searle, J. Smith, M. Squires, M. Tripathi, R. Yohay University of California, Los Angeles, USA V. Andreev, D. Cline, R. Cousins, S. 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Das, M. De Gruttola, G.P. Di Giovanni, D. Dobur, A. Drozdetskiy, R.D. Field, M. Fisher, Y. Fu, I.K. Furic, J. Hugon, B. Kim, J. Konigsberg, A. Korytov, A. Kropivnitskaya, T. Kypreos, J.F. Low, K. Matchev, P. Milenovic52, G. Mitselmakher, L. Muniz, R. Remington, A. Rinkevicius, N. Skhirtladze, M. Snowball, J. Yelton, M. Zakaria Florida International University, Miami, USA V. Gaultney, S. Hewamanage, L.M. Lebolo, S. Linn, P. Markowitz, G. Martinez, J.L. Rodriguez Florida State University, Tallahassee, USA T. Adams, A. Askew, J. Bochenek, J. Chen, B. Diamond, S.V. Gleyzer, J. Haas, S. Hagopian, V. Hagopian, K.F. Johnson, H. Prosper, V. Veeraraghavan, M. Weinberg Florida Institute of Technology, Melbourne, USA M.M. Baarmand, B. Dorney, M. Hohlmann, H. Kalakhety, F. Yumiceva University of Illinois at Chicago (UIC), Chicago, USA M.R. Adams, L. Apanasevich, V.E. Bazterra, R.R. Betts, I. Bucinskaite, J. Callner, R. Cavanaugh, O. Evdokimov, L. Gauthier, C.E. Gerber, D.J. Hofman, S. Khalatyan, P. Kurt, F. Lacroix, C. O’Brien, C. Silkworth, D. Strom, P. Turner, N. Varelas The University of Iowa, Iowa City, USA U. Akgun, E.A. Albayrak, B. Bilki53, W. Clarida, K. Dilsiz, F. Duru, S. Griffiths, J.-P. Merlo, H. Mermerkaya54, A. Mestvirishvili, A. Moeller, J. Nachtman, C.R. Newsom, H. Ogul, Y. Onel, F. Ozok46, S. Sen, P. Tan, E. Tiras, J. Wetzel, T. Yetkin55,K.Yi Johns Hopkins University, Baltimore, USA B.A. Barnett, B. Blumenfeld, S. Bolognesi, D. Fehling, G. Giurgiu, A.V. Gritsan, G. Hu, P. Maksimovic, M. Swartz, A. Whitbeck The University of Kansas, Lawrence, USA P. Baringer, A. Bean, G. Benelli, R.P. Kenny III, M. Murray, D. Noonan, S. Sanders, R. Stringer, J.S. Wood