Search for anomalous Wtb couplings and flavour-changing neutral currents in t-channel single top quark production in pp collisions at \( \sqrt{s}=7 \) and 8 TeV

Journal of High Energy Physics, Feb 2017

Single top quark events produced in the t channel are used to set limits on anomalous Wtb couplings and to search for top quark flavour-changing neutral current (FCNC) interactions. The data taken with the CMS detector at the LHC in proton-proton collisions at \( \sqrt{s}=7 \) and 8 TeV correspond to integrated luminosities of 5.0 and 19.7 fb−1, respectively. The analysis is performed using events with one muon and two or three jets. A Bayesian neural network technique is used to discriminate between the signal and backgrounds, which are observed to be consistent with the standard model prediction. The 95% confidence level (CL) exclusion limits on anomalous right-handed vector, and left- and right-handed tensor Wtb couplings are measured to be |f V R | < 0.16, |f T L | < 0.057, and − 0.049 < f T R < 0.048, respectively. For the FCNC couplings κ tug and κ tcg, the 95% CL upper limits on coupling strengths are |κ tug|/Λ < 4.1 × 10− 3 TeV−1 and |κ tcg|/Λ < 1.8 × 10− 2 TeV−1, where Λ is the scale for new physics, and correspond to upper limits on the branching fractions of 2.0 × 10−5 and 4.1 × 10−4 for the decays t → ug and t → cg, respectively.

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Search for anomalous Wtb couplings and flavour-changing neutral currents in t-channel single top quark production in pp collisions at \( \sqrt{s}=7 \) and 8 TeV

Received: October top quark production in pp collisions at s = 7 and p The CMS collaboration 0 1 2 3 4 5 6 7 E-mail: 0 1 2 3 4 5 6 7 0 Open Access , Copyright CERN 1 avour-changing neutral current 2 Chulalongkorn University, Faculty of Science, Department of Physics , Bangkok 3 State University of New York at Bu alo , Bu alo , U.S.A 4 tute' (MEPhI) , Moscow , Russia 5 University , Budapest , Hungary 6 15: Also at Tbilisi State University , Tbilisi , Georgia 7 60: Also at Hacettepe University , Ankara , Turkey Single top quark events produced in the t channel are used to set limits on anomalous Wtb couplings and to search for top quark (FCNC) interactions. The data taken with the CMS detector at the LHC in proton-proton s = 7 and 8 TeV correspond to integrated luminosities of 5.0 and 19.7 fb 1, respectively. The analysis is performed using events with one muon and two or three jets. A Bayesian neural network technique is used to discriminate between the signal and backgrounds, which are observed to be consistent with the standard model prediction. The 95% con dence level (CL) exclusion limits on anomalous right-handed vector, and left- and righthanded tensor Wtb couplings are measured to be jfVRj < 0:16, jfTLj < 0:057, and fTR < 0:048, respectively. For the FCNC couplings tug and tcg, the 95% CL upper limits Flavour Changing Neutral Currents; Hadron-Hadron scattering (experi- - on coupling strengths are j tugj= 10 3 TeV 1 and j tcgj= is the scale for new physics, and correspond to upper limits on the branching fractions of 2:0 10 4 for the decays t ! ug and t ! cg, respectively. ments), Top physics 1 Introduction 2 The CMS detector 3 Data and simulated events 4 Event selection 7.1 7.2 8.1 9 Summary The CMS collaboration Introduction 5 Signal extraction with Bayesian neural networks 6 Systematic uncertainties and statistical analysis 7 Search for anomalous contributions to the Wtb vertex Modelling the structure of the anomalous Wtb vertex Exclusion limits on anomalous couplings 8 Search for tcg and tug FCNC interactions Theoretical introduction Exclusion limits on tug and tcg anomalous couplings 1 Single top quark (t) production provides ways to investigate aspects of top quark physics that cannot be studied with tt events [1]. The theory of electroweak interactions predicts three mechanisms for producing single top quarks in hadron-hadron collisions. At leading order (LO), these are classi ed according to the virtuality of the W boson propagation in t-channel, s-channel, or associated tW production [2]. Single top quark production in all channels is directly related to the squared modulus of the Cabibbo-Kobayashi-Maskawa matrix element Vtb. As a consequence, it provides a direct measurement of this quantity and thereby a check of the standard model (SM). The single top quark topology also opens a window for searches of anomalous Wtb couplings relative to the SM, where the interaction vertex of the top quark with the bottom quark (b) and the W boson (Wtb vertex) has a VA axial-vector structure. Flavour-changing neutral currents (FCNC) are absent at lowest order in the SM, and are signi cantly suppressed through the Glashow-Iliopoulos-Maiani mechanism [3] at higher orders. Various rare decays of K, D, and B mesons, as well as the oscillations in K0K0, D0D0, and B0B0 systems, strongly constrain FCNC interactions involving the rst two generations and the b quark [4]. The V-A structure of the charged current with light quarks is well established [4]. However, FCNC involving the top quark, as well as the structure of the Wtb vertex, are signi cantly less constrained. In the SM, the FCNC couplings of the top quark are predicted to be very small and not detectable at current experimental sensitivity. However, they can be signi cantly enhanced in various SM extensions, such as supersymmetry [5{7], and models with multiple Higgs boson doublets [8{10], extra quarks [11{13], or a composite top quark [14]. New vertices with top quarks are predicted, in particular, in models with light composite Higgs bosons [15, 16], extra-dimension models with warped geometry [17], or holographic structures [18]. Such possibilities can be encoded in an e ective eld theory through higher-dimensional gaugeinvariant operators [19, 20]. Direct limits on top quark FCNC parameters have been established by the CDF [21], D0 [22], and ATLAS [23] Collaborations. There are two complementary strategies to search for FCNC in single top quark production. A search can be performed in the s channel for resonance production through the fusion of a gluon (g) with an up (u) or charm (c) quark, as was the case in analyses by the CDF and ATLAS Collaborations. However, as pointed out by the D0 Collaboration, the s-channel production rate is proportional to the square of the FCNC coupling parameter and is therefore expected to be small [22]. On the other hand, the t-channel cross section and its corresponding kinematic properties have been measured accurately at the LHC [24{26], with an important feature being that the t-channel signature contains a light-quark jet produced in association with the single top quark. This light-quark jet can be used to search for deviations from the SM prediction caused by FCNC in the top quark sector. This strategy was applied by the D0 Collaboration [22], as well as in our analysis. Models that have contributions from FCNC in the production of single top quarks can have sizable deviations relative to SM predictions. Processes with FCNC vertices in the decay of the top quark are negligible. In contrast, the modelling of Wtb couplings can involve anomalous Wtb interactions in both the production and the decay, because both are signi cantly a ected by anomalous contributions. All these features are explicitly taken into account in the CompHEP Monte Carlo (MC) generator [27]. In this paper, we present a search by the CMS experiment at the CERN LHC for anomalous Wtb couplings and FCNC interactions of the top quark through the u or c quarks and a gluon (tug or tcg vertices), by selecting muons arising from W boson decay (including lepton) from the top quarks in muon+jets events. Separation of signal and background is achieved through a Bayesian neural network (BNN) technique [28, 29], performed using the Flexible Bayesian modelling package [30]. Limits on Wtb and top quark FCNC anomalous couplings are obtained from the distribution in the BNN discriminants. The CMS detector The central feature of the CMS apparatus is a superconducting solenoid of 6 m internal diameter, providing a magnetic eld of 3.8 T. Within the solenoid volume are a silicon pixel and strip tracker, a lead tungstate crystal electromagnetic calorimeter (ECAL), and a brass and scintillator hadron calorimeter (HCAL), each composed of a barrel and two endcap sections. Forward calorimeters extend the pseudorapidity [31] coverage provided by the barrel and endcap detectors. Muons are measured in gas-ionization detectors embedded in the steel ux-return yoke outside the solenoid. The rst level of the CMS trigger system, composed of custom hardware processors, uses information from the calorimeters and muon detectors to select the most interesting events in a xed time interval of less than 4 s. The high-level trigger processor farm further decreases the event rate from around 100 kHz to less than 1 kHz, before data storage. A more detailed description of the CMS detector, together with a de nition of the coordinate system used and the relevant kinematic variables, can be found in ref. [31]. The particle- ow event algorithm [32, 33] reconstructs and identi es each individual particle with an optimized combination of information from the various elements of the CMS detector. The energy of photons is directly obtained from the ECAL measurement, corrected for zero-suppression e ects. The energy of electrons is determined from a combination of the electron momentum at the primary interaction vertex as determined by the tracker, the energy of the corresponding ECAL cluster, and the energy sum of all bremsstrahlung photons spatially compatible with originating from the electron track. The energy of muons is obtained from the curvature of the corresponding track. The energy of charged hadrons is determined from a combination of their momentum measured in the tracker and the matching ECAL and HCAL energy deposits, corrected for zero-suppression e ects and for the response function of the calorimeters to hadronic showers. Finally, the energy of neutral hadrons is obtained from the corresponding corrected ECAL and HCAL energy. Jets are reconstructed o ine from particle- ow candidates clustered by the anti-kT algorithm [34, 35] with a size parameter of 0.5. Jet momentum is determined as the vectorial sum of all particle momenta in the jet, and is found from simulation to be within 5 to 10% of the true momentum over the whole transverse momentum (pT) spectrum and detector acceptance. An o set correction is applied to jet energies to take into account the contribution from additional proton-proton interactions within the same or nearby bunch crossing (pileup). Jet energy corrections are derived from simulation, and are con rmed with in situ measurements of the energy balance in dijet and photon+jet events. Additional selection criteria are applied to each event to remove spurious jet-like features originating from isolated noise patterns in certain HCAL regions. The missing transverse momentum vector p~miss is de ned as the projection on the plane perpendicular to the beams of the negative vector sum of the momenta of all reconstructed particles in an event. Its magnitude is referred to as ETmiss [32]. Data and simulated events The analysis is performed using proton-proton collisions recorded with the CMS detector in 2011 and 2012 at centre-of-mass energies of 7 and 8 TeV, respectively, and corresponding to integrated luminosities of 5.0 and 19.7 fb 1. The t-channel production of a single top quark is modelled using the CompHEP 4.5 package [27], supplemented by an additional matching method used to simulate an e ective next-to-leading-order (NLO) approach [36]. The alternative model to estimate the sensitivity of the analysis to the modelling of the signal. Contributions from anomalous operators are added to the CompHEP simulation for both the production and decay of top quarks. This takes into account the width of the top quark, spin correlations between the production and decay, and the b quark mass in the anomalous and SM contributions. The LO MadGraph 5.1 [41] generator is used to simulate the main background processes: top quark pair production with total cross sections of (7 TeV) = 172:0+67::56 pb [42] and (8 TeV) = 253+1134 pb [43], and W boson production with total cross sections of (7 TeV) = 31:3 1:6 nb and (8 TeV) = 36:7 1:3 nb [44], for processes with up to 3 and 4 additional jets in the matrix element calculations, respec0:3 nb and (8 TeV) = 4:3 0:2 nb [44], and and (8 TeV) = 73:8 1:9 pb [45] are modelled using LO pythia 6.426 [46]. The contribution from multijet events, with one of the jets misidenti ed as a lepton, is estimated using a mutually exclusive data sample. The details are given in the next section. Single top quark production in the s channel with (7 TeV) = 4:6+00::22 pb, (8 TeV) = 5:5 and in the tW channel with (7 TeV) = 15:7 1:2 pb, (8 TeV) = 22:2 1:5 pb [47] are modelled using the powheg generator. The pythia 6.4 program is also used to simulate parton showers for the hard processes calculated in the CompHEP, MadGraph, and powheg generators. The PDF4LHC recipe [48] is used to reweight all simulated events to the central value of CT10 PDF [49]. The Z2Star [50, 51] set of parameters is used to simulate the underlying-events. Because of the importance of the W+jets background and the signi cant di erence in the kinematic distributions, the following contributions are considered separately in the analysis: W boson produced together with a pair of b or c quarks (W+QQ); W boson produced in association with a c quark (W+c); W boson events that do not contain heavy quarks (W+light); and events associated with underlying events (UE) that contain heavy quarks originating from the initial parton interaction (W+QX). Di erent nuisance parameters for the normalization scale factors are used for these components of the complete W+jets MadGraph simulation. Simulated events are reweighted to reproduce the observed particle multiplicity from pileup. Small di erences between the data and simulation in trigger e ciency [52, 53], lepton identi cation and isolation [52, 53], and b tagging [54] are corrected via scale factors, which are generally close to unity. Event selection The following signature is used to identify t-channel single top quark production candidates: exactly one isolated muon [52], one light- avour jet in the forward region (de ned below); one b-tagged jet [54] from the b quark originating from the decay of the top quark, and an associated \soft" b jet. The \soft" b jet is likely to fail either the pT or below). The presence of a neutrino in the decay of the W boson leads to a signi cant amount of ETmiss, which is used to enhance the signal. The analysis is performed using data collected with a trigger requiring at least one muon in each event. To accommodate the increasing instantaneous luminosity delivered by the LHC in 2011, di erent triggers were used for various data-taking periods, with the muon pT threshold ranging from 20 to events are required to have: (i). at least one primary vertex reconstructed from at least four tracks, and located within 24 cm in the longitudinal direction and 2 cm in the radial direction from the centre of the detector; (ii). only one isolated (Irel < 0:12) muon [52] with pT > 20 (27) GeV according to the variation of the trigger pT threshold at p s = 7 and pT > 26 GeV at p s = 8 TeV, and j j < 2:1, originating from the primary vertex, where the relative isolation parameter of the muon, Irel, is de ned as the sum of the energy deposited by long-lived charged hadrons, neutral hadrons, and photons in a cone with radius R = ) = 0:4, divided by the muon pT, where di erences in pseudorapidity and azimuthal angle (in radians), respectively, between the muon and the other particle's directions. Events with additional muons or electrons are rejected using a looser quality requirement of pT > 10 GeV for muons and e 15 GeV for electrons, j j < 2:5, and having Irel < 0:2 and Irel < 0:15, where the electron relative isolation parameter Ireel is measured similarly to that for a muon; (iii). two or three jets with pT > 30 GeV and j j < 4:7, and, at p s = 8 TeV, the highest-pT jet (j1) is required to satisfy pT(j1) > 40 GeV. For events with 3 jets we require the second-highest-pT jet (j2) to have pT(j2) > 40 GeV; (iv). at least one b-tagged jet and at least one jet that fails the combined secondary vertex algorithm tight b tagging working-point requirement [54]. A tight b tagging selection corresponds to an e ciency of 50% for jets originating from true b quarks and a mistagging rate of 0:1% for other jets in the signal simulation. Control regions containing events with 2 or 3 jets and no b-tagged jet, and events with 4 jets, 2 of which are b-tagged, are used to validate the modelling of the W+jets and tt backgrounds, respectively. The multijet events contribute background when there is a muon from the semileptonic decay of a b or c quark, or a light charged hadron is misidenti ed as a muon. These background muons candidates are usually surrounded by hadrons. This feature is exploited to de ne a control region by demanding exactly one muon with an inverted isolation criteria for hadronic activity of 0:35 < Irel < 1. The jets falling inside the cone of a the criteria that de ne the signal. To suppress the multijet background, we use a dedicated Bayesian neural network (multijet BNN), with the following input variables, sensitive to of the reconstructed W boson, the azimuthal angle tion and p~miss, the quantity ETmiss, and the muon pT. The same set of variables is used T shown for the multijet BNN discriminant and the mT(W) distributions for the p di erent BNNs are trained for each set. In gure 1, data-to-simulation comparisons are s = 8 TeV data. The predictions for the multijet BNN discriminant and mT(W) agree with the data. ( ; p~Tmiss) between the muon direc/s2 4 t E 2 and the predicted backgrounds from simulation ( lled histograms) for p ground rejection (left) and the reconstructed transverse W boson mass (right) from data (points) s = 8 TeV. The lower part of each plot shows the relative di erence between the data and the total predicted background. The vertical bars represent the statistical uncertainties. s = 7 TeV s = 8 TeV Multijet BNN > 0.7 Basic selection Multijet BNN > 0.7 2 080 160 16 100 800 53 800+33 970000 1 760 130 12 700 630 38 380+11 010000 9 220 620 101 100+56110000 36 100+11220000 5 960 320 30 200+66 030000 206 650+88 190000 6 620 450 72 200+34 630000 23 700 800 2 060 110 123 400+34 850000 for the two data sets. The uncertainties include the estimation of the scale and parton distribution function uncertainties. The normalization of the multijet background is taken from a t to the multijet BNN distribution, and all other processes involving a W boson are normalized to their theoretical cross sections. To reduce the multijet background, the multijet BNN discriminant is required to have a value greater than 0.7. Using the value of the discriminant rather than a selection on mT(W) increases the signal e ciency by 10%, with a similar background rejection. This requirement rejects about 90% of the multijet background, while rejecting only about 20% of the signal, as determined from simulation. The observed and predicted event yields before and after the multijet background suppression are listed in table 1. Signal extraction with Bayesian neural networks Events that pass the initial selection and the multijet BNN discriminant requirement are considered in the nal analysis, which requires the training of the BNN (SM BNN) to distinguish the t-channel single top quark production process from other SM processes. The s- and tW-channels, tt, W+jets, diboson, and Drell-Yan processes with their relative normalizations are treated as a combined background for the training of the SM BNN. The SM BNN discriminant is used to remove the SM backgrounds in the search for an anomalous structure at the Wtb vertex. Three additional Wtb BNNs are used to separate the individual contributions of right-handed vector (fVR), left-handed (fTL) and right-handed (fTR) tensor couplings from the left-handed vector coupling (fVL) expected in the SM. The physical meanings of these couplings are discussed in section 7. The FCNC processes with anomalous tcg and tug vertices are assumed to be completely independent of the SM contribution. In addition tcg BNN and tug BNN are trained to distinguish the corresponding contributions from the SM contribution. The kinematic properties of the potential tcg and tug contributions are slightly di erent owing to the di erent initial states and the discussion of the couplings appears in section 8. The input variables used by each BNN are summarised in table 2. Their choice is based on the di erence in the structure of the Feynman diagrams contributing to the signal and background processes. Distributions of four representative variables for data and simulated events are shown in gure 2. Several variables in the analysis require full kinematic reconstruction of the top quark and W boson candidates. For the kinematic reconstruction of the top quark, the W boson mass constraint is applied to extract the component of the neutrino momentum along the beam direction (pz). This leads to a quadratic equation in pz. For two real solutions of the equation, the smaller value of pz is used as the solution. For events with complex solutions, The data-to-simulation comparisons shown in gure 3 demonstrate good agreement in the control regions enriched in top quark pair events (4 jets with 2 b tags) and W+jets (no b-tagged jets), as well as in the signal regions, as discussed in section 4. In gure 3, the simulated events are normalized to the results obtained in the t to the data. Systematic uncertainties and statistical analysis The analysis extracts the parameters of single top quark production and any signs of beyond the SM behaviour based on the BNN discriminant distributions. It follows the same methodology for estimating the uncertainties as used in previously CMS measurements of single top quark production [58, 59]. Bayesian inference is used to derive the posterior probability. A signal strength ~ s is the central value of the posterior probability distribution p(~ sjd) with a certain data set d. This posterior probability can be obtained as the integral p(~ sjd) = where ~ b are the background yields, ~ are additional nuisance parameters, which are the systematic uncertainties of the analysis, (~ s), (~ b), and (~) are the prior probabiliM (P i6=ibest (ji)) pT of the leading b jet (the b-tagged jet with the highest pT) pT of the next-to-leading b jet pT of the leading jet vector sum of the pT of the leading and the next-to-leading jet pT of the light- avour jet (untagged jet with the highest value of j j) pT of the muon pT of the W boson and the leading b jet scalar sum of the pT of the leading and the next-to-leading jet missing transverse energy of the light- avour jet invariant mass of the leading and the next-to-leading jets invariant mass of all jets without the best one invariant mass of the W boson and all jets invariant mass of the W boson and the leading b jet azimuthal angle between the muon and p~Tmiss azimuthal angle between the muon and the W boson cosine of the angle between the muon and the light- avour jet in the top quark rest frame, for top quark reconstructed with the leading b jet [55] cosine of the angle between the muon momentum in the W boson rest frame and the direction of the W boson boost vector [56] cosine of the angle between the W boson and the light- avour jet in the top quark rest frame [56] charge of the muon measure of the atness of the event using the smallest eigenvalue of the normalized momentum tensor [57] SM BNN discriminant used for each particular BNN. The number 7 or 8 marks the variables used in just the p represents the variables s = 7 or 8 TeV analysis. The symbol \tug" marks the variables used just in the training of the tug FCNC BNN. The notations \leading" and \next-to-leading" refer to the highest-pT and second-highest-pT jet, respectively. The notation \best" jet is used for the jet that gives a reconstructed mass of the top quark closest to the value of 172.5 GeV, which is used in the MC simulation. 19.7 fb-1 (8 TeV) 19.7 fb-1 (8 TeV) CMS /s0 6 t vE 4 4 t/s 4 n veE 2 V 8 e /s6 6 t ve 4 E statistical uncertainties. Plots are for the p s = 8 TeV data set. Comparison of experimental with simulated data of the BNNs input variables cos( ;jL )jtop, (jL), HT(j1; j2), and M (W; b1). The variables are described in table 2. The lower part of each plot shows the relative di erence between the data and the total predicted background. The hatched band corresponds to the total simulation uncertainty. The vertical bars represent the ties of the corresponding parameters, (d) is a normalization factor, and p(dj~ s; ~ b; ~) is the probability to obtain a given d with given ~ s, ~ b, and ~. Uncertainties considered in the analysis are discussed next. For the variation of the background normalization, scale parameters are introduced in the statistical model, and the corresponding variations of these parameters are the same as for the SM measurement in ref. [59]. All background processes and their normalizations are treated as being statistically independent. To estimate the uncertainty in the multijet distributions, two di erent isolation criteria are used (0:3 < Irel < 0:5 and 0:5 < Irel < 1). Also, a comparison is made between data and events generated with the pythia 6.4 simulation. The impact of the changes in the multijet template are well within the range of 50% to +100%, and this is included as a prior uncertainty in the statistical model. To estimate the uncertainties in the detector-related jet and ETmiss corrections, the four-momenta of all reconstructed jets in simulated events are scaled simultaneously in accordance with pT- and -dependent jet energy correction (JEC) uncertainties [60]. These changes are also propagated to ETmiss. The e ect of the 10% uncertainty in ETmiss coming from unclustered energy deposits in the calorimeters that are not associated with jets is estimated after subtracting all the jet and lepton energies from the ETmiss calculation. Parameters in the procedure to correct the jet energy resolution (JER) are varied within their uncertainties, and the procedure is repeated for all jets in the simulation [60, 61]. The variations coming from the uncertainty in the b quark tagging 19.7 fb-1 (8 TeV) 19.7 fb-1 (8 TeV) SM BNN in 2 jets, 1 tag 0 t/s 3 n v E 2 SM BNN in 3 jets, 1 tag 19.7 fb-1 (8 TeV) SM BNN in 3 jets, 2 tags 19.7 fb-1 (8 TeV) SM BNN in tt CR (4 jets, 2 tags) SM BNN in W+jets CR (no b-tagged jets) three separate signal regions of two jets with one b-tagged (2 jets, 1 tag) (upper), three jets with one of them b-tagged (3 jets, 1 tag) (middle left), and three jets with two of them b-tagged (3 jets, 2 tags) (middle right), and in tt (4 jets, 2 tags) (lower left) and W+jets (no b-tagged jets) (lower right) background control regions (CR). The lower part of each plot shows the relative di erence between the data and the total predicted background. The hatched band corresponds to the total simulation uncertainty. The vertical bars represent the statistical uncertainties. e ciency and mistagging rate of jets are propagated to the simulated events [54]. The uncertainties for c quark jets are assumed to be twice as large as for b quark jets. The scale factors for tagging b and c quark jets are treated as fully correlated, whereas the mistagging scale factors are varied independently. The integrated luminosity in the s = 7 and 8 TeV data-taking periods is measured with a relative uncertainty of 2.2% [62] and 2.6% [63], respectively. In the combined ts, all experimental uncertainties, including these from the integrated luminosity, are treated as uncorrelated between the data sets. The uncertainty in the pileup modelling is estimated by using di erent multiplicity distributions obtained by changing the minimum-bias cross section by 5% [64]. Trigger scale factors, muon identi cation, and muon isolation uncertainties are introduced in the statistical model as additional factors, Gaussian-distributed parameters with a mean of 1 and widths of 0.2%, 0.5%, and 0.2%, respectively. The uncertainties from additional hard-parton radiation and the matching of the samples with di erent jet multiplicity are evaluated by doubling or halving the threshold for the MadGraph jet-matching procedure for the top quark pair and W+jets production, using dedicated MadGraph samples generated with such shifts in the parameters [65]. The renormalization and factorization scale uncertainties are estimated using MC simulated samples generated by doubling or halving the renormalization and factorization scales for the signal and the main background processes. Uncertainties in the parton distribution functions (PDF) are evaluated with the CT10 PDF set according to the PDF4LHC formulae for Hessian-based sets. We follow this recommendation and reweight the simulated events to obtain the uncertainty, which is about 5% on average. The uncertainty from the choice of the event generator to model the signal is estimated using pseudo-experiments. These pseudo-experiments are used to t simulated events, obtained from the CompHEP signal sample, and from the powheg signal sample. Half of the di erence between these two measurements is taken as the uncertainty (5%). Previous CMS studies [66, 67] of top quark pair production showed a softer pT distribution of the top quark in the data than predicted by the NLO simulation. A correction for the simulation of tt production background is applied. The small e ect of this reweighting procedure (0.8%) is taken into account as an uncertainty. The uncertainty owing to the nite size of the simulated samples is taken into account through the Barlow-Beeston method [68]. The BNN discriminant distributions can be a ected by di erent types of systematic uncertainties. Some of these only impact the overall normalization, while others change the shape of the distribution. Both types of systematic uncertainties are included in the statistical model through additional nuisance parameters. Systematic uncertainties related to the modelling of JEC, JER, b tagging and mistagging rates, ETmiss, and pileup, are included as nuisance parameters in the t. The variations in these quantities leads to a total uncertainty of about 6%. Other systematic uncertainties, i.e. those related to the signal model, renormalization and factorization scales, matching of partons to nal jets, and choice of PDF, are handled through the pseudo-experiments to determine the di erence between the varied and the nominal result. The total uncertainty from these sources is about 8%. We include uncertainties in the statistical model by following the same approach as described in previous CMS measurements of the single top quark t-channel cross section [24, 58, 59]. The SM BNN discriminant distribution after the statistical analysis and evaluation of all the uncertainties are shown in gure 4 for the two data sets. As the p s = 7 and 8 TeV data sets have similar selection criteria, reweighting, and uncertainties and the physics is expected to also be similar, the data sets are combined by performing a joint t. The previously described systematic uncertainties and methods of statistical analysis are used in the combination. In the statistical model, the experimental uncertainties are treated as uncorrelated between the data sets. The theoretical uncertainties (from the choice of generator, scales, and PDF) are treated as fully correlated between the data sets. The sensitivity of the separate p CMS ./00 6 ve 4 E -M-C0.2 a t SM BNN all the uncertainties. The lower part of each plot shows the relative di erence between the data and The vertical bars represent the statistical uncertainties. The left (right) plot corresponds to p the total predicted background. The hatched band corresponds to the total simulation uncertainty. s = 7 their corresponding systematic uncertainties. Therefore, the combined statistical model does not necessarily provide the tightest exclusion limits. In order to validate the analysis strategy and the statistical treatment of the uncertainties, we measure the cross sections in the SM t channel, and nd values and uncertainties in agreement with previous measurements [58, 59] and with the prediction of the SM. Search for anomalous contributions to the Wtb vertex Modelling the structure of the anomalous Wtb vertex The t-channel single top quark production is sensitive to possible deviations from the SM prediction for the Wtb vertex. The most general, lowest-dimension, CP-conserving Lagrangian for the Wtb vertex has the following form [69, 70]: L = p b fVLPL + fVRPR tW fTLPL + fTRPR t + h:c:; where PL;R = (1 5)=2, = i( )=2, g is the coupling constant of the weak interaction, the form factor fVL (fVR) represents the left-handed (right-handed) vector coupling, and fTL (fTR) represents the left-handed (right-handed) tensor coupling. The analysis scheme proposed in refs. [71, 72] is used to look for possible deviations from the SM, by postulating the presence of a left-handed vector coupling. Two of the four couplings are considered simultaneously in two-dimensional scenarios: (fVL, fVR) and (fVL, fTL), where the couplings are allowed to vary from 0 to +1, and (fVL, fTR) with variation bounds from -1 to +1. Then, considering three couplings simultaneously leads to couplings have the same variation range of (0; +1) for fVR and fTL, and (-1; +1) for fVL and fTR. In the presence of anomalous Wtb couplings in both the production and decay of the top quark, the kinematic and angular distributions are signi cantly a ected relative to their SM expectations. It is therefore important to correctly model the kinematics of such processes. Following the method of ref. [73], the event samples with left-handed (SM) interactions and a purely right-handed vector (left-handed tensor) interactions are generated to model the (fVL, f R) ((fVL, fTL)) scenario. Simulated event samples with the V left-handed interaction in the production and the right-handed vector (left-handed tensor) interaction in the decay of the top quark, and vice versa, are also generated. The scenarios with fTR couplings are more complicated because of the presence of cross terms, such fTR), in the squared matrix element describing the single top quark production process. Special event samples are generated for such scenarios. Owing to the presence of the cross terms with odd power of fVL and fTR couplings, the analysis is sensitive to negative values of these couplings. The details of the simulation approach are provided in ref. [73]. All signal samples are simulated at NLO precision following ref. [36]. Exclusion limits on anomalous couplings Following the strategy described in section 5, in addition to the SM BNN, the anomalous Wtb BNNs are trained to distinguish possible right-handed vector or left-/right-handed tensor structures from the SM left-handed vector structure in the t-channel single top quark events. The set of variables chosen for the di erent Wtb BNNs are listed in table 2. The rst two-dimensional scenario considers a possible mixture of fVL and (anomalous) fVR couplings. The corresponding Wtb BNN (fVL, fVR) is trained to distinguish the contribution of these two couplings. For the (fVL, fTL) scenario, another Wtb BNN is trained to separate the left-handed vector interacting single top quark SM events from events with a left-handed tensor operator in the Wtb vertex. For the third scenario, (fVL, fTR), the last Wtb BNN is trained to separate left-handed-vector-interacting single top quark SM events from events with a right-handed-tensor operator in the Wtb vertex. Figure 5 shows the comparison between the data and simulation for the outputs of the Wtb BNN (fVL, fVR), Wtb BNN (fVL, fTL), and Wtb BNN (fVL, fTR). The SM BNN and one of the Wtb BNN discriminants are used as inputs in the simultaneous t of the two BNN discriminants. One-dimensional constraints on the anomalous parameters are obtained by integrating over the other anomalous parameter in the corresponding scenario. The results of the ts are presented in the form of two-dimensional contours at 68% and 95% CL exclusion limits, and as given in table 3, as one-dimensional constraints in di erent scenarios. Both the one- and two-dimension limits are measured for the individual data sets and their combination. The combined observed and expected two-dimensional contours in the (fVL, fVR), (fVL, fTL), and (fVL, fTR) spaces are As the interference terms between fTL and fTR or fVR and fTR couplings are negligible [20], it is possible to consider three-dimensional scenarios with simultaneous variation of fVL, fTL, fTR or fVL, fVR, fTR couplings. The three-dimensional statistical analysis is performed using the SM BNN, Wtb BNN (fVL, fTR), and either the Wtb BNN (fVL, fTL) or Wtb BNN (fVL, fVR) discriminants to obtain the excluded regions at 68% and 95% CL for fTL and f R, again by integrating over the other anomalous couplings. The combined T couplings are presented in gure 7 (left) in the form of observed and expected 68% and s tn 6 e E 4 ven 3 en 4 19.7 fb-1 (8 TeV) 19.7 fb-1 (8 TeV) / ts 2 n on the left (right) correspond to p histograms) for the scenarios (fVL, fVR) (top), (fVL, fTL) (middle), and (fVL, fTR) (bottom). The plots handed interactions from one of the anomalous interactions. In each plot, the expected distribution with the corresponding anomalous coupling set to 1.0 is shown by the solid curve. The lower part of each plot shows the relative di erence between the data and the total predicted background. The hatched band corresponds to the total simulation uncertainty. The vertical bars represent the statistical uncertainties. f R, and fTR couplings are shown in V gure 7 (right) as two-dimensional exclusion limits in the (fVR, fTR) plane. The measured exclusion limits from the three-dimensional ts with the conservative limits from the three-dimensional ts of 0:049 < f R < 0:048 as our measurement. These limits are much more restrictive than those obtained by the D0 Collaboration in a direct search [72], and agree well with the recent results obtained by the ATLAS [74] and CMS [75, 76] experiments from measurements of the W boson helicity fractions. 5.0 fb-1 (7 TeV) + 19.7 fb-1 (8 TeV) R T 0.3 f dimensional planes (f L 8 TeV exclusion limits in f R ) (top-left), (f L , fTR) (bottom) at 68% 5.0 fb-1 (7 TeV) + 19.7 fb-1 (8 TeV) 5.0 fb-1 (7 TeV) + 19.7 fb-1 (8 TeV) 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 CL in the two-dimension planes (jfTLj, fTR) (left) and (jfVRj, fTR) (right). , f R (left), and f L , f R (right) in the form of observed and expected exclusion limits s = 7 TeV (fVL, fTL, fTR) (fVL, fVR, fTR) s = 8 TeV (fVL, fTL, fTR) (fVL, fVR, fTR) (fVL, fTL, fTR) (fVL, fVR, fTR) s = 7 and 8 TeV scenarios. The rst column shows the couplings allowed to vary in the t, with the remaining couplings set to the SM values. The observed (expected) 95% CL limits for each of the two data sets and their combination are given in the following columns. Search for tcg and tug FCNC interactions Theoretical introduction The FCNC tcg and tug interactions can be written in a model-independent form with the following e ective Lagrangian [1]: L = is the scale of new physics ( 1 TeV), q refers to either the u or c quarks, tqg de nes of the SU(3) colour gauge group, gs is the coupling constant of the strong interaction, and Ga is a gluon eld strength tensor. The Lagrangian is assumed to be symmetric with respect to the left and right projectors. Single top quark production through FCNC interactions contains 48 subprocesses for both the tug and tcg channels, and the cross processes are shown in gure 8. Since the in uence of the FCNC parameters on the total top quark width is negligible for the allowed region of FCNC parameters, the SM value for the top quark width is used in this analysis. The CompHEP generator is used to simulate of the signal tug and tcg processes. The FCNC samples are normalized to the NLO cross sections using a K factor of 1.6 for higher-order QCD corrections [77]. Exclusion limits on tug and tcg anomalous couplings FCNC processes are kinematically di erent from any SM processes, therefore, it is reasonable to train a new BNN to discriminate between FCNC production as the signal and the SM background, including the t-channel single top quark production. Owing to the possible presence of a FCNC tug or tcg signal, two BNNs are trained to distinguish each of the couplings. The variable choices for these BNNs, shown in table 2, are motivated by analysis of the Feynman diagrams of the FCNC and SM processes. The comparison of the neural network output for the data and model is shown in gure 9. Output histograms from the tug and tcg FCNC BNN discriminants for the SM backgrounds are used as input tained by tting the histograms. The combined p s = 7 and 8 TeV observed and expected and j tcgj= exclusion limits at 68% and 95% CL on the anomalous FCNC parameters in the form of two-dimensional contours are shown in gure 10. The two-dimensional contours re ect the possible simultaneous presence of the two FCNC parameters. Individual exclusion limits on j tugj= are obtained by integrating over j tcgj= and vice versa. These individual limits can be used to calculate the upper limits on the branching fractions B(t ! cg) [78]. The observed and expected exclusion limits at 95% CL on the FCNC couplings and the corresponding branching fractions are given in table 4. These limits are signi cantly better than those obtained by the D0 [22] and CDF [21] experiments, and in previous CMS results, and are comparable to recent ATLAS measurements [23]. A direct search for model-independent anomalous operators in the Wtb vertex and FCNC couplings has been performed using single top quark t-channel production in data collected by the CMS experiment in pp collisions at p s = 7 and 8 TeV. Di erent possible .02 8 s ten 6 E 4 2 6 0 s ten 4 19.7 fb-1 (8 TeV) simulations by the lled histograms. The plots on the left (right) correspond to the p t ! ug (upper) or t ! cg (lower) processes as signal from the SM processes as background. The results from data are shown as points and the predicted distributions from the background s = 7 (8) TeV data. The solid and dashed lines give the expected distributions for t ! ug and t ! cg, respectively, assuming a coupling of j tugj= = 0:04 (0:06) and j tcgj= = 0:08 (0:12) TeV 1 on the left (right) plots. The lower part of each plot shows the relative di erence between the data and the total predicted background. The hatched band corresponds to the total simulation uncertainty. The vertical bars represent the statistical uncertainties. 5.0 fb-1 (7 TeV) + 19.7 fb-1 (8 TeV) 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04 Figure 10. Combined p on the j tugj= and j tcgj= 7 TeV 8 TeV 7 and 8 TeV j tugj= (TeV 1 10.1 (6.9) 10 4 fractions obtained using the p s = 7 and 8 TeV data, and their combination. anomalous contributions are investigated. The observed event rates are consistent with the SM prediction, and exclusion limits are extracted at 95% CL. The combined limits in three-dimensional scenarios on possible Wtb anomalous couplings are fVL > 0:98 for the left-handed vector coupling, jfVRj < 0:16 for the right-handed vector coupling, jfTLj < 0:057 for the left-handed tensor coupling, and 0:049 < fTR < 0:048 for the righthanded tensor coupling. For FCNC couplings of the gluon to top and up quarks (tug) or top and charm quarks (tcg), the 95% CL exclusion limits on the coupling strengths are j tugj= fractions, B(t ! ug) < 2:0 10 3 TeV 1 and j tcgj= 10 2 TeV 1 or, in terms of branching Acknowledgments We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative sta s at CERN and at other CMS institutes for their contributions to the success of the CMS e ort. In addition, we gratefully acknowledge the computing centres and personnel of the Worldwide LHC Computing Grid for delivering so e ectively 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: the Austrian Federal Ministry of Science, Research and Economy and the Austrian Science Fund; the Belgian Fonds de la Recherche Scienti que, and Fonds voor Wetenschappelijk Onderzoek; the Brazilian Funding Agencies (CNPq, CAPES, FAPERJ, and FAPESP); the Bulgarian Ministry of Education and Science; CERN; the Chinese Academy of Sciences, Ministry of Science and Technology, and National Natural Science Foundation of China; the Colombian Funding Agency (COLCIENCIAS); the Croatian Ministry of Science, Education and Sport, and the Croatian Science Foundation; the Research Promotion Foundation, Cyprus; the Secretariat for Higher Education, Science, Technology and Innovation, Ecuador; the Ministry of Education and Research, Estonian Research Council via IUT23-4 and IUT236 and European Regional Development Fund, Estonia; the Academy of Finland, Finnish Ministry of Education and Culture, and Helsinki Institute of Physics; the Institut National de Physique Nucleaire et de Physique des Particules / CNRS, and Commissariat a l'Energie Atomique et aux Energies Alternatives / CEA, France; the Bundesministerium fur Bildung und Forschung, Deutsche Forschungsgemeinschaft, and Helmholtz-Gemeinschaft Deutscher Forschungszentren, Germany; the General Secretariat for Research and Technology, Greece; simulating electroweak top-quark production events in the NLO approximation: singleTop event generator, Phys. 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Carrera Jarrin Academy of Scienti c Research and Technology of the Arab Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt S. Elgammal8, A. Mohamed9, Y. Mohammed10, E. Salama8;11 National Institute of Chemical Physics and Biophysics, Tallinn, Estonia B. Calpas, M. Kadastik, M. Murumaa, L. Perrini, M. Raidal, A. Tiko, C. Veelken Department of Physics, University of Helsinki, Helsinki, Finland P. Eerola, J. Pekkanen, M. Voutilainen Helsinki Institute of Physics, Helsinki, Finland J. Harkonen, V. Karimaki, R. Kinnunen, T. Lampen, K. Lassila-Perini, S. Lehti, T. Linden, P. Luukka, T. Peltola, J. Tuominiemi, E. Tuovinen, L. Wendland Lappeenranta University of Technology, Lappeenranta, Finland J. Talvitie, T. Tuuva IRFU, CEA, Universite 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. 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Kress, A. Kunsken, J. Lingemann, A. Nehrkorn, A. Nowack, I.M. Nugent, C. Pistone, O. Pooth, Deutsches Elektronen-Synchrotron, Hamburg, Germany M. Aldaya Martin, C. Asawatangtrakuldee, I. Asin, K. Beernaert, O. Behnke, U. Behrens, A.A. Bin Anuar, K. Borras16, A. Campbell, P. Connor, C. Contreras-Campana, F. Costanza, C. Diez Pardos, G. Dolinska, G. Eckerlin, D. Eckstein, E. Gallo17, J. Garay Garcia, A. Geiser, A. Gizhko, J.M. Grados Luyando, P. Gunnellini, A. Harb, J. Hauk, M. Hempel18, H. Jung, A. Kalogeropoulos, O. Karacheban18, M. Kasemann, J. Keaveney, J. Kieseler, C. Kleinwort, I. Korol, W. Lange, A. Lelek, J. Leonard, K. Lipka, A. Lobanov, W. Lohmann18, R. Mankel, I.-A. Melzer-Pellmann, A.B. Meyer, G. Mittag, J. Mnich, A. Mussgiller, E. Ntomari, D. Pitzl, R. Placakyte, A. Raspereza, B. Roland, M.O . Sahin, P. Saxena, T. Schoerner-Sadenius, C. Seitz, S. Spannagel, N. Stefaniuk, K.D. Trippkewitz, G.P. Van Onsem, R. Walsh, C. Wissing University of Hamburg, Hamburg, Germany V. Blobel, M. Centis Vignali, A.R. Draeger, T. Dreyer, E. Garutti, K. Goebel, D. Gonzalez, J. Haller, M. Ho mann, A. Junkes, R. Klanner, R. Kogler, N. Kovalchuk, T. Lapsien, T. Lenz, I. Marchesini, D. Marconi, M. Meyer, M. Niedziela, D. Nowatschin, J. Ott, F. Pantaleo13, T. Pei er, A. Perieanu, J. Poehlsen, C. Sander, C. Scharf, P. Schleper, A. Schmidt, S. Schumann, J. Schwandt, H. Stadie, G. Steinbruck, F.M. Stober, M. Stover, H. Tholen, D. Troendle, E. Usai, L. Vanelderen, A. Vanhoefer, B. Vormwald Institut fur Experimentelle Kernphysik, Karlsruhe, Germany C. Barth, C. Baus, J. Berger, E. Butz, T. Chwalek, F. Colombo, W. De Boer, A. Dierlamm, S. Fink, R. Friese, M. Gi els, A. Gilbert, D. Haitz, F. Hartmann13, S.M. Heindl, Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece I. Topsis-Giotis G. Anagnostou, G. Daskalakis, T. Geralis, V.A. Giakoumopoulou, A. Kyriakis, D. Loukas, National and Kapodistrian University of Athens, Athens, Greece A. Agapitos, S. Kesisoglou, A. Panagiotou, N. Saoulidou, E. Tziaferi University of Ioannina, Ioannina, Greece I. Evangelou, G. Flouris, C. Foudas, P. Kokkas, N. Loukas, N. Manthos, I. Papadopoulos, MTA-ELTE Lendulet CMS Particle and Nuclear Physics Group, Eotvos Lorand University, Budapest, Hungary Wigner Research Centre for Physics, Budapest, Hungary G. Bencze, C. Hajdu, P. Hidas, D. Horvath19, F. Sikler, V. Veszpremi, G. Vesztergombi20, Institute of Nuclear Research ATOMKI, Debrecen, Hungary N. Beni, S. Czellar, J. Karancsi21, A. Makovec, J. Molnar, Z. Szillasi University of Debrecen, Debrecen, Hungary M. Bartok20, P. Raics, Z.L. Trocsanyi, B. Ujvari National Institute of Science Education and Research, Bhubaneswar, India S. Bahinipati, S. Choudhury22, P. Mal, K. Mandal, A. Nayak23, D.K. Sahoo, N. Sahoo, Panjab University, Chandigarh, India S. Bansal, S.B. Beri, V. Bhatnagar, R. Chawla, U.Bhawandeep, A.K. Kalsi, A. Kaur, M. Kaur, R. Kumar, A. Mehta, M. Mittal, J.B. Singh, G. Walia University of Delhi, Delhi, India Ashok Kumar, A. Bhardwaj, B.C. Choudhary, R.B. Garg, S. Keshri, A. Kumar, S. Malhotra, M. Naimuddin, N. Nishu, K. Ranjan, R. Sharma, V. Sharma Saha Institute of Nuclear Physics, Kolkata, India R. Bhattacharya, S. Bhattacharya, K. Chatterjee, S. Dey, S. Dutt, S. Dutta, S. Ghosh, N. Majumdar, A. Modak, K. Mondal, S. Mukhopadhyay, S. Nandan, A. Purohit, A. Roy, D. Roy, S. Roy Chowdhury, S. Sarkar, M. Sharan, S. Thakur Indian Institute of Technology Madras, Madras, India Bhabha Atomic Research Centre, Mumbai, India R. Chudasama, D. Dutta, V. Jha, V. Kumar, A.K. Mohanty13, P.K. Netrakanti, L.M. Pant, P. Shukla, A. Topkar Tata Institute of Fundamental Research-A, Mumbai, India T. Aziz, S. Dugad, G. Kole, B. Mahakud, S. Mitra, G.B. Mohanty, N. Sur, B. Sutar Tata Institute of Fundamental Research-B, Mumbai, India S. Banerjee, S. Bhowmik24, R.K. Dewanjee, S. Ganguly, M. Guchait, Sa. Jain, S. Kumar, M. Maity24, G. Majumder, K. Mazumdar, B. Parida, T. Sarkar24, N. Wickramage25 Indian Institute of Science Education and Research (IISER), Pune, India S. Chauhan, S. Dube, A. Kapoor, K. Kothekar, A. Rane, S. Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran H. Behnamian, S. Chenarani26, E. Eskandari Tadavani, S.M. Etesami26, A. Fahim27, M. Khakzad, M. Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi, F. Rezaei Hosseinabadi, B. Safarzadeh28, M. Zeinali University College Dublin, Dublin, Ireland M. Felcini, M. Grunewald INFN Sezione di Bari a, Universita di Bari b, Politecnico di Bari c, Bari, Italy M. Abbresciaa;b, C. Calabriaa;b, C. Caputoa;b, A. Colaleoa, D. Creanzaa;c, L. Cristellaa;b, N. De Filippisa;c, M. De Palmaa;b, L. Fiorea, G. Iasellia;c, G. Maggia;c, M. Maggia, G. Minielloa;b, S. Mya;b, S. Nuzzoa;b, A. Pompilia;b, G. Pugliesea;c, R. Radognaa;b, A. Ranieria, G. Selvaggia;b, L. Silvestrisa;13, R. Vendittia;b, P. Verwilligena INFN Sezione di Bologna a, Universita 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. Cu ania;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;13 INFN Sezione di Catania a, Universita di Catania b, Catania, Italy S. Albergoa;b, M. Chiorbolia;b, S. Costaa;b, A. Di Mattiaa, F. Giordanoa;b, R. Potenzaa;b, A. Tricomia;b, C. Tuvea;b INFN Sezione di Firenze a, Universita di Firenze b, Firenze, Italy G. Barbaglia, V. Ciullia;b, C. Civininia, R. D'Alessandroa;b, E. Focardia;b, V. Goria;b, P. Lenzia;b, M. Meschinia, S. Paolettia, G. Sguazzonia, L. Viliania;b;13 INFN Laboratori Nazionali di Frascati, Frascati, Italy L. Benussi, S. Bianco, F. Fabbri, D. Piccolo, F. Primavera13 INFN Sezione di Genova a, Universita di Genova b, Genova, Italy V. Calvellia;b, F. Ferroa, M. Lo Veterea;b, M.R. Mongea;b, E. Robuttia, S. Tosia;b INFN Sezione di Milano-Bicocca a, Universita di Milano-Bicocca b, Milano, Malvezzia, Manzonia;b;13, Marzocchia;b, Menascea, L. Moronia, M. Paganonia;b, D. Pedrinia, S. Pigazzini, S. Ragazzia;b, T. Tabarelli de Fatisa;b INFN Sezione di Napoli a, Universita di Napoli 'Federico II' b, Napoli, Italy, Universita della Basilicata c, Potenza, Italy, Universita G. Marconi d, Roma, S. Buontempoa, N. Cavalloa;c, G. De Nardo, S. Di Guidaa;d;13, M. Espositoa;b, F. Fabozzia;c, A.O.M. Iorioa;b, G. Lanzaa, L. Listaa, S. Meolaa;d;13, P. Paoluccia;13, C. Sciaccaa;b, F. Thyssen Trento c, Trento, Italy INFN Sezione di Padova a, Universita di Padova b, Padova, Italy, Universita di P. Azzia;13, 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;13, N. Pozzobona;b, P. Ronchesea;b, F. Simonettoa;b, E. Torassaa, M. Zanetti, P. Zottoa;b, A. Zucchettaa;b, G. Zumerlea;b INFN Sezione di Pavia a, Universita di Pavia b, Pavia, Italy A. Braghieria, A. Magnania;b, P. Montagnaa;b, S.P. Rattia;b, V. Rea, C. Riccardia;b, P. Salvinia, I. Vaia;b, P. Vituloa;b INFN Sezione di Perugia a, Universita di Perugia b, Perugia, Italy L. Alunni Solestizia;b, G.M. Bileia, D. Ciangottinia;b, L. Fanoa;b, P. Laricciaa;b, R. Leonardia;b, G. Mantovania;b, M. Menichellia, A. Sahaa, A. Santocchiaa;b INFN Sezione di Pisa a, Universita di Pisa b, Scuola Normale Superiore di Pisa c, Pisa, Italy K. Androsova;29, P. Azzurria;13, G. Bagliesia, J. Bernardinia, T. Boccalia, R. Castaldia, M.A. Cioccia;29, R. Dell'Orsoa, S. Donatoa;c, G. Fedi, A. Giassia, M.T. Grippoa;29, F. Ligabuea;c, T. Lomtadzea, L. Martinia;b, A. Messineoa;b, F. Pallaa, A. Rizzia;b, A. SavoyNavarroa;30, P. Spagnoloa, R. Tenchinia, G. Tonellia;b, A. Venturia, P.G. Verdinia A. Zanettia INFN Sezione di Roma a, Universita di Roma b, Roma, Italy S. Gellia;b, C. Jordaa, E. Longoa;b, F. Margarolia;b, P. Meridiania, G. Organtinia;b, R. Paramattia, F. Preiatoa;b, S. Rahatloua;b, C. Rovellia, F. Santanastasioa;b INFN Sezione di Torino a, Universita di Torino b, Torino, Italy, Universita del Piemonte Orientale c, Novara, Italy N. Amapanea;b, R. Arcidiaconoa;c;13, S. Argiroa;b, M. Arneodoa;c, N. Bartosika, R. Bellana;b, C. Biinoa, N. Cartigliaa, F. Cennaa;b, M. Costaa;b, R. Covarellia;b, A. Deganoa;b, N. Demariaa, L. Fincoa;b, B. Kiania;b, C. Mariottia, S. Masellia, E. Migliorea;b, V. Monacoa;b, E. Monteila;b, M.M. Obertinoa;b, L. Pachera;b, N. Pastronea, 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. Traczyka;b INFN Sezione di Trieste a, Universita di Trieste b, Trieste, Italy S. Belfortea, M. Casarsaa, F. Cossuttia, G. Della Riccaa;b, C. La Licataa;b, A. Schizzia;b, Kyungpook National University, Daegu, Korea D.H. Kim, G.N. Kim, M.S. Kim, S. Lee, S.W. Lee, Y.D. Oh, S. Sekmen, D.C. Son, Chonbuk National University, Jeonju, Korea Hanyang University, Seoul, Korea J.A. Brochero Cifuentes, T.J. Kim Korea University, Seoul, Korea S. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, Y. Jo, Y. Kim, B. Lee, K. Lee, K.S. Lee, S. Lee, J. Lim, S.K. Park, Y. Roh Seoul National University, Seoul, Korea J. Almond, J. Kim, S.B. Oh, S.h. Seo, U.K. Yang, H.D. Yoo, G.B. Yu University of Seoul, Seoul, Korea M. Choi, H. Kim, H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park, G. Ryu, M.S. Ryu Sungkyunkwan University, Suwon, Korea Y. Choi, J. Goh, C. Hwang, J. Lee, I. Yu Vilnius University, Vilnius, Lithuania V. Dudenas, A. Juodagalvis, J. Vaitkus National Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Malaysia I. Ahmed, Z.A. Ibrahim, J.R. Komaragiri, M.A.B. Md Ali31, F. Mohamad Idris32, W.A.T. Wan Abdullah, M.N. Yusli, Z. Zolkapli Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico H. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-De La Cruz33, A. Hernandez-Almada, R. Lopez-Fernandez, J. Mejia Guisao, A. Sanchez-Hernandez Universidad Iberoamericana, Mexico City, Mexico S. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia Benemerita Universidad Autonoma de Puebla, Puebla, Mexico S. Carpinteyro, I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad Autonoma de San Luis Potos , San Luis Potos , Mexico A. Morelos Pineda University of Auckland, Auckland, New Zealand D. Krofcheck P.H. Butler University of Canterbury, Christchurch, New Zealand National Centre for Physics, Quaid-I-Azam University, Islamabad, Pakistan A. Ahmad, M. Ahmad, Q. Hassan, H.R. Hoorani, W.A. Khan, M.A. Shah, M. Shoaib, National Centre for Nuclear Research, Swierk, Poland H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Gorski, M. Kazana, K. Nawrocki, K. Romanowska-Rybinska, M. Szleper, P. Zalewski Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Warsaw, Poland K. Bunkowski, A. Byszuk34, K. Doroba, A. Kalinowski, M. Konecki, J. Krolikowski, M. Misiura, M. Olszewski, M. Walczak Laboratorio de Instrumentac~ao e F sica Experimental de Part culas, Lisboa, Joint Institute for Nuclear Research, Dubna, Russia A. Malakhov, V. Matveev35;36, V.V. Mitsyn, P. Moisenz, V. Palichik, V. Perelygin, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, E. Tikhonenko, A. Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia L. Chtchipounov, V. Golovtsov, Y. Ivanov, V. Kim37, E. Kuznetsova38, V. Murzin, V. Oreshkin, V. Sulimov, A. Vorobyev Institute for Nuclear Research, Moscow, Russia Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov, N. Krasnikov, A. Pashenkov, D. Tlisov, A. Toropin Institute for Theoretical and Experimental Physics, Moscow, Russia V. Epshteyn, V. Gavrilov, N. Lychkovskaya, V. Popov, I. Pozdnyakov, G. Safronov, A. Spiridonov, M. Toms, E. Vlasov, A. Zhokin National Research Nuclear University 'Moscow Engineering Physics Institute' (MEPhI), Moscow, Russia M. Chadeeva39, M. Danilov39, O. Markin P.N. Lebedev Physical Institute, Moscow, Russia V. Andreev, M. Azarkin36, I. Dremin36, M. Kirakosyan, A. Leonidov36, S.V. Rusakov, Moscow, Russia P. Volkov, G. Vorotnikov Physics, Protvino, Russia Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, A. Baskakov, A. Belyaev, E. Boos, V. Bunichev, M. Dubinin40, L. Dudko, V. Klyukhin, O. Kodolova, N. Korneeva, I. Lokhtin, I. Miagkov, S. Obraztsov, M. Per lov, V. Savrin, State Research Center of Russian Federation, Institute for High Energy 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, University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia P. Adzic41, P. Cirkovic, D. Devetak, J. Milosevic, V. Rekovic nologicas (CIEMAT), Madrid, Spain J. Alcaraz Maestre, E. Calvo, M. Cerrada, M. Chamizo Llatas, N. Colino, B. De La Cruz, A. Delgado Peris, A. Escalante Del Valle, C. Fernandez Bedoya, J.P. Fernandez Ramos, J. Flix, M.C. Fouz, P. Garcia-Abia, O. Gonzalez Lopez, S. Goy Lopez, J.M. Hernandez, M.I. Josa, E. Navarro De Martino, A. Perez-Calero Yzquierdo, J. Puerta Pelayo, A. Quintario Olmeda, I. Redondo, L. Romero, M.S. Soares Universidad Autonoma de Madrid, Madrid, Spain J.F. de Troconiz, M. Missiroli, D. Moran Universidad de Oviedo, Oviedo, Spain J. Cuevas, J. Fernandez Menendez, I. Gonzalez Caballero, J.R. Gonzalez Fernandez, E. Palencia Cortezon, S. Sanchez Cruz, I. Suarez Andres, J.M. Vizan Garcia Instituto de F sica de Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, Spain I.J. Cabrillo, A. Calderon, J.R. Castin~eiras De Saa, E. Curras, M. Fernandez, J. GarciaFerrero, G. Gomez, A. Lopez Virto, J. Marco, C. Martinez Rivero, F. Matorras, J. Piedra CERN, European Organization for Nuclear Research, Geneva, Switzerland Paul Scherrer Institut, Villigen, Switzerland W. Bertl, K. Deiters, W. Erdmann, R. Horisberger, Q. Ingram, H.C. Kaestli, D. Kotlinski, U. Langenegger, T. Rohe Institute for Particle Physics, ETH Zurich, Zurich, Switzerland F. Bachmair, L. Bani, L. Bianchini, B. Casal, G. Dissertori, M. Dittmar, M. Donega, P. Eller, C. Grab, C. Heidegger, D. Hits, J. Hoss, G. Kasieczka, P. Lecomtey, W. Lustermann, B. Mangano, M. Marionneau, P. Martinez Ruiz del Arbol, M. Masciovecchio, M.T. Meinhard, D. Meister, F. Micheli, P. Musella, F. Nessi-Tedaldi, F. Pandol , J. Pata, F. Pauss, G. Perrin, L. Perrozzi, M. Quittnat, M. Rossini, M. Schonenberger, A. Starodumov47, M. Takahashi, V.R. Tavolaro, K. Theo latos, R. Wallny Universitat Zurich, Zurich, Switzerland T.K. Aarrestad, C. Amsler48, L. Caminada, M.F. Canelli, V. Chiochia, A. De Cosa, C. Galloni, A. Hinzmann, T. Hreus, B. Kilminster, C. Lange, J. Ngadiuba, D. Pinna, G. Rauco, P. Robmann, D. Salerno, Y. Yang National Central University, Chung-Li, Taiwan V. Candelise, T.H. Doan, Sh. Jain, R. Khurana, M. Konyushikhin, C.M. Kuo, W. Lin, Y.J. Lu, A. Pozdnyakov, S.S. Yu National Taiwan University (NTU), Taipei, Taiwan Arun Kumar, P. Chang, Y.H. Chang, Y.W. Chang, Y. Chao, K.F. Chen, P.H. Chen, C. Dietz, F. Fiori, W.-S. Hou, Y. Hsiung, Y.F. Liu, R.-S. Lu, M. Min~ano Moya, E. Paganis, A. Psallidas, J.f. Tsai, Y.M. Tzeng B. Asavapibhop, G. Singh, N. Srimanobhas, N. Suwonjandee Cukurova University, Adana, Turkey A. Adiguzel, M.N. Bakirci49, S. Cerci50, S. Damarseckin, Z.S. Demiroglu, C. Dozen, I. Dumanoglu, S. Girgis, G. Gokbulut, Y. Guler, E. Gurpinar, I. Hos, E.E. Kangal51, O. Kara, A. Kayis Topaksu, U. Kiminsu, M. Oglakci, G. Onengut52, K. Ozdemir53, B. Tali50, S. Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East Technical University, Physics Department, Ankara, Turkey B. Bilin, S. Bilmis, B. Isildak54, G. Karapinar55, M. Yalvac, M. Zeyrek Bogazici University, Istanbul, Turkey E. Gulmez, M. Kaya56, O. Kaya57, E.A. Yetkin58, T. Yetkin59 Istanbul Technical University, Istanbul, Turkey A. Cakir, K. Cankocak, S. Sen60 Institute for Scintillation Materials of National Academy of Science of Ukraine, Kharkov, Ukraine Kharkov, Ukraine L. Levchuk, P. Sorokin National Scienti c Center, Kharkov Institute of Physics and Technology, University of Bristol, Bristol, United Kingdom R. Aggleton, F. Ball, L. Beck, J.J. Brooke, D. Burns, E. Clement, D. Cussans, H. Flacher, J. Goldstein, M. Grimes, G.P. Heath, H.F. Heath, J. Jacob, L. Kreczko, C. Lucas, D.M. Newbold61, S. Paramesvaran, A. Poll, T. Sakuma, S. Seif El Nasr-storey, D. Smith, Rutherford Appleton Laboratory, Didcot, United Kingdom K.W. Bell, A. Belyaev62, C. Brew, R.M. Brown, L. Calligaris, D. Cieri, D.J.A. Cockerill, J.A. Coughlan, K. Harder, S. Harper, E. Olaiya, D. Petyt, C.H. Shepherd-Themistocleous, A. Thea, I.R. Tomalin, T. Williams Imperial College, London, United Kingdom M. Baber, R. Bainbridge, O. Buchmuller, A. Bundock, D. Burton, S. Casasso, M. Citron, D. Colling, L. Corpe, P. Dauncey, G. Davies, A. De Wit, M. Della Negra, P. Dunne, A. Elwood, D. Futyan, Y. Haddad, G. Hall, G. Iles, R. Lane, C. Laner, R. Lucas61, L. Lyons, A.-M. Magnan, S. Malik, L. Mastrolorenzo, J. Nash, A. Nikitenko47, J. Pela, B. Penning, M. Pesaresi, D.M. Raymond, A. Richards, A. Rose, C. Seez, A. Tapper, K. Uchida, M. Vazquez Acosta63, T. Virdee13, S.C. Zenz Brunel University, Uxbridge, United Kingdom J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, D. Leslie, I.D. Reid, P. Symonds, L. Teodorescu, M. Turner A. Borzou, K. Call, J. Dittmann, K. Hatakeyama, H. Liu, N. Pastika The University of Alabama, Tuscaloosa, U.S.A. O. Charaf, S.I. Cooper, C. Henderson, P. Rumerio Boston University, Boston, U.S.A. Brown University, Providence, U.S.A. G. Benelli, E. Berry, D. Cutts, A. Garabedian, J. Hakala, U. Heintz, J.M. Hogan, O. Jesus, E. Laird, G. Landsberg, Z. Mao, M. Narain, S. Piperov, S. Sagir, E. Spencer, R. Syarif University of California, Davis, Davis, U.S.A. R. Breedon, G. Breto, D. Burns, M. Calderon De La Barca Sanchez, S. Chauhan, M. Chertok, J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk, M. Gardner, W. Ko, R. Lander, C. Mclean, M. Mulhearn, D. Pellett, J. Pilot, F. Ricci-Tam, S. Shalhout, J. Smith, M. Squires, D. Stolp, M. Tripathi, S. Wilbur, R. Yohay University of California, Los Angeles, U.S.A. R. Cousins, P. Everaerts, A. Florent, J. Hauser, M. Ignatenko, D. Saltzberg, E. Takasugi, V. Valuev, M. Weber University of California, Riverside, Riverside, U.S.A. K. Burt, R. Clare, J. Ellison, J.W. Gary, G. Hanson, J. Heilman, P. Jandir, E. Kennedy, F. Lacroix, O.R. Long, M. Malberti, M. Olmedo Negrete, M.I. Paneva, A. Shrinivas, H. Wei, S. Wimpenny, B. R. Yates University of California, San Diego, La Jolla, U.S.A. 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. Wasserbaech64, C. Welke, J. Wood, F. Wurthwein, A. Yagil, G. Zevi Della Porta University of California, Santa Barbara - Department of Physics, Santa Barbara, U.S.A. C. West, J. Yoo R. Bhandari, J. Bradmiller-Feld, C. Campagnari, A. Dishaw, V. Dutta, K. Flowers, M. Franco Sevilla, P. Ge ert, C. George, F. Golf, L. Gouskos, J. Gran, R. Heller, J. Incandela, N. Mccoll, S.D. Mullin, A. Ovcharova, J. Richman, D. Stuart, I. Suarez, California Institute of Technology, Pasadena, U.S.A. D. Anderson, A. Apresyan, J. Bendavid, A. Bornheim, J. Bunn, Y. Chen, J. Duarte, A. Mott, H.B. Newman, C. Pena, M. 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Rodriguez Florida State University, Tallahassee, U.S.A. A. Ackert, J.R. Adams, T. Adams, A. Askew, S. Bein, B. Diamond, S. Hagopian, V. Hagopian, K.F. Johnson, A. Khatiwada, H. Prosper, A. Santra, M. Weinberg Florida Institute of Technology, Melbourne, U.S.A. M.M. Baarmand, V. Bhopatkar, S. Colafranceschi66, M. Hohlmann, D. Noonan, T. Roy, University of Illinois at Chicago (UIC), Chicago, U.S.A. M.R. Adams, L. Apanasevich, D. Berry, R.R. Betts, I. Bucinskaite, R. Cavanaugh, O. Evdokimov, L. Gauthier, C.E. Gerber, D.J. Hofman, P. Kurt, C. O'Brien, I.D. Sandoval Gonzalez, P. Turner, N. Varelas, H. Wang, Z. Wu, M. Zakaria, J. Zhang B. Bilki67, W. Clarida, K. Dilsiz, S. Durgut, R.P. Gandrajula, M. Haytmyradov, V. Khristenko, J.-P. Merlo, H. Mermerkaya68, A. Mestvirishvili, A. Moeller, J. Nachtman, H. Ogul, Y. Onel, F. Ozok69, A. Penzo, C. Snyder, E. Tiras, J. Wetzel, K. Yi Johns Hopkins University, Baltimore, U.S.A. I. Anderson, B. Blumenfeld, A. Cocoros, N. Eminizer, D. Fehling, L. Feng, A.V. Gritsan, P. Maksimovic, M. Osherson, J. Roskes, U. Sarica, M. Swartz, M. Xiao, Y. Xin, C. You The University of Kansas, Lawrence, U.S.A. A. Al-bataineh, P. Baringer, A. Bean, J. Bowen, C. Bruner, J. Castle, R.P. Kenny III, A. Kropivnitskaya, D. Majumder, W. Mcbrayer, M. Murray, S. Sanders, R. Stringer, J.D. Tapia Takaki, Q. Wang Kansas State University, Manhattan, U.S.A. A. Ivanov, K. Kaadze, S. Khalil, M. Makouski, Y. Maravin, A. Mohammadi, L.K. Saini, N. Skhirtladze, S. Toda Lawrence Livermore National Laboratory, Livermore, U.S.A. D. Lange, F. Rebassoo, D. Wright University of Maryland, College Park, U.S.A. C. Anelli, A. Baden, O. Baron, A. Belloni, B. Calvert, S.C. Eno, C. Ferraioli, J.A. Gomez, N.J. Hadley, S. Jabeen, R.G. Kellogg, T. Kolberg, J. Kunkle, Y. Lu, A.C. Mignerey, Y.H. Shin, A. Skuja, M.B. Tonjes, S.C. Tonwar Massachusetts Institute of Technology, Cambridge, U.S.A. D. Abercrombie, B. Allen, A. Apyan, R. Barbieri, A. Baty, R. Bi, K. Bierwagen, S. Brandt, W. 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Alyari, J. Dolen, J. George, A. Godshalk, C. Harrington, I. Iashvili, J. Kaisen, A. Kharchilava, A. Kumar, A. Parker, S. Rappoccio, B. Roozbahani Northeastern University, Boston, U.S.A. G. Alverson, E. Barberis, D. Baumgartel, A. Hortiangtham, A. Massironi, D.M. Morse, D. Nash, T. Orimoto, R. Teixeira De Lima, D. Trocino, R.-J. Wang, D. Wood Northwestern University, Evanston, U.S.A. S. Bhattacharya, K.A. Hahn, A. Kubik, J.F. Low, N. Mucia, N. Odell, B. Pollack, M.H. Schmitt, K. Sung, M. Trovato, M. Velasco University of Notre Dame, Notre Dame, U.S.A. N. Dev, M. Hildreth, K. Hurtado Anampa, C. Jessop, D.J. Karmgard, N. Kellams, K. Lannon, N. Marinelli, F. Meng, C. Mueller, Y. Musienko35, M. Planer, A. Reinsvold, R. Ruchti, G. Smith, S. Taroni, N. Valls, M. Wayne, M. Wolf, A. Woodard The Ohio State University, Columbus, U.S.A. J. Alimena, L. Antonelli, J. Brinson, B. Bylsma, L.S. Durkin, S. Flowers, B. Francis, A. Hart, C. Hill, R. Hughes, W. Ji, B. Liu, W. Luo, D. Puigh, B.L. Winer, H.W. Wulsin Princeton University, Princeton, U.S.A. S. Cooperstein, O. Driga, P. Elmer, J. Hardenbrook, P. Hebda, J. Luo, D. Marlow, T. Medvedeva, M. Mooney, J. Olsen, C. Palmer, P. Piroue, D. Stickland, C. Tully, University of Puerto Rico, Mayaguez, U.S.A. Purdue University, West Lafayette, U.S.A. A. Barker, V.E. Barnes, D. Benedetti, S. Folgueras, L. Gutay, M.K. Jha, M. Jones, A.W. Jung, K. Jung, D.H. Miller, N. Neumeister, B.C. Radburn-Smith, X. Shi, J. Sun, A. Svyatkovskiy, F. Wang, W. Xie, L. Xu Purdue University Calumet, Hammond, U.S.A. N. Parashar, J. Stupak Rice University, Houston, U.S.A. A. Adair, B. Akgun, Z. Chen, K.M. Ecklund, F.J.M. Geurts, M. Guilbaud, W. Li, B. Michlin, M. Northup, B.P. Padley, R. Redjimi, J. Roberts, J. Rorie, Z. Tu, J. Zabel University of Rochester, Rochester, U.S.A. B. Betchart, A. Bodek, P. de Barbaro, R. Demina, Y.t. Duh, T. Ferbel, M. Galanti, A. Garcia-Bellido, J. Han, O. Hindrichs, A. Khukhunaishvili, K.H. Lo, P. Tan, M. Verzetti Rutgers, The State University of New Jersey, Piscataway, U.S.A. J.P. Chou, E. Contreras-Campana, Y. Gershtein, T.A. Gomez Espinosa, E. Halkiadakis, M. Heindl, D. Hidas, E. Hughes, S. Kaplan, R. Kunnawalkam Elayavalli, S. Kyriacou, S. Thomas, P. Thomassen, M. Walker University of Tennessee, Knoxville, U.S.A. M. Foerster, J. Heideman, G. Riley, K. Rose, S. Spanier, K. Thapa Texas A&M University, College Station, U.S.A. O. Bouhali70, A. Celik, M. Dalchenko, M. De Mattia, A. Delgado, S. Dildick, R. Eusebi, J. Gilmore, T. Huang, E. Juska, T. Kamon71, R. Mueller, Y. Pakhotin, R. Patel, A. Perlo , L. Pernie, D. Rathjens, A. Rose, A. Safonov, A. Tatarinov, K.A. Ulmer Texas Tech University, Lubbock, U.S.A. N. Akchurin, C. Cowden, J. Damgov, C. Dragoiu, P.R. Dudero, J. Faulkner, S. Kunori, K. Lamichhane, S.W. Lee, T. Libeiro, S. Undleeb, I. Volobouev, Z. Wang Vanderbilt University, Nashville, U.S.A. A.G. Delannoy, S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, P. Sheldon, S. Tuo, J. Velkovska, Q. Xu University of Virginia, Charlottesville, U.S.A. T. Sinthuprasith, X. Sun, Y. Wang, E. Wolfe, F. Xia Wayne State University, Detroit, U.S.A. C. Clarke, R. Harr, P.E. Karchin, P. Lamichhane, J. Sturdy M.W. Arenton, P. Barria, B. Cox, J. Goodell, R. Hirosky, A. Ledovskoy, H. Li, C. Neu, University of Wisconsin - Madison, Madison, WI, U.S.A. D.A. Belknap, S. Dasu, L. Dodd, S. Duric, B. Gomber, M. Grothe, M. Herndon, A. Herve, P. Klabbers, A. Lanaro, A. Levine, K. Long, R. Loveless, I. Ojalvo, T. Perry, G.A. Pierro, G. Polese, T. Ruggles, A. Savin, A. Sharma, N. Smith, W.H. Smith, D. Taylor, N. Woods 1: Also at Vienna University of Technology, Vienna, Austria 2: Also at State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, 3: Also at Institut Pluridisciplinaire Hubert Curien, Universite de Strasbourg, Universite de Haute Alsace Mulhouse, CNRS/IN2P3, Strasbourg, France 4: Also at Universidade Estadual de Campinas, Campinas, Brazil 5: Also at Universite Libre de Bruxelles, Bruxelles, Belgium 6: Also at Deutsches Elektronen-Synchrotron, Hamburg, Germany 7: Also at Joint Institute for Nuclear Research, Dubna, Russia 8: Now at British University in Egypt, Cairo, Egypt 9: Also at Zewail City of Science and Technology, Zewail, Egypt 10: Now at Fayoum University, El-Fayoum, Egypt 11: Now at Ain Shams University, Cairo, Egypt 12: Also at Universite de Haute Alsace, Mulhouse, France 13: Also at CERN, European Organization for Nuclear Research, Geneva, Switzerland 14: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, 16: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany 17: Also at University of Hamburg, Hamburg, Germany 18: Also at Brandenburg University of Technology, Cottbus, Germany 19: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary 20: Also at MTA-ELTE Lendulet CMS Particle and Nuclear Physics Group, Eotvos Lorand 21: Also at University of Debrecen, Debrecen, Hungary 22: Also at Indian Institute of Science Education and Research, Bhopal, India 23: Also at Institute of Physics, Bhubaneswar, India 24: Also at University of Visva-Bharati, Santiniketan, India 25: Also at University of Ruhuna, Matara, Sri Lanka 26: Also at Isfahan University of Technology, Isfahan, Iran 27: Also at University of Tehran, Department of Engineering Science, Tehran, Iran 28: Also at Plasma Physics Research Center, Science and Research Branch, Islamic Azad University, Tehran, Iran 29: Also at Universita degli Studi di Siena, Siena, Italy 30: Also at Purdue University, West Lafayette, U.S.A. 31: Also at International Islamic University of Malaysia, Kuala Lumpur, Malaysia 32: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia 33: Also at Consejo Nacional de Ciencia y Tecnolog a, Mexico city, Mexico 34: Also at Warsaw University of Technology, Institute of Electronic Systems, Warsaw, Poland 35: Also at Institute for Nuclear Research, Moscow, Russia at National Research Nuclear University 'Moscow Engineering Physics Insti37: Also at St. Petersburg State Polytechnical University, St. Petersburg, Russia 38: Also at University of Florida, Gainesville, U.S.A. 39: Also at P.N. Lebedev Physical Institute, Moscow, Russia 40: Also at California Institute of Technology, Pasadena, U.S.A. 41: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia 42: Also at INFN Sezione di Roma; Universita di Roma, Roma, Italy 43: Also at National Technical University of Athens, Athens, Greece 44: Also at Scuola Normale e Sezione dell'INFN, Pisa, Italy 45: Also at National and Kapodistrian University of Athens, Athens, Greece 46: Also at Riga Technical University, Riga, Latvia 47: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia 48: Also at Albert Einstein Center for Fundamental Physics, Bern, Switzerland 49: Also at Gaziosmanpasa University, Tokat, Turkey 50: Also at Adiyaman University, Adiyaman, Turkey 51: Also at Mersin University, Mersin, Turkey 52: Also at Cag University, Mersin, Turkey 53: Also at Piri Reis University, Istanbul, Turkey 54: Also at Ozyegin University, Istanbul, Turkey 55: Also at Izmir Institute of Technology, Izmir, Turkey 56: Also at Marmara University, Istanbul, Turkey 57: Also at Kafkas University, Kars, Turkey 58: Also at Istanbul Bilgi University, Istanbul, Turkey 59: Also at Yildiz Technical University, Istanbul, Turkey 61: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom 62: Also at School of Physics and Astronomy, University of Southampton, Southampton, United 63: Also at Instituto de Astrof sica de Canarias, La Laguna, Spain 64: Also at Utah Valley University, Orem, U.S.A. 65: Also at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, 66: Also at Facolta Ingegneria, Universita di Roma, Roma, Italy 67: Also at Argonne National Laboratory, Argonne, U.S.A. 68: Also at Erzincan University, Erzincan, Turkey 69: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey 70: Also at Texas A&M University at Qatar, Doha, Qatar 71: Also at Kyungpook National University, Daegu, Korea Summary [39] P. 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Search for anomalous Wtb couplings and flavour-changing neutral currents in t-channel single top quark production in pp collisions at \( \sqrt{s}=7 \) and 8 TeV, Journal of High Energy Physics, 2017, DOI: 10.1007/JHEP02(2017)028