Evidence for the associated production of a W boson and a top quark in ATLAS at sqrt(s) = 7 TeV

arXiv:1205.5764v2 [hep-ex] 16 Aug 2012

EUROPEAN ORGANISATION FOR NUCLEAR RESEARCH (CERN)

CERN-PH-EP-2012-117

Submitted to: Physics Letters B

Evidence for the associated production of a

W

boson and

a top quark in ATLAS at

√

_{s = 7 TeV}

The ATLAS Collaboration

Abstract

This Letter presents evidence for the associated production of a

W

boson and a top quark using

2.05 fb

−1

_of

_pp

_{collision data at}

√

_{s = 7 TeV}

_{accumulated with the ATLAS detector at the LHC. The}

analysis is based on the selection of the dileptonic final states with events featuring two isolated

leptons, electron or muon, with significant transverse missing momentum and at least one jet. An

approach based on boosted decision trees has been developed to improve the discrimination of single

top-quark

Wt

events from background. A template fit to the final classifier distributions is performed

to determine the cross-section. The result is incompatible with the background-only hypothesis at

the 3.3σ

level, the expected sensitivity assuming the Standard Model production rate being 3.4σ.

The corresponding cross-section is determined and found to be

σ

Wt

= 16.8

± 2.9 (stat) ± 4.9 (syst) pb

,

in good agreement with the Standard Model expectation. From this result the CKM matrix element

|V

tb

| = 1.03

+0.16_−0.19

is derived assuming that the

Wt

production through

|V

ts

|

and

|V

td

|

is small.

Evidence for the associated production of a W boson and a top quark

in ATLAS at

√

s = 7 TeV

The ATLAS Collaboration

Abstract

This letter presents evidence for the associated production of a W boson and a top quark using 2.05 fb−1_{of pp collision}

data at √s = 7 TeV accumulated with the ATLAS detector at the LHC. The analysis is based on the selection of the

dileptonic final states with events featuring two isolated leptons, electron or muon, with significant transverse missing momentum and at least one jet. An approach based on boosted decision trees has been developed to improve the discrimination of single top-quark Wt events from background. A template fit to the final classifier distributions is performed to determine the cross-section. The result is incompatible with the background-only hypothesis at the 3.3σ level, the expected sensitivity assuming the Standard Model production rate being 3.4σ. The corresponding

cross-section is determined and found to be σWt = 16.8± 2.9 (stat) ± 4.9 (syst) pb, in good agreement with the

Standard Model expectation. From this result the CKM matrix element_|Vtb| = 1.03+0.16_−0.19is derived assuming that the

Wt production through_|Vts| and |Vtd| is small.

Keywords: ATLAS, Top quark, W+t, single top-quark

1. Introduction

The observation of single top-quark production was

first reported by both D0 [1] and CDF [2] experiments at

the Tevatron. The observations by the two experiments are consistent with the Standard Model (SM) expecta-tion for single top-quark producexpecta-tion resulting from two mechanisms, the t-channel and the s-channel, measured inclusively. The third SM single top-quark production mechanism, the associated production of a top quark and a W boson, has not been observed at the Tevatron.

At the Large Hadron Collider (LHC), the electroweak production of single top-quarks represents about half of the t¯t-pair production cross-section. First

measure-ments of the single top-quark production [3, 4] have

been obtained in the t-channel at a centre-of-mass en-ergy of 7 TeV, and show good agreement with the SM expectation. The associated production of a top quark and a W boson involves the interaction of a gluon and a b-quark emitting an on-shell W boson, as shown in

the Feynman diagrams in Figure 1. The final state

thus contains two W bosons and an additional quark from the top quark decay, normally a b-quark. Next-to-leading-order Wt Feynman diagrams including a sec-ond b-quark may interfere with t¯t-pair production. The interference should be small in the reconstructed

exclu-sive final state with only one quark, where the largest fraction of Wt signal is expected. In this analysis, the Wt leading-order approximation is used, and the differ-ence between leading-order and next-to-leading-order Wt calculation is considered as modelling uncertainty. Because of the massive particles in the final state, this production mechanism has an extremely low rate at the Tevatron compared to t-channel, but is expected to have a much higher cross-section at the LHC, where the available partonic energy and the gluon flux are larger. For proton-proton collisions at 7 TeV, the single top-quark Wt-channel production cross-section is estimated

to be 15.7_{±1.1 pb [}5] for a top quark mass of 172.5 GeV.

Figure 1: Leading-order Feynman diagrams for associated production of a single top-quark and a W boson.

produc-tion are sensitive to different manifestaproduc-tions of physics beyond the SM, measurements of the individual cross-sections are complementary to each other and allow some sources of new phenomena to be disentangled. The production mode with both a W boson and a top quark in the final state has the special feature that both particles can be identified. Thus, the measurement of the corresponding cross-section can be sensitive to new phenomena which modify the W-t-b interaction, but in-sensitive to flavour-changing neutral currents (FCNCs)

or new particles such as W′, t′and techni-pions [6]. The

measurement of the single top-quark Wt-channel pro-duction cross-sections therefore serves as a direct probe of the W-t-b coupling and allows the direct

determina-tion of the quark-mixing matrix element_|Vtb| [7,8]. This

result can be compared to the results obtained from t-and s-channel production measurements.

In this Letter, an analysis is presented that estab-lishes evidence for the associated production of a top quark and a W boson in the dilepton channel, with pp _{→ Wt → ℓνbℓν, where ℓ = e, µ. Events featuring} two leptons and neutrinos from W boson decays and an additional jet originating from the top quark decay, are selected and analysed. The corresponding cross-section is extracted and the magnitude of the CKM matrix

el-ement_|Vtb| is derived. Comparison is made with the

Tevatron average and ATLAS measurements.

2. Data and Monte Carlo simulation

The present analysis uses LHC proton-proton colli-sion data at a centre-of-mass energy of 7 TeV collected between March and July 2011 with the ATLAS

detec-tor [9], which is composed of inner tracking detectors

in a 2 tesla magnetic field surrounded by calorimeters and a muon spectrometer. The selected events were recorded based on single-electron or single-muon trig-gers. Detector and data-quality requirements are ap-plied offline, resulting in a data set corresponding to an

integrated luminosity of 2.05_{± 0.08 fb}−1[10,11].

In the following, all Monte Carlo (MC) simula-tions of quark related processes assume a top-quark mass of 172.5 GeV, and a width of 1.3 GeV,

consistent with the world average value [12].

Sam-ples of simulated events for single top-quark processes

are produced with AcerMC version 3.7 [13] coupled

with the MRST2007 [14] parton distribution

func-tions (PDFs). The t¯t-pair processes are generated

us-ing MC@NLO version 3.41 [15], interfaced with the

CTEQ6.6 PDFs set [16]. All top quark samples are

normalised using next-to-next-to-leading order (NNLO)

cross-sections [5, 17, 18, 19]. Gauge boson (W/Z)

production in association with jets is simulated using

the leading-order generator ALPGEN version 2.13 [20],

coupled with CTEQ6L1 PDFs [21]. The diboson

pro-cesses WW, WZ and ZZ are generated using

ALP-GEN version 2.13 with MRST2007 PDFs. In all

cases, HERWIG [22] is used for the showering and is

linked to the underlying event model in JIMMY version

4.31 [23]. After the event generation, all samples are

passed through the full simulation of the ATLAS

detec-tor [24] based on GEANT4 [25] and are reconstructed

using the same procedure as collision data. The simula-tion includes the effect of a variable number of proton-proton collisions per bunch crossing and is weighted to reproduce the same distribution of the number of colli-sions per bunch crossing as observed in data. The aver-age number of interactions per bunch crossing is 6.2 in this data set.

3. Event reconstruction and selection

A set of general-purpose event-quality

require-ments [26] are applied to the data. Events are selected if

they contain at least one primary vertex candidate with a minimum of five associated tracks, each reconstructed

with transverse momentum (pT) above 400 MeV. Events

must not contain any jet, with pT (calculated with the

electromagnetic response for jets) greater than 20 GeV, arising from out-of-time energy depositions or from real energy depositions with a hardware or calibration prob-lem.

Electron candidates are reconstructed using a

cluster-based algorithm [27] and are required to have transverse

energy ET > 25 GeV and |η| < 2.47, where η denotes

the pseudorapidity1_{. Events with electrons falling in}

the calorimeter barrel-endcap transition region,

corre-sponding to 1.37 < _{|η| < 1.52, are rejected.}

Candi-dates must satisfy a set of quality criteria, referred to

as either “loose” or “tight” criteria [27], which for the

latter, includes additional stringent requirements on the matching between the electron track candidate and the cluster. Isolation criteria require that the sum of the calorimeter transverse energy within a cone of radius

∆R = p(∆η)2_{+ (∆φ)}2 _{= 0.3 around the electron} direc-tion (excluding the cells associated with the electron)

1_{ATLAS uses a right-handed coordinate system with its origin at} the nominal interaction point (IP) in the centre of the detector and the z-axis along the beam pipe. The x-axis points from the IP to the centre of the LHC ring, and the y-axis points upwards. Cylindrical coordinates (r, φ) are used in the transverse plane, φ is the azimuthal angle around the beam pipe. The pseudorapidity η is defined in terms of the polar angle θ as η =− ln(tan θ/2).

must be less than 15% of the electron transverse energy.

In addition, the sum of the pT of all tracks within the

same cone radius around the electron direction, exclud-ing the track belongexclud-ing to the electron, must be less than

10% of the electron ET.

Muon candidates are reconstructed by combining track segments found in the inner detector and in the

muon spectrometer, and are required to have pT >

25 GeV and_{|η| < 2.5. Selected muons must}

addition-ally satisfy a series of cuts on the number of hits on the track in the various tracking sub-detectors, referred to as

“tight” quality criteria [28]. The isolation requirements

are the same as those for electrons. In order to reject events in which a muon emitting a hard photon is also reconstructed as an electron, events are vetoed when a selected electron-muon pair shares the same inner de-tector track.

Hadronic jets are reconstructed from calorimeter

clusters [29] using the anti-ktalgorithm [30] with a

ra-dius parameter R = 0.4. To take into account the differ-ences in calorimeter response to electrons and hadrons,

a pT- and η-dependent scale factor is applied to each

jet in order to make an average energy scale

correc-tion [31]. Jets are required to have ET > 30 GeV and

|η| < 2.5. Jets overlapping with selected electron

candi-dates within ∆R < 0.2 are removed, keeping the electron

candidate. The missing transverse momentum ~E_Tmiss is

calculated using the clusters identified in the calorime-ter that are calibrated according to the associated

recon-structed high-pTobjects. Taking also into account the

energy clusters not associated to any high-pT objects,

projections of this vectorial sum in the transverse plane,

correspond to the negative of the ~Emiss

T components. The

missing transverse momentum is also corrected for the

presence of electrons, muons, and jets [32].

A dilepton event preselection classifies the events ac-cording to exclusive ee, eµ and µµ categories. The fol-lowing event selections are common to all three ee, µµ and eµ channels. Candidate events must contain two “tight” opposite-sign leptons. Events having any

ad-ditional isolated leptons with pT greater than 25 GeV

are vetoed in order to ensure the orthogonality of the ee, eµ and µµ categories and suppress diboson back-grounds. Since the signal signature contains a single

high-pT quark from top quark decay, only events with

at least one jet are selected. However, no b-tagging re-quirements are applied as they do not offer significant rejection over the primary background originating from t¯t-pair events. As signal events also feature neutrinos from the leptonic decays of W bosons, the magnitude of the missing transverse momentum of the event is re-quired to be greater than 50 GeV.

In the ee and µµ channels, the invariant mass of the

lepton pair mℓℓ is required to satisfy mℓℓ < 81 GeV or

mℓℓ > 101 GeV in order to reduce the contamination

from Z boson decays. In all three channels, the Z_{→ ττ}

background is reduced by applying a selection on the sum of the two angles in the transverse plane between each lepton and the missing transverse momentum di-rection:

∆φ(ℓ1, ~EmissT ) + ∆φ(ℓ2, ~EmissT ) > 2.5 .

The application of this cut results in an expected

rejec-tion of 95% of Z _{→ ττ events, 30% of Z → ee and}

Z _{→ µµ events and 21% of t¯t-pair events, while} keep-ing 87% of the expected signal rate. After the selection, signal is expected mainly in events with exactly one jet. Events with at least two jets are expected to be domi-nated by background events and are used as control re-gions.

4. Background estimation

The main background originates from t¯t-pair

produc-tion in the dilepton channel t¯t → ℓνbℓνb. The

t¯t-pair background is estimated using MC simulation

nor-malised to the NNLO cross-section [17,18,19], and the

uncertainty is further constrained by the fit of data in

2-jet and_{≥3-jet bins.}

Diboson events, where initial state radiation produces a jet that passes the jet selection requirements, represent about 15% of the background in events selected with exactly one jet.

Drell-Yan including Z(∗)_{events can be selected if they}

contain an additional jet from gluon radiation. The con-tribution of the Drell-Yan process to the background in the ee and µµ categories is determined via a data-driven procedure. In this method, orthogonal cuts on the

re-constructed dilepton invariant mass mℓℓand the missing

transverse momentum Emiss

T variables are used to

de-fine a set of six regions, including two signal-enriched and four background-enriched regions for the ee final state or the µµ final state. The contamination of the signal regions by Drell-Yan events is estimated from data which are scaled by the measured ratio of numbers of events selected in the corresponding control regions. This scale factor is corrected for the contamination by non-Drell-Yan backgrounds (top quark production, di-boson, W +jets) that are predicted by MC simulation and subtracted prior to its determination. Both the scale fac-tor and non-Drell-Yan background-specific normalisa-tion factors are determined using a likelihood fit of data

in bins of Emiss

normalisation factors are used to estimate the system-atic uncertainty affecting the Drell-Yan event yield. The total uncertainty (statistical plus systematic) ranges be-tween 10% and 35% depending upon the jet multiplic-ity. Drell-Yan events contribute about 5% of selected events.

Contamination of selected events by “fake dileptons” may occur if a lepton from real W/Z decay and an-other lepton from jet misidentification or heavy-flavour (b- and c-hadron) decays are selected, or both leptons from jet misidentification or heavy-flavour decays are selected, such as t¯t-pair lepton+jets final state, W+jets or multijet events. These backgrounds are difficult to model accurately, so a data-driven approach based on

the matrix method [33] is followed. The method builds

upon the use of “tight” and “loose” lepton selection cri-teria mentioned in Section 3. For these backgrounds, the efficiency for a “loose” lepton to be reconstructed as a “tight” lepton is determined using a data sample enriched in multijet events, where some of the lepton quality criteria have been reversed and the isolation re-quirement has been removed. The “loose” to “tight”

efficiency for real leptons is measured from Z _{→ ℓℓ}

events using a tag-and-probe analysis technique. The composition of the selected dilepton sample is extracted

by inverting a 4_{× 4 matrix which relates the observed}

sample composition in terms of selected leptons of dif-ferent quality to its true composition in terms of real and “fake” leptons. The background originating from these events represents less than 1% of the selected sample. The corresponding systematic uncertainty is taken con-servatively at 100%.

A data-driven technique has been used to check the

MC prediction of the Z _{→ ττ contamination. The}

selected sample is split into background- and signal-enriched regions, using the summed ∆φ between the

leptons and the ~Emiss

T direction requirement, as defined

in Section 3. The Z _{→ ττ background in the signal}

region is extracted using the ratio of the correspond-ing MC estimates in both regions, scaled by the num-ber of selected data events from which non-Drell-Yan as well as Drell-Yan ee and µµ backgrounds have been subtracted using MC. The difference between the purely MC-based expectations and this determination is in-cluded as a systematic error and results in an uncertainty

of 60%. The Z → ττ events constitute less than 1% of

the selected event sample.

The jet multiplicity distribution is shown in

Fig-ure2(a)after the selection described in Section 3.

Ta-ble1reports the expected signal, estimated backgrounds

and total event yields in the 1-jet, 2-jet and_≥3-jet

cat-egories, with ee, µµ and eµ channels combined. No

contamination from t-channel or s-channel single top-quark events is expected in the dilepton final state. A to-tal of 224 signal events are expected over a background of 2840. The dominant t¯t-pair production accounts for 75% of the background yield in 1-jet events.

jets N 0 1 2 3 4 5 ≥ 6 Events 0 500 1000 1500 2000 Data JES uncertainty Wt t t WW/ZZ/WZ )+jets µ µ Z(ee/ )+jets τ τ Z( Fake dileptons -1 L dt = 2.05 fb

∫

ATLAS = 7 TeV s (a) BDT output -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 dx / (1/N) dN 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 Testing Wt-channel

, diboson, DY, and fakes t

t Training

Wt-channel , diboson, DY, and fakes t t ATLAS = 7 TeV s Dilepton 1 jet -1 L dt = 2.05 fb

∫

(b)

Figure 2:(a)Number of jets with pT> 30 GeV and |η| < 2.5 after the selection; hatched bands show the jet energy scale (JES) uncertainty. The Wt signal is normalised to the theory prediction.(b)Distribution of BDT output for the signal (Wt-channel) and background (t¯t dibo-son, Drell-Yan and fake dileptons) in signal enriched 1-jet bin. The BDT method uses 2 statistically independent sets of MC-simulated events, indicated as training and testing samples, to check both signal and background BDT output stability. The BDT weight file is derived from a training sample and applied to a testing sample.

5. Discriminating variables for W t events

After the event selection, the signal-to-background ratio is 18% in 1-jet events, where most of the sig-nal is expected. As no individual variable is found to carry a large discriminating power, the analysis strategy uses a multivariate approach based on the “boosted

de-cision trees” (BDT) [34] technique in the framework of

TMVA [35] to discriminate between the Wt-channel and

1-jet 2-jet _{≥ 3-jet} Wt 147_{± 13} 60_{± 9} 17_{± 5} t¯t 610_{± 110} 1160_{± 140} 740_{± 130} Diboson 130_{± 17} 47_{± 5} 17_{± 4} Z_{→ ee} 20_{± 2} 11_{± 2} 5_{± 2} Z_{→ µµ} 29_{± 3} 28_{± 3} 12_{± 3} Z_{→ ττ} 9_{± 6} 4_{± 3} 2_{± 1}

Fake dileptons 11_{± 11} 5_{± 5} negl.

Total bkgd. 810± 120 1260± 140 780± 130

Total expected 960_{± 120} 1320_{± 140} 790_{± 130}

Data observed 934 1300 825

Table 1: Observed and expected event yield in the selected dilepton sample in the 1-jet, 2-jet and≥3-jet bins for an integrated luminosity

of 2.05 fb−1_{. The Wt, t¯t and diboson expectations are normalised to}

the theory predictions. Dilepton and lepton+jets channels are included in t¯t. Only leptonic decays of diboson events are considered. “Fake dileptons” are events with at least one fake lepton, as described in the text. Uncertainties are the sum of statistical and systematic sources added in quadrature.

advantage of using the correlations between variables as part of the distinguishing power. The goal is to ex-ploit the differences between signal and background in many specific kinematic and topological distributions to form a classifier. This BDT classifier is trained using 1-jet events to maximise the expected significance without overtraining. BDT classifiers using the same input vari-ables are also formed for 2-jet events and events with at least 3 jets: while no significant signal yield is expected in these events, the BDT output distribution serves to constrain the background normalisation.

Twenty-two variables with significant separation power are used as input to the BDT, all of which are well modelled by simulation. The two most powerful

variables are psys_T , defined as the magnitude of the

vec-torial sum of pTof the leading jet, leptons and missing

transverse momentum, and the ratio psys_T /√HT+P ET,

where HT is the scalar sum of the two leptons and the

leading jet transverse momenta, and P ET the scalar

sum of the transverse energies of all energy deposits in the calorimeter. Other variables with lesser discrim-inating power are: the event centrality, the thrust and its associated pseudorapidity, the transverse momentum and pseudorapidity of the leading jet, the pseudorapidity of each lepton, the transverse momentum and pseudora-pidity of the system formed by the dilepton and the lead-ing jet, the invariant masses formed by each individual lepton with the leading jet, the missing transverse mo-mentum, the azimuthal angle between the dilepton sys-tem and the leading jet directions, the pseudorapidity

difference between the dilepton system and the leading jet, and the minimal azimuthal angle between the two leptons and the leading jet.

Figure2(b)displays the BDT output probability

den-sity functions for signal and background in 1-jet events. Several checks are performed to ensure that the input variables are well modelled in a large phase space: both background-enriched regions, defined by events with exactly two jets and with at least three jets, and re-gions where most of the signal events are expected.

Fig-ures3(a),3(b)and 3(c)show the resulting good

agree-ment of BDT outputs for data and MC simulation for 1-jet events, 2-jet events and events with at least 3 jets, respectively.

6. Cross-section determination

In order to determine the cross-section, a template fit is performed to the three BDT output distributions for

1-jet, 2-jet and_{≥3-jet events. The determination of the}

Wt-channel single top-quark production yield is treated as a counting experiment in each bin and modelled using a likelihood function in terms of Poisson and Gaussian distributions: L(σWt, ~α) = 3 Y i=1 Nbin Y j=1 PN_{i, j}obs_{|Ni, j}exp(~α) Nsyst Y k=1 G(αk|0, 1)

where the index i runs over the three jet multiplicity

bins (1-jet, 2-jet and≥3-jet), and j runs over all bins of

the corresponding BDT output distribution. The

vari-ables N_{i, j}expand N_{i, j}obsare summed over the three dilepton

flavour combinations. The index k runs over the list of systematic uncertainty sources, which are presented be-low.

The likelihood function includes a Poisson term

PNobs

i, j |N

exp

i, j (~α)



in the observed number of events Nobs

i, j

with the expectation value N_{i, j}exp defined as the sum of

the expected contributions from signal and all MC- or data-driven backgrounds in bin j for the jet multiplicity bin i. Systematic uncertainties are grouped in uncorre-lated sets (k) and their effect is parameterised for each k using a nuisance parameter αk, where αk = 0 maps

to the nominal value and αk = ±1 map to ±1σ shifts

of the parameter. Piecewise-linear interpolation is used

to propagate the effect of the αkto the signal and

back-ground yields. A Gaussian shape G(αk|0, 1) centred at

zero with unit width is used for the αkconstraint terms

in the likelihood.

The contributions to the uncertainty on the fitted

BDT output -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 Events / 0.03 0 20 40 60 80 100 ATLAS Dilepton 1 jet = 7 TeV s -1 L dt = 2.05 fb

∫

Data JES uncertainty Wt t t WW/ZZ/WZ )+jets µ µ Z(ee/ )+jets τ τ Z( Fake dileptons (a) BDT output -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 Events / 0.03 -1 10 1 10 2 10 3 10 4 10 5 10 ATLAS Dilepton 2 jets = 7 TeV s -1 L dt = 2.05 fb

∫

Data JES uncertainty Wt t t WW/ZZ/WZ )+jets µ µ Z(ee/ )+jets τ τ Z( Fake dileptons (b) BDT output -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 Events / 0.03 -1 10 1 10 2 10 3 10 4 10 5 10 ATLAS 3 jets ≥ Dilepton = 7 TeV s -1 L dt = 2.05 fb

∫

Data JES uncertainty Wt t t WW/ZZ/WZ )+jets µ µ Z(ee/ )+jets τ τ Z( Fake dileptons (c)

Figure 3: BDT output for selected events in(a)1-jet,(b)2-jet and(c)

≥3-jet categories. The Wt signal is normalised to the theory prediction

in all three categories.

described below. The main experimental source of sys-tematic uncertainties comes from the knowledge of the jet energy scale (JES), which carries an uncertainty of

2% to 7% parameterised as a function of jet pT and

η [31]. The presence of a b-jet in the event is also taken

into account and an extra uncertainty of 2% to 5%

de-pending on jet pT is added in quadrature to the

non-b-jet uncertainty. Other experimental uncertainty sources which have been considered are the jet energy resolu-tion, the jet reconstruction efficiency, the lepton identi-fication efficiency, the lepton energy scale determination and resolution as well as the multiple proton-proton col-lision and underlying event modelling. The uncertainty

in the luminosity determination is 3.7% [10,11].

Uncertainties in the simulation include the effects of the MC generator choice, the scheme used in the hadronisation and showering and models of the initial and final state radiation (ISR/FSR). Generator choice uncertainty is estimated by comparing AcerMC with MC@NLO generators for single top-quark Wt events, and comparing POWHEG with MC@NLO generators for top quark pair events. Hadronisation and shower-ing effects are estimated usshower-ing the differences seen in

generated events interfaced with either PYTHIA [36]

or HERWIG. Finally, ISR/FSR modelling effects are assessed on MC signal and background samples inter-faced with PYTHIA. Specific tunes are used to sep-arately vary ISR and FSR modelling via changes to

1/ΛISR_QCD, the maximum parton virtuality in a space-like

parton shower, the ΛFSR_QCDscale and the FSR infrared

cut-off [37].

The impacts on both acceptance and kinematic distri-butions shapes are considered for the experimental and simulation uncertainties.

Remaining theoretical uncertainty sources include the cross-section normalisation for the t¯t-pair

back-ground (+7%

−10%) [17, 18, 19] and diboson production

(_{±5%) [}33], as well as the choice of the parton distri-bution functions. For the latter, acceptance variations

have been assessed using the CTEQ [21], MRST [38]

and NNPDF [39] sets.

The cross-section is obtained by maximising the

like-lihood function using RooFit [40]. The total uncertainty

is inferred from the shape of the profile likelihood

ra-tio [41]:

−2lnL(data|σWt, ˆ~ασWt)

L(data| ˆσWt, ˆ~α)

,

where ˆα and ˆ~ σWtare the parameters that maximise the

likelihood with the constraint of ˆσWt > 0, and ˆ~ασWt are

likeli-hood for a given σWt. The maximisation is performed

by varying all the nuisance parameters, except the sys-tematic uncertainties due to the generator and the par-ton shower whose effects are estimated separately using pseudo-experiments.

The inclusion of 2-jet and _{≥3-jet events in the fit}

brings additional constraints on the effect of systematic uncertainties, as jet energy scale and resolution effects as well as ISR/FSR modelling directly affect the jet mul-tiplicity distributions and the BDT outputs. These ef-fects have been evaluated by varying the correspond-ing nuisance parameter central values in the fit to the data. The studies show that the fitted result for the cross-section is not biased by the models used to describe the JES and ISR/FSR uncertainties.

Source ∆σWt/σWt[%]

observed expected

Data statistics 17 17

MC statistics < 5 < 5

Lepton energy scale/res. < 5 < 5

Lepton efficiencies 7 6

Jet energy scale 16 14

Jet energy resolution < 5 < 5

Jet reconstruction eff. < 5 < 5

Generator 10 12 Parton shower 15 14 ISR/FSR 5 6 PDF < 5 6 Pile-up 10 7 t¯t cross-section 6 6 Diboson cross-section 6 5 Drell-Yan estimate < 5 < 5

Fake dileptons estimate < 5 < 5

Z_{→ ττ estimate} < 5 < 5

Luminosity 7 7

All systematics 29 29

Total 34 33

Table 2: Contributions to the uncertainty on the Wt-channel cross-section. The expected results assume the SM cross-section for the signal.

The fitted result for the Wt cross-section at 7 TeV is:

σWt= 16.8± 2.9 (stat) ± 4.9 (syst) pb.

In order to determine the sensitivity of the anal-ysis, an ensemble test is performed on

pseudo-experiments. Systematic uncertainties are treated as

nuisance parameters which are constrained using

Gaus-sian functions. Both “background-only” and

“sig-nal+background” (where the signal rate is predicted by the SM) hypotheses are tested via the generation of ded-icated sets of pseudo-experiments. The likelihood ratio defined as LLR =_−2lnL(data |σ SM Wt, ˆ~ασSM Wt) L(data|0, ˆ~α0)

is computed for each pseudo-experiment. It is used to derive the p-value, which measures the probability for the background to fluctuate above the observed or ex-pected number of events. This p-value is in turn in-terpreted in terms of significance and corresponds to a 3.3σ effect for the data. The corresponding significance for the expected value assuming the SM cross-section corresponds to a 3.4σ effect.

7. Determination of |Vtb|

A direct determination of|Vtb| can be extracted from

the cross-section, assuming that the Wt production

through _|Vts| and |Vtd| is small. The t¯t background,

which is the only background in the analysis that

in-volves_|Vtb|2, does not affect this determination since top

quark decays to a fourth generation heavier quark is

dis-favoured by kinematics. The observed_|Vtb|2is obtained

by dividing the measured cross-section by the theoreti-cal single top-quark cross-section theoreti-calculated with a top

quark mass of 172.5 GeV. Using σtheory_Wt = 15.7(_{±1.1) ×}

|Vtb|2pb [5], the following value is obtained for|Vtb|:

|Vtb| = 1.03+0.16_−0.19,

where the uncertainties in the cross-section measure-ment and in the theoretical predictions have been added in quadrature. This result is compatible with the

com-bination of direct measurements at the Tevatron [42]:

|Vtb| = 0.88+0.07_−0.07, and the measurement by ATLAS [3]:

|Vtb| = 1.13+0.14_−0.13.

8. Conclusion

Evidence for the production of single top-quark

events in the Wt-channel is reported with 2.05 fb−1 of

data collected at 7 TeV with ATLAS during 2011. The strategy followed consists of selecting dilepton events with at least one central jet. Drell-Yan and fake-dilepton backgrounds are estimated in data, while a classifier is used to optimise the discrimination of signal and t¯t-pair events. A fit of the classifier distributions is per-formed to extract the Wt-channel cross-section. The observed significance is 3.3 standard deviations for an

expected sensitivity of 3.4. The corresponding fitted

cross-section is σ(pp→ Wt + X) = 16.8 ± 2.9 (stat) ±

4.9 (syst) pb. A direct determination of_|Vtb| = 1.03+0.16_−0.19

is extracted assuming that the Wt production through

|Vts| and |Vtd| is small. 9. Acknowledgements

We thank CERN for the very successful operation of the LHC, as well as the support staff from our institu-tions without whom ATLAS could not be operated effi-ciently.

We acknowledge the support of ANPCyT, Ar-gentina; YerPhI, Armenia; ARC, Australia; BMWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF, DNSRC and Lundbeck Foundation, Denmark; EPLANET and ERC,

European Union; IN2P3-CNRS, CEA-DSM/IRFU,

France; GNAS, Georgia; BMBF, DFG, HGF, MPG and AvH Foundation, Germany; GSRT, Greece; ISF, MINERVA, GIF, DIP and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Mo-rocco; FOM and NWO, Netherlands; RCN, Norway; MNiSW, Poland; GRICES and FCT, Portugal; MERYS (MECTS), Romania; MES of Russia and ROSATOM, Russian Federation; JINR; MSTD, Serbia; MSSR, Slo-vakia; ARRS and MVZT, Slovenia; DST/NRF, South Africa; MICINN, Spain; SRC and Wallenberg Foun-dation, Sweden; SER, SNSF and Cantons of Bern and Geneva, Switzerland; NSC, Taiwan; TAEK, Turkey; STFC, the Royal Society and Leverhulme Trust, United Kingdom; DOE and NSF, United States of America.

The crucial computing support from all WLCG part-ners is acknowledged gratefully, in particular from CERN and the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Tai-wan), RAL (UK) and BNL (USA) and in the Tier-2 fa-cilities worldwide.

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P. Conde Mui˜no124a_{, E. Coniavitis}118_{, M.C. Conidi}11_{, S.M. Consonni}89a,89b_{, V. Consorti}48_{, S. Constantinescu}25a_,

C. Conta119a,119b_{, G. Conti}57_{, F. Conventi}102a, j_{, M. Cooke}14_{, B.D. Cooper}77_{, A.M. Cooper-Sarkar}118_{, K. Copic}14_,

T. Cornelissen175_{, M. Corradi}19a_{, F. Corriveau}85,k_{, A. Cortes-Gonzalez}165_{, G. Cortiana}99_{, G. Costa}89a_{, M.J. Costa}167_,

D. Costanzo139_{, T. Costin}30_{, D. Cˆot´e}29_{, L. Courneyea}169_{, G. Cowan}76_{, C. Cowden}27_{, B.E. Cox}82_{, K. Cranmer}108_,

F. Crescioli122a,122b, M. Cristinziani20, G. Crosetti36a,36b, R. Crupi72a,72b, S. Cr´ep´e-Renaudin55, C.-M. Cuciuc25a,

C. Cuenca Almenar176, T. Cuhadar Donszelmann139, M. Curatolo47, C.J. Curtis17, C. Cuthbert150, P. Cwetanski60,

H. Czirr141, P. Czodrowski43, Z. Czyczula176, S. D’Auria53, M. D’Onofrio73, A. D’Orazio132a,132b, C. Da Via82,

W. Dabrowski37, A. Dafinca118, T. Dai87, C. Dallapiccola84, M. Dam35, M. Dameri50a,50b, D.S. Damiani137,

H.O. Danielsson29, V. Dao49, G. Darbo50a, G.L. Darlea25b, W. Davey20, T. Davidek126, N. Davidson86,

R. Davidson71, E. Davies118,c, M. Davies93, A.R. Davison77, Y. Davygora58a, E. Dawe142, I. Dawson139,

R.K. Daya-Ishmukhametova22_{, K. De}7_{, R. de Asmundis}102a_{, S. De Castro}19a,19b_{, S. De Cecco}78_{, J. de Graat}98_,

N. De Groot104_{, P. de Jong}105_{, C. De La Taille}115_{, H. De la Torre}80_{, F. De Lorenzi}63_{, L. de Mora}71_{, L. De Nooij}105_,

D. De Pedis132a_{, A. De Salvo}132a_{, U. De Sanctis}164a,164c_{, A. De Santo}149_{, J.B. De Vivie De Regie}115_,

G. De Zorzi132a,132b_{, W.J. Dearnaley}71_{, R. Debbe}24_{, C. Debenedetti}45_{, B. Dechenaux}55_{, D.V. Dedovich}64_,

J. Degenhardt120_{, C. Del Papa}164a,164c_{, J. Del Peso}80_{, T. Del Prete}122a,122b_{, T. Delemontex}55_{, M. Deliyergiyev}74_,

A. Dell’Acqua29_{, L. Dell’Asta}21_{, M. Della Pietra}102a, j_{, D. della Volpe}102a,102b_{, M. Delmastro}4_{, P.A. Delsart}55_,

C. Deluca148_{, S. Demers}176_{, M. Demichev}64_{, B. Demirkoz}11,l_{, J. Deng}163_{, S.P. Denisov}128_{, D. Derendarz}38_,

J.E. Derkaoui135d_{, F. Derue}78_{, P. Dervan}73_{, K. Desch}20_{, E. Devetak}148_{, P.O. Deviveiros}105_{, A. Dewhurst}129_,

B. DeWilde148_{, S. Dhaliwal}158_{, R. Dhullipudi}24,m_{, A. Di Ciaccio}133a,133b_{, L. Di Ciaccio}4_{, A. Di Girolamo}29_,

B. Di Girolamo29_{, S. Di Luise}134a,134b_{, A. Di Mattia}173_{, B. Di Micco}29_{, R. Di Nardo}47_{, A. Di Simone}133a,133b_,

R. Di Sipio19a,19b, M.A. Diaz31a, F. Diblen18c, E.B. Diehl87, J. Dietrich41, T.A. Dietzsch58a, S. Diglio86,

K. Dindar Yagci39, J. Dingfelder20, C. Dionisi132a,132b, P. Dita25a, S. Dita25a, F. Dittus29, F. Djama83, T. Djobava51b,

M.A.B. do Vale23c, A. Do Valle Wemans124a,n, T.K.O. Doan4, M. Dobbs85, R. Dobinson29,∗, D. Dobos29,

E. Dobson29,o, J. Dodd34, C. Doglioni49, T. Doherty53, Y. Doi65,∗, J. Dolejsi126, I. Dolenc74, Z. Dolezal126,

B.A. Dolgoshein96,∗, T. Dohmae155, M. Donadelli23d, M. Donega120, J. Donini33, J. Dopke29, A. Doria102a,

A. Dos Anjos173, A. Dotti122a,122b, M.T. Dova70, A.D. Doxiadis105, A.T. Doyle53, M. Dris9, J. Dubbert99, S. Dube14,

E. Duchovni172_{, G. Duckeck}98_{, A. Dudarev}29_{, F. Dudziak}63_{, M. D¨uhrssen}29_{, I.P. Duerdoth}82_{, L. Duflot}115_,

M-A. Dufour85_{, M. Dunford}29_{, H. Duran Yildiz}3a_{, R. Duxfield}139_{, M. Dwuznik}37_{, F. Dydak}29_{, M. D¨uren}52_,

J. Ebke98_{, S. Eckweiler}81_{, K. Edmonds}81_{, C.A. Edwards}76_{, N.C. Edwards}53_{, W. Ehrenfeld}41_{, T. Eifert}143_{, G. Eigen}13_,

K. Einsweiler14_{, E. Eisenhandler}75_{, T. Ekelof}166_{, M. El Kacimi}135c_{, M. Ellert}166_{, S. Elles}4_{, F. Ellinghaus}81_{, K. Ellis}75_,

J. Erdmann54, A. Ereditato16, D. Eriksson146a, J. Ernst1, M. Ernst24, J. Ernwein136, D. Errede165, S. Errede165,

E. Ertel81, M. Escalier115, C. Escobar123, X. Espinal Curull11, B. Esposito47, F. Etienne83, A.I. Etienvre136,

E. Etzion153_{, D. Evangelakou}54_{, H. Evans}60_{, L. Fabbri}19a,19b_{, C. Fabre}29_{, R.M. Fakhrutdinov}128_{, S. Falciano}132a_,

Y. Fang173_{, M. Fanti}89a,89b_{, A. Farbin}7_{, A. Farilla}134a_{, J. Farley}148_{, T. Farooque}158_{, S. Farrell}163_{, S.M. Farrington}118_,

P. Farthouat29_{, P. Fassnacht}29_{, D. Fassouliotis}8_{, B. Fatholahzadeh}158_{, A. Favareto}89a,89b_{, L. Fayard}115_{, S. Fazio}36a,36b_,

R. Febbraro33_{, P. Federic}144a_{, O.L. Fedin}121_{, W. Fedorko}88_{, M. Fehling-Kaschek}48_{, L. Feligioni}83_{, D. Fellmann}5_,

C. Feng32d_{, E.J. Feng}30_{, A.B. Fenyuk}128_{, J. Ferencei}144b_{, W. Fernando}5_{, S. Ferrag}53_{, J. Ferrando}53_{, V. Ferrara}41_,

A. Ferrari166_{, P. Ferrari}105_{, R. Ferrari}119a_{, D.E. Ferreira de Lima}53_{, A. Ferrer}167_{, D. Ferrere}49_{, C. Ferretti}87_,

A. Ferretto Parodi50a,50b_{, M. Fiascaris}30_{, F. Fiedler}81_{, A. Filipˇciˇc}74_{, F. Filthaut}104_{, M. Fincke-Keeler}169_,

M.C.N. Fiolhais124a,h_{, L. Fiorini}167_{, A. Firan}39_{, G. Fischer}41_{, M.J. Fisher}109_{, M. Flechl}48_{, I. Fleck}141_{, J. Fleckner}81_,

P. Fleischmann174_{, S. Fleischmann}175_{, T. Flick}175_{, A. Floderus}79_{, L.R. Flores Castillo}173_{, M.J. Flowerdew}99_,

T. Fonseca Martin16_{, A. Formica}136_{, A. Forti}82_{, D. Fortin}159a_{, D. Fournier}115_{, H. Fox}71_{, P. Francavilla}11_,

S. Franchino119a,119b, D. Francis29, T. Frank172, M. Franklin57, S. Franz29, M. Fraternali119a,119b, S. Fratina120,

S.T. French27, C. Friedrich41, F. Friedrich43, R. Froeschl29, D. Froidevaux29, J.A. Frost27, C. Fukunaga156,

E. Fullana Torregrosa29, B.G. Fulsom143, J. Fuster167, C. Gabaldon29, O. Gabizon172, T. Gadfort24, S. Gadomski49,

G. Gagliardi50a,50b_{, P. Gagnon}60_{, C. Galea}98_{, E.J. Gallas}118_{, V. Gallo}16_{, B.J. Gallop}129_{, P. Gallus}125_{, K.K. Gan}109_,

Y.S. Gao143,e_{, A. Gaponenko}14_{, F. Garberson}176_{, M. Garcia-Sciveres}14_{, C. Garc´ıa}167_{, J.E. Garc´ıa Navarro}167_,

R.W. Gardner30_{, N. Garelli}29_{, H. Garitaonandia}105_{, V. Garonne}29_{, J. Garvey}17_{, C. Gatti}47_{, G. Gaudio}119a_{, B. Gaur}141_,

L. Gauthier136_{, P. Gauzzi}132a,132b_{, I.L. Gavrilenko}94_{, C. Gay}168_{, G. Gaycken}20_{, E.N. Gazis}9_{, P. Ge}32d_{, Z. Gecse}168_,

C.N.P. Gee129_{, D.A.A. Geerts}105_{, Ch. Geich-Gimbel}20_{, K. Gellerstedt}146a,146b_{, C. Gemme}50a_{, A. Gemmell}53_,

M.H. Genest55_{, S. Gentile}132a,132b_{, M. George}54_{, S. George}76_{, P. Gerlach}175_{, A. Gershon}153_{, C. Geweniger}58a_,

H. Ghazlane135b_{, N. Ghodbane}33_{, B. Giacobbe}19a_{, S. Giagu}132a,132b_{, V. Giakoumopoulou}8_{, V. Giangiobbe}11_,

F. Gianotti29_{, B. Gibbard}24_{, A. Gibson}158_{, S.M. Gibson}29_{, D. Gillberg}28_{, A.R. Gillman}129_{, D.M. Gingrich}2,d_,

J. Ginzburg153_{, N. Giokaris}8_{, M.P. Giordani}164c_{, R. Giordano}102a,102b_{, F.M. Giorgi}15_{, P. Giovannini}99_{, P.F. Giraud}136_,

D. Giugni89a_{, M. Giunta}93_{, P. Giusti}19a_{, B.K. Gjelsten}117_{, L.K. Gladilin}97_{, C. Glasman}80_{, J. Glatzer}48_{, A. Glazov}41_,

K.W. Glitza175, G.L. Glonti64, J.R. Goddard75, J. Godfrey142, J. Godlewski29, M. Goebel41, T. G¨opfert43,

C. Goeringer81, C. G¨ossling42, T. G¨ottfert99, S. Goldfarb87, T. Golling176, A. Gomes124a,b, L.S. Gomez Fajardo41,

R. Gonc¸alo76, J. Goncalves Pinto Firmino Da Costa41, L. Gonella20, S. Gonzalez173, S. Gonz´alez de la Hoz167,

G. Gonzalez Parra11, M.L. Gonzalez Silva26, S. Gonzalez-Sevilla49, J.J. Goodson148, L. Goossens29,

P.A. Gorbounov95, H.A. Gordon24, I. Gorelov103, G. Gorfine175, B. Gorini29, E. Gorini72a,72b, A. Goriˇsek74,

E. Gornicki38, B. Gosdzik41, A.T. Goshaw5, M. Gosselink105, M.I. Gostkin64, I. Gough Eschrich163, M. Gouighri135a,

D. Goujdami135c_{, M.P. Goulette}49_{, A.G. Goussiou}138_{, C. Goy}4_{, S. Gozpinar}22_{, I. Grabowska-Bold}37_{, P. Grafstr¨om}29_,

K-J. Grahn41_{, F. Grancagnolo}72a_{, S. Grancagnolo}15_{, V. Grassi}148_{, V. Gratchev}121_{, N. Grau}34_{, H.M. Gray}29_,

J.A. Gray148_{, E. Graziani}134a_{, O.G. Grebenyuk}121_{, T. Greenshaw}73_{, Z.D. Greenwood}24,m_{, K. Gregersen}35_,

I.M. Gregor41_{, P. Grenier}143_{, J. Griffiths}138_{, N. Grigalashvili}64_{, A.A. Grillo}137_{, S. Grinstein}11_{, Y.V. Grishkevich}97_,

J.-F. Grivaz115_{, E. Gross}172_{, J. Grosse-Knetter}54_{, J. Groth-Jensen}172_{, K. Grybel}141_{, D. Guest}176_{, C. Guicheney}33_,

A. Guida72a,72b_{, S. Guindon}54_{, H. Guler}85,p_{, J. Gunther}125_{, B. Guo}158_{, J. Guo}34_{, V.N. Gushchin}128_{, P. Gutierrez}111_,

N. Guttman153_{, O. Gutzwiller}173_{, C. Guyot}136_{, C. Gwenlan}118_{, C.B. Gwilliam}73_{, A. Haas}143_{, S. Haas}29_{, C. Haber}14_,

H.K. Hadavand39_{, D.R. Hadley}17_{, P. Haefner}99_{, F. Hahn}29_{, S. Haider}29_{, Z. Hajduk}38_{, H. Hakobyan}177_{, D. Hall}118_,

J. Haller54_{, K. Hamacher}175_{, P. Hamal}113_{, M. Hamer}54_{, A. Hamilton}145b,q_{, S. Hamilton}161_{, L. Han}32b_{, K. Hanagaki}116_,

K. Hanawa160_{, M. Hance}14_{, C. Handel}81_{, P. Hanke}58a_{, J.R. Hansen}35_{, J.B. Hansen}35_{, J.D. Hansen}35_{, P.H. Hansen}35_,

P. Hansson143, K. Hara160, G.A. Hare137, T. Harenberg175, S. Harkusha90, D. Harper87, R.D. Harrington45,

O.M. Harris138, K. Harrison17, J. Hartert48, F. Hartjes105, T. Haruyama65, A. Harvey56, S. Hasegawa101,

Y. Hasegawa140, S. Hassani136, S. Haug16, M. Hauschild29, R. Hauser88, M. Havranek20, C.M. Hawkes17,

R.J. Hawkings29, A.D. Hawkins79, D. Hawkins163, T. Hayakawa66, T. Hayashi160, D. Hayden76, H.S. Hayward73,

S.J. Haywood129, M. He32d, S.J. Head17, V. Hedberg79, L. Heelan7, S. Heim88, B. Heinemann14, S. Heisterkamp35,

L. Helary4, C. Heller98, M. Heller29, S. Hellman146a,146b, D. Hellmich20, C. Helsens11, R.C.W. Henderson71,

M. Henke58a_{, A. Henrichs}54_{, A.M. Henriques Correia}29_{, S. Henrot-Versille}115_{, F. Henry-Couannier}83_{, C. Hensel}54_,

T. Henß175_{, C.M. Hernandez}7_{, Y. Hern´andez Jim´enez}167_{, R. Herrberg}15_{, G. Herten}48_{, R. Hertenberger}98_{, L. Hervas}29_,

G.G. Hesketh77_{, N.P. Hessey}105_{, E. Hig ´on-Rodriguez}167_{, J.C. Hill}27_{, K.H. Hiller}41_{, S. Hillert}20_{, S.J. Hillier}17_,

I. Hinchliffe14_{, E. Hines}120_{, M. Hirose}116_{, F. Hirsch}42_{, D. Hirschbuehl}175_{, J. Hobbs}148_{, N. Hod}153_,