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2016 New J. Phys. 18 093016

(http://iopscience.iop.org/1367-2630/18/9/093016)

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New J. Phys. 18 (2016) 093016 doi:10.1088/1367-2630/18/9/093016

PAPER

Search for scalar leptoquarks in pp collisions atffiffiffi

sp

=13TeV withthe ATLAS experiment

TheATLASCollaboration

Keywords: leptoquark, ATLAS, LHC

AbstractAn inclusive search for a new-physics signature of lepton-jet resonances has been performed by theATLAS experiment. Scalar leptoquarks, pair-produced in pp collisions at s =13 TeV at the largehadron collider, have been considered. An integrated luminosity of 3.2 f b−1, corresponding to the full2015 dataset was used. First (second) generation leptoquarks were sought in events with two electrons(muons) and two ormore jets. The observed event yield in each channel is consistent with StandardModel background expectations. The observed (expected) lower limits on the leptoquarkmass at 95%confidence level are 1100 and 1050 GeV (1160 and 1040 GeV) for first and second generationleptoquarks, respectively, assuming a branching ratio into a charged lepton and a quark of 100%.Upper limits on the aforementioned branching ratio are also given as a function of leptoquarkmass.Comparedwith the results of earlier ATLAS searches, the sensitivity is increased for leptoquarkmassesabove 860 GeV, and the observed exclusion limits confirm and extend the published results.

Contents

1. Introduction 1

2. TheATLAS detector 3

3. Signal and background simulations 3

4. Physics object definition 4

5. Dataset and event selection 5

6. Analysis strategy: signal, control and validation regions 5

7. Background estimation 6

8. Sources of systematic uncertainties 7

9. Results 9

10. Summary and conclusions 11

1. Introduction

The large hadron collider (LHC)Run 2 has provided the possibility to study pp collisions at 13 TeV centre-of-mass energy for thefirst time, and has thus opened a new discoverywindow for physics beyond the standardmodel (SM). The presented analysis is an inclusive search for newphysics phenomena resulting infinal statesignatures of lepton-jet resonances in the first 3.2 f b−1 of 13 TeV data collected by theATLAS detector. Suchphenomenamay not have been kinematically accessible at the lower Run 1 centre-of-mass energy of 8 TeV. As abenchmark signalmodel, scalar leptoquarks decaying to jets and leptonswere used.

OPEN ACCESS

RECEIVED

20May 2016

REVISED

15 July 2016

ACCEPTED FOR PUBLICATION

2August 2016

PUBLISHED

7 September 2016

Original content from thisworkmay be used underthe terms of the CreativeCommonsAttribution 3.0licence.

Any further distribution ofthis workmustmaintainattribution to theauthor(s) and the title ofthework, journal citationandDOI. Article fundedby SCOAP3.

© 2016CERN for the benefit of the ATLASCollaboration

Leptoquarks (LQs) feature in a number of theories [1–7]which extend the SM, such as grand unified theoriesandmodels with quark and lepton substructure. LQs possess non-zero baryon and lepton numbers and theirexistencewould provide a connection between quarks and leptons. This could help explain the observedsimilarity of the quark and lepton sectors in the SM. LQs carry a colour-triplet charge and a fractional electriccharge [8]. They can be scalar or vector bosons and they decay directly to lepton–quark pairs. The analysispresented in this paper focuses on the pair production of scalar leptoquarks.

A single Yukawa coupling ( ℓl ) governs the interaction strength between a scalar LQ and a given quark (q)and lepton (ℓ) pair. A Feynman diagram showing a LQdecay is shown infigure 1. The couplings are determinedby two free parameters of themodel: the branching ratio into charged leptons, β, and the coupling parameter,λ.The coupling to a charged lepton and a quark is given by ℓl bl= , the coupling to a neutrino and a quark by

l bl= -n 1 . The pair-production cross section of leptoquarks in pp collisions is largely insensitive to thecoupling values, since the basic processes of LQpair-production are gluon fusion and quark–antiquarkannihilation. Example LOdiagrams are shown infigure 2. At a centre-of-mass energy of =s 13TeV, gluonfusion is the dominant process. For LQmasses (mLQ) up to a few hundredGeV, it contributes up to 95%of thetotal cross section. AbovemLQ = 1.5 TeV, the contribution fromquark–antiquark annihilation amounts toabout 30% [9]. Therefore, the parameter of interest— apart from the LQmass— is the branching ratioβ.

The signal benchmarkmodel for LQproduction used in this analysis is theminimal Buchmüller–Rückl–Wylermodel (mBRW) [10]. In this approach a number of constraints are imposed on the LQproperties. Leptonnumber and baryon number are separately conserved to prevent fast proton decay. The LQ couplings are alsoconsidered to be purely chiral. Furthermore, it is assumed that LQs belong to three generations (first, second andthird)which interact only with lepton–quark pairs within the same generation.With this assumption, lepton-flavour violation is suppressed.However, in amore generic picture of leptoquarks, a LQmay couple to a quarkand a lepton belonging to different generations [11]. Although the results of this searchwere not explicitlyinterpreted in this type ofmodel, the event selections usedwere designed to retain sensitivity to leptoquarkmodels inwhich decays into first or second generation leptons and bottom-quarks (b) are possible.

Previous searches for pair-produced LQshave been performedby theATLAS andCMScollaborations [12–24] at s =7 and 8 TeV. The existence of scalar LQswithmasses up to 1050 and 1000 GeV (for b = 1) forfirst-

Figure 1. Feynman diagram showing the Yukawa coupling ℓl bl= between a leptoquark, a lepton (ℓ) and a quark (q).

Figure 2.Dominant leading-order Feynman diagrams for the pair production of scalar leptoquarks fromgluon fusion andquark–antiquark annihilation.

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New J. Phys. 18 (2016) 093016 MAaboud et al

and second-generation scalar LQs, respectively, is excluded at 95%confidence level (CL) byATLAS [20] in a studyperformed at s=8 TeVusing 20 f b−1 of integrated luminosity. TheCMSexperiment similarly excludedfirst-and second-generation scalar leptoquarks up tomasses of 1010 GeVand 1080 GeV (for b = 1), respectively [21].

In this paper, searches for the pair-production of leptoquarks of the first (LQ1) and second (LQ2)generations, based on events containing exactly two electrons ormuons and at least two jets (denoted by eejj andmmjj , respectively), are reported. In order to keep the search as inclusive as possible, it was not required that thecharges of the two leptons in an eventmust be opposite. Similarly, no selections on the jetflavourwereintroduced so as not to exclude possible ebLQ and m bLQ decays.

2. TheATLAS detector

TheATLAS experiment [25] is amulti-purpose detector with a forward-backward symmetric cylindricalgeometry and nearly 4π coverage in solid angle225. The threemajor sub-components of ATLAS are the trackingdetector, the calorimeter and themuon spectrometer (MS). Charged-particle tracks and vertices arereconstructed by the inner detector (ID) tracking system, comprising silicon pixel (including the newly installedinnermost pixel layer), andmicrostrip detectors covering the pseudorapidity range ∣ ∣h <2.5, and a straw tubetracker that covers ∣ ∣h <2.0. The ID is immersed in a homogeneous 2 Tmagnetic field provided by a solenoid.Electron, photon, jet and τ lepton energies aremeasuredwith sampling calorimeters. TheATLAS calorimetersystem covers a pseudorapidity range of ∣ ∣h <4.9.Within the region ∣ ∣h <3.2, electromagnetic calorimetry isprovided by barrel and endcap high-granularity lead/liquid argon (LAr) calorimeters, with an additional thinLAr presampler covering ∣ ∣h <1.8, to correct for energy loss inmaterial upstreamof the calorimeters. Hadroniccalorimetry is provided by a steel/scintillator-tile calorimeter, segmented into three barrel structures within∣ ∣h <1.7, and two copper/LAr hadronic endcap calorimeters. The forward region (3.1< ∣ ∣h <4.9) isinstrumented by a LAr calorimeter with copper (electromagnetic) and tungsten (hadronic) absorbers.Surrounding the calorimeters is aMSwith superconducting air-core toroids, providing bending powers of 3 Tmin the barrel and 6 Tm in the endcaps. TheMS includes a systemof precision tracking chambers providingcoverage over ∣ ∣h <2.7. Three stations of precision tracking chambers are used tomeasure the curvature oftracks. TheMS also contains detectors with triggering capabilities over ∣ ∣h <2.4 to provide fastmuonidentification andmomentummeasurements.

TheATLAS two-level trigger system is used to select events considered in this paper. Thefirst-level trigger ishardware-basedwhile the second, high-level trigger is implemented in software and employs algorithms similarto those used offline in the full event reconstruction.

3. Signal and background simulations

The PYTHIA 8.160 [26]MonteCarlo (MC)model, based on leading-order (LO)matrix-element calculationssupplementedwith parton showers, was usedwith theATLASA14 [27] set of tuned parameters (tune) for theunderlying event, together with theNNPDF23LO [28] parton distribution functions (PDFs), to producesimulated samples of pair-produced first- and second-generation scalar LQs. Leptoquarks of the first (second)generation decay to ¯+ -e e uu ( ¯m m+ -cc )final states. Samples were produced for LQmasses in the range of500–1500 GeV. Aswas also done in the previous ATLAS publication [20], the value of the coupling parameterλwas set to pa´0.01 4 , whereα is thefine-structure constant. This value ofλ determines the leptoquarknatural width, which is less than 100MeV and is smaller than the detector resolution for the reconstruction ofleptoquarkmass. It also leads to a LQ lifetime sufficiently small such that LQs in themass range considered inthis workwould decay promptly. Next-to-leading-order (NLO) calculations [9] of the cross sections for scalarleptoquark pair-productionwere used to normalise the signal samples.

The dominant SMbackgrounds arise fromprocesses which can produce a final state containing tworeconstructed high transversemomentum (pT) leptons (electrons ormuons) and jets. Simulated samples weremade ofDrell–Yan production ( ℓ ℓ¯ *g + -qq Z ) and the production of ¯tt , diboson (WW,WZ, andZZ)and single top-quarks in associationwith aW boson.

Drell–Yan events with associated jets were simulated using the SHERPA 2.1.1 [29] generator.Matrix elementswere calculated for up to two partons atNLO and four partons at LOusing theCOMIX [30] andOPENLOOPS [31]matrix-element generators andmergedwith the SHERPA parton shower [32] using theME+PS@NLO

225ATLAS uses a right-handed coordinate systemwith its origin at the nominal interaction point (IP) in the centre of the detector and the

z-axis along the beampipe. The x-axis points from the IP to the centre of the LHC ring, and the y-axis points upward. Cylindrical coordinates( )fr, are used in the transverse plane,f being the azimuthal angle around the z-axis. The pseudorapidity is defined in terms of the polarangle θ as ( )h q= -ln tan 2 .

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New J. Phys. 18 (2016) 093016 MAaboud et al

prescription [33]. TheCT10 PDF set [34]was used in conjunctionwith dedicated parton-shower tuningdeveloped by the authors of SHERPA [32].

For the generation of ¯tt and single top quarks in theWt channel, the POWHEG-BOX v2 generator [35–38]with theCT10 PDF set in thematrix-element calculations was used. For both processes the parton shower,fragmentation, and the underlying eventwere simulated using PYTHIA 6.428 [39]with the PERUGIA 2012 tune[40] and using theCTEQ6L1 PDF set [41]. The top-quarkmasswas set to 172.5 GeV. The EVTGEN v1.2.0program [42]was used to simulate the bottom and charmhadron decays.

Diboson processes with four charged leptons, three charged leptons+ one neutrino or two charged leptonsand twoneutrinos were simulated using the SHERPA 2.1.1 generator.Matrix elements contain all diagramswithfour electroweak vertices. Theywere calculated for up to one ( ℓ4 , ℓ n+2 2 ) or zero partons ( ℓ n+3 1 ) atNLOand up to three partons at LOusing theCOMIX andOPENLOOPSmatrix element generators andmergedwith theSHERPA parton shower using theME+PS@NLOprescription. Diboson processes with one of the bosonsdecaying hadronically and the other leptonically were simulated using the same SHERPA version.

All samples of simulated events include the effect ofmultiple proton–proton interactions in the same orneighbouring bunch crossings (pile-up)whichweremodelled by overlaying simulatedminimum-bias events oneach generated signal and background event. Thesemultiple interactions were simulatedwith the soft QCDprocesses of PYTHIA 8.186 [26] using tuneA2 [43] and theMSTW2008LOPDF set [44]. The number of overlaidevents was chosen tomatch the average number of interactions per pp bunch crossing observed in the data as itevolved throughout the data-taking period (giving an average of 14 interactions per crossing for thewhole data-taking period). The SMbackground samples were processed through theGEANT4-based detector simulation[45, 46], while a fast simulation using a parameterisation of the performance of the calorimeters [47] andGEANT4 for the other parts of the detector was used for the signal samples and some samples used for studies ofsystematic uncertainties. The standardATLAS reconstruction software was used for both simulated andcollision data.

Estimates of the cross sections of background processes were taken from the following theoreticalpredictions. Single-top productionwas calculated atNLO+next-to-next-to-leading-logarithm (NNLL)accuracy [48]. Estimates of Drell–Yan and ¯tt production cross sections atNLO [29] andNLO+NNLO [49]accuracy, respectively, were used.

4. Physics object definition

The electron energy wasmeasured using its associated cluster of electromagnetic-calorimeter cells withsignificant energy deposits, whereas the directionwas determined by the track associatedwith this cluster. Toidentify and select electrons, requirements were placed on the shape of the cluster, on the quality of theassociated track, and on the degree ofmatching between the track and cluster. Electron candidatesmust havetransverse energy ET >30GeVand∣ ∣h < 2.47. Electron candidates associatedwith clusters in the transitionregion between the barrel and endcap calorimeters (1.37< ∣ ∣h <1.52)were not considered. All electronsmustbe reconstructedwith a cluster-based or a combined cluster- and track-based algorithm [50]. Furthermore, theimpact parameters of the electron track relative to the beam linewere required to satisfy ∣ ∣s <d 5d0 0

and∣ ∣q <z sin 0.5 mm0 , where d0, sd0

and z0 are the transverse impact parameter, its uncertainty, and thelongitudinal impact parameter, respectively. In addition, electron isolation requirements were imposed on thesummed transversemomentumof tracks (transverse energy of clusters) in a cone around the electron track(cluster barycentre). The radius of the cone around the track isD =R p10 GeV T for >p 50 GeVT and 0.2otherwise226. For the cluster isolation, afixed cone radius size of 0.2 is used. The efficiency of these isolationcriteria is higher than 99%.The reconstruction efficiency is higher than 98% inmost regions of transversemomentum and pseudorapidity. The identification efficiency varies between 75%and 92%, rising as a functionof ET [51]. All of these efficiencies refer to the efficiency for a single electron, independent of the specific eventtopology.

Muon tracks were reconstructed independently in the ID and theMS. Thesemuon trackswere required tohave aminimumnumber of associated hits in each system and to satisfy geometrical andmomentummatchingcriteria. The two tracks were then used as input to a combined fit which takes into account the energy loss in thecalorimeter andmultiple-scattering effects [52]. To improvemomentum resolution and ensure a reliablemeasurement at very highmomenta,muon tracks were required to have at least three hits in each of the threeprecision chambers in theMS. Tracks which traverse precision chambers with poor alignment were rejected.Finally,measurements of charge overmomentum, performed independently in the ID andMS, were required toagreewithin seven standard deviations of the sum in quadrature of the uncertainties in the corresponding ID

226Here, ( ) ( )h fD = D + DR 2 2 is a cone defined by differences in pseudorapidity and azimuthal angle. pT is given inGeV.

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New J. Phys. 18 (2016) 093016 MAaboud et al

andMSmeasurements.Muon candidates were required to have pT>40 GeV and ∣ ∣h <2.5. Those falling in theoverlap region of theMSbarrel and endcap ( ∣ ∣h< <1.01 1.10)were rejected due to the potentialpTmismeasurement resulting from relative barrel-endcapmisalignment.Muon candidates were required tofulfil ∣ ∣sd d0 0

<3 and ∣ ∣qz sin0 <0.5mm. In order to reduce the background from light- and heavy-hadrondecays within jets,muonswere required to fulfil isolation requirements. The track-based isolation variable usedis the sumof the transversemomenta of the tracks in a cone around themuon of sizeD =R 10 GeV/ mpT ,excluding themuon itself andwith mpT inGeV. The isolation efficiency is greater than 99%. The efficiency forreconstructing and identifyingmuons using the criteria described above is typically greater than 80% for thetransversemomentum and pseudorapidity selections used in this work [53]. As for electrons, these efficienciesrefer to single objects.

The anti-kt algorithm [54]with a radius parameterR=0.4was used to reconstruct jets fromenergy clusters inthe calorimeter [55]. Jet calibration is performedusing energy- and η-dependent correction factors derived fromsimulations togetherwith further corrections from in situmeasurements. The jets used in thisworkmust satisfypT>50 GeV and ∣ ∣h <2.8. Further selectionswere applied to ensure that all jets considered arewellmeasured [56].A description of the jet energy scale (JES)measurement and its associated systematic uncertainties can be found in[57]. Jet-flavour tagging techniqueswere not used in this paper and, as a consequence, good sensitivitywasmaintained for LQdecays into a lepton plus any quarkflavourbarring the topquark.

Ambiguities in the object identification during reconstruction, i.e. when a reconstructed objectmatchedmultiple object identification hypotheses (electron,muon, jet), were resolved in the followingway. First,electronswere removed if they shared their trackwith amuon. In a second step, ambiguities between electronsand jets were removed; if the two objects hadD <R 0.2 the jet was rejected; if < D <R0.2 0.4 the electronwasrejected. Finally,muon-jet ambiguities were resolved as follows: if themuon and jet were closer thanD =R 0.4the jet was rejected if it has less than three tracks, otherwise themuonwas rejected. For the definition of signaland control regions (see section 6) only objects remaining after this procedure were considered.

5.Dataset and event selection

Proton–proton collision data at a centre-of-mass energy of s=13 TeV, collected by theATLAS detector at theLHCduring 2015, were used. After applying data quality criteria, the dataset corresponds to an integratedluminosity of 3.2 f b−1.

Events considered in the searchwere selected by the ATLAS two-level trigger system [58]. In the eejj channel,a two-electron trigger was usedwith an ET threshold of 17GeV for each electron. The mmjj search used eventsselected by either of two single-muon triggers. Thefirst trigger has amuon pT threshold of 26 GeV andadditional requirements on its properties. In particular, it requires themuon to be isolated, which leads to a lossin efficiency at high pT. To retain a high trigger efficiency in the region of high pT, the second trigger, which has apT threshold of 50 GeVbut no additional requirements, was used. The trigger efficiencies for the eejj and mmjjsearches exceed 90% for the object kinematics considered in this analysis.

Multiplepp interactions during bunch crossings lead to events containing a number of reconstructed vertices.The primary vertex of the event is defined as that vertexwith the largest sumof squared transversemomenta of itsassociated tracks. Eventswhich contain a primary vertexwith at least twoassociated tracks satisfying

>pT,track 0.4 GeVwere selected. Furthermore,MCeventswere given a per-eventweight to correct for differencesin the distributionof the averagenumber ofpp interactions per bunch crossing betweendata and simulation.

Only events with exactly two charged leptons and at least two jets were considered for this analysis. Scalefactors were applied as event weights to correct theMCdescription of lepton trigger, reconstruction,identification, isolation and impact-parameter cut efficiencies. A description of the derivation of the scalefactors, obtained by comparing data andMCpredictions in dedicated studies, can be found in [50, 59].

6. Analysis strategy: signal, control and validation regions

The analysis presented here used signal (SR), control (CR) and validation (VR) regions to optimise signalsignificance and to constrain the normalisation of themain background sources. The latter areDrell–Yan eventscontaining *g m m + - + -Z e e , +jets processes (hereafter termedDY+jets) and ¯tt events inwhich both topquarks decay leptonically. The signal, control and validation regionswere defined using the followingdiscriminating observables:

• The dilepton invariantmass: ℓℓm .

• The scalar sum ST of the transversemomentumof the two leptons and of the two leading jets.

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New J. Phys. 18 (2016) 093016 MAaboud et al

• Theminimum invariantmass of the two lepton–jet pairs in an event, mLQmin . The lepton–jet pairs were chosen

such that the invariantmass difference between themwas smallest. The lowermass of the two combinationswas chosen as the discriminating variable following dedicated sensitivity studies.

The signal regionwas defined by requiring ℓℓ >m 130 GeV and ST>600 GeV. The cut on ℓℓm was chosento reduce theDY+jets background. The cut on ST was optimised bymaximising the discovery significance [60]for LQswithmasses between 500 and 1500 GeV, i.e. by performing a likelihood fit (described inmore detail atthe end of this section)using the mLQ

min distribution defined above for ST values between 0 and 3 TeV in steps of100 GeV. This study showed that there is little dependence of the optimised ST value on the LQmasswhen usingthe shape information of themass spectrum. It was confirmed that the approach used in previous results, i.e. acut-and-count analysis in several signal regions defined by varying cuts on the three variablesmentioned above,does not give better sensitivity.

The signal selection efficiency is defined as the fraction of all simulated signal events, generated across the fullphase space, that survive the trigger and the final SR selection. For leptoquarks of the first (second) generation,the overall selection efficiency rises from around 62% to 71% (38% to 43%) as themass increases from500 to1500 GeV. The lower efficiency for second-generation leptoquarks is due to themuon track requirements,which demand hits in threeMS stations, andwhich are needed to give an optimalmomentum resolution at highpT for this analysis.

Three non-overlapping control regionswithnegligible signal contaminationwere defined.Differences in thepredicted andobserved event yields in these regionswere used to evaluate scale factorswhichwere used tonormalise theMCpredictions for the ¯tt andDY+jets backgrounds in the SRs. The twoDY+jetsCRs— one for theeejj andone for the mmjj channel—were definedby requiring at least two jets and exactly two same-flavour leptonswith a dilepton invariantmass restricted to awindowaround theZbosonmass: ℓℓ< <m70 110 GeV. The ¯ttcontrol region requires at least two jets, exactly onemuon andexactly one electron: these eventswere selectedwiththe same single-muon triggers as described in section 5. This control region is common toboth channels.

Validation regionswere used to verify that data andMCpredictions agree in a phase space close to the signalregions, but still with a negligible signal contamination. This was achieved by applying the same selection as forthe signal region, but inverting the cut on ST, i.e. allowing only values below 600 GeV. The requirements for thevarious regions are collected in table 1.

For the statistical analysis, a profile-likelihood fit of signal plus background templates to the data wasperformed using theHistFitter package [61]. Systematic uncertainties, which are discussed in section 8, wereincorporated into the likelihood as constrained nuisance parameters. Thefit was performed in theCRs and theSR simultaneously andwas used to extract normalisation factors, i.e. scaling corrections to the event yieldspredicted by theoretical cross-section calculations, described in section 3. In theCRs, only the event yieldwasused to extract the dominant background ( ¯tt andDY+jets)normalisation factors. In the SR, both thenormalisation and the shape of mLQ

min distributionwere used in the fit to extract the signal normalisation factor.

The templates of the mLQmin shape consisted of ten bins: six bins of 100 GeVwidth from0 to 600 GeV and four

bins of 200 GeVwidth that cover the range up to 1.4 TeV. The template for the signal was derived fromMCpredictions. For the background templates,MCpredictions aswell as data-driven techniques were used, asdetailed in the following section.

7. Background estimation

Normalisation factors for theMCpredictions of the twomain SMbackgrounds (DY+jets and ¯tt )were estimatedwith afit to the data, as described in section 6. In total, four normalisation factors were calculated: one each for ¯ttandDY+jets events in both the electron andmuon channels.

Table 1.Definition of control, signal and validation regions. In all regions, at leasttwo jets were required.

Region Channel #e #μ ℓℓm (GeV) ST (GeV)

¯tt CR Both 1 1 — —

DY+jets CR eejj 2 0 [ ]70, 110 —

mmjj 0 2

SR eejj 2 0 >130 >600

mmjj 0 2

VR eejj 2 0 >130 <600

mmjj 0 2

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New J. Phys. 18 (2016) 093016 MAaboud et al

Smaller background contributions arise from the production of a single top quark in theWt channel,diboson events and ttZ +jets events. Thesewere estimated purely from simulation, i.e. their normalisationwas not a free parameter in the combined fit.

Misidentified or non-prompt leptons originating fromhadron decays or photon conversions can arise inmulti-jet events, single top production in the s- or t-channel,W+jets and ¯tt events (with at least one top quarkdecaying hadronically). This fake-lepton background is negligible in the mmjjchannel. In the eejjchannel it wasevaluated using the same data-drivenmethod as in [62]. Thismethodwas used to evaluate themigration ofevents among four different data samples: the nominal SR and three analogous samples selectedwithmodifiedelectron selection criteria. Themigration between different regions can be described by amatrix, the elements ofwhich are functions of the proportions of true and fake electrons. As a simplification of [62], the fake and realrates were evaluated as a function of pT only, since theywere observed to be independent of ηwithin the requiredaccuracy. Theywere considered to be the same for all electron candidates in an event. The fake backgroundestimation suffers from low statistical precision. Its statistical uncertainty was treated as one source of thesystematic uncertainty in the total backgroundmodelling.

Figure 3 shows the dilepton invariantmass for pairs of electrons (a) andmuons (b) in events containingexactly two reconstructed same-flavour leptons and at least two reconstructed jets, following the selections givenin section 5. This selection stage is also referred to as preselection. The predictions of various backgroundsources are comparedwith the data. The hatched bands show the total systematic uncertainty in the backgroundprediction.Within the uncertainties, agreement between data and simulation is observed. Normalisation factorsfor theMCpredictions forDY+jets and ¯tt events are not applied in the plot.

Figure 4 shows the spectrumof theminimum reconstructed lepton–jetmass in the ¯tt control region beforethefit.Within uncertainties, the data andMCdistributions are consistent.

8. Sources of systematic uncertainties

The following sources of systematic uncertainty were considered:

• The uncertainty in the integrated luminosity is 5%. It was derived following amethodology similar to thatdetailed in [63], from a calibration of the luminosity scale using x–y beam-separation scans performed inAugust 2015. This uncertainty affects the predicted signal event yield and those background rates for whichtheoretical estimates are used.

• The JES uncertainty depends on the pTand η of the jet and on the pile-up conditions in an event. A furtheruncertainty in the jet energy resolutionwas taken into account. These sources each correspond touncertainties in the jet energy of up to 3%. The largest resulting uncertainty in the background event yields is

Figure 3.Dilepton invariantmass for pairs of (a) electrons and (b)muons in events containing exactly two reconstructed same-flavourleptons and at least two reconstructed jets. Data are compared to the background prediction. TheDY+jets and ¯tt expectations areshownwithout the normalisation factors from thefit described in section 6. The hatched bands show the total systematic uncertaintyin the background prediction.

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New J. Phys. 18 (2016) 093016 MAaboud et al

about 10% in the control regions. In the signal region, the uncertainty in the event yields amounts to atmost5% for the background and less than 1% for the signal.

• The uncertainty in the lepton trigger efficiency scale factors is around 2% for the kinematic regionconsidered here.

• Differences between theMCand data in the efficiency of the isolation requirement on the selectedmuonscorrespond to uncertainties of 1%–5%on the scale factor to correct theMCprediction. Othermuon-relateduncertainties arise from themomentum scale, resolution, and quality criteria and typically affect themuonevent yields by around 1% in all regions for both signal and background.

• Uncertainties in the electron energy scale, identification and isolation affect the electron event yields by up to2% in all regions for both signal and background.

• Uncertainties due to choices that have to bemade in the event generationwhich affectfinal-state observableswere estimated for the twomajor background sources: ¯tt andDY+jets. Thesemodelling uncertainties refer toe.g. possible differences in the generation of the hard scattering, scale dependencies, the parton shower andhadronisation and fragmentationmodels. Differences in the backgroundmodelling can change the eventyields (total normalisation) in theCRs.Moreover, there is an uncertainty in the shape of the mLQ

min distribution

in the signal region due to backgroundmodelling effects. This was estimated as one uncertainty per mLQmin -bin

in the signal region and propagated to the normalisation factor by thefit. The uncertainties were treated asuncorrelated between different bins.The impact ofmodelling uncertainties infinal-state predictions for ¯tt processes was quantified by comparingvarious simulated samples: differences due to the parton shower aswell as the hadronisation andfragmentationmodel were estimated by comparing the nominal sample to one that usesHERWIG++ [64],effects of additional or reduced radiationwere estimated by varying the parton-shower and scale parameterswithin PYTHIA, and an alternative generator (AMC@NLO [65]withHERWIG++)was used to estimatedifferences in the hard scatter generation. The total uncertainty in the predicted ¯tt event yield varies between14% (in the ¯tt CR) to about 30% (in the signal regions).Modelling uncertainties for theDY+jets backgroundwere assessedwith different approaches, simulation-based, as well as data-driven in different regions of phase space. The baseline estimate used events from theDY+jets control regionwith ST higher than 600 GeV. In this region, the shapes of both the mLQ

min and ST

distributions are very similar to those in the signal region, which differs only by the cut on the dileptoninvariantmass. This cutwas found to not affect the shapes of the other discriminating variables. The differencebetween the data and the background prediction in this regionwas used as an estimate of themodellinguncertainty.The result was cross-checked using simulated samples inwhich the renormalisation, factorisation andresummation scales, as well as the scale formatrix element and parton showermatching, were independentlyvaried up and downby a factor of two.Within the statistical uncertainties resulting from the limited number

Figure 4.Minimum reconstructed lepton–jet invariantmass in the ¯tt control region.Data are compared to the backgroundprediction. The ¯tt prediction is shownwithout the normalisation factor from thefit described in section 6. The hatched bands showthe total systematic uncertainty in the background prediction.

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of events in these samples, the estimate from the data-driven approachwas confirmed. The result is a 10%uncertainty in theDY+jets event yield in the control regions and 20% in each mLQ

min bin in the signal region.

• PDFuncertainties on the ¯tt andDY+jets normalisation as well as the mLQmin shape amount to less than 4%and

do not affect the final result given the largemodelling uncertainties described above.

• The effects of higher-order contributions on the signal cross sectionwere estimated by varying theQCDrenormalisation and factorisation scales, set to a common value, up and down by a factor of two, as done in[9]. One half of the difference between the predicted cross section for the increased and reduced scale choice isused as the cross section uncertainty for a givenmass. This uncertainty lies in the the range 12%–17% for themass points considered in this paper.

• The impact of theoretical uncertainties related to the parton-shower algorithm andmultiple-interactions tunewere evaluated by varying the corresponding parameters, as specified in [66]. This leads to an uncertainty insignal acceptance of up to 2%.

• The uncertainty in the signal cross section due to the choice of PDF set was calculated as the envelope of thepredictions of 40 different CTEQ6.6NLOerror sets [9]. The uncertainty ranges from11%at mLQ=500 GeVto 34%at mLQ=1500 GeV. The predicted signal acceptancewas studied usingNNPDF23LO [28], CT14 [67]andMMHT14 [68]PDF sets. The acceptance is very insensitive to the choice of parton distribution function;the systematic uncertainty from this source is less than 1%.

9. Results

The results are consistent with SMexpectations. The normalisation factors obtained in the fit described insection 6 are summarised in table 2. Similar results are obtained in the two channels and the normalisationfactors are found to be compatible with unity within the uncertainties. The reliability of extrapolating thebackground predictions from the control regions to the signal regionwas checked in theVRs defined insection 6. The distribution of mLQ

min in the two validation regions is compared to the background prediction afterthefit infigure 5.Within the uncertainties, the predictions are compatible with the observed data.

Table 2.Normalisation factors for themain backgrounds obtained from thecombined fit in each of the channels.

Channel DY+jets ¯tt

eejj 0.9±0.1 1.0±0.1mmjj 0.9±0.1 -

+1.0 0.10.2

Figure 5.Minimum reconstructed lepton–jet invariantmass in the validation regions for pairs of (a) electrons and (b)muons. Data arecompared to the background prediction. TheDY+jets and ¯tt expectations are scaled by the normalisation factors obtained from thefit described in section 6. The hatched bands show the total systematic uncertainty in the background prediction.

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The observed and expected event yields in the signal regions for the eejj and the mmjj channels, after the fits,are shown in tables 3 and 4, respectively. The values in these tables are intended to illustrate the sensitivityindependent of a specific signal hypothesis and thus, in this case, the fit was performed using only the controlregions as input. The resulting fit parameters (DY+jets and ¯tt normalisation factors and values of the nuisanceparameters)were transferred to the signal region, using appropriate transfer factors based on theMCmodels.The different contributions to the background do not necessarily exactly sum to the total quoted number ofbackground events owing to the rounding scheme used. The dominant experimental systematic uncertainties inthe background prediction arise fromuncertainties on corrections to the simulated electron andmuon triggerefficiencies and the JES; the latter source gives an uncertainty of 2%–4% in the signal region. The luminosityuncertainty of 5% contributes for simulated backgrounds not constrained by the fit (diboson and single-topproduction). The theoretical uncertainties after the fit range from3% to 12% for theDY+jets background andfrom3% to 16% for the ¯tt background. The globalfit takes correlations of the nuisance parameters into account,which results in the uncertainty in the total background being smaller than the quadratic sumof theuncertainties in the separate components. The contribution of tt +Z jets to the background is negligibleand not shown in the tables.

Figure 6 shows the SR distribution of mLQmin compared to background predictions based on the combined fit

in theCRs and the SR. The signal prediction for a LQofmass 1.1 TeV is also shown. Thewider signal shape in themuon channel compared to the electron channel is due theworsening of themuonmomentum resolutionwithincreasingmomentum. Again, no significant deviation from the SMpredictionswas observed. Limits on the LQ

Table 3.Observed and predicted event yields in the signal and control regions in the eejj channel.The background predictionwith its total uncertainty after thefit is shown. The fit is performedusing only the control regions as input. The lower part of the table shows the separate contribu-tions from the different background processes and their total uncertainty after the fit. In addition,the expected signal event yields for b = 1 and LQmasses of 500, 1000, and 1500 GeV are given.

SR CRDY+jets CR ¯tt

Observed events 279 20328 5194

Total background events 300±30 20300±200 5200±50

FittedDY+jets events 74±7 19100±200 <0.01

Fitted ¯tt events 190±30 1060±10 4840±40MCpredicted diboson events 12.5±0.6 63±3 115±6MCpredicted single-top events 20±1 42±2 230±10Estimated fake-lepton events 9±4 120±10 6±3

MCexp. signal events (mLQ=500 GeV) 1000±100 26±4 <0.01

MCexp. signal events (mLQ=1000 GeV) 13±2 0.03±0.00 <0.01

MCexp. signal events (mLQ=1500 GeV) 0.6±0.1 <0.01 <0.01

Table 4.Observed and predicted event yields in the signal and control regions in the mmjj channel.The background predictionwith its total uncertainty after thefit is shown. The fit is performedusing only the control regions as input. The lower part of the table shows the separate contribu-tions from the different background processes and their total uncertainty after the fit.Where nonumber is given, the contribution is found to be negligible. In addition, the expected signal eventyields for b = 1 and LQmasses of 500, 1000, and 1500 GeV are given.

SR CRDY+jets CR ¯tt

Observed events 188 10233 5194

Fitted background events 200±30 10200±100 5200±70

FittedDY+jets events 56±8 9800±100 9±1Fitted ¯tt events 120±30 400±20 4840±80MCpredicted diboson events 8.6±0.6 32±3 115±10MCpredicted single-top events 12.8±0.9 18±2 230±20Estimated fake-lepton events — — —

MCexp. signal events (mLQ=500 GeV) 610±40 25±2 3±3MCexp. signal events (mLQ=1000 GeV) 8.0±0.8 0.08±0.01 0.1±0.1MCexp. signal events (mLQ=1500 GeV) 0.33±0.06 <0.01 <0.01

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signal strengthwere derived using pseudo-experiments and following amodified frequentist CLs method [69].Apart from the luminosity uncertainty (5%), dominant uncertainties in the signal event yields arise from leptonscale factors and are of the order of 2%–5%at lowmasses and up to 10%at highmasses.

Infigure 7, limits on the cross section times branching ratio are shown on the left, for leptoquarks of thefirst(second) generation in the top (bottom)plot. The expected limit is depicted by the dashed line; the uncertaintybands result from considering all sources of systematic aswell as statistical uncertainties. The observed limit isgiven by the solid line. TheNLOpair-production cross section for b = 1 is shown as a linewith a shaded bandrepresenting the uncertainties. The shaded band around it illustrates the uncertainties in the theoreticalprediction due to PDF and scale uncertainties. The intersection of this linewith the cross-section limits yields thelower limit on the leptoquarkmass for a value of b = 1. These observed (expected) limits are found to be 1100(1160 GeV) and 1050 GeV (1040 GeV) forfirst- and second-generation LQs, respectively. The observed limit foreach channel is stronger than the previous bound [20] by 50 GeV. The expected limits are improved by 110 GeVfor thefirst-generation search and by 40 GeV in the second generation search. The theoretical cross sectionwasscaled by b2 and then used to obtain the limits on the branching ratio as a function of the LQmass shown on theright offigure 7. BelowLQmasses of 650 GeV, the limits onβ are weaker than those obtained at 8 TeV centre-of-mass energy, which are shown as the dashed–dotted line, owing to themuch lower integrated luminositycollected in 2015 and the effects of background at lower LQmasses. At highmasses (above 900GeV), however,the gain in the production cross section at 13 TeV compensates for the smaller luminosity and stronger boundsthan at 8 TeV are obtained. In the intermediatemass region, the results are comparable.Mass limits for variousvalues ofβ are summarised in table 5.

10. Summary and conclusions

Searches forfirst- and second-generation scalar leptoquarks, pair-produced in pp collisions at 13 TeV centre-of-mass energy, have been performedwith the ATLAS detector at the LHC.An integrated luminosity of 3.2f b−1ofdata was used. No significant excess above the SMbackground expectationwas observed in either channel. Theresults were interpreted in the framework of themBRWmodel.Mass-dependent limits were derived on the pair-production cross section times the square of the branching ratio (b2) and onβ. For b = 1, the observed(expected) LQmass limits at 95% CL are 1100 and 1050 GeV (1160 and 1040 GeV) forfirst- and second-generation leptoquarks, respectively. The observed bounds aremore stringent than the previous ATLAS limitsby 50 GeV in each channel. This analysis is the first result at 13 TeVusing the Run 2 data collected by the ATLASexperiment in a programof high precision inclusive searches for resonant signatures involving a lepton and a jet.

Figure 6.Distribution of theminimum reconstructed LQ candidatemass, mLQmin , in the signal region of (a) the first-generation

leptoquark search and (b) the second-generation search. Data are compared to the background prediction. TheDY+jets and ¯ttexpectations are scaled by the normalisation factors obtained from thefit described in section 6. The signal expectation for a LQofmass 1.1 TeV is also shown. The hatched bands show the total systematic uncertainty in the background prediction.

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New J. Phys. 18 (2016) 093016 MAaboud et al

Acknowledgments

We thankCERN for the very successful operation of the LHC, as well as the support staff fromour institutionswithoutwhomATLAS could not be operated efficiently.We acknowledge the support of ANPCyT, Argentina;

Figure 7.The cross-section limits (a) on scalar LQpair production times the square of the branching ratio as a function ofmass and (b)limits on the branching ratio as a function ofmass forfirst-generation leptoquarks. Analogous limits are shown for second-generationleptoquarks in (c) and (d). Expected and observed limits are also shown. The uncertainty bands on the expected limit represent allsources of systematic and statistical uncertainty. On the left, the expectedNLOproduction cross section (β=1.0) for scalarleptoquark pair-production and its corresponding theoretical uncertainty due to the choice of PDF set and renormalisation/factorisation scale are also included. The observed limit from the 8 TeV analysis is also shown on plots (b) and (d) [20].

Table 5.Expected and observed 95% CL lower limits onfirst- andsecond-generation leptoquarkmasses for different assumptionsofβ.

β95%CL limit on

mLQ1 (GeV) mLQ2 (GeV)

Expected Observed Expected Observed

1.00 1160 1100 1040 1050

0.75 1050 1000 950 960

0.50 900 900 800 830

0.25 680 700 580 600

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YerPhI, Armenia; ARC, Australia; BMWFWand FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq andFAPESP, Brazil; NSERC,NRC andCFI, Canada; CERN;CONICYT,Chile; CAS,MOST andNSFC, China;COLCIENCIAS, Colombia;MSMTCR,MPOCRandVSCCR,CzechRepublic; DNRF andDNSRC,Denmark;IN2P3-CNRS, CEA-DSM/IRFU, France; GNSF, Georgia; BMBF,HGF, andMPG,Germany; GSRT,Greece;RGC,HongKong SAR, China; ISF, I-CORE andBenoziyo Center, Israel; INFN, Italy;MEXT and JSPS, Japan;CNRST,Morocco; FOMandNWO,Netherlands; RCN,Norway;MNiSWandNCN, Poland; FCT, Portugal;MNE/IFA, Romania;MES of Russia andNRCKI, Russian Federation; JINR;MESTD, Serbia;MSSR, Slovakia;ARRS andMIZŠ Slovenia; DST/NRF, SouthAfrica;MINECO, Spain; SRC andWallenberg Foundation,Sweden; SERI, SNSF andCantons of Bern andGeneva, Switzerland;MOST, Taiwan; TAEK, Turkey; STFC,UnitedKingdom;DOE andNSF,United States of America. In addition, individual groups andmembers havereceived support fromBCKDF, theCanadaCouncil, CANARIE, CRC, Compute Canada, FQRNT, and theOntario Innovation Trust, Canada; EPLANET, ERC, FP7,Horizon 2020 andMarie Skłodowska-Curie Actions,EuropeanUnion; Investissements d’Avenir Labex and Idex, ANR, RégionAuvergne and Fondation Partager leSavoir, France; DFG andAvHFoundation, Germany;Herakleitos, Thales andAristeia programmes co-financedby EU-ESF and theGreekNSRF; BSF, GIF andMinerva, Israel; BRF,Norway; Generalitat de Catalunya,Generalitat Valenciana, Spain; the Royal Society and LeverhulmeTrust, United Kingdom. The crucialcomputing support from allWLCGpartners is acknowledged gratefully, in particular fromCERNand theATLASTier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (UK) andBNL (USA) and in the Tier-2 facilities worldwide.

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MAaboud136d, GAad87, BAbbott114, J Abdallah65, OAbdinov12, BAbeloos118, RAben108, O SAbouZeid138,N LAbraham150, HAbramowicz154, HAbreu153, RAbreu117, YAbulaiti147a,147b, B SAcharya164a,164b,179,LAdamczyk40a, D LAdams27, J Adelman109, S Adomeit101, TAdye132, AAAffolder76, TAgatonovic-Jovin14,J Agricola56, J AAguilar-Saavedra127a,127f, S PAhlen24, FAhmadov67,180, GAielli134a,134b, HAkerstedt147a,147b,T PAÅkesson83, AVAkimov97, G LAlberghi22a,22b, J Albert169, S Albrand57,M JAlconadaVerzini73,MAleksa32, I NAleksandrov67, CAlexa28b, GAlexander154, TAlexopoulos10,MAlhroob114,MAliev75a,75b,GAlimonti93a, J Alison33, S PAlkire37, BMMAllbrooke150, BWAllen117, P PAllport19, AAloisio105a,105b,

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DTurgeman172, RTurra93a,93b, A J Turvey42,PMTuts37,MTyndel132, GUcchielli22a,22b, I Ueda156, RUeno31,MUghetto147a,147b, FUkegawa161, GUnal32,AUndrus27, GUnel163, F CUngaro90, YUnno68, CUnverdorben101, J Urban145b, PUrquijo90, PUrrejola85,GUsai8, AUsanova64, LVacavant87, VVacek129, BVachon89, CValderanis101, EValdesSanturio147a,147b,NValencic108, S Valentinetti22a,22b, AValero167, LValery13, S Valkar130, S Vallecorsa51, J AVallsFerrer167,WVanDenWollenberg108, PCVanDerDeijl108, R vanderGeer108, H vanderGraaf108, N vanEldik153,P vanGemmeren6, J VanNieuwkoop143, I vanVulpen108,MCvanWoerden32,MVanadia133a,133b,WVandelli32, RVanguri123, AVaniachine131, PVankov108, GVardanyan177, RVari133a, EWVarnes7,TVarol42, DVarouchas82, AVartapetian8, K EVarvell151, J GVasquez176, FVazeille36, TVazquezSchroeder89,J Veatch56, LMVeloce159, FVeloso127a,127c, S Veneziano133a, AVentura75a,75b,MVenturi169, NVenturi159,AVenturini25, VVercesi122a,MVerducci133a,133b,WVerkerke108, J CVermeulen108, AVest46,221,MCVetterli143,182, OViazlo83, I Vichou166, TVickey140, O EVickeyBoeriu140, GHAViehhauser121, S Viel16,

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LVigani121, RVigne64,MVilla22a,22b,MVillaplanaPerez93a,93b, EVilucchi49,MGVincter31, VBVinogradov67,CVittori22a,22b, I Vivarelli150, S Vlachos10,MVlasak129,MVogel175, PVokac129, GVolpi125a,125b,MVolpi90,H vonderSchmitt102, E vonToerne23, VVorobel130, KVorobev99,MVos167, RVoss32, JHVossebeld76,NVranjes14,MVranjesMilosavljevic14, VVrba128,MVreeswijk108, RVuillermet32, I Vukotic33, ZVykydal129,PWagner23,WWagner175, HWahlberg73, SWahrmund46, JWakabayashi104, JWalder74, RWalker101,WWalkowiak142, VWallangen147a,147b, CWang35c, CWang35d,87, FWang173, HWang16, HWang42, JWang44,JWang151, KWang89, RWang6, SMWang152, TWang23, TWang37,WWang35b, XWang176, CWanotayaroj117,AWarburton89, C PWard30, DRWardrope80, AWashbrook48, PMWatkins19, ATWatson19,MFWatson19,GWatts139, SWatts86, BMWaugh80, SWebb85,M SWeber18, SWWeber174, J SWebster6, ARWeidberg121,BWeinert63, JWeingarten56, CWeiser50, HWeits108, P SWells32, TWenaus27, TWengler32, SWenig32,NWermes23,MWerner50,MDWerner66, PWerner32,MWessels60a, JWetter162, KWhalen117,N LWhallon139, AMWharton74, AWhite8,M JWhite1, RWhite34b, DWhiteson163, F JWickens132,WWiedenmann173,MWielers132, PWienemann23, CWiglesworth38, LAMWiik-Fuchs23, AWildauer102,FWilk86, HGWilkens32, HHWilliams123, SWilliams108, CWillis92, SWillocq88, J AWilson19,IWingerter-Seez5, FWinklmeier117, O JWinston150, B TWinter23,MWittgen144, JWittkowski101,S JWollstadt85,MWWolter41, HWolters127a,127c, BKWosiek41, JWotschack32,M JWoudstra86,KWWozniak41,MWu57,MWu33, S LWu173, XWu51, YWu91, TRWyatt86, BMWynne48, S Xella38, DXu35a,LXu27, BYabsley151, S Yacoob146a, RYakabe69, DYamaguchi158, Y Yamaguchi119, AYamamoto68,S Yamamoto156, TYamanaka156, KYamauchi104, YYamazaki69, Z Yan24, HYang35e,35f, HYang173, Y Yang152,ZYang15,W-MYao16, YCYap82, Y Yasu68, E Yatsenko5, KHYauWong23, J Ye42, S Ye27, I Yeletskikh67,A LYen59, E Yildirim85, KYorita171, R Yoshida6, KYoshihara123, CYoung144, C J SYoung32, S Youssef24,DRYu16, J Yu8, JMYu91, J Yu66, L Yuan69, S PYYuen23, I Yusuff30,222, B Zabinski41, R Zaidan35d,AMZaitsev131,209, NZakharchuk44, J Zalieckas15, A Zaman149, S Zambito59, L Zanello133a,133b, DZanzi90,C Zeitnitz175,MZeman129, AZemla40a, J CZeng166, QZeng144, K Zengel25, OZenin131, TŽeniš145a, DZerwas118,DZhang91, F Zhang173, G Zhang35b,217, HZhang35c, J Zhang6, L Zhang50, R Zhang23, R Zhang35b,223, X Zhang35d,Z Zhang118, X Zhao42, Y Zhao35d, Z Zhao35b, AZhemchugov67, J Zhong121, B Zhou91, C Zhou47, L Zhou37,L Zhou42,MZhou149, NZhou35g, CGZhu35d, HZhu35a, J Zhu91, Y Zhu35b, X Zhuang35a, K Zhukov97, A Zibell174,DZieminska63, N I Zimine67, C Zimmermann85, S Zimmermann50, Z Zinonos56,MZinser85,MZiolkowski142,LŽivković14, GZobernig173, A Zoccoli22a,22b,M zurNedden17, GZurzolo105a,105b and LZwalinski32

1 Department of Physics, University of Adelaide, Adelaide, Australia2 PhysicsDepartment, SUNYAlbany, AlbanyNY,USA3 Department of Physics, University of Alberta, EdmontonAB,Canada4a Department of Physics, AnkaraUniversity, Ankara4b Istanbul AydinUniversity, Istanbul4c Division of Physics, TOBBUniversity of Economics andTechnology, Ankara, Turkey5 LAPP, CNRS/IN2P3 andUniversité SavoieMont Blanc, Annecy-le-Vieux, France6 High Energy PhysicsDivision, ArgonneNational Laboratory, Argonne IL, USA7 Department of Physics, University of Arizona, TucsonAZ,USA8 Department of Physics, TheUniversity of Texas at Arlington, ArlingtonTX,USA9 PhysicsDepartment, University of Athens, Athens, Greece10 PhysicsDepartment, National Technical University of Athens, Zografou, Greece11 Department of Physics, TheUniversity of Texas at Austin, Austin TX,USA12 Institute of Physics, AzerbaijanAcademy of Sciences, Baku, Azerbaijan13 Institut de Física d’Altes Energies (IFAE), The Barcelona Institute of Science andTechnology, Barcelona, Spain14 Institute of Physics, University of Belgrade, Belgrade, Serbia15 Department for Physics andTechnology, University of Bergen, Bergen, Norway16 PhysicsDivision, Lawrence BerkeleyNational Laboratory andUniversity of California, Berkeley CA,USA17 Department of Physics, HumboldtUniversity, Berlin, Germany18 Albert Einstein Center for Fundamental Physics and Laboratory forHigh Energy Physics, University of Bern, Bern, Switzerland19 School of Physics andAstronomy,University of Birmingham, Birmingham,UK20a Department of Physics, Bogazici University, Istanbul20b Department of Physics Engineering, GaziantepUniversity, Gaziantep, Turkey20d Istanbul Bilgi University, Faculty of Engineering andNatural Sciences, Istanbul, Turkey20e Bahcesehir University, Faculty of Engineering andNatural Sciences, Istanbul, Turkey21 Centro de Investigaciones, Universidad AntonioNarino, Bogota, Colombia22a INFNSezione di Bologna, Italy22b Dipartimento di Fisica e Astronomia, Università di Bologna, Bologna, Italy23 Physikalisches Institut, University of Bonn, Bonn, Germany24 Department of Physics, BostonUniversity, BostonMA,USA25 Department of Physics, Brandeis University,WalthamMA,USA26a Universidade Federal doRioDe JaneiroCOPPE/EE/IF, Rio de Janeiro, Brazil26b Electrical Circuits Department, Federal University of Juiz de Fora (UFJF), Juiz de Fora, Brazil26c Federal University of Sao Joao del Rei (UFSJ), Sao Joao del Rei, Brazil26d Instituto de Fisica, Universidade de Sao Paulo, Sao Paulo, Brazil27 PhysicsDepartment, BrookhavenNational Laboratory, UptonNY,USA28a Transilvania University of Brasov, Brasov, Romania

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28b National Institute of Physics andNuclear Engineering, Bucharest, Romania28c National Institute for Research andDevelopment of Isotopic andMolecular Technologies, PhysicsDepartment, ClujNapoca, Romania28d University Politehnica Bucharest, Bucharest, Romania28e West University in Timisoara, Timisoara, Romania29 Departamento de Física, Universidad de BuenosAires, Buenos Aires, Argentina30 Cavendish Laboratory, University of Cambridge, Cambridge, UK31 Department of Physics, CarletonUniversity, OttawaON,Canada32 CERN,Geneva, Switzerland33 Enrico Fermi Institute, University of Chicago, Chicago IL, USA34a Departamento de Física, PontificiaUniversidadCatólica deChile, Santiago, Chile34b Departamento de Física, Universidad Técnica Federico SantaMaría, Valparaíso, Chile35a Institute ofHigh Energy Physics, Chinese Academy of Sciences, Beijing, People’s Republic of China35b Department ofModern Physics, University of Science andTechnology of China, Anhui, People’s Republic of China35c Department of Physics, NanjingUniversity, Jiangsu, People’s Republic of China35d School of Physics, ShandongUniversity, Shandong, People’s Republic of China35e Department of Physics andAstronomy, Shanghai Key Laboratory for Particle Physics andCosmology, Shanghai Jiao TongUniversity,

Shanghai, People’s Republic of China35f Also affiliatedwith PKU-CHEP35g PhysicsDepartment, TsinghuaUniversity, Beijing 100084, People’s Republic of China36 Laboratoire de PhysiqueCorpusculaire, ClermontUniversité andUniversité Blaise Pascal andCNRS/IN2P3, Clermont-Ferrand, France37 Nevis Laboratory, ColumbiaUniversity, IrvingtonNY,USA38 Niels Bohr Institute, University of Copenhagen, Kobenhavn, Denmark39a INFNGruppoCollegato di Cosenza, Laboratori Nazionali di Frascati, Italy39b Dipartimento di Fisica, Università della Calabria, Rende, Italy40a AGHUniversity of Science andTechnology, Faculty of Physics andAppliedComputer Science, Krakow, Poland40b Marian Smoluchowski Institute of Physics, JagiellonianUniversity, Krakow, Poland41 Institute ofNuclear Physics Polish Academy of Sciences, Krakow, Poland42 PhysicsDepartment, SouthernMethodist University, Dallas TX,USA43 PhysicsDepartment, University of Texas atDallas, RichardsonTX,USA44 DESY,Hamburg andZeuthen, Germany45 Institut für Experimentelle Physik IV, TechnischeUniversität Dortmund,Dortmund, Germany46 Institut für Kern-undTeilchenphysik, TechnischeUniversität Dresden, Dresden, Germany47 Department of Physics, DukeUniversity, DurhamNC,USA48 SUPA—School of Physics andAstronomy,University of Edinburgh, Edinburgh, UK49 INFNLaboratori Nazionali di Frascati, Frascati, Italy50 Fakultät fürMathematik undPhysik, Albert-Ludwigs-Universität, Freiburg, Germany51 Section de Physique, Université deGenève, Geneva, Switzerland52a INFNSezione diGenova, Italy52b Dipartimento di Fisica, Università di Genova, Genova, Italy53a E. Andronikashvili Institute of Physics, Iv. Javakhishvili Tbilisi StateUniversity, Tbilisi, Georgia53b High Energy Physics Institute, Tbilisi StateUniversity, Tbilisi, Georgia54 II Physikalisches Institut, Justus-Liebig-Universität Giessen, Giessen, Germany55 SUPA—School of Physics andAstronomy,University of Glasgow,Glasgow,UK56 II Physikalisches Institut, Georg-August-Universität, Göttingen, Germany57 Laboratoire de Physique Subatomique et de Cosmologie, Université Grenoble-Alpes, CNRS/IN2P3, Grenoble, France58 Department of Physics, HamptonUniversity, HamptonVA,USA59 Laboratory for Particle Physics andCosmology, HarvardUniversity, CambridgeMA,USA60a Kirchhoff-Institut für Physik, Ruprecht-Karls-Universität Heidelberg, Heidelberg, Germany60b Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg,Heidelberg, Germany60c ZITI Institut für technische Informatik, Ruprecht-Karls-Universität Heidelberg,Mannheim,Germany61 Faculty of Applied Information Science,Hiroshima Institute of Technology,Hiroshima, Japan62a Department of Physics, TheChineseUniversity ofHongKong, Shatin, N.T., HongKong, People’s Republic of China62b Department of Physics, TheUniversity ofHongKong,HongKong, People’s Republic of China62c Department of Physics, TheHongKongUniversity of Science andTechnology, ClearWater Bay, Kowloon,HongKong, People’s

Republic of China63 Department of Physics, IndianaUniversity, Bloomington IN,USA64 Institut für Astro-undTeilchenphysik, Leopold-Franzens-Universität, Innsbruck, Austria65 University of Iowa, IowaCity IA, USA66 Department of Physics andAstronomy, Iowa StateUniversity, Ames IA, USA67 Joint Institute forNuclear Research, JINRDubna, Dubna, Russia68 KEK,High Energy Accelerator ResearchOrganization, Tsukuba, Japan69 Graduate School of Science, KobeUniversity, Kobe, Japan70 Faculty of Science, KyotoUniversity, Kyoto, Japan71 KyotoUniversity of Education, Kyoto, Japan72 Department of Physics, KyushuUniversity, Fukuoka, Japan73 Instituto de Física La Plata, UniversidadNacional de La Plata andCONICET, La Plata, Argentina74 PhysicsDepartment, LancasterUniversity, Lancaster, UK75a INFNSezione di Lecce, Italy75b Dipartimento diMatematica e Fisica, Università del Salento, Lecce, Italy76 Oliver Lodge Laboratory, University of Liverpool, Liverpool, UK77 Department of Physics, Jožef Stefan Institute andUniversity of Ljubljana, Ljubljana, Slovenia78 School of Physics andAstronomy,QueenMaryUniversity of London, London,UK79 Department of Physics, RoyalHollowayUniversity of London, Surrey, UK

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80 Department of Physics andAstronomy,University College London, London, UK81 Louisiana TechUniversity, Ruston LA,USA82 Laboratoire de PhysiqueNucléaire et deHautes Energies, UPMCandUniversité Paris-Diderot andCNRS/IN2P3, Paris, France83 Fysiska institutionen, Lunds universitet, Lund, Sweden84 Departamento de Fisica Teorica C-15, Universidad Autonoma deMadrid,Madrid, Spain85 Institut für Physik, UniversitätMainz,Mainz, Germany86 School of Physics andAstronomy,University ofManchester,Manchester, UK87 CPPM,Aix-Marseille Université andCNRS/IN2P3,Marseille, France88 Department of Physics, University ofMassachusetts, AmherstMA,USA89 Department of Physics,McGill University,MontrealQC,Canada90 School of Physics, University ofMelbourne, Victoria, Australia91 Department of Physics, TheUniversity ofMichigan, AnnArborMI,USA92 Department of Physics andAstronomy,Michigan StateUniversity, East LansingMI,USA93a INFNSezione diMilano, Italy93b Dipartimento di Fisica, Università diMilano,Milano, Italy94 B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus,Minsk, Republic of Belarus95 National Scientific and Educational Centre for Particle andHigh Energy Physics,Minsk, Republic of Belarus96 Group of Particle Physics, University ofMontreal,MontrealQC, Canada97 P.N. Lebedev Physical Institute of the RussianAcademy of Sciences,Moscow, Russia98 Institute for Theoretical and Experimental Physics (ITEP),Moscow, Russia99 National ResearchNuclearUniversityMEPhI,Moscow, Russia100 D.V. Skobeltsyn Institute ofNuclear Physics,M.V. LomonosovMoscow StateUniversity,Moscow, Russia101 Fakultät für Physik, Ludwig-Maximilians-UniversitätMünchen,München, Germany102 Max-Planck-Institut für Physik (Werner-Heisenberg-Institut),München, Germany103 Nagasaki Institute of Applied Science, Nagasaki, Japan104 Graduate School of Science andKobayashi-Maskawa Institute, NagoyaUniversity, Nagoya, Japan105a INFNSezione diNapoli, Italy105b Dipartimento di Fisica, Università diNapoli, Napoli, Italy106 Department of Physics andAstronomy,University ofNewMexico, AlbuquerqueNM,USA107 Institute forMathematics, Astrophysics and Particle Physics, RadboudUniversityNijmegen/Nikhef, Nijmegen, TheNetherlands108 NikhefNational Institute for Subatomic Physics andUniversity of Amsterdam, Amsterdam, TheNetherlands109 Department of Physics, Northern IllinoisUniversity, DeKalb IL, USA110 Budker Institute ofNuclear Physics, SB RAS,Novosibirsk, Russia111 Department of Physics, NewYorkUniversity, NewYorkNY,USA112 Ohio StateUniversity, ColumbusOH,USA113 Faculty of Science, OkayamaUniversity, Okayama, Japan114 Homer L.DodgeDepartment of Physics andAstronomy,University ofOklahoma,NormanOK,USA115 Department of Physics, Oklahoma StateUniversity, StillwaterOK,USA116 PalackýUniversity, RCPTM,Olomouc, Czech Republic117 Center forHigh Energy Physics, University ofOregon, EugeneOR,USA118 LAL,Univ. Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay, France119 Graduate School of Science, OsakaUniversity, Osaka, Japan120 Department of Physics, University of Oslo, Oslo,Norway121 Department of Physics, OxfordUniversity, Oxford, UK122a INFNSezione di Pavia, Italy122b Dipartimento di Fisica, Università di Pavia, Pavia, Italy123 Department of Physics, University of Pennsylvania, Philadelphia PA,USA124 National ResearchCentre ‘Kurchatov Institute’B.P.Konstantinov PetersburgNuclear Physics Institute, St. Petersburg, Russia125a INFNSezione di Pisa, Italy125b Dipartimento di Fisica E. Fermi, Università di Pisa, Pisa, Italy126 Department of Physics andAstronomy,University of Pittsburgh, Pittsburgh PA,USA127a Laboratório de Instrumentação e Física Experimental de Partículas—LIP, Lisboa, Portugal127b Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal127c Department of Physics, University of Coimbra, Coimbra, Portugal127d Centro de FísicaNuclear daUniversidade de Lisboa, Lisboa, Portugal127e Departamento de Fisica, Universidade doMinho, Braga, Portugal127f Departamento de Fisica Teorica y del Cosmos andCAFPE,Universidad deGranada, Granada, Spain127g Dep Fisica andCEFITECof Faculdade deCiencias e Tecnologia, UniversidadeNova de Lisboa, Caparica, Portugal128 Institute of Physics, Academy of Sciences of theCzechRepublic, Praha, CzechRepublic129 Czech Technical University in Prague, Praha, Czech Republic130 Faculty ofMathematics and Physics, Charles University in Prague, Praha, CzechRepublic131 State ResearchCenter Institute forHigh Energy Physics (Protvino), NRCKI, Russia132 Particle PhysicsDepartment, RutherfordAppleton Laboratory, Didcot, UK133a INFNSezione di Roma, Italy133b Dipartimento di Fisica, SapienzaUniversità di Roma, Roma, Italy134a INFNSezione di RomaTorVergata, Italy134b Dipartimento di Fisica, Università di RomaTorVergata, Roma, Italy135a INFNSezione di RomaTre, Italy135b Dipartimento diMatematica e Fisica, Università RomaTre, Roma, Italy136a Faculté des Sciences AinChock, RéseauUniversitaire de Physique desHautes Energies—UniversitéHassan II, Casablanca,Morocco136b CentreNational de l’Energie des Sciences TechniquesNucleaires, Rabat,Morocco136c Faculté des Sciences Semlalia, Université Cadi Ayyad, LPHEA-Marrakech,Morocco136d Faculté des Sciences, UniversitéMohamed Premier and LPTPM,Oujda,Morocco

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136e Faculté des sciences, UniversitéMohammedV, Rabat,Morocco137 DSM/IRFU (Institut de Recherches sur les Lois Fondamentales de l’Univers), CEA Saclay (Commissariat à l’Energie Atomique et aux

Energies Alternatives), Gif-sur-Yvette, France138 Santa Cruz Institute for Particle Physics, University of California Santa Cruz, Santa CruzCA,USA139 Department of Physics, University ofWashington, SeattleWA,USA140 Department of Physics andAstronomy,University of Sheffield, Sheffield, UK141 Department of Physics, ShinshuUniversity, Nagano, Japan142 Fachbereich Physik, Universität Siegen, Siegen, Germany143 Department of Physics, Simon FraserUniversity, Burnaby BC,Canada144 SLACNational Accelerator Laboratory, StanfordCA,USA145a Faculty ofMathematics, Physics & Informatics, ComeniusUniversity, Bratislava, Slovakia145b Department of Subnuclear Physics, Institute of Experimental Physics of the SlovakAcademy of Sciences, Kosice, Slovak Republic,

Slovakia146a Department of Physics, University of Cape Town, CapeTown, SouthAfrica146b Department of Physics, University of Johannesburg, Johannesburg, SouthAfrica146c School of Physics, University of theWitwatersrand, Johannesburg, SouthAfrica147a Department of Physics, StockholmUniversity, Sweden147b TheOskarKlein Centre, Stockholm, Sweden148 PhysicsDepartment, Royal Institute of Technology, Stockholm, Sweden149 Departments of Physics &Astronomy andChemistry, Stony BrookUniversity, Stony BrookNY,USA150 Department of Physics andAstronomy,University of Sussex, Brighton, UK151 School of Physics, University of Sydney, Sydney, Australia152 Institute of Physics, Academia Sinica, Taipei, Taiwan153 Department of Physics, Technion: Israel Institute of Technology,Haifa, Israel154 Raymond andBeverly Sackler School of Physics andAstronomy, Tel AvivUniversity, Tel Aviv, Israel155 Department of Physics, Aristotle University of Thessaloniki, Thessaloniki, Greece156 International Center for Elementary Particle Physics andDepartment of Physics, TheUniversity of Tokyo, Tokyo, Japan157 Graduate School of Science andTechnology, TokyoMetropolitanUniversity, Tokyo, Japan158 Department of Physics, Tokyo Institute of Technology, Tokyo, Japan159 Department of Physics, University of Toronto, TorontoON,Canada160a TRIUMF, Vancouver BC, Canada160b Department of Physics andAstronomy, YorkUniversity, TorontoON,Canada161 Faculty of Pure andApplied Sciences, andCenter for Integrated Research in Fundamental Science and Engineering, University of

Tsukuba, Tsukuba, Japan162 Department of Physics andAstronomy, TuftsUniversity,MedfordMA,USA163 Department of Physics andAstronomy,University of California Irvine, Irvine CA,USA164a INFNGruppoCollegato diUdine, Sezione di Trieste, Udine, Italy164b ICTP, Trieste, Italy164c Dipartimento di Chimica, Fisica e Ambiente, Università diUdine, Udine, Italy165 Department of Physics andAstronomy,University ofUppsala, Uppsala, Sweden166 Department of Physics, University of Illinois, Urbana IL,USA167 Instituto de Fisica Corpuscular (IFIC) andDepartamento de Fisica Atomica,Molecular yNuclear andDepartamento de Ingeniería

Electrónica and Instituto deMicroelectrónica de Barcelona (IMB-CNM), University of Valencia andCSIC, Valencia, Spain168 Department of Physics, University of British Columbia, Vancouver BC,Canada169 Department of Physics andAstronomy,University of Victoria, Victoria BC,Canada170 Department of Physics, University ofWarwick, Coventry, UK171 WasedaUniversity, Tokyo, Japan172 Department of Particle Physics, TheWeizmann Institute of Science, Rehovot, Israel173 Department of Physics, University ofWisconsin,MadisonWI,USA174 Fakultät für Physik undAstronomie, Julius-Maximilians-Universität,Würzburg, Germany175 Fakultät fürMathematik undNaturwissenschaften, Fachgruppe Physik, BergischeUniversitätWuppertal,Wuppertal, Germany176 Department of Physics, YaleUniversity, NewHavenCT,USA177 Yerevan Physics Institute, Yerevan, Armenia178 Centre deCalcul de l’InstitutNational de PhysiqueNucléaire et de Physique des Particules (IN2P3), Villeurbanne, France179 Also atDepartment of Physics, Kingʼs College London, London, UK180 Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan181 Also atNovosibirsk StateUniversity, Novosibirsk, Russia182 Also at TRIUMF,Vancouver BC, Canada183 Also atDepartment of Physics &Astronomy,University of Louisville, Louisville, KY,USA184 Also atDepartment of Physics, California StateUniversity, FresnoCA,USA185 Also atDepartment of Physics, University of Fribourg, Fribourg, Switzerland186 Also atDepartament de Fisica de laUniversitat Autonoma de Barcelona, Barcelona, Spain187 Also atDepartamento de Fisica e Astronomia, Faculdade de Ciencias, Universidade do Porto, Portugal188 Also at Tomsk StateUniversity, Tomsk, Russia189 Also atUniversita diNapoli Parthenope, Napoli, Italy190 Also at Institute of Particle Physics (IPP), Canada191 Also atNational Institute of Physics andNuclear Engineering, Bucharest, Romania192 Also atDepartment of Physics, St. Petersburg State Polytechnical University, St. Petersburg, Russia193 Also atDepartment of Physics, TheUniversity ofMichigan, AnnArborMI, USA194 Also at Centre forHigh Performance Computing, CSIRCampus, Rosebank, CapeTown, SouthAfrica195 Also at Louisiana TechUniversity, Ruston LA,USA196 Also at InstitucioCatalana deRecerca i Estudis Avancats, ICREA, Barcelona, Spain197 Also at Graduate School of Science, OsakaUniversity, Osaka, Japan

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New J. Phys. 18 (2016) 093016 MAaboud et al

198 Also atDepartment of Physics, National TsingHuaUniversity, Taiwan199 Also at Institute forMathematics, Astrophysics and Particle Physics, RadboudUniversity Nijmegen/Nikhef, Nijmegen, The

Netherlands200 Also atDepartment of Physics, TheUniversity of Texas at Austin, Austin TX,USA201 Also at Institute of Theoretical Physics, Ilia StateUniversity, Tbilisi, Georgia202 Also at CERN,Geneva, Switzerland203 Also at GeorgianTechnical University (GTU),Tbilisi, Georgia204 Also atOchadai Academic Production, OchanomizuUniversity, Tokyo, Japan205 Also atManhattanCollege,NewYorkNY,USA206 Also atHellenicOpenUniversity, Patras, Greece207 Also at Academia SinicaGrid Computing, Institute of Physics, Academia Sinica, Taipei, Taiwan208 Also at School of Physics, ShandongUniversity, Shandong, People’s Republic of China209 Also atMoscow Institute of Physics andTechnology StateUniversity, Dolgoprudny, Russia210 Also at section de Physique, Université deGenève, Geneva, Switzerland211 Also at Eotvos LorandUniversity, Budapest, Hungary212 Also at International School for Advanced Studies (SISSA), Trieste, Italy213 Also atDepartment of Physics andAstronomy,University of SouthCarolina, Columbia SC,USA214 Also at School of Physics and Engineering, SunYat-senUniversity, Guangzhou, People’s Republic of China215 Also at Institute forNuclear Research andNuclear Energy (INRNE) of the Bulgarian Academy of Sciences, Sofia, Bulgaria216 Also at Faculty of Physics,M.V.LomonosovMoscow StateUniversity,Moscow, Russia217 Also at Institute of Physics, Academia Sinica, Taipei, Taiwan218 Also atNational ResearchNuclearUniversityMEPhI,Moscow, Russia219 Also atDepartment of Physics, StanfordUniversity, StanfordCA,USA220 Also at Institute for Particle andNuclear Physics,Wigner ResearchCentre for Physics, Budapest, Hungary221 Also at FlensburgUniversity of Applied Sciences, Flensburg, Germany222 Also atUniversity ofMalaya, Department of Physics, Kuala Lumpur,Malaysia223 Also at CPPM,Aix-Marseille Université andCNRS/IN2P3,Marseille, France224 Deceased

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New J. Phys. 18 (2016) 093016 MAaboud et al