Measurement of the associated production of a single top quark and a Z boson in pp collisions at $\sqrt{s} =$ TeV

Contents lists available atScienceDirect

Physics

Letters

B

www.elsevier.com/locate/physletb

Measurement

of

the

associated

production

of

a

single

top

quark

and

a

Z

boson

in

pp

collisions

at

√

s

=

13 TeV

.

The

CMS

Collaboration



CERN,Switzerland

a

r

t

i

c

l

e

i

n

f

o

a

b

s

t

r

a

c

t

Articlehistory:

Received7December2017

Receivedinrevisedform5February2018 Accepted9February2018

Availableonline14February2018 Editor: M.Doser Keywords: SM Singletop Crosssection tZq

AmeasurementispresentedoftheassociatedproductionofasingletopquarkandaZboson.Thestudy usesdatafromproton–protoncollisionsat√s=13 TeV recordedbytheCMSexperiment,corresponding toanintegratedluminosityof35.9 fb−1_{.Usingfinalstateswiththreeleptons(electronsormuons),the}

tZq productioncross sectionis measuredtobe

σ

(pp_→tZq_→Wb+−q)=123+₋33₃₁(stat)+₋29₂₃(syst) fb, wherestandsforelectrons,muons,or

τ

leptons,withobservedandexpectedsignificancesof3.7and 3.1standarddeviations,respectively.

©2018TheAuthor.PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCCBYlicense (http://creativecommons.org/licenses/by/4.0/).FundedbySCOAP3_.

1. Introduction

AttheCERNLHC,singletopquarkproductionproceedsthrough threeelectroweakinteractionprocesses:t-channel, s-channel,and associatedtW production.Crosssectionsforsingletopquark pro-ductionhavebeenreportedbytheCDFandD0 Collaborations[1,

2],aswellasbytheATLAS [3–7] andCMS [8–11] Collaborations. Thehighcentre-of-massproton–proton(pp)collisionenergyof 13 TeV attheLHC,togetherwithlargeintegratedluminosities, al-lows the study of processes with very small cross sections that werenotaccessibleatlowerenergies.Oneexampleofsucha pro-cessistherareassociatedproductionofasingletopquarkwitha Z boson.Thisproductionmechanism,leadingtoafinalstatewitha topquark,aZ boson,andanadditionalquark,canprobethe stan-dard model (SM) in a unique way. The main leading-order (LO) diagramsthatcontributetothisfinalstateareshowninFig.1. Al-thoughgenericallydenotedinthisLetterbytZq,thisprocessalso includes a small contribution fromnon-resonant lepton pairs, as shownin the lower right-hand diagram in Fig.1. The process is sensitive to top quark couplings to the Z boson,asillustrated in the middle right-hand diagram in Fig. 1, and also to the triple

 _{E-mailaddress:cms-publication-committee-chair@cern.ch.}

gauge-boson coupling WWZ,asillustrated inthe lower left-hand diagraminFig.1.

The top quark couplingsto the Z bosonandthetriple gauge-bosoncouplingsaresensitivetonewphysicalphenomena. In par-ticular,measurementsoftZq productionaresensitivetoprocesses beyondtheSMthathavesimilarexperimentalsignatures,suchas flavour-changingneutralcurrents(FCNC)involvingthedirect cou-pling of the top quark to a Z boson andan up orcharm quark, atthetopquarkproductionordecay[12,13].WithintheSM,FCNC processesareforbiddenatLOandsuppressedathigherorders [14]. Deviations from the expectedSM tZq production could therefore beindicativeofbeyond-SMFCNCprocesses.

The next-to-leading-order (NLO) cross section for tZq

→

Wb



+



−q, considering only the leptonic decays of Z bosons (to electrons,muons,or

τ

leptons,genericallydenotedby



),is calcu-latedforpp collisionsatacentre-of-massenergyof13 TeV,using theMonteCarlo(MC)generator MadGraph5_amc@nlo 2.2.2 [15]. The calculation, which includes lepton pairs from off-shell Z bosons withinvariantmassm+−

>

30 GeV,uses theNNPDF3.0 setofpartondistributionfunctions(PDFs) [16] in thefive-flavour scheme.Theresultis

σ

SM

₍

_t

_

+

_

−_q

₎

₌

₉₄

_.

₂+1.9

−1.8(scale)

±

2

.

5(PDF) fb,

with the “scale” and “PDF” uncertainties estimated, respectively, bychangingthequantumchromodynamics(QCD)renormalization andfactorizationscales byfactors of0.5and2,andbyusing the 68% confidence level (CL) uncertainty on the NNPDF3.0 PDF set.

https://doi.org/10.1016/j.physletb.2018.02.025

0370-2693/©2018TheAuthor.PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCCBYlicense(http://creativecommons.org/licenses/by/4.0/).Fundedby SCOAP3_.

Fig. 1. Leading-order tZq production diagrams. The lower right-hand diagram represents the non-resonant contribution to the tZq process.

Thiscrosssectionisusedasthereferenceinthisanalysis.Another calculation,includingall Z bosondecays,givesacompatiblecross section whenthe branching fraction to charged leptons is taken intoaccount[17].PrevioussearchesfortZq productionat8 TeV by theCMSCollaboration [18] reportedasignalwithasignificanceof 2.4standarddeviations.TheATLASCollaborationrecentlyreported ameasurementofthetZq productioncrosssectionat13 TeV [19] withasignificanceof4.2standarddeviations.

ThisLetterpresentsasearchfortZq productioninpp collisions at

√

s

=

13 TeV,usingdatacollectedin2016byCMS, correspond-ing to an integrated luminosity of 35.9 fb−1. The signature for tZq production consists of a single top quark produced in the t

channel,a Z boson, andan additional(“recoiling”) jet emittedat pseudorapidity

|

η

|

<

4

.

5.TheanalysisuseseventswheretheZ bo-son decays to e+e− or

μ

+

μ

−, while the W boson, produced in thedecayofthe topquark, decaysto aneutrinoandan electron or a muon, resulting in four possible final-state leptonic combi-nations: eee, eeμ, eμμ, and

μμμ

. There will also be a small contributionfrom

τ

leptonsdecayingintoelectronsormuons.The finalresultreflectsanextrapolationtoincludealldecaymodes in-volving

τ

leptons. The measurement is based on a multivariate analysis,whereboosteddecisiontrees(BDTs) [20] areusedto en-hancethesignal-to-backgroundseparation.Severalcontrolregions are definedto better constrain the backgrounds, each containing differentcontributionsfromsignalandbackgroundprocesses.

2. TheCMSdetector

The central feature of the CMS apparatus is a superconduct-ingsolenoidof 6 minternal diameter,providing amagnetic field of3.8 T.Withinthesolenoidvolumeare asilicon pixelandstrip

tracker,aleadtungstatecrystalelectromagneticcalorimeter(ECAL), andabrass andscintillatorhadroncalorimeter(HCAL),each com-posedof a barrelandtwo endcapsections.Forward calorimeters extend the pseudorapidity coverage provided by the barrel and endcapdetectors.Muonsaremeasuredingas-ionizationdetectors embedded inthesteel flux-returnyokeoutsidethesolenoid. The electron momentum is evaluated by combiningthe energy mea-surement inthe ECAL with the momentum measurement in the tracker. The momentum resolution for electrons with transverse momentum, pT,around 45 GeVfromZ

→

ee decays rangesfrom

1.7% for nonshowering electrons in the barrelregion to 4.5% for showering electrons in the endcaps [21]. Muons are measured in the range

|

η

|

<

2

.

4, with detection planes made using three technologies: drift tubes, cathode strip chambers, and resistive plate chambers. Matching muons to tracks measured inthe sili-contracker resultsin arelative transverse momentum resolution formuonswith20

<

pT

<

100 GeV of 1.3–2.0%in thebarreland

better than 6% in the endcaps [22]. A more detaileddescription ofthe CMSdetector, together witha definitionofthe coordinate systemusedandtherelevantkinematicvariables,canbefoundin Ref. [23].

Events of interest are selected using a two-tiered trigger sys-tem [24].Thefirstlevel,composedofcustomhardwareprocessors, usesinformationfromthecalorimetersandmuondetectorsto se-lectevents ata rateofaround100 kHzwithin a timeinterval of lessthan 4 μs.The second level,knownasthe high-level trigger, consistsofafarmofprocessorsrunningaversionofthefullevent reconstructionsoftwareoptimisedforfastprocessing,andreduces theeventratetolessthan1 kHzbeforedatastorage.

3. Onlineselection,reconstruction,andidentification

The data are selected online using triggers that rely on the presenceofeitherone, two,orthreehigh-pT leptons. Thelowest

pTthresholdsofthethree-leptontriggersare16,12,and8 GeVfor

electrons,and12,10,and5 GeVformuons;thecorresponding val-uesforthedileptontriggersare23and12 GeVforelectrons,and 17and8 GeVformuons.Triggersrequiringthepresenceofatleast oneelectronandatleastonemuonarealsoused.Forthebaseline offlineselection,atriggerefficiencyofnearly 100%isachievedby includingsingle-leptontriggerswiththresholdsof32and24 GeV forelectrons andmuons,respectively,inadditiontothetwo- and three-leptontriggers.

The events are reconstructed using the particle-flow (PF) al-gorithm [25], which reconstructs and identifies each individual particle with an optimised combination of information fromthe variouselementsoftheCMSdetector.Theenergyofthephotonsis directlyobtainedfromtheECALmeasurement,correctedfor zero-suppressioneffects,whilethatoftheelectronsisdeterminedfrom acombinationoftheelectronmomentumattheprimary interac-tionvertexasdeterminedbythetracker,theenergyofthe corre-spondingECALcluster,andthetotalenergyofall bremsstrahlung photons spatially compatible with originating from the electron track.The energyofthemuonsisobtainedfromthecurvatureof thecorresponding track.The energyof chargedhadronsis deter-mined froma combinationoftheir momentum, measured inthe tracker, and the matching ECAL and HCAL energy deposits, cor-rectedforzero-suppressioneffectsandfortheresponsefunctionof thecalorimeterstohadronicshowers.Finally,theenergyofneutral hadronsis obtainedfromthe corresponding ECALandHCAL cor-rectedenergydeposits.Foreachevent, jetsareclusteredfromthe PFcandidatesusingtheanti-kT algorithm [26,27],witha distance

parameterof0.4. The reconstructedvertexwiththe largestvalue ofsummedphysics-object p2_T istakentobetheprimary pp inter-actionvertex. The physicsobjects arethe jets, clusteredwiththe tracksassignedtothevertexasinputs,andtheassociatedmissing transversemomentum,takenasthenegativevectorsumofthepT

ofthose jets.All chargedparticles considered inthisanalysisare requiredtobecompatiblewithoriginatingfromtheprimary inter-actionvertex.

Theeventselectionreliesontheconceptofrelativelepton iso-lation,reflectedinthevariable Irel,computedasthescalarsumof

the pT ofallparticles inacone ofradius



R

=



(

η

)

2

_{+ (φ)}

2

around the lepton (where

φ

is the azimuth), excluding the lep-ton,anddivided by thelepton pT.Thesumis thencorrected for

theneutralparticlesproducedinextra pp interactionswithinthe sameor neighbouringLHC bunch crossings, referred toaspileup (PU) collisions. Forelectrons,



R is setto 0.3, andthe expected PUwithintheisolationconeisestimatedfromthemedianenergy densityper area of PU contamination. Muon Irel uses



R

=

0

.

4,

andiscorrectedfortheaverageneutralPUenergyinsidethe iso-lationcone,whichhasbeenmeasuredinmultijeteventstobeone half of the energy coming from charged hadrons not associated withtheprimary vertex.Electronsandmuonsare considered iso-latedifIrel issmallerthan0.06and0.15,respectively.

The data with prompt leptons are contaminated by genuine leptons from hadron decays (usually referred to as “nonprompt leptons”)andby hadronsorjetsmisidentified asleptons(usually referredtoas“fakeleptons”).Inaddition,nonpromptisolated elec-tronscan arise fromthe conversion ofphotons. Forsimplicity of notation, and giventhat thesebackground sources are evaluated withsimilar methods,based oncontrol samplesin data,all such sources are referredto as“not-prompt”leptons, orsimply “NPL”, inthisLetter.DatasamplesforevaluatingtheNPLbackgroundare builtusingobjects reconstructed similarlyto theprompt leptons,

withtwo importantdifferences. First, whilethe prompt and not-promptleptonsareidentifiedusingthesamevariables [21,22],less stringent criteriaare applied to theNPL sample. Second, leptons are considerednot-prompt onlyifthey arenot isolated,requiring not-prompt electrons ormuonstohave Irel

>

0

.

17 or

>

0

.

25,

re-spectively. Inaddition, not-prompt electronsare requiredto have

Irel

<

1, removing a large fraction of photons with Irel

≈

1 and

Z

+

jetseventscontaining a low-pT jet misidentified asa high Irel

electron. Tight criteria to reject photon conversions [21] are re-quiredforbothpromptandnot-promptelectrons.

The jet momentum is determined from the vectorial sum of all particle momentain thejet, andis found insimulation stud-ies tobe within5 to10%ofthe truemomentumoverthe whole

pT spectrum and detector acceptance.Jet energy corrections are

obtainedfromsimulationstudiesandconfirmedwithin situ mea-surementsthrough thebalancein dijet,multijet,photon

+

jet,and leptonicZ

+

jetevents[28].Inthecentralregion,thejetenergy res-olutionisapproximately15%at10 GeV,8%at100 GeV,and4%at 1 TeV. Jetsreconstructed atangulardistances



R

<

0

.

4 from the selectedleptonsarenotconsideredforfurtheranalysis.Asthe re-gion 2

.

7

<

|

η

|

<

3

.

0 isparticularlyaffected bynoise, eventswith jetsof pT

<

50 GeV inthatregionarerejected.

Jetsthatoriginatefromthehadronizationofab quarkare iden-tified(tagged)usingthecombinedsecondaryvertex(CSVv2) algo-rithm [29,30],which combinesvarious track-basedvariableswith secondary-vertexvariablestoconstructadiscriminatingobservable in theregion

|

η

|

<

2

.

4. Atthechosen operating point,theCSVv2 algorithmhasanefficiencyofabout83%tocorrectlytagb jetsand aprobabilityof10%formistagginggluonsandlightquarks,as es-timatedfromsimulationstudiesofmultijetevents.

The missing transverse momentum vector



pmiss_T is defined as the projection onto the plane perpendicular to the beam axis of the negative vector sum of the momenta of all recon-structed PF objects in an event. Its magnitude is denoted by

pmiss_T . The transverse mass of the W boson is defined as mW_T

=



2pTpmissT

[

1

−

cos

(φ)

]

, where pT is the transverse momentum

oftheleptonproduced inthe W bosondecay,and

φ

isthe dif-ference in azimuth between the direction of the lepton and the directionof



pmiss

T .

4. Simulatedevents

MonteCarlosimulatedeventsareusedextensivelyinthis mea-surementto evaluate thedetector resolution,theefficiencies and acceptance, and to estimate the contributions from background processes that have topologies similar to the trilepton tZq final state.

The tZq signal samples are generated at NLO precision using the MadGraph5_amc@nlo 2.2.2package [15].Thetwomain back-ground processes, WZ

+

jets and top quark pair production in association with vector bosons (ttZ and ttW), are also simulated withthesameeventgenerator,withuptooneadditionalhadronic jet at NLO. Other minorbackgrounds are ZZ and ttH production, for whichwe use theNLO generators MadGraph5_amc@nlo and powheg_{v2.0 [31–36],respectively,andtWZ production,generated} at LO accuracy using MadGraph5_amc@nlo.The PDF set NNPDF 3.0isusedinallgenerators.Thesimulatedsamplesareinterfaced to pythia 8.205 [37] with the CUETP8M1 tune [38] for the par-ton showerandhadronization.Thedetectorresponseissimulated usingthe Geant4package [39].

The eventsaresimulatedinfinal statesthat includedecaysto electrons, muons, and

τ

leptons. Atop quark mass of172.5 GeV isassumed. Multipleminimum-biaseventsgeneratedwith pythia are added toeach simulated eventto mimicthe presence ofPU,

with weights that reproduce the measured distribution of the numberofPUvertices.

Theeventsamplesare normalizedto theirexpectedcross sec-tions,obtainedfromNLO calculationsforall processes,exceptfor tWZ,whichisestimatedatLOaccuracy.

Correctionfactorsthatdependonthe pT and

η

ofthejetsand

leptonsareappliedtothesamples,sothattheresolutions,energy scales, andefficiencies measured indata are well reproduced by thesimulation.Thecorrectionsincludeanextrasmearingofthejet energy,whichhasabetterresolutioninthesimulationthanfound indata,andscalefactorsthat account fordifferentefficienciesin leptonidentificationandreconstruction.Theshapeofthe distribu-tionintheCSVv2discriminantisoneofthevariablesusedinthe multivariateanalysistoextractthesignal.Thesimulatedshapehas beencorrected [29,30] toassurethat thebtaggingefficiencyand purityvariablesreproducethosefoundindata.

One of the most abundant background sources in the three-leptonfinalstatearisesfromeventswithatleastoneNPL.Unlike allother backgrounds,whicharemodelledby MCsimulation,the samplesusedtoestimatetheNPLbackgroundcontributionare ob-tainedfromthedata,asdescribedinSection6.2.

5. Eventselection:signalandbackgroundcontrolregions

Theevent selectionmakes use oftZq event candidateswhere t

→

Wb,W

→

l

ν,

andZ

→

l +l −,

tZq

→ (

t

→

bl

ν

) (

Z

→

l +l −

)

q

,

where l and l are either electrons or muons, coming from the W or Z boson decay, respectively, asopposed to generic leptons (including

τ

leptons),whichhavebeendenotedby



.Asstatedin Section 1, l includes a small contribution from W

→

τ ν

decays, withthesubsequentdecayofthe

τ

intoelectrons ormuons. The finalresultwillbegivenforalldecaymodestoagenericlepton,



. Insingletopquarkproduction,theassociatedrecoiljetusually fol-lowsthedirectionoftheincomingproton,soitisdetectedinthe veryforwardregionsofthedetector.Forthisreason,weselectjets intheextendedpseudorapidity range

|

η

|

<

4

.

5.Giventhe tracker acceptance,b-taggedjets are confinedto the

|

η

|

<

2

.

4 range. All jets,bothtaggedanduntagged,arerequiredtohavepT

>

30 GeV.

Thebaselineselectionfortheanalysisconsistsinexactlythree leptons, two of which have the same flavour, are oppositely charged, and have an invariant mass compatible with the Z bo-son mass within 15 GeV. Electrons and muons are required to have pT

>

25 GeV,andto bemeasured within

|

η

|

<

2

.

5 and 2.4,

respectively.Toreduce backgroundsfromfourormore leptonsin thefinal state, e.g. from ZZ, ttZ,andttH,eventscontaining addi-tionalleptonswith pT

>

10 GeVandpassinglooseridentification

criteriaareremovedfromtheanalysis.

Severalother SM processes,some ofwhich have much larger crosssections than expectedfortZq, contain three reconstructed leptons in the final state. Out of these, the most important are the WZ

+

jets, the ttZ, and those contributing to the NPL back-ground. For the first two, the three-lepton topology is identical to tZq:two oppositely chargedleptons of same flavour decaying fromtheZ boson,andathirdhigh-pT,isolatedlepton.ThettZ

pro-ductionforthe four-leptonfinal state hasa smallercrosssection than that forthe three-lepton final state, andis also suppressed bythe alreadymentioned vetooneventswithfour ormore lep-tons.Althoughthemisidentificationrateperlepton,especiallyfor muons,issmall,thecrosssectionsoftheprocessesproducingthe NPLbackground (dominated by Drell–Yan production in associa-tionwithjets,DY

+

jets,andtt production)areordersofmagnitude largerthantheexpectedtZq crosssection,makingNPLoneofthe mostimportantbackgroundstothethree-leptonfinalstate.

For the tZq final state, two jets are expected, one of which arises from a b quark. In the ttZ three-lepton final state, two b jetsare expected. However, given the inefficienciesof the b tag-ging algorithm, one of the two b jets maybe untagged, leading to afinal state identicalto thesignal. Likewise,one ofthe bjets produced by gluon splittingin theWZ

+

jets final statesmaybe tagged,or,mostfrequently,light-flavourjetsfromWZ

+

jets pro-duction canbe mistaggedasb jets, againresultingina topology identicaltothesignal.

To reduce the impact of the background-related uncertainties onthemeasurement ofthe tZq yield,we proceedasfollows.The baseline three-leptonselectionissubdividedintothreeregions of interest, one enriched in tZq events, another selected to contain mostly ttZ events, and a third containing mostly WZ

+

jets and NPLbackground events. The final analysisperforms a simultane-ous fit to these three regions, so that the signal cross section is determined andthe normalizations of themain backgrounds are betterconstrained.

The three regions are defined according to their jet and b-taggedjetmultiplicities,asfollows:

1. 1bjet (signalregion):definedtoselecteventsfromtZq produc-tionwithoneb jetandonerecoilingjet. Eventswithathird jetarealsoincluded,tocovercaseswhereanadditionaljetis producedbyradiation.

2. 2bjets control region (ttZ enriched): defined by requiring at leasttwojets, withatleasttwoofthembtagged,enhancing therebytheyieldinttZ events.

3. 0bjet control region(WZ

+

jets enriched): definedby atleast onejet,butnob-taggedjets, selectedasmostlikely originat-ingfromaWZ process.SincethemajorityofDY

+

jets events alsodonotcontainbjets,thisregionisalsorichinNPL back-groundevents.

6. Shape-basedanalysis

The tZq cross section is extracted from a binned maximum-likelihoodfittothedistributions intheBDTdiscriminators(tobe definedlater)inthe2bjets and1bjet regions,andtothemW_T dis-tributioninthe0bjet region.Normalizeddistributions(templates) are constructed using thesevariables in their respective regions, foreachofthefourfinalstates(eee,eeμ,eμμ,and

μμμ

),adding upto12distributionsthataresimultaneouslyfitted.

6.1. InputnormalizationoftheSMpredictions

Theinput(pre-fit)normalizationsofthesimulatedbackgrounds reflect their corresponding theoretical cross sections. The contri-butions from WZ

+

b, WZ

+

c, and WZ

+

light-flavour jets in the WZ

+

jets MC eventsare separated usinggenerator-level informa-tion, and considered as independent backgrounds in all steps of theanalysis.Thisprovidesabettermodellingoftheheavy-flavour contentoftheWZ

+

jetssample, andavoidsrelyingontheflavour contentoftheMCsimulation.

6.2. TheNPLbackground

The templatesforthe NPLbackgroundare basedondata.The origin of not-prompt leptons depends on the lepton flavour. For muons, the dominantsource isthe semileptonicdecay of heavy-flavourhadrons.Inthecaseofelectrons,thedominantsourcesare photon conversions and light hadrons that are misreconstructed as electrons. The not-prompt electrons and muons are therefore treatedasseparatebackgroundsources.

Thebackgroundeventscontainingnot-promptleptonsoriginate from,inorderofimportance,DY

+

jetsprocesses,tt events contain-ing twoleptons, andWW and tW processes.Each ofthese back-groundsources containtwo prompt andonenot-prompt leptons. GiventhelowprobabilitythatanNPLisidentifiedasaprompt lep-ton,thecontributionfromeventswithmorethanoneNPLis neg-ligible. Not-promptelectron (muon) templates are obtained from eventscontaining exactlyone not-prompt electron (muon), iden-tified as described in Section 3,and two prompt leptons (either electrons or muons). In the NPLsample, the not-prompt leptons canbe associated eitherwiththe topquark orwith theZboson candidates.

The samples used to obtain the NPL background templates arequitecopious, typicallyhavingtwo ordersofmagnitudemore events than the signal sample obtainedwith the baseline selec-tion.Whiletheshapesofthedistributionsusedinthemultivariate analysis are provided by templates, their normalizations are de-terminedthrougha two-stepprocedure.Inthefirst step,themW_T

distributioninthe0bjet controlregionprovidesthenormalization of all NPLcomponents, independently in the four channels. This fixes the relative NPLnormalization ofthe templates in the four channels.Inasubsequentstep,thenot-promptelectronandmuon yields are treated as free and independent parameters, in a si-multaneous fitof the0bjet/1bjet/2bjets regions. Thissecond step representsthefinalfitusedtoprovidetheresultsreportedinthis Letter.

The useofthe 0bjet regionto provide therelative NPLyields inthefourchannelsisjustifiedbythe dominanceoftheDY pro-cess as source of NPL background events in all three b tagging regions. To check the validity of the procedure, an independent analysisisperformedwheretheweightoftheDY background rel-ativetott productionissuppressedbymeansofmildrequirements onpmiss

T andmWT .Inthiscross-checkanalysis,therelative

normal-izationsofthenot-promptelectronandmuonbackgroundsareleft freeinthefourchannels, andtheresultsareobtainedinasingle commonfit.Thisalternativeproceduregivessimilarfinalresults.

6.3. Multivariateanalysis

The signal extraction relieson a simultaneous fit to the data inthe three regions definedin Section 5,to better constrainthe backgroundsinthesignalregion.

Twomultivariatediscriminators,basedonobservablesfromthe 1bjet and 2bjets regions, are usedto enhance theseparation be-tween signal and background processes. The discriminators are based on theBDT algorithm [20] implemented in the toolkit for multivariateanalysisTMVA [40].TheBDTistrainedusingthe sim-ulatedsamplesdescribedinSection4.

SeveralobservablesserveasinputvariablesfortheBDT.These includethereconstructedtopquarkmassanddistributionsof vari-ablesreflectingthekinematics andtheanglesoftherecoilingjet, ofthetopquark,andoftheZ boson,aswellasthoseoftheir de-cay products. Once the two oppositely charged leptons of same flavour are identified as Z boson decay products, the additional leptonisassumedtoarisefromthedecayW

→

l

ν.

The longitudi-nalcomponentoftheneutrinomomentumiscalculatedusingthe W mass constraintforthel

+

ν

system, andassuming the event

pmiss_T to be equal to the transverse momentum of the neutrino. ThereconstructedW bosoncandidateisthenassociatedtoab-jet candidate forthe t

→

Wb hypothesis.The b-jet candidateis the taggedjet.Iftwosolutionsare foundforthelongitudinal compo-nentoftheneutrinomomentum,orifmorethanonejetistagged (inthe2bjets region),thesolutiongivingtheWb candidate invari-antmassclosest tothatofthe topquark istaken.The remaining jet withthe largest pT istakenastherecoiling jet.The

informa-tion relatedto btaggingisalsousedthroughthe distributionsof theCSVv2discriminant [29,30] andtheb-taggedjetmultiplicity.

Variables computed usingthe matrix element method (MEM) [41] are alsoincludedinthemultivariate analysis. Aweight wi,α

iscomputedforeacheventi andhypothesis

α

(where

α

iseither signal,ttZ,orWZ

+

jets)as wi,α

(



)

=

1

σ

α



d



α

δ

4



pμ₁

+

pμ₂

−



k>1 pμ_k



×

f

(

x1

,

μ

F

)

f

(

x2

,

μ

F

)

x1x2s





M

α

(

p_kμ

)





2 W

(



|

α

),

where:

σ

α is the cross section;



 are the 4-momenta of the

reconstructed particles; d



α is the element of phase space

cor-responding to parton-level variables with momentum conserva-tion enforced [42]; f

(

x

,

μ

F

)

are the PDFs, where

μ

F is the QCD

factorization scale, computed using the NNPDF2.3LO set [43];

|

M

α

|

2 is the squared matrix element, computed with

Mad-Graph5_amc@nlo standalone [15] at LO accuracy, in a narrow-width approximationfor thetop quarks; and W arethe transfer functions forjet energy and pmiss_T , relatingparton-level variables toreconstructedquantities,evaluatedfromsimulationstudiesand normalizedtounity.

Forall threeprocesses,the massoftheW boson arisingfrom thetopquark decayfollowsaBreit–Wigner distribution,as speci-fiedinthematrixelement.Thevirtual Z bosoninthettZ hypoth-esisalsofollowsaBreit–Wignerform,andinterferencewith

γ

∗ is included in the matrixelement. The matrix element provided at LOin MadGraph5_amc@nlo does notcontain additionaljetsthat arepresentinthedata.ToevaluatethematrixelementatLO,the momentumofthetZq systemmusthaveanulltransverse compo-nent.ThetZq momentumiscomputedasthesumofthemomenta ofallparticlesfromthetZq decay.Aninverseboostcorresponding totheoppositeofthetZq pT isappliedtoallfinalstate particles,

correctingthereby anyrecoilingjetsnot presentintheLOmatrix element.

In computingthe MEM weights, jetswith the highest CSVv2 discriminantvaluesareassignedtothebquarksfromtopdecays. Amongtheremainingjets,uptotwojetswiththehighest

|

η

|

(sig-nalhypothesis),withinvariant massclosesttotheW bosonmass (forthettZ hypothesis),orwiththehighestpT(fortheWZ

+

jets

hypothesis),areassignedtothequarksatpartonlevel.Jetsinthe 1bjet regionmaynotbematchedtoallparton-levelquarksneeded inthettZ hypothesis(twob-quarksandtwonot-bquarks).Insuch cases, thettZ weightcan still be computedby leavingthe phase spaceofthemissingjetsunconstrainedintheintegral.

The finalweightforeachhypothesis

α

istakenastheaverage oftheweightscomputedforeachleptonandjetpermutation.The MEM weights are combined in likelihood ratios of signal to the combinationofttZ andWZ

+

jets inthe1bjet regionandsignalto ttZ inthe2bjets region.Theseratiosareincludedasinputvariables totheBDT.Inaddition,themaximumvalue ofthefunctionbeing integratedisalsoincluded,correspondingtotheMEMscore associ-atedtothemostprobablekinematicconfiguration.Eightvariables weretestedandfivewereretainedforthetraining;theotherthree were excluded because they were highly correlated with other variables orhada negligible discriminantpower. The normalized BDT discriminators for signal and backgrounds in the 1bjet and 2bjets regions are shown in Fig. 2 for BDT trainings with and withoutMEMvariables.IncludingtheMEMvariablesimprovesthe expectedsignificancebyabout20%.

The predictions forsome of the mostdiscriminating variables intheBDT forthe1bjet and2bjets regionsare comparedtodata inFig.3.ThesevariablesarethelargestCSVv2discriminantvalue amongallselectedjets,thelogarithmoftheMEMscoreassociated

Fig. 2. NormalizeddistributionsoftheBDToutputforsignal(thicklines)and back-grounds(thinlines)fromsimulationforthe1bjet (top)and2bjets (bottom)regions. ThediscriminatorsincludingandexcludingMEMvariablesintheBDTtrainingare shown,respectively,assolidanddashedlines.Contributionsfromthefour consid-eredchannelsareincludedinthesignalsandbackgrounds.

tothemostprobabletZq kinematicconfiguration,andthe



R

sep-arationbetweenthe jet identified asa bquark andthe recoiling jet.Fig.4shows,foreventsinthe0bjet region,the

η

andpT

dis-tributionsoftherecoilingjet,

η

(

j

)

andpT

(

j

)

,andtheasymmetry

ofthetopquarkdecaylepton,definedastheproductofitscharge andpseudorapidity, ql

|

η

(

l

)

|

.Thedistributions inFigs.3and4are

showncombinedforthefourchannels:eee,eeμ,eμμ,and

μμμ

. The quadratic sumof the systematicand statistical uncertainties onthe predictions is shownasa hatched band. The pulls ofthe distributions,defined ineach bin asthe difference betweendata andprediction,dividedbythequadraticsumoftotaluncertainties inthepredictions(systematicandstatistical)andthedata (statis-tical),areshownatthebottomoftheplots.

ThecompletelistofvariablesusedinthetwoBDTsisgivenin AppendixA.

7.Systematicuncertainties

Differentsourcesofsystematicuncertaintycanaffectthe num-berofeventspassingtheselections, ortheshapeofthe distribu-tionsusedinthemultivariateanalysis.

The sources of systematic uncertainty considered correspond to:

•

Luminosity:An uncertaintyof 2.5% onthe sample integrated luminosity [44] is propagated asa normalization-only uncer-taintyforthetotalpredictedyields.

•

Correction factors applied to the signal and simulated back-grounds:

– Pileup:Thenumberofsimulatedpileupeventsiscorrected tomatchthe measured numberofeventsindata. The un-certaintyonthetotalinelasticcrosssectionistakenas4.6%, andconsideredonlyintheshapesofthedistributions. – Trigger:Thetriggerefficiencyisestimatedtobe near100%

both in data and in simulation. Variations in normaliza-tion of

±

1% (

±

2%) are applied to the predicted yields in the

μμμ

andeeμ(eμμ andeee) channelstoaccount for residual differences in trigger efficiencybetween data and simulation.

– Lepton selection: The factors used to correct the simu-lateddistributionsforleptonisolationandidentification ef-ficienciesarevaried bytheiruncertainty,affectingboth the shapesandthenormalizations.

– Jet energy scale and resolution: The jet energy scale and resolutioncorrections are bothvaried by their uncertainty. Theobservedchange ispropagatedtoall relatedkinematic quantities, in particular



pmiss_T . These uncertainties affect boththeshapeandthenormalizationofthesimulated dis-tributions.

– btagging:Thescalefactorsrelatedtobtaggingand mistag-gingefficiencies arevariedbyonestandarddeviation.Eight independent changes are considered, including two types of statistical uncertainties on the b-, c-, and light-flavour componentsoftheMCeventsamples,light-flavour contam-inationofthebtaggingscale factors,andbquark contam-inationin themistagscale factors.Thereis one“nuisance” parameterforeachvariation.Both shapeandnormalization areaffected.

•

The normalization of the simulated backgrounds: The input normalizations of all simulated background distributions are assumed to have a relative uncertainty of 30%. This reflects the theoretical uncertainties on the corresponding cross sec-tions, scaled up by a factor of two or more, to account for possible limitationsin the simulations inthe phase space of theanalysis.

•

TheNPLbackgroundestimation:Theshape-related uncertain-tieson thebackgrounds involving not-prompt leptons, deter-minedwithcontrolsamplesindata,areestimatedbyvarying the isolation criteriaused to determinethe NPLsample. The shape variations of not-prompt muons andelectrons involve differentnuisanceparameters.

•

ThescaleandPDFuncertaintiesforsimulatedsignal(tZq)and backgroundprocesses:Theseuncertaintiesaffecttheshapeof thesignalaswell astheshapeandnormalizationofthe sim-ulated background distributions, except for tWZ events, for which only normalization uncertainties from scales and PDF areconsidered.

– The renormalizationandfactorization scales, atthe matrix elementlevel,are setto anidenticalvalue, whichdepends onthe eventgenerator andonthe simulatedprocesses.In particular, the scales for the simulated signal are set to



(

m2

₊

_p2

T

)/

2, wherethe sumrunsover all particles in

thefinalstate.Thescalesarevariedup anddownbya fac-torof2.

– The renormalization and factorizationscales at the parton showerlevel,identicaltothematrixelementscales,arealso variedbyfactorsof0.5and2;thisuncertaintyisonly eval-uatedforthesignalsample.

Fig. 3. Data-to-predictioncomparisonsinthe1bjet region(signal-enriched,upperrow)andinthe2bjets region(lowerrow)forthelargestCSVv2discriminantvalueamong allselectedjets(left),thelogarithmoftheMEMscoreassociatedtothemostprobabletZq kinematicconfiguration(centre),andtheR separationbetweenthebquark andtherecoilingjet(right).Thedistributionsincludeeventsfromallfinalstates.Underflowsandoverflowsareshowninthefirstandlastbins,respectively.Thepredictions correspondtothenormalizationsobtainedafterthefitdescribedinSection8.Thehatchedbandsincludethetotaluncertaintyonthebackgroundandsignalcontributions. Thepullsinthedistributionsareshowninthebottompanels.(Forinterpretationofthecoloursinthefigure(s),thereaderisreferredtothewebversionofthisarticle.)

Fig. 4. Data-to-predictioncomparisonsinthe0bjet regionfortheη(left)and pT(centre)distributionsoftherecoilingjet,andfortheasymmetryofthetopquarkdecay

– The PDF uncertainties are evaluated by the root-mean-squareoftheresultsfrom100variationsoftheNNPDFset.

8. Results

Thetool usedfor thisstatisticalanalysis [45] is basedon the RooStatsframework [46].Theanalysisisperformedbeginningwith abinnedlikelihoodfunction

L

(

data

|

μ

, θ )

=



i

μ

si

(θ )

+

bi

(θ )

+

α

eBei

(θ )

+

α

μB μ i

(θ )



Ni Ni

!

×

e−μsi(θ )−bi(θ )−αeBei(θ )−αμ Bμi(θ )

_,

whereNi istheobservednumberofeventsineachbin,andsi

(θ )

andbi

(θ )

are the expectedsignal and backgroundyields in each

bin,respectively,normalizedasdiscussedintheprevioussections andtaking into account all systematic uncertainties, represented by

θ

, as nuisance parameters associated with log-normal priors. TheBe_i,μ

(θ )

aretheyieldsofNPLbackgrounds,andtheparameters

α

e,μ,whichdeterminethenormalizationoftheNPLbackgrounds,

areleft freeinthefit.The simultaneousfittothe datatemplates (BDTdiscriminatorsormW

T, dependingon theregion)inthefour

channelsmaximizes

L(

data

|

μ

,

θ )

,fromwhichthemeasuredcross section

σ

(

t



+



−q

)

isextractedaccordingtoitsrelationtothe sig-nalstrength

μ

=

σ

(

t



+

_

−_q

₎

σ

SM

₍

_t

_

+

_

−_q

₎

,

wherethecrosssectionisdefinedforanydecayofthetopquark, andany decayof the Z boson to charged leptons. The reference crosssection is

σ

SM

₍

_t

_

+

_

−_q

₎

₌

₉₄

_.

_{2 fb, form}

+−

>

30 GeV.The measurementimpliesan extrapolationfromtheconsidered phase space (Section 5), defined as containing three leptons in the fi-nal state (l +l −l), and an additional constraint for m+− to be within15 GeVoftheZbosonmass.Theacceptance,definedasthe fractionoft



+



−q events fulfillingtheeventselection criteria, is estimatedfromthesimulatedtZq sampleas1.81%,combiningthe 1bjet,2bjets, and 0bjet regions.All nuisanceparameters are con-strainedinthefit.

The distributions resulting from the fit (post-fit) of the three variables used as templates in the measurement are shown in Fig.5. Althoughthe fitis performedforeach channel,the figure displaystheresultscombiningthefourchannels.

Table1showstheresultsforthepost-fityields, separatelyfor each channel, in the 1bjet region. The last two rows show the totalnumber ofpredicted(“Total”) andobserved(“Data”) events. Thelastcolumndisplaystheratioofthepost-fittopre-fit predic-tions, Npost-fit

/

Npre-fit,accountingforthesystematicuncertainties. The post-fit background normalizations are close to the pre-fit values for most of the background processes. The event yields for the WZ

+

light-flavour jets background preferred by the fit issignificantly lower than theSM prediction.This feature,which mightreflectthesomewhatworse agreementbetweensimulation and data for some bins of jet multiplicity [47], does not affect the measurement, as verified by the following checks. First, the predictedshapesof thekinematic variables relevantto the anal-ysis are verified to describe the data in the WZ

+

light-flavour enriched region. The analysis is then repeated with the WZ

+

light-flavour normalizationrelative uncertainty increased to 50%, leavingtheresultsunchangedwithinabouthalfapercent.Finally, theWZ

+

light-flavouryieldisfittedsimultaneouslywiththeNPL

background yields using only the 0bjet region, and the resulting

Npost-fit

/

Npre-fit scale factor is found to be 0

.

73

±

0

.

11, in good agreementwiththeresultsofTable1.The post-fitnumberoftZq eventsinthe1bjet regionis32.3.The0bjet and2bjets control re-gions (notshown)also containtZq events, withpost-fit yields of

≈

23and19events,respectively. TheobservedtZq signalstrengthis

μ

=

1

.

31+₋0_0..₃₃35(stat)+₋0₀._.31₂₅(syst)

,

fromwhich,usingthe referenceNLO crosssection, themeasured crosssectionisfoundtobe

σ

(

t



+



−q

)

=

123₋+33₃₁(stat)+₋29₂₃(syst) fb

,

form+−

>

30 GeV,where



stands for electrons,muons, and

τ

leptons. The best-fit signal strength andcrosssection, as well as anapproximate68%CLinterval,areextractedfollowingtheprofile likelihoodscan proceduredescribed inRef. [48]. Thefitisredone withoutincludingthesystematicuncertainties,toevaluatethe sta-tisticaluncertaintyoftheresult.Thequotedsystematicuncertainty isthencalculatedasthedifferenceinquadraturebetweenthe68% CLintervalsobtainedinthenominalfitandinthefitwithout sys-tematicuncertainties.Theprecisionofthemeasurementislimited bythestatisticaluncertainty.Among thesystematicuncertainties, thedominatingonesarisefromthenormalizationoftheNPL back-ground (left free in the fit), the scale dependence at the parton shower level, the b tagging efficiency, and the normalization of thettZ background.Thecorrespondingobserved(expected) signif-icanceagainstthebackground-onlyhypothesisis3.7 (3.1)standard deviations,withan observedstatisticalp-valueof0.0001.The ex-pectedsignificanceis estimatedfroman Asimovtoy dataset[49]. The68%CLintervaloftheexpectedsignificanceis1.4–5.9.

Potential biases from the background yields used as input have beensearched for. First, the analysiswas repeatedto mea-sure simultaneously the tZq and ttZ cross sections, in addition to determining the NPL background normalization. The tZq sig-nal strength increases by less than 1%, whereas the observed and expectedsignificances decrease by about 1%. Then, the not-prompt muon and electron normalizations are set to their in-put values, described as the first step in Section 6.2, and al-lowed to vary in the fit as Gaussian constraints of 100% uncer-tainty. In thiscase, both the tZq signal strength and the signifi-cancesincreasebyabout10%,whiletheuncertaintiesonthesignal strength increase by about 5%. In addition, the measurement is repeatedin each channel, andthe measured signal strengths are foundtobe1

.

32+₋1_0..₉₉14

,

0

.

66+₋0₀._.78₆₃

,

0

.

01+₋0₀._.97₀₁,and1

.

22+₋0₀._.75₆₃forthe eee, eeμ, eμμ, and

μμμ

channels, respectively.The highest ob-served (expected) significance is 2.1 (1.9) standard deviations in the

μμμ

channel. Finally,theresultswere verifiedina counting analysis, usingtheyieldsobserved incontrolregions selected us-ingsimilarcriteriatothoseofthe1bjet,2bjets,and0bjet regions. The simulatedbackgroundsare normalizedaccordingtotheir SM predictions,whilethenormalizationoftheNPLcontributions fol-lows the procedure described in Section 6.2 as the first step of theNPLnormalizationintheshapeanalysis. Theresultsfromthe countingandshapeanalysesareinagreement.

9. Summary

The associated production cross section of a single top quark and a Z boson was measured using data from pp collisions at 13 TeV collectedbytheCMSexperiment, correspondingtoan in-tegrated luminosity of 35.9 fb−1. The measurement uses events containing three charged leptons in the final state. Evidence for tZq productionis foundwithan observed (expected)significance

Fig. 5. Templatedistributionsusedfor signalextraction.Left:BDTdiscriminator inthe1bjet region; centre:BDToutputinthe2bjets controlregion;right: mW T inthe

0bjet controlregion.MoredetailsaregiveninthecaptionofFig.3.

Table 1

Observedandpost-fitexpectedyieldsforeachproductionprocessinthe1bjet region.Theyieldsofcolumns2–5correspondtoeachchannel,andcolumn6displaysthetotal forallchannels.Thelastcolumndisplaystheratiobetweenpost-fitandpre-fityields.

Process eee eeμ eμμ μμμ All channels Npost-fit_/Npre-fit

tZq 5.0±1.5 6.6±1.9 8.5±2.5 12.3±3.6 32.3±5.0 – t¯tZ 3.7±0.7 4.7±0.9 6.1±1.2 8.0±1.5 22.4±2.2 0.9±0.2 t¯tW 0.3±0.1 0.3±0.1 0.7±0.2 0.6±0.2 1.9±0.3 1.0±0.2 ZZ 4.8±1.3 3.2±0.9 9.0±2.5 7.8±2.2 24.7±3.6 1.3±0.3 WZ+b 3.0±0.9 3.4±1.1 4.6±1.4 5.5±1.7 16.6±2.6 1.0±0.2 WZ+c 9.0±2.4 13.7±3.7 18.0±4.9 24.2±6.5 64.8±9.3 1.0±0.2 WZ+light 12.2±1.6 16.6±2.0 22.4±2.8 29.1±3.4 80.3±5.1 0.7±0.1 t¯tH 0.6±0.2 0.9±0.3 1.0±0.3 1.5±0.4 4.0±0.6 1.0±0.2 tWZ 1.0±0.3 1.3±0.4 1.7±0.5 2.4±0.7 6.5±1.0 1.0±0.2 NPL: electrons 19.2±3.1 0.6±0.1 17.9±2.8 – 37.7±4.2 – NPL: muons – 7.2±2.3 31.1±9.9 15.3±4.9 53.6±11.3 – Total 58.8±4.8 58.4±5.5 121±12 107±10 345±18 Data 56 58 104 125 343

of3.7 (3.1)standarddeviations.Thecrosssectionismeasuredtobe

σ

(

t



+



−q

)

=

123+₋33₃₁(stat)+₋29₂₃(syst) fb,form+−

>

30 GeV,where



stands forelectrons,muons, or

τ

leptons.Thisvalueis compat-ible with the next-to-leading-order standard model prediction of 94

.

2

±

3

.

1 fb.

Acknowledgements

WecongratulateourcolleaguesintheCERNaccelerator depart-ments for the excellent performance of the LHC and thank the technicalandadministrativestaffs atCERN andatother CMS in-stitutes for their contributions to the success of the CMS effort. Inaddition,wegratefullyacknowledgethecomputingcentresand personneloftheWorldwideLHCComputingGridfordeliveringso effectivelythe computinginfrastructureessential to ouranalyses. Finally, we acknowledge the enduring support for the construc-tionandoperation oftheLHCandthe CMSdetectorprovidedby thefollowingfundingagencies:BMWFWandFWF(Austria);FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MOST, and NSFC (China); COLCIEN-CIAS(Colombia);MSESandCSF(Croatia);RPF(Cyprus);SENESCYT (Ecuador); MoER, ERC IUT, and ERDF (Estonia); Academy of Fin-land,MEC,andHIP(Finland);CEAandCNRS/IN2P3(France);BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NIH (Hun-gary);DAEandDST(India);IPM(Iran);SFI(Ireland);INFN(Italy); MSIPandNRF(RepublicofKorea);LAS (Lithuania);MOE andUM (Malaysia); BUAP, CINVESTAV,CONACYT, LNS, SEP, and UASLP-FAI

(Mexico); MBIE (New Zealand); PAEC (Pakistan); MSHE and NSC (Poland);FCT(Portugal);JINR(Dubna);MON,ROSATOM,RAS,RFBR andRAEP(Russia);MESTD (Serbia); SEIDI,CPAN,PCTIandFEDER (Spain);SwissFundingAgencies(Switzerland);MST(Taipei); ThEP-Center, IPST, STAR, and NSTDA (Thailand); TUBITAK and TAEK (Turkey);NASU andSFFR (Ukraine);STFC(United Kingdom);DOE andNSF(USA).

Individuals have received support from the Marie-Curie pro-gramme and the European Research Council and Horizon 2020 Grant, contractNo. 675440 (EuropeanUnion); theLeventis Foun-dation; the A.P. Sloan Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science Policy Office; the Fonds pourlaFormationàlaRecherchedansl’Industrieetdans l’Agricul-ture (FRIA-Belgium); the Agentschap voorInnovatie door Weten-schap en Technologie (IWT-Belgium); the Ministry of Education, YouthandSports(MEYS)oftheCzechRepublic;theCouncilof Sci-enceandIndustrialResearch,India;theHOMINGPLUSprogramme of the Foundation for Polish Science, cofinanced from European Union, RegionalDevelopmentFund, theMobilityPlusprogramme oftheMinistryofScienceandHigherEducation,theNational Sci-ence Center (Poland), contracts Harmonia 2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543,2014/15/B/ST2/03998,and2015/19/B/ ST2/02861, Sonata-bis 2012/07/E/ST2/01406; the National Priori-tiesResearch Programby Qatar NationalResearchFund;the Pro-grama Severo Ochoa del Principado de Asturias; the Thalis and Aristeia programmes cofinanced by EU-ESF and the Greek NSRF; theRachadapisekSompotFundforPostdoctoralFellowship,

Chula-Table A.2

DescriptionofthevariablesusedintheBDTs.ThesymbolY(N)inthethirdandfourthcolumnsindicatesthatthevariablewas(wasnot)usedinthe1bjet and2bjets BDTs.

Variable description 1bjet 2bjets

1 CSVv2 algorithm discriminant Y Y

2 R separation between the jet identified as a b quark and the recoiling jet Y Y

3 ηof the recoiling jet Y Y

4 pTof the recoiling jet Y Y

5 ηof the Z boson Y Y

6 Top quark mass Y Y

7 R separation between the top quark decay lepton and the jet closest to it Y Y

8 Top quark decay lepton asymmetry Y Y

9 Azimuth angle separation between the top quark decay lepton and the Z boson Y Y

10 Azimuth angle separation between the top quark decay lepton and the b quark Y N

11 ηof the top quark decay lepton Y N

12 ηof the jet with highest pT Y N

13 R separation between the top quark decay lepton and the recoil jet N Y

14 R separation between the Z boson and the top quark N Y

15 pTof the Z boson N Y

16 Number of b tagged jets N Y

17 Logarithm of the MEM score associated to the most probable tZq kinematic configuration Y Y

18 Logarithm of the MEM score associated to the most probable ttZ kinematic configuration N Y

19 Log-likelihood ratio of the tZq hypothesis against the ttZ hypothesis Y N

20 Log-likelihood ratio of the tZq hypothesis against the ttZ hypothesis Y N

with ttZ and tZq weights rescaled such that their mean values are similar

21 Log-likelihood ratio of the MEM weights for ttZ against ttZ+WZ hypothesis Y N

longkornUniversity andthe ChulalongkornAcademicintoIts 2nd CenturyProjectAdvancementProject (Thailand);theWelch Foun-dation,contractC-1845;andtheWestonHavensFoundation(USA).

Appendix A. Variablesusedintheshapeanalysis

Ashortdescriptionof thevariables usedinthe Boosted Deci-sionTreesinthe1bjet and2bjets regionsisgiveninTableA.2.The BDTsin the 1bjet regionand2bjets region used 16 and15 vari-ableseach, respectively,10 ofwhichcommonto thetwo regions (variables1–9and17inTableA.2).Fromthetotalof21variables, 16are relatedto the kinematic quantitiesassociated to the final stateobjects(1–16inTableA.2),whilefiveofthemarerelatedto theMEM(17–21inTableA.2).

References

[1] CDF and D0 Collaborations, Tevatron combination ofsingle-top-quark cross sections and determination of the magnitude of the Cabibbo–Kobayashi– Maskawa matrix element Vtb, Phys. Rev.Lett. 115(2015) 152003, https://

doi.org/10.1103/PhysRevLett.115.152003,arXiv:1503.05027.

[2] CDFandD0Collaborations,Observationofs-channelproductionofsingletop quarksattheTevatron,Phys.Rev.Lett.112(2014)231803,https://doi.org/10. 1103/PhysRevLett.112.231803,arXiv:1402.5126.

[3] ATLAS Collaboration,Comprehensive measurementsoft-channelsingle top-quarkproductioncrosssectionsat√s=7 TeV withtheATLASdetector,Phys. Rev.D90(2014)112006,https://doi.org/10.1103/PhysRevD.90.112006,arXiv: 1406.7844.

[4] ATLASCollaboration,Measurementoftheproductioncrosssectionofasingle topquarkinassociationwithaWbosonat8TeVwiththeATLASexperiment, J.HighEnergyPhys.01(2016)064,https://doi.org/10.1007/JHEP01(2016)064, arXiv:1510.03752.

[5] ATLASCollaboration,Evidenceforsingletop-quarkproductioninthes-channel

inproton–protoncollisionsat√s=8 TeV withtheATLASdetectorusingthe MatrixElementMethod,Phys.Lett.B756(2016)228,https://doi.org/10.1016/ j.physletb.2016.03.017,arXiv:1511.05980.

[6] ATLASCollaboration,Measurementoftheinclusivecross-sectionsofsingle top-quark and top-antiquarkt-channel production in pp collisions at √s=13 TeV with the ATLAS detector,J. High Energy Phys. 04(2017) 086,https:// doi.org/10.1007/JHEP04(2017)086,arXiv:1609.03920.

[7] ATLASCollaboration,Measurementofthecross-sectionforproducingaW bo-soninassociationwith asingletopquarkinpp collisionsat√s=13 TeV with ATLAS, J. High Energy Phys. 01 (2018) 063, https://doi.org/10.1007/ JHEP01(2018)063,arXiv:1612.07231,2016.

[8] CMSCollaboration,Measurementofthesingle-top-quarkt-channelcross sec-tioninppcollisionsat√s=7 TeV,J.HighEnergyPhys.12(2012)035,https:// doi.org/10.1007/JHEP12(2012)035,arXiv:1209.4533.

[9] CMSCollaboration,Observationoftheassociated productionofasingletop quarkandaWbosoninppcollisionsat√s=8 TeV,Phys.Rev.Lett.112(2014) 231802,https://doi.org/10.1103/PhysRevLett.112.231802,arXiv:1401.2942. [10] CMS Collaboration,Search for s-channelsingle topquarkproduction inpp

collisionsat √s=7 and8TeV,J.HighEnergyPhys. 09(2016)027,https:// doi.org/10.1007/JHEP09(2016)027,arXiv:1603.02555.

[11] CMSCollaboration,Crosssectionmeasurementoft-channelsingletopquark productioninppcollisionsat√s=13 TeV,Phys.Lett.B72(2017)752,https:// doi.org/10.1016/j.physletb.2017.07.047,arXiv:1610.00678.

[12] J.A.Aguilar-Saavedra,Topflavor-changingneutralinteractions:Theoretical ex-pectationsandexperimentaldetection,in:ParticlePhysicsPhenomenologyat HighEnergyColliders.Proceedings,FinalMeetingoftheEuropeanUnion Net-work,Montpellier,France,September26–27,2004,2004,p. 2695,http://www. actaphys.uj.edu.pl/fulltext?series=Reg\&vol=35\&page=2695, Acta Phys. Pol. B 35(2004)2695,arXiv:hep-ph/0409342.

[13] J.-L.Agram, J.Andrea,E.Conte,B.Fuks,D.Gelé,P.Lansonneur,Probingtop anomalous couplingsat theLHCwithtrilepton signaturesinthesingletop mode,Phys.Lett.B725(2013)123,https://doi.org/10.1016/j.physletb.2013.06. 052,arXiv:1304.5551.

[14] S.L.Glashow,J. Iliopoulos,L.Maiani,Weakinteractionswith leptonhadron symmetry, Phys. Rev. D 2(1970) 1285, https://doi.org/10.1103/PhysRevD.2. 1285.

[15] J. Alwall, R. Frederix,S. Frixione, V.Hirschi, F.Maltoni, O. Mattelaer, H.S. Shao, T. Stelzer,P. Torrielli, M. Zaro, The automated computation of tree-levelandnext-to-leadingorderdifferentialcrosssections,andtheirmatching to partonshower simulations,J. HighEnergy Phys. 07(2014)079, https:// doi.org/10.1007/JHEP07(2014)079,arXiv:1405.0301.

[16] R.D.Ball,V.Bertone,S.Carrazza,C.S.Deans,L.DelDebbio,S.Forte,A. Guf-fanti,N.P.Hartland,J.I.Latorre,J.Rojo,M.Ubiali,NNPDFCollaboration,Parton distributionsfortheLHCRunII,J.HighEnergyPhys.04(2015)040,https:// doi.org/10.1007/JHEP04(2015)040,arXiv:1410.8849.

[17] J.Campbell,R.K.Ellis,R.Roentsch,Singletopproductioninassociationwith aZbosonattheLHC,Phys.Rev.D87(2013)114006,https://doi.org/10.1103/ PhysRevD.87.114006,arXiv:1302.3856.

[18] CMS Collaboration, Search for associated production ofa Z boson with a single top quark and for tZ flavour-changing interactions in pp collisions at √s=8 TeV,J.HighEnergy Phys.07(2017)003,https://doi.org/10.1007/ JHEP07(2017)003,arXiv:1702.01404.

[19]ATLASCollaboration,Measurementoftheproductioncross-sectionofasingle topquarkinassociationwithaZbosoninproton–protoncollisionsat13TeV withtheATLASdetector,arXiv:1710.03659,2017.

[20] L.Breiman,J.Friedman,C.J.Stone,R.A.Olshen,ClassificationandRegression Trees, Chapman& Hall, New York,1984, http://www.crcpress.com/product/ isbn/9780412048418.

[21] CMSCollaboration,Performanceofelectronreconstructionandselectionwith the CMSdetectorinproton–protoncollisions at√s=8 TeV,J.Instrum. 10 (2015) P06005, https://doi.org/10.1088/1748-0221/10/06/P06005, arXiv:1502. 02701.

[22] CMSCollaboration,PerformanceofCMSmuonreconstructioninppcollision eventsat √s=7 TeV, J.Instrum.7(2012) P10002,https://doi.org/10.1088/ 1748-0221/7/10/P10002,arXiv:1206.4071.

[23] CMSCollaboration,TheCMSexperimentattheCERNLHC,J.Instrum.3(2008) S08004,https://doi.org/10.1088/1748-0221/3/08/S08004.

[24] CMS Collaboration, The CMStrigger system, J. Instrum. 12 (2017)P01020,

https://doi.org/10.1088/1748-0221/12/01/P01020,arXiv:1609.02366. [25] CMSCollaboration, Particle-flowreconstructionand globaleventdescription

withtheCMSdetector,J.Instrum.12(2017)P10003,https://doi.org/10.1088/ 1748-0221/12/10/P10003,arXiv:1706.04965.

[26] M.Cacciari,G.P.Salam,G.Soyez,Theanti-ktjetclusteringalgorithm,J.High

Energy Phys. 04(2008)063,https://doi.org/10.1088/1126-6708/2008/04/063, arXiv:0802.1189.

[27] M.Cacciari,G.P.Salam,G.Soyez,FastJetusermanual,Eur.Phys.J.C72(2012) 1896,https://doi.org/10.1140/epjc/s10052-012-1896-2,arXiv:1111.6097. [28] CMSCollaboration,JetenergyscaleandresolutionintheCMSexperimentin

ppcollisionsat8TeV,J.Instrum.12(2017)P02014,https://doi.org/10.1088/ 1748-0221/12/02/P02014,arXiv:1607.03663.

[29] CMSCollaboration,Identificationofb-quarkjetswiththeCMSexperiment,J. Instrum.8(2013)P04013,https://doi.org/10.1088/1748-0221/8/04/P04013. [30] CMSCollaboration, Identificationofbquarkjetsat theCMSExperiment in

theLHCRun2,CMSPhysicsAnalysisSummaryCMS-PAS-BTV-15-001(2016),

http://cds.cern.ch/record/2138504.

[31] P.Nason,AnewmethodforcombiningNLOQCDwithshowerMonteCarlo algorithms,J.HighEnergyPhys.11(2004)040,https://doi.org/10.1088/1126 -6708/2004/11/040,arXiv:hep-ph/0409146.

[32] S.Frixione,P.Nason,C.Oleari,MatchingNLOQCDcomputationswithparton showersimulations:thePOWHEGmethod,J.HighEnergyPhys.11(2007)070,

https://doi.org/10.1088/1126-6708/2007/11/070,arXiv:0709.2092.

[33] S.Alioli, P.Nason, C. Oleari,E.Re, A general frameworkfor implementing NLOcalculationsinshowerMonteCarloprograms:thePOWHEGBOX,J.High Energy Phys.06 (2010)043,https://doi.org/10.1007/JHEP06(2010)043,arXiv: 1002.2581.

[34] E.Re,Single-topW t-channel-productionmatchedwithpartonshowersusing thePOWHEGmethod,Eur.Phys.J.C71(2011)1547,https://doi.org/10.1140/ epjc/s10052-011-1547-z,arXiv:1009.2450.

[35] S.Alioli, P.Nason,C.Oleari,E.Re,NLOsingle-topproductionmatchedwith showerinPOWHEG: s- andt-channelcontributions,J.HighEnergyPhys.09 (2009)111,https://doi.org/10.1088/1126-6708/2009/09/111,arXiv:0907.4076. [36] T.Melia,P.Nason,R.Rontsch,G.Zanderighi,W+W−,WZandZZproductionin

thePOWHEGBOX,J.HighEnergyPhys.11(2011)078,https://doi.org/10.1007/ JHEP11(2011)078,arXiv:1107.5051.

[37] T.Sjöstrand, S.Ask,J.R.Christiansen,R.Corke, N.Desai,P.Ilten,S.Mrenna, S.Prestel,C.O.Rasmussen,P.Z.Skands,AnintroductiontoPYTHIA8.2, Com-put.Phys.Commun.191(2015)159,https://doi.org/10.1016/j.cpc.2015.01.024, arXiv:1410.3012.

[38] CMSCollaboration,Eventgeneratortunesobtainedfromunderlyingeventand multipartonscatteringmeasurements,Eur.Phys.J.C76(2016)155,https:// doi.org/10.1140/epjc/s10052-016-3988-x,arXiv:1512.00815.

[39] S.Agostinelli,etal.,GEANT4Collaboration,GEANT4:asimulationtoolkit,Nucl. Instrum.MethodsPhys.Res.,Sect.A506(2003)250,https://doi.org/10.1016/ S0168-9002(03)01368-8.

[40] H.Voss,A.Höcker,J.Stelzer,F.Tegenfeldt,TMVA,thetoolkitformultivariate dataanalysiswithROOT,in:XIthInternationalWorkshoponAdvanced Com-putingandAnalysisTechniquesinPhysicsResearch(ACAT),2007,p. 40,arXiv: physics/0703039,http://pos.sissa.it/archive/conferences/050/040/ACAT_040.pdf. [41] V.M.Abazov,etal.,D0 Collaboration,Aprecisionmeasurementofthe mass ofthetopquark,Nature429(2004)638,https://doi.org/10.1038/nature02589, arXiv:hep-ex/0406031.

[42] P.Artoisenet,V.Lemaitre,F.Maltoni,O.Mattelaer,Automationofthematrix elementreweightingmethod,J.HighEnergyPhys.12(2010)068,https://doi. org/10.1007/JHEP12(2010)068,arXiv:1007.3300.

[43] R.D.Ball,V.Bertone,S.Carrazza,C.S.Deans,L.DelDebbio,S.Forte,A.Guffanti, N.P.Hartland,J.I.Latorre,J.Rojo,M.Ubiali,NNPDFCollaboration,Parton distri-butionswithLHCdata,Nucl.Phys.B867(2013)244,https://doi.org/10.1016/j. nuclphysb.2012.10.003,arXiv:1207.1303.

[44] CMS Collaboration, CMSluminosity measurementfor the 2015 datataking period,CMSPhysicsAnalysisSummaryCMS-PAS-LUM-15–001(2016),http:// cds.cern.ch/record/2138682.

[45] ATLASandCMSCollaborations,ProcedurefortheLHCHiggsbosonsearch com-binationinSummer 2011, JointCMSand ATLASnoteCMS-NOTE-2011-005; ATL-PHYS-PUB-2011-11,2011.https://cds.cern.ch/record/1379837.

[46] L. Moneta, K. Belasco, K.S. Cranmer, A. Lazzaro, D. Piparo, G. Schott, W. Verkerke,M.Wolf,The RooStats Project,in:Proc. ofthe 13th International Workshopon AdvancedComputing and AnalysisTechniques inPhysics Re-search (ACAT2010), SISSA, 2010, arXiv:1009.1003, http://pos.sissa.it/archive/ conferences/093/057/ACAT2010_057.pdf.

[47] CMSCollaboration,MeasurementoftheWZproductioncrosssectioninpp col-lisionsat√s=13 TeV,Phys.Lett.B766(2017)268,https://doi.org/10.1016/j. physletb.2017.01.011,arXiv:1607.06943.

[48] CMSCollaboration,PrecisedeterminationofthemassoftheHiggsbosonand testsofcompatibilityofitscouplingswiththestandardmodelpredictions us-ingproton collisionsat7and8 TeV,Eur.Phys. J.C75(2015)212,https:// doi.org/10.1140/epjc/s10052-015-3351-7,arXiv:1412.8662.

[49] G.Cowan,K.Cranmer,E.Gross,O.Vitells,Asymptoticformulaefor likelihood-basedtestsofnewphysics,Eur.Phys.J.C71(2011)1554,https://doi.org/10. 1140/epjc/s10052-011-1554-0,arXiv:1007.1727.

TheCMSCollaboration

A.M. Sirunyan,

A. Tumasyan

YerevanPhysicsInstitute,Yerevan,Armenia

W. Adam,

F. Ambrogi,

E. Asilar,

T. Bergauer,

J. Brandstetter,

E. Brondolin,

M. Dragicevic,

J. Erö,

A. Escalante Del Valle,

M. Flechl,

M. Friedl,

R. Frühwirth

1

,

V.M. Ghete,

J. Grossmann,

J. Hrubec,

M. Jeitler

1

,

A. König,

N. Krammer,

I. Krätschmer,

D. Liko,

T. Madlener,

I. Mikulec,

E. Pree,

N. Rad,

H. Rohringer,

J. Schieck

1

,

R. Schöfbeck,

M. Spanring,

D. Spitzbart,

A. Taurok,

W. Waltenberger,

J. Wittmann,

C.-E. Wulz

1

,

M. Zarucki

InstitutfürHochenergiephysik,Wien,Austria

V. Chekhovsky,

V. Mossolov,

J. Suarez Gonzalez

InstituteforNuclearProblems,Minsk,Belarus

E.A. De Wolf,

D. Di Croce,

X. Janssen,

J. Lauwers,

M. Van De Klundert,

H. Van Haevermaet,

P. Van Mechelen,

N. Van Remortel

UniversiteitAntwerpen,Antwerpen,Belgium

S. Abu Zeid,

F. Blekman,

J. D’Hondt,

I. De Bruyn,

J. De Clercq,

K. Deroover,

G. Flouris,

D. Lontkovskyi,

S. Lowette,

I. Marchesini,

S. Moortgat,

L. Moreels,

Q. Python,

K. Skovpen,

S. Tavernier,

W. Van Doninck,

P. Van Mulders,

I. Van Parijs

D. Beghin,

B. Bilin,

H. Brun,

B. Clerbaux,

G. De Lentdecker,

H. Delannoy,

B. Dorney,

G. Fasanella,

L. Favart,

R. Goldouzian,

A. Grebenyuk,

A.K. Kalsi,

T. Lenzi,

J. Luetic,

T. Maerschalk,

A. Marinov,

T. Seva,

E. Starling,

C. Vander Velde,

P. Vanlaer,

D. Vannerom,

R. Yonamine,

F. Zenoni

UniversitéLibredeBruxelles,Bruxelles,Belgium

T. Cornelis,

D. Dobur,

A. Fagot,

M. Gul,

I. Khvastunov

2

,

D. Poyraz,

C. Roskas,

S. Salva,

D. Trocino,

M. Tytgat,

W. Verbeke,

M. Vit,

N. Zaganidis

GhentUniversity,Ghent,Belgium

H. Bakhshiansohi,

O. Bondu,

S. Brochet,

G. Bruno,

C. Caputo,

A. Caudron,

P. David,

S. De Visscher,

C. Delaere,

M. Delcourt,

B. Francois,

A. Giammanco,

M. Komm,

G. Krintiras,

V. Lemaitre,

A. Magitteri,

A. Mertens,

M. Musich,

K. Piotrzkowski,

L. Quertenmont,

A. Saggio,

M. Vidal Marono,

S. Wertz,

J. Zobec

UniversitéCatholiquedeLouvain,Louvain-la-Neuve,Belgium

W.L. Aldá Júnior,

F.L. Alves,

G.A. Alves,

L. Brito,

G. Correia Silva,

C. Hensel,

A. Moraes,

M.E. Pol,

P. Rebello Teles

CentroBrasileirodePesquisasFisicas,RiodeJaneiro,Brazil

E. Belchior Batista Das Chagas,

W. Carvalho,

J. Chinellato

3

,

E. Coelho,

E.M. Da Costa,

G.G. Da Silveira

4

,

D. De Jesus Damiao,

S. Fonseca De Souza,

L.M. Huertas Guativa,

H. Malbouisson,

M. Melo De Almeida,

C. Mora Herrera,

L. Mundim,

H. Nogima,

L.J. Sanchez Rosas,

A. Santoro,

A. Sznajder,

M. Thiel,

E.J. Tonelli Manganote

3

,

F. Torres Da Silva De Araujo,

A. Vilela Pereira

UniversidadedoEstadodoRiodeJaneiro,RiodeJaneiro,Brazil

S. Ahuja

a

,

C.A. Bernardes

a

,

T.R. Fernandez Perez Tomei

a

,

E.M. Gregores

b

,

P.G. Mercadante

b

,

S.F. Novaes

a

,

Sandra S. Padula

a

,

D. Romero Abad

b

,

J.C. Ruiz Vargas

a

a_{UniversidadeEstadualPaulista,SãoPaulo,Brazil} b_{UniversidadeFederaldoABC,SãoPaulo,Brazil}

A. Aleksandrov,

R. Hadjiiska,

P. Iaydjiev,

M. Misheva,

M. Rodozov,

M. Shopova,

G. Sultanov

InstituteforNuclearResearchandNuclearEnergy,BulgarianAcademyofSciences,Sofia,Bulgaria

A. Dimitrov,

L. Litov,

B. Pavlov,

P. Petkov

UniversityofSofia,Sofia,Bulgaria

W. Fang

5

,

X. Gao

5

,

L. Yuan

BeihangUniversity,Beijing,China

M. Ahmad,

J.G. Bian,

G.M. Chen,

H.S. Chen,

M. Chen,

Y. Chen,

C.H. Jiang,

D. Leggat,

H. Liao,

Z. Liu,

F. Romeo,

S.M. Shaheen,

A. Spiezia,

J. Tao,

C. Wang,

Z. Wang,

E. Yazgan,

H. Zhang,

J. Zhao

InstituteofHighEnergyPhysics,Beijing,China

Y. Ban,

G. Chen,

J. Li,

Q. Li,

S. Liu,

Y. Mao,

S.J. Qian,

D. Wang,

Z. Xu,

F. Zhang

5

StateKeyLaboratoryofNuclearPhysicsandTechnology,PekingUniversity,Beijing,China

Y. Wang

TsinghuaUniversity,Beijing,China

C. Avila,

A. Cabrera,

C.A. Carrillo Montoya,

L.F. Chaparro Sierra,

C. Florez,

C.F. González Hernández,

J.D. Ruiz Alvarez,

M.A. Segura Delgado

B. Courbon,

N. Godinovic,

D. Lelas,

I. Puljak,

P.M. Ribeiro Cipriano,

T. Sculac

UniversityofSplit,FacultyofElectricalEngineering,MechanicalEngineeringandNavalArchitecture,Split,Croatia

Z. Antunovic,

M. Kovac

UniversityofSplit,FacultyofScience,Split,Croatia

V. Brigljevic,

D. Ferencek,

K. Kadija,

B. Mesic,

A. Starodumov

6

,

T. Susa

InstituteRudjerBoskovic,Zagreb,Croatia

M.W. Ather,

A. Attikis,

G. Mavromanolakis,

J. Mousa,

C. Nicolaou,

F. Ptochos,

P.A. Razis,

H. Rykaczewski

UniversityofCyprus,Nicosia,Cyprus

M. Finger

7

,

M. Finger Jr.

7

CharlesUniversity,Prague,CzechRepublic

E. Carrera Jarrin

UniversidadSanFranciscodeQuito,Quito,Ecuador

Y. Assran

8

,

9

,

M.A. Mahmoud

10

,

9

,

A. Mahrous

11

AcademyofScientificResearchandTechnologyoftheArabRepublicofEgypt,EgyptianNetworkofHighEnergyPhysics,Cairo,Egypt

S. Bhowmik,

R.K. Dewanjee,

M. Kadastik,

L. Perrini,

M. Raidal,

C. Veelken

NationalInstituteofChemicalPhysicsandBiophysics,Tallinn,Estonia

P. Eerola,

H. Kirschenmann,

J. Pekkanen,

M. Voutilainen

DepartmentofPhysics,UniversityofHelsinki,Helsinki,Finland

J. Havukainen,

J.K. Heikkilä,

T. Järvinen,

V. Karimäki,

R. Kinnunen,

T. Lampén,

K. Lassila-Perini,

S. Laurila,

S. Lehti,

T. Lindén,

P. Luukka,

T. Mäenpää,

H. Siikonen,

E. Tuominen,

J. Tuominiemi

HelsinkiInstituteofPhysics,Helsinki,Finland

T. Tuuva

LappeenrantaUniversityofTechnology,Lappeenranta,Finland

M. Besancon,

F. Couderc,

M. Dejardin,

D. Denegri,

J.L. Faure,

F. Ferri,

S. Ganjour,

S. Ghosh,

A. Givernaud,

P. Gras,

G. Hamel de Monchenault,

P. Jarry,

C. Leloup,

E. Locci,

M. Machet,

J. Malcles,

G. Negro,

J. Rander,

A. Rosowsky,

M.Ö. Sahin,

M. Titov

IRFU,CEA,UniversitéParis-Saclay,Gif-sur-Yvette,France

A. Abdulsalam

12

,

C. Amendola,

I. Antropov,

S. Baffioni,

F. Beaudette,

P. Busson,

L. Cadamuro,

C. Charlot,

R. Granier de Cassagnac,

M. Jo,

I. Kucher,

S. Lisniak,

A. Lobanov,

J. Martin Blanco,

M. Nguyen,

C. Ochando,

G. Ortona,

P. Paganini,

P. Pigard,

R. Salerno,

J.B. Sauvan,

Y. Sirois,

A.G. Stahl Leiton,

T. Strebler,

Y. Yilmaz,

A. Zabi,

A. Zghiche

LaboratoireLeprince-Ringuet,Ecolepolytechnique,CNRS/IN2P3,UniversitéParis-Saclay,Palaiseau,France

J.-L. Agram

13

,

J. Andrea,

D. Bloch,

J.-M. Brom,

M. Buttignol,

E.C. Chabert,

N. Chanon,

C. Collard,

E. Conte

13

,

X. Coubez,

F. Drouhin

13

,

J.-C. Fontaine

13

,

D. Gelé,

U. Goerlach,

M. Jansová,

P. Juillot,

A.-C. Le Bihan,

N. Tonon,

P. Van Hove