Evidence for the production of three massive vector bosons with the ATLAS detector

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Contents lists available atScienceDirect

Physics

Letters

B

www.elsevier.com/locate/physletb

Evidence

for

the

production

of

three

massive

vector

bosons

with

the

ATLAS

detector

.TheATLASCollaboration

a r t i c l e i n f o a b s t ra c t

Articlehistory:

Received26March2019

Receivedinrevisedform28August2019 Accepted2September2019

Availableonline10September2019 Editor:M.Doser

A search for the production of three massive vector bosons in proton–proton collisions is performed using data at √s=13 TeV recorded with the ATLAS detector at the Large Hadron Collider in the years 2015–2017, corresponding to an integrated luminosity of 79.8 fb−1. Events with two same-sign leptons (electrons or muons) and at least two reconstructed jets are selected to search for W W W→ ννqq.

Events with three leptons without any same-ﬂavour opposite-sign lepton pairs are used to search for

W W W→ ννν, while events with three leptons and at least one same-ﬂavour opposite-sign lepton pair and one or more reconstructed jets are used to search for W W Z→ νqq. Finally, events with four leptons are analysed to search for W W Z_→νν and W Z Z_→qq. Evidence for the joint production of three massive vector bosons is observed with a signiﬁcance of 4.1 standard deviations, where the expectation is 3.1 standard deviations.

(http://creativecommons.org/licenses/by/4.0/). Funded by SCOAP3_.

1. Introduction

Thejointproductionofthreevectorbosonsisarareprocessin theStandardModel (SM).Studies oftribosonproductioncan test thenon-AbeliangaugestructureoftheSM theoryandany devia-tionsfromtheSM predictionwouldprovidehintsofnewphysics athigherenergyscales [1–4].Tribosonproductionhasbeen stud-iedat the LargeHadron Collider (LHC)using proton–proton(pp) collisiondatatakenat√s=8 TeV forprocessessuchas γ γ γ [5], Wγ γ [6,7],Zγ γ [8,7],W Wγ andW Zγ [9,10],andW W W [11]. Thisletterpresents theﬁrst evidenceforthe jointproduction ofthreemassive vector bosonsin pp collisionsusing thedataset collected with the ATLAS detector between 2015 and 2017 at √

s=13 TeV. At leading order(LO) inquantum chromodynamics (QCD),theproductionofthreemassivevectorbosons(V V V , with V =W, Z )canproceedviatheradiationofeachvectorbosonfrom afermion,froman associatedboson productionwithan interme-diateboson(W , Z/γ∗ or H )decayingintotwo vectorbosons,or fromaquarticgaugecouplingvertex. RepresentativeFeynman di-agramsareshowninFig.1.

Twodedicatedsearchesareperformed,onefortheW±W±W∓ (denotedas W W W )process andoneforthe W±W∓Z (denoted asW W Z )andW±Z Z (denotedasW Z Z )processes.Tosearchfor the W W W process, eventswith two same-sign leptons with at leasttwojetsresultingfromW W W→ ννqq ( =e, μ,including τ→ νν) or threeleptons resultingfrom W W W → ννν are

_E-mail_address:_atlas_{.publications}_@cern_.ch_.

consideredandarehereafterreferredtoasthe ννqq and ννν channels,respectively.TosearchfortheW W Z andW Z Z (denoted as W V Z )processes, events withthree or four leptons resulting fromW V Z→ νqq,W W Z→ νν,andW Z Z→qqare used. Selection criteria are chosen in order to ensure there is no overlapbetweendifferentchannels. Adiscriminant that sepa-ratesthe W W W or W V Z signalfromthebackgroundisdefined in each channel. The discriminants are combinedusing a binned maximum-likelihood fit, which allows the signal yield and the backgroundnormalisationstobeextracted.Thecombined observ-ableisthesignalstrengthparameter μdefinedastheratioofthe measured W V V cross section to its SM expectation, where one commonratioisassumedforW W W andW V Z .

2. TheATLASdetector,dataandsimulationsamples

TheATLASdetector [12–14] isamulti-purposeparticledetector comprisedofaninnerdetector(ID)surroundedbya2 T supercon-ductingsolenoid,electromagnetic(EM)andhadroniccalorimeters, anda muon spectrometer (MS) withone barrel andtwo endcap air-coretoroids.TheIDconsistsofasiliconpixeldetector,asilicon microstrip detector,anda transitionradiation tracker,andcovers |η| <2.5 in pseudorapidity.1 The calorimeter system covers the 1 _ATLAS_uses _a_right-handed_coordinate_system_with _its_origin_at _the_nominal

interactionpoint(IP)inthecentreofthedetectorandthez-axisalongthebeam pipe.Thex-axispointsfromtheIPtothecentreoftheLHCring,andthe y-axis

points upward.Cylindricalcoordinates(r,φ)areusedinthetransverseplane,φ https://doi.org/10.1016/j.physletb.2019.134913

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Fig. 1. Representative Feynman diagrams at LO for the production of three massive vector bosons, including diagrams sensitive to triple and quartic gauge couplings.

pseudorapidityrange |η| <4.9.The MS providesmuon triggering capabilityfor|η| <2.4 andmuonidentiﬁcationandmeasurement for|η| <2.7.Atwo-leveltriggersystem [15], usingcustom hard-warefollowedbyasoftware-basedtriggerlevel,isusedtoreduce theeventratetoanaverageofaround1 kHzforoﬄinestorage.

The data used were collected between 2015and 2017 in pp collisionsat√s=13 TeV.Onlyeventsrecordedwithafully oper-ationaldetector andstablebeamsare included. Candidateevents areselectedbysingleisolated-lepton(e or μ)triggerswith trans-versemomentumthresholdsvaryingfrompT=20 GeV to26 GeV

(dependingontheleptonﬂavour andrunperiod)orsingle-lepton triggers with thresholds of pT=50 GeV for muons and pT=

60 GeV forelectrons.Duetothepresenceoftwo,threeorfour lep-tonsinthefinalstate,thesesingle-leptontriggersarefullyefficient forthetribosonsignalsinthesignalregionsdefinedinSections4 and5.Theresultingtotalintegratedluminosityis79.8fb−1.

Signal andbackground processes were simulatedwith several MonteCarlo(MC) eventgenerators, whilethe ATLAS detector re-sponsewasmodelled [16] with Geant4 [17].Theeffectofmultiple pp interactions in the same and neighbouring bunch crossings (pile-up) was included by overlaying minimum-bias events sim-ulated with Pythia 8.186 [18] interfaced to EvtGen 1.2.0 [19], referred toas Pythia 8.1 in thefollowing, andusingthe A3[20] setoftuned MCparameters, oneachgenerated eventinall sam-ples. Triboson signal events [21] were generated using Sherpa 2.2.2 [22–24] with the NNPDF3.0NNLO [25] parton distribution function(PDF)set,whereallthreebosonsareon-mass-shell,using a factorised approach [26]. Events with an off-mass-shell boson through W H→W V V∗ and Z H→Z V V∗ were generated using Powheg-Box 2 [27–32] interfaced to Pythia 8.1 for the W W W analysis, while for the W V Z analysis only Pythia 8.1 was used. ThegeneratorwasinterfacedtotheCT10[33] (NNPDF2.3LO[34]) PDF andtheAZNLO[35] (A14 [36])setof tunedMC parameters fortheW W W (W V Z )analysis.Bothon-mass-shelland off-mass-shellprocessesweregeneratedatnext-to-leadingorder(NLO)QCD accuracy [37–40] and are included in the signal deﬁnition. The expected cross sections for W W W and W W Z production are 0.50 pb and0.29 pb, respectively,with an uncertainty of∼10%, evaluated by varying parameters inthe simulationrelated tothe renormalisation and factorisation scales, parton shower and PDF sets.

Diboson(W W , W Z ,Z Z ) [26],W/Z+γ [21] andsingleboson (W/Z+jets) [41] production,aswellaselectroweakproductionof W±W±+2 jets,W Z+2 jets,andZ Z+2 jets,weremodelled us-ing Sherpa 2.2.2withtheNNPDF3.0NNLOPDFset.Inorderto im-provetheagreementbetweenthesimulatedandobservedjet mul-tiplicitydistributionsforthe W Z→ ν and Z Z→ events, ajet-multiplicitybasedreweighting was appliedtothesimulated W Z and Z Z samples. Top-quark pair events (tt)¯ were gener-ated using Powheg-Box 2 [42] interfaced to Pythia 8.230 [43]

beingtheazimuthalanglearoundthebeampipe.Thepseudorapidityisdeﬁnedin termsofthepolarangleθ asη= − ln tan(θ/2).Angulardistanceismeasuredin unitsofR =(η)2_{+ (φ)}2_.

and EvtGen 1.6.0. The NNPDF3.0NLO PDF set was used for the matrix-element calculation, while the NNPDF2.3LO PDF set was used for the showering with the A14 set of tuned parameters. Other background processes containing top quarks were gener-ated with MadGraph5_aMC@NLO [44] interfaced to Pythia 8, at LO (t¯tγ, t Z , t¯t W W , and ttt¯¯t) or at NLO (tt W ,¯ t¯t Z , and t¯t H ),with MadGraph5_aMC@NLO interfacedto Herwig [45] (t W Z and t W H ) or with Powheg-Box 2 [46] interfaced to Pythia 6 (t W ).

3. Objectdeﬁnitionsandselectioncriteria

Selected events are required to contain at least one recon-structed primary vertex. If more than one vertex is found, the vertexwiththelargest p2_T sumofassociatedID tracksisselected astheprimaryvertex.

Electrons are reconstructed as energy clusters in the EM calorimeterthatarematchedtotracksfoundintheID.Muonsare reconstructed by combining tracks reconstructed in the ID with tracksortracksegments foundintheMS. Leptonsneedtosatisfy pT>15 GeV and have|η| <2.47 forelectrons (electrons within

likelihood-based“Tight”qualitydeﬁnitionwhichresultsin eﬃcien-ciesof58% at ET=4.5 GeV to88% atET=100 GeV [47].Forthe

W W W (W V Z ) analysis, muonsare requiredto pass the “Medi-um”(“Loose”)identiﬁcationcriteriawhichresultsineﬃcienciesof approximately96% (98%)formuonsfroma Z→μμsample [48].

To reject jetsmisidentified asleptons orleptons from hadron decays (including b- and c-hadron decays), referred to as “non-prompt” leptons in the following,leptons are requiredto be iso-lated from other particles in both the calorimeters and the ID. Theleptonisolation conesizeisatmost R=0.2,exceptforthe muon isolationintheID,whereitisatmostR=0.3.Electrons are requiredto pass the “Fix (Loose)” isolation requirement [49] andmuons arerequired topass the “Gradient”(“FixedCutLoose”) isolation requirement [48] for the W W W (W V Z ) analysis. The identification andisolation requirements formuonsare more re-strictive in the W W W analysis because a larger contamination fromnon-promptleptonsisexpected.TheelectronFix(Loose) iso-lation requirement results in an efficiency above 95% [47]. The muon isolationefficiencyisabove 90%(99%)fortheGradient iso-lation criteria for muons with pT of 25 GeV (60 GeV), and the

FixedCutLooseeﬃciencyisabove95% [48].

A dedicatedboosteddecision tree(BDT), termed“non-prompt lepton BDT” [50], is used to reject leptons likely to originate fromheavy-ﬂavourdecays.Inaddition,electrons havetopassthe “chargemisidentiﬁcationsuppressionBDT” [49] torejectelectrons

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likely to have the electric charge wrongly measured. The non-prompt lepton BDT uses isolation and b-tagging information de-rivedfromenergydepositsandtracksinaconearoundthelepton direction. The charge misidentification suppression BDT uses the electrontrack impact parameter, thetrack curvature significance, the cluster width and the quality of the matching between the cluster andits associated track.Leptons passing all requirements listedabovearereferredtoas“nominal”leptons.Thecombination ofisolation, non-prompt lepton BDT andcharge misidentification suppressionBDT criteria resultsin an efficiencyof 65% (89%)for electrons with pT of 20 GeV (80 GeV) [47]. The combinationof

isolation and non-prompt lepton BDT results in an eﬃciency of 65%(99%) formuonsthat havetheGradient isolation with pT of

20 GeV (100 GeV),andaneﬃciencyof74%(99%)formuonsthat havetheFixedCutLooseisolationwithpTof20 GeV (80 GeV) [48].

Jetsarereconstructed fromcalibratedtopologicalclustersbuilt fromenergydepositsinthecalorimeter [51] usingtheanti-kt algo-rithmwitharadiusparameterof0.4 [52,53] andcalibratedusing thetechniquesdescribedinRef. [54].Jetcandidatesarerequiredto havepT>20 GeV and|η| <2.5.Torejectjetslikelytobe arising

frompile-up collisions, an additional criterion using the jet ver-textagger [55] discriminantis appliedforjetswith pT<60 GeV

and|η| <2.4.Jetscontainingb-hadrons(b-jets)areidentiﬁedbya multivariate discriminantcombining informationfrom algorithms usingsecondaryverticesreconstructedwithinthejetandtrack im-pactparameters [56,57], withan eﬃciency of 85% (70%) for the W W W (W V Z )analysis.

The missing transverse momentum, whose magnitude is de-noted Emiss

T , is deﬁned as the negative vector sum of the pT of

all reconstructed and calibrated objects in the event. This sum includes a term to account for the energy from low-momentum particlesthat arenot associatedwithanyofthe selectedobjects, andiscalculatedfromIDtracksmatchedtothereconstructed pri-mary vertex in the event [58]. The sum also includes jets with |η| >2.5 and pT>30 GeV.

Theobjectreconstruction andidentiﬁcationalgorithms do not always resultinunambiguous identiﬁcations.An overlapremoval algorithmisthereforeapplied. Electronssharinga trackwithany muons are removed. Any jet within R <0.2 of an electron is removedandelectrons within R <0.4 ofanyremainingjetsare removed. Jets with lessthan three associated tracks and within R <0.2 ofamuonareremoved,andmuonswithin R <0.4 of anyoftheremainingjetsareremoved.

Atleastonereconstructed“trigger”leptonwithaminimumpT

is required to match within R <0.15 a lepton with the same ﬂavourreconstructed by thetriggeralgorithm.The thresholdsfor the trigger (other) leptons are 27 GeV (20 GeV) for the W W W analysis,andfrom21 GeV to27 GeV (15 GeV),dependingonthe runperiodandleptonﬂavour,forthe W V Z analysis.

4. AnalysistargetingW W W

Theexperimental signatureofthe ννqq processisthe pres-ence of two same-sign leptons, Emiss_T , and two jets. The signa-tureof the ννν process is the presence ofthree leptons and Emiss_T .Toreducethebackgroundcontributionsfromprocessesthat havemorethantwo(three)leptonsinthe ννqq (ννν) chan-nel a “veto lepton” deﬁnition is introduced. Compared with the nominallepton selection criteriadescribed inSection 3, the veto lepton pT threshold islowered to7 GeV, andthe isolation,

non-promptleptonBDT,charge misidentificationsuppressionBDT, and impact parameter requirements are removed. For veto electrons, the likelihood-based Loose identification definition [49] is used. For veto muons, the Loose identification definition [48] is used, andthepseudorapidityrangeisextendedto|η| <2.7.

To select ννqq candidates, events are required to have ex-actlytwonominalleptonswithpT>20 GeV andthesameelectric

charge, at least two jets, and no identiﬁed b-jets. Four regions are considered, based on the lepton ﬂavour, namely ee, eμ, μe, and μμ,whereeμdenotes thehighest-pT (leading) leptonbeing

an electron, while μe denotes the leading lepton beinga muon. Events with an additional veto lepton are removed. The invari-ant mass of the dilepton system is required to be in the range 40 <m<400 GeV.Theupper masslimitreduces the contribu-tionfromtheW Z+jetsprocess.Theleading(sub-leading)jetmust have pT>30(20) GeV and|η| <2.5. Thedijetsystem, formedby

thetwojetswiththelargestpT,isrequiredtohavemj j<300 GeV and|ηj j| <1.5,wheremj j isthe dijetinvariant massand ηj j is the pseudorapidity separation between the two jets. The cuts appliedonthe dijetsystemmainlyreduce thecontributionsfrom thesame-sign W W vectorboson scatteringprocess.Additionally, intheee finalstate, Emiss_T isrequiredtobeabove55 GeV andm mustsatisfym<80 GeV orm>100 GeV, toreduce contami-nationfrom Z→ee where thecharge ofone electronis misiden-tified.Thism cutisnot appliedinthe μμfinal state,since the muonchargemisidentificationrateisfoundtobenegligible,noris itappliedintheeμand μe finalstates,wherethecontamination fromZ eventsissmall.

Toselect νννcandidates,eventsarerequiredtohaveexactly threenominalleptons with pT>20 GeV and noidentiﬁedb-jets.

Eventswithanadditionalvetoleptonareremoved.Toreducethe contributionfromtheW Z→ ν process,eventsarerequiredto haveno same-ﬂavouropposite-sign (SFOS)lepton pairs,andthus only μ±e∓e∓ande±μ∓μ∓eventsareselected.

AmajorbackgroundoriginatesfromtheW Z+jets→ ν+jets process, contributing to the ννqq channel when one lepton is notreconstructedoridentiﬁed,ortothe ννν channel,whena Z bosondecaysintoapairof τ leptonsbothofwhichdecaytoan electronormuon.Simulationisusedtoestimatethisbackground. The W Z+jetsmodellingistested ina W Z -dominated validation regiondeﬁnedbyselectingeventswithexactlythreenominal lep-tonswithoneSFOSleptonpair.Inaddition,eventsarerequiredto havenob-jets reconstructed,E_Tmiss>55 GeV andthetrilepton in-variant mass m>110 GeV. Data and simulation agree in this validationregion, asshowninFig. 2(a)forthe leading lepton pT

distribution.

ContributionsfromSMprocessesthatproduceatleastone non-prompt lepton are estimated using a data-driven method as de-scribed inRef. [59] by introducing“fake” leptons. The definitions of nominal and fake leptons are mutually exclusive. Fake elec-trons have to satisfy the likelihood-based Medium [49] but fail theTightidentification, andtheisolation, non-promptleptonBDT andchargemisidentificationsuppressionBDTrequirementsare re-moved.Fakemuonshavetheimpactparameterrequirements loos-ened to|d0|/σd0<10,andboth isolation andnon-promptlepton BDT requirementsareremoved.Additionally, theyhavetofailthe nominalmuondefinition.Simulationshowsthat thet¯t processis the dominantcontributorofeventswithfake leptons, withmore than90%inthe ννqq channelandmorethan95%inthe ννν channeloriginatingfromthisprocess.Eventscontainingone(two) nominallepton(s)andonefakeleptonwithpT>20 GeV arescaled

by a “fake factor” to predict the non-prompt lepton background contribution in the ννqq (ννν) channel. The fake factor is theratioofthenumberofnon-promptleptons passingthe nomi-nalleptoncriteriaoverthenumberpassingthefakeleptoncriteria. Its value is derived from two t¯t-enriched regions selected with twoorthreeleptons(noSFOSleptonpairs)andexactlyoneb-jet. Oneofthesame-signleptonspasseseithernominalorfakelepton criteria, while the other lepton(s) must pass the nominal lepton

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Fig. 2. Comparisonbetweendataandpredictionof(a)theleadingleptonpT distributioninthe W Z validationregionand(b)theleadingjetpT distributioninthe W

sidebandregion.Thecontributiondenoted“Other”isdominatedbytheW±W±+2 jetsprocessfortheW sidebandregion.Thecontributiondenoted“γ-conv.”isdescribed inthetext.Predictionsfromsimulationarescaledtotheintegratedluminosityofthedatausingthetheoreticalcrosssectionsofeachsample.Thehatchedarearepresents thestatisticaluncertaintyinthepredictionduetothelimitednumberofsimulatedevents.Thelastbincontainstheoverﬂow.Thebottompaneldisplaystheratioofdatato thetotalprediction.

criteria.Thefakefactorisfound tobe0.017±0.010 forelectrons and0.035±0.005 formuons.

EventsresultingfromtheVγj j productioncanpasstheee,eμ or μe signalselectioncriteriaifthephotonismisreconstructedas an electron.This contribution(referred toas “γ conv.”) is evalu-ated usinga data-drivenmethod similar to the non-prompt lep-tonbackgroundevaluationbyintroducing “photon-like”electrons. A photon-like electron is an object reconstructed like a nomi-nal electron except that the track has no hit in the innermost layer of the pixel detector and the non-prompt lepton BDT and chargemisidentiﬁcationsuppressionBDTrequirementsarenot ap-plied. The photon fake factor is determined in two regions se-lected with two nominal muons, no b-jets, and one nominal or photon-like electron. The trilepton invariant mass is required to satisfy80 GeV<meμμ<100 GeV.Mostoftheseeventscontaina Z→μμdecay,whereonemuonradiatesaphoton,whichis mis-reconstructedasanelectron.

The charge misidentification background originates from pro-cessesthatproduceoppositely-chargedpromptleptons,whereone lepton’s charge is misidentified and results in final states with twosame-signleptons.Thebackgroundisestimatedusinga data-driventechniqueasdescribedinRef. [11].

All ννqq candidates with mj j <50 GeV or mj j>120 GeV (denoted as the “W sideband” region) are used to validate the modellingofdifferentbackgroundsdescribedabove.Dataand pre-dictionagree,asshowninFig.2(b)fortheleadingjet pT

distribu-tion.Eventswithmj j<300 GeV areusedintheﬁttoextractthe signal.

5. AnalysistargetingW W Z andW Z Z

Theexperimental signature ofthe W V Z→ νqq, W W Z→ νν, and W Z Z →qq processes is the presence of three or four charged leptons. In order to increase the signal accep-tance,“loose”leptons are definedinadditionto nominalleptons, the latterbeing a subset of the former. Loose leptons have both the isolation andnon-prompt lepton BDT requirements removed. In addition, loose electrons are required to pass the likelihood-basedLooseidentificationdefinitionandthecharge misidentifica-tionsuppressionBDTrequirementisremoved.

Sixregionsaredefinedwitheitherthreeorfourlooseleptons, sensitive to triboson final statescontaining Z bosons. Among all possibleSFOSleptonpairs,theonewithmclosesttotheZ boson mass isdefinedasthe best Z candidate.Inall regions, the pres-enceofsuchabest Z candidatewith|m−91.2 GeV| <10 GeV, is required.Furthermore,anySFOSlepton paircombinationis re-quiredtohaveaminimuminvariantmassofm>12 GeV.Events withb-taggedjetsarevetoed.

For the three-lepton channel, the lepton which is not part of thebestZ candidateisrequiredtobeanominallepton.Thescalar sumofthetransversemomentaofallleptons andjets(HT)is

re-quired to be larger than 200 GeV. This signiﬁcantly reduces the contribution of the Z→ processes with one additional non-promptlepton.Threeregionsaredeﬁnedaccordingtothenumber ofjetsinthe event:onejet (3-1j),twojets(3-2j),andatleast threejets(3-3j).

For thefour-lepton channel, the third andfourth leading lep-tons are required to be nominal leptons. The two leptons which arenotpartofthebestZ candidatedefinitionarerequiredtohave opposite charges. These“other leptons” are used to define three regions, depending onwhethertheyare different-flavour(4-DF), or same-flavour andtheir masslies within a window of 10 GeV around the Z boson mass (4-SF-Z) ortheir massis outsidethis window(4-SF-noZ).

In each ofthe sixregions thedistribution ofa dedicatedBDT discriminant, separating the W V Z signal from the dominating diboson background, is fed as input to the binned maximum-likelihood fit toextract the signal. Forthe three-leptonchannels, 13, 15,and 12input variables are used forthe 3-1j, 3-2j, and 3-3j finalstates,respectively, whileforthefour-leptonchannels, six input variables are used for each of the 4-DF, 4-SF-Z and 4-SF-noZfinalstates.TheseinputvariablesarelistedinTable1.

Due totherequiredpresenceofnominalleptons inthe three-and four-leptonchannels, backgroundswith a Z bosonand non-promptleptonsarereduced.Theremainingbackgroundsare dom-inatedbyprocesseswithpromptleptonsandthusallbackgrounds are estimated using simulation. The W Z+jets and Z+jets back-groundsarevalidatedinaregiondeﬁnedinthesamewayasthe 3-1jregion,withtheexceptionthatnorequirementonHTis

ap-plied,thethird-highest-pTleptonisrequiredtohaveasmall

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Table 1

ListofinputvariablesusedinthemultivariateanalysisforeachoftheW V Z channels,denotedby ×.Thesubscripts 1,2 and3 refertotheleading,subleadingandthirdleadingleptonorjet.Thedefinitionsof“best Z candidate”and “otherleptons”aregiveninthetext.ThevariablemT(W)istheW -bosontransversemassoftheleptonicallydecaying W -bosoncandidate.Amongtheinvariantmassesformedbyallpossiblejetpairs,theoneclosesttotheW -bosonmass definesthe“mj jofbestW candidate”andthesmallestonedefinesthe“smallestmj j”.Finally,theleptonicandhadronic HTarecalculatedasthescalarsumofthepTofallleptonsoralljets,respectively.

Variable 3-1j 3-2j 3-3j 4DF 4SF on-shell 4SF off-shell

pT(1) × × pT(2) × × × pT(3) × × × Sum of pT() × × × m12 × × m13 × × m23 × × mof best Z candidate × × mof other leptons × × × m3 × × × m4 × × ×

Sum of lepton charges × × ×

pT(j1) × × pT(j2) × × Sum of pT(j) × Number of jets × × × × mj1j2 × mT(W) × mj jof best W candidate × Smallest mj j × EmissT × × × × × HT × × × × Leptonic HT × Hadronic HT ×

Invariant mass of all leptons, jets and ETmiss × ×

Invariant mass of the best Z leptons and j1 ×

ofthethreeleptonshastobesmallerthan150 GeV.Dataand ex-pectationagreeinthe3-1jvalidationregion,asshowninFig.3(a) forthetransversemomentum distributionofthethird-highest-pT

lepton.

Thett Z background¯ isdeterminedinaregiondeﬁnedlikethe 3-3jregionwiththeexception thatnorequirementon HT is

ap-plied,andatleastfourjetsarerequired,ofwhichatleasttwoare b-tagged.Thisregionisincludedasasingle-bincontrolregion(CR) intheﬁtmodel,outlinedinSection6.Dataandexpectationagree, asshowninFig.3(b)forthet¯t Z controlregion.

6. Signalextractionandcombination

TheW W W ,W W Z andW Z Z regionsarecombinedusingthe profilelikelihoodmethoddescribedinRef. [60] basedona simul-taneous fit to distributions in the signal and background control regions. A total of eleven signal regions are considered: four re-gions (ee, eμ, μe, and μμ) for the ννqq channel, one region (μee and eμμ combined) forthe ννν channel, three regions (3-1j, 3-2j, and3-3j)for the W V Z three-lepton channel, and threeregions(4-DF,4-SF-Z,and4-SF-noZ)forthe W V Z four-leptonchannel. Onecontrol region isconsidered: the tt Z control¯ regiondescribed inSection5.Thedistributionsusedinthefitare themj j distributions forthe ννqq channel andtheBDT distri-butions forthe W V Z three-leptonandfour-lepton channels. The numberofselectedeventsinthe νννchannelandthett Z con-¯ trolregionareeachincludedasasinglebininthefit.Intotal,186 binsareusedinthecombinedfit.

Abinned likelihoodfunction L(μ, θ ) isconstructed asa prod-uct of Poisson probability terms over all bins considered. This likelihood function depends on the signal-strength parameter μ, a multiplicative factor that scales the numberof expected signal events,andθ,asetofnuisanceparametersthatencodetheeffect ofsystematicuncertainties inthesignalandbackground expecta-tions.Thenuisanceparametersareimplementedinthelikelihood

functionasGaussian,log-normalorPoissonconstraints.Thesame value for μ =μW V V is assumed for the on- and off-mass-shell W W W , W W Z and W Z Z processes. Correlations of systematic uncertainties arisingfromcommonsources aremaintainedacross processesandchannels.

Experimentaluncertaintiesarerelatedtotheleptontrigger, re-constructionandidentificationefficiencies [49,48],leptonisolation criteria [50],leptonenergy(momentum)scaleandresolution [48, 61], jet energy scale and resolution [54], jet vertextagging [55, 62], b-tagging [57], modelling of pile-up and missing transverse momentum [58], andintegratedluminosity [63,64]. Nuisance pa-rameters related to these uncertainties are treatedas correlated between all channels. The time-dependence of the efficiencies, scalesandresolutionsacrossthevariousrunperiodsistakeninto account.

Foreach ofthe backgroundprocessesevaluated using simula-tion, a nuisance parameter representing its normalisation uncer-tainty is included. The following prior uncertainties in the nor-malisations are assumed: 20% for W Z and Z Z ; 40% for Z+jets, 10% [65] for W t Z , 30% [66,67] for t Z ,11% [68] fortt Z ,¯ and30% for V H not producingthree massive bosons.For dominant back-grounds from the W Z and Z Z processes, the simultaneous ﬁt modelhasthepowertoconstraintheirnormalisationsatthe∼5% level,independentlyoftheassumedprior.Inaddition,shape-only variationsforbackgroundsfromtheW Z andZ Z processesare de-rivedfromalternativesamples,generatedusing Powheg [69] with Pythia 8 fortheparton shower to account fordifferencesin the modellingofdibosonproductionandshowering. Shapevariations due to renormalisation and factorisation scales are also consid-eredforthesetwoprocesses.Theprior uncertaintiesassumedfor Z+jetsand V H covertheobserveddata/simulation agreementin validation regions, andthe calculationsin Ref. [68], respectively. Theimpactoftheseuncertaintiesonthemeasurementissmall.

Uncertainties in data-driven background evaluations mainly come from statistical and systematic uncertainties in the charge

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Fig. 3. Datacomparedwithexpectationsfor(a)thetransversemomentumofthethird-highest-pTleptoninthe3-1jregionwiththeadditionalrequirementm<150 GeV,

norequirementonHT,andincludingthe10 GeV<pT<15 GeV validationregionand(b)thenumberofjetsinthett Z control¯ region.Thecontributionsdenoted“Other”

aredominatedby(a)thet Z andV H processes,wheretheHiggsbosondoesnotdecaytotwomassivebosons,and(b)thet Z process.Predictionsfromsimulationarescaled totheintegratedluminosityofthedatausingthetheoreticalcrosssectionsofeachsample.Thehatchedarearepresentsthestatisticaluncertaintyinthepredictiondueto thelimitednumberofsimulatedevents.Thelastbincontainstheoverﬂow.Thebottompaneldisplaystheratioofdatatothetotalprediction.

Table 2

Post-ﬁtbackground,signalandobservedyieldsfortheννqq andνννchannels.Uncertaintiesinthepredictionsincludebothstatisticaland systematicuncertaintiesaddedinquadrature;correlationsamongsystematicuncertaintiesaretakenintoaccountinthecalculationofthetotal.

ee eμ μe μμ μee+eμμ W W W 9.9±3.3 26±9 23±8 30±10 15±5 W Z 37.4±2.2 121±6 96±5 119±6 8.6±0.5 Z Z 0.46±0.05 5.11±0.25 3.44±0.18 4.12±0.24 0.69±0.03 Non-prompt 6.1±3.0 35±5 17±9 37±7 9.4±1.5 γconv. 20.9±1.9 35.0±3.1 76±7 – 1.06±0.11 Other 12.9±1.0 25.7±1.7 20.3±1.3 25.3±1.6 3.5±0.4 Total 88±4 249±9 237±10 216±9 38±4 Data 87 239 235 237 27 Table 3

Post-ﬁtbackground,signalandobservedyieldsforthethree-leptonandfour-leptonchannelsaswellasthet¯t Z controlregion.Uncertaintiesinthepredictionsincludeboth statisticalandsystematicuncertaintiesaddedinquadrature;correlationsamongsystematicuncertaintiesaretakenintoaccountinthecalculationofthetotal.

4-DF 4-SF-Z 4-SF-noZ 3-1j 3-2j 3-3j t¯t Z CR W V Z 9.6±3.5 5.0±1.8 10±4 62±23 85±30 84±30 – W Z 1.11±0.13 – 1.08±0.14 2580±80 1830±60 1110±50 5.7±0.4 Z Z 6.7±0.4 933±28 310±10 344±12 182±13 98±12 0.58±0.06 t¯t Z 5.1±0.5 0.55±0.08 4.5±0.5 7.6±1.1 22.6±2.5 82±8 122±9 t W Z 1.9±0.4 0.23±0.10 1.6±0.4 4.2±0.9 11.2±2.2 20±4 10.3±0.8 Non-prompt – – 0.18±0.12 130±50 77±28 59±24 0.47±0.18 γconv. – – – 42±8 32±7 9.6±3.4 0.4±0.6 Other 0.4±0.4 1.8±1.1 1.0±0.7 200±15 182±16 120±10 24.4±2.5 Total 24.8±3.5 941±27 329±10 3370±70 2430±40 1580±40 160±10 Data 28 912 360 3351 2438 1572 170

misidentiﬁcationrate,lepton fakefactor,andphoton-likeelectron scalefactor.Additionaluncertaintiescomefromthestatistical un-certaintiesinthe subsamples usedtoextrapolate thebackground evaluationsto the signal region.Nuisance parameters are treated as correlated for backgrounds evaluated using the same method andfromthesamesystematicsources.

Shape-only variations of the signal distributions due to QCD renormalisation and factorisation scales, PDF, andparton-shower matchingscalesareconsideredinthesimultaneousﬁt.The corre-sponding nuisance parameters are treated as correlated between the ννqq and ννν channelsinthe W W W analysisand be-tweenthree-leptonandfour-leptonchannelsintheW V Z analysis. TheseparametersaretreatedasuncorrelatedbetweentheW W W andW V Z analyses.

Tables 2 and 3 show the post-fit background, signal and ob-served yields for the signal regions and the background control region. Thecontributionto the W V V signal fromV H associated productionis ∼40% in theW W W fiducialregions and∼30% in the W V Z fiducialregions.Contributions fromSM processes pro-ducing thesame detector signature as eventsin thesesignal re-gions(orthett Z control¯ region)besidesthoselistedarecombined into“Other”.The uncertaintiesshownincludebothstatisticaland systematic uncertainties. Data and predictions agree in all chan-nels.

Fig.4showsthecomparisonbetweendataandpost-ﬁt predic-tionofthecombinedmj j distributionforthe ννqq channel,the number ofselected events forthe ννν channel, and theBDT output distributionsinthe3-2j and4-DFregions forthe W V Z

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Fig. 4. Post-ﬁtdistributionof(a)mj jfortheW W W→ ννqq analysis(ee,eμ,μe,μμcombined),(b)numberofeventsfortheW W W→ ννν analysis,andtheBDT

responseinthe(c)3-2jand(d)4-DFchannelsfortheW V Z analysis.Thecontributionsdenoted“Other”aredominatedbythe(a)W±W±+2jets,(b)t¯t W and(c)t Z

process,respectively.Theuncertaintybandincludesbothstatisticalandsystematicuncertaintiesasobtainedbytheﬁt.

analysis.The 3-2j and4-DFregions arechosen since theyhave thebestsensitivityamongthethree-leptonandfour-lepton chan-nels.Dataandpredictionsagreeinalldistributions.

The overall observed (expected) significance for W V V pro-ductionis found to be 4.1σ (3.1σ), constituting evidence forthe productionofthreemassivevectorbosons. Thecombinedbest-fit signal strength forthe W V V process,obtained by thefit to the elevensignalregionsandonecontrolregion,is μW V V=1.40+₋00..3937

withrespect to the SM prediction (Section 2). The compatibility of the individual signal strengths is 0.13, determined by repeat-ing the ﬁt, assuming individual signal strengths, and evaluating the p-value of the χ2 _of _the _comparison. _The _statistical

uncer-taintyinthemeasured signalstrengthis+₋₀0_..25₂₄andthesystematic uncertaintyis+₋0₀_..₂₇30.The impactofthe mostimportantgroupsof systematicuncertaintiesonthemeasuredvalueof μW V V isshown inTable4.Thelargestsystematicuncertainties comefrom uncer-taintiesrelatedtodata-drivenbackgroundevaluationsaffectingthe W W W channels, fromtheoretical uncertainties relatedto renor-malisationandfactorisationscalevariationsandexperimental un-certainties.Theimpactofeachsystematicuncertaintyontheresult isassessedandtherankingforthenuisanceparameterswiththe largestcontributiontotheuncertaintyin μW V V isshowninFig.5.

Table 4

Summaryoftheeffectsofthemostimportantgroupsofsystematicuncertainties inμW V V: Uncertainties relatedto data-drivenbackground evaluationsaffecting

theW W W channels(data-driven);theoreticaluncertaintiesrelatedto renormali-sationandfactorisationscalevariations,mostlyinthedibosonbackground, evalu-atedusingsimulations(theory);experimentaluncertaintiesinthesignaland back-groundevaluations(instrumental);thestatisticaluncertaintyinsimulatedevents (MCstat. uncertainty);andmodellinguncertaintyevaluatedbycomparingdifferent eventgenerators(generators).

Uncertainty source μW V V Data-driven +0.14 −0.14 Theory +0.15 −0.13 Instrumental +0.12 −0.09 MC stat. uncertainty +0.06 −0.04 Generators +0.04 −0.03

Total systematic uncertainty +0.30 −0.27

AdditionalfitsareperformedseparatelyintheW W W andthe W V Z channels.Forthesefitstheothersignal strengthisfixed to its SM expectation. Forthefits ofthe W W W channels, the W Z controlregiondefinedinSection4isusedinthefit.Theinclusion ofthe W Z controlregion helpsconstrainingthe overall normali-sationofthe W Z+jetsbackground,whichin thecombinedfit is constrainedbytheW V Z three-leptonsignalregions.Thet¯t Z

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con-Fig. 5. Impactofsystematicuncertaintiesontheﬁttedsignal-strengthparameter

μforthecombined W V V fittodata.Thesystematicuncertaintiesarelistedin decreasingorderoftheirpost-fitimpactinthefit,andonlythe15mostimportant aredisplayed.Theeffectofvaryingeachnuisanceparameterθisshown,whereθ0

isthepre-fitvalue,ˆθisthepost-fitvalue,andθand ˆθarethepre- andpost-fit uncertainties,respectively.

trolregion isusedinthe W V Z fit,however,itisnot usedinthe W W W fit.Theobserved(expected)significanceis3.2σ (2.4σ)for W W W productionand3.2σ (2.0σ)forW V Z production.

Table 5 and Fig. 6(a) summarise the observed and expected significanceswithrespect tothe background-onlyhypothesis and the observed best-fit values of the signal strength for the in-dividual and combined fits. The measured signal strengths from the individual fits are converted to inclusive cross-section mea-surements using the signal samples described in Section 2 and thecentral values ofthe theoretical predictions.All uncertainties

Table 5

ObservedandexpectedsigniﬁcanceswithrespecttotheSMbackground-only hy-pothesisforthefourW V V channelsenteringtheﬁt.

Decay channel Signiﬁcance

Observed Expected W W W combined 3.2σ 2.4σ W W W→ ννqq 4.0σ 1.7σ W W W→ ννν 1.0σ 2.0σ W V Z combined 3.2σ 2.0σ W V Z→ νqq 0.5σ 1.0σ W V Z→ νν/qq 3.5σ 1.8σ W V V combined 4.1σ 3.1σ

determined in the ﬁt are included in the conversion, except for thenormalisationuncertaintyinthesignalprediction.Theresults are: σW W W =0.65₋+00..1615(stat.)+

0.16

−0.14(syst.) pband σW W Z =0.55± 0.14(stat.)₋+0₀_..15₁₃(syst.) pb.Forthe σW W Z extraction,theW Z Z nor-malisationisﬁxedtotheSM expectation.Thecrosssectionofthe latterisnotreported,sincethereisnotenough sensitivitytothis channeltoquoteaseparatecross-sectionvalue.

Fig. 6(b)showsthe data,backgroundandsignal yields, where thediscriminant binsinallsignal regionsare combinedintobins of log₁₀(S/B), S beingthe expectedsignal yield and B the back-ground yield. The background and signal yields are shown after theglobalsignal-plus-backgroundﬁttothedata.

7. Conclusion

In conclusion, asearch for thejoint productionof three mas-sivevectorbosons(W orZ )inproton–protoncollisionsusing79.8 fb−1 _of _data _at √_s₌_{13 TeV collected} _by _the _ATLAS _detector_at

theLHC,ispresented.Eventswithtwo,threeorfourreconstructed electrons ormuons are analysed. Evidence forthe production of three massive vector bosons is observed with a combined sig-niﬁcance of 4.1standard deviations,where theexpectationis 3.1 standard deviations. The measured production cross sections are σW W W=0.65+₋0₀._.23₂₁ pb,and σW W Z =0.55+₋0₀._.21₁₉ pb, in agreement withtheStandardModelpredictions.

Fig. 6. (a)Extractedsignalstrengthsμforthefouranalysisregionsandforthecombination.(b)Eventyieldsasafunctionoflog10(S/B)fordata,backgroundBandthesignal

S.Eventsinallelevensignalregionsareincluded.Thebackgroundandsignalyieldsareshownaftertheglobalsignal-plus-backgroundﬁt.Thehatchedbandcorresponds tothesystematicuncertainties,andthestatisticaluncertaintiesarerepresentedbytheerrorbarsonthedatapoints.Thelowerpanelshowstheratioofthedatatothe expectedbackgroundestimatedfromtheﬁt,comparedtotheexpecteddistributionincludingthesignal(redline).

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Acknowledgements

We thankCERN for thevery successful operation ofthe LHC, aswell asthe support stafffromour institutions without whom ATLAScouldnotbeoperatedeﬃciently.

WeacknowledgethesupportofANPCyT,Argentina;YerPhI, Ar-menia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azer-baijan;SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI,Canada; CERN; CONICYT,Chile; CAS, MOSTandNSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic;DNRFandDNSRC,Denmark;IN2P3-CNRS,CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF, andMPG, Germany; GSRT, Greece;RGC,HongKong SAR,China;ISFandBenoziyo Center, Is-rael; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands;RCN, Norway;MNiSW andNCN, Poland;FCT, Portu-gal;MNE/IFA,Romania;MESofRussiaandNRCKI,Russian Feder-ation;JINR;MESTD,Serbia;MSSR,Slovakia;ARRSandMIZŠ, Slove-nia; DST/NRF, South Africa; MINECO, Spain;SRC and Wallenberg Foundation,Sweden;SERI,SNSF andCantonsofBernandGeneva, Switzerland;MOST,Taiwan; TAEK,Turkey;STFC,UnitedKingdom; DOE and NSF, United States of America. In addition, individual groupsandmembershavereceivedsupportfromBCKDF,CANARIE, CRCandComputeCanada,Canada;COST,ERC,ERDF,Horizon2020, andMarieSkłodowska-Curie Actions,European Union; Investisse-mentsd’AvenirLabexandIdex,ANR,France;DFGandAvH Foun-dation,Germany;Herakleitos,ThalesandAristeiaprogrammes co-ﬁnanced by EU-ESF and the Greek NSRF, Greece; BSF-NSF and GIF,Israel;CERCAProgrammeGeneralitatdeCatalunya,Spain;The RoyalSocietyandLeverhulmeTrust,UnitedKingdom.

The crucialcomputing support fromall WLCG partners is ac-knowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Swe-den),CC-IN2P3(France),KIT/GridKA(Germany),INFN-CNAF(Italy), NL-T1(Netherlands),PIC(Spain),ASGC(Taiwan),RAL(UK)andBNL (USA),theTier-2facilitiesworldwideandlargenon-WLCGresource providers.Majorcontributorsofcomputingresources arelistedin Ref. [70].

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TheATLASCollaboration

G. Aad101, B. Abbott128,D.C. Abbott102, O. Abdinov13,∗, A. Abed Abud70a,70b,K. Abeling53,

D.K. Abhayasinghe93,S.H. Abidi167,O.S. AbouZeid40, N.L. Abraham156,H. Abramowicz161, H. Abreu160,

Y. Abulaiti6, B.S. Acharya66a,66b,o, B. Achkar53, S. Adachi163,L. Adam99,L. Adamczyk83a,L. Adamek167,

J. Adelman121,M. Adersberger114, A. Adiguzel12c,aj,S. Adorni54, T. Adye144,A.A. Affolder146,Y. Aﬁk160,

C. Agapopoulou132, M.N. Agaras38,A. Aggarwal119, C. Agheorghiesei27c, J.A. Aguilar-Saavedra140f,140a,ai,

F. Ahmadov79,W.S. Ahmed103, X. Ai15a, G. Aielli73a,73b, S. Akatsuka85,T.P.A. Åkesson96, E. Akilli54,

A.V. Akimov110,K. Al Khoury132, G.L. Alberghi23b,23a, J. Albert176, M.J. Alconada Verzini88,

S. Alderweireldt36,M. Aleksa36, I.N. Aleksandrov79, C. Alexa27b,D. Alexandre19, T. Alexopoulos10,

A. Alfonsi120, M. Alhroob128,B. Ali142,G. Alimonti68a,J. Alison37,S.P. Alkire148, C. Allaire132,

B.M.M. Allbrooke156,B.W. Allen131, P.P. Allport21, A. Aloisio69a,69b,A. Alonso40,F. Alonso88,

C. Alpigiani148,A.A. Alshehri57,M. Alvarez Estevez98, D. Álvarez Piqueras174,M.G. Alviggi69a,69b,

Y. Amaral Coutinho80b,A. Ambler103,L. Ambroz135,C. Amelung26,D. Amidei105,

S.P. Amor Dos Santos140a, S. Amoroso46, C.S. Amrouche54,F. An78,C. Anastopoulos149, N. Andari145,

T. Andeen11,C.F. Anders61b,J.K. Anders20,A. Andreazza68a,68b,V. Andrei61a,C.R. Anelli176,

S. Angelidakis38,A. Angerami39,A.V. Anisenkov122b,122a,A. Annovi71a,C. Antel61a, M.T. Anthony149,

M. Antonelli51,D.J.A. Antrim171,F. Anulli72a, M. Aoki81, J.A. Aparisi Pozo174,L. Aperio Bella36,

G. Arabidze106,J.P. Araque140a, V. Araujo Ferraz80b, R. Araujo Pereira80b, C. Arcangeletti51,

A.T.H. Arce49,F.A. Arduh88,J-F. Arguin109, S. Argyropoulos77, J.-H. Arling46, A.J. Armbruster36,

L.J. Armitage92,A. Armstrong171,O. Arnaez167, H. Arnold120,A. Artamonov111,∗, G. Artoni135,S. Artz99,

S. Asai163,N. Asbah59, E.M. Asimakopoulou172, L. Asquith156, K. Assamagan29,R. Astalos28a,

R.J. Atkin33a,M. Atkinson173, N.B. Atlay151,H. Atmani132,K. Augsten142, G. Avolio36,R. Avramidou60a,

M.K. Ayoub15a,A.M. Azoulay168b,G. Azuelos109,ax, M.J. Baca21,H. Bachacou145, K. Bachas67a,67b,

M. Backes135,F. Backman45a,45b,P. Bagnaia72a,72b, M. Bahmani84, H. Bahrasemani152,A.J. Bailey174,

V.R. Bailey173,J.T. Baines144,M. Bajic40, C. Bakalis10,O.K. Baker183,P.J. Bakker120,D. Bakshi Gupta8,

S. Balaji157,E.M. Baldin122b,122a,P. Balek180, F. Balli145, W.K. Balunas135,J. Balz99,E. Banas84,

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D. Barberis55b,55a,M. Barbero101, T. Barillari115,M-S. Barisits36,J. Barkeloo131,T. Barklow153,

R. Barnea160,S.L. Barnes60c, B.M. Barnett144,R.M. Barnett18,Z. Barnovska-Blenessy60a, A. Baroncelli60a,

G. Barone29,A.J. Barr135,L. Barranco Navarro174, F. Barreiro98,J. Barreiro Guimarães da Costa15a,

S. Barsov138,R. Bartoldus153,G. Bartolini101, A.E. Barton89,P. Bartos28a, A. Basalaev46, A. Bassalat132,

R.L. Bates57,S.J. Batista167,S. Batlamous35e,J.R. Batley32, B. Batool151,M. Battaglia146,M. Bauce72a,72b,

F. Bauer145,K.T. Bauer171,H.S. Bawa31,m,J.B. Beacham126,T. Beau136,P.H. Beauchemin170,

F. Becherer52, P. Bechtle24, H.C. Beck53,H.P. Beck20,s,K. Becker52, M. Becker99, C. Becot46,

A. Beddall12d, A.J. Beddall12a,V.A. Bednyakov79,M. Bedognetti120, C.P. Bee155,T.A. Beermann76,

M. Begalli80b, M. Begel29,A. Behera155, J.K. Behr46,F. Beisiegel24,A.S. Bell94,G. Bella161,

L. Bellagamba23b,A. Bellerive34,P. Bellos9,K. Beloborodov122b,122a, K. Belotskiy112, N.L. Belyaev112,

D. Benchekroun35a, N. Benekos10,Y. Benhammou161, D.P. Benjamin6, M. Benoit54,J.R. Bensinger26,

S. Bentvelsen120,L. Beresford135,M. Beretta51, D. Berge46, E. Bergeaas Kuutmann172,N. Berger5,

B. Bergmann142, L.J. Bergsten26,J. Beringer18, S. Berlendis7, N.R. Bernard102,G. Bernardi136,

C. Bernius153,T. Berry93,P. Berta99, C. Bertella15a,I.A. Bertram89, G.J. Besjes40,

O. Bessidskaia Bylund182, N. Besson145, A. Bethani100, S. Bethke115, A. Betti24,A.J. Bevan92,J. Beyer115,

R. Bi139,R.M. Bianchi139,O. Biebel114, D. Biedermann19,R. Bielski36,K. Bierwagen99,

N.V. Biesuz71a,71b, M. Biglietti74a, T.R.V. Billoud109,M. Bindi53, A. Bingul12d,C. Bini72a,72b,

S. Biondi23b,23a,M. Birman180, T. Bisanz53,J.P. Biswal161,A. Bitadze100, C. Bittrich48,K. Bjørke134,

K.M. Black25, T. Blazek28a, I. Bloch46, C. Blocker26, A. Blue57,U. Blumenschein92, G.J. Bobbink120,

V.S. Bobrovnikov122b,122a, S.S. Bocchetta96,A. Bocci49, D. Boerner46, D. Bogavac14,

A.G. Bogdanchikov122b,122a,C. Bohm45a, V. Boisvert93,P. Bokan53,172, T. Bold83a,A.S. Boldyrev113,

A.E. Bolz61b, M. Bomben136, M. Bona92,J.S. Bonilla131,M. Boonekamp145,H.M. Borecka-Bielska90,

A. Borisov123,G. Borissov89,J. Bortfeldt36,D. Bortoletto135,V. Bortolotto73a,73b, D. Boscherini23b,

M. Bosman14,J.D. Bossio Sola103,K. Bouaouda35a,J. Boudreau139, E.V. Bouhova-Thacker89,

D. Boumediene38,C. Bourdarios132, S.K. Boutle57,A. Boveia126, J. Boyd36, D. Boye33b,ar,I.R. Boyko79,

A.J. Bozson93, J. Bracinik21, N. Brahimi101, G. Brandt182,O. Brandt61a,F. Braren46,U. Bratzler164,

B. Brau102,J.E. Brau131, W.D. Breaden Madden57,K. Brendlinger46,L. Brenner46,R. Brenner172,

S. Bressler180,B. Brickwedde99,D.L. Briglin21,D. Britton57,D. Britzger115,I. Brock24, R. Brock106,

G. Brooijmans39, W.K. Brooks147b, E. Brost121, J.H Broughton21, P.A. Bruckman de Renstrom84,

D. Bruncko28b, A. Bruni23b, G. Bruni23b, L.S. Bruni120, S. Bruno73a,73b, B.H. Brunt32,M. Bruschi23b,

N. Bruscino139,P. Bryant37, L. Bryngemark96,T. Buanes17, Q. Buat36,P. Buchholz151,A.G. Buckley57,

I.A. Budagov79, M.K. Bugge134, F. Bührer52,O. Bulekov112,T.J. Burch121, S. Burdin90, C.D. Burgard120,

A.M. Burger129,B. Burghgrave8,K. Burka84,J.T.P. Burr46, V. Büscher99,E. Buschmann53, P. Bussey57,

J.M. Butler25,C.M. Buttar57,J.M. Butterworth94,P. Butti36,W. Buttinger36, A. Buzatu158,

A.R. Buzykaev122b,122a,G. Cabras23b,23a,S. Cabrera Urbán174,D. Caforio56,H. Cai173,V.M.M. Cairo153,

O. Cakir4a, N. Calace36,P. Calaﬁura18, A. Calandri101,G. Calderini136, P. Calfayan65,G. Callea57,

L.P. Caloba80b,S. Calvente Lopez98, D. Calvet38, S. Calvet38,T.P. Calvet155,M. Calvetti71a,71b,

R. Camacho Toro136,S. Camarda36, D. Camarero Munoz98, P. Camarri73a,73b, D. Cameron134,

R. Caminal Armadans102,C. Camincher36,S. Campana36, M. Campanelli94,A. Camplani40,

A. Campoverde151,V. Canale69a,69b,A. Canesse103, M. Cano Bret60c,J. Cantero129,T. Cao161,Y. Cao173,

M.D.M. Capeans Garrido36,M. Capua41b,41a,R. Cardarelli73a,F.C. Cardillo149, I. Carli143, T. Carli36,

G. Carlino69a, B.T. Carlson139, L. Carminati68a,68b, R.M.D. Carney45a,45b,S. Caron119, E. Carquin147b,

S. Carrá46, J.W.S. Carter167,M.P. Casado14,f, A.F. Casha167, D.W. Casper171, R. Castelijn120,

F.L. Castillo174, V. Castillo Gimenez174,N.F. Castro140a,140e, A. Catinaccio36,J.R. Catmore134,A. Cattai36,

J. Caudron24,V. Cavaliere29, E. Cavallaro14, D. Cavalli68a,M. Cavalli-Sforza14,V. Cavasinni71a,71b,

E. Celebi12b, L. Cerda Alberich174,K. Cerny130, A.S. Cerqueira80a, A. Cerri156, L. Cerrito73a,73b_,

F. Cerutti18, A. Cervelli23b,23a, S.A. Cetin12b,D. Chakraborty121,S.K. Chan59, W.S. Chan120, W.Y. Chan90,

J.D. Chapman32,B. Chargeishvili159b,D.G. Charlton21, T.P. Charman92, C.C. Chau34, S. Che126,

A. Chegwidden106,S. Chekanov6,S.V. Chekulaev168a,G.A. Chelkov79,aw,M.A. Chelstowska36,B. Chen78,

C. Chen60a,C.H. Chen78, H. Chen29,J. Chen60a, J. Chen39,S. Chen137,S.J. Chen15c, X. Chen15b,av,

Y. Chen82, Y-H. Chen46, H.C. Cheng63a,H.J. Cheng15d, A. Cheplakov79,E. Cheremushkina123,

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G. Chiarelli71a, G. Chiodini67a,A.S. Chisholm36,21, A. Chitan27b, I. Chiu163,Y.H. Chiu176,M.V. Chizhov79,

K. Choi65, A.R. Chomont72a,72b,S. Chouridou162, Y.S. Chow120, M.C. Chu63a,J. Chudoba141,

A.J. Chuinard103, J.J. Chwastowski84, L. Chytka130,K.M. Ciesla84,D. Cinca47,V. Cindro91, I.A. Cioar˘a27b,

A. Ciocio18, F. Cirotto69a,69b, Z.H. Citron180, M. Citterio68a,D.A. Ciubotaru27b,B.M. Ciungu167,

A. Clark54, M.R. Clark39,P.J. Clark50,C. Clement45a,45b,Y. Coadou101,M. Cobal66a,66c,A. Coccaro55b,

J. Cochran78,H. Cohen161,A.E.C. Coimbra36,L. Colasurdo119,B. Cole39,A.P. Colijn120,J. Collot58,

P. Conde Muiño140a,g,E. Coniavitis52, S.H. Connell33b, I.A. Connelly57, S. Constantinescu27b,

F. Conventi69a,ay, A.M. Cooper-Sarkar135,F. Cormier175,K.J.R. Cormier167,L.D. Corpe94,

M. Corradi72a,72b, E.E. Corrigan96,F. Corriveau103,ae, A. Cortes-Gonzalez36, M.J. Costa174,F. Costanza5,

D. Costanzo149, G. Cowan93, J.W. Cowley32, J. Crane100, K. Cranmer124, S.J. Crawley57, R.A. Creager137,

S. Crépé-Renaudin58,F. Crescioli136, M. Cristinziani24,V. Croft120, G. Crosetti41b,41a,A. Cueto5,

T. Cuhadar Donszelmann149,A.R. Cukierman153, S. Czekierda84,P. Czodrowski36,

M.J. Da Cunha Sargedas De Sousa60b,J.V. Da Fonseca Pinto80b, C. Da Via100,W. Dabrowski83a,

T. Dado28a,S. Dahbi35e, T. Dai105,C. Dallapiccola102,M. Dam40, G. D’amen23b,23a, V. D’Amico74a,74b,

J. Damp99,J.R. Dandoy137,M.F. Daneri30, N.P. Dang181,N.D Dann100,M. Danninger175, V. Dao36,

G. Darbo55b, O. Dartsi5,A. Dattagupta131, T. Daubney46, S. D’Auria68a,68b,W. Davey24, C. David46,

T. Davidek143,D.R. Davis49,I. Dawson149, K. De8,R. De Asmundis69a,M. De Beurs120,

S. De Castro23b,23a, S. De Cecco72a,72b, N. De Groot119,P. de Jong120, H. De la Torre106,A. De Maria15c,

D. De Pedis72a,A. De Salvo72a,U. De Sanctis73a,73b,M. De Santis73a,73b,A. De Santo156,

K. De Vasconcelos Corga101,J.B. De Vivie De Regie132, C. Debenedetti146,D.V. Dedovich79,

M. Del Gaudio41b,41a, J. Del Peso98, Y. Delabat Diaz46, D. Delgove132, F. Deliot145,r, C.M. Delitzsch7,

M. Della Pietra69a,69b,D. Della Volpe54,A. Dell’Acqua36, L. Dell’Asta73a,73b,M. Delmastro5,

C. Delporte132,P.A. Delsart58,D.A. DeMarco167,S. Demers183,M. Demichev79,G. Demontigny109,

S.P. Denisov123,D. Denysiuk120, L. D’Eramo136,D. Derendarz84,J.E. Derkaoui35d, F. Derue136,

P. Dervan90,K. Desch24, C. Deterre46, K. Dette167, C. Deutsch24,M.R. Devesa30,P.O. Deviveiros36,

A. Dewhurst144, S. Dhaliwal26,F.A. Di Bello54, A. Di Ciaccio73a,73b, L. Di Ciaccio5, W.K. Di Clemente137,

C. Di Donato69a,69b,A. Di Girolamo36,G. Di Gregorio71a,71b, B. Di Micco74a,74b, R. Di Nardo102,

K.F. Di Petrillo59, R. Di Sipio167,D. Di Valentino34, C. Diaconu101, F.A. Dias40,T. Dias Do Vale140a,

M.A. Diaz147a,J. Dickinson18, E.B. Diehl105,J. Dietrich19,S. Díez Cornell46, A. Dimitrievska18,

W. Ding15b,J. Dingfelder24, F. Dittus36, F. Djama101, T. Djobava159b, J.I. Djuvsland17, M.A.B. Do Vale80c,

M. Dobre27b,D. Dodsworth26,C. Doglioni96,J. Dolejsi143, Z. Dolezal143, M. Donadelli80d,J. Donini38,

A. D’onofrio92,M. D’Onofrio90,J. Dopke144,A. Doria69a, M.T. Dova88,A.T. Doyle57, E. Drechsler152,

E. Dreyer152,T. Dreyer53, A.S. Drobac170,Y. Duan60b,F. Dubinin110, M. Dubovsky28a, A. Dubreuil54,

E. Duchovni180, G. Duckeck114, A. Ducourthial136, O.A. Ducu109,D. Duda115, A. Dudarev36,

A.C. Dudder99,E.M. Duﬃeld18,L. Duﬂot132,M. Dührssen36, C. Dülsen182,M. Dumancic180,

A.E. Dumitriu27b, A.K. Duncan57,M. Dunford61a,A. Duperrin101,H. Duran Yildiz4a,M. Düren56,

A. Durglishvili159b,D. Duschinger48,B. Dutta46,D. Duvnjak1,G. Dyckes137,M. Dyndal36,S. Dysch100,

B.S. Dziedzic84,K.M. Ecker115,R.C. Edgar105,T. Eifert36,G. Eigen17,K. Einsweiler18,T. Ekelof172,

M. El Kacimi35c, R. El Kosseiﬁ101,V. Ellajosyula172,M. Ellert172, F. Ellinghaus182,A.A. Elliot92,

N. Ellis36,J. Elmsheuser29, M. Elsing36, D. Emeliyanov144,A. Emerman39, Y. Enari163, J.S. Ennis178,

M.B. Epland49, J. Erdmann47,A. Ereditato20,M. Errenst36, M. Escalier132,C. Escobar174,

O. Estrada Pastor174,E. Etzion161,H. Evans65,A. Ezhilov138, F. Fabbri57, L. Fabbri23b,23a,V. Fabiani119,

G. Facini94,R.M. Faisca Rodrigues Pereira140a,R.M. Fakhrutdinov123,S. Falciano72a,P.J. Falke5,S. Falke5,

J. Faltova143, Y. Fang15a, Y. Fang15a,G. Fanourakis44, M. Fanti68a,68b, A. Farbin8, A. Farilla74a,

E.M. Farina70a,70b,T. Farooque106,S. Farrell18, S.M. Farrington178, P. Farthouat36,F. Fassi35e,

P. Fassnacht36,D. Fassouliotis9, M. Faucci Giannelli50, W.J. Fawcett32,L. Fayard132, O.L. Fedin138,p_,

W. Fedorko175, M. Feickert42, S. Feigl134, L. Feligioni101, A. Fell149, C. Feng60b,E.J. Feng36, M. Feng49,

M.J. Fenton57,A.B. Fenyuk123, J. Ferrando46, A. Ferrante173, A. Ferrari172, P. Ferrari120,R. Ferrari70a,

D.E. Ferreira de Lima61b, A. Ferrer174,D. Ferrere54, C. Ferretti105, F. Fiedler99, A. Filipˇciˇc91,

F. Filthaut119, K.D. Finelli25, M.C.N. Fiolhais140a,a, L. Fiorini174,F. Fischer114, W.C. Fisher106,I. Fleck151,

P. Fleischmann105, R.R.M. Fletcher137,T. Flick182,B.M. Flierl114, L.M. Flores137,L.R. Flores Castillo63a,