Measurements of gluon-gluon fusion and vector-boson fusion Higgs boson production cross-sections in the $H \to WW^{\ast} \to e\nu\mu\nu$ decay channel in $pp$ collisions at $\sqrt{s}=13$ TeV with the ATLAS detector

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Physics

Letters

B

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Measurements

of

gluon–gluon

fusion

and

vector-boson

fusion

Higgs

boson

production

cross-sections

in

the

H

→

W W

∗

→

e

νμν

decay

channel

in

pp collisions

at

√

s

=

13 TeV with

the

ATLAS

detector

.TheATLASCollaboration

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

Articlehistory:

Received28August2018

Receivedinrevisedform15November2018 Accepted18November2018

Availableonlinexxxx Editor: W.-D.Schlatter

Higgsbosonproductioncross-sectionsinproton–protoncollisionsaremeasuredintheH→W W∗→eνμν

decaychannel.Theproton–protoncollisiondatawereproducedattheLargeHadronColliderata centre-of-massenergyof13 TeV andrecordedbytheATLASdetectorin2015and2016,corresponding toan integratedluminosityof36.1 fb−1.TheproductoftheH→W W∗branchingfraction timesthegluon– gluonfusionandvector-bosonfusioncross-sectionsaremeasuredtobe11.4₋+₁1_..2₁(stat.)+₋₁1_..8₇(syst.)pb and 0.50+0.24

−0.22(stat.)±0.17(syst.)pb,respectively,inagreementwithStandardModelpredictions.

1. Introduction

ThisLetterpresentsa measurementoftheinclusiveHiggs bo-son production cross-sections via gluon–gluon fusion (ggF) and vector-bosonfusion (VBF) through the decay H→W W∗→eνμν using 36.1 fb−1 of proton–proton collisions at a centre-of-mass energy of 13 TeV recorded by the ATLAS detector. Higgs boson couplings havebeen studied inthis channel with Run-1 data by theATLAS [1] and CMS [2] experiments andrecentlywithRun-2 data by the CMS experiment [3]. The H→W W∗ decay channel has the second-largest branching fraction and allowed the most preciseHiggsbosoncross-sectionmeasurementsinRun-1 [4].The measured cross-sectionof theggF productionprocess probes the Higgsbosoncouplingstogluonsandheavyquarks,whiletheVBF process directly probes the couplings to W and Z bosons. The leading-orderdiagramsfortheggF andVBFproductionprocesses aredepictedinFig.1.

2. ATLASdetector

ATLAS is a particle detector designedto achieve a nearly full coverage in solid angle1 [5,6]. It consists of an inner tracking detectorsurrounded by a thinsuperconducting solenoid,

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

1 _ATLAS_uses_a_right-handed_coordinate_system_with_its_origin_at_the _nominal interactionpoint(IP)inthecentreofthedetectorandthez-axisalongthebeam pipe.Thex-axispointsfromtheIPtothecentreoftheLHCring,andthe y-axis pointsupward.Cylindricalcoordinates(r,φ)areusedinthe transverseplane,φ

beingtheazimuthalanglearoundthez-axis.Thepseudorapidityisdeﬁnedinterms ofthepolarangleθasη= −ln tan(θ/2).Thedistancein(η,φ)coordinates,R=

magneticandhadroniccalorimeters,andamuonspectrometer in-corporatingthreelargesuperconductingair-coretoroidalmagnets. Theinner trackingdetector(ID)islocatedina2 Tmagneticfield and is designedto measure charged-particle trajectories up to a pseudorapidity of |η|=2.5. Surrounding the ID are electromag-neticandhadroniccalorimeters,whichuseliquidargon(LAr)and leadabsorberfortheelectromagneticcentralandendcap calorime-ters(|η|<3.2),copperabsorberforthehadronicendcap calorime-ter(1.5<|η|<3.2),andscintillator-tileactivematerialwithsteel absorberforthecentral(|η|<1.7)hadroniccalorimeter.Thesolid angle coverage is extended to |η|=4.9 with forward copper/LAr and tungsten/LAr calorimeter modules. The muon spectrometer comprises separate trigger chambers within the range |η|<2.4 andhigh-precision trackingchamberswithin the range |η|<2.7, measuring thedeflection ofmuonsin amagnetic field generated bythethreesuperconductingtoroidalmagnets.A two-leveltrigger systemisusedtoselectevents [7].

3. SignalandbackgroundMonteCarlopredictions

HiggsbosonproductionviaggFwassimulatedat next-to-next-to-leading-order (NNLO) accuracy in QCD using the Powheg-Box v2 NNLOPS program [8], withthe PDF4LHC15 NNLO set of par-tondistributionfunctions(PDF) [9].ThesimulationachievesNNLO accuracyforarbitraryinclusive gg→H observablesby reweight-ingtheHiggsbosonrapidityspectruminHj-MiNLO [10] tothatof HNNLO [11].ThetransversemomentumspectrumoftheHiggs bo-

φ2₊_η2_,_is_also_used_to_deﬁne_cone_sizes._Transverse_momentum_and_energy aredeﬁnedaspT=psinθandET=E sinθ,respectively.

https://doi.org/10.1016/j.physletb.2018.11.064

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Fig. 1. Diagramsfortheleadingproductionmodes(ggFandVBF),wheretheV V H andqqH couplingverticesaremarkedwithshadedandemptycircles,respectively.TheV representsaW orZ vectorboson.

Table 1

Overviewofsimulationtoolsusedtogeneratesignalandbackgroundprocesses,andtomodeltheUEPS.ThePDFsetsarealsosummarised.Alternativeeventgeneratorsand conﬁgurationsusedtoestimatesystematicuncertaintiesareshowninparentheses.

Process Matrix element (alternative) PDF set UEPS model (alternative model) Prediction order for total cross-section ggF H Powheg-Boxv2 PDF4LHC15 NNLO [9] Pythia8 [14] N3LO QCD+NLO EW [24–28]

NNLOPS [8,10,16]

(MG5_aMC@NLO [47,48]) (Herwig 7 [49])

VBF H Powheg-Boxv2 PDF4LHC15 NLO Pythia8 NNLO QCD+NLO EW [24,29–31] (Herwig 7)

V H Powheg-Boxv2 [50] PDF4LHC15 NLO Pythia8 NNLO QCD+NLO EW [51–53] qq→W W Sherpa2.2.2 [32,33] NNPDF3.0NNLO [34] Sherpa2.2.2 [35,36] NLO [37]

(Powheg-Box v2, (Herwig++ [49])

MG5_aMC@NLO)

gg→W W Sherpa2.1.1 [37] CT10 [54] Sherpa2.1 NLO [38]

W Z/Vγ∗/Z Z Sherpa2.1 CT10 Sherpa2.1 NLO [37]

Vγ Sherpa2.2.2 NNPDF3.0NNLO Sherpa2.2.2 NLO [37]

(MG5_aMC@NLO) (CSS variation [35,55])

tt¯ Powheg-Boxv2 [56] NNPDF3.0NLO Pythia8 NNLO+NNLL [57]

(Sherpa 2.2.1) (Herwig 7)

W t Powheg-Boxv1 [58] CT10 [54] Pythia6.428 [59] NLO [58]

(MG5_aMC@NLO) (Herwig++)

Z/γ∗ Sherpa2.2.1 NNPDF3.0NNLO Sherpa2.2.1 NNLO [60,61]

sonobtainedwiththissamplewasfoundtobecompatiblewithin uncertainties with the resummed NNLO+NNLL HRes2.3 calcula-tion [12,13].Theparton-leveleventsproducedbythe Powheg-Box v2NNLOPSprogramwerepassed to Pythia 8 [14] toprovide par-tonshowering, hadronisation andthe underlyingevent,usingthe AZNLOsetofdata-tunedparameters [15].

Higgs boson production via VBF was simulated at next-to-leading-order (NLO) accuracy in QCD using Powheg-Box v2 [8,

10,16,17] withthe PDF4LHC15NLO PDF set [9]. The parton-level eventswerepassed to Pythia 8 [14] withthesameparametersas forggF.

The mass of the Higgs boson was set to 125 GeV, compati-blewiththeexperimental measurement [18–20].The correspond-ing SM branching fraction BH→W W∗ is calculated using

HDe-cay v6.50 [21,22] tobe 0.214 [23].The H→W W∗→ ν ν decay, where =e or μ, always includes the small contribution from

W →τ ν→ ννν decays. Other production anddecay modes of theHiggsbosonareeitherﬁxedtoSMpredictions(V H production andH→τ τ decay)orneglected(tt H and¯ bbH associated¯ produc-tion).

TheggF productioncross-section was calculatedwith next-to-next-to-next-to-leading-order accuracy in QCD and includes NLO electroweak(EW)corrections [24–28]. TheNLO QCDandEW cal-culationsareusedwithapproximateNNLOQCDcorrectionsforthe VBFproductioncross-section [24,29–31].

The W W backgroundwas generated separately forthe qq→ W W and gg→W W production mechanisms. The qq→W W

productionprocesswasgeneratedusing Sherpa 2.2.2 [32,33] inter-facedwiththeNNPDF3.0NNLO PDFset [34] andthe Sherpa par-tonshower,hadronisationandunderlyingeventsimulation(UEPS) model [35,36].Thematrixelementswerecalculatedforuptoone

additionalpartonatNLOanduptothreeadditionalpartonsatLO precision.Theloop-induced gg→W W processwassimulatedby Sherpa 2.1.1 with zero orone additional jet [37]. The sample is normalisedtotheNLOgg→W W cross-section [38].Interferences with direct W W productionhave anegligible impact afterevent selectioncutshavebeenappliedandare,therefore,notconsidered inthisanalysis[39].

WhileNNLOcross-sectionsareavailablefordibosonproduction processes [40–42],the Sherpa MEPS@NLOprescription [36] isused inthisanalysis.Thisprocedurealreadycapturesthemajorityofthe NNLOshapecorrections.

The MC generators, PDFs,andprogrammes used fortheUEPS are summarised inTable1. Theorder oftheperturbative predic-tionforeachsampleisalsoreported.

Thegeneratedeventswerepassedthrougha Geant 4 [43] sim-ulation of the ATLAS detector [44] and reconstructed with the same analysis software as used for the data. Additional proton– protoninteractions(pile-up)areincludedinthesimulationforall generated eventssuch thatthe distributionsof theaverage num-berofinteractionsperbunchcrossingreproducesthatobservedin thedata.Theinelasticproton–protoncollisions wereproduced us-ing Pythia 8 withthe A2 setof data-tuned parameters [45] and the MSTW2008LO PDF set [46]. Correction factors are applied to account for small differences observed between data and simu-lation inelectrons, muons, andjetsidentiﬁcationeﬃciencies and energy/momentumscalesandresolutions.

4. Eventselectionandcategorisations

Events are triggered using single-lepton triggers and a dilep-ton e–μ trigger. The transversemomentum threshold ranges

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Eventselectioncriteriausedtodeﬁnethesignalregionsinthe H→W W∗→eνμνanalysis.FortheNjet≥2 VBFsignalregion,theinputvariablesusedfortheboosted decisiontree(BDT)trainingarealsoreported.

Category Njet,(pT>30 GeV)=0 ggF Njet,(pT>30 GeV)=1 ggF Njet,(pT>30 GeV)≥2 VBF

Preselection

Two isolated, different-ﬂavour leptons( =e,μ)with opposite charge plead T >22 GeV,p sublead T >15 GeV m >10 GeV pmiss T >20 GeV Background rejection Nb-jet,(pT>20 GeV)=0

φ( ,Emiss T ) >π/2 max m T >50 GeV p T >30 GeV mτ τ<mZ−25 GeV

H→W W∗→eνμνtopology m <55 GeV central jet veto

φ <1.8 outside lepton veto

Discriminant variable mT BDT

BDT input variables mj j,yj j, m ,φ , mT, C , ,jm j, ptotT

tween24 GeV and26 GeV forsingle-electrontriggersandbetween 20 GeV and 26 GeV for single-muon triggers, depending on the runperiod [7].Thee–μtriggerrequiresa minimumpT threshold

of17 GeV forelectronsand14 GeV formuons.

Electroncandidates are reconstructed from energy clustersin the electromagnetic calorimeter with an associated well-recon-structedtrack [62,63]. Electronsarerequiredtosatisfy |η|<2.47, excluding the transition region between the barrel and endcap calorimeters,1.37<|η|<1.52.Muoncandidatesareselectedfrom tracksreconstructedintheID matchedto tracksreconstructedin themuonspectrometer [64] andare requiredtosatisfy |η|<2.5. To reject particles misidentiﬁed as leptons, several identiﬁcation requirementsaswellascalorimeterandtrackisolationcriteria [64,

65] are applied. The electron identiﬁcation criteria applied pro-videan eﬃciencyinthe range88–94%depending on electron pT

and η.For muons, highefficiency,closeto 95%, isobserved over the full instrumented η range. The final lepton-selection criteria requiretwo different-flavour opposite-signleptons, the higher-pT

(leading)leptonwithpT>22 GeV andthesubleadingleptonwith

pT>15 GeV.Atleastoneoftheleptonsmustcorrespondtoa

lep-tonthattriggeredtherecordingoftheevent.Whenthee–μ trig-gerissolelyresponsiblefortherecordingoftheevent,eachlepton mustbematchedtooneofthetriggerobjects.Thetrigger match-ingrequirestheoﬄinepTofthematchingobjecttobehigherthan

thetriggerlevelthresholdbyatleast1 GeV.Jetsarereconstructed usingtheanti-kt algorithm [66] with aradiusparameter R=0.4.

Thefour-momentaofjetsarecorrectedforthenon-compensating response of calorimeter, signal losses due to noise threshold ef-fects, energylost in non-instrumentedregions, andcontributions from pile-up [67]. Jets are required to have pT>20 GeV and

|η|<4.5.A multivariateselectionthatreducescontaminationfrom pile-up [68] isappliedtojetswithpT<60 GeV and|η|<2.4,

util-isingcalorimeterandtrackinginformationtoseparatehard-scatter jetsfrom pile-up jets. For jets with pT<50 GeV and |η|>2.5,

jet shapesand topologicaljet correlationsin pile-up interactions areexploitedtoreducecontamination.JetswithpT>20 GeV and

|η|<2.5 containingb-hadrons(b-jets)areidentifiedusinga multi-variatetechniquehavingasinputthetrackimpactparametersand informationfrom secondary vertices. The adopted working point provides a nominal 3% light-flavour (u-, d-, s-quark and gluon) misidentificationrate anda 32% c-jet misidentification ratewith an average 85% b-jet tagging efficiency, asestimated from simu-latedt¯t events [69]. Ambiguities fromoverlapping reconstructed jetandleptoncandidatesareresolvedasfollows.Ifareconstructed muonshares an ID trackwitha reconstructedelectron, the elec-tron is removed. Reconstructed jetsgeometrically overlapping in a cone ofradius R=0.2 withelectrons or muonsare also re-moved.Electronsandmuons, withtransversemomentum pT,are

removed ifthey are within R=min(0.4,0.04+10 GeV/pT) of

theaxis of anysurviving jet. The missing transverse momentum

Fig. 2. Jet multiplicity distribution after applying the preselection criteria. The shadedbandrepresentsthesystematicuncertaintyandaccountsforexperimental uncertaintiesonly.

Emiss

T (with magnitude EmissT ) is deﬁned as the negative vector

sumof the pT ofall the selectedleptons andjets, andincluding

reconstructed tracks not associated with these objects, and con-sistentwithoriginatingfromtheprimary pp collision [70].A sec-ond deﬁnitionofmissingtransversemomentum (inthiscase de-notedpmiss_T )usesthetracksassociatedwiththejetsinsteadofthe calorimeter-measured jets. It was found during the optimisation that pmiss

T performsbetterintermsofbackgroundrejection [70].

Events areclassiﬁedintoone ofthreecategoriesbasedonthe numberofjetswithpT>30 GeV:eventswithzerojetsandevents

with exactly one jet target the ggF production mode (Njet=0

and Njet=1 ggF categories), and events with at least two jets

target the VBF production mode (Njet≥2 VBF category). Fig. 2

shows the jet multiplicity distribution after applying the prese-lectioncriteriadeﬁnedinTable2.Thedifferentbackground com-positions asa functionofjetmultiplicity motivate thedivision of the data sample into the various Njet categories and the

deﬁni-tion ofa signal region ineach jet multiplicity bin.Detailsof the background estimationare provided in Section 5. Toreject back-groundfrom top-quarkproduction, eventscontaining b-jets with

pT>20 GeV (Nb-jet,(pT>20 GeV)) are vetoed. The full event

selec-tion is summarised in Table 2, where φ( ,Emiss

T ) is deﬁned

as the azimuthal angle between Emiss

T and the dilepton system,

p

T is the transverse momentum of the dilepton system, m is

the invariant mass of the two leptons, φ is the azimuthal

angle between the two leptons, and maxm _T is the larger of

m i T = 2 p i T ·EmissT · 1−cosφ i,EmissT

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Fig. 3. Post-ﬁtmTdistributionswiththesignalandthebackgroundmodelled contributionsinthe(a) Njet=0 and(b) Njet=1 signalregions.Thehatchedbandshowsthe totaluncertaintyofthesignalandbackgroundmodelled contributions.

Fig. 4. Post-ﬁtmj j(a)andyj j(b)distributionswithsignalandbackgroundmodelled contributionsintheNjet≥2 VBFsignalregion.ThedashedlineshowstheVBFsignal scaledbyafactorof30.Thehatchedbandshowsthetotaluncertaintyofthesignalandbackgroundmodelled contributions.

Table 3

Eventselectioncriteriausedtodeﬁnethecontrolregions.Everycontrolregionselectionstartsfromtheselectionlabelled “Preselection”inTable2.Nb-jet,(20 GeV<pT<30 GeV)representsthenumberofb-jetswith20 GeV<pT<30 GeV.

CR Njet,(pT>30 GeV)=0 ggF Njet,(pT>30 GeV)=1 ggF Njet,(pT>30 GeV)≥2 VBF

W W 55<m <110 GeV m >80 GeV φ <2.6 |mτ τ−mZ| >25 GeV Nb-jet,(pT>20 GeV)=0 maxm T >50 GeV

t¯t/W t Nb-jet,(20 GeV<pT<30 GeV)>0 Nb-jet,(pT>30 GeV)=1 Nb-jet,(pT>20 GeV)=1

Nb-jet,(20 GeV<pT<30 GeV)=0

φ( ,Emiss T ) >π/2 max m T

>50 GeV central jet veto p

T >30 GeV mτ τ<mZ−25 GeV

φ <2.8 outside lepton veto

Z/γ∗ Nb-jet,(pT>20 GeV)=0

m <80 GeV

no pmiss

T requirement central jet veto

maxm

T

>50 GeV outside lepton veto

φ >2.8 mτ τ>mZ−25 GeV |mτ τ−mZ| ≤25 GeV

thertheleadingorthesubleadinglepton.The“outsideleptonveto” requiresthetwoleptonstoresidewithintherapiditygapspanned by the two leading jets, and the “central jet veto”rejects events withadditionaljetswithpT>20 GeV intherapiditygapbetween

the two leading jets. In the Njet=1 and Njet≥2 categories, the

invariant mass of the τ-lepton pair (mττ ), calculated using the collinearapproximation [71],isusedtovetobackgroundfromZ→ τ τ production.Signal regions(SRs)are deﬁnedineach Njet

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goryafterapplyingallselectioncriteria. Forboththe Njet=0 and

Njet=1 ggFSRs,eightregions,laterusedfortheﬁt,aredeﬁnedby

subdividing inm atm <30 GeV andm ≥30 GeV, in pT of

thesubleadingleptonat psublead

T <20 GeV and psubleadT ≥20 GeV,

and by the ﬂavour of the subleading lepton. For the categories withzero jets andwith exactly one jet, the discriminating vari-ablebetweensignalandSM backgroundprocessesisthedilepton transversemass,deﬁnedasmT=

E_T +Emiss_T 2− p _T +Emiss_T 2 where E T = |p

T |2+m2 andp T isthe vector sumofthe

lep-tontransversemomenta.ThediscriminatingvariablemT isusedin

theggF SRs,witheight binsfor the Njet=0 andsixbins forthe

Njet=1 regions.Thebinboundariesarechosensuchthat

approxi-matelythesamenumberofsignaleventsisexpectedineachbin. ThemT distributions forthe Njet=0 and Njet=1 SRs are shown

in Fig. 3. All figures in thisLetter, except Fig. 2, use signal and backgroundnormalisationsasfittedbythefinalstatisticalanalysis ofall signalandcontrol regions, includingpullsofstatisticaland systematicuncertainty parameters (post-fit). Forthe Njet≥2 VBF

selection, a boosted decisiontree (BDT) [72] is used to enhance discrimination power between the VBF signal and backgrounds, including the ggF process. Kinematic variables of the two lead-ing jets ( j) and the two leading leptons ( ) are used as inputs to the BDT: the invariant masses (mj j, m ), the difference

be-tween the two jet rapidities (yj j), and the difference between

the azimuthal angles of the two leptons (φ ). Other variables

usedinthe BDT trainingare: mT,thelepton η-centrality( C ,

whereC = |2η −ηj|/ηj j),whichquantiﬁes thepositionsof

theleptonsrelativeto theleadingjetsinpseudorapidity [73],the sumof the invariant masses ofall four possiblelepton–jet pairs (_,_jm j),andthetotaltransversemomentum(ptotT ),whichis

de-ﬁnedasthemagnitudeofthevectorialsumofallselectedobjects. Theobservablesprovidingthe bestdiscrimination betweensignal andbackgroundare mj j andyj j,andare showninFig. 4after

applyingallselections. TheBDTscorereﬂectsthecompatibilityof an eventwithVBF-likekinematics. Signal-like eventswouldtend tohavehighBDTscore,whilebackground-likeeventstendtohave lowBDTscore.Thesignalpurity,therefore,increasesathighvalues ofBDTscore.TheBDT scoreisusedasthediscriminatingvariable inthe statistical analysis withfour bins. The bin boundaries are chosen tomaximise theexpected sensitivityforthe VBF produc-tionmode,resultinginsmallerbinwidthsforlargervaluesofthe BDT score. In the highest-score BDT bin, the expected signal-to-backgroundratiooftheVBFsignal isapproximately0.6. The BDT distributionfortheVBF-enrichedregionispresentedinFig.5.

5. Backgroundestimation

ThebackgroundcontaminationintheSRsoriginatesfrom vari-ousprocesses:non-resonant W W , top-quarkpair(tt)¯ and single-top-quark(W t),diboson(W Z , Z Z ,Wγ andWγ∗)andDrell–Yan (mainly Z→τ τ,hereafterdenotedZ/γ∗)production.Other back-groundcontributionsarisefromW+jets andmulti-jetproduction withmisidentified leptons, which are either non-prompt leptons fromdecays of heavy-flavourhadrons orjets faking prompt lep-tons.Dedicated regionsindata,identifiedhereafter ascontrol re-gions(CRs),areused tonormalisethepredictions ofsomeofthe background processes. CRs are defined for the main background processes: W W (only for Njet≤1 final states),t¯t/W t,and Z/γ∗.

Table3summarisestheeventselectionforallCRs.FortheNjet=0

andNjet=1 W W CRs, m selectionsorthogonal to those ofthe

SRsareapplied. Forthett/W t CRs,¯ the b-vetois replacedwitha

b-tagrequirement.FortheNjet=1 andNjet≥2 VBFZ/γ∗CRs,the

mττ selectionisinverted,whilefortheNjet=0 Z/γ∗CRtheφ

Table 4

Post-ﬁtnormalisationfactorswhichscalethecorrespondingestimatedyieldsinthe signalregion;thedashindicateswhereMC-basednormalisationisused.Theerrors includethestatisticalandsystematicuncertainties.

Category W W t¯t/W t Z/γ∗ Njet,(pT>30 GeV)=0 ggF 1.06±0.09 0.99±0.17 0.84±0.04

Njet,(pT>30 GeV)=1 ggF 0.97±0.17 0.98±0.08 0.90±0.12 Njet,(pT>30 GeV)≥2 VBF – 1.01±0.01 0.93±0.07

Fig. 5. Post-ﬁtBDTscoredistributionwiththesignalandthebackgroundmodelled contributionsintheVBFsignalregion.Thehatchedbandshowsthe total uncer-taintyofthesignalandbackgroundmodelled contributions.

selection criterionis inverted.Fig.6 presentsthepost-ﬁt mT

dis-tributionsintheNjet=0 andNjet=1 CRs.

In Fig. 7, the post-ﬁt yj j distributions in the Njet≥2 VBF

CRsare shown.Data andsimulationareinagreement within un-certainties for all the relevant distributions in the different CRs. Thebackgroundcontributions withmisidentifiedleptons are esti-matedusingadata-driventechnique.A controlsamplewhereone ofthetwoleptoncandidates failstomeetthenominal identifica-tionandisolationcriteriabutsatisfieslooseridentificationcriteria, referred as an anti-identifiedlepton, is used.The contribution of this background in the SRs and CRs is then obtained by scaling thenumberofdataevents,afterthesubtractionofprocesseswith two prompt leptons, in the control samples by an extrapolation factor. The latter is measured in a Z+jets-enriched data sample, where the Z boson decays to a pair of electrons or muons, and themisidentifiedleptoncandidaterecoilsagainsttheZ boson.The extrapolationfactorisdefinedastheratioofthenumbersof iden-tified and anti-identified leptons, and is measured in bins of pT

andη.Furthermore,asample compositioncorrectionfactoris ap-plied separately in pT<25 GeV and pT>25 GeV bins, and is

deﬁnedineach binastheratioofthe extrapolationfactors mea-suredin W+jets and Z+jets MCsimulation.Thetotaluncertainty of thebackground withmisidentiﬁed leptons includes uncertain-ties due to the difference in sample composition between the

W+jets and Z+jets control samples determined withMC simu-lation,thestatisticaluncertaintyoftheZ+jets controlsample,and the subtractionof other processes. In the VBF regions, the back-groundestimationiscorrectedforthecontaminationfromevents with two misidentiﬁed leptons, whose origin is largely multi-jet events.This contributionis negligible inother regions. Details of thismethodcanbefoundinRef. [1].

The post-ﬁt backgroundnormalisation factorsare summarised inTable 4.The Z/γ∗ normalisation factorsare affected by resid-ual misalignments in the inner detector which distort the mea-surements of the track parameters for particles originating from secondaryverticese.g.leptonsfrom τ decays.

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Fig. 6. Post-ﬁtmTdistributionswithsignalandbackgroundexpectationsintheNjet=0 andNjet=1 controlregionsfortheW W (a, b),t¯t/W t (c, d),andZ/γ∗(e, f)processes. Thehatchedbandshowsthetotaluncertaintyofthesignalandbackgroundmodelled contributions.Somecontributionsaretoosmalltobevisible.

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130

Fig. 7. Post-ﬁtyj jdistributionwithsignalandbackgroundmodelled contributionsinthe(a) t¯t/W t and(b) Z/γ∗controlregionsintheNjet≥2 VBFanalysiscategory.The hatchedbandshowsthetotaluncertaintyofthesignalandbackgroundmodelled contributions.Somecontributionsaretoosmalltobevisible.

6. Systematicuncertainties

The sources of uncertainty can be classiﬁed into two cate-gories: experimental and theoretical. The dominant experimental uncertaintiesarethejetenergyscaleandresolution [74],andthe

b-tagging eﬃciency [75].Other sources ofuncertainty are lepton energy(momentum)scaleandresolution,identiﬁcationand isola-tion [63,64,76],missingtransversemomentummeasurement [77], modellingofpile-up,andluminositymeasurement [78].The lumi-nosityuncertainty is only applied to the Higgsboson signal and to background processes that are normalised to theoretical pre-dictions.Forthemain processes,thetheoretical uncertainties are assessedby acomparisonbetweennominalandalternativeevent generatorsandUEPS models,asindicated inTable 1.Forthe pre-dictionof W Z , Z Z , Vγ∗,and Vγ production(V V ), variationsof thematchingscaleareconsideredinsteadofanalternative gener-ator.Inaddition,theeffectsofQCDfactorisationand renormalisa-tionscalevariationsandPDFmodeluncertaintiesareevaluated.

7.Signalregionyieldsandresults

The ggF and VBF cross-sections are obtained froma simulta-neousstatistical analysis ofthe data samples in all SRs and CRs bymaximisinga likelihoodfunction ina fitusingscaling param-eters multiplying the predicted total production cross-section of eachsignalprocessandapplyingtheprofilelikelihoodmethod.The CRsareusedtodeterminethenormalisationofthecorresponding backgrounds.Thesystematicuncertaintiesenterthefitasnuisance parametersinthelikelihoodfunction.

Table5showsthepost-fityieldsforallofthethreeSRs.Yields inthehighest-scoreVBFBDTbinarealsogiven. Theuncertainties inthetotal yieldsare smallerthan thoseofsome ofthe individ-ualbackgroundprocesses.Thiseffectisduetocorrelationsamong differentdataregions,backgroundprocesses,andnuisance param-eters.Thecorrelationsare imposed bythe fitasitconstrains the totalyieldto matchthedata.Forexample,fortheb-tagging effi-ciency,whichisthemainsourceofuncertaintyinthett/W t yields¯

intheSRsaswellasinW W CRs,thecombinationofthesetwo re-gionsinthestatisticalanalysisleadstoananti-correlationbetween theSRyieldsofthe W W andtt/W t backgrounds.¯ Changesinthe

b-taggingeﬃciencysimultaneouslyincrease/decreasetheyieldsof

t¯t/W t andW W backgrounds, resultingina smalluncertaintyin thecombinedyieldsoftheprocessesbutlargeuncertaintiesinthe individualcomponents.

Table 5

Post-ﬁtMCanddatayieldsintheggFandVBFSRs.Yieldsinthehighest-scoreVBF BDTbinarealsopresented.Thequoteduncertaintiesincludethetheoreticaland ex-perimentalsystematicsourcesandthoseduetosamplestatistics.Thesumofallthe contributionsmaydifferfromthetotalvalueduetorounding.Moreover,thetotal uncertaintydiffersfromthesuminquadratureofthesingle-processuncertainties duetothecorrelations.

Process Njet=0 ggF Njet=1 ggF Njet≥2 VBF

Inclusive BDT:[0.86,1.0] HggF 639±110 285±51 42±16 6±3 HVBF 7±1 31±2 28±16 16±6 W W 3016±203 1053±206 400±60 11±2 V V 333±38 208±32 70±12 3±1 t¯t/W t 588±130 1397±179 1270±80 14±2 Mis-Id 447±77 234±49 90±30 6±2 Z/γ∗ 27±11 76±24 280±40 4±1 Total 5067±80 3296±61 2170±50 60±10 Observed 5089 3264 2164 60

Fig.8showsthecombinedmTdistributionforNjet≤1.The

bot-tompanelofFig.8showsthedifferencebetweenthedataandthe total estimatedbackgroundcompared tothemT distributionofa

SM Higgs boson with mH =125 GeV. The total signal observed

(seeTable5)ofabout1000eventsisinagreement,inbothshape and rate, with the expected SM signal. The cross-section times branching fractions, σggF·BH→W W∗ and σVBF·BH→W W∗,are

si-multaneouslydeterminedtobe:

σggF·BH→W W∗

=11.4+₋1₁._.2₁(stat.)₋+1₁_..2₁(theo syst.)₋+₁1._.4₃(exp syst.)pb

=11.4+₋2₂._.2₁pb

σVBF·BH→W W∗

=0.50₋+0₀._.24₂₂(stat.)±0.10(theo syst.)+₋0₀._.12₁₃(exp syst.)pb

=0.50+₋0₀._.29₂₈pb.

The predicted cross-section times branching fraction values are 10.4±0.6 pb and 0.81±0.02 pb for ggF and VBF [23], respec-tively.The68%and95%conﬁdenceleveltwo-dimensionalcontours of σggF·BH→W W∗ and σVBF·BH→W W∗ areshowninFig.9andare

consistentwiththeSMpredictions.

Thesignal strengthparameter μis deﬁnedastheratioofthe measuredsignal yieldtothat predictedby theSM.Themeasured

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130

Fig. 8. Post-ﬁtcombinedtransversemassdistributionforNjet≤1.Thebottompanel showsthe differencebetweenthedataandthe estimatedbackgroundcompared tothedistributionforaSMHiggsbosonwithmH=125 GeV.Thesignalandthe

backgroundcontributionsareﬁttedtothedatawithaﬂoatingsignalstrength.The hatchedbandshowsthetotaluncertaintyofthesignalandbackgroundmodelled contributions.TheHV B F contributionistoosmalltobevisible.

Fig. 9. 68%and95%conﬁdenceleveltwo-dimensionallikelihoodcontoursofσggF·

BH→W W∗vs.σVBF· BH→W W∗,comparedtotheStandardModelpredictionshown bytheredmarker.TheerrorbarsontheSMpredictionrepresenttheggFandVBF theoryuncertainty [23],respectively.

signal strengths for the ggF and VBF production modes in the

H→W W∗ decaychannelaresimultaneouslydeterminedtobe

μggF=1.10₋+₀0._.10₀₉(stat.)+₋₀0_..13₁₁(theo syst.)+₋0₀._.14₁₃(exp syst.)

=1.10+₋0₀._.21₂₀

μVBF=0.62+₋00..2729(stat.)−+00..1213(theo syst.)±0.15(exp syst.)

=0.62+₋0₀._.36₃₅.

Table 6 shows the relative impact of the main uncertainties on the measured values for σggF·BH→W W∗ and σVBF·BH→W W∗.

The theory uncertainties in the non-resonant W W background

Table 6

BreakdownofthemaincontributionstothetotaluncertaintyinσggF· BH→W W∗

andσVBF·BH→W W∗.Theindividualsourcesofsystematicuncertaintiesaregrouped together.Thesuminquadratureoftheindividualcomponentsdiffersfromthetotal uncertaintyduetocorrelationsbetweenthecomponents.

Source σggF· BH→W W∗[%] σVBF· BH→W W∗[%] Data statistics 10 46 CR statistics 7 9 MC statistics 6 21 Theoretical uncertainties 10 19 ggF signal 5 13 VBF signal <1 4 W W 6 12 Top-quark 5 5 Experimental uncertainties 8 9 b-tagging 4 6 Modelling of pile-up 5 2 Jet 2 2 Lepton 3 <1 Misidentiﬁed leptons 6 9 Luminosity 3 3 TOTAL 18 57

produce one of the largest uncertainties, of the order of 6%, in the measured ggF cross-section. The uncertainty in the ratio of

gg→W W toqq→W W comesfromthelimitedNLOaccuracyof the gg→W W productioncross-section [38].Theresulting uncer-tainty inthe cross-section whenusingacceptance criteriasimilar to those in this analysis was evaluated in Ref. [79] for Njet=0

and for Njet=1. In the Njet≥2 VBF SR, the 12% uncertainty in

theW W backgroundoriginatesfromthematchingandUEPS mod-ellingofqq→W W .TheamountofggFcontaminationintheVBF region issubjecttoQCD scaleuncertainties andthisproducesan uncertainty ofabout13% inthe measuredVBF cross-section. The statistical uncertaintyofthe MC simulation hasa relatively large impact, especially forthe VBF cross-section measurement, where itcontributes21%.

Theobserved(expected)ggFandVBFsignalshavesigniﬁcances of6.0(5.3)and1.8(2.6)standarddeviations,respectively.

8. Conclusions

Measurements of the inclusive cross-section of Higgs boson productionvia thegluon–gluon fusion(ggF)andvector-boson fu-sion(VBF) modesinthe H→W W∗ decaychannel arepresented. Theyarebasedon36.1 fb−1 of√s=13 TeV proton–proton colli-sions recorded by the ATLAS detector at the LHC in 2015–2016. The ggF and VBF cross-sections times the H→W W∗ branch-ing ratio are measured to be 11.4+₋1₁_..₁2(stat.)+₋1₁._.8₇(syst.) pb and 0.50+₋0₀._.24₂₂(stat.)±0.17(syst.) pb, respectively, in agreement with StandardModelpredictions.

Acknowledgements

We thank CERN forthe very successful operation ofthe LHC, as well asthe supportstaff fromour institutions withoutwhom 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,MOSTand NSFC,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,Hong KongSAR, China;ISFandBenoziyoCenter, Is-rael; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO,

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Netherlands;RCN, Norway;MNiSW andNCN, Poland;FCT, Portu-gal; MNE/IFA, Romania; MES of Russiaand NRC KI, Russian Fed-eration; JINR; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia;DST/NRF,SouthAfrica;MINECO,Spain;SRCand Wallen-berg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom;DOEandNSF, UnitedStatesofAmerica. Inaddition, in-dividualgroupsandmembershavereceivedsupportfromBCKDF, Canarie,CRCandComputeCanada,Canada;COST,ERC,ERDF, Hori-zon2020, andMarie Skłodowska-Curie Actions, European Union; Investissements d’Avenir Labex and Idex, ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia pro-grammesco-ﬁnancedbyEU-ESFandtheGreekNSRF,Greece; BSF-NSF andGIF, Israel; CERCA Programme Generalitat de Catalunya, Spain;TheRoyalSocietyandLeverhulmeTrust,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. [80].

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TheATLASCollaboration

M. Aaboud34d,G. Aad99,B. Abbott124, O. Abdinov13,∗,B. Abeloos128,D.K. Abhayasinghe91, S.H. Abidi164, O.S. AbouZeid39,N.L. Abraham153, H. Abramowicz158,H. Abreu157,Y. Abulaiti6, B.S. Acharya64a,64b,n, S. Adachi160,L. Adam97, L. Adamczyk81a,J. Adelman119, M. Adersberger112, A. Adiguzel12c,ag, T. Adye141,A.A. Affolder143,Y. Aﬁk157, C. Agheorghiesei27c,

J.A. Aguilar-Saavedra136f,136a, F. Ahmadov77,ae, G. Aielli71a,71b, S. Akatsuka83, T.P.A. Åkesson94, E. Akilli52, A.V. Akimov108,G.L. Alberghi23b,23a,J. Albert173,P. Albicocco49, M.J. Alconada Verzini86, S. Alderweireldt117,M. Aleksa35, I.N. Aleksandrov77, C. Alexa27b,T. Alexopoulos10, M. Alhroob124, B. Ali138, G. Alimonti66a, J. Alison36, S.P. Alkire145,C. Allaire128, B.M.M. Allbrooke153,B.W. Allen127, P.P. Allport21, A. Aloisio67a,67b, A. Alonso39, F. Alonso86,C. Alpigiani145, A.A. Alshehri55,M.I. Alstaty99, B. Alvarez Gonzalez35,D. Álvarez Piqueras171,M.G. Alviggi67a,67b,B.T. Amadio18,

Y. Amaral Coutinho78b,A. Ambler101,L. Ambroz131,C. Amelung26,D. Amidei103,

S.P. Amor Dos Santos136a,136c, S. Amoroso44,C.S. Amrouche52,C. Anastopoulos146,L.S. Ancu52, N. Andari142,T. Andeen11,C.F. Anders59b,J.K. Anders20,K.J. Anderson36, A. Andreazza66a,66b,

V. Andrei59a,C.R. Anelli173,S. Angelidakis37, I. Angelozzi118,A. Angerami38,A.V. Anisenkov120b,120a, A. Annovi69a,C. Antel59a,M.T. Anthony146, M. Antonelli49, D.J.A. Antrim168, F. Anulli70a,M. Aoki79, J.A. Aparisi Pozo171,L. Aperio Bella35, G. Arabidze104, J.P. Araque136a,V. Araujo Ferraz78b,

R. Araujo Pereira78b,A.T.H. Arce47,R.E. Ardell91,F.A. Arduh86, J-F. Arguin107, S. Argyropoulos75, A.J. Armbruster35,L.J. Armitage90,A Armstrong168, O. Arnaez164,H. Arnold118,M. Arratia31,

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O. Arslan24,A. Artamonov109,∗,G. Artoni131,S. Artz97, S. Asai160,N. Asbah57, E.M. Asimakopoulou169, L. Asquith153,K. Assamagan29,R. Astalos28a, R.J. Atkin32a,M. Atkinson170,N.B. Atlay148,K. Augsten138, G. Avolio35, R. Avramidou58a, M.K. Ayoub15a,G. Azuelos107,ar, A.E. Baas59a,M.J. Baca21,

H. Bachacou142,K. Bachas65a,65b,M. Backes131,P. Bagnaia70a,70b, M. Bahmani82, H. Bahrasemani149, A.J. Bailey171, J.T. Baines141,M. Bajic39,C. Bakalis10,O.K. Baker180,P.J. Bakker118,D. Bakshi Gupta93, S. Balaji154,E.M. Baldin120b,120a,P. Balek177, F. Balli142,W.K. Balunas133,J. Balz97,E. Banas82,

A. Bandyopadhyay24,S. Banerjee178,j, A.A.E. Bannoura179,L. Barak158, W.M. Barbe37,E.L. Barberio102, D. Barberis53b,53a,M. Barbero99, T. Barillari113,M-S. Barisits35,J. Barkeloo127,T. Barklow150,

R. Barnea157,S.L. Barnes58c, B.M. Barnett141,R.M. Barnett18,Z. Barnovska-Blenessy58a, A. Baroncelli72a, G. Barone26,A.J. Barr131,L. Barranco Navarro171, F. Barreiro96,J. Barreiro Guimarães da Costa15a, R. Bartoldus150, A.E. Barton87,P. Bartos28a, A. Basalaev134, A. Bassalat128, R.L. Bates55, S.J. Batista164, S. Batlamous34e, J.R. Batley31, M. Battaglia143,M. Bauce70a,70b,F. Bauer142, K.T. Bauer168,

H.S. Bawa150,l,J.B. Beacham122,T. Beau132,P.H. Beauchemin167,P. Bechtle24,H.C. Beck51,H.P. Beck20,q, K. Becker50,M. Becker97,C. Becot44,A. Beddall12d,A.J. Beddall12a,V.A. Bednyakov77, M. Bedognetti118, C.P. Bee152,T.A. Beermann35, M. Begalli78b, M. Begel29, A. Behera152,J.K. Behr44, A.S. Bell92,

G. Bella158, L. Bellagamba23b, A. Bellerive33,M. Bellomo157, P. Bellos9,K. Belotskiy110,N.L. Belyaev110, O. Benary158,∗, D. Benchekroun34a,M. Bender112,N. Benekos10, Y. Benhammou158,

E. Benhar Noccioli180,J. Benitez75,D.P. Benjamin47, M. Benoit52,J.R. Bensinger26,S. Bentvelsen118, L. Beresford131,M. Beretta49,D. Berge44,E. Bergeaas Kuutmann169, N. Berger5,L.J. Bergsten26, J. Beringer18,S. Berlendis7,N.R. Bernard100, G. Bernardi132,C. Bernius150,F.U. Bernlochner24, T. Berry91, P. Berta97,C. Bertella15a, G. Bertoli43a,43b, I.A. Bertram87,G.J. Besjes39,

O. Bessidskaia Bylund179, M. Bessner44, N. Besson142,A. Bethani98, S. Bethke113, A. Betti24,

A.J. Bevan90,J. Beyer113, R.M.B. Bianchi135, O. Biebel112, D. Biedermann19, R. Bielski35,K. Bierwagen97, N.V. Biesuz69a,69b, M. Biglietti72a, T.R.V. Billoud107,M. Bindi51, A. Bingul12d,C. Bini70a,70b,

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S.K. Boutle55, A. Boveia122, J. Boyd35, D. Boye32b, I.R. Boyko77,A.J. Bozson91,J. Bracinik21,

N. Brahimi99,A. Brandt8, G. Brandt179,O. Brandt59a,F. Braren44,U. Bratzler161, B. Brau100,J.E. Brau127, W.D. Breaden Madden55,K. Brendlinger44,L. Brenner44,R. Brenner169, S. Bressler177,B. Brickwedde97, D.L. Briglin21, D. Britton55, D. Britzger59b,I. Brock24, R. Brock104,G. Brooijmans38,T. Brooks91,

W.K. Brooks144b, E. Brost119, J.H Broughton21, P.A. Bruckman de Renstrom82,D. Bruncko28b, A. Bruni23b, G. Bruni23b,L.S. Bruni118, S. Bruno71a,71b, B.H. Brunt31,M. Bruschi23b,N. Bruscino135, P. Bryant36, L. Bryngemark44,T. Buanes17,Q. Buat35,P. Buchholz148, A.G. Buckley55, I.A. Budagov77, F. Buehrer50,M.K. Bugge130,O. Bulekov110, D. Bullock8, T.J. Burch119,S. Burdin88,C.D. Burgard118, A.M. Burger5,B. Burghgrave119,K. Burka82,S. Burke141, I. Burmeister45,J.T.P. Burr131,V. Büscher97, E. Buschmann51,P. Bussey55,J.M. Butler25,C.M. Buttar55,J.M. Butterworth92,P. Butti35,

W. Buttinger35,A. Buzatu155,A.R. Buzykaev120b,120a, G. Cabras23b,23a, S. Cabrera Urbán171, D. Caforio138, H. Cai170,V.M.M. Cairo2,O. Cakir4a,N. Calace52,P. Calaﬁura18, A. Calandri99, G. Calderini132,P. Calfayan63, G. Callea40b,40a, L.P. Caloba78b,S. Calvente Lopez96,D. Calvet37, S. Calvet37,T.P. Calvet152, M. Calvetti69a,69b, R. Camacho Toro132, S. Camarda35,P. Camarri71a,71b, D. Cameron130,R. Caminal Armadans100,C. Camincher35, S. Campana35,M. Campanelli92,

A. Camplani39,A. Campoverde148, V. Canale67a,67b, M. Cano Bret58c,J. Cantero125,T. Cao158,Y. Cao170, M.D.M. Capeans Garrido35,I. Caprini27b, M. Caprini27b, M. Capua40b,40a, R.M. Carbone38,

R. Cardarelli71a, F.C. Cardillo146,I. Carli139,T. Carli35,G. Carlino67a,B.T. Carlson135,L. Carminati66a,66b, R.M.D. Carney43a,43b, S. Caron117,E. Carquin144b,S. Carrá66a,66b, G.D. Carrillo-Montoya35,D. Casadei32b, M.P. Casado14,f,A.F. Casha164,D.W. Casper168,R. Castelijn118, F.L. Castillo171, V. Castillo Gimenez171, N.F. Castro136a,136e_,_{A. Catinaccio}35_, _{J.R. Catmore}130_, _{A. Cattai}35_,_{J. Caudron}24_,_{V. Cavaliere}29_,

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E. Cavallaro14,D. Cavalli66a,M. Cavalli-Sforza14,V. Cavasinni69a,69b,E. Celebi12b, F. Ceradini72a,72b, L. Cerda Alberich171,A.S. Cerqueira78a, A. Cerri153, L. Cerrito71a,71b,F. Cerutti18,A. Cervelli23b,23a, S.A. Cetin12b,A. Chafaq34a, D Chakraborty119, S.K. Chan57, W.S. Chan118, Y.L. Chan61a, J.D. Chapman31, B. Chargeishvili156b, D.G. Charlton21,C.C. Chau33,C.A. Chavez Barajas153, S. Che122,A. Chegwidden104, S. Chekanov6,S.V. Chekulaev165a,G.A. Chelkov77,aq, M.A. Chelstowska35, C. Chen58a,C.H. Chen76, H. Chen29,J. Chen58a,J. Chen38, S. Chen133, S.J. Chen15c,X. Chen15b,ap, Y. Chen80,Y-H. Chen44, H.C. Cheng103,H.J. Cheng15d, A. Cheplakov77,E. Cheremushkina140, R. Cherkaoui El Moursli34e,

E. Cheu7,K. Cheung62,L. Chevalier142, V. Chiarella49,G. Chiarelli69a,G. Chiodini65a, A.S. Chisholm35,21, A. Chitan27b, I. Chiu160, Y.H. Chiu173, M.V. Chizhov77, K. Choi63, A.R. Chomont128, S. Chouridou159, Y.S. Chow118,V. Christodoulou92, M.C. Chu61a,J. Chudoba137,A.J. Chuinard101,J.J. Chwastowski82, L. Chytka126, D. Cinca45,V. Cindro89, I.A. Cioar˘a24, A. Ciocio18, F. Cirotto67a,67b, Z.H. Citron177, M. Citterio66a, A. Clark52, M.R. Clark38,P.J. Clark48, C. Clement43a,43b,Y. Coadou99,M. Cobal64a,64c, A. Coccaro53b,53a, J. Cochran76,H. Cohen158,A.E.C. Coimbra177,L. Colasurdo117,B. Cole38,

A.P. Colijn118,J. Collot56,P. Conde Muiño136a,136b,E. Coniavitis50, S.H. Connell32b,I.A. Connelly98, S. Constantinescu27b,F. Conventi67a,as, A.M. Cooper-Sarkar131,F. Cormier172,K.J.R. Cormier164,

L.D. Corpe92,M. Corradi70a,70b, E.E. Corrigan94, F. Corriveau101,ac, A. Cortes-Gonzalez35, M.J. Costa171, F. Costanza5, D. Costanzo146, G. Cottin31, G. Cowan91, B.E. Cox98,J. Crane98, K. Cranmer121,

S.J. Crawley55, R.A. Creager133,G. Cree33,S. Crépé-Renaudin56, F. Crescioli132,M. Cristinziani24, V. Croft121,G. Crosetti40b,40a, A. Cueto96,T. Cuhadar Donszelmann146,A.R. Cukierman150, S. Czekierda82,P. Czodrowski35,M.J. Da Cunha Sargedas De Sousa58b,136b, C. Da Via98,

W. Dabrowski81a, T. Dado28a,x, S. Dahbi34e,T. Dai103, F. Dallaire107,C. Dallapiccola100, M. Dam39, G. D’amen23b,23a,J. Damp97,J.R. Dandoy133,M.F. Daneri30,N.P. Dang178,j,N.D Dann98,

M. Danninger172,V. Dao35,G. Darbo53b,S. Darmora8,O. Dartsi5, A. Dattagupta127,T. Daubney44, S. D’Auria55, W. Davey24,C. David44,T. Davidek139, D.R. Davis47, E. Dawe102,I. Dawson146, K. De8, R. De Asmundis67a,A. De Benedetti124,M. De Beurs118,S. De Castro23b,23a, S. De Cecco70a,70b, N. De Groot117, P. de Jong118,H. De la Torre104, F. De Lorenzi76,A. De Maria51,s,D. De Pedis70a, A. De Salvo70a,U. De Sanctis71a,71b,M. De Santis71a,71b,A. De Santo153, K. De Vasconcelos Corga99, J.B. De Vivie De Regie128,C. Debenedetti143,D.V. Dedovich77, N. Dehghanian3, M. Del Gaudio40b,40a, J. Del Peso96, Y. Delabat Diaz44, D. Delgove128, F. Deliot142,C.M. Delitzsch7,M. Della Pietra67a,67b, D. Della Volpe52, A. Dell’Acqua35, L. Dell’Asta25,M. Delmastro5,C. Delporte128, P.A. Delsart56, D.A. DeMarco164, S. Demers180, M. Demichev77,S.P. Denisov140, D. Denysiuk118, L. D’Eramo132, D. Derendarz82, J.E. Derkaoui34d,F. Derue132,P. Dervan88,K. Desch24, C. Deterre44, K. Dette164, M.R. Devesa30,P.O. Deviveiros35, A. Dewhurst141, S. Dhaliwal26,F.A. Di Bello52, A. Di Ciaccio71a,71b, L. Di Ciaccio5, W.K. Di Clemente133, C. Di Donato67a,67b,A. Di Girolamo35,B. Di Micco72a,72b, R. Di Nardo100,K.F. Di Petrillo57,R. Di Sipio164, D. Di Valentino33,C. Diaconu99,M. Diamond164, F.A. Dias39,T. Dias Do Vale136a,M.A. Diaz144a,J. Dickinson18,E.B. Diehl103, J. Dietrich19,

S. Díez Cornell44,A. Dimitrievska18,J. Dingfelder24,F. Dittus35,F. Djama99,T. Djobava156b, J.I. Djuvsland59a,M.A.B. Do Vale78c,M. Dobre27b, D. Dodsworth26, C. Doglioni94, J. Dolejsi139, Z. Dolezal139, M. Donadelli78d,J. Donini37, A. D’onofrio90,M. D’Onofrio88,J. Dopke141,A. Doria67a, M.T. Dova86,A.T. Doyle55, E. Drechsler51,E. Dreyer149,T. Dreyer51, D. Du58b,Y. Du58b,F. Dubinin108, M. Dubovsky28a,A. Dubreuil52,E. Duchovni177,G. Duckeck112,A. Ducourthial132,O.A. Ducu107,w, D. Duda113,A. Dudarev35,A.C. Dudder97,E.M. Duffield18, L. Duflot128,M. Dührssen35, C. Dülsen179, M. Dumancic177,A.E. Dumitriu27b,d, A.K. Duncan55, M. Dunford59a, A. Duperrin99,H. Duran Yildiz4a, M. Düren54,A. Durglishvili156b, D. Duschinger46,B. Dutta44,D. Duvnjak1, M. Dyndal44,S. Dysch98, B.S. Dziedzic82,C. Eckardt44,K.M. Ecker113,R.C. Edgar103,T. Eifert35,G. Eigen17,K. Einsweiler18, T. Ekelof169,M. El Kacimi34c, R. El Kosseifi99, V. Ellajosyula99, M. Ellert169,F. Ellinghaus179, A.A. Elliot90,N. Ellis35, J. Elmsheuser29,M. Elsing35,D. Emeliyanov141,Y. Enari160,J.S. Ennis175, M.B. Epland47, J. Erdmann45,A. Ereditato20,S. Errede170, M. Escalier128,C. Escobar171,

O. Estrada Pastor171,A.I. Etienvre142, E. Etzion158,H. Evans63, A. Ezhilov134,M. Ezzi34e,F. Fabbri55, L. Fabbri23b,23a,V. Fabiani117,G. Facini92, R.M. Faisca Rodrigues Pereira136a,R.M. Fakhrutdinov140, S. Falciano70a, P.J. Falke5, S. Falke5,J. Faltova139, Y. Fang15a,M. Fanti66a,66b,A. Farbin8,A. Farilla72a, E.M. Farina68a,68b,T. Farooque104,S. Farrell18, S.M. Farrington175, P. Farthouat35,F. Fassi34e,