Search for invisible Higgs boson decays in vector boson fusion at root s=13 TeV with the ATLAS detector

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Search

for

invisible

Higgs

boson

decays

in

vector

boson

fusion

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:

Received18September2018

Receivedinrevisedform12February2019 Accepted9April2019

Availableonline15April2019 Editor:M.Doser

We report a search for Higgs bosons that are produced via vector boson fusion and subsequently decayintoinvisible particles.The experimentalsignature is anenergetic jetpairwith invariantmass ofO(1)TeV andO(100)GeV missingtransversemomentum.Theanalysisuses36.1 fb−1ofpp collision dataat√s=13TeV recordedbytheATLASdetectorattheLHC.Inthesignalregionthe2252 observed eventsareconsistentwiththebackgroundestimation.Assuminga125GeV scalarparticlewithStandard Modelcrosssections,theupper limitonthebranchingfractionoftheHiggsbosondecayintoinvisible particlesis0.37 at95% conﬁdencelevelwhere0.28 wasexpected.ThislimitisinterpretedinHiggsportal modelstosetboundsonthe wimp–nucleonscatteringcrosssection.Wealsoconsiderinvisibledecaysof additionalscalarbosonswithmassesupto3TeV forwhichtheupperlimitsonthecrosssectiontimes branchingfractionareintherangeof0.3–1.7pb.

1. Introduction

We presenta search forthe decays of the Higgs boson [1,2], produced via the vector boson fusion (VBF) process [3,4], into invisible particles (χχ¯) with an anomalous and sizable O(10)% branching fraction. The hypothesis underconsideration [5–16] is thattheHiggsbosonmightdecayintoapairofweaklyinteracting massiveparticles(wimp)[17,18],whichmayexplainthenatureof darkmatter (seeRef. [19] andthereferencestherein).The search carriedout forthe125GeV Higgsbosonisrepeatedfor hypothet-ical scalars with masses up to 3TeV. The search is independent onthedecayofthemediatorbecausethefinal stateparticles are invisibletothedetector,whileit isdependentonits Emiss_T distri-bution (defined below) because that quantity is reflective of the mediator’s pTdistribution.

The data sample corresponds to an integrated luminosity of 36.1fb−1 ofproton-proton(pp)collisionsat√s=13TeV recorded by the ATLAS detector at the LHC in 2015 and 2016. The ex-perimental signature of the VBF production process is a pair of energetic quark jetswith a wide gap in pseudorapidity (η) cor-responding to the O(1)TeV value of the invariant mass (mj j) of thehighest-pTjetsintheevent.1 Thesignatureforthedecay

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

1 _ATLAS_uses_a_right-handed_coordinate_system_with_its_origin_at_the _nominal

interactionpointinthecenterofthedetectorandthez-axisalongthebeam di-rection.Thex-axispointsfromtheinteractionpointtothecenteroftheLHCring; they-axispointsupward.Cylindricalcoordinates(r,φ)areusedinthetransverse plane,whereφistheazimuthalanglearoundthez-axis.Thepseudorapidityis de-ﬁnedasη= −ln(tan(θ/2)),whereθisthepolarangle.

cessistheO(100)GeV valueofthemissingtransversemomentum

Emiss T

thatcorrespondstotheHiggsbosonpT.TheVBFtopology

offersapowerfulrejectionofthestronglyproduced2 _backgrounds

due to single vector boson plus two jets, and the multijet back-groundproduced fromQCD processes. In thisanalysis, the Higgs productionviathegluonfusionmechanismissubdominanttoVBF andisconsideredaspartofthesignal.

DirectsearchesforinvisibleHiggsdecayslookforan excessof eventsoverStandardModelexpectations.Theabsenceofanexcess isinterpretedasanupperlimitonthebranchingfractionof invis-ible decays(Binv) assuming theStandard Modelproduction cross

section [20] of the125GeV Higgs boson.Other published results have targeted a variety of production mechanisms—gluon fusion, VBF,W or Z associatedproduction[21–25]—tosetupperlimitson

Binv.Thebestlimitsarefromthestatisticalcombinationofsearch

results for which ATLAS reports an observed (expected) limit of 0.26 (0.17) [26] and CMS reports 0.26 (0.20) [27] at 95% conﬁ-dencelevel(CL).Forthesecombinationsthesingleinputwiththe highestexpectedsensitivityisVBF, thechannelpursued here.For theVBFchannelusingRun-1 data,ATLAS reports0.28 (0.31)[28] andCMSreports0.43 (0.31)[29]. Inamorerecentupdateofthe VBFchannelusingRun-2 data,ATLASreports0.37 (0.28)[this pa-per]CMSreports0.33 (0.25)[27].

Global ﬁts to the measurements of visible decay channels of the Higgsbosonplace indirectconstraints onthe beyond-the-SM

2 _For_the_{W and}_{Z background}_processes_in_this_paper,_electroweak_(EW)_refers

todiagramsthatareofO(α4

ew)orgreater,whilestrongreferstodiagramsthatare

ofO(α2

s)orgreateraccompaniedbyO(α 2 ew). https://doi.org/10.1016/j.physletb.2019.04.024

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decaybranching fractionBbsm. The Bbsm isthe sum of B_inv that

representsinvisibledecaysandBundet thatrepresentsthechannels

thatareundetected,i.e.,thosethatarenotincludedinthe follow-ing combination. ForBbsm using Run-1 data, ATLAS reports 0.49

(0.48)[30] andCMSreports0.57 (0.52)[31] withsimilar butnot identical assumptions. A combination of ATLAS and CMS results usingRun-1 datagives0.34 (0.39) [32]. Ina morerecentupdate usingRun-2data,CMSreportsanobservedlimitonBundet of0.38

[33].As notedinRef. [28],thereiscomplementarity betweenthe directsearchforinvisibleHiggsdecaysandtheindirectconstraints fromtheglobalﬁts.

In this analysis, several changes and improvements are made withrespectto the previous ATLASpaper onthistopic[28].The trigger and hadronic objects are deﬁned considering the simul-taneous pp collisions in the same and nearby bunch crossings (pileup)(Section2).Theleading backgroundsare simulatedusing state-of-the-art QCD predictions (Section 3). The eventselections arechangedtoretainagoodsensitivitydespitethehigherpileup. Theanalysisextractsthesignal yieldusingabinnedlikelihoodﬁt to the mj j spectrum in 3 bins to increase the signal sensitivity (Section4). Theestimation ofthe importantanddominant back-groundfor the Z→νν process (denoted Zνν ) relies only onthe

ZeeandZμμ controlsamples,andisnotaffectedbytheoretical un-certaintiesoftheW -to- Z extrapolation(Section5).Thesystematic uncertaintiesareevaluatedseparatelyforeachmj j bin(Section6). Thesearch isrepeatedforother scalars withmassesup to 3TeV, whichcaneasilybereinterpretedformodelsnotconsideredinthis Letter(Section7).Severalaspectsoftheanalysishavenotchanged compared tothe ATLAS Run-1 analysis—e.g., subdetector descrip-tions, transferfactormethod, Higgsportal models—and detailsof thesemaybefoundinRef. [28].

2. Detector,trigger,andanalysisobjects

ATLAS is a multipurpose particle physics detector with a forward–backwardsymmetriccylindricalgeometryconsistingofa trackingsystem,electromagneticandhadroniccalorimeters,anda muonsystem[34].

Thetrigger torecord eventsinthesample containing theVBF signalcandidatesusedatwo-levelEmiss

T algorithmwiththresholds

adjusted throughoutthe data-taking periodto cope withvarying levelsofpileup[35,36].The level-1systemusedcoarse-granularity analog sums ofthe energy depositsin the calorimetertowers to require Emiss_T >50GeV. The second-level highleveltrigger sys-tem[37] usedjetsthatare reconstructedfromcalibratedclusters of cell energies [38] and requires Emiss

T >70–110GeV depending

ontheluminosityandthepileuplevel.Thetriggerefficiency[39] forsignal events is98% for Emiss_T >180GeV when comparingthe triggerselectionwiththeoffline Emiss_T definitionthatcontains ad-ditionalcorrections.

Thetriggerstorecordthecontrolsamplesforbackground stud-iesusedleptonandjetalgorithms[40].Thesampleswithleptonic

W and Z decays were collected witha single-electronor-muon

triggerwithpT>24GeV (26GeV)andan isolationrequirementin

2015(towardstheendof2016).Thesampleofmultijeteventswas collectedusingasetoflow-thresholdsingle-jettriggerswithlarge prescalevaluestokeeptheeventraterelativelylow.

For each event, a vertex is reconstructed from two or more associated tracks (t) with pT>400MeV. If multiple vertices are

present, we consider the one with the largest _t(pT,t)2 as the primaryvertexofourcandidates.

Leptons ( =e, μ) are identiﬁed to help characterize events withleptonic ﬁnalstatesfromdecaysof vectorbosons. Sincethe signal process contains no leptons, such events are used forthe backgroundestimation,whichisdescribed inSection 5.Electrons

(muons)musthavepT>7GeV,|η| <2.47 (2.5),andsatisfyan

iso-lationrequirement. Electronsare reconstructedby matching clus-teredenergydepositsintheelectromagneticcalorimetertotracks fromtheinnerdetector[41,42] andmuonsbymatchinginner de-tector and muonspectrometer tracks [43]. Forelectrons (muons) withapT valueofatleast30GeV (20-100GeV),thereconstruction

eﬃciency 80% (96%) witha rejectionfactorof around 500 (600). Allleptonsmustoriginatefromtheprimaryvertex.

Jetsarereconstructedfromtopologicalclustersinthe calorime-ters using the anti-kt algorithm [44] with a radius parameter

R=0.4. Jets must have pT>20GeV and |η| <4.5. The subset of

jetswithpT<60GeV and|η| <2.4 arejetvertextagged(jvt)[45]

tosuppresspileupeffects,usingtrackingandvertexing.The jvt is 92% eﬃcientforthejetsinthesignalprocessfromtheprimary in-teractionwitharejectionfactorofaround100 forpileupjetswith

pT valueintherangeof20-50GeV [45].

Cleaningrequirementshelpsuppressnon-collisionbackgrounds [46].Fakejetsduetonoisycells areremovedbyrequiringagood ﬁt to the expected pulse shape for each constituent calorimeter cell.Fakejetsinducedbybeam-halointeractionswiththeLHC col-limatorsareremovedbyrequirementsontheirenergydistribution andthefractionoftheirconstituenttracksthatoriginatefromthe primaryvertex.

Ineventswithidentifiedleptons,anoverlapremovalprocedure is applied toresolve the ambiguitiesin caseswhere ajet is also identified in the same η-φ area, which could occur in situations such ashavingaheavy-flavorhadrondecaywithinajet[47].The lepton–jet overlapinR distance3 isresolved sequentiallyas fol-lows.IfanelectronisnearajetwithR<0.2,thejetisremoved to avoidthedoublecountingof electronenergydeposits.Ifa re-maining jet is nearan electron with0.2≤ R<0.4,the electron is removed. If a muon is near a jet with R<0.4 and the jet is associated with at least(less than) three charged tracks with

pT>500MeV,themuon(jet)isremoved.

The E_Tmissvariableisthemagnitudeofthenegativevectorsum of the transverse momenta, −_ipT,i, where i represents both the “hard objects” andthe “soft term.” The hard objects consist of leptonsandjets, whichare individually reconstructedand cal-ibrated; thelistexcludespileupjets, whichare removedbya jvt requirement. The soft termis formed from inner detector tracks not associatedwiththehard objects,butmatchedtotheprimary vertex.Inthesearchregion,theEmiss_T producedbytheHiggsdecay isbalancedinthetransverseplanebythedijetsystem.

The jvt procedure is intended to remove pileup jets, but can cause large fake Emiss

T if it removesa high-pT jet from the hard

scatter, e.g., a jet from a pT-balanced three-jet event. In order

to reduce this, a correlated quantity H_Tmiss—deﬁned as |_jpT,j|, where j represents all jets without the jvt requirement—is re-quired to be Hmiss_T >150GeV. In the three-jet example, Hmiss_T

wouldbenearzero. The Emiss

T signiﬁcance (Smet) is used only in events with

one identified electron in the final state and is defined as

Emiss_T /√pT,j1+pT,j2+pT,e,wherethe pT quantitiesare forleading

jet ( j1),subleading jet( j2), andelectron,respectively.The useof

thisquantity to reducethe contamination fromjetsmisidentiﬁed aselectronsisdiscussedinSection5.

3. Eventsimulation

Monte Carlo simulation (MC) consists of an event generation followedbydetectorsimulation[48] using geant4[49].Simulated eventswere correctedforthesmalldifferencesbetweendataand

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troweak.The showering simulation followedthe same procedure asfortheVBFsample. Forboth theVBFandgluonfusionevents, the H→Z Z∗→4ν process isincludedin thesample asinvisible decaysof the Higgs boson.Additional scalars withmassesup to 3TeV were simulated as described above for VBF signal process, assumingafullwidthof4MeV.

TheW and Z eventsweregeneratedusing sherpa2.2.1[60] with comix [61] and openloops [62] matrix-element generators, and mergedwith sherpa partonshower[63] usingthe me+ps_@nlo pre-scription[64]. The nnpdf3.0 NNLO PDF setwas used.In termsof theorderofthevariousprocesses,thestrongproductionwas cal-culated atNLO forup to twojetsand leading order(LO) forthe third andfourthjets. The electroweakproduction was calculated atLOforthesecond andthirdjets.The levelsoftheinterference between electroweak and strong processes were computed with madgraph5_amc@nlo[65]. Theinterferenceon thetotalexpected backgroundisonly0.1% andthusneglected.

Other potential background processes involve top quarks, di-bosons, and multijets. Top quarks and dibosons were generated with powheg interfacedwith pythia and evtgen [66],which sim-ulate the heavy-ﬂavor decays. The diboson backgrounds include electroweak-mediated processes. The multijet estimate does not directlyusetheMC.

Toeachhard-scatterMCevent,pileupcollisions(30 onaverage) wereaddedtomimictheenvironmentoftheLHC.Thepileup col-lisions,simulatedwith pythia8[52] using mstw2008 PDF[67] and the a2setoftunedparameters[68],weresubsequentlyreweighted toreproducethepileupdistributionindata.

The sizes of the MC samples vary depending on the process. TheeffectiveluminosityrangesfortheMCsamplesvaries depend-ing on the process and on the selections, which are deﬁned in Section4.FortheW process,theMCsampleisapproximatelyhalf ofthatofthedataselectedfortheW controlregionandalsohalf forthesignalregion.Forthe Z process,theMCsampleforthe Z subprocessisapproximatelytwicethatofdatainthe Z control re-gion;theMCsampleforZνν subprocessisapproximatelythesame asthatofdatainthesignalregion.

4. Eventselection

Alleventsmusthaveaprimary vertex.Theselectionlisted be-low divides thedata sample into a signal-enrichedsearch region (SR)andbackground-enrichedcontrolregions(CR).Thecontrol re-gionsandthestatisticalﬁtarediscussedindetailinSection5.The restofthissectionfocusesontheSRandthepreﬁteventyields.4

FortheSR,aneventisrequiredtohave •noisolatedelectronormuon,

•aleadingjetwithpT>80GeV,

•asubleadingjetwithpT>50GeV,

4 _{“Preﬁt”}_indicates_that_the_event_yields_are_not_adjusted_according_to_the

statis-ticaltreatmentofthebackgroundpredictions,whichisdescribedinthesecondhalf ofSection5.“Postﬁt”labelsthe quantitiesthatcomeoutoftheﬁtprocedure.

Z→νν 1111 [18%] – – Z→ee,μμ 12 [9%] 38 [9%] 181 [23%] Z→τ τ 10 [16%] 11 [16%] – W→eν,μν 540 [16%] 1400 [30%] – W→τ ν 533 [20%] 130 [34%] – Other 36 67 2 S, signal 1070 – – VBF 930 – – Gluon fusion 140 – –

• noadditionaljetswithpT>25GeV,

• Emiss_T >180GeV, • H_Tmiss>150GeV.

Thetwojetsarerequiredtohavethefollowingproperties: • notbealignedwithEmiss_T ,|φj-met| >1,

• notbeback-to-back,|φj j| <1.8, • bewellseparatedin η,|ηj j| >4.8, • beinopposite η hemispheres, ηj1·ηj2<0, • mj j>1TeV.

TheSRincludesbackgroundeventscontainingaW or Z plustwo jets, wherethe W decaysintoeν, μν,and τ ν,andthe Z decays

into twoneutrinos. Here theleptons fromthe W decays arenot reconstructed since they would otherwise be rejectedby the se-lection.

Table1 givestheprefitSRyields inthe firstcolumn. TheVBF productionprocessgivesthebiggestcontribution(87%)tothe sig-nalsample(fixedasBinv=1).Thecontributionfromgluonfusion

accompaniedbypartonradiationissmall(13%)andother produc-tionmodescontributenegligibly.ThefractionofVBFsignalevents thatpassthesignalregioneventselections,definedasacceptance times reconstruction efficiency, is 0.7%. As is discussed in Sec-tion7,thesignalsignificanceisimprovedbyconsideringthreebins ofmj j definedasfollows:1<mj j≤1.5TeV, 1.5<mj j≤2TeV,and

mj j>2TeV.Thepreﬁt S/B ratio(forBinv=1)inthesebinsis

ap-proximately0.3,0.4,0.8,respectively.

For thebackgrounds, both the strong production andthe EW productioncontribute in theSR. The strongproduction processes contributes more than 70% of the backgrounds in all of the mj j bins. There is variation in the EW fractions for the background processes due to a combination of the following factors: known differencesintheproductiondiagramsbetween W and Z , differ-ences in kinematic acceptance for the particular W or Z decay,

anddifferencesintheMCsamplesizeforeachEWprocess. 5. Controlsamplesandstatisticaltreatment

The main backgrounds in the SR, comprising of 98% of the background,arethe W and Z processes.The minorbackgrounds, comprising the remaining 2%, are the diboson, tt,¯ and multijet processes. Accurate estimation of the W and Z processes is the biggest challengeoftheanalysis. Themain backgroundyieldsare extractedusingdedicatedcontrolsamplesindata.

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Fig. 1. Data-to-MCyieldcomparisonsinthe27 subsamplesusedinthestatisticalﬁt.TheobserveddataN (dots)aresuperimposedonthepreﬁt backgroundsB (stacked

histogramwithshadedsystematicuncertaintybands).ThehypotheticalsignalS (emptybluehistogram)isshownontopofB forBinv=1.Thebottompanelsshowthe

ratiosofN (dots)and B+S (blueline)to B withthesystematicuncertaintybandshownonthelineat 1.The1,2,and3 binlabelscorrespondsto1<mj j≤1.5TeV,

1.5<mj j≤2TeV,andmj j>2TeV,respectively.The“e fakes”referstoSmet<4

√

GeV selectionandisdeterminedbytheﬁt,sopostﬁt valuesareshownforthepurposesof illustration.Thedibosoncontributionisincludedintheelectroweak(EW)W andZ bosons.

Thissection isorganizedasfollows.First,thetwomainCRare described and the associated prefit yields are given. Second, the fitparametersaredefinedalongwithadiscussionofthe contami-nationintheWeν subsample.Third,thefitprocedureisdescribed

andthepostﬁtyieldsarestated.Lastly,theminorbackgroundsand theestimationofthemultijetprocessesaredescribed.

The W CR requires one identiﬁed lepton witha pT threshold

of 30GeV,but the selections are otherwise identical to those of theSR.The initial ν selectionisdividedby leptonﬂavor,charge, and, for the eν ﬁnal state, a passing selection on Smet>4

√ GeV to deﬁne four W CR subsamples _{W μ}+ν , W μ−ν , Wehigh+ν , W

high

e−ν

. ThecomplementaryfailedselectiononSmet deﬁnesthetwo

“fake-enriched” subsamples Wlow

e+ν , W low

e−ν

. The E_Tmiss is calculated by addingthecalibratedleptonstothesum.

The Z CRisbasedonthesameselectioncriteriaastheSR,but theleptonvetoisreplacedbytherequirementoftwosame-ﬂavor opposite-signleptons with|m −mZ|<25GeV.The sample is divided bylepton ﬂavor, butnot by charge ( Zee, Zμμ).The lead-inglepton-pT thresholdisthesameasabove, andthesubleading

lepton-pT threshold is 7GeV. The EmissT is calculated as is done

above.

Table1givesthepreﬁt CRyieldsfortheinclusiveselection of

mj j>1TeV forthe W ( Z )CRinthethird(fourth)columns.These preﬁt yields are theinputsfor thestatistical ﬁtdescribed below. Thesamples arevery pure,asthe relativecontributionofthe W

( Z ) CR is 95% (99%) from W ( Z ) decays. The deﬁnitions of the mainnormalizationsparametersintheﬁtare

Bsr W estimate =N cr W·B sr W/B cr W = B sr W·N cr W/B cr W Bsr Z estimate =N cr Z ·B sr Z /B cr Z αtransfer = Bsr Z ·N cr Z /B cr Z βnormalization ,

wheretheeventyields arefortheobserveddata(N) andtheMC estimateofthebackground(B).Thetransferfactor αisthe SR-to-CRratiooftheMC yields,andisa quantityusefulforvisualizing howthesystematicuncertaintiespartiallycancelout.The normal-izationβisthedata-to-MCratiointheCR,whichisextractedfrom theﬁt.Theanalysisisperformedinthreemj j bins i,soi also in-dexes αandβ.

Forthe Whigh

eν subsampleintheW CR,ayieldparameter νfake

isintroducedtoquantifythe“e fakes,”thegroup ofelectron can-didatesthat are not prompt electrons. Thiscontamination occurs mostoftenwhenajetfromamultijeteventidentiﬁedasan elec-troncandidate.The underlyingidea isthat the W decays

(multi-jets) have high(low) Emiss_T resolution event-by-event. Since Smet

is a proxy for Emiss_T resolution, a passing (failing) selection on

Smet>4

√

GeV providesa Whigh

eν (W low

eν )subsampledepleted

(en-riched) ine fakes.In thefake-enriched Wlow

eν subsample,abouta

third ofthe eventsare duetoe fakes. (Forthe Weν process, the Emiss_T comesfromtheneutrino.Forthisreason,thekinematicbias inEmiss_T duetothe Smet selectionwasfoundtobenegligibleatthe

1% level.)Theresultingsubsamplesaretiedtogetherbyaﬁxed ra-tio ρfake,whichisdeterminedusingaseparate“pure-fake”region.

Thepure-fakeregion(Feν )isdeﬁnedbyaselectiononthe

elec-tron likelihood (Le). Since Le is optimized to separate electrons from backgroundsoriginatingfrom dijetprocesses[41], requiring that thecandidate’s Le value fail the tight deﬁnition[42], while satisfyingalooserdeﬁnition,selectsthe Feν datasample.Asdone

above, the Smet selection creates two subsamples

Fhigh eν , Floweν . The Flow eν -to- F high

eν ratioofthe numberofeventsin datais ρfake,

withthesmallamountofpromptW contaminationsubtracted us-ingMC.

Modeltestingusesaproﬁlelikelihood-ratioteststatistic[69] in the CLs-modiﬁed frequentistformalism [70]. The statistical

treat-mentconsiders atotalof27 bins: threemj j binsforeachofnine subsamples (onefortheSR, fourforthe W CR,twoforthe fake-enrichedsubsamples,twofortheZ CR).Amaximum-likelihoodﬁt to the observeddata ineach mj j binsets an upperlimit,5 using aone-sidedconﬁdencelevel,onBinvforthe125GeV Higgsboson

andontheproduct σvbf

scalar·Binv forascalarofdifferentmass.The

preﬁt comparisons ofdataandMC are shownfor all subsamples inFig.1.

The fitprocedure extractsthe nine floating parameters intro-duced above (βW, βZ, νfake for each mj j bin). After the fit, the postfitβ parameters are consistentwiththe SM prefitprediction withintheir1 σ uncertainties.Thepostfitcomparisonsofdataand expected backgrounds are shown in Fig. 2 for the two key vari-ables, mj j and Emiss_T , for the W and Z CR. The mj j (Emiss_T ) plot groupsthe backgroundsto show thedependenceof the distribu-tionshapeontheproductionmechanism(finalstate).

5 _The _likelihood_is _a_product _of_Poisson_functions, _one _for _each_sample_of _N

eventswhileexpectingλ,aGaussianfunctionforeachsystematicuncertainty,and aPoissonfunctionforthenumberofMCevents.Inthesimplescenariowithonly WandZbackgrounds,theλfortheSRwouldbeS+ βW·BWsr+ βZ·B

Z

sr,witheach

quantitymultipliedbytheresponsefunctionforasystematicuncertainty.Forthe

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Fig. 2. Distributionofeventyieldsinthe Z (top)andW (bottom)controlregions. Thepostﬁt normalizationsformj j(left)andEmissT (right)aresummedoverthe

sub-samples.TheEmiss

T distributionsstartat180GeV asindicated.TheobserveddataN

(dots)aresuperimposedonthesumofthebackgroundsB (stackedhistogramwith shadedsystematicuncertaintybands).ThebreakdownoftheB isgiveninthelower leftboxineachpanel.ThebottompanelsshowtheratiosofN toB withthe sys-tematicuncertaintybandshownonthelineat1.The“other,”aslistedinTable1, contributeafeweventsatlowvaluesofmj jand EmissT ,andareomitted.Thelast

binineachplotcontainstheoverﬂow.

Thepostﬁtvalueof νfake (theproduct ρfake·νfake) isthe

abso-lute number of e fake events in the Whigh

eν (W low

eν ) subsamples.

Since there isa νfake parameter foreach bin i, the mj j shape is also predicted. Apart fromdetermining the ρfake value, which is

fixedinthefit, Feν isnotpartofthefitmodel.Wenote thatthe Whigh

eν -W low

eν samplesaresplitbycharge,becauseW±production

isnotsymmetricinpp collisions.However,thesame νfake

param-eterisusedforbothchargesbecausethe e fakesareexpectedto besymmetricincharge since theyoriginate mostly frommultijet events.

The remaining processes—top quarks, dibosons, multijets— contribute negligibly to the SR (called “other” in Table 1). The ﬁrsttwoareestimatedwithMCusingnominalcrosssections.The multijetcontributionis very small, butitis a diﬃcultprocess to estimate. It is a potentially dangerous background because those eventsthat passthe Emiss_T selection aremostlydueto instrumen-taleffects.

The billionfold-or-more reduction of multijets after the event selectionmakesitimpracticaltosimulate,soadata-drivenmethod basedonarebalance-and-smearstrategy[72] isused.The assump-tionisthattheEmiss_T isduetojetmismeasurementinthedetector response to jets andneutrinos fromheavy-ﬂavor decays [73,74]. Usingthejet-triggeredsample,thejetmomentaarerebalancedby akinematicﬁt,within their experimental uncertainties, toobtain thebalancedvalueofthejets’ pT.Therebalancedjetsaresmeared

accordingto jetresponsetemplates, whichareobtainedfromMC and validated with dijet data. The rebalance-and-smear method predictsboththeshapeofthe Emiss_T distributionandtheabsolute normalization. Theprocedure is veriﬁedin a φj j-sideband vali-dation region (VR) with 95% purity ofQCD multijet events.This VRisdeﬁnedby1.8<|φj j| <2.7 andthelooseningoftheother requirements(|ηj j| >3,mj j>0.6TeV,andallowathird leading jetwith25<pT<50GeV,butnootherjetswithpT>25GeV).The

Fig. 3. Distributionofeventyieldsinthemultijetvalidationregionformj j(left)and EmissT (right).Themj jplotshowsthe100<EmissT <120GeV subsetoftherightplot

asindicatedbythe arrow.The N observeddata(dots)aresuperimposedonthe sumofthe B backgrounds (stackedhistogram).Thesystematicuncertaintyband appliesonlytothemultijetcomponent.Thestatisticaluncertaintiesarerelatively largebecauseofthe weightingofthetriggersampleswith largeprescalevalues. SeethecaptionofFig.2forotherplottingdetails.

comparisonofthepredictionsandthedataintheVRshowsgood agreement(Fig. 3). Themultijetcomponentisobtainedusingthe rebalance-and-smear method with the associated systematic un-certainty bands,while thenon-multijet componentsare obtained usingMC.

6. Uncertainties

Experimentalandtheoreticalsourcesofuncertaintiesaswellas thecorrelationsbetweenthevarioussourcesaredescribed.The re-sultingimpactoftheuncertaintiesontheyieldsandonthesignal sensitivityissummarizedlaterinTable2.

Experimental sourcesof uncertaintyare duemainlyto thejet energy scale and resolution [75], Emiss_T soft term [76], and lep-ton measurements [42,43]. Inorderto reduce ﬂuctuationsdueto limitedMC sample size, theuncertainties innumber ofexpected eventsforthevariationsofjetenergyscaleandresolutionforthe strongandelectroweak backgroundsamplesare averaged.This is motivatedbythesimilaritiesofthekinematicsandthedetector ef-fectsforthetwoproductionprocessesforeachmj jbin.The uncer-tainty relatedtoleptonidentiﬁcationorvetohasanon-negligible (negligible)effecton αW (αZ)because ofthefollowingscenarios.

The W ν background issigniﬁcant intheSR, whichresults inan

uncertaintyforthecasesrelatedtotheleptonveto.The Z back-groundisnegligibleintheSR,becausetheselectionrequiresthere tobenoleptons.

The following experimental sources have small or negligible impact inthe ﬁnal result. The pileupdistribution andluminosity [77,78] havearelativelysmallimpact.Thetriggereﬃciency mod-eling,forboththeleptontriggersfortheCRandEmiss

T triggersfor

theSR,arenotlistedinTable2.Theirimpactontheeventsyields was atthe1% levelandtheirimpact onthesignal sensitivityare foundtobenegligible.

Theoretical sources of uncertainty are due mainly to scale choices inﬁxed-order matrix-elementcalculations. Forthe back-ground processes, QCD scales are varied for the resummation scale (resum.),renormalizationscale (renorm.),factorizationscale (fact.),and ckkw matchingscale.Theﬁrstthreescalesinthelist— technically calledq2, μR, μF, respectively—are varied by a factor

oftwo [79,80]. Forthe ckkw matching scalebetweenthe matrix element and the parton shower [60], the central value and the consideredvariationsare20+₋10₅ GeV.Thehigher-orderelectroweak correctionstothestronglyproducedW or Z arefoundtobe neg-ligible.

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Table 2

Sourcesofuncertainty.Theﬁrstsetshows,therelative improvementofthe95%CLupperlimitonBinv whenthesourceofuncertaintyis“removed”byﬁxingittoits

best-ﬁtvalue.The“visual”columnshowsbarswhoselengthsfromthecentertickareproportionalto.Thesecondsetshowstheeffectontheyieldsandtheαtransfer factorsforthe1<mj j≤1.5 TeV bin.TheyieldsareforthesignalprocessintheSR(S),Z MCintheSR(BsrZ),and Z MCintheCR(B

cr

Z).TheαZisgiventodemonstrate

thereductionintheuncertaintyintheratioBsr Z/B

cr

Z.TheindividualyieldsfortheW arenotshownbecausethecancellationeffectsaresimilartothe Z counterparts.

Thevaluefor“3rd jetveto”correspondsonlytotheuncertaintyrelatedtojetbinmigrationforsignalprocesses;thecorrespondingeffectforthebackgroundprocessesare evaluatedinthevariousjetenergyandtheoreticalvariations.Theabbreviationsforthetheoreticalsourcesaredescribedinthetext.The‘-’indicatesthatthequantityis notapplicable.The“combined”rowsatthebottomarenotsimplesumsoftherowsabovebecauseofthemetric;thesymbols(†,‡,)areparentheticallydeﬁnedinthe table.Thepenultimate(last)rowshowsthesummaryimpactofremovingthesystematicuncertaintiesduetotheexperimentalandtheoreticalsources(aswellasstatistical uncertaintiesoftheMCsamples).

Source Binvimprove.[%]usingallmj jbins Yields,αchanges (%) in 1<mj j≤1.5 TeV

visual S BZsr B

Z

cr αZ αW

Experimental (†)

Jet energy scale 10 12 7 8 8 6

Jet energy resol. 2 2 0 1 1 4

Emiss

T soft term 1 2 2 2 2 2

Lepton id., veto 2 – – – 0 4

Pileup distrib. 1 3 1 2 3 1 Luminosity 0 2 2 2 – – Theoretical (‡) Resum. scale 1 – 2 3 0 2 Renorm., fact. 2 – 20 19 1 2 ckkwmatching 4 – 2 3 1 5 PDF 0 1 1 2 1 1 3rd jet veto 2 7 – – – – Statistical MC sample () 12 4 5 9 10 9 Data sample 21 6 5 12 12 6 Combined All † sources 17 All ‡ sources 10 Combine †, ‡ 28 Combine †, ‡, 42

The effects of the theoretical variations are evaluated with a sample of generated MC events prior to reconstruction, which is largerthanthereconstructedsample.Moreover,inordertoreduce fluctuationsduetolimitedMC statistics,theeffectofthe resum-mation and ckkw variationsasa function ofmj j are determined byalinearfit,usingmj j valuesbelowtheselectionfortheSRand asample withloosened selection onηj j andφj j.Weverified that an additionalsystematicuncertainty associatedwiththe ex-trapolationisdominatedbythestatisticalfluctuationsinthevaried samples.

Forboth signalandbackground,the effectsof thechoice ofa partondistribution function(PDF) set havea relativelysmall im-pact. The variations are considered using an ensemble of PDFs withinthe nnpdf set [54] andthestandarddeviationofthe distri-butionistakenastheuncertainty.

Forthesignalprocess,theeffectofthescaleuncertaintyonthe third-jetvetoforthegluonfusionplustwo-jetcontributionis eval-uatedusingthejet-binmethod[81].ThesimilareffectfortheVBF contribution is evaluated by comparing the scale varied samples beforeandafterthethird-jetveto.TheimpactontheHiggssignal yieldisdominatedbytheVBFcontribution,whichisaround7%.

Statistical uncertainties are due to the data and MC sample sizes.

Systematicuncertainties are assumedto be either fully corre-latedoruncorrelated.Theuncertaintiesfromthefollowingsources in each independent mj j binare correlated betweenthe SR and CR:QCDscales,PDF,andleptonmeasurements.Thetheoretical un-certaintiesduetoQCDscalesareuncorrelatedbetweenthe follow-ingpairs:signalvs.background,electroweakvs.strongproduction,

andW vs. Z production.Theoreticaluncertaintiesarefully

uncor-relatedbetweenbinsofmj j,whiletheexperimentaluncertainties arefullycorrelated,bothofwhichareexpectedtobeconservative assumptions.

One major difference between Ref. [28] and this paper—with theformer(latter)employing(notemploying)theW -to- Z

extrap-olationstrategy—isthat wenowhavealarger Z controlsample. Wefoundthattheﬁnallimitresultbasedonthestatistical uncer-tainty of theenlarged Z controlsample issimilar to theresult assuming the theoretical uncertainties on the W -to- Z ratio (in-cluding the associated MC sample statistical uncertainties). This beingthe case, thispaperadopts themethodthat is less depen-dentontheoreticalassumptions.

The sources of uncertainty are grouped into the three main categoriesgivenabove(Table2).Theimpactofeachsourceis mea-sured in two ways: (1) on the 95% CL upper limit on Binv and

(2)ontheeventyieldsand α transferfactors.Impact(1)assesses thepercentageimprovementoftheBinvlimitifthatsourceof

un-certainty is removed after ﬁxing the associated parameter to its best-ﬁtvalue.Impact (2)demonstratesthat thesystematic uncer-tainties in the individual yields partially cancel out for many of the theoretical sources. However, for many of the experimental sources thecancellationisnotachieveddueto limitedMC statis-ticsofthevaried samples.Forexample,theeffectsofvarying the renormalization and factorization scales change the MC yield in the Z SRBZ sr in Table2 andthe Z CRBZ cr by about20%,but the αZ transfer factor changes by only 1%. In Table 2, only the 1<mj j≤1.5TeV yields are shown forthe purpose of illustrating thepartialcancellationintheratio.

Ingeneral,theuncertaintiesarehigherwithmj j.TheMC sam-plestatisticsisthelargestsourceofsystematicuncertainties,with theuncertaintyincreasingwithmj j duetolimitednumberof sim-ulated events. The theory uncertainties are also higher withmj j values for the same reason. The experimental jet energy uncer-tainties are also affected by the limited sample size, with larger ﬂuctuations because of ﬂuctuations that do not cancel for each individual systematicvariations. For the sources contributing the

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Fig. 4. ContributionstotherelativeuncertaintyinthetransferfactorsαZ(left)and αW (right)inthethreemj j binsoftheSR.Thetheoreticaluncertaintiesfromthe

sourcesnotedinthelegendarecombinedinquadrature.

Fig. 5. Distributionofeventyieldsinthesignalregionformj j(left)andEmissT (right).

TheEmiss

T distributionsstartat180GeV andshowsthemostsensitivemj j>2TeV

subsetoftheSRasindicatedbythearrow.Thepostﬁt normalizationsformj j(EmissT )

distributionsuseseparatebackground,B,normalizationsinthethree(one)mj jbins

of1<mj j≤1.5TeV,1.5<mj j≤2TeV,andmj j>2TeV (mj j>2TeV), andsumthe

contributionsfrom W andZ bosons(electroweakandstrongproductionmodes).

ThehypotheticalsignalS (emptybluehistogram)isshownontopofB forBinv=1.

ThebottompanelsshowtheratiosofN (dots)andB+S (blueline)toB withthe systematicuncertaintybandshownonthelineat1.Thebinwidthinthemj jplots

(Emiss

T )is500GeV (50GeV exceptfortheﬁrstbinwiththenon-zeroentry,whichis

20GeV).SeethecaptionofFig.2forotherplottingdetails.

largest uncertainties, the αZ and the αW variations in the three mj j binsareshowngraphicallyinFig.4.

The combination ofuncertainties from various sources shows that the dominantcategory has a systematic origin(penultimate rowofTable2).ThelackofMCstatisticalprecisionforbackground processeswithmj j>2TeV hasthelargestimpactonBinv.Wenote

thatthe valuesarepercentimprovements oftheﬁnal limiton

Binv, so they do not add in quadrature or in anysuch standard

statisticalcombinations. 7.Resultsandinterpretations

The 2252 observed events in the SR are divided among the three mj j bins defined previously: 952, 667, and 633 events. Thesevaluesareconsistentwiththebackground-onlypostfityields of the sum of the background processes of 2100 events, which are divided among the three mj j bins: 850±113, 660±90, and 590±81,respectively.Theuncertaintyrepresentsthecombined ef-fectdueto experimentalandtheoretical systematicuncertainties. Thesepostfitvaluesarealsoconsistentwiththeprefitpredictions. Theexpectedsignalyields(for Binv=1 forVBF andgluon fusion)

are 300,310,and 460,respectively, andthelast mj j bin hasthe highestsensitivitywithS/B≈0.8.

ThepostﬁtSR eventdistributionsofmj j and EmissT are shown

inFig.5,andweobserveagreement,withinuncertainties,between thedataandtheexpectedbackgrounds.

Fig. 6. Upperlimitson(a)thespin-independent wimp–nucleoncrosssectionusing HiggsportalinterpretationsofBinvat90% CLvs.mwimpand(b)theVBFcross

sec-tiontimesthebranchingfractiontoinvisibledecaysat95% CLvs.mscalar.Thetop

plotshowsresultsfromRef. [85–87].

Theleft plotinFig.5alsoshowsthatthe S/B ratioriseswith increasingmj j values,whichmotivatesourdivision oftheSRinto multiplebins.ThetotalelectroweakcontributionintheSRis rela-tivelysmallatO(10%)(Table 1),butthemuchflatterdistribution ofmj j makes it an important contributionto the final result. As noted in Section 5, the background estimation is done indepen-dentlyforeachmj j bintoreducethedependenceonmj j modeling. Thefit,assumingthe 125GeV Higgsboson,givestheobserved (expected)upperlimitonBinv of0.37

0.28+₋0₀._.11₀₈at95% CL,and 0.320.23₋+₀0._.11₁₀at90% CL,wheretheuncertaintiesplacedonthe expectedlimit representthe1σ variations. Withthisresult, con-nectionsto wimp darkmattercanbemadeinthecontextofHiggs portal models [82]. The limit on Binv can be used to set limit

ontheHiggs-wimp couplingbythe wimp-nucleonscattering cross sectionformulae(σwimp-nucleon).Inthispaper,scalarandMajorana

fermion wimp modelsareconsidered[11,83,84].

The overlay of the interpretation of this result with the limits from some of the direct detection experiments [85–87] showsthe complementarityin coverage (Fig.6(a)). Forthe scalar wimp interpretationcrosssectionsare excluded atvaluesranging from O10−42 to O10−45cm2 and for the Majorana fermion wimp _{interpretation} _the _exclusion _range _is _from O₁₀−45 _to

O10−46_cm2_,_depending_on_{the wimp mass.}_The_uncertainty_band

intheplotusesanupdatedcomputationofthenucleonform fac-tors[88].

The correlation between Binv and σwimp-nucleon is presented

in the effective ﬁeld theory framework assuming that the new-physicsscale isO(1)TeV [28], wellabovethescale probedatthe Higgsbosonmass.Addingarenormalizablemechanismfor gener-atingthefermion wimp massescouldmodifytheabove-mentioned correlation[89].

Inplaceofthe125GeV Higgsboson,thesameselectionis ap-plied to additional scalars with masses (mscalar) of up to 3TeV

assuming only VBF production.The fraction ofVBF signal events that pass thesignal region eventselections corresponding tothe

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acceptance times eﬃciency ranges from 0.6–3%. The signal eﬃ-ciency for the inclusive mj j>1TeV selection increases with the mass of the scalar boson, because the VBF jetsis more forward withhighermass,andthus havemoreeventsathighervaluesof

mj j.The limiton σscalarvbf ·Binv asa functionofmscalar is shownin

Fig.6(b).The95% conﬁdencelevel upperlimitson thecross sec-tiontimesbranchingfractionareintherangeof0.3–1.7pb.

8. Conclusions

A search for Higgs boson decays into invisible particles is presented using the 36.1fb−1 _of _{pp collision} _data _taken _at

√

s=13TeV collected in 2015 and 2016 by the ATLAS detector atthe LHC.The targeted signature isthe VBF topology withtwo energeticjetswithawidegapin ηandlarge Emiss_T .

Assuming the Standard Model cross section for the 125GeV Higgsboson,an upperlimit of0.37 issetonBinv at95% CL. This

resultisinterpretedusingHiggsportalmodelsto excluderegions

inthe σwimp-nucleonvs.mwimpparameterspacetoexcludecross

sec-tion values ranging from O10−42 to O10−46cm2, depending onthe wimp massandthe wimp model.

Searches for invisible decays of scalars with masses of up to 3TeV arereported fortheﬁrst time fromATLAS in theVBF pro-ductionmode.Theseresultsarerathergeneralandcanbeusedfor furtherinterpretations.

Acknowledgements

We thankCERN for the very successfuloperation of theLHC, aswell asthe support stafffrom ourinstitutions without whom ATLAScouldnotbeoperatedeﬃciently.

WeacknowledgethesupportofANPCyT,Argentina;YerPhI, Ar-menia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azer-baijan; SSTC, Belarus; CNPq andFAPESP, 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, and MPG, Germany; GSRT, Greece;RGC,Hong KongSAR,China;ISF andBenoziyo Center, Is-rael; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands;RCN, Norway;MNiSW andNCN, Poland;FCT, Portu-gal; MNE/IFA, Romania; MES of Russia andNRC 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-dividualgroupsandmembershavereceivedsupport fromBCKDF, Canarie,CRCandComputeCanada,Canada;COST,ERC,ERDF, Hori-zon 2020, andMarie Skłodowska-Curie Actions, European Union; Investissements d’ AvenirLabex and Idex, ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia pro-grammesco-ﬁnancedbyEU-ESFandtheGreekNSRF,Greece; BSF-NSF and GIF, Israel; CERCA Programme Generalitat de Catalunya, Spain;TheRoyalSocietyandLeverhulmeTrust,UnitedKingdom.

The crucial computingsupport fromall WLCG partners is ac-knowledged gratefully,in particularfromCERN, theATLAS Tier-1 facilities atTRIUMF(Canada),NDGF(Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA(Germany), INFN-CNAF (Italy), NL-T1 (Netherlands),PIC (Spain), ASGC (Taiwan), RAL (UK) andBNL (USA),theTier-2facilitiesworldwideandlargenon-WLCGresource providers.Majorcontributorsofcomputingresourcesarelisted in Ref. [90].

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TheATLASCollaboration

M. Aaboud34d,G. Aad99,B. Abbott125, O. Abdinov13,∗,B. Abeloos129,D.K. Abhayasinghe91, S.H. Abidi164, O.S. AbouZeid39,N.L. Abraham153, H. Abramowicz158,H. Abreu157,Y. Abulaiti6,

B.S. Acharya64a,64b,o,S. Adachi160,L. Adamczyk81a, J. Adelman119,M. Adersberger112,A. Adiguzel12c,ah, T. Adye141,A.A. Affolder143,Y. Aﬁk157, C. Agheorghiesei27c,J.A. Aguilar-Saavedra137f,137a,

F. Ahmadov77,af,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. Alhroob125, B. Ali139, G. Alimonti66a, J. Alison36,S.P. Alkire145,C. Allaire129, B.M.M. Allbrooke153,B.W. Allen128, 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,L. Ambroz132,C. Amelung26,D. Amidei103,S.P. Amor Dos Santos137a,137c, S. Amoroso44,C.S. Amrouche52, C. Anastopoulos146,L.S. Ancu52,N. Andari21,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,L. Aperio Bella35,

G. Arabidze104,J.P. Araque137a, 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,O. Arslan24,A. Artamonov109,∗,G. Artoni132, S. Artz97, S. Asai160,N. Asbah44, A. Ashkenazi158, E.M. Asimakopoulou169, L. Asquith153,K. Assamagan29, R. Astalos28a, R.J. Atkin32a,M. Atkinson170,N.B. Atlay148,K. Augsten139, G. Avolio35,R. Avramidou58a, M.K. Ayoub15a,G. Azuelos107,au, A.E. Baas59a,M.J. Baca21, H. Bachacou142,K. Bachas65a,65b,

M. Backes132,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, E.M. Baldin120b,120a, P. Balek177,F. Balli142,W.K. Balunas134,J. Balz97,E. Banas82,A. Bandyopadhyay24, S. Banerjee178,k, A.A.E. Bannoura179,L. Barak158, W.M. Barbe37,E.L. Barberio102, D. Barberis53b,53a,M. Barbero99, T. Barillari113,M-S. Barisits35,J. Barkeloo128,T. Barklow150, N. Barlow31, R. Barnea157, S.L. Barnes58c, B.M. Barnett141,R.M. Barnett18,Z. Barnovska-Blenessy58a, A. Baroncelli72a,G. Barone26, A.J. Barr132, L. Barranco Navarro171, F. Barreiro96,J. Barreiro Guimarães da Costa15a, R. Bartoldus150, A.E. Barton87, P. Bartos28a,A. Basalaev135,A. Bassalat129, R.L. Bates55,S.J. Batista164,S. Batlamous34e,J.R. Batley31, M. Battaglia143,M. Bauce70a,70b,F. Bauer142, K.T. Bauer168,H.S. Bawa150,m,J.B. Beacham123,

M.D. Beattie87,T. Beau133,P.H. Beauchemin167, P. Bechtle24,H.C. Beck51,H.P. Beck20,r,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. Beresford132, M. Beretta49,D. Berge44,E. Bergeaas Kuutmann169, N. Berger5, L.J. Bergsten26, J. Beringer18,S. Berlendis7,N.R. Bernard100, G. Bernardi133,C. Bernius150, F.U. Bernlochner24, T. Berry91,P. Berta97, C. Bertella15a,G. Bertoli43a,43b,I.A. Bertram87,G.J. Besjes39,

O. Bessidskaia Bylund43a,43b, M. Bessner44,N. Besson142,A. Bethani98,S. Bethke113, A. Betti24, A.J. Bevan90, J. Beyer113,R.M. Bianchi136, O. Biebel112, D. Biedermann19, R. Bielski98,K. Bierwagen97, N.V. Biesuz69a,69b,M. Biglietti72a, T.R.V. Billoud107, M. Bindi51,A. Bingul12d,C. Bini70a,70b,

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A.E. Bolz59b,M. Bomben133, M. Bona90, J.S. Bonilla128, M. Boonekamp142, A. Borisov121,G. Borissov87, J. Bortfeldt35, D. Bortoletto132,V. Bortolotto71a,61b,61c,71b,D. Boscherini23b,M. Bosman14,

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M. Campanelli92,A. Camplani39, A. Campoverde148,V. Canale67a,67b,M. Cano Bret58c, J. Cantero126, T. Cao158, Y. Cao170, M.D.M. Capeans Garrido35,I. Caprini27b, M. Caprini27b, M. Capua40b,40a,

R.M. Carbone38, R. Cardarelli71a, F.C. Cardillo50,I. Carli140,T. Carli35,G. Carlino67a,B.T. Carlson136, L. Carminati66a,66b, R.M.D. Carney43a,43b, S. Caron117,E. Carquin144b, S. Carrá66a,66b,

G.D. Carrillo-Montoya35,D. Casadei32b, M.P. Casado14,g, A.F. Casha164,M. Casolino14,D.W. Casper168, R. Castelijn118,F.L. Castillo171,V. Castillo Gimenez171,N.F. Castro137a,137e,A. Catinaccio35,

J.R. Catmore131,A. Cattai35,J. Caudron24,V. Cavaliere29,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,

D.G. Charlton21,C.C. Chau33,C.A. Chavez Barajas153, S. Che123,A. Chegwidden104, S. Chekanov6, S.V. Chekulaev165a, G.A. Chelkov77,at,M.A. Chelstowska35,C. Chen58a, C.H. Chen76,H. Chen29, J. Chen58a,J. Chen38,S. Chen134, S.J. Chen15c,X. Chen15b,as,Y. Chen80,Y-H. Chen44,H.C. Cheng103, H.J. Cheng15d,A. Cheplakov77, E. Cheremushkina121,R. Cherkaoui El Moursli34e, E. Cheu7,K. Cheung62, L. Chevalier142,V. Chiarella49, G. Chiarelli69a,G. Chiodini65a, A.S. Chisholm35,A. Chitan27b,I. Chiu160, Y.H. Chiu173, M.V. Chizhov77,K. Choi63, A.R. Chomont129, S. Chouridou159,Y.S. Chow118,

V. Christodoulou92, M.C. Chu61a,J. Chudoba138,A.J. Chuinard101,J.J. Chwastowski82,L. Chytka127, 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, A.E.C. Coimbra177, L. Colasurdo117, B. Cole38,A.P. Colijn118, J. Collot56,

P. Conde Muiño137a,137b, E. Coniavitis50, S.H. Connell32b, I.A. Connelly98, S. Constantinescu27b, F. Conventi67a,av,A.M. Cooper-Sarkar132, F. Cormier172,K.J.R. Cormier164, M. Corradi70a,70b,

E.E. Corrigan94,F. Corriveau101,ad, A. Cortes-Gonzalez35, M.J. Costa171,D. Costanzo146, G. Cottin31, G. Cowan91, B.E. Cox98,J. Crane98, K. Cranmer122, S.J. Crawley55, R.A. Creager134, G. Cree33, S. Crépé-Renaudin56, F. Crescioli133, M. Cristinziani24,V. Croft122,G. Crosetti40b,40a,A. Cueto96, T. Cuhadar Donszelmann146, A.R. Cukierman150,J. Cúth97, S. Czekierda82,P. Czodrowski35,

M.J. Da Cunha Sargedas De Sousa58b, C. Da Via98, W. Dabrowski81a, T. Dado28a,y,S. Dahbi34e,T. Dai103, F. Dallaire107, C. Dallapiccola100,M. Dam39,G. D’amen23b,23a,J. Damp97,J.R. Dandoy134,M.F. Daneri30, N.P. Dang178,k,N.D Dann98, M. Danninger172,V. Dao35,G. Darbo53b, S. Darmora8,O. Dartsi5,

A. Dattagupta128, T. Daubney44, S. D’Auria55, W. Davey24,C. David44,T. Davidek140, D.R. Davis47, E. Dawe102, I. Dawson146,K. De8, R. De Asmundis67a,A. De Benedetti125,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,t, D. De Pedis70a, A. De Salvo70a,U. De Sanctis71a,71b,A. De Santo153,

K. De Vasconcelos Corga99, J.B. De Vivie De Regie129,C. Debenedetti143,D.V. Dedovich77,

N. Dehghanian3, M. Del Gaudio40b,40a, J. Del Peso96,Y. Delabat Diaz44, D. Delgove129, F. Deliot142, C.M. Delitzsch7,M. Della Pietra67a,67b, D. Della Volpe52, A. Dell’Acqua35,L. Dell’Asta25,M. Delmastro5, C. Delporte129,P.A. Delsart56, D.A. DeMarco164, S. Demers180, M. Demichev77,S.P. Denisov121,

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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 Clemente134,C. Di Donato67a,67b,

A. Di Girolamo35, B. Di Micco72a,72b,R. Di Nardo100, K.F. Di Petrillo57, A. Di Simone50,R. Di Sipio164, D. Di Valentino33,C. Diaconu99,M. Diamond164, F.A. Dias39,T. Dias Do Vale137a, 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. Dolejsi140,Z. Dolezal140,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,Y. Du58b,J. Duarte-Campderros158,F. Dubinin108, M. Dubovsky28a,A. Dubreuil52, E. Duchovni177, G. Duckeck112, A. Ducourthial133,O.A. Ducu107,x, D. Duda113,A. Dudarev35, A.C. Dudder97,E.M. Duﬃeld18,L. Duﬂot129,M. Dührssen35, C. Dülsen179,M. Dumancic177, A.E. Dumitriu27b,e,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. Escalier129,C. Escobar171, O. Estrada Pastor171,A.I. Etienvre142,

E. Etzion158,H. Evans63, A. Ezhilov135,M. Ezzi34e, F. Fabbri55,L. Fabbri23b,23a, V. Fabiani117,

G. Facini92,R.M. Faisca Rodrigues Pereira137a,R.M. Fakhrutdinov121,S. Falciano70a,P.J. Falke5,S. Falke5, J. Faltova140, Y. Fang15a, M. Fanti66a,66b, A. Farbin8, A. Farilla72a,E.M. Farina68a,68b,T. Farooque104, S. Farrell18,S.M. Farrington175,P. Farthouat35, F. Fassi34e,P. Fassnacht35,D. Fassouliotis9,

M. Faucci Giannelli48, A. Favareto53b,53a, W.J. Fawcett52,L. Fayard129, O.L. Fedin135,p,W. Fedorko172, M. Feickert41,S. Feigl131,L. Feligioni99,C. Feng58b,E.J. Feng35,M. Feng47, M.J. Fenton55,

A.B. Fenyuk121, L. Feremenga8,J. Ferrando44,A. Ferrari169, P. Ferrari118,R. Ferrari68a, D.E. Ferreira de Lima59b, A. Ferrer171,D. Ferrere52, C. Ferretti103, F. Fiedler97, A. Filipˇciˇc89, F. Filthaut117, K.D. Finelli25, M.C.N. Fiolhais137a,137c,a, L. Fiorini171, C. Fischer14,W.C. Fisher104,

N. Flaschel44,I. Fleck148, P. Fleischmann103, R.R.M. Fletcher134, T. Flick179, B.M. Flierl112,L.M. Flores134, L.R. Flores Castillo61a,N. Fomin17,G.T. Forcolin98,A. Formica142,F.A. Förster14,A.C. Forti98,

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K.K. Gan123, S. Ganguly177, Y. Gao88,Y.S. Gao150,m, C. García171, J.E. García Navarro171, J.A. García Pascual15a,M. Garcia-Sciveres18, R.W. Gardner36,N. Garelli150,V. Garonne131, K. Gasnikova44,A. Gaudiello53b,53a, G. Gaudio68a, I.L. Gavrilenko108, A. Gavrilyuk109,C. Gay172,

G. Gaycken24, E.N. Gazis10, C.N.P. Gee141,J. Geisen51, M. Geisen97,M.P. Geisler59a,K. Gellerstedt43a,43b, C. Gemme53b,M.H. Genest56,C. Geng103,S. Gentile70a,70b,C. Gentsos159,S. George91, D. Gerbaudo14, G. Gessner45, S. Ghasemi148,M. Ghasemi Bostanabad173,M. Ghneimat24, B. Giacobbe23b,

S. Giagu70a,70b,N. Giangiacomi23b,23a, P. Giannetti69a, A. Giannini67a,67b,S.M. Gibson91,M. Gignac143, D. Gillberg33, G. Gilles179,D.M. Gingrich3,au, M.P. Giordani64a,64c,F.M. Giorgi23b, P.F. Giraud142,

P. Giromini57, G. Giugliarelli64a,64c,D. Giugni66a,F. Giuli132, M. Giulini59b,S. Gkaitatzis159, I. Gkialas9,j, E.L. Gkougkousis14, P. Gkountoumis10, L.K. Gladilin111,C. Glasman96,J. Glatzer14,P.C.F. Glaysher44, A. Glazov44,M. Goblirsch-Kolb26,J. Godlewski82,S. Goldfarb102,T. Golling52,D. Golubkov121, A. Gomes137a,137b,137d,R. Goncalves Gama78a, R. Gonçalo137a, G. Gonella50,L. Gonella21, A. Gongadze77,F. Gonnella21,J.L. Gonski57, S. González de la Hoz171,S. Gonzalez-Sevilla52, L. Goossens35, P.A. Gorbounov109,H.A. Gordon29, B. Gorini35,E. Gorini65a,65b,A. Gorišek89, A.T. Goshaw47, C. Gössling45, M.I. Gostkin77,C.A. Gottardo24,C.R. Goudet129,D. Goujdami34c, A.G. Goussiou145,N. Govender32b,c, C. Goy5,E. Gozani157,I. Grabowska-Bold81a,P.O.J. Gradin169, E.C. Graham88, J. Gramling168,E. Gramstad131,S. Grancagnolo19,V. Gratchev135, P.M. Gravila27f, C. Gray55,H.M. Gray18,Z.D. Greenwood93,aj, C. Grefe24,K. Gregersen92, I.M. Gregor44,P. Grenier150, K. Grevtsov44,J. Griﬃths8, A.A. Grillo143,K. Grimm150,b, S. Grinstein14,z, Ph. Gris37,J.-F. Grivaz129,