Article
Reference
Search for non-resonant Higgs boson pair production in the final state with the ATLAS detector in Collisions at TeV
ATLAS Collaboration
ADORNI BRACCESI CHIASSI, Sofia (Collab.), et al.
Abstract
A search for non-resonant Higgs boson pair production, as predicted by the Standard Model, is presented, where one of the Higgs bosons decays via the H→bb channel and the other via one of the H→WW⁎/ZZ⁎/ττ channels. The analysis selection requires events to have at least two b-tagged jets and exactly two leptons (electrons or muons) with opposite electric charge in the final state. Candidate events consistent with Higgs boson pair production are selected using a multi-class neural network discriminant. The analysis uses 139 fb$^{−1}$ of pp collision data recorded at a centre-of-mass energy of 13 TeV by the ATLAS detector at the Large Hadron Collider. An observed (expected) upper limit of 1.2 (0.9−0.3+0.4) pb is set on the non-resonant Higgs boson pair production cross-section at 95% confidence level, which is equivalent to 40 (29−9+14) times the value predicted in the Standard Model.
ATLAS Collaboration, ADORNI BRACCESI CHIASSI, Sofia (Collab.), et al . Search for
non-resonant Higgs boson pair production in the final state with the ATLAS detector in Collisions at TeV. Physics Letters. B , 2020, vol. 801, p. 135145
DOI : 10.1016/j.physletb.2019.135145
Available at:
http://archive-ouverte.unige.ch/unige:131175
Disclaimer: layout of this document may differ from the published version.
1 / 1
Contents lists available atScienceDirect
Physics Letters B
www.elsevier.com/locate/physletb
Search for non-resonant Higgs boson pair production in the bb ν ν
final state with the ATLAS detector in pp collisions at √
s = 13 TeV
.TheATLASCollaboration
a r t i c l e i n f o a b s t ra c t
Articlehistory:
Received19August2019
Receivedinrevisedform4December2019 Accepted5December2019
Availableonline13December2019 Editor:M.Doser
Asearchfornon-resonantHiggsbosonpairproduction,aspredictedbytheStandardModel,ispresented, where one ofthe Higgs bosonsdecays via the H→bb channel and the othervia one of the H→ W W∗/Z Z∗/τ τ channels.Theanalysisselection requireseventstohaveatleasttwob-taggedjetsand exactlytwoleptons(electronsormuons)withoppositeelectricchargeinthefinalstate.Candidateevents consistentwithHiggsbosonpairproductionareselectedusingamulti-classneuralnetworkdiscriminant.
Theanalysis uses139 fb−1 ofpp collisiondata recordedatacentre-of-massenergyof13 TeVbythe ATLASdetectorattheLargeHadronCollider.Anobserved(expected)upperlimitof1.2(0.9+−00..43) pbis set on thenon-resonant Higgsboson pairproductioncross-section at95% confidence level,which is equivalentto40(29+−149)timesthevaluepredictedintheStandardModel.
©2019TheAuthor(s).PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCCBYlicense (http://creativecommons.org/licenses/by/4.0/).FundedbySCOAP3.
1. Introduction
In2012,theATLASandCMSCollaborationsreportedtheobser- vationofanewparticleinthesearchfortheStandardModel(SM) Higgsboson (H)[1,2]. Sofar,measurementsofthespin andcou- plingsofthe newparticleare consistentwiththose predictedby theBrout–Englert–Higgs(BEH)mechanismofthe SM[3–12]. The SM predicts non-resonant productionof Higgs boson pairs (H H) in proton–proton(pp) collisions, referred to as non-resonantH H production,withthedominantproductionmodesattheLHCpro- ceedingviathegluon–gluonfusion(ggF)process.TheggFprocess hastwo leading order contributions: thefirst corresponds to the so-called‘trianglediagram’,which includesthe Higgsboson self- coupling,andthesecond istheso-called‘boxdiagram’,whichin- cludesaheavy-quarkloopwithtwofermion–fermion–Higgs(f f H) vertices.Thesetwoamplitudesinterferedestructively,resultingin alow cross-section of only31.05±1.90 fb forthe ggF H H pro- ductionmode,computedatnext-to-next-to-leading order(NNLO) andincludingfinitetop-quarkmasseffects[13–20].Feynmandia- gramsillustratingthesetwocontributionsareshowninFig.1.The measurementofnon-resonant H HproductionattheLHCstandsas animportanttestoftheBEHmechanism.Inmanybeyond-the-SM (BSM)theories,H Hproductioncanbeenhancedbymodifyingthe Higgs boson self-coupling, λH H H, or the top-quark Yukawa cou- pling, yt,and/orbyintroducingnewcontactinteractions between
E-mailaddress:atlas.publications@cern.ch.
Fig. 1.FeynmandiagramsforleadingorderggFproductionofHiggsbosonpairs:the
‘trianglediagram’sensitivetotheHiggsbosonself-couplingontheleftandthe‘box diagram’ontheright.
two top-quarks or gluons and two Higgs bosons or introducing productionmechanismsviaintermediateBSMparticles[21–23].
The ATLAS and CMS Collaborations have performed searches for non-resonant H H production in a variety of final states at 13 TeV [24–33]. No significant excess of events beyond SM ex- pectationsisobservedinthesesearches,withtheATLAS andCMS data-analyses setting observed(expected) limitson non-resonant H H production to be no larger than 6.9 (10.0) and 22.2 (12.8) timesthepredictedrateintheSM,respectively[34,35].
This Letter describes a search for non-resonant H H produc- tion inthe bbνν final state, where refers to a lepton(either an electron ora muon), using13 TeV pp collision datacollected with the ATLAS detector during 2015–2018 and corresponding to a total integrated luminosity of 139 fb−1. The analysis uses machine-learningtechniquesbasedonfeedforwardneuralnetwork architectures[36] toconstruct an event-level classifier trainedto distinguish between the H H signal and SM backgrounds. Analy- ses searching for non-resonant H H production via similar decay channelswereperformedpreviouslyinthesingle-leptonfinalstate https://doi.org/10.1016/j.physletb.2019.135145
0370-2693/©2019TheAuthor(s).PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCCBYlicense(http://creativecommons.org/licenses/by/4.0/).Fundedby SCOAP3.
byATLASinsearchesforH H→bbW W∗ [28] andinthedilepton channelbyCMSinsearchesforH H→bbW W∗/bb Z Z∗ [31].
2. ATLASdetector
The ATLAS detector [37–39] is a general-purpose particle de- tectorwithforward–backwardsymmetriccylindricalgeometry.1 It includesaninnertrackingdetector(ID),immersedinanaxialmag- netic field,which providesprecision tracking ofchargedparticles over the rangeof |η|<2.5.Calorimeter systems with eitherliq- uidargonorscintillatortilesastheactivemediumprovideenergy measurements overthe rangeof|η|<4.9.The muon spectrome- ter(MS)ispositioned outsidethecalorimetersandincludesthree air-coretoroidalmagnets.TheMSiscomposedofseveraltypesof muondetectorswhichprovidetriggerandhigh-precisiontracking capabilitiesfor |η|<2.4 and |η|<2.7,respectively. A hardware- based trigger followed by a software-based trigger reduce the recordedeventratetoanaverageof1 kHz[40].
3. Datasetandsimulatedevents
Thedatausedforthissearchwerecollectedin ppcollisionsat theLHCwithacentre-of-massenergyof13 TeV.Onlythose data collected during stableLHC beam conditions andwith all ATLAS detectorsubsystems fullyoperationalare used,andcorrespondto an integrated luminosity of 139 fb−1. The selection of candidate eventswithoppositelychargedleptons isbasedonacombination of single-lepton and dilepton triggers.2 The use of a given trig- gerdepends on the flavour and the transverse momenta (pT) of thetwo(pT-ordered)leptonsintheevent,andonthedata-taking period.Single-leptontriggerswith pT thresholds between22 and 28 GeVaregivenpriorityoverdileptontriggers.Thecriteriaofthe dileptontriggersarecheckedonlyifnosingle-leptontriggercrite- riaare metandhavepT thresholdsaslowas19(10) GeVforthe leading (subleading)lepton.At leastone reconstructed lepton(or leptonpair)hastomatchacorrespondingtriggerobject,inwhich casetheir offline pT mustbehigherthanthetriggerthresholdby atleast2 GeV,inordertobeontheefficiencyplateauofthecor- respondingtrigger.
MonteCarlo(MC) simulation[41] isused tomodel thesignal processes and in the estimation of SM background processes. A GEANT4 [42] simulation ofthe ATLAS detectorwas used forthe backgroundprocesses.ThesignalMCsampleswereprocessedwith afastsimulationthatreliesonaparameterisationofthecalorime- terresponse[41] andonGEANT4forthetrackingdetectors.Simu- latedeventsare reconstructedusingthesamealgorithms asused fordataandincludetheeffectsofmultiple ppinteractions inthe sameor neighbouringbunch crossings, collectively referred to as pile-up.The simulation of pile-up collisions was performed with Pythia 8.186 [43] using the ATLAS A3 set of tuned parameters [44] and the NNPDF2.3LO parton distribution function (PDF) set [45].Simulatedeventswere reweightedtomatchthedistribution ofpile-up interactions indata. Theaverage amount ofpile-up in thedatacollectedduring2015–2018was33.7.
Thesignal processes withggF-initiated non-resonant H H pro- ductioninthebbννfinalstateweregeneratedwithaneffective
1 ATLASusesaright-handed coordinatesystemwith itsoriginat thenominal interactionpoint(IP)inthecentreofthedetectorandthez-axisalongthebeam pipe.Thex-axispointsfromtheIPtothecentreoftheLHCring,andthe y-axis pointsupwards.Cylindricalcoordinates(r,φ)areusedinthetransverseplane,φ beingtheazimuthalanglearoundthez-axis.Thepseudorapidityisdefinedinterms ofthepolarangleθasη= −ln tan(θ/2).Theangulardistanceismeasuredinunits ofR≡
(η)2+(φ)2.
2 Distinctsetsofsingle-leptontriggersareusedforelectronsandmuons.Dilepton triggersrequireeithertwoelectrons,twomuons,oroneelectronandonemuon.
Lagrangianintheinfinitetop-quarkmassapproximation.Thegen- erated signal eventswerereweighted withformfactors thattake into account the finite mass of the top-quark [46,47]. SM back- groundprocessesweresimulatedusingdifferentMCeventgener- ators.TheMCmatrixelement(ME)eventgeneratorsandPDFsets, the parton showering (PS) and the underlying event (UE) mod- elling, UE tuned parameters (tune), andthe accuracy ofthe the- oretical cross-sections usedto normalise thesimulated processes are summarised in Table 1.Each SM backgroundprocess is nor- malised to the best available respective theoretical cross-section.
ThemassoftheHiggsbosonwassetto125 GeVforallsignaland backgroundprocesses.The H H branching fractions(BF)predicted bytheSM [13] areusedforallHiggsbosondecays.MadSpin[48]
was used to model top-quark spin correlations and EvtGen [49]
was usedtomodelpropertiesofb- andc-hadrondecays forpro- cessesusingPythiaandforthesignalprocesses.
SM top-quarkpair production (tt)¯ andthe production of sin- gletop-quarksinassociationwithW bosons(W t)contributewith significantbackgroundcontaminationinthebbνν finalstate.At next-to-leading-order (NLO) accuracy, there exists non-trivial in- terferencebetweenthesetwoprocessesthatmaybe enhancedin phase-spaceregionswhereintherearehighfractionsofW tevents [50]. Twoschemes are typically used to remove the overlap be- tween these two processes: the so-called diagram removal (DR) and diagram subtraction (DS) schemes [51]; the former is used inthe presentanalysisto removetheoverlapping eventsandthe latterisusedtoevaluatethesystematicuncertaintyincorrespond- ing background event yields. Because of these effects, the sum of the simulated t¯t and W t processes is considered as a single background process and referred to asthe ‘Top’ process in what follows.
4. Eventselectionandobjectdefinitions
Selectedeventsarerequiredtohaveatleastone ppinteraction vertexreconstructedfromatleasttwoIDtrackswithpT>0.4 GeV.
Theprimaryvertexforeacheventisdefinedasthevertexwiththe highest
(pT)2 ofassociatedID tracks[102].Eventsthat contain atleastonejetarisingfromnon-collisionsourcesordetectornoise arerejectedbyasetofqualitycriteria[103].
Loose and signal criteria are defined in orderto selectrecon- structed lepton and jet candidates, where the latter is a subset of the former. Compared to the loose objects, the signal objects arerequiredtosatisfytighteridentificationorqualitycriteriathat are designedtosuppressbackgroundcontributions.Reconstructed loose(signal) electrons arerequiredto satisfy the‘Loose’(‘Tight’) likelihoodidentificationcriteria[104].Looseelectronsarerequired tohave pT>10 GeV andtobewithin|η|<2.47.Inaddition,sig- nal electrons are required to be outside the range 1.37<|η|<
1.52,whichcorrespondstothetransitionregionsbetweenthebar- rel and endcaps of the electromagnetic calorimeters. In order to reduce background contributions fromjets misidentified as elec- trons,signal electronsarerequiredtobeisolated accordingtothe
‘Gradient’ selection criteria [104]. Reconstructed loose andsignal muon candidatesare requiredtohave pT>10 GeV,to be within
|η|<2.4,andtosatisfy the‘Medium’identificationcriteria[105].
Additionally,signalmuonsarerequiredtobeisolatedaccordingto the‘FixedCutLoose’selectioncriteria[105].Signalelectron(muon) candidates are required to originate from the primary vertex by demanding that the significanceof thetransverse impact param- eter, definedasthe absolutevalue ofthetracktransverse impact parameter,d0,measuredrelativetotheprimaryvertex,dividedby its uncertainty, σd0, satisfy |d0|/σd0 <5 (3). The difference z0 betweenthevalueofthez coordinateofthepointonthetrackat which d0 is definedandthe longitudinalpositionof theprimary
Table 1
ListoftheMEgeneratorsandPS/UEmodellingalgorithmsusedinthesimulation.AlternativegeneratorsandPS/UEmodels,usedtoestimatesystematicuncertainties,are showninparentheses.ThePDFsets,tunes,andtheperturbativeQCDhighest-orderaccuracy(leading-order,LO;next-to-leading-order,NLO;next-to-next-to-leading-order, NNLO;next-to-next-to-leading-logarithm,NNLL)usedforthenormalisationofthesamplesarealsoincluded.Thetop-quarkmassissetto172.5 GeV.
Process MEgenerator
(alternative)
ME PDF PS/UEmodel
(alternative)
UE tune Predictionorderfor totalcross-section tt¯[52,53] Powheg-Box v2[54,55] NNPDF3.0NLO [56] Pythia8.230 [57] A14 [58] NNLO + NNLL [59–65]
(MadGraph5_aMC@NLO) (Herwig7.0.4) (H7-MMHT14)
Single-tops-channel,W t [52,66,67]
Powheg-Box NNPDF3.0NLO Pythia8.230 A14 NLO + NNLL [68,69]
(MadGraph5_aMC@NLO) (Herwig7.0.4) (H7-MMHT14)
Single-topt-channel[52,66] Powheg-Box,MadSpin[48] NNPDF3.04fNLO Pythia8.230 A14 NLO + NNLL [70]
(MadGraph5_aMC@NLO) (Herwig7.0.4) (H7-MMHT14)
W,Z/γ∗+jets [71] Sherpa2.2.1 [72,73] NNPDF3.0NNLO Sherpa2.2.1 Sherpadefault NLO(LO)≤2(4) partons [74–78]
(Z/γ∗+jets) (MadGraph5_aMC@NLO) (Pythia8.230) (A14)
Diboson(W W,W Z,Z Z) [79]
Sherpa2.2.2 NNPDF3.0NNLO Sherpa2.2.2 Sherpadefault NLO(LO)≤1(3) partons [75–78]
tt W¯ ,t¯t Z[80] MadGraph5_aMC@NLO [81] NNPDF3.0NLO Pythia8.210 A14 NLO [82,83]
tt H¯ [80] MadGraph5_aMC@NLO NNPDF3.0NLO Pythia8.210 A14 NLO [84,85]
W H,Z H[86] Pythia8.186 [43] NNPDF2.3LO [45] Pythia8.186 A14 NNLO QCD + NLO EW [87–93]
ggFH[94] Powheg-Box v2NNLOPS [95] CT10 [96] Pythia8.212 AZNLO [97] NNNLO QCD + NLO EW [98]
SMH H→bbνν[99] MadGraph5_aMC@NLO 2.6.2 CT10 Herwig7.0.4 [100] H7-MMHT14 [101] NNLO [14–20]
vertexisrequiredtosatisfy|z0×sinθ|<0.5 mm,whereθ isthe polarangleofthetrackwithrespecttothez-axis.
Jetsare reconstructed fromtopological clusters of energy de- positsinthe calorimeters[106] usingthe anti-kt algorithm[107, 108] with a radius parameter of R=0.4 and calibrated as de- scribed in Ref. [109]. Candidate loose jets are required to have pT>20 GeV. Signaljetsare requiredto have|η|<2.8 andmust satisfypile-upsuppressionrequirementsbasedontheoutputofa multivariate classifier [110], which identifies jetsconsistent with a primary vertex in the region |η|<2.4 and pT <120 GeV.
The MV2c10multivariate algorithm [111] isused to identify jets containing b-hadrons (b-tagged jets). An MV2c10 working point with a b-tagging efficiency of 70%, estimated from simulated tt¯ events[112], is used. The b-tagged jetsmust have pT>20 GeV and |η|<2.5. The momentum of b-tagged jets is adjusted us- ing the muon-in-jet correction, as described in Ref. [6], by ac- countingformomentumlossesduetomuonsoriginatingfromin- flightsemileptonicb-hadrondecaysoccurringwithintheb-tagged jet.
The missing transverse momentum pmissT , the magnitude of whichis denotedby EmissT ,isconstructed fromthe negative vec- torial sumofthe transverse momenta ofcalibrated looseobjects intheevent.Anadditionaltermisincludedtoaccountfortheen- ergy ofID tracks that are matched to the primary vertexin the eventbutnottoanyoftheselectedlooseobjects[113].
Toavoiddouble-counting,looseobjectsaresubjecttotheover- lapremovalprocedure definedasfollows.Ifareconstructedelec- tron andmuon share a trackin theID, the electron is removed.
However, if the muon sharing the track with the electron is calorimeter-tagged,3thenthemuonisremovedinsteadoftheelec- tron.IfajetandanelectronarereconstructedwithinR=0.2 of eachother,thenthejetisremoved.Ifajetandamuonarewithin R=0.2 of eachother,andthe jethaslessthan threetracksor carrieslessthan50% ofthemuonpT,thenthejetisremoved;oth- erwise,themuon isremoved.Electronsormuonsseparatedfrom theremainingjetsbyR<0.4 areremoved.
The analysis selects candidate events with exactly two oppo- sitelychargedsignalleptons,electronsormuons,andatleasttwo signal b-tagged jets. To enhance sensitivity to the signal process
3 Acalorimeter-taggedmuonhasonlyareconstructedtrackintheIDmatched toenergydepositsinthecalorimetercompatiblewithaminimumionisingparticle, butnocorrespondingtracksegmentintheMS.
and to maximise rejection of the expected SM backgrounds, the analysisusesamultivariateapproachtoselectsignalevents.
5. Analysisstrategy
Theanalysisreliesontheuseofamultivariatediscriminantde- signedtoselectcandidateeventsconsistentwithnon-resonantH H production.Section 5.1describesthearchitectureandthetraining ofthe deep neural network(DNN) classifier fromwhich thedis- criminant is constructed. Section 5.2 describes the signal region selection criteria. Section 5.3describesthe final backgroundesti- mationprocedure.
5.1. DeeplearningapproachtotargetH H
The discriminant uses the outputs of a DNN classifier that is builtusingtheKeraslibrarywithTensorflow asabackend[114, 115] andusesthelwtnnlibrary[116] tointerfacewiththeanaly- sissoftwareinfrastructureoftheATLASexperiment.Thesampleof eventsused fortraining iscomposedof equalnumbersof events fromthe signalandeach ofthe dominantbackgroundprocesses:
Top(asdefinedinSection 3), Z/γ∗→(Z-),and Z/γ∗→τ τ
(Z-τ τ) production.The signal sample used inthe training ofthe classifier containsonly the H H→bbW W∗ componentduetoits larger BF relative to the H H→bbτ τ and H H→bb Z Z∗ compo- nents. However,the sumofall threesignal componentsisevalu- ated asthesignal when performing thestatisticalanalysis. Addi- tionally, all processes that make up the training sample (H H→ bbW W∗, Top,Z-,and Z-τ τ) havethe same weightduring the trainingoftheclassifier.Thetrainingsampleiscomposedofsimu- latedcandidateeventswithm>20 GeV andhavingoneormore b-taggedjets, whereeventswithexactly oneb-tagged jetare in- cludedtoincreasethenumberofeventsavailablefortraining.For thetrainingeventswithexactlyoneb-taggedjet,eachobservable thatrequiresatleasttwob-taggedjetsissettoitsmeanvalueas computedwiththefullsetoftraining eventsthatcontainatleast two b-taggedjets. Observablesthatrequiretwo b-taggedjetsare definedusingtheleadingtwob-taggedjets.Theclassifiercontains two fullyconnectedhiddenlayers each with250nodes.Rectified linearunit(ReLU)activations areusedforeachlayer[117].Inor- dertoimprovetherobustnessofthetrainingandtoreduceeffects duetoovertraining, thereisa dropoutlayer thatrandomly drops 50% ofthe nodesbetween thetwo fullyconnected layers during training[118].Theclassifierproducesfouroutputsthatarepassed through asoftmaxactivation, constraining their sumto one[36].
