Contents lists available atScienceDirect
Physics
Letters
B
www.elsevier.com/locate/physletb
Search
for
a
massive
resonance
decaying
to
a
pair
of
Higgs
bosons
in
the
four
b
quark
final
state
in
proton–proton
collisions
at
√
s
=
13 TeV
.
The
CMS
Collaboration
CERN,Switzerland
a
r
t
i
c
l
e
i
n
f
o
a
b
s
t
r
a
c
t
Articlehistory:
Received13October2017
Receivedinrevisedform23March2018
Accepted29March2018
Availableonline4April2018
Editor: M.Doser Keywords: CMS Physics Extradimensions Graviton Radion
di-Higgsbosonresonance
AsearchforamassiveresonancedecayingintoapairofstandardmodelHiggsbosons,inafinalstate consisting of two b quark–antiquark pairs, is performed. A data sample of proton–proton collisions at acentre-of-massenergy of13 TeV isused, collectedby the CMSexperiment atthe CERN LHCin 2016,andcorrespondingtoanintegratedluminosityof35.9 fb−1.TheHiggsbosonsarehighly
Lorentz-boosted andare eachreconstructedasasinglelarge-areajet. Thesignalischaracterizedbyapeakin thedijetinvariantmassdistribution,aboveabackgroundfromthestandardmodelmultijetproduction. Theobservationsareconsistentwiththebackgroundexpectations,andareinterpretedasupperlimitson theproductsofthes-channelproductioncrosssectionsandbranchingfractionsofnarrowbulkgravitons andradionsinwarpedextra-dimensionalmodels.Thelimitsrangefrom126to1.4 fb at95%confidence levelforresonanceswithmassesbetween750and3000 GeV,andarethemoststringenttodate,over theexploredmassrange.
©2018TheAuthor(s).PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCCBYlicense (http://creativecommons.org/licenses/by/4.0/).FundedbySCOAP3.
1. Introduction
In the standard model (SM), the pair production of Higgs bosons(H) [1–3] inproton–proton(pp) collisionsat
√
s=
13 TeV isarareprocess [4].However,theexistenceofmassiveresonances decaying to Higgs boson pairs (HH) in many new physics mod-els mayenhancethisrateto a levelobservable attheCERN LHC using the current data. For instance, models with warped extra dimensions(WED) [5] containnewparticlessuchasthespin-0 ra-dion [6–8] andthespin-2firstKaluza–Klein(KK)excitationofthe graviton [9–11],whichhavesizeablebranchingfractionstoHH.TheWEDmodelshaveanextraspatialdimensioncompactified between two branes, with the region between (called the bulk) warpedviaanexponentialmetric
κ
l,κ
beingthewarpfactorand l the coordinateof theextra spatial dimension [12]. The reduced Planck scale (MPl≡
MPl/
8π
, MPl beingthe Planck scale) iscon-sideredafundamentalscale.Thefreeparametersofthemodelare
κ
/
MPlandtheultravioletcutoffofthetheoryR
≡
√
6e−κlM Pl[6].
In pp collisionsatthe LHC,the graviton andthe radionare pro-ducedprimarilythrough gluon–gluon fusionandarepredictedto decaytoHH [13].
Other scenarios, such as the two-Higgs doublet models [14] (in particular, the minimal supersymmetric model [15]) andthe
E-mailaddress:cms-publication-committee-chair@cern.ch.
Georgi–Machacek model [16] predict spin-0 resonances that are produced primarily through gluon–gluon fusion, anddecay toan HH pair.TheseparticleshavethesameLorentzstructureand effec-tive couplingstothe gluonsand, fornarrowwidths,resultinthe samekinematicdistributions asthoseforthebulk radion.Hence, theresultsofthispaperarealsoapplicabletothisclassofmodels. Searches for a new particle X in the HH decay channel have beenperformedby theATLAS [17–19] andCMS [20–24] Collabo-rations inpp collisions at
√
s=
7 and8 TeV. More recently, the ATLAS Collaboration haspublished limitson the production of a KKbulkgraviton,decayingtoHH,inthebbbb finalstate,usingpp collisiondataat√
s=
13 TeV,correspondingtoanintegrated lumi-nosityof3.2 fb−1[25].Becausethelongitudinalcomponentsofthe W and Z bosonscoupletotheHiggsfieldintheSM, aresonance decaying to HH potentially also decays intoWW and ZZ, with a comparablebranching fraction forX→
ZZ, andwitha branching fractionforX→
WW thatistwiceaslarge.SearchesforX→
WW andZZ havebeenperformedbyATLASandCMS [26–35].This letter reportson the search for a massive resonance de-caying to an HH pair, in the bbbb final state (with a branching fraction
≈
33% [36]),performedusinga datasetcorresponding to 35.9 fb−1 ofpp collisionsat√
s=
13 TeV.Thesearch significantly improves upon the CMS analysis performed using the LHC data collectedat√
s=
8 TeV [24],andextendsthesearchedmassrange to 750–3000 GeV. This search is conducted for both the radionhttps://doi.org/10.1016/j.physletb.2018.03.084
0370-2693/©2018TheAuthor(s).PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCCBYlicense(http://creativecommons.org/licenses/by/4.0/).Fundedby
andthe graviton, whereas the earliersearch only considered the former.
In this search, the X
→
HH decay would result in highly Lorentz-boostedandcollimated decayproductsofH→
bb,which are referred to asH jets. These are reconstructed using jet sub-structure and jet flavour-tagging techniques [37–39]. The back-ground consists mostly of SM multijet events, and is estimated using several control regions defined in the phase space of the massesandflavour-tagging discriminatorsof the two H jets, and the HH dijet invariant mass,allowing thebackground to be pre-dicted over the entire range of mX explored. The signal wouldappearasa peak inthe HH dijet invariant massspectrum above asmoothbackgrounddistribution.
2. TheCMSdetectorandeventsimulations
TheCMSdetectorwithits coordinatesystemandtherelevant kinematic variables is described in Ref. [40]. The central feature of the CMS apparatus is a superconducting solenoid of 6 m in-ternal diameter, providing a magnetic field of 3.8 T. Within the field volume are siliconpixel andstrip trackers, alead tungstate crystalelectromagneticcalorimeter (ECAL), anda brass and scin-tillatorhadroncalorimeter(HCAL),eachcomposed ofabarreland twoendcapsections.The trackercoversa pseudorapidity
η
range from−
2.
5 to 2.5 withthe ECAL andthe HCAL extending up to|
η
|
=
3. Forward calorimeters in the region up to|
η
|
=
5 pro-vide almost hermetic detector coverage. Muons are detected in gas-ionization chambers embedded in the steel flux-return yoke outsidethesolenoid,coveringaregionof|
η
|
<
2.
4.Events ofinterest are selected usinga two-tieredtrigger sys-tem [41].The firstlevel(L1),composed ofcustom hardware pro-cessors,uses informationfromthe calorimetersandmuon detec-torstoselecteventsatarateofaround100 kHz.Thesecondlevel, knownas thehigh-level trigger (HLT), consistsofa farm of pro-cessorsrunningaversionofthefulleventreconstructionsoftware optimizedforfastprocessing,andreducestheeventratetoaround 1 kHz beforedata storage.Eventsare selectedatthe triggerlevel bythepresenceofjetsofparticlesinthedetector.TheL1trigger algorithmsreconstructjetsfromenergydeposits inthe calorime-ters. At the HLT, physics objects (charged and neutral hadrons, electrons,muons,andphotons)arereconstructedusinga particle-flow(PF)algorithm [42].The anti-kT algorithm [43,44] isusedto
clustertheseobjectswithadistanceparameterof0.8(AK8jets)or 0.4(AK4jets).
Bulkgravitonandradionsignaleventsaresimulatedatleading orderusing the MadGraph5_amc@nlo 2.3.3 [45] eventgenerator formassesintherange750–3000 GeV andwidthsof1 MeV (nar-row width approximation). The NNPDF3.0 leading order parton distribution functions (PDFs) [46], taken from the LHAPDF6 PDF set [47–50], withthefour-flavour scheme,isused.Theshowering andhadronizationofpartonsissimulatedwith pythia 8.212 [51]. The herwig++ 2.7.1 [52] generatorisusedforanalternativemodel toevaluatethesystematicuncertaintyassociatedwiththeparton showerandhadronization.The tuneCUETP8M1-NNPDF2.3LO [53] is used for pythia 8, while the EE5C tune [54] is used for her-wig++.
Thebackgroundismodelledentirelyfromdata.However, sim-ulatedbackground samplesare used to develop and validate the background estimation techniques, prior to being applied to the data.These are multijetevents, generated atleading order using MadGraph5_amc@nlo,andtt
+
jets, generatedatnext-to-leading orderusing powheg 2.0 [55–57].Boththesebackgroundsare inter-facedto pythia 8forsimulatingthepartonshowerand hadroniza-tion.Studiesusingsimulations establishedthat themultijetcom-ponentismorethan99%ofthebackground,withtherestmostly fromtt
+
jets production.Allgeneratedsampleswereprocessedthrougha Geant4-based [58,59] simulationoftheCMSdetector.Multiplepp collisionsmay occur in the same oradjacent LHC bunch crossings(pileup) and contribute totheoveralleventactivityinthedetector.Thiseffect isincludedinthesimulations,andthesamplesarereweightedto matchthenumberofpp interactionsobservedinthedata, assum-ingatotalinelasticpp collisioncrosssectionof69.2 mb [60].
3. Eventselection
Events were collected using several HLT algorithms. The first required the scalar pT sumof all AK4 jetsin the event (HT) to
be greaterthan800or900 GeV,depending ontheLHCbeam in-stantaneous luminosity. A second trigger criterion required HT
≥
650 GeV, with a pair of AK4 jets with invariant mass above 900 GeV and a pseudorapidityseparation
|
η
|
<
1.
5.A third set oftriggers selectedeventswiththescalar pT sumofallAK8jetsgreaterthan650or700 GeV andthepresenceofan AK8jetwith a “trimmedmass”above50 GeV,i.e.thejet massafterremoving remnants ofsoftradiationusingjet trimmingtechnique [61].The fourthtriggering condition wasbased onthe presenceofan AK8 jet with pT
>
360 GeV and trimmed mass greater than 30 GeV.Thelast triggerselection acceptedeventscontainingtwoAK8jets having pT
>
280 and200 GeV with atleast onehaving trimmedmassgreaterthan30 GeV,togetherwithanAK4jetpassingaloose b-taggingcriterion.
The pp interaction vertex with the highest
p2T of the
as-sociated clusters of physics objects is considered to be the one associatedwiththehardscatteringinteraction,theprimaryvertex. Thephysicsobjectsarethejets,clusteredusingthejetfinding al-gorithm [43,44] withthe tracksassigned tothe vertexasinputs, and the associated missing transverse momentum, taken as the negative vectorsumofthe pT ofthosejets. Theotherinteraction
verticesaredesignatedaspileupvertices.
Tomitigatetheeffectofpileup,particles areassignedweights usingthepileupper particleidentification(PUPPI)algorithm [62], withtheweightcorrespondingtoitsestimatedprobabilityto orig-inatefromapileupinteraction.Chargedparticlesfrompileup ver-ticesreceiveaweightofzerowhilethosefromtheprimaryvertex receiveaweightofone.Neutralparticlesareassignedaweight be-tweenzeroandone,withhighervaluesforthoselikelytooriginate fromtheprimaryvertex.ParticlesarethenclusteredintoAK8jets. Thevectorsumoftheweightedmomentaofallparticlesclustered inthejetistakentobethejetmomentum.Toaccount for detec-tor response nonlinearity,jet energy correctionsare applied as a functionofjet
η
andpT[63,64].Ineachevent,theleadingandthesubleadingpTAK8jets,j1 andj2,respectively,arerequiredtohave
pT
>
300 GeV and|
η
|
<
2.
4.Theremovalofeventscontainingisolatedleptons(electronsor muons) with pT
>
20 GeV and|
η
|
<
2.
4 helps suppresstt+
jetsanddibosonbackgrounds.The isolationvariableis definedasthe scalar pT sum of the charged and neutral hadrons, and photons
in a cone of
R
=
0.
3 for an electron orR
=
0.
4 fora muon, whereR
≡
(
η
)
2+ (φ)
2,φ
beingtheazimuthal angleinra-dians.Theenergyfrompileupdepositedintheisolationcone,and the pT oftheleptonitself,is subtracted [65,66].The isolation
re-quirementremovesjetsmisidentifiedasleptons.Additionalquality criteria are applied to improve the purity of the isolated lepton samples.Electronspassingcombinedisolation andquality criteria correspondingtoaselectionefficiencyof90%(70%)aredesignated “loose” (“medium”)electrons.Forthe “loose”(“medium”)muons, the totalassociated efficiencyis 100% (95%).The probability ofa jet to be misidentified as an electron ora muon is in the range
0.5–2%,dependingonpT,
η
,andthechoiceofmediumorloosese-lectioncriteria.Eventscontainingonemediumlepton,ortwoloose leptonsofthesameflavour,butofoppositecharge,arerejected.
The H
→
bb systemis reconstructed as a single high-pT AK8jet, where the decay products have merged within the jet, and thetwohighest pT jetsintheeventare assumedtobe theHiggs
boson candidates. The jet is groomed [67] to remove soft and wide-angle radiation using the soft-drop algorithm [68,69], with the soft radiationfraction parameter z set to 0
.
1 andthe angu-lar exponent parameterβ
set to 0. The groomed jet is used to compute thesoft-drop jet mass,which peaksatthe Higgsboson massforsignaleventsandreducesthemassofbackground quark-andgluon-initiatedjets. Dedicated mass corrections [70], derived fromsimulationanddatainaregionenrichedwithtt eventswith merged W→
qq decays, are applied to the jet mass inorder to remove residual dependenceon thejet pT,andto matchthe jetmassscaleandresolutionobservedindata.
Thesoft-dropmassesofj1 andj2arerequiredtobewithinthe
range105–135 GeV, withan efficiency ofabout 60–70%,for jets arisingfromasignal ofmassmX intherange750–3000 GeV.The
“N-subjettiness”algorithmisusedtodeterminetheconsistencyof the jet with two subjets froma two-pronged H
→
bb decay, by computing the inclusive jet shape variablesτ
1 andτ
2 [71]. Theratio
τ
21≡
τ
2/
τ
1 witha valuemuch lessthan oneindicates ajetwith two subjets. The selection
τ
21<
0.
55 is used, having a jetpT-dependentefficiencyof 50–70%,beforeapplying thesoft-drop
massrequirement.
For background events, j1 and j2 are often well separated in
η
,especiallyathighinvariant mass(mjj)ofj1 andj2.Incontrast,signaleventsthatcontain aheavyresonancedecayingtotwo en-ergetic H jets are characterized bya small separationofthe two jetsin
η
. Events are thereforerequired to havea pseudorapidity separation|
η
(
j1,
j2)
|
<
1.
3.Theefficiencyofthetriggercombinationismeasuredina sam-ple of multijet events, collected with a control trigger requiring a single AK4 jet with pT
>
260 GeV, and with the leading andthe subleading pT AK8 jets, j1 and j2, respectively, passing the
above selectionson pT,
η
,andthesoft-drop mass.The efficiencyisgreater than99% formjj
≥
1100 GeV,andintherange40–99%for750
<
mjj<
1100 GeV.The triggerefficiencyofthe simulatedsamplesiscorrectedusingascalefactortomatchtheobserved ef-ficiencyin the data. This scale factor isapplied asa function of
|
η
(
j1,
j2)
|
becauseithasamilddependenceonthisvariable.Themainmethodtosuppressthemultijetbackgroundisb tag-ging: sincea true H
→
bb jet contains two b hadrons, the H jet candidatesareidentifiedusingthededicated“double-b tagger” al-gorithm [72]. The double-b tagger exploits the presence of two hadronized b quarks inside the H jet, anduses variables related tob hadronlifetimeandmass todistinguishbetweenH jets and thebackgroundfrommultijetproduction;italsoexploitsthefact thattheb hadronflightdirectionsarestronglycorrelatedwiththe axesusedtocalculatetheN-subjettinessobservables.Thedouble-b tagger is a multivariate discriminator with output between−
1 and 1, with a higher value indicating a greater probability for the jet to contain a bb pair. The double-b tagger discriminator thresholds of 0.3 and 0.8 correspond to H jet tagging efficien-ciesof 80and 30%and are referred toas “loose”(L) and“tight” (T)requirements, respectively. Events musthave the two leading pT AK8jetssatisfyingtheloosedouble-b taggerrequirement.Thedata-to-simulationscale factor forthe double-b tagger efficiency ismeasured inan eventsample enriched in bb pairsfromgluon splitting [72],andappliedtothesignalstoobtainthecorrect sig-nalyields.
The main variable used in the search for a HH resonance is the “reduced dijet invariant mass” mjj,red
≡
mjj− (
mj1−
mH)
−
Fig. 1. The soft-dropmass(upper),theN-subjettinessτ21(middle),andthedouble-b
taggerdiscriminator (lower) distributions ofthe selectedAK8 jets.The multijet
backgroundcomponentsfor thedifferentjet flavoursareshown:jetshavingtwo
Bhadrons(bb)orasingleone(b),jetshavingacharmhadron(c),andallother
jets(light).Alsoplottedarethedistributionsforthesimulatedbulkgravitonand
radionsignalsofmasses1400and2500 GeV.Thenumberofsignalandbackground
eventscorrespondtoanintegratedluminosityof35.9 fb−1.Asignalcrosssection
σ(pp→X→HH→bbbb)=20 pb isassumedforallthe masshypotheses.The
eventsarerequiredtohavepassedthetriggerselection,leptonrejection,theAK8
jet kinematicselectionspT>300 GeV and|η|<2.4,and |η(j1,j2)|<1.3.The
reduceddijetinvariantmassmjj,redisrequiredtobegreaterthan750 GeV.The
N-subjettinessrequirementofτ21<0.55 isappliedtotheupperandlowerfigures.
Thesoft-dropmassesofthetwojetsarebetween105–135 GeV forthemiddleand
lowerfigures.
(
mj2−
mH)
, where mj1 and mj2 are the soft-drop masses of theleading and subleading H-tagged jets in the event, and mH
=
125
.
09 GeV [73,74] is theHiggs bosonmass.The quantity mjj,redis usedratherthanmjj sinceby subtractingthe soft-dropmasses
of thetwo H-tagged jetsandaddingback the exactHiggs boson massmH,fluctuationsinmj1 andmj2 duetothejet mass
resolu-Fig. 2. The jetseparation|η(j1,j2)|(left)andthereduceddijetinvariantmassmjj,red(right)distributions.Themultijetbackgroundcomponentsforthedifferentjetflavours
areshown:eventscontainingatleastonejetwithtwoBhadrons(bb)orasingleone(b),eventscontainingajethavingacharmhadron(c),andallotherevents(light).Also
plottedarethedistributionsforthesimulatedbulkgravitonandradionsignalsofmasses1400and2500 GeV.Thenumbersofsignalandbackgroundeventscorrespondto
anintegratedluminosityof35.9 fb−1.Thesignalcrosssectionσ(pp→X→HH→bbbb)isassumedtobe20 pb forallthemasshypotheses.Theeventsarerequiredtohave
passedtheonlineselection,leptonrejection,theAK8jetkinematicselectionspT>300 GeV,|η|<2.4.Thesoft-dropmassesofthetwojetsarebetween105and135 GeV,
andtheN-subjettinessrequirementofτ21<0.55 andmjj,red>750 GeV areapplied.Themjj,reddistributions(right)require|η(j1,j2)|<1.3.
tionarecorrected,leadingto8–10%improvementinthedijetmass resolution.Arequirementofmjj,red
>
750 GeV isappliedforselect-ingsignal-likeevents.
Thesoft-dropmass,
τ
21,anddouble-b taggerdiscriminatordis-tributionsofthetwo leading pT jetsare showninFig.1 for
sim-ulatedevents after passing the onlineselection, lepton rejection, kinematicselection, andthe requirementmjj,red
>
750 GeV. Also,the N-subjettiness requirement of
τ
21<
0.
55 is applied for thesoft-drop mass and the double-b tagger distributions, while the soft-drop mass requirement is applied to the
τ
21, and double-btaggerdiscriminator distributions. Sincesome ofthe triggers im-poseatrimmedjetmassrequirement,thisaffectstheshapeofthe offlinesoft-dropjetmass,resultinginasteepriseabove
∼
20 GeV. The distributions of the|
η
(
j1,
j2)
|
and the mjj,red variables areshowninFig.2.Inthesefigures,themultijetbackgroundisshown fordifferentjet flavourcategories:jetshavingtwoBhadrons(bb) orasingle one (b),jetshavingacharm hadron(c),andall other jets(light).
Thedouble-b taggerdiscriminator ofthetwo leadingAK8jets mustexceed the loosethreshold. In addition,if both discrimina-torvaluesalsoexceedthetightthreshold,eventsareclassifiedin the“TT”category. Otherwise,they are classifiedin the“LL” cate-gory,which contains events withboth j1 andj2 failingthe tight
thresholdaswell aseventswitheitherj1 orj2 passingthe tight
thresholdwhiletheotherpassestheloosethresholdonly. The backgrounds are estimated separately for each category, andthecombinationofthelikelihoodsfortheTTandLLcategories givestheoptimalsignalsensitivityoverawiderangeofresonance masses,accordingtostudiesperformedusingsimulatedsignaland multijetsamples.TheTTcategoryhasagoodbackgroundrejection formX up to 2000 GeV. At higher resonance masses, where the
backgroundissmall, theLLcategory providesbetter signal sensi-tivity. The full event selection efficiencies forbulk gravitons and radionsofdifferentassumedmassesare showninFig. 3. The ra-dion has a smaller efficiency than the bulk graviton because its
|
η
(
j1,
j2)
|
distributionis considerablywider than that ofa bulkgravitonofthesamemass,asshowninFig.2(left).
4. Signalandbackgroundmodelling
Themethodchosen forthebackgroundmodellingdependson whethertheresonancemassmXisbeloworabove1200 GeV,since
atlow masses thebackground doesnot fall smoothly as a
func-Fig. 3. The signalselectionefficienciesforthebulkgravitonandradionmodelsfor
differentmasshypothesesoftheresonances,shownfortheLLandtheTTsignal
eventcategories.Owingtothelargesamplesizesofthesimulatedevents,the
sta-tisticaluncertaintiesaresmall.
tion of mjj,red, because of the trigger requirements, while above
1200 GeV it does. The background estimation relies on a set of control regions to predict the total background shape and nor-malization in the signal regions. The entire range of the mjj,red
distributionabove750 GeV isusedfortheprediction.
For signals with mX
≥
1200 GeV, the underlying backgrounddistribution falls monotonically with mjj,red, thus allowing the
background shape to be modelled by a smooth function, above which alocalized signal issearched for.This smooth background modellinghelpstoreduceuncertaintiesinthebackground estima-tionfromlocalstatisticalfluctuationsinmjj,red,therebyimproving
the signal search sensitivity. The parameters of the function and itstotalnormalizationareconstrainedbyasimultaneousfitofthe signal andbackgroundmodelsto thedatain thecontrol andthe signalregions.FormX
≥
1200 GeV,themjj,reddistributionsforthesignalaremodelledusingthesumofaGaussianandaCrystalBall function [75],asshowninFig.4foronesignalcategory.Thesame modellingisusedfortheothersignalcategories,withdifferent pa-rametersfortheGaussianandtheCrystalBallfunctions.
Thesignalandcontrolregionsaredefinedbytwovariables re-latedtotheleading pTjetj1:(i)itssoft-dropmassmj1 and(ii)the
Fig. 4. The bulkgravitonsignalmjj,reddistributionfortheLLcategory,modelled
us-ingthesumofGaussianandCrystalBallfunctions.Thismodellingisperformedfor
signalsintherange1100<mjj,red<3000 GeV,wherethebackgrounddistribution
fallssmoothly.Noeventsareobservedwithmjj,redgreaterthan3000 GeV.
Table 1
Definitionofthesignal,the antitag,andthesidebandregionsusedforthe
back-groundestimation.Theregionsaredefinedintermsofthesoft-dropmassesofthe
leadingpT(j1)andthesubleadingpT(j2)AK8jets,andtheirdouble-btagger
dis-criminatorvalues.
Event category Jet Soft-drop mass (GeV) Double-b tagger discriminator
Signal (LL) j1 105–135 >0.3, but j2 not both>0.8 Signal (TT) j1 >0.8 j2 Antitag (LL) j1 105–135 <0.3 j2 0.3–0.8 Antitag (TT) j1 <0.3 j2 >0.8 Sideband j1 <105 or>135 >0.3, but
(LL, passing) j2 105–135 not both>0.8
Sideband j1 <105 or>135 >0.8 (TT, passing) j2 105–135 Sideband j1 <105 or>135 <0.3 (LL, failing) j2 105–135 0.3–0.8 Sideband j1 <105 or>135 <0.3 (TT, failing) j2 105–135 >0.8
is estimatedin bins of the mjj,red distribution. Considering these
twovariables,severalregionsaredefined.
The pre-tag region includes events fulfilling the selection re-quirements inSections 2–3 apart fromthose on mj1 andon the
j1 double-b tagger discriminator. The signal region is the subset
of pre-tag events where mj1 is inside the H jet mass window
of 105–135 GeV, and with the j1 double-b tagger discriminator
greaterthan0.3or0.8,fortheLLandTTregions,respectively.The antitag regionsrequirethej1 double-b taggerdiscriminatortobe
lessthan0.3, withtherequirementonj2 beingthesameasthat
for the corresponding LL or TT signal regions. The mj1 sideband
regionconsistsofeventsinthepre-tagregion,wheremj1 lies
out-side theH jetmass window.Based onwhetherj1 passesorfails
thedouble-b tagger discriminator threshold,the sidebandregion is divided into either “passing”or “failing”, respectively. The an-titagregionsare dominatedby themultijetbackground,andhave identicalkinematicdistributionstothemultijetbackgroundevents in the signal region, according to studies using simulations. The definitionsofthesignal,theantitag,andthesidebandregionsare giveninTable1.
Intheabsence ofacorrelation betweenmj1 andthe double-b
tagger discriminator values, one could measure in the mj1
side-band the ratio of the number of events passing and failing the
Fig. 5. The pass-failratioRp/foftheleadingpTjetfortheLL(upper)andTT(lower)
signalregioncategoriesasafunctionofthedifferencebetweenthesoft-dropmass
oftheleadingjetandtheHiggsbosonmass,mj1- mH.Themeasuredratioin
differ-entbinsofmj1−mHisusedinthefit(redsolidline),exceptintheregionaround
mj1−mH=0,whichcorrespondstothesignalregion(bluetriangularmarkers).The
fittedfunctionisinterpolatedtoobtainRp/finthesignalregion.Thehorizontalbars
onthedatapointsindicatethebinwidths.(Forinterpretationofthecoloursinthe
figure(s),thereaderisreferredtothewebversionofthisarticle.)
double-b tagger selection, Rp/f
≡
Npass/
Nfail,i.e.the“pass-failra-tio”.Theyieldintheantitagregion(ineachmjj,redbin)couldthen
bescaledby Rp/f toobtainanestimateofthebackground
normal-ization inthesignal region.However, thereis asmallcorrelation betweenthedouble-b taggerdiscriminatorandmj1,whichistaken
intoaccountbymeasuring thepass-failratio Rp/f asafunctionof
mj1.Thesignalfractionwasfoundtobelessthan10−
3inthe
side-bandregionsusedtoevaluate Rp/f,assumingasignalcrosssection
σ
(
pp→
X→
HH→
bbbb)
of10 fb.The Rp/ffortheLLsignalregionismeasuredusingratioofthe
numberofeventsinthe“LL,passing”and“LL,failing”sideband re-gions, asdefined in Table 1.Likewise, the Rp/f for the TT signal
regionusestheratioofthenumberofeventsinthe“TT,passing” tothe“TT,failing”sidebandregions.ThevariationofRp/fasa
func-tionofmj1 ineachmj1sidebandisfittedwithaquadraticfunction.
Thefittothepass-failratioisinterpolatedtotheregionwheremj1
lieswithintheH jetmasswindowof105–135 GeV.Analternative fitusingathirdorderpolynomialwas foundtogivethesame in-terpolatedvalueofRp/fintheHiggsjetmasswindow.Everyevent
in theantitagregionisscaled by thepass-failratio evaluatedfor themj1 ofthat event,to obtainthebackground predictioninthe
signalregion.
Fig.5showsthequadraticfitinthemj1 sidebandsofthe
pass-fail ratio Rp/f as a function ofmj1, as obtained in the data. The
backgroundpredictionusingthismethod,alongwiththenumber ofobservedeventsinthesignalregionisshowninFig.6.
Fig. 6. The reducedmass distributionsmjj,red for theLL(upper)and TT(lower)
signalregioncategories.Thepointswithbarsshowthedata,thehistogramwith
shaded band shows the estimated background and associated uncertainty. The
mjj,redspectrumforthebackgroundisobtainedbyweightingthemjj,red spectrum
intheantitagregionbytheratioRp/fofFig.5.Thesignalpredictionsforabulk
gravitonofmass1000 GeV,areoverlaidforcomparison,assumingacrosssection
σ(pp→X→HH→bbbb)of10 fb.Thelastbinsofthedistributionscontainall
eventswithmjj,red>3000 GeV.Thedifferencesbetweenthedataandthepredicted
background,dividedbythedatastatisticaluncertainty(dataunc.)asgivenbythe
Garwoodinterval [76],areshowninthelowerpanels.
Forresonancemassesof1200 GeV andabove,thebackground estimation is improved by simultaneously fitting a parametric model for the background and signal to the data in the signal andtheantitagregions formjj,red
≥
1100 GeV.Inthefit,theratioRp/f obtainedfromthesidebandsisusedtoconstrain therelative
numberofbackground eventsin thetwo regions. Toaccount for possible Rp/fdependenceonmjj,redathighmjj,red values,the Rp/f
obtainedfromthefitsshowninFig.5isalsoparametrizedasa lin-earfunctionofmjj,red.Thesignalnormalizationisunconstrainedin
thefit,while theuncertaintiesintheparameters ofthe functions used to model the background and Rp/f are treated asnuisance
parameters. For the background modelling, a choice among an exponentialfunction Ne−a mjj,red,a “levelled exponential” function
Ne−a mjj,red/(1+a b mjj,red),anda“quadraticlevelled exponential
func-tion”Ne[−a mjj,red/(1+a b mjj,red)]−[−c m2jj,red/(1+b c m 2
jj,red)] wasmade,using
aFisher F-test [77]. Ataconfidencelevel of95%,thelevelled ex-ponentialfunctionwasfoundtobeoptimal. Sincethebackground shapes in the signal regions, as predicted using the antitag
re-gions,werefoundtobesimilar(Fig.6),theparametricbackground modellingwas tested usingthe antitagregion inthe databefore applyingittothesignalregion.
The simultaneous fits to the antitag and the signal regions are shown in Figs. 7 and 8, respectively, using the background modelonly.Thesearelabelledas“post-fit”curveswiththesignal region background yields constrained to be Rp/f times the
back-ground yields from the antitag regions. The “pre-fit” curves, ob-tained by fitting the antitagandthe signal regions separately to thebackground-onlymodel,withthebackgroundeventyields un-constrained,arealsoshownforcomparison.Inthepost-fitresults, the Rp/fdependenceonmjj,redwasfoundtobenegligible.
Amongthefourfittedregions,correspondingtotheantitagand thesignalregionsintheLLandTTcategories, theeventswiththe highestvalueofmjj,redoccur intheantitagregionoftheLL
cate-gory,ataroundmjj,red
=
2850 GeV. Asthe parametricbackgroundmodel is only reliable within the range of observed events, the likelihoodis onlyevaluated uptomjj,red
=
3000 GeV.ThisresultsinatruncationofthesignaldistributionforresonanceshavingmX
of2800 GeV andabove,withsignalefficiencylossesincreasingto 30%formX
=
3000 GeV,asshowninFig.4.Closuretestsofthebackgroundestimationmethodswere per-formed using simulated multijet samples withsignals of various crosssections.Thetestsindicatedagoodconsistencybetweenthe expectedandtheassumedsignalstrengths.
5. Systematicuncertainties
The following sources ofsystematicuncertainty affectthe ex-pectedsignalyields. Noneoftheseleadtoa significantchangein thesignalshape.
Trigger response modelling uncertainties are particularly im-portant formjj,red
<
1200 GeV,where thetriggerefficiency dropsbelow99%.Ascalefactorisappliedtocorrectforthedifferencein efficiencyobservedbetweenthe dataandsimulation.Thecontrol triggerusedtomeasurethisscalefactorrequiresasingle AK4jet withpT
>
260 GeV,andittooissubjecttosomeinefficiencywhenmjj,rediscloseto750 GeV,becauseofadifferencebetweenthejet
energyscaleusedinthetriggerandthatusedintheoffline recon-struction.Thisinefficiencyismeasuredusingsimulations,andhas anassociatedtotaluncertaintyofbetween1%and15%.
Thejetenergyscaleandresolutionuncertaintyisabout1% [63,
64].Thejetmassscaleandresolution,and
τ
21selectionefficiencydata-to-simulation scale factor are measured using a sample of mergedW jetsinsemileptonictt events.Thecorresponding uncer-taintiesareextrapolatedtoahigher pT rangethanthatassociated
withtt events,usingsimulations.Acorrectionfactorisappliedto account forthe difference in the jet shower profile of W
→
qq and H→
bb decays, by comparing the ratio of the efficiency of H and W jets using the pythia 8 and herwig++ shower gener-ators. The jet mass scale and resolution has a 2% effect on the signal yields becauseof a changeinthe meanof theH jet mass distribution. Theτ
21 selection efficiency uncertainty amounts toa
+
30/
−
26% change in the signal yields. The uncertainty in the H tagging correction factor is in the range 7–20% depending on theresonancemassmX.The double-b taggerefficiencyscalefac-toruncertainty isabout2–5%,depending onthe double-b tagger requirementthreshold andjet pT, andis propagated to the total
uncertaintyinthesignalyield.
Theimpact ofthePDFsandthetheoretical scaleuncertainties areestimatedtobe0.1–2%,usingthePDF4LHCprocedure [50],and affecttheproductofthesignalacceptanceandtheefficiency.The PDF and scale uncertainties have negligibleimpact on the signal
Fig. 7. The reducedmassmjj,reddistributionsintheantitagregionfortheLL(left)andTT(right)categories.Theblackmarkersarethedatawhilethecurvesshowthepre-fit
andpost-fitbackgroundshapes.Thedifferencesbetweenthedataandthepre-fitbackgrounddistribution,dividedbythestatisticaluncertaintyinthedata(dataunc.)as
givenbytheGarwoodinterval [76],areshowninthelowerpanels.
Fig. 8. The reducedmassmjj,red distributionsinthesignalregionfortheLL(left)andtheTT(right)categories.Theblackmarkersarethedatawhilethecurvesshow
thepre-fitandpost-fitbackgroundshapes.Thecontributionofbulkgravitonsofmasses1600and2500 GeV inthe signalregionareshownassumingacross section
σ(pp→X→HH→bbbb)of10 fb.Thedifferencesbetweenthedataandthepre-fitbackgrounddistribution,dividedbythestatisticaluncertaintyinthedata(dataunc.)as
givenbytheGarwoodinterval [76],areshowninthelowerpanels.
withthepileupmodelling(2%)andtheintegratedluminosity de-termination(2.5%) [78],areappliedtothesignalyield.
Themainsource ofuncertaintyforthe multijetbackgroundin theregion mjj,red
<
1200 GeV is duetothe statisticaluncertaintyin the fit to the Rp/f ratio performed in the H jet mass
side-bands. This uncertainty, amounting to 2.6% for the LL, and 6.8% for the TT signal categories, is fully correlated between all bins ofaparticularestimate.Furthermore,thestatisticaluncertaintyin the antitag region is propagated to the signal region when the estimate is made. This is uncorrelated from bin to bin,and the Barlow–Beeston Lite [79,80] method is used to treat the bin-by-bin statistical uncertainty in the data. These uncertainties affect both the shape of the background in the mjj,red distribution and
thetotalbackgroundyield.
For mjj,red
≥
1200 GeV, the overall background uncertainty isobtainedfrom the uncertainty in the four simultaneous fits per-formed for the antitag andthe signal regions in the LL andthe
Table 2
Summaryofsystematicuncertaintiesinthesignalandbackgroundyields.
Source Uncertainty (%)
Signal yield
Trigger efficiency 1–15
H jet energy scale and resolution 1
H jet mass scale and resolution 2
H jetτ21selection +30/−26
H-tagging correction factor 7–20
Double-b tagger discriminator 2–5
Pileup modelling 2
PDF and scales 0.1–2
Luminosity 2.5
Background yield
Rp/ffit 2.6 (LL category) 6.8 (TT category)
TT categories. The dependenceof Rp/f onmjj,red isaccountedfor,
althoughthiswasfoundtobenegligible.
Fig. 9. The limitsforthespin-0radion(upper)andthespin-2bulkgraviton(lower)
models.Theresultfor mX<1200 GeV usesthebackgroundpredictedusingthe
controlregions,whileformX≥1200 GeV thebackgroundisderivedfroma
com-binedsignalandbackgroundfittothedatainthecontrolandthesignalregions.
Thepredictedtheoreticalcrosssectionsforanarrowradionorabulkgravitonare
alsoshown.
6. Results
AsshowninFigs.6and
8
,forthesignalregions,theobservedmjj,red distribution is consistent with the estimated background.
Theresultsare interpreted intermsof upperlimitsonthe prod-uct of the production cross sections andthe branching fractions
σ
(
pp→
X)B(
X→
HH→
bbbb)
forradionandbulkgravitonof var-iousmasshypotheses.Theasymptoticapproximationofthe mod-ifiedfrequentist approachforconfidence levels,takingtheprofile likelihoodasateststatistic [81–83],isused.Thelimitsareshown inFig.9fora narrowwidth radionorabulk graviton. Theseare comparedwiththe theoretical valuesofthe productof thecross sectionsandbranchingfractionsforthe benchmarksκ
/
MPl=
0.
5and
R
=
3 TeV, where the narrow width approximation for asignal is valid, and where the corresponding HH decay branch-ing fractions in the mass range of interest are 10 and 23%, for thegraviton andtheradion,respectively [13].Theexpectedlimits onthebulkgraviton aremorestringentthanthoseontheradion becauseof thehigher efficiencyofthe
|
η
(
j1,
j2)
|
separation re-quirementfortheformersignal.The upperlimits on the productionof the cross sectionsand branchingfractionliesin therange126–1.4 fb fora narrow reso-nanceX ofmass 750
<
mX<
3000 GeV.AssumingR
=
3 TeV, abulkradionwithamassbetween970and1400 GeV isexcludedat 95%confidencelevel,exceptina smallregion closeto1200 GeV, wheretheobservedlimit is11.4 pb,thetheoreticalprediction be-ing11.2 pb.
7. Summary
A search for a narrow massive resonance decaying to two standardmodelHiggsbosonsisperformedusingtheLHCproton– proton collision data collected at a centre-of-mass energy of 13 TeV by theCMS detector,and corresponding to an integrated luminosityof35.9 fb−1.Thefinalstateconsistsofeventswithboth Higgs bosons decaying to b quark–antiquark pairs, which were identifiedusingjetsubstructureandb-taggingtechniquesapplied to large-area jets. The data are found to be consistent withthe standard model expectations, dominated by multijet events. Up-perlimitsaresetontheproductsoftheresonantproductioncross sections ofa Kaluza–Klein bulk graviton anda Randall–Sundrum radion, and their branching fraction to HH
→
bbbb. The limits range from 126 to 1.4 fb at 95% confidence level for bulk gravi-tonsandradionsin themassrange 750–3000 GeV.Forthe mass scaleR
=
3 TeV, a radionof mass between970 and1400 GeV(except in a small region close to 1200 GeV) is excluded. These limitson the bulk graviton andthe radiondecaying to a pair of standardmodelHiggsbosonsarethemoststringenttodate,over themassrangeexplored.
Acknowledgements
WecongratulateourcolleaguesintheCERNaccelerator depart-ments for the excellent performance of the LHC and thank the technicalandadministrative staffsatCERN andatother CMS in-stitutes for their contributions to the success of the CMS effort. Inaddition,wegratefullyacknowledgethecomputingcentresand personneloftheWorldwideLHCComputingGridfordeliveringso effectivelythe computinginfrastructureessential to ouranalyses. Finally, we acknowledge the enduring support for the construc-tionandoperation oftheLHC andtheCMSdetectorprovidedby thefollowingfundingagencies:BMWFWandFWF(Austria);FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MOST, and NSFC (China); COLCIEN-CIAS(Colombia);MSESandCSF(Croatia);RPF(Cyprus);SENESCYT (Ecuador); MoER, ERC IUT, and ERDF (Estonia); Academy of Fin-land,MEC,andHIP(Finland);CEAandCNRS/IN2P3(France);BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NIH (Hun-gary);DAEandDST(India);IPM(Iran);SFI(Ireland);INFN(Italy); MSIPandNRF(RepublicofKorea);LAS (Lithuania);MOEandUM (Malaysia); BUAP, CINVESTAV,CONACYT, LNS, SEP, andUASLP-FAI (Mexico); MBIE (New Zealand); PAEC (Pakistan); MSHE and NSC (Poland);FCT(Portugal);JINR(Dubna);MON,ROSATOM,RAS,RFBR andRAEP(Russia);MESTD (Serbia);SEIDI,CPAN, PCTIandFEDER (Spain);SwissFundingAgencies(Switzerland);MST(Taipei); ThEP-Center, IPST, STAR, and NSTDA (Thailand); TUBITAK and TAEK (Turkey);NASUandSFFR(Ukraine); STFC(United Kingdom);DOE andNSF(USA).
Individuals have received support from the Marie-Curie pro-gramme and the European Research Council and Horizon 2020 Grant,contract No. 675440 (EuropeanUnion);the Leventis Foun-dation;the A. P. Sloan Foundation; the Alexandervon Humboldt Foundation; the Belgian Federal Science Policy Office; the Fonds pourlaFormationàlaRecherchedansl’Industrieetdans l’Agricul-ture (FRIA-Belgium); the Agentschapvoor Innovatie door Weten-schap en Technologie (IWT-Belgium); the Ministry of Education, YouthandSports(MEYS)oftheCzechRepublic;theCouncilof Sci-enceandIndustrialResearch,India;theHOMINGPLUSprogramme of the Foundation for Polish Science, cofinanced from European Union,Regional DevelopmentFund, theMobilityPlusprogramme oftheMinistryofScienceandHigherEducation,theNational Sci-ence Center (Poland), contracts Harmonia 2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543, 2014/15/B/ST2/03998, and 2015/19/
B/ST2/02861,Sonata-bis2012/07/E/ST2/01406; the National Prior-itiesResearchProgrambyQatar NationalResearchFund;the Pro-grama Severo Ochoa del Principado de Asturias; the Thalis and Aristeia programmes cofinanced by EU-ESF andthe Greek NSRF; theRachadapisekSompotFundforPostdoctoralFellowship, Chula-longkornUniversityandtheChulalongkornAcademicintoIts 2nd CenturyProjectAdvancement Project(Thailand);theWelch Foun-dation,contractC-1845;andtheWestonHavensFoundation(USA).
References
[1] ATLASCollaboration,Observationofanewparticleinthesearchforthe
Stan-dardModelHiggsbosonwiththeATLASdetectorattheLHC,Phys.Lett.B716
(2012)01,https://doi.org/10.1016/j.physletb.2012.08.020,arXiv:1207.7214.
[2] CMSCollaboration,Observationofanewboson atamassof125GeVwith
theCMSexperimentattheLHC,Phys.Lett.B716(2012)30,https://doi.org/10.
1016/j.physletb.2012.08.021,arXiv:1207.7235.
[3] CMSCollaboration,Observationofanewbosonwithmassnear125GeVin
ppcollisionsat√s=7 and8TeV,J.HighEnergyPhys.06(2013)081,https://
doi.org/10.1007/JHEP06(2013)081,arXiv:1303.4571.
[4] D. deFlorian,J.Mazzitelli,Higgsboson pair productionat
next-to-next-to-leadingorderinQCD,Phys.Rev.Lett.111(2013)201801,https://doi.org/10.
1103/PhysRevLett.111.201801,arXiv:1309.6594.
[5] L.Randall,R.Sundrum,Alargemasshierarchyfromasmallextradimension,
Phys. Rev.Lett. 83(1999) 3370,https://doi.org/10.1103/PhysRevLett.83.3370,
arXiv:hep-ph/9905221.
[6] W.D.Goldberger,M.B.Wise,Modulusstabilizationwithbulkfields,Phys.Rev.
Lett.83(1999)4922, https://doi.org/10.1103/PhysRevLett.83.4922,arXiv:hep
-ph/9907447.
[7] C.Csaki,M.Graesser,L.Randall,J.Terning,Cosmologyofbranemodelswith
radion stabilization,Phys. Rev.D62(2000)045015, https://doi.org/10.1103/
PhysRevD.62.045015,arXiv:hep-ph/9911406.
[8] C.Csaki,M.L.Graesser,G.D.Kribs,Radiondynamicsandelectroweakphysics,
Phys. Rev.D63 (2001) 065002,https://doi.org/10.1103/PhysRevD.63.065002,
arXiv:hep-th/0008151.
[9] H.Davoudiasl,J.L.Hewett,T.G.Rizzo,PhenomenologyoftheRandall–Sundrum
gaugehierarchymodel,Phys.Rev.Lett.84(2000)2080,https://doi.org/10.1103/
PhysRevLett.84.2080,arXiv:hep-ph/9909255.
[10] O.DeWolfe,D.Z.Freedman,S.S.Gubser,A.Karch,Modelingthefifth
dimen-sionwithscalarsandgravity,Phys.Rev.D62(2000)046008,https://doi.org/
10.1103/PhysRevD.62.046008,arXiv:hep-th/9909134.
[11] K.Agashe,H.Davoudiasl,G.Perez,A.Soni,WarpedgravitonsattheLHCand
beyond,Phys.Rev.D76(2007)036006,https://doi.org/10.1103/PhysRevD.76.
036006,arXiv:hep-ph/0701186.
[12] G.F.Giudice,R.Rattazzi,J.D.Wells,Graviscalarsfromhigherdimensional
met-ricsandcurvatureHiggsmixing,Nucl.Phys.B595(2001)250,https://doi.org/
10.1016/S0550-3213(00)00686-6,arXiv:hep-ph/0002178.
[13]A.Oliveira,Gravityparticlesfromwarpedextradimensions,areview.Parti– KKgraviton,arXiv:1404.0102,2014.
[14] G.C.Branco,P.M.Ferreira,L.Lavoura,M.N.Rebelo,M.Sher,J.P.Silva,Theory
andphenomenologyoftwo-Higgs-doubletmodels,Phys.Rep.516(2012)01,
https://doi.org/10.1016/j.physrep.2012.02.002,arXiv:1106.0034.
[15] A. Djouadi, The anatomy ofelectroweak symmetrybreaking. Tome II: the
Higgsbosonsinthe minimalsupersymmetricmodel,Phys. Rep.459(2008)
01,https://doi.org/10.1016/j.physrep.2007.10.005,arXiv:hep-ph/0503173.
[16] H.Georgi,M.Machacek,DoublychargedHiggsbosons,Nucl.Phys.B262(1985)
463,https://doi.org/10.1016/0550-3213(85)90325-6.
[17] ATLASCollaboration,SearchforHiggsbosonpairproductionintheγ γb¯b final
stateusing pp collisiondataat √s=8 TeV fromthe ATLASdetector,Phys.
Rev.Lett.114(2015)081802,https://doi.org/10.1103/PhysRevLett.114.081802,
arXiv:1406.5053.
[18] ATLASCollaboration,SearchforHiggsbosonpairproductionintheb¯bb¯b final
statefromppcollisionsat√s=8 TeVwiththeATLASdetector,Eur.Phys.J.
C75(2015)412,https://doi.org/10.1140/epjc/s10052-015-3628-x,arXiv:1506. 00285.
[19] ATLASCollaboration,SearchesforHiggsbosonpair productioninthehh→
bbτ τ,γ γW W∗,γ γbb,bbbb channelswiththeATLASdetector,Phys.Rev.D92
(2015)092004,https://doi.org/10.1103/PhysRevD.92.092004,arXiv:1509.04670.
[20] CMS Collaboration, Searches for heavy Higgs bosons intwo-Higgs-doublet
modelsandfort→ch decayusingmultileptonanddiphotonfinalstatesin
pp collisionsat8TeV,Phys.Rev.D90(2014)112013,https://doi.org/10.1103/ PhysRevD.90.112013,arXiv:1410.2751.
[21] CMSCollaboration,SearchforresonantpairproductionofHiggsbosons
decay-ingtotwobottomquark–antiquarkpairsinproton–protoncollisionsat8TeV,
Phys. Lett. B749 (2015) 560, https://doi.org/10.1016/j.physletb.2015.08.047,
arXiv:1503.04114.
[22] CMSCollaboration,SearchesforaheavyscalarbosonHdecayingtoapairof
125GeVHiggsbosonshhorforaheavypseudoscalarbosonAdecayingtoZh,
inthefinalstateswithh→τ τ,Phys.Lett.B755(2016)217,https://doi.org/
10.1016/j.physletb.2016.01.056,arXiv:1510.01181.
[23] CMSCollaboration,SearchfortwoHiggsbosonsinfinalstatescontainingtwo
photonsand twobottomquarksinproton–protoncollisionsat 8TeV,Phys.
Rev.D94(2016)052012,https://doi.org/10.1103/PhysRevD.94.052012, arXiv:
1603.06896.
[24] CMSCollaboration,SearchforheavyresonancesdecayingtotwoHiggsbosons
infinalstatescontainingfourbquarks,Eur.Phys.J.C76(2016)371,https://
doi.org/10.1140/epjc/s10052-016-4206-6,arXiv:1602.08762.
[25] ATLASCollaboration,SearchforpairproductionofHiggsbosonsintheb¯bbb¯
finalstate using proton–proton collisionsat √s=13 TeV with the ATLAS
detector,Phys.Rev.D94(2016)052002,https://doi.org/10.1103/PhysRevD.94.
052002,arXiv:1606.04782.
[26] ATLAS Collaboration,Search for high-massdiboson resonanceswith
boson-taggedjetsinproton–protoncollisionsat√s=8 TeVwiththeATLASdetector,
J.HighEnergyPhys.12(2015)055,https://doi.org/10.1007/JHEP12(2015)055,
arXiv:1506.00962.
[27] ATLASCollaboration,SearchforproductionofW W/W Z resonancesdecaying
toalepton,neutrinoandjetsinpp collisionsat√s=8 TeVwiththeATLAS
de-tector,Eur.Phys.J.C75(2015)209,https://doi.org/10.1140/epjc/s10052-015
-3425-6,arXiv:1503.04677, Erratum:https://doi.org/10.1140/epjc/s10052-015
-3593-4.
[28] ATLASCollaboration,Searchforresonantdibosonproductioninthe q¯q final
stateinpp collisionsat√s=8 TeVwiththeATLASdetector,Eur.Phys.J.C75
(2015)69,https://doi.org/10.1140/epjc/s10052-015-3261-8,arXiv:1409.6190.
[29] CMSCollaboration,Searchformassiveresonancesindijetsystemscontaining
jetstaggedasWorZ bosondecaysinpp collisionsat√s=8 TeV,J.High
EnergyPhys. 08(2014)173,https://doi.org/10.1007/JHEP08(2014)173,arXiv:
1405.1994.
[30] CMS Collaboration, Search for massive resonances decaying into pairs of
boostedbosonsinsemi-leptonicfinalstatesat√s=8 TeV,J.HighEnergyPhys.
08(2014)174,https://doi.org/10.1007/JHEP08(2014)174,arXiv:1405.3447.
[31] ATLASCollaboration,Searchfordibosonresonanceswithboson-taggedjetsin
pp collisionsat√s=13 TeV withtheATLASdetector,Phys.Lett.B777(2018) 91,https://doi.org/10.1016/j.physletb.2017.12.011,arXiv:1708.04445.
[32] ATLASCollaboration,Searchfor W W/W Z resonanceproductionin νqq
fi-nalstatesin pp collisionsat √s=13 TeV withthe ATLASdetector,J.High
EnergyPhys. 03(2017)042,https://doi.org/10.1007/JHEP03(2018)042,arXiv:
1710.07235.
[33] ATLASCollaboration,Searchesforheavy Z Z andZ W resonancesinthe qq
andννqq finalstatesinpp collisionsat√s=13 TeV withtheATLASdetector,
J.HighEnergyPhys.03(2018)009,https://doi.org/10.1007/JHEP03(2018)009,
arXiv:1708.09638,2017.
[34] CMSCollaboration,Combinationofsearchesforhearyresonancesdecayingto
WW,WZ,ZZ,andZHbosonpairsinproton–protoncollisionsat √s=8 and
13 TeV,Phys.Lett.B774(2017)533,https://doi.org/10.1016/j.physletb.2017.
09.083,arXiv:1705.09171.
[35]CMSCollaboration,SearchformassiveresonancesdecayingintoWW,WZ,ZZ, qW,andqZwithdijetfinalstatesat√s=13 TeV,arXiv:1708.05379,Phys.Rev. D(2018),submittedforpublication.
[36] D. deFlorian,etal.,Handbook ofLHCHiggsCross Sections:4.Deciphering
theNatureoftheHiggsSector,CERNReportCERN-2017-002-M,CERN,2016,
https://doi.org/10.23731/CYRM-2017-002,arXiv:1610.07922.
[37] J.M.Butterworth,A.R.Davison,M.Rubin,G.P.Salam,Jetsubstructureasanew
HiggssearchchannelattheLHC,Phys.Rev.Lett.100(2008)242001,https://
doi.org/10.1103/PhysRevLett.100.242001,arXiv:0802.2470.
[38] B.Cooper,N.Konstantinidis,L.Lambourne,D.Wardrope,Boostedhh→b¯bbb:¯
a newtopologyinsearchesforTeV-scaleresonancesattheLHC,Phys.Rev.D88
(2013)114005,https://doi.org/10.1103/PhysRevD.88.114005,arXiv:1307.0407.
[39] M.Gouzevitch,A.Oliveira, J. Rojo,R.Rosenfeld,G.P. Salam,V.Sanz,
Scale-invariant resonance tagging in multijet events and new physics in Higgs
pairproduction,J.HighEnergyPhys.07(2013)148,https://doi.org/10.1007/
JHEP07(2013)148,arXiv:1303.6636.
[40] CMSCollaboration,TheCMSexperimentattheCERNLHC,J.Instrum.3(2008)
S08004,https://doi.org/10.1088/1748-0221/3/08/S08004.
[41] CMS Collaboration, The CMStrigger system,J. Instrum. 12 (2017) P01020,
https://doi.org/10.1088/1748-0221/12/01/P01020,arXiv:1609.02366.
[42] CMS Collaboration,Particle-flowreconstruction andglobalevent description
withtheCMSdetector,J.Instrum.12(2017)P10003,https://doi.org/10.1088/
1748-0221/12/10/P10003,arXiv:1706.04965.
[43] M.Cacciari,G.P.Salam,G.Soyez,Theanti-ktjetclusteringalgorithm,J.High
EnergyPhys. 04(2008) 063,https://doi.org/10.1088/1126-6708/2008/04/063,
arXiv:0802.1189.
[44] M.Cacciari,G.P.Salam,G.Soyez,FastJetusermanual,Eur.Phys.J.C72(2012)
1896,https://doi.org/10.1140/epjc/s10052-012-1896-2,arXiv:1111.6097.
[45] J. Alwall, R. Frederix, S. Frixione, V. Hirschi, F. Maltoni, O. Mattelaer, H.S.
Shao, T. Stelzer, P. Torrielli,M. Zaro,The automated computation of
toparton showersimulations,J. HighEnergy Phys. 07(2014) 079,https:// doi.org/10.1007/JHEP07(2014)079,arXiv:1405.0301.
[46] R.D.Ball,etal.,NNPDFCollaboration,PartondistributionsfortheLHCRunII,
J.HighEnergyPhys.04(2015)040,https://doi.org/10.1007/JHEP04(2015)040,
arXiv:1410.8849.
[47] L.A.Harland-Lang,A.D.Martin,P.Motylinski,R.S.Thorne,Partondistributions
intheLHCera:MMHT2014PDFs,Eur.Phys.J.C75(2015)204,https://doi.
org/10.1140/epjc/s10052-015-3397-6,arXiv:1412.3989.
[48] A. Buckley, J. Ferrando,S. Lloyd, K. Nordström, B. Page, M. Rüfenacht,M.
Schönherr,G.Watt,LHAPDF6:partondensityaccessintheLHCprecisionera,
Eur.Phys.J.C75(2015)132,https://doi.org/10.1140/epjc/s10052-015-3318-8,
arXiv:1412.7420.
[49] S.Carrazza,J.I.Latorre,J.Rojo,G.Watt,Acompressionalgorithmforthe
com-binationofPDFsets,Eur.Phys.J.C75(2015)474,https://doi.org/10.1140/epjc/ s10052-015-3703-3,arXiv:1504.06469.
[50] J.Butterworth, et al.,PDF4LHC recommendationsfor LHCRunII, J.Phys. G
43(2016)023001,https://doi.org/10.1088/0954-3899/43/2/023001,arXiv:1510. 03865.
[51] T.Sjöstrand,S. Ask,J.R.Christiansen,R.Corke,N. Desai,P.Ilten, S.Mrenna,
S.Prestel,C.O.Rasmussen,P.Z.Skands,AnIntroductiontoPYTHIA8.2,
Com-put.Phys.Commun.191(2015)159,https://doi.org/10.1016/j.cpc.2015.01.024,
arXiv:1410.3012.
[52] M.Bähr,S.Gieseke,M.A.Gigg,D.Grellscheid,K.Hamilton,O.Latunde-Dada,
S.Plätzer,P.Richardson,M.H.Seymour,A.Sherstnev,B.R.Webber,Herwig++
physicsandmanual,Eur.Phys.J.C58(2008)639,https://doi.org/10.1140/epjc/
s10052-008-0798-9,arXiv:0803.0883.
[53] CMSCollaboration,Eventgeneratortunesobtainedfromunderlyingeventand
multipartonscatteringmeasurements,Eur.Phys.J.C76(2016)155,https://
doi.org/10.1140/epjc/s10052-016-3988-x,arXiv:1512.00815.
[54] S.Gieseke,C.Rohr,A.Siodmok,ColourreconnectionsinHerwig++,Eur.Phys.
J. C72 (2012)2225, https://doi.org/10.1140/epjc/s10052-012-2225-5, arXiv:
1206.0041.
[55] S.Frixione,G.Ridolfi,P.Nason,Apositive-weightnext-to-leading-ordermonte
carloforheavyflavourhadroproduction,J.HighEnergyPhys.09(2007)126,
https://doi.org/10.1088/1126-6708/2007/09/126,arXiv:0707.3088.
[56] S.Frixione,P.Nason,C.Oleari,MatchingNLOQCDcomputationswithParton
Showersimulations:thePOWHEGmethod,J.HighEnergyPhys.11(2007)070,
https://doi.org/10.1088/1126-6708/2007/11/070,arXiv:0709.2092.
[57] S.Alioli, P.Nason, C. Oleari,E.Re, Ageneral framework for implementing
NLOcalculationsinshowerMonteCarloprograms:thePOWHEGBOX,J.High
Energy Phys.06(2010)043,https://doi.org/10.1007/JHEP06(2010)043, arXiv:
1002.2581.
[58] S.Agostinelli,etal.,GEANT4Collaboration,GEANT4—asimulationtoolkit,Nucl.
Instrum.MethodsPhys.Res.,Sect.A506(2003)250,https://doi.org/10.1016/
S0168-9002(03)01368-8.
[59] J.Allison,etal.,Geant4developmentsandapplications,IEEETrans.Nucl.Sci.
53(2006)270,https://doi.org/10.1109/TNS.2006.869826.
[60]CMSCollaboration,Measurementoftheinelasticproton–protoncrosssection at√s=13 TeV,arXiv:1802.02613,J.HighEnergyPhys.(2018),submittedfor publication.
[61] D.Krohn,J.Thaler,L.-T.Wang,Jet trimming,J.HighEnergyPhys.02(2010)
084,https://doi.org/10.1007/JHEP02(2010)084,arXiv:0912.1342.
[62] D.Bertolini,P.Harris,M.Low,N.Tran,Pileupperparticleidentification,J.High
Energy Phys.10(2014)059,https://doi.org/10.1007/JHEP10(2014)059, arXiv:
1407.6013.
[63] CMSCollaboration,JetenergyscaleandresolutionintheCMSexperimentin
ppcollisionsat8TeV,J.Instrum.12(2017)P02014,https://doi.org/10.1088/
1748-0221/12/02/P02014,arXiv:1607.03663.
[64] CMSCMSCollaboration, JetEnergy Scaleand ResolutionPerformances with
13 TeVData, CMSDetectorPerformanceSummaryCMS-DP-2016-020,CERN,
2016,https://cds.cern.ch/record/2160347.
[65] CMSCollaboration,Performanceofelectronreconstructionandselectionwith
the CMSdetectorinproton–protoncollisions at√s=8 TeV,J.Instrum. 10
(2015) P06005, https://doi.org/10.1088/1748-0221/10/06/P06005, arXiv:1502.
02701.
[66] CMSCollaboration,PerformanceofCMSmuonreconstructioninppcollision
eventsat √s=7 TeV, J.Instrum.7(2012) P10002,https://doi.org/10.1088/
1748-0221/7/10/P10002,arXiv:1206.4071.
[67] G.P.Salam,Towardsjetography,Eur.Phys.J.C67(2010)637,https://doi.org/10.
1140/epjc/s10052-010-1314-6,arXiv:0906.1833.
[68] M.Dasgupta,A.Fregoso,S.Marzani,G.P.Salam,Towardsanunderstandingof
jet substructure,J.HighEnergyPhys.09(2013)029,https://doi.org/10.1007/
JHEP09(2013)029,arXiv:1307.0007.
[69] A.J.Larkoski,S.Marzani,G.Soyez,J.Thaler,Softdrop,J.HighEnergyPhys.05
(2014)146,https://doi.org/10.1007/JHEP05(2014)146,arXiv:1402.2657.
[70] CMSCollaboration,Jet algorithmsperformancein13TeVdata,CMSPhysics
Analysis Summary CMS-PAS-JME-16-003, CERN, 2017, https://cds.cern.ch/
record/2256875.
[71] J.Thaler,K.VanTilburg, Maximizingboostedtopidentificationby
minimiz-ingN-subjettiness,J.HighEnergyPhys.02(2012)093,https://doi.org/10.1007/
JHEP02(2012)093,arXiv:1108.2701.
[72]CMSCollaboration,Identificationofheavy-flavourjetswiththeCMSdetectorin ppcollisionsat13 TeV,arXiv:1712.07158,2017,J.Instrum.(2018),submitted forpublication.
[73] ATLASandCMSCollaborations, Combinedmeasurementofthe Higgsboson
massinpp collisionsat√s=7 and8tevwiththeATLASandCMS
experi-ments,Phys.Rev.Lett.114(2015)191803,https://doi.org/10.1103/PhysRevLett.
114.191803,arXiv:1503.07589.
[74] CMS Collaboration, Measurements ofproperties ofthe Higgs boson
decay-inginto thefour-leptonfinalstate inpp collisionsat √s=13 TeV,J. High
Energy Phys. 11(2017) 047,https://doi.org/10.1007/JHEP11(2017)047,arXiv:
1706.09936,2017.
[75] M.Oreglia,A Studyofthe Reactionsψ→γ γψ, Ph.D. thesis,SLAC,1980,
http://www.slac.stanford.edu/pubs/slacreports/slac-r-236.html.
[76] F.Garwood,(i)FiduciallimitsforthePoissondistribution,Biometrika28(1936)
437,https://doi.org/10.1093/biomet/28.3-4.437.
[77] R.G. Lomax,D.L.Hahs-Vaughn, StatisticalConcepts: ASecondCourse, Taylor
andFrancis,Hoboken,NJ,2012,https://cds.cern.ch/record/1487958.
[78]CMSCollaboration, CMSLuminosity Measurementforthe 2016DataTaking Period,CMSPhysicsAnalysisSummaryCMS-PAS-LUM-17-001,CERN,2017,in preparation.
[79] R.Barlow,C.Beeston,FittingusingfiniteMonteCarlosamples,Comput.Phys.
Commun.77(1993)219,https://doi.org/10.1016/0010-4655(93)90005-W.
[80] J.S.Conway,Incorporatingnuisanceparametersinlikelihoodsformultisource
spectra, in: Proceedings, PHYSTAT 2011 Workshop on StatisticalIssues
Re-latedtoDiscoveryClaimsinSearchExperimentsandUnfolding,CERN,Geneva,
Switzerland 17–20January2011,2011,p. 115,https://doi.org/10.5170/CERN
-2011-006.115,arXiv:1103.0354.
[81] A.L.Read,Presentationofsearchresults:theC Lstechnique,J.Phys.G28(2002)
2693,https://doi.org/10.1088/0954-3899/28/10/313.
[82] T. Junk, Confidence level computation for combining searches with small
statistics,Nucl.Instrum.MethodsPhys.Res.,Sect.A434(1999)435,https://
doi.org/10.1016/S0168-9002(99)00498-2,arXiv:hep-ex/9902006.
[83] G.Cowan,K.Cranmer,E.Gross,O.Vitells,Asymptoticformulaefor
likelihood-basedtestsofnewphysics,Eur.Phys.J.C71(2011)1554,https://doi.org/10.
1140/epjc/s10052-011-1554-0, arXiv:1007.1727, Erratum: https://doi.org/10. 1140/epjc/s10052-013-2501-z.
TheCMSCollaboration
A.M. Sirunyan,
A. Tumasyan
YerevanPhysicsInstitute,Yerevan,Armenia
W. Adam,
F. Ambrogi,
E. Asilar,
T. Bergauer,
J. Brandstetter,
E. Brondolin,
M. Dragicevic,
J. Erö,
M. Flechl,
M. Friedl,
R. Frühwirth
1,
V.M. Ghete,
J. Grossmann,
J. Hrubec,
M. Jeitler
1,
A. König,
N. Krammer,
I. Krätschmer,
D. Liko,
T. Madlener,
I. Mikulec,
E. Pree,
N. Rad,
H. Rohringer,
J. Schieck
1,
R. Schöfbeck,
M. Spanring,
D. Spitzbart,
W. Waltenberger,
J. Wittmann,
C.-E. Wulz
1,
M. Zarucki
V. Chekhovsky,
V. Mossolov,
J. Suarez Gonzalez
InstituteforNuclearProblems,Minsk,Belarus
E.A. De Wolf,
D. Di Croce,
X. Janssen,
J. Lauwers,
M. Van De Klundert,
H. Van Haevermaet,
P. Van Mechelen,
N. Van Remortel
UniversiteitAntwerpen,Antwerpen,Belgium
S. Abu Zeid,
F. Blekman,
J. D’Hondt,
I. De Bruyn,
J. De Clercq,
K. Deroover,
G. Flouris,
D. Lontkovskyi,
S. Lowette,
S. Moortgat,
L. Moreels,
Q. Python,
K. Skovpen,
S. Tavernier,
W. Van Doninck,
P. Van Mulders,
I. Van Parijs
VrijeUniversiteitBrussel,Brussel,Belgium
D. Beghin,
H. Brun,
B. Clerbaux,
G. De Lentdecker,
H. Delannoy,
B. Dorney,
G. Fasanella,
L. Favart,
R. Goldouzian,
A. Grebenyuk,
G. Karapostoli,
T. Lenzi,
J. Luetic,
T. Maerschalk,
A. Marinov,
A. Randle-conde,
T. Seva,
E. Starling,
C. Vander Velde,
P. Vanlaer,
D. Vannerom,
R. Yonamine,
F. Zenoni,
F. Zhang
2UniversitéLibredeBruxelles,Bruxelles,Belgium
A. Cimmino,
T. Cornelis,
D. Dobur,
A. Fagot,
M. Gul,
I. Khvastunov
3,
D. Poyraz,
C. Roskas,
S. Salva,
M. Tytgat,
W. Verbeke,
N. Zaganidis
GhentUniversity,Ghent,Belgium
H. Bakhshiansohi,
O. Bondu,
S. Brochet,
G. Bruno,
C. Caputo,
A. Caudron,
P. David,
S. De Visscher,
C. Delaere,
M. Delcourt,
B. Francois,
A. Giammanco,
M. Komm,
G. Krintiras,
V. Lemaitre,
A. Magitteri,
A. Mertens,
M. Musich,
K. Piotrzkowski,
L. Quertenmont,
A. Saggio,
M. Vidal Marono,
S. Wertz,
J. Zobec
UniversitéCatholiquedeLouvain,Louvain-la-Neuve,Belgium
N. Beliy
UniversitédeMons,Mons,Belgium
W.L. Aldá Júnior,
F.L. Alves,
G.A. Alves,
L. Brito,
M. Correa Martins Junior,
C. Hensel,
A. Moraes,
M.E. Pol,
P. Rebello Teles
CentroBrasileirodePesquisasFisicas,RiodeJaneiro,Brazil
E. Belchior Batista Das Chagas,
W. Carvalho,
J. Chinellato
4,
E. Coelho,
E.M. Da Costa,
G.G. Da Silveira
5,
D. De Jesus Damiao,
S. Fonseca De Souza,
L.M. Huertas Guativa,
H. Malbouisson,
M. Melo De Almeida,
C. Mora Herrera,
L. Mundim,
H. Nogima,
L.J. Sanchez Rosas,
A. Santoro,
A. Sznajder,
M. Thiel,
E.J. Tonelli Manganote
4,
F. Torres Da Silva De Araujo,
A. Vilela Pereira
UniversidadedoEstadodoRiodeJaneiro,RiodeJaneiro,Brazil
S. Ahuja
a,
C.A. Bernardes
a,
T.R. Fernandez Perez Tomei
a,
E.M. Gregores
b,
P.G. Mercadante
b,
S.F. Novaes
a,
Sandra S. Padula
a,
D. Romero Abad
b,
J.C. Ruiz Vargas
aaUniversidadeEstadualPaulista,SãoPaulo,Brazil bUniversidadeFederaldoABC,SãoPaulo,Brazil
A. Aleksandrov,
R. Hadjiiska,
P. Iaydjiev,
M. Misheva,
M. Rodozov,
M. Shopova,
G. Sultanov
InstituteforNuclearResearchandNuclearEnergyofBulgariaAcademyofSciences,Bulgaria
A. Dimitrov,
I. Glushkov,
L. Litov,
B. Pavlov,
P. Petkov
UniversityofSofia,Sofia,Bulgaria
BeihangUniversity,Beijing,China
M. Ahmad,
J.G. Bian,
G.M. Chen,
H.S. Chen,
M. Chen,
Y. Chen,
C.H. Jiang,
D. Leggat,
H. Liao,
Z. Liu,
F. Romeo,
S.M. Shaheen,
A. Spiezia,
J. Tao,
C. Wang,
Z. Wang,
E. Yazgan,
H. Zhang,
S. Zhang,
J. Zhao
InstituteofHighEnergyPhysics,Beijing,China
Y. Ban,
G. Chen,
Q. Li,
S. Liu,
Y. Mao,
S.J. Qian,
D. Wang,
Z. Xu
StateKeyLaboratoryofNuclearPhysicsandTechnology,PekingUniversity,Beijing,China
C. Avila,
A. Cabrera,
L.F. Chaparro Sierra,
C. Florez,
C.F. González Hernández,
J.D. Ruiz Alvarez
UniversidaddeLosAndes,Bogota,Colombia
B. Courbon,
N. Godinovic,
D. Lelas,
I. Puljak,
P.M. Ribeiro Cipriano,
T. Sculac
UniversityofSplit,FacultyofElectricalEngineering,MechanicalEngineeringandNavalArchitecture,Split,Croatia
Z. Antunovic,
M. Kovac
UniversityofSplit,FacultyofScience,Split,Croatia
V. Brigljevic,
D. Ferencek,
K. Kadija,
B. Mesic,
A. Starodumov
7,
T. Susa
InstituteRudjerBoskovic,Zagreb,Croatia
M.W. Ather,
A. Attikis,
G. Mavromanolakis,
J. Mousa,
C. Nicolaou,
F. Ptochos,
P.A. Razis,
H. Rykaczewski
UniversityofCyprus,Nicosia,Cyprus
M. Finger
8,
M. Finger Jr.
8CharlesUniversity,Prague,CzechRepublic
E. Carrera Jarrin
UniversidadSanFranciscodeQuito,Quito,Ecuador
A.A. Abdelalim
9,
10,
Y. Mohammed
11,
E. Salama
12,
13AcademyofScientificResearchandTechnologyoftheArabRepublicofEgypt,EgyptianNetworkofHighEnergyPhysics,Cairo,Egypt
R.K. Dewanjee,
M. Kadastik,
L. Perrini,
M. Raidal,
A. Tiko,
C. Veelken
NationalInstituteofChemicalPhysicsandBiophysics,Tallinn,Estonia
P. Eerola,
H. Kirschenmann,
J. Pekkanen,
M. Voutilainen
DepartmentofPhysics,UniversityofHelsinki,Helsinki,Finland
J. Havukainen,
J.K. Heikkilä,
T. Järvinen,
V. Karimäki,
R. Kinnunen,
T. Lampén,
K. Lassila-Perini,
S. Laurila,
S. Lehti,
T. Lindén,
P. Luukka,
H. Siikonen,
E. Tuominen,
J. Tuominiemi
HelsinkiInstituteofPhysics,Helsinki,Finland
J. Talvitie,
T. Tuuva
LappeenrantaUniversityofTechnology,Lappeenranta,Finland