Search for light pseudoscalar boson pairs produced from decays of the 125 GeV Higgs boson in final states with two muons and two nearby tracks in pp collisions at root s d=13TeV

Contents lists available atScienceDirect

Physics

Letters

B

www.elsevier.com/locate/physletb

Search

for

light

pseudoscalar

boson

pairs

produced

from

decays

of

the

125 GeV

Higgs

boson

in

final

states

with

two

muons

and

two

nearby

tracks

in

pp

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:

Received16July2019

Receivedinrevisedform12October2019 Accepted4November2019

Availableonline8November2019 Editor: M.Doser Keywords: CMS Physics Higgsboson NMSSM 2HD+1S

A search is presented for pairs of light pseudoscalarbosons, in the mass range from 4 to 15 GeV, producedfromdecaysofthe125 GeVHiggsboson.Thedecaymodesconsideredarefinalstatesthatarise whenoneofthepseudoscalarsdecaystoapairoftauleptons,andtheotheroneeitherintoapairoftau leptonsormuons.Thesearchisbasedonproton-protoncollisionscollectedbytheCMSexperimentin 2016atacenter-of-massenergyof13 TeVthatcorrespondtoanintegratedluminosityof35.9 fb−1.The 2

μ

2

τ

and4

τ

channelsareusedincombinationtoconstraintheproductoftheHiggsbosonproduction cross sectionand the branchingfraction into 4

τ

finalstate,

σ

B,exploitingthe lineardependence of the fermioniccouplingstrengthofpseudoscalarbosonsonthe fermionmass. Nosignificantexcessis observedbeyondtheexpectationfromthestandardmodel.Theobservedandexpectedupperlimitsat 95% confidencelevel on

σ

B,relativetothe standardmodel Higgsbosonproductioncrosssection,are setrespectivelybetween0.022and0.23andbetween0.027and0.19inthemassrangeprobedbythe analysis.

©2019TheAuthor(s).PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCCBYlicense (http://creativecommons.org/licenses/by/4.0/).FundedbySCOAP3_.

1. Introduction

After the discovery of the 125GeV Higgs boson (H) [1,2], searches for additional Higgs bosons, based on predictions be-yond the standard model (SM), constitute an important part of the scientific program at the CERN Large Hadron Collider (LHC). Thepresentanalysisexaminestheoreticalmodelsthatcontaintwo Higgsdoubletsandanadditionalcomplex singletHiggsfield (de-noted hereafter as 2HD+1S), that does not couple at tree level to fermions or gauge bosons and interacts only with itself and the Higgs doublets [3–10]. In CP conserving models, which are considered in this Letter, the Higgs sector features seven physi-cal states, namely three CP-even, two CP-odd, and two charged bosons,whereoneoftheCP-evenstatescorrespondstotheH.This kindof Higgs sector is realized, forexample, in next-to-minimal supersymmetricmodelsthatsolvetheso-called

μ

problemofthe minimalsupersymmetricextension ofthe SM [11].Alarge setof the2HD+1S models is allowed by measurements andconstraints set by searches for additional Higgs bosons andsupersymmetric particles [12–17].

 _{E-mailaddress:cms-publication-committee-chair@cern.ch.}

This Letter addresses specific 2HD+1S models in which the lightestpseudoscalarboson(a1) withmass2ma1

<

125GeV hasa large singletcomponent, andthereforeits couplings toSM parti-clesaresignificantlyreduced.Forthisreason,analysesusingdirect production modes of a1, such as gluon-gluon fusion (ggF) or b

quarkassociatedproduction,havelimitedsensitivity.Thea1 boson

isnonetheless potentially accessibleinthe H decay totwo pseu-doscalarbosons.Thea1statescanbeidentifiedviatheirdecayinto

apairoffermions [18–25].ConstraintsontheH couplingsallowa branching fractionforH decays intonon-SMparticles aslarge as 34% [26],whichcanpotentiallyaccommodatetheH

→

a1a1 decay

ataratesufficientlyhighfordetectionattheLHC.

Several searches for H

→

a1a1 decays have been performed

in the ATLAS andCMS experiments in Run1 (8TeV)and Run 2 (13TeV) ofLHC,exploitingvarious decaymodesofthe a1 boson,

andprobing different ranges ofits mass [27–40]. These searches found no significant deviation from the expectation of the SM backgroundandupperlimitswereset ontheproductofthe pro-ductioncrosssection andthe branchingfractionforsignal result-inginconstraintsonparametersofthe2HD+1Smodels.

Thisanalysispresentsasearchforlight a1 bosonsinthedecay

channels H

→

a1a1

→

4

τ

/

2

μ

2

τ

, using data corresponding to an

integratedluminosityof35

.

9fb−1,collectedwiththeCMSdetector

https://doi.org/10.1016/j.physletb.2019.135087

0370-2693/©2019TheAuthor(s).PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCCBYlicense(http://creativecommons.org/licenses/by/4.0/).Fundedby SCOAP3_.

Fig. 1. Illustrationofthesignaltopology,inwhichtheH decaysintotwoa1bosons,

whereonea1bosondecaysintoapairoftauleptons,whiletheotheronedecays

intoapairofmuonsorapairoftauleptons.Theanalyzedfinalstateconsistsof onemuonandanoppositelychargedtrackineacha1decay.

in2016atacenter-of-massenergyof13TeV.Theanalysiscovers themass rangefrom 4to 15GeV andemploys a special analysis strategytoselectandidentifyhighlyLorentz-boostedmuonortau leptonpairswithoverlappingdecayproducts.Thestudyupdatesa similaroneperformedbytheCMSCollaborationinRun1 [28],and complementsother recentCMSsearches forthe H

→

a1a1 decay

performedinRun2datainthe2

μ

2

τ

[30],2

τ

2b [31],2

μ

2b [38] and4

μ

[39] finalstates,coveringrespectivemassrangesof0

.

25

<

ma1

<

3

.

40GeV forthe 4

μ

final state and15

.

0

<

ma1

<

62

.

5GeV forthe2

μ

2

τ

,

2

τ

2b,and2

μ

2b finalstates.

Thebranching fractiona1

→

τ τ

dependson thedetailsofthe

model,namelytheparametertan

β

,the ratioofvacuum expecta-tionvaluesofthetwoHiggsdoublets,andonwhichHiggsdoublet couples to either charged leptons, up-type quarks or down-type quarks [41]. InType-II 2HD+1S models,whereone Higgsdoublet couplestoup-typefermionswhiletheothercouplestodown-type fermions, the a1

→

τ τ

decay rate gets enhanced atlarge values

oftan

β

.Thebranchingfractionofthisdecayreachesvaluesabove 90% attan

β >

3 for 2mτ

<

ma1

<

2mb,wheremτ is themass of

thetauleptonandmb isthemassofthebottomquark.Forhigher

valuesofma1 thebranching fractiondecreases to 5–6% sincethe decayintoapairofbottomquarksbecomeskinematicallypossible andoverwhelmsthedecayintoapairoftauleptons.However, in someofthe2HD+1Smodelsthea1

→

τ τ

decaymaybedominant

evenabovethe a1

→

bb decay

¯

threshold.Thisisrealized,e.g.,for

tan

β >

1 intheType-III2HD+1Smodels,whereoneHiggsdoublet couplestochargedleptons, whereas theother doubletcouplesto quarks [41].

The signal topology targeted by the present analysis is illus-trated in Fig. 1. Each a1 boson is identified by the presence of

a muon and only one additional charged particle, the objective of this approach being the decay channels a1

→

μμ

and a1

→

τ

μ

τ

one-prong. The

τ

μ denotes the muonic tau lepton decay, and

τ

one-prong standsforitsleptonic orone-pronghadronicdecay.The

three-prong modes are not used because of the very high QCD multijetbackgroundandlowerreconstructionsignalefficiency.

Giventhe large differencein massbetween thea1 andtheH

states,thea1 bosonswillbeproducedhighlyLorentz-boosted,and

their decay products are highly collimated. This will result in a signature with two muons, each of which is accompanied by a nearby particle of opposite charge. The search focuses primarily on the dominant ggF process, in which the H state is produced withrelativelysmall transversemomentum pT,andthe a1

pseu-doscalarsareemitted nearlyback-to-backinthetransverseplane, witha largeseparation inazimuth

φ

betweenthe particles orig-inating fromone of the a1 decaysand those of the other a1. In

theggF process,theHcanbealsoproducedwitharelativelyhigh Lorentzboostwhenahardgluonisradiatedfromtheinitial-state

gluonsorfromtheheavy-quarkloop.Inthiscase,theseparationin

φ

isreduced, buttheseparationinpseudorapidity

η

canbelarge. The analysisthereforesearches forasignal ina sample of same-charge (SC)dimuoneventswithlargeangularseparationbetween the muons,where eachmuon isaccompaniedby one nearby op-positely chargedparticleoriginatingfromthe samea1 decay.The

requirement ofhaving SC muons in theevent largely suppresses background fromthe top-quark-pair,Drell–Yan, anddiboson pro-duction.Thisrequirementalsofacilitatesthe implementationofa dedicatedSCdimuontriggerwithrelativelylowthresholdsand ac-ceptableratesasdescribedinSection4.

2. CMSdetector

The central feature of the CMS detectoris a superconducting solenoid of 6m internal diameter, providing a magnetic field of 3

.

8T. Within the solenoid volume are a silicon pixel and strip tracker,aleadtungstatecrystalelectromagneticcalorimeter,anda brass andscintillatorhadroncalorimeter,eachcomposedofa bar-rel and two endcap sections.Forward calorimeters extend the

η

coverage providedby thebarrelandendcapdetectors.Muonsare detected ingas-ionization chambers embedded in the steel flux-returnyokeoutsidethesolenoid.

Events ofinterest are selected using a two-tiered trigger sys-tem [42].Thefirstlevel,composedofcustomhardwareprocessors, usesinformationfromthecalorimetersandmuondetectorsto se-lect eventsat arateof around 100kHz within atime interval of less than 4μs. The second level, known asthe high-level trigger, consistsofafarmofprocessorsrunningaversionofthefullevent reconstructionsoftwareoptimizedforfastprocessing,andreduces theeventratebelow1kHz beforedatastorage.

AmoredetaileddescriptionoftheCMSdetector,togetherwith a definitionofthecoordinatesystemusedandtherelevant kine-maticvariables,canbefoundinRef. [43].

3. Simulatedsamples

For the simulation of the dominant ggF production process, the MonteCarlo (MC)event generators pythia (v.8.212) [44] and MadGraph5_amc@nlo (v.2.2.2) [45] are used in order to model the H

→

a1a1

→

4

τ

and H

→

a1a1

→

2

μ

2

τ

signal events,

re-spectively. For both decay modes the pT distribution of the H

emerging fromggF isreweighted withnext-to-next-to-leading or-der (NNLO) K factors obtained by the program HqT (v2.0) [46,

47] withNNLONNPDF3.0partondistributionfunctions(PDF) [48], hereby takingintoaccount the moreprecise spectrum calculated to NNLO withresummationtonext-to-next-to-leading-logarithms order.Subdominantcontributionsfromother productionmodesof H, namely vector boson fusion process (VBF),vector boson asso-ciated production(VH) andtop quark pairassociated production (t

¯

tH)areestimatedusingthe pythia (v.8.212)generator.

The backgroundsfromdibosonproductionandquantum chro-modynamics production ofmultijet (QCD multijet) are simulated with the pythia (v.8.212) generator. Inclusive Z and W boson production processes are generated with MadGraph5_amc@nlo (v.2.2.2).The single-topand t

¯

t production are generatedat Next-to-LO(NLO)withthe powheg (v.2.0)generator[49–53].Thesetof PDFusedisNLONNPDF3.0forNLOsamples,andLONNPDF3.0for LOsamples [48].

Showering and hadronization are carried out by the pythia (v.8.212)generatorwiththeCUETP8M1underlyingeventtune [54], while a detailedsimulation of the CMSdetectoris based on the Geant4[55] package.

4. Eventselection

EventsareselectedusingaSC dimuontriggerwith pT

thresh-oldsof17

(

8

)

GeV fortheleading (subleading)muon.Topassthe high-leveltrigger,thetracksofthetwomuonsareadditionally re-quiredtohavepoints ofclosestapproachtothebeamaxiswithin 2mm ofeachotheralongthelongitudinaldirection.

Events are reconstructed with the particle-flow (PF) algo-rithm [56] whichaims toidentifyandreconstructindividual par-ticlesasphotons, chargedhadrons, neutralhadrons, electrons, or muons(PFobjects).Theproton-proton(pp)interactionverticesare reconstructedusingaKalmanfilteringtechnique [57,58].Typically morethanonesuchvertexisreconstructedbecauseofmultiplepp collisions within the sameor neighbouring bunch crossings. The meannumberof such interactions per bunch crossingwas 23in 2016.

The reconstructed vertex with the largest value of summed physics-object p2

T is taken to be the primary interaction vertex

(PV). The physics objects are the jets, clustered using the jet-findingalgorithm [59,60] withthetracksassignedtothevertexas inputs,andtheassociatedmissingtransversemomentum,takenas thenegative vectorsumofthe pT ofthosejets.Events must

con-tain atleasttwo SC muonsreconstructed withthe PFalgorithm, whichhavetofulfilthefollowingrequirements.

•

Thepseudorapidityoftheleading(higherpT)andthe

sublead-ing(lower pT)muonsmustbe

|

η

|

<

2

.

4.

•

The pT of the leading (subleading) muon must exceed 18

(

10

)

GeV.

•

The transverse (longitudinal) impact parameters of muons with respectto thePVare required tobe

|

d0

|

<

0

.

05

(

|

dz

|

<

0

.

1

)

cm.

•

The

_

angular separation between the muons is



R

=

(φ)

2

_{+ (}

_η

2

_{) >}

_2.

IfmorethanoneSCmuonpairisfoundintheeventtosatisfy theserequirements,thepairwiththelargestscalarsumofmuon

pTischosen.

Inthenextstep,theanalysisemploysinformationabouttracks associatedwiththereconstructedchargedPFobjects,excludingthe pairofSCmuons.Selectedmuonsandtracksareusedtobuildand isolate candidates for the a1

→

τ

μ

τ

one-prong or a1

→

μμ

decays

(referredtoasa1candidatesthroughouttheLetter).Threetypesof

tracksareconsideredintheanalysis.

•

“Isolation”tracksareusedtodefineisolationrequirements im-posedon a1 candidatesandhavetofulfilthefollowing

crite-ria: pT

>

1GeV,

|

η

|

<

2

.

4,

|

d0

|

<

1cm,

|

dz

|

<

1cm.

•

“Signal” tracks are selectedamong “isolation”tracks to build a1candidates.ThesetracksmusthavepT

>

2

.

5GeV,

|

η

|

<

2

.

4,

|

d0

|

<

0

.

02cm,

|

dz

|

<

0

.

04cm.

•

“Soft” tracks are also a subset of “isolation” tracks.They are utilized to define one of the sideband regions, used for the construction of the background model, as described in Sec-tion 5.2. “Soft” tracks must satisfy the requirements: 1

.

0

<

pT

<

2

.

5GeV,

|

η

|

<

2

.

4,

|

d0

|

<

1cm,

|

dz

|

<

1cm.

Atrackisregardedasbeingnearbyamuoniftheangular sep-aration



R betweenthem issmaller than 0.5.Each muon ofthe SCpairisrequiredtohaveonenearby“signal”trackwithacharge opposite toits charge. This muon-tracksystemis acceptedas an a1candidateifnoadditional“isolation”tracksarefoundinthe



R

coneof 0.5around themuon momentum direction. The eventis selectedinthe final sample ifitcontains two a1 candidates.The

Table 1

Thesignalacceptanceandthenumberofexpectedsignaleventsafterselectionin theSR.Thenumberofexpectedsignaleventsiscomputedforabenchmarkvalue ofbranchingfraction,B(H→a1a1)B2(a1→τ τ)=0.2 andassumingthatthe H

productioncrosssectionistheonepredictedintheSM.Thequoteduncertainties forpredictionsfromsimulationincludeonlystatisticalones.

ma1[GeV] Acceptance×10 4 _{Number of events} 4τ 2μ2τ 4τ 2μ2τ 4 3.29±0.16 89.3±1.4 129.9±6.2 54.7±0.9 7 2.50±0.14 69.0±1.4 98.8±5.5 22.5±0.5 10 1.46±0.11 47.1±1.2 57.8±4.2 14.2±0.4 15 0.21±0.04 3.5±0.3 8.5±1.1 1.0±0.1

setofselectionrequirementsoutlinedabovedefinesthesignal re-gion(SR).

Theexpectedsignalacceptanceandsignalyieldforafew rep-resentativevaluesofma1 arereportedinTable1.Thesignalyields are computed for a benchmark value of the branching fraction,

B(

H

→

a1a1

)B

2

(

a1

→

τ τ

)

=

0

.

2 and assumingthattheH

produc-tion cross section is the one predicted in the SM. Contributions from the ggF, VBF, VH and t

¯

tH processes are summed up. The yield ofthe 2

μ

2

τ

signal is estimatedunderthe assumptionthat thepartialwidthsofthea1

→

μμ

anda1

→

τ τ

decayssatisfythe

relation [23]

(

a1

→

μμ

)

(

a1

→

τ τ

)

=

m2_μ m2 τ



1

−



2mτ

/

ma1



2

.

(1)

The ratioofbranchingfractionsofthe a1a1

→

2

μ

2

τ

anda1a1

→

4

τ

decays is computed through the ratio of the partial widths

(

a1

→

μμ

)

and

(

a1

→

τ τ

)

as

B

(

a1a1

→

2

μ

2

τ

)

B

(

a1a1

→

4

τ

)

=

2

B

(

a1

→

μμ

)

B

(

a1

→

τ τ

)

=

2

(

a1

→

μμ

)

(

a1

→

τ τ

)

.

(2)

The factor of 2 in Eq. (2) arises from two possible decays, a₁(1)a(₁2)

→

2

μ

2

τ

anda₁(1)a(₁2)

→

2

τ

2

μ

,thatproducethefinalstate withtwo muonsandtwo tauleptons. TheratioinEq. (2) ranges fromabout0.0073atma1

=

15GeV to0.0155atma1

=

4GeV.

The contributionfromtheH

→

a1a1

→

4

μ

decayisestimated

takinginto account Eq. (1). It ranges between0.4 and2% of the totalsignalyieldinthe2

μ

2

τ

and4

τ

finalstates,dependingonthe probed massofthea1 boson.Thiscontributionis notconsidered

inthepresentanalysis.

The number of observed events selected in the SR amounts to 2035. A simulation-based study shows that the QCD multijet eventsdominatethesampleofeventsselectedintheSR. Contribu-tionfromotherbackgroundsourcesconstitutesabout1% ofevents selectedintheSR.

The two-dimensional(2D) distributionoftheinvariant masses ofthe muon-tracksystems,constituting a1 candidates, isusedto

discriminatebetweensignalandthedominantQCDmultijet back-groundin the signal extractionprocedure. The 2D distribution is filledwithapairofthemuon-trackinvariantmasses(m1

,

m2),

or-deredbytheirvalue,m2

>

m1.Thebinning ofthe2D distribution

adopted inthe analysisis illustrated in Fig. 2. As m2 is required

to exceedm1, only

(

i

,

j

)

bins with j

≥

i arefilled inthe 2D

dis-tribution,yielding intotal6

(

6

+

1

)/

2

=

21 independentbins.Bins

(

i

,

6

)

withi

=

1

,

5 containall eventswithm2

>

6GeV.Bin

(

6

,

6

)

containsalleventswithm1,2

>

6GeV.

5. Modelingbackground

Asimulation-based studyrevealsthat thesample ofSC muon pairsselectedasdescribedinSection4,butwithoutrequiringthe

Table 2

Controlregionsusedtoconstructandvalidatethebackgroundmodel.ThesymbolsNsig,NisoandNsoftdenote

thenumberof“signal”,“isolation”(whichareasubsetof“signal”tracks)and“soft”tracks,respectively,withina coneofR=0.5 aroundthemuonmomentumdirection.ThelastrowdefinestheSR.

Control region Firstμ Secondμ Purpose Observed events

N23 Niso=1, Nsig=1 Niso=2,3 Determination of f1D(i) 62 438

Niso,2=1 Niso>1, Nsig≥1 Niso=1, Nsig=1 Validation of f1D(i) 472 570

Niso,2=2,3 Niso>1, Nsig≥1 Niso=2,3 Validation of f1D(i) 17 667 900

N45 Niso=1, Nsig=1 Niso=4,5 Assessment of

systematics in f1D(i) 52 437

Both muons

Loose-Iso Nsig=1, Nsoft=1,2 Determination of C(i,j) 35 824

Signal region Nsig=1, Niso=1 Signal extraction 2 035

Fig. 2. Binning of the 2D (m1,m2) distribution.

presence of a1 candidates, is dominatedby QCD multijet events,

whereabout85% ofall selectedevents containbottom quarksin thefinalstate.TheSCmuonpairsintheseeventsoriginatemainly fromthefollowingsources:

•

muonicdecayofabottomhadroninonebottomquarkjetand cascadedecayofabottom hadron intoa charmhadron with asubsequentmuonicdecayofthecharmhadronintheother bottomquarkjet;

•

muonicdecayofabottomhadroninonebottomquarkjetand decayofaquarkoniumstateintoapairofmuonsintheother jet;

•

muonicdecayofabottomhadroninonebottomquarkjetand muonicdecay ofa B0 _{mesonin the other bottom quark jet.}

TheSCmuonpairinthiscasemayappearasaresultofB0–B0 oscillations.

The normalized 2D (m1

,

m2) distribution for the muon-track

pairs with m2

>

m1 is represented in the sample of background

eventsbyabinned templateconstructedusingthefollowing rela-tion f2D

(

i

,

j

)

=

C

(

i

,

j

)(

f1D

(

i

)

f1D

(

j

))

sym

,

(

f1D

(

i

)

f1D

(

i

))

sym

=

f1D

(

i

)

f1D

(

i

),

(

f1D

(

i

)

f1D

(

j

))

sym

=

f1D

(

i

)

f1D

(

j

)

+

f1D

(

j

)

f1D

(

i

)

=

2 f1D

(

i

)

f1D

(

j

),

if j

>

i

,

(3) where

•

f2D

(

i

,

j

)

isthecontent ofthebin

(

i

,

j

)

inthenormalized2D

(m1

,

m2)distribution;

•

f1D

(

i

)

is the content of bin i in the normalized

one-dimen-sional(1D)distributionofthemuon-trackinvariantmass;

•

C

(

i

,

j

)

isasymmetricmatrix,accountingforpossible

correla-tion betweenm1 andm2, the elements of thematrix C

(

i

,

j

)

arereferredtoas“correlationfactors”inthefollowing. The condition C

(

i

,

j

)

=

1 for all bins

(

i

,

j

)

would indicate an absenceofcorrelation betweenm1 andm2.Wesumthecontents

of the nondiagonal bins

(

i

,

j

)

and

(

j

,

i

)

in the Cartesian product

f1D

(

i

)

f1D

(

j

)

toaccountforthefactthateachevententersthe2D

(m1

,

m2) distribution with ordered values of the muon-track

in-variantmasses.

Byconstructionthebackgroundmodelestimatesthedominant QCDmultijetproductionaswellassmallcontributionsfromother processes.

Multiplecontrolregions(CRs)areintroducedinordertoderive and validate the modeling of f1D

(

i

)

and C

(

i

,

j

)

. The CRs are

de-finedonthebasisofamodifiedisolationcriteriaappliedtooneor both muon-track pairs.The isolation criteriaare specified by the multiplicity of“isolation” tracks inthe cone of



R

=

0

.

5 around the muon momentumdirection. The summary ofall CRsused to derive andvalidate themodelingofbackgroundshapeisgivenin Table2.

5.1. Modelingof f1D

(

i

)

The f1D

(

i

)

distribution is modeled using the N23 CR. Events

in thisCRpass theSC dimuonselection andcontainonly one a1

candidatecomposedoftheisolated“signal”trackandmuon(first muon). Theinvariant massofthefirstmuonandassociatedtrack entersthe f1D

(

i

)

distribution.Anothermuon(secondmuon)is

re-quiredtobeaccompaniedbyeithertwoorthreenearby“isolation” tracks. The simulation shows that more than 95% of events se-lectedintheCRN23areQCDmultijetevents,whiletheremaining

5% is comingfrom t

¯

t, Drell-Yanand other electroweakprocesses. The modeling ofthe f1D

(

i

)

template is based on the hypothesis

that thekinematic distributionsforthe muon-tracksystem, mak-ing up an a1 candidate(the first muonandassociatedtrack), are

weaklyaffectedbytheisolation requirementimposed onthe sec-ond muon; therefore the f1D

(

i

)

distribution of the muon-track

system forming an a1 candidate is expectedto be similar in the

SRandtheN23CR.

Thishypothesisisverifiedincontrolregionslabelled Niso,2

=

1

and Niso,2

=

2

,

3. Events are selected in these CR if one of the

muons(firstmuon)hasmorethanone“isolation”track(Niso

>

1).

At least one of these“isolation” tracks should also fulfil the cri-teria imposed on the “signal” track. As more than one of these tracks can pass the criteria imposed on “signal”tracks, two sce-narios havebeen investigated,namely usingeither thelowest or thehighestpT “signal”tracks(“softest”and“hardest”)tocalculate

themuon-trackinvariantmass.Ifonlyone“signal”trackisfound nearby tothe firstmuon, thetrackis usedboth asthe“hardest”

Fig. 3. Theobservedinvariantmassdistribution,normalizedtounity,ofthefirst muonandthesoftest(upper)orhardest(lower)accompanying“signal”trackfor differentisolationrequirementsimposedonthesecondmuon:whenthe second muonhasonlyoneaccompanying“isolation”track(Niso,2=1;circles);orwhenit

hastwoorthreeaccompanying“isolation”tracks(Niso,2=2,3;squares).

andthe“softest”signaltrack.Forthesecondmuon,two isolation requirementsare considered: whenthe muon isaccompanied by onlyone“signal”trackandthemuon-tracksystemisisolatedasin theSR(CRNiso,2

=

1),orwhenitisaccompaniedby twoorthree

“isolation”tracks as inthe CR N23 (CR Niso,2

=

2

,

3). The

invari-antmassdistributionsofthefirstmuonandthesoftestorhardest accompanyingtrackarethencomparedforthetwodifferent isola-tionrequirementsonthesecondmuon,Niso,2

=

1 andNiso,2

=

2

,

3.

The results of this studyare illustrated in Fig. 3. In both cases, theinvariantmassdistributionsdifferineachbinbylessthan6%. This observation indicates that the invariant mass of the muon-tracksystem, makingup an a1 candidate,weaklydependsonthe

isolationrequirementimposedonthesecondmuon,thus support-ingtheassumptionthatthe f1D

(

i

)

distributioncanbedetermined

fromtheN23CR.

Fig. 4. Theobservedinvariantmassdistribution,normalizedtounity,ofthe muon-trackinvariantmassincontrolregionsN23(circles)andN45(squares).

The potential dependence of the muon-track invariant mass distribution onthe isolation requirement imposed onthe second muon isverifiedalsoby comparingshapesinthecontrol regions

N23 and N45.The latter CR isdefined by requiring the presence

of4or5“isolation”tracksnearbytothesecondmuon, whilethe firstmuon-trackpairpassesselectioncriteriaforthea1 candidate.

TheresultsareillustratedinFig.4.Aslightdifferenceisobserved between distributions in these two CRs. This difference is taken asashapeuncertaintyinthenormalizedtemplate f1D

(

j

)

entering

Eq. (3).

Fig.5presentsthenormalizedinvariantmassdistributionofthe muon-tracksystem fordata selectedin theSR andforthe back-groundmodelderivedfromtheN23 CR.Thedataandbackground

distributions are compared to the signal distributions, obtained fromsimulation,forfourrepresentativemasshypotheses,ma1=4, 7, 10,and 15GeV.The invariant mass ofthe muon-track system is found to havehigher discrimination power betweenthe back-groundandthesignalathigherma1.Forlowermasses,thesignal shape becomes morebackgroundlike, resultingina reduction of discriminationpower.

5.2. ModelingofC

(

i

,

j

)

In order to determine the correlation factors C

(

i

,

j

)

, an addi-tional CR (labelled Loose-Iso) is used. It consists of events that containtwoSCmuonspassingtheidentificationandkinematic se-lectioncriteriaoutlinedinSection4.Eachmuonisrequiredtohave twoorthreenearbytracks.Oneofthemshouldbelongtothe cate-goryof“signal”tracks,whereasremainingtracksshouldbelongto thecategoryof“soft”tracks.About36kdataeventsareselectedin thisCR.ThesimulationpredictsthattheQCDmultijetevents dom-inatethisCR,comprisingmorethan99%ofselectedevents.Itwas alsofoundthattheoverallbackground-to-signalratioisenhanced comparedtotheSRbyafactorof30to40,dependingonthemass hypothesis,ma1. Theeventsample inthisregion isused tobuild thenormalizeddistribution f2D

(

i

,

j

)

.Finally,thecorrelationfactors

C

(

i

,

j

)

areobtainedaccordingtoEq. (3) as

C

(

i

,

j

)

=

f2D

(

i

,

j

)

(

f1D

(

i

)

f1D

(

j

))

sym

Fig. 5. Normalizedinvariantmassdistributionofthemuon-tracksystemforevents passingthesignalselection.Observednumbersofeventsarerepresentedbydata pointswith errorbars.TheQCDmultijetbackgroundmodelisderivedfromthe controlregionN23.Alsoshownarethenormalizeddistributionsfromsignal

sim-ulationsforfourmasshypotheses,ma1=4,7,10,and15GeV (dashedhistograms),

whereasforhighermassesthe analysishasnosensitivity.Eacheventinthe ob-servedandexpectedsignaldistributionscontributestwoentries,correspondingto thetwomuon-tracksystemsineacheventpassingtheselection.Thesignal distri-butionsinclude2μ2τand4τcontributions.Thelowerpanelshowstheratioofthe observedtoexpectednumberofbackgroundeventsineachbinofthedistribution. Thegreyshadedarearepresentsthebackgroundmodeluncertainty.

Fig. 6. The(m1,m2)correlationfactorsC(i,j)withtheirstatisticaluncertainties,

derivedfromdataintheCRLoose-Iso.

where f1D

(

i

)

is the 1D normalized distribution withtwo entries

perevent(m1andm2).ThecorrelationfactorsC

(

i

,

j

)

derivedfrom

dataintheLoose-IsoCRarepresentedinFig.6.Toobtainestimates of C

(

i

,

j

)

in the signal region, the correlation factors derived in theLoose-IsoCRhavetobe correctedforthedifference inC

(

i

,

j

)

betweenthesignal regionandLoose-IsoCR. Thisdifferenceis as-sessedbycomparingsamplesofsimulatedbackgroundevents.The correlationfactors estimatedfromsimulationinthesignal region andtheLoose-IsoCRarepresentedinFig.7.

Fig. 7. The(m1,m2)correlationfactorsC(i,j)alongwith theirMCstatistical

un-certainties,derived fromsimulated samplesinthe (upper:signalregion, lower: Loose-IsoCR).

The correlationfactorsinthe signalregionare thencomputed as C

(

i

,

j

)

SR_data

=

C

(

i

,

j

)

CR_dataC

(

i

,

j

)

SR MC C

(

i

,

j

)

CR_MC

,

(5) where

•

C

(

i

,

j

)

_dataCR are correlation factorsderived fortheLoose-IsoCR indata(Fig.6);

•

C

(

i

,

j

)

SR_MC arecorrelationfactorsderivedfortheSRinthe sim-ulatedQCDmultijetsample(Fig.7,upper);

•

C

(

i

,

j

)

_MCCR are correlation factors derived for the Loose-IsoCR inthesimulatedQCDmultijetsample(Fig.7,lower).

Table 3

SystematicuncertaintiesandtheireffectontheestimatesoftheQCDmultijetbackgroundandsignal.

Source Value Affected sample Type Effect on the total yield Stat. unc. in C(i,j) 3–60% bkg. bin-by-bin –

Extrapolation unc. in C(i,j) – bkg. shape –

Unc. in f1D(i) – bkg. shape –

Integrated luminosity 2.5% signal norm. 2.5% Muon id. and trigger efficiency 2% per muon signal norm. 4% Track id. efficiency 4–12% per track signal shape 10–18% MC stat. unc. in signal yields 8–100% signal bin-by-bin 5–20% Theoretical uncertainties in the signal acceptance

μRandμFvariations signal norm. 0.8–2%

PDF signal norm. 1–2%

Theoretical uncertainties in the signal cross sections

μR,Fvariations (ggF) 5–7% signal norm. 5–7%

μR,Fvariations (other processes) 0.4–9% signal norm. <0.5%

PDF (ggF) 3.1% signal norm. 3.1%

PDF (other processes) 2.1–3.6% signal norm. <0.5%

Fig. 8. Thedistributionofthesignaltemplates f2D(i,j)inonerowformass

hy-pothesisma1=4GeV (upper)and 10GeV (lower).TheH→a1a1→2μ2τ (blue

histogram)andH→a1a1→4τ(redhistogram)contributionsareshown.The

nota-tionofthebinsfollowsthatofFig.2.

The difference incorrelation factors derived in the SR(Fig. 7, upper)andintheLoose-IsoCR(Fig.7,lower)usingtheQCD mul-tijetsampleistakenintoaccountasanuncertaintyinC

(

i

,

j

)

.

6. Modelingsignal

The signal templates are derived fromthe simulated samples oftheH

→

a1a1

→

4

τ

andH

→

a1a1

→

2

μ

2

τ

decays.The study

probes the signal strength modifier, defined as the ratio of the product of the measured signal cross section andthe branching

fraction into the 4

τ

final state

B(

H

→

a1a1

)B

2

(

a1

→

τ τ

)

to the

inclusive cross section of the H production predictedin the SM. The relative contributions from different production modesof H are defined by the corresponding cross sectionspredicted in the SM.ThecontributionoftheH

→

a1a1

→

2

μ

2

τ

decay,iscomputed

assumingthatthepartialwidthsofa1

→

τ τ

anda1

→

μμ

decays

satisfyEq. (1).

The invariant mass distribution of the muon-track system in the a1

→

μμ

decay channel peaks at the nominal value of the

a1 boson mass, while the reconstructed mass of the muon-track

system in the a1

→

τ τ

decay is typically lower, because of the

missingneutrinos.ThisiswhytheH

→

a1a1

→

2

μ

2

τ

signal

sam-ples have a largely different shape of the (m1

,

m2) distribution

compared totheH

→

a1a1

→

4

τ

signal samples.Fig.8compares

the (m1

,

m2) distributions unrolled in a one row between the

H

→

a1a1

→

4

τ

and H

→

a1a1

→

2

μ

2

τ

signal samplesfor mass

hypothesesma14GeV and10GeV.Thesignaldistributionsare nor-malized assuming the SM H production rate withthe branching fraction

B(

H

→

a1a1

)B

2

(

a1

→

τ τ

)

equalto0.2.

7. Systematicuncertainties

Table3liststhesystematicuncertaintiesconsideredinthe anal-ysisforbothsignalandbackground.

7.1. Uncertaintiesrelatedtothebackground

TheestimationoftheQCDmultijetbackgroundisbasedon ob-served data, therefore it is not affected by imperfections in the simulation,reconstruction,ordetectorresponse.

The shape of the background in the (m1

,

m2) distribution is

modeledaccordingtoEq. (3),whileitsuncertaintyisdominatedby uncertaintiesrelatedtothecorrelationfactorsC

(

i

,

j

)

(asdescribed inSection5.2).Additionally,itisalsoaffectedbytheshape uncer-taintyinthe1Dtemplate f1D

(

m

)

(asdiscussedinSection5.1).The

bin-by-binuncertaintiesinmasscorrelationfactorsC

(

i

,

j

)

,derived fromEq. (5), are composed of the statisticaluncertainties in ob-serveddataandsimulatedsamples,aspresentedinFigs. 6and7, andrangefrom3to60%.Theseuncertaintiesareaccountedforin thesignalextractionprocedurebyonenuisanceparameterperbin inthe (m1

,

m2)distribution [61].The systematicuncertainties

re-latedtotheextrapolationofC

(

i

,

j

)

fromtheLoose-IsoCRtotheSR are derivedfromthe dedicatedMC studyoutlinedinSection 5.2. Therelatedshapeuncertaintyisdeterminedbycomparing correla-tionfactors derivedinthesimulatedsamples,betweenthesignal regionandtheLoose-IsoCR.

In the case when

B(

H

→

a1a1

)

B

2

(

a1

→

τ τ

)

=

0

.

34,

branching fraction of the H decay into non-SM particles from Ref. [26],theimpactofpossiblesignalcontaminationinthe Loose-IsoCRisestimatedonabin-by-binbasis,anditisatmost2.8%in thebin(6

,

6) whichwas foundto haveanegligible effectonthe finalresults.ForallotherCRs,thesignalcontaminationwasfound tobewellbelow1%.

7.2. Uncertaintiesrelatedtosignal

Anuncertaintyof2.5%isassignedtotheintegratedluminosity estimate [62].

The uncertainty in the muon identification and trigger effi-ciencyisestimatedtobe2%foreachselectedmuonobtainedwith thetag-and-probe technique [63].The trackselection and muon-trackisolationefficiencyisassessedwitha studyperformedona sampleofZ bosonsdecayingintoa pairoftauleptons.Inthe se-lected Z

→

τ τ

events,one taulepton isidentified viaits muonic decay,while the other is identified asan isolated trackresulting froma one-prongdecay. The trackisrequired topass the nomi-nal selection criteria usedin the main analysis. From this study, the uncertainty in the track selection and isolation efficiency is evaluated. Therelated uncertaintyaffects theshape ofthe signal estimate, while changingthe overall signal yield by 10–18%. The muon and trackmomentum scale uncertainties are smaller than 0.3%andhaveanegligibleeffectontheanalysis.

Thebin-by-binstatisticaluncertaintiesinthesignal acceptance rangefrom8to100%,whiletheimpactontheoverallsignal nor-malizationvariesbetween5and20%.

Theoretical uncertainties have an impact on the differential kinematic distributions of the produced H, in particular its pT

spectrum,therebyaffectingsignalacceptance.Theuncertaintydue tomissinghigher-ordercorrectionstotheggF processisestimated with the HqT programby varying the renormalization (

μ

R) and

factorization(

μ

F)scales.TheH pT-dependentK factorsare

recom-puted accordingtothese variations andappliedto thesimulated signalsamples.Theresultingeffectonthesignalacceptanceis esti-matedtovarybetween1.2and1.5%,dependingonma1.Inasimilar way,theuncertaintyinthesignal acceptanceiscomputedforthe VBF, VHandt

¯

tH productionprocesses.The impacton the accep-tanceisestimatedtovarybetween0.8and2.0%,dependingonthe processandprobedmassofthea1 boson.

The HqT program is also used to evaluate the effect of the PDF uncertainties. The nominal K factors for the H pT spectrum

are computedwiththe NNPDF3.0PDF set [48]. Variations ofthe NNPDF3.0PDFswithintheiruncertaintieschangethesignal accep-tancebyabout1%,whilstusingtheCTEQ6L1PDFset [64] changes the signal acceptance by about 0.7%. The impact of the PDF un-certaintiesonthe acceptancefortheVBF,VHandt

¯

tH production processes is estimatedin the same wayand a 2% uncertaintyis consideredtoaccountforthese.

Systematicuncertaintiesintheoreticalpredictionsforthesignal crosssectionsaredrivenbyvariationsofthe

μ

Rand

μ

Fscalesand

PDF uncertainties. Uncertainties related to scale variations range from0.4to9%, dependingon theproductionmode.Uncertainties relatedtoPDFvarybetween2.1and3.6%.

8. Results

The signal is extractedwitha binned maximum-likelihoodfit appliedtothe (m1

,

m2) distribution.Foreach probedmassofthe

a1 boson,the(m1

,

m2)distribution isfittedwiththe sumoftwo

templates,corresponding to expectationsforthesignal and back-ground,dominatedbyQCDmultijetevents.

The normalizationof both signal andbackground are allowed to float freely in the fit. The systematic uncertainties affecting

Fig. 9. The (m1,m2)inonerowdistributionusedtoextractthesignal.Observed

numbersofeventsarerepresentedbydatapointswitherrorbars.Thebackground withitsuncertaintyisshownasthebluehistogramwiththeshadederrorband. Theshapeandthenormalizationofthebackgrounddistributionareobtainedby applyingafittotheobserveddataunderthebackground-onlyhypothesis.Signal expectationsforthe4τand2μ2τ finalstatesareshownasdottedhistogramsfor themasshypothesesma1=4,7,10and15GeV.Therelativenormalizationofthe4τ

and2μ2τfinalstatesaregivenbyEq. (1) asexplainedinSection6.Thesignal nor-malizationiscomputedassumingthattheH bosonisproducedinpp collisionswith aratepredictedbytheSM,anddecaysintoa1a1→4τfinalstatewiththe

branch-ingfractionof20%.Thelowerplotshowstheratiooftheobserveddataeventsto theexpectedbackgroundyieldineachbinofthe(m1,m2)distribution.

the normalizationofthesignal templates areincorporatedin the fit via nuisance parameters with a log-normal prior probability density function. The shape-altering systematic uncertainties are represented by nuisance parameters whose variations cause con-tinuousmorphingofthesignalorbackgroundtemplateshape,and are assigned a Gaussian prior probability density functions. The bin-by-binstatisticaluncertaintiesareassignedgammaprior prob-abilitydensityfunctions.

Fig.9showsthedistributionof(m1

,

m2),wherethenotationfor

thebinsfollowsthatofFig.2.Theshapeandthenormalizationof the backgrounddistributionare obtainedby applyinga fitto the observeddataunderthebackground-onlyhypothesis.Alsoshown are the expectations for thesignal atma1=4, 7, 10,and 15GeV. ThesignalnormalizationiscomputedassumingthattheH is pro-ducedinpp collisionswitharatepredictedbythestandardmodel, anddecaysintoa1a1

→

4

τ

finalstatewithabranchingfractionof

20%.Nosignificantdeviationsfromthebackgroundexpectationare observedinthe(m1

,

m2)distribution.

Results of the analysis are used to set upper limits at 95% CL on the product of the cross section and branching fraction,

σ

(

pp

→

H

+

X

)B(

H

→

a1a1

)B

2

(

a1

→

τ τ

)

, relative to the

inclu-sive SM cross section of H production. The modified frequentist CLs criterion [65,66], and the asymptotic formulae are used for

the test statistic [67], implemented inthe RooStats package [68]. Fig. 10showsthe observed andexpectedupperlimitsat 95% CL onthesignalcrosssectiontimesthebranchingfraction,relativeto the totalcross sectionof theH bosonproductionaspredictedin theSM. Theobservedlimit iscompatiblewiththe expectedlimit within one standard deviationinthe entirerangeof ma1 consid-ered,andrangesfrom0.022atma1

=

9GeV to0.23atma1

=

4GeV andreaches0.16atma1

=

15GeV.Theexpectedupperlimitranges from 0.027 at ma1

=

9GeV to 0.16 at ma1

=

4GeV and reaches 0.19 atma1

=

15GeV.The degradation ofthe analysis sensitivity towardslowervaluesofma1 iscausedbytheincreaseofthe back-groundyield atlow invariant massesofthe muon-tracksystems, asillustratedinFigs.5and9.Withincreasingma1,theaverage

an-Fig. 10. Theobservedandexpectedupperlimitsat95%confidencelevelsonthe productofsignalcrosssectionandthebranchingfractionσ(pp→H+X)B(H→ a1a1)B2(a1→τ τ),relativetotheinclusiveHiggsbosonproductioncrosssection

σSMpredictedintheSM.Thegreenandyellowbandsindicatetheregionsthat

con-tain68%and95%ofthedistributionoflimitsexpectedunderthebackground-only hypothesis.Theshadedareainblueindicatestheexcludedregionof>34%forthe branchingfractionoftheH decayintonon-SMparticlesat95%CL fromRef. [26].

gular separation between the decay products of the a1 boson is

increasing.Asaconsequence,theefficiencyofthesignalselection drops down, aswe require the muon and the track, originating fromthea1

→

τ

μ

τ

one-prongora1

→

μμ

decay,tobewithinacone

of



R

=

0

.

5.Thisexplainsthedeteriorationofthesearch sensitiv-ityathighervaluesofma1.The shadedarea inblueindicatesthe excludedregionof

>

34%forthebranchingfractionoftheH decay intonon-SMparticlesat95%CL [26].

The new limits improve significantly over the previous 8TeV limits [28] by30%(forlowmasses)andupto80%(for intermedi-atemassesof8GeV),while thenewanalysisfurther extendsthe coverageofma1 upto15GeV.

9. Summary

A search is presented for light pseudoscalar a1 bosons,

pro-ducedfromdecaysofthe 125GeV Higgsboson (H) ina dataset correspondingto anintegratedluminosity of35

.

9fb−1 of proton-protoncollisionsatacenter-of-massenergyof13TeV.Theanalysis isbasedontheH inclusiveproductionandtargetstheH

→

a1a1

→

4

τ

/

2

μ

2

τ

decaychannels. Both channelsareusedincombination to constrain the product of the inclusive signal production cross sectionandthebranchingfractionintothe4

τ

finalstate, exploit-ingthelineardependenceofthefermioniccouplingstrengthofa1

onthefermionmass.Withnoevidenceforasignal,theobserved 95% confidencelevel upper limit onthe product of the inclusive signalcrosssectionandthebranchingfraction,relative totheSM H productioncross section, ranges from0.022 atma1

=

9GeV to 0.23 at ma1

=

4GeV and reaches 0.16 at ma1

=

15GeV. The ex-pected upper limit ranges from0.027 at ma1

=

9GeV to 0.16at

ma1

=

4GeV andreaches0.19atma1

=

15GeV.

Acknowledgements

WecongratulateourcolleaguesintheCERNaccelerator depart-ments for the excellent performance of the LHC and thank the technicalandadministrativestaffs atCERN andatother CMS in-stitutes for their contributions to the success of the CMS effort. Inaddition,wegratefullyacknowledgethecomputingcentersand

personneloftheWorldwideLHCComputingGridfordeliveringso effectivelythe computinginfrastructureessential to ouranalyses. Finally, we acknowledge the enduring support for the construc-tionandoperation oftheLHC andtheCMSdetectorprovidedby thefollowing fundingagencies:BMBWF andFWF(Austria); FNRS and FWO(Belgium); CNPq,CAPES, FAPERJ, FAPERGS, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MOST, and NSFC (China); COLCIENCIAS (Colombia); MSES andCSF (Croatia); RPF (Cyprus); SENESCYT (Ecuador); MoER, ERC IUT, PUT and ERDF (Estonia); AcademyofFinland,MEC,andHIP(Finland);CEAandCNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); NK-FIA (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN(Italy);MSIPandNRF(RepublicofKorea);MES(Latvia);LAS (Lithuania);MOEandUM(Malaysia);BUAP,CINVESTAV,CONACYT, LNS,SEP,andUASLP-FAI(Mexico);MOS(Montenegro);MBIE(New Zealand); PAEC (Pakistan); MSHE and NSC (Poland); FCT (Portu-gal);JINR(Dubna); MON,ROSATOM,RAS, RFBR,andNRCKI (Rus-sia);MESTD(Serbia);SEIDI,CPAN,PCTI,andFEDER(Spain);MoSTR (Sri Lanka); Swiss Funding Agencies(Switzerland); MST (Taipei); ThEPCenter,IPST,STAR,andNSTDA(Thailand);TUBITAKandTAEK (Turkey);NASUandSFFR(Ukraine); STFC(United Kingdom);DOE andNSF(USA).

Individuals have received support from the Marie-Curie pro-gramandtheEuropeanResearchCouncilandHorizon2020Grant, contract Nos. 675440, 752730, and 765710 (European Union); the Leventis Foundation; the A.P. Sloan Foundation; the Alexan-der von Humboldt Foundation; the Belgian Federal Science Pol-icy Office; the Fonds pour la Formation à la Recherche dans l’Industrie et dans l’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the F.R.S.-FNRSand FWO(Belgium) underthe “Excellence of Sci-ence – EOS” – be.h project n. 30820817; the Beijing Municipal Science & Technology Commission, No. Z181100004218003; the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Lendület (“Momentum”) Program and the János Bolyai Research Scholarship of the Hungarian Academy of Sci-ences, the New National Excellence Program ÚNKP, the NKFIA researchgrants123842,123959,124845,124850,125105,128713, 128786, and 129058 (Hungary); the Council of Science and In-dustrial Research,India;theHOMING PLUSprogramofthe Foun-dation for Polish Science, cofinanced from European Union, Re-gional Development Fund, the Mobility Plus program of the Ministry of Science and Higher Education, the National Science 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;theNationalPriorities Re-search Programby QatarNationalResearchFund;the Ministryof Science and Education, grant no. 3.2989.2017 (Russia); the Pro-gramaEstatalde Fomento delaInvestigación CientíficayTécnica de Excelencia María de Maeztu, grant MDM-2015-0509 and the Programa Severo Ochoa del Principado de Asturias; the Thalis andAristeiaprogramscofinancedbyEU-ESF andtheGreek NSRF; theRachadapisekSompotFundforPostdoctoralFellowship, Chula-longkornUniversityandtheChulalongkornAcademic intoIts2nd CenturyProjectAdvancementProject(Thailand);TheWelch Foun-dation,contractC-1845;andtheWestonHavensFoundation(USA).

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TheCMSCollaboration

A.M. Sirunyan,

A. Tumasyan

YerevanPhysicsInstitute,Yerevan,Armenia

W. Adam,

F. Ambrogi,

E. Asilar,

T. Bergauer,

J. Brandstetter,

M. Dragicevic,

J. Erö,

A. Escalante Del Valle,

M. Flechl,

R. Frühwirth

1

,

V.M. Ghete,

J. Hrubec,

M. Jeitler

1

,

N. Krammer,

I. Krätschmer,

D. Liko,

T. Madlener,

I. Mikulec,

N. Rad,

H. Rohringer,

J. Schieck

1

,

R. Schöfbeck,

M. Spanring,

D. Spitzbart,

W. Waltenberger,

J. Wittmann,

C.-E. Wulz

1

,

M. Zarucki

InstitutfürHochenergiephysik,Wien,Austria

V. Chekhovsky,

V. Mossolov,

J. Suarez Gonzalez

InstituteforNuclearProblems,Minsk,Belarus

E.A. De Wolf,

D. Di Croce,

X. Janssen,

J. Lauwers,

A. Lelek,

M. Pieters,

H. Van Haevermaet,

P. Van Mechelen,

N. Van Remortel

UniversiteitAntwerpen,Antwerpen,Belgium

F. Blekman,

J. D’Hondt,

J. De Clercq,

K. Deroover,

G. Flouris,

D. Lontkovskyi,

S. Lowette,

I. Marchesini,

S. Moortgat,

L. Moreels,

Q. Python,

K. Skovpen,

S. Tavernier,

W. Van Doninck,

P. Van Mulders,

I. Van Parijs

VrijeUniversiteitBrussel,Brussel,Belgium

D. Beghin,

B. Bilin,

H. Brun,

B. Clerbaux,

G. De Lentdecker,

H. Delannoy,

B. Dorney,

G. Fasanella,

L. Favart,

A. Grebenyuk,

A.K. Kalsi,

J. Luetic,

A. Popov

2

,

N. Postiau,

E. Starling,

L. Thomas,

C. Vander Velde,

P. Vanlaer,

D. Vannerom,

Q. Wang

UniversitéLibredeBruxelles,Bruxelles,Belgium

T. Cornelis,

D. Dobur,

A. Fagot,

M. Gul,

I. Khvastunov

3

,

C. Roskas,

D. Trocino,

M. Tytgat,

W. Verbeke,

B. Vermassen,

M. Vit,

N. Zaganidis

GhentUniversity,Ghent,Belgium

O. Bondu,

G. Bruno,

C. Caputo,

P. David,

C. Delaere,

M. Delcourt,

A. Giammanco,

G. Krintiras,

V. Lemaitre,

A. Magitteri,

K. Piotrzkowski,

A. Saggio,

M. Vidal Marono,

P. Vischia,

J. Zobec

UniversitéCatholiquedeLouvain,Louvain-la-Neuve,Belgium

F.L. Alves,

G.A. Alves,

G. Correia Silva,

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,

C. De Oliveira Martins,

S. Fonseca De Souza,

L.M. Huertas Guativa,

H. Malbouisson,

D. Matos Figueiredo,

M. Melo De Almeida,

C. Mora Herrera,

L. Mundim,

H. Nogima,

W.L. Prado Da Silva,

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

,

L. Calligaris

a

,

T.R. Fernandez Perez Tomei

a

,

E.M. Gregores

b

,

P.G. Mercadante

b

,

S.F. Novaes

a

,

Sandra

S. Padula

a

a_{UniversidadeEstadualPaulista,SãoPaulo,Brazil} b_{UniversidadeFederaldoABC,SãoPaulo,Brazil}

A. Aleksandrov,

R. Hadjiiska,

P. Iaydjiev,

A. Marinov,

M. Misheva,

M. Rodozov,

M. Shopova,

G. Sultanov

InstituteforNuclearResearchandNuclearEnergy,BulgarianAcademyofSciences,Sofia,Bulgaria

A. Dimitrov,

L. Litov,

B. Pavlov,

P. Petkov

UniversityofSofia,Sofia,Bulgaria

W. Fang

6

,

X. Gao

6

,

L. Yuan

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,

S.M. Shaheen

7

,

A. Spiezia,

J. Tao,

E. Yazgan,

H. Zhang,

S. Zhang

7

,

J. Zhao

InstituteofHighEnergyPhysics,Beijing,China

Y. Ban,

G. Chen,

A. Levin,

J. Li,

L. Li,

Q. Li,

Y. Mao,

S.J. Qian,

D. Wang

StateKeyLaboratoryofNuclearPhysicsandTechnology,PekingUniversity,Beijing,China

Y. Wang

TsinghuaUniversity,Beijing,China

C. Avila,

A. Cabrera,

C.A. Carrillo Montoya,

L.F. Chaparro Sierra,

C. Florez,

C.F. González Hernández,

M.A. Segura Delgado

UniversidaddeLosAndes,Bogota,Colombia

J.D. Ruiz Alvarez

UniversidaddeAntioquia,Medellin,Colombia

N. Godinovic,

D. Lelas,

I. Puljak,

T. Sculac

UniversityofSplit,FacultyofElectricalEngineering,MechanicalEngineeringandNavalArchitecture,Split,Croatia