Search for pair production of vector-like quarks in thebWb‾Wchannel from proton–proton collisions ats=13TeV

Contents lists available atScienceDirect

Physics

Letters

B

www.elsevier.com/locate/physletb

Search

for

pair

production

of

vector-like

quarks

in

the

bWbW channel

from

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:

Received4October2017

Receivedinrevisedform23December2017 Accepted30January2018

Availableonline3February2018 Editor:M.Doser

Keywords:

CMS Physics Vector-likequarks

A searchis presented for theproductionof vector-likequark pairs,TT or YY,with electricchargeof 2/3 (T) or−4/3 (Y),inproton–protoncollisions at√s=13TeV.The datawerecollectedbythe CMS experiment attheLHCin2016and correspondtoanintegratedluminosity of35.8fb−1.The T andY quarksareassumedtodecayexclusivelytoaW bosonandab quark.Thesearchisbasedoneventswith asingleisolatedelectronormuon,largemissingtransversemomentum,andatleastfourjetswithlarge transversemomenta.Inthesearch,akinematicreconstructionofthefinalstateobservablesisperformed, which would permitasignal to be detectedas a narrowmass peak(≈7%resolution). The observed numberofeventsisconsistentwiththestandardmodelprediction.Assumingstrongpairproductionof thevector-likequarksanda100%branchingfractiontobW,alowerlimitof1295 GeV at95%confidence levelissetontheT andY quarkmasses.

©2018TheAuthor(s).PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCCBYlicense (http://creativecommons.org/licenses/by/4.0/).FundedbySCOAP3_.

1. Introduction

Vector-like quarks (VLQs) are hypothetical spin-1/2 fermions, whoseleft- and right-handedcomponents transforminthesame way under the standard model (SM) symmetries, and hence have vector couplings. Nonchiral VLQs appear in a number of beyond-the-SM scenarios, such as “Randall–Sundrum” and other extra-dimensional models [1,2]; the beautiful mirrors [3], little Higgs[4–8],and compositeHiggs [9]models; grand unified the-ories [10]; and also other models that provide insights into the SM flavorstructure [11]. Thesemodelsprovide possiblesolutions to a number of problems, such as electroweak symmetry break-ing,apoorgeneralfittotheprecisionelectroweakdata,theorigin of flavor patterns, and the hierarchy problem. In particular, the hierarchy problem, namely the instability within the SM of the Higgsbosonmassparametertoquantumcorrections,canbesolved throughtheintroductionofVLQcontributionsthatcancelthe con-tributionsfromthetopquark.

Ingeneral,VLQsT,withcharge

+

2/3,areexpectedtomix sig-nificantlyonlywiththetopquark,leadingtothedominantT quark decayT

→

bW[12].Weconsiderthecaseinwhichthisdecayhas abranchingfraction

B(

T

→

bW)

=

100%.Alsoinsomemodels[13], aVLQ Y withan electricchargeof

−

4/3ispredicted, eitherwith

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

or without thepresence of a T VLQ. The Y quark isexpected to decay witha 100% branching fraction via thesame bW channel. Since jets originatingfrom the hadronization of b quarks and b antiquarks are not distinguished in thisanalysis, the results pre-sentedapply equally tothestrong pairproductionofboth T and Y VLQs. WeconsiderthecasewhereeitheronlyT quarksoronly Y quarksare produced.Thisassumptionproduces amore conser-vativeestimationofthelowermasslimitonVLQs.Throughoutthe rest of this paper, we will use T to representboth the T and Y VLQs.

In thispaper, results are presentedof a search forthe strong pair production of heavy VLQs and their subsequent decays throughthesignalchannel

TT

→

bWbW

→

b



ν

bqq

inproton–proton(pp)collisionsat

√

s

=

13TeV usingtheCMS de-tector at the CERN LHC, where



is an electron or muon from the leptonicdecayofone oftheW bosons, andq andq are the quark andantiquarkfromthehadronicdecayoftheotherW bo-son.Theanalyzeddatasetcorrespondstoanintegratedluminosity of 35.8fb−1. This analysis is an extension to higher mass values of anearlierCMSsearch forthe T quarkat

√

s

=

8TeV. Both the previous analysis andthe present one are based on a kinematic reconstruction with a constrainedfit to the bWbW final state in the signal decay channel shown above. Kinematic reconstruction

https://doi.org/10.1016/j.physletb.2018.01.077

0370-2693/©2018TheAuthor(s).PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCCBYlicense(http://creativecommons.org/licenses/by/4.0/).Fundedby SCOAP3_.

enablesdetection ofthe signal asa narrow mass peak. The pre-viousresultswere combinedwithotherCMST quarksearchesin Ref. [14]. The present observed lower mass limitsfor a T quark decaying 100% via the bW channel are 920 GeV for CMS [14] at

√

s

=

8TeV,and770 GeV at8 TeV[15] and1350 GeV at13 TeV for ATLAS[16].

Thesearch strategy requiresthat one oftheW bosons decays leptonically, producing an electron or a muon accompanied by a neutrino, andtheother decays hadronicallyto a quark–antiquark pair. We select events with a single isolated muon or electron, missing transverse momentum, and at least four jets with high transversemomenta,arisingfromthehadronizationofthequarks inthefinalstate.Weclassifysucheventsas

μ

+jetsore+jets.

Weperformaconstrainedkinematicfitoneachselectedevent forthesignaldecayprocessshownabove.Thefullkinematic quan-titiesofthe final state are reconstructed, andthe invariant mass ofthe T quark, mreco, is obtained. We consider also cases when WbosonsdecayinghadronicallyathighLorentzboostsare recon-structed as single jets. Such merged jets are then resolved into two subjets by employing jet substructure techniques based on the“softdrop”groomingalgorithm[17].Theseresolvedsubjetsare countedindividually whenselectingfour-jet final statesand con-tributeseparately inthekinematicfit(seeSection 5).Events with leptonically decaying W bosons include those decaying into a

τ

lepton(inthedecaysequenceW

→

τ

+

ν,

τ

→ 

+

2ν).Theyare treatedinthesamewayaseventswithdirectdecaystomuonsor electrons.

2. TheCMSdetector

The central feature of the CMS apparatus is a superconduct-ing solenoidof 6 m internal diameter,providing a magnetic field of 3.8 T. Within the superconducting solenoid volume are a sili-con pixel and strip tracker, a lead tungstate crystal electromag-neticcalorimeter(ECAL)withpreshowerdetector,andabrassand scintillatorhadron calorimeter(HCAL),each composedofabarrel andtwo endcapsections. Forwardcalorimeters extendthe pseu-dorapidity [18] coverage provided by the barrel and endcap de-tectors. The detectoris nearly hermetic, allowing formomentum balancemeasurementsintheplanetransversetothebeam direc-tion.Muonsaredetectedingas-ionizationchambersembeddedin thesteelflux-returnyokeoutsidethesolenoid.

AmoredetaileddescriptionoftheCMSdetector,togetherwith adefinitionofthecoordinatesystemusedandtherelevant kine-maticvariables,canbefoundinRef.[18].

3. Eventsamples

Theanalysisisbasedonintegratedluminositiesof35.8fb−1 in themuonchanneland35.6fb−1intheelectronchannel.The trig-gerproviding the muon data sample requires the presence ofat least one muon with pT

>

50GeV and pseudorapidity

|

η

| <

2.5. Fortheelectrondatasample,eventsarerequiredtohavea single isolatedelectronwithpT

>

32GeV and

|

η

| <

2.1.

Simulatedeventsamples are used to estimate the signal effi-cienciesandbackgroundcontributions. The followingbackground production processes are modeled: tt+jets; W+jets and Z+jets (single boson production); single top quark via the tW, s- and t-channel processes; WW, WZ,and ZZ(diboson production); and quantum chromodynamic (QCD) multijet production. The domi-nantbackgroundisfrom tt+jetsproduction.Allother background processes are collectively referred to as non-tt. The non-tt back-groundexcludingmultijetsiscalledtheelectroweakbackground.

The tt

+

jets events are generated using the powheg v2.0

[19–22] event generator. The diboson samples are produced

us-ing the pythia 8.205[23] generator. TheW+jets, Z+jets,andQCD multijet simulatedevents are produced withthe generator Mad-Graph_{5_amc@nlo v2.2.2}

[24]

_{.Single top quark eventsare} gener-atedwith powheg and MadGraph5_amc@nlo.

The simulated TT signal events are generated with Mad-Graph_{5_amc@nlo at leading order for T quark massesfrom 800} to1600 GeV in 100 GeV steps.The totalTT inclusivecrosssection (gg

→

TT

+

X ) iscomputedforeach T quarkmass valueat next-to-next-to-leading order, using a soft-gluon resummation with next-to-next-to-leading-logarithmic accuracy [25]. Signal samples are produced in the narrow-width approximation in which the widthofthegeneratedT quarkmassdistributionof1 GeV ismuch lessthanthemassresolutionofthedetector.

The generatedeventsare processedthrough theCMSdetector simulationbasedon Geant4[26].Additionalminimum-biasevents, generated with pythia, are superimposed on the hard-scattering eventsto simulatemultipleinelasticpp collisions inthe sameor nearbybeamcrossings(pileup).Thesimulatedeventsareweighted toreproducethedistributionofthenumberofpileupinteractions observedindata,withanaverageof23collisionsperbeam cross-ing.AllsampleshavebeengeneratedwiththeNNPDF3.0set[27]

ofpartondistributionfunctions(PDFs),usingthetuneCUETP8M1. pythiaisusedtoshowerandhadronizeallgeneratedpartons.

4. Eventreconstruction

Events are reconstructed using a particle-flow (PF) algorithm

[28] that combines informationfrom all the subdetectors:tracks inthe silicontrackerandenergydepositsin theECALandHCAL, as well as signalsin the preshower detector andthe muon sys-tem.Thisprocedurecategorizesallparticlesintofivetypes:muons, electrons, photons, and charged andneutral hadrons. An energy calibrationisperformedseparatelyforeachparticletype.

Muon candidates are identified by multiple reconstruction al-gorithms based on hits in the silicon tracker and signals in the muonsystem. Thestandalone-muonalgorithmusesonly informa-tionfromthemuonchambers.Thesilicontrackermuonalgorithm starts from tracks found in the silicon tracker and then asso-ciates them withmatching signalsin the muon detectors.In the global-muonalgorithm,foreach standalone-muon tracka match-ing trackermuon is found by comparing parameters of the two tracks propagated onto a common surface. A global-muon track isfittedbycombininghitsfromthesilicontrackermuonandthe standalone-muontrack,usingtheKalman-filtertechnique[29].The PFalgorithmusesglobalmuons.

Electron candidates are reconstructed fromclusters of energy deposited intheECALmatched withtracksinthesilicon tracker. Electron tracks are reconstructed using a dedicated modeling of theelectronenergylossandarefittedwithaGaussiansumfilter algorithm.Finally,electronsarefurtherdistinguishedfromcharged hadronsusingamultivariateapproach[30].

Charged leptons, originating from decays of heavy VLQs, are expectedtobeisolatedfromnearbyjets.Therefore,arelative isola-tionparameter(Irel)isused,whichisdefinedasthesumofthe pT ofchargedhadrons, neutralhadrons, andphotonsinacone with distanceparameter



R

=



(φ)

2

_{+ (}

_η)

2 _{around thelepton} di-rection,where

φ

and

η

are theazimuthal andpseudorapidity differences, dividedbythe lepton pT.The isolationconeradius is takenas



R

=

0.4 for muons.Pileupcorrectionsto Irel are com-putedusingtracksfromreconstructed vertices[29].Forelectrons,



R

=

0.3 andpileupcorrectionsarecalculatedusingjet effective areas[31,32]separatelyforthebarrelandendcapregions.

Particlesfound by thePFalgorithm are clusteredintojets us-ing the PF jet identification procedure [28]. Using the charged-hadron subtraction (CHS) algorithm, charged hadrons associated

with pileup vertices are not considered, and particles that are identifiedasisolated leptons are removed fromthejet clustering procedure.Inthe analysis,two typesofjetsareused: jets recon-structedusingtheanti-kTalgorithm[33]withdistanceparameters ofeither R

=

0.4 (AK4) or0.8(AK8), as implementedin FastJet v3.0.1[34,35].Anevent-by-eventjetarea-basedcorrection [31,32, 36,37]isappliedto removeon astatisticalbasispileup contribu-tionsthatarenotalreadyremovedbytheCHSprocedure.

Since most jet constituents are identified and reconstructed withclose toa correct energyby the PFalgorithm, only a small residualenergycorrection mustbe appliedtoeachjet.These cor-rectionswereobtainedasafunctionofjet pT and

η

froma com-parison of Geant4-based CMS Monte Carlo (MC) simulation [38]

andcollisiondata.Jetenergycorrections(JEC)areappliedtoeach jetasafunctionof

p

T and

η

.

Fortheidentificationofjetsoriginatingfromthehadronization ofab quark(b-tagged jets)we usethecombinedsecondary ver-tex(CSVv2) algorithm[39].This provides b taggingidentification by combining information about impact parameter significance, secondary vertex reconstruction, and jet kinematic distributions. We use two operating points: medium (CSVM), with a mistag-ging rate of 1%, and loose (CSVL), with a 10% mistagging rate, forwhichtheefficiencies ofcorrectlytaggingjetscomingfromb quarkhadronizationare66%and82%,respectively[39].The differ-encesinthe performance ofthe b tagging algorithmindata and MCsimulationareaccountedforbydata/MCscalefactors(SFs).

Themissingtransversemomentuminanevent,

p

miss

T ,isdefined as the magnitude of the missing transverse momentum vector, whichis theprojection onthe plane perpendicularto thebeams of the negative vector sum of the momenta of all reconstructed particlesintheevent.Thevertexwiththehighestsumofsquared

pT ofallassociatedtracksistakenasthehard-scatteringprimary vertex.

5. Eventselectionandmassreconstruction

Selected events are required to contain exactly one charged lepton(muonor electron).Muon candidatesare requiredto have

pT

>

55GeV and

|

η

| <

2.4. Therelativemuon isolationparameter mustsatisfy Irel

<

0.15. Selectedelectrons should have

|

η

| <

2.1. Toensurethatthee+jetschannelcoversasimilarkinematicphase spacetothe

μ

+jets channel,electron candidatesmustsatisfy the same pT

>

55GeV requirement. Simulation shows that lowering the

p

T thresholdwouldnotimprovethesignalsignificance.Events with a second more loosely identified electron or muon, with

pT

>

20GeV and

|

η

| <

2.5 (2.4)forelectrons(muons),arevetoed. At the next step, we select a collection of jetsthat are used asinputtothekinematicfit.ThecollectionincludesAK4jetsthat have pT

>

30 GeV and

|

η

| <

2.4, and AK8 jetsthat satisfy pT

>

200 GeV and

|

η

| <

2.4.Aselectedeventmusthaveeitheratleast fourAK4jets,oratleastthreeAK4jetsandatleastoneAK8jetfor thecasewherethe AK8jet overlapsanAK4jet(see explanations below).Thisisneededtosatisfy therequirementtohaveatleast fourjetsinthefinaljetcollectionusedforthekinematicfit.

AsthemassofaheavyVLQincreases,thereconstructed topol-ogy of its decay is modified by the overlapping andmerging of jetsowing to thehigh Lorentz boosts its decayproducts receive. Thequark pairfromthehadronically decayingW bosonbecomes increasingly collimated, producing overlapping hadronic showers thatcannotberesolvedasseparatejets.Thisprecludesperforming constrainedkinematicfitsthatusejetsasproxiesforthefinal-state quarksinthesignaldecayprocess.

TheAK8jetsareusedtoidentifythemergedhadronicWboson decaysby applyingthe“softdrop”(SD)grooming algorithm[17], withparameters

z

cut

=

0.1 and

β

=

0.Thisprocedureremovessoft

andwide-angleradiationfromjetsandresolvestheinternal struc-tureofthewide jetintotwo distinctsubjets,associatedwiththe underlying W boson decay.The JECsthat are applied to theAK8 jetsarepropagated tothepairofsubjetsby scalingthemso that thesumoftheirfour-momentaisequaltotheparentAK8jet four-momentum.Thegroomedjetmass,calledthesoftdropmass,

m

SD, is takenasthe invariant mass ofthe constituentsof theAK8 jet withtheSD algorithmapplied,andthusisequal totheinvariant mass ofthetwosubjets.It isrequiredto bewithin theW boson mass window 60

<

mSD

<

100GeV, inwhich case theAK8 jet is labeled“W-tagged”.

ForeachW-taggedAK8jet,representinganidentifiedfootprint ofahighly boosted,hadronicallydecayingWboson,wesearchfor thecorrespondingfootprintofthesameWbosondecayintheAK4 jetcollection.ThisisdonebytryingtomatchaW-taggedAK8jet to an AK4 jet orto the vector sum ofa pair ofnearby AK4jets for which



R

(AK8,

AK4) <0.8. Since the opening angle of AK8 subjets, resolved by the SDalgorithm, can go down up to



R

=

0.15, the system of the two subjets represents a more accurate assignmentofjetconstituentstotwoseparatesubjetscomparedto theclusteringintotwoAK4jets,withtheir morecoarsethreshold of



R

=

0.4.Amatchrequires



R

(

A K 8

,

A K 4

)

= 

Rmatch

<

0.05. Matching witha pairofAK4jetsis preferredto amatchingwith onlyoneAK4jet,whenthe



Rmatch valueforthat pairissmaller than thevaluesforanyofthe singlejetsinthe pair.Inthiscase matchingwiththepair(representedbythevectorsumofthetwo AK4momenta)providesthebestassociationofAK4/AK8jets.

A matched AK4 jet is replaced by the two subjets of the W-taggedAK8jet,thususingthefullkinematicinformationobtained by theWtaggingandincludingthatintoajet collectionusedfor thekinematicfit.Thisprocedureresultsinahybridjetcollection, consistingofAK4jetsleftunmatchedandsubjetsofW-taggedAK8 jets,thusexcludingthepossibilityofdoublecountingthejetslater usedasinputtothekinematicfit.

Onlythejetsinthehybridcollectionareusedintherestofthe analysis. Asetofpreselectionrequirementsisnowapplied tothe event:

•

The missingtransverse momentum inthe eventmustsatisfy

pmiss_T

>

30GeV.Thisrequirementisdesignedtobothselect fi-nalstatescontainingneutrinoandsuppressQCDmultijet back-groundcontribution.

•

Each of the jets must have pT

>

30GeV and

|

η

| <

2.4 (these requirements were not applied to the newly included W-tagged subjets).

•

Jetstooclosetotheleptondirectionarediscardedbyrequiring



R

(jet,

)

>

0.4.

•

Theremustbeatleast4remainingjetsintheeventafterthe previouscriteria.

•

Thetwohighest-pT jetsmustsatisfy

p

T

>

100 and70 GeV, re-spectively.

Eventsthatpassalltheserequirementsareusedasinputtothe kinematic fit, which is performedusing the HitFit package [40]. ThisfittingprogramwasdevelopedbytheD0experiment[41]for themeasurementofthetopquarkmassinthelepton+jetschannel. Itcontainsafittingengine,whichminimizesa

χ

2 _{quantitysubject} toasetofconstraints,andaninterface.

The inputtothefittingenginecomprises thetwo-dimensional vector p



miss_T andthemeasuredthree-dimensionalmomentaofthe chargedleptonandfourjets.The fourquarksinthefinalstate of the signaldecayprocess manifestthemselvesasjetswhose mea-suredthree-momentaareusedasestimatesofthequarkmomenta. The

p

miss

T intheeventisusedasanestimateofthetransverse mo-mentumoftheneutrino.Theunmeasuredlongitudinalcomponent

oftheneutrinomomentumiscalculatedfromoneofthekinematic constraintsshowninEqs.(1)and

(3)

below.

The fit isperformed by minimizing a

χ

2 _{computed fromthe} differences between the measured momentum components and their fitted values, divided by the corresponding uncertainties, summedover all thereconstructed objectsin thefinal state. The fitissubjecttothefollowingconstraints:

m

(

ν

)

=

mW

,

(1)

m

(

qq

)

=

mW

,

(2)

m

(

ν

b

)

=

m

(

qqb

)

=

mreco

,

(3)

where mW is the W boson mass [42],



stands for electron or muon, and

,

ν

, b can denote either a particle or antiparti-cle. Equation (2) requires that the invariant mass of the quark– antiquark pair equals the W boson mass. Equation (3) demands thatthereconstructedinvariantmasses

m

reco ofthetwoproduced T quarks are equal. After one constraint is used for the calcula-tionofthe longitudinalneutrinomomentum, twoconstraints are left.Tochecktowhatextenttheassumedkinematichypothesisis compatiblewiththefittedmomenta,aso-called“goodness-of-fit” iscalculated,given bythe probability P

(χ

2

_≥

_χ

2

min

)

for the

χ

2 min valueobtainedafterminimization.

Foreventswithexactly4jets,alljetpermutationsinwhichjets areassignedspecificquarkrolesinthefinalstateofthesignal pro-cessarepreparedbythe HitFit interfaceandenteredinturninto thefittingengine.Iftherearemorethanfourjetsinanevent pass-ingthejetrequirements,thenthefivejetswiththehighest

p

T are consideredandallpermutationsoffourjetsoutoffiveareusedas inputto the fitter.Thecalculation ofthe longitudinalcomponent oftheneutrinomomentumhasatwo-foldambiguityfromsolving a quadratic equation. This doubles the number of fitted combi-nations,based on thejet permutations. At the endof thefitting process, HitFit deliversinformationabout24 (120)fitted permuta-tionsforthecaseof4 (5)jets.

Afterthe event fitting is done, we have to decide which fit-tedcombinationmustbechosentorepresentthefinalstateofthe signal process. To reduce the numberof accidental combinatoric assignments,weuseinformationonb taggingandWtagging.Pairs ofW-taggedsubjets (ifavailable)areassignedtothe hadronicW bosondecay.Toidentifythemostlikelylepton+4jetscombination arisingfromthedecaychainofthesignalprocess,weinspecteach fittedcombinationinturn,proceedingasfollows:

•

In each fit combination, two jets are taken to be the b jets from theT and T decays. Wecall bl the b jet accompanying the leptonic W boson decay,and bh the b jet accompanying thehadronicWbosondecay.Combinationsinwhichneitherof thesejetsisb-taggedoronlyonehasaCSVLtagarerejected.

•

The fourjetsin thefittedcombination, designatedin the or-der: bh jet, bl jet, highest-pT jet in the hadronic W boson decay, second-highest-pT jet in the hadronic W boson de-cay, must satisfy the requirements pT

>

200,100,100, and 30 GeV,respectively.

•

For each fitted jet combination a variable ST is calculated, defined as the scalar sum of pmiss

T and the transverse mo-menta of the lepton and the four jets in that combination:

ST

=

pmissT

+

pT

+

p J1 T

+

p J2 T

+

p J3 T

+

p J4 T ,where Ji (with

i

=

1

to4)referstothefourjetsand

S

Tisevaluatedusingthe mea-sured momenta. Toselect hard-scatteringprocesses resulting intheproductionofheavyobjects,werequireST

>

1000GeV.

•

Sfit_L

/

Sfit_T

<

1.5,where Sfit_L

=

pν_L

+

p L

+

p J1 L

+

p J2 L

+

p J3 L

+

p J4 L , and pL is the longitudinal momentum of each ofthe corre-sponding objects. Both Sfit

L and SfitT are calculated using the

Table 1

Thenumbersofexpectedbackgroundeventsforeach pro-cessinthe

μ

+jetsande+jetschannels,normalizedtothe integratedluminosityofthedata,thenumberofobserved events,andtheratiooftheobservedtopredictedevents. Theuncertaintiesinthepredictednumbersofbackground eventsarestatisticalonly.

μ+ jets e + jets Background process tt+jets 533±6 470±5 Single top 115±5 100±4 W+jets 94±2 73±2 Z+jets 10.7±0.3 9.4±0.3 QCD multijet 8.8±4.4 15±8 Diboson 4.4±4.4 1.8±1.8 tt V 10.9±0.9 8.0±0.8 Total background (MC) 777±10 678±11 Total observed (Data) 768 684 Data/MC 0.99±0.04 1.01±0.04

Table 2

Selectionefficienciesfrom MCsimulationfor theTT signalasa functionofthe TquarkmassassumingB(T→bW)=100%,andthenumbersofexpectedsignal eventsafterthefinalselectionfortheintegratedluminosityofthedata.The uncer-taintiesarestatisticalonly.

Mass [GeV] μ+ jets e + jets

Efficiency (%) Events Efficiency (%) Events 800 2.37±0.05 166.1±3.7 2.20±0.05 153.5±3.5 900 2.71±0.06 87.8±1.9 2.36±0.05 75.8±1.8 1000 2.97±0.06 46.7±0.9 2.69±0.06 42.2±0.9 1100 3.08±0.06 24.7±0.5 2.77±0.06 22.1±0.4 1200 3.14±0.06 13.3±0.3 2.80±0.06 11.8±0.2 1300 3.10±0.07 7.09±0.15 2.79±0.06 6.34±0.14 1400 3.14±0.06 3.98±0.08 2.77±0.06 3.50±0.07 1500 3.21±0.06 2.30±0.04 2.76±0.06 1.96±0.04 1600 3.01±0.06 1.24±0.02 2.84±0.06 1.16±0.02 fitted momenta.This requirement relieson the fact that the final-stateobjectsfromthesignalprocess typicallyhaveboth high-pTandmoderate-pz values.

•

Theinvariant massofthetwo jetsattributedtotheW boson hadronicdecaymustbeintherange60–100 GeV.

•

P

(χ

2

₎

_>

_{0.1% (corresponding to 3 standard deviations for a} one-sidedGaussiandistribution).

The signal decayprocess contains two b quarks,which mani-festthemselvesasb-taggedjets. Thefitcombinationspassingthe aboveselectionaresortedintofourgroupsaccordingtotheb tag-gingcategoriesofthe{bl

,

bh}jetpair:twoCSVMb tags;oneCSVM andoneCSVL b tag;onlyone CSVMb tag;andtwoCSVL b tags. Thecombinationwiththelargest

P

(χ

2

₎

_{valuefromthegroupwith} thetightestb taggingisselectedforthesignalsample.

CombinationscontainingW-taggedsubjetsareconsideredfirst, ifsuch existin theevent. Ifno combinationwithW-tagged sub-jetspassestheselectioncriteria, thentheother combinationsare considered.

5.1. Results of the event selection

Table 1presentsthenumbersofobservedandpredicted back-groundevents,normalizedto theintegratedluminosity.Selection efficiencies forthe TT signal, includingacceptanceandbranching fractionsofdecays,andthenumberofexpectedsignaleventsare givenin

Table 2

asafunctionoftheT quarkmass.

Fig. 1 shows the distributions of the T quark reconstructed mass,

m

reco,obtainedfromtheselected

μ

+jetsande+jets events, and

Fig. 2

showstheir sum. The integratedluminosity and cross

Fig. 1. TheT quark reconstructedmass spectrafor the μ+jets(upperplot)and e+jets(lowerplot)channelsfromdataandfromMCsimulationsofsignaland back-groundprocesses.TheMCpredictionforpairproductionofaT quarkwithamassof 1300 GeV isshownbyadashedline,enhancedbyafactorof20.Thelowerpanels showtheratioofthedatatothebackgroundprediction.Theuncertainties repre-sentedbytheverticalbarsonthepoints arestatisticalonly.Theshadedregions showthetotalstatisticaluncertaintiesinthebackground.

sectionsofthebackgroundprocessesareusedfornormalizationof thebackgroundcontributions.Onlythestatisticaluncertaintiesare shownfortheestimated background,sincethe systematic uncer-taintiesentertheworkflowlaterandarenotavailableatthispoint ofthe analysis. Nevertheless, itis evident that the data distribu-tionsarewelldescribedbythepredictedbackgroundsalone.

Theresolutionofthereconstructedmasswas foundtobe pro-portionaltothevalue ofthemass,withtheGaussian coreofthe

mreco resolution curveshavinga width-to-mass ratioof

≈

7%.We makeuseofthisfeaturebyemployingvariablebinwidthsequalto 7% ofthebin-center valueswhen plotting

m

reco andusinga log-arithmicscaleforthehorizontalaxis.Inthisway,thebinwidths appeartobeofthesamesize,equalto thelocalmassresolution. This helps smooth statistical fluctuations causing peaks that are narrowerthanthelocalmassresolution,andavoidwrong interpre-tationswhensearchingfornarrowstructuresintheobservedmass distribution.

Fig. 2

(lowerplot)showstheresulting

m

recospectrum plottedthiswayforthesumofthe

μ

+jetsande+jetschannels.The

Fig. 2. The T quarkreconstructedmassspectraforthesumof

μ

+jetsande+jets channelsfromdataandfromMCsimulationsofsignalandbackgroundprocesses. Thelowerplothasalogarithmicx-axisscaleandthebinsizecorrespondsto7%of themassvalueinthemiddleofthebin.TheMCpredictionforthepairproduction ofaT quarkwithamassof1300 GeV isshownbyadashedline,enhancedbya factorof20.Thelowerpanelsshowtheratioofthedatatothebackground predic-tion.Theuncertaintiesrepresentedbytheverticalbarsonthepointsarestatistical only.Theshadedregionsshowthetotalstatisticaluncertaintiesinthebackground.

reconstructedtopquark peakfromthett+jetsbackgroundprocess andthe predictedsignal fora T quark witha massof 1300 GeV, enhancedbyafactorof20forbettervisibility,appearinthefigure asnarrowpeakswithsimilarwidths.

The analysis selection has been optimized to obtain the best signal significanceathighmasses, andthemassreconstructionin the regionofthetopquark hasnot receivedspecialattention. As aresult, thebinwidthusedin

Fig. 1

andtheupperpartof

Fig. 2

is too coarse to reveal details ofthe mass reconstruction in this region. Nonetheless,the topquark peak provides auseful bench-markforcheckingthereconstructedmass scaleandresolutionin dataandMonteCarlo.

6. Systematicuncertainties

Inthissection,wedescribethesystematicuncertaintiesinthe calculation of the signal cross section. The uncertainties can be

divided into two categories: those that only impact the normal-izationsofthedistributions,andthosethat alsoaffecttheshapes ofthe distributions. Eachsystematic uncertaintyis includedas a nuisanceparameterinthelikelihoodfitdescribedinSection7.

Theuncertaintiesinthett+jets, electroweak,andQCDmultijet crosssections,thetotalintegratedluminosity,andthelepton effi-cienciesaffectonlythenormalization.

The uncertainty in the cross section for tt+jets production of 5.3% is taken from a previous CMS measurement [43]. The in-tegrated luminosity is known to a precision of 2.5% [44]. A 10% uncertainty is assigned to the sum of the non-tt backgrounds, whichis dominated by the uncertaintyin the W+jetsand single top quark backgrounds. This uncertainty isobtained fromearlier CMSmeasurementsonsingle topquarkproduction[45]andfrom apreliminaryCMSmeasurementoninclusiveWproduction.

Trigger and lepton identification efficiencies and data/MC SFs areobtainedfromdatausingdecaysofZ bosonstodileptons.The systematicuncertaintyintheleptonidentificationandtrigger effi-cienciesis2.5%.

Uncertaintiesthat affect the shapes of the

m

reco distributions include those in the jet energy scales (JES), jet energy resolu-tion (JER), b tagging efficiency, pileup, renormalization/factoriza-tionscale,andPDFs.Tomodeltheseuncertainties,weproduce ad-ditionaldistributions,calledtemplates,byvaryingthenuisance pa-rameterthat characterizes eachsystematiceffectbyone standard deviationup anddown. Todeterminethe signal andbackground templatesforanyvalueofthenuisanceparameter,weinterpolate thecontentofeachbinbetweenthevariedandnominaltemplates. Thisprocedureisoftenreferredtoasverticalmorphing[46].

The JES uncertainty affects the normalization and the shape of the mreco distribution. This is taken into account by generat-ing

m

reco distributions forvaluesof thejet energyscaled by one standarddeviationofthe

η

- and pT-dependentuncertainties.

The MC was found to underestimate the JER observed in the data,andasaresulttheMCsimulatedjetsaresmearedtodescribe thedata.Tothisend,thedifferencebetweenthereconstructedjet

pT and the generated jet pT is scaled by

η

-dependent SFs (the so-called“nominal”variation). Toestimatetheuncertaintyinthis rescaling, the analysis is repeatedtwice, each time applying ad-ditionalsets of SFsthat correspond to varying the nominalones up anddown by one standard deviation. Both AK4andAK8jets aresubject toJER systematicvariations. The JESandJER system-aticvariationsareapplied beforetheAK8jet splitting.Systematic variationsofeachsubjetaredonewiththesamerelativevariation astheentireAK8 jet,so that their sumis equalto themodified AK8four-momentum.Theresultingjetmomentumchangesinthe AK4jetcollectionarepropagatedto pmiss

T .

The systematicuncertainty related to the b taggingefficiency is estimated by varying the b tagging SFs for both the medium andloose operating points by one standard deviation separately forheavy-flavorandlight-flavorjets.

Thepileup uncertaintyis evaluated by varying the minimum-biascrosssectionusedtocalculatethepileupdistributionindata by

±

4.6%,andadjustingthenumberofpileupinteractions inthe simulationtothesedistributions. Thisvariationistakenfromthe uncertaintyinapreliminaryCMSmeasurementofthe minimum-biascrosssection.

Theuncertainties dueto variationsin therenormalizationand factorizationscales are evaluated using per-event weights, corre-spondingtorenormalization/factorizationscalevariationsbya fac-toroftwoupanddown.Thecombinationsofscalescorresponding tounphysicalanti-correlatedvariationsarenotconsidered.The en-velopeoftheobservedvariationsinthe

m

recospectrumistakenas anestimateoftheuncertainty.

Table 3

VariationsinpercentontheyieldoftheselectedMCeventsdue toshapesystematicuncertaintiesforasignalwithaT quarkmass of1200 GeV andbackground.

Signal (%) Background (%)

JES +0.2,−2.5 17

JER +0.02,−0.3 0.03

b tag heavy flavor 2.5 +2.8,−1.4 b tag light flavor 0.2 0.8 Renorm./fact. scales 1.1 +18,−14

Pileup 0.05 0.2

PDF 0.3 2.0

Top quark pTreweighting – 11

W+jets reweighting – +4.9,−3.3 Rmatch +0,−0.8 +0,−1.9

ForevaluatingtheuncertaintyrelatedtothePDFs,weuse100 MC replicas,generated withthe NNPDF3.0PDFsetandtheir cor-respondingweights, tosample the

m

reco distribution.Theper-bin RMSinthe

m

recodistributionistakenasameasureofthePDF un-certainty in the corresponding templates. The PDF uncertainty is appliedbothtothebackgroundandthesignalMC replicas.Inthe caseofthesignal,theuncertaintyaffectsboththeshapeandyield, though thelatterisonlydueto thesignal acceptance,nottothe signalcrosssection.

It is known that the top quark pT distribution in the tt+jets background process is not well modeled by the MC simula-tion [47]. Therefore, a reweighting of the top quark MC pT dis-tribution is applied. An eventweight is calculated, based onthe generator-leveltopquark

p

T.Thesystematicuncertaintyrelatedto thetopquark pT distributionreweighting isdeterminedfromthe differencebetweenapplyingandnotapplyingthereweighting,and byapplyingthereweightingtwice.

For the W+jets background modeling, we use HT-binned MC samples,forwhichthe generator-level HT distributionwas found to deviate from the same distribution in the inclusive W+jets simulation. The variable HT is defined as the scalar sumof the transversemomentaofallpartonsina simulatedeventthat orig-inatefromthehard-scatteringprocess.Ineach HT-binnedsample, events are simulated in a certain range of HT (200 to 400 GeV, 400to600 GeV,etc.).Toimprovethemodeling,weimplementan event-weightingtechnique inwhicheach simulatedW+jetsevent isweighted dependingon its HT value.The weightisbasedona parametrizationobtainedfroma fittothe ratioofthe generator-level HT distributions of inclusive and HT-binned samples. The systematic uncertainty related to the event weighting is esti-matedfromthedifferencebetweenapplyingandnotapplyingthe weighting,andbyapplyingtheweightingtwice.

Toestimatethesystematicuncertaintiesrelatedtothe



Rmatch requirementusedtoassociateW-taggedAK8jetswithAK4jetsin thejet-splittingprocedure, twotemplates with

±

20%variation in themaximumallowed



Rmatch valuewereprepared.

Table 3showstheinfluenceoftheshapesystematic uncertain-tiesonthesignal,foraT massof1200 GeV,andbackgroundyields. Othersourcesofsystematicuncertaintieshaveanegligibleimpact ontheanalysis.

7. Crosssectionandmasslimits

Since the observed distributions are consistent with the ex-pected background, we use the results to set limits on the TT productioncrosssectionandontheT quarkmass.

As discussed in Section 5, there are two types of selected events: those with W-tagged jets (labeled as “W-tagged”), and those without (labeledas “no W tag”). The

m

reco invariant mass distributions for these two categoriesof events are shown

sepa-Fig. 3. TheT quarkreconstructedmassspectraforthesumofthe

μ

+jetsande+jets channelsforthe“noWtag”categoryofevents(upperplot),andforthe“W-tagged” category(lowerplot)fromdataandfromMCsimulationsofthebackground pro-cesses.TheMCpredictionforTT productionofaT quarkwithamassof1300 GeV isshownbyadashedline,enhancedbyafactorof100(upper)and10(lower).The lowerpanelsshowtheratioofthedatatothebackgroundprediction.The uncer-taintiesrepresentedbytheverticalbarsonthedatapointsarestatisticalonly.

ratelyin

Fig. 3

fordataandsimulatedbackground,combiningthe

μ+jets

and e+jets contributions. The no W tag category is more sensitive to lower-mass TT signalevents, asshown in the upper plotof

Fig. 3

bythecleartopquarkmasspeak.Athighmassesthis category of events gives a very small contribution to the signal. Conversely,theW-taggedcategory ismoresensitivetohigh-mass signal events,as canbe seenin Fig. 3from thepredicted distri-butions for a TT signal with a T mass of 1300 GeV for the two categories. We thereforeusethe data

m

reco distributionfromthe W-taggedeventsinsettingalowerlimitontheT quarkmass.We checkedthat using the no W tag category together withthe W-taggedcategorydidnotimprovethesensitivityathighmasses.

The distribution shown in Fig. 3 (lower plot) is used for the limitcalculations. FortheMC backgrounddistributionwe require that the relative statistical uncertainty in each bin is not worse than20%.Formassesabove1200GeVthebinsaremergedtomeet thisrequirement.Thefinalbinningcanbeseenonthepost-fit dis-tributionshownin

Fig. 4

(lowerplot).

Fig. 4. Upperplot:ObservedandexpectedBayesianupperlimitsat95%CLonthe product oftheTT or YY productioncrosssection andthe branchingfractionto bW usingonlytheW-taggedevents.Theinnerandouterbandsshowthe1and 2standard deviationuncertaintyrangesintheexpectedlimits,respectively. The dashed–dottedlineshowstheprediction ofthe theory.Lowerplot:Thepost-fit distributionofthereconstructedT quarkmass,mreco.Horizontalbarsonthedata

pointsshowbinsize.Theshadedbandonthehistogramandontheratioplotshows thequadraturesumofthestatisticalandsystematicuncertainties.TheMC predic-tionforheavyquarkproductionwith amassof1300 GeV is shownbyadashed line,enhancedbyafactorof10.

The 95% confidence level (CL) upper limits on the produc-tion cross section of TT are computed within the Theta frame-work [48] usinga Bayesianinterpretation [49],inwhich the sys-tematicuncertainties are takenintoaccountasnuisance parame-ters. The binned maximum-likelihood fit to the data distribution isperformedwithacombinationofthebackgroundcontributions plus asignal. Themain backgroundsare tt+jets,single topquark, andW+jetsproduction.Othersmallerbackgrounds,including elec-troweak and QCD multijet processes, are summed up with the single top quark and W+jetscontributions andare callednon-tt background (see Table 1). Distributionsof possibleTT signals are consideredforT massesfrom800to1600 GeV (Table 2).

Thelikelihoodfunctionismarginalizedwithrespecttothe nui-sanceparameters representingthesystematicuncertainties inthe shape and normalization. Thirteen nuisance parameters are em-ployed in the likelihood fit: tt+jets cross section uncertainty of

5.3%, normalization of the non-tt contribution of 10%, the inte-grated luminosity uncertainty of 2.5%, lepton identification and triggeruncertaintyof2.5%; other uncertaintiesare theshape un-certainties that include the JES, JER, the b tag SFs for light-andheavy-flavorjets,therenormalizationandfactorizationscales, pileup, PDFs, top quark pT reweighting, and W+jets background reweighting. Shapes of the SM background and signal templates arechanged(“morphed”)inthelimit-settingprocedure according to the varying values of the shape nuisance parameters. Contri-butionsfromtheSM processesareallowedtovaryindependently withintheirsystematicuncertainties,usinglog-normalpriors[50, 51]. The nuisance parameters describing the shape uncertainties areconstrainedusingGaussianpriors.Aflatpriorprobability den-sityfunctiononthetotalsignalyieldisassumed.TheMCstatistical uncertainties in the simulated samples are also included in this calculation.

Fig. 4 (upper plot) showsthe observed andexpected 95% CL upperlimitson theTT crosssection asa functionofthe Tquark mass.

Fig. 4

(lowerplot)showsthepost-fitdistributionofthe re-constructedmass.Fromtheuppercrosssectionlimitswesetlower limits on the T quark mass. The 95% CL lower limit on the T massisgivenbythevalueatwhichthe95%CLupperlimit curve forthe TT crosssection intersects the theory curve, asshownin

Fig. 4.Inthe bWbW channelwithanassumedbranchingfraction

B(

T

→

bW)

=

100%,theobserved(expected)lowerlimitontheT quarkmassis1295 (1275) GeV.

8. Summary

Theresultsofasearchforvector-likequarks,eitherT orY,with electric charge of 2/3 and

−

4/3, respectively, that are pair pro-ducedinppinteractionsat

√

s

=

13TeV anddecayexclusivelyvia thebW channelhavebeenpresented.Eventsareselectedrequiring thatoneW bosondecaystoaleptonandneutrino,andtheother toaquark–antiquark pair.The selectionrequiresa muonor elec-tron,significant missing transversemomentum, andat leastfour jets. A kinematicfit assuming TT or YY production is performed andfor every event a candidate T/Y quark massmreco is recon-structed. The analysis provides a high-resolution (7%) mass scan ofthebW spectruminthe rangefromthetopquark massup to

≈

2 TeV,inwhichthesignalfrompairproductionofequalmass ob-jectsdecayingtobW wouldshowupinamodel-independentway asa narrowpeak. A binned maximum-likelihoodfit to the

m

reco distributionis madeandno significant deviationsfromthe stan-dardmodelexpectationsarefound.UpperlimitsaresetontheTT andYY pairproductioncrosssectionsasafunctionoftheirmass. Bycomparingtheselimitswiththepredictedtheoreticalcross sec-tion of the pair production, the production of T and Y quarks is excluded at 95% confidence level for masses below 1295 GeV (1275 GeV expected). More generally,the resultsset upper limits ontheproductoftheproductioncrosssectionandbranching frac-tiontobW foranynewheavyquarkdecayingtothischannel.

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 effectivelythecomputinginfrastructure essential toour analyses. Finally, we acknowledge the enduring support for the construc-tionandoperationofthe LHCandtheCMSdetectorprovided by 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-gramandtheEuropeanResearchCouncilandHorizon2020Grant, contract No. 675440 (European Union); the Leventis Foundation; the A. P. Sloan Foundation; the Alexander von Humboldt Foun-dation;the BelgianFederal Science Policy Office; theFonds pour laFormation à laRecherche dans l’Industrieet dansl’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Council of Sci-ence and Industrial Research, India; the HOMING PLUS program of the Foundation for Polish Science, cofinanced from European Union,Regional Development Fund,the MobilityPlusprogram of theMinistryofScienceandHigherEducation,theNationalScience 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 Program by Qatar National Research Fund; the Programa Severo Ochoa del Principado de Asturias; the Thalis and Aris-teia programs cofinanced by EU-ESF and the Greek NSRF; the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chula-longkornUniversityandtheChulalongkornAcademic intoIts2nd CenturyProjectAdvancement Project(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,

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,

D. Rabady,

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,

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

H. Brun,

B. Clerbaux,

G. De Lentdecker,

H. Delannoy,

G. Fasanella,

L. Favart,

R. Goldouzian,

A. Grebenyuk,

G. Karapostoli,

T. Lenzi,

J. Luetic,

T. Maerschalk,

A. Marinov,

A. Randle-conde,

T. Seva,

C. Vander Velde,

P. Vanlaer,

D. Vannerom,

R. Yonamine,

F. Zenoni,

F. Zhang

2

UniversitéLibredeBruxelles,Bruxelles,Belgium

A. Cimmino,

T. Cornelis,

D. Dobur,

A. Fagot,

M. Gul,

I. Khvastunov,

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,

S. De Visscher,

C. Delaere,

M. Delcourt,

B. Francois,

A. Giammanco,

A. Jafari,

M. Komm,

G. Krintiras,

V. Lemaitre,

A. Magitteri,

A. Mertens,

M. Musich,

K. Piotrzkowski,

L. Quertenmont,

M. Vidal Marono,

S. Wertz

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

3

,

A. Custódio,

E.M. Da Costa,

G.G. Da Silveira

4

,

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,

A. Santoro,

A. Sznajder,

E.J. Tonelli Manganote

3

,

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

a

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

A. Aleksandrov,

R. Hadjiiska,

P. Iaydjiev,

M. Misheva,

M. Rodozov,

M. Shopova,

S. Stoykova,

G. Sultanov

A. Dimitrov,

I. Glushkov,

L. Litov,

B. Pavlov,

P. Petkov

UniversityofSofia,Sofia,Bulgaria

W. Fang

5

,

X. Gao

5

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

6

,

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

7

,

M. Finger Jr.

7

CharlesUniversity,Prague,CzechRepublic

E. Carrera Jarrin

UniversidadSanFranciscodeQuito,Quito,Ecuador

E. El-khateeb

8

,

S. Elgammal

9

,

A. Ellithi Kamel

10

AcademyofScientificResearchandTechnologyoftheArabRepublicofEgypt,EgyptianNetworkofHighEnergyPhysics,Cairo,Egypt

R.K. Dewanjee,

M. Kadastik,

L. Perrini,

M. Raidal,

A. Tiko,

C. Veelken

NationalInstituteofChemicalPhysicsandBiophysics,Tallinn,Estonia

P. Eerola,

J. Pekkanen,

M. Voutilainen

DepartmentofPhysics,UniversityofHelsinki,Helsinki,Finland

J. Härkönen,

T. Järvinen,

V. Karimäki,

R. Kinnunen,

T. Lampén,

K. Lassila-Perini,

S. Lehti,

T. Lindén,

P. Luukka,

E. Tuominen,

J. Tuominiemi,

E. Tuovinen

HelsinkiInstituteofPhysics,Helsinki,Finland

J. Talvitie,

T. Tuuva

M. Besancon,

F. Couderc,

M. Dejardin,

D. Denegri,

J.L. Faure,

F. Ferri,

S. Ganjour,

S. Ghosh,

A. Givernaud,

P. Gras,

G. Hamel de Monchenault,

P. Jarry,

I. Kucher,

E. Locci,

M. Machet,

J. Malcles,

G. Negro,

J. Rander,

A. Rosowsky,

M.Ö. Sahin,

M. Titov

IRFU,CEA,UniversitéParis-Saclay,Gif-sur-Yvette,France

A. Abdulsalam,

I. Antropov,

S. Baffioni,

F. Beaudette,

P. Busson,

L. Cadamuro,

C. Charlot,

R. Granier de Cassagnac,

M. Jo,

S. Lisniak,

A. Lobanov,

J. Martin Blanco,

M. Nguyen,

C. Ochando,

G. Ortona,

P. Paganini,

P. Pigard,

R. Salerno,

J.B. Sauvan,

Y. Sirois,

A.G. Stahl Leiton,

T. Strebler,

Y. Yilmaz,

A. Zabi,

A. Zghiche

LaboratoireLeprince-Ringuet,Ecolepolytechnique,CNRS/IN2P3,UniversitéParis-Saclay,Palaiseau,France

J.-L. Agram

11

,

J. Andrea,

D. Bloch,

J.-M. Brom,

M. Buttignol,

E.C. Chabert,

N. Chanon,

C. Collard,

E. Conte

11

,

X. Coubez,

J.-C. Fontaine

11

,

D. Gelé,

U. Goerlach,

M. Jansová,

A.-C. Le Bihan,

N. Tonon,

P. Van Hove

UniversitédeStrasbourg,CNRS,IPHCUMR7178,F-67000Strasbourg,France

S. Gadrat

CentredeCalculdel’InstitutNationaldePhysiqueNucleaireetdePhysiquedesParticules,CNRS/IN2P3,Villeurbanne,France

S. Beauceron,

C. Bernet,

G. Boudoul,

R. Chierici,

D. Contardo,

P. Depasse,

H. El Mamouni,

J. Fay,

L. Finco,

S. Gascon,

M. Gouzevitch,

G. Grenier,

B. Ille,

F. Lagarde,

I.B. Laktineh,

M. Lethuillier,

L. Mirabito,

A.L. Pequegnot,

S. Perries,

A. Popov

12

,

V. Sordini,

M. Vander Donckt,

S. Viret

UniversitédeLyon,UniversitéClaudeBernardLyon1,CNRS-IN2P3,InstitutdePhysiqueNucléairedeLyon,Villeurbanne,France

A. Khvedelidze

7

GeorgianTechnicalUniversity,Tbilisi,Georgia

Z. Tsamalaidze

7

TbilisiStateUniversity,Tbilisi,Georgia

C. Autermann,

L. Feld,

M.K. Kiesel,

K. Klein,

M. Lipinski,

M. Preuten,

C. Schomakers,

J. Schulz,

T. Verlage,

V. Zhukov

12

RWTHAachenUniversity,I.PhysikalischesInstitut,Aachen,Germany

A. Albert,

E. Dietz-Laursonn,

D. Duchardt,

M. Endres,

M. Erdmann,

S. Erdweg,

T. Esch,

R. Fischer,

A. Güth,

M. Hamer,

T. Hebbeker,

C. Heidemann,

K. Hoepfner,

S. Knutzen,

M. Merschmeyer,

A. Meyer,

P. Millet,

S. Mukherjee,

T. Pook,

M. Radziej,

H. Reithler,

M. Rieger,

F. Scheuch,

D. Teyssier,

S. Thüer

RWTHAachenUniversity,III.PhysikalischesInstitutA,Aachen,Germany

G. Flügge,

B. Kargoll,

T. Kress,

A. Künsken,

J. Lingemann,

T. Müller,

A. Nehrkorn,

A. Nowack,

C. Pistone,

O. Pooth,

A. Stahl

13

RWTHAachenUniversity,III.PhysikalischesInstitutB,Aachen,Germany

M. Aldaya Martin,

T. Arndt,

C. Asawatangtrakuldee,

K. Beernaert,

O. Behnke,

U. Behrens,

A. Bermúdez Martínez,

A.A. Bin Anuar,

K. Borras

14

,

V. Botta,

A. Campbell,

P. Connor,

C. Contreras-Campana,

F. Costanza,

C. Diez Pardos,

G. Eckerlin,

D. Eckstein,

T. Eichhorn,

E. Eren,

E. Gallo

15

,

J. Garay Garcia,

A. Geiser,

A. Gizhko,

J.M. Grados Luyando,

A. Grohsjean,

P. Gunnellini,

M. Guthoff,

A. Harb,

J. Hauk,

M. Hempel

16

,

H. Jung,

A. Kalogeropoulos,

M. Kasemann,

J. Keaveney,

C. Kleinwort,

I. Korol,

D. Krücker,

W. Lange,

A. Lelek,

T. Lenz,

J. Leonard,

K. Lipka,

W. Lohmann

16

,

R. Mankel,

I.-A. Melzer-Pellmann,

A.B. Meyer,

G. Mittag,

J. Mnich,

A. Mussgiller,

E. Ntomari,

D. Pitzl,

A. Raspereza,

B. Roland,

M. Savitskyi,

P. Saxena,

R. Shevchenko,

S. Spannagel,

N. Stefaniuk,

G.P. Van Onsem,

R. Walsh,

Y. Wen,

K. Wichmann,

C. Wissing,

O. Zenaiev

DeutschesElektronen-Synchrotron,Hamburg,Germany

S. Bein,

V. Blobel,

M. Centis Vignali,

T. Dreyer,

E. Garutti,

D. Gonzalez,

J. Haller,

A. Hinzmann,

M. Hoffmann,

A. Karavdina,

R. Klanner,

R. Kogler,

N. Kovalchuk,

S. Kurz,

T. Lapsien,

I. Marchesini,

D. Marconi,

M. Meyer,

M. Niedziela,

D. Nowatschin,

F. Pantaleo

13

,

T. Peiffer,

A. Perieanu,

C. Scharf,

P. Schleper,

A. Schmidt,

S. Schumann,

J. Schwandt,

J. Sonneveld,

H. Stadie,

G. Steinbrück,

F.M. Stober,

M. Stöver,

H. Tholen,

D. Troendle,

E. Usai,

L. Vanelderen,

A. Vanhoefer,

B. Vormwald

UniversityofHamburg,Hamburg,Germany

M. Akbiyik,

C. Barth,

S. Baur,

E. Butz,

R. Caspart,

T. Chwalek,

F. Colombo,

W. De Boer,

A. Dierlamm,

B. Freund,

R. Friese,

M. Giffels,

A. Gilbert,

D. Haitz,

F. Hartmann

13

,

S.M. Heindl,

U. Husemann,

F. Kassel

13

,

S. Kudella,

H. Mildner,

M.U. Mozer,

Th. Müller,

M. Plagge,

G. Quast,

K. Rabbertz,

M. Schröder,

I. Shvetsov,

G. Sieber,

H.J. Simonis,

R. Ulrich,

S. Wayand,

M. Weber,

T. Weiler,

S. Williamson,

C. Wöhrmann,

R. Wolf

InstitutfürExperimentelleKernphysik,Karlsruhe,Germany

G. Anagnostou,

G. Daskalakis,

T. Geralis,

V.A. Giakoumopoulou,

A. Kyriakis,

D. Loukas,

I. Topsis-Giotis

InstituteofNuclearandParticlePhysics(INPP),NCSRDemokritos,AghiaParaskevi,Greece

G. Karathanasis,

S. Kesisoglou,

A. Panagiotou,

N. Saoulidou

NationalandKapodistrianUniversityofAthens,Athens,Greece

K. Kousouris

NationalTechnicalUniversityofAthens,Athens,Greece

I. Evangelou,

C. Foudas,

P. Kokkas,

S. Mallios,

N. Manthos,

I. Papadopoulos,

E. Paradas,

J. Strologas,

F.A. Triantis

UniversityofIoánnina,Ioánnina,Greece

M. Csanad,

N. Filipovic,

G. Pasztor,

G.I. Veres

17

MTA-ELTELendületCMSParticleandNuclearPhysicsGroup,EötvösLorándUniversity,Budapest,Hungary

G. Bencze,

C. Hajdu,

D. Horvath

18

,

Á. Hunyadi,

F. Sikler,

V. Veszpremi,

A.J. Zsigmond

WignerResearchCentreforPhysics,Budapest,Hungary

N. Beni,

S. Czellar,

J. Karancsi

19

,

A. Makovec,

J. Molnar,

Z. Szillasi

InstituteofNuclearResearchATOMKI,Debrecen,Hungary

M. Bartók

17

,

P. Raics,

Z.L. Trocsanyi,

B. Ujvari

InstituteofPhysics,UniversityofDebrecen,Debrecen,Hungary

S. Choudhury,

J.R. Komaragiri

IndianInstituteofScience(IISc),Bangalore,India

S. Bahinipati

20

,

S. Bhowmik,

P. Mal,

K. Mandal,

A. Nayak

21

,

D.K. Sahoo

20

,

N. Sahoo,

S.K. Swain

NationalInstituteofScienceEducationandResearch,Bhubaneswar,India

S. Bansal,

S.B. Beri,

V. Bhatnagar,

R. Chawla,

N. Dhingra,

A.K. Kalsi,

A. Kaur,

M. Kaur,

R. Kumar,

P. Kumari,

A. Mehta,

J.B. Singh,

G. Walia