Running of the top quark mass from proton-proton collisions at √s = 13TeV

Contents lists available atScienceDirect

Physics

Letters

B

www.elsevier.com/locate/physletb

Running

of

the

top

quark

mass

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: Received19September2019

Receivedinrevisedform26January2020 Accepted27January2020

Availableonline10February2020 Editor:M.Doser

Keywords: CMS Physics Topquarkmass QCD

Renormalization

The running of the top quark mass is experimentally investigated for the first time. The mass of the top quark in the modified minimal subtraction (MS) renormalization scheme is extracted from a comparison of the differential top quark-antiquark (t¯t) cross section as a function of the invariant mass of the t¯t system to next-to-leading-order theoretical predictions. The differential cross section is determined at the parton level by means of a maximum-likelihood fit to distributions of final-state observables. The analysis is performed using t¯t candidate events in the e±_μ∓_{channel in proton-proton collision data at a}

centre-of-mass energy of 13 TeV recorded by the CMS detector at the CERN LHC in 2016, corresponding to an integrated luminosity of 35.9 fb−1_{. The extracted running is found to be compatible with the scale}

dependence predicted by the corresponding renormalization group equation. In this analysis, the running is probed up to a scale of the order of 1 TeV.

©2020 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Funded by SCOAP3_.

1. Introduction

Beyondleading order inperturbation theory,the fundamental parametersofthequantumchromodynamics(QCD)Lagrangian,i.e. thestrongcouplingconstant

α

S andthequarkmasses,aresubject

to renormalization. As a result, these parameters depend on the scaleatwhichthey areevaluated.Theevolutionof

α

S andofthe

quarkmassesasafunctionofthe scale,commonlyreferredtoas “running”,isdescribedbyrenormalizationgroupequations(RGEs). The running of

α

S was experimentally verified on a wide range

ofscalesusing jetproductionin electron-proton,positron-proton, electron-positron,proton-antiproton,andproton-proton(pp) colli-sions,assummarized,e.g. inRefs. [1,2].Todeterminetherunning, the value of

α

S evaluated at an arbitrary reference scale is

ex-tractedinbinsofaphysicalenergyscale Q andthenconvertedto

α

S

(

Q

)

usingthe corresponding RGE [2]. Thevalidity ofthis

pro-cedure lies inthe fact that, ina calculation, the renormalization scaleis normallyidentified withthephysical energyscale ofthe process. The sameprocedure can be used to determine the run-ningofthemassofaquark. Inthemodified minimalsubtraction (MS)renormalizationscheme,thedependenceofaquark massm

onthescale

μ

isdescribedbytheRGE

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

μ

2dm

(

μ

)

d

μ

2

= −

γ

(

α

S

(

μ

))

m

(

μ

),

(1)

where

γ

(

α

S

(

μ

))

is the mass anomalous dimension, which is

knownup to five-looporder inperturbative QCD [3,4].The solu-tionofEq. (1) canbeused toobtainthequark massatanyscale

μ

from the mass evaluated at an initial scale

μ

0. The running

ofthe b quark masswas demonstrated [5] usingdata from vari-ous experimentsatthe CERNLEP [6–9],SLACSLC [10],andDESY HERA [11] colliders. Measurementsof charm quark pair produc-tion in deepinelastic scatteringat theDESY HERA were used to determinetherunningofthecharmquarkmass [12].These mea-surementsrepresentapowerfultestofthevalidityofperturbative QCD. Furthermore, RGEs can be modified by contributions from physics beyond thestandard model, e.g. inthe context of super-symmetrictheories [13].

ThisLetterdescribesthefirstexperimentalinvestigationofthe runningofthetop quarkmass,mt,asdefinedintheMS scheme.

Therunningofmt isextractedfroma measurementofthe

differ-ential top quark-antiquarkpairproductioncross section,

σ

t¯t,asa

functionoftheinvariant massofthe t

¯

t system,m_t¯t.The differen-tialcross section,d

σ

t¯t

/

dmt¯t,is determinedatthe partonlevelby

means of a maximum-likelihoodfit to distributions of final-state observablesusingt

¯

t candidateeventsinthee±

μ

∓ final state, ex-tendingthemethoddescribedinRef. [14] tothecaseofa differen-tialmeasurement.Thismethodallowsthedifferentialcrosssection to be constrained simultaneously with the systematic

uncertain-https://doi.org/10.1016/j.physletb.2020.135263

0370-2693/©2020TheAuthor(s).PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCCBYlicense(http://creativecommons.org/licenses/by/4.0/).Fundedby SCOAP3_.

ties. In this analysis, the parton level is definedbefore radiation fromthepartonshower,whichallowsforadirectcomparisonwith fixed-ordertheoreticalpredictions.Themeasurementisperformed using pp collision dataat

√

s

=

13TeV recorded by the CMS de-tector at the CERN LHC in 2016, corresponding to an integrated luminosity of35.9 fb−1.The runningmass,mt

(

μ

)

,is extractedat

next-to-leadingorder(NLO) inQCD asafunction ofmt¯t by

com-paringfixed-order theoreticalpredictionsatNLOtothemeasured d

σ

t¯t

/

dmt¯t.Therunningofmt isprobeduptoa scaleoftheorder

of1 TeV.

2. TheCMSdetectorandMonteCarlosimulation

The central feature of the CMS apparatus is a superconduct-ing solenoidof 6 m internal diameter, providinga magnetic field of3.8 T. Withinthe solenoidvolume area siliconpixel andstrip tracker,aleadtungstatecrystalelectromagneticcalorimeter(ECAL), andabrass andscintillatorhadron calorimeter,eachcomposedof abarrelandtwoendcapsections.Forwardcalorimetersextendthe pseudorapidity (

η

) coverage provided by the barrel and endcap detectors.Muonsaredetected ingas-ionizationchambers embed-dedinthesteelflux-returnyokeoutsidethesolenoid. Atwo-level triggersystemselects eventsofinterestforanalysis [15].A more detaileddescriptionoftheCMSdetector,togetherwithadefinition ofthecoordinatesystemusedandtherelevantkinematicvariables, canbefoundinRef. [16].

The particle-flow (PF) algorithm [17] aims to reconstruct and identify electrons, muons, photons, charged and neutral hadrons inan event, withan optimizedcombination ofinformation from thevariouselementsoftheCMSdetector.Theenergyofelectrons isdetermined from acombination ofthe electron momentumat the primary interaction vertex asdetermined by the tracker,the energyofthecorresponding ECALcluster, andthe energysumof all bremsstrahlung photons spatially compatible with originating from the electron track [18]. The momentum of muons is ob-tained from the curvature of the corresponding track [19]. Jets are reconstructed from the PFcandidates using the anti-kT

clus-teringalgorithmwithadistanceparameterof0.4 [20,21],andthe jet momentum isdetermined as thevectorial sumofall particle momentain thejet. Themissingtransverse momentum vectoris computedasthenegative vector sumof thetransversemomenta (pT) ofallthePFcandidatesinanevent.Jetsoriginatingfromthe

hadronization ofb quarks(b jets) are identified (b tagged) using the combined secondary vertex [22] algorithm, using a working pointthatcorrespondstoanaverageb taggingefficiencyof41%for simulatedt

¯

t events,andanaveragemisidentificationprobabilityof 0.1%and2.2%forlight-flavourjetsandc jets,respectively [22].

Inthisanalysis, the sameMonte Carlo(MC) simulationsas in Ref. [14] are used.Inparticular,t

¯

t, tW,andDrell–Yan(DY) events are simulated using the powheg v2 [23–28] NLO MC generator interfaced to pythia 8.202 [29] for the modelling of the parton showerandusingtheCUETP8M2T4underlyingeventtune [30,31]. In the simulation, the proton structure is described by means ofthe NNPDF3.0 [32] parton distributionfunction (PDF) set.The largest background contributions are represented by tW and DY production. Other background processes include W+jets produc-tion and diboson events, while the contribution from QCD mul-tijet production is found to be negligible. Contributions from all backgroundprocessesareestimatedfromsimulationandare nor-malizedtotheirpredictedcrosssection.FurtherdetailsontheMC simulationofthebackgroundscanbefoundinRef. [14].

3. Eventselectionandsystematicuncertainties

Eventsare collected usingacombinationoftriggerswhich re-quire eitherone electron with pT

>

12GeV and one muon with

pT

>

23GeV,oroneelectronwithpT

>

23GeV andonemuonwith pT

>

8GeV,orone electronwith pT

>

27GeV,orone muonwith pT

>

24GeV.In the analysis, tight isolation requirements are

ap-pliedtoelectronsandmuonsbasedontheratioofthescalarsum of the pT ofneighbouring PF candidates to the pT of the lepton

candidate. Events are then required to contain atleast one elec-tron andone muon ofopposite electriccharge with pT

>

25GeV

for the leading and pT

>

20GeV for the subleading lepton, and

|

η

|

<

2

.

4.Thiskinematicselection definesthevisiblephasespace. Ineventswithmorethantwoleptons,thetwoleptonsofopposite charge withthe highest pT are used. Jets with pT

>

30GeV and

|

η

|

<

2

.

4 areconsidered,butnorequirementonthenumberof re-constructedjetsorb-taggedjetsisimposed.Furtherdetailsonthe eventselectioncanbefoundinRef. [14].

In events with at leasttwo jets, the invariant mass of the t

¯

t systemisestimatedbymeans ofthekinematicreconstruction al-gorithmdescribedinRef. [33].Thereconstructedinvariantmassis indicated with mreco

t¯t . The kinematicreconstruction algorithm

ex-aminesallpossiblecombinationsofreconstructedjetsandleptons andsolves asystemofequationsundertheassumptions that the invariant massofthereconstructedW bosonis80.4 GeV andthat themissingtransversemomentum originatessolelyfromthe two neutrinos coming from the leptonic decays of the W bosons. In addition, the kinematic reconstruction algorithm requires an as-sumptionon thevalue ofthe topquark mass,mkin

t .Any possible

bias dueto the choice of this value is avoided by incorporating thedependenceonmkin

t inthefitdescribedinSection 4.To

esti-matethisdependence,thekinematicreconstructionandtheevent selection arerepeatedwiththreedifferentchoicesofmkin_t , corre-sponding to169.5, 172.5,and175.5 GeV,andthe topquark mass usedintheMCsimulation,mMC_t ,isvariedaccordingly.The param-etermkin

t

=

mMCt isthentreatedasafreeparameterofthefit.

The sourcesofsystematicuncertainties areclassifiedas exper-imental and modelling uncertainties. Experimental uncertainties arerelatedtothecorrectionsappliedtotheMCsimulation.These includeuncertaintiesassociatedwithtriggerandlepton identifica-tion efficiencies, jet energy scale [34] andresolution [35], lepton energy scales, b tagging efficiencies [22], and the uncertainty in theintegratedluminosity [36].Modellinguncertaintiesarerelated tothesimulationofthet

¯

t signal,andincludematrix-elementscale variationsinthe powheg simulation [37,38],scalevariationsinthe partonshower [31],variations inthematchingscalebetweenthe matrix element andthe parton shower [30], uncertainties in the underlying eventtune [30], thePDFs [39], the B hadron branch-ing fractionandfragmentationfunction [40,41], anduncertainties related to the choice of the colour reconnection model [42,43]. Furthermore,asinpreviousCMSanalyses,e.g. [14,44,45],an uncer-taintythataccountsfortheobserveddifferenceintheshapeofthe top quark pT distributionbetweendataandsimulation [33,46,47]

is applied.The dependenceon thetop quark widthhas been in-vestigated andwas found to be negligible. Other sources of un-certainty includethe modellingof the additional pp interactions withinthesameornearbybunchcrossingsandthenormalization of background processes. Forthe latter, an uncertainty of 30% is assignedtothenormalizationofeachbackgroundprocess.Further details onthesourcesofsystematicuncertaintiesandthe consid-eredvariationscanbefoundinRef. [14].

The simulated t

¯

t sample is split into four subsamples corre-sponding to bins of m_t¯t at the parton level. Each subsample is treatedasan independentsignalprocess,representingthet

¯

t pro-ductionatthescale

μ

k,whichischosentobethecentre-of-gravity

ofbink,definedasthemeanvalueofm_t¯t inthatbin.The subsam-plecorresponding tothebink isdenotedwith“Signal

(

μ

k

)

”.The mt¯t binboundaries,thecorrespondingfractionofsimulatedevents

Table 1

The mt¯t bin boundaries, thecorresponding fraction of

eventsinthe powheg simulation,andtherepresentative scaleμk.

Bin mt¯t[GeV] Fraction [%] μk[GeV]

1 <420 30 384

2 420–550 39 476

3 550–810 24 644

4 >810 7 1024

Fig. 1. Distributionofmreco

t¯t afterthefittothedata,withthesamebinningasused

inthefit.Thehatchedbandcorrespondstothetotaluncertaintyinthepredicted yields,includingthe contributionfrommMC

t (mMCt )andallcorrelations.Thet¯t

MCsampleissplitintofoursubsamples,denotedwith“Signal(μk)”,corresponding

tobinsofmt¯t atthepartonlevel.Thefirstand lastbinscontainalleventswith

mreco

t¯t <420GeV andm reco

t¯t >810GeV,respectively.

Table1,wherethevaluesareestimatedfromthenominal powheg simulation.Thewidthofeachbin,



m_tk_¯t,ischosentakinginto ac-counttheresolutioninmreco

t¯t .Fig.1showsthedistributionofm reco t¯t

afterthefittothedata,whichisdescribedinthenextsection. 4. Fitprocedureandcrosssectionresults

Thedifferentialt

¯

t crosssectionatthepartonlevelismeasured by means of a maximum-likelihood fit to distributions of final-state observables where the systematic uncertainties are treated asnuisanceparameters.Inthelikelihood,thenumberofeventsin eachbinofanydistributionoffinal-stateobservablesisassumedto followaPoissondistribution.With

σ

(μk)

t¯t

= (

d

σ

t¯t

/

dmt¯t

)

mkt¯t being

thetotalt

¯

t crosssectioninthebink ofmt¯t,theexpectednumber

ofeventsinthebini ofanyoftheconsideredfinal-state distribu-tions,denotedwith

ν

i,canbewrittenas

ν

i

=

4



k=1 sk_i

(

σ

(μk) t¯t

,

m MC t

, 

λ)

+



j b_ij

(

mMC_t

, 

λ).

(2) Here, sk

i indicates theexpected numberoft

¯

t events inthe bink

ofm_t¯t anddependson

σ

(μk)

t¯t ,m MC

t ,andthenuisanceparameters

λ

.

Similarly,b_ijrepresentstheexpectednumberofbackgroundevents froma source j and depends on mMC

t and the nuisance

param-eters

λ

. Thedependence of thebackground processes onmMC_t is introducednotonlybythecontributionoftW andsemileptonict

¯

t events,butalsobythechoiceofmkin

t inthekinematic

reconstruc-tion.Equation (2),whichrelatesthevarious

σ

(μk)

t¯t (andhencethe

parton-leveldifferentialcrosssection)todistributionsoffinal-state observables, embeds the detector response and its parametrized

dependenceon thesystematicuncertainties. Therefore,the maxi-mizationofthelikelihoodfunctionprovidesresults for

σ

(μk)

t¯t that

are automatically unfolded to the partonlevel.This method (de-scribed,e.g. inRef. [48])isalsoreferredtoasmaximum-likelihood unfolding and, unlikeother unfoldingtechniques,allows the nui-sance parameters to be constrained simultaneously withthe dif-ferential cross section. The unfolding problem was found to be well-conditioned, andtherefore no regularization is needed. The expected signal andbackground distributions contributing to the fitaremodelledwithtemplatesconstructedusingsimulated sam-ples.

Selectedeventsare categorizedaccordingto thenumberof b-tagged jets, as events with 1 b-tagged jet, 2 b-tagged jets, or a different number of b-tagged jets (zero or more than two). The effectofthesystematicuncertainties onthe normalizationofthe differentsignalsineachofthesecategoriesisparametrizedusing multinomial probabilities. Inparticular, based onthe t

¯

t topology, the number of events with one (Sk

1b), two (Sk2b), or a different

number of b-tagged jets(Sk_other) in each bin ofmt¯t is expressed

as: Sk_1b

=

L

σ

(μk) t¯t A k sel

selk 2

bk

(

1

−

Ckb

bk

),

(3) Sk_2b

=

L

σ

(μk) t¯t A k sel

selk Cbk

(

kb

)

2

,

(4) Sk_other

=

L

σ

(μk) t¯t A k sel

selk



1

−

2

_bk

(

1

−

C_bk

_bk

)

−

Ck_b

(

_bk

)

2



.

(5)

Here,

L

is the integrated luminosity, Ak

sel is the acceptance of

the event selection in the mt¯t bin k, and

ksel represents the

ef-ficiency for an eventin the visible phase space to pass the full eventselection. The acceptance Ak

sel is definedas thefraction of

t

¯

t eventsin thebink that,atthegenerator (particle)level,enter thevisiblephasespacedescribed inSection3,while _selk includes experimental selection criteria, e.g. isolation and trigger require-ments. Furthermore,

k

b represents the b tagging probability and

the parameter Ck_b accounts for any residual correlation between thetaggingoftwob jetsinat

¯

t event.Thequantities Ak_sel, _selk , _bk, and C_bk are determined from thesignal simulation and, although they are not free parameters of the fit, they vary according to theparameters

λ

andmMC_t .Ineachcategory,theremainingeffects ofthe systematicuncertainties on signalprocessesare treatedas shape uncertainties. Thequantities sk_i inEq. (2) arethen derived fromthesignalshapeandnormalizationinthecorresponding cat-egory.Inthisway,apreciseparametrizationofthedependenceof signalnormalizationsonthenuisanceparametersandmMC

t is

ob-tained. In fact,the parameters inEqs. (3)–(5) are lesssubject to statisticalfluctuationsthanthesk_i.

Inordertoconstraineachindividual

σ

(μk)

tt¯ ,eventswithatleast

twojetsarefurtherdivided intosubcategories ofmreco

t¯t ,usingthe

samebinningasform_t¯t (Table1).Thechoiceoftheinput distribu-tions tothefitinthedifferenteventcategoriesissummarizedin Table2.Thetotalnumberofeventsischosenasinputtothefitfor allsubcategorieswithzeroormorethantwob-taggedjets,where thecontributionofthebackgroundprocessesisthelargest,in or-der to mitigatethe sensitivity of the measurement to the shape of the distributions ofbackground processes. The same choice is madeforthesubcategoriescorrespondingtothelastbininmreco_t¯t , where the statistical uncertainty in both data and simulation is large,andforeventswithlessthantwojets, wherethekinematic reconstruction cannot be performed. In the remaining subcate-gories withone b-taggedjet,the minimuminvariant massfound whencombiningthereconstructedb jet andalepton,referred to as the mmin

Table 2

Inputdistributionstothefitinthedifferentevent cate-gories.Thenumberofjets,thenumberofb-taggedjets, thenumberofevents,andthe pTofthesoftestjetare

denotedwith Njets,Nb, Nevents,and“jet pminT ”,

respec-tively,whilethecategorycorrespondingtothebink in mreco

t¯t isindicatedwith“m reco t¯t k”.

Nb=1 Nb=2 Other Nb

Njets<2 Nevents n.a. Nevents

mreco

t¯t 1 m min

b jet pminT Nevents

mreco t¯t 2 m min b jet p min T Nevents mreco t¯t 3 m min

b jet pminT Nevents

mreco_t¯t 4 Nevents Nevents Nevents

sensitivityto constrain mMC

t [49]. In the remaining subcategories

with two b-tagged jets, the pT spectrum of the softest selected

jet in the event is used to constrain jet energy scale uncertain-tiesat smallvaluesof pT, thekinematic rangewhere systematic

uncertainties arethe largest.The distributionsused inthe fitare comparedtothedataafterthefitinthesupplementalmaterial.

The efficiencies of the kinematic reconstruction in data and simulationhavebeeninvestigatedinRef. [33] andtheywerefound todifferby0.2%.Therefore,theefficiencyinthesimulationis cor-rectedtomatchtheoneindata.Anuncertaintyof0.2%isassigned toeachbinofmt¯t independently.Thesameuncertaintyisalso

as-signedto t

¯

t eventswithoneortwo b-taggedjets,independently. For t

¯

t events with zero or more than two b-tagged jets, where the combinatorialbackground is larger, an uncertainty of0.5% is conservativelyassigned.Theseuncertaintiesaretreatedas uncorre-latedtoaccountforpossibledifferencesbetweenthedifferentm_t¯t

binsandcategoriesofb-taggedjet multiplicity.Similarly,an addi-tionaluncertaintyof1%isassignedtothesumofthebackground processes,independentlyforeach binofmreco

t¯t , inordertoreduce

thecorrelationbetweenthesignalandthebackgroundtemplates. Theimpact oftheseuncertainties on thefinal resultsis foundto besmallcomparedtothetotaluncertainty.

The dependence of the signal shapes, ofthe parameters Ak sel,

k

sel,

bk, and Ckb, and of the background contributions on mMCt

andonthenuisanceparameters

λ

ismodelledusingsecond-order polynomials [14]. In the fit, Gaussian priors are assumed for all thenuisanceparameters.Thenegativelog-likelihoodisthen mini-mized,usingthe Minuit program [50],withrespectto

σ

(μk)

t¯t ,m MC t ,

and

λ

. Finally, the fit uncertainties in the various

σ

(μk)

t¯t are

de-terminedusing Minos [50].Additional extrapolationuncertainties, which reflect the impact of modelling uncertainties on Ak_sel, are estimatedwithouttakingintoaccounttheconstraintsobtainedin the visiblephase space [14]. Moreover, an additional uncertainty arising from the limited statistical precision of the simulation is estimatedusingMCpseudo-experiments [14],wheretemplatesare variedwithintheirstatisticaluncertaintiestakingintoaccountthe correlationsbetweenthenominaltemplatesandthetemplates cor-responding tothe systematic variations. The template dependen-cies are then rederivedand the fit to the datais repeated more thantenthousandtimes.Foreachparameterofinterest,the root-mean-squareofthebestfitvaluesobtainedwiththisprocedureis takenasanadditionaluncertaintyandaddedinquadraturetothe totaluncertaintyfromthefit.

The measured

σ

(μk)

t¯t are shown in Fig. 2 and compared to

fixed-ordertheoretical predictionsinthe MS schemeatNLO [51] implemented for the purpose of this analysis in the mcfm v6.8 program [52,53].Inthe calculation,therenormalizationscale,

μ

r,

andfactorizationscale,

μ

f,arebothsettomt.TheMS massofthe

top quark evaluatedat thescale

μ

=

mt isdenoted withmt

(

mt

)

.

Fig. 2. Measuredvaluesofσ(μk)

t¯t (markers)andtheiruncertainties(verticalerror

bars)comparedtoNLOpredictionsintheMS schemeobtainedwithdifferentvalues ofmt(mt)(horizontallinesofdifferentstyles).Thevaluesofσ_t(μ_¯tk)areshownatthe

representativescaleoftheprocessμk,definedasthecentre-of-gravityofbink in

mt¯t.Thefirstandlastbinscontainalleventswithmt¯t<420GeV andmt¯t>810GeV,

respectively.

ThecalculationisinterfacedwiththeABMP16_5_nloPDFset [54], whichistheonlyavailablePDFsetwheremt istreatedintheMS

scheme andwhere the correlations between the gluon PDF,

α

S,

and mt are taken into account. In the calculation, the value of

α

S at theZ boson mass,

α

S

(

mZ

)

, isset to thevalue determined

in the ABMP16_5_nlo fit, which in the central PDF corresponds to 0

.

1191 [54].Inorderto demonstratethesensitivitytothe top quark mass,predictionsford

σ

t¯t

/

dmt¯t obtainedwithdifferent

val-uesofmt

(

mt

)

areshown.Furthermore,itisworthnotingthatthis

methodprovidesacrosssectionresultwithsignificantlyimproved precision comparedtomeasurements thatperformunfoldingasa separatestep,e.g. astheonedescribedinRef. [33].

The dominantuncertainties inthe measured

σ

(μk)

t¯t are

associ-ated withtheintegratedluminosity,theleptonidentification effi-ciencies,the jet energyscales and, atlarge m_t¯t,the modellingof thetopquark pT.Thetwolatteruncertaintiesaremarginally

con-strainedinthefit,whilethefirsttwoarenotconstrained. Further-more,thepost-fitvaluesofallnuisanceparametersarefoundtobe compatiblewiththeirpre-fitvalue,withinonestandarddeviation. Thenumericalvaluesofthemeasured

σ

(μk)

t¯t ,theircorrelations,the

impact of the various sources of uncertainty, and the pulls and constraints of the nuisance parameters related to the modelling uncertaintiescanbefoundinthesupplementalmaterial.

5. Extractionoftherunningofthetopquarkmass

The measured differential crosssection is used to extract the running of the top quark MS mass at NLO as a function of the scale

μ

=

mt¯t. The procedure is similar to the one used to

ex-tract the running of the charm quark mass [12]. The value of

mt

(

mt

)

is determined independently in each bin of mt¯t from a

χ

2 _{fit of fixed-order theoretical predictions at NLO to the}

mea-sured

σ

(μk)

tt¯ .The theoreticalpredictionsareobtainedasdescribed

in Section 4 for Fig. 2. The

χ

2 _{definition follows the one}

de-scribed inRef. [55],whichaccountsforasymmetriesinthe input uncertainties. Theextractedmt

(

mt

)

are then convertedtomt

(

μ

k

)

using the CRunDec v3.0 program [56], where

μ

k is the

repre-sentative scale ofthe process ina given binof m_t¯t,asdescribed in Section 3. As relevant in a NLO calculation, the conversion is performed withone-loop precision, assuming five active flavours (nf

=

5)and

α

S

(

mZ

)

=

0

.

1191 consistentlywiththeusedPDFset.

Thisprocedure isequivalentto extractingdirectlymt

(

μ

k

)

ineach

μ

k,providedthatitisrepresentativeofthephysicalenergyscaleof

theprocess.Infact,achangein

μ

k wouldcorrespondtoachange

inmt

(

μ

k

)

accordingto the RGE. The extracted valuesof mt

(

μ

k

)

andtheiruncertaintiescanbefoundinthesupplementalmaterial. In orderto benefitfrom the cancellation ofcorrelated uncer-tainties in the measured

σ

(μk)

t¯t , the ratios of the various mt

(

μ

k

)

to mt

(

μ

2

)

are considered. In particular, the quantities r12

=

mt

(

μ

1

)/

mt

(

μ

2

)

, r32

=

mt

(

μ

3

)/

mt

(

μ

2

)

, and r42

=

mt

(

μ

4

)/

mt

(

μ

2

)

are extracted. With this approach the running of mt, i.e. the

quantity predictedby the RGE (Eq. (1)),is accessed directly. The measurementatthescale

μ

2 ischosenasareferenceinorderto

minimizethecorrelationbetweentheextractedratios.

Four different types of systematic uncertainty are considered for the ratios: the uncertainty in the various

σ

(μk)

t¯t in the

visi-blephase space(referred toas fituncertainty), theextrapolation uncertainties,theuncertaintiesintheprotonPDFs,andthe uncer-taintyinthe valueof

α

S

(

mZ

)

.Thefit uncertaintyincludes

exper-imentalandmodellinguncertainties described inSection 3.Scale variations in the mcfm predictions are not performed, since the scale dependenceof mt is beinginvestigated at a fixed order in

perturbationtheory.Infact,scalevariationsinthehard scattering crosssectionareconventionallyperformedasameansof estimat-ingtheeffectofmissinghigherordercorrectionsandaretherefore notapplicableinthiscontext.

Uncertainties in the proton PDFs affect the mcfm prediction andtherefore the extractedvalues of the various mt

(

μ

k

)

. In

or-derto estimate their impact, thecalculation is repeatedforeach eigenvectorofthePDFsetandthedifferencesintheextracted ra-tiosare added inquadratureto yield thetotal PDF uncertainties. In the ABMP16_5_nlo PDF set,

α

S

(

mZ

)

is determined

simultane-ously with the PDFs, therefore its uncertainty is incorporated in thatofthePDFs.However,theuncertaintyin

α

S

(

mZ

)

alsoaffects

the CRunDec conversionfrommt

(

mt

)

tomt

(

μ

k

)

.Thiseffectis

es-timatedindependentlyandisfoundtobenegligible.

Theimpactofextrapolationuncertaintiesisestimatedby vary-ingthemeasured

σ

(μk)

t¯t withintheirextrapolationuncertainty,

sep-arately for each source and simultaneously in the different bins in mt¯t, taking the correlations into account. The various

contri-butions are added in quadrature to yield the total extrapolation uncertainty.

Thecorrelationsbetweentheextractedmassesarisingfromthe fit uncertaintyare estimated usingMC pseudo-experiments, tak-ing the correlations between the measured

σ

(μk)

t¯t asinputs. The

uncertaintiesarethenpropagated totheratiosusinglinear uncer-taintypropagation,takingtheestimatedcorrelationsintoaccount. Thenumericalvaluesoftheratiosaredeterminedtobe:

r12

=

1

.

030

±

0

.

018

(

fit

)

₋+00..003006

(

PDF+

α

S

)

₋+00..003002

(

extr

),

r32

=

0

.

982

±

0

.

025

(

fit

)

+₋00..006005

(

PDF+

α

S

)

±

0

.

004

(

extr

),

r42

=

0

.

904

±

0

.

050

(

fit

)

₋+00..019017

(

PDF+

α

S

)

₋+00..017013

(

extr

).

Here,thefituncertainty(fit),thecombinationofPDFand

α

S

un-certainty (PDF+

α

S), and the extrapolation uncertainty (extr) are

given. Themost relevantsources ofexperimental uncertainty are theintegratedluminosity,theleptonidentificationefficiencies,and thejet energyscale and resolution.Among modelling uncertain-tiesrelated to the powheg+pythia 8 simulation of the t

¯

t signal, thelargestcontributionsoriginatefromthescalevariations inthe partonshower,theuncertaintyintheshapeofthepT spectrumof

thetopquark,andthematchingscalebetweenthematrixelement andthe partonshower. The statisticaluncertainties are found to benegligible.Thecorrelationsbetweentheratiosarisingfromthe fituncertaintyareinvestigatedusinga pseudo-experiment proce-durewhichconsistsinrepeatingtheextractionoftheratiosusing

Fig. 3. Extracted running of the top quark mass mt(μ)/mt(μref) compared to

the RGE prediction at one-loop precision, with nf =5, evolved from the

ini-tial scaleμ0=μref=476GeV (upper).The result iscompared tothe value of

mincl

t (mt)/mt(μref),whereminclt (mt)isthevalueofmt(mt)extractedfromthe

in-clusivecrosssectionmeasuredinRef. [14],whichisbasedonthesamedataset. Theuncertaintyinmincl

t (mt)isevolvedfromtheinitialscaleμ0=minclt (mt),which

correspondstoabout163 GeV,usingthesameRGEprediction(lower).

pseudo-measurementsof

σ

(μk)

tt¯ ,generatedaccordingtothe

corre-spondingfittedvalues,uncertainties,andcorrelations.With

ρ

ik

be-ingthecorrelationbetweenri2 andrk2,theresultsare

ρ

13

=

13%,

ρ

14

= −

45%,and

ρ

34

=

11%.

Theextractedratiosmt

(

μ

k

)/

mt

(

μ

2

)

areshowninFig.3(upper)

togetherwiththeRGEprediction(Eq. (1))atone-loopprecision.In the figure,the referencescale

μ

2 is indicated with

μ

ref, andthe

RGE evolutioniscalculatedfromtheinitialscale

μ

0

=

μ

ref.Good

agreementbetweentheextractedrunningandtheRGEprediction isobserved.

For comparison, the MS mass of the top quark is also ex-tracted from the inclusive cross section measured in Ref. [14], using Hathor 2.0 [57] predictions at NLO interfaced with the ABMP16_5_nlo PDF set, and is denoted with mincl

t

(

mt

)

. Fig. 3

(lower) comparestheextractedratiosmt

(

μ

k

)/

mt

(

μ

2

)

tothevalue

ofmincl_t

(

mt

)/

mt

(

μ

2

)

.The uncertaintyinminclt

(

mt

)

includesfit,

ex-trapolation,andPDFuncertainties,andisevolvedtohigherscales, while thevalue ofmt

(

μ

2

)

inthe ratiominclt

(

mt

)/

mt

(

μ

2

)

istaken

withoutuncertainty.Here,theRGEevolutioniscalculatedfromthe initial scale

μ

0

=

minclt

(

mt

)

,which corresponds toabout163 GeV.

Theextractedvalue ofmincl

t

(

mt

)

andits uncertaintycanbefound

inthesupplementalmaterial.

Finally,theextractedrunningisparametrizedwiththefunction f

(

x

,

μ

)

=

x [r

(

μ

)

−

1]

+

1

,

(6)

where r

(

μ

)

=

mt

(

μ

)/

mt

(

μ

2

)

corresponds to the RGE prediction

r

(

μ

)

forx

=

1 andto1,i.e. norunning,forx

=

0.Thebestfitvalue forx,denotedwithx,

ˆ

isdetermined viaa

χ

2 _{fitto theextracted}

ratiostakingthecorrelations

ρ

ikintoaccount,andisfoundtobe

ˆ

x

=

2

.

05

±

0

.

61

(

fit

)

₋+0_0..31₅₅

(

PDF

+

α

S

)

₋+₀0._.24₄₉

(

extr

).

The result shows agreement between the extracted running and theRGEpredictionatone-loopprecisionwithin1.1standard devi-ationsintheGaussianapproximationandexcludestheno-running hypothesisatabove95%confidencelevel(2.1standarddeviations) inthesameapproximation.

6. Summary

InthisLetter,thefirstexperimentalinvestigationoftherunning ofthetop quark mass,mt, ispresented.Therunning isextracted

from a measurement of the differential top quark-antiquark (t

¯

t) cross section as a function of the invariant mass of the t

¯

t sys-tem,m_t¯t.Thedifferential t

¯

t crosssection,d

σ

_t¯t

/

dm_t¯t,isdetermined at the parton level using a maximum-likelihood fit to distribu-tions of final-state observables, using t

¯

t candidate events in the e±

μ

∓ channel. This technique allows the nuisanceparameters to beconstrainedsimultaneouslywiththedifferentialcrosssectionin thevisiblephasespaceandthereforeprovidesresultswith signifi-cantlyimprovedprecisioncomparedtoconventionalproceduresin whichtheunfoldingisperformedasaseparate step.The analysis isperformedusingproton-protoncollisiondataatacentre-of-mass energyof13 TeV recordedbytheCMSdetectorattheCERNLHCin 2016,correspondingtoanintegratedluminosityof35.9 fb−1.

The runningmass mt

(

μ

)

, asdefined inthe modified minimal

subtraction(MS)renormalizationscheme,isextractedatone-loop precision asa function ofmt¯t bycomparing fixed-order

theoreti-calpredictionsatnext-to-leadingordertothemeasuredd

σ

t¯t

/

dmt¯t.

The extracted running of mt is found to be in agreement with

the predictionof the corresponding renormalization group equa-tion,within1.1standarddeviations,andtheno-runninghypothesis is excluded at above 95% confidence level. The running of mt is

probeduptoascaleoftheorderof1 TeV. 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,wegratefullyacknowledgethecomputingcentresand personneloftheWorldwideLHCComputingGridfordeliveringso effectivelythe computinginfrastructureessential to ouranalyses. Finally, we acknowledge the enduring support for the construc-tionandoperation oftheLHCandthe CMSdetectorprovidedby thefollowingfunding agencies:BMBWFandFWF(Austria); FNRS andFWO (Belgium); CNPq,CAPES, FAPERJ, FAPERGS, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MOST, and NSFC (China); COLCIENCIAS (Colombia); MSESand CSF (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);NASU andSFFR (Ukraine);STFC(United Kingdom);DOE andNSF(USA).

Individuals have received support from the Marie-Curie pro-gramme and the European Research Council and Horizon 2020 Grant, contract Nos. 675440, 752730, and 765710 (European Union); the Leventis Foundation; the Alfred P. Sloan Founda-tion; the Alexander von Humboldt Foundation; the Belgian Fed-eral Science Policy 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 Technolo-gie (IWT-Belgium); the F.R.S.-FNRS and FWO (Belgium) under the “Excellence of Science – EOS” – be.h project n. 30820817; the Beijing Municipal Science & Technology Commission, No. Z181100004218003; The Ministryof Education,Youth andSports (MEYS) of the Czech Republic; the Lendület (“Momentum”) Pro-gramme and the János Bolyai Research Scholarship of the Hun-garian Academy of Sciences, the New National Excellence Pro-gram ÚNKP, the NKFIA research grants 123842, 123959, 124845, 124850, 125105, 128713, 128786, and 129058 (Hungary); the Council of Science and Industrial Research, India; the HOMING PLUSprogrammeoftheFoundation forPolishScience,cofinanced from European Union, Regional Development Fund, the Mobility Plus programme of the Ministry of Science and Higher Educa-tion, the National Science Center (Poland), contracts Harmonia 2014/14/M/ST2/00428,Opus2014/13/B/ST2/02543,2014/15/B/ST2/ 03998,and2015/19/B/ST2/02861,Sonata-bis2012/07/E/ST2/01406; the National Priorities Research Program by Qatar National Re-search Fund; the Ministry of Science and Education, grant no. 3.2989.2017 (Russia); thePrograma Estatal de Fomento de la In-vestigación Científica y Técnica de Excelencia María de Maeztu, grantMDM-2015-0509andtheProgramaSeveroOchoadel Princi-pado de Asturias;the ThalisandAristeiaprogrammes cofinanced byEU-ESFandtheGreekNSRF;theRachadapisekSompotFundfor Postdoctoral Fellowship, Chulalongkorn University and the Chu-lalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand);theNvidiaCorporation;TheWelchFoundation, contractC-1845;andtheWestonHavensFoundation(USA). Appendix A. Supplementarymaterial

Supplementarymaterialrelatedtothisarticlecanbefound on-lineathttps://doi.org/10.1016/j.physletb.2020.135263.

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TheCMSCollaboration

A.M. Sirunyan

†

,

A. Tumasyan

YerevanPhysicsInstitute,Yerevan,Armenia

W. Adam,

F. Ambrogi,

T. Bergauer,

J. Brandstetter,

M. Dragicevic,

J. Erö,

A. Escalante Del Valle,

M. Flechl,

R. Frühwirth

1

,

M. Jeitler

1

,

N. Krammer,

I. Krätschmer,

D. Liko,

T. Madlener,

I. Mikulec,

N. Rad,

J. Schieck

1

,

R. Schöfbeck,

M. Spanring,

D. Spitzbart,

W. Waltenberger,

C.-E. Wulz

1

,

M. Zarucki

InstitutfürHochenergiephysik,Wien,Austria

V. Drugakov,

V. Mossolov,

J. Suarez Gonzalez

InstituteforNuclearProblems,Minsk,Belarus

M.R. Darwish,

E.A. De Wolf,

D. Di Croce,

X. Janssen,

A. Lelek,

M. Pieters,

H. Rejeb Sfar,

H. Van Haevermaet,

P. Van Mechelen,

S. Van Putte,

N. Van Remortel

UniversiteitAntwerpen,Antwerpen,Belgium

F. Blekman,

E.S. Bols,

S.S. Chhibra,

J. D’Hondt,

J. De Clercq,

D. Lontkovskyi,

S. Lowette,

I. Marchesini,

S. Moortgat,

Q. Python,

K. Skovpen,

S. Tavernier,

W. Van Doninck,

P. Van Mulders

VrijeUniversiteitBrussel,Brussel,Belgium

D. Beghin,

B. Bilin,

H. Brun,

B. Clerbaux,

G. De Lentdecker,

H. Delannoy,

B. Dorney,

L. Favart,

A. Grebenyuk,

A.K. Kalsi,

A. Popov,

N. Postiau,

E. Starling,

L. Thomas,

C. Vander Velde,

P. Vanlaer,

D. Vannerom

UniversitéLibredeBruxelles,Bruxelles,Belgium

T. Cornelis,

D. Dobur,

I. Khvastunov

2

,

M. Niedziela,

C. Roskas,

M. Tytgat,

W. Verbeke,

B. Vermassen,

M. Vit

GhentUniversity,Ghent,Belgium

O. Bondu,

G. Bruno,

C. Caputo,

P. David,

C. Delaere,

M. Delcourt,

A. Giammanco,

V. Lemaitre,

J. Prisciandaro,

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,

P. Rebello Teles

CentroBrasileirodePesquisasFisicas,RiodeJaneiro,Brazil

E. Belchior Batista Das Chagas,

W. Carvalho,

J. Chinellato

3

,

E. Coelho,

E.M. Da Costa,

G.G. Da Silveira

4

,

D. De Jesus Damiao,

C. De Oliveira Martins,

S. Fonseca De Souza,

L.M. Huertas Guativa,

H. Malbouisson,

J. Martins

5

,

D. Matos Figueiredo,

M. Medina Jaime

6

,

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

3

,

F. Torres Da Silva De Araujo,

A. Vilela Pereira

UniversidadedoEstadodoRiodeJaneiro,RiodeJaneiro,Brazil

C.A. Bernardes

a

,

L. Calligaris

a

,

T.R. Fernandez Perez Tomei

a

,

E.M. Gregores

b

,

D.S. Lemos,

P.G. Mercadante

b

,

S.F. Novaes

a

,

Sandra

S. Padula

a

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

A. Aleksandrov,

G. Antchev,

R. Hadjiiska,

P. Iaydjiev,

M. Misheva,

M. Rodozov,

M. Shopova,

G. Sultanov

M. Bonchev,

A. Dimitrov,

T. Ivanov,

L. Litov,

B. Pavlov,

P. Petkov

UniversityofSofia,Sofia,Bulgaria

W. Fang

7

,

X. Gao

7

,

L. Yuan

BeihangUniversity,Beijing,China

G.M. Chen,

H.S. Chen,

M. Chen,

C.H. Jiang,

D. Leggat,

H. Liao,

Z. Liu,

A. Spiezia,

J. Tao,

E. Yazgan,

H. Zhang,

S. Zhang

8

,

J. Zhao

InstituteofHighEnergyPhysics,Beijing,China

A. Agapitos,

Y. Ban,

G. Chen,

A. Levin,

J. Li,

L. Li,

Q. Li,

Y. Mao,

S.J. Qian,

D. Wang,

Q. Wang

StateKeyLaboratoryofNuclearPhysicsandTechnology,PekingUniversity,Beijing,China

M. Ahmad,

Z. Hu,

Y. Wang

TsinghuaUniversity,Beijing,China

M. Xiao

ZhejiangUniversity,Hangzhou,China

C. Avila,

A. Cabrera,

C. Florez,

C.F. González Hernández,

M.A. Segura Delgado

UniversidaddeLosAndes,Bogota,Colombia

J. Mejia Guisao,

J.D. Ruiz Alvarez,

C.A. Salazar González,

N. Vanegas Arbelaez

UniversidaddeAntioquia,Medellin,Colombia

D. Giljanovi ´c,

N. Godinovic,

D. Lelas,

I. Puljak,

T. Sculac

UniversityofSplit,FacultyofElectricalEngineering,MechanicalEngineeringandNavalArchitecture,Split,Croatia

Z. Antunovic,

M. Kovac

UniversityofSplit,FacultyofScience,Split,Croatia

V. Brigljevic,

D. Ferencek,

K. Kadija,

B. Mesic,

M. Roguljic,

A. Starodumov

9

,

T. Susa

InstituteRudjerBoskovic,Zagreb,Croatia

M.W. Ather,

A. Attikis,

E. Erodotou,

A. Ioannou,

M. Kolosova,

S. Konstantinou,

G. Mavromanolakis,

J. Mousa,

C. Nicolaou,

F. Ptochos,

P.A. Razis,

H. Rykaczewski,

D. Tsiakkouri

UniversityofCyprus,Nicosia,Cyprus

M. Finger

10

,

M. Finger Jr.

10

,

A. Kveton,

J. Tomsa

CharlesUniversity,Prague,CzechRepublic

E. Ayala

EscuelaPolitecnicaNacional,Quito,Ecuador

E. Carrera Jarrin

UniversidadSanFranciscodeQuito,Quito,Ecuador

Y. Assran

11

,

12

,

S. Elgammal

12

S. Bhowmik,

A. Carvalho Antunes De Oliveira,

R.K. Dewanjee,

K. Ehataht,

M. Kadastik,

M. Raidal,

C. Veelken

NationalInstituteofChemicalPhysicsandBiophysics,Tallinn,Estonia

P. Eerola,

L. Forthomme,

H. Kirschenmann,

K. Osterberg,

M. Voutilainen

DepartmentofPhysics,UniversityofHelsinki,Helsinki,Finland

F. Garcia,

J. Havukainen,

J.K. Heikkilä,

V. Karimäki,

M.S. Kim,

R. Kinnunen,

T. Lampén,

K. Lassila-Perini,

S. Laurila,

S. Lehti,

T. Lindén,

P. Luukka,

T. Mäenpää,

H. Siikonen,

E. Tuominen,

J. Tuominiemi

HelsinkiInstituteofPhysics,Helsinki,Finland

T. Tuuva

LappeenrantaUniversityofTechnology,Lappeenranta,Finland

M. Besancon,

F. Couderc,

M. Dejardin,

D. Denegri,

B. Fabbro,

J.L. Faure,

F. Ferri,

S. Ganjour,

A. Givernaud,

P. Gras,

G. Hamel de Monchenault,

P. Jarry,

C. Leloup,

B. Lenzi,

E. Locci,

J. Malcles,

J. Rander,

A. Rosowsky,

M.Ö. Sahin,

A. Savoy-Navarro

13

,

M. Titov,

G.B. Yu

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

S. Ahuja,

C. Amendola,

F. Beaudette,

P. Busson,

C. Charlot,

B. Diab,

G. Falmagne,

R. Granier de Cassagnac,

I. Kucher,

A. Lobanov,

C. Martin Perez,

M. Nguyen,

C. Ochando,

P. Paganini,

J. Rembser,

R. Salerno,

J.B. Sauvan,

Y. Sirois,

A. Zabi,

A. Zghiche

LaboratoireLeprince-Ringuet,CNRS/IN2P3,EcolePolytechnique,InstitutPolytechniquedeParis,France

J.-L. Agram

14

,

J. Andrea,

D. Bloch,

G. Bourgatte,

J.-M. Brom,

E.C. Chabert,

C. Collard,

E. Conte

14

,

J.-C. Fontaine

14

,

D. Gelé,

U. Goerlach,

M. Jansová,

A.-C. Le Bihan,

N. Tonon,

P. Van Hove

UniversitédeStrasbourg,CNRS,IPHCUMR7178,Strasbourg,France

S. Gadrat

CentredeCalculdel’InstitutNationaldePhysiqueNucleaireetdePhysiquedesParticules,CNRS/IN2P3,Villeurbanne,France

S. Beauceron,

C. Bernet,

G. Boudoul,

C. Camen,

A. Carle,

N. Chanon,

R. Chierici,

D. Contardo,

P. Depasse,

H. El Mamouni,

J. Fay,

S. Gascon,

M. Gouzevitch,

B. Ille,

Sa. Jain,

F. Lagarde,

I.B. Laktineh,

H. Lattaud,

A. Lesauvage,

M. Lethuillier,

L. Mirabito,

S. Perries,

V. Sordini,

L. Torterotot,

G. Touquet,

M. Vander Donckt,

S. Viret

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

T. Toriashvili

15

GeorgianTechnicalUniversity,Tbilisi,Georgia

Z. Tsamalaidze

10

TbilisiStateUniversity,Tbilisi,Georgia

C. Autermann,

L. Feld,

M.K. Kiesel,

K. Klein,

M. Lipinski,

D. Meuser,

A. Pauls,

M. Preuten,

M.P. Rauch,

J. Schulz,

M. Teroerde,

B. Wittmer

RWTHAachenUniversity,I.PhysikalischesInstitut,Aachen,Germany

M. Erdmann,

B. Fischer,

S. Ghosh,

T. Hebbeker,

K. Hoepfner,

H. Keller,

L. Mastrolorenzo,

M. Merschmeyer,

A. Meyer,

P. Millet,

G. Mocellin,

S. Mondal,

S. Mukherjee,

D. Noll,

A. Novak,

T. Pook,

A. Pozdnyakov,

T. Quast,

M. Radziej,

Y. Rath,

H. Reithler,

J. Roemer,

A. Schmidt,

S.C. Schuler,

A. Sharma,

S. Wiedenbeck,

S. Zaleski

G. Flügge,

W. Haj Ahmad

16

,

O. Hlushchenko,

T. Kress,

T. Müller,

A. Nowack,

C. Pistone,

O. Pooth,

D. Roy,

H. Sert,

A. Stahl

17

RWTHAachenUniversity,III.PhysikalischesInstitutB,Aachen,Germany

M. Aldaya Martin,

P. Asmuss,

I. Babounikau,

H. Bakhshiansohi,

K. Beernaert,

O. Behnke,

A. Bermúdez Martínez,

D. Bertsche,

A.A. Bin Anuar,

K. Borras

18

,

V. Botta,

A. Campbell,

A. Cardini,

P. Connor,

S. Consuegra Rodríguez,

C. Contreras-Campana,

V. Danilov,

A. De Wit,

M.M. Defranchis,

C. Diez Pardos,

D. Domínguez Damiani,

G. Eckerlin,

D. Eckstein,

T. Eichhorn,

A. Elwood,

E. Eren,

E. Gallo

19

,

A. Geiser,

A. Grohsjean,

M. Guthoff,

M. Haranko,

A. Harb,

A. Jafari,

N.Z. Jomhari,

H. Jung,

A. Kasem

18

,

M. Kasemann,

H. Kaveh,

J. Keaveney,

C. Kleinwort,

J. Knolle,

D. Krücker,

W. Lange,

T. Lenz,

J. Lidrych,

K. Lipka,

W. Lohmann

20

,

R. Mankel,

I.-A. Melzer-Pellmann,

A.B. Meyer,

M. Meyer,

M. Missiroli,

G. Mittag,

J. Mnich,

S.O. Moch,

A. Mussgiller,

V. Myronenko,

D. Pérez Adán,

S.K. Pflitsch,

D. Pitzl,

A. Raspereza,

A. Saibel,

M. Savitskyi,

V. Scheurer,

P. Schütze,

C. Schwanenberger,

R. Shevchenko,

A. Singh,

H. Tholen,

O. Turkot,

A. Vagnerini,

M. Van De Klundert,

R. Walsh,

Y. Wen,

K. Wichmann,

C. Wissing,

O. Zenaiev,

R. Zlebcik

DeutschesElektronen-Synchrotron,Hamburg,Germany

R. Aggleton,

S. Bein,

L. Benato,

A. Benecke,

V. Blobel,

T. Dreyer,

A. Ebrahimi,

F. Feindt,

A. Fröhlich,

C. Garbers,

E. Garutti,

D. Gonzalez,

P. Gunnellini,

J. Haller,

A. Hinzmann,

A. Karavdina,

G. Kasieczka,

R. Klanner,

R. Kogler,

N. Kovalchuk,

S. Kurz,

V. Kutzner,

J. Lange,

T. Lange,

A. Malara,

J. Multhaup,

C.E.N. Niemeyer,

A. Perieanu,

A. Reimers,

O. Rieger,

C. Scharf,

P. Schleper,

S. Schumann,

J. Schwandt,

J. Sonneveld,

H. Stadie,

G. Steinbrück,

F.M. Stober,

B. Vormwald,

I. Zoi

UniversityofHamburg,Hamburg,Germany

M. Akbiyik,

C. Barth,

M. Baselga,

S. Baur,

T. Berger,

E. Butz,

R. Caspart,

T. Chwalek,

W. De Boer,

A. Dierlamm,

K. El Morabit,

N. Faltermann,

M. Giffels,

P. Goldenzweig,

A. Gottmann,

M.A. Harrendorf,

F. Hartmann

17

,

U. Husemann,

S. Kudella,

S. Mitra,

M.U. Mozer,

D. Müller,

Th. Müller,

M. Musich,

A. Nürnberg,

G. Quast,

K. Rabbertz,

M. Schröder,

I. Shvetsov,

H.J. Simonis,

R. Ulrich,

M. Wassmer,

M. Weber,

C. Wöhrmann,

R. Wolf

KarlsruherInstitutfuerTechnologie,Karlsruhe,Germany

G. Anagnostou,

P. Asenov,

G. Daskalakis,

T. Geralis,

A. Kyriakis,

D. Loukas,

G. Paspalaki

InstituteofNuclearandParticlePhysics(INPP),NCSRDemokritos,AghiaParaskevi,Greece

M. Diamantopoulou,

G. Karathanasis,

P. Kontaxakis,

A. Manousakis-katsikakis,

A. Panagiotou,

I. Papavergou,

N. Saoulidou,

A. Stakia,

K. Theofilatos,

K. Vellidis,

E. Vourliotis

NationalandKapodistrianUniversityofAthens,Athens,Greece

G. Bakas,

K. Kousouris,

I. Papakrivopoulos,

G. Tsipolitis

NationalTechnicalUniversityofAthens,Athens,Greece

I. Evangelou,

C. Foudas,

P. Gianneios,

P. Katsoulis,

P. Kokkas,

S. Mallios,

K. Manitara,

N. Manthos,

I. Papadopoulos,

J. Strologas,

F.A. Triantis,

D. Tsitsonis

UniversityofIoánnina,Ioánnina,Greece

M. Bartók

21

,

R. Chudasama,

M. Csanad,

P. Major,

K. Mandal,

A. Mehta,

M.I. Nagy,

G. Pasztor,

O. Surányi,

G.I. Veres

MTA-ELTELendületCMSParticleandNuclearPhysicsGroup,EötvösLorándUniversity,Budapest,Hungary

G. Bencze,

C. Hajdu,

D. Horvath

22

,

F. Sikler,

T.Á. Vámi,

V. Veszpremi,

G. Vesztergombi

†