Search for disappearing tracks in proton-proton collisions at √s=13TeV

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Contents lists available atScienceDirect

Physics

Letters

B

www.elsevier.com/locate/physletb

Search

for

disappearing

tracks

in

proton-proton

collisions

at

√

s

=

13 TeV

.

The

CMS

Collaboration

CERN,Switzerland

a

r

t

i

c

l

e

i

n

f

o

a

b

s

t

r

a

c

t

Articlehistory: Received10April2020

Receivedinrevisedform13May2020 Accepted18May2020

Availableonline22May2020 Editor:M.Doser

Keywords:

CMS Physics

Disappearingtracks

Asearchispresentedforlong-livedchargedparticlesthatdecaywithinthevolumeofthesilicontracker ofthe CMSexperiment. Suchparticlescan produce eventswith anisolatedtrack thatismissing hits intheoutermostlayersofthesilicontracker,andisalsoassociatedwithlittleenergydepositedinthe calorimeters and nohits inthe muondetectors. The searchfor eventswith this“disappearingtrack” signature is performed in a sample of proton-proton collisions recorded by the CMS experiment at theLHCwithacenter-of-massenergyof13 TeV,corresponding toanintegratedluminosityof101 fb−1 recordedin2017and 2018.Theobservationof48 eventsisconsistentwiththeestimatedbackground of47.8+₋2₂._.7₃(stat)±8.1(syst) events.Upper limits are set oncharginoproductionin thecontext ofan anomaly-mediated supersymmetry breakingmodel for purelywinoand higgsino neutralinoscenarios. At95%confidencelevel,thefirstconstraintisplacedoncharginomassesinthehiggsinocase,excluding below750 (175) GeV foralifetimeof3(0.05) ns.Inthewinocase,theresultsofthissearcharecombined with apreviousCMS searchto produce aresult representing thecomplete LHCdata set recorded in 2015–2018,themoststringentconstraintstodate.At95%confidencelevel,charginomassesinthewino caseareexcludedbelow884 (474) GeV foralifetimeof3(0.2) ns.

1. Introduction

Many beyond-the-standard-model (BSM) scenarios introduce long-lived chargedparticles that could decay within the volume of the tracking detectors used by the CERN LHC experiments. If the decayproducts of such a particle are undetected, either be-causethey havetoo littlemomentum to be reconstructedor be-causetheyinteractonlyweakly,a“disappearingtrack”signatureis produced.Thissignature isidentiﬁedasan isolatedparticletrack thatextendsfromtheinteractionregionbutismissinghitsinthe outermostregionofthetrackingdetector,andalsohaslittle associ-atedenergydepositedinthecalorimetersandnoassociatedhitsin theoutermuondetectors.Becausestandardmodel(SM)processes rarelyproducethissignature,backgroundprocessesarealmost en-tirelycomposed offailuresof theparticle reconstructionor track ﬁndingalgorithms.

The disappearing track signature arises in a broad range of BSMscenarios [1–13]. For example, in anomaly-mediated super-symmetry breaking (AMSB) [14,15] the particle mass spectrum includes a chargino and neutralino (electroweakinos

χ

±₁ and

χ

0₁, respectively)that are nearly degeneratein mass.Inthisscenario,

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

withachargino-neutralino massdifferenceoforder100MeV, the chargino is long-lived and can reach the CMS tracking detector before decaying to a neutralino and a pion (

χ

±1

→

χ

0

1

π

±). The

produced pion doesnot havesuﬃcient momentum to be recon-structed asa track, nor to contribute signiﬁcantly to the energy associatedwiththeoriginalcharginotrack.Theneutralino,asthe lightestsupersymmetricparticle(LSP),isstableassumingR-parity conservationandinteractsonlyweakly,leavingnotraceinthe de-tector. Consequently,the decayofan AMSBcharginoto aweakly interactingneutralinoandanunreconstructedpionwouldproduce thedisappearingtracksignature.

Thisletterpresentsa searchfordisappearingtracksin proton-proton (pp) collision data collected at

√

s

=

13TeV throughout 2017 and 2018, corresponding to an integrated luminosity of 101 fb−1. The results of this search are presented in terms of chargino masses and lifetimes within the context of AMSB. The results are also presented more generallyin a formthat can be used to test any BSM scenario producing the disappearing track signature. The ATLAS experiment has previously excluded AMSB, withapurely winoLSP,forcharginomassesbelow460GeV with alifetimeof0

.

2 ns [16].The CMSexperimenthasexcludedAMSB chargino massesfora purely winoLSP below715GeV for a life-time of3 ns [17],usingthedatacollected during 2015and2016. This search extends the previous CMS results to encompass the

https://doi.org/10.1016/j.physletb.2020.135502

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entire available

√

s

=

13TeV data set, referred to as the Run 2 dataset,correspondingtoatotalintegratedluminosityof140 fb−1. Priortothe2017data-takingperiod,anewpixeldetectorwas in-stalled aspartofthePhase 1 upgrade [18,19]. Thisnewdetector containsafourthinnerlayerata radiusof2

.

9 cm fromthe inter-action region.The additionof thisnew layer enablesthis search to accept shortertracks that traverse fewer layers of thetracker, thereby increasing itssensitivity toshorterlifetime particles.The interpretationoftheresultsisextendedtoincludethedirect elec-troweakproduction ofcharginos inthe caseofa purely higgsino LSP.

2. TheCMSdetector

Thecentralfeature oftheCMSapparatusisasuperconducting solenoidof6 m internaldiameter.Withinthesolenoidvolumeare a silicon pixel andstrip tracker, a lead tungstate crystal electro-magnetic calorimeter(ECAL), anda brass and scintillator hadron calorimeter (HCAL), each composed of a barrel and two endcap sections.Forwardcalorimetersextendthepseudorapiditycoverage providedbythebarrelandendcapdetectors.Muonsaremeasured ingas-ionizationdetectorsembeddedinthesteelﬂux-returnyoke outsidethesolenoid.

Thesilicontrackermeasureschargedparticleswithinthe pseu-dorapidity range

|

η

|

<

2

.

5. Duringthe LHC running periodwhen the data used in this analysis were recorded, the silicon tracker consisted of 1856 silicon pixel and 15 148 silicon strip detector modules.

Events of interest are selected using a two-tiered trigger sys-tem [20].The ﬁrstlevel (L1),composedofcustom hardware pro-cessors, usesinformationfromthe calorimetersandmuon detec-tors to selectevents at a rate of around 100 kHz within a ﬁxed time interval of less than 4μs. The second level, known as the high-level trigger (HLT),consists ofa farm ofprocessors running a version of the full eventreconstruction software optimized for fastprocessing,andreducestheeventrateto

O(

1

)

kHz beforedata storage.

AmoredetaileddescriptionoftheCMSdetector,togetherwith adeﬁnitionofthecoordinatesystemused andthe relevant kine-maticvariables,canbefoundinRef. [21].

3. Datasets

Thissearchisbasedonpp collisiondatarecordedbytheCMS detectorat

√

s

=

13TeV correspondingtoanintegratedluminosity of 42 fb−1 [22] and 60 fb−1 [23] from the 2017 and 2018 data-takingperiods,respectively.

Simulatedsignaleventsaregeneratedatleadingorder(LO) pre-cisionwith pythia 8.240 [24],usingtheNNPDF3.0 LO [25] parton distributionfunction(PDF)setwiththeCP5tune [26] todescribe the underlying event. Supersymmetric particle mass spectra are produced by isajet 7.70 [27], for chargino masses in the range 100–1100 (100–900) GeV in steps of 100 GeV for the wino (hig-gsino)LSPcase.Theratioofthevacuumexpectationvaluesofthe two Higgsdoublets (tan

β

) isﬁxed to 5,witha positive higgsino mass parameter (

μ

>

0). The

χ

±1–

χ

0

1 mass difference has little

dependenceontan

β

andthesignof

μ

[28]. Whilethismass dif-ferencetypicallydeterminesthechargino’sproperdecaytime(the lifetimeintherestframe,

τ

),inthesesimulatedsignalevents

τ

is explicitlyvariedfrom6

.

67 ps to333 ns (correspondingtoa range inc

τ

of0

.

2–10000 cm)inlogarithmicsteps,toexaminesensitivity toabroaderrangeofmodels.

In thewino LSP case, the chargino branching fraction(

B

) for

χ

±1

→

χ

0

1

π

± is set to 100%, and both

χ

1±

χ

∓1 and

χ

±1

χ

0

1

produc-tionprocessesaresimulated.InthehiggsinoLSP case,thesecond

neutralino (

χ

0₂) is completely degenerate in mass with

χ

0₁, hav-ingequalproductioncrosssections(

σ

)andbranchingfractionsfor the

χ

±1

→

χ

0

1,2

+

X decays. FollowingRef. [29], theseare takento

be95.5%for

χ

±1

→

χ

0

1,2

π

±,3%for

χ

±1

→

χ

0

1,2e

ν

,and1.5%for

χ

±1

→

χ

01,2

μν

intherangeofcharginomassesofinterest,andboth

χ

±1

χ

∓1

and

χ

±₁

χ

0₁_,₂productionprocessesaresimulated.

Simulatedsignaleventsarenormalizedusingcrosssections cal-culated to next-to-leading order plus next-to-leading-logarithmic (NLO+NLL) precision, using Resummino 1.0.9 [30,31] with the CTEQ6.6 [32] andMSTW2008nlo90cl [33] PDF sets,and theﬁnal numbersarecalculatedusingthePDF4LHC recommendations [34] for the two sets of crosssections. In thewino case, the ratio of

χ

±1

χ

0

1 to

χ

±1

χ

1∓ productionis roughly2:1 forall charginomasses

considered.Inthehiggsinocase,theratioof

χ

±1

χ

0

1,2to

χ

±1

χ

∓1

pro-ductionisroughly7:2.

AsanLOgenerator, pythia isknowntobedeﬁcientinmodeling the rateofinitial-state radiation(ISR) andthe resultinghadronic recoil [35,36], so data-derived corrections forthis deﬁciency are appliedasfunctionsofthetransversemomentum(pT)ofthe

elec-troweakinopair (either

χ

±1

χ

∓1 or

χ

±1

χ

0

1,2). Similar tothe method

usedinRef. [36],thecorrectionfactorsarederivedastheratioof the pT of Z

→μμ

candidates in datato simulated pythia events,

under theassumption thatthe productionofISR in Z bosonand electroweakino paireventsaresimilar, sincebothareelectroweak processes. The ISR correction factors typically range between1.8 and2.0inthekinematicregionrelevantforthissearch.

Simulated events are generated with a Monte Carlo program incorporating afull modelofthe CMSdetector,basedon Geant4 [37],andreconstructedwiththesamesoftwareusedforcollision data. Simulated minimum bias events are superimposed on the hardinteractiontodescribetheeffectofadditionalinelasticpp in-teractionswithinthesameorneighboringbunchcrossings,known aspileup,andthesamplesare weightedtomatchthepileup dis-tributionobservedindata.

4. Eventreconstructionandselection

A particle-ﬂow (PF) algorithm [38] aims to reconstruct and identify each individual particle in an event with an optimized combinationofinformationfromthevariouselementsoftheCMS detector. The energyof photonsis obtainedfromthe ECAL mea-surement. Theenergyofelectronsisdeterminedfroma combina-tion oftheelectronmomentum attheprimary interactionvertex as determined by the tracker, the energy of the corresponding ECAL cluster, and the energy sumof all bremsstrahlung photons spatially compatiblewithoriginatingfromtheelectron track.The energyofmuonsisobtainedfromthecurvatureofthe correspond-ing track. The energy of charged hadrons is determined from a combinationoftheir momentummeasuredinthetrackerandthe matching ECAL and HCAL energy deposits, corrected for the re-sponse function ofthe calorimeters to hadronic showers. Finally, theenergyofneutralhadronsisobtainedfromthecorresponding correctedECALandHCALenergies.

For each event, hadronicjets are clustered from these recon-structedparticles usingtheinfrared- andcollinear-safe anti-kT

al-gorithm [39,40] with adistanceparameter of0.4. Jet momentum is determined asthe vector sum of all particle momenta in the jet, and is found from simulation to be, on average, within 5 to 10% ofthetrue momentumoverthe entire pT spectrum and

de-tectoracceptance.Hadronic

τ

leptondecaysarereconstructedwith thehadron-plus-stripsalgorithm [41],whichstartsfromthe recon-structedjets.

Themissingtransversemomentumvectorp

miss_T iscomputedas the negative vector sumofthetransverse momentaof allthe PF

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candidatesinanevent [42],anditsmagnitudeisdenotedaspmiss_T . The

pmissT ismodiﬁedtoaccountforcorrectionstotheenergyscale

ofthereconstructedjetsintheevent.Therelatedvector

pmiss_T ,μ/ is calculatedinthesamemanneras

pmissT ,exceptingthatthe

trans-versemomentaofPFmuonsareignored.Themagnitudeof

pmiss_T ,μ/

isdenotedby p_Tmiss,μ/. Signaleventsforthissearch typicallyhave noreconstructedmuons,inwhichcase

pmiss_T and

pmiss_T ,μ/ are iden-tical.

AstrackinginformationisnotavailableintheL1trigger,events are collected by several triggers requiring large p_Tmiss or pmiss_T ,μ/, whichwouldbeproducedinsignal eventsbyan ISR jetrecoiling againsttheelectroweakinopair.TheL1triggersrequirepmissT above

athresholdthat wasvariedduring thedata-takingperiod accord-ing tothe instantaneous luminosity. TheHLT requires both pmissT

andpmiss_T ,μ/ witharangeofthresholds.Thelowestthreshold trig-ger,designedspeciallyforthissearch,requirespmissT

>

105GeV and

anisolatedtrackwithp_T

>

50GeV andatleast5associatedtracker hitsatthe HLT.Theremaining triggers requirepmiss_T or pmiss_T ,/μ

>

120GeV anddonothaveatrackrequirement.

Afterthetrigger,eventsselectedoﬄinearerequiredtobe con-sistentwiththetopologyofanISRjetattheHLT,having pmiss_T ,μ/

>

120GeV, and at least one jet with p_T

>

110GeV and

|

η

|

<

2

.

4. Toreject eventswith spurious pmiss_T frommismeasured jets, the differencein theazimuthal angle

φ

betweenthe directionofthe highestpTjetand

p

miss

T isrequiredtobegreaterthan0.5radians.

Foreventswithatleasttwojets,themaximumdifferencein

φ

be-tweenanytwojets,

φ

max,isrequiredtobelessthan2.5radians.

In2018, a 40◦ section ofone endofthehadronicendcap calori-meter(HEM)lostpower during thedata-taking period.The2018 dataarethereforeseparatedintotwosamples,2018AandB, cor-respondingtoeventsbeforeandafterthislossofpower,with in-tegratedluminositiesof21and39 fb−1,respectively.Eventsfrom the2018B periodarerejectedifthe

pmissT points to theaffected

region,having

−

1

.

6

< φ (

pTmiss

)

<

−

0

.

6.Thisrequirement, referred

toasthe “HEMveto”, removes31% ofthe eventsin2018B, and leadstoareductioninthesignalacceptanceof16%forthis data-takingperiod,asexpectedfromgeometricalconsiderationsandas veriﬁedin simulation.The selection requirements applied tothis pointdeﬁnethe“basicselection”,withtheresultingsample domi-natedbyW

→ ν

events.

Afterthebasicselection, isolatedtrackswith p_T

>

55GeV and

|

η

|

<

2

.

1 arefurther selected,wherethe isolation requirementis deﬁned such that the scalar sum of the pT of all other tracks

within

R

=

(

η

)

2

+ (φ)

2

<

0

.

3 of thecandidate trackmust belessthan5%ofthe candidatetrack’s p_T.Tracksmustbe sepa-ratedfromjetshaving pT

>

30GeV by

R

(

track

,

jet

)

>

0

.

5.Tracks

are also required to be associated with the primary pp interac-tion vertex (PV), the candidate vertex with the largest value of summedphysics-objectp2_T.Thephysicsobjectsinthissumarethe jets,clusteredwiththetracksassignedtocandidateverticesas in-puts,andthe associatedmissingtransverse momentum,takenas thenegative vector sumof the p_T of those jets. Withrespect to thePV,candidatetracksmusthaveatransverseimpactparameter (

|

d₀

|

)lessthan0

.

02 cm andalongitudinalimpactparameter(

|

d_z

|

) lessthan0

.

50 cm.

Tracksaresaid tohaveamissinghit iftheyare reconstructed aspassing through a functional tracker layer, but no hit in that layer is associated with the track. A missing hit is described as “inner”ifthe missinglayer is betweenthe interaction point and the track’s innermost hit, “middle” if between the track’s inner-mostand outermost hits, and “outer” if it is beyond the track’s outermosthit.Thetrackreconstructionalgorithmgenerallyallows

for some missing hits, to improve eﬃciency for tracks travers-ing theentiretracker.However,forshortertracksthismayresult in spurious reconstructed tracks, arising not fromcharged parti-cletrajectoriesbutfrompatternrecognitionerrors.Thesespurious tracks are one oftwo sources of backgrounds considered in this search.Thisbackgroundisreducedbyrequiringtrackstohaveno missing inner or middle hits, and at leastfour hits in the pixel detector.

The other source of background is isolated, high-p_T charged leptons fromSM decaysofW± orZ bosons,orfromvirtual pho-tons.Thesetrackscanseemtodisappearifthetrackreconstruction fails to ﬁnd all of the associated hits. Missingouter hits in lep-ton tracks mayoccur becauseofhighly energetic bremsstrahlung in the caseof electrons, or nuclear interactions withthe tracker materialinthecaseofhadronicallydecaying

τ

leptons (

τ

_h). Elec-tronsor

τ

h maybe associatedwithlittleenergydeposited inthe

calorimeters becauseof nonfunctional ornoisy calorimeter chan-nels. To mitigate this background,tracks are rejectedif they are within

R

(

track

,

lepton

)

<

0

.

15 ofanyreconstructedlepton candi-date,whetherelectron,muon,or

τ

_h.Thisrequirementisreferred toasthe “reconstructedleptonveto”. Toavoidregions ofthe de-tector known to have lower eﬃciency for lepton reconstruction, ﬁducial criteria are applied to the track selection. In the muon system,trackswithinregionsofincompletedetectorcoverage,i.e., within0

.

15

<

|

η

|

<

0

.

35 and1

.

55

<

|

η

|

<

1

.

85,arerejected.Inthe ECAL,tracksinthetransitionregionbetweenthebarreland end-capsectionsat1

.

42

<

|

η

|

<

1

.

65 arerejected,asaretrackswhose projected entranceinto thecalorimeteris within

R

<

0

.

05 ofa nonfunctional or noisy channel. Because two layers of the pixel tracker were not fully functional in certain data-taking periods, some regionsexhibitedlow eﬃciencyfortherequirementoffour or more pixel hits, and tracks within theseregions are rejected. Theseregionscorrespondtotherange2

.

7

< φ <

π

fortheregion 0

<

η

<

1

.

42 inthe2017dataset,andtotherange0

.

4

< φ <

0

.

8 forthesame

η

regioninthe2018dataset.Applicationofthisﬁnal requirementrejectsapproximately20%ofsimulatedsignaltracks.

Additional regions of lower lepton reconstruction eﬃciency areidentiﬁed using“tag-and-probe”(T&P)studies [43].Candidate Z

→

objectsare selectedin datawheretheinvariant massofa tag lepton anda probetrack iswithin 10GeV of m_Z, the world-averagemassofthe Z boson [44],resultingina sample oftracks havinga highprobability ofbeing alepton withoutexplicitly re-quiringthatthey passtheleptonreconstruction. Theeﬃciencyof the lepton reconstruction is calculated using these probe tracks across the full coverage of the detector, and also for each local

η

-

φ

regionofsize0

.

1

×

0

.

1.Candidatetracksarerejectedfromthe search regioniftheyarewithin an

η

-

φ

region inwhichthelocal eﬃciencyislessthan theoverall meaneﬃciencyby atleasttwo standard deviations. This procedure removes an additional 4% of simulatedsignaltracks.

Finally, two criteria deﬁne the condition by which a track is consideredtohave“disappeared”:(1)thetrackmusthaveatleast threemissingouter hits,and(2)thesumofall associated calori-meterenergywithin

R

<

0

.

5 ofthetrack(E_caloR<0.5)mustbeless than10GeV.Fromthesampleoftrackspassingallofthe require-mentsdescribedabove,threesignalcategoriesaredeﬁned depend-ing on the number oftracker layers that have hits associatedto thetrack,nlay:nlay

=

4,nlay

=

5,andnlay

≥

6.At

η

=

0 these

cat-egoriescorrespond,respectively,totracklengthsofapproximately 20,20–30,and

>

30 cm.ThepreviousCMSsearchfordisappearing tracks [17] requiredatleastsevenhitsassociatedwiththeselected tracks,which resultedin asensitivity comparable tothat ofonly then_lay

≥

6 categoryinthissearch.

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Table 1

SummaryofestimatedvaluesofPveto.Theuncertaintiesshownrepresentonlythestatisticalcomponent.

Data-taking period nlay Pveto

Electrons Muons τh 2017 4 (8.2±5.2)×10−4 (0.0+−30..90)×10− 3 (6.9+−85..31)×10− 2 5 (2.2±0.9)×10−4 (3.2±1.3)×10−2 (6.5₋+22..97)×10− 2 ≥6 (2.7±0.5)×10−5 (1.2±0.5)×10−6 (1.0±0.4)×10−3 2018 A 4 (1.3±0.7)×10−3 (1.0±1.0)×10−1 (7.1−+35..58)×10− 2 5 (0.9+₋10..59)×10− 4 (7.4±4.2)×10−2 (4.4+₋54..54)×10− 2 ≥6 (1.6±0.6)×10−5 (1.9±0.8)×10−6 (0.0₋+07..30)×10− 4 2018 B 4 (0.0+−10..10)×10− 4 (4.0+−154.0.0)×10− 2 (5.6+−65..50)×10− 2 5 (1.4±1.1)×10−4 (5.8±3.8)×10−2 (5.1−+34..57)×10− 2 ≥6 (3.3±0.7)×10−5 (1.5±0.6)×10−6 (2.3±1.0)×10−3 5. Backgroundestimation 5.1. Chargedleptons

Fortracksfromcharged, high-p_T leptons(electrons,muons, or

τ

h)tobeselectedbythesearchcriteria,theleptonreconstruction

mustfail insuch a waythata trackisstill observed butno lep-ton candidateisproduced, resultingin amismeasurement ofthe calorimeterenergyintheevent. Forthisreconstruction failureto occur,thefollowingconditionsmustbepresent:

•

There is a reconstructed lepton track that is isolated from othertracksandhaszeromissinginnerormiddlehits.In ad-dition,theremustbenocandidateleptonidentiﬁedneartoit,

E_caloR<0.5mustbelessthan10GeV,andthetrackmusthaveat leastthreemissingouterhits.

•

Theresultingpmiss_T ,/μmustbelargeenoughtopasstheoﬄine

pmiss_T ,μ/ requirement.

•

Theresulting pmiss_T and p_Tmiss,μ/ mustbe largeenoughtopass totriggerrequirement.

•

Inthe2018Bdata-takingperiod,theresultingpmiss_T mustpass theHEMveto.

The backgroundfromchargedleptons isestimated bycalculating the conditional probability ofeach of thesefour requirements in thegivenorder,asdescribedbelow,treatingeachleptonﬂavor in-dependentlyineachofthethreesignalcategories.

5.1.1. P_veto

Theprobabilityofsatisfyingtheﬁrstcondition, Pveto,isdeﬁned

astheprobabilityforaleptoncandidatetofailtobe identiﬁedas alepton.Thisisestimatedforelectrons(muons)usingaT&Pstudy withZ

→

ee (Z

→μμ

)candidates.Eventsareselectediftheysatisfy asingle-electron(single-muon)triggerandcontaina tagelectron (muon)candidatepassingtightidentiﬁcationandisolationcriteria. A probe trackis required to pass the disappearing trackcriteria, exceptingthereconstructedleptonvetofortheﬂavorunderstudy, the EcaloR<0.5 requirement,andthemissingouterhitsrequirement.

Thetagleptonandtheprobedtrackarerequiredtohave opposite-signelectricchargesandaninvariantmasswithin10GeV ofmZ.

Tostudytheseprobabilitiesfor

τ

h,Z

→ττ

candidateeventsare

selectedinwhichone

τ

decaysvia

τ→

e

νν

or

τ→μνν

,withthe electronormuon serving asthetag lepton.Theother

τ

inthese events is selected asthe probe track and, after applying the re-constructedelectronandmuonvetoestoit,theresultisasample oftracksdominatedby

τ

h.The electronandmuonselectionsare

asdescribedabove,withtwomodiﬁcations forthecaseof

τ

_h.To

reduce contamination from W

→ ν

events, the transverse mass

mT

=

2p Tp

miss

T

(

1

−

cos

φ)

is required to be less than 40GeV,

where p _T isthemagnitudeofthetaglepton’stransverse momen-tum and

φ

is the difference in

φ

between the

pT of the tag

leptonandthe

pmiss_T .Inaddition,because

τ

leptonsfromtheZ de-cayarenotfullyreconstructed,theinvariantmassofthetag-probe pairisrequiredtobeintherangem_Z

−

50

<

M

<

m_Z

−

15GeV.

For each T&P study of Pveto (electrons, muons, and

τ

h), the

number of selected T&P pairs before andafter applying the rel-evantﬂavorofthereconstructedleptonveto,the EcaloR<0.5

require-ment,andthemissingouterhitsrequirementarelabeledN_T&Pand

NvetoT&P,respectively.Tosubtractnon-Z bosoncontributionsfromthe

opposite-sign T&Psamples,theselectionsabove arerepeatedbut requiring instead that the tag lepton and probe track have the same electriccharge, yielding the quantities N_{SS T&P} and Nveto_{SS T&P}. The probability thata leptoncandidateisnot explicitlyidentiﬁed asaleptonisthengivenby:

Pveto

=

Nveto

T&P

−

NvetoSS T&P NT&P

−

NSS T&P

.

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Theresultsobtainedfor P_veto aresummarizedinTable1.

5.1.2. P_off

The probability of satisfyingthe second condition, Poff, is

de-ﬁnedastheconditionalprobabilityofasingle-leptoneventtopass theoﬄinerequirementsofpmiss_T ,/μ

>

120GeV and

|φ(

leading jet

,

pmiss_T ,μ/

)

|

>

0

.

5, given that the lepton candidate is not explicitly identiﬁed asa lepton.Thelatterofthesecriteriarequiresthe ex-istenceofa jethaving pT

>

110GeV and

|

η

|

<

2

.

4,asisrequired

in thebasicselection. The

p_Tmiss,μ/ ofeventswithan unidentiﬁed leptonismodeledbyassumingtheleptoncontributesno calorime-ter energyto theevent, replacing pmiss_T ,μ/ withthe magnitudeof

pmiss_T ,μ/

+

p_T .Thismodificationisappliedinsingle-leptoncontrol samplesforeachflavor,definedascontaining dataeventspassing single-leptontriggersandhavingatleastonetagleptonofthe ap-propriateflavor.Inthecaseofmuons,nomodificationof

pmiss_T ,μ/ is madeastheyarealreadyexcluded fromitscalculation.The quan-tity Poffisestimatedforeachleptonﬂavorbycountingthefraction

ofsingle-leptoncontrolsampleeventswithpmiss_T ,μ/

>

120GeV and

|φ(

leading jet

pmiss_T ,μ/

)

|

>

0

.

5,aftermodifying

pmiss_T ,μ/ inthisway. For electrons and muons, P_off is approximately 0.7–0.8, and ap-proximately0.2for

τ

_h.

5.1.3. Ptrig

Theprobabilityofsatisfyingthethirdcondition,P_trig,isdeﬁned as the conditional probability that a single-lepton event passes

(5)

the trigger requirement, given that the lepton candidate is not identiﬁed as a lepton and the event passes the oﬄine require-mentsofpmiss_T ,μ/

>

120GeV and

|φ(

leading jetp

miss_T ,μ/

)

|

>

0

.

5.In the single-lepton control samples used to measure Poff, the

ef-ﬁciencyof the trigger requirement is calculatedas a function of

pmiss_T ,μ/.Thetriggereﬃciencyisthenmultipliedbin-by-binbythe magnitudeof

pmiss_T ,μ/

+

pT

,describedabove for Poff.Thefraction

ofeventsin thisproduct that survivethe requirementof pmiss_T ,μ/

(modiﬁed)

>

120GeV is then the estimate of P_trig. The value of

P_trigisapproximately0.3–0.6forallleptonﬂavors.

5.1.4. PHEM

Theprobabilityofsatisfyingthefourthcondition, P_HEM,is de-finedastheconditionalprobabilitythatasingle-leptonevent sur-vivestheHEMveto,giventhattheleptoncandidateisnot explic-itlyidentifiedasaleptonandtheeventpassesboththeofflineand triggerrequirements. Thisprobability iscalculated in the sample ofeventsformingthenumeratorof Ptrig.BecausetheHEMvetois

appliedonlyinthe2018Bdataset, PHEM isﬁxedtounityinthe

otherdata-takingperiods.Thevalueof P_HEM isapproximately0.8 forallleptonﬂavors.

5.1.5. Chargedleptonbackgroundestimation

The product of these four conditional probabilities gives the overallprobabilityforan eventwithachargedleptontopassthe search selection criteria. These probabilities are measured sepa-rately foreach flavor andwithin each signal category ofn_lay.To normalizetheseprobabilitiestoformthebackgroundestimate,the numberof events witha chargedlepton of each flavor (N _ctrl) is countedbyselectingeventspassingsingle-leptontriggersand con-taining a lepton of the appropriate flavor with pT

>

55GeV. No

requirementon the presence of pmiss_T ,μ/ or the reconstruction of jetsis madein counting N_ctrl , as P_off accountsfor the probabil-ity to pass those criteria. The value of Nctrl is corrected by the

eﬃciencyoftherelevantsingle-leptontrigger,

trigger , inorderto

account foranyineﬃciencies in that trigger. From the T&P sam-ples used to study Pveto,

trigger is measured as the fraction of

probetrackssatisfyingthesingle-leptontriggerrequirementofthe

N ctrl selection. The valuesare observed to be 84% inthe caseof

electrons, 94% in the case of muons, and 90% in the caseof

τ

_h candidates.Theestimatedbackgroundfromchargedleptonsis cal-culatedusingthesecomponentsas

N est

=

N _ctrl

_trigger PvetoPoffPtrigPHEM

.

(2)

Inthecaseofthenlay

=

4 andnlay

=

5 signalcategories,

insuﬃ-cientnumbersofeventsareavailableformuonsintheestimation ofP_HEM,andformuonsand

τ

_hintheestimationofboth P_off and

Ptrig.Therefore,thesequantitiesareestimatedastheaverageover

theinclusivecategorynlay

≥

4.Thedependenceofthesevalueson n_lay for electrons is applied asa systematic uncertainty inthese cases,describedbelowinSection6.1.

5.2.Spurioustracks

Because spurious tracks do not represent the trajectory of an actualchargedparticle,thecombinationoftrackerlayerswith as-sociated hitsis largely random. The requirementof zeromissing innerandmiddlehitsgreatlysuppressestheprobabilityof select-ingaspurioustrack.

Tomeasure the probability that an event contains a spurious track, two control samplescontaining Z

→

ee and Z

→μμ

decays,

respectively, areselected asrepresentative samplesofSM events. The signal benchmark chosen does not contain Z bosons,so any candidate disappearing tracks observed in these control samples can reliably be labeled asa spurious track.Since spurious tracks generallydonotpointtothePV,thepurityofthespurious tracks samplescanbeenhancedbyreplacingthenominalrequirementof

|

d0

|

<

0

.

02 cm witha“sideband”selection,deﬁnedas0

.

05

≤ |

d0

|

<

0

.

50 cm.

To normalizethe sideband selection to the search region, the shape ofthed₀ distributionisdescribed witha ﬁtto aGaussian function with an added constant, foreach control sample in the

nlay

=

4 category. The ﬁt is madein the slightlyrestricted range

0

.

1

≤ |

d₀

|

<

0

.

5 cm to remove anyoverlapwiththesignal region. A transfer factor

ζ

isthen calculated asthe ratio ofthe integral of the ﬁt function in the signal region to that in the sideband. The value of

ζ

derived from the nlay

=

4 category is applied to

the n_lay

=

5 and n_lay

≥

6 categories because the eventcounts in these categories are not suﬃcient to observe a differentd0

dis-tribution. Finally, the spurious track background is estimated as the rawprobability fora controlsample eventto contain a side-banddisappearing trackcandidate( Praw_spurious),multipliedby

ζ

and normalized to the number of events passing the basic selection (Nctrlbasic):

N_spuriousest

=

Nbasic_ctrl

ζ

Praw_spurious

.

(3)

Thiscalculationisperformedseparatelyforeachsignalcategoryof

n_layforbothZ

→

ee andZ

→μμ

controlsamples,usingtheZ

→μμ

estimateasthecentralvalueofthespurioustrackbackground es-timate.

6. Systematicuncertainties

6.1. Systematicuncertaintiesinthebackgroundestimates

Theleptonbackgroundestimatesmaketheassumptionthatno visibleenergyisdepositedinthecalorimetersbyleptonsthatare not explicitly identiﬁed. This is tested for electrons and

τ

_h by allowing selected candidates to deposit 10GeV in the calorime-ters,themaximalvalueallowed bytherequirementofEcaloR<0.5

<

10GeV for candidate signal tracks. The modiﬁed pmiss_T ,μ/ is con-structedasbefore,butnowthecalculationincludes10GeV inthe directionof thelepton momentum.This isapplied separately for eachnlay categoryforelectrons,andintheinclusivenlay

≥

4

cate-goryfor

τ

hbecauseofsmallsamplesizes.Thisresultsina13–15%

decreasein theelectronbackgroundestimate andan 11–25% de-creaseinthe

τ

_hbackgroundestimate.Thesechangesare takenas systematicuncertainties.

InthecalculationofPoff, Ptrig,and PHEM,theavailabledatain

then_lay

=

4 andn_lay

=

5 categoriesdo notseparately provide ro-bust measurements for the muon and

τ

_h background estimates. Thereforewemeasurethevaluesintheinclusivecategorynlay

≥

4

instead.Theeffectofthisaveragingisestimatedbycomparing val-ues obtained for these quantities in exclusive and inclusive nlay

categories for the single-electron control sample, where there is adequate data to measure each. The differences in these values rangebetween1 and11%. Thesevaluesare applied asone-sided systematicuncertainties intheestimateofthebackground contri-butionfrommuonand

τ

_h candidatesforthenlay

=

4 andnlay

=

5

categories.

The spurious track background estimate relies on several as-sumptions.Theﬁrstassumptionisthatthespurioustrack probabil-ityisindependentoftheunderlyingphysicscontentoftheevent. ThisistestedbycomparingtheestimatesobtainedfromtheZ

→

ee andZ

→μμ

controlsamples.The differencesintheestimates de-rived fromthesetwocontrol samplesrangefrom0 to 200%,and

(6)

Table 2

Summaryofthesystematicuncertaintiesineachbackgroundestimate.Eachvaluelisted rep-resentsthe average acrossall data-takingperiods.Some uncertainties aresingle-sided,as indicated,andthosegivenasadasharenegligible.

Background Source Uncertainty

nlay=4 nlay=5 nlay≥6

Spurious tracks Control sample ±19% ±29% ±116%

ζ ±47% ±47% ±47%

Electrons Visible calorimeter energy ±14% ±14% ±13%

Muons Poff +7% +7% —

Ptrig +8% +2% —

τh Visible calorimeter energy ±19% ±19% ±19%

Poff +7% +7% —

Ptrig +8% +2% —

Table 3

Summaryofthesystematicuncertaintiesinthesignaleﬃciencies.Eachvaluelisted istheaverageacrossalldata-takingperiods,allcharginomassesandlifetimes con-sidered,andwinoandhiggsinocases.Thevaluesgivenasadasharenegligible.

Source Uncertainty

nlay=4 nlay=5 nlay≥6

Pileup 3.0% 3.3% 2.8%

ISR 13% 13% 13%

Trigger eﬃciency 1.1% 0.8% 0.4%

Jet energy scale 0.6% 0.7% 1.6%

Jet energy resolution 0.5% 0.5% 1.3%

pmissT 0.3% 0.3% 0.4%

EcaloR<0.5 0.7% 0.7% 0.7%

Missing inner hits 2.3% 1.0% 0.3%

Missing middle hits 3.9% 5.1% 4.4%

Missing outer hits — — 0.2%

Reconstructed lepton veto eﬃciency 0.1% 0.1% —

Track reconstruction eﬃciency 2.3% 2.3% 2.3%

Total 14% 15% 14%

are takenas systematicuncertainties in thespurious track back-ground estimate. In every case, the statistical uncertainty in the differenceisconsiderablylargerthanthedifferenceitself.

Thesecond assumption ofthespurious trackbackground esti-mateisthattheprojection ofthed₀ sidebandcorrectlydescribes thesignal d₀ region.This assumptionis testedby comparingthe number of signal-like tracks

(

|

d₀

|

<

0

.

02 cm

)

in the Z

→

ee and Z

→μμ

control samples to the number projected from the side-band. Within the statistical and ﬁt uncertainties, the projected numberoftracksagreeswellwiththeobservedsignal-likecounts, sonosystematicuncertaintyisapplied.

The third assumption of the spurious track background esti-mateisthatitisindependentofthedeﬁnitionofthed0 sideband.

The validity of thisassumption is examined by deﬁning nine al-ternative,disjointsidebandsofwidth0

.

05 cm insteadofthesingle sidebandregion ofwidth 0

.

50 cm.The spurious trackestimate is determined for each of these. The observed deviations of these estimatesarewellwithinstatisticalﬂuctuationsofthenominal es-timate.Therefore,nosystematicuncertaintyisintroducedtocover thesedifferences.

The uncertaintyin

ζ

dueto the ﬁt procedureis evaluated by varying the ﬁtparameters within

±

1 standard deviationof their statisticaluncertainties, and comparingthe resulting valuesof

ζ

. A variation of

±(

43–52

)

% from the nominal value is found, and thisvariationistakenasanestimateofthecontributionfromthis sourceto theoverall systematicuncertainty inthespurious track background.

The systematic uncertainties in the background estimates are summarizedinTable2.

6.2. Systematicuncertaintiesinsignalselectioneﬃciencies

Theoretical uncertainties inthecharginoproductioncross sec-tion arise from the choice of factorization and renormalization scalesandfromuncertaintiesinthePDFsused.Theseeffectsresult in an assigneduncertaintyin theexpectedsignal yields of 2–9%, depending onthe chargino mass.A 2.3(2.5)% uncertaintyin the total integrated luminosity ofthe 2017 [22] (2018 [23])data set isassigned.Uncertaintiesinthesignalyieldsduetocorrectionsor scalefactorsareevaluatedbyvaryingeachcorrectionby

±

1 stan-darddeviationoftheirmeasureduncertainties,andcomparingthe resultingsignalyieldstotheirnominalvalue.Thecorrections con-sideredincludethecorrectionsrelatedtothestatisticaluncertainty intheISRcorrections(12–15%)andthemodelingofpileup(2–5%), jet energy scaleandresolution (0.1–1.6%), and pmiss_T ,μ/ (0.1–2.3%), withthevaluesvaryingdependingonthecharginomassand life-time.Uncertaintiesareestimatedintheselectioncriteriaof miss-ing inner,middle,andouterhits(0.1–4.6,2.5–5.2, and

<

0

.

3%, re-spectively) bycomparingtheeﬃciencyofeach betweendataand simulationina controlsample ofsingle-muonevents.The uncer-tainty in the eﬃciency of the EcaloR<0.5 requirement is taken to

bethedifferencebetweentheeﬃcienciesobtainedfromdataand from simulation in the Z

→μμ

control sample (0.4–1.0%), where thetracksare expectedtobepredominantlyspurious.The uncer-taintyinthetrackreconstructioneﬃciencyisevaluatedtobe2.1% in2017data [45] and2.5%in2018data [46].

The eﬃciency of the reconstructed lepton veto in simulated events depends on the modeling of detector noise, which may producecalorimeterormuon detectorhitsthat resultina lepton

(7)

Table 4

Summaryoftheestimatedbackgroundsandtheobservation.Theﬁrstandseconduncertaintiesshownarethe statisticalandsystematiccontributions,respectively.

Data-taking period nlay Expected backgrounds Observation

Leptons Spurious tracks Total

2017 4 1.4±0.9±0.2 10.9±0.7±4.7 12.2±1.1±4.7 17 5 1.1±0.4±0.1 1.0±0.2±0.6 2.1±0.4±0.6 4 ≥6 6.7±1.1±0.7 0.04±0.04−+00..0804 6.7±1.1±0.7 6 2018 A 4 1.1+−10..06±0.1 6.2±0.5±3.5 7.3+ 1.1 −0.8±3.5 5 5 0.2+₋00..62±0.0 0.5±0.1±0.3 0.6+ 0.6 −0.2±0.3 0 ≥6 1.8+₋00..56±0.2 0.04±0.04+ 0.06 −0.04 1.8+ 0.6 −0.5±0.2 2 2018 B 4 0.0+−00..80±0.0 10.3±0.6±5.4 10.3+ 1.0 −0.6±5.4 11 5 0.4+₋00..73±0.1 0.6±0.2±0.3 1.0+ 0.7 −0.3±0.3 2 ≥6 5.7₋+11..21±0.6 0.00+ 0.04 −0.00±0.00 5.7+ 1.2 −1.1±0.6 1

Fig. 1. Theexpectedandobserved95%CL upperlimitsontheproductofcrosssectionandbranchingfractionfordirectproductionofcharginosasafunctionofchargino massforcharginolifetimesof0.33,3.34,33.4,and333 ns,forapurelywinoLSPwiththebranchingfractionforχ±1→χ

0

1π±setto100%.ShownarethefullRun 2results,

derivedfromtheresultsofthesearchinthe2017and2018datasetscombinedwiththoseofRef. [17],obtainedinthe2015and2016datasets.Thecrosssectionincludes bothχ±1χ

0

1andχ±1χ∓1 productioninroughlya2:1ratioforallcharginomassesconsidered.Theredlineindicatesthetheoreticalprediction,describedinSection3,with

scaleandPDFuncertaintiesdisplayedinthesurroundingband.

candidateand thereby reject the track.The differences in recon-structedlepton vetoeﬃcienciesbetweendata andsimulation are studiedbyestimatingtheeﬃcienciesrelativetotighterlepton cri-teria,forwhichdetailedscale factorsare available,inthe sample

ofeventsusedtomeasure Pveto fortheelectronandmuon

back-grounds.Differencesbetweenestimatesfromdataandsimulation of up to 0.1% are observed, andthese are taken into account as systematicuncertainties.

(8)

Statisticaluncertaintiesintriggereﬃcienciesfordataand sim-ulation are estimated to be 0.4% for each nlay category, and are

applied as systematic uncertainties. In the case of short tracks (nlay

=

4 andnlay

=

5),nosourceindataisavailableoutsideofthe

searchregiontomeasuretheefficiencyofthetracklegofthe trig-gerrequirement,whichrequiresatleastfivetrackerhitsassociated withthetrackatHLT.Tostudy thisrequirement’seffect,the trig-gerefficiencyismeasuredforsignaleventsineachsearchcategory asafunctionof p_Tmiss,μ/,andthedifferencesbetweenn_lay

≥

6 and

nlay

=

4 (5)eﬃcienciesareusedtodeﬁneweightsforthenlay

=

4

(5)category.Theseweights are notappliedto thenominalsignal yield, but are used to evaluate a conservative systematic uncer-tainty. The weighted signal yields are compared to the nominal, unweightedvalues,resultinginan averagesystematicuncertainty of1.0%(0.3%)forthenlay

=

4 (5)category.

Thesystematicuncertainties inthesignaleﬃciencies are sum-marizedinTable3.

7. Results

The expectednumberof backgroundevents andtheobserved number of events are shown in Table 4 for each event cate-gory and each data-taking period. The observations are consis-tent with theexpected total background.Upper limits are set at 95%conﬁdencelevel(CL)onthe productofthe crosssection and branching fraction foreach signal model.These limits are calcu-lated with an asymptotic CLs criterion [47–49] that uses a test

statistic based on a profile likelihood ratio and treats nuisance parameters in a frequentist context. Nuisance parameters forthe theoretical uncertainties in the signal cross sections, integrated luminosity, and signal selection efficiencies are constrained with log-normal distributions. Theuncertainties in thebackground es-timates are estimated separately for spurious tracks and for re-construction failures of each flavor of charged leptons, and are treatedasindependent nuisanceparameters.Uncertainties result-ingfromlimitedcontrolsamplesizesareconstrainedwithgamma distributions,whereas thoseassociatedwithmultiplicative factors or discussed in Section 6.1 are constrained with log-normal dis-tributions. The three nlay categories are treated as independent

counting experiments,as are the data-taking periods 2017, 2018 A,and2018 B.

In the case of electroweak production with a wino LSP, the resultsofthissearch arecombinedwiththeprevious search pre-sentedbyCMS,basedondatacollectedin2015and2016 [17].All data-takingperiodsaretreatedascompletelyuncorrelatedandare considered asindependent counting experiments. Systematic un-certaintiesaremeasuredindependentlyforeachperiodandtreated as uncorrelated nuisance parameters, with the exception of un-certainties inthe signal crosssection, which are treatedas100% correlated.

Theexpectedandobservedupperlimitsontheproductofcross sectionsofelectroweakproductionandbranchingfractionsinthe wino LSP case are shown in Fig. 1 for four chargino lifetimes. Two-dimensional constraintsderived fromthe intersectionofthe theoreticalpredictionswiththeexpectedandobservedupper lim-its,for eachchargino massandmean properlifetimeconsidered, areshowninFig.2forapurelywinoLSPandinFig.3forapurely higgsinoLSP.

Charginos in the wino LSP case with a lifetime of 3 (0.2) ns areexcluded up toa massof 884 (474) GeV at95% CL, themost stringentconstraints to date. In the higgsinoLSP case, charginos witha lifetime of3 (0.05) ns are excluded up to a mass of 750 (175) GeV at95% CL. Thisresultisthe ﬁrstto constrainchargino masseswithahiggsinoLSP obtainedwiththedisappearing track signature.

Fig. 2. Theexpectedandobservedconstraintsoncharginolifetimeandmassfora purelywinoLSPinthecontextofAMSB,wherethecharginolifetimeisexplicitly varied.Thecharginobranchingfractionissetto100%forχ±1→χ

0

1π±.Shownare

thefullRun 2results,derivedfromtheresultsofthesearchinthe2017and2018 datasetscombinedwiththoseofRef. [17],obtainedinthe2015and2016data sets.Theregiontotheleftofthecurveisexcludedat95%CL.Thepredictionfor thecharginolifetimefromRef. [28] isindicatedasthedashedline.

Fig. 3. Theexpectedand observedconstraintsoncharginolifetimeandmass for apurelyhiggsinoLSPinthecontextofAMSB,wherethecharginolifetimeis ex-plicitly varied.FollowingRef. [29],thebranchingfractionsaretakentobe95.5% forχ±1→χ 0 1,2π±,3% forχ±1→χ 0 1,2eν,and1.5% forχ±1→χ 0 1,2μνintherange

ofcharginomassesofinterest,withequalbranchingfractionsandproductioncross sectionsbetweenχ01andχ

0

2.Theregiontotheleftofthecurveisexcludedat95%

CL.ThepredictionforthecharginolifetimefromRef. [50] isindicatedasthedashed line.

8. Summary

A search has been presented for long-lived charged particles that decaywithin the CMSdetectorandproduce a“disappearing track”signature.Inthesampleofproton-protoncollisionsrecorded byCMSin2017and2018,correspondingtoanintegrated luminos-ity of101 fb−1,48 events are observed, whichis consistentwith

(9)

theexpectedbackgroundof47

.

8₋+2₂._.7₃(stat)

±

8

.

1(syst) events.These resultsare applicableto anybeyond-the-standard-model scenario capableofproducingthissignature and, incombinationwiththe previous CMSsearch [17], are theﬁrst such results on the com-pleteRun 2dataset,correspondingtoatotalintegratedluminosity of140 fb−1.

Twointerpretations of these results are provided in the con-textofanomaly-mediated supersymmetrybreaking.Inthecaseof apurelyhiggsinoneutralino,charginos areexcludeduptoamass of 750 (175) GeV for a mean proper lifetime of 3 (0.05) ns, us-ing the 2017 and 2018 data sets. In the case of a purely wino neutralino,charginosareexcluded uptoa massof884 (474) GeV fora mean proper lifetime of 3(0.2) ns. Theseresults make use oftheupgradedCMSpixeldetectortogreatly improvesensitivity toshorterparticlelifetimes.Forcharginolifetimesabove approxi-mately0.1 ns, thissearch placesthemoststringentconstraintson directcharginoproductionwithapurelywinoneutralinoobtained withthedisappearingtracksignature. Fora purelyhiggsino neu-tralino,theseconstraintsaretheﬁrstobtainedwiththissignature.

Declarationofcompetinginterest

Theauthorsdeclarethattheyhavenoknowncompeting ﬁnan-cialinterestsorpersonalrelationshipsthatcouldhaveappearedto inﬂuencetheworkreportedinthispaper.

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: BMBWFandFWF(Austria);FNRS andFWO (Belgium); CNPq, CAPES, FAPERJ,FAPERGS, andFAPESP (Brazil); MES (Bulgaria); CERN; CAS, MOST, and NSFC (China); COLCIENCIAS (Colombia); MSES and 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, andNRC KI (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 (Ukraine); STFC (United Kingdom); DOE andNSF (USA).

Individuals have received support from the Marie-Curie pro-gramandtheEuropeanResearchCouncilandHorizon2020Grant, contractNos.675440,752730,and765710(EuropeanUnion);the LeventisFoundation;theAlfredP.SloanFoundation;theAlexander vonHumboldt Foundation;theBelgianFederal SciencePolicy Of-ﬁce;theFondspourlaFormationàlaRecherchedansl’Industrieet dansl’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the F.R.S.-FNRS andFWO(Belgium)underthe“ExcellenceofScience–EOS”–be.h projectn. 30820817; the BeijingMunicipal Science & Technology Commission, No. Z191100007219010; The Ministry of Education,

Youth and Sports (MEYS) of the Czech Republic; the Deutsche Forschungsgemeinschaft (DFG)under Germany’s Excellence Strat-egy – EXC 2121“Quantum Universe” – 390833306; theLendület (“Momentum”)ProgramandtheJánosBolyaiResearchScholarship of the Hungarian Academy of Sciences, the New National Excel-lence ProgramÚNKP, theNKFIA research grants 123842, 123959, 124845,124850,125105,128713,128786,and129058(Hungary); the Council of Science and Industrial Research, India; the HOM-ING PLUS program of the Foundation for Polish Science, cofi-nanced from European Union, Regional Development Fund, the MobilityPlus programof theMinistry ofScience andHigher Ed-ucation,theNationalScienceCentre (Poland),contractsHarmonia 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. 14.W03.31.0026 (Russia); the Tomsk Polytechnic University Com-petitiveness Enhancement Program and “Nauka” Project FSWW-2020-0008(Russia);theProgramaEstataldeFomentodela Inves-tigaciónCientíficayTécnicadeExcelenciaMaríade Maeztu,grant MDM-2015-0509 and the Programa SeveroOchoa del Principado deAsturias;theThalisandAristeiaprogramscofinancedbyEU-ESF andtheGreek NSRF;theRachadapisekSompotFund for Postdoc-toralFellowship,Chulalongkorn Universityandthe Chulalongkorn AcademicintoIts2ndCenturyProjectAdvancementProject (Thai-land);TheKavliFoundation;theNvidiaCorporation;the SuperMi-cro Corporation;TheWelchFoundation,contract C-1845;andthe WestonHavensFoundation(USA).

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TheCMSCollaboration

A.M. Sirunyan

†

,

A. Tumasyan

YerevanPhysicsInstitute,Yerevan,Armenia

W. Adam,

F. Ambrogi,

T. Bergauer,

M. Dragicevic,

J. Erö,

A. Escalante Del Valle,

R. Frühwirth

1

,

M. Jeitler

1

,

N. Krammer,

L. Lechner,

D. Liko,

T. Madlener,

I. Mikulec,

N. Rad,

J. Schieck

1

,

R. Schöfbeck,

M. Spanring,

S. Templ,

W. Waltenberger,

C.-E. Wulz

1

,

M. Zarucki

InstitutfürHochenergiephysik,Wien,Austria

V. Chekhovsky,

A. Litomin,

V. Makarenko,

J. Suarez Gonzalez

(11)

M.R. Darwish,

E.A. De Wolf,

D. Di Croce,

X. Janssen,

T. Kello

2

,

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,

S. Tavernier,

W. Van Doninck,

P. Van Mulders

VrijeUniversiteitBrussel,Brussel,Belgium

D. Beghin,

B. Bilin,

B. Clerbaux,

G. De Lentdecker,

H. Delannoy,

B. Dorney,

L. Favart,

A. Grebenyuk,

A.K. Kalsi,

I. Makarenko,

L. Moureaux,

L. Pétré,

A. Popov,

N. Postiau,

E. Starling,

L. Thomas,

C. Vander Velde,

P. Vanlaer,

D. Vannerom,

L. Wezenbeek

UniversitéLibredeBruxelles,Bruxelles,Belgium

T. Cornelis,

D. Dobur,

I. Khvastunov

3

,

M. Niedziela,

C. Roskas,

K. Skovpen,

M. Tytgat,

W. Verbeke,

B. Vermassen,

M. Vit

GhentUniversity,Ghent,Belgium

G. Bruno,

C. Caputo,

P. David,

C. Delaere,

M. Delcourt,

I.S. Donertas,

A. Giammanco,

V. Lemaitre,

J. Prisciandaro,

A. Saggio,

A. Taliercio,

P. Vischia,

S. Wuyckens,

J. Zobec

UniversitéCatholiquedeLouvain,Louvain-la-Neuve,Belgium

G.A. Alves,

G. Correia Silva,

C. Hensel,

A. Moraes

CentroBrasileirodePesquisasFisicas,RiodeJaneiro,Brazil

W.L. Aldá Júnior,

E. Belchior Batista Das Chagas,

W. Carvalho,

J. Chinellato

4

,

E. Coelho,

E.M. Da Costa,

G.G. Da Silveira

5

,

D. De Jesus Damiao,

S. Fonseca De Souza,

H. Malbouisson,

J. Martins

6

,

D. Matos Figueiredo,

M. Medina Jaime

7

,

M. Melo De Almeida,

C. Mora Herrera,

L. Mundim,

H. Nogima,

P. Rebello Teles,

L.J. Sanchez Rosas,

A. Santoro,

S.M. Silva Do Amaral,

A. Sznajder,

M. Thiel,

E.J. Tonelli Manganote

4

,

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

a

,

P.G. Mercadante

b

,

S.F. Novaes

a

,

S.S. Padula

a

UniversidadeEstadualPaulista,SãoPaulo,Brazil b

UniversidadeFederaldoABC,SãoPaulo,Brazil

A. Aleksandrov,

G. Antchev,

I. Atanasov,

R. Hadjiiska,

P. Iaydjiev,

M. Misheva,

M. Rodozov,

M. Shopova,

G. Sultanov

InstituteforNuclearResearchandNuclearEnergy,BulgarianAcademyofSciences,Soﬁa,Bulgaria

M. Bonchev,

A. Dimitrov,

T. Ivanov,

L. Litov,

B. Pavlov,

P. Petkov,

A. Petrov

UniversityofSoﬁa,Soﬁa,Bulgaria

W. Fang

2

,

X. Gao

2

,

Q. Guo,

H. Wang,

L. Yuan

BeihangUniversity,Beijing,China

M. Ahmad,

Z. Hu,

Y. Wang

DepartmentofPhysics,TsinghuaUniversity,Beijing,China

E. Chapon,

G.M. Chen

8

,

H.S. Chen

8

,

M. Chen,

C.H. Jiang,

D. Leggat,

H. Liao,

Z. Liu,

A. Spiezia,

J. Tao,

J. Wang,

E. Yazgan,

H. Zhang,

S. Zhang

8

,

J. Zhao

(12)

InstituteofHighEnergyPhysics,Beijing,China

A. Agapitos,

Y. Ban,

C. Chen,

G. Chen,

A. Levin,

J. Li,

L. Li,

Q. Li,

Y. Mao,

S.J. Qian,

D. Wang,

Q. Wang

StateKeyLaboratoryofNuclearPhysicsandTechnology,PekingUniversity,Beijing,China

Z. You

SunYat-SenUniversity,Guangzhou,China

M. Xiao

ZhejiangUniversity,Hangzhou,China

C. Avila,

A. Cabrera,

C. Florez,

C.F. González Hernández,

A. Sarkar,

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,

D. Majumder,

B. Mesic,

M. Roguljic,

A. Starodumov

9

,

T. Susa

InstituteRudjerBoskovic,Zagreb,Croatia

M.W. Ather,

A. Attikis,

E. Erodotou,

A. Ioannou,

G. Kole,

M. Kolosova,

S. Konstantinou,

G. Mavromanolakis,

J. Mousa,

C. Nicolaou,

F. Ptochos,

P.A. Razis,

H. Rykaczewski,

H. Saka,

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

E. Salama

11

,

12

AcademyofScientiﬁcResearchandTechnologyoftheArabRepublicofEgypt,EgyptianNetworkofHighEnergyPhysics,Cairo,Egypt