Search for long-lived particles using nonprompt jets and missing transverse momentum with proton-proton collisions at sqrt(s)=13TeV

Contents lists available atScienceDirect

Physics

Letters

B

www.elsevier.com/locate/physletb

Search

for

long-lived

particles

using

nonprompt

jets

and

missing

transverse

momentum

with

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:

Received15June2019

Receivedinrevisedform18August2019 Accepted19August2019

Availableonline21August2019 Editor: M.Doser

Keywords:

Exotica

Long-livedparticles

Asearchforlong-livedparticlesdecayingtodisplaced,nonpromptjetsandmissingtransversemomentum is presented. The data sample correspondsto an integrated luminosity of137 fb−1 of proton-proton collisions atacenter-of-mass energyof 13 TeV collectedbythe CMSexperiment atthe CERN LHCin 2016–2018.Candidatesignaleventscontainingnonpromptjetsareidentifiedusingthetimingcapabilities ofthe CMSelectromagneticcalorimeter. Theresults ofthe searchare consistentwiththebackground prediction andare interpretedusingagauge-mediated supersymmetrybreaking referencemodel with agluinonext-to-lightestsupersymmetricparticle. Inthismodel,gluinomassesupto2100, 2500,and 1900 GeV areexcludedat95%confidencelevelforproperdecaylengthsof0.3,1,and100 m,respectively. Thesearethebestlimitstodateforsuchmassivegluinoswithproperdecaylengthsgreaterthan_∼0.5 m.

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

1. Introduction

A large number of models for physics beyond the standard model predict long-lived particles that may be produced at the CERNLHCanddecayintofinalstatescontainingjetswithmissing transversemomentum, pmiss_T [1].Thesemodelsinclude supersym-metry(SUSY)withgauge-mediatedSUSYbreaking(GMSB) [2],split andstealth SUSY [3–5], andhidden valley models [6]. The pmiss

T

mayarise fromastableneutralweaklyinteractingparticleinthe finalstate orfromaheavy neutrallong-livedparticlethatdecays outsidethedetector.

ThetimingcapabilitiesoftheCMSelectromagneticcalorimeter (ECAL) [7] are used to identifynonprompt or “delayed”jets pro-ducedbythedisplaceddecaysofheavylong-livedparticleswithin theECAL volume orwithin the tracking volume boundedby the ECAL.ThedelayisexpectedtobeafewnsforaTeVscaleparticle that travels

∼

1 m before decaying.A representative GMSBmodel isused asa benchmark to quantifythe sensitivity ofthe search. Inthismodel,pair-producedlong-livedgluinos each decayintoa gluon,whichformsajet,andagravitino,whichescapesthe detec-torcausingsignificant pmiss_T inthe event.Adiagram showingthe benchmarkmodelisshowninFig.1(upperfigure).

Therehave beenmultiplesearches forlong-livedparticles de-cayingto jetsby the ATLAS [8], CMS [9] andLHCb [10] Collabo-rations at

√

s

=

7TeV,

√

s

=

8TeV and

√

s

=

13TeV [11–25]. The

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

useofcalorimetertiminghassofar beenlimitedto searches tar-getingdisplacedphotonsat

√

s

=

8TeV [26,27]. Thepresentstudy representsthefirstapplicationofECALtimingtoasearchfor non-promptjetsfromlong-livedparticledecays.Thistechniqueallows thereduction ofbackgroundcontributionstothefew eventlevel, whileretaininghighefficiencyforsignalsignaturesofoneormore displacedjetsandpmiss

T inthefinal state.AsdetailedinRef. [28],

thisapproach brings significantnewsensitivityto long-lived par-ticlesearches.Adiagramofacharacteristiceventtargetedbythis analysis is shown in Fig. 1 (lower figure). Such an event would escapereconstructioninatracker-basedsearchbecauseofthe dif-ficulty in reconstructing tracks that originate from decay points separated fromthe primary vertexby more than

∼

50 cm in the plane perpendicular to thebeam axis.There are two effectsthat contributetothetimedelayofjetsfromthedecayofheavy long-livedparticles.First,theindirectpath,composedoftheinitial long-lived particle and the subsequent jet trajectories,will be longer, andsecond,thelong-livedparticlewillmovewithalower veloc-ityowingtoitshighmass.Thelatteristhedominanteffectforthe signalmodelsconsideredinthisanalysis.

2. TheCMSdetector

The central feature of the CMSdetector is a superconducting solenoid of 6 m internal diameter, providing a magnetic field of 3.8 T. Within the solenoid volume are a silicon pixel and strip tracker, a lead tungstate crystal ECAL, and a brass and scintilla-tor hadron calorimeter (HCAL), each composed of a barrel and

https://doi.org/10.1016/j.physletb.2019.134876

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

Fig. 1. DiagramshowingtheGMSBsignalmodel(upperfigure),anddiagramofa typicalevent(lowerfigure),expectedtopassthesignalregionselection.Theevent hasdelayedenergydepositionsinthecalorimetersbutnotracksfromaprimary vertex.

two endcap sections.Forward calorimeters extend the pseudora-pidity coverageprovided by thebarrelandendcapdetectors.The silicon tracker measures charged particles within the pseudora-pidity range

|

η

|

<

2

.

5. It consists of 1440 silicon pixel and 15 148siliconstrip detectormodules. Fornonisolatedparticles with 1

<

pT

<

10GeV,inthe region

|

η

|

<

1

.

4,thetrackresolutionsare

typically1.5%inpTand25–90(45–150) μminthetransverse

(lon-gitudinal)impactparameter [29].TheHCALissegmentedinto indi-vidualcalorimetercellsalongpseudorapidity(

η

),azimuth(

φ

),and depth. The barrelmuon systemis composed of drift-tubes (DTs) andresistiveplatechambers(RPCs).Theseprovidehighresolution hitpositioning andtiming todeterminethe muontrajectory. The hitsintheDTsareclusteredintotracksegments,referredtoasDT segments,asdetailedinRef. [30].Intheforwardregion,RPCsare usedalongwithcathodestripchambers(CSCs),whichhavegreater resistanceto thehigher radiationflux occurringalongthe beam-line than DTs. A more detailed description of the CMS detector, together withadefinitionof thecoordinatesystemusedandthe relevantkinematicalvariables,canbefoundinRef. [9].

TheCMSECALconsistsof75848leadtungstatecrystals,which provide coverage in pseudorapidity

|

η

|

<

1

.

48 in a barrel region (EB)and1

.

48

<

|

η

|

<

3

.

00 intwoendcapregions (EE).This anal-ysisreliesonthetiming capabilitiesoftheEB [7].TheECAL mea-surestheenergyofincomingelectromagneticparticlesthroughthe scintillation light produced in the lead tungstate crystals.Silicon avalanche photodiodes (APDs) are used as photodetectors in the barrelregion.Thesearecapableofmeasuringthetimeofincoming particleswitha resolutionaslowas

∼

200 ps for energydeposits

above50 GeV [31].EachECALcrystalwithanAPDunitattachedis referredtoasanECALcell.

Intheregion

|

η

|

<

1

.

74,theHCALcellshavewidthsof0.087in

η

and0.087 in

φ

.Inthe

η

–

φ

plane,andfor

|

η

|

<

1

.

48,theHCAL cells map onto 5

×

5 arrays ofECAL crystalsto formcalorimeter towers projectingradiallyoutwardsfromclosetothenominal in-teractionpoint.For

|

η

|

>

1

.

74,thecoverageofthetowersincreases progressivelytoamaximumof0.174in



η

and

φ

.Withineach tower,theenergydepositsinECALandHCALcellsaresummedto define the calorimetertower energies, subsequently usedto pro-videtheenergiesanddirectionsofhadronicjets.

Events ofinterest are selected using a two-tiered trigger sys-tem [32].Thefirstlevel,composedofcustomhardwareprocessors, usesinformationfromthecalorimetersandmuondetectorsto se-lect eventsata rateof around100 kHz within atime interval of less than 4 μs. The second level, known as thehigh-level trigger (HLT),consistsofafarmofprocessorsrunningaversionofthefull event reconstruction software optimized for fast processing, and reducestheeventratetoaround1 kHz beforedatastorage.

3. Objectandeventreconstruction

The primary physics objects used in thisanalysis are jets re-constructed from the energy deposits in the calorimeter towers, clusteredusing the anti-kT algorithm [33,34] with a distance

pa-rameter of 0.4. The contribution from each calorimetertower is assignedthecoordinatesofthetowerandamomentum,the abso-lute value andthe directionofwhich are found fromtheenergy measured in the tower assuming that the contributing particles originated at the center of the detector. The raw jet energy is obtainedfromthesumofthetowerenergies,andtherawjet mo-mentum by the vectorialsum ofthe tower momenta, which are found fromthe energymeasured inthetower. The rawjet ener-giesarethencorrectedtoreflectauniformrelativeresponseofthe calorimeterin

η

anda calibratedabsoluteresponsein transverse momentum pT[35].JetsreconstructedusingtheCMSparticleflow

(PF) algorithm [36] are not used in this analysis because non-promptjetsdonotproducereliableinformationinthetrackerand out-of-time energydepositsare not includedinthePF jet recon-struction.

All reconstructed vertices in the event, consistent with origi-natingfromaproton-proton(pp)interaction,areconsideredtobe primary vertices (PVs) [29]. Eachtrackthat is identifiedas origi-nating fromaPVis associatedwithajet iftheseparation ofthe track from the jet axis



R

=

√

(

η

)

2

+ (φ)

2

<

0

.

4, where



η

and

φ

representthedifference (inradians)betweenthejetaxis andthetrackinthepseudorapidityandintheazimuthaldirection, respectively.

The jet timing is determined using all ECALcells that satisfy



R

<

0

.

4 betweenthe jet axis andcell position,that exceed an energythresholdof0.5 GeV andthatsatisfyreconstruction quality criteria. For each cell within theECAL detector,the timing offset isdefinedsuch thataparticletravelingatthespeedoflightfrom thecenterofthecollisionregiontothecellpositionarrivesattime zero.Energydepositswitharecordedtimethatiseitherlessthan

−

20ns or greaterthan 20 ns arerejected, toremove events orig-inatingfromprecedingorfollowingbunchcollisions, respectively. The time of the jet,tjet, isdefined by themedian cell time. The

jet-based requirements used to reject the dominant background sources, referredtoasthesignal jetrequirements,aredetailedin Section5.

The missingtransversemomentum vector,



pmiss_T ,usedforthis analysis is defined as the projection on the plane perpendicular to thebeamsofthe negativevector sumofcalorimetermomenta

depositsinan eventsatisfyingreconstruction qualitycriteria cho-sentoreduce instrumentalnoise effects,butwithnorejectionof out-of-timeECALcells.

4. Datasetsandsimulatedsamples

The data sample was collected in 2016, 2017, and 2018 by the CMS detector in pp collisions at a center-of-mass en-ergy of 13 TeV, corresponding to an integrated luminosity of 137

±

3

.

3 fb−1 [37–39]. Thetrigger requiredthe eventsto satisfy

pmiss

T (trigger)

>

120GeV. This is computed as the negative

vec-tor



pT sum of all HLT PF candidates, which include out-of-time

deposits [40].

The search is interpreted using the GMSB signal model with samplesproducedwithgluinomassesfrom1000to3000 GeV,and properdecaylengths(c

τ

0) varying from0.3to 100 m.Thegluino

pair production cross sections are determined at approximate-NNLO+NNLL order in

α

s [41–47]. All other SUSY particles, apart

from the gravitino, are assumed to be heavy and decoupled from the interaction. Signal samples are produced with pythia 8.212 [48], and NNPDF3.1LO [49] is used for parton distribution function (PDF) modeling. If a gluino is long-lived, it will have enoughtimetoformahadronicstate,anR-hadron [50–52],which issimulatedwith pythia 8.212.Forunderlyingeventmodelingthe CP2tuneisused [53].

Systematicuncertaintiesinthemodelingofthejet-based vari-ables discussed in Section 5 are derived using a simulated sam-ple of jets produced through the strong interaction, referred to as quantum chromodynamics (QCD) multijet events. This sam-pleis simulated withthe MadGraph5_amc@nlo 2.2.2 [54] event generator atleading-order (LO) accuracy. Thisgenerator is inter-facedwith pythia 8.212forhadronizationandfragmentation. The jetsfromthe matrix elementcalculations are matched toparton showerjetsusingtheMLMalgorithm [54].Theunderlyingeventis modeledusingtheCUETP8M1(CP5)tune [53] forsimulationwith NNPDF3.0NLO(NNPDF3.1NNLO) [49] usedforPDFmodelingforthe 2016(2017and2018)detectoroperatingconditions.

The description of the detector response is implemented us-ingthe Geant4 [55] packageforallsimulatedprocesses.Tomodel the effect of additional pp interactions within the same bunch crossing (in-time pileup) or nearby bunch crossings(out-of-time pileup), minimum bias events generated with pythia are added tothe simulatedeventsample, witha frequencydistribution per bunchcrossingweightedtomatchthatobservedindata.

5. Eventandobjectselection

The selection criteria are optimized taking into account the principalbackgroundsourcesthat producedelayedtimingsignals, whicharedetailedbelow.

•

ECAL time resolution tails: these tails affectthe collisions of in-time(“core”)bunchesandarisefromintercalibration uncer-tainties,crystal-dependentvariationsinscintillationrisetime, loss ofcrystaltransparencybecauseofradiation,and run-by-runshiftsassociatedwiththereadoutelectronics [31].

•

Electronic noise:electronic noise intheECALcan cause indi-vidualcellstorecorddepositsatarbitrarytimes,typicallywith lowenergies,anduncorrelatedwithsurroundingcells.

•

Direct ionization in the APD: the traversalof a charged par-ticle produces a signal that is

∼

11 ns earlier than the signal fromscintillationlight.However,theionizationsignalmay ar-rive later iftheassociated chargedparticle travelsback from theHCAL,orisassociatedwithalaterbunchcrossing.

•

In-time pileup: additional pp collisions in the same bunch crossingcanproduceparticles withaspreadincollisiontime andwithvaryingflightpaths, depending onthepointof ori-gin along thebeamaxis.These effectsresultin timing shifts ofuptoafewhundredps.

•

Out-of-time pileup: additional pp collisions in neighboring bunchcrossingscan resultindepositsthataredelayedby in-tegermultiplesofthebunchspacing(25 ns).

•

Satellite bunches: the LHC radiofrequency (RF) cavities oper-ate at a frequency of 400 MHz, such that RF “buckets” are separated by

∼

2.5 ns. In order to achieve the desiredbunch spacing,onlyoneintenofthesebuckets(separatedby25 ns) isfilled. However, adjacent“satellite” bunchesmayalso con-tainprotonsatalevelcorrespondingto

O(

10−5

)

timesthatof themainbunch.

•

Beamhalo:collisionsbetweenbeamprotonsandanLHC colli-mator [56] canresultinmuonsthatpassthroughthedetector approximately parallel to the beam line. These “beam halo” muonscan depositenergywithin the ECAL,causingan early signalifthebeamhaloisfromthecurrentorpreviousbunch oradelayedsignalifthebeamhalooriginatesfroma follow-ingbunch.

•

Cosmicraymuonhits:cosmicray muonsmaycausedeposits intheECALthatoccuratrandomtimes.

The events considered in this analysis as including candidate long-lived particles are required to satisfy a series of selections that define the signal region(SR). Each requirementischosen to be atleast

∼

90% efficientforjets fromthe decayof aTeV scale long-livedparticlewhileallowingatleastafactor

∼

10rejectionof theidentifiedbackgroundprocess.Inorderto predictbackground contributionstotheSR,someoftheserequirementsareinvertedto enhanceparticularbackgroundprocesses,asdetailedinSection6.

5.1. Jetselection

5.1.1. Baselinejetselection

Alljetsconsideredinthisanalysismustpassbaseline pT and

η

requirements.Arequirementof pT

>

30GeV isimposedtoreduce

contributions from pileup jets. For the SR, further mitigation of pileupjetsisachievedthroughselectionsdetailedinSection5.1.2. The jetsare requiredtosatisfy

|

η

|

<

1

.

48 sothat theyare recon-structed in the EB. The barrel requirement is made because the timing resolution is significantly better in this region compared with the endcap [31], andjets of the targeted signal model are stronglypeakedinthecentral

η

region.

5.1.2. Signaljetselection

The SR requirement on the jet time is tjet

>

3ns. The timing

resolutionimprovesforhigherenergyECALdepositsbefore reach-inga plateau [31].ArequirementontheECALenergycomponent ofthejetofEECAL

>

20GeV isappliedasthisthresholdwasfound

to optimizethetiming resolutionof thejetswhileensuring high signalefficiency.

Jetsfromsignaleventsareexpectedtohavealargenumberof ECALcells(N_ECALcell ) hit,whilejetsdominatedbydirectAPDhitsor ECAL noise oftenhave a low number ofcells hit. A threshold of

Ncell

ECAL

>

25 isappliedtorejectthesebackgroundsources.

Jets from signal events will typically have similar energy de-positionsintheECALandHCAL,whilejetsoriginatingfromnoise orbeamhalotypically haveasmallorzeroHCALenergy compo-nent (EHCAL). Inorderto rejectsuch backgroundsources, jetsare

requiredtohaveahadronicenergyfractionHEF

=

EHCAL

/(

EECAL

+

EHCAL

)

>

0

.

2.AnadditionalrequirementofEHCAL

>

50GeV ismade

to reject background contributions fromnoise and beamhalo as wellastoensureawell-measuredhadroniccomponent.

Signal jetstypically havea smallRMSinthe timeofthe con-stituentcells (tRMS_jet )asallthe componentcells originate fromthe same delayed jet. Jets that are significantly delayed because of contributionsfromuncorrelatednoiseoftencontain cellsthat are widely spread intime. In such cases thetRMS_jet will be correlated with tjet, so a requirement is made on both tRMSjet

<

0

.

4tjet and t_jetRMS

<

2

.

5ns.

Jets that originate from a PV and have a mismeasured time or originate from satellite bunch collisions typically contain sig-nificant total momentum in tracks associated withtheir PV. The PVfraction

track , defined as the ratio of the total pT of all PV tracks

matched to the jet (



R

<

0

.

5) to thetransverse calorimeter en-ergy ofthe jet,is usedto selectpotential signal jets thatdo not originatefromaPV.ArequirementofPVfraction

track

<

0

.

08 isapplied.

Beamhalomuonswill traveldirectly throughthe CSCsbefore leavingenergydepositsintheECAL,sothefractionofECALenergy that can be associated with CSC hitsprovides rejection of back-groundcontributionsfrombeamhalo.Theratioofthetotalenergy ofECALcellsmatched toaCSChit (

φ <

0

.

04)to EECAL,defined

asECSC

ECAL

/

EECAL,isusedtodiscriminatebeamhalobackground

con-tributions.ArequirementofECSC_ECAL

/

EECAL

<

0

.

8 isapplied. 5.2. Eventselection

Theeventsarerequiredtocontainatleastonejetsatisfyingthe requirementsoutlinedinSection5.1.Inaddition,arequirementof

pmiss

T

>

300GeV isappliedtorejectbackgroundcontributionsfrom

multijetproductionfromcoreandsatellitebunchcollisions. The DT and RPC muon systems are used to reduce the back-groundcontribution fromcosmic ray muons. Signal events could alsohavedepositsinthemuonsystemsifthejetscontainmuons, if there is “punch-through”of jet constituents to the muon sys-tem, or if the long-lived particle decays within the muon sys-tem. To mitigate the inefficiency for signal events, only the DT segments and RPC hits with r

>

560cm (where r is the trans-verse radial distance to the interaction point)and RPC hits with

|

z

|

>

600cm (where z is thedistance along the beamline to the interaction point) are considered. In order to reduce the effect of noise, DT segments and RPC hits are required to be within



R

<

0

.

5 ofaDT segmentwitha hit.The maximal

φ

between such“paired”DT segmentsandRPC hitsisdefinedasmax

(φ

DT

)

andmax

(φ

RPC

)

,respectively.Eventssatisfyingmax

(φ

DT

)

>

π

/

2

or max

(φ

RPC

)

>

π

/

2 are rejected to reduce the contribution of

cosmicraymuonevents.

Finally,eventsarerequiredtosatisfyaseriesoffiltersdesigned to reject anomalous high-pmiss_T events, which can be due to a varietyofreconstructionfailures,detectormalfunctionsand back-grounds not arising from pp collisions [40]. All SR requirements aresummarizedinTable1.

6. Backgroundestimation

Thissectiondetails thecharacterizationofthedominant back-ground sources and the methods used to estimate residual con-tributionstotheSR.Thebackgroundcontributionsareinvestigated byinvertingtherequirementsonthediscriminatingvariables sum-marized in Table 1 to define control regions (CRs) enriched in particularbackgroundprocesses.Therearethreemainbackground sources:beamhalomuonsdeposits,whichtypicallyhavelow HEF and large ECSC_ECAL

/

EECAL; out-of-time jets from core and satellite

bunch collisions, which have large PVfraction

track ; andjets originating

fromcosmicraymuons,whichhavehighmax

(φ

DT/RPC

)

andtRMSjet .

Table 1

Summaryofthe requirementsused todefinethesignalregion.

Baseline jet selection

|η| <1.48

pT>30 GeV

Signal jet selection EECAL>20 GeV

Ncell ECAL>25

HEF>0.2 and EHCAL>50 GeV

tRMSjet /tjet<0.4 and tRMSjet <2.5 ns

PVfraction track <0.08

ECSC

ECAL/EECAL<0.8

tjet>3 ns

Event level selection

At least one signal jet

pmiss T >300 GeV

Quality filters max(φDT) <π/2

max(φRPC) <π/2

The backgroundsources are estimatedfromthe CRsusing meth-odsthatrelyondata.Thesepredictionsaretestedusingvalidation regions (VRs) that do not overlap with the SRs to ensure they are unbiased. The agreement of the observation with prediction intheVRsisusedtoestimate systematicuncertaintiesinthe pre-diction in the SR. For jets in the CRs and VRs with

|

tjet|

<

3ns, thetRMS_jet

/

tjet

<

0

.

4 requirement isreplacedwitharequirementof tRMS_jet

<

1

.

2ns.

6.1. Beamhalo

The beam halo contribution is estimated by measuring the pass/failratiooftheECSC_ECAL

/

EECAL

>

0

.

8 requirementforeventswith

HEF

<

0

.

2 andapplyingittotheobservednumberofeventswith HEF

>

0

.

2. The prediction is made without any requirement on

EHCALandcanthereforebeconsideredanupperlimitonthe

con-tributionfromthebeamhalobackgroundcontribution.

The VR forthisprediction isdefinedby selecting eventswith

tjet

<

−

2ns and applyingall signal requirementsexceptthose on ECSC_ECAL

/

EECAL,HEF,andEHCAL.Toenhancethecontributionofbeam

haloeventsrelativetothecontributionsfromsatellitebunchesand cosmicraymuonsintheVR,the

φ

valuesofthejetsarerequired to be within 0.2 radians of 0 or

±

π

. The correlation between

ECSC_ECAL

/

EECAL and HEF inthe VR is consistent withzero, meaning

they canbe usedto makean unbiasedprediction.Theprediction fromthismethodforthenumberofeventspassingsignal thresh-olds on ECSC_ECAL

/

EECAL and HEF in the VR is 0

.

02+₋0₀._.06₀₂ events, in

agreementwiththe0eventsobserved.

The levelofagreementbetweenpredictionandobservationin theVRisusedtoderiveasystematicuncertaintyintheprediction. Theslopeofalinearfittothepass/failratioofthe E_ECALCSC

/

EECAL

>

0

.

8 requirement as a function of HEF is found to be consistent withzero.The uncertaintyis thenpropagated tothe regionwith

ECSC

ECAL

/

EECAL

>

0

.

8 andHEF

>

0

.

2.ThefinalpredictionfortheSRis

0

.

02+₋0_0..₀₂06(stat)+₋0₀._.05₀₁(syst) events.

6.2. Coreandsatellitebunchbackgroundprediction

The core and satellite bunch background contribution is es-timated by measuring the pass/fail ratio of the requirement PVfraction

the observed number of events with tjet

>

3ns and PVfractiontrack

>

0

.

08.TwoVRsare definedtoverifythepredictionofthe satellite bunchandtimingtailbackgroundcontributions.

ThefirstVR isselectedtocontaineventswithtjet

<

−

1ns and

passing all signal requirements except for that on PVfraction_track . The pass/failratioofthePVfraction_track

<

0

.

08 requirementismeasured for eventswith

−

3

<

tjet

<

−

1ns andappliedtothenumberofevents

with tjet

<

−

3ns and PVfractiontrack

>

0

.

08. The upper bound on tjet

ensuresthesample isenriched withjetsinthetailofthetjet

dis-tribution.Thecorrelation betweenthevariables intheVRis con-firmedtobeconsistentwithzero,whichallowsan unbiased pre-dictiontobemade.Thepredictionfromthismethodforthe num-berofeventspassingtjet

<

−

3ns andPVfraction_track

<

0

.

08 is0

.

09+₋00..206

events,tobe comparedwith1observedevent.Theeventpassing selectionhasnopairedRPCorDThitsandisthereforeunlikelyto originatefromacosmicraymuon.Thecompatibilitywith expecta-tioniswithintwostandarddeviations,however,toensurethe pre-dictionisunbiased,afurthervalidationiscarriedout.The require-mentof pmiss_T

>

300GeV is inverted andtheprediction repeated. Theeventsmuststill satisfythe pmiss_T (trigger)

>

120GeV require-ment.Thenumberofeventssatisfyingtjet

<

−

3ns andPVfraction_track

<

0

.

08 ispredicted tobe 1

.

95

±

0

.

29 events, to be compared with 1event observed. As the validationwith pmiss_T

<

300GeV probes asimilar phasespace tothevalidation with pmiss_T

>

300GeV,but witha significantlyincreasednumberofevents,an excessdueto asystematiceffectwouldbeenhanced.Theobservationinthe re-gionwithtjet

<

−

3ns andPVfractiontrack

<

0

.

08,for p

miss

T

>

300GeV,is

thereforeconsideredtobeconsistentwithastatisticalfluctuation. Asecond VR is definedusing eventswith 1

<

tjet

<

3ns.The

pass/fail ratio of the PVfraction_track

<

0

.

08 requirement is measured for events with 1

<

tjet

<

2ns and applied to the number of

events with 2

<

tjet

<

3ns and PVfraction_track

>

0

.

08. The estimation

fromthismethodforthenumberofeventspassing2

<

tjet

<

3ns

andPVfraction_track

<

0

.

08 is0

.

03₋+₀0._.08₀₃ events,inagreementwiththe0 eventsobserved.

Theprediction fortheSR relieson usingthe efficiencyofthe PVfraction_track requirementofeventswith1

<

tjet

<

3ns topredictthe

efficiencyof the PVfraction

track requirement for tjet

>

3ns. Because of

differences in the reconstruction of the calorimeter energy and tracker pT, this efficiency may be expected to have some small

time dependence. In order to measure any such tjet dependence

and derive an associated systematic uncertainty, a data sample withtheofflinepmiss_T requirementinverted(butpassingtrigger re-quirements)andtjet

>

2ns isused.TheregionofPVfraction_track

<

0

.

08 is

notincludedtoavoidcontaminationfromcosmicrayorbeamhalo muondeposits.The slopeofalinearfit tothepass/fail ratioofa looserrequirementofPVfraction_track

<

0

.

5 againsttjet isconsistentwith

zero.Asforthebeamhaloprediction,theuncertaintyfromthefit ispropagated to the region withtjet

>

3ns and PVfractiontrack

>

0

.

08.

The final prediction for the core andsatellite bunch background contributionis0

.

11₋+0_0..09₀₅(stat)+₋0₀._.02₀₂(syst) events.

6.3.Cosmicrayevents

The discriminating variables used for the cosmic back-ground prediction are the tRMS_jet of the jet and the larger of max

(φ

DT

)

and max

(φ

RPC

)

, labeled as max

(φ

DT/RPC

)

. The

pass/fail ratio of the t_jetRMS

<

2

.

5ns requirement is measured for events with max

(φ

DT/RPC

)

>

π

/

2 and applied to events with

max

(φ

DT/RPC

)

<

π

/

2.Cosmicraymuonsthatradiateaphotonvia

bremsstrahlungwhilepassingthroughtheHCALwilltypically de-positsignificantenergyinasingleisolatedcell.TheHCALnoise re-jectionqualityfiltersaredesignedtorejecteventscontainingsuch

Table 2

Summaryoftheestimatednumberofbackgroundevents. Background source Events predicted Beam halo muons 0.02+0.06

−0.02(stat)+ 0.05

−0.01(syst)

Coreandsatellite bunchcollisions

0.11+₋00..0905(stat)+ 0.02

−0.02(syst)

Cosmic ray muons 1.0+₋11..80(stat)+ 1.8

−1.0(syst)

Fig. 2. Thetimingdistributionofthebackgroundsourcespredictedtocontributeto thesignalregion,comparedtothoseforarepresentativesignalmodel.Thetimeis definedbythejetintheeventwiththelargesttjetpassingtherelevantselection.

Thedistributionsforthemajorbackgroundsourcesaretakenfromcontrolregions andnormalizedtothepredictionsdetailedinSection6.Theobserveddataisshown bytheblackpoints.Noeventsareobservedindatafortjet>3ns (indicatedwitha

verticalblackline).

isolated deposits, thus inverting these filters, with all other re-quirementsapplied,providesavalidationregionenrichedinevents withcosmicraymuons.

The correlation between t_jetRMS and max

(φ

DT/RPC

)

in the

val-idation sample is consistent with zero, allowing them to be used to make an unbiased prediction. The estimation in the VR for the number of events passing signal thresholds in t_jetRMS and max

(φ

DT/RPC

)

is1

.

1+₋11..91 events,in agreement withthe 1 event

observed.AsystematicuncertaintyintheSRpredictionisderived fromthe statisticaluncertainty inthe VR.The final prediction in theSRis1

.

0₋+1_1..8₀(stat)+₋1₁._.8₀(syst) events.

6.4. Backgroundsummary

Theestimatedbackgroundyieldsanduncertaintiesare summa-rizedinTable2.Thetotalbackgroundpredictionis1

.

1+₋2₁._.5₁ events.

7. Resultsandinterpretation

Fig.2showsthe timingdistribution foreventswithjets pass-ing alltheSRrequirements.Thedistributions forthe major back-groundsourcesare takenfromcontrolregions andnormalizedto thepredictionsdetailedinSection6.Thesedistributionsareshown forillustrationonlyandarenotusedforthestatistical interpreta-tion.TheoverallbackgroundpredictionfortheSRis1

.

1+₋2₁._.5₁events, whichisconsistentwiththeobservationof0events.

ThemodelusedfortheinterpretationistheGMSBSUSYmodel inwhichgluinosarepairproducedandformR-hadrons.The

long-Fig. 3. Theproduct,Aε,oftheacceptanceandefficiencyinthecτ0vs.mgplanefor

theGMSBmodel,afterallrequirements.

lived gluinos then decay to a gluon and gravitino producing a delayedjetandpmiss_T .

The trigger efficiency for the simulated samples is evaluated from an emulation. The inefficiency due to the pmiss_T trigger re-quirement ranges from

∼

5 to

∼

15% for c

τ

0

=

1 and 10 m,

re-spectively. The trigger emulation is validated withdata using an independentsample collected witha single muon reference trig-ger.

The product of the experimental acceptance and efficiency (

A

ε

),showninFig.3,isevaluated independentlyforeachmodel point, defined in terms of the gluino mass (m_g) and proper

de-caylength.Theefficiencyismaximizedforhighgluinomassesand fora rangein c

τ

0 bounded by the requirements that thegluino

must have sufficient lifetime for its decay products to pass the

tjet

>

3ns requirement andthat thegluino must decaybefore or

withintheECAL.Foragluinomodelwithm_g

=

2400GeV the

effi-ciencyishighest(upto

∼

35%)fortherange 1

<

c

τ

0

<

10m.The

efficiencyislargerforhighermassesbecauseoftheincreasedpmiss_T

intheeventandthereducedvelocityofthegluino.

Interactions of the R-hadrons with the detector lead to sig-natures exploited by searches for heavy stable charged particles and, in order to maintain model independence, are not consid-eredfortheinterpretationofthisanalysis.However,theimpactof suchinteractions was evaluated fortwo benchmarksignal points,

mg

=

1500GeV andc

τ

0

=

1 m,andmg

=

1500GeV andc

τ

0

=

10m,

using the “cloud”model of R-hadron/matter interactions [51,57], which assumes that the R-hadron is surrounded by a cloud of colored,lightconstituentsthatinteractduringscattering.The frac-tionof



g whichhadronizetoaneutral



g-gluonstatewas takento be0.1.Comparedtonon-interactingR-hadrons,therelative reduc-tion inselection efficiencyforboth benchmark signal points was found to be

∼

15% with the largest effect beingon the PVfraction track

andmax

(φ

DT/RPC

)

requirements.

7.1. Signalsystematicuncertainties

Inordertoevaluatesystematicuncertaintiesinthemodelingof thevariablesusedtoselectsignaljets(definedinSection5.1.2),the correspondingdistributionsforeventsfromthemultijetsimulation arecomparedwithdata.Foreachvariable,thethresholdusedfor the selection is varied in the simulation to matchthe efficiency measured in data. The change in acceptance from this variation isshown foreach of thejet-based variables inTable 3, usingan examplemodel point.This variationis takenasa systematic

un-Table 3

Thederiveduncertaintyintheproduct,Aε,oftheacceptanceand efficiency from the modelingof the variables discussed in Sec-tion5.1.2,forarepresentativemodelwithmg=2400GeV.

Variable Derived uncertainty (%)

cτ0=1 m cτ0=10 m PVfraction track 0.01 0.03 Ncell ECAL 3.2 4.2 HEF 2.8 2.5 ECSC ECAL/EECAL 0.9 0.9 tRMS jet 22 15

certaintyinthesignalmodelacceptance.Inaddition,thevariation int_jetRMSispropagatedtotRMS_jet

/

tjet.

Inadditiontotheuncertaintyinthemodelingofthevariables usedtoselectsignaljets,thesystematicuncertaintiesinthesignal

A

ε

aresummarizedbelow.

•

Integratedluminosity: 2.5% [37], 2.3% [38], and2.5% [39] un-correlateduncertaintiesforthe2016,2017,and2018data tak-ingperiods,respectively.

•

Triggerinefficiency:typically5–15%.

•

Limitedsimulatedsamplesize: upto

∼

10%,dependingonSR

A

ε

.

•

Pileupreweighting: 4.6%uncertainty inthe total inelastic pp crosssection [58],whichcorrespondstoanuncertaintyinthe SR

A

ε

of1–5%.

•

Jetenergyresolution/scale:a1–5%percentuncertainty [35].

7.2. Interpretation

Under the signal plus background hypothesis, a modified fre-quentist approach is used to determineobserved upper limitsat 95% confidence level (CL) on the cross section (

σ

) to produce a pair ofgluinos, each decaying with100% branching fraction to a gluon andagravitino,asafunction ofm_g andc

τ

0.The approach

usestheLHC-styleprofilelikelihoodratioasthetest statistic [59] and the CLs criterion [60,61]. The expected and observed upper

limitsareevaluated throughtheuseofpseudodatasets.Potential signal contributions to eventcountsinthe SRandCRsare taken intoconsideration.

Fig. 4 shows the observed upper limit on

σ

as a function of lifetimeandgluinomassfortheGMSBmodel.Gluinomasses be-low2100 GeV areexcludedat95%confidencelevelforc

τ

0between

0.3and30 m.Thedependenceoftheexpectedandobservedupper limitasafunctionofc

τ

0isshowninFig.5formg

=

2400GeV.The

observedlimitiscomparedtotheresultsoftheCMSdisplacedjet search [20],basedonadatasamplewithintegratedluminosityof 36

.

1 fb−1,showingthecomplementarycoverage.Theseresults ex-tendthereachbeyondprevioussearchesformodelswithjetsand significant pmiss_T inthefinalstateforc

τ

0



0

.

5m [17,20,21].

8. Summary

Aninclusivesearchforlong-livedparticleshasbeenpresented, based on a data sample of proton-proton collisions collected at

√

s

=

13TeV by the CMS experiment, corresponding to an inte-grated luminosity of 137 fb−1.The search uses the timing of en-ergydepositsintheelectromagneticcalorimetertoselectdelayed jets from the decays of heavy long-lived particles, with residual background contributions estimated using measurements in con-trolregionsinthedata.Theresultsareinterpretedusingthegluino gauge-mediated supersymmetrybreakingsignal modelandgluino

Fig. 4. Theobservedupperlimitsat95%CL forthegluinopair productioncross sectionintheGMSBmodel,shownintheplaneofmgandcτ0.Abranchingfraction

of100%forthegluinodecaytoagluonandagravitinoisassumed.Theareabelow thethickblackcurverepresentstheobservedexclusionregion,whilethedashed redlinesindicatetheexpectedlimitsandtheir±1 standarddeviationranges.The thinblacklinesshowtheeffectofthetheoreticaluncertaintiesonthesignalcross section.

Fig. 5. Theobservedandexpectedupperlimitsat95%CLonthegluinopair pro-ductioncrosssectionforagluinoGMSBmodelwithmg=2400GeV.Theone(two)

standarddeviationvariationintheexpectedlimitisshownintheinnergreen(outer yellow)band.ThebluesolidlineshowstheobservedlimitobtainedbytheCMS dis-placedjetsearch [20].

massesupto 2100,2500,and1900GeV areexcludedat95% con-fidence level for proper decay lengths of 0.3, 1, and 100m, re-spectively. The reach for models that predict significant missing transverse momentum inthe final state is significantly extended beyondallprevioussearches,forproperdecaylengthsgreaterthan

∼

0.5 m.

Acknowledgements

WecongratulateourcolleaguesintheCERNaccelerator depart-ments for the excellent performance of the LHC and thank the technicalandadministrative staffsatCERN andatother CMS in-stitutes for their contributions to the success of the CMS effort. Inaddition,wegratefullyacknowledgethecomputingcentersand personneloftheWorldwideLHCComputingGridfordeliveringso effectivelythe computinginfrastructureessential to ouranalyses. Finally, we acknowledge the enduring support for the construc-tionandoperation oftheLHC andtheCMSdetectorprovidedby thefollowing fundingagencies:BMBWF andFWF(Austria); FNRS and FWO(Belgium); CNPq,CAPES, FAPERJ, FAPERGS, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MOST, and NSFC (China); COLCIENCIAS (Colombia); MSES andCSF (Croatia); RPF (Cyprus); SENESCYT (Ecuador); MoER, ERC IUT, PUT and ERDF (Estonia); AcademyofFinland,MEC,andHIP(Finland);CEAandCNRS/IN2P3 (France); BMBF, DFG,and HGF (Germany); GSRT (Greece);NKFIA (Hungary); DAE and Department of Science andTechnology (In-dia);IPM(Iran);SFI(Ireland);INFN(Italy);MSIPandNRF(Republic ofKorea);MES(Latvia);LAS(Lithuania);MOEandUM(Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MOS (Montenegro); MBIE(New Zealand);PAEC (Pakistan); MSHE andNSC(Poland);FCT(Portugal);JINR(Dubna); MON,ROSATOM, RAS,RFBR,andNRCKI(Russia);MESTD(Serbia);SEIDI,CPAN,PCTI, and FEDER (Spain); MoSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); MST (Taipei); ThEPCenter, IPST, STAR, and NSTDA (Thailand);TUBITAKandTAEK(Turkey);NASUandSFFR(Ukraine); STFC(UnitedKingdom);DOEandNSF(USA).

Individuals have received support from the Marie-Curie pro-gramandtheEuropeanResearchCouncilandHorizon2020Grant, contract Nos. 675440, 752730, and 765710 (European Union); the Leventis Foundation; the A.P. Sloan Foundation; the Alexan-der vonHumboldt Foundation;theBelgianFederalScience Policy Office; the Fonds pourla Formation àla Recherche dans l’Indus-trie et dans l’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the F.R.S.-FNRS and FWO(Belgium) under the “Excellence ofScience –EOS”–be.h projectn.30820817; theBeijingMunicipalScience & Technology Commission, No. Z181100004218003; the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Lendület (“Momentum”) Program and the János Bolyai Re-search Scholarship of the Hungarian Academy of Sciences, the NewNationalExcellenceProgramÚNKP,theNKFIAresearchgrants 123842, 123959, 124845, 124850, 125105, 128713, 128786, and 129058(Hungary);theCouncilofScienceandIndustrialResearch, India; the HOMING PLUS program of the Foundation for Polish Science, cofinanced from European Union, Regional Development Fund, the Mobility Plus program of the Ministry of Science and Higher Education, theNational ScienceCenter (Poland), contracts Harmonia 2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543, 2014/15/B/ST2/03998, and 2015/19/B/ST2/02861, Sonata-bis 2012/07/E/ST2/01406;theNationalPrioritiesResearchProgramby Qatar NationalResearch Fund; the Ministry of Science and Edu-cation, grant no. 3.2989.2017 (Russia); the Programa Estatal de Fomento de la Investigación Científica y Técnica de Excelencia MaríadeMaeztu,grantMDM-2015-0509andtheProgramaSevero OchoadelPrincipadodeAsturias;theThalisandAristeiaprograms cofinancedbyEU-ESFandtheGreekNSRF;theRachadapisek Som-pot Fund for Postdoctoral Fellowship, Chulalongkorn University andtheChulalongkornAcademicintoIts2nd CenturyProject Ad-vancement Project (Thailand); the Welch Foundation, contract C-1845;andtheWestonHavensFoundation(USA).

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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,

L. Moreels,

Q. Python,

K. Skovpen,

S. Tavernier,

W. Van Doninck,

P. Van Mulders,

I. Van Parijs

VrijeUniversiteitBrussel,Brussel,Belgium

D. Beghin,

B. Bilin,

H. Brun,

B. Clerbaux,

G. De Lentdecker,

H. Delannoy,

B. Dorney,

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,

D. Trocino,

M. Tytgat,

W. Verbeke,

B. Vermassen,

M. Vit,

N. Zaganidis

GhentUniversity,Ghent,Belgium

O. Bondu,

G. Bruno,

C. Caputo,

P. David,

C. Delaere,

M. Delcourt,

A. Giammanco,

V. Lemaitre,

A. Magitteri,

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

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,

A. Marinov,

M. Misheva,

M. Rodozov,

M. Shopova,

G. Sultanov

InstituteforNuclearResearchandNuclearEnergy,BulgarianAcademyofSciences,Sofia,Bulgaria

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

M. Ahmad,

G.M. Chen,

H.S. Chen,

M. Chen,

C.H. Jiang,

D. Leggat,

H. Liao,

Z. Liu,

S.M. Shaheen

8

,

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

Z. Hu,

Y. Wang

TsinghuaUniversity,Beijing,China

C. Avila,

A. Cabrera,

L.F. Chaparro Sierra,

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,

S. Ceci,

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

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

AcademyofScientificResearchandTechnologyoftheArabRepublicofEgypt,EgyptianNetworkofHighEnergyPhysics,Cairo,Egypt

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,

T. Järvinen,

V. Karimäki,

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,

E. Locci,

J. Malcles,

J. Rander,

A. Rosowsky,

M.Ö. Sahin,

A. Savoy-Navarro

13

,

M. Titov

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,Ecolepolytechnique,CNRS/IN2P3,UniversitéParis-Saclay,Palaiseau,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,

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,

M. Lethuillier,

L. Mirabito,

S. Perries,

V. Sordini,

G. Touquet,

M. Vander Donckt,

S. Viret

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

A. Khvedelidze

10

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,

C. Schomakers,

J. Schulz,

M. Teroerde,

B. Wittmer

RWTHAachenUniversity,I.PhysikalischesInstitut,Aachen,Germany

A. Albert,

M. Erdmann,

S. Erdweg,

T. Esch,

B. Fischer,

R. 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,

M. Rieger,

J. Roemer,

A. Schmidt,

S.C. Schuler,

A. Sharma,

S. Thüer,

S. Wiedenbeck

RWTHAachenUniversity,III.PhysikalischesInstitutA,Aachen,Germany

G. Flügge,

W. Haj Ahmad

15

,

O. Hlushchenko,

T. Kress,

T. Müller,

A. Nehrkorn,

A. Nowack,

C. Pistone,

O. Pooth,

D. Roy,

H. Sert,

A. Stahl

16

RWTHAachenUniversity,III.PhysikalischesInstitutB,Aachen,Germany

M. Aldaya Martin,

P. Asmuss,

I. Babounikau,

H. Bakhshiansohi,

K. Beernaert,

O. Behnke,

U. Behrens,

A. Bermúdez Martínez,

D. Bertsche,

A.A. Bin Anuar,

K. Borras

17

,

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

18

,

A. Geiser,

J.M. Grados Luyando,

A. Grohsjean,

M. Guthoff,

M. Haranko,

A. Harb,

A. Jafari,

N.Z. Jomhari,

H. Jung,

A. Kasem

17

,

M. Kasemann,

H. Kaveh,

J. Keaveney,

C. Kleinwort,

J. Knolle,

D. Krücker,

W. Lange,

T. Lenz,

J. Leonard,

J. Lidrych,

K. Lipka,

W. Lohmann

19

,

R. Mankel,

I.-A. Melzer-Pellmann,

A.B. Meyer,

M. Meyer,

M. Missiroli,

G. Mittag,

J. Mnich,

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,

G.P. Van Onsem,

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,

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,

M. Stöver,

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

16

,

U. Husemann,

S. Kudella,

S. Mitra,

M.U. Mozer,

Th. Müller,

M. Musich,

A. Nürnberg,

G. Quast,

K. Rabbertz,

M. Schröder,

I. Shvetsov,

H.J. Simonis,

R. Ulrich,

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