EUROPEAN ORGANISATION FOR NUCLEAR RESEARCH (CERN) JHEP06 (2016) 067 CERN-PH-EP-2015-296 DOI: 10.1007/JHEP06(2016)067 10th June 2016 6 1 0 2 n u J A search for top squarks with R-parity-violating decays to √ 2 = all-hadronic final states with the ATLAS detector in s 8 TeV 2 proton–proton collisions ] x e - p e TheATLASCollaboration h [ 3 v Abstract 3 5 Asearchforthepairproductionoftopsquarks,eachwithR-parity-violatingdecaysintotwo 4 √ StandardModelquarks,isperformedusing17.4fb−1of s = 8TeVproton–protoncollision 7 0 data recorded by the ATLAS experiment at the LHC. Each top squark is assumed to decay . 1 to a b- and an s-quark, leading to four quarks in the final state. Background discrimination 0 is achieved with the use of b-tagging and selections on the mass and substructure of large- 6 radius jets, providing sensitivity to top squark masses as low as 100 GeV. No evidence of 1 : an excess beyond the Standard Model background prediction is observed and top squarks v decayingtob¯s¯areexcludedfortopsquarkmassesintherange100 ≤ m ≤ 315GeVat95% i t˜ X confidencelevel. r a (cid:13)c 2016CERNforthebenefitoftheATLASCollaboration. ReproductionofthisarticleorpartsofitisallowedasspecifiedintheCC-BY-4.0license. 1 Introduction Supersymmetry (SUSY) is an extension of the Standard Model (SM) [1–7] that fundamentally relates fermions and bosons. It is an especially alluring theoretical possibility given its potential to solve the hierarchyproblem[8–11]andtoprovideadark-mattercandidate[12,13]. This paper presents a search for the pair production of supersymmetric top squarks (stops)1, which then √ eachdecaytotwoSMquarks,using17.4fb−1 of s = 8TeVproton–proton(pp)collisiondatarecorded bytheATLASexperimentattheLargeHadronCollider(LHC).ThisdecayviolatestheR-parityconser- vation (RPC) [14] assumed by most searches for stops [15,16]. In RPC scenarios, SUSY particles are requiredtobeproducedinpairsanddecaytothelightestsupersymmetricparticle(LSP),whichisstable. In R-parity-violating (RPV) models, decays to only SM particles are allowed, and generally relax the strongconstraintsnowplacedonstandardRPCSUSYscenariosbytheLHCexperiments. Itistherefore crucial to expand the scope of the SUSY search programme to include RPV models. Common signa- tures used for RPV searches include resonant lepton-pair production [17], exotic decays of long-lived particles with displaced vertices [18–21], high lepton multiplicities [22,23], and high-jet-multiplicity fi- nalstates[24]. Scenarioswhichhavestopsofmassbelow1TeVareofparticularinterestastheseaddress thehierarchyproblem[25–28]. SUSY RPV decays to SM quarks and leptons are controlled by three Yukawa couplings in the generic supersymmetricsuperpotential[29,30]. Thesecouplingsarerepresentedbyλ ,λ(cid:48) ,λ(cid:48)(cid:48) ,wherei, j,k ∈ ijk ijk ijk 1,2,3aregenerationindicesthataresometimesomittedinthediscussionthatfollows. Thefirsttwo(λ,λ(cid:48)) are lepton-number-violating couplings, whereas the third (λ(cid:48)(cid:48)) violates baryon number. It is therefore generally necessary that either of the couplings to quarks, λ(cid:48) or λ(cid:48)(cid:48), be vanishingly small to prevent spontaneous proton decay [7]. It is common to consider non-zero values of each coupling separately. Scenariosinwhichλ(cid:48)(cid:48) (cid:44) 0areoftenreferredtoUDDscenariosbecauseofthebaryon-number-violating termthatλ(cid:48)(cid:48) controlsinthesuperpotential. Currentindirectexperimentalconstraints[31]onthesizesof each of the UDD couplings λ(cid:48)(cid:48) from sources other than proton decay are primarily valid for low squark massandforfirst-andsecond-generationcouplings. Thoselimitsaredrivenbydoublenucleondecay[32] (forλ(cid:48)(cid:48) ),neutronoscillations[33](forλ(cid:48)(cid:48) ),andZ-bosonbranchingratios[34]. 112 113 Thebenchmarkmodelconsideredinthispaperisabaryon-number-violatingRPVscenarioinwhichthe stop is the LSP. The search specifically targets low-mass stops in the range 100–400GeV that decay via the λ(cid:48)(cid:48) coupling, thus resulting in stop decays t˜ → b¯s¯ (assuming a 100% branching ratio) as shown 323 in Figure 1. The motivation to focus on the third-generation UDD coupling originates primarily from the minimal flavour violation (MFV) hypothesis [35] and the potential for this decay channel to yield a possible signal of RPV SUSY with a viable dark-matter candidate [36]. The MFV hypothesis essen- tiallyrequiresthatallflavour-andCP-violatinginteractionsarelinkedtotheknownstructureofYukawa couplings,andhasbeenusedtoarguefortheimportanceoftheλ(cid:48)(cid:48) couplings[37]. The process t˜t˜∗ → b¯s¯bs represents an important channel in which to search for SUSY in scenarios not yet excluded by LHC data [36–38]. Some of the best constraints on this process are from the ALEPH Collaboration,whichsetlowerboundsonthemassofthestopatm (cid:38) 80GeV[39]. TheCDFCollabor- t˜ ationextendedtheselimits,excluding50 (cid:46) m (cid:46) 90GeV[40]. TheCMSCollaborationrecentlyreleased t˜ the results of a search that excludes 200 (cid:46) m (cid:46) 385 GeV [41] in the case where heavy-flavour jets are t˜ present in the final state. In addition, two ATLAS searches have placed constraints on RPV stops that 1Thesuperpartnersoftheleft-andright-handedtopquarks,t˜ andt˜ ,mixtoformthetwomasseigenstatest˜ andt˜,wheret˜ L R 1 2 1 isthelighterone.Thisanalysisfocusesont˜,whichisreferredtohereafterast˜. 1 2 decay to b¯s¯ when they are produced in the decays of light gluinos (m (cid:46)900–1000GeV) [42,43]. The g˜ search presented here specifically focuses on direct stop pair production and seeks to close the gap in excludedstopmassbetween∼ 100–200GeV. ContributionsfromRPVinteractionsatproduction–such aswouldberequiredforresonantsinglestopproduction–areneglectedinthisanalysis. Thisapproachis validprovidedthattheRPVinteractionstrengthissmallcomparedtothestrongcouplingconstant,which is the case for λ(cid:48)(cid:48) (cid:46) 10−2–10−1 [44] and for the estimated size of λ(cid:48)(cid:48) ∼ 10−4 from MFV in the model 323 323 describedinRef.[37]. The reduced sensitivity of standard SUSY searches to RPV scenarios is primarily due to the limited effectivenessofthehighmissingtransversemomentumrequirementsusedintheeventselectioncommon to many of those searches, motivated by the assumed presence of undetected LSPs. Consequently, the primarychallengeinsearchesforRPVSUSYfinalstatesistoidentifysuitablesubstitutesforbackground rejectiontothecanonicallargemissingtransversemomentumsignature. Figure1:Benchmark signal process considered in this analysis. The solid black lines represent Standard Model particles,thedashedredlinesrepresentthestops,andthebluepointsrepresentRPVverticeslabelledbytherelevant couplingforthisdiagram. Backgrounds dominated by multijet final states typically overwhelm the signal in the four-jet topology. In order to overcome this challenge, new observables are employed to search for t˜t˜∗ → b¯s¯bs in the low- m regime [38]. For m ≈ 100–300GeV, the initial stop transverse momentum (p ) spectrum extends t˜ t˜ T significantlyintotherangeforwhich p (cid:29) m. Thisfeatureistheresultofboostsreceivedfrominitial- T t˜ stateradiation(ISR)aswellasoriginatingfromthepartondistributionfunctions(PDFs). AstheLorentz boostofeachstopbecomeslarge,thestopdecayproductsbegintomergewitharadiusroughlygivenby ∆R ≈ 2m/p , and thus can be clustered together within a single large-radius (large-R) jet with a mass t˜ T mjet ≈ m. Byfocusingonsuchcases,thedijetandmultijetbackgroundcanbesignificantlyreducedvia t˜ selections that exploit this kinematic relationship and the structure of the resulting stop jet, in a similar way to boosted objects used in previous measurements and searches by ATLAS [45–49]. In this case, since the stop is directly produced in pairs instead of from the decay of a massive parent particle, the strategyismosteffectiveatlowm wheretheboostsarethelargest. t˜ 3 2 The ATLAS detector TheATLASdetector[50,51]providesnearlyfullsolidangle2coveragearoundthecollisionpointwithan innertrackingsystem(innerdetector,orID)coveringthepseudorapidityrange|η| < 2.5,electromagnetic (EM) and hadronic calorimeters covering |η| < 4.9, and a muon spectrometer covering |η| < 2.7 that providesmuontriggercapabilityupto|η| < 2.4. TheIDcomprisesasiliconpixeltrackerclosesttothebeamline,amicrostripsilicontracker,andastraw- tubetransition-radiationtrackeratradiiupto108cm. Athinsolenoidsurroundingthetrackerprovidesa 2Taxialmagneticfieldenablingthemeasurementofcharged-particlemomenta. TheoverallIDaccept- ancespansthefullazimuthalrangeinφ,andtherange|η| < 2.5forparticlesoriginatingnearthenominal LHCinteractionregion[52]. The EM and hadronic calorimeters are composed of multiple subdetectors spanning |η| ≤ 4.9. The EM barrel calorimeter uses a liquid-argon (LAr) active medium and lead absorbers. In the region |η| < 1.7, the hadronic (Tile) calorimeter is constructed from steel absorber and scintillator tiles and is separated into barrel (|η| < 1.0) and extended-barrel (0.8 < |η| < 1.7) sections. The endcap (1.375 < |η| < 3.2) andforward(3.1 < |η| < 4.9)regionsareinstrumentedwithLArcalorimetersforEMaswellashadronic energymeasurements. A three-level trigger system is used to select events to record for offline analysis. The different parts of the trigger system are referred to as the level-1 trigger, the level-2 trigger, and the event filter [53]. The level-1 trigger is implemented in hardware and uses a subset of detector information to reduce the event rate to a design value of at most 75 kHz. The level-1 trigger is followed by two software-based triggers,thelevel-2triggerandtheeventfilter,whichtogetherreducetheeventratetoafewhundredHz. The search presented in this document uses a trigger that requires a high-p jet and a large summed jet T transversemomentum(H ),asdescribedinSection5. T 3 Monte Carlo simulation samples MonteCarlo(MC)simulationisusedtostudythesignalacceptanceandsystematicuncertainties,totest the background estimation methods used, and to estimate the tt¯background. In all cases, events are passedthroughthefullGEANT4[54]detectorsimulationofATLAS[55]afterthesimulationoftheparton showerandhadronisationprocesses. Followingthedetectorsimulation,identicaleventreconstructionand selectioncriteriaareappliedtoboththeMCsimulationandtothedata. Multiple ppcollisionsinthesame and neighbouring bunch crossings (pile-up) are simulated for all samples by overlaying additional soft ppcollisionswhicharegeneratedwithPYTHIA8.160[56]usingtheATLASA2setoftunedparameters (tune) in the MC generator [57] and the MSTW2008LO PDF set [58]. These additional interactions are overlaid onto the hard scatter and events are reweighted such that the MC distribution of the average number of pp interactions per bunch crossing matches the measured distribution in the full 8 TeV data sample. 2TheATLASreferencesystemisaCartesianright-handedcoordinatesystem,withthenominalcollisionpointattheorigin. Theanticlockwisebeamdirectiondefinesthepositivez-axis,whilethepositivex-axisisdefinedaspointingfromthecollision pointtothecentreoftheLHCringandthepositivey-axispointsupwards. Theazimuthalangleφismeasuredaroundthe beam axis, and the polar angle θ is measured with respect to the z-axis. Pseudorapidity is defined as η = −ln[tan(θ/2)], rapidityisdefinedasy=0.5 ln[(E+p)/(E−p)],whereEistheenergyand p isthez-componentofthemomentum,and z z z transverseenergyisdefinedasE =Esinθ. T 4 The signal process is simulated using Herwig++ 2.6.3a [59] with the UEEE3 tune [60] for several stop- mass hypotheses using the PDF set CTEQ6L1 [61,62]. All non-SM particles masses are set to 5 TeV exceptforthestopmass,whichisscannedin25GeVstepsfromm = 100GeVtom = 400GeV. t˜ t˜ The signal cross-section used (shown in Figure 2) is calculated to next-to-leading order in the strong couplingconstant,addingtheresummationofsoftgluonemissionatnext-to-leading-logarithmicaccuracy (NLO+NLL) [63–65]. For the range of stop masses considered, the uncertainty on the cross-section is approximately 15% [66]. MadGraph 5.1.4.8 [67] is used to study the impact of ISR on the stop p T spectrum. TheMadGraphsampleshaveoneadditionalpartoninthematrixelement,whichimprovesthe modelling of a hard ISR jet. MadGraph is then interfaced to PYTHIA 6.426 with the AUET2B tune [68] and the CTEQ6L1 PDF set for parton shower and hadronisation. The distribution of p (t˜t˜∗) from the T nominalHerwig++signalsampleisthenreweightedtomatchthatoftheMadGraph+PYTHIAsample. Dijet and multijet events, as well as top quark pair (tt¯) production processes, are simulated in order to study the SM contributions and background estimation techniques. For optimisation studies, SM dijet and multijet events are generated using Herwig++ 2.6.3a with the CTEQ6L1 PDF set. Top quark pair events are generated with the POWHEG-BOX-r2129 [69–71] event generator with the CT10 NLO PDF set [72]. These events are then interfaced to PYTHIA 6.426 with the P2011C tune [73] and the same CTEQ6L1PDFsetasHerwig++. Thett¯productioncross-sectioniscalculatedatnext-to-next-to-leadingorder(NNLO)inQCDincluding resummation of next-to-next-to-leading logarithmic (NNLL) soft gluon terms with top++2.0 [74–79]. Thevalueofthett¯cross-sectionisσ = 253+13 pb. tt¯ −15 ] b p 103 pp ˜t˜t∗ [ → n α + scale + PDF o s ti 102 s =8 TeV c e p s - 1 s 10 s o r C 0 10 -1 10 -2 10 -3 10 100 200 300 400 500 600 700 800 m [GeV] ˜t √ Figure2:Cross-sectionfordirectt˜t˜∗pairproductionattheLHCcentre-of-massenergyof s=8TeV[63–65]. 5 4 Object definitions The data are required to have satisfied criteria designed to reject events with significant contamination from detector noise, non-collision beam backgrounds, cosmic rays, and other spurious effects. To re- ject non-collision beam backgrounds and cosmic rays, events are required to contain a primary vertex consistent with the LHC beamspot, reconstructed from at least two tracks with transverse momenta ptrack > 400 MeV. If more than one vertex satisfies these criteria, the primary vertex is chosen as the T (cid:80) onewiththehighest (p2). tracks T Theanti-k algorithm[80],witharadiusparameterofR = 0.4,isusedforinitialjet-findingusingversion3 t ofFastJet[81]. Theinputstothejetreconstructionarethree-dimensionaltopo-clusters[82]. Thismethod firstclusterstogethertopologicallyconnectedcalorimetercellsandclassifiestheseclustersaseitherelec- tromagnetic or hadronic. The classification uses a local cluster weighting calibration scheme based on cell-energydensityandshowerdepthwithinthecalorimeter[83]. Basedonthisclassification,energycor- rectionsareappliedwhicharederivedfromsingle-pionMCsimulations. Dedicatedhadroniccorrections are derivedto accountfor theeffects ofdifferences inresponse tohadrons comparedto electrons, signal lossesduetonoise-suppressionthresholdeffects,andenergylostinnon-instrumentedregions. Thefinal jet energy calibration is derived from MC simulation as a correction relating the calorimeter response to the jet energy at generator level. In order to determine these corrections, the same jet definition used in the reconstruction is applied to stable (with lifetimes greater than 10 ps) generator-level particles, ex- cluding muons and neutrinos. A subtraction procedure is also applied in order to mitigate the effects of pile-up [84]. Finally, the R = 0.4 jets are further calibrated with additional correction factors derived in situfromacombinationofγ+jet,Z+jet,anddijet-balancemethods[83]. All jets reconstructed with the anti-k algorithm using a radius parameter of R = 0.4 and a measured t jet p > 20 GeV are required to satisfy the quality criteria discussed in detail in Ref. [85]. These quality T criteria selections for jets are extended to prevent contamination from detector noise through several detector-region-specific requirements. Jets contaminated by energy deposits due to noise in the forward hadronic endcap calorimeter are rejected and jets in the central region (|η| < 2.0) that are at least 95% containedwithintheEMcalorimeterarerequiredtonotexhibitanyelectronicpulseshapeanomalies[86]. Anyeventwithajetthatfailstheserequirementsisremovedfromtheanalysis. Identificationofjetscontainingb-hadrons(so-calledb-jets)isachievedthroughtheuseofamultivariate b-tagging algorithm referred to as MV1 [87]. This algorithm is based on an artificial neural-network algorithmthatexploitstheimpactparametersofcharged-particletracks,theparametersofreconstructed secondary vertices, and the topology of b- and c-hadron decays inside an anti-k R = 0.4 jet. A working t point corresponding to a 70% b-jet efficiency in simulated tt¯events is used. The corresponding mis- tag rates, defined as the fraction of jets originating from non-b-jets which are tagged by the b-tagging algorithminaninclusivejetsample,forlightjetsandc-jetsareapproximately1%and20%,respectively. Toaccountfordifferenceswithrespecttodata,data-derivedcorrectionsareappliedtotheMCsimulation fortheidentificationefficiencyofb-jetsandtheprobabilitytomis-identifyjetsresultingfromlight-flavour quarks,charmquarks,andgluons. Initialjet-findingisextendedusinganapproachcalledjetre-clustering[88]. Thisallowstheuseoflarger- radius jet algorithms while maintaining the calibrations and systematic uncertainties associated with the input jet definition. Small-radius anti-k R = 0.4 jets with p > 20GeV and |η| < 2.4 are used as input t T withoutmodificationtoananti-k R = 1.5large-Rjetalgorithm,toidentifythehadronicstopdecays. The t small-R jets with p < 50GeV are required to have a jet vertex fraction (JVF) of at least 50%. After T 6 summingthe p ofcharged-particletracksmatchedtoajet,theJVFisthefractionduetotracksfromthe T selectedhard-scatteringinteractionanditprovidesameansbywhichtosuppressjetsfrompile-up. Tofurtherimprovethebackgroundrejection,asplittingprocedureisperformedoneachofthetwolead- ing large-R jets. After jet-finding, the constituents of these large-R jets – the anti-k R = 0.4 input t objects – are processed separately by the Cambridge–Aachen (C/A) algorithm [89,90], as implemented in FastJet3. The C/A algorithm performs pair-wise recombinations of proto-jets (the inputs to the jet algorithm) purely based on their angular separation. Smaller-angle pairs are recombined first, thus the finalrecombinedpairtypicallyhasthelargestseparation. TheC/Afinalclusteringisthenundonebyone step,suchthattherearetwobranches”a”and”b”. Thefollowingsplittingcriteriaarethenappliedtothe branches”a”and”b”ofeachofthetwoleadinglarge-Rjets: • Bothbranchescarryappreciable p relativetothelarge-Rjet: T min[p (a),p (b)] T T > 0.1. (1) p (large−R) T • Themassofeachbranchissmallrelativetoits p : T m(a) m(b) < 0.3 and < 0.3. (2) p (a) p (b) T T Ifeitheroftheleadingtwolarge-Rjetsfailstheseselections,theeventisdiscarded. Thisimplementation isidenticaltoRef.[38],whichisderivedfromthediboson-jettagger[91]. Thisapproachdifferssomewhat fromthatusedinRef.[92]inthatnorequirementisplacedontherelativemassesofthelarge-Randsmall- Rjets. 5 Trigger and offline event selections Events must satisfy jet and H selections applied in the trigger which require H = (cid:80)p > 500GeV, T T T calculated as the sum of level-2 trigger jets within |η| < 3.2, and a leading jet within |η| < 3.2 with p > 145GeV. This relatively low-threshold jet trigger came online part-way through the data-taking T period in 2012 and collected 17.4 fb−1 of data. The corresponding offline selections require events to have at least one anti-k R = 0.4 jet with p > 175 GeV and |η| < 2.4, as well as H > 650GeV, where t T T the sum is over all anti-k R = 0.4 jets with p > 20GeV, |η| < 2.4, and JVF > 0.5 if p < 50GeV. t T T Thecumulativetriggerselectionefficiencyisgreaterthan99%fortheseofflinerequirements. Theoffline event preselection further requires that at least two large-R jets with p > 200GeV and mass > 20GeV T bepresentineachevent. Theserequirementsselectarangeofphasespaceforlowstopmassesinwhich thetransversemomentumofthestopsisoftensignificantlygreaterthantheirmass. The signal region (SR) is defined to suppress the large multijet background and to enhance the fraction ofeventsthatcontainlarge-Rjetsconsistentwiththeproductionofstoppairs,witheachstopdecayingto alightquarkandab-quark. Simulationstudiesindicatethatthreekinematicobservablesareparticularly usefulforbackgrounddiscrimination: 7 1. The mass asymmetry between the two leading large-R jets in the event (with masses m and m , 1 2 respectively),definedas |m −m | A = 1 2 , (3) m +m 1 2 differentiatessignalfrombackgroundsincethetwostopsubjet-pairresonancesareexpectedtobe ofequalmass. 2. The (absolute value of the cosine of the) stop-pair production angle, |cosθ∗|, with respect to the beamlineinthecentre-of-massreferenceframe3distinguishesbetweencentrallyproducedmassive particles and high-mass forward-scattering events from QCD. It provides efficient discrimination anddoesnotexhibitsignificantvariationwiththestopmass. 3. Inaddition,arequirementonthesubjetsisappliedtoeachoftheleadinglarge-Rjetsintheevent. The p ofeachsubjetaandbrelativetotheotherisreferredtoasthesubjet p /p ,definedby T T2 T1 min[p (a),p (b)] subjet p /p = T T . (4) T2 T1 max[p (a),p (b)] T T TheA,|cosθ∗|,andsubjetp /p variablesprovidegooddiscriminationbetweensignalandbackground T2 T1 √ andaremotivatedbyanATLASsearchforscalargluonsat s = 7TeV[93]aswellasbyRefs.[38,94]. Inadditiontothekinematicobservablesdescribedabove,b-taggingappliedtoanti-k R = 0.4jetsprovides t averypowerfuldiscriminantfordefiningboththesignalandthecontrolregions,andonethatisapprox- imatelyuncorrelatedwiththekinematicfeaturesdiscussedabove. Usingthesekinematicobservablesand the presence of at least two b-tagged jets per event, the signal region is defined by (for the leading two large-Rjets) A < 0.1, |cosθ∗| < 0.3, (5) subjet p /p > 0.3. T2 T1 Distributions of the discriminating variables are shown in Figure 3. Insofar as the data points are dom- inated by background in these plots, even in the case of a potential signal, the data points should be understoodtorepresentthebackground. Following these selections, the distribution of the average mass of the leading two large-R jets, mjet = avg (mjet +mjet)/2, is used to search for an excess of events above the background prediction. The search is 1 2 jet done in regions of m that are optimised to give the best significance. As shown in Figure 4, the stop avg signal is expected as a peak that would appear on top of a smoothly falling background spectrum. A Gaussiandistributionisfittedtothestopsignalmjet peak. Themeanofthefit,(cid:104)mjet (cid:105),isconsistentwith avg avg m ineachcase. Theresolutionofthemjet peakisgivenapproximately s/(cid:104)mjet (cid:105) ∼ 5−7%(where sisthe t˜ avg avg standarddeviationofthefit),andhasonlyaweakdependenceonthestopmassintherangeprobedbythis analysis. Masswindowsinmjet aredeterminedbytakingintoaccounttheeffectofjetenergyscale(JES) avg jet and jet energy resolution (JER) measurement uncertainties on the expected signal m distribution and avg theestimatedbackground. Thesizeofeachmasswindowisdefinedtobeequaltoorlargerthanthefull jet widthofthem massspectrumforthem modelthatbestcorrespondstothatrange. Thedefinitionsof avg t˜ 3Thisscatteringangle,θ∗,isformedbyboostingthetwostoplarge-Rjetstothecentre-of-massframeandmeasuringtheangle ofeitherstoplarge-Rjetwithrespecttothebeamline. 8 1.2 0.7 s 5 ent ATLAS Data 0.0 ATLAS Data Fraction of ev 0.81 A|scsu o <b=s j0(e q8.t1 * p)T|T e2</V p0T,. 131>70.4.3 fSb-1R mmm ~~~ttt === 124050000 GGGeeeVVV n of events / 000...456 n|scsu o ‡b=s j2(e q8t * p)T|T e2</V p0T,. 131>70.4.3 fb-1 mmm ~~~ttt === 124050000 GGGeeeVVV 0.6 o acti 0.3 r F 0.4 0.2 0.2 0.1 SR 0 1 2 3 4 0 0.1 0.2 0.3 0.4 0.5 0.6 Number of b-jets, n Mass asymmetry, A (a) (b) 1 0.4 1 0.6 s / 0.0.35 AsT =L 8A TSe V, 17.4 fb-1 Dma~ t=a 100 GeV s / 0. AsT =L 8A TSe V, 17.4 fb-1 Dma~ t=a 100 GeV nt n ‡ 2 m ~t = 250 GeV nt 0.5 n ‡ 2 m ~t = 250 GeV eve 0.3 Asu <b j0e.t1 p /p >0.3 m ~tt = 400 GeV eve A|c o<s 0(q.*1)| < 0.3 m ~tt = 400 GeV of 0.25 T2 T1 of 0.4 n n o o SR cti 0.2 cti 0.3 a a r r F F 0.15 0.2 0.1 0.1 0.05 SR 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 |cosq *| Leading jet: subjet p /p T2 T1 (c) (d) Figure3:Distributions of the discriminating variables for events in which the other three selections are applied for each subfigure. The signal region is indicated with a red arrow. All distributions are normalised to unity. Overflowsareincludedinthelastbinforsubfigures(a)and(b).(a)Numberofb-tags/event,n.(b)Large-Rjetmass asymmetry,A. (c)Stop-paircentre-of-massframeproductionangle,|cosθ∗|. (d)Subjet p /p fortheleadingjet T2 T1 ineachevent. thesemasswindowsandthesignalefficiencyineachwindowaregiveninTable1. Figure4(a)showsthe masswindowsoverlaidontopofthesignalmjet distributionsforafewstopmasses. Theefficiencyofthe avg mass windows (relative to the SR cuts of Eq. (5)) varies from 79% at 100GeV to 19% at 400GeV. The low efficiency at high mass is due to the fact that the decay products are often not fully contained in the large-Rjet, ascanbeseeninFigure4(b). Figure5showstheproductofacceptanceandefficiency, after 9 the SR cuts and mass windows, as a function of m. The significantly lower acceptance times efficiency t˜ for light stop masses in Figure 5 is almost entirely due to the efficiency of the trigger selections which are for 100, 250, and 400 GeV stop masses 0.56%, 22%, and 96%, respectively. This low efficiency is compensatedbythelargecrosssectionforlowstopmassesretainingsensitivitytothesemassvalues. (a) Linearscale V Ge 105 AsT =L 8A TSeVS, im17u.4la ftbi-o1n mm ~~tt == 110500 GGeeVV,, ss//<<mmajajeevvttgg>> == 66..79%% 10 104 m ~t = 200 GeV, s/<majevtg> = 5.5% / m ~t = 250 GeV, s/<majevtg> = 5.9% ents 103 s is the stdm.d ~et =v .3 a0n0d G <emV,aje v tgs>/< ism tajehvtge> m = e5a.6n% v of the Gaussian fitted to the mjet spectrum E 102 avg 10 1 100 150 200 250 300 350 mjet [GeV] avg (b) Logarithmicscale Figure4:Distributionsoftheaveragejetmassmjet forsignalsampleswithm =100,150,200,250,and300GeV, avg t˜ inlinear(a)andlogarithmic(b)scales(solidlines).AGaussiandistributionisfittedtothemasspeakofeachsample (dashed lines). The resolution, s/(cid:104)mjet (cid:105), is quoted for each stop mass value. The mass windows are highlighted avg with the shaded rectangles in (a). The long tail peaking around m/2 for high-mass stops shown in (b) is due to t˜ eventswherenotallstopdecayproductsareclusteredwithinthelarge-Rjets. 10