A search for top squarks with R-parity-violating decays to all-hadronic final states with the ATLAS detector in $\sqrt{s}$ = 8 TeV proton-proton collisions

2.1 MB·

by  ATLAS Collaboration

EUROPEAN ORGANISATION FOR NUCLEAR RESEARCH (CERN)
JHEP06 (2016) 067 CERN-PH-EP-2015-296
DOI: 10.1007/JHEP06(2016)067 10th June 2016
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n
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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
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proton–proton collisions
]
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e TheATLASCollaboration
h
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v Abstract
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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
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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.
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