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arXiv:1209.2102v2 [hep-ex] 25 Mar 2013

EUROPEAN ORGANISATION FOR NUCLEAR RESEARCH (CERN)

CERN-PH-EP-2012-207

Submitted to: Phys. Lett. B.

Search for light top squark pair production in final states with

leptons and

b

-jets with the ATLAS detector in

√s = 7 TeV

proton–proton collisions

The ATLAS Collaboration

Abstract

The results of a search for pair production of light top squarks are presented, using 4.7 fb

−1

of

s = 7 TeV

proton–proton collisions collected with the ATLAS detector at the Large Hadron Collider.

This search targets top squarks with masses similar to, or lighter than, the top quark mass. Final states

containing exclusively one or two leptons (

e, µ

), large missing transverse momentum, light flavour jets

and

b

-jets are used to reconstruct the top squark pair system. Event-based mass scale variables

are used to separate the signal from a large

t

background. No excess over the Standard Model

expectations is found. The results are interpreted in the framework of the Minimal Supersymmetric

Standard Model, assuming the top squark decays exclusively to a chargino and a

b

-quark, while

requiring different mass relationships between the Supersymmetric particles in the decay chain. Light

top squarks with masses between 123–167

GeV

are excluded for neutralino masses around 55

GeV

.

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Search for light top squark pair production in final states with leptons and b-jets

with the ATLAS detector in

s

= 7 TeV proton–proton collisions

The ATLAS Collaboration

Abstract

The results of a search for pair production of light top squarks are presented, using 4.7 fb−1 ofs = 7 TeV proton–

proton collisions collected with the ATLAS detector at the Large Hadron Collider. This search targets top squarks with masses similar to, or lighter than, the top quark mass. Final states containing exclusively one or two leptons (e, µ), large missing transverse momentum, light flavour jets and b-jets are used to reconstruct the top squark pair system.

Event-based mass scale variables are used to separate the signal from a large t¯t background. No excess over the Standard Model

expectations is found. The results are interpreted in the framework of the Minimal Supersymmetric Standard Model, assuming the top squark decays exclusively to a chargino and a b-quark, while requiring different mass relationships between the Supersymmetric particles in the decay chain. Light top squarks with masses between 123–167 GeV are excluded for neutralino masses around 55 GeV.

1. Introduction

Supersymmetry (SUSY) [1–9] is an extension of the

Standard Model (SM) which naturally resolves the hier-archy problem by introducing supersymmetric partners to the known fermions and bosons. In the framework of a generic R-parity conserving minimal supersymmetric

ex-tension of the SM (MSSM) [10–14], SUSY particles are

produced in pairs and the lightest supersymmetric particle (LSP) is stable. In a large variety of models the LSP is the

lightest neutralino, ˜χ0

1, which only interacts weakly. The

scalar partners of right-handed and left-handed quarks

(squarks) can mix to form two mass eigenstates (˜q1, ˜q2).

In particular, the lightest top squark (stop, ˜t1), could have

a mass similar to, or lower than, the top quark (t) mass. In this Letter, a search for direct stop pair production is presented targeting these scenarios. A SUSY particle

mass hierarchy is assumed such that mt&m˜t1 > mχ˜

± 1 and the stop decays exclusively into a b-quark and a chargino (˜t1 → ˜χ

±

1b). The chargino subsequently decays via a

vir-tual or real W boson ( ˜χ±1 → W(∗)χ˜01). The masses of

all other supersymmetric particles, including the mass of ˜

t2, are assumed to be above the TeV scale. In the case

where m˜t1 ∼ mt, direct stop pair production will lead

to final states very similar to SM t¯t events, which form

the dominant background. In the first stage of the

anal-ysis the t¯t system (including stop pairs) is reconstructed

from final states which contain exclusively one or two lep-tons (ℓ = e, µ), b-jets, light flavour jets, and large miss-ing transverse momentum. The use of event-based mass scale variables allows discrimination between stop pairs

and the t¯t background. The results are interpreted in

three MSSM scenarios where stop and neutralino masses are varied and different assumptions are made about the

chargino–neutralino mass difference: gaugino universality (mχ˜±1 ≃ 2 × mχ˜

0

1); fixed chargino mass of 106 GeV (above

the present exclusion limit from LEP [15]); and fixed stop

mass of 180 GeV with variations of the chargino–neutralino mass difference. Previous results for direct production of top squark pairs in the same MSSM scenarios have

been presented by the CDF [16] and ATLAS

Collabora-tions [17].

2. The ATLAS Detector

The ATLAS detector is described in detail

else-where [18]. It comprises an inner detector (ID) surrounded

by a thin superconducting solenoid, a calorimeter sys-tem and an extensive muon spectrometer embedded in a toroidal magnetic field. The ID tracking system con-sists of a silicon pixel detector, a silicon microstrip de-tector (SCT), and a transition radiation tracker (TRT). It provides tracking information for charged particles in a

pseudorapidity1 range |η| < 2.5 and allows efficient

iden-tification of jets originating from b-hadron decays using impact parameter measurements to reconstruct secondary decay vertices. The ID is immersed in a 2 T axial mag-netic field and is surrounded by high-granularity liquid-argon (LAr) sampling electromagnetic calorimeters. An iron/scintillator tile calorimeter provides hadronic energy

1ATLAS uses a right-handed coordinate system with its origin at

the nominal interaction point (IP) in the centre of the detector, with the z-axis coinciding with the beam pipe axis. The x-axis points from the IP to the centre of the LHC ring, and the y-axis points upwards. Cylindrical coordinates (r, φ) are used in the transverse plane, φ being the azimuthal angle around the beam pipe. The pseudorapidity is defined in terms of the polar angle θ as η = − ln tan(θ/2). The

distance ∆R in the η −φ space is defined as ∆R =p(∆η)2+ (∆φ)2.

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measurements in the central pseudorapidity range (|η| < 1.7). In the forward regions (1.5 < |η| < 4.9), it is comple-mented by two end-cap calorimeters using LAr as the ac-tive material and copper or tungsten as an absorber. The muon spectrometer (MS) surrounds the calorimeters and consists of three large superconducting eight-coil toroids, a system of tracking chambers, and detectors for triggering. The MS is segmented into barrel (|η| < 1.05) and end-cap regions (1.05 < |η| < 2.7).

3. Simulated Event Samples

Monte Carlo (MC) simulated event samples are used to develop and validate the analysis procedure and to help evaluate the SM backgrounds in the signal regions.

Pro-duction of top quark pairs is simulated with MC@NLO [19–

21], using a top quark mass of 172.5 GeV and the

next-to-leading-order (NLO) parton distribution function (PDF)

set CT10 [22]. Samples of W and Z/γ∗

production, with

accompanying light- and heavy-flavour jets, and t¯t with

additional b-jets (t¯tb¯b) are generated using ALPGEN [23].

Samples of Zt¯t, W t¯t and W W t¯t are generated with

MadGraph [24] interfaced to PYTHIA [25]. Diboson (W W ,

W Z, ZZ) production is generated with HERWIG [26].

Sin-gle top production is generated with MC@NLO for the s- and

t + W -channels, and AcerMC [27] for the t-channel.

Frag-mentation and hadronisation modelling for the ALPGEN and

MC@NLOsamples are performed by HERWIG, using JIMMY [28]

for the underlying event. ALPGEN and POWHEG [29]

sam-ples are used to assess the systematic uncertainties

asso-ciated with the choice of generator for t¯t production, and

AcerMCsamples are used to assess the uncertainties

associ-ated with initial and final state radiation (ISR/FSR). The choice of PDF depends on the generator: the MRST2007

LO [30] set is used with HERWIG, CTEQ6L1 [31] with ALPGEN.

The background predictions are normalised to the theoret-ical cross sections, including higher-order QCD corrections

when available, as detailed in Ref. [32].

Direct stop pair production samples are generated using

PYTHIA6 and Herwig++ [33]. Polarisation effects due to

the choice of left- and right-handed scalar top mixing were found to have a negligible impact on the analysis. Signal cross sections are calculated to NLO in the strong coupling constant, adding the resummation of soft gluon emission at

next-to-leading-logarithmic accuracy (NLO + NLL) [34–

36].

All MC samples are produced using a detector

simu-lation [37] based on GEANT4 [38]. MC samples are

re-weighted such that the number of additional proton– proton interactions per bunch crossing (pile-up) agrees with that observed in data.

4. Event Reconstruction and Preselection

Electron candidates are reconstructed from energy clus-ters in the electromagnetic calorimeclus-ters matched to a track

in the ID. They are required to have momentum in the

transverse plane (pT) pT> 20 GeV, |η| < 2.47 and to pass

the “medium” shower shape and track selection criteria of Ref. [39].

Muons are reconstructed using an algorithm [40] that

combines information from the ID and MS. Candidate

muons are required to have pT> 10 GeV, |η| < 2.4, and be

reconstructed with sufficient numbers of hits in the pixel, SCT and TRT detectors. In order to reject muons originat-ing from cosmic rays, events containoriginat-ing muon candidates with a closest approach distance greater than 1 mm to the primary vertex in the z direction, or a transverse impact parameter greater than 0.2 mm, are rejected. The pri-mary vertex itself is defined as the vertex with the highest

summed track p2

T.

Jet candidates are reconstructed using the anti-kt jet

clustering algorithm [41] with a radius parameter of R =

0.4. The measured jet energy is corrected for inhomo-geneities and for the non-compensating nature of the

calorimeter using pT and η dependent correction factors

based on MC simulation validated with extensive test-beam and collision-data studies. Furthermore, the recon-structed jet is modified such that its direction points to the primary vertex, and events containing jets likely to have

arisen from detector noise or cosmic rays are rejected [42].

Only jet candidates with corrected transverse momenta

pT> 20 GeV and |η| < 4.5 are retained.

Following their reconstruction, candidate jets and lep-tons may point to the same energy deposits in the calorimeter. These overlaps are resolved by first discard-ing any jet candidate within ∆R = 0.2 of an electron. Then, any electron or muon candidate remaining within ∆R = 0.4 of any surviving jet is also discarded.

The two-dimensional missing transverse momentum

vec-tor, pmiss

T , and its magnitude ETmiss, are computed from the

negative of the vector sum of the pT of the reconstructed

electrons, muons and jets, and all energy clusters with |η| < 4.9 not associated with such objects.

Electrons must additionally pass the “tight” electron

criteria of Ref. [39], and be isolated such that the

scalar pTsum of tracks within a cone of ∆R = 0.2 around

the electron candidate (not including the electron track)

must be less than 10% of the electron pT. Muons must also

be isolated such that the pTsum of tracks (not including

the muon track) within ∆R = 0.2 is less than 1.8 GeV. Jets are further required to lie within |η| < 2.5 and must have

more than 75% of pT-weighted ID tracks associated to the

primary vertex. This reduces the presence of jets arising from uncorrelated soft collisions (pile-up) and discards jets without reconstructed tracks.

A b-tagging algorithm [43] is used to identify jets

con-taining a b-hadron decay. The algorithm uses a multivari-ate technique based on the properties of the secondary ver-tex, of tracks within the jet, and of the jet itself. The

nom-inal b-tagging efficiency, determined from t¯t MC events, is

on average 60%, with a misidentification, or mis-tag, rate for c-quark (light-quark/gluon) jets of 10% (1%).

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5. Signal Region Definitions

The data are selected with a three-level trigger system. The events used in this search satisfied single-lepton trig-ger requirements that varied with the data-taking period. The tightest electron trigger has an efficiency of ∼97% for

electrons with pT > 25 GeV. The muon trigger reaches

an efficiency plateau of ∼90% in the end-caps for muons

with pT> 20 GeV. The equivalent efficiency in the barrel

region is ∼75% due to a lower geometrical acceptance for the muon trigger chambers in this region. Collision events are selected by requiring at least one reconstructed vertex

with at least five associated tracks with pT > 400 MeV,

consistent with the beam spot position. Two signal re-gions are defined containing either exclusively one or two charged leptons (ℓ = e, µ) in the final state, referred to hereafter as the 1- and 2-lepton channels respectively. A

total integrated luminosity of 4.7 ± 0.2 fb−1 is used,

fol-lowing the beam, detector and data-quality requirements

as described in Refs. [44,45].

In the 1-lepton channel, events are required to contain

the minimum number of objects expected from the t¯t →

W bW ¯b → q¯q′

bℓ¯ν¯b decay. Exactly one lepton is required,

which must have pT > 25 GeV (20 GeV) for the electron

(muon) channel and fulfil the trigger requirements. Events

with an additional electron (muon) with pT > 20 GeV

(10 GeV) are rejected to ensure no events are classified as belonging to both 1- and 2-lepton channels. A minimum of four jets are required in the event, at least two of which must pass the b-tagging requirements and at least two must fail them. Events are required to have a missing transverse

momentum of Emiss

T > 40 GeV. Background from

multi-jet processes, in which multi-jets are misidentified as leptons, is rejected by requiring that the transverse mass of the

lepton-Emiss

T system, mT =

q 2pℓ

TETmiss− 2pℓT. pmissT , is

larger than 30 GeV.

The invariant mass of the hadronic top decay products

(mhad

t ) is used as an additional discriminating variable.

In scenarios where the stop is lighter than the top, mhad

t

will tend to be lower than for background t¯t processes,

as illustrated in Fig. 1(a). Since there is an

ambigu-ity as to which b-jet arises from the hadronic top decay (and additional ambiguities at higher jet multiplicities), the hadronic decay products are tagged using the follow-ing algorithm: for every possible combination of light and

b-tagged jets in the event, the invariant masses mhad

W (of

two light jets, mjj), mlepW (assuming that the lepton and

ETmiss arise from the W → ℓν decay), mhadt and m

lep t

(the leptonic top mass) are calculated. A t¯t estimator

of Ptot = P (mhadW )P (m

lep

W)P (m

lep

t )P (mhadt ) is assigned to

this combination, where P (m) is related to the probability for reconstructing a particle of mass m, assuming a Gaus-sian probability density function with mean values taken

from Ref. [46] and widths from MC simulation. The

com-bination which maximises Ptot is used to assign one b-jet

and two light flavour jets (one b-jet, the lepton and Emiss

T )

as arising from the hadronic (leptonic) decay of the top quark.

Events are then required to have mhad

t < ˆµ−0.5ˆσ, where

ˆ

µ and ˆσ are the mean and width respectively of a Gaussian

fit to the mhad

t distribution in a 40 GeV window around

the top mass. This approach is taken to reduce some of the systematic uncertainties affecting the shape of this

dis-tribution, as detailed in Section6.

In the 2-lepton channel, the following requirements are imposed to ensure that the event contains the required

number of objects consistent with the t¯t → W bW¯b →

ℓνbℓ¯ν¯b decay. Exactly two oppositely-charged leptons are

required to pass the selection described in Section4. For

same-flavour pairs, the highest pT lepton is required to

have pT> 25 GeV (20 GeV) for electrons (muons). In the

case of different-flavour pairs, either the electron must have

pT> 25 GeV or the muon pT> 20 GeV. At least two jets

are required in the event, of which the two with highest pT

are assumed to originate from the t¯t process. At least one

of these two jets is required to be b-tagged. The event is

required to fulfil Emiss

T > 40 GeV and the invariant mass

of the two leptons (mℓℓ) must satisfy 30 < mℓℓ< 81 GeV

to increase the discrimination against the background, as

illustrated in Fig.1(c).

In order to distinguish between stop and top pair

pro-duction the mass scale subsystem variable√s(sub)min [47] is

employed. Conceptually, the variable is constructed by dividing an event’s topology into a subsystem comprising both the visible and invisible particles originating from the hard-scattering process of interest and a set of other vis-ible particles labelled as coming from other, “upstream”, processes such as the underlying event or ISR. With these definitions, the minimum invariant mass compatible with the subsystem is:

√ s(sub)min = ( q m2 (sub)+ pT2(sub)+ q (mmiss)2+ Emiss T 2 2 −pT(sub)+ pmissT 2 1 2 , (1)

where m(sub) and pT(sub) are the invariant mass and the

transverse momentum of the visible subsystem particles.

The variable mmissis the scalar sum of the invisible

parti-cle masses in the event. The final term in Eq. 1is a

two-dimensional vector sum representing the boost correction in the transverse plane caused by upstream processes. In

this analysis √s(sub)min is calculated making the hypothesis

that each event arises from t¯t production, with the invisible

subsystem comprising one or two neutrinos, and therefore

mmiss = 0 in Eq. 1. With this assumption, the

recon-structed √s(sub)min distribution for t¯t background events is

expected to peak at around mt¯t = 2mt ≃ 345 GeV. On

the other hand, stop pair production will peak at lower values if the mass difference between the stop and the neu-3

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tralino is less than the top mass, as illustrated in Figs.1(b)

and1(d). Signal events are therefore selected by imposing

an upper limit on√s(sub)min .

In the 1-lepton channel, the visible subsystem comprises the single lepton, two light flavour jets and two b-jets. In events where combinatorial ambiguities arise, the subsys-tem objects are chosen which give the highest estimator in the algorithm described above. In the 2-lepton chan-nel, the two leptons and the two leading jets are used.

In both channels, the upper limit on √s(sub)min has been

chosen to maximise the expected signal efficiency with re-spect to background rejection, across a range of scenarios

described in Section 1. In the 1-lepton channel, the

op-timal requirement is √s(sub)min < 250 GeV, defining a

sig-nal region referred to hereafter as 1LSR. In the 2-lepton channel two signal regions are defined, the first requiring √

s(sub)min < 225 GeV (2LSR1). The invariant mass of the

two leptons and two jets (mℓℓjj) was also found be a

use-ful discriminating variable. Imposing mℓℓjj < 140 GeV

in combination with√s(sub)min < 235 GeV was found to give

the optimal performance and defines a second signal region (2LSR2).

6. Background Estimation

The dominant SM background process in the 1-lepton

(2-lepton) channel arises from single-lepton (dilepton) t¯t

decays, comprising 60% (80%) of the total background. The second most significant background in the 1-lepton

(2-lepton) channel arises from W (Z/γ∗) production in

association with jets from heavy flavour quarks. For both channels, similar methods are used to estimate these back-grounds. For each channel and background process a con-trol region is defined that is rich in the background of inter-est. The region is kinematically similar to the signal region but distinct from it, such that the signal and control re-gions have no events in common. For a control region

con-taining Nobs

CR observed events (corrected for the

contamina-tion from other backgrounds), the number of events in the

signal region is calculated as NSR = NCRobs× (NSRMC/NCRMC),

where NMC

SR and NCRMC are the MC-based estimates in the

signal and control regions respectively. The advantage of this method is that many systematic uncertainties par-tially cancel.

In the 1-lepton channel, the t¯t background is

deter-mined with a control region defined identically to the

sig-nal region, except that ˆµ − 0.5ˆσ < mhad

t < ˆµ + 0.5ˆσ and

s(sub)

min < 320 GeV, corresponding to a t¯t purity of 93%.

The definition of a control region using these fitted pa-rameters reduces the systematic uncertainties related to the jet energy scale and resolution. A high-purity W +b-jets control region is more difficult to define due to the

kinematic similarity with t¯t events, which have a higher

fiducial cross section. A control region can, however, be defined with 38% purity for W +b-jets events by

requir-ing mhad

t > 250 GeV and that the invariant mass of the

two b-jets is less than 50 GeV. As the t¯t contamination in

this region is still relatively high (60%), the W +b-jets and

t¯t contributions are determined by scaling their

contribu-tions simultaneously such that the total number of events matches the data in both control regions.

In the 2-lepton channel, the t¯t background (including

dileptonic W t decays) is determined using a control region

identical to the signal region except that mℓℓ > 101 GeV

and√s(sub)min < 325 GeV, with 94% purity of t¯t events. The

Z+jets background, with Z decaying to any of the three lepton flavours, is determined in a region requiring two

same-flavour leptons, 81 < mℓℓ< 101 GeV and√s(sub)min <

225 GeV, with a Z purity of 90%.

The contribution to the background from events where a jet is misidentified as a lepton, or where a lepton from a b- or c-hadron decay is selected (referred to as “fake” lepton background), is estimated using a data-driven

tech-nique in both channels [39, 48]. The probability of such

a misidentification is estimated by relaxing the electron and muon identification criteria to obtain control samples dominated by multi-jet production. In the 1-lepton chan-nel, the main contribution is from multi-jet events. In the 2-lepton channel, the dominant contribution is from processes containing one real and one fake lepton, such as

W +jet or single-lepton t¯t decays. The contribution from

events containing two fake leptons was found to be negli-gible.

Other less significant processes in the 1-lepton channel

include Z/γ∗+jets and single top quark production.

Di-boson and t¯t + X (X = W, Z, W W, b¯b) production give a

minor contribution to both channels. The contribution to the total background from these processes (referred to as

“Others” in the following and in Fig. 1) is 2.5% (2%) in

the 1-lepton (2-lepton) channel, and is taken directly from the MC predictions.

7. Systematic Uncertainties

The effect of the jet energy scale (JES) uncertainty on

the final event yield is calculated by shifting the pT of all

jets up and down by pT and η dependent factors, which

are 5–3% for jets with pT of 20–60 GeV. Repeating the

analysis with these pTshifts applied to the MC simulation

leads to variations on the final background estimate of 6– 10% depending on the signal region. The uncertainty due to the jet energy resolution (JER) is calculated by

smear-ing the pT of each jet by factors depending on the jet pT

and η. The smearing on a single jet is typically around 10%, and results in an overall uncertainty of 1–10%. Sys-tematic uncertainties in the lepton identification efficiency

amount to 1%. The uncertainty on the Emiss

T due to the

energy scale of the clusters in the calorimeter not associ-ated with jets and electrons is evaluassoci-ated using the method

described in Ref. [49], extended to include pile-up

uncer-tainties. The effect is up to 9% on the total background estimate depending on the signal region. The uncertainty

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0 50 100 150 200 250 300 350 400 450 500 Events / 10 GeV 1 10 2 10 3 10 4 10 5 10 6 10 2 bjets ≥ 1-lepton, Data 2011 SM Total Top W Others Multi-jet )=(170,140,70) GeV 1 0 χ∼ , 1 ± χ∼ , 1 t ~ ( )=(180,140,20) GeV 1 0 χ∼ , 1 ± χ∼ , 1 t ~ ( = 7 TeV s , -1 L dt = 4.7 fb

ATLAS [GeV] had t m 0 50 100 150 200 250 300 350 400 450 500 Data / SM 0 0.5 1 1.5 2 > (a) 0 100 200 300 400 500 600 700 800 900 1000 Events / 25 GeV 1 10 2 10 3 10 4 10 5 10 1-lepton, requirement (sub) min s 1LSR before Data 2011 SM Total Top W Others Multi-jet )=(170,140,70) GeV 1 0 χ∼ , 1 ± χ∼ , 1 t ~ ( )=(180,140,20) GeV 1 0 χ∼ , 1 ± χ∼ , 1 t ~ ( = 7 TeV s , -1 L dt = 4.7 fb

ATLAS [GeV] (sub) min s 0 100 200 300 400 500 600 700 800 900 1000 Data / SM 0 0.5 1 1.5 2 > (b) 40 60 80 100 120 140 160 180 200 220 Events / 5 GeV 1 10 2 10 3 10 4 10 5 10 2-lepton Data 2011 SM Total Top Z + Drell Yan Fakes Others ) = (170,140,70) GeV 0 1 χ∼ , ± 1 χ∼ , 1 t ~ ( ) = (180,140,20) GeV 0 1 χ∼ , ± 1 χ∼ , 1 t ~ ( ATLAS = 7 TeV s , -1 L dt = 4.7 fb

-1, s = 7 TeV L dt = 4.7 fb

[GeV] ll m 40 60 80 100 120 140 160 180 200 220 Data / SM 0 0.5 1 1.5 2 > (c) 0 100 200 300 400 500 600 700 800 900 1000 Events / 25 GeV 1 10 2 10 3 10 4 10 5 10 < 81 GeV ll 2-lepton, 30 < m Data 2011 SM Total Top Z + Drell Yan Fakes Others ) = (170,140,70) GeV 0 1 χ∼ , ± 1 χ∼ , 1 t ~ ( ) = (180,140,20) GeV 0 1 χ∼ , ± 1 χ∼ , 1 t ~ ( ATLAS = 7 TeV s , -1 L dt = 4.7 fb

-1, s = 7 TeV L dt = 4.7 fb

[GeV] (sub) min s 0 100 200 300 400 500 600 700 800 900 1000 Data / SM 0 0.5 1 1.5 2 > (d)

Figure 1: The 1-lepton channel mhadt distribution after all requirements except those on mhadt and

s(sub)min (a), and the√s(sub)min distribution

after all requirements except that on√s(sub)min (b). For the 2-lepton channel, the mℓℓdistribution is shown after all requirements except those

on mℓℓ and√s(sub)min (c), and the√s(sub)min distribution, before the requirements on√s(sub)min itself (d). The last bin in each histogram contains

the integral of all events with values greater than the upper axis bound. The hatched bands display the total uncertainties on the background expectation and the dashed lines show the expected distributions for two signal models. The bottom panels show the ratio of data to the expected background (points) and the total uncertainty on the background (hatched area).

due to b-tagging is evaluated by varying the b-tagging ef-ficiency and mis-tag rates within the uncertainties of the

measured values [50–52], giving an effect of 1% in all

sig-nal regions. The uncertainty associated with pile-up re-weighting is evaluated by varying the number of interac-tions per bunch-crossing by 10%. The overall effect on the predicted background yield is at most 3%.

Uncertainties related to the overall normalisation of the top background are reduced compared to estimates based purely on MC simulation by employing the method

de-scribed in Sec. 6. Residual uncertainties related to the

shape of the predicted kinematic distributions are de-scribed in the following. Theoretical uncertainties on the

t¯t background due to the choice of generator are

evalu-ated by comparing event yields from MC@NLO to those from

POWHEGwith the same parton shower model (HERWIG). The

parton shower uncertainties are then calculated by com-paring samples generated with the HERWIG and PYTHIA parton shower models, with the same generator (POWHEG). The uncertainty due to ISR/FSR is assessed using AcerMC samples with variations of PYTHIA parameters related to

the ISR branching phase-space and the FSR low-pT

cut-off. These variations are chosen to produce jet activity in

t¯t events that is consistent with the data [53, 54]. The

total uncertainty on the t¯t estimate due to these effects

amounts to 10–15%. Uncertainties due to the PDF choice 5

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Number of events Process 1LSR 2LSR1 2LSR2 Top 24 ± 3 ± 5 89 ± 6 ± 10 36 ± 2 ± 5 W +jets 6 ± 1 ± 2 — — Z+jets 0.5 ± 0.3 ± 0.3 11 ± 4 ± 3 3 ± 1 ± 1 Fake leptons 7 ± 1 ± 2 12 ± 5 ± 11 6 ± 4 ± 4 Others 0.3 ± 0.1 ± 0.1 2.7 ± 0.9 ± 0.7 0.9 ± 0.2 ± 0.5 Total SM 38 ± 3 ± 7 115 ± 8 ± 15 46 ± 4 ± 7 Data 50 123 47 m˜t1= 170 GeV, mχ˜ 0 1 = 70 GeV 26 ± 2 ± 6 57 ± 3 ± 6 36 ± 2 ± 4 m˜t1= 180 GeV, mχ˜ 0 1 = 20 GeV 20 ± 2 ± 4 41 ± 3 ± 5 27 ± 2 ± 3 95% CL upper limits σvis (expected) [fb] 4.2 9.3 4.6 σvis (observed) [fb] 6.1 11 5.2

Table 1: Predicted and observed number of events in all signal regions together with their statistical and systematic uncertainties. No values are shown for the W +jets contributions in the 2-lepton signal regions as these are included in the fake contributions. The expected number of events for two signal scenarios, both with a chargino mass of 140 GeV, are also shown. The observed and expected upper limits at 95%

confidence level on σvis= σ × A × ǫ are also given.

and errors are found to be negligible.

In the 1-lepton channel, the theoretical uncertainty in the W estimate due to variations of the factorisation, renormalisation and matching scales is found to be 15%.

Similar uncertainties on the Z/γ∗

contribution in the 2-lepton channel are 9% (2%) in 2LSR1 (2LSR2).

Uncertainties on the data-driven background from fake leptons arise from the lepton fake rate determination and from the definition of the fake-enriched control regions. The effect is between 45–84% of the fake contribution.

Theoretical uncertainties on the stop pair production cross section are taken from an envelope of predictions which use different PDF sets and factorisation and

renor-malisation scales, as described in Ref. [55]. Signal

uncer-tainties on JES (10–30%), JER (1–30%) and b-tagging (5– 10%) vary depending on the sparticle masses and the signal channel considered. They are treated as fully correlated with their respective background uncertainties. Finally, the luminosity uncertainty is 3.9%.

8. Results and Interpretation

Table 1 shows the observed number of events in data

and the SM predictions for the signal regions of the 1-and 2-lepton channels. In all SRs, the data are in good agreement with the SM expectations.

The results are translated into 95% confidence-level (CL) upper limits on contributions from new physics using

the CLsprescription [56] with a profile log-likelihood ratio

as a test statistic [57], where the parameter to describe the

non-SM signal strength is constrained to be non-negative

in the fit. As shown in Table 1, the three signal regions

are used to set limits on the visible cross section of the

new physics models, σvis= σ × A × ǫ, where σ is the total

production cross section for any non-SM signal, A is the acceptance defined by the fraction of events passing the

geometric and kinematic selections at particle level, and ǫ is the detector reconstruction, identification and trigger efficiency. Results are interpreted in the MSSM scenarios

described in Section1. In order to maximise the

sensitiv-ity of the analysis, results from the 1- and 2-lepton chan-nels are combined using the following method: for each signal point, the 2-lepton signal region (2LSR1 or 2LSR2)

which yields the lowest expected CLsvalue is chosen. This

region is then statistically combined with the 1LSR by multiplying the respective likelihood functions. Correlated systematic uncertainties are treated as common between the two channels, and a common signal strength param-eter µ is applied. The effect of signal contamination in the control regions (typically 5–10% depending on the sig-nal point) is also considered. In the gaugino universality

scenario, shown in Fig. 2(a), stop masses between 120–

167 GeV are excluded for mχ˜0

1 = 55 GeV. The sensitivity

of the search is also evaluated for a stop mass of 180 GeV in

the chargino–neutralino mass plane, as shown in Fig.2(b).

In such a scenario, where the stop-top mass difference is

small, a region around mχ˜0

1 = 70 GeV, mχ˜

±

1 = 140 GeV is

still excluded. The scenario with mχ˜±

1 = 106 GeV is shown

in Fig.2(c), where stop masses are excluded between 123–

167 GeV for mχ˜0

1 = 55 GeV. Neutralino masses of 70 GeV

are excluded for 125 < m˜t1< 155 GeV.

9. Conclusions

A search has been performed for top squarks with masses near to, or less than, the top quark mass. Good agreement is observed between data and the SM predic-tions in all channels. The results allow limits to be set

on the stop mass, assuming that ˜t1 → ˜χ

±

1b is the only

allowed decay mode, followed by ˜χ±1 → W(∗)χ˜01. For

sce-narios in which mχ˜±1 ≃ 2 × mχ˜

0

1, stop masses between

120–167 GeV are excluded for mχ˜0

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[GeV] 1 t ~ m 120 140 160 180 200 220 [GeV] 0χ∼1 m 55 60 65 70 75 80 85 90 0 1 χ∼ =2*m ± 1 χ∼ , m ± 1 χ∼ b+ → 1 t ~ production, 1 t ~ -1 t ~ =7 TeV s , -1 L dt = 4.7 fb

Leptons + b-jets combined ATLAS forbidden ± 1 χ∼ b+ → 1 t ~ ) theory SUSY σ 1 ± Observed limit ( ) exp σ 1 ± Expected limit ( All limits at 95% CL (a) [GeV] ± 1 χ∼ m 90 100 110 120 130 140 150 160 170 180 [GeV] 0χ∼1 m 0 20 40 60 80 100 120 140 160 180 =180 GeV 1 t ~ , m ± 1 χ∼ b+ → 1 t ~ production, 1 t ~ -1 t ~ >103.5 GeV±χ∼1 L E P e x c lu s io n : m =7 TeV s , -1 L dt = 4.7 fb

Leptons + b-jets combined ATLAS 0 1 χ∼ < m ± 1 χ ∼ m ) theory SUSY σ 1 ± Observed limit ( ) exp σ 1 ± Expected limit ( All limits at 95% CL (b) [GeV] 1 t ~ m 120 140 160 180 200 220 [GeV] 0χ∼1 m 0 20 40 60 80 100 120 =106 GeV ± 1 χ∼ , m ± 1 χ∼ b+ → 1 t ~ production, 1 t ~ -1 t ~ =7 TeV s , -1 L dt = 4.7 fb

Leptons + b-jets combined ATLAS ) theory SUSY σ 1 ± Observed limit ( ) exp σ 1 ± Expected limit ( CDF Run II

ATLAS light stop dilepton All limits at 95% CL

(c)

Figure 2: Exclusion limits at 95% CL for the scenarios described

in the text. The dashed (solid) lines show the expected (observed) limits, including all uncertainties except for the theoretical signal cross section uncertainty (PDF and scale). The bands around the expected limits show the ±1σ results. The lines around the observed limits represent the results obtained when moving the nominal signal cross section up or down by the ±1σ theoretical uncertainty. In (c),

results are compared to previous limits from the Tevatron [16], where

the lowest neutralino mass considered was 44 GeV (dotted line), and

from ATLAS [17].

stop mass of 180 GeV, a region around mχ˜0

1 = 70 GeV,

˜±1 = 140 GeV is excluded. In the scenario where

mχ˜±

1 = 106 GeV, neutralino masses of 70 GeV are

ex-cluded for 125 < m˜t1 < 155 GeV, significantly extending

previous limits in such scenarios.

10. Acknowledgements

We thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently.

We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONI-CYT, Chile; CAS, MOST and NSFC, China; COLCIEN-CIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF, DNSRC and Lundbeck Founda-tion, Denmark; EPLANET and ERC, European Union; IN2P3-CNRS, CEA-DSM/IRFU, France; GNAS, Georgia; BMBF, DFG, HGF, MPG and AvH Foundation, Ger-many; GSRT, Greece; ISF, MINERVA, GIF, DIP and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; FOM and NWO, Netherlands; RCN, Norway; MNiSW, Poland; GRICES and FCT, Por-tugal; MERYS (MECTS), Romania; MES of Russia and ROSATOM, Russian Federation; JINR; MSTD, Serbia; MSSR, Slovakia; ARRS and MVZT, Slovenia; DST/NRF, South Africa; MICINN, Spain; SRC and Wallenberg Foundation, Sweden; SER, SNSF and Cantons of Bern and Geneva, Switzerland; NSC, Taiwan; TAEK, Turkey; STFC, the Royal Society and Leverhulme Trust, United Kingdom; DOE and NSF, United States of America.

The crucial computing support from all WLCG part-ners is acknowledged gratefully, in particular from CERN and the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (UK) and BNL (USA) and in the Tier-2 facilities worldwide.

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The ATLAS Collaboration

G. Aad48, T. Abajyan21, B. Abbott111, J. Abdallah12, S. Abdel Khalek115, A.A. Abdelalim49, O. Abdinov11,

R. Aben105, B. Abi112, M. Abolins88, O.S. AbouZeid158, H. Abramowicz153, H. Abreu136, E. Acerbi89a,89b,

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T. Adye129, S. Aefsky23, J.A. Aguilar-Saavedra124b,a, M. Agustoni17, M. Aharrouche81, S.P. Ahlen22, F. Ahles48,

A. Ahmad148, M. Ahsan41, G. Aielli133a,133b, T. Akdogan19a, T.P.A. ˚Akesson79, G. Akimoto155, A.V. Akimov94,

M.S. Alam2, M.A. Alam76, J. Albert169, S. Albrand55, M. Aleksa30, I.N. Aleksandrov64, F. Alessandria89a, C. Alexa26a,

G. Alexander153, G. Alexandre49, T. Alexopoulos10, M. Alhroob164a,164c, M. Aliev16, G. Alimonti89a, J. Alison120,

B.M.M. Allbrooke18, P.P. Allport73, S.E. Allwood-Spiers53, J. Almond82, A. Aloisio102a,102b, R. Alon172, A. Alonso79,

F. Alonso70, B. Alvarez Gonzalez88, M.G. Alviggi102a,102b, K. Amako65, C. Amelung23, V.V. Ammosov128,∗,

S.P. Amor Dos Santos124a, A. Amorim124a,b, N. Amram153, C. Anastopoulos30, L.S. Ancu17, N. Andari115,

T. Andeen35, C.F. Anders58b, G. Anders58a, K.J. Anderson31, A. Andreazza89a,89b, V. Andrei58a, M-L. Andrieux55,

X.S. Anduaga70, P. Anger44, A. Angerami35, F. Anghinolfi30, A. Anisenkov107, N. Anjos124a, A. Annovi47,

A. Antonaki9, M. Antonelli47, A. Antonov96, J. Antos144b, F. Anulli132a, M. Aoki101, S. Aoun83, L. Aperio Bella5,

R. Apolle118,c, G. Arabidze88, I. Aracena143, Y. Arai65, A.T.H. Arce45, S. Arfaoui148, J-F. Arguin15, E. Arik19a,∗,

M. Arik19a, A.J. Armbruster87, O. Arnaez81, V. Arnal80, C. Arnault115, A. Artamonov95, G. Artoni132a,132b,

D. Arutinov21, S. Asai155, R. Asfandiyarov173, S. Ask28, B. ˚Asman146a,146b, L. Asquith6, K. Assamagan25,d,

A. Astbury169, M. Atkinson165, B. Aubert5, E. Auge115, K. Augsten127, M. Aurousseau145a, G. Avolio163,

R. Avramidou10, D. Axen168, G. Azuelos93,e, Y. Azuma155, M.A. Baak30, G. Baccaglioni89a, C. Bacci134a,134b,

A.M. Bach15, H. Bachacou136, K. Bachas30, M. Backes49, M. Backhaus21, E. Badescu26a, P. Bagnaia132a,132b,

S. Bahinipati3, Y. Bai33a, D.C. Bailey158, T. Bain158, J.T. Baines129, O.K. Baker176, M.D. Baker25, S. Baker77,

E. Banas39, P. Banerjee93, Sw. Banerjee173, D. Banfi30, A. Bangert150, V. Bansal169, H.S. Bansil18, L. Barak172,

S.P. Baranov94, A. Barbaro Galtieri15, T. Barber48, E.L. Barberio86, D. Barberis50a,50b, M. Barbero21, D.Y. Bardin64,

T. Barillari99, M. Barisonzi175, T. Barklow143, N. Barlow28, B.M. Barnett129, R.M. Barnett15, A. Baroncelli134a,

G. Barone49, A.J. Barr118, F. Barreiro80, J. Barreiro Guimar˜aes da Costa57, P. Barrillon115, R. Bartoldus143,

A.E. Barton71, V. Bartsch149, A. Basye165, R.L. Bates53, L. Batkova144a, J.R. Batley28, A. Battaglia17, M. Battistin30,

F. Bauer136, H.S. Bawa143,f, S. Beale98, T. Beau78, P.H. Beauchemin161, R. Beccherle50a, P. Bechtle21, H.P. Beck17,

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K. Bendtz146a,146b, N. Benekos165, Y. Benhammou153, E. Benhar Noccioli49, J.A. Benitez Garcia159b, D.P. Benjamin45,

M. Benoit115, J.R. Bensinger23, K. Benslama130, S. Bentvelsen105, D. Berge30, E. Bergeaas Kuutmann42, N. Berger5,

F. Berghaus169, E. Berglund105, J. Beringer15, P. Bernat77, R. Bernhard48, C. Bernius25, T. Berry76, C. Bertella83,

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K. Brendlinger120, R. Brenner166, S. Bressler172, D. Britton53, F.M. Brochu28, I. Brock21, R. Brock88, F. Broggi89a,

C. Bromberg88, J. Bronner99, G. Brooijmans35, T. Brooks76, W.K. Brooks32b, G. Brown82, H. Brown8,

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T. Buran117, H. Burckhart30, S. Burdin73, T. Burgess14, S. Burke129, E. Busato34, P. Bussey53, C.P. Buszello166,

B. Butler143, J.M. Butler22, C.M. Buttar53, J.M. Butterworth77, W. Buttinger28, M. Byszewski30,

S. Cabrera Urb´an167, D. Caforio20a,20b, O. Cakir4a, P. Calafiura15, G. Calderini78, P. Calfayan98, R. Calkins106,

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L. Carminati89a,89b, B. Caron85, S. Caron104, E. Carquin32b, G.D. Carrillo-Montoya173, A.A. Carter75, J.R. Carter28,

J. Carvalho124a,h, D. Casadei108, M.P. Casado12, M. Cascella122a,122b, C. Caso50a,50b,∗,

A.M. Castaneda Hernandez173,i, E. Castaneda-Miranda173, V. Castillo Gimenez167, N.F. Castro124a, G. Cataldi72a,

P. Catastini57, A. Catinaccio30, J.R. Catmore30, A. Cattai30, G. Cattani133a,133b, S. Caughron88, V. Cavaliere165,

P. Cavalleri78, D. Cavalli89a, M. Cavalli-Sforza12, V. Cavasinni122a,122b, F. Ceradini134a,134b, A.S. Cerqueira24b,

A. Cerri30, L. Cerrito75, F. Cerutti47, S.A. Cetin19b, A. Chafaq135a, D. Chakraborty106, I. Chalupkova126, K. Chan3,

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C.A. Chavez Barajas30, S. Cheatham85, S. Chekanov6, S.V. Chekulaev159a, G.A. Chelkov64, M.A. Chelstowska104,

C. Chen63, H. Chen25, S. Chen33c, X. Chen173, Y. Chen35, A. Cheplakov64, R. Cherkaoui El Moursli135e,

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A. Chilingarov71, G. Chiodini72a, A.S. Chisholm18, R.T. Chislett77, A. Chitan26a, M.V. Chizhov64, G. Choudalakis31,

S. Chouridou137, I.A. Christidi77, A. Christov48, D. Chromek-Burckhart30, M.L. Chu151, J. Chudoba125,

G. Ciapetti132a,132b, A.K. Ciftci4a, R. Ciftci4a, D. Cinca34, V. Cindro74, C. Ciocca20a,20b, A. Ciocio15, M. Cirilli87,

P. Cirkovic13b, Z.H. Citron172, M. Citterio89a, M. Ciubancan26a, A. Clark49, P.J. Clark46, R.N. Clarke15,

W. Cleland123, J.C. Clemens83, B. Clement55, C. Clement146a,146b, Y. Coadou83, M. Cobal164a,164c, A. Coccaro138,

J. Cochran63, J.G. Cogan143, J. Coggeshall165, E. Cogneras178, J. Colas5, S. Cole106, A.P. Colijn105, N.J. Collins18,

C. Collins-Tooth53, J. Collot55, T. Colombo119a,119b, G. Colon84, P. Conde Mui˜no124a, E. Coniavitis118, M.C. Conidi12,

S.M. Consonni89a,89b, V. Consorti48, S. Constantinescu26a, C. Conta119a,119b, G. Conti57, F. Conventi102a,j,

M. Cooke15, B.D. Cooper77, A.M. Cooper-Sarkar118, K. Copic15, T. Cornelissen175, M. Corradi20a, F. Corriveau85,k,

A. Cortes-Gonzalez165, G. Cortiana99, G. Costa89a, M.J. Costa167, D. Costanzo139, D. Cˆot´e30, L. Courneyea169,

G. Cowan76, C. Cowden28, B.E. Cox82, K. Cranmer108, F. Crescioli122a,122b, M. Cristinziani21, G. Crosetti37a,37b,

S. Cr´ep´e-Renaudin55, C.-M. Cuciuc26a, C. Cuenca Almenar176, T. Cuhadar Donszelmann139, M. Curatolo47,

C.J. Curtis18, C. Cuthbert150, P. Cwetanski60, H. Czirr141, P. Czodrowski44, Z. Czyczula176, S. D’Auria53,

M. D’Onofrio73, A. D’Orazio132a,132b, M.J. Da Cunha Sargedas De Sousa124a, C. Da Via82, W. Dabrowski38,

A. Dafinca118, T. Dai87, C. Dallapiccola84, M. Dam36, M. Dameri50a,50b, D.S. Damiani137, H.O. Danielsson30,

V. Dao49, G. Darbo50a, G.L. Darlea26b, J.A. Dassoulas42, W. Davey21, T. Davidek126, N. Davidson86, R. Davidson71,

E. Davies118,c, M. Davies93, O. Davignon78, A.R. Davison77, Y. Davygora58a, E. Dawe142, I. Dawson139,

R.K. Daya-Ishmukhametova23, K. De8, R. de Asmundis102a, S. De Castro20a,20b, S. De Cecco78, J. de Graat98,

N. De Groot104, P. de Jong105, C. De La Taille115, H. De la Torre80, F. De Lorenzi63, L. de Mora71, L. De Nooij105,

D. De Pedis132a, A. De Salvo132a, U. De Sanctis164a,164c, A. De Santo149, J.B. De Vivie De Regie115,

G. De Zorzi132a,132b, W.J. Dearnaley71, R. Debbe25, C. Debenedetti46, B. Dechenaux55, D.V. Dedovich64,

J. Degenhardt120, C. Del Papa164a,164c, J. Del Peso80, T. Del Prete122a,122b, T. Delemontex55, M. Deliyergiyev74,

A. Dell’Acqua30, L. Dell’Asta22, M. Della Pietra102a,j, D. della Volpe102a,102b, M. Delmastro5, P.A. Delsart55,

C. Deluca105, S. Demers176, M. Demichev64, B. Demirkoz12,l, J. Deng163, S.P. Denisov128, D. Derendarz39,

J.E. Derkaoui135d, F. Derue78, P. Dervan73, K. Desch21, E. Devetak148, P.O. Deviveiros105, A. Dewhurst129,

B. DeWilde148, S. Dhaliwal158, R. Dhullipudi25 ,m, A. Di Ciaccio133a,133b, L. Di Ciaccio5, A. Di Girolamo30,

B. Di Girolamo30, S. Di Luise134a,134b, A. Di Mattia173, B. Di Micco30, R. Di Nardo47, A. Di Simone133a,133b,

R. Di Sipio20a,20b, M.A. Diaz32a, E.B. Diehl87, J. Dietrich42, T.A. Dietzsch58a, S. Diglio86, K. Dindar Yagci40,

J. Dingfelder21, F. Dinut26a, C. Dionisi132a,132b, P. Dita26a, S. Dita26a, F. Dittus30, F. Djama83, T. Djobava51b,

M.A.B. do Vale24c, A. Do Valle Wemans124a,n, T.K.O. Doan5, M. Dobbs85, R. Dobinson30,∗, D. Dobos30,

E. Dobson30,o, J. Dodd35, C. Doglioni49, T. Doherty53, Y. Doi65,∗, J. Dolejsi126, I. Dolenc74, Z. Dolezal126,

B.A. Dolgoshein96,∗, T. Dohmae155, M. Donadelli24d, J. Donini34, J. Dopke30, A. Doria102a, A. Dos Anjos173,

A. Dotti122a,122b, M.T. Dova70, A.D. Doxiadis105, A.T. Doyle53, N. Dressnandt120, M. Dris10, J. Dubbert99, S. Dube15,

E. Duchovni172, G. Duckeck98, D. Duda175, A. Dudarev30, F. Dudziak63, M. D¨uhrssen30, I.P. Duerdoth82, L. Duflot115,

M-A. Dufour85, L. Duguid76, M. Dunford30, H. Duran Yildiz4a, R. Duxfield139, M. Dwuznik38, F. Dydak30,

M. D¨uren52, W.L. Ebenstein45, J. Ebke98, S. Eckweiler81, K. Edmonds81, W. Edson2, C.A. Edwards76,

N.C. Edwards53, W. Ehrenfeld42, T. Eifert143, G. Eigen14, K. Einsweiler15, E. Eisenhandler75, T. Ekelof166,

M. El Kacimi135c, M. Ellert166, S. Elles5, F. Ellinghaus81, K. Ellis75, N. Ellis30, J. Elmsheuser98, M. Elsing30,

D. Emeliyanov129, R. Engelmann148, A. Engl98, B. Epp61, J. Erdmann54, A. Ereditato17, D. Eriksson146a, J. Ernst2,

M. Ernst25, J. Ernwein136, D. Errede165, S. Errede165, E. Ertel81, M. Escalier115, H. Esch43, C. Escobar123,

X. Espinal Curull12, B. Esposito47, F. Etienne83, A.I. Etienvre136, E. Etzion153, D. Evangelakou54, H. Evans60,

L. Fabbri20a,20b, C. Fabre30, R.M. Fakhrutdinov128, S. Falciano132a, Y. Fang173, M. Fanti89a,89b, A. Farbin8,

A. Farilla134a, J. Farley148, T. Farooque158, S. Farrell163, S.M. Farrington170, P. Farthouat30, F. Fassi167,

P. Fassnacht30, D. Fassouliotis9, B. Fatholahzadeh158, A. Favareto89a,89b, L. Fayard115, S. Fazio37a,37b, R. Febbraro34,

(12)

E.J. Feng6, A.B. Fenyuk128, J. Ferencei144b, W. Fernando6, S. Ferrag53, J. Ferrando53, V. Ferrara42, A. Ferrari166,

P. Ferrari105, R. Ferrari119a, D.E. Ferreira de Lima53, A. Ferrer167, D. Ferrere49, C. Ferretti87, A. Ferretto Parodi50a,50b,

M. Fiascaris31, F. Fiedler81, A. Filipˇciˇc74, F. Filthaut104, M. Fincke-Keeler169, M.C.N. Fiolhais124a,h, L. Fiorini167,

A. Firan40, G. Fischer42, M.J. Fisher109, M. Flechl48, I. Fleck141, J. Fleckner81, P. Fleischmann174, S. Fleischmann175,

T. Flick175, A. Floderus79, L.R. Flores Castillo173, M.J. Flowerdew99, T. Fonseca Martin17, A. Formica136, A. Forti82,

D. Fortin159a, D. Fournier115, A.J. Fowler45, H. Fox71, P. Francavilla12, M. Franchini20a,20b, S. Franchino119a,119b,

D. Francis30, T. Frank172, S. Franz30, M. Fraternali119a,119b, S. Fratina120, S.T. French28, C. Friedrich42, F. Friedrich44,

R. Froeschl30, D. Froidevaux30, J.A. Frost28, C. Fukunaga156, E. Fullana Torregrosa30, B.G. Fulsom143, J. Fuster167,

C. Gabaldon30, O. Gabizon172, T. Gadfort25, S. Gadomski49, G. Gagliardi50a,50b, P. Gagnon60, C. Galea98,

B. Galhardo124a, E.J. Gallas118, V. Gallo17, B.J. Gallop129, P. Gallus125, K.K. Gan109, Y.S. Gao143,f, A. Gaponenko15,

F. Garberson176, M. Garcia-Sciveres15, C. Garc´ıa167, J.E. Garc´ıa Navarro167, R.W. Gardner31, N. Garelli30,

H. Garitaonandia105, V. Garonne30, C. Gatti47, G. Gaudio119a, B. Gaur141, L. Gauthier136, P. Gauzzi132a,132b,

I.L. Gavrilenko94, C. Gay168, G. Gaycken21, E.N. Gazis10, P. Ge33d, Z. Gecse168, C.N.P. Gee129, D.A.A. Geerts105,

Ch. Geich-Gimbel21, K. Gellerstedt146a,146b, C. Gemme50a, A. Gemmell53, M.H. Genest55, S. Gentile132a,132b,

M. George54, S. George76, P. Gerlach175, A. Gershon153, C. Geweniger58a, H. Ghazlane135b, N. Ghodbane34,

B. Giacobbe20a, S. Giagu132a,132b, V. Giakoumopoulou9, V. Giangiobbe12, F. Gianotti30, B. Gibbard25, A. Gibson158,

S.M. Gibson30, M. Gilchriese15, D. Gillberg29, A.R. Gillman129, D.M. Gingrich3,e, J. Ginzburg153, N. Giokaris9,

M.P. Giordani164c, R. Giordano102a,102b, F.M. Giorgi16, P. Giovannini99, P.F. Giraud136, D. Giugni89a, C. Giuliani48,

M. Giunta93, P. Giusti20a, B.K. Gjelsten117, L.K. Gladilin97, C. Glasman80, J. Glatzer48, A. Glazov42, K.W. Glitza175,

G.L. Glonti64, J.R. Goddard75, J. Godfrey142, J. Godlewski30, M. Goebel42, T. G¨opfert44, C. Goeringer81,

C. G¨ossling43, S. Goldfarb87, T. Golling176, A. Gomes124a,b, L.S. Gomez Fajardo42, R. Gon¸calo76,

J. Goncalves Pinto Firmino Da Costa42, L. Gonella21, S. Gonzalez173, S. Gonz´alez de la Hoz167, G. Gonzalez Parra12,

M.L. Gonzalez Silva27, S. Gonzalez-Sevilla49, J.J. Goodson148, L. Goossens30, P.A. Gorbounov95, H.A. Gordon25,

I. Gorelov103, G. Gorfine175, B. Gorini30, E. Gorini72a,72b, A. Goriˇsek74, E. Gornicki39, B. Gosdzik42, A.T. Goshaw6,

M. Gosselink105, M.I. Gostkin64, I. Gough Eschrich163, M. Gouighri135a, D. Goujdami135c, M.P. Goulette49,

A.G. Goussiou138, C. Goy5, S. Gozpinar23, I. Grabowska-Bold38, P. Grafstr¨om20a,20b, K-J. Grahn42, F. Grancagnolo72a,

S. Grancagnolo16, V. Grassi148, V. Gratchev121, N. Grau35, H.M. Gray30, J.A. Gray148, E. Graziani134a,

O.G. Grebenyuk121, T. Greenshaw73, Z.D. Greenwood25,m, K. Gregersen36, I.M. Gregor42, P. Grenier143, J. Griffiths8,

N. Grigalashvili64, A.A. Grillo137, S. Grinstein12, Ph. Gris34, Y.V. Grishkevich97, J.-F. Grivaz115, E. Gross172,

J. Grosse-Knetter54, J. Groth-Jensen172, K. Grybel141, D. Guest176, C. Guicheney34, S. Guindon54, U. Gul53,

H. Guler85,p, J. Gunther125, B. Guo158, J. Guo35, P. Gutierrez111, N. Guttman153, O. Gutzwiller173, C. Guyot136,

C. Gwenlan118, C.B. Gwilliam73, A. Haas143, S. Haas30, C. Haber15, H.K. Hadavand40, D.R. Hadley18, P. Haefner21,

F. Hahn30, S. Haider30, Z. Hajduk39, H. Hakobyan177, D. Hall118, J. Haller54, K. Hamacher175, P. Hamal113,

K. Hamano86, M. Hamer54, A. Hamilton145b,q, S. Hamilton161, L. Han33b, K. Hanagaki116, K. Hanawa160, M. Hance15,

C. Handel81, P. Hanke58a, J.R. Hansen36, J.B. Hansen36, J.D. Hansen36, P.H. Hansen36, P. Hansson143, K. Hara160,

G.A. Hare137, T. Harenberg175, S. Harkusha90, D. Harper87, R.D. Harrington46, O.M. Harris138, J. Hartert48,

F. Hartjes105, T. Haruyama65, A. Harvey56, S. Hasegawa101, Y. Hasegawa140, S. Hassani136, S. Haug17, M. Hauschild30,

R. Hauser88, M. Havranek21, C.M. Hawkes18, R.J. Hawkings30, A.D. Hawkins79, D. Hawkins163, T. Hayakawa66,

T. Hayashi160, D. Hayden76, C.P. Hays118, H.S. Hayward73, S.J. Haywood129, M. He33d, S.J. Head18, V. Hedberg79,

L. Heelan8, S. Heim88, B. Heinemann15, S. Heisterkamp36, L. Helary22, C. Heller98, M. Heller30, S. Hellman146a,146b,

D. Hellmich21, C. Helsens12, R.C.W. Henderson71, M. Henke58a, A. Henrichs54, A.M. Henriques Correia30,

S. Henrot-Versille115, C. Hensel54, T. Henß175, C.M. Hernandez8, Y. Hern´andez Jim´enez167, R. Herrberg16,

G. Herten48, R. Hertenberger98, L. Hervas30, G.G. Hesketh77, N.P. Hessey105, E. Hig´on-Rodriguez167, J.C. Hill28,

K.H. Hiller42, S. Hillert21, S.J. Hillier18, I. Hinchliffe15, E. Hines120, M. Hirose116, F. Hirsch43, D. Hirschbuehl175,

J. Hobbs148, N. Hod153, M.C. Hodgkinson139, P. Hodgson139, A. Hoecker30, M.R. Hoeferkamp103, J. Hoffman40,

D. Hoffmann83, M. Hohlfeld81, M. Holder141, S.O. Holmgren146a, T. Holy127, J.L. Holzbauer88, T.M. Hong120,

L. Hooft van Huysduynen108, S. Horner48, J-Y. Hostachy55, S. Hou151, A. Hoummada135a, J. Howard118, J. Howarth82,

I. Hristova16, J. Hrivnac115, T. Hryn’ova5, P.J. Hsu81, S.-C. Hsu15, D. Hu35, Z. Hubacek127, F. Hubaut83,

F. Huegging21, A. Huettmann42, T.B. Huffman118, E.W. Hughes35, G. Hughes71, M. Huhtinen30, M. Hurwitz15,

U. Husemann42, N. Huseynov64,r, J. Huston88, J. Huth57, G. Iacobucci49, G. Iakovidis10, M. Ibbotson82,

I. Ibragimov141, L. Iconomidou-Fayard115, J. Idarraga115, P. Iengo102a, O. Igonkina105, Y. Ikegami65, M. Ikeno65,

D. Iliadis154, N. Ilic158, T. Ince21, J. Inigo-Golfin30, P. Ioannou9, M. Iodice134a, K. Iordanidou9, V. Ippolito132a,132b,

A. Irles Quiles167, C. Isaksson166, M. Ishino67, M. Ishitsuka157, R. Ishmukhametov40, C. Issever118, S. Istin19a,

A.V. Ivashin128, W. Iwanski39, H. Iwasaki65, J.M. Izen41, V. Izzo102a, B. Jackson120, J.N. Jackson73, P. Jackson1,

M.R. Jaekel30, V. Jain60, K. Jakobs48, S. Jakobsen36, T. Jakoubek125, J. Jakubek127, D.K. Jana111, E. Jansen77,

H. Jansen30, A. Jantsch99, M. Janus48, R.C. Jared173, G. Jarlskog79, L. Jeanty57, I. Jen-La Plante31, D. Jennens86,

P. Jenni30, A.E. Loevschall-Jensen36, P. Jeˇz36, S. J´ez´equel5, M.K. Jha20a, H. Ji173, W. Ji81, J. Jia148, Y. Jiang33b,

Imagem

Figure 1: The 1-lepton channel m had t distribution after all requirements except those on m had t and √
Table 1: Predicted and observed number of events in all signal regions together with their statistical and systematic uncertainties
Figure 2: Exclusion limits at 95% CL for the scenarios described in the text. The dashed (solid) lines show the expected (observed) limits, including all uncertainties except for the theoretical signal cross section uncertainty (PDF and scale)

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