Eur. Phys. J. C (2017) 77:710 DOI 10.1140/epjc/s10052-017-5267-x

Regular Article - Experimental Physics

Search for new phenomena with the MT2 variable in theall-hadronic final state produced in proton–proton collisions at√s = 13TeV

CMS Collaboration∗

CERN, 1211 Geneva 23, Switzerland

Received: 12 May 2017 / Accepted: 26 September 2017© CERN for the benefit of the CMS collaboration 2017. This article is an open access publication

Abstract A search for new phenomena is performed usingevents with jets and significant transverse momentum imbal-ance, as inferred through the MT2 variable. The results arebased on a sample of proton–proton collisions collected in2016 at a center-of-mass energy of 13 TeV with the CMSdetector and corresponding to an integrated luminosity of35.9 fb−1. No excess event yield is observed above the pre-dicted standard model background, and the results are inter-preted as exclusion limits at 95% confidence level on themasses of predicted particles in a variety of simplified mod-els of R-parity conserving supersymmetry. Depending onthe details of the model, 95% confidence level lower limitson the gluino (light-flavor squark) masses are placed up to2025 (1550) GeV. Mass limits as high as 1070 (1175) GeVare set on the masses of top (bottom) squarks. Information isprovided to enable re-interpretation of these results, includ-ing model-independent limits on the number of non-standardmodel events for a set of simplified, inclusive search regions.

1 Introduction

We present results of a search for new phenomena in eventswith jets and significant transverse momentum imbalance inproton–proton collisions at

√s = 13 TeV. Such searches

were previously conducted by both the ATLAS [1–5] andCMS [6–9] Collaborations. Our search builds on the workpresented in Ref. [6], using improved methods to estimate thebackground from standard model (SM) processes and a dataset corresponding to an integrated luminosity of 35.9 fb−1 ofpp collisions collected during 2016 with the CMS detectorat the CERN LHC. Event counts in bins of the number ofjets (Nj), the number of b-tagged jets (Nb), the scalar sum ofthe transverse momenta pT of all selected jets (HT), and theMT2 variable [6,10] are compared against estimates of thebackground from SM processes derived from dedicated data

� e-mail: cms-publication-committee-chair@cern.ch

control samples. We observe no evidence for a significantexcess above the expected background event yield and inter-pret the results as exclusion limits at 95% confidence levelon the production of pairs of gluinos and squarks using sim-plified models of supersymmetry (SUSY) [11–18]. Model-independent limits on the number of non-SM events are alsoprovided for a simpler set of inclusive search regions.

2 The CMS detector

The central feature of the CMS apparatus is a superconduct-ing solenoid of 6 m internal diameter, providing a magneticfield of 3.8 T. Within the solenoid volume are a silicon pixeland strip tracker, a lead tungstate crystal electromagneticcalorimeter, and a brass and scintillator hadron calorimeter,each composed of a barrel and two endcap sections. For-ward calorimeters extend the pseudorapidity (η) coverageprovided by the barrel and endcap detectors. Muons are mea-sured in gas-ionization detectors embedded in the steel flux-return yoke outside the solenoid. The first level of the CMStrigger system, composed of custom hardware processors,uses information from the calorimeters and muon detectorsto select the most interesting events in a fixed time interval ofless than 4 μs. The high-level trigger processor farm furtherdecreases the event rate from around 100 kHz to less than1 kHz, before data storage. A more detailed description ofthe CMS detector and trigger system, together with a defini-tion of the coordinate system used and the relevant kinematicvariables, can be found in Refs. [19,20].

3 Event selection and Monte Carlo simulation

Events are processed using the particle-flow (PF) algo-rithm [21], which is designed to reconstruct and identifyall particles using the optimal combination of information

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Table 1 Summary ofreconstruction objects and eventpreselection. Here R is thedistance parameter of the anti-kTalgorithm. For veto leptons andtracks, the transverse mass MTis determined using the vetoobject and the �pmiss

T . Thevariable psum

T is a measure ofisolation and it denotes the sumof the transverse momenta of allthe PF candidates in a conearound the lepton or the track.The size of the cone, in units ofΔR ≡

√(Δφ)2 + (Δη)2 is

given in the table. Furtherdetails of the lepton selectionare described in Ref. [6]. The i thhighest-pT jet is denoted as ji

Trigger pmissT > 120 GeV and Hmiss

T > 120 GeV or

HT > 300 GeV and pmissT > 110 GeV or

HT > 900 GeV or jet pT > 450 GeV

Jet selection R = 0.4, pT > 30 GeV, |η| < 2.4

b tag selection pT > 20 GeV, |η| < 2.4

pmissT pmiss

T > 250 GeV for HT < 1000 GeV, else pmissT > 30 GeV

Δφmin = Δφ(pmiss

T , j1,2,3,4)

> 0.3

| �pmissT − �Hmiss

T |/pmissT < 0.5

MT2 MT2 > 200 GeV for HT < 1500 GeV, else MT2 > 400 GeV

Veto muon pT > 10 GeV, |η| < 2.4, psumT < 0.2 plep

T or

pT > 5 GeV, |η| < 2.4, MT < 100 GeV, psumT < 0.2 plep

T

Veto electron pT > 10 GeV, |η| < 2.4, psumT < 0.1 plep

T or

pT > 5 GeV, |η| < 2.4, MT < 100 GeV, psumT < 0.2 plep

T

Veto track pT > 10 GeV, |η| < 2.4, MT < 100 GeV,psumT < 0.1 ptrack

T

psumT cone Veto e or μ: ΔR = min(0.2, max(10 GeV/plep

T , 0.05))

Veto track: ΔR = 0.3

from the elements of the CMS detector. Physics objectsreconstructed with this algorithm are hereafter referred to asparticle-flow candidates. The physics objects and the eventpreselection are similar to those described in Ref. [6], and aresummarized in Table 1. We select events with at least one jet,and veto events with an isolated lepton (e or μ) or chargedPF candidate. The isolated charged PF candidate selection isdesigned to provide additional rejection against events withelectrons and muons, as well as to reject hadronic tau decays.Jets are formed by clustering PF candidates using the anti-kT

algorithm [22,23] and are corrected for contributions fromevent pileup [24] and the effects of non-uniform detectorresponse. Only jets passing the selection criteria in Table 1are used for counting and the determination of kinematic vari-ables. Jets consistent with originating from a heavy-flavorhadron are identified using the combined secondary vertextagging algorithm [25], with a working point chosen suchthat the efficiency to identify a b quark jet is in the range50–65% for jet pT between 20 and 400 GeV. The misidenti-fication rate is approximately 1% for light-flavor and gluonjets and 10% for charm jets. A more detailed discussion ofthe algorithm performance is given in Ref. [25].

The negative of the vector sum of the pT of all selectedjets is denoted by �Hmiss

T , while �pmissT is defined as the nega-

tive of the vector pT sum of all reconstructed PF candidates.The jet corrections are also used to correct �pmiss

T . Events withpossible contributions from beam-halo processes or anoma-lous noise in the calorimeter are rejected using dedicatedfilters [26,27]. For events with at least two jets, we start withthe pair having the largest dijet invariant mass and iterativelycluster all selected jets using a hemisphere algorithm thatminimizes the Lund distance measure [28,29] until two stable

pseudo-jets are obtained. The resulting pseudo-jets togetherwith the �pmiss

T are used to calculate the kinematic variableMT2 as:

MT2 = min�pmiss

TX(1)+ �pmiss

TX(2) = �pmiss

T

[max

(M (1)

T , M (2)T

)], (1)

where �pmissT

X(i) (i = 1,2) are trial vectors obtained by

decomposing �pmissT , and M (i)

T are the transverse massesobtained by pairing either of the trial vectors with one of thetwo pseudo-jets. The minimization is performed over all trialmomenta satisfying the �pmiss

T constraint. The backgroundfrom multijet events (discussed in Sect. 4) is characterizedby small values of MT2, while larger MT2 values are obtainedin processes with significant, genuine �pmiss

T .Collision events are selected using triggers with require-

ments on HT, pmissT , Hmiss

T , and jet pT. The combined trig-ger efficiency, as measured in a data sample of events withan isolated electron, is found to be > 98% across the fullkinematic range of the search. To suppress background frommultijet production, we require MT2 > 200 GeV in eventswith Nj ≥ 2 and HT < 1500 GeV. This MT2 threshold isincreased to 400 GeV for events with HT > 1500 GeV tomaintain multijet processes as a subdominant background inall search regions. To protect against jet mismeasurement, werequire the minimum difference in azimuthal angle betweenthe �pmiss

T vector and each of the leading four jets, Δφmin,to be greater than 0.3, and the magnitude of the differencebetween �pmiss

T and �HmissT to be less than half of pmiss

T . Forthe determination of Δφmin we consider jets with |η| < 4.7.If less than four such jets are found, all are considered in theΔφmin calculation.

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Events containing at least two jets are categorized by thevalues of Nj, Nb, and HT. Each such bin is referred to asa topological region. Signal regions are defined by furtherdividing topological regions into bins of MT2. Events withonly one jet are selected if the pT of the jet is at least 250 GeV,and are classified according to the pT of this jet and whetherthe event contains a b-tagged jet. The search regions are sum-marized in Tables 5, 6, 7 in Appendix A. We also define supersignal regions, covering a subset of the kinematic space ofthe full analysis with simpler inclusive selections. The supersignal regions can be used to obtain approximate interpreta-tions of our result, as discussed in Sect. 5, where these regionsare defined.

Monte Carlo (MC) simulations are used to design thesearch, to aid in the estimation of SM backgrounds, and toevaluate the sensitivity to gluino and squark pair produc-tion in simplified models of SUSY. The main backgroundsamples (Z+jets, W+jets, and tt+jets), as well as signal sam-ples of gluino and squark pair production, are generated atleading order (LO) precision with the MadGraph 5 gen-erator [30,31] interfaced with pythia 8.2 [32] for frag-mentation and parton showering. Up to four, three, or twoadditional partons are considered in the matrix element cal-culations for the generation of the V+jets (V = Z, W),tt+jets, and signal samples, respectively. Other backgroundprocesses are also considered: ttV(V = Z, W) samples aregenerated at LO precision with the MadGraph 5 gener-ator, with up to two additional partons in the matrix ele-ment calculations, while single top samples are generatedat next-to-leading order (NLO) precision with the Mad-Graph_aMC@NLO [30] or powheg [33,34] generators.Contributions from rarer processes such as diboson, triboson,and four top production, are found to be negligible. Standardmodel samples are simulated with a detailed Geant4 [35]based detector simulation and processed using the same chainof reconstruction programs as collision data, while the CMSfast simulation program [36] is used for the signal sam-ples. The most precise available cross section calculationsare used to normalize the simulated samples, correspondingmost often to NLO or next-to-NLO accuracy [30,33,34,37–40].

To improve on the MadGraph modeling of the multiplic-ity of additional jets from initial state radiation (ISR), Mad-Graph tt MC events are weighted based on the number ofISR jets (N ISR

j ) so as to make the jet multiplicity agree withdata. The same reweighting procedure is applied to SUSYMC events. The weighting factors are obtained from a con-trol region enriched in tt, obtained by selecting events withtwo leptons and exactly two b-tagged jets, and vary between0.92 for N ISR

j = 1 and 0.51 for N ISRj ≥ 6. We take one half

of the deviation from unity as the systematic uncertainty inthese reweighting factors, to cover for differences between ttand SUSY production.

[GeV]T2M200 400 600 800 1000 1200 1400 1600 1800

Eve

nts

/ Bin

1−10

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> 250 GeVTH

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> 250 GeVTH

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C

0

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1.5

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Fig. 1 Distributions of the MT2 variable in data and simulation for thesingle-lepton control region selection, after normalizing the simulationto data in the control region bins of HT, Nj, and Nb for events with nob-tagged jets (upper), and events with at least one b-tagged jet (lower).The hatched bands on the top panels show the MC statistical uncer-tainty, while the solid gray bands in the ratio plots show the systematicuncertainty in the MT2 shape

4 Backgrounds

The backgrounds in jets-plus-pmissT final states typically arise

from three categories of SM processes:

– “lost lepton (LL)”, i.e., events with a lepton from a Wdecay where the lepton is either out of acceptance, notreconstructed, not identified, or not isolated.This background originates mostly from W+jets and

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tt+jets events, with smaller contributions from rarer pro-cesses such as diboson or ttV(V = Z, W) production.

– “irreducible”, i.e., Z+jets events, where the Z bosondecays to neutrinos. This background is most similar topotential signals. It is a major background in nearly allsearch regions, its importance decreasing with increasingNb.

– “instrumental background”, i.e., mostly multijet eventswith no genuine pmiss

T . These events enter a search regiondue to either significant jet momentum mismeasure-ments, or sources of anomalous noise.

4.1 Estimation of the background from events with leptonicW boson decays

Control regions with exactly one lepton candidate areselected using the same triggers and preselections used for thesignal regions, with the exception of the lepton veto, whichis inverted. Selected events are binned according to the samecriteria as the search regions, and the background in eachsignal bin, NSR

LL , is obtained from the number of events in thecontrol region, NCR

1� , using transfer factors according to:

NSRLL

(HT, Nj, Nb, MT2

)

= NCR1�

(HT, Nj, Nb, MT2

)

×R0�/1�MC

(HT, Nj, Nb, MT2

)k (MT2) . (2)

The single-lepton control region typically has 1–2 timesas many events as the corresponding signal region. The fac-tor R0�/1�

MC

(HT, Nj, Nb, MT2

)accounts for lepton acceptance

and efficiency and the expected contribution from the decayof W bosons to hadrons through an intermediate τ lepton. Itis obtained from MC simulation, and corrected for measureddifferences in lepton efficiencies between data and simula-tion.

The factor k (MT2) accounts for the distribution, in bins ofMT2, of the estimated background in each topological region.It is obtained using both data and simulation as follows. Ineach topological region, the control region corresponding tothe highest MT2 bin is successively combined with the nexthighest bin until the expected SM yield in combined bins isat least 50 events. When two or more control region bins arecombined, the fraction of events expected to populate a par-ticular MT2 bin, k (MT2), is determined using the expectationfrom SM simulated samples, including all relevant processes.The modeling of MT2 is checked in data using single-leptoncontrol samples enriched in events originating from eitherW+jets or tt+jets, as shown in the upper and lower panels ofFig. 1, respectively. The predicted distributions in the com-parison are obtained by summing all control regions afternormalizing MC yields to data and distributing events amongMT2 bins according to the expectation from simulation, asis done for the estimate of the lost-lepton background. For

jN1 2 3 4 5 6 7 8 9 10

SF/

OF

R

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

DataStat. unc.Syst. unc.

(13 TeV)-135.9 fbCMS

[GeV]T2M200 400 600 800 1000 1200

Frac

tion

/ 100

GeV

3−10

2−10

1−10

1 < 1500 GeVT1000 < H

(MC)ννZ control sample (data)γ

W control sample (data)Z control sample (data)

(13 TeV)-135.9 fbCMS

Rat

io

0.51

1.5

Fig. 2 (Upper) Ratio RSF/OF in data as a function of Nj. The solidblack line enclosed by the red dashed lines corresponds to a value of1.13±0.15 that is observed to be stable with respect to event kinematics,while the two dashed black lines denote the statistical uncertainty in theRSF/OF value. (Lower) The shape of the MT2 distribution in Z → νν

simulation compared to shapes from γ , W, and Z data control samplesin a region with 1000 < HT < 1500 GeV and Nj ≥ 2, inclusive in Nb.The solid gray band on the ratio plot shows the systematic uncertaintyin the MT2 shape

events with Nj = 1, a control region is defined for each binof jet pT.

Uncertainties from the limited size of the control sampleand from theoretical and experimental sources are evaluatedand propagated to the final estimate. The dominant uncer-tainty in R0�/1�

MC

(HT, Nj, Nb, MT2

)arises from the mod-

eling of the lepton efficiency (for electrons, muons, and

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[GeV]T2M60 70 100 200 300 4000.01

0.1

1

10

100φr

< 1500 GeVT1000 < HDataData after subtractionFit

(13 TeV)-1 27.3 fb

/ndf = 4.5/4: 34.8%2χ

CMS

jN2 3 4 5 6 7 8 9 10 110

0.2

0.4

0.6

0.8

1

1.2

fj

(13 TeV)-1 27.3 fbCMS

< 1500 GeVT1000 < H

Data

Simulation

bN0 1 2 3 4 5 6

2−10

1−10

1

br

(13 TeV)-1 27.3 fbCMS

6≤j N≤4

Data

Simulation

Fig. 3 The ratio rφ as a function of MT2 for 1000 < HT < 1500 GeV(left). The superimposed fit is performed to the open circle data points.The black points represent the data before subtracting non-multijet con-tributions using simulation. Data point uncertainties are statistical only.The red line and the grey band around it show the result of the fit to apower-law function performed in the window 70 < MT2 < 100 GeV

and the associated fit uncertainty. Values of fj, the fraction of eventsin bin Nj, (middle) and rb, the fraction of events in bin Nj that fall inbin Nb, (right) are measured in data after requiring Δφmin < 0.3 and100 < MT2 < 200 GeV. The hatched bands represent both statisticaland systematic uncertainties

hadronically-decaying tau leptons) and jet energy scale (JES)and is of order 15–20%. The uncertainty in the MT2 extrap-olation, which is as large as 40%, arises primarily from theJES, the relative fractions of W+jets and tt+jets, and varia-tions of the renormalization and factorization scales assumedfor their simulation. These and other uncertainties are similarto those in Ref. [6].

4.2 Estimation of the background from Z(νν)+jets

The Z → νν background is estimated from a dilepton con-trol sample selected using triggers requiring two leptons. Thetrigger efficiency, measured with a data sample of events withlarge HT, is found to be greater than 97% in the selectedkinematic range. To obtain a control sample enriched inZ → �+�− events (� = e, μ), we require that the leptons areof the same flavor, opposite charge, that the pT of the leadingand trailing leptons are at least 100 and 30 GeV, respectively,and that the invariant mass of the lepton pair is consistent withthe mass of a Z boson within 20 GeV. After requiring that thepT of the dilepton system is at least 200 GeV, the preselectionrequirements are applied based on kinematic variables recal-culated after removing the dilepton system from the event toreplicate the Z → νν kinematics. For events with Nj = 1,one control region is defined for each bin of jet pT. For eventswith at least two jets, the selected events are binned in HT,Nj, and Nb, but not in MT2, to increase the dilepton eventyield in each control region.

The contribution to each control region from flavor-symmetric processes, most importantly tt, is estimated usingopposite-flavor (OF) eμ events obtained with the same selec-tions as same-flavor (SF) ee and μμ events. The backgroundin each signal bin is then obtained using transfer factors

according to:

NSRZ→νν

(HT, Nj, Nb, MT2

)

=[NCRSF

��

(HT, Nj, Nb

) − NCROF��

(HT, Nj, Nb

)RSF/OF

]

×RZ→νν/Z→�+�−MC

(HT, Nj, Nb

)k (MT2) . (3)

Here NCRSF�� and NCROF

�� are the number of SF and OF

events in the control region, while RZ→νν/Z→�+�−MC and

k (MT2) are defined below. The factor RSF/OF accounts forthe difference in acceptance and efficiency between SF andOF events. It is determined as the ratio of the number of SFevents to OF events in a tt enriched control sample, obtainedwith the same selections as the Z → �+�− sample, but invert-ing the requirements on the pT and the invariant mass of thelepton pair. A measured value of RSF/OF = 1.13 ± 0.15 isobserved to be stable with respect to event kinematics, and isapplied in all regions. Figure 2 (left) shows RSF/OF measuredas a function of the number of jets.

An estimate of the Z → νν background in each topolog-ical region is obtained from the corresponding dilepton con-

trol region via the factor RZ→νν/Z→�+�−MC , which accounts for

the acceptance and efficiency to select the dilepton pair andthe ratio of branching fractions for Z → �+�− and Z → νν

decays. This factor is obtained from simulation, includingcorrections for differences in the lepton efficiencies betweendata and simulation.

The factor k (MT2) accounts for the distribution, in binsof MT2, of the estimated background in each topologi-cal region. This distribution is constructed using the MT2

shape from dilepton data and Z → νν simulation in eachtopological region. Studies with simulated samples indi-cate that the MT2 shape for Z → νν events is inde-

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[250

,350

][3

50,4

50]

[450

,575

][5

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00]

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0][1

000,

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50]

[450

,575

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00]

>700

2-3j

, 0b

2-3j

, 1b

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, 2b

4j, 0

b≥ 4j

, 1b

≥ 4j, 2

b≥

3b≥2j

, ≥ 2-

3j, 0

b2-

3j, 1

b2-

3j, 2

b4-

6j, 0

b4-

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b4-

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, 0b

≥ 7j, 1

b≥ 7j

, 2b

≥3b≥

2-6j

, 3b≥

7j,

≥ 2-3j

, 0b

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, 1b

2-3j

, 2b

4-6j

, 0b

4-6j

, 1b

4-6j

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7j, 0

b≥ 7j

, 1b

≥ 7j, 2

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3b≥2-

6j,

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3j, 2

b4-

6j, 0

b4-

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≥3b≥

2-6j

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≥ 2-3j

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6j,

3b≥7j

, ≥

Ent

ries

2−10

1−10

1

10

210

310

410

510

610

(13 TeV)-1 35.9 fbCMS

1 Jet [250,450]TH [450,575]TH [575,1000]TH [1000,1500]TH > 1500 GeVTH0b 1b≥ Data

MultijetLost lepton

ννZ

Pre-fit backgroundD

ata/

Est

.

00.5

11.5

2

[200

,300

]

[300

,400

][4

00,6

00]

[600

,800

]

>800

[200

,300

]

[300

,400

][4

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00]

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,800

]

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[200

,300

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][4

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,300

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,800

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[200

,300

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][4

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,300

][3

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[400

,600

][6

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>800

[200

,300

][3

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[400

,600

][6

00,8

00]

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[200

,300

][3

00,4

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[400

,600

]

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,300

][3

00,4

00]

[400

,600

]

>600

[200

,300

][3

00,4

00]

[400

,600

]

>600

[200

,300

][3

00,4

00]

[400

,600

]

>600

T2

Ent

ries

in b

ins

of M

2−10

1−10

1

10

210

310

410

510

610DataMultijetLost lepton

ννZ

(13 TeV)-1 35.9 fbCMS

[575, 1000] GeVTHPre-fit background

2-3j0b

2-3j1b

2-3j2b

4-6j0b

4-6j1b

4-6j2b

7j≥0b

7j≥1b

7j≥2b

2-6j3b≥

7j≥3b≥

Dat

a/E

st.

00.5

11.5

2

Fig. 4 (Upper) Comparison of estimated (pre-fit) background andobserved data events in each topological region. Hatched bands repre-sent the full uncertainty in the background estimate. The results shownfor Nj = 1 correspond to the monojet search regions binned in jet pT,

whereas for the multijet signal regions, the notations j, b indicate Nj, Nblabeling. (Lower) Same for individual MT2 signal bins in the mediumHT region. On the x-axis, the MT2 binning is shown in units of GeV

pendent of Nb for a given HT and Nj selection, and thatthe shape is also independent of the number of jets forHT > 1500 GeV. The MC modeling of Nb and Nj as wellas of the MT2 shape in bins of Nj and Nb is validatedin data, using a dilepton control sample. As a result, MT2

templates for topological regions differing only in Nb are

combined, separately for data and simulation. For HT >

1500 GeV, only one MT2 template is constructed for dataand one for simulation by combining all relevant topologicalregions.

Starting from the highest MT2 bin in each control region,we merge bins until the sum of the merged bins contains

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Table 2 Definitions of supersignal regions, along withpredictions, observed data, andthe observed 95% CL upperlimits on the number of signalevents contributing to eachregion (N obs

95 ). The limits areshown as a range correspondingto an assumed uncertainty in thesignal acceptance of 0–15%. Adash in the selections means thatno requirement is applied

Region Nj Nb HT (GeV) MT2 (GeV) Prediction Data N obs95

2j loose ≥ 2 — > 1000 > 1200 38.9 ± 11.2 42 26.6–27.8

2j tight ≥ 2 — > 1500 > 1400 2.9 ± 1.3 4 6.5–6.7

4j loose ≥ 4 — > 1000 > 1000 19.4 ± 5.8 21 15.8–16.4

4j tight ≥ 4 — > 1500 > 1400 2.1 ± 0.9 2 4.4–4.6

7j loose ≥ 7 — > 1000 > 600 23.5+5.9−5.6 27 18.0–18.7

7j tight ≥ 7 — > 1500 > 800 3.1+1.7−1.4 5 7.6–7.9

2b loose ≥ 2 ≥ 2 > 1000 > 600 12.9+2.9−2.6 16 12.5–13.0

2b tight ≥ 2 ≥ 2 > 1500 > 600 5.1+2.7−2.1 4 5.8–6.0

3b loose ≥ 2 ≥ 3 > 1000 > 400 8.4 ± 1.8 10 9.3–9.7

3b tight ≥ 2 ≥ 3 > 1500 > 400 2.0 ± 0.6 4 6.6–6.9

7j3b loose ≥ 7 ≥ 3 > 1000 > 400 5.1 ± 1.5 5 6.4–6.6

7j3b tight ≥ 7 ≥ 3 > 1500 > 400 0.9 ± 0.5 1 3.6–3.7

P1

P2g̃

g̃

b

b

χ01

χ01

b

b

P1

P2g̃

g̃

t̄

t

χ01

χ01

t̄

t

P1

P2g̃

g̃

q

q

χ01

χ01

q

q

P1

P2

b̄1

b1

b̄

χ01

χ01

b

P1

P2

t̄1

t1

t̄

χ01

χ01

t

P1

P2

q̄

q

q̄

χ01

χ01

q

P1

P2

t̄1

t1

χ−1

χ+1

b̄

W−

χ01

χ01

W+

b

P1

P2

t̄1

t1χ+1

t̄

χ01

χ01

W+

b

P1

P2

t̄1

t1

c̄

χ01

χ01

c

Fig. 5 (Upper) Diagrams for the three scenarios of gluino-mediatedbottom squark, top squark and light flavor squark production consid-ered. (Middle) Diagrams for the direct production of bottom, top andlight-flavor squark pairs. (Lower) Diagrams for three alternate scenarios

of direct top squark production with different decay modes. For mixeddecay scenarios, we assume a 50% branching fraction for each decaymode

at least 50 expected events from simulation. The fraction ofevents in each uncombined bin is determined using the cor-responding MT2 template from dilepton data, corrected by

the ratio RZ→νν/Z→�+�−MC . The MT2 shape from simulation is

used to distribute events among the combined bins, after nor-

malizing the simulation to the data yield in the same groupof bins.

The modeling of MT2 is validated in data using controlsamples enriched in γ , W → �ν, and Z → �+�− eventsin each bin of HT. The lower panel of Fig. 2 shows agree-

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Table 3 Typical values of the systematic uncertainties as evaluated forthe simplified models of SUSY used in the context of this search. Thehigh statistical uncertainty in the simulated signal sample corresponds toa small number of signal bins with low acceptance, which are typicallynot among the most sensitive signal bins to that model point.

Source Typical values (%)

Integrated luminosity 2.5

Limited size of MC samples 1–100

Renormalization and factorization scales 5

ISR modeling 0–30

b Tagging efficiency, heavy flavors 0–40

b Tagging efficiency, light flavors 0–20

Lepton efficiency 0–20

Jet energy scale 5

Fast simulation pmissT modeling 0–5

Fast simulation pileup modeling 4.6

ment between the MT2 distributions obtained from γ , W,and Z data control samples with that from Z → νν simula-tion for events with 1000 < HT < 1500 GeV. In this com-parison, the γ sample is obtained by selecting events withpγ

T > 180 GeV and is corrected for contributions from mul-

tijet events and RZ/γMC , the W sample is corrected for RZ/W

MC ,both the W and Z samples are corrected for contributionsfrom top quark events, and the Z sample is further corrected

for RZ→νν/Z→�+�−MC . Here RZ/γ

MC (RZ/WMC ) is the ratio of the MT2

distributions for Z boson and γ (W) boson events derived insimulation.

The largest uncertainty in the estimate of the invisibleZ background in most regions results from the limited sizeof the dilepton control sample. This uncertainty, as well asall other relevant theoretical and experimental uncertainties,are evaluated and propagated to the final estimate. The domi-

nant uncertainty in the ratio RZ→νν/Z→�+�−MC is obtained from

measured differences in lepton efficiency between data andsimulation, and is about 5%. The uncertainty in the k (MT2)

factor arises from data statistics for uncombined bins, whilefor combined bins it is due to uncertainties in the JES and vari-ations in the renormalization and factorization scales. Thesecan result in effects as large as 40%.

4.3 Estimation of the multijet background

For events with at least two jets, a multijet-enriched controlregion is obtained in each HT bin by inverting the Δφmin

requirement described in Sect. 3. Events are selected usingHT triggers, and the extrapolation from low- to high-Δφmin

is based on the following ratio:

rφ(MT2) = N (Δφmin > 0.3)/N (Δφmin < 0.3). (4)

Studies with simulated samples show that the ratio can bedescribed by a power law as rφ(MT2) = a Mb

T2. The param-eters a and b are determined separately in each HT bin byfitting rφ in an MT2 sideband in data after subtracting non-multijet contributions using simulation. The sideband spansMT2 values of 60–100 GeV for events with HT < 1000 GeV,and 70–100 GeV for events with larger values of HT. The fitto the rφ distribution in the 1000 < HT < 1500 GeV region isshown in Fig. 3 (left). The inclusive multijet contribution ineach signal region, NSR

j,b (MT2), is estimated using the ratiorφ(MT2) measured in the MT2 sideband and the number ofevents in the low-Δφmin control region, NCR

inc (MT2), accord-ing to

NSRj,b (MT2) = NCR

inc (MT2) rφ(MT2) fj (HT) rb(Nj

), (5)

where fj is the fraction of multijet events in bin Nj, and rb isthe fraction of events in bin Nj that are in bin Nb. (Here, Nj

denotes a jet multiplicity bin, and Nb denotes a b jet multi-plicity bin within Nj). The values of fj and rb are measuredusing events with MT2 between 100 and 200 GeV in the lowΔφmin sideband, where fj is measured separately in each HT

bin, while rb is measured in bins of Nj integrated over HT, asrb is found to be independent of the latter. Values of fj andrb measured in data are shown in Fig. 3 (center and right)compared to simulation.

The largest uncertainties in the estimate in most regionsresult from the statistical uncertainty in the fit and from thesensitivity of the rφ value to variations in the fit window.These variations result in an uncertainty that increases withMT2 and ranges from 20–50%. The total uncertainty in theestimate is found to be of similar size as in Ref. [6], varyingbetween 40–180% depending on the search region.

An estimate based on rφ(MT2) is not viable in the mono-jet search regions, which therefore require a different strat-egy. A control region is obtained by selecting events witha second jet with 30 < pT < 60 GeV and inverting theΔφmin requirement. After subtracting non-multijet contribu-tions using simulation, the data yield in the control region istaken as an estimate of the background in the correspondingmonojet search region. Tests in simulation show the methodprovides a conservative estimate of the multijet background,which is less than 8% in all monojet search regions. In allmonojet bins, a 50% uncertainty in the non-multijet subtrac-tion is combined with the statistical uncertainty from the datayield in the control region with a second jet.

5 Results

The data yields in the search regions are statistically com-patible with the estimated backgrounds from SM processes.A summary of the results of this search is shown in Fig. 4.Each bin in the upper panel corresponds to a single HT, Nj, Nb

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Fig. 6 Exclusion limits at 95% CL for gluino-mediated bottom squarkproduction (upper left), gluino-mediated top squark production (upperright), and gluino-mediated light-flavor (u,d,s,c) squark production(below). The area enclosed by the thick black curve represents the

observed exclusion region, while the dashed red lines indicate theexpected limits and their ±1 standard deviation ranges. The thin blacklines show the effect of the theoretical uncertainties on the signal crosssection

topological region, integrated over MT2. The lower panel fur-ther breaks down the background estimates and observed datayields into MT2 bins for the region 575 < HT < 1000 GeV.Distributions for the other HT regions can be found inAppendix B. The background estimates and correspondinguncertainties shown in these plots rely exclusively on theinputs from control samples and simulation described inSect. 4, and are referred to in the rest of the text as “pre-fit background” results.

To allow simpler reinterpretation, we also provide resultsfor super signal regions, which cover subsets of the full anal-ysis with simpler inclusive selections and that can be used toobtain approximate interpretations of this search. The defini-tions of these regions are given in Table 2, with the predictedand observed number of events and the 95% confidence level(CL) upper limit on the number of signal events contribut-ing to each region. Limits are set using a modified frequen-tist approach, employing the CLs criterion and relying on

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Fig. 7 Exclusion limit at 95% CL for bottom squark pair production(upper left), top squark pair production (upper right), and light-flavorsquark pair production (below). The area enclosed by the thick blackcurve represents the observed exclusion region, while the dashed redlines indicate the expected limits and their ±1 standard deviation ranges.For the top squark pair production plot, the ±2 standard deviation rangesare also shown. The thin black lines show the effect of the theoretical

uncertainties on the signal cross section. The white diagonal band in theupper right plot corresponds to the region |m t̃ − mt − mχ̃0

1| < 25 GeV

and small mχ̃01. Here the efficiency of the selection is a strong func-

tion of m t̃ −mχ̃01, and as a result the precise determination of the cross

section upper limit is uncertain because of the finite granularity of theavailable MC samples in this region of the (m t̃,mχ̃0

1) plane

asymptotic approximations to calculate the distribution ofthe profile likelihood test-statistic used [41–44].

5.1 Interpretation

The results of the search can be interpreted by perform-ing a maximum likelihood fit to the data in the signal

regions. The fit is carried out under either a background-only or a background+signal hypothesis. The uncertain-ties in the modeling of the backgrounds, summarized inSect. 4, are inputs to the fitting procedure. The likelihoodis constructed as the product of Poisson probability den-sity functions, one for each signal region, with constraintterms that account for uncertainties in the background esti-

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Fig. 8 Exclusion limit at 95% CL for top squark pair productionfor different decay modes of the top squark. For the scenario wherepp → t̃̃t → bbχ̃±

1 χ̃∓1 , χ̃±

1 → W±χ̃01 (upper left), the mass of the

chargino is chosen to be half way in between the masses of the top squarkand the neutralino. A mixed decay scenario (upper right), pp → t̃̃twith equal branching fractions for the top squark decays t̃ → tχ̃0

1 and

t̃ → bχ̃+1 , χ̃+

1 → W∗+χ̃01 , is also considered, with the chargino mass

chosen such that Δm(χ̃±

1 , χ̃01

) = 5 GeV. Finally, we also consider a

compressed scenario (below) where pp → t̃̃t → ccχ̃01 χ̃0

1 . The areaenclosed by the thick black curve represents the observed exclusionregion, while the dashed red lines indicate the expected limits and their±1 standard deviation ranges. The thin black lines show the effect ofthe theoretical uncertainties on the signal cross section

mates and, if considered, the signal yields. The result ofthe background-only fit, denoted as “post-fit background”,is given in Appendix B. If the magnitude and correlationmodel of the uncertainties associated to the pre-fit estimatesare properly assigned, and the data are found to be in agree-ment with the estimates, then the fit has the effect of con-straining the background and reducing the associated uncer-tainties.

The results of the search are used to constrain the sim-plified models of SUSY [45] shown in Fig. 5. For eachscenario of gluino (squark) pair production, the simplifiedmodels assume that all SUSY particles other than the gluino(squark) and the lightest neutralino are too heavy to be pro-duced directly, and that the gluino (squark) decays promptly.The models assume that each gluino (squark) decays witha 100% branching fraction into the decay products depicted

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in Fig. 5. For models where the decays of the two squarksdiffer, we assume a 50% branching fraction for each decaymode. For the scenario of top squark pair production, thepolarization of the top quark is model dependent and is afunction of the top-squark and neutralino mixing matrices.To remain agnostic to a particular model realization, eventsare generated without polarization. Signal cross sections arecalculated at NLO + NLL order in αs [46–50].

Typical values of the uncertainties in the signal yield forthe simplified models considered are listed in Table 3. Thesources of uncertainties and the methods used to evaluatetheir effect on the interpretation are the same as those dis-cussed in Ref. [6]. Uncertainties due to the luminosity [51],ISR and pileup modeling, and b tagging and lepton efficien-cies are treated as correlated across search bins. Remaininguncertainties are taken as uncorrelated.

Figure 6 shows the exclusion limits at 95% CL for gluino-mediated bottom squark, top squark, and light-flavor squarkproduction. Exclusion limits at 95% CL for the direct produc-tion of bottom, top, and light-flavor squark pairs are shownin Fig. 7. Direct production of top squarks for three alternatedecay scenarios are also considered, and exclusion limits at95% CL are shown in Fig. 8. Table 4 summarizes the limits onthe masses of the SUSY particles excluded in the simplifiedmodel scenarios considered. These results extend the con-straints on gluinos and squarks by about 300 GeV and on χ̃0

1by 200 GeV with respect to those in Ref. [6]. The largest dif-ferences between the observed and expected limits are foundfor scenarios of top squark pair production with moderatemass splittings and result from observed yields that are lessthan the expected background in topological regions with HT

between 575 and 1500 GeV, at least 7 jets, and either one ortwo b-tagged jets.

We note that the 95% CL upper limits on signal cross sec-tions obtained using the most sensitive super signal regionsof Table 2 are typically less stringent by a factor of ∼1.5–3 compared to those obtained in the fully-binned analysis.The full analysis performs better because of its larger sig-nal acceptance and because it splits the events into bins withmore favorable signal-to-background ratio.

6 Summary

This paper presents the results of a search for new phenom-ena using events with jets and large MT2. Results are basedon a 35.9 fb−1 data sample of proton–proton collisions at√s = 13 TeV collected in 2016 with the CMS detector. No

significant deviations from the standard model expectationsare observed. The results are interpreted as limits on the pro-duction of new, massive colored particles in simplified mod-els of supersymmetry. This search probes gluino masses upto 2025 GeV and χ̃0

1 masses up to 1400 GeV. Constraints

Table 4 Summary of 95% CL observed exclusion limits on the massesof SUSY particles (sparticles) in different simplified model scenarios.The limit on the mass of the produced sparticle is quoted for a masslessχ̃0

1 , while for the mass of the χ̃01 we quote the highest limit that is

obtained

Simplifiedmodel

Limit on producedsparticle

Highest limiton the

mass (GeV) formχ̃0

1= 0 GeV

χ̃01 mass (GeV)

Direct squark production

Bottom squark 1175 590

Top squark 1070 550

Single light squark 1050 475

Eight degenerate light squarks 1550 775

Gluino-mediated production

g̃ → bbχ̃01 2025 1400

g̃ → ttχ̃01 1900 1010

g̃ → qqχ̃01 1860 1100

are also obtained on the pair production of light-flavor, bot-tom, and top squarks, probing masses up to 1550, 1175, and1070 GeV, respectively, and χ̃0

1 masses up to 775, 590, and550 GeV in each scenario.

Acknowledgements We congratulate our colleagues in the CERNaccelerator departments for the excellent performance of the LHC andthank the technical and administrative staffs at CERN and at other CMSinstitutes for their contributions to the success of the CMS effort. Inaddition, we gratefully acknowledge the computing centers and per-sonnel of the Worldwide LHC Computing Grid for delivering so effec-tively the computing infrastructure essential to our analyses. Finally, weacknowledge the enduring support for the construction and operation ofthe LHC and the CMS detector provided by the following funding agen-cies: BMWFW and FWF (Austria); FNRS and FWO (Belgium); CNPq,CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS,MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES andCSF (Croatia); RPF (Cyprus); SENESCYT (Ecuador); MoER, ERCIUT, and ERDF (Estonia); Academy of Finland, MEC, and HIP (Fin-land); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Ger-many); GSRT (Greece); OTKA and NIH (Hungary); DAE and DST(India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Repub-lic of Korea); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CIN-VESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MBIE(New Zealand); PAEC (Pakistan); MSHE and NSC (Poland); FCT(Portugal); JINR (Dubna); MON, RosAtom, RAS, RFBR and RAEP(Russia); MESTD (Serbia); SEIDI, CPAN, PCTI and FEDER (Spain);Swiss Funding Agencies (Switzerland); MST (Taipei); ThEPCenter,IPST, STAR, and NSTDA (Thailand); TUBITAK and TAEK (Turkey);NASU and SFFR (Ukraine); STFC (UK); DOE and NSF (USA).Individuals have received support from the Marie-Curie program and theEuropean Research Council and EPLANET (European Union); the Lev-entis Foundation; the A. P. Sloan Foundation; the Alexander von Hum-boldt Foundation; the Belgian Federal Science Policy Office; the Fondspour la Formation à la Recherche dans l’Industrie et dans l’Agriculture(FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap enTechnologie (IWT-Belgium); the Ministry of Education, Youth andSports (MEYS) of the Czech Republic; the Council of Science andIndustrial Research, India; the HOMING PLUS program of the Foun-

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dation for Polish Science, cofinanced from European Union, RegionalDevelopment Fund, the Mobility Plus program of the Ministry of Sci-ence and Higher Education, the National Science Center (Poland), con-tracts Harmonia 2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543,2014/15/B/ST2/03998, and 2015/19/B/ST2/02861, Sonata-bis 2012/07-/E/ST2/01406; the National Priorities Research Program by QatarNational Research Fund; the Programa Clarín-COFUND del Princi-pado de Asturias; the Thalis and Aristeia programs cofinanced by EU-ESF and the Greek NSRF; the Rachadapisek Sompot Fund for Post-doctoral Fellowship, Chulalongkorn University and the ChulalongkornAcademic into Its 2nd Century Project Advancement Project (Thai-land); and the Welch Foundation, contract C-1845.

Open Access This article is distributed under the terms of the CreativeCommons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution,and reproduction in any medium, provided you give appropriate creditto the original author(s) and the source, provide a link to the CreativeCommons license, and indicate if changes were made.Funded by SCOAP3.

A Definition of search regions

The 213 exclusive search regions are defined in Tables 5, 6and 7.

Table 5 Summary of signal regions for the monojet selection

Nb Jet pT binning (GeV)

0 [250, 350, 450, 575, 700, 1000, 1200, ∞)

≥ 1 [250, 350, 450, 575, 700, ∞)

Table 6 The MT2 binning in each topological region of the multi-jetsearch regions, for the very low, low and medium HT regions

HT range (GeV) Jet multiplicities MT2 binning (GeV)

[250, 450] 2 − 3j, 0b [200, 300, 400, ∞)

2 − 3j, 1b [200, 300, 400, ∞)

2 − 3j, 2b [200, 300, 400, ∞)

≥ 4j, 0b [200, 300, 400, ∞)

≥ 4j, 1b [200, 300, 400, ∞)

≥ 4j, 2b [200, 300, 400, ∞)

≥ 2j, ≥ 3b [200, 300, 400, ∞)

[450, 575] 2 − 3j, 0b [200, 300, 400, 500, ∞)

2 − 3j, 1b [200, 300, 400, 500, ∞)

2 − 3j, 2b [200, 300, 400, 500, ∞)

4 − 6j, 0b [200, 300, 400, 500, ∞)

4 − 6j, 1b [200, 300, 400, 500, ∞)

4 − 6j, 2b [200, 300, 400, 500, ∞)

≥ 7j, 0b [200, 300, 400, ∞)

≥ 7j, 1b [200, 300, 400, ∞)

≥ 7j, 2b [200, 300, 400, ∞)

2 − 6j, ≥ 3b [200, 300, 400, 500, ∞)

≥ 7j, ≥ 3b [200, 300, 400, ∞)

Table 6 continued

HT range (GeV) Jet multiplicities MT2 binning (GeV)

[575, 1000] 2 − 3j, 0b [200, 300, 400, 600, 800, ∞)

2 − 3j, 1b [200, 300, 400, 600, 800, ∞)

2 − 3j, 2b [200, 300, 400, 600, 800, ∞)

4 − 6j, 0b [200, 300, 400, 600, 800, ∞)

4 − 6j, 1b [200, 300, 400, 600, 800, ∞)

4 − 6j, 2b [200, 300, 400, 600, 800, ∞)

≥ 7j, 0b [200, 300, 400, 600, 800, ∞)

≥ 7j, 1b [200, 300, 400, 600, ∞)

≥ 7j, 2b [200, 300, 400, 600, ∞)

2 − 6j, ≥ 3b [200, 300, 400, 600, ∞)

≥ 7j, ≥ 3b [200, 300, 400, 600, ∞)

Table 7 The MT2 binning in each topological region of the multijetsearch regions, for the high- and extreme-HT regions

HT range (GeV) Jet multi-plicities

MT2 binning (GeV)

[1000, 1500] 2 − 3j, 0b [200, 400, 600, 800, 1000, 1200, ∞)

2 − 3j, 1b [200, 400, 600, 800, 1000, 1200, ∞)

2 − 3j, 2b [200, 400, 600, 800, 1000, ∞)

4 − 6j, 0b [200, 400, 600, 800, 1000, 1200, ∞)

4 − 6j, 1b [200, 400, 600, 800, 1000, 1200, ∞)

4 − 6j, 2b [200, 400, 600, 800, 1000, ∞)

≥ 7j, 0b [200, 400, 600, 800, 1000, ∞)

≥ 7j, 1b [200, 400, 600, 800, ∞)

≥ 7j, 2b [200, 400, 600, 800, ∞)

2 − 6j, ≥ 3b [200, 400, 600, ∞)

≥ 7j, ≥ 3b [200, 400, 600, ∞)

[1500, ∞) 2 − 3j, 0b [400, 600, 800, 1000, 1400, ∞)

2 − 3j, 1b [400, 600, 800, 1000, ∞)

2 − 3j, 2b [400, ∞)

4 − 6j, 0b [400, 600, 800, 1000, 1400, ∞)

4 − 6j, 1b [400, 600, 800, 1000, 1400, ∞)

4 − 6j, 2b [400, 600, 800, ∞)

≥ 7j, 0b [400, 600, 800, 1000, ∞)

≥ 7j, 1b [400, 600, 800, ∞)

≥ 7j, 2b [400, 600, 800, ∞)

2 − 6j, ≥ 3b [400, 600, ∞)

≥ 7j, ≥ 3b [400, ∞)

B Detailed results

See Figs. 9, 10, 11, 12, 13 and 14 in Appendix.

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[250

,350

]

[350

,450

]

[450

,575

]

[575

,700

]

[700

,100

0]

[100

0,12

00]

>120

0

[250

,350

]

[350

,450

]

[450

,575

]

[575

,700

]

>700

TE

ntrie

s in

bin

s of

jet p

1−10

1

10

210

310

410

510

610DataMultijetLost lepton

ννZ

(13 TeV)-1 35.9 fbCMS

Monojet regionPre-fit background

1j0b

1j 1b≥

Dat

a/E

st.

00.5

11.5

2

[200

,300

]

[300

,400

]

>400

[200

,300

]

[300

,400

]

>400

[200

,300

]

[300

,400

]

>400

[200

,300

]

[300

,400

]

>400

[200

,300

]

[300

,400

]

>400

[200

,300

]

[300

,400

]

>400

[200

,300

]

[300

,400

]

>400

T2

Ent

ries

in b

ins

of M

1−10

1

10

210

310

410

510

610DataMultijetLost lepton

ννZ

(13 TeV)-1 35.9 fbCMS

[250, 450] GeVTHPre-fit background

2-3j0b

2-3j1b

2-3j2b

4j≥0b

4j≥1b

4j≥2b

2j≥3b≥

Dat

a/E

st.

00.5

11.5

2

Fig. 9 (Upper) Comparison of the estimated background and observeddata events in each signal bin in the monojet region. On the x-axis, thepjet1

T binning is shown in units of GeV. Hatched bands represent the full

uncertainty in the background estimate. (Lower) Same for the very lowHT region. On the x-axis, the MT2 binning is shown in units of GeV

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Fig. 10 (Upper) Comparison ofthe estimated background andobserved data events in eachsignal bin in the low-HT region.Hatched bands represent the fulluncertainty in the backgroundestimate. Same for the high-(middle) and extreme- (lower)HT regions. On the x-axis, theMT2 binning is shown in unitsof GeV. For the extreme-HTregion, the last bin is left emptyfor visualization purposes

[200

,300

]

[300

,400

]

[400

,500

]

>500

[200

,300

]

[300

,400

]

[400

,500

]

>500

[200

,300

]

[300

,400

]

[400

,500

]

>500

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]

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>400

[200

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>400

[200

,300

]

[300

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]

[400

,500

]

>500

[200

,300

]

[300

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]

>400

T2

Ent

ries

in b

ins

of M

2−10

1−10

1

10

210

310

410

510

610DataMultijetLost lepton

ννZ

(13 TeV)-1 35.9 fbCMS

[450, 575] GeVTHPre-fit background

2-3j0b

2-3j1b

2-3j2b

4-6j0b

4-6j1b

4-6j2b

7j≥0b

7j≥1b

7j≥2b

2-6j3b≥

7j≥3b≥

Dat

a/E

st.

01

2

3[2

00,4

00]

[400

,600

][6

00,8

00]

[800

,100

0][1

000,

1200

]

>120

0[2

00,4

00]

[400

,600

][6

00,8

00]

[800

,100

0][1

000,

1200

]>1

200

[200

,400

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[250

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Post-fit backgroundD

ata/

Est

.

00.5

11.5

2

Fig. 11 Comparison of post-fit background prediction and observeddata events in each topological region. Hatched bands represent thepost-fit uncertainty in the background prediction. For the monojet, on

the x-axis the pjet1T binning is shown in units of GeV, whereas for the

multijet signal regions, the notations j, b indicate Nj, Nb labeling

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Fig. 12 (Upper) Comparison ofthe post-fit backgroundprediction and observed dataevents in each signal bin in themonojet region. On the x-axis,the pjet1

T binning is shown inunits of GeV. (Middle) and(lower): Same for the very lowand low-HT region. On thex-axis, the MT2 binning isshown in units of GeV. Thehatched bands represent thepost-fit uncertainty in thebackground prediction

[250

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bin

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ries

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Dat

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Fig. 13 (Upper) Comparison ofthe post-fit backgroundprediction and observed dataevents in each signal bin in themedium-HT region. Same forthe high- (middle) and extreme-(lower) HT regions. On thex-axis, the MT2 binning isshown in units of GeV. Thehatched bands represent thepost-fit uncertainty in thebackground prediction. For theextreme-HT region, the last binis left empty for visualizationpurposes

[300

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00]

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ries

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610DataMultijetLost lepton

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Fig. 14 (Upper) The post-fit background prediction and observed dataevents in the analysis binning, for all topological regions with theexpected yield for the signal model of gluino mediated bottom-squarkproduction (m g̃ = 1000 GeV, mχ̃0

1= 800 GeV) stacked on top of the

expected background. For the monojet regions, the pjet1T binning is in

units of GeV. (Lower) Same for the extreme-HT region for the samesignal with (m g̃ = 1900 GeV,mχ̃0

1= 100 GeV). On the x-axis, the MT2

binning is shown in units of GeV. The hatched bands represent the post-fit uncertainty in the background prediction. For the extreme-HT region,the last bin is left empty for visualization purposes

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CMS Collaboration

Yerevan Physics Institute, Yerevan, ArmeniaA. M. Sirunyan, A. Tumasyan, A. Johnson41

Institut für Hochenergiephysik, Wien, AustriaW. Adam, F. Ambrogi, E. Asilar, T. Bergauer, J. Brandstetter, E. Brondolin, M. Dragicevic, J. Erö, M. Flechl, M. Friedl,R. Frühwirth1, V. M. Ghete, J. Grossmann, J. Hrubec, M. Jeitler1, A. König, N. Krammer, I. Krätschmer, D. Liko,T. Madlener, I. Mikulec, E. Pree, D. Rabady, N. Rad, H. Rohringer, J. Schieck1, R. Schöfbeck, M. Spanring, D. Spitzbart,J. Strauss, W. Waltenberger, J. Wittmann, C.-E. Wulz1, M. Zarucki

Institute for Nuclear Problems, Minsk, BelarusV. Chekhovsky, V. Mossolov, J. Suarez Gonzalez

Universiteit Antwerpen, Antwerp, BelgiumE. A. De Wolf, D. Di Croce, X. Janssen, J. Lauwers, M. Van De Klundert, H. Van Haevermaet, P. Van Mechelen,N. Van Remortel, A. Van Spilbeeck

Vrije Universiteit Brussel, Brussels, BelgiumS. Abu Zeid, F. Blekman, J. D’Hondt, I. De Bruyn, J. De Clercq, K. Deroover, G. Flouris, D. Lontkovskyi, S. Lowette,S. Moortgat, L. Moreels, A. Olbrechts, Q. Python, K. Skovpen, S. Tavernier, W. Van Doninck, P. Van Mulders, I. Van Parijs

Université Libre de Bruxelles, Brussels, BelgiumH. Brun, B. Clerbaux, G. De Lentdecker, H. Delannoy, G. Fasanella, L. Favart, R. Goldouzian, A. Grebenyuk,G. Karapostoli, T. Lenzi, J. Luetic, T. Maerschalk, A. Marinov, A. Randle-conde, T. Seva, C. Vander Velde, P. Vanlaer,D. Vannerom, R. Yonamine, F. Zenoni, F. Zhang2

Ghent University, Ghent, BelgiumA. Cimmino, T. Cornelis, D. Dobur, A. Fagot, M. Gul, I. Khvastunov, D. Poyraz, C. Roskas, S. Salva, M. Tytgat,W. Verbeke, N. Zaganidis

Université Catholique de Louvain, Louvain-la-Neuve, BelgiumH. Bakhshiansohi, O. Bondu, S. Brochet, G. Bruno, A. Caudron, S. De Visscher, C. Delaere, M. Delcourt, B. Francois,A. Giammanco, A. Jafari, M. Komm, G. Krintiras, V. Lemaitre, A. Magitteri, A. Mertens, M. Musich, K. Piotrzkowski,L. Quertenmont, M. Vidal Marono, S. Wertz

Université de Mons, Mons, BelgiumN. Beliy

Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, BrazilW. L. Aldá Júnior, F. L. Alves, G. A. Alves, L. Brito, M. Correa Martins Junior, C. Hensel, A. Moraes, M. E. Pol,P. Rebello Teles

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Universidade do Estado do Rio de Janeiro, Rio de Janeiro, BrazilE. Belchior Batista Das Chagas, W. Carvalho, J. Chinellato3, A. Custódio, E. M. Da Costa, G. G. Da Silveira4,D. De Jesus Damiao, S. Fonseca De Souza, L. M. Huertas Guativa, H. Malbouisson, M. Melo De Almeida,C. Mora Herrera, L. Mundim, H. Nogima, A. Santoro, A. Sznajder, E. J. Tonelli Manganote3,F. Torres Da Silva De Araujo, A. Vilela Pereira

Universidade Estadual Paulistaa , Universidade Federal do ABCb, São Paulo, BrazilS. Ahujaa , C. A. Bernardesa , T. R. Fernandez Perez Tomeia , E. M. Gregoresb, P. G. Mercadanteb, C. S. Moona ,S. F. Novaesa , Sandra S. Padulaa , D. Romero Abadb, J. C. Ruiz Vargasa

Institute for Nuclear Research and Nuclear Energy of Bulgaria Academy of Sciences, Sofia, BulgariaA. Aleksandrov, R. Hadjiiska, P. Iaydjiev, M. Misheva, M. Rodozov, M. Shopova, S. Stoykova, G. Sultanov

University of Sofia, Sofia, BulgariaA. Dimitrov, I. Glushkov, L. Litov, B. Pavlov, P. Petkov

Beihang University, Beijing, ChinaW. Fang5, X. Gao5

Institute of High Energy Physics, Beijing, ChinaM. Ahmad, J. G. Bian, G. M. Chen, H. S. Chen, M. Chen, Y. Chen, C. H. Jiang, D. Leggat, Z. Liu, F. Romeo,S. M. Shaheen, A. Spiezia, J. Tao, C. Wang, Z. Wang, E. Yazgan, H. Zhang, J. Zhao

State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, ChinaY. Ban, G. Chen, Q. Li, S. Liu, Y. Mao, S. J. Qian, D. Wang, Z. Xu

Universidad de Los Andes, Bogota, ColombiaC. Avila, A. Cabrera, L. F. Chaparro Sierra, C. Florez, C. F. González Hernández, J. D. Ruiz Alvarez

Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, Split, CroatiaB. Courbon, N. Godinovic, D. Lelas, I. Puljak, P. M. Ribeiro Cipriano, T. Sculac

Faculty of Science, University of Split, Split, CroatiaZ. Antunovic, M. Kovac

Institute Rudjer Boskovic, Zagreb, CroatiaV. Brigljevic, D. Ferencek, K. Kadija, B. Mesic, T. Susa

University of Cyprus, Nicosia, CyprusM. W. Ather, A. Attikis, G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos, P. A. Razis, H. Rykaczewski

Charles University, Prague, Czech RepublicM. Finger6, M. Finger Jr.6

Universidad San Francisco de Quito, Quito, EcuadorE. Carrera Jarrin

Academy of Scientific Research and Technology of the Arab Republic of Egypt, Egyptian Network of High EnergyPhysics, Cairo, EgyptA. Ellithi Kamel7, S. Khalil8, A. Mohamed8

National Institute of Chemical Physics and Biophysics, Tallinn, EstoniaR. K. Dewanjee, M. Kadastik, L. Perrini, M. Raidal, A. Tiko, C. Veelken

Department of Physics, University of Helsinki, Helsinki, FinlandP. Eerola, J. Pekkanen, M. Voutilainen

Helsinki Institute of Physics, Helsinki, FinlandJ. Härkönen, T. Järvinen, V. Karimäki, R. Kinnunen, T. Lampén, K. Lassila-Perini, S. Lehti, T. Lindén, P. Luukka,E. Tuominen, J. Tuominiemi, E. Tuovinen

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Lappeenranta University of Technology, Lappeenranta, FinlandJ. Talvitie, T. Tuuva

IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, FranceM. Besancon, F. Couderc, M. Dejardin, D. Denegri, J. L. Faure, F. Ferri, S. Ganjour, S. Ghosh, A. Givernaud, P. Gras,G. Hamel de Monchenault, P. Jarry, I. Kucher, E. Locci, M. Machet, J. Malcles, G. Negro, J. Rander, A. Rosowsky,M. Ö. Sahin, M. Titov

Laboratoire Leprince-Ringuet, Ecole Polytechnique, CNRS/IN2P3, Université Paris-Saclay, Palaiseau, FranceA. Abdulsalam, I. Antropov, S. Baffioni, F. Beaudette, P. Busson, L. Cadamuro, E. Chapon, C. Charlot, O. Davignon,R. Granier de Cassagnac, M. Jo, S. Lisniak, A. Lobanov, J. Martin Blanco, M. Nguyen, C. Ochando, G. Ortona,P. Paganini, P. Pigard, S. Regnard, R. Salerno, J. B. Sauvan, Y. Sirois, A. G. Stahl Leiton, T. Strebler, Y. Yilmaz, A. Zabi

Université de Strasbourg, CNRS, IPHC UMR 7178, 67000 Strasbourg, FranceJ.-L. Agram9, J. Andrea, A. Aubin, J.-M. Brom, M. Buttignol, E. C. Chabert, N. Chanon, C. Collard, E. Conte9,X. Coubez, J.-C. Fontaine9, D. Gelé, U. Goerlach, M. Jansová, A.-C. Le Bihan, N. Tonon, P. Van Hove

Centre de Calcul de l’Institut National de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3,Villeurbanne, FranceS. Gadrat

Université de Lyon, Université Claude Bernard Lyon 1, CNRS-IN2P3, Institut de Physique Nucléaire de Lyon,Villeurbanne, FranceS. Beauceron, C. Bernet, G. Boudoul, R. Chierici, D. Contardo, P. Depasse, H. El Mamouni, J. Fay, L. Finco, S. Gascon,M. Gouzevitch, G. Grenier, B. Ille, F. Lagarde, I. B. Laktineh, M. Lethuillier, L. Mirabito, A. L. Pequegnot, S. Perries,A. Popov10, V. Sordini, M. Vander Donckt, S. Viret

Georgian Technical University, Tbilisi, GeorgiaA. Khvedelidze6

Tbilisi State University, Tbilisi, GeorgiaZ. Tsamalaidze6

RWTH Aachen University, I. Physikalisches Institut, Aachen, GermanyC. Autermann, S. Beranek, L. Feld, M. K. Kiesel, K. Klein, M. Lipinski, M. Preuten, C. Schomakers, J. Schulz, T. Verlage

RWTH Aachen University, III. Physikalisches Institut A, Aachen, GermanyA. Albert, M. Brodski, E. Dietz-Laursonn, D. Duchardt, M. Endres, M. Erdmann, S. Erdweg, T. Esch, R. Fischer, A. Güth,M. Hamer, T. Hebbeker, C. Heidemann, K. Hoepfner, S. Knutzen, M. Merschmeyer, A. Meyer, P. Millet, S. Mukherjee,M. Olschewski, K. Padeken, T. Pook, M. Radziej, H. Reithler, M. Rieger, F. Scheuch, D. Teyssier, S. Thüer

RWTH Aachen University, III. Physikalisches Institut B, Aachen, GermanyG. Flügge, B. Kargoll, T. Kress, A. Künsken, J. Lingemann, T. Müller, A. Nehrkorn, A. Nowack, C. Pistone, O. Pooth,A. Stahl11

Deutsches Elektronen-Synchrotron, Hamburg, GermanyM. Aldaya Martin, T. Arndt, C. Asawatangtrakuldee, K. Beernaert, O. Behnke, U. Behrens, A. A. Bin Anuar, K. Borras12,V. Botta, A. Campbell, P. Connor, C. Contreras-Campana, F. Costanza, C. Diez Pardos, G. Eckerlin, D. Eckstein,T. Eichhorn, E. Eren, E. Gallo13, J. Garay Garcia, A. Geiser, A. Gizhko, J. M. Grados Luyando, A. Grohsjean,P. Gunnellini, A. Harb, J. Hauk, M. Hempel14, H. Jung, A. Kalogeropoulos, M. Kasemann, J. Keaveney, C. Kleinwort,I. Korol, D. Krücker, W. Lange, A. Lelek, T. Lenz, J. Leonard, K. Lipka, W. Lohmann14, R. Mankel,I.-A. Melzer-Pellmann, A. B. Meyer, G. Mittag, J. Mnich, A. Mussgiller, E. Ntomari, D. Pitzl, R. Placakyte, A. Raspereza,B. Roland, M. Savitskyi, P. Saxena, R. Shevchenko, S. Spannagel, N. Stefaniuk, G. P. Van Onsem, R. Walsh, Y. Wen,K. Wichmann, C. Wissing, O. Zenaiev

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University of Hamburg, Hamburg, GermanyS. Bein, V. Blobel, M. Centis Vignali, A. R. Draeger, T. Dreyer, E. Garutti, D. Gonzalez, J. Haller, A. Hinzmann,M. Hoffmann, A. Junkes, A. Karavdina, R. Klanner, R. Kogler, N. Kovalchuk, S. Kurz, T. Lapsien, I. Marchesini,D. Marconi, M. Meyer, M. Niedziela, D. Nowatschin, F. Pantaleo11, T. Peiffer, A. Perieanu, C. Scharf, P. Schleper,A. Schmidt, S. Schumann, J. Schwandt, J. Sonneveld, H. Stadie, G. Steinbrück, F. M. Stober, M. Stöver, H. Tholen,D. Troendle, E. Usai, L. Vanelderen, A. Vanhoefer, B. Vormwald

Institut für Experimentelle Kernphysik, Karlsruhe, GermanyM. Akbiyik, C. Barth, S. Baur, E. Butz, R. Caspart, T. Chwalek, F. Colombo, W. De Boer, A. Dierlamm, B. Freund,R. Friese, M. Giffels, A. Gilbert, D. Haitz, F. Hartmann11, S. M. Heindl, U. Husemann, F. Kassel11, S. Kudella,H. Mildner, M. U. Mozer, Th. Müller, M. Plagge, G. Quast, K. Rabbertz, M. Schröder, I. Shvetsov, G. Sieber,H. J. Simonis, R. Ulrich, S. Wayand, M. Weber, T. Weiler, S. Williamson, C. Wöhrmann, R. Wolf

Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, GreeceG. Anagnostou, G. Daskalakis, T. Geralis, V. A. Giakoumopoulou, A. Kyriakis, D. Loukas, I. Topsis-Giotis

National and Kapodistrian University of Athens, Athens, GreeceS. Kesisoglou, A. Panagiotou, N. Saoulidou

University of Ioánnina, Ioánnina, GreeceI. Evangelou, C. Foudas, P. Kokkas, N. Manthos, I. Papadopoulos, E. Paradas, J. Strologas, F. A. Triantis

MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös Loránd University, Budapest, HungaryM. Csanad, N. Filipovic, G. Pasztor

Wigner Research Centre for Physics, Budapest, HungaryG. Bencze, C. Hajdu, D. Horvath15, Á. Hunyadi, F. Sikler, V. Veszpremi, G. Vesztergombi16, A. J. Zsigmond

Institute of Nuclear Research ATOMKI, Debrecen, HungaryN. Beni, S. Czellar, J. Karancsi17, A. Makovec, J. Molnar, Z. Szillasi

Institute of Physics, University of Debrecen, Debrecen, HungaryM. Bartók16, P. Raics, Z. L. Trocsanyi, B. Ujvari

Indian Institute of Science (IISc), Bangalore, IndiaS. Choudhury, J. R. Komaragiri

National Institute of Science Education and Research, Bhubaneswar, IndiaS. Bahinipati18, S. Bhowmik, P. Mal, K. Mandal, A. Nayak19, D. K. Sahoo18, N. Sahoo, S. K. Swain

Panjab University, Chandigarh, IndiaS. Bansal, S. B. Beri, V. Bhatnagar, U. Bhawandeep, R. Chawla, N. Dhingra, A. K. Kalsi, A. Kaur, M. Kaur, R. Kumar,P. Kumari, A. Mehta, J. B. Singh, G. Walia

University of Delhi, Delhi, IndiaAshok Kumar, Aashaq Shah, A. Bhardwaj, S. Chauhan, B. C. Choudhary, R. B. Garg, S. Keshri, A. Kumar, S. Malhotra,M. Naimuddin, K. Ranjan, R. Sharma, V. Sharma

Saha Institute of Nuclear Physics, HBNI, Kolkata, IndiaR. Bhardwaj, R. Bhattacharya, S. Bhattacharya, S. Dey, S. Dutt, S. Dutta, S. Ghosh, N. Majumdar, A. Modak, K. Mondal,S. Mukhopadhyay, S. Nandan, A. Purohit, A. Roy, D. Roy, S. Roy Chowdhury, S. Sarkar, M. Sharan, S. Thakur

Indian Institute of Technology Madras, Chennai, IndiaP. K. Behera

Bhabha Atomic Research Centre, Mumbai, IndiaR. Chudasama, D. Dutta, V. Jha, V. Kumar, A. K. Mohanty11, P. K. Netrakanti, L. M. Pant, P. Shukla, A. Topkar

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Tata Institute of Fundamental Research-A, Mumbai, IndiaT. Aziz, S. Dugad, B. Mahakud, S. Mitra, G. B. Mohanty, B. Parida, N. Sur, B. Sutar

Tata Institute of Fundamental Research-B, Mumbai, IndiaS. Banerjee, S. Bhattacharya, S. Chatterjee, P. Das, M. Guchait, Sa. Jain, S. Kumar, M. Maity20, G. Majumder,K. Mazumdar, T. Sarkar20, N. Wickramage21

Indian Institute of Science Education and Research (IISER), Pune, IndiaS. Chauhan, S. Dube, V. Hegde, A. Kapoor, K. Kothekar, S. Pandey, A. Rane, S. Sharma

Institute for Research in Fundamental Sciences (IPM), Tehran, IranS. Chenarani22, E. Eskandari Tadavani, S. M. Etesami22, M. Khakzad, M. Mohammadi Najafabadi, M. Naseri,S. Paktinat Mehdiabadi23, F. Rezaei Hosseinabadi, B. Safarzadeh24, M. Zeinali

University College Dublin, Dublin, IrelandM. Felcini, M. Grunewald

INFN Sezione di Baria , Università di Barib, Politecnico di Baric, Bari, ItalyM. Abbresciaa ,b, C. Calabriaa ,b, C. Caputoa ,b, A. Colaleoa , D. Creanzaa ,c, L. Cristellaa ,b, N. De Filippisa ,c,M. De Palmaa ,b, F. Erricoa ,b, S. Lezkia ,b, L. Fiorea , G. Iasellia ,c, G. Maggia ,c, M. Maggia , G. Minielloa ,b, S. Mya ,b,S. Nuzzoa ,b, A. Pompilia ,b, G. Pugliesea ,c, R. Radognaa ,b, A. Ranieria , G. Selvaggia ,b, A. Sharmaa , L. Silvestrisa ,11,R. Vendittia , P. Verwilligena

INFN Sezione di Bolognaa , Università di Bolognab, Bologna, ItalyG. Abbiendia , C. Battilana, D. Bonacorsia ,b, S. Braibant-Giacomellia ,b, L. Brigliadoria ,b, R. Campaninia ,b,P. Capiluppia ,b, A. Castroa ,b, F. R. Cavalloa , S. S. Chhibraa ,b, G. Codispotia ,b, M. Cuffiania ,b, G. M. Dallavallea ,F. Fabbria , A. Fanfania ,b, D. Fasanellaa ,b, P. Giacomellia , L. Guiduccia ,b, S. Marcellinia , G. Masettia , F. L. Navarriaa ,b,A. Perrottaa , A. M. Rossia ,b, T. Rovellia ,b, G. P. Sirolia ,b, N. Tosia ,b,11

INFN Sezione di Cataniaa , Università di Cataniab, Catania, ItalyS. Albergoa ,b, S. Costaa ,b, A. Di Mattiaa , F. Giordanoa ,b, R. Potenzaa ,b, A. Tricomia ,b, C. Tuvea ,b

INFN Sezione di Firenzea , Università di Firenzeb, Firenze, ItalyG. Barbaglia , K. Chatterjeea ,b, V. Ciullia ,b, C. Civininia , R. D’Alessandroa ,b, E. Focardia ,b, P. Lenzia ,b, M. Meschinia ,S. Paolettia , L. Russoa ,25, G. Sguazzonia , D. Stroma , L. Viliania ,b,11

INFN Laboratori Nazionali di Frascati, Frascati, ItalyL. Benussi, S. Bianco, F. Fabbri, D. Piccolo, F. Primavera11

INFN Sezione di Genovaa , Università di Genovab, Genova, ItalyV. Calvellia ,b, F. Ferroa , E. Robuttia , S. Tosia ,b

INFN Sezione di Milano-Bicoccaa , Università di Milano-Bicoccab, Milan, ItalyL. Brianzaa ,b, F. Brivioa ,b, V. Cirioloa ,b, M. E. Dinardoa ,b, S. Fiorendia ,b, S. Gennaia , A. Ghezzia ,b, P. Govonia ,b,M. Malbertia ,b, S. Malvezzia , R. A. Manzonia ,b, D. Menascea , L. Moronia , M. Paganonia ,b, K. Pauwelsa ,b, D. Pedrinia ,S. Pigazzinia ,b,26, S. Ragazzia ,b, T. Tabarelli de Fatisa ,b

INFN Sezione di Napolia , Università di Napoli ’Federico II’ b, Naples, Italy, Università della Basilicatac, Potenza,Italy, Università G. Marconid , Rome, ItalyS. Buontempoa , N. Cavalloa ,c, S. Di Guidaa ,d ,11, M. Espositoa ,b, F. Fabozzia ,c, F. Fiengaa ,b, A. O. M. Iorioa ,b,W. A. Khana , G. Lanzaa , L. Listaa , S. Meolaa ,d ,11, P. Paoluccia ,11, C. Sciaccaa ,b, F. Thyssena

INFN Sezione di Padovaa , Università di Padovab, Padua, Italy, Università di Trentoc, Trento, ItalyP. Azzia ,11, N. Bacchettaa , L. Benatoa ,b, M. Biasottoa ,27, D. Biselloa ,b, A. Bolettia ,b, R. Carlina ,b,A. Carvalho Antunes De Oliveiraa ,b, P. Checchiaa , M. Dall’Ossoa ,b, P. De Castro Manzanoa , T. Dorigoa , U. Dossellia ,S. Fantinela , F. Fanzagoa , U. Gasparinia ,b, S. Lacapraraa , M. Margonia ,b, A. T. Meneguzzoa ,b, N. Pozzobona ,b,P. Ronchesea ,b, R. Rossina ,b, F. Simonettoa ,b, E. Torassaa , M. Zanettia ,b, P. Zottoa ,b

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INFN Sezione di Paviaa , Università di Paviab, Pavia, ItalyA. Braghieria , F. Fallavollitaa ,b, A. Magnania ,b, P. Montagnaa ,b, S. P. Rattia ,b, V. Rea , M. Ressegotti, C. Riccardia ,b,P. Salvinia , I. Vaia ,b, P. Vituloa ,b

INFN Sezione di Perugiaa , Università di Perugiab, Perugia, ItalyL. Alunni Solestizia ,b, G. M. Bileia , D. Ciangottinia ,b, L. Fanòa ,b, P. Laricciaa ,b, R. Leonardia ,b, G. Mantovania ,b,V. Mariania ,b, M. Menichellia , A. Sahaa , A. Santocchiaa ,b, D. Spiga

INFN Sezione di Pisaa , Università di Pisab, Scuola Normale Superiore di Pisac, Pisa, ItalyK. Androsova , P. Azzurria ,11, G. Bagliesia , J. Bernardinia , T. Boccalia , L. Borrello, R. Castaldia , M. A. Cioccia ,b,R. Dell’Orsoa , G. Fedia , L. Gianninia ,c, A. Giassia , M. T. Grippoa ,25, F. Ligabuea ,c, T. Lomtadzea , E. Mancaa ,c,G. Mandorlia ,c, L. Martinia ,b, A. Messineoa ,b, F. Pallaa , A. Rizzia ,b, A. Savoy-Navarroa ,28, P. Spagnoloa , R. Tenchinia ,G. Tonellia ,b, A. Venturia , P. G. Verdinia

INFN Sezione di Romaa , Sapienza Università di Romab, Rome, ItalyL. Baronea ,b, F. Cavallaria , M. Cipriania ,b, D. Del Rea ,b,11, M. Diemoza , S. Gellia ,b, E. Longoa ,b, F. Margarolia ,b,B. Marzocchia ,b, P. Meridiania , G. Organtinia ,b, R. Paramattia ,b, F. Preiatoa ,b, S. Rahatloua ,b, C. Rovellia ,F. Santanastasioa ,b

INFN Sezione di Torinoa , Università di Torinob, Tourin, Italy, Università del Piemonte Orientalec, Novara, ItalyN. Amapanea ,b, R. Arcidiaconoa ,c,11, S. Argiroa ,b, M. Arneodoa ,c, N. Bartosika , R. Bellana ,b, C. Biinoa , N. Cartigliaa ,F. Cennaa ,b, M. Costaa ,b, R. Covarellia ,b, A. Deganoa ,b, N. Demariaa , B. Kiania ,b, C. Mariottia , S. Masellia ,E. Migliorea ,b, V. Monacoa ,b, E. Monteila ,b, M. Montenoa , M. M. Obertinoa ,b, L. Pachera ,b, N. Pastronea , M. Pelliccionia ,G. L. Pinna Angionia ,b, F. Raveraa ,b, A. Romeroa ,b, M. Ruspaa ,c, R. Sacchia ,b, K. Shchelinaa ,b, V. Solaa , A. Solanoa ,b,A. Staianoa , P. Traczyka ,b

INFN Sezione di Triestea , Università di Triesteb, Trieste, ItalyS. Belfortea , M. Casarsaa , F. Cossuttia , G. Della Riccaa ,b, A. Zanettia

Kyungpook National University, Daegu, KoreaD. H. Kim, G. N. Kim, M. S. Kim, J. Lee, S. Lee, S. W. Lee, Y. D. Oh, S. Sekmen, D. C. Son, Y. C. Yang

Chonbuk National University, Jeonju, KoreaA. Lee

Institute for Universe and Elementary Particles, Chonnam National University, Kwangju, KoreaH. Kim, D. H. Moon, G. Oh

Hanyang University, Seoul, KoreaJ. A. Brochero Cifuentes, J. Goh, T. J. Kim

Korea University, Seoul, KoreaS. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, Y. Jo, Y. Kim, K. Lee, K. S. Lee, S. Lee, J. Lim, S. K. Park, Y. Roh

Seoul National University, Seoul, KoreaJ. Almond, J. Kim, J. S. Kim, H. Lee, K. Lee, K. Nam, S. B. Oh, B. C. Radburn-Smith, S. h. Seo, U. K. Yang, H. D. Yoo,G. B. Yu

University of Seoul, Seoul, KoreaM. Choi, H. Kim, J. H. Kim, J. S. H. Lee, I. C. Park, G. Ryu

Sungkyunkwan University, Suwon, KoreaY. Choi, C. Hwang, J. Lee, I. Yu

Vilnius University, Vilnius, LithuaniaV. Dudenas, A. Juodagalvis, J. Vaitkus

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National Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, MalaysiaI. Ahmed, Z. A. Ibrahim, M. A. B. Md Ali29, F. Mohamad Idris30, W. A. T. Wan Abdullah, M. N. Yusli, Z. Zolkapli

Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, MexicoH. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-De La Cruz31, R. Lopez-Fernandez, J. Mejia Guisao,A. Sanchez-Hernandez

Universidad Iberoamericana, Mexico City, MexicoS. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia

Benemerita Universidad Autonoma de Puebla, Puebla, MexicoI. Pedraza, H. A. Salazar Ibarguen, C. Uribe Estrada

Universidad Autónoma de San Luis Potosí, San Luis Potosí, MexicoA. Morelos Pineda

University of Auckland, Auckland, New ZealandD. Krofcheck

University of Canterbury, Christchurch, New ZealandP. H. Butler

National Centre for Physics, Quaid-I-Azam University, Islamabad, PakistanA. Ahmad, M. Ahmad, Q. Hassan, H. R. Hoorani, S. Qazi, A. Saddique, M. Shoaib, M. Waqas

National Centre for Nuclear Research, Swierk, PolandH. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Górski, M. Kazana, K. Nawrocki, K. Romanowska-Rybinska,M. Szleper, P. Zalewski

Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Warsaw, PolandK. Bunkowski, A. Byszuk32, K. Doroba, A. Kalinowski, M. Konecki, J. Krolikowski, M. Misiura, M. Olszewski,A. Pyskir, M. Walczak

Laboratório de Instrumentação e Física Experimental de Partículas, Lisbon, PortugalP. Bargassa, C. Beirão Da Cruz E Silva, B. Calpas, A. Di Francesco, P. Faccioli, M. Gallinaro, J. Hollar, N. Leonardo,L. Lloret Iglesias, M. V. Nemallapudi, J. Seixas, O. Toldaiev, D. Vadruccio, J. Varela

Joint Institute for Nuclear Research, Dubna, RussiaS. Afanasiev, P. Bunin, M. Gavrilenko, I. Golutvin, I. Gorbunov, A. Kamenev, V. Karjavin, A. Lanev, A. Malakhov,V. Matveev33,34, V. Palichik, V. Perelygin, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, N. Voytishin, A. Zarubin

Petersburg Nuclear Physics Institute, Gatchina, St. Petersburg, RussiaY. Ivanov, V. Kim35, E. Kuznetsova36, P. Levchenko, V. Murzin, V. Oreshkin, I. Smirnov, V. Sulimov, L. Uvarov,S. Vavilov, A. Vorobyev

Institute for Nuclear Research, Moscow, RussiaYu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov, N. Krasnikov, A. Pashenkov, D. Tlisov,A. Toropin

Institute for Theoretical and Experimental Physics, Moscow, RussiaV. Epshteyn, V. Gavrilov, N. Lychkovskaya, V. Popov, I. Pozdnyakov, G. Safronov, A. Spiridonov, A. Stepennov,M. Toms, E. Vlasov, A. Zhokin

Moscow Institute of Physics and Technology, Moscow, RussiaT. Aushev, A. Bylinkin34

National Research Nuclear University ‘Moscow Engineering Physics Institute’ (MEPhI), Moscow, RussiaM. Chadeeva37, O. Markin, P. Parygin, D. Philippov, S. Polikarpov, V. Rusinov

P.N. Lebedev Physical Institute, Moscow, RussiaV. Andreev, M. Azarkin34, I. Dremin34, M. Kirakosyan34, A. Terkulov

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Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, RussiaA. Baskakov, A. Belyaev, E. Boos, M. Dubinin38, L. Dudko, A. Ershov, A. Gribushin, V. Klyukhin, O. Kodolova,I. Lokhtin, I. Miagkov, S. Obraztsov, S. Petrushanko, V. Savrin, A. Snigirev

Novosibirsk State University (NSU), Novosibirsk, RussiaV. Blinov39, Y. Skovpen39, D. Shtol39

State Research Center of Russian Federation, Institute for High Energy Physics, Protvino, RussiaI. Azhgirey, I. Bayshev, S. Bitioukov, D. Elumakhov, V. Kachanov, A. Kalinin, D. Konstantinov, V. Krychkine, V. Petrov,R. Ryutin, A. Sobol, S. Troshin, N. Tyurin, A. Uzunian, A. Volkov

Faculty of Physics and Vinca Institute of Nuclear Sciences, University of Belgrade, Belgrade, SerbiaP. Adzic40, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic, V. Rekovic

Centro de Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT), Madrid, SpainJ. Alcaraz Maestre, M. Barrio Luna, M. Cerrada, N. Colino, B. De La Cruz, A. Delgado Peris, A. Escalante Del Valle,C. Fernandez Bedoya, J. P. Fernández Ramos, J. Flix, M. C. Fouz, P. Garcia-Abia, O. Gonzalez Lopez, S. Goy Lopez,J. M. Hernandez, M. I. Josa, A. Pérez-Calero Yzquierdo, J. Puerta Pelayo, A. Quintario Olmeda, I. Redondo, L. Romero,M. S. Soares, A. Álvarez Fernández

Universidad Autónoma de Madrid, Madrid, SpainJ. F. de Trocóniz, M. Missiroli, D. Moran

Universidad de Oviedo, Oviedo, SpainJ. Cuevas, C. Erice, J. Fernandez Menendez, I. Gonzalez Caballero, J. R. González Fernández, E. Palencia Cortezon,S. Sanchez Cruz, I. Suárez Andrés, P. Vischia, J. M. Vizan Garcia

Instituto de Física de Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, SpainI. J. Cabrillo, A. Calderon, B. Chazin Quero, E. Curras, M. Fernandez, J. Garcia-Ferrero, G. Gomez, A. Lopez Virto,J. Marco, C. Martinez Rivero, P. Martinez Ruiz del Arbol, F. Matorras, J. Piedra Gomez, T. Rodrigo, A. Ruiz-Jimeno,L. Scodellaro, N. Trevisani, I. Vila, R. Vilar Cortabitarte

CERN, European Organization for Nuclear Research, Geneva, SwitzerlandD. Abbaneo, E. Auffray, P. Baillon, A. H. Ball, D. Barney, M. Bianco, P. Bloch, A. Bocci, C. Botta, T. Camporesi,R. Castello, M. Cepeda, G. Cerminara, E. Chapon, Y. Chen, D. d’Enterria, A. Dabrowski, V. Daponte, A. David,M. De Gruttola, A. De Roeck, E. Di Marco41, M. Dobson, B. Dorney, T. du Pree, M. Dünser, N. Dupont, A. Elliott-Peisert,P. Everaerts, G. Franzoni, J. Fulcher, W. Funk, D. Gigi, K. Gill, F. Glege, D. Gulhan, S. Gundacker, M. Guthoff, P. Harris,J. Hegeman, V. Innocente, P. Janot, O. Karacheban14, J. Kieseler, H. Kirschenmann, V. Knünz, A. Kornmayer11,M. J. Kortelainen, C. Lange, P. Lecoq, C. Lourenço, M. T. Lucchini, L. Malgeri, M. Mannelli, A. Martelli, F. Meijers,J. A. Merlin, S. Mersi, E. Meschi, P. Milenovic42, F. Moortgat, M. Mulders, H. Neugebauer, S. Orfanelli, L. Orsini,L. Pape, E. Perez, M. Peruzzi, A. Petrilli, G. Petrucciani, A. Pfeiffer, M. Pierini, A. Racz, T. Reis, G. Rolandi43,M. Rovere, H. Sakulin, C. Schäfer, C. Schwick, M. Seidel, M. Selvaggi, A. Sharma, P. Silva, P. Sphicas44, J. Steggemann,M. Stoye, M. Tosi, D. Treille, A. Triossi, A. Tsirou, V. Veckalns45, G. I. Veres16, M. Verweij, N. Wardle, W. D. Zeuner

Paul Scherrer Institut, Villigen, SwitzerlandW. Bertl†, K. Deiters, W. Erdmann, R. Horisberger, Q. Ingram, H. C. Kaestli, D. Kotlinski, U. Langenegger, T. Rohe,S. A. Wiederkehr

Institute for Particle Physics, ETH Zurich, Zurich, SwitzerlandF. Bachmair, L. Bäni, P. Berger, L. Bianchini, B. Casal, G. Dissertori, M. Dittmar, M. Donegà, C. Grab, C. Heidegger,D. Hits, J. Hoss, G. Kasieczka, T. Klijnsma, W. Lustermann, B. Mangano, M. Marionneau, M. T. Meinhard, D. Meister,F. Micheli, P. Musella, F. Nessi-Tedaldi, F. Pandolfi, J. Pata, F. Pauss, G. Perrin, L. Perrozzi, M. Quittnat, M. Rossini,M. Schönenberger, L. Shchutska, A. Starodumov46, V. R. Tavolaro, K. Theofilatos, M. L. Vesterbacka Olsson, R. Wallny,A. Zagozdzinska32, D. H. Zhu

Universität Zürich, Zurich, SwitzerlandT. K. Aarrestad, C. Amsler47, L. Caminada, M. F. Canelli, A. De Cosa, S. Donato, C. Galloni, T. Hreus, B. Kilminster,J. Ngadiuba, D. Pinna, G. Rauco, P. Robmann, D. Salerno, C. Seitz, A. Zucchetta

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National Central University, Chung-Li, TaiwanV. Candelise, T. H. Doan, Sh. Jain, R. Khurana, M. Konyushikhin, C. M. Kuo, W. Lin, A. Pozdnyakov, S. S. Yu

National Taiwan University (NTU), Taipei, TaiwanArun Kumar, P. Chang, Y. Chao, K. F. Chen, P. H. Chen, F. Fiori, W.-S. Hou, Y. Hsiung, Y. F. Liu, R.-S. Lu,M. Miñano Moya, E. Paganis, A. Psallidas, J. f. Tsai

Department of Physics, Faculty of Science, Chulalongkorn University, Bangkok, ThailandB. Asavapibhop, K. Kovitanggoon, G. Singh, N. Srimanobhas

Cukurova University-Physics Department, Science and Art Faculty, Adana, TurkeyA. Adiguzel48, F. Boran, S. Cerci49, S. Damarseckin, Z. S. Demiroglu, C. Dozen, I. Dumanoglu, S. Girgis, G. Gokbulut,Y. Guler, I. Hos50, E. E. Kangal51, O. Kara, A. Kayis Topaksu, U. Kiminsu, M. Oglakci, G. Onengut52, K. Ozdemir53,D. Sunar Cerci49, H. Topakli54, S. Turkcapar, I. S. Zorbakir, C. Zorbilmez

Physics Department, Middle East Technical University, Ankara, TurkeyB. Bilin, G. Karapinar55, K. Ocalan56, M. Yalvac, M. Zeyrek

Bogazici University, Istanbul, TurkeyE. Gülmez, M. Kaya57, O. Kaya58, S. Tekten, E. A. Yetkin59

Istanbul Technical University, Istanbul, TurkeyM. N. Agaras, S. Atay, A. Cakir, K. Cankocak

Institute for Scintillation Materials of National Academy of Science of Ukraine, Kharkov, UkraineB. Grynyov

National Scientific Center, Kharkov Institute of Physics and Technology, Kharkov, UkraineL. Levchuk, P. Sorokin

University of Bristol, Bristol, UKR. Aggleton, F. Ball, L. Beck, J. J. Brooke, D. Burns, E. Clement, D. Cussans, H. Flacher, J. Goldstein, M. Grimes,G. P. Heath, H. F. Heath, J. Jacob, L. Kreczko, C. Lucas, D. M. Newbold60, S. Paramesvaran, A. Poll, T. Sakuma,S. Seif El Nasr-storey, D. Smith, V. J. Smith

Rutherford Appleton Laboratory, Didcot, UKK. W. Bell, A. Belyaev61, C. Brew, R. M. Brown, L. Calligaris, D. Cieri, D. J. A. Cockerill, J. A. Coughlan, K. Harder,S. Harper, E. Olaiya, D. Petyt, C. H. Shepherd-Themistocleous, A. Thea, I. R. Tomalin, T. Williams

Imperial College, London, UKM. Baber, R. Bainbridge, S. Breeze, O. Buchmuller, A. Bundock, S. Casasso, M. Citron, D. Colling, L. Corpe, P. Dauncey,G. Davies, A. De Wit, M. Della Negra, R. Di Maria, P. Dunne, A. Elwood, D. Futyan, Y. Haddad, G. Hall, G. Iles,T. James, R. Lane, C. Laner, L. Lyons, A.-M. Magnan, S. Malik, L. Mastrolorenzo, T. Matsushita, J. Nash, A. Nikitenko46,J. Pela, M. Pesaresi, D. M. Raymond, A. Richards, A. Rose, E. Scott, C. Seez, A. Shtipliyski, S. Summers, A. Tapper,K. Uchida, M. Vazquez Acosta62, T. Virdee11, D. Winterbottom, J. Wright, S. C. Zenz

Brunel University, Uxbridge, UKJ. E. Cole, P. R. Hobson, A. Khan, P. Kyberd, I. D. Reid, P. Symonds, L. Teodorescu, M. Turner

Baylor University, Waco, USAA. Borzou, K. Call, J. Dittmann, K. Hatakeyama, H. Liu, N. Pastika

Catholic University of America, Washington, DC, USAR. Bartek, A. Dominguez

The University of Alabama, Tuscaloosa, USAA. Buccilli, S. I. Cooper, C. Henderson, P. Rumerio, C. West

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Boston University, Boston, USAD. Arcaro, A. Avetisyan, T. Bose, D. Gastler, D. Rankin, C. Richardson, J. Rohlf, L. Sulak, D. Zou

Brown University, Providence, USAG. Benelli, D. Cutts, A. Garabedian, J. Hakala, U. Heintz, J. M. Hogan, K. H. M. Kwok, E. Laird, G. Landsberg, Z. Mao,M. Narain, S. Piperov, S. Sagir, R. Syarif, D. Yu

University of California, Davis, CA, USAR. Band, C. Brainerd, D. Burns, M. Calderon De La Barca Sanchez, M. Chertok, J. Conway, R. Conway, P. T. Cox,R. Erbacher, C. Flores, G. Funk, M. Gardner, W. Ko, R. Lander, C. Mclean, M. Mulhearn, D. Pellett, J. Pilot, S. Shalhout,M. Shi, J. Smith, M. Squires, D. Stolp, K. Tos, M. Tripathi, Z. Wang

University of California, Los Angeles, USAM. Bachtis, C. Bravo, R. Cousins, A. Dasgupta, A. Florent, J. Hauser, M. Ignatenko, N. Mccoll, D. Saltzberg,C. Schnaible, V. Valuev

University of California, Riverside, CA, USAE. Bouvier, K. Burt, R. Clare, J. Ellison, J. W. Gary, S. M. A. Ghiasi Shirazi, G. Hanson, J. Heilman, P. Jandir, E. Kennedy,F. Lacroix, O. R. Long, M. Olmedo Negrete, M. I. Paneva, A. Shrinivas, W. Si, L. Wang, H. Wei, S. Wimpenny, B. R. Yates

University of California, San Diego, La Jolla, USAJ. G. Branson, S. Cittolin, M. Derdzinski, B. Hashemi, A. Holzner, D. Klein, G. Kole, V. Krutelyov, J. Letts, I. Macneill,M. Masciovecchio, D. Olivito, S. Padhi, M. Pieri, M. Sani, V. Sharma, S. Simon, M. Tadel, A. Vartak, S. Wasserbaech63,C. Welke, J. Wood, F. Würthwein, A. Yagil, G. Zevi Della Porta

University of California, Santa Barbara - Department of Physics, Santa Barbara, USAN. Amin, R. Bhandari, J. Bradmiller-Feld, C. Campagnari, A. Dishaw, V. Dutta, M. Franco Sevilla, C. George, F. Golf,L. Gouskos, J. Gran, R. Heller, J. Incandela, S. D. Mullin, A. Ovcharova, H. Qu, J. Richman, D. Stuart, I. Suarez, J. Yoo

California Institute of Technology, Pasadena, USAD. Anderson, J. Bendavid, A. Bornheim, J. M. Lawhorn, H. B. Newman, T. Nguyen, C. Pena, M. Spiropulu, J. R. Vlimant,S. Xie, Z. Zhang, R. Y. Zhu

Carnegie Mellon University, Pittsburgh, USAM. B. Andrews, T. Ferguson, T. Mudholkar, M. Paulini, J. Russ, M. Sun, H. Vogel, I. Vorobiev, M. Weinberg

University of Colorado Boulder, Boulder, USAJ. P. Cumalat, W. T. Ford, F. Jensen, M. Krohn, S. Leontsinis, T. Mulholland, K. Stenson, S. R. Wagner

Cornell University, Ithaca, USAJ. Alexander, J. Chaves, J. Chu, S. Dittmer, K. Mcdermott, N. Mirman, J. R. Patterson, A. Rinkevicius, A. Ryd,L. Skinnari, L. Soffi, S. M. Tan, Z. Tao, J. Thom, J. Tucker, P. Wittich, M. Zientek

Fermi National Accelerator Laboratory, Batavia, USAS. Abdullin, M. Albrow, G. Apollinari, A. Apresyan, A. Apyan, S. Banerjee, L. A. T. Bauerdick, A. Beretvas, J. Berryhill,P. C. Bhat, G. Bolla, K. Burkett, J. N. Butler, A. Canepa, G. B. Cerati, H. W. K. Cheung, F. Chlebana, M. Cremonesi,J. Duarte, V. D. Elvira, J. Freeman, Z. Gecse, E. Gottschalk, L. Gray, D. Green, S. Grünendahl, O. Gutsche, R. M. Harris,S. Hasegawa, J. Hirschauer, Z. Hu, B. Jayatilaka, S. Jindariani, M. Johnson, U. Joshi, B. Klima, B. Kreis, S. Lammel,D. Lincoln, R. Lipton, M. Liu, T. Liu, R. Lopes De Sá, J. Lykken, K. Maeshima, N. Magini, J. M. Marraffino,S. Maruyama, D. Mason, P. McBride, P. Merkel, S. Mrenna, S. Nahn, V. O’Dell, K. Pedro, O. Prokofyev, G. Rakness,L. Ristori, B. Schneider, E. Sexton-Kennedy, A. Soha, W. J. Spalding, L. Spiegel, S. Stoynev, J. Strait, N. Strobbe,L. Taylor, S. Tkaczyk, N. V. Tran, L. Uplegger, E. W. Vaandering, C. Vernieri, M. Verzocchi, R. Vidal, M. Wang,H. A. Weber, A. Whitbeck

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University of Florida, Gainesville, USAD. Acosta, P. Avery, P. Bortignon, A. Brinkerhoff, A. Carnes, M. Carver, D. Curry, S. Das, R. D. Field, I. K. Furic,J. Konigsberg, A. Korytov, K. Kotov, P. Ma, K. Matchev, H. Mei, G. Mitselmakher, D. Rank, D. Sperka, N. Terentyev,L. Thomas, J. Wang, S. Wang, J. Yelton

Florida International University, Miami, USAY. R. Joshi, S. Linn, P. Markowitz, G. Martinez, J. L. Rodriguez

Florida State University, Tallahassee, USAA. Ackert, T. Adams, A. Askew, S. Hagopian, V. Hagopian, K. F. Johnson, T. Kolberg, T. Perry, H. Prosper, A. Santra,R. Yohay

Florida Institute of Technology, Melbourne, USAM. M. Baarmand, V. Bhopatkar, S. Colafranceschi, M. Hohlmann, D. Noonan, T. Roy, F. Yumiceva

University of Illinois at Chicago (UIC), Chicago, USAM. R. Adams, L. Apanasevich, D. Berry, R. R. Betts, R. Cavanaugh, X. Chen, O. Evdokimov, C. E. Gerber, D. A. Hangal,D. J. Hofman, K. Jung, J Kamin, I. D. Sandoval Gonzalez, M. B. Tonjes, H. Trauger, N. Varelas, H. Wang, Z. Wu,M. Zakaria, J. Zhang

The University of Iowa, Iowa City, USAB. Bilki64, W. Clarida, K. Dilsiz65, S. Durgut, R. P. Gandrajula, M. Haytmyradov, V. Khristenko, J.-P. Merlo,H. Mermerkaya66, A. Mestvirishvili, A. Moeller, J. Nachtman, H. Ogul67, Y. Onel, F. Ozok68, A. Penzo, C. Snyder,E. Tiras, J. Wetzel, K. Yi

Johns Hopkins University, Baltimore, USAB. Blumenfeld, A. Cocoros, N. Eminizer, D. Fehling, L. Feng, A. V. Gritsan, P. Maksimovic, J. Roskes, U. Sarica,M. Swartz, M. Xiao, C. You

The University of Kansas, Lawrence, USAA. Al-bataineh, P. Baringer, A. Bean, S. Boren, J. Bowen, J. Castle, S. Khalil, A. Kropivnitskaya, D. Majumder,W. Mcbrayer, M. Murray, C. Royon, S. Sanders, E. Schmitz, R. Stringer, J. D. Tapia Takaki, Q. Wang

Kansas State University, Manhattan, USAA. Ivanov, K. Kaadze, Y. Maravin, A. Mohammadi, L. K. Saini, N. Skhirtladze, S. Toda

Lawrence Livermore National Laboratory, Livermore, USAF. Rebassoo, D. Wright

University of Maryland, College Park, USAC. Anelli, A. Baden, O. Baron, A. Belloni, B. Calvert, S. C. Eno, C. Ferraioli, N. J. Hadley, S. Jabeen, G. Y. Jeng,R. G. Kellogg, J. Kunkle, A. C. Mignerey, F. Ricci-Tam, Y. H. Shin, A. Skuja, S. C. Tonwar

Massachusetts Institute of Technology, Cambridge, USAD. Abercrombie, B. Allen, V. Azzolini, R. Barbieri, A. Baty, R. Bi, S. Brandt, W. Busza, I. A. Cali, M. D’Alfonso,Z. Demiragli, G. Gomez Ceballos, M. Goncharov, D. Hsu, Y. Iiyama, G. M. Innocenti, M. Klute, D. Kovalskyi, Y. S. Lai,Y.-J. Lee, A. Levin, P. D. Luckey, B. Maier, A. C. Marini, C. Mcginn, C. Mironov, S. Narayanan, X. Niu, C. Paus,C. Roland, G. Roland, J. Salfeld-Nebgen, G. S. F. Stephans, K. Tatar, D. Velicanu, J. Wang, T. W. Wang, B. Wyslouch

University of Minnesota, Minneapolis, USAA. C. Benvenuti, R. M. Chatterjee, A. Evans, P. Hansen, S. Kalafut, Y. Kubota, Z. Lesko, J. Mans, S. Nourbakhsh,N. Ruckstuhl, R. Rusack, J. Turkewitz

University of Mississippi, Oxford, USAJ. G. Acosta, S. Oliveros

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University of Nebraska-Lincoln, Lincoln, USAE. Avdeeva, K. Bloom, D. R. Claes, C. Fangmeier, R. Gonzalez Suarez, R. Kamalieddin, I. Kravchenko, J. Monroy,J. E. Siado, G. R. Snow, B. Stieger

State University of New York at Buffalo, Buffalo, USAM. Alyari, J. Dolen, A. Godshalk, C. Harrington, I. Iashvili, D. Nguyen, A. Parker, S. Rappoccio, B. Roozbahani

Northeastern University, Boston, USAG. Alverson, E. Barberis, A. Hortiangtham, A. Massironi, D. M. Morse, D. Nash, T. Orimoto, R. Teixeira De Lima,D. Trocino, R.-J. Wang, D. Wood

Northwestern University, Evanston, USAS. Bhattacharya, O. Charaf, K. A. Hahn, N. Mucia, N. Odell, B. Pollack, M. H. Schmitt, K. Sung, M. Trovato, M. Velasco

University of Notre Dame, Notre Dame, USAN. Dev, M. Hildreth, K. Hurtado Anampa, C. Jessop, D. J. Karmgard, N. Kellams, K. Lannon, N. Loukas, N. Marinelli,F. Meng, C. Mueller, Y. Musienko33, M. Planer, A. Reinsvold, R. Ruchti, G. Smith, S. Taroni, M. Wayne, M. Wolf,A. Woodard

The Ohio State University, Columbus, USAJ. Alimena, L. Antonelli, B. Bylsma, L. S. Durkin, S. Flowers, B. Francis, A. Hart, C. Hill, W. Ji, B. Liu, W. Luo,D. Puigh, B. L. Winer, H. W. Wulsin

Princeton University, Princeton, USAA. Benaglia, S. Cooperstein, P. Elmer, J. Hardenbrook, P. Hebda, S. Higginbotham, D. Lange, J. Luo, D. Marlow, K. Mei,I. Ojalvo, J. Olsen, C. Palmer, P. Piroué, D. Stickland, A. Svyatkovskiy, C. Tully

University of Puerto Rico, Mayagüez, USAS. Malik, S. Norberg

Purdue University, West Lafayette, USAA. Barker, V. E. Barnes, S. Folgueras, L. Gutay, M. K. Jha, M. Jones, A. W. Jung, A. Khatiwada, D. H. Miller,N. Neumeister, J. F. Schulte, J. Sun, F. Wang, W. Xie

Purdue University Northwest, Hammond, USAT. Cheng, N. Parashar, J. Stupak

Rice University, Houston, USAA. Adair, B. Akgun, Z. Chen, K. M. Ecklund, F. J. M. Geurts, M. Guilbaud, W. Li, B. Michlin, M. Northup, B. P. Padley,J. Roberts, J. Rorie, Z. Tu, J. Zabel

University of Rochester, Rochester, USAA. Bodek, P. de Barbaro, R. Demina, Y. t. Duh, T. Ferbel, M. Galanti, A. Garcia-Bellido, J. Han, O. Hindrichs,A. Khukhunaishvili, K. H. Lo, P. Tan, M. Verzetti

The Rockefeller University, New York, USAR. Ciesielski, K. Goulianos, C. Mesropian

Rutgers, The State University of New Jersey, Piscataway, USAA. Agapitos, J. P. Chou, Y. Gershtein, T. A. Gómez Espinosa, E. Halkiadakis, M. Heindl, E. Hughes, S. Kaplan,R. Kunnawalkam Elayavalli, S. Kyriacou, A. Lath, R. Montalvo, K. Nash, M. Osherson, H. Saka, S. Salur, S. Schnetzer,D. Sheffield, S. Somalwar, R. Stone, S. Thomas, P. Thomassen, M. Walker

University of Tennessee, Knoxville, USAM. Foerster, J. Heideman, G. Riley, K. Rose, S. Spanier, K. Thapa

Texas A&M University, College Station, USAO. Bouhali69, A. Castaneda Hernandez69, A. Celik, M. Dalchenko, M. De Mattia, A. Delgado, S. Dildick, R. Eusebi,J. Gilmore, T. Huang, T. Kamon70, R. Mueller, Y. Pakhotin, R. Patel, A. Perloff, L. Perniè, D. Rathjens, A. Safonov,A. Tatarinov, K. A. Ulmer

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Texas Tech University, Lubbock, USAN. Akchurin, J. Damgov, F. De Guio, P. R. Dudero, J. Faulkner, E. Gurpinar, S. Kunori, K. Lamichhane, S. W. Lee,T. Libeiro, T. Peltola, S. Undleeb, I. Volobouev, Z. Wang

Vanderbilt University, Nashville, USAS. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, P. Sheldon, S. Tuo, J. Velkovska, Q. Xu

University of Virginia, Charlottesville, USAM. W. Arenton, P. Barria, B. Cox, R. Hirosky, A. Ledovskoy, H. Li, C. Neu, T. Sinthuprasith, X. Sun, Y. Wang, E. Wolfe,F. Xia

Wayne State University, Detroit, USAC. Clarke, R. Harr, P. E. Karchin, J. Sturdy, S. Zaleski

University of Wisconsin - Madison, Madison, WI, USAJ. Buchanan, C. Caillol, S. Dasu, L. Dodd, S. Duric, B. Gomber, M. Grothe, M. Herndon, A. Hervé, U. Hussain,P. Klabbers, A. Lanaro, A. Levine, K. Long, R. Loveless, G. A. Pierro, G. Polese, T. Ruggles, A. Savin, N. Smith,W. H. Smith, D. Taylor, N. Woods

† Deceased

1: Also at Vienna University of Technology, Vienna, Austria2: Also at State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, China3: Also at Universidade Estadual de Campinas, Campinas, Brazil4: Also at Universidade Federal de Pelotas, Pelotas, Brazil5: Also at Université Libre de Bruxelles, Brussels, Belgium6: Also at Joint Institute for Nuclear Research, Dubna, Russia7: Now at Cairo University, Cairo, Egypt8: Also at Zewail City of Science and Technology, Zewail, Egypt9: Also at Université de Haute Alsace, Mulhouse, France

10: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia11: Also at CERN, European Organization for Nuclear Research, Geneva, Switzerland12: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany13: Also at University of Hamburg, Hamburg, Germany14: Also at Brandenburg University of Technology, Cottbus, Germany15: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary16: Also at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös Loránd University, Budapest, Hungary17: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary18: Also at Indian Institute of Technology Bhubaneswar, Bhubaneswar, India19: Also at Institute of Physics, Bhubaneswar, India20: Also at University of Visva-Bharati, Santiniketan, India21: Also at University of Ruhuna, Matara, Sri Lanka22: Also at Isfahan University of Technology, Isfahan, Iran23: Also at Yazd University, Yazd, Iran24: Also at Plasma Physics Research Center, Science and Research Branch, Islamic Azad University, Tehran, Iran25: Also at Università degli Studi di Siena, Siena, Italy26: Also at INFN Sezione di Milano-Bicocca; Università di Milano-Bicocca, Milan, Italy27: Also at Laboratori Nazionali di Legnaro dell’INFN, Legnaro, Italy28: Also at Purdue University, West Lafayette, USA29: Also at International Islamic University of Malaysia, Kuala Lumpur, Malaysia30: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia31: Also at Consejo Nacional de Ciencia y Tecnología, Mexico City, Mexico32: Also at Warsaw University of Technology, Institute of Electronic Systems, Warsaw, Poland33: Also at Institute for Nuclear Research, Moscow, Russia34: Now at National Research Nuclear University ‘Moscow Engineering Physics Institute’ (MEPhI), Moscow, Russia35: Also at St. Petersburg State Polytechnical University, St. Petersburg, Russia

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36: Also at University of Florida, Gainesville, USA37: Also at P.N. Lebedev Physical Institute, Moscow, Russia38: Also at California Institute of Technology, Pasadena, USA39: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia40: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia41: Also at INFN Sezione di Roma;Sapienza Università di Roma, Rome, Italy42: Also at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia43: Also at Scuola Normale e Sezione dell’INFN, Pisa, Italy44: Also at National and Kapodistrian University of Athens, Athens, Greece45: Also at Riga Technical University, Riga, Latvia46: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia47: Also at Albert Einstein Center for Fundamental Physics, Bern, Switzerland48: Also at Istanbul University, Faculty of Science, Istanbul, Turkey49: Also at Adiyaman University, Adiyaman, Turkey50: Also at Istanbul Aydin University, Istanbul, Turkey51: Also at Mersin University, Mersin, Turkey52: Also at Cag University, Mersin, Turkey53: Also at Piri Reis University, Istanbul, Turkey54: Also at Gaziosmanpasa University, Tokat, Turkey55: Also at Izmir Institute of Technology, Izmir, Turkey56: Also at Necmettin Erbakan University, Konya, Turkey57: Also at Marmara University, Istanbul, Turkey58: Also at Kafkas University, Kars, Turkey59: Also at Istanbul Bilgi University, Istanbul, Turkey60: Also at Rutherford Appleton Laboratory, Didcot, UK61: Also at School of Physics and Astronomy, University of Southampton, Southampton, UK62: Also at Instituto de Astrofísica de Canarias, La Laguna, Spain63: Also at Utah Valley University, Orem, USA64: Also at Beykent University, Istanbul, Turkey65: Also at Bingol University, Bingol, Turkey66: Also at Erzincan University, Erzincan, Turkey67: Also at Sinop University, Sinop, Turkey68: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey69: Also at Texas A&M University at Qatar, Doha, Qatar70: Also at Kyungpook National University, Daegu, Korea

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