JHEP01(2015)069 ± → 52 . W = 0 ). Springer . µ in the same b ¯ b January 14, 2015 = 7 and 8 TeV, : November 11, 2014 November 21, 2014 September 23, 2014 s 14 (syst → . : : : √ 0 Z ± ) . 10.1007/JHEP01(2015)069 production, where Revised Published Received Accepted doi: H ) 09 (stat collisions at . 0 W/Z pp ± production with 74 . Published for SISSA by production with the Z from ) 1 − H W/Z ) W/Z ( decay of the Standard Model Higgs boson is performed . The observed (expected) deviation from the background- b ¯ b decay of the Standard Model Higgs νν b ¯ → b Z ) for a Higgs boson mass of 125.36 GeV. The analysis procedure is . . 3 and 1409.6212 24 (syst . Hadron-Hadron Scattering 0 ee/µµ A search for the , Copyright CERN, ± [email protected] → ) . Z , 32 (stat E-mail: . Article funded by SCOAP Open Access for the benefit of the ATLAS Collaboration. ArXiv ePrint: 0 validated by a measurement offinal the states as yield for of the ( to Higgs the boson Standard search, Model from expectation which the is ratio found of to the beKeywords: observed 0 signal yield integrated luminosities used are 4.7respectively. and The 20.3 fb processeseν/µν considered are associated ( only hypothesis corresponds to aof significance the of measured 1.4 signal (2.6) yield standard to deviations and the the Standard ratio Model expectation is found to be Abstract: with the ATLAS experiment using the full dataset recorded at the LHC in Run 1. The The ATLAS collaboration ATLAS detector Search for the boson in associated JHEP01(2015)069 53 36 35 29 21 55 50 25 46 58 40 – i – 23 3 34 50 51 34 50 51 21 6 3 14 42 44 42 53 50 8 1 60 11.1 Nominal results 11.2 Cross-check with the11.3 dijet-mass analysis Cross-check with the diboson analysis 10.2 Event selection 10.3 Background composition and10.4 modelling Systematic uncertainties 10.5 Statistical procedure 9.2 Technical details 9.3 Cross checks using diboson production 10.1 Object reconstruction 8.3 Uncertainties on8.4 the modelling of Uncertainties the on simulated the backgrounds signal modelling 9.1 General aspects 7.3 Distributions in7.4 the dijet-mass analysis Distributions in the multivariate analysis 8.1 Experimental uncertainties 8.2 Uncertainties on the multijet backgrounds 7.1 Multijet background 7.2 Corrections to the simulation 12 Summary 11 Results 10 Analysis of the 7 TeV data 9 Statistical procedure 8 Systematic uncertainties 6 Multivariate analysis 7 Background composition and modelling 3 Data and simulated samples 4 Object reconstruction 5 Event selection Contents 1 Introduction 2 The ATLAS detector JHEP01(2015)069 , ]. is 9 for `ν b – b 7 σ decay → b → b W H → ) collisions at H pp ]. 10 ). It is also essential to verify ]. In addition to the increase in ]. Recently, the CMS experiment production in the 18 16 WW production of the SM Higgs boson H from proton-proton ( ) 1 H → = 125 GeV [ − ) ]. Since then, more precise measurements H W/Z H 6 , m decay mode with a significance of 2.1 decays is therefore crucial for constraining, 5 W/Z decay mode of the Higgs boson at a level of b b b b = 125 GeV [ – 1 – , and ττ ) for H → → σ m ZZ H H ], the overall Higgs boson decay width and, in a global for → ] of the Standard Model (SM) remained an unconfirmed , can be efficiently used for triggering and background 12 σ 4 H – νν 1 , 71 61 → γγ ]. The CDF and D0 experiments at the Tevatron reported an Z → 15 ]. Accessing , H 11 14 ]. decay mode is predicted in the SM to have a branching ratio of 58% ), and b 17 b e, µ → = ], offers a viable alternative because leptonic decays of the vector boson, decay mode is presented, using the full integrated luminosity accumulated by ` H ( 13 = 125 GeV [ b [ b `` H Z = 125 GeV [ In this paper, a search for associated ( The m or → H 7 TeV dataset has alreadythe been amount published of by data ATLASanalysis analysed, [ improvements. the Some update of presentedare the in available improvements this only to for paper the the benefitstwo object 8 datasets. from TeV reconstruction, dataset, numerous however, which leads to separate analysis strategies for the reported an excess ofm events in the in the ATLAS during Run 1 ofcentre-of-mass the energies LHC: of 4.7 7 and and 20.3 8 fb TeV in 2011 and 2012, respectively. An analysis of the W Z reduction purposes [ excess of events inmode their at search a significance for level associated of ( 2.8 fit to all accessiblefor combinations measurements of of absolute Higgsnot Higgs boson feasible boson production at couplings. andproduction. hadron decay An colliders In modes, inclusive because spite search todominant of for of gluon-fusion allow process, a the associated cross overwhelming production section of background a more from Higgs boson than multijet with an a vector order boson, of magnitude lower than the Collaboration reported evidence forsignificance the of 3.4 standard deviations ( for under fairly general assumptions [ with those expected for thehave SM strengthened Higgs boson the [ These hypothesis measurements, that however, the haveof new been the mainly particle new performed is particle inwhether indeed ( it the a decays bosonic into Higgs decay fermions boson modes as [ predicted by the Standard Model. Recently, the CMS 1 Introduction For decades, the Higgs bosonprediction. [ In Julyobservation of 2012, a the new particle ATLAS with and a mass CMS of experiments about 125 at GeV and the with LHC properties consistent reported the The ATLAS collaboration A Tables of event yields JHEP01(2015)069 , 11 . The 8 replaced b b production is → Z . For the 7 TeV ) H 9 W/Z decay modes of the vector `` → Z , or explains the construction of the final 6 `ν . ) production, with normalisations taken -tagging algorithm is used to identify the b decay. To improve the sensitivity, the three → 12 decays when the lepton is produced outside details the event selections applied to the b ZZ discusses the background composition in the b W production. The normalisations of these back- 5 decays, the 0-lepton channel has a smaller but W 7 , -tagging requirements, constrain the contribu- t – 2 – → b t and -tagged jets. Topological and kinematic selection νν νν -tagging information, provides the final discrimi- b b H → → WZ Z Z . The results are presented and discussed in section . Section 4 10 . This is followed by sections describing the dijet-mass and multivariate 3 . Details of the data and simulated samples used in this analysis are 2 -tagged jets is the final discriminating variable used in the statistical analysis; . b b b )+heavy-flavour-jet production and → This paper is organised as follows. A brief description of the ATLAS detector is A binned maximum likelihood fit is used to extract the signal yield and the background The analysis is performed for events containing zero, one, or two charged leptons Z W/Z various analysis regions, while thestatistical systematic uncertainties procedure are used addressed in todata, section extract only the a results dijet-massanalysis is are analysis described specified is in in used, section and section and a summary differences of with the respect paper is to given the in 8 section TeV data given in section provided in section analyses applied to theand 8 TeV jets data. is The reconstruction addresseddijet-mass of and in physics multivariate section analyses, objects while suchdiscriminating section as variable of leptons the MVA. Section 8 TeV dataset to extractthe dijet-mass the and final MVA approaches, results.performed a in measurement To the of same validate the final the yield statesby of analysis and ( with procedures, the same both event selection, for with ( grounds are fully determinedare by single-top-quark the and likelihood dibosonfrom fit. theory, ( as Other well as significant multijetSince background events, the sources normalised MVA using has multijet-enriched higher control expected samples. sensitivity, it is chosen as the nominal analysis for the addition to the dijetnating mass, variable. as Because well7 the TeV as dataset, latter the information MVAcontrol is is samples, not used available typically only in with fortions similar loosened of the the detail 8 TeV dominant for dataset. background the processes. In The both most analyses, significant dedicated background sources are that are varied inthe the likelihood, fit. associated with Eachin its nuisance uncertainty. this parameter Two paper: is versionssystem of constrained in of the by the analysis a are first, penaltyin presented referred term the to in other, as a multivariate the analysis dijet-mass (MVA) analysis, incorporating the various kinematic mass variables of in the dijet channels are each split according tojets the (two vector-boson or transverse three), momentum, thecriteria and number are the of applied number within of each of the resulting categories. normalisations. Systematic uncertainties onplemented the as signal deviations and in background their modelling respective are im- models in the form of “nuisance” parameters (electrons or muons), targeting the boson, respectively. In additionnot to insignificant contribution from leptonic of the detector acceptancejets or consistent not with identified. originating from A an JHEP01(2015)069 , θ of sin miss E T recon- , is also 2 E ) = η T ) are used in miss T E φ , E 475), endcap r + (∆ . 2 1 and ) φ θ < | (∆ η sin -axis points from the IP | p x p 5 and by a straw-tube . = = 2 T R p < | +jets events collected with η | triggers were not available for µµ 0. The pixel detectors are crucial → . miss T range 2 trigger configuration evolved during E Z 1 -axis. The pseudorapidity is defined in terms trigger efficiency on the < ) coordinates, ∆ z φ | 9) sections. The hadronic calorimeters , 9 with a variety of detector technologies. . miss T . η η | 4 collision data recorded in stable beam con- ] for the 7 and 8 TeV data, respectively. 4 E miss T 20 E < < is calculated relative to the geometric centre of the pp [ | | 7 ranges, respectively. η calculated without the muon contribution. As 1 . η η | – 3 – | 2 − +jets and < < miss µν T 9. The muon spectrometer measures the deflection | . -axis points upward. Cylindrical coordinates ( E 1 4 η y . | → < | η W | 2). The distance in ( 4 and θ/ . 2 < -axis coinciding with the axis of the beam pipe. The | z ] is cylindrically symmetric around the beam axis and is structured ln tan( η | − 19 = being the azimuthal angle around the η φ 2), and forward (3 . as 3 θ < | η | < -tagging, and the TRT also contributes to electron identification. The calorimeters, lo- Events in the 0-lepton channel are selected by triggers based on the magnitude The trigger system is organised in three levels. The first level is based on custom-made ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP) in the b 375 1 . centre of the detector and the towards the centre of thethe LHC transverse ring, plane, and the of the polar angle used to define conerespectively. sizes. Transverse For momentum the anddetector; purpose energy otherwise, of are it defined object is as relative selections, to the reconstructed primary vertex of each event. for the 8 TeVstructed data. offline The is dependencesingle-muon measured of triggers, in with the the offline there was a brief period of data-taking in which the ditions and with all relevantintegrated sub-detectors luminosities providing high-quality are data. 4.7 The and corresponding 20.3 fb the missing transverse momentum vector.data taking The to cope with the increasing luminosity, and the trigger efficiency was improved select events, which are thenover logged an for accelerator offline fill. analysis at a rate of3 up to 400 Data Hz averaged and simulatedThe datasets samples used in this analysis include only hardware and uses coarse-granularity calorimeterthird and levels muon are information. implemented TheAt as the second software second and algorithms level, only and regionsthird use deemed level, interesting the called at the full the event first detector filter, level granularity. makes are use analysed, of while the the full detector read-out to reconstruct and (using scintillator tiles orcalorimeters liquid with argon a coverage as of of active muon materials) tracks surround in thesuperconducting the electromagnetic coils. field It of is three instrumentedchambers large with covering air-core separate the trigger toroidal and magnets, high-precision each tracking containing eight transition-radiation tracker (TRT) in thefor range cated beyond the solenoid, cover theThe range liquid-argon electromagnetic calorimeters are(1 divided into barrel ( The ATLAS detector [ in a barrel and twotector endcaps. is immersed It in consists the ofCharged-particle 2 three position T main axial and magnetic subsystems. momentum fieldlowed The measurements produced by inner are by silicon-strip tracking a made detectors de- superconducting in by solenoid. the pixel pseudorapidity detectors fol- 2 The ATLAS detector JHEP01(2015)069 µµ ZH pro- ] with → ], which +jets at 23 with the and ] is used Z ] is used [ Z 39 30 26 – , photos and WH 28 25 leptons can also ee generator is used pythia8 τ pythia8 → +jets and ]. Signal samples are Z W 11 -initiated [ q generator [ q pythia8 decay mode is considered in production. Version 1.4.1 of production, the simulation is b t t b t t ], and with electroweak correc- production is ], interfaced to hdecay 36 powheg 32 – threshold of the single-electron trig- ZH . Events in the 1-lepton channel are 34 1 T − E production, NLO corrections [ and )+jets and -quarks. For ZH ], except for the response of the calorimeters b WH – 4 – W/Z . ], which includes a full simulation of the ATLAS 22 triggers are also used to compensate for the lim- ]. Additional normalisation-preserving differential 1 21 decays, as leptonic decays of the 37 - and miss T production processes. For c Z E -initiated q ZH and program [ q ] with the CT10 PDFs [ 31 W simulation [ ] is used with the CT10 PDFs to simulate threshold of the single-muon trigger was similarly increased from geant4 40 production cross section by about 5%, are taken into account. The T p ]. (For the analysis of the 7 TeV data, the 33 ] parton distribution functions (PDFs). The AU2 tune [ ZH ]. For gluon-gluon-initiated atlfast-II 24 38 .) The transverse momentum distributions of the Higgs boson show substan- generator [ ZH ] is used for QED final-state radiation. The 27 → production at leading order (LO) in QCD, with results cross-checked by an indepen- The main background processes are ( The MC generator used for Monte Carlo (MC) simulated samples are produced for signal and background pro- sherpa gg be selected in thethe analysis. analysis. For the Higgs boson, only the the leading-order in QCD, with massive electroweak NLO corrections are appliedvector as boson a [ function ofincrease the the transverse total momentum of the Higgs boson decay branchingsimulated ratios for Higgs are boson calculated masses from with flavours 100 are to 150 simulated GeV in in steps the of 5 GeV. All charged-lepton for tial differences between theproduction, two the total productionat cross sections next-to-next-to-leading and order associated (NNLO) uncertaintiestions are at in next-to-leading computed QCD order (NLO) [ [ within the MiNLO approach [ AU2 tune, as atance cross-check and and kinematic to properties. evaluateZH systematic It uncertainties is on also used thedent for computation signal the [ accep- generation of gluon-gluon-initiated background simulations is given in table the CTEQ6L1 [ for the parton shower, hadronisation,gram and [ multiple parton interactions. The thresholds of the dilepton triggers are 12 GeV forcesses electrons using and the 13 GeV fordetector muons. based on the for which a parameterised simulation is used. A list of the generators used for signal and data include isolation criteria,36 GeV triggers for muons) with but higher noefficiencies isolation thresholds requirements are (60 are GeV measured used in using forevents. addition. a electrons In Single-lepton tag-and-probe and the trigger method 1-muon sub-channel, ited applied muon to trigger-chamber coverage in somechannel regions are of selected the by a detector. combination Events of in single-lepton, the dielectron 2-lepton and dimuon triggers. The channel in the 7 TeVprimarily dataset selected is by single-lepton reducedger triggers. to was 4.6 raised The fb from 20the to 8 TeV 22 data. GeV during The 18 the GeV 7 for TeV the data-taking 7 period, TeV data and to to 24 24 GeV GeV at for 8 TeV. As the single-lepton triggers for the 8 TeV the first bunch crossings of two bunch trains, the integrated luminosity for the 0-lepton JHEP01(2015)069 ] ) ], 49 41 pro- [ ZZ ) For ? ]. The ].) W t 47 51 , and – process, and 45 pythia6 generator [ WZ generator with , ZH ], and the cross → ]. 26 ] are used. In this , WW 43 gg , using the CTEQ6L1 [ 25 herwig t 26 pythia8 , t with the AU2 tune, is used 25 -channel exchange process is t pythia6 pythia8 ]. They are overlaid on the simulated -channel exchange process and 26 , s , while the 25 t pythia8 powheg+pythia8 pythia8 Sherpa 1.4.1 Sherpa 1.4.1 Sherpa 1.4.1 powheg+pythia AcerMC+pythia powheg+pythia powheg+pythia powheg+pythia8 powheg+pythia8 powheg+pythia8 powheg+pythia8 t ] and at NNLO, including resummations of ] with the MSTW2008NLO PDFs [ 42 50 ] interfaced with – 5 – [ 44 is used for the simulation of the , as for mcfm )+jets [ `νbb ννbb/``bb ννbb/``bb → → → ) W/Z ? generator [ `` pythia8 ( generator with the CT10 PDFs, interfaced with ] and the A2 tune [ powheg ) ? ( `ν ZH ZH WH 52 νν ∗ → ]. (For the analysis of the 7 TeV data, the → → → → Process Generator → 48 q q -channel ¯ t -channel Signal q gg q Vector boson + jets W Z/γ Z Top-quark t t s W t Diboson WW WZ ZZ powheg AcerMC generator with the CT10 PDFs, interfaced to for the simulation of diboson processes. . The generators used for the simulation of the signal and background processes. ( Events from minimum-bias interactions are simulated with the Additional backgrounds arise from single-top-quark and diboson ( the MSTW2008LO PDFs [ for which theanalysis, CTEQ6L1 the PDFs final and normalisationsdata, the of but Perugia2011C these theoretical cross tune dominantare sections backgrounds [ calculated are are used at constrained to NNLO bynext-to-next-to-leading optimise logarithmic the for the (NNLL) ( selection. soft gluon The terms, cross for sections powheg for diboson processes [ is used instead withsections are the obtained CTEQ6L1 at PDFs NLO from and the AUET2 tune [ Table 1 the analysis of theherwig 7 TeV data, performed with the production. For single-top-quark production, the duction are simulated with simulated with the PDFs and the Perugia2011C tune. The cross sections are taken from refs. [ JHEP01(2015)069 -, 47 u . 2 , are 5 GeV Z < ]. The -hadron b > | or 54 η is denoted | T p W V cc and 20 GeV identified in > stands for V bl T p , V -jet, the event belongs to the V bc b -jet, the event belongs to the 1, where there is limited muon- . , c and is required to have at least threshold of 400 MeV. The pri- 0 2 T T < p V bb category. Further subdivisions are ] are used in the analysis, referred to p ]. Three types of muons are included | -hadron is found, the jet is labelled c η 55 | 56 V l [ ee 5 identified in the muon spectrometer, and +hf because the main production process is . → 2 V +jet events, where Z > – 6 – V | η 4 around the reconstructed jet axis. If a | . ] and muons [ 54 = 0 , -jet. If not and a -hadron is found, the jet is labelled as a light (i.e., R 53 b c . The combination of 7 GeV. Loose electrons are required to have > V cl , T - nor a E b V cc , . V bl 8 , final state is not included in V bc V cl , rather than gluon splitting. . -quark, or gluon) jet. Simulated V bb 10 s -jet. If neither a W c c Three categories of electrons [ Charged-particle tracks are reconstructed with a Simulated jets are labelled according to which generated hadrons with Additional generators are used for the assessment of systematic uncertainties as ex- category. If not and one of the jets is labelled as a category. Otherwise, the event belongs to the → +hf. The -, or in the loose definitionmuon to spectrometer maximise and the the innerthe acceptance: detector calorimeter and (ID); (1) associated (2) muons with muons an reconstructedchamber with ID coverage; in track with and both (3) the muonswhich with do not match full ID tracks due to the limited inner-detector coverage. For muons of and to fulfillikelihood-based the electron “very identification loose combinescriteria, likelihood” shower-shape the identification information, matching criteria track-quality qualitycalorimeter defined between (direction the in and track ref. momentum/energy), andidentify [ TRT electrons its information originating from associated and photon energy a conversions.by making cluster criterion The use electron in of to energies reference the help are processes such calibrated as sum of associated-track squaredthree transverse momenta associated Σ tracks. as loose, medium and tightwith leptons in transverse order energy of increasing purity. Loose leptons are selected In this section,data the is reconstruction presented. of Differencessection physics relevant objects for the used analysis in of the the analysis 7 TeVmary of data vertex is the are selected reported 8 from TeV in amongst all reconstructed vertices as the one with the largest V gs 4 Object reconstruction Higgs boson candidate. IfV b one of those jetsV c is labelled asdefined a according to theorder: flavour of the other jet from the pair, using the same precedence are found within a coneis of found, size the ∆ jetas is a labelled asd a then categorised according to the labels of the two jets that are used to reconstruct the contributions from these “pile-up” interactionscrossing are as simulated the both hard-scattering process withinevents and the are in same then neighbouring bunch processed bunch crossings. through the The same resulting reconstruction programsplained as in the section data. signal and background events according to the luminosity profile of the recorded data. The JHEP01(2015)069 ] - .) b 59 5 -jets c ] with 25 GeV. 64 – > ]. Further 62 -quark frag- T b 61 E , ]). To reduce the 60 of tracks matched 60 T p -jet rejection factor is 1.9 c 2, the muon is kept unless it . 0 4, the jet is discarded. Next, if . events. In this analysis, the 80%, 0 t t R < 5. . R < 4 < | η | 4, the jet is discarded if it has three or fewer . 0 – 7 – ] with a radius parameter of 0.4. Jet energies are 58 R < ]. For both the tight electrons and the tight muons, 54 and in the jet energy corrections described in section 20 GeV and 3 around the lepton, excluding energy associated with the -dependent correction factors determined from simulation, . > η miss -tagging selection criteria (or operating points) are calibrated T algorithm [ T b = 0 t p E 4. Jets without any matched track are retained. The jets kept k . R 2 - and 5. Tight electrons are required to additionally fulfil the “very tight . T < 2 p 2 centred on the lepton-candidate track, excluding the lepton track, . | 20 GeV, as measured in simulated < η | | > -tagging algorithm is used to identify jets originating from = 0 η | b T p R of all tracks matched to the jet. This requirement is only applied to jets with ] using the anti- T -jet rejection. Four 57 c p 50 GeV and -hadron decay vertices. It is an improved version of the MV1 algorithm [ -jets with c The MV1c To avoid double-counting, the following procedure is applied to loose leptons and jets. Jets are reconstructed from noise-suppressed topological clusters of energy in the calori- Medium leptons must meet the loose identification criteria and have b < -axis, respectively. Finally, the scalar sum of the transverse momenta of tracks within a T times larger than obtained with the MV1 algorithm. and used in the analysis,for corresponding to average efficiencies70% of and 80%, 50% 70%, operating 60% pointstight and are (loose) 50% denoted operating loose, point, mediumand the and light rejection tight, jets, factors respectively. respectively. are For the For 26 the (3) tight and operating 1400 point, (30) the against is identified only in the calorimeter, in which casementation. the electron This is kept. algorithmalgorithms combines based in on a trackand neural impact-parameter network significance the orhigher information explicit from reconstruction various of a jet and amatched muon tracks are since separated in by thisthe ∆ case calorimeter; it otherwise is thein likely muon to the is originate computation discarded. from of (SuchFinally, a the if muons muon an are having electron nevertheless showered and in included a muon are separated by ∆ of the p for the analysis must have First, if a jet and an electron are separated by ∆ with residual correctionsadjustments from are made in based on situ jetwithout measurements internal changing properties, the applied which average improve calibration to the (globalcontamination energy sequential data by resolution calibration jets [ [ from pile-up interactions,to the the scalar jet sum and of originating the from the primary vertex must be at least 50% of the scalar sum requirement is tightened from 10% to 4%. meters [ corrected for the contributionand of pile-up calibrated interactions using using a jet-area-based technique [ Medium muons must betector reconstructed and in have both thelikelihood” muon identification spectrometer criteria and [ more the stringent inner isolation de- criteriaposits must in be a satisfied: cone oflepton the candidate, size sum must ∆ of be the less calorimeter than 4% energy of de- the lepton energy, and the track-based isolation vertex must be smallerz than 0.1 mmcone and of 10 size mm ∆ is in required the to transverse be plane less than and 10% along of the the transverse momentum of the lepton. the first and second type, the muon-track impact parameters with respect to the primary JHEP01(2015)069 , R V c , - and c V l 1. No such and, for light T -tagged jets are p R < b . , is calculated as the 4 associated with the . 10 2 miss T < p | -jets, events with identified events to provide a reliable η b -tagging algorithm. It is im- | b ] is measured as the negative V c events with ∆ -tagged jets are required. These 66 -tagged are used for the , b b -tagged jets. and 65 b V cc [ production, these backgrounds remain events for V l t t miss T -jets by the V c b E and – 8 – V l -jets and light jets are measured in both data and c events. A dedicated correction, depending on ∆ leptons, and photons), using the calibrations of these -jets, WW τ b events. -labelled jets with the MV1c algorithm, parameterisations l and of their probabilities to be V cc | V l η , - and | c V cl and T -jets, or multijet events for light jets. The small differences observed are p c , the angular separation from the closest other jet, and a significant difference 9. Corrections are applied to the energies of clusters associated with recon- . The SFs are, however, strictly valid only for the generator used to derive . R | 4 η processes in all analysis samples in which two | -tagging efficiencies for b < | η | WW The analysis is optimised for a Higgs boson mass of 125 GeV. Events are first cate- Additional corrections are applied to the simulation to account for small differences The missing transverse momentum vector Because of the large cross sections of The mesons for ∗ In this section, theDifferences event in selection the applied analysis in of the the analysis 7 TeV of data the aregorised 8 reported TeV according data in to section is the presented. numbers of leptons, jets, and from data for trigger efficiencies,well for as lepton for reconstruction and lepton identification energy efficiencies, and as momentum resolutions. 5 Event selection objects. The transversedeposited momenta by of these reconstructed muons muons inIn addition, the are a calorimeters included, track-based properly missing withnegative removed transverse the vector to momentum sum vector, energy avoid of double-counting. theprimary transverse momenta vertex. of tracks with is therefore applied to the vector sum of the transversewith momenta associated with energystructed clusters objects in (jets, the electrons, calorimeters parameterisations are, however, integrated overlight-jet other tagging variables efficiencies. that In canserved particular, on affect ∆ a the strong dependenceis of seen these between efficiencies direct isdifference and ob- is parameterised seen tagging for for description of these backgroundsrequired. in An the alternative procedure, analysis parameterisedof samples tagging, directly for is therefore tagging which used. the two as Here, instead functions of and them. The differences observed whenare the taken efficiencies are into measured account with by differente.g., additional generators different “MC-to-MC” SFs. production fractions Such of differences can heavy-flavour hadrons be or caused by, modellingsignificant of despite their the decays. powerful rejectionpractical of to non- simulate a sufficiently large number of simulation using dedicated event samplesD such as used to correct thetwo simulation operating by points. so-called These “scale SFsjets, are factors” parameterised also (SFs) as within a function intervals of between the jet JHEP01(2015)069 . . V T p miss T , the -jets. value b E 2 -tagged -tagging b b miss T E 120 GeV to 30 GeV and 20 GeV and > in the 0-lepton > > -tagged jet and = 120 GeV, and b W T T T p p p miss T miss and detailed below. T E E 2 jet is loosely 45 GeV. The following T > mentioned in table p i T p jet T p P . Events with two jets satisfying 1 of the vector sum of the transverse trigger is used for Z T p miss T E -tagging criterion, form the MM (or Medium) – 9 – background. Only selected jets are considered b 160 GeV, 97% efficient for t t -tagged jets must have > b -tagged form the 1-tag category, and those with no -tagging can be applied. There must be exactly two b b miss T E -tagged jet for events in the 1-tag category, and by the two b of the vector sum of the lepton transverse momentum and the intervals, with boundaries at 0, 90, 120, 160, and 200 GeV. In the W T p ) non- V T = 100 GeV, with an efficiency that decreases rapidly for lower p T -tagged jets in any of the 2-tag categories, by the p b miss -tagged, and 3-jet events in which the lowest- T b , to take advantage of the better signal-to-background ratio at high E range within which V T p η -tagging criterion form the TT (or Tight) category; those not classified as TT, -tagging algorithm is applied to all selected jets. There must be no more than two b b -tagged jet form the 0-tag category. In the 3-jet categories, the dijet system is 5 are discarded to reduce the b 5, the . . in the 1-lepton channel, and the magnitude 2 trigger is fully efficient for 2 Further categorisation is performed according to the transverse momentum of the Additional topological and kinematic criteria are applied to reject background events The jets used in this analysis, called “selected jets”, must have The Events containing no loose leptons are assigned to the 0-lepton channel. Events con- > < miss | | T miss T -tagging categories are then defined as shown in figure η η E 80% efficient for Only four intervals are therefore usedof in 100 the GeV. 0-lepton channel, Inrecover with events the a not minimum selected 1-muon by sub-channel, the single-muon the trigger, thus increasing the signal acceptance The transverse momentum of the vectorchannel, boson the is magnitude reconstructed as the E momenta of the two leptonsare in categorised the in 2-lepton five channel.0-lepton In channel the and dijet-mass for analysis, events the fulfilling events the condition on and enhance the sensitivity ofIn the general, search. the They selection areorder criteria outlined to in are maximise table looser the in information the available to MVA than the in finalvector the discriminant. boson, dijet-mass analysis in loosely formed by the two the leading (highest- leading jets in the 0-tag category. category; those not classified ascriterion, TT or form MM, the but with LLwith two jets (or respect satisfying Loose) to the loose category. whatthe would LL This be category categorisation obtained providing improvesEvents using constraints the with on a sensitivity exactly the single one backgrounds category, not jet such containing loosely as two TT+MM, real with such jets loosely are discarded. At least oneb of the two the tight but with two jets satisfying the medium | or three such selected| jets. Eventsfurther, containing e.g., an to additional define the jet jet with multiplicity, or to calculate kinematic variables. taining one tight lepton and no additionalEvents loose containing leptons one are medium assigned to leptonand the and 1-lepton no one channel. additional other loose loosechannels, lepton leptons, for of at are the least same assigned one flavour, that of to the satisfied the lepton the 2-lepton triggers trigger by channel. are which the required In event to was the be selected, 1- the associated objects and with 2-lepton the selected leptons. JHEP01(2015)069 100 GeV; -jet purity ), the az- interval of b ) as defined production, > V T t miss T t interval. The p below or above p 200 GeV. , which depends , miss T V T i V T p > E p jet T p V T miss T p E +jet production, while P ( = 2; -tagging algorithm for the jet)], and the azimuthal MV1c(jet) OP φ V b , jet , ∆ ) is the azimuthal angle be- N miss T 2 E ( jet miss T , dijet). In addition, a minimum φ p 1 , (jet miss T and φ E ( φ ), which depend on the miss T 2 E jet , – 10 – 1 5. Here, ∆ . of the track-based missing transverse momentum 0 (jet ) information is used in the final discriminant, only a R 2 > interval, where the amount of background is smallest. miss T p V T L jet p , to take advantage of the increasing collimation of the dijet 1 and the nearest jet, min[∆ information is used in the final discriminant. V T -tagging efficiencies of 100%, 80%, 70%, 50%, i.e., the p b V T (jet p 7; and R miss T > E and the dijet system, ∆ S 7; . miss T 2 E jets. The bin boundaries denote the operating points ( < , the azimuthal angle between T ) p 2 , corresponding to 4 jet . Event classification as a function of the output of the MV1c miss T , p 1 In the 0-lepton channel, the multijet (MJ) background is suppressed by imposing In the dijet-mass analysis, requirements are applied to the angular separation between (jet φ angle between value is required for theon scalar the sum jet of the multiplicity.the jet Additional 0-lepton transverse momenta, requirements channel, are where∆ applied the in MJ the background lowest is largest: minimum value is required, a requirement which is also removedrequirements for on thevector magnitude imuthal angle between requirement on the minimum valuethe reduces requirement the on background the from maximum value,is which tightened reduces with the increasing background from system for the signal.value To increase is the removed signal in acceptance, theIn the the highest requirement MVA, on where the the minimum ∆ in this channel by 8%.120 GeV, In the but MVA, the only detailed two intervals are defined, with the two jets of the dijet system, ∆ Figure 1 two highest in section increases from left (bottom) toLL right for (top). 2-tag, The as event explained categories in are 0-tag, the 1-tag, text. and TT, MM and JHEP01(2015)069 < V T 2 p is the in the 2. , which 20 30 1.5 120 – – T `` W T > > > 200 GeV) ) In the 0- H > < π/ 120 (150) m m > π/ ∗ – – < background. ) 3 > V T to the square , and azimuthal t 71-121 p t T miss miss T p miss T , E 180 0.7 ( – E NU ); the magnitude of the 0–120 Multivariate analysis , the MJ background 2 > > miss T E jet ( , 120 GeV intervals. 7.1 φ ; and the cosine of the helicity 1 50 i 1.4 200 < jet T > (jet )120 GeV, where < p > V T φ > p ( P 2 < 30 2.8 1.5 – V T dijet); ∆ > 0.7–1.8 p , > > 160–200 < π/ 120 (150) 20 divided by > miss > T E ) for ( miss T φ interval is set at 100 GeV instead of 90 GeV. For H 60 120 ; miss 0.7–2.3 T 120–160 )). V T < – 11 – 83-99 E p < ( miss T ]. For the MJ background, the probability density functions miss H φ T 67 2 2-lepton selection 1-lepton selection 0-lepton selection − H Common selection 30 –120 ` 2.2 Dijet-mass analysis – ) significance, defined as the ratio of φ ∗ ( > > < π/ 120 (NU) 0.7–3.0 90 180 cos( – miss T > − E > (1 is calculated from the transverse momentum and the azimuthal angle of the miss T NU W T is a likelihood ratio constructed to discriminate further against the 0–90 , and from the missing transverse momentum magnitude, is the E ` 0.7–3.4 m ` T and the transverse momenta of the two leading jets and the lepton. φ L p S 2 p ) and miss 2 T jet)] = , ` T E ; and p i [GeV] ) miss T W T 2 i dijet) p jet T m miss T , , p jet T : jet E p , ( . Event topological and kinematic selections. NU stands for ‘Not Used’. ( 1 P φ miss miss miss [GeV] [GeV] T T [GeV] φ [GeV] [GeV] E E [GeV] (jet In the 2-lepton channel, criteria are imposed on the dilepton invariant mass, In the 1-lepton channel, a requirement is imposed on the transverse mass [GeV] =2(3) ( ( =1 The likelihood ratio uses the following inputs: ∆ The transverse mass P i `` W T φ φ R T 3 2 miss miss T T jet miss T V T E m E H m N ∆ min[∆ ∆ p ∆ p Variable vector sum of the two jetangle transverse in momenta, the dijet restused frame as in defined the in likelihood ref. [ ratio are constructed fromcharged data lepton, events selected withangle, ∆ This mainly reduces the MJis background. difficult As to discussed model120 in GeV and section intervals. remains Therefore, only substantial the in 1-muon the sub-channel is 1-electron used sub-channel in in these intervals. the MJ background. dijet-mass analysis. This requirementRequirements reduces are the contamination also from imposedscalar the sum on of lepton channel, the lowerthe edge 1-lepton of channel, the only second the 1-muon sub-channel is used in the tween the two jets, root of Table 2 JHEP01(2015)069 , νν ) used → events. 9 involved Z , H ) `` spectrum of miss T interval, and T E → V T p W/Z p Z simulated events), , `ν ZH → W -tagging information is used events. All 2-tag signal and b events (playing a role similar t t with ZH H -tagged jets is improved as follows. ) b W/Z = 125 GeV in simulated ( mass resolution is improved by 30% in the H -tagged, these selection criteria define a set of b b m b spectrum in boson. In the dijet-mass analysis a requirement – 12 – T p Z process with respect to the 2-lepton channel. `` → Z ). 7 (b)). 2 (a)). In the 2-lepton channel, wherein there is no true 2 ; this variable is used in the final discriminant of the MVA. -tagging categories. In the MVA, where the b miss T process with respect to the 1-lepton channel. Similarly, the 1-lepton channel E `ν , as well as the acceptances in the three channels after full selection are given in b → b → W for the MVA and the dijet-mass analysis. The acceptance for other production and 3 system momentum (with a width of 9 GeV, as determined from -dependent correction is applied to account for biases in the response due to resolution H The cross sections times branching ratios for ( After event selection, the energy calibration of the For events in which two jets are loosely T p and table decay modes of the Higgsfor boson the is negligible. Theadds 0-lepton 10% channel in adds acceptance 7% for in acceptance the values (after the muon-in-jeta correction, prior but built without from theto the resolution expected the correction) true resolution as jet correction). well2-lepton as channel Overall, (figure the except possibly from semileptonicis heavy-flavour further decays, improved the by energy aon calibration kinematic likelihood the of fit, the dilepton which jets mass, includes``bb a Gaussian Breit-Wigner constraints constraint ondedicated each transfer of functions relating the the transverse true jet components transverse of momenta to the their reconstructed a effects (resolution correction). Thisjets latter from correction is the determined decayThe for of dijet the a mass Higgs resolution bosontypically for 11% with the (figure signal is improved by 14% after these corrections and is to extract the results.studies (reported The in 0-tag section control regions are used onlyThe for energy background from modelling muonsremoving the within energy deposited a by the jet muon in is the calorimeter added (muon-in-jet correction), to and the calorimeter-based jet energy after in the final discriminant,TT a and MM similar categories subdivision areand merged is in 0-tag performed the “control 0- with regions” andIn the 2-lepton are the difference channels. used 1-lepton Similarly that in defined channel, the as 1-tag the the control analysis 2-tag regions to signal because constrain1-tag regions they control the with regions are main a are largely backgrounds. third used dominated simultaneously selected in by jet the act global fit in (described practice in section is imposed on “2-tag signal regions”, categorised injet terms multiplicity of (2 channel or (0, 3). 1,TT, In or MM the and 2 LL dijet-mass leptons), analysis, a further division is performed into the must be consistent with the mass of the JHEP01(2015)069 = 200 GSC H σ )/ [GeV] σ - m bb 180 GSC m σ = 125 GeV 160 16.4 GeV -- 11.4 GeV 30% H m 140 Resolutions ( 120 100 (b) , decays to all three lepton 80 Acceptance [%] `` MC 60 b → b → Z 40 Simulation 0-lepton 1-lepton 2-lepton . The acceptance is calculated as the Global Sequential Calib. (GSC) + Muon-in-Jet Correction + Kinematic Likelihood Fit 20 inclusive V T νν = 8TeV p ATLAS Pythia VH, H 2 lep., 2 jets, 2 b-tags s 0 0 → 0.1 √

0.08 0.06 0.02 0.04 Events / 4.0 GeV 4.0 / Events Z BR [fb] × 200 – 13 – GSC σ )/ [GeV] σ 1.3 – 0.9 (0.7) 10.5 (8.1) 3.8 5.5 (5.0) – – - 14.9 – 1.3 (1.1) 13.4 (10.9) 44.2 4.0 (3.8) – – bb 131.7 0.3 (0.3) 4.2 (3.7) – 180 GSC m σ 160 = 125 GeV at 16.4 GeV -- 14.4 GeV 12% 14.1 GeV 14% H 140 Resolutions ( m Cross section -initiated processes are shown separately. The branching ratios are 120 gg ) ) ) ) b ) b b b b b b b 100 b b (a) → - and → → and decays to neutrinos for → → 80 q q H H H H ] and the parameter representing the width of the core of the distribution is `ν H MC )( )( )( 60 b )( )( 68 b → `ν , the → `` νν `` νν 40 Simulation → W → → → → ZH Global Sequential Calib. (GSC) + Muon-in-Jet Correction + Resolution Correction . Dijet-invariant-mass distribution for the decay products of a Higgs boson with 20 Z Z inclusive Z W Z V T . The cross section times branching ratio (BR) and acceptance for the three channels at ( ( ( ( ( ATLAS Pythia VH, H 2 lep., 2 jets, 2 b-tags p 0 0 → → → → → 0.1

0.02 0.08 0.06 q q q 0.04 Events / 4.0 GeV 4.0 / Events Process q gg q q gg for resolution effects specific(dash-dotted); to the (b) kinematics using ofmuons the jets inside decay after jets of global a andBukin Higgs applying sequential function boson the calibration [ with kinematicshown (GSC, in fit solid), the (dash-dotted). figures, and asthe The well after global as distributions sequential adding the are calibration. relative improvement fit in to the resolution the with respect to jets after Figure 2 125 GeV in thesequential 2-lepton calibration (GSC, MVA solid), selection. and after The adding muons distributions inside jets are (dotted) shown and after (a) correcting using jets after global calculated considering only decaysflavours to for muons and electronsfraction of for events remaining inafter the the combined full 2-tag event signal selection. regions of the MVA (dijet-mass analysis) Table 3 8 TeV. For JHEP01(2015)069 , and their -tagged jet 2 b b and 1 b ] is used, which, sim- -tagged jets and their as b 70 120 GeV. For the small , respectively. In the 0- , T and the mass of the 3-jet | p ) 3 ). The angular separation, > 69 2 -tagged jets belonging to the b b V T ( ) signal from the sum of the p V, bb c b ( 1 b η and presented in more detail in ∆ 7 . The | → MV 4 -tagging information is provided by the b ) and ) and 1 )]. The other variables were defined in the VH,H b ( V, bb c `, b ( . The ( 1 | – 14 – φ φ ) 2 , corrections to the simulation as explained in sec- -tagging properties of the selected events in a multi- MV , b b 1 ) are labelled in decreasing b ( 7.1 . bb η 120 GeV. Events in the electron and muon sub-channels 4 m ∆ | > V T p In this figure, as for all figures in this section, the MJ background . 4 . bbj is defined as the scalar sum of the transverse momenta of all jets and 3 m T H 120 GeV and 120 GeV interval, which has reduced sensitivity, no dedicated BDT is trained < < V T . A similarly good agreement is found for the correlations between pairs of input p V T are applied, and background normalisations and shapes are adjusted by the global 9 120 GeV are used, whereas for the 1- and 2-lepton channels individual BDTs are . In the 1-lepton channel, the angle between the lepton and the closest The input variables of the BDTs are compared between data and simulation, and good The BDTs are trained to separate the ( Dedicated BDTs are constructed, trained and evaluated in each of the 0-, 1- and 2- < p 7.2 > In this and all similar figures, all backgrounds are taken into account, but those contributing less than 4 miss T V T fit of the MVAsection as outlined at thevariables, beginning as can of be section seen in figure 1% are omitted from the legend. agreement is found within theare assessed shown uncertainties. in Selected figure input-variableis distributions estimated as describedtion in section pseudorapidity separation are denotedlepton ∆ channel, E in the transverse planeprevious is sections. denoted In min[∆ 3-jetsystem events, the is third denoted jet is labelled as jet of variables for the different channels aredijet listed system in table (with mass denoted separation in pseudorapidity is outputs of the MV1cin neural the network, transverse plane, of the vector boson and the dijet system of expected background processes. The inputin variables used order to to construct maximise the the BDTsperformance are separation, significantly. chosen while Starting avoiding from theat use the a of dijet time variables mass, and not additional the improvinguntil one variables the adding are yielding more the tried variables does best one not separation result gain in is a kept. significant performance This gain. procedure is The repeated final sets are combined since nonechannel, of the the final variables used results100 are are lepton-flavour obtained specific. usingand the In only the MVA the for 0-lepton dijet-mass distribution is used. lepton channels in the 2-tagseparately for regions the (with events the with LL,p two and MM three and jets. TT In categoriesused the combined) for 0-lepton and channel, only events with Although the dijet massbetween signal is and the backgrounds, the kinematicadditional sensitivity variable kinematic, of topological the that search and provides isvariate improved the analysis. by best making The use discrimination Boosted of ilarly Decision Tree to (BDT) other technique multivariate [ methods, properly accounts for correlations between variables. 6 Multivariate analysis JHEP01(2015)069 ) B ( A . At the end, the output B × × ], is used to train the BDTs. 71 are merged for both the simulated B × × × × and A Only in 3-jet events – 15 – × × × × × × × × × × × × × × × × × × × × × × × × × × × × × × × × × 0-Lepton 1-Lepton 2-Lepton )] | . The performance of the BDTs trained on sample | ) in order to avoid using identical events for both training ) ) ) ) ) 2 `, b ) 2 B 2 1 A ( b b ( , b , b ( ( φ 1 1 c c V, bb b b B 1 1 V, bb and ( ( ( ( 3 η η bbj `` W T bb 2 1 φ R T miss T A jet T b T b T V T ∆ ∆ m p MV MV m m min[∆ H | ∆ | ∆ m p p E p Variable . Variables used in the multivariate analysis for the 0-, 1- and 2-lepton channels. , and the other half with the BDTs trained on sample A The values of the BDT outputs do not have a well-defined interpretation. A dedicated The Toolkit for Multivariate Data Analysis, TMVA [ Table 4 ground events in each bin.distribution, Starting the from procedure a merges veryuntil histogram fine-binned a histogram bins, certain of from requirement, the high basedmerged BDT-output on to bin, the low is fractions BDT-output of satisfied.tistical values, signal fluctuations, and a To background further limit events condition in the is the number that of the bins statistical uncertainty and of to the reduce expected the impact of sta- distributions of the BDTs trainedand on data samples events. procedure is applied to transformtribution the for BDT-output the distributions background tosignal processes obtain contribution, and a while a smoother at finer dis- the binning same in time the preserving regions a with sufficiently the large largest number of back- for the BDT training andsamples evaluation of in equal an size, unbiasedis way, the evaluated MC with events sample areand split evaluation into of two the samesample BDT. 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JHEP01(2015)069

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JHEP01(2015)069

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24 500 JHEP01(2015)069 t t , it jet)] , miss T 2 shows E miss T π/ E ( +jets and arising from 4 is required, φ . V 0 miss T < . These MJ back- is close to the di- E miss T jet)] E , miss T designed to suppress the E L miss T ) above and below E ( -tagged jet in the 1-tag control φ b miss T p 2. In region C, the requirement on , jet)].) For events with real , miss T < π/ E ) ( miss discriminant in the 2-tag signal regions, as T . φ E 9 value of the ( miss T VH φ p c – 21 – , 1 ) as in regions A and C, respectively. A comparison miss T MV E ( , are similar. In events with fake miss T interval, the likelihood ratio φ p , V T miss T p p miss T E ( 5 and ∆ and . φ 1 jet)] distributions for ∆ ) variables, such that three of the regions are dominated by back- , > miss T miss T miss E T ) is reversed. In regions B and D, min[∆ p jet)] E , , ( φ miss T p miss T miss T , E . E ( ( 8 φ φ miss T The MJ background is estimated in the 0-lepton channel using an “ABCD method”, In all distributions presented in this section, unless otherwise specified, the normalisa- For the multijet (MJ) backgrounds, the normalisations and shapes provided as inputs E ( φ min[∆ ∆ with requirements on ∆ of the min[∆ that these two variables are only weakly correlated, and this observation is confirmed in a ground. (In the 100–120MJ GeV background is usedis expected instead of thatverse min[∆ the momenta, directions ofa the jet calorimeter-based and energyrection track-based fluctuation, missing of it trans- the is poorly expected that measured the jet. direction of The signal region (A) is therefore selected with grounds cannot be determined reliablyof by the simulation, 0-, and 1-, are and 2-lepton estimated channels, from and data in in each each ofwithin the 2- which and 3-jet, the 0-,and 1-, data and ∆ are 2-tag regions. divided into four regions based on the min[∆ fore give rise to potentiallyjets large or backgrounds. photon A conversions firstdecays; misidentified class the as of 1- MJ electrons, and backgroundAnother or 2-lepton arises class, from from channels which semileptonic are affects heavy-flavour jet mostly especially the energy sensitive 0-lepton measurements to channel, in this arises the class from calorimeters, of large which fluctuations background. create in “fake” those distributions within thesection constraints from the systematic uncertainties discussed7.1 in Multijet background Multijet events are produced with a huge cross section via the strong interaction, and there- backgrounds that are left freedescribed to below, float in are the applied fit. prior The to corrections the to fit. thesetions two backgrounds, of the various backgroundsor are multivariate those analysis, extracted as from the appropriate. global fit The for fit the dijet-mass also adjusts the background shapes in appropriate, as well asregions. those More of details the are provided in section to the fit areinputs are estimated taken from from data, the as simulation, explained except for below. the normalisations For of the the other backgrounds the This section describes theare modelling able of to individual constrain backgrounds.likelihood the fit normalisations (also In and called many “global shapes cases, fit”)and better is the constraints used than data on to the simultaneously the a extractthe background both priori the normalisations fit estimates. signal and are yield A shapes. those of The the distributions dijet used mass by or BDT 7 Background composition and modelling JHEP01(2015)069 ) c < 2 1 miss T jet W T E , p MV 1 120 GeV (jet < R value of the , and in the W T c ) in the global W T p t 1 p t MV +jets and V 120 GeV in the 1-electron sub- < W T p 120 GeV, the MJ background is much value drawn from the appropriate > . An MJ template in region A is obtained c 1 W T p – 22 – MV pythia8 4%; and the calorimeter-based isolation is loosened < 120 GeV it ranges from 11% of the total background in the < -tagging requirement is therefore dropped in regions B, C and W T b 1% of the total background. p -tagging normalisation factor is applied to the resulting template, ∼ b 4%. The sample sizes of the MJ-templates are however rather low in the < of the tagged jet and, for the electron sub-channel, according to ∆ c 1 . This procedure is applied in each of the 2- and 3-jet, LL, MM and TT categories. MV W T 7% from p The MJ background in the 1-lepton channel is concentrated at low In the 1-lepton channel, the MJ background is determined separately for the electron < fit. Since thechannel MJ than background in is the twice120 GeV 1-muon as so sub-channel, large as only for to theresulting provide 1-muon loss the sub-channel in most issmaller: reliable sensitivity kept constraints 4% for is on and 0.6%. the 2% in non-MJ the backgrounds. For LL The and TT categories, respectively, for 2-jet events. templates for these othermentioned background above. processes are taken from the2-jet improved 2-tag simulation sample with LL category to 6% inintervals is the to TT provide category. constraints The on main the purpose largest backgrounds of ( including the to the and The normalisations of the MJdistributions templates are in then obtained the from 2-with “multijet fits” and floating to the 3-jet, normalisations 1- for and the 2-tag templates (LL, of MM the and other TT background combined) processes. categories, The signing to the untaggeddistribution jet observed an in emulated theon corresponding 2-tag the MJ rank template. (leadingtagged This or jet. distribution sub-leading) To depends cope of withpseudo-2-tag the residual MJ untagged events differences and jet observed the in and actual some 2-tag on distributions MJ the between events, these a reweighting is applied according and muons respectively, insteadto of 2-tag regions. Sinceevents it in is the MJ-dominated observedMJ regions that are templates. the similar, kinematic 1-tag Events properties events in are of the used the 1-tag to 1-tag category enrich and the are 2-tag 2-tag promoted to the 2-tag category by as- from the other backgrounds. Theby other scale backgrounds factors are taken for fromMJ-dominated the a region various simulation contributions improved is obtained obtainedstead from by of a modifying tight, leptons preliminary the and global loosening nominalThe fit. both selection track-based the to The track isolation and use is calorimeter-based medium, isolation changed criteria. in- to the intervals 5%–12% and 7%–50% for electrons D, and an additional taken as the fraction ofis 2-tag found events to in amount region to D. The MJ background inand the muon signal sub-channels. regions Forobtained each signal in or an control MJ-dominated region, region an MJ-background after template subtracting is the small remaining contribution using events in regionfrom C simulation. The after template subtracting isB normalised the to by contribution that the of in ratio of regionpopulations other the D, of backgrounds, number again events of taken after events in in subtracting2-tag the region other requirement. various backgrounds regions from The suffer those from regions. low The statistical precision after the multijet event sample simulated with JHEP01(2015)069 ) 2 jet back- , distri- distri- 1 Z T W T shown in p p (jet W cl 5 φ and 1% of the total simulations are < W l ]. W cl background events in 72 generator used in this distribution is important. W b ) distribution, and , with the higher intervals ) due to the two jets becoming 2 V T 2 +jet events in the 2-lepton V T p p jet Z jet and W l , , sherpa 1 1 above and below 120 GeV. The (jet (jet ) distribution in data is better reproduced +jets and MJ components are free W cc φ W T 2 (b). This reweighting also improves φ Z p +jets production in the 1-muon sub- ) are taken from the simulation. The jet 7 t , t 1 W (jet φ – 23 – . generator used in this analysis [ 8 spectrum for sherpa W T p )=0.7 comes from the combination of two effects: a rise towards low values are randomly assigned to the jets according to their 2 c jet 1 , 1 ) reweighting is found to improve the modelling of the ) distributions show good agreement between data and simulation 2 2 (jet MV φ jet jet , , +jet backgrounds by the version of the 1 1 V mass peak. Altogether, the MJ background amounts to (jet (jet In order to address this mismodelling, the φ Z φ (a) shows that the 6 7 ) due to gluon splitting, and a drop towards low ∆ ) 120 GeV region. After this reweighting, the modelling of the whole 2 (b)). This reweighting increases (reduces) by 0.7% (5.6%) the normalisation of the > (a). jet ( , 8 1 8 < A similar, but not identical, procedure is used for the Figure A template for the MJ background in the 2-electron sub-channel is obtained in a similar It has indeed been observed that the shape of theThe ∆ peak around ∆ (jet 5 6 φ W T bution in the 0-tag regions. In the signal-depleted 2-tag regionsby NLO obtained generators by than the by exclusion the baseline ∆ unresolved. the 0- and 1-tag regionsreweighting are is too applied small to toassessed these allow instead, conclusive backgrounds, as studies but explained of in an their section associated modelling, systematic so no uncertaintychannel. is A ∆ p bution is greatly improved,the as can modelling be of seen othermodelling in distributions, in figure the most 1-tag notablygrounds control the in regions all dijet and regions mass. is of all therefore It channels. applied also The to numbers improves the of the reweighted based on parameterised fits to thevariable ratio in of data the to simulation 0-tag inare region, the ∆ derived: where these for backgroundsreweighted the dominate. ∆ 2- Four and separate 3-jet(figure functions categories and for providing most of the sensitivity, an accurate modelling of the channel is softer inis the strongly data correlated thanfigure with in a the mismodelling simulation. of It the is ∆ found that this mismodelling 7.2 Corrections to theThe simulation large number ofmodelling events of in the the 0-taganalysis. samples Given allows that for the detailed search investigations is of performed the in intervals of 1-lepton channel is used,and wherein combinations the of pretag MJdistribution sample in is the weighted 2-tagis by MJ found its to template. 2-tag be fraction bands In negligible of from the the a 2-muon comparison sub-channel,background between in the data the MJ and 2-lepton MC background channel. prediction in the side- way, by loosening identification and isolation requirements.by a The normalisation fit is to performed parameters, the dilepton-mass while distribution, the where otherMJ the backgrounds normalisation (mostly factors are found towith be the consistent reduced in size the of 0-, the 1- 2-tag and MJ 2-tag event regions. sample, a To cope procedure similar to that used in the JHEP01(2015)069 ) 2 250 250 3 3 ,jet 1 =1.0) [GeV] µ W T (jet p φ ∆ 2.5 2.5 200 200 t Data 2012 VH(bb) ( Diboson t Single top Multijet W+hf W+cl W+l Z+hf Z+cl Z+l 2 2 150 150 =1.0) µ 1.5 1.5 (b) (b) t VH(bb) ( t Multijet W+cl Z+hf Z+l 100 100 -1 -1 1 1 50 50 = 8 TeV 0.5 0.5 Data 2012 Diboson Single top W+hf W+l Z+cl s = 8 TeV ATLAS s L dt = 20.3 fb ATLAS L dt = 20.3 fb ∫ ∫ 0 0 1 0 0

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3 3 JHEP01(2015)069 t t → ]. Z 66 ] related (and thus 61 of 100 GeV, miss T +jets and miss T E E µν → W 120 GeV. The associated > ], with a separate contribution miss T interval of the 0-lepton channel E 74 -tagging efficiencies for simulated , as are the much smaller uncer- b miss T miss T E E = 20 GeV to less than 5% for jets with ]. The T p 64 , 63 – 34 – -jets. Small uncertainties on the corrections ap- b -jets, the precision is driven by an analysis of b range, for jets with η trigger, an efficiency correction is derived from miss T E of 20 GeV and 1 TeV, respectively. An additional specific uncertainty of about -tagging efficiencies for the different jet flavours are measured in both data and also comes from the uncertainties on the energy calibration (8%) and resolution b T ) intervals, and reach about 3% for the low p V T miss +jets events. This correction amounts to 4.5% for events with an T 200 GeV. p -jets. The total relative systematic uncertainty on the JER ranges from about 10% to The The JES uncertainties are propagated to the Several sources contribute to the uncertainty of the jet energy scale (JES) [ For electrons and muons, uncertainties associated with the corrections for the trigger, For the − E b > µ + T simulation using dedicated event samplesjets [ are corrected withindepend intervals on between the operatingevents jet points in kinematics. by final MC-to-data states For SFs, containing which two leptons. The MC-to-data SFs are close to unity, 20%, depending on the p tainties related to thethe energy and momentum(2.5%) calibration of of calorimeter leptons. energy clusters An not associated uncertainty with on any reconstructed object [ with a 1%–2% affects the energyplied calibration to of improve the dijet-massare resolution also are considered also included. forfor the Corrections and jet uncertainties energy resolution (JER) [ e.g. to uncertainties fromthe in flavour composition situ of calibration jetscorrelated analyses, in components, pile-up-dependent different these event are corrections classes. treated and relative as After systematic independent being uncertainties sources decomposed in on into the the un- analysis. JES The range total from about 3% to 1% for central jets (100–120 GeV). reconstruction, identification and isolation efficiencies areon taken energy into and account. resolution Uncertainties corrections ofuncertainties the is leptons very are small, also considered. typically less The than impact of 1%. these µ the threshold required in the analysis,uncertainties and arise is from below the 1% statistical for uncertaintiesin of this the method two and differences eventhigh observed classes. They are very small (below 1%) for the high All relevant experimental systematicthe uncertainties are trigger considered, selection, such theand as object momentum those reconstruction affecting calibrations andthe and identification, following. resolutions. and the object The energy most relevant ones are discussed in The systematic uncertainties discussedthose in related this to section theelling multijet are: of background the those estimation; simulated of and backgrounds those experimental and associated Higgs origin; boson with8.1 signal. the mod- Experimental uncertainties 8 Systematic uncertainties JHEP01(2015)069 -jets c and on T p -jets in the - and c b to the closest R . Half of the correction range, reaching 5% for 1%) background, uncor- ranges. For 4 T ∼ η p -jets are decomposed into 15 , a correction to c and 4 T p – 35 – ], from a preliminary calibration of the luminosity -tag categories. The MJ background in the 2-lepton 20 b jet)] values defining the B and D regions of the ABCD method, , miss T -tagging fractions measured in region D by those measured in region b E ( φ samples, for which parameterised tagging is used, is applied at low ∆ In the 1-lepton channel, shape uncertainties are assessed in the various regions by In the 1-lepton channel, normalisation uncertainties arise from the statistical uncer- The uncertainty on the integrated luminosity is 2.8%. It is derived, following the same A 4% uncertainty on the average number of interactions per bunch crossing is taken = 20 GeV and 8% above 200 GeV. The uncertainties, which depend on T an alternative template isterval, constructed and with a another track-based alternative4% isolation template interval. in with In the the a 12% muonare calorimeter-based to sub-channel, 50% isolation compared the in- results in with obtained the thoseby with 0% the obtained track-based nominal to isolation with MJ intervals tighter template of or 7%–9.5% looser and isolation 9.5%–50%, requirements, respectively. defined Furthermore, and 22% in thecorresponding LL, uncertainties MM are about and threeMJ-enriched TT times samples. categories, larger respectively. because of In the the smaller muon size sub-channel, ofcomparison the the of evaluations obtained using MJ-enrichedments samples different defined by from isolation those require- applied in the nominal selections. In the electron sub-channel, tainties of the multijet fitsperformed and from to uncertainties construct on the thein non-MJ MJ the background templates. subtractions LL, Normalisationinclusively MM in uncertainties and the are TT 2-tag alsoof categories regions assessed the and to electron in cover sub-channel, the differences the individual between categories. overall multijet normalisation In fits uncertainties the amount performed 2-jet to 2-tag 11%, region 14% and by replacing the B. A systematic uncertainty ofrelated 100% between 2- is and assessed 3-jet, forchannel 1- this and is small 2- also ( at the per-cent level, and an uncertainty of 100% is assigned. into account. 8.2 Uncertainties onIn the the multijet backgrounds 0-lepton channel,varying the the min[∆ robustness of the MJ background estimation is assessed by methodology as that described inscale ref. derived [ from beam-separationthe scans signal performed and backgrounds in estimates November that 2012. are taken It from is simulation. applied to are decomposed into tenfurther components, accounted uncertainties for are in addedobtain generator for specific the MC-to-data applicationis SFs as of used explained as the in systematic additional section V uncertainty. cc MC-to-MC As SFs discussed to jet. in section Half of this correction is assigned as a systematic uncertainty. p the interval between operating points,the are ten decomposed most into significant uncorrelatedcomponents ones components have are a and kept negligible in impact.components, and the The the analysis. uncertainties uncertainties on on It light jets, was to checked which the that analysis the is neglected much less sensitive, with uncertainties at the level of 2–3% over most of the jet JHEP01(2015)069 distribution ]. A system- ). It is found T 73 p for the electron ]), by the parton ), by the amount distributions, the , or by the imple- 75 V T ) are compared, fo- 7.1 p pythia . ]+ pythia herwig 77 9.2 [ , which is therefore used to + ]+ pythia + 76 [ , the top-quark 7 ), by the implementation of the alpgen alpgen AcerMC with HERAPDF [ powheg background in the 2-jet category is left herwig mc@nlo t + t pythia + – 36 – generator ( powheg t t reweightings mentioned in section distributions. For the MVA, systematic uncertainties As explained in section +light jets. In other cases, uncertainties are assessed by powheg W T bb W p m discriminant are covered by the assigned uncertainties. ) and 2 . VH 5 +jets and jet , Z 1 (jet R discriminant, this uncertainty is sufficient to cover all variations observed with the VH In the global fit, the normalisation of the The predictions of the nominal A summary of the systematic uncertainties affecting the modelling of the backgrounds A given source of systematic uncertainty can affect different analysis regions. Whether Details of the assessment of systematic uncertainties are provided below in the con- that, in general, the largestassess deviations further are systematic observed uncertainties for as explained below. floating freely, independently inthe each 3-to-2-jet of ratio the is lepton estimated channels. from the An generator uncertainty comparisons of explained 20% above. on In the tors differing by the PDFshowering choice and ( hadronisation schemeNLO ( matrix element andof the initial- matching and scheme final-state ( mentation radiation of (ISR/FSR) using higher-order tree-level matrix elements ( Top-quark-pair background. is reweighted at generator level to bringatic it uncertainty into amounting agreement to with half measurement [ of this correction is assigned, correlatedcussing across channels. on the 1-lepton channel selection, with those obtained using a variety of genera- such an uncertainty should beresulting treated from as correlated the or global notthe fit depends procedures should on leading be whether to constraints propagated such from decisions one are region provided to incan section another. be Details found in of table BDT different generators, it isin considered addition to on be the sufficient.variations of next If the most BDT not, discrepant an variable uncertainty and is the considered procedure is iterated until all text of the MVA.generators, When all systematic relevant uncertainties variables arelargest are derived discrepancy considered from in independently. a some generator comparison Theuncertainty with between variable covering respect showing this to the the discrepancy, nominal which generator is is symmetrised. assigned an If, once propagated to the flavour composition andaffecting the the other variablespossible, used dedicated as control inputs regions areThis to used is the the to BDTs case extract are for informationcomparison also directly of from considered. MC the predictions data. Whenever based on a variety of generators with the nominal ones. sub-channel are taken as systematic uncertainties. 8.3 Uncertainties on theThe modelling physics-modelling of systematic the uncertainties simulated evaluatedused focus backgrounds in on the the global quantities fit, that are i.e., those affecting the jet multiplicities, the half of the ∆ JHEP01(2015)069 , . bb m pro- frame- W t 120 GeV herwig -channel, s acerMC ]+ < , of the order -channel and V T . For 82 s V T , p p 81 interval: for 2-jet [ madgraph-5 7 V T p for the acerMC production with mc@nlo 120 GeV, and for 2- and 3-jet : 15%), and typically 20% for pythia -channel at low W t V T > t + = 50 GeV, it decreases it by 1% ]. p distribution of the leading jet in 120 GeV. This uncertainty is not V T formalism and the 78 bb T > p p ; for distribution in the 1-lepton channel, m V T p miss T powheg E -channel) are compared, after the 1-lepton production, which need to be considered. mc@nlo t -channel with a t t t mc@nlo 120 GeV interval. Finally, the same approach distribution, from which a 7.5% uncertainty is – 37 – V T = 50 GeV, it decreases it by 40% at 200 GeV. A 120 GeV and > p and for the bb V T < 120 GeV and p m V T The theoretical uncertainties on the cross sections of < p V T shape for 3-jet events, where the corresponding shifts are ; and for the is based on the p pythia bb production. The first uncertainty is on the shape of the acerMC production, respectively [ + m interval for 2-jet events where, when a shift from the nominal distribution is also studied with the same set of generators, W t W t V T bb mc@nlo p mc@nlo m ]. The former is used in the nominal generation, and the second for acerMC 83 , and production (except for 3-jet events at high -channel, and interval for 2-jet events. t 120 GeV. The associated variation is larger in the higher herwig ]. W t V T + p > 80 production; , V T 79 -channel. p In addition to the acceptance uncertainties, the effects of the model variations described Uncertainties on the acceptance for each of the three processes are taken as the largest The predictions of the nominal generators ( The same procedure is used for the The shape of the s W t Event generation with a 7 -channel, second uncertainty is on the 25% and 20%. Finally,the a low third uncertainty is on the work [ above on variables input to the BDTare are found evaluated to and three be shape neededdistribution systematic in uncertainties in the high model increases the rate by 20% for deviations observed, separately for events. They can be asof large 5% as for 52% for 2-jetthe events in the For all three processes, theduction, impact there of are ISR/FSR isTwo interference methods evaluated effects are using available with for this:tion (DS) the Diagram schemes Removal [ (DR)comparison. and the Diagram Subtrac- for channel selection, with thosethe obtained comparison is using made apowheg with variety of generators. For the applied in the 0- and 2-lepton channels. Single-top-quark background. the three processess contributing to single-top production are 4%, 4%, and 7% for the at 200 GeV; the effect is similar, but of oppositeassessed sign, on for the 3-jet normalisation events. calls of for the a shapedifferent systematic but uncertainty correlated on between the and uncorrelated with the 2-lepton channel. leading to correlated shapeand uncertainties for 2-events, and when 3-jet it events, increases and the distribution for by 3% for global fit, this uncertainty is treated as correlated between the 0- and 1-lepton channels, JHEP01(2015)069 ) F Zb Zb Zc µ and , of W bb com- + + back- Zl Zc Zl Zc and . 2 W cl / 1 pythia8 2] ) reweighting, W cl / + 2 ) 2 reweightings are ) jet b ( , Z T 1 T are covered by this p p + (jet powheg ) reweighting is applied 2 ) and factorisation ( φ ) 2 R b components, uncorrelated ) and ( µ 2 jet T , sherpa p 1 jet background are taken directly , W cl + ( 1 2 b (jet and background are determined from m φ +hf events, yielding 12% for each W l (jet and . Comparisons are also made be- components. The notation Z + +hf. The same procedure is used to Zl φ generator in the 2-tag region of the 2 Z ) +hf components are assessed through Zb W l , a ∆ , ∆ W Z ( 7 + background, for which dedicated control 7 alpgen T p herwig Zc + + and sherpa W bb 2 W – 38 – and m with renormalisation ( Zcl and 20% for = [ Zl F alpgen reweighting, uncorrelated systematic uncertainties of uncorrelated between 2- and 3-jet samples. µ Zcl backgrounds are left free in the global fit. The uncer- Z T = bb p / R mc@nlo µ Zbb bl components, respectively. For the ∆ generator are compared to those of ] and of distribution is compared between data and simulation in the Zb and with the nominal As explained in section 84 As explained in section bb [ + , with m bb Zcl Zc / component, no reweighting is applied but a systematic uncertainty is sherpa bc components. Uncorrelated systematic uncertainties amounting to half of and alpgen W b and Zl W cl + herwig++ bb / + and components. The differences between cc W cc components. independently modified by factors of 2 or 0.5 and also with different PDF sets , W l Zc 8 bb Zb / To assign further uncertainties on the The normalisation and the 3-to-2-jet ratio for the The shape of the The normalisation and the 3-to-2-jet ratio for the The nominal scales are taken as + +jets background. 8 bl +jets background. mc@nlo predictions of the a tween samples generated with a scales ground is also assignedbackgrounds an are uncertainty left of free 10%. in the The global normalisations fit. ofregions the are nottor available level, in with the kinematic data, selections extensive mimicking comparisons those are applied performed after at reconstruction. genera- The assigned, equal to the fullbetween correction 2- applied and to 3-jet the events. from simulation, both withbetween a data 10% and uncertainty. prediction This in is the based 0-tag on sample. the The agreement 3-to-2-jet observed ratio for the uncertainty. W to the the correction are assigned toFor these the two components, for each of the 2- and 3-jet categories. 2-tag region of the 2-leptonuncertainty channel, is excluding derived the that, 100–150 GeV when range,it it from decreases increases which the it a dijet-mass shape by distributionZb 5% by at 3% 200 at GeV. 50 GeV, This uncertainty is applied uncorrelated to the tainties on the 3-to-2-jeta ratios comparison for of the 2-lepton channel; these are 26%estimate for uncertainties on theof flavour fractions within half the correction are assignedis to meant the to indicate thatand a systematic uncertainty is treated as correlated betweendata the in the 0-tagnormalisations region of the of the 2-lepton channel, both with an uncertainty of 5%. The applied to the a systematic uncertainty amountingponent, to while half an of uncertaintycomponents. the amounting to This correction is the is done full assigned separatelytreated correction for to as is 2- uncorrelated. the and assigned 3-jet to For events, the the and all these uncertainties are Z JHEP01(2015)069 ; > are V T pairs p WW . The gener- b b by factors cc/bb . For F alpgen µ V T , it is further- p distribution by and pythia8 and + and W T W cc p R + µ bc/bb sherpa W bb production is affected by powheg interval, to two uncorrelated at NLO in QCD. The sources VZ V T . For p +hf processes. Shape uncertain- W channel and intermediate for mcfm W bc + intervals and in exclusive 2- and 3-jet ZZ V T intervals (with the three highest intervals p , the production of light flavours and heavy and 12% for each of W bl lineshape in W T p ]). As a result, a 10% uncertainty is assigned b b distributions. When the former increases the 85 and – 39 – bl/bb W T → p alpgen Z W cc + and -partons, is used to remove the overlap between bb b intervals (with the three highest intervals correlated for the m W bb , W T The uncertainties on the cross sections for diboson production p ]. This procedure leads, in each W cl 86 , is uncorrelated between ) are assessed at parton level using W l +hf samples: 35% for ], i.e., using the envelope of predictions from the CT10, MSTW2008NLO, ZZ W bl/bb 87 channel, roughly half this size in the and dependence observed. separation between = 50 GeV, it decreases it by 23% at 200 GeV. It is taken as correlated for all V T R W T p p WZ WZ , The shape of the reconstructed The uncertainties due to the PDF choice are evaluated according to the PDF4LHC rec- The scale uncertainties are evaluated by varying simultaneously Predictions using the inclusive production of all flavours by +hf processes, and uncorrelated between the 2- and 3-jet samples. WW and NNPDF2.3 PDF setswith and no their associated uncertainties. They range from 2%the to parton-shower 4%, and hadronisationsessed model. by comparing A the shape-only lineshapes obtained systematic with uncertainty the is nominal as- 200 GeV, the two uncertainties affectingin the the 2-jet category can beand as the large uncertainty as affecting 29% the and 3-jet 22% category is aboutommendation 17% [ in all channels. categories, the uncertainties are evaluated forcategories each channel (2 separately and in those 3 intervalsthe and final-state prescription partons of within ref. the [ uncertainties nominal in selection the acceptance) following 2-jetthe category, removal of one 3-jet for events,uncertainty and 2+3 in to jets one the inclusively in 2-jet the and category. 3-jet one category These associated anti-correlated uncertainties with with the are latter largest at high of uncertainty considered are thePDFs. renormalisation and The factorisation nominal scales scales and aresystem the dynamically and choice set the of to nominal half PDFs of are the the invariant mass CT10 of set. of the 2 diboson or 0.5. Since the analysis is performed in uncertainty on correlated for the dijet-mass analysis). Diboson background. ( element and parton-shower levels. (For flavours are performed separately at theon matrix-element the level; a ∆ dedicated procedure,produced based at the matrix-element andassigned parton-shower levels.) in The the following uncertainties are dijet-mass analysis). When the9% latter for shape uncertainty increasesW the compared after full reconstruction and eventfractions selection that to assign take uncertainties on properly the flavour into account heavy-flavour production at both the matrix- to the 3-to-2-jet ratio,ties taken as are correlated also between assesseddijet-mass all for distribution by the 23%as at uncorrelated 50 GeV, for it decreasesmore uncorrelated it among by 28% at 200 GeV. It is taken (CT10, MSTW2008NLO and NNPDF2.3 [ JHEP01(2015)069 shape samples to reach V T p V T production, p ZH → ZH gg and of PDFs. F µ . Acceptance variations varied independently by F , a conservative uncertainty and µ R µ ZH herwig and samples, when they increase the → R ] is used, after kinematic selections spectrum is seen to be affected, and . The uncertainties on these cross spectrum associated with the NLO q H µ ) q V T 86 3 ]. The contribution of decays to final V T p p 120 GeV interval, where the variation is 11 and with and W/Z > ( , with samples. V T p → signal samples are normalised respectively to WH . The relative uncertainty on the Higgs boson ZH q – 40 – q production. It is larger (3%) for → → pythia8 ZH q ZH pythia8 q = 125 GeV [ gg → → WH , respectively, for the 2- and 3-jet categories combined, H m gg gg samples. There is no evidence of a need for ZH . The same procedure leads to PDF uncertainties of 2.4% → ZH ZH , and ] are typically at the level of 2%, increasing with = 50 GeV, they decrease it by 3% at 200 GeV. These variations gg interfaced to → 38 interfaced with . V T → interval. ZH p 5 . The relative difference between the shapes is 20% for a dijet mass gg and is 3.3% for q V T is verified to amount to less than 1% after selection. q → p b and 17% for b b q b ZH q H powheg ) , powheg → herwig q q ] include those arising from the choice of scales WH W/Z , ( 88 tunes. The effect of the parton-shower modelling is examined by comparison of → → q WH q q The effect of the underlying-event modelling is found to be negligible, using various A summary of the systematic uncertainties affecting the modelling of the Higgs boson The applied uncertainties on the shape of the Acceptance uncertainties due to the PDF choice are determined in a similar way, Acceptance uncertainties due to the choice of scales are determined from signal samples The scale uncertainty is 1% for q → q signal is given in table pythia simulations by of 8% are seen, exceptat for the 3-jet level events of in 13%. the These variations are taken as systematic uncertainties. to 5% inuncertainties the related 3-jet to the PDFs. electroweak corrections [ 2.5% in the highest shape uncertainties are derived.distribution For by the 1% for are 2% and 8%, respectively, for the following the PDF4LHC prescription. They range from 2% in the 2-jet applied at generator level, leadingq to acceptance uncertainties ofand 3.0%, of 4.2%, 3.4% 3.6% and and 1.5%with 3.3% for an for acceptance the uncertainty 3-jet associated category. withcategory the The to removal latter form of uncertainty the 3-jet is 2-jet events anti-correlated from category. the In 2+3-jet addition, the branching ratio to states other than generated with factors of 2 or 0.5. The procedure advocated in ref. [ sections [ due to the contribution of thescale gluon-gluon uncertainties initiated are process. similar (1%) Under for theof assumption 50% that is the inferredfor for around 125 GeV. 8.4 Uncertainties onThe the signal modelling their inclusive cross sections as explained in section ator and with JHEP01(2015)069 ) W t ) ) gg gg S S S S S S S S ), 17% ( 5% 26% 20% 12% 10% 10% 35% 12% 20% ), 50% ( 7.5% q 100% 3.3 % q q 2%–5% 2%–4% 8%–13% 3%–52% 3%–29% 2%–60% q 1.5%–3.3% 3.3%–4.2% -channel), 7% ( t -, s 1% ( 2.4% ( 4% ( t t +jets +jets Signal – 41 – Z W Multijet Diboson Single top ratio miss T bb bb E m m , , , bb W bb / V T V T m p p , ratio ), ), T W cc 2 2 V T p ratio ratio p , jet jet +hf 3/2-jet ratio , , 1 1 1 Zbb b T W W bb W bb p / 3/2-jet ratio , / normalisation, 3/2-jet ratio , shape (scale) shape (NLO EW correction) (jet (jet normalisation, 3/2-jet ratio bb bb φ φ +hf 3/2-jet ratio +hf/ V T V T Cross section (scale) Cross section (PDF) Branching ratio Acceptance (scale) 3-jet acceptance (scale) p Acceptance (PDF) p Acceptance (parton shower) Zl Zcl Z Z ∆ W l W cl W bl W bc ∆ 3/2-jet ratio High/low- Top-quark Cross section Acceptance (generator) m Cross section and acceptance (scale) Cross section and acceptance (PDF) m 0-, 2-lepton channels normalisation 1-lepton channel normalisation Template variations, reweighting . Summary of the systematic uncertainties on the signal and background modelling. An Table 5 “S” symbol is used when only a shape uncertainty is assessed. JHEP01(2015)069 . A binned b . In the dijet- b interval of the 6 , that multiplies V T µ p -tagging categories ] is used to extract b is shifted away from θ 90 , intervals, two number- 89 V T intervals, the two number- p . The parameterisation of -discriminant distributions θ discriminants in the 24 2-tag V T p VH VH distributions in the 81 2-tag signal distributions are combined in each c bb 1 . For each NP, the prior is added as a bins in the 38 regions of the MVA, to m θ bins in the 92 regions of the dijet-mass c c 1 MV interval of the 2-jet 1-tag category of the These BDT 1 9 V T p MV , which are constrained by Gaussian or log- -tagged jet in the 11 1-tag control regions of MV b θ – 42 – and ), which decreases it as soon as distributions in the 100–120 GeV bb -tagging categories (LL, MM and TT). Here and in the θ b m bb µ, 120 GeV intervals, which also results in 11 1-tag control ( m L > V T p -discriminant and distributions are to be understood as transformed distributions, as VH distributions of the -tagging categories. In the 1-lepton channel, the bb b . In the MVA, the inputs are the BDT c 1 m 6 MV 120 GeV and < V T p The impact of systematic uncertainties on the signal and background expectations is The different regions entering the likelihood fit are summarised in table While keeping distinct MM and TT categories in the 1-lepton channel improves the sensitivity, this is 9 its nominal value. Theare statistical included uncertainties of through background bin-by-bin predictions nuisance parameters. from simulation not observed for the 0-the and sensitivity 2-lepton in channels. all Keeping lepton the LL channels. category separated from the others improves to prevent normalisation factors fromof becoming signal negative in and the background fit.each events NP The in expected is each numbers chosen binlog-normally such are distributed that for functions a the of normallypenalty predicted distributed term signal to and the likelihood, background yields in each bin are analysis, and 251 BDT be used in the global fits. described by nuisance parametersnormal probability (NPs), density functions, the latter being used for normalisation uncertainties 2-jet 2-tag categories (LL, MM,inputs and TT) are of the the 0-leptonthe channel. MVA For selection the and MVA, additional 0-lepton in channel. the In 100–120 GeV the dijet-massof analysis, the the regions. Altogether, there are 584 signal regions defined by the threeof-jet lepton categories, channels, and up to two are LL, MM andcombined TT. MM In and the TTare 0- category supplemented and by (MM+TT). 2-lepton the channels, three they are the LL category and a mass analysis, the inputs toregions the defined “global by fit” three are the channelsof-jet categories (0, (2 1 or or 3), 2 andrest three leptons), of this up section, to five explained in section likelihood function is constructed asof the the product input of distributions Poisson-probability involving terms thebackground over numbers yields, the of taking bins into data account events the andand effects the of the expected the systematic signal floating and uncertainties. background normalisations 9.1 General aspects A statistical fitting procedure basedthe on signal the strength Roostats from frameworkthe the [ SM data. Higgs The boson signal strength production is cross a section parameter, times branching ratio into 9 Statistical procedure JHEP01(2015)069 , ≤ by 91 µ of the 0 p method [ BDT is an input to s 2-lepton bb distribution in the CL c m with its associated BDT 1 c ]. 1 µ discriminant”. For each 92 . Expected results are MV µ , BDT BDT ) MVA MV VH ˆ θ ≤ 1-lepton ˆ µ µ, (ˆ ) ) ≤ ∗ ∗ L ( ( / ) µ distribution, which is reoptimised. θ ˆ ˆ BDT BDT bb 0-lepton µ, ( m L = is obtained from the variation of 2 ln Λ intervals: five in the dijet-mass analysis and two µ . The results are presented in terms of: the µ 0 V T σ p 2-lepton interval of the 0-lepton channel, the MVA uses the – 43 – interval (100–120 GeV) of the 0-lepton channel where V T p 2 ln Λ c V T with Λ 1 p − bb bb bb µ m m m = MV 0 1-lepton q . These distributions are input to the fit for the 2-jet and 3-jet 2 ln Λ value is obtained by maximising the likelihood function with 2 − ) In the low µ Dijet-mass analysis ∗ = is then constructed from the profile likelihood ratio 10 µ µ q q 0-lepton is now defined without the constraint 0 µ are the parameters that maximise the likelihood with the constraint 0 are the nuisance parameter values that maximise the likelihood for a given . The fitted ˆ 1-tag 2-tag ˆ θ µ µ σ θ ˆ ˆ and Channel . The distributions used in each region by the likelihood fit in the dijet-mass analysis and LL MM TT µ , and µ While the analysis is optimised for a Higgs boson of mass 125 GeV, results are also The test statistic distributions in the LL, MM and TT 2-tag categories as well as the This type of pseudo-data sample is referred to as an Asimov dataset in ref. [ ]. To measure the compatibility of the background-only hypothesis with the observed ≤ 10 bb . This test statistic is used for exclusion intervals derived with the ˆ the BDTs. The MVA resultsfor for other each masses of are the thereforeprovided obtained masses in using the tested BDTs rest retrained at ofof 5 this GeV 125 GeV. section intervals refer between to 100 the and analysis 150 performed GeV. for a The Higgs details boson mass extracted for otheranalysis, masses. except for These the binningFor are the of MVA, obtained the it transformed is without observedfor that any which the change performance the degrades to BDTs for the are masses away trained. dijet-mass from 125 GeV, This is largely due to the fact that respect to all parameters.one The unit, uncertainty where Λ obtained in the sameby way as the the expectation observed fromfrom results simulation the by with fit replacing all to the the NPs data data. set in each to input their bin best-fit values, as obtained µ 92 data, the test statistic95% used confidence is level (CL)background-only upper hypothesis; limit and on theuncertainty the best-fit signal signal-strength strength; value the ˆ probability where ˆ µ are combined in them MVA. ( 1-tag category. Table 6 in the MVA applied toentry the listed, 8 there TeV are data. additionalin Here, divisions the “BDT” into stands MVA, for ascategories “BDT shown separately, in except table inonly the the low 2-jet category is used. In the 0- and 2-lepton channels, the MM and TT 2-tag categories JHEP01(2015)069 t t Zcl . As back- 7 lepton) and Zcl τ Zbb range probed , , and (fully leptonic V T b p ) Zbb W cl , `ν , background is almost t W cl → background is normalised t W bb , t , t t W t W bb background contributes quite , t t t t 12 05 10 15 04 09 14 ...... 0 0 0 0 0 0 0 ± ± ± ± ± ± ± 88 09 14 83 99 12 36 ...... leptons. Futhermore, the 0 1 1 0 0 1 1 Scale factor τ 100 GeV in contrast to being inclusive in the 1- – 44 – > , a large number of sources of systematic uncertainty V T p 8 2-lepton 1-lepton 0-lepton t t t Zcl Zbb W cl W bb t t t Process background is normalised in the 2-jet category independently in t t ) decay is missed, while in the 2-lepton channel it is likely that an q q , the (semileptonic decays) with a missed light-quark jet. Finally, in the 0- → 8 b ) 0 W q ( q b → → . Factors applied to the nominal normalisations of the t W As described in detail in section differently in the 2-tagthe 3-jet 2-lepton regions channel of onfrom the the a other. 0- and In 1-leptonISR the or channels 0- FSR on and jet one 1-leptonof is side, channels, lepton selected. it and channels, is This of the likely is systematic that the uncertainty a reason attached for jet to not correlating, the between 3-to-2 these jet two ratio sets for the and 2-lepton channels. are considered. The number ofappropriately nuisance uncorrelate parameters the is impact evenbackground of larger processes because the or care same across is source regionsavoids taken of unduly accessing to systematic very propagating uncertainty different constraints. across parts For of instance, phase the space. This into ( lepton channel, the main contributionsundetected are and from fully from leptonic semileptonicjet; decays decays with here with the again, two a the leptons is missed missed different lepton leptons in and are the often a 0-lepton missed channel: light-quark different between the three channels.entirely In due the to 2-lepton channel, eventsdecays) the with in all which final-state bothchannel, objects it top is detected quarks in (apart part decayundetected, due from and into to in the fully ( part neutrinos). leptonic to decays cases with where In one one the of of 1-lepton the the top leptons quarks (often decays a as above and the other processes. The correspondingas factors resulting applied from to thestated the global in nominal fit section background of normalisations theeach of MVA to the the leptonlepton 8 channels. TeV channels data, The is reason are that for shown uncorrelating the in the table regions normalisations of in phase the space three probed in the 2-jet category are very and systematic uncertainties. 9.2 Technical details The data have sufficient statistical power toNPs, constrain which the are largest background-normalisation left free to float in the fit. This applies to the Table 7 grounds, as obtained fromin the the global 2-jet MVA category fit independently to in the each 8 of TeV the data. lepton The channels. The errors include the statistical JHEP01(2015)069 VH W l and -tagging b W cl distributions of the φ backgrounds but, in the +jets processes, which is backgrounds. As explained W W b W l and and W cc W cl reweighting in the – 45 – φ ) is close to twenty thousand, which renders the fits highly σ 1 − ) variation. The limited size of the MC samples for some simu- σ 1 and ± σ backgrounds, uncorrelated with the uncertainty applied to the , this reweighting is not applied to the W b 7 and The behaviour of the global fit is evaluated by a number of checks, including how much Altogether, given the number of regions and NPs, the number of systematic-variation The fit uses templates constructed from the predicted yields for the signal and the related systematic uncertainties.the To expectations assess from these simulation and effects,their the comparisons observations source in are is the made investigated, data.systematic and between When uncertainties differences this by arise, means leads ofbeing in additional propagated a NPs. from number This one of kinematic is cases region to to prevent to a another uncorrelating constraint if further from this is not considered well moti- shape. This is onlyare done expected. for those This systematic procedurefactor uncertainties of reduces where two. the opposite-sign variations number of systematic-variation templates byeach a NP is pulled awayrespect from to its its nominal nominal uncertainty, value, and how which much correlations its develop uncertainty between is initially reduced uncor- with uncertainty is dropped ifall the bins). associated Additional template pruning variation criterialess are is than applied below 2% to of 0.5% regions the where (belowbackground the total 0.5% prediction signal background contribution in and by is where less theif than systematic the 0.5%. variations impact up- Furthermore, the and total shape down-varied uncertainties shapes are dropped are more similar to each other than to the nominal discriminant, and with at most one local extremum fortemplate a pairs dijet (+1 mass. time consuming. Toimpact address on this the issue, final results systematic are uncertainties pruned that away, have region a by negligible region. A normalisation (shape) the JES uncertainties, additionalthe statistical templates fluctuations of may systematic beto variations. introduced, each which systematic-variation In template affect suchstraints in cases, that each region. the a statistical smoothing Binsshapes uncertainty procedure are of in merged is the each based applied systematic-variation bin on templates should the remain be con- physical: less monotonous than for 5% a and BDT that the of systematic variations.reweighting of When the nominal the template,already impact no present statistical of in fluctuations a the areuncertainties. expected nominal systematic For beyond template. variation those, those no translates This specificvariation is into action may the is a taken. introduce case, On for changes the instance, in other for hand, the the when events a selected, systematic as is the case for instance with being of experimental origin. various backgrounds in theuncertainties bins are of encoded the in inputeach distribution templates up-and-down in of ( each variations region. relativelated to background The processes the systematic in nominal some template regions for can cause large local fluctuations in templates derived in the 0-tagin sample section and applied toabsence of the further information,W an cc uncertainty is assessedbackgrounds. for Altogether, the the ∆ fit has to handle almost 170 NPs, with roughly half of those background. Another example is the ∆ JHEP01(2015)069 W T p W bl/W bb . The five µ distribution is , shifted up or ˆ θ bb m distribution peaking at bb 120 GeV; on the m -quarks and produced in as- > b are dropped: those associated W T p µ set to unity, the SM value. Each of µ background normalisation; on the W bb is a measure of the observed impact of the µ – 46 – backgrounds for spectrum and with a and of its uncertainty are determined for both the +hf background; and on the signal acceptance due to bb T µ p W cc W boson has a signature very similar to the one considered boson decaying to a pair of and Z 120 GeV; on the ]. A large number of event samples are randomly extracted Z > or 93 W bb W T W p boson mass. For the MVA, the BDTs are retrained to discriminate with the NPs ordered by decreasing post-fit impact on ˆ Z 16 Since the same data sample is used for both the dijet-mass analysis and the MVA, the It is particularly useful to understand which systematic uncertainties have the largest values to be compared and their statistical correlation to be extracted. At the same ˆ in this analysis, butlower values. with The a cross section softer a is about mass five of times 125 larger GeV.procedure. than for For Diboson the the SM production dijet-mass Higgsreoptimised analysis, is boson for the therefore with the binning used of as the a transformed validation of the analysis time, the expected distributionsdijet-mass of analysis and ˆ the MVA. 9.3 Cross checksDiboson using diboson production production with a sociation with either a from the simulated samples, withthem the is signal representative strength ofexpected the yields integrated as luminosity well usedis as for of subjected the associated data to Poisson analysis bothµ fluctuations. in the terms Each dijet-mass of of these analysis event and samples the MVA, thus allowing the two fitted shape in the 3-jet categorythe for parton-shower the modelling. consistency of the twothe final “bootstrap” results, method i.e., the [ two fitted signal strengths, is assessed using ranking of the systematic uncertaintiesis obtained shown with in the figure MVAsystematic applied uncertainties to the with 8 the TeVdijet-mass data largest shape impact for are, the normalisation in ratio descending for order, those: on the negligible effect onwith the the expected muon fitted momentumone uncertainty scale of on and those ˆ resolution associatedgluon and with composition with the the of electron jet theassociated energy energy backgrounds, with resolution; which scale; the turn and difference out those to in associated be energy with fully the response correlated quark- between with quark those and gluon jets. The down by its fitted uncertainty,properly with into all the account other theof parameters correlations allowed the between to shift systematic vary so uncertainties.considered in as NP. the The to The take magnitude fitted sameof procedure signal its is strength associated repeated, ˆ using uncertaintytime to the and provide nominal its values therefore of expected to the impact. enable NP To and more reduce detailed the fit computation studies, some of the NPs which have a independently, which can also help to identify from which region eachimpact constraint originates. on the final results,purpose, and a so-called therefore ranking should of befit the considered NPs is is with performed established. greater again care. For with each the For systematic this uncertainty, corresponding the NP fixed to its fitted value, vated. The stability of the results is also tested by performing fits for each lepton channel JHEP01(2015)069 from ˆ θ for the µ -axis, when x modified upwards or µ µ µ 6 ∆ ˆ θ 0.2 2 θ ∆ )/ 0 0.15 4 θ 1.5 - θ Postfit Impact on Postfit Impact on 0.1 1 σ σ Normalisation +1 -1 Pull: ( , referring to the top 2 µ 0.5 0.05 to its post-fit value -1 0 0 0 θ -0.5 -0.05 -2 Ldt = 20.3 fb -1 – 47 – ∫ -0.1 -tagging uncertainties are decomposed into uncorrelated -4 -1.5 b =125 GeV -0.15 = 8 TeV, H s -2 m shape shape jj jj -axis, show the deviations of the fitted nuisance parameters m m x c c shape (2-jet) normalisation normalisation shape (3-jet) normalisation normalisation normalisation t V T V T V T b b b , Z+c , W+c > 120 GeV) b Jet energy scale 1 b V T Z+b W+b normalisation (2-jet) Jet energy resolution , expressed in terms of standard deviations with respect to their nominal Z+b b b-jet energy resolution > 120 GeV) 0 (p W+b W+HF p W+HF p V T Dilepton t b-jet tagging efficiency 4 -axis. The boxes show the variations of ˆ θ ttbar high p y ATLAS W+bl to W+b (p Z+bl to Z+b . The associated error bars show the post-fit uncertainties of the nuisance param- Signal acceptance (parton shower) -axis, show the fitted values and uncertainties of the normalisation parameters that θ x , the jet energy scale and on the . Impact of systematic uncertainties on the fitted signal-strength parameter ˆ µ 8.1 eters, relative to theirto nominal the uncertainties. bottom The openare circles freely floating with in their thein error fit. bars, section The also normalisation referring parameterscomponents; have a the pre-fit labels value 1 of one. and 4 As refer explained to such components. downwards by its post-fit uncertainty,and and open repeating areas the correspond fitcles, to as referring the explained to upwards in the and thetheir bottom downwards text. nominal variations, values The respectively. hatched Theuncertainties ∆ filled cir- Figure 16 MVA applied to the 8 TeVimpact data. on The systematic ˆ uncertaintiesfixing are the listed corresponding in individual decreasing nuisance order parameter of their JHEP01(2015)069 fits” VZ distributions bb m for 2-tag signal regions 17 = 125 GeV is included as a background, H m – 48 – with respect to the SM expectation, except for the left freely floating, to study the correlation between µ VZ µ and production, which is treated as a background and constrained VZ µ WW discriminants of the MVA are shown in figure VZ 120 GeV in the 2-jet category of the 0-, 1- and 2-lepton channels. > V T p As an additional check, fits are also performed with both the diboson and Higgs boson trained for that same mass, as well as the associated optimised binnings. of the BDT with signal-strength parameters the two strength parameters.with The binning fits optimised in for the a Higgs dijet-mass boson analysis mass use of the 125 GeV. The fits in the MVA use BDTs are performed, wherewith the a normalisation multiplicative of scale the factor small contribution diboson from contributions iswithin its allowed uncertainty. to A SM vary Higgswith boson a with production cross section at the SM value with an uncertainty of 50%. Distributions the diboson signal from all backgrounds (including the Higgs boson). So-called “

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= VZ 1.5 µ VZ fit 0.67 0.80 0.77 0.74 Ldt=4.7 fb ∫ (b) 09(stat 1 . best fit 0 for (a) the 7 TeV, 8 TeV and values for the lepton channels =7 TeV, s ± stat. tot. VZ VZ ) decay channels considered are 0.5 µ 74 µ . ATLAS W/Z 0 2 lepton 1 lepton 0 lepton Combination , from which the ratio of the observed signal b b → – 60 – 3 -1 ) ) ) Z 0.39 0.37 0.16 0.14 0.15 0.13 + − + − + − 2.5 =125 GeV Ldt=20.3 fb H ∫ ). The analysis procedure is validated by a measurement -quark fragmentation, and on the transverse momentum 0.10 0.09 0.09 0.09 0.30 0.29 . The dataset corresponds to integrated luminosities of . + − + − + − b ( stat syst ) ( ( ( collisions at 7 TeV and 8 TeV, respectively, recorded by the for m 2 νν =8 TeV,

s SM σ ; pp tot / -1 has been presented. The ( 0.19 0.17 0.17 0.16 0.49 0.47 σ → + − + − + −

= b 24(syst . VZ b 1.5 Z µ 0 0.50 0.77 0.74 VZ fit production with from Ldt=4.7 fb ∫ ± 1 Z (a) ) . ) − 1 and best fit =7 TeV, s `` stat. tot. W/Z → 0.5 32(stat . 0 Z . The fitted values of the diboson signal strength , ATLAS ± and 20.3 fb 0 1 `ν 52 − . 7 TeV 8 TeV We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Aus- For a Higgs boson mass of 125.36 GeV, the observed (expected) deviation from the The analysis is carried out in event categories based on the numbers of leptons, jets, and → = 0 Combination We thank CERN for thefrom very our successful institutions operation without of whom the ATLAS LHC, could as not well be astralia; the operated support efficiently. BMWFW staff andFAPESP, Brazil; FWF, NSERC, NRC and Austria; CFI, Canada; ANAS, CERN; CONICYT, Azerbaijan; Chile; CAS, SSTC, MOST Belarus; CNPq and µ of the yield of ( yield to the Standard Model expectation is found toAcknowledgments be 0 alternative analysis using invariant-mass distributionsto of consistent the results. Higgs boson candidates leads background-only hypothesis corresponds toand a the significance ratio of of the 1.4 measured (2.6) signal standard yield to deviations the Standard Model expectation is found to be 4.7 fb ATLAS experiment during Run 1 of the LHC. jets tagged as originatingof from the vector-boson candidate. A multivariate analysis provides the nominal results. An 12 Summary A search for theboson and Standard decaying Model into HiggsW boson produced in association with a Figure 26 combined datasets, and (b) for thedataset. three lepton The channels MVA separately is andare used combined, obtained for for from the the combined a 8 simultaneous TeV fit data. with The the individual signal strength for each floating independently. JHEP01(2015)069 . 11 – 9 – 61 – ˇ S, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wal- The crucial computing support from all WLCG partners is acknowledged gratefully, A Tables of event yields The event yields in each category for the multivariate analysis are shown in tables in particular from CERN(Denmark, and Norway, Sweden), the CC-IN2P3 ATLAS (France), Tier-1 KIT/GridKA(Italy), (Germany), facilities INFN-CNAF at NL-T1 TRIUMF (Canada), (Netherlands),(U.S.A.) NDGF and PIC in the (Spain), Tier-2 facilities ASGC worldwide. (Taiwan), RAL (U.K.) and BNL way; MNiSW and NCN, Poland;of GRICES and Russia FCT, and Portugal; MNE/IFA, ROSATOM,ARRS Romania; Russian MES and Federation; MIZ JINR;lenberg MSTD, Foundation, Sweden; Serbia; SER, MSSR, SNSFNSC, Slovakia; and Taiwan; Cantons TAEK, of Turkey;Kingdom; Bern STFC, DOE and the and Geneva, Royal NSF, Switzerland; United Society States and of Leverhulme America. Trust, United Czech Republic; DNRF, DNSRCand and Lundbeck NSRF, Foundation, European Denmark; Union; EPLANET,BMBF, ERC IN2P3-CNRS, DFG, CEA-DSM/IRFU, HGF, France; MPGISF, GNSF, and MINERVA, Georgia; GIF, AvH I-CORE Foundation,JSPS, Germany; and Japan; GSRT Benoziyo CNRST, and Center, Morocco; NSRF, Israel; Greece; FOM INFN, and Italy; NWO, MEXT Netherlands; and BRF and RCN, Nor- and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR,

JHEP01(2015)069

ieiodfi.Alsseai netite r nlddi h niae uncertainties. indicated the in included are uncertainties systematic All fit. likelihood

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JHEP01(2015)069

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h xetdsga n te akrudyed o ahctgr fte1lpo hne fe h ulslcino h multivariate the of selection full the after channel 1-lepton the of category each for yields background fitted and signal expected The . 10 Table

35 25 3637 5125 971838 4977 2356 5551 3472 6336 42557 93359 Data

± 5501 43 ± 3376 57 ± 6447 200 ± 42570 320 ± 93350 Total ± 1796 55 ± 4995 33 ± 2405 50 30

J( MJ 309 2 . 1 . 80.8 58 3.2 117 4.9 227 91 5300 ) µ

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48 12 8 2 22 . 0.4 1.1 20 42 322 588 11320 24980 +l W

igetop Single 3021 638692153188 503 261 619 318 66 2815 7390

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JHEP01(2015)069

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19 8311 8. 88414 2858 287.7 1916 2853 21090 +hf Z

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Fleischmann 170 , V. Croft 124b , 133a , M. Curatolo , S. Donati , B. Di Micco 29 , U. De Sanctis 107 , S. Fernandez Perez , M.J. Da Cunha Sargedas De Sousa , J.E. Derkaoui , P. Davison , P. de Jong , N. Ellis 89 , M. Dyndal 21 50b , M. Endo , D. Francis , , O.A. Ducu , C. Deluca , J.I. Djuvsland , H. Esch , M. Dell’Orso , D. Costanzo , D.E. Ferreira de Lima , T. Dai 74 39 78 83 , T. Doherty 177 153 , D. Fournier 24d , A.T. Doyle 83 124a 130 30 106 55 38a 22 , M. D¨uhrssen 133a , C. David , J. Faltova 50a , G. Eigen 100 49 , C. Debenedetti , J. Fischer , J. Ernst 117 51b , S.M. Farrington 168 , A. Ezhilov 71 120 , A. Dimitrievska 2 77 21 121a 78 , S. Cr´ep´e-Renaudin 25 160a 15 61 144 85 176 29 A. Fischer P. Fleischmann L.R. Flores Castillo D. Fortin S. Franchino A. Favareto M. Fehling-Kaschek A.B. Fenyuk R. Ferrari A. Ferretto Parodi M. Fincke-Keeler O.C. Endner G. Ernis M. Escalier H. Evans R.J. Falla S. Farrell M.T. Dova G. Duckeck L. Duguid M. Dwuznik T. Eifert F. Ellinghaus A. Di Mattia D. Di Valentino S. Diglio T. Djobava C. Doglioni M. Donadelli T. Del Prete L. Dell’Asta P.A. Delsart D. Derendarz P.O. Deviveiros A. Di Domenico W. Davey A.R. Davison R.K. Daya-Ishmukhametova N. De Groot A. De Salvo R. Debbe G. Cree M. Cristinziani J. Cummings M. D’Onofrio A. Dafinca M. Dano Hoffmann M.J. Costa JHEP01(2015)069 , , , , , , , 67 38a , , 127 161 118 , , 138 154 31 25 , , , ,e , , 3 , , , 155 44 , 77 , , 157 , 50b , , 42 168 , , 173 8 , , 42 16 , , 46 131 , 44 , 147b , , 6 , 30 , , 50a 92 54 , , 78 30 83 76 , 25 33d , J. Hejbal 36 16 176 , , , 147a 154 , T. Hayashi , , 49 95 , 110 , , M. Hasegawa , A.A. Grillo 20a , K. Hanagaki 81 8 , N. Guttman 30 , S. George , J.P. Grohs 177 , H.A. Gordon 168 123 107 , 78 , P. Ge , R.W. Gardner 33b 54 , K.H. Hiller , S. Gkaitatzis 97 117 , T. Heck , M. Haleem , I. Grabowska-Bold , C. Fukunaga 10 , D.M. Gingrich 15 130 , B.J. Gallop 28 , F.M. Giorgi , M. Hamer 18 , C. Gumpert 119 , C. Helsens 54 28 34 17 178 , S. Harkusha , G. 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Glaysher J. Godlewski A. Gomes P. Gauzzi Z. Gecse C. Gemme D. Gerbaudo S. Giagu S.M. Gibson E. Fullana Torregrosa A. Gabrielli P. Gagnon P. Gallus F. Garberson N. Garelli S.T. French JHEP01(2015)069 , , , , , , , , , 9 , , 30 74 120 , , 148 , , , 105 81 128 74 8 , 39 , 120 , 98 104a 9 130 , 117 , 80 30 , ,s , , 11 , , , , , 137 , , , 110 , 122 , 48 147b , 53 , , ,o 171 , 29 49 88 152 144 , , , , 10 65 31 , 5 , , , 134b 176 36 28 , P. Iengo , , Z. Hubacek , H.Y. Kim , 147a 106 , J. Jakubek , J. Jovicevic 66 , K. Korcyl , G. Jarlskog , , R.S.B. King , M. Jackson 70 111 33b 42 84 , J. Hrivnac 48 168 51b 136e 134a 127 171 , J. Kretzschmar 110 168 122 , F. Kiss , C. Kourkoumelis 16 , S. Hou , T. Koi , K. Iordanidou , , M. Huhtinen , A. Knue , C.W. Kalderon 45 58c , G. Jones , M.W. Krasny , V.A. Korotkov , V.A. Kantserov 55 66 , M.R. Hoeferkamp 38a , T. Koffas , T.M. Hong 72 85 45 98 158 28 , F. Khalil-zada 30 135a , D. Jennens 140 , R. Konoplich 15 , W. Kozanecki 129 147b , G. Iacobucci , , T.J. Khoo , Y. Ilchenko ,r , Y. Jiang , P.F. Klok , P. Klimek , T. Kondo 159 151 , M. Kaci , Y. Huang 38a 57 , R.D. Kass 66 66 , Z. Idrissi 30 , M. King 83 , R. Iuppa 58a , N. Karastathis ,n 149 , M. Janus , K. Kawagoe 147a 156 89 , K.D. Joshi , J. Khubua , A.K. Kopp , H. Keoshkerian 74 84 , D. Hirschbuehl 7 , M.Y. Kazarinov 58b 10 , B. Jackson 12 , K. Karthik 21 177 , I. Hristova 65 , M. Kretz 83 77 , T. Jakoubek , M.D. Joergensen , A. Kotwal 65 158 109 126b , , T. Kohriki 30 115 , S. Kaneti , G. Hughes 110 104a 65 , M. Iodice 158 , P. Kodys , J. Jia 9 30 35 , A. Hoecker , J. Huth 128 , X. Hu , J. Keung , M. Ishitsuka , J-Y. Hostachy 126a , T. Kono , D. Kisielewska , M. Ikeno 144 , T.R. Holmes 90 35 174 , E. Kajomovitz 68 140 , G.-Y. Jeng 83 156 67 , E. Ideal 103 83 ,p 142 , E.V. Korolkova , E.B.F.G. Knoops , Y. Komori , B.T. King 144 , A. Khomich , L. K¨opke ∗ , D. Krasnopevtsev , K. Jon-And , J. Janssen , T.Z. Kowalski 12 , , V. Kaushik 117 , V. 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H¨ulsing G. Iakovidis O. Igonkina D. Iliadis V. Ippolito R. Ishmukhametov J. Hobbs F. Hoenig L. Hooft van Huysduynen A. Hoummada T. Hryn’ova F. Hubaut S. Hillert JHEP01(2015)069 , , , , , , , , , 15 67 , 101 21 10 , 80 83 , , 123 , , , , , 80 , 6 , , 124b 61 , , 75 , , 65 48 45 62 152 78 80 , , , , ,f 156 , , , 173 , 25 24a , 90 124a 76 21 72 , , , , 144 , , ,n , 37b 168 , , ,u , 7 , 24b 42 , 9 76 149 12 54 , 14 126a 21 , 25 33c 37a , , M. Liu , , L. Masetti , A.A. Maier 21 20b , S. Maltezos , A.M. Leyko , W. Lavrijsen 89 , , G. Lefebvre , S. Kuehn , I. Mandi´c , R. Kurumida 32b 30 , W. Lukas 1 , R. Mazini 101 , B. Malaescu 47 24a 4c 144 110 92 ,c , M. Levchenko , X. Lei 61 20a , S. Leone , T. LeCompte 91a ,x 7 , B. Martin , Y. Li , G. Marchiori 30 12 , D. Lellouch , D. Lissauer , A.J. Lowe 109 122 , L. Lambourne 30 45 137 29 , T. Masubuchi , D. Lynn , L. Lopes , J. Kroseberg 72 , L. Liu , S.L. Lloyd , W. Liebig 129 166 , F. Marroquim 58a , Z.V. Krumshteyn , L. Lee 83 72 , C. Lapoire , M.P.J. Landon 37b , H.J. Maddocks ,w 82 21 , 122 , M. Martinez , K. Lohwasser , V.R. Lacuesta , E. Magradze 64 , N. Lorenzo Martinez 80 48 48 152 126a 16 80 , B.E. Lindquist , A. Marzin 99 , S. Li 33b , I. Massa 37a , S. Kuday 137 , P. Laurelli , L. La Rotonda 100 , S. Kuleshov ,c , C. Malone , R. Leone , P. Mal 78 , G.H. Lewis 107 33e 6 30 49 , A. Macchiolo 92 , F. Luehring 133a 30 , L. Mandelli 109 , B. Martin 117 47 120 55 , T. Loddenkoetter 30 , H. Laier , P.A. Love , C. Maidantchik , C.M. Lester , J. Kroll , T.M. Liss , R. Leitner 6 , Y.A. Kurochkin , J. Liebal 168 48 , K. Liu , R.E. Long 28 138 42 , L. Li , S.C. Lee , E. Le Menedeu 137 , D.A. Maximov 67 101 , T. Lohse , R. Madar , J.F. Marchand 24d 89 166 , S. Laplace , A. Manousakis-Katsikakis , M. Lungwitz 45 33b 85 74 , D. Lacour 118 85 , J. Lorenz , U. Landgraf 30 , F. Linde 177 , N. Krumnack 16 , H. Kucuk , D. Malon 138 , B. Lenzi , G. Lehmann Miotto 148 146c , A. Maevskiy , H. Martinez 12 , L. 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Leight B. Lemmer C. Leonidopoulos J. Levˆeque M. Leyton E. Ladygin S. Lammers V.S. Lang J.F. Laporte A.T. Law F. Ledroit-Guillon J. Krstic A. Kruse A. Kugel M. Kuna V. Kus C. Lacasta K. Kreutzfeldt JHEP01(2015)069 , , , , , , 84 , 6 , , , ,z , 66 91a 31 , 120 , 10 54 , 140 , 130 30 , , 25 , 125 , , , , , 25 , 101 27 , 85 , 88 8 149 , 30 66 , , A. Oh 103 63 , , ,o 15 , , , 31 , 61 , 31 , 163 , 46 , , 144 118 , 12 , 83 166 31 121b 25 , , 25 162 21 , C. Meroni 156 , , K. Nagano , , , F. Nuti 73b 57 85 , , J. Mueller , A. Paramonov , Y. Okumura , 121a 48 , 21 , S. Palestini ,l 104b 78 , 25 , N. Ozturk , , G. Mchedlidze 16 , R.B. Nickerson 137 58a 73a , M. Nozaki , E. Monnier , L. Morvaj , H. Oberlack 6 , P.S. Miyagawa , C. Mills , H. Ogren , A.G. Myagkov 155 78 160b 36 ,e 19a , N. Morange 154 76 104a , E. Mountricha 49 31 101 66 , L.M. Mir 3 , Y. Nakahama , C. Meyer , G. Navarro 153 29 , E. Meoni , E. Panagiotopoulou , R.L. McCarthy , S. Meehan 30 , T.K. Nelson , S. Pagan Griso , M. 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Mellado Garcia K.M. Mercurio F.S. Merritt L. Mazzaferro JHEP01(2015)069 , , , , , , , , , 12 , 28 53 , 150 , ,ab 155 44 , 121a 117 , , 25 168 , 64 116 , 28 165c , , , 106 , 27 , , , , , , I. Riu 91b 80 15 , , 30 172 , 139 , 119 48 , , G. Qin 165a 62 154 , , , , , , , 91a , 138 , 89 137 65 27 , 50a 77 , , 84 121b , , 139 , 125 , 131 , C.J. Potter , 137 65 , T. Sandoval 126b , D. Pluth , , G. Rybkin 25 , C. Petridou , 48 , C. Rudolph 116 13a 133a , , P. Radloff 65 , G. Polesello 30 30 121a 99 , 176 129 34 , R. Piegaia 49 , M. Ridel 147b , T. Pauly 126a 147b , A. Salvucci 149 , D. Robinson , 30 , , I. Sadeh , A. Pranko , O. Røhne , P. Rose , J. Qian , E. Ritsch 3 , C. Pizio , Y. Sakurai 20b 87 101 , D.V. Perepelitsa , 150 85 30 77 , U. Parzefall 104b , H. Reisin 147a 147a 117 , 20a 61 173 156 , L.P. Rossi 20a , D. Prieur 35 , C.R. Royon 16 , Fr. Pastore , M. Pinamonti 6 , A. Sapronov ∗ , V. Sanchez Martinez , E. Ptacek , 104a , T.C. Rave , N. Rompotis , V.I. Rud 5 117 , K. Peters , M. 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Perez Codina S. Perrella D. Paredes Hernandez JHEP01(2015)069 , , , , , , , , , , , 98 90 , 21 , , 122 40 , , 21 137 , 21 58a , 154 117 68 18 123 , , , ∗ , 79 , , 5 143 , , , 5 137 30 , , , , , , 119 ,ad , , 44 40 , 101 42 , , D. Ta 14 , , , 128 , 30 ,j 30 159 150 8 152 135a , 137 160a 42 129 , 123 , , J. Saxon 13a 170 , , E. Scifo 50b 55 , S. Schaepe 22 53 , , V. Scharf 85 , M. Slater 17 , , , , E. Sedykh , T. Sumida 42 , , N. Taiblum , B. Stelzer 53 96 50a 149 , O. Simard 42 113 , L. Shi 4d , J.A. Stillings , E.Yu. Soldatov 151 , S. Staerz 99 , D. South , F. Sforza 25 , G. Sauvage ∗ , L. Schoeffel , R. Stroynowski , M.J. Schultens 78 , V. Sopko , 53 , G. Spigo ,c 128 160a , S.J. Sekula , C. Serfon 75 , Ph. Schwemling 128 , A. Strandlie 44 83 , P. Sinervo , L. Smestad , K. Schmieden 53 156 116 , R. Sobie 128 20a 109 , T. Sykora , R. Subramaniam , J. Stark 20b 46 , Ph. Schune 48 101 , , M.R. Sutton , C. Stanescu 104a , Dj. Sijacki 25 91b , D. Schouten 147b , 6 , M. Talby , V. 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Schmitt A. Schoening J. Schovancova H.-C. Schultz-Coulon C. Schwanenberger R. Schwienhorst E. Sauvan C. Sbarra V. Scarfone S. Schaetzel V.A. Schegelsky J. Schieck J.G. Saraiva JHEP01(2015)069 , , , , , , 8 6 , , , 30 21 , , 120 142 , , 34 151 , , 80 35 48 , 159 133b , 65 , , , , 20b , , , , 140 , , , 90 , 107 , 166 34 30 88 , , , G. Usai 73b , , 133a , 132 , , , 20a 15 107 , , , , , , 133a 21 88 15 65 , A. Vogel 156 29 30 83 25 20b 176 28 85 73a , 68 77 , 128 , , W. Vandelli , , , , C. Weiser 20a 17 , P.M. Tuts , I.J. Watson , J.C-L. Tseng 12 66 , 78 54 40 , R. Voss ,af , W. Walkowiak 18 30 133b , 49 , , I. Vichou , P. van Gemmeren , R. Vari , D.R. Tovey 96 , H. Wang 168 , F. Vazeille 100 , S. Tanaka , K. Tollefson 81 , T. Wang , R. Ueno 30 101 85 , P.D. Thompson , R. Vigne , G.N. Taylor 178 133a , M. Verducci , P. Urquijo 66 174 , S. Trincaz-Duvoid , K. Terashi 151 117 , V.B. Vinogradov 18 , A. Undrus 152 156 94 , M. Vreeswijk , T. Tashiro 35 , W. Wagner 169 , A. Ventura , N.D. 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Teixeira Dias Castanheira 177 , C. Wasicki , I. Turk Cakir , G. Tsipolitis , B.B. Tannenwald , P.K. Teng , B. Trocm´e 33a 107 30 147b , A. Warburton , J. Wakabayashi 175 , M. Trzebinski 26a 129 , M. Vranjes Milosavljevic 46 , , A.R. Weidberg 30 128 , F. Tian 137 , P. Vankov 143 44 159 , I. Vukotic 90 ∗ 6 116 31 , , V. Vacek 137 , S. Watts , L. Tremblet , N. Venturi , E. Torr´oPastor 30 147a , M. Tomoto , M. Uhlenbrock 89 85 , Y. Unno , G.F. Tartarelli 139 84 14 , D. Varouchas 175 170 143 , S. Valkar , G. Volpi 48 , F. Vives Vaque 29 , J. Veatch , M. Testa 86 , B. Walsh 34 , J. Wang 128 54 150 74 , I. van Vulpen , P. True 101 , E. von Toerne 42 , S. Timoshenko , R. Van Der Leeuw , W. Van Den Wollenberg ,c , J.Y.C. Tam 48 143 , D. Turecek , D. Tsionou , A.S. Thompson ,c 135b 107 , H. Ten Kate , A. Tudorache , N. Vranjes 168 , , E.G. Tskhadadze , O.E. Vickey Boeriu , W. Trischuk 109 , A. Washbrook 92 ,ae 84 , J.C. Vermeulen , G. Watts , M. Tylmad 48 , J.S. Webster , R.P. Thun 74 , S. Wahrmund , J. Thomas-Wilsker , H. Torres , M. Villaplana Perez 109 48 , A. Tavares Delgado 12 , F.A. Teischinger 48 , A. Vaniachine 149 , T. Varol 99 , M. Ugland , L. Vacavant ,ah 18 49 , M. Venturi 88 135a , R. Vuillermet , T. Trefzger 71 7 18 107 , S. Todorova-Nova , L. Valery 175 , F. Tarrade , A.J. Tanasijczuk , P. Vokac , C. Wanotayaroj 116 85 20b 62 5 37b , S. Terzo 86 , , L. Tomlinson 122 48 , J. Wang , , F.C. Ungaro , P. Waller 160b 117 66 146c 168 , I. Vivarelli 82 153 57 32a 40 177 20a 37a 164 177 15 H. Wang X. Wang M. Warsinsky M.F. Watson S.W. Weber M. Vogel H. von Radziewski J.H. Vossebeld T. Vu Anh H. Wahlberg R. Wall T. Vazquez Schroeder D. Ventura W. Verkerke T. Vickey M. Villa J. Virzi A. Valero J.A. Valls Ferrer H. van der Graaf J. Van Nieuwkoop R. Vanguri E.W. Varnes D. Tsybychev S. Turchikhin A. Tykhonov M. Ughetto G. Unel A. Usanova E. Torrence H.L. Tran M.F. Tripiana M. Trovatelli P.V. Tsiareshka V. Tsiskaridze J.P. Thomas R.J. Thompson W.M. Thong Yu.A. Tikhonov T. Todorov E. Tolley S. Tanaka S. Tarem E. Tassi W. Taylor K.K. Temming J. Terron A.A. Talyshev JHEP01(2015)069 , , , , 30 83 , 33d 172 , 8 , , 21 , , , , 8 , , 111 63 176 131 35 40 151 , 5 , , , , , , S. Wenig , J. Yu . , X. Zhang , , K. Yorita 84 156 96 , A. White 122 30 174 15 , J. Ye , 30 35 29 , 152 125 , Y. Yang 21 21 , , S.J. Wollstadt , L. Zhou 84 118 , R. Zaidan 89 , C. Zeitnitz 117 100 , B. Yabsley 39 88 , F.J. Wickens ,ak , D.R. Yu , E. Wulf , K. Zhukov 176 , L.A.M. Wiik-Fuchs 33b 22 89 , L. Zhang , T. Wengler 6 36 , G. Zobernig , K. Whalen , T. Yamanaka 33a , L. Zwalinski , B. Zhou ,ad , I. Wingerter-Seez , H.H. Williams , M.J. Woudstra , U.K. Yang 142 162 156 , D. Zerwas 18 30 108 30 , D. Zanzi 120 152 174 , R. Yoosoofmiya , L. Xu , B. Zabinski , K.H. Yau Wong , Y. Yamaguchi , Y. Wu , R. Zimmermann 145a 4b , J. Wittkowski 133b Vinca Institute of Nuclear Sciences, 42 , D. Wicke , 49 33a 83 ) ,am 156 43 b , J. Zhang , S. 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Fermi, Universit`adi Pisa, Pisa, Italy ( b ) ( b ( Centro de Nuclear F´ısica da Universidade de Lisboa, Lisboa; ) d ( Laboratorio de Instrumentacao e Fisica Experimental de Particulas - LIP, Lisboa; INFN Sezione di Pavia; INFN Sezione di Pisa; INFN Sezione di Napoli; ) ) ) ) a a a a Ciencias e Tecnologia, Universidade NovaInstitute de of Lisboa, Physics, Caparica, Academy Portugal Czech of Technical Sciences University of in the Prague,Faculty Czech Praha, of Republic, Czech Mathematics Praha, Republic and CzechState Republic Physics, Research Charles Center University Institute in forParticle Prague, High Physics Praha, Energy Department, Czech Physics, Rutherford Republic Appleton Protvino, Russia Laboratory, Didcot, United Kingdom America de Ciˆencias,Universidade de Lisboa, Lisboa; Coimbra; Fisica, Universidade do Minho,CAFPE, Braga; Universidad de Granada, Granada (Spain); Department of Physics, Oxford University, Oxford, United Kingdom Department of Physics, UniversityPetersburg of Nuclear Pennsylvania, Physics Philadelphia Institute, PA, Gatchina, United Russia States of America Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh PA, United States of United States of America Department of Physics, OklahomaPalack´yUniversity, State RCPTM, University, Olomouc, Stillwater Czech OK, Republic Center United for States High of Energy America LAL, Physics, Universit´eParis-Sud University and of CNRS/IN2P3, Oregon, Orsay,Graduate Eugene School France OR, of United Science, States OsakaDepartment of of University, America Physics, Osaka, University Japan of Oslo, Oslo, Norway Department of Physics, NorthernBudker Illinois Institute University, of DeKalb Nuclear IL,Department Physics, United of SB States Physics, RAS, of New Novosibirsk, America Ohio York Russia University, State New University, York ColumbusFaculty NY, OH, of United United Science, States States Okayama of of University,Homer America America Okayama, L. 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University Lebedev of Institute Montreal, of Montreal Physics, QC,Institute Academy Canada for of Theoretical and Sciences, Moscow, ExperimentalNational Russia Physics Research Nuclear (ITEP), University Moscow, MEPhI, Russia Moscow, Russia National Scientific and Educational Centre for Particle and High Energy Physics, Minsk, Republic ( ( ( ( 99 94 95 96 97 98 93 127 128 129 130 131 126 120 121 122 123 124 125 114 115 116 117 118 119 108 109 110 111 112 113 105 106 107 100 101 102 103 104 JHEP01(2015)069 Department ) b ( Dipartimento ) c ( Facult´edes sciences, ) e ( Department of Physics, ) ICTP, Trieste; b ( ) b ( The Oskar Klein Centre, Stockholm, Sweden ) b ( School of Physics, University of the Witwatersrand, ) c ( – 85 – Dipartimento di Fisica, Universit`adi Roma Tor Vergata, ) b ( Centre National de l’Energie des Sciences Techniques ) b ( Dipartimento di Matematica e Fisica, Universit`aRoma Tre, ) b Department of Physics and Astronomy, York University, Toronto ( ) b 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Universit`adi Udine, Udine, Italy Graduate School of Science andDepartment of Technology, Tokyo Physics, Metropolitan Tokyo University, InstituteDepartment Tokyo, of of Japan Physics, Technology, Tokyo, University Japan of Toronto, Toronto ON, Canada ON, Canada Faculty of Pure and Applied Sciences, University of Tsukuba, Tsukuba, Japan Department of Physics, Technion:Raymond Israel and Institute Beverly of Sackler Technology, Haifa,Israel School Israel of Physics andDepartment Astronomy, of Tel Physics, Aviv Aristotle University,International University Tel Center Aviv, of for Thessaloniki, Elementary Thessaloniki,of Particle Greece Tokyo, Physics Tokyo, and Japan Department of Physics, The University Physics Department, Royal InstituteDepartments of of Technology, Stockholm, Physics Sweden &United Astronomy States and of Chemistry, America StonyDepartment Brook of University, Physics Stony and BrookSchool NY, Astronomy, of University Physics, of University Sussex,Institute of Brighton, of Sydney, United Physics, Sydney, Kingdom Academia Australia Sinica, Taipei, Taiwan of Subnuclear Physics, InstituteKosice, of Slovak Experimental Republic Physics of the Slovak Academy ofUniversity Sciences, of Johannesburg, Johannesburg; Johannesburg, South Africa United States of America Department of Physics, UniversityDepartment of of Washington, Physics Seattle and WA,Department United Astronomy, of States University Physics, of of Shinshu America Sheffield,Fachbereich University, Sheffield, Physik, Nagano, United Universit¨atSiegen, Siegen, Japan Kingdom Germany Department of Physics, SimonSLAC Fraser University, National Burnaby Accelerator Laboratory, BC, Stanford CA, Canada United States of America Nucleaires, Rabat; ( Universit´eMohammed V-Agdal, Rabat, Morocco DSM/IRFU (Institut de Recherches sur(Commissariat les `al’Energie Atomique Lois et Fondamentales aux deSanta Energies l’Univers), Cruz Alternatives), CEA Institute Gif-sur-Yvette, Saclay for France Particle Physics, University of California Santa Cruz, Santa Cruz CA, Roma, Italy Roma, Italy Universit´eHassan II, Casablanca; Ritsumeikan University, Kusatsu, Shiga, Japan ( ( ( ( ( ( ( ( ( 163 164 165 157 158 159 160 161 162 153 154 155 156 147 148 149 150 151 152 145 146 139 140 141 142 143 144 137 138 134 135 136 132 133 JHEP01(2015)069 – 86 – Also at Dipartimento diAlso Fisica, at Sapienza Moscow Universit`adi Roma, Institute Roma,Also of Italy at Physics section and de Technology StateAlso Physique, at University, Universit´ede Gen`eve,Geneva, International Dolgoprudny, Switzerland School Russia Also for at Advanced Studies Department (SISSA), ofStates Trieste, Physics Italy of and America Astronomy, University of South Carolina, Columbia SC, United Also at LAL, Universit´eParis-Sud andAlso CNRS/IN2P3, at Orsay, Academia Sinica France GridAlso Computing, at Institute Laboratoire de of PhysiqueParis-Diderot et Physics, Nucl´eaire and de Academia CNRS/IN2P3, Sinica, Hautes Taipei, Paris, 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Israel WI,Fachbereich United C States Physik, of Bergische America Universit¨atWuppertal,Department Wuppertal, of Germany Physics, Yale University, New Haven CT, United States of America Department of Physics andInstituto Astronomy, de University Corpuscular F´ısica of (IFIC) Uppsala, andand Uppsala, Departamento Departamento Sweden Molecular de and de At´omica, y F´ısica Instituto Ingenier´ıaElectr´onica Nuclear (IMB-CNM), de de University Microelectr´onica Barcelona of ValenciaDepartment and of CSIC, Physics, Valencia, University Spain Department of of British Physics Columbia, and VancouverDepartment BC, Astronomy, of University Canada Physics, of University Victoria, of Victoria Warwick, BC, Coventry, Canada United Kingdom Department of Physics, University of Illinois, Urbana IL, United States of America l i t b c j s e q r o z p d g v y a k x f h u n w m ab ac aa 179 172 173 174 175 176 177 178 168 169 170 171 166 167 JHEP01(2015)069 Deceased ∗ – 87 – Also at Department ofAmerica Physics, The University ofAlso Michigan, at Ann Discipline Arbor of MI,Also Physics, United at University States University of of of KwaZulu-Natal, Malaya, Durban, Department South of Africa Physics, Kuala Lumpur, Malaysia Also at Faculty ofAlso Physics, at M.V.Lomonosov Moscow National State Research NuclearAlso University, University at Moscow, MEPhI, Institute Russia Moscow, for Russia Hungary Particle and Nuclear Physics,Also Wigner at Research Department Centre of forAlso Physics, Physics, at Oxford Budapest, Department University, of Oxford,Also Physics, United at Kingdom Nanjing Institut University, f¨urExperimentalphysik, Jiangsu, Universit¨atHamburg, Hamburg, China Germany Also at School of Physics and Engineering, Sun Yat-sen University, Guangzhou, China al ai aj ae ad ag ak af ah am