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ATLAS CONF NoteATLAS-PHYS-CONF-2017-001

A model-independent general search for newphenomena with the ATLAS detector at

√s = 13 TeV

The ATLAS Collaboration

30th January 2017

This note presents results of a model-independent general search for new physics using3.2 fb−1 of proton-proton collision data at a centre-of-mass energy of 13 TeV with the ATLASdetector at the LHC. Event topologies involving isolated leptons (electrons and muons),photons, jets, b-tagged jets and missing transverse momentum, leading to 639 different fi-nal states, are investigated. For each final state, a search algorithm tests the compatibility ofdata against the Monte Carlo simulated background in two kinematic variables sensitive tonew physics effects. The expected frequency of the maximal local significance observed ineach channel is estimated using pseudo-experiments generated assuming the Standard Modelprediction. The largest observed discrepancy, with a local p0-value of 5 · 10−4, correspondsto a global significance of less than one sigma.

© 2017 CERN for the benefit of the ATLAS Collaboration.Reproduction of this article or parts of it is allowed as specified in the CC-BY-4.0 license.

1 Introduction

Direct searches for as yet unknown particles and forces are one of the primary objectives of the ATLASphysics program. The ATLAS experiment at the Large Hadron Collider (LHC) has thoroughly analyzedthe Run-1 dataset and a small fraction of the expected Run-2 dataset and no evidence of physics beyondthe Standard Model (SM) has been found so far in any of the searches performed.

The existing searches do not fully cover the enormous parameter space of masses, cross-sections anddecay possibilities of all possible new particles. Signals might be hidden in so far unexplored kinematicregimes and final states, motivating a structured, global and automated way to search for new physics.

Such an analysis detects discrepancies between data and the prediction which serve as an alert to performmore precise and model-dependent analyses in the potentially interesting final states.

This note presents a model-independent general search for deviations from the Standard Model predictionin 13 TeV proton-proton collision data collected with the ATLAS detector in 2015, corresponding toan integrated luminosity of 3.2 fb−1. The analysis partitions all recorded events into exclusive classesaccording to the number of high transverse momentum (pT) reconstructed objects: electrons, muons,photons, jets, b-tagged jets and missing transverse momentum (Emiss

T ). The distributions of the effectivemass (meff) and the visible invariant mass (minv) of the event are investigated systematically for each class.A statistical search algorithm is used to locate the region of largest deviation from the SM prediction inthese distributions. Monte Carlo (MC) simulation is used to model the SM backgrounds. The probabilityto measure a deviation with a significance equal of bigger than the observed one is estimated by comparingdata results with pseudo-experiment predictions.

Model-independent searches have been previously performed by the H1 Collaboration [1, 2] at HERA andby the D0 [3–5] and CDF [6, 7] Collaborations at the Tevatron. At the LHC model-independent searcheshave been performed by the CMS Collaboration at

√s=7 TeV [8] and by the ATLAS Collaboration at 7

and 8 TeV [9, 10].

The note is organized as follows. An overview of the ATLAS detector is given in Section 2, followed bya description of the dataset and triggers used in 3. The MC samples used are described in Section 4, andthe object definitions in Section 5. Systematic uncertainties are presented in Section 6. Next, in Section 7,the classification of events according to the reconstructed objects is presented. In Section 8 the statisticalinterpretation is discussed and conclusions are presented in Section 9.

2 ATLAS detector

The ATLAS detector [11] is a multi-purpose particle physics detector with a forward-backward symmetriccylindrical geometry and nearly 4π coverage in solid angle∗. The inner tracking detector (ID) consistsof pixel and silicon microstrip detectors covering the pseudorapidity region |η | < 2.5, surrounded by atransition radiation tracker which enhances electron identification in the region |η | < 2.0. Between Run-1

∗ ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point in the centre of the detector.The positive x-axis is defined by the direction from the interaction point to the centre of the LHC ring, with the positivey-axis pointing upwards, while the beam direction defines the z-axis. Cylindrical coordinates (r , φ) are used in the transverseplane, φ being the azimuthal angle around the z-axis. The pseudorapidity η is defined in terms of the polar angle θ byη = − ln tan(θ/2). Rapidity is defined as y = 0.5 · ln[(E + pz )/(E − pz )] where E denotes the energy and pz is the componentof the momentum along the beam direction.

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and Run-2, a new inner pixel layer, the Insertable B-Layer (IBL) [12], was inserted at a mean sensorradius of 3.3 cm. The inner detector is surrounded by a thin superconducting solenoid providing an axial2 T magnetic field and by a fine-granularity lead/liquid-argon (LAr) electromagnetic calorimeter covering|η | < 3.2. A steel/scintillator-tile calorimeter provides hadronic coverage in the central pseudorapidityrange (|η | < 1.7). The endcap and forward regions (1.5 < |η | < 4.9) of the hadronic calorimeter aremade of LAr active layers with either copper or tungsten as the absorber material. An extensive muonspectrometer with an air-core toroid magnet system surrounds the calorimeters. Three layers of high-precision tracking chambers provide coverage in the range |η | < 2.7, while dedicated fast chambersallow triggering in the region |η | < 2.4. The ATLAS trigger system consists of a hardware-based level-1trigger followed by a software-based high-level trigger [13].

3 Dataset and trigger

The data used in this analysis were collected by the ATLAS detector in pp collisions at the LHC witha centre-of-mass energy of 13 TeV and a 25 ns bunch crossing interval during 2015. After applyingbeam-, data- and detector-quality criteria, the available dataset corresponds to an integrated luminosityof 3.2 fb−1. In this dataset, each event includes an average of approximately 14 additional inelastic ppcollisions in the same bunch crossing (pile-up).

Different triggers have been used to collect the events used in the analysis, with the aim of maximizing theacceptance for all the reconstructed objects considered. For an event passing more than one trigger, thefollowing priority list is applied, where for the definition of the objects the same requirements as in Sec. 5are applied. Events with reconstructed Emiss

T > 200 GeV are required to pass the EmissT trigger. If the

event fails the EmissT requirement but contains a signal muon with pT > 25 GeV it is taken from the single

muon trigger. Events with an electron with pT > 25 GeV but no reconstructed signal muons or largeEmiss

T are required to pass the single electron trigger. Remaining events with a photon with pT > 140 GeVor two photons with pT > 50 GeV are taken from the single and diphoton triggers, respectively. Finallyany remaining event with a jet with pT > 500 GeV is taken from the single jet trigger. In addition to thethresholds imposed by the trigger, a further selection is applied in final states containing only one leptonand jets, where the lepton is required to have pT > 100 GeV if the event has less than three jets withpT > 60 GeV.

4 Monte Carlo Samples

Monte Carlo simulated event samples are used for the description and estimation of SM background pro-cesses and to model the expected signals. The ATLAS detector is simulated [14] either by a softwaresystem based on GEANT4 [15] or by a faster simulation based on a parameterization [16] of the calor-imeter response and GEANT4 for the other detector systems. To account for additional pp interactionsfrom the same and close-by bunch crossings, a set of minimum-bias interactions generated using Pythia8.186 [17], the MSTW2008LO [18] parton distribution function (PDF) set and the A2 set of paramet-ers (tune) [19] is superimposed onto the hard scattering events to reproduce the observed distribution ofthe average number of interactions per bunch crossing. In all MC samples, except those produced bySherpa, the EvtGen v1.2.0 program [20] is used to model the properties of the bottom and charm hadrondecays.

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Samples of multijet production are simulated with 2 → 2 matrix elements (ME) at leading order (LO)using the Pythia 8.186 generator. The A14 tune [21] of shower and multiple parton interactions paramet-ers is used together with the NNPDF23LO PDF set [22]. Alternative multijet samples with 2→ 2 ME atLO are generated with Herwig 2.7.1 [23] with the UEEE5 underlying-event tune and the CTEQ6L1 [24]PDF set, and with Sherpa 2.1.1 with 2 → 3 ME at LO. All Sherpa samples use the CT10 [25] PDF setand the Sherpa parton shower [26] with a dedicated shower tuning developed by the Sherpa authors.

Events containing W or Z bosons with associated jets (W /Z+jets) are simulated using the Sherpa 2.1.1generator [27]. Matrix elements are calculated using the Comix [28] and Open-Loops [29] generat-ors. They include up to two partons at NLO and four partons at leading order (LO), merged using theME+PS@NLO prescription [30]. The W /Z+jets events are normalised to their inclusive next-to-next-to-leading-order (NNLO) cross-sections [31, 32]. Simulated samples of massive vector bosons produced inassociation with one or two real photons are also generated with Sherpa 2.1.1 with a ME calculated at LOfor up to three partons. They are scaled to their NLO cross-sections computed with MCFM [33, 34].

Samples of prompt photon production in association with jets (γ+jets) have been generated using Sherpa2.1.1. For these samples up to three real parton emissions are included at LO. Events containing twoprompt photons (γγ+jets) are also generated with Sherpa 2.1.1. Matrix elements are calculated with upto two partons at LO. The gluon-induced box process is also included. These samples are scaled to datawith the procedure described in Sec. 7.1.

Top pair production events, and single top quarks in the Wt and s-channel, are simulated using thePowheg-Box v2 [35] generator with the CT10 PDF set, as detailed in [36]. The top mass is set to172.5 GeV. The hdamp parameter, which regulates the transverse momentum of the first extra emissionbeyond the Born configuration and thus controls the pT of the tt̄ system, is set to the mass of the topquark. Electroweak t-channel single-top-quark events are generated using the Powheg-Box v1 generator.This generator uses the four-flavour scheme for the NLO matrix-element calculations together with thefixed four-flavour PDF set CT10f4. For all top-quark processes, top-quark spin correlations are preserved(for the single-top t-channel, top quarks are decayed using MadSpin [37]). An alternative sample of tt̄ isgenerated with the Sherpa 2.1.1 generator, including up to one additional parton at NLO and up to fouradditional partons at LO accuracy, interfaced to the parton shower using the ME+PS@NLO prescrip-tion. The parton shower (PS), fragmentation, and the underlying event of the Powheg-Box samples aresimulated using Pythia 6.428 [38] with the CTEQ6L1 PDF set and the corresponding Perugia 2012 tune(P2012) [39]. The tt̄ and single-top quark events are normalized to the NNLO order cross-section in-cluding the resummation of soft gluon emission at next-to-next-to-logarithmic accuracy using Top++2.0[40]. Both the default and the alternative tt̄ samples are corrected to reproduce the NNLO prediction [41,42] of the top quark pT and the pT of the tt̄ system, following the same procedure used in [43]. Thecontribution of tt̄ + bb̄ is generated separately with Sherpa 2.1.1 at NLO; the calculation is performed inthe four-flavor scheme and with the CT10f4 PDF set.

Diboson samples are generated with the Sherpa 2.1.1 generator, and are described in detail in [44]. Thematrix elements contain the doubly resonant WW , W Z and Z Z processes and all other diagrams withfour or six electroweak vertices (such as same-electric-charge W boson production in association withtwo jets, W±W± j j). Fully leptonic triboson processes (WWW , WW Z , W Z Z and Z Z Z) with up to sixcharged leptons are also simulated using Sherpa v2.1.1. The ME for the Z Z processes are calculated atNLO for up to one additional parton; final states with two and three additional partons are calculated atLO. The W Z and WW processes are calculated at NLO with up to three extra partons at LO using theME+PS@NLO prescription. The WW final states have been generated without bottom quarks in the hardscattering process, to avoid contributions from top-quark mediated processes. The triboson processes

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Table 1: A summary of the MC samples used in the analysis to model SM background processes. For each samplethe corresponding generator, parton shower, cross-section, PDF set and tune are indicated.

Physics process Generator Parton shower Cross-section PDF set Tunenormalisation

W (→ `ν) + jets Sherpa 2.1.1 Sherpa 2.1.1 NNLO NLO CT10 Sherpa defaultZ (→ ``) + jets Sherpa 2.1.1 Sherpa 2.1.1 NNLO NLO CT10 Sherpa defaultW /Z + γ(γ) Sherpa 2.1.1 Sherpa 2.1.1 NLO NLO CT10 Sherpa defaultγ(γ) + jets Sherpa 2.1.1 Sherpa 2.1.1 data NLO CT10 Sherpa defaultt t̄ Powheg-Box v2 Pythia 6.428 NNLO+NNLL NLO CT10 Perugia 2012t t̄ + bb̄ Sherpa 2.2.0 Pythia 6.428 NNLO+NNLL NLO CT10 Perugia 2012Single-top (t-channel) Powheg-Box v1 Pythia 6.428 NLO NLO CT10f4 Perugia 2012Single-top (s- and Wt-channel) Powheg-Box v2 Pythia 6.428 NLO NLO CT10 Perugia 2012t t̄ + W /Z/WW MG5_aMC@NLO 2.2.2 Pythia 8.186 NLO NNPDF2.3LO A14t t̄ + γ MG5_aMC@NLO 2.2.2 Pythia 8.186 LO NNPDF2.3LO A143-top, t Z MG5_aMC@NLO 2.2.2 Pythia 8.186 LO NNPDF2.3LO A144-top MG5_aMC@NLO 2.2.2 Pythia 8.186 NLO NNPDF2.3LO A14WW , WZ and ZZ Sherpa 2.1.1 Sherpa 2.1.1 NLO NLO CT10 Sherpa defaultMultijets Pythia 8.186 Pythia 8.186 data NNPDF2.3LO A14Higgs (ggF/VBF) Powheg-Box v2 Pythia 8.186 NNLO NLO CT10 AZNLOHiggs (t t̄H ) MG5_aMC@NLO 2.2.2 Herwig++ NNLO NLO CT10 UEEE5Higgs (W /ZH ) Pythia 8.186 Pythia 8.186 NNLO NNPDF2.3LO A14Tribosons Sherpa 2.1.1 Sherpa 2.1.1 NLO NLO CT10 Sherpa default

are calculated with the same configuration and with up to two extra partons at LO. The generator cross-sections are used for the normalization of these backgrounds.

Samples of top quark production in association with vector bosons [45] (W , Z , γ and WW , includingthe non-resonant Z/γ∗ contributions) are generated at LO with MG5_aMC@NLO v2.2.2 [46] interfacedto Pythia 8.186, with up to two (tt̄W ), one (tt̄ Z) or no (tt̄WW , tt̄γ) extra partons included in the matrixelement. The A14 tune is used together with the NNPDF2.3LO PDF set. The tt̄γ sample uses a fixedrenormalization and factorisation scale of 2 · mt , and the top decay is performed in MG5_aMC@NLOto account for hard photon radiation from the top decay products. The same generator is also used tosimulate the tZ , 3-top and 4-top quarks processes. The tt̄W , tt̄ Z , tt̄WW and 4-top samples are normalisedto their NLO cross-sections [47] while the LO cross-section from the generator is used for tZ and 3-topquarks.

The Higgs boson mass is set to 125 GeV and all Higgs boson decay modes are considered. The pro-duction of the SM Higgs boson in the ggF and VBF channels is modelled using the Powheg-Box v2generator, using the CT10 PDF set. It is interfaced to Pythia 8.186 with the CTEQ6L1 PDF set and theAZNLO tune [48]. Production of a Higgs boson in association with a pair of top quarks is simulated usingMG5_aMC@NLO v2.2.2 interfaced to Herwig 2.7.1 [23] for showering and hadronization. The UEEE5underlying-event tune is used together with the CT10 (matrix element) and CTEQ6L1 (parton shower)PDF sets. Simulated samples of SM Higgs boson production in association with a W or Z boson areproduced with Pythia 8.186, using the A14 tune and the NNPDF23LO PDF set. Events are normalisedto their most accurate cross-sections calculations (typically NNLO) [49].

To avoid double counting, events with a hard photon from final state radiation are removed from themultijet, tt̄ and W /Z+jet samples.

In addition to the SM background processes two possible signals are considered as benchmarks.

The first benchmark model considered is the production of a new heavy gauge boson (Z ′), as predicted bymany extensions of the SM. We consider the specific case of an E6 extension of the SM gauge group [50,

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51], which, after symmetry breaking, introduces two new neutral gauge bosons that mix with an angleθE . The two bosons are defined by Z ′ = Z ′ψ cos θE6 + Z ′χ sin θE6, and the specific choice of couplingscorresponding to θE6 = π is made, resulting in only the Z ′χ being produced. This process is generatedat LO using Pythia 8.186 with the NNPDF23LO PDF set and the A14 tune. Only decays of the Z ′ intoelectron or muon pairs are considered. Interference effects (such as with SM Drell-Yan production) arenot included.

The second signal considered is the supersymmetric [52–57] production of gluino pairs through stronginteractions. The gluinos are assumed to decay promptly into a pair of top quarks and a neutralino via anoff-shell top squark g̃ → tt χ̃0

1. Samples for this process are generated at LO with up to two additionalpartons using MG5_aMC@NLO v2.2.2 with the CTEQ6L1 PDF set, interfaced to Pythia 8.186 withthe A14 tune. The matching with the parton shower is done using the CKKW-L [58] prescription, witha matching scale set to one quarter of the pair-produced resonance mass. The signal cross-sections arecalculated at NLO in the strong coupling constant, adding the resummation of soft gluon emission atnext-to-leading-logarithmic (NLL) accuracy [59–61].

5 Object reconstruction

Candidate events are required to have a reconstructed vertex [62], with at least two associated trackswith pT > 400 MeV. The vertex with the highest sum of squared transverse momenta of the tracks isconsidered as the primary vertex.

Electron candidates are reconstructed from an isolated electromagnetic calorimeter energy deposit matchedto an ID track and are required to have |η | < 2.47, a transverse momentum pT > 10 GeV, and to passa loose likelihood-based identification requirement [63, 64]. The likelihood input variables include mea-surements of calorimeter shower shapes and measurements of track properties from the ID. The candidateelectrons are selected if the matched tracks have a transverse impact parameter significance with respectto the reconstructed primary vertex of |d0 |/σ(d0) < 5. Candidates within the transition region betweenthe barrel and endcap electromagnetic calorimeters, 1.37 < |η | < 1.52, are removed.

Muon candidates are reconstructed in the region |η | < 2.7 from muon spectrometer tracks matched to IDtracks. The muon candidates are selected if they have a transverse momentum above 10 GeV and passthe medium identification requirements defined in [65], based on selections on the number of hits in thedifferent ID and muon spectrometer subsystems, and the significance of the charge to momentum ratioq/p.

All candidate leptons (electrons and muons) are used for the object overlap removal described below.Further requirements are applied to the “signal” leptons used in the analyis as follows. Signal electronsmust satisfy a tight likelihood-based identification requirement [63, 64]. Signal muons must fulfil therequirement of |d0 |/σ(d0) < 3. The track associated to the signal leptons must have a longitudinal impactparameter with respect to the reconstructed primary vertex, z0, satisfying |z0 · sin θ | < 0.5 mm. Isolationrequirements are applied to both the signal electrons and muons. The calorimeter isolation is computedas the sum of the energies of calorimeter energy clusters in a cone of ∆R =

√(∆η)2 + (∆φ)2 = 0.2

around the lepton. Track isolation is defined as the scalar sum of the pT of tracks within a variable-sizecone around the lepton, in a cone of radius ∆R = 0.2 (0.3) for electron (muon) transverse momentapT < 50 GeV (pT < 33 GeV) and of radius ∆R = 10 GeV

pTfor pT > 50 GeV (pT > 33 GeV). The

efficiency of these criteria increases with the lepton transverse momentum, reaching 95% at 25 GeV and

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99% at 60 GeV, as determined in a control sample of Z decays into leptons selected with a tag-and-probetechnique [65, 66].

Photon candidates are reconstructed from calorimeter cell clusters and are required to satisfy the tightidentification criteria described in [67–69]. Furthermore, photons are required to have pT > 25 GeV and|η | < 2.37, excluding the barrel-endcap calorimeter transition in the range 1.37 < |η | < 1.52. Photonsmust further satisfy isolation criteria based on both track and calorimeter information [67]. After correct-ing for contributions from pile-up, the energy within a cone of ∆R = 0.4 around the cluster barycentreis required to be less than 2.45 GeV + 0.022 × pγT, where pγT is the transverse momentum of the photoncandidate. The energy of tracks in a cone of ∆R = 0.2 should be less than 0.05 × pγT.

Jets are reconstructed with the anti-kt algorithm [70] with radius parameter R = 0.4, using as inputthree-dimensional energy clusters in the calorimeter [71] calibrated to the electromagnetic scale. Thereconstructed jets are then calibrated to the jet energy scale (JES) derived from simulation and in-situcorrections based on 13 TeV data [72, 73]. For all jets the expected average energy contribution frompile-up clusters is subtracted according to the jet area prescription [74]. Quality criteria are imposed toidentify jets arising from non-collision sources or detector noise and any event containing such a jet isremoved [75]. All jets are required to have pT > 20 GeV and |η | < 2.8.

Identification of jets containing b-hadrons (b-tagging) is performed with a multivariate discriminant,MV2c20, making use of track impact parameters, the b- and c-hadron flight paths inside the jet andreconstructed secondary vertices [45, 76]. The algorithm working point used corresponds to a 77% aver-age efficiency obtained for b-jets in simulated tt̄ events. The rejection factors for light-quark jets, c-quarkjets and hadronically decaying τ leptons in simulated tt̄ events are approximately 140, 4.5 and 10, re-spectively [45]. Jets with |η | < 2.5 which satisfy this b-tagging requirement are identified as b-jets. Tocompensate for differences between data and MC simulation in the b-tagging efficiencies and mis-tagrates, correction factors are applied to the simulated samples [45].

After object identification, overlaps between objects are resolved. If an electron and a muon share thesame ID track, the electron is removed. Any jet within a distance ∆R = 0.2 of an electron candidate isdiscarded, unless the jet has a value of the MV2c20 discriminant larger than that corresponding to ap-proximately 85% b-tagging efficiency, in which case the electron is discarded since it is likely originatingfrom a semi-leptonic b-hadron decay. Any remaining electron within ∆R = 0.4 of a jet is discarded.Muons within ∆R = 0.4 of a jet are also removed. However, if the jet has fewer than three associatedtracks, the muon is kept and the jet is discarded instead to avoid inefficiencies for high-energy muonsundergoing significant energy loss in the calorimeter. If a photon candidate is found within ∆R = 0.4 ofa jet, the jet is discarded and the object is considered a photon. Photons within a cone of ∆R = 0.4 of anelectron or muon candidate are discarded.

The missing transverse momentum (and its magnitude EmissT ) is defined as the negative vector sum of

the transverse momenta of all selected and calibrated physics objects (electrons, photons, muons, jets) inthe event, with an additional soft-term [77, 78]. The soft-term is constructed from all tracks that are notassociated with any physics object, and that are associated with the primary vertex.

6 Systematic uncertainties

Uncertainties in the background estimate arise from experimental effects, and the prediction of the norm-alisation and acceptance. Their effect is evaluated for all the background processes used in the analysis

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as well as for the benchmark signals. Among the main systematic uncertainties on the total backgroundpredictions are the ones associated with the jet and b-tagging calibrations and the finite size of the MCsamples.

The dominant experimental systematic uncertainties arise from the limited knowledge of the jet energyscale (JES) and resolution (JER) and the scale and resolution of the Emiss

T soft-term. The jet uncertaintiesare derived as a function of pT and η of the jet, as well as of the pile-up conditions and the jet flavourcomposition of the selected jet sample. They are determined using a combination of simulated samplesand studies of data, such as measurements of the transverse jet balance in dijet, Z+jet and γ+jet events[72, 73]. The uncertainties on the b-tagging scale factors are determined in samples of top quark andsimulated events [45]. Leptonic decays of J/ψ and Z-bosons in data and simulation are exploited toestimate the uncertainties in lepton reconstruction, identification, momentum/energy scale and resolution,and isolation criteria [65, 66]. Photon reconstruction and identification efficiencies are evaluated fromsamples of Z → ee and Z + γ events [67, 79]. The uncertainty related to the modelling of Emiss

T in thesimulation is estimated by propagating the uncertainties on the energy and momentum scale of each of theobjects entering the calculation, with an additional uncertainty on the resolution and scale of the soft-term[77, 78]. The luminosity measurement was calibrated during dedicated beam-separation scans, using thesame methodology as that described in [80]. The uncertainty of this measurement is found to be 2.1%.

Two different sources of uncertainty in the theoretical modelling of the SM production processes areconsidered, as described in the following. A first uncertainty is assigned to account for the knowledge ofthe cross-section for the inclusive process. A second uncertainty, larger in most cases, is used to coveracceptance modelling. In order to derive the modelling uncertainties either variation of the scales usedto perform the calculation or comparisons of the nominal MC samples with alternative ones are used.The total uncertainty is taken as the quadratic sum of the two components. Uncertainties on the PDFshave been found to be negligible in all but the multijet samples, for which they have been explicitlyestimated.

The inclusive W and Z cross-sections are known at NNLO, with an uncertainty of about 5% [31, 32].Modelling uncertainties on W+jets and Z+jets are determined by varying the renormalization, factoriza-tion and resummation scales in the ME by factors 0.5 and 2, together with a change of the merging scalefrom 20 GeV to 15 GeV or 30 GeV.

For top quark pair or single-top production, processes known to NNLO+NNLL [40] or approximateNNLO [81–83], respectively, the cross-section uncertainty is 7%. The modelling uncertainty on tt̄ isdetermined by comparing the nominal NLO+PS sample with an alternative sample generated with Sherpaincluding up to two ME at NLO and four at LO accuracy. The single-top uncertainty is estimated varyingthe renormalization and factorization scales, and by changing the hdamp parameter and the shower tune.An uncertainty on the interference between the Wt and tt̄ production is estimated by comparing thenominal Wt sample, where all doubly resonant NLO Wt diagrams are removed, with a sample where thecross-section contribution from Feynman diagrams containing two top quarks is subtracted [84].

Diboson processes (WW , W Z and Z Z) are calculated at NLO, and a 6% uncertainty on their cross-section, derived with the MCFM program [33, 34], is applied. Their modelling uncertainty is evaluatedanalogously to V+jets by varying the scales used to perform the calculation. For W +γ and Z +γ samples,which are computed at LO, a 20% uncertainty on the cross-section is used, with a further 20% modellinguncertainty assigned, based on the measurement in [85].

The cross-sections for top pair production in association with one or two vector bosons are calculated atNLO and an uncertainty of 15% is used [47]. Their modelling uncertainty is evaluated from variations of

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Table 2: The physics objects used for classifying the events, with their corresponding label and minimum pTrequirement.

Object jet b-jet electron muon photon EmissT

Label j b e µ γ EmissT

pT (min) [GeV] 60 60 25 25 50 200

the renormalization and factorization scales, together with a change in the merging scale. For tt̄ + γ, anadditional 12% uncertainty on the normalization is considered, while a uniform 30% uncertainty on themodelling is assigned.

Multijet and γ+jets processes are scaled to data, and no uncertainty on their normalization is applied.For multijets the maximum bin-by-bin difference between the Pythia 8 nominal sample and alternativesamples generated with Sherpa and Herwig++ is considered as an uncertainty on the physics modelling.In addition the envelope of the 100 replica sets of the NNPDF23LO PDF is used. The modelling uncer-tainty on γ+jets is estimated from scale variations with the same methodology as for the V+jets samples.The uncertainty on the γγ+jets modelling is instead taken to be of 30% from parton level comparisons ofsamples with varied scales.

A conservative uncertainty of 20% [49] is used for Higgs production in the gluon fusion, VBF and V Hchannels. An further uncertainty of 20% is assigned for the physics modelling.

For the subdominant triboson (including V + γγ), ttH , 3-top, 4-top and tZ production processes a 50%uncertainty is assigned to the event yields, similarly to [86].

7 Event Classification

The events are subdivided into exclusive classes based on the number and type of objects reconstructedin the event; electrons (e), muons (µ), photons (γ), jets ( j), b-tagged jets (b) and large Emiss

T (EmissT ) † are

considered. The subdivision can be regarded as a classification according to the most important featuresof the events. The pT requirements applied on top of the trigger selection and the labels used for eachobject are summarized in Table 2. The classification includes all possible final state configurations andobject multiplicities, e.g. if a data event with seven reconstructed muons is found it is classified in a “7-muon” event class (7µ). Similarly an event with missing transverse momentum, two muons, one photonand four jets is classified and considered in a corresponding event class denoted Emiss

T 2µ1γ4 j.

To suppress sources of fake EmissT additional requirements are applied on events to be classified in Emiss

Tcategories as follows. The meff variable is defined as the scalar sum of the pT of each reconstructed objectin the event and of the Emiss

T . The ratio of EmissT over meff is required to be greater than 0.2, and the

minimum azimuthal separation between the EmissT direction and the three leading reconstructed jets (if

present) has to be greater than 0.4, otherwise the event is rejected. Events in which the jet closest in φ tothe Emiss

T direction is found in or near an inactive detector region in the hadronic calorimeter barrel arealso discarded.

† Where the EmissT can originate from SM neutrinos or any other weakly interacting neutral particle.

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7.1 Corrections to the MC background

The MC samples for multijet and γ+jets production, while giving a good description of kinematic vari-ables, predict an overall cross-section and a jet multiplicity distribution that disagrees with data. In classescontaining only j and b the multijet MC samples are scaled to data with normalization factors derivedseparately in each exclusive jet multiplicity class. For event classes with fewer than 10 events, the nor-malization factor is taken from the event class with one jet (or b-jet) less. For γ+jets final states the samerescaling procedure is applied to channels with exactly one photon, no leptons or Emiss

T , and any numberof jets.

The Sherpa 2.1.1 MC has a known deficiency in the modelling of EmissT due to too large forward jet

activity. This results in a visible mismodelling of the EmissT distribution in event classes with two photons,

which also affects the meff distribution. To correct for this mismodelling a reweighting [87] is applied tothe background from real diphoton events (γγ+jet). The diphoton MC events are reweighted as functionof Emiss

T and of the number of selected jets to match the respective distributions for the inclusive diphotonsample in the range Emiss

T < 100 GeV.

7.2 Classification results

After classification, 639 event classes are found with at least one data event or a SM expectation greaterthan 0.1 events. The data and the background predictions from MC for these classes are shown in Figures1–10. Agreement is observed between data and the prediction in most of the event classes. Event classeswith a large fraction of tt̄ and multiple b-jets show small disagreements with the expectation, consistentwith the findings in Ref. [43]. Data events are found in 470 different event classes. These include eventswith up to four muons, four electrons, three photons, twelve jets and eight b-jets; 17 event classes havea SM expectation of less than 0.1 events. As in none of these classes more than two data events areobserved, they are not considered further in the analysis. The number of classes with a SM expectationlarger than 0.1 events is 622, and these classes are further considered for the statistical analysis.

Final states containing a single object, as well as those containing only EmissT and a lepton are sensitive to

the modelling of the soft particles they recoil against, and are hence discarded from the analysis. In addi-tion final states containing one electron and up to four jets or one b-jet are discarded as the contributionfrom the multijets background with one of the jets faking an electron is important and found to be poorlymodelled by the MC simulation.

8 Statistical Interpretation

In order to quantitatively determine the level of agreement between the data and the SM expectation andto identify regions of possible deviations an algorithm, developed by the H1 Collaboration [1], is used.The algorithm locates the region of largest deviation, be it a deficit or an excess, in a distribution providedin the form of a histogram. In each event class the values of the effective mass and of the total invariantmass in the event are considered. The invariant mass is computed from all visible objects in the event,with no attempt to use the Emiss

T information. These variables have been widely used in searches for newphysics, being sensitive to a large range of new physics signals, manifesting either as bumps or wideexcesses.

10

2j 3j 4j 5j 6j 7j 8j 9j10

j11

j12

j13

j14

j1b

1j1b

2j1b

3j1b

4j1b

5j1b

6j1b

7j1b

8j1b

9j1b

10j

1b11

j2b

2b1j

2b2j

2b3j

2b4j

2b5j

2b6j

2b7j

2b8j

2b9j 3b

3b1j

3b2j

3b3j

3b4j

3b5j

3b6j

3b7j

3b8j

3b9j 4b

4b1j

4b2j

4b3j

4b4j

4b5j

4b6j 5b

5b1j

5b2j

5b3j

5b4j 6b

6b1j

6b2j

6b3j 7b

8b1j

Eve

nts

1−10

1

10

210

310

410

510

610

710

810Data 2015 3-/4-top Higgs +Z/W/WWtt γ+tt single top

di-/triboson )γ(γZ/W+ +jetstt )+jetsγ(γ Z/W+jets multijets

ATLAS Preliminary-1 = 13 TeV, 3.21 fbs

dijet and multijet

Figure 1: The number of events in data and for the different SM background predictions considered. The classesare labeled according to the multiplicity and type (e, µ, γ, j, b, Emiss

T ) of the reconstructed objects for this eventclass. The hatched bands indicate the total uncertainty of the SM prediction. Part 1 of 12.

1jγ12jγ13jγ14jγ15jγ16jγ17jγ18jγ19jγ1 10j

γ11bγ1 1b1j

γ11b

2jγ11b

3jγ11b

4jγ11b

5jγ11b

6jγ11b

7jγ11b

8jγ1

2bγ1 2b1j

γ12b

2jγ12b

3jγ12b

4jγ12b

5jγ12b

6jγ12b

7jγ1

3bγ1 3b1j

γ13b

2jγ13b

3jγ13b

4jγ1

4bγ1 4b1j

γ14b

2jγ1

γ2 1jγ22jγ23jγ24jγ25jγ26jγ27jγ2

1bγ2 1b1j

γ21b

2jγ21b

3jγ21b

4jγ21b

5jγ2

2bγ2 2b1j

γ22b

2jγ22b

3jγ2

γ3 1jγ3

Eve

nts

1−10

1

10

210

310

410

510

610

710 Data 2015 3-/4-top Higgs +Z/W/WWtt γ+tt single top



photon(s)



11

1e5j

1e6j

1e7j

1e8j

1e9j

1e1b

4j

1e1b

5j

1e1b

6j

1e1b

7j

1e1b

8j

1e1b

9j

1e2b

1e2b

1j

1e2b

2j

1e2b

3j

1e2b

4j

1e2b

5j

1e2b

6j

1e2b

7j

1e2b

8j

1e3b

1e3b

1j

1e3b

2j

1e3b

3j

1e3b

4j

1e3b

5j

1e3b

6j

1e4b

1e4b

1j

1e4b

2j

1e4b

3j

1e4b

4j

1e4b

5j

1e5b

1e5b

1j

1e5b

2j

Eve

nts

1−10

1

10

210

310

410

510




single electron



1jµ12jµ13jµ14jµ15jµ16jµ17jµ18jµ19jµ1 1bµ1 1b1j

µ11b

2jµ1

1b3j

µ11b

4jµ1

1b5j

µ11b

6jµ1

1b7j

µ11b

8jµ1

1b9j

µ12bµ1 2b1j

µ12b

2jµ1

2b3j

µ12b

4jµ1

2b5j

µ12b

6jµ1

2b7j

µ12b

8jµ1

3bµ1 3b1j

µ13b

2jµ1

3b3j

µ13b

4jµ1

3b5j

µ13b

6jµ1

3b7j

µ14bµ1 4b1j

µ14b

2jµ1

4b3j

µ14b

4jµ1

4b5j

µ15bµ1 5b1j

µ15b

2jµ1

Eve

nts

1−10

1

10

210

310

410

510

610




single muon



12

1eµ1 1e1j

µ1

1e2j

µ1

1e3j

µ1

1e4j

µ1

1e5j

µ1

1e6j

µ1

1e7j

µ1 1e1b

µ1 1e1b

1jµ1

1e1b

2jµ1

1e1b

3jµ1

1e1b

4jµ1

1e1b

5jµ1

1e1b

6jµ1

1e1b

7jµ1

1e2b

µ1 1e2b

1jµ1

1e2b

2jµ1

1e2b

3jµ1

1e2b

4jµ1

1e2b

5jµ1

1e2b

6jµ1

1e3b

µ1 1e3b

1jµ1

1e3b

2jµ1

1e3b

3jµ1

1e3b

4jµ1

1e4b

µ1 1e4b

1jµ1

1e4b

2jµ1

Eve

nts

1−10

1

10

210

310

410




muon + electron



2e2e

1j2e

2j2e

3j2e

4j2e

5j2e

6j2e

7j2e

8j2e

1b2e

1b1j

2e1b

2j2e

1b3j

2e1b

4j2e

1b5j

2e1b

6j2e

1b7j

2e2b

2e2b

1j2e

2b2j

2e2b

3j2e

2b4j

2e2b

5j2e

3b2e

3b1j

2e3b

2j2e

3b3j

2e3b

4j2e

4b2e

4b1j µ2 1jµ22jµ23jµ24jµ25jµ26jµ27jµ28jµ2

1bµ2 1b1j

µ21b

2jµ2

1b3j

µ21b

4jµ2

1b5j

µ21b

6jµ2

1b7j

µ22bµ2 2b1j

µ22b

2jµ2

2b3j

µ22b

4jµ2

2b5j

µ22b

6jµ2

3bµ2 3b1j

µ23b

2jµ2

3b3j

µ24bµ2 4b1j

µ2

Eve

nts

1−10

1

10

210

310

410

510

610

710




dilepton



13

3e3e

1j3e

2j3e

3j3e

4j3e

1b3e

1b1j

3e1b

2j3e

1b3j

3e2b

3e2b

1j3e

2b2j 2eµ1 2e1j

µ12e

2jµ1

2e3j

µ12e

4jµ1 2e

1bµ1 2e

1b1j

µ12e

1b2j

µ12e

1b3j

µ12e

2bµ1 2e

2b1j

µ12e

2b2j

µ12e

2b5j

µ11eµ2 1e1j

µ21e

2jµ2

1e3j

µ21e

4jµ21e

1bµ2 1e

1b1j

µ21e

1b2j

µ21e

1b3j

µ21e

2bµ2 1e

2b1j

µ21e

2b2j

µ2µ3 1jµ32jµ33jµ34jµ35jµ3

1bµ3 1b1j

µ31b

2jµ3

1b3j

µ31b

4jµ3

2bµ3 2b1j

µ32b

2jµ3

4e4e

1j4e

1b 3eµ12eµ2 2e1j

µ22e

2jµ22e

1bµ2 2e

1b1j

µ21e

2bµ3

µ4 1jµ42jµ4

Eve

nts

1−10

1

10

210

310




3- and 4-lepton



γ1e

1 1jγ1e

12jγ

1e1

3jγ1e

14jγ

1e1

5jγ1e

16jγ

1e1

7jγ1e

1 1bγ1e

1 1b1j

γ1e

11b

2jγ

1e1

1b3j

γ1e

11b

4jγ

1e1

1b5j

γ1e

12bγ

1e1 2b

1jγ

1e1

2b2j

γ1e

12b

3jγ

1e1

2b4j

γ1e

12b

5jγ

1e1

3bγ1e

1 3b1j

γ1e

13b

2jγ

1e1

3b3j

γ1e

1γ

1e2 1jγ

1e2

2jγ1e

23jγ

1e2 1b

1jγ

1e2

1b2j

γ1e

2γ1µ11jγ1µ12jγ1µ13jγ1µ14jγ1µ15jγ1µ16jγ1µ1

1bγ1µ11b

1jγ1µ11b

2jγ1µ11b

3jγ1µ11b

4jγ1µ11b

5jγ1µ1

2bγ1µ12b

1jγ1µ12b

2jγ1µ12b

3jγ1µ12b

4jγ1µ12b

5jγ1µ1

3bγ1µ13b

1jγ1µ13b

2jγ1µ1

γ2µ11jγ2µ13jγ2µ1

1b2j

γ2µ1

Eve

nts

1−10

1

10

210

310




single lepton + photon(s)



14

γ2e

1 1jγ2e

1

2jγ2e

1

3jγ2e

1

4jγ2e

1

5jγ2e

1 1bγ2e

1 1b1j

γ2e

1

1b2j

γ2e

1

1b3j

γ2e

1

2bγ2e

1 2b1j

γ2e

1

3bγ2e

1

γ2e

2 γ1e

1µ1

1jγ1e

1µ1

2jγ1e

1µ1

3jγ1e

1µ1

1bγ1e

1µ1

1b1j

γ1e

1µ1

1b2j

γ1e

1µ1

1b3j

γ1e

1µ1

1b4j

γ1e

1µ1

2bγ1e

1µ1

2b1j

γ1e

1µ1

2b2j

γ1e

1µ1

γ1µ2

1jγ1µ2

2jγ1µ2

3jγ1µ2

4jγ1µ2

1bγ1µ2

1b1j

γ1µ2

1b2j

γ1µ2

1b3j

γ1µ2

2bγ1µ2

2b1j

γ1µ2

2b2j

γ1µ2γ2µ2

2jγ2µ2

1jγ1e

1µ2

Eve

nts

1−10

1

10

210

310




multilepton + photon(s)



1e1j

mis

sT

E1e

2jm

iss

TE

1e3j

mis

sT

E1e

4jm

iss

TE

1e5j

mis

sT

E1e

6jm

iss

TE

1e7j

mis

sT

E1e

8jm

iss

TE

1e1b

mis

sT

E1e

1b1j

mis

sT

E1e

1b2j

mis

sT

E1e

1b3j

mis

sT

E1e

1b4j

mis

sT

E1e

1b5j

mis

sT

E1e

1b6j

mis

sT

E1e

1b7j

mis

sT

E1e

2bm

iss

TE

1e2b

1jm

iss

TE

1e2b

2jm

iss

TE

1e2b

3jm

iss

TE

1e2b

4jm

iss

TE

1e2b

5jm

iss

TE

1e3b

mis

sT

E1e

3b1j

mis

sT

E1e

3b2j

mis

sT

E1e

3b3j

mis

sT

E1e

3b4j

mis

sT

E1e

4b1j

mis

sT

Eγ

1e1

mis

sT

E1jγ

1e1

mis

sT

E2jγ

1e1

mis

sT

E3jγ

1e1

mis

sT

E4jγ

1e1

mis

sT

E1bγ

1e1

mis

sT

E1b

1jγ

1e1

mis

sT

E1b

2jγ

1e1

mis

sT

E1b

3jγ

1e1

mis

sT

E2b

2jγ

1e1

mis

sT

E2e

mis

sT

E2e

1jm

iss

TE

2e2j

mis

sT

E2e

3jm

iss

TE

2e4j

mis

sT

E2e

1bm

iss

TE

2e1b

1jm

iss

TE

2e1b

2jm

iss

TE

2e1b

3jm

iss

TE

2e1b

4jm

iss

TE

2e2b

mis

sT

E2e

2b1j

mis

sT

E2e

2b2j

mis

sT

E2e

2b3j

mis

sT

E3e

mis

sT

E3e

1jm

iss

TE

3e2j

mis

sT

E1jµ1

mis

sT

E2jµ1

mis

sT

E3jµ1

mis

sT

E4jµ1

mis

sT

E5jµ1

mis

sT

E6jµ1

mis

sT

E7jµ1

mis

sT

E1bµ1

mis

sT

E1b

1jµ1

mis

sT

E1b

2jµ1

mis

sT

E1b

3jµ1

mis

sT

E1b

4jµ1

mis

sT

E

Eve

nts

1−10

1

10

210

310

410

510




+ (multi-)lepton (1/2)TmissE



15

1b5j

µ1m

iss

TE

1b6j

µ1m

iss

TE

1b7j

µ1m

iss

TE

2bµ1m

iss

TE

2b1j

µ1m

iss

TE

2b2j

µ1m

iss

TE

2b3j

µ1m

iss

TE

2b4j

µ1m

iss

TE

2b5j

µ1m

iss

TE

2b6j

µ1m

iss

TE

3bµ1m

iss

TE

3b1j

µ1m

iss

TE

3b2j

µ1m

iss

TE

3b3j

µ1m

iss

TE

3b4j

µ1m

iss

TE

γ1µ1m

iss

TE

1jγ1µ1m

iss

TE

2jγ1µ1m

iss

TE

3jγ1µ1m

iss

TE

4jγ1µ1m

iss

TE

5jγ1µ1m

iss

TE

1bγ1µ1m

iss

TE

1b1j

γ1µ1m

iss

TE

1b2j

γ1µ1m

iss

TE

1b3j

γ1µ1m

iss

TE

1eµ1m

iss

TE

1e1j

µ1m

iss

TE

1e2j

µ1m

iss

TE

1e3j

µ1m

iss

TE

1e4j

µ1m

iss

TE

1e5j

µ1m

iss

TE

1e1b

µ1m

iss

TE

1e1b

1jµ1

mis

sT

E1e

1b2j

µ1m

iss

TE

1e1b

3jµ1

mis

sT

E1e

1b4j

µ1m

iss

TE

1e2b

µ1m

iss

TE

1e2b

1jµ1

mis

sT

E1e

2b2j

µ1m

iss

TE

1e2b

3jµ1

mis

sT

E1e

2b4j

µ1m

iss

TE

γ1e

1µ1

mis

sT

E1jγ

1e1

µ1m

iss

TE

1bγ1e

1µ1

mis

sT

E2eµ1

mis

sT

E2e

1jµ1

mis

sT

E2e

2jµ1

mis

sT

Eµ2

mis

sT

E1jµ2

mis

sT

E2jµ2

mis

sT

E3jµ2

mis

sT

E4jµ2

mis

sT

E5jµ2

mis

sT

E1bµ2

mis

sT

E1b

1jµ2

mis

sT

E1b

2jµ2

mis

sT

E1b

3jµ2

mis

sT

E1b

4jµ2

mis

sT

E2bµ2

mis

sT

E2b

1jµ2

mis

sT

E2b

2jµ2

mis

sT

E2b

3jµ2

mis

sT

E1eµ2

mis

sT

E1e

1jµ2

mis

sT

E1e

2jµ2

mis

sT

E1jµ3

mis

sT

E2jµ3

mis

sT

E

Eve

nts

1

10

210

310




+ (multi-)lepton (2/2)TmissE



1jm

iss

TE

2jm

iss

TE

3jm

iss

TE

4jm

iss

TE

5jm

iss

TE

6jm

iss

TE

7jm

iss

TE

8jm

iss

TE

9jm

iss

TE

1bm

iss

TE

1b1j

mis

sT

E1b

2jm

iss

TE

1b3j

mis

sT

E1b

4jm

iss

TE

1b5j

mis

sT

E1b

6jm

iss

TE

1b7j

mis

sT

E1b

8jm

iss

TE

2bm

iss

TE

2b1j

mis

sT

E2b

2jm

iss

TE

2b3j

mis

sT

E2b

4jm

iss

TE

2b5j

mis

sT

E2b

6jm

iss

TE

3bm

iss

TE

3b1j

mis

sT

E3b

2jm

iss

TE

3b3j

mis

sT

E3b

4jm

iss

TE

3b5j

mis

sT

E4b

mis

sT

E4b

1jm

iss

TE

4b2j

mis

sT

E4b

3jm

iss

TE

γ1m

iss

TE

1jγ1m

iss

TE

2jγ1m

iss

TE

3jγ1m

iss

TE

4jγ1m

iss

TE

5jγ1m

iss

TE

6jγ1m

iss

TE

1bγ1m

iss

TE

1b1j

γ1m

iss

TE

1b2j

γ1m

iss

TE

1b3j

γ1m

iss

TE

1b4j

γ1m

iss

TE

2bγ1m

iss

TE

2b1j

γ1m

iss

TE

2b2j

γ1m

iss

TE

2b3j

γ1m

iss

TE

γ2m

iss

TE

1jγ2m

iss

TE

2jγ2m

iss

TE

1b2j

γ2m

iss

TE

Eve

nts

1−10

1

10

210

310

410

510

610

710

Data 2015 3-/4-top Higgs +Z/W/WWtt γ+tt single top



+ photons / jetsTmissE



16

The meff and minv distributions input to the scan use a variable bin width with values ranging from 20 GeVto about 2000 GeV. In each event class, the bin widths are determined from the expected resolution ofeach object as function of pT. A given scans starts at the value of the scanned variable greater than twotimes the sum of the minimum pT requirement of each contributing object considered (e.g. 100 GeV fora 2µ class). This avoids sensitivity to the threshold regions. The total number of independent bins with aSM expectation larger than 0.01 events or with data events is 15749.

The number of data events Nobs and the expectation NSM with its total systematic uncertainty δNSM isdetermined for each possible contiguous regions of histogram bins. For each region, a statistical estim-ator is determined from the convolution of the Poisson probability density function (pdf) to account forstatistical errors with a Gaussian pdf, G(x; NSM, δNSM) with mean NSM and width δNSM, to include theeffect of non negligible systematic uncertainties and is defined via:

p0 =

A∫ ∞

0dx G(x; NSM, δNSM)

∞∑i=Nobs

e−x xi

i!Nobs > NSM

A∫ ∞

0dx G(x; NSM, δNSM)

i=Nobs∑i=0

e−x xi

i!+ A∫ 0

−∞

dx G(x; NSM, δNSM) Nobs < NSM

(1)

The factor A ensures that the pdf is normalized to unity. If the Gaussian pdf G is replaced by a Diracdelta function δ(x − NSM) the estimator p0 results in a usual Poisson probability. The value of p0 givesan estimate of the probability for the SM expectation to fluctuate at least as high (or low) as observedin the data in a given region. Here p0 is to be interpreted as a local p0-value. The region of greatestdeviation found by the algorithm is the region with the smallest p0-value. Such a method is able to findnarrow resonances and single outstanding bins as well as signals spread over large regions of phase spacein distributions of any shape. To avoid being sensitive to the effect of poor MC statistics, regions wherethe background prediction has a relative uncertainty of over 100%, are discarded by the algorithm. As aconsequence, a signal that would show up as an excess in data in classes or regions with poor or no MCstatistics would be missed. To avoid overlooking potential excesses it was checked that no region withmore than four data event is discarded by the algorithm.

To illustrate how the algorithm operates, three example distributions are presented. Figure 13a shows theeffective mass distribution for the event class with three b-jets, one jet and Emiss

T (EmissT 3b1 j). Figure 13b

shows the visible invariant mass distribution for the event class with three electrons (3e) and Figure 13cthe visible invariant mass distribution for the class containing one muon, one photon, two b-jets, and twojets (1µ1γ2b2 j). The region of greatest deviation found by the search algorithm in these distributions, anexcess in 13a, deficits in 13b and 13c, is indicated by vertical blue lines.

8.1 Pseudo-experiments generation

The probability that a deviation of a given size occurs somewhere in the event class distributions ismodelled by pseudo-experiments. In this procedure, the data are replaced by pseudo-data which aregenerated according to the SM expectation. Each pseudo-experiment consists of the same event classesand distributions as considered in the data. The search algorithm can then be applied to each of thesedistributions. The p0-value distributions of the pseudo-experiments and their statistical properties can becompared with the p0-value distributions obtained from data.

17

[GeV]effm900 1000 1100 1200 1300 1400 1500 1600

Eve

nts

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+jetstt Z/W+jets

single top +Z/W/WWtt

Higgs di-/triboson

Other

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3b1jmissTChannel: E

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Data 2015 Total SM

di-/triboson )γ(γZ/W+

Z/W+jets Other

-1 = 13 TeV, 3.21 fbs

Channel: 3e

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(all objects) [GeV]invm200 400 600 800 1000 1200

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Data 2015 Total SM

γ+tt +jetstt

)γ(γZ/W+ single top

+Z/W/WWtt Other

-1 = 13 TeV, 3.21 fbs

2b2jγ1µChannel: 1

ATLAS Preliminary

(all objects) [GeV]invm1000 1500 2000 2500

Dat

a / M

C

01234

(c)

Figure 13: Examples distributions showing the results of the scan algorithm. (a) The meff distribution for the eventclass with three b-jets, one jet and large Emiss

T (EmissT 3b1 j). (b) The minv distribution for the event class with three

electrons (3e) and (c) the event class with one muon, one photon, two b-jets and two jets (1µ1γ2b2 j). The hatchedgrey band includes all systematic uncertainties. The dashed vertical blue lines indicate the region of interest, ROI,which has the smallest p0-value returned by the search algorithm.

18

In generating pseudo-experiments the effect of correlations between bins of the same distribution orbetween distributions of different final states is taken into account. For the experimental uncertaintiesa 100% correlation is assumed for the value of each nuisance parameter. The uncertainty in the normal-ization of the various backgrounds is also considered as 100% correlated across bins and final states. Foruncertainties in the background modelling it has been assumed that there is no correlation, both amongfinal states and within different bins of the same final state. It has been tested that changing the correlationassumptions and the size of the theoretical uncertainties by a factor of two does not lead to an appreciablechange in the results.

Figure 14 shows the fractions of pseudo-experiments that predict at least one, two, or three event classeswith deviations below a given p0-value (pmin) in the scans of the minv and meff distributions. The lowestp0-value in the data is found in the meff distribution of the 1m1e4b2 j event class and amounts to 5 · 10−4.This is consistent at the 70% level with the SM expectation obtained from the pseudo-experiment gen-eration. At least one class with a local p0-value below 10−4 is expected to be found in 30% of thepseudo-experiments in the scans of both the visible invariant mass distributions, and of the effective massdistribution.

)min

(p10

-log0 1 2 3 4 5 6 7 8

Fra

ctio

n of

pse

udo

expe

rimen

ts

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σ1 σ2 σ3 σ4 σ5


invvariable: m

pseudo experiments 1 class≥ 2 classes≥ 3 classes≥

Data

pseudo experiments SM-onlyincluding syst. correlations

)min

(p10

-log0 1 2 3 4 5 6 7 8

Fra

ctio

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udo

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0.2

0.4

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σ1 σ2 σ3 σ4 σ5


effvariable: m

pseudo experiments 1 class≥ 2 classes≥ 3 classes≥

Data


Figure 14: The fraction of pseudo-experiments in which a deviation is found with a p0-value smaller than a givenvalue, − log10(pmin), in the scans of the visible invariant mass, minv (left), and of the effective mass, meff (right). Inblue, green and red, respectively, are shown the expected fractions for observing at least one, two and three eventclasses with deviations above a given − log10(pmin). The coloured arrows represents the largest deviations observedin data.

8.2 Sensitivity to new physics signals

Pseudo-experiments have also been used to test the sensitivity of the analysis to the two benchmark signalmodels (as introduced before). The prediction of a model is added to the SM prediction, and this new totalprediction is used to generate pseudo-data samples. Again a MC technique is used to vary the distributionof signal events and to generate pseudo-experiments. The algorithm is run on the pseudo-experiments asfor real data, and the distribution of local p0-values is derived.

As figure of merit of the analysis’ sensitivity the fraction of pseudo-experiments which predict at least oneevent class below a given p0-value (pmin) is computed, both for the SM and SM plus signal hypotheses. InFigure 15 we show the sensitivity for the two benchmark signals considered as function of the mass of theproduced particle. For the Z ′ model, where we expect to reconstruct the resonance mass from its decay

19

)min

(p10

-log0 1 2 3 4 5 6 7 8

Fra

ctio

n of

pse

udo

expe

rimen

ts

0.0

0.2

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σ1 σ2 σ3 σ4 σ5

pseudo experiments 1 class≥SM-only,

= 9.54 fbZ'σ = 2 TeV, Z'

SM + Z', m

= 0.816 fbZ'σ = 3 TeV, Z'

SM + Z', m

= 0.00852 fbZ'σ = 4 TeV, Z'

SM + Z', m

ATLASSimulation Preliminary

invvariable: m

)min

(p10

-log0 1 2 3 4 5 6 7 8

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ctio

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σ1 σ2 σ3 σ4 σ5

pseudo experiments 1 class≥SM-only,

= 325 fbg~

σ, 0

1χ∼+t t→ g~SM +

) = (1000,1) GeV1

0χ∼

,mg~

(m

= 85.6 fbg~

σ, 0


) = (1200,1) GeV1

0χ∼

,mg~

(m

= 25.3 fbg~

σ, 0


) = (1400,1) GeV1

0χ∼

,mg~

(m

ATLASSimulation Preliminary

effvariable: m

Figure 15: The fraction of pseudo-experiments in which a deviation is found with a p0-value smaller than a givenvalue, − log10(pmin). The distribution is shown for pseudo-experiments generated under the hypothesis of SMbackground, and after injecting signals of Z ′ → ee, µµ (left) or gluino pairs (right) with g → tt̄ χ̃1

0 decays ofvarying masses. The line corresponding to the injection of a Z ′ with a mass of 4 TeV fully overlaps with the lineobtained from SM-only pseudo-experiments due to the small signal cross-section.

products, we inject the signal on the scan of the minv distribution. Gluinos cascade decay to the lightestneutralino which is undetected leading to missing transverse momentum. In gluino pair production due tothe presence of neutralinos in the decay, it is not possible to fully reconstruct the event. The gluino signalis thus injected in the scan of meff , where a broad excess at large values of this quantity is expected.

Exclusion and discovery sensitivity have to be distinguished when the results of the general search arecompared to model-based searches. An exclusion sensitivity at 95% CL in a dedicated search is equivalentto a single class having a p0-value smaller than 0.05. For discovery a deviation with a global p0-valueless than 3 · 10−7 is required.

In the general search pseudo-experiments are used to compute the probability, Pexp, to find a deviationof a given size in any of the 639 classes. We consider any deviation which would lead to Pexp < 1%as interesting, and worth a dedicated investigation. Applying this sensitivity criteria we can read fromFigure 15 how this search is sensitive to a Z ′ with a mass of about 2 TeV or a gluino with a mass of about1 TeV.

9 Conclusions

The data collected by the ATLAS experiment at the LHC during 2015, corresponding to a total of 3.2 fb−1

of pp collisions, have been used to search for deviations from the SM prediction at high transverse mo-mentum by a model-independent approach. Final states containing electrons, muons, photons, jets, b-tagged jets and missing transverse momentum have been scanned for deviations from the SM MonteCarlo prediction in the distributions of the effective mass and the total visible invariant mass of the re-constructed particles. The total number of exclusive final states investigated is 639. The distribution ofthe significances of the largest deviations found in each final state is compared to an expectation obtainedwith pseudo experiments. No significant deviations are found in the data. The largest discrepancy, with alocal p0-value of 5 · 10−4, is expected in about 70% of the pseudo-experiments.

20

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√s = 13 TeV pp collisions at the LHC using the ATLAS detector,

Eur. Phys. J. C 76 (2016) 517, arXiv: 1606.09150 [hep-ex].

Appendix

Figure 16 shows the distribution of the local p0-values observed in data for each event class, comparedto the expectation obtained by generating pseudo-experiments under the SM hypothesis for the minv andmeff scans.

(p-value)10

-log0 1 2 3 4 5 6 7 8

Num

ber

of e

vent

cla

sses

1

10

210

Fra

ctio

n of

pse

udo

expe

rimen

ts

3−10

2−10

1−10

1σ1 σ2 σ3 σ4 σ5


effvariable: m

pseudo experiments Data


(p-value)10

-log0 1 2 3 4 5 6 7 8

Num

ber

of e

vent

cla

sses

1

10

210

Fra

ctio

n of

pse

udo

expe

rimen

ts

3−10

2−10

1−10

1σ1 σ2 σ3 σ4 σ5


invvariable: m

pseudo experiments Data


Figure 16: The observed and expected distributions for the number of event classes having a given range in− log10(p0−value) in the scans of the visible invariant mass, minv, and of the effective mass, meff distributions.The data (black dots) are shown together with the expected distribution obtained from pseudo-experiments (redfilled area).

26

http://dx.doi.org/10.1140/epjc/s10052-016-4344-x


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