search for heavy resonances decaying into a pair of z

Eur. Phys. J. C (2021) 81:332https://doi.org/10.1140/epjc/s10052-021-09013-y

Regular Article - Experimental Physics

Search for heavy resonances decaying into a pair of Z bosons inthe �+�−�′+�′− and �+�−νν final states using 139 fb−1 ofproton–proton collisions at

√s = 13TeV with the ATLAS detector

ATLAS Collaboration�

CERN, 1211 Geneva 23, Switzerland

Received: 1 October 2020 / Accepted: 26 February 2021 / Published online: 19 April 2021© CERN for the benefit of the ATLAS collaboration 2021

Abstract A search for heavy resonances decaying into apair of Z bosons leading to �+�−�′+�′− and �+�−νν finalstates, where � stands for either an electron or a muon, ispresented. The search uses proton–proton collision data at acentre-of-mass energy of 13 TeV collected from 2015 to 2018that corresponds to the integrated luminosity of 139 fb−1

recorded by the ATLAS detector during Run 2 of the LargeHadron Collider. Different mass ranges spanning 200 GeVto 2000 GeV for the hypothetical resonances are considered,depending on the final state and model. In the absence ofa significant observed excess, the results are interpreted asupper limits on the production cross section of a spin-0 orspin-2 resonance. The upper limits for the spin-0 resonanceare translated to exclusion contours in the context of Type-Iand Type-II two-Higgs-doublet models, and the limits for thespin-2 resonance are used to constrain the Randall–Sundrummodel with an extra dimension giving rise to spin-2 gravitonexcitations.

Contents

1 Introduction . . . . . . . . . . . . . . . . . . . . . 12 ATLAS detector . . . . . . . . . . . . . . . . . . . 23 Data and simulation . . . . . . . . . . . . . . . . . 34 Event reconstruction . . . . . . . . . . . . . . . . . 45 Analysis of �+�−�′+�′− final state . . . . . . . . . 5

5.1 Event selection and categorisation . . . . . . . 55.1.1 Common event selection . . . . . . . . . 55.1.2 Event categorisation: multivariate analysis 65.1.3 Event categorisation: cut-based analysis . 7

5.2 Background estimation . . . . . . . . . . . . . 75.3 Signal and background modelling . . . . . . . . 8

Interference modelling . . . . . . . . . . . . . 96 Analysis of �+�−νν final state . . . . . . . . . . . 10

6.1 Event selection and categorisation . . . . . . . 10

� e-mail: [email protected]

6.2 Background estimation . . . . . . . . . . . . . 106.3 Signal and background modelling . . . . . . . . 11

7 Systematic uncertainties . . . . . . . . . . . . . . . 127.1 Experimental uncertainties . . . . . . . . . . . 127.2 Theoretical uncertainties . . . . . . . . . . . . 12

8 Results . . . . . . . . . . . . . . . . . . . . . . . . 138.1 Statistical procedure and impact of systematic

uncertainties . . . . . . . . . . . . . . . . . . . 138.2 General results . . . . . . . . . . . . . . . . . . 13

9 Interpretations . . . . . . . . . . . . . . . . . . . . 139.1 Spin-0 resonances . . . . . . . . . . . . . . . . 14

9.1.1 Spin-0 resonances with NWA . . . . . . 149.1.2 Spin-0 resonances with LWA . . . . . . . 169.1.3 Two-Higgs-doublet model . . . . . . . . 16

9.2 Spin-2 resonances . . . . . . . . . . . . . . . . 1710 Summary . . . . . . . . . . . . . . . . . . . . . . . 19Appendix . . . . . . . . . . . . . . . . . . . . . . . . 21References . . . . . . . . . . . . . . . . . . . . . . . . 23

1 Introduction

The discovery of a scalar particle by the ATLAS and CMScollaborations [1,2] in 2012, with measured properties [3–7] consistent with those of the Standard Model (SM) [8–10] Higgs boson, was a major milestone in the understand-ing of electroweak symmetry breaking [11–13]. One impor-tant question is whether the discovered particle is part ofan extended scalar sector as postulated by various exten-sions to the Standard Model such as the two-Higgs-doubletmodel (2HDM) [14]. These extensions predict additionalHiggs bosons, motivating searches in an extended massrange.

This paper reports on two searches for heavy resonancesdecaying into two SM Z bosons, encompassing the finalstates produced from the subsequent Z Z →�+�−�′+�′− andZ Z → �+�−νν decays, where � stands for either an elec-tron or a muon and ν stands for all three neutrino flavours.

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The data employed were recorded by the ATLAS detec-tor between 2015 and 2018 in proton–proton collisions at√s = 13 TeV and correspond to an integrated luminosity

of 139 fb−1. The additional Higgs boson (spin-0 resonance),denoted by H throughout this paper, is assumed to be pro-duced mainly via gluon–gluon fusion (ggF) and vector-bosonfusion (VBF) processes with the ratio of the two productionmechanisms unknown in the absence of a specific model.The results are interpreted separately for the ggF and VBFproduction modes, with events being classified into ggF- andVBF-enriched categories in both final states, as discussed inSects. 5 and 6. The searches cover a wide mass range from200 GeV up to 2000 GeV and look for an excess in the dis-tribution of the the four-lepton invariant mass, m4�, for the�+�−�′+�′− final state, and the transverse mass, mT, for the�+�−νν final state, as the escaping neutrinos do not allowthe full reconstruction of the final state. This mass range ischosen based on the sensitivity of the analysis as determinedby the selection criteria and the size of the data sample.

The transverse mass is defined as:

mT ≡√√√√

[√

m2Z +

(

p��T

)2 +√

m2Z +

(

EmissT

)2]2

−∣∣∣ �pT

�� + �EmissT

∣∣∣

2,

where mZ is the mass of the Z boson [15], �pT�� and �Emiss

Tare the transverse momentum of the lepton pair and the miss-ing transverse momentum with magnitudes of p��

T and EmissT ,

respectively. In the absence of such an excess, limits on theproduction rate of different signal hypotheses are obtainedfrom a simultaneous likelihood fit in the two final states.The hypothesis of a heavy Higgs boson in the narrow-widthapproximation (NWA) is studied. The upper limits on the pro-duction rate of a heavy Higgs boson are also translated intoexclusion contours in the context of the two-Higgs-doubletmodel. As several theoretical models favour non-negligiblenatural widths, large-width assumption (LWA) models [14],assuming widths of 1%, 5%, 10% and 15% of the resonancemass, are examined only for ggF production, which dom-inates in many scenarios over the next-largest contribution(VBF) in the search range. Results are also interpreted assum-ing the bulk Randall–Sundrum (RS) model [16,17] with awarped extra dimension giving rise to a spin-2 Kaluza–Klein(KK) excitation of the graviton GKK.

The main improvements relative to the previous search[18] are the following: (i) full LHC Run 2 integrated lumi-nosity is used; (ii) both analyses profit from improved lep-ton reconstruction and isolation selection to mitigate theimpact of additional pp interactions in the same or neigh-bouring bunch crossing (pile-up); (iii) the reconstruction ofjets uses a particle-flow algorithm which combines measure-ments from the tracker and the calorimeter; (iv) the nor-malisation of the SM Z Z background is derived from data

rather than being estimated from SM predictions; (v) eventclassification targeting different production processes is opti-mised using machine learning (ML) algorithms in the caseof Z Z → �+�−�′+�′− final state; (vi) the mT distribution isused to search for signals in the VBF-enriched category inthe case of the Z Z → �+�−νν final state, in addition to theuse of mT in the ggF-enriched category; and (vii) the searchrange is extended to 2000 GeV in signal mass. The improvedanalyses reduce the expected upper limit on the productioncross section of an additional heavy resonance by up to 40%in comparison with the previous published result scaled tothe full Run 2 luminosity. Results of a similar search from asubset of data collected at the LHC with

√s = 13 TeV have

been reported by the CMS Collaboration in Ref. [19].The paper is organised as follows. A brief description of

the ATLAS detector is given in Sect. 2. In Sect. 3 the dataand simulated samples are described. The object reconstruc-tion is described in Sect. 4. The analysis strategies for the�+�−�′+�′− and �+�−νν final states are described in Sects. 5and 6, respectively. Section 7 describes the systematic uncer-tainties, Sect. 8 the final results, and Sect. 9 the interpretationof these results in the various models.

2 ATLAS detector

The ATLAS experiment is described in detail in Ref. [20].ATLAS is a multipurpose detector with a forward–backwardsymmetric cylindrical geometry and a solid-angle1 coverageof nearly 4π . The inner tracking detector (ID), covering theregion |η| < 2.5, consists of a silicon pixel detector, a siliconmicrostrip detector, and a transition-radiation tracker. Theinnermost layer of the pixel detector, the insertable B-layer[21], was installed between Run 1 and Run 2 of the LHC.The inner detector is surrounded by a thin superconductingsolenoid providing a 2 T magnetic field, and by a finely seg-mented lead/liquid-argon (LAr) electromagnetic calorimetercovering the region |η| < 3.2. A steel/scintillator-tile hadroncalorimeter provides coverage in the central region |η| <

1.7. The endcap and forward regions, covering the pseudo-rapidity range 1.5 < |η| < 4.9, are instrumented with LArelectromagnetic and hadron calorimeters, with steel, copper,or tungsten as the absorber material. A muon spectrometer(MS) system incorporating large superconducting toroidalair-core magnets surrounds the calorimeters. Three layers ofprecision wire chambers provide muon tracking in the range

1 The ATLAS experiment uses a right-handed coordinate system withits origin at the nominal interaction point (IP) in the centre of the detectorand the z-axis along the beam pipe. The x-axis points from the IP tothe centre of the LHC ring, and the y-axis points upward. Cylindricalcoordinates (r, φ) are used in the transverse plane, φ being the azimuthalangle around the z-axis. The pseudorapidity is defined in terms of thepolar angle θ as η = − ln tan(θ/2).

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|η| < 2.7, while dedicated fast chambers are used for trigger-ing in the region |η| < 2.4. The trigger system, composed oftwo stages, was upgraded [22] before Run 2. The first stage,implemented with custom hardware, uses information fromthe calorimeters and muon chambers to select events from the40 MHz bunch crossings at a maximum rate of 100 kHz. Thesecond stage, called the high-level trigger (HLT), reduces thedata acquisition rate to about 1 kHz on average. The HLT issoftware-based and runs reconstruction algorithms similar tothose used in the offline reconstruction.

3 Data and simulation

The proton–proton (pp) collision data used in these searcheswere collected by the ATLAS detector at a centre-of-massenergy of 13 TeV with a 25 ns bunch-spacing configura-tion from 2015 to 2018. The data are subjected to qualityrequirements: if any relevant detector component was notoperating correctly during the period in which an event wasrecorded, the event is rejected. The efficiency for recordinggood-quality data during Run 2 is 95.6% [23].

Simulated events are used to determine the signal accep-tance and some of the background contributions. The eventsproduced by each Monte Carlo (MC) event generator wereprocessed through the ATLAS detector simulation [24]within the Geant4 framework [25]. Additional inelastic ppinteractions were overlaid on the simulated signal and back-ground events. The MC event generator used for pile-upis Pythia 8.186 [26] with the A2 set of tuned parameters[27] and the MSTW2008LO [28] parton distribution function(PDF) set. The simulated events are weighted to reproducethe observed distribution of the mean number of interactionsper bunch crossing in data (pile-up reweighting).

Heavy spin-0 resonance production was simulated usingthe Powheg- Box v2 [29] MC event generator. The gluon–gluon fusion and vector-boson fusion production modeswere simulated separately, with matrix elements calcu-lated to next-to-leading-order (NLO) accuracy in quantumchromodynamics (QCD). Powheg- Box was interfaced toPythia 8.212 [30] for parton showering and hadronisationwith the AZNLO set of tuned parameters [31], and for decay-ing the Higgs boson into the H → Z Z → �+�−�′+�′− orH → Z Z → �+�−νν final states. The event generator wasinterfaced to the EvtGen v1.2.0 program [32] for the simu-lation of bottom and charm hadron decays. The leading-order(LO)CT10PDF set [33] was used for the hard-scattering pro-cess. Events from ggF and VBF production were generatedin the resonance mass range of 300–2000 GeV in the NWA,using a step size of 100 GeV up to 1000 GeV and 200 GeVabove. For the �+�−�′+�′− final state, due to the sensitivity ofthe analysis at lower masses, events were also generated formH = 200 GeV. In addition, events from ggF heavy Higgs

production with a width of 15% of the Higgs boson massmH were generated at NLO accuracy in QCD with Mad-

Graph5_aMC@NLO v2.3.2 [34], which was interfaced toPythia 8.210 for parton showering and hadronisation withthe A14 set of tuned parameters (A14 tune) [35], and fordecaying the Higgs boson into the two leptonic final states.The properties of bottom and charm hadron decays were sim-ulated by EvtGen v1.2.0. Events were generated in the res-onance mass range of 400–2000 GeV using a step size of100 (200) GeV up to (above) 1000 GeV. Similarly, eventswith a width of 5% or 10% of mH = 900 GeV were gen-erated for validating the analytic parametrisation of the m4�

distribution used in the �+�−�′+�′− final state as described inSect. 5.3. For the �+�−νν final state, a reweighting procedureas described in Sect. 6.3 is used on fully simulated events toobtain the reconstructed mT distribution at any value of massand width tested.

Spin-2 Kaluza–Klein gravitons from the bulk Randall–Sundrum model [17,36] were generated withMadGraph5_aMC@NLO at LO accuracy in QCD with theNNPDF2.3 LO PDF set with αs = 0.130 [37], which isthen interfaced to Pythia 8.210 for parton showering andhadronisation with the A14 tune and for decaying the heavyZ Z resonance into the two leptonic final states. The proper-ties of bottom and charm hadron decays were simulated byEvtGen v1.2.0. The dimensionless coupling k/MPl, whereMPl = MPl/

√8π is the reduced Planck scale and k is the

curvature scale of the extra dimension, is set to 1. The widthof the resonance is correlated with the coupling k/MPl and inthis configuration it is around ∼ 6% of its mass. Mass pointsbetween 600 GeV and 2 TeV with 200 GeV spacing weregenerated for both final states.

The qq → Z Z background was simulated by theSherpa v2.2.2 [38] generator, in which the NNPDF3.0NNLO PDF set [37] was used for the hard-scattering process,achieving NLO accuracy in the matrix-element calculationfor 0- and 1-jet final states and LO accuracy for 2- and 3-jetfinal states with the Comix [39] and OpenLoops [40–42]matrix-element generators. The merging with the Sherpa

parton shower [43] was performed using the MEPS@NLOprescription [44]. NLO electroweak (EW) corrections wereapplied as a function of m4� for the �+�−�′+�′− final state[45,46], and as a function of the transverse momentum of theZ boson that decays into two neutrinos for the �+�−νν finalstate [40,47–50]. The EW production of a Z Z pair and twoadditional jets via vector-boson scattering up to O(α6

EW) wasgenerated using Sherpa v2.2.2 for both the �+�−�′+�′− and�+�−νν final states, where the process Z Z Z → 4�qq isalso taken into account. In addition, the WZ diboson eventsfrom both QCD and EW production, with the subsequent lep-tonic decays of both the W and Z bosons, were simulated bySherpa with a similar set-up. The WZ events with Z boson

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decaying leptonically and W boson decaying hadronicallywere modelled with Sherpa v2.2.1.

The gg → Z Z process was modelled by Sherpa v2.2.2 atLO accuracy in QCD for both final states, including the off-shell SM h boson contribution and the interference betweenthe h and Z Z processes. The higher-order correction fac-tor accounting for up to NLO accuracy in QCD for thegg → Z Z continuum production was calculated for mass-less quark loops [51–53] in the heavy-top-quark approxima-tion [54], including the gg → h∗ → Z Z process [55]. Basedon these studies, a constant factor of 1.7 is used, and a relativeuncertainty of 60% is assigned to the normalisation in bothsearches.

For the �+�−νν final state, the contribution from WWproduction was removed in the Sherpa simulation of theqq → Z Z and gg → Z Z processes by requiring thecharged leptons and the neutrinos to have different leptonflavours. The qq → WW and gg → WW processes werethen modelled with Powheg- Box v2 and Sherpa v2.2.2,respectively. The interference between WW and Z Z pro-duction is expected to be negligible [48] and is therefore notconsidered.

Events containing a single Z boson with associated jetswere simulated using the Sherpa v2.2.1 event generator.Matrix elements were calculated for up to two partons at NLOand four partons at LO using the Comix and OpenLoops

matrix-element generators and merged with the Sherpa

parton shower using the MEPS@NLO prescription. TheNNPDF3.0 NNLO PDF set was used in conjunction withdedicated parton-shower tuning developed by the Sherpa

authors. The Z + jets events are normalised using the NNLOcross sections [56].

The triboson backgrounds Z Z Z , WZZ , and WWZ withfully leptonic decays and at least four prompt charged lep-tons were modelled using Sherpa v2.2.2 with LO accuracyof the QCD calculations and the CT10 PDF set. The simula-tion of t t+V production (V = W or Z ) with both top quarksdecaying semileptonically and the vector boson decayinginclusively was performed with MadGraph5_aMC@NLOinterfaced to Pythia 8.210 for parton showering and hadro-nisation with the A14 tune and to EvtGen v1.2.0 for thesimulation of bottom and charm hadron decays. The totalcross section is normalised to the prediction of Ref. [57],which includes the two dominant terms at both LO and NLOin a mixed perturbative expansion in the QCD and EW cou-plings. The t t background, as well as single-top and Wt pro-duction, were modelled using Powheg- Box v2 interfacedto Pythia 8.230 with the A14 tune and to EvtGen v1.6.0for the simulation of bottom and charm hadron decays.

In order to study the interference treatment for the LWAcase, samples containing the gg → Z Z continuum back-ground (B) as well as its interference (I) with a hypotheticalheavy Higgs signal (S) were used and are referred to as SBI

samples hereafter. In the �+�−�′+�′− final state the MCFM

NLO event generator [58], interfaced to Pythia 8.212, wasused to produce SBI samples where the width of the heavyscalar is set to 15% of its mass, for masses of 200, 300, 400,500, 600, 800, 1000, 1200, and 1400 GeV. Background-onlysamples were also generated with the MCFM event genera-tor, and are used to extract the signal-plus-interference term(SI) by subtracting them from the aforementioned SBI sam-ples. For the �+�−νν final state, the SBI samples were gener-ated with the gg2VV event generator [59,60]. The samplesinclude signal events with a scalar mass of 400, 700, 900,1200, and 1500 GeV.

4 Event reconstruction

Electron reconstruction uses a dynamic, topologicalcalorimeter-cell clustering-based approach which allowsimproved measurement of the electron energy, particularly insituations where an electron radiates a bremsstrahlung pho-ton; details can be found in Ref. [61]. Electron candidatesare clusters of energy deposits in the calorimeter associatedwith ID tracks, where the final track–cluster matching is per-formed after the tracks have been fitted with a Gaussian-sumfilter (GSF) [62] to account for bremsstrahlung energy losses.The electron’s transverse momentum is computed from thecluster energy and the track direction at the interaction point.Background rejection relies on the longitudinal and trans-verse shapes of the electromagnetic showers in the calorime-ters, track–cluster matching, and properties of tracks in theID. All of this information, except for that related to trackhits, is combined into a likelihood discriminant. The selec-tion combines the likelihood with the number of track hitsand defines several working points (WP). Selected electronshave pT > 4.5 GeV and |η| < 2.47. The �+�−�′+�′− analy-sis uses a ‘loose’ WP, with an efficiency of at least 90% forelectrons with pT > 30 GeV [63]. The ‘medium’ WP (withan efficiency about 85% for electrons with pT > 30 GeV) isadopted to select candidate electrons in the �+�−νν analysis.

Muons are formed from tracks reconstructed in the IDand MS, and their identification is primarily based on thepresence of the track or track segment in the MS [64]. Ifa complete track is present in both the ID and the MS, acombined muon track is formed by a global fit using thehit information from both the ID and MS detectors (com-bined muon); otherwise the momentum is measured usingthe ID, and the MS track segment serves as identification(segment-tagged muon). The segment-tagged muon is lim-ited to the centre of the barrel region (|η| < 0.1) which hasreduced MS geometrical coverage. Furthermore, in this cen-tral region an ID track with pT > 15 GeV is identified as amuon if its calorimetric energy deposition is consistent witha minimum-ionising particle (calorimeter-tagged muon). In

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the forward region (2.5 < |η| < 2.7) with limited or noID coverage, the MS track formed out of three MS layersis either used alone (stand-alone muon) or combined withsilicon-detector hits, if found in the forward ID (combinedmuon). The ID tracks associated with the muons are requiredto have at least a minimum number of associated hits in eachof the ID subdetectors to ensure good track reconstruction.The minimum pT for muon candidates is 5 GeV, while themaximum |η| is 2.7. A ‘loose’ muon identification WP, whichuses all muon types, is adopted by the �+�−�′+�′− analysis.This criterion has an efficiency of at least 98% [64] for iso-lated muons with pT = 5 GeV and rises to 99.5% at higherpT. For the �+�−νν analysis a ‘medium’ WP is used, whichonly includes combined muons and has an efficiency of 98%.

The reconstruction of jets uses a particle-flow algorithm[65] which combines measurements from both the trackerand the calorimeter. The energy deposited in the calorimeterby all charged particles is removed, and the jet reconstructionis performed on an ensemble of ‘particle-flow objects’ con-sisting of the remaining calorimeter energy and tracks whichare matched to the hard interaction. This improves the accu-racy of the charged-hadron measurement, while retainingthe calorimeter measurements of neutral-particle energies.Compared to only using topological clusters [66], jets recon-structed with the particle-flow algorithm with pT of about30 GeV have approximately 10% better transverse momen-tum resolution. The two different algorithms have similar res-olutions for pT above 100 GeV. Particle-flow jets are recon-structed using the anti-kt algorithm [67] with a radius param-eter R = 0.4. The jet four-momentum is corrected for thecalorimeter’s non-compensating response, signal losses dueto noise threshold effects, energy lost in non-instrumentedregions, and contributions from pile-up [68]. The jets usedare required to satisfy pT > 30 GeV and |η| < 4.5. Jets frompile-up with |η| < 2.5 are suppressed using a jet-vertex-tagger multivariate discriminant [69,70].

Jets containing b-hadrons, referred to as b-jets, are iden-tified by the long lifetime, high mass, and decay multiplicityof b-hadrons, as well as the hard b-quark fragmentation func-tion. The �+�−νν analysis identifies b-jets of pT > 20 GeVand |η| < 2.5 using an algorithm that achieves an identifi-cation efficiency of about 85% in simulated t t events, with arejection factor for light-flavour jets of about 30 [71].

Selected events are required to have at least one vertex hav-ing at least two associated tracks with pT > 500 MeV, andthe primary vertex is chosen to be the vertex reconstructedwith the largest

∑

p2T of its associated tracks. As lepton and

jet candidates can be reconstructed from the same detectorinformation, a procedure to resolve overlap ambiguities isapplied. In the �+�−�′+�′− case, the overlap ambiguities areresolved as follows. If two electrons have overlapping energydeposits, the electron with the higher pT is retained. If areconstructed electron and muon share the same ID track,

the muon is rejected if it is calorimeter-tagged; otherwise theelectron is rejected. Reconstructed jets geometrically over-lapping in a cone of size R = 0.2 with electrons or muonsare also removed. The overlap removal in the �+�−νν caseis similar to that in the �+�−�′+�′− case, except for an addi-tional criterion that removes any leptons close to the remain-ing jets with 0.2 < R < 0.4. This additional criterion isnot imposed in the �+�−�′+�′− case due to the cleaner envi-ronment of this final state and in order to maximise the signalefficiency.

The missing transverse momentum �EmissT , which accounts

for the imbalance of visible momenta in the plane transverseto the beam axis, is computed as the negative vector sum ofthe transverse momenta of all identified electrons, muons andjets, as well as a ‘soft term’, accounting for unclassified softtracks and energy clusters in the calorimeters [72]. This anal-ysis uses a track-based soft term, which is built by combiningthe information provided by the ID and the calorimeter, inorder to minimise the effect of pile-up, which degrades theEmiss

T resolution.

5 Analysis of �+�−�′+�′− final state

5.1 Event selection and categorisation

In Sect. 5.1.1 the four-lepton event selection is described.After this selection, events are further split into several cate-gories, in order to probe different signal production modes,such as VBF production and ggF production. To enhance thesearch sensitivity to the NWA signals, multivariate classi-fiers are optimised for the event categorisation as describedin Sect. 5.1.2. In order to also obtain results that are moremodel-independent (since the training of the multivariateclassifiers is usually based on a specific signal model), a cut-based event categorisation that enhances the sensitivity in theVBF production mode is also considered and is described inSect. 5.1.3.

In the search for LWA signals, due to the complexityof modelling the categorisation of the interference betweenheavy Higgs boson and SM Higgs boson processes, onlythe ggF-enriched categories of the cut-based analysis (CBA)are used. The same strategy is adopted in the search for aKaluza–Klein graviton excitation.

5.1.1 Common event selection

Four-lepton events are selected and initially classified accord-ing to the lepton flavours: 4μ, 2e2μ, 4e, called ‘channels’hereafter. They are selected using a combination of single-lepton, dilepton and trilepton triggers with different trans-verse momentum thresholds. The single-lepton triggers withthe lowest pT thresholds had tighter requirements than the

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high pT threshold single-lepton triggers and the multilep-ton triggers. Due to an increasing peak luminosity, these pT

thresholds increased during the data-taking periods [73,74].For single-muon triggers, the pT threshold increased from 20to 26 GeV, while for single-electron triggers, the pT thresholdincreased from 24 to 26 GeV. The overall trigger efficiencyfor signal events passing the final selection requirements isabout 98%.

In each channel, four-lepton candidates are formed byselecting a lepton-quadruplet made out of two same-flavour,opposite-sign lepton pairs, selected as described in Sect. 4.Each electron (muon) must satisfy pT > 7 (5) GeV andbe measured in the pseudorapidity range of |η| < 2.47(2.7). The highest-pT lepton in the quadruplet must satisfypT > 20 GeV, and the second (third) lepton in pT ordermust satisfy pT > 15 GeV (10 GeV). In the case of muons, atmost one calorimeter-tagged, segment-tagged or stand-alone(2.5 < |η| < 2.7) muon is allowed per quadruplet.

If there is ambiguity in assigning leptons to a pair, only onequadruplet per channel is selected by keeping the quadrupletwith the invariant mass of the lepton pairs closest (leadingpair) and second closest (subleading pair) to the Z bosonmass [15], with invariant masses referred to as m12 andm34 respectively. In the selected quadruplet, m12 must sat-isfy 50 GeV < m12 < 106 GeV and m34 must satisfy50 GeV < m34 < 115 GeV.

Selected quadruplets are required to have their leptonsseparated from each other by R > 0.1. For 4μ and 4equadruplets, if an opposite-charge same-flavour lepton pairis found with m�� below 5 GeV, the quadruplet is removedto suppress the contamination from J/ψ mesons. If multiplequadruplets from different channels are selected at this point,only the quadruplet from the channel with the highest signalacceptance is retained, in the order: 4μ, 2e2μ, 4e.

The Z + jets and t t background contributions are reducedby imposing impact-parameter requirements as well as track-and calorimeter-based isolation requirements on the leptons.The transverse impact-parameter significance, defined as theimpact parameter calculated relative to the measured beam-line position in the transverse plane divided by its uncer-tainty, |d0|/σd0 , for all muons (electrons), is required to belower than 3 (5). The track-isolation discriminant is calcu-lated from the tracks with pT > 500 MeV that lie withina cone of R = 0.3 around the muon or electron and thateither originate from the primary vertex or have a longitudi-nal impact parameter z0 satisfying |z0 sin(θ)| < 3 mm if notassociated with any vertex. Above a lepton pT of 33 GeV,the cone size falls linearly with pT to a minimum cone sizeof 0.2 at 50 GeV. Similarly, the calorimeter isolation is cal-culated from the positive-energy topological clusters that arenot associated with a lepton track in a cone of R = 0.2around the muon or electron. The sum of the track isolationand 40% of the calorimeter isolation is required to be less than

16% of the lepton pT. The calorimeter isolation is correctedfor electron shower leakage, pile-up, and underlying-eventcontributions. Both isolations are corrected for track andtopological cluster contributions from the remaining threeleptons. The pile-up dependence of this isolation selection isreduced compared with that of the previous search by opti-mising the criteria used for exclusion of tracks associatedwith a vertex other than the primary vertex and by the removalof topological clusters associated with tracks.

An additional requirement based on a vertex-reconstructionalgorithm, which fits the four-lepton candidates with the con-straint that they originate from a common vertex, is appliedin order to further reduce the Z + jets and t t backgroundcontributions. A cut of χ2/ndof < 6 for 4μ and < 9 for theother channels is applied, with an efficiency larger than 99%for signal in all channels.

The QED process of radiative photon production in Zboson decays is well modelled by simulation. Some of thefinal-state-radiation (FSR) photons can be identified in thecalorimeter and incorporated into the �+�−�′+�′− analysis.The strategy to include FSR photons into the reconstructionof Z bosons is the same as in Run 1 [75]. It consists of a searchfor collinear (for muons) and non-collinear FSR photons (formuons and electrons) with only one FSR photon allowedper event. After the FSR correction, the four-momenta ofboth dilepton pairs are recomputed by means of a Z -mass-constrained kinematic fit [76]. The fit uses a Breit–Wigner Zboson lineshape and a single Gaussian function per lepton tomodel the momentum response function with the Gaussianwidth set to the expected resolution for each lepton. The Z -mass constraint is applied to both Z candidates.

Events that pass the common event selection (as describedabove) which are not yet split according to lepton flavours,form a category which is called ‘inclusive’ hereafter.

5.1.2 Event categorisation: multivariate analysis

In order to improve the sensitivity in the search for anNWA Higgs boson signal produced either in the VBF or theggF production mode, two multivariate classifiers, namely a‘VBF classifier’ and a ‘ggF classifier’, are used. These clas-sifiers are built with deep neural networks (DNN) and usea architecture similar to that in Ref. [77], combining a mul-tilayer perceptron (MLP) and one or two recurrent neuralnetworks (rNN) [78]. For both classifiers, the outputs of theMLP and rNN(s) are concatenated and fed into an additionalMLP that produces an event score.

The ‘VBF classifier’ uses two rNNs and an MLP. The tworNNs have as inputs the pT-ordered transverse momenta andthe pseudorapidities of the two leading jets and the trans-verse momenta and the pseudorapidities of the four leptonsin the event. The MLP uses as inputs the invariant mass ofthe four-lepton system, the invariant mass and the transverse

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momentum of the two-leading-jets system, the difference inpseudorapidity between the �+�−�′+�′− system and the lead-ing jet, and the minimum angular separation between the�+�− or �′+�′− pair and a jet.

The ‘ggF classifier’ uses one rNN and an MLP. The rNNhas as inputs the pT-ordered transverse momenta and thepseudorapidities of the four leptons in the event. The MLPuses as inputs the following variables: (1) the four-leptoninvariant mass; (2) the transverse momentum and the pseu-dorapidity of the four-lepton system; (3) the production angleof the leading Z defined in the four-lepton rest frame, cos θ∗;(4) the angle between the negative final-state lepton and thedirection of flight of leading (subleading) Z in the Z restframe, cos θ1 (cos θ2); (5) the angle between the decay planesof the four final-state leptons expressed in the four-lepton restframe, �; and (6) the transverse momentum and the pseudo-rapidity of the leading jet.

The two classifiers are trained separately using the above-listed discriminating variables on all simulated NWA signalevents from their corresponding production mode, and theSM Z Z background events. The ‘VBF classifier’ is trainedon events with at least two jets while the ‘ggF classifier’ istrained on events with fewer than two jets. In order to rep-resent the relative importance of the signal and backgroundevents, weights that scale the events to the same luminosityaccording to their production cross sections are used in thetraining. Furthermore, in order to achieve good discriminat-ing power of the classifiers over a large range of signal masshypotheses, the signal events are reweighted such that theiroverall four-lepton invariant mass spectrum matches that ofthe SM background events. As a result of this reweightingmethod the classifiers do not produce a bias towards a specificmass point. Extensive checks are performed to ensure suchtreatment does not create a local excess of background eventsthat would fake a signal. Figure 1 shows the ‘ggF classifier’and ‘VBF classifier’ output for the data, the SM backgroundand an example signal with mH = 600 GeV.

After the common event selection, as described inSect. 5.1.1, events with at least two jets (njets ≥ 2) and a ‘VBFclassifier’ score value greater than 0.8 form the VBF-MVA-enriched category. Events failing to enter the VBF-MVA-enriched category are classified into the ggF-MVA-high cat-egory if the ‘ggF classifier’ score value is greater than 0.5;these events are further split into three distinct categoriesaccording to the lepton flavour of the �+�−�′+�′− system.Finally, events failing both classifiers form the ggF-low cate-gory. Overall, five mutually exclusive categories are formed:VBF-MVA-enriched, ggF-MVA-high-4μ, ggF-MVA-high-2e2μ, ggF-MVA-high-4e, ggF-MVA-low. This categorisa-tion is used in the search for a heavy scalar with the NWAand in the search in the context of a CP-conserving 2HDM.

The signal acceptance, defined as the ratio of the numberof reconstructed events after all selection requirements to the

total number of simulated events, is found to be between 30%(15%) and 46% (22%) in the ggF (VBF)-enriched categoryfor the ggF (VBF) production mode depending on the signalmass hypothesis.

5.1.3 Event categorisation: cut-based analysis

As in the previous publication [18], a cut-based analysisis also performed to probe the sensitivity in the VBF pro-duction mode. If an event has two or more jets with pT

greater than 30 GeV, with the two leading jets being wellseparated in η, ηjj > 3.3, and having an invariant massmjj > 400 GeV, this event is classified into the VBF-enrichedcategory; otherwise the event is classified into one of theggF-enriched categories further split according to the leptonflavour of the �+�−�′+�′− system. Four distinct categoriesare formed, namely VBF-CBA-enriched, ggF-CBA-4μ, ggF-CBA-2e2μ, and ggF-CBA-4e. The ggF-enriched categoriesare used in the search for a heavy large-width scalar and thesearch for a Kaluza–Klein graviton excitation. In addition,as for the multivariate-based analysis, such categorisation isused in the search for a heavy scalar with the NWA and thecorresponding results are described in the Appendix.

5.2 Background estimation

The main background source in the H → Z Z →�+�−�′+�′−final state is non-resonant SM Z Z production, accountingfor 97% of the total background events in the inclusive cate-gory. It arises from quark–antiquark annihilation qq → Z Z(86%), gluon-initiated production gg → Z Z (10%), and asmall contribution from EW vector-boson scattering (1%).The last of these is more important in the VBF-enriched cat-egory using the DNN-based categorisation, where it accountsfor 20% of the total background events. While in the previ-ous publication [18] the SM Z Z background was exclusivelyestimated from simulation for both the shape and the normal-isation, in this analysis its normalisation is derived from thedata in the likelihood fit used in the statistical treatment ofthe data as explained in Sect. 8. The shapes of the qq → Z Zand gg → Z Z invariant mass distributions are parameterisedwith analytic functions as described in Sect. 5.3. Additionalbackground comes from the Z + jets and t t processes. Thesecontribute to the total background yields at the percent leveland decrease more rapidly than the non-resonant Z Z con-tribution as a function of m4�. These backgrounds are esti-mated using data where possible, following slightly differentapproaches for final states with a dimuon (�� + μμ) or adielectron (�� + ee) subleading pair [79,80].

The ��+μμ non-Z Z background comprises mostly t t andZ + jets events, where in the latter case the muons arise mostlyfrom heavy-flavour semileptonic decays and to a lesser extentfrom π /K in-flight decays. The normalisations of the Z +

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nts

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+V , VVVtt tt+jets,Z

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red.

(b)

Fig. 1 The output of a the ‘ggF classifier’ (NNggF) and b the ‘VBFclassifier’ (NNVBF) for the events passing the common event selectionsfor the data, the SM background and NWA signal events with a mass of600 GeV. For b the ‘VBF classifier’ output, an additional requirementof at least two jets in the event, is applied. The signal cross section is set

to 100 times the observed limit for the ‘ggF classifier’ and 30 times theobserved limit for the ‘VBF classifier’. The Z Z background is scaled bythe normalisation factors shown in Table 2. The lower panels show theratio of data to prediction. Only statistical and experimental systematicuncertainties are included

jets and t t backgrounds are determined by fitting the invari-ant mass of the leading lepton pair in dedicated data con-trol regions. The control regions are formed by relaxing theχ2 requirement on the four-lepton vertex fit, and by invert-ing and relaxing isolation and/or impact-parameter require-ments on the subleading muon pair. An additional controlregion (eμμμ) is used to improve the t t background estimate.The contribution of transfer factors, defined as the number ofevents in the signal region divided by the number of eventsin the control region, are obtained separately for t t and Z +jets using simulated events to extrapolate the yields from thecontrol regions to the signal regions.

The main non-prompt background for the ��+ ee processarises from three sources: light-flavour jets misidentified aselectrons; photon conversions; and semileptonic decays ofheavy-flavour hadrons. The �� + ee control-region selec-tion requires the electrons in the subleading lepton pair tohave the same charge, and relaxes the identification and isola-tion requirements on the electron candidate, denoted X , withthe lower transverse momentum. The heavy-flavour back-ground is found to be negligible, whereas the light-flavourand photon-conversion background is obtained with the sPlot[81] method, based on a fit to the number of hits in the inner-most ID layer in the data control region. Transfer factors forthe light-flavour jets and converted photons, obtained fromsimulated samples, are corrected using a Z+X control regionand then used to extrapolate the extracted yields to the sig-

nal region. Both the yield extraction and the extrapolationare performed in bins of the transverse momentum of theelectron candidate and the jet multiplicity.

The WZ production process is included in the data-drivenestimates for the �� + ee final states, while it is added fromsimulation for the �� + μμ final states even though its con-tribution to the total background is at the per-mille level. Thecontributions from t tV (where V stands for either a W or aZ boson) and triboson processes are minor and taken fromsimulated samples.

5.3 Signal and background modelling

The reconstructed four-lepton invariant mass m4� distribu-tion is used as the discriminating variable for the �+�−�′+�′−final state. It is extracted from simulation for signal eventsand for most background components (t tV , VVV , �� + μμ

and heavy-flavour hadron component of �� + ee), except forthe light-flavour jets and photon conversions in the case of��+ ee background, which are taken from the control regionas described in Sect. 5.2.

To obtain statistical interpretations for each mass hypoth-esis, the m4� distribution for signal is parameterised as afunction of the mass hypothesis mH . In the case of a narrowresonance, the width in m4� is determined by the detectorresolution, which is modelled by the sum of a Crystal Ball(C) function [82,83] and a Gaussian (G) function:

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Ps(m4�) = fC × C(m4�;μ, σC, αC, nC)

+(1 − fC) × G(m4�;μ, σG).

The Crystal Ball and Gaussian functions share the same peakvalue of m4� (μ), but have different resolution parameters,σC and σG . The αC and nC parameters control the shapeand position of the non-Gaussian tail, and the parameter fCensures the relative normalisation of the two probability den-sity functions. To improve the stability of the parameterisa-tion in the full mass range considered, the parameter nC isset to a fixed value. The bias in the extraction of signal yieldsintroduced by using the analytic function is below 2% andtreated as a systematic uncertainty of the signal parameter-isation. The function parameters are determined separatelyfor each final state using the simulated events for each gen-erated mass mH , and then fitted with a polynomial in mH tointerpolate between the generated mass points. The order ofthe polynomial is determined by first fitting with a third-orderpolynomial and then decreasing its order until the χ2 is threetimes larger than the number of degrees of freedom. The useof this parameterisation for the function parameters intro-duces a bias in the signal yield and mH extraction of about1%. The extra bias is included in the systematic uncertaintiesof the signal acceptance.

In the case of the LWA and the graviton model, a parton-level lineshape of m4� is derived from a theoretical calcula-tion and multiplied by the signal acceptance obtained fromthe simulated events; it is then convolved with the detectorresolution, using the same functions as those for modellingthe narrow resonance. The parton-level lineshape of m4� istaken from Ref. [84] for the LWA, and from Ref. [85] for thegraviton model.

For the Z Z continuum background, the m4� distributionis parameterised by an empirical function for both the quark-and gluon-initiated processes in order to reduce the statisticaluncertainties stemming from the limited number of simulatedevents. The empirical function is described by the following:

fqqZ Z/ggZ Z (m4�) = C0 × H(m0 − m4�) × f1(m4�)

+H(m4� − m0) × f2(m4�),

where,

f1(m4�) =(m4� − a4

a3

)a1−1(

1 + m4� − a4

a3

)−a1−a2,

f2(m4�) = exp[

b0

(m4� − b4

b3

)b1−1(

1 + m4� − b4

b3

)−b1−b2]

,

C0 = f2(m0)

f1(m0).

The function’s first part, f1, covers the low-mass part of thespectrum until the Z Z threshold around 2·mZ , and the secondpart, f2, describes the high-mass tail. The transition betweenlow- and high-mass parts is modelled with the Heaviside stepfunction H(x) around m0 = 260 GeV for qq → Z Z and

around 350 GeV for gg → Z Z . The continuity of the func-tion around m0 is ensured by the normalisation factor C0

that is applied to the low-mass part. Finally, ai and bi areshape parameters which are obtained by fitting the m4� dis-tribution in simulation for each category. A large number ofm4� distributions are calculated from the analytic functionwith variations of the ai and bi values sampled from a mul-tivariate Gaussian distribution that is constructed from theircovariance matrix. The uncertainty in the m4� distribution isdetermined by calculating a central interval that captures 68%of the variations, and is treated as a nuisance parameter inthe likelihood fit, namely a Z Z parameterisation uncertainty.The Z Z parameterisation uncertainty is one of the leadingsystematic uncertainties for a low-mass signal, as shown inTable 1.

Interference modelling

The gluon-initiated production of a heavy scalar H , the SMHiggs h and the gg → Z Z continuum background all sharethe same initial and final state, and thus lead to interfer-ence terms in the total amplitude. Theoretical calculationsdescribed in Ref. [86] have shown that the effect of inter-ference could modify the integrated cross section by up toO(10%), and this effect is enhanced as the width of the heavyscalar increases. Therefore, a search for a heavy scalar Higgsboson in the LWA case must properly account for two inter-ference effects: the interference between the heavy scalarand the SM Higgs boson (denoted by H–h) and betweenthe heavy scalar and the gg → Z Z continuum (denoted byH–B). However, because the width of the KK excitation res-onance is relatively small, the interference effect is assumedto be negligible in the graviton interpretation for both finalstates.

If the H and h bosons have similar properties, they havethe same production and decay amplitudes and therefore theonly difference between the signal and interference termsin the production cross section comes from the propagator.Hence, the acceptance and resolution of the signal and inter-ference terms are expected to be the same. The H–h interfer-ence is obtained by reweighting the particle-level lineshapeof generated signal events using the following formula:

w(m4�) =2 · Re

[1

s−sH· 1

(s−sh)∗]

1|s−sH |2

,

where 1/(

s − sH(h)

)

is the propagator for a scalar (H orh). The particle-level lineshape is then convolved with thedetector resolution function, and the signal and interferenceacceptances are assumed to be the same.

In order to extract the H–B interference contribution,signal-only and background-only samples are subtractedfrom the generated SBI samples. The extracted particle-level

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m4� distribution for the H–B interference term is then con-volved with the detector resolution.

6 Analysis of �+�−νν final state

6.1 Event selection and categorisation

The �+�−νν final state consists of a pair of high-pT isolatedleptons (electrons or muons) and large Emiss

T , and is subject tolarger background contamination than the �+�−�′+�′− chan-nel. Candidate events are recorded with a combination ofmultiple single-lepton triggers, which gives a high efficiencyof about 98% for typical signal processes in the signal regiondefined in the following.

Candidate events are preselected by requiring exactly twoelectrons or muons with opposite charges and pT > 20 GeV,where the electrons (muons) must have |η| < 2.47 (2.5). Theleading lepton is further required to have pT > 30 GeV,well above the threshold of the single-lepton triggers. Theselected electrons or muons must have a longitudinal impactparameter satisfying |z0 sin(θ)| < 0.5 mm. The lepton candi-dates are required to satisfy the same isolation criteria and thesame requirement on the transverse impact-parameter signif-icance as used in the �+�−�′+�′− channel (see Sect. 5.1.1),which leads to an efficiency above 98% for typical promptleptons with pT > 30 GeV. To suppress theWZ background,events containing any additional lepton satisfying the ‘loose’identification requirement with pT > 7 GeV, in additionto the other requirements, are rejected. Requiring the dilep-ton invariant mass (m��) to be in the range between 76 and106 GeV largely reduces the contamination from the non-resonant-�� background, originating from t t , Wt , WW , andZ → ττ production. The data sample after the preselectionis dominated by the Z + jets and non-resonant-�� processes.To suppress these backgrounds, a further selection based onEmiss

T and event topology is applied.Candidate events are required to have Emiss

T > 120 GeV,which suppresses the Z + jets contamination by severalorders of magnitude. The number of residual Z + jets events,which have large fake Emiss

T , is further reduced by requir-ing S(Emiss

T ) > 10, where S(EmissT ) is the statistical sig-

nificance of the EmissT value against the null hypothesis

of zero-EmissT [87]. Additional selection criteria based on

angular variables are imposed to further reject the Z +jets and non-resonant-�� background events. The selectionon angular variables is motivated by the desired detectorsignature, where the �Emiss

T is back-to-back with the trans-verse momentum of the dilepton system. The azimuthalangle difference between the dilepton system and �Emiss

T ,φ( �p��

T , �EmissT ), must be larger than 2.5 radians, and the

selected leptons must be close to each other, with the dis-

tance R�� = √

(φ��)2 + (η��)2 < 1.8. Furthermore, theazimuthal angle difference between any of the selected jetswith pT > 100 GeV and �Emiss

T must be larger than 0.4 radi-ans. As a consequence of all the requirements, the Z + jetsprocess only constitutes a small fraction of the total back-ground (about 4%) after the full selection. Finally, eventscontaining one or more b-jets are vetoed to further suppressthe t t and Wt backgrounds.

The signal region for the VBF production mode (VBF-enriched signal region) is defined for candidate events con-taining at least two selected jets with pT > 30 GeV, where thetwo leading jets must have mjj > 550 GeV and ηjj > 4.4.The remaining events, failing the requirements for the VBF-enriched signal region, are categorised for the ggF-enrichedsignal region. The signal acceptance in the ggF-enriched sig-nal region for signal events containing a heavy spin-0 reso-nance from ggF production is about 30% at mH = 400 GeVand up to 50% at mH = 1.4 TeV. For VBF signal eventsthe signal acceptance in the VBF-enriched signal region isgenerally lower, ranging from 3% at mH = 400 GeV to 20%at mH = 1.6 TeV.

6.2 Background estimation

In the ggF-enriched signal region, the major backgroundsoriginate from the Z Z and WZ processes, which account for60% and 30% of the total background contribution, respec-tively. The non-resonant-�� background yields a relative con-tribution of about 5% to the total background, while thelargely suppressed Z + jets background only constitutesa small fraction (4%). Finally, the remaining contributionsfrom other processes (VVV and t tV ), amount in total toless than 1% of the total background. A similar compositionof background processes is found in the VBF-enriched sig-nal region, where the total background yield is expected to besmaller than 1% of that in the ggF-enriched signal region, dueto the event selection for the VBF phase space. The variousbackground estimates and their uncertainties are describedbelow.

The main background contribution from Z Z productionis estimated using a semi-data-driven method. Similarly tothe �+�−�′+�′− analysis, the predicted Z Z yield is scaled bya floating normalisation factor, which is determined in thestatistical fit to the signal-region data (see Sect. 8.1). Theintroduction of the data-driven normalisation factor helpsconstrain the total uncertainty in the Z Z yield, while thetheoretical and experimental uncertainties in the transversemass distribution are evaluated from simulation.

To estimate the background from WZ production in theggF-enriched signal region, a control region enriched in WZevents, with a purity of over 90%, is defined using the prese-lection criteria, except that a third lepton with pT > 20 GeVis required. Several further selections such as S(Emiss

T ) > 3,

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a b-jets veto, and mWT > 60 GeV, where mW

T is constructedfrom the third lepton’s transverse momentum and the �Emiss

Tvector,2 are applied to suppress non-WZ contributions. Anormalisation factor is calculated in the control region asthe number of observed events in data, after subtracting thenon-WZ contributions estimated from simulation, dividedby the predicted WZ yield. The factor is found to be 1.05with a total uncertainty of 5%, which is consistent with arecent WZ measurement [88] performed within a broaderfiducial phase space. The statistical uncertainty of the datain the control region leads to a 0.8% uncertainty in the WZestimate in the signal region. The main systematic uncer-tainty is evaluated for the ratio of the WZ predictions inthe signal and control regions, and covers the experimentaluncertainties and the theoretical ones related to the PDFs andthe QCD scales. The uncertainty related to the subtraction ofthe non-WZ contribution in the control region is estimatedby applying cross-section uncertainties for all the relevantprocesses and is found to be negligible. An additional uncer-tainty is assigned to the WZ prediction in the signal region,to account for the efficiency mismodelling of vetoing a thirdlepton in WZ → ��ν events. The total uncertainty in theWZ estimate for the ggF-enriched signal region is about 5%.A similar method is adopted to estimate the WZ contributionin the VBF-enriched signal region, except that the controlregion additionally selects two jets with pT > 30 GeV. Thenormalisation factor is found to be 0.83 with an uncertaintyof 0.27, which is compatible with the results presented inRef. [89]. The total uncertainty in the WZ estimate for theVBF-enriched signal region is about 30%. The kinematicdistributions are estimated from simulation.

To estimate the non-resonant-�� background, a controlregion dominated by the non-resonant-�� processes (witha purity of about 95%) is defined with all the event selec-tion criteria except that the final state is required to con-tain an opposite-sign eμ pair. The non-resonant-�� contribu-tion in the ee (μμ) channel is calculated as one half of theobserved data yield after subtracting the contribution fromthe other background processes in the control region, andthen corrected for the difference in the lepton reconstruc-tion and identification efficiencies between selecting an eμpair and an ee (μμ) pair. The lepton efficiency correctionis derived as the square root of the ratio of the numbers ofμμ and ee events in data after the preselection. The choiceof deriving the correction after preselection minimises theresulting statistical uncertainty. The total uncertainty in thenon-resonant-�� estimate in the ggF-enriched signal regionis about 9%, including the statistical uncertainty of the data inthe control region and the method bias estimated from simu-lation. The estimation of the non-resonant-�� background in

2 mWT =

√

2p�TE

missT [1 − cos φ( �p�

T, �EmissT )].

the VBF-enriched signal region relies on a similar method-ology, except that the control region is defined with a jetselection that is looser than in the signal region. The non-resonant-�� estimate obtained with the looser selection isthen scaled by a simulation-based transfer factor to derive thefinal estimate in the VBF-enriched signal region. The transferfactor is subject to experimental and theoretical uncertainties,and the relative uncertainty in the final estimate in the VBF-enriched signal region is 70%. The kinematic distributionsfor the non-resonant-�� background in the signal region arepredicted with simulation, and the assigned systematic uncer-tainty covers the experimental uncertainty in the simulatedshape as well as the difference between data and simulationin the control region.

The Z + jets background contribution is estimated fromsimulation and scaled by a normalisation factor derived ina control region enriched in Z + jets events. The controlregion is defined with all event selection criteria except thatS(Emiss

T ) must be less than 9 and no requirements on theazimuthal angle difference between jets with pT > 100 GeVand �Emiss

T are made. The normalisation factor is found tobe close to one. Apart from the statistical uncertainty in thecontrol sample, the experimental and theoretical uncertain-ties are evaluated for the ratio of the number of simulatedevents in the signal region to that in the control region. Thetotal uncertainty in the Z + jets estimate is about 40%. Thekinematic distributions for the Z + jets background are mod-elled with simulation. Finally, backgrounds from the VVVand t tV processes, which contribute less than 1% of the totalbackground, are estimated from simulation.

6.3 Signal and background modelling

The modelling of the transverse mass mT distribution forsignal and background is based on templates derived fromfully simulated events and afterwards used to fit the data. Inthe case of a narrow resonance, simulated events generatedfor fixed mass hypotheses as described in Sect. 3 are used asthe inputs in the moment-morphing technique [90] to obtainthe mT distribution for any other mass hypothesis.

The extraction of the interference terms for the LWA caseis performed in the same way as in the �+�−�′+�′− final state,as described in Sect. 5.3. In the case of the �+�−νν final statea correction factor, extracted as a function of mZZ , is usedto reweight the interference distributions obtained at particlelevel to account for reconstruction effects. The final expectedLWAmT distribution is obtained from the combination of theinterference distributions with simulated mT distributions,which are interpolated between the simulated mass pointswith a weighting technique using the Higgs propagator, amethod similar to that used for the interference.

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7 Systematic uncertainties

The systematic uncertainties can be categorised into exper-imental and theoretical uncertainties. The first categoryincludes the uncertainties resulting from the integrated lumi-nosity, the trigger efficiencies, the momentum scale and res-olution of tracks, the reconstruction and identification of lep-tons and jets, and their energy scale and resolution calibra-tions. Systematic uncertainties associated with data-drivenmethods are also in this category, but described in their cor-responding sections: Sect. 5.2 for �+�−�′+�′− final state andSect. 6.2 for �+�−νν final state. The second category includesthe uncertainties in the theoretical descriptions of the signaland background simulations.

These systematic uncertainties evaluated separately forsignal and background in each category affect signal accep-tances and background yields as well as the probabilitydensity distributions of the discriminating variables. Theyare provided as the inputs for the statistical interpretationsdescribed in Sect. 9, in which the impact of these uncertain-ties on the expected signal yields are also presented.

7.1 Experimental uncertainties

The uncertainty in the combined 2015–2018 integrated lumi-nosity is 1.7% [91], obtained using the LUCID-2 detector[92] for the primary luminosity measurements.

The lepton identification and reconstruction efficiency andenergy/momentum scale and resolution are derived from datausing J/ψ → �� and Z → �� decay events. The uncertain-ties in the reconstruction performance are computed follow-ing the method described in Ref. [64] for muons and Ref.[63] for electrons. In general, their impact on the signal andbackground yields is less than 1% in the �+�−νν final state,and up to 1.5% in the �+�−�′+�′− final state. In addition, thelepton isolation uncertainty is estimated to be less than 1%in both final states.

The uncertainties in the jet energy scale and resolutionhave several sources, including uncertainties in the absoluteand relative in situ calibration, the correction for pile-up, theflavour composition and response [93]. Each source is treatedas an independent component. They vary from 4.5% for jetswith transverse momentum pT = 20 GeV, decreasing to 1%for jets with pT = 100–1500 GeV and increasing again to 3%for jets with higher pT. They are the dominant uncertaintiesin the VBF-enriched categories for ggF signal productionand SM Z Z production in both final states.

Uncertainties in the lepton and jet energy scales are prop-agated to the uncertainty in the Emiss

T [94]. Additionally, theuncertainties from the momentum scale and resolution of thetracks that are not associated with any identified lepton or jetcontribute 8% and 3%, respectively, to the uncertainty in theEmiss

T value.

The efficiency of the lepton triggers in events with recon-structed leptons is nearly 100%, and hence the related uncer-tainties are negligible. The uncertainties associated with thepile-up reweighting are also taken into account; their impacton the signal and background yields is about 1% for bothfinal states.

These experimental uncertainties are common to the twofinal states; therefore, they are fully correlated between thetwo final states.

7.2 Theoretical uncertainties

For the simulation-based estimates, the theoretical uncer-tainties stemming from parton distribution functions (PDFs),missing higher-order QCD corrections, and parton shower-ing are considered.

The PDF uncertainty is evaluated by taking the envelope ofvariations among alternative PDF choices and the estimatefrom its internal PDF error sets, following the PDF4LHCrecommendation [95]. The missing higher-order QCD cor-rections are estimated by halving or doubling the factorisa-tion and renormalisation scales independently, among whichthe largest effect is taken as the systematic uncertainty.The parton-showering uncertainty is assessed by varying thePythia configurations, such as the parameter values of theAZNLO tune, the multi-parton models and the final-stateradiation models.

For different signal hypotheses, the impact of these the-oretical uncertainties on the signal acceptance and the spec-trum of the discriminating variables is evaluated. In total, thetheoretical uncertainty in the signal acceptance varies fromless than 1% in the low mass region to 12% in the high massregion of the �+�−νν final state, and from less than 1% inthe low mass region to up to 20% in the high mass region ofthe �+�−�′+�′− final state.

For the continuum Z Z background, a common floatingnormalisation factor is introduced to scale the number ofevents for the qq → Z Z and gg → Z Z processes, whilethe relative yields of the two processes are estimated fromthe simulations. Therefore, in addition to the spectrum of thediscriminating variables in the Z Z background, the theoreti-cal uncertainties are also propagated to the simulation-basedestimation of the relative yields. Moreover, the uncertaintyassociated with the NLO EW corrections, calculated in Refs.[45,46,48], are also taken into account, affecting the discrim-inating variables by less than 1% in the low mass region andup to 10% in the high mass region for both final states.

Because the �+�−�′+�′− and �+�−νν searches are sensi-tive to different energy scales, these theoretical uncertaintiesare assumed to be completely uncorrelated between the twoanalyses. A fully correlated scenario is also examined andthe differences between the two scenarios in terms of theexpected limits on various signal hypotheses are negligible.

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8 Results

The statistical procedure used to extract the results isdescribed in Sect. 8.1 and the results are presented inSect. 8.2.

8.1 Statistical procedure and impact of systematicuncertainties

The statistical treatment of the data interpretation follows theprocedure for the Higgs-boson search combination in 7 TeVdata [96,97]. The test statistic used for limit setting is the pro-file likelihood ratio �(α, θ), which depends on one or moreparameters of interest α, additional normalisation factors andextra nuisance parameters θ . The parameter of interest is thecross section times branching ratio of the heavy resonancedecaying into the two final states. The normalisation factors,which were not used in the previous publication [18], areintroduced separately for each final state to scale the expectednumber of the SM Z Z background events in each cate-gory and are determined by a likelihood fit to the data. Thisallows the systematic uncertainty to be reduced by removingboth the theoretical and luminosity uncertainties contribut-ing to the normalisation uncertainty. In the �+�−�′+�′− finalstate, three floating normalisation factors are introduced forthe VBF-enriched, ggF-MVA-high and ggF-MVA-low cate-gories. They are referred to as μVBF-MVA

Z Z , μggF-MVA-highZ Z and

μggF-MVA-lowZ Z , respectively. The use of three Z Z normalisa-

tion factors for the �+�−�′+�′− final state is motivated bythe different phase spaces defined for the respective signalregions. Only one floating normalisation factor μZ Z is intro-duced in the �+�−νν final state, due to the limited size of thedata sample and the worse signal-to-background ratio in therespective VBF-enriched signal region.

The nuisance parameters represent the estimates of thesystematic uncertainties and each of them is constrained bya Gaussian distribution. For each category of each final state,a discriminating variable is used to further separate signalfrom background. The number of signal events is extractedfrom a simultaneous fit to the discriminating variable, m4� inthe �+�−�′+�′− analysis and mT in the �+�−νν analysis, inthe event categories described in Sects. 5 and 6.

The impact of a systematic uncertainty on the resultdepends on the production mode and the mass hypothesis.For the ggF production mode, at lower masses the Z Z param-eterisation for the �+�−�′+�′− final state and the systematicuncertainty of the Z + jets background for the �+�−νν finalstate dominate, and at higher masses the uncertainties in theNLO EW correction and parton showering become impor-tant, as also seen in VBF production. For the VBF productionmode, the dominant uncertainties come from the theoreticalmodelling of the discriminating variables of the Z Z events in

the VBF category. At lower masses, jet-energy-scale uncer-tainties are also important. Table 1 shows the impact of theleading systematic uncertainties on the predicted signal eventyield when the cross section times branching ratio is set to theexpected upper limit (shown in Fig. 4), for ggF and VBF pro-duction modes. The statistical uncertainty of the data sampledominates in both of the present searches, and the systematicuncertainties impact the searches to a much lesser extent.

8.2 General results

The total number of observed events is 3275 in the�+�−�′+�′−final state (m4� > 200 GeV) and 2794 in the �+�−νν finalstate. The expected background yields are obtained from asimultaneous likelihood fit of the two final states under thebackground-only hypothesis. The fitted normalisation factorsfor the SM Z Z background are summarised in Table 2.

The number of observed candidate events with mass above200 GeV together with the expected background yields foreach of the five categories of the �+�−�′+�′− analysis asdescribed in Sect. 5.1.2 are presented in Table 3. The m4�

spectrum in each category is shown in Fig. 2 for illustra-tion, since the backgrounds are determined from a combinedunbinned likelihood fit to the data under the background-onlyhypothesis. Table 4 contains the number of observed eventsalong with the obtained background yields for the �+�−νν

analysis and Fig. 3 shows the mT distribution for the electronand muon channels in the ggF-enriched and VBF-enrichedcategories.

The two previous excesses around 240 GeV and 700 GeVthat were observed in the publication [18] using 2015 and2016 data are not confirmed using the full Run 2 dataset asexplained below. The maximum deviation of the data fromthe background-only hypothesis is evaluated in the contextof a NWA signal from the ggF production or from the VBFproduction separately. For the ggF production, the maximumdeviation is for a signal mass hypothesis around 240 GeV,with a local significance of 2.0 standard deviations and aglobal significance of 0.5 standard deviation. For the VBFproduction, the maximum deviation is for a signal masshypothesis around 620 GeV, with a local significance of 2.4standard deviations and a global significance of 0.9 standarddeviation.

9 Interpretations

Since no significant excess with respect to the backgroundpredictions is found, results obtained from the combinationof the �+�−�′+�′− and �+�−νν final states are interpreted interms of exclusion limits for different signal hypotheses aspresented below.

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Table 1 Impact of the leading systematic uncertainties, the data sta-tistical uncertainties and the total uncertainties on the predicted signalevent yield with the cross section times branching ratio being set to the

expected upper limit, expressed as a percentage of the signal yield forthe ggF (left) and VBF (right) production modes at mH = 300, 600,1000, and 1500 GeV

ggF production VBF production

Systematic source Impact [%] Systematic source Impact (%)

mH = 300 GeV

Z Z parameterisation (�+�−�′+�′−) 4.5 Jet flavor composition 3.0

Z + jets modelling (�+�−νν) 2.3 qq → Z Z QCD scale (VBF-enriched category, �+�−�′+�′−) 2.8

Parton showering of ggF (�+�−�′+�′−) 2.2 Z Z parameterisation (�+�−�′+�′−) 2.3

eμ statistical uncertainty �+�−νν 2.0 Jet energy scale(in-su calibration) 1.8

Data stat. uncertainty 53 Data stat. uncertainty 58

Total uncertainty 55 Total uncertainty 60

mH = 600 GeV

Electroweak corrections for qq → Z Z (�+�−νν) 4.9 QCD scale of qq → Z Z (�+�−νν) 7.6

QCD scale of qq → Z Z (�+�−νν) 2.5 Jet energy resolution 5.4

Z + jets modelling (�+�−νν) 2.5 Parton showering (�+�−νν) 3.3

PDF of qq → Z Z (�+�−�′+�′−) 2.2 Electroweak corrections for qq → Z Z (�+�−νν) 3.0



mH = 1000 GeV

Electroweak corrections for qq → Z Z (�+�−νν) 9.3 Parton showering (�+�−νν) 6.8

Parton showering (�+�−νν) 5.2 Electroweak corrections for qq → Z Z (�+�−νν) 4.7

QCD scale of qq → Z Z (�+�−νν) 4.8 QCD scale of qq → Z Z (�+�−νν) 2.4

Z + jets modelling (�+�−νν) 2.4 Jet flavor composition 2.4



mH = 1500 GeV

Parton showering (�+�−νν) 9.6 Parton showering (�+�−νν) 9.0

Electroweak corrections for qq → Z Z (�+�−νν) 6.8 Electroweak corrections for qq → Z Z (�+�−νν) 4.6

PDF of qq → Z Z (�+�−νν) 5.4 PDF of qq → Z Z (�+�−νν) 3.4

QCD scale of qq → Z Z (�+�−νν) 4.6 QCD scale of qq → Z Z (�+�−νν) 2.8



Table 2 The Z Z normalisation factors together with their total (statis-tical+systematic) uncertainties in each category of the two final states,which scale the number of Z Z events estimated from the simulations,obtained from a simultaneous likelihood fit of the two final states underthe background-only hypothesis. For the �+�−�′+�′− final state, theMVA-based categorisation is used

Final state Normalisation factor Fitted value

�+�−�′+�′− μVBF-MVAZ Z 0.9 ± 0.3

μggF-MVA-highZ Z 1.07 ± 0.05

μggF-MVA-lowZ Z 1.12 ± 0.03

�+�−νν μZ Z 1.04 ± 0.06

9.1 Spin-0 resonances

9.1.1 Spin-0 resonances with NWA

Upper limits on the cross section times branching ratio(σ × B(H → Z Z)) for a heavy resonance are obtained fromthe combination of the two final states, as a function of mH

with the CLs procedure [98] in the asymptotic approxima-tion. The results were verified to be correct within about 4%using pseudo-experiments. It is assumed that an additionalheavy scalar would be produced mainly via the ggF and VBFprocesses but that the ratio of the two production mechanismsmight depend on the model considered. For this reason, fitsfor the ggF and VBF processes are done separately, and ineach case the other process is allowed to float in the fit asan additional free parameter. Figure 4 presents the observed

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Table 3 Expected and observed numbers of events in the �+�−�′+�′−final state for m4� > 200 GeV, together with their uncertainties,for the VBF-MVA-enriched, ggF-MVA-high and ggF-MVA-low cat-egories. The expected numbers of events, as well as their uncertain-

ties, are obtained from a combined likelihood fit to the data under thebackground-only hypothesis. The uncertainties of the Z Z normalisationfactors, presented in Table 2, are also taken into account

Process VBF-enriched ggF-MVA-high ggF-MVA-low4μ channel 2e2μ channel 4e channel

qq → Z Z 11 ± 4 232 ± 10 389 ± 17 154 ± 7 2008 ± 47

gg → Z Z 3 ± 2 37 ± 6 64 ± 10 26 ± 4 247 ± 19

Z Z (EW) 4.1 ± 0.4 4.5 ± 0.2 7.5 ± 0.4 3 ± 0.2 14.3 ± 0.7

Z + jets, t t 0.08 ± 0.02 0.6 ± 0.1 1.7 ± 0.4 0.8 ± 0.1 8.8 ±2.1

t tV , VVV 0.96 ± 0.1 9.8 ± 0.2 17.5 ± 0.4 7.7 ± 0.2 21.9 ± 0.5

Total background 19 ± 5 284 ± 12 480 ± 20 192 ± 8 2300 ± 51

Observed 19 271 493 191 2301

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Fig. 2 Distributions of the four-lepton invariant mass m4� in the�+�−�′+�′− search for the ggF-MVA-high categories (μ+μ−μ+μ−(a), e+e−μ+μ− (b), and e+e−e+e− (c) final states), for the ggF-MVA-low category (d), and for the VBF-MVA-enriched category (e). Thebackgrounds are determined from a combined likelihood fit to the dataunder the background-only hypothesis. The simulated mH = 600 GeVsignal is normalised to a cross section corresponding to 50 (5) times

the observed limit given in Sect. 9.1.1 for the ggF (VBF) productionmode. The error bars on the data points indicate the statistical uncer-tainty, while the systematic uncertainty in the prediction is shown bythe hatched band. The lower panels show the ratio of data to prediction.The red arrows indicate data points that are outside the displayed range

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Table 4 Expected and observed numbers of events together with theiruncertainties in the �+�−νν final state, for the ggF- and VBF-enrichedcategories. The expected numbers of events, as well as their uncertain-

ties, are obtained from a likelihood fit to the data under the background-only hypothesis. The uncertainties of the Z Z normalisation factors,presented in Table 2, are also taken into account

Process ggF-enriched VBF-enrichede+e− channel μ+μ− channel e+e− channel μ+μ− channel

qq → Z Z 695 ± 39 795 ± 44 2.8 ± 0.2 3.3 ± 0.2

gg → Z Z 87 ± 28 97 ± 31 1 ± 0.4 1 ± 0.4

Z Z (EW) 6.6 ± 0.5 7 ± 0.5 0.8 ± 0.1 0.9 ± 0.1

WZ 400 ± 13 443 ± 12 2.4 ± 0.5 3 ± 1.3

Z + jets 39 ± 12 56 ± 21 0.2 ± 0.2 0.3 ± 0.3

Non-resonant-�� 66 ± 6 77 ± 7 0.2 ± 0.2 0.3 ± 0.2

t tV , VVV 5.9 ± 0.4 5.9 ± 0.4 0.08 ± 0.02 0.04 ± 0.01

Total backgrounds 1299 ± 52 1480 ± 59 7.4 ± 0.7 8.4 ± 1.4

Observed 1280 1498 7 9

and expected limits at 95% CL on the σ × B(H → Z Z)

of a narrow scalar resonance for the ggF (left) and VBF(right) production modes, as well as the expected limits fromthe �+�−�′+�′− and �+�−νν searches. This result is validfor models in which the width is less than 0.5% of mH .When combining the two final states, the 95% CL upperlimits range from 215 fb at mH = 240 GeV to 2.0 fb atmH = 1900 GeV for the ggF production mode and from87 fb at mH = 255 GeV to 1.5 fb at mH = 1800 GeV for theVBF production mode. Compared with the expected limitsprojected to the luminosity of 139 fb−1 from the previouspublication [18], the current expected limits are decreasedby a factor ranging from 20 to 28% for the ggF productionmode and from 27 to 43% for the VBF production mode,depending on the mass hypothesis.

9.1.2 Spin-0 resonances with LWA

In the case of the LWA, upper limits on the cross section forthe ggF process times branching ratio (σggF × B(H → Z Z))are set for different widths of the heavy scalar. Figure 5shows the limits for a width of 1%, 5%, 10% and 15% ofmH respectively. The limits are set for masses of mH higherthan 400 GeV. The choice of 400 GeV as the lower boundaryis to avoid any major instability in the parametrization of themass spectra for the LWA signals and the interference effects,especially when the signal pole mass gets smaller. The inter-pretation has only been carried out for the ggF process, asit is the leading channel to study the impact of non-trivialwidth on the search.

9.1.3 Two-Higgs-doublet model

A search in the context of a CP-conserving 2HDM is alsopresented. This model has five physical Higgs bosons afterelectroweak symmetry breaking: two CP-even, one CP-odd,and two charged. The model considered here has seven free

parameters: the Higgs boson masses, the ratio of the vac-uum expectation values of the two Higgs doublets (tan β),the mixing angle between the CP-even Higgs bosons (α),and the potential parameter m2

12 that mixes the two Higgsdoublets. The two Higgs doublets �1 and �2 can couple toleptons and up- and down-type quarks in several ways. In theType-I model, �2 couples to all quarks and leptons, whereasfor Type-II, �1 couples to down-type quarks and leptons and�2 couples to up-type quarks. The ‘lepton-specific’ model issimilar to Type-I except for the fact that the leptons coupleto �1, instead of �2; the ‘flipped’ model is similar to Type-II except that the leptons couple to �2, instead of �1. Inall these models, the coupling of the heavier CP-even Higgsboson to vector bosons is proportional to cos(β − α). Inthe limit cos(β − α) → 0, the light CP-even Higgs bosonis indistinguishable from a SM Higgs boson with the samemass. In the context of H → Z Z decays there is no directcoupling of the Higgs boson to leptons, so only the Type-Iand II interpretations are presented. In addition, our interpre-tations assume other Higgs bosons are heavy enough so thatthe heavy CP-even Higgs boson will not decay to them.

Figure 6 shows exclusion limits in the tan β versus cos(β−α) plane for Type-I and Type-II 2HDMs, for a heavy Higgsboson with mass mH = 220 GeV. This mH value is chosenso that the assumption of a narrow Higgs boson is valid overmost of the parameter space, and the experimental sensitiv-ity is maximal. At this low mass, only the �+�−�′+�′− finalstate contributes to this result. The range of cos(β − α) andtan β explored is limited to the region where the assumptionof a heavy narrow Higgs boson with negligible interferenceis valid. When calculating the limits at a given choice ofcos(β − α) and tan β, the relative rates of ggF and VBFproduction in the fit are set to the prediction of the 2HDMfor that parameter choice. Figure 7 shows exclusion limitsas a function of the heavy Higgs boson mass mH and theparameter tan β for cos(β − α) = −0.1, which is chosen sothat the light Higgs boson properties are still compatible with

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Fig. 3 The mT distribution in the �+�−νν search for a, b the ggF cat-egories and c, d the VBF categories. Events beyond the upper limit ofthe histogram are included in the last bin of the distribution. The back-grounds are determined from a combined likelihood fit to data under thebackground-only hypothesis. The simulated mH = 600 GeV (1.5 TeV)signals are normalised to a cross section corresponding to 50 (5) timesthe observed limit given in Sect. 9.1.1 for the ggF production mode and

to 5 (1) times the observed limit for the VBF production mode. The errorbars on the data points indicate the statistical uncertainty and markersare drawn at the bin centre. The systematic uncertainty in the predictionis shown by the hatched band. The lower panels show the ratio of datato prediction. The red arrows indicate data points that are outside thedisplayed range

the recent measurements of the SM Higgs boson properties[99]. The white regions in the exclusion plots indicate regionsof parameter space which are not excluded by the presentanalysis. In these regions the cross section predicted by the2HDM is below the observed cross-section limit. In compar-ison with the previous publication, the excluded regions aresignificantly expanded. For example, in the tan β versus mH

plane for the Type-II 2HDM the excluded region in tan β ismore than 60% larger for 200 < mH < 400 GeV.

9.2 Spin-2 resonances

The results are also interpreted as a search for a Kaluza–Klein graviton excitation, GKK, in the context of the bulk RSmodel with k/MPl = 1. The limits on σ ×B(GKK → Z Z) at95% CL as a function of the KK graviton mass, m(GKK), areshown in Fig. 8 together with the predicted GKK cross sec-tion. A spin-2 graviton is excluded up to a mass of 1830 GeV.

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Fig. 6 The exclusion contour in the 2HDM a type-I and b type-II models for mH = 220 GeV shown as a function of the parameters cos(β − α)

and tan β. The green and yellow bands represent the ±1σ and ±2σ uncertainties in the expected limits. The hatched area shows the observedexclusion

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10 Summary

A search is conducted for heavy resonances decaying into apair of Z bosons which subsequently decay into �+�−�′+�′−or �+�−νν final states. The search uses proton–proton col-lision data collected with the ATLAS detector from 2015

to 2018 at the Large Hadron Collider at a centre-of-massenergy of 13 TeV corresponding to the full Run 2 integratedluminosity of 139 fb−1. No significant excess is observedwith respect to the predicted SM background; therefore, theresults are interpreted as upper limits on the production crosssection of spin-0 resonances or a spin-2 resonance. The mass

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600 800 1000 1200 1400 1600 1800 2000) [GeV]

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10) [pb

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Z→

KK

G(B

×gg

Fσ

95%

CL

limits

on



) ZZ→KKG(B×σ


νν-l+ + l-l'+l'-l+ l→ ZZ →KKG = 1PlMk/

Fig. 8 The upper limits at 95% CL on cross section times branchingratio σ × B(GKK → Z Z) for a KK graviton produced with k/MPl =1. The black line indicates the observed limit. The green and yellowbands give the ±1σ and ±2σ uncertainties in the expected limits. Thepredicted production cross section times branching ratio as a functionof the GKK mass m(GKK) is shown by the red solid line

range of the hypothetical resonances considered is between200 GeV and 2000 GeV depending on the final state and themodel considered. The spin-0 resonance is assumed to be aheavy scalar, whose dominant production modes are gluon–gluon fusion and vector-boson fusion, and it is studied inthe narrow-width approximation and with the large-widthassumption. In the case of the narrow-width approximation,upper limits on the production rate of a heavy scalar decayinginto two Z bosons (the production cross-section times thecorresponding decay branching fraction) are set separatelyfor ggF and VBF production modes. Combining the twofinal states, 95% CL upper limits range from 215 fb at mH =240 GeV to 2.0 fb at mH = 1900 GeV for the gluon–gluonfusion production mode and from 87 fb at mH = 255 GeVto 1.5 fb at mH = 1800 GeV for the vector-boson fusion

production mode. The results are also interpreted in the con-text of Type-I and Type-II two-Higgs-doublet models, withexclusion contours given in the tan β versus cos(β − α) (formH = 220 GeV) and tan β versusmH planes. ThismH valueis chosen so that the assumption of a narrow Higgs boson isvalid over most of the parameter space and the experimen-tal sensitivity is maximal. The limits on the production rateof a large-width scalar are obtained for widths of 1%, 5%,10% and 15% of the mass of the resonance, with the inter-ference between the heavy scalar and the SM Higgs bosonas well as between the heavy scalar and the gg → Z Z con-tinuum taken into account. In the framework of the Randall–Sundrum model with one warped extra dimension a gravitonexcitation spin-2 resonance with m(GKK) < 1830 GeV isexcluded at 95% CL.

Acknowledgements We thank CERN for the very successful oper-ation of the LHC, as well as the support staff from our institutionswithout whom ATLAS could not be operated efficiently. We acknowl-edge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC,Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC,Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada;CERN; ANID, Chile; CAS, MOST and NSFC, China; COLCIEN-CIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic;DNRF and DNSRC, Denmark; IN2P3-CNRS and CEA-DRF/IRFU,France; SRNSFG, Georgia; BMBF, HGF and MPG, Germany; GSRT,Greece; RGC and Hong Kong SAR, China; ISF and Benoziyo Center,Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO,Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal;MNE/IFA, Romania; JINR; MES of Russia and NRC KI, Russian Fed-eration; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia;DST/NRF, South Africa; MICINN, Spain; SRC and Wallenberg Foun-dation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzer-land; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom; DOEand NSF, United States of America. In addition, individual groups andmembers have received support from BCKDF, CANARIE, ComputeCanada, CRC and IVADO, Canada; Beijing Municipal Science & Tech-nology Commission, China; COST, ERC, ERDF, Horizon 2020 andMarie Skłodowska-Curie Actions, European Union; Investissementsd’Avenir Labex, Investissements d’Avenir Idex and ANR, France; DFGand AvH Foundation, Germany; Herakleitos, Thales and Aristeia pro-grammes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and GIF, Israel; La Caixa Banking Foundation, CERCA Pro-gramme Generalitat de Catalunya and PROMETEO and GenT Pro-grammes Generalitat Valenciana, Spain; Göran Gustafssons Stiftelse,Sweden; The Royal Society and Leverhulme Trust, United Kingdom.The crucial computing support from all WLCG partners is acknowl-edged gratefully, in particular from CERN, the ATLAS Tier-1 facili-ties at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (UK) and BNL(USA), the Tier-2 facilities worldwide and large non-WLCG resourceproviders. Major contributors of computing resources are listed in Ref.[100].

Data Availability Statement This manuscript has no associated dataor the data will not be deposited. [Authors’ comment:All ATLAS sci-entific output is published in journals, and preliminary results are madeavailable in Conference Notes. All are openly available, without restric-tion on use by external parties beyond copyright law and the standardconditions agreed by CERN. Data associated with journal publicationsare also made available: tables and data from plots (e.g. cross sectionvalues, likelihood profiles, selection efficiencies, cross section limits,. . .) are stored in appropriate repositories such as HEPDATA (http://hepdata.cedar.ac.uk/). ATLAS also strives to make additional materialrelated to the paper available that allows a reinterpretation of the datain the context of new theoretical models. For example, an extendedencapsulation of the analysis is often provided for measurements in theframework of RIVET (http://rivet.hepforge.org/).” This information istaken from the ATLAS Data Access Policy, which is a public docu-ment that can be downloaded from http://opendata.cern.ch/record/413[opendata.cern.ch].]

Open Access This article is licensed under a Creative Commons Attri-bution 4.0 International License, which permits use, sharing, adaptation,distribution and reproduction in any medium or format, as long as yougive appropriate credit to the original author(s) and the source, pro-vide a link to the Creative Commons licence, and indicate if changeswere made. The images or other third party material in this articleare included in the article’s Creative Commons licence, unless indi-cated otherwise in a credit line to the material. If material is notincluded in the article’s Creative Commons licence and your intended

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use is not permitted by statutory regulation or exceeds the permit-ted use, you will need to obtain permission directly from the copy-right holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.Funded by SCOAP3.

Appendix

The results based on the cut-based categorisation as describedin Sect. 5.1.3 are presented here. The number of observedcandidate events with mass above 200 GeV together with theexpected background yields for each of the four categoriesof the �+�−�′+�′− analysis as described in Sect. 5.1.3 ispresented in Table 5. The obtained Z Z normalisation factors

Table 5 �+�−�′+�′− search: expected and observed numbers of eventsfor m4� > 200 GeV, together with their uncertainties, for the VBF-CBA-enriched and ggF-CBA-enriched categories using the cut-basedcategorisation. The expected numbers of events, as well as their uncer-tainties, are obtained from a combined likelihood fit to the data underthe background-only hypothesis. The uncertainties of the Z Z normali-sation factors, presented in Table 6, are also taken into account

Process VBF-CBA-enriched

ggF-CBA-enriched

4μ channel 2e2μ channel 4e channel

qq → Z Z 48 ± 8 860 ± 18 1360 ± 28 515 ± 11

gg → Z Z 13 ± 4 114 ± 9 189 ± 14 73 ± 6

Z Z (EW) 10.9 ± 0.9 6.9 ± 0.3 11.1 ± 0.4 4.4 ± 0.2

Z + jets/t t /WZ 0.3 ± 0.1 2.1 ± 0.4 6.7 ± 1.6 3.1± 0.4

Otherbackgrounds

3 ± 0.2 16.3 ± 0.4 26.8 ± 0.6 11.8 ± 0.3

Totalbackground

75 ± 9 999 ± 20 1594 ± 31 607 ± 13

Observed 75 932 1656 612

are summarised in Table 6, and the m4� spectrum in eachcategory is shown in Fig. 9. The upper limits at 95% CL onthe cross section times branching ratio as a function of theheavy resonance mass in the case of the NWA is presentedin Fig. 10.

Table 6 The Z Z normalisation factors in each category of the two finalstates, which scale the number of Z Z events estimated from the MCsimulations, obtained from a simultaneous likelihood fit of the two finalstates under the background-only hypothesis. For the �+�−�′+�′− finalstate, the cut-based categorisation is used

Analysis Normalisation factor Fitted value

�+�−�′+�′− μVBF-CBAZ Z 1.1 ± 0.2

μggFZ Z 1.10 ± 0.02

�+�−νν μZ Z 1.04 ± 0.06

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Fig. 9 Distribution of the four-lepton invariant mass m4� in the�+�−�′+�′− search for a, b, c the ggF-CBA-enriched categories andd the VBF-CBA-enriched category. The backgrounds are determinedfrom a combined likelihood fit to the data under the background-onlyhypothesis. The simulated mH = 600 GeV signal is normalised to a

cross section corresponding to 50 (5) times the observed limit givenin Sect. 9.1.1 for the ggF (VBF) production mode. The error bars onthe data points indicate the statistical uncertainty, while the systematicuncertainty in the prediction is shown by the hatched band. The lowerpanels show the ratio of data to prediction

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Fig. 10 The upper limits at 95% CL on the cross section times branch-ing ratio as a function of the heavy resonance mass mH for a the ggFproduction mode (σggF × B(H → Z Z)) and b for the VBF produc-tion mode (σVBF × B(H → Z Z)) in the case of the NWA. For the

�+�−�′+�′− state the cut-based categorisation is used. The green andyellow bands represent the ±1σ and ±2σ uncertainties in the expectedlimits. The dashed coloured lines indicate the expected limits obtainedfrom the individual searches

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1 Department of Physics, University of Adelaide, Adelaide, Australia2 Physics Department, SUNY Albany, Albany, NY, USA3 Department of Physics, University of Alberta, Edmonton, AB, Canada4 (a)Department of Physics, Ankara University, Ankara, Turkey; (b)Istanbul Aydin University, Application and Research

Center for Advanced Studies, Istanbul, Turkey; (c)Division of Physics, TOBB University of Economics and Technology,Ankara, Turkey

5 LAPP, Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS/IN2P3, Annecy, France6 High Energy Physics Division, Argonne National Laboratory, Argonne, IL, USA7 Department of Physics, University of Arizona, Tucson, AZ, USA8 Department of Physics, University of Texas at Arlington, Arlington, TX, USA9 Physics Department, National and Kapodistrian University of Athens, Athens, Greece

10 Physics Department, National Technical University of Athens, Zografou, Greece11 Department of Physics, University of Texas at Austin, Austin, TX, USA

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http://orcid.org/0000-0001-9473-7836

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http://orcid.org/0000-0001-8290-3200

http://orcid.org/0000-0001-9606-7688

http://orcid.org/0000-0002-0688-3380

http://orcid.org/0000-0002-4368-9202

http://orcid.org/0000-0002-7402-369X

http://orcid.org/0000-0001-9184-2921

http://orcid.org/0000-0002-9588-1773

http://orcid.org/0000-0001-5975-8164

http://orcid.org/0000-0002-6620-6277

http://orcid.org/0000-0002-8993-3063

http://orcid.org/0000-0002-3865-4996

http://orcid.org/0000-0003-4273-6334

http://orcid.org/0000-0003-1171-0887

http://orcid.org/0000-0002-3298-4900

http://orcid.org/0000-0001-5866-1504

http://orcid.org/0000-0001-7655-389X

http://orcid.org/0000-0002-1528-4865

http://orcid.org/0000-0002-4055-218X

http://orcid.org/0000-0001-9690-2997

http://orcid.org/0000-0001-9895-4475

http://orcid.org/0000-0002-0988-1655

http://orcid.org/0000-0002-1344-8723

http://orcid.org/0000-0001-6473-7886

http://orcid.org/0000-0001-6355-2767

http://orcid.org/0000-0001-6110-2172

http://orcid.org/0000-0001-8997-3199

http://orcid.org/0000-0002-1928-1717

http://orcid.org/0000-0002-0215-6151

http://orcid.org/0000-0001-5661-1917

http://orcid.org/0000-0001-9563-4804

http://orcid.org/0000-0001-9571-3131

http://orcid.org/0000-0001-9602-4901

http://orcid.org/0000-0002-2680-0474

http://orcid.org/0000-0001-6977-3456

http://orcid.org/0000-0003-4716-5817

http://orcid.org/0000-0002-6885-282X

http://orcid.org/0000-0002-3725-4800

http://orcid.org/0000-0002-5351-5169

http://orcid.org/0000-0003-0411-3590

http://orcid.org/0000-0003-3710-6995

http://orcid.org/0000-0002-2483-4937

http://orcid.org/0000-0001-7367-1380

http://orcid.org/0000-0003-3554-7113

http://orcid.org/0000-0002-0204-984X

http://orcid.org/0000-0002-4996-1924

http://orcid.org/0000-0002-1452-9824

http://orcid.org/0000-0002-9201-0972

http://orcid.org/0000-0001-8524-1855

http://orcid.org/0000-0002-7374-2334

http://orcid.org/0000-0002-3335-1988

http://orcid.org/0000-0001-8939-666X

http://orcid.org/0000-0002-4886-9851

http://orcid.org/0000-0001-9274-707X

http://orcid.org/0000-0002-7864-4282

http://orcid.org/0000-0003-0586-7052

http://orcid.org/0000-0002-1827-9201

http://orcid.org/0000-0002-9595-2623

http://orcid.org/0000-0003-2174-807X

http://orcid.org/0000-0003-1988-8401

http://orcid.org/0000-0002-3656-2326

http://orcid.org/0000-0001-5858-6639

http://orcid.org/0000-0003-3268-3486

http://orcid.org/0000-0002-0398-8179

http://orcid.org/0000-0002-8452-0315

http://orcid.org/0000-0001-6956-3205

http://orcid.org/0000-0002-4105-2988

http://orcid.org/0000-0001-5626-0993

http://orcid.org/0000-0002-3156-4453

http://orcid.org/0000-0003-1714-9218

http://orcid.org/0000-0002-6932-2804

http://orcid.org/0000-0002-4961-8368

http://orcid.org/0000-0001-7909-4772

http://orcid.org/0000-0002-4963-8836

http://orcid.org/0000-0002-4499-2545

http://orcid.org/0000-0002-1222-7937

http://orcid.org/0000-0002-9037-2152

http://orcid.org/0000-0003-2280-8636

http://orcid.org/0000-0001-6331-3272

http://orcid.org/0000-0002-2029-2659

http://orcid.org/0000-0002-5447-1989

http://orcid.org/0000-0001-8265-6916

http://orcid.org/0000-0002-4198-3029

http://orcid.org/0000-0002-5110-5959

http://orcid.org/0000-0002-9726-6707

http://orcid.org/0000-0001-7335-4983

http://orcid.org/0000-0002-5706-7180

http://orcid.org/0000-0002-9907-838X

http://orcid.org/0000-0002-9778-9209

http://orcid.org/0000-0002-9336-9338

http://orcid.org/0000-0001-5241-6559

http://orcid.org/0000-0001-8659-5727

http://orcid.org/0000-0002-8265-474X

http://orcid.org/0000-0003-4731-0754

http://orcid.org/0000-0003-4341-1603

http://orcid.org/0000-0002-4554-2554

http://orcid.org/0000-0002-7853-9079

http://orcid.org/0000-0003-0054-8749

http://orcid.org/0000-0003-0494-6728

http://orcid.org/0000-0002-3360-4965

http://orcid.org/0000-0002-8323-7753

http://orcid.org/0000-0001-9377-650X

http://orcid.org/0000-0001-5904-7258

http://orcid.org/0000-0002-7986-9045

http://orcid.org/0000-0001-7223-8403

http://orcid.org/0000-0002-1775-2511

http://orcid.org/0000-0001-8015-3901

http://orcid.org/0000-0002-5918-9050

http://orcid.org/0000-0001-8479-1345

http://orcid.org/0000-0001-8066-7048

http://orcid.org/0000-0002-5278-2855

http://orcid.org/0000-0002-7306-1053

http://orcid.org/0000-0003-0996-3279

http://orcid.org/0000-0003-2468-9634

http://orcid.org/0000-0002-0306-9199

http://orcid.org/0000-0002-6311-7420

http://orcid.org/0000-0003-0277-4870

http://orcid.org/0000-0002-1529-8925

http://orcid.org/0000-0003-4236-8930

http://orcid.org/0000-0001-8113-1499

http://orcid.org/0000-0002-0993-6185

http://orcid.org/0000-0003-2138-6187

http://orcid.org/0000-0003-2073-4901

http://orcid.org/0000-0002-0542-1264

http://orcid.org/0000-0002-9397-2313

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12 (a)Bahcesehir University, Faculty of Engineering and Natural Sciences, Istanbul, Turkey; (b)Istanbul Bilgi University,Faculty of Engineering and Natural Sciences, Istanbul, Turkey; (c)Department of Physics, Bogazici University, Istanbul,Turkey; (d)Department of Physics Engineering, Gaziantep University, Gaziantep, Turkey

13 Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan14 Institut de Física d’Altes Energies (IFAE), Barcelona Institute of Science and Technology, Barcelona, Spain15 (a)Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China; (b)Physics Department, Tsinghua

University, Beijing, China; (c)Department of Physics, Nanjing University, Nanjing, China; (d)University of ChineseAcademy of Science (UCAS), Beijing, China

16 Institute of Physics, University of Belgrade, Belgrade, Serbia17 Department for Physics and Technology, University of Bergen, Bergen, Norway18 Physics Division, Lawrence Berkeley National Laboratory and University of California, Berkeley, CA, USA19 Institut für Physik, Humboldt Universität zu Berlin, Berlin, Germany20 Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics, University of Bern, Bern,

Switzerland21 School of Physics and Astronomy, University of Birmingham, Birmingham, UK22 (a)Facultad de Ciencias y Centro de Investigaciónes, Universidad Antonio Nariño, Bogotá, Colombia; (b)Departamento

de Física, Universidad Nacional de Colombia, Bogotá, Colombia, Colombia23 (a)Dipartimento di Fisica, INFN Bologna and Universita’ di Bologna, Bologna, Italy; (b)INFN Sezione di Bologna,

Bologna, Italy24 Physikalisches Institut, Universität Bonn, Bonn, Germany25 Department of Physics, Boston University, Boston, MA, USA26 Department of Physics, Brandeis University, Waltham, MA, USA27 (a)Transilvania University of Brasov, Brasov, Romania; (b)Horia Hulubei National Institute of Physics and Nuclear

Engineering, Bucharest, Romania; (c)Department of Physics, Alexandru Ioan Cuza University of Iasi, Iasi, Romania; (d)Physics Department, National Institute for Research and Development of Isotopic and Molecular Technologies,Cluj-Napoca, Romania; (e)University Politehnica Bucharest, Bucharest, Romania; (f)West University in Timisoara,Timisoara, Romania

28 (a)Faculty of Mathematics, Physics and Informatics, Comenius University, Bratislava, Slovakia; (b)Department ofSubnuclear Physics, Institute of Experimental Physics of the Slovak Academy of Sciences, Kosice, Slovak Republic

29 Physics Department, Brookhaven National Laboratory, Upton, NY, USA30 Departamento de Física, Universidad de Buenos Aires, Buenos Aires, Argentina31 California State University, Long Beach, CA, United States of America32 Cavendish Laboratory, University of Cambridge, Cambridge, UK33 (a)Department of Physics, University of Cape Town, Cape Town, South Africa; (b)iThemba Labs, Johannesburg, Western

Cape, South Africa; (c)Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg,South Africa; (d)University of South Africa, Department of Physics, Pretoria, South Africa; (e)School of Physics,University of the Witwatersrand, Johannesburg, South Africa

34 Department of Physics, Carleton University, Ottawa, ON, Canada35 (a)Faculté des Sciences Ain Chock, Réseau Universitaire de Physique des Hautes Energies-Université Hassan II,

Casablanca, Morocco; (b)Faculté des Sciences, Université Ibn-Tofail, Kenitra, Morocco; (c)Faculté des SciencesSemlalia, Université Cadi Ayyad, LPHEA-Marrakech, Marrakesh, Morocco; (d)Moroccan Foundation for AdvancedScience Innovation and Research (MAScIR), Rabat, Morocco; (e)LPMR, Faculté des Sciences, Université MohamedPremier, Oujda, Morocco; (f)Faculté des sciences, Université Mohammed V, Rabat, Morocco

36 CERN, Geneva, Switzerland37 Enrico Fermi Institute, University of Chicago, Chicago, IL, USA38 LPC, Université Clermont Auvergne, CNRS/IN2P3, Clermont-Ferrand, France39 Nevis Laboratory, Columbia University, Irvington, NY, USA40 Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark41 (a)Dipartimento di Fisica, Università della Calabria, Rende, Italy; (b)INFN Gruppo Collegato di Cosenza, Laboratori

Nazionali di Frascati, Italy42 Physics Department, Southern Methodist University, Dallas, TX, USA43 Physics Department, University of Texas at Dallas, Richardson, TX, USA44 National Centre for Scientific Research “Demokritos”, Agia Paraskevi, Greece

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45 (a)Department of Physics, Stockholm University, Stockholm, Sweden; (b)Oskar Klein Centre, Stockholm, Sweden46 Deutsches Elektronen-Synchrotron DESY, Hamburg and Zeuthen, Germany47 Lehrstuhl für Experimentelle Physik IV, Technische Universität Dortmund, Dortmund, Germany48 Institut für Kern- und Teilchenphysik, Technische Universität Dresden, Dresden, Germany49 Department of Physics, Duke University, Durham, NC, USA50 SUPA-School of Physics and Astronomy, University of Edinburgh, Edinburgh, UK51 INFN e Laboratori Nazionali di Frascati, Frascati, Italy52 Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany53 II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen, Germany54 Département de Physique Nucléaire et Corpusculaire, Université de Genève, Geneva, Switzerland55 (a)Dipartimento di Fisica, Università di Genova, Genoa, Italy; (b)INFN Sezione di Genova, Genoa, Italy56 II. Physikalisches Institut, Justus-Liebig-Universität Giessen, Giessen, Germany57 SUPA-School of Physics and Astronomy, University of Glasgow, Glasgow, UK58 LPSC, Université Grenoble Alpes, CNRS/IN2P3, Grenoble INP, Grenoble, France59 Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge, MA, USA60 (a)Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics, University of Science

and Technology of China, Hefei, China; (b)Institute of Frontier and Interdisciplinary Science and Key Laboratory ofParticle Physics and Particle Irradiation (MOE), Shandong University, Qingdao, China; (c)School of Physics andAstronomy, Shanghai Jiao Tong University, Key Laboratory for Particle Astrophysics and Cosmology (MOE), SKLPPC,Shanghai, China; (d)Tsung-Dao Lee Institute, Shanghai, China

61 (a)Kirchhoff-Institut für Physik, Ruprecht-Karls-Universität Heidelberg, Heidelberg, Germany; (b)Physikalisches Institut,Ruprecht-Karls-Universität Heidelberg, Heidelberg, Germany

62 Faculty of Applied Information Science, Hiroshima Institute of Technology, Hiroshima, Japan63 (a)Department of Physics, Chinese University of Hong Kong, Shatin N.T., Hong Kong, China; (b)Department of Physics,

University of Hong Kong, Pok Fu Lam, Hong Kong; (c)Department of Physics and Institute for Advanced Study, HongKong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China

64 Department of Physics, National Tsing Hua University, Hsinchu, Taiwan65 IJCLab, Université Paris-Saclay, CNRS/IN2P3, 91405, Orsay, France66 Department of Physics, Indiana University, Bloomington, IN, USA67 (a)INFN Gruppo Collegato di Udine, Sezione di Trieste, Udine, Italy; (b)ICTP, Trieste, Italy; (c)Dipartimento Politecnico

di Ingegneria e Architettura, Università di Udine, Udine, Italy68 (a)INFN Sezione di Lecce, Lecce, Italy; (b)Dipartimento di Matematica e Fisica, Università del Salento, Lecce, Italy69 (a)INFN Sezione di Milano, Milan, Italy; (b)Dipartimento di Fisica, Università di Milano, Milan, Italy70 (a)INFN Sezione di Napoli, Naples, Italy; (b)Dipartimento di Fisica, Università di Napoli, Naples, Italy71 (a)INFN Sezione di Pavia, Pavia, Italy; (b)Dipartimento di Fisica, Università di Pavia, Pavia, Italy72 (a)INFN Sezione di Pisa, Pisa, Italy; (b)Dipartimento di Fisica E. Fermi, Università di Pisa, Pisa, Italy73 (a)INFN Sezione di Roma, Rome, Italy; (b)Dipartimento di Fisica, Sapienza Università di Roma, Rome, Italy74 (a)INFN Sezione di Roma Tor Vergata, Rome, Italy; (b)Dipartimento di Fisica, Università di Roma Tor Vergata, Rom,

Italy75 (a)INFN Sezione di Roma Tre, Rome, Italy; (b)Dipartimento di Matematica e Fisica, Università Roma Tre, Rome, Italy76 (a)INFN-TIFPA, Trento, Italy; (b)Università degli Studi di Trento, Trento, Italy77 Institut für Astro- und Teilchenphysik, Leopold-Franzens-Universität, Innsbruck, Austria78 University of Iowa, Iowa City, IA, USA79 Department of Physics and Astronomy, Iowa State University, Ames, IA, USA80 Joint Institute for Nuclear Research, Dubna, Russia81 (a)Departamento de Engenharia Elétrica, Universidade Federal de Juiz de Fora (UFJF), Juiz de Fora, Brazil

; (b)Universidade Federal do Rio De Janeiro COPPE/EE/IF, Rio de Janeiro, Brazil; (c)Instituto de Física, Universidade deSão Paulo, São Paulo, Brazil

82 KEK, High Energy Accelerator Research Organization, Tsukuba, Japan83 Graduate School of Science, Kobe University, Kobe, Japan84 (a)AGH University of Science and Technology, Faculty of Physics and Applied Computer Science, Kraków, Poland

; (b)Marian Smoluchowski Institute of Physics, Jagiellonian University, Kraków, Poland85 Institute of Nuclear Physics Polish Academy of Sciences, Kraków, Poland

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86 Faculty of Science, Kyoto University, Kyoto, Japan87 Kyoto University of Education, Kyoto, Japan88 Research Center for Advanced Particle Physics and Department of Physics, Kyushu University, Fukuoka , Japan89 Instituto de Física La Plata, Universidad Nacional de La Plata and CONICET, La Plata, Argentina90 Physics Department, Lancaster University, Lancaster, UK91 Oliver Lodge Laboratory, University of Liverpool, Liverpool, UK92 Department of Experimental Particle Physics, Jožef Stefan Institute and Department of Physics, University of Ljubljana,

Ljubljana, Slovenia93 School of Physics and Astronomy, Queen Mary University of London, London, UK94 Department of Physics, Royal Holloway University of London, Egham, UK95 Department of Physics and Astronomy, University College London, London, UK96 Louisiana Tech University, Ruston, LA, USA97 Fysiska institutionen, Lunds universitet, Lund, Sweden98 Centre de Calcul de l’Institut National de Physique Nucléaire et de Physique des Particules (IN2P3), Villeurbanne,

France99 Departamento de Física Teorica C-15 and CIAFF, Universidad Autónoma de Madrid, Madrid, Spain

100 Institut für Physik, Universität Mainz, Mainz, Germany101 School of Physics and Astronomy, University of Manchester, Manchester, UK102 CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille, France103 Department of Physics, University of Massachusetts, Amherst, MA, USA104 Department of Physics, McGill University, Montreal, QC, Canada105 School of Physics, University of Melbourne, Victoria, Australia106 Department of Physics, University of Michigan, Ann Arbor, MI, USA107 Department of Physics and Astronomy, Michigan State University, East Lansing, MI, USA108 B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk, Belarus109 Research Institute for Nuclear Problems of Byelorussian State University, Minsk, Belarus110 Group of Particle Physics, University of Montreal, Montreal, QC, Canada111 P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow, Russia112 National Research Nuclear University MEPhI, Moscow, Russia113 D.V. Skobeltsyn Institute of Nuclear Physics, M.V. Lomonosov Moscow State University, Moscow, Russia114 Fakultät für Physik, Ludwig-Maximilians-Universität München, Munich, Germany115 Max-Planck-Institut für Physik (Werner-Heisenberg-Institut), Munich, Germany116 Nagasaki Institute of Applied Science, Nagasaki, Japan117 Graduate School of Science and Kobayashi-Maskawa Institute, Nagoya University, Nagoya, Japan118 Department of Physics and Astronomy, University of New Mexico, Albuquerque, NM, USA119 Institute for Mathematics, Astrophysics and Particle Physics, Radboud University/Nikhef, Nijmegen, The Netherlands120 Nikhef National Institute for Subatomic Physics and University of Amsterdam, Amsterdam, The Netherlands121 Department of Physics, Northern Illinois University, DeKalb, IL, USA122 (a)Budker Institute of Nuclear Physics and NSU, SB RAS, Novosibirsk, Russia; (b)Novosibirsk State University

Novosibirsk, Novosibirsk, Russia123 Institute for High Energy Physics of the National Research Centre Kurchatov Institute, Protvino, Russia124 Institute for Theoretical and Experimental Physics named by A.I. Alikhanov of National Research Centre “Kurchatov

Institute”, Moscow, Russia125 Department of Physics, New York University, New York, NY, USA126 Ochanomizu University, Otsuka, Bunkyo-ku, Tokyo, Japan127 Ohio State University, Columbus, OH, USA128 Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman, OK, USA129 Department of Physics, Oklahoma State University, Stillwater, OK, USA130 Palacký University, RCPTM, Joint Laboratory of Optics, Olomouc, Czech Republic131 Institute for Fundamental Science, University of Oregon, Eugene, OR, USA132 Graduate School of Science, Osaka University, Osaka, Japan133 Department of Physics, University of Oslo, Oslo, Norway134 Department of Physics, Oxford University, Oxford, UK

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135 LPNHE, Sorbonne Université, Université de Paris, CNRS/IN2P3, Paris, France136 Department of Physics, University of Pennsylvania, Philadelphia, PA, USA137 Konstantinov Nuclear Physics Institute of National Research Centre “Kurchatov Institute”, PNPI, St. Petersburg, Russia138 Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA, USA139 (a)Laboratório de Instrumentação e Física Experimental de Partículas-LIP, Lisbon, Portugal; (b)Departamento de Física,

Faculdade de Ciências, Universidade de Lisboa, Lisbon, Portugal; (c)Departamento de Física, Universidade de Coimbra,Coimbra, Portugal; (d)Centro de Física Nuclear da Universidade de Lisboa, Lisbon, Portugal; (e)Departamento de Física,Universidade do Minho, Braga, Portugal; (f)Departamento de Física Teórica y del Cosmos, Universidad de Granada,Granada, Spain; (g)Dep Física and CEFITEC of Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa,Caparica, Spain; (h)Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal

140 Institute of Physics of the Czech Academy of Sciences, Prague, Czech Republic141 Czech Technical University in Prague, Prague, Czech Republic142 Charles University, Faculty of Mathematics and Physics, Prague, Czech Republic143 Particle Physics Department, Rutherford Appleton Laboratory, Didcot, UK144 IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France145 Santa Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz, CA, USA146 (a)Departamento de Física, Pontificia Universidad Católica de Chile, Santiago, Chile; (b)Universidad Andres Bello,

Department of Physics, Santiago, Chile; (c)Instituto de Alta Investigación, Universidad de Tarapacá, Arica,Chile; (d)Departamento de Física, Universidad Técnica Federico Santa María, Valparaiso, Chile

147 Universidade Federal de São João del Rei (UFSJ), São João del Rei, Brazil148 Department of Physics, University of Washington, Seattle, WA, USA149 Department of Physics and Astronomy, University of Sheffield, Sheffield, UK150 Department of Physics, Shinshu University, Nagano, Japan151 Department Physik, Universität Siegen, Siegen, Germany152 Department of Physics, Simon Fraser University, Burnaby, BC, Canada153 SLAC National Accelerator Laboratory, Stanford, CA, USA154 Physics Department, Royal Institute of Technology, Stockholm, Sweden155 Departments of Physics and Astronomy, Stony Brook University, Stony Brook, NY, USA156 Department of Physics and Astronomy, University of Sussex, Brighton, UK157 School of Physics, University of Sydney, Sydney, Australia158 Institute of Physics, Academia Sinica, Taipei, Taiwan159 (a)E. Andronikashvili Institute of Physics, Iv. Javakhishvili Tbilisi State University, Tbilisi, Georgia; (b)High Energy

Physics Institute, Tbilisi State University, Tbilisi, Georgia160 Department of Physics, Technion, Israel Institute of Technology, Haifa, Israel161 Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv University, Tel Aviv, Israel162 Department of Physics, Aristotle University of Thessaloniki, Thessaloniki, Greece163 International Center for Elementary Particle Physics and Department of Physics, University of Tokyo, Tokyo, Japan164 Graduate School of Science and Technology, Tokyo Metropolitan University, Tokyo, Japan165 Department of Physics, Tokyo Institute of Technology, Tokyo, Japan166 Tomsk State University, Tomsk, Russia167 Department of Physics, University of Toronto, Toronto, ON, Canada168 (a)TRIUMF, Vancouver, BC, Canada; (b)Department of Physics and Astronomy, York University, Toronto, ON, Canada169 Division of Physics and Tomonaga Center for the History of the Universe, Faculty of Pure and Applied Sciences,

University of Tsukuba, Tsukuba, Japan170 Department of Physics and Astronomy, Tufts University, Medford, MA, USA171 Department of Physics and Astronomy, University of California Irvine, Irvine, CA, USA172 Department of Physics and Astronomy, University of Uppsala, Uppsala, Sweden173 Department of Physics, University of Illinois, Urbana, IL, USA174 Instituto de Física Corpuscular (IFIC), Centro Mixto Universidad de Valencia-CSIC, Valencia, Spain175 Department of Physics, University of British Columbia, Vancouver, BC, Canada176 Department of Physics and Astronomy, University of Victoria, Victoria, BC, Canada177 Fakultät für Physik und Astronomie, Julius-Maximilians-Universität Würzburg, Würzburg, Germany178 Department of Physics, University of Warwick, Coventry, UK

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179 Waseda University, Tokyo, Japan180 Department of Particle Physics and Astrophysics, Weizmann Institute of Science, Rehovot, Israel181 Department of Physics, University of Wisconsin, Madison, WI, USA182 Fakultät für Mathematik und Naturwissenschaften, Fachgruppe Physik, Bergische Universität Wuppertal, Wuppertal,

Germany183 Department of Physics, Yale University, New Haven, CT, USA

a Also at Borough of Manhattan Community College, City University of New York, New York, NY, USAb Centro Studi e Ricerche Enrico Fermi, Rome, Italyc CERN, Geneva, Switzerlandd Also at CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille, Francee Also at Département de Physique Nucléaire et Corpusculaire, Université de Genève, Geneva, Switzerlandf Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona, Spaing Also at Department of Financial and Management Engineering, University of the Aegean, Chios, Greeceh Also at Department of Physics and Astronomy, Michigan State University, East Lansing, MI, USAi Also at Department of Physics and Astronomy, University of Louisville, Louisville, KY, USAj Also at Department of Physics, Ben Gurion University of the Negev, Beer Sheva, Israel

k Also at Department of Physics, California State University, East Bay, USAl Also at Department of Physics, California State University, Fresno, USA

m Also at Department of Physics, California State University, Sacramento, USAn Also at Department of Physics, King’s College London, London, UKo Also at Department of Physics, St. Petersburg State Polytechnical University, St. Petersburg, Russiap Also at Department of Physics, University of Fribourg, Fribourg, Switzerlandq Also at Dipartimento di Matematica, Informatica e Fisica, Università di Udine, Udine, Italyr Also at Faculty of Physics, M.V. Lomonosov Moscow State University, Moscow, Russias Also at Giresun University, Faculty of Engineering, Giresun, Turkeyt Also at Graduate School of Science, Osaka University, Osaka, Japanu Hellenic Open University, Patras, Greecev Also at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona, Spainw Also at Institut für Experimentalphysik, Universität Hamburg, Hamburg, Germanyx Institute for Nuclear Research and Nuclear Energy (INRNE) of the Bulgarian Academy of Sciences, Sofia, Bulgariay Also at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest, Hungaryz Institute of Particle Physics (IPP), Montreal, Canada

aa Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijanab Also at Instituto de Fisica Teorica, IFT-UAM/CSIC, Madrid, Spainac Also at Department of Physics, Istanbul University, Istanbul, Turkeyad Joint Institute for Nuclear Research, Dubna, Russiaae Moscow Institute of Physics and Technology State University, Dolgoprudny, Russiaaf National Research Nuclear University MEPhI, Moscow, Russiaag Also at Physics Department, An-Najah National University, Nablus, Palestineah Also at Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg, Germanyai The City College of New York, New York, NY, USAaj TRIUMF, Vancouver, BC, Canada

ak Universita di Napoli Parthenope, Naples, Italyal University of Chinese Academy of Sciences (UCAS), Beijing, China∗ Deceased

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search for heavy resonances decaying into a pair of z

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