Published for SISSA by Springer Received: February 18, 2019 Accepted: March 24, 2019 Published: April 5, 2019 Measurement of the four-lepton invariant mass JHEP04(2019)048 spectrum in 13 TeV proton-proton collisions with the ATLAS detector The ATLAS collaboration E-mail: atlas.publications@cern.ch Abstract: A measurement of the four-lepton invariant mass spectrum is made with the ATLAS detector, using an integrated luminosity of 36.1 fb−1 of proton-proton collisions √ at s = 13 TeV delivered by the Large Hadron Collider. The differential cross-section is measured for events containing two same-flavour opposite-sign lepton pairs. It exhibits a rich structure, with different mass regions dominated in the Standard Model by single Z boson production, Higgs boson production, and Z boson pair production, and non- negligible interference effects at high invariant masses. The measurement is compared with state-of-the-art Standard Model calculations, which are found to be consistent with the data. These calculations are used to interpret the data in terms of gg → ZZ → 4` and Z → 4` subprocesses, and to place constraints on a possible contribution from physics beyond the Standard Model. Keywords: Hadron-Hadron scattering (experiments) ArXiv ePrint: 1902.05892 Open Access, c The Authors. https://doi.org/10.1007/JHEP04(2019)048 Article funded by SCOAP3 . Contents 1 Introduction 1 2 ATLAS detector 3 3 Definition of fiducial cross-section 4 4 Data sample and event selection 6 JHEP04(2019)048 5 Theoretical predictions and simulation 7 6 Unfolding for detector effects 10 7 Uncertainties 11 8 Measured distributions 14 9 Interpretations 18 10 Conclusion 26 The ATLAS collaboration 33 1 Introduction This paper presents a measurement of the four-lepton invariant mass (m4` ) spectrum in events containing two same-flavour opposite-sign lepton (electron or muon) pairs. The data correspond to 36.1 fb−1 of proton-proton collisions collected with the ATLAS detector √ during the s = 13 TeV Large Hadron Collider (LHC) run in 2015–2016. In pp collisions four-lepton production is expected to receive contributions from several Standard Model (SM) physics processes, the most important of which are shown in figure 1. The predicted cross-sections for these processes are shown as a function of the invariant four-lepton mass m4` in figure 2. Largest in magnitude is the quark-induced t-channel process q q̄ → 4`, with leptonic (` = e, µ) decays of the Z bosons. Gluon-induced gg → 4` production also occurs, via an intermediate quark loop. The theoretical uncertainties in the SM prediction for this latter contribution are comparatively large. At around m4` ' mZ = 91.19 GeV [1], single resonant Z → 4` production through QED radiative processes leads to a peak in the spectrum, and allows an extraction of the cross-section and branching fraction for Z → 4` to be made. Pairs of Z bosons can also be produced from the decay of an intermediate Higgs boson. The majority of these are produced via gluon-gluon fusion, with minor contributions from –1– q ℓ+ ℓ+ Z (∗) g ℓ+ ℓ− q (∗) (∗) ℓ− g Z Z Z (∗) Z (∗) ℓ+ ℓ− ℓ− ℓ+ Z (∗) ℓ− H (∗) + ℓ q̄ ℓ − Z (∗) g q̄ Z (∗) ℓ + ℓ− ℓ− g ℓ+ (a) (b) (c) (d) Figure 1. Main contributions to the pp → 4` (` = e, µ) process: (a) t-channel q q̄ → 4` production, (b) gluon-induced gg → 4` production via a quark loop, (c) internal conversion in Z boson decays and (d) Higgs-boson-mediated s-channel production (here: gluon-gluon fusion). The notation Z (∗) JHEP04(2019)048 refers to a Z boson which may be either on-shell or off-shell. dσ/dm4l [fb/GeV] ATLAS Simulation qq→ 4l 1 s=13 TeV gg→ 4l (inclusive) gg→ H → 4l gg→ ZZ → 4l 10−1 VH/ttH/VBF H → 4l 10−2 10−3 80 100 200 300 400 1000 m4l [GeV] Figure 2. Differential cross-sections as a function of the four-lepton invariant mass m4` predicted by MC simulation. The total gg → 4` includes contributions from gg → H (∗) → 4` as well as gg → 4` and the interference between the two. The q q̄ → 4` and gg → 4` processes including off- shell Higgs boson production are modelled using Sherpa 2.2.2 including all corrections described in section 5, while on-shell Higgs production is modelled using the dedicated samples based on Powheg + Pythia 8 and MadGraph5 aMC@NLO + Herwig++ described in the same section. vector-boson fusion and associated production with vector bosons or top-quark pairs. There is resonant production around the Higgs boson mass of mH = 124.97 ± 0.24 GeV [2], as well as off-shell production at higher mass values, which is enhanced at approximately 350 GeV due to top-quark loops in the gluon-gluon fusion mechanism. At around 180 GeV there is an enhancement of all the processes involving two Z bosons, as on-shell production is possible above this mass. The box diagram gg → 4` and gg → H (∗) → 4` processes interfere destructively in the SM. While interference is maximal around m4` = 220 GeV [3], the relative effect of the gg → H (∗) → 4` contribution to the overall gg → 4` lineshape is most pronounced above 350 GeV, as is visible in figure 2. –2– The off-shell Higgs production rate may be affected by beyond-the-SM (BSM) processes involving additional heavy particles, or modifications of the Higgs couplings, even if there is no effect on on-shell Higgs boson production [4]. √ Previous measurements in this final state were carried out at s = 13 TeV by the ATLAS [5] and CMS [6] collaborations with a focus on ZZ production. The CMS result additionally includes a determination of the Z → 4` branching ratio using a dedicated detector-level analysis. The ATLAS collaboration performed a measurement of inclusive √ four-lepton production at s = 8 TeV [7] and set constraints on the contribution from √ gg → 4`. An analysis using s = 7 TeV and 8 TeV data [8] to determine the Z → 4` branching fraction has also been published by ATLAS. Constraints on off-shell Higgs boson JHEP04(2019)048 production have recently been set by ATLAS [9] using the 4` and 2`2ν final states in a dedicated detector-level analysis. This measurement is carried out in a fiducial phase space based on the kinematic acceptance of the detector to ensure a high selection efficiency. The fiducial phase space and all observables are defined using stable final-state particles to minimise model dependence. The observation at detector level is corrected for experimental effects such as the detector and trigger system efficiencies and the detector resolution to provide results which may be used and reinterpreted without requiring a full simulation of the ATLAS detector. Electrons or muons originating from leptonic decays of the τ -lepton are not considered to be part of the signal and their contribution to the observation at detector level is subtracted. Cross-sections are measured differentially in the invariant four-lepton mass m4` , and double-differentially with respect to both m4` and the following kinematic variables: the transverse momentum of the four-lepton system p4` T , the rapidity of the four-lepton system y4` , and a matrix-element discriminant (introduced in ref. [3] and denoted by DME in this paper) designed to distinguish the s-channel Higgs-mediated production process from all other processes. The m4` measurement is also made separately for each flavour combination of leptons in the event; 4e, 4µ and 2e2µ. The double-differential cross-sections can provide additional sensitivity to the various subprocesses contributing to the measured final state; for example, the p4` T is expected to discriminate gg → ZZ from q q̄ → ZZ. They are also of interest for future interpretation; for example, some BSM contributions can have an impact which depends upon the final-state lepton flavours [10]. The measurements are compared with SM predictions. To explore the potential of reinterpreting differential cross-section measurements, they are also used to constrain the gg → 4` process and set a limit on the gg → H ∗ → 4` off-shell signal strength, to extract the Z → 4` contribution and to place limits on a selected BSM scenario. 2 ATLAS detector The ATLAS experiment [11–13] at the LHC is a multipurpose particle detector with a forward-backward symmetric cylindrical geometry and a near 4π coverage in solid angle.1 1 ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP) in the centre of the detector and the z-axis along the beam pipe. The x-axis points from the IP to the centre of the LHC ring, and the y-axis points upwards. Cylindrical coordinates (r, φ) are used in the transverse –3– It consists of an inner tracking detector surrounded by a thin superconducting solenoid providing a 2 T axial magnetic field, electromagnetic and hadron calorimeters, and a muon spectrometer. The inner tracking detector covers the pseudorapidity range |η| < 2.5, and consists of silicon pixel, silicon microstrip, and transition radiation tracking detect- ors. Lead/liquid-argon (LAr) sampling calorimeters provide electromagnetic (EM) energy measurements with high granularity. A hadron (steel/scintillator-tile) calorimeter covers the central pseudorapidity range (|η| < 1.7). The endcap and forward regions are instru- mented with LAr calorimeters for both the EM and hadronic energy measurements up to |η| = 4.9. The muon spectrometer (MS) surrounds the calorimeters and includes three large air-core toroidal superconducting magnets with eight coils each. The field integral of JHEP04(2019)048 the toroids ranges between 2.0 and 6.0 Tm across most of the detector. The MS is based on a system of precision chambers providing tracking information up to |η| = 2.7 and fast detectors for triggering in the region |η| < 2.4. A two-level trigger system is used to select events [14]. The first-level trigger is implemented in hardware and processes a subset of the detector information to reduce the accepted rate to at most 100 kHz. This is followed by the software-based high-level trigger, which reduces the accepted event rate to 1 kHz on average depending on the data-taking conditions. 3 Definition of fiducial cross-section The fiducial phase space used for the measurement is driven by the kinematic accept- ance of the detector and closely follows the detector-level event selection described in section 4. The kinematic selection is defined using stable final-state particles [15]. Stable, prompt leptons (electrons and muons) are dressed by adding to their four-momenta the four-momenta of any photons not originating from hadron decays within a cone of size p ∆R = (∆η)2 + (∆φ)2 = 0.005 around the lepton direction. The fiducial phase space and any observables defined in this way are referred to as being at particle level. This definition is chosen to ensure that the particle-level distributions extrapolated from the detector-level observation are as model-independent as possible. This allows the extrapolation to be per- formed using detector resolutions and efficiencies which are known within experimentally controlled uncertainties, as described in section 6, without additional significant theoretical uncertainty. Events are required to contain a quadruplet consisting of two same-flavour opposite- sign (SFOS) lepton pairs. The three leading leptons in the quadruplet must have transverse momenta (pT ) larger than 20, 15, and 10 GeV, while the fourth lepton is required to have pT > 7 (5) GeV for electrons (muons). First, the lepton pair with an invariant mass closest to the Z boson mass is selected as the primary dilepton pair with mass m12 . The remaining pair closest to the Z boson mass is referred to as the secondary pair, with mass m34 , and completes the quadruplet. In this way, only one quadruplet is selected even in events containing more than four leptons. Requirements of 50 < m12 < 106 GeV and f (m4` ) < m34 < 115 GeV are imposed, where the lower bound on m34 is calculated on an plane, φ being the azimuthal angle around the z-axis. The pseudorapidity is p defined in terms of the polar angle θ as η = − ln tan(θ/2). Angular distance is measured in units of ∆R ≡ (∆η)2 + (∆φ)2 . –4– Physics Object Preselection Muon selection pT > 5 GeV, |η| < 2.7 Electron selection pT > 7 GeV, |η| < 2.47 Quadruplet Selection Assign SFOS lepton pairs with smallest Lepton pairing and second-smallest |m`` − mZ | as primary and secondary lepton pair, defining exactly one quadruplet Lepton kinematics pT > 20/15/10 GeV for leading three leptons JHEP04(2019)048 Mass window, primary pair 50 GeV< m12 < 106 GeV Mass window, secondary pair f (m4` ) < m34 < 115 GeV Lepton separation ∆Rij > 0.1(0.2) for same (opposite) flavour leptons J/ψ veto mij > 5 GeV for all SFOS pairs Mass interval of measurement 70 GeV< m4` < 1200 GeV Table 1. Definition of the fiducial region used for this measurement. All kinematic observables are defined using the dressed leptons. event-by-event basis as a function of the four-lepton invariant mass m4` ,     5 GeV, for m 4` < 100 GeV     5 GeV + 0.7 × (m − 100 GeV) , for 100 GeV < m < 110 GeV   4` 4`         f (m4` ) = 12 GeV, for 110 GeV < m4` < 140 GeV .   12 GeV + 0.76 × (m4` − 140 GeV) , for 140 GeV < m4` < 190 GeV              50 GeV, for m > 190 GeV  4` This approach preserves high acceptance for low m4` values, particularly for Z → 4`, while suppressing events with leptons from leptonic τ -lepton decays at higher values of m4` . The angular separation between opposite flavour leptons in the quadruplet is required to satisfy ∆R > 0.2, while any same flavour leptons have to be separated by ∆R > 0.1 from each other. The latter condition enhances the acceptance for boosted topologies in high-m4` Z boson pair production. To exclude leptons originating from quarkonia decays, the invariant mass of any same-flavour, opposite-sign lepton pair in the event is required to exceed 5 GeV. A dedicated veto of leptons originating from Υ decays is not performed, in order to retain acceptance at low m4` , in particular for the single resonant Z boson decay. This background is negligible within the phase space of this measurement. The full list of selection criteria is given in table 1 and largely follows refs. [16, 17]. The overall range in m4` considered for this measurement is 70 GeV < m4` < 1200 GeV and was chosen based on the yields predicted in MC simulation. All candidates observed in the collision data fall into this interval. In addition to the invariant mass m4` , transverse momentum p4` T , rapidity y4` and flavour composition of the selected quadruplet, the observables measured in this paper also –5– include a matrix-element discriminant (DME ) defined as   2 µ M̃gg→H (∗) →ZZ (∗) →4` p1,2,3,4 DME = log10    , (3.1) 2 µ 2 µ M̃gg p + 0.1 · M̃ p (→H (∗) )→ZZ (∗) →4` 1,2,3,4 q q̄→ZZ (∗) →4` 1,2,3,4 with     M2X pµ1,2,3,4 2 M̃X pµ1,2,3,4 = , M2X (m4` )   where M2X pµ1,2,3,4 indicates the squared matrix element for process X evaluated for the JHEP04(2019)048 specific four-momenta and flavours of the leptons in the given event, and M2X (m4` ) rep- resents the average squared matrix element for process X in the fiducial region for the given four-lepton invariant mass. The first squared matrix element M̃gg 2 in the (→H (∗) )→ZZ (∗) →4` denominator of eq. (3.1) includes the non-Higgs box diagram (figure 1b), Higgs-mediated production (figure 1d), as well as the interference of the two, whereas the squared matrix element in the numerator M̃gg→H2 (∗) →ZZ (∗) →4` only includes for Higgs-mediated produc- tion. The constant factor multiplying the t-channel matrix element in the denominator affects the shape of the observable, but does not have a significant impact on its separation power. The value of 0.1 is chosen to keep the peak of the distribution sufficiently distant from the maximum possible value of 0 while also limiting tails in the negative direction. The numerator represents the s-channel matrix element involving the Higgs boson pro- duced via gluon-gluon fusion. The squared matrix elements are computed at leading-order QCD precision using the MCFM [18] program version 8.0. The strong coupling constant is evaluated at the scale of half the four-lepton invariant mass. The Higgs boson mass is set to mH = 125.0 GeV, and its width to the Standard Model prediction for this mass. Given the leading-order QCD precision, the incoming parton momenta are approximated by assuming the four-lepton centre-of-mass system is produced at rest. 4 Data sample and event selection This measurement uses 36.1 fb−1 of proton-proton collision data with a centre-of-mass √ energy s = 13 TeV, collected during 2015 and 2016 with the ATLAS detector. Events are selected in the online trigger system by requiring that one of several triggers be passed, in which one, two or three leptons (electrons or muons) are required with a range of lepton pT requirements dependent upon the multiplicity [19]. The combined efficiency of these triggers for events within the detector-level phase space of the measurement is above 96% for 70 GeV < m4` < 180 GeV and increases beyond 99% for m4` > 180 GeV as the final-state leptons become more likely to satisfy the trigger thresholds. Electron identification is based on variables describing the longitudinal and transverse shapes of the electromagnetic showers in the calorimeters, properties of tracks in the inner detector, and track-cluster matching [20, 21]. Muons are identified using information from the muon spectrometer, the inner tracking detector and calorimeters, with the requirements depending upon the angular region and pT of the muon [22]. –6– Using the candidates identified in this way, the detector-level event selection looks for four prompt leptons, as detailed in table 2. Electrons are required to satisfy a loose- identification working point for which the efficiency is about 95% [23], have ET > 7 GeV and |η| < 2.47. Muons must likewise satisfy a loose-identification working point, designed to achieve high efficiencies of about 99% with relatively low backgrounds [22], and have pT > 5 GeV, or pT > 15 GeV if they are tagged solely in the calorimeter (“calorimeter- tagged muon”). To select leptons originating from the primary proton-proton interaction, their tracks are required to have a longitudinal impact parameter (z0 ) satisfying |z0 sin(θ)| < 0.5 mm from the primary interaction vertex. Background from cosmic-ray muons is rejected by requiring each muon track’s transverse impact parameter (d0 ) to satisfy |d0 | < 1 mm. JHEP04(2019)048 This additionally discriminates against non-prompt muons. Using the leptons selected in this way, a quadruplet is formed according to the kin- ematic selection criteria defining the fiducial phase space described in section 3. The quadruplet is then subjected to further requirements in order to suppress the contribution of leptons from secondary decays or misidentifications related to jet activity. It must not contain more than one muon identified solely in the calorimeter or solely in the muon spec- trometer. None of the leptons constituting the quadruplet may have a transverse impact parameter significance d0 /σd0 > 5 (3) for electrons (muons). All leptons of the quadruplet are required to satisfy isolation criteria based on particle-tracks measured in the inner detector and energy deposits in the electromagnetic calorimeter. When evaluating these criteria, tracks or deposits originating from leptons in the quadruplet are not considered in order to retain events with close-by prompt leptons. Finally, the four leptons of the quadruplet are required to be loosely compatible with originating from a common vertex, evaluated by means of the reduced-χ2 vertex fit using the four lepton trajectories. This further suppresses the contribution of secondary leptons from b- and c-hadron decays. 5 Theoretical predictions and simulation Simulated events are used to correct the observed events for detector effects, as well as to estimate the expected numbers of signal and background events and the systematic uncer- tainty of the final results. Events from Monte Carlo simulation (MC) were passed through a detailed simulation of the ATLAS detector and trigger [24], and the same reconstruc- tion and analysis software as applied to the data. The effect of multiple pp interactions per bunch crossing, as well as the effect on the detector response due to interactions from bunch crossings before or after the one containing the hard interaction, referred to as “pile- up”, is emulated by overlaying inelastic pp collisions onto the generated events. The events are then reweighted to reproduce the distribution of the number of collisions per bunch- crossing observed in the data. This procedure is known as “pile-up reweighting”. To allow the contamination from events with τ -leptons to be evaluated, generated samples include τ -leptons. The pair production of two Z bosons via the q q̄ → 4` process was simulated with the Sherpa 2.2.2 event generator [25]. Matrix elements were calculated for up to one parton at next-to-leading order (NLO) in QCD and up to three partons at leading order (LO) –7– Physics Object preselection Electrons Muons Identification Loose working point [23] Loose working point [22] pT > 5 GeV and |η| < 2.7 Kinematics ET > 7 GeV and |η| < 2.47 pT > 15 GeV if calorimeter-tagged [22] Interaction point constraint |z0 · sin θ| < 0.5 mm |z0 · sin θ| < 0.5 mm Cosmic-ray muon veto |d0 | < 1 mm Quadruplet Selection Quadruplet formation Procedure and kinematic selection criteria as in table 1 JHEP04(2019)048 Lepton isolation Electrons Muons e pT < 0.15pµT P P Track isolation pT < 0.15ET ∆R≤0.2 ∆R≤0.3 e ET < 0.3pµT P P Calorimeter isolation ET < 0.2ET ∆R=0.2 ∆R=0.2 Contributions from the other leptons of the quadruplet not considered Lepton transverse impact parameter Electrons Muons d0 /σd0 < 5 d0 /σd0 < 3 4` vertex fit χ2 /ndof < 6 (4µ) or < 9 (4e, 2e2µ) Table 2. Summary of the event selection requirements at detector level. using Comix [26] and OpenLoops [27], and merged with the Sherpa parton shower [28] according to the ME+PS@NLO prescription [29]. The NNPDF3.0NNLO PDF set [30] was used, and the QCD renormalisation and factorisation scales were set to m4` /2. The total cross-section from this calculation agrees within scale uncertainties with an NNLO QCD prediction obtained using the MATRIX program [31–34]. A reweighting for virtual NLO EW effects [35, 36] was applied as a function of the four-lepton invariant mass, m4` , which modifies the differential cross-section by between +3% (for m4` ∼ 130 GeV) and −20% for m4` > 800 GeV. The real higher-order electroweak contribution to 4` production in association with two jets (which includes vector-boson scattering) is not included in the sample discussed above but it was modelled separately using Sherpa 2.2.2 with the NNPDF3.0NNLO PDF set. A second q q̄ → 4` sample was generated at NLO precision in QCD using Powheg-Box v2 [37–39] configured with the CT10 PDF set [40] and interfaced to Pythia 8.186 [41, 42] for parton showering. A correction to higher-order precision (K- factor), defined for this process as the ratio of the cross-section at NNLO QCD accuracy to the one at NLO QCD accuracy, was obtained using the MATRIX NNLO QCD prediction and applied to this sample as a function of m4` , modifying the inclusive cross-section by between +10% for m4` < 180 GeV and +25% for m4` > 800 GeV. The reweighting for virtual NLO EW effects discussed above for the Sherpa case was also applied to this sample. –8– The purely gluon-initiated ZZ production process enters at next-to-next-to-leading order (NNLO) in αS . It was modelled using Sherpa 2.2.2 [43], at LO precision for zero- and one-jet final states, and the NNPDF3.0NNLO PDF set was chosen. This sample includes the box diagram, the s-channel process proceeding via a Higgs boson, and the interference between the two. Recently, a NLO QCD calculation for the three components became available [44, 45] allowing m4` differential K-factors to be calculated with the 1/mt expansion below 2mt , and assuming a massless quark approximation above this threshold. This NLO QCD calculation was used to correct the s-channel process gg → H ∗ → ZZ (∗) → 4`, the box diagram gg → 4` and the interference with separate K-factors. These represent significant corrections of the order of +100% to the leading-order cross-section. There JHEP04(2019)048 are, however, NNLO QCD precision calculations for the off-shell Higgs boson production cross-section [46, 47] which show additional enhancement of the cross-section. Since these corrections are not known differentially in m4` for all three components, the prediction for each component is scaled by an additional overall correction factor of 1.2, assumed to be the same for the signal, background and interference. This additional constant scale factor is justified by the approximately constant behaviour of the NNLO/NLO QCD prediction. In addition, a purely leading-order prediction for the gg → 4` process was obtained using the MCFM program [18] with the CT10 PDF set [40], interfaced to Pythia 8 [41, 42]. In the mass range 100 GeV < m4` < 150 GeV, where on-shell Higgs production dom- inates and the effect of interference is negligible, dedicated samples are used to model the on-shell Higgs and box diagram continuum ZZ production processes. In the case of the box diagram, the same combination of NLO QCD K-factor and a factor of 1.2 to ac- count for higher-order effects, as described above, is applied to correct the cross-section. The Higgs production processes via gluon-gluon fusion (ggF) [48] (which dominates the on-shell Higgs production), via vector-boson fusion (VBF) [49] and in association with a vector boson (V H) [50] were all simulated at NLO precision in QCD using Powheg- Box v2 with the PDF4LHC next-to-leading-order (NLO) set of parton distribution func- tions [51] and interfaced to Pythia 8.186. The decay of the Higgs and Z bosons was performed within Pythia. The description of the gluon-gluon fusion process was further improved by reweighting to NNLO QCD accuracy using the HNNLO program [52–54], referred to as the NNLOPS method [55], and the resulting prediction was normalised using cross-sections calculated at N3LO precision in QCD [47]. For VBF production, full NLO QCD and EW calculations were used with approximate NNLO QCD corrections. The VH production was calculated at NNLO in QCD and NLO EW corrections are applied. Production in association with a top-quark pair was simulated to NLO accuracy in QCD using MadGraph5 aMC@NLO [56, 57] configured with the CT10 PDF set and interfaced to Herwig++ [58, 59]. The contribution from this process is very small in the analysis. Other SM processes resulting in four prompt leptons in the final state are considered as irreducible backgrounds, and were also simulated using MC generators. These include triboson production (ZW W , ZZW and ZZZ) and tt̄ pairs produced in association with vector bosons (tt̄Z, tt̄W W ) collectively referred to as tt̄V (V ). The triboson processes were generated with Sherpa 2.1.1 using the CT10 PDF set. The W W Z prediction has leading- order QCD precision for up to two additional outgoing partons while the W ZZ and ZZZ –9– prediction has next-to-leading-order QCD precision for zero additional outgoing partons and leading-order QCD precision for up to two partons. The tt̄V processes were generated with Sherpa 2.2.0 at leading-order QCD precision and the NNPDF3.0NNLO PDF set. In addition to these contributions, reducible background processes which can contribute to the final event selection but contain at least one non-prompt or mis-reconstructed lepton are estimated using a partially data-driven method detailed in refs. [16, 17]. These processes include one or more leptons produced from heavy-flavour hadron decays, muons from pion or kaon decays, or electrons from either photon conversion or hadron misidentification. The majority of these events originate from Z bosons produced in association with jets, tt̄ production with leptons from heavy-flavour decay, and W Z production in association with JHEP04(2019)048 jets. Contributions from these processes are estimated separately depending on the flavour of the leptons in the secondary pair and the source of the non-prompt lepton(s). This estimation procedure uses a number of different control regions and simultaneous fits, and for some specific processes the estimation is taken directly from MC simulation. The data- driven results were validated in separate control regions using data. This contribution is small compared to that of prompt four-lepton production, and negligible for m4` > 200 GeV. 6 Unfolding for detector effects The measured four-lepton mass spectrum and additional double-differential spectra are “unfolded” to correct for experimental effects, including the resolution and efficiency of the detector and trigger system. This allows direct comparison with particle-level predictions within the fiducial phase space. The unfolding procedure is based on describing the relationship between the number of events measured in a bin d of a particular detector-level differential distribution and the yield in bin p of the corresponding particle-level distribution using a single response matrix Rdp . This matrix consists of three contributions: • The reconstruction efficiency is measured as the ratio of the number of events which pass both the fiducial and detector event selections to the number passing the fiducial selection, as a function of the kinematic observable(s) at particle level. Above m4` = 200 GeV, it is typically between 60% and 80%, while for lower values of m4` , values as low as 30% are reached for the 4e final state, due to reduced detector efficiency when reconstructing leptons of low transverse momenta. It enters Rdp as a diagonal matrix. • A “migration matrix” which contains the probabilities that a particle-level event from a given fiducial bin which passes the detector selection will be found in a particular reconstructed bin. It accounts for bin-to-bin migrations. For all measurements, the diagonal elements of this matrix, also referred to as the “fiducial purity” in each bin, have values above 80%, with most of the small amount of migration occurring between neighbouring mass bins. • Finally, the fiducial fraction accounts for events which pass the detector selection but fail the fiducial event selection. This can occur due to the resolution of the detector, – 10 – or leptons originating from leptonically decaying τ -leptons. It is measured by taking the ratio of events which pass both the fiducial and detector selection to the total passing the detector selection. It is close to unity for m4` > 200 GeV, and above 90% below this threshold. It enters Rdp as a diagonal matrix. In the unfolding procedure, first, the fiducial fraction is accounted for by multiplying the background-subtracted observation in each bin of the measurement with the fiducial fraction for that particular bin. Then, an iterative Bayesian procedure [60], using the particle-level predicted distribution as the initial prior and the migration matrix, is used to correct for bin migration. The iteration procedure reduces the dependence on the initial JHEP04(2019)048 prior. The number of iterations is used as a regularisation parameter and controls the statistical uncertainty. Two iterations are found to be optimal for all distributions by MC studies aiming to minimise both the statistical uncertainty and the bias. Finally, the resulting estimate of the particle-level distribution is divided by the reconstruction efficiency bin by bin to obtain the final result. This approach represents a compromise between accounting for the small migration effects that occur and minimising the effect of small fluctuations in the detector-level distributions through the regularisation approach. The binning used for the measurements presented in this paper is driven by the re- quirements of the procedure described above. Bin edges are placed to cover as wide as possible a phase-space interval with fine granularity while ensuring a fiducial purity of at least 80%. In addition, a minimum predicted detector-level yield of 10 events is required in each bin to ensure the numerical stability of the unfolding procedure and the viability for reinterpretation. The robustness of the unfolding procedure to possible deviations of the data from the SM prediction was studied to ensure the model-independence of the analysis. Three scen- arios were checked by unfolding pseudo-data after including the following: a greatly varied rate from off-shell Higgs production, or gluon-induced ZZ production, (−75%/+200% and −100%/+400% respectively) and the injection of an additional scalar resonance (masses of 200, 400 and 900 GeV were used). For the smooth, non-resonant modifications of the lineshape, the true lineshape was reproduced by unfolding with the SM-based response matrix with excellent accuracy, with residual biases far less than statistical precision. For large, resonant BSM contributions the bias is larger, up to the order of the statistical uncer- tainty when using the high-DME region (defined in section 8). This type of interpretation is not considered here, but it is noted for any reinterpretations which may be affected. 7 Uncertainties The limiting source of uncertainty in this measurement is the statistical uncertainty, which is many times greater than the total systematic uncertainty in some bins. Experimental and theoretical sources both contribute to the systematic uncertainty, and their relative impact varies depending on the bin. The statistical uncertainty of the data is estimated using 2000 Poisson-distributed pseudo-datasets centred on the observed value in each bin, and repeating the unfolding – 11 – procedure for each set. The root mean square of the differences between the resulting unfolded distributions and the unfolded data is taken as the statistical uncertainty in each bin. Experimental systematic uncertainties affect the response matrix used in the unfolding procedure. They are dominated by the reconstruction, identification and isolation efficiency uncertainties for electrons [23, 61] and muons [22]. There are smaller contributions from lepton momentum resolution and scale uncertainties, and the uncertainty in the pile-up reweighting. The uncertainty in the combined 2015+2016 integrated luminosity is 2.1%. It is de- rived, following a methodology similar to that detailed in ref. [62], and using the LUCID-2 JHEP04(2019)048 detector for the baseline luminosity measurements [63], from calibration of the luminos- ity scale using x-y beam-separation scans. This uncertainty is fully correlated across all measured cross-section bins and is propagated to the limit setting in the interpretations of the results. All other sources of systematic uncertainty are propagated to the final unfol- ded distributions by varying the inputs within their uncertainty, repeating the unfolding, and taking in each bin the resulting deviation from the nominal response matrix as the uncertainty. Theoretical uncertainties primarily affect the particle-level predictions obtained from simulation. Since they affect the contribution of individual subprocesses to the total cross- section and the final-state lepton kinematics, they also impact the response matrix and hence the measured cross-sections. However, this is a very small effect compared to the experimental uncertainties and the statistical uncertainty. The most significant sources of theoretical uncertainty are the choice of factorisation and renormalisation scales, PDF set, and parton showering model within the event generator for the q q̄ → 4` and gg → 4` MC samples. In the case of q q̄ → 4`, the full uncertainty due to the scale choice was estimated using seven sets of values for the renormalisation and factorisation scales obtained by independently varying each to either one half, one, or two times the nominal value while keeping their ratio in the range of [0.5, 2]. Since a NLO QCD K-factor obtained within the fiducial phase space is applied in the gg → 4` samples, the uncertainty due to the scale choice for this production process within the fiducial phase space is evaluated using the differential scale uncertainty of this K-factor. In addition, seven sets of two values for the scales as described above are used to evaluate the impact of the scale choice on the acceptance for gg → 4`. Due to the reweighting of the purely gluon-induced ZZ production processes described in section 5, there are several other uncertainties affecting the normalisation in addition to the scale-induced uncertainties calculated together with the NLO QCD K-factors dis- cussed above. In the m4` region below 2mt , the higher-order corrections were computed solely for events not featuring jets with pT > 150 GeV to ensure a good description by the 1/mt expansion. Therefore, the default scale uncertainty is doubled for about 8% of the events in this region which contain such jets. Likewise, the scale uncertainty is also doubled at 2mt , with a Gaussian-smoothed transition from this maximal value down to the default uncertainty within a distance of 50 GeV to either side of the threshold. The inflated – 12 – uncertainty is intended to account for potential effects as the top quarks become on-shell. It is assumed that the relative NLO QCD corrections for massless and massive loops be- have similarly beyond 2mt and that the NNLO QCD correction calculated for the off-shell Higgs production process mimics the continuum production and the interference well, so no further uncertainty is considered. It is expected that the NLO QCD scale uncertainty covers these effects, as it is larger than the one calculated at NNLO QCD. The uncertainty due to the choice of PDF set was estimated for both q q̄ → 4` and gg → 4` by reweighting the sample to the alternative PDF sets CT10 and MSTW [64] as well as evaluating eigenvector variations of the default NNPDF3.0NNLO PDF set. In the case of q q̄ → 4`, the envelope of these three variations is used to assign an uncertainty. For JHEP04(2019)048 gg → 4`, the envelope is formed using only the effect of the variations on the shapes, as the cross-section is taken from the higher-order reweighting. The impact on the detector corrections originating from differences in the showering model was assessed for both processes by varying the CKKW matching scale [65, 66] from the Sherpa 2.2.2 default, changing the dipole recoil scheme in the shower to the one in [67] and by varying the resummation scale up and down by a factor of two. Furthermore, in order to account for non-factorising effects, q q̄ → 4` events with high QCD activity [68] were assigned an additional uncertainty of the size of the NLO EW correction. As the NLO EW reweighting is only applied for q q̄ → 4`, this last uncertainty is not applied to the gg → 4` or gg → H (∗) → 4` processes. Theoretical uncertainties in the modelling of resonant Higgs boson production do not have a significant effect on the response matrix, since this process is confined to a single bin in the m4` spectrum. They mainly affect the predicted particle-level differential cross- sections. The same uncertainties as reported in ref. [16] are applied in this paper. They are dominated by QCD scale and PDF uncertainties affecting the gluon-gluon fusion com- ponent. In order to cross-check and estimate the uncertainty due to the choice of generator used to model the q q̄ → 4` process, the difference between the unfolded results using the nominal Sherpa 2.2.2 samples and the alternative Powheg + Pythia 8 sample is taken as a systematic uncertainty. The MC statistical uncertainty in the unfolding procedure is evaluated using a boot- strap method with 2000 toy samples, each assigning a Poisson weight with an expected value of one to every MC event used in the analysis. The RMS of the unfolded result in each bin for all toy samples is then taken as an uncertainty, and is typically between 0.5% and 1.5% per bin. The uncertainty due to the unfolding method itself is estimated as follows. The MC events are reweighted with fitted functions of the particle-level observables to give good agreement between the reconstructed MC distribution and the observed data distribution. The reconstructed MC distribution is then unfolded using the nominal response matrix and compared with the reweighted particle-level distribution, with the difference between the two taken as a systematic uncertainty in each bin. For the majority of bins this is less than 1%, with the exception of two bins with the fewest number of events in the double-differential m4` –p4`T distribution (defined in section 8) which result in 3% and 5% – 13 – Uncertainty [%] 100 ATLAS Total Unc. Unfolding s=13 TeV, 36.1 fb-1 Theory Lumi. & Pile-Up Measured cross-section Lepton Data stat. DD bkg., MC stat. 30 20 10 3 2 JHEP04(2019)048 1 0.3 80 100 200 300 400 1000 m 4l [GeV] Figure 3. The leading sources of uncertainty in the measured cross-section after unfolding are given in percent as a function of the four-lepton invariant mass. The “Unfolding” category includes the effect of the generator choice for q q̄ → 4` and the uncertainty due to the unfolding method itself, added in quadrature. The “Lepton” category comprises the lepton reconstruction and selection efficiencies as well as momentum resolution and scale uncertainties. “DD bkg” refers to the data- driven estimation used for the reducible background contribution. uncertainties. For comparison, the statistical uncertainty is around 25% and 45% in those respective bins. The various contributions to the uncertainties in the final result are summarised in figures 3–5. 8 Measured distributions Figures 6–9 show the observed distributions for events passing the full selection at detector level, before unfolding, compared with the expected distributions based on the simulated signal and irreducible background and estimated reducible background processes. In the m4` distribution, enhancements in the first and third bins correspond to single Z boson production and radiative decay, and on-shell Higgs production, respectively. An enhance- ment at around 180 GeV due to the onset of on-shell ZZ production is also clearly visible. Overall, no significant discrepancy between the prediction and observation is found. The observed distributions are then corrected for detector effects by unfolding as de- scribed in section 6. The resulting measured differential cross-section as a function of m4` and double-differential cross-sections as functions of m4` and p4`T , |y4` |, the DME discrimin- ant, or the final-state lepton flavour configuration are shown in figures 10–14, and compared with particle-level predictions. Overall the predictions are consistent with the measurement when using either Sherpa 2.2.2 or Powheg + Pythia 8 to describe the dominant q q̄ → 4` component, considering the systematic and statistical uncertainties. – 14 – Total Unfolding Total Unfolding ATLAS ATLAS Theory Lumi. & Pile-Up Theory Lumi. & Pile-Up -1 -1 s=13 TeV, 36.1 fb Lepton Data stat. s=13 TeV, 36.1 fb Lepton Data stat. Measured cross-section DD bkg., MC stat. Measured cross-section DD bkg., MC stat. Uncertainty [%] Uncertainty [%] 0< p 4l < 20 GeV 20 GeV < p 4l < 50 GeV 0 < | y | < 0.4 0.4 < | y | < 0.8 T T 4l 4l 10 10 10 10 1 1 1 1 50 GeV < p 4l < 100 GeV 100 GeV < p 4l < 600 GeV 0.8 < | y | < 1.2 1.2 < | y | < 2.5 T T 4l 4l JHEP04(2019)048 10 10 10 10 1 1 1 1 100 200 400 600 900 100 200 400 600 900 100 200 400 600 900 100 200 400 600 900 m 4l [GeV] m 4l [GeV] (a) double-differential p4` T -m4` . (b) double-differential |y4` |-m4` . Figure 4. The leading sources of uncertainty in the measured cross-section after unfolding are given in percent as a function of (a) the four-lepton invariant mass in slices of p4` T and (b) the four- lepton invariant mass in slices of |y4` |. The “Unfolding” category includes the effect of the generator choice for q q̄ → 4` and the uncertainty due to the unfolding method itself, added in quadrature. The “Lepton” category comprises the lepton reconstruction and selection efficiencies as well as momentum resolution and scale uncertainties. “DD bkg” refers to the data-driven estimation used for the reducible background contribution. Uncertainty [%] Total Unfolding ATLAS 4µ 4µ ATLAS Theory Lumi. & Pile-Up s=13 TeV, 36.1 fb-1 Total Unfolding s=13 TeV, 36.1 fb-1 Lepton Data stat. Measured cross-section Measured cross-section DD bkg., MC stat. Theory Lumi. & Pile-Up Uncertainty [%] D ME < -1.4 D ME > -1.4 10 Lepton Data stat. DD bkg., MC stat. 1 4e 2e2µ 10 10 10 10 1 1 1 1 200 300 400 600 8001000 200 300 400 600 8001000 100 200 400 600 900 100 200 400 600 900 m 4l [GeV] m 4l [GeV] (a) double differential DME -m4` . (b) m4` per lepton flavour channel. Figure 5. The leading sources of uncertainty in the measured cross-section after unfolding are given in percent as a function of (a) the four-lepton invariant mass in slices of the DME discriminant and (b) the four-lepton invariant mass per final-state flavour channel. The “Unfolding” category includes the effect of the generator choice for q q̄ → 4` and the uncertainty due to the unfolding method itself, added in quadrature. The “Lepton” category comprises the lepton reconstruction and selection efficiencies as well as momentum resolution and scale uncertainties. “DD bkg” refers to the data-driven estimation used for the reducible background contribution. – 15 – Events / 10 GeV 3 Data H→ ZZ* 10 ATLAS s=13 TeV, 36.1 fb-1 qq→ ZZ(*) gg→ ZZ(*) Reducible ttV(V),VVV 102 10 1 JHEP04(2019)048 Observation / Prediction 1.5 1 0.5 80 100 150 200 300 500 700 1100 m 4l [GeV] Figure 6. Distribution of events passing the selection as a function of the four-lepton invariant mass m4` , where observed event yields (black dots) are compared with the total SM prediction. The ratio of the data to the prediction is given in the lower panel. The statistical uncertainty of the data is displayed with black error bars and the total uncertainty (including statistical and systematic sources) of the prediction is displayed with a grey hashed band. Furthermore, the predictions from Sherpa 2.2.2 and Powheg + Pythia 8 are in ex- cellent agreement. This gives confidence in the validity of the procedure used to reweight Powheg-Box events to NNLO QCD accuracy by applying m4` -based K-factors calculated with MATRIX [31–34]. It also indicates that, at least for this observable, an analogous re- weighting of Sherpa events is not required due to this generator’s intrinsic higher accuracy. The fixed-order NNLO QCD prediction by MATRIX shows an expected underestimation at and below the on-shell mZZ threshold. This underestimation is mainly due to missing real, wide-angle QED emission effects in events where both Z bosons are on-shell, and amounts to several tens of percent of the total population in the region just below the on-shell threshold [36]. For the Sherpa 2.2.2 and Powheg + Pythia 8 samples, QED effects are included from estimates taken from QED shower programs. Moreover, the fixed- order MATRIX prediction is equivalent to having leading-order precision for the continuum gg → 4` process and on-shell Higgs boson production, while the event generator samples include sizeable higher-order contributions. The predictions from Sherpa, Powheg-Box and MATRIX agree at the level of a few percent, outside the region of resonant Higgs boson production, if the comparison is performed prior to QED showering and without both the additional NLO electroweak corrections and the application of higher-order corrections to the gg → 4` contribution. – 16 – ATLAS Data H→ ZZ* ATLAS Data H→ ZZ* s=13 TeV, 36.1 fb-1 qq→ ZZ(*) gg→ ZZ(*) s=13 TeV, 36.1 fb-1 qq→ ZZ(*) gg→ ZZ(*) Reducible ttV(V),VVV Reducible ttV(V),VVV Observation / Prediction Observation / Prediction Events / 10 GeV Events / 10 GeV 0 < p 4l < 20 GeV 50 GeV < p 4l < 100 GeV 100 T 1.5 100 T 1.5 10 10 1 1 1 1 0.1 0.5 0.1 0.5 20 GeV < p 4l < 50 GeV 100 GeV < p 4l < 600 GeV 100 T 1.5 100 T 1.5 10 10 JHEP04(2019)048 1 1 1 1 0.1 0.5 0.1 0.5 100 200 300 500 900 100 200300 500 900 100 200 300 500 900 100 200300 500 900 m 4l [GeV] m 4l [GeV] Figure 7. Distribution of events passing the selection as a function of the four-lepton invariant mass m4` and of p4` T , where observed event yields (black dots) are compared with the total SM prediction. The m4` bins are shown along the horizontal axis, and the bins of p4` T are stacked vertically and labelled with the bin range values. The ratio of the data to the prediction as a function of m4` for each secondary variable bin is given in the panel to the right-hand side. The statistical uncertainty of the data is displayed with black error bars and the total uncertainty (including statistical and systematic sources) of the prediction is displayed with a grey hashed band. ATLAS Data H→ ZZ* ATLAS Data H→ ZZ* s=13 TeV, 36.1 fb-1 qq→ ZZ(*) gg→ ZZ(*) s=13 TeV, 36.1 fb-1 qq→ ZZ(*) gg→ ZZ(*) Reducible ttV(V),VVV Reducible ttV(V),VVV Observation / Prediction Observation / Prediction Events / 10 GeV Events / 10 GeV 0 < | y | < 0.4 0.8 < | y | < 1.2 100 4l 1.5 100 4l 1.5 10 10 1 1 1 1 0.1 0.5 0.1 0.5 0.4 < | y | < 0.8 1.2 < | y | < 2.5 4l 4l 100 1.5 100 1.5 10 10 1 1 1 1 0.1 0.5 0.1 0.5 100 200 300 500 900 100 200300 500 900 100 200 300 500 900 100 200300 500 900 m 4l [GeV] m 4l [GeV] Figure 8. Distribution of events passing the selection as a function of the four-lepton invariant mass m4` and of |y4` |, where observed event yields (black dots) are compared with the total SM prediction. The m4` bins are shown along the horizontal axis, and the bins of |y4` | are stacked vertically and labelled with the bin range values. The ratio of the data to the prediction as a function of m4` for each secondary variable bin is given in the panel to the right-hand side. The statistical uncertainty of the data is displayed with black error bars and the total uncertainty (including statistical and systematic sources) of the prediction is displayed with a grey hashed band. – 17 – ATLAS Data H→ ZZ* ATLAS Data H→ ZZ* s=13 TeV, 36.1 fb-1 qq→ ZZ(*) gg→ ZZ(*) s=13 TeV, 36.1 fb-1 qq→ ZZ(*) gg→ ZZ(*) Reducible ttV(V),VVV Reducible ttV(V),VVV Observation / Prediction Observation / Prediction Events / 10 GeV Events / 10 GeV D ME < -1.4 100 4µ 1.5 100 1.5 10 1 10 1 1 0.1 0.5 1 4e 100 1.5 0.1 0.5 10 1 D ME > -1.4 1 100 1.5 0.1 0.5 JHEP04(2019)048 10 2e2µ 100 1.5 1 1 10 1 1 0.1 0.5 0.1 0.5 200 300 500 1000 200 300 500 1000 100 200 300 500 900 100 200300 500 900 m 4l [GeV] m 4l [GeV] (a) double-differential DME –m4` . (b) m4` per lepton flavour channel. Figure 9. Distribution of events passing the selection as a function of the four-lepton invariant mass m4` and of DME (a) and the final-state lepton flavour channel (b), where observed event yields (black dots) are compared with the total SM prediction. The m4` bins are given along the horizontal axis, and the bins of the secondary variable are stacked vertically and labelled with the bin range values. The ratio of the data to the prediction as a function of m4` for each secondary variable bin is given in the panel to the right-hand side. The statistical uncertainty of the data is displayed with black error bars and the total uncertainty (including statistical and systematic sources) of the prediction is displayed with a grey hashed band. 9 Interpretations The measured particle-level differential and double-differential fiducial cross-sections can be interpreted to measure SM parameters and set limits on BSM contributions. To explore and demonstrate this potential, a range of interpretations are presented in this paper. The production rate of gg → 4` is extracted with respect to the SM prediction using the differential cross-section measured as a function of m4` . The Z → 4` branching fraction is estimated from the measured fiducial cross-section in the mass bin corresponding to mZ . Constraints on the rate of off-shell Higgs boson production (gg → H ∗ → 4`) are derived using the double-differential cross-section measured as a function of m4` and the DME discriminant, which greatly enhances sensitivity to this type of process. Constraints on modified couplings of the Higgs boson to top quarks and gluons in the off-shell region are also derived, using the measured differential cross-section as a function of m4` . All interpretations use a common statistical approach. A multivariate Gaussian like- lihood function is used to quantify the level of agreement between a given prediction and observed data simultaneously across all bins of a measurement, taking into account correl- ations due to bin migration. The χ2 function defining the exponential component of the likelihood takes the form: χ2 = (ydata − ypred )T C −1 (ydata − ypred ), – 18 – dσ /dm 4l [fb/GeV] ATLAS 1 s = 13 TeV, 36.1 fb-1 10−1 10−2 JHEP04(2019)048 Data Sherpa ⊕ NLO EW Powheg ⊕ NLO EW ⊕ NNLO QCD Prediction / Observation 10−3 Matrix fixed-order NNLO 3 1.5 102 10 1 0.5 80 100 200 300 400 500 1000 m 4l [GeV] Figure 10. Measured differential cross-section (black dots) compared with particle-level SM pre- dictions (coloured lines) for the m4` distribution. The total systematic plus statistical uncertainty of the measured cross-section is displayed as a grey band. Two SM predictions with different event generator samples for q q̄ → 4` (described in section 5) are shown with different line colours and styles. In addition, an unmodified NNLO-precision fixed-order calculation using the MATRIX program is shown with a grey histogram, to illustrate the effects of additional higher-order correc- tions and QED final state radiation included in the event generator predictions. The ratio of the particle-level MC predictions to the unfolded data is shown in the lower panel. where ydata is a vector of unfolded observed values in each of the distribution bins, ypred is a vector of the predicted values in each of the distribution bins, which is a function of the parameter of interest (POI) and nuisance parameters (NP), and C −1 is the inverse of the total covariance matrix for the prediction being tested. This covariance matrix is obtained by rescaling the covariance matrix resulting from unfolding the detector-level SM prediction, to account for the change in the predicted yield relative to the original prediction for the values of the POI and NP under consideration. Each element C(i, j) of the rescaled matrix corresponding to bins i and j can be expressed using the systematic, statistical and background components Csyst SM , C SM and C SM of the covariance matrix corresponding to stat bkg the SM prediction: q SM SM SM C(i, j) = Ri × Rj × Csyst (i, j) + (Ri × Rj ) × Cstat (i, j) + Cbkg (i, j), where Rk = Nkpred (POI, NP)/Nkpred (POI = SM, NP = 0) is the ratio of the predicted yield – 19 – Sherpa ⊕ NLO EW ATLAS Data Powheg ⊕ NLO EW ⊕ NNLO QCD -1 s = 13 TeV, 36.1 fb Matrix fixed-order NNLO dσ /dm 4l [fb/GeV] Prediction / Observation 1.5 10−1 1 10−2 −3 10 0.5 0 < p 4l < 20 GeV T 80 100 200 300 400 600 1000 100 200 300 400 600 1000 JHEP04(2019)048 10 −1 1.5 10− 2 1 −3 10 0.5 20 GeV < p 4l < 50 GeV T 80 100 200 300 400 600 1000 100 200 300 400 600 1000 m 4l [GeV] Sherpa ⊕ NLO EW ATLAS Data Powheg ⊕ NLO EW ⊕ NNLO QCD -1 s = 13 TeV, 36.1 fb Matrix fixed-order NNLO dσ /dm 4l [fb/GeV] Prediction / Observation 10−1 1.5 10−2 1 −3 10 0.5 50 GeV < p 4l < 100 GeV T 80 100 200 300 400 600 1000 100 200 300 400 600 1000 1.5 −2 10 1 −3 10 0.5 100 GeV < p 4l < 600 GeV T 80 100 200 300 400 600 1000 100 200 300 400 600 1000 m 4l [GeV] Figure 11. Measured differential cross-section (black dots) compared with particle-level SM pre- dictions (coloured lines) as a function of m4` in slices of p4` T . The total systematic plus statistical uncertainty of the measured cross-section is displayed as a grey band. Two SM predictions with different event generator samples for q q̄ → 4` (described in section 5) are shown with different line colours and styles. In addition, an unmodified NNLO-precision fixed-order calculation using the MATRIX program is shown with a grey histogram, to illustrate the effects of additional higher- order corrections and QED final state radiation included in the event generator predictions. The m4` bins are given along the horizontal axis, and the bins of the secondary variable are stacked vertically and labelled with the bin range values. The ratio of the particle-level MC predictions to the unfolded data as a function of m4` for each secondary variable bin is given in the panel to the right-hand side. – 20 – Sherpa ⊕ NLO EW ATLAS Data Powheg ⊕ NLO EW ⊕ NNLO QCD -1 s = 13 TeV, 36.1 fb Matrix fixed-order NNLO dσ /dm 4l [fb/GeV] Prediction / Observation 10−1 1.5 10−2 1 −3 10 0.5 0< y < 0.4 4l 80 100 200 300 400 600 1000 100 200 300 400 600 1000 JHEP04(2019)048 10− 1 1.5 10− 2 1 −3 10 0.5 0.4 < y < 0.8 4l 80 100 200 300 400 600 1000 100 200 300 400 600 1000 m 4l [GeV] Sherpa ⊕ NLO EW ATLAS Data Powheg ⊕ NLO EW ⊕ NNLO QCD -1 s = 13 TeV, 36.1 fb Matrix fixed-order NNLO dσ /dm 4l [fb/GeV] Prediction / Observation −1 10 1.5 10−2 1 −3 10 0.5 0.8 < y < 1.2 4l 80 100 200 300 400 600 1000 100 200 300 400 600 1000 1.5 10− 1 10− 2 1 −3 10 0.5 1.2 < y < 2.5 4l 80 100 200 300 400 600 1000 100 200 300 400 600 1000 m 4l [GeV] Figure 12. Measured differential cross-section (black dots) compared with particle-level SM pre- dictions (coloured lines) as a function of m4` in slices of |y4` |. The total systematic plus statistical uncertainty of the measured cross-section is displayed as a grey band. Two SM predictions with different event generator samples for q q̄ → 4` (described in section 5) are shown with different line colours and styles. In addition, an unmodified NNLO-precision fixed-order calculation using the MATRIX program is shown with a grey histogram, to illustrate the effects of additional higher- order corrections and QED final state radiation included in the event generator predictions. The m4` bins are given along the horizontal axis, and the bins of the secondary variable are stacked vertically and labelled with the bin range values. The ratio of the particle-level MC predictions to the unfolded data as a function of m4` for each secondary variable bin is given in the panel to the right-hand side. – 21 – ATLAS Data Sherpa ⊕ NLO EW -1 s = 13 TeV, 36.1 fb Powheg ⊕ NLO EW ⊕ NNLO QCD dσ /dm 4l [fb/GeV] Prediction / Observation 1 1.5 10−1 1 10−2 −3 0.5 10 D ME < -1.4 200 300 400 500 600 800 1000 200 300 400 500 600 800 1000 1.5 10− 2 JHEP04(2019)048 1 −3 10 0.5 D ME > -1.4 200 300 400 500 600 800 1000 200 300 400 500 600 800 1000 m 4l [GeV] Figure 13. Measured differential cross-section (black dots) compared with particle-level SM predic- tions (coloured lines) as a function of m4` in slices of the DME discriminant. The total systematic plus statistical uncertainty of the measured cross-section is displayed as a grey band. Two SM predictions with different generator samples for q q̄ → 4` (described in section 5) are shown with different line colours and styles. The m4` bins are given along the horizontal axis, and the bins of the secondary variable are stacked vertically and labelled with the bin range values. The ratio of the particle-level MC predictions to the unfolded data as a function of m4` for each secondary variable bin is given in the panel to the right-hand side. in bin k assuming the given values of the parameter of interest and nuisance parameters to the yield in bin k using the SM value of the POI and a nominal value of the NP. All sources of experimental uncertainty, including those related to the unfolding procedure itself, are included in the systematic covariance matrix. The background component includes any uncertainties in the estimated background subtracted prior to unfolding and does not vary with the POI or NP. Theoretical uncertainties in the predictions do not enter the covariance matrix but are modelled with a nuisance parameter for each of the shape and normalisation components, constrained with Gaussian probability density functions. Upper limits on the values of the parameters of interest are set using the CL s method [69] with a confidence level of 95%. Signal strength for gluon-induced 4` production. The best prediction for the fi- ducial cross-section for gluon-induced 4` production (gg → 4`) in the interval 180 GeV < m4` < 1200 GeV, where the Higgs resonance is not dominant, is approximately 6.5 fb, com- pared to a leading order MCFM prediction of 3.0 fb. The relative contribution of gg → 4` to the differential pp → 4` cross-section is greatest in the region 180 GeV < m4` . 400 GeV, contributing around 18% at m4` ∼ 200 GeV, as visible in figure 6. For a comparison with measured /σ SM the best theoretical prediction, the signal strength for this process, µgg = σgg→4` gg→4` , is extracted. The differential m4` distribution is used for this interpretation, as NLO QCD – 22 – Sherpa ⊕ NLO EW ATLAS Data Powheg ⊕ NLO EW ⊕ NNLO QCD s = 13 TeV, 36.1 fb-1 Matrix fixed-order NNLO dσ /dm 4l [fb/GeV] Prediction / Observation 10− 1 1.5 10− 2 1 −3 10 4µ 0.5 80 100 200 300 400 600 1000 100 200 300 400 600 1000 10−1 1.5 10−2 1 −3 10 0.5 4e JHEP04(2019)048 80 100 200 300 400 600 1000 100 200 300 400 600 1000 1.5 10− 1 1 10− 2 −3 2e2µ 0.5 10 80 100 200 300 400 600 1000 100 200 300 400 600 1000 m 4l [GeV] Figure 14. Measured differential cross-section (black dots) compared with particle-level SM pre- dictions (coloured lines) as a function of m4` for each final-state lepton flavour configuration. The total systematic plus statistical uncertainty of the measured cross-section is displayed as a grey band. Two SM predictions with different generator samples for q q̄ → 4` (described in section 5) are shown with different line colours and styles. In addition, an unmodified NNLO-precision fixed-order calculation using the MATRIX program is shown with a grey histogram, to illustrate the effects of additional higher-order corrections and QED final state radiation included in the event generator predictions. The m4` bins are given along the horizontal axis, and the bins of the secondary variable are stacked vertically and labelled with the bin range values. The ratio of the particle-level MC predictions to the unfolded data as a function of m4` for each secondary variable bin is given in the panel to the right-hand side. precision is available in the description of this variable. A likelihood scan is performed using the procedure outlined above. The contribution from q q̄ → 4` production is set to the theoretical prediction as described in section 5 and allowed to vary within the associ- ated theoretical uncertainties described in section 7 by means of nuisance parameters with Gaussian constraints. The best available simulation of gg → 4` as described in section 5 is scaled by the parameter of interest, µgg , and in addition also allowed to vary within the associated theoretical uncertainties. A signal strength µgg = 1.3 ± 0.5 is measured with an SM, LO QCD expected value of 1.0 ± 0.4. In addition, a signal strength µLO measured gg = σgg→4` /σgg→4` , is extracted relative to an uncorrected leading-order precision MCFM prediction of gg → 4` as µLO gg = 2.7 ± 0.9, with an expected value of 2.2 ± 0.9. This value can be compared √ with a previous ATLAS measurement of µLO gg = 2.4 ± 1.4 performed at s = 8 TeV [7]. In both cases, the uncertainty is dominated by data statistics. The largest systematic uncertainty contribution is the QCD scale choice in the q q̄ → 4` prediction, and is small compared to the statistical uncertainty. Consistent results were also obtained when us- ing the double-differential m4` –p4` T or m4` –y4` distributions and the m4` measurement per final-state flavour configuration, all of which showed comparable sensitivity. – 23 – Extraction of the Z → 4` branching fraction. The branching fraction of Z → 4` is extracted using the lowest m4` bin (75–100 GeV) in the unfolded m4` distribution shown in figure 10. This bin is dominated by single Z boson production (figure 1c), but there are minor non-resonant contributions from t-channel q q̄ production (figure 1a) and gg → ZZ (∗) (figure 1b). The measurement is performed in an extended phase space defined by values of the invariant mass of the four-lepton system m4` and the lowest dilepton invariant mass in the event, m`` , satisfying 80 < m4` < 100 GeV and m`` > 4 GeV. The branching fraction is then calculated as: Nfid × (1 − fnon-res ) BZ→4` = , σZ × Afid × L JHEP04(2019)048 where Nfid is the number of unfolded events in this bin, Afid is the fiducial acceptance, defined as the ratio of the events passing the fiducial selection to those in the extended phase space, σZ is the total cross-section for single Z production, L is the integrated luminosity, and fnon-res is the fraction of non-resonant events in the extended phase space, calculated using Powheg-Box. The acceptance (including the non-resonant contribution) is calculated using MC simulation as Afid = (4.75±0.02)% and the fraction of non-resonant events as fnon-res = (4.8 ± 0.5)%, where the uncertainty includes the statistical uncertainty of the samples used and the systematic uncertainty from the theoretical variations described in section 7. The branching fraction is measured to be BZ→4` = [4.70 ± 0.32(stat) ± 0.21(syst) ± 0.14(lumi)] × 10−6 using the measured value for σZ from ref. [70]. Here, the systematic uncertainty includes the systematic uncertainty of the measured σZ and the systematic uncertainty of the unfolded cross-section in the bin used for the measurement, as well as the uncertainty in Afid and fnon-res . As ref. [70] is based on 81 pb−1 of pp collision data taken during the 2015 LHC run while this measurement uses the full 2015–2016 ATLAS dataset comprising 36 fb−1 , all detector-related systematic uncertainties as well as the luminosity uncertainty of σZ are conservatively treated as uncorrelated with the equivalent uncertainties in the measured cross-section in the lowest m4` bin. This result is compared with previous dedicated measurements by the ATLAS [8] and CMS [6] collaborations in table 3. The largest contributing systematic uncertainties in this mass region come from lepton identification and reconstruction efficiencies, as shown in figure 3. The difference in systematic uncertainties compared to ref. [8] is due to the as- sumptions of non-correlation between uncertainties in the two contributing measurements discussed above. The larger statistical uncertainty compared to ref. [6] arises from an ac- ceptance which has not been fully optimised for this interpretation. Nevertheless, the final precision including all error sources allows this measurement to contribute an improvement in the total precision of the Z → 4` branching fraction. Constraint on off-shell Higgs boson signal strength. The double-differential dis- tribution for m4` –DME is used to constrain the off-shell Higgs production process at high mass (m4` >180 GeV), assuming that the contribution of the box diagram is as predicted – 24 – Measurement BZ→4` /10−6 √ ATLAS, s = 7 TeV and 8 TeV [8] 4.31±0.34(stat)±0.17(syst) √ CMS, s = 13 TeV [6] 4.83 +0.23 +0.32 −0.22 (stat) −0.29 (syst)±0.08(theo)±0.12(lumi) √ ATLAS, s = 13 TeV 4.70 ± 0.32(stat) ± 0.21(syst) ± 0.14(lumi) Table 3. Comparison of measurements for the Z → 4` branching fraction in the phase-space region 80 GeV < m4` < 100 GeV, m`` > 4 GeV. by the Standard Model. As in the extraction of the signal strength for gluon-induced JHEP04(2019)048 4` production, a likelihood scan is performed where the contribution of q q̄ → 4` is set to the Standard Model prediction and allowed to float within the associated theoretical uncertainties. The total yield from gg → 4` is then parameterised [9] as  q   q  q gg→4` gg→H ∗ →ZZ (∗) →4` gg→4`(box) gg→4` µOS µOS OS OS + µOS  N H = H − µH ×NSM + 1− µH ×NSM H ×NSM , where µOS SM H = σgg→H ∗ →4` /σgg→H ∗ →4` is the signal strength for the off-shell Higgs produc- gg→H →ZZ →4` ∗ (∗) tion process, the parameter of interest for this measurement. The yields NSM , gg→4`(box) gg→4` NSM , and NSM are those predicted by the Standard Model for only the off-shell Higgs production process, only the box diagram, and the total gg → 4` contribution in- cluding interference, respectively, and are set to the best available prediction as discussed in section 5. They are allowed to float within the associated theoretical uncertainties dis- cussed in section 7. The observed 95% CL upper limit on the signal strength obtained in this way is 6.5. This agrees with the expected 95% CL upper limit of 5.4 within the range of [4.2, 7.2] for ±1σ uncertainty. This extraction demonstrates the degree to which an interpretation of measured cross-sections can approach the precision of dedicated meas- urements performed at detector level. The result can be compared to the upper limit of 4.5 obtained by the dedicated detector-level measurement [9] in the 4` final state using the same dataset and the same model. The sensitivity of this interpretation is slightly lower in comparison, due to the restrictions the unfolding procedure imposes on the binning of observables, the DME discriminant in particular. Constraint on modified Higgs boson couplings. Finally, the detector-corrected four- lepton mass distribution is used to constrain possible BSM modifications of the couplings of the Higgs boson to top quarks (ct ) and gluons (cg , zero in the SM) [71]. On-shell rates for Higgs production via gluon-gluon fusion are only sensitive to |ct + cg |2 , but measurements at higher mass (> 180 GeV) can be used to probe these parameters independently, as the partonic centre-of-mass energy of the process becomes larger than the top-quark mass. This provides an interesting test of the off-shell behaviour beyond dedicated measurements based on the rare tt̄H production mode [72]. Again, the yield from q q̄ → 4` is set to the Standard Model prediction and allowed to float within the associated theoretical uncertainties, while the yield from gg → 4` is parameterised as a function of ct and cg using the procedure described in ref. [71]. The observed and expected 95% CL exclusion contours obtained – 25 – 10 cg Expected 95% CL ATLAS Observed 95% CL -1 ± 1σ s= 13 TeV, 36.1 fb ± 2σ 5 SM value 0 JHEP04(2019)048 −5 −10 −10 −5 0 5 10 ct Figure 15. Observed (solid) and expected (dashed) exclusion limits at 95% CL in the cg versus ct plane for modified tt̄H and ggH couplings. The uncertainties in the expected limit corresponding to one and two standard deviations are displayed as green and yellow bands respectively. The hollow circle denotes the tree-level SM values of the parameters: cg = 0 and ct = 1. using the CLs method [69] are shown in figure 15, and the expected limit has green and yellow bands indicating uncertainties of ±1σ and ±2σ. The parameter space which lies outside of the observed contour is excluded at 95% CL. Exclusion limits were also explored for a model of anomalous triple gauge couplings considered in a dedicated search region of the ATLAS on-shell ZZ → 4` measurement [5]. Here, it was found that the present detector-corrected analysis is far less sensitive. This is a general feature of cross-section measurement reinterpretations in terms of models with effects that appear in the very poorly populated tails of distributions: the statistical re- quirements of unfolding mean that bins will need to be wide in these regions, and therefore sensitivity will be decreased. 10 Conclusion The four-lepton mass distribution has been measured using 36.1 fb−1 of proton-proton col- √ lision data at a centre-of-mass energy of s = 13 TeV recorded with the ATLAS detector at the LHC. The measurement is made differentially in the invariant mass m4` of the four-lepton system, and double-differentially as a function of m4` versus the transverse momentum of the four-lepton system, the rapidity of the system, the matrix-element dis- criminant DME designed to isolate off-shell Higgs boson contributions, and the final state lepton flavour channel. The measurements are consistent with the predictions of the SM. All measurements made are readily reinterpretable in terms of improved SM calculations or additional BSM – 26 – scenarios. A range of example interpretations are presented to demonstrate and explore this potential. The signal strength of the gluon-gluon fusion production process is measured to be µgg = 1.3 ± 0.5 compared to an expected value of 1.0 ± 0.4. A value for the Z → 4` branching fraction of [4.70±0.32(stat)±0.25(syst)]×10−6 is obtained, consistent with existing measurements and exceeding the precision of previous ATLAS results. An upper limit on the signal strength for the off-shell Higgs production process of µOS H < 6.5 is obtained at 95% CL. Finally, limits on anomalous couplings of the Higgs boson to gluons and top quarks are derived. JHEP04(2019)048 Acknowledgments We thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Aus- tralia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, 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; MES of Russia and NRC KI, Russian Federation; JINR; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, CANARIE, CRC and Compute Canada, Canada; COST, ERC, ERDF, Horizon 2020, and Marie Sklodowska-Curie Actions, European Union; Inves- tissements d’ Avenir Labex and Idex, ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and GIF, Israel; CERCA Programme Generalitat de Catalunya, Spain; The Royal Society and Leverhulme Trust, United Kingdom. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (U.K.) and BNL (U.S.A.), the Tier-2 facilities worldwide and large non-WLCG resource providers. Ma- jor contributors of computing resources are listed in ref. [73]. Open Access. 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Gagnon107 , C. Galea27b , B. Galhardo137a,137c , E.J. Gallas132 , B.J. Gallop141 , P. Gallus139 , G. Galster39 , R. Gamboa Goni90 , K.K. Gan123 , S. Ganguly177 , J. Gao58a , Y. Gao88 , JHEP04(2019)048 Y.S. Gao150,n , C. Garcı́a171 , J.E. Garcı́a Navarro171 , J.A. Garcı́a Pascual15a , M. Garcia-Sciveres18 , R.W. Gardner36 , N. Garelli150 , S. Gargiulo50 , V. Garonne131 , K. Gasnikova44 , A. Gaudiello53b,53a , G. Gaudio68a , I.L. Gavrilenko108 , A. Gavrilyuk109 , C. Gay172 , G. Gaycken24 , E.N. Gazis10 , C.N.P. Gee141 , J. Geisen51 , M. Geisen97 , M.P. Geisler59a , C. Gemme53b , M.H. Genest56 , C. Geng103 , S. Gentile70a,70b , S. George91 , D. Gerbaudo14 , G. Gessner45 , S. Ghasemi148 , M. Ghasemi Bostanabad173 , M. Ghneimat24 , B. Giacobbe23b , S. Giagu70a,70b , N. Giangiacomi23b,23a , P. Giannetti69a , A. Giannini67a,67b , S.M. Gibson91 , M. Gignac143 , D. Gillberg33 , G. Gilles179 , D.M. Gingrich3,av , M.P. Giordani64a,64c , F.M. Giorgi23b , P.F. Giraud142 , P. Giromini57 , G. Giugliarelli64a,64c , D. Giugni66a , F. Giuli132 , M. Giulini59b , S. Gkaitatzis159 , I. Gkialas9,k , E.L. Gkougkousis14 , P. Gkountoumis10 , L.K. Gladilin111 , C. Glasman96 , J. Glatzer14 , P.C.F. Glaysher44 , A. Glazov44 , M. Goblirsch-Kolb26 , J. Godlewski82 , S. Goldfarb102 , T. Golling52 , D. Golubkov121 , A. Gomes137a,137b , R. Goncalves Gama51 , R. Gonçalo137a , G. Gonella50 , L. Gonella21 , A. Gongadze77 , F. Gonnella21 , J.L. Gonski57 , S. González de la Hoz171 , S. Gonzalez-Sevilla52 , L. Goossens35 , P.A. Gorbounov109 , H.A. Gordon29 , B. Gorini35 , E. Gorini65a,65b , A. Gorišek89 , A.T. Goshaw47 , C. Gössling45 , M.I. Gostkin77 , C.A. Gottardo24 , C.R. Goudet129 , D. Goujdami34c , A.G. Goussiou145 , N. Govender32b,c , C. Goy5 , E. Gozani157 , I. Grabowska-Bold81a , P.O.J. Gradin169 , E.C. Graham88 , J. Gramling168 , E. Gramstad131 , S. Grancagnolo19 , V. Gratchev135 , P.M. Gravila27f , F.G. Gravili65a,65b , C. Gray55 , H.M. Gray18 , Z.D. Greenwood93,al , C. Grefe24 , K. Gregersen94 , I.M. Gregor44 , P. Grenier150 , K. Grevtsov44 , N.A. Grieser125 , J. Griffiths8 , A.A. Grillo143 , K. Grimm150,b , S. Grinstein14,z , Ph. Gris37 , J.-F. Grivaz129 , S. Groh97 , E. Gross177 , J. Grosse-Knetter51 , G.C. Grossi93 , Z.J. Grout92 , C. Grud103 , A. Grummer116 , L. Guan103 , W. Guan178 , J. Guenther35 , A. Guerguichon129 , F. Guescini165a , D. Guest168 , R. Gugel50 , B. Gui123 , T. Guillemin5 , S. Guindon35 , U. Gul55 , C. Gumpert35 , J. Guo58c , W. Guo103 , Y. Guo58a,t , Z. Guo99 , R. Gupta44 , S. Gurbuz12c , G. Gustavino125 , B.J. Gutelman157 , P. Gutierrez125 , C. Gutschow92 , C. Guyot142 , M.P. Guzik81a , C. Gwenlan132 , C.B. Gwilliam88 , A. Haas122 , C. Haber18 , H.K. Hadavand8 , N. Haddad34e , A. Hadef58a , S. Hageböck24 , M. Hagihara166 , H. Hakobyan181,∗ , M. Haleem174 , J. Haley126 , G. Halladjian104 , G.D. Hallewell99 , K. Hamacher179 , P. Hamal127 , K. Hamano173 , A. Hamilton32a , G.N. Hamity146 , K. Han58a,ak , L. Han58a , S. Han15d , K. 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Herrmann112 , T. Herrmann46 , G. Herten50 , R. Hertenberger112 , L. Hervas35 , T.C. Herwig134 , G.G. Hesketh92 , N.P. Hessey165a , A. Higashida160 , S. Higashino79 , E. Higón-Rodriguez171 , K. Hildebrand36 , E. Hill173 , J.C. Hill31 , K.K. Hill29 , K.H. Hiller44 , S.J. Hillier21 , M. Hils46 , I. Hinchliffe18 , F. Hinterkeuser24 , M. Hirose130 , D. Hirschbuehl179 , B. Hiti89 , O. Hladik138 , D.R. Hlaluku32c , X. Hoad48 , J. Hobbs152 , N. Hod165a , M.C. Hodgkinson146 , A. Hoecker35 , M.R. Hoeferkamp116 , F. Hoenig112 , D. Hohn50 , D. Hohov129 , T.R. Holmes36 , M. Holzbock112 , M. Homann45 , B.H. Hommels31 , S. Honda166 , T. Honda79 , T.M. Hong136 , A. Hönle113 , B.H. Hooberman170 , W.H. Hopkins128 , Y. Horii115 , P. Horn46 , A.J. Horton149 , L.A. Horyn36 , J-Y. Hostachy56 , JHEP04(2019)048 A. Hostiuc145 , S. Hou155 , A. Hoummada34a , J. Howarth98 , J. Hoya86 , M. Hrabovsky127 , J. Hrdinka35 , I. Hristova19 , J. Hrivnac129 , A. Hrynevich106 , T. Hryn’ova5 , P.J. Hsu62 , S.-C. Hsu145 , Q. Hu29 , S. Hu58c , Y. Huang15a , Z. Hubacek139 , F. Hubaut99 , M. Huebner24 , F. Huegging24 , T.B. Huffman132 , M. Huhtinen35 , R.F.H. Hunter33 , P. Huo152 , A.M. Hupe33 , N. Huseynov77,af , J. Huston104 , J. Huth57 , R. Hyneman103 , G. Iacobucci52 , G. Iakovidis29 , I. Ibragimov148 , L. Iconomidou-Fayard129 , Z. Idrissi34e , P. Iengo35 , R. Ignazzi39 , O. Igonkina118,ab , R. Iguchi160 , T. Iizawa52 , Y. Ikegami79 , M. Ikeno79 , D. Iliadis159 , N. Ilic117 , F. Iltzsche46 , G. Introzzi68a,68b , M. Iodice72a , K. Iordanidou38 , V. Ippolito70a,70b , M.F. Isacson169 , N. Ishijima130 , M. Ishino160 , M. Ishitsuka162 , W. Islam126 , C. Issever132 , S. Istin157 , F. Ito166 , J.M. Iturbe Ponce61a , R. Iuppa73a,73b , A. Ivina177 , H. Iwasaki79 , J.M. Izen42 , V. Izzo67a , P. Jacka138 , P. Jackson1 , R.M. Jacobs24 , V. Jain2 , G. Jäkel179 , K.B. Jakobi97 , K. Jakobs50 , S. Jakobsen74 , T. Jakoubek138 , D.O. Jamin126 , R. Jansky52 , J. Janssen24 , M. Janus51 , P.A. Janus81a , G. Jarlskog94 , N. 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Kass123 , A. Kastanas43a,43b , Y. Kataoka160 , C. Kato58d,58c , J. Katzy44 , K. Kawade80 , K. Kawagoe85 , T. Kawamoto160 , G. Kawamura51 , E.F. Kay88 , V.F. Kazanin120b,120a , R. Keeler173 , R. Kehoe41 , J.S. Keller33 , E. Kellermann94 , J.J. Kempster21 , J. Kendrick21 , O. Kepka138 , S. Kersten179 , B.P. Kerševan89 , S. Ketabchi Haghighat164 , R.A. Keyes101 , M. Khader170 , F. Khalil-Zada13 , A. Khanov126 , A.G. Kharlamov120b,120a , T. Kharlamova120b,120a , E.E. Khoda172 , A. Khodinov163 , T.J. Khoo52 , E. Khramov77 , J. Khubua156b , S. Kido80 , M. Kiehn52 , C.R. Kilby91 , Y.K. Kim36 , N. Kimura64a,64c , O.M. Kind19 , B.T. King88 , D. Kirchmeier46 , J. Kirk141 , A.E. Kiryunin113 , T. Kishimoto160 , D. Kisielewska81a , V. Kitali44 , O. Kivernyk5 , E. Kladiva28b,∗ , T. Klapdor-Kleingrothaus50 , M.H. Klein103 , M. Klein88 , U. Klein88 , K. Kleinknecht97 , P. Klimek119 , A. Klimentov29 , T. Klingl24 , T. Klioutchnikova35 , F.F. Klitzner112 , P. Kluit118 , S. Kluth113 , E. Kneringer74 , E.B.F.G. Knoops99 , A. Knue50 , A. Kobayashi160 , D. Kobayashi85 , T. Kobayashi160 , M. Kobel46 , M. Kocian150 , P. Kodys140 , P.T. Koenig24 , T. Koffas33 , E. Koffeman118 , N.M. Köhler113 , T. Koi150 , M. Kolb59b , I. Koletsou5 , T. Kondo79 , N. Kondrashova58c , K. Köneke50 , A.C. König117 , T. Kono79 , R. Konoplich122,an , V. Konstantinides92 , N. Konstantinidis92 , B. Konya94 , – 37 – R. Kopeliansky63 , S. Koperny81a , K. Korcyl82 , K. Kordas159 , G. Koren158 , A. Korn92 , I. Korolkov14 , E.V. Korolkova146 , N. Korotkova111 , O. Kortner113 , S. Kortner113 , T. Kosek140 , V.V. Kostyukhin24 , A. Kotwal47 , A. Koulouris10 , A. Kourkoumeli-Charalampidi68a,68b , C. Kourkoumelis9 , E. Kourlitis146 , V. Kouskoura29 , A.B. Kowalewska82 , R. Kowalewski173 , T.Z. Kowalski81a , C. Kozakai160 , W. Kozanecki142 , A.S. Kozhin121 , V.A. Kramarenko111 , G. Kramberger89 , D. Krasnopevtsev58a , M.W. Krasny133 , A. Krasznahorkay35 , D. Krauss113 , J.A. Kremer81a , J. Kretzschmar88 , P. Krieger164 , K. Krizka18 , K. Kroeninger45 , H. Kroha113 , J. Kroll138 , J. Kroll134 , J. Krstic16 , U. Kruchonak77 , H. Krüger24 , N. Krumnack76 , M.C. Kruse47 , T. Kubota102 , S. Kuday4b , J.T. Kuechler179 , S. Kuehn35 , A. Kugel59a , T. Kuhl44 , V. Kukhtin77 , R. Kukla99 , Y. Kulchitsky105,aj , S. Kuleshov144b , Y.P. Kulinich170 , M. Kuna56 , T. Kunigo83 , A. Kupco138 , T. Kupfer45 , O. Kuprash158 , H. Kurashige80 , L.L. Kurchaninov165a , JHEP04(2019)048 Y.A. Kurochkin105 , A. Kurova110 , M.G. Kurth15d , E.S. Kuwertz35 , M. Kuze162 , J. Kvita127 , T. Kwan101 , A. La Rosa113 , J.L. La Rosa Navarro78d , L. La Rotonda40b,40a , F. La Ruffa40b,40a , C. Lacasta171 , F. Lacava70a,70b , J. Lacey44 , D.P.J. Lack98 , H. Lacker19 , D. Lacour133 , E. Ladygin77 , R. Lafaye5 , B. Laforge133 , T. Lagouri32c , S. Lai51 , S. Lammers63 , W. Lampl7 , E. Lançon29 , U. Landgraf50 , M.P.J. Landon90 , M.C. Lanfermann52 , V.S. Lang44 , J.C. Lange51 , R.J. Langenberg35 , A.J. Lankford168 , F. Lanni29 , K. Lantzsch24 , A. Lanza68a , A. Lapertosa53b,53a , S. Laplace133 , J.F. Laporte142 , T. Lari66a , F. Lasagni Manghi23b,23a , M. Lassnig35 , T.S. Lau61a , A. Laudrain129 , M. Lavorgna67a,67b , M. Lazzaroni66a,66b , B. Le102 , O. Le Dortz133 , E. Le Guirriec99 , E.P. Le Quilleuc142 , M. LeBlanc7 , T. LeCompte6 , F. Ledroit-Guillon56 , C.A. Lee29 , G.R. Lee144a , L. Lee57 , S.C. Lee155 , B. Lefebvre101 , M. Lefebvre173 , F. Legger112 , C. Leggett18 , K. Lehmann149 , N. Lehmann179 , G. Lehmann Miotto35 , W.A. Leight44 , A. Leisos159,w , M.A.L. Leite78d , R. Leitner140 , D. Lellouch177 , K.J.C. Leney92 , T. Lenz24 , B. Lenzi35 , R. Leone7 , S. Leone69a , C. Leonidopoulos48 , G. Lerner153 , C. Leroy107 , R. Les164 , A.A.J. Lesage142 , C.G. Lester31 , M. Levchenko135 , J. Levêque5 , D. Levin103 , L.J. Levinson177 , D. Lewis90 , B. Li15b , B. Li103 , C-Q. Li58a,am , H. Li58a , H. Li58b , L. Li58c , M. Li15a , Q. Li15d , Q.Y. Li58a , S. Li58d,58c , X. Li58c , Y. Li148 , Z. Liang15a , B. Liberti71a , A. Liblong164 , K. Lie61c , S. Liem118 , A. Limosani154 , C.Y. Lin31 , K. Lin104 , T.H. Lin97 , R.A. Linck63 , J.H. Lindon21 , B.E. Lindquist152 , A.L. Lionti52 , E. Lipeles134 , A. Lipniacka17 , M. Lisovyi59b , T.M. Liss170,as , A. Lister172 , A.M. Litke143 , J.D. Little8 , B. Liu76 , B.L Liu6 , H.B. Liu29 , H. Liu103 , J.B. Liu58a , J.K.K. Liu132 , K. Liu133 , M. Liu58a , P. Liu18 , Y. Liu15a , Y.L. Liu58a , Y.W. Liu58a , M. Livan68a,68b , A. Lleres56 , J. Llorente Merino15a , S.L. Lloyd90 , C.Y. Lo61b , F. Lo Sterzo41 , E.M. Lobodzinska44 , P. Loch7 , T. Lohse19 , K. Lohwasser146 , M. Lokajicek138 , J.D. Long170 , R.E. Long87 , L. Longo65a,65b , K.A. Looper123 , J.A. Lopez144b , I. Lopez Paz98 , A. Lopez Solis146 , J. Lorenz112 , N. Lorenzo Martinez5 , M. Losada22 , P.J. Lösel112 , A. Lösle50 , X. Lou44 , X. Lou15a , A. Lounis129 , J. Love6 , P.A. Love87 , J.J. Lozano Bahilo171 , H. Lu61a , M. Lu58a , Y.J. Lu62 , H.J. Lubatti145 , C. Luci70a,70b , A. Lucotte56 , C. Luedtke50 , F. Luehring63 , I. Luise133 , L. Luminari70a , B. Lund-Jensen151 , M.S. Lutz100 , P.M. Luzi133 , D. Lynn29 , R. Lysak138 , E. Lytken94 , F. Lyu15a , V. Lyubushkin77 , T. Lyubushkina77 , H. Ma29 , L.L. Ma58b , Y. Ma58b , G. Maccarrone49 , A. Macchiolo113 , C.M. Macdonald146 , J. Machado Miguens134,137b , D. Madaffari171 , R. Madar37 , W.F. Mader46 , A. Madsen44 , N. Madysa46 , J. Maeda80 , K. Maekawa160 , S. Maeland17 , T. Maeno29 , M. Maerker46 , A.S. Maevskiy111 , V. Magerl50 , D.J. Mahon38 , C. Maidantchik78b , T. Maier112 , A. Maio137a,137b,137d , O. Majersky28a , S. Majewski128 , Y. Makida79 , N. Makovec129 , B. Malaescu133 , Pa. Malecki82 , V.P. Maleev135 , F. Malek56 , U. Mallik75 , D. Malon6 , C. Malone31 , S. Maltezos10 , S. Malyukov35 , J. Mamuzic171 , G. Mancini49 , I. Mandić89 , J. Maneira137a , L. Manhaes de Andrade Filho78a , J. Manjarres Ramos46 , K.H. Mankinen94 , A. Mann112 , A. Manousos74 , B. Mansoulie142 , J.D. Mansour15a , S. Manzoni66a,66b , A. Marantis159 , G. Marceca30 , L. March52 , L. Marchese132 , G. Marchiori133 , M. Marcisovsky138 , C. Marcon94 , – 38 – C.A. Marin Tobon35 , M. Marjanovic37 , F. Marroquim78b , Z. Marshall18 , M.U.F Martensson169 , S. Marti-Garcia171 , C.B. Martin123 , T.A. Martin175 , V.J. Martin48 , B. Martin dit Latour17 , M. Martinez14,z , V.I. Martinez Outschoorn100 , S. Martin-Haugh141 , V.S. Martoiu27b , A.C. Martyniuk92 , A. Marzin35 , L. Masetti97 , T. Mashimo160 , R. Mashinistov108 , J. Masik98 , A.L. Maslennikov120b,120a , L.H. Mason102 , L. Massa71a,71b , P. Massarotti67a,67b , P. Mastrandrea152 , A. Mastroberardino40b,40a , T. Masubuchi160 , P. Mättig179 , J. Maurer27b , B. Maček89 , S.J. Maxfield88 , D.A. Maximov120b,120a , R. Mazini155 , I. Maznas159 , S.M. Mazza143 , G. Mc Goldrick164 , S.P. Mc Kee103 , A. McCarn41 , T.G. McCarthy113 , L.I. McClymont92 , W.P. McCormack18 , E.F. McDonald102 , J.A. Mcfayden35 , G. Mchedlidze51 , M.A. McKay41 , K.D. McLean173 , S.J. McMahon141 , P.C. McNamara102 , C.J. McNicol175 , R.A. McPherson173,ad , J.E. Mdhluli32c , Z.A. Meadows100 , S. Meehan145 , T.M. Megy50 , S. Mehlhase112 , A. Mehta88 , JHEP04(2019)048 T. Meideck56 , B. Meirose42 , D. Melini171,h , B.R. Mellado Garcia32c , J.D. Mellenthin51 , M. Melo28a , F. Meloni44 , A. Melzer24 , S.B. Menary98 , E.D. Mendes Gouveia137a , L. Meng88 , X.T. Meng103 , S. Menke113 , E. Meoni40b,40a , S. Mergelmeyer19 , S.A.M. Merkt136 , C. Merlassino20 , P. Mermod52 , L. Merola67a,67b , C. Meroni66a , F.S. Merritt36 , A. Messina70a,70b , J. Metcalfe6 , A.S. Mete168 , C. Meyer134 , J. Meyer157 , J-P. Meyer142 , H. Meyer Zu Theenhausen59a , F. Miano153 , R.P. Middleton141 , L. Mijović48 , G. Mikenberg177 , M. Mikestikova138 , M. Mikuž89 , M. Milesi102 , A. Milic164 , D.A. Millar90 , D.W. Miller36 , A. Milov177 , D.A. Milstead43a,43b , R.A. Mina150,r , A.A. Minaenko121 , M. Miñano Moya171 , I.A. Minashvili156b , A.I. Mincer122 , B. Mindur81a , M. Mineev77 , Y. Minegishi160 , Y. Ming178 , L.M. Mir14 , A. Mirto65a,65b , K.P. Mistry134 , T. Mitani176 , J. Mitrevski112 , V.A. Mitsou171 , M. Mittal58c , A. Miucci20 , P.S. Miyagawa146 , A. Mizukami79 , J.U. Mjörnmark94 , T. Mkrtchyan181 , M. Mlynarikova140 , T. Moa43a,43b , K. Mochizuki107 , P. Mogg50 , S. Mohapatra38 , S. Molander43a,43b , R. Moles-Valls24 , M.C. Mondragon104 , K. Mönig44 , J. Monk39 , E. Monnier99 , A. Montalbano149 , J. Montejo Berlingen35 , F. Monticelli86 , S. Monzani66a , N. Morange129 , D. Moreno22 , M. Moreno Llácer35 , P. Morettini53b , M. Morgenstern118 , S. Morgenstern46 , D. Mori149 , M. Morii57 , M. Morinaga176 , V. Morisbak131 , A.K. Morley35 , G. Mornacchi35 , A.P. Morris92 , J.D. Morris90 , L. Morvaj152 , P. Moschovakos10 , M. Mosidze156b , H.J. Moss146 , J. Moss150,o , K. Motohashi162 , R. Mount150 , E. Mountricha35 , E.J.W. Moyse100 , S. Muanza99 , F. Mueller113 , J. Mueller136 , R.S.P. Mueller112 , D. Muenstermann87 , G.A. Mullier94 , F.J. Munoz Sanchez98 , P. Murin28b , W.J. 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Ospanov58a , G. Otero y Garzon30 , H. Otono85 , M. Ouchrif34d , F. Ould-Saada131 , A. Ouraou142 , Q. Ouyang15a , M. Owen55 , R.E. Owen21 , V.E. Ozcan12c , N. Ozturk8 , J. Pacalt127 , H.A. Pacey31 , K. Pachal149 , A. Pacheco Pages14 , L. Pacheco Rodriguez142 , C. Padilla Aranda14 , S. Pagan Griso18 , M. Paganini180 , G. Palacino63 , S. Palazzo48 , S. Palestini35 , M. Palka81b , D. Pallin37 , I. Panagoulias10 , C.E. Pandini35 , J.G. Panduro Vazquez91 , P. Pani35 , G. Panizzo64a,64c , L. Paolozzi52 , T.D. Papadopoulou10 , K. Papageorgiou9,k , A. Paramonov6 , D. Paredes Hernandez61b , S.R. Paredes Saenz132 , B. Parida163 , T.H. Park33 , A.J. Parker87 , K.A. Parker44 , M.A. Parker31 , F. Parodi53b,53a , J.A. Parsons38 , U. Parzefall50 , V.R. Pascuzzi164 , JHEP04(2019)048 J.M.P. Pasner143 , E. Pasqualucci70a , S. Passaggio53b , F. Pastore91 , P. Pasuwan43a,43b , S. Pataraia97 , J.R. Pater98 , A. Pathak178,l , T. Pauly35 , B. Pearson113 , M. Pedersen131 , L. Pedraza Diaz117 , R. 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Ukegawa166 , G. Unal35 , A. Undrus29 , G. Unel168 , F.C. Ungaro102 , Y. Unno79 , K. Uno160 , J. Urban28b , P. Urquijo102 , P. Urrejola97 , G. Usai8 , J. Usui79 , L. Vacavant99 , V. Vacek139 , B. Vachon101 , K.O.H. Vadla131 , A. Vaidya92 , C. Valderanis112 , E. Valdes Santurio43a,43b , M. Valente52 , S. Valentinetti23b,23a , A. Valero171 , L. Valéry44 , R.A. Vallance21 , A. Vallier5 , J.A. Valls Ferrer171 , T.R. Van Daalen14 , H. Van der Graaf118 , P. Van Gemmeren6 , I. Van Vulpen118 , M. Vanadia71a,71b , W. Vandelli35 , A. Vaniachine163 , P. Vankov118 , R. Vari70a , E.W. Varnes7 , C. Varni53b,53a , T. Varol41 , D. Varouchas129 , K.E. Varvell154 , G.A. Vasquez144b , J.G. Vasquez180 , F. Vazeille37 , D. Vazquez Furelos14 , T. Vazquez Schroeder35 , J. Veatch51 , V. Vecchio72a,72b , L.M. Veloce164 , F. Veloso137a,137c , S. Veneziano70a , A. Ventura65a,65b , N. Venturi35 , V. Vercesi68a , M. Verducci72a,72b , C.M. Vergel Infante76 , C. Vergis24 , W. Verkerke118 , A.T. Vermeulen118 , J.C. Vermeulen118 , M.C. Vetterli149,av , N. Viaux Maira144b , M. Vicente Barreto Pinto52 , I. Vichou170,∗ , T. Vickey146 , O.E. Vickey Boeriu146 , G.H.A. Viehhauser132 , S. Viel18 , L. Vigani132 , M. Villa23b,23a , M. Villaplana Perez66a,66b , E. Vilucchi49 , M.G. Vincter33 , V.B. Vinogradov77 , A. Vishwakarma44 , C. Vittori23b,23a , I. Vivarelli153 , S. Vlachos10 , M. Vogel179 , P. Vokac139 , G. Volpi14 , S.E. von Buddenbrock32c , E. Von Toerne24 , V. Vorobel140 , K. Vorobev110 , M. Vos171 , J.H. Vossebeld88 , N. Vranjes16 , M. Vranjes Milosavljevic16 , V. Vrba139 , M. Vreeswijk118 , T. Šfiligoj89 , R. Vuillermet35 , I. Vukotic36 , T. Ženiš28a , L. Živković16 , P. Wagner24 , W. Wagner179 , J. Wagner-Kuhr112 , H. Wahlberg86 , S. Wahrmund46 , K. Wakamiya80 , V.M. Walbrecht113 , J. Walder87 , R. Walker112 , S.D. Walker91 , W. Walkowiak148 , – 42 – V. Wallangen43a,43b , A.M. Wang57 , C. Wang58b , F. Wang178 , H. Wang18 , H. Wang3 , J. Wang154 , J. Wang59b , P. Wang41 , Q. Wang125 , R.-J. Wang133 , R. Wang58a , R. Wang6 , S.M. Wang155 , W.T. Wang58a , W. Wang15c,ae , W.X. Wang58a,ae , Y. Wang58a,am , Z. Wang58c , C. Wanotayaroj44 , A. Warburton101 , C.P. Ward31 , D.R. Wardrope92 , A. Washbrook48 , P.M. Watkins21 , A.T. Watson21 , M.F. Watson21 , G. Watts145 , S. Watts98 , B.M. Waugh92 , A.F. Webb11 , S. Webb97 , C. Weber180 , M.S. Weber20 , S.A. Weber33 , S.M. Weber59a , A.R. Weidberg132 , J. Weingarten45 , M. Weirich97 , C. Weiser50 , P.S. Wells35 , T. Wenaus29 , T. Wengler35 , S. Wenig35 , N. Wermes24 , M.D. Werner76 , P. Werner35 , M. Wessels59a , T.D. Weston20 , K. Whalen128 , N.L. Whallon145 , A.M. Wharton87 , A.S. White103 , A. White8 , M.J. White1 , R. White144b , D. Whiteson168 , B.W. Whitmore87 , F.J. Wickens141 , W. Wiedenmann178 , M. Wielers141 , C. Wiglesworth39 , L.A.M. Wiik-Fuchs50 , F. Wilk98 , H.G. Wilkens35 , L.J. Wilkins91 , JHEP04(2019)048 H.H. Williams134 , S. Williams31 , C. Willis104 , S. Willocq100 , J.A. Wilson21 , I. Wingerter-Seez5 , E. Winkels153 , F. Winklmeier128 , O.J. Winston153 , B.T. Winter50 , M. Wittgen150 , M. Wobisch93 , A. Wolf97 , T.M.H. Wolf118 , R. Wolff99 , M.W. Wolter82 , H. Wolters137a,137c , V.W.S. Wong172 , N.L. Woods143 , S.D. Worm21 , B.K. Wosiek82 , K.W. Woźniak82 , K. Wraight55 , M. Wu36 , S.L. Wu178 , X. Wu52 , Y. Wu58a , T.R. Wyatt98 , B.M. Wynne48 , S. Xella39 , Z. Xi103 , L. Xia175 , D. Xu15a , H. Xu58a,e , L. Xu29 , T. Xu142 , W. Xu103 , Z. Xu150 , B. Yabsley154 , S. Yacoob32a , K. Yajima130 , D.P. Yallup92 , D. Yamaguchi162 , Y. Yamaguchi162 , A. Yamamoto79 , T. Yamanaka160 , F. Yamane80 , M. Yamatani160 , T. Yamazaki160 , Y. Yamazaki80 , Z. Yan25 , H.J. Yang58c,58d , H.T. Yang18 , S. Yang75 , Y. Yang160 , Z. Yang17 , W-M. Yao18 , Y.C. Yap44 , Y. Yasu79 , E. Yatsenko58c,58d , J. Ye41 , S. Ye29 , I. Yeletskikh77 , E. Yigitbasi25 , E. Yildirim97 , K. Yorita176 , K. Yoshihara134 , C.J.S. Young35 , C. Young150 , J. Yu8 , J. Yu76 , X. Yue59a , S.P.Y. Yuen24 , B. Zabinski82 , G. Zacharis10 , E. Zaffaroni52 , R. Zaidan14 , A.M. Zaitsev121,ao , T. Zakareishvili156b , N. Zakharchuk33 , J. Zalieckas17 , S. Zambito57 , D. Zanzi35 , D.R. Zaripovas55 , S.V. Zeißner45 , C. Zeitnitz179 , G. Zemaityte132 , J.C. Zeng170 , Q. Zeng150 , O. Zenin121 , D. Zerwas129 , M. Zgubič132 , D.F. Zhang58b , D. Zhang103 , F. Zhang178 , G. Zhang58a , G. Zhang15b , H. Zhang15c , J. Zhang6 , L. Zhang15c , L. Zhang58a , M. Zhang170 , P. Zhang15c , R. Zhang58a , R. Zhang24 , X. Zhang58b , Y. Zhang15d , Z. Zhang129 , P. Zhao47 , Y. Zhao58b,129,ak , Z. Zhao58a , A. Zhemchugov77 , Z. Zheng103 , D. Zhong170 , B. Zhou103 , C. Zhou178 , L. Zhou41 , M.S. Zhou15d , M. Zhou152 , N. Zhou58c , Y. Zhou7 , C.G. Zhu58b , H.L. Zhu58a , H. Zhu15a , J. Zhu103 , Y. Zhu58a , X. Zhuang15a , K. Zhukov108 , V. Zhulanov120b,120a , A. Zibell174 , D. Zieminska63 , N.I. Zimine77 , S. Zimmermann50 , Z. Zinonos113 , M. Ziolkowski148 , G. Zobernig178 , A. Zoccoli23b,23a , K. Zoch51 , T.G. Zorbas146 , R. Zou36 , M. Zur Nedden19 , L. Zwalinski35 1 Department of Physics, University of Adelaide, Adelaide; Australia 2 Physics Department, SUNY Albany, Albany NY; United States of America 3 Department of Physics, University of Alberta, Edmonton AB, Canada 4 (a) Department of Physics, Ankara University, Ankara;(b) Istanbul Aydin University, Istanbul;(c) Division of Physics, TOBB University of Economics and Technology, Ankara, Turkey 5 LAPP, Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS/IN2P3, Annecy, France 6 High Energy Physics Division, Argonne National Laboratory, Argonne IL, United States of America 7 Department of Physics, University of Arizona, Tucson AZ, United States of America 8 Department of Physics, University of Texas at Arlington, Arlington TX, United States of America 9 Physics Department, National and Kapodistrian University of Athens, Athens, Greece 10 Physics Department, National Technical University of Athens, Zografou, Greece 11 Department of Physics, University of Texas at Austin, Austin TX, United States of America 12 (a) Bahcesehir University, Faculty of Engineering and Natural Sciences, Istanbul; (b) Istanbul Bilgi University, Faculty of Engineering and Natural Sciences, Istanbul;(c) Department of Physics, Bogazici University, Istanbul;(d) Department of Physics Engineering, Gaziantep University, Gaziantep, Turkey – 43 – 13 Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan 14 Institut de Fı́sica d’Altes Energies (IFAE), Barcelona Institute of Science and Technology, Barcelona, Spain 15 (a) Institute of High Energy Physics, Chinese Academy of Sciences, Beijing;(b) Physics Department, Tsinghua University, Beijing;(c) Department of Physics, Nanjing University, Nanjing;(d) University of Chinese Academy of Science (UCAS), Beijing, China 16 Institute of Physics, University of Belgrade, Belgrade, Serbia 17 Department for Physics and Technology, University of Bergen, Bergen, Norway 18 Physics Division, Lawrence Berkeley National Laboratory and University of California, Berkeley CA, United States of America 19 Institut für Physik, Humboldt Universität zu Berlin, Berlin, Germany 20 Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics, JHEP04(2019)048 University of Bern, Bern, Switzerland 21 School of Physics and Astronomy, University of Birmingham, Birmingham, United Kingdom 22 Centro de Investigaciónes, Universidad Antonio Nariño, Bogota, Colombia 23 (a) Dipartimento di Fisica e Astronomia, Università di Bologna, Bologna; (b) INFN Sezione di Bologna, Italy 24 Physikalisches Institut, Universität Bonn, Bonn, Germany 25 Department of Physics, Boston University, Boston MA, United States of America 26 Department of Physics, Brandeis University, Waltham MA, United States of America 27 (a) Transilvania University of Brasov, Brasov;(b) Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest;(c) Department of Physics, Alexandru Ioan Cuza University of Iasi, Iasi;(d) National Institute for Research and Development of Isotopic and Molecular Technologies, Physics Department, Cluj-Napoca;(e) University Politehnica Bucharest, Bucharest;(f ) West University in Timisoara, Timisoara, Romania 28 (a) Faculty of Mathematics, Physics and Informatics, Comenius University, Bratislava;(b) Department of Subnuclear Physics, Institute of Experimental Physics of the Slovak Academy of Sciences, Kosice, Slovak Republic 29 Physics Department, Brookhaven National Laboratory, Upton NY, United States of America 30 Departamento de Fı́sica, Universidad de Buenos Aires, Buenos Aires, Argentina 31 Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom 32 (a) Department of Physics, University of Cape Town, Cape Town;(b) Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg;(c) School of Physics, University of the Witwatersrand, Johannesburg, South Africa 33 Department of Physics, Carleton University, Ottawa ON, Canada 34 (a) Faculté des Sciences Ain Chock, Réseau Universitaire de Physique des Hautes Energies — Université Hassan II, Casablanca;(b) Centre National de l’Energie des Sciences Techniques Nucleaires (CNESTEN), Rabat;(c) Faculté des Sciences Semlalia, Université Cadi Ayyad, LPHEA-Marrakech;(d) Faculté des Sciences, Université Mohamed Premier and LPTPM, Oujda;(e) Faculté des sciences, Université Mohammed V, Rabat, Morocco 35 CERN, Geneva, Switzerland 36 Enrico Fermi Institute, University of Chicago, Chicago IL, United States of America 37 LPC, Université Clermont Auvergne, CNRS/IN2P3, Clermont-Ferrand, France 38 Nevis Laboratory, Columbia University, Irvington NY, United States of America 39 Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark 40 (a) Dipartimento di Fisica, Università della Calabria, Rende;(b) INFN Gruppo Collegato di Cosenza, Laboratori Nazionali di Frascati, Italy 41 Physics Department, Southern Methodist University, Dallas TX, United States of America 42 Physics Department, University of Texas at Dallas, Richardson TX, United States of America 43 (a) Department of Physics, Stockholm University;(b) Oskar Klein Centre, Stockholm, Sweden 44 Deutsches Elektronen-Synchrotron DESY, Hamburg and Zeuthen, Germany 45 Lehrstuhl für Experimentelle Physik IV, Technische Universität Dortmund, Dortmund, Germany – 44 – 46 Institut für Kern und Teilchenphysik, Technische Universität Dresden, Dresden, Germany 47 Department of Physics, Duke University, Durham NC, United States of America 48 SUPA — School of Physics and Astronomy, University of Edinburgh, Edinburgh, United Kingdom 49 INFN e Laboratori Nazionali di Frascati, Frascati, Italy 50 Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany 51 II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen, Germany 52 Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève, Switzerland 53 (a) Dipartimento di Fisica, Università di Genova, Genova;(b) INFN Sezione di Genova, Italy 54 II. Physikalisches Institut, Justus-Liebig-Universität Giessen, Giessen, Germany 55 SUPA — School of Physics and Astronomy, University of Glasgow, Glasgow, United Kingdom 56 LPSC, Université Grenoble Alpes, CNRS/IN2P3, Grenoble INP, Grenoble, France 57 Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge MA, United States JHEP04(2019)048 of America 58 (a) Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei;(b) Institute of Frontier and Interdisciplinary Science and Key Laboratory of Particle Physics and Particle Irradiation (MOE), Shandong University, Qingdao;(c) School of Physics and Astronomy, Shanghai Jiao Tong University, KLPPAC-MoE, SKLPPC, Shanghai;(d) Tsung-Dao Lee Institute, Shanghai, China 59 (a) Kirchhoff-Institut für Physik, Ruprecht-Karls-Universität Heidelberg, Heidelberg; (b) Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg, Germany 60 Faculty of Applied Information Science, Hiroshima Institute of Technology, Hiroshima, Japan 61 (a) Department of Physics, Chinese University of Hong Kong, Shatin, N.T., Hong Kong;(b) Department of Physics, University of Hong Kong, Hong Kong;(c) Department of Physics and Institute for Advanced Study, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China 62 Department of Physics, National Tsing Hua University, Hsinchu, Taiwan 63 Department of Physics, Indiana University, Bloomington IN, United States of America 64 (a) INFN Gruppo Collegato di Udine, Sezione di Trieste, Udine;(b) ICTP, Trieste;(c) Dipartimento di Chimica, Fisica e Ambiente, Università di Udine, Udine, Italy 65 (a) INFN Sezione di Lecce;(b) Dipartimento di Matematica e Fisica, Università del Salento, Lecce, Italy 66 (a) INFN Sezione di Milano;(b) Dipartimento di Fisica, Università di Milano, Milano, Italy 67 (a) INFN Sezione di Napoli;(b) Dipartimento di Fisica, Università di Napoli, Napoli, Italy 68 (a) INFN Sezione di Pavia;(b) Dipartimento di Fisica, Università di Pavia, Pavia, Italy 69 (a) INFN Sezione di Pisa;(b) Dipartimento di Fisica E. Fermi, Università di Pisa, Pisa, Italy 70 (a) INFN Sezione di Roma;(b) Dipartimento di Fisica, Sapienza Università di Roma, Roma, Italy 71 (a) INFN Sezione di Roma Tor Vergata;(b) Dipartimento di Fisica, Università di Roma Tor Vergata, Roma, Italy 72 (a) INFN Sezione di Roma Tre;(b) Dipartimento di Matematica e Fisica, Università Roma Tre, Roma, Italy 73 (a) INFN-TIFPA;(b) Università degli Studi di Trento, Trento, Italy 74 Institut für Astro und Teilchenphysik, Leopold-Franzens-Universität, Innsbruck, Austria 75 University of Iowa, Iowa City IA, United States of America 76 Department of Physics and Astronomy, Iowa State University, Ames IA, United States of America 77 Joint Institute for Nuclear Research, Dubna, Russia 78 (a) Departamento de Engenharia Elétrica, Universidade Federal de Juiz de Fora (UFJF), Juiz de Fora;(b) Universidade Federal do Rio De Janeiro COPPE/EE/IF, Rio de Janeiro; (c) Universidade Federal de São João del Rei (UFSJ), São João del Rei;(d) Instituto de Fı́sica, Universidade de São Paulo, São Paulo, Brazil 79 KEK, High Energy Accelerator Research Organization, Tsukuba, Japan 80 Graduate School of Science, Kobe University, Kobe, Japan 81 (a) AGH University of Science and Technology, Faculty of Physics and Applied Computer Science, Krakow;(b) Marian Smoluchowski Institute of Physics, Jagiellonian University, Krakow, Poland – 45 – 82 Institute of Nuclear Physics Polish Academy of Sciences, Krakow, Poland 83 Faculty of Science, Kyoto University, Kyoto, Japan 84 Kyoto University of Education, Kyoto, Japan 85 Research Center for Advanced Particle Physics and Department of Physics, Kyushu University, Fukuoka, Japan 86 Instituto de Fı́sica La Plata, Universidad Nacional de La Plata and CONICET, La Plata, Argentina 87 Physics Department, Lancaster University, Lancaster, United Kingdom 88 Oliver Lodge Laboratory, University of Liverpool, Liverpool, United Kingdom 89 Department of Experimental Particle Physics, Jožef Stefan Institute and Department of Physics, University of Ljubljana, Ljubljana, Slovenia 90 School of Physics and Astronomy, Queen Mary University of London, London, United Kingdom 91 Department of Physics, Royal Holloway University of London, Egham, United Kingdom JHEP04(2019)048 92 Department of Physics and Astronomy, University College London, London, United Kingdom 93 Louisiana Tech University, Ruston LA, United States of America 94 Fysiska institutionen, Lunds universitet, Lund, Sweden 95 Centre de Calcul de l’Institut National de Physique Nucléaire et de Physique des Particules (IN2P3), Villeurbanne, France 96 Departamento de Fı́sica Teorica C-15 and CIAFF, Universidad Autónoma de Madrid, Madrid, Spain 97 Institut für Physik, Universität Mainz, Mainz, Germany 98 School of Physics and Astronomy, University of Manchester, Manchester, United Kingdom 99 CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille, France 100 Department of Physics, University of Massachusetts, Amherst MA, United States of America 101 Department of Physics, McGill University, Montreal QC, Canada 102 School of Physics, University of Melbourne, Victoria, Australia 103 Department of Physics, University of Michigan, Ann Arbor MI, United States of America 104 Department of Physics and Astronomy, Michigan State University, East Lansing MI, United States of America 105 B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk, Belarus 106 Research Institute for Nuclear Problems of Byelorussian State University, Minsk, Belarus 107 Group of Particle Physics, University of Montreal, Montreal QC, Canada 108 P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow, Russia 109 Institute for Theoretical and Experimental Physics of the National Research Centre Kurchatov Institute, Moscow, Russia 110 National Research Nuclear University MEPhI, Moscow, Russia 111 D.V. Skobeltsyn Institute of Nuclear Physics, M.V. Lomonosov Moscow State University, Moscow, Russia 112 Fakultät für Physik, Ludwig-Maximilians-Universität München, München, Germany 113 Max-Planck-Institut für Physik (Werner-Heisenberg-Institut), München, Germany 114 Nagasaki Institute of Applied Science, Nagasaki, Japan 115 Graduate School of Science and Kobayashi-Maskawa Institute, Nagoya University, Nagoya, Japan 116 Department of Physics and Astronomy, University of New Mexico, Albuquerque NM, United States of America 117 Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen, Netherlands 118 Nikhef National Institute for Subatomic Physics and University of Amsterdam, Amsterdam, Netherlands 119 Department of Physics, Northern Illinois University, DeKalb IL, United States of America 120 (a) Budker Institute of Nuclear Physics and NSU, SB RAS, Novosibirsk;(b) Novosibirsk State University Novosibirsk, Russia 121 Institute for High Energy Physics of the National Research Centre Kurchatov Institute, Protvino, Russia – 46 – 122 Department of Physics, New York University, New York NY, United States of America 123 Ohio State University, Columbus OH, United States of America 124 Faculty of Science, Okayama University, Okayama, Japan 125 Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman OK, United States of America 126 Department of Physics, Oklahoma State University, Stillwater OK, United States of America 127 Palacký University, RCPTM, Joint Laboratory of Optics, Olomouc, Czech Republic 128 Center for High Energy Physics, University of Oregon, Eugene OR, United States of America 129 LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay, France 130 Graduate School of Science, Osaka University, Osaka, Japan 131 Department of Physics, University of Oslo, Oslo, Norway 132 Department of Physics, Oxford University, Oxford, United Kingdom JHEP04(2019)048 133 LPNHE, Sorbonne Université, Paris Diderot Sorbonne Paris Cité, CNRS/IN2P3, Paris, France 134 Department of Physics, University of Pennsylvania, Philadelphia PA, United States of America 135 Konstantinov Nuclear Physics Institute of National Research Centre “Kurchatov Institute”, PNPI, St. Petersburg, Russia 136 Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh PA, United States of America 137 (a) Laboratório de Instrumentação e Fı́sica Experimental de Partı́culas — LIP; (b) Departamento de Fı́sica, Faculdade de Ciências, Universidade de Lisboa, Lisboa; (c) Departamento de Fı́sica, Universidade de Coimbra, Coimbra;(d) Centro de Fı́sica Nuclear da Universidade de Lisboa, Lisboa;(e) Departamento de Fı́sica, Universidade do Minho, Braga;(f ) Departamento de Fı́sica Teorica y del Cosmos, Universidad de Granada, Granada (Spain); (g) Dep Fı́sica and CEFITEC of Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal 138 Institute of Physics of the Czech Academy of Sciences, Prague, Czech Republic 139 Czech Technical University in Prague, Prague, Czech Republic 140 Charles University, Faculty of Mathematics and Physics, Prague, Czech Republic 141 Particle Physics Department, Rutherford Appleton Laboratory, Didcot, United Kingdom 142 IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France 143 Santa Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz CA, United States of America 144 (a) Departamento de Fı́sica, Pontificia Universidad Católica de Chile, Santiago; (b) Departamento de Fı́sica, Universidad Técnica Federico Santa Marı́a, Valparaı́so, Chile 145 Department of Physics, University of Washington, Seattle WA, United States of America 146 Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom 147 Department of Physics, Shinshu University, Nagano, Japan 148 Department Physik, Universität Siegen, Siegen, Germany 149 Department of Physics, Simon Fraser University, Burnaby BC, Canada 150 SLAC National Accelerator Laboratory, Stanford CA, United States of America 151 Physics Department, Royal Institute of Technology, Stockholm, Sweden 152 Departments of Physics and Astronomy, Stony Brook University, Stony Brook NY, United States of America 153 Department of Physics and Astronomy, University of Sussex, Brighton, United Kingdom 154 School of Physics, University of Sydney, Sydney, Australia 155 Institute of Physics, Academia Sinica, Taipei, Taiwan 156 (a) E. Andronikashvili Institute of Physics, Iv. Javakhishvili Tbilisi State University, Tbilisi; (b) High Energy Physics Institute, Tbilisi State University, Tbilisi, Georgia 157 Department of Physics, Technion, Israel Institute of Technology, Haifa, Israel 158 Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv University, Tel Aviv, Israel 159 Department of Physics, Aristotle University of Thessaloniki, Thessaloniki, Greece 160 International Center for Elementary Particle Physics and Department of Physics, University of Tokyo, Tokyo, Japan – 47 – 161 Graduate School of Science and Technology, Tokyo Metropolitan University, Tokyo, Japan 162 Department of Physics, Tokyo Institute of Technology, Tokyo, Japan 163 Tomsk State University, Tomsk, Russia 164 Department of Physics, University of Toronto, Toronto ON, Canada 165 (a) TRIUMF, Vancouver BC;(b) Department of Physics and Astronomy, York University, Toronto ON, Canada 166 Division of Physics and Tomonaga Center for the History of the Universe, Faculty of Pure and Applied Sciences, University of Tsukuba, Tsukuba, Japan 167 Department of Physics and Astronomy, Tufts University, Medford MA, United States of America 168 Department of Physics and Astronomy, University of California Irvine, Irvine CA, United States of America 169 Department of Physics and Astronomy, University of Uppsala, Uppsala, Sweden JHEP04(2019)048 170 Department of Physics, University of Illinois, Urbana IL, United States of America 171 Instituto de Fı́sica Corpuscular (IFIC), Centro Mixto Universidad de Valencia — CSIC, Valencia, Spain 172 Department of Physics, University of British Columbia, Vancouver BC, Canada 173 Department of Physics and Astronomy, University of Victoria, Victoria BC, Canada 174 Fakultät für Physik und Astronomie, Julius-Maximilians-Universität Würzburg, Würzburg, Germany 175 Department of Physics, University of Warwick, Coventry, United Kingdom 176 Waseda University, Tokyo, Japan 177 Department of Particle Physics, Weizmann Institute of Science, Rehovot, Israel 178 Department of Physics, University of Wisconsin, Madison WI, United States of America 179 Fakultät für Mathematik und Naturwissenschaften, Fachgruppe Physik, Bergische Universität Wuppertal, Wuppertal, Germany 180 Department of Physics, Yale University, New Haven CT, United States of America 181 Yerevan Physics Institute, Yerevan, Armenia a Also at Borough of Manhattan Community College, City University of New York, NY, United States of America b Also at California State University, East Bay, United States of America c Also at Centre for High Performance Computing, CSIR Campus, Rosebank, Cape Town, South Africa d Also at CERN, Geneva, Switzerland e Also at CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille, France f Also at Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève, Switzerland g Also at Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona, Spain h Also at Departamento de Fı́sica Teorica y del Cosmos, Universidad de Granada, Granada (Spain), Spain i Also at Departamento de Fı́sica, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal j Also at Department of Applied Physics and Astronomy, University of Sharjah, Sharjah, United Arab Emirates k Also at Department of Financial and Management Engineering, University of the Aegean, Chios, Greece l Also at Department of Physics and Astronomy, University of Louisville, Louisville, KY, United States of America m Also at Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom n Also at Department of Physics, California State University, Fresno CA, United States of America o Also at Department of Physics, California State University, Sacramento CA, United States of America – 48 – p Also at Department of Physics, King’s College London, London, United Kingdom q Also at Department of Physics, St. Petersburg State Polytechnical University, St. Petersburg, Russia r Also at Department of Physics, Stanford University, United States of America s Also at Department of Physics, University of Fribourg, Fribourg, Switzerland t Also at Department of Physics, University of Michigan, Ann Arbor MI, United States of America u Also at Giresun University, Faculty of Engineering, Giresun, Turkey v Also at Graduate School of Science, Osaka University, Osaka, Japan w Also at Hellenic Open University, Patras, Greece x Also at Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest, Romania y Also at II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen, Germany z Also at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona, Spain aa Also at Institut für Experimentalphysik, Universität Hamburg, Hamburg, Germany JHEP04(2019)048 ab Also at Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen, Netherlands ac Also at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest, Hungary ad Also at Institute of Particle Physics (IPP), Canada ae Also at Institute of Physics, Academia Sinica, Taipei, Taiwan af Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan ag Also at Institute of Theoretical Physics, Ilia State University, Tbilisi, Georgia ah Also at Instituto de Fı́sica Teórica de la Universidad Autónoma de Madrid, Spain ai Also at Istanbul University, Department of Physics, Istanbul, Turkey aj Also at Joint Institute for Nuclear Research, Dubna, Russia ak Also at LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay, France al Also at Louisiana Tech University, Ruston LA, United States of America am Also at LPNHE, Sorbonne Université, Paris Diderot Sorbonne Paris Cité, CNRS/IN2P3, Paris, France an Also at Manhattan College, New York NY, United States of America ao Also at Moscow Institute of Physics and Technology State University, Dolgoprudny, Russia ap Also at National Research Nuclear University MEPhI, Moscow, Russia aq Also at Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany ar Also at School of Physics, Sun Yat-sen University, Guangzhou, China as Also at The City College of New York, New York NY, United States of America at Also at The Collaborative Innovation Center of Quantum Matter (CICQM), Beijing, China au Also at Tomsk State University, Tomsk, and Moscow Institute of Physics and Technology State University, Dolgoprudny, Russia av Also at TRIUMF, Vancouver BC, Canada aw Also at Universita di Napoli Parthenope, Napoli, Italy ∗ Deceased – 49 –