# Search for squarks and gluinos in events with an isolated lepton, jets, and missing transverse momentum at $\sqrt{s}$ = 13 TeV with the ATLAS detector

M. Aaboud et al. *

(ATLAS Collaboration)

(Received 29 August 2017; published 26 December 2017)

The results of a search for squarks and gluinos in final states with an isolated electron or muon, multiple jets and large missing transverse momentum using proton-proton collision data at a center-of-mass energy of $\sqrt{s}$ = 13 TeV are presented. The data set used was recorded during 2015 and 2016 by the ATLAS experiment at the Large Hadron Collider and corresponds to an integrated luminosity of 36.1 fb$^{-1}$. No significant excess beyond the expected background is found. Exclusion limits at 95% confidence level are set in a number of supersymmetric scenarios, reaching masses up to 2.1 TeV for gluino pair production and up to 1.25 TeV for squark pair production.

DOI: 10.1103/PhysRevD.96.112010

## I. INTRODUCTION

Supersymmetry (SUSY) [1–6] is a theoretical framework of physics beyond the Standard Model (SM) which predicts for each SM particle the existence of a supersymmetric partner (sparticle) differing by half a unit of spin. The partner particles of the SM fermions (quarks and leptons) are the scalar squarks ($\tilde{q}$) and sleptons ($\tilde{e}$). In the boson sector, the supersymmetric partner of the gluon is the fermionic gluino ($\tilde{g}$), whereas the supersymmetric partners of the Higgs (higgsinos) and the electroweak gauge bosons (winos and bino) mix to form charged mass eigenstates (charginos) and neutral mass eigenstates (neutralinos). In the minimal supersymmetric extension of the Standard Model (MSSM) [7,8] two scalar Higgs doublets along with their higgsino partners are necessary, resulting in four chargino states ($\tilde{\chi}_{1,2}^{\pm}$) and four neutralinos ($\tilde{\chi}_{1,2,3,4}^{0}$). SUSY addresses the SM hierarchy problem [9–12] provided that the masses of at least some of the supersymmetric particles (most notably the higgsinos, the top squarks and the gluinos) are near the TeV scale.

In R-parity-conserving SUSY [13], gluinos or squarks are pair produced at the Large Hadron Collider (LHC) via the strong interaction and decay either directly or via intermediate states to the lightest supersymmetric particle (LSP). The LSP, which is assumed to be the lightest neutralino ($\tilde{\chi}_{1}^{0}$) in this paper, is stable and weakly interacting, making it a candidate for dark matter [14,15].

The decay topologies targeted in this paper are largely inspired by decay chains that could be realized in the pMSSM scenario, which is a two-dimensional subspace of

the 19-parameter phenomenological minimal supersymmetric Standard Model (pMSSM) [16,17]. Four SUSY models with gluino or squark pair production and different decay topologies are considered. The first two models, referred to as the gluino and squark one-step models for the rest of this paper, are SUSY simplified models [18–20] in which pair-produced gluinos or squarks decay via the lightest chargino ($\tilde{\chi}_{1}^{\pm}$) to the LSP. In the model with gluino production, the gluino decays to the lightest chargino and two SM quarks via $\tilde{g} \rightarrow q\bar{q}'\tilde{\chi}_{1}^{\pm}$, as illustrated in Fig. 1 (left). The gluino decay is assumed to proceed via virtual first- and second-generation squarks, hence no bottom or top quarks are produced in the simplified model. The chargino then decays to the LSP by emitting an on- or off-shell W boson, $\tilde{\chi}_{1}^{\pm} \rightarrow W^{(*)\pm}\tilde{\chi}_{1}^{0}$, depending on the available phase space. In the MSSM this decay chain is realized when the gluino decays, via a virtual squark that is the partner particle of the left-handed SM quark, to the chargino with a dominant wino component. In the squark production model, the squark decays to the chargino via $\tilde{q} \rightarrow q'\tilde{\chi}_{1}^{\pm}$, followed by the same chargino decay, as illustrated in Fig. 1 (middle).

The third model, referred to as the gluino two-step model for the rest of this paper, assumes gluino pair production with a subsequent decay to the chargino via $\tilde{g} \rightarrow q\bar{q}'\tilde{\chi}^{\pm}$. The chargino then decays via emission of an on- or off-shell W boson to the second lightest neutralino according to $\tilde{\chi}^{\pm} \rightarrow W^{\pm}\tilde{\chi}_{2}^{0}$. In the last step of the cascade, the second lightest neutralino decays via emission of a Z boson to the LSP. The decay chain of this signal model is illustrated in Fig. 1 (right). The model is used as a proxy for SUSY scenarios with many decay products in the final state. Within the MSSM, additional decay modes lead to a significant reduction in the cross section times branching fraction for this particular decay.

Finally, the fourth set of SUSY models, the pMSSM model, is selected to have a bino-dominated neutralino as

<footnote>*Full author list given at the end of the article.</footnote>
<figure><img src="image_1.png" /><figcaption>FIG. 1. The decay topologies of the simplified signal models considered in this search: gluino one-step (left), squark one-step (middle) and gluino two-step (right).</figcaption></figure>

the LSP, kinematically accessible gluinos, and a higgsino-dominated multiplet at intermediate mass. The higgsino multiplet contains two neutralinos (the $\tilde{\chi}_2^0$ and $\tilde{\chi}_3^0$) and a chargino. The decays proceed predominantly via virtual third-generation supersymmetric quarks due to their enhanced couplings with the higgsinos. Examples of dominant characteristic decay chains of this model for $m_{\tilde{\chi}_1^\pm} \lesssim 500$ GeV and $m_{\tilde{g}} \gtrsim 1200$ GeV are $\tilde{g} \to t\bar{t}\tilde{\chi}_{2,3}^0$ and $\tilde{g} \to t\bar{b}\tilde{\chi}_1^\pm$, with $\tilde{\chi}_{2,3}^0$ decaying to $Z/h\tilde{\chi}_1^0$ and $\tilde{\chi}_1^\pm$ to $W^\pm\tilde{\chi}_1^0$.

In this search, the experimental signature consists of a lepton (electron or muon), several jets, and missing transverse momentum ($E_{\text{miss}}^T$) from the undetectable neutralinos and neutrino(s). Depending on the sparticle masses of the model considered, different amounts of energy are available in their decays. Therefore, the number of leptons and jets in the final state, as well as their kinematic properties, depend on the mass spectrum in the model of interest. Four signal regions with jet multiplicities ranging from two to six are defined to provide sensitivity to a broad range of mass spectra in the gluino and squark one-step models. For the two-step and pMSSM models, a dedicated signal region requiring nine jets is constructed to take advantage of the large jet multiplicities in these models. In each signal region, the event yield is compared with the SM prediction, which is estimated using a combination of simulation and observed data in control regions.

The search presented in this paper uses the ATLAS data collected in proton-proton collisions at the LHC during 2015 and 2016 at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 36.1 fb⁻<fnref n="1" />. The analysis extends previous ATLAS searches with similar event selections performed with data collected in 2010–2012 (LHC Run-1) [21] and in 2015 (Run-2) [22], at center-of-mass energies of 8 TeV and 13 TeV, respectively. Similar searches for gluinos and squarks with decays via intermediate supersymmetric particles were performed by the CMS Collaboration in Run 1 [23,24] and Run 2 [25–27]. The results of all Run-1 ATLAS searches targeting squark and gluino pair production are summarized in Ref. [28]. The same SUSY models considered in this paper were also targeted in other Run-2 ATLAS searches using different experimental signatures [29–31].

This paper is structured as follows. After a brief description of the ATLAS detector in Sec. II, the simulated data samples for the background and signal processes used in the analysis as well as the data set and the trigger strategy are detailed in Sec. III. The reconstructed objects and quantities used in the analysis are described in Sec. IV and the event selection is presented in Sec. V. The background estimation and the systematic uncertainties associated with the expected event yields are discussed in Secs. VI and VII, respectively. Finally, the results of the analysis are presented in Sec. VIII, and are followed by a conclusion.

## II. ATLAS DETECTOR

ATLAS [32] is a general-purpose detector with a forward-backward symmetric design that provides almost full solid angle coverage around the interaction point.<fnref n="1" /> The main components are the inner detector (ID), which is surrounded by a superconducting solenoid providing a 2 T axial magnetic field, the calorimeter system, and the muon spectrometer (MS), which is immersed in a magnetic field generated by three large superconducting toroidal magnets. The ID provides track reconstruction within $|\eta| < 2.5$, employing pixel detectors close to the beam pipe, silicon microstrip detectors at intermediate radii, and a straw-tube tracker with particle identification capabilities based on transition radiation at radii up to 1080 mm. The innermost pixel detector layer, the insertable B-layer [33], was added during the shutdown between LHC Run 1 and Run 2, at a radius of 33 mm around a new, narrower, beam pipe. The calorimeters cover $|\eta| < 4.9$. The forward region ($3.2 < |\eta| < 4.9$) is instrumented with a liquid-argon (LAr) calorimeter for both the electromagnetic and

<footnote n="1">¹ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP) in the center of the detector and the z axis along the beam pipe. The x axis points from the IP to the center of the LHC ring, and the y axis points upward. Cylindrical coordinates (r, φ) are used in the transverse plane, φ being the azimuthal angle around the z axis. The pseudorapidity is defined in terms of the polar angle θ as $\eta = -\ln \tan(\theta/2)$. Rapidity is defined as $y = 0.5 \ln[(E + p_z)/(E - p_z)]$ where E denotes the energy and p_z is the component of the momentum along the beam direction.</footnote>
hadronic measurements. In the central region, a lead/LAr electromagnetic calorimeter covers $|η| < 3.2$, while the hadronic calorimeter uses two different detector technologies, with scintillator tiles ($|η| < 1.7$) or liquid argon ($1.5 < |η| < 3.2$) as the active medium. The MS consists of three layers of precision tracking chambers providing coverage over $|η| < 2.7$, while dedicated fast chambers allow triggering over $|η| < 2.4$. The ATLAS trigger system used for real-time event selection [34] consists of a hardware-based first-level trigger and a software-based high-level trigger.

### III. SIMULATED EVENT SAMPLES AND DATA SAMPLES

Three simplified SUSY signal models and a set of pMSSM scenarios are considered in this search. Gluinos or squarks are assumed to be produced in pairs ($\tilde{g}\tilde{g}$ or $\tilde{q}\tilde{q}$). In the case of the simplified models, 100% branching ratios to the decay of interest are assumed.

The gluino/squark one-step simplified models have three free parameters: the masses of the gluino or squark ($m_{\tilde{g}/\tilde{q}}$), the lightest chargino ($m_{\tilde{\chi}_1^+}$), and the lightest neutralino ($m_{\tilde{\chi}_1^0}$). Other sparticles that do not appear in the decay chain are set to have a high mass. To probe a broad range of SUSY mass spectra, two model parametrizations are considered. In the first type, $m_{\tilde{g}/\tilde{q}}$ and the mass ratio $x = (m_{\tilde{\chi}_1^+} - m_{\tilde{\chi}_1^0})/(m_{\tilde{g}/\tilde{q}} - m_{\tilde{\chi}_1^0})$ are free parameters, while $m_{\tilde{\chi}_1^0}$ is fixed to 60 GeV. In the second type, $m_{\tilde{g}/\tilde{q}}$ and $m_{\tilde{\chi}_1^0}$ are free parameters, while $m_{\tilde{\chi}_1^+}$ is fixed by setting $x = 1/2$. For the rest of this paper, the former type is referred to as variable-$x$ and the latter one is referred to as $x = 1/2$.

The gluino two-step simplified model has two free parameters that are varied to probe different mass configurations: the masses of the gluino ($m_{\tilde{g}}$) and the lightest neutralino ($m_{\tilde{\chi}_1^0}$). The masses of the lightest chargino and the second-lightest neutralino are constrained to be $m_{\tilde{\chi}_1^+} = (m_{\tilde{g}} + m_{\tilde{\chi}_1^0})/2$ and $m_{\tilde{\chi}_2^0} = (m_{\tilde{\chi}_1^+} + m_{\tilde{\chi}_1^0})/2$, respectively. All other sparticles are kinematically inaccessible.

In the pMSSM scenario, the sparticle masses are varied by scanning the gluino mass parameter $M_3$ (related to $m_{\tilde{g}}$) and the bilinear Higgs mass parameter $\mu$ (related to $m_{\tilde{\chi}_1^+}$ and $m_{\tilde{\chi}_2^0}$). The scan ranges are 690 GeV < $M_3$ < 2140 GeV and -770 GeV < $\mu$ < -160 GeV. The bino mass parameter $M_1$ (related to $m_{\tilde{\chi}_1^0}$) was set to 60 GeV. The remaining model parameters, defined in Ref. [35], are set to $M_A = M_2 = 3$ TeV, $A_τ = 0$, $\tan β = 10$, and $A_t = A_b = m_{\tilde{\tau}_{L(1,2,3)}} = m_{(\tilde{e}_R, \tilde{\mu}_R, \tilde{\tau}_R)} = m_{\tilde{Q}_{L(1,2,3)}} = m_{(\tilde{u}_R, \tilde{c}_R, \tilde{\tau}_R)} = m_{(\tilde{d}_R, \tilde{s}_R, \tilde{b}_R)} = 5$ TeV, such that the mass of the lightest Higgs boson is compatible with 125 GeV and all other sparticles are kinematically inaccessible. Mass spectra consistent with electroweak symmetry breaking were generated using

SOFTSUSY 3.4.0 [36] and the decay branching ratios were calculated with SDECAY/HDECAY 1.3b/3.4 [37].

The signal samples were generated at leading order (LO) using MADGRAPH 2.2.2 [38] with up to two extra partons in the matrix element, interfaced to PYTHIA 8.186 [39] for parton showers and hadronization. The CKKW-L matching scheme [40] was applied for the matching of the matrix element and the parton shower, with a scale parameter set to a quarter of the mass of the sparticle produced. The ATLAS A14 [41] set of tuned parameters (tune) was used for the shower and the underlying event, together with the NNPDF2.3 LO [42] parton distribution function (PDF) set. The EVTGEN 1.2.0 program [43] was used to describe the properties of the bottom and charm hadron decays in the signal samples.

The signal cross sections were calculated at next-to-leading order (NLO) in the strong coupling constant, adding the resummation of soft gluon emission at next-to-leading-logarithmic accuracy (NLL) [44–48]. The nominal cross section and its uncertainty are taken from an envelope of cross section predictions using different PDF sets and factorization and renormalization scales, as described in Ref. [49], considering only the four light-flavor left-handed squarks ($\tilde{u}_L, \tilde{d}_L, \tilde{s}_L$, and $\tilde{c}_L$).

The simulated event samples for the signal and SM backgrounds are summarized in Table I. Additional samples are used to assess systematic uncertainties, as explained in Sec. VII.

To generate $t\bar{t}$ and single-top-quark events in the $Wt$ and $s$-channel [50], the POWHEG-BOX v2 [51] event generator with the CT10 [52] PDF set in the matrix-element calculations was used. Electroweak $t$-channel single-top-quark events were generated using the POWHEG-BOX v1 event generator. This event generator uses the four-flavor scheme for the NLO matrix-element calculations together with the fixed four-flavor PDF set CT10f4. For all top quark processes, top quark spin correlations are preserved (for the single-top $t$-channel, top quarks are decayed using MADSPIN [53]). The parton shower, fragmentation, and the underlying event were simulated using PYTHIA 6.428 [54] with the CTEQ6L1 [55] PDF set and the corresponding PERUGIA2012 tune (P2012) [56]. The top quark mass was set to 172.5 GeV. The EVTGEN 1.2.0 program was also used to describe the properties of the bottom and charm hadron decays in the $t\bar{t}$ and the single-top-quark samples. The $h_{damp}$ parameter, which controls the $p_T$ of the first additional emission beyond the Born configuration, was set to the mass of the top quark. The main effect of this is to regulate the high-$p_T$ emission against which the $t\bar{t}$ system recoils. The $t\bar{t}$ events are normalized using the cross sections computed at next-to-next-to-leading order (NNLO) with next-to-next-to-leading-logarithmic (NNLL) corrections [57]. The single top quark events are normalized using the NLO + NNLL cross sections for the $Wt$-channel [58] and to the NLO cross sections for the $t$- and $s$-channels [59].
<table><caption>TABLE I. Simulated signal and background event samples: the corresponding event generator, parton shower, cross section normalization, PDF set and underlying-event tune are shown.</caption><thead><tr><th>Physics process<br>Signal</th><th>Generator<br>MG5_AMC@NLO 2.2.2</th><th>Parton shower<br>PYTHIA 8.186</th><th>Cross section<br>NLO + NLL</th><th>PDF set<br>NNPDF2.3 LO</th><th>Tune<br>ATLAS A14</th></tr></thead><tbody><tr><td>t<span style="text-decoration: overline;">t</span></td><td>POWHEG-BOX v2</td><td>PYTHIA 6.428</td><td>NNLO + NNLL</td><td>CT10 NLO</td><td>PERUGIA2012</td></tr><tr><td>Single-top</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>t-channel</td><td>POWHEG-BOX v1</td><td>PYTHIA 6.428</td><td>NLO</td><td>CT10f4 NLO</td><td>PERUGIA2012</td></tr><tr><td>s-channel</td><td>POWHEG-BOX v2</td><td>PYTHIA 6.428</td><td>NLO</td><td>CT10 NLO</td><td>PERUGIA2012</td></tr><tr><td>Wt-channel</td><td>POWHEG-BOX v2</td><td>PYTHIA 6.428</td><td>NLO + NNLL</td><td>CT10 NLO</td><td>PERUGIA2012</td></tr><tr><td>W(→ℓν) + jets</td><td>SHERPA 2.2.1</td><td>SHERPA</td><td>NNLO</td><td>NNPDF3.0 NNLO</td><td>SHERPA default</td></tr><tr><td>Z/γ*(→ℓℓ) + jets</td><td>SHERPA 2.2.1</td><td>SHERPA</td><td>NNLO</td><td>NNPDF3.0 NNLO</td><td>SHERPA default</td></tr><tr><td>WW, WZ and ZZ</td><td>SHERPA 2.1.1 / SHERPA 2.2.1</td><td>SHERPA</td><td>NLO</td><td>CT10 NLO /<br>NNPDF3.0 NNLO</td><td>SHERPA default</td></tr><tr><td>t<span style="text-decoration: overline;">t</span> + W/Z/WW</td><td>MG5_AMC@NLO 2.2.2</td><td>PYTHIA 8.186</td><td>NLO</td><td>NNPDF2.3 LO</td><td>ATLAS A14</td></tr></tbody></table>

Events containing W or Z bosons with associated jets (W/Z + jets) [60] were simulated using the SHERPA 2.2.1 event generator [61]. Matrix elements were calculated for up to two partons at NLO and four partons at LO using the Comix [62] and OpenLoops [63] generators. They were merged with the SHERPA 2.2.1 parton shower [64] with massive b- and c-quarks using the ME+PS@NLO prescription [65]. The NNPDF3.0 NNLO PDF set [66] was used in conjunction with a dedicated parton shower tuning developed by the SHERPA authors. The W/Z + jets events are normalized using their NNLO cross sections [67].

The diboson samples [68] were generated using the SHERPA 2.1.1 and 2.2.1 event generators using the CT10 and NNPDF3.0 PDF sets, respectively. The fully leptonic diboson processes were simulated including final states with four charged leptons, three charged leptons and one neutrino, two charged leptons and two neutrinos, and one charged lepton and three neutrinos. The semileptonic diboson processes were simulated with one of the bosons decaying hadronically and the other leptonically. The processes were calculated for up to one parton (for ZZ) or no additional partons (for WW, WZ) at NLO and up to three partons at LO.

For the $t\bar{t} + W/Z/WW$ processes [69], all events were simulated using MG5_AMC@NLO 2.2.2 at LO interfaced to the PYTHIA 8.186 parton shower model, with up to two ($t\bar{t} + W$), one ($t\bar{t} + Z$) or no ($t\bar{t} + WW$) extra partons included in the matrix element. The EvtGen 1.2.0 program [43] was used to describe the properties of the bottom and charm hadron decays. The ATLAS shower and underlying-event tune A14 was used together with the NNPDF2.3 LO PDF set. The events are normalized using their NLO cross sections [70,71].

The response of the detector to particles was modeled either with a full ATLAS detector simulation [72] using GEANT4 [73] or with a fast simulation [74]. The fast simulation is based on a parametrization of the performance of the electromagnetic and hadronic calorimeters and on GEANT4 elsewhere. All background (signal) samples were

prepared using the full (fast) detector simulation. All simulated events were generated with a varying number of minimum-bias interactions overlaid on the hard-scattering event to model the multiple proton-proton interactions in the same and nearby bunch crossings. The minimum-bias interactions were simulated with the soft QCD processes of PYTHIA 8.186 using the A2 tune [75] and the MSTW2008LO PDF set [76]. Corrections were applied to the samples to account for differences between data and simulation for trigger, identification and reconstruction efficiencies.

The proton-proton data analyzed in this paper were collected by ATLAS during 2015 and 2016 at a center-of-mass energy of 13 TeV with up to 50 simultaneous interactions per proton bunch crossing. After application of data-quality requirements related to the beam and detector conditions, the total integrated luminosity corresponds to 36.1 fb⁻¹. The uncertainty in the combined 2015 and 2016 integrated luminosity is 3.2%. It is derived from a calibration of the luminosity scale using x-y beam-separation scans. This methodology is further detailed in Ref. [77].

The data were collected using the higher-level triggers that select events based on the magnitude of the missing transverse momentum, $E_T^{\text{miss}}$. The triggers used are close to fully efficient for events with an offline-reconstructed $E_T^{\text{miss}}$ greater than 200 GeV.

## IV. EVENT RECONSTRUCTION

In each event, proton-proton interaction vertices are reconstructed from at least two tracks, each with a transverse momentum $p_T > 400$ MeV and consistent with the beamspot envelope. The primary vertex (PV) of the event is selected as the vertex with the largest $\sum p_T^2$ of the associated tracks.

A distinction is made between preselected and signal leptons and jets. Preselected leptons and jets are used in the $E_T^{\text{miss}}$ computation and are subject to a series of basic
quality requirements. Signal leptons and jets are a subset of the preselected objects with more stringent requirements and are used for the definition of signal, control and validation regions.

Three-dimensional topological energy clusters in the calorimeters are used as input to the anti-$k_t$ algorithm with a radius parameter $R = 0.4$ [78–80] to reconstruct preselected jets. The effect of multiple interactions per proton bunch crossing (pileup) is accounted for using the jet area method [81,82]. Subsequent calibrations are applied to the reconstructed jet to improve the energy resolution [83,84]. The residual contamination by pileup jets is further suppressed using a multivariate discriminant that estimates the compatibility of the jet with the PV, as detailed in Ref. [85].

Signal jets must satisfy $p_T > 30$ GeV and $|\eta| < 2.8$. Signal jets within $|\eta| < 2.5$ are identified as candidates for containing b-hadrons (b-tagged) using the MV2c10 algorithm [86,87]. This b-tagging algorithm provides an overall efficiency of 77% for jets containing b-hadrons in simulated $t\bar{t}$ events, with rejection factors of 6 and 134 on charm and light-jets, respectively [88].

Electron candidates are reconstructed by matching an isolated energy cluster in the electromagnetic calorimeter to at least one ID track. Preselected electrons are identified with the likelihood-based Loose criterion described in Ref. [89] with additional requirements on the number of hits in the innermost pixel layer to discriminate against photon conversions. Furthermore, preselected electrons are required to satisfy $p_T > 7$ GeV and $|\eta| < 2.47$. Muon candidates are formed by a combined refitting of tracks reconstructed in the ID and the MS subsystems. Preselected muons are required to have $p_T > 6$ GeV and $|\eta| < 2.5$, and satisfy the Medium identification criteria in Ref. [90].

To avoid double-counting of the preselected jets, electrons, and muons, a sequence of overlap-removal procedures based on the angular distance $\Delta R = \sqrt{(\Delta y)^2 + (\Delta \phi)^2}$ is applied. First, any jet reconstructed within $\Delta R < 0.2$ of a preselected electron is rejected. This prevents electromagnetic energy clusters simultaneously reconstructed as an electron and a jet from being selected twice. Next, to remove bremsstrahlung from muons followed by a photon conversion into electron pairs, electrons within $\Delta R < 0.01$ from a preselected muon are discarded. Subsequently, the contamination from muons from decays of heavy hadrons is suppressed by removing muons that are within $\Delta R < \min(0.04 + (10 \text{ GeV})/p_T^\mu, 0.4)$ from preselected jets meeting the previous criteria, or $\Delta R < 0.2$ from a b-tagged jet or a jet containing more than three tracks with $p_T > 500$ MeV. In the former case, the $p_T$-dependent angular separation mitigates the rejection of energetic muons close to jets in boosted event topologies. Finally, jets reconstructed with $\Delta R < 0.2$ from a preselected muon are rejected.

Signal electrons are required to satisfy the likelihood-based tight identification criteria detailed in Ref. [89].

Signal muons and electrons satisfy a sequence of $\eta$- and $p_T$-dependent isolation requirements on tracking-based and calorimeter-based variables, defined as the GradientLoose [90] isolation criteria. Compatibility of the signal lepton tracks with the PV is enforced by requiring the distance $|z_0 \sin \theta|$ to be less than 0.5 mm, where $z_0$ is the longitudinal impact parameter. In addition, the transverse impact parameter, $d_0$, divided by its uncertainty, $\sigma(d_0)$, must satisfy $|d_0/\sigma(d_0)| < 3$ for signal muons and $|d_0/\sigma(d_0)| < 5$ for signal electrons.

Corrections derived from data control samples are applied to simulated events to calibrate the reconstruction and identification efficiencies, the momentum scale and resolution of leptons and the efficiency and mistag rate of b-tagged jets.

## V. EVENT SELECTION

Each event must satisfy the trigger selection criteria, and must contain a reconstructed primary vertex. Noncollision background and detector noise are suppressed by rejecting events with any preselected jet not satisfying a set of quality criteria [91]. Exactly one signal lepton, either an electron or a muon, is required. Events with additional preselected leptons are rejected to suppress the dilepton $t\bar{t}$, single-top (Wt-channel), $Z$ + jets and diboson backgrounds. The following observables are used in the definition of signal regions in the analysis.

The missing transverse momentum, $E_T^{\text{miss}}$, is defined as the magnitude of $p_T^{\text{miss}}$, the negative vectorial sum of the transverse momenta of preselected muons, electrons, jets, and identified and calibrated photons. The calculation of $p_T^{\text{miss}}$ also includes the transverse momenta of all tracks originating from the PV and not associated with any identified object [92,93].

The transverse mass, $m_T$, is defined from the lepton transverse momentum $p_T^\ell$ and $p_T^{\text{miss}}$ as

$$m_T = \sqrt{2p_T^\ell E_T^{\text{miss}} (1 - \cos[\Delta\phi(p_T^\ell, p_T^{\text{miss}})])},$$

where $\Delta\phi(p_T^\ell, p_T^{\text{miss}})$ is the azimuthal angle between $p_T^\ell$ and $p_T^{\text{miss}}$. For $W$ + jets and semileptonic $t\bar{t}$ events, in which one on-shell W boson decays leptonically, the observable has an upper endpoint at the W-boson mass. The $m_T$ distribution for signal events extends significantly beyond the distributions of the $W$ + jets and semileptonic $t\bar{t}$ events.

The effective mass, $m_{\text{eff}}$, is the scalar sum of the $p_T$ of the signal lepton and all signal jets and $E_T^{\text{miss}}$:

$$m_{\text{eff}} = p_T^\ell + \sum_{j=1}^{N_{\text{jet}}} p_{T,j} + E_T^{\text{miss}}.$$

The effective mass provides good discrimination against SM backgrounds, especially for the signal scenarios where
energetic jets are expected. Gluino production leads to higher jet multiplicity than squark production. High-mass sparticles tend to produce harder jets than low-mass sparticles. Thus the optimal $m_{\text{eff}}$ value depends on the different signal scenarios. To achieve sensitivity to a wide range of SUSY scenarios with a limited number of signal regions, this variable is binned in the final region definition instead of one simple $m_{\text{eff}}$ cut. The detailed description can be found in Sec. VA.

The transverse momentum scalar sum, $H_T$, is defined as

$$H_T = \sum_{j=1}^{N_{\text{jet}}} p_{T,j},$$

where the index $j$ runs over all the signal jets in the event. Empirically, the experimental resolution of $E_T^{\text{miss}}$ scales with $\sqrt{H_T}$, and the ratio $E_T^{\text{miss}}/\sqrt{H_T}$ is useful for suppressing background events with large $E_T^{\text{miss}}$ due to jet mismeasurement.

The aplanarity is a variable designed to provide more global information about the full momentum tensor of the event. It is defined as $(3/2) \times \lambda_3$, where $\lambda_3$ is the smallest eigenvalue of the normalized momentum tensor [94] calculated using the momenta of the jets and leptons in the event. Typical measured aplanarity values lie in the range 0–0.3, with values near zero indicating relatively planar backgroundlike events. Signal events tend to have high aplanarity values, since they are more spherical than background events due to multiple objects emitted in the sparticles decay chains.

### A. Signal region definitions

Five sets of event selection criteria, each defining a signal region (SR), are designed to maximize the signal sensitivity. Each SR is labeled by the minimum required number of jets and, optionally, the characteristics of the

targeted supersymmetric mass spectrum. Four of the five SRs, 2J, 4J high-x, 4J low-x, and 6J, target the gluino/ squark one-step models. The fifth SR, 9J, targets the gluino two-step and pMSSM models.

Table II summarizes the four SRs targeting the gluino/ squark one-step models. The four SRs are mutually exclusive. For setting model-dependent exclusion limits (“excl”), each of the four SRs is further binned in $b$-veto/$b$-tag and $m_{\text{eff}}$, and a simultaneous fit is performed across all 28 bins of the four SRs. This choice enhances the sensitivity to a range of new-physics scenarios with different properties such as the presence or absence in the final state of jets containing $b$-hadrons, and different mass separations between the supersymmetric particles. For model-independent limits and null-hypothesis tests (“disc” for discovery), the event yield above a minimum value of $m_{\text{eff}}$ in each SR is used to search for an excess over the SM background.

The 2J SR provides sensitivity to scenarios characterized by a relatively heavy $\tilde{\chi}_1^0$ and small differences between $m_{\tilde{\chi}_1^0}$, $m_{\tilde{\chi}_1^\pm}$, and $m_{\tilde{\chi}_1^0}$, where most of the decay products tend to have small $p_T$. Events with one low-$p_T$ lepton and at least two jets are selected. The minimum lepton $p_T^\ell$ is 7(6) GeV for the electron (muon), and the maximum $p_T$ is scaled with the number of signal jets in the event as $5 \text{ GeV} \times N_{\text{jet}}$ up to 35 GeV. The maximum $p_T^\ell$ requirement balances background rejection and signal acceptance for models with increasing mass splittings, where there are more energetic leptons and jets. Stringent requirements on $E_T^{\text{miss}}$ and on $m_{\text{eff}}$ enhance the signal sensitivity by selecting signal events in which the final-state neutralinos are boosted against energetic initial-state radiation (ISR) jets. The SM background is further suppressed by a tight requirement on $E_T^{\text{miss}}/m_{\text{eff}}$.

The 4J high-x SR is optimized for models where $m_{\tilde{\chi}_1^0}$ is fixed to 60 GeV and $x \approx 1$, i.e., $m_{\tilde{\chi}_1^\pm}$ is close to $m_{\tilde{\chi}_1^0}$. The W boson produced in the chargino decay is significantly

<table><caption>TABLE II. Overview of the selection criteria for the signal regions used for gluino/squark one-step models.</caption><thead><tr><th>SR</th><th>2J</th><th>4J high-x</th><th>4J low-x</th><th>6J</th></tr></thead><tbody><tr><td>$N_e$</td><td>=1</td><td>=1</td><td>=1</td><td>=1</td></tr><tr><td>$p_T^\ell$ [GeV]</td><td>&gt;7(6) for $e(\mu)$ and &lt; min(5 &middot; $N_{jet}$, 35)</td><td>&gt;35</td><td>&gt;35</td><td>&gt;35</td></tr><tr><td>$N_{jet}$</td><td>&ge;2</td><td>4-5</td><td>4-5</td><td>&ge;6</td></tr><tr><td>$E_T^{\text{miss}}$ [GeV]</td><td>&gt;430</td><td>&gt;300</td><td>&gt;250</td><td>&gt;350</td></tr><tr><td>$m_T$ [GeV]</td><td>&gt;100</td><td>&gt;450</td><td>150-450</td><td>&gt;175</td></tr><tr><td>Aplanarity</td><td>...</td><td>&gt;0.01</td><td>&gt;0.05</td><td>&gt;0.06</td></tr><tr><td>$E_T^{\text{miss}}/m_{\text{eff}}$</td><td>&gt;0.25</td><td>&gt;0.25</td><td>...</td><td>...</td></tr><tr><td>$N_{b-jet}$ (excl)</td><td></td><td>=0 for $b$-veto, &ge;1 for $b$-tag</td><td></td><td></td></tr><tr><td>$m_{\text{eff}}$ [GeV] (excl)</td><td>3 bins &isin; [700, 1900] + [&gt;1900]</td><td>2 bins &isin; [1000, 2000] + [&gt;2000]</td><td>2 bins &isin; [1300, 2000] + [&gt;2000]</td><td>3 bins &isin; [700, 2300] + [&gt;2300]</td></tr><tr><td>$m_{\text{eff}}$ [GeV] (disc)</td><td>&gt;1100</td><td>&gt;1500</td><td>&gt;1650(1300) for gluino (squark)</td><td>&gt;2300(1233) for gluino (squark)</td></tr></tbody></table>
<table><caption>TABLE III. Overview of the selection criteria for the signal region used for pMSSM and gluino two-step models.</caption><thead><tr><th>SR</th><th>9J</th></tr></thead><tbody><tr><td>N<sub>ℓ</sub></td><td>=1</td></tr><tr><td>p<sub>T</sub><sup>ℓ</sup> [GeV]</td><td>>35</td></tr><tr><td>N<sub>jet</sub></td><td>≥9</td></tr><tr><td>E<sub>T</sub><sup>miss</sup> [GeV]</td><td>>200</td></tr><tr><td>m<sub>T</sub> [GeV]</td><td>>175</td></tr><tr><td>Aplanarity</td><td>>0.07</td></tr><tr><td>E<sub>T</sub><sup>miss</sup>/√H<sub>T</sub> [GeV<sup>1/2</sup>]</td><td>≥8</td></tr><tr><td>m<sub>eff</sub> [GeV] (excl)</td><td>[1000, 1500], [>1500]</td></tr><tr><td>m<sub>eff</sub> [GeV] (disc)</td><td>>1500</td></tr></tbody></table>

boosted, giving rise to a high-$p_T$ lepton. The main characteristics of signal events in this model are large $m_T$ values and relatively soft jets emitted from the sparticle decay. Tight requirements are placed on $E_T^{\text{miss}}$, $m_T$, and $E_T^{\text{miss}}/m_{\text{eff}}$.

The 4J low-x SR targets models where $m_{\tilde{\chi}_1^0}$ is fixed to 60 GeV and $x \approx 0$, i.e., $m_{\tilde{\chi}_1^\pm}$ is close to $m_{\tilde{\chi}_1^0}$. The large $m_{\tilde{\chi}_1/\tilde{q}} - m_{\tilde{\chi}_1^\pm}$ mass splitting leads to high jet activity, where events are expected to have higher $m_{\text{eff}}$ and larger aplanarity than in the high-x scenarios. The W boson tends to be off-shell, leading to small $m_T$, and accordingly an upper bound is imposed to keep this region orthogonal to the 4J high-x SR.

The 6J SR is optimized for models with $x = 1/2$, targeting scenarios with large sparticle mass. Events with one high-$p_T$ lepton and six or more jets are selected. Requirements on $m_T$, $E_T^{\text{miss}}$, $m_{\text{eff}}$, and aplanarity are imposed to reduce the SM background from $t\bar{t}$ and W+jets production. The sensitivity is improved for scenarios with large $m_{\tilde{\chi}_1/\tilde{q}}$ and small $m_{\tilde{\chi}_1^0}$ by introducing a higher $m_{\text{eff}}$ bin.

Finally, one signal region, 9J SR, is defined to target the pMSSM and gluino two-step models. The selection criteria are summarized in Table III. At least nine jets are required, targeting the models' long decay chains in which multiple vector or Higgs bosons are produced. The background is further suppressed by tight requirements on the aplanarity and on $E_T^{\text{miss}}/\sqrt{H_T}$. For setting model-dependent exclusion limits ("excl"), the SR is separated into $1000 < m_{\text{eff}} < 1500$ GeV and $m_{\text{eff}} > 1500$ GeV to achieve good discrimination power for different gluino masses. For model-independent null-hypothesis tests ("disc"), events selected with $m_{\text{eff}} > 1500$ GeV are used to search for an excess over the SM background.

## VI. BACKGROUND ESTIMATION

The dominant SM backgrounds in most signal regions originate from top quark ($t\bar{t}$ and single top) and W+jets production. In this section, the techniques employed to

estimate the contribution of these backgrounds in the signal regions are detailed.

Additional sources of background in all signal regions originate from the production of $Z + \text{jets}$, $t\bar{t}$ in association with a W or Z boson, and diboson (WW, WZ, ZZ) events. Their contributions are estimated entirely using simulated event samples normalized to NLO cross sections.

The contribution from multijet processes with a misidentified lepton is found to be negligible once the lepton isolation and $E_T^{\text{miss}}$ requirements used in this search are imposed. A data-driven matrix method, following the implementation described in Ref. [21], determined this in previous iterations of the analysis [22]. As this background is found to be negligible, it is not further considered in the analysis.

The dominant top quark and W+jets backgrounds in the 2J, 4J high-x, 4J low-x, and 6J signal regions are estimated by simultaneously normalizing the predicted event yields from simulation to the number of data events observed in dedicated control regions (CR) using the fitting procedure described in Sec. VIII. The simulation is then

<table><caption>TABLE IV. Overview of the control and validation region selection criteria corresponding to the 2J SR. The top and W+jets control regions are denoted by TR and WR, respectively.</caption><thead><tr><th>2J</th><th>WR/TR</th><th>VR $E_T^{\text{miss}}$</th><th>VR $m_T$</th></tr></thead><tbody><tr><td>$N_\ell$</td><td></td><td>=1</td><td></td></tr><tr><td>$p_T^\ell$ [GeV]</td><td></td><td>>7(6) for $e(\mu)$ and &lt; min(5 &middot; $N_{jet}$, 35)</td><td></td></tr><tr><td>$N_{jet}$</td><td></td><td>≥2</td><td></td></tr><tr><td>$N_{b-jet}$</td><td>=0/≥1</td><td>...</td><td>...</td></tr><tr><td>$m_T$ [GeV]</td><td>[40, 100]</td><td>[40, 100]</td><td>>100</td></tr><tr><td>$E_T^{\text{miss}}$ [GeV]</td><td>[300, 430]</td><td>>430</td><td>[300, 430]</td></tr><tr><td>Aplanarity</td><td>...</td><td>...</td><td>...</td></tr><tr><td>$E_T^{\text{miss}}/m_{\text{eff}}$</td><td>>0.15</td><td>>0.25</td><td>>0.1</td></tr><tr><td>$m_{\text{eff}}$ [GeV]</td><td colspan="3">3 bins ∈ [700, 1900] + [>1900]</td></tr></tbody></table>

<table><caption>TABLE V. Overview of the control and validation region selection criteria corresponding to the 4J high-x SR. The top and W+jets control regions are denoted by TR and WR, respectively.</caption><thead><tr><th>4J high-x</th><th>WR/TR</th><th>VR Aplanarity</th><th>VR $m_T$</th><th>VR Hybrid</th></tr></thead><tbody><tr><td>$N_\ell$</td><td></td><td></td><td>=1</td><td></td></tr><tr><td>$p_T^\ell$ [GeV]</td><td></td><td></td><td>>35</td><td></td></tr><tr><td>$N_{jet}$</td><td></td><td></td><td>4-5</td><td></td></tr><tr><td>$N_{b-jet}$</td><td>=0/≥1</td><td>...</td><td>...</td><td>...</td></tr><tr><td>$m_T$ [GeV]</td><td>[50, 200]</td><td>[50, 150]</td><td>>200</td><td>[150, 450]</td></tr><tr><td>$E_T^{\text{miss}}$ [GeV]</td><td>>300</td><td>>250</td><td>>250</td><td>>250</td></tr><tr><td>Aplanarity</td><td>&lt;0.01</td><td>&gt;0.05</td><td>&lt;0.01</td><td>[0.01, 0.05]</td></tr><tr><td>$E_T^{\text{miss}}/m_{\text{eff}}$</td><td>>0.25</td><td>>0.25</td><td>>0.25</td><td>...</td></tr><tr><td>$m_{\text{eff}}$ [GeV]</td><td colspan="3">2 bins ∈ [1000, 2000] + [>2000]</td><td></td></tr></tbody></table>
<table><caption>TABLE VI. Overview of the control and validation region selection criteria corresponding to the 4J low-x SR. The top and W+jets control regions are denoted by TR and WR, respectively.</caption><thead><tr><th>4J low-x</th><th>WR/TR</th><th>VR Aplanarity</th><th>VR Hybrid</th></tr></thead><tbody><tr><td>N<sub>ℓ</sub></td><td></td><td>=1</td><td></td></tr><tr><td>p<sub>T</sub><sup>ℓ</sup> [GeV]</td><td></td><td>>35</td><td></td></tr><tr><td>N<sub>jet</sub></td><td></td><td>4-5</td><td></td></tr><tr><td>N<sub>b-jet</sub></td><td>=0/≥1</td><td>...</td><td>...</td></tr><tr><td>m<sub>T</sub> [GeV]</td><td>[50, 150]</td><td>[50, 150]</td><td>[150, 450]</td></tr><tr><td>E<sub>T</sub><sup>miss</sup> [GeV]</td><td></td><td>>250</td><td></td></tr><tr><td>Aplanarity</td><td>[0.01, 0.05]</td><td>>0.05</td><td>[0.01, 0.05]</td></tr><tr><td>m<sub>eff</sub> [GeV]</td><td colspan="3">2 bins ∈ [1300, 2000] + [>2000]</td></tr></tbody></table>

<table><caption>TABLE VII. Overview of the control and validation region selection criteria corresponding to the 6J SR. The top and W+jets control regions are denoted by TR and WR, respectively.</caption><thead><tr><th>6J</th><th>WR/TR</th><th>VR Aplanarity</th><th>VR m<sub>T</sub></th></tr></thead><tbody><tr><td>N<sub>ℓ</sub></td><td></td><td>=1</td><td></td></tr><tr><td>p<sub>T</sub><sup>ℓ</sup> [GeV]</td><td></td><td>>35</td><td></td></tr><tr><td>N<sub>jet</sub></td><td></td><td>≥6</td><td></td></tr><tr><td>N<sub>b-jet</sub></td><td>=0/≥1</td><td>...</td><td>...</td></tr><tr><td>m<sub>T</sub> [GeV]</td><td>[50, 175]</td><td>[50, 175]</td><td>[175, 400]</td></tr><tr><td>E<sub>T</sub><sup>miss</sup> [GeV]</td><td>>350</td><td>>350</td><td>>250</td></tr><tr><td>Aplanarity</td><td>&lt;0.06</td><td>>0.06</td><td>&lt;0.06</td></tr><tr><td>m<sub>eff</sub> [GeV]</td><td colspan="3">3 bins ∈ [700, 2300] + [>2300]</td></tr></tbody></table>

used to extrapolate the measured background rates to the corresponding signal regions.

The CRs are designed to have high purity in the background process of interest, a sufficiently large number of events to obtain small statistical uncertainties in the background prediction, and a small contamination by events from the signal models under consideration. Moreover, they are designed to have kinematic properties

resembling as closely as possible those of the signal regions, in order to provide good estimates of the kinematics of background processes there. This procedure limits the impact of potentially large systematic uncertainties in the expected yields from the extrapolation.

Tables IV–VII list the criteria that define the control regions corresponding to signal regions 2J, 4J high-x, 4J low-x, and 6J. As described in Sec. V, these signal regions contain multiple bins in $m_{eff}$. The same binning is maintained for the control regions, so that every signal region bin in $m_{eff}$ has corresponding control regions with the same requirements on $m_{eff}$ and, therefore, the backgrounds are estimated independently in each $m_{eff}$ bin.

Dedicated top and W+jets control regions, respectively denoted by TR and WR, are constructed in each bin of $m_{eff}$. The TR and WR are distinguished by requiring at least one or exactly zero b-tagged signal jets, respectively. Cross-contamination from top and W+jets processes between these two types of control regions is accounted for in the fit. The measured top and W+jets background rates from the TR and WR regions in a given $m_{eff}$ bin are extrapolated to the signal region within the same $m_{eff}$ bin. The signal regions in a given $m_{eff}$ bin may be further separated into regions with at least one or exactly zero b-tagged signal jets as described in Sec. V. For such signal regions separated by b-tagged jet multiplicity, the extrapolation is performed from both the TR and WR regions to each individual bin of b-tagged jet multiplicity.

To validate the extrapolation from control to signal regions using simulated event samples, dedicated validation regions (VRs) are defined for each set of control and signal regions. The selection criteria defining these VRs are also shown in Tables IV–VII. The same binning in $m_{eff}$ used in the control and signal regions is also maintained in the validation regions. The VRs are designed to be kinematically close to the signal regions, with only a small contamination from the signal in the models considered in this search. The VRs are not used to constrain parameters in

<table><caption>TABLE VIII. Overview of the control and validation region selection criteria corresponding to the 9J SR. The control regions $CR_{A,A'B,C,C'}$ are further divided into bins of exactly 0 or ≥1 b-tagged signal jets to enrich top and W+jets backgrounds, respectively.</caption><thead><tr><th>9J</th><th>CR<sub>A</sub></th><th>CR<sub>B</sub></th><th>CR<sub>C</sub></th><th>VR m<sub>T</sub></th><th>CR<sub>C'</sub></th><th>VR N<sub>jet</sub></th><th>CR<sub>A'</sub></th></tr></thead><tbody><tr><td>N<sub>ℓ</sub></td><td></td><td></td><td></td><td>=1</td><td></td><td></td><td></td></tr><tr><td>p<sub>T</sub><sup>ℓ</sup> [GeV]</td><td></td><td></td><td></td><td>≥35</td><td></td><td></td><td></td></tr><tr><td>N<sub>jet</sub></td><td>5-6</td><td>5-6</td><td>≥ 9</td><td>7-8</td><td>7-8</td><td>≥ 9</td><td>5-6</td></tr><tr><td>p<sub>T</sub><sup>jet</sup> [GeV]</td><td></td><td></td><td></td><td>≥30</td><td></td><td></td><td></td></tr><tr><td>N<sub>b-jet</sub></td><td>=0/≥1</td><td>=0/≥1</td><td>=0/≥1</td><td>...</td><td>=0/≥1</td><td>...</td><td>=0/≥1</td></tr><tr><td>m<sub>T</sub> [GeV]</td><td>>175</td><td>&lt;100</td><td>&lt;100</td><td>>175</td><td>&lt;100</td><td>[100, 175]</td><td>[100, 175]</td></tr><tr><td>E<sub>T</sub><sup>miss</sup> [GeV]</td><td></td><td></td><td></td><td>>200</td><td></td><td></td><td></td></tr><tr><td>E<sub>T</sub><sup>miss</sup>/√H<sub>T</sub></td><td></td><td></td><td></td><td>≥8</td><td></td><td></td><td></td></tr><tr><td>Aplanarity</td><td>...</td><td>...</td><td>>0.07</td><td>&lt;0.05</td><td>&lt;0.05</td><td>&lt;0.05</td><td>...</td></tr><tr><td>m<sub>eff</sub> [GeV]</td><td>>1000</td><td>>1000</td><td>>1000</td><td>[1000, 1500], [>1500]</td><td>>1000</td><td>>1000</td><td>>1000</td></tr></tbody></table>
<figure><img src="image_2.png" /><figcaption>FIG. 2. Illustration of the control and validation region configuration corresponding to the 9J SR. The control regions that are used for the background estimation in the signal region are indicated by red lines, while the blue lines indicate control regions that are used for the background estimation in the validation regions and the validation regions themselves. The definitions for all regions are given in Table III (signal region) and Table VIII (control and validation regions).</figcaption></figure>

the fit, but provide a statistically independent cross-check of the extrapolation. The observed event yields in the VRs are found to be consistent with the background prediction as further discussed in Sec. VIII.

One of the dominant background components in the 2J, 4J high-x, 4J low-x, and 6J SRs is $t\bar{t}$ production with dileptonic final state, where one lepton fails to be reconstructed (“missing lepton”) or is a semihadronically decaying $\tau$ lepton; this background is characterized by high values of $m_T$. To validate the above described background estimation technique, which is largely a simulation-based extrapolation from low-$m_T$ control regions populated by events with semileptonic $t\bar{t}$ decays, an alternative method was developed. This method (hereafter referred to as the object replacement method) uses events in a dileptonic control region. To emulate the missing lepton case, the $p_T$ of one of the two leptons is added vectorially to the calculation of $E_T^{\text{miss}}$. To emulate the hadronic $\tau$ decay case, one of the two leptons is resimulated as a hadronic tau decay using the Tauola generator [95] with appropriate energy scale and resolution corrections. The accuracy of this alternative background estimation technique was validated on simulated samples as well as in data validation regions. The background estimates derived from this object replacement method are found to be consistent with those obtained from the standard semi-data-driven approach as further demonstrated in Sec. VIII.

While the background estimation strategy described above works well for the signal regions 2J, 4J high-x, 4J low-x, and 6J, it is not viable for the 9J SR. The reason for this is that the simulation-based extrapolation from the control regions, which are typically located around the peak region of the transverse mass distribution ($m_T \sim 80$ GeV),

<table><caption>TABLE IX. Breakdown of the dominant systematic uncertainties in the background estimates in the 2J and 4J high-x SRs. The individual uncertainties can be correlated and do not necessarily add up in quadrature to the total background uncertainty. The percentages show the size of the uncertainty relative to the total expected background.</caption><thead><tr><th>Signal region</th><th>2J b-tag</th><th>2J b-veto</th><th>4J high-x b-tag</th><th>4J high-x b-veto</th></tr></thead><tbody><tr><td>Total background expectation</td><td>47</td><td>36</td><td>54</td><td>44</td></tr><tr><td>Total background systematic uncertainty</td><td>±4[9%]</td><td>±9[24%]</td><td>±7[12%]</td><td>±10[23%]</td></tr><tr><td>Experimental uncertainty</td><td>±1.3</td><td>±2.2</td><td>±2.6</td><td>±5</td></tr><tr><td>Normalization uncertainty</td><td>±2.8</td><td>±0.9</td><td>±4</td><td>±1.9</td></tr><tr><td>Theoretical uncertainty</td><td>±3.5</td><td>±9</td><td>±5</td><td>±6</td></tr><tr><td>Statistical uncertainty of MC samples</td><td>±1.4</td><td>±1.8</td><td>±1.7</td><td>±7</td></tr></tbody></table>

<table><caption>TABLE X. Breakdown of the dominant systematic uncertainties in the background estimates in the 4J low-x and 6J SRs. The individual uncertainties can be correlated and do not necessarily add up in quadrature to the total background uncertainty. The percentages show the size of the uncertainty relative to the total expected background.</caption><thead><tr><th>Signal region</th><th>4J low-x b-tag</th><th>4J low-x b-veto</th><th>6J b-tag</th><th>6J b-veto</th></tr></thead><tbody><tr><td>Total background expectation</td><td>31</td><td>16</td><td>27</td><td>7.3</td></tr><tr><td>Total background systematic uncertainty</td><td>±6[21%]</td><td>±4[25%]</td><td>±4[15%]</td><td>±2.0[27%]</td></tr><tr><td>Experimental uncertainty</td><td>±1.8</td><td>±1.0</td><td>±1.1</td><td>±0.8</td></tr><tr><td>Normalization uncertainty</td><td>±2.3</td><td>±0.8</td><td>±1.4</td><td>±0.5</td></tr><tr><td>Theoretical uncertainty</td><td>±6</td><td>±4</td><td>±4</td><td>±2.0</td></tr><tr><td>Statistical uncertainty of MC samples</td><td>±1.2</td><td>±1.0</td><td>±0.9</td><td>±0.6</td></tr></tbody></table>
<table><caption>TABLE XI. Breakdown of the dominant systematic uncertainties in the background estimates in the 9J SR. The individual uncertainties can be correlated and do not necessarily add up in quadrature to the total background uncertainty. The percentage shows the size of the uncertainty relative to the total expected background.</caption><tr><td>Signal region</td><td>9J</td></tr><tr><td>Total background expectation</td><td>7</td></tr><tr><td>Total background systematic uncertainty</td><td>±4[50%]</td></tr><tr><td>Theoretical uncertainty</td><td>±4</td></tr><tr><td>Normalization uncertainty</td><td>±2.0</td></tr><tr><td>Experimental uncertainty</td><td>±1.9</td></tr><tr><td>Statistical uncertainty of MC samples</td><td>±0.7</td></tr></table>

to the high-$m_T$ signal regions ($m_T \gg 80$ GeV) is affected by large theoretical uncertainties at high jet multiplicities. Because the peak and tail regions of the $m_T$ distribution are dominated by semileptonic and dileptonic final states from $t\bar{t}$ decays, respectively, additional jets from initial- or final-state radiation are required to obtain the same jet multiplicity for dileptonic $t\bar{t}$ final states. Inadequate modeling of such additional jets is the dominant source of the theoretical uncertainty. To reduce the dependence on the modeling of additional jets, a dedicated data-driven background estimation technique was designed for the 9J SR. The method relies on the assumption that the $m_T$ distribution is approximately invariant under changes in the jet

<table><caption>TABLE XII. Event yields and background-only fit results for the 2J and 4J high-x SRs. Each column corresponds to a bin in $m_{eff}$ [GeV]. Uncertainties in the fitted background estimates combine statistical (in the simulated event yields) and systematic uncertainties. The uncertainties in this table are symmetrized for propagation purposes but truncated at zero to remain within the physical boundaries.</caption><thead><tr><th></th><th>All m<sub>eff</sub> bins</th><th>[700, 1100]</th><th>[1100, 1500]</th><th>[1500, 1900]</th><th>&gt;1900 [GeV]</th></tr></thead><tbody><tr><td>2J b-tag</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Observed events</td><td>47</td><td>8</td><td>21</td><td>12</td><td>6</td></tr><tr><td>Fitted bkg events</td><td>47 ± 4</td><td>6.0 ± 1.3</td><td>23.0 ± 3.0</td><td>12.9 ± 2.1</td><td>5.2 ± 1.8</td></tr><tr><td>Fitted t<span style="text-decoration: overline">t</span> events</td><td>31.1 ± 3.5</td><td>2.7 ± 0.8</td><td>15.3 ± 2.5</td><td>9.4 ± 1.7</td><td>3.8 ± 1.4</td></tr><tr><td>Fitted W + jets events</td><td>3.7 ± 1.4</td><td>1.1 ± 0.9</td><td>2.0 ± 1.0</td><td>0.5 ± 0.4</td><td>0.10 ± 0.10</td></tr><tr><td>Fitted Z + jets events</td><td>2.0 ± 0.6</td><td>0.70 ± 0.20</td><td>0.90 ± 0.30</td><td>0.30 ± 0.10</td><td>0.10 ± 0.10</td></tr><tr><td>Fitted single-top events</td><td>5.6 ± 1.8</td><td>0.6 ± 0.4</td><td>2.7 ± 1.3</td><td>1.5 ± 1.0</td><td>0.8 ± 0.8</td></tr><tr><td>Fitted diboson events</td><td>1.8 ± 1.4</td><td>0.30 ± 0.20</td><td>0.8 ± 0.8</td><td>0.50 ± 0.30</td><td>0.10 ± 0.10</td></tr><tr><td>Fitted t<span style="text-decoration: overline">t</span> + V events</td><td>2.92 ± 0.25</td><td>0.60 ± 0.10</td><td>1.30 ± 0.10</td><td>0.70 ± 0.10</td><td>0.30 ± 0.04</td></tr><tr><td>2J b-veto</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Observed events</td><td>61</td><td>20</td><td>26</td><td>9</td><td>6</td></tr><tr><td>Fitted bkg events</td><td>36 ± 9</td><td>10 ± 4</td><td>16 ± 5</td><td>7.0 ± 1.9</td><td>2.5 ± 0.8</td></tr><tr><td>Fitted t<span style="text-decoration: overline">t</span> events</td><td>5.1 ± 1.0</td><td>1.00 ± 0.30</td><td>2.7 ± 0.6</td><td>1.00 ± 0.30</td><td>0.40 ± 0.20</td></tr><tr><td>Fitted W + jets events</td><td>13 ± 4</td><td>5 ± 4</td><td>5.8 ± 1.8</td><td>2.4 ± 1.1</td><td>0.50 ± 0.30</td></tr><tr><td>Fitted Z + jets events</td><td>5.8 ± 1.7</td><td>1.8 ± 0.6</td><td>2.3 ± 0.8</td><td>1.00 ± 0.30</td><td>0.60 ± 0.30</td></tr><tr><td>Fitted single-top events</td><td>1.1 ± 0.4</td><td>0.10 ± 0.10</td><td>0.70 ± 0.30</td><td>0.20 ± 0.10</td><td>0.10 ± 0.10</td></tr><tr><td>Fitted diboson events</td><td>10 ± 8</td><td>2.5 ± 1.7</td><td>4 ± 4</td><td>2.3 ± 1.5</td><td>0.8 ± 0.7</td></tr><tr><td>Fitted t<span style="text-decoration: overline">t</span> + V events</td><td>0.34 ± 0.08</td><td>0.048 ± 0.019</td><td>0.20 ± 0.10</td><td>0.066 ± 0.013</td><td>0.025 ± 0.007</td></tr><tr><td>4J high-x b-tag</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Observed events</td><td>44</td><td>38</td><td>4</td><td>2</td><td>2</td></tr><tr><td>Fitted bkg events</td><td>54 ± 7</td><td>44 ± 6</td><td>7.7 ± 1.5</td><td>1.8 ± 0.7</td><td>1.8 ± 0.7</td></tr><tr><td>Fitted t<span style="text-decoration: overline">t</span> events</td><td>39 ± 6</td><td>34 ± 6</td><td>4.9 ± 1.2</td><td>0.8 ± 0.5</td><td>0.8 ± 0.5</td></tr><tr><td>Fitted W + jets events</td><td>3.2 ± 1.5</td><td>2.7 ± 1.5</td><td>0.20 ± 0.10</td><td>0.20 ± 0.10</td><td>0.20 ± 0.10</td></tr><tr><td>Fitted Z + jets events</td><td>0.14 ± 0.13</td><td>0.10 ± 0.10</td><td>0.036 ± 0.025</td><td>0.007<sup>+0.019</sup><sub>-0.007</sub></td><td>0.007<sup>+0.019</sup><sub>-0.007</sub></td></tr><tr><td>Fitted single-top events</td><td>6.0 ± 2.3</td><td>4.1 ± 2.2</td><td>1.6 ± 0.7</td><td>0.30 ± 0.30</td><td>0.30 ± 0.30</td></tr><tr><td>Fitted diboson events</td><td>1.6 ± 1.0</td><td>1.0 ± 0.6</td><td>0.30 ± 0.30</td><td>0.30 ± 0.30</td><td>0.30 ± 0.30</td></tr><tr><td>Fitted t<span style="text-decoration: overline">t</span> + V events</td><td>3.69 ± 0.25</td><td>2.84 ± 0.18</td><td>0.70 ± 0.10</td><td>0.155 ± 0.026</td><td>0.155 ± 0.026</td></tr><tr><td>4J high-x b-veto</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Observed events</td><td>37</td><td>27</td><td>7</td><td>3</td><td>3</td></tr><tr><td>Fitted bkg events</td><td>44 ± 10</td><td>36 ± 10</td><td>5.8 ± 1.9</td><td>2.4 ± 1.0</td><td>2.4 ± 1.0</td></tr><tr><td>Fitted t<span style="text-decoration: overline">t</span> events</td><td>4.0 ± 1.1</td><td>3.3 ± 1.0</td><td>0.60 ± 0.20</td><td>0.10 ± 0.10</td><td>0.10 ± 0.10</td></tr><tr><td>Fitted W + jets events</td><td>28 ± 8</td><td>24 ± 8</td><td>3.0 ± 1.1</td><td>1.0 ± 0.4</td><td>1.0 ± 0.4</td></tr><tr><td>Fitted Z + jets events</td><td>1.4 ± 0.8</td><td>0.9 ± 0.5</td><td>0.10 ± 0.10</td><td>0.30 ± 0.30</td><td>0.30 ± 0.30</td></tr><tr><td>Fitted single-top events</td><td>0.9 ± 0.4</td><td>0.6 ± 0.4</td><td>0.20 ± 0.10</td><td>0.10 ± 0.10</td><td>0.10 ± 0.10</td></tr><tr><td>Fitted diboson events</td><td>9 ± 5</td><td>6.2 ± 3.4</td><td>1.8 ± 1.5</td><td>0.9 ± 0.8</td><td>0.9 ± 0.8</td></tr><tr><td>Fitted t<span style="text-decoration: overline">t</span> + V events</td><td>0.36 ± 0.09</td><td>0.25 ± 0.07</td><td>0.057 ± 0.018</td><td>0.054 ± 0.024</td><td>0.054 ± 0.024</td></tr></tbody></table>
multiplicity requirements. This assumption is found to be valid when tight $m_{eff}$ requirements as used in this analysis are applied such that the overall activity in the calorimeter and thus the missing transverse momentum resolution are not significantly affected by variations in the jet multiplicity. Based on the $m_T$ invariance, mutually exclusive control regions $CR_{A,B,C}$ are defined in the $m_T-N_{jet}$ plane, where $CR_A$ is located at high $m_T$ and low $N_{jet}$, $CR_B$ at low $m_T$ and low $N_{jet}$, and $CR_C$ at low $m_T$ and high $N_{jet}$. The precise requirements of these regions are defined in Table VIII and illustrated in Fig. 2. Based on these regions, the background

in the high $m_T$ and high $N_{jet}$ signal region can then be estimated with the following equation:

$$ \frac{N_{CR_A}}{N_{CR_B}} = \frac{N_{SR_{oj}}^{est}}{N_{CR_C}} \rightarrow N_{SR_{oj}}^{est} = \frac{N_{CR_A}}{N_{CR_B}} N_{CR_C}, $$

where $N_{SR_{oj}}^{est}$ is the (estimated) number of events in a given region. The residual small correlations between $m_T$ and $N_{jet}$ that bias the background estimate in the signal region can then be expressed in terms of a simulation-based closure parameter defined as

<table><caption>TABLE XIII. Event yields and background-only fit results for the 4J low-x and 6J SRs. Each column corresponds to a bin in $m_{eff}$ [GeV]. Uncertainties in the fitted background estimates combine statistical (in the simulated event yields) and systematic uncertainties. The uncertainties in this table are symmetrized for propagation purposes but truncated at zero to remain within the physical boundaries.</caption><thead><tr><th></th><th>All m<sub>eff</sub> bins</th><th>[1300, 1650]</th><th>[1650, 2000]</th><th>>2000 [GeV]</th></tr></thead><tbody><tr><td>4J low-x b-tag</td><td></td><td></td><td></td><td></td></tr><tr><td>Observed events</td><td>31</td><td>19</td><td>6</td><td>6</td></tr><tr><td>Fitted bkg. events</td><td>31 ± 6</td><td>20 ± 5</td><td>6.6 ± 2.3</td><td>4.4 ± 1.6</td></tr><tr><td>Fitted t<span style="text-decoration: overline">t</span> events</td><td>19 ± 5</td><td>13 ± 4</td><td>4.3 ± 1.6</td><td>2.1 ± 1.0</td></tr><tr><td>Fitted W + jets events</td><td>2.4 ± 1.1</td><td>1.6 ± 1.1</td><td>0.40 ± 0.20</td><td>0.40 ± 0.20</td></tr><tr><td>Fitted Z + jets events</td><td>0.10 ± 0.05</td><td>0.037 ± 0.033</td><td>0.017 ± 0.014</td><td>0.042 ± 0.030</td></tr><tr><td>Fitted single-top events</td><td>6.5 ± 3.4</td><td>3.5 ± 2.8</td><td>1.5 ± 1.5</td><td>1.5 ± 1.1</td></tr><tr><td>Fitted diboson events</td><td>1.2 ± 0.9</td><td>0.7 ± 0.4</td><td>0.20 ± 0.20</td><td>0.30 ± 0.30</td></tr><tr><td>Fitted t<span style="text-decoration: overline">t</span> + V events</td><td>1.41 ± 0.14</td><td>1.03 ± 0.12</td><td>0.24 ± 0.05</td><td>0.14 ± 0.04</td></tr><tr><td>4J low-x b-veto</td><td></td><td></td><td></td><td></td></tr><tr><td>Observed events</td><td>19</td><td>7</td><td>7</td><td>5</td></tr><tr><td>Fitted bkg events</td><td>16 ± 4</td><td>10.0 ± 3.0</td><td>3.5 ± 1.1</td><td>2.7 ± 1.1</td></tr><tr><td>Fitted t<span style="text-decoration: overline">t</span> events</td><td>2.3 ± 0.8</td><td>1.6 ± 0.6</td><td>0.40 ± 0.20</td><td>0.30 ± 0.20</td></tr><tr><td>Fitted W + jets events</td><td>7.5 ± 2.6</td><td>4.6 ± 2.3</td><td>1.9 ± 0.8</td><td>1.0 ± 0.5</td></tr><tr><td>Fitted Z + jets events</td><td>0.18 ± 0.09</td><td>0.06<sup>+0.06</sup><sub>-0.06</sub></td><td>0.05 ± 0.04</td><td>0.070 ± 0.032</td></tr><tr><td>Fitted single-top events</td><td>1.2 ± 0.7</td><td>0.5 ± 0.4</td><td>0.20 ± 0.20</td><td>0.5 ± 0.4</td></tr><tr><td>Fitted diboson events</td><td>4.9 ± 3.3</td><td>3.2 ± 1.9</td><td>1.0 ± 0.7</td><td>0.7<sup>+0.9</sup><sub>-0.7</sub></td></tr><tr><td>Fitted t<span style="text-decoration: overline">t</span> + V events</td><td>0.125 ± 0.031</td><td>0.099 ± 0.023</td><td>0.014 ± 0.008</td><td>0.012<sup>+0.014</sup><sub>-0.012</sub></td></tr><tr><td>6J b-tag</td><td></td><td></td><td></td><td></td></tr><tr><td>Observed events</td><td>31</td><td>6</td><td>16</td><td>9</td></tr><tr><td>Fitted bkg events</td><td>27 ± 4</td><td>8.5 ± 2.0</td><td>12.1 ± 2.7</td><td>4.1 ± 1.0</td></tr><tr><td>Fitted t<span style="text-decoration: overline">t</span> events</td><td>19 ± 4</td><td>6.1 ± 1.8</td><td>9.1 ± 2.5</td><td>2.6 ± 0.8</td></tr><tr><td>Fitted W + jets events</td><td>0.75 ± 0.29</td><td>0.20 ± 0.20</td><td>0.30 ± 0.10</td><td>0.20 ± 0.10</td></tr><tr><td>Fitted Z + jets events</td><td>0.07 ± 0.06</td><td>...</td><td>0.025<sup>+0.026</sup><sub>-0.025</sub></td><td>0.029<sup>+0.035</sup><sub>-0.029</sub></td></tr><tr><td>Fitted single-top events</td><td>3.1 ± 1.1</td><td>0.7 ± 0.5</td><td>1.3 ± 0.8</td><td>0.6 ± 0.4</td></tr><tr><td>Fitted diboson events</td><td>0.8 ± 0.7</td><td>0.20 ± 0.20</td><td>0.30 ± 0.20</td><td>0.20 ± 0.20</td></tr><tr><td>Fitted t<span style="text-decoration: overline">t</span> + V events</td><td>2.9 ± 0.5</td><td>1.20 ± 0.20</td><td>1.10 ± 0.30</td><td>0.50 ± 0.10</td></tr><tr><td>6J b-veto</td><td></td><td></td><td></td><td></td></tr><tr><td>Observed events</td><td>6</td><td>3</td><td>2</td><td>1</td></tr><tr><td>Fitted bkg events</td><td>7.3 ± 2.0</td><td>2.1 ± 1.1</td><td>3.4 ± 0.8</td><td>1.2 ± 0.5</td></tr><tr><td>Fitted t<span style="text-decoration: overline">t</span> events</td><td>1.6 ± 0.5</td><td>0.50 ± 0.20</td><td>0.80 ± 0.30</td><td>0.20 ± 0.10</td></tr><tr><td>Fitted W + jets events</td><td>2.4 ± 0.9</td><td>0.6<sup>+0.8</sup><sub>-0.6</sub></td><td>1.1 ± 0.4</td><td>0.50 ± 0.30</td></tr><tr><td>Fitted Z + jets events</td><td>0.29 ± 0.13</td><td>0.1 ± 0.0</td><td>0.20 ± 0.10</td><td>0.026 ± 0.015</td></tr><tr><td>Fitted single-top events</td><td>0.48 ± 0.21</td><td>0.10 ± 0.10</td><td>0.20 ± 0.10</td><td>0.10 ± 0.10</td></tr><tr><td>Fitted diboson events</td><td>2.4 ± 1.9</td><td>0.7 ± 0.7</td><td>1.1 ± 0.7</td><td>0.4 ± 0.4</td></tr><tr><td>Fitted t<span style="text-decoration: overline">t</span> + V events</td><td>0.13 ± 0.04</td><td>0.023 ± 0.021</td><td>0.089 ± 0.021</td><td>0.015 ± 0.010</td></tr></tbody></table>
<table><caption>TABLE XIV. Event yields and background-only fit results for the 9J SR. Each column corresponds to a bin in $m_{eff}$ [GeV]. Uncertainties in the fitted background estimates combine statistical (in the simulated event yields) and systematic uncertainties. The uncertainties in this table are symmetrized for propagation purposes but truncated at zero to remain within the physical boundaries.</caption><thead><tr><th>9J</th><th>All $m_{eff}$ bins</th><th>[1000, 1500]</th><th>&gt;1500 [GeV]</th></tr></thead><tbody><tr><td>Observed events</td><td>10</td><td>6</td><td>4</td></tr><tr><td>Fitted bkg events</td><td>7 ± 4</td><td>4.0 ± 2.6</td><td>3.1 ± 1.6</td></tr><tr><td>Fitted W+jets events</td><td>0.028<sup>+0.057</sup><sub>-0.028</sub></td><td>0.006<sup>+0.018</sup><sub>-0.006</sub></td><td>0.022<sup>+0.043</sup><sub>-0.022</sub></td></tr><tr><td>Fitted t<span style="text-decoration: overline">t</span> events</td><td>6 ± 4</td><td>3.6 ± 2.5</td><td>2.3 ± 1.6</td></tr><tr><td>Fitted single-top events</td><td>0.7 ± 0.6</td><td>0.18<sup>+0.27</sup><sub>-0.18</sub></td><td>0.5 ± 0.4</td></tr><tr><td>Fitted t<span style="text-decoration: overline">t</span> + V events</td><td>0.30 ± 0.17</td><td>0.14 ± 0.09</td><td>0.16 ± 0.09</td></tr><tr><td>Fitted diboson events</td><td>0.15<sup>+0.16</sup><sub>-0.15</sub></td><td>0.029<sup>+0.041</sup><sub>-0.029</sub></td><td>0.12 ± 0.12</td></tr><tr><td>Fitted Z + jets events</td><td>0.008<sup>+0.011</sup><sub>-0.008</sub></td><td>...</td><td>0.008<sup>+0.011</sup><sub>-0.008</sub></td></tr></tbody></table>

$$f_{\text{closure}} = \frac{N_{\text{SR}_{9J}}^{\text{sim}}}{N_{\text{SR}_{9J}}^{\text{sim,est}}} = \frac{N_{\text{SR}_{9J}}^{\text{sim}} \cdot N_{\text{CR}_{B}}^{\text{sim}}}{N_{\text{CR}_{C}}^{\text{sim}} \cdot N_{\text{CR}_{A}}^{\text{sim}}}$$

where $N_{\text{SR}_{9J}}^{\text{sim}}$ is the number of events in a given region as predicted by simulation while $N_{\text{SR}_{9J}}^{\text{sim,est}}$ is the estimated number of events in the signal region based on the simulation predictions in regions A, B, and C. The estimated number of background events in the signal region can then be rewritten as

$$ \begin{aligned} N_{\text{SR}_{9J}}^{\text{est}} &= f_{\text{closure}} \cdot \frac{N_{\text{CR}_{A}}^{\text{obs}}}{N_{\text{CR}_{B}}^{\text{obs}}} \cdot N_{\text{CR}_{C}}^{\text{obs}} \\ &= N_{\text{SR}_{9J}}^{\text{sim}} \cdot \left( \frac{N_{\text{CR}_{A}}}{N_{\text{CR}_{B}}} \right)^{\text{obs}} / \left( \frac{N_{\text{CR}_{A}}}{N_{\text{CR}_{B}}} N_{\text{CR}_{C}} \right)^{\text{sim}} \\ &= N_{\text{SR}_{9J}}^{\text{sim}} \cdot \underbrace{\frac{N_{\text{CR}_{C}}^{\text{obs}}}{N_{\text{CR}_{C}}^{\text{sim}}} \cdot \underbrace{\left( \frac{N_{\text{CR}_{A}}}{N_{\text{CR}_{B}}} \right)^{\text{obs}}}_{\mu_{C}}}_{\mu_{A/B}} \cdot \underbrace{\left( \frac{N_{\text{CR}_{A}}}{N_{\text{CR}_{B}}} \right)^{\text{sim}}}_{\mu_{A/B}}, \end{aligned} $$

<figure><img src="image_3.png" /><figcaption>FIG. 3. Comparison of the observed and expected event yields in the 2J validation and signal regions. Uncertainties in the background estimates include both the statistical (in the simulated event yields) and systematic uncertainties. Both the integrated regions and the regions for each $m_{eff}$ bin are presented.</figcaption></figure>
<figure><img src="image_4.png" /><figcaption>FIG. 4. Comparison of the observed and expected event yields in the 4J low-x validation and signal regions. Uncertainties in the background estimates include both the statistical (in the simulated event yields) and systematic uncertainties. Both the integrated regions and the regions for each $m_{eff}$ bin are presented.</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>FIG. 5. Comparison of the observed and expected event yields in the 4J high-x validation and signal regions. Uncertainties in the background estimates include both the statistical (in the simulated event yields) and systematic uncertainties. Both the integrated regions and the regions for each $m_{eff}$ bin are presented.</figcaption></figure>
<figure><img src="image_6.png" /><figcaption>FIG. 6. Comparison of the observed and expected event yields in the 6J validation and signal regions. Uncertainties in the background estimates include both the statistical (in the simulated event yields) and systematic uncertainties. Both the integrated regions and the regions for each $m_{\text{eff}}$ bin are presented.</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>FIG. 7. Comparison of the observed and expected event yields in the 9J validation and signal regions. Uncertainties in the background estimates include both the statistical (in the simulated event yields) and systematic uncertainties. Both the integrated regions and the regions for each $m_{\text{eff}}$ bin are presented.</figcaption></figure>
where $N_{\text{region}}^{\text{obs}}$ is the observed number of events in a given region, $\mu_C$ is the normalization parameter in region C, and the normalization parameter $\mu_{A/B}$ is fitted simultaneously with the normalization $\mu_B$ of the backgrounds in region CR$_B$ according to

$$N_{\text{CRB}}^{\text{obs}} = N_{\text{CRB}}^{\text{sim}} \cdot \underbrace{\frac{N_{\text{CRB}}^{\text{obs}}}{N_{\text{CRB}}^{\text{sim}}} \quad \text{and} \quad N_{\text{CRA}}^{\text{obs}} = N_{\text{CRA}}^{\text{sim}} \cdot \underbrace{\frac{\left(\frac{N_{\text{CRA}}}{N_{\text{CRB}}}\right)^{\text{obs}}}{\left(\frac{N_{\text{CRA}}}{N_{\text{CRB}}}\right)^{\text{sim}}} \cdot \frac{N_{\text{CRB}}^{\text{obs}}}{N_{\text{CRB}}^{\text{sim}}}}_{\mu_{A/B}}$$

The control regions listed in Table VIII are optimized to provide a sufficient number of events in the backgrounds of interest, low contamination from the signal models considered, and a closure parameter $f_{\text{closure}}$ close to unity. All control regions are fitted simultaneously in two bins requiring either zero or at least one b-tagged signal jet to enrich the contributions from the W+jets and top

backgrounds, respectively. Therefore, the normalization factors $\mu_B$, $\mu_C$, and $\mu_{A/B}$ exist separately for the W+jets and top backgrounds. The top backgrounds considered in the fit comprise $t\bar{t}$ as well as single-top production processes, which are treated with a common set of normalization parameters.

To validate that the fitted ratio of low-$m_T$ to high-$m_T$ events ($\mu_{A/B}$) extrapolates to high values of $N_{\text{jet}}$, a validation region VR $m_T$ with seven or eight jets and high $m_T$ requirements is introduced. Similarly, a validation region VR $N_{\text{jet}}$ with at least nine jets and moderate $m_T$ requirements is introduced to validate the extrapolation of the normalization factor $\mu_C$ in region CR$_C$ to higher $m_T$ values. Since the normalization factors for different jet multiplicities are expected to differ, a control region CR$_{C'}$ along with its normalization factor ($\mu_{C'}$) is introduced. This region is only used to obtain the background estimate in VR $m_T$. Similarly, a control region CR$_{A'}$ is constructed to obtain the normalization factor $\mu_{A'/B}$ that is needed for the background estimation in validation

<figure><img src="image_8.png" /><figcaption>FIG. 8. Normalization factors $\mu_{\text{top}}$ and $\mu_W$ of the top and W+jets backgrounds in the $m_{\text{eff}}$ bins of the 2J, 4J high-x, 4J low-x, and 6J SRs obtained with the background-only fit. The error bars correspond to the uncertainties as derived in the fit.</figcaption></figure>
region VR $N_{jet}$. The definition of the validation regions along with their corresponding control regions is given in Table VIII.

## VII. SYSTEMATIC UNCERTAINTIES

Experimental and theoretical sources of systematic uncertainty are described in this section. Their effects are evaluated for all simulated signal and background events.

The dominant experimental systematic effects are the uncertainties associated with the jet energy scale (JES) and resolution (JER) and with the b-tagging efficiency and mistagging rate. The impact of the jet-related uncertainties on the total background prediction ranges from 1.3% in the 6J SR to 18% in the 9J SR. Similarly, the impact of the uncertainties associated with the b-tagging procedure amounts to 1.9% in the 6J SR bins with at least one b-tagged jet and increases to 9.5% in the 6J SR bins with no b-tagged jets. The simulation is reweighted to match the distribution of the average number of proton-proton interactions per bunch crossing ($\mu$) observed in data. The uncertainty in $\mu$ is propagated by varying up and down the reweighting factor: it becomes relevant in the signal regions characterized by the highest jet multiplicities.

Uncertainties in the theoretical predictions and the modeling of simulated events are also considered. For the $W^+$ jets and the $t\bar{t}$ and single top backgrounds, they affect the extrapolation from each $m_{eff}$ bin in the control regions to the corresponding bin in the signal regions. In the 9J SR the $f_{closure}$ parameter used in the background estimation in this channel is affected as well. For all the other background sources, they impact the inclusive cross section of each specific process, the acceptance of the analysis selection requirements and the shape of the $m_{eff}$ distribution in each SR.

An uncertainty stems from the choice of MC event generator modeling the $t\bar{t}$, single top, diboson and $W/Z$ + jets processes. For $t\bar{t}$ and single top, POWHEG-BOX is compared with MG5_AMc@NLO [38] and the relative difference in the extrapolation factors is evaluated. For $W/Z$ + jets, the predictions from SHERPA are compared with MG5_AMc@NLO [38]. For dibosons, the event yield predictions from SHERPA are compared with POWHEG-BOX interfaced to PYTHIA. The impact of varying the amount of initial- and final-state radiation is evaluated for $t\bar{t}$ and single top production. Specific samples are used, with altered renormalization and factorization scales as well as parton shower and NLO radiation [50]. Moreover, the difference between the predictions from POWHEG-BOX interfaced to PYTHIA and to HERWIG++ [96] is computed to estimate the

<figure><img src="image_9.png" /><figcaption>FIG. 9. Comparison of estimated Standard Model background event yield from $t\bar{t}$ processes with dileptonic decays in the 2J, 4J high-x, 4J low-x, and 6J SR using the nominal semi-data-driven background estimation technique and the alternative object-replacement technique described in Sec. VI. The error bands include both the statistical and systematic uncertainties.</figcaption></figure>
uncertainty associated with the parton shower modeling. For W/Z + jets samples, the uncertainties in the renormalization, factorization, resummation scales and the matching scale between matrix elements and parton shower (CKKW-L) are evaluated by varying up and down by a factor of 2 the corresponding parameters in SHERPA. For $t\bar{t}$ and W + jets samples, the uncertainties due to choosing the PDF set CT10 [52] are considered.

Inclusive $WWbb$ events generated using MG5AMC@NLO [38] are compared to the sum of $t\bar{t}$ and $Wt$ production, to assign an uncertainty to the interference effects between single top and $t\bar{t}$ production at NLO. The uncertainty in the inclusive Z + jets cross section, amounting to 5%, is accounted for [97]. An overall 6% systematic uncertainty in the inclusive cross section of diboson processes is also considered. In addition, the

SHERPA parameters controlling the renormalization, factorization, resummation and matching scales are varied by a factor of 2 to estimate the corresponding uncertainties. An uncertainty of 30% is assigned to the small contributions of $t\bar{t} + W/Z/WW$.

The total systematic uncertainty in the predicted background yields in the various signal regions ranges from 12% in the 2J SR bins with $\ge$1 b-tagged jet, to 50% in the 9J SR. The largest uncertainties in the SR bins with $\ge$1 b-tagged jet originate from the modeling of $t\bar{t}$ events and amount to 5% in the 2J SR, increasing to 40% in the 9J SR. Similarly, in the SR bins where b-tagged jets are vetoed, the dominant source of systematic uncertainty is the modeling of W + jets events, ranging from 9% in the 6J SR to 20% in the 4J low-x SR. Other important uncertainties are those associated with the finite size of the MC

<figure><img src="image_10.png" /><figcaption>FIG. 10. The $m_{eff}$ distribution in 2J (top left), 4J low-x (top right), 4J high-x (bottom left) and 6J (bottom right) b-veto signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.</figcaption></figure>
samples, which amount to 18% in the 6J SR, and the theoretical uncertainties originating from the modeling of the diboson background, amounting to 26% in the 6J SR. Tables IX–XI list the breakdown of the dominant systematic uncertainties in background estimates in the various signal regions.

For the signal processes, the modeling of initial-state radiation can be affected by sizable theoretical uncertainty. The uncertainties in the expected yields for SUSY signal models are estimated with variations of a factor of 2 to the $\text{MG}_{5\_\text{AMC}}$@NLO parameters corresponding to the renormalization, factorization and jet matching scales, and to the PYTHIA shower tune parameters. The overall uncertainties range from about 1% for signal models with large mass splitting between the gluino or squark, the

chargino, and the neutralino, to 35% for models with very compressed mass spectra.

VIII. RESULTS AND INTERPRETATION

The statistical interpretation of the results is performed based on a profile likelihood method [98] using the HistFitter framework [99]. The likelihood function consists of a product of Poisson probability density functions for the signal and control regions that contribute to the fit. The inputs to the likelihood function are the observed numbers of data events and the expected numbers of signal and SM background events in each region. Three normalization factors, one for signal, one for W+jets, one for $t\bar{t}$ and single top, are introduced to adjust the relative

<figure><img src="image_11.png" /><figcaption>FIG. 11. The $m_{\text{eff}}$ distribution in 2J (top left), 4J low-x (top right), 4J high-x (bottom left) and 6J (bottom right) b-tag signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.</figcaption></figure>
<figure><img src="image_12.png" /><figcaption>FIG. 12. The $m_{\text{eff}}$ distribution in the 9J signal region after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.</figcaption></figure>

contributions of the main background and signal components. The small sources of SM background, i.e., diboson, $Z + \text{jets}$ and $t\bar{t} + V$, are estimated directly from simulation. The uncertainties are implemented in the fit as nuisance parameters, which are correlated between the SRs and the CRs. The systematic uncertainties described in Sec. VII are constrained by Gaussian probability density functions, while the statistical uncertainties are constrained by Poisson probability density functions.

The observed numbers of events in the signal regions are given in Tables XII–XIV, along with the SM background prediction as determined with the background-only fit. In a background-only fit, the data event yields in the CRs are used to determine the two background normalization factors: for $W + \text{jets}$ and for $t\bar{t}$ and single top production. The fit is independent of the observation in the SR, and does not consider signal contamination in the CRs. The above-mentioned signal normalization parameter is therefore not included in this fit configuration.

The compatibility of the observed and expected event yields in both the validation and signal regions is illustrated in Figures 3–7. No significant excess in data is observed over the SM prediction.

The top and $W + \text{jets}$ background normalization factors obtained for the 2J, 4J low-x, 4J high-x, and 6J SRs are shown in bins of $m_{\text{eff}}$ in Fig. 8. A trend toward smaller normalization factors at large values of $m_{\text{eff}}$ is observed, which demonstrates the necessity of applying the same binning requirements in control and signal regions. The predicted event yields from $t\bar{t}$ events in which both top quarks decay semileptonically are cross-checked using the alternative object-replacement method described in Sec. VI. Figure 9 shows that the background estimates obtained from the two methods are consistent. Figures 10,11 show the $m_{\text{eff}}$ distribution in 2J, 4J low-x, 4J high-x and 6J in b-tag and b-veto signal regions after fit. Figure 12 shows the $m_{\text{eff}}$ distribution in 9J signal region after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

Using the results of the background-only fit, a model-independent limit fit is performed to test for the presence of any beyond-the-Standard-Model (BSM) physics processes that contribute to the SR (“disc” SR in Table II). The BSM signal is assumed to contribute only to the SR and not to the CRs, thus giving a conservative estimate of background in the SR. Observed ($S_{\text{obs}}^{95}$) and expected ($S_{\text{exp}}^{95}$) 95% confidence level (C.L.) upper limits on the number of BSM signal events are derived using the CLs prescription [100]. Table XV presents these limits, together with the upper limits on the visible BSM cross section, $\langle\epsilon\sigma\rangle_{\text{obs}}^{95}$, defined as the product of acceptance, selection efficiency and production cross section. The upper limits on the visible BSM cross section are calculated by dividing the observed upper limit on the beyond-SM events by the integrated luminosity of $36.1 \text{ fb}^{-1}$. Moreover, the discovery p-values are given. They quantify the probability under the background-only hypothesis to produce event yields greater than or equal to the observed data.

Additionally, the results are interpreted in the specific supersymmetric scenarios described in Sec. III using

<table><caption>TABLE XV. Results of the model-independent limit fits. For each SR, the observed 95% C.L. upper limit on the visible cross section ($\langle\epsilon\sigma\rangle_{\text{obs}}^{95}$), the observed ($S_{\text{obs}}^{95}$) and expected ($S_{\text{exp}}^{95}$) 95% C.L. upper limits on the BSM event yield, and the one-sided discovery p-value [$p(s = 0)$] are presented. The p-values are capped at 0.5 if fewer events than the fitted background estimate are observed.</caption><thead><tr><th>SR<sub>disc</sub></th><th>2J</th><th>4J high-x</th><th>4J low-x (gluino)</th><th>4J low-x (squark)</th><th>6J (gluino)</th><th>6J (squark)</th><th>9J</th></tr></thead><tbody><tr><td>Observed events</td><td>80</td><td>16</td><td>24</td><td>50</td><td>0</td><td>28</td><td>4</td></tr><tr><td>Fitted bkg events</td><td>67 ± 6</td><td>17.7 ± 2.7</td><td>17.2 ± 3.2</td><td>47 ± 7</td><td>2.6 ± 0.6</td><td>23.4 ± 3.1</td><td>3.1 ± 1.6</td></tr><tr><td>⟨εσ⟩<sup>95</sup><sub>obs</sub> [fb]</td><td>0.92</td><td>0.27</td><td>0.50</td><td>0.62</td><td>0.08</td><td>0.46</td><td>0.20</td></tr><tr><td>S<sup>95</sup><sub>obs</sub></td><td>33.1</td><td>9.8</td><td>18.0</td><td>22.5</td><td>3.0</td><td>16.6</td><td>7.1</td></tr><tr><td>S<sup>95</sup><sub>exp</sub></td><td>21.6<sup>+9.2</sup><sub>-5.6</sub></td><td>10.8<sup>+3.7</sup><sub>-3.0</sub></td><td>11.8<sup>+4.8</sup><sub>-2.7</sub></td><td>19.9<sup>+7.5</sup><sub>-5.6</sub></td><td>4.5<sup>+1.8</sup><sub>-1.0</sub></td><td>12.7<sup>+5.0</sup><sub>-4.0</sub></td><td>6.0<sup>+2.2</sup><sub>-1.2</sub></td></tr><tr><td>p(s = 0)</td><td>0.10</td><td>0.50</td><td>0.10</td><td>0.35</td><td>0.50</td><td>0.21</td><td>0.34</td></tr></tbody></table>
<figure><img src="image_13.png" /><figcaption>FIG. 13. Exclusion contours for gluino one-step $x = 1/2$ (top left), gluino one-step variable-$x$ (top right), squark one-step $x = 1/2$ (middle left) and squark one-step variable-$x$ (middle right), gluino two-step (bottom left), and the pMSSM scenario (bottom right). The red solid line corresponds to the observed limit with the red dotted lines indicating the $\pm 1\sigma$ variation of this limit due to the effect of theoretical scale and PDF uncertainties in the signal cross section. The dark gray dashed line indicates the expected limit with the yellow band representing the $\pm 1\sigma$ variation of the median expected limit due to the experimental and theoretical uncertainties. For reference, exclusion bounds from previous searches with $20.3 \text{ fb}^{-1}$ at 8 TeV center-of-mass energy [28] and $3.2 \text{ fb}^{-1}$ at 13 TeV center-of-mass energy [22,30] are overlaid where applicable by the gray area (the observed limit is shown by the solid line, while the dashed line shows the expected limit).</figcaption></figure>

*model-dependent limit* fits. A *model-dependent limit* fit takes the data event yields in multiple, statistically independent SRs and their associated CRs to compute an upper limit on the cross section of a targeted SUSY model. The fit

includes the expected signal contributions to the SRs and to the CRs, scaled by a floating signal normalization factor. The background normalization factors are also determined simultaneously in the fit.
The sparticle mass in a specific SUSY model can be excluded if the upper limit of the signal normalization factor obtained in the fit is smaller than unity.

For the gluino/squark one-step models, a model-dependent fit is performed over all bins of the 2J, 4J high-x, 4J low-x, and 6J SRs. An independent set of background normalization factors are allocated for each bin of each SR ("excl" SR in Table II) and its associated CRs. Figure 13 (top and middle) shows the observed and expected exclusion bounds at 95% C.L. for the one-step simplified models with gluino and squark production. Gluino masses up to 2.1 TeV and squark masses up to 1.25 TeV are excluded.

Figure 13 (bottom) shows the exclusion contours of the 9J SR (Table III) for the gluino two-step as well as the pMSSM scenario described in Sec. III. In both cases the limits reach well beyond 1.7 TeV in gluino mass.

## IX. CONCLUSION

A search for the pair production of squarks and gluinos in proton-proton collisions provided by the LHC at a center-of-mass energy of $\sqrt{s} = 13$ TeV has been performed by the ATLAS Collaboration. Events containing one isolated electron or muon, two or more jets, and large missing transverse momentum are selected in the data collected in 2015 and 2016, corresponding to an integrated luminosity of 36.1 fb$^{-1}$. No significant excess over the Standard Model background prediction is observed. Exclusion limits are set at 95% C.L. on generic new phenomena beyond the Standard Model and on sparticle masses in a number of specific SUSY scenarios. The exclusion limits extend up to 2.1 TeV in gluino mass and 1.25 TeV in squark mass thus significantly improving on the sensitivity of previous searches in this final state.

## 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, Australia; 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-DSM/IRFU, France; SRNSF, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, Hong Kong SAR, China; ISF, I-CORE 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, the Canada Council, CANARIE, CRC, Compute Canada, FQRNT, and the Ontario Innovation Trust, Canada; EPLANET, ERC, ERDF, FP7, Horizon 2020 and Marie Skłodowska-Curie Actions, European Union; Investissements d'Avenir Labex and Idex, ANR, Région Auvergne and Fondation Partager le Savoir, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF; BSF, GIF and Minerva, Israel; BRF, Norway; CERCA Programme Generalitat de Catalunya, Generalitat Valenciana, 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 (UK) and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resource providers. Major contributors of computing resources are listed in Ref. [101].

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D. R. Davis,⁴⁸ P. Davison,⁸¹ E. Dawe,⁹¹ I. Dawson,¹⁴¹ K. De,⁸ R. de Asmundis,¹⁰⁶a A. De Benedetti,¹¹⁵ S. De Castro,²²a,²²b
S. De Cecco,⁸³ N. De Groot,¹⁰⁸ P. de Jong,¹⁰⁹ H. De la Torre,⁹³ F. De Lorenzi,⁶⁷ A. De Maria,⁵⁷ D. De Pedis,¹³⁴a
A. De Salvo,¹³⁴a U. De Sanctis,¹³⁵a,¹³⁵b A. De Santo,¹⁵¹ K. De Vasconcelos Corga,⁸⁸ J. B. De Vivie De Regie,¹¹⁹

W. J. Dearnaley,⁷⁵ R. Debbe,²⁷ C. Debenedetti,¹³⁹ D. V. Dedovich,⁶⁸ N. Dehghanian,³ I. Deigaard,¹⁰⁹ M. Del Gaudio,⁴⁰a,⁴⁰b
J. Del Peso,⁸⁵ D. Delgove,¹¹⁹ F. Deliot,¹³⁸ C. M. Delitzsch,⁷ A. Dell'Acqua,³² L. Dell'Asta,²⁴ M. Dell'Orso,¹²⁶a,¹²⁶b

M. Della Pietra,¹⁰⁶a,¹⁰⁶b D. della Volpe,⁵² M. Delmastro,⁵ C. Delporte,¹¹⁹ P. A. Delsart,⁵⁸ D. A. DeMarco,¹⁶¹ S. Demers,¹⁷⁹

M. Demichev,⁶⁸ A. Demilly,⁸³ S. P. Denisov,¹³² D. Denysiuk,¹³⁸ D. Derendarz,⁴² J. E. Derkaoui,¹³⁷d F. Derue,⁸³ P. Dervan,⁷⁷

K. Desch,²³ C. Deterre,⁴⁵ K. Dette,⁴⁶ M. R. Devesa,²⁹ P. O. Deviveiros,³² A. Dewhurst,¹³³ S. Dhaliwal,²⁵ F. A. Di Bello,⁵²

A. Di Ciaccio,¹³⁵a,¹³⁵b L. Di Ciaccio,⁵ W. K. Di Clemente,¹²⁴ C. Di Donato,¹⁰⁶a,¹⁰⁶b A. Di Girolamo,³² B. Di Girolamo,³²

B. Di Micco,¹³⁶a,¹³⁶b R. Di Nardo,³² K. F. Di Petrillo,⁵⁹ A. Di Simone,⁵¹ R. Di Sipio,¹⁶¹ D. Di Valentino,³¹ C. Diaconu,⁸⁸
M. Diamond,¹⁶¹ F. A. Dias,³⁹ M. A. Diaz,³⁴a E. B. Diehl,⁹² J. Dietrich,¹⁷ S. Díez Cornell,⁴⁵ A. Dimitrievska,¹⁴

J. Dingfelder,²³ P. Dita,²⁸b S. Dita,²⁸b F. Dittus,³² F. Djama,⁸⁸ T. Djobava,⁵⁴b J. I. Djuvsland,⁶⁰a M. A. B. do Vale,²⁶c

D. Dobos,³² M. Dobre,²⁸b C. Doglioni,⁸⁴ J. Dolejsi,¹³¹ Z. Dolezal,¹³¹ M. Donadelli,²⁶d S. Donati,¹²⁶a,¹²⁶b P. Dondero,¹²³a,¹²³b
J. Donini,³⁷ J. Dopke,¹³³ A. Doria,¹⁰⁶a M. T. Dova,⁷⁴ A. T. Doyle,⁵⁶ E. Drechsler,⁵⁷ M. Dris,¹⁰ Y. Du,³⁶b

J. Duarte-Campderros,¹⁵⁵ A. Dubreuil,⁵² E. Duchovni,¹⁷⁵ G. Duckeck,¹⁰² A. Ducourthial,⁸³ O. A. Ducu,⁹⁷q D. Duda,¹⁰⁹

A. Dudarev,³² A. Chr. Dudder,⁸⁶ E. M. Duffield,¹⁶ L. Duflot,¹¹⁹ M. Dührssen,³² M. Dumancic,¹⁷⁵ A. E. Dumitriu,²⁸b
A. K. Duncan,⁵⁶ M. Dunford,⁶⁰a H. Duran Yildiz,⁴a M. Düren,⁵⁵ A. Durglishvili,⁵⁴b D. Duschinger,⁴⁷ B. Dutta,⁴⁵
D. Duvnjak,¹ M. Dyndal,⁴⁵ B. S. Dziedzic,⁴² C. Eckardt,⁴⁵ K. M. Ecker,¹⁰³ R. C. Edgar,⁹² T. Eifert,³² G. Eigen,¹⁵

K. Einsweiler,¹⁶ T. Ekelof,¹⁶⁸ M. El Kacimi,¹³⁷c R. El Kosseifi,⁸⁸ V. Ellajosyula,⁸⁸ M. Ellert,¹⁶⁸ S. Elles,⁵ F. Ellinghaus,¹⁷⁸

A. A. Elliot,¹⁷² N. Ellis,³² J. Elmsheuser,²⁷ M. Elsing,³² D. Emeliyanov,¹³³ Y. Enari,¹⁵⁷ O. C. Endner,⁸⁶ J. S. Ennis,¹⁷³

J. Erdmann,⁴⁶ A. Ereditato,¹⁸ M. Ernst,²⁷ S. Errede,¹⁶⁹ M. Escalier,¹¹⁹ C. Escobar,¹⁷⁰ B. Esposito,⁵⁰ O. Estrada Pastor,¹⁷⁰

A. I. Etienvre,¹³⁸ E. Etzion,¹⁵⁵ H. Evans,⁶⁴ A. Ezhilov,¹²⁵ M. Ezzi,¹³⁷e F. Fabbri,²²a,²²b L. Fabbri,²²a,²²b V. Fabiani,¹⁰⁸

G. Facini,⁸¹ R. M. Fakhrutdinov,¹³² S. Falciano,¹³⁴a R. J. Falla,⁸¹ J. Faltova,³² Y. Fang,³⁵a M. Fanti,⁹⁴a,⁹⁴b A. Farbin,⁸

A. Farilla,¹³⁶a C. Farina,¹²⁷ E. M. Farina,¹²³a,¹²³b T. Farooque,⁹³ S. Farrell,¹⁶ S. M. Farrington,¹⁷³ P. Farthouat,³² F. Fassi,¹³⁷e

P. Fassnacht,³² D. Fassouliotis,⁹ M. Faucci Giannelli,⁸⁰ A. Favareto,⁵³a,⁵³b W. J. Fawcett,¹²² L. Fayard,¹¹⁹ O. L. Fedin,¹²⁵,r
W. Fedorko,¹⁷¹ S. Feigl,¹²¹ L. Feligioni,⁸⁸ C. Feng,³⁶b E. J. Feng,³² H. Feng,⁹² M. J. Fenton,⁵⁶ A. B. Fenyuk,¹³²

L. Feremenga,⁸ P. Fernandez Martinez,¹⁷⁰ S. Fernandez Perez,¹³ J. Ferrando,⁴⁵ A. Ferrari,¹⁶⁸ P. Ferrari,¹⁰⁹ R. Ferrari,¹²³a

D. E. Ferreira de Lima,⁶⁰b A. Ferrer,¹⁷⁰ D. Ferrere,⁵² C. Ferretti,⁹² F. Fiedler,⁸⁶ A. Filipčič,⁷⁸ M. Filipuzzi,⁴⁵ F. Filthaut,¹⁰⁸

M. Fincke-Keeler,¹⁷² K. D. Finelli,¹⁵² M. C. N. Fiolhais,¹²⁸a,¹²⁸c,⁵ L. Fiorini,¹⁷⁰ A. Fischer,² C. Fischer,¹³ J. Fischer,¹⁷⁸
W. C. Fisher,⁹³ N. Flaschel,⁴⁵ I. Fleck,¹⁴³ P. Fleischmann,⁹² R. R. M. Fletcher,¹²⁴ T. Flick,¹⁷⁸ B. M. Flierl,¹⁰²

L. R. Flores Castillo,⁶²a M. J. Flowerdew,¹⁰³ G. T. Forcolin,⁸⁷ A. Formica,¹³⁸ F. A. Förster,¹³ A. Forti,⁸⁷ A. G. Foster,¹⁹

D. Fournier,¹¹⁹ H. Fox,⁷⁵ S. Fracchia,¹⁴¹ P. Francavilla,⁸³ M. Franchini,²²a,²²b S. Franchino,⁶⁰a D. Francis,³² L. Franconi,¹²¹

M. Franklin,⁵⁹ M. Frate,¹⁶⁶ M. Fraternali,¹²³a,¹²³b D. Freeborn,⁸¹ S. M. Fressard-Batraneanu,³² B. Freund,⁹⁷ D. Froidevaux,³²

J. A. Frost,¹²² C. Fukunaga,¹⁵⁸ T. Fusayasu,¹⁰⁴ J. Fuster,¹⁷⁰ C. Gabaldon,⁵⁸ O. Gabizon,¹⁵⁴ A. Gabrielli,²²a,²²b A. Gabrielli,¹⁶
G. P. Gach,⁴¹a S. Gadatsch,³² S. Gadomski,⁸⁰ G. Gagliardi,⁵³a,⁵³b L. G. Gagnon,⁹⁷ C. Galea,¹⁰⁸ B. Galhardo,¹²⁸a,¹²⁸c
E. J. Gallas,¹²² B. J. Gallop,¹³³ P. Gallus,¹³⁰ G. Galster,³⁹ K. K. Gan,¹¹³ S. Ganguly,³⁷ Y. Gao,⁷⁷ Y. S. Gao,¹⁴⁵,h

F. M. Garay Walls,⁴⁹ C. García,¹⁷⁰ J. E. García Navarro,¹⁷⁰ J. A. García Pascual,³⁵a M. Garcia-Sciveres,¹⁶ R. W. Gardner,³³
N. Garelli,¹⁴⁵ V. Garonne,¹²¹ A. Gascon Bravo,⁴⁵ K. Gasnikova,⁴⁵ C. Gatti,⁵⁰ A. Gaudiello,⁵³a,⁵³b G. Gaudio,¹²³a

I. L. Gavrilenko,⁹⁸ C. Gay,¹⁷¹ G. Gaycken,²³ E. N. Gazis,¹⁰ C. N. P. Gee,¹³³ J. Geisen,⁵⁷ M. Geisen,⁸⁶ M. P. Geisler,⁶⁰a
K. Gellerstedt,¹⁴⁸a,¹⁴⁸b C. Gemme,⁵³a M. H. Genest,⁵⁸ C. Geng,⁹² S. Gentile,¹³⁴a,¹³⁴b C. Gentsos,¹⁵⁶ S. George,⁸⁰
D. Gerbaudo,¹³ A. Gershon,¹⁵⁵ G. Geßner,⁴⁶ S. Ghasemi,¹⁴³ M. Ghneimat,²³ B. Giacobbe,²²a S. Giagu,¹³⁴a,¹³⁴b

N. Giangiacomi,²²a,²²b P. Giannetti,¹²⁶a,¹²⁶b S. M. Gibson,⁸⁰ M. Gignac,¹⁷¹ M. Gilchriese,¹⁶ D. Gillberg,³¹ G. Gilles,¹⁷⁸
D. M. Gingrich,³e N. Giokaris,⁹a M. P. Giordani,¹⁶⁷a,¹⁶⁷c F. M. Giorgi,²²a P. F. Giraud,¹³⁸ P. Giromini,⁵⁹

G. Giugliarelli,¹⁶⁷a,¹⁶⁷c D. Giugni,⁹⁴a F. Giuli,¹²² C. Giuliani,¹⁰³ M. Giulini,⁶⁰b B. K. Gjelsten,¹²¹ S. Gkaitatzis,¹⁵⁶ I. Gkialas,⁹t

E. L. Gkougkousis,¹³⁹ P. Gkountoumis,¹⁰ L. K. Gladilin,¹⁰¹ C. Glasman,⁸⁵ J. Glatzer,¹³ P. C. F. Glaysher,⁴⁵ A. Glazov,⁴⁵

M. Goblirsch-Kolb,²⁵ J. Godlewski,⁴² S. Goldfarb,⁹¹ T. Golling,⁵² D. Golubkov,¹³² A. Gomes,¹²⁸a,¹²⁸b,¹²⁸d R. Gonçalo,¹²⁸a
R. Goncalves Gama,²⁶a J. Goncalves Pinto Firmino Da Costa,¹³⁸ G. Gonella,⁵¹ L. Gonella,¹⁹ A. Gongadze,⁶⁸

S. González de la Hoz,¹⁷⁰ S. Gonzalez-Sevilla,⁵² L. Goossens,³² P. A. Gorbounov,⁹⁹ H. A. Gordon,²⁷ I. Gorelov,¹⁰⁷

B. Gorini,³² E. Gorini,⁷⁶a,⁷⁶b A. Gorišek,⁷⁸ A. T. Goshaw,⁴⁸ C. Gössling,⁴⁶ M. I. Gostkin,⁶⁸ C. A. Gottardo,²³ C. R. Goudet,¹¹⁹

D. Goujdami,¹³⁷c A. G. Goussiou,¹⁴⁰ N. Govender,¹⁴⁷b,u E. Gozani,¹⁵⁴ L. Graber,⁵⁷ I. Grabowska-Bold,⁴¹a P. O. J. Gradin,¹⁶⁸
J. Gramling,¹⁶⁶ E. Gramstad,¹²¹ S. Grancagnolo,¹⁷ V. Gratchev,¹²⁵ P. M. Gravila,²⁸f C. Gray,⁵⁶ H. M. Gray,¹⁶

Z. D. Greenwood,⁸²,v C. Grefe,²³ K. Gregersen,⁸¹ I. M. Gregor,⁴⁵ P. Grenier,¹⁴⁵ K. Grevtsov,⁵ J. Griffiths,⁸ A. A. Grillo,¹³⁹ K. Grimm,⁷⁵ S. Grinstein,¹³,w Ph. Gris,³⁷ J.-F. Grivaz,¹¹⁹ S. Groh,⁸⁶ E. Gross,¹⁷⁵ J. Grosse-Knetter,⁵⁷ G. C. Grossi,⁸²

Z. J. Grout,⁸¹ A. Grummer,¹⁰⁷ L. Guan,⁹² W. Guan,¹⁷⁶ J. Guenther,⁶⁵ F. Guescini,¹⁶³a D. Guest,¹⁶⁶ O. Gueta,¹⁵⁵ B. Gui,¹¹³ E. Guido,⁵³a,⁵³b T. Guillemin,⁵ S. Guindon,² U. Gul,⁵⁶ C. Gumpert,³² J. Guo,³⁶c W. Guo,⁹² Y. Guo,³⁶a,x R. Gupta,⁴³

S. Gupta,¹²² G. Gustavino,¹³⁴a,¹³⁴b P. Gutierrez,¹¹⁵ N. G. Gutierrez Ortiz,⁸¹ C. Gutschow,⁸¹ C. Guyot,¹³⁸ M. P. Guzik,⁴¹a

C. Gwenlan,¹²² C. B. Gwilliam,⁷⁷ A. Haas,¹¹² C. Haber,¹⁶ H. K. Hadavand,⁸ N. Haddad,¹³⁷e A. Hadef,⁸⁸ S. Hageböck,²³ M. Hagihara,¹⁶⁴ H. Hakobyan,¹⁸⁰,a M. Haleem,⁴⁵ J. Haley,¹¹⁶ G. Halladjian,⁹³ G. D. Hallewell,⁸⁸ K. Hamacher,¹⁷⁸

P. Hamal,¹¹⁷ K. Hamano,¹⁷² A. Hamilton,¹⁴⁷a G. N. Hamity,¹⁴¹ P. G. Hamnett,⁴⁵ L. Han,³⁶a S. Han,³⁵a,³⁵d K. Hanagaki,⁶⁹,y

K. Hanawa,¹⁵⁷ M. Hance,¹³⁹ B. Haney,¹²⁴ P. Hanke,⁶⁰a J. B. Hansen,³⁹ J. D. Hansen,³⁹ M. C. Hansen,²³ P. H. Hansen,³⁹ K. Hara,¹⁶⁴ A. S. Hard,¹⁷⁶ T. Harenberg,¹⁷⁸ F. Hariri,¹¹⁹ S. Harkusha,⁹⁵ R. D. Harrington,⁴⁹ P. F. Harrison,¹⁷³

N. M. Hartmann,¹⁰² M. Hasegawa,⁷⁰ Y. Hasegawa,¹⁴² A. Hasib,⁴⁹ S. Hassani,¹³⁸ S. Haug,¹⁸ R. Hauser,⁹³ L. Hauswald,⁴⁷ L. B. Havener,³⁸ M. Havranek,¹³⁰ C. M. Hawkes,¹⁹ R. J. Hawkings,³² D. Hayakawa,¹⁵⁹ D. Hayden,⁹³ C. P. Hays,¹²² J. M. Hays,⁷⁹ H. S. Hayward,⁷⁷ S. J. Haywood,¹³³ S. J. Head,¹⁹ T. Heck,⁸⁶ V. Hedberg,⁸⁴ L. Heelan,⁸ S. Heer,²³

K. K. Heidegger,⁵¹ S. Heim,⁴⁵ T. Heim,¹⁶ B. Heinemann,⁴⁵,z J. J. Heinrich,¹⁰² L. Heinrich,¹¹² C. Heinz,⁵⁵ J. Hejbal,¹²⁹ L. Helary,³² A. Held,¹⁷¹ S. Hellman,¹⁴⁸a,¹⁴⁸b C. Helsens,³² R. C. W. Henderson,⁷⁵ Y. Heng,¹⁷⁶ S. Henkelmann,¹⁷¹

A. M. Henriques Correia,³² S. Henrot-Versille,¹¹⁹ G. H. Herbert,¹⁷ H. Herde,²⁵ V. Herget,¹⁷⁷ Y. Hernández Jiménez,¹⁴⁷c

H. Herr,⁸⁶ G. Herten,⁵¹ R. Hertenberger,¹⁰² L. Hervas,³² T. C. Herwig,¹²⁴ G. G. Hesketh,⁸¹ N. P. Hessey,¹⁶³a J. W. Hetherly,⁴³

S. Higashino,⁶⁹ E. Higón-Rodriguez,¹⁷⁰ K. Hildebrand,³³ E. Hill,¹⁷² J. C. Hill,³⁰ K. H. Hiller,⁴⁵ S. J. Hillier,¹⁹ M. Hils,⁴⁷ I. Hinchliffe,¹⁶ M. Hirose,⁵¹ D. Hirschbuehl,¹⁷⁸ B. Hiti,⁷⁸ O. Hladik,¹²⁹ X. Hoad,⁴⁹ J. Hobbs,¹⁵⁰ N. Hod,¹⁶³a

M. C. Hodgkinson,¹⁴¹ P. Hodgson,¹⁴¹ A. Hoecker,³² M. R. Hoeferkamp,¹⁰⁷ F. Hoenig,¹⁰² D. Hohn,²³ T. R. Holmes,³³

M. Homann,⁴⁶ S. Honda,¹⁶⁴ T. Honda,⁶⁹ T. M. Hong,¹²⁷ B. H. Hooberman,¹⁶⁹ W. H. Hopkins,¹¹⁸ Y. Horii,¹⁰⁵ A. J. Horton,¹⁴⁴ J.-Y. Hostachy,⁵⁸ S. Hou,¹⁵³ A. Hoummada,¹³⁷a J. Howarth,⁸⁷ J. Hoya,⁷⁴ M. HRabovsky,¹¹⁷ J. Hrdinka,³² I. Hristova,¹⁷

J. HRivnac,¹¹⁹ T. Hryn'ova,⁵ A. Hrynevich,⁹⁶ P. J. Hsu,⁶³ S.-C. Hsu,¹⁴⁰ Q. Hu,³⁶a S. Hu,³⁶c Y. Huang,³⁵a Z. Hubacek,¹³⁰

F. Hubaut,⁸⁸ F. Huegging,²³ T. B. Huffman,¹²² E. W. Hughes,³⁸ G. Hughes,⁷⁵ M. Huhtinen,³² P. Huo,¹⁵⁰ N. Huseynov,⁶⁸,c

J. Huston,⁹³ J. Huth,⁵⁹ G. Iacobucci,⁵² G. Iakovidis,²⁷ I. Ibragimov,¹⁴³ L. Iconovidou-Fayard,¹¹⁹ Z. Idrissi,¹³⁷e P. Iengo,³² O. Igonkina,¹⁰⁹,aa T. Iizawa,¹⁷⁴ Y. Ikegami,⁶⁹ M. Ikeno,⁶⁹ Y. Ilchenko,¹¹,bb D. Iliadis,¹⁵⁶ N. Ilic,¹⁴⁵ G. Introzzi,¹²³a,¹²³b

P. Ioannou,⁹,a M. Iodice,¹³⁶a K. Iordanidou,³⁸ V. Ippolito,⁵⁹ M. F. Isacson,¹⁶⁸ N. Ishijima,¹²⁰ M. Ishino,¹⁵⁷ M. Ishitsuka,¹⁵⁹

C. Issever,¹²² S. Istin,²⁰a F. Ito,¹⁶⁴ J. M. Iturbe Ponce,⁶²a R. Iuppa,¹⁶²a,¹⁶²b H. Iwasaki,⁶⁹ J. M. Izen,⁴⁴ V. Izzo,¹⁰⁶a S. Jabbar,³ P. Jackson,¹ R. M. Jacobs,²³ V. Jain,² K. B. Jakobi,⁸⁶ K. Jakobs,⁵¹ S. Jakobsen,⁶⁵ T. Jakoubek,¹²⁹ D. O. Jamin,¹¹⁶ D. K. Jana,⁸² R. Jansky,⁵² J. Janssen,²³ M. Janus,⁵⁷ P. A. Janus,⁴¹a G. Jarlskog,⁸⁴ N. Javadov,⁶⁸,c T. Javůrek,⁵¹

M. Javurkova,⁵¹ F. Jeanneau,¹³⁸ L. Jeanty,¹⁶ J. Jejelava,⁵⁴a,cc A. Jelinskas,¹⁷³ P. Jenni,⁵¹,dd C. Jeske,¹⁷³ S. Jézéquel,⁵ H. Ji,¹⁷⁶ J. Jia,¹⁵⁰ H. Jiang,⁶⁷ Y. Jiang,³⁶a Z. Jiang,¹⁴⁵ S. Jiggins,⁸¹ J. Jimenez Pena,¹⁷⁰ S. Jin,³⁵a A. Jinaru,²⁸b O. Jinnouchi,¹⁵⁹ H. Jivan,¹⁴⁷c P. Johansson,¹⁴¹ K. A. Johns,⁷ C. A. Johnson,⁶⁴ W. J. Johnson,¹⁴⁰ K. Jon-And,¹⁴⁸a,¹⁴⁸b R. W. L. Jones,⁷⁵

S. D. Jones,¹⁵¹ S. Jones,⁷ T. J. Jones,⁷⁷ J. Jongmanns,⁶⁰a P. M. Jorge,¹²⁸a,¹²⁸b J. Jovicevic,¹⁶³a X. Ju,¹⁷⁶ A. Juste Rozas,¹³,w M. K. Köhler,¹⁷⁵ A. Kaczmarska,⁴² M. Kado,¹¹⁹ H. Kagan,¹¹³ M. Kagan,¹⁴⁵ S. J. Kahn,⁸⁸ T. Kaji,¹⁷⁴ E. Kajomovitz,⁴⁸ C. W. Kalderon,⁸⁴ A. Kaluza,⁸⁶ S. Kama,⁴³ A. Kamenshchikov,¹³² N. Kanaya,¹⁵⁷ L. Kanjir,⁷⁸ V. A. Kantserov,¹⁰⁰

J. Kanzaki,⁶⁹ B. Kaplan,¹¹² L. S. Kaplan,¹⁷⁶ D. Kar,¹⁴⁷c K. Karakostas,¹⁰ N. Karastathis,¹⁰ M. J. Kareem,⁵⁷ E. Karentzos,¹⁰ S. N. Karpov,⁶⁸ Z. M. Karpova,⁶⁸ K. Karthik,¹¹² V. Kartvelishvili,⁷⁵ A. N. Karyukhin,¹³² K. Kasahara,¹⁶⁴ L. Kashif,¹⁷⁶ R. D. Kass,¹¹³ A. Kastanas,¹⁴⁹ Y. Kataoka,¹⁵⁷ C. Kato,¹⁵⁷ A. Katre,⁵² J. Katzy,⁴⁵ K. Kawade,⁷⁰ K. Kawagoe,⁷³

T. Kawamoto,¹⁵⁷ G. Kawamura,⁵⁷ E. F. Kay,⁷⁷ V. F. Kazanin,¹¹¹,d R. Keeler,¹⁷² R. Kehoe,⁴³ J. S. Keller,³¹ J. J. Kempster,⁸⁰ J. Kendrick,¹⁹ H. Keoshkerian,¹⁶¹ O. Kepka,¹²⁹ B. P. Kerševan,⁷⁸ S. Kersten,¹⁷⁸ R. A. Keyes,⁹⁰ M. Khader,¹⁶⁹

F. Khalil-zada,¹² A. Khanov,¹¹⁶ A. G. Kharlamov,¹¹¹,d T. Kharlamova,¹¹¹,d A. Khodinov,¹⁶⁰ T. J. Khoo,⁵² V. Khovanskiy,⁹⁹,a

E. Khramov,⁶⁸ J. Khubua,⁵⁴b,ee S. Kido,⁷⁰ C. R. Kilby,⁸⁰ H. Y. Kim,⁸ S. H. Kim,¹⁶⁴ Y. K. Kim,³³ N. Kimura,¹⁵⁶ O. M. Kind,¹⁷

B. T. King,⁷⁷ D. Kirchmeier,⁴⁷ J. Kirk,¹³³ A. E. Kiryunin,¹⁰³ T. Kishimoto,¹⁵⁷ D. Kisielewska,⁴¹a V. Kitali,⁴⁵ K. Kiuchi,¹⁶⁴ O. Kivernyk,⁵ E. Kladiva,¹⁴⁶b T. Klapdor-Kleingrothaus,⁵¹ M. H. Klein,⁹² M. Klein,⁷⁷ U. Klein,⁷⁷ K. Kleinknecht,⁸⁶

P. Klimek,¹¹⁰ A. Klimentov,²⁷ R. Klingenberg,⁴⁶ T. Klingl,²³ T. Klioutchnikova,³² E.-E. Kluge,⁶⁰a P. Kluit,¹⁰⁹ S. Kluth,¹⁰³ E. Kneringer,⁶⁵ E. B. F. G. Knoops,⁸⁸ A. Knue,¹⁰³ A. Kobayashi,¹⁵⁷ D. Kobayashi,¹⁵⁹ T. Kobayashi,¹⁵⁷ M. Kobel,⁴⁷ M. Kocian,¹⁴⁵ P. Kodys,¹³¹ T. Koffas,³¹ E. Koffeman,¹⁰⁹ N. M. Köhler,¹⁰³ T. Koi,¹⁴⁵ M. Kolb,⁶⁰b I. Koletsou,⁵
A. A. Komar,⁹⁸,ª Y. Komori,¹⁵⁷ T. Kondo,⁶⁹ N. Kondrashova,³⁶,⁶c K. Köneke,⁵¹ A. C. König,¹⁰⁸ T. Kono,⁶⁹,ff

R. Konoplich,¹¹²,gg N. Konstantinidis,⁸¹ R. Kopeliansky,⁶⁴ S. Koperny,⁴¹a A. K. Kopp,⁵¹ K. Korcyl,⁴² K. Kordas,¹⁵⁶

A. Korn,⁸¹ A. A. Korol,¹¹¹,d I. Korolkov,¹³ E. V. Korolkova,¹⁴¹ O. Kortner,¹⁰³ S. Kortner,¹⁰³ T. Kosek,¹³¹ V. V. Kostyukhin,²³

A. Kotwal,⁴⁸ A. Koulouris,¹⁰ A. Kourkoumeli-Charalampidi,¹²³a,¹²³b C. Kourkoumelis,⁹ E. Kourlitis,¹⁴¹ V. Kouskoura,²⁷

A. B. Kowalewska,⁴² R. Kowalewski,¹⁷² T. Z. Kowalski,⁴¹a C. Kozakai,¹⁵⁷ W. Kozanecki,¹³⁸ A. S. Kozhin,¹³²

V. A. Kramarenko,¹⁰¹ G. Kramberger,⁷⁸ D. Krasnopevtsev,¹⁰⁰ M. W. Krasny,⁸³ A. Krasznahorkay,³² D. Krauss,¹⁰³

J. A. Kremer,⁴¹a J. Kretzschmar,⁷⁷ K. Kreutzfeldt,⁵⁵ P. Krieger,¹⁶¹ K. Krizka,³³ K. Kroeninger,⁴⁶ H. Kroha,¹⁰³ J. Kroll,¹²⁹

J. Kroll,¹²⁴ J. Kroseberg,²³ J. Krstic,¹⁴ U. Kruchonak,⁶⁸ H. Krüger,²³ N. Krumnack,⁶⁷ M. C. Kruse,⁴⁸ T. Kubota,⁹¹

H. Kucuk,⁸¹ S. Kuday,⁴b J. T. Kuechler,¹⁷⁸ S. Kuehn,³² A. Kugel,⁶⁰a F. Kuger,¹⁷⁷ T. Kuhl,⁴⁵ V. Kukhtin,⁶⁸ R. Kukla,⁸⁸

Y. Kulchitsky,⁹⁵ S. Kuleshov,³⁴b Y. P. Kulinich,¹⁶⁹ M. Kuna,¹³⁴a,¹³⁴b T. Kunigo,⁷¹ A. Kupco,¹²⁹ T. Kupfer,⁴⁶ O. Kuprash,¹⁵⁵

H. Kurashige,⁷⁰ L. L. Kurchaninov,¹⁶³a Y. A. Kurochkin,⁹⁵ M. G. Kurth,³⁵a,³⁵d V. Kus,¹²⁹ E. S. Kuwertz,¹⁷² M. Kuze,¹⁵⁹

J. Kvita,¹¹⁷ T. Kwan,¹⁷² D. Kyriazopoulos,¹⁴¹ A. La Rosa,¹⁰³ J. L. La Rosa Navarro,²⁶d L. La Rotonda,⁴⁰a,⁴⁰b

F. La Ruffa,⁴⁰a,⁴⁰b C. Lacasta,¹⁷⁰ F. Lacava,¹³⁴a,¹³⁴b J. Lacey,⁴⁵ H. Lacker,¹⁷ D. Lacour,⁸³ E. Ladygin,⁶⁸ R. Lafaye,⁵

B. Laforge,⁸³ T. Lagouri,¹⁷⁹ S. Lai,⁵⁷ S. Lammers,⁶⁴ W. Lampl,⁷ E. Lançon,²⁷ U. Landgraf,⁵¹ M. P. J. Landon,⁷⁹

M. C. Lanfermann,⁵² V. S. Lang,⁶⁰a J. C. Lange,¹³ R. J. Langenberg,³² A. J. Lankford,¹⁶⁶ F. Lanni,²⁷ K. Lantzsch,²³

A. Lanza,¹²³a A. Lapertosa,⁵³a,⁵³b S. Laplace,⁸³ J. F. Laporte,¹³⁸ T. Lari,⁹⁴a F. Lasagni Manghi,²²a,²²b M. Lassnig,³²

P. Laurelli,⁵⁰ W. Lavrijsen,¹⁶ A. T. Law,¹³⁹ P. Laycock,⁷⁷ T. Lazovich,⁵⁹ M. Lazzaroni,⁹⁴a,⁹⁴b B. Le,⁹¹ O. Le Dortz,⁸³

E. Le Guirriec,⁸⁸ E. P. Le Quilleuc,¹³⁸ M. LeBlanc,¹⁷² T. LeCompte,⁶ F. Ledroit-Guillon,⁵⁸ C. A. Lee,²⁷ G. R. Lee,¹³³,hh

S. C. Lee,¹⁵³ L. Lee,⁵⁹ B. Lefebvre,⁹⁰ G. Lefebvre,⁸³ M. Lefebvre,¹⁷² F. Legger,¹⁰² C. Leggett,¹⁶ G. Lehmann Miotto,³²

X. Lei,⁷ W. A. Leight,⁴⁵ M. A. L. Leite,²⁶d R. Leitner,¹³¹ D. Lellouch,¹⁷⁵ B. Lemmer,⁵⁷ K. J. C. Leney,⁸¹ T. Lenz,²³

B. Lenzi,³² R. Leone,⁷ S. Leone,¹²⁶a,¹²⁶b C. Leonidopoulos,⁴⁹ G. Lerner,¹⁵¹ C. Leroy,⁹⁷ A. A. J. Lesage,¹³⁸ C. G. Lester,³⁰

M. Levchenko,¹²⁵ J. Levêque,⁵ D. Levin,⁹² L. J. Levinson,¹⁷⁵ M. Levy,¹⁹ D. Lewis,⁷⁹ B. Li,³⁶a,x Changqiao Li,³⁶a H. Li,¹⁵⁰

L. Li,³⁶c Q. Li,³⁵a,³⁵d S. Li,⁴⁸ X. Li,³⁶c Y. Li,¹⁴³ Z. Liang,³⁵a B. Liberti,¹³⁵a A. Liblong,¹⁶¹ K. Lie,⁶²c J. Liebal,²³ W. Liebig,¹⁵

A. Limosani,¹⁵² S. C. Lin,¹⁸² T. H. Lin,⁸⁶ R. A. Linck,⁶⁴ B. E. Lindquist,¹⁵⁰ A. E. Lionti,⁵² E. Lipeles,¹²⁴ A. Lipniacka,¹⁵

M. Lisovyi,⁶⁰b T. M. Liss,¹⁶⁹,ii A. Lister,¹⁷¹ A. M. Litke,¹³⁹ B. Liu,¹⁵³,jj H. Liu,⁹² H. Liu,²⁷ J. K. K. Liu,¹²² J. Liu,³⁶b

J. B. Liu,³⁶a K. Liu,⁸⁸ L. Liu,¹⁶⁹ M. Liu,³⁶a Y. L. Liu,³⁶a Y. Liu,³⁶a M. Livan,¹²³a,¹²³b A. Lleres,⁵⁸ J. Llorente Merino,³⁵a

S. L. Lloyd,⁷⁹ C. Y. Lo,⁶²b F. Lo Sterzo,¹⁵³ E. M. Lobodzinska,⁴⁵ P. Loch,⁷ F. K. Loebinger,⁸⁷ A. Loesle,⁵¹ K. M. Loew,²⁵

A. Loginov,¹⁷⁹,ª T. Lohse,¹⁷ K. Lohwasser,¹⁴¹ M. Lokajicek,¹²⁹ B. A. Long,²⁴ J. D. Long,¹⁶⁹ R. E. Long,⁷⁵ L. Longo,⁷⁶a,⁷⁶b

K. A. Looper,¹¹³ J. A. Lopez,³⁴b D. Lopez Mateos,⁵⁹ I. Lopez Paz,¹³ A. Lopez Solis,⁸³ J. Lorenz,¹⁰² N. Lorenzo Martinez,⁵

M. Losada,²¹ P. J. Lösel,¹⁰² X. Lou,³⁵a A. Lounis,¹¹⁹ J. Love,⁶ P. A. Love,⁷⁵ H. Lu,⁶²a N. Lu,⁹² Y. J. Lu,⁶³ H. J. Lubatti,¹⁴⁰

C. Luci,¹³⁴a,¹³⁴b A. Lucotte,⁵⁸ C. Luedtke,⁵¹ F. Luehring,⁶⁴ W. Lukas,⁶⁵ L. Luminari,¹³⁴a O. Lundberg,¹⁴⁸a,¹⁴⁸b

B. Lund-Jensen,¹⁴⁹ M. S. Lutz,⁸⁹ P. M. Luzi,⁸³ D. Lynn,²⁷ R. Lysak,¹²⁹ E. Lytken,⁸⁴ F. Lyu,³⁵a V. Lyubushkin,⁶⁸ H. Ma,²⁷

L. L. Ma,³⁶b Y. Ma,³⁶b G. Maccarrone,⁵⁰ A. Macchiolo,¹⁰³ C. M. Macdonald,¹⁴¹ B. Maček,⁷⁸ J. Machado Miguens,¹²⁴,¹²⁸b

D. Madaffari,¹⁷⁰ R. Madar,³⁷ W. F. Mader,⁴⁷ A. Madsen,⁴⁵ J. Maeda,⁷⁰ S. Maeland,¹⁵ T. Maeno,²⁷ A. S. Maevskiy,¹⁰¹

V. Magerl,⁵¹ J. Mahlstedt,¹⁰⁹ C. Maiani,¹¹⁹ C. Maidantchik,²⁶a A. A. Maier,¹⁰³ T. Maier,¹⁰² A. Maio,¹²⁸a,¹²⁸b,¹²⁸d

O. Majersky,¹⁴⁶a S. Majewski,¹¹⁸ Y. Makida,⁶⁹ N. Makovec,¹¹⁹ B. Malaescu,⁸³ Pa. Malecki,⁴² V. P. Maleev,¹²⁵ F. Malek,⁵⁸

U. Mallik,⁶⁶ D. Malon,⁶ C. Malone,³⁰ S. Maltezos,¹⁰ S. Malyukov,³² J. Mamuzic,¹⁷⁰ G. Mancini,⁵⁰ I. Mandić,⁷⁸

J. Maneira,¹²⁸a,¹²⁸b L. Manhaes de Andrade Filho,²⁶b J. Manjarres Ramos,⁴⁷ K. H. Mankinen,⁸⁴ A. Mann,¹⁰² A. Manousos,³²

B. Mansoulie,¹³⁸ J. D. Mansour,³⁵a R. Mantifel,⁹⁰ M. Mantoani,⁵⁷ S. Manzoni,⁹⁴a,⁹⁴b L. Mapelli,³² G. Marceca,²⁹ L. March,⁵²

L. Marchese,¹²² G. Marchiori,⁸³ M. Marcisovsky,¹²⁹ M. Marjanovic,³⁷ D. E. Marley,⁹² F. Marroquim,²⁶a S. P. Marsden,⁸⁷

Z. Marshall,¹⁶ M. U. F. Martensson,¹⁶⁸ S. Marti-Garcia,¹⁷⁰ C. B. Martin,¹¹³ T. A. Martin,¹⁷³ V. J. Martin,⁴⁹

B. Martin dit Latour,¹⁵ M. Martinez,¹³,w V. I. Martinez Outschoorn,¹⁶⁹ S. Martin-Haugh,¹³³ V. S. Martoiu,²⁸b

A. C. Martyniuk,⁸¹ A. Marzin,³² L. Masetti,⁶⁶ T. Mashimo,¹⁵⁷ R. Mashinistov,⁹⁸ J. Masik,⁸⁷ A. L. Maslennikov,¹¹¹,d

L. Massa,¹³⁵a,¹³⁵b P. Mastrandrea,⁵ A. Mastroberardino,⁴⁰a,⁴⁰b T. Masubuchi,¹⁵⁷ P. Mättig,¹⁷⁸ J. Maurer,²⁸b S. J. Maxfield,⁷⁷

D. A. Maximov,¹¹¹,d R. Mazini,¹⁵³ I. Maznas,¹⁵⁶ S. M. Mazza,⁹⁴a,⁹⁴b N. C. Mc Fadden,¹⁰⁷ G. Mc Goldrick,¹⁶¹ S. P. Mc Kee,⁹²

A. McCarn,⁹² R. L. McCarthy,¹⁵⁰ T. G. McCarthy,¹⁰³ L. I. McClymont,⁸¹ E. F. McDonald,⁹¹ J. A. Mcfayden,⁸¹

G. Mchedlidze,⁵⁷ S. J. McMahon,¹³³ P. C. McNamara,⁹¹ R. A. McPherson,¹⁷²,p S. Meehan,¹⁴⁰ T. J. Megy,⁵¹ S. Mehlhase,¹⁰²

A. Mehta,⁷⁷ T. Meideck,⁵⁸ K. Meier,⁶⁰a B. Meirose,⁴⁴ D. Melini,¹⁷⁰,kk B. R. Mellado Garcia,¹⁴⁷c J. D. Mellenthin,⁵⁷

M. Melo,¹⁴⁶a F. Meloni,¹⁸ A. Melzer,²³ S. B. Menary,⁸⁷ L. Meng,⁷⁷ X. T. Meng,⁹² A. Mengarelli,²²a,²²b S. Menke,¹⁰³
E. Meoni,⁴⁰a,⁴⁰b S. Mergelmeyer,¹⁷ P. Mermod,⁵² L. Merola,¹⁰⁶a,¹⁰⁶b C. Meroni,⁹⁴a F. S. Merritt,³³ A. Messina,¹³⁴a,¹³⁴b
J. Metcalfe,⁶ A. S. Mete,¹⁶⁶ C. Meyer,¹²⁴ J-P. Meyer,¹³⁸ J. Meyer,¹⁰⁹ H. Meyer Zu Theenhausen,⁶⁰a F. Miano,¹⁵¹
R. P. Middleton,¹³³ S. Miglioranzi,⁵³a,⁵³b L. Mijović,⁴⁹ G. Mikenberg,¹⁷⁵ M. Mikestikova,¹²⁹ M. Mikuž,⁷⁸ M. Milesi,⁹¹
A. Milic,¹⁶¹ D. W. Miller,³³ C. Mills,⁴⁹ A. Milov,¹⁷⁵ D. A. Milstead,¹⁴⁸a,¹⁴⁸b A. A. Minaenko,¹³² Y. Minami,¹⁵⁷
I. A. Minashvili,⁵⁴b A. I. Mincer,¹¹² B. Mindur,⁴¹a M. Mineev,⁶⁸ Y. Minegishi,¹⁷⁵ Y. Ming,¹⁷⁶ L. M. Mir,¹³ K. P. Mistry,¹²⁴
T. Mitani,¹⁷⁴ J. Mitrevski,¹⁰² V. A. Mitsou,¹⁷⁰ A. Miucci,¹⁸ P. S. Miyagawa,¹⁴¹ A. Mizukami,⁶⁹ J. U. Mjörnmark,⁸⁴
T. Mkrtchyan,¹⁸⁰ M. Mlynarikova,¹³¹ T. Moa,¹⁴⁸a,¹⁴⁸b K. Mochizuki,⁹⁷ P. Mogg,⁵¹ S. Mohapatra,³⁸ S. Molander,¹⁴⁸a,¹⁴⁸b
R. Moles-Valls,²³ R. Monden,⁷¹ M. C. Mondragon,⁹³ K. Mönig,⁴⁵ J. Monk,³⁹ E. Monnier,⁸⁸ A. Montalbano,¹⁵⁰
J. Montejo Berlingen,³² F. Monticelli,⁷⁴ S. Monzani,⁹⁴a,⁹⁴b R. W. Moore,³ N. Morange,¹¹⁹ D. Moreno,²¹ M. Moreno Llácer,³²
P. Morettini,⁵³a S. Morgenstern,³² D. Mori,¹⁴⁴ T. Mori,¹⁵⁷ M. Morii,⁵⁹ M. Morinaga,¹⁵⁷ V. Morisbak,¹²¹ A. K. Morley,³²
G. Mornacchi,³² J. D. Morris,⁷⁹ L. Morvaj,¹⁵⁰ P. Moschovakos,¹⁰ M. Mosidze,⁵⁴b H. J. Moss,¹⁴¹ J. Moss,¹⁴⁵,¹¹¹
K. Motohashi,¹⁵⁹ R. Mount,¹⁴⁵ E. Mountricha,²⁷ E. J. W. Moyse,⁸⁹ S. Muanza,⁸⁸ F. Mueller,¹⁰³ J. Mueller,¹²⁷
R. S. P. Mueller,¹⁰² D. Muenstermann,⁷⁵ P. Mullen,⁵⁶ G. A. Mullier,¹⁸ F. J. Munoz Sanchez,⁸⁷ W. J. Murray,¹⁷³,¹³³
H. Musheghyan,³² M. Muškinja,⁷⁸ A. G. Myagkov,¹³²,mm M. Myska,¹³⁰ B. P. Nachman,¹⁶ O. Nackenhorst,⁵² K. Nagai,¹²²
R. Nagai,⁶⁹,ff K. Nagano,⁶⁹ Y. Nagasaka,⁶¹ K. Nagata,¹⁶⁴ M. Nagel,⁵¹ E. Nagy,⁸⁸ A. M. Nairz,³² Y. Nakahama,¹⁰⁵
K. Nakamura,⁶⁹ T. Nakamura,¹⁵⁷ I. Nakano,¹¹⁴ R. F. Naranjo Garcia,⁴⁵ R. Narayan,¹¹ D. I. Narrias Villar,⁶⁰a I. Naryshkin,¹²⁵
T. Naumann,⁴⁵ G. Navarro,²¹ R. Nayyar,⁷ H. A. Neal,⁹² P. Yu. Nechaeva,⁹⁸ T. J. Neep,¹³⁸ A. Negri,¹²³a,¹²³b M. Negrini,²²a
S. Nektarijevic,¹⁰⁸ C. Nellist,¹¹⁹ A. Nelson,¹⁶⁶ M. E. Nelson,¹²² S. Nemecek,¹²⁹ P. Nemethy,¹¹² M. Nessi,³²,nn
M. S. Neubauer,¹⁶⁹ M. Neumann,¹⁷⁸ P. R. Newman,¹⁹ T. Y. Ng,⁶²c T. Nguyen Manh,⁹⁷ R. B. Nickerson,¹²² R. Nicolaidou,¹³⁸
J. Nielsen,¹³⁹ V. Nikolaenko,¹³²,mm I. Nikolic-Audit,⁸³ K. Nikolopoulos,¹⁹ J. K. Nilsen,¹²¹ P. Nilsson,²⁷ Y. Ninomiya,¹⁵⁷
A. Nisati,¹³⁴a N. Nishu,³⁵c R. Nisius,¹⁰³ I. Nitsche,⁴⁶ T. Nitta,¹⁷⁴ T. Nobe,¹⁵⁷ Y. Noguchi,⁷¹ M. Nomachi,¹²⁰ I. Nomidis,³¹
M. A. Nomura,²⁷ T. Nooney,⁷⁹ M. Nordberg,³² N. Norjoharuddeen,¹²² O. Novgorodova,⁴⁷ M. Nozaki,⁶⁹ L. Nozka,¹¹⁷
K. Ntekas,¹⁶⁶ E. Nurse,⁸¹ F. Nuti,⁹¹ K. O'connor,²⁵ D. C. O'Neil,¹⁴⁴ A. A. O'Rourke,⁴⁵ V. O'Shea,⁵⁶ F. G. Oakham,³¹,ε
H. Oberlack,¹⁰³ T. Obermann,²³ J. Ocariz,⁸³ A. Ochi,⁷⁰ I. Ochoa,³⁸ J. P. Ochoa-Ricoux,³⁴a S. Oda,⁷³ S. Odaka,⁶⁹ A. Oh,⁸⁷
S. H. Oh,⁴⁸ C. C. Ohm,¹⁶ H. Ohman,¹⁶⁸ H. Oide,⁵³a,⁵³b H. Okawa,¹⁶⁴ Y. Okumura,¹⁵⁷ T. Okuyama,⁶⁹ A. Olariu,²⁸b
L. F. Oleiro Seabra,¹²⁸a S. A. Olivares Pino,⁴⁹ D. Oliveira Damazio,²⁷ A. Olszewski,⁴² J. Olszowska,⁴² A. Onofre,¹²⁸a,¹²⁸b
K. Onogi,¹⁰⁵ P. U. E. Onyisi,¹¹,bb H. Oppen,¹²¹ M. J. Oreglia,³³ Y. Oren,¹⁵⁵ D. Orestano,¹³⁶a,¹³⁶b N. Orlando,⁶²b R. S. Orr,¹⁶¹
B. Osculati,⁵³a,⁵³b,a R. Ospanov,³⁶a G. Otero y Garzon,²⁹ H. Otono,⁷³ M. Ouchrif,¹³⁷d F. Ould-Saada,¹²¹ A. Ouraou,¹³⁸
K. P. Ouussoren,¹⁰⁹ Q. Ouyang,³⁵a M. Owen,⁵⁶ R. E. Owen,¹⁹ V. E. Ozcan,²⁰a N. Ozturk,⁸ K. Pachal,¹⁴⁴ A. Pacheco Pages,¹³
L. Pacheco Rodriguez,¹³⁸ C. Padilla Aranda,¹³ S. Pagan Griso,¹⁶ M. Paganini,¹⁷⁹ F. Paige,²⁷ G. Palacino,⁶⁴ S. Palazzo,⁴⁰a,⁴⁰b
S. Palestini,³² M. Palka,⁴¹b D. Pallin,³⁷ E. St. Panagiotopoulou,¹⁰ I. Panagoulias,¹⁰ C. E. Pandini,¹²⁶a,¹²⁶b
J. G. Panduro Vazquez,⁸⁰ P. Pani,³² S. Panitkin,²⁷ D. Pantea,²⁸b L. Paolozzi,⁵² Th. D. Papadopoulou,¹⁰ K. Papageorgiou,⁹,¹
A. Paramonov,⁶ D. Paredes Hernandez,¹⁷⁹ A. J. Parker,⁷⁵ M. A. Parker,³⁰ K. A. Parker,⁴⁵ F. Parodi,⁵³a,⁵³b J. A. Parsons,³⁸
U. Parzefall,⁵¹ V. R. Pascuzzi,¹⁶¹ J. M. Pasner,¹³⁹ E. Pasqualucci,¹³⁴a S. Passaggio,⁵³a Fr. Pastore,⁸⁰ S. Pataraia,⁸⁶ J. R. Pater,⁸⁷
T. Pauly,³² B. Pearson,¹⁰³ S. Pedraza Lopez,¹⁷⁰ R. Pedro,¹²⁸a,¹²⁸b S. V. Peleganchuk,¹¹¹,d O. Penc,¹²⁹ C. Peng,³⁵a,³⁵d
H. Peng,³⁶a J. Penwell,⁶⁴ B. S. Peralva,²⁶b M. M. Perego,¹³⁸ D. V. Perepelitsa,²⁷ F. Peri,¹⁷ L. Perini,⁹⁴a,⁹⁴b H. Pernegger,³²
S. Perrella,¹⁰⁶a,¹⁰⁶b R. Peschke,⁴⁵ V. D. Peshekhonov,⁶⁸a K. Peters,⁴⁵ R. F. Y. Peters,⁸⁷ B. A. Petersen,³² T. C. Petersen,³⁹
E. Petit,⁵⁸ A. Petridis,¹ C. Petridou,¹⁵⁶ P. Petroff,¹¹⁹ E. Petrolo,¹³⁴a M. Petrov,¹²² F. Petrucci,¹³⁶a,¹³⁶b N. E. Pettersson,⁸⁹
A. Peyaud,¹³⁸ R. Pezoa,³⁴b F. H. Phillips,⁹³ P. W. Phillips,¹³³ G. Piacquadio,¹⁵⁰ E. Pianori,¹⁷³ A. Picazio,⁸⁹ E. Piccaro,⁷⁹
M. A. Pickering,¹²² R. Piegaia,²⁹ J. E. Pilcher,³³ A. D. Pilkington,⁸⁷ A. W. J. Pin,⁸⁷ M. Pinamonti,¹³⁵a,¹³⁵b J. L. Pinfold,³
H. Pirumov,⁴⁵ M. Pitt,¹⁷⁵ L. Plazak,¹⁴⁶a M.-A. Pleier,²⁷ V. Pleskot,⁶⁸ E. Plotnikova,⁶⁸ D. Pluth,⁶⁷ P. Podberezko,¹¹¹
R. Poettgen,¹⁴⁸a,¹⁴⁸b R. Poggi,¹²³a,¹²³b L. Poggioli,¹¹⁹ D. Pohl,²³ G. Polesello,¹²³a A. Poley,⁴⁵ A. Policicchio,⁴⁰a,⁴⁰b
R. Polifka,³² A. Polini,²²a C. S. Pollard,⁵⁶ V. Polychronakos,²⁷ K. Pommès,³² D. Ponomarenko,¹⁰⁰ L. Pontecorvo,¹³⁴a
G. A. Popeneciu,²⁸d A. Poppleton,³² S. Pospisil,¹³⁰ K. Potamianos,¹⁶ I. N. Potrap,⁶⁸ C. J. Potter,³⁰ G. Poulard,³² T. Poulsen,⁸⁴
J. Poveda,³² M. E. Pozo Astigarraga,³² P. Pralavorio,⁸⁸ A. Pranko,¹⁶ S. Prell,⁶⁷ D. Price,⁸⁷ M. Primavera,⁷⁶a S. Prince,⁹⁰
N. Proklova,¹⁰⁰ K. Prokofiev,⁶²c F. Prokoshin,³⁴b S. Protopopescu,²⁷ J. Proudfoot,⁶ M. Przybycien,⁴¹a A. Puri,¹⁶⁹ P. Puzo,¹¹⁹
J. Qian,⁹² G. Qin,⁵⁶ Y. Qin,⁸⁷ A. Quadt,⁵⁷ M. Queitsch-Maitland,⁴⁵ D. Quilty,⁵⁶ S. Raddum,¹²¹ V. Radeka,²⁷ V. Radescu,¹²²
S. K. Radhakrishnan,¹⁵⁰ P. Radloff,¹¹⁸ P. Rados,⁹¹ F. Ragusa,⁹⁴a,⁹⁴b G. Rahal,¹⁸¹ J. A. Raine,⁸⁷ S. Rajagopalan,²⁷
C. Rangel-Smith,¹⁶⁸ T. Rashid,¹¹⁹ S. Raspopov,⁵ M. G. Ratti,⁹⁴a,⁹⁴b D. M. Rauch,⁴⁵ F. Rauscher,¹⁰² S. Rave,⁸⁶
I. Ravinovich,¹⁷⁵ J. H. Rawling,⁸⁷ M. Raymond,³² A. L. Read,¹²¹ N. P. Readioff,⁵⁸ M. Reale,⁷⁶,⁷⁶b D. M. Rebuzzi,¹²³a,¹²³b

A. Redelbach,¹⁷⁷ G. Redlinger,²⁷ R. Reece,¹³⁹ R. G. Reed,¹⁴⁷c K. Reeves,⁴⁴ L. Rehnisch,¹⁷ J. Reichert,¹²⁴ A. Reiss,⁸⁶

C. Rembser,³² H. Ren,³⁵a,³⁵d M. Rescigno,¹³⁴a S. Resconi,⁹⁴a E. D. Resseguie,¹²⁴ S. Rettie,¹⁷¹ E. Reynolds,¹⁹

O. L. Rezanova,¹¹¹, d P. Reznicek,¹³¹ R. Rezvani,⁹⁷ R. Richter,¹⁰³ S. Richter,⁸¹ E. Richter-Was,⁴¹b O. Ricken,²³ M. Ridel,⁸³

P. Rieck,¹⁰³ C. J. Riegel,¹⁷⁸ J. Rieger,⁵⁷ O. Rifki,¹¹⁵ M. Rijssenbeek,¹⁵⁰ A. Rimoldi,¹²³a,¹²³b M. Rimoldi,¹⁸ L. Rinaldi,²²a

G. Ripellino,¹⁴⁹ B. Ristić,³² E. Ritsch,³² I. Riu,¹³ F. Rizatdinova,¹¹⁶ E. Rizvi,⁷⁹ C. Rizzi,¹³ R. T. Roberts,⁸⁷

S. H. Robertson,⁹⁰, p A. Robichaud-Veronneau,⁹⁰ D. Robinson,³⁰ J. E. M. Robinson,⁴⁵ A. Robson,⁵⁶ E. Rocco,⁸⁶

C. Roda,¹²⁶a,¹²⁶b Y. Rodina,⁸⁸,⁰⁰ S. Rodriguez Bosca,¹⁷⁰ A. Rodriguez Perez,¹³ D. Rodriguez Rodriguez,¹⁷⁰ S. Roe,³²

C. S. Rogan,⁵⁹ O. Røhne,¹²¹ J. Roloff,⁵⁹ A. Romaniouk,¹⁰⁰ M. Romano,²²a,²²b S. M. Romano Saez,³⁷ E. Romero Adam,¹⁷⁰

N. Rompotis,⁷⁷ M. Ronzani,⁵¹ L. Roos,⁸³ S. Rosati,¹³⁴a K. Rosbach,⁵¹ P. Rose,¹³⁹ N.-A. Rosien,⁵⁷ E. Rossi,¹⁰⁶a,¹⁰⁶b

L. P. Rossi,⁵³a J. H. N. Rosten,³⁰ R. Rosten,¹⁴⁰ M. Rotaru,²⁸b J. Rothberg,¹⁴⁰ D. Rousseau,¹¹⁹ A. Rozanov,⁸⁸ Y. Rozen,¹⁵⁴

X. Ruan,¹⁴⁷c F. Rubbo,¹⁴⁵ F. Rühr,⁵¹ A. Ruiz-Martinez,³¹ Z. Rurikova,⁵¹ N. A. Rusakovich,⁶⁸ H. L. Russell,⁹⁰

J. P. Rutherford,⁷ N. Ruthmann,³² Y. F. Ryabov,¹²⁵ M. Rybar,¹⁶⁹ G. Rybkin,¹¹⁹ S. Ryu,⁶ A. Ryzhov,¹³² G. F. Rzehorz,⁵⁷

A. F. Saavedra,¹⁵² G. Sabato,¹⁰⁹ S. Sacerdoti,²⁹ H. F.-W. Sadrozinski,¹³⁹ R. Sadykov,⁶⁸ F. Safai Tehrani,¹³⁴a P. Saha,¹¹⁰

M. Sahinsoy,⁶⁰a M. Saimpert,⁴⁵ M. Saito,¹⁵⁷ T. Saito,¹⁵⁷ H. Sakamoto,¹⁵⁷ Y. Sakurai,¹⁷⁴ G. Salamanna,¹³⁶a,¹³⁶b

J. E. Salazar Loyola,³⁴b D. Salek,¹⁰⁹ P. H. Sales De Bruin,¹⁶⁸ D. Salihagic,¹⁰³ A. Salnikov,¹⁴⁵ J. Salt,¹⁷⁰ D. Salvatore,⁴⁰a,⁴⁰b

F. Salvatore,¹⁵¹ A. Salvucci,⁶²a,⁶²b,⁶²c A. Salzburger,³² D. Sammel,⁵¹ D. Sampsonidis,¹⁵⁶ D. Sampsonidou,¹⁵⁶ J. Sánchez,¹⁷⁰

V. Sanchez Martinez,¹⁷⁰ A. Sanchez Pineda,¹⁶⁷a,¹⁶⁷c H. Sandaker,¹²¹ R. L. Sandbach,⁷⁹ C. O. Sander,⁴⁵ M. Sandhoff,¹⁷⁸

C. Sandoval,²¹ D. P. C. Sankey,¹³³ M. Sannino,⁵³a,⁵³b Y. Sano,¹⁰⁵ A. Sansoni,⁵⁰ C. Santoni,³⁷ H. Santos,¹²⁸a

I. Santoyo Castillo,¹⁵¹ A. Sapronov,⁶⁸ J. G. Saraiva,¹²⁸a,¹²⁸d B. Sarrazin,²³ O. Sasaki,⁶⁹ K. Sato,¹⁶⁴ E. Sauvan,⁵ G. Savage,⁸⁰

P. Savard,¹⁶¹, e N. Savic,¹⁰³ C. Sawyer,¹³³ L. Sawyer,⁸², v J. Saxon,³³ C. Sbarra,²²a A. Sbrizzi,²²a,²²b T. Scanlon,⁸¹

D. A. Scannicchio,¹⁶⁶ M. Scarcella,¹⁵² J. Schaarschmidt,¹⁴⁰ P. Schacht,¹⁰³ B. M. Schachtner,¹⁰² D. Schaefer,³² L. Schaefer,¹²⁴

R. Schaefer,⁴⁵ J. Schaeffer,⁸⁶ S. Schaepe,²³ S. Schaetzel,⁶⁰b U. Schäfer,⁸⁶ A. C. Schaffer,¹¹⁹ D. Schaile,¹⁰²

R. D. Schamberger,¹⁵⁰ V. A. Schegelsky,¹²⁵ D. Scheirich,¹³¹ M. Schernau,¹⁶⁶ C. Schiavi,⁵³a,⁵³b S. Schier,¹³⁹

L. K. Schildgen,²³ C. Schillo,⁵¹ M. Schioppa,⁴⁰a,⁴⁰b S. Schlenker,³² K. R. Schmidt-Sommerfeld,¹⁰³ K. Schmieden,³²

C. Schmitt,⁸⁶ S. Schmitt,⁴⁵ S. Schmitz,⁸⁶ U. Schnoor,⁵¹ L. Schoeffel,¹³⁸ A. Schoening,⁶⁰b B. D. Schoenrock,⁹³ E. Schopf,²³

M. Schott,⁸⁶ J. F. P. Schouwenberg,¹⁰⁸ J. Schovancova,³² S. Schramm,⁵² N. Schuh,⁸⁶ A. Schulte,⁸⁶ M. J. Schultens,²³

H.-C. Schultz-Coulon,⁶⁰a H. Schulz,¹⁷ M. Schumacher,⁵¹ B. A. Schumm,¹³⁹ Ph. Schune,¹³⁸ A. Schwartzman,¹⁴⁵

T. A. Schwarz,⁹² H. Schweiger,⁸⁷ Ph. Schwemling,¹³⁸ R. Schwienhorst,⁹³ J. Schwindling,¹³⁸ A. Sciandra,²³ G. Sciolla,²⁵

M. Scornajenghi,⁴⁰a,⁴⁰b F. Scuri,¹²⁶a,¹²⁶b F. Scutti,⁹¹ J. Searcy,⁹² P. Seema,²³ S. C. Seidel,¹⁰⁷ A. Seiden,¹³⁹ J. M. Seixas,²⁶a

G. Sekhniaidze,¹⁰⁶a K. Sekhon,⁹² S. J. Sekula,⁴³ N. Semprini-Cesari,²²a,²²b S. Senkin,³⁷ C. Serfon,¹²¹ L. Serin,¹¹⁹

L. Serkin,¹⁶⁷a,¹⁶⁷b M. Sessa,¹³⁶a,¹³⁶b R. Seuster,¹⁷² H. Severini,¹¹⁵ T. Sfiligoj,⁷⁸ F. Sforza,³² A. Sfyrla,⁵² E. Shabalina,⁵⁷

N. W. Shaikh,¹⁴⁸a,¹⁴⁸b L. Y. Shan,³⁵a R. Shang,¹⁶⁹ J. T. Shank,²⁴ M. Shapiro,¹⁶ P. B. Shatalov,⁹⁹ K. Shaw,¹⁶⁷a,¹⁶⁷b

S. M. Shaw,⁸⁷ A. Shcherbakova,¹⁴⁸a,¹⁴⁸b C. Y. Shehu,¹⁵¹ Y. Shen,¹¹⁵ N. Sherafati,³¹ P. Sherwood,⁸¹ L. Shi,¹⁵³, pp S. Shimizu,⁷⁰

C. O. Shimmin,¹⁷⁹ M. Shimojima,¹⁰⁴ I. P. J. Shipsey,¹²² S. Shirabe,⁷³ M. Shiyakova,⁶⁸, qq J. Shlomi,¹⁷⁵ A. Shmeleva,⁹⁸

D. Shoaleh Saadi,⁹⁷ M. J. Shochet,³³ S. Shojaii,⁹⁴a D. R. Shope,¹¹⁵ S. Shrestha,¹¹³ E. Shulga,¹⁰⁰ M. A. Shupe,⁷ P. Sicho,¹²⁹

A. M. Sickles,¹⁶⁹ P. E. Sidebo,¹⁴⁹ E. Sideras Haddad,¹⁴⁷c O. Sidiropoulou,¹⁷⁷ A. Sidoti,²²a,²²b F. Siegert,⁴⁷ Dj. Sijacki,¹⁴

J. Silva,¹²⁸a,¹²⁸d S. B. Silverstein,¹⁴⁸a V. Simak,¹³⁰ L. Simic,¹⁴ S. Simion,¹¹⁹ E. Simioni,⁸⁶ B. Simmons,⁸¹ M. Simon,⁸⁶

P. Sinervo,¹⁶¹ N. B. Sinev,¹¹⁸ M. Sioli,²²a,²²b G. Siragusa,¹⁷⁷ I. Siral,⁹² S. Yu. Sivoklokov,¹⁰¹ J. Sjölin,¹⁴⁸a,¹⁴⁸b M. B. Skinner,⁷⁵

P. Skubic,¹¹⁵ M. Slater,¹⁹ T. Slavicek,¹³⁰ M. Slawinska,⁴² K. Sliwa,¹⁶⁵ R. Slovak,¹³¹ V. Smakhtin,¹⁷⁵ B. H. Smart,⁵

J. Smiesko,¹⁴⁶a N. Smirnov,¹⁰⁰ S. Yu. Smirnov,¹⁰⁰ Y. Smirnov,¹⁰⁰ L. N. Smirnova,¹⁰¹, rr O. Smirnova,⁸⁴ J. W. Smith,⁵⁷

M. N. K. Smith,³⁸ R. W. Smith,³⁸ M. Smizanska,⁷⁵ K. Smolek,¹³⁰ A. A. Snesarev,⁹⁸ I. M. Snyder,¹¹⁸ S. Snyder,²⁷

R. Sobie,¹⁷², p F. Socher,⁴⁷ A. Soffer,¹⁵⁵ A. Søgaard,⁴⁹ D. A. Soh,¹⁵³ G. Sokhrannyi,⁷⁸ C. A. Solans Sanchez,³² M. Solar,¹³⁰

E. Yu. Soldatov,¹⁰⁰ U. Soldevila,¹⁷⁰ A. A. Solodkov,¹³² A. Soloshenko,⁶⁸ O. V. Solovyanov,¹³² V. Solovyev,¹²⁵ P. Sommer,⁵¹

H. Son,¹⁶⁵ A. Sopczak,¹³⁰ D. Sosa,⁶⁰b C. L. Sotiropoulou,¹²⁶a,¹²⁶b R. Soualah,¹⁶⁷a,¹⁶⁷c A. M. Soukharev,¹¹¹, d D. South,⁴⁵

B. C. Sowden,⁸⁰ S. Spagnolo,⁷⁶a,⁷⁶b M. Spalla,¹²⁶a,¹²⁶b M. Spangenberg,¹⁷³ F. Spanò,⁸⁰ D. Sperlich,¹⁷ F. Spettel,¹⁰³

T. M. Spieker,⁶⁰a R. Spighi,²²a G. Spigo,³² L. A. Spiller,⁹¹ M. Spousta,¹³¹ R. D. St. Denis,⁵⁶, a A. Stabile,⁹⁴a R. Stamen,⁶⁰a

S. Stamm,¹⁷ E. Stanecka,⁴² R. W. Stanek,⁶ C. Stanescu,¹³⁶a M. M. Stanitzki,⁴⁵ B. S. Stapf,¹⁰⁹ S. Stapnes,¹²¹

E. A. Starchenko,¹³² G. H. Stark,³³ J. Stark,⁵⁸ S. H. Stark,³⁹ P. Staroba,¹²⁹ P. Starovoitov,⁶⁰a S. Stärz,³² R. Staszewski,⁴²
P. Steinberg,²⁷ B. Stelzer,¹⁴⁴ H. J. Stelzer,³² O. Stelzer-Chilton,¹⁶³a H. Stenzel,⁵⁵ G. A. Stewart,⁵⁶ M. C. Stockton,¹¹⁸
M. Stoebe,⁹⁰ G. Stoicea,²⁸b P. Stolte,⁵⁷ S. Stonjek,¹⁰³ A. R. Stradling,⁸ A. Straessner,⁴⁷ M. E. Stramaglia,¹⁸ J. Strandberg,¹⁴⁹
S. Strandberg,¹⁴⁸a,¹⁴⁸b M. Strauss,¹¹⁵ P. Strizenec,¹⁴⁶b R. Ströhmer,¹⁷⁷ D. M. Strom,¹¹⁸ R. Stroynowski,⁴³ A. Strubig,⁴⁹
S. A. Stucci,²⁷ B. Stugu,¹⁵ N. A. Styles,⁴⁵ D. Su,¹⁴⁵ J. Su,¹²⁷ S. Suchek,⁶⁰a Y. Sugaya,¹²⁰ M. Suk,¹³⁰ V. V. Sulin,⁹⁸
DMS Sultan,¹⁶²a,¹⁶²b S. Sultansoy,⁴c T. Sumida,⁷¹ S. Sun,⁵⁹ X. Sun,³ K. Suruliz,¹⁵¹ C. J. E. Suster,¹⁵² M. R. Sutton,¹⁵¹
S. Suzuki,⁶⁹ M. Svatos,¹²⁹ M. Swiatlowski,³³ S. P. Swift,² I. Sykora,¹⁴⁶a T. Sykora,¹³¹ D. Ta,⁵¹ K. Tackmann,⁴⁵ J. Taenzer,¹⁵⁵
A. Taffard,¹⁶⁶ R. Tafirout,¹⁶³a N. Taiblum,¹⁵⁵ H. Takai,²⁷ R. Takashima,⁷² E. H. Takasugi,¹⁰³ T. Takeshita,¹⁴² Y. Takubo,⁶⁹
M. Talby,⁸⁸ A. A. Talyshev,¹¹¹,¹d J. Tanaka,¹⁵⁷ M. Tanaka,¹⁵⁹ R. Tanaka,¹¹⁹ S. Tanaka,⁶⁹ R. Tanioka,⁷⁰ B. B. Tannenwald,¹¹³
S. Tapia Araya,³⁴b S. Tapprogge,⁸⁶ S. Tarem,¹⁵⁴ G. F. Tartarelli,⁹⁴a P. Tas,¹³¹ M. Tasevsky,¹²⁹ T. Tashiro,⁷¹ E. Tassi,⁴⁰a,⁴⁰b
A. Tavares Delgado,¹²⁸a,¹²⁸b Y. Tayalati,¹³⁷e A. C. Taylor,¹⁰⁷ G. N. Taylor,⁹¹ P. T. E. Taylor,⁹¹ W. Taylor,¹⁶³b
P. Teixeira-Dias,⁸⁰ D. Temple,¹⁴⁴ H. Ten Kate,³² P. K. Teng,¹⁵³ J. J. Teoh,¹²⁰ F. Tepel,¹⁷⁸ S. Terada,⁶⁹ K. Terashi,¹⁵⁷
J. Terron,⁸⁵ S. Terzo,¹³ M. Testa,⁵⁰ R. J. Teuscher,¹⁶¹,p T. Theveneaux-Pelzer,⁸⁸ F. Thiele,³⁹ J. P. Thomas,¹⁹
J. Thomas-Wilsker,⁸⁰ P. D. Thompson,¹⁹ A. S. Thompson,⁵⁶ L. A. Thomsen,¹⁷⁹ E. Thomson,¹²⁴ M. J. Tibbetts,¹⁶
R. E. Ticse Torres,⁸⁸ V. O. Tikhomirov,⁹⁸,ss Yu. A. Tikhonov,¹¹¹,¹d S. Timoshenko,¹⁰⁰ P. Tipton,¹⁷⁹ S. Tisserant,⁸⁸
K. Todome,¹⁵⁹ S. Todorova-Nova,⁵ S. Todt,⁴⁷ J. Tojo,⁷³ S. Tokár,¹⁴⁶a K. Tokushuku,⁶⁹ E. Tolley,¹¹³ L. Tomlinson,⁸⁷
M. Tomoto,¹⁰⁵ L. Tompkins,¹⁴⁵,tt K. Toms,¹⁰⁷ B. Tong,⁵⁹ P. Tornambe,⁵¹ E. Torrence,¹¹⁸ H. Torres,¹⁴⁴ E. Torró Pastor,¹⁴⁰
J. Toth,⁸⁸,uu F. Touchard,⁸⁸ D. R. Tovey,¹⁴¹ C. J. Treado,¹¹² T. Trefzger,¹⁷⁷ F. Tresoldi,¹⁵¹ A. Tricoli,²⁷ I. M. Trigger,¹⁶³a
S. Trincaz-Duvoid,⁸³ M. F. Tripiana,¹³ W. Trischuk,¹⁶¹ B. Trocmé,⁵⁸ A. Trofymov,⁴⁵ C. Troncon,⁹⁴a
M. Trottier-McDonald,¹⁶ M. Trovatelli,¹⁷² L. Truong,¹⁴⁷b M. Trzebinski,⁴² A. Trzupek,⁴² K. W. Tsang,⁶²a J. C.-L. Tseng,¹²²
P. V. Tsiareshka,⁹⁵ G. Tsipolitis,¹⁰ N. Tsirintanis,⁹ S. Tsiskaridze,¹³ V. Tsiskaridze,⁵¹ E. G. Tskhadadze,⁵⁴a K. M. Tsui,⁶²a
I. I. Tsukerman,⁹⁹ V. Tsulaia,¹⁶ S. Tsuno,⁶⁹ D. Tsybychev,¹⁵⁰ Y. Tu,⁶²b A. Tudorache,²⁸b V. Tudorache,²⁸b T. T. Tulbure,²⁸a
A. N. Tuna,⁵⁹ S. A. Tupputi,²²a,²²b S. Turchikhin,⁶⁸ D. Turgeman,¹⁷⁵ I. Turk Cakir,⁴b,vv R. Turra,⁹⁴a P. M. Tuts,³⁸
G. Ucchielli,²²a,²²b I. Ueda,⁶⁹ M. Ughetto,¹⁴⁸a,¹⁴⁸b F. Ukegawa,¹⁶⁴ G. Unal,³² A. Undrus,²⁷ G. Unel,¹⁶⁶ F. C. Ungaro,⁹¹
Y. Unno,⁶⁹ C. Unverdorben,¹⁰² J. Urban,¹⁴⁶b P. Urquijo,⁹¹ P. Urrejola,⁸⁶ G. Usai,⁸ J. Usui,⁶⁹ L. Vacavant,⁸⁸ V. Vacek,¹³⁰
B. Vachon,⁹⁰ K. O. H. Vadla,¹²¹ A. Vaidya,⁸¹ C. Valderanis,¹⁰² E. Valdes Santurio,¹⁴⁸a,¹⁴⁸b S. Valentinetti,²²a,²²b A. Valero,¹⁷⁰
L. Valéry,¹³ S. Valkar,¹³¹ A. Vallier,⁵ J. A. Valls Ferrer,¹⁷⁰ W. Van Den Wollenberg,¹⁰⁹ H. van der Graaf,¹⁰⁹
P. van Gemmeren,⁶ J. Van Nieuwkoop,¹⁴⁴ I. van Vulpen,¹⁰⁹ M. C. van Woerden,¹⁰⁹ M. Vanadia,¹³⁵a,¹³⁵b W. Vandelli,³²
A. Vaniachine,¹⁶⁰ P. Vankov,¹⁰⁹ G. Vardanyan,¹⁸⁰ R. Vari,¹³⁴a E. W. Varnes,⁷ C. Varni,⁵³a,⁵³b T. Varol,⁴³ D. Varouchas,¹¹⁹
A. Vartapetian,⁸ K. E. Varvell,¹⁵² J. G. Vasquez,¹⁷⁹ G. A. Vasquez,³⁴b F. Vazeille,³⁷ T. Vazquez Schroeder,⁹⁰ J. Veatch,⁵⁷
V. Veeraraghavan,⁷ L. M. Veloce,¹⁶¹ F. Veloso,¹²⁸a,¹²⁸c S. Veneziano,¹³⁴a A. Ventura,⁷⁶a,⁷⁶b M. Venturi,¹⁷² N. Venturi,³²
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M. C. Vetterli,¹⁴⁴,e N. Viaux Maira,³⁴b O. Viazlo,⁸⁴ I. Vichou,¹⁶⁹,a T. Vickey,¹⁴¹ O. E. Vickey Boeriu,¹⁴¹
G. H. A. Viehhauser,¹²² S. Viel,¹⁶ L. Vigani,¹²² M. Villa,²²a,²²b M. Villaplaná Perez,⁹⁴a,⁹⁴b E. Vilucchi,⁵⁰ M. G. Vinčer,³¹
V. B. Vinogradov,⁶⁸ A. Vishwakarma,⁴⁵ C. Vittori,²²a,²²b I. Vivarelli,¹⁵¹ S. Vlachos,¹⁰ M. Vogel,¹⁷⁸ P. Vokac,¹³⁰
G. Volpi,¹²⁶a,¹²⁶b H. von der Schmitt,¹⁰³ E. von Toerne,²³ V. Vorobel,¹³¹ K. Vorobev,¹⁰⁰ M. Vos,¹⁷⁰ R. Voss,³²
J. H. Vossebeld,⁷⁷ N. Vranjes,¹⁴ M. Vranjes Milosavljević,¹⁴ V. Vrba,¹³⁰ M. Vreeswijk,¹⁰⁹ R. Vuillermet,³² I. Vukotic,³³
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M. F. Watson,¹⁹ G. Watts,¹⁴⁰ S. Watts,⁸⁷ B. M. Waugh,⁸¹ A. F. Webb,¹¹ S. Webb,⁸⁶ M. S. Weber,¹⁸ S. W. Weber,¹⁷⁷
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P. S. Wells,³² T. Wenaus,²⁷ T. Wengler,³² S. Wenig,³² N. Wermes,²³ M. D. Werner,⁶⁷ P. Werner,³² M. Wessels,⁶⁰a
K. Whalen,¹¹⁸ N. L. Whallon,¹⁴⁰ A. M. Wharton,⁷⁵ A. S. White,⁹² A. White,⁸ M. J. White,¹ R. White,³⁴b D. Whiteson,¹⁶⁶
B. W. Whitmore,⁷⁵ F. J. Wickens,¹³³ W. Wiedenmann,¹⁷⁶ M. Wielers,¹³³ C. Wiglesworth,³⁹ L. A. M. Wiik-Fuchs,⁵¹
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I. Wingerter-Seez,⁵ E. Winkels,¹⁵¹ F. Winklmeier,¹¹⁸ O. J. Winston,¹⁵¹ B. T. Winter,²³ M. Wittgen,¹⁴⁵ M. Wobisch,⁸²,v
T. M. H. Wolf,¹⁰⁹ R. Wolff,⁸⁸ M. W. Wolter,⁴² H. Wolters,¹²⁸a,¹²⁸c V. W. S. Wong,¹⁷¹ S. D. Worm,¹⁹ B. K. Wosiek,⁴²
J. Wotschack,³² K. W. Wozniak,⁴² M. Wu,³³ S. L. Wu,¹⁷⁶ X. Wu,⁵² Y. Wu,⁹² T. R. Wyatt,⁸⁷ B. M. Wynne,⁴⁹ S. Xella,³⁹
Z. Xi,⁹² L. Xia,³⁵c D. Xu,³⁵a L. Xu,<fnref n="27" /> T. Xu,¹³⁸ B. Yabsley,¹⁵² S. Yacoob,¹⁴⁷a D. Yamaguchi,¹⁵⁹ Y. Yamaguchi,¹²⁰

A. Yamamoto,⁶⁹ S. Yamamoto,¹⁵⁷ T. Yamanaka,¹⁵⁷ M. Yamatani,¹⁵⁷ K. Yamauchi,¹⁰⁵ Y. Yamazaki,⁷⁰ Z. Yan,<fnref n="24" /> H. Yang,³⁶c

H. Yang,<fnref n="16" /> Y. Yang,¹⁵³ Z. Yang,<fnref n="15" /> W-M. Yao,<fnref n="16" /> Y. C. Yap,⁸³ Y. Yasu,⁶⁹ E. Yatsenko,<fnref n="5" /> K. H. Yau Wong,<fnref n="23" /> J. Ye,⁴³ S. Ye,<fnref n="27" />

I. Yeletskikh,⁶⁸ E. Yigitbasi,<fnref n="24" /> E. Yildirim,⁸⁶ K. Yorita,¹⁷⁴ K. Yoshihara,¹²⁴ C. Young,¹⁴⁵ C. J. S. Young,³² J. Yu,<fnref n="8" /> J. Yu,⁶⁷

S. P. Y. Yuen,<fnref n="23" /> I. Yusuff,³⁰,zz B. Zabinski,⁴² G. Zacharis,<fnref n="10" /> R. Zaidan,<fnref n="13" /> A. M. Zaitsev,¹³²,mm N. Zakharchuk,⁴⁵

J. Zalieckas,<fnref n="15" /> A. Zaman,¹⁵⁰ S. Zambito,⁵⁹ D. Zanzi,⁹¹ C. Zeitnitz,¹⁷⁸ G. Zemaityte,¹²² A. Zemla,⁴¹a J. C. Zeng,¹⁶⁹

Q. Zeng,¹⁴⁵ O. Zenin,¹³² T. Ženiš,¹⁴⁶a D. Zerwas,¹¹⁹ D. Zhang,⁹² F. Zhang,¹⁷⁶ G. Zhang,³⁶a,yy H. Zhang,³⁵b J. Zhang,<fnref n="6" />

L. Zhang,⁵¹ L. Zhang,³⁶a M. Zhang,¹⁶⁹ P. Zhang,³⁵b R. Zhang,<fnref n="23" /> R. Zhang,³⁶a,ww X. Zhang,³⁶b Y. Zhang,³⁵a,³⁵d Z. Zhang,¹¹⁹

X. Zhao,⁴³ Y. Zhao,³⁶b,aaa Z. Zhao,³⁶a A. Zhemchugov,⁶⁸ B. Zhou,⁹² C. Zhou,¹⁷⁶ L. Zhou,⁴³ M. Zhou,³⁵a,³⁵d M. Zhou,¹⁵⁰

N. Zhou,³⁵c C. G. Zhu,³⁶b H. Zhu,³⁵a J. Zhu,⁹² Y. Zhu,³⁶a X. Zhuang,³⁵a K. Zhukov,⁹⁸ A. Zibell,¹⁷⁷ D. Zieminska,⁶⁴

N. I. Zimine,⁶⁸ C. Zimmermann,⁸⁶ S. Zimmermann,⁵¹ Z. Zinonos,¹⁰³ M. Zinser,⁸⁶ M. Ziolkowski,¹⁴³ L. Živković,<fnref n="14" />

G. Zobernig,¹⁷⁶ A. Zoccoli,²²a,²²b R. Zou,³³ M. zur Nedden,<fnref n="17" /> and L. Zwalinski³²

(ATLAS Collaboration)

<footnote n="1">¹Department of Physics, University of Adelaide, Adelaide, Australia</footnote>

<footnote n="2">²Physics Department, SUNY Albany, Albany, New York, USA</footnote>

<footnote n="3">³Department of Physics, University of Alberta, Edmonton, Alberta, Canada</footnote>

<footnote n="4">⁴ªDepartment of Physics, Ankara University, Ankara, Turkey</footnote>

<footnote n="4">⁴ᵇIstanbul Aydin University, Istanbul, Turkey</footnote>

<footnote n="4">⁴ᶜDivision of Physics, TOBB University of Economics and Technology, Ankara, Turkey</footnote>

<footnote n="5">⁵LAPP, CNRS/IN2P3 and Université Savoie Mont Blanc, Annecy-le-Vieux, France</footnote>

<footnote n="6">⁶High Energy Physics Division, Argonne National Laboratory, Argonne, Illinois, USA</footnote>

<footnote n="7">⁷Department of Physics, University of Arizona, Tucson, Arizona, USA</footnote>

<footnote n="8">⁸Department of Physics, The University of Texas at Arlington, Arlington, Texas, USA</footnote>

<footnote n="9">⁹Physics Department, National and Kapodistrian University of Athens, Athens, Greece</footnote>

<footnote n="10">¹⁰Physics Department, National Technical University of Athens, Zografou, Greece</footnote>

<footnote n="11">¹¹Department of Physics, The University of Texas at Austin, Austin, Texas, USA</footnote>

<footnote n="12">¹²Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan</footnote>

<footnote n="13">¹³Institut de Física d'Altes Energies (IFAE), The Barcelona Institute of Science and Technology,
Barcelona, Spain</footnote>

<footnote n="14">¹⁴Institute of Physics, University of Belgrade, Belgrade, Serbia</footnote>

<footnote n="15">¹⁵Department for Physics and Technology, University of Bergen, Bergen, Norway</footnote>

<footnote n="16">¹⁶Physics Division, Lawrence Berkeley National Laboratory and University of California, Berkeley,
California, USA</footnote>

<footnote n="17">¹⁷Department of Physics, Humboldt University, Berlin, Germany</footnote>

<footnote n="18">¹⁸Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics,
University of Bern, Bern, Switzerland</footnote>

<footnote n="19">¹⁹School of Physics and Astronomy, University of Birmingham, Birmingham, United Kingdom</footnote>

<footnote n="20">²⁰ªDepartment of Physics, Bogazici University, Istanbul, Turkey</footnote>

<footnote n="20">²⁰ᵇDepartment of Physics Engineering, Gaziantep University, Gaziantep, Turkey</footnote>

<footnote n="20">²⁰ᵈIstanbul Bilgi University, Faculty of Engineering and Natural Sciences, Istanbul, Turkey</footnote>

<footnote n="20">²⁰ᵉBahcesehir University, Faculty of Engineering and Natural Sciences, Istanbul, Turkey</footnote>

<footnote n="21">²¹Centro de Investigaciones, Universidad Antonio Narino, Bogota, Colombia</footnote>

<footnote n="22">²²ªINFN Sezione di Bologna, Italy</footnote>

<footnote n="22">²²ᵇDipartimento di Fisica e Astronomia, Università di Bologna, Bologna, Italy</footnote>

<footnote n="23">²³Physikalisches Institut, University of Bonn, Bonn, Germany</footnote>

<footnote n="24">²⁴Department of Physics, Boston University, Boston, Massachusetts, USA</footnote>

<footnote n="25">²⁵Department of Physics, Brandeis University, Waltham, Massachusetts, USA</footnote>

<footnote n="26">²⁶ªUniversidade Federal do Rio De Janeiro COPPE/EE/IF, Rio de Janeiro, Brazil</footnote>

<footnote n="26">²⁶ᵇElectrical Circuits Department, Federal University of Juiz de Fora (UFJF), Juiz de Fora, Brazil</footnote>

<footnote n="26">²⁶ᶜFederal University of Sao Joao del Rei (UFSJ), Sao Joao del Rei, Brazil</footnote>

<footnote n="26">²⁶ᵈInstituto de Fisica, Universidade de Sao Paulo, Sao Paulo, Brazil</footnote>

<footnote n="27">²⁷Physics Department, Brookhaven National Laboratory, Upton, New York, USA</footnote>

<footnote n="28">²⁸ªTransilvania University of Brasov, Brasov, Romania</footnote>

<footnote n="28">²⁸ᵇHoria Hulubei National Institute of Physics and Nuclear Engineering, Bucharest, Romania</footnote>

<footnote n="28">²⁸ᶜDepartment of Physics, Alexandru Ioan Cuza University of Iasi, Iasi, Romania</footnote>
²⁸dNational Institute for Research and Development of Isotopic and Molecular Technologies,
Physics Department, Cluj Napoca, Romania

²⁸eUniversity Politehnica Bucharest, Bucharest, Romania

²⁸fWest University in Timisoara, Timisoara, Romania

²⁹Departamento de Física, Universidad de Buenos Aires, Buenos Aires, Argentina

³⁰Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom

³¹Department of Physics, Carleton University, Ottawa ON, Canada

³²CERN, Geneva, Switzerland

³³Enrico Fermi Institute, University of Chicago, Chicago, Illinois, USA

³⁴aDepartamento de Física, Pontificia Universidad Católica de Chile, Santiago, Chile

³⁴bDepartamento de Física, Universidad Técnica Federico Santa María, Valparaíso, Chile

³⁵aInstitute of High Energy Physics, Chinese Academy of Sciences, Beijing, China

³⁵bDepartment of Physics, Nanjing University, Jiangsu, China

³⁵cPhysics Department, Tsinghua University, Beijing 100084, China

³⁵dUniversity of Chinese Academy of Science (UCAS), Beijing, China

³⁶aDepartment of Modern Physics and State Key Laboratory of Particle Detection and Electronics,
University of Science and Technology of China, Anhui, China

³⁶bSchool of Physics, Shandong University, Shandong, China

³⁶cDepartment of Physics and Astronomy, Key Laboratory for Particle Physics, Astrophysics and Cosmology,
Ministry of Education; Shanghai Key Laboratory for Particle Physics and Cosmology, Shanghai Jiao Tong
University, Shanghai(also at PKU-CHEP), China

³⁷Université Clermont Auvergne, CNRS/IN2P3, LPC, Clermont-Ferrand, France

³⁸Nevis Laboratory, Columbia University, Irvington, New York, USA

³⁹Niels Bohr Institute, University of Copenhagen, Kobenhavn, Denmark

⁴⁰aINFN Gruppo Collegato di Cosenza, Laboratori Nazionali di Frascati, Italy

⁴⁰bDipartimento di Fisica, Università della Calabria, Rende, Italy

⁴¹aAGH University of Science and Technology, Faculty of Physics and Applied Computer Science,
Krakow, Poland

⁴¹bMarian Smoluchowski Institute of Physics, Jagiellonian University, Krakow, Poland

⁴²Institute of Nuclear Physics Polish Academy of Sciences, Krakow, Poland

⁴³Physics Department, Southern Methodist University, Dallas, Texas, USA

⁴⁴Physics Department, University of Texas at Dallas, Richardson, Texas, USA

⁴⁵DESY, Hamburg and Zeuthen, Germany

⁴⁶Lehrstuhl für Experimentelle Physik IV, Technische Universität Dortmund, Dortmund, Germany

⁴⁷Institut für Kern- und Teilchenphysik, Technische Universität Dresden, Dresden, Germany

⁴⁸Department of Physics, Duke University, Durham, North Carolina, USA

⁴⁹SUPA - School of Physics and Astronomy, University of Edinburgh, Edinburgh, United Kingdom

⁵⁰INFN e Laboratori Nazionali di Frascati, Frascati, Italy

⁵¹Fakultät für Mathematik und Physik, Albert-Ludwigs-Universität, Freiburg, Germany

⁵²Departement de Physique Nucleaire et Corpusculaire, Université de Genève, Geneva, Switzerland

⁵³aINFN Sezione di Genova, Genova, Italy

⁵³bDipartimento di Fisica, Università di Genova, Genova, Italy

⁵⁴aE. Andronikashvili Institute of Physics, Iv. Javakhishvili Tbilisi State University, Tbilisi, Georgia

⁵⁴bHigh Energy Physics Institute, Tbilisi State University, Tbilisi, Georgia

⁵⁵II Physikalisches Institut, Justus-Liebig-Universität Giessen, Giessen, Germany

⁵⁶SUPA - School of Physics and Astronomy, University of Glasgow, Glasgow, United Kingdom

⁵⁷II Physikalisches Institut, Georg-August-Universität, Göttingen, Germany

⁵⁸Laboratoire de Physique Subatomique et de Cosmologie, Université Grenoble-Alpes,
CNRS/IN2P3, Grenoble, France

⁵⁹Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge, Massachusetts, USA

⁶⁰aKirchhoff-Institut für Physik, Ruprecht-Karls-Universität Heidelberg, Heidelberg, Germany

⁶⁰bPhysikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg, Germany

⁶¹Faculty of Applied Information Science, Hiroshima Institute of Technology, Hiroshima, Japan

⁶²aDepartment of Physics, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China

⁶²bDepartment of Physics, The University of Hong Kong, Hong Kong, China

⁶²cDepartment of Physics and Institute for Advanced Study, The Hong Kong University of Science and
Technology, Clear Water Bay, Kowloon, Hong Kong, China

⁶³Department of Physics, National Tsing Hua University, Taiwan, Taiwan

⁶⁴Department of Physics, Indiana University, Bloomington, Indiana, USA

⁶⁵Institut für Astro- und Teilchenphysik, Leopold-Franzens-Universität, Innsbruck, Austria
⁶⁶University of Iowa, Iowa City, Iowa, USA

⁶⁷Department of Physics and Astronomy, Iowa State University, Ames, Iowa, USA

⁶⁸Joint Institute for Nuclear Research, JINR Dubna, Dubna, Russia

⁶⁹KEK, High Energy Accelerator Research Organization, Tsukuba, Japan

⁷⁰Graduate School of Science, Kobe University, Kobe, Japan

⁷¹Faculty of Science, Kyoto University, Kyoto, Japan

⁷²Kyoto University of Education, Kyoto, Japan

⁷³Research Center for Advanced Particle Physics and Department of Physics, Kyushu University, Fukuoka, Japan

⁷⁴Instituto de Física La Plata, Universidad Nacional de La Plata and CONICET, La Plata, Argentina

⁷⁵Physics Department, Lancaster University, Lancaster, United Kingdom

⁷⁶INFN Sezione di Lecce, Italy

⁷⁶bDipartimento di Matematica e Fisica, Università del Salento, Lecce, Italy

⁷⁷Oliver Lodge Laboratory, University of Liverpool, Liverpool, United Kingdom

⁷⁸Department of Experimental Particle Physics, Jožef Stefan Institute and Department of Physics, University of Ljubljana, Ljubljana, Slovenia

⁷⁹School of Physics and Astronomy, Queen Mary University of London, London, United Kingdom

⁸⁰Department of Physics, Royal Holloway University of London, Surrey, United Kingdom

⁸¹Department of Physics and Astronomy, University College London, London, United Kingdom

⁸²Louisiana Tech University, Ruston, Los Angeles, USA

⁸³Laboratoire de Physique Nucléaire et de Hautes Energies, UPMC and Université Paris-Diderot and CNRS/IN2P3, Paris, France

⁸⁴Fysiska institutionen, Lunds universitet, Lund, Sweden

⁸⁵Departamento de Fisica Teorica C-15, Universidad Autonoma de Madrid, Madrid, Spain

⁸⁶Institut für Physik, Universität Mainz, Mainz, Germany

⁸⁷School of Physics and Astronomy, University of Manchester, Manchester, United Kingdom

⁸⁸CPPM, Aix-Marseille Université and CNRS/IN2P3, Marseille, France

⁸⁹Department of Physics, University of Massachusetts, Amherst, Massachusetts, USA

⁹⁰Department of Physics, McGill University, Montreal QC, Canada

⁹¹School of Physics, University of Melbourne, Victoria, Australia

⁹²Department of Physics, The University of Michigan, Ann Arbor, Michigan, USA

⁹³Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan, USA

⁹⁴aINFN Sezione di Milano, Milano, Italy

⁹⁴bDipartimento di Fisica, Università di Milano, Milano, Italy

⁹⁵B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk, Republic of Belarus

⁹⁶Research Institute for Nuclear Problems of Byelorussian State University, Minsk, Republic of Belarus

⁹⁷Group of Particle Physics, University of Montreal, Montreal QC, Canada

⁹⁸P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow, Russia

⁹⁹Institute for Theoretical and Experimental Physics (ITEP), Moscow, Russia

¹⁰⁰National Research Nuclear University MEPhI, Moscow, Russia

¹⁰¹D.V. Skobeltsyn Institute of Nuclear Physics, M.V. Lomonosov Moscow State University, Moscow, Russia

¹⁰²Fakultät für Physik, Ludwig-Maximilians-Universität München, München, Germany

¹⁰³Max-Planck-Institut für Physik (Werner-Heisenberg-Institut), München, Germany

¹⁰⁴Nagasaki Institute of Applied Science, Nagasaki, Japan

¹⁰⁵Graduate School of Science and Kobayashi-Maskawa Institute, Nagoya University, Nagoya, Japan

¹⁰⁶aINFN Sezione di Napoli, Italy

¹⁰⁶bDipartimento di Fisica, Università di Napoli, Napoli, Italy

¹⁰⁷Department of Physics and Astronomy, University of New Mexico, Albuquerque, New Mexico, USA

¹⁰⁸Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen, Netherlands

¹⁰⁹Nikhef National Institute for Subatomic Physics and University of Amsterdam, Amsterdam, Netherlands

¹¹⁰Department of Physics, Northern Illinois University, DeKalb, Illinois, USA

¹¹¹Budker Institute of Nuclear Physics, SB RAS, Novosibirsk, Russia

¹¹²Department of Physics, New York University, New York, New York, USA

¹¹³Ohio State University, Columbus, Ohio, USA

¹¹⁴Faculty of Science, Okayama University, Okayama, Japan

¹¹⁵Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman, Oklahoma, USA

¹¹⁶Department of Physics, Oklahoma State University, Stillwater, Oklahoma, USA
¹¹⁷Palacký University, RCPTM, Olomouc, Czech Republic

¹¹⁸Center for High Energy Physics, University of Oregon, Eugene, Oregon, USA

¹¹⁹LAL, Univ. Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay, France

¹²⁰Graduate School of Science, Osaka University, Osaka, Japan

¹²¹Department of Physics, University of Oslo, Oslo, Norway

¹²²Department of Physics, Oxford University, Oxford, United Kingdom

¹²³aINFN Sezione di Pavia, Italy

¹²³bDipartimento di Fisica, Università di Pavia, Pavia, Italy

¹²⁴Department of Physics, University of Pennsylvania, Philadelphia, Pennsylvania, USA

¹²⁵National Research Centre “Kurchatov Institute” B.P.Konstantinov Petersburg Nuclear Physics Institute, St. Petersburg, Russia

¹²⁶aINFN Sezione di Pisa, Italy

¹²⁶bDipartimento di Fisica E. Fermi, Università di Pisa, Pisa, Italy

¹²⁷Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, Pennsylvania, USA

¹²⁸aLaboratório de Instrumentação e Física Experimental de Partículas - LIP, Lisboa, Portugal

¹²⁸bFaculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal

¹²⁸cDepartment of Physics, University of Coimbra, Coimbra, Portugal

¹²⁸dCentro de Física Nuclear da Universidade de Lisboa, Lisboa, Portugal

¹²⁸eDepartamento de Fisica, Universidade do Minho, Braga, Portugal

¹²⁸fDepartamento de Fisica Teorica y del Cosmos, Universidad de Granada, Granada, Portugal

¹²⁸gDep Fisica and CEFITEC of Faculdade de Ciencias e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal

¹²⁹Institute of Physics, Academy of Sciences of the Czech Republic, Praha, Czech Republic

¹³⁰Czech Technical University in Prague, Praha, Czech Republic

¹³¹Charles University, Faculty of Mathematics and Physics, Prague, Czech Republic

¹³²State Research Center Institute for High Energy Physics (Protvino), NRC KI, Russia

¹³³Particle Physics Department, Rutherford Appleton Laboratory, Didcot, United Kingdom

¹³⁴aINFN Sezione di Roma, Italy

¹³⁴bDipartimento di Fisica, Sapienza Università di Roma, Roma, Italy

¹³⁵aINFN Sezione di Roma Tor Vergata, Italy

¹³⁵bDipartimento di Fisica, Università di Roma Tor Vergata, Roma, Italy

¹³⁶aINFN Sezione di Roma Tre, Italy

¹³⁶bDipartimento di Matematica e Fisica, Università Roma Tre, Roma, Italy

¹³⁷aFaculté des Sciences Ain Chock, Réseau Universitaire de Physique des Hautes Energies - Université Hassan II, Casablanca, Morocco

¹³⁷bCentre National de l'Energie des Sciences Techniques Nucleaires, Rabat, Morocco

¹³⁷cFaculté des Sciences Semlalia, Université Cadi Ayyad, LPHEA-Marrakech, Morocco

¹³⁷dFaculté des Sciences, Université Mohamed Premier and LPTPM, Oujda, Morocco

¹³⁷eFaculté des sciences, Université Mohammed V, Rabat, Morocco

¹³⁸DSM/IRFU (Institut de Recherches sur les Lois Fondamentales de l'Univers), CEA Saclay (Commissariat à l'Energie Atomique et aux Energies Alternatives), Gif-sur-Yvette, France

¹³⁹Santa Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz, California, USA

¹⁴⁰Department of Physics, University of Washington, Seattle, Washington, USA

¹⁴¹Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom

¹⁴²Department of Physics, Shinshu University, Nagano, Japan

¹⁴³Department Physik, Universität Siegen, Siegen, Germany

¹⁴⁴Department of Physics, Simon Fraser University, Burnaby BC, Canada

¹⁴⁵SLAC National Accelerator Laboratory, Stanford, California, USA

¹⁴⁶aFaculty of Mathematics, Physics & Informatics, Comenius University, Bratislava, Slovak Republic

¹⁴⁶bDepartment of Subnuclear Physics, Institute of Experimental Physics of the Slovak Academy of Sciences, Kosice, Slovak Republic

¹⁴⁷aDepartment of Physics, University of Cape Town, Cape Town, South Africa

¹⁴⁷bDepartment of Physics, University of Johannesburg, Johannesburg, South Africa

¹⁴⁷cSchool of Physics, University of the Witwatersrand, Johannesburg, South Africa

¹⁴⁸aDepartment of Physics, Stockholm University, Stockholm, Sweden

¹⁴⁸bThe Oskar Klein Centre, Stockholm, Sweden

¹⁴⁹Physics Department, Royal Institute of Technology, Stockholm, Sweden

¹⁵⁰Departments of Physics and Astronomy and Chemistry, Stony Brook University, Stony Brook, New York, USA
¹⁵¹Department of Physics and Astronomy, University of Sussex, Brighton, United Kingdom

¹⁵²School of Physics, University of Sydney, Sydney, Australia

¹⁵³Institute of Physics, Academia Sinica, Taipei, Taiwan

¹⁵⁴Department of Physics, Technion: Israel Institute of Technology, Haifa, Israel

¹⁵⁵Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv University, Tel Aviv, Israel

¹⁵⁶Department of Physics, Aristotle University of Thessaloniki, Thessaloniki, Greece

¹⁵⁷International Center for Elementary Particle Physics and Department of Physics,
The University of Tokyo, Tokyo, Japan

¹⁵⁸Graduate School of Science and Technology, Tokyo Metropolitan University, Tokyo, Japan

¹⁵⁹Department of Physics, Tokyo Institute of Technology, Tokyo, Japan

¹⁶⁰Tomsk State University, Tomsk, Russia

¹⁶¹Department of Physics, University of Toronto, Toronto ON, Canada

¹⁶²aINFN-TIFPA, Trento, Italy

¹⁶²bUniversity of Trento, Trento, Italy

¹⁶³aTRIUMF, Vancouver BC, Canada

¹⁶³bDepartment of Physics and Astronomy, York University, Toronto ON, Canada

¹⁶⁴Faculty of Pure and Applied Sciences, and Center for Integrated Research in Fundamental Science and Engineering, University of Tsukuba, Tsukuba, Japan

¹⁶⁵Department of Physics and Astronomy, Tufts University, Medford, Massachusetts, USA

¹⁶⁶Department of Physics and Astronomy, University of California Irvine, Irvine, California, USA

¹⁶⁷aINFN Gruppo Collegato di Udine, Sezione di Trieste, Udine, Italy

¹⁶⁷bICTP, Trieste, Italy

¹⁶⁷cDipartimento di Chimica, Fisica e Ambiente, Università di Udine, Udine, Italy

¹⁶⁸Department of Physics and Astronomy, University of Uppsala, Uppsala, Sweden

¹⁶⁹Department of Physics, University of Illinois, Urbana, Illinois, USA

¹⁷⁰Instituto de Fisica Corpuscular (IFIC), Centro Mixto Universidad de Valencia - CSIC, Valencia, Spain

¹⁷¹Department of Physics, University of British Columbia, Vancouver BC, Canada

¹⁷²Department of Physics and Astronomy, University of Victoria, Victoria BC, Canada

¹⁷³Department of Physics, University of Warwick, Coventry, United Kingdom

¹⁷⁴Waseda University, Tokyo, Japan

¹⁷⁵Department of Particle Physics, The Weizmann Institute of Science, Rehovot, Israel

¹⁷⁶Department of Physics, University of Wisconsin, Madison, Wisconsin, USA

¹⁷⁷Fakultät für Physik und Astronomie, Julius-Maximilians-Universität, Würzburg, Germany

¹⁷⁸Fakultät für Mathematik und Naturwissenschaften, Fachgruppe Physik,
Bergische Universität Wuppertal, Wuppertal, Germany

¹⁷⁹Department of Physics, Yale University, New Haven, Connecticut, USA

¹⁸⁰Yerevan Physics Institute, Yerevan, Armenia

¹⁸¹Centre de Calcul de l'Institut National de Physique Nucléaire et de Physique des Particules (IN2P3),
Villeurbanne, France

¹⁸²Academia Sinica Grid Computing, Institute of Physics, Academia Sinica, Taipei, Taiwan

<footnote>ᵃDeceased.</footnote>

<footnote>ᵇAlso at Department of Physics, King's College London, London, United Kingdom.</footnote>

<footnote>ᶜAlso at Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan.</footnote>

<footnote>ᵈAlso at Novosibirsk State University, Novosibirsk, Russia.</footnote>

<footnote>ᵉAlso at TRIUMF, Vancouver BC, Canada.</footnote>

<footnote>>fAlso at Department of Physics and Astronomy, University of Louisville, Louisville, KY, USA.</footnote>

<footnote>gAlso at Physics Department, An-Najah National University, Nablus, Palestine.</footnote>

<footnote>hAlso at Department of Physics, California State University, Fresno CA, USA.</footnote>

<footnote>iAlso at Department of Physics, University of Fribourg, Fribourg, Switzerland.</footnote>

<footnote>jAlso at II Physikalisches Institut, Georg-August-Universität, Göttingen, Germany.</footnote>

<footnote>kAlso at Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona, Spain.</footnote>

<footnote>lAlso at Departamento de Fisica e Astronomia, Faculdade de Ciencias, Universidade do Porto, Portugal.</footnote>

<footnote>mAlso at Tomsk State University, Tomsk, and Moscow Institute of Physics and Technology State University, Dolgoprudny, Russia.</footnote>

<footnote>nAlso at The Collaborative Innovation Center of Quantum Matter (CICQM), Beijing, China.</footnote>

<footnote>oAlso at Universita di Napoli Parthenope, Napoli, Italy.</footnote>

<footnote>pAlso at Institute of Particle Physics (IPP), Canada.</footnote>

<footnote>qAlso at Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest, Romania.</footnote>

<footnote>rAlso at Department of Physics, St. Petersburg State Polytechnical University, St. Petersburg, Russia.</footnote>

<footnote>sAlso at Borough of Manhattan Community College, City University of New York, New York City, USA.</footnote>
¹Also at Department of Financial and Management Engineering, University of the Aegean, Chios, Greece.

²Also at Centre for High Performance Computing, CSIR Campus, Rosebank, Cape Town, South Africa.

³Also at Louisiana Tech University, Ruston LA, USA.

⁴Also at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona, Spain.

⁵Also at Department of Physics, The University of Michigan, Ann Arbor MI, USA.

⁶Also at Graduate School of Science, Osaka University, Osaka, Japan.

⁷Also at Fakultät für Mathematik und Physik, Albert-Ludwigs-Universität, Freiburg, Germany.

⁸Also at Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen, Netherlands.

⁹Also at Department of Physics, The University of Texas at Austin, Austin TX, USA.

¹⁰Also at Institute of Theoretical Physics, Ilia State University, Tbilisi, Georgia.

¹¹Also at CERN, Geneva, Switzerland.

¹²Also at Georgian Technical University (GTU), Tbilisi, Georgia.

¹³Also at Ochadai Academic Production, Ochanomizu University, Tokyo, Japan.

¹⁴Also at Manhattan College, New York, New York, USA.

¹⁵Also at Departamento de Física, Pontificia Universidad Católica de Chile, Santiago, Chile.

¹⁶Also at The City College of New York, New York, New York, USA.

¹⁷Also at School of Physics, Shandong University, Shandong, China.

¹⁸Also at Departamento de Física Teórica y del Cosmo, Universidad de Granada, Granada, Portugal.

¹⁹Also at Department of Physics, California State University, Sacramento CA, USA.

²⁰Also at Moscow Institute of Physics and Technology State University, Dolgoprudny, Russia.

²¹Also at Departement de Physique Nucleaire et Corpusculaire, Université de Genève, Geneva, Switzerland.

²²Also at Institut de Física d'Altes Energies (IFAE), The Barcelona Institute of Science and Technology, Barcelona, Spain.

²³Also at School of Physics, Sun Yat-sen University, Guangzhou, China.

²⁴Also at Institute for Nuclear Research and Nuclear Energy (INRNE) of the Bulgarian Academy of Sciences, Sofia, Bulgaria.

²⁵Also at Faculty of Physics, M.V.Lomonosov Moscow State University, Moscow, Russia.

²⁶Also at National Research Nuclear University MEPhI, Moscow, Russia.

²⁷Also at Department of Physics, Stanford University, Stanford CA, USA.

²⁸Also at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest, Hungary.

²⁹Also at Giresun University, Faculty of Engineering, Turkey.

³⁰Also at CPPM, Aix-Marseille Université and CNRS/IN2P3, Marseille, France.

³¹Also at Department of Physics, Nanjing University, Jiangsu, China.

³²Also at Institute of Physics, Academia Sinica, Taipei, Taiwan.

³³Also at University of Malaya, Department of Physics, Kuala Lumpur, Malaysia.

³⁴Also at LAL, Univ. Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay, France.