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Springer
Received: August 13, Revised: October 25, Accepted: November 3, Published: November 13,
2018 2018 2018 2018
The ATLAS collaboration E-mail:
[email protected] Abstract: A search for charged Higgs bosons heavier than the top quark and decaying via H ± → tb is presented. The data analysed corresponds to 36.1 fb−1 of pp collisions at √ s = 13 TeV and was recorded with the ATLAS detector at the LHC in 2015 and 2016. The production of a charged Higgs boson in association with a top quark and a bottom quark, pp → tbH ± , is explored in the mass range from mH ± = 200 to 2000 GeV using multi-jet final states with one or two electrons or muons. Events are categorised according to the multiplicity of jets and how likely these are to have originated from hadronisation of a bottom quark. Multivariate techniques are used to discriminate between signal and background events. No significant excess above the background-only hypothesis is observed and exclusion limits are derived for the production cross-section times branching ratio of a charged Higgs boson as a function of its mass, which range from 2.9 pb at mH ± = 200 GeV to 0.070 pb at mH ± = 2000 GeV. The results are interpreted in two benchmark scenarios of the Minimal Supersymmetric Standard Model. Keywords: Beyond Standard Model, Hadron-Hadron scattering (experiments), Higgs physics ArXiv ePrint: 1808.03599
Open Access, Copyright CERN, for the benefit of the ATLAS Collaboration. Article funded by SCOAP3 .
https://doi.org/10.1007/JHEP11(2018)085
JHEP11(2018)085
Search for charged Higgs bosons decaying into top √ and bottom quarks at s = 13 TeV with the ATLAS detector
Contents 1
2 ATLAS detector
3
3 Signal and background modelling
4
4 Object and event selection
6
5 Analysis strategy 5.1 Background estimate 5.2 Multivariate analysis
9 9 10
6 Systematic uncertainties
16
7 Statistical analysis
20
8 Results
20
9 Conclusions
27
A BDT input variables
28
The ATLAS collaboration
38
1
Introduction
Following the discovery of a Higgs boson, H, with a mass of around 125 GeV and consistent with the Standard Model (SM) [1–3] at the Large Hadron Collider (LHC) in 2012 [4] a key question is whether this Higgs boson is the only Higgs boson, or the first observed physical state of an extended Higgs sector. No charged fundamental scalar boson exists in the SM, but many beyond the Standard Model (BSM) scenarios contain an extended Higgs sector with at least one set of charged Higgs bosons, H + and H − , in particular two-Higgs-doublet models (2HDM) [5–8] and models containing Higgs triplets [9–13]. The production mechanisms and decay modes of a charged Higgs boson1 depend on its mass, mH + . This analysis searches for heavy charged Higgs bosons with mH + > mt + mb , where mt and mb are the masses of the top and bottom quarks, respectively. The dominant production mode is expected to be in association with a top quark and a bottom quark (tbH + ), as illustrated in figure 1. In the 2HDM, H + production and decay at tree level For simplicity in the following, charged Higgs bosons are denoted H + , with the charge-conjugate H − always implied. Similarly, the difference between quarks and antiquarks, q and q¯, is generally understood from the context, so that e.g. H + → tb means both H + → t¯b and H − → t¯b. 1
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1 Introduction
✁ g
t¯
H+
g
¯b t
b
Figure 1. Leading-order Feynman diagram for the production of a heavy charged Higgs boson (mH + > mt + mb ) in association with a top quark and a bottom quark (tbH + ).
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depend on its mass and two parameters: tanβ and α, which are the ratio of the vacuum expectation values of the two Higgs doublets and the mixing angle between the CP-even Higgs bosons, respectively. The dominant decay mode for heavy charged Higgs bosons is H + → tb in a broad range of models [14, 15]. In particular, this is the preferred decay mode in both the decoupling limit scenario and the alignment limit cos(β − α) ≈ 0, where the lightest CP-even neutral Higgs boson of the extended Higgs sector has properties similar to those of the SM Higgs boson [7]. For lower mH + , the dominant decay mode is H + → τ ν. It is also predicted that this decay mode becomes more relevant as the value of tanβ increases, irrespective of mH + . Therefore, the H + → tb and H + → τ ν decays naturally complement each other in searches for charged Higgs bosons. Limits on charged Higgs boson production have been obtained by many experiments, such as the LEP experiments with upper limits on H + production in the mass range 40– 100 GeV [16], and CDF and DØ at the Tevatron that set upper limits on the branching ratio B(t → bH + ) for 80 GeV < mH + < 150 GeV [17, 18]. The CMS Collaboration has performed direct searches for heavy charged Higgs bosons in 8 TeV proton-proton (pp) collisions. By assuming the branching ratio B(H + → tb) = 1, an upper limit of 2.0–0.13 pb was obtained for the production cross-section σ(pp → tbH + ) for 180 GeV < mH + < 600 GeV [19]. The ATLAS Collaboration has searched for similar heavy charged Higgs boson production in the H + → tb decay channel at 8 TeV, setting upper limits on the production cross-section times the H + → tb branching ratio of 6–0.2 pb for 200 GeV < mH + < 600 GeV [20]. Indirect constraints can be obtained from the measurement of flavour-physics observables sensitive to charged Higgs boson exchange. Such observables include the relative branching ratios of B or K meson decays, B meson mixing parameters, the ratio of the Z decay partial widths Γ(Z → b¯b)/Γ(Z → hadrons), as well as the measurements of b → sγ decays [21, 22]. The relative branching ratio R(D(∗) ) = B(B → D(∗) τ ν)/B(B → D(∗) `ν), where ` denotes e or µ, are especially sensitive to contributions from new physics. Measurements from BaBar [23] exclude H + for all mH + and tanβ values in a Type-II 2HDM. However, more recent measurements from Belle [24–26] and LHCb [27] place a weaker constraint on the allowed range of mH + / tanβ values. A global fit combining the most recent flavour-physics results [22] sets a lower limit at 95% confidence level on the charged Higgs boson mass of mH + & 600 GeV for tanβ > 1 and mH + & 650 GeV for lower tanβ values, assuming a Type-II 2HDM. This paper presents a search for H + production in the H + → tb decay mode using pp √ collisions at s = 13 TeV. Events with one charged lepton (` = e, µ) and jets in the final
2
ATLAS detector
The ATLAS detector [31] at the LHC is a multipurpose particle detector with a forwardbackward symmetric cylindrical geometry and near 4π coverage around the collision point.2 The ATLAS detector consists of an inner tracking detector (ID) surrounded by a thin superconducting solenoid producing a 2 T axial magnetic field, electromagnetic (EM) and hadronic calorimeters, and an external muon spectrometer (MS) incorporating three large toroid magnet assemblies. The ID contains a high-granularity silicon pixel detector, including an insertable B-layer [32] added in 2014 as a new innermost layer, and a silicon microstrip tracker, providing precision tracking in the pseudorapidity range |η| < 2.5. The silicon detectors are complemented by a transition radiation tracker providing tracking and electron identification information for |η| < 2.0. The EM sampling calorimeter uses lead as the absorber material and liquid argon (LAr) as the active medium, and is divided into barrel (|η| < 1.47) and endcap (1.37 < |η| < 3.20) regions. Hadron calorimetry is also based on 2
ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP) in the centre of the detector and the z-axis along the beam pipe. The x-axis points from the IP to the centre of the LHC ring, and the y-axis points upwards. Cylindrical coordinates (r, φ) are used in the transverse plane, φ being the azimuthal angle around the z-axis. The pseudorapidity is defined in terms of p 2 + (∆φ)2 the polar angle θ as η = − ln tan(θ/2). Angular distance is measured in units of ∆R ≡ (∆η) p 2 2 (pseudorapidity and azimuthal angle). Alternatively, the distance ∆Ry ≡ (∆y) + (∆φ) is used, where y = 0.5 ln [(E + pz ) / (E − pz )] is the rapidity of a particle of energy E and momentum component pz along the beam axis.
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state (`+jets final state) and events with two charged leptons and jets in the final state (`` final state) are considered. Exclusive regions are defined according to the number of jets and those that are tagged as originating from the hadronisation of a b-quark. In order to separate the signal from the SM background, multivariate discriminants are employed in the regions where the signal contributions are expected to be largest. Limits on the H + → tb production cross-section are set by means of a simultaneous fit of binned distributions of multivariate discriminants in the signal-rich regions and inclusive event yields in the signaldepleted regions. The results are interpreted in two benchmark scenarios of the Minimal Supersymmetric Standard Model (MSSM): the mmod− scenario [28] and the hMSSM [29]. h Both scenarios exploit the MSSM in such a way that the light CP-even Higgs boson can be interpreted as the observed Higgs boson with mH = 125 GeV. Limits on the value of tanβ are extracted as a function of the charged Higgs boson mass. Finally, the excluded range √ of mH + and tanβ values from the H + → tb and H + → τ ν [30] searches at s = 13 TeV are superimposed, providing a summary of the ATLAS sensitivity to H + through the two decay modes. The paper is organised as follows. Section 2 briefly describes the ATLAS detector. The samples of simulated events used for the analysis are summarised in section 3. Section 4 presents the reconstruction of objects in ATLAS and the event selection. Section 5 describes the analysis strategy while systematic uncertainties are discussed in section 6. The statistical analysis of the data is described in section 7 and the results are presented in section 8. Finally, a summary is given in section 9.
the sampling technique, with scintillator tiles or LAr as the active medium, and with steel, copper, or tungsten as the absorber material. The calorimeters cover |η| < 4.9. The MS measures the deflection of muons with |η| < 2.7 using multiple layers of high-precision tracking chambers located in a toroidal field in the central and endcap regions of ATLAS. The field integral of the toroids ranges between 2.0 and 6.0 T m across most of the detector. The MS is also instrumented with separate trigger chambers covering |η| < 2.4. A two-level trigger system, with the first level implemented in custom hardware and followed by a softwarebased second level, is used to reduce the trigger rate to around 1 kHz for offline storage [33].
Signal and background modelling
The tbH + process was modelled with MadGraph5 aMC@NLO (MG5 aMC) [34] at nextto-leading order (NLO) in QCD [35] using a four-flavour scheme (4FS) implementation with the NNPDF2.3NLO [36] parton distribution function (PDF).3 Parton showering and hadronisation were modelled by Pythia 8.186 [37] with the A14 [38] set of underlyingevent (UE) related parameters tuned to ATLAS data (tune). For the simulation of the tbH + process, the narrow-width approximation was used. This assumption has a negligible impact on the analysis for the models considered in this paper, as the experimental resolution is much larger than the H + natural width. Interference with the SM tt¯ + b¯b background is neglected. Altogether 18 H + mass hypotheses are used, with 25 GeV mass steps between an H + mass of 200 GeV and 300 GeV, 50 GeV steps between 300 GeV and 400 GeV, 100 GeV steps between 400 GeV and 1000 GeV and 200 GeV steps from 1000 GeV to 2000 GeV. The step sizes are selected to match the expected resolution of the H + signal. The samples were processed with a fast simulation of the ATLAS detector [39]. Unless otherwise indicated, the cross-section of the signal is set to 1 pb, for easy rescaling to various model predictions. Only the H + decay into tb is considered, and the top quark decays according to the SM predictions. The nominal sample used to model the tt¯ background was generated using the Powheg-Box v2 NLO-in-QCD generator [40–43], referred to as Powheg in the remainder of this article, with the NNPDF3.0NLO PDF set [44]. The hdamp parameter, which controls the transverse momentum pT of the first additional emission beyond the Born configuration, was set to 1.5 times the top quark mass [45]. Parton shower and hadronisation were modelled by Pythia 8.210 [46] with the A14 UE tune. The sample was normalised to the top++2.0 [47] theoretical cross-section of 832+46 −51 pb, calculated at next-to-next-to-leading order (NNLO) in QCD including resummation of next-to-next-toleading logarithmic (NNLL) soft gluon terms [48–52]. The generation of the tt¯ sample was performed inclusively, with all possible flavours of additional jets produced. The decay of c- and b-hadrons was simulated with the EvtGen v1.2.0 [53] program. The tt¯ + jets background is categorised according to the flavour of additional jets in the event, using 3
Five-flavour scheme (5FS) PDFs consider b-quarks as a source of incoming partons and the b-quarks are therefore assumed to be massless. In contrast, 4FS PDFs only include lighter quarks and gluons, allowing the b-quark mass to be taken into account properly in the matrix element calculation.
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3
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the same procedure as described in ref. [54]. The tt¯ + additional heavy-flavour (HF) jets background is subdivided into the categories tt¯+ ≥1b and tt¯+ ≥1c, depending on whether the additional HF jets originate from hadrons containing b- or c-quarks. Particle jets were reconstructed from stable particles (mean lifetime τ > 3 × 10−11 seconds) at generator level using the anti-kt algorithm [55] with a radius parameter of 0.4, and were required to have pT > 15 GeV and |η| < 2.5. If at least one particle-level jet in the event is matched (∆R < 0.3) to a b-hadron (not originating from a t-decay) with pT > 5 GeV, the event is categorised as tt¯+ ≥1b. In the remaining events, if at least one jet is matched to a c-hadron (not originating from a W decay) but no b-hadron, the event is categorised as tt¯+ ≥1c. Events with tt¯ + jets that belong to neither the tt¯+ ≥1b nor tt¯+ ≥1c category are called tt¯ + light events. For the tt¯+ ≥1b process, subcategories are defined in accord with the matching between particle-level jets and the b-hadrons not from t-decay: events where exactly two jets are matched to b-hadrons (tt¯ + b¯b), events where exactly one jet is matched to a b-hadron (tt¯ + b), events where exactly one jet is matched to two or more b-hadrons (tt¯ + B), and all other events (tt¯+ ≥ 3b). Events where the additional HF jets can only be matched to b-hadrons from multi-parton interactions and final-state gluon radiation are considered separately and labelled as tt¯ + b (MPI/FSR). To model the irreducible tt¯+ ≥1b background to the highest available precision, the tt¯+ ≥1b events from the nominal Powheg+Pythia8 simulation are reweighted to an NLO prediction of tt¯b¯b including parton showering and hadronisation from Sherpa 2.1.1 [56, 57] with OpenLoops [58]. This sample was generated using the 4FS PDF set CT10F4 [59]. Q 1/4 The renormalisation scale (µr ) for this sample was set to the µCMMPS = i=t,t¯,b,¯b ET,i [57, P 60], and the factorisation (µf ) and resummation (µq ) scales to HT /2 = 12 i=t,t¯,b,¯b ET,i . A first type of reweighting is performed in the tt¯+ ≥1b subcategories, using a method similar to the one outlined in ref. [61]. The reweighting corrects the relative normalisation of the tt¯+ ≥1b subcategories to match the predictions from Sherpa, while keeping the overall tt¯+ ≥1b normalisation unchanged. After applying the first reweighting based on the relative normalisation of the tt¯+ ≥1b subcategories, a second type of reweighting is derived and performed on several kinematic variables sequentially. First the pT of the tt¯ system is reweighted, and secondly the pT of the top quarks. The final reweighting is performed depending on the type of tt¯+ ≥1b events. If there is only one additional HF jet, the pT of that jet is used in the final reweighting. If there is more than one additional HF jet, first the ∆R between the HF jets is reweighted and then the pT of the HF dijet system. A closure test is performed on each of the reweighted kinematic variables, showing a reasonable level of agreement between the reweighted Powheg+Pythia8 sample and the Sherpa sample. The Powheg-Box v1 generator was used to produce the samples of W t single-topquark backgrounds, with the CT10 PDF set. Overlaps between the tt¯ and W t final states were handled using the ‘diagram removal’ scheme [62]. The t-channel single-top-quark events were generated using the Powheg-Box v1 generator with the 4FS for the NLO matrix element calculations and the fixed 4FS PDF set CT10F4. The top quarks were decayed with MadSpin [63], which preserves the spin correlations. The samples were interfaced to Pythia 6.428 [64] with the Perugia 2012 UE tune [65]. The single-top-
mT = p2T + m2 of all final-state particles. The events were interfaced to Pythia 8.210 with the A14 UE tune. Variations in tt¯H production due to the extended Higgs sector are not considered in this analysis, since the contribution from the tt¯H background is found to be small. Measurements of the tt¯H production cross-section are compatible with the SM expectation [77, 78]. The minor tH + X backgrounds, consisting of the production of a single top quark in association with a Higgs boson and jets (tHjb), and the production of a single top quark, a W boson and a Higgs boson (W tH), are treated as one background. The tHjb process was simulated with MG5 aMC interfaced to Pythia 8.210 and the CT10 PDF set, and W tH was modelled with MG5 aMC interfaced to Herwig++ [79] using the CTEQ6L1 PDF set [80]. Additional minor SM backgrounds (diboson production, single top s-channel, tZ, tW Z, 4t, ttW W ) were also simulated and accounted for, even though they contribute less than 1% in any analysis region. Except where otherwise stated, all simulated event samples were produced using the full ATLAS detector simulation [81] based on Geant 4 [82]. Additional pile-up interactions were simulated with Pythia 8.186 using the A2 set of tuned parameters [83] and the MSTW2008LO PDF set [84], and overlaid onto the simulated hard-scatter event. All simulated samples were reweighted such that the average number of interactions per bunch crossing (pile-up) matches that of the data. In the simulation, the top quark mass was set to mt = 172.5 GeV. Decays of b- and c-hadrons were performed by EvtGen v1.2.0, except in samples simulated by the Sherpa event generator. The samples and their basic generation parameters are summarised in table 1.
4
Object and event selection
√ The data used in this analysis were recorded in 2015 and 2016 from s = 13 TeV pp collisions with an integrated luminosity of 36.1 fb−1 . Only runs with stable colliding beams and in which all relevant detector components were functional are used. Events are required to have at least one reconstructed vertex with two or more tracks with
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quark W t and t-channel samples were normalised to the approximate NNLO (aNNLO) theoretical cross-section [66–68]. Samples of W/Z+jets events were generated using Sherpa 2.2.1 [56]. Matrix elements were calculated for up to 2 partons at NLO and 4 partons at LO using Comix [69] and OpenLoops and merged with the Sherpa parton shower [70] using the ME+PS@NLO prescription [71]. The NNPDF3.0NNLO PDF set was used together with a dedicated parton shower tune developed by the Sherpa authors. The W/Z+jets events were normalised to the NNLO cross-sections [72–76]. Samples of tt¯V (V = W, Z) events were generated at NLO in the matrix elements calculation using MG5 aMC with the NNPDF3.0NLO PDF set interfaced to Pythia 8.210 with the A14 UE tune. The tt¯H process was modelled using MG5 aMC with NLO matrix elements, NNPDF3.0NLO PDF set and factorisation and renormalisation scales set to µf = q µr = mT /2, where mT is defined as the scalar sum of the transverse masses
Physics process
Generator
Parton shower Cross-section
PDF set
Tune
NNPDF2.3NLO
A14
Powheg-Box v2 Pythia 8.210 NNLO+NNLL NNPDF3.0NLO Sherpa 2.1.1 Sherpa 2.1.1 NLO for tt¯b¯b CT10F4
A14
generator +
normalisation
tbH tt¯ + jets tt¯b¯b
MG5 aMC
Pythia 8.186 —
tt¯V tt¯H
MG5 aMC
Pythia 8.210 NLO
NNPDF3.0
A14
MG5 aMC
Pythia 8.210 NLO
NNPDF3.0NLO
A14
Single top, W t
Powheg-Box v1 Pythia 6.428 aNNLO
Sherpa default
Perugia 2012
CT10F4
Perugia 2012
W +jets
Sherpa 2.2.1
Sherpa 2.2.1 NNLO
NNPDF3.0NNLO Sherpa default
Z+jets
Sherpa 2.2.1
Sherpa 2.2.1 NNLO
NNPDF3.0NNLO Sherpa default
Table 1. Nominal simulated signal and background event samples. The generator, parton shower generator and cross-section used for normalisation are shown together with the applied PDF set and tune. The tt¯b¯b event sample generated using Sherpa 2.1.1 is used to reweight the events from the tt¯+ ≥1b process in the tt¯ + jets sample.
pT > 0.4 GeV. The vertex with the largest sum of the squared pT of associated tracks is taken as the primary vertex. Events were recorded using single-lepton triggers, in both the `+jets and `` final states. To maximise the event selection efficiency, multiple triggers were used, with either low pT thresholds and lepton identification and isolation requirements, or with higher pT thresholds but looser identification criteria and no isolation requirements. Slightly different sets of triggers were used for 2015 and 2016 data. For muons, the lowest pT threshold was 20 (26) GeV in 2015 (2016), while for electrons, triggers with a pT threshold of 24 (26) GeV were used. Simulated events were also required to satisfy the trigger criteria. Electrons are reconstructed from energy clusters in the EM calorimeter associated with tracks reconstructed in the ID [85]. Candidates in the calorimeter transition region 1.37 < |ηcluster | < 1.52 are excluded. Electrons are required to satisfy the tight identification criterion described in ref. [85], based on shower-shape and track-matching variables. Muons are reconstructed from track segments in the MS that are matched to tracks in the ID [86]. Tracks are then re-fit using information from both detector systems. The medium identification criterion described in ref. [86] is used to select muons. To reduce the contribution of leptons from hadronic decays (non-prompt leptons), both the electrons and muons must satisfy isolation criteria. These criteria include both track and calorimeter information, and have an efficiency of 90% for leptons with a pT of 25 GeV, rising to 99% above 60 GeV, as measured in Z → ee [85] and Z → µµ [86] samples. Finally, the lepton tracks must point to the primary vertex of the event: the longitudinal impact parameter z0 must satisfy |z0 sinθ| < 0.5 mm, while the transverse impact parameter significance must satisfy, |d0 |/σ(|d0 |) < 5 (3) for electrons (muons). Jets are reconstructed from three-dimensional topological energy clusters [87] in the calorimeter using the anti-kt jet algorithm [55, 88] with a radius parameter of 0.4. Each topological cluster is calibrated to the EM scale response prior to jet reconstruction. The
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CT10
Single top, t-channel Powheg-Box v1 Pythia 6.428 aNNLO
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reconstructed jets are then calibrated to the jet energy scale (JES) derived from simulation √ and in situ corrections based on s = 13 TeV data [89]. After energy calibration, jets are required to have pT > 25 GeV and |η| < 2.5. Quality criteria are imposed to identify jets arising from non-collision sources or detector noise, and events containing any such jets are removed [90]. Finally, to reduce the effect of pile-up an additional requirement using information about the tracks and the primary vertex associated to a jet (Jet Vertex Tagger) [91] is applied for jets with pT < 60 GeV and |η| < 2.4. Jets are identified as containing the decay of a b-hadron (b-tagged) via an algorithm using multivariate techniques to combine information from the impact parameters of displaced tracks with the topological properties of secondary and tertiary decay vertices reconstructed within the jet [92, 93]. Jets are b-tagged by directly requiring the output discriminant of the b-tagging algorithm to be above a threshold. A criterion with an efficiency of 70% for b-jets in tt¯ events is used to determine the b-jet multiplicity for all final states and H + masses. For this working point, the c-jet and light-jet rejection factors are 12 and 381, respectively. For mH + ≤ 300 GeV, five exclusive efficiency bins are defined using the same b-tagging discriminant: 0–60%, 60–70%, 70–77%, 77–85% and 85–100%, following the procedure described in ref. [94]. These step-wise efficiencies are used as input to the kinematic discriminant described in section 5. When ‘a b-tagged jet’ is mentioned without any further specification, an efficiency of 70% is implied. To avoid counting a single detector response as two objects, an overlap removal procedure is used. First, the closest jet within ∆Ry = 0.2 of a selected electron is removed. If the nearest jet surviving this selection is within ∆Ry = 0.4 of the electron, the electron is discarded, to ensure it is sufficiently separated from nearby jet activity. Muons are removed if they are separated from the nearest jet by ∆Ry < 0.4, to reduce the background from muons from HF decays inside jets. However, if this jet has fewer than three associated tracks, the muon is kept and the jet is removed instead; this avoids an inefficiency for high-energy muons undergoing significant energy loss in the calorimeter. The missing transverse momentum in the event is defined as the negative vector sum of the pT of all the selected electrons, muons and jets described above, with an extra term added to account for energy in the event that is not associated with any of these. This extra term, referred to as the ‘soft term’ in the following, is calculated from ID tracks matched to the primary vertex to make it resilient to pile-up contamination [95–97]. The missing transverse momentum is not used for event selection but is an input to the multivariate discriminants. Events are required to have at least one electron or muon. The leading lepton must be matched to a lepton with the same flavour reconstructed by the trigger algorithm within ∆R < 0.15, and have a pT > 27 GeV. Additional leptons are required to have pT > 10 GeV, or > 15 GeV for events with two electrons. The latter requirement reduces the bakground due to jets and photons that are misidentified as electrons. Events in the `+jets channel and the `` channel are required to be mutually exclusive. Electrons or muons from τ decays are also included in the analysis. For the `+jets channel, five or more jets, of which at least two jets have to be b-tagged, are required. For the `` channel, events with two leptons with opposite charge are selected,
and at least three jets are required, of which two or more must be b-tagged. In the ee and µµ channels, the dilepton invariant mass must be > 15 GeV and outside the Z boson mass window of 83–99 GeV.
5
Analysis strategy
5.1
Background estimate
The background from processes with prompt leptons is estimated using the simulated event samples described in section 3. For tt¯ production, the number of events with high leading jet pT is overestimated in the simulation, and a reweighting function for the leading jet pT distribution is determined by comparing simulation with data in a `+jets CR that requires exactly four jets and at least two b-tagged jets. This function is validated in the dilepton channel and applied to both channels. The normalisation of the Z+HF jets backgrounds is corrected by a factor of 1.3, extracted from dedicated control regions in data, defined by requiring two opposite-charge same-flavour leptons (e+ e− or µ+ µ− ) with an invariant mass compatible with the Z boson mass, 83 GeV < m`` < 99 GeV. Processes that do not contain enough prompt electrons or muons from W or Z boson decays can still satisfy the selection criteria if they contain non-prompt leptons. The leading 4
XjY b means that X jets are found in the event, and among them Y are b-tagged.
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After the event selection, the samples in both the `` and the `+jets final states contain mostly tt¯ events. Events passing the event selection are categorised into separate regions according to the number of reconstructed jets and b-tagged jets. The regions where tbH + is enhanced relative to the backgrounds are referred to as signal regions (SRs), whereas the remaining regions are referred to as control regions (CRs). For the `+jets final state, two CRs (5j2b and ≥6j2b)4 and four SRs (5j3b, 5j≥4b, ≥6j3b and ≥6j≥4b) are defined, while in the `` final state, two CRs (3j2b and ≥4j2b) and two SRs (≥4j3b and ≥4j≥4b) are defined for all mass hypotheses. In addition, for the `` final state, the region with three b-tagged jets and no other jets (3j3b) is considered a SR for mH + < 1 TeV and a CR for mH + ≥ 1 TeV due to the change in expected signal yield for the different H + mass hypotheses. In the SRs, for each H + mass hypothesis a different discriminating variable based on boosted decision trees (BDTs) is defined. In order to separate the H + signal from the SM background, the binned output of this variable is used together with the total event yields in the CRs in a combined profile likelihood fit. The fit simultaneously determines both the signal and background yields, while constraining the overall background model within the assigned systematic uncertainties. The event yields in the CRs are used to constrain the background normalisation and systematic uncertainties. In the following subsections the background estimate and the design of the multivariate discriminator are described. The profile likelihood fit, including the treatment of backgrounds in the fit, is described in detail in section 7.
sources of non-prompt leptons in the `+jets final state are from semileptonic hadron decays or misidentified jets in multi-jet production. In the `` final state, the dominant source of non-prompt leptons is from misidentified jets as leptons arising from W +jets or `+jets tt¯ production. These backgrounds are estimated using data. For the `+jets final state a matrix method [98] is employed. An event sample that is enriched in non-prompt leptons is selected by using looser isolation or identification requirements for the lepton. These events are then weighted according to the efficiencies for both the prompt and non-prompt leptons to pass the tighter default selection. These efficiencies are measured using data in dedicated CRs. In the `` final state, this background is estimated from simulations, and the normalisation is determined by comparing data and simulations in a CR of same-sign dilepton events. The contribution of multi-jet events to the `` final state is found to be negligible. The expected event yields of all SM processes and the number of events observed in the data are shown in figure 2 for the `` and the `+jets final states before performing the fit to data. The expected H + signal yields for mH + = 200 GeV, assuming a cross-section times branching ratio of 1 pb, are also shown. 5.2
Multivariate analysis
The training of the BDTs that are used to discriminate signal from background in the SRs is performed with the TMVA toolkit [99]. BDTs are trained separately for each value of
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Figure 2. Comparison of predicted and observed event yields. Each background process is normalised according to its cross-section and the prediction has not been fitted to the data. The tt¯+ X includes contributions from tt¯W , tt¯Z and tt¯H. A signal with mH + = 200 GeV, normalised to a cross-section times branching ratio for H + → tb of 1 pb, is shown as a dashed line. The lower panel displays the ratio of the data to the total prediction. The hatched bands show uncertainties before the fit to the data, which are dominated by systematic uncertainties as discussed in section 6. The comparison is shown for all signal and control regions used in the analysis. For the `` final state: CR 3j2b, CR/SR 3j3b, CR ≥4j2b, SR ≥4j3b, SR ≥4j≥4b. For the `+jets final state: CR 5j2b, SR 5j3b, SR 5j≥4b, CR ≥6j2b, SR ≥6j3b, SR ≥6j≥4b.
• the mass of the semileptonically decaying top quark, mb` `ν , • the mass of the hadronically decaying W boson, mq1 q2 , • the difference between the masses of the hadronically decaying top quark and the hadronically decaying W boson mbh q1 q2 − mq1 q2 , and • the difference between the mass of the charged Higgs boson and the mass of the leptonically or hadronically decaying top quark, mbH + b` `ν − mb` `ν or mbH + bh q1 q2 − mbh q1 q2 , depending on whether the top quark from the charged Higgs boson decays leptonically or hadronically. In this context q1 or q2 refer to the quarks from the W boson decay, ` and ν to the lepton and neutrino from the other W boson decay, bh to the b-quark from the hadronic top quark decay, b` to the b-quark from the leptonic top quark decay and bH + to the b-quark directly from the H + decay. The probability Ptt¯(x) is constructed from probability density functions obtained from simulated tt¯ events. For the SRs with five jets, Ptt¯(x) is defined using the same invariant masses as above. The jet that does not originate from a top quark decay is used instead of bH + . For the SRs with at least six jets the power of the discriminant is improved by using the invariant mass of the two highest-pT jets not originating from the hadronisation of q1 , q2 , bh or b` instead of mbH + b` `ν − mb` `ν or mbH + bh q1 q2 − mbh q1 q2 . The functional form of the probability density functions is obtained from simulation using the reconstructed masses of jets and leptons matched to simulated partons and leptons for H + and tt¯. The neutrino four-momentum is derived with the assumption that the
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the 18 generated H + masses and for each SR against all the backgrounds (`+jets channel) or the tt¯ background (`` channel). For the BDT training in the `+jets channel, the SRs 5j3b and 5j≥4b are treated as one region, in order to increase the number of simulated events available for training. The BDT variables include various kinematic quantities with the optimal discrimination against the tt¯+ ≥1b background. For H + masses above 400 GeV the most important variables in the `+jets final state are the scalar sum of the pT of all jets, HTjets , and the leading jet pT . For a mass at or below 300 GeV, a kinematic discriminant, D, as described below, is used as an input variable for the BDT. The kinematic discriminant, D, and the invariant mass of the pair of jets that are not b-tagged and have the smallest ∆R are the most important variables in the low mass range. The latter variable is not used in the 5j≥4b SR, where it is not well defined. The kinematic discriminant, D, is a variable reflecting the probability that an event is compatible with the H + → tb and the tt¯ hypotheses, and is defined as D = PH + (x)/(PH + (x) + Ptt¯(x)), where PH + (x) and Ptt¯(x) are probability density functions for x under the signal hypothesis and background (tt¯) hypothesis, respectively. Here, the event variable x indicates the set of the missing transverse momentum and the four-momenta of reconstructed electrons, muons and jets. The probability PH + (x) is defined as the product of the probability density functions for each of the reconstructed invariant masses in the event:
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missing transverse momentum is solely due to the neutrino; the constraint m2W = (p` + pν )2 is used to obtain pν,z . If two real solutions exist, they are sorted according to the absolute value of their pz , i.e., |pz,v1 | < |pz,v2 |. In approximately 60% of the cases pz,v1 is closer than pz,v2 to the generator-level neutrino pz . Two different probability density functions are constructed, one for each solution, and the probability is defined as a weighted average of the two probability density functions. The weight is taken as the fraction of the corresponding solution being closer to the generated neutrino pz . Also, if no real solution exists, the px and py components are scaled by a common factor until the discriminant of the quadratic equation is exactly zero, yielding only one solution. When evaluating PH + (x) and Ptt¯(x) for the calculation of D, all possible parton-jet assignments are considered since the partonic origin of the jets is not known. In order to suppress the impact from parton-jet assignments that are inconsistent with the correct parton flavours, a weighted average over all parton-jet assignments is used. The value of PH + (x) and Ptt¯(x) for each parton-jet assignment is weighted with a probability based on the b-tagging discriminant value of each jet. The distribution of the step-wise efficiencies of the b-tagging algorithm, as described in section 4, is used as a probability density function, with the b-jet hypothesis for generated b-quarks and the light-jet hypothesis for other generated partons. Due to the large number of events in which q1 and q2 cannot be matched to different jets, the average of two different probability density functions, where either all partons can be matched to jets or only one jet can be matched to q1 and q2 , is used. This discriminant gives better background suppression than would be obtained by adding the kinematic input variables directly to the BDT. In the `` final state, approximately ten optimal kinematic variables from the analysis objects and their combinations were selected for each SR, independently for the low-mass region (mH + ≤ 600 GeV) and the high-mass region (mH + > 600 GeV). For the high-mass region, the most important variables are the scalar sum of the pT of all jets and leptons, HTall , and the transverse momentum of the jet pair with maximum pT . For the low-mass region, the smallest invariant mass formed by two b-tagged jets and the smallest invariant mass formed by a lepton and a b-tagged jet, are among the most important variables. All BDT input variables in the `+jets and `` final states are listed in the appendix. In most regions, the distributions show a reasonable level of agreement between simulation and data within the systematic and statistical uncertainties before the fit to the data (prefit). As examples, figures 3 and 4 show the distribution of the observed and pre-fit expected event yields for HTjets in the `+jets channel and HTall in the `` channel. Figure 5 shows the expected BDT output distributions, normalised to unity, for selected H + signal samples and the background processes in the SRs.
(b)
(c)
(d)
Figure 3. Distributions of the HTjets variable before the fit to the data in the four SRs of the `+jets channel: (a) 5j3b, (b) ≥6j3b, (c) 5j≥4b, (d) ≥6j≥4b. Each background process is normalised according to its cross-section and the normalisation of the tt¯+ ≥1b and tt¯+ ≥1c backgrounds corresponds to the prediction from Powheg+Pythia8 for the fraction of each of these components relative to the total tt¯ prediction. The tt¯ + X includes contributions from tt¯W , tt¯Z and tt¯H. In addition, the expectation for a 200 GeV signal is shown for a cross-section times branching ratio of 1 pb. The lower panels display the ratio of the data to the total prediction. The hatched bands show the pre-fit uncertainties. The level of agreement is improved post-fit due to the adjustment of the normalisation of the tt¯+ ≥1b and tt¯+ ≥1c backgrounds and the other nuisance parameters by the fit.
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(a)
(b)
(c)
Figure 4. Distributions of the HTall variable before the fit to the data in the three SRs of the `` channel: (a) 3j3b, (b) ≥4j3b and (c) ≥4j≥4b. Each background process is normalised according to its cross-section and the normalisation of the tt¯+ ≥1b and tt¯+ ≥1c backgrounds corresponds to the prediction from Powheg+Pythia8 for the fraction of each of these components relative to the total tt¯ prediction. The tt¯ + X includes contributions from tt¯W , tt¯Z and tt¯H. In addition, the expectation for a 200 GeV signal is shown for a cross-section times branching ratio of 1 pb. The lower panels display the ratio of the data to the total prediction. The hatched bands show the pre-fit uncertainties. The level of agreement is improved post-fit due to the adjustment of the normalisation of the tt¯+ ≥1b and tt¯+ ≥1c backgrounds and the other nuisance parameters by the fit.
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(a)
(b)
(c)
(d)
(e)
(f )
Figure 5. The expected output distributions of the BDTs employed for H + masses of 200 GeV and 800 GeV for SM backgrounds and H + signal in the three `+jets and the three `` SRs used in the BDT training: (a) `+jets final state, 5j≥3b, (b) `+jets final state, ≥6j3b, (c) `+jets final state, ≥6j≥4b, (d) `` final state, 3j3b, (e) `` final state, ≥4j3b and (f) `` final state, ≥4j≥4b. All distributions are normalised to unity.
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(a)
Type
Luminosity
N
1
Pile-up
NS
1
Electron reconstruction
NS
6
Muon reconstruction
NS
13
miss ET
NS
28
Flavour tagging, 70% efficiency calibration (*)
NS
27
Flavour tagging, step-wise efficiency calibration (*)
NS
126
Signal QCD scale and PDF Background modelling, tt¯ + jets
NS
31
NS
29
Background modelling, other top
NS
25
Background modelling, non-top (`+jets final state)
N
13
Background modelling, non-top (`` final state)
N
4
Jet and
reconstruction
Number of components
Table 2. List of systematic uncertainties considered. The details of the systematic uncertainties are described in section 6. ‘N’ indicates that the uncertainty is taken as normalisation-only for all processes and channels affected, while ‘NS’ means that the uncertainty applies to both normalisation and shape. The systematic uncertainties are split into several components for a more accurate treatment. Flavour-tagging uncertainties marked (*) are different for the two sets of calibrations: the step-wise efficiency calibration for mH + ≤ 300 GeV, and the 70% efficiency point calibration elsewhere.
6
Systematic uncertainties
Systematic uncertainties from various sources affect this search, such as uncertainties in the luminosity measurement, the reconstruction and calibration of physics objects, in particular b-tagged jets, and the modelling of the signal and background processes. Uncertainties can either modify the normalisation of the signal and background processes, change the shape of the final distributions, or both. The experimental uncertainties were obtained from dedicated analyses detailed in the corresponding references. The uncertainties related to this analysis are described in this section. For a precise treatment, the uncertainties are split into several components as explained in the following. The exact number of components for each category is listed in table 2. The most important uncertainties are related to jet flavour tagging, background modelling, jet energy scale and resolution and the limited number of events in the simulation samples. The impact of all systematic uncertainties is listed in table 5 in section 8. The combined uncertainty in the integrated luminosity for the data collected in 2015 and 2016 is 2.1%, and it is applied as a normalisation uncertainty for all processes estimated using simulation. It is derived, following a methodology similar to that detailed in ref. [100], from a preliminary calibration of the luminosity scale using x-y beam-separation scans performed in August 2015 and May 2016. A variation in the pile-up reweighting of MC
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Systematic uncertainty
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events is included to cover the uncertainty in the ratio of the predicted and measured inelastic cross-sections in the fiducial volume defined by MX > 13 GeV where MX is the mass of the hadronic system [101]. Uncertainties associated with charged leptons arise from the trigger selection, the object reconstruction, the identification, and the isolation criteria, as well as the lepton momentum scale and resolution. These are estimated by comparing Z → `+ `− (` = e, µ) events in data and simulation [85, 86]. Correction factors are applied to the simulation to better model the efficiencies observed in data. The charged-lepton uncertainties have a small impact on the analysis. Uncertainties associated with jets arise from the jet reconstruction and identification efficiencies related to the JES and jet energy resolution, and on the Jet Vertex Tagger efficiency [102]. The JES-related uncertainties contain 23 components that are treated as statistically independent and uncorrelatd. The JES and its uncertainty were derived by combining information from test-beam data, LHC collision data (in situ techniques) and simulation [89]. The many sources of uncertainties related to the in situ calibration using Z+jets, γ+jets and multi-jet data were reduced to eight uncorrelated components through an eigen-decomposition. Other components are relativ to jet flavour, pile-up corrections, η-dependence and high-pT jets. miss is used. The E miss calIn the reconstruction of quantities used for the BDT, ET T culation depends on the reconstruction of leptons and jets. The uncertainties associated miss uncertainty estimation. Uncerwith these objects are therefore propagated to the ET tainties due to soft objects (not included in the calculation of the leptons and jets) are also considered [96]. Differences between data and simulation in the b-tagging efficiency for b-jets, c-jets and light jets are taken into account using correction factors. For b-jets, the corrections are derived from tt¯ events with final states containing two leptons, and the corrections are consistent with unity within uncertainties at the level of a few percent over most of the jet pT range. The mis-tag rate for c-jets is also measured in tt¯ events, identifying hadronic decays of W bosons including c-jets. For light jets, the mis-tag rate is measured in multi-jet events using jets containing secondary vertices and tracks with impact parameters consistent with a negative lifetime. Systematic uncertainties affecting the correction factors are derived in the pT and η bins used for extracting the correction factors. They are transformed into uncorrelated components using an eigenvector decomposition, taking into account the bin-to-bin correlations [92, 93, 103]. For mH + > 300 GeV, corrections corresponding to the fixed working point of 70% efficiency are used and a total of 6, 3 and 16 independent uncorrelated eigen-variations are considered as systematic uncertainties for b-, c- and light jets, respectively. For mH + ≤ 300 GeV, corrections for the step-wise efficiencies are used to support the kinematic discriminant D and the number of eigen-variations is increased by a factor of five to account for the five b-tagging efficiency bins. In addition, uncertainties due to tagging the hadronic decays of τ -leptons as b-jets are considered. For mH + > 300 GeV, an additional uncertainty is included due to the extrapolation of scale factors for jets with pT > 300 GeV, beyond the kinematic reach of the data calibration samples used [93].
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The uncertainty due to different scale choices in the H + signal is estimated by varying the renormalisation and factorisation scales up and down by a factor of two. The uncertainty ranges from 7% at low masses to 15% at masses above 1300 GeV for the `+jets final state, and from 12% to 16.5% for the `` final state. The PDF uncertainty in the modelling is estimated using the PDF4LHC15 30 PDF set [104], which is based on a combination of the CT14 [105], MMHT14 [106] and NNPDF3.0 [44] PDF sets and contains 30 components obtained using the Hessian reduction method [107–109]. The modelling of the tt¯ + jets background is one of the largest sources of uncertainty in the analysis and many different components are considered. The uncertainty in the inclusive tt¯ production cross-section at NNLO+NNLL [47] is 6%, including effects from varying the factorisation and renormalisation scales, the PDF, the QCD coupling constant αs , and the top quark mass. Due to the large difference between the 4FS prediction and the various 5FS predictions for the tt¯+ ≥ 3b process, an additional 50% normalisation uncertainty is assigned to this background. The uncertainty due to the choice of NLO generator is derived by comparing the nominal Powheg sample with a sample generated using Sherpa 2.2.1 with a 5FS PDF. A Powheg sample with the same settings as in the nominal Powheg+Pythia8 sample, but using Herwig7 [79, 110] for parton showering, is used to assess the uncertainty due to the choice of parton shower and hadronisation model. Furthermore, the uncertainty due to the modelling of initial- and final-state radiation is evaluated with two different Powheg+Pythia8 samples in which the radiation is increased or decreased by halving or doubling the renormalisation and factorisation scales in addition to simultaneous changes to the hdamp parameter and the A14 tune parameters [111]. For the tt¯+ ≥ 1b background, an additional uncertainty is assigned by comparing the predictions from Powheg+Pythia8 and Sherpa with 4FS. This takes into account the difference between a 5FS inclusive tt¯ prediction at NLO and a 4FS NLO tt¯b¯b prediction. For the tt¯+ ≥1c background, an additional uncertainty is derived by comparing a MG5 aMC sample that is interfaced to Herwig++ [79] with the nominal event sample. In this MG5 aMC event sample, a three-flavour scheme is employed and the tt¯c¯ c process is generated at the matrix element level [112] using the CT10F3 PDF set, while in the nominal sample the charm jets are primarily produced in the parton shower. All of these uncertainties, with the exception of the inclusive and tt¯+ ≥3b cross-sections, are considered to be uncorrelated amongst the tt¯+ ≥1b, tt¯+ ≥1c, and tt¯ + light samples. For the modelling of the tt¯+ ≥1b backgrounds, the alternative samples are reweighted to the NLO prediction of tt¯b¯b from Sherpa before the uncertainty is evaluated. In addition, uncertainties due to the reweighting to the Sherpa NLO prediction of tt¯b¯b are considered. For these uncertainties, the tt¯+ ≥1b is reweighted to different Sherpa predictions with modified scale parameters, in particular where the renormalisation scale is varied up and down by a factor of two, where the functional form of the resummation scale is changed to µCMMPS and where a global scale choice µq = µr = µf = µCMMPS is used. Two alternative PDF sets, MSTW2008NLO [84] and NNPDF2.3NLO [44], are used, and uncertainties in the underlying event and parton shower are estimated from samples with an alternative set of tuned parameters for the underlying event and an alternative shower
recoil scheme. Due to the absence of b-jets from multi-parton interactions and final-state gluon radiation in the tt¯b¯b prediction from Sherpa, a 50% uncertainty is assigned to the tt¯ + b (MPI/FSR) category based on studies of different sets of UE tunes. An uncertainty due to the reweighting of the leading jet pT is determined by comparing a reweighted event sample with an event sample without reweighting. Because the reweighting changes the normalisation for jet pT > 400 GeV by 15%, an additional normalisation uncertainty of 15% is applied in this region. The reweighting factors are derived from the CR with exactly four jets and at least two b-tagged jets and applied to higher jet multiplicity bins. However, the effect of this extrapolation is expected to be small and is covered by the above uncertainties.
The tt¯H modelling uncertainty is assessed through an uncertainty in the cross-section, uncorrelated between QCD (+5.8 −9.2 %) and the PDFs (±3.6%) [15, 117–121], and the modelling of the parton shower and hadronisation by comparing Pythia8 with Herwig++. The minor tH + X backgrounds, tHjb and W tH are treated as one background and its cross-section uncertainty is 6% due to PDF uncertainties and another 10% due to factorisation and renormalisation scale uncertainties [15]. The uncertainties from the data-driven estimation of non-prompt leptons are based on a comparison between data and the non-prompt lepton estimates in CRs. A 50% uncertainty is assigned in the `+jets final state. In the `` final state, where all backgrounds with one or no prompt leptons fall into this category, including W +jets and single top production, an uncertainty of 25% is assigned. An uncertainty of 40% is assumed for the W +jets cross-section, uncorrelated between jet bins, with an additional 30% for W +HF jets, uncorrelated for two, three and more than three HF jets. These uncertainties are derived from variations of the renormalisation and factorisation scales and matching parameters in Sherpa simulations. An uncertainty in Z+jets of 35% is applied, uncorrelated among jet bins in the `` final state. This uncertainty accounts for both the variation of the scales and matching parameters in Sherpa simulations and the data-driven correction factors applied to the Z+HF jets component. In the `` final state, only the Z+jets component is estimated separately, and the W +jets background is included in the estimation of the background from non-prompt leptons.
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An uncertainty of 5% is assigned to the total cross-section for single top-quark production [66–68], uncorrelated between W t and t-channel production. An additional uncertainty due to initial- and final-state radiation is estimated using samples with factorisation and renormalisation scale variations and appropriate variations of the Perugia 2012 set of tuned parameters. The parton showering and hadronisation modelling uncertainties in the single-top W t and t-channel production are estimated by comparing with samples where the parton shower generator is Herwig++ instead of Pythia 6.428. The uncertainty in the interference between W t and tt¯ production at NLO [62] is assessed by comparing the default ‘diagram removal’ scheme with an alternative ‘diagram subtraction’ scheme [62, 113]. The uncertainty arising from tt¯V generation is estimated by comparison with samples generated with Sherpa. The uncertainty in the tt¯V production cross-section is about 15%, taken from the NLO predictions [15, 114–116], treated as uncorrelated between tt¯W and tt¯Z with PDF and QCD scale variations.
7
Statistical analysis
The values of the signal strength and nuisance parameters that maximise the likelihood ˆ respectively. For a given value of µ, the values of the function are represented by µ ˆ and θ, ˆˆ nuisance parameters that maximise the likelihood function are represented by θ(µ).
8
Results
Tables 3 and 4 show the post-fit event yields under the background-plus-signal hypothesis for a signal mass mH + = 200 GeV. A value of σ(pp → tbH + ) × B(H + → tb) = −0.36 pb is obtained from the fit. The corresponding post-fit distributions of the BDT discriminant in the SRs are shown in figures 6 and 7 for a 200 GeV H + mass hypotheses for the `+jets and `` final state, respectively. A summary of the systematic uncertainties is given in table 5. Depending on the particular H + mass hypothesis, the total systematic uncertainty is dominated by the uncertainties in the modelling of the tt¯+ ≥1b background, the jet flavour-tagging uncertainties and the uncertainties due to the limited size of simulated event samples. The 95% confidence level (CL) upper limits on σ(pp → tbH + ) × B(H + → tb) using the CLs method are presented in figure 8. The observed (expected) 95% CL upper limits
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In order to test for the presence of an H + signal, a binned maximum-likelihood fit to the data is performed simultaneously in all categories, and each mass hypothesis is tested separately. The inputs to the fit include the number of events in the CRs and the binned BDT output in the SRs. Two initially unconstrained fit parameters are used to model the normalisation of the tt¯+ ≥1b and tt¯+ ≥1c backgrounds. The procedures used to quantify the level of agreement with the background-only or background-plus-signal hypothesis and to determine exclusion limits are based on the profile likelihood ratio test and the CL s method [122–124]. The parameter of interest is the signal strength, µ, defined as the product of the production cross-section σ(pp → tbH + ) and the branching ratio B(H + → tb). To estimate the signal strength, a likelihood function, L(µ, θ), is constructed as the product of Poisson probability terms. One Poisson term is included for every CR and every bin of the BDT distribution in the SRs. The expected number of events in the Poisson terms is a function of µ, and a set of nuisance parameters, θ. The nuisance parameters encode effects from the normalisation of backgrounds, including two free normalisation factors for the tt¯+ ≥1b and tt¯+ ≥1c backgrounds, the systematic uncertainties and one parameter per bin to model statistical uncertainties in the simulated samples. All nuisance parameters are constrained with Gaussian or log-normal terms. There are about 170 nuisance parameters considered in the fit, the number varying slightly across the range of mass hypotheses. To extract the exclusion limit on µ = σ(pp → tbH + ) × B(H + → tb), the following test statistic is used: ˆ ˆ L µ,θ(µ) ˆ < 0, −2 ln ˆˆ µ L 0,θ(0) t˜µ = ˆ ˆ −2 ln L µ,θ(µ) µ ˆ ≥ 0. L( µ ˆ,θˆ)
(b)
(c)
(d)
Figure 6. Distributions of the BDT output after the fit to the data in the four SRs of the `+jets final state: (a) 5j3b, (b) ≥6j3b, (c) 5j≥4b and (d) ≥6j≥4b for the 200 GeV mass hypothesis. Each background process is normalised according to its post-fit cross-section. The tt¯ + X includes contributions from tt¯W , tt¯Z and tt¯H. The total prediction of the BDT distributions includes cases where the signal obtained from the fit is negative. For this particular mass point the fitted signal strength is µ = −0.4±1.5 pb. The pre-fit signal distribution is shown superimposed as a dashed line with arbitrary normalisation. The lower panels display the ratio of the data to the total prediction. The hatched bands show the post-fit uncertainties.
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(a)
(b)
(c)
Figure 7. Distributions of the BDT output after the fit to the data in the three SRs of the `` final state: (a) 3j3b, (b) ≥4j3b and (c) ≥4j≥4b for the 200 GeV mass hypothesis. Each background process is normalised according to its post-fit cross-section. The tt¯ + X includes contributions from tt¯W , tt¯Z and tt¯H. The total prediction of the BDT distributions includes cases where the signal obtained from the fit is negative. For this particular mass point the fitted signal strength is µ = −0.4 ± 1.5 pb. The pre-fit signal distribution is shown superimposed as a dashed line with arbitrary normalisation. The lower panels display the ratio of the data to the total prediction. The hatched bands show the post-fit uncertainties.
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(a)
Process tt¯+≥1b tt¯+≥1c tt¯ + light
CR 5j2b
Single top W t Other top
SR 5j≥4b
15 300±2300
7400±1000 750±110
47 000±12 000
6400±1700 260±80
226 000±11 000 12 200±1100
Non-prompt leptons 15 000±6000 tt¯W tt¯Z
SR 5j3b
CR ≥6j2b 17100±2800
SR ≥6j3b
SR ≥6j≥4b
11 100±1500 2410±260
55 000±11 000
9400±2000 450±180
89±35
132 000±10 000
8500±1100 260±120
600±500
11±8
13 000±6000
700±400
4±5
340±50
29±4
0.66±0.22
540±80
72±11
5.0±1.2
390±50
78±10
12.2±2.2
720±90
183±23
50±7
8900±2400
690±210
23±13
5400±1800
640±260
53±31
328±27
28.2±2.6
3.1±0.6
183±20
46±11
14±5
410±210
29±15
2.0±2.1
340±170
37±19
4.3±2.5
9000±4000
540±240
16±9
5200±2100
470±200
27±12
Z + jets tt¯H
2100±600
104±35
4.9±1.8
1300±400
130±40
11±4
252±24
127±13
30±4
520±50
315±32
117±16
tH
19.5±2.4
10.6±1.3
2.21±0.32
27.2±3.5
15.7±2.0
5.0±0.7
Total
328 000±7000
28 400±900 1220±60
233 000±6000
31 800±800 3410±150
Data
334 813
29 322
234 053
32 151
H + (200 GeV) H
+
(800 GeV)
1210
3459
470±50
220±23
25.3±3.3
340±50
235±34
60±9
630±90
390±70
56±12
1230±190
1020±170
350±70
Table 3. Event yields of the SM background processes and data in all categories of the `+jets final state, after the fit to the data under the background-plus-signal hypothesis (mH + = 200 GeV). The expected event yields for the H + signal masses of 200 GeV and 800 GeV are shown with pre-fit uncertainties and assuming a cross-section times branching ratio of 1 pb. The quoted uncertainties include both the statistical and systematic components. The uncertainties take into account correlations and constraints of the nuisance parameters. ‘Other top’ includes contributions from Zt as well as s- and t-channel single top production.
on the pp → tbH + production cross-section times the branching ratio B(H + → tb) range from σ × B = 2.9 (3.0) pb at mH + = 200 GeV to σ × B = 0.070 (0.077) pb at mH + = 2 TeV. The compatibility of the SM hypothesis with the results obtained from the fit to the data is tested. The largest deviation from the SM hypothesis is observed at 300 GeV. Given that a negative µ ˆ is observed under this mass hypothesis, the test statistic t0 = ˆ ˆ ˆ −2 ln (L(0, θ(0))/L(ˆ µ, θ)) is used to quantify the deviation of the fitted result from the SM expectation. A local p0 value of 1.13% is obtained at 300 GeV, corresponding to the probability to obtain a deviation at least as large as the one observed in data provided that only SM processes are present. Figure 9 shows 95% CL exclusion limits set on tanβ for the mmod− scenario of the h MSSM [14, 15, 28] and the hMSSM [29, 125, 126]. Beyond tree level, the Higgs sector is affected by the choice of parameters in addition to Higgs boson masses and tanβ. For the mmod− benchmark scenario the top-squark mixing parameter is chosen such that the h mass of the lightest CP-even Higgs boson, mh , is close to the measured mass of the Higgs boson that was discovered at the LHC. In the hMSSM scenario, instead of adjusting the parameters of soft supersymmetry breaking, the value of mh is used to predict the masses and couplings of the MSSM Higgs bosons.
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Diboson W + jets
Process
CR 3j2b
SR/CR 3j3b
CR ≥4j2b
SR ≥4j3b
SR ≥4j≥4b
tt¯+ ≥1b tt¯+ ≥1c
2330 ± 330
940 ± 130
3300 ± 500
2050 ± 280
322 ± 35
6100 ± 1300
520 ± 140
9900 ± 2000
1310 ± 290
30 ± 14
32 500 ± 2100
420 ± 120
4±5
48 ± 13
2.2 ± 0.8
tt¯ + light
50 700 ± 2300
260 ± 70 6.7 ± 2.4
48 ± 7
1.48 ± 0.17
129 ± 7
9.8 ± 1.1
0.55 ± 0.21
43 ± 5
5.8 ± 1.1
174 ± 10
32.9 ± 2.0
7.0 ± 1.3
1700 ± 500
40 ± 12
1110 ± 330
63 ± 26
3.9 ± 2.0
Other top
3.9 ± 0.5
0.12 ± 0.05
21.8 ± 3.5
5.8 ± 2.2
2.0 ± 0.9
Diboson
36 ± 4
1.2 ± 0.4
46 ± 6
3.1 ± 0.9
0.48 ± 0.28
Z + jets tt¯H
1600 ± 500
42 ± 16
1300 ± 400
82 ± 29
5.3 ± 2.0
26.2 ± 1.3
8.5 ± 0.5
116 ± 6
52.2 ± 3.5
16.0 ± 1.9
tH
1.95 ± 0.27
0.42 ± 0.10
5.7 ± 0.7
2.14 ± 0.32
0.48 ± 0.09
62 800 ± 2800
1810 ± 110
4060 ± 200
390 ± 28
tt¯Z Single top W t
Total Data
62 399
620 ± 160
49 300 ± 2300
1774
48 356
4047
376
H
+
(200 GeV)
92 ± 12
27 ± 4
72 ± 12
49 ± 8
9.0 ± 1.6
H
+
(800 GeV)
70 ± 12
32 ± 7
212 ± 33
157 ± 27
44 ± 9
σ(pp → tbH±) × B(H±→ tb) [pb]
Table 4. Event yields of the SM background processes and data in all categories of the `` final state, after the fit to the data under the background-plus-signal hypothesis (mH + = 200 GeV). The expected event yields for the H + signal masses of 200 GeV and 800 GeV are shown with pre-fit uncertainties and assuming a cross-section times branching ratio of 1 pb. The quoted uncertainties include both the statistical and systematic components. The uncertainties take into account correlations and constraints of the nuisance parameters. ‘Other top’ includes contributions from Zt as well as s- and t-channel single top production. 10 ATLAS s=13 TeV, 36.1 fb-1
95% observed limit (CL ) s
95% expected limit (CL s ) Expected ± 1σ Expected ± 2σ mmodtanβ = 0.5 h
1
mmodtanβ = 1 h mmodtanβ = 60 h
10−1
200 400 600 800 1000 1200 1400 1600 1800 2000 mH+ [GeV]
Figure 8. Expected and observed limits for the production of H + → tb in association with a top quark and a bottom quark. The bands surrounding the expected limit show the 68% and 95% confidence intervals. The limits are based on the combination of the `+jets and `` final states. Theory predictions are shown for three representative values of tanβ in the mmod− benchmark scenario [28]. h Uncertainties in the predicted H + cross-sections or branching ratios are not considered.
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420 ± 110
Non-prompt leptons tt¯W
Uncertainty Source
+ ∆µ(H200 ) [pb]
+ ∆µ(H800 ) [pb]
Jet flavour tagging tt¯+ ≥1b modelling
0.70
0.050
0.65
0.008
0.44
0.031
0.44
0.019
Jet energy scale and resolution tt¯+light modelling
0.37
0.044
0.36
0.032
Other background modelling
0.36
0.039
Luminosity
0.24
0.010
Jet-vertex assoc., pile-up modelling
0.10
0.006
miss , ID, isol., trigger Lepton, ET
0.08
0.003
H+
0.03
0.006
Total systematic uncertainty tt¯+ ≥1b normalisation
1.4
0.11
0.61
0.022
tt¯+ ≥1c normalisation
0.28
0.012
Total statistical uncertainty
0.69
0.050
Total uncertainty
1.5
0.12
modelling
Table 5. The summary of the effects of the systematic uncertainties on the signal strength parameter, µ = σ(pp → tbH + ) × B(H + → tb), for the combination of the `+jets and `` final states is shown for an H + signal with a mass of 200 and 800 GeV. Due to correlations between the different sources of uncertainty, the total systematic uncertainty can be different from the sum in quadrature of the individual sources. The normalisation factors for both tt¯+ ≥1b and tt¯+ ≥1c are included in the statistical component. The total uncertainty corresponds to a best-fit value of µ of −0.4 pb at mH + = 200 GeV and −0.02 pb at mH + = 800 GeV. The expected upper limit on µ is 3.05 pb at mH + = 200 GeV and 0.26 pb at mH + = 800 GeV.
For H + masses of 200–920 GeV (200–965 GeV), the observed exclusion of low values of tanβ at 95% CL is in the range 0.5–1.91 (0.5–1.95) for the mmod− (hMSSM) scenario. The h + most stringent limits on tanβ are set for H masses around 250 GeV. High values of tanβ between 36 and 60 are excluded in the H + mass range 200–520 GeV (220–540 GeV) for the mmod− (hMSSM) scenario. The most stringent exclusion, tanβ > 36, is at 300 GeV for h both the mmod− and hMSSM benchmark scenarios. In the mmod− scenario for tanβ = 0.5, h h + the observed (expected) exclusion of H masses is mH + < 920 GeV (mH + < 930 GeV). In comparison with a previous search for t[b]H + production followed by H + → tb decays [20], more stringent limits on H + masses for particular models and parameter choices can be set. The analysis reach is increased and now also includes H + masses between 600 GeV and 2 TeV. The excluded region of parameter space for the modeldependent interpretation is extended significantly for low tanβ and an additional excluded region is added at high tanβ.
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MC statistics tt¯+ ≥1c modelling
10
tanβ
tanβ
40 30 20
ATLAS tbH+, H+→ tb mmodh s = 13 TeV 36.1 fb-1
40 30 20
95% obs. excl. (CLs)
10
95% exp. excl. (CLs) Expected ± 1σ
95% obs. excl. (CLs)
tbH+, H+→ tb hMSSM s = 13 TeV 36.1 fb-1
95% exp. excl. (CLs) Expected ± 1σ
3 2
Expected ± 2σ
1
Expected ± 2σ
1
0.6 200 300 400 500 600 700 800 900 1000
0.6 200 300 400 500 600 700 800 900 1000
mH+ [GeV] (a)
mH+ [GeV] (b)
Figure 9. Expected and observed limits on tanβ as a function of mH + in the mmod− [28] (left) and h the hMSSM [29] (right) scenarios of the MSSM. Limits are shown for tanβ values in the range of 0.5–60, where predictions are available from both scenarios. The bands surrounding the expected limits show the 68% and 95% confidence intervals. The limits are based on the combination of the `+jets and `` final states. The production cross-section of tt¯H and tH, as well as the branching ratios of the H, are fixed to their SM values at each point in the plane. Uncertainties in the predicted H + cross-sections or branching ratios are not considered.
The ATLAS Collaboration has also set limits on the production of H + using the → τ ν decay with the same data [30]. The τ ν final state can be used to set limits at high tanβ which are more stringent than those from the tb final state, and to probe H + masses below 200 GeV, in both the mmod− and hMSSM scenarios. Figure 10 shows h a superposition of the limits from the two final states, where the limits from the τ ν final state exclude a larger portion of the parameter space at high tanβ and low H + masses than the tb limits alone. H+
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3 2
ATLAS
tanβ
tanβ
40 30 20 10
95% CLs exclusions
10
ATLAS 95% CLs exclusions
H+→ τν,tb hMSSM s = 13 TeV 36.1 fb-1
Observed, τν Expected, τν
3 2
Observed, tb Expected, tb
1
Observed, τν Expected, τν Observed, tb Expected, tb
1
0.6
0.6 200 400 600 800 1000 1200 1400
200
400
600
mH [GeV] (a)
800 1000 1200 1400 mH+ [GeV]
+
(b)
Figure 10. Expected and observed limits on tanβ as a function of mH + in the mmod− [28] (left) h and the hMSSM [29] (right) scenarios of the MSSM. Limits are shown for tanβ values in the range of 0.5–60, where predictions are available from both scenarios. The limits are a superposition of the results obtained in the analysis presented here, and the ATLAS limits derived from the H + → τ ν decay [30]. The expected limits from the τ ν final state are shown as the horizontally hatched area, with the observed limit as a dash-dotted curve. The expected limits from the tb final state are shown as diagonally hatched areas, with the observed limit as dashed lines. At low tanβ, the strongest limits are from the tb final state, whereas the exclusions at high tanβ and low H + masses are obtained from the τ ν final state. The exclusion limits for the hMSSM scenario are shown only for mH + > 150 GeV, where the corresponding theoretical predictions are available.
9
Conclusions
A search for charged Higgs bosons is performed using a data sample corresponding to √ an integrated luminosity of 36.1 fb−1 from pp collisions at s = 13 TeV, recorded by the ATLAS detector at the LHC. The search for pp → tbH + is performed in the H + mass range 200–2000 GeV. The analysis uses multivariate techniques in the signal regions to enhance the separation of signal from background and utilises control regions to reduce the effect of large uncertainties in background predictions. No significant excess above the expected SM background is found and observed (expected) 95% CL upper limits are set on the pp → tbH + production cross-section times the branching ratio B(H + → tb), which range from σ × B = 2.9 (3.0) pb at mH + = 200 GeV to σ × B = 0.070 (0.077) pb at mH + = 2 TeV. In the context of the mmod− (hMSSM) scenario of the MSSM, some values of tanβ, in h the range 0.5–1.91 (0.5–1.95), are excluded for H + masses of 200–920 (200–965) GeV. For H + masses between 200 and 520 GeV (220 and 540 GeV), high values of tanβ are excluded, e.g. tanβ > 36 is excluded at 300 GeV.
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3 2
H+→ τν,tb mmodh s = 13 TeV 36.1 fb-1
ATLAS
40 30 20
Additionally, taking into consideration the H + → τ ν decay, even stricter exclusions can be made at high tanβ and low H + masses. In the context of the hMSSM, the H + mass range up to 1100 GeV is excluded at tanβ = 60, and all tanβ values are excluded for mH + below 160 GeV.
Acknowledgments
A
BDT input variables
In this appendix, the full list of variables used as inputs to the BDTs, described in section 5, is reported.
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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-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; MNE/IFA, Romania; MES of Russia and NRC KI, Russian Federation; JINR; ˇ Slovenia; DST/NRF, South Africa; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZS, MINECO, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, CANARIE, CRC and Compute Canada, Canada; COST, ERC, ERDF, Horizon 2020, and Marie Sklodowska-Curie Actions, European Union; Investissements d’ Avenir Labex and Idex, ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and GIF, Israel; CERCA Programme Generalitat de Catalunya, Spain; The Royal Society and Leverhulme Trust, United Kingdom. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (U.K.) and BNL (U.S.A.), the Tier-2 facilities worldwide and large non-WLCG resource providers. Major contributors of computing resources are listed in ref. [127].
`+jets channel pT (j1 )
Leading jet transverse momentum
min
m(b-pair∆R ) pT (j5 ) H2 ∆Ravg (b-pair) ∆R(`, b-pair∆R m(u-pair jets HT
min
∆Rmin
Invariant mass of pair of b-tagged jets with smallest ∆R Transverse momentum of fifth jet Second Fox-Wolfram moment [128] calculated using all jets and leptons Average ∆R between all b-tagged jet pairs in the event )
)
max
m(b-pairpT ) mmax (b-pair) mmax (j-triplet) D
∆R between the lepton and the b-tagged jet pair with smallest ∆R Invariant mass of the non-b-tagged jet-pair with minimum ∆R Scalar sum of all jets transverse momenta Invariant mass of the b-tagged jet pair with maximum transverse momentum Largest invariant mass of any two b-tagged jets Largest invariant mass of any three jets Kinematic discriminant based on mass templates (for mH + ≤ 300 GeV)
`` channel, m ≤ 600 GeV
pT ((`, b)∆η
max
)
min
m((`, b)∆φ ) miss ∆E(b1 , `1 + ET ) ∆m(j2 + j3 , j1 + `1 + `2 ) miss ∆m(`1 + j3 + ET , j 1 + j2 + `2 ) ∆pT (j1 , j3 ) min m (b-pair) mmin (`, b) miss pT (b2 + `1 + `2 + ET ) miss ∆R(`2 , j2 + j3 + `1 + ET ) all HT
3j3b ≥4j3b ≥4j≥4b Inv. mass of the jet and b-tagged jet with largest pT Energy difference between the third jet and the subleading lepton Energy of third jet miss Inv. mass difference between j1 + j2 and j1 + j3 + `2 + ET miss Angular difference between subleading jet and j1 + `2 + ET pT of leading b-tagged jet
X X X X X X
pT of the pair of lepton and b-tagged jet with largest ∆η
X
Inv. mass of the pair of lepton and b-tagged jet with smallest ∆φ miss Energy difference between the leading b-tagged jet and `1 + ET Inv. mass difference between j2 + j3 and j1 + `1 + `2 miss Inv. mass difference between `1 + j3 + ET and j1 + j2 + `2 pT difference between leading and third jet Smallest invariant mass of any b-tagged jet pair Smallest invariant mass of any pair of lepton and b-tagged jet miss pT of b2 + `1 + `2 + ET miss Angular difference between `2 and j2 + j3 + `1 + ET Scalar sum of all jets and leptons transverse energy
min
pT ((`, b)∆R
min
)
pT of the pair of lepton and b-tagged jet with smallest ∆η pT difference between leading and third jets miss Inv. mass difference between j2 + `1 + ET and j1 + j3 + `1
X X X
pT of the pair of lepton and b-tagged jet with smallest ∆R
X
m(j-pair ) miss ∆pT (j1 , j2 + ET ) pT (j1 + j2 + j3 + `1 ) miss ∆E(`1 + ET , j 1 + j2 ) E(j1 ) max pT (j-pair) miss m(b1 + b2 + `1 + `2 + ET )
Inv. mass of the jet pair with smallest ∆η miss pT difference between leading jet and j2 + ET pT of j1 + j2 + j3 + `1 miss Energy difference between `1 + ET and j1 + j2 Energy of the leading jet Maximum pT of any jet pair miss Inv. mass of b1 + b2 + `1 + `2 + ET
X X X X X X
pT ((`, b)∆η ) miss ∆pT (`2 , u1 + b2 + ET ) miss ∆pT (`2 , u1 + b1 + ET ) miss ∆pT (`2 , `1 + ET ) miss ∆pT (j1 , j3 + `1 + ET ) miss ∆E(`1 , j2 + ET ) mmin (b-pair) all HT pT (j3 + `1 ) ∆pT (b2 , b1 + `2 ) miss ∆pT (j2 , j3 + `1 + ET ) miss ∆E(j3 , j2 + `1 + `2 + ET ) miss miss ∆m(j2 + `2 + ET , j 1 + `2 + E T )
pT of the lepton-b-jet pair with smallest separation in η miss pT difference between subleading lepton and u1 + b2 + ET miss pT difference between subleading lepton and u1 + b1 + ET miss pT difference between subleading lepton and `1 + ET miss pT difference between leading jet and j3 + `1 + ET miss Energy difference between leading lepton and j2 + ET Smallest invariant mass of any b-tagged jet pair Scalar sum of all jets and leptons transverse momenta pT of j3 + `1 pT difference between subleading b-tagged jet and b1 + `2 miss pT difference between subleading jet and j3 + `1 + ET miss Energy difference between third jet and j2 + `1 + `2 + ET miss miss Inv. mass difference between j2 + `2 + ET and j1 + `2 + ET
∆η min
min
X X X X X X
3j3b ≥4j3b ≥4j≥4b
`` channel, m > 600 GeV pT ((`, b)∆η ) ∆pT (j1 , j3 ) miss ∆m(j2 + `1 + ET , j 1 + j3 + `1 )
X X X X X X X
X X
X X X X X X X X X X
X X X X X X X
Table 6. Input variables to the classification BDT in the `+jets and `` channels. The symbols j, b, miss u, ` and ET represent the four-momenta of jets, b-tagged jets, non-b-tagged jets, the lepton and the missing transverse momentum. All numbered indices refer to ordering in transverse momentum, with 1 as leading. The SRs where the variables are used are indicated for the `` channel. In the `+jets channels the variables are used for all channels. In the `+jets channel the discriminant, D, is only used for charged Higgs boson masses mH + ≤ 300 GeV. For the `` channel a very large set of kinematic variables using combinations of the analysis objects was examined, and approximately ten optimal variables were selected for each SR independently for the low-mass region (mH + ≤ 600 GeV) and the high-mass region (mH + > 600 GeV).
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max
m((j, b)pT ) ∆E(j3 , `2 ) E(j3 ) miss ∆m(j1 + j2 , j1 + j3 + `2 + ET ) miss ∆R(j2 , j1 + `2 + ET ) pT (b1 )
Open Access. This article is distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits any use, distribution and reproduction in any medium, provided the original author(s) and source are credited.
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C. Bini70a,70b , S. Biondi23b,23a , M. Birman177 , T. Bisanz51 , J.P. Biswal158 , C. Bittrich46 , D.M. Bjergaard47 , J.E. Black150 , K.M. Black25 , T. Blazek28a , I. Bloch44 , C. Blocker26 , A. Blue55 , U. Blumenschein90 , Dr. Blunier144a , G.J. Bobbink118 , V.S. Bobrovnikov120b,120a , S.S. Bocchetta94 , A. Bocci47 , D. Boerner179 , D. Bogavac112 , A.G. Bogdanchikov120b,120a , C. Bohm43a , V. Boisvert91 , P. Bokan169,51 , T. Bold81a , A.S. Boldyrev111 , A.E. Bolz59b , M. Bomben132 , M. Bona90 , J.S. Bonilla127 , M. Boonekamp142 , A. Borisov140 , G. Borissov87 , J. Bortfeldt35 , D. Bortoletto131 , V. Bortolotto71a,61b,61c,71b , D. Boscherini23b , M. Bosman14 , J.D. Bossio Sola30 , K. Bouaouda34a , J. Boudreau135 , E.V. Bouhova-Thacker87 , D. Boumediene37 , C. Bourdarios128 , S.K. Boutle55 , A. Boveia122 , J. Boyd35 , I.R. Boyko77 , A.J. Bozson91 , J. Bracinik21 , N. Brahimi99 , A. Brandt8 , G. Brandt179 , O. Brandt59a , F. Braren44 , U. Bratzler161 , B. Brau100 , J.E. Brau127 , W.D. Breaden Madden55 , K. Brendlinger44 , A.J. Brennan102 , L. Brenner44 , R. Brenner169 , S. Bressler177 , B. Brickwedde97 , D.L. Briglin21 , D. Britton55 , D. Britzger59b , I. Brock24 , R. Brock104 , G. Brooijmans38 , T. Brooks91 , W.K. Brooks144b , E. Brost119 , J.H Broughton21 , P.A. Bruckman de Renstrom82 , D. Bruncko28b , A. Bruni23b , G. Bruni23b , L.S. Bruni118 , S. Bruno71a,71b , B.H. Brunt31 , M. Bruschi23b , N. Bruscino135 , P. Bryant36 , L. Bryngemark44 , T. Buanes17 , Q. Buat35 , P. Buchholz148 , A.G. Buckley55 , I.A. Budagov77 , F. Buehrer50 , M.K. Bugge130 , O. Bulekov110 , D. Bullock8 , T.J. Burch119 , S. Burdin88 , C.D. Burgard118 , A.M. Burger5 , B. Burghgrave119 , K. Burka82 , S. Burke141 , I. Burmeister45 , J.T.P. Burr131 , D. B¨ uscher50 , V. B¨ uscher97 , E. Buschmann51 , P. Bussey55 , J.M. Butler25 , C.M. Buttar55 , 92 J.M. Butterworth , P. Butti35 , W. Buttinger35 , A. Buzatu155 , A.R. Buzykaev120b,120a , G. Cabras23b,23a , S. Cabrera Urb´an171 , D. Caforio138 , H. Cai170 , V.M.M. Cairo2 , O. Cakir4a , N. Calace52 , P. Calafiura18 , A. Calandri99 , G. Calderini132 , P. Calfayan63 , G. Callea40b,40a , L.P. Caloba78b , S. Calvente Lopez96 , D. Calvet37 , S. Calvet37 , T.P. Calvet152 , M. Calvetti69a,69b , R. Camacho Toro132 , S. Camarda35 , P. Camarri71a,71b , D. Cameron130 , R. Caminal Armadans100 , C. Camincher35 , S. Campana35 , M. Campanelli92 , A. Camplani39 , A. Campoverde148 , V. Canale67a,67b , M. Cano Bret58c , J. Cantero125 , T. Cao158 , Y. Cao170 , M.D.M. Capeans Garrido35 , I. Caprini27b , M. Caprini27b , M. Capua40b,40a , R.M. Carbone38 , R. Cardarelli71a , F.C. Cardillo50 , I. Carli139 , T. Carli35 , G. Carlino67a , B.T. Carlson135 , L. Carminati66a,66b , R.M.D. Carney43a,43b , S. Caron117 , E. Carquin144b , S. Carr´a66a,66b , G.D. Carrillo-Montoya35 , D. Casadei32b , M.P. Casado14,f , A.F. Casha164 , M. Casolino14 , D.W. Casper168 , R. Castelijn118 , F.L. Castillo171 , V. Castillo Gimenez171 , N.F. Castro136a,136e , A. Catinaccio35 , J.R. Catmore130 , A. Cattai35 , J. Caudron24 , V. Cavaliere29 , E. Cavallaro14 , D. Cavalli66a , M. Cavalli-Sforza14 , V. Cavasinni69a,69b , E. Celebi12b , F. Ceradini72a,72b , L. Cerda Alberich171 , A.S. Cerqueira78a , A. Cerri153 , L. Cerrito71a,71b , F. Cerutti18 , A. Cervelli23b,23a , S.A. Cetin12b , A. Chafaq34a , D Chakraborty119 , S.K. Chan57 , W.S. Chan118 , Y.L. Chan61a , J.D. Chapman31 , D.G. Charlton21 , C.C. Chau33 , C.A. Chavez Barajas153 , S. Che122 , A. Chegwidden104 , S. Chekanov6 , S.V. Chekulaev165a , G.A. Chelkov77,ar , M.A. Chelstowska35 , C. Chen58a , C.H. Chen76 , H. Chen29 , J. Chen58a , J. Chen38 , S. Chen133 , S.J. Chen15c , X. Chen15b,aq , Y. Chen80 , Y-H. Chen44 , H.C. Cheng103 , H.J. Cheng15d , A. Cheplakov77 , E. Cheremushkina140 , R. Cherkaoui El Moursli34e , E. Cheu7 , K. Cheung62 , L. Chevalier142 , V. Chiarella49 , G. Chiarelli69a , G. Chiodini65a , A.S. Chisholm35 , A. Chitan27b , I. Chiu160 , Y.H. Chiu173 , M.V. Chizhov77 , K. Choi63 , A.R. Chomont128 , S. Chouridou159 , Y.S. Chow118 , V. Christodoulou92 , M.C. Chu61a , J. Chudoba137 , A.J. Chuinard101 , J.J. Chwastowski82 , L. Chytka126 , D. Cinca45 , V. Cindro89 , I.A. Cioar˘a24 , A. Ciocio18 , F. Cirotto67a,67b , Z.H. Citron177 , M. Citterio66a , A. Clark52 , M.R. Clark38 , P.J. Clark48 , C. Clement43a,43b , Y. Coadou99 , M. Cobal64a,64c , A. Coccaro53b,53a , J. Cochran76 , A.E.C. Coimbra177 , L. Colasurdo117 , B. Cole38 , A.P. Colijn118 , J. Collot56 , P. Conde Mui˜ no136a,136b , E. Coniavitis50 , S.H. Connell32b , I.A. Connelly98 , S. Constantinescu27b ,
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JHEP11(2018)085
F. Conventi67a,at , A.M. Cooper-Sarkar131 , F. Cormier172 , K.J.R. Cormier164 , M. Corradi70a,70b , E.E. Corrigan94 , F. Corriveau101,ac , A. Cortes-Gonzalez35 , M.J. Costa171 , D. Costanzo146 , G. Cottin31 , G. Cowan91 , B.E. Cox98 , J. Crane98 , K. Cranmer121 , S.J. Crawley55 , R.A. Creager133 , G. Cree33 , S. Cr´ep´e-Renaudin56 , F. Crescioli132 , M. Cristinziani24 , V. Croft121 , G. Crosetti40b,40a , A. Cueto96 , T. Cuhadar Donszelmann146 , A.R. Cukierman150 , J. C´ uth97 , 82 35 58b,136b S. Czekierda , P. Czodrowski , M.J. Da Cunha Sargedas De Sousa , C. Da Via98 , 81a 28a,x 34e 103 107 W. Dabrowski , T. Dado , S. Dahbi , T. Dai , F. Dallaire , C. Dallapiccola100 , 39 23b,23a M. Dam , G. D’amen , J. Damp97 , J.R. Dandoy133 , M.F. Daneri30 , N.P. Dang178,j , N.D Dann98 , M. Danninger172 , V. Dao35 , G. Darbo53b , S. Darmora8 , O. Dartsi5 , A. Dattagupta127 , T. Daubney44 , S. D’Auria55 , W. Davey24 , C. David44 , T. Davidek139 , D.R. Davis47 , E. Dawe102 , I. Dawson146 , K. De8 , R. De Asmundis67a , A. De Benedetti124 , M. De Beurs118 , S. De Castro23b,23a , S. De Cecco70a,70b , N. De Groot117 , P. de Jong118 , H. De la Torre104 , F. De Lorenzi76 , A. De Maria51,s , D. De Pedis70a , A. De Salvo70a , U. De Sanctis71a,71b , A. De Santo153 , K. De Vasconcelos Corga99 , J.B. De Vivie De Regie128 , C. Debenedetti143 , D.V. Dedovich77 , N. Dehghanian3 , M. Del Gaudio40b,40a , J. Del Peso96 , Y. Delabat Diaz44 , D. Delgove128 , F. Deliot142 , C.M. Delitzsch7 , M. Della Pietra67a,67b , D. Della Volpe52 , A. Dell’Acqua35 , L. Dell’Asta25 , M. Delmastro5 , C. Delporte128 , P.A. Delsart56 , D.A. DeMarco164 , S. Demers180 , M. Demichev77 , S.P. Denisov140 , D. Denysiuk118 , L. D’Eramo132 , D. Derendarz82 , J.E. Derkaoui34d , F. Derue132 , P. Dervan88 , K. Desch24 , C. Deterre44 , K. Dette164 , M.R. Devesa30 , P.O. Deviveiros35 , A. Dewhurst141 , S. Dhaliwal26 , F.A. Di Bello52 , A. Di Ciaccio71a,71b , L. Di Ciaccio5 , W.K. Di Clemente133 , C. Di Donato67a,67b , A. Di Girolamo35 , B. Di Micco72a,72b , R. Di Nardo100 , K.F. Di Petrillo57 , A. Di Simone50 , R. Di Sipio164 , D. Di Valentino33 , C. Diaconu99 , M. Diamond164 , F.A. Dias39 , T. Dias Do Vale136a , M.A. Diaz144a , J. Dickinson18 , E.B. Diehl103 , J. Dietrich19 , S. D´ıez Cornell44 , A. Dimitrievska18 , J. Dingfelder24 , F. Dittus35 , F. Djama99 , T. Djobava156b , J.I. Djuvsland59a , M.A.B. Do Vale78c , M. Dobre27b , D. Dodsworth26 , C. Doglioni94 , J. Dolejsi139 , Z. Dolezal139 , M. Donadelli78d , J. Donini37 , A. D’onofrio90 , M. D’Onofrio88 , J. Dopke141 , A. Doria67a , M.T. Dova86 , A.T. Doyle55 , E. Drechsler51 , E. Dreyer149 , T. Dreyer51 , Y. Du58b , J. Duarte-Campderros158 , F. Dubinin108 , M. Dubovsky28a , A. Dubreuil52 , E. Duchovni177 , G. Duckeck112 , A. Ducourthial132 , O.A. Ducu107,w , D. Duda113 , A. Dudarev35 , A.C. Dudder97 , E.M. Duffield18 , L. Duflot128 , M. D¨ uhrssen35 , C. D¨ ulsen179 , M. Dumancic177 , A.E. Dumitriu27b,d , A.K. Duncan55 , 59a 99 M. Dunford , A. Duperrin , H. Duran Yildiz4a , M. D¨ uren54 , A. Durglishvili156b , D. Duschinger46 , B. Dutta44 , D. Duvnjak1 , M. Dyndal44 , S. Dysch98 , B.S. Dziedzic82 , C. Eckardt44 , K.M. Ecker113 , R.C. Edgar103 , T. Eifert35 , G. Eigen17 , K. Einsweiler18 , T. Ekelof169 , M. El Kacimi34c , R. El Kosseifi99 , V. Ellajosyula99 , M. Ellert169 , F. Ellinghaus179 , A.A. Elliot90 , N. Ellis35 , J. Elmsheuser29 , M. Elsing35 , D. Emeliyanov141 , Y. Enari160 , J.S. Ennis175 , M.B. Epland47 , J. Erdmann45 , A. Ereditato20 , S. Errede170 , M. Escalier128 , C. Escobar171 , O. Estrada Pastor171 , A.I. Etienvre142 , E. Etzion158 , H. Evans63 , A. Ezhilov134 , M. Ezzi34e , F. Fabbri55 , L. Fabbri23b,23a , V. Fabiani117 , G. Facini92 , R.M. Faisca Rodrigues Pereira136a , R.M. Fakhrutdinov140 , S. Falciano70a , P.J. Falke5 , S. Falke5 , J. Faltova139 , Y. Fang15a , M. Fanti66a,66b , A. Farbin8 , A. Farilla72a , E.M. Farina68a,68b , T. Farooque104 , S. Farrell18 , S.M. Farrington175 , P. Farthouat35 , F. Fassi34e , P. Fassnacht35 , D. Fassouliotis9 , M. Faucci Giannelli48 , A. Favareto53b,53a , W.J. Fawcett52 , L. Fayard128 , O.L. Fedin134,o , W. Fedorko172 , M. Feickert41 , S. Feigl130 , L. Feligioni99 , C. Feng58b , E.J. Feng35 , M. Feng47 , M.J. Fenton55 , A.B. Fenyuk140 , L. Feremenga8 , J. Ferrando44 , A. Ferrari169 , P. Ferrari118 , R. Ferrari68a , D.E. Ferreira de Lima59b , A. Ferrer171 , D. Ferrere52 , C. Ferretti103 , F. Fiedler97 , A. Filipˇciˇc89 , F. Filthaut117 , K.D. Finelli25 , M.C.N. Fiolhais136a,136c,a , L. Fiorini171 , C. Fischer14 , W.C. Fisher104 , N. Flaschel44 , I. Fleck148 , P. Fleischmann103 , R.R.M. Fletcher133 ,
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T. Flick179 , B.M. Flierl112 , L.M. Flores133 , L.R. Flores Castillo61a , N. Fomin17 , G.T. Forcolin98 , A. Formica142 , F.A. F¨orster14 , A.C. Forti98 , A.G. Foster21 , D. Fournier128 , H. Fox87 , S. Fracchia146 , P. Francavilla69a,69b , M. Franchini23b,23a , S. Franchino59a , D. Francis35 , L. Franconi130 , M. Franklin57 , M. Frate168 , M. Fraternali68a,68b , D. Freeborn92 , S.M. Fressard-Batraneanu35 , B. Freund107 , W.S. Freund78b , D. Froidevaux35 , J.A. Frost131 , C. Fukunaga161 , E. Fullana Torregrosa171 , T. Fusayasu114 , J. Fuster171 , O. Gabizon157 , A. Gabrielli23b,23a , A. Gabrielli18 , G.P. Gach81a , S. Gadatsch52 , P. Gadow113 , G. Gagliardi53b,53a , L.G. Gagnon107 , C. Galea27b , B. Galhardo136a,136c , E.J. Gallas131 , B.J. Gallop141 , P. Gallus138 , G. Galster39 , R. Gamboa Goni90 , K.K. Gan122 , S. Ganguly177 , J. Gao58a , Y. Gao88 , Y.S. Gao150,l , C. Garc´ıa171 , J.E. Garc´ıa Navarro171 , J.A. Garc´ıa Pascual15a , M. Garcia-Sciveres18 , R.W. Gardner36 , N. Garelli150 , V. Garonne130 , K. Gasnikova44 , A. Gaudiello53b,53a , G. Gaudio68a , I.L. Gavrilenko108 , A. Gavrilyuk109 , C. Gay172 , G. Gaycken24 , E.N. Gazis10 , C.N.P. Gee141 , J. Geisen51 , M. Geisen97 , M.P. Geisler59a , K. Gellerstedt43a,43b , C. Gemme53b , M.H. Genest56 , C. Geng103 , S. Gentile70a,70b , S. George91 , D. Gerbaudo14 , G. Gessner45 , S. Ghasemi148 , M. Ghasemi Bostanabad173 , M. Ghneimat24 , B. Giacobbe23b , S. Giagu70a,70b , N. Giangiacomi23b,23a , P. Giannetti69a , A. Giannini67a,67b , S.M. Gibson91 , M. Gignac143 , D. Gillberg33 , G. Gilles179 , D.M. Gingrich3,as , M.P. Giordani64a,64c , F.M. Giorgi23b , P.F. Giraud142 , P. Giromini57 , G. Giugliarelli64a,64c , D. Giugni66a , F. Giuli131 , M. Giulini59b , S. Gkaitatzis159 , I. Gkialas9,i , E.L. Gkougkousis14 , P. Gkountoumis10 , L.K. Gladilin111 , C. Glasman96 , J. Glatzer14 , P.C.F. Glaysher44 , A. Glazov44 , M. Goblirsch-Kolb26 , J. Godlewski82 , S. Goldfarb102 , T. Golling52 , D. Golubkov140 , A. Gomes136a,136b,136d , R. Goncalves Gama78a , R. Gon¸calo136a , G. Gonella50 , L. Gonella21 , A. Gongadze77 , F. Gonnella21 , J.L. Gonski57 , S. Gonz´ alez de la Hoz171 , S. Gonzalez-Sevilla52 , L. Goossens35 , P.A. Gorbounov109 , H.A. Gordon29 , B. Gorini35 , E. Gorini65a,65b , A. Goriˇsek89 , A.T. Goshaw47 , C. G¨ossling45 , M.I. Gostkin77 , C.A. Gottardo24 , C.R. Goudet128 , D. Goujdami34c , A.G. Goussiou145 , N. Govender32b,b , C. Goy5 , E. Gozani157 , I. Grabowska-Bold81a , P.O.J. Gradin169 , E.C. Graham88 , J. Gramling168 , E. Gramstad130 , S. Grancagnolo19 , V. Gratchev134 , P.M. Gravila27f , F.G. Gravili65a,65b , C. Gray55 , H.M. Gray18 , Z.D. Greenwood93,ai , C. Grefe24 , K. Gregersen92 , I.M. Gregor44 , P. Grenier150 , K. Grevtsov44 , J. Griffiths8 , A.A. Grillo143 , K. Grimm150 , S. Grinstein14,y , Ph. Gris37 , J.-F. Grivaz128 , S. Groh97 , E. Gross177 , J. Grosse-Knetter51 , G.C. Grossi93 , Z.J. Grout92 , C. Grud103 , A. Grummer116 , L. Guan103 , W. Guan178 , J. Guenther35 , A. Guerguichon128 , F. Guescini165a , D. Guest168 , R. Gugel50 , B. Gui122 , T. Guillemin5 , S. Guindon35 , U. Gul55 , C. Gumpert35 , J. Guo58c , W. Guo103 , Y. Guo58a,r , Z. Guo99 , R. Gupta41 , S. Gurbuz12c , G. Gustavino124 , B.J. Gutelman157 , P. Gutierrez124 , C. Gutschow92 , C. Guyot142 , M.P. Guzik81a , C. Gwenlan131 , C.B. Gwilliam88 , A. Haas121 , C. Haber18 , H.K. Hadavand8 , N. Haddad34e , A. Hadef58a , S. Hageb¨ock24 , M. Hagihara166 , H. Hakobyan181,∗ , M. Haleem174 , J. Haley125 , G. Halladjian104 , G.D. Hallewell99 , K. Hamacher179 , P. Hamal126 , K. Hamano173 , A. Hamilton32a , G.N. Hamity146 , K. Han58a,ah , L. Han58a , S. Han15d , K. Hanagaki79,u , M. Hance143 , D.M. Handl112 , B. Haney133 , R. Hankache132 , P. Hanke59a , E. Hansen94 , J.B. Hansen39 , J.D. Hansen39 , M.C. Hansen24 , P.H. Hansen39 , K. Hara166 , A.S. Hard178 , T. Harenberg179 , S. Harkusha105 , P.F. Harrison175 , N.M. Hartmann112 , Y. Hasegawa147 , A. Hasib48 , S. Hassani142 , S. Haug20 , R. Hauser104 , L. Hauswald46 , L.B. Havener38 , M. Havranek138 , C.M. Hawkes21 , R.J. Hawkings35 , D. Hayden104 , C. Hayes152 , C.P. Hays131 , J.M. Hays90 , H.S. Hayward88 , S.J. Haywood141 , M.P. Heath48 , V. Hedberg94 , L. Heelan8 , S. Heer24 , K.K. Heidegger50 , J. Heilman33 , S. Heim44 , T. Heim18 , B. Heinemann44,an , J.J. Heinrich112 , L. Heinrich121 , C. Heinz54 , J. Hejbal137 , L. Helary35 , A. Held172 , S. Hellesund130 , S. Hellman43a,43b , C. Helsens35 , R.C.W. Henderson87 , Y. Heng178 , S. Henkelmann172 , A.M. Henriques Correia35 , G.H. Herbert19 , H. Herde26 , V. Herget174 ,
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JHEP11(2018)085
Y. Hern´ andez Jim´enez32c , H. Herr97 , M.G. Herrmann112 , G. Herten50 , R. Hertenberger112 , L. Hervas35 , T.C. Herwig133 , G.G. Hesketh92 , N.P. Hessey165a , J.W. Hetherly41 , S. Higashino79 , E. Hig´ on-Rodriguez171 , K. Hildebrand36 , E. Hill173 , J.C. Hill31 , K.K. Hill29 , K.H. Hiller44 , S.J. Hillier21 , M. Hils46 , I. Hinchliffe18 , M. Hirose129 , D. Hirschbuehl179 , B. Hiti89 , O. Hladik137 , D.R. Hlaluku32c , X. Hoad48 , J. Hobbs152 , N. Hod165a , M.C. Hodgkinson146 , A. Hoecker35 , M.R. Hoeferkamp116 , F. Hoenig112 , D. Hohn24 , D. Hohov128 , T.R. Holmes36 , M. Holzbock112 , M. Homann45 , S. Honda166 , T. Honda79 , T.M. Hong135 , A. H¨onle113 , B.H. Hooberman170 , W.H. Hopkins127 , Y. Horii115 , P. Horn46 , A.J. Horton149 , L.A. Horyn36 , J-Y. Hostachy56 , A. Hostiuc145 , S. Hou155 , A. Hoummada34a , J. Howarth98 , J. Hoya86 , M. Hrabovsky126 , J. Hrdinka35 , I. Hristova19 , J. Hrivnac128 , A. Hrynevich106 , T. Hryn’ova5 , P.J. Hsu62 , S.-C. Hsu145 , Q. Hu29 , S. Hu58c , Y. Huang15a , Z. Hubacek138 , F. Hubaut99 , M. Huebner24 , F. Huegging24 , T.B. Huffman131 , E.W. Hughes38 , M. Huhtinen35 , R.F.H. Hunter33 , P. Huo152 , A.M. Hupe33 , N. Huseynov77,ae , J. Huston104 , J. Huth57 , R. Hyneman103 , G. Iacobucci52 , G. Iakovidis29 , I. Ibragimov148 , L. Iconomidou-Fayard128 , Z. Idrissi34e , P. Iengo35 , R. Ignazzi39 , O. Igonkina118,aa , R. Iguchi160 , T. Iizawa52 , Y. Ikegami79 , M. Ikeno79 , D. Iliadis159 , N. Ilic150 , F. Iltzsche46 , G. Introzzi68a,68b , M. Iodice72a , K. Iordanidou38 , V. Ippolito70a,70b , M.F. Isacson169 , N. Ishijima129 , M. Ishino160 , M. Ishitsuka162 , W. Islam125 , C. Issever131 , S. Istin12c,am , F. Ito166 , J.M. Iturbe Ponce61a , R. Iuppa73a,73b , A. Ivina177 , H. Iwasaki79 , J.M. Izen42 , V. Izzo67a , P. Jacka137 , P. Jackson1 , R.M. Jacobs24 , V. Jain2 , G. J¨akel179 , K.B. Jakobi97 , K. Jakobs50 , S. Jakobsen74 , T. Jakoubek137 , D.O. Jamin125 , D.K. Jana93 , R. Jansky52 , J. Janssen24 , M. Janus51 , P.A. Janus81a , G. Jarlskog94 , N. Javadov77,ae , T. Jav˚ urek50 , M. Javurkova50 , 142 18 156a,af 175 F. Jeanneau , L. Jeanty , J. Jejelava , A. Jelinskas , P. Jenni50,c , J. Jeong44 , S. J´ez´equel5 , H. Ji178 , J. Jia152 , H. Jiang76 , Y. Jiang58a , Z. Jiang150,p , S. Jiggins50 , F.A. Jimenez Morales37 , J. Jimenez Pena171 , S. Jin15c , A. Jinaru27b , O. Jinnouchi162 , H. Jivan32c , P. Johansson146 , K.A. Johns7 , C.A. Johnson63 , W.J. Johnson145 , K. Jon-And43a,43b , R.W.L. Jones87 , S.D. Jones153 , S. Jones7 , T.J. Jones88 , J. Jongmanns59a , P.M. Jorge136a,136b , J. Jovicevic165a , X. Ju178 , J.J. Junggeburth113 , A. Juste Rozas14,y , A. Kaczmarska82 , M. Kado128 , H. Kagan122 , M. Kagan150 , T. Kaji176 , E. Kajomovitz157 , C.W. Kalderon94 , A. Kaluza97 , S. Kama41 , A. Kamenshchikov140 , L. Kanjir89 , Y. Kano160 , V.A. Kantserov110 , J. Kanzaki79 , B. Kaplan121 , L.S. Kaplan178 , D. Kar32c , M.J. Kareem165b , E. Karentzos10 , S.N. Karpov77 , Z.M. Karpova77 , V. Kartvelishvili87 , A.N. Karyukhin140 , K. Kasahara166 , L. Kashif178 , R.D. Kass122 , A. Kastanas151 , Y. Kataoka160 , C. Kato160 , J. Katzy44 , K. Kawade80 , K. Kawagoe85 , T. Kawamoto160 , G. Kawamura51 , E.F. Kay88 , V.F. Kazanin120b,120a , R. Keeler173 , R. Kehoe41 , J.S. Keller33 , E. Kellermann94 , J.J. Kempster21 , J. Kendrick21 , O. Kepka137 , S. Kersten179 , B.P. Kerˇsevan89 , R.A. Keyes101 , M. Khader170 , F. Khalil-Zada13 , A. Khanov125 , A.G. Kharlamov120b,120a , T. Kharlamova120b,120a , A. Khodinov163 , T.J. Khoo52 , E. Khramov77 , J. Khubua156b , S. Kido80 , M. Kiehn52 , C.R. Kilby91 , S.H. Kim166 , Y.K. Kim36 , N. Kimura64a,64c , O.M. Kind19 , B.T. King88 , D. Kirchmeier46 , J. Kirk141 , A.E. Kiryunin113 , T. Kishimoto160 , D. Kisielewska81a , V. Kitali44 , O. Kivernyk5 , E. Kladiva28b , T. Klapdor-Kleingrothaus50 , M.H. Klein103 , M. Klein88 , U. Klein88 , K. Kleinknecht97 , P. Klimek119 , A. Klimentov29 , R. Klingenberg45,∗ , T. Klingl24 , T. Klioutchnikova35 , F.F. Klitzner112 , P. Kluit118 , S. Kluth113 , E. Kneringer74 , E.B.F.G. Knoops99 , A. Knue50 , A. Kobayashi160 , D. Kobayashi85 , T. Kobayashi160 , M. Kobel46 , M. Kocian150 , P. Kodys139 , T. Koffas33 , E. Koffeman118 , N.M. K¨ ohler113 , T. Koi150 , M. Kolb59b , I. Koletsou5 , T. Kondo79 , N. Kondrashova58c , K. K¨ oneke50 , A.C. K¨onig117 , T. Kono79 , R. Konoplich121,aj , V. Konstantinides92 , N. Konstantinidis92 , B. Konya94 , R. Kopeliansky63 , S. Koperny81a , K. Korcyl82 , K. Kordas159 , A. Korn92 , I. Korolkov14 , E.V. Korolkova146 , O. Kortner113 , S. Kortner113 , T. Kosek139 , V.V. Kostyukhin24 , A. Kotwal47 , A. Koulouris10 , A. Kourkoumeli-Charalampidi68a,68b ,
– 43 –
JHEP11(2018)085
C. Kourkoumelis9 , E. Kourlitis146 , V. Kouskoura29 , A.B. Kowalewska82 , R. Kowalewski173 , T.Z. Kowalski81a , C. Kozakai160 , W. Kozanecki142 , A.S. Kozhin140 , V.A. Kramarenko111 , G. Kramberger89 , D. Krasnopevtsev110 , M.W. Krasny132 , A. Krasznahorkay35 , D. Krauss113 , J.A. Kremer81a , J. Kretzschmar88 , P. Krieger164 , K. Krizka18 , K. Kroeninger45 , H. Kroha113 , J. Kroll137 , J. Kroll133 , J. Krstic16 , U. Kruchonak77 , H. Kr¨ uger24 , N. Krumnack76 , M.C. Kruse47 , 102 4b 179 35 T. Kubota , S. Kuday , J.T. Kuechler , S. Kuehn , A. Kugel59a , F. Kuger174 , T. Kuhl44 , V. Kukhtin77 , R. Kukla99 , Y. Kulchitsky105 , S. Kuleshov144b , Y.P. Kulinich170 , M. Kuna56 , T. Kunigo83 , A. Kupco137 , T. Kupfer45 , O. Kuprash158 , H. Kurashige80 , L.L. Kurchaninov165a , Y.A. Kurochkin105 , M.G. Kurth15d , E.S. Kuwertz173 , M. Kuze162 , J. Kvita126 , T. Kwan101 , A. La Rosa113 , J.L. La Rosa Navarro78d , L. La Rotonda40b,40a , F. La Ruffa40b,40a , C. Lacasta171 , F. Lacava70a,70b , J. Lacey44 , D.P.J. Lack98 , H. Lacker19 , D. Lacour132 , E. Ladygin77 , R. Lafaye5 , B. Laforge132 , T. Lagouri32c , S. Lai51 , S. Lammers63 , W. Lampl7 , E. Lan¸con29 , U. Landgraf50 , M.P.J. Landon90 , M.C. Lanfermann52 , V.S. Lang44 , J.C. Lange14 , R.J. Langenberg35 , A.J. Lankford168 , F. Lanni29 , K. Lantzsch24 , A. Lanza68a , A. Lapertosa53b,53a , S. Laplace132 , J.F. Laporte142 , T. Lari66a , F. Lasagni Manghi23b,23a , M. Lassnig35 , T.S. Lau61a , A. Laudrain128 , M. Lavorgna67a,67b , A.T. Law143 , P. Laycock88 , M. Lazzaroni66a,66b , B. Le102 , O. Le Dortz132 , E. Le Guirriec99 , E.P. Le Quilleuc142 , M. LeBlanc7 , T. LeCompte6 , F. Ledroit-Guillon56 , C.A. Lee29 , G.R. Lee144a , L. Lee57 , S.C. Lee155 , B. Lefebvre101 , M. Lefebvre173 , F. Legger112 , C. Leggett18 , N. Lehmann179 , G. Lehmann Miotto35 , W.A. Leight44 , A. Leisos159,v , M.A.L. Leite78d , R. Leitner139 , D. Lellouch177 , B. Lemmer51 , K.J.C. Leney92 , T. Lenz24 , B. Lenzi35 , R. Leone7 , S. Leone69a , C. Leonidopoulos48 , G. Lerner153 , C. Leroy107 , R. Les164 , A.A.J. Lesage142 , C.G. Lester31 , M. Levchenko134 , J. Levˆeque5 , D. Levin103 , L.J. Levinson177 , D. Lewis90 , B. Li103 , C-Q. Li58a , H. Li58b , L. Li58c , Q. Li15d , Q.Y. Li58a , S. Li58d,58c , X. Li58c , Y. Li148 , Z. Liang15a , B. Liberti71a , A. Liblong164 , K. Lie61c , S. Liem118 , A. Limosani154 , C.Y. Lin31 , K. Lin104 , T.H. Lin97 , R.A. Linck63 , B.E. Lindquist152 , A.L. Lionti52 , E. Lipeles133 , A. Lipniacka17 , M. Lisovyi59b , T.M. Liss170,ap , A. Lister172 , A.M. Litke143 , J.D. Little8 , B. Liu76 , B.L Liu6 , H.B. Liu29 , H. Liu103 , J.B. Liu58a , J.K.K. Liu131 , K. Liu132 , M. Liu58a , P. Liu18 , Y. Liu15a , Y.L. Liu58a , Y.W. Liu58a , M. Livan68a,68b , A. Lleres56 , J. Llorente Merino15a , S.L. Lloyd90 , C.Y. Lo61b , F. Lo Sterzo41 , E.M. Lobodzinska44 , P. Loch7 , A. Loesle50 , K.M. Loew26 , T. Lohse19 , K. Lohwasser146 , M. Lokajicek137 , B.A. Long25 , J.D. Long170 , R.E. Long87 , L. Longo65a,65b , K.A. Looper122 , J.A. Lopez144b , I. Lopez Paz14 , A. Lopez Solis146 , J. Lorenz112 , N. Lorenzo Martinez5 , M. Losada22 , P.J. L¨osel112 , X. Lou44 , X. Lou15a , A. Lounis128 , J. Love6 , P.A. Love87 , J.J. Lozano Bahilo171 , H. Lu61a , M. Lu58a , N. Lu103 , Y.J. Lu62 , H.J. Lubatti145 , C. Luci70a,70b , A. Lucotte56 , C. Luedtke50 , F. Luehring63 , I. Luise132 , W. Lukas74 , L. Luminari70a , B. Lund-Jensen151 , M.S. Lutz100 , P.M. Luzi132 , D. Lynn29 , R. Lysak137 , E. Lytken94 , F. Lyu15a , V. Lyubushkin77 , H. Ma29 , L.L. Ma58b , Y. Ma58b , G. Maccarrone49 , A. Macchiolo113 , C.M. Macdonald146 , J. Machado Miguens133,136b , D. Madaffari171 , R. Madar37 , W.F. Mader46 , A. Madsen44 , N. Madysa46 , J. Maeda80 , K. Maekawa160 , S. Maeland17 , T. Maeno29 , A.S. Maevskiy111 , V. Magerl50 , C. Maidantchik78b , T. Maier112 , A. Maio136a,136b,136d , O. Majersky28a , S. Majewski127 , Y. Makida79 , N. Makovec128 , B. Malaescu132 , Pa. Malecki82 , V.P. Maleev134 , F. Malek56 , U. Mallik75 , D. Malon6 , C. Malone31 , S. Maltezos10 , S. Malyukov35 , J. Mamuzic171 , G. Mancini49 , I. Mandi´c89 , J. Maneira136a , L. Manhaes de Andrade Filho78a , J. Manjarres Ramos46 , K.H. Mankinen94 , A. Mann112 , A. Manousos74 , B. Mansoulie142 , J.D. Mansour15a , M. Mantoani51 , S. Manzoni66a,66b , G. Marceca30 , L. March52 , L. Marchese131 , G. Marchiori132 , M. Marcisovsky137 , C.A. Marin Tobon35 , M. Marjanovic37 , D.E. Marley103 , F. Marroquim78b , Z. Marshall18 , M.U.F Martensson169 , S. Marti-Garcia171 , C.B. Martin122 , T.A. Martin175 , V.J. Martin48 , B. Martin dit Latour17 , M. Martinez14,y , V.I. Martinez Outschoorn100 , S. Martin-Haugh141 ,
– 44 –
JHEP11(2018)085
V.S. Martoiu27b , A.C. Martyniuk92 , A. Marzin35 , L. Masetti97 , T. Mashimo160 , R. Mashinistov108 , J. Masik98 , A.L. Maslennikov120b,120a , L.H. Mason102 , L. Massa71a,71b , P. Massarotti67a,67b , P. Mastrandrea5 , A. Mastroberardino40b,40a , T. Masubuchi160 , P. M¨attig179 , J. Maurer27b , B. Maˇcek89 , S.J. Maxfield88 , D.A. Maximov120b,120a , R. Mazini155 , I. Maznas159 , S.M. Mazza143 , N.C. Mc Fadden116 , G. Mc Goldrick164 , S.P. Mc Kee103 , A. McCarn103 , T.G. McCarthy113 , L.I. McClymont92 , E.F. McDonald102 , J.A. Mcfayden35 , G. Mchedlidze51 , M.A. McKay41 , K.D. McLean173 , S.J. McMahon141 , P.C. McNamara102 , C.J. McNicol175 , R.A. McPherson173,ac , J.E. Mdhluli32c , Z.A. Meadows100 , S. Meehan145 , T.M. Megy50 , S. Mehlhase112 , A. Mehta88 , T. Meideck56 , B. Meirose42 , D. Melini171,g , B.R. Mellado Garcia32c , J.D. Mellenthin51 , M. Melo28a , F. Meloni44 , A. Melzer24 , S.B. Menary98 , E.D. Mendes Gouveia136a , L. Meng88 , X.T. Meng103 , A. Mengarelli23b,23a , S. Menke113 , E. Meoni40b,40a , S. Mergelmeyer19 , C. Merlassino20 , P. Mermod52 , L. Merola67a,67b , C. Meroni66a , F.S. Merritt36 , A. Messina70a,70b , J. Metcalfe6 , A.S. Mete168 , C. Meyer133 , J. Meyer157 , J-P. Meyer142 , H. Meyer Zu Theenhausen59a , F. Miano153 , R.P. Middleton141 , L. Mijovi´c48 , G. Mikenberg177 , M. Mikestikova137 , M. Mikuˇz89 , M. Milesi102 , A. Milic164 , D.A. Millar90 , D.W. Miller36 , A. Milov177 , D.A. Milstead43a,43b , A.A. Minaenko140 , M. Mi˜ nano Moya171 , 156b 121 81a 77 I.A. Minashvili , A.I. Mincer , B. Mindur , M. Mineev , Y. Minegishi160 , Y. Ming178 , 14 L.M. Mir , A. Mirto65a,65b , K.P. Mistry133 , T. Mitani176 , J. Mitrevski112 , V.A. Mitsou171 , A. Miucci20 , P.S. Miyagawa146 , A. Mizukami79 , J.U. Mj¨ornmark94 , T. Mkrtchyan181 , M. Mlynarikova139 , T. Moa43a,43b , K. Mochizuki107 , P. Mogg50 , S. Mohapatra38 , S. Molander43a,43b , R. Moles-Valls24 , M.C. Mondragon104 , K. M¨onig44 , J. Monk39 , E. Monnier99 , A. Montalbano149 , J. Montejo Berlingen35 , F. Monticelli86 , S. Monzani66a , R.W. Moore3 , N. Morange128 , D. Moreno22 , M. Moreno Ll´acer35 , P. Morettini53b , M. Morgenstern118 , S. Morgenstern46 , D. Mori149 , T. Mori160 , M. Morii57 , M. Morinaga176 , V. Morisbak130 , A.K. Morley35 , G. Mornacchi35 , A.P. Morris92 , J.D. Morris90 , L. Morvaj152 , P. Moschovakos10 , M. Mosidze156b , H.J. Moss146 , J. Moss150,m , K. Motohashi162 , R. Mount150 , E. Mountricha35 , E.J.W. Moyse100 , S. Muanza99 , F. Mueller113 , J. Mueller135 , R.S.P. Mueller112 , D. Muenstermann87 , P. Mullen55 , G.A. Mullier20 , F.J. Munoz Sanchez98 , P. Murin28b , W.J. Murray175,141 , A. Murrone66a,66b , M. Muˇskinja89 , C. Mwewa32a , A.G. Myagkov140,ak , J. Myers127 , M. Myska138 , B.P. Nachman18 , O. Nackenhorst45 , K. Nagai131 , K. Nagano79 , Y. Nagasaka60 , K. Nagata166 , M. Nagel50 , E. Nagy99 , A.M. Nairz35 , Y. Nakahama115 , K. Nakamura79 , T. Nakamura160 , I. Nakano123 , H. Nanjo129 , F. Napolitano59a , R.F. Naranjo Garcia44 , R. Narayan11 , D.I. Narrias Villar59a , I. Naryshkin134 , T. Naumann44 , G. Navarro22 , R. Nayyar7 , H.A. Neal103 , P.Y. Nechaeva108 , T.J. Neep142 , A. Negri68a,68b , M. Negrini23b , S. Nektarijevic117 , C. Nellist51 , M.E. Nelson131 , S. Nemecek137 , P. Nemethy121 , M. Nessi35,e , M.S. Neubauer170 , M. Neumann179 , P.R. Newman21 , T.Y. Ng61c , Y.S. Ng19 , H.D.N. Nguyen99 , T. Nguyen Manh107 , E. Nibigira37 , R.B. Nickerson131 , R. Nicolaidou142 , J. Nielsen143 , N. Nikiforou11 , V. Nikolaenko140,ak , I. Nikolic-Audit132 , K. Nikolopoulos21 , P. Nilsson29 , Y. Ninomiya79 , A. Nisati70a , N. Nishu58c , R. Nisius113 , I. Nitsche45 , T. Nitta176 , T. Nobe160 , Y. Noguchi83 , M. Nomachi129 , I. Nomidis132 , M.A. Nomura29 , T. Nooney90 , M. Nordberg35 , N. Norjoharuddeen131 , T. Novak89 , O. Novgorodova46 , R. Novotny138 , L. Nozka126 , K. Ntekas168 , E. Nurse92 , F. Nuti102 , F.G. Oakham33,as , H. Oberlack113 , T. Obermann24 , J. Ocariz132 , A. Ochi80 , I. Ochoa38 , J.P. Ochoa-Ricoux144a , K. O’Connor26 , S. Oda85 , S. Odaka79 , S. Oerdek51 , A. Oh98 , S.H. Oh47 , C.C. Ohm151 , H. Oide53b,53a , H. Okawa166 , Y. Okazaki83 , Y. Okumura160 , T. Okuyama79 , A. Olariu27b , L.F. Oleiro Seabra136a , S.A. Olivares Pino144a , D. Oliveira Damazio29 , J.L. Oliver1 , M.J.R. Olsson36 , A. Olszewski82 , J. Olszowska82 , D.C. O’Neil149 , A. Onofre136a,136e , K. Onogi115 , P.U.E. Onyisi11 , H. Oppen130 , M.J. Oreglia36 , Y. Oren158 , D. Orestano72a,72b , E.C. Orgill98 , N. Orlando61b , A.A. O’Rourke44 ,
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JHEP11(2018)085
R.S. Orr164 , B. Osculati53b,53a,∗ , V. O’Shea55 , R. Ospanov58a , G. Otero y Garzon30 , H. Otono85 , M. Ouchrif34d , F. Ould-Saada130 , A. Ouraou142 , Q. Ouyang15a , M. Owen55 , R.E. Owen21 , V.E. Ozcan12c , N. Ozturk8 , J. Pacalt126 , H.A. Pacey31 , K. Pachal149 , A. Pacheco Pages14 , L. Pacheco Rodriguez142 , C. Padilla Aranda14 , S. Pagan Griso18 , M. Paganini180 , G. Palacino63 , S. Palazzo40b,40a , S. Palestini35 , M. Palka81b , D. Pallin37 , I. Panagoulias10 , C.E. Pandini35 , J.G. Panduro Vazquez91 , P. Pani35 , G. Panizzo64a,64c , L. Paolozzi52 , T.D. Papadopoulou10 , K. Papageorgiou9,i , A. Paramonov6 , D. Paredes Hernandez61b , S.R. Paredes Saenz131 , B. Parida58c , A.J. Parker87 , K.A. Parker44 , M.A. Parker31 , F. Parodi53b,53a , J.A. Parsons38 , U. Parzefall50 , V.R. Pascuzzi164 , J.M.P. Pasner143 , E. Pasqualucci70a , S. Passaggio53b , F. Pastore91 , P. Pasuwan43a,43b , S. Pataraia97 , J.R. Pater98 , A. Pathak178,j , T. Pauly35 , B. Pearson113 , M. Pedersen130 , L. Pedraza Diaz117 , R. Pedro136a,136b , S.V. Peleganchuk120b,120a , O. Penc137 , C. Peng15d , H. Peng58a , B.S. Peralva78a , M.M. Perego142 , A.P. Pereira Peixoto136a , D.V. Perepelitsa29 , F. Peri19 , L. Perini66a,66b , H. Pernegger35 , S. Perrella67a,67b , V.D. Peshekhonov77,∗ , K. Peters44 , R.F.Y. Peters98 , B.A. Petersen35 , T.C. Petersen39 , E. Petit56 , A. Petridis1 , C. Petridou159 , P. Petroff128 , E. Petrolo70a , M. Petrov131 , F. Petrucci72a,72b , M. Pettee180 , N.E. Pettersson100 , A. Peyaud142 , R. Pezoa144b , T. Pham102 , F.H. Phillips104 , P.W. Phillips141 , G. Piacquadio152 , E. Pianori18 , A. Picazio100 , M.A. Pickering131 , R. Piegaia30 , J.E. Pilcher36 , A.D. Pilkington98 , M. Pinamonti71a,71b , J.L. Pinfold3 , M. Pitt177 , M-A. Pleier29 , V. Pleskot139 , E. Plotnikova77 , D. Pluth76 , P. Podberezko120b,120a , R. Poettgen94 , R. Poggi52 , L. Poggioli128 , I. Pogrebnyak104 , D. Pohl24 , I. Pokharel51 , G. Polesello68a , A. Poley44 , A. Policicchio70a,70b , R. Polifka35 , A. Polini23b , C.S. Pollard44 , V. Polychronakos29 , D. Ponomarenko110 , L. Pontecorvo70a , G.A. Popeneciu27d , D.M. Portillo Quintero132 , S. Pospisil138 , K. Potamianos44 , I.N. Potrap77 , C.J. Potter31 , H. Potti11 , T. Poulsen94 , J. Poveda35 , T.D. Powell146 , M.E. Pozo Astigarraga35 , P. Pralavorio99 , S. Prell76 , D. Price98 , M. Primavera65a , S. Prince101 , N. Proklova110 , K. Prokofiev61c , F. Prokoshin144b , S. Protopopescu29 , J. Proudfoot6 , M. Przybycien81a , A. Puri170 , P. Puzo128 , J. Qian103 , Y. Qin98 , A. Quadt51 , M. Queitsch-Maitland44 , A. Qureshi1 , P. Rados102 , F. Ragusa66a,66b , G. Rahal95 , J.A. Raine98 , S. Rajagopalan29 , A. Ramirez Morales90 , T. Rashid128 , S. Raspopov5 , M.G. Ratti66a,66b , D.M. Rauch44 , F. Rauscher112 , S. Rave97 , B. Ravina146 , I. Ravinovich177 , J.H. Rawling98 , M. Raymond35 , A.L. Read130 , N.P. Readioff56 , M. Reale65a,65b , D.M. Rebuzzi68a,68b , A. Redelbach174 , G. Redlinger29 , R. Reece143 , R.G. Reed32c , K. Reeves42 , L. Rehnisch19 , J. Reichert133 , A. Reiss97 , C. Rembser35 , H. Ren15d , M. Rescigno70a , S. Resconi66a , E.D. Resseguie133 , S. Rettie172 , E. Reynolds21 , O.L. Rezanova120b,120a , P. Reznicek139 , E. Ricci73a,73b , R. Richter113 , S. Richter92 , E. Richter-Was81b , O. Ricken24 , M. Ridel132 , P. Rieck113 , C.J. Riegel179 , O. Rifki44 , M. Rijssenbeek152 , A. Rimoldi68a,68b , M. Rimoldi20 , L. Rinaldi23b , G. Ripellino151 , B. Risti´c87 , E. Ritsch35 , I. Riu14 , J.C. Rivera Vergara144a , F. Rizatdinova125 , E. Rizvi90 , C. Rizzi14 , R.T. Roberts98 , S.H. Robertson101,ac , A. Robichaud-Veronneau101 , D. Robinson31 , J.E.M. Robinson44 , A. Robson55 , E. Rocco97 , C. Roda69a,69b , Y. Rodina99 , S. Rodriguez Bosca171 , A. Rodriguez Perez14 , D. Rodriguez Rodriguez171 , A.M. Rodr´ıguez Vera165b , S. Roe35 , C.S. Rogan57 , O. Røhne130 , R. R¨ ohrig113 , C.P.A. Roland63 , J. Roloff57 , A. Romaniouk110 , M. Romano23b,23a , N. Rompotis88 , M. Ronzani121 , L. Roos132 , S. Rosati70a , K. Rosbach50 , P. Rose143 , N-A. Rosien51 , E. Rossi44 , E. Rossi67a,67b , L.P. Rossi53b , L. Rossini66a,66b , J.H.N. Rosten31 , R. Rosten14 , M. Rotaru27b , J. Rothberg145 , D. Rousseau128 , D. Roy32c , A. Rozanov99 , Y. Rozen157 , X. Ruan32c , F. Rubbo150 , F. R¨ uhr50 , A. Ruiz-Martinez171 , Z. Rurikova50 , N.A. Rusakovich77 , H.L. Russell101 , J.P. Rutherfoord7 , E.M. R¨ uttinger44,k , Y.F. Ryabov134 , M. Rybar170 , G. Rybkin128 , S. Ryu6 , A. Ryzhov140 , G.F. Rzehorz51 , P. Sabatini51 , G. Sabato118 , S. Sacerdoti128 , H.F-W. Sadrozinski143 , R. Sadykov77 , F. Safai Tehrani70a , P. Saha119 , M. Sahinsoy59a ,
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A. Sahu179 , M. Saimpert44 , M. Saito160 , T. Saito160 , H. Sakamoto160 , A. Sakharov121,aj , D. Salamani52 , G. Salamanna72a,72b , J.E. Salazar Loyola144b , D. Salek118 , P.H. Sales De Bruin169 , D. Salihagic113 , A. Salnikov150 , J. Salt171 , D. Salvatore40b,40a , F. Salvatore153 , A. Salvucci61a,61b,61c , A. Salzburger35 , J. Samarati35 , D. Sammel50 , D. Sampsonidis159 , D. Sampsonidou159 , J. S´anchez171 , A. Sanchez Pineda64a,64c , H. Sandaker130 , C.O. Sander44 , M. Sandhoff179 , C. Sandoval22 , D.P.C. Sankey141 , M. Sannino53b,53a , Y. Sano115 , A. Sansoni49 , C. Santoni37 , H. Santos136a , I. Santoyo Castillo153 , A. Sapronov77 , J.G. Saraiva136a,136d , O. Sasaki79 , K. Sato166 , E. Sauvan5 , P. Savard164,as , N. Savic113 , R. Sawada160 , C. Sawyer141 , L. Sawyer93,ai , C. Sbarra23b , A. Sbrizzi23b,23a , T. Scanlon92 , J. Schaarschmidt145 , P. Schacht113 , B.M. Schachtner112 , D. Schaefer36 , L. Schaefer133 , J. Schaeffer97 , S. Schaepe35 , U. Sch¨afer97 , A.C. Schaffer128 , D. Schaile112 , R.D. Schamberger152 , N. Scharmberg98 , V.A. Schegelsky134 , D. Scheirich139 , F. Schenck19 , M. Schernau168 , C. Schiavi53b,53a , S. Schier143 , L.K. Schildgen24 , Z.M. Schillaci26 , E.J. Schioppa35 , M. Schioppa40b,40a , K.E. Schleicher50 , S. Schlenker35 , K.R. Schmidt-Sommerfeld113 , K. Schmieden35 , C. Schmitt97 , S. Schmitt44 , S. Schmitz97 , U. Schnoor50 , L. Schoeffel142 , A. Schoening59b , E. Schopf24 , M. Schott97 , J.F.P. Schouwenberg117 , J. Schovancova35 , S. Schramm52 , A. Schulte97 , H-C. Schultz-Coulon59a , M. Schumacher50 , B.A. Schumm143 , Ph. Schune142 , A. Schwartzman150 , T.A. Schwarz103 , H. Schweiger98 , Ph. Schwemling142 , R. Schwienhorst104 , A. Sciandra24 , G. Sciolla26 , M. Scornajenghi40b,40a , F. Scuri69a , F. Scutti102 , L.M. Scyboz113 , J. Searcy103 , C.D. Sebastiani70a,70b , P. Seema24 , S.C. Seidel116 , A. Seiden143 , T. Seiss36 , J.M. Seixas78b , G. Sekhniaidze67a , K. Sekhon103 , S.J. Sekula41 , N. Semprini-Cesari23b,23a , S. Sen47 , S. Senkin37 , C. Serfon130 , L. Serin128 , L. Serkin64a,64b , M. Sessa72a,72b , H. Severini124 , F. Sforza167 , A. Sfyrla52 , E. Shabalina51 , J.D. Shahinian143 , N.W. Shaikh43a,43b , L.Y. Shan15a , R. Shang170 , J.T. Shank25 , M. Shapiro18 , A.S. Sharma1 , A. Sharma131 , P.B. Shatalov109 , K. Shaw153 , S.M. Shaw98 , A. Shcherbakova134 , Y. Shen124 , N. Sherafati33 , A.D. Sherman25 , P. Sherwood92 , L. Shi155,ao , S. Shimizu80 , C.O. Shimmin180 , M. Shimojima114 , I.P.J. Shipsey131 , S. Shirabe85 , M. Shiyakova77 , J. Shlomi177 , A. Shmeleva108 , D. Shoaleh Saadi107 , M.J. Shochet36 , S. Shojaii102 , D.R. Shope124 , S. Shrestha122 , E. Shulga110 , P. Sicho137 , A.M. Sickles170 , P.E. Sidebo151 , E. Sideras Haddad32c , O. Sidiropoulou174 , A. Sidoti23b,23a , F. Siegert46 , Dj. Sijacki16 , J. Silva136a , M. Silva Jr.178 , M.V. Silva Oliveira78a , S.B. Silverstein43a , L. Simic77 , S. Simion128 , E. Simioni97 , M. Simon97 , R. Simoniello97 , P. Sinervo164 , N.B. Sinev127 , M. Sioli23b,23a , G. Siragusa174 , I. Siral103 , S.Yu. Sivoklokov111 , J. Sj¨olin43a,43b , M.B. Skinner87 , P. Skubic124 , M. Slater21 , T. Slavicek138 , M. Slawinska82 , K. Sliwa167 , R. Slovak139 , V. Smakhtin177 , B.H. Smart5 , J. Smiesko28a , N. Smirnov110 , S.Yu. Smirnov110 , Y. Smirnov110 , L.N. Smirnova111 , O. Smirnova94 , J.W. Smith51 , M.N.K. Smith38 , R.W. Smith38 , M. Smizanska87 , K. Smolek138 , A. Smykiewicz82 , A.A. Snesarev108 , I.M. Snyder127 , S. Snyder29 , R. Sobie173,ac , A.M. Soffa168 , A. Soffer158 , A. Søgaard48 , D.A. Soh155 , G. Sokhrannyi89 , C.A. Solans Sanchez35 , M. Solar138 , E.Yu. Soldatov110 , U. Soldevila171 , A.A. Solodkov140 , A. Soloshenko77 , O.V. Solovyanov140 , V. Solovyev134 , P. Sommer146 , H. Son167 , W. Song141 , A. Sopczak138 , F. Sopkova28b , D. Sosa59b , C.L. Sotiropoulou69a,69b , S. Sottocornola68a,68b , R. Soualah64a,64c,h , A.M. Soukharev120b,120a , D. South44 , B.C. Sowden91 , S. Spagnolo65a,65b , M. Spalla113 , M. Spangenberg175 , F. Span`o91 , D. Sperlich19 , F. Spettel113 , T.M. Spieker59a , R. Spighi23b , G. Spigo35 , L.A. Spiller102 , D.P. Spiteri55 , M. Spousta139 , A. Stabile66a,66b , R. Stamen59a , S. Stamm19 , E. Stanecka82 , R.W. Stanek6 , C. Stanescu72a , B. Stanislaus131 , M.M. Stanitzki44 , B. Stapf118 , S. Stapnes130 , E.A. Starchenko140 , G.H. Stark36 , J. Stark56 , S.H Stark39 , P. Staroba137 , P. Starovoitov59a , S. St¨ arz35 , R. Staszewski82 , M. Stegler44 , P. Steinberg29 , B. Stelzer149 , H.J. Stelzer35 , O. Stelzer-Chilton165a , H. Stenzel54 , T.J. Stevenson90 , G.A. Stewart55 , M.C. Stockton127 , G. Stoicea27b , P. Stolte51 , S. Stonjek113 , A. Straessner46 , J. Strandberg151 , S. Strandberg43a,43b ,
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M. Strauss124 , P. Strizenec28b , R. Str¨ohmer174 , D.M. Strom127 , R. Stroynowski41 , A. Strubig48 , S.A. Stucci29 , B. Stugu17 , J. Stupak124 , N.A. Styles44 , D. Su150 , J. Su135 , S. Suchek59a , Y. Sugaya129 , M. Suk138 , V.V. Sulin108 , D.M.S. Sultan52 , S. Sultansoy4c , T. Sumida83 , S. Sun103 , X. Sun3 , K. Suruliz153 , C.J.E. Suster154 , M.R. Sutton153 , S. Suzuki79 , M. Svatos137 , M. Swiatlowski36 , S.P. Swift2 , A. Sydorenko97 , I. Sykora28a , T. Sykora139 , D. Ta97 , K. Tackmann44,z , J. Taenzer158 , A. Taffard168 , R. Tafirout165a , E. Tahirovic90 , N. Taiblum158 , H. Takai29 , R. Takashima84 , E.H. Takasugi113 , K. Takeda80 , T. Takeshita147 , Y. Takubo79 , M. Talby99 , A.A. Talyshev120b,120a , J. Tanaka160 , M. Tanaka162 , R. Tanaka128 , R. Tanioka80 , B.B. Tannenwald122 , S. Tapia Araya144b , S. Tapprogge97 , A. Tarek Abouelfadl Mohamed132 , S. Tarem157 , G. Tarna27b,d , G.F. Tartarelli66a , P. Tas139 , M. Tasevsky137 , T. Tashiro83 , E. Tassi40b,40a , A. Tavares Delgado136a,136b , Y. Tayalati34e , A.C. Taylor116 , A.J. Taylor48 , G.N. Taylor102 , P.T.E. Taylor102 , W. Taylor165b , A.S. Tee87 , P. Teixeira-Dias91 , H. Ten Kate35 , P.K. Teng155 , J.J. Teoh118 , F. Tepel179 , S. Terada79 , K. Terashi160 , J. Terron96 , S. Terzo14 , M. Testa49 , R.J. Teuscher164,ac , S.J. Thais180 , T. Theveneaux-Pelzer44 , F. Thiele39 , D.W. Thomas91 , J.P. Thomas21 , A.S. Thompson55 , P.D. Thompson21 , L.A. Thomsen180 , E. Thomson133 , Y. Tian38 , R.E. Ticse Torres51 , V.O. Tikhomirov108,al , Yu.A. Tikhonov120b,120a , S. Timoshenko110 , P. Tipton180 , S. Tisserant99 , K. Todome162 , S. Todorova-Nova5 , S. Todt46 , J. Tojo85 , S. Tok´ar28a , K. Tokushuku79 , E. Tolley122 , K.G. Tomiwa32c , M. Tomoto115 , L. Tompkins150,p , K. Toms116 , B. Tong57 , P. Tornambe50 , E. Torrence127 , H. Torres46 , E. Torr´ o Pastor145 , C. Tosciri131 , J. Toth99,ab , F. Touchard99 , D.R. Tovey146 , C.J. Treado121 , T. Trefzger174 , F. Tresoldi153 , A. Tricoli29 , I.M. Trigger165a , S. Trincaz-Duvoid132 , M.F. Tripiana14 , W. Trischuk164 , B. Trocm´e56 , A. Trofymov128 , C. Troncon66a , M. Trovatelli173 , F. Trovato153 , L. Truong32b , M. Trzebinski82 , A. Trzupek82 , F. Tsai44 , J.C-L. Tseng131 , P.V. Tsiareshka105 , N. Tsirintanis9 , V. Tsiskaridze152 , E.G. Tskhadadze156a , I.I. Tsukerman109 , V. Tsulaia18 , S. Tsuno79 , D. Tsybychev152 , Y. Tu61b , A. Tudorache27b , V. Tudorache27b , T.T. Tulbure27a , A.N. Tuna57 , S. Turchikhin77 , D. Turgeman177 , I. Turk Cakir4b,t , R. Turra66a , P.M. Tuts38 , E. Tzovara97 , G. Ucchielli23b,23a , I. Ueda79 , M. Ughetto43a,43b , F. Ukegawa166 , G. Unal35 , A. Undrus29 , G. Unel168 , F.C. Ungaro102 , Y. Unno79 , K. Uno160 , J. Urban28b , P. Urquijo102 , P. Urrejola97 , G. Usai8 , J. Usui79 , L. Vacavant99 , V. Vacek138 , B. Vachon101 , K.O.H. Vadla130 , A. Vaidya92 , C. Valderanis112 , E. Valdes Santurio43a,43b , M. Valente52 , S. Valentinetti23b,23a , A. Valero171 , L. Val´ery44 , R.A. Vallance21 , A. Vallier5 , J.A. Valls Ferrer171 , T.R. Van Daalen14 , W. Van Den Wollenberg118 , H. Van der Graaf118 , P. Van Gemmeren6 , J. Van Nieuwkoop149 , I. Van Vulpen118 , M. Vanadia71a,71b , W. Vandelli35 , A. Vaniachine163 , P. Vankov118 , R. Vari70a , E.W. Varnes7 , C. Varni53b,53a , T. Varol41 , D. Varouchas128 , K.E. Varvell154 , G.A. Vasquez144b , J.G. Vasquez180 , F. Vazeille37 , D. Vazquez Furelos14 , T. Vazquez Schroeder101 , J. Veatch51 , V. Vecchio72a,72b , L.M. Veloce164 , F. Veloso136a,136c , S. Veneziano70a , A. Ventura65a,65b , M. Venturi173 , N. Venturi35 , V. Vercesi68a , M. Verducci72a,72b , C.M. Vergel Infante76 , W. Verkerke118 , A.T. Vermeulen118 , J.C. Vermeulen118 , M.C. Vetterli149,as , N. Viaux Maira144b , M. Vicente Barreto Pinto52 , I. Vichou170,∗ , T. Vickey146 , O.E. Vickey Boeriu146 , G.H.A. Viehhauser131 , S. Viel18 , L. Vigani131 , M. Villa23b,23a , M. Villaplana Perez66a,66b , E. Vilucchi49 , M.G. Vincter33 , V.B. Vinogradov77 , A. Vishwakarma44 , C. Vittori23b,23a , I. Vivarelli153 , S. Vlachos10 , M. Vogel179 , P. Vokac138 , G. Volpi14 , S.E. von Buddenbrock32c , E. Von Toerne24 , V. Vorobel139 , K. Vorobev110 , M. Vos171 , J.H. Vossebeld88 , N. Vranjes16 , M. Vranjes Milosavljevic16 , V. Vrba138 , M. Vreeswijk118 , 89 ˇ ˇ s28a , L. Zivkovi´ ˇ T. Sfiligoj , R. Vuillermet35 , I. Vukotic36 , T. Zeniˇ c16 , P. Wagner24 , W. Wagner179 , 112 86 46 J. Wagner-Kuhr , H. Wahlberg , S. Wahrmund , K. Wakamiya80 , V.M. Walbrecht113 , J. Walder87 , R. Walker112 , S.D. Walker91 , W. Walkowiak148 , V. Wallangen43a,43b , A.M. Wang57 , C. Wang58b,d , F. Wang178 , H. Wang18 , H. Wang3 , J. Wang154 , J. Wang59b , P. Wang41 ,
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Department of Physics, University of Adelaide, Adelaide; Australia. Physics Department, SUNY Albany, Albany NY; United States of America. Department of Physics, University of Alberta, Edmonton AB; Canada. (a) Department of Physics, Ankara University, Ankara;(b) Istanbul Aydin University, Istanbul;(c) Division of Physics, TOBB University of Economics and Technology, Ankara; Turkey. LAPP, Universit´e Grenoble Alpes, Universit´e Savoie Mont Blanc, CNRS/IN2P3, Annecy; France. High Energy Physics Division, Argonne National Laboratory, Argonne IL; United States of America. Department of Physics, University of Arizona, Tucson AZ; United States of America. Department of Physics, University of Texas at Arlington, Arlington TX; United States of America. Physics Department, National and Kapodistrian University of Athens, Athens; Greece. Physics Department, National Technical University of Athens, Zografou; Greece. Department of Physics, University of Texas at Austin, Austin TX; United States of America. (a) Bahcesehir University, Faculty of Engineering and Natural Sciences, Istanbul; (b) Istanbul Bilgi University, Faculty of Engineering and Natural Sciences, Istanbul;(c) Department of Physics, Bogazici University, Istanbul;(d) Department of Physics Engineering, Gaziantep University, Gaziantep; Turkey. Institute of Physics, Azerbaijan Academy of Sciences, Baku; Azerbaijan.
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Q. Wang124 , R.-J. Wang132 , R. Wang58a , R. Wang6 , S.M. Wang155 , W.T. Wang58a , W. Wang15c,ad , W.X. Wang58a,ad , Y. Wang58a , Z. Wang58c , C. Wanotayaroj44 , A. Warburton101 , C.P. Ward31 , D.R. Wardrope92 , A. Washbrook48 , P.M. Watkins21 , A.T. Watson21 , M.F. Watson21 , G. Watts145 , S. Watts98 , B.M. Waugh92 , A.F. Webb11 , S. Webb97 , C. Weber180 , M.S. Weber20 , S.A. Weber33 , S.M. Weber59a , A.R. Weidberg131 , B. Weinert63 , J. Weingarten51 , M. Weirich97 , C. Weiser50 , P.S. Wells35 , T. Wenaus29 , T. Wengler35 , S. Wenig35 , N. Wermes24 , M.D. Werner76 , P. Werner35 , M. Wessels59a , T.D. Weston20 , K. Whalen127 , N.L. Whallon145 , A.M. Wharton87 , A.S. White103 , A. White8 , M.J. White1 , R. White144b , D. Whiteson168 , B.W. Whitmore87 , F.J. Wickens141 , W. Wiedenmann178 , M. Wielers141 , C. Wiglesworth39 , L.A.M. Wiik-Fuchs50 , A. Wildauer113 , F. Wilk98 , H.G. Wilkens35 , L.J. Wilkins91 , H.H. Williams133 , S. Williams31 , C. Willis104 , S. Willocq100 , J.A. Wilson21 , I. Wingerter-Seez5 , E. Winkels153 , F. Winklmeier127 , O.J. Winston153 , B.T. Winter24 , M. Wittgen150 , M. Wobisch93 , A. Wolf97 , T.M.H. Wolf118 , R. Wolff99 , M.W. Wolter82 , H. Wolters136a,136c , V.W.S. Wong172 , N.L. Woods143 , S.D. Worm21 , B.K. Wosiek82 , K.W. Wo´zniak82 , K. Wraight55 , M. Wu36 , S.L. Wu178 , X. Wu52 , Y. Wu58a , T.R. Wyatt98 , B.M. Wynne48 , S. Xella39 , Z. Xi103 , L. Xia175 , D. Xu15a , H. Xu58a , L. Xu29 , T. Xu142 , W. Xu103 , B. Yabsley154 , S. Yacoob32a , K. Yajima129 , D.P. Yallup92 , D. Yamaguchi162 , Y. Yamaguchi162 , A. Yamamoto79 , T. Yamanaka160 , F. Yamane80 , M. Yamatani160 , T. Yamazaki160 , Y. Yamazaki80 , Z. Yan25 , H.J. Yang58c,58d , H.T. Yang18 , S. Yang75 , X. Yang58b , Y. Yang160 , Z. Yang17 , W-M. Yao18 , Y.C. Yap44 , Y. Yasu79 , E. Yatsenko58c,58d , J. Ye41 , S. Ye29 , I. Yeletskikh77 , E. Yigitbasi25 , E. Yildirim97 , K. Yorita176 , K. Yoshihara133 , C.J.S. Young35 , C. Young150 , J. Yu8 , J. Yu76 , X. Yue59a , S.P.Y. Yuen24 , B. Zabinski82 , G. Zacharis10 , E. Zaffaroni52 , R. Zaidan14 , A.M. Zaitsev140,ak , N. Zakharchuk44 , J. Zalieckas17 , S. Zambito57 , D. Zanzi35 , D.R. Zaripovas55 , S.V. Zeißner45 , C. Zeitnitz179 , G. Zemaityte131 , J.C. Zeng170 , Q. Zeng150 , O. Zenin140 , D. Zerwas128 , M. Zgubiˇc131 , D.F. Zhang58b , D. Zhang103 , F. Zhang178 , G. Zhang58a , H. Zhang15c , J. Zhang6 , L. Zhang15c , L. Zhang58a , M. Zhang170 , P. Zhang15c , R. Zhang58a , R. Zhang24 , X. Zhang58b , Y. Zhang15d , Z. Zhang128 , P. Zhao47 , X. Zhao41 , Y. Zhao58b,128,ah , Z. Zhao58a , A. Zhemchugov77 , B. Zhou103 , C. Zhou178 , L. Zhou41 , M.S. Zhou15d , M. Zhou152 , N. Zhou58c , Y. Zhou7 , C.G. Zhu58b , H.L. Zhu58a , H. Zhu15a , J. Zhu103 , Y. Zhu58a , X. Zhuang15a , K. Zhukov108 , V. Zhulanov120b,120a , A. Zibell174 , D. Zieminska63 , N.I. Zimine77 , S. Zimmermann50 , Z. Zinonos113 , M. Zinser97 , M. Ziolkowski148 , G. Zobernig178 , A. Zoccoli23b,23a , K. Zoch51 , T.G. Zorbas146 , R. Zou36 , M. Zur Nedden19 and L. Zwalinski35
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Institut de F´ısica d’Altes Energies (IFAE), Barcelona Institute of Science and Technology, Barcelona; Spain. (a) Institute of High Energy Physics, Chinese Academy of Sciences, Beijing;(b) Physics Department, Tsinghua University, Beijing;(c) Department of Physics, Nanjing University, Nanjing;(d) University of Chinese Academy of Science (UCAS), Beijing; China. Institute of Physics, University of Belgrade, Belgrade; Serbia. Department for Physics and Technology, University of Bergen, Bergen; Norway. Physics Division, Lawrence Berkeley National Laboratory and University of California, Berkeley CA; United States of America. Institut f¨ ur Physik, Humboldt Universit¨ at zu Berlin, Berlin; Germany. Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics, University of Bern, Bern; Switzerland. School of Physics and Astronomy, University of Birmingham, Birmingham; United Kingdom. Centro de Investigaci´ ones, Universidad Antonio Nari˜ no, Bogota; Colombia. (a) Dipartimento di Fisica e Astronomia, Universit` a di Bologna, Bologna; (b) INFN Sezione di Bologna; Italy. Physikalisches Institut, Universit¨ at Bonn, Bonn; Germany. Department of Physics, Boston University, Boston MA; United States of America. Department of Physics, Brandeis University, Waltham MA; United States of America. (a) Transilvania University of Brasov, Brasov;(b) Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest;(c) Department of Physics, Alexandru Ioan Cuza University of Iasi, Iasi;(d) National Institute for Research and Development of Isotopic and Molecular Technologies, Physics Department, Cluj-Napoca;(e) University Politehnica Bucharest, Bucharest;(f ) West University in Timisoara, Timisoara; Romania. (a) Faculty of Mathematics, Physics and Informatics, Comenius University, Bratislava;(b) Department of Subnuclear Physics, Institute of Experimental Physics of the Slovak Academy of Sciences, Kosice; Slovak Republic. Physics Department, Brookhaven National Laboratory, Upton NY; United States of America. Departamento de F´ısica, Universidad de Buenos Aires, Buenos Aires; Argentina. Cavendish Laboratory, University of Cambridge, Cambridge; United Kingdom. (a) Department of Physics, University of Cape Town, Cape Town;(b) Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg;(c) School of Physics, University of the Witwatersrand, Johannesburg; South Africa. Department of Physics, Carleton University, Ottawa ON; Canada. (a) Facult´e des Sciences Ain Chock, R´eseau Universitaire de Physique des Hautes Energies Universit´e Hassan II, Casablanca;(b) Centre National de l’Energie des Sciences Techniques Nucleaires (CNESTEN), Rabat;(c) Facult´e des Sciences Semlalia, Universit´e Cadi Ayyad, LPHEA-Marrakech;(d) Facult´e des Sciences, Universit´e Mohamed Premier and LPTPM, Oujda;(e) Facult´e des sciences, Universit´e Mohammed V, Rabat; Morocco. CERN, Geneva; Switzerland. Enrico Fermi Institute, University of Chicago, Chicago IL; United States of America. LPC, Universit´e Clermont Auvergne, CNRS/IN2P3, Clermont-Ferrand; France. Nevis Laboratory, Columbia University, Irvington NY; United States of America. Niels Bohr Institute, University of Copenhagen, Copenhagen; Denmark. (a) Dipartimento di Fisica, Universit` a della Calabria, Rende;(b) INFN Gruppo Collegato di Cosenza, Laboratori Nazionali di Frascati; Italy. Physics Department, Southern Methodist University, Dallas TX; United States of America. Physics Department, University of Texas at Dallas, Richardson TX; United States of America. (a) Department of Physics, Stockholm University;(b) Oskar Klein Centre, Stockholm; Sweden. Deutsches Elektronen-Synchrotron DESY, Hamburg and Zeuthen; Germany. Lehrstuhl f¨ ur Experimentelle Physik IV, Technische Universit¨ at Dortmund, Dortmund; Germany. Institut f¨ ur Kern- und Teilchenphysik, Technische Universit¨ at Dresden, Dresden; Germany.
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Department of Physics, Duke University, Durham NC; United States of America. SUPA - School of Physics and Astronomy, University of Edinburgh, Edinburgh; United Kingdom. INFN e Laboratori Nazionali di Frascati, Frascati; Italy. Physikalisches Institut, Albert-Ludwigs-Universit¨ at Freiburg, Freiburg; Germany. II. Physikalisches Institut, Georg-August-Universit¨ at G¨ ottingen, G¨ ottingen; Germany. D´epartement de Physique Nucl´eaire et Corpusculaire, Universit´e de Gen`eve, Gen`eve; Switzerland. (a) Dipartimento di Fisica, Universit` a di Genova, Genova;(b) INFN Sezione di Genova; Italy. II. Physikalisches Institut, Justus-Liebig-Universit¨ at Giessen, Giessen; Germany. SUPA - School of Physics and Astronomy, University of Glasgow, Glasgow; United Kingdom. LPSC, Universit´e Grenoble Alpes, CNRS/IN2P3, Grenoble INP, Grenoble; France. Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge MA; United States of America. (a) Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei;(b) Institute of Frontier and Interdisciplinary Science and Key Laboratory of Particle Physics and Particle Irradiation (MOE), Shandong University, Qingdao;(c) School of Physics and Astronomy, Shanghai Jiao Tong University, KLPPAC-MoE, SKLPPC, Shanghai;(d) Tsung-Dao Lee Institute, Shanghai; China. (a) Kirchhoff-Institut f¨ ur Physik, Ruprecht-Karls-Universit¨ at Heidelberg, Heidelberg; (b) Physikalisches Institut, Ruprecht-Karls-Universit¨ at Heidelberg, Heidelberg; Germany. Faculty of Applied Information Science, Hiroshima Institute of Technology, Hiroshima; Japan. (a) Department of Physics, Chinese University of Hong Kong, Shatin, N.T., Hong Kong;(b) Department of Physics, University of Hong Kong, Hong Kong;(c) Department of Physics and Institute for Advanced Study, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong; China. Department of Physics, National Tsing Hua University, Hsinchu; Taiwan. Department of Physics, Indiana University, Bloomington IN; United States of America. (a) INFN Gruppo Collegato di Udine, Sezione di Trieste, Udine;(b) ICTP, Trieste;(c) Dipartimento di Chimica, Fisica e Ambiente, Universit` a di Udine, Udine; Italy. (a) INFN Sezione di Lecce;(b) Dipartimento di Matematica e Fisica, Universit` a del Salento, Lecce; Italy. (a) INFN Sezione di Milano;(b) Dipartimento di Fisica, Universit` a di Milano, Milano; Italy. (a) INFN Sezione di Napoli;(b) Dipartimento di Fisica, Universit` a di Napoli, Napoli; Italy. (a) INFN Sezione di Pavia;(b) Dipartimento di Fisica, Universit` a di Pavia, Pavia; Italy. (a) INFN Sezione di Pisa;(b) Dipartimento di Fisica E. Fermi, Universit` a di Pisa, Pisa; Italy. (a) INFN Sezione di Roma;(b) Dipartimento di Fisica, Sapienza Universit` a di Roma, Roma; Italy. (a) INFN Sezione di Roma Tor Vergata;(b) Dipartimento di Fisica, Universit` a di Roma Tor Vergata, Roma; Italy. (a) INFN Sezione di Roma Tre;(b) Dipartimento di Matematica e Fisica, Universit` a Roma Tre, Roma; Italy. (a) INFN-TIFPA;(b) Universit` a degli Studi di Trento, Trento; Italy. Institut f¨ ur Astro- und Teilchenphysik, Leopold-Franzens-Universit¨ at, Innsbruck; Austria. University of Iowa, Iowa City IA; United States of America. Department of Physics and Astronomy, Iowa State University, Ames IA; United States of America. Joint Institute for Nuclear Research, Dubna; Russia. (a) Departamento de Engenharia El´etrica, Universidade Federal de Juiz de Fora (UFJF), Juiz de Fora;(b) Universidade Federal do Rio De Janeiro COPPE/EE/IF, Rio de Janeiro; (c) Universidade Federal de S˜ ao Jo˜ ao del Rei (UFSJ), S˜ ao Jo˜ ao del Rei;(d) Instituto de F´ısica, Universidade de S˜ ao Paulo, S˜ ao Paulo; Brazil. KEK, High Energy Accelerator Research Organization, Tsukuba; Japan. Graduate School of Science, Kobe University, Kobe; Japan. (a) AGH University of Science and Technology, Faculty of Physics and Applied Computer Science, Krakow;(b) Marian Smoluchowski Institute of Physics, Jagiellonian University, Krakow; Poland.
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90
Institute of Nuclear Physics Polish Academy of Sciences, Krakow; Poland. Faculty of Science, Kyoto University, Kyoto; Japan. Kyoto University of Education, Kyoto; Japan. Research Center for Advanced Particle Physics and Department of Physics, Kyushu University, Fukuoka; Japan. Instituto de F´ısica La Plata, Universidad Nacional de La Plata and CONICET, La Plata; Argentina. Physics Department, Lancaster University, Lancaster; United Kingdom. Oliver Lodge Laboratory, University of Liverpool, Liverpool; United Kingdom. Department of Experimental Particle Physics, Joˇzef Stefan Institute and Department of Physics, University of Ljubljana, Ljubljana; Slovenia. School of Physics and Astronomy, Queen Mary University of London, London; United Kingdom. Department of Physics, Royal Holloway University of London, Egham; United Kingdom. Department of Physics and Astronomy, University College London, London; United Kingdom. Louisiana Tech University, Ruston LA; United States of America. Fysiska institutionen, Lunds universitet, Lund; Sweden. Centre de Calcul de l’Institut National de Physique Nucl´eaire et de Physique des Particules (IN2P3), Villeurbanne; France. Departamento de F´ısica Teorica C-15 and CIAFF, Universidad Aut´ onoma de Madrid, Madrid; Spain. Institut f¨ ur Physik, Universit¨ at Mainz, Mainz; Germany. School of Physics and Astronomy, University of Manchester, Manchester; United Kingdom. CPPM, Aix-Marseille Universit´e, CNRS/IN2P3, Marseille; France. Department of Physics, University of Massachusetts, Amherst MA; United States of America. Department of Physics, McGill University, Montreal QC; Canada. School of Physics, University of Melbourne, Victoria; Australia. Department of Physics, University of Michigan, Ann Arbor MI; United States of America. Department of Physics and Astronomy, Michigan State University, East Lansing MI; United States of America. B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk; Belarus. Research Institute for Nuclear Problems of Byelorussian State University, Minsk; Belarus. Group of Particle Physics, University of Montreal, Montreal QC; Canada. P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow; Russia. Institute for Theoretical and Experimental Physics (ITEP), Moscow; Russia. National Research Nuclear University MEPhI, Moscow; Russia. D.V. Skobeltsyn Institute of Nuclear Physics, M.V. Lomonosov Moscow State University, Moscow; Russia. Fakult¨ at f¨ ur Physik, Ludwig-Maximilians-Universit¨ at M¨ unchen, M¨ unchen; Germany. Max-Planck-Institut f¨ ur Physik (Werner-Heisenberg-Institut), M¨ unchen; Germany. Nagasaki Institute of Applied Science, Nagasaki; Japan. Graduate School of Science and Kobayashi-Maskawa Institute, Nagoya University, Nagoya; Japan. Department of Physics and Astronomy, University of New Mexico, Albuquerque NM; United States of America. Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen; Netherlands. Nikhef National Institute for Subatomic Physics and University of Amsterdam, Amsterdam; Netherlands. Department of Physics, Northern Illinois University, DeKalb IL; United States of America. (a) Budker Institute of Nuclear Physics, SB RAS, Novosibirsk;(b) Novosibirsk State University Novosibirsk; Russia. Department of Physics, New York University, New York NY; United States of America. Ohio State University, Columbus OH; United States of America.
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133
Faculty of Science, Okayama University, Okayama; Japan. Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman OK; United States of America. Department of Physics, Oklahoma State University, Stillwater OK; United States of America. Palack´ y University, RCPTM, Joint Laboratory of Optics, Olomouc; Czech Republic. Center for High Energy Physics, University of Oregon, Eugene OR; United States of America. LAL, Universit´e Paris-Sud, CNRS/IN2P3, Universit´e Paris-Saclay, Orsay; France. Graduate School of Science, Osaka University, Osaka; Japan. Department of Physics, University of Oslo, Oslo; Norway. Department of Physics, Oxford University, Oxford; United Kingdom. LPNHE, Sorbonne Universit´e, Paris Diderot Sorbonne Paris Cit´e, CNRS/IN2P3, Paris; France. Department of Physics, University of Pennsylvania, Philadelphia PA; United States of America. Konstantinov Nuclear Physics Institute of National Research Centre “Kurchatov Institute”, PNPI, St. Petersburg; Russia. Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh PA; United States of America. (a) Laborat´ orio de Instrumenta¸ca ˜o e F´ısica Experimental de Part´ıculas - LIP; (b) Departamento de F´ısica, Faculdade de Ciˆencias, Universidade de Lisboa, Lisboa; (c) Departamento de F´ısica, Universidade de Coimbra, Coimbra;(d) Centro de F´ısica Nuclear da Universidade de Lisboa, Lisboa;(e) Departamento de F´ısica, Universidade do Minho, Braga;(f ) Departamento de F´ısica Teorica y del Cosmos, Universidad de Granada, Granada (Spain); (g) Dep F´ısica and CEFITEC of Faculdade de Ciˆencias e Tecnologia, Universidade Nova de Lisboa, Caparica; Portugal. Institute of Physics, Academy of Sciences of the Czech Republic, Prague; Czech Republic. Czech Technical University in Prague, Prague; Czech Republic. Charles University, Faculty of Mathematics and Physics, Prague; Czech Republic. State Research Center Institute for High Energy Physics, NRC KI, Protvino; Russia. Particle Physics Department, Rutherford Appleton Laboratory, Didcot; United Kingdom. IRFU, CEA, Universit´e Paris-Saclay, Gif-sur-Yvette; France. Santa Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz CA; United States of America. (a) Departamento de F´ısica, Pontificia Universidad Cat´ olica de Chile, Santiago; (b) Departamento de F´ısica, Universidad T´ecnica Federico Santa Mar´ıa, Valpara´ıso; Chile. Department of Physics, University of Washington, Seattle WA; United States of America. Department of Physics and Astronomy, University of Sheffield, Sheffield; United Kingdom. Department of Physics, Shinshu University, Nagano; Japan. Department Physik, Universit¨ at Siegen, Siegen; Germany. Department of Physics, Simon Fraser University, Burnaby BC; Canada. SLAC National Accelerator Laboratory, Stanford CA; United States of America. Physics Department, Royal Institute of Technology, Stockholm; Sweden. Departments of Physics and Astronomy, Stony Brook University, Stony Brook NY; United States of America. Department of Physics and Astronomy, University of Sussex, Brighton; United Kingdom. School of Physics, University of Sydney, Sydney; Australia. Institute of Physics, Academia Sinica, Taipei; Taiwan. (a) E. Andronikashvili Institute of Physics, Iv. Javakhishvili Tbilisi State University, Tbilisi; (b) High Energy Physics Institute, Tbilisi State University, Tbilisi; Georgia. Department of Physics, Technion, Israel Institute of Technology, Haifa; Israel. Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv University, Tel Aviv; Israel. Department of Physics, Aristotle University of Thessaloniki, Thessaloniki; Greece. International Center for Elementary Particle Physics and Department of Physics, University of Tokyo, Tokyo; Japan.
161 162 163 164 165
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Also at Borough of Manhattan Community College, City University of New York, NY; United States of America. Also at Centre for High Performance Computing, CSIR Campus, Rosebank, Cape Town; South Africa. Also at CERN, Geneva; Switzerland. Also at CPPM, Aix-Marseille Universit´e, CNRS/IN2P3, Marseille; France. Also at D´epartement de Physique Nucl´eaire et Corpusculaire, Universit´e de Gen`eve, Gen`eve; Switzerland. Also at Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona; Spain. Also at Departamento de F´ısica Teorica y del Cosmos, Universidad de Granada, Granada (Spain); Spain. Also at Department of Applied Physics and Astronomy, University of Sharjah, Sharjah; United Arab Emirates. Also at Department of Financial and Management Engineering, University of the Aegean, Chios; Greece. Also at Department of Physics and Astronomy, University of Louisville, Louisville, KY; United States of America. Also at Department of Physics and Astronomy, University of Sheffield, Sheffield; United Kingdom. Also at Department of Physics, California State University, Fresno CA; United States of America. Also at Department of Physics, California State University, Sacramento CA; United States of America. Also at Department of Physics, King’s College London, London; United Kingdom. Also at Department of Physics, St. Petersburg State Polytechnical University, St. Petersburg; Russia.
– 53 –
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169
Graduate School of Science and Technology, Tokyo Metropolitan University, Tokyo; Japan. Department of Physics, Tokyo Institute of Technology, Tokyo; Japan. Tomsk State University, Tomsk; Russia. Department of Physics, University of Toronto, Toronto ON; Canada. (a) TRIUMF, Vancouver BC;(b) Department of Physics and Astronomy, York University, Toronto ON; Canada. Division of Physics and Tomonaga Center for the History of the Universe, Faculty of Pure and Applied Sciences, University of Tsukuba, Tsukuba; Japan. Department of Physics and Astronomy, Tufts University, Medford MA; United States of America. Department of Physics and Astronomy, University of California Irvine, Irvine CA; United States of America. Department of Physics and Astronomy, University of Uppsala, Uppsala; Sweden. Department of Physics, University of Illinois, Urbana IL; United States of America. Instituto de F´ısica Corpuscular (IFIC), Centro Mixto Universidad de Valencia - CSIC, Valencia; Spain. Department of Physics, University of British Columbia, Vancouver BC; Canada. Department of Physics and Astronomy, University of Victoria, Victoria BC; Canada. Fakult¨ at f¨ ur Physik und Astronomie, Julius-Maximilians-Universit¨ at W¨ urzburg, W¨ urzburg; Germany. Department of Physics, University of Warwick, Coventry; United Kingdom. Waseda University, Tokyo; Japan. Department of Particle Physics, Weizmann Institute of Science, Rehovot; Israel. Department of Physics, University of Wisconsin, Madison WI; United States of America. Fakult¨ at f¨ ur Mathematik und Naturwissenschaften, Fachgruppe Physik, Bergische Universit¨ at Wuppertal, Wuppertal; Germany. Department of Physics, Yale University, New Haven CT; United States of America. Yerevan Physics Institute, Yerevan; Armenia.
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as at
– 54 –
JHEP11(2018)085
aa
Also at Department of Physics, Stanford University; United States of America. Also at Department of Physics, University of Fribourg, Fribourg; Switzerland. Also at Department of Physics, University of Michigan, Ann Arbor MI; United States of America. Also at Dipartimento di Fisica E. Fermi, Universit` a di Pisa, Pisa; Italy. Also at Giresun University, Faculty of Engineering, Giresun; Turkey. Also at Graduate School of Science, Osaka University, Osaka; Japan. Also at Hellenic Open University, Patras; Greece. Also at Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest; Romania. Also at II. Physikalisches Institut, Georg-August-Universit¨ at G¨ ottingen, G¨ ottingen; Germany. Also at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona; Spain. Also at Institut f¨ ur Experimentalphysik, Universit¨ at Hamburg, Hamburg; Germany. Also at Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen; Netherlands. Also at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest; Hungary. Also at Institute of Particle Physics (IPP); Canada. Also at Institute of Physics, Academia Sinica, Taipei; Taiwan. Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku; Azerbaijan. Also at Institute of Theoretical Physics, Ilia State University, Tbilisi; Georgia. Also at Istanbul University, Dept. of Physics, Istanbul; Turkey. Also at LAL, Universit´e Paris-Sud, CNRS/IN2P3, Universit´e Paris-Saclay, Orsay; France. Also at Louisiana Tech University, Ruston LA; United States of America. Also at Manhattan College, New York NY; United States of America. Also at Moscow Institute of Physics and Technology State University, Dolgoprudny; Russia. Also at National Research Nuclear University MEPhI, Moscow; Russia. Also at Near East University, Nicosia, North Cyprus, Mersin; Turkey. Also at Physikalisches Institut, Albert-Ludwigs-Universit¨ at Freiburg, Freiburg; Germany. Also at School of Physics, Sun Yat-sen University, Guangzhou; China. Also at The City College of New York, New York NY; United States of America. Also at The Collaborative Innovation Center of Quantum Matter (CICQM), Beijing; China. Also at Tomsk State University, Tomsk, and Moscow Institute of Physics and Technology State University, Dolgoprudny; Russia. Also at TRIUMF, Vancouver BC; Canada. Also at Universita di Napoli Parthenope, Napoli; Italy. ∗ Deceased
