Published for SISSA by Springer Received: February 20, 2019 Accepted: April 29, 2019 Published: May 16, 2019 Combinations of single-top-quark production cross-section measurements and |fLV Vtb| √ determinations at s = 7 and 8 TeV with the ATLAS JHEP05(2019)088 and CMS experiments The ATLAS and CMS collaborations E-mail: atlas.publications@cern.ch, cms-publication-committee-chair@cern.ch Abstract: This paper presents the combinations of single-top-quark production cross- section measurements by the ATLAS and CMS Collaborations, using data from LHC √ proton–proton collisions at s = 7 and 8 TeV corresponding to integrated luminosities √ √ of 1.17 to 5.1 fb−1 at s = 7 TeV and 12.2 to 20.3 fb−1 at s = 8 TeV. These com- binations are performed per centre-of-mass energy and for each production mode: t- channel, tW , and s-channel. The combined t-channel cross-sections are 67.5 ± 5.7 pb √ and 87.7 ± 5.8 pb at s = 7 and 8 TeV respectively. The combined tW cross-sections √ are 16.3 ± 4.1 pb and 23.1 ± 3.6 pb at s = 7 and 8 TeV respectively. For the s- √ channel cross-section, the combination yields 4.9 ± 1.4 pb at s = 8 TeV. The square of the magnitude of the CKM matrix element Vtb multiplied by a form factor fLV is de- termined for each production mode and centre-of-mass energy, using the ratio of the mea- sured cross-section to its theoretical prediction. It is assumed that the top-quark-related CKM matrix elements obey the relation |Vtd |, |Vts |  |Vtb |. All the |fLV Vtb |2 determina- √ tions, extracted from individual ratios at s = 7 and 8 TeV, are combined, resulting in |fLV Vtb | = 1.02 ± 0.04 (meas.) ± 0.02 (theo.). All combined measurements are consistent with their corresponding Standard Model predictions. Keywords: Hadron-Hadron scattering (experiments) ArXiv ePrint: 1902.07158 Open Access, Copyright CERN, https://doi.org/10.1007/JHEP05(2019)088 for the benefit of the ATLAS-CMS Collaboration. Article funded by SCOAP3 . Contents 1 Introduction 1 2 Theoretical cross-section calculations 3 √ 3 Single-top-quark cross-section measurements at s = 7 and 8 TeV 5 4 Combination methodology 6 JHEP05(2019)088 5 Systematic uncertainties and correlation assumptions 7 5.1 Systematic uncertainties in measured cross-sections 7 5.2 Systematic uncertainties in theoretical cross-section predictions 16 6 Combinations of cross-section measurements 17 6.1 Combinations of t-channel cross-section measurements 17 6.2 Combinations of tW cross-section measurements 18 6.3 Combination of s-channel cross-section measurements 20 6.4 Summary of cross-section combinations 21 7 Combinations of |fLV Vtb | determinations 21 7.1 Results 23 7.2 Stability tests 26 8 Summary 28 A Systematic uncertainties in cross-section measurements 29 A.1 Systematic uncertainties in t-channel cross-section measurements 29 A.2 Systematic uncertainties in tW cross-section measurements 31 A.3 Systematic uncertainties in s-channel cross-section measurements 34 The ATLAS collaboration 45 The CMS collaboration 62 1 Introduction Measurements of single-top-quark production via the electroweak interaction, a process first observed in proton–antiproton (pp̄) collisions at the Tevatron [1, 2], have entered the precision era at the Large Hadron Collider (LHC). It has become possible to measure top- quark properties using single-top-quark events [3]. Single-top-quark production is sensitive to new physics mechanisms [4] that either modify the tW b coupling [5–10] or introduce new –1– particles and interactions [11–16]. The production rate of single top quarks is proportional to the square of the left-handed coupling at the tW b production vertex, assuming that there are no significant tW d or tW s contributions. In the Standard Model (SM), this coupling is given by the Cabibbo-Kobayashi-Maskawa (CKM) [17, 18] matrix element Vtb . Indirect measurements of |Vtb |, from precision measurements of B-meson decays [19] and from top- quark decays [20–23], rely on the SM assumptions that the CKM matrix is unitary and that there are three quark generations. The most stringent indirect determination comes from a global fit to all available B-physics measurements, resulting in |Vtb | = 0.999105 ± 0.000032 [19]. This fit also assumes the absence of any new physics mechanisms that might affect b-quarks. The most precise indirect measurement using top-quark events was JHEP05(2019)088 performed by the CMS Collaboration in proton–proton (pp) collisions at a centre-of-mass √ energy of s = 7 TeV, resulting in |Vtb | = 1.007 ± 0.016 [23]. A direct estimate of the coupling at the tW b production vertex, |fLV Vtb |, is obtained from the measured single-top-quark cross-section σmeas. and its corresponding theoretical expectation σtheo. , r σmeas. |fLV Vtb | = . (1.1) σtheo. (Vtb = 1) The fLV term is a form factor, assumed to be real, that parameterises the possible presence of anomalous left-handed vector couplings [24]. By construction, this form factor is exactly one in the SM, while it can be different from one in models of new physics processes. The direct estimation assumes that |Vtd |, |Vts |  |Vtb | [25, 26], and that the tW b interaction involves a left-handed weak coupling, like that in the SM. The |fLV Vtb | determination via single-top-quark production is independent of assumptions about the number of quark gen- erations and the unitarity of the CKM matrix [4, 27–29]. Since the indirect determination of |Vtb | gives a value close to unity, Vtb is considered equal to one in theoretical calculations of the single-top-quark cross-section. The combination of single-top-quark measurements from the Tevatron gives |fLV Vtb | = 1.02+0.06 −0.05 [30]. Single-top-quark production at a hadron collider mostly proceeds, according to the SM prediction, via three modes that can be defined at leading order (LO) in perturbative quantum chromodynamics (QCD): the exchange of a virtual W boson in the t-channel or in the s-channel, and the associated production of a top quark and a W boson (tW ). Representative Feynman diagrams for these processes at LO are shown in figure 1. In pp collisions at the LHC, the process with the largest single-top-quark production cross-section is the t-channel, where a light-flavour quark q from one of the colliding protons interacts with a b-quark by exchanging a space-like virtual W boson, producing a top quark (t-quark) and a recoiling light-flavour quark q 0 , called the spectator quark. For t-channel production at LO, the b-quark can be considered as directly emitted from the other proton (five-flavour-number scheme or 5FS) or it can come from gluon splitting (four-flavour- number scheme or 4FS) [31]. The kinematic properties of the spectator quark provide distinctive features for this process [32, 33]. The associated production of a W boson and a top quark has the second-largest production cross-section. In a representative process of tW production, a gluon interacts with an initial b-quark by exchanging a virtual b-quark, –2– q q′ g W q b̄ b W W b t b t q̄ ′ t (a) (b) (c) Figure 1. Representative Feynman diagrams at LO in QCD and in the five-flavour-number scheme for single-top-quark production in (a) the t-channel, (b) tW production, and (c) the s-channel. JHEP05(2019)088 producing a t-quark and a W boson. The measurement of this process suffers from a large background from top-quark pair (tt̄) production [34, 35]. The s-channel cross-section is the smallest at the LHC. In this process, a quark–antiquark pair annihilates to produce a time-like virtual W boson, which decays to a t-quark and a b̄-quark. This process was observed in pp̄ collisions at the Tevatron [36] and evidence of it was reported by the ATLAS √ Collaboration in pp collisions at s = 8 TeV [37]. In this paper, the t-channel, tW , and s-channel single-top-quark cross-section measure- ments by the ATLAS and CMS experiments are combined for each production mode, sepa- rately at pp centre-of-mass energies of 7 and 8 TeV. A combined determination of |fLV Vtb | is also presented, using as inputs the values of |fLV Vtb |2 calculated from the measured and pre- √ dicted single-top-quark cross-sections in the three production modes at s = 7 and 8 TeV. Using the same approach, results are also shown for |fLV Vtb | combinations for each pro- duction mode. The theoretical cross-section calculations are described in section 2. Section 3 presents the cross-section measurements. The combination methodology is briefly described in sec- tion 4. Section 5 is devoted to a discussion of systematic uncertainties in the cross-section measurements as well as theoretical calculations, where the latter affect the |fLV Vtb | extrac- tion in particular. The assumptions made about the correlation of uncertainties between the two experiments, as well as between theoretical calculations, are also discussed. Sec- tion 6 presents the combination of cross-sections for each production mode at the same centre-of-mass energy. In section 7, determinations of |fLV Vtb | are performed using all single-top-quark cross-section measurements together or by production mode. Stability tests are also shown and discussed. In section 8, the results are summarised. 2 Theoretical cross-section calculations The theoretical predictions for the single-top-quark production cross-sections are calculated at next-to-leading order (NLO) in the strong coupling constant αs , at NLO with next-to- next-to-leading-logarithm (NNLL) resummation (named NLO+NNLL), and at next-to- next-to-leading order (NNLO). The difference between 4FS and 5FS is small [38, 39], and the calculations use the 5FS. The NLO prediction is used in the Vtb combination for the t-channel and s-channel, while the NLO+NNLL prediction is used for tW , as explained –3– below. The NLO prediction is calculated with HatHor (v2.1) [40, 41]. Uncertainties comprise the scale uncertainty, the αs uncertainty, and the parton distribution function (PDF) uncertainty. The scale uncertainty is evaluated by varying the renormalisation and factorisation scales up and down together by a factor of two. The combination of the PDF+αs uncertainty is calculated according to the PDF4LHC prescription [42] from the envelope of the uncertainties at 68% confidence level (CL) in the MSTW2008 NLO, CT10 NLO [43], and NNPDF2.3 [44] PDF sets. The NLO+NNLL predictions [45] are available for all single-top-quark production modes [46–48]. Uncertainties in these calculations are estimated by varying the renormali- JHEP05(2019)088 sation and factorisation scales between mt /2 and 2mt , where mt is the top-quark mass, and from the 90% CL uncertainties in the MSTW2008 NNLO [49, 50] PDF set. The evaluation of the PDF uncertainties is provided by the author of refs. [46–48] and is not fully compat- √ ible with the PDF4LHC prescription. The t-channel cross-sections at s = 7 and 8 TeV are also computed at NNLO in αs [51], with the renormalisation and factorisation scales set to mt . This results in cross-sections which are about 0.3% and 0.6% lower than the √ NLO values at s = 7 and 8 TeV respectively. However, only a limited number of scale variations are evaluated [51]. A summary of all the available theoretical cross-section predictions for t-channel, tW , t-chan. , σ tW , and σ s-chan. respectively, with their uncertainties and s-channel production, σtheo. theo. theo. is shown in table 1. In this paper, NLO predictions serve as the reference for the t- and s-channel processes, following the prescriptions presented above, because higher-order calculations and their uncertainties are not fully computed and available for the parameter values of choice. The advantage of the NLO cross-section calculations is that the configurable parameters in HatHor can be set according to those used to generate the ATLAS and CMS simulation samples. The t- and s-channel processes do not interfere at NLO [52]. For these two processes, the entire phase space is included in the integration in order to obtain the tW , is available at NLO [41] and total cross-section. The tW cross-section prediction, σtheo. NLO+NNLL [47, 53]. The tW process at NLO interferes with the tt̄ process at LO with the subsequent decay t̄ → W b̄. In the NLO prediction for tW production provided in ref. [41], a kinematic cut-off is imposed on the transverse momentum (pT ) of the outgoing b-quark, suppressing the contribution from tt̄ production. Since the treatment of this interference in HatHor is still being developed [54, 55], the NLO+NNLL calculation is used as reference for tW production. For the reference cross-section predictions, uncertainties corresponding to the dependence on mt and on the LHC beam energy, Ebeam , are evaluated. The mt dependence is estimated by varying its central value of 172.5 GeV (the value used in the simulation samples used to measure the single-top-quark cross-sections) by ±1 GeV, using the functional form proposed in ref. [56]. The theoretical calculations are performed at a given centre-of-mass energy while the energy of the LHC beam is measured with an uncertainty. The single-top-quark cross-sections are assumed to depend on Ebeam according to the model given in ref. [57], with a relative uncertainty δEbeam /Ebeam of 0.1% [58]. The theoretical cross-sections that are used as reference are marked with a † in table 1. –4– √ s Process Accuracy σtheo. [pb] NLO† 63.9+1.9 −1.3 (scale) ± 2.2 (PDF+αs ) ± 0.7 (mt ) ± 0.1 (Ebeam ) t-channel NLO+NNLL 64.6+2.6 −1.7 (scale+PDF+αs ) NNLO 63.7+0.5 −0.3 (scale) 7 TeV NLO 13.2+0.5 −0.6 (scale) ± 1.3 (PDF+αs ) tW NLO+NNLL† 15.74 ± 0.40 (scale)+1.10 −1.14 (PDF+αs ) ± 0.28 (mt ) ± 0.04 (Ebeam ) NLO† 4.29+0.12 −0.10 (scale) ± 0.14 (PDF+αs ) ± 0.10 (mt ) ± 0.01 (Ebeam ) s-channel NLO+NNLL 4.63+0.20 −0.18 (scale+PDF+αs ) NLO† 84.7+2.6 −1.7 (scale) ± 2.8 (PDF+αs ) ± 0.8 (mt ) ± 0.2 (Ebeam ) JHEP05(2019)088 t-channel NLO+NNLL 87.8+3.4 −1.9 (scale+PDF+αs ) NNLO 84.2+0.3 −0.2 (scale) 8 TeV NLO 18.77+0.77 −0.82 (scale) ± 1.70 (PDF+αs ) tW NLO+NNLL† 22.37 ± 0.60 (scale) ± 1.40 (PDF+αs ) ± 0.38 (mt ) ± 0.06 (Ebeam ) NLO† 5.24+0.15 −0.12 (scale) ± 0.16 (PDF+αs ) ± 0.12 (mt ) ± 0.01 (Ebeam ) s-channel NLO+NNLL 5.61 ± 0.22 (scale+PDF+αs ) √ Table 1. Predicted cross-sections for single-top-quark production at s = 7 and 8 TeV at the LHC. Uncertainties include scale and PDF+αs variations, except for the NNLO predictions, which only contain the scale variation. The PDF+αs uncertainties are evaluated according to the PDF4LHC prescription only for the NLO predictions. The uncertainties associated with the top-quark mass mt and beam energy Ebeam are also given for the NLO predictions for the t- and s-channels, and for the NLO+NNLL prediction for tW production. The value of mt is set to 172.5 GeV in all predictions. The cross-sections marked with † are those used in the |fLV Vtb | combination. √ 3 Single-top-quark cross-section measurements at s = 7 and 8 TeV The t-channel single-top-quark production cross-sections, σt-chan. , were measured by the √ ATLAS and CMS Collaborations at s = 7 TeV [59, 60] and 8 TeV [32, 33]. Evidence √ of tW production was reported at s = 7 TeV by ATLAS [61] and CMS [62], while at √ s = 8 TeV its cross-section, σtW , was measured by both experiments [34, 35]. Evidence of s-channel production was reported by ATLAS, with a measured cross-section, σs-chan. , at √ s = 8 TeV [37], whereas CMS set upper limits on the s-channel production cross-section √ at s = 7 and 8 TeV. The observed (expected) significance of the CMS measurement at √ s = 8 TeV is 2.3 (0.8) standard deviations [63]. The ATLAS and CMS analyses use similar approaches to measure the single-top-quark production cross-sections. Both experiments select events containing at least one prompt isolated lepton (electron or muon) and at least one high-pT jet. The analyses use various multivariate analysis (MVA) techniques, such as boosted decision trees [64–66], neural networks [67], or the matrix element method (MEM) [68, 69], to separate the signal from background. To measure the cross-section, analyses perform a binned maximum-likelihood fit to data using the distribution of the corresponding MVA discriminator. Exceptions √ are the ATLAS s-channel and CMS t-channel measurements at s = 8 TeV. In the ATLAS s-channel analysis, the fit is performed simultaneously to the MEM discriminant –5– ATLAS CMS √ s Process σ [pb] Lumi. [fb−1 ] σ [pb] Lumi. [fb−1 ] t-channel 68 ± 8 4.59 67.2 ± 6.1 1.17–1.56 7 TeV tW 16.8 ± 5.7 2.05 16+5 −4 4.9 s-channel — — 7.1 ± 8.1 5.1 t-channel 89.6+7.1 −6.3 20.2 83.6 ± 7.8 19.7 +3.6 8 TeV tW 23.0−3.9 20.3 23.4 ± 5.4 12.2 JHEP05(2019)088 s-channel 4.8+1.8 −1.5 20.3 13.4 ± 7.3 19.7 Table 2. Summary of the single-top-quark cross-section measurements published by the ATLAS √ and CMS Collaborations at s = 7 and 8 TeV. Total uncertainties are shown. Small differences between the integrated luminosity values in different analyses within the same experiment and centre-of-mass energy are due to different luminosity calibrations at the time of publication. in the signal region and the lepton-charge distribution in the W +jets control region. The √ CMS t-channel measurement at s = 8 TeV is based on a simultaneous fit to the absolute pseudorapidity (η) distributions of the recoiling light-flavour jet in events with negative and with positive lepton charge. The analyses measuring different single-top-quark production modes within the same experiment and at the same centre-of-mass energy have disjoint signal regions. Both experiments simulate the single-top-quark processes using the NLO Powheg-Box generator [70–74] for the matrix-element (ME) calculations. ATLAS also uses the Powheg-Box generator to simulate top-quark-pair background events, while CMS uses the LO MadGraph generator [75]. The Pythia [76] event generator is used for modelling the parton shower (PS), hadronisation and the underlying event in both the single-top-quark and tt̄ processes. The cross-sections are measured assuming a value of 172.5 GeV for mt for all top-quark processes and all centre-of-mass energies. A summary of the uncertainties in each measurement is shown in table 2, with details given in appendix A. 4 Combination methodology The ATLAS and CMS single-top-quark production cross-section measurements shown in table 2 are combined, and the combined |fLV Vtb | value determined, using the best linear unbiased estimator (BLUE) method [77–79]. The BLUE method is applied iteratively in order to reduce a possible bias arising from the dependence of systematic uncertainties on the central value of the cross-section [80]. Convergence is reached when the central value changes by less than 0.01% compared with the previous iteration. In each iteration, the BLUE method minimises the global χ2 by adjusting the weight for each input measure- ment [79]. The global χ2 is calculated taking correlations into account. The sum of weights is required to be equal to one. Negative weights are allowed; these indicate strong correla- tions [81]. The number of degrees of freedom is n−1, where n is number of measurements in the combination. The χ2 and n are then used to calculate a corresponding probability [79]. –6– The systematic uncertainties are scaled with the cross-section in each iteration, i.e. they are treated as relative uncertainties. The data and simulation statistical uncertainties are not scaled [80]. The systematic uncertainties in the s-channel cross-section combination are also not scaled because the s-channel measurements have large backgrounds. Following the same strategy as in the input measurements by the ATLAS and CMS Collaborations, the combined cross-sections are reported at mt = 172.5 GeV, not including the uncertainty associated with the mt variation. The shift in the combined cross-section due to a variation of ±1 GeV in the top-quark mass is given where this information is avail- able. For the determination of the combined |fLV Vtb | value, the uncertainty in the measured cross-sections due to a variation of ±1 GeV in the mass is considered. Uncertainties in the JHEP05(2019)088 measurements are symmetrised, before combination, by averaging the magnitude of the downward and upward variations. More details are given in sections 5 and 6. 5 Systematic uncertainties and correlation assumptions In order to combine single-top-quark cross-section measurements and |fLV Vtb | values, the sources of uncertainty are grouped into categories. While the categorisation and evaluation of uncertainties varies somewhat between experiments and between measurements, each individual measurement considers a complete set of uncertainties. Assumptions are made about correlations between similar sources of uncertainty in different measurements, as explained in section 5.1. Uncertainties associated with theoretical predictions are taken into account in the |fLV Vtb | combination. The correlations between similar uncertainties in different theoretical predictions are discussed in section 5.2. 5.1 Systematic uncertainties in measured cross-sections √ Systematic uncertainties in the ATLAS t-channel measurements at s = 7 and 8 TeV are evaluated using pseudoexperiments, except the background normalisation uncertain- √ ties, which are constrained in the fit to data. In the ATLAS tW measurements at s = √ 7 and 8 TeV and the s-channel measurement at s = 8 TeV, systematic uncertainties are included as nuisance parameters in profile-likelihood fits. Systematic uncertainties in √ the CMS t-channel and tW measurements at s = 7 and 8 TeV are included as nuisance parameters in fits to data, except the theory modelling uncertainties in signal and back- grounds, described below, which are evaluated using pseudoexperiments. All systematic √ uncertainties in the CMS s-channel measurements at s = 7 and 8 TeV are obtained through pseudoexperiments, except the background normalisation uncertainties, which are constrained in the fit to data. In the analyses where systematic uncertainties are included as nuisance parameters, the total uncertainty presented in table 2 is evaluated by vary- ing all the nuisance parameters in the fit simultaneously. To extract the impact of each source of this type of uncertainty, these analyses use approximate procedures which neglect the correlations between sources of uncertainty introduced by the fits. Throughout this paper, individual uncertainties are taken as reported by the input analyses, regardless of the method used to determine them. The total uncertainties are evaluated as the sum in quadrature of individual contributions. –7– Although the sources of systematic uncertainty and the procedures used to estimate their impact on the measured cross-section are partially different in the individual analyses, it is still possible to identify contributions that describe similar physical effects. These contributions are listed below; they are grouped together, and only the resulting categories are used in the combination. Categories are treated as uncorrelated among each other. For each source of uncertainty, correlations between different measurements are assumed to be positive, unless explicitly mentioned otherwise. The stability of the cross-section and |fLV Vtb | combinations is studied by varying the correlation assumptions for the dominant uncertainties, as discussed in section 7.2. JHEP05(2019)088 The uncertainties in each category are listed below, with the correlation assumptions across experiments given in parentheses. These correlations correspond to those used in the cross-section combinations. They are also valid for the combination of the |fLV Vtb | extrac- tions, unless explicitly mentioned otherwise. The symbol “—” means that the uncertainty is either considered only in the ATLAS or the CMS measurement, or is not considered at all. A summary of uncertainties in the cross-section measurements together with the corresponding correlation assumptions between experiments is provided in appendix A. Data statistical (Correlation 0): this statistical uncertainty arises from the limited size of the data sample. It is uncorrelated between ATLAS and CMS, between production modes, and between centre-of-mass energies. √ Simulation statistical (Correlation 0 and — for CMS tW at s = 7 TeV and s-channel √ at s = 8 TeV): this statistical uncertainty comes from the limited size of simulated event samples. It is uncorrelated between ATLAS and CMS, between production modes, √ and between centre-of-mass energies. For the CMS tW analysis at s = 7 TeV and s- √ channel analysis at s = 8 TeV, this uncertainty is evaluated as part of the total statistical uncertainty, which is also considered uncorrelated, as discussed above. More details are given in appendices A.2 and A.3. Integrated luminosity (Correlation 0.3): this uncertainty originates from the system- atic uncertainty in the integrated luminosity, as determined by the individual experiments using the methods described in refs. [82–85]. It affects the determination of both the signal and background yields. The integrated-luminosity uncertainty has a component that is cor- related between ATLAS and CMS, arising from imperfect knowledge of the beam currents during van der Meer scans in the LHC accelerator [86], and an uncorrelated component √ from the long-term luminosity monitoring that is experiment-specific. At s = 7 TeV, these components are 0.5% and 1.7% respectively for ATLAS and 0.5% and 2.1% respec- √ tively for CMS. At s = 8 TeV, they are 0.6% and 1.8% respectively for ATLAS and 0.7% and 2.5% respectively for CMS. At both centre-of-mass energies, the correlation coefficient between the integrated-luminosity uncertainty in ATLAS and CMS at the same centre-of- mass energy is ρ = 0.3. Within the same experiment, the integrated-luminosity uncertainty is assumed to be correlated between production modes and uncorrelated between centre- of-mass energies. In section 7.2, it is shown that the combined |fLV Vtb |2 result does not depend significantly on the correlation assumptions. –8– Theory modelling: this category contains the uncertainties in the modelling of the simulated single-top-quark processes, as well as smaller contributions from the modelling of the tt̄ and W +jets background processes. Both signal and background modelling are included because the uncertainties in all top-quark processes are closely related. These in- clude initial- and final-state radiation (ISR/FSR), renormalisation and factorisation scales, NLO matching method, PS and hadronisation modelling, and PDF uncertainties. For the tW process, the uncertainty due to the treatment of interference between tW and tt̄ final states is also included, as discussed below. These modelling uncertainties in signal and background processes are summed in quadrature in each input measurement. JHEP05(2019)088 • Scales and radiation modelling (Correlation 1) The renormalisation and factorisation scales and ISR/FSR uncertainties account for missing higher-order corrections in the perturbative expansion and the amount of initial- and final-state radiation in simulated signal and background processes. In the ATLAS measurements of all three production modes, these uncertainties are es- timated using dedicated single-top-quark and tt̄ simulated event samples, by con- sistently varying the renormalisation and factorisation scales and the amount of ISR/FSR in accordance with a measurement of additional jet activity in tt̄ events at √ s = 7 TeV [87, 88]. In the ATLAS t-channel measurements, they are also estimated in W +jets simulated event samples, by varying the scale and matching parameters in √ the Alpgen LO multileg generator [89] at s = 7 TeV and by varying the parameters √ controlling the scale in the Sherpa LO multileg generator [90] at s = 8 TeV. In the CMS measurements, these uncertainties are estimated by varying the renormalisation and factorisation scales, and ISR/FSR, consistently in the simulated event samples. √ In the CMS t-channel measurement at s = 8 TeV, this uncertainty applies only to the signal modelling since the modelling of the dominant tt̄ and W +jets background √ processes is obtained from data. However, for the t-channel analysis at s = 7 TeV, the scales are varied in the simulated signal, tt̄, W +jets and other single-top-quark processes. The same approach is followed in the CMS s-channel measurements at both centre-of-mass energies. The tW cross-section measurements of CMS account for this uncertainty only in the tW signal and tt̄ background, given the negligible contributions from the W +jets and other single-top-quark processes in the dilepton final state. Although the methods are apparently different, they mostly address the same un- certainty, hence this uncertainty is considered correlated between ATLAS and CMS. It is also considered correlated between production modes and centre-of-mass ener- gies. The combined |fLV Vtb | result does not depend significantly on this correlation assumption, as discussed in section 7.2. • NLO matching (Correlation 1 for t-channel and — for tW and s-channel) The ATLAS measurements include an uncertainty to account for different NLO matching methods implemented in different NLO event generators. This is eval- uated in single-top-quark and tt̄ simulations by comparing the Powheg-Box, –9– MC@NLO [91, 92], and MadGraph5 aMC@NLO [93] event generators, all inter- faced to Herwig [94] (with Jimmy [95] for the underlying-event modelling). In the √ CMS t-channel measurement at s = 7 TeV, the NLO matching uncertainty is eval- uated by comparing Powheg-Box with CompHEP [96, 97]. In the CMS t-channel √ analysis at s = 8 TeV, this uncertainty accounts for different NLO matching meth- ods in the t-channel signal event generator, as well as for differences between event generation in the 4FS and 5FS, by comparing Powheg-Box with MadGraph. The NLO matching uncertainty is considered correlated between ATLAS and CMS, be- tween production modes, and between centre-of-mass energies. In the CMS tW and √ s-channel analyses at s = 7 and 8 TeV, this uncertainty is not considered, since the JHEP05(2019)088 modelling uncertainties in the scheme to remove overlap with tt̄ are dominant in the tW analysis and the renormalisation/factorisation scale is dominant in the s-channel analysis. The results of the stability test for this uncertainty are shown in section 7.2. • Parton shower and hadronisation (Correlation 1) In both experiments, the difference between the Pythia and Herwig showering programs is considered in the jet energy scale (JES) [98–101] and b-tagging calibra- tion [102–106]. The ATLAS analyses additionally include an uncertainty in the PS and hadronisation modelling in simulated single-top-quark and tt̄ events, evaluated by comparing the Powheg-Box event generator interfaced to Pythia or to Her- wig. The CMS analyses additionally include an uncertainty in the tt̄ and W +jets backgrounds estimated with the MadGraph event generator interfaced to Pythia. It is evaluated in simulated event samples where the value of the ME/PS match- ing threshold in the MLM method [107] is doubled or halved from its initial value. √ The CMS t-channel measurement at s = 8 TeV does not consider this uncertainty in the tt̄ and W +jets backgrounds since the distribution and normalisation of the tt̄ and W +jets processes are derived mostly from data. In the CMS tW analyses √ at s = 7 and 8 TeV, the contributions of the W +jets and other single-top-quark processes in the dilepton final state are negligible. This uncertainty is considered correlated between ATLAS and CMS, between differ- ent production modes, and between different centre-of-mass energies. The combined |fLV Vtb | result does not depend significantly on this correlation assumption, as shown in section 7.2. • Parton distribution functions (Correlation 1) The PDF uncertainty is evaluated following the PDF4LHC procedures [42, 108, 109] and is considered correlated between ATLAS and CMS, between different production modes, and between different centre-of-mass energies. • tW and tt̄ interference (Correlation 1 for tW and — for t- and s-channels) The tW process interferes with tt̄ production at NLO [110–112]. In both ATLAS and CMS, two simulation approaches are compared: diagram removal (DR) [110] and dia- gram subtraction (DS) [27, 110]. In the DR approach, all NLO diagrams that overlap – 10 – with the doubly resonant tt̄ contributions are removed from the calculation of the tW amplitude. This approach accounts for the interference term, but it is not gauge invariant (though the effect is numerically negligible) [110]. In the DS approach, a subtraction term is built into the amplitude to cancel out the tt̄ component close to the top-quark resonance while respecting gauge invariance. The DR approach is the default, and the comparison with the DS approach is used to assess this systematic uncertainty. For the tW analyses, this uncer- tainty is considered correlated between the two experiments and between different centre-of-mass energies. JHEP05(2019)088 • Modelling of the top-quark pT spectrum (Correlation —) √ In the CMS tW and s-channel analyses at s = 8 TeV, the simulated tt̄ events are reweighted to correct the pT spectrum of the generated top quarks, which was found to be significantly harder than the spectrum observed in data in differential cross-section measurements [113, 114]. To estimate the uncertainty related to this mismodelling, the tW measurement is repeated without the reweighting, and the change relative to the default result is taken as the uncertainty. In the CMS s-channel analysis, the measurement is repeated with the effect of the weights removed and doubled. The resulting variation in the cross-section is symmetrised. This uncertainty is not √ considered in the CMS t-channel measurement at s = 8 TeV where the modelling of the tt̄ background is extracted from data. In the ATLAS measurements, modelling uncertainties in the top-quark pT spectrum in tt̄ events [115] are covered by the PS and hadronisation uncertainty and they are found to be small in comparison with other systematic uncertainties. This uncertainty is considered correlated between the √ CMS tW and s-channel analyses at s = 8 TeV. • Dependence on the top-quark mass (Correlation 1) The measured single-top-quark cross-sections shown in table 2 assume a nominal mt value of 172.5 GeV. The dependence of the measured cross-section on mt is √ estimated for the ATLAS t-channel measurements at s = 7 and 8 TeV and for √ the ATLAS tW measurement at s = 8 TeV. It is determined using dedicated simulations of single-top-quark and tt̄ samples with different mt values. The cross- section measurements assuming the different mt values are interpolated using a first- or a second-order polynomial, for which the constant term is given by the central value √ of mt = 172.5 GeV. The CMS measurements at s = 8 TeV provide information for a variation of ±2 GeV in the top-quark mass, which is scaled to a ±1 GeV shift √ assuming a linear dependence. For the CMS t-channel and tW measurements at s = 8 TeV, the changes in cross-sections are symmetrised and reported as uncertainties. In the CMS s-channel analysis, the change in the cross-section is determined for the up and down variation of mt . No estimates are available for the CMS t-channel √ √ analysis at s = 7 TeV, the ATLAS and CMS tW analyses at s = 7 TeV or the √ ATLAS s-channel analysis at s = 8 TeV. The top-quark-mass uncertainty is small – 11 – for each measurement, thus the impact of not evaluating it for these measurements is negligible. In this paper, a symmetrised uncertainty in the measured cross-section due to a variation of ±1 GeV in the top-quark mass is considered. When the full cross-section dependence on the top-quark mass is available for a given production mode at a given centre-of-mass energy, the sign of the dependence of the uncertainty per unit of mass is taken into account in the correlations. In the case of the CMS t-channel and tW √ measurements at s = 8 TeV, where the sign of the dependence is not available, it is assumed that the sign is the same as for the ATLAS measurement, since the JHEP05(2019)088 phase space and background composition are comparable between CMS and ATLAS. Given that the uncertainty in the measured cross-section is considered for the same mt variation and considering the sign of the dependence when available, this uncertainty is considered correlated between ATLAS and CMS and between different centre-of- mass energies and uncorrelated between the t-channel and tW production modes. Background normalisation (Correlation 0): three background uncertainties are con- sidered: in top-quark background (tt̄ and other single-top-quark processes), in other back- ground determined from simulation (W/Z+jets, diboson, and other smaller background channels), and in background estimated from data (multijet background from misidentified √ and non-prompt leptons). The exceptions are the t-channel measurements at s = 7 TeV, where the background from simulation includes top-quark background, as shown in ta- bles 9–13 in appendix A. The normalisation of the main background processes is deter- mined from data, either by inclusion of normalisation uncertainties as nuisance parameters in the fit used to extract the signal, or through dedicated techniques based on data. In the t-channel and s-channel measurements, the uncertainties in the theoretical cross-section predictions for the top-quark, W/Z+jets, and diboson processes are included. In the tW measurements, the uncertainties in the theoretical cross-section predictions for the top- quark and diboson processes are taken into account. In the ATLAS measurements of the √ t-channel process at s = 7 and 8 TeV, the uncertainty in the multijet background is estimated by comparing background estimates made using different techniques based on √ simulation and data samples. In the ATLAS tW analyses at s = 7 and 8 TeV, the nor- malisation uncertainty in the background from misidentified and non-prompt leptons is obtained from variations in the data-based estimate. In the ATLAS s-channel analysis, the uncertainty assigned to the normalisation of the multijet background is based on control samples. For all CMS measurements, background normalisations are constrained in the fits to data. In the CMS measurements of the t-channel and s-channel processes, the un- certainties in the multijet background are assessed by comparing the results of alternative background estimation methods based on data. Hence, the associated uncertainties are considered uncorrelated between ATLAS and CMS, between different production modes, and between different centre-of-mass energies. Jets: in the analyses, the uncertainties related to the reconstruction and energy calibra- tion of jets are propagated through variations in the modelling of the detector response. – 12 – These uncertainties, classified in categories as JES, jet identification (JetID), and jet energy resolution (JER), are discussed below. • Jet energy scale (Correlation 0 and — for JES flavour) The JES is derived using information from data and simulation. Its uncertainty increases with increasing |η| and decreases with increasing pT of the reconstructed jet. √ For all of the ATLAS measurements, except the tW measurement at s = 7 TeV, the JES uncertainty is split into components originating from the jet calibration proce- dure; most of them are derived from in situ techniques based on data [98, 99]. These JHEP05(2019)088 components are categorised as modelling, detector, calibration method, and statis- tical components, which are grouped into the “JES common” uncertainty, as well as a flavour-dependence component (“JES flavour”), which accounts for the flavour composition of the jets and the calorimeter response to jets of different flavours. The modelling of additional pp collisions in each bunch-crossing (pile-up) is considered separately, as discussed below. The η-dependent component is dominant for the t-channel production mode. Thus, the JES common uncertainty is considered uncor- related between the t-channel and the other single-top-quark production modes. For √ the tW analysis at s = 8 TeV, the modelling component, which is constrained in the fit to data, is dominant. The uncertainty in the flavour composition of the jets is dominant for the s-channel. For the CMS measurements, sources contributing to the JES uncertainty are com- bined together into the “JES common” uncertainty, and the effect is propagated to the cross-section measurements through η- and pT -dependent JES uncertain- ties [100, 101]. The jet energy corrections and their corresponding uncertainties are extracted from data. The JES uncertainty is estimated from its effect on the normalisation and shape of the discriminant in each analysis. The JES uncertainty is considered uncorrelated between the t-channel and the other single-top-quark pro- duction modes because it is dominated by the forward jet in the t-channel. The correlation between the JES common uncertainty (or the JES uncertainty for √ the tW measurement at s = 7 TeV) in ATLAS and the JES uncertainty in CMS follows the prescription in refs. [116, 117], with the slight differences for the t-channel described above. The JES common (or JES) uncertainty is considered uncorrelated between ATLAS and CMS, between centre-of-mass energies, and between production modes. Within the ATLAS experiment, the JES common uncertainty is considered correlated between tW and s-channel and uncorrelated between t-channel and the other production modes. For the ATLAS t-channel analyses, a correlation of 0.75 √ is assumed between s = 7 and 8 TeV, since these analyses are mainly affected by the same uncertainty components. This correlation value is estimated by comparing variations of the JES uncertainty components in these two measurements. √ In all CMS measurements and in the ATLAS tW measurement at s = 7 TeV, the JES uncertainty is not split and therefore the JES flavour uncertainty is included in the overall JES uncertainty. For the ATLAS measurements where this component – 13 – is available, the JES flavour uncertainty is considered correlated between different production modes and uncorrelated between centre-of-mass energies. The JES uncertainty is one of the dominant contributions in most of the single-top- quark measurements. To ensure the robustness of the results against the correlation assumptions for this large uncertainty, the combination is performed with alternative correlation values, as discussed in section 7.2. • Jet identification (Correlation —) In the ATLAS measurements, the JetID uncertainty includes the jet and vertex re- JHEP05(2019)088 construction efficiency uncertainties. In the CMS measurements, this uncertainty is included in the JES uncertainty. For ATLAS, it is considered correlated between the different production modes at the same centre-of-mass energy and uncorrelated for the other cases. • Jet energy resolution (Correlation 0) The uncertainty in the JER, which is not split into components, is extracted from data. Generally, the JER uncertainty is propagated via a nuisance parameter in √ the signal extraction fit, except for the ATLAS t-channel measurements at s = 7 and 8 TeV, and the CMS s-channel measurement, where this uncertainty is de- termined using pseudoexperiments. The JER uncertainty is considered uncorrelated between ATLAS and CMS, and between centre-of-mass energies. It is considered correlated between different production modes. Detector modelling: this category includes the uncertainty in the modelling of leptons, magnitude of the missing transverse momentum (ET miss ), and identification of jets from b-quarks (b-tagging). • Lepton modelling (Correlation 0) The lepton modelling uncertainty includes components associated with the lepton energy scale and resolution, reconstruction and trigger efficiencies. This uncertainty is considered uncorrelated between ATLAS [118–121] and CMS [122] and between different centre-of-mass energies, since it is determined from data. It is considered correlated between different production modes. • Hadronic part of the high-level trigger (Correlation —) √ In the CMS t-channel cross-section measurement at s = 7 TeV, the high-level trigger (HLT) criteria for the electron channel are based on the presence of an electron together with a b-tagged jet. In this analysis, the uncertainty in the modelling of the hadronic part of the HLT requirement is determined from data. This uncertainty is only evaluated in this one measurement. miss modelling (Correlation 0) • ET The ATLAS measurements include separate components for the uncertainties in the miss [123]. The CMS measurements account for a energy scale and resolution of the ET – 14 – combined ET miss scale and resolution uncertainty [100, 124], arising from the jet-energy uncertainties. Additionally, CMS accounts for an uncertainty in ET miss arising from energy deposits in the detector that are not included in the reconstruction of leptons, photons, and jets. The ET miss uncertainty is considered uncorrelated between ATLAS and CMS, and between different centre-of-mass energies. It is considered correlated √ between production modes, except for the ATLAS and CMS tW analyses at s = 8 TeV, where it is considered uncorrelated with the other production modes because miss uncertainty is constrained in the fit to data. In the ATLAS tW analysis at the ET √ s = 7 TeV, this uncertainty is included in the pile-up modelling uncertainty. JHEP05(2019)088 • b-tagging (Correlation 0) In the ATLAS analyses, b-tagging modelling uncertainties are split into components associated with b-quark, c-quark, and light-flavour quark and gluon jets [102–104]. They are evaluated by varying the pT -dependence (η-dependence in the case of light- flavour jets) of the flavour-dependent scale factors applied to each jet in simulation within a range that reflects the systematic uncertainty in the measured tagging effi- ciency and misidentification rates. This uncertainty is not considered in the ATLAS √ tW analysis at s = 7 TeV because no b-tagging criterion is applied in the event selection. In the CMS measurements, the uncertainties in b-tagging efficiency and misidentification rates of jets initiated by light-flavour quarks and gluons are derived from data, using control samples [105, 106]. The CMS uncertainties are propagated to the cross-section measurements using pseudoexperiments. Exceptions are the t- √ √ channel measurement at s = 7 TeV and the tW measurement at s = 8 TeV, where these uncertainties are constrained in the fit to data. The two collaborations split up the different sources of systematic uncertainties re- lated to b-tagging in a different way. However, the different sources are combined by adding their contributions in quadrature to obtain a single b-tagging uncertainty per analysis. This means that the b-tagging uncertainty also contains the uncer- tainties associated with the misidentification rates of jets initiated by charm quarks, light-flavour quarks and gluons. The resulting uncertainty is considered uncorre- lated between ATLAS and CMS, and between different centre-of-mass energies. It is considered correlated between different production modes. • Pile-up modelling (Correlation 0) In both ATLAS and CMS, simulated events are reweighted to match the distribution of the average number of interactions per bunch-crossing in data. The corresponding uncertainty is obtained from in situ techniques based on data and simulated event √ samples. In the ATLAS analyses at s = 7 TeV, the uncertainty due to pile-up is derived from the impact of the reweighting on ET miss . In the ATLAS analyses at √ s = 8 TeV, this uncertainty is evaluated as a component of the JES, separated into four terms (number of primary vertices, average number of collisions per bunch- crossing, average pile-up energy density in the calorimeter, and pT dependence) since the pile-up calibration (assuming average conditions during 8 TeV data-taking) is – 15 – applied to both data and simulation before selecting and calibrating the jets [117]. In CMS, the reweighting uses a model with a free parameter that can be interpreted as an effective cross-section for inelastic pp interactions. This uncertainty is obtained from a fit to the number of additional primary vertices in simulation. In the CMS analyses, this uncertainty is introduced as a nuisance parameter in the fit. The only exception is the s-channel measurement, where the pile-up uncertainty is estimated from pseudoexperiments. In all cases, the effects of pile-up on the jet energy and the isolation of leptons are taken into account in the jet and lepton uncertainties respectively. The pile-up uncertainty is considered uncorrelated between ATLAS and CMS and between different centre-of-mass energies. It is considered correlated JHEP05(2019)088 between different production modes [116, 117]. 5.2 Systematic uncertainties in theoretical cross-section predictions The systematic uncertainties in the combined |fLV Vtb | value are evaluated from uncertain- ties in the individual cross-section measurements σmeas. and the theoretical predictions σtheo. . The uncertainties associated with σtheo. are discussed in section 2; they are sum- marised in table 1. The correlation assumptions for the systematic uncertainties related to the theoretical cross-section are explained below. In section 7.2, the stability of the |fLV Vtb | combination against variations in the correlations is examined. For clarity, the correlations are given in parentheses next to the systematic-uncertainty name. These correlations are used in the combination of the |fLV Vtb | extractions. PDF+αs (Correlation 1 for centre-of-mass energies and 0.5 for production modes): the PDF uncertainty is considered correlated between centre-of-mass energies and 50% corre- lated between production modes, since different production modes have one initial-state particle in common (a quark or a gluon), but not both. Renormalisation and factorisation scales (Correlation 1 for t-channel and s-channel and 0 for tW ): the renormalisation and factorisation scale uncertainties in σtheo. are consid- ered correlated between production modes and centre-of-mass energies, except between the tW production mode and the other production modes, where they are considered uncor- related because the tW prediction is computed at a different order in perturbation theory. Top-quark mass (Correlation 1): the uncertainty due to mt is evaluated by varying mt from its central value of 172.5 GeV by ±1 GeV and evaluating the corresponding change in cross-section using the parameterisation given in ref. [56], as discussed in section 2. This uncertainty is considered correlated between centre-of-mass energies and production modes. Ebeam (Correlation 1): the uncertainty in the cross-section due to the uncertainty in Ebeam is estimated by computing the cross-section variation corresponding to a ±1 standard deviation shift in the beam-energy uncertainty. It is considered correlated between centre- of-mass energies and production modes. – 16 – 6 Combinations of cross-section measurements The cross-section measurements described in section 3 are combined at each centre-of-mass energy for each production mode. Systematic uncertainties are categorised and correlation assumptions are employed according to section 5. The combinations are performed using the iterative BLUE method, as described in section 4. As discussed in section 4, the uncertainty in the measured cross-section associated with the mt variation is not considered in the combination of cross-sections. However, the shift in the combined cross-section resulting from a variation of ±1 GeV in the top-quark mass is provided where this information is available. This is calculated by repeating the JHEP05(2019)088 combination with the up-shifted and down-shifted input cross-sections. In measurements where only the magnitude of the shift is available for one experiment, the sign of the shift is assumed to be the same for both experiments, as discussed in section 5.1. If the uncertainty associated with the mt variation is not available for one or both of the input measurements, then no shift in the combined cross-section is given. Additional information about the uncertainties considered in the combination of cross- section measurements is provided in appendix A. 6.1 Combinations of t-channel cross-section measurements √ The combination of the ATLAS and CMS t-channel cross-section measurements at s= 7 TeV [59, 60] results, after one iteration, in σt-chan. = 67.5 ± 2.4 (stat.) ± 5.0 (syst.) ± 1.1 (lumi.) pb = 67.5 ± 5.7 pb. The relative uncertainty is 8.4%, which improves on the uncertainty of 9.1% in the most precise individual measurement from CMS [60]. The χ2 for the combination is 0.01, cor- responding to a probability of 93%. The CMS weight in the combination is 0.58, while the ATLAS weight is 0.42. The overall correlation between the two measurements is 20%. The contribution from each uncertainty category to the total uncertainty in the combined √ t-channel cross-section measurement at s = 7 TeV is shown in table 3(a). The combination of the ATLAS and CMS t-channel cross-section measurements at √ s = 8 TeV [32, 33] results, after two iterations, in a cross-section of σt-chan. = 87.7 ± 1.1 (stat.) ± 5.5 (syst.) ± 1.5 (lumi.) pb = 87.7 ± 5.8 pb. The relative uncertainty is 6.7%, which improves on the uncertainty of 7.5% in the most precise individual measurement from ATLAS [32]. The χ2 for the combination is 0.59, corresponding to a probability of 44%. This probability is lower than the probability √ of the combination at s = 7 TeV because of the differences between the ATLAS and CMS measured cross-sections and their small uncertainties. The ATLAS weight in the combination is 0.68, while the CMS weight is 0.32. The overall correlation between the two measurements is 42%. This is larger than the correlation between the measurements √ at s = 7 TeV because the statistical and detector uncertainties are lower, thus increasing the importance of the theory modelling uncertainty (which is correlated between the two – 17 – (a) (b) √ √ σt-chan. , s = 7 TeV σt-chan. , s = 8 TeV Combined cross-section 67.5 pb Combined cross-section 87.7 pb Uncertainty Uncertainty Uncertainty category Uncertainty category [%] [pb] [%] [pb] Data statistical 3.5 2.4 Data statistical 1.3 1.1 Simulation statistical 1.4 0.9 Simulation statistical 0.6 0.5 Integrated luminosity 1.7 1.1 Integrated luminosity 1.7 1.5 Theory modelling 5.1 3.5 Theory modelling 5.3 4.7 JHEP05(2019)088 Background normalisation 1.9 1.3 Background normalisation 1.2 1.1 Jets 3.4 2.3 Jets 2.6 2.3 Detector modelling 3.4 2.3 Detector modelling 1.8 1.6 Total syst. unc. (excl. lumi.) 7.5 5.0 Total syst. unc. (excl. lumi.) 6.3 5.5 Total syst. unc. (incl. lumi.) 7.6 5.2 Total syst. unc. (incl. lumi.) 6.5 5.7 Total uncertainty 8.4 5.7 Total uncertainty 6.7 5.8 Table 3. Contribution from each uncertainty category to the combined t-channel cross-section √ √ (σt-chan. ) uncertainty at (a) s = 7 TeV and (b) s = 8 TeV. The total uncertainty is computed by adding in quadrature all the individual systematic uncertainties (including the uncertainty in the integrated luminosity) and the statistical uncertainty in data. Correlations of systematic un- certainties between experiments are presented in appendix A.1. experiments), as shown in appendix A.1. The contribution from each uncertainty category √ to the total uncertainty in the combined t-channel cross-section measurement at s = 8 TeV is shown in table 3(b). At both centre-of-mass energies, the uncertainties from theory modelling are found to be dominant. Details of the central values, the impact of individual sources of uncertain- √ ties, and their correlations between experiments at s = 7 and 8 TeV can be found in appendix A.1. √ The shift in the combined cross-section at s = 8 TeV from a variation of ±1 GeV in the top-quark mass is ∓0.8 pb, which is similar to the shifts in the input measurements √ for the same mt variation. The shift in the combined cross-section at s = 7 TeV is not √ evaluated since no estimate is available for the CMS input measurement at s = 7 TeV. 6.2 Combinations of tW cross-section measurements √ The combination of the ATLAS and CMS tW cross-section measurements at s = 7 TeV [61, 62] yields, after two iterations, a cross-section of σtW = 16.3 ± 2.3 (stat.) ± 3.3 (syst.) ± 0.7 (lumi.) pb = 16.3 ± 4.1 pb. The relative uncertainty is 25%, which improves on the uncertainty of 28% in the most precise individual measurement from CMS [62]. The χ2 for the combination is 0.01, corre- sponding to a probability of 91%. The CMS weight in the combination is 0.59, while the – 18 – (a) (b) √ √ σtW , s = 7 TeV σtW , s = 8 TeV Combined cross-section 16.3 pb Combined cross-section 23.1 pb Uncertainty Uncertainty Uncertainty category Uncertainty category [%] [pb] [%] [pb] Data statistical 14.0 2.3 Data statistical 4.7 1.1 Simulation statistical 0.8 0.1 Simulation statistical 0.8 0.2 Integrated luminosity 4.4 0.7 Integrated luminosity 3.6 0.8 Theory modelling 13.9 2.3 Theory modelling 11.8 2.7 JHEP05(2019)088 Background normalisation 6.0 1.0 Background normalisation 2.2 0.5 Jets 11.5 1.9 Jets 6.2 1.4 Detector modelling 6.2 1.0 Detector modelling 4.9 1.1 Total syst. unc. (excl. lumi.) 20.0 3.3 Total syst. unc. (excl. lumi.) 14.4 3.3 Total syst. unc. (incl. lumi.) 20.5 3.3 Total syst. unc. (incl. lumi.) 14.8 3.4 Total uncertainty 24.8 4.1 Total uncertainty 15.6 3.6 Table 4. Contribution from each uncertainty category to the combined tW cross-section (σtW ) √ √ uncertainty at (a) s = 7 TeV and (b) s = 8 TeV. The total uncertainty is computed by adding in quadrature all the individual systematic uncertainties (including the uncertainty in the integrated luminosity) and the statistical uncertainty in data. Correlations of systematic uncertainties between experiments are presented in appendix A.2. ATLAS weight is 0.41. The overall correlation between the two measurements is 17%. The contribution from each uncertainty category to the total uncertainty in the combined tW √ cross-section measurement at s = 7 TeV is shown in table 4(a). √ The combination of the ATLAS and CMS tW cross-section measurements at s = 8 TeV [34, 35] results, after two iterations, in σtW = 23.1 ± 1.1 (stat.) ± 3.3 (syst.) ± 0.8 (lumi.) pb = 23.1 ± 3.6 pb. The relative uncertainty is 15.6%, which improves on the uncertainty of 16.5% in the most precise individual measurement from ATLAS [34]. The χ2 for the combination is 0.01, corresponding to a probability of 94%. The ATLAS weight in the combination is 0.70, while the CMS weight is 0.30. The overall correlation between the two measurements is 40%. Similar to the t-channel, this is larger than the correlation between the measurements √ at s = 7 TeV due to the increased importance of the theory modelling uncertainties. The contribution from each uncertainty category to the total uncertainty in the combined tW √ cross-section measurement at s = 8 TeV is shown in table 4(b). At both centre-of-mass energies, the uncertainties in the theory modelling are found to be dominant. The jet uncertainties are also important. Details of the central values, the impact of individual sources of uncertainties, and their correlations between experiments √ at s = 7 and 8 TeV are presented in appendix A.2. – 19 – √ σs-chan. , s = 8 TeV Combined cross-section 4.9 pb Uncertainty Uncertainty category [%] [pb] Data statistical 16 0.8 Simulation statistical 12 0.6 Integrated luminosity 5 0.2 Theory modelling 14 0.7 Background normalisation 8 0.4 JHEP05(2019)088 Jets 13 0.6 Detector modelling 8 0.4 Total syst. unc. (excl. lumi.) 25 1.2 Total syst. unc. (incl. lumi.) 25 1.2 Total uncertainty 30 1.4 Table 5. Contribution from each uncertainty category to the combined s-channel cross-section √ (σs-chan. ) uncertainty at s = 8 TeV. The total uncertainty is computed by adding in quadrature all the individual systematic uncertainties (including the uncertainty in the integrated luminosity) and the statistical uncertainty in data. Correlations of systematic uncertainties between experiments are presented in appendix A.3. √ The shift in the combined cross-section at s = 8 TeV from a variation of ±1 GeV in the top-quark mass is ±1.1 pb, which is similar in magnitude to that in the input measurements √ for the same mt variation. The shift in the combined cross-section at s = 7 TeV is not √ evaluated since no estimates are available for the input measurements at s = 7 TeV. 6.3 Combination of s-channel cross-section measurements The ATLAS and CMS s-channel cross-section measurements suffer from large backgrounds, and the cross-section measurements have large uncertainties. Since the systematic uncer- tainties mainly affect the background prediction, they are not scaled in the iterative BLUE procedure. Only the luminosity uncertainty is scaled with the central value. The combina- √ tion of the ATLAS and CMS s-channel cross-section measurements at s = 8 TeV [37, 63] results, after two iterations, in a cross-section of σs-chan. = 4.9 ± 0.8 (stat.) ± 1.2 (syst.) ± 0.2 (lumi.) pb = 4.9 ± 1.4 pb. The relative uncertainty is 30%, very similar to the most precise individual measurement from ATLAS [37]. The χ2 for the combination is 1.45, corresponding to a probability of 23%. The ATLAS weight in the combination is 0.99, while the CMS weight is 0.01. The overall correlation between the two measurements is 15%. The contribution from each uncertainty category to the total uncertainty in the combined s-channel cross-section √ measurement at s = 8 TeV is shown in table 5. – 20 – Since the ATLAS measurement has a large weight in the combination, the importance of each uncertainty in the combination is similar to that in the ATLAS measurement, as presented in appendix A.3. √ The shift in the combined cross-section at s = 8 TeV from a variation in the top-quark mass is not evaluated since no estimate is available for the ATLAS input measurement. 6.4 Summary of cross-section combinations A summary of the cross-sections measured by ATLAS and CMS and their combinations in all single-top-quark production modes at each centre-of-mass energy is shown in fig- JHEP05(2019)088 ure 2. The measurements are compared with the theoretical predictions shown in table 1: NNLO for t-channel only, NLO and NLO+NNLL for all three production modes. For the NLO calculation, the renormalisation- and factorisation-scale uncertainties and the sum in quadrature of the contributions from scale, PDF, and αs are shown separately. Only the scale uncertainty is shown for the NNLO calculation. For the NLO+NNLL calculation, the sum in quadrature of the contributions from scale, PDF, and αs is shown. All mea- surements are in good agreement with their corresponding theoretical predictions within their total uncertainties. The stability of the combinations of the cross-section measurements to variations in the correlation assumptions, discussed in section 5, is checked for the theory modelling, JES, the most important contributions to the theoretical cross-section predictions (i.e. PDF+αs and scale) and the integrated luminosity. The results of these tests show that their impacts on the cross-section combinations are very small, similar to the stability tests for the combination of the |fLV Vtb | values discussed in section 7.2. 7 Combinations of |fLV Vtb | determinations The measured cross-section for a given single-top-quark production mode, σmeas. , has a linear dependence on |fLV Vtb |2 as defined in eq. (1.1). Thus, a value of |fLV Vtb |2 is ex- tracted from each cross-section measurement and the corresponding theoretical prediction (presented in sections 3 and 2 respectively). These values are then combined per channel, and in an overall |fLV Vtb |2 combination. In the overall combination, the value from the CMS measurement of σs-chan. is excluded. The reason for excluding the CMS s-channel analysis from the overall |fLV Vtb |2 combination is that, at the same centre-of-mass energy, the CMS t-channel determination has strong correlations with the s-channel determina- tion, which contains relatively large uncertainties. The strong correlation between these two measurements makes the combined |fLV Vtb |2 value strongly dependent on the correla- tion assumptions for the dominant uncertainties. This results in a large variation of the combined |fLV Vtb |2 value for different correlation assumptions. All uncertainties in σmeas. and σtheo. are propagated to the |fLV Vtb |2 values, taking into account the correlations described in section 5. The combined value of |fLV Vtb |2 is evaluated using the reference theoretical cross-section central values marked with a † in table 1, where it can also be seen that the Ebeam uncertainty is negligible compared to other uncertainties. For the most precise measurements (i.e. for σt-chan. cross-section – 21 – Inclusive cross-section [pb] ATLAS+CMS ATLAS LHCtopWG CMS 102 stat. total ATLAS+CMS t-channel LHCtop WG NNLO t-channel scale uncertainty NLO + NNLL scale ⊕ PDF ⊕ αs uncertainty tW NLO scale uncertainty JHEP05(2019)088 scale ⊕ PDF ⊕ αs uncertainty 10 s-channel 7 8 s [TeV] Figure 2. Single-top-quark cross-section measurements performed by ATLAS and CMS, together with the combined results shown in sections 6.1–6.3. These measurements are compared with the theoretical predictions at NLO and NLO+NNLL for all three production modes and the prediction at NNLO for t-channel only. The corresponding theoretical uncertainties are also presented. The scale uncertainty for the NNLO prediction is small and is presented as a narrow band under the dashed line. √ measurements at s = 8 TeV), which have a large expected impact on the combination, the other theoretical calculations from table 1 are used as cross-checks. Table 6 contains a summary of the individual |fLV Vtb |2 determinations that are the in- puts to the overall |fLV Vtb |2 combination, together with their experimental and theoretical uncertainties using the reference theoretical cross-sections and uncertainties. For the same processes and at the same centre-of-mass energies, there are some important differences √ between uncertainty categories. In analyses based on t-channel events at s = 7 TeV, the data statistical uncertainty is larger in CMS than in ATLAS because the two experiments use data samples of different size. Differences in the category of jet uncertainties are due to the evaluation of the JES uncertainty in ATLAS using pseudoexperiments, while this √ uncertainty is introduced as a nuisance parameter in the fit in CMS. At s = 8 TeV, the difference between ATLAS and CMS in the background-normalisation category is due to the different techniques used to estimate each background uncertainty. Additional details √ are discussed in appendix A.1. In the CMS tW analysis at s = 7 TeV, the uncertainty – 22 – associated with the size of the simulated samples is evaluated as part of the total statistical uncertainty. The large difference in the pile-up uncertainty between ATLAS and CMS is due to the different methods used to assess this uncertainty, as discussed in section 5.1. √ At s = 8 TeV, the sizes of the data and simulated samples used in the CMS tW analysis are smaller than in the ATLAS analysis, resulting in larger data and simulation statis- tical uncertainties. The large difference between the two experiments in the category of jet uncertainties arises because the JES uncertainty in ATLAS is evaluated in different categories mostly using pseudoexperiments, while in CMS the JES uncertainty is intro- duced as a nuisance parameter in the fit. Further details are discussed in appendix A.2. In the CMS s-channel analysis, the uncertainty associated with the size of the simulated JHEP05(2019)088 samples is evaluated as part of the total statistical uncertainty. More details are discussed in appendix A.3. 7.1 Results The combination of |fLV Vtb |2 is performed using the inputs from all three single-top-quark production modes. Using the same method, the combination of |fLV Vtb |2 is also performed separately for each production mode for comparison. Combining the |fLV Vtb |2 values extracted from the t-channel and tW cross-section √ measurements at s = 7 and 8 TeV from ATLAS and CMS, as well as the ATLAS s- √ channel measurement at s = 8 TeV, results in |fLV Vtb |2 = 1.05 ± 0.02 (stat.) ± 0.06 (syst.) ± 0.01 (lumi.) ± 0.04 (theo.) = 1.05 ± 0.08, with a relative uncertainty of 7.4%. The contribution from each experimental uncertainty category to the total uncertainty in the combined |fLV Vtb |2 value is shown in table 7. The theory modelling uncertainties in signal and background processes, discussed in sec- tion 5.1, dominate the experimental uncertainty and the total uncertainty. The theoretical cross-section uncertainty is the second-largest contribution to the total uncertainty in the combined |fLV Vtb |2 value. Changes in the combined |fLV Vtb |2 value from using alternative NNLO and NLO+NNLL theoretical predictions for the t-channel are less than 1%. Figure 3 illustrates the correlations between the input measurements in the combina- tion. The correlations are all below 0.6. The largest correlations are generally between the measurements in the same experiment at the same centre-of-mass energy, and for those that have large contributions from the same theory modelling components, such as the ATLAS s-channel measurement, which has a correlation of over 0.5 with each of the tW measurements. The BLUE weights for each of the contributing measurements are shown in table 8. √ The t-channel measurements at s = 8 TeV have the largest weight in the combination, √ followed by the t-channel measurements at s = 7 TeV. The tW measurements have smaller cross-section uncertainties than the s-channel measurements, but, in addition to the correlation between tW and s-channel measurements, the tW measurements are also more correlated with the t-channel measurements in each experiment. The negative weights indicate the presence of large correlations between the corresponding measurement and some of the other measurements [81]. – 23 – t-channel t-channel t-channel t-channel tW tW tW tW s-channel ATLAS CMS ATLAS CMS ATLAS CMS ATLAS CMS ATLAS 8 TeV 8 TeV 7 TeV 7 TeV 8 TeV 8 TeV 7 TeV 7 TeV 8 TeV |fLV Vtb |2 1.06 0.99 1.06 1.05 1.03 1.05 1.07 1.02 0.92 Uncertainties: Data statistical 0.01 0.03 0.03 0.06 0.06 0.09 0.18 0.21 0.15 Simulation statistical 0.01 0.01 0.02 0.02 0.01 0.03 0.02 − 0.11 Integrated luminosity 0.02 0.03 0.02 0.02 0.05 0.03 0.07 0.04 0.05 Theory modelling JHEP05(2019)088 ISR/FSR, ren./fact. scale 0.04 0.02 0.03 0.04 0.09 0.13 0.05 0.03 0.06 NLO match., generator 0.03 0.05 0.02 0.04 0.03 − 0.11 − 0.10 Parton shower 0.02 − − 0.01 0.02 0.15 0.16 0.10 0.02 PDF 0.01 0.02 0.03 0.01 0.01 0.02 0.02 0.02 0.03 DS/DR scheme − − − − 0.04 0.02 − 0.06 − Top-quark pT rew. − − − − − <0.01 − − − Background normalisation Top-quark bkg. <0.01 0.02 0.02 0.01 0.02 0.02 0.06 0.06 0.05 Other bkg. from sim. 0.01 <0.01 <0.01 0.03 0.02 0.03 0.09 0.04 0.05 Bkg. from data <0.01 0.02 0.01 0.01 <0.01 − 0.02 − 0.01 Jets JES common 0.03 0.04 0.08 0.01 0.05 0.04 0.17 0.15 0.05 JES flavour <0.01 − 0.02 − 0.02 − − − 0.01 JetID <0.01 − 0.01 − <0.01 − 0.05 − 0.01 JER <0.01 0.01 0.02 <0.01 0.07 0.01 0.02 0.04 0.11 Detector modelling Leptons 0.02 0.01 0.03 0.04 0.03 0.02 0.07 0.05 0.02 HLT (had. part) − − − 0.02 − − − − − miss scale ET <0.01 <0.01 0.03 <0.01 0.06 <0.01 − 0.03 0.01 miss res. ET <0.01 − − − <0.01 − − − 0.01 b-tagging 0.01 0.02 0.04 0.02 0.01 0.01 − 0.02 0.07 Pile-up <0.01 0.01 <0.01 0.01 0.03 <0.01 0.11 0.01 0.01 Top-quark mass 0.01 <0.01 0.01 − 0.05 0.05 − − − Theoretical cross-section PDF+αs 0.03 0.03 0.04 0.04 0.06 0.07 0.08 0.07 0.03 Ren./fact. scale 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.02 Top-quark mass 0.01 0.01 0.01 0.01 0.02 0.02 0.02 0.02 0.02 Ebeam <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 Total systematic uncertainty 0.09 0.09 0.13 0.10 0.18 0.23 0.34 0.24 0.24 Total uncertainty 0.09 0.10 0.13 0.12 0.19 0.24 0.38 0.32 0.28 Table 6. Results of the ATLAS and CMS individual |fLV Vtb |2 determinations that are the inputs to the overall |fLV Vtb |2 combination together with their experimental uncertainties. The values of |fLV Vtb |2 may slightly differ from those published for the different analyses since in this paper the theoretical cross-sections used are those marked with † in table 1. Experimental uncertainties contributing less than 1% are denoted by <0.01. Entries with − mean that this uncertainty was not evaluated for this analysis. Descriptions of the background categories and of the correlations of systematic uncertainties between experiments are presented in appendix A. – 24 – Combined |fLV Vtb |2 1.05 Uncertainty Uncertainty category [%] ∆|fLV Vtb |2 Data statistical 1.8 0.02 Simulation statistical 0.9 0.01 Integrated luminosity 1.3 0.01 Theory modelling 4.5 0.05 Background normalisation 1.3 0.01 Jets 2.6 0.03 JHEP05(2019)088 Detector modelling 1.6 0.02 Top-quark mass 0.7 0.01 Theoretical cross-section 4.3 0.04 Total syst. unc. (excl. lumi.) 7.1 0.07 Total syst. unc. (incl. lumi.) 7.2 0.08 Total uncertainty 7.4 0.08 Table 7. Contributions from each experimental and theoretical uncertainty category to the overall |fLV Vtb |2 combination. The total uncertainty is computed by adding in quadrature all of the indi- vidual systematic uncertainties (including the integrated luminosity and theoretical cross-section) and the statistical uncertainty in data. 1 t -chan. ATLAS 8 TeV 0.46 0.32 0.18 0.28 0.47 0.20 0.19 0.07 1.00 0.9 t -chan. CMS 8 TeV 0.18 0.07 0.08 0.20 0.20 0.34 0.21 1.00 0.8 t -chan. ATLAS 7 TeV 0.32 0.21 0.22 0.24 0.22 0.39 1.00 0.7 t -chan. CMS 7 TeV 0.43 0.21 0.16 0.27 0.50 1.00 0.6 tW ATLAS 8 TeV 0.44 0.23 0.17 0.27 1.00 0.5 tW CMS 8 TeV 0.52 0.44 0.31 1.00 0.4 ATLAS+CMS LHCtop WG 0.3 tW ATLAS 7 TeV 0.55 0.33 1.00 0.2 tW CMS 7 TeV 0.54 1.00 0.1 s -chan. ATLAS 8 TeV 1.00 s -ch tW tW t t t t t t 0 an. C ATL W CM W ATL -chan. -chan. -chan. -chan. ATL M S 7 AS S8 AS CM ATL CM ATL AS T 7 Te TeV 8 Te S7 A S8 A 8 Te eV V V TeV S 7 T eV TeV S 8 T eV V Figure 3. Correlation matrix of the overall |fLV Vtb |2 combination. Each bin corresponds to a measurement in a given production mode, experiment, and at a given centre-of-mass energy. – 25 – √ Process s Experiment BLUE weight ATLAS 0.56 8 TeV CMS 0.27 t-channel ATLAS 0.07 7 TeV CMS 0.15 ATLAS 0.05 8 TeV CMS −0.04 tW ATLAS −0.02 7 TeV CMS 0.02 JHEP05(2019)088 s-channel 8 TeV ATLAS −0.07 Table 8. BLUE weights for the overall |fLV Vtb |2 combination. √ The combined |fLV Vtb | value from the cross-section measurements at s = 7 and 8 TeV, including uncertainties in σtheo. for each production mode, is |fLV Vtb | = 1.02 ± 0.01 (stat.) ± 0.03 (syst.) ± 0.01 (lumi.) ± 0.02 (theo.) = 1.02 ± 0.04 (meas.) ± 0.02 (theo.) = 1.02 ± 0.04, with a relative uncertainty of 3.7%, which improves on the precision of 4.7% of the most precise individual |fLV Vtb | extraction, which comes from the ATLAS t-channel analysis at √ s = 8 TeV [32]. This is a 30% improvement over the Tevatron combination [30]. The |fLV Vtb | values are also combined for each production mode, combining across experiments and centre-of-mass energies. For the s-channel, the ATLAS and CMS mea- √ surements at s = 8 TeV are combined. The results are t-channel : |fLV Vtb | = 1.02 ± 0.01 (stat.) ± 0.03 (syst.) ± 0.01 (lumi.) ± 0.02 (theo.) = 1.02 ± 0.04 (meas.) ± 0.02 (theo.) = 1.02 ± 0.04, tW : |fLV Vtb | = 1.02 ± 0.03 (stat.) ± 0.07 (syst.) ± 0.02 (lumi.) ± 0.04 (theo.) = 1.02 ± 0.09 (meas.) ± 0.04 (theo.) = 1.02 ± 0.09, s-channel : |fLV Vtb | = 0.97 ± 0.08 (stat.) ± 0.12 (syst.) ± 0.02 (lumi.) ± 0.02 (theo.) = 0.97 ± 0.15 (meas.) ± 0.02 (theo.) = 0.97 ± 0.15. The relative uncertainties are 3.9%, 8.4% and 15.0% respectively. In all cases, these results are more precise than the best individual determinations of |fLV Vtb |, which have uncertain- ties of 4.7%, 9.9% and 20.8% for the t-channel [32], tW [34] and s-channel [37] analyses respectively. Figure 4 shows a summary of the |fLV Vtb | combinations. The combination is dominated by the t-channel analyses. 7.2 Stability tests The stability of the combination of the |fLV Vtb |2 values to variations in the correlation assumptions, discussed in section 5, is checked for the dominant uncertainty contributions. – 26 – ATLAS+CMS LHCtop WG σmeas. |fLVVtb| = σtheo. from single-top-quark production σtheo.: NLO (t- and s-channel), NLO+NNLL (tW) total theo. δσtheo.: scale ⊕ PDF ⊕ αs ⊕ mt ⊕ Ebeam mt = 172.5 GeV |fLVVtb| ± (meas.) ± (theo.) ATLAS+CMS LHCtop WG 1.02 ± 0.04 ± 0.02 t -channel, s = 7, 8 TeV JHEP05(2019)088 ATLAS+CMS LHCtop WG 1.02 ± 0.09 ± 0.04 tW , s = 7, 8 TeV ATLAS+CMS LHCtop WG 0.97 ± 0.15 ± 0.02 s -channel, s = 8 TeV ATLAS+CMS LHCtop WG 1.02 ± 0.04 ± 0.02 t -channel, tW , s -channel, s = 7, 8 TeV 0.6 0.8 1 1.2 1.4 |fLVVtb| Figure 4. The combined |fLV Vtb | value extracted from the t-channel and tW cross-section measure- √ ments at s = 7 and 8 TeV from ATLAS and CMS, as well as the ATLAS s-channel measurement √ at s = 8 TeV, is shown together with the combined |fLV Vtb | values for each production mode. The theoretical predictions for t-channel and s-channel production are computed at NLO accuracy, while the theoretical predictions for tW are calculated at NLO+NNLL accuracy. The σtheo. uncertainties used to compute |fLV Vtb | include scale, PDF+αs , mt , and Ebeam variations. The correlation values are varied for the theory modelling, JES, and the most important contributions to the theoretical cross-section predictions (i.e. PDF+αs and scale). Because of the scheme that is used for the correlations, stability tests are also performed for the uncertainties associated with the integrated luminosity. Figure 5 summarises the results of these stability tests, where the correlations between ATLAS and CMS (and also between centre-of-mass energies for the integrated luminosity) are varied. The uncertainties in the theory modelling category (i.e. scales and radiation mod- elling, NLO matching, and PS and hadronisation) are varied from their default value of fully correlated to half correlated and to the more extreme tests of uncorrelated and half anti-correlated. The JES category is varied from its default value of uncorrelated to half correlated and half anti-correlated and the more extreme variation of fully correlated. The theoretical cross-section uncertainties, PDF+αs and scale, are varied from their default values of fully correlated to half correlated, uncorrelated and half anti-correlated. For the integrated luminosity, the correlation between ATLAS and CMS is varied from its default – 27 – ATLAS+CMS LHCtop WG ρ = −0.5 Scales and radiation modelling ρ = 0.0 ρ = 1.0 (default) ρ = +0.5 NLO matching ρ = 1.0 ρ = 1.0 (default) PS ρ = 1.0 (default) JES scale ρ = 0.0 (default) PDF (theo.) JHEP05(2019)088 ρ = 1.0 (default) Scale (theo.) ρ = 1.0 (default) Int. lumi. 8 TeV (ATLAS, CMS) ρ = 0.3 (default) Int. lumi. 7 TeV (ATLAS, CMS) ρ = 0.3 (default) Int. lumi. 7, 8 TeV (CMS) ρ = 0.0 (default) Int. lumi. 7, 8 TeV (ATLAS) ρ = 0.0 (default) −0.008 −0.006 −0.004 −0.002 0 0.002 −0.1 0 0.1 ∆|fLVVtb|2 / |fLVVtb|2 ∆(δ|fLVVtb|2) / δ|fLVVtb|2 Figure 5. Results of the stability tests performed by varying of the correlation assumptions in different uncertainty categories: theory modelling (scales and radiation modelling, NLO matching, and PS and hadronisation), JES, dominant theoretical cross-section predictions (i.e. PDF+αs and scale) and integrated luminosity. Two or three variations are considered depending on the uncer- tainty category. The corresponding relative shifts (with shift = varied − nominal) in the central value, ∆|fLV Vtb |2 /|fLV Vtb |2 , and in its uncertainty, ∆(δ|fLV Vtb |2 )/(δ|fLV Vtb |2 ), are shown. value of 30% correlated to half correlated and uncorrelated. The correlation between differ- ent centre-of-mass energies for each experiment is varied from the default of uncorrelated to half and fully correlated. The correlation of the theoretical scale uncertainty between different processes is also tested. For all variations, the relative changes in the central value of the combined |fLV Vtb | are significantly smaller (<0.5%) than the relative total uncertainty of 3.7%. Additionally, the relative changes in the total uncertainty are below 0.004, i.e., less than 10% of the total uncertainty of 0.04. These tests show that the result of the combination is robust and does not critically depend on any of the correlation as- sumptions. The cross-section combinations similarly do not depend significantly on any of the correlation assumptions. 8 Summary The combinations of single-top-quark production cross-section measurements in the t- channel, tW , and s-channel production modes are presented, using data from LHC pp – 28 – collisions collected by the ATLAS and CMS Collaborations. The combinations for each √ production mode are performed at s = 7 and 8 TeV, using data corresponding to in- √ tegrated luminosities of 1.17 to 5.1 fb−1 at s = 7 TeV, and of 12.2 to 20.3 fb−1 at √ s = 8 TeV. The combined t-channel cross-sections are found to be 67.5 ± 5.7 pb and √ 87.7 ± 5.8 pb at s = 7 and 8 TeV respectively. The values of the combined tW cross- √ sections at s = 7 and 8 TeV are 16.3 ± 4.1 pb and 23.1 ± 3.6 pb respectively. For the √ s-channel cross-section, the combination yields 4.9 ± 1.4 pb at s = 8 TeV. The square of the magnitude of the CKM matrix element Vtb multiplied by a form factor accounting for possible contributions from physics beyond the SM, fLV , is determined from each produc- tion mode at each centre-of-mass energy, using the ratio of the measured cross-section to JHEP05(2019)088 its theoretical prediction, and assuming that the top-quark-related CKM matrix elements obey the relation |Vtd |, |Vts |  |Vtb |. The values of |fLV Vtb |2 extracted from individual ratios √ at s = 7 and 8 TeV yield a combined value of |fLV Vtb | = 1.02±0.04 (meas.)±0.02 (theo.). All combined measurements are consistent with their corresponding SM predictions. A Systematic uncertainties in cross-section measurements The single-top-quark cross-sections measured by the ATLAS and CMS Collaborations at √ s = 7 and 8 TeV, as well as the uncertainties and their correlations between experiments, are summarised in tables 9–13 for the t-channel, tW , and s-channel production modes. Similar to the approach that is followed in combinations using the BLUE method, the total uncertainty in these tables is evaluated as the sum in quadrature of the individual uncertainties. To obtain the impact of each source of uncertainty, the input analyses use either pseudoexperiments or approximate procedures which neglect the correlations between sources of uncertainty introduced by the fit to data. In the latter case, this may lead to small changes in the total uncertainty compared with the input measurements presented in table 2. The likelihood fit includes all nuisance parameters at the same time to evaluate the total uncertainty. The method used by each input analysis to evaluate the individual uncertainties is described below. A.1 Systematic uncertainties in t-channel cross-section measurements √ The t-channel cross-sections measured by the ATLAS and CMS Collaborations at s = √ 7 TeV [59, 60] and s = 8 TeV [32, 33], as well as the uncertainties and their correlations between experiments, are shown in tables 9 and 10 respectively. The total uncertainty given for each measurement is the sum in quadrature of the individual uncertainties. This is slightly different from the total uncertainty shown in table 2 for the CMS measurements √ at s = 7 and 8 TeV since the total uncertainty is evaluated, through the fit, by varying all nuisance parameters at the same time. √ In table 9, the CMS result at s = 7 TeV has a larger data statistical uncertainty than the ATLAS result because the two experiments use data samples of different size (see table 2). In the background-normalisation category, the “Bkg. from MC” uncertainty refers to the tW , s-channel, tt̄, W/Z+jets, and diboson backgrounds. In the ATLAS measure- ment, the normalisation uncertainty in the multijet background is estimated by comparing – 29 – √ √ ATLAS (σt-chan. , s = 7 TeV) CMS (σt-chan. , s = 7 TeV) Cross-section 68.0 pb 67.2 pb Uncertainty category Uncertainty Uncertainty ρ Data statistical 2.7% 5.8% 0.0 Simulation statistical 1.9% 1.9% 0.0 Integrated luminosity 1.8% 2.2% 0.3 Theory modelling Ren./fact. scales, ISR/FSR 2.6% Ren./fact. scales 3.5% 1.0 NLO match., PS (tt̄, t-chan.) 2.2% Sig. modelling (NLO method) 4.3% 1.0 Parton shower 0.8% 1.0 PDF 3.2% PDF 1.4% 1.0 Category subtotal 4.7% 5.8% 0.85 JHEP05(2019)088 Background norm. Bkg. from MC: norm. 1.6% Bkg. from MC: norm. 2.7% 0.0 Bkg. from MC/data: multijet norm. 1.4% Bkg. from data: multijet norm. 1.3% 0.0 Category subtotal 2.1% 3.0% 0.0 Jets JES common 7.6% JES 0.9% 0.0 JES flavour 1.8% 0.0 JetID 1.1% 0.0 JER 1.9% JER 0.3% 0.0 Category subtotal 8.1% 0.9% 0.0 Detector modelling Lepton modelling 2.8% Lepton modelling 3.5% 0.0 HLT (had. part) 1.5% 0.0 miss modelling ET 2.6% miss modelling ET 0.1% 0.0 b-tagging 3.9% b-tagging 2.2% 0.0 Pile-up 0.2% Pile-up 0.6% 0.0 Category subtotal 5.5% 4.4% 0.0 Total uncertainty 11.7% 10.2% 0.20 Table 9. Measured cross-sections, uncertainty components, their magnitudes (relative to the indi- vidual measurements) and the correlation (ρ) between the ATLAS and CMS σt-chan. measurements √ at s = 7 TeV. Uncertainties in the same row can be compared between experiments, as detailed in the text. The naming conventions follow those of the corresponding experiments. background estimates made using different techniques based on data and simulation sam- ples, while in the CMS measurement, it is estimated from the difference between alternative methods based on data. There is also a large difference between the two experiments in the jets category. As discussed in section 5.1, the uncertainty in each JES component in the ATLAS measurement is evaluated using pseudoexperiments. The CMS measurement is a BLUE combination of three different measurements, two of which introduce JES com- ponents as a nuisance parameter in the fit. Since these fits use additional control regions, the impact of the JES is reduced. In addition, the JES uncertainty in the analyses at √ s = 7 TeV is smaller for CMS [100] than for ATLAS [99]. √ In the analyses at s = 8 TeV, summarised in table 10, the difference between ATLAS and CMS in the background normalisation category is due to the different techniques used to estimate each background uncertainty. The “Other bkg. from MC” uncertainty includes the contributions from the tW , s-channel, tt̄, W/Z+jets, and diboson backgrounds in the ATLAS analysis, and the tW , s-channel, Z+jets, and diboson backgrounds in the CMS analysis. In the ATLAS measurement, the normalisation uncertainties associated with the – 30 – √ √ ATLAS (σt-chan. , s = 8 TeV) CMS (σt-chan. , s = 8 TeV) Cross-section 89.6 pb 83.6 pb Uncertainty category Uncertainty Uncertainty ρ Data statistical 1.4% 2.7% 0.0 Simulation statistical 0.8% 0.7% 0.0 Integrated luminosity 1.9% 2.6% 0.3 Theory modelling Ren./fact. scales 3.6% Ren./fact. scales 1.9% 1.0 NLO match. 3.3% NLO match., 4FS vs 5FS 4.9% 1.0 Parton shower 2.1% 1.0 PDF 1.3% PDF 1.9% 1.0 Category subtotal 5.5% 5.6% 0.84 JHEP05(2019)088 Background norm. tt̄, tW and s-chan. norm. 0.1% tt̄ and W +jets norm. 2.2% 0.0 Other bkg. from MC: norm. 0.9% Other bkg. from MC: norm. 0.3% 0.0 Bkg. from MC/data: multijet norm. 0.3% Bkg. from data: multijet norm. 2.3% 0.0 Category subtotal 1.0% 3.2% 0.0 Jets JES common 3.2% JES 4.2% 0.0 JES flavour 0.2% 0.0 JetID 0.1% 0.0 JER 0.4% JER 0.7% 0.0 Category subtotal 3.2% 4.3% 0.0 Detector modelling Lepton modelling 1.9% Lepton modelling 0.6% 0.0 miss scale ET 0.4% miss modelling ET 0.3% 0.0 miss ET resolution 0.2% 0.0 b-tagging 1.1% b-tagging 2.5% 0.0 Pile-up 0.3% Pile-up 0.7% 0.0 Category subtotal 2.3% 2.7% 0.0 Total uncertainty 7.3% 9.0% 0.42 Table 10. Measured cross-sections, uncertainty components, their magnitudes (relative to the indi- vidual measurements) and the correlation (ρ) between the ATLAS and CMS σt-chan. measurements √ at s = 8 TeV. Uncertainties in the same row can be compared between experiments, as detailed in the text. The naming conventions follow those of the corresponding experiments. top-quark, W/Z+jets, diboson, and multijet backgrounds are estimated using pseudoexper- iments. Variations in the theoretical cross-section predictions for these processes are also considered, except for the multijet background, where the results obtained from data and simulation samples analysed with various techniques are compared. In the CMS measure- ment, the uncertainty in the multijet background is estimated from the difference between alternative methods based on data. The normalisations of the tt̄ and W +jets backgrounds are included as nuisance parameters in the fit, while the shapes of their distributions are adjusted by corrections based on data in control regions. A.2 Systematic uncertainties in tW cross-section measurements √ The tW cross-sections measured by the ATLAS and CMS Collaborations at s = 7 TeV [61, √ 62] and s = 8 TeV [34, 35], as well as the uncertainties and their correlations between experiments, are shown in tables 11 and 12 respectively. √ In table 11, the CMS measurement at s = 7 TeV takes into account the uncer- tainty associated with the size of the simulated event samples using the Barlow-Beeston – 31 – √ √ ATLAS (σtW , s = 7 TeV) CMS (σtW , s = 7 TeV) Cross-section 16.8 pb 16.0 pb Uncertainty category Uncertainty Uncertainty ρ Data statistical 17.0% 20.8% 0.0 Simulation statistical 2.0% 0.0% 0.0 Integrated luminosity 7.0% 4.3% 0.3 Theory modelling ISR/FSR, scales 5.0% ISR/FSR, scales 2.8% 1.0 tW /tt̄ NLO match. 10.0% 1.0 tW /tt̄ PS 15.0% tW ME/PS match. thr. 10.1% 1.0 PDF 2.0% PDF 2.1% 1.0 DR/DS scheme 5.9% 1.0 JHEP05(2019)088 Category subtotal 18.8% 12.2% 0.74 Background norm. tt̄ norm. 6.0% tt̄ norm. 6.0% 0.0 Z+jets, diboson norm. 8.0% Z/γ ∗ +jets norm. 4.2% 0.0 Bkg. from data: fake lept. norm. 2.0% 0.0 Category subtotal 10.2% 7.3% 0.0 Jets JES 16.0% JES 15.1% 0.0 JetID 5.0% 0.0 JER 2.0% JER 3.6% 0.0 Category subtotal 16.9% 15.6% 0.0 Detector modelling Lepton modelling 7.0% Lepton modelling 5.2% 0.0 miss modelling ET 2.5% 0.0 b-tagging 1.9% 0.0 Pile-up 10.0% Pile-up 1.5% 0.0 Category subtotal 12.2% 6.2% 0.0 Total uncertainty 35.1% 30.6% 0.17 Table 11. Measured cross-sections, uncertainty components, their magnitudes (relative to the individual measurements) and the correlation (ρ) between the ATLAS and CMS σtW measurements √ at s = 7 TeV. Uncertainties in the same row can be compared between experiments, as detailed in the text. The naming conventions follow those of the corresponding experiments. method [125]. This contribution is included as part of the total statistical uncertainty. This uncertainty is therefore considered to be zero for the CMS measurement to avoid double-counting. Since the statistical uncertainties in the data and simulation are uncorre- lated between the two experiments, this choice has almost no effect on the combination. In the ATLAS analysis, the normalisation uncertainty in the misidentified lepton (fake lept.) background is conservatively taken to be 100%, based on comparisons in data. The ET miss uncertainties are included in the pile-up modelling uncertainty. The b-tagging uncertainty is not considered because no b-tagging criterion is required in the event selection. The large difference in the pile-up uncertainty between ATLAS and CMS arises from different methods employed by the experiments to assess this uncertainty, as discussed in section 5.1. √ In table 12, the tW measurement by CMS at s = 8 TeV is based on the first half √ of the s = 8 TeV data sample. This leads to a larger data statistical uncertainty for CMS than for ATLAS. For the same reason, the sizes of the simulated event samples are smaller, resulting in a larger simulation statistical uncertainty in the CMS result. In the ATLAS measurement, the normalisation uncertainty in the multijet background is estimated by comparing estimates made using different techniques on data and simulation – 32 – √ √ ATLAS (σtW , s = 8 TeV) CMS (σtW , s = 8 TeV) Cross-section 23.0 pb 23.4 pb Uncertainty category Uncertainty Uncertainty ρ Data statistical 5.8% 8.1% 0.0 Simulation statistical 0.5% 2.4% 0.0 Integrated luminosity 4.6% 3.0% 0.3 Theory modelling ISR/FSR 8.8% Ren./fact. scales 12.4% 1.0 NLO match. 2.5% 1.0 Parton shower 1.7% Parton shower 14.1% 1.0 PDF 0.6% PDF 1.7% 1.0 tW /tt̄ overlap 3.5% tW DR/DS scheme 2.1% 1.0 JHEP05(2019)088 Top-quark pT reweight. 0.4% 0.0 Category subtotal 10.0% 19.0% 0.75 Background norm. tt̄ norm. 1.9% tt̄ norm. 1.7% 0.0 Z+jets, diboson norm. 2.0% Z+jets norm. 2.6% 0.0 Bkg. from data: fake lept. norm. 0.3% 0.0 Category subtotal 2.8% 3.1% 0.0 Jets JES common 5.3% JES 3.8% 0.0 JES flavour 1.9% 0.0 JetID 0.2% 0.0 JER 6.5% JER 0.9% 0.0 Category subtotal 8.6% 3.9% 0.0 Detector modelling Lepton modelling 3.0% Lepton modelling 1.8% 0.0 miss scale ET 5.5% miss modelling ET 0.4% 0.0 miss resolution ET 0.2% 0.0 b-tagging 1.0% b-tagging 0.9% 0.0 Pile-up 2.7% Pile-up 0.4% 0.0 Category subtotal 6.9% 2.0% 0.0 Total uncertainty 16.8% 21.7% 0.40 Table 12. Measured cross-sections, uncertainty components, their magnitudes (relative to the individual measurements) and the correlation (ρ) between the ATLAS and CMS σtW measurements √ at s = 8 TeV. Uncertainties in the same row can be compared between experiments, as detailed in the text. The naming conventions follow those of the corresponding experiments. samples, while in the CMS measurement, the uncertainty contribution of the multijet background is estimated from the difference between alternative methods based on data. In the ATLAS analysis, the misidentified lepton and non-prompt (fake lept.) background has a normalisation uncertainty of 60%, based on comparisons in data, to account for possible mismodelling of the jet multiplicity and jet acceptance. There is a large difference between the two experiments in the jets category. As discussed in section 5.1, the JES uncertainty in the ATLAS measurement is evaluated in different categories. The detector modelling component of the JES common uncertainty is constrained in the fit to data. In the CMS measurement, different components of the JES uncertainty are grouped together, and the group is introduced as a nuisance parameter in the fit. The ET miss modelling uncertainty is smaller for the CMS measurement due to the use of low-pT jets, which allows this uncertainty to be constrained in the fit to data, as discussed in section 5.1. – 33 – √ √ ATLAS (σs-chan. , s = 8 TeV) CMS (σs-chan. , s = 8 TeV) Cross-section 4.8 pb 13.4 pb Uncertainty category Uncertainty Uncertainty ρ Data statistical 16.0% 10.0% 0.0 Simulation statistical 12.0% 0.0% 0.0 Integrated luminosity 5.0% 4.0% 0.3 Theory modelling Ren./fact. scales 7.0% Ren./fact. scales 30.0% 1.0 tt̄, t-chan. generator 11.0% 1.0 Parton shower 2.0% Parton shower 7.0% 1.0 PDF 3.0% PDF 7.0% 1.0 Top-quark pT reweight. 6.0% 0.0 JHEP05(2019)088 Category subtotal 13.5% 32.2% 0.56 Background norm. t-chan., tt̄ norm. 5.0% t-chan., tt̄ norm. 12.0% 0.0 W/Z+jets, diboson norm. 6.0% W/Z+jets, diboson norm. 12.0% 0.0 Bkg. from data: multijet norm. 1.0% Bkg. from data: multijet norm. 2.0% 0.0 Category subtotal 7.9% 17.1% 0.0 Jets JES common 5.0% JES 32.5% 0.0 JES flavour 1.0% 0.0 JetID 1.0% 0.0 JER 12.0% JER 10.2% 0.0 Category subtotal 13.1% 34.1% 0.0 Detector modelling Lepton modelling 2.4% Lepton modelling 1.0% 0.0 miss ET scale 1.0% miss ET modelling 6.0% 0.0 miss ET res 1.0% 0.0 b-tagging 8.0% b-tagging 14.0% 0.0 Pile-up 1.0% Pile-up 9.0% 0.0 Category subtotal 8.5% 17.7% 0.0 Total uncertainty 30.2% 54.0% 0.15 Table 13. Measured cross-sections, uncertainty components, their magnitudes (relative to the indi- vidual measurements) and the correlation (ρ) between the ATLAS and CMS σs-chan. measurements √ at s = 8 TeV. Uncertainties in the same row can be compared between experiments, as detailed in the text. The naming conventions follow those of the corresponding experiments. A.3 Systematic uncertainties in s-channel cross-section measurements √ The s-channel cross-sections measured by the ATLAS and CMS Collaborations at s = 8 TeV [37, 63], as well as the uncertainties and their correlations between experiments, are shown in table 13. The CMS measurement takes into account the uncertainty associated with the size of the simulated event samples using the Barlow-Beeston method [125]. The contribution is included in the total statistical uncertainty. This uncertainty is therefore considered to be zero for the CMS measurement to avoid double-counting. Since the statistical uncertainties in the data and simulation are uncorrelated between the two experiments, this choice has almost no effect on the combination. The result from ATLAS has smaller uncertainties. This is attributed to the use of the latest simulation samples with tuned parameters [126] as well as the use of the matrix element method in the ATLAS analysis. In addition, all sys- tematic uncertainties are profiled in the ATLAS analysis, while in the CMS analysis, major – 34 – uncertainties, including those from jets and in the theory modelling category, are excluded from the fit and evaluated using pseudoexperiments. The total uncertainties in table 13 are slightly different from the uncertainties shown in table 2 because here the uncertainties are summed in quadrature, while in the input analyses the impacts of at least some of the uncertainties are included in the fits to data. In particular, the difference between the relative total uncertainty shown in table 2 for the ATLAS measurement, i.e. 34.4%, and the relative total uncertainty shown in table 13 is due to the usage of an approximate procedure to compute the individual uncertainty contributions. Possible correlation terms between the systematic uncertainties introduced by the fit are not included here. JHEP05(2019)088 Acknowledgments We thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS and CMS 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 Re- public; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; MNE/IFA, Romania; MES of Russia and NRC KI, Russian Federation; JINR; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, CANARIE, CRC and Compute Canada, Canada; COST, ERC, ERDF, Horizon 2020, and Marie Sklodowska-Curie Actions, European Union; Investisse- ments d’ Avenir Labex and Idex, ANR, France; DFG and AvH Foundation, Germany; Her- akleitos, 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. We acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies: BMBWF and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, FAPERGS, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES and CSF (Croatia); RPF (Cyprus); SENESCYT (Ecuador); MoER, ERC IUT, and ERDF (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); NKFIA (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); MES (Latvia); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MOS (Montenegro); MBIE (New Zealand); PAEC (Pakistan); – 35 – MSHE and NSC (Poland); FCT (Portugal); JINR (Dubna); MON, RosAtom, RAS, RFBR, and NRC KI (Russia); MESTD (Serbia); SEIDI, CPAN, PCTI, and FEDER (Spain); MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); MST (Taipei); ThEPCenter, IPST, STAR, and NSTDA (Thailand); TUBITAK and TAEK (Turkey); NASU and SFFR (Ukraine); STFC (United Kingdom); DOE and NSF (U.S.A.). Individuals have received support from the Marie-Curie programme and the European Research Council and Horizon 2020 Grant, contract No. 675440 (European Union); the Leventis Foundation; the A.P. Sloan Foundation; the Alexander von Humboldt Founda- tion; the Belgian Federal Science Policy Office; the Fonds pour la Formation à la Recherche JHEP05(2019)088 dans l’Industrie et dans l’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the F.R.S.-FNRS and FWO (Belgium) under the “Excellence of Science — EOS” — be.h project n. 30820817; the Beijing Municipal Sci- ence & Technology Commission, No. Z181100004218003; the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Lendület (“Momentum”) Programme and the János Bolyai Research Scholarship of the Hungarian Academy of Sciences, the New National Excellence Program ÚNKP, the NKFIA research grants 123842, 123959, 124845, 124850, and 125105 (Hungary); the Council of Science and Industrial Research, India; the HOMING PLUS programme of the Foundation for Polish Science, cofinanced from European Union, Regional Development Fund, the Mobility Plus programme of the Min- istry of Science and Higher Education, the National Science Center (Poland), contracts Harmonia 2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543, 2014/15/B/ST2/03998, and 2015/19/B/ST2/02861, Sonata-bis 2012/07/E/ST2/01406; the National Priorities Re- search Program by Qatar National Research Fund; the Programa Estatal de Fomento de la Investigación Cientı́fica y Técnica de Excelencia Marı́a de Maeztu, grant MDM-2015-0509 and the Programa Severo Ochoa del Principado de Asturias; the Thalis and Aristeia pro- grammes cofinanced by EU-ESF and the Greek NSRF; the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University and the Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand); the Welch Foundation, contract C-1845; and the Weston Havens Foundation (U.S.A.). 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Dattagupta129 , T. Daubney45 , S. D’Auria67a,67b , W. Davey24 , C. David45 , T. Davidek141 , D.R. Davis48 , E. Dawe103 , I. Dawson147 , K. De8 , R. De Asmundis68a , JHEP05(2019)088 A. De Benedetti126 , M. De Beurs119 , S. De Castro23b,23a , S. De Cecco71a,71b , N. De Groot118 , P. de Jong119 , H. De la Torre105 , A. De Maria15c , D. De Pedis71a , A. De Salvo71a , U. De Sanctis72a,72b , M. De Santis72a,72b , A. De Santo154 , K. De Vasconcelos Corga100 , J.B. De Vivie De Regie130 , C. Debenedetti144 , D.V. Dedovich78 , M. Del Gaudio40b,40a , J. Del Peso97 , Y. Delabat Diaz45 , D. Delgove130 , F. Deliot143 , C.M. Delitzsch7 , M. Della Pietra68a,68b , D. Della Volpe53 , A. Dell’Acqua35 , L. Dell’Asta25 , M. Delmastro5 , C. Delporte130 , P.A. Delsart57 , D.A. DeMarco165 , S. Demers181 , M. Demichev78 , G. Demontigny108 , S.P. Denisov122 , D. Denysiuk119 , L. D’Eramo134 , D. Derendarz83 , J.E. Derkaoui34d , F. Derue134 , P. Dervan89 , K. Desch24 , C. Deterre45 , K. Dette165 , M.R. 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Hod178 , M.C. Hodgkinson147 , A. Hoecker35 , F. Hoenig113 , D. Hohn51 , D. Hohov130 , T.R. Holmes36 , M. Holzbock113 , L.B.A.H Hommels31 , S. Honda167 , T. Honda80 , T.M. Hong137 , A. Hönle114 , B.H. Hooberman171 , W.H. Hopkins6 , Y. Horii116 , P. Horn47 , A.J. Horton150 , L.A. Horyn36 , J-Y. Hostachy57 , A. Hostiuc146 , S. Hou156 , A. Hoummada34a , J. Howarth99 , J. Hoya87 , JHEP05(2019)088 M. Hrabovsky128 , J. Hrdinka75 , I. Hristova19 , J. Hrivnac130 , A. Hrynevich107 , T. Hryn’ova5 , P.J. Hsu63 , S.-C. Hsu146 , Q. Hu29 , S. Hu59c , Y. Huang15a , Z. Hubacek140 , F. Hubaut100 , M. Huebner24 , F. Huegging24 , T.B. Huffman133 , M. Huhtinen35 , R.F.H. Hunter33 , P. Huo153 , A.M. Hupe33 , N. Huseynov78,ae , J. Huston105 , J. Huth58 , R. Hyneman104 , S. Hyrych28a , G. Iacobucci53 , G. Iakovidis29 , I. Ibragimov149 , L. Iconomidou-Fayard130 , Z. Idrissi34e , P. Iengo35 , R. Ignazzi39 , O. Igonkina119,z , R. Iguchi161 , T. Iizawa53 , Y. Ikegami80 , M. Ikeno80 , D. Iliadis160 , N. Ilic118 , F. Iltzsche47 , G. Introzzi69a,69b , M. Iodice73a , K. Iordanidou38 , V. Ippolito71a,71b , M.F. Isacson170 , N. Ishijima131 , M. Ishino161 , M. Ishitsuka163 , W. Islam127 , C. Issever133 , S. Istin158 , F. Ito167 , J.M. Iturbe Ponce62a , R. Iuppa74a,74b , A. Ivina178 , H. Iwasaki80 , J.M. Izen42 , V. Izzo68a , P. Jacka139 , P. Jackson1 , R.M. Jacobs24 , V. Jain2 , G. Jäkel180 , K.B. Jakobi98 , K. Jakobs51 , S. Jakobsen75 , T. Jakoubek139 , J. Jamieson56 , D.O. Jamin127 , R. Jansky53 , J. Janssen24 , M. Janus52 , P.A. Janus82a , G. Jarlskog95 , N. Javadov78,ae , T. Javůrek35 , M. Javurkova51 , F. Jeanneau143 , L. Jeanty129 , J. Jejelava157a,af , A. Jelinskas176 , P. Jenni51,d , J. Jeong45 , N. Jeong45 , S. Jézéquel5 , H. Ji179 , J. Jia153 , H. Jiang77 , Y. Jiang59a , Z. Jiang151,q , S. Jiggins51 , F.A. Jimenez Morales37 , J. Jimenez Pena172 , S. Jin15c , A. Jinaru27b , O. Jinnouchi163 , H. Jivan32c , P. Johansson147 , K.A. Johns7 , C.A. Johnson64 , K. Jon-And44a,44b , R.W.L. 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Korolkova147 , – 49 – N. Korotkova112 , O. Kortner114 , S. Kortner114 , T. Kosek141 , V.V. Kostyukhin24 , A. Kotwal48 , A. Koulouris10 , A. Kourkoumeli-Charalampidi69a,69b , C. Kourkoumelis9 , E. Kourlitis147 , V. Kouskoura29 , A.B. Kowalewska83 , R. Kowalewski174 , C. Kozakai161 , W. Kozanecki143 , A.S. Kozhin122 , V.A. Kramarenko112 , G. Kramberger90 , D. Krasnopevtsev59a , M.W. Krasny134 , A. Krasznahorkay35 , D. Krauss114 , J.A. Kremer82a , J. Kretzschmar89 , P. Krieger165 , A. Krishnan60b , K. Krizka18 , K. Kroeninger46 , H. Kroha114 , J. Kroll139 , J. Kroll135 , J. Krstic16 , U. Kruchonak78 , H. Krüger24 , N. Krumnack77 , M.C. Kruse48 , T. Kubota103 , S. Kuday4b , J.T. Kuechler45 , S. Kuehn35 , A. Kugel60a , T. Kuhl45 , V. Kukhtin78 , R. Kukla100 , Y. Kulchitsky106,ai , S. Kuleshov145b , Y.P. Kulinich171 , M. Kuna57 , T. Kunigo84 , A. Kupco139 , T. Kupfer46 , O. Kuprash51 , H. Kurashige81 , L.L. Kurchaninov166a , Y.A. Kurochkin106 , A. Kurova111 , M.G. Kurth15d , E.S. 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Magerl51 , N. Magini77 , D.J. Mahon38 , C. Maidantchik79b , T. Maier113 , A. Maio138a,138b,138d , O. Majersky28a , S. Majewski129 , Y. Makida80 , N. Makovec130 , B. Malaescu134 , Pa. Malecki83 , V.P. Maleev136 , F. Malek57 , U. Mallik76 , D. Malon6 , C. Malone31 , S. Maltezos10 , S. Malyukov35 , J. Mamuzic172 , G. Mancini50 , I. Mandić90 , L. Manhaes de Andrade Filho79a , I.M. Maniatis160 , J. Manjarres Ramos47 , K.H. Mankinen95 , A. Mann113 , A. Manousos75 , B. Mansoulie143 , I. Manthos160 , S. Manzoni119 , A. Marantis160 , G. Marceca30 , L. Marchese133 , G. Marchiori134 , M. Marcisovsky139 , C. Marcon95 , C.A. Marin Tobon35 , M. Marjanovic37 , F. Marroquim79b , Z. Marshall18 , M.U.F Martensson170 , – 50 – S. Marti-Garcia172 , C.B. Martin124 , T.A. Martin176 , V.J. Martin49 , B. Martin dit Latour17 , M. Martinez14,x , V.I. Martinez Outschoorn101 , S. Martin-Haugh142 , V.S. Martoiu27b , A.C. Martyniuk93 , A. Marzin35 , L. Masetti98 , T. Mashimo161 , R. Mashinistov109 , J. Masik99 , A.L. Maslennikov121b,121a , L.H. Mason103 , L. Massa72a,72b , P. Massarotti68a,68b , P. Mastrandrea70a,70b , A. Mastroberardino40b,40a , T. Masubuchi161 , A. Matic113 , P. Mättig24 , J. Maurer27b , B. Maček90 , S.J. Maxfield89 , D.A. Maximov121b,121a , R. Mazini156 , I. Maznas160 , S.M. Mazza144 , S.P. Mc Kee104 , A. McCarn, Deiana41 , T.G. McCarthy114 , L.I. McClymont93 , W.P. McCormack18 , E.F. McDonald103 , J.A. Mcfayden35 , G. Mchedlidze52 , M.A. McKay41 , K.D. McLean174 , S.J. McMahon142 , P.C. McNamara103 , C.J. McNicol176 , R.A. McPherson174,ac , J.E. Mdhluli32c , Z.A. Meadows101 , S. Meehan146 , T.M. Megy51 , S. Mehlhase113 , A. Mehta89 , T. Meideck57 , B. Meirose42 , D. Melini172 , B.R. Mellado Garcia32c , J.D. Mellenthin52 , M. Melo28a , JHEP05(2019)088 F. Meloni45 , A. Melzer24 , S.B. Menary99 , E.D. Mendes Gouveia138a,138e , L. Meng35 , X.T. Meng104 , S. Menke114 , E. Meoni40b,40a , S. Mergelmeyer19 , S.A.M. Merkt137 , C. Merlassino20 , P. Mermod53 , L. 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Naumann45 , G. Navarro22 , H.A. Neal104,∗ , P.Y. Nechaeva109 , F. Nechansky45 , T.J. Neep21 , A. Negri69a,69b , M. Negrini23b , S. Nektarijevic118 , C. Nellist52 , M.E. Nelson133 , S. Nemecek139 , P. Nemethy123 , M. Nessi35,f , M.S. Neubauer171 , M. Neumann180 , P.R. Newman21 , T.Y. Ng62c , Y.S. Ng19 , Y.W.Y. Ng169 , H.D.N. Nguyen100 , T. Nguyen Manh108 , E. Nibigira37 , R.B. Nickerson133 , R. Nicolaidou143 , D.S. Nielsen39 , J. Nielsen144 , N. Nikiforou11 , V. Nikolaenko122,an , I. Nikolic-Audit134 , K. Nikolopoulos21 , P. Nilsson29 , H.R. Nindhito53 , Y. Ninomiya80 , A. Nisati71a , N. Nishu59c , R. Nisius114 , I. Nitsche46 , T. Nitta177 , T. Nobe161 , Y. Noguchi84 , M. Nomachi131 , I. Nomidis134 , M.A. Nomura29 , M. Nordberg35 , N. Norjoharuddeen133 , T. Novak90 , O. Novgorodova47 , R. Novotny140 , L. Nozka128 , K. Ntekas169 , E. Nurse93 , F. Nuti103 , F.G. Oakham33,av , H. Oberlack114 , J. Ocariz134 , A. Ochi81 , I. Ochoa38 , J.P. Ochoa-Ricoux145a , K. O’Connor26 , S. Oda86 , S. 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Rifki45 , M. Rijssenbeek153 , A. Rimoldi69a,69b , M. Rimoldi20 , L. Rinaldi23b , G. Ripellino152 , B. Ristić88 , E. Ritsch35 , I. Riu14 , J.C. Rivera Vergara145a , F. Rizatdinova127 , E. Rizvi91 , C. Rizzi35 , R.T. Roberts99 , S.H. Robertson102,ac , M. Robin45 , D. Robinson31 , J.E.M. Robinson45 , A. Robson56 , E. Rocco98 , C. Roda70a,70b , Y. Rodina100 , S. Rodriguez Bosca172 , A. Rodriguez Perez14 , D. Rodriguez Rodriguez172 , A.M. Rodrı́guez Vera166b , S. Roe35 , O. Røhne132 , R. Röhrig114 , C.P.A. Roland64 , J. Roloff58 , A. Romaniouk111 , M. Romano23b,23a , N. Rompotis89 , M. Ronzani123 , L. Roos134 , S. Rosati71a , K. Rosbach51 , N-A. Rosien52 , G. Rosin101 , B.J. Rosser135 , E. Rossi45 , E. Rossi73a,73b , E. Rossi68a,68b , L.P. Rossi54b , L. Rossini67a,67b , J.H.N. Rosten31 , R. Rosten14 , M. Rotaru27b , J. Rothberg146 , D. Rousseau130 , D. Roy32c , A. Rozanov100 , Y. Rozen158 , X. Ruan32c , F. Rubbo151 , F. Rühr51 , A. Ruiz-Martinez172 , – 52 – A. Rummler35 , Z. 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Saraiva138a,138d , JHEP05(2019)088 O. Sasaki80 , K. Sato167 , E. Sauvan5 , P. Savard165,av , N. Savic114 , R. Sawada161 , C. Sawyer142 , L. Sawyer94,ak , C. Sbarra23b , A. Sbrizzi23a , T. Scanlon93 , J. Schaarschmidt146 , P. Schacht114 , B.M. Schachtner113 , D. Schaefer36 , L. Schaefer135 , J. Schaeffer98 , S. Schaepe35 , U. Schäfer98 , A.C. Schaffer130 , D. Schaile113 , R.D. Schamberger153 , N. Scharmberg99 , V.A. Schegelsky136 , D. Scheirich141 , F. Schenck19 , M. Schernau169 , C. Schiavi54b,54a , S. Schier144 , L.K. Schildgen24 , Z.M. Schillaci26 , E.J. Schioppa35 , M. Schioppa40b,40a , K.E. Schleicher51 , S. Schlenker35 , K.R. Schmidt-Sommerfeld114 , K. Schmieden35 , C. Schmitt98 , S. Schmitt45 , S. Schmitz98 , J.C. Schmoeckel45 , U. Schnoor51 , L. Schoeffel143 , A. Schoening60b , E. Schopf133 , M. Schott98 , J.F.P. Schouwenberg118 , J. Schovancova35 , S. Schramm53 , F. Schroeder180 , A. Schulte98 , H-C. Schultz-Coulon60a , M. Schumacher51 , B.A. Schumm144 , Ph. Schune143 , A. Schwartzman151 , T.A. Schwarz104 , Ph. Schwemling143 , R. Schwienhorst105 , A. Sciandra24 , G. Sciolla26 , M. Scornajenghi40b,40a , F. Scuri70a , F. Scutti103 , L.M. Scyboz114 , C.D. Sebastiani71a,71b , P. Seema19 , S.C. Seidel117 , A. Seiden144 , T. Seiss36 , J.M. Seixas79b , G. Sekhniaidze68a , K. Sekhon104 , S.J. Sekula41 , N. Semprini-Cesari23b,23a , S. Sen48 , S. Senkin37 , C. Serfon75 , L. Serin130 , L. Serkin65a,65b , M. Sessa59a , H. Severini126 , F. Sforza168 , A. Sfyrla53 , E. Shabalina52 , J.D. Shahinian144 , N.W. Shaikh44a,44b , D. Shaked Renous178 , L.Y. Shan15a , R. Shang171 , J.T. Shank25 , M. Shapiro18 , A.S. Sharma1 , A. Sharma133 , P.B. Shatalov110 , K. Shaw154 , S.M. Shaw99 , A. Shcherbakova136 , Y. Shen126 , N. Sherafati33 , A.D. Sherman25 , P. Sherwood93 , L. Shi156,ar , S. Shimizu80 , C.O. Shimmin181 , Y. Shimogama177 , M. Shimojima115 , I.P.J. Shipsey133 , S. Shirabe86 , M. Shiyakova78,aa , J. Shlomi178 , A. Shmeleva109 , M.J. Shochet36 , S. Shojaii103 , D.R. Shope126 , S. Shrestha124 , E. Shulga111 , P. Sicho139 , A.M. Sickles171 , P.E. Sidebo152 , E. Sideras Haddad32c , O. Sidiropoulou35 , A. Sidoti23b,23a , F. Siegert47 , Dj. Sijacki16 , M. Silva Jr.179 , M.V. Silva Oliveira79a , S.B. Silverstein44a , S. Simion130 , E. Simioni98 , M. Simon98 , R. Simoniello98 , P. Sinervo165 , N.B. Sinev129 , M. Sioli23b,23a , I. Siral104 , S.Yu. Sivoklokov112 , J. Sjölin44a,44b , E. Skorda95 , P. Skubic126 , M. Slawinska83 , K. Sliwa168 , R. Slovak141 , V. Smakhtin178 , B.H. Smart142 , J. Smiesko28a , N. Smirnov111 , S.Yu. Smirnov111 , Y. Smirnov111 , L.N. Smirnova112 , O. Smirnova95 , J.W. Smith52 , M. Smizanska88 , K. Smolek140 , A. Smykiewicz83 , A.A. Snesarev109 , I.M. Snyder129 , S. Snyder29 , R. Sobie174,ac , A.M. Soffa169 , A. Soffer159 , A. Søgaard49 , F. Sohns52 , G. Sokhrannyi90 , C.A. Solans Sanchez35 , E.Yu. Soldatov111 , U. Soldevila172 , A.A. Solodkov122 , A. Soloshenko78 , O.V. Solovyanov122 , V. Solovyev136 , P. Sommer147 , H. Son168 , W. Song142 , W.Y. Song166b , A. Sopczak140 , F. Sopkova28b , C.L. Sotiropoulou70a,70b , S. Sottocornola69a,69b , R. Soualah65a,65c,i , A.M. Soukharev121b,121a , D. South45 , S. Spagnolo66a,66b , M. Spalla114 , M. Spangenberg176 , F. Spanò92 , D. Sperlich19 , T.M. Spieker60a , R. Spighi23b , G. Spigo35 , L.A. Spiller103 , M. Spina154 , D.P. Spiteri56 , M. Spousta141 , A. Stabile67a,67b , B.L. Stamas120 , R. Stamen60a , M. Stamenkovic119 , S. Stamm19 , E. Stanecka83 , R.W. Stanek6 , B. Stanislaus133 , M.M. Stanitzki45 , M. Stankaityte133 , B. Stapf119 , E.A. Starchenko122 , G.H. Stark144 , J. Stark57 , – 53 – S.H Stark39 , P. Staroba139 , P. Starovoitov60a , S. Stärz102 , R. Staszewski83 , G. Stavropoulos43 , M. Stegler45 , P. Steinberg29 , B. Stelzer150 , H.J. Stelzer35 , O. Stelzer-Chilton166a , H. Stenzel55 , T.J. Stevenson154 , G.A. Stewart35 , M.C. Stockton35 , G. Stoicea27b , M. Stolarski138a , P. Stolte52 , S. Stonjek114 , A. Straessner47 , J. Strandberg152 , S. Strandberg44a,44b , M. Strauss126 , P. Strizenec28b , R. Ströhmer175 , D.M. Strom129 , R. Stroynowski41 , A. Strubig49 , S.A. Stucci29 , B. Stugu17 , J. Stupak126 , N.A. Styles45 , D. Su151 , S. Suchek60a , Y. Sugaya131 , V.V. Sulin109 , M.J. Sullivan89 , D.M.S. Sultan53 , S. Sultansoy4c , T. Sumida84 , S. Sun104 , X. Sun3 , K. Suruliz154 , C.J.E. Suster155 , M.R. Sutton154 , S. Suzuki80 , M. Svatos139 , M. Swiatlowski36 , S.P. Swift2 , A. Sydorenko98 , I. Sykora28a , M. Sykora141 , T. Sykora141 , D. Ta98 , K. Tackmann45,y , J. Taenzer159 , A. Taffard169 , R. Tafirout166a , E. Tahirovic91 , H. Takai29 , R. Takashima85 , K. Takeda81 , T. Takeshita148 , E.P. Takeva49 , Y. Takubo80 , M. Talby100 , A.A. Talyshev121b,121a , JHEP05(2019)088 N.M. Tamir159 , J. Tanaka161 , M. Tanaka163 , R. Tanaka130 , B.B. Tannenwald124 , S. Tapia Araya171 , S. Tapprogge98 , A. Tarek Abouelfadl Mohamed134 , S. Tarem158 , G. Tarna27b,e , G.F. Tartarelli67a , P. Tas141 , M. Tasevsky139 , T. Tashiro84 , E. Tassi40b,40a , A. Tavares Delgado138a,138b , Y. Tayalati34e , A.J. Taylor49 , G.N. Taylor103 , P.T.E. Taylor103 , W. Taylor166b , A.S. Tee88 , R. Teixeira De Lima151 , P. Teixeira-Dias92 , H. Ten Kate35 , J.J. Teoh119 , S. Terada80 , K. Terashi161 , J. Terron97 , S. Terzo14 , M. Testa50 , R.J. Teuscher165,ac , S.J. Thais181 , T. Theveneaux-Pelzer45 , F. Thiele39 , D.W. Thomas92 , J.O. Thomas41 , J.P. Thomas21 , A.S. Thompson56 , P.D. Thompson21 , L.A. Thomsen181 , E. Thomson135 , Y. Tian38 , R.E. Ticse Torres52 , V.O. Tikhomirov109,ao , Yu.A. Tikhonov121b,121a , S. Timoshenko111 , P. Tipton181 , S. Tisserant100 , K. Todome23b,23a , S. Todorova-Nova5 , S. Todt47 , J. Tojo86 , S. Tokár28a , K. Tokushuku80 , E. Tolley124 , K.G. Tomiwa32c , M. Tomoto116 , L. Tompkins151,q , K. Toms117 , B. Tong58 , P. Tornambe101 , E. Torrence129 , H. Torres47 , E. Torró Pastor146 , C. Tosciri133 , J. Toth100,ab , D.R. Tovey147 , C.J. Treado123 , T. Trefzger175 , F. Tresoldi154 , A. Tricoli29 , I.M. Trigger166a , S. Trincaz-Duvoid134 , W. Trischuk165 , B. Trocmé57 , A. Trofymov130 , C. Troncon67a , M. Trovatelli174 , F. Trovato154 , L. Truong32b , M. Trzebinski83 , A. Trzupek83 , F. Tsai45 , J.C-L. Tseng133 , P.V. Tsiareshka106,ai , A. Tsirigotis160 , N. Tsirintanis9 , V. Tsiskaridze153 , E.G. Tskhadadze157a , M. Tsopoulou160 , I.I. Tsukerman110 , V. Tsulaia18 , S. Tsuno80 , D. Tsybychev153,164 , Y. Tu62b , A. Tudorache27b , V. Tudorache27b , T.T. Tulbure27a , A.N. Tuna58 , S. Turchikhin78 , D. Turgeman178 , I. Turk Cakir4b,t , R.J. Turner21 , R.T. Turra67a , P.M. Tuts38 , S Tzamarias160 , E. Tzovara98 , G. Ucchielli46 , I. Ueda80 , M. Ughetto44a,44b , F. Ukegawa167 , G. Unal35 , A. Undrus29 , G. Unel169 , F.C. Ungaro103 , Y. Unno80 , K. Uno161 , J. Urban28b , P. Urquijo103 , G. Usai8 , J. Usui80 , L. Vacavant100 , V. Vacek140 , B. Vachon102 , K.O.H. Vadla132 , A. Vaidya93 , C. Valderanis113 , E. Valdes Santurio44a,44b , M. Valente53 , S. Valentinetti23b,23a , A. Valero172 , L. Valéry45 , R.A. Vallance21 , A. Vallier35 , J.A. Valls Ferrer172 , T.R. Van Daalen14 , P. Van Gemmeren6 , I. Van Vulpen119 , M. Vanadia72a,72b , W. Vandelli35 , A. Vaniachine164 , R. Vari71a , E.W. Varnes7 , C. Varni54b,54a , T. Varol41 , D. Varouchas130 , K.E. Varvell155 , M.E. Vasile27b , G.A. Vasquez174 , J.G. Vasquez181 , F. Vazeille37 , D. Vazquez Furelos14 , T. Vazquez Schroeder35 , J. Veatch52 , V. Vecchio73a,73b , L.M. Veloce165 , F. Veloso138a,138c , S. Veneziano71a , A. Ventura66a,66b , N. Venturi35 , A. Verbytskyi114 , V. Vercesi69a , M. Verducci73a,73b , C.M. Vergel Infante77 , C. Vergis24 , W. Verkerke119 , A.T. Vermeulen119 , J.C. Vermeulen119 , M.C. Vetterli150,av , N. Viaux Maira145b , M. Vicente Barreto Pinto53 , I. Vichou171,∗ , T. Vickey147 , O.E. Vickey Boeriu147 , G.H.A. Viehhauser133 , L. Vigani133 , M. Villa23b,23a , M. Villaplana Perez67a,67b , E. Vilucchi50 , M.G. Vincter33 , V.B. Vinogradov78 , A. Vishwakarma45 , C. Vittori23b,23a , I. Vivarelli154 , M. Vogel180 , P. Vokac140 , G. Volpi14 , S.E. von Buddenbrock32c , E. Von Toerne24 , V. Vorobel141 , K. Vorobev111 , M. Vos172 , J.H. Vossebeld89 , N. Vranjes16 , M. Vranjes Milosavljevic16 , V. Vrba140 , M. Vreeswijk119 , T. Šfiligoj90 , R. Vuillermet35 , I. Vukotic36 , T. Ženiš28a , L. Živković16 , – 54 – P. Wagner24 , W. Wagner180 , J. Wagner-Kuhr113 , H. Wahlberg87 , S. Wahrmund47 , K. Wakamiya81 , V.M. Walbrecht114 , J. Walder88 , R. Walker113 , S.D. Walker92 , W. Walkowiak149 , V. Wallangen44a,44b , A.M. Wang58 , C. Wang59b , F. Wang179 , H. Wang18 , H. Wang3 , J. Wang155 , J. Wang60b , P. Wang41 , Q. Wang126 , R.-J. Wang134 , R. Wang59a , R. Wang6 , S.M. Wang156 , W.T. Wang59a , W. Wang15c,ad , W.X. Wang59a,ad , Y. Wang59a,al , Z. Wang59c , C. Wanotayaroj45 , A. Warburton102 , C.P. Ward31 , D.R. Wardrope93 , A. Washbrook49 , A.T. Watson21 , M.F. Watson21 , G. Watts146 , B.M. Waugh93 , A.F. Webb11 , S. Webb98 , C. Weber181 , M.S. Weber20 , S.A. Weber33 , S.M. Weber60a , A.R. Weidberg133 , J. Weingarten46 , M. Weirich98 , C. Weiser51 , P.S. Wells35 , T. Wenaus29 , T. Wengler35 , S. Wenig35 , N. Wermes24 , M.D. Werner77 , P. Werner35 , M. Wessels60a , T.D. Weston20 , K. Whalen129 , N.L. Whallon146 , A.M. Wharton88 , A.S. White104 , A. White8 , M.J. White1 , R. White145b , D. Whiteson169 , B.W. Whitmore88 , JHEP05(2019)088 F.J. Wickens142 , W. Wiedenmann179 , M. Wielers142 , C. Wiglesworth39 , L.A.M. Wiik-Fuchs51 , F. Wilk99 , H.G. Wilkens35 , L.J. Wilkins92 , H.H. Williams135 , S. Williams31 , C. Willis105 , S. Willocq101 , J.A. Wilson21 , I. Wingerter-Seez5 , E. Winkels154 , F. Winklmeier129 , O.J. Winston154 , B.T. Winter51 , M. Wittgen151 , M. Wobisch94 , A. Wolf98 , T.M.H. Wolf119 , R. Wolff100 , R.W. Wölker133 , J. Wollrath51 , M.W. Wolter83 , H. Wolters138a,138c , V.W.S. Wong173 , N.L. Woods144 , S.D. Worm21 , B.K. Wosiek83 , K.W. Woźniak83 , K. Wraight56 , S.L. Wu179 , X. Wu53 , Y. Wu59a , T.R. Wyatt99 , B.M. Wynne49 , S. Xella39 , Z. Xi104 , L. 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Zwalinski35 1 Department of Physics, University of Adelaide, Adelaide; Australia 2 Physics Department, SUNY Albany, Albany NY; United States of America 3 Department of Physics, University of Alberta, Edmonton AB; Canada 4 Department of Physics(a) , Ankara University, Ankara; Istanbul Aydin University(b) , Istanbul; Division of Physics(c) , TOBB University of Economics and Technology, Ankara; Turkey 5 LAPP, Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS/IN2P3, Annecy; France 6 High Energy Physics Division, Argonne National Laboratory, Argonne IL; United States of America 7 Department of Physics, University of Arizona, Tucson AZ; United States of America 8 Department of Physics, University of Texas at Arlington, Arlington TX; United States of America 9 Physics Department, National and Kapodistrian University of Athens, Athens; Greece 10 Physics Department, National Technical University of Athens, Zografou; Greece 11 Department of Physics, University of Texas at Austin, Austin TX; United States of America – 55 – 12 Bahcesehir University(a) , Faculty of Engineering and Natural Sciences, Istanbul; Istanbul Bilgi University(b) , Faculty of Engineering and Natural Sciences, Istanbul; Department of Physics (c) , Bogazici University, Istanbul; Department of Physics Engineering(d) , Gaziantep University, Gaziantep; Turkey 13 Institute of Physics, Azerbaijan Academy of Sciences, Baku; Azerbaijan 14 Institut de Fı́sica d’Altes Energies (IFAE), Barcelona Institute of Science and Technology, Barcelona; Spain 15 Institute of High Energy Physics(a) , Chinese Academy of Sciences, Beijing; Physics Department(b) , Tsinghua University, Beijing; Department of Physics(c) , Nanjing University, Nanjing; University of Chinese Academy of Science (UCAS)(d) , Beijing; China 16 Institute of Physics, University of Belgrade, Belgrade; Serbia 17 Department for Physics and Technology, University of Bergen, Bergen; Norway JHEP05(2019)088 18 Physics Division, Lawrence Berkeley National Laboratory and University of California, Berkeley CA; United States of America 19 Institut für Physik, Humboldt Universität zu Berlin, Berlin; Germany 20 Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics, University of Bern, Bern; Switzerland 21 School of Physics and Astronomy, University of Birmingham, Birmingham; United Kingdom 22 Facultad de Ciencias y Centro de Investigaciónes, Universidad Antonio Nariño, Bogota; Colombia 23 INFN Bologna and Università di Bologna(a) , Dipartimento di Fisica; INFN Sezione di Bologna(b) ; Italy 24 Physikalisches Institut, Universität Bonn, Bonn; Germany 25 Department of Physics, Boston University, Boston MA; United States of America 26 Department of Physics, Brandeis University, Waltham MA; United States of America 27 Transilvania University of Brasov(a) , Brasov; Horia Hulubei National Institute of Physics and Nuclear Engineering(b) , Bucharest; Department of Physics(c) , Alexandru Ioan Cuza University of Iasi, Iasi; National Institute for Research and Development of Isotopic and Molecular Technologies(d) , Physics Department, Cluj-Napoca; University Politehnica Bucharest (e) , Bucharest; West University in Timisoara(f ) , Timisoara; Romania 28 Faculty of Mathematics(a) , Physics and Informatics, Comenius University, Bratislava; Department of Subnuclear Physics(b) , Institute of Experimental Physics of the Slovak Academy of Sciences, Kosice; Slovak Republic 29 Physics Department, Brookhaven National Laboratory, Upton NY; United States of America 30 Departamento de Fı́sica, Universidad de Buenos Aires, Buenos Aires; Argentina 31 Cavendish Laboratory, University of Cambridge, Cambridge; United Kingdom 32 Department of Physics(a) , University of Cape Town, Cape Town; Department of Mechanical Engineering Science(b) , University of Johannesburg, Johannesburg; School of Physics(c) , University of the Witwatersrand, Johannesburg; South Africa 33 Department of Physics, Carleton University, Ottawa ON; Canada 34 Faculté des Sciences Ain Chock(a) , Réseau Universitaire de Physique des Hautes Energies — Université Hassan II, Casablanca; Centre National de l’Energie des Sciences Techniques Nucleaires (CNESTEN)(b) , Rabat; Faculté des Sciences Semlalia(c) , Université Cadi Ayyad, LPHEA-Marrakech; Faculté des Sciences(d) , Université Mohamed Premier and LPTPM, Oujda; Faculté des sciences(e) , Université Mohammed V, Rabat; Morocco 35 CERN, Geneva; Switzerland 36 Enrico Fermi Institute, University of Chicago, Chicago IL; United States of America 37 LPC, Université Clermont Auvergne, CNRS/IN2P3, Clermont-Ferrand; France 38 Nevis Laboratory, Columbia University, Irvington NY; United States of America 39 Niels Bohr Institute, University of Copenhagen, Copenhagen; Denmark 40 Dipartimento di Fisica(a) , Università della Calabria, Rende; INFN Gruppo Collegato di Cosenza (b) , Laboratori Nazionali di Frascati; Italy 41 Physics Department, Southern Methodist University, Dallas TX; United States of America 42 Physics Department, University of Texas at Dallas, Richardson TX; United States of America – 56 – 43 National Centre for Scientific Research “Demokritos”, Agia Paraskevi; Greece 44 Department of Physics(a) , Stockholm University; Oskar Klein Centre(b) , Stockholm; Sweden 45 Deutsches Elektronen-Synchrotron DESY, Hamburg and Zeuthen; Germany 46 Lehrstuhl für Experimentelle Physik IV, Technische Universität Dortmund, Dortmund; Germany 47 Institut für Kern- und Teilchenphysik, Technische Universität Dresden, Dresden; Germany 48 Department of Physics, Duke University, Durham NC; United States of America 49 SUPA — School of Physics and Astronomy, University of Edinburgh, Edinburgh; United Kingdom 50 INFN e Laboratori Nazionali di Frascati, Frascati; Italy 51 Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg; Germany 52 II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen; Germany 53 Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève; Switzerland 54 Dipartimento di Fisica(a) , Università di Genova, Genova; INFN Sezione di Genova(b) ; Italy JHEP05(2019)088 55 II. Physikalisches Institut, Justus-Liebig-Universität Giessen, Giessen; Germany 56 SUPA — School of Physics and Astronomy, University of Glasgow, Glasgow; United Kingdom 57 LPSC, Université Grenoble Alpes, CNRS/IN2P3, Grenoble INP, Grenoble; France 58 Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge MA; United States of America 59 Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics (a) , University of Science and Technology of China, Hefei; Institute of Frontier and Interdisciplinary Science and Key Laboratory of Particle Physics and Particle Irradiation (MOE) (b) , Shandong University, Qingdao; School of Physics and Astronomy(c) , Shanghai Jiao Tong University, KLPPAC-MoE, SKLPPC, Shanghai; Tsung-Dao Lee Institute(d) , Shanghai; China 60 Kirchhoff-Institut für Physik(a) , Ruprecht-Karls-Universität Heidelberg, Heidelberg; Physikalisches Institut(b) , Ruprecht-Karls-Universität Heidelberg, Heidelberg; Germany 61 Faculty of Applied Information Science, Hiroshima Institute of Technology, Hiroshima; Japan 62 Department of Physics(a) , Chinese University of Hong Kong, Shatin, N.T., Hong Kong; Department of Physics(b) , University of Hong Kong, Hong Kong; Department of Physics and Institute for Advanced Study(c) , Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong; China 63 Department of Physics, National Tsing Hua University, Hsinchu; Taiwan 64 Department of Physics, Indiana University, Bloomington IN; United States of America 65 INFN Gruppo Collegato di Udine(a) , Sezione di Trieste, Udine; ICTP(b) , Trieste; Dipartimento Politecnico di Ingegneria e Architettura(c) , Università di Udine, Udine; Italy 66 INFN Sezione di Lecce(a) ; Dipartimento di Matematica e Fisica(b) , Università del Salento, Lecce; Italy 67 INFN Sezione di Milano(a) ; Dipartimento di Fisica(b) , Università di Milano, Milano; Italy 68 INFN Sezione di Napoli(a) ; Dipartimento di Fisica(b) , Università di Napoli, Napoli; Italy 69 INFN Sezione di Pavia(a) ; Dipartimento di Fisica(b) , Università di Pavia, Pavia; Italy 70 INFN Sezione di Pisa(a) ; Dipartimento di Fisica E. Fermi(b) , Università di Pisa, Pisa; Italy 71 INFN Sezione di Roma(a) ; Dipartimento di Fisica(b) , Sapienza Università di Roma, Roma; Italy 72 INFN Sezione di Roma Tor Vergata(a) ; Dipartimento di Fisica(b) , Università di Roma Tor Vergata, Roma; Italy 73 INFN Sezione di Roma Tre(a) ; Dipartimento di Matematica e Fisica(b) , Università Roma Tre, Roma; Italy 74 INFN-TIFPA(a) ; Università degli Studi di Trento(b) , Trento; Italy 75 Institut für Astro- und Teilchenphysik, Leopold-Franzens-Universität, Innsbruck; Austria 76 University of Iowa, Iowa City IA; United States of America 77 Department of Physics and Astronomy, Iowa State University, Ames IA; United States of America 78 Joint Institute for Nuclear Research, Dubna; Russia 79 Departamento de Engenharia Elétrica(a) , Universidade Federal de Juiz de Fora (UFJF), Juiz de Fora; Universidade Federal do Rio De Janeiro COPPE/EE/IF(b) , Rio de Janeiro; Universidade Federal de São João del Rei (UFSJ)(c) , São João del Rei; Instituto de Fı́sica(d) , Universidade de São Paulo, São Paulo; Brazil – 57 – 80 KEK, High Energy Accelerator Research Organization, Tsukuba; Japan 81 Graduate School of Science, Kobe University, Kobe; Japan 82 AGH University of Science and Technology(a) , Faculty of Physics and Applied Computer Science, Krakow; Marian Smoluchowski Institute of Physics(b) , Jagiellonian University, Krakow; Poland 83 Institute of Nuclear Physics Polish Academy of Sciences, Krakow; Poland 84 Faculty of Science, Kyoto University, Kyoto; Japan 85 Kyoto University of Education, Kyoto; Japan 86 Research Center for Advanced Particle Physics and Department of Physics, Kyushu University, Fukuoka; Japan 87 Instituto de Fı́sica La Plata, Universidad Nacional de La Plata and CONICET, La Plata; Argentina 88 Physics Department, Lancaster University, Lancaster; United Kingdom 89 Oliver Lodge Laboratory, University of Liverpool, Liverpool; United Kingdom JHEP05(2019)088 90 Department of Experimental Particle Physics, Jožef Stefan Institute and Department of Physics, University of Ljubljana, Ljubljana; Slovenia 91 School of Physics and Astronomy, Queen Mary University of London, London; United Kingdom 92 Department of Physics, Royal Holloway University of London, Egham; United Kingdom 93 Department of Physics and Astronomy, University College London, London; United Kingdom 94 Louisiana Tech University, Ruston LA; United States of America 95 Fysiska institutionen, Lunds universitet, Lund; Sweden 96 Centre de Calcul de l’Institut National de Physique Nucléaire et de Physique des Particules (IN2P3), Villeurbanne; France 97 Departamento de Fı́sica Teorica C-15 and CIAFF, Universidad Autónoma de Madrid, Madrid; Spain 98 Institut für Physik, Universität Mainz, Mainz; Germany 99 School of Physics and Astronomy, University of Manchester, Manchester; United Kingdom 100 CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille; France 101 Department of Physics, University of Massachusetts, Amherst MA; United States of America 102 Department of Physics, McGill University, Montreal QC; Canada 103 School of Physics, University of Melbourne, Victoria; Australia 104 Department of Physics, University of Michigan, Ann Arbor MI; United States of America 105 Department of Physics and Astronomy, Michigan State University, East Lansing MI; United States of America 106 B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk; Belarus 107 Research Institute for Nuclear Problems of Byelorussian State University, Minsk; Belarus 108 Group of Particle Physics, University of Montreal, Montreal QC; Canada 109 P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow; Russia 110 Institute for Theoretical and Experimental Physics of the National Research Centre Kurchatov Institute, Moscow; Russia 111 National Research Nuclear University MEPhI, Moscow; Russia 112 D.V. Skobeltsyn Institute of Nuclear Physics, M.V. Lomonosov Moscow State University, Moscow; Russia 113 Fakultät für Physik, Ludwig-Maximilians-Universität München, München; Germany 114 Max-Planck-Institut für Physik (Werner-Heisenberg-Institut), München; Germany 115 Nagasaki Institute of Applied Science, Nagasaki; Japan 116 Graduate School of Science and Kobayashi-Maskawa Institute, Nagoya University, Nagoya; Japan 117 Department of Physics and Astronomy, University of New Mexico, Albuquerque NM; United States of America 118 Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen; Netherlands 119 Nikhef National Institute for Subatomic Physics and University of Amsterdam, Amsterdam; Netherlands 120 Department of Physics, Northern Illinois University, DeKalb IL; United States of America – 58 – 121 Budker Institute of Nuclear Physics and NSU(a) , SB RAS, Novosibirsk; Novosibirsk State University Novosibirsk(b) ; Russia 122 Institute for High Energy Physics of the National Research Centre Kurchatov Institute, Protvino; Russia 123 Department of Physics, New York University, New York NY; United States of America 124 Ohio State University, Columbus OH; United States of America 125 Faculty of Science, Okayama University, Okayama; Japan 126 Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman OK; United States of America 127 Department of Physics, Oklahoma State University, Stillwater OK; United States of America 128 Palacký University, RCPTM, Joint Laboratory of Optics, Olomouc; Czech Republic 129 Center for High Energy Physics, University of Oregon, Eugene OR; United States of America JHEP05(2019)088 130 LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay; France 131 Graduate School of Science, Osaka University, Osaka; Japan 132 Department of Physics, University of Oslo, Oslo; Norway 133 Department of Physics, Oxford University, Oxford; United Kingdom 134 LPNHE, Sorbonne Université, Paris Diderot Sorbonne Paris Cité, CNRS/IN2P3, Paris; France 135 Department of Physics, University of Pennsylvania, Philadelphia PA; United States of America 136 Konstantinov Nuclear Physics Institute of National Research Centre “Kurchatov Institute”, PNPI, St. Petersburg; Russia 137 Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh PA; United States of America 138 Laboratório de Instrumentação e Fı́sica Experimental de Partı́culas — LIP (a) ; Departamento de Fı́sica(b) , Faculdade de Ciências, Universidade de Lisboa, Lisboa; Departamento de Fı́sica (c) , Universidade de Coimbra, Coimbra; Centro de Fı́sica Nuclear da Universidade de Lisboa (d) , Lisboa; Departamento de Fı́sica(e) , Universidade do Minho, Braga; Universidad de Granada(f ) , Granada (Spain); Dep Fı́sica and CEFITEC of Faculdade de Ciências e Tecnologia (g) , Universidade Nova de Lisboa, Caparica; Portugal 139 Institute of Physics of the Czech Academy of Sciences, Prague; Czech Republic 140 Czech Technical University in Prague, Prague; Czech Republic 141 Charles University, Faculty of Mathematics and Physics, Prague; Czech Republic 142 Particle Physics Department, Rutherford Appleton Laboratory, Didcot; United Kingdom 143 IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette; France 144 Santa Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz CA; United States of America 145 Departamento de Fı́sica(a) , Pontificia Universidad Católica de Chile, Santiago; Departamento de Fı́sica(b) , Universidad Técnica Federico Santa Marı́a, Valparaı́so; Chile 146 Department of Physics, University of Washington, Seattle WA; United States of America 147 Department of Physics and Astronomy, University of Sheffield, Sheffield; United Kingdom 148 Department of Physics, Shinshu University, Nagano; Japan 149 Department Physik, Universität Siegen, Siegen; Germany 150 Department of Physics, Simon Fraser University, Burnaby BC; Canada 151 SLAC National Accelerator Laboratory, Stanford CA; United States of America 152 Physics Department, Royal Institute of Technology, Stockholm; Sweden 153 Departments of Physics and Astronomy, Stony Brook University, Stony Brook NY; United States of America 154 Department of Physics and Astronomy, University of Sussex, Brighton; United Kingdom 155 School of Physics, University of Sydney, Sydney; Australia 156 Institute of Physics, Academia Sinica, Taipei; Taiwan 157 E. Andronikashvili Institute of Physics(a) , Iv. Javakhishvili Tbilisi State University, Tbilisi; High Energy Physics Institute(b) , Tbilisi State University, Tbilisi; Georgia 158 Department of Physics, Technion, Israel Institute of Technology, Haifa; Israel – 59 – 159 Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv University, Tel Aviv; Israel 160 Department of Physics, Aristotle University of Thessaloniki, Thessaloniki; Greece 161 International Center for Elementary Particle Physics and Department of Physics, University of Tokyo, Tokyo; Japan 162 Graduate School of Science and Technology, Tokyo Metropolitan University, Tokyo; Japan 163 Department of Physics, Tokyo Institute of Technology, Tokyo; Japan 164 Tomsk State University, Tomsk; Russia 165 Department of Physics, University of Toronto, Toronto ON; Canada 166 TRIUMF(a) , Vancouver BC; Department of Physics and Astronomy(b) , York University, Toronto ON; Canada 167 Division of Physics and Tomonaga Center for the History of the Universe, Faculty of Pure and JHEP05(2019)088 Applied Sciences, University of Tsukuba, Tsukuba; Japan 168 Department of Physics and Astronomy, Tufts University, Medford MA; United States of America 169 Department of Physics and Astronomy, University of California Irvine, Irvine CA; United States of America 170 Department of Physics and Astronomy, University of Uppsala, Uppsala; Sweden 171 Department of Physics, University of Illinois, Urbana IL; United States of America 172 Instituto de Fı́sica Corpuscular (IFIC), Centro Mixto Universidad de Valencia — CSIC, Valencia; Spain 173 Department of Physics, University of British Columbia, Vancouver BC; Canada 174 Department of Physics and Astronomy, University of Victoria, Victoria BC; Canada 175 Fakultät für Physik und Astronomie, Julius-Maximilians-Universität Würzburg, Würzburg; Germany 176 Department of Physics, University of Warwick, Coventry; United Kingdom 177 Waseda University, Tokyo; Japan 178 Department of Particle Physics, Weizmann Institute of Science, Rehovot; Israel 179 Department of Physics, University of Wisconsin, Madison WI; United States of America 180 Fakultät für Mathematik und Naturwissenschaften, Fachgruppe Physik, Bergische Universität Wuppertal, Wuppertal; Germany 181 Department of Physics, Yale University, New Haven CT; United States of America 182 Yerevan Physics Institute, Yerevan; Armenia a Also at Borough of Manhattan Community College, City University of New York, NY; United States of America b Also at California State University, East Bay; United States of America c Also at Centre for High Performance Computing, CSIR Campus, Rosebank, Cape Town; South Africa d Also at CERN, Geneva; Switzerland e Also at CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille; France f Also at Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève; Switzerland g Also at Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona; Spain h Also at Departamento de Fı́sica, Instituto Superior Técnico, Universidade de Lisboa, Lisboa; Portugal i Also at Department of Applied Physics and Astronomy, University of Sharjah, Sharjah; United Arab Emirates j Also at Department of Financial and Management Engineering, University of the Aegean, Chios; Greece k Also at Department of Physics and Astronomy, University of Louisville, Louisville, KY; United States of America l Also at Department of Physics and Astronomy, University of Sheffield, Sheffield; United Kingdom – 60 – m Also at Department of Physics, California State University, Fresno CA; United States of America n Also at Department of Physics, California State University, Sacramento CA; United States of America o Also at Department of Physics, King’s College London, London; United Kingdom p Also at Department of Physics, St. Petersburg State Polytechnical University, St. Petersburg; Russia q Also at Department of Physics, Stanford University, Stanford CA; United States of America r Also at Department of Physics, University of Fribourg, Fribourg; Switzerland s Also at Department of Physics, University of Michigan, Ann Arbor MI; United States of America t Also at Giresun University, Faculty of Engineering, Giresun; Turkey u Also at Graduate School of Science, Osaka University, Osaka; Japan v Also at Hellenic Open University, Patras; Greece JHEP05(2019)088 w Also at Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest; Romania x Also at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona; Spain y Also at Institut für Experimentalphysik, Universität Hamburg, Hamburg; Germany z Also at Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen; Netherlands aa Also at Institute for Nuclear Research and Nuclear Energy (INRNE) of the Bulgarian Academy of Sciences, Sofia; Bulgaria ab Also at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest; Hungary ac Also at Institute of Particle Physics (IPP); Canada ad Also at Institute of Physics, Academia Sinica, Taipei; Taiwan ae Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku; Azerbaijan af Also at Institute of Theoretical Physics, Ilia State University, Tbilisi; Georgia ag Also at Instituto de Fı́sica Teórica de la Universidad Autónoma de Madrid; Spain ah Also at Istanbul University, Dept. of Physics, Istanbul; Turkey ai Also at Joint Institute for Nuclear Research, Dubna; Russia aj Also at LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay; France ak Also at Louisiana Tech University, Ruston LA; United States of America al Also at LPNHE, Sorbonne Université, Paris Diderot Sorbonne Paris Cité, CNRS/IN2P3, Paris; France am Also at Manhattan College, New York NY; United States of America an Also at Moscow Institute of Physics and Technology State University, Dolgoprudny; Russia ao Also at National Research Nuclear University MEPhI, Moscow; Russia ap Also at Physics Dept, University of South Africa, Pretoria; South Africa aq Also at Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg; Germany ar Also at School of Physics, Sun Yat-sen University, Guangzhou; China as Also at The City College of New York, New York NY; United States of America at Also at The Collaborative Innovation Center of Quantum Matter (CICQM), Beijing; China au Also at Tomsk State University, Tomsk, and Moscow Institute of Physics and Technology State University, Dolgoprudny; Russia av Also at TRIUMF, Vancouver BC; Canada aw Also at Università di Napoli Parthenope, Napoli; Italy ∗ Deceased – 61 – The CMS collaboration Yerevan Physics Institute, Yerevan, Armenia A.M. Sirunyan, A. Tumasyan Institut für Hochenergiephysik, Wien, Austria W. Adam, F. Ambrogi, E. Asilar, T. Bergauer, J. Brandstetter, M. Dragicevic, J. Erö, A. Escalante Del Valle, M. Flechl, R. Frühwirth1 , V.M. Ghete, J. Hrubec, M. Jeitler1 , N. Krammer, I. Krätschmer, D. Liko, T. Madlener, I. Mikulec, N. Rad, H. Rohringer, J. Schieck1 , R. Schöfbeck, M. Spanring, D. Spitzbart, W. Waltenberger, J. Wittmann, JHEP05(2019)088 C.-E. Wulz1 , M. Zarucki Institute for Nuclear Problems, Minsk, Belarus V. Chekhovsky, V. Mossolov, J. Suarez Gonzalez Universiteit Antwerpen, Antwerpen, Belgium E.A. De Wolf, D. Di Croce, X. Janssen, J. Lauwers, A. Lelek, M. Pieters, H. Van Haever- maet, P. Van Mechelen, N. Van Remortel Vrije Universiteit Brussel, Brussel, Belgium F. Blekman, J. D’Hondt, J. De Clercq, K. Deroover, G. Flouris, D. Lontkovskyi, S. Lowette, I. Marchesini, S. Moortgat, L. Moreels, Q. Python, K. Skovpen, S. Tavernier, W. Van Don- inck, P. Van Mulders, I. Van Parijs Université Libre de Bruxelles, Bruxelles, Belgium D. Beghin, B. Bilin, H. Brun, B. Clerbaux, G. De Lentdecker, H. Delannoy, B. Dorney, G. Fasanella, L. Favart, A. Grebenyuk, A.K. Kalsi, J. Luetic, A. Popov 2 , N. Postiau, E. Starling, L. Thomas, C. Vander Velde, P. Vanlaer, D. Vannerom, Q. Wang Ghent University, Ghent, Belgium T. Cornelis, D. Dobur, A. Fagot, M. Gul, I. Khvastunov3 , C. Roskas, D. Trocino, M. Tytgat, W. Verbeke, B. Vermassen, M. Vit, N. Zaganidis Université Catholique de Louvain, Louvain-la-Neuve, Belgium H. Bakhshiansohi, O. Bondu, G. Bruno, C. Caputo, P. David, C. Delaere, M. Delcourt, A. Giammanco, G. Krintiras, V. Lemaitre, A. Magitteri, K. Piotrzkowski, A. Saggio, M. Vidal Marono, P. Vischia, J. Zobec Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil F.L. Alves, G.A. Alves, G. Correia Silva, C. Hensel, A. Moraes, M.E. Pol, P. Rebello Teles Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil E. Belchior Batista Das Chagas, W. Carvalho, J. Chinellato4 , E. Coelho, E.M. Da Costa, G.G. Da Silveira5 , D. De Jesus Damiao, C. De Oliveira Martins, S. Fonseca De Souza, L.M. Huertas Guativa, H. Malbouisson, D. Matos Figueiredo, M. Melo De Almeida, C. Mora Herrera, L. Mundim, H. Nogima, W.L. Prado Da Silva, L.J. Sanchez Rosas, A. Santoro, A. Sznajder, M. Thiel, E.J. Tonelli Manganote4 , F. Torres Da Silva De Araujo, A. Vilela Pereira – 62 – Universidade Estadual Paulistaa , Universidade Federal do ABCb , São Paulo, Brazil S. Ahujaa , C.A. Bernardesa , L. Calligarisa , T.R. Fernandez Perez Tomeia , E.M. Gregoresb , P.G. Mercadanteb , S.F. Novaesa , SandraS. Padulaa Institute for Nuclear Research and Nuclear Energy, Bulgarian Academy of Sciences, Sofia, Bulgaria A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, A. Marinov, M. Misheva, M. Rodozov, M. Shopova, G. Sultanov University of Sofia, Sofia, Bulgaria JHEP05(2019)088 A. Dimitrov, L. Litov, B. Pavlov, P. Petkov Beihang University, Beijing, China W. Fang6 , X. Gao6 , L. Yuan Institute of High Energy Physics, Beijing, China M. Ahmad, J.G. Bian, G.M. Chen, H.S. Chen, M. Chen, Y. Chen, C.H. Jiang, D. Leggat, H. Liao, Z. Liu, S.M. Shaheen7 , A. Spiezia, J. Tao, E. Yazgan, H. Zhang, S. Zhang7 , J. Zhao State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, China Y. Ban, G. Chen, A. Levin, J. Li, L. Li, Q. Li, Y. Mao, S.J. Qian, D. Wang Tsinghua University, Beijing, China Y. Wang Universidad de Los Andes, Bogota, Colombia C. Avila, A. Cabrera, C.A. Carrillo Montoya, L.F. Chaparro Sierra, C. Florez, C.F. González Hernández, M.A. Segura Delgado University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Split, Croatia N. Godinovic, D. Lelas, I. Puljak, T. Sculac University of Split, Faculty of Science, Split, Croatia Z. Antunovic, M. Kovac Institute Rudjer Boskovic, Zagreb, Croatia V. Brigljevic, D. Ferencek, K. Kadija, B. Mesic, M. Roguljic, A. Starodumov 8 , T. Susa University of Cyprus, Nicosia, Cyprus M.W. Ather, A. Attikis, M. Kolosova, G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos, P.A. Razis, H. Rykaczewski Charles University, Prague, Czech Republic M. Finger9 , M. Finger Jr.9 Escuela Politecnica Nacional, Quito, Ecuador E. Ayala – 63 – Universidad San Francisco de Quito, Quito, Ecuador E. Carrera Jarrin Academy of Scientific Research and Technology of the Arab Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt H. Abdalla10 , Y. Assran11,12 , A. Mohamed13 National Institute of Chemical Physics and Biophysics, Tallinn, Estonia S. Bhowmik, A. Carvalho Antunes De Oliveira, R.K. Dewanjee, K. Ehataht, M. Kadastik, M. Raidal, C. Veelken JHEP05(2019)088 Department of Physics, University of Helsinki, Helsinki, Finland P. Eerola, H. Kirschenmann, J. Pekkanen, M. Voutilainen Helsinki Institute of Physics, Helsinki, Finland J. Havukainen, J.K. Heikkilä, T. Järvinen, V. Karimäki, R. Kinnunen, T. Lampén, K. Lassila-Perini, S. Laurila, S. Lehti, T. Lindén, P. Luukka, T. Mäenpää, H. Siikonen, E. Tuominen, J. Tuominiemi Lappeenranta University of Technology, Lappeenranta, Finland T. Tuuva IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France M. Besancon, F. Couderc, M. Dejardin, D. Denegri, J.L. Faure, F. Ferri, S. Ganjour, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry, C. Leloup, E. Locci, J. Malcles, G. Negro, J. Rander, A. Rosowsky, M.Ö. Sahin, A. Savoy-Navarro14 , M. Titov Laboratoire Leprince-Ringuet, Ecole polytechnique, CNRS/IN2P3, Université Paris-Saclay, Palaiseau, France C. Amendola, F. Beaudette, P. Busson, C. Charlot, B. Diab, R. Granier de Cassagnac, I. Kucher, A. Lobanov, J. Martin Blanco, C. Martin Perez, M. Nguyen, C. Ochando, G. Ortona, P. Paganini, J. Rembser, R. Salerno, J.B. Sauvan, Y. Sirois, A.G. Stahl Leiton, A. Zabi, A. Zghiche Université de Strasbourg, CNRS, IPHC UMR 7178, Strasbourg, France J.-L. Agram15 , J. Andrea, D. Bloch, G. Bourgatte, J.-M. Brom, E.C. Chabert, V. Cherepanov, C. Collard, E. Conte15 , J.-C. Fontaine15 , D. Gelé, U. Goerlach, M. Jansová, A.-C. Le Bihan, N. Tonon, P. Van Hove Centre de Calcul de l’Institut National de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3, Villeurbanne, France S. Gadrat Université de Lyon, Université Claude Bernard Lyon 1, CNRS-IN2P3, Institut de Physique Nucléaire de Lyon, Villeurbanne, France S. Beauceron, C. Bernet, G. Boudoul, N. Chanon, R. Chierici, D. Contardo, P. Depasse, H. El Mamouni, J. Fay, S. Gascon, M. Gouzevitch, G. Grenier, B. Ille, F. Lagarde, I.B. Laktineh, H. Lattaud, M. Lethuillier, L. Mirabito, S. Perries, V. Sordini, G. Touquet, M. Vander Donckt, S. Viret – 64 – Georgian Technical University, Tbilisi, Georgia T. Toriashvili16 Tbilisi State University, Tbilisi, Georgia Z. Tsamalaidze9 RWTH Aachen University, I. Physikalisches Institut, Aachen, Germany C. Autermann, L. Feld, M.K. Kiesel, K. Klein, M. Lipinski, M. Preuten, M.P. Rauch, C. Schomakers, J. Schulz, M. Teroerde, B. Wittmer RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany JHEP05(2019)088 A. Albert, M. Erdmann, S. Erdweg, T. Esch, R. Fischer, S. Ghosh, T. Hebbeker, C. Heidemann, K. Hoepfner, H. Keller, L. Mastrolorenzo, M. Merschmeyer, A. Meyer, P. Millet, S. Mukherjee, A. Novak, T. Pook, A. Pozdnyakov, M. Radziej, H. Reithler, M. Rieger, A. Schmidt, D. Teyssier, S. Thüer RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany G. Flügge, O. Hlushchenko, T. Kress, T. Müller, A. Nehrkorn, A. Nowack, C. Pistone, O. Pooth, D. Roy, H. Sert, A. Stahl17 Deutsches Elektronen-Synchrotron, Hamburg, Germany M. Aldaya Martin, T. Arndt, C. Asawatangtrakuldee, I. Babounikau, K. Beernaert, O. Behnke, U. Behrens, A. Bermúdez Martı́nez, D. Bertsche, A.A. Bin Anuar, K. Borras 18 , V. Botta, A. Campbell, P. Connor, C. Contreras-Campana, V. Danilov, A. De Wit, M.M. Defranchis, C. Diez Pardos, D. Domı́nguez Damiani, G. Eckerlin, T. Eichhorn, A. El- wood, E. Eren, E. Gallo19 , A. Geiser, J.M. Grados Luyando, A. Grohsjean, M. Guthoff, M. Haranko, A. Harb, N.Z. Jomhari, H. Jung, M. Kasemann, J. Keaveney, C. Kleinwort, J. Knolle, D. Krücker, W. Lange, T. Lenz, J. Leonard, K. Lipka, W. Lohmann 20 , R. Mankel, I.-A. Melzer-Pellmann, A.B. Meyer, M. Meyer, M. Missiroli, G. Mittag, J. Mnich, V. Myronenko, S.K. Pflitsch, D. Pitzl, A. Raspereza, A. Saibel, M. Savitskyi, P. Saxena, P. Schütze, C. Schwanenberger, R. Shevchenko, A. Singh, H. Tholen, O. Turkot, A. Vagnerini, M. Van De Klundert, G.P. Van Onsem, R. Walsh, Y. Wen, K. Wichmann, C. Wissing, O. Zenaiev University of Hamburg, Hamburg, Germany R. Aggleton, S. Bein, L. Benato, A. Benecke, V. Blobel, T. Dreyer, A. Ebrahimi, E. Garutti, D. Gonzalez, P. Gunnellini, J. Haller, A. Hinzmann, A. Karavdina, G. Kasieczka, R. Klan- ner, R. Kogler, N. Kovalchuk, S. Kurz, V. Kutzner, J. Lange, D. Marconi, J. Multhaup, M. Niedziela, C.E.N. Niemeyer, D. Nowatschin, A. Perieanu, A. Reimers, O. Rieger, C. Scharf, P. Schleper, S. Schumann, J. Schwandt, J. Sonneveld, H. Stadie, G. Steinbrück, F.M. Stober, M. Stöver, B. Vormwald, I. Zoi Karlsruher Institut fuer Technologie, Karlsruhe, Germany M. Akbiyik, C. Barth, M. Baselga, S. Baur, T. Berger, E. Butz, R. Caspart, T. Chwalek, W. De Boer, A. Dierlamm, K. El Morabit, N. Faltermann, M. Giffels, M.A. Harrendorf, F. Hartmann17 , U. Husemann, I. Katkov2 , S. Kudella, S. Mitra, M.U. Mozer, Th. Müller, – 65 – M. Musich, G. Quast, K. Rabbertz, M. Schröder, I. Shvetsov, H.J. Simonis, R. Ulrich, M. Weber, C. Wöhrmann, R. Wolf Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece G. Anagnostou, G. Daskalakis, T. Geralis, A. Kyriakis, D. Loukas, G. Paspalaki National and Kapodistrian University of Athens, Athens, Greece A. Agapitos, G. Karathanasis, P. Kontaxakis, A. Panagiotou, I. Papavergou, N. Saoulidou, K. Vellidis JHEP05(2019)088 National Technical University of Athens, Athens, Greece G. Bakas, K. Kousouris, I. Papakrivopoulos, G. Tsipolitis University of Ioánnina, Ioánnina, Greece I. Evangelou, C. Foudas, P. Gianneios, P. Katsoulis, P. Kokkas, S. Mallios, K. Manitara, N. Manthos, I. Papadopoulos, E. Paradas, J. Strologas, F.A. Triantis, D. Tsitsonis MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös Loránd University, Budapest, Hungary M. Bartók21 , M. Csanad, N. Filipovic, P. Major, K. Mandal, A. Mehta, M.I. Nagy, G. Pasztor, O. Surányi, G.I. Veres Wigner Research Centre for Physics, Budapest, Hungary G. Bencze, C. Hajdu, D. Horvath22 , Á. Hunyadi, F. Sikler, T.Á. Vámi, V. Veszpremi, G. Vesztergombi† Institute of Nuclear Research ATOMKI, Debrecen, Hungary N. Beni, S. Czellar, J. Karancsi21 , A. Makovec, J. Molnar, Z. Szillasi Institute of Physics, University of Debrecen, Debrecen, Hungary P. Raics, Z.L. Trocsanyi, B. Ujvari Indian Institute of Science (IISc), Bangalore, India S. Choudhury, J.R. Komaragiri, P.C. Tiwari National Institute of Science Education and Research, HBNI, Bhubaneswar, India S. Bahinipati24 , C. Kar, P. Mal, A. Nayak25 , S. Roy Chowdhury, D.K. Sahoo24 , S.K. Swain Panjab University, Chandigarh, India S. Bansal, S.B. Beri, V. Bhatnagar, S. Chauhan, R. Chawla, N. Dhingra, R. Gupta, A. Kaur, M. Kaur, S. Kaur, P. Kumari, M. Lohan, M. Meena, K. Sandeep, S. Sharma, J.B. Singh, A.K. Virdi, G. Walia University of Delhi, Delhi, India A. Bhardwaj, B.C. Choudhary, R.B. Garg, M. Gola, S. Keshri, Ashok Kumar, S. Malhotra, M. Naimuddin, P. Priyanka, K. Ranjan, Aashaq Shah, R. Sharma – 66 – Saha Institute of Nuclear Physics, HBNI, Kolkata, India R. Bhardwaj26 , M. Bharti26 , R. Bhattacharya, S. Bhattacharya, U. Bhawandeep26 , D. Bhowmik, S. Dey, S. Dutt26 , S. Dutta, S. Ghosh, M. Maity27 , K. Mondal, S. Nandan, A. Purohit, P.K. Rout, A. Roy, G. Saha, S. Sarkar, T. Sarkar27 , M. Sharan, B. Singh26 , S. Thakur26 Indian Institute of Technology Madras, Madras, India P.K. Behera, A. Muhammad Bhabha Atomic Research Centre, Mumbai, India JHEP05(2019)088 R. Chudasama, D. Dutta, V. Jha, V. Kumar, D.K. Mishra, P.K. Netrakanti, L.M. Pant, P. Shukla, P. Suggisetti Tata Institute of Fundamental Research-A, Mumbai, India T. Aziz, M.A. Bhat, S. Dugad, G.B. Mohanty, N. Sur, RavindraKumar Verma Tata Institute of Fundamental Research-B, Mumbai, India S. Banerjee, S. Bhattacharya, S. Chatterjee, P. Das, M. Guchait, Sa. Jain, S. Karmakar, S. Kumar, G. Majumder, K. Mazumdar, N. Sahoo, S. Sawant Indian Institute of Science Education and Research (IISER), Pune, India S. Chauhan, S. Dube, V. Hegde, A. Kapoor, K. Kothekar, S. Pandey, A. Rane, A. Rastogi, S. Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran S. Chenarani28 , E. Eskandari Tadavani, S.M. Etesami28 , M. Khakzad, M. Mohammadi Na- jafabadi, M. Naseri, F. Rezaei Hosseinabadi, B. Safarzadeh29 , M. Zeinali University College Dublin, Dublin, Ireland M. Felcini, M. Grunewald INFN Sezione di Baria , Università di Barib , Politecnico di Baric , Bari, Italy M. Abbresciaa,b , C. Calabriaa,b , A. Colaleoa , D. Creanzaa,c , L. Cristellaa,b , N. De Filippisa,c , M. De Palmaa,b , A. Di Florioa,b , F. Erricoa,b , L. Fiorea , A. Gelmia,b , G. Iasellia,c , M. Incea,b , S. Lezkia,b , G. Maggia,c , M. Maggia , G. Minielloa,b , S. Mya,b , S. Nuzzoa,b , A. Pompilia,b , G. Pugliesea,c , R. Radognaa , A. Ranieria , G. Selvaggia,b , A. Sharmaa , L. Silvestrisa , R. Vendittia , P. Verwilligena INFN Sezione di Bolognaa , Università di Bolognab , Bologna, Italy G. Abbiendia , C. Battilanaa,b , D. Bonacorsia,b , L. Borgonovia,b , S. Braibant-Giacomellia,b , R. Campaninia,b , P. Capiluppia,b , A. Castroa,b , F.R. Cavalloa , S.S. Chhibraa,b , G. Codispotia,b , M. Cuffiania,b , G.M. Dallavallea , F. Fabbria , A. Fanfania,b , E. Fontanesi, P. Giacomellia , C. Grandia , L. Guiduccia,b , F. Iemmia,b , S. Lo Meoa,30 , S. Marcellinia , G. Masettia , A. Montanaria , F.L. Navarriaa,b , A. Perrottaa , F. Primaveraa,b , A.M. Rossia,b , T. Rovellia,b , G.P. Sirolia,b , N. Tosia INFN Sezione di Cataniaa , Università di Cataniab , Catania, Italy S. Albergoa,b,31 , A. Di Mattiaa , R. Potenzaa,b , A. Tricomia,b,31 , C. Tuvea,b – 67 – INFN Sezione di Firenzea , Università di Firenzeb , Firenze, Italy G. Barbaglia , K. Chatterjeea,b , V. Ciullia,b , C. Civininia , R. D’Alessandroa,b , E. Focardia,b , G. Latino, P. Lenzia,b , M. Meschinia , S. Paolettia , L. Russoa,32 , G. Sguazzonia , D. Stroma , L. Viliania INFN Laboratori Nazionali di Frascati, Frascati, Italy L. Benussi, S. Bianco, F. Fabbri, D. Piccolo INFN Sezione di Genovaa , Università di Genovab , Genova, Italy F. Ferroa , R. Mulargiaa,b , E. Robuttia , S. Tosia,b INFN Sezione di Milano-Bicoccaa , Università di Milano-Bicoccab , Milano, Italy JHEP05(2019)088 A. Benagliaa , A. Beschib , F. Brivioa,b , V. Cirioloa,b,17 , S. Di Guidaa,b,17 , M.E. Dinardoa,b , S. Fiorendia,b , S. Gennaia , A. Ghezzia,b , P. Govonia,b , M. Malbertia,b , S. Malvezzia , D. Menascea , F. Monti, L. Moronia , M. Paganonia,b , D. Pedrinia , S. Ragazzia,b , T. Tabarelli de Fatisa,b , D. Zuoloa,b INFN Sezione di Napolia , Università di Napoli ‘Federico II’b , Napoli, Italy, Università della Basilicatac , Potenza, Italy, Università G. Marconid , Roma, Italy S. Buontempoa , N. Cavalloa,c , A. De Iorioa,b , A. Di Crescenzoa,b , F. Fabozzia,c , F. Fiengaa , G. Galatia , A.O.M. Iorioa,b , L. Listaa , S. Meolaa,d,17 , P. Paoluccia,17 , C. Sciaccaa,b , E. Voevodinaa,b INFN Sezione di Padovaa , Università di Padovab , Padova, Italy, Università di Trentoc , Trento, Italy P. Azzia , N. Bacchettaa , D. Biselloa,b , A. Bolettia,b , A. Bragagnolo, R. Carlina,b , P. Checchiaa , M. Dall’Ossoa,b , P. De Castro Manzanoa , T. Dorigoa , U. Dossellia , F. Gasparinia,b , U. Gasparinia,b , A. Gozzelinoa , S.Y. Hoh, S. Lacapraraa , P. Lujan, M. Margonia,b , A.T. Meneguzzoa,b , J. Pazzinia,b , M. Presillab , P. Ronchesea,b , R. Rossina,b , F. Simonettoa,b , A. Tiko, E. Torassaa , M. Tosia,b , M. Zanettia,b , P. Zottoa,b , G. Zumerlea,b INFN Sezione di Paviaa , Università di Paviab , Pavia, Italy A. Braghieria , A. Magnania , P. Montagnaa,b , S.P. Rattia,b , V. Rea , M. Ressegottia,b , C. Riccardia,b , P. Salvinia , I. Vaia,b , P. Vituloa,b INFN Sezione di Perugiaa , Università di Perugiab , Perugia, Italy M. Biasinia,b , G.M. Bileia , C. Cecchia,b , D. Ciangottinia,b , L. Fanòa,b , P. Laricciaa,b , R. Leonardia,b , E. Manonia , G. Mantovania,b , V. Mariania,b , M. Menichellia , A. Rossia,b , A. Santocchiaa,b , D. Spigaa INFN Sezione di Pisaa , Università di Pisab , Scuola Normale Superiore di Pisac , Pisa, Italy K. Androsova , P. Azzurria , G. Bagliesia , L. Bianchinia , T. Boccalia , L. Borrello, R. Castaldia , M.A. Cioccia,b , R. Dell’Orsoa , G. Fedia , F. Fioria,c , L. Gianninia,c , A. Giassia , M.T. Grippoa , F. Ligabuea,c , E. Mancaa,c , G. Mandorlia,c , A. Messineoa,b , F. Pallaa , A. Rizzia,b , G. Rolandi33 , P. Spagnoloa , R. Tenchinia , G. Tonellia,b , A. Venturia , P.G. Verdinia – 68 – INFN Sezione di Romaa , Sapienza Università di Romab , Rome, Italy L. Baronea,b , F. Cavallaria , M. Cipriania,b , D. Del Rea,b , E. Di Marcoa,b , M. Diemoza , S. Gellia,b , E. Longoa,b , B. Marzocchia,b , P. Meridiania , G. Organtinia,b , F. Pandolfia , R. Paramattia,b , F. Preiatoa,b , C. Quarantaa,b , S. Rahatloua,b , C. Rovellia , F. Santanastasioa,b INFN Sezione di Torinoa , Università di Torinob , Torino, Italy, Università del Piemonte Orientalec , Novara, Italy N. Amapanea,b , R. Arcidiaconoa,c , S. Argiroa,b , M. Arneodoa,c , N. Bartosika , R. Bellana,b , C. Biinoa , A. Cappatia,b , N. Cartigliaa , F. Cennaa,b , S. Comettia , M. Costaa,b , JHEP05(2019)088 R. Covarellia,b , N. Demariaa , B. Kiania,b , C. Mariottia , S. Masellia , E. Migliorea,b , V. Monacoa,b , E. Monteila,b , M. Montenoa , M.M. Obertinoa,b , L. Pachera,b , N. Pastronea , M. Pelliccionia , G.L. Pinna Angionia,b , A. Romeroa,b , M. Ruspaa,c , R. Sacchia,b , R. Salvaticoa,b , K. Shchelinaa,b , V. Solaa , A. Solanoa,b , D. Soldia,b , A. Staianoa INFN Sezione di Triestea , Università di Triesteb , Trieste, Italy S. Belfortea , V. Candelisea,b , M. Casarsaa , F. Cossuttia , A. Da Rolda,b , G. Della Riccaa,b , F. Vazzolera,b , A. Zanettia Kyungpook National University, Daegu, Korea D.H. Kim, G.N. Kim, M.S. Kim, J. Lee, S.W. Lee, C.S. Moon, Y.D. Oh, S.I. Pak, S. Sekmen, D.C. Son, Y.C. Yang Chonnam National University, Institute for Universe and Elementary Particles, Kwangju, Korea H. Kim, D.H. Moon, G. Oh Hanyang University, Seoul, Korea B. Francois, J. Goh34 , T.J. Kim Korea University, Seoul, Korea S. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, Y. Jo, K. Lee, K.S. Lee, S. Lee, J. Lim, S.K. Park, Y. Roh Sejong University, Seoul, Korea H.S. Kim Seoul National University, Seoul, Korea J. Almond, J. Kim, J.S. Kim, H. Lee, K. Lee, S. Lee, K. Nam, S.B. Oh, B.C. Radburn- Smith, S.h. Seo, U.K. Yang, H.D. Yoo, G.B. Yu University of Seoul, Seoul, Korea D. Jeon, H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park Sungkyunkwan University, Suwon, Korea Y. Choi, C. Hwang, J. Lee, I. Yu Riga Technical University, Riga, Latvia V. Veckalns35 – 69 – Vilnius University, Vilnius, Lithuania V. Dudenas, A. Juodagalvis, J. Vaitkus National Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Malaysia Z.A. Ibrahim, M.A.B. Md Ali36 , F. Mohamad Idris37 , W.A.T. Wan Abdullah, M.N. Yusli, Z. Zolkapli Universidad de Sonora (UNISON), Hermosillo, Mexico J.F. Benitez, A. Castaneda Hernandez, J.A. Murillo Quijada JHEP05(2019)088 Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico H. Castilla-Valdez, E. De La Cruz-Burelo, M.C. Duran-Osuna, I. Heredia-De La Cruz 38 , R. Lopez-Fernandez, J. Mejia Guisao, R.I. Rabadan-Trejo, G. Ramirez-Sanchez, R. Reyes- Almanza, A. Sanchez-Hernandez Universidad Iberoamericana, Mexico City, Mexico S. Carrillo Moreno, C. Oropeza Barrera, M. Ramirez-Garcia, F. Vazquez Valencia Benemerita Universidad Autonoma de Puebla, Puebla, Mexico J. Eysermans, I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad Autónoma de San Luis Potosı́, San Luis Potosı́, Mexico A. Morelos Pineda University of Montenegro, Podgorica, Montenegro N. Raicevic University of Auckland, Auckland, New Zealand D. Krofcheck University of Canterbury, Christchurch, New Zealand S. Bheesette, P.H. Butler National Centre for Physics, Quaid-I-Azam University, Islamabad, Pakistan A. Ahmad, M. Ahmad, M.I. Asghar, Q. Hassan, H.R. Hoorani, W.A. Khan, M.A. Shah, M. Shoaib, M. Waqas National Centre for Nuclear Research, Swierk, Poland H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Górski, M. Kazana, M. Szleper, P. Traczyk, P. Zalewski Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Warsaw, Poland K. Bunkowski, A. Byszuk39 , K. Doroba, A. Kalinowski, M. Konecki, J. Krolikowski, M. Misiura, M. Olszewski, A. Pyskir, M. Walczak – 70 – Laboratório de Instrumentação e Fı́sica Experimental de Partı́culas, Lisboa, Portugal M. Araujo, P. Bargassa, C. Beirão Da Cruz E Silva, A. Di Francesco, P. Faccioli, B. Galinhas, M. Gallinaro, J. Hollar, N. Leonardo, J. Seixas, G. Strong, O. Toldaiev, J. Varela Joint Institute for Nuclear Research, Dubna, Russia S. Afanasiev, P. Bunin, M. Gavrilenko, I. Golutvin, I. Gorbunov, A. Kamenev, V. Kar- javine, A. Lanev, A. Malakhov, V. Matveev40,41 , P. Moisenz, V. Palichik, V. Perelygin, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, N. Voytishin, A. Zarubin JHEP05(2019)088 Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia V. Golovtsov, Y. Ivanov, V. Kim42 , E. Kuznetsova43 , P. Levchenko, V. Murzin, V. Ore- shkin, I. Smirnov, D. Sosnov, V. Sulimov, L. Uvarov, S. Vavilov, A. Vorobyev Institute for Nuclear Research, Moscow, Russia Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov, N. Krasnikov, A. Pashenkov, A. Shabanov, D. Tlisov, A. Toropin Institute for Theoretical and Experimental Physics, Moscow, Russia V. Epshteyn, V. Gavrilov, N. Lychkovskaya, V. Popov, I. Pozdnyakov, G. Safronov, A. Spiridonov, A. Stepennov, V. Stolin, M. Toms, E. Vlasov, A. Zhokin Moscow Institute of Physics and Technology, Moscow, Russia T. Aushev National Research Nuclear University ‘Moscow Engineering Physics Institute’ (MEPhI), Moscow, Russia M. Chadeeva44 , S. Polikarpov44 , E. Popova, V. Rusinov P.N. Lebedev Physical Institute, Moscow, Russia V. Andreev, M. Azarkin, I. Dremin41 , M. Kirakosyan, A. Terkulov Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia A. Belyaev, E. Boos, V. Bunichev, M. Dubinin45 , L. Dudko, A. Gribushin, V. Klyukhin, N. Korneeva, I. Lokhtin, S. Obraztsov, M. Perfilov, V. Savrin, P. Volkov Novosibirsk State University (NSU), Novosibirsk, Russia A. Barnyakov46 , V. Blinov46 , T. Dimova46 , L. Kardapoltsev46 , Y. Skovpen46 Institute for High Energy Physics of National Research Centre ‘Kurchatov Institute’, Protvino, Russia I. Azhgirey, I. Bayshev, S. Bitioukov, V. Kachanov, A. Kalinin, D. Konstantinov, P. Man- drik, V. Petrov, R. Ryutin, S. Slabospitskii, A. Sobol, S. Troshin, N. Tyurin, A. Uzunian, A. Volkov National Research Tomsk Polytechnic University, Tomsk, Russia A. Babaev, S. Baidali, V. Okhotnikov – 71 – University of Belgrade: Faculty of Physics and VINCA Institute of Nuclear Sciences P. Adzic47 , P. Cirkovic, D. Devetak, M. Dordevic, P. Milenovic48 , J. Milosevic Centro de Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain J. Alcaraz Maestre, A. Álvarez Fernández, I. Bachiller, M. Barrio Luna, J.A. Brochero Ci- fuentes, M. Cerrada, N. Colino, B. De La Cruz, A. Delgado Peris, C. Fernandez Bedoya, J.P. Fernández Ramos, J. Flix, M.C. Fouz, O. Gonzalez Lopez, S. Goy Lopez, J.M. Her- nandez, M.I. Josa, D. Moran, A. Pérez-Calero Yzquierdo, J. Puerta Pelayo, I. Redondo, JHEP05(2019)088 L. Romero, S. Sánchez Navas, M.S. Soares, A. Triossi Universidad Autónoma de Madrid, Madrid, Spain C. Albajar, J.F. de Trocóniz Universidad de Oviedo, Oviedo, Spain J. Cuevas, C. Erice, J. Fernandez Menendez, S. Folgueras, I. Gonzalez Caballero, J.R. González Fernández, E. Palencia Cortezon, V. Rodrı́guez Bouza, S. Sanchez Cruz, J.M. Vizan Garcia Instituto de Fı́sica de Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, Spain I.J. Cabrillo, A. Calderon, B. Chazin Quero, J. Duarte Campderros, M. Fernandez, P.J. Fernández Manteca, A. Garcı́a Alonso, J. Garcia-Ferrero, G. Gomez, A. Lopez Virto, J. Marco, C. Martinez Rivero, P. Martinez Ruiz del Arbol, F. Matorras, J. Piedra Gomez, C. Prieels, T. Rodrigo, A. Ruiz-Jimeno, L. Scodellaro, N. Trevisani, I. Vila, R. Vi- lar Cortabitarte University of Ruhuna, Department of Physics, Matara, Sri Lanka N. Wickramage CERN, European Organization for Nuclear Research, Geneva, Switzerland D. Abbaneo, B. Akgun, E. Auffray, G. Auzinger, P. Baillon, A.H. Ball, D. Barney, J. Ben- david, M. Bianco, A. Bocci, C. Botta, E. Brondolin, T. Camporesi, M. Cepeda, G. Cermi- nara, E. Chapon, Y. Chen, G. Cucciati, D. d’Enterria, A. Dabrowski, N. Daci, V. Daponte, A. David, A. De Roeck, N. Deelen, M. Dobson, M. Dünser, N. Dupont, A. Elliott-Peisert, F. Fallavollita49 , D. Fasanella, G. Franzoni, J. Fulcher, W. Funk, D. Gigi, A. Gilbert, K. Gill, F. Glege, M. Gruchala, M. Guilbaud, D. Gulhan, J. Hegeman, C. Heidegger, Y. Iiyama, V. Innocente, G.M. Innocenti, A. Jafari, P. Janot, O. Karacheban 20 , J. Kieseler, A. Kornmayer, M. Krammer1 , C. Lange, P. Lecoq, C. Lourenço, L. Malgeri, M. Mannelli, A. Massironi, F. Meijers, J.A. Merlin, S. Mersi, E. Meschi, F. Moortgat, M. Mulders, J. Ngadiuba, S. Nourbakhsh, S. Orfanelli, L. Orsini, F. Pantaleo17 , L. Pape, E. Perez, M. Peruzzi, A. Petrilli, G. 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Vesterbacka Olsson, R. Wallny, D.H. Zhu Universität Zürich, Zurich, Switzerland T.K. Aarrestad, C. Amsler52 , D. Brzhechko, M.F. Canelli, A. De Cosa, R. Del Burgo, S. Donato, C. Galloni, T. Hreus, B. Kilminster, S. Leontsinis, V.M. Mikuni, I. Neutelings, G. Rauco, P. Robmann, D. Salerno, K. Schweiger, C. Seitz, Y. Takahashi, S. Wertz, A. Zucchetta National Central University, Chung-Li, Taiwan T.H. Doan, C.M. Kuo, W. Lin, S.S. Yu National Taiwan University (NTU), Taipei, Taiwan P. Chang, Y. Chao, K.F. Chen, P.H. Chen, W.-S. Hou, Y.F. Liu, R.-S. Lu, E. Paganis, A. Psallidas, A. Steen Chulalongkorn University, Faculty of Science, Department of Physics, Bangkok, Thailand B. Asavapibhop, N. Srimanobhas, N. Suwonjandee Çukurova University, Physics Department, Science and Art Faculty, Adana, Turkey A. Bat, F. Boran, S. Cerci53 , S. Damarseckin54 , Z.S. Demiroglu, F. Dolek, C. Dozen, I. Du- manoglu, G. Gokbulut, EmineGurpinar Guler55 , Y. Guler, I. Hos56 , C. Isik, E.E. Kangal57 , O. Kara, A. 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Zientek Fermi National Accelerator Laboratory, Batavia, U.S.A. S. Abdullin, M. Albrow, M. Alyari, G. Apollinari, A. Apresyan, A. Apyan, S. Banerjee, L.A.T. Bauerdick, A. Beretvas, J. Berryhill, P.C. Bhat, K. Burkett, J.N. Butler, A. Canepa, G.B. Cerati, H.W.K. Cheung, F. Chlebana, M. Cremonesi, J. Duarte, V.D. Elvira, J. Free- man, Z. Gecse, E. Gottschalk, L. Gray, D. Green, S. Grünendahl, O. Gutsche, J. Hanlon, – 75 – R.M. Harris, S. Hasegawa, J. Hirschauer, Z. Hu, B. Jayatilaka, S. Jindariani, M. Johnson, U. Joshi, B. Klima, M.J. Kortelainen, B. Kreis, S. Lammel, D. Lincoln, R. Lipton, M. Liu, T. Liu, J. Lykken, K. Maeshima, J.M. Marraffino, D. Mason, P. McBride, P. Merkel, S. Mrenna, S. Nahn, V. O’Dell, K. Pedro, C. Pena, O. Prokofyev, G. Rakness, F. Ravera, A. Reinsvold, L. Ristori, B. Schneider, E. Sexton-Kennedy, A. Soha, W.J. Spalding, L. Spiegel, S. Stoynev, J. Strait, N. Strobbe, L. Taylor, S. Tkaczyk, N.V. Tran, L. Uplegger, E.W. Vaandering, C. Vernieri, M. Verzocchi, R. 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Mills, M.B. Tonjes, N. Varelas, H. Wang, X. Wang, Z. Wu, J. Zhang The University of Iowa, Iowa City, U.S.A. M. Alhusseini, B. Bilki55 , W. Clarida, K. Dilsiz72 , S. Durgut, R.P. Gandrajula, M. Hayt- myradov, V. Khristenko, O.K. Köseyan, J.-P. Merlo, A. Mestvirishvili, A. Moeller, J. Nachtman, H. Ogul73 , Y. Onel, F. Ozok74 , A. Penzo, C. Snyder, E. Tiras, J. Wetzel Johns Hopkins University, Baltimore, U.S.A. B. Blumenfeld, A. Cocoros, N. Eminizer, D. Fehling, L. Feng, A.V. Gritsan, W.T. Hung, P. Maksimovic, J. Roskes, U. Sarica, M. Swartz, M. Xiao The University of Kansas, Lawrence, U.S.A. A. Al-bataineh, P. Baringer, A. Bean, S. Boren, J. Bowen, A. Bylinkin, J. Castle, S. Khalil, A. Kropivnitskaya, D. Majumder, W. Mcbrayer, M. Murray, C. Rogan, S. Sanders, E. Schmitz, J.D. Tapia Takaki, Q. Wang Kansas State University, Manhattan, U.S.A. S. Duric, A. Ivanov, K. Kaadze, D. Kim, Y. Maravin, D.R. Mendis, T. Mitchell, A. Modak, A. Mohammadi – 76 – Lawrence Livermore National Laboratory, Livermore, U.S.A. F. Rebassoo, D. Wright University of Maryland, College Park, U.S.A. A. Baden, O. Baron, A. Belloni, S.C. Eno, Y. Feng, C. Ferraioli, N.J. Hadley, S. Jabeen, G.Y. Jeng, R.G. Kellogg, J. Kunkle, A.C. Mignerey, S. Nabili, F. Ricci-Tam, M. Seidel, Y.H. Shin, A. Skuja, S.C. Tonwar, K. Wong Massachusetts Institute of Technology, Cambridge, U.S.A. D. Abercrombie, B. Allen, V. Azzolini, A. Baty, R. Bi, S. Brandt, W. Busza, I.A. Cali, JHEP05(2019)088 M. D’Alfonso, G. Gomez Ceballos, M. Goncharov, P. Harris, D. Hsu, M. Hu, M. Klute, D. Kovalskyi, Y.-J. Lee, P.D. Luckey, B. Maier, A.C. Marini, C. Mcginn, C. Mironov, S. Narayanan, X. Niu, C. Paus, D. Rankin, C. Roland, G. Roland, Z. Shi, G.S.F. Stephans, K. Sumorok, K. Tatar, D. Velicanu, J. Wang, T.W. Wang, B. Wyslouch University of Minnesota, Minneapolis, U.S.A. A.C. Benvenuti† , R.M. Chatterjee, A. Evans, P. Hansen, J. Hiltbrand, Sh. Jain, S. Kalafut, M. Krohn, Y. Kubota, Z. Lesko, J. Mans, R. Rusack, M.A. Wadud University of Mississippi, Oxford, U.S.A. J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, U.S.A. E. Avdeeva, K. Bloom, D.R. Claes, C. Fangmeier, L. Finco, F. Golf, R. Gonzalez Suarez, R. Kamalieddin, I. Kravchenko, J.E. Siado, G.R. Snow, B. Stieger State University of New York at Buffalo, Buffalo, U.S.A. A. Godshalk, C. Harrington, I. Iashvili, A. Kharchilava, C. Mclean, D. Nguyen, A. Parker, S. Rappoccio, B. Roozbahani Northeastern University, Boston, U.S.A. G. Alverson, E. Barberis, C. Freer, Y. Haddad, A. Hortiangtham, G. Madigan, D.M. Morse, T. Orimoto, A. Tishelman-charny, T. Wamorkar, B. Wang, A. Wisecarver, D. Wood Northwestern University, Evanston, U.S.A. S. Bhattacharya, J. Bueghly, T. Gunter, K.A. Hahn, N. Odell, M.H. Schmitt, K. Sung, M. Trovato, M. Velasco University of Notre Dame, Notre Dame, U.S.A. R. Bucci, N. Dev, R. Goldouzian, M. Hildreth, K. Hurtado Anampa, C. Jessop, D.J. Kar- mgard, K. Lannon, W. Li, N. Loukas, N. Marinelli, F. Meng, C. Mueller, Y. Musienko 40 , M. Planer, R. Ruchti, P. Siddireddy, G. Smith, S. Taroni, M. Wayne, A. Wightman, M. Wolf, A. Woodard The Ohio State University, Columbus, U.S.A. J. Alimena, L. Antonelli, B. Bylsma, L.S. Durkin, S. Flowers, B. Francis, C. Hill, W. Ji, A. Lefeld, T.Y. Ling, W. Luo, B.L. Winer – 77 – Princeton University, Princeton, U.S.A. S. Cooperstein, G. Dezoort, P. Elmer, J. Hardenbrook, N. Haubrich, S. Higginbotham, A. Kalogeropoulos, S. Kwan, D. Lange, M.T. Lucchini, J. Luo, D. Marlow, K. Mei, I. Ojalvo, J. Olsen, C. Palmer, P. Piroué, J. Salfeld-Nebgen, D. Stickland, C. Tully University of Puerto Rico, Mayaguez, U.S.A. S. Malik, S. Norberg Purdue University, West Lafayette, U.S.A. A. Barker, V.E. Barnes, S. Das, L. Gutay, M. Jones, A.W. Jung, A. Khatiwada, B. Ma- hakud, D.H. Miller, N. Neumeister, C.C. Peng, S. Piperov, H. Qiu, J.F. Schulte, J. Sun, JHEP05(2019)088 F. Wang, R. Xiao, W. Xie Purdue University Northwest, Hammond, U.S.A. T. Cheng, J. Dolen, N. Parashar Rice University, Houston, U.S.A. Z. Chen, K.M. Ecklund, S. Freed, F.J.M. Geurts, M. Kilpatrick, Arun Kumar, W. Li, B.P. Padley, R. Redjimi, J. Roberts, J. Rorie, W. Shi, Z. Tu, A. Zhang University of Rochester, Rochester, U.S.A. A. Bodek, P. de Barbaro, R. Demina, Y.t. Duh, J.L. Dulemba, C. Fallon, T. Ferbel, M. Galanti, A. Garcia-Bellido, J. Han, O. Hindrichs, A. Khukhunaishvili, E. Ranken, P. Tan, R. Taus Rutgers, The State University of New Jersey, Piscataway, U.S.A. B. Chiarito, J.P. Chou, Y. Gershtein, E. Halkiadakis, A. Hart, M. Heindl, E. Hughes, S. Kaplan, S. Kyriacou, I. Laflotte, A. Lath, R. Montalvo, K. Nash, M. Osherson, H. Saka, S. Salur, S. Schnetzer, D. Sheffield, S. Somalwar, R. Stone, S. Thomas, P. Thomassen University of Tennessee, Knoxville, U.S.A. H. Acharya, A.G. Delannoy, J. Heideman, G. Riley, S. Spanier Texas A&M University, College Station, U.S.A. O. Bouhali75 , A. Celik, M. Dalchenko, M. De Mattia, A. Delgado, S. Dildick, R. Eusebi, J. Gilmore, T. Huang, T. Kamon76 , S. Luo, D. Marley, R. Mueller, D. Overton, L. Perniè, D. Rathjens, A. Safonov Texas Tech University, Lubbock, U.S.A. N. Akchurin, J. Damgov, F. De Guio, P.R. Dudero, S. Kunori, K. Lamichhane, S.W. Lee, T. Mengke, S. Muthumuni, T. Peltola, S. Undleeb, I. Volobouev, Z. Wang, A. Whitbeck Vanderbilt University, Nashville, U.S.A. S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, K. Padeken, F. Romeo, P. Sheldon, S. Tuo, J. Velkovska, M. Verweij, Q. Xu University of Virginia, Charlottesville, U.S.A. M.W. Arenton, P. Barria, B. Cox, R. Hirosky, M. Joyce, A. Ledovskoy, H. Li, C. Neu, Y. Wang, E. Wolfe, F. Xia – 78 – Wayne State University, Detroit, U.S.A. R. Harr, P.E. Karchin, N. Poudyal, J. Sturdy, P. Thapa, S. Zaleski University of Wisconsin — Madison, Madison, WI, U.S.A. J. Buchanan, C. Caillol, D. Carlsmith, S. Dasu, I. De Bruyn, L. Dodd, B. Gomber 77 , M. Grothe, M. Herndon, A. Hervé, U. Hussain, P. Klabbers, A. Lanaro, K. Long, R. Loveless, T. Ruggles, A. Savin, V. Sharma, N. Smith, W.H. Smith, N. Woods †: Deceased 1: Also at Vienna University of Technology, Vienna, Austria JHEP05(2019)088 2: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia 3: Also at IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France 4: Also at Universidade Estadual de Campinas, Campinas, Brazil 5: Also at Federal University of Rio Grande do Sul, Porto Alegre, Brazil 6: Also at Université Libre de Bruxelles, Bruxelles, Belgium 7: Also at University of Chinese Academy of Sciences, Beijing, China 8: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia 9: Also at Joint Institute for Nuclear Research, Dubna, Russia 10: Also at Cairo University, Cairo, Egypt 11: Also at Suez University, Suez, Egypt 12: Now at British University in Egypt, Cairo, Egypt 13: Also at Zewail City of Science and Technology, Zewail, Egypt 14: Also at Purdue University, West Lafayette, U.S.A. 15: Also at Université de Haute Alsace, Mulhouse, France 16: Also at Tbilisi State University, Tbilisi, Georgia 17: Also at CERN, European Organization for Nuclear Research, Geneva, Switzerland 18: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany 19: Also at University of Hamburg, Hamburg, Germany 20: Also at Brandenburg University of Technology, Cottbus, Germany 21: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary 22: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary 23: Also at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös Loránd University, Budapest, Hungary 24: Also at Indian Institute of Technology Bhubaneswar, Bhubaneswar, India 25: Also at Institute of Physics, Bhubaneswar, India 26: Also at Shoolini University, Solan, India 27: Also at University of Visva-Bharati, Santiniketan, India 28: Also at Isfahan University of Technology, Isfahan, Iran 29: Also at Plasma Physics Research Center, Science and Research Branch, Islamic Azad University, Tehran, Iran 30: Also at Italian National Agency for New Technologies, Energy and Sustainable Economic Development, Bologna, Italy 31: Also at Centro Siciliano di Fisica Nucleare e di Struttura della Materia, Catania, Italy 32: Also at Università degli Studi di Siena, Siena, Italy 33: Also at Scuola Normale e Sezione dell’INFN, Pisa, Italy 34: Also at Kyung Hee University, Department of Physics, Seoul, Korea 35: Also at Riga Technical University, Riga, Latvia – 79 – 36: Also at International Islamic University of Malaysia, Kuala Lumpur, Malaysia 37: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia 38: Also at Consejo Nacional de Ciencia y Tecnologı́a, Mexico City, Mexico 39: Also at Warsaw University of Technology, Institute of Electronic Systems, Warsaw, Poland 40: Also at Institute for Nuclear Research, Moscow, Russia 41: Now at National Research Nuclear University ‘Moscow Engineering Physics Institute’ (MEPhI), Moscow, Russia 42: Also at St. Petersburg State Polytechnical University, St. Petersburg, Russia 43: Also at University of Florida, Gainesville, U.S.A. 44: Also at P.N. Lebedev Physical Institute, Moscow, Russia 45: Also at California Institute of Technology, Pasadena, U.S.A. JHEP05(2019)088 46: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia 47: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia 48: Also at University of Belgrade — Faculty of Physics, Belgrade, Serbia 49: Also at INFN Sezione di Paviaa , Università di Paviab , Pavia, Italy 50: Also at National and Kapodistrian University of Athens, Athens, Greece 51: Also at Universität Zürich, Zurich, Switzerland 52: Also at Stefan Meyer Institute for Subatomic Physics (SMI), Vienna, Austria 53: Also at Adiyaman University, Adiyaman, Turkey 54: Also at Sirnak University, SIRNAK, Turkey 55: Also at Beykent University, Istanbul, Turkey 56: Also at Istanbul Aydin University, Istanbul, Turkey 57: Also at Mersin University, Mersin, Turkey 58: Also at Piri Reis University, Istanbul, Turkey 59: Also at Gaziosmanpasa University, Tokat, Turkey 60: Also at Ozyegin University, Istanbul, Turkey 61: Also at Izmir Institute of Technology, Izmir, Turkey 62: Also at Marmara University, Istanbul, Turkey 63: Also at Kafkas University, Kars, Turkey 64: Also at Istanbul University, Faculty of Science, Istanbul, Turkey 65: Also at Istanbul Bilgi University, Istanbul, Turkey 66: Also at Hacettepe University, Ankara, Turkey 67: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom 68: Also at School of Physics and Astronomy, University of Southampton, Southampton, United Kingdom 69: Also at Monash University, Faculty of Science, Clayton, Australia 70: Also at Bethel University, St. Paul, U.S.A. 71: Also at Karamanoğlu Mehmetbey University, Karaman, Turkey 72: Also at Bingol University, Bingol, Turkey 73: Also at Sinop University, Sinop, Turkey 74: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey 75: Also at Texas A&M University at Qatar, Doha, Qatar 76: Also at Kyungpook National University, Daegu, Korea 77: Also at University of Hyderabad, Hyderabad, India – 80 –