Published for SISSA by Springer Received: August 8, 2019 Accepted: October 9, 2019 Published: October 18, 2019 Measurement of the inclusive isolated-photon cross √ JHEP10(2019)203 section in pp collisions at s = 13 TeV using 36 fb−1 of ATLAS data The ATLAS collaboration E-mail: atlas.publications@cern.ch Abstract: The differential cross section for isolated-photon production in pp collisions is measured at a centre-of-mass energy of 13 TeV with the ATLAS detector at the LHC using an integrated luminosity of 36.1 fb−1 . The differential cross section is presented as a function of the photon transverse energy in different regions of photon pseudorapidity. The differential cross section as a function of the absolute value of the photon pseudorapidity is also presented in different regions of photon transverse energy. Next-to-leading-order QCD calculations from Jetphox and Sherpa as well as next-to-next-to-leading-order QCD calculations from Nnlojet are compared with the measurement, using several parame- terisations of the proton parton distribution functions. The predictions provide a good description of the data within the experimental and theoretical uncertainties. Keywords: Hadron-Hadron scattering (experiments), Photon production, QCD ArXiv ePrint: 1908.02746 Open Access, Copyright CERN, https://doi.org/10.1007/JHEP10(2019)203 for the benefit of the ATLAS Collaboration. Article funded by SCOAP3 . Contents 1 Introduction 1 2 ATLAS detector 3 3 Data sample and Monte Carlo simulations 3 4 Event selection 5 JHEP10(2019)203 5 Background evaluation and signal extraction 7 6 Fiducial phase space and unfolding 8 7 Systematic uncertainties 9 8 Theoretical predictions 12 8.1 Theoretical uncertainties in the NLO QCD predictions 15 8.2 Theoretical uncertainties in the NNLO QCD prediction 16 9 Results 20 10 Summary and conclusions 28 The ATLAS collaboration 34 1 Introduction Prompt photons with large transverse momenta constitute colourless probes of the hard interaction and their production in proton-proton collisions, pp → γ + X, provides a testing ground for perturbative QCD (pQCD). Prompt photons are defined as those that are not secondaries from hadron decays. Prompt-photon production is understood to proceed via two processes: the one in which the photon arises directly from the hard interaction (the direct-photon process) and the one in which the photon is emitted in the fragmentation of a high transverse momentum (pT ) parton (the fragmentation-photon process) [1, 2]. In proton-proton collisions, due to the abundance of photons from neutral-hadron decays and the contribution from the fragmentation process, prompt-photon production is studied by requiring the photons to be isolated. Measurements of inclusive isolated-photon √ production in pp collisions at centre-of-mass energies ( s) of 7, 8 and 13 TeV are available from the ATLAS [3–5] and CMS [6, 7] collaborations. At the LHC the dominant contribution to prompt-photon production arises from the qg → qγ process. As a consequence, the production is sensitive to the gluon density in the proton [8–10] even at leading order (LO) in pQCD. A recent study [11] has included –1– the ATLAS measurement of inclusive isolated-photon production at 8 TeV [4] in a next-to- next-to-leading-order (NNLO) QCD fit to obtain the parton distribution functions (PDF) of the proton. The inclusion of the ATLAS data leads to a reduction in the gluon density uncertainties [11]. Measurements of inclusive prompt-photon production also provide benchmarks to use in investigating novel approaches to parton radiation [12], next-to-leading-order (NLO) QCD corrections with matched parton showers [13], the relevance of threshold logarithms in QCD and electroweak corrections [14] and NNLO QCD corrections [15–17]. More specif- ically, the production of prompt photons, which is less sensitive to hadronisation effects JHEP10(2019)203 than that of jets, can be used to pursue an alternative QCD description based on the kT fac- torisation approach combining off-shell amplitudes and transverse-momentum-dependent parton densities [12]. The prompt-photon data allow the investigation of the fragmentation contribution, which can be done either via fragmentation functions or through the inclusion of parton showers [13]. Electroweak corrections are likely to play an important role at the TeV scale and, thereby, measurements at photon transverse energies in that region would help to unveil such phenomena [14]. The prompt-photon measurements at the LHC are characterised by small uncertainties that demand precise theoretical predictions, e.g. those from NNLO QCD calculations [15–17], in order to fully exploit these data. Measurements involving isolated photons have also been used to constrain the contributions from new light scalar particles decaying into a photon pair [18]. This paper presents a measurement of isolated prompt-photon production in pp colli- √ sions at s = 13 TeV with the ATLAS detector at the LHC using an integrated luminosity of 36.1 fb−1 . The differential cross section as a function of the photon transverse energy 1 γ γ (ET ) is measured in different regions of the photon pseudorapidity (η γ ) for ET > 125 GeV γ γ and |η | < 2.37, excluding the region 1.37 < |η | < 1.56. In addition, the double-differential γ cross section as a function of |η γ | in different regions of ET is also presented. The results are based on a data sample with a more than ten-fold increase in statistics relative to the previous study [5]. The measurement presented here is found to be consistent with the previous one in the overlapping kinematic regions. This increase in statistics allows improvements in the calibration of the photon energy and reductions in the experimental systematic uncertainties affecting the cross-section measurement, as well as an extension of γ the coverage in ET to higher values than previously measured. In this analysis, the region γ where the measurement is limited by systematic uncertainties is extended to ET ∼ 1 TeV, beyond what was achieved in the previous measurement. The NLO QCD predictions of Jetphox [19, 20] and Sherpa [21] based on several parameterisations of the PDFs are compared with the measurement. The NNLO QCD prediction of Nnlojet [16], which has significantly reduced uncertainties due to fewer missing higher-order terms, is also confronted with the data. 1 ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP) in the centre of the detector and the z-axis along the beam pipe. The x-axis points from the IP to the centre of the LHC ring, and the y-axis points upwards. Cylindrical coordinates (r, φ) are used in the transverse plane, φ being the azimuthal angle around the z-axis. The transverse energy is defined as ET = E sin θ, where E is the energy and θ is the polar angle. pThe pseudorapidity is defined as η = − ln tan(θ/2) and the angular distance is measured in units of ∆R ≡ (∆η)2 + (∆φ)2 . –2– 2 ATLAS detector The ATLAS detector [22–24] is a multipurpose detector with a forward-backward symmet- ric cylindrical geometry. It consists of an inner tracking detector surrounded by a thin superconducting solenoid, electromagnetic and hadronic calorimeters, and a muon spec- trometer incorporating three large superconducting toroid magnets. The inner-detector system is immersed in a 2 T axial magnetic field and provides charged-particle tracking in the range |η| < 2.5. The high-granularity silicon pixel detector is closest to the interac- tion region and provides four measurements per track. The pixel detector is followed by the silicon microstrip tracker, which typically provides four three-dimensional space point JHEP10(2019)203 measurements per track. These silicon detectors are complemented by the transition ra- diation tracker, which enables radially extended track reconstruction up to |η| = 2. The calorimeter system covers the range |η| < 4.9. Within the region |η| < 3.2, electromag- netic (EM) calorimetry is provided by barrel and endcap high-granularity lead/liquid-argon (LAr) calorimeters, with an additional thin LAr presampler covering |η| < 1.8 to correct for energy loss in material upstream of the calorimeters; for |η| < 2.5, the EM calorimeter is di- vided into three layers in depth. Hadronic calorimetry is provided by a steel/scintillator-tile calorimeter, segmented into three barrel structures within |η| < 1.7, and two copper/LAr hadronic endcap calorimeters, which cover the region 1.5 < |η| < 3.2. The solid-angle cov- erage is completed out to |η| = 4.9 with forward copper/LAr and tungsten/LAr calorimeter modules, which are optimised for EM and hadronic measurements, respectively. Events are selected using a first-level trigger implemented in custom electronics, which reduces the maximum bunch crossing rate of 40 MHz to a design value of 100 kHz using a subset of detector information. Software algorithms with access to the full detector information are then used in the high-level trigger to yield a recorded event rate of about 1 kHz [25]. 3 Data sample and Monte Carlo simulations The data used in this analysis were collected with the ATLAS detector during the proton- proton collision running periods of 2015 and 2016, when the LHC operated at a centre- √ of-mass energy of s = 13 TeV. Only events taken during stable beam conditions and satisfying detector- and data-quality requirements, which include the calorimeters and inner tracking detectors being in nominal operation, are considered. In the collected data sample the average number of pp interactions per bunch crossing is 24, while the total integrated luminosity is 36.1 ± 0.8 fb−1 out of which 3.22 ± 0.07 fb−1 corresponds to the 2015 running period. The uncertainty in the combined 2015–2016 integrated luminosity is 2.1% [26], obtained using the LUCID-2 detector [27] for the primary luminosity measurements. The simulated events were produced using MC event generators and were passed through the Geant4-based [28] ATLAS detector and trigger simulation programs [29]. They are reconstructed and analysed with the same programs chain as the data. Simulated signal samples. Samples of prompt-photon events were generated using the programs Pythia 8.186 [30] and Sherpa 2.1.1 [21] to study the characteristics of signal events. In both cases, the event generation was performed using tree-level matrix elements, –3– with the inclusion of initial- and final-state parton showers. Fragmentation into hadrons is described by the Lund string model [31] in the case of Pythia and by a modified version of the cluster model [32] in the case of Sherpa. The proton’s structure was parameterised by the LO NNPDF2.3 [33] PDF set for Pythia and by the NLO CT10 [34] PDF set for Sherpa. All samples include a simulation of the underlying event (UE), with parameter values set according to the ATLAS 2014 tune series (A14 tune) for Pythia [35] or to the tune developed by the authors of Sherpa for use in conjunction with the NLO CT10 PDF set. The Pythia simulation of the signal includes LO photon-plus-jet events from direct processes (the hard subprocesses qg → qγ and q q̄ → gγ, called the ‘hard’ component) and photon bremsstrahlung in LO QCD dijet events (called the ‘bremsstrahlung’ component). JHEP10(2019)203 The bremsstrahlung component is modelled by final-state QED radiation arising from calculations of all 2 → 2 QCD processes. The Sherpa samples were generated with LO matrix elements for photon-plus-jet final states with up to three additional partons (2 → n processes with n from 2 to 5); the matrix elements were merged with the Sherpa parton shower using the ME+PS@LO prescription [36]. The bremsstrahlung component is accounted for in Sherpa through the matrix elements of 2 → n processes with n ≥ 3. In the generation of the Sherpa samples, a requirement on the photon isolation at the matrix- element level is imposed using the criterion defined in ref. [37]. This criterion, commonly called Frixione’s criterion, requires the total transverse energy inside a cone of size r in the η–φ plane around the generated final-state photon, excluding the photon itself, to be below a certain threshold, ET max (r) = E γ ((1 − cos r)/(1 − cos R))n , for all r < R, where R T γ is the maximal cone size, n is the power and  is a constant such that ET represents the threshold for r = R. The parameters for the threshold are chosen to be R = 0.3, n = 2 and  = 0.025. The criterion is applied to avoid divergencies in the matrix elements when the photon is collinear with a parton. Simulated background samples. The main background to isolated-photon events arises from jets misidentified as photons. This background is subtracted using a data- driven technique, which is described in section 5; thus, no MC sample is used to simulate this background. The background from electrons or positrons misidentified as photons is evaluated using MC samples generated with the program Sherpa 2.2.1 [21, 38–42]. The pp → Z/γ ∗ → e+ e− + X and pp → W → eν + X processes were generated with matrix elements calculated for up to two additional partons at NLO and up to four partons at LO. The NNLO NNPDF3.0 PDF set [43] was used in conjunction with a dedicated set of parton-shower-generator parameter values (tune) developed by the Sherpa authors. Simulation of pile-up. Pile-up from additional pp collisions in the same and neighbour- ing bunch crossings was simulated by overlaying each MC event with a variable number of simulated inelastic pp collisions generated using Pythia 8.186 with the ATLAS set of tuned parameters for minimum-bias events (A2 tune) [44] and the MSTW2008LO PDF set [45]. The MC events are weighted (‘pile-up reweighting’) to reproduce the distribution of the average number of interactions per bunch crossing observed in the data. –4– 4 Event selection Events were recorded using a single-photon trigger with a transverse energy threshold of 120 GeV (140 GeV) for the 2015 (2015 and 2016) data-taking period2 and ‘loose’ photon identification requirements [25, 46].3 Events are required to contain at least one recon- structed proton-proton interaction vertex. The vertex with the highest sum of the p2T of the associated tracks is selected as the primary vertex. Photon candidates are reconstructed from clusters of energy deposited in the EM calorimeter and classified [46] as unconverted photon candidates (clusters without a match- ing track or without a matching reconstructed conversion vertex in the inner detector) or JHEP10(2019)203 converted photon candidates (clusters with a matching reconstructed conversion vertex or a matching track consistent with originating from a photon conversion). The main back- ground in the prompt-photon production measurement comes from an energetic π 0 or η meson which is misidentified as a photon because it decays into an almost collinear photon pair. Such energetic π 0 or η mesons are produced copiously inside jets. This background is reduced by the photon identification criteria and by requiring the photon candidate to be isolated. Photon candidates are identified by using variables that characterise the lat- eral and longitudinal electromagnetic shower development in the EM calorimeter and the energy fraction leaking into the hadronic calorimeter. Tight requirements are imposed on the shower shapes in the second layer and in the finely segmented first layer of the EM calorimeter as well as on the energy deposited in the hadronic calorimeter [46]. These re- quirements are optimised separately for unconverted and converted photon candidates and ensure the compatibility of the measured shower profile with that originating from a single photon impacting the calorimeter. Small differences in the average values of the shower- shape variables between data and simulation are observed and corrected for in simulated events prior to the application of the photon identification criteria. Three data-driven methods based on radiative Z decays, electron extrapolation and an inclusive sample of photon candidates [46] are used to measure the efficiency of the tight identification crite- ria. The results of the three methods agree in the overlapping kinematic regions and the measured efficiencies are above 90% (95%) for unconverted (converted) photon candidates γ with ET > 125 GeV. Efficiency scale factors are evaluated as the ratios of the measured efficiencies to the efficiencies obtained in simulation and are applied to photon candidates in simulated events. The resulting efficiency scale factors are compatible with unity and γ have uncertainties in the range 1%–3%, depending on ET and η γ . The photon isolation requirement is based on the amount of transverse energy (ET iso ) inside a cone of size ∆R = 0.4 around the photon candidate, excluding an area of size ∆η × ∆φ = 0.125 × 0.175 centred on the barycentre of the photon cluster. The measured value of ET iso is computed from topological clusters of calorimeter cells [47] and is corrected for the expected leakage of the photon energy into the isolation cone as well as for the 2 The single-photon trigger with the threshold of 120 GeV was kept unprescaled during 2015 whereas it had to be prescaled during 2016 due to the increase in instantaneous luminosity. 3 The discriminating variables used for ‘loose’ and ‘tight’ photon identification can be found in table 1 of ref. [46]. –5– Phase-space region γ γ Requirement on ET ET > 125 GeV Isolation requirement iso < 4.2 × 10−3 × E γ + 4.8 GeV ET T Requirement on |η γ | |η γ | < 0.6 0.6 < |η γ | < 1.37 1.56 < |η γ | < 1.81 1.81 < |η γ | < 2.37 Number of events with γ 125 < ET < 150 GeV 182 754 248 538 74 405 144 713 Number of events with γ ET > 150 GeV 2 030 144 2 696 077 814 623 1 471 953 JHEP10(2019)203 Table 1. Definition of the phase-space region for the measurement and predictions. The (next- γ to) last row indicates the number of data events selected in each |η γ | region for ET > 150 GeV γ γ (125 < ET < 150 GeV). For 125 < ET < 150 GeV only data from the 2015 running period are used γ while for ET > 150 GeV data from the 2015 and 2016 running periods are used. contributions from the UE and pile-up [48, 49]. The correction to ET iso from the combined effect of the UE and pile-up is evaluated using the jet-area method [50, 51] on an event-by- event basis and is typically 3.5 GeV (1.3 GeV) in the region |η γ | < 1.37 (1.56 < |η γ | < 2.37). In simulated events, ET iso is adjusted so that the peak position in the E iso distribution T coincides in data and simulation. After the corrections, ET iso is required to be less than γ iso ET,cut ≡ 4.2 × 10−3 × ET + 4.8 GeV [4]. The calibration of the photon energy in the calorimeter accounts for upstream energy loss as well as lateral and longitudinal leakages. The procedure used for photon energy calibration in Run 1 [52] is employed here, optimised for the detector configuration in Run 2 [53]. The energy of the cluster of calorimeter cells associated with the photon candidate is corrected using a combination of simulation-based and data-driven calibration factors determined from Z → e+ e− events collected during the 2015 and 2016 data-taking periods. The calibration is performed separately for converted and unconverted candidates. γ The uncertainty in the photon energy scale at ET = 125 GeV varies in the range 0.4%–3.1% (0.4%–2.7%) for unconverted (converted) candidates depending on |η γ |. γ Events with at least one photon candidate with calibrated ET above 125 GeV and γ γ |η | < 2.37 are selected. Candidates in the region 1.37 < |η | < 1.56, which includes the transition region between the barrel and endcap calorimeters, are not considered. Photon γ γ candidates with 125 < ET < 150 GeV (ET > 150 GeV) are selected from the 2015 (2015 and 2016) data-taking period. If an event contains more than one photon candidate satisfying the selection criteria γ above, only the highest-ET (leading) photon is considered for further study. The total γ γ number of selected events with a photon candidate with ET > 150 GeV (125 < ET < 150 GeV) is 7 012 797 (650 410). The kinematic requirements and the number of selected events in data in each |η γ | region are summarised in table 1. Each region in |η γ | is divided γ γ into 16 bins of ET starting at ET = 125 GeV and ending at 2500 GeV. The binning is given γ by the following array of values of ET (in units of GeV): 125, 150, 175, 200, 250, 300, 350, γ 400, 470, 550, 650, 750, 900, 1100, 1500, 2000 and 2500. Some of the high-ET bins are not γ measured depending on the |η | region. –6– 5 Background evaluation and signal extraction After the event selection described above, there is a residual background contribution from jets misidentified as photons. This background is evaluated bin-by-bin using a data- driven technique [4, 5] and subtracted to obtain the signal yield. For this purpose, a two-dimensional sideband method is applied, based on a plane formed by the variable ET iso and the photon identification criteria. A photon candidate that fulfils the tight identifica- tion criteria is classified as ‘tight’; the requirements are described in ref. [46]. A photon candidate is classified as ‘non-tight’ if it satisfies a modified set of requirements, but fails the tight identification. The modified set of requirements is built from the full list of tight JHEP10(2019)203 requirements by removing four4 of the selections associated with the shower-shape variables computed from the energy deposits in the first layer of the EM calorimeter. The variables that are removed from the list of tight requirements are those that are least correlated with ET iso . Four regions are defined in the E iso -tightness plane: a signal region (A) con- T taining isolated (ET iso < E iso ) tight photons; a background control region B consisting of T,cut iso + 2 GeV < E iso < 50 GeV) tight photons; a background control region non-isolated (ET,cut T C containing isolated non-tight photons; and a background control region D consisting of non-isolated non-tight photons. The signal yield NAsig in region A is extracted by solving the equation (NC − fC NAsig ) NAsig = NA − Rbg · (NB − fB NAsig ) · , (5.1) (ND − fD NAsig ) where NK , with K = A, B, C, D, is the number of events in region K and Rbg = NAbg · bg ND /(NBbg · NCbg ) is the so-called background correlation, where NK bg with K = A, B, C, D, is the a priori unknown number of background events in each region. The number of sig signal events in each of the three background control regions (NK ) is taken into account sig sig in eq. (5.1) via the signal leakage fractions fK ≡ NK /NA with K = B, C, D. MC simulations of the signal are used to evaluate the signal leakage fractions. Equation (5.1) with Rbg = 1 can be understood as the relationship arising from the application of the standard ABCD method [48] taking into account the contributions from signal events in each region. The ratio of the signal yield to the number of photon candidates in region A is used to estimate the signal purity and is above 90% in all bins of the measured distributions. The signal yield is extracted using leakage fractions from MC simulations and, hence, depends on the modelling of the final state. This dependence is studied by comparing 4 The four variables are ws 3 , fside , ∆Es and Eratio [46]. These variables make use of the first layer of the EM calorimeter; this layer is segmented into high-granularity strips in the η direction. The variable ws 3 is the lateral shower width calculated from three strips around the strip with maximum energy deposit. The variable fside is the energy outside the core of the three central strips but within seven strips divided by the energy within the three central strips. The variable ∆Es is the difference between the energy associated with the second maximum in the strip layer and the energy reconstructed in the strip with the minimum value found between the first and second maxima. The variable Eratio is the ratio of the energy difference between the maximum energy deposit and the energy deposit in the secondary maximum in the cluster to the sum of these energies. –7– the results obtained using either Pythia or Sherpa simulations. The calculations using the two generators lead to similar signal yields and the differences are taken as systematic uncertainties. The signal yields obtained using Pythia for the signal leakage fractions are γ taken as the nominal ones. The distributions of the signal yields as functions of ET in γ different regions of |η | are well described by the Pythia and Sherpa MC simulations, γ except for ET & 900 GeV in the range |η γ | < 1.37. The impact of this mismodelling in the measured cross section, which is estimated by reweighting the MC simulations so that the distributions have the same shape as the data and re-evaluating the unfolding correction factors (see section 6), is found to be negligible. For the nominal results it is assumed that the photon isolation and identification JHEP10(2019)203 variables are uncorrelated for background events, i.e. Rbg = 1. The dependence of the signal yield on this assumption is investigated in validation regions, which are defined within the background control regions B and D. Region B is subdivided into two regions: region B 0 of tight photon candidates with ET,cut iso + 2 GeV < ET iso < E iso T,cut + 10 GeV and region B 00 of tight photon candidates with ET iso > E iso T,cut + 10 GeV. Likewise, region D 0 00 is subdivided into two regions, D and D , using the same separation in ET iso as above. The four regions B 0 , B 00 , D0 and D00 are used to extract values of Rbg from the data after accounting for the signal leakage fractions in those regions using either Pythia or Sherpa MC simulations. The dependence on the signal leakage is investigated by increasing the lower limits on ET iso for the validation regions, E iso iso T,cut + 2 GeV (ET,cut + 10 GeV), each time by 1 GeV up to ET,cut iso iso + 7 GeV (ET,cut + 15 GeV) for regions B 0 and D0 (B 00 and D00 ), keeping the width in ET iso fixed to 8 GeV for the regions B 0 and D 0 . The maximum bg deviations of R from unity in the validation regions vary in the range 15%–40% depending γ on ET and η γ . The differences between the nominal signal yields and those obtained using the maximum deviations of Rbg from unity observed in the validation regions are taken as systematic uncertainties. Electrons or positrons can be misidentified as photons and represent an additional source of background. This background is largely suppressed by the photon selection. The residual background contribution is evaluated using MC simulations of the Drell- Yan processes Z/γ ∗ → e+ e− and W → eν and is found to be sub-percent in the phase- space region of the analysis. Accordingly, no subtraction is performed and a systematic uncertainty of the size of the evaluated background is assigned. 6 Fiducial phase space and unfolding γ The measured differential cross section is unfolded from the distribution in ET separately for each of the four regions in |η γ | after the selection explained in section 4 and after back- ground subtraction, as discussed in section 5. The phase-space region of the measurement closely follows the applied event selection and is indicated in table 1. The fiducial phase- space region is defined at particle level for all particles with a decay length of cτ > 10 mm; these particles are referred to as ‘stable’. The isolation requirement on the photon at parti- cle level is based on the total transverse energy of all stable particles, excluding muons and neutrinos, in a cone of size ∆R = 0.4 around the photon direction after the contributions –8– from the photon itself and the UE are subtracted. The same subtraction procedure of the UE used at detector level is applied at the particle level. The particle-level requirement on ETiso is also the same as the one used at detector level, i.e. E iso < E iso . T T,cut γ The distributions of the background-subtracted signal yields as functions of ET in different regions of |η γ | are unfolded to the particle level using the MC samples of events via a bin-by-bin technique which corrects for resolution effects and the efficiency of the photon selection through the formula dσ NAsig (i) C MC (i) γ (i) = γ , JHEP10(2019)203 dET L ∆ET (i) γ where dσ/dET (i) is the differential cross section in bin i, NAsig (i) is the signal yield in bin i, C MC (i) is the unfolding correction factor in bin i, L is the integrated luminosity γ and ∆ET (i) is the width of bin i. The unfolding correction factors are computed using the MC samples as C MC (i) = Npart MC (i)/N MC (i), where N MC (i) (N MC (i)) is the number det part det of events generated (reconstructed) in bin i at the particle (detector) level. The Pythia MC simulation is used in the evaluation of the unfolding correction factors to obtain the nominal cross section. The unfolding correction factors vary approximately between 1.1 γ and 1.3 depending on ET and |η γ |. The dependence of the results on the modelling of the final state, namely the inclusion of higher-order tree-level matrix elements, the parton shower approach and the hadronisation model, is studied with the Sherpa MC simulation. The differences between the results obtained by using either the Pythia or Sherpa MC simulations are taken as systematic uncertainties. The cross section is also obtained using an iterative Bayesian unfolding method [54] and compared with the nominal result; the two results are consistent with each other independently of whether the Pythia or Sherpa MC simulations are used for the unfolding. 7 Systematic uncertainties The sources of systematic uncertainty that affect the measurement are discussed below. These sources include the signal modelling, the background subtraction, the photon iden- tification and isolation, the unfolding procedure, the modelling of pile-up, the trigger effi- ciency, the luminosity measurement and the photon energy scale and resolution. For some of the systematic uncertainties, the Bootstrap technique [55] is used to evaluate the data statistical influence on the uncertainties. The results are then used in a fit to smooth the systematic uncertainties. Model dependence of the signal leakage fractions. The nominal signal leakage frac- tions used in the extraction of the signal yield are evaluated with the Pythia simulation. The effect of the implementation of the matrix-element calculation in the generator as well as the models used for the parton shower and hadronisation are evaluated by comparing the nominal results with those obtained using the Sherpa simulation for the determina- tion of the signal leakage fractions (see section 5). The differences are taken as systematic –9– uncertainties. The resulting uncertainty in the measured cross section is always less than 2% and typically less than 1%. Background subtraction. The data-driven background subtraction depends on the choice of background control regions. This dependence is studied by varying the lower limit on ETiso for regions B and D by ±1 GeV, removing the upper limit on E iso for regions T B and D, as well as changing the choice of inverted photon identification variables. For the last variation, the analysis is repeated increasing or decreasing the number of the shower- shape variables computed from the energy deposits in the first layer of the EM calorimeter that are removed from the list of tight requirements used in the classification of non-tight JHEP10(2019)203 photon candidates. For each variation, the differences between the nominal signal yields and those extracted using the modified background control regions are taken as systematic uncertainties. The resulting uncertainties in the measured cross section due to the first two variations mentioned above are less than 0.2%. The third variation leads to uncertainties in the measured cross section that are less than 2% and typically less than 1%. As described in section 5, a systematic uncertainty is assigned to the assumption Rbg = 1. The resulting uncertainty in the measured cross section is less than 2.5% and typically less than 1%. The background contribution from electrons or positrons misidentified as photons is sub-percent and a systematic uncertainty is included by assigning the full size of this background; as an example, the background from W (Z) decays is 0.22% (0.07%) for |η γ | < 0.6. Photon identification and isolation. The uncertainties in the efficiency scale factors, which are applied to simulated events to match the tight photon identification efficiency measured in data [46], are propagated to the measured cross section. The resulting uncer- tainty in the measured cross section is in the range 1%–3%. The uncertainties in the cross section due to the modelling of ET iso in simulated events are evaluated by comparing the nominal results with those obtained using MC samples of events in which the data-driven correction to ET iso is not applied (see section 4). The resulting uncertainty in the measured γ cross section is less than 2% except for ET > 500 GeV in the regions 0.6 < |η γ | < 1.37 and γ 1.56 < |η | < 1.81, where it increases to 3%. Model dependence of the unfolding. The nominal unfolding correction factors are computed using the Pythia simulation. As discussed in section 6, the effects on the unfold- ing correction factors due to the matrix elements and the parton shower and hadronisation models employed in the generators are investigated. The difference in the cross section between the nominal result and that obtained using the Sherpa simulation for the de- termination of the unfolding correction factors is taken as a systematic uncertainty. The uncertainties in the measured cross section are less than 2% and typically less than 1%. The uncertainty in the cross section due to the statistical uncertainty of the MC samples is propagated into the measured cross section and typically amounts to less than 0.5%. Pile-up. A variation in the pile-up reweighting of simulated events is included to cover the uncertainty in the ratio of the predicted to measured inelastic cross sections [56]. The resulting uncertainty in the measured cross section is less than 1.5%. – 10 – Trigger efficiency. The uncertainty in the trigger efficiency is estimated using the same methodology as in ref. [25] and is propagated into the measured cross section. The uncer- tainty in the measured cross section is at most 0.4%. Luminosity measurement. The uncertainty in the integrated luminosity is 2.1%. It is γ fully correlated between all bins with ET > 150 GeV of the cross section. For the bin with γ 125 < ET < 150 GeV only data from the 2015 running period is used and the uncertainty in the luminosity measurement is not fully correlated with the uncertainty in the combined integrated luminosity corresponding to the 2015 and 2016 running periods. However, the impact of the uncorrelated part can be safely neglected. JHEP10(2019)203 Photon energy scale and resolution. A detailed analysis of the sources of uncertainty in the energy scale and resolution for photons was made with Run 1 data [52]. The same model is implemented and updated for Run 2 data [53]. The sources of uncertainty include: the uncertainty in the overall energy scale adjustment using Z → e+ e− decays; the uncer- tainty in the non-linearity of the energy measurement at the cell level; the uncertainty in the relative calibration of the different calorimeter layers; the uncertainty in the amount of material in front of the calorimeter; the uncertainty in the modelling of the reconstruction of photon conversions; the uncertainty in the modelling of the lateral shower shape; the uncertainty in the modelling of the sampling term;5 the uncertainty in the measurement of the constant term in Z-boson decays. The sources of uncertainty are modelled using independent components to account for their η dependence. A total of 76 individual com- ponents influencing the energy scale and resolution of the photon are identified to assess the overall uncertainty in the energy measurement. All the uncertainty components are propagated separately through the analysis to keep track of the information about the correlations between different bins. The systematic uncertainty in the measured cross sec- tion is evaluated by varying each individual source of uncertainty separately by ±1σ in the MC simulations and then adding the uncertainty contributions in quadrature. The resulting uncertainties in the measured cross section are typically less than 0.5% for the energy resolution and in the range 1%–16% for the energy scale. Total systematic uncertainty. The total experimental systematic uncertainty is cal- culated by adding in quadrature the uncertainties listed above. The total systematic un- γ certainty is in the range 3%–17%, depending on ET and the |η γ | region. The dominant sources of uncertainty arise from the photon energy scale, the photon identification ef- ficiency and the integrated luminosity. Figure 1 shows the total systematic uncertainty for each measured cross section together with the dominant components. The systematic γ uncertainty dominates the total experimental uncertainty for ET . 1 TeV and |η γ | < 1.37, γ whereas for higher ET values, the statistical uncertainty of the data limits the precision of the measurement, as can be seen in figure 2. This represents an improvement relative to the previous measurement [5], where the region dominated by the systematic uncertainties γ was ET . 600 GeV. 5 √ The relative energy resolution is parameterised as σ(E)/E = a/ E ⊕ b/E ⊕ c, where a is the sampling term, b is the noise term and c is the constant term. – 11 – 0.2 0.2 Relative uncertainty Relative uncertainty ATLAS ATLAS s = 13 TeV, 36.1 fb-1 s = 13 TeV, 36.1 fb-1 γ γ 0.1 |η | < 0.6 0.1 0.6 < |η | < 1.37 0 0 −0.1 Total systematic −0.1 Total systematic Photon energy scale Photon energy scale JHEP10(2019)203 Photon identification Photon identification bg bg R correlation R correlation −0.2 −0.2 200 300 1000 2000 200 300 1000 2000 γ γ ET [GeV] ET [GeV] 0.2 0.2 Relative uncertainty Relative uncertainty ATLAS ATLAS s = 13 TeV, 36.1 fb-1 s = 13 TeV, 36.1 fb-1 γ γ 0.1 1.56 < |η | < 1.81 0.1 1.81 < |η | < 2.37 0 0 −0.1 Total systematic −0.1 Total systematic Photon energy scale Photon energy scale Photon identification Photon identification bg bg R correlation R correlation −0.2 −0.2 200 300 1000 200 300 400 1000 γ γ ET [GeV] ET [GeV] Figure 1. The relative total systematic uncertainty in the cross section (white areas) as a function γ of ET in different |η γ | regions. The relative uncertainty due to the photon energy scale (grey areas), the relative uncertainty due to the photon identification efficiency (green areas) and the relative uncertainty due to Rbg (blue hatched areas) are also shown. 8 Theoretical predictions The NLO pQCD predictions are computed using two programs, namely Jetphox 1.3.1 2 and Sherpa 2.2.2. The Jetphox program provides NLO QCD calculations of the di- rect and fragmentation contributions to the prompt-photon cross section. The number of massless quark flavours is set to five. The renormalisation (µR ), factorisation (µF ) and γ fragmentation (µf ) scales are chosen to be µR = µF = µf = ET . Variations of these scales are considered to get an estimate of the uncertainties due to missing higher-order terms in the perturbative expansion (see section 8.1). The nominal prediction is obtained us- ing the MMHT2014 [57] PDF set and the BFG set II of parton-to-photon fragmentation functions [58], both of which are determined at NLO. The strong coupling constant is – 12 – 0.6 0.6 Relative uncertainty Relative uncertainty ATLAS ATLAS s = 13 TeV, 36.1 fb-1 s = 13 TeV, 36.1 fb-1 0.4 0.4 γ γ |η | < 0.6 0.6 < |η | < 1.37 0.2 0.2 0 0 −0.2 −0.2 Total systematic Total systematic −0.4 Statistical −0.4 Statistical JHEP10(2019)203 −0.6 −0.6 200 300 1000 2000 200 300 1000 2000 γ γ ET [GeV] ET [GeV] 0.6 0.6 Relative uncertainty Relative uncertainty ATLAS ATLAS s = 13 TeV, 36.1 fb-1 s = 13 TeV, 36.1 fb-1 0.4 0.4 γ γ 1.56 < |η | < 1.81 1.81 < |η | < 2.37 0.2 0.2 0 0 −0.2 −0.2 Total systematic Total systematic −0.4 Statistical −0.4 Statistical −0.6 −0.6 200 300 1000 200 300 400 1000 γ γ ET [GeV] ET [GeV] Figure 2. The relative total systematic uncertainty in the cross section (white areas) as a function γ of ET in different |η γ | regions. The relative statistical uncertainty from the data is also shown (cyan areas). set to αs (mZ ) = 0.120 since it is the value assumed in the MMHT2014 PDF fit. For the electromagnetic coupling (αem ), the low-energy limit of 1/137.036 is used. A parton-level isolation criterion is used which requires the total transverse energy from the partons inside a cone of size ∆R = 0.4 around the photon direction to be below the same ET,cut iso applied at particle and detector level; this isolation prescription is referred to as ‘fixed-cone isolation’. Predictions based on other PDF sets, namely CT14 [59], ABMP16 [60], HERAPDF2.0 [61] and NNPDF3.0 [43], are also compared with the data; in each case αs (mZ ) is set to the value assumed in the PDF fit. The Sherpa 2.2.2 program consistently combines parton-level calculations of γ + (1, 2)-jet events at NLO in pQCD and γ+(3, 4)-jet events at LO [39, 40] supplemented with a parton shower [41] while avoiding double-counting effects [42]. The sample of events gen- – 13 – erated with Sherpa 2.2.2 is different from the sample of events from Sherpa 2.1.1 described in section 3. The former includes the higher-order virtual corrections for γ + (1, 2)-jet and is not passed through the ATLAS detector simulation programs since the goal is to com- pare the Sherpa 2.2.2 prediction with the measured cross section. Photon isolation at the matrix-element level is applied by using Frixione’s criterion with R = 0.1, n = 2 and  = 0.1 (see section 3). The parameters are chosen to be as loose as possible to minimise a bias from the application of the photon isolation requirement at particle level. Since Frix- ione’s criterion requires the upper limit on the transverse energy isolation to be exactly zero at r = 0, the criterion cannot be strictly looser than any non-zero photon isolation requirement at detector or particle level for all r < R. The photon isolation requirement is JHEP10(2019)203 applied (see table 1) using the procedure described in section 6; the prescription employed is referred to as ‘hybrid-cone isolation’ [16, 62] since it includes the application of the Frix- ione’s criterion at a small value of ∆R (R = 0.1) and the fixed-cone isolation at ∆R = 0.4 used for the fiducial region of the measurement. Dynamic factorisation and renormalisation γ scales are adopted (ET ) as well as a dynamical merging scale with Q̄cut = 20 GeV [62]. The strong coupling constant is set to αs (mZ ) = 0.118. The same prescription for the elec- tromagnetic coupling as for the Jetphox prediction is used. Fragmentation into hadrons and simulation of the UE are performed using the same models as for the Sherpa samples of simulated events presented in section 3. The NNLO NNPDF3.0 PDF set is used in conjunction with the corresponding Sherpa tuning. The NNLO QCD prediction is calculated [16] in the Nnlojet framework. The NNLO corrections include three types of parton-level contributions, namely the two-loop correc- tions to photon-plus-one-parton production, the virtual corrections to photon-plus-two- parton production and the tree-level photon-plus-three-parton production. Only direct- photon processes are included; fragmentation processes are circumvented by the applica- tion of the Frixione’s criterion at small ∆R using the same parameter settings as for the Sherpa 2.2.2 prediction. The photon transverse energy is used as the baseline choice for the renormalisation and factorisation scales. The NNPDF3.1 PDF set [63] at NNLO is used. G The electromagnetic coupling is taken in the Gµ -scheme [64] as αemµ = 1/132.232. Photon isolation is implemented following the ‘hybrid-cone isolation’ prescription described above. For the Nnlojet prediction the fixed-cone isolation at ∆R = 0.4 is applied at the parton level using the same requirement as for the particle level. The prediction at NLO pQCD in the Nnlojet framework is also calculated to illustrate the improvements achieved by including the NNLO QCD corrections. The NLO QCD prediction of Nnlojet differs from that of Jetphox in the fragmentation contribution, the photon isolation prescription, the value of αem and the PDF set. There are several differences between the calculations using Jetphox, Sherpa 2.2.2 and Nnlojet: the calculations from Nnlojet include NNLO QCD corrections; the cal- culations using Sherpa 2.2.2 include higher-order contributions as well as parton showers; the application of the Frixione’s criterion (Sherpa 2.2.2 and Nnlojet) at matrix-element level allows the fragmentation contribution to be ignored; and the prediction for the cross section using Sherpa 2.2.2 is at particle level and include UE effects. A compilation of the major features of the three different approaches is shown in table 2. – 14 – Program Order in αs Fragmentation Parton Isolation αem Particle shower Level Jetphox NLO Yes No Fixed cone 1/137.036 No Sherpa 2.2.2 NLO for γ + (1, 2)-jet No Yes Hybrid cone 1/137.036 Yes LO for γ + (3, 4)-jet Nnlojet NNLO No No Hybrid cone 1/132.232 No Table 2. Major features of the three predictions used for inclusive isolated-photon production. Electroweak corrections are not included in the calculations of Jetphox, Sherpa 2.2.2 JHEP10(2019)203 or Nnlojet. As mentioned earlier, the corrections are likely to play an important role at the TeV scale. Electroweak Sudakov corrections for single photon production are avail- able [65]. However, these constitute only part of the full electroweak corrections since the real corrections are not included. The full electroweak corrections can differ significantly from the Sudakov corrections because the latter corrections and the real corrections par- tially cancel out when the presence of W or Z bosons in the final state is not vetoed. The measurement presented here does not preclude the presence of massive gauge bosons in addition to the high-transverse-momentum photon. 8.1 Theoretical uncertainties in the NLO QCD predictions The major source of uncertainty affecting the predictions is due to terms beyond NLO in QCD. In the case of Jetphox it is evaluated by repeating the calculations using values of µR , µF and µf scaled by the factors 0.5 and 2. The three scales are either varied si- multaneously or independently; in addition, configurations in which one scale is fixed and the other two are varied simultaneously are also considered. In all cases, the condition 0.5 ≤ µA /µB ≤ 2 is imposed, where A, B = R, F, f. The final uncertainty is taken as the largest deviation from the nominal value among the 14 possible variations; this is done separately for the positive and negative contributions, so the final uncertainty is not nec- essarily symmetric. In the case of Sherpa 2.2.2, which does not include the fragmentation contribution, µR and µF are varied as above and the largest deviation from the nominal prediction among the six possible variations is taken as the uncertainty. The resulting uncertainties in the prediction are 10%–15% (20%–30%) for Jetphox (Sherpa 2.2.2). The fact that the uncertainties are larger for Sherpa than for Jetphox is attributed to multi-jet configurations which are accounted for only in the case of Sherpa. The uncertainty in the prediction of Jetphox due to the uncertainty in the proton PDFs is estimated by repeating the calculations using the 50 sets from the MMHT2014 error analysis and applying the Hessian method [66]. In the case of Sherpa 2.2.2, it is estimated using the 100 replicas from the NNPDF3.0 analysis. The resulting uncertain- ties in the prediction is in the range 1%–6% for Jetphox and 1%–9% for Sherpa 2.2.2, γ depending on ET and the |η γ | region. The uncertainty in the prediction of Jetphox (Sherpa 2.2.2) due to the uncertainty in αs is evaluated by repeating the calculations using two additional sets of proton PDFs from the MMHT2014 (NNPDF3.0) analysis for which different values of αs at mZ are – 15 – assumed in the fits, namely 0.118 (0.117) and 0.122 (0.119); in this way, the correlation between αs and the PDFs is preserved. The uncertainties in Jetphox associated with αs are evaluated as the differences between the varied and the nominal cross sections scaled by a factor 1.5/2. This scaling factor accounts for the difference in αs (mZ ) between the nominal and the αs (mZ )-varied calculations (0.002) and the uncertainty in αs (mZ ) (0.0015) recommended by the authors of MMHT2014 [67]. The uncertainties in Sherpa 2.2.2 due to αs are evaluated as the differences between the varied and the nominal cross sections scaled by a factor 1.5 to match the prescription used for MMHT2014. The resulting uncertainties in the prediction of Jetphox (Sherpa 2.2.2) are less than 3% (6% except for the highest γ measured ET point in the region 1.81 < |η γ | < 2.37, where it increases to 12%). JHEP10(2019)203 Since the NLO pQCD prediction from Jetphox is at the parton level while the mea- surement is at the particle level, correction factors for the non-perturbative (NP) effects of hadronisation and the underlying event are needed for the former to match the data. However, the data are corrected for pile-up and UE effects and the distributions are un- folded to a phase-space definition in which the requirement on ET iso at particle level is applied after subtraction of the UE. Therefore, corrections for NP effects are expected to be close to unity. They are evaluated by computing the ratio of the particle-level cross section for a Pythia sample with UE effects to the parton-level cross section without UE effects. The resulting corrections are consistent with unity within ±1%. Thus, no cor- rection is applied to the NLO QCD prediction of Jetphox and an uncertainty of 1% is assigned. The Sherpa 2.2.2 prediction is based on particle-level observables after apply- ing the requirements listed in table 1 and, therefore, can be compared directly with the measurement. Although no tunes are available to assess the impact of hadronisation and UE in the Sherpa 2.2.2 prediction, it is expected that the associated uncertainty is of a similar size as that evaluated using Pythia and, therefore, can be neglected in comparison to the other uncertainties. The total theoretical uncertainty is obtained by adding in quadrature the individual uncertainties listed above (see figures 3 and 4). The dominant theoretical uncertainty for the prediction using Jetphox or Sherpa 2.2.2 is that arising from the variation of the scales. The uncertainty arising from the PDFs (αs (mZ )) is the second dominant uncertainty for the prediction of Jetphox (Sherpa 2.2.2). A prediction from Jetphox using as scales γ µ R = µ F = µ f = ET /2 is also made and the associated theoretical uncertainties are calculated using the same procedure as above, including variations of the scales by the γ factors 0.5 and 2 with respect to ET /2. 8.2 Theoretical uncertainties in the NNLO QCD prediction The uncertainty in the NNLO QCD prediction due to higher-order terms is evaluated by varying the renormalisation and factorisation scales as is done for the Sherpa 2.2.2 prediction (see section 8.1). The resulting uncertainties are compared with those of the NLO QCD prediction from Nnlojet in figure 5. The uncertainties in the NNLO QCD prediction arising from the scale variations are in the range 0.6%–5% and are smaller than γ those in the NLO QCD prediction by a factor in the range 2–20, depending on ET and η γ . The uncertainties due to the PDFs and αs are not available, but they are expected to be – 16 – 0.4 0.4 Relative uncertainty Relative uncertainty s = 13 TeV s = 13 TeV γ γ |η | < 0.6 0.6 < |η | < 1.37 0.2 0.2 0 0 −0.2 Total uncertainty (JETPHOX) −0.2 Total uncertainty (JETPHOX) Scale variations Scale variations JHEP10(2019)203 PDF uncertainty PDF uncertainty αS uncertainty αS uncertainty −0.4 −0.4 200 300 1000 2000 200 300 1000 2000 γ γ ET [GeV] ET [GeV] 0.4 0.4 Relative uncertainty s = 13 TeV Relative uncertainty s = 13 TeV γ γ 1.56 < |η | < 1.81 1.81 < |η | < 2.37 0.2 0.2 0 0 −0.2 Total uncertainty (JETPHOX) −0.2 Total uncertainty (JETPHOX) Scale variations Scale variations PDF uncertainty PDF uncertainty αS uncertainty αS uncertainty −0.4 −0.4 200 300 1000 200 300 400 1000 γ γ ET [GeV] ET [GeV] Figure 3. The relative total theoretical uncertainty in the cross-section prediction of Jetphox γ as a function of ET in different regions of |η γ |. The uncertainty from the scale variations, the uncertainty from the PDFs and the uncertainty from the value of αs are also included. similar to, or smaller than, those affecting the Jetphox prediction. For the comparison with the data in section 9, the ‘total’ uncertainty associated with the Nnlojet prediction is taken as the sum in quadrature of the scale uncertainties, the statistical uncertainties of the calculations, the uncertainty of 1% assigned to the non-perturbative corrections (see section 8.1) and, as an approximation, the uncertainties due to the PDFs and αs as estimated from Jetphox at NLO. – 17 – 0.4 0.4 Relative uncertainty Relative uncertainty ATLAS Simulation ATLAS Simulation s = 13 TeV s = 13 TeV γ γ |η | < 0.6 0.6 < |η | < 1.37 JHEP10(2019)203 0.2 0.2 0 0 −0.2 Total uncertainty (SHERPA) −0.2 Total uncertainty (SHERPA) Scale variations Scale variations PDF uncertainty PDF uncertainty αS uncertainty αS uncertainty −0.4 −0.4 200 300 1000 2000 200 300 1000 2000 γ γ ET [GeV] ET [GeV] 0.4 0.4 Relative uncertainty Relative uncertainty ATLAS Simulation ATLAS Simulation s = 13 TeV s = 13 TeV γ γ 1.56 < |η | < 1.81 1.81 < |η | < 2.37 0.2 0.2 0 0 −0.2 Total uncertainty (SHERPA) −0.2 Total uncertainty (SHERPA) Scale variations Scale variations PDF uncertainty PDF uncertainty αS uncertainty αS uncertainty −0.4 −0.4 200 300 1000 200 300 400 1000 γ γ ET [GeV] ET [GeV] Figure 4. The relative total theoretical uncertainty in the cross-section prediction of Sherpa 2.2.2 γ as a function of ET in different regions of |η γ |. The uncertainty from the scale variations, the uncertainty from the PDFs and the uncertainty from the value of αs are also included. – 18 – 0.4 0.4 Relative uncertainty Relative uncertainty s = 13 TeV s = 13 TeV γ γ |η | < 0.6 0.6 < |η | < 1.37 JHEP10(2019)203 0.2 0.2 0 0 −0.2 −0.2 NLO scale uncertainty (NNLOJET) NLO scale uncertainty (NNLOJET) NNLO scale uncertainty (NNLOJET) NNLO scale uncertainty (NNLOJET) X. Chen et al., arXiv:1904.01044 X. Chen et al., arXiv:1904.01044 −0.4 −0.4 200 300 1000 2000 200 300 1000 2000 γ γ ET [GeV] ET [GeV] 0.4 0.4 Relative uncertainty Relative uncertainty s = 13 TeV s = 13 TeV γ γ 1.56 < |η | < 1.81 1.81 < |η | < 2.37 0.2 0.2 0 0 −0.2 −0.2 NLO scale uncertainty (NNLOJET) NLO scale uncertainty (NNLOJET) NNLO scale uncertainty (NNLOJET) NNLO scale uncertainty (NNLOJET) X. Chen et al., arXiv:1904.01044 X. Chen et al., arXiv:1904.01044 −0.4 −0.4 200 300 1000 200 300 400 1000 γ γ ET [GeV] ET [GeV] Figure 5. The relative theoretical uncertainty in the cross-section prediction of Nnlojet arising γ from the scale variations as a function of ET in different regions of |η γ |: for NLO and NNLO QCD predictions. – 19 – 9 Results The measurement of the inclusive isolated-photon differential cross section as a function γ of ET in different regions of |η γ | is shown in figure 6. In the region |η γ | < 0.6 (0.6 < |η γ | < 1.37) the cross section decreases by seven orders of magnitude in the measured γ γ range 125 < ET < 2500 GeV (125 < ET < 2000 GeV). In the forward regions 1.56 < γ γ γ |η | < 1.81 and 1.81 < |η | < 2.37, the measured ranges are 125 < ET < 1500 GeV and γ 125 < ET < 1100 GeV, respectively, and the cross section spans approximately six orders of magnitude. Figure 7 shows the inclusive isolated-photon double-differential cross section JHEP10(2019)203 2 γ γ γ d σ/d|η γ |dET as a function of |η γ | in different regions of ET . At high ET , the decrease of γ the double-differential cross section with increasing |η | is more prominent. Whereas the measured double-differential cross section decreases by 12% from the most central point γ to the most forward point for the lowest ET range, the decrease is 98% for the highest γ ET range. The NLO QCD prediction of Jetphox is compared with the measurement in figures 6 and 7. The NLO QCD prediction from Sherpa 2.2.2 is also reported in figures 6 and 7 and is denoted by ‘ME+PS@NLO QCD’ to highlight the differences relative to the predictions from Jetphox discussed in section 8. The nominal prediction of Sherpa 2.2.2 is above that of Jetphox; this is attributed to the fact that the former includes contributions from parton showers, virtual corrections for γ + 2-jet and higher-order tree-level matrix elements for the processes 2 → n with n = 4 and 5, which are not present in the prediction of Jetphox. Both types of predictions adequately reproduce the dependence of the single- γ and double-differential cross section on ET and |η γ | as observed in the data. Although the predictions are overall consistent with the measurement within the un- certainties, a detailed comparison is presented in terms of the ratios of theory predictions γ to data. The ratios of the predictions of Jetphox with µR = µF = µf = ET using different γ PDF sets to the measured cross section as a function of ET are shown in figures 8 and 9; the full theoretical uncertainty, including the variations of the scales, is shown for the predic- tion based on the MMHT2014 PDF set. The predictions based on the MMHT2014, CT14 and NNPDF3.0 PDF sets are similar and closest to the data for |η γ | < 1.37 for most of γ the range in ET . For 1.56 < |η γ | < 2.37, the prediction based on the HERAPDF2.0 PDF set is closest to the data. The prediction based on the ABMP16 PDF set is further away γ from the data than that based on the MMHT2014 PDF set for ET . 1 TeV in the region γ γ |η | < 1.37. The prediction of Jetphox with µR = µF = µf = ET exhibits a tendency to γ underestimate the data over most of the measured range in ET . However, the prediction γ of Jetphox with a different choice for the scales, namely µR = µF = µf = ET /2, provides an improved description of the normalisation of the data, as can be seen in figure 10; the γ full theoretical uncertainty, including the variations of the scales with respect to ET /2, is shown for the prediction based on the MMHT2014 PDF set. The ratio of the prediction of γ Sherpa 2.2.2 to the measured cross section as a function of ET is also shown in figure 10. Good agreement is observed between this prediction and the data distribution. In general, the NLO pQCD predictions are consistent with the measurement within the experimental and theoretical uncertainties. – 20 – dσ/dET [pb/GeV] 102 ATLAS Data: -1 γ 0 s = 13 TeV, 36.1 fb |η | < 0.6 (x10 ) 10 0.6 < |η | < 1.37 (x10-1) γ 1 1.56 < |η | < 1.81 (x10-2) γ γ -3 1.81 < |η | < 2.37 (x10 ) 10−1 γ 10−2 JHEP10(2019)203 10−3 10−4 10−5 10−6 NNLOJET −7 (NNLO QCD, NNPDF3.1) 10 (PDF and α s unc. from NLO JETPHOX) 10−8 SHERPA (ME+PS@NLO QCD, NNPDF3.0) −9 10 JETPHOX (NLO QCD, MMHT2014) −10 10 200 300 1000 γ 2000 ET [GeV] Figure 6. The measured differential cross section for isolated-photon production as a function γ of ET in |η γ | < 0.6 (black dots), 0.6 < |η γ | < 1.37 (open circles), 1.56 < |η γ | < 1.81 (black squares) and 1.81 < |η γ | < 2.37 (open squares). The NLO pQCD prediction from Jetphox, the ME+PS@NLO QCD prediction from Sherpa 2.2.2 and the NNLO QCD prediction from Nnlo- jet are also shown. The measurement and the predictions are normalised by the factors shown in parentheses to aid visibility. The error bars represent the data statistical uncertainties and system- atic uncertainties added in quadrature. For most of the points, the error bars are smaller than the marker size and, thus, not visible. The bands represent the theoretical uncertainty associated with the predictions; in the case of Nnlojet, the uncertainties due to the PDFs and αs are estimated at NLO with Jetphox. The NNLO QCD prediction from Nnlojet, which represent a significant step forward in precision, is compared with the data in figures 6, 7, 11 and 12. The inclusion of the NNLO QCD corrections increases the normalisation of the prediction and significantly reduces the uncertainties due to the scale variations, which are dominant for NLO QCD calculations. With the described choice of the input parameters, the NNLO QCD prediction provides an excellent description of the data except in the region 1.56 < |η γ | < 1.81, where there is a tendency in the theory to underestimate the data. The improvements in the description of the data by the NNLO QCD prediction relative to that of NLO QCD are shown in figures 11 and 12. – 21 – d2σ/d|η | dE [pb/GeV] ATLAS Data: 103 s = 13 TeV, 36.1 fb-1 γ 125 < ET < 150 GeV γ JHEP10(2019)203 300 < ET < 350 GeV 102 γ 550 < ET < 650 GeV γ 10 900 < ET < 1100 GeV T γ 1 γ 10−1 10−2 10−3 10−4 NNLOJET (NNLO QCD, NNPDF3.1) 10−5 (PDF and α s unc. from NLO JETPHOX) SHERPA (ME+PS@NLO QCD, NNPDF3.0) JETPHOX (NLO QCD, MMHT2014) 10−6 0 0.5 1 1.5 2 |ηγ | Figure 7. The measured double-differential cross section for isolated-photon production as a γ γ function of |η γ | in 125 < ET < 150 GeV (black dots), 300 < ET < 350 GeV (open circles), γ γ 550 < ET < 650 GeV (black squares) and 900 < ET < 1100 GeV (open squares). The NLO pQCD prediction from Jetphox, the ME+PS@NLO QCD prediction from Sherpa 2.2.2 and the NNLO QCD prediction from Nnlojet are also shown. The error bars represent the data statistical uncertainties and systematic uncertainties added in quadrature. For most of the points, the error bars are smaller than the marker size and, thus, not visible. The bands represent the theoretical uncertainty associated with the predictions; in the case of Nnlojet, the uncertainties due to the PDFs and αs are estimated at NLO with Jetphox. – 22 – Theory/Data ATLAS 1.4 s = 13 TeV, 36.1 fb-1 γ Data |η | < 0.6 1.2 JHEP10(2019)203 1 0.8 γ JETPHOX (NLO QCD; µ = E ): T MMHT2014 0.6 Data CT14 γ NNPDF3.0 0.6 < |η | < 1.37 0.4 Theory/Data 1.4 1.2 1 0.8 0.6 Data Data γ γ 1.56 < |η | < 1.81 1.81 < |η | < 2.37 0.4 200 300 1000 2000 200 300 1000 2000 γ γ ET [GeV] ET [GeV] γ Figure 8. The ratio of the NLO pQCD prediction of Jetphox with µR = µF = µf = ET using the MMHT2014 PDF set to the measured differential cross section for isolated-photon production (solid γ lines) as a function of ET in different regions of |η γ |. The symbols for the data are centred at unity and the inner (outer) error bars represent the relative data statistical uncertainties (statistical and systematic uncertainties added in quadrature). The hatched bands represent the full theoretical uncertainty associated to the prediction based on the MMHT2014 PDF set, including the variations of the scales. For comparison, the predictions using the CT14 (dashed lines) and NNPDF3.0 (dotted lines) PDF sets are also included. – 23 – Theory/Data ATLAS 1.4 s = 13 TeV, 36.1 fb-1 γ Data |η | < 0.6 1.2 JHEP10(2019)203 1 0.8 γ JETPHOX (NLO QCD; µ = E ): T MMHT2014 0.6 Data HERAPDF2.0 γ ABMP16 0.6 < |η | < 1.37 0.4 Theory/Data 1.4 1.2 1 0.8 0.6 Data Data γ γ 1.56 < |η | < 1.81 1.81 < |η | < 2.37 0.4 200 300 1000 2000 200 300 1000 2000 γ γ ET [GeV] ET [GeV] γ Figure 9. The ratio of the NLO pQCD prediction of Jetphox with µR = µF = µf = ET using the MMHT2014 PDF set to the measured differential cross section for isolated-photon production (solid γ lines) as a function of ET in different regions of |η γ |. The symbols for the data are centred at unity and the inner (outer) error bars represent the relative data statistical uncertainties (statistical and systematic uncertainties added in quadrature). The hatched bands represent the full theoretical uncertainty associated to the prediction based on the MMHT2014 PDF set, including the variations of the scales. For comparison, the predictions using the HERAPDF2.0 (dashed lines) and ABMP16 (dotted lines) PDF sets are also included. – 24 – Theory/Data ATLAS 1.4 s = 13 TeV, 36.1 fb-1 γ Data |η | < 0.6 1.2 JHEP10(2019)203 1 0.8 γ JETPHOX (NLO QCD; µ = ET): MMHT2014 γ 0.6 JETPHOX (NLO QCD; µ = ET/2): MMHT2014 Data γ SHERPA (ME+PS@NLO QCD): 0.6 < |η | < 1.37 NNPDF3.0 0.4 Theory/Data 1.4 1.2 1 0.8 0.6 Data Data γ γ 1.56 < |η | < 1.81 1.81 < |η | < 2.37 0.4 200 300 1000 2000 200 300 1000 2000 γ γ ET [GeV] ET [GeV] γ Figure 10. The ratio of the NLO pQCD prediction of Jetphox with µR = µF = µf = ET , the γ ratio of the NLO pQCD prediction of Jetphox with µR = µF = µf = ET /2 and the ratio of the ME+PS@NLO QCD prediction of Sherpa 2.2.2 to the measured differential cross section for γ isolated-photon production as a function of ET in different regions of |η γ |. The symbols for the data are centred at unity and the inner (outer) error bars represent the relative data statistical uncertainties (statistical and systematic uncertainties added in quadrature). The bands represent the full theoretical uncertainty, which includes the variations of the scales. – 25 – Theory/Data ATLAS 1.4 s = 13 TeV, 36.1 fb-1 γ Data |η | < 0.6 1.2 JHEP10(2019)203 1 0.8 NNLOJET: (PDF and α s unc. from NLO JETPHOX) 0.6 Data NLO QCD (NNPDF3.1) γ NNLO QCD (NNPDF3.1) 0.6 < |η | < 1.37 0.4 Theory/Data 1.4 1.2 1 0.8 0.6 Data Data γ γ 1.56 < |η | < 1.81 1.81 < |η | < 2.37 0.4 200 300 1000 2000 200 300 1000 2000 γ γ ET [GeV] ET [GeV] Figure 11. The ratio of the NNLO (NLO) QCD prediction of Nnlojet using the NNPDF3.1 PDF set to the measured differential cross section for isolated-photon production as a function of γ ET in different regions of |η γ | is shown as a solid (dashed) line. The symbols for the data are centred at unity and the inner (outer) error bars represent the relative data statistical uncertainties (statistical and systematic uncertainties added in quadrature). The shaded bands represent the theoretical uncertainties, which include those due to the PDFs and αs as estimated at NLO with Jetphox. – 26 – Theory/Data ATLAS 1.4 s = 13 TeV, 36.1 fb-1 γ Data |η | < 0.6 1.2 JHEP10(2019)203 1 0.8 NNLOJET (NNLO QCD): NNPDF3.1 (PDF and αs unc. from NLO JETPHOX) 0.6 SHERPA (ME+PS@NLO QCD): NNPDF3.0 Data γ γ JETPHOX (NLO QCD; µ = ET): 0.6 < |η | < 1.37 MMHT2014 0.4 Theory/Data 1.4 1.2 1 0.8 0.6 Data Data γ γ 1.56 < |η | < 1.81 1.81 < |η | < 2.37 0.4 200 300 1000 2000 200 300 1000 2000 γ γ ET [GeV] ET [GeV] γ Figure 12. The ratio of the NLO pQCD prediction of Jetphox with µR = µF = µf = ET , the ratio of the ME+PS@NLO QCD prediction of Sherpa 2.2.2 and the ratio of the NNLO QCD prediction of Nnlojet to the measured differential cross section for isolated-photon production γ as a function of ET in different regions of |η γ |. The symbols for the data are centred at unity and the inner (outer) error bars represent the relative data statistical uncertainties (statistical and systematic uncertainties added in quadrature). The bands represent the theoretical uncertainty; in the case of Nnlojet, the uncertainties due to the PDFs and αs are estimated at NLO with Jetphox. – 27 – 10 Summary and conclusions √ The cross section for inclusive isolated-photon production in pp collisions at s = 13 TeV is measured using data with an integrated luminosity of 36.1 fb−1 collected by the ATLAS γ detector at the LHC. The differential cross section as a function of ET is measured in γ γ γ different regions of |η | for photons with ET > 125 GeV and |η | < 2.37, excluding the region 1.37 < |η γ | < 1.56. The measurement presented here constitutes an improvement in terms of statistical and systematic uncertainties relative to that published earlier thanks to the ten-fold increase in γ the integrated luminosity. In the new measurement, the reach in ET is extended upwards JHEP10(2019)203 by 1000, 500, 400 and 200 GeV for |η | < 0.6, 0.6 < |η | < 1.37, 1.56 < |η γ | < 1.81 and γ γ √ 1.81 < |η γ | < 2.37, respectively, relative to the previous measurement at s = 13 TeV. The range in which the measurement is limited by systematic uncertainties is extended upwards to 1 TeV for |η γ | < 1.37, where previously the limitation was at 600 GeV. Next-to-leading-order QCD predictions using several PDF sets are compared with the measurement and found to provide an adequate description of the data within the exper- imental and theoretical uncertainties. The comparison of data and theory is limited by the theoretical uncertainties due to terms beyond NLO in QCD. Experimental systematic uncertainties are smaller than the theoretical uncertainties over the full investigated phase space. The inclusion of higher-order matrix elements and parton showers, as provided by the Sherpa 2.2.2 program, improves the description of the normalisation of the data by the prediction. Recently, a next-to-next-to-leading-order QCD prediction was calculated in which the uncertainties due to the scale variations are reduced by a factor in the range 2–20 relative to those of a NLO QCD calculation. Overall, the NNLO QCD prediction gives an excellent description of the data. The comparison of the NNLO QCD prediction with the measured cross section represents a precise test of the theory at O(αem αs3 ) in the range of photon transverse energies from 125 GeV up to and beyond 1 TeV. The measurement has the potential to further constrain the PDFs, particularly the gluon density in the proton, within a global NNLO QCD fit. Acknowledgments We thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Aus- tralia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, – 28 – 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; Investissements d’ Avenir Labex and Idex, ANR, France; DFG and AvH Foundation, Ger- many; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and GIF, Israel; CERCA Programme Generalitat de Catalunya, JHEP10(2019)203 Spain; The Royal Society and Leverhulme Trust, United Kingdom. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (U.K.) and BNL (U.S.A.), the Tier-2 facilities worldwide and large non-WLCG resource providers. Ma- jor contributors of computing resources are listed in ref. [68]. 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Cranmer124 , S.J. Crawley57 , R.A. Creager137 , S. Crépé-Renaudin58 , F. Crescioli136 , M. Cristinziani24 , V. Croft120 , G. Crosetti41b,41a , A. Cueto5 , T. Cuhadar Donszelmann149 , A.R. Cukierman153 , S. Czekierda84 , P. Czodrowski36 , M.J. Da Cunha Sargedas De Sousa60b , J.V. Da Fonseca Pinto80b , C. Da Via100 , W. Dabrowski83a , T. Dado28a , S. Dahbi35e , T. Dai105 , C. Dallapiccola102 , M. Dam40 , G. D’amen23b,23a , V. D’Amico74a,74b , J. Damp99 , J.R. Dandoy137 , M.F. Daneri30 , N.P. Dang181,k , N.S. Dann100 , M. Danninger175 , V. Dao36 , G. Darbo55b , O. Dartsi5 , A. Dattagupta131 , T. Daubney46 , JHEP10(2019)203 S. D’Auria68a,68b , W. Davey24 , C. David46 , T. Davidek143 , D.R. Davis49 , I. Dawson149 , K. De8 , R. De Asmundis69a , M. De Beurs120 , S. De Castro23b,23a , S. De Cecco72a,72b , N. De Groot119 , P. de Jong120 , H. De la Torre106 , A. De Maria15c , D. De Pedis72a , A. De Salvo72a , U. De Sanctis73a,73b , M. De Santis73a,73b , A. De Santo156 , K. 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Hellman45a,45b , C. Helsens36 , R.C.W. Henderson89 , Y. Heng181 , S. Henkelmann175 , A.M. Henriques Correia36 , G.H. Herbert19 , H. Herde26 , V. Herget177 , Y. Hernández Jiménez33c , H. Herr99 , M.G. Herrmann114 , T. Herrmann48 , G. Herten52 , R. Hertenberger114 , L. Hervas36 , T.C. Herwig137 , G.G. Hesketh94 , N.P. Hessey168a , A. Higashida163 , S. Higashino81 , E. Higón-Rodriguez174 , K. Hildebrand37 , E. Hill176 , J.C. Hill32 , K.K. Hill29 , K.H. Hiller46 , S.J. Hillier21 , M. Hils48 , I. Hinchliffe18 , F. Hinterkeuser24 , M. Hirose133 , S. Hirose52 , D. Hirschbuehl182 , B. Hiti91 , O. Hladik141 , D.R. Hlaluku33c , X. Hoad50 , J. Hobbs155 , N. Hod180 , M.C. Hodgkinson149 , A. Hoecker36 , F. Hoenig114 , D. Hohn52 , D. Hohov132 , T.R. Holmes37 , M. Holzbock114 , L.B.A.H Hommels32 , S. Honda169 , T. Honda81 , T.M. Hong139 , A. Hönle115 , B.H. Hooberman173 , W.H. Hopkins6 , Y. Horii117 , P. Horn48 , L.A. Horyn37 , J-Y. Hostachy58 , A. Hostiuc148 , S. Hou158 , JHEP10(2019)203 A. Hoummada35a , J. Howarth100 , J. Hoya88 , M. Hrabovsky130 , J. Hrdinka76 , I. Hristova19 , J. Hrivnac132 , A. Hrynevich108 , T. Hryn’ova5 , P.J. Hsu64 , S.-C. Hsu148 , Q. Hu29 , S. Hu60c , Y. Huang15a , Z. Hubacek142 , F. Hubaut101 , M. Huebner24 , F. Huegging24 , T.B. Huffman135 , M. Huhtinen36 , R.F.H. Hunter34 , P. Huo155 , A.M. Hupe34 , N. Huseynov79,aj , J. Huston106 , J. Huth59 , R. Hyneman105 , S. Hyrych28a , G. Iacobucci54 , G. Iakovidis29 , I. Ibragimov151 , L. Iconomidou-Fayard132 , Z. Idrissi35e , P. Iengo36 , R. Ignazzi40 , O. Igonkina120,ad,∗ , R. Iguchi163 , T. Iizawa54 , Y. Ikegami81 , M. Ikeno81 , D. Iliadis162 , N. Ilic119 , F. Iltzsche48 , G. Introzzi70a,70b , M. Iodice74a , K. Iordanidou168a , V. Ippolito72a,72b , M.F. Isacson172 , M. Ishino163 , M. Ishitsuka165 , W. Islam129 , C. Issever135 , S. Istin160 , F. Ito169 , J.M. Iturbe Ponce63a , R. Iuppa75a,75b , A. Ivina180 , H. Iwasaki81 , J.M. Izen43 , V. Izzo69a , P. Jacka141 , P. Jackson1 , R.M. Jacobs24 , B.P. Jaeger152 , V. Jain2 , G. Jäkel182 , K.B. Jakobi99 , K. Jakobs52 , S. Jakobsen76 , T. Jakoubek141 , J. Jamieson57 , K.W. Janas83a , R. Jansky54 , J. Janssen24 , M. Janus53 , P.A. Janus83a , G. Jarlskog96 , N. Javadov79,aj , T. Javůrek36 , M. Javurkova52 , F. Jeanneau145 , L. Jeanty131 , J. Jejelava159a,ak , A. Jelinskas178 , P. Jenni52,c , J. Jeong46 , N. Jeong46 , S. Jézéquel5 , H. Ji181 , J. Jia155 , H. Jiang78 , Y. Jiang60a , Z. Jiang153,s , S. Jiggins52 , F.A. Jimenez Morales38 , J. Jimenez Pena174 , S. Jin15c , A. Jinaru27b , O. Jinnouchi165 , H. Jivan33c , P. Johansson149 , K.A. Johns7 , C.A. Johnson65 , K. Jon-And45a,45b , R.W.L. Jones89 , S.D. Jones156 , S. Jones7 , T.J. Jones90 , J. Jongmanns61a , P.M. Jorge140a , J. Jovicevic36 , X. Ju18 , J.J. Junggeburth115 , A. Juste Rozas14,ab , A. Kaczmarska84 , M. Kado72a,72b , H. Kagan126 , M. Kagan153 , C. Kahra99 , T. Kaji179 , E. Kajomovitz160 , C.W. Kalderon96 , A. Kaluza99 , A. Kamenshchikov123 , L. Kanjir91 , Y. Kano163 , V.A. Kantserov112 , J. Kanzaki81 , L.S. Kaplan181 , D. Kar33c , M.J. Kareem168b , E. Karentzos10 , S.N. Karpov79 , Z.M. Karpova79 , V. Kartvelishvili89 , A.N. Karyukhin123 , L. Kashif181 , R.D. Kass126 , A. Kastanas45a,45b , Y. Kataoka163 , C. Kato60d,60c , J. Katzy46 , K. Kawade82 , K. Kawagoe87 , T. Kawaguchi117 , T. Kawamoto163 , G. Kawamura53 , E.F. Kay176 , V.F. Kazanin122b,122a , R. Keeler176 , R. Kehoe42 , J.S. Keller34 , E. Kellermann96 , D. Kelsey156 , J.J. Kempster21 , J. Kendrick21 , O. Kepka141 , S. Kersten182 , B.P. Kerševan91 , S. Ketabchi Haghighat167 , M. Khader173 , F. Khalil-Zada13 , M. Khandoga145 , A. Khanov129 , A.G. Kharlamov122b,122a , T. Kharlamova122b,122a , E.E. Khoda175 , A. Khodinov166 , T.J. Khoo54 , E. Khramov79 , J. Khubua159b , S. Kido82 , M. Kiehn54 , C.R. Kilby93 , Y.K. Kim37 , N. Kimura66a,66c , O.M. Kind19 , B.T. King90,∗ , D. Kirchmeier48 , J. Kirk144 , A.E. Kiryunin115 , T. Kishimoto163 , D.P. Kisliuk167 , V. Kitali46 , O. Kivernyk5 , E. Kladiva28b,∗ , T. Klapdor-Kleingrothaus52 , M. Klassen61a , M.H. Klein105 , M. Klein90 , U. Klein90 , K. Kleinknecht99 , P. Klimek121 , A. Klimentov29 , T. Klingl24 , T. Klioutchnikova36 , F.F. Klitzner114 , P. Kluit120 , S. Kluth115 , E. Kneringer76 , E.B.F.G. Knoops101 , A. Knue52 , D. Kobayashi87 , T. Kobayashi163 , M. Kobel48 , M. Kocian153 , P. Kodys143 , P.T. Koenig24 , T. Koffas34 , N.M. Köhler115 , T. Koi153 , M. Kolb61b , I. Koletsou5 , T. Komarek130 , T. Kondo81 , N. Kondrashova60c , K. Köneke52 , A.C. König119 , T. Kono125 , R. Konoplich124,ar , – 38 – V. Konstantinides94 , N. Konstantinidis94 , B. Konya96 , R. Kopeliansky65 , S. Koperny83a , K. Korcyl84 , K. Kordas162 , G. Koren161 , A. Korn94 , I. Korolkov14 , E.V. Korolkova149 , N. Korotkova113 , O. Kortner115 , S. Kortner115 , T. Kosek143 , V.V. Kostyukhin24 , A. Kotwal49 , A. Koulouris10 , A. Kourkoumeli-Charalampidi70a,70b , C. Kourkoumelis9 , E. Kourlitis149 , V. Kouskoura29 , A.B. Kowalewska84 , R. Kowalewski176 , C. Kozakai163 , W. Kozanecki145 , A.S. Kozhin123 , V.A. Kramarenko113 , G. Kramberger91 , D. Krasnopevtsev60a , M.W. Krasny136 , A. Krasznahorkay36 , D. Krauss115 , J.A. Kremer83a , J. Kretzschmar90 , P. Krieger167 , F. Krieter114 , A. Krishnan61b , K. Krizka18 , K. Kroeninger47 , H. Kroha115 , J. Kroll141 , J. Kroll137 , J. Krstic16 , U. Kruchonak79 , H. Krüger24 , N. Krumnack78 , M.C. Kruse49 , J.A. Krzysiak84 , T. Kubota104 , O. Kuchinskaia166 , S. Kuday4b , J.T. Kuechler46 , S. Kuehn36 , A. Kugel61a , T. Kuhl46 , V. Kukhtin79 , R. Kukla101 , Y. Kulchitsky107,an , S. Kuleshov147b , Y.P. Kulinich173 , M. Kuna58 , JHEP10(2019)203 T. Kunigo85 , A. Kupco141 , T. Kupfer47 , O. Kuprash52 , H. Kurashige82 , L.L. Kurchaninov168a , Y.A. Kurochkin107 , A. Kurova112 , M.G. Kurth15a,15d , E.S. Kuwertz36 , M. Kuze165 , A.K. Kvam148 , J. Kvita130 , T. Kwan103 , A. La Rosa115 , L. La Rotonda41b,41a , F. La Ruffa41b,41a , C. Lacasta174 , F. Lacava72a,72b , D.P.J. Lack100 , H. Lacker19 , D. Lacour136 , E. Ladygin79 , R. Lafaye5 , B. Laforge136 , T. Lagouri33c , S. Lai53 , S. Lammers65 , W. Lampl7 , C. Lampoudis162 , E. Lançon29 , U. Landgraf52 , M.P.J. Landon92 , M.C. Lanfermann54 , V.S. Lang46 , J.C. Lange53 , R.J. Langenberg36 , A.J. Lankford171 , F. Lanni29 , K. Lantzsch24 , A. Lanza70a , A. Lapertosa55b,55a , S. Laplace136 , J.F. Laporte145 , T. Lari68a , F. Lasagni Manghi23b,23a , M. Lassnig36 , T.S. Lau63a , A. Laudrain132 , A. Laurier34 , M. Lavorgna69a,69b , M. Lazzaroni68a,68b , B. Le104 , E. Le Guirriec101 , M. LeBlanc7 , T. LeCompte6 , F. Ledroit-Guillon58 , C.A. Lee29 , G.R. Lee17 , L. Lee59 , S.C. Lee158 , S.J. Lee34 , B. Lefebvre168a , M. Lefebvre176 , F. Legger114 , C. Leggett18 , K. Lehmann152 , N. Lehmann182 , G. Lehmann Miotto36 , W.A. Leight46 , A. Leisos162,aa , M.A.L. Leite80d , C.E. Leitgeb114 , R. Leitner143 , D. Lellouch180,∗ , K.J.C. Leney42 , T. Lenz24 , B. Lenzi36 , R. Leone7 , S. Leone71a , C. Leonidopoulos50 , A. Leopold136 , G. Lerner156 , C. Leroy109 , R. Les167 , C.G. Lester32 , M. Levchenko138 , J. Levêque5 , D. Levin105 , L.J. Levinson180 , D.J. Lewis21 , B. Li15b , B. Li105 , C-Q. Li60a , F. Li60c , H. Li60a , H. Li60b , J. Li60c , K. Li153 , L. Li60c , M. Li15a , Q. Li15a,15d , Q.Y. Li60a , S. Li60d,60c , X. Li46 , Y. Li46 , Z. Li60b , Z. Liang15a , B. Liberti73a , A. Liblong167 , K. Lie63c , S. Liem120 , C.Y. Lin32 , K. Lin106 , T.H. Lin99 , R.A. Linck65 , J.H. Lindon21 , A.L. Lionti54 , E. Lipeles137 , A. Lipniacka17 , M. Lisovyi61b , T.M. Liss173,ay , A. Lister175 , A.M. Litke146 , J.D. Little8 , B. Liu78,ag , B.L Liu6 , H.B. Liu29 , H. Liu105 , J.B. Liu60a , J.K.K. Liu135 , K. Liu136 , M. Liu60a , P. Liu18 , Y. Liu15a,15d , Y.L. Liu105 , Y.W. Liu60a , M. Livan70a,70b , A. Lleres58 , J. Llorente Merino15a , S.L. Lloyd92 , C.Y. Lo63b , F. Lo Sterzo42 , E.M. Lobodzinska46 , P. Loch7 , S. Loffredo73a,73b , T. Lohse19 , K. Lohwasser149 , M. Lokajicek141 , J.D. Long173 , R.E. Long89 , L. Longo36 , K.A. Looper126 , J.A. Lopez147b , I. Lopez Paz100 , A. Lopez Solis149 , J. Lorenz114 , N. Lorenzo Martinez5 , M. Losada22 , P.J. Lösel114 , A. Lösle52 , X. Lou46 , X. Lou15a , A. Lounis132 , J. Love6 , P.A. Love89 , J.J. Lozano Bahilo174 , M. Lu60a , Y.J. Lu64 , H.J. Lubatti148 , C. Luci72a,72b , A. Lucotte58 , C. Luedtke52 , F. Luehring65 , I. Luise136 , L. Luminari72a , B. Lund-Jensen154 , M.S. Lutz102 , D. Lynn29 , R. Lysak141 , E. Lytken96 , F. Lyu15a , V. Lyubushkin79 , T. Lyubushkina79 , H. Ma29 , L.L. Ma60b , Y. Ma60b , G. Maccarrone51 , A. Macchiolo115 , C.M. Macdonald149 , J. Machado Miguens137 , D. Madaffari174 , R. Madar38 , W.F. Mader48 , N. Madysa48 , J. Maeda82 , K. Maekawa163 , S. Maeland17 , T. Maeno29 , M. Maerker48 , A.S. Maevskiy113 , V. Magerl52 , N. Magini78 , D.J. Mahon39 , C. Maidantchik80b , T. Maier114 , A. Maio140a,140b,140d , O. Majersky28a , S. Majewski131 , Y. Makida81 , N. Makovec132 , B. Malaescu136 , Pa. Malecki84 , V.P. Maleev138 , F. Malek58 , U. Mallik77 , D. Malon6 , C. Malone32 , S. Maltezos10 , S. Malyukov79 , J. Mamuzic174 , G. Mancini51 , I. Mandić91 , L. Manhaes de Andrade Filho80a , I.M. Maniatis162 , J. Manjarres Ramos48 , K.H. Mankinen96 , A. Mann114 , A. Manousos76 , B. Mansoulie145 , I. Manthos162 , S. Manzoni120 , A. Marantis162 , – 39 – G. Marceca30 , L. Marchese135 , G. Marchiori136 , M. Marcisovsky141 , C. Marcon96 , C.A. Marin Tobon36 , M. Marjanovic38 , Z. Marshall18 , M.U.F Martensson172 , S. Marti-Garcia174 , C.B. Martin126 , T.A. Martin178 , V.J. Martin50 , B. Martin dit Latour17 , L. Martinelli74a,74b , M. Martinez14,ab , V.I. Martinez Outschoorn102 , S. Martin-Haugh144 , V.S. Martoiu27b , A.C. Martyniuk94 , A. Marzin36 , S.R. Maschek115 , L. Masetti99 , T. Mashimo163 , R. Mashinistov110 , J. Masik100 , A.L. Maslennikov122b,122a , L.H. Mason104 , L. Massa73a,73b , P. Massarotti69a,69b , P. Mastrandrea71a,71b , A. Mastroberardino41b,41a , T. Masubuchi163 , A. Matic114 , P. Mättig24 , J. Maurer27b , B. Maček91 , D.A. Maximov122b,122a , R. Mazini158 , I. Maznas162 , S.M. Mazza146 , S.P. Mc Kee105 , T.G. McCarthy115 , L.I. McClymont94 , W.P. McCormack18 , E.F. McDonald104 , J.A. Mcfayden36 , M.A. McKay42 , K.D. McLean176 , S.J. McMahon144 , P.C. McNamara104 , C.J. McNicol178 , R.A. McPherson176,ah , J.E. Mdhluli33c , JHEP10(2019)203 Z.A. Meadows102 , S. Meehan148 , T. Megy52 , S. Mehlhase114 , A. Mehta90 , T. Meideck58 , B. Meirose43 , D. Melini174 , B.R. Mellado Garcia33c , J.D. Mellenthin53 , M. Melo28a , F. Meloni46 , A. Melzer24 , S.B. Menary100 , E.D. Mendes Gouveia140a,140e , L. Meng36 , X.T. Meng105 , S. Menke115 , E. Meoni41b,41a , S. Mergelmeyer19 , S.A.M. Merkt139 , C. Merlassino20 , P. Mermod54 , L. Merola69a,69b , C. Meroni68a , O. Meshkov113,110 , J.K.R. Meshreki151 , A. Messina72a,72b , J. Metcalfe6 , A.S. Mete171 , C. Meyer65 , J. Meyer160 , J-P. Meyer145 , H. Meyer Zu Theenhausen61a , F. Miano156 , M. Michetti19 , R.P. Middleton144 , L. Mijović50 , G. Mikenberg180 , M. Mikestikova141 , M. Mikuž91 , H. Mildner149 , M. Milesi104 , A. Milic167 , D.A. Millar92 , D.W. Miller37 , A. Milov180 , D.A. Milstead45a,45b , R.A. Mina153,s , A.A. Minaenko123 , M. Miñano Moya174 , I.A. Minashvili159b , A.I. Mincer124 , B. Mindur83a , M. Mineev79 , Y. Minegishi163 , Y. Ming181 , L.M. Mir14 , A. Mirto67a,67b , K.P. Mistry137 , T. Mitani179 , J. Mitrevski114 , V.A. Mitsou174 , M. Mittal60c , A. Miucci20 , P.S. Miyagawa149 , A. Mizukami81 , J.U. Mjörnmark96 , T. Mkrtchyan184 , M. Mlynarikova143 , T. Moa45a,45b , K. Mochizuki109 , P. Mogg52 , S. Mohapatra39 , R. Moles-Valls24 , M.C. Mondragon106 , K. Mönig46 , J. Monk40 , E. Monnier101 , A. Montalbano152 , J. Montejo Berlingen36 , M. Montella94 , F. Monticelli88 , S. Monzani68a , N. Morange132 , D. Moreno22 , M. Moreno Llácer36 , C. Moreno Martinez14 , P. Morettini55b , M. Morgenstern120 , S. Morgenstern48 , D. Mori152 , M. Morii59 , M. Morinaga179 , V. Morisbak134 , A.K. Morley36 , G. Mornacchi36 , A.P. Morris94 , L. Morvaj155 , P. Moschovakos36 , B. Moser120 , M. Mosidze159b , T. Moskalets145 , H.J. Moss149 , J. Moss31,p , K. Motohashi165 , E. Mountricha36 , E.J.W. Moyse102 , S. Muanza101 , J. Mueller139 , R.S.P. Mueller114 , D. Muenstermann89 , G.A. Mullier96 , J.L. Munoz Martinez14 , F.J. Munoz Sanchez100 , P. Murin28b , W.J. Murray178,144 , A. Murrone68a,68b , M. Muškinja18 , C. Mwewa33a , A.G. Myagkov123,as , J. Myers131 , M. Myska142 , B.P. Nachman18 , O. Nackenhorst47 , A.Nag Nag48 , K. Nagai135 , K. Nagano81 , Y. Nagasaka62 , M. Nagel52 , E. Nagy101 , A.M. Nairz36 , Y. Nakahama117 , K. Nakamura81 , T. Nakamura163 , I. Nakano127 , H. Nanjo133 , F. Napolitano61a , R.F. Naranjo Garcia46 , R. Narayan42 , D.I. Narrias Villar61a , I. Naryshkin138 , T. Naumann46 , G. Navarro22 , H.A. Neal105,∗ , P.Y. Nechaeva110 , F. Nechansky46 , T.J. Neep21 , A. Negri70a,70b , M. Negrini23b , C. Nellist53 , M.E. Nelson135 , S. Nemecek141 , P. Nemethy124 , M. Nessi36,e , M.S. Neubauer173 , M. Neumann182 , P.R. Newman21 , Y.S. Ng19 , Y.W.Y. Ng171 , H.D.N. Nguyen101 , T. Nguyen Manh109 , E. Nibigira38 , R.B. Nickerson135 , R. Nicolaidou145 , D.S. Nielsen40 , J. Nielsen146 , N. Nikiforou11 , V. Nikolaenko123,as , I. Nikolic-Audit136 , K. Nikolopoulos21 , P. Nilsson29 , H.R. Nindhito54 , Y. Ninomiya81 , A. Nisati72a , N. Nishu60c , R. Nisius115 , I. Nitsche47 , T. Nitta179 , T. Nobe163 , Y. Noguchi85 , I. Nomidis136 , M.A. Nomura29 , M. Nordberg36 , N. Norjoharuddeen135 , T. Novak91 , O. Novgorodova48 , R. Novotny142 , L. Nozka130 , K. Ntekas171 , E. Nurse94 , F.G. Oakham34,bb , H. Oberlack115 , J. Ocariz136 , A. Ochi82 , I. Ochoa39 , J.P. Ochoa-Ricoux147a , K. O’Connor26 , S. Oda87 , S. Odaka81 , S. Oerdek53 , A. Ogrodnik83a , A. Oh100 , S.H. Oh49 , C.C. Ohm154 , H. Oide55b,55a , M.L. Ojeda167 , H. Okawa169 , Y. Okazaki85 , Y. Okumura163 , T. Okuyama81 , – 40 – A. Olariu27b , L.F. Oleiro Seabra140a , S.A. Olivares Pino147a , D. Oliveira Damazio29 , J.L. Oliver1 , M.J.R. Olsson171 , A. Olszewski84 , J. Olszowska84 , D.C. O’Neil152 , A. Onofre140a,140e , K. Onogi117 , P.U.E. Onyisi11 , H. Oppen134 , M.J. Oreglia37 , G.E. Orellana88 , D. Orestano74a,74b , N. Orlando14 , R.S. Orr167 , V. O’Shea57 , R. Ospanov60a , G. Otero y Garzon30 , H. Otono87 , M. Ouchrif35d , J. Ouellette29 , F. Ould-Saada134 , A. Ouraou145 , Q. Ouyang15a , M. Owen57 , R.E. Owen21 , V.E. Ozcan12c , N. Ozturk8 , J. Pacalt130 , H.A. Pacey32 , K. Pachal49 , A. Pacheco Pages14 , C. Padilla Aranda14 , S. Pagan Griso18 , M. Paganini183 , G. Palacino65 , S. Palazzo50 , S. Palestini36 , M. Palka83b , D. Pallin38 , I. Panagoulias10 , C.E. Pandini36 , J.G. Panduro Vazquez93 , P. Pani46 , G. Panizzo66a,66c , L. Paolozzi54 , C. Papadatos109 , K. Papageorgiou9,i , A. Paramonov6 , D. Paredes Hernandez63b , S.R. Paredes Saenz135 , B. Parida166 , T.H. Park167 , A.J. Parker89 , M.A. Parker32 , F. Parodi55b,55a , E.W.P. Parrish121 , J.A. Parsons39 , U. Parzefall52 , JHEP10(2019)203 L. Pascual Dominguez136 , V.R. Pascuzzi167 , J.M.P. Pasner146 , E. Pasqualucci72a , S. Passaggio55b , F. Pastore93 , P. Pasuwan45a,45b , S. Pataraia99 , J.R. Pater100 , A. Pathak181 , T. Pauly36 , B. Pearson115 , M. Pedersen134 , L. Pedraza Diaz119 , R. Pedro140a , T. Peiffer53 , S.V. Peleganchuk122b,122a , O. Penc141 , H. Peng60a , B.S. Peralva80a , M.M. Perego132 , A.P. Pereira Peixoto140a , D.V. Perepelitsa29 , F. Peri19 , L. Perini68a,68b , H. Pernegger36 , S. Perrella69a,69b , K. Peters46 , R.F.Y. Peters100 , B.A. Petersen36 , T.C. Petersen40 , E. Petit101 , A. Petridis1 , C. Petridou162 , P. Petroff132 , M. Petrov135 , F. Petrucci74a,74b , M. Pettee183 , N.E. Pettersson102 , K. Petukhova143 , A. Peyaud145 , R. Pezoa147b , L. Pezzotti70a,70b , T. Pham104 , F.H. Phillips106 , P.W. Phillips144 , M.W. Phipps173 , G. Piacquadio155 , E. Pianori18 , A. Picazio102 , R.H. Pickles100 , R. Piegaia30 , D. Pietreanu27b , J.E. Pilcher37 , A.D. Pilkington100 , M. Pinamonti73a,73b , J.L. Pinfold3 , M. Pitt180 , L. Pizzimento73a,73b , M.-A. Pleier29 , V. Pleskot143 , E. Plotnikova79 , D. Pluth78 , P. Podberezko122b,122a , R. Poettgen96 , R. Poggi54 , L. Poggioli132 , I. Pogrebnyak106 , D. Pohl24 , I. Pokharel53 , G. Polesello70a , A. Poley18 , A. Policicchio72a,72b , R. Polifka143 , A. Polini23b , C.S. Pollard46 , V. Polychronakos29 , D. Ponomarenko112 , L. Pontecorvo36 , S. Popa27a , G.A. Popeneciu27d , D.M. Portillo Quintero58 , S. Pospisil142 , K. Potamianos46 , I.N. Potrap79 , C.J. Potter32 , H. Potti11 , T. Poulsen96 , J. Poveda36 , T.D. Powell149 , G. Pownall46 , M.E. Pozo Astigarraga36 , P. Pralavorio101 , S. Prell78 , D. Price100 , M. Primavera67a , S. Prince103 , M.L. Proffitt148 , N. Proklova112 , K. Prokofiev63c , F. Prokoshin79 , S. Protopopescu29 , J. Proudfoot6 , M. Przybycien83a , D. Pudzha138 , A. Puri173 , P. Puzo132 , J. Qian105 , Y. Qin100 , A. Quadt53 , M. Queitsch-Maitland46 , A. Qureshi1 , P. Rados104 , F. Ragusa68a,68b , G. Rahal97 , J.A. Raine54 , S. Rajagopalan29 , A. Ramirez Morales92 , K. Ran15a,15d , T. Rashid132 , S. Raspopov5 , D.M. Rauch46 , F. Rauscher114 , S. Rave99 , B. Ravina149 , I. Ravinovich180 , J.H. Rawling100 , M. Raymond36 , A.L. Read134 , N.P. Readioff58 , M. Reale67a,67b , D.M. Rebuzzi70a,70b , A. Redelbach177 , G. Redlinger29 , K. Reeves43 , L. Rehnisch19 , J. Reichert137 , D. Reikher161 , A. Reiss99 , A. Rej151 , C. Rembser36 , M. Renda27b , M. Rescigno72a , S. Resconi68a , E.D. Resseguie137 , S. Rettie175 , E. Reynolds21 , O.L. Rezanova122b,122a , P. Reznicek143 , E. Ricci75a,75b , R. Richter115 , S. Richter46 , E. Richter-Was83b , O. Ricken24 , M. Ridel136 , P. Rieck115 , C.J. Riegel182 , O. Rifki46 , M. Rijssenbeek155 , A. Rimoldi70a,70b , M. Rimoldi46 , L. Rinaldi23b , G. Ripellino154 , B. Ristić89 , E. Ritsch36 , I. Riu14 , J.C. Rivera Vergara176 , F. Rizatdinova129 , E. Rizvi92 , C. Rizzi36 , R.T. Roberts100 , S.H. Robertson103,ah , M. Robin46 , D. Robinson32 , J.E.M. Robinson46 , C.M. Robles Gajardo147b , A. Robson57 , E. Rocco99 , C. Roda71a,71b , S. Rodriguez Bosca174 , A. Rodriguez Perez14 , D. Rodriguez Rodriguez174 , A.M. Rodrı́guez Vera168b , S. Roe36 , O. Røhne134 , R. Röhrig115 , C.P.A. Roland65 , J. Roloff59 , A. Romaniouk112 , M. Romano23b,23a , N. Rompotis90 , M. Ronzani124 , L. Roos136 , S. Rosati72a , K. Rosbach52 , G. Rosin102 , B.J. Rosser137 , E. Rossi46 , E. Rossi74a,74b , E. Rossi69a,69b , L.P. Rossi55b , L. Rossini68a,68b , R. Rosten14 , M. Rotaru27b , J. Rothberg148 , D. Rousseau132 , G. Rovelli70a,70b , A. Roy11 , – 41 – D. Roy33c , A. Rozanov101 , Y. Rozen160 , X. Ruan33c , F. Rubbo153 , F. Rühr52 , A. Ruiz-Martinez174 , A. Rummler36 , Z. Rurikova52 , N.A. Rusakovich79 , H.L. Russell103 , L. Rustige38,47 , J.P. Rutherfoord7 , E.M. Rüttinger46,l , M. Rybar39 , G. Rybkin132 , A. Ryzhov123 , G.F. Rzehorz53 , P. Sabatini53 , G. Sabato120 , S. Sacerdoti132 , H.F-W. Sadrozinski146 , R. Sadykov79 , F. Safai Tehrani72a , B. Safarzadeh Samani156 , P. Saha121 , S. Saha103 , M. Sahinsoy61a , A. Sahu182 , M. Saimpert46 , M. Saito163 , T. Saito163 , H. Sakamoto163 , A. Sakharov124,ar , D. Salamani54 , G. Salamanna74a,74b , J.E. Salazar Loyola147b , P.H. Sales De Bruin172 , A. Salnikov153 , J. Salt174 , D. Salvatore41b,41a , F. Salvatore156 , A. Salvucci63a,63b,63c , A. Salzburger36 , J. Samarati36 , D. Sammel52 , D. Sampsonidis162 , D. Sampsonidou162 , J. Sánchez174 , A. Sanchez Pineda66a,66c , H. Sandaker134 , C.O. Sander46 , I.G. Sanderswood89 , M. Sandhoff182 , C. Sandoval22 , D.P.C. Sankey144 , M. Sannino55b,55a , Y. Sano117 , A. Sansoni51 , C. Santoni38 , H. Santos140a,140b , JHEP10(2019)203 S.N. Santpur18 , A. Santra174 , A. Sapronov79 , J.G. Saraiva140a,140d , O. Sasaki81 , K. Sato169 , E. Sauvan5 , P. Savard167,bb , N. Savic115 , R. Sawada163 , C. Sawyer144 , L. Sawyer95,ap , C. Sbarra23b , A. Sbrizzi23a , T. Scanlon94 , J. Schaarschmidt148 , P. Schacht115 , B.M. Schachtner114 , D. Schaefer37 , L. Schaefer137 , J. Schaeffer99 , S. Schaepe36 , U. Schäfer99 , A.C. Schaffer132 , D. Schaile114 , R.D. Schamberger155 , N. Scharmberg100 , V.A. Schegelsky138 , D. Scheirich143 , F. Schenck19 , M. Schernau171 , C. Schiavi55b,55a , S. Schier146 , L.K. Schildgen24 , Z.M. Schillaci26 , E.J. Schioppa36 , M. Schioppa41b,41a , K.E. Schleicher52 , S. Schlenker36 , K.R. Schmidt-Sommerfeld115 , K. Schmieden36 , C. Schmitt99 , S. Schmitt46 , S. Schmitz99 , J.C. Schmoeckel46 , U. Schnoor52 , L. Schoeffel145 , A. Schoening61b , P.G. Scholer52 , E. Schopf135 , M. Schott99 , J.F.P. Schouwenberg119 , J. Schovancova36 , S. Schramm54 , F. Schroeder182 , A. Schulte99 , H-C. Schultz-Coulon61a , M. Schumacher52 , B.A. Schumm146 , Ph. Schune145 , A. Schwartzman153 , T.A. Schwarz105 , Ph. Schwemling145 , R. Schwienhorst106 , A. Sciandra146 , G. Sciolla26 , M. Scodeggio46 , M. Scornajenghi41b,41a , F. Scuri71a , F. Scutti104 , L.M. Scyboz115 , C.D. Sebastiani72a,72b , P. Seema19 , S.C. Seidel118 , A. Seiden146 , T. Seiss37 , J.M. Seixas80b , G. Sekhniaidze69a , K. Sekhon105 , S.J. Sekula42 , N. Semprini-Cesari23b,23a , S. Sen49 , S. Senkin38 , C. Serfon76 , L. Serin132 , L. Serkin66a,66b , M. Sessa60a , H. Severini128 , T. Šfiligoj91 , F. Sforza170 , A. Sfyrla54 , E. Shabalina53 , J.D. Shahinian146 , N.W. Shaikh45a,45b , D. Shaked Renous180 , L.Y. Shan15a , R. Shang173 , J.T. Shank25 , M. Shapiro18 , A. Sharma135 , A.S. Sharma1 , P.B. Shatalov111 , K. Shaw156 , S.M. Shaw100 , A. Shcherbakova138 , Y. Shen128 , N. Sherafati34 , A.D. Sherman25 , P. Sherwood94 , L. Shi158,ax , S. Shimizu81 , C.O. Shimmin183 , Y. Shimogama179 , M. Shimojima116 , I.P.J. Shipsey135 , S. Shirabe87 , M. Shiyakova79,ae , J. Shlomi180 , A. Shmeleva110 , M.J. Shochet37 , J. Shojaii104 , D.R. Shope128 , S. Shrestha126 , E.M. Shrif33c , E. Shulga180 , P. Sicho141 , A.M. Sickles173 , P.E. Sidebo154 , E. Sideras Haddad33c , O. Sidiropoulou36 , A. Sidoti23b,23a , F. Siegert48 , Dj. Sijacki16 , M.Jr. Silva181 , M.V. Silva Oliveira80a , S.B. Silverstein45a , S. Simion132 , E. Simioni99 , R. Simoniello99 , S. Simsek12b , P. Sinervo167 , V. Sinetckii113,110 , N.B. Sinev131 , M. Sioli23b,23a , I. Siral105 , S.Yu. Sivoklokov113 , J. Sjölin45a,45b , E. Skorda96 , P. Skubic128 , M. Slawinska84 , K. Sliwa170 , R. Slovak143 , V. Smakhtin180 , B.H. Smart144 , J. Smiesko28a , N. Smirnov112 , S.Yu. Smirnov112 , Y. Smirnov112 , L.N. Smirnova113,x , O. Smirnova96 , J.W. Smith53 , M. Smizanska89 , K. Smolek142 , A. Smykiewicz84 , A.A. Snesarev110 , H.L. Snoek120 , I.M. Snyder131 , S. Snyder29 , R. Sobie176,ah , A.M. Soffa171 , A. Soffer161 , A. Søgaard50 , F. Sohns53 , C.A. Solans Sanchez36 , E.Yu. Soldatov112 , U. Soldevila174 , A.A. Solodkov123 , A. Soloshenko79 , O.V. Solovyanov123 , V. Solovyev138 , P. Sommer149 , H. Son170 , W. Song144 , W.Y. Song168b , A. Sopczak142 , F. Sopkova28b , C.L. Sotiropoulou71a,71b , S. Sottocornola70a,70b , R. Soualah66a,66c,h , A.M. Soukharev122b,122a , D. South46 , S. Spagnolo67a,67b , M. 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Sulin110 , M.J. Sullivan90 , D.M.S. Sultan54 , S. Sultansoy4c , T. Sumida85 , S. Sun105 , X. Sun3 , K. Suruliz156 , C.J.E. Suster157 , M.R. Sutton156 , S. Suzuki81 , M. Svatos141 , M. Swiatlowski37 , S.P. Swift2 , T. Swirski177 , A. Sydorenko99 , I. Sykora28a , M. Sykora143 , T. Sykora143 , D. Ta99 , K. Tackmann46,ac , JHEP10(2019)203 J. Taenzer161 , A. Taffard171 , R. Tafirout168a , H. Takai29 , R. Takashima86 , K. Takeda82 , T. Takeshita150 , E.P. Takeva50 , Y. Takubo81 , M. Talby101 , A.A. Talyshev122b,122a , N.M. Tamir161 , J. Tanaka163 , M. Tanaka165 , R. Tanaka132 , S. Tapia Araya173 , S. Tapprogge99 , A. Tarek Abouelfadl Mohamed136 , S. Tarem160 , G. Tarna27b,d , G.F. Tartarelli68a , P. Tas143 , M. Tasevsky141 , T. Tashiro85 , E. Tassi41b,41a , A. Tavares Delgado140a,140b , Y. Tayalati35e , A.J. Taylor50 , G.N. Taylor104 , W. Taylor168b , A.S. Tee89 , R. Teixeira De Lima153 , P. Teixeira-Dias93 , H. Ten Kate36 , J.J. Teoh120 , S. Terada81 , K. Terashi163 , J. Terron98 , S. 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Zwalinski36 1 Department of Physics, University of Adelaide, Adelaide; Australia 2 Physics Department, SUNY Albany, Albany NY; U.S.A. 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; U.S.A. 7 Department of Physics, University of Arizona, Tucson AZ; U.S.A. 8 Department of Physics, University of Texas at Arlington, Arlington TX; U.S.A. 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; U.S.A. – 44 – 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 JHEP10(2019)203 18 Physics Division, Lawrence Berkeley National Laboratory and University of California, Berkeley CA; U.S.A. 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 Universita’ 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; U.S.A. 26 Department of Physics, Brandeis University, Waltham MA; U.S.A. 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; U.S.A. 30 Departamento de Fı́sica, Universidad de Buenos Aires, Buenos Aires; Argentina 31 California State University, CA; U.S.A. 32 Cavendish Laboratory, University of Cambridge, Cambridge; United Kingdom 33 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 34 Department of Physics, Carleton University, Ottawa ON; Canada 35 Faculté des Sciences Ain Chock(a) , Réseau Universitaire de Physique des Hautes Energies — Université Hassan II, Casablanca; Faculté des Sciences(b) , Université Ibn-Tofail, Kénitra; 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 36 CERN, Geneva; Switzerland 37 Enrico Fermi Institute, University of Chicago, Chicago IL; U.S.A. 38 LPC, Université Clermont Auvergne, CNRS/IN2P3, Clermont-Ferrand; France 39 Nevis Laboratory, Columbia University, Irvington NY; U.S.A. 40 Niels Bohr Institute, University of Copenhagen, Copenhagen; Denmark 41 Dipartimento di Fisica(a) , Università della Calabria, Rende; INFN Gruppo Collegato di Cosenza (b) , Laboratori Nazionali di Frascati; Italy – 45 – 42 Physics Department, Southern Methodist University, Dallas TX; U.S.A. 43 Physics Department, University of Texas at Dallas, Richardson TX; U.S.A. 44 National Centre for Scientific Research “Demokritos”, Agia Paraskevi; Greece 45 Department of Physics(a) , Stockholm University; Oskar Klein Centre(b) , Stockholm; Sweden 46 Deutsches Elektronen-Synchrotron DESY, Hamburg and Zeuthen; Germany 47 Lehrstuhl für Experimentelle Physik IV, Technische Universität Dortmund, Dortmund; Germany 48 Institut für Kern- und Teilchenphysik, Technische Universität Dresden, Dresden; Germany 49 Department of Physics, Duke University, Durham NC; U.S.A. 50 SUPA — School of Physics and Astronomy, University of Edinburgh, Edinburgh; United Kingdom 51 INFN e Laboratori Nazionali di Frascati, Frascati; Italy 52 Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg; Germany 53 II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen; Germany JHEP10(2019)203 54 Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève; Switzerland 55 Dipartimento di Fisica(a) , Università di Genova, Genova; INFN Sezione di Genova(b) ; Italy 56 II. Physikalisches Institut, Justus-Liebig-Universität Giessen, Giessen; Germany 57 SUPA — School of Physics and Astronomy, University of Glasgow, Glasgow; United Kingdom 58 LPSC, Université Grenoble Alpes, CNRS/IN2P3, Grenoble INP, Grenoble; France 59 Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge MA; U.S.A. 60 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 61 Kirchhoff-Institut für Physik(a) , Ruprecht-Karls-Universität Heidelberg, Heidelberg; Physikalisches Institut(b) , Ruprecht-Karls-Universität Heidelberg, Heidelberg; Germany 62 Faculty of Applied Information Science, Hiroshima Institute of Technology, Hiroshima; Japan 63 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 64 Department of Physics, National Tsing Hua University, Hsinchu; Taiwan 65 Department of Physics, Indiana University, Bloomington IN; U.S.A. 66 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 67 INFN Sezione di Lecce(a) ; Dipartimento di Matematica e Fisica(b) , Università del Salento, Lecce; Italy 68 INFN Sezione di Milano(a) ; Dipartimento di Fisica(b) , Università di Milano, Milano; Italy 69 INFN Sezione di Napoli(a) ; Dipartimento di Fisica(b) , Università di Napoli, Napoli; Italy 70 INFN Sezione di Pavia(a) ; Dipartimento di Fisica(b) , Università di Pavia, Pavia; Italy 71 INFN Sezione di Pisa(a) ; Dipartimento di Fisica E. Fermi(b) , Università di Pisa, Pisa; Italy 72 INFN Sezione di Roma(a) ; Dipartimento di Fisica(b) , Sapienza Università di Roma, Roma; Italy 73 INFN Sezione di Roma Tor Vergata(a) ; Dipartimento di Fisica(b) , Università di Roma Tor Vergata, Roma; Italy 74 INFN Sezione di Roma Tre(a) ; Dipartimento di Matematica e Fisica(b) , Università Roma Tre, Roma; Italy 75 INFN-TIFPA(a) ; Università degli Studi di Trento(b) , Trento; Italy 76 Institut für Astro- und Teilchenphysik, Leopold-Franzens-Universität, Innsbruck; Austria 77 University of Iowa, Iowa City IA; U.S.A. 78 Department of Physics and Astronomy, Iowa State University, Ames IA; U.S.A. 79 Joint Institute for Nuclear Research, Dubna; Russia 80 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 – 46 – Federal de São João del Rei (UFSJ)(c) , São João del Rei; Instituto de Fı́sica(d) , Universidade de São Paulo, São Paulo; Brazil 81 KEK, High Energy Accelerator Research Organization, Tsukuba; Japan 82 Graduate School of Science, Kobe University, Kobe; Japan 83 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 84 Institute of Nuclear Physics Polish Academy of Sciences, Krakow; Poland 85 Faculty of Science, Kyoto University, Kyoto; Japan 86 Kyoto University of Education, Kyoto; Japan 87 Research Center for Advanced Particle Physics and Department of Physics, Kyushu University, Fukuoka; Japan 88 Instituto de Fı́sica La Plata, Universidad Nacional de La Plata and CONICET, La Plata; Argentina JHEP10(2019)203 89 Physics Department, Lancaster University, Lancaster; United Kingdom 90 Oliver Lodge Laboratory, University of Liverpool, Liverpool; United Kingdom 91 Department of Experimental Particle Physics, Jožef Stefan Institute and Department of Physics, University of Ljubljana, Ljubljana; Slovenia 92 School of Physics and Astronomy, Queen Mary University of London, London; United Kingdom 93 Department of Physics, Royal Holloway University of London, Egham; United Kingdom 94 Department of Physics and Astronomy, University College London, London; United Kingdom 95 Louisiana Tech University, Ruston LA; U.S.A. 96 Fysiska institutionen, Lunds universitet, Lund; Sweden 97 Centre de Calcul de l’Institut National de Physique Nucléaire et de Physique des Particules (IN2P3), Villeurbanne; France 98 Departamento de Fı́sica Teorica C-15 and CIAFF, Universidad Autónoma de Madrid, Madrid; Spain 99 Institut für Physik, Universität Mainz, Mainz; Germany 100 School of Physics and Astronomy, University of Manchester, Manchester; United Kingdom 101 CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille; France 102 Department of Physics, University of Massachusetts, Amherst MA; U.S.A. 103 Department of Physics, McGill University, Montreal QC; Canada 104 School of Physics, University of Melbourne, Victoria; Australia 105 Department of Physics, University of Michigan, Ann Arbor MI; U.S.A. 106 Department of Physics and Astronomy, Michigan State University, East Lansing MI; U.S.A. 107 B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk; Belarus 108 Research Institute for Nuclear Problems of Byelorussian State University, Minsk; Belarus 109 Group of Particle Physics, University of Montreal, Montreal QC; Canada 110 P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow; Russia 111 Institute for Theoretical and Experimental Physics of the National Research Centre Kurchatov Institute, Moscow; Russia 112 National Research Nuclear University MEPhI, Moscow; Russia 113 D.V. Skobeltsyn Institute of Nuclear Physics, M.V. Lomonosov Moscow State University, Moscow; Russia 114 Fakultät für Physik, Ludwig-Maximilians-Universität München, München; Germany 115 Max-Planck-Institut für Physik (Werner-Heisenberg-Institut), München; Germany 116 Nagasaki Institute of Applied Science, Nagasaki; Japan 117 Graduate School of Science and Kobayashi-Maskawa Institute, Nagoya University, Nagoya; Japan 118 Department of Physics and Astronomy, University of New Mexico, Albuquerque NM; U.S.A. 119 Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen; Netherlands 120 Nikhef National Institute for Subatomic Physics and University of Amsterdam, Amsterdam; Netherlands 121 Department of Physics, Northern Illinois University, DeKalb IL; U.S.A. – 47 – 122 Budker Institute of Nuclear Physics and NSU(a) , SB RAS, Novosibirsk; Novosibirsk State University Novosibirsk(b) ; Russia 123 Institute for High Energy Physics of the National Research Centre Kurchatov Institute, Protvino; Russia 124 Department of Physics, New York University, New York NY; U.S.A. 125 Ochanomizu University, Otsuka, Bunkyo-ku, Tokyo; Japan 126 Ohio State University, Columbus OH; U.S.A. 127 Faculty of Science, Okayama University, Okayama; Japan 128 Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman OK; U.S.A. 129 Department of Physics, Oklahoma State University, Stillwater OK; U.S.A. 130 Palacký University, RCPTM, Joint Laboratory of Optics, Olomouc; Czech Republic JHEP10(2019)203 131 Center for High Energy Physics, University of Oregon, Eugene OR; U.S.A. 132 LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay; France 133 Graduate School of Science, Osaka University, Osaka; Japan 134 Department of Physics, University of Oslo, Oslo; Norway 135 Department of Physics, Oxford University, Oxford; United Kingdom 136 LPNHE, Sorbonne Université, Université de Paris, CNRS/IN2P3, Paris; France 137 Department of Physics, University of Pennsylvania, Philadelphia PA; U.S.A. 138 Konstantinov Nuclear Physics Institute of National Research Centre “Kurchatov Institute”, PNPI, St. Petersburg; Russia 139 Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh PA; U.S.A. 140 Laboratório de Instrumentação e Fı́sica Experimental de Partı́culas — LIP (a) , Lisbon; Departamento de Fı́sica(b) , Faculdade de Ciências, Universidade de Lisboa, Lisbon; Departamento de Fı́sica(c) , Universidade de Coimbra, Coimbra; Centro de Fı́sica Nuclear da Universidade de Lisboa(d) , Lisbon; 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; Av. Rovisco Pais(h) , 1 1049-001 Lisbon, Portugal; Portugal 141 Institute of Physics of the Czech Academy of Sciences, Prague; Czech Republic 142 Czech Technical University in Prague, Prague; Czech Republic 143 Charles University, Faculty of Mathematics and Physics, Prague; Czech Republic 144 Particle Physics Department, Rutherford Appleton Laboratory, Didcot; United Kingdom 145 IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette; France 146 Santa Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz CA; U.S.A. 147 Departamento de Fı́sica(a) , Pontificia Universidad Católica de Chile, Santiago; Departamento de Fı́sica(b) , Universidad Técnica Federico Santa Marı́a, Valparaı́so; Chile 148 Department of Physics, University of Washington, Seattle WA; U.S.A. 149 Department of Physics and Astronomy, University of Sheffield, Sheffield; United Kingdom 150 Department of Physics, Shinshu University, Nagano; Japan 151 Department Physik, Universität Siegen, Siegen; Germany 152 Department of Physics, Simon Fraser University, Burnaby BC; Canada 153 SLAC National Accelerator Laboratory, Stanford CA; U.S.A. 154 Physics Department, Royal Institute of Technology, Stockholm; Sweden 155 Departments of Physics and Astronomy, Stony Brook University, Stony Brook NY; U.S.A. 156 Department of Physics and Astronomy, University of Sussex, Brighton; United Kingdom 157 School of Physics, University of Sydney, Sydney; Australia 158 Institute of Physics, Academia Sinica, Taipei; Taiwan 159 E. Andronikashvili Institute of Physics(a) , Iv. Javakhishvili Tbilisi State University, Tbilisi; High Energy Physics Institute(b) , Tbilisi State University, Tbilisi; Georgia 160 Department of Physics, Technion, Israel Institute of Technology, Haifa; Israel 161 Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv University, Tel Aviv; Israel – 48 – 162 Department of Physics, Aristotle University of Thessaloniki, Thessaloniki; Greece 163 International Center for Elementary Particle Physics and Department of Physics, University of Tokyo, Tokyo; Japan 164 Graduate School of Science and Technology, Tokyo Metropolitan University, Tokyo; Japan 165 Department of Physics, Tokyo Institute of Technology, Tokyo; Japan 166 Tomsk State University, Tomsk; Russia 167 Department of Physics, University of Toronto, Toronto ON; Canada 168 TRIUMF(a) , Vancouver BC; Department of Physics and Astronomy(b) , York University, Toronto ON; Canada 169 Division of Physics and Tomonaga Center for the History of the Universe, Faculty of Pure and Applied Sciences, University of Tsukuba, Tsukuba; Japan 170 Department of Physics and Astronomy, Tufts University, Medford MA; U.S.A. JHEP10(2019)203 171 Department of Physics and Astronomy, University of California Irvine, Irvine CA; U.S.A. 172 Department of Physics and Astronomy, University of Uppsala, Uppsala; Sweden 173 Department of Physics, University of Illinois, Urbana IL; U.S.A. 174 Instituto de Fı́sica Corpuscular (IFIC), Centro Mixto Universidad de Valencia — CSIC, Valencia; Spain 175 Department of Physics, University of British Columbia, Vancouver BC; Canada 176 Department of Physics and Astronomy, University of Victoria, Victoria BC; Canada 177 Fakultät für Physik und Astronomie, Julius-Maximilians-Universität Würzburg, Würzburg; Germany 178 Department of Physics, University of Warwick, Coventry; United Kingdom 179 Waseda University, Tokyo; Japan 180 Department of Particle Physics, Weizmann Institute of Science, Rehovot; Israel 181 Department of Physics, University of Wisconsin, Madison WI; U.S.A. 182 Fakultät für Mathematik und Naturwissenschaften, Fachgruppe Physik, Bergische Universität Wuppertal, Wuppertal; Germany 183 Department of Physics, Yale University, New Haven CT; U.S.A. 184 Yerevan Physics Institute, Yerevan; Armenia a Also at Borough of Manhattan Community College, City University of New York, New York NY; U.S.A. b Also at Centre for High Performance Computing, CSIR Campus, Rosebank, Cape Town; South Africa c Also at CERN, Geneva; Switzerland d Also at CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille; France e Also at Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève; Switzerland f Also at Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona; Spain g Also at Departamento de Fı́sica, Instituto Superior Técnico, Universidade de Lisboa, Lisboa; Portugal h Also at Department of Applied Physics and Astronomy, University of Sharjah, Sharjah; United Arab Emirates i Also at Department of Financial and Management Engineering, University of the Aegean, Chios; Greece j Also at Department of Physics and Astronomy, Michigan State University, East Lansing MI; U.S.A. k Also at Department of Physics and Astronomy, University of Louisville, Louisville, KY; U.S.A. l Also at Department of Physics and Astronomy, University of Sheffield, Sheffield; United Kingdom m Also at Department of Physics, Ben Gurion University of the Negev, Beer Sheva; Israel n Also at Department of Physics, California State University, East Bay; U.S.A. o Also at Department of Physics, California State University, Fresno; U.S.A. – 49 – p Also at Department of Physics, California State University, Sacramento; U.S.A. q Also at Department of Physics, King’s College London, London; United Kingdom r Also at Department of Physics, St. Petersburg State Polytechnical University, St. Petersburg; Russia s Also at Department of Physics, Stanford University, Stanford CA; U.S.A. t Also at Department of Physics, University of Adelaide, Adelaide; Australia u Also at Department of Physics, University of Fribourg, Fribourg; Switzerland v Also at Department of Physics, University of Michigan, Ann Arbor MI; U.S.A. w Also at Dipartimento di Matematica, Informatica e Fisica, Università di Udine, Udine; Italy x Also at Faculty of Physics, M.V. Lomonosov Moscow State University, Moscow; Russia y Also at Giresun University, Faculty of Engineering, Giresun; Turkey z Also at Graduate School of Science, Osaka University, Osaka; Japan JHEP10(2019)203 aa Also at Hellenic Open University, Patras; Greece ab Also at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona; Spain ac Also at Institut für Experimentalphysik, Universität Hamburg, Hamburg; Germany ad Also at Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen; Netherlands ae Also at Institute for Nuclear Research and Nuclear Energy (INRNE) of the Bulgarian Academy of Sciences, Sofia; Bulgaria af Also at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest; Hungary ag Also at Institute of High Energy Physics, Chinese Academy of Sciences, Beijing; China ah Also at Institute of Particle Physics (IPP), Vancouver; Canada ai Also at Institute of Physics, Academia Sinica, Taipei; Taiwan aj Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku; Azerbaijan ak Also at Institute of Theoretical Physics, Ilia State University, Tbilisi; Georgia al Also at Instituto de Fisica Teorica, IFT-UAM/CSIC, Madrid; Spain am Also at Istanbul University, Dept. of Physics, Istanbul; Turkey an Also at Joint Institute for Nuclear Research, Dubna; Russia ao Also at LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay; France ap Also at Louisiana Tech University, Ruston LA; U.S.A. aq Also at LPNHE, Sorbonne Université, Université de Paris, CNRS/IN2P3, Paris; France ar Also at Manhattan College, New York NY; U.S.A. as Also at Moscow Institute of Physics and Technology State University, Dolgoprudny; Russia at Also at National Research Nuclear University MEPhI, Moscow; Russia au Also at Physics Department, An-Najah National University, Nablus; Palestine av Also at Physics Dept, University of South Africa, Pretoria; South Africa aw Also at Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg; Germany ax Also at School of Physics, Sun Yat-sen University, Guangzhou; China ay Also at The City College of New York, New York NY; U.S.A. az Also at The Collaborative Innovation Center of Quantum Matter (CICQM), Beijing; China ba Also at Tomsk State University, Tomsk, and Moscow Institute of Physics and Technology State University, Dolgoprudny; Russia bb Also at TRIUMF, Vancouver BC; Canada bc Also at Universita di Napoli Parthenope, Napoli; Italy ∗ Deceased – 50 –