Physics Letters B 788 (2019) 316–335 Contents lists available at ScienceDirect Physics Letters B www.elsevier.com/locate/physletb Search for light resonances decaying to boosted quark pairs and produced in √ association with a photon or a jet in proton–proton collisions at s = 13 TeV with the ATLAS detector .The ATLAS Collaboration  a r t i c l e i n f o a b s t r a c t Article history: This Letter presents a search for new light resonances decaying to pairs of quarks and produced in Received 26 January 2018 association with a high-p T photon or jet. The dataset consists √ of proton–proton collisions with an Received in revised form 27 September integrated luminosity of 36.1 fb−1 at a centre-of-mass energy of s = 13 TeV recorded by the ATLAS 2018 detector at the Large Hadron Collider. Resonance candidates are identified as massive large-radius jets Accepted 30 September 2018 Available online 2 November 2018 with substructure consistent with a particle decaying into a quark pair. The mass spectrum of the Editor: M. Doser candidates is examined for local excesses above background. No evidence of a new resonance is observed in the data, which are used to exclude the production of a lepto-phobic axial-vector Z  boson. © 2018 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Funded by SCOAP3 . 1. Introduction the light resonance is boosted in the transverse direction1 via re- coil from high transverse momentum (p T ) initial-state radiation Searches for resonance signals in the invariant mass spectrum (ISR) of a photon or jet. Requiring a hard ISR object in the final of hadrons are an essential part of the physics programme at the state comes at the cost of reduced signal production rates, but al- energy frontier. Many theoretical models predict resonances [1–3] lows highly efficient triggering at masses much lower than when with significant couplings to quarks and gluons, including reso- triggering directly on the resonance decay products. nances which also couple to dark-matter particles [4–7]. At the The search is performed for resonance masses from 100 GeV to Large Hadron Collider (LHC), the ability to discover or exclude such 220 GeV, a range in which the resonance is boosted and its de- hadronic resonances has been extended into the TeV range, al- cay products are collimated, such that the resonance mass can be though no evidence of statistically significant excesses has been calculated from the mass of a large-radius jet. The dominant back- seen [8,9]. ground processes are multijet production in the jet channel and Sensitivity to light resonances is reduced by the immense back- photons produced in association with jets in the photon channel, ground rates that would saturate the trigger and data acquisition both characterised by non-resonant jets initiated predominantly by systems. The recording of collision data typically requires placing single gluons or light-flavour quarks. The Z  signal models consid- thresholds of several hundred GeV on the transverse momentum ered decay to quark–antiquark pairs. This difference in the domi- (p min T ) of the jet used to trigger the event, which translates to ap- nant jet production mechanism between the signal and the leading proximate thresholds on mass of m ≈ 2p min T . Consequently, recent backgrounds means that, in the boosted regime considered in this searches for dijet resonances at the LHC have poor sensitivity for Letter, the use of jet substructure methods strongly suppresses the masses well below 1 TeV. This limitation can be avoided by record- background, making it a crucial component for the search sensitiv- ing only a summary of the jet information needed for performing a ity. In addition, current datasets are the largest collected, allowing resonance search in the dijet mass spectrum. This strategy is called the sensitivity to rare processes to be extended beyond that of ear- “data scouting” in CMS [10], “real-time analysis” in LHCb [11] and lier studies. “trigger-object-level analysis” in ATLAS [12], and has set limits for resonance masses in the range 500–800 GeV [10]. 1 In this Letter, a search using an alternative approach [4,13] is 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 performed, in order to cover even lower resonance masses. The pipe. The x-axis points from the IP to the centre of the LHC ring, and the y-axis trigger threshold limitations are reduced by examining data where points upwards. Cylindrical coordinates (r , φ) are used in the transverse plane, φ being the azimuthal angle around the z-axis. The pseudorapidity is defined in terms of the polar angle θ as η = − ln tan(θ/2). It is equivalent to  the rapidity for massless  E-mail address: atlas.publications@cern.ch. particles. Angular distance is measured in units of  R ≡ (η)2 + (φ)2 . https://doi.org/10.1016/j.physletb.2018.09.062 0370-2693/© 2018 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Funded by SCOAP3 . The ATLAS Collaboration / Physics Letters B 788 (2019) 316–335 317 Recently, CMS reported results of applying a similar technique to three partons for W / Z +γ samples. The cross sections were cor- [14,15] to exclude a light Z  boson with Standard Model (SM) rected at next-to-leading order (NLO) using K -factors derived from coupling values (gq ) exceeding 0.1 to 0.25 in the mass range corresponding samples with leptonic vector-boson decays gener- 50–300 GeV. With respect to those results, this Letter also exploits ated at NLO using Sherpa 2.1.1 [24], with matrix elements calcu- the channel with the ISR photon. lated for up to two partons at NLO and four partons at LO using Comix [25] and OpenLoops [26]. All the above LO background sam- 2. ATLAS detector ples were merged with the Sherpa parton shower [27] using the ME+PS@LO prescription [28]. The CT10 set of parton distribution The ATLAS experiment [16] at the LHC is a multi-purpose functions (PDFs) [29] were used in conjunction with the dedicated particle detector with a forward–backward symmetric cylindrical parton shower tuning developed by the Sherpa authors. For the geometry with layers of tracking, calorimeter, and muon detec- NLO leptonic vector-boson samples utilised to calculate K -factors, tors over nearly the entire solid angle around the proton–proton the ME+PS@NLO prescription [28] and the CT10nlo PDF set are (pp) collision point. The inner detector (ID) consists of a high- used. granularity silicon pixel detector, including an insertable B-layer As a benchmark signal, samples with a Z  resonance with only [17], and a silicon microstrip tracker, together providing preci- hadronic couplings were generated as in Refs. [30–32]. This Z  sion tracking in the pseudorapidity range |η| < 2.5. Complemen- has axial-vector couplings to quarks. The coupling of the Z  to quarks, gq , is set to be universal in quark flavour and equal to tary, a transition radiation tracker provides tracking and electron 0.5. The corresponding total width  Z  is negligible compared to identification information for |η| < 2.0. The ID is surrounded by the experimental resolution, which is about 10% of the boson a 2 T superconducting solenoid. Lead/liquid-argon (LAr) sampling mass. A set of samples was generated with m Z  between 100 and calorimeters provide electromagnetic (EM) energy measurements 220 GeV, in 30 GeV steps. A linear and parameterised interpolation with high granularity, covering the region |η| < 3.2. A hadron was performed in 10 GeV steps in between the generated mass (steel/scintillator-tile) calorimeter covers the central pseudorapid- points. The samples were produced with gq = 0.5, using the Mad- ity range (|η| < 1.7). The end-cap and forward regions are instru- Graph_aMC@NLO generator [33] with the NNPDF2.3 LO PDF [34] mented with copper/LAr calorimeters (1.7 < |η| < 3.2) and LAr and the A14 set of tuned parameters (tune) [35]. Parton showers calorimeters with copper and tungsten absorbers, providing EM were produced in Pythia 8.186 [36]. Interference of this bench- and hadronic energy measurements covering the region |η| ≤ 4.9. mark model with the Standard Model Z boson is assumed to be The muon spectrometer consists of precision tracking chambers negligible. For efficient population of the kinematic phase space, covering the region |η| ≤ 2.7. The first-level trigger is implemented a photon (jet) with p T ≥ 100 GeV (350 GeV) was required in the in hardware and uses a subset of the detector information to re- generation phase. duce the accepted rate to 100 kHz. This hardware trigger [18] The response of the detector to particles was modelled with a is followed by a software-based trigger that reduces the rate of full ATLAS detector simulation [37] based on Geant4 [38]. All sim- recorded events to 1 kHz. ulated events were overlaid with additional pp interactions (pile- up) simulated with the soft strong-interaction processes of Pythia 3. Data and simulation samples 8.186 [36] using the A2 tune [39] and the MSTW2008LO PDF set √ [40]. The simulated events were reconstructed in the same way as The data were collected in pp collisions at s = 13 TeV dur- the data, and were reweighted such that the distribution of the ex- ing 2015 and 2016. Collision events are recorded with two triggers. pected number of pp interactions per bunch crossing matches that The first selects events with at least one photon candidate that has seen in data. an online transverse energy E T > 140 GeV and passes the “loose” identification requirements based on the shower shapes in the 4. Event reconstruction and selection EM and hadronic calorimeters [18]. The photon trigger reaches its maximum efficiency for E T > 155 GeV. The second trigger selects Events are required to have a reconstructed primary vertex, events with at least one jet candidate with online E T > 380 GeV defined as a vertex with at least two reconstructed tracks with formed from clusters of energy deposits in the calorimeters [19] p T > 400 MeV each and with the largest sum of track p 2T . by the anti-kt algorithm [20,21] with radius parameter R = 0.4, Photons are reconstructed from clusters of energy deposits in implemented in the FastJet package [22]. The jet trigger reaches the electromagnetic calorimeter. The photon energy scale is cor- its maximum efficiency for p T > 420 GeV. Only data satisfying rected using events with Z → e + e − decays in data [41]. Identifi- beam, detector and data-quality criteria are considered [23]. The cation requirements are applied to reduce the contamination from data used correspond to an integrated luminosity of 36.1 fb−1 . π 0 or other neutral hadrons decaying into photons. The photon Samples of simulated events are used to characterise the hypo- identification is based on the profile of the energy deposits in the thetical resonances as well as to study the kinematic distributions first and second layers of the electromagnetic calorimeter. Photons of background processes. These samples are not used to estimate used in the event selection must satisfy the “tight” identification the background contributions, except when validating the data- and isolation criteria defined in Ref. [42], and must have |η| < 2.37, driven background estimate (described in Section 5). excluding the EM calorimeter’s barrel/end-cap transition region of Background samples were simulated using the Sherpa 2.1.1 1.37 < |η| < 1.52. The efficiency of the photon selection is roughly event generator [24]. Processes containing a photon with associ- 95% for photons with E T > 150 GeV. ated jets were generated in several bins of photon p T . The matrix Two non-exclusive categories of jet candidates are built from elements were calculated at leading order (LO) with up to three clusters of energy deposits in the calorimeters [19] and are dis- partons for photon p T < 70 GeV or four partons for higher photon tinguished by the radius parameter used in the anti-kt algorithm. p T . Multijet background samples were generated at LO in several Jets with a radius parameter R = 1.0 are referred to as large-R jets, bins of leading-jet p T . Samples of W +jets, Z +jets, W +γ and denoted by J and required to have |η| < 2.0, whereas jets with a Z +γ events with hadronic decays of the vector-bosons were sim- radius parameter R = 0.4 are referred to as narrow jets, denoted ulated in bins of W / Z -boson p T . Matrix elements were calculated as j and are required to have |η| < 2.4. To mitigate the effects at LO with up to four partons for the W / Z +jets samples and up of pile-up and soft radiation, the large-R jets are trimmed [43]. 318 The ATLAS Collaboration / Physics Letters B 788 (2019) 316–335 DDT Fig. 1. Mean value of τ21 as a function of the large-R jet mass, for various ranges of large-R jet transverse momentum, for cases where the ISR object is a jet (left) and a photon (right).   Trimming takes the original constituents of the jet and reclusters m2J DDT ρ ≡ log , them using the kt algorithm [44] with a smaller radius parame- J pT × μ ter, R subjet , to produce a collection of subjets. These subjets are discarded if they carry less than a specific fraction ( f cut ) of the where μ ≡ 1 GeV is an arbitrary scale parameter. For ρ DDT  1, original jet p T . The trimming parameters optimised for this search there is a linear relationship between ρ DDT and the mean value of are R subjet = 0.2 and f cut = 5% [45]. Large-R jets are calibrated fol- τ21 . ρ DDT is a purely kinematic jet variable, which allows the def- lowing the procedure described in Ref. [46]. inition of τ21DDT [52,53], a linearly corrected version of τ21 , which The energies of selected narrow jets are corrected for contribu- has mean values that are independent of the mass of the jet, as tions from pile-up interactions [47]. A correction used to calibrate J seen in Fig. 1 for various ranges of large-R p T . jet energy measurements to the scale of the constituent particles Selected events are required to have at least one large-R jet, of the jet [48] is then applied. Narrow jets with 25 GeV < p T < the resonance candidate, and at least one narrow jet or photon 60 GeV are required to originate from the primary vertex as deter- with azimuthal angular separation of at least φ = π /2 from the mined by a jet vertex tagger [47] that relies on tracks associated resonance candidate. The ISR jet is the leading narrow jet with with the jets. j p T > 420 GeV, while the ISR photon is the leading photon with Quality requirements are applied to photon candidates to iden- γ p T > 155 GeV. tify those arising from instrumental problems or non-collision J background [49], and events containing such candidates are re- In the signal region (SR), the large-R jet must satisfy p T > J jected. In addition, quality requirements are applied to remove 200 GeV in the photon channel and pT > 450 GeV in the jet events containing jets misreconstructed from detector noise or out- channel. Those thresholds are defined due to the minimum J of-time energy deposits in the calorimeter from cosmic rays or p T > 200 GeV for which large-R jets uncertainties have been de- J other non-collision sources [50]. rived (photon channel) and to select events with p T close to the The production cross sections of the signal models consid- j recoil jet pT , as expected for signal (jet channel). In addition, it is ered in this search are many orders of magnitude lower than the J required that p T > 2 × m J to ensure sufficient collimation of the background cross sections. In order to enhance the sensitivity to quark pairs from signal resonances so as to avoid edge effects of the signal, jet substructure techniques are used to identify the using a fixed-cone jet algorithm, τ21 DDT < 0.50 to suppress back- expected two-body quark-pair signal-like events within a single grounds and ρ DDT DDT > 1.5. The τ21 requirement was chosen by large-R jet. One of the commonly used jet substructure variables is maximising the expected signal significance. The ρ DDT constraint τ21 [51], defined as the ratio τ2 /τ1 . The variable τN is a measure ensures that the τ21 DDT variable is linear relative to ρ DDT . If mul- of how consistent a given jet’s constituents are with being fully tiple jets satisfy these requirements, the jet with the lower τ21 DDT aligned along N or more axes; thus τ21 is a useful discriminant from the two leading large-R jets is selected. for differentiating between a two-particle jet from the decay of a boosted resonance and a single-particle jet. However, τ21 is cor- 5. Background estimation and systematic uncertainties related with the reconstructed large-R jet mass m J . Any selection requirement on τ21 leads to a selection of jets from the leading The dominant backgrounds in the jet and photon channels are background processes with efficiency strongly dependent on the due to multi-jet production and inclusive γ production, respec- jet mass, and modifies the final jet mass distribution in a way that tively. The inclusive γ background is dominated by γ +jets and makes it difficult to model using a simple functional approach, also includes multi-jet processes being misidentified with the same effectively increasing the systematic uncertainties and weakening topology. In both channels, there is a sub-leading contribution the overall sensitivity. To avoid this, the designed decorrelated tag- from production of a jet or photon in association with a hadroni- ger (DDT) method [14,52,53] is used to decorrelate τ21 from the cally decaying electroweak gauge boson, V , where V represents a reconstructed jet mass. The variable ρ DDT is defined as W or Z boson. The ATLAS Collaboration / Physics Letters B 788 (2019) 316–335 319 In the dominant backgrounds, the boosted phase space rele- the ISR γ channel the scale factor ranges from 1 to 2 across the vant to this search is not well described by Monte Carlo programs. values of m Z  . This difference between channels comes from the Therefore, a data-driven technique is used to model the expected number of events in data: the ISR jet channel has 10 times more background in the signal region via a transfer-factor method which events than the ISR γ channel. extrapolates from a control region (CR), defined by inverting the As a cross-check, the TF method is applied to a candidate mass DDT range near the W and Z boson masses: the signal region’s mass jet substructure requirement to τ21 > 0.50. The multi-jet and inclusive γ background estimates are con- range is set as a ±20% window around 85 GeV ([68, 102] GeV), and structed in bins of candidate resonance mass. In each bin, the the validation region as a ±30% window around the same mass, estimate is calculated as ( N CR − N V ) multiplied by the transfer but with the SR removed ([59.5, 68] GeV and [102, 110.5] GeV). factor, where N CR is the number of events in the CR and N V Fig. 2 shows distributions of the large-R jet mass for data and the resulting background estimate. The latter is found to agree is the expected contribution from production with an associated with the data within uncertainties. The SM prediction for W and vector boson estimated from simulated samples, typically around Z production is scaled with the NLO cross section using NLO 1%. The transfer factor (TF) is the expected ratio of events which DDT K -factors, as described in Section 3. The cross sections used are pass the τ21 requirement to events which fail, measured using 40.6 pb (18.6 pb) for the W ( Z )+jets processes in the ISR jet chan- data with m J < (0.8 × m Z  ) or m J > (1.2 × m Z  ), to avoid poten- nel, and 1.52 pb (0.983 pb) for W ( Z )+γ processes in the ISR γ tial contamination from a signal near m Z  . The TF is parameterised channel. These cross sections are taken from the phase space of J in terms of two kinematic quantities, log( p T /μ) and ρ DDT ; it is p T ( W , Z ) > 280 (140) GeV for the jet (photon) channels, as mo- implemented as a two-dimensional histogram, smoothed and in- tivated by the analysis kinematic selections. The best-fit signal terpolated into the signal region using a Gaussian process (GP) strength relative to the SM prediction for W and Z production, regression [54] using a squared exponential or “Gaussian kernel” μ̂ = σ /σW / Z , is μ̂ = 0.93 ± 0.03 (stat) ± 0.24 (syst) in the ISR jet with a characteristic length scale ∝ 1/σ for a Gaussian width σ . channel and μ̂ = 1.07 ± 0.13 (stat) ± 0.35 (syst) in the ISR γ chan- The length scale d along each dimension d of the TF histogram in nel, consistent with the SM predictions. This result shows that the (ρ DDT , log( p T /μ)) is a free parameter, determined by maximising TF method works well. the marginal likelihood given by [55]: The largest systematic uncertainty is due to the estimate of the dominant background using the TF method. The Gaussian pro- n   1 cess regression provides a natural measure of the uncertainty in log L (y | x, { d }) = − log y R { d} (x, x) y − log | R { d} (x, x)| the interpolation, since it yields a mean function value across 2 2 (log( p T /μ), ρ DDT ) and a covariance function cov(x, x ) relating the J where x and y are the measured TF histogram bins with values TF measurements at different (log( p T /μ), ρ DDT ). A 68% confidence scaled to have zero mean and unit variance, n is the number of level uncertainty band, within which the √ true transfer factor is ex- data points, and R { d } (x, x) is the correlation matrix of the TF mea- pected to lie [54], can be obtained as cov(x, x). This uncertainty surements induced by the Gaussian kernel with length scales { d }. band, conditioned on the measurement of the ratio of numbers of The TF values are regularised by the statistical uncertainties on the events in the signal and control regions (N SR / N CR ), is used as the measurements according to Ref. [55]. The first term quantifies the systematic uncertainty on the transfer factor fit. This uncertainty is fit to the measurements, while the second term penalises model tuned using the validation region defined above. The final uncer- complexity (short length scales) [54]. J tainty is approximately 1% of the total multi-jet or inclusive photon The transfer factor is parametrised by (log( p T /μ), ρ DDT ) be- background estimate. DDT DDT cause τ21 is decorrelated from ρ , making the transform fac- The uncertainty in the integrated luminosity is 2.1%; it is de- tor maximally uniform along this variable. In addition, including rived following a methodology similar to that detailed in Ref. [56]. J log( p T /μ) in the parametrisation renders the dependence on the Additional systematic uncertainties stem from the use of simulated jet mass explicit, allowing for the construction of mass-dependent samples for the vector boson associated backgrounds as well as signal region windows. The TF assume values between 0.6 and 1.3 the hypothetical signals. The largest sources of systematic uncer- J across the (log( p T /μ), ρ DDT ) parameter space, in the jet channel, tainty in each channel arise from uncertainties in the calibration while the TF is between 0.5 and 0.9 in the photon channel. The dif- and resolution of the large-R jet energy and mass, as well as the DDT ference in the TF distributions is due to the choice of the common modelling of τ21 [57]; individually these uncertainties range up DDT τ21 > 0.5 cut, which has comparable but not identical background to 10% relative to the signal, but together these uncertainties are acceptances in simulation for the two channels, while the spread less than 1% of the background estimate in the signal region. Addi- in the range is due to discrepancies between data and simulation tional, smaller systematic uncertainties are due to the uncertainty DDT in the parton distribution functions and integrated luminosity. as well as the residual correlation between τ21 and the jet kine- matic parameters. Residual contamination from signal events which leak into the 6. Results control region is accounted for in the statistical analysis as fol- lows: the background estimate and its uncertainty are validated The observed distributions of the large-R jet mass are com- by constructing an interpolation using data with m J < (0.7 × m Z  ) pared with the background estimates in Fig. 3 and Fig. 4 for two or m J > (1.3 × m Z  ), which is then compared to the data ob- representative Z  mass values for the ISR jet and ISR γ channels, served in a validation region (VR) in which m J ∈ [0.7, 0.8]m Z  respectively. The slope in the data and background distributions or m J ∈ [1.2, 1.3]m Z  . If the difference between the data and the changes for a large-R jet mass around 225 GeV (100 GeV) for Fig. 3 J background estimate in the VR is larger than the derived uncer- (Fig. 4), due to the boosted topology requirement, p T > 2 × m J . The J tainty, the uncertainty is inflated by a scale factor, without chang- beginning of this effect is determined by the p T requirements of ing the nominal value of the background estimate. This can happen 450 GeV and 200 GeV for the ISR jet and ISR γ channels, respec- when the background estimate in the VR is derived from a control tively. The observed distributions of the large-R jet mass are well region with fewer events, and is therefore more sensitive to sta- reproduced by the estimated background contributions. tistical fluctuations. For the ISR jet channel, the scale factor in the A binned likelihood function L(μ, θ), constructed as a product background uncertainty is found to be consistent with 1, while for of Poisson probability terms over all bins of the contributions of 320 The ATLAS Collaboration / Physics Letters B 788 (2019) 316–335 Fig. 2. Top: distribution of large-R jet mass near the W and Z boson masses, as a validation of background estimate using the transfer factor described in the text. The vertical dashed lines indicate the signal region (SR) surrounding the target W and Z boson masses. Bottom: residual between data and the estimated background. The distributions are shown for both the (left) jet and (right) photon channels. The contributions from the W and Z backgrounds have been scaled by their best-fit values, as described in the text. In the top panel, the statistical uncertainty is too small to be visible; in the bottom panel it is incorporated into the error bars on the data. Fig. 3. Top: distribution of large-R jet mass in the jet channel for m Z  = 160 GeV (left) and 220 GeV (right). The vertical dashed lines indicate the signal region (SR) surrounding the target Z  mass. The signal is generated with gq = 0.5. Bottom: ratio of data to the estimated background. The background estimate is different for each signal mass hypothesis; more details are given in the text. the background and of a hypothetical signal of strength μ rela- nal contamination in the control region used to define the TF is tive to the benchmark model, is used to set limits. The likelihood accounted for by scaling the best-fit signal strength by the ratio of DDT function is also dependant on θ , a set of nuisance parameters with expected signal events passing the τ21 selection to the expected Gaussian prior distributions encoding the effects of the systematic number of TF-weighted signal events included in the background uncertainties in background and signal predictions. The fit to the estimation, as determined in simulation. Typical values for this large-R jet mass distribution is performed in each mass-dependent scale factor are 0.7 for the ISR jet channel and 0.6 for the ISR γ signal region in both the ISR jet and γ channels. The potential sig- channel. The ATLAS Collaboration / Physics Letters B 788 (2019) 316–335 321 Fig. 4. Top: distribution of large-R jet mass in the photon channel for m Z  = 160 GeV (left) and 220 GeV (right). The vertical dashed lines indicate the signal region (SR) surrounding the target Z  mass. The signal is generated with gq = 0.5. Bottom: ratio of data to the estimated background. The background estimate is different for each signal mass hypothesis; more details are given in the text. The blue triangles indicate bins where the ratio is nonzero and outside the vertical range of the plot. Fig. 5. Observed and expected limits at 95% confidence level on the lepto-phobic axial-vector Z  [30–32] production cross section (σ ) times kinematic acceptance ( A, see text for details) in the ISR jet channel (left) and the ISR γ channel (right). The largest excess is observed in the ISR jet signal region cen- simulation. For the Z  signal model considered in this paper, ac- tred at 150 GeV. Performing a signal-plus-background fit with a Z  ceptance values vary from 0.10% to 0.06% in the ISR jet channel model assumption, the local significance in this region is found to and from 4.0% to 1.0% in the ISR γ channel, in the mass range be- DDT be 2.5σ , corresponding to a global significance of 1.1σ , where the tween 100 and 220 GeV. The efficiency of the τ21 requirement is look-elsewhere effect [58] is calculated with respect to the entire less model dependent but more dependent on accurate modelling DDT mass window examined. The largest positive deviation from the of the τ21 variable in simulated samples. The acceptance times expected background in the ISR γ channel is seen in the signal re- efficiency varies between 0.07%–0.04% (2.6%–0.5%) for the ISR jet gion centred at 140 GeV, with local (global) significance of 2.2σ (ISR γ ) channel over the 100–220 GeV mass interval. (0.8σ ). The observed and expected limits on the coupling gq are shown Upper limits are derived at 95% confidence level on the Z  pro- in Fig. 6, for the combination of the ISR jet and ISR γ channels. duction cross section times acceptance as a function of the Z  mass The narrow width approximation is valid for the gq range tested. between 100 and 220 GeV using profile-likelihood-ratio tests [59] In the combination, the nuisance parameters corresponding to lu- with the CLs method [60], shown in Fig. 5. minosity and large-R jet energy scale and resolution uncertainties The acceptance accounts for all selection criteria except for the are fully correlated between channels, while the background uncer- DDT requirement on τ21 ; it can vary significantly for various theoret- tainties are uncorrelated. The largest deviation is for the 140 GeV ical models, yet can be well estimated without detailed detector signal hypothesis, corresponding to 2.4σ local and 1.2σ global sig- 322 The ATLAS Collaboration / Physics Letters B 788 (2019) 316–335 Table 1 The source of each of the largest uncertainties and their relative impact in the expected signal, quantified by the uncertainty in the best-fit signal strength (μ) over the best-fit signal strength (μ), for hypothesised signal production of Z  with m Z  = 100 GeV, m Z  = 160 GeV and m Z  = 220 GeV. Uncertainty source μ/μ [%] m Z  = 100 GeV m Z  = 160 GeV m Z  = 220 GeV Transfer factor 86 90 88 Large-R jet calib. and modelling 19 25 17 W/Z normalisation 43 1 1 Signal PDF 1 1 1 Luminosity 2 1 1 Total systematic uncertainty 91 93 91 Statistical uncertainty 9 10 11 or jet is presented. The search is based on 36.1 fb−1 of 13 TeV pp collisions recorded by the ATLAS detector at the LHC. Reso- nance candidates are identified as massive large-radius jets with substructure consistent with a quark pair. The mass spectrum of the candidates is examined for local excesses above a data-derived estimate of a smoothly falling background. No evidence of anoma- lous phenomena is observed in the data, and limits are presented on the cross section and couplings of a leptophobic axial-vector Z  benchmark model. Upper limits at 95% confidence level on pro- duction cross sections times acceptance are 0.50 pb (0.04 pb) for a 100 GeV signal hypothesis, and 0.35 pb (0.03 pb) for a 220 GeV signal hypothesis in the ISR jet (ISR γ ) channels. The observed up- per limits on the coupling gq are 0.17 for m Z  = 100 GeV and 0.21 for m Z  = 220 GeV, when combining ISR jet and ISR γ channels. Acknowledgements Fig. 6. Observed and expected limits at 95% confidence level on the coupling (gq ) We thank CERN for the very successful operation of the LHC, from the lepto-phobic axial-vector Z  model [30–32], for the combination of the as well as the support staff from our institutions without whom ISR jet and ISR γ channels. ATLAS could not be operated efficiently. We acknowledge the support of ANPCyT, Argentina; YerPhI, Ar- nificances. The observed upper limits on the coupling gq in the menia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azer- 100–220 GeV Z  mass range are competitive but slightly under- baijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and perform the latest results reported by the CMS experiment [15], CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; partially due to differences in the effect of jet trimming versus COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech soft-drop grooming on relevant large-R jet observables such as jet Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DRF/IRFU, mass. France; SRNSFG, Georgia; BMBF, HGF, and MPG, Germany; GSRT, The effects of systematic uncertainties are studied for hypoth- Greece; RGC, Hong Kong SAR, China; ISF, I-CORE and Benoziyo esised signals using the signal-strength parameter μ. The relative Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Mo- uncertainties in the best-fit μ value from the leading sources of rocco; NWO, Netherlands; RCN, Norway; MNiSW and NCN, Poland; systematic uncertainty are shown in Table 1 for m Z  = 100, 160 FCT, Portugal; MNE/IFA, Romania; MES of Russia and NRC KI, and 220 GeV. The TF systematic uncertainty has the largest impact Russian Federation; JINR; MESTD, Serbia; MSSR, Slovakia; ARRS on the sensitivity, accounting for 86%, 90% and 88% of the total and MIZŠ, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC impact for the 100, 160 and 220 GeV signal hypothesis, respec- and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of tively. The TF uncertainty is larger for the jet channel, due to its Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, smaller length scale of the Gaussian process. For the Z  160 GeV United Kingdom; DOE and NSF, United States of America. In ad- hypothesis, it accounts for 87% of the impact in the signal strength dition, individual groups and members have received support in the ISR jet channel and 61% in the ISR γ channel. The second from BCKDF, the Canada Council, CANARIE, CRC, Compute Canada, biggest impact is due to uncertainties associated with large-R jets. FQRNT, and the Ontario Innovation Trust, Canada; EPLANET, ERC, Ref. [57] details the derivation procedure and the breakdown of ERDF, FP7, Horizon 2020 and Marie Skłodowska-Curie Actions, Eu- those uncertainties. The data’s statistical uncertainty accounts for ropean Union; Investissements d’Avenir Labex and Idex, ANR, Ré- about 10% of the total impact at all mass points considered. It is gion Auvergne and Fondation Partager le Savoir, France; DFG and larger in the ISR γ channel than in the ISR jet channel due to the AvH Foundation, Germany; Herakleitos, Thales and Aristeia pro- order of magnitude difference in the number of events; this ac- grammes co-financed by EU-ESF and the Greek NSRF; BSF, GIF counts for 21% of the impact in the former and 9% in the latter for and Minerva, Israel; BRF, Norway; CERCA Programme Generalitat m Z  = 160 GeV. de Catalunya, Generalitat Valenciana, Spain; the Royal Society and Leverhulme Trust, United Kingdom. 7. 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Chiu 174 , M.V. Chizhov 77 , K. Choi 63 , A.R. Chomont 37 , S. Chouridou 160 , Y.S. Chow 61a , V. Christodoulou 92 , M.C. Chu 61a , J. Chudoba 137 , A.J. Chuinard 101 , J.J. Chwastowski 82 , L. Chytka 126 , A.K. Ciftci 4a , D. Cinca 45 , V. Cindro 89 , I.A. Cioară 24 , A. Ciocio 18 , F. Cirotto 67a,67b , Z.H. Citron 178 , M. Citterio 66a , M. Ciubancan 27b , A. Clark 52 , M.R. Clark 38 , P.J. Clark 48 , R.N. Clarke 18 , C. Clement 43a,43b , Y. Coadou 99 , M. Cobal 64a,64c , A. Coccaro 52 , J. Cochran 76 , L. Colasurdo 117 , B. Cole 38 , A.P. Colijn 118 , J. Collot 56 , T. Colombo 169 , P. Conde Muiño 136a,136b , E. Coniavitis 50 , S.H. Connell 32b , I.A. Connelly 98 , S. Constantinescu 27b , G. Conti 35 , F. Conventi 67a,av , M. Cooke 18 , A.M. Cooper-Sarkar 131 , F. Cormier 173 , K.J.R. Cormier 165 , M. Corradi 70a,70b , E.E. Corrigan 94 , F. Corriveau 101,ae , A. Cortes-Gonzalez 35 , G. Costa 66a , M.J. Costa 172 , D. Costanzo 146 , G. Cottin 31 , G. Cowan 91 , B.E. Cox 98 , K. 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Forcolin 98 , A. Formica 142 , F.A. Förster 14 , A.C. Forti 98 , A.G. Foster 21 , D. Fournier 128 , H. Fox 87 , S. Fracchia 146 , P. Francavilla 69a,69b , M. Franchini 23b,23a , S. Franchino 59a , D. Francis 35 , L. Franconi 130 , M. Franklin 57 , M. Frate 169 , M. Fraternali 68a,68b , D. Freeborn 92 , S.M. Fressard-Batraneanu 35 , B. Freund 107 , W.S. Freund 78b , D. Froidevaux 35 , J.A. Frost 131 , C. Fukunaga 162 , T. Fusayasu 114 , J. Fuster 172 , O. Gabizon 158 , A. Gabrielli 23b,23a , A. Gabrielli 18 , G.P. Gach 81a , S. Gadatsch 35 , S. Gadomski 52 , G. Gagliardi 53b,53a , L.G. Gagnon 107 , C. Galea 117 , B. Galhardo 136a,136c , E.J. Gallas 131 , B.J. Gallop 141 , P. Gallus 138 , G. Galster 39 , K.K. Gan 122 , S. Ganguly 37 , Y. Gao 88 , Y.S. Gao 150,m , C. García 172 , J.E. García Navarro 172 , J.A. García Pascual 15a , M. Garcia-Sciveres 18 , R.W. Gardner 36 , N. Garelli 150 , V. Garonne 130 , A. Gascon Bravo 44 , K. Gasnikova 44 , C. Gatti 49 , A. Gaudiello 53b,53a , G. 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Gomes 136a,136b,136d , R. Goncalves Gama 78b , J. Goncalves Pinto Firmino Da Costa 142 , R. Gonçalo 136a , G. Gonella 50 , L. Gonella 21 , A. Gongadze 77 , F. Gonnella 21 , J.L. Gonski 57 , S. González de la Hoz 172 , S. Gonzalez-Sevilla 52 , L. Goossens 35 , P.A. Gorbounov 109 , H.A. Gordon 29 , B. Gorini 35 , E. Gorini 65a,65b , A. Gorišek 89 , A.T. Goshaw 47 , C. Gössling 45 , M.I. Gostkin 77 , C.A. Gottardo 24 , C.R. Goudet 128 , D. Goujdami 34c , A.G. Goussiou 145 , N. Govender 32b,c , C. Goy 5 , E. Gozani 158 , I. Grabowska-Bold 81a , P.O.J. Gradin 170 , E.C. Graham 88 , J. Gramling 169 , E. Gramstad 130 , S. Grancagnolo 19 , V. Gratchev 134 , P.M. Gravila 27f , C. Gray 55 , H.M. Gray 18 , Z.D. Greenwood 93,aj , C. Grefe 24 , K. Gregersen 92 , I.M. Gregor 44 , P. Grenier 150 , K. Grevtsov 5 , J. Griffiths 8 , A.A. Grillo 143 , K. Grimm 87 , S. Grinstein 14,z , Ph. Gris 37 , J.-F. Grivaz 128 , S. Groh 97 , E. Gross 178 , J. Grosse-Knetter 51 , G.C. Grossi 93 , Z.J. Grout 92 , A. Grummer 116 , L. Guan 103 , W. Guan 179 , J. Guenther 35 , F. Guescini 166a , D. Guest 169 , O. Gueta 159 , B. Gui 122 , E. Guido 53b,53a , T. Guillemin 5 , The ATLAS Collaboration / Physics Letters B 788 (2019) 316–335 327 S. Guindon 35 , U. Gul 55 , C. Gumpert 35 , J. Guo 58c , W. Guo 103 , Y. Guo 58a,t , R. Gupta 41 , S. Gurbuz 12c , G. Gustavino 124 , B.J. Gutelman 158 , P. Gutierrez 124 , N.G. Gutierrez Ortiz 92 , C. Gutschow 92 , C. Guyot 142 , M.P. Guzik 81a , C. Gwenlan 131 , C.B. Gwilliam 88 , A. Haas 121 , C. Haber 18 , H.K. Hadavand 8 , N. Haddad 34e , A. Hadef 99 , S. Hageböck 24 , M. Hagihara 167 , H. Hakobyan 182,∗ , M. Haleem 44 , J. Haley 125 , G. Halladjian 104 , G.D. Hallewell 99 , K. Hamacher 180 , P. Hamal 126 , K. Hamano 174 , A. Hamilton 32a , G.N. Hamity 146 , P.G. Hamnett 44 , K. Han 58a,ai , L. Han 58a , S. Han 15d , K. Hanagaki 79,w , K. Hanawa 161 , M. Hance 143 , D.M. Handl 112 , B. Haney 133 , R. Hankache 132 , P. Hanke 59a , J.B. Hansen 39 , J.D. 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Hetherly 41 , S. Higashino 79 , E. Higón-Rodriguez 172 , K. Hildebrand 36 , E. Hill 174 , J.C. Hill 31 , K.H. Hiller 44 , S.J. Hillier 21 , M. Hils 46 , I. Hinchliffe 18 , M. Hirose 50 , D. Hirschbuehl 180 , B. Hiti 89 , O. Hladik 137 , D.R. Hlaluku 32c , X. Hoad 48 , J. Hobbs 152 , N. Hod 166a , M.C. Hodgkinson 146 , P. Hodgson 146 , A. Hoecker 35 , M.R. Hoeferkamp 116 , F. Hoenig 112 , D. Hohn 24 , T.R. Holmes 36 , M. Holzbock 112 , M. Homann 45 , S. Honda 167 , T. Honda 79 , T.M. Hong 135 , B.H. Hooberman 171 , W.H. Hopkins 127 , Y. Horii 115 , A.J. Horton 149 , J-Y. Hostachy 56 , A. Hostiuc 145 , S. Hou 155 , A. Hoummada 34a , J. Howarth 98 , J. Hoya 86 , M. Hrabovsky 126 , J. Hrdinka 35 , I. Hristova 19 , J. Hrivnac 128 , A. Hrynevich 106 , T. Hryn’ova 5 , P.J. Hsu 62 , S.-C. Hsu 145 , Q. Hu 29 , S. Hu 58c , Y. Huang 15a , Z. Hubacek 138 , F. Hubaut 99 , F. Huegging 24 , T.B. Huffman 131 , E.W. Hughes 38 , M. Huhtinen 35 , R.F.H. Hunter 33 , P. Huo 152 , N. Huseynov 77,ag , J. 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Lafaye 5 , B. Laforge 132 , S. Lai 51 , S. Lammers 63 , W. Lampl 7 , E. Lançon 29 , U. Landgraf 50 , M.P.J. Landon 90 , M.C. Lanfermann 52 , V.S. Lang 44 , J.C. Lange 14 , R.J. Langenberg 35 , A.J. Lankford 169 , F. Lanni 29 , K. Lantzsch 24 , A. Lanza 68a , A. Lapertosa 53b,53a , S. Laplace 132 , J.F. Laporte 142 , T. Lari 66a , F. Lasagni Manghi 23b,23a , M. Lassnig 35 , T.S. Lau 61a , P. Laurelli 49 , W. Lavrijsen 18 , A.T. Law 143 , P. Laycock 88 , T. Lazovich 57 , M. Lazzaroni 66a,66b , B. Le 102 , O. Le Dortz 132 , E. Le Guirriec 99 , E.P. Le Quilleuc 142 , M. LeBlanc 7 , T. LeCompte 6 , F. Ledroit-Guillon 56 , C.A. Lee 29 , G.R. Lee 144a , L. Lee 57 , S.C. Lee 155 , B. Lefebvre 101 , G. Lefebvre 132 , M. Lefebvre 174 , F. Legger 112 , C. Leggett 18 , G. Lehmann Miotto 35 , X. Lei 7 , W.A. Leight 44 , M.A.L. Leite 78d , R. Leitner 139 , D. Lellouch 178 , B. Lemmer 51 , K.J.C. Leney 92 , T. Lenz 24 , B. Lenzi 35 , R. Leone 7 , S. Leone 69a , C. Leonidopoulos 48 , G. 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Lokajicek 137 , B.A. Long 25 , J.D. Long 171 , R.E. Long 87 , L. Longo 65a,65b , K.A. Looper 122 , J.A. Lopez 144b , I. Lopez Paz 14 , A. Lopez Solis 132 , J. Lorenz 112 , N. Lorenzo Martinez 5 , M. Losada 22 , P.J. Lösel 112 , X. Lou 15a , A. Lounis 128 , J. Love 6 , P.A. Love 87 , H. Lu 61a , N. Lu 103 , Y.J. Lu 62 , H.J. Lubatti 145 , C. Luci 70a,70b , A. Lucotte 56 , C. Luedtke 50 , F. Luehring 63 , W. Lukas 74 , L. Luminari 70a , B. Lund-Jensen 151 , M.S. Lutz 100 , P.M. Luzi 132 , D. Lynn 29 , R. Lysak 137 , E. Lytken 94 , F. Lyu 15a , V. Lyubushkin 77 , H. Ma 29 , L.L. Ma 58b , Y. Ma 58b , G. Maccarrone 49 , A. Macchiolo 113 , C.M. Macdonald 146 , J. Machado Miguens 133,136b , D. Madaffari 172 , R. Madar 37 , W.F. Mader 46 , A. Madsen 44 , N. Madysa 46 , J. Maeda 80 , S. Maeland 17 , T. Maeno 29 , A.S. Maevskiy 111 , V. Magerl 50 , C. Maiani 128 , C. Maidantchik 78b , T. Maier 112 , A. Maio 136a,136b,136d , O. Majersky 28a , S. Majewski 127 , Y. Makida 79 , N. Makovec 128 , B. Malaescu 132 , Pa. Malecki 82 , V.P. Maleev 134 , F. Malek 56 , U. Mallik 75 , D. Malon 6 , C. Malone 31 , S. Maltezos 10 , S. Malyukov 35 , J. Mamuzic 172 , G. Mancini 49 , I. Mandić 89 , J. Maneira 136a,136b , L. Manhaes de Andrade Filho 78a , J. Manjarres Ramos 46 , K.H. Mankinen 94 , A. Mann 112 , A. Manousos 35 , B. Mansoulie 142 , J.D. Mansour 15a , R. Mantifel 101 , M. Mantoani 51 , S. Manzoni 66a,66b , L. Mapelli 35 , G. Marceca 30 , L. March 52 , L. Marchese 131 , G. Marchiori 132 , M. Marcisovsky 137 , C.A. Marin Tobon 35 , M. Marjanovic 37 , D.E. Marley 103 , F. Marroquim 78b , S.P. Marsden 98 , Z. Marshall 18 , M.U.F Martensson 170 , S. Marti-Garcia 172 , C.B. Martin 122 , T.A. Martin 176 , V.J. Martin 48 , B. Martin dit Latour 17 , M. Martinez 14,z , V.I. Martinez Outschoorn 171 , S. Martin-Haugh 141 , V.S. Martoiu 27b , A.C. Martyniuk 92 , A. Marzin 35 , L. Masetti 97 , T. Mashimo 161 , R. Mashinistov 108 , J. Masik 98 , A.L. Maslennikov 120b,120a , L.H. Mason 102 , L. 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Odaka 79 , A. Oh 98 , S.H. Oh 47 , C.C. Ohm 151 , H. Ohman 170 , H. Oide 53b,53a , H. Okawa 167 , Y. Okumura 161 , T. Okuyama 79 , A. Olariu 27b , L.F. Oleiro Seabra 136a , S.A. Olivares Pino 144a , D. Oliveira Damazio 29 , M.J.R. Olsson 36 , A. Olszewski 82 , J. Olszowska 82 , D.C. O’Neil 149 , A. Onofre 136a,136e , K. Onogi 115 , P.U.E. Onyisi 11 , H. Oppen 130 , M.J. Oreglia 36 , Y. Oren 159 , D. Orestano 72a,72b , E.C. Orgill 98 , N. Orlando 61b , A.A. O’Rourke 44 , R.S. Orr 165 , B. Osculati 53b,53a,∗ , V. O’Shea 55 , R. Ospanov 58a , G. Otero y Garzon 30 , H. Otono 85 , M. Ouchrif 34d , F. Ould-Saada 130 , A. Ouraou 142 , K.P. Oussoren 118 , Q. Ouyang 15a , M. Owen 55 , R.E. Owen 21 , V.E. Ozcan 12c , N. Ozturk 8 , K. Pachal 149 , A. Pacheco Pages 14 , L. Pacheco Rodriguez 142 , C. Padilla Aranda 14 , S. Pagan Griso 18 , M. Paganini 181 , F. Paige 29 , G. Palacino 63 , S. Palazzo 40b,40a , S. Palestini 35 , M. Palka 81b , D. Pallin 37 , E.St. Panagiotopoulou 10 , I. Panagoulias 10 , C.E. Pandini 52 , J.G. Panduro Vazquez 91 , P. Pani 35 , S. Panitkin 29 , D. Pantea 27b , L. Paolozzi 52 , T.D. Papadopoulou 10 , K. Papageorgiou 9,j , A. Paramonov 6 , D. Paredes Hernandez 181 , A.J. Parker 87 , K.A. Parker 44 , M.A. Parker 31 , F. Parodi 53b,53a , J.A. Parsons 38 , U. Parzefall 50 , V.R. Pascuzzi 165 , J.M.P. Pasner 143 , E. Pasqualucci 70a , S. Passaggio 53b , F. Pastore 91 , S. Pataraia 97 , J.R. Pater 98 , T. Pauly 35 , B. Pearson 113 , S. Pedraza Lopez 172 , R. Pedro 136a,136b , S.V. Peleganchuk 120b,120a , O. Penc 137 , C. Peng 15d , H. Peng 58a , J. Penwell 63 , B.S. Peralva 78a , M.M. Perego 142 , D.V. Perepelitsa 29 , F. Peri 19 , L. Perini 66a,66b , H. Pernegger 35 , S. Perrella 67a,67b , R. Peschke 44 , V.D. Peshekhonov 77,∗ , K. Peters 44 , R.F.Y. Peters 98 , B.A. Petersen 35 , T.C. Petersen 39 , E. Petit 56 , A. Petridis 1 , C. Petridou 160 , P. Petroff 128 , E. 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Pozo Astigarraga 35 , P. Pralavorio 99 , A. Pranko 18 , S. Prell 76 , D. Price 98 , M. Primavera 65a , S. Prince 101 , N. Proklova 110 , K. Prokofiev 61c , F. Prokoshin 144b , S. Protopopescu 29 , J. Proudfoot 6 , M. Przybycien 81a , A. Puri 171 , P. Puzo 128 , J. Qian 103 , Y. Qin 98 , A. Quadt 51 , M. Queitsch-Maitland 44 , D. Quilty 55 , S. Raddum 130 , V. Radeka 29 , V. Radescu 131 , S.K. Radhakrishnan 152 , P. Radloff 127 , P. Rados 102 , F. Ragusa 66a,66b , G. Rahal 95 , J.A. Raine 98 , S. Rajagopalan 29 , C. Rangel-Smith 170 , T. Rashid 128 , S. Raspopov 5 , M.G. Ratti 66a,66b , D.M. Rauch 44 , F. Rauscher 112 , S. Rave 97 , I. Ravinovich 178 , J.H. Rawling 98 , M. Raymond 35 , A.L. Read 130 , N.P. Readioff 56 , M. Reale 65a,65b , D.M. Rebuzzi 68a,68b , A. Redelbach 175 , G. Redlinger 29 , R. Reece 143 , R.G. Reed 32c , K. Reeves 42 , L. Rehnisch 19 , J. Reichert 133 , A. Reiss 97 , C. Rembser 35 , H. Ren 15d , M. Rescigno 70a , S. Resconi 66a , E.D. Resseguie 133 , S. Rettie 173 , E. Reynolds 21 , O.L. Rezanova 120b,120a , P. Reznicek 139 , R. Rezvani 107 , R. Richter 113 , S. Richter 92 , E. Richter-Was 81b , O. Ricken 24 , M. Ridel 132 , P. Rieck 113 , C.J. Riegel 180 , J. Rieger 51 , O. Rifki 124 , M. Rijssenbeek 152 , A. Rimoldi 68a,68b , M. Rimoldi 20 , L. Rinaldi 23b , G. Ripellino 151 , B. Ristić 35 , E. Ritsch 35 , I. Riu 14 , F. Rizatdinova 125 , E. Rizvi 90 , C. Rizzi 14 , R.T. Roberts 98 , S.H. Robertson 101,ae , A. Robichaud-Veronneau 101 , D. Robinson 31 , J.E.M. Robinson 44 , A. Robson 55 , E. Rocco 97 , C. Roda 69a,69b , Y. Rodina 99,aa , S. Rodriguez Bosca 172 , A. Rodriguez Perez 14 , D. Rodriguez Rodriguez 172 , S. Roe 35 , C.S. Rogan 57 , O. Røhne 130 , J. Roloff 57 , A. Romaniouk 110 , M. Romano 23b,23a , S.M. Romano Saez 37 , E. Romero Adam 172 , N. Rompotis 88 , M. Ronzani 50 , L. Roos 132 , S. Rosati 70a , K. Rosbach 50 , P. Rose 143 , N-A. Rosien 51 , E. Rossi 67a,67b , L.P. Rossi 53b , J.H.N. Rosten 31 , R. Rosten 145 , M. 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Sandhoff 180 , C. Sandoval 22 , D.P.C. Sankey 141 , M. Sannino 53b,53a , Y. Sano 115 , A. Sansoni 49 , C. Santoni 37 , H. Santos 136a , I. Santoyo Castillo 153 , A. Sapronov 77 , J.G. Saraiva 136a,136d , O. Sasaki 79 , K. Sato 167 , E. Sauvan 5 , G. Savage 91 , P. Savard 165,au , N. Savic 113 , C. Sawyer 141 , L. Sawyer 93,aj , C. Sbarra 23b , A. Sbrizzi 23b,23a , T. Scanlon 92 , D.A. Scannicchio 169 , J. Schaarschmidt 145 , P. Schacht 113 , B.M. Schachtner 112 , D. Schaefer 36 , L. Schaefer 133 , J. Schaeffer 97 , S. Schaepe 35 , S. Schaetzel 59b , U. Schäfer 97 , A.C. Schaffer 128 , D. Schaile 112 , R.D. Schamberger 152 , V.A. Schegelsky 134 , D. Scheirich 139 , F. Schenck 19 , M. Schernau 169 , C. Schiavi 53b,53a , S. Schier 143 , L.K. Schildgen 24 , C. Schillo 50 , M. Schioppa 40b,40a , S. Schlenker 35 , K.R. Schmidt-Sommerfeld 113 , K. Schmieden 35 , C. Schmitt 97 , S. Schmitt 44 , S. Schmitz 97 , U. Schnoor 50 , L. Schoeffel 142 , A. Schoening 59b , B.D. Schoenrock 104 , E. Schopf 24 , M. Schott 97 , J.F.P. Schouwenberg 117 , J. Schovancova 35 , S. Schramm 52 , N. Schuh 97 , A. Schulte 97 , M.J. Schultens 24 , H-C. Schultz-Coulon 59a , M. Schumacher 50 , B.A. Schumm 143 , Ph. Schune 142 , A. Schwartzman 150 , T.A. Schwarz 103 , H. Schweiger 98 , Ph. Schwemling 142 , R. Schwienhorst 104 , A. Sciandra 24 , G. Sciolla 26 , M. Scornajenghi 40b,40a , F. Scuri 69a , F. Scutti 102 , J. Searcy 103 , P. Seema 24 , S.C. Seidel 116 , A. Seiden 143 , J.M. Seixas 78b , G. Sekhniaidze 67a , K. Sekhon 103 , S.J. Sekula 41 , N. Semprini-Cesari 23b,23a , S. Senkin 37 , C. Serfon 130 , L. Serin 128 , L. Serkin 64a,64b , M. Sessa 72a,72b , R. Seuster 174 , H. Severini 124 , F. Sforza 168 , A. Sfyrla 52 , E. Shabalina 51 , N.W. Shaikh 43a,43b , L.Y. Shan 15a , R. Shang 171 , J.T. Shank 25 , M. Shapiro 18 , P.B. Shatalov 109 , K. Shaw 64a,64b , S.M. Shaw 98 , A. Shcherbakova 43a,43b , C.Y. Shehu 153 , Y. Shen 124 , The ATLAS Collaboration / Physics Letters B 788 (2019) 316–335 331 N. Sherafati 33 , A.D. Sherman 25 , P. Sherwood 92 , L. Shi 155,aq , S. Shimizu 80 , C.O. Shimmin 181 , M. Shimojima 114 , I.P.J. Shipsey 131 , S. Shirabe 85 , M. Shiyakova 77 , J. Shlomi 178 , A. Shmeleva 108 , D. Shoaleh Saadi 107 , M.J. Shochet 36 , S. Shojaii 102 , D.R. Shope 124 , S. Shrestha 122 , E. Shulga 110 , M.A. Shupe 7 , P. Sicho 137 , A.M. Sickles 171 , P.E. Sidebo 151 , E. Sideras Haddad 32c , O. Sidiropoulou 175 , A. Sidoti 23b,23a , F. Siegert 46 , Dj. Sijacki 16 , J. Silva 136a,136d , M. Silva Jr. 179 , S.B. Silverstein 43a , V. Simak 138 , L. Simic 77 , S. Simion 128 , E. Simioni 97 , B. Simmons 92 , M. Simon 97 , P. Sinervo 165 , N.B. Sinev 127 , M. Sioli 23b,23a , G. Siragusa 175 , I. Siral 103 , S.Yu. Sivoklokov 111 , J. Sjölin 43a,43b , M.B. Skinner 87 , P. Skubic 124 , M. Slater 21 , T. Slavicek 138 , M. Slawinska 82 , K. Sliwa 168 , R. Slovak 139 , V. Smakhtin 178 , B.H. Smart 5 , J. Smiesko 28a , N. Smirnov 110 , S.Yu. Smirnov 110 , Y. Smirnov 110 , L.N. Smirnova 111 , O. Smirnova 94 , J.W. Smith 51 , M.N.K. Smith 38 , R.W. Smith 38 , M. Smizanska 87 , K. Smolek 138 , A.A. Snesarev 108 , I.M. Snyder 127 , S. Snyder 29 , R. Sobie 174,ae , F. Socher 46 , A. Soffer 159 , A. Søgaard 48 , D.A. Soh 155 , G. Sokhrannyi 89 , C.A. Solans Sanchez 35 , M. Solar 138 , E.Yu. Soldatov 110 , U. Soldevila 172 , A.A. Solodkov 140 , A. Soloshenko 77 , O.V. Solovyanov 140 , V. Solovyev 134 , P. Sommer 146 , H. Son 168 , A. Sopczak 138 , D. Sosa 59b , C.L. Sotiropoulou 69a,69b , S. Sottocornola 68a,68b , R. Soualah 64a,64c,i , A.M. Soukharev 120b,120a , D. South 44 , B.C. Sowden 91 , S. Spagnolo 65a,65b , M. Spalla 69a,69b , M. Spangenberg 176 , F. Spanò 91 , D. Sperlich 19 , F. Spettel 113 , T.M. Spieker 59a , R. Spighi 23b , G. Spigo 35 , L.A. Spiller 102 , M. Spousta 139 , R.D. St. Denis 55,∗ , A. Stabile 66a,66b , R. Stamen 59a , S. Stamm 19 , E. Stanecka 82 , R.W. Stanek 6 , C. Stanescu 72a , M.M. Stanitzki 44 , B. Stapf 118 , S. Stapnes 130 , E.A. Starchenko 140 , G.H. Stark 36 , J. Stark 56 , S.H Stark 39 , P. Staroba 137 , P. Starovoitov 59a , S. Stärz 35 , R. Staszewski 82 , M. Stegler 44 , P. Steinberg 29 , B. Stelzer 149 , H.J. Stelzer 35 , O. Stelzer-Chilton 166a , H. Stenzel 54 , T.J. Stevenson 90 , G.A. Stewart 55 , M.C. Stockton 127 , M. Stoebe 101 , G. Stoicea 27b , P. Stolte 51 , S. Stonjek 113 , A.R. Stradling 8 , A. Straessner 46 , M.E. Stramaglia 20 , J. Strandberg 151 , S. Strandberg 43a,43b , M. Strauss 124 , P. Strizenec 28b , R. Ströhmer 175 , D.M. Strom 127 , R. Stroynowski 41 , A. Strubig 48 , S.A. Stucci 29 , B. Stugu 17 , N.A. Styles 44 , D. Su 150 , J. Su 135 , S. Suchek 59a , Y. Sugaya 129 , M. Suk 138 , V.V. Sulin 108 , D.M.S. Sultan 73a,73b , S. Sultansoy 4c , T. Sumida 83 , S. Sun 57 , X. Sun 3 , K. Suruliz 153 , C.J.E. Suster 154 , M.R. Sutton 153 , S. Suzuki 79 , M. Svatos 137 , M. Swiatlowski 36 , S.P. Swift 2 , I. Sykora 28a , T. Sykora 139 , D. Ta 50 , K. Tackmann 44,ab , J. Taenzer 159 , A. Taffard 169 , R. Tafirout 166a , E. Tahirovic 90 , N. Taiblum 159 , H. Takai 29 , R. Takashima 84 , E.H. Takasugi 113 , K. Takeda 80 , T. Takeshita 147 , Y. Takubo 79 , M. Talby 99 , A.A. Talyshev 120b,120a , J. Tanaka 161 , M. Tanaka 163 , R. Tanaka 128 , R. Tanioka 80 , B.B. Tannenwald 122 , S. Tapia Araya 144b , S. Tapprogge 97 , S. Tarem 158 , G.F. Tartarelli 66a , P. Tas 139 , M. Tasevsky 137 , T. Tashiro 83 , E. Tassi 40b,40a , A. Tavares Delgado 136a,136b , Y. Tayalati 34e , A.C. Taylor 116 , A.J. Taylor 48 , G.N. Taylor 102 , P.T.E. Taylor 102 , W. Taylor 166b , P. Teixeira-Dias 91 , D. Temple 149 , H. Ten Kate 35 , P.K. Teng 155 , J.J. Teoh 129 , F. Tepel 180 , S. Terada 79 , K. Terashi 161 , J. Terron 96 , S. Terzo 14 , M. Testa 49 , R.J. Teuscher 165,ae , S.J. Thais 181 , T. Theveneaux-Pelzer 99 , F. Thiele 39 , J.P. Thomas 21 , J. Thomas-Wilsker 91 , A.S. Thompson 55 , P.D. Thompson 21 , L.A. Thomsen 181 , E. Thomson 133 , Y. Tian 38 , M.J. Tibbetts 18 , R.E. Ticse Torres 51 , V.O. Tikhomirov 108,am , Yu.A. Tikhonov 120b,120a , S. Timoshenko 110 , P. Tipton 181 , S. Tisserant 99 , K. Todome 163 , S. Todorova-Nova 5 , S. Todt 46 , J. Tojo 85 , S. Tokár 28a , K. Tokushuku 79 , E. Tolley 122 , L. Tomlinson 98 , M. Tomoto 115 , L. Tompkins 150,r , K. Toms 116 , B. Tong 57 , P. Tornambe 50 , E. Torrence 127 , H. Torres 46 , E. Torró Pastor 145 , J. Toth 99,ad , F. Touchard 99 , D.R. Tovey 146 , C.J. Treado 121 , T. Trefzger 175 , F. Tresoldi 153 , A. Tricoli 29 , I.M. Trigger 166a , S. Trincaz-Duvoid 132 , M.F. Tripiana 14 , W. Trischuk 165 , B. Trocmé 56 , A. Trofymov 44 , C. Troncon 66a , M. Trovatelli 174 , L. Truong 32b , M. Trzebinski 82 , A. Trzupek 82 , K.W. Tsang 61a , J.C-L. Tseng 131 , P.V. Tsiareshka 105 , N. Tsirintanis 9 , S. Tsiskaridze 14 , V. Tsiskaridze 50 , E.G. Tskhadadze 157a , I.I. Tsukerman 109 , V. Tsulaia 18 , S. Tsuno 79 , D. Tsybychev 152 , Y. Tu 61b , A. Tudorache 27b , V. Tudorache 27b , T.T. Tulbure 27a , A.N. Tuna 57 , S. Turchikhin 77 , D. Turgeman 178 , I. Turk Cakir 4b,v , R. Turra 66a , P.M. Tuts 38 , G. Ucchielli 23b,23a , I. Ueda 79 , M. Ughetto 43a,43b , F. Ukegawa 167 , G. Unal 35 , A. Undrus 29 , G. Unel 169 , F.C. Ungaro 102 , Y. Unno 79 , K. Uno 161 , J. Urban 28b , P. Urquijo 102 , P. Urrejola 97 , G. Usai 8 , J. Usui 79 , L. Vacavant 99 , V. Vacek 138 , B. Vachon 101 , K.O.H. Vadla 130 , A. Vaidya 92 , C. Valderanis 112 , E. Valdes Santurio 43a,43b , M. Valente 52 , S. Valentinetti 23b,23a , A. Valero 172 , L. Valéry 14 , A. Vallier 5 , J.A. Valls Ferrer 172 , W. Van Den Wollenberg 118 , H. Van der Graaf 118 , P. Van Gemmeren 6 , J. Van Nieuwkoop 149 , I. Van Vulpen 118 , M.C. van Woerden 118 , M. Vanadia 71a,71b , W. Vandelli 35 , A. Vaniachine 164 , P. Vankov 118 , G. Vardanyan 182 , R. Vari 70a , E.W. Varnes 7 , C. Varni 53b,53a , T. Varol 41 , D. Varouchas 128 , 332 The ATLAS Collaboration / Physics Letters B 788 (2019) 316–335 A. Vartapetian 8 , K.E. Varvell 154 , G.A. Vasquez 144b , J.G. Vasquez 181 , F. Vazeille 37 , D. Vazquez Furelos 14 , T. Vazquez Schroeder 101 , J. Veatch 51 , V. Veeraraghavan 7 , L.M. Veloce 165 , F. Veloso 136a,136c , S. Veneziano 70a , A. Ventura 65a,65b , M. Venturi 174 , N. Venturi 35 , V. Vercesi 68a , M. Verducci 72a,72b , W. Verkerke 118 , A.T. Vermeulen 118 , J.C. Vermeulen 118 , M.C. Vetterli 149,au , N. Viaux Maira 144b , O. Viazlo 94 , I. Vichou 171,∗ , T. Vickey 146 , O.E. Vickey Boeriu 146 , G.H.A. Viehhauser 131 , S. Viel 18 , L. Vigani 131 , M. Villa 23b,23a , M. Villaplana Perez 66a,66b , E. Vilucchi 49 , M.G. Vincter 33 , V.B. Vinogradov 77 , A. Vishwakarma 44 , C. Vittori 23b,23a , I. Vivarelli 153 , S. Vlachos 10 , M. Vogel 180 , P. Vokac 138 , G. Volpi 14 , S.E. von Buddenbrock 32c , H. von der Schmitt 113 , E. Von Toerne 24 , V. Vorobel 139 , K. Vorobev 110 , M. Vos 172 , R. Voss 35 , J.H. Vossebeld 88 , N. Vranjes 16 , M. Vranjes Milosavljevic 16 , V. Vrba 138 , M. Vreeswijk 118 , T. Šfiligoj 89 , R. Vuillermet 35 , I. Vukotic 36 , T. Ženiš 28a , L. Živković 16 , P. Wagner 24 , W. Wagner 180 , J. Wagner-Kuhr 112 , H. Wahlberg 86 , S. Wahrmund 46 , K. Wakamiya 80 , J. Walder 87 , R. Walker 112 , W. Walkowiak 148 , V. Wallangen 43a,43b , C. Wang 15c , C. Wang 58b,e , F. Wang 179 , H. Wang 18 , H. Wang 3 , J. Wang 154 , J. Wang 44 , Q. Wang 124 , R.-J. Wang 132 , R. Wang 6 , S.M. Wang 155 , T. Wang 38 , W. Wang 155,p , W.X. Wang 58a,af , Z. Wang 58c , C. Wanotayaroj 44 , A. Warburton 101 , C.P. Ward 31 , D.R. Wardrope 92 , A. Washbrook 48 , P.M. Watkins 21 , A.T. Watson 21 , M.F. Watson 21 , G. Watts 145 , S. Watts 98 , B.M. Waugh 92 , A.F. Webb 11 , S. Webb 97 , M.S. Weber 20 , S.A. Weber 33 , S.M. Weber 59a , S.W. Weber 175 , J.S. Webster 6 , A.R. Weidberg 131 , B. Weinert 63 , J. Weingarten 51 , M. Weirich 97 , C. Weiser 50 , P.S. Wells 35 , T. Wenaus 29 , T. Wengler 35 , S. Wenig 35 , N. Wermes 24 , M.D. Werner 76 , P. Werner 35 , M. Wessels 59a , T.D. Weston 20 , K. Whalen 127 , N.L. Whallon 145 , A.M. Wharton 87 , A.S. White 103 , A. White 8 , M.J. White 1 , R. White 144b , D. Whiteson 169 , B.W. Whitmore 87 , F.J. Wickens 141 , W. Wiedenmann 179 , M. Wielers 141 , C. Wiglesworth 39 , L.A.M. Wiik-Fuchs 50 , A. Wildauer 113 , F. Wilk 98 , H.G. Wilkens 35 , H.H. Williams 133 , S. Williams 31 , C. Willis 104 , S. Willocq 100 , J.A. Wilson 21 , I. Wingerter-Seez 5 , E. Winkels 153 , F. Winklmeier 127 , O.J. Winston 153 , B.T. Winter 24 , M. Wittgen 150 , M. Wobisch 93 , A. Wolf 97 , T.M.H. Wolf 118 , R. Wolff 99 , M.W. Wolter 82 , H. Wolters 136a,136c , V.W.S. Wong 173 , N.L. Woods 143 , S.D. Worm 21 , B.K. Wosiek 82 , J. Wotschack 35 , K.W. Woźniak 82 , M. Wu 36 , S.L. Wu 179 , X. Wu 52 , Y. Wu 103 , T.R. Wyatt 98 , B.M. Wynne 48 , S. Xella 39 , Z. Xi 103 , L. Xia 15b , D. Xu 15a , L. Xu 29 , T. Xu 142 , W. Xu 103 , B. Yabsley 154 , S. Yacoob 32a , D. Yamaguchi 163 , Y. Yamaguchi 163 , A. Yamamoto 79 , S. Yamamoto 161 , T. Yamanaka 161 , F. Yamane 80 , M. Yamatani 161 , T. Yamazaki 161 , Y. Yamazaki 80 , Z. Yan 25 , H.J. Yang 58c,58d , H.T. Yang 18 , Y. Yang 155 , Z. Yang 17 , W-M. Yao 18 , Y.C. Yap 44 , Y. Yasu 79 , E. Yatsenko 5 , K.H. Yau Wong 24 , J. Ye 41 , S. Ye 29 , I. Yeletskikh 77 , E. Yigitbasi 25 , E. Yildirim 97 , K. Yorita 177 , K. Yoshihara 133 , C.J.S. Young 35 , C. Young 150 , J. Yu 8 , J. Yu 76 , S.P.Y. Yuen 24 , I. Yusuff 31,a , B. Zabinski 82 , G. Zacharis 10 , R. Zaidan 14 , A.M. Zaitsev 140,al , N. Zakharchuk 44 , J. Zalieckas 17 , A. Zaman 152 , S. Zambito 57 , D. Zanzi 102 , C. Zeitnitz 180 , G. Zemaityte 131 , A. Zemla 81a , J.C. Zeng 171 , Q. Zeng 150 , O. Zenin 140 , D. Zerwas 128 , D.F. Zhang 58b , D. Zhang 103 , F. Zhang 179 , G. Zhang 58a,af , H. Zhang 128 , J. Zhang 6 , L. Zhang 50 , L. Zhang 58a , M. Zhang 171 , P. Zhang 15c , R. Zhang 58a,e , R. Zhang 24 , X. Zhang 58b , Y. Zhang 15d , Z. Zhang 128 , X. Zhao 41 , Y. Zhao 58b,128,ai , Z. Zhao 58a , A. Zhemchugov 77 , B. Zhou 103 , C. Zhou 179 , L. Zhou 41 , M.S. Zhou 15d , M. Zhou 152 , N. Zhou 58c , Y. Zhou 7 , C.G. Zhu 58b , H. Zhu 15a , J. Zhu 103 , Y. Zhu 58a , X. Zhuang 15a , K. Zhukov 108 , A. Zibell 175 , D. Zieminska 63 , N.I. Zimine 77 , C. Zimmermann 97 , S. Zimmermann 50 , Z. Zinonos 113 , M. Zinser 97 , M. Ziolkowski 148 , G. Zobernig 179 , A. Zoccoli 23b,23a , R. Zou 36 , M. Zur Nedden 19 , L. Zwalinski 35 1 Department of Physics, University of Adelaide, Adelaide, Australia 2 Physics Department, SUNY Albany, Albany, NY, United States of America 3 Department of Physics, University of Alberta, Edmonton, AB, Canada 4 (a) Department of Physics, Ankara University, Ankara; (b) Istanbul Aydin University, Istanbul; (c) Division of Physics, TOBB University of Economics and Technology, Ankara, Turkey 5 LAPP, Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS/IN2P3, Annecy, France 6 High Energy Physics Division, Argonne National Laboratory, Argonne, IL, United States of America 7 Department of Physics, University of Arizona, Tucson, AZ, United States of America 8 Department of Physics, University of Texas at Arlington, Arlington, TX, United States of America 9 Physics Department, National and Kapodistrian University of Athens, Athens, Greece 10 Physics Department, National Technical University of Athens, Zografou, Greece 11 Department of Physics, University of Texas at Austin, Austin, TX, United States of America 12 (a) Bahcesehir University, Faculty of Engineering and Natural Sciences, Istanbul; (b) Istanbul Bilgi University, Faculty of Engineering and Natural Sciences, Istanbul; (c) Department of Physics, Bogazici University, Istanbul; (d) Department of Physics Engineering, Gaziantep University, Gaziantep, Turkey 13 Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan 14 Institut de Física d’Altes Energies (IFAE), Barcelona Institute of Science and Technology, Barcelona, Spain 15 (a) Institute of High Energy Physics, Chinese Academy of Sciences, Beijing; (b) Physics Department, Tsinghua University, Beijing; (c) Department of Physics, Nanjing University, Nanjing; (d) University of Chinese Academy of Science (UCAS), Beijing, China 16 Institute of Physics, University of Belgrade, Belgrade, Serbia The ATLAS Collaboration / Physics Letters B 788 (2019) 316–335 333 17 Department for Physics and Technology, University of Bergen, Bergen, Norway 18 Physics Division, Lawrence Berkeley National Laboratory and University of California, Berkeley, CA, United States of America 19 Institut für Physik, Humboldt Universität zu Berlin, Berlin, Germany 20 Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics, University of Bern, Bern, Switzerland 21 School of Physics and Astronomy, University of Birmingham, Birmingham, United Kingdom 22 Centro de Investigaciónes, Universidad Antonio Nariño, Bogota, Colombia 23 (a) Dipartimento di Fisica e Astronomia, Università di Bologna, Bologna; (b) INFN Sezione di Bologna, Italy 24 Physikalisches Institut, Universität Bonn, Bonn, Germany 25 Department of Physics, Boston University, Boston, MA, United States of America 26 Department of Physics, Brandeis University, Waltham, MA, United States of America 27 (a) Transilvania University of Brasov, Brasov; (b) Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest; (c) Department of Physics, Alexandru Ioan Cuza University of Iasi, Iasi; (d) National Institute for Research and Development of Isotopic and Molecular Technologies, Physics Department, Cluj-Napoca; (e) University Politehnica Bucharest, Bucharest; (f ) West University in Timisoara, Timisoara, Romania 28 (a) Faculty of Mathematics, Physics and Informatics, Comenius University, Bratislava; (b) Department of Subnuclear Physics, Institute of Experimental Physics of the Slovak Academy of Sciences, Kosice, Slovak Republic 29 Physics Department, Brookhaven National Laboratory, Upton, NY, United States of America 30 Departamento de Física, Universidad de Buenos Aires, Buenos Aires, Argentina 31 Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom 32 (a) Department of Physics, University of Cape Town, Cape Town; (b) Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg; (c) School of Physics, University of the Witwatersrand, Johannesburg, South Africa 33 Department of Physics, Carleton University, Ottawa, ON, Canada 34 (a) Faculté des Sciences Ain Chock, Réseau Universitaire de Physique des Hautes Energies – Université Hassan II, Casablanca; (b) Centre National de l’Energie des Sciences Techniques Nucleaires (CNESTEN), Rabat; (c) Faculté des Sciences Semlalia, Université Cadi Ayyad, LPHEA, Marrakech; (d) Faculté des Sciences, Université Mohamed Premier and LPTPM, Oujda; (e) Faculté des sciences, Université Mohammed V, Rabat, Morocco 35 CERN, Geneva, Switzerland 36 Enrico Fermi Institute, University of Chicago, Chicago, IL, United States of America 37 LPC, Université Clermont Auvergne, CNRS/IN2P3, Clermont-Ferrand, France 38 Nevis Laboratory, Columbia University, Irvington, NY, United States of America 39 Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark 40 (a) Dipartimento di Fisica, Università della Calabria, Rende; (b) INFN Gruppo Collegato di Cosenza, Laboratori Nazionali di Frascati, Italy 41 Physics Department, Southern Methodist University, Dallas, TX, United States of America 42 Physics Department, University of Texas at Dallas, Richardson, TX, United States of America 43 (a) Department of Physics, Stockholm University; (b) Oskar Klein Centre, Stockholm, Sweden 44 Deutsches Elektronen-Synchrotron DESY, Hamburg and Zeuthen, Germany 45 Lehrstuhl für Experimentelle Physik IV, Technische Universität Dortmund, Dortmund, Germany 46 Institut für Kern- und Teilchenphysik, Technische Universität Dresden, Dresden, Germany 47 Department of Physics, Duke University, Durham, NC, United States of America 48 SUPA – School of Physics and Astronomy, University of Edinburgh, Edinburgh, United Kingdom 49 INFN e Laboratori Nazionali di Frascati, Frascati, Italy 50 Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany 51 II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen, Germany 52 Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève, Switzerland 53 (a) Dipartimento di Fisica, Università di Genova, Genova; (b) INFN Sezione di Genova, Italy 54 II. Physikalisches Institut, Justus-Liebig-Universität Giessen, Giessen, Germany 55 SUPA – School of Physics and Astronomy, University of Glasgow, Glasgow, United Kingdom 56 LPSC, Université Grenoble Alpes, CNRS/IN2P3, Grenoble INP, Grenoble, France 57 Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge, MA, United States of America 58 (a) Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei; (b) Institute of Frontier and Interdisciplinary Science and Key Laboratory of Particle Physics and Particle Irradiation (MOE), Shandong University, Qingdao; (c) School of Physics and Astronomy, Shanghai Jiao Tong University, KLPPAC-MoE, SKLPPC, Shanghai; (d) Tsung-Dao Lee Institute, Shanghai, China 59 (a) Kirchhoff-Institut für Physik, Ruprecht-Karls-Universität Heidelberg, Heidelberg; (b) Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg, Germany 60 Faculty of Applied Information Science, Hiroshima Institute of Technology, Hiroshima, Japan 61 (a) Department of Physics, Chinese University of Hong Kong, Shatin, N.T., Hong Kong; (b) Department of Physics, University of Hong Kong, Hong Kong; (c) Department of Physics and Institute for Advanced Study, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China 62 Department of Physics, National Tsing Hua University, Hsinchu, Taiwan 63 Department of Physics, Indiana University, Bloomington, IN, United States of America 64 (a) INFN Gruppo Collegato di Udine, Sezione di Trieste, Udine; (b) ICTP, Trieste; (c) Dipartimento di Chimica, Fisica e Ambiente, Università di Udine, Udine, Italy 65 (a) INFN Sezione di Lecce; (b) Dipartimento di Matematica e Fisica, Università del Salento, Lecce, Italy 66 (a) INFN Sezione di Milano; (b) Dipartimento di Fisica, Università di Milano, Milano, Italy 67 (a) INFN Sezione di Napoli; (b) Dipartimento di Fisica, Università di Napoli, Napoli, Italy 68 (a) INFN Sezione di Pavia; (b) Dipartimento di Fisica, Università di Pavia, Pavia, Italy 69 (a) INFN Sezione di Pisa; (b) Dipartimento di Fisica E. Fermi, Università di Pisa, Pisa, Italy 70 (a) INFN Sezione di Roma; (b) Dipartimento di Fisica, Sapienza Università di Roma, Roma, Italy 71 (a) INFN Sezione di Roma Tor Vergata; (b) Dipartimento di Fisica, Università di Roma Tor Vergata, Roma, Italy 72 (a) INFN Sezione di Roma Tre; (b) Dipartimento di Matematica e Fisica, Università Roma Tre, Roma, Italy 73 (a) INFN-TIFPA; (b) Università degli Studi di Trento, Trento, Italy 74 Institut für Astro- und Teilchenphysik, Leopold-Franzens-Universität, Innsbruck, Austria 75 University of Iowa, Iowa City, IA, United States of America 76 Department of Physics and Astronomy, Iowa State University, Ames, IA, United States of America 77 Joint Institute for Nuclear Research, Dubna, Russia 78 (a) Departamento de Engenharia Elétrica, Universidade Federal de Juiz de Fora (UFJF), Juiz de Fora; (b) Universidade Federal do Rio De Janeiro COPPE/EE/IF, Rio de Janeiro; (c) Universidade Federal de São João del Rei (UFSJ), São João del Rei; (d) Instituto de Física, Universidade de São Paulo, São Paulo, Brazil 79 KEK, High Energy Accelerator Research Organization, Tsukuba, Japan 80 Graduate School of Science, Kobe University, Kobe, Japan 81 (a) AGH University of Science and Technology, Faculty of Physics and Applied Computer Science, Krakow; (b) Marian Smoluchowski Institute of Physics, Jagiellonian University, Krakow, Poland 82 Institute of Nuclear Physics Polish Academy of Sciences, Krakow, Poland 83 Faculty of Science, Kyoto University, Kyoto, Japan 84 Kyoto University of Education, Kyoto, Japan 334 The ATLAS Collaboration / Physics Letters B 788 (2019) 316–335 85 Research Center for Advanced Particle Physics and Department of Physics, Kyushu University, Fukuoka, Japan 86 Instituto de Física La Plata, Universidad Nacional de La Plata and CONICET, La Plata, Argentina 87 Physics Department, Lancaster University, Lancaster, United Kingdom 88 Oliver Lodge Laboratory, University of Liverpool, Liverpool, United Kingdom 89 Department of Experimental Particle Physics, Jožef Stefan Institute and Department of Physics, University of Ljubljana, Ljubljana, Slovenia 90 School of Physics and Astronomy, Queen Mary University of London, London, United Kingdom 91 Department of Physics, Royal Holloway University of London, Egham, United Kingdom 92 Department of Physics and Astronomy, University College London, London, United Kingdom 93 Louisiana Tech University, Ruston, LA, United States of America 94 Fysiska institutionen, Lunds universitet, Lund, Sweden 95 Centre de Calcul de l’Institut National de Physique Nucléaire et de Physique des Particules (IN2P3), Villeurbanne, France 96 Departamento de Física Teorica C-15 and CIAFF, Universidad Autónoma de Madrid, Madrid, Spain 97 Institut für Physik, Universität Mainz, Mainz, Germany 98 School of Physics and Astronomy, University of Manchester, Manchester, United Kingdom 99 CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille, France 100 Department of Physics, University of Massachusetts, Amherst, MA, United States of America 101 Department of Physics, McGill University, Montreal, QC, Canada 102 School of Physics, University of Melbourne, Victoria, Australia 103 Department of Physics, University of Michigan, Ann Arbor, MI, United States of America 104 Department of Physics and Astronomy, Michigan State University, East Lansing, MI, United States of America 105 B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk, Belarus 106 Research Institute for Nuclear Problems of Byelorussian State University, Minsk, Belarus 107 Group of Particle Physics, University of Montreal, Montreal, QC, Canada 108 P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow, Russia 109 Institute for Theoretical and Experimental Physics (ITEP), Moscow, Russia 110 National Research Nuclear University MEPhI, Moscow, Russia 111 D.V. Skobeltsyn Institute of Nuclear Physics, M.V. Lomonosov Moscow State University, Moscow, Russia 112 Fakultät für Physik, Ludwig-Maximilians-Universität München, München, Germany 113 Max-Planck-Institut für Physik (Werner-Heisenberg-Institut), München, Germany 114 Nagasaki Institute of Applied Science, Nagasaki, Japan 115 Graduate School of Science and Kobayashi–Maskawa Institute, Nagoya University, Nagoya, Japan 116 Department of Physics and Astronomy, University of New Mexico, Albuquerque, NM, United States of America 117 Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen, Netherlands 118 Nikhef National Institute for Subatomic Physics and University of Amsterdam, Amsterdam, Netherlands 119 Department of Physics, Northern Illinois University, DeKalb, IL, United States of America 120 (a) Budker Institute of Nuclear Physics, SB RAS, Novosibirsk; (b) Novosibirsk State University Novosibirsk, Russia 121 Department of Physics, New York University, New York, NY, United States of America 122 Ohio State University, Columbus, OH, United States of America 123 Faculty of Science, Okayama University, Okayama, Japan 124 Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman, OK, United States of America 125 Department of Physics, Oklahoma State University, Stillwater, OK, United States of America 126 Palacký University, RCPTM, Joint Laboratory of Optics, Olomouc, Czech Republic 127 Center for High Energy Physics, University of Oregon, Eugene, OR, United States of America 128 LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay, France 129 Graduate School of Science, Osaka University, Osaka, Japan 130 Department of Physics, University of Oslo, Oslo, Norway 131 Department of Physics, Oxford University, Oxford, United Kingdom 132 LPNHE, Sorbonne Université, Paris Diderot Sorbonne Paris Cité, CNRS/IN2P3, Paris, France 133 Department of Physics, University of Pennsylvania, Philadelphia, PA, United States of America 134 Konstantinov Nuclear Physics Institute of National Research Centre “Kurchatov Institute”, PNPI, St. Petersburg, Russia 135 Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA, United States of America 136 (a) Laboratório de Instrumentação e Física Experimental de Partículas – LIP; (b) Departamento de Física, Faculdade de Ciências, Universidade de Lisboa, Lisboa; (c) Departamento de Física, Universidade de Coimbra, Coimbra; (d) Centro de Física Nuclear da Universidade de Lisboa, Lisboa; (e) Departamento de Física, Universidade do Minho, Braga; (f ) Departamento de Física Teorica y del Cosmos, Universidad de Granada, Granada, Spain; (g) Dep Física and CEFITEC of Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal 137 Institute of Physics, Academy of Sciences of the Czech Republic, Prague, Czech Republic 138 Czech Technical University in Prague, Prague, Czech Republic 139 Charles University, Faculty of Mathematics and Physics, Prague, Czech Republic 140 State Research Center Institute for High Energy Physics, NRC KI, Protvino, Russia 141 Particle Physics Department, Rutherford Appleton Laboratory, Didcot, United Kingdom 142 IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France 143 Santa Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz, CA, United States of America 144 (a) Departamento de Física, Pontificia Universidad Católica de Chile, Santiago; (b) Departamento de Física, Universidad Técnica Federico Santa María, Valparaíso, Chile 145 Department of Physics, University of Washington, Seattle, WA, United States of America 146 Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom 147 Department of Physics, Shinshu University, Nagano, Japan 148 Department Physik, Universität Siegen, Siegen, Germany 149 Department of Physics, Simon Fraser University, Burnaby, BC, Canada 150 SLAC National Accelerator Laboratory, Stanford, CA, United States of America 151 Physics Department, Royal Institute of Technology, Stockholm, Sweden 152 Departments of Physics and Astronomy, Stony Brook University, Stony Brook, NY, United States of America 153 Department of Physics and Astronomy, University of Sussex, Brighton, United Kingdom 154 School of Physics, University of Sydney, Sydney, Australia 155 Institute of Physics, Academia Sinica, Taipei, Taiwan 156 Academia Sinica Grid Computing, Institute of Physics, Academia Sinica, Taipei, Taiwan 157 (a) E. Andronikashvili Institute of Physics, Iv. Javakhishvili Tbilisi State University, Tbilisi; (b) High Energy Physics Institute, Tbilisi State University, Tbilisi, Georgia 158 Department of Physics, Technion, Israel Institute of Technology, Haifa, Israel 159 Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv University, Tel Aviv, Israel 160 Department of Physics, Aristotle University of Thessaloniki, Thessaloniki, Greece 161 International Center for Elementary Particle Physics and Department of Physics, University of Tokyo, Tokyo, Japan The ATLAS Collaboration / Physics Letters B 788 (2019) 316–335 335 162 Graduate School of Science and Technology, Tokyo Metropolitan University, Tokyo, Japan 163 Department of Physics, Tokyo Institute of Technology, Tokyo, Japan 164 Tomsk State University, Tomsk, Russia 165 Department of Physics, University of Toronto, Toronto, ON, Canada 166 (a) TRIUMF, Vancouver, BC; (b) Department of Physics and Astronomy, York University, Toronto, ON, Canada 167 Division of Physics and Tomonaga Center for the History of the Universe, Faculty of Pure and Applied Sciences, University of Tsukuba, Tsukuba, Japan 168 Department of Physics and Astronomy, Tufts University, Medford, MA, United States of America 169 Department of Physics and Astronomy, University of California Irvine, Irvine, CA, United States of America 170 Department of Physics and Astronomy, University of Uppsala, Uppsala, Sweden 171 Department of Physics, University of Illinois, Urbana, IL, United States of America 172 Instituto de Física Corpuscular (IFIC), Centro Mixto Universidad de Valencia – CSIC, Valencia, Spain 173 Department of Physics, University of British Columbia, Vancouver, BC, Canada 174 Department of Physics and Astronomy, University of Victoria, Victoria, BC, Canada 175 Fakultät für Physik und Astronomie, Julius-Maximilians-Universität Würzburg, Würzburg, Germany 176 Department of Physics, University of Warwick, Coventry, United Kingdom 177 Waseda University, Tokyo, Japan 178 Department of Particle Physics, Weizmann Institute of Science, Rehovot, Israel 179 Department of Physics, University of Wisconsin, Madison, WI, United States of America 180 Fakultät für Mathematik und Naturwissenschaften, Fachgruppe Physik, Bergische Universität Wuppertal, Wuppertal, Germany 181 Department of Physics, Yale University, New Haven, CT, United States of America 182 Yerevan Physics Institute, Yerevan, Armenia a Also at Department of Physics, University of Malaya, Kuala Lumpur, Malaysia. b Also at Borough of Manhattan Community College, City University of New York, NY, United States of America. c Also at Centre for High Performance Computing, CSIR Campus, Rosebank, Cape Town, South Africa. d Also at CERN, Geneva, Switzerland. e Also at CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille, France. f Also at Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève, Switzerland. g Also at Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona, Spain. h Also at Departamento de Física Teorica y del Cosmos, Universidad de Granada, Granada, Spain. i Also at Department of Applied Physics and Astronomy, University of Sharjah, Sharjah, United Arab Emirates. j Also at Department of Financial and Management Engineering, University of the Aegean, Chios, Greece. k Also at Department of Physics and Astronomy, University of Louisville, Louisville, KY, United States of America. l Also at Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom. m Also at Department of Physics, California State University, Fresno, CA, United States of America. n Also at Department of Physics, California State University, Sacramento, CA, United States of America. o Also at Department of Physics, King’s College London, London, United Kingdom. p Also at Department of Physics, Nanjing University, Nanjing, China. q Also at Department of Physics, St. Petersburg State Polytechnical University, St. Petersburg, Russia. r Also at Department of Physics, Stanford University, United States of America. s Also at Department of Physics, University of Fribourg, Fribourg, Switzerland. t Also at Department of Physics, University of Michigan, Ann Arbor, MI, United States of America. u Also at Dipartimento di Fisica E. Fermi, Università di Pisa, Pisa, Italy. v Also at Giresun University, Faculty of Engineering, Giresun, Turkey. w Also at Graduate School of Science, Osaka University, Osaka, Japan. x Also at Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest, Romania. y Also at II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen, Germany. z Also at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona, Spain. aa Also at Institut de Física d’Altes Energies (IFAE), Barcelona Institute of Science and Technology, Barcelona, Spain. ab Also at Institut für Experimentalphysik, Universität Hamburg, Hamburg, Germany. ac Also at Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen, Netherlands. ad Also at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest, Hungary. ae Also at Institute of Particle Physics (IPP), Canada. af Also at Institute of Physics, Academia Sinica, Taipei, Taiwan. ag Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan. ah Also at Institute of Theoretical Physics, Ilia State University, Tbilisi, Georgia. ai Also at LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay, France. aj Also at Louisiana Tech University, Ruston, LA, United States of America. ak Also at Manhattan College, New York, NY, United States of America. al Also at Moscow Institute of Physics and Technology State University, Dolgoprudny, Russia. am Also at National Research Nuclear University MEPhI, Moscow, Russia. an Also at Near East University, Nicosia, North Cyprus, Mersin, Turkey. ao Also at Ochadai Academic Production, Ochanomizu University, Tokyo, Japan. ap Also at Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany. aq Also at School of Physics, Sun Yat-sen University, Guangzhou, China. ar Also at The City College of New York, New York, NY, United States of America. as Also at The Collaborative Innovation Center of Quantum Matter (CICQM), Beijing, China. at Also at Tomsk State University, Tomsk, and Moscow Institute of Physics and Technology State University, Dolgoprudny, Russia. au Also at TRIUMF, Vancouver, BC, Canada. av Also at Universita di Napoli Parthenope, Napoli, Italy. ∗ Deceased.