Eur. Phys. J. C (2019) 79:847 https://doi.org/10.1140/epjc/s10052-019-7321-3 Regular Article - Experimental Physics Measurement of the inclusive cross-section for the production of jets in association with a Z boson in proton–proton collisions at 8 TeV using the ATLAS detector ATLAS Collaboration CERN, 1211 Geneva 23, Switzerland Received: 17 July 2019 / Accepted: 18 September 2019 / Published online: 14 October 2019 © CERN for the benefit of the ATLAS collaboration 2019 Abstract The inclusive cross-section for jet production 8.6 Statistical uncertainties . . . . . . . . . . . . . 10 in association with a Z boson decaying into an electron– 8.7 Summary of experimental uncertainties . . . . . 10 positron pair is measured as a function of the transverse 9 Fixed-order predictions and theoretical uncertainties 11 momentum and the absolute rapidity of jets using 19.9 fb−1 9.1 Fixed-order calculations . . . . . . . . . . . . . 11 √ of s = 8 TeV proton–proton collision data collected with 9.2 Non-perturbative correction . . . . . . . . . . . 11 the ATLAS detector at the Large Hadron Collider. The mea- 9.3 QED radiation correction . . . . . . . . . . . . 14 sured Z + jets cross-section is unfolded to the particle level. 9.4 Summary of theoretical uncertainties . . . . . . 14 The cross-section is compared with state-of-the-art Stan- 10 Results . . . . . . . . . . . . . . . . . . . . . . . . 14 dard Model calculations, including the next-to-leading-order 11 Quantitative data and theory comparison . . . . . . 18 and next-to-next-to-leading-order perturbative QCD calcu- 12 Conclusions . . . . . . . . . . . . . . . . . . . . . 21 lations, corrected for non-perturbative and QED radiation Appendix . . . . . . . . . . . . . . . . . . . . . . . . 24 effects. The results of the measurements cover final-state A Tables of measured cross-sections . . . . . . . . . . 24 jets with transverse momenta up to 1 TeV, and show good References . . . . . . . . . . . . . . . . . . . . . . . . 32 agreement with fixed-order calculations. 1 Introduction Contents The measurement of the production cross-section of jets, a 1 Introduction . . . . . . . . . . . . . . . . . . . . . 1 collimated spray of hadrons, in association with a Z boson 2 The ATLAS detector . . . . . . . . . . . . . . . . . 2 (Z + jets), is an important process for testing the predictions 3 Data sample . . . . . . . . . . . . . . . . . . . . . 2 of perturbative quantum chromodynamics (pQCD). It pro- 4 Monte Carlo simulations . . . . . . . . . . . . . . . 3 vides a benchmark for fixed-order calculations and predic- 5 Object definitions and event selection . . . . . . . . 4 tions from Monte Carlo (MC) simulations, which are often 5.1 Electron reconstruction and identification . . . 4 used to estimate the Z + jets background in the measure- 5.2 Jet reconstruction, pile-up suppression and qual- ments of Standard Model processes, such as Higgs boson ity criteria . . . . . . . . . . . . . . . . . . . . 4 production, and in searches for new physics beyond the Stan- 5.3 Event selection . . . . . . . . . . . . . . . . . 5 dard Model. 6 Backgrounds . . . . . . . . . . . . . . . . . . . . . 5 Various properties of Z + jets production have been mea- √ 7 Unfolding of detector effects . . . . . . . . . . . . . 6 sured in proton–antiproton collisions at s = 1.96 TeV at 8 Experimental uncertainties . . . . . . . . . . . . . . 8 the Tevatron [1–4]. The differential Z + jets cross-section is 8.1 Electron uncertainties . . . . . . . . . . . . . . 8 measured as functions of the Z boson transverse momentum 8.2 Jet uncertainties . . . . . . . . . . . . . . . . . 8 and the jets’ transverse momenta and rapidities, and as a func- 8.3 Background uncertainties . . . . . . . . . . . . 9 tion of the angular separation between the Z boson and jets in 8.4 Unfolding uncertainty . . . . . . . . . . . . . . 9 final states with different jet multiplicities. The experiments 8.5 Reduction of statistical fluctuations in system- at the Large Hadron Collider (LHC) [5] have an increased atic uncertainties . . . . . . . . . . . . . . . . 10 phase space compared to previous measurements by using √ proton–proton collision data at s = 7, 8 and 13 TeV [6–15].  e-mail: atlas.publications@cern.ch The measurements at the LHC allow state-of-the-art theoreti- 123 847 Page 2 of 47 Eur. Phys. J. C (2019) 79:847 cal Z + jets predictions to be tested. These have recently been It consists of an inner tracking detector surrounded by a calculated to next-to-next-to-leading-order (NNLO) accu- thin superconducting solenoid, electromagnetic and hadronic racy in pQCD [16,17]. calorimeters, and a muon spectrometer incorporating three This paper studies the double-differential cross-section of large superconducting toroidal magnets. inclusive jet production in association with a Z boson which The inner-detector system (ID) is immersed in a 2 T axial decays into an electron–positron pair. The cross-section is magnetic field and provides charged-particle tracking in the measured as a function of absolute jet rapidity, |yjet |, and range |η| < 2.5. A high-granularity silicon pixel detector jet covers the pp interaction region and typically provides three jet transverse momentum, pT , using the proton–proton (pp) √ collision data at s = 8 TeV collected by the ATLAS exper- measurements per track. It is followed by a silicon microstrip iment. The measured cross-section is unfolded to the particle tracker (SCT), which usually provides four two-dimensional level. measurement points per track. These silicon detectors are The cross-section calculated at fixed order for Z + jets complemented by a transition radiation tracker (TRT), which √ production in pp collisions at s = 8 TeV is dominated by provides electron identification information. quark–gluon scattering. The Z + jets cross-section is sensi- The calorimeter system covers the pseudorapidity range tive to the gluon and sea-quark parton distribution functions |η| < 4.9. In the region |η| < 3.2, electromagnetic calorime- (PDFs) in the proton. In the central |yjet | region the Z + jets try is provided by barrel and endcap high-granularity cross-section probes the PDFs in the low x range, where x lead/liquid-argon (LAr) electromagnetic calorimeters, with is the proton momentum fraction, while in the forward |yjet | an additional thin LAr presampler covering |η| < 1.8 to region it examines the intermediate and high x values. The correct for energy loss in material upstream of the calorime- jet ters. Hadronic calorimetry is provided by a steel/scintillator- scale of the probe is set by pT . The measured cross-section is compared with the next-to- tile calorimeter, segmented into three barrel structures for leading-order (NLO) and NNLO Z + jets fixed-order calcu- |η| < 1.7, and two copper/LAr hadronic endcap calorime- lations, corrected for hadronisation and the underlying event. ters in the range 1.5 < |η| < 3.2. The calorimetry in the In addition, the data are compared with the predictions from forward pseudorapidity region, 3.1 < |η| < 4.9, is provided multi-leg matrix element (ME) MC event generators supple- by the copper-tungsten/LAr calorimeters. mented with parton shower simulations. The muon spectrometer surrounds the calorimeters and The structure of the paper is as follows. The ATLAS detec- contains three large air-core toroidal superconducting mag- tor is briefly described in Sect. 2. This is followed by a nets with eight coils each. The field integral of the toroids description of the data in Sect. 3 and the simulated sam- ranges between 2.0 and 6.0 T m across most of the detec- ples in Sect. 4. The definition of the object reconstruction, tor. The muon spectrometer includes a system of precision calibration and identification procedures and a summary of tracking chambers and fast detectors for triggering. the selection criteria are given in Sect. 5. The Z + jets back- A three-level trigger [19] was used to select events for grounds are discussed in Sect. 6. The correction of the mea- offline analysis. The first-level trigger is implemented in sured spectrum to the particle level is described in Sect. 7. The hardware and used a subset of the detector information to experimental uncertainties are discussed in Sect. 8. The fixed- reduce the accepted rate to at most 75 kHz. This was followed order calculations together with parton-to-particle-level cor- by two software-based trigger levels that together reduced the rections are presented in Sect. 9. Finally, the measured cross- average accepted event rate to 400 Hz. section is presented and compared with the theory predictions in Sect. 10. The quantitative comparisons with the fixed-order pQCD predictions are summarised in Sect. 11. 3 Data sample The data used for this analysis are from proton–proton colli- √ 2 The ATLAS detector sions at s = 8 TeV that were collected by the ATLAS detec- tor in 2012 during stable beam conditions. Events recorded The ATLAS experiment [18] at the LHC is a multipurpose when any of the ATLAS subsystems were defective or non- particle detector with a forward–backward symmetric cylin- operational are excluded. Data were selected with a dielec- drical geometry and nearly 4π coverage in solid angle.1 tron trigger, which required two reconstructed electron can- didates with transverse momenta greater than 12 GeV. Only 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- Footnote 1 continued axis along the beam pipe. The x-axis points from the IP to the centre of around the z-axis. The pseudorapidity is defined in terms of the polar the LHC ring, and the y-axis points upwards. Cylindrical coordinates angle θ as η = − ln tan(θ/2). Angular distance is measured in units of (r, φ) are used in the transverse plane, φ being the azimuthal angle R ≡ (η)2 + (φ)2 . 123 Eur. Phys. J. C (2019) 79:847 Page 3 of 47 847 events with electron energy leakage of less than 1 GeV into An additional Z + jets signal sample with up to five par- the hadronic calorimeter were accepted. The trigger required tons in the final state at LO was generated using Alp- that reconstructed electron candidates were identified using gen v. 2.14 [30]. The parton showers were generated using the ‘loose1’ criteria [20], which are discussed in Sect. 5.1. Pythia v. 6.426 [31] with the Perugia 2011C [32] set of The integrated luminosity of the analysis data sample after tuned parameters to model the underlying event’s contribu- the trigger selection is 19.9 fb−1 measured with an uncer- tion. The Alpgen MEs were matched to the parton showers tainty of ±1.9% [21]. The average number of simultaneous following the MLM prescription [30]. The proton structure proton–proton interactions per bunch crossing is 20.7. was described by the CTEQ6L1 [33] PDF. Referred to as the In addition, a special data sample was selected for a data- Alpgen+Pythia sample, these predictions were normalised driven study of multijet and W + jets backgrounds. For this to the NNLO cross-section. This sample is used in the analy- purpose, the analysis data sample was enlarged by includ- sis for the unfolding uncertainty evaluation and for compar- ing auxiliary events selected by a logical OR of two single- isons with the measurement. electron triggers. The five-flavour scheme with massless quarks was used The first single-electron trigger required events with at in both the Sherpa and Alpgen+Pythia predictions. least one reconstructed electron candidate with a transverse Backgrounds from the Z → τ τ , diboson (W W , W Z momentum greater than 24 GeV and hadronic energy leak- and Z Z ), t t¯ and single-top-quark events are estimated using age less than 1 GeV. The electron candidate satisfied the MC simulations. The Z → τ τ events were generated ‘medium1’ identification criteria [20], a tightened subset of using Powheg- Box v. 1.0 [34,35] interfaced to Pythia v. ‘loose1’. The reconstructed electron track was required to be 8.160 [36] for parton showering using the CT10 PDFs and isolated from other tracks in the event. The isolation require- the AU2 [37] set of tuned parameters. The Z → τ τ pre- ment rejected an event if the scalar sum of reconstructed track diction was normalised to the NNLO cross-section [27– transverse momenta in a cone of size R = 0.2 around the 29]. The W W , W Z and Z Z events were generated using electron track exceeded 10% of the electron track’s transverse Herwig v. 6.520.2 [38] with the CTEQ6L1 PDFs and the momentum. AUET2 [39] set of tuned parameters. The diboson predic- The second single-electron trigger accepted events with tions were normalised to the NLO cross-sections [40,41]. at least one electron candidate with a transverse momentum Samples of single-top-quark events, produced via the s-, greater than 60 GeV and identified as ‘medium1’. This trig- t- and W t-channels, and t t¯ events were generated with ger reduced inefficiencies in events with high- pT electrons Powheg- Box v. 1.0 interfaced to Pythia v. 6.426, which that resulted from the isolation requirement used in the first used the CTEQ6L1 PDFs and the Perugia 2011C set of trigger. tuned parameters. The prediction for single-top-quark pro- Events selected by single-electron triggers include a large duction in s-channel were normalised to the NNLO cal- number of background events that are normally rejected by culations matched to the next-to-next-to-leading-logarithm the Z + jets selection requirements, but these events are used (NNLL) calculations (NNLO+NNLL) [42], while predic- in the data-driven background studies. tions in t- and W t-channel are normalised to the NLO+NNLL calculations [43,44]. The t t¯ samples were normalised to the 4 Monte Carlo simulations NNLO+NNLL calculations [45]. The Photos [46] and Tauola [47] programs were interfaced Simulated Z + jets signal events were generated using the to the MC generators, excluding Sherpa, to model electro- Sherpa v. 1.4 [22] multi-leg matrix element MC generator. magnetic final-state radiation and τ -lepton decays, respec- The MEs were calculated at NLO accuracy for the inclusive Z tively. production process, and additionally with LO accuracy for Additional proton–proton interactions, generally called up to five partons in the final state, using Amegic++ [23]. pile-up, were simulated using the Pythia v. 8.160 gener- Sherpa MEs were convolved with the CT10 [24] PDFs. ator with the MSTW2008 [48] PDFs and the A2 [37] set Sherpa parton showers were matched to MEs following the of tuned parameters. The pile-up events were overlaid onto CKKW scheme [25]. The MENLOPS [26] prescription was the events from the hard-scattering physics processes. MC used to combine different parton multiplicities from matrix simulated events were reweighted to match the distribution elements and parton showers. Sherpa predictions were nor- of the average number of interactions per bunch crossing in malised to the inclusive Z boson production cross-section data. calculated at NNLO [27–29] and are used for the unfolding All MC predictions were obtained from events processed to particle level and for the evaluation of systematic uncer- with the ATLAS detector simulation [49] that is based on tainties. Geant 4 [50]. 123 847 Page 4 of 47 Eur. Phys. J. C (2019) 79:847 5 Object definitions and event selection and second LAr calorimeter layers, energy leakage into the hadronic calorimeter, the number of hits in the pixel and The measured objects are the electrons and jets reconstructed SCT detectors, and the angular distance between the cluster in ATLAS. The methods used to reconstruct, identify and cal- position in the first LAr calorimeter layer and the extrapo- ibrate electrons are presented in Sect. 5.1. The reconstruction lated track. The ‘medium’ selection tightens ‘loose’ require- of jets, their calibration, and background suppression meth- ments on shower shape variables. In addition, the ‘medium’ ods are discussed in Sect. 5.2. Finally, all selection require- selection sets conditions on the energy deposited in the third ments are summarised in Sect. 5.3. calorimeter layer, track properties in the TRT detector and the vertex position. The ‘tight’ selection tightens the ‘medium’ 5.1 Electron reconstruction and identification identification criteria thresholds, sets conditions on the mea- sured ratio of cluster energy to track momentum and rejects Electron reconstruction in the central region, |η| < 2.5, starts reconstructed electron candidates matched to photon conver- from energy deposits in calorimeter cells. A sliding-window sions. algorithm scans the central volume of the electromagnetic Each MC simulated event is reweighted by scale factors calorimeter in order to seed three-dimensional clusters. The that make the trigger, reconstruction and identification effi- window has a size of 3 × 5 in units of 0.025 × 0.025 in η– ciencies the same in data and MC simulation. The scale fac- φ space. Seeded cells have an energy sum of the constituent tors are generally close to one and are calculated in bins of calorimeter cells greater than 2.5 GeV. An electron candidate electron transverse momenta and pseudorapidity [20,51]. is reconstructed if the cluster is matched to at least one track assigned to the primary vertex, as measured in the inner detec- tor. The energy of a reconstructed electron candidate is given 5.2 Jet reconstruction, pile-up suppression and quality by the energy of a cluster that is enlarged to a size of 3 × 7 criteria (5 × 5) in η–φ space in the central (endcap) electromagnetic calorimeter in order to take into account the shape of elec- Jets are reconstructed using the anti-kt algorithm [53] with tromagnetic shower energy deposits in different calorimeter a radius parameter R = 0.4, as implemented in the Fast- regions. The η and φ coordinates of a reconstructed electron Jet software package [54]. Jet reconstruction uses topo- candidate are taken from the matched track. The details of logically clustered cells from both the electromagnetic the electron reconstruction are given in Ref. [51]. and hadronic calorimeters [55]. The topological clustering A multistep calibration is used to correct the electron algorithm groups cells with statistically significant energy energy scale to that of simulated electrons [52]. Cluster ener- deposits as a method to suppress noise. The energy scale of gies in data and in MC simulation are corrected for energy calorimeter cells is initially established for electromagnetic loss in the material upstream of the electromagnetic calorime- particles. The local cell weighting (LCW) [56] calibration ter, energy lost outside of the cluster volume and energy is applied to topological clusters to correct for the differ- leakage beyond the electromagnetic calorimeter. The recon- ence between the detector responses to electromagnetic and structed electron energy in data is corrected as a function hadronic particles, energy losses in inactive material and out- of electron pseudorapidity using a multiplicative scale factor of-cluster energy deposits. The LCW corrections are derived obtained from a comparison of Z → ee mass distributions using the MC simulation of the detector response to single between data and simulation. In addition, the electron energy pions. in the MC simulation is scaled by a random number taken The jet energy scale (JES) calibration [57] corrects the from a Gaussian distribution with a mean value of one and energy scale of reconstructed jets to that of simulated an η-dependent width, equal to the difference between the particle-level jets. The JES calibration includes origin cor- electron energy resolution in data and MC simulation, deter- rection, pile-up correction, MC-based correction of the jet mined in situ using Z → ee events. energy and pseudorapidity (MCJES), global sequential cali- A set of cut-based electron identification criteria, which bration (GSC) and residual in situ calibration. use cluster shape and track properties, is applied to recon- The origin correction forces the four-momentum of the jet structed electrons to suppress the residual backgrounds to point to the hard-scatter primary vertex rather than to the from photon conversions, jets misidentified as electrons and centre of the detector, while keeping the jet energy constant. semileptonic heavy-hadron decays. There are three types Pile-up contributions to the measured jet energies are of identification criteria, listed in the order of increas- accounted for by using a two-step procedure. First, the recon- ing background-rejection strength but diminishing electron structed jet energy is corrected for the effect of pile-up by selection efficiency: ‘loose’, ‘medium’ and ‘tight’ [51]. The using the average energy density in the event and the area of ‘loose’ criteria identify electrons using a set of thresholds the jet [58]. Second, a residual correction is applied to remove applied to cluster shape properties measured in the first the remaining dependence of the jet energy on the number of 123 Eur. Phys. J. C (2019) 79:847 Page 5 of 47 847 reconstructed primary vertices, NPV , and the expected aver- Each event is required to have exactly two reconstructed age number of interactions per bunch crossing, μ. electrons, each with transverse momentum greater than The MCJES corrects the reconstructed jet energy to the 20 GeV and an absolute pseudorapidity less than 2.47, particle-level jet energy using MC simulation. In addition, a excluding the detector transition region, 1.37 < |ηe | < 1.52, correction is applied to the reconstructed jet pseudorapidity between barrel and endcap electromagnetic calorimeters. to account for the biases caused by the transition between dif- The electrons are required to have opposite charges, be iden- ferent calorimeter regions and the differences in calorimeter tified using the ‘medium’ [51] criteria and be matched to granularity. electron candidates that were selected by the trigger. The Next, the GSC corrects the jet four-momenta to reduce ‘medium’ identification ensures the electrons originate from the response’s dependence on the flavour of the parton that the hard-scatter vertex. The electron-pair invariant mass, m ee , initiates the jet. The GSC is determined using the number of is required to be in the 66 GeV < m ee < 116 GeV range. tracks assigned to a jet, the pT -weighted transverse distance Jets are required to have a transverse momentum greater in the η–φ space between the jet axis and all tracks assigned to than 25 GeV and an absolute jet rapidity less than 3.4. Jets jet the jet (track width), and the number of muon track segments with pT < 50 GeV, |ηdet | < 2.4, where ηdet is recon- assigned to the jet. structed relative to the detector centre, and |JVF| < 0.25 are Finally, the residual in situ correction makes the jet considered to be from pile-up. Jets originating from pile-up response the same in data and MC simulation as a func- are removed from the measurement. MC simulations poorly jet tion of detector pseudorapidity by using dijet events (η- describe the effects of high pile-up in the pT < 50 GeV intercalibration), and as a function of jet transverse momen- and |yjet | > 2.4 region, so this region is not included in tum by using well-calibrated reference objects in Z /γ and the measurement. Jets reconstructed within R = 0.4 of multijet events. selected electrons are rejected in order to avoid overlap. Jets Jets originating from pile-up interactions are suppressed are required to satisfy the ‘medium’ [57] quality criteria. In using the jet vertex fraction (JVF) [58]. The JVF is calculated addition, jets in regions of the detector that are poorly mod- for each jet and each primary vertex in the event as a ratio of elled are rejected in data and MC simulations in order to avoid the scalar sum of pT of tracks, matched to a jet and assigned biasing the measured jet energy [57]. Each jet that meets the to a given vertex, to the scalar sum of pT of all tracks matched selection requirements is used in the measurement. to a jet. As a result, 1,486,415 events with two electrons and at Applying jet quality criteria suppresses jets from non- least one jet were selected for the analysis. collision backgrounds that arise from proton interactions with the residual gas in the beam pipe, beam interactions with the collimator upstream of the ATLAS detector, cosmic rays overlapping in time with the proton–proton collision 6 Backgrounds and noise in the calorimeter. Jet quality criteria are used to distinguish jets by using the information about the quality of The majority of irreducible backgrounds in this measure- the energy reconstruction in calorimeter cells, the direction of ment are studied using MC samples that simulate Z → τ τ , the shower development and the properties of tracks matched diboson, t t¯ and single top-quark production. The Z → τ τ to jets. There are four sets of selection criteria that establish process is a background if both τ -leptons decay into an elec- jet quality: ‘looser’, ‘loose’, ‘medium’ and ‘tight’. They are tron and neutrino. Diboson production constitutes a back- listed in the order of increasing suppression of non-collision ground to the Z + jets signal if the W and/or Z boson decays jet background but decreasing jet selection efficiency. The into electrons. Since the top-quark decays predominantly via ‘medium’ jet selection is used in the paper due to its high t → W b, the t t¯ and single top-quark constitute a background background rejection rate together with about 100% jet selec- to the Z + jets signal when W bosons decay into an electron jet tion efficiency in the pT > 60 GeV region [57]. or jets are misidentified as electrons. Multijet production constitutes a background to the Z + jets signal when two jets are misidentified as electrons. 5.3 Event selection The W + jets background is due to an electron from W boson decay and a jet misidentified as electron. A combined back- Events are required to have a primary vertex with at least three ground from multijet and W + jets events is studied using a assigned tracks that have a transverse momentum greater than data-driven technique, thus providing a model-independent 400 MeV. When several reconstructed primary vertices sat- background estimate. isfy this requirement, the hard-scatter vertex is taken to be A background-enriched data sample is used for the com- the one with the highest sum of the squares of the transverse bined multijet and W + jets background control region. Its momenta of its assigned tracks. selection requires two reconstructed electrons with at least 123 847 Page 6 of 47 Eur. Phys. J. C (2019) 79:847 one electron that satisfies the ‘medium’ identification criteria, a function of the jet transverse momenta, reaching 30% in jet but not the ‘tight’ ones. This allows selection of events with the 400 GeV < pT < 1050 GeV region. at least one jet misidentified as an electron. No identification The dominant background in the measurement is from jet criteria are applied to the second reconstructed electron, in t t¯ events. It is 0.3–0.8% in the 25 GeV < pT < 50 GeV order to allow for the possibility of W + jets events with a gen- jet region and 1–2.5% in the 50 GeV < pT < 100 GeV region, uine electron from W boson decay, and multijet events with with the largest contribution in the central rapidity region. In a jet misidentified as another electron. Both selected elec- jet the 100 GeV < pT < 200 GeV region, this background is trons are required to have the same charge to suppress the jet approximately 3%, while in the 200 GeV < pT < 1050 GeV Z + jets signal events. The combined multijet and W + jets region it is 1.8–8%, increasing for forward rapidity jets. background template is constructed by subtracting the MC The combined multijet and W + jets background and the simulated Z + jets signal events and Z → τ τ , diboson, t t¯ diboson background are similar in size. The contributions of and single-top-quark background events in the control region these backgrounds are 0.5–1%. from data. The Z → τ τ and single-top-quark backgrounds are below The purity of the template is calculated as the fraction of 0.1%. multijet and W + jets events in the data control region. The purity is about 98% in the tails of the m ee distribution and is about 80% near the m ee peak at 91 GeV. The template purity jet 7 Unfolding of detector effects is above 90% in all |yjet | and pT bins. The combined multijet and W + jets background template The experimental measurements are affected by the detector is normalised to data using the invariant mass distribution resolution and reconstruction inefficiencies. In order to com- of reconstructed electron pairs. A maximum-likelihood fit pare the measured cross-sections with the theoretical Z + jets is used to adjust the normalisation of the combined multijet predictions at the particle level, the reconstructed spectrum and W + jets background template relative to the measured is corrected for detector effects using the iterative Bayesian Z + jets distribution. The normalisations of MC simulated unfolding method [59]. The unfolding is performed using the samples are fixed in the fit: the Z → τ τ , diboson, t t¯ and Sherpa Z + jets simulation. single-top-quark distributions are normalised by their fixed- The particle-level phase space in the MC simulation is order cross-sections, whereas the normalisation of the MC defined using two dressed electrons and at least one jet. For simulated Z + jets signal events is scaled to data to give the the dressed electron, the four-momenta of any photons within same total number of events near the peak of the Z mass spec- a cone of R = 0.1 around its axis are added to the four- trum in the 90 GeV < m ee < 92 GeV range. The combined momentum of the electron. Electrons are required to have multijet and W + jets background is fit to data in an extended |η| < 2.47 and pT > 20 GeV. The electron pair’s invariant m ee region, 60 GeV < m ee < 140 GeV, excluding the bins mass is required to be within the range 66 GeV < m ee < under the Z peak within the 80 GeV < m ee < 100 GeV 116 GeV. region. The extended m ee region is used for the normalisa- Jets at the particle level are built by using the anti-kt jet tion extraction only, as it allows more background events in algorithm with a radius parameter R = 0.4 to cluster stable the tails of the Z mass spectrum. The normalisation of the final-state particles with a decay length of cτ > 10 mm, multijet and W + jets background template, calculated in the excluding muons and neutrinos. Jets are selected in the fit, is used to adjust the templates, obtained in the |yjet | and jet jet |yjet | < 3.4 and pT > 25 GeV region. Jets within R = 0.4 pT bins, to the Z + jets signal region. of electrons are rejected. The total number of jets in Z + jets events are shown as a jet The closest reconstructed and particle-level jets are con- function of |yjet | and pT bins in Fig. 1. Data are compared sidered matched if R between their axes satisfies R < with the sum of signal MC events and all backgrounds. 0.4. The Sherpa Z + jets simulation, normalised to the NNLO The input for the unfolding is the transfer matrix, which jet cross-section, is lower than data by about 10% in the pT < maps reconstructed jets to the particle-level jets in the |yjet |– 200 GeV region. These differences are mostly covered by the jet pT plane, taking into account the bin-to-bin migrations that variations within electron and jet uncertainties introduced jet jet arise from limited detector resolution. An additional pT bin, in Sect. 8. In the pT > 200 GeV region, agreement with jet data is within the statistical uncertainties. 17 GeV < pT < 25 GeV, is included in the reconstructed The Alpgen+Pythia predictions are in agreement with and particle-level jet spectra to account for the migrations jet data within 10% for jets with transverse momenta below from the low pT range. This bin is not reported in the mea- 100 GeV. However, the level of disagreement increases as surement. 123 Eur. Phys. J. C (2019) 79:847 Page 7 of 47 847 (a) (b) (c) (d) (e) (f) Fig. 1 The total number of jets in Z + jets events as a function of |yjet | predictions. Lower panels show ratios of MC predictions to data. The in pT bins for the integrated luminosity of 19.9 fb−1 . Data are presented jet grey band shows the sum in quadrature of the electron and jet uncer- with markers. The filled areas correspond to the backgrounds stacked. tainties. The statistical uncertainties are shown with vertical error bars. All backgrounds are added to the Z + jets Sherpa and Alpgen+Pythia In the lower panels the total data + MC statistical uncertainty is shown 123 847 Page 8 of 47 Eur. Phys. J. C (2019) 79:847 Given the significant amount of migration between jet tainties. The scale factor for electron energy resolution in MC transverse momentum bins, the unfolding is performed in all simulation is varied by ±1σ in the total uncertainty in order jet |yjet | and pT bins simultaneously. The migration between to propagate this uncertainty into the Z + jets cross-section adjacent |yjet | bins is found to be small. measurements. The transfer matrix is defined for matched jets. There- The uncertainties in calculations of the electron trigger, fore, the reconstructed jet spectrum must be corrected to reconstruction and identification efficiencies are propagated account for matching efficiencies prior to unfolding. The into the measurements by ±1σ variations of the scale factors, reconstruction-level matching efficiency is calculated as the used to reweight the MC simulated events, within the total fraction of reconstructed jets matching particle-level jets. uncertainty of each efficiency [20,51]. jet This efficiency is 80–90% in the 25 GeV < pT < 100 GeV For each systematic variation a new transfer matrix and jet region and is above 99% in the pT > 100 GeV region. The new matching efficiencies are calculated, and data unfold- particle-level jet matching efficiency is calculated as the frac- ing is performed. The deviation from the nominal unfolded tion of particle-level jets matching reconstructed jets. This result is assigned as the systematic uncertainty in the mea- efficiency is 45–55% in all bins of the measurement due to surements. the inefficiency of the Z boson reconstruction. The backgrounds are subtracted from data prior to unfold- 8.2 Jet uncertainties ing. The unfolded number of jets in data, NiP , in each bin i of the measurement is obtained as The uncertainty in the jet energy measurement is described by 65 uncertainty components [57]. Of these, 56 JES uncer- 1  tainty components are related to detector description, physics NiP = Ui j ERj N Rj , (1) modelling and sample sizes of the Z /γ and multijet MC sam- EiP j ples used for JES in situ measurements. The single-hadron response studies are used to describe the JES uncertainty in where N Rj is the number of jets reconstructed in bin j after high- pT jet regions, where the in situ studies have few events. the background subtraction, Ui j is an element of the unfold- The MC non-closure uncertainty takes into account the dif- ing matrix, and ERj and EiP are the reconstruction-level and ferences in the jet response due to different shower mod- particle-level jet matching efficiencies, respectively. els used in MC generators. Four uncertainty components are The transfer matrix and the matching efficiencies are due to the pile-up corrections of the jet kinematics, and take improved using three unfolding iterations to reduce the into account mis-modelling of NPV and μ distributions, the impact of the particle-level jet spectra mis-modelling on the average energy density and the residual pT dependence of the unfolded data. NPV and μ terms. Two flavour-based uncertainties take into account the difference between the calorimeter responses to the quark- and gluon-initiated jets. One uncertainty compo- 8 Experimental uncertainties nent describes the correction for the energy leakage beyond the calorimeter (‘punch-through’ effect). All JES uncertain- 8.1 Electron uncertainties ties are treated as bin-to-bin correlated and independent of each other. The electron energy scale has associated statistical uncertain- A reduced set of uncertainties, which combines the uncer- ties and systematic uncertainties arising from a possible bias tainties of the in situ methods into six components with a in the calibration method, the choice of generator, the pre- small loss of correlation information, is used in this measure- sampler energy scale, and imperfect knowledge of the mate- ment. The JES uncertainties are propagated into the measure- rial in front of the EM calorimeter. The total energy-scale ments in the same way as done for electron uncertainties. uncertainty is calculated as the sum in quadrature of these The uncertainty that accounts for the difference in JVF components. It is varied by ±1σ in order to propagate the requirement efficiency between data and MC simulation electron energy scale uncertainty into the measured Z + jets is evaluated by varying the nominal JVF requirement in cross-sections. MC simulation to represent a few percent change in effi- The electron energy resolution has uncertainties associ- ciency [60]. The unfolding transfer matrix and the matching ated to the extraction of the resolution difference between efficiencies are re-derived, and the results of varying the JVF data and simulation using Z → ee events, to the knowledge requirement are propagated to the unfolded data. The devi- of the sampling term of the calorimeter energy resolution and ations from the nominal results are used as the systematic to the pile-up noise modelling. These uncertainties are evalu- uncertainty. ated in situ using the Z → ee events, and the total uncertainty Pile-up jets are effectively suppressed by the selection is calculated as the sum in quadrature of the different uncer- requirements. The jet yields in events with low μ and 123 Eur. Phys. J. C (2019) 79:847 Page 9 of 47 847 high μ are compared with the jet yields in events without sured Z + jets events, due to different amounts of background any requirements on μ. These jet yields agree with each contamination in the tails of the m ee distribution. other within the statistical uncertainties. The same result is To evaluate the template shape uncertainty due to the con- achieved by comparing the jet yields in events that have low trol region selection, a different set of electron identification or high numbers of reconstructed primary vertices with the criteria is used to derive a modified template. The selection jet yields in events from the nominal selection. Consequently, requires two reconstructed electrons with at least one elec- no additional pile-up uncertainty is introduced. tron that satisfies the ‘loose’ identification criteria, but not The jet energy resolution (JER) uncertainty accounts for the ‘medium’ ones. The difference between the nominal and the mis-modelling of the detector jet energy resolution by modified templates is used to create a symmetric template the MC simulation. To evaluate the JER uncertainty in the to provide up and down variations of this systematic uncer- measured Z + jets cross-sections, the energy of each jet in tainty. MC simulation is smeared by a random number taken from To estimate the template shape uncertainty due to the con- a Gaussian distribution with a mean value of one and a trol region contaminations by the other backgrounds, the width equal to the quadratic difference between the varied Z → τ τ , diboson, t t¯ and single-top-quark cross-sections resolution and the nominal resolution [61]. The smearing is are varied within their uncertainties. The dominant change repeated 100 times and then averaged. The transfer matrix in the template shape is due to t t¯ cross-section variation, determined from the averaged smearing is used for unfolding. while the contributions from the variation of the other back- The result is compared with the nominal measurement and ground cross-sections are small. The templates varied within the symmetrised difference is used as the JER uncertainty. the t t¯ cross-section uncertainties are used to propagate this The uncertainty that accounts for the mis-modelling of the uncertainty into the measurement. ‘medium’ jet quality criteria is evaluated using jets, selected The uncertainty in the multijet and W + jets background with the ‘loose’ and ‘tight’ criteria. The data-to-MC ratios template normalisation to the measured Z + jets events is of the reconstructed Z + jets distributions, obtained with dif- evaluated by fitting the template in the 66 GeV < m ee < ferent jet quality criteria, is compared with the nominal. An 140 GeV and 60 GeV < m ee < 116 GeV regions, excluding uncertainty of 1%, which takes the observed differences into the bins under the Z boson peak within the 80 GeV < m ee < account, is assigned to the measured Z + jets cross-section 100 GeV region, and in the 60 GeV < m ee < 140 GeV jet in all bins of |yjet | and pT . region, excluding the bins within the 70 GeV < m ee < 110 GeV. As a result, the normalisation varies up and down depending on the number of background events in both tails 8.3 Background uncertainties of the m ee distribution. The templates with the largest change in the normalisation are used to propagate this uncertainty The uncertainties in each background estimation are propa- into the measurement. gated to the measured Z + jets cross-sections. The data unfolding is repeated for each systematic varia- The data contamination by the Z → τ τ , diboson, t t¯ and tion of the backgrounds. The differences relative to the nom- single-top-quark backgrounds is estimated using simulated inal Z + jets cross-section are used as the systematic uncer- spectra scaled to the corresponding total cross-sections. Each tainties. of these background cross-sections has an uncertainty. The normalisation of each background is independently varied up and down by its uncertainty and propagated to the final 8.4 Unfolding uncertainty result. The MC simulation of the dominant t t¯ background jet The accuracy of the unfolding procedure depends on the qual- describes the shapes of the jet pT and yjet distributions in data to within a few percent [62], such that possible shape ity of the description of the measured spectrum in the MC mis-modellings of the jet kinematics in t t¯ events are covered simulation used to build the unfolding matrix. Two effects by the uncertainty in the total t t¯ cross-section. The shape are considered in order to estimate the influence of MC mod- mis-modellings in other backgrounds have negligible effect elling on the unfolding results: the shape of the particle-level on the final results. Therefore, no dedicated uncertainties due spectrum and the parton shower description. to the background shape mis-modelling are assigned. The impact of the particle-level shape mis-modelling on The uncertainties in the combined multijet and W + jets the unfolding is estimated using a data-driven closure test. For jet background arise from assumptions about the template shape this test, the particle-level (|yjet |, pT ) distribution in Sherpa and normalisation. The shape of the template depends on the is reweighted using the transfer matrix, such that the shape jet control region selection and the control region contamina- of the matched reconstructed (|yjet |, pT ) distribution agrees tions by the other backgrounds. The template normalisation with the measured spectrum corrected for the matching effi- jet depends on the m ee range, used to fit the template to the mea- ciency. The reweighted reconstructed (|yjet |, pT ) distribu- 123 847 Page 10 of 47 Eur. Phys. J. C (2019) 79:847 tions are then unfolded using the nominal Sherpa trans- If up and down systematic variations within a bin result in fer matrix. The results are compared with the reweighted uncertainties with the same sign, then the smaller uncertainty jet particle-level (|yjet |, pT ) spectrum and the relative differ- is set to zero. ences are assigned as the uncertainty. The impact of the differences in the parton shower 8.6 Statistical uncertainties description between Sherpa and Alpgen+Pythia on the unfolding results is estimated using the following test. Statistical uncertainties are derived using toy MC simulations jet The Alpgen+Pythia particle-level (|yjet |, pT ) spectrum is with 100 pseudo-experiments performed in both data and reweighted using the Alpgen+Pythia transfer matrix, such MC simulation. The data portion of the statistical uncertainty that its reconstruction-level distribution agrees with the one is evaluated by unfolding the replicas of the data using the jet in Sherpa. The original reconstructed (|yjet |, pT ) distribu- nominal transfer matrix and matching efficiencies. The MC tion in Sherpa is then unfolded using the reweighted Alp- portion is calculated using the replicas of the transfer matrix gen+Pythia transfer matrix. The results are compared with and matching efficiencies to unfold the nominal data. To cal- jet the original particle-level (|yjet |, pT ) spectrum in Sherpa culate the total statistical uncertainty in the measurement, and the differences are assigned as the uncertainty. the Z + jets distributions, obtained from pseudo-experiments Both unfolding uncertainties are symmetrised at the cross- drawn from the data yields, are unfolded using the transfer section level. matrices and efficiency corrections, calculated using pseudo- experiments in the MC simulation. The covariance matrices between bins of the measurement are computed using the unfolded results. The total statistical uncertainties are calcu- 8.5 Reduction of statistical fluctuations in systematic lated using the diagonal elements of the covariance matrices. uncertainties 8.7 Summary of experimental uncertainties The systematic uncertainties suffer from fluctuations of a statistical nature. The Z + jets cross-section measurement has 39 systematic The statistical components in the electron and jet uncer- uncertainty components. All systematic uncertainties are tainties are estimated using toy MC simulations with 100 treated as being uncorrelated with each other and fully cor- pseudo-experiments. Each Z + jets event in the systemati- jet related among |yjet | and pT bins. cally varied configurations is reweighted by a random num- The systematic uncertainties in the electron energy scale, ber taken from a Poisson distribution with a mean value of electron energy resolution, and electron trigger, reconstruc- one. As a result, 100 replicas of transfer matrix and match- tion and identification efficiencies are found to be below 1%. ing efficiencies are created for a given systematic uncertainty The JES in situ methods uncertainty is 2–5% in most bins variation, and are used to unfold the data. The replicas of of the measurement. The η-intercalibration uncertainty is unfolded spectra are then divided by the nominal Z + jets jet below 1% in the |yjet | < 1.0 and pT < 200 GeV regions, but distributions to create an ensemble of systematic uncertainty it increases with |yjet |, reaching 6–14% in the most forward spectra. The statistical component in the systematic uncer- rapidity bins. The η-intercalibration uncertainty is below tainties is calculated as the RMS across all replicas in an jet 1.5% for jets with pT > 200 GeV. The flavour-based JES ensemble. uncertainties are below 3%. The pile-up components of the The pseudo-experiments are not performed for the JER JES uncertainty are 0.5–1.5%. Other components of the JES systematic uncertainty. The statistical errors in the JER sys- uncertainty are below 0.2%. tematic uncertainty are calculated, considering the unfolded The JVF uncertainty is below 1%. data in the nominal and JER varied configurations to be inde- The JER is the dominant source of uncertainty in the pendent of each other. jet Z + jets cross-section in the 25 GeV < pT < 50 GeV region Each component of the unfolding uncertainty is derived jet using 100 pseudo-experiments to calculate the statistical with a 3–10% contribution. In the 50 GeV < pT < 100 GeV error. region the JER uncertainty is 1–3%, and below 1% for jets To reduce the statistical fluctuations, the bins are com- with higher transverse momenta. bined iteratively starting from both the right and left sides of The jet quality uncertainty is set constant at 1%, as dis- each systematic uncertainty spectrum until their significance cussed in Sect. 8.2. satisfies σ > 1.5. The result with the most bins remaining The unfolding uncertainty due to the shape of the particle- jet jet is used as the systematic uncertainty. A Gaussian kernel is level spectrum is 2–5% in the first pT bin, 25 GeV < pT < jet then applied to regain the fine binning and smooth out any 50 GeV. In the 50 GeV < pT < 200 GeV region, this additional statistical fluctuations. uncertainty is about 1.5% for central jets below |yjet | = 2, 123 Eur. Phys. J. C (2019) 79:847 Page 11 of 47 847 while for forward jets this uncertainty increases to 5%. In the where m ee is the electron pair’s invariant mass, pT,Z is the jet  pT > 200 GeV region, this uncertainty is below 1.5%. The transverse momentum of the Z boson and pT, partons is the unfolding uncertainty due to the parton shower description sum of the transverse momenta of the partons. jet is 0.7% in the 400 GeV < pT < 1050 GeV region, while The NLO Z + jets predictions are obtained using the for jets with smaller transverse momenta this uncertainty is CT14 NLO [64], NNPDF3.1 [65], JR14 NLO [66], HERA- negligible. PDF2.0 [67], MMHT2014 [68], ABMP16 [69] and ATLAS- The t t¯ background uncertainty is 0.02–0.6% in all bins epWZ16 [70] PDF sets. The PDFs are determined by various of the measurement. The Z → τ τ , diboson and single-top- groups using the experimental data and are provided with the quark background uncertainties are below 0.05%. uncertainties. The PDF uncertainties in the Z + jets cross- The multijet and W + jets background uncertainty is 0.1– sections are calculated at the 68% confidence level accord- jet ing to the prescription recommended by the PDF4LHC 1.2% depending on |yjet | and pT . The uncertainty in the background template normalisation is asymmetric due to dif- group [71]. ferent background contributions in the tails of the m ee dis- The following variations of factorisation and renor- tribution in the background normalisation evaluation proce- malisation scales are performed to assess the uncertainty dure. This uncertainty is +0.1 jet due to missing higher-order terms: {μR /2, μF }, {2μR , μF }, −0.4 % in the low pT bins, increasing {μR , μF /2}, {μR , 2μF }, {μR /2, μF /2}, {2μR , 2μF }. The to +0.4 jet −1.2 % in the high pT bins. The uncertainty in the multijet envelope of the cross-sections calculated with different scales and W + jets background control region selection increases jet is used as the uncertainty. from 0.03% to 0.6% as a function of pT . The contribution The uncertainty due to the strong coupling is estimated of the t t¯ cross-section variation to the multijet and W + jets using additional PDF sets, calculated with αS (m 2Z ) = 0.116 background uncertainty is below 0.1%. and αS (m 2Z ) = 0.120. The resulting uncertainty is scaled jet The statistical uncertainties are 0.5–4% in the pT < to the uncertainty of the world average αS (m 2Z ) = 0.118 ± jet 100 GeV region, 2–14% in the 100 GeV < pT < 300 GeV 0.0012, as recommended by the PDF4LHC group [71]. jet region, 8–39% in the 300 GeV < pT < 400 GeV region and The state-of-the-art NNLO Z + jets cross-section is cal- jet jet 11–18% in the last pT bin, 400 GeV < pT < 1050 GeV. culated by the authors of Ref. [16] using NNLOJET [72]. The smallest statistical uncertainty corresponds to central The NNLO predictions are convolved with the CT14 PDF. rapidity regions, while the largest uncertainty corresponds to The renormalisation and factorisation scales are set similarly forward rapidity regions. to those in NLO calculations. The experimental uncertainties are shown in Fig. 2. The largest total systematic uncertainty of 7–12% is in the 9.2 Non-perturbative correction jet 25 GeV < pT < 50 GeV region, where the uncertainty increases from central rapidity jets to the forward rapid- The fixed-order predictions are obtained at the parton level. ity jets, and up to 15% for the forward rapidity jets in Bringing fixed-order predictions to the particle level for com- jet the 100 GeV < pT < 200 GeV region. The total sys- parisons with the measured Z + jets cross-sections requires jet a non-perturbative correction (NPC) that accounts for both tematic uncertainty decreases with increasing pT . In the jet the hadronisation and underlying-event effects. 400 GeV < pT < 1050 GeV region the total systematic The NPCs are studied using several MC generators to uncertainty is 2–5%. The luminosity uncertainty of 1.9% is account for differences in the modelling of hadronisation not shown and not included in the total uncertainty and its and the underlying event. The studies are done using the components. leading-logarithm parton shower MC generators Pythia v. 8.210 with the A14 [73] underlying-event tune and Her- wig++ v. 2.7.1 with the UE-EE5 tune [74], and the multi- 9 Fixed-order predictions and theoretical uncertainties leg matrix element MC generators Sherpa v. 1.4.5 with the CT10 PDF, Sherpa v. 2.2.0 with NNPDF 2.3 [75] and Mad- 9.1 Fixed-order calculations Graph v. 2.2.3 [76], supplemented with parton showers from Pythia v. 8.210 with the A14 tune. Theoretical Z + jets predictions at NLO are calculated using The NPCs are calculated using the ratios of Z + jets cross- MCFM [40] interfaced to APPLgrid [63] for fast convolution sections obtained at the particle level to those at the par- with PDFs. The renormalisation and factorisation scales, μR ton level. The correction derived using Sherpa v. 1.4.5 is and μF , are set to the nominal one in this analysis. The envelope of the non-   perturbative corrections, calculated with other MC gener- m 2ee + pT,Z 2 + pT, partons ators, is used as the systematic uncertainty. The NPCs in μR = μF = , different MC generators are shown in Fig. 3. The nominal 2 123 847 Page 12 of 47 Eur. Phys. J. C (2019) 79:847 Relative uncertainty Relative uncertainty jet jet 0.4 ATLAS 25 GeV < pT < 50 GeV 0.15 ATLAS 50 GeV < pT < 100 GeV s = 8 TeV, 19.9 fb-1 s = 8 TeV, 19.9 fb-1 0.3 Z(→ee) + jets Z(→ee) + jets 0.1 0.2 anti-kt R =0.4 anti-kt R =0.4 0.1 0.05 0 0 −0.1 −0.05 Total Sys. Uncertainty Total Sys. Uncertainty −0.2 Jet energy scale Jet energy scale Jet energy resolution −0.1 Jet energy resolution −0.3 Unfolding Unfolding −0.4 Other −0.15 Other Stat. Uncertainty Stat. Uncertainty 0 0.5 1 1.5 2 0 0.5 1 1.5 2 2.5 3 |y | |y | jet jet jet jet (a) 25 GeV < pT < 50 GeV (b) 50 GeV < pT < 100 GeV Relative uncertainty Relative uncertainty jet jet 0.15 ATLAS 100 GeV < pT < 200 GeV 0.15 ATLAS 200 GeV < pT < 300 GeV s = 8 TeV, 19.9 fb-1 s = 8 TeV, 19.9 fb-1 0.1 Z(→ee) + jets 0.1 Z(→ee) + jets anti-kt R =0.4 anti-kt R =0.4 0.05 0.05 0 0 −0.05 −0.05 Total Sys. Uncertainty Total Sys. Uncertainty Jet energy scale Jet energy scale −0.1 Jet energy resolution −0.1 Jet energy resolution Unfolding Unfolding −0.15 Other −0.15 Other Stat. Uncertainty Stat. Uncertainty 0 0.5 1 1.5 2 2.5 3 0 0.5 1 1.5 2 2.5 3 |y | |y | jet jet jet jet (c) 100 GeV < pT < 200 GeV (d) 200 GeV < pT < 300 GeV Relative uncertainty Relative uncertainty 0.4 jet 0.4 jet ATLAS 300 GeV < p < 400 GeV ATLAS 400 GeV < p < 1050 GeV -1 T -1 T 0.3 s = 8 TeV, 19.9 fb 0.3 s = 8 TeV, 19.9 fb Z(→ee) + jets Z(→ee) + jets 0.2 anti-kt R =0.4 0.2 anti-kt R =0.4 0.1 0.1 0 0 −0.1 −0.1 Total Sys. Uncertainty Total Sys. Uncertainty −0.2 Jet energy scale −0.2 Jet energy scale Jet energy resolution Jet energy resolution −0.3 Unfolding −0.3 Unfolding Other Other −0.4 Stat. Uncertainty −0.4 Stat. Uncertainty 0 0.5 1 1.5 2 2.5 3 0 0.5 1 1.5 2 2.5 |y | |y | jet jet jet jet (e) 300 GeV < pT < 400 GeV (f) 400 GeV < pT < 1050 GeV Fig. 2 Experimental uncertainties in the measured double-differential in quadrature of two unfolding uncertainties. The ‘other’ systematic jet Z + jets production cross-section as a function of |yjet | in pT bins. uncertainty is the sum in quadrature of the electron uncertainties, back- The jet energy scale, jet energy resolution, unfolding, ‘other’ and total ground uncertainties, JVF and jet quality uncertainties. The total sys- systematic uncertainties are shown with different colours overlaid. The tematic uncertainty is the sum in quadrature of all systematic uncer- jet energy scale uncertainty is the sum in quadrature of the jet energy tainty components except for the luminosity uncertainty of 1.9%. The scale uncertainty components. The unfolding uncertainty is the sum total statistical uncertainties are shown with vertical error bars 123 Eur. Phys. J. C (2019) 79:847 Page 13 of 47 847 Non-perturbative correction 1.2 Non-perturbative correction ATLAS Simulation SHERPA 1.4 CT10 1.1 ATLAS Simulation SHERPA 1.4 CT10 s=8 TeV, Z(→ee) + jets SHERPA 2.2 NNPDF s=8 TeV, Z(→ee) + jets SHERPA 2.2 NNPDF 1.15 MADGRAPH + PYTHIA8 A14 1.08 MADGRAPH + PYTHIA8 A14 anti-k t R =0.4 PYTHIA8 A14 anti-k t R =0.4 PYTHIA8 A14 jet 25 GeV 200 GeV region, both the negative and positive is below 2%. These corrections together with uncertainties parts of the total uncertainty are within 6% in most bins. are provided in HEPData [77]. The uncertainty in the QED correction is below 0.5% and is negligible in the fixed-order theory predictions. 9.3 QED radiation correction The fixed-order Z + jets cross-section predictions must be 10 Results corrected for the QED radiation in order to be compared with data. The correction is determined as the ratio of two The double-differential Z + jets cross-section as a function jet Z + jets cross-sections, one calculated using dressed elec- of |yjet | and pT is calculated as trons after QED final-state radiation (FSR), with all pho- tons clustered within a cone of R = 0.1 around the elec- d2 σ 1 NiP tron axis, and the other calculated using Born-level electrons = , jet d pT d|yjet | L p jet |yjet | at the lowest order in the electromagnetic coupling αQED T prior to QED FSR radiation. The baseline correction is cal- culated using the Sherpa MC samples, while the correc- where L is the integrated luminosity, NiP is the number of jets jet tion calculated using Alpgen+Pythia is used to estimate in data at the particle level as given in Eq. (1), and pT and the uncertainty. The uncertainty is calculated as the width |yjet | are the widths of the jet transverse momentum and of the envelope of corrections obtained with these two MC absolute jet rapidity ranges for bin i, respectively. The back- generators. The results are shown in Fig. 4. The QED cor- grounds are subtracted before data unfolding is performed to jet rection is largest in the 25 GeV < pT < 50 GeV region. It is obtain NiP . about 5% for jets in the central absolute rapidity regions. In The measured Z + jets cross-section covers five orders jet the pT > 50 GeV regions the QED correction is 1.5–2.5%, of magnitude and falls steeply as a function of |yjet | and jet decreasing as a function of jet transverse momentum. The pT . A summary of measured cross-sections, together with QED corrections calculated using Alpgen+Pythia are in the systematic and statistical uncertainties, is provided good agreement with those from Sherpa. These corrections in Appendix A. The measured cross-sections with the full together with uncertainties are provided in HEPData. breakdown of all uncertainties are provided in HEPData. The comparisons with the theoretical predictions are 9.4 Summary of theoretical uncertainties shown in Figs. 7, 8, 9, 10, 11 and 12. The fixed-order theo- retical predictions are corrected for the non-perturbative and The total theoretical uncertainties are calculated as the sum in QED radiation effects. The NLO predictions are lower than quadrature of the effects of the PDF, scale, and αS uncertain- the data by approximately 5–10%. However, this difference ties, and the uncertainties due to non-perturbative and QED is covered by the uncertainties. The NNLO calculations com- radiation effects. pensate for the NLO-to-data differences in most bins of the The uncertainties for the Z + jets cross-section calculated measurement and show better agreement with the central val- jet at NLO using the CT14 PDF as a function of |yjet | in pT bins ues of the cross-sections in data. The Sherpa v. 1.4 and Alp- are shown in Fig. 5. The total uncertainties are dominated gen+Pythia MC-to-data ratios are approximately constant jet jet by the scale and NPC uncertainties in the pT < 100 GeV across all |yjet | bins, but a dependence on pT is observed. region, where they reach ±15% and −10%, respectively. In The Sherpa v. 1.4 predictions are lower than the data by jet jet the pT > 100 GeV region, the scale uncertainty alone domi- about 10% in the 25 GeV < pT < 200 GeV region, but jet nates, as the NPC uncertainty decreases for high jet transverse in the pT > 200 GeV region they agree within a few per- momenta. The total uncertainty in this region is 10–20%. cent. The Alpgen+Pythia predictions agree with data in the jet Other uncertainties are below 5%. 25 GeV < pT < 100 GeV region, but exceed the data as a The NNLO uncertainties are shown in Fig. 6. The scale jet function of pT , the largest difference being about 20% in uncertainty at NNLO is significantly reduced. This uncer- jet jet jet the highest pT bin, 400 GeV < pT < 1050 GeV. tainty is below 1% in the 25 GeV < pT < 50 GeV bin, Additionally, data is compared to the Sherpa v. 2.2 pre- jet increasing to 5% in the 400 GeV < pT < 1050 GeV bin. diction. In this prediction, the matrix elements are calcu- jet In the pT < 200 GeV region, the negative part of the total lated with NLO accuracy for the inclusive Z production uncertainty is dominated by the NPC uncertainty and its abso- process up to two additional partons in the final state, and 123 Eur. Phys. J. C (2019) 79:847 Page 15 of 47 847 Dressed / Born-level 0.97 0.982 Dressed / Born-level ATLAS Simulation ATLAS Simulation SHERPA 1.4 SHERPA 1.4 s=8 TeV, Z(→ee) + jets s=8 TeV, Z(→ee) + jets 0.965 ALPGEN+PY6 ALPGEN+PY6 anti-k t R =0.4 anti-k t R =0.4 jet Uncertainty 0.98 jet Uncertainty 25 GeV < p < 50 GeV 50 GeV < p < 100 GeV T T 0.96 0.978 0.955 0.976 0.95 0.945 0.974 0 0.5 1 1.5 2 0 1 2 3 |y | |y | jet jet jet jet (a) 25 GeV < pT < 50 GeV (b) 50 GeV < pT < 100 GeV 0.99 0.99 Dressed / Born-level Dressed / Born-level ATLAS Simulation ATLAS Simulation SHERPA 1.4 SHERPA 1.4 s=8 TeV, Z(→ee) + jets s=8 TeV, Z(→ee) + jets ALPGEN+PY6 0.989 ALPGEN+PY6 0.988 anti-k t R =0.4 anti-k t R =0.4 100 GeV < p jet < 200 GeV Uncertainty 200 GeV < p jet < 300 GeV Uncertainty T 0.988 T 0.986 0.987 0.984 0.986 0.982 0.985 0.98 0.984 0 1 2 3 0 1 2 3 |y | |y | jet jet jet jet (c) 100 GeV < pT < 200 GeV (d) 200 GeV < pT < 300 GeV 0.99 0.99 Dressed / Born-level Dressed / Born-level ATLAS Simulation ATLAS Simulation SHERPA 1.4 SHERPA 1.4 s=8 TeV, Z(→ee) + jets s=8 TeV, Z(→ee) + jets 0.989 ALPGEN+PY6 0.989 ALPGEN+PY6 anti-k t R =0.4 anti-k t R =0.4 300 GeV < p jet < 400 GeV Uncertainty 400 GeV < p jet < 1050 GeV Uncertainty 0.988 T 0.988 T 0.987 0.987 0.986 0.986 0.985 0.985 0.984 0.984 0 0.5 1 1.5 2 2.5 3 0 0.5 1 1.5 2 2.5 |y | |y | jet jet jet jet (e) 300 GeV < pT < 400 GeV (f) 400 GeV < pT < 1050 GeV jet Fig. 4 The correction for QED radiation effects for the Z + jets production cross-section as a function of |yjet | in pT bins. The spread of predictions represents the uncertainty 123 847 Page 16 of 47 Eur. Phys. J. C (2019) 79:847 Relative uncertainty 0.25 Relative uncertainty Z(→ee) + jets NLO (CT14 PDF) Z(→ee) + jets NLO (CT14 PDF) 0.2 0.2 Scale uncertainty Total pQCD uncertainty Scale uncertainty Total pQCD uncertainty PDF uncertainty Total theory uncertainty 0.15 PDF uncertainty Total theory uncertainty α s uncertainty α s uncertainty 0.1 0.1 0.05 0 0 −0.05 −0.1 s=8 TeV −0.1 s=8 TeV jet jet anti-k t R =0.4 25 GeV

200 GeV region. The differences PDFs. The MEs are merged with Sherpa parton shower between the cross-sections calculated at NLO accuracy with using the ME+PS@NLO [78] prescription. This prediction various PDF sets are covered by the theoretical uncertain- shows a good agreement with data in all bins of the measure- ties. In the NNLO calculations, the difference between CT14 ment. PDF and NNPDF3.1 predictions is 2–5%, which is compa- The ratios between the measured Z + jets production rable to the size of the theoretical uncertainties, as shown cross-sections and the NLO predictions, calculated with var- in Fig. 16. ious PDF sets, are shown in Figs. 13, 14 and 15. The cal- culations with MMHT2014 and NNPDF3.1 predict 1–2% larger cross-sections compared to those using the CT14 PDF. The cross-sections calculated with ATLAS-epWZ16 PDF 11 Quantitative data and theory comparison are larger by 2–3%. The ABMP16 and HERAPDF2.0 cross- jet section predictions in the |yjet | < 2.0 and pT < 100 GeV The fixed-order pQCD predictions at NNLO accuracy, cor- regions are 3–5% larger than those from the CT14 PDF, while rected for electroweak and non-perturbative effects, are quan- in other bins of the measurement their predictions are up titatively compared with the measured cross-section using a to 5% lower than those obtained with the CT14 PDF. The χ 2 function that accounts for both the experimental and the- JR14 PDF predictions are 2–5% lower than those from the oretical uncertainties 123 Eur. Phys. J. C (2019) 79:847 Page 19 of 47 847 d2σ/dp /d|y | [fb/GeV] d2σ/dp /d|y | [fb/GeV] jet 100 GeV

50 GeV range, with jet different MC simulations (two-point systematic uncertain- not so good agreement in the 25 < pT < 50 GeV range. ties) are less justified. In order to investigate the impact of The level of agreement between data and predictions is very these assumptions on the results of χ 2 tests performed in similar for different PDF sets. this section, the uncertainties that are derived from compar- In addition to fits of the predictions to measured cross- isons of two different MC models, namely uncertainties in jet sections in the individual pT bins, all measured data points the jet flavour composition and jet flavour response, were jet are fitted simultaneously. Several ranges of pT are consid- split into two subcomponents [80,81]. The first subcompo- ered. The results of the global fits are presented in Table 2. nent is derived by multiplying the original nuisance parame- jet Very good agreement between measurement and calculation ter with a linear function of pT and jet absolute rapidity and jet is observed when using the pT > 50 GeV bins, while not so the second subcomponent is constructed such that the sum 123 Eur. Phys. J. C (2019) 79:847 Page 21 of 47 847 ATLAS Theory/Data Theory/Data jet jet 1.3 25 GeV < p T < 50 GeV 1.3 50 GeV < p T < 100 GeV 1.2 1.2 s=8 TeV, 19.9 fb-1 1.1 1.1 anti-kt R =0.4 1 1 0.9 0.9 0.8 0.8 Data 0.7 0.7 jet jet 1.3 100 GeV < p < 200 GeV T 1.3 200 GeV < p < 300 GeV T NLO QCD 1.2 1.2 × kNP × kQED 1.1 1.1 1 1 CT14 0.9 0.9 MMHT2014 0.8 0.8 0.7 0.7 NNPDF 3.1 jet jet 1.4 300 GeV < p < 400 GeV 1.4 400 GeV < p < 1050 GeV T T 1.2 1.2 1 1 0.8 0.8 0.6 0.6 0 0.5 1 1.5 2 2.5 3 0 0.5 1 1.5 2 2.5 3 |yjet| |yjet| Fig. 13 Ratio of the measured Z + jets production cross-section and of the PDF, scale, and αS uncertainties, and the uncertainties from the the NLO QCD predictions, obtained using MCFM, corrected for the non-perturbative and QED radiation corrections. The grey band shows non-perturbative and QED radiation effects as a function of |yjet | and the sum in quadrature of the statistical and systematic uncertainties in jet the measurement except for the luminosity uncertainty of 1.9% pT bins. Theoretical predictions are calculated using various PDF sets. The coloured error bars represent the sum in quadrature of the effects ATLAS Theory/Data Theory/Data jet jet 1.3 25 GeV < p T < 50 GeV 1.3 50 GeV < p T < 100 GeV 1.2 1.2 s=8 TeV, 19.9 fb-1 1.1 1.1 anti-kt R =0.4 1 1 0.9 0.9 0.8 0.8 Data 0.7 0.7 jet jet 1.3 100 GeV < p < 200 GeV T 1.3 200 GeV < p < 300 GeV T NLO QCD 1.2 1.2 × kNP × kQED 1.1 1.1 1 1 CT14 0.9 0.9 HERAPDF 2.0 0.8 0.8 0.7 0.7 ABMP16 jet jet 1.4 300 GeV < p < 400 GeV 1.4 400 GeV < p < 1050 GeV T T 1.2 1.2 1 1 0.8 0.8 0.6 0.6 0 0.5 1 1.5 2 2.5 3 0 0.5 1 1.5 2 2.5 3 |yjet| |yjet| Fig. 14 Ratio of the measured Z + jets production cross-section and of the PDF, scale, and αS uncertainties, and the uncertainties from the the NLO QCD predictions, obtained using MCFM, corrected for the non-perturbative and QED radiation corrections. The grey band shows non-perturbative and QED radiation effects as a function of |yjet | and the sum in quadrature of the statistical and systematic uncertainties in jet the measurement except for the luminosity uncertainty of 1.9% pT bins. Theoretical predictions are calculated using various PDF sets. The coloured error bars represent the sum in quadrature of the effects in quadrature of both subcomponents is equal to the original using proton–proton collision data with an integrated lumi- nuisance parameter. These decorrelations did not result in a nosity 19.9 fb−1 collected by the ATLAS experiment at the √ large improvement in the χ 2 values. LHC in 2012 at s = 8 TeV centre-of-mass energy. The measurement is performed as a function of the absolute jet rapidity and the jet transverse momentum. 12 Conclusions The measured cross-section is corrected for detector effects and the results are provided at the particle level. The double-differential Z + jets cross-section, with the Z The measurements are compared with theory predictions, boson decaying into an electron–positron pair, is measured calculated using the multi-leg matrix element MC genera- 123 847 Page 22 of 47 Eur. Phys. J. C (2019) 79:847 ATLAS Theory/Data Theory/Data jet jet 1.3 25 GeV < p T < 50 GeV 1.3 50 GeV < p T < 100 GeV 1.2 1.2 s=8 TeV, 19.9 fb-1 1.1 1.1 anti-kt R =0.4 1 1 0.9 0.9 0.8 0.8 Data 0.7 0.7 jet jet 1.3 100 GeV < p < 200 GeV T 1.3 200 GeV < p < 300 GeV T NLO QCD 1.2 1.2 × kNP × kQED 1.1 1.1 1 1 CT14 0.9 0.9 JR14 0.8 0.8 0.7 0.7 ATLAS WZ16 jet jet 1.4 300 GeV < p T < 400 GeV | 1.4 400 GeV < p T < 1050 GeV 1.2 1.2 1 1 0.8 0.8 0.6 0.6 0 0.5 1 1.5 2 2.5 3 0 0.5 1 1.5 2 2.5 3 |yjet| |yjet| Fig. 15 Ratio of the measured Z + jets production cross-section and of the PDF, scale, and αS uncertainties, and the uncertainties from the the NLO QCD predictions, obtained using MCFM, corrected for the non-perturbative and QED radiation corrections. The grey band shows non-perturbative and QED radiation effects as a function of |yjet | and the sum in quadrature of the statistical and systematic uncertainties in jet the measurement except for the luminosity uncertainty of 1.9% pT bins. Theoretical predictions are calculated using various PDF sets. The coloured error bars represent the sum in quadrature of the effects ATLAS Theory/Data Theory/Data jet jet 1.3 25 GeV < p T < 50 GeV 1.3 50 GeV < p T < 100 GeV 1.2 1.2 s=8 TeV, 19.9 fb-1 1.1 1.1 anti-kt R =0.4 1 1 0.9 0.9 0.8 0.8 Data 0.7 0.7 jet jet 1.3 100 GeV < p < 200 GeV T 1.3 200 GeV < p < 300 GeV T NNLO QCD 1.2 1.2 × kNP × kQED 1.1 1.1 1 1 CT14 0.9 0.9 NNPDF 3.1 0.8 0.8 0.7 0.7 jet jet 1.4 300 GeV < p < 400 GeV 1.4 400 GeV < p < 1050 GeV T T 1.2 1.2 1 1 0.8 0.8 0.6 0.6 0 0.5 1 1.5 2 2.5 3 0 0.5 1 1.5 2 2.5 3 |yjet| |yjet| Fig. 16 Ratio of the measured Z + jets production cross-section and of the PDF, scale, and αS uncertainties, and the uncertainties from the the NNLO QCD predictions, obtained using NNLOJET, corrected for non-perturbative and QED radiation corrections. The grey band shows the non-perturbative and QED radiation effects as a function of |yjet | and the sum in quadrature of the statistical and systematic uncertainties in jet the measurement except for the luminosity uncertainty of 1.9% pT bins. Theoretical predictions are calculated using various PDF sets. The coloured error bars represent the sum in quadrature of the effects tors Sherpa and Alpgen+Pythia, supplemented with par- The uncertainties in the measured cross-sections are about ton shower simulations. Sherpa v. 1.4 and Alpgen+Pythia half of the theoretical uncertainties in the NLO calculations in describe well the shape of the Z + jets distribution as a func- most bins of the measurement and are approximately similar jet tion of |yjet |, but not so well as a function of pT . Sherpa v. to the uncertainties in the NNLO calculations. 2.2 is in good agreement with data in all bins of the measure- The measured double-differential Z + jets cross-section ment. provides a precision input to constrain the parton distribution The parton-level fixed-order Z + jets predictions, cor- functions. rected for hadronisation, underlying-event and QED radi- ation effects, agree with the data within the uncertainties. 123 Eur. Phys. J. C (2019) 79:847 Page 23 of 47 847 jet Table 1 Values of χuncorr 2 and χcorr 2 evaluated for theory predictions χcorr 2 . The fits are performed individually in each p bin. The predic- T corrected for non-perturbative and electroweak effects and measured tions are calculated using several NNLO QCD PDF sets and one NLO Z + jets cross-sections. The total χ 2 is equal to the sum of χuncorr 2 and QCD PDF set, CT14nlo CT14nlo CT14 NNPDF3.1 MMHT2014 ABMP16 jet pT range (GeV) n bins χuncorr 2 χcorr 2 χuncorr 2 χcorr 2 χuncorr 2 χcorr 2 χuncorr 2 χcorr 2 χuncorr 2 χcorr 2 jet 25 < pT < 50 12 31.5 14.7 32.2 15.6 33.6 15.7 32.7 15.9 31.8 13.8 jet 50 < pT < 100 17 23.6 2.6 24.2 2.3 27.1 2.3 26.3 2.1 24.9 2.5 jet 100 < pT < 200 17 24.9 3.6 24.8 2.5 26.1 1.8 27.2 2.8 22.6 1.5 jet 200 < pT < 300 7 3.1 0.9 2.9 0.7 3.6 0.1 4.5 0.5 2.7 0.2 jet 300 < pT < 400 6 2.7 0.1 2.7 0.1 2.9 0.1 3.2 0.0 2.5 0.3 jet 400 < pT < 1050 4 1.9 0.4 1.9 0.4 1.9 0.5 2.0 0.3 1.7 0.8 Table 2 Values of χ 2 evaluated jet pT range (GeV) CT14nlo CT14 NNPDF3.1 MMHT2014 ABMP16 from the comparison of theory predictions corrected for jet non-perturbative and pT > 25 GeV jet electroweak effects with the χuncorr 2 25 < pT < 50 38.9 40.5 42.3 41.3 38.7 measured Z + jets jet 50 < pT < 100 32.1 33.0 37.5 39.2 31.6 cross-sections. The fits are jet performed globally in all bins of 100 < pT < 200 26.4 27.8 31.0 31.7 27.8 the measurement within several jet jet 200 < pT < 300 6.3 6.3 5.1 5.6 4.1 pT ranges. The predictions are jet calculated using several 300 < pT < 400 2.9 3.0 2.9 3.1 2.5 NNLO QCD PDF sets and one jet 400 < pT < 1050 2.2 2.4 2.2 2.3 1.7 NLO QCD PDF set, CT14nlo χcorr 2 21.2 19.8 19.3 18.7 17.8 χ 2 /n bins 129.9/63 132.6/63 140.0/63 141.9/63 124.3/63 jet pT > 50 GeV jet χuncorr 2 50 < pT < 100 24.4 24.8 26.9 27.1 24.8 jet 100 < pT < 200 24.4 24.6 26.6 27.7 22.7 jet 200 < pT < 300 4.4 4.2 4.4 4.7 3.4 jet 300 < pT < 400 2.7 2.8 3.0 3.1 2.5 jet 400 < pT < 1050 3.6 4.0 3.8 3.9 2.9 χcorr 2 6.5 4.7 4.3 5.1 4.1 χ 2 /n bins 66.1/51 65.2/51 69.0/51 71.6/51 60.4/51 jet pT > 100 GeV jet χuncorr 2 100 < pT < 200 24.8 25.0 25.9 26.6 22.4 jet 200 < pT < 300 3.2 3.3 4.1 4.4 3.3 jet 300 < pT < 400 2.7 2.8 3.0 3.1 2.6 jet 400 < pT < 1050 3.4 3.8 3.6 3.6 3.3 χcorr 2 4.9 3.7 2.7 4.1 2.3 χ 2 /n bins 39.0/34 38.5/34 39.3/34 41.8/34 33.8/34 Acknowledgements We thank CERN for the very successful oper- France; SRNSFG, Georgia; BMBF, HGF, and MPG, Germany; GSRT, ation of the LHC, as well as the support staff from our institutions Greece; RGC, Hong Kong SAR, China; ISF and Benoziyo Center, without whom ATLAS could not be operated efficiently. We acknowl- Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, edge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, MNE/IFA, Romania; MES of Russia and NRC KI, Russian Federation; Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; JINR; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIEN- DST/NRF, South Africa; MINECO, Spain; SRC and Wallenberg Foun- CIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Repub- dation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzer- lic; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DRF/IRFU, land; MOST, Taiwan; TAEK, Turkey; STFC, UK; DOE and NSF, USA. 123 847 Page 24 of 47 Eur. Phys. J. C (2019) 79:847 In addition, individual groups and members have received support from are stored in appropriate repositories such as HEPDATA (http://hepdata. BCKDF, CANARIE, CRC and Compute Canada, Canada; COST, ERC, cedar.ac.uk/). ATLAS also strives to make additional material related to ERDF, Horizon 2020, and Marie Skłodowska-Curie Actions, European the paper available that allows a reinterpretation of the data in the con- Union; Investissements d’ Avenir Labex and Idex, ANR, France; DFG text of new theoretical models. For example, an extended encapsulation and AvH Foundation, Germany; Herakleitos, Thales and Aristeia pro- of the analysis is often provided for measurements in the framework grammes co-financed by EU-ESF and the Greek NSRF, Greece; BSF- of RIVET (http://rivet.hepforge.org/).” This information is taken from NSF and GIF, Israel; CERCA Programme Generalitat de Catalunya, the ATLAS Data Access Policy, which is a public document that can be Spain; The Royal Society and Leverhulme Trust, UK. The crucial com- downloaded from http://opendata.cern.ch/record/413.] puting support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF Open Access This article is distributed under the terms of the Creative (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), Commons Attribution 4.0 International License (http://creativecomm KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), ons.org/licenses/by/4.0/), which permits unrestricted use, distribution, PIC (Spain), ASGC (Taiwan), RAL (UK) and BNL (USA), the Tier-2 and reproduction in any medium, provided you give appropriate credit facilities worldwide and large non-WLCG resource providers. Major to the original author(s) and the source, provide a link to the Creative contributors of computing resources are listed in Ref. [82]. Commons license, and indicate if changes were made. Funded by SCOAP3 . Data Availability Statement This manuscript has no associated data or the data will not be deposited. [Authors’ comment: “All ATLAS sci- entific output is published in journals, and preliminary results are made available in Conference Notes. All are openly available, without restric- Appendix tion on use by external parties beyond copyright law and the standard conditions agreed by CERN. Data associated with journal publications A Tables of measured cross-sections are also made available: tables and data from plots (e.g. cross section values, likelihood profiles, selection efficiencies, cross section limits, ...) Table 3 The measured double-differential Z + jets production cross- JES ); sum in quadra- to pile-up corrections of the jet kinematics (δpile-up jet sections as a function of |yjet | in the 25 GeV < pT < 50 GeV range. JES ture of the flavour-based uncertainties (δflavour ); punch-through uncer- δdata and δMC are the statistical uncertainties in data and MC simulation, stat stat JES tainty (δpthrough ); JER uncertainty (δ JER ); JVF uncertainty (δ JVF ); sum sys respectively. δtot is the total systematic uncertainty and includes the fol- in quadrature of the unfolding uncertainties (δ unf ); sum in quadrature lowing components: uncertainties due to electron reconstruction (δrec el ), el el of the uncertainties due to MC generated backgrounds normalisation identification (δID ) and trigger (δtrig ) efficiencies; electron energy scale bg (δMC ); sum in quadrature of the uncertainty due to combined multijet el ) and energy resolution (δ el ) uncertainties; sum in quadrature (δscale res bg JES ); sum in quadra- and W + jets backgrounds (δmult ); uncertainty due to jet quality selec- of the uncertainties from JES in situ methods (δin situ qual tion (δ ). All uncertainties are given in %. The luminosity uncertainty ture of the uncertainties from JES η-intercalibration methods (δη-int JES ); an of 1.9% is not shown and not included in the total uncertainty and its uncertainty of the measured single-hadron response (δhadron JES ); MC non- components JES ); sum in quadrature of the uncertainties due closure uncertainty (δclosure d2σ sys |yjet | jet δdata stat δMC stat δtot δrec el δID el δtrig el δscale el δres el δin JES situ δη−int JES d|yjet |dpT (fb/GeV) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) 0.0–0.2 1643.603 0.42 0.51 + 6.70 + 0.08 + 0.23 + 0.31 − 0.16 + 0.01 + 3.04 + 0.30 − 6.80 − 0.08 − 0.27 − 0.44 + 0.14 − 0.01 − 3.04 − 0.49 0.2–0.4 1595.690 0.34 0.60 + 6.72 + 0.08 + 0.23 + 0.31 − 0.16 + 0.01 + 3.16 + 0.30 − 6.70 − 0.08 − 0.27 − 0.44 + 0.14 − 0.01 − 3.02 − 0.49 0.4–0.6 1587.440 0.37 0.60 + 7.01 + 0.08 + 0.23 + 0.31 − 0.16 + 0.01 + 3.17 + 0.30 − 7.14 − 0.08 − 0.27 − 0.44 + 0.14 − 0.01 − 3.14 − 0.49 0.6–0.8 1569.884 0.38 0.60 + 7.02 + 0.08 + 0.23 + 0.31 − 0.16 + 0.01 + 3.19 + 0.30 − 7.24 − 0.08 − 0.27 − 0.44 + 0.14 − 0.01 − 3.25 − 0.49 0.8–1.0 1520.883 0.36 0.59 + 6.98 + 0.08 + 0.23 + 0.31 − 0.16 + 0.01 + 3.33 + 0.30 − 7.04 − 0.08 − 0.27 − 0.33 + 0.14 − 0.01 − 3.25 − 0.49 1.0–1.2 1393.139 0.38 0.64 + 8.49 + 0.08 + 0.23 + 0.31 − 0.16 + 0.01 + 3.60 + 0.76 − 8.32 − 0.08 − 0.27 − 0.33 + 0.14 − 0.01 − 3.35 − 0.49 1.2–1.4 1377.328 0.47 0.57 + 11.78 + 0.08 + 0.23 + 0.31 − 0.16 + 0.01 + 3.69 + 0.76 − 11.50 − 0.08 − 0.27 − 0.33 + 0.14 − 0.01 − 3.29 − 0.69 1.4–1.6 1228.213 0.42 0.60 + 12.01 + 0.08 + 0.23 + 0.31 − 0.16 + 0.01 + 3.65 + 1.44 − 11.69 − 0.08 − 0.27 − 0.33 + 0.14 − 0.01 − 3.22 − 1.14 1.6–1.8 987.654 0.48 0.64 + 12.09 + 0.08 + 0.23 + 0.31 − 0.16 + 0.01 + 3.37 + 1.42 − 11.95 − 0.08 − 0.27 − 0.33 + 0.14 − 0.01 − 3.10 − 1.25 123 Eur. Phys. J. C (2019) 79:847 Page 25 of 47 847 Table 3 continued d2σ sys |yjet | jet δdata stat δMC stat δtot δrec el δID el δtrig el δscale el δres el δin JES situ δη−int JES d|yjet |dpT (fb/GeV) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) 1.8–2.0 944.560 0.45 0.65 + 10.24 + 0.08 + 0.23 + 0.40 − 0.16 + 0.01 + 3.38 + 1.58 − 10.02 − 0.08 − 0.27 − 0.33 + 0.14 − 0.01 − 3.09 − 1.25 2.0–2.2 871.035 0.49 0.85 + 10.30 + 0.08 + 0.23 + 0.40 − 0.16 + 0.01 + 3.65 + 1.96 − 10.18 − 0.08 − 0.27 − 0.33 + 0.14 − 0.01 − 3.41 − 1.74 2.2–2.4 749.498 0.54 0.80 + 11.14 + 0.08 + 0.23 + 0.40 − 0.16 + 0.01 + 4.23 + 2.57 − 10.92 − 0.08 − 0.27 − 0.33 + 0.14 − 0.01 − 3.95 − 2.33 bg bg |yjet | δhadron JES δclosure JES δpile-up JES δflavour JES δpthrough JES δ JER δ JVF δ unf δMC δmult δ qual (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) 0.0–0.2 + 0.00 + 0.01 + 1.63 + 2.95 + 0.00 − 3.83 + 0.47 + 2.84 + 0.06 + 0.14 + 1.00 − 0.01 − 0.01 − 1.68 − 3.04 − 0.02 + 3.83 − 0.72 − 2.84 − 0.05 − 0.38 − 1.00 0.2–0.4 + 0.00 + 0.01 + 1.65 + 3.04 + 0.00 − 3.89 + 0.47 + 2.55 + 0.06 + 0.14 + 1.00 − 0.01 − 0.01 − 1.60 − 3.05 − 0.02 + 3.89 − 0.72 − 2.55 − 0.05 − 0.39 − 1.00 0.4–0.6 + 0.00 + 0.01 + 1.59 + 3.08 + 0.00 − 4.17 + 0.46 + 2.86 + 0.06 + 0.15 + 1.00 − 0.01 − 0.01 − 1.72 − 3.23 − 0.02 + 4.17 − 0.67 − 2.86 − 0.05 − 0.39 − 1.00 0.6–0.8 + 0.00 + 0.01 + 1.62 + 3.26 + 0.00 − 3.74 + 0.46 + 3.22 + 0.05 + 0.15 + 1.00 − 0.01 − 0.01 − 1.82 − 3.46 − 0.02 + 3.74 − 0.67 − 3.22 − 0.05 − 0.40 − 1.00 0.8–1.0 + 0.00 + 0.01 + 1.80 + 3.54 + 0.00 − 2.88 + 0.46 + 3.48 + 0.05 + 0.15 + 1.00 − 0.01 − 0.01 − 1.88 − 3.61 − 0.02 + 2.88 − 0.56 − 3.48 − 0.05 − 0.39 − 1.00 1.0–1.2 + 0.00 + 0.01 + 1.97 + 3.93 + 0.00 − 5.18 + 0.46 + 3.32 + 0.05 + 0.16 + 1.00 − 0.01 − 0.01 − 1.81 − 3.87 − 0.02 + 5.18 − 0.56 − 3.32 − 0.05 − 0.41 − 1.00 1.2–1.4 + 0.00 + 0.01 + 2.04 + 4.49 + 0.00 − 8.88 + 0.46 + 4.47 + 0.05 + 0.17 + 1.00 − 0.01 − 0.01 − 1.78 − 4.14 − 0.02 + 8.88 − 0.56 − 4.47 − 0.05 − 0.41 − 1.00 1.4–1.6 + 0.00 + 0.01 + 2.00 + 4.37 + 0.00 − 9.07 + 0.71 + 4.67 + 0.05 + 0.18 + 1.00 − 0.01 − 0.01 − 1.74 − 4.02 − 0.02 + 9.07 − 0.69 − 4.67 − 0.05 − 0.42 − 1.00 1.6–1.8 + 0.00 + 0.01 + 1.83 + 3.60 + 0.00 − 10.46 + 0.71 + 2.32 + 0.06 + 0.17 + 1.00 − 0.01 − 0.01 − 1.62 − 3.51 − 0.02 + 10.46 − 0.69 − 2.32 − 0.05 − 0.43 − 1.00 1.8–2.0 + 0.00 + 0.01 + 1.90 + 3.38 + 0.00 − 8.31 + 0.55 + 2.32 + 0.05 + 0.16 + 1.00 − 0.01 − 0.01 − 1.66 − 3.23 − 0.02 + 8.31 − 0.55 − 2.32 − 0.05 − 0.43 − 1.00 2.0–2.2 + 0.00 + 0.01 + 2.05 + 3.56 + 0.00 − 6.74 + 0.55 + 5.01 + 0.05 + 0.17 + 1.00 − 0.01 − 0.01 − 1.94 − 3.60 − 0.02 + 6.74 − 0.55 − 5.01 − 0.05 − 0.43 − 1.00 2.2–2.4 + 0.00 + 0.01 + 2.70 + 3.91 + 0.00 − 7.48 + 0.55 + 4.42 + 0.05 + 0.18 + 1.00 − 0.01 − 0.01 − 2.50 − 3.85 − 0.02 + 7.48 − 0.55 − 4.42 − 0.05 − 0.42 − 1.00 123 847 Page 26 of 47 Eur. Phys. J. C (2019) 79:847 Table 4 The measured double-differential Z + jets production cross- JES ); sum in quadra- to pile-up corrections of the jet kinematics (δpile-up jet sections as a function of |yjet | in the 50 GeV < pT < 100 GeV range. JES ture of the flavour-based uncertainties (δflavour ); punch-through uncer- δdata stat and δ stat are the statistical uncertainties in data and MC simulation, MC JES tainty (δpthrough ); JER uncertainty (δ JER ); JVF uncertainty (δ JVF ); sum sys respectively. δtot is the total systematic uncertainty and includes the fol- in quadrature of the unfolding uncertainties (δ unf ); sum in quadrature lowing components: uncertainties due to electron reconstruction (δrec el ), el ) and trigger (δ el ) efficiencies; electron energy scale of the uncertainties due to MC generated backgrounds normalisation identification (δID trig bg (δMC ); sum in quadrature of the uncertainty due to combined multijet el ) and energy resolution (δ el ) uncertainties; sum in quadrature (δscale res bg JES ); sum in quadra- and W + jets backgrounds (δmult ); uncertainty due to jet quality selec- of the uncertainties from JES in situ methods (δin situ tion (δ qual ). All uncertainties are given in %. The luminosity uncertainty ture of the uncertainties from JES η-intercalibration methods (δη-int JES ); an of 1.9% is not shown and not included in the total uncertainty and its JES uncertainty of the measured single-hadron response (δhadron ); MC non- components JES ); sum in quadrature of the uncertainties due closure uncertainty (δclosure d2σ sys |yjet | jet δdata stat δMC stat δtot δrec el δID el δtrig el δscale el δres el δin JES situ δη−int JES d|yjet |dpT (fb/GeV) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) 0.0–0.2 349.964 0.56 0.80 + 3.75 + 0.03 + 0.15 + 0.24 − 0.25 + 0.00 + 2.67 + 0.31 − 3.71 − 0.08 − 0.21 − 0.29 + 0.19 − 0.05 − 2.61 − 0.26 0.2–0.4 352.217 0.71 0.80 + 3.68 + 0.03 + 0.15 + 0.24 v0.25 + 0.00 + 2.56 + 0.31 − 3.77 − 0.08 − 0.21 − 0.29 + 0.19 − 0.05 − 2.70 − 0.26 0.4–0.6 338.924 0.74 0.81 + 3.78 + 0.03 + 0.15 + 0.24 − 0.25 + 0.00 + 2.52 + 0.31 − 3.99 − 0.08 − 0.21 − 0.29 + 0.19 − 0.05 − 2.86 − 0.26 0.6–0.8 328.606 0.72 0.93 + 3.99 + 0.03 + 0.15 + 0.24 − 0.25 + 0.00 + 2.75 + 0.31 − 4.15 − 0.08 − 0.21 − 0.29 + 0.19 − 0.05 − 2.86 − 0.26 0.8–1.0 303.475 0.69 0.87 + 4.05 + 0.03 + 0.15 + 0.24 − 0.25 + 0.00 + 2.98 + 0.31 − 3.89 − 0.08 − 0.21 − 0.29 + 0.19 − 0.05 − 2.76 − 0.26 1.0–1.2 274.407 0.71 1.05 + 3.85 + 0.03 + 0.15 + 0.24 − 0.25 + 0.00 + 2.74 + 0.31 − 4.09 − 0.08 − 0.21 − 0.29 + 0.19 − 0.05 − 2.83 − 0.96 1.2–1.4 261.553 0.81 0.84 + 4.14 + 0.03 + 0.15 + 0.24 − 0.25 + 0.00 + 2.86 + 1.25 − 4.31 − 0.08 − 0.21 − 0.29 + 0.19 − 0.05 − 2.86 − 0.96 1.4–1.6 233.170 0.75 1.02 + 4.48 + 0.03 + 0.15 + 0.24 − 0.25 + 0.00 + 2.82 + 1.25 − 4.38 − 0.08 − 0.21 − 0.29 + 0.19 − 0.05 − 2.74 − 0.96 1.6–1.8 192.405 0.92 1.16 + 5.11 + 0.03 + 0.15 + 0.24 − 0.25 + 0.00 + 3.09 + 2.10 − 4.80 − 0.08 − 0.21 − 0.29 + 0.19 − 0.05 − 2.92 − 1.97 1.8–2.0 174.081 0.90 1.18 + 5.75 + 0.03 + 0.15 + 0.24 − 0.25 + 0.00 + 3.38 + 2.61 − 5.14 − 0.08 − 0.21 − 0.29 + 0.19 − 0.05 − 3.05 − 2.27 2.0–2.2 145.578 0.94 1.11 + 5.92 + 0.03 + 0.15 + 0.24 − 0.25 + 0.00 + 3.48 + 2.80 − 5.31 − 0.08 − 0.21 − 0.29 + 0.19 − 0.05 − 3.02 − 2.36 2.2–2.4 117.333 1.08 1.37 + 5.99 + 0.03 + 0.15 + 0.24 − 0.25 + 0.00 + 3.56 + 2.78 − 5.18 − 0.08 − 0.21 − 0.29 + 0.19 − 0.05 − 2.83 − 2.23 2.4–2.6 98.813 1.31 1.42 + 5.65 + 0.03 + 0.15 + 0.24 − 0.25 + 0.00 + 3.32 + 2.56 − 5.25 − 0.08 − 0.21 − 0.29 + 0.19 − 0.05 − 2.87 − 2.20 2.6–2.8 75.900 1.47 1.67 + 6.65 + 0.03 + 0.15 + 0.24 − 0.25 + 0.00 + 3.21 + 2.88 − 6.11 − 0.08 − 0.21 − 0.29 + 0.19 − 0.05 − 2.85 − 2.20 2.8–3.0 58.038 1.59 2.21 + 6.49 + 0.03 + 0.15 + 0.24 − 0.25 + 0.00 + 3.08 + 2.88 − 6.76 − 0.08 − 0.21 − 0.29 + 0.19 − 0.05 − 2.85 − 3.79 3.0–3.2 44.324 1.58 2.56 + 7.78 + 0.03 + 0.15 + 0.24 − 0.25 + 0.00 + 3.08 + 4.36 − 7.26 − 0.08 − 0.21 − 0.29 + 0.19 − 0.05 − 2.72 − 3.79 3.2–3.4 32.909 2.09 2.91 + 8.34 + 0.03 + 0.15 + 0.24 − 0.25 + 0.00 + 3.08 + 4.91 − 9.23 − 0.08 − 0.21 − 0.29 + 0.19 − 0.05 − 2.72 − 6.55 123 Eur. Phys. J. C (2019) 79:847 Page 27 of 47 847 Table 4 continued bg bg |yjet | δhadron JES δclosure JES δpile-up JES δflavour JES δpthrough JES δ JER δ JVF δ unf δMC δmult δ qual (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) 0.0–0.2 + 0.00 + 0.00 + 1.02 + 0.81 + 0.00 − 1.47 − 0.46 + 1.28 + 0.17 + 0.15 + 1.00 − 0.03 − 0.02 − 0.92 − 0.77 − 0.02 + 1.47 + 0.49 − 1.28 − 0.15 − 0.42 − 1.00 0.2–0.4 + 0.00 + 0.00 + 1.02 + 0.81 + 0.00 − 1.47 − 0.46 + 1.28 + 0.16 + 0.15 + 1.00 − 0.03 − 0.02 − 0.92 − 0.77 − 0.02 + 1.47 + 0.49 − 1.28 − 0.15 − 0.42 − 1.00 0.4–0.6 + 0.00 + 0.00 + 1.07 + 0.81 + 0.00 − 1.60 − 0.46 + 1.43 + 0.16 + 0.15 + 1.00 − 0.03 − 0.02 − 0.92 − 0.77 − 0.02 + 1.60 + 0.49 − 1.43 − 0.15 − 0.43 − 1.00 0.6–0.8 + 0.00 + 0.00 + 1.07 + 1.28 + 0.00 − 1.47 − 0.46 + 1.41 + 0.16 + 0.16 + 1.00 − 0.03 − 0.02 − 1.08 − 1.44 − 0.02 + 1.47 + 0.49 − 1.41 − 0.14 − 0.43 − 1.00 0.8–1.0 + 0.00 + 0.00 + 1.07 + 1.50 + 0.00 − 1.21 − 0.46 + 1.07 + 0.15 + 0.17 + 1.00 − 0.03 − 0.02 − 1.08 − 1.44 − 0.02 + 1.21 + 0.49 − 1.07 − 0.14 − 0.45 − 1.00 1.0–1.2 + 0.00 + 0.00 + 1.01 + 1.49 + 0.00 − 1.21 − 0.46 + 1.07 + 0.15 + 0.19 + 1.00 − 0.03 − 0.02 − 1.19 − 1.44 − 0.02 + 1.21 + 0.49 − 1.07 − 0.14 − 0.46 − 1.00 1.2–1.4 + 0.00 + 0.00 + 1.01 + 1.54 + 0.00 − 1.21 − 0.46 + 1.07 + 0.14 + 0.21 + 1.00 − 0.03 − 0.02 − 1.19 − 1.94 − 0.02 + 1.21 + 0.49 − 1.07 − 0.13 − 0.49 − 1.00 1.4–1.6 + 0.00 + 0.00 + 1.01 + 1.78 + 0.00 − 1.42 − 0.46 + 1.73 + 0.13 + 0.37 + 1.00 − 0.03 − 0.02 − 1.05 − 1.69 − 0.02 + 1.42 + 0.40 − 1.73 − 0.12 − 0.60 − 1.00 1.6–1.8 + 0.00 + 0.00 + 1.34 + 2.01 + 0.00 − 1.42 − 0.46 + 1.73 + 0.13 + 0.19 + 1.00 − 0.03 − 0.02 − 1.05 − 1.69 − 0.02 + 1.42 + 0.40 − 1.73 − 0.12 − 0.51 − 1.00 1.8–2.0 + 0.00 + 0.00 + 1.34 + 2.25 + 0.00 − 1.89 − 0.34 + 1.73 + 0.12 + 0.20 + 1.00 − 0.03 − 0.02 − 1.05 − 1.66 − 0.02 + 1.89 + 0.40 − 1.73 − 0.11 − 0.55 − 1.00 2.0–2.2 + 0.00 + 0.00 + 1.40 + 1.91 + 0.00 − 1.89 − 0.34 + 2.16 + 0.11 + 0.20 + 1.00 − 0.03 − 0.02 − 0.92 − 1.66 − 0.02 + 1.89 + 0.40 − 2.16 − 0.10 − 0.56 − 1.00 2.2–2.4 + 0.00 + 0.00 + 1.40 + 1.91 + 0.00 − 0.76 − 0.34 + 2.83 + 0.11 + 0.21 + 1.00 − 0.03 − 0.02 − 0.92 − 1.66 − 0.02 + 0.76 + 0.40 − 2.83 − 0.10 − 0.58 − 1.00 2.4–2.6 + 0.00 + 0.00 + 0.87 + 1.91 + 0.00 − 0.76 − 0.34 + 2.83 + 0.11 + 0.23 + 1.00 − 0.03 − 0.02 − 0.92 − 1.82 − 0.02 + 0.76 + 0.40 − 2.83 − 0.10 − 0.64 − 1.00 2.6–2.8 + 0.00 + 0.00 + 0.87 + 2.25 + 0.00 − 0.76 − 0.34 + 4.23 + 0.10 + 0.24 + 1.00 − 0.03 − 0.02 − 0.92 − 1.82 − 0.02 + 0.76 + 0.40 − 4.23 − 0.10 − 0.67 − 1.00 2.8–3.0 + 0.00 + 0.00 + 0.87 + 2.25 + 0.00 − 0.76 − 0.34 + 4.08 + 0.10 + 0.25 + 1.00 − 0.03 − 0.02 − 0.92 − 1.82 − 0.02 + 0.76 + 0.40 − 4.08 − 0.09 − 0.69 − 1.00 3.0–3.2 + 0.00 + 0.00 + 0.87 + 2.25 + 0.00 − 0.76 − 0.34 + 4.94 + 0.09 + 0.26 + 1.00 − 0.03 − 0.02 − 0.92 − 1.82 − 0.02 + 0.76 + 0.40 − 4.94 − 0.09 − 0.70 − 1.00 3.2–3.4 + 0.00 + 0.00 + 0.87 + 2.25 + 0.00 − 0.76 − 0.34 + 5.32 + 0.09 + 0.25 + 1.00 − 0.03 − 0.02 − 0.92 − 1.82 − 0.02 + 0.76 + 0.40 − 5.32 − 0.09 − 0.70 − 1.00 123 847 Page 28 of 47 Eur. Phys. J. C (2019) 79:847 Table 5 The measured double-differential Z + jets production cross- JES ); sum in quadra- to pile-up corrections of the jet kinematics (δpile-up jet sections as a function of |yjet | in the 100 GeV < pT < 200 GeV range. JES ture of the flavour-based uncertainties (δflavour ); punch-through uncer- δdata stat and δ stat are the statistical uncertainties in data and MC simulation, MC JES tainty (δpthrough ); JER uncertainty (δ JER ); JVF uncertainty (δ JVF ); sum sys respectively. δtot is the total systematic uncertainty and includes the fol- in quadrature of the unfolding uncertainties (δ unf ); sum in quadrature lowing components: uncertainties due to electron reconstruction (δrec el ), el ) and trigger (δ el ) efficiencies; electron energy scale of the uncertainties due to MC generated backgrounds normalisation identification (δID trig bg (δMC ); sum in quadrature of the uncertainty due to combined multijet el ) and energy resolution (δ el ) uncertainties; sum in quadrature (δscale res bg JES ); sum in quadra- and W + jets backgrounds (δmult ); uncertainty due to jet quality selec- of the uncertainties from JES in situ methods (δin situ tion (δ qual ). All uncertainties are given in %. The luminosity uncertainty ture of the uncertainties from JES η-intercalibration methods (δη-int JES ); an of 1.9% is not shown and not included in the total uncertainty and its JES uncertainty of the measured single-hadron response (δhadron ); MC non- components JES ); sum in quadrature of the uncertainties due closure uncertainty (δclosure d2σ sys |yjet | jet δdata stat δMC stat δtot δrec el δID el δtrig el δscale el δres el δin JES situ δη−int JES d|yjet |dpT (fb/GeV) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) 0.0–0.2 45.769 1.28 1.29 + 2.58 − 0.04 + 0.02 + 0.11 − 0.29 + 0.06 + 1.44 + 0.50 − 3.54 + 0.00 − 0.08 − 0.15 + 0.38 + 0.00 − 2.11 − 0.67 0.2–0.4 46.342 1.22 1.39 + 2.58 − 0.04 + 0.02 + 0.11 − 0.29 + 0.06 + 1.44 + 0.50 − 3.54 + 0.00 − 0.08 − 0.15 + 0.38 + 0.00 − 2.11 − 0.67 0.4–0.6 43.964 1.25 1.47 + 2.58 − 0.04 + 0.02 + 0.11 − 0.29 + 0.06 + 1.44 + 0.50 − 3.21 + 0.00 − 0.08 − 0.15 + 0.38 + 0.00 − 1.93 − 0.67 0.6–0.8 40.076 1.40 1.67 + 2.58 − 0.04 + 0.02 + 0.11 − 0.29 + 0.06 + 1.44 + 0.50 − 3.15 + 0.00 − 0.08 − 0.15 + 0.38 + 0.00 − 1.93 − 0.67 0.8–1.0 37.981 1.40 1.38 + 2.50 − 0.04 + 0.02 + 0.11 − 0.29 + 0.06 + 1.44 + 0.50 − 3.15 + 0.00 − 0.08 − 0.15 + 0.38 + 0.00 − 1.93 − 0.67 1.0–1.2 32.122 1.63 1.68 + 2.74 − 0.04 + 0.02 + 0.11 − 0.29 + 0.06 + 1.44 + 0.50 − 3.08 + 0.00 − 0.08 − 0.15 + 0.38 + 0.00 − 1.82 − 0.67 1.2–1.4 31.772 1.33 1.53 + 2.99 − 0.04 + 0.02 + 0.11 − 0.29 + 0.06 + 1.87 + 0.50 − 3.09 + 0.00 − 0.08 − 0.15 + 0.38 + 0.00 − 1.82 − 0.67 1.4–1.6 27.737 1.34 1.85 + 3.19 − 0.04 + 0.02 + 0.11 − 0.29 + 0.06 + 1.87 + 0.50 − 3.15 + 0.00 − 0.08 − 0.15 + 0.38 + 0.00 − 1.82 − 0.67 1.6–1.8 21.873 1.85 2.01 + 3.16 − 0.04 + 0.02 + 0.11 − 0.29 + 0.06 + 1.87 + 0.50 − 3.10 + 0.00 − 0.08 − 0.15 + 0.38 + 0.00 − 1.82 − 0.67 1.8–2.0 17.806 1.88 2.00 + 3.33 − 0.04 + 0.02 + 0.11 − 0.29 + 0.06 + 1.98 + 0.50 − 3.29 + 0.00 − 0.08 − 0.15 + 0.38 + 0.00 − 1.95 − 0.67 2.0–2.2 13.820 2.26 2.26 + 3.33 − 0.04 + 0.02 + 0.11 − 0.29 + 0.06 + 1.98 + 0.50 − 3.30 + 0.00 − 0.08 − 0.15 + 0.38 + 0.00 − 1.95 − 0.67 2.2–2.4 10.613 2.55 2.81 + 3.98 − 0.04 + 0.02 + 0.11 − 0.29 + 0.06 + 2.23 + 0.50 − 4.38 + 0.00 − 0.08 − 0.15 + 0.38 + 0.00 − 1.95 − 2.96 2.4–2.6 8.152 3.12 2.94 + 5.72 − 0.04 + 0.02 + 0.11 − 0.29 + 0.06 + 2.23 + 4.14 − 4.41 + 0.00 − 0.08 − 0.15 + 0.38 + 0.00 − 1.95 − 2.96 2.6–2.8 5.663 3.22 3.91 + 5.73 − 0.04 + 0.02 + 0.11 − 0.29 + 0.06 + 2.23 + 4.14 − 4.45 + 0.00 − 0.08 − 0.15 + 0.38 + 0.00 − 1.95 − 2.96 2.8–3.0 3.248 3.91 4.78 + 9.42 − 0.04 + 0.02 + 0.11 − 0.29 + 0.06 + 2.23 + 8.54 − 9.46 + 0.00 − 0.08 − 0.15 + 0.38 + 0.00 − 1.95 − 7.71 3.0–3.2 2.169 5.43 5.73 + 9.48 − 0.04 + 0.02 + 0.11 − 0.29 + 0.06 + 2.47 + 8.54 − 9.46 + 0.00 − 0.08 − 0.15 + 0.38 + 0.00 − 1.95 − 7.71 3.2–3.4 1.234 7.36 9.27 + 15.87 − 0.04 + 0.02 + 0.11 − 0.29 + 0.06 + 2.47 + 15.33 − 13.57 + 0.00 − 0.08 − 0.15 + 0.38 + 0.00 − 1.95 − 12.42 123 Eur. Phys. J. C (2019) 79:847 Page 29 of 47 847 Table 5 continued bg bg |yjet | δhadron JES δclosure JES δpile-up JES δflavour JES δpthrough JES δ JER δ JVF δ unf δMC δmult δ qual (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) 0.0–0.2 + 0.00 + 0.00 + 0.83 + 1.51 + 0.00 − 0.36 − 0.04 + 0.14 + 0.19 + 0.18 + 1.00 − 0.06 − 0.03 − 1.13 − 2.20 − 0.06 + 0.36 + 0.00 − 0.14 − 0.18 − 0.43 − 1.00 0.2–0.4 + 0.00 + 0.00 + 0.83 + 1.51 + 0.00 − 0.36 − 0.04 + 0.14 + 0.18 + 0.18 + 1.00 − 0.06 − 0.03 − 1.13 − 2.20 − 0.06 + 0.36 + 0.00 − 0.14 − 0.17 − 0.44 − 1.00 0.4–0.6 + 0.00 + 0.00 + 0.83 + 1.51 + 0.00 − 0.36 − 0.04 + 0.14 + 0.19 + 0.17 + 1.00 − 0.06 − 0.03 − 1.13 − 1.84 − 0.06 + 0.36 + 0.00 − 0.14 − 0.17 − 0.43 − 1.00 0.6–0.8 + 0.00 + 0.00 + 0.83 + 1.51 + 0.00 − 0.36 − 0.04 + 0.14 + 0.18 + 0.20 + 1.00 − 0.06 − 0.03 − 1.13 − 1.73 − 0.06 + 0.36 + 0.00 − 0.14 − 0.17 − 0.47 − 1.00 0.8–1.0 + 0.00 + 0.00 + 0.83 + 1.37 + 0.00 − 0.36 − 0.04 + 0.14 + 0.17 + 0.17 + 1.00 − 0.06 − 0.03 − 1.13 − 1.73 − 0.06 + 0.36 + 0.00 − 0.14 − 0.16 − 0.46 − 1.00 1.0–1.2 + 0.00 + 0.00 + 0.83 + 1.37 + 0.00 − 0.36 − 0.04 + 1.13 + 0.18 + 0.18 + 1.00 − 0.06 − 0.03 − 0.92 − 1.45 − 0.06 + 0.36 + 0.00 − 1.13 − 0.16 − 0.48 − 1.00 1.2–1.4 + 0.00 + 0.00 + 0.83 + 1.37 + 0.00 − 0.36 − 0.04 + 1.13 + 0.17 + 0.19 + 1.00 − 0.06 − 0.03 − 0.92 − 1.45 − 0.06 + 0.36 + 0.00 − 1.13 − 0.15 − 0.53 − 1.00 1.4–1.6 + 0.00 + 0.00 + 0.83 + 1.70 + 0.00 − 0.36 − 0.04 + 1.13 + 0.17 + 0.52 + 1.00 − 0.06 − 0.03 − 0.92 − 1.45 − 0.06 + 0.36 + 0.00 − 1.13 − 0.16 − 0.79 − 1.00 1.6–1.8 + 0.00 + 0.00 + 0.83 + 1.70 + 0.00 − 0.36 − 0.04 + 1.13 + 0.16 + 0.24 + 1.00 − 0.06 − 0.03 − 0.92 − 1.45 − 0.06 + 0.36 + 0.00 − 1.13 − 0.15 − 0.60 − 1.00 1.8–2.0 + 0.00 + 0.00 + 1.17 + 1.70 + 0.00 − 0.36 − 0.04 + 1.13 + 0.15 + 0.26 + 1.00 − 0.06 − 0.03 − 0.92 − 1.66 − 0.06 + 0.36 + 0.00 − 1.13 − 0.14 − 0.68 − 1.00 2.0–2.2 + 0.00 + 0.00 + 1.17 + 1.70 + 0.00 − 0.36 − 0.04 + 1.13 + 0.15 + 0.26 + 1.00 − 0.06 − 0.03 − 0.92 − 1.66 − 0.06 + 0.36 + 0.00 − 1.13 − 0.14 − 0.70 − 1.00 2.2–2.4 + 0.00 + 0.00 + 1.17 + 2.57 + 0.00 − 0.36 − 0.04 + 1.13 + 0.15 + 0.25 + 1.00 − 0.06 − 0.03 − 0.92 − 1.66 − 0.06 + 0.36 + 0.00 − 1.13 − 0.14 − 0.70 − 1.00 2.4–2.6 + 0.00 + 0.00 + 1.17 + 2.57 + 0.00 − 0.36 − 0.04 + 1.13 + 0.15 + 0.32 + 1.00 − 0.06 − 0.03 − 0.92 − 1.66 − 0.06 + 0.36 + 0.00 − 1.13 − 0.14 − 0.87 − 1.00 2.6–2.8 + 0.00 + 0.00 + 1.17 + 2.57 + 0.00 − 0.36 − 0.04 + 1.13 + 0.17 + 0.44 + 1.00 − 0.06 − 0.03 − 0.92 − 1.66 − 0.06 + 0.36 + 0.00 − 1.13 − 0.16 − 1.04 − 1.00 2.8–3.0 + 0.00 + 0.00 + 1.17 + 2.57 + 0.00 − 0.36 − 0.04 + 1.13 + 0.18 + 0.40 + 1.00 − 0.06 − 0.03 − 0.92 − 4.65 − 0.06 + 0.36 + 0.00 − 1.13 − 0.17 − 1.07 − 1.00 3.0–3.2 + 0.00 + 0.00 + 1.17 + 2.57 + 0.00 − 0.36 − 0.04 + 1.13 + 0.18 + 0.46 + 1.00 − 0.06 − 0.03 − 0.92 − 4.65 − 0.06 + 0.36 + 0.00 − 1.13 − 0.17 − 1.09 − 1.00 3.2–3.4 + 0.00 + 0.00 + 1.17 + 2.57 + 0.00 − 0.36 − 0.04 + 1.13 + 0.15 + 0.41 + 1.00 − 0.06 − 0.03 − 0.92 − 4.65 − 0.06 + 0.36 + 0.00 − 1.13 − 0.13 − 1.07 − 1.00 123 847 Page 30 of 47 Eur. Phys. J. C (2019) 79:847 Table 6 The measured double-differential Z + jets production cross- JES ); sum in quadra- to pile-up corrections of the jet kinematics (δpile-up jet sections as a function of |yjet | in the 200 GeV < pT < 300 GeV range. JES ture of the flavour-based uncertainties (δflavour ); punch-through uncer- δdata stat and δ stat are the statistical uncertainties in data and MC simulation, MC JES tainty (δpthrough ); JER uncertainty (δ JER ); JVF uncertainty (δ JVF ); sum sys respectively. δtot is the total systematic uncertainty and includes the fol- in quadrature of the unfolding uncertainties (δ unf ); sum in quadrature lowing components: uncertainties due to electron reconstruction (δrec el ), el ) and trigger (δ el ) efficiencies; electron energy scale of the uncertainties due to MC generated backgrounds normalisation identification (δID trig bg (δMC ); sum in quadrature of the uncertainty due to combined multijet el ) and energy resolution (δ el ) uncertainties; sum in quadrature (δscale res bg JES ); sum in quadra- and W + jets backgrounds (δmult ); uncertainty due to jet quality selec- of the uncertainties from JES in situ methods (δin situ tion (δ qual ). All uncertainties are given in %. The luminosity uncertainty ture of the uncertainties from JES η-intercalibration methods (δη-int JES ); an of 1.9% is not shown and not included in the total uncertainty and its JES uncertainty of the measured single-hadron response (δhadron ); MC non- components JES ); sum in quadrature of the uncertainties due closure uncertainty (δclosure d2σ sys |yjet | jet δdata stat δMC stat δtot δrec el δID el δtrig el δscale el δres el δin JES situ δη−int JES d|yjet |dpT (fb/GeV) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) 0.0–0.4 5.561 2.50 2.63 + 3.55 − 0.05 + 0.12 + 0.10 − 0.18 − 0.06 + 2.62 + 0.39 − 4.33 + 0.04 + 0.00 − 0.01 + 0.18 + 0.05 − 3.10 − 0.77 0.4–0.8 4.889 2.36 2.93 + 3.55 − 0.05 + 0.12 + 0.10 − 0.18 − 0.06 + 2.62 + 0.39 − 4.33 + 0.04 + 0.00 − 0.01 + 0.18 + 0.05 − 3.10 − 0.77 0.8–1.2 4.260 3.18 3.41 + 3.54 − 0.05 + 0.12 + 0.10 − 0.18 − 0.06 + 2.62 + 0.39 − 4.33 + 0.04 + 0.00 − 0.01 + 0.18 + 0.05 − 3.10 − 0.77 1.2–1.6 3.055 3.61 3.17 + 3.55 − 0.05 + 0.12 + 0.10 − 0.18 − 0.06 + 2.62 + 0.39 − 4.35 + 0.04 + 0.00 − 0.01 + 0.18 + 0.05 − 3.10 − 0.77 1.6–2.0 1.780 4.43 4.42 + 3.56 − 0.05 + 0.12 + 0.10 − 0.18 − 0.06 + 2.62 + 0.39 − 4.38 + 0.04 + 0.00 − 0.01 + 0.18 + 0.05 − 3.10 − 0.77 2.0–2.4 0.831 6.45 7.17 + 3.60 − 0.05 + 0.12 + 0.10 − 0.18 − 0.06 + 2.62 + 0.39 − 6.26 + 0.04 + 0.00 − 0.01 + 0.18 + 0.05 − 5.37 − 0.77 2.4–3.4 0.136 9.48 11.75 + 3.58 − 0.05 + 0.12 + 0.10 − 0.18 − 0.06 + 2.62 + 0.39 − 6.25 + 0.04 + 0.00 − 0.01 + 0.18 + 0.05 − 5.37 − 0.77 bg bg |yjet | δhadron JES δclosure JES δpile-up JES δflavour JES δpthrough JES δ JER δ JVF δ unf δMC δmult δ qual (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) 0.0–0.4 + 0.04 + 0.15 + 0.36 + 1.40 + 0.20 − 0.58 − 0.04 + 1.40 + 0.09 + 0.28 + 1.00 + 0.00 + 0.00 − 0.75 − 2.08 − 0.06 + 0.58 + 0.09 − 1.40 − 0.08 − 0.54 − 1.00 0.4–0.8 + 0.04 + 0.15 + 0.36 + 1.40 + 0.20 − 0.58 − 0.04 + 1.40 + 0.10 + 0.25 + 1.00 + 0.00 + 0.00 − 0.75 − 2.08 − 0.06 + 0.58 + 0.09 − 1.40 − 0.09 − 0.55 − 1.00 0.8–1.2 + 0.04 + 0.15 + 0.36 + 1.40 + 0.20 − 0.58 − 0.04 + 1.40 + 0.11 + 0.21 + 1.00 + 0.00 + 0.00 − 0.75 − 2.08 − 0.06 + 0.58 + 0.09 − 1.40 − 0.10 − 0.57 − 1.00 1.2–1.6 + 0.04 + 0.15 + 0.36 + 1.40 + 0.20 − 0.58 − 0.04 + 1.40 + 0.14 + 0.27 + 1.00 + 0.00 + 0.00 − 0.75 − 2.08 − 0.06 + 0.58 + 0.09 − 1.40 − 0.13 − 0.71 − 1.00 1.6–2.0 + 0.04 + 0.15 + 0.36 + 1.40 + 0.20 − 0.58 − 0.04 + 1.40 + 0.17 + 0.39 + 1.00 + 0.00 + 0.00 − 0.75 − 2.08 − 0.06 + 0.58 + 0.09 − 1.40 − 0.16 − 0.84 − 1.00 2.0–2.4 + 0.04 + 0.15 + 0.36 + 1.40 + 0.20 − 0.58 − 0.04 + 1.40 + 0.22 + 0.65 + 1.00 + 0.00 + 0.00 − 0.75 − 2.08 − 0.06 + 0.58 + 0.09 − 1.40 − 0.20 − 1.19 − 1.00 2.4–3.4 + 0.04 + 0.15 + 0.36 + 1.40 + 0.20 − 0.58 − 0.04 + 1.40 + 0.32 + 0.42 + 1.00 + 0.00 + 0.00 − 0.75 − 2.08 − 0.06 + 0.58 + 0.09 − 1.40 − 0.29 − 1.12 − 1.00 123 Eur. Phys. J. C (2019) 79:847 Page 31 of 47 847 Table 7 The measured double-differential Z + jets production cross- JES ); sum in quadra- to pile-up corrections of the jet kinematics (δpile-up jet sections as a function of |yjet | in the 300 GeV < pT < 400 GeV range. JES ture of the flavour-based uncertainties (δflavour ); punch-through uncer- δdata stat and δ stat are the statistical uncertainties in data and MC simulation, MC JES tainty (δpthrough ); JER uncertainty (δ JER ); JVF uncertainty (δ JVF ); sum sys respectively. δtot is the total systematic uncertainty and includes the fol- in quadrature of the unfolding uncertainties (δ unf ); sum in quadrature lowing components: uncertainties due to electron reconstruction (δrec el ), el ) and trigger (δ el ) efficiencies; electron energy scale of the uncertainties due to MC generated backgrounds normalisation identification (δID trig bg (δMC ); sum in quadrature of the uncertainty due to combined multijet el ) and energy resolution (δ el ) uncertainties; sum in quadrature (δscale res bg JES ); sum in quadra- and W + jets backgrounds (δmult ); uncertainty due to jet quality selec- of the uncertainties from JES in situ methods (δin situ tion (δ qual ). All uncertainties are given in %. The luminosity uncertainty ture of the uncertainties from JES η-intercalibration methods (δη-int JES ); an of 1.9% is not shown and not included in the total uncertainty and its JES uncertainty of the measured single-hadron response (δhadron ); MC non- components JES ); sum in quadrature of the uncertainties due closure uncertainty (δclosure d2σ sys |yjet | jet δdata stat δMC stat δtot δrec el δID el δtrig el δscale el δres el δin JES situ δη−int JES d|yjet |dpT [fb/GeV] (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) 0.0–0.4 1.190 5.83 6.75 + 5.95 + 0.74 + 0.56 + 0.00 + 0.00 + 0.76 + 4.03 + 1.41 − 2.33 + 0.00 + 0.00 + 0.51 + 0.72 + 0.00 − 1.63 + 0.00 0.4–0.8 1.083 5.52 5.50 + 5.94 + 0.74 + 0.56 + 0.00 + 0.00 + 0.76 + 4.03 + 1.41 − 2.30 + 0.00 + 0.00 + 0.51 + 0.72 + 0.00 − 1.63 + 0.00 0.8–1.2 0.946 6.68 6.87 + 5.95 + 0.74 + 0.56 + 0.00 + 0.00 + 0.76 + 4.03 + 1.41 − 2.34 + 0.00 + 0.00 + 0.51 + 0.72 + 0.00 − 1.63 + 0.00 1.2–1.6 0.628 8.15 8.34 + 5.96 + 0.74 + 0.56 + 0.00 + 0.00 + 0.76 + 4.03 + 1.41 − 2.43 + 0.00 + 0.00 + 0.51 + 0.72 + 0.00 − 1.63 + 0.00 1.6–2.0 0.322 11.56 11.42 + 5.97 + 0.74 + 0.56 + 0.00 + 0.00 + 0.76 + 4.03 + 1.41 − 2.46 + 0.00 + 0.00 + 0.51 + 0.72 + 0.00 − 1.63 + 0.00 2.0–3.0 0.032 26.98 24.63 + 6.01 + 0.74 + 0.56 + 0.00 + 0.00 + 0.76 + 4.03 + 1.41 − 2.64 + 0.00 + 0.00 + 0.51 + 0.72 + 0.00 − 1.63 + 0.00 bg bg |yjet | δhadron JES δclosure JES δpile-up JES δflavour JES δpthrough JES δ JER δ JVF δ unf δMC δmult δ qual (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) 0.0–0.4 + 0.68 + 0.46 + 2.42 + 2.24 + 0.54 − 1.16 + 0.79 + 0.08 + 0.10 + 0.30 + 1.00 + 0.00 + 0.00 − 0.13 + 0.00 + 0.00 + 1.16 + 0.00 − 0.08 − 0.09 − 0.65 − 1.00 0.4–0.8 + 0.68 + 0.46 + 2.42 + 2.24 + 0.54 − 1.16 + 0.79 + 0.08 + 0.11 + 0.23 + 1.00 + 0.00 + 0.00 − 0.13 + 0.00 + 0.00 + 1.16 + 0.00 − 0.08 − 0.10 − 0.55 − 1.00 0.8–1.2 + 0.68 + 0.46 + 2.42 + 2.24 + 0.54 − 1.16 + 0.79 + 0.08 + 0.12 + 0.30 + 1.00 + 0.00 + 0.00 − 0.13 + 0.00 + 0.00 + 1.16 + 0.00 − 0.08 − 0.11 − 0.68 − 1.00 1.2–1.6 + 0.68 + 0.46 + 2.42 + 2.24 + 0.54 − 1.16 + 0.79 + 0.08 + 0.19 + 0.45 + 1.00 + 0.00 + 0.00 − 0.13 + 0.00 + 0.00 + 1.16 + 0.00 − 0.08 − 0.17 − 0.95 − 1.00 1.6–2.0 + 0.68 + 0.46 + 2.42 + 2.24 + 0.54 − 1.16 + 0.79 + 0.08 + 0.26 + 0.51 + 1.00 + 0.00 + 0.00 − 0.13 + 0.00 + 0.00 + 1.16 + 0.00 − 0.08 − 0.24 − 1.00 − 1.00 2.0–3.0 + 0.68 + 0.46 + 2.42 + 2.24 + 0.54 − 1.16 + 0.79 + 0.08 + 0.69 + 0.63 + 1.00 + 0.00 + 0.00 − 0.13 + 0.00 + 0.00 + 1.16 + 0.00 − 0.08 − 0.63 − 1.25 − 1.00 123 847 Page 32 of 47 Eur. Phys. J. C (2019) 79:847 Table 8 The measured double-differential Z + jets production cross- JES ); sum in quadra- to pile-up corrections of the jet kinematics (δpile-up jet sections as a function of |yjet | in the 400 GeV < pT < 1050 GeV range. JES ture of the flavour-based uncertainties (δflavour ); punch-through uncer- δdata stat and δ stat are the statistical uncertainties in data and MC simulation, MC JES tainty (δpthrough ); JER uncertainty (δ JER ); JVF uncertainty (δ JVF ); sum sys respectively. δtot is the total systematic uncertainty and includes the fol- in quadrature of the unfolding uncertainties (δ unf ); sum in quadrature lowing components: uncertainties due to electron reconstruction (δrec el ), el ) and trigger (δ el ) efficiencies; electron energy scale of the uncertainties due to MC generated backgrounds normalisation identification (δID trig bg (δMC ); sum in quadrature of the uncertainty due to combined multijet el ) and energy resolution (δ el ) uncertainties; sum in quadrature (δscale res bg JES ); sum in quadra- and W + jets backgrounds (δmult ); uncertainty due to jet quality selec- of the uncertainties from JES in situ methods (δin situ tion (δ qual ). All uncertainties are given in %. The luminosity uncertainty ture of the uncertainties from JES η-intercalibration methods (δη-int JES ); an of 1.9% is not shown and not included in the total uncertainty and its JES uncertainty of the measured single-hadron response (δhadron ); MC non- components JES ); sum in quadrature of the uncertainties due closure uncertainty (δclosure d2σ sys |yjet | jet δdata stat δMC stat δtot δrec el δID el δtrig el δscale el δres el δin JES situ δη−int JES d|yjet |dpT [fb/GeV] (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) 0.0–0.4 0.110 6.84 8.88 + 2.79 − 0.34 + 0.00 + 0.00 − 0.82 − 0.41 + 2.01 + 0.22 − 5.82 + 0.00 − 0.26 − 0.43 + 0.00 + 0.00 − 4.74 − 0.50 0.4–0.8 0.076 9.45 9.66 + 2.76 − 0.34 + 0.00 + 0.00 − 0.82 − 0.41 + 2.01 + 0.22 − 5.81 + 0.00 − 0.26 − 0.43 + 0.00 + 0.00 − 4.74 − 0.50 0.8–1.2 0.058 11.67 11.68 + 2.78 − 0.34 + 0.00 + 0.00 − 0.82 − 0.41 + 2.01 + 0.22 − 5.83 + 0.00 − 0.26 − 0.43 + 0.00 + 0.00 − 4.74 − 0.50 1.2–2.6 0.012 12.84 13.36 + 2.84 − 0.34 + 0.00 + 0.00 − 0.82 − 0.41 + 2.01 + 0.22 − 5.90 + 0.00 − 0.26 − 0.43 + 0.00 + 0.00 − 4.74 − 0.50 bg bg |yjet | δhadron JES δclosure JES δpile-up JES δflavour JES δpthrough JES δ JER δ JVF δ unf δMC δmult δ qual (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) 0.0–0.4 + 0.00 + 0.00 + 0.10 + 0.33 + 0.13 − 0.14 + 0.01 + 1.47 + 0.15 + 0.59 + 1.00 − 0.36 − 0.33 − 0.91 − 2.13 − 0.58 + 0.14 − 0.32 − 1.47 − 0.14 − 0.84 − 1.00 0.4–0.8 + 0.00 + 0.00 + 0.10 + 0.33 + 0.13 − 0.14 + 0.01 + 1.47 + 0.18 + 0.42 + 1.00 − 0.36 − 0.33 − 0.91 − 2.13 − 0.58 + 0.14 − 0.32 − 1.47 − 0.16 − 0.71 − 1.00 0.8–1.2 + 0.00 + 0.00 + 0.10 + 0.33 + 0.13 − 0.14 + 0.01 + 1.47 + 0.21 + 0.54 + 1.00 − 0.36 − 0.33 − 0.91 − 2.13 − 0.58 + 0.14 − 0.32 − 1.47 − 0.20 − 0.86 − 1.00 1.2–2.6 + 0.00 + 0.00 + 0.10 + 0.33 + 0.13 − 0.14 + 0.01 + 1.47 + 0.37 + 0.73 + 1.00 − 0.36 − 0.33 − 0.91 − 2.13 − 0.58 + 0.14 − 0.32 − 1.47 − 0.34 − 1.24 − 1.00 References 7 TeV with the ATLAS detector. 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Zwalinski36 1 Department of Physics, University of Adelaide, Adelaide, Australia 2 Physics Department, SUNY Albany, Albany, NY, USA 3 Department of Physics, University of Alberta, Edmonton, AB, Canada 4 (a) Department of Physics, Ankara University, Ankara, Turkey; (b) Istanbul Aydin University, Istanbul, Turkey; (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, USA 7 Department of Physics, University of Arizona, Tucson, AZ, USA 8 Department of Physics, University of Texas at Arlington, Arlington, TX, USA 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, USA 12 (a) Bahcesehir University, Faculty of Engineering and Natural Sciences, Istanbul, Turkey; (b) Istanbul Bilgi University, Faculty of Engineering and Natural Sciences, Istanbul, Turkey; (c) Department of Physics, Bogazici University, Istanbul, Turkey; (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 123 Eur. Phys. J. C (2019) 79:847 Page 43 of 47 847 15 (a) Instituteof High Energy Physics, Chinese Academy of Sciences, Beijing, China; (b) Physics Department, Tsinghua University, Beijing, China; (c) Department of Physics, Nanjing University, Nanjing, China; (d) University of Chinese Academy of Science (UCAS), Beijing, China 16 Institute of Physics, University of Belgrade, Belgrade, Serbia 17 Department for Physics and Technology, University of Bergen, Bergen, Norway 18 Physics Division, Lawrence Berkeley National Laboratory and University of California, Berkeley, CA, USA 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, UK 22 Facultad de Ciencias y Centro de Investigaciónes, Universidad Antonio Nariño, Bogota, Colombia 23 (a) Dipartimento di Fisica, INFN Bologna and Universita’ di Bologna, Bologna, Italy; (b) INFN Sezione di Bologna, Bologna, Italy 24 Physikalisches Institut, Universität Bonn, Bonn, Germany 25 Department of Physics, Boston University, Boston, MA, USA 26 Department of Physics, Brandeis University, Waltham, MA, USA 27 (a) Transilvania University of Brasov, Brasov, Romania; (b) Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest, Romania; (c) Department of Physics, Alexandru Ioan Cuza University of Iasi, Iasi, Romania; (d) Physics Department, National Institute for Research and Development of Isotopic and Molecular Technologies, Cluj-Napoca, Romania; (e) University Politehnica Bucharest, Bucharest, Romania; (f) West University in Timisoara, Timisoara, Romania 28 (a) Faculty of Mathematics, Physics and Informatics, Comenius University, Bratislava, Slovak Republic; (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, USA 30 Departamento de Física, Universidad de Buenos Aires, Buenos Aires, Argentina 31 California State University, Long Beach, CA, USA 32 Cavendish Laboratory, University of Cambridge, Cambridge, UK 33 (a) Department of Physics, University of Cape Town, Cape Town, South Africa; (b) Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg, South Africa; (c) School of Physics, University of the Witwatersrand, Johannesburg, South Africa 34 Department of Physics, Carleton University, Ottawa, ON, Canada 35 (a) Faculté des Sciences Ain Chock, Réseau Universitaire de Physique des Hautes Energies-Université Hassan II, Casablanca, Morocco; (b) Faculté des Sciences, Université Ibn-Tofail, Kenitra, Morocco; (c) Faculté des Sciences Semlalia, Université Cadi Ayyad, LPHEA-Marrakech, Marrakesh, Morocco; (d) Faculté des Sciences, Université Mohamed Premier and LPTPM, Oujda, Morocco; (e) Faculté des sciences, Université Mohammed V, Rabat, Morocco 36 CERN, Geneva, Switzerland 37 Enrico Fermi Institute, University of Chicago, Chicago, IL, USA 38 LPC, Université Clermont Auvergne, CNRS/IN2P3, Clermont-Ferrand, France 39 Nevis Laboratory, Columbia University, Irvington, NY, USA 40 Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark 41 (a) Dipartimento di Fisica, Università della Calabria, Rende, Italy; (b) INFN Gruppo Collegato di Cosenza, Laboratori Nazionali di Frascati, Frascati, Italy 42 Physics Department, Southern Methodist University, Dallas, TX, USA 43 Physics Department, University of Texas at Dallas, Richardson, TX, USA 44 National Centre for Scientific Research “Demokritos”, Agia Paraskevi, Greece 45 (a) Department of Physics, Stockholm University, Stockholm, Sweden; (b) Oskar Klein Centre, 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, USA 50 SUPA-School of Physics and Astronomy, University of Edinburgh, Edinburgh, UK 51 INFN e Laboratori Nazionali di Frascati, Frascati, Italy 52 Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany 123 847 Page 44 of 47 Eur. Phys. J. C (2019) 79:847 53 II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen, Germany 54 Département de Physique Nucléaire et Corpusculaire, Université de Genève, Geneva, Switzerland 55 (a) Dipartimento di Fisica, Università di Genova, Genoa, Italy; (b) INFN Sezione di Genova, Genoa, Italy 56 II. Physikalisches Institut, Justus-Liebig-Universität Giessen, Giessen, Germany 57 SUPA-School of Physics and Astronomy, University of Glasgow, Glasgow, UK 58 LPSC, Université Grenoble Alpes, CNRS/IN2P3, Grenoble INP, Grenoble, France 59 Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge, MA, USA 60 (a) Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei, China; (b) Institute of Frontier and Interdisciplinary Science and Key Laboratory of Particle Physics and Particle Irradiation (MOE), Shandong University, Qingdao, China; (c) School of Physics and Astronomy, Shanghai Jiao Tong University, KLPPAC-MoE, SKLPPC, Shanghai, China; (d) Tsung-Dao Lee Institute, Shanghai, China 61 (a) Kirchhoff-Institut für Physik, Ruprecht-Karls-Universität Heidelberg, Heidelberg, Germany; (b) Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg, Germany 62 Faculty of Applied Information Science, Hiroshima Institute of Technology, Hiroshima, Japan 63 (a) Department of Physics, Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China; (b) Department of Physics, University of Hong Kong, Hong Kong, China; (c) Department of Physics and Institute for Advanced Study, 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, USA 66 (a) INFN Gruppo Collegato di Udine, Sezione di Trieste, Udine, Italy; (b) ICTP, Trieste, Italy; (c) Dipartimento Politecnico di Ingegneria e Architettura, Università di Udine, Udine, Italy 67 (a) INFN Sezione di Lecce, Lecce, Italy; (b) Dipartimento di Matematica e Fisica, Università del Salento, Lecce, Italy 68 (a) INFN Sezione di Milano, Milan, Italy; (b) Dipartimento di Fisica, Università di Milano, Milan, Italy 69 (a) INFN Sezione di Napoli, Naples, Italy; (b) Dipartimento di Fisica, Università di Napoli, Naples, Italy 70 (a) INFN Sezione di Pavia, Pavia, Italy; (b) Dipartimento di Fisica, Università di Pavia, Pavia, Italy 71 (a) INFN Sezione di Pisa, Pisa, Italy; (b) Dipartimento di Fisica E. Fermi, Università di Pisa, Pisa, Italy 72 (a) INFN Sezione di Roma, Rome, Italy; (b) Dipartimento di Fisica, Sapienza Università di Roma, Rome, Italy 73 (a) INFN Sezione di Roma Tor Vergata, Rome, Italy; (b) Dipartimento di Fisica, Università di Roma Tor Vergata, Rome, Italy 74 (a) INFN Sezione di Roma Tre, Rome, Italy; (b) Dipartimento di Matematica e Fisica, Università Roma Tre, Rome, Italy 75 (a) INFN-TIFPA, Povo, Italy; (b) Università degli Studi di Trento, Trento, Italy 76 Institut für Astro- und Teilchenphysik, Leopold-Franzens-Universität, Innsbruck, Austria 77 University of Iowa, Iowa City, IA, USA 78 Department of Physics and Astronomy, Iowa State University, Ames, IA, USA 79 Joint Institute for Nuclear Research, Dubna, Russia 80 (a) Departamento de Engenharia Elétrica, Universidade Federal de Juiz de Fora (UFJF), Juiz de Fora, Brazil; (b) Universidade Federal do Rio De Janeiro COPPE/EE/IF, Rio de Janeiro, Brazil; (c) Universidade Federal de São João del Rei (UFSJ), São João del Rei, Brazil; (d) Instituto de Física, 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 (a) AGH University of Science and Technology, Faculty of Physics and Applied Computer Science, Kraków, Poland; (b) Marian Smoluchowski Institute of Physics, Jagiellonian University, Kraków, Poland 84 Institute of Nuclear Physics Polish Academy of Sciences, Kraków, 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 Física La Plata, Universidad Nacional de La Plata and CONICET, La Plata, Argentina 89 Physics Department, Lancaster University, Lancaster, UK 90 Oliver Lodge Laboratory, University of Liverpool, Liverpool, UK 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, UK 123 Eur. Phys. J. C (2019) 79:847 Page 45 of 47 847 93 Department of Physics, Royal Holloway University of London, Egham, UK 94 Department of Physics and Astronomy, University College London, London, UK 95 Louisiana Tech University, Ruston, LA, USA 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 Física 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, UK 101 CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille, France 102 Department of Physics, University of Massachusetts, Amherst, MA, USA 103 Department of Physics, McGill University, Montreal, QC, Canada 104 School of Physics, University of Melbourne, Melbourne, VIC, Australia 105 Department of Physics, University of Michigan, Ann Arbor, MI, USA 106 Department of Physics and Astronomy, Michigan State University, East Lansing, MI, USA 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, Munich, Germany 115 Max-Planck-Institut für Physik (Werner-Heisenberg-Institut), Munich, 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, USA 119 Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen, The Netherlands 120 Nikhef National Institute for Subatomic Physics and University of Amsterdam, Amsterdam, The Netherlands 121 Department of Physics, Northern Illinois University, DeKalb, IL, USA 122 (a) Budker Institute of Nuclear Physics and NSU, SB RAS, Novosibirsk, Russia; (b) Novosibirsk State University Novosibirsk, Novosibirsk, 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, USA 125 Ochanomizu University, Otsuka, Bunkyo-ku, Tokyo, Japan 126 Ohio State University, Columbus, OH, USA 127 Faculty of Science, Okayama University, Okayama, Japan 128 Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman, OK, USA 129 Department of Physics, Oklahoma State University, Stillwater, OK, USA 130 Palacký University, RCPTM, Joint Laboratory of Optics, Olomouc, Czech Republic 131 Center for High Energy Physics, University of Oregon, Eugene, OR, USA 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, UK 136 LPNHE, Sorbonne Université, Paris Diderot Sorbonne Paris Cité, CNRS/IN2P3, Paris, France 137 Department of Physics, University of Pennsylvania, Philadelphia, PA, USA 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, USA 140 (a) Laboratório de Instrumentação e Física Experimental de Partículas-LIP, Lisbon, Portugal; (b) Departamento de Física, Faculdade de Ciências, Universidade de Lisboa, Lisbon, Portugal; (c) Departamento de Física, Universidade de Coimbra, Coimbra, Portugal; (d) Centro de Física Nuclear da Universidade de Lisboa, Lisbon, Portugal; (e) Departamento de Física, 123 847 Page 46 of 47 Eur. Phys. J. C (2019) 79:847 Universidade do Minho, Braga, Portugal; (f) Universidad de Granada, Granada, Spain; (g) Dep Física and CEFITEC of Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica, 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, UK 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, USA 147 (a) Departamento de Física, Pontificia Universidad Católica de Chile, Santiago, Chile; (b) Departamento de Física, Universidad Técnica Federico Santa María, Valparaiso, Chile 148 Department of Physics, University of Washington, Seattle, WA, USA 149 Department of Physics and Astronomy, University of Sheffield, Sheffield, UK 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, USA 154 Physics Department, Royal Institute of Technology, Stockholm, Sweden 155 Departments of Physics and Astronomy, Stony Brook University, Stony Brook, NY, USA 156 Department of Physics and Astronomy, University of Sussex, Brighton, UK 157 School of Physics, University of Sydney, Sydney, Australia 158 Institute of Physics, Academia Sinica, Taipei, Taiwan 159 (a) E. Andronikashvili Institute of Physics, Iv. Javakhishvili Tbilisi State University, Tbilisi, Georgia; (b) High Energy Physics Institute, 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 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 (a) TRIUMF, Vancouver, BC, Canada; (b) Department of Physics and Astronomy, 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, USA 171 Department of Physics and Astronomy, University of California Irvine, Irvine, CA, USA 172 Department of Physics and Astronomy, University of Uppsala, Uppsala, Sweden 173 Department of Physics, University of Illinois, Urbana, IL, USA 174 Instituto de Física 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, UK 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, USA 182 Fakultät für Mathematik und Naturwissenschaften, Fachgruppe Physik, Bergische Universität Wuppertal, Wuppertal, Germany 183 Department of Physics, Yale University, New Haven, CT, USA 184 Yerevan Physics Institute, Yerevan, Armenia a Also at CERN, Geneva, Switzerland b Also at CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille, France 123 Eur. Phys. J. C (2019) 79:847 Page 47 of 47 847 c Also at Département de Physique Nucléaire et Corpusculaire, Université de Genève, Geneva, Switzerland d Also at Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona, Spain e Also at Departamento de Física, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal f Also at Department of Applied Physics and Astronomy, University of Sharjah, Sharjah, United Arab Emirates g Also at Department of Financial and Management Engineering, University of the Aegean, Chios, Greece h Also at Department of Physics and Astronomy, Michigan State University, East Lansing MI, USA i Also at Department of Physics and Astronomy, University of Louisville, Louisville, KY, USA j Also at Department of Physics and Astronomy, University of Sheffield, Sheffield, UK k Also at Department of Physics, California State University, East Bay, USA l Also at Department of Physics, California State University, Fresno, USA m Also at Department of Physics, California State University, Sacramento, USA n Also at Department of Physics, King’s College London, London, UK o Also at Department of Physics, St. Petersburg State Polytechnical University, St. Petersburg, Russia p Also at Department of Physics, Stanford University, Stanford CA, USA q Also at Department of Physics, University of Adelaide, Adelaide, Australia r Also at Department of Physics, University of Fribourg, Fribourg, Switzerland s Also at Department of Physics, University of Michigan, Ann Arbor MI, USA t Also at Faculty of Physics, M.V. Lomonosov Moscow State University, Moscow, Russia u Also at Giresun University, Faculty of Engineering, Giresun, Turkey v Also at Graduate School of Science, Osaka University, Osaka, Japan w Also at Hellenic Open University, Patras, Greece x Also at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona, Spain y Also at Institut für Experimentalphysik, Universität Hamburg, Hamburg, Germany z Also at Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen, Netherlands aa Also at Institute for Nuclear Research and Nuclear Energy (INRNE) of the Bulgarian Academy of Sciences, Sofia, Bulgaria ab Also at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest, Hungary ac Also at Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China ad Also at Institute of Particle Physics (IPP), Canada ae Also at Institute of Physics, Academia Sinica, Taipei, Taiwan af Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan ag Also at Institute of Theoretical Physics, Ilia State University, Tbilisi, Georgia ah Also at Instituto de Fisica Teorica, IFT-UAM/CSIC, Madrid, Spain ai Also at Istanbul University, Dept. of Physics, Istanbul, Turkey aj Also at Joint Institute for Nuclear Research, Dubna, Russia ak Also at LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay, France al Also at Louisiana Tech University, Ruston LA, USA am Also at LPNHE, Sorbonne Université, Paris Diderot Sorbonne Paris Cité, CNRS/IN2P3, Paris, France an Also at Manhattan College, New York NY, USA ao Also at Moscow Institute of Physics and Technology State University, Dolgoprudny, Russia ap Also at National Research Nuclear University MEPhI, Moscow, Russia aq Also at Physics Department, An-Najah National University, Nablus, Palestine ar Also at Physics Dept, University of South Africa, Pretoria, South Africa as Also at Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany at Also at School of Physics, Sun Yat-sen University, Guangzhou, China au Also at The City College of New York, New York NY, USA av Also at The Collaborative Innovation Center of Quantum Matter (CICQM), Beijing, China aw Also at Tomsk State University, Tomsk, and Moscow Institute of Physics and Technology State University, Dolgoprudny, Russia ax Also at TRIUMF, Vancouver BC, Canada ay Also at Universita di Napoli Parthenope, Napoli, Italy ∗ Deceased 123