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Various Standard Model (SM) measurements [1, 2] and searches for physics beyond the SM [3] at the Large Hadron Collider (LHC) [4] benefit from the identification of showers of hadronic particles (jets) originating from quarks or gluons. Several searches employing quark/gluon (
$ q/g $ ) tagging, techniques that tag jets originating from a quark or a gluon, have demonstrated improved sensitivity to new physics and the ability to discriminate between new resonances that decay into different types of hadronic jets [5−8]. For example, in some supersymmetry scenarios, many final-state light quarks can be produced [9, 10]. The ability to discriminate between quark- and gluon-initiated jets, hereafter referred to as ‘quark-jets’ and ‘gluon-jets’, therefore provides a powerful tool to use in searches for new physics. If a new particle were discovered, such a discriminant could provide valuable information about the nature of the particle. Moreover, accurate identification of the origin of jets is crucial in certain SM measurements, such as when reconstructing hadronic decays of W bosons in a measurement of the mass of the top quark.In the theory of quantum chromodynamics (QCD), quarks and gluons are not free particles in their kinematic evolution, and they produce streams of particles that the LHC experiments can measure. Discrimination between jets of different partonic origins has been attempted at several experiments [11−25]. For example, some analyses [26, 27] used the full radiation pattern inside a jet as an image processed in a deep neural network classifier. Most work has relied on jet properties that result from the different colour charges of the partons. According to QCD, the colour charge of a gluon is larger than that of a quark by a factor of
$ 9/4 $ (the ‘Casimir ratio’) [28]. Hence, in their kinematic evolution and hadronisation, the gluons produce more particles, leading to jets with a higher number of constituents and a broader radiation pattern than in quark-jets. Advances in the theoretical [29] and phenomenological [30−33] understanding of the radiation patterns of quark- and gluon-jets have led to recent progress in$ q/g $ tagging. Compared to previous studies which considered single-variable taggers for a lower${p_{{\rm{T}}}}$ range [34, 35], this study focuses on the construction of a new$ q/g $ tagger that utilises several jet substructure variables, and on extending the$ q/g $ tagging of jets to a higher energy range.This paper investigates the performance of two
$ q/g $ taggers, which are built with the goal of identifying quark-jets and rejecting gluon-jets. The first tagger is based on a requirement placed on the charged-particle multiplicity ($n_{\text {track }}$ ) of a jet. The second tagger employs a boosted decision tree (BDT) that takes as input a set of jet kinematic and substructure variables. The$ q/g $ tagging efficiencies are estimated in data by using a method that splits the data sample into subsamples where the fraction of quark-jets is higher or lower than the fraction of gluon-jets (i.e. quark- or gluon-enriched subsamples, respectively).The paper is structured as follows. Section II introduces the ATLAS detector. A brief description of the data and Monte Carlo (MC) samples used in the analysis is given in Section III. In Section IV the object definitions and event selection criteria used to select events and classify them into the various categories are described. Variables used in the definition of the
$ q/g $ taggers studied in this analysis are presented in Section V. The method developed to evaluate the$ q/g $ tagging efficiencies and the taggers' discrimination power is presented in Section VI. Systematic uncertainties affecting the analysis are detailed in Section VII. Measurements of the tagging efficiencies in data and their ratio to those expected from MC simulation (scale factors) are shown in Section VIII, while conclusions are drawn in Section IX. -
The ATLAS detector [36] at the LHC covers nearly the entire solid angle around the collision point.
1 It consists of an inner tracking detector surrounded by a thin superconducting solenoid, electromagnetic and hadron calorimeters, and a muon spectrometer incorporating three large superconducting air-core toroidal magnets.The inner-detector system (ID) is immersed in a 2 T axial magnetic field and provides charged-particle tracking in the range
$|\eta| < 2.5$ . The high-granularity silicon pixel detector covers the vertex region and typically provides four measurements per track, the first hit normally being in the insertable B-layer, which was installed before Run 2 [37]. It is followed by the silicon microstrip tracker, which usually provides eight measurements per track. These silicon detectors are complemented by the transition radiation tracker (TRT), which enables radially extended track reconstruction up to$|\eta| = $ 2.0. The TRT also provides electron identification information based on the fraction of hits (typically 30 in total) above a higher energy-deposit threshold corresponding to transition radiation.The calorimeter system covers the range
$|\eta| < 4.9$ . Within the region$|\eta| < 3.2$ , electromagnetic calorimetry is provided by barrel and endcap high-granularity lead/liquid-argon (LAr) calorimeters, with an additional thin LAr presampler covering$|\eta| < 1.8$ to correct for energy loss in material upstream of the calorimeters. Hadron calorimetry is provided by the steel/scintillator-tile calorimeter, segmented into three barrel structures within$|\eta| < 1.7$ , and two copper/LAr hadron endcap calorimeters. The solid angle coverage is completed with forward copper/LAr and tungsten/LAr calorimeter modules optimised for electromagnetic and hadronic energy measurements, respectively.The muon spectrometer comprises separate trigger and high-precision tracking chambers measuring the deflection of muons in a magnetic field generated by the superconducting air-core toroidal magnets. The field integral of the toroids ranges between 2.0 and 6.0 T m across most of the detector. Three layers of precision chambers, each consisting of layers of monitored drift tubes, cover the region
$|\eta| < 2.7$ . They are complemented by cathode-strip chambers in the forward region, where the background is highest. The muon trigger system covers the range$|\eta| < 2.4$ with resistive-plate chambers in the barrel and thin-gap chambers in the endcap regions.Interesting events are selected by the first-level trigger system implemented in custom hardware, followed by selections made by algorithms implemented in software in the high-level trigger [38]. The first-level trigger accepts events from the 40 MHz bunch crossings at a rate below 100 kHz, which the high-level trigger reduces in order to record events to disk at about 1 kHz.
An extensive software suite [39] is used in data simulation, the reconstruction and analysis of real and simulated data, in detector operations, and in the trigger and data acquisition systems of the experiment.
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The data used in this analysis were collected by the ATLAS detector between 2015 and 2018 from proton– proton collisions at a centre-of-mass energy of
$ \sqrt{s} = 13 $ TeV, and correspond to an integrated luminosity of 140 fb−1 [40]. The events included in this dataset satisfy quality requirements which ensure that all detector systems were operational [41]. This was achieved by monitoring detector-level quantities and the characteristics of reconstructed collision events at key stages of the data processing chain.MC simulations are used to model SM multijet production, which is the main process expected to play a role in this analysis. The Pythia 8.230 [42] generator was used to simulate multijet production with a QCD matrix element (ME) calculation and leading-order (LO) accuracy in the parton shower evolution. The NNPDF2.3lo parton distribution function (PDF) [43] set was used, and Pythia internal parameter values were set according to the A14 tune [44]. The Pythia 8.230 MC sample is taken as the default choice to obtain the nominal result, as it has been tested extensively in previous ATLAS analyses [45, 46] and has been seen to accurately describe the data [47].
Several alternative MC samples are used for the estimation of uncertainties coming from hadronisation modelling. Two sets of MC samples were produced using the Sherpa 2.2.5 [48] generator, with the same ME for the
$2\rightarrow2$ process at LO, the same parton shower configurations based on Catani–Seymour dipole factorisation [49], and the same CT14nnlo PDF set [50], but different hadronisation algorithms. The first set of samples uses the dedicated Sherpa AHADIC model for hadronisation [51], based on cluster fragmentation. The second set of samples was generated with the same configuration but using the Sherpa interface to the Lund string fragmentation model of Pythia 6 [52] and its decay tables.Two multijet MC samples were generated at next-to-leading order (NLO) by Herwig 7.1.3 [53] with the same MMHT2014nlo [54] PDF set and hadronisation model, but with one using of the default parton shower model with angular ordering and the other using the dipole shower as an alternative, allowing an estimation of the effect of the shower model on the results.
Another set of QCD multijet samples with NLO precision in the ME is also included for the ME uncertainty estimation. They were generated with Powheg Box v2 [55–57] and interfaced to Pythia for the parton shower and hadronisation models. The NNPDF3.0nlo [58] PDF set was used for these samples.
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Jets are reconstructed with the anti-
$k_t$ algorithm [59] with a radius parameter of$ R=0.4 $ using as constituents particle-flow (PFlow) objects [60], with the combined information from the ID and the calorimeter. Reconstructed jets are considered isolated if there is no other reconstructed jet within a cone of size$ \Delta R = 0.7 $ around the jet axis. Only isolated jets are considered in this study. An overall jet energy calibration [61] is performed with a sequence of simulation-based corrections and in situ calibrations, which accounts for residual detector effects as well as contributions from the effects of multiple simultaneous$ pp $ collisions (pile-up). Only light-flavoured quark-jets (u, d, s) are considered in this study.Tracks arising from charged particles are reconstructed [62] from the hits in the ID and are required to have transverse momentum
${p_T} > 500$ MeV,$| \eta |< 2.5 $ , at least one pixel hit and at least six hits in the silicon microstrip tracker, as well as transverse and longitudinal impact parameters with respect to the hard-scattering vertex that satisfy$ |d_0| < 1 $ mm and$ |z_0 \sin (\theta)| < 1 $ mm respectively. Additionally, the event is required to have at least one vertex with two or more associated tracks. The vertex with the highest$p_{T}^2$ sum of the associated tracks is considered to be the primary vertex. The ghost-association technique [63] is employed to match tracks to jets; tracks are treated as four-vectors of infinitesimal magnitude during the jet reconstruction and are then assigned to the jet with which they are clustered.A second jet collection used is called ‘truth jets’ [61]. Truth jets are reconstructed from stable final-state particles from the simulation samples, using the same anti-
$k_t \;\; R=0.4 $ algorithm as PFlow jets. They are geometrically matched to PFLow jets by requiring that their angular separation satisfies$ \Delta R< 0.4 $ . Truth jets are assigned a flavour label [34, 35], called ‘truth label’. The truth label of a jet is defined by the flavour of the highest-energy parton in the parton shower, before hadronisation, within a cone of size$ \Delta R = 0.4 $ around the jet axis. Using this definition, jets that originate from gluons splitting into b-quark or c-quark pairs are labelled as heavy-flavour jets, which are often identified by the presence of long-lived or leptonically decaying hadrons, and thus no special discriminant for heavy-flavour quarks is used here [64, 65]. Jets remain unlabelled if no truth parton with${p_{T}} > 1$ GeV is found within the cone surrounding the truth jet. Unlabelled jets typically arise from pile-up, and are less than 1% of the dataset at${p_{T}} > 500$ GeV. They are thus ignored [66].Events used in the analysis were selected with a single-jet trigger, and must have at least two jets with
${p_T} > 500$ GeV. The two leading jets must each have$| \eta |< 2.1 $ to guarantee that they are well within the acceptance of the tracking detector. The ratio of the leading jet's${p_T}$ to the sub-leading jet's${p_{T}}$ is required to be less than 1.5, to select a sample in which the two jets are balanced in${p_T}$ . The two leading-${p_{T}}$ jets are used to define quark-enriched and gluon-enriched subsamples.For each selected jet pair, the jet with the higher
$|\eta|$ value is selected to populate the quark-enriched sample. The other jet, which has a lower$|\eta|$ value, is assigned to a gluon-enriched sample. This selection strategy leverages the fact that in the high proton-momentum-fraction range, the PDF has a higher probability of including valence-quarks. Consequently, the ensemble of jets which are more forward (higher$|\eta|$ ) have a higher probability of being quark-jets, whereas the ensemble of jets which are more central (lower$|\eta|$ ) have a higher probability of being gluon-jets [67]. This is illustrated later for the Pythia MC multijet sample, in Figure 2, where the quark-jet fraction is higher in the forward region than in the central region and also increases with jet${p_{T}}$ . -
Jet substructure variables are useful in developing
$ q/g $ taggers, given the predicted difference between the radiation patterns of quark- and gluon-jets. A variable well suited to this task is the track multiplicity, as gluon-jets are expected to have more constituents than quark-jets. Hence, the$n_{\text {track }}$ in a jet can be used to define a single-variable$ q/g $ tagger by imposing a requirement on its value. In this analysis, a more advanced$ q/g $ tagger based on a BDT is also developed, using information about the jet${p_{T}}$ ,$n_{\text {track }}$ , the jet track width$w^{\text {track }}$ [34, 68], and the two-point energy correlation function$C_1^{\beta=0.2}$ [69, 70], which takes into account the energy distribution within the jet.2 The$|\eta|$ of a jet is not used as an input to the BDT, as it could interfere with the definition of the quark- and gluon-enriched samples and distort the estimation of the fractions of quark- and gluon-jets using the method presented in Section VI.The BDT-tagger is trained using 60 million events with two jets from Pythia MC samples described in Section III, with a dataset distribution of 8:1:1 for training, validation, and testing, respectively. For the simulated events employed in the BDT training process, an additional processing step is implemented to obtain a flattened distribution of the
${p_{T}}$ spectra for quark- and gluon-jets. This step aims to emphasise the training for jets in the tail of the${p_{T}}$ spectrum, and to equalise the numbers of quark- and gluon-jets in the training. In training procedure, the LGBMClassifier from the lightGBM [71] framework is used, with Optuna [72] for hyperparameter tuning. A score is assigned to each BDT that goes into the boosting process based on its error rate. After 100 iterations of this procedure, a stable BDT is established, defined with 224 leaves. The BDT score is used to classify a jet as a quark-jet or a gluon-jet.The performance of a jet tagger is evaluated using a receiver operating characteristic (ROC) curve defined from the quark- and gluon-jet efficiencies. The area under the ROC curve (AUC) is used as a metric to quantify the effectiveness of a tagger, with a larger AUC value indicating better performance. Figure 1 shows the performance of jet tagging variables. The BDT performs better than individual jet-substructure variables, meaning that the BDT-tagger can reject more gluon-jets than the
$n_{\text {track }}$ -only tagger at the same quark-jet efficiency. Since the tagging variables strongly depend on the${p_{T}}$ of a jet, performances and comparisons among taggers are given in different jet-${p_{T}}$ bins with boundaries at 500, 600, 800, 1000, 1200, 1500 and 2000 GeV.
Figure 1. (color online) ROC curves for quark-jet tagging variables, using the Pythia MC sample.
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Evaluating the performance of the
$ q/g $ taggers under study needs samples containing solely quark- or gluon-jets. To extract the$ q/g $ tagging-variable distribution shapes for quark- and gluon-jets in the data, a method that exploits samples with different$ q/g $ fractions is used, called the matrix method [35].In the matrix method, the distribution of a jet variable x for forward jets,
$ p_{\mathrm{F}}(x) $ , and for central jets,$ p_{\mathrm{C}}(x) $ , can be written as:$ \begin{eqnarray} \left(\begin{array}{c} p_{\mathrm{F}}(x)\\ p_{\mathrm{C}}(x)\\ \end{array}\right) &=& \underbrace{ \left(\begin{array}{cc} f_{\mathrm{F,Q}}&f_{\mathrm{F,G}}\\ f_{\mathrm{C,Q}}&f_{\mathrm{C,G}}\\ \end{array}\right) }_{{ \equiv F }} \left(\begin{array}{c} p_\mathrm{Q}(x)\\ p_\mathrm{G}(x)\\ \end{array}\right). \end{eqnarray} $
(1) Here
$ p_{\mathrm{Q}}(x) $ and$ p_{\mathrm{G}}(x) $ are the distributions of the variable x for pure quark- and gluon-jets, respectively, and the matrix F contains the fractions of quark- or gluon-jets in the samples of jets in the forward/central region. Such fractions are taken from MC simulation and are shown in Fig. 2 for the Pythia MC samples. The matrix method allows$ p_{\mathrm{Q}}(x) $ and$ p_{\mathrm{G}}(x) $ to be extracted by inverting the matrix F for every${p_{T}}$ range considered.
Figure 2. (color online) Fractions of quark-jets in the forward (triangles) and the central regions (open triangles) from the Pythia MC multijet sample. The statistical uncertainty is smaller than the marker size.
Equation (1) is valid if it is assumed that the shapes of
$ p_{\mathrm{Q}}(x) $ and$ p_{\mathrm{G}}(x) $ do not depend on whether the jets are in the central region or the forward region. Jet fragmentation at a$ pp $ collider is expected to be mainly governed by the jet${p_{T}}$ and is generally considered independent of η in accordance with the parton type. Therefore, an approach to extract distributions derived from the quark-jets' and gluon-jets' radiation patterns should be valid at the particle level. At the detector level, however, the measured radiation pattern inside jets is no longer independent of η, since changes in detector material and technology may cause variations in the response and introduce differences between the central and forward regions. These effects result in a non-closure of the matrix method.A re-weighting procedure is applied to accommodate this feature and to ensure that the distributions of the jet tagging variables in the central and forward regions match. For each event, the central jet is weighted by a so-called re-weighting factor:
$ \begin{eqnarray*} w(x) =\frac{ p_\text{F} (x)}{ p_\text{C} (x)}. \label{eq:QG-reweight} \end{eqnarray*} $
Even if the re-weighting factor corrects for an effect that is, at first order, independent on the origin of the jet,
$ w(x) $ can be calculated separately for truth-labelled quark-jets and gluon-jets. By default, the re-weighting factor obtained from truth-labelled quark-jets is applied to both the quark-jets and gluon-jets, while the re-weighting factor obtained from truth-labelled gluon-jets is used as an alternative to evaluate the systematic uncertainty associated with the re-weighting procedure.After re-weighting, the extracted
$ p_{\mathrm{Q}}(x) $ and$ p_{\mathrm{G}}(x) $ distributions exhibit good agreement with the truth distributions, as shown in Fig. 3. The shapes of the$ p_{\mathrm{Q}}(x) $ and$ p_{\mathrm{G}}(x) $ distributions extracted from the Pythia MC samples are similar to those in data, with differences within 25%, hence validating the method. A residual non-closure of a few percent still remains, as shown in the middle panel of Figs. 3(a)–3(d), and is taken as an MC non-closure systematic uncertainty, as described in Section VII.
Figure 3. (color online) The distributions of
$n_{\text {track }}$ (a,b) and BDT score (c,d) in quark-jets (left) and gluon-jets (right) in the${p_{T}}$ range between 500 GeV and 600 GeV obtained from truth Pythia (dashed line), extracted Pythia before re-weighting (dash dotted line) and after re-weighting (solid line), and extracted data (dots) are shown in the top panel. The middle panel shows the ratio of extracted Pythia to truth Pythia. The bottom panel shows the ratio of extracted data to extracted Pythia after re-weighting.The tagger working points (WP) are defined for fixed quark-jets efficiency in the nominal Pythia MC sample, for both taggers. The efficiencies for quark- and gluon-jets at a given WP are defined as:
$ \begin{eqnarray} \epsilon_\text{Q/G} (x^{\text{WP}}) = \int_{x<x^\text{WP}} p_\text{Q/G} (x) {{\rm{d}}} x. \end{eqnarray} $
(2) Rejection factors for quark- and gluon-jets can also be defined, as:
$ \begin{eqnarray} \xi_\text{Q/G} (x^{\text{WP}}) = 1 \Big/ \int_{x>x^\text{WP}} p_\text{Q/G} (x) {{\rm{d}}} x = 1 / (1- \epsilon_\text{Q/G} (x^{\text{WP}})). \end{eqnarray} $
(3) Differences between the quark-jet tagging efficiencies and gluon-jet rejection measured in data and the ones extracted from MC samples are described by data-to-MC scale factors (SF), for each
$ q/g $ tagger and in various${p_{T}}$ bins, at a fixed WP. The SF is defined using Eqs. (2) and (3) for quark- and gluon-jets, respectively:$ \begin{eqnarray} {\rm{SF}}_{\mathrm{Q}} (x^{\text{WP}}) =\frac{\epsilon_\mathrm{Q}^\text{Data}(x^{\text{WP}})}{\epsilon_\mathrm{Q}^\text{MC}(x^{\text{WP}})} \end{eqnarray} $
(4) $ \begin{eqnarray} {\rm{SF}}_{\mathrm{G}} (x^{\text{WP}}) =\frac{\xi_\mathrm{G}^\text{Data}(x^{\text{WP}})}{\xi_\mathrm{G}^\text{MC}(x^{\text{WP}})}, \end{eqnarray} $
(5) where
$ \epsilon_\mathrm{Q/G}^\text{Data} (x^{\text{WP}}) $ and$ \epsilon_\mathrm{Q/G}^\text{MC} (x^{\text{WP}}) $ are$ \epsilon_\mathrm{Q/G}(x^{\text{WP}}) $ in data and MC samples, respectively. The same definitions apply to$ \xi_\mathrm{Q/G}(x^{\text{WP}}) $ . The WPs corresponding to 50%, 60%, 70% and 80% fixed quark-jets tagging efficiency have been studied and their corresponding SFs exhibit similar characteristics. The results for the 50% WP are shown in Section VIII. -
Several sources of systematic uncertainty affect the measurement of the SFs. Theoretical uncertainties arise from the modelling in the MC simulation, due to the choice of matrix element, parton showering model, PDF, renormalisation and factorisation scales, and hadronisation model. The experimental uncertainties coming from the calibration of the jet energy scale (JES) and jet energy resolution (JER) [73] and from track reconstruction are also taken into account. Uncertainties due to methodology, such as the one associated with the re-weighting procedure and the residual MC non-closure, are also considered and propagated to the final SF measurements.
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The uncertainty due to the modelling of the parton shower is obtained by comparing SFs in two Herwig MC samples with the same ME and hadronisation model but different shower algorithms, as described in Section III; this uncertainty varies between 1% and 9%. The systematic uncertainty due to the hadronisation modelling is estimated as the difference between the SFs obtained with two Sherpa MC samples with different hadronisation models; this uncertainty ranges between 1% and 8%. An additional uncertainty covering the calculation of the ME and its matching to the parton shower algorithm is estimated from the differences between the SFs extracted using Powheg+Pythia and Pythia MC samples. This uncertainty amounts to approximately 1% to 4%.
The uncertainty due to the chosen PDF is evaluated using the LHAPDF recommendations [74]. The uncertainty is estimated using the variations of the NNPDF2.3lo PDF set in the nominal Pythia MC sample, and it amounts to 5%–7%.
Variations of the renormalisation (
$\mu_{\rm{r}}$ ) and factorisation ($\mu_{\rm{f}}$ ) scales for initial- and final-state radiation are used as scale uncertainties to estimate the uncertainty due to missing higher-order corrections. Seven variations of ($\mu_{\rm{r}}$ ,$\mu_{\rm{f}}$ ), with their nominal values multiplied by factors of (0.5, 0.5), (0.5, 1), (1, 0.5), (1, 1), (2, 1), (1,2) and (2, 2), are used for the uncertainty, which is estimated from the envelope of the SFs obtained from such variations in Pythia MC samples. The uncertainty amounts to approximately 4% to 7%.The splitting-Kernel variations [75] pertain to modifications of the non-singular part of the splitting functions for initial-state radiation and final-state radiation, since significant uncertainties in the non-singular terms indicate more matched matrix elements included in the computation. The uncertainty is estimated by taking the envelope of the variations of non-singular terms and it is less than 1%.
In total, the whole theoretical uncertainty amounts to approximately 18% for both taggers and is found to be the main source of uncertainty.
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Experimental uncertainties come from two sources: tracking efficiencies and the JES/JER calibration. The number of associated tracks is the most important input for both taggers, and the tracking-related systematic uncertainties can impact the SF measurements. The uncertainty in the number of reconstructed tracks is split into two terms: the uncertainty in the track reconstruction efficiency and the fake-track rate [62]. Both uncertainty sources are taken into account to recalculate the number of tracks associated with jets. The track reconstruction efficiency is affected by detector material uncertainties, which are the dominant source, and the physics model. They are estimated by comparing the track reconstruction efficiencies in MC samples with varied detector modelling. The fake-track rate uncertainty is estimated from a data-to-MC comparison of the evolution of the non-linear component of the track multiplicity as a function of the average mean number of interactions per bunch crossing. The tracking systematic uncertainty is obtained from changes in the SFs after applying the systematic variations and is approximately 1% to 8%.
The JES uncertainties [73] arise from calibrating the transverse momentum balance between central and forward jets, as well as accounting for single-particle and test-beam uncertainties. The JER uncertainties consider the JER difference between data and MC samples, by studying the dijet
${p_{T}}$ balance asymmetry. An SF is obtained for each JES/JER variation, and the change from the nominal SF value is taken as the systematic uncertainty. The total JES/JER uncertainty is approximately 0.2%. -
Uncertainties associated with the matrix method come from the re-weighting process and the residual MC non-closure. In estimating the systematic uncertainty from the re-weighting process, the weights obtained from truth-labelled gluon-jets are used as an alternative, as explained in Section VI. The resulting impact on the SFs is small (between 0.1% and 0.5%) across the whole
${p_{T}}$ range considered. The residual MC non-closure, which is observed after the re-weighting procedure, affects the SFs at the 1% level for both$ q/g $ taggers studied.The statistical uncertainty is calculated by varying the input data distributions bin-by-bin using a Poisson distribution with the number of events in each bin as the central value. The same procedure is applied to the MC samples, but using a Gaussian distribution. Each variation of the input distributions is used as an input to the matrix method. This procedure is repeated 5000 times, with the standard deviation of the uncertainties from all pseudo-datasets taken to be the statistical uncertainty of the scale factor. This uncertainty is approximately 0.1%.
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Figure 4 shows the gluon-jets efficiency factor defined by Eq. (2) as a function of jet
${p_{T}}$ in both the MC samples and data, for the 50% quark-jets efficiency WP (50% WP). For this WP, around 90% of the gluon-jets are rejected by the$n_{\text {track }}$ -only tagger, while approximately 93% of gluon-jets are rejected by the BDT-tagger. The BDT-tagger is found to perform better or as well as the$n_{\text {track }}$ -only tagger, i.e. it has a lower gluon-jet efficiency at the same WP. This is because the BDT-tagger includes more jet substructure variables. The difference between the gluon-jets efficiency in data and MC samples increases with increasing jet${p_{T}}$ , which is related to the MC modelling of gluons being different from the actual data. Such effect is more significant for the BDT-tagger.
Figure 4. (color online) Inverse of the gluon-jet efficiency for the
$n_{\text {track }}$ -only tagger (circles) and BDT-tagger (stars) as a function of jet${p_{T}}$ at the 50% WP in data (closed symbols) and the Pythia MC sample (open symbols). The vertical error bars show the statistical uncertainty.Figure 5 shows that the SFs for both quark-jets and gluon-jets at the 50% quark-jets efficiency WP are between 0.92 and 1.02, with a total systematic uncertainty of about 20%. The dominant source of systematic uncertainty is theoretical modelling. Tests were performed to check the stability of the results versus
$|\eta|$ . The SF measurements were repeated after flattening the jet$|\eta|$ of the quark-/gluon-enriched subsamples. These alternative results are compatible with the nominal ones, within the total uncertainty reported.
Figure 5. (color online) The scale factors (dots) defined in Eq. (5) with the total uncertainty (band), leading theoretical uncertainties (lines) and experimental uncertainty (vertical error bar) of the
$n_{\text {track }}$ -only tagger (a,b) and the BDT-tagger (c,d) as a function of jet${p_{T}}$ for quark-jets (left) and gluon-jets (right) at the 50% WP using the Pythia MC sample.Since analyses interested in using the results reported in Fig. 5 may use different MC samples, a MC-to-MC SF is obtained by using each of the alternative MC samples and treating the Pythia MC samples as pseudo-data, to account for modelling differences between the Pythia and alternative MC samples. The MC-to-MC SFs for both jet taggers vary from 0.9 to 1.1 for most MC samples, as shown in Fig. 6. There are relatively large gluon modelling differences between the Herwig dipole parton shower and the Pythia parton shower, resulting in large MC-to-MC SFs.
Figure 6. (color online) The MC-to-MC scale factor for the
$n_{\text {track }}$ -only tagger (a,b) and BDT-tagger (c,d) as a function of jet${p_{T}}$ for quark-jets (left) and gluon-jets (right) at the 50% WP. The vertical error bars show the statistical uncertainty. -
The performance of taggers for quark- and gluon-initiated jets is studied using 140 fb
$ ^{-1} $ of data from$ pp $ collisions at$ \sqrt{s} = 13 $ TeV collected by the ATLAS detector at the LHC, taking full advantage of the large dataset recorded from 2015 to 2018 to extend the taggers' reach to high jet energy. Two methods of jet tagging are investigated: a BDT-tagger, which combines several jet substructure observables, and a tagger based on the charged-particle jet-constituent multiplicity$n_{\text {track }}$ . A matrix method is used to estimate the distribution shape of the tagging variables for quark- and gluon-jets, by combining information from quark-enriched and gluon-enriched samples obtained from a selection of two-jet events with jet${p_{T}}$ ranging from 500 GeV to 2 TeV. The variables considered are found to be described adequately by the MC, as differences with respect to ones measured in data are found to be smaller than 25%, in all the different regions defined. When tested in data, the BDT-tagger is found to have better performance than the$n_{\text {track }}$ -only tagger in selecting quark-jets over gluon-jets between 500 GeV and 1200 GeV, while above this range, the performance of the two taggers is comparable. For a fixed quark-jet efficiency of 50%, the$n_{\text {track }}$ -only tagger is able to reject approximately 90% of gluon-jets, while the BDT-tagger is able to reject approximately 93% of gluon-jets. A measurement of tagger performance differences in data and MC samples is provided through the definition of data-to-MC scale factors. The scale factors are measured in different jet-${p_{T}}$ intervals and are found to range from 0.92 to 1.02, with a total uncertainty of around 20% which increases at higher${p_{T}}$ . The main source of uncertainty comes from the different modelling choices in MC simulation and amounts to approximately 18% for both taggers. To account for differences among various MC generators, MC-to-MC scale factors are also provided, ranging from 0.9 to 1.1 for most MC samples. The$ q/g $ taggers developed in this article and the measurement of their SFs will benefit various analyses such as SM measurements that rely on the correct identification of jet origins, or new physics searches by enhancing their sensitivity to the presence of new particles. -
We thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), RAL (UK) and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resource providers. Major contributors of computing resources are listed in Ref. [76].
Performance and calibration of quark/gluon-jet taggers using 140 fb−1 of pp collisions at ${{\sqrt{\boldsymbol s}\bf = 13}}$
TeV with the ATLAS detector
- G. Aad 102, ,
- B. Abbott 120, ,
- K. Abeling 55, ,
- N.J. Abicht 49, ,
- S.H. Abidi 29, ,
- A. Aboulhorma 35e, ,
- H. Abramowicz 151, ,
- H. Abreu 150, ,
- Y. Abulaiti 117, ,
- B.S. Acharya 69a,69b,q, ,
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- P. Camarri 76a,76b, ,
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- M. Caspar 48, ,
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- V. Castillo Gimenez 163, ,
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- N. Cavalli 23b,23a, ,
- V. Cavasinni 74a,74b, ,
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- F. Celli 126, ,
- M.S. Centonze 70a,70b, ,
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- A.S. Cerqueira 83a, ,
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- B. Cervato 141, ,
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- A. Chitan 27b, ,
- M. Chitishvili 163, ,
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- K. Choi 11, ,
- A.R. Chomont 75a,75b, ,
- Y. Chou 103, ,
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- T. Chowdhury 33g, ,
- K.L. Chu 169, ,
- M.C. Chu 64a, ,
- X. Chu 14a,14e, ,
- J. Chudoba 131, ,
- J.J. Chwastowski 87, ,
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- K.M. Ciesla 86a, ,
- V. Cindro 93, ,
- A. Ciocio 17a, ,
- F. Cirotto 72a,72b, ,
- Z.H. Citron 169,o, ,
- M. Citterio 71a, ,
- D.A. Ciubotaru 27b, ,
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- A. Clark 56, ,
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- J.M. Clavijo Columbie 48, ,
- S.E. Clawson 48, ,
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- L. Clissa 23b,23a, ,
- Y. Coadou 102, ,
- M. Cobal 69a,69c, ,
- A. Coccaro 57b, ,
- R.F. Coelho Barrue 130a, ,
- R. Coelho Lopes De Sa 103, ,
- S. Coelli 71a, ,
- H. Cohen 151, ,
- A.E.C. Coimbra 71a,71b, ,
- B. Cole 41, ,
- J. Collot 60, ,
- P. Conde Muiño 130a,130g, ,
- M.P. Connell 33c, ,
- S.H. Connell 33c, ,
- I.A. Connelly 59, ,
- E.I. Conroy 126, ,
- F. Conventi 72a,ax, ,
- H.G. Cooke 20, ,
- A.M. Cooper-Sarkar 126, ,
- A. Cordeiro Oudot Choi 127, ,
- L.D. Corpe 40, ,
- M. Corradi 75a,75b, ,
- F. Corriveau 104,ai, ,
- A. Cortes-Gonzalez 18, ,
- M.J. Costa 163, ,
- F. Costanza 4, ,
- D. Costanzo 139, ,
- B.M. Cote 119, ,
- G. Cowan 95, ,
- K. Cranmer 170, ,
- D. Cremonini 23b,23a, ,
- S. Crépé-Renaudin 60, ,
- F. Crescioli 127, ,
- M. Cristinziani 141, ,
- M. Cristoforetti 78a,78b, ,
- V. Croft 114, ,
- J.E. Crosby 121, ,
- G. Crosetti 43b,43a, ,
- A. Cueto 99, ,
- T. Cuhadar Donszelmann 160, ,
- H. Cui 14a,14e, ,
- Z. Cui 7, ,
- W.R. Cunningham 59, ,
- F. Curcio 43b,43a, ,
- P. Czodrowski 36, ,
- M.M. Czurylo 63b, ,
- M.J. Da Cunha Sargedas De Sousa 57b,57a, ,
- J.V. Da Fonseca Pinto 83b, ,
- C. Da Via 101, ,
- W. Dabrowski 86a, ,
- T. Dado 49, ,
- S. Dahbi 33g, ,
- T. Dai 106, ,
- D. Dal Santo 19, ,
- C. Dallapiccola 103, ,
- M. Dam 42, ,
- G. D'amen 29, ,
- V. D'Amico 109, ,
- J. Damp 100, ,
- J.R. Dandoy 128, ,
- M.F. Daneri 30, ,
- M. Danninger 142, ,
- V. Dao 36, ,
- G. Darbo 57b, ,
- S. Darmora 6, ,
- S.J. Das 29,az, ,
- S. D'Auria 71a,71b, ,
- C. David 156b, ,
- T. Davidek 133, ,
- B. Davis-Purcell 34, ,
- I. Dawson 94, ,
- H.A. Day-hall 132, ,
- K. De 8, ,
- R. De Asmundis 72a, ,
- N. De Biase 48, ,
- S. De Castro 23b,23a, ,
- N. De Groot 113, ,
- P. de Jong 114, ,
- H. De la Torre 115, ,
- A. De Maria 14c, ,
- A. De Salvo 75a, ,
- U. De Sanctis 76a,76b, ,
- A. De Santo 146, ,
- J.B. De Vivie De Regie 60, ,
- D.V. Dedovich 38, ,
- J. Degens 114, ,
- A.M. Deiana 44, ,
- F. Del Corso 23b,23a, ,
- J. Del Peso 99, ,
- F. Del Rio 63a, ,
- F. Deliot 135, ,
- C.M. Delitzsch 49, ,
- M. Della Pietra 72a,72b, ,
- D. Della Volpe 56, ,
- A. Dell'Acqua 36, ,
- L. Dell'Asta 71a,71b, ,
- M. Delmastro 4, ,
- P.A. Delsart 60, ,
- S. Demers 172, ,
- M. Demichev 38, ,
- S.P. Denisov 37, ,
- L. D'Eramo 40, ,
- D. Derendarz 87, ,
- F. Derue 127, ,
- P. Dervan 92, ,
- K. Desch 24, ,
- C. Deutsch 24, ,
- F.A. Di Bello 57b,57a, ,
- A. Di Ciaccio 76a,76b, ,
- L. Di Ciaccio 4, ,
- A. Di Domenico 75a,75b, ,
- C. Di Donato 72a,72b, ,
- A. Di Girolamo 36, ,
- G. Di Gregorio 36, ,
- A. Di Luca 78a,78b, ,
- B. Di Micco 77a,77b, ,
- R. Di Nardo 77a,77b, ,
- C. Diaconu 102, ,
- M. Diamantopoulou 34, ,
- F.A. Dias 114, ,
- T. Dias Do Vale 142, ,
- M.A. Diaz 137a,137b, ,
- F.G. Diaz Capriles 24, ,
- M. Didenko 163, ,
- E.B. Diehl 106, ,
- L. Diehl 54, ,
- S. Díez Cornell 48, ,
- C. Diez Pardos 141, ,
- C. Dimitriadi 161,24,161, ,
- A. Dimitrievska 17a, ,
- J. Dingfelder 24, ,
- I-M. Dinu 27b, ,
- S.J. Dittmeier 63b, ,
- F. Dittus 36, ,
- F. Djama 102, ,
- T. Djobava 149b, ,
- J.I. Djuvsland 16, ,
- C. Doglioni 101,98, ,
- A. Dohnalova 28a, ,
- J. Dolejsi 133, ,
- Z. Dolezal 133, ,
- K.M. Dona 39, ,
- M. Donadelli 83c, ,
- B. Dong 107, ,
- J. Donini 40, ,
- A. D'Onofrio 77a,77b, ,
- M. D'Onofrio 92, ,
- J. Dopke 134, ,
- A. Doria 72a, ,
- N. Dos Santos Fernandes 130a, ,
- P. Dougan 101, ,
- M.T. Dova 90, ,
- A.T. Doyle 59, ,
- M.A. Draguet 126, ,
- E. Dreyer 169, ,
- I. Drivas-koulouris 10, ,
- M. Drnevich 117, ,
- A.S. Drobac 158, ,
- M. Drozdova 56, ,
- D. Du 62a, ,
- T.A. du Pree 114, ,
- F. Dubinin 37, ,
- M. Dubovsky 28a, ,
- E. Duchovni 169, ,
- G. Duckeck 109, ,
- O.A. Ducu 27b, ,
- D. Duda 52, ,
- A. Dudarev 36, ,
- E.R. Duden 26, ,
- M. D'uffizi 101, ,
- L. Duflot 66, ,
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- J.A. Krzysiak 87, ,
- O. Kuchinskaia 37, ,
- S. Kuday 3a, ,
- S. Kuehn 36, ,
- R. Kuesters 54, ,
- T. Kuhl 48, ,
- V. Kukhtin 38, ,
- Y. Kulchitsky 37,a, ,
- S. Kuleshov 137d,137b, ,
- M. Kumar 33g, ,
- N. Kumari 48, ,
- A. Kupco 131, ,
- T. Kupfer 49, ,
- A. Kupich 37, ,
- O. Kuprash 54, ,
- H. Kurashige 85, ,
- L.L. Kurchaninov 156a, ,
- O. Kurdysh 66, ,
- Y.A. Kurochkin 37, ,
- A. Kurova 37, ,
- M. Kuze 154, ,
- A.K. Kvam 103, ,
- J. Kvita 122, ,
- T. Kwan 104, ,
- N.G. Kyriacou 106, ,
- L.A.O. Laatu 102, ,
- C. Lacasta 163, ,
- F. Lacava 75a,75b, ,
- H. Lacker 18, ,
- D. Lacour 127, ,
- N.N. Lad 96, ,
- E. Ladygin 38, ,
- B. Laforge 127, ,
- T. Lagouri 137e, ,
- F.Z. Lahbabi 35a, ,
- S. Lai 55, ,
- I.K. Lakomiec 86a, ,
- N. Lalloue 60, ,
- J.E. Lambert 165,n, ,
- S. Lammers 68, ,
- W. Lampl 7, ,
- C. Lampoudis 152,f, ,
- A.N. Lancaster 115, ,
- E. Lançon 29, ,
- U. Landgraf 54, ,
- M.P.J. Landon 94, ,
- V.S. Lang 54, ,
- R.J. Langenberg 103, ,
- O.K.B. Langrekken 125, ,
- A.J. Lankford 160, ,
- F. Lanni 36, ,
- K. Lantzsch 24, ,
- A. Lanza 73a, ,
- A. Lapertosa 57b,57a, ,
- J.F. Laporte 135, ,
- T. Lari 71a, ,
- F. Lasagni Manghi 23b, ,
- M. Lassnig 36, ,
- V. Latonova 131, ,
- A. Laudrain 100, ,
- A. Laurier 150, ,
- S.D. Lawlor 139, ,
- Z. Lawrence 101, ,
- M. Lazzaroni 71a,71b, ,
- B. Le 101, ,
- E.M. Le Boulicaut 51, ,
- B. Leban 93, ,
- A. Lebedev 81, ,
- M. LeBlanc 101,as, ,
- F. Ledroit-Guillon 60, ,
- A.C.A. Lee 96, ,
- S.C. Lee 148, ,
- S. Lee 47a,47b, ,
- T.F. Lee 92, ,
- L.L. Leeuw 33c, ,
- H.P. Lefebvre 95, ,
- M. Lefebvre 165, ,
- C. Leggett 17a, ,
- G. Lehmann Miotto 36, ,
- M. Leigh 56, ,
- W.A. Leight 103, ,
- W. Leinonen 113, ,
- A. Leisos 152,ac, ,
- M.A.L. Leite 83c, ,
- C.E. Leitgeb 48, ,
- R. Leitner 133, ,
- K.J.C. Leney 44, ,
- T. Lenz 24, ,
- S. Leone 74a, ,
- C. Leonidopoulos 52, ,
- A. Leopold 144, ,
- C. Leroy 108, ,
- R. Les 107, ,
- C.G. Lester 32, ,
- M. Levchenko 37, ,
- J. Levêque 4, ,
- D. Levin 106, ,
- L.J. Levinson 169, ,
- M.P. Lewicki 87, ,
- D.J. Lewis 4, ,
- A. Li 5, ,
- B. Li 62b, ,
- C. Li 62a, ,
- C-Q. Li 62c, ,
- H. Li 62a, ,
- H. Li 62b, ,
- H. Li 14c, ,
- H. Li 14b, ,
- H. Li 62b, ,
- J. Li 62c, ,
- K. Li 138, ,
- L. Li 62c, ,
- M. Li 14a,14e, ,
- Q.Y. Li 62a, ,
- S. Li 14a,14e, ,
- S. Li 62d,62c,e, ,
- T. Li 5,c, ,
- X. Li 104, ,
- Z. Li 126, ,
- Z. Li 104, ,
- Z. Li 92, ,
- Z. Li 14a,14e, ,
- S. Liang 14a,14e, ,
- Z. Liang 14a, ,
- M. Liberatore 135,am, ,
- B. Liberti 76a, ,
- K. Lie 64c, ,
- J. Lieber Marin 83b, ,
- H. Lien 68, ,
- K. Lin 107, ,
- R.E. Lindley 7, ,
- J.H. Lindon 2, ,
- E. Lipeles 128, ,
- A. Lipniacka 16, ,
- A. Lister 164, ,
- J.D. Little 4, ,
- B. Liu 14a, ,
- B.X. Liu 142, ,
- D. Liu 62d,62c, ,
- J.B. Liu 62a, ,
- J.K.K. Liu 32, ,
- K. Liu 62d,62c, ,
- M. Liu 62a, ,
- M.Y. Liu 62a, ,
- P. Liu 14a, ,
- Q. Liu 62d,138,62c, ,
- X. Liu 62a, ,
- Y. Liu 14d,14e, ,
- Y.L. Liu 62b, ,
- Y.W. Liu 62a, ,
- J. Llorente Merino 142, ,
- S.L. Lloyd 94, ,
- E.M. Lobodzinska 48, ,
- P. Loch 7, ,
- T. Lohse 18, ,
- K. Lohwasser 139, ,
- E. Loiacono 48, ,
- M. Lokajicek 131, ,
- J.D. Lomas 20, ,
- J.D. Long 162, ,
- I. Longarini 160, ,
- L. Longo 70a,70b, ,
- R. Longo 162, ,
- I. Lopez Paz 67, ,
- A. Lopez Solis 48, ,
- J. Lorenz 109, ,
- N. Lorenzo Martinez 4, ,
- A.M. Lory 109, ,
- O. Loseva 37, ,
- X. Lou 47a,47b, ,
- X. Lou 14a,14e, ,
- A. Lounis 66, ,
- J. Love 6, ,
- P.A. Love 91, ,
- G. Lu 14a,14e, ,
- M. Lu 80, ,
- S. Lu 128, ,
- Y.J. Lu 65, ,
- H.J. Lubatti 138, ,
- C. Luci 75a,75b, ,
- F.L. Lucio Alves 14c, ,
- A. Lucotte 60, ,
- F. Luehring 68, ,
- I. Luise 145, ,
- O. Lukianchuk 66, ,
- O. Lundberg 144, ,
- B. Lund-Jensen 144, ,
- N.A. Luongo 123, ,
- M.S. Lutz 151, ,
- A.B. Lux 25, ,
- D. Lynn 29, ,
- H. Lyons 92, ,
- R. Lysak 131, ,
- E. Lytken 98, ,
- V. Lyubushkin 38, ,
- T. Lyubushkina 38, ,
- M.M. Lyukova 145, ,
- H. Ma 29, ,
- K. Ma 62a, ,
- L.L. Ma 62b, ,
- Y. Ma 121, ,
- D.M. Mac Donell 165, ,
- G. Maccarrone 53, ,
- J.C. MacDonald 100, ,
- P.C. Machado De Abreu Farias 83b, ,
- R. Madar 40, ,
- W.F. Mader 50, ,
- T. Madula 96, ,
- J. Maeda 85, ,
- T. Maeno 29, ,
- H. Maguire 139, ,
- V. Maiboroda 135, ,
- A. Maio 130a,130b,130d, ,
- K. Maj 86a, ,
- O. Majersky 48, ,
- S. Majewski 123, ,
- N. Makovec 66, ,
- V. Maksimovic 15, ,
- B. Malaescu 127, ,
- Pa. Malecki 87, ,
- V.P. Maleev 37, ,
- F. Malek 60, ,
- M. Mali 93, ,
- D. Malito 95,s, ,
- U. Mallik 80, ,
- S. Maltezos 10, ,
- S. Malyukov 38, ,
- J. Mamuzic 13, ,
- G. Mancini 53, ,
- G. Manco 73a,73b, ,
- J.P. Mandalia 94, ,
- I. Mandić 93, ,
- L. Manhaes de Andrade Filho 83a, ,
- I.M. Maniatis 169, ,
- J. Manjarres Ramos 102,an, ,
- D.C. Mankad 169, ,
- A. Mann 109, ,
- B. Mansoulie 135, ,
- S. Manzoni 36, ,
- X. Mapekula 33c, ,
- A. Marantis 152,ac, ,
- G. Marchiori 5, ,
- M. Marcisovsky 131, ,
- C. Marcon 71a,71b, ,
- M. Marinescu 20, ,
- M. Marjanovic 120, ,
- E.J. Marshall 91, ,
- Z. Marshall 17a, ,
- S. Marti-Garcia 163, ,
- T.A. Martin 167, ,
- V.J. Martin 52, ,
- B. Martin dit Latour 16, ,
- L. Martinelli 75a,75b, ,
- M. Martinez 13,ad, ,
- P. Martinez Agullo 163, ,
- V.I. Martinez Outschoorn 103, ,
- P. Martinez Suarez 13, ,
- S. Martin-Haugh 134, ,
- V.S. Martoiu 27b, ,
- A.C. Martyniuk 96, ,
- A. Marzin 36, ,
- D. Mascione 78a,78b, ,
- L. Masetti 100, ,
- T. Mashimo 153, ,
- J. Masik 101, ,
- A.L. Maslennikov 37, ,
- L. Massa 23b, ,
- P. Massarotti 72a,72b, ,
- P. Mastrandrea 74a,74b, ,
- A. Mastroberardino 43b,43a, ,
- T. Masubuchi 153, ,
- T. Mathisen 161, ,
- J. Matousek 133, ,
- N. Matsuzawa 153, ,
- J. Maurer 27b, ,
- B. Maček 93, ,
- D.A. Maximov 37, ,
- R. Mazini 148, ,
- I. Maznas 152, ,
- M. Mazza 107, ,
- S.M. Mazza 136, ,
- E. Mazzeo 71a,71b, ,
- C. Mc Ginn 29, ,
- J.P. Mc Gowan 104, ,
- S.P. Mc Kee 106, ,
- E.F. McDonald 105, ,
- A.E. McDougall 114, ,
- J.A. Mcfayden 146, ,
- R.P. McGovern 128, ,
- G. Mchedlidze 149b, ,
- R.P. Mckenzie 33g, ,
- T.C. Mclachlan 48, ,
- D.J. Mclaughlin 96, ,
- S.J. McMahon 134, ,
- C.M. Mcpartland 92, ,
- R.A. McPherson 165,ai, ,
- S. Mehlhase 109, ,
- A. Mehta 92, ,
- D. Melini 150, ,
- B.R. Mellado Garcia 33g, ,
- A.H. Melo 55, ,
- F. Meloni 48, ,
- A.M. Mendes Jacques Da Costa 101, ,
- H.Y. Meng 155, ,
- L. Meng 91, ,
- S. Menke 110, ,
- M. Mentink 36, ,
- E. Meoni 43b,43a, ,
- C. Merlassino 126, ,
- L. Merola 72a,72b, ,
- C. Meroni 71a,71b, ,
- G. Merz 106, ,
- O. Meshkov 37, ,
- J. Metcalfe 6, ,
- A.S. Mete 6, ,
- C. Meyer 68, ,
- J-P. Meyer 135, ,
- R.P. Middleton 134, ,
- L. Mijović 52, ,
- G. Mikenberg 169, ,
- M. Mikestikova 131, ,
- M. Mikuž 93, ,
- H. Mildner 100, ,
- A. Milic 36, ,
- C.D. Milke 44, ,
- D.W. Miller 39, ,
- L.S. Miller 34, ,
- A. Milov 169, ,
- D.A. Milstead 47a,47b, ,
- T. Min 14c, ,
- A.A. Minaenko 37, ,
- I.A. Minashvili 149b, ,
- L. Mince 59, ,
- A.I. Mincer 117, ,
- B. Mindur 86a, ,
- M. Mineev 38, ,
- Y. Mino 88, ,
- L.M. Mir 13, ,
- M. Miralles Lopez 163, ,
- M. Mironova 17a, ,
- A. Mishima 153, ,
- M.C. Missio 113, ,
- A. Mitra 167, ,
- V.A. Mitsou 163, ,
- Y. Mitsumori 111, ,
- O. Miu 155, ,
- P.S. Miyagawa 94, ,
- T. Mkrtchyan 63a, ,
- M. Mlinarevic 96, ,
- T. Mlinarevic 96, ,
- M. Mlynarikova 36, ,
- S. Mobius 19, ,
- P. Moder 48, ,
- P. Mogg 109, ,
- A.F. Mohammed 14a,14e, ,
- S. Mohapatra 41, ,
- G. Mokgatitswane 33g, ,
- L. Moleri 169, ,
- B. Mondal 141, ,
- S. Mondal 132, ,
- G. Monig 146, ,
- K. Mönig 48, ,
- E. Monnier 102, ,
- L. Monsonis Romero 163, ,
- J. Montejo Berlingen 13, ,
- M. Montella 119, ,
- F. Montereali 77a,77b, ,
- F. Monticelli 90, ,
- S. Monzani 69a,69c, ,
- N. Morange 66, ,
- A.L. Moreira De Carvalho 130a, ,
- M. Moreno Llácer 163, ,
- C. Moreno Martinez 56, ,
- P. Morettini 57b, ,
- S. Morgenstern 36, ,
- M. Morii 61, ,
- M. Morinaga 153, ,
- A.K. Morley 36, ,
- F. Morodei 75a,75b, ,
- L. Morvaj 36, ,
- P. Moschovakos 36, ,
- B. Moser 36, ,
- M. Mosidze 149b, ,
- T. Moskalets 54, ,
- P. Moskvitina 113, ,
- J. Moss 31,p, ,
- E.J.W. Moyse 103, ,
- O. Mtintsilana 33g, ,
- S. Muanza 102, ,
- J. Mueller 129, ,
- D. Muenstermann 91, ,
- R. Müller 19, ,
- G.A. Mullier 161, ,
- A.J. Mullin 32, ,
- J.J. Mullin 128, ,
- D.P. Mungo 155, ,
- D. Munoz Perez 163, ,
- F.J. Munoz Sanchez 101, ,
- M. Murin 101, ,
- W.J. Murray 167,134, ,
- A. Murrone 71a,71b, ,
- M. Muškinja 17a, ,
- C. Mwewa 29, ,
- A.G. Myagkov 37,a, ,
- A.J. Myers 8, ,
- G. Myers 68, ,
- M. Myska 132, ,
- B.P. Nachman 17a, ,
- O. Nackenhorst 49, ,
- A. Nag 50, ,
- K. Nagai 126, ,
- K. Nagano 84, ,
- J.L. Nagle 29,az, ,
- E. Nagy 102, ,
- A.M. Nairz 36, ,
- Y. Nakahama 84, ,
- K. Nakamura 84, ,
- K. Nakkalil 5, ,
- H. Nanjo 124, ,
- R. Narayan 44, ,
- E.A. Narayanan 112, ,
- I. Naryshkin 37, ,
- M. Naseri 34, ,
- S. Nasri 159, ,
- C. Nass 24, ,
- G. Navarro 22a, ,
- J. Navarro-Gonzalez 163, ,
- R. Nayak 151, ,
- A. Nayaz 18, ,
- P.Y. Nechaeva 37, ,
- F. Nechansky 48, ,
- L. Nedic 126, ,
- T.J. Neep 20, ,
- A. Negri 73a,73b, ,
- M. Negrini 23b, ,
- C. Nellist 114, ,
- C. Nelson 104, ,
- K. Nelson 106, ,
- S. Nemecek 131, ,
- M. Nessi 36,j, ,
- M.S. Neubauer 162, ,
- F. Neuhaus 100, ,
- J. Neundorf 48, ,
- R. Newhouse 164, ,
- P.R. Newman 20, ,
- C.W. Ng 129, ,
- Y.W.Y. Ng 48, ,
- B. Ngair 35e, ,
- H.D.N. Nguyen 108, ,
- R.B. Nickerson 126, ,
- R. Nicolaidou 135, ,
- J. Nielsen 136, ,
- M. Niemeyer 55, ,
- J. Niermann 55,36, ,
- N. Nikiforou 36, ,
- V. Nikolaenko 37,a, ,
- I. Nikolic-Audit 127, ,
- K. Nikolopoulos 20, ,
- P. Nilsson 29, ,
- I. Ninca 48, ,
- H.R. Nindhito 56, ,
- G. Ninio 151, ,
- A. Nisati 75a, ,
- N. Nishu 2, ,
- R. Nisius 110, ,
- J-E. Nitschke 50, ,
- E.K. Nkadimeng 33g, ,
- T. Nobe 153, ,
- D.L. Noel 32, ,
- T. Nommensen 147, ,
- M.B. Norfolk 139, ,
- R.R.B. Norisam 96, ,
- B.J. Norman 34, ,
- J. Novak 93, ,
- T. Novak 48, ,
- L. Novotny 132, ,
- R. Novotny 112, ,
- L. Nozka 122, ,
- K. Ntekas 160, ,
- N.M.J. Nunes De Moura Junior 83b, ,
- E. Nurse 96, ,
- J. Ocariz 127, ,
- A. Ochi 85, ,
- I. Ochoa 130a, ,
- S. Oerdek 48,y, ,
- J.T. Offermann 39, ,
- A. Ogrodnik 133, ,
- A. Oh 101, ,
- C.C. Ohm 144, ,
- H. Oide 84, ,
- R. Oishi 153, ,
- M.L. Ojeda 48, ,
- M.W. O'Keefe 92, ,
- Y. Okumura 153, ,
- L.F. Oleiro Seabra 130a, ,
- S.A. Olivares Pino 137d, ,
- D. Oliveira Damazio 29, ,
- D. Oliveira Goncalves 83a, ,
- J.L. Oliver 160, ,
- Ö.O. Öncel 54, ,
- A.P. O'Neill 19, ,
- A. Onofre 130a,130e, ,
- P.U.E. Onyisi 11, ,
- M.J. Oreglia 39, ,
- G.E. Orellana 90, ,
- D. Orestano 77a,77b, ,
- N. Orlando 13, ,
- R.S. Orr 155, ,
- V. O'Shea 59, ,
- L.M. Osojnak 128, ,
- R. Ospanov 62a, ,
- G. Otero y Garzon 30, ,
- H. Otono 89, ,
- P.S. Ott 63a, ,
- G.J. Ottino 17a, ,
- M. Ouchrif 35d, ,
- J. Ouellette 29, ,
- F. Ould-Saada 125, ,
- M. Owen 59, ,
- R.E. Owen 134, ,
- K.Y. Oyulmaz 21a, ,
- V.E. Ozcan 21a, ,
- F. Ozturk 87, ,
- N. Ozturk 8, ,
- S. Ozturk 82, ,
- H.A. Pacey 126, ,
- A. Pacheco Pages 13, ,
- C. Padilla Aranda 13, ,
- G. Padovano 75a,75b, ,
- S. Pagan Griso 17a, ,
- G. Palacino 68, ,
- A. Palazzo 70a,70b, ,
- S. Palestini 36, ,
- J. Pan 172, ,
- T. Pan 64a, ,
- D.K. Panchal 11, ,
- C.E. Pandini 114, ,
- J.G. Panduro Vazquez 95, ,
- H.D. Pandya 1, ,
- H. Pang 14b, ,
- P. Pani 48, ,
- G. Panizzo 69a,69c, ,
- L. Paolozzi 56, ,
- C. Papadatos 108, ,
- S. Parajuli 44, ,
- A. Paramonov 6, ,
- C. Paraskevopoulos 10, ,
- D. Paredes Hernandez 64b, ,
- K.R. Park 41, ,
- T.H. Park 155, ,
- M.A. Parker 32, ,
- F. Parodi 57b,57a, ,
- E.W. Parrish 115, ,
- V.A. Parrish 52, ,
- J.A. Parsons 41, ,
- U. Parzefall 54, ,
- B. Pascual Dias 108, ,
- L. Pascual Dominguez 151, ,
- E. Pasqualucci 75a, ,
- S. Passaggio 57b, ,
- F. Pastore 95, ,
- P. Pasuwan 47a,47b, ,
- P. Patel 87, ,
- U.M. Patel 51, ,
- J.R. Pater 101, ,
- T. Pauly 36, ,
- J. Pearkes 143, ,
- M. Pedersen 125, ,
- R. Pedro 130a, ,
- S.V. Peleganchuk 37, ,
- O. Penc 36, ,
- E.A. Pender 52, ,
- K.E. Penski 109, ,
- M. Penzin 37, ,
- B.S. Peralva 83d, ,
- A.P. Pereira Peixoto 60, ,
- L. Pereira Sanchez 47a,47b, ,
- D.V. Perepelitsa 29,az, ,
- E. Perez Codina 156a, ,
- M. Perganti 10, ,
- L. Perini 71a,71b, ,
- H. Pernegger 36, ,
- O. Perrin 40, ,
- K. Peters 48, ,
- R.F.Y. Peters 101, ,
- B.A. Petersen 36, ,
- T.C. Petersen 42, ,
- E. Petit 102, ,
- V. Petousis 132, ,
- C. Petridou 152,f, ,
- A. Petrukhin 141, ,
- M. Pettee 17a, ,
- N.E. Pettersson 36, ,
- A. Petukhov 37, ,
- K. Petukhova 133, ,
- R. Pezoa 137f, ,
- L. Pezzotti 36, ,
- G. Pezzullo 172, ,
- T.M. Pham 170, ,
- T. Pham 105, ,
- P.W. Phillips 134, ,
- G. Piacquadio 145, ,
- E. Pianori 17a, ,
- F. Piazza 123, ,
- R. Piegaia 30, ,
- D. Pietreanu 27b, ,
- A.D. Pilkington 101, ,
- M. Pinamonti 69a,69c, ,
- J.L. Pinfold 2, ,
- B.C. Pinheiro Pereira 130a, ,
- A.E. Pinto Pinoargote 100,135, ,
- L. Pintucci 69a,69c, ,
- K.M. Piper 146, ,
- A. Pirttikoski 56, ,
- D.A. Pizzi 34, ,
- L. Pizzimento 64b, ,
- A. Pizzini 114, ,
- M.-A. Pleier 29, ,
- V. Plesanovs 54, ,
- V. Pleskot 133, ,
- E. Plotnikova 38, ,
- G. Poddar 4, ,
- R. Poettgen 98, ,
- L. Poggioli 127, ,
- I. Pokharel 55, ,
- S. Polacek 133, ,
- G. Polesello 73a, ,
- A. Poley 142,156a, ,
- R. Polifka 132, ,
- A. Polini 23b, ,
- C.S. Pollard 167, ,
- Z.B. Pollock 119, ,
- V. Polychronakos 29, ,
- E. Pompa Pacchi 75a,75b, ,
- D. Ponomarenko 113, ,
- L. Pontecorvo 36, ,
- S. Popa 27a, ,
- G.A. Popeneciu 27d, ,
- A. Poreba 36, ,
- D.M. Portillo Quintero 156a, ,
- S. Pospisil 132, ,
- M.A. Postill 139, ,
- P. Postolache 27c, ,
- K. Potamianos 167, ,
- P.A. Potepa 86a, ,
- I.N. Potrap 38, ,
- C.J. Potter 32, ,
- H. Potti 1, ,
- T. Poulsen 48, ,
- J. Poveda 163, ,
- M.E. Pozo Astigarraga 36, ,
- A. Prades Ibanez 163, ,
- J. Pretel 54, ,
- D. Price 101, ,
- M. Primavera 70a, ,
- M.A. Principe Martin 99, ,
- R. Privara 122, ,
- T. Procter 59, ,
- M.L. Proffitt 138, ,
- N. Proklova 128, ,
- K. Prokofiev 64c, ,
- G. Proto 110, ,
- S. Protopopescu 29, ,
- J. Proudfoot 6, ,
- M. Przybycien 86a, ,
- W.W. Przygoda 86b, ,
- J.E. Puddefoot 139, ,
- D. Pudzha 37, ,
- D. Pyatiizbyantseva 37, ,
- J. Qian 106, ,
- R. Qian 107, ,
- D. Qichen 101, ,
- Y. Qin 101, ,
- T. Qiu 52, ,
- A. Quadt 55, ,
- M. Queitsch-Maitland 101, ,
- G. Quetant 56, ,
- R.P. Quinn 164, ,
- G. Rabanal Bolanos 61, ,
- D. Rafanoharana 54, ,
- F. Ragusa 71a,71b, ,
- J.L. Rainbolt 39, ,
- J.A. Raine 56, ,
- S. Rajagopalan 29, ,
- E. Ramakoti 37, ,
- I.A. Ramirez-Berend 34, ,
- K. Ran 48,14e, ,
- N.P. Rapheeha 33g, ,
- H. Rasheed 27b, ,
- V. Raskina 127, ,
- D.F. Rassloff 63a, ,
- S. Rave 100, ,
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- E.J. Weik 117, ,
- J. Weingarten 49, ,
- M. Weirich 100, ,
- C. Weiser 54, ,
- C.J. Wells 48, ,
- T. Wenaus 29, ,
- B. Wendland 49, ,
- T. Wengler 36, ,
- N.S. Wenke 110, ,
- N. Wermes 24, ,
- M. Wessels 63a, ,
- A.M. Wharton 91, ,
- A.S. White 61, ,
- A. White 8, ,
- M.J. White 1, ,
- D. Whiteson 160, ,
- L. Wickremasinghe 124, ,
- W. Wiedenmann 170, ,
- C. Wiel 50, ,
- M. Wielers 134, ,
- C. Wiglesworth 42, ,
- D.J. Wilbern 120, ,
- H.G. Wilkens 36, ,
- D.M. Williams 41, ,
- H.H. Williams 128, ,
- S. Williams 32, ,
- S. Willocq 103, ,
- B.J. Wilson 101, ,
- P.J. Windischhofer 39, ,
- F.I. Winkel 30, ,
- F. Winklmeier 123, ,
- B.T. Winter 54, ,
- J.K. Winter 101, ,
- M. Wittgen 143, ,
- M. Wobisch 97, ,
- Z. Wolffs 114, ,
- J. Wollrath 160, ,
- M.W. Wolter 87, ,
- H. Wolters 130a,130c, ,
- A.F. Wongel 48, ,
- E.L. Woodward 41, ,
- S.D. Worm 48, ,
- B.K. Wosiek 87, ,
- K.W. Woźniak 87, ,
- S. Wozniewski 55, ,
- K. Wraight 59, ,
- C. Wu 20, ,
- J. Wu 14a,14e, ,
- M. Wu 64a, ,
- M. Wu 113, ,
- S.L. Wu 170, ,
- X. Wu 56, ,
- Y. Wu 62a, ,
- Z. Wu 135, ,
- J. Wuerzinger 110,au, ,
- T.R. Wyatt 101, ,
- B.M. Wynne 52, ,
- S. Xella 42, ,
- L. Xia 14c, ,
- M. Xia 14b, ,
- J. Xiang 64c, ,
- M. Xie 62a, ,
- X. Xie 62a, ,
- S. Xin 14a,14e, ,
- A. Xiong 123, ,
- J. Xiong 17a, ,
- D. Xu 14a, ,
- H. Xu 62a, ,
- L. Xu 62a, ,
- R. Xu 128, ,
- T. Xu 106, ,
- Y. Xu 14b, ,
- Z. Xu 52, ,
- Z. Xu 14a, ,
- B. Yabsley 147, ,
- S. Yacoob 33a, ,
- Y. Yamaguchi 154, ,
- E. Yamashita 153, ,
- H. Yamauchi 157, ,
- T. Yamazaki 17a, ,
- Y. Yamazaki 85, ,
- J. Yan 62c, ,
- S. Yan 126, ,
- Z. Yan 25, ,
- H.J. Yang 62c,62d, ,
- H.T. Yang 62a, ,
- S. Yang 62a, ,
- T. Yang 64c, ,
- X. Yang 36, ,
- X. Yang 14a, ,
- Y. Yang 44, ,
- Y. Yang 62a, ,
- Z. Yang 62a, ,
- W-M. Yao 17a, ,
- Y.C. Yap 48, ,
- H. Ye 14c, ,
- H. Ye 55, ,
- J. Ye 14a, ,
- S. Ye 29, ,
- X. Ye 62a, ,
- Y. Yeh 96, ,
- I. Yeletskikh 38, ,
- B.K. Yeo 17b, ,
- M.R. Yexley 96, ,
- P. Yin 41, ,
- K. Yorita 168, ,
- S. Younas 27b, ,
- C.J.S. Young 36, ,
- C. Young 143, ,
- C. Yu 14a,14e,ay, ,
- Y. Yu 62a, ,
- M. Yuan 106, ,
- R. Yuan 62b, ,
- L. Yue 96, ,
- M. Zaazoua 62a, ,
- B. Zabinski 87, ,
- E. Zaid 52, ,
- T. Zakareishvili 149b, ,
- N. Zakharchuk 34, ,
- S. Zambito 56, ,
- J.A. Zamora Saa 137d,137b, ,
- J. Zang 153, ,
- D. Zanzi 54, ,
- O. Zaplatilek 132, ,
- C. Zeitnitz 171, ,
- H. Zeng 14a, ,
- J.C. Zeng 162, ,
- D.T. Zenger Jr 26, ,
- O. Zenin 37, ,
- T. Ženiš 28a, ,
- S. Zenz 94, ,
- S. Zerradi 35a, ,
- D. Zerwas 66, ,
- M. Zhai 14a,14e, ,
- B. Zhang 14c, ,
- D.F. Zhang 139, ,
- J. Zhang 62b, ,
- J. Zhang 6, ,
- K. Zhang 14a,14e, ,
- L. Zhang 14c, ,
- P. Zhang 14a,14e, ,
- R. Zhang 170, ,
- S. Zhang 106, ,
- S. Zhang 44, ,
- T. Zhang 153, ,
- X. Zhang 62c, ,
- X. Zhang 62b, ,
- Y. Zhang 62c,5, ,
- Y. Zhang 96, ,
- Y. Zhang 14c, ,
- Z. Zhang 17a, ,
- Z. Zhang 66, ,
- H. Zhao 138, ,
- P. Zhao 51, ,
- T. Zhao 62b, ,
- Y. Zhao 136, ,
- Z. Zhao 62a, ,
- A. Zhemchugov 38, ,
- J. Zheng 14c, ,
- K. Zheng 162, ,
- X. Zheng 62a, ,
- Z. Zheng 143, ,
- D. Zhong 162, ,
- B. Zhou 106, ,
- H. Zhou 7, ,
- N. Zhou 62c, ,
- Y. Zhou 7, ,
- C.G. Zhu 62b, ,
- J. Zhu 106, ,
- Y. Zhu 62c, ,
- Y. Zhu 62a, ,
- X. Zhuang 14a, ,
- K. Zhukov 37, ,
- V. Zhulanov 37, ,
- N.I. Zimine 38, ,
- J. Zinsser 63b, ,
- M. Ziolkowski 141, ,
- L. Živković 15, ,
- A. Zoccoli 23b,23a, ,
- K. Zoch 61, ,
- T.G. Zorbas 139, ,
- O. Zormpa 46, ,
- W. Zou 41, ,
- L. Zwalinski 36, ,
- The ATLAS Collaboration ,
- 1. Department of Physics, University of Adelaide, Adelaide, Australia
- 2. Department of Physics, University of Alberta, Edmonton AB, Canada
- 3a. Department of Physics, Ankara University, Ankara, Türkiye
- 3b. Division of Physics, TOBB University of Economics and Technology, Ankara, Türkiye
- 4. LAPP, Université Savoie Mont Blanc, CNRS/IN2P3, Annecy, France
- 5. APC, Université Paris Cité, CNRS/IN2P3, Paris, France
- 6. High Energy Physics Division, Argonne National Laboratory, Argonne IL, United States of America
- 7. Department of Physics, University of Arizona, Tucson AZ, United States of America
- 8. Department of Physics, University of Texas at Arlington, Arlington TX, United States of America
- 9. Physics Department, National and Kapodistrian University of Athens, Athens, Greece
- 10. Physics Department, National Technical University of Athens, Zografou, Greece
- 11. Department of Physics, University of Texas at Austin, Austin TX, United States of America
- 12. Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan
- 13. Institut de Física d'Altes Energies (IFAE), Barcelona Institute of Science and Technology, Barcelona, Spain
- 14a. Institute of High Energy Physics, Chinese Academy of Sciences, Beijing
- 14b. Physics Department, Tsinghua University, Beijing
- 14c. Department of Physics, Nanjing University, Nanjing
- 14d. School of Science, Shenzhen Campus of Sun Yat-sen University, Shenzhen
- 14e. University of Chinese Academy of Science (UCAS), Beijing
- 15. Institute of Physics, University of Belgrade, Belgrade, Serbia
- 16. Department for Physics and Technology, University of Bergen, Bergen, Norway
- 17a. Physics Division, Lawrence Berkeley National Laboratory, Berkeley CA, United States of America
- 17b. University of California, Berkeley CA, United States of America
- 18. Institut für Physik, Humboldt Universität zu Berlin, Berlin, Germany
- 19. Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics, University of Bern, Bern, Switzerland
- 20. School of Physics and Astronomy, University of Birmingham, Birmingham, United Kingdom
- 21a. Department of Physics, Bogazici University, Istanbul, Türkiye
- 21b. Department of Physics Engineering, Gaziantep University, Gaziantep, Türkiye
- 21c. Department of Physics, Istanbul University, Istanbul, Türkiye
- 22a. Facultad de Ciencias y Centro de Investigaciónes, Universidad Antonio Nariño, Bogotá, Colombia
- 22b. Departamento de Física, Universidad Nacional de Colombia, Bogotá, Colombia
- 23a. Dipartimento di Fisica e Astronomia A. Righi, Università di Bologna, Bologna, Italy
- 23b. INFN Sezione di Bologna, Italy
- 24. Physikalisches Institut, Universität Bonn, Bonn, Germany
- 25. Department of Physics, Boston University, Boston MA, United States of America
- 26. Department of Physics, Brandeis University, Waltham MA, United States of America
- 27a. Transilvania University of Brasov, Brasov, Romania
- 27b. Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest, Romania
- 27c. Department of Physics, Alexandru Ioan Cuza University of Iasi, Iasi, Romania
- 27d. National Institute for Research and Development of Isotopic and Molecular Technologies, Physics Department, Cluj-Napoca, Romania
- 27e. University Politehnica Bucharest, Bucharest, Romania
- 27f. West University in Timisoara, Timisoara, Romania
- 27g. Faculty of Physics, University of Bucharest, Bucharest, Romania
- 28a. Faculty of Mathematics, Physics and Informatics, Comenius University, Bratislava, Slovak Republic
- 28b. Department of Subnuclear Physics, Institute of Experimental Physics of the Slovak Academy of Sciences, Kosice, Slovak Republic
- 29. Physics Department, Brookhaven National Laboratory, Upton NY, United States of America
- 30. Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Física, y CONICET, Instituto de Física de Buenos Aires (IFIBA), Buenos Aires, Argentina
- 31. California State University, CA, United States of America
- 32. Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom
- 33a. Department of Physics, University of Cape Town, Cape Town, South Africa
- 33b. iThemba Labs, Western Cape, South Africa
- 33c. Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg, South Africa
- 33d. National Institute of Physics, University of the Philippines Diliman (Philippines), South Africa
- 33e. University of South Africa, Department of Physics, Pretoria, South Africa
- 33f. University of Zululand, KwaDlangezwa, South Africa
- 33g. School of Physics, University of the Witwatersrand, Johannesburg, South Africa
- 34. Department of Physics, Carleton University, Ottawa ON, Canada
- 35a. Faculté des Sciences Ain Chock, Réseau Universitaire de Physique des Hautes Energies - Université Hassan II, Casablanca, Morocco
- 35b. Faculté des Sciences, Université Ibn-Tofail, Kénitra, Morocco
- 35c. Faculté des Sciences Semlalia, Université Cadi Ayyad, LPHEA-Marrakech, Morocco
- 35d. LPMR, Faculté des Sciences, Université Mohamed Premier, Oujda, Morocco
- 35e. Faculté des sciences, Université Mohammed V, Rabat, Morocco
- 35f. Institute of Applied Physics, Mohammed VI Polytechnic University, Ben Guerir, Morocco
- 36. CERN, Geneva, Switzerland
- 37. Affiliated with an institute covered by a cooperation agreement with CERN
- 38. Affiliated with an international laboratory covered by a cooperation agreement with CERN
- 39. Enrico Fermi Institute, University of Chicago, Chicago IL, United States of America
- 40. LPC, Université Clermont Auvergne, CNRS/IN2P3, Clermont-Ferrand, France
- 41. Nevis Laboratory, Columbia University, Irvington NY, United States of America
- 42. Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark
- 43a. Dipartimento di Fisica, Università della Calabria, Rende, Italy
- 43b. INFN Gruppo Collegato di Cosenza, Laboratori Nazionali di Frascati, Italy
- 44. Physics Department, Southern Methodist University, Dallas TX, United States of America
- 45. Physics Department, University of Texas at Dallas, Richardson TX, United States of America
- 46. National Centre for Scientific Research "Demokritos", Agia Paraskevi, Greece
- 47a. Department of Physics, Stockholm University, Sweden
- 47b. Oskar Klein Centre, Stockholm, Sweden
- 48. Deutsches Elektronen-Synchrotron DESY, Hamburg and Zeuthen, Germany
- 49. Fakultät Physik, Technische Universität Dortmund, Dortmund, Germany
- 50. Institut für Kern- und Teilchenphysik, Technische Universität Dresden, Dresden, Germany
- 51. Department of Physics, Duke University, Durham NC, United States of America
- 52. SUPA - School of Physics and Astronomy, University of Edinburgh, Edinburgh, United Kingdom
- 53. INFN e Laboratori Nazionali di Frascati, Frascati, Italy
- 54. Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany
- 55. II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen, Germany
- 56. Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève, Switzerland
- 57a. Dipartimento di Fisica, Università di Genova, Genova, Italy
- 57b. INFN Sezione di Genova, Italy
- 58. II. Physikalisches Institut, Justus-Liebig-Universität Giessen, Giessen, Germany
- 59. SUPA - School of Physics and Astronomy, University of Glasgow, Glasgow, United Kingdom
- 60. LPSC, Université Grenoble Alpes, CNRS/IN2P3, Grenoble INP, Grenoble, France
- 61. Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge MA, United States of America
- 62a. Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei
- 62b. Institute of Frontier and Interdisciplinary Science and Key Laboratory of Particle Physics and Particle Irradiation (MOE), Shandong University, Qingdao
- 62c. School of Physics and Astronomy, Shanghai Jiao Tong University, Key Laboratory for Particle Astrophysics and Cosmology (MOE), SKLPPC, Shanghai
- 62d. Tsung-Dao Lee Institute, Shanghai
- 63a. Kirchhoff-Institut für Physik, Ruprecht-Karls-Universität Heidelberg, Heidelberg, Germany
- 63b. Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg, Germany
- 64a. Department of Physics, Chinese University of Hong Kong, Shatin, N.T., Hong Kong
- 64b. Department of Physics, University of Hong Kong, Hong Kong
- 64c. Department of Physics and Institute for Advanced Study, Hong Kong, China University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
- 65. Department of Physics, National Tsing Hua University, Hsinchu
- 66. IJCLab, Université Paris-Saclay, CNRS/IN2P3, 91405, Orsay, France
- 67. Centro Nacional de Microelectrónica (IMB-CNM-CSIC), Barcelona, Spain
- 68. Department of Physics, Indiana University, Bloomington IN, United States of America
- 69a. INFN Gruppo Collegato di Udine, Sezione di Trieste, Udine, Italy
- 69b. ICTP, Trieste, Italy
- 69c. Dipartimento Politecnico di Ingegneria e Architettura, Università di Udine, Udine, Italy
- 70a. INFN Sezione di Lecce, Italy
- 70b. Dipartimento di Matematica e Fisica, Università del Salento, Lecce, Italy
- 71a. INFN Sezione di Milano, Italy
- 71b. Dipartimento di Fisica, Università di Milano, Milano, Italy
- 72a. INFN Sezione di Napoli, Italy
- 72b. Dipartimento di Fisica, Università di Napoli, Napoli, Italy
- 73a. INFN Sezione di Pavia, Italy
- 73b. Dipartimento di Fisica, Università di Pavia, Pavia, Italy
- 74a. INFN Sezione di Pisa, Italy
- 74b. Dipartimento di Fisica E. Fermi, Università di Pisa, Pisa, Italy
- 75a. INFN Sezione di Roma, Italy
- 75b. Dipartimento di Fisica, Sapienza Università di Roma, Roma, Italy
- 76a. INFN Sezione di Roma Tor Vergata
- 76b. Dipartimento di Fisica, Università di Roma Tor Vergata, Roma, Italy
- 77a. INFN Sezione di Roma Tre, Italy
- 77b. Dipartimento di Matematica e Fisica, Università Roma Tre, Roma, Italy
- 78a. INFN-TIFPA, Italy
- 78b. Università degli Studi di Trento, Trento, Italy
- 79. Universität Innsbruck, Department of Astro and Particle Physics, Innsbruck, Austria
- 80. University of Iowa, Iowa City IA; United States of America
- 81. Department of Physics and Astronomy, Iowa State University, Ames IA, United States of America
- 82. Istinye University, Sariyer, Istanbul, Türkiye
- 83a. Departamento de Engenharia Elétrica, Universidade Federal de Juiz de Fora (UFJF), Juiz de Fora, Brazil
- 83b. Universidade Federal do Rio De Janeiro COPPE/EE/IF, Rio de Janeiro, Brazil
- 83c. Instituto de Física, Universidade de São Paulo, São Paulo, Brazil
- 83d. Rio de Janeiro State University, Rio de Janeiro, Brazil
- 84. KEK, High Energy Accelerator Research Organization, Tsukuba, Japan
- 85. Graduate School of Science, Kobe University, Kobe, Japan
- 86a. AGH University of Krakow, Faculty of Physics and Applied Computer Science, Krakow, Poland
- 86b. Marian Smoluchowski Institute of Physics, Jagiellonian University, Krakow, Poland
- 87. Institute of Nuclear Physics Polish Academy of Sciences, Krakow, Poland
- 88. Faculty of Science, Kyoto University, Kyoto, Japan
- 89. Research Center for Advanced Particle Physics and Department of Physics, Kyushu University, Fukuoka, Japan
- 90. Instituto de Física La Plata, Universidad Nacional de La Plata and CONICET, La Plata, Argentina
- 91. Physics Department, Lancaster University, Lancaster, United Kingdom
- 92. Oliver Lodge Laboratory, University of Liverpool, Liverpool, United Kingdom
- 93. Department of Experimental Particle Physics, Jožef Stefan Institute and Department of Physics, University of Ljubljana, Ljubljana, Slovenia
- 94. School of Physics and Astronomy, Queen Mary University of London, London, United Kingdom
- 95. Department of Physics, Royal Holloway University of London, Egham, United Kingdom
- 96. Department of Physics and Astronomy, University College London, London, United Kingdom
- 97. Louisiana Tech University, Ruston LA, United States of America
- 98. Fysiska institutionen, Lunds universitet, Lund, Sweden
- 99. Departamento de Física Teorica C-15 and CIAFF, Universidad Autónoma de Madrid, Madrid, Spain
- 100. Institut für Physik, Universität Mainz, Mainz, Germany
- 101. School of Physics and Astronomy, University of Manchester, Manchester, United Kingdom
- 102. CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille, France
- 103. Department of Physics, University of Massachusetts, Amherst MA, United States of America
- 104. Department of Physics, McGill University, Montreal QC, Canada
- 105. School of Physics, University of Melbourne, Victoria, Australia
- 106. Department of Physics, University of Michigan, Ann Arbor MI, United States of America
- 107. Department of Physics and Astronomy, Michigan State University, East Lansing MI, United States of America
- 108. Group of Particle Physics, University of Montreal, Montreal QC, Canada
- 109. Fakultät für Physik, Ludwig-Maximilians-Universität München, München, Germany
- 110. Max-Planck-Institut für Physik (Werner-Heisenberg-Institut), München, Germany
- 111. Graduate School of Science and Kobayashi-Maskawa Institute, Nagoya University, Nagoya, Japan
- 112. Department of Physics and Astronomy, University of New Mexico, Albuquerque NM, United States of America
- 113. Institute for Mathematics, Astrophysics and Particle Physics, Radboud University/Nikhef, Nijmegen, Netherlands
- 114. Nikhef National Institute for Subatomic Physics and University of Amsterdam, Amsterdam, Netherlands
- 115. Department of Physics, Northern Illinois University, DeKalb IL, United States of America
- 116a. New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
- 116b. University of Sharjah, Sharjah, United Arab Emirates
- 117. Department of Physics, New York University, New York NY, United States of America
- 118. Ochanomizu University, Otsuka, Bunkyo-ku, Tokyo, Japan
- 119. Ohio State University, Columbus OH, United States of America
- 120. Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman OK, United States of America
- 121. Department of Physics, Oklahoma State University, Stillwater OK, United States of America
- 122. Palacký University, Joint Laboratory of Optics, Olomouc, Czech Republic
- 123. Institute for Fundamental Science, University of Oregon, Eugene, OR, United States of America
- 124. Graduate School of Science, Osaka University, Osaka, Japan
- 125. Department of Physics, University of Oslo, Oslo, Norway
- 126. Department of Physics, Oxford University, Oxford, United Kingdom
- 127. LPNHE, Sorbonne Université, Université Paris Cité, CNRS/IN2P3, Paris, France
- 128. Department of Physics, University of Pennsylvania, Philadelphia PA, United States of America
- 129. Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh PA, United States of America
- 130a. Laboratório de Instrumentação e Física Experimental de Partículas - LIP, Lisboa, Portugal
- 130b. Departamento de Física, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal
- 130c. Departamento de Física, Universidade de Coimbra, Coimbra, Portugal
- 130d. Centro de Física Nuclear da Universidade de Lisboa, Lisboa, Portugal
- 130e. Departamento de Física, Universidade do Minho, Braga, Portugal
- 130f. Departamento de Física Teórica y del Cosmos, Universidad de Granada, Granada (Spain), Portugal
- 130g. Departamento de Física, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal
- 131. Institute of Physics of the Czech Academy of Sciences, Prague, Czech Republic
- 132. Czech Technical University in Prague, Prague, Czech Republic
- 133. Charles University, Faculty of Mathematics and Physics, Prague, Czech Republic
- 134. Particle Physics Department, Rutherford Appleton Laboratory, Didcot, United Kingdom
- 135. IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
- 136. Santa Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz CA, United States of America
- 137a. Departamento de Física, Pontificia Universidad Católica de Chile, Santiago, Chile
- 137b. Millennium Institute for Subatomic physics at high energy frontier (SAPHIR), Santiago, Chile
- 137c. Instituto de Investigación Multidisciplinario en Ciencia y Tecnología, y Departamento de Física, Universidad de La Serena, Chile
- 137d. Universidad Andres Bello, Department of Physics, Santiago, Chile
- 137e. Instituto de Alta Investigación, Universidad de Tarapacá, Arica, Chile
- 137f. Departamento de Física, Universidad Técnica Federico Santa María, Valparaíso, Chile
- 138. Department of Physics, University of Washington, Seattle WA, United States of America
- 139. Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom
- 140. Department of Physics, Shinshu University, Nagano, Japan
- 141. Department Physik, Universität Siegen, Siegen, Germany
- 142. Department of Physics, Simon Fraser University, Burnaby BC, Canada
- 143. SLAC National Accelerator Laboratory, Stanford CA, United States of America
- 144. Department of Physics, Royal Institute of Technology, Stockholm, Sweden
- 145. Departments of Physics and Astronomy, Stony Brook University, Stony Brook NY, United States of America
- 146. Department of Physics and Astronomy, University of Sussex, Brighton, United Kingdom
- 147. School of Physics, University of Sydney, Sydney, Australia
- 148. Institute of Physics, Academia Sinica, Taipei
- 149a. E. Andronikashvili Institute of Physics, Iv. Javakhishvili Tbilisi State University, Tbilisi, Georgia
- 149b. High Energy Physics Institute, Tbilisi State University, Tbilisi, Georgia
- 149c. University of Georgia, Tbilisi, Georgia
- 150. Department of Physics, Technion, Israel Institute of Technology, Haifa, Israel
- 151. Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv University, Tel Aviv, Israel
- 152. Department of Physics, Aristotle University of Thessaloniki, Thessaloniki, Greece
- 153. International Center for Elementary Particle Physics and Department of Physics, University of Tokyo, Tokyo, Japan
- 154. Department of Physics, Tokyo Institute of Technology, Tokyo, Japan
- 155. Department of Physics, University of Toronto, Toronto ON, Canada
- 156a. TRIUMF, Vancouver BC, Canada
- 156b. Department of Physics and Astronomy, York University, Toronto ON, Canada
- 157. Division of Physics and Tomonaga Center for the History of the Universe, Faculty of Pure and Applied Sciences, University of Tsukuba, Tsukuba, Japan
- 158. Department of Physics and Astronomy, Tufts University, Medford MA, United States of America
- 159. United Arab Emirates University, Al Ain, United Arab Emirates
- 160. Department of Physics and Astronomy, University of California Irvine, Irvine CA, United States of America
- 161. Department of Physics and Astronomy, University of Uppsala, Uppsala, Sweden
- 162. Department of Physics, University of Illinois, Urbana IL, United States of America
- 163. Instituto de Física Corpuscular (IFIC), Centro Mixto Universidad de Valencia - CSIC, Valencia, Spain
- 164. Department of Physics, University of British Columbia, Vancouver BC, Canada
- 165. Department of Physics and Astronomy, University of Victoria, Victoria BC, Canada
- 166. Fakultät für Physik und Astronomie, Julius-Maximilians-Universität Würzburg, Würzburg, Germany
- 167. Department of Physics, University of Warwick, Coventry, United Kingdom
- 168. Waseda University, Tokyo, Japan
- 169. Department of Particle Physics and Astrophysics, Weizmann Institute of Science, Rehovot, Israel
- 170. Department of Physics, University of Wisconsin, Madison WI, United States of America
- 171. Fakultät für Mathematik und Naturwissenschaften, Fachgruppe Physik, Bergische Universität Wuppertal, Wuppertal, Germany
- 172. Department of Physics, Yale University, New Haven CT, United States of America
- a. Also Affiliated with an institute covered by a cooperation agreement with CERN
- b. Also at An-Najah National University, Nablus, Palestine
- c. Also at APC, Université Paris Cité, CNRS/IN2P3, Paris, France
- d. Also at Borough of Manhattan Community College, City University of New York, New York NY, United States of America
- e. Also at Center for High Energy Physics, Peking University, Beijing
- f. Also at Center for Interdisciplinary Research and Innovation (CIRI-AUTH), Thessaloniki, Greece
- g. Also at Centro Studi e Ricerche Enrico Fermi, Italy
- h. Also at CERN Tier-0, Switzerland
- i. Also at CERN, Geneva, Switzerland
- j. Also at Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève, Switzerland
- k. Also at Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona, Spain
- l. Also at Department of Financial and Management Engineering, University of the Aegean, Chios, Greece
- m. Also at Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom
- n. Also at Department of Physics and Astronomy, University of Victoria, Victoria BC, Canada
- o. Also at Department of Physics, Ben Gurion University of the Negev, Beer Sheva, Israel
- p. Also at Department of Physics, California State University, Sacramento, United States of America
- q. Also at Department of Physics, King's College London, London, United Kingdom
- r. Also at Department of Physics, Oxford University, Oxford, United Kingdom
- s. Also at Department of Physics, Royal Holloway University of London, Egham, United Kingdom
- t. Also at Department of Physics, Stanford University, Stanford CA, United States of America
- u. Also at Department of Physics, University of Fribourg, Fribourg, Switzerland
- v. Also at Department of Physics, University of Massachusetts, Amherst MA, United States of America
- w. Also at Department of Physics, University of Thessaly, Greece
- x. Also at Department of Physics, Westmont College, Santa Barbara, United States of America
- y. Also at Deutsches Elektronen-Synchrotron DESY, Hamburg and Zeuthen, Germany
- z. Also at Fakultät Physik, Technische Universität Dortmund, Dortmund, Germany
- aa. Also at Fakultät für Mathematik und Naturwissenschaften, Fachgruppe Physik, Bergische Universität Wuppertal, Wuppertal, Germany
- ab. Also at Group of Particle Physics, University of Montreal, Montreal QC, Canada
- ac. Also at Hellenic Open University, Patras, Greece
- ad. Also at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona, Spain
- ae. Also at Institut für Experimentalphysik, Universität Hamburg, Hamburg, Germany
- af. Also at Institut für Physik, Universität Mainz, Mainz, Germany
- ag. Also at Institute for Nuclear Research and Nuclear Energy (INRNE) of the Bulgarian Academy of Sciences, Sofia, Bulgaria
- ah. Also at Institute of Applied Physics, Mohammed VI Polytechnic University, Ben Guerir, Morocco
- ai. Also at Institute of Particle Physics (IPP), Canada
- aj. Also at Institute of Physics and Technology, Ulaanbaatar, Mongolia
- ak. Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan
- al. Also at Institute of Theoretical Physics, Ilia State University, Tbilisi, Georgia
- am. Also at IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
- an. Also at L2IT, Université de Toulouse, CNRS/IN2P3, UPS, Toulouse, France
- ao. Also at Lawrence Livermore National Laboratory, Livermore, United States of America
- ap. Also at National Institute of Physics, University of the Philippines Diliman (Philippines), Philippines
- aq. Also at Ochanomizu University, Otsuka, Bunkyo-ku, Tokyo, Japan
- ar. Also at School of Physics and Astronomy, University of Birmingham, Birmingham, United Kingdom
- as. Also at School of Physics and Astronomy, University of Manchester, Manchester, United Kingdom
- at. Also at SUPA - School of Physics and Astronomy, University of Glasgow, Glasgow, United Kingdom
- au. Also at Technical University of Munich, Munich, Germany
- av. Also at The Collaborative Innovation Center of Quantum Matter (CICQM), Beijing
- aw. Also at TRIUMF, Vancouver BC, Canada
- ax. Also at Università di Napoli Parthenope, Napoli, Italy
- ay. Also at University of Chinese Academy of Sciences (UCAS), Beijing
- az. Also at University of Colorado Boulder, Department of Physics, Colorado, United States of America
- ba. Also at Washington College, Chestertown, MD, United States of America
- bb. Also at Yeditepe University, Physics Department, Istanbul, Türkiye
- Received Date: 2023-08-01
- Available Online: 2024-02-15
Abstract: The identification of jets originating from quarks and gluons, often referred to as quark/gluon tagging, plays an important role in various analyses performed at the Large Hadron Collider, as Standard Model measurements and searches for new particles decaying to quarks often rely on suppressing a large gluon-induced background. This paper describes the measurement of the efficiencies of quark/gluon taggers developed within the ATLAS Collaboration, using 
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